id	sid	tid	token	lemma	pos
cana-1859	1	1	communications	communication	NOUN
cana-1859	1	2	on	on	ADP
cana-1859	1	3	applied	apply	VERB
cana-1859	1	4	nonlinear	nonlinear	ADJ
cana-1859	1	5	analysis	analysis	NOUN
cana-1859	1	6	issn	issn	NOUN
cana-1859	1	7	:	:	PUNCT
cana-1859	1	8	1074	1074	NUM
cana-1859	1	9	-	-	PUNCT
cana-1859	1	10	133x	133x	NUM
cana-1859	1	11	vol	vol	NOUN
cana-1859	1	12	32	32	NUM
cana-1859	1	13	no	no	NOUN
cana-1859	1	14	.	.	NOUN
cana-1859	1	15	2	2	NUM
cana-1859	1	16	(	(	PUNCT
cana-1859	1	17	2025	2025	NUM
cana-1859	1	18	)	)	PUNCT
cana-1859	1	19	638	638	NUM
cana-1859	1	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	1	21	vmcnn	vmcnn	NOUN
cana-1859	1	22	:	:	PUNCT
cana-1859	1	23	integrating	integrate	VERB
cana-1859	1	24	vedic	vedic	ADJ
cana-1859	1	25	mathematics	mathematic	NOUN
cana-1859	1	26	for	for	ADP
cana-1859	1	27	enhanced	enhanced	ADJ
cana-1859	1	28	convolutional	convolutional	ADJ
cana-1859	1	29	neural	neural	ADJ
cana-1859	1	30	network	network	NOUN
cana-1859	1	31	performance	performance	NOUN
cana-1859	1	32	in	in	ADP
cana-1859	1	33	image	image	NOUN
cana-1859	1	34	classification	classification	NOUN
cana-1859	1	35	tasks	task	NOUN
cana-1859	1	36	geetanjali	geetanjali	VERB
cana-1859	1	37	kale	kale	NOUN
cana-1859	1	38	(	(	PUNCT
cana-1859	1	39	rao	rao	NOUN
cana-1859	1	40	)	)	PUNCT
cana-1859	1	41	1	1	NUM
cana-1859	1	42	*	*	PUNCT
cana-1859	1	43	dr	dr	PROPN
cana-1859	1	44	.	.	PROPN
cana-1859	1	45	seema	seema	PROPN
cana-1859	1	46	raut2	raut2	PROPN
cana-1859	1	47	*	*	PUNCT
cana-1859	1	48	*	*	NOUN
cana-1859	1	49	1,2	1,2	NUM
cana-1859	1	50	g	g	NOUN
cana-1859	1	51	h	h	PROPN
cana-1859	1	52	raisoni	raisoni	PROPN
cana-1859	1	53	university	university	PROPN
cana-1859	1	54	,	,	PUNCT
cana-1859	1	55	amravati	amravati	PROPN
cana-1859	1	56	,	,	PUNCT
cana-1859	1	57	india	india	PROPN
cana-1859	1	58	article	article	NOUN
cana-1859	1	59	history	history	NOUN
cana-1859	1	60	:	:	PUNCT
cana-1859	1	61	received	receive	VERB
cana-1859	1	62	:	:	PUNCT
cana-1859	1	63	19	19	NUM
cana-1859	1	64	-	-	PUNCT
cana-1859	1	65	07	07	NUM
cana-1859	1	66	-	-	PUNCT
cana-1859	1	67	2024	2024	NUM
cana-1859	1	68	revised	revise	VERB
cana-1859	1	69	:	:	PUNCT
cana-1859	1	70	19	19	NUM
cana-1859	1	71	-	-	PUNCT
cana-1859	1	72	09	09	NUM
cana-1859	1	73	-	-	PUNCT
cana-1859	1	74	2024	2024	NUM
cana-1859	1	75	accepted	accept	VERB
cana-1859	1	76	:	:	PUNCT
cana-1859	1	77	27	27	NUM
cana-1859	1	78	-	-	SYM
cana-1859	1	79	09	09	NUM
cana-1859	1	80	-	-	PUNCT
cana-1859	1	81	2024	2024	NUM
cana-1859	1	82	abstract	abstract	NOUN
cana-1859	1	83	:	:	PUNCT
cana-1859	1	84	in	in	ADP
cana-1859	1	85	the	the	DET
cana-1859	1	86	rapidly	rapidly	ADV
cana-1859	1	87	advancing	advance	VERB
cana-1859	1	88	field	field	NOUN
cana-1859	1	89	of	of	ADP
cana-1859	1	90	deep	deep	ADJ
cana-1859	1	91	learning	learning	NOUN
cana-1859	1	92	,	,	PUNCT
cana-1859	1	93	convolutional	convolutional	ADJ
cana-1859	1	94	neural	neural	ADJ
cana-1859	1	95	networks	network	NOUN
cana-1859	1	96	(	(	PUNCT
cana-1859	1	97	cnns	cnns	PROPN
cana-1859	1	98	)	)	PUNCT
cana-1859	1	99	have	have	AUX
cana-1859	1	100	emerged	emerge	VERB
cana-1859	1	101	as	as	ADP
cana-1859	1	102	a	a	DET
cana-1859	1	103	cornerstone	cornerstone	NOUN
cana-1859	1	104	for	for	ADP
cana-1859	1	105	various	various	ADJ
cana-1859	1	106	image	image	NOUN
cana-1859	1	107	classification	classification	NOUN
cana-1859	1	108	tasks	task	NOUN
cana-1859	1	109	.	.	PUNCT
cana-1859	2	1	however	however	ADV
cana-1859	2	2	,	,	PUNCT
cana-1859	2	3	the	the	DET
cana-1859	2	4	existing	exist	VERB
cana-1859	2	5	cnn	cnn	PROPN
cana-1859	2	6	architectures	architecture	NOUN
cana-1859	2	7	and	and	CCONJ
cana-1859	2	8	optimization	optimization	NOUN
cana-1859	2	9	methods	method	NOUN
cana-1859	2	10	often	often	ADV
cana-1859	2	11	grapple	grapple	VERB
cana-1859	2	12	with	with	ADP
cana-1859	2	13	trade	trade	NOUN
cana-1859	2	14	-	-	PUNCT
cana-1859	2	15	offs	off	NOUN
cana-1859	2	16	between	between	ADP
cana-1859	2	17	computational	computational	ADJ
cana-1859	2	18	efficiency	efficiency	NOUN
cana-1859	2	19	,	,	PUNCT
cana-1859	2	20	accuracy	accuracy	NOUN
cana-1859	2	21	,	,	PUNCT
cana-1859	2	22	and	and	CCONJ
cana-1859	2	23	generalizability	generalizability	NOUN
cana-1859	2	24	.	.	PUNCT
cana-1859	3	1	this	this	DET
cana-1859	3	2	work	work	NOUN
cana-1859	3	3	addresses	address	VERB
cana-1859	3	4	these	these	DET
cana-1859	3	5	limitations	limitation	NOUN
cana-1859	3	6	by	by	ADP
cana-1859	3	7	integrating	integrate	VERB
cana-1859	3	8	principles	principle	NOUN
cana-1859	3	9	of	of	ADP
cana-1859	3	10	vedic	vedic	ADJ
cana-1859	3	11	mathematics	mathematic	NOUN
cana-1859	3	12	,	,	PUNCT
cana-1859	3	13	an	an	DET
cana-1859	3	14	ancient	ancient	ADJ
cana-1859	3	15	indian	indian	ADJ
cana-1859	3	16	mathematical	mathematical	ADJ
cana-1859	3	17	system	system	NOUN
cana-1859	3	18	known	know	VERB
cana-1859	3	19	for	for	ADP
cana-1859	3	20	its	its	PRON
cana-1859	3	21	efficiency	efficiency	NOUN
cana-1859	3	22	and	and	CCONJ
cana-1859	3	23	simplicity	simplicity	NOUN
cana-1859	3	24	,	,	PUNCT
cana-1859	3	25	into	into	ADP
cana-1859	3	26	cnn	cnn	PROPN
cana-1859	3	27	optimization	optimization	NOUN
cana-1859	3	28	.	.	PUNCT
cana-1859	4	1	traditional	traditional	ADJ
cana-1859	4	2	optimization	optimization	NOUN
cana-1859	4	3	techniques	technique	NOUN
cana-1859	4	4	often	often	ADV
cana-1859	4	5	fall	fall	VERB
cana-1859	4	6	short	short	ADJ
cana-1859	4	7	in	in	ADP
cana-1859	4	8	balancing	balance	VERB
cana-1859	4	9	the	the	DET
cana-1859	4	10	computational	computational	ADJ
cana-1859	4	11	load	load	NOUN
cana-1859	4	12	with	with	ADP
cana-1859	4	13	the	the	DET
cana-1859	4	14	accuracy	accuracy	NOUN
cana-1859	4	15	of	of	ADP
cana-1859	4	16	the	the	DET
cana-1859	4	17	model	model	NOUN
cana-1859	4	18	,	,	PUNCT
cana-1859	4	19	particularly	particularly	ADV
cana-1859	4	20	in	in	ADP
cana-1859	4	21	diverse	diverse	ADJ
cana-1859	4	22	and	and	CCONJ
cana-1859	4	23	complex	complex	ADJ
cana-1859	4	24	datasets	dataset	NOUN
cana-1859	4	25	.	.	PUNCT
cana-1859	5	1	to	to	PART
cana-1859	5	2	overcome	overcome	VERB
cana-1859	5	3	these	these	DET
cana-1859	5	4	challenges	challenge	NOUN
cana-1859	5	5	,	,	PUNCT
cana-1859	5	6	we	we	PRON
cana-1859	5	7	propose	propose	VERB
cana-1859	5	8	a	a	DET
cana-1859	5	9	novel	novel	ADJ
cana-1859	5	10	model	model	NOUN
cana-1859	5	11	that	that	PRON
cana-1859	5	12	incorporates	incorporate	VERB
cana-1859	5	13	specific	specific	ADJ
cana-1859	5	14	vedic	vedic	ADJ
cana-1859	5	15	mathematical	mathematical	ADJ
cana-1859	5	16	sutras	sutra	NOUN
cana-1859	5	17	,	,	PUNCT
cana-1859	5	18	namely	namely	ADV
cana-1859	5	19	urdhvatiryakbhyam	urdhvatiryakbhyam	NOUN
cana-1859	5	20	,	,	PUNCT
cana-1859	5	21	anurupyena	anurupyena	PROPN
cana-1859	5	22	,	,	PUNCT
cana-1859	5	23	nikhilam	nikhilam	PROPN
cana-1859	5	24	navatashcaramam	navatashcaramam	NOUN
cana-1859	5	25	dashatah	dashatah	NOUN
cana-1859	5	26	,	,	PUNCT
cana-1859	5	27	shunyam	shunyam	PROPN
cana-1859	5	28	saamyasamuccaye	saamyasamuccaye	NOUN
cana-1859	5	29	,	,	PUNCT
cana-1859	5	30	paravartya	paravartya	PROPN
cana-1859	5	31	yojayet	yojayet	NOUN
cana-1859	5	32	,	,	PUNCT
cana-1859	5	33	sankalana	sankalana	PROPN
cana-1859	5	34	-	-	PUNCT
cana-1859	5	35	vyavakalanabhyam	vyavakalanabhyam	NOUN
cana-1859	5	36	,	,	PUNCT
cana-1859	5	37	ekadhikina	ekadhikina	NOUN
cana-1859	5	38	purvena	purvena	NOUN
cana-1859	5	39	,	,	PUNCT
cana-1859	5	40	and	and	CCONJ
cana-1859	5	41	gunitasamuchyah	gunitasamuchyah	VERB
cana-1859	5	42	,	,	PUNCT
cana-1859	5	43	for	for	ADP
cana-1859	5	44	optimizing	optimize	VERB
cana-1859	5	45	internal	internal	ADJ
cana-1859	5	46	operations	operation	NOUN
cana-1859	5	47	of	of	ADP
cana-1859	5	48	cnns	cnn	NOUN
cana-1859	5	49	.	.	PUNCT
cana-1859	6	1	these	these	DET
cana-1859	6	2	sutras	sutra	NOUN
cana-1859	6	3	were	be	AUX
cana-1859	6	4	meticulously	meticulously	ADV
cana-1859	6	5	selected	select	VERB
cana-1859	6	6	for	for	ADP
cana-1859	6	7	their	their	PRON
cana-1859	6	8	potential	potential	NOUN
cana-1859	6	9	to	to	PART
cana-1859	6	10	simplify	simplify	VERB
cana-1859	6	11	computational	computational	ADJ
cana-1859	6	12	processes	process	NOUN
cana-1859	6	13	,	,	PUNCT
cana-1859	6	14	enhance	enhance	VERB
cana-1859	6	15	parallel	parallel	ADJ
cana-1859	6	16	processing	processing	NOUN
cana-1859	6	17	capabilities	capability	NOUN
cana-1859	6	18	,	,	PUNCT
cana-1859	6	19	and	and	CCONJ
cana-1859	6	20	optimize	optimize	VERB
cana-1859	6	21	training	training	NOUN
cana-1859	6	22	algorithms	algorithm	NOUN
cana-1859	6	23	.	.	PUNCT
cana-1859	7	1	the	the	DET
cana-1859	7	2	application	application	NOUN
cana-1859	7	3	of	of	ADP
cana-1859	7	4	these	these	DET
cana-1859	7	5	sutras	sutra	NOUN
cana-1859	7	6	has	have	AUX
cana-1859	7	7	led	lead	VERB
cana-1859	7	8	to	to	ADP
cana-1859	7	9	a	a	DET
cana-1859	7	10	remarkable	remarkable	ADJ
cana-1859	7	11	improvement	improvement	NOUN
cana-1859	7	12	in	in	ADP
cana-1859	7	13	the	the	DET
cana-1859	7	14	performance	performance	NOUN
cana-1859	7	15	of	of	ADP
cana-1859	7	16	cnns	cnn	NOUN
cana-1859	7	17	across	across	ADP
cana-1859	7	18	various	various	ADJ
cana-1859	7	19	datasets	dataset	NOUN
cana-1859	7	20	,	,	PUNCT
cana-1859	7	21	including	include	VERB
cana-1859	7	22	imagenet	imagenet	NOUN
cana-1859	7	23	,	,	PUNCT
cana-1859	7	24	cifar	cifar	ADV
cana-1859	7	25	,	,	PUNCT
cana-1859	7	26	chestxray8	chestxray8	PROPN
cana-1859	7	27	,	,	PUNCT
cana-1859	7	28	and	and	CCONJ
cana-1859	7	29	architectural	architectural	ADJ
cana-1859	7	30	heritage	heritage	NOUN
cana-1859	7	31	datasets	dataset	NOUN
cana-1859	7	32	.	.	PUNCT
cana-1859	8	1	the	the	DET
cana-1859	8	2	optimized	optimize	VERB
cana-1859	8	3	cnn	cnn	PROPN
cana-1859	8	4	models	model	NOUN
cana-1859	8	5	demonstrated	demonstrate	VERB
cana-1859	8	6	a	a	DET
cana-1859	8	7	significant	significant	ADJ
cana-1859	8	8	enhancement	enhancement	NOUN
cana-1859	8	9	in	in	ADP
cana-1859	8	10	classification	classification	NOUN
cana-1859	8	11	accuracy	accuracy	NOUN
cana-1859	8	12	(	(	PUNCT
cana-1859	8	13	9.5	9.5	NUM
cana-1859	8	14	%	%	NOUN
cana-1859	8	15	increase	increase	NOUN
cana-1859	8	16	)	)	PUNCT
cana-1859	8	17	,	,	PUNCT
cana-1859	8	18	precision	precision	NOUN
cana-1859	8	19	(	(	PUNCT
cana-1859	8	20	8.3	8.3	NUM
cana-1859	8	21	%	%	NOUN
cana-1859	8	22	increase	increase	NOUN
cana-1859	8	23	)	)	PUNCT
cana-1859	8	24	,	,	PUNCT
cana-1859	8	25	recall	recall	INTJ
cana-1859	8	26	(	(	PUNCT
cana-1859	8	27	8.5	8.5	NUM
cana-1859	8	28	%	%	NOUN
cana-1859	8	29	increase	increase	NOUN
cana-1859	8	30	)	)	PUNCT
cana-1859	8	31	,	,	PUNCT
cana-1859	8	32	area	area	NOUN
cana-1859	8	33	under	under	ADP
cana-1859	8	34	the	the	DET
cana-1859	8	35	curve	curve	NOUN
cana-1859	8	36	(	(	PUNCT
cana-1859	8	37	auc	auc	NOUN
cana-1859	8	38	)	)	PUNCT
cana-1859	8	39	(	(	PUNCT
cana-1859	8	40	4.9	4.9	NUM
cana-1859	8	41	%	%	NOUN
cana-1859	8	42	increase	increase	NOUN
cana-1859	8	43	)	)	PUNCT
cana-1859	8	44	,	,	PUNCT
cana-1859	8	45	mae	mae	PROPN
cana-1859	8	46	(	(	PUNCT
cana-1859	8	47	5.5	5.5	NUM
cana-1859	8	48	%	%	NOUN
cana-1859	8	49	improvement	improvement	NOUN
cana-1859	8	50	)	)	PUNCT
cana-1859	8	51	,	,	PUNCT
cana-1859	8	52	and	and	CCONJ
cana-1859	8	53	reduction	reduction	NOUN
cana-1859	8	54	in	in	ADP
cana-1859	8	55	delay	delay	NOUN
cana-1859	8	56	(	(	PUNCT
cana-1859	8	57	6.5	6.5	NUM
cana-1859	8	58	%	%	NOUN
cana-1859	8	59	decrease	decrease	NOUN
cana-1859	8	60	)	)	PUNCT
cana-1859	8	61	compared	compare	VERB
cana-1859	8	62	to	to	ADP
cana-1859	8	63	existing	exist	VERB
cana-1859	8	64	methods	method	NOUN
cana-1859	8	65	.	.	PUNCT
cana-1859	9	1	the	the	DET
cana-1859	9	2	integration	integration	NOUN
cana-1859	9	3	of	of	ADP
cana-1859	9	4	vedic	vedic	ADJ
cana-1859	9	5	mathematics	mathematics	PROPN
cana-1859	9	6	into	into	ADP
cana-1859	9	7	cnn	cnn	PROPN
cana-1859	9	8	optimization	optimization	NOUN
cana-1859	9	9	not	not	PART
cana-1859	9	10	only	only	ADV
cana-1859	9	11	paves	pave	VERB
cana-1859	9	12	the	the	DET
cana-1859	9	13	way	way	NOUN
cana-1859	9	14	for	for	ADP
cana-1859	9	15	more	more	ADV
cana-1859	9	16	efficient	efficient	ADJ
cana-1859	9	17	and	and	CCONJ
cana-1859	9	18	accurate	accurate	ADJ
cana-1859	9	19	image	image	NOUN
cana-1859	9	20	classification	classification	NOUN
cana-1859	9	21	models	model	NOUN
cana-1859	9	22	but	but	CCONJ
cana-1859	9	23	also	also	ADV
cana-1859	9	24	opens	open	VERB
cana-1859	9	25	new	new	ADJ
cana-1859	9	26	avenues	avenue	NOUN
cana-1859	9	27	for	for	ADP
cana-1859	9	28	interdisciplinary	interdisciplinary	ADJ
cana-1859	9	29	research	research	NOUN
cana-1859	9	30	,	,	PUNCT
cana-1859	9	31	blending	blend	VERB
cana-1859	9	32	ancient	ancient	ADJ
cana-1859	9	33	mathematical	mathematical	ADJ
cana-1859	9	34	wisdom	wisdom	NOUN
cana-1859	9	35	with	with	ADP
cana-1859	9	36	contemporary	contemporary	ADJ
cana-1859	9	37	artificial	artificial	ADJ
cana-1859	9	38	intelligence	intelligence	NOUN
cana-1859	9	39	techniques	technique	NOUN
cana-1859	9	40	.	.	PUNCT
cana-1859	10	1	this	this	DET
cana-1859	10	2	advancement	advancement	NOUN
cana-1859	10	3	has	have	VERB
cana-1859	10	4	profound	profound	ADJ
cana-1859	10	5	implications	implication	NOUN
cana-1859	10	6	for	for	ADP
cana-1859	10	7	various	various	ADJ
cana-1859	10	8	applications	application	NOUN
cana-1859	10	9	,	,	PUNCT
cana-1859	10	10	including	include	VERB
cana-1859	10	11	medical	medical	ADJ
cana-1859	10	12	imaging	imaging	NOUN
cana-1859	10	13	,	,	PUNCT
cana-1859	10	14	autonomous	autonomous	ADJ
cana-1859	10	15	vehicles	vehicle	NOUN
cana-1859	10	16	,	,	PUNCT
cana-1859	10	17	and	and	CCONJ
cana-1859	10	18	heritage	heritage	NOUN
cana-1859	10	19	conservation	conservation	NOUN
cana-1859	10	20	,	,	PUNCT
cana-1859	10	21	thereby	thereby	ADV
cana-1859	10	22	contributing	contribute	VERB
cana-1859	10	23	significantly	significantly	ADV
cana-1859	10	24	to	to	ADP
cana-1859	10	25	the	the	DET
cana-1859	10	26	field	field	NOUN
cana-1859	10	27	of	of	ADP
cana-1859	10	28	ai	ai	ADJ
cana-1859	10	29	and	and	CCONJ
cana-1859	10	30	computational	computational	ADJ
cana-1859	10	31	efficiency	efficiency	NOUN
cana-1859	10	32	.	.	PUNCT
cana-1859	11	1	keywords	keyword	NOUN
cana-1859	11	2	:	:	PUNCT
cana-1859	11	3	convolutional	convolutional	ADJ
cana-1859	11	4	neural	neural	ADJ
cana-1859	11	5	networks	network	NOUN
cana-1859	11	6	,	,	PUNCT
cana-1859	11	7	vedic	vedic	ADJ
cana-1859	11	8	mathematics	mathematic	NOUN
cana-1859	11	9	,	,	PUNCT
cana-1859	11	10	image	image	NOUN
cana-1859	11	11	classification	classification	NOUN
cana-1859	11	12	,	,	PUNCT
cana-1859	11	13	computational	computational	ADJ
cana-1859	11	14	efficiency	efficiency	NOUN
cana-1859	11	15	,	,	PUNCT
cana-1859	11	16	algorithm	algorithm	NOUN
cana-1859	11	17	optimization	optimization	NOUN
cana-1859	11	18	1	1	NUM
cana-1859	11	19	.	.	PUNCT
cana-1859	11	20	introduction	introduction	NOUN
cana-1859	11	21	in	in	ADP
cana-1859	11	22	the	the	DET
cana-1859	11	23	domain	domain	NOUN
cana-1859	11	24	of	of	ADP
cana-1859	11	25	deep	deep	ADJ
cana-1859	11	26	learning	learning	NOUN
cana-1859	11	27	,	,	PUNCT
cana-1859	11	28	convolutional	convolutional	ADJ
cana-1859	11	29	neural	neural	ADJ
cana-1859	11	30	networks	network	NOUN
cana-1859	11	31	(	(	PUNCT
cana-1859	11	32	cnns	cnns	PROPN
cana-1859	11	33	)	)	PUNCT
cana-1859	11	34	have	have	AUX
cana-1859	11	35	been	be	AUX
cana-1859	11	36	at	at	ADP
cana-1859	11	37	the	the	DET
cana-1859	11	38	forefront	forefront	NOUN
cana-1859	11	39	of	of	ADP
cana-1859	11	40	breakthroughs	breakthrough	NOUN
cana-1859	11	41	in	in	ADP
cana-1859	11	42	image	image	NOUN
cana-1859	11	43	classification	classification	NOUN
cana-1859	11	44	.	.	PUNCT
cana-1859	12	1	their	their	PRON
cana-1859	12	2	ability	ability	NOUN
cana-1859	12	3	to	to	PART
cana-1859	12	4	extract	extract	VERB
cana-1859	12	5	and	and	CCONJ
cana-1859	12	6	learn	learn	VERB
cana-1859	12	7	features	feature	NOUN
cana-1859	12	8	from	from	ADP
cana-1859	12	9	images	image	NOUN
cana-1859	12	10	has	have	AUX
cana-1859	12	11	made	make	VERB
cana-1859	12	12	them	they	PRON
cana-1859	12	13	indispensable	indispensable	ADJ
cana-1859	12	14	in	in	ADP
cana-1859	12	15	a	a	DET
cana-1859	12	16	variety	variety	NOUN
cana-1859	12	17	of	of	ADP
cana-1859	12	18	applications	application	NOUN
cana-1859	12	19	,	,	PUNCT
cana-1859	12	20	ranging	range	VERB
cana-1859	12	21	from	from	ADP
cana-1859	12	22	medical	medical	ADJ
cana-1859	12	23	diagnostics	diagnostic	NOUN
cana-1859	12	24	to	to	ADP
cana-1859	12	25	autonomous	autonomous	ADJ
cana-1859	12	26	vehicle	vehicle	NOUN
cana-1859	12	27	navigation	navigation	NOUN
cana-1859	12	28	.	.	PUNCT
cana-1859	13	1	however	however	ADV
cana-1859	13	2	,	,	PUNCT
cana-1859	13	3	as	as	SCONJ
cana-1859	13	4	the	the	DET
cana-1859	13	5	demand	demand	NOUN
cana-1859	13	6	for	for	ADP
cana-1859	13	7	higher	high	ADJ
cana-1859	13	8	accuracy	accuracy	NOUN
cana-1859	13	9	and	and	CCONJ
cana-1859	13	10	computational	computational	ADJ
cana-1859	13	11	efficiency	efficiency	NOUN
cana-1859	13	12	grows	grow	VERB
cana-1859	13	13	,	,	PUNCT
cana-1859	13	14	communications	communication	NOUN
cana-1859	13	15	on	on	ADP
cana-1859	13	16	applied	apply	VERB
cana-1859	13	17	nonlinear	nonlinear	ADJ
cana-1859	13	18	analysis	analysis	NOUN
cana-1859	13	19	issn	issn	NOUN
cana-1859	13	20	:	:	PUNCT
cana-1859	13	21	1074	1074	NUM
cana-1859	13	22	-	-	PUNCT
cana-1859	13	23	133x	133x	NUM
cana-1859	13	24	vol	vol	NOUN
cana-1859	13	25	32	32	NUM
cana-1859	13	26	no	no	NOUN
cana-1859	13	27	.	.	NOUN
cana-1859	13	28	2	2	NUM
cana-1859	13	29	(	(	PUNCT
cana-1859	13	30	2025	2025	NUM
cana-1859	13	31	)	)	PUNCT
cana-1859	13	32	639	639	NUM
cana-1859	13	33	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	13	34	traditional	traditional	ADJ
cana-1859	13	35	cnn	cnn	PROPN
cana-1859	13	36	architectures	architecture	NOUN
cana-1859	13	37	and	and	CCONJ
cana-1859	13	38	optimization	optimization	NOUN
cana-1859	13	39	methods	method	NOUN
cana-1859	13	40	increasingly	increasingly	ADV
cana-1859	13	41	face	face	VERB
cana-1859	13	42	challenges	challenge	NOUN
cana-1859	13	43	in	in	ADP
cana-1859	13	44	meeting	meet	VERB
cana-1859	13	45	these	these	DET
cana-1859	13	46	demands	demand	NOUN
cana-1859	13	47	,	,	PUNCT
cana-1859	13	48	particularly	particularly	ADV
cana-1859	13	49	when	when	SCONJ
cana-1859	13	50	processing	processing	NOUN
cana-1859	13	51	diverse	diverse	ADJ
cana-1859	13	52	and	and	CCONJ
cana-1859	13	53	complex	complex	ADJ
cana-1859	13	54	datasets	dataset	NOUN
cana-1859	13	55	.	.	PUNCT
cana-1859	14	1	the	the	DET
cana-1859	14	2	quest	quest	NOUN
cana-1859	14	3	for	for	ADP
cana-1859	14	4	optimizing	optimize	VERB
cana-1859	14	5	cnns	cnn	NOUN
cana-1859	14	6	has	have	AUX
cana-1859	14	7	led	lead	VERB
cana-1859	14	8	researchers	researcher	NOUN
cana-1859	14	9	to	to	PART
cana-1859	14	10	explore	explore	VERB
cana-1859	14	11	various	various	ADJ
cana-1859	14	12	avenues	avenue	NOUN
cana-1859	14	13	,	,	PUNCT
cana-1859	14	14	from	from	ADP
cana-1859	14	15	architectural	architectural	ADJ
cana-1859	14	16	innovations	innovation	NOUN
cana-1859	14	17	to	to	ADP
cana-1859	14	18	advanced	advanced	ADJ
cana-1859	14	19	training	training	NOUN
cana-1859	14	20	algorithms	algorithm	NOUN
cana-1859	14	21	.	.	PUNCT
cana-1859	15	1	yet	yet	ADV
cana-1859	15	2	,	,	PUNCT
cana-1859	15	3	these	these	DET
cana-1859	15	4	efforts	effort	NOUN
cana-1859	15	5	often	often	ADV
cana-1859	15	6	encounter	encounter	VERB
cana-1859	15	7	limitations	limitation	NOUN
cana-1859	15	8	in	in	ADP
cana-1859	15	9	balancing	balance	VERB
cana-1859	15	10	computational	computational	ADJ
cana-1859	15	11	load	load	NOUN
cana-1859	15	12	,	,	PUNCT
cana-1859	15	13	model	model	NOUN
cana-1859	15	14	accuracy	accuracy	NOUN
cana-1859	15	15	,	,	PUNCT
cana-1859	15	16	and	and	CCONJ
cana-1859	15	17	generalizability	generalizability	NOUN
cana-1859	15	18	.	.	PUNCT
cana-1859	16	1	this	this	DET
cana-1859	16	2	paper	paper	NOUN
cana-1859	16	3	addresses	address	VERB
cana-1859	16	4	these	these	DET
cana-1859	16	5	challenges	challenge	NOUN
cana-1859	16	6	by	by	ADP
cana-1859	16	7	turning	turn	VERB
cana-1859	16	8	to	to	ADP
cana-1859	16	9	a	a	DET
cana-1859	16	10	rather	rather	ADV
cana-1859	16	11	unconventional	unconventional	ADJ
cana-1859	16	12	source	source	NOUN
cana-1859	16	13	:	:	PUNCT
cana-1859	16	14	vedic	vedic	ADJ
cana-1859	16	15	mathematics	mathematic	NOUN
cana-1859	16	16	.	.	PUNCT
cana-1859	17	1	this	this	DET
cana-1859	17	2	ancient	ancient	ADJ
cana-1859	17	3	indian	indian	ADJ
cana-1859	17	4	mathematical	mathematical	ADJ
cana-1859	17	5	system	system	NOUN
cana-1859	17	6	is	be	AUX
cana-1859	17	7	renowned	renowne	VERB
cana-1859	17	8	for	for	ADP
cana-1859	17	9	its	its	PRON
cana-1859	17	10	simplified	simplified	ADJ
cana-1859	17	11	and	and	CCONJ
cana-1859	17	12	efficient	efficient	ADJ
cana-1859	17	13	computational	computational	ADJ
cana-1859	17	14	techniques	technique	NOUN
cana-1859	17	15	,	,	PUNCT
cana-1859	17	16	which	which	PRON
cana-1859	17	17	have	have	VERB
cana-1859	17	18	the	the	DET
cana-1859	17	19	potential	potential	NOUN
cana-1859	17	20	to	to	PART
cana-1859	17	21	revolutionize	revolutionize	VERB
cana-1859	17	22	the	the	DET
cana-1859	17	23	way	way	NOUN
cana-1859	17	24	cnns	cnns	PROPN
cana-1859	17	25	are	be	AUX
cana-1859	17	26	optimized	optimize	VERB
cana-1859	17	27	.	.	PUNCT
cana-1859	18	1	vedic	vedic	ADJ
cana-1859	18	2	mathematics	mathematics	PROPN
cana-1859	18	3	,	,	PUNCT
cana-1859	18	4	with	with	ADP
cana-1859	18	5	its	its	PRON
cana-1859	18	6	array	array	NOUN
cana-1859	18	7	of	of	ADP
cana-1859	18	8	sutras	sutra	NOUN
cana-1859	18	9	(	(	PUNCT
cana-1859	18	10	formulas	formula	NOUN
cana-1859	18	11	or	or	CCONJ
cana-1859	18	12	principles	principle	NOUN
cana-1859	18	13	)	)	PUNCT
cana-1859	18	14	,	,	PUNCT
cana-1859	18	15	offers	offer	VERB
cana-1859	18	16	a	a	DET
cana-1859	18	17	unique	unique	ADJ
cana-1859	18	18	approach	approach	NOUN
cana-1859	18	19	to	to	ADP
cana-1859	18	20	simplifying	simplify	VERB
cana-1859	18	21	complex	complex	ADJ
cana-1859	18	22	calculations	calculation	NOUN
cana-1859	18	23	.	.	PUNCT
cana-1859	19	1	in	in	ADP
cana-1859	19	2	this	this	DET
cana-1859	19	3	study	study	NOUN
cana-1859	19	4	,	,	PUNCT
cana-1859	19	5	we	we	PRON
cana-1859	19	6	harness	harness	VERB
cana-1859	19	7	this	this	DET
cana-1859	19	8	potential	potential	NOUN
cana-1859	19	9	to	to	PART
cana-1859	19	10	enhance	enhance	VERB
cana-1859	19	11	the	the	DET
cana-1859	19	12	performance	performance	NOUN
cana-1859	19	13	of	of	ADP
cana-1859	19	14	cnns	cnn	NOUN
cana-1859	19	15	.	.	PUNCT
cana-1859	20	1	we	we	PRON
cana-1859	20	2	meticulously	meticulously	ADV
cana-1859	20	3	integrate	integrate	VERB
cana-1859	20	4	specific	specific	ADJ
cana-1859	20	5	vedic	vedic	ADJ
cana-1859	20	6	sutras	sutra	NOUN
cana-1859	20	7	such	such	ADJ
cana-1859	20	8	as	as	ADP
cana-1859	20	9	urdhva	urdhva	NOUN
cana-1859	20	10	-	-	PUNCT
cana-1859	20	11	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	20	12	for	for	ADP
cana-1859	20	13	efficient	efficient	ADJ
cana-1859	20	14	matrix	matrix	NOUN
cana-1859	20	15	multiplication	multiplication	NOUN
cana-1859	20	16	,	,	PUNCT
cana-1859	20	17	anurupyena	anurupyena	ADJ
cana-1859	20	18	for	for	ADP
cana-1859	20	19	scaling	scale	VERB
cana-1859	20	20	operations	operation	NOUN
cana-1859	20	21	,	,	PUNCT
cana-1859	20	22	and	and	CCONJ
cana-1859	20	23	nikhilam	nikhilam	PROPN
cana-1859	20	24	navatashcaramam	navatashcaramam	NOUN
cana-1859	20	25	dashatah	dashatah	NOUN
cana-1859	20	26	for	for	ADP
cana-1859	20	27	optimized	optimize	VERB
cana-1859	20	28	subtraction	subtraction	NOUN
cana-1859	20	29	processes	process	NOUN
cana-1859	20	30	,	,	PUNCT
cana-1859	20	31	among	among	ADP
cana-1859	20	32	others	other	NOUN
cana-1859	20	33	.	.	PUNCT
cana-1859	21	1	these	these	DET
cana-1859	21	2	sutras	sutra	NOUN
cana-1859	21	3	were	be	AUX
cana-1859	21	4	chosen	choose	VERB
cana-1859	21	5	for	for	ADP
cana-1859	21	6	their	their	PRON
cana-1859	21	7	relevance	relevance	NOUN
cana-1859	21	8	to	to	ADP
cana-1859	21	9	the	the	DET
cana-1859	21	10	computational	computational	ADJ
cana-1859	21	11	processes	process	NOUN
cana-1859	21	12	integral	integral	ADJ
cana-1859	21	13	to	to	ADP
cana-1859	21	14	cnn	cnn	PROPN
cana-1859	21	15	operations	operation	NOUN
cana-1859	21	16	,	,	PUNCT
cana-1859	21	17	such	such	ADJ
cana-1859	21	18	as	as	ADP
cana-1859	21	19	convolution	convolution	NOUN
cana-1859	21	20	,	,	PUNCT
cana-1859	21	21	pooling	pooling	NOUN
cana-1859	21	22	,	,	PUNCT
cana-1859	21	23	and	and	CCONJ
cana-1859	21	24	backpropagation	backpropagation	NOUN
cana-1859	21	25	.	.	PUNCT
cana-1859	22	1	the	the	DET
cana-1859	22	2	application	application	NOUN
cana-1859	22	3	of	of	ADP
cana-1859	22	4	these	these	DET
cana-1859	22	5	principles	principle	NOUN
cana-1859	22	6	to	to	ADP
cana-1859	22	7	cnn	cnn	PROPN
cana-1859	22	8	optimization	optimization	NOUN
cana-1859	22	9	is	be	AUX
cana-1859	22	10	not	not	PART
cana-1859	22	11	merely	merely	ADV
cana-1859	22	12	a	a	DET
cana-1859	22	13	theoretical	theoretical	ADJ
cana-1859	22	14	exercise	exercise	NOUN
cana-1859	22	15	;	;	PUNCT
cana-1859	22	16	it	it	PRON
cana-1859	22	17	has	have	VERB
cana-1859	22	18	practical	practical	ADJ
cana-1859	22	19	and	and	CCONJ
cana-1859	22	20	significant	significant	ADJ
cana-1859	22	21	implications	implication	NOUN
cana-1859	22	22	.	.	PUNCT
cana-1859	23	1	our	our	PRON
cana-1859	23	2	optimized	optimize	VERB
cana-1859	23	3	cnn	cnn	PROPN
cana-1859	23	4	models	model	NOUN
cana-1859	23	5	,	,	PUNCT
cana-1859	23	6	when	when	SCONJ
cana-1859	23	7	tested	test	VERB
cana-1859	23	8	on	on	ADP
cana-1859	23	9	diverse	diverse	ADJ
cana-1859	23	10	datasets	dataset	NOUN
cana-1859	23	11	like	like	ADP
cana-1859	23	12	imagenet	imagenet	NOUN
cana-1859	23	13	,	,	PUNCT
cana-1859	23	14	cifar	cifar	ADV
cana-1859	23	15	,	,	PUNCT
cana-1859	23	16	chestxray8	chestxray8	PROPN
cana-1859	23	17	,	,	PUNCT
cana-1859	23	18	and	and	CCONJ
cana-1859	23	19	architectural	architectural	ADJ
cana-1859	23	20	heritage	heritage	NOUN
cana-1859	23	21	,	,	PUNCT
cana-1859	23	22	exhibited	exhibit	VERB
cana-1859	23	23	substantial	substantial	ADJ
cana-1859	23	24	improvements	improvement	NOUN
cana-1859	23	25	in	in	ADP
cana-1859	23	26	several	several	ADJ
cana-1859	23	27	key	key	ADJ
cana-1859	23	28	performance	performance	NOUN
cana-1859	23	29	metrics	metric	NOUN
cana-1859	23	30	.	.	PUNCT
cana-1859	24	1	notably	notably	ADV
cana-1859	24	2	,	,	PUNCT
cana-1859	24	3	there	there	PRON
cana-1859	24	4	was	be	VERB
cana-1859	24	5	an	an	DET
cana-1859	24	6	increase	increase	NOUN
cana-1859	24	7	in	in	ADP
cana-1859	24	8	classification	classification	NOUN
cana-1859	24	9	accuracy	accuracy	NOUN
cana-1859	24	10	,	,	PUNCT
cana-1859	24	11	precision	precision	NOUN
cana-1859	24	12	,	,	PUNCT
cana-1859	24	13	recall	recall	NOUN
cana-1859	24	14	,	,	PUNCT
cana-1859	24	15	area	area	NOUN
cana-1859	24	16	under	under	ADP
cana-1859	24	17	the	the	DET
cana-1859	24	18	curve	curve	NOUN
cana-1859	24	19	(	(	PUNCT
cana-1859	24	20	auc	auc	NOUN
cana-1859	24	21	)	)	PUNCT
cana-1859	24	22	,	,	PUNCT
cana-1859	24	23	and	and	CCONJ
cana-1859	24	24	specificity	specificity	NOUN
cana-1859	24	25	,	,	PUNCT
cana-1859	24	26	along	along	ADP
cana-1859	24	27	with	with	ADP
cana-1859	24	28	a	a	DET
cana-1859	24	29	reduction	reduction	NOUN
cana-1859	24	30	in	in	ADP
cana-1859	24	31	computational	computational	ADJ
cana-1859	24	32	delay	delay	NOUN
cana-1859	24	33	.	.	PUNCT
cana-1859	25	1	these	these	DET
cana-1859	25	2	enhancements	enhancement	NOUN
cana-1859	25	3	are	be	AUX
cana-1859	25	4	critical	critical	ADJ
cana-1859	25	5	in	in	ADP
cana-1859	25	6	applications	application	NOUN
cana-1859	25	7	where	where	SCONJ
cana-1859	25	8	speed	speed	NOUN
cana-1859	25	9	and	and	CCONJ
cana-1859	25	10	accuracy	accuracy	NOUN
cana-1859	25	11	are	be	AUX
cana-1859	25	12	paramount	paramount	ADJ
cana-1859	25	13	,	,	PUNCT
cana-1859	25	14	such	such	ADJ
cana-1859	25	15	as	as	ADP
cana-1859	25	16	real	real	ADJ
cana-1859	25	17	-	-	PUNCT
cana-1859	25	18	time	time	NOUN
cana-1859	25	19	image	image	NOUN
cana-1859	25	20	analysis	analysis	NOUN
cana-1859	25	21	in	in	ADP
cana-1859	25	22	medical	medical	ADJ
cana-1859	25	23	and	and	CCONJ
cana-1859	25	24	automotive	automotive	ADJ
cana-1859	25	25	fields	field	NOUN
cana-1859	25	26	.	.	PUNCT
cana-1859	26	1	this	this	DET
cana-1859	26	2	integration	integration	NOUN
cana-1859	26	3	of	of	ADP
cana-1859	26	4	ancient	ancient	ADJ
cana-1859	26	5	mathematical	mathematical	ADJ
cana-1859	26	6	wisdom	wisdom	NOUN
cana-1859	26	7	into	into	ADP
cana-1859	26	8	modern	modern	ADJ
cana-1859	26	9	ai	ai	NOUN
cana-1859	26	10	techniques	technique	NOUN
cana-1859	26	11	does	do	AUX
cana-1859	26	12	not	not	PART
cana-1859	26	13	only	only	ADV
cana-1859	26	14	contribute	contribute	VERB
cana-1859	26	15	to	to	ADP
cana-1859	26	16	the	the	DET
cana-1859	26	17	advancement	advancement	NOUN
cana-1859	26	18	of	of	ADP
cana-1859	26	19	cnn	cnn	PROPN
cana-1859	26	20	optimization	optimization	NOUN
cana-1859	26	21	but	but	CCONJ
cana-1859	26	22	also	also	ADV
cana-1859	26	23	opens	open	VERB
cana-1859	26	24	new	new	ADJ
cana-1859	26	25	pathways	pathway	NOUN
cana-1859	26	26	for	for	ADP
cana-1859	26	27	interdisciplinary	interdisciplinary	ADJ
cana-1859	26	28	research	research	NOUN
cana-1859	26	29	.	.	PUNCT
cana-1859	27	1	it	it	PRON
cana-1859	27	2	demonstrates	demonstrate	VERB
cana-1859	27	3	the	the	DET
cana-1859	27	4	untapped	untapped	ADJ
cana-1859	27	5	potential	potential	NOUN
cana-1859	27	6	of	of	ADP
cana-1859	27	7	traditional	traditional	ADJ
cana-1859	27	8	knowledge	knowledge	NOUN
cana-1859	27	9	systems	system	NOUN
cana-1859	27	10	in	in	ADP
cana-1859	27	11	addressing	address	VERB
cana-1859	27	12	contemporary	contemporary	ADJ
cana-1859	27	13	technological	technological	ADJ
cana-1859	27	14	challenges	challenge	NOUN
cana-1859	27	15	.	.	PUNCT
cana-1859	28	1	this	this	DET
cana-1859	28	2	paper	paper	NOUN
cana-1859	28	3	aims	aim	VERB
cana-1859	28	4	to	to	PART
cana-1859	28	5	bridge	bridge	VERB
cana-1859	28	6	this	this	DET
cana-1859	28	7	gap	gap	NOUN
cana-1859	28	8	,	,	PUNCT
cana-1859	28	9	showcasing	showcase	VERB
cana-1859	28	10	how	how	SCONJ
cana-1859	28	11	the	the	DET
cana-1859	28	12	synergy	synergy	NOUN
cana-1859	28	13	between	between	ADP
cana-1859	28	14	historical	historical	ADJ
cana-1859	28	15	mathematical	mathematical	ADJ
cana-1859	28	16	principles	principle	NOUN
cana-1859	28	17	and	and	CCONJ
cana-1859	28	18	current	current	ADJ
cana-1859	28	19	computational	computational	ADJ
cana-1859	28	20	methods	method	NOUN
cana-1859	28	21	can	can	AUX
cana-1859	28	22	lead	lead	VERB
cana-1859	28	23	to	to	ADP
cana-1859	28	24	significant	significant	ADJ
cana-1859	28	25	advancements	advancement	NOUN
cana-1859	28	26	in	in	ADP
cana-1859	28	27	the	the	DET
cana-1859	28	28	field	field	NOUN
cana-1859	28	29	of	of	ADP
cana-1859	28	30	artificial	artificial	ADJ
cana-1859	28	31	intelligence	intelligence	NOUN
cana-1859	28	32	and	and	CCONJ
cana-1859	28	33	deep	deep	ADJ
cana-1859	28	34	learning	learning	NOUN
cana-1859	28	35	process	process	NOUN
cana-1859	28	36	.	.	PUNCT
cana-1859	29	1	motivation	motivation	NOUN
cana-1859	29	2	&	&	CCONJ
cana-1859	29	3	contribution	contribution	NOUN
cana-1859	29	4	motivation	motivation	NOUN
cana-1859	29	5	the	the	DET
cana-1859	29	6	motivation	motivation	NOUN
cana-1859	29	7	behind	behind	ADP
cana-1859	29	8	this	this	DET
cana-1859	29	9	research	research	NOUN
cana-1859	29	10	stems	stem	VERB
cana-1859	29	11	from	from	ADP
cana-1859	29	12	a	a	DET
cana-1859	29	13	fundamental	fundamental	ADJ
cana-1859	29	14	challenge	challenge	NOUN
cana-1859	29	15	in	in	ADP
cana-1859	29	16	the	the	DET
cana-1859	29	17	field	field	NOUN
cana-1859	29	18	of	of	ADP
cana-1859	29	19	artificial	artificial	ADJ
cana-1859	29	20	intelligence	intelligence	NOUN
cana-1859	29	21	:	:	PUNCT
cana-1859	29	22	the	the	DET
cana-1859	29	23	pursuit	pursuit	NOUN
cana-1859	29	24	of	of	ADP
cana-1859	29	25	optimizing	optimize	VERB
cana-1859	29	26	deep	deep	ADJ
cana-1859	29	27	learning	learning	NOUN
cana-1859	29	28	models	model	NOUN
cana-1859	29	29	,	,	PUNCT
cana-1859	29	30	particularly	particularly	ADV
cana-1859	29	31	convolutional	convolutional	ADJ
cana-1859	29	32	neural	neural	ADJ
cana-1859	29	33	networks	network	NOUN
cana-1859	29	34	(	(	PUNCT
cana-1859	29	35	cnns	cnns	PROPN
cana-1859	29	36	)	)	PUNCT
cana-1859	29	37	,	,	PUNCT
cana-1859	29	38	for	for	ADP
cana-1859	29	39	greater	great	ADJ
cana-1859	29	40	efficiency	efficiency	NOUN
cana-1859	29	41	and	and	CCONJ
cana-1859	29	42	accuracy	accuracy	NOUN
cana-1859	29	43	.	.	PUNCT
cana-1859	30	1	the	the	DET
cana-1859	30	2	rapid	rapid	ADJ
cana-1859	30	3	expansion	expansion	NOUN
cana-1859	30	4	of	of	ADP
cana-1859	30	5	digital	digital	ADJ
cana-1859	30	6	data	datum	NOUN
cana-1859	30	7	,	,	PUNCT
cana-1859	30	8	especially	especially	ADV
cana-1859	30	9	in	in	ADP
cana-1859	30	10	image	image	NOUN
cana-1859	30	11	form	form	NOUN
cana-1859	30	12	,	,	PUNCT
cana-1859	30	13	necessitates	necessitate	VERB
cana-1859	30	14	models	model	NOUN
cana-1859	30	15	that	that	PRON
cana-1859	30	16	not	not	PART
cana-1859	30	17	only	only	ADV
cana-1859	30	18	perform	perform	VERB
cana-1859	30	19	with	with	ADP
cana-1859	30	20	high	high	ADJ
cana-1859	30	21	accuracy	accuracy	NOUN
cana-1859	30	22	but	but	CCONJ
cana-1859	30	23	also	also	ADV
cana-1859	30	24	operate	operate	VERB
cana-1859	30	25	efficiently	efficiently	ADV
cana-1859	30	26	on	on	ADP
cana-1859	30	27	diverse	diverse	ADJ
cana-1859	30	28	and	and	CCONJ
cana-1859	30	29	voluminous	voluminous	ADJ
cana-1859	30	30	datasets	dataset	NOUN
cana-1859	30	31	.	.	PUNCT
cana-1859	31	1	traditional	traditional	ADJ
cana-1859	31	2	optimization	optimization	NOUN
cana-1859	31	3	methods	method	NOUN
cana-1859	31	4	in	in	ADP
cana-1859	31	5	cnns	cnn	NOUN
cana-1859	31	6	,	,	PUNCT
cana-1859	31	7	while	while	SCONJ
cana-1859	31	8	effective	effective	ADJ
cana-1859	31	9	to	to	ADP
cana-1859	31	10	an	an	DET
cana-1859	31	11	extent	extent	NOUN
cana-1859	31	12	,	,	PUNCT
cana-1859	31	13	often	often	ADV
cana-1859	31	14	struggle	struggle	VERB
cana-1859	31	15	to	to	PART
cana-1859	31	16	maintain	maintain	VERB
cana-1859	31	17	a	a	DET
cana-1859	31	18	balance	balance	NOUN
cana-1859	31	19	between	between	ADP
cana-1859	31	20	computational	computational	ADJ
cana-1859	31	21	resource	resource	NOUN
cana-1859	31	22	demands	demand	VERB
cana-1859	31	23	communications	communication	NOUN
cana-1859	31	24	on	on	ADP
cana-1859	31	25	applied	apply	VERB
cana-1859	31	26	nonlinear	nonlinear	ADJ
cana-1859	31	27	analysis	analysis	NOUN
cana-1859	31	28	issn	issn	NOUN
cana-1859	31	29	:	:	PUNCT
cana-1859	31	30	1074	1074	NUM
cana-1859	31	31	-	-	PUNCT
cana-1859	31	32	133x	133x	NUM
cana-1859	31	33	vol	vol	NOUN
cana-1859	31	34	32	32	NUM
cana-1859	31	35	no	no	NOUN
cana-1859	31	36	.	.	NOUN
cana-1859	31	37	2	2	NUM
cana-1859	31	38	(	(	PUNCT
cana-1859	31	39	2025	2025	NUM
cana-1859	31	40	)	)	PUNCT
cana-1859	31	41	640	640	NUM
cana-1859	31	42	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	31	43	and	and	CCONJ
cana-1859	31	44	the	the	DET
cana-1859	31	45	desired	desire	VERB
cana-1859	31	46	performance	performance	NOUN
cana-1859	31	47	metrics	metric	NOUN
cana-1859	31	48	.	.	PUNCT
cana-1859	32	1	this	this	PRON
cana-1859	32	2	creates	create	VERB
cana-1859	32	3	a	a	DET
cana-1859	32	4	bottleneck	bottleneck	NOUN
cana-1859	32	5	in	in	ADP
cana-1859	32	6	applications	application	NOUN
cana-1859	32	7	requiring	require	VERB
cana-1859	32	8	real	real	ADJ
cana-1859	32	9	-	-	PUNCT
cana-1859	32	10	time	time	NOUN
cana-1859	32	11	processing	processing	NOUN
cana-1859	32	12	and	and	CCONJ
cana-1859	32	13	high	high	ADJ
cana-1859	32	14	-	-	PUNCT
cana-1859	32	15	precision	precision	NOUN
cana-1859	32	16	results	result	NOUN
cana-1859	32	17	,	,	PUNCT
cana-1859	32	18	such	such	ADJ
cana-1859	32	19	as	as	ADP
cana-1859	32	20	in	in	ADP
cana-1859	32	21	medical	medical	ADJ
cana-1859	32	22	imaging	imaging	NOUN
cana-1859	32	23	or	or	CCONJ
cana-1859	32	24	autonomous	autonomous	ADJ
cana-1859	32	25	vehicle	vehicle	NOUN
cana-1859	32	26	systems	system	NOUN
cana-1859	32	27	.	.	PUNCT
cana-1859	33	1	the	the	DET
cana-1859	33	2	exploration	exploration	NOUN
cana-1859	33	3	of	of	ADP
cana-1859	33	4	vedic	vedic	ADJ
cana-1859	33	5	mathematics	mathematic	NOUN
cana-1859	33	6	as	as	ADP
cana-1859	33	7	a	a	DET
cana-1859	33	8	tool	tool	NOUN
cana-1859	33	9	for	for	ADP
cana-1859	33	10	optimization	optimization	NOUN
cana-1859	33	11	presents	present	VERB
cana-1859	33	12	an	an	DET
cana-1859	33	13	opportunity	opportunity	NOUN
cana-1859	33	14	to	to	PART
cana-1859	33	15	address	address	VERB
cana-1859	33	16	these	these	DET
cana-1859	33	17	challenges	challenge	NOUN
cana-1859	33	18	.	.	PUNCT
cana-1859	34	1	its	its	PRON
cana-1859	34	2	methods	method	NOUN
cana-1859	34	3	,	,	PUNCT
cana-1859	34	4	known	know	VERB
cana-1859	34	5	for	for	ADP
cana-1859	34	6	their	their	PRON
cana-1859	34	7	computational	computational	ADJ
cana-1859	34	8	simplicity	simplicity	NOUN
cana-1859	34	9	and	and	CCONJ
cana-1859	34	10	efficiency	efficiency	NOUN
cana-1859	34	11	,	,	PUNCT
cana-1859	34	12	offer	offer	VERB
cana-1859	34	13	a	a	DET
cana-1859	34	14	novel	novel	ADJ
cana-1859	34	15	approach	approach	NOUN
cana-1859	34	16	to	to	PART
cana-1859	34	17	streamline	streamline	VERB
cana-1859	34	18	cnn	cnn	PROPN
cana-1859	34	19	processes	process	NOUN
cana-1859	34	20	.	.	PUNCT
cana-1859	35	1	the	the	DET
cana-1859	35	2	motivation	motivation	NOUN
cana-1859	35	3	is	be	AUX
cana-1859	35	4	further	far	ADV
cana-1859	35	5	fueled	fuel	VERB
cana-1859	35	6	by	by	ADP
cana-1859	35	7	the	the	DET
cana-1859	35	8	need	need	NOUN
cana-1859	35	9	to	to	PART
cana-1859	35	10	explore	explore	VERB
cana-1859	35	11	and	and	CCONJ
cana-1859	35	12	integrate	integrate	VERB
cana-1859	35	13	diverse	diverse	ADJ
cana-1859	35	14	knowledge	knowledge	NOUN
cana-1859	35	15	systems	system	NOUN
cana-1859	35	16	into	into	ADP
cana-1859	35	17	modern	modern	ADJ
cana-1859	35	18	technology	technology	NOUN
cana-1859	35	19	,	,	PUNCT
cana-1859	35	20	recognizing	recognize	VERB
cana-1859	35	21	that	that	SCONJ
cana-1859	35	22	ancient	ancient	ADJ
cana-1859	35	23	mathematical	mathematical	ADJ
cana-1859	35	24	principles	principle	NOUN
cana-1859	35	25	can	can	AUX
cana-1859	35	26	contribute	contribute	VERB
cana-1859	35	27	significantly	significantly	ADV
cana-1859	35	28	to	to	ADP
cana-1859	35	29	contemporary	contemporary	ADJ
cana-1859	35	30	computational	computational	ADJ
cana-1859	35	31	challenges	challenge	NOUN
cana-1859	35	32	.	.	PUNCT
cana-1859	36	1	contribution	contribution	NOUN
cana-1859	36	2	this	this	DET
cana-1859	36	3	research	research	NOUN
cana-1859	36	4	makes	make	VERB
cana-1859	36	5	several	several	ADJ
cana-1859	36	6	key	key	ADJ
cana-1859	36	7	contributions	contribution	NOUN
cana-1859	36	8	to	to	ADP
cana-1859	36	9	the	the	DET
cana-1859	36	10	field	field	NOUN
cana-1859	36	11	of	of	ADP
cana-1859	36	12	deep	deep	ADJ
cana-1859	36	13	learning	learning	NOUN
cana-1859	36	14	and	and	CCONJ
cana-1859	36	15	cnn	cnn	PROPN
cana-1859	36	16	optimization	optimization	NOUN
cana-1859	36	17	:	:	PUNCT
cana-1859	36	18	•	•	NUM
cana-1859	36	19	innovative	innovative	ADJ
cana-1859	36	20	integration	integration	NOUN
cana-1859	36	21	of	of	ADP
cana-1859	36	22	ancient	ancient	ADJ
cana-1859	36	23	mathematics	mathematic	NOUN
cana-1859	36	24	with	with	ADP
cana-1859	36	25	modern	modern	ADJ
cana-1859	36	26	ai	ai	NOUN
cana-1859	36	27	:	:	PUNCT
cana-1859	36	28	by	by	ADP
cana-1859	36	29	incorporating	incorporate	VERB
cana-1859	36	30	vedic	vedic	ADJ
cana-1859	36	31	mathematics	mathematic	NOUN
cana-1859	36	32	into	into	ADP
cana-1859	36	33	cnn	cnn	PROPN
cana-1859	36	34	optimization	optimization	NOUN
cana-1859	36	35	,	,	PUNCT
cana-1859	36	36	this	this	DET
cana-1859	36	37	study	study	NOUN
cana-1859	36	38	bridges	bridge	VERB
cana-1859	36	39	a	a	DET
cana-1859	36	40	gap	gap	NOUN
cana-1859	36	41	between	between	ADP
cana-1859	36	42	traditional	traditional	ADJ
cana-1859	36	43	mathematical	mathematical	ADJ
cana-1859	36	44	wisdom	wisdom	NOUN
cana-1859	36	45	and	and	CCONJ
cana-1859	36	46	contemporary	contemporary	ADJ
cana-1859	36	47	computational	computational	ADJ
cana-1859	36	48	needs	need	NOUN
cana-1859	36	49	.	.	PUNCT
cana-1859	37	1	it	it	PRON
cana-1859	37	2	provides	provide	VERB
cana-1859	37	3	a	a	DET
cana-1859	37	4	fresh	fresh	ADJ
cana-1859	37	5	perspective	perspective	NOUN
cana-1859	37	6	on	on	ADP
cana-1859	37	7	how	how	SCONJ
cana-1859	37	8	ancient	ancient	ADJ
cana-1859	37	9	techniques	technique	NOUN
cana-1859	37	10	can	can	AUX
cana-1859	37	11	be	be	AUX
cana-1859	37	12	adapted	adapt	VERB
cana-1859	37	13	to	to	ADP
cana-1859	37	14	modern	modern	ADJ
cana-1859	37	15	technology	technology	NOUN
cana-1859	37	16	.	.	PUNCT
cana-1859	38	1	•	•	NUM
cana-1859	38	2	enhanced	enhance	VERB
cana-1859	38	3	cnn	cnn	PROPN
cana-1859	38	4	performance	performance	NOUN
cana-1859	38	5	:	:	PUNCT
cana-1859	38	6	the	the	DET
cana-1859	38	7	application	application	NOUN
cana-1859	38	8	of	of	ADP
cana-1859	38	9	specific	specific	ADJ
cana-1859	38	10	vedic	vedic	ADJ
cana-1859	38	11	sutras	sutra	NOUN
cana-1859	38	12	to	to	ADP
cana-1859	38	13	cnns	cnns	PROPN
cana-1859	38	14	leads	lead	NOUN
cana-1859	38	15	to	to	ADP
cana-1859	38	16	significant	significant	ADJ
cana-1859	38	17	improvements	improvement	NOUN
cana-1859	38	18	in	in	ADP
cana-1859	38	19	performance	performance	NOUN
cana-1859	38	20	metrics	metric	NOUN
cana-1859	38	21	across	across	ADP
cana-1859	38	22	various	various	ADJ
cana-1859	38	23	datasets	dataset	NOUN
cana-1859	38	24	.	.	PUNCT
cana-1859	39	1	this	this	PRON
cana-1859	39	2	includes	include	VERB
cana-1859	39	3	higher	high	ADJ
cana-1859	39	4	accuracy	accuracy	NOUN
cana-1859	39	5	,	,	PUNCT
cana-1859	39	6	precision	precision	NOUN
cana-1859	39	7	,	,	PUNCT
cana-1859	39	8	recall	recall	NOUN
cana-1859	39	9	,	,	PUNCT
cana-1859	39	10	auc	auc	NOUN
cana-1859	39	11	,	,	PUNCT
cana-1859	39	12	and	and	CCONJ
cana-1859	39	13	specificity	specificity	NOUN
cana-1859	39	14	,	,	PUNCT
cana-1859	39	15	along	along	ADP
cana-1859	39	16	with	with	ADP
cana-1859	39	17	reduced	reduced	ADJ
cana-1859	39	18	computational	computational	ADJ
cana-1859	39	19	delays	delay	NOUN
cana-1859	39	20	.	.	PUNCT
cana-1859	40	1	such	such	ADJ
cana-1859	40	2	enhancements	enhancement	NOUN
cana-1859	40	3	are	be	AUX
cana-1859	40	4	crucial	crucial	ADJ
cana-1859	40	5	for	for	ADP
cana-1859	40	6	applications	application	NOUN
cana-1859	40	7	requiring	require	VERB
cana-1859	40	8	rapid	rapid	ADJ
cana-1859	40	9	and	and	CCONJ
cana-1859	40	10	accurate	accurate	ADJ
cana-1859	40	11	image	image	NOUN
cana-1859	40	12	processing	processing	NOUN
cana-1859	40	13	.	.	PUNCT
cana-1859	41	1	•	•	NUM
cana-1859	41	2	methodological	methodological	ADJ
cana-1859	41	3	advancement	advancement	NOUN
cana-1859	41	4	:	:	PUNCT
cana-1859	41	5	this	this	DET
cana-1859	41	6	research	research	NOUN
cana-1859	41	7	introduces	introduce	VERB
cana-1859	41	8	a	a	DET
cana-1859	41	9	novel	novel	ADJ
cana-1859	41	10	methodology	methodology	NOUN
cana-1859	41	11	for	for	ADP
cana-1859	41	12	optimizing	optimize	VERB
cana-1859	41	13	cnns	cnn	NOUN
cana-1859	41	14	.	.	PUNCT
cana-1859	42	1	the	the	DET
cana-1859	42	2	use	use	NOUN
cana-1859	42	3	of	of	ADP
cana-1859	42	4	vedic	vedic	ADJ
cana-1859	42	5	sutras	sutra	NOUN
cana-1859	42	6	for	for	ADP
cana-1859	42	7	specific	specific	ADJ
cana-1859	42	8	operations	operation	NOUN
cana-1859	42	9	within	within	ADP
cana-1859	42	10	cnns	cnn	NOUN
cana-1859	42	11	,	,	PUNCT
cana-1859	42	12	such	such	ADJ
cana-1859	42	13	as	as	ADP
cana-1859	42	14	convolution	convolution	NOUN
cana-1859	42	15	,	,	PUNCT
cana-1859	42	16	pooling	pooling	NOUN
cana-1859	42	17	,	,	PUNCT
cana-1859	42	18	and	and	CCONJ
cana-1859	42	19	backpropagation	backpropagation	NOUN
cana-1859	42	20	,	,	PUNCT
cana-1859	42	21	represents	represent	VERB
cana-1859	42	22	a	a	DET
cana-1859	42	23	new	new	ADJ
cana-1859	42	24	approach	approach	NOUN
cana-1859	42	25	in	in	ADP
cana-1859	42	26	the	the	DET
cana-1859	42	27	field	field	NOUN
cana-1859	42	28	of	of	ADP
cana-1859	42	29	deep	deep	ADJ
cana-1859	42	30	learning	learning	NOUN
cana-1859	42	31	.	.	PUNCT
cana-1859	43	1	•	•	NUM
cana-1859	43	2	broad	broad	ADJ
cana-1859	43	3	applicability	applicability	NOUN
cana-1859	43	4	:	:	PUNCT
cana-1859	43	5	the	the	DET
cana-1859	43	6	improved	improve	VERB
cana-1859	43	7	cnn	cnn	PROPN
cana-1859	43	8	models	model	NOUN
cana-1859	43	9	have	have	VERB
cana-1859	43	10	potential	potential	ADJ
cana-1859	43	11	applications	application	NOUN
cana-1859	43	12	in	in	ADP
cana-1859	43	13	a	a	DET
cana-1859	43	14	wide	wide	ADJ
cana-1859	43	15	range	range	NOUN
cana-1859	43	16	of	of	ADP
cana-1859	43	17	fields	field	NOUN
cana-1859	43	18	.	.	PUNCT
cana-1859	44	1	from	from	ADP
cana-1859	44	2	medical	medical	ADJ
cana-1859	44	3	diagnostics	diagnostic	NOUN
cana-1859	44	4	,	,	PUNCT
cana-1859	44	5	where	where	SCONJ
cana-1859	44	6	accurate	accurate	ADJ
cana-1859	44	7	and	and	CCONJ
cana-1859	44	8	quick	quick	ADJ
cana-1859	44	9	image	image	NOUN
cana-1859	44	10	analysis	analysis	NOUN
cana-1859	44	11	can	can	AUX
cana-1859	44	12	be	be	AUX
cana-1859	44	13	life	life	NOUN
cana-1859	44	14	-	-	PUNCT
cana-1859	44	15	saving	saving	NOUN
cana-1859	44	16	,	,	PUNCT
cana-1859	44	17	to	to	AUX
cana-1859	44	18	heritage	heritage	VERB
cana-1859	44	19	conservation	conservation	NOUN
cana-1859	44	20	,	,	PUNCT
cana-1859	44	21	where	where	SCONJ
cana-1859	44	22	precise	precise	ADJ
cana-1859	44	23	image	image	NOUN
cana-1859	44	24	classification	classification	NOUN
cana-1859	44	25	can	can	AUX
cana-1859	44	26	aid	aid	VERB
cana-1859	44	27	in	in	ADP
cana-1859	44	28	preserving	preserve	VERB
cana-1859	44	29	cultural	cultural	ADJ
cana-1859	44	30	heritage	heritage	NOUN
cana-1859	44	31	,	,	PUNCT
cana-1859	44	32	the	the	DET
cana-1859	44	33	implications	implication	NOUN
cana-1859	44	34	are	be	AUX
cana-1859	44	35	vast	vast	ADJ
cana-1859	44	36	.	.	PUNCT
cana-1859	45	1	•	•	NUM
cana-1859	45	2	interdisciplinary	interdisciplinary	ADJ
cana-1859	45	3	research	research	NOUN
cana-1859	45	4	pathways	pathway	NOUN
cana-1859	45	5	:	:	PUNCT
cana-1859	45	6	this	this	DET
cana-1859	45	7	work	work	NOUN
cana-1859	45	8	opens	open	VERB
cana-1859	45	9	new	new	ADJ
cana-1859	45	10	avenues	avenue	NOUN
cana-1859	45	11	for	for	ADP
cana-1859	45	12	interdisciplinary	interdisciplinary	ADJ
cana-1859	45	13	research	research	NOUN
cana-1859	45	14	,	,	PUNCT
cana-1859	45	15	combining	combine	VERB
cana-1859	45	16	the	the	DET
cana-1859	45	17	fields	field	NOUN
cana-1859	45	18	of	of	ADP
cana-1859	45	19	ancient	ancient	ADJ
cana-1859	45	20	mathematics	mathematic	NOUN
cana-1859	45	21	,	,	PUNCT
cana-1859	45	22	computer	computer	NOUN
cana-1859	45	23	science	science	NOUN
cana-1859	45	24	,	,	PUNCT
cana-1859	45	25	and	and	CCONJ
cana-1859	45	26	artificial	artificial	ADJ
cana-1859	45	27	intelligence	intelligence	NOUN
cana-1859	45	28	.	.	PUNCT
cana-1859	46	1	it	it	PRON
cana-1859	46	2	encourages	encourage	VERB
cana-1859	46	3	a	a	DET
cana-1859	46	4	cross	cross	ADJ
cana-1859	46	5	-	-	ADJ
cana-1859	46	6	disciplinary	disciplinary	ADJ
cana-1859	46	7	approach	approach	NOUN
cana-1859	46	8	,	,	PUNCT
cana-1859	46	9	emphasizing	emphasize	VERB
cana-1859	46	10	the	the	DET
cana-1859	46	11	value	value	NOUN
cana-1859	46	12	of	of	ADP
cana-1859	46	13	diverse	diverse	ADJ
cana-1859	46	14	knowledge	knowledge	NOUN
cana-1859	46	15	systems	system	NOUN
cana-1859	46	16	in	in	ADP
cana-1859	46	17	advancing	advance	VERB
cana-1859	46	18	technology	technology	NOUN
cana-1859	46	19	.	.	PUNCT
cana-1859	47	1	in	in	ADP
cana-1859	47	2	summary	summary	NOUN
cana-1859	47	3	,	,	PUNCT
cana-1859	47	4	this	this	DET
cana-1859	47	5	study	study	NOUN
cana-1859	47	6	not	not	PART
cana-1859	47	7	only	only	ADV
cana-1859	47	8	contributes	contribute	VERB
cana-1859	47	9	to	to	ADP
cana-1859	47	10	the	the	DET
cana-1859	47	11	technical	technical	ADJ
cana-1859	47	12	advancement	advancement	NOUN
cana-1859	47	13	of	of	ADP
cana-1859	47	14	cnn	cnn	PROPN
cana-1859	47	15	optimization	optimization	NOUN
cana-1859	47	16	but	but	CCONJ
cana-1859	47	17	also	also	ADV
cana-1859	47	18	underscores	underscore	VERB
cana-1859	47	19	the	the	DET
cana-1859	47	20	importance	importance	NOUN
cana-1859	47	21	of	of	ADP
cana-1859	47	22	integrating	integrate	VERB
cana-1859	47	23	diverse	diverse	ADJ
cana-1859	47	24	and	and	CCONJ
cana-1859	47	25	historical	historical	ADJ
cana-1859	47	26	knowledge	knowledge	NOUN
cana-1859	47	27	systems	system	NOUN
cana-1859	47	28	into	into	ADP
cana-1859	47	29	modern	modern	ADJ
cana-1859	47	30	technological	technological	ADJ
cana-1859	47	31	innovations	innovation	NOUN
cana-1859	47	32	.	.	PUNCT
cana-1859	48	1	it	it	PRON
cana-1859	48	2	exemplifies	exemplify	VERB
cana-1859	48	3	how	how	SCONJ
cana-1859	48	4	interdisciplinary	interdisciplinary	ADJ
cana-1859	48	5	research	research	NOUN
cana-1859	48	6	can	can	AUX
cana-1859	48	7	lead	lead	VERB
cana-1859	48	8	to	to	ADP
cana-1859	48	9	significant	significant	ADJ
cana-1859	48	10	breakthroughs	breakthrough	NOUN
cana-1859	48	11	,	,	PUNCT
cana-1859	48	12	expanding	expand	VERB
cana-1859	48	13	the	the	DET
cana-1859	48	14	horizons	horizon	NOUN
cana-1859	48	15	of	of	ADP
cana-1859	48	16	what	what	PRON
cana-1859	48	17	is	be	AUX
cana-1859	48	18	possible	possible	ADJ
cana-1859	48	19	in	in	ADP
cana-1859	48	20	the	the	DET
cana-1859	48	21	realm	realm	NOUN
cana-1859	48	22	of	of	ADP
cana-1859	48	23	artificial	artificial	ADJ
cana-1859	48	24	intelligence	intelligence	NOUN
cana-1859	48	25	process	process	NOUN
cana-1859	48	26	.	.	PUNCT
cana-1859	49	1	communications	communication	NOUN
cana-1859	49	2	on	on	ADP
cana-1859	49	3	applied	apply	VERB
cana-1859	49	4	nonlinear	nonlinear	ADJ
cana-1859	49	5	analysis	analysis	NOUN
cana-1859	49	6	issn	issn	NOUN
cana-1859	49	7	:	:	PUNCT
cana-1859	49	8	1074	1074	NUM
cana-1859	49	9	-	-	PUNCT
cana-1859	49	10	133x	133x	NUM
cana-1859	49	11	vol	vol	NOUN
cana-1859	49	12	32	32	NUM
cana-1859	49	13	no	no	NOUN
cana-1859	49	14	.	.	NOUN
cana-1859	49	15	2	2	NUM
cana-1859	49	16	(	(	PUNCT
cana-1859	49	17	2025	2025	NUM
cana-1859	49	18	)	)	PUNCT
cana-1859	49	19	641	641	NUM
cana-1859	50	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	50	2	2	2	NUM
cana-1859	50	3	.	.	X
cana-1859	50	4	review	review	NOUN
cana-1859	50	5	of	of	ADP
cana-1859	50	6	existing	exist	VERB
cana-1859	50	7	models	model	NOUN
cana-1859	50	8	used	use	VERB
cana-1859	50	9	for	for	ADP
cana-1859	50	10	optimization	optimization	NOUN
cana-1859	50	11	of	of	ADP
cana-1859	50	12	cnns	cnn	NOUN
cana-1859	50	13	the	the	DET
cana-1859	50	14	recent	recent	ADJ
cana-1859	50	15	advancements	advancement	NOUN
cana-1859	50	16	in	in	ADP
cana-1859	50	17	convolutional	convolutional	ADJ
cana-1859	50	18	neural	neural	ADJ
cana-1859	50	19	networks	network	NOUN
cana-1859	50	20	(	(	PUNCT
cana-1859	50	21	cnns	cnns	PROPN
cana-1859	50	22	)	)	PUNCT
cana-1859	50	23	have	have	AUX
cana-1859	50	24	led	lead	VERB
cana-1859	50	25	to	to	ADP
cana-1859	50	26	significant	significant	ADJ
cana-1859	50	27	progress	progress	NOUN
cana-1859	50	28	across	across	ADP
cana-1859	50	29	various	various	ADJ
cana-1859	50	30	fields	field	NOUN
cana-1859	50	31	,	,	PUNCT
cana-1859	50	32	as	as	SCONJ
cana-1859	50	33	evidenced	evidence	VERB
cana-1859	50	34	by	by	ADP
cana-1859	50	35	the	the	DET
cana-1859	50	36	array	array	NOUN
cana-1859	50	37	of	of	ADP
cana-1859	50	38	studies	study	NOUN
cana-1859	50	39	conducted	conduct	VERB
cana-1859	50	40	in	in	ADP
cana-1859	50	41	2023	2023	NUM
cana-1859	50	42	.	.	PUNCT
cana-1859	51	1	this	this	DET
cana-1859	51	2	literature	literature	NOUN
cana-1859	51	3	review	review	NOUN
cana-1859	51	4	examines	examine	VERB
cana-1859	51	5	these	these	DET
cana-1859	51	6	developments	development	NOUN
cana-1859	51	7	,	,	PUNCT
cana-1859	51	8	focusing	focus	VERB
cana-1859	51	9	on	on	ADP
cana-1859	51	10	the	the	DET
cana-1859	51	11	diverse	diverse	ADJ
cana-1859	51	12	applications	application	NOUN
cana-1859	51	13	and	and	CCONJ
cana-1859	51	14	innovations	innovation	NOUN
cana-1859	51	15	of	of	ADP
cana-1859	51	16	cnns	cnns	PROPN
cana-1859	51	17	.	.	PUNCT
cana-1859	52	1	recognition	recognition	NOUN
cana-1859	52	2	of	of	ADP
cana-1859	52	3	stone	stone	NOUN
cana-1859	52	4	carved	carve	VERB
cana-1859	52	5	calligraphy	calligraphy	NOUN
cana-1859	52	6	characters	character	NOUN
cana-1859	52	7	:	:	PUNCT
cana-1859	52	8	huang	huang	PROPN
cana-1859	52	9	et	et	PROPN
cana-1859	52	10	al	al	PROPN
cana-1859	52	11	.	.	PUNCT
cana-1859	53	1	[	[	X
cana-1859	53	2	1	1	X
cana-1859	53	3	]	]	PUNCT
cana-1859	53	4	developed	develop	VERB
cana-1859	53	5	a	a	DET
cana-1859	53	6	method	method	NOUN
cana-1859	53	7	utilizing	utilize	VERB
cana-1859	53	8	cnns	cnn	NOUN
cana-1859	53	9	for	for	ADP
cana-1859	53	10	recognizing	recognize	VERB
cana-1859	53	11	stone	stone	NOUN
cana-1859	53	12	carved	carve	VERB
cana-1859	53	13	calligraphy	calligraphy	NOUN
cana-1859	53	14	characters	character	NOUN
cana-1859	53	15	.	.	PUNCT
cana-1859	54	1	this	this	DET
cana-1859	54	2	work	work	NOUN
cana-1859	54	3	highlights	highlight	VERB
cana-1859	54	4	the	the	DET
cana-1859	54	5	adaptability	adaptability	NOUN
cana-1859	54	6	of	of	ADP
cana-1859	54	7	cnns	cnn	NOUN
cana-1859	54	8	in	in	ADP
cana-1859	54	9	processing	processing	NOUN
cana-1859	54	10	and	and	CCONJ
cana-1859	54	11	recognizing	recognize	VERB
cana-1859	54	12	complex	complex	ADJ
cana-1859	54	13	patterns	pattern	NOUN
cana-1859	54	14	in	in	ADP
cana-1859	54	15	historical	historical	ADJ
cana-1859	54	16	and	and	CCONJ
cana-1859	54	17	cultural	cultural	ADJ
cana-1859	54	18	contexts	contexts	NOUN
cana-1859	54	19	.	.	PUNCT
cana-1859	55	1	microorganism	microorganism	NOUN
cana-1859	55	2	image	image	NOUN
cana-1859	55	3	analysis	analysis	NOUN
cana-1859	55	4	:	:	PUNCT
cana-1859	55	5	zhang	zhang	PROPN
cana-1859	55	6	et	et	PROPN
cana-1859	55	7	al	al	PROPN
cana-1859	55	8	.	.	PUNCT
cana-1859	56	1	[	[	X
cana-1859	56	2	2	2	NUM
cana-1859	56	3	]	]	PUNCT
cana-1859	56	4	provided	provide	VERB
cana-1859	56	5	a	a	DET
cana-1859	56	6	comprehensive	comprehensive	ADJ
cana-1859	56	7	review	review	NOUN
cana-1859	56	8	of	of	ADP
cana-1859	56	9	the	the	DET
cana-1859	56	10	application	application	NOUN
cana-1859	56	11	of	of	ADP
cana-1859	56	12	artificial	artificial	ADJ
cana-1859	56	13	neural	neural	ADJ
cana-1859	56	14	networks	network	NOUN
cana-1859	56	15	,	,	PUNCT
cana-1859	56	16	including	include	VERB
cana-1859	56	17	cnns	cnn	NOUN
cana-1859	56	18	,	,	PUNCT
cana-1859	56	19	in	in	ADP
cana-1859	56	20	microorganism	microorganism	NOUN
cana-1859	56	21	image	image	NOUN
cana-1859	56	22	analysis	analysis	NOUN
cana-1859	56	23	.	.	PUNCT
cana-1859	57	1	their	their	PRON
cana-1859	57	2	work	work	NOUN
cana-1859	57	3	emphasizes	emphasize	VERB
cana-1859	57	4	the	the	DET
cana-1859	57	5	potency	potency	NOUN
cana-1859	57	6	of	of	ADP
cana-1859	57	7	cnns	cnn	NOUN
cana-1859	57	8	in	in	ADP
cana-1859	57	9	biomedical	biomedical	ADJ
cana-1859	57	10	imaging	imaging	NOUN
cana-1859	57	11	and	and	CCONJ
cana-1859	57	12	analysis	analysis	NOUN
cana-1859	57	13	.	.	PUNCT
cana-1859	58	1	medical	medical	ADJ
cana-1859	58	2	imaging	imaging	NOUN
cana-1859	58	3	and	and	CCONJ
cana-1859	58	4	diagnosis	diagnosis	NOUN
cana-1859	58	5	:	:	PUNCT
cana-1859	58	6	the	the	DET
cana-1859	58	7	application	application	NOUN
cana-1859	58	8	of	of	ADP
cana-1859	58	9	cnns	cnn	NOUN
cana-1859	58	10	in	in	ADP
cana-1859	58	11	medical	medical	ADJ
cana-1859	58	12	imaging	imaging	NOUN
cana-1859	58	13	is	be	AUX
cana-1859	58	14	extensive	extensive	ADJ
cana-1859	58	15	.	.	PUNCT
cana-1859	59	1	kulkarni	kulkarni	PROPN
cana-1859	59	2	et	et	PROPN
cana-1859	59	3	al	al	PROPN
cana-1859	59	4	.	.	PUNCT
cana-1859	60	1	[	[	X
cana-1859	60	2	3	3	NUM
cana-1859	60	3	]	]	PUNCT
cana-1859	60	4	implemented	implement	VERB
cana-1859	60	5	a	a	DET
cana-1859	60	6	classical	classical	ADJ
cana-1859	60	7	-	-	PUNCT
cana-1859	60	8	quantum	quantum	ADJ
cana-1859	60	9	cnn	cnn	NOUN
cana-1859	60	10	for	for	ADP
cana-1859	60	11	pneumonia	pneumonia	NOUN
cana-1859	60	12	detection	detection	NOUN
cana-1859	60	13	from	from	ADP
cana-1859	60	14	chest	chest	NOUN
cana-1859	60	15	radiographs	radiograph	NOUN
cana-1859	60	16	,	,	PUNCT
cana-1859	60	17	while	while	SCONJ
cana-1859	60	18	mann	mann	PROPN
cana-1859	60	19	et	et	PROPN
cana-1859	60	20	al	al	PROPN
cana-1859	60	21	.	.	PUNCT
cana-1859	61	1	[	[	X
cana-1859	61	2	16	16	NUM
cana-1859	61	3	]	]	PUNCT
cana-1859	61	4	developed	develop	VERB
cana-1859	61	5	a	a	DET
cana-1859	61	6	hybrid	hybrid	ADJ
cana-1859	61	7	deep	deep	ADJ
cana-1859	61	8	cnn	cnn	PROPN
cana-1859	61	9	model	model	NOUN
cana-1859	61	10	for	for	ADP
cana-1859	61	11	improved	improved	ADJ
cana-1859	61	12	pneumonia	pneumonia	NOUN
cana-1859	61	13	diagnosis	diagnosis	NOUN
cana-1859	61	14	.	.	PUNCT
cana-1859	62	1	additionally	additionally	ADV
cana-1859	62	2	,	,	PUNCT
cana-1859	62	3	marin	marin	NOUN
cana-1859	62	4	-	-	PUNCT
cana-1859	62	5	santos	santos	NOUN
cana-1859	62	6	et	et	NOUN
cana-1859	62	7	al	al	PROPN
cana-1859	62	8	.	.	PUNCT
cana-1859	63	1	[	[	X
cana-1859	63	2	8	8	NUM
cana-1859	63	3	]	]	PUNCT
cana-1859	63	4	utilized	utilize	VERB
cana-1859	63	5	a	a	DET
cana-1859	63	6	deep	deep	ADJ
cana-1859	63	7	cnn	cnn	NOUN
cana-1859	63	8	for	for	ADP
cana-1859	63	9	detecting	detect	VERB
cana-1859	63	10	crohn	crohn	NOUN
cana-1859	63	11	's	's	PART
cana-1859	63	12	disease	disease	NOUN
cana-1859	63	13	in	in	ADP
cana-1859	63	14	endoscopic	endoscopic	ADJ
cana-1859	63	15	images	image	NOUN
cana-1859	63	16	.	.	PUNCT
cana-1859	64	1	these	these	DET
cana-1859	64	2	studies	study	NOUN
cana-1859	64	3	demonstrate	demonstrate	VERB
cana-1859	64	4	the	the	DET
cana-1859	64	5	effectiveness	effectiveness	NOUN
cana-1859	64	6	of	of	ADP
cana-1859	64	7	cnns	cnn	NOUN
cana-1859	64	8	in	in	ADP
cana-1859	64	9	enhancing	enhance	VERB
cana-1859	64	10	diagnostic	diagnostic	ADJ
cana-1859	64	11	accuracy	accuracy	NOUN
cana-1859	64	12	in	in	ADP
cana-1859	64	13	healthcare	healthcare	PROPN
cana-1859	64	14	.	.	PUNCT
cana-1859	65	1	agricultural	agricultural	ADJ
cana-1859	65	2	applications	application	NOUN
cana-1859	65	3	:	:	PUNCT
cana-1859	65	4	in	in	ADP
cana-1859	65	5	agriculture	agriculture	NOUN
cana-1859	65	6	,	,	PUNCT
cana-1859	65	7	stephen	stephen	PROPN
cana-1859	65	8	et	et	PROPN
cana-1859	65	9	al	al	PROPN
cana-1859	65	10	.	.	PUNCT
cana-1859	66	1	[	[	X
cana-1859	66	2	4	4	X
cana-1859	66	3	]	]	PUNCT
cana-1859	66	4	proposed	propose	VERB
cana-1859	66	5	an	an	DET
cana-1859	66	6	optimal	optimal	ADJ
cana-1859	66	7	deep	deep	ADJ
cana-1859	66	8	generative	generative	ADJ
cana-1859	66	9	adversarial	adversarial	ADJ
cana-1859	66	10	network	network	NOUN
cana-1859	66	11	combined	combine	VERB
cana-1859	66	12	with	with	ADP
cana-1859	66	13	cnn	cnn	PROPN
cana-1859	66	14	for	for	ADP
cana-1859	66	15	predicting	predict	VERB
cana-1859	66	16	rice	rice	NOUN
cana-1859	66	17	leaf	leaf	NOUN
cana-1859	66	18	diseases	disease	NOUN
cana-1859	66	19	,	,	PUNCT
cana-1859	66	20	showing	show	VERB
cana-1859	66	21	the	the	DET
cana-1859	66	22	potential	potential	NOUN
cana-1859	66	23	of	of	ADP
cana-1859	66	24	cnns	cnn	NOUN
cana-1859	66	25	in	in	ADP
cana-1859	66	26	agricultural	agricultural	ADJ
cana-1859	66	27	disease	disease	NOUN
cana-1859	66	28	management	management	NOUN
cana-1859	66	29	.	.	PUNCT
cana-1859	67	1	cross	cross	ADJ
cana-1859	67	2	-	-	ADJ
cana-1859	67	3	linguistic	linguistic	ADJ
cana-1859	67	4	entity	entity	NOUN
cana-1859	67	5	alignment	alignment	NOUN
cana-1859	67	6	:	:	PUNCT
cana-1859	67	7	zhao	zhao	PROPN
cana-1859	67	8	et	et	PROPN
cana-1859	67	9	al	al	PROPN
cana-1859	67	10	.	.	PUNCT
cana-1859	68	1	[	[	X
cana-1859	68	2	5	5	NUM
cana-1859	68	3	]	]	PUNCT
cana-1859	68	4	explored	explore	VERB
cana-1859	68	5	a	a	DET
cana-1859	68	6	cross	cross	ADJ
cana-1859	68	7	-	-	ADJ
cana-1859	68	8	linguistic	linguistic	ADJ
cana-1859	68	9	entity	entity	NOUN
cana-1859	68	10	alignment	alignment	NOUN
cana-1859	68	11	method	method	NOUN
cana-1859	68	12	using	use	VERB
cana-1859	68	13	a	a	DET
cana-1859	68	14	graph	graph	NOUN
cana-1859	68	15	cnn	cnn	NOUN
cana-1859	68	16	and	and	CCONJ
cana-1859	68	17	graph	graph	NOUN
cana-1859	68	18	attention	attention	NOUN
cana-1859	68	19	network	network	NOUN
cana-1859	68	20	,	,	PUNCT
cana-1859	68	21	underscoring	underscore	VERB
cana-1859	68	22	cnns	cnn	NOUN
cana-1859	68	23	'	'	PART
cana-1859	68	24	capability	capability	NOUN
cana-1859	68	25	in	in	ADP
cana-1859	68	26	handling	handle	VERB
cana-1859	68	27	complex	complex	ADJ
cana-1859	68	28	linguistic	linguistic	ADJ
cana-1859	68	29	data	datum	NOUN
cana-1859	68	30	.	.	PUNCT
cana-1859	69	1	innovations	innovation	NOUN
cana-1859	69	2	in	in	ADP
cana-1859	69	3	cnn	cnn	PROPN
cana-1859	69	4	architecture	architecture	NOUN
cana-1859	69	5	:	:	PUNCT
cana-1859	69	6	zhao	zhao	PROPN
cana-1859	69	7	et	et	PROPN
cana-1859	69	8	al	al	PROPN
cana-1859	69	9	.	.	PUNCT
cana-1859	70	1	[	[	X
cana-1859	70	2	6	6	NUM
cana-1859	70	3	]	]	PUNCT
cana-1859	70	4	introduced	introduce	VERB
cana-1859	70	5	edense	edense	NOUN
cana-1859	70	6	,	,	PUNCT
cana-1859	70	7	a	a	DET
cana-1859	70	8	cnn	cnn	NOUN
cana-1859	70	9	with	with	ADP
cana-1859	70	10	elm	elm	NOUN
cana-1859	70	11	-	-	PUNCT
cana-1859	70	12	based	base	VERB
cana-1859	70	13	dense	dense	ADJ
cana-1859	70	14	connections	connection	NOUN
cana-1859	70	15	,	,	PUNCT
cana-1859	70	16	indicating	indicate	VERB
cana-1859	70	17	ongoing	ongoing	ADJ
cana-1859	70	18	innovations	innovation	NOUN
cana-1859	70	19	in	in	ADP
cana-1859	70	20	cnn	cnn	PROPN
cana-1859	70	21	architectures	architecture	NOUN
cana-1859	70	22	for	for	ADP
cana-1859	70	23	enhanced	enhanced	ADJ
cana-1859	70	24	performance	performance	NOUN
cana-1859	70	25	.	.	PUNCT
cana-1859	71	1	image	image	NOUN
cana-1859	71	2	segmentation	segmentation	NOUN
cana-1859	71	3	:	:	PUNCT
cana-1859	71	4	askari	askari	PROPN
cana-1859	71	5	and	and	CCONJ
cana-1859	71	6	motamed	motame	VERB
cana-1859	72	1	[	[	X
cana-1859	72	2	7	7	NUM
cana-1859	72	3	]	]	PUNCT
cana-1859	72	4	evaluated	evaluated	ADJ
cana-1859	72	5	image	image	NOUN
cana-1859	72	6	segmentation	segmentation	NOUN
cana-1859	72	7	algorithms	algorithm	NOUN
cana-1859	72	8	based	base	VERB
cana-1859	72	9	on	on	ADP
cana-1859	72	10	fuzzy	fuzzy	ADJ
cana-1859	72	11	cnn	cnn	PROPN
cana-1859	72	12	,	,	PUNCT
cana-1859	72	13	highlighting	highlight	VERB
cana-1859	72	14	cnns	cnns	NOUN
cana-1859	72	15	'	'	PART
cana-1859	72	16	role	role	NOUN
cana-1859	72	17	in	in	ADP
cana-1859	72	18	improving	improve	VERB
cana-1859	72	19	image	image	NOUN
cana-1859	72	20	segmentation	segmentation	NOUN
cana-1859	72	21	techniques	technique	NOUN
cana-1859	72	22	.	.	PUNCT
cana-1859	73	1	watermarking	watermarking	NOUN
cana-1859	73	2	and	and	CCONJ
cana-1859	73	3	security	security	NOUN
cana-1859	73	4	:	:	PUNCT
cana-1859	73	5	tavakoli	tavakoli	PROPN
cana-1859	73	6	et	et	PROPN
cana-1859	73	7	al	al	PROPN
cana-1859	73	8	.	.	PUNCT
cana-1859	74	1	[	[	X
cana-1859	74	2	9	9	NUM
cana-1859	74	3	]	]	PUNCT
cana-1859	74	4	utilized	utilize	VERB
cana-1859	74	5	a	a	DET
cana-1859	74	6	cnn	cnn	PROPN
cana-1859	74	7	-	-	PUNCT
cana-1859	74	8	based	base	VERB
cana-1859	74	9	image	image	NOUN
cana-1859	74	10	watermarking	watermarking	NOUN
cana-1859	74	11	using	use	VERB
cana-1859	74	12	discrete	discrete	ADJ
cana-1859	74	13	wavelet	wavelet	NOUN
cana-1859	74	14	transform	transform	NOUN
cana-1859	74	15	,	,	PUNCT
cana-1859	74	16	showcasing	showcase	VERB
cana-1859	74	17	cnns	cnn	NOUN
cana-1859	74	18	'	'	PART
cana-1859	74	19	applicability	applicability	NOUN
cana-1859	74	20	in	in	ADP
cana-1859	74	21	digital	digital	ADJ
cana-1859	74	22	security	security	NOUN
cana-1859	74	23	.	.	PUNCT
cana-1859	75	1	head	head	NOUN
cana-1859	75	2	detection	detection	NOUN
cana-1859	75	3	and	and	CCONJ
cana-1859	75	4	pose	pose	NOUN
cana-1859	75	5	estimation	estimation	NOUN
cana-1859	75	6	:	:	PUNCT
cana-1859	75	7	wang	wang	PROPN
cana-1859	75	8	et	et	PROPN
cana-1859	75	9	al	al	PROPN
cana-1859	75	10	.	.	PUNCT
cana-1859	76	1	[	[	X
cana-1859	76	2	10	10	NUM
cana-1859	76	3	]	]	PUNCT
cana-1859	76	4	developed	develop	VERB
cana-1859	76	5	a	a	DET
cana-1859	76	6	novel	novel	ADJ
cana-1859	76	7	cnn	cnn	NOUN
cana-1859	76	8	for	for	ADP
cana-1859	76	9	head	head	NOUN
cana-1859	76	10	detection	detection	NOUN
cana-1859	76	11	and	and	CCONJ
cana-1859	76	12	pose	pose	NOUN
cana-1859	76	13	estimation	estimation	NOUN
cana-1859	76	14	in	in	ADP
cana-1859	76	15	complex	complex	ADJ
cana-1859	76	16	environments	environment	NOUN
cana-1859	76	17	,	,	PUNCT
cana-1859	76	18	demonstrating	demonstrate	VERB
cana-1859	76	19	cnns	cnn	NOUN
cana-1859	76	20	'	'	PART
cana-1859	76	21	utility	utility	NOUN
cana-1859	76	22	in	in	ADP
cana-1859	76	23	computer	computer	NOUN
cana-1859	76	24	vision	vision	NOUN
cana-1859	76	25	and	and	CCONJ
cana-1859	76	26	surveillance	surveillance	NOUN
cana-1859	76	27	systems	system	NOUN
cana-1859	76	28	.	.	PUNCT
cana-1859	77	1	communications	communication	NOUN
cana-1859	77	2	on	on	ADP
cana-1859	77	3	applied	apply	VERB
cana-1859	77	4	nonlinear	nonlinear	ADJ
cana-1859	77	5	analysis	analysis	NOUN
cana-1859	77	6	issn	issn	NOUN
cana-1859	77	7	:	:	PUNCT
cana-1859	77	8	1074	1074	NUM
cana-1859	77	9	-	-	PUNCT
cana-1859	77	10	133x	133x	NUM
cana-1859	77	11	vol	vol	NOUN
cana-1859	77	12	32	32	NUM
cana-1859	77	13	no	no	NOUN
cana-1859	77	14	.	.	NOUN
cana-1859	77	15	2	2	NUM
cana-1859	77	16	(	(	PUNCT
cana-1859	77	17	2025	2025	NUM
cana-1859	77	18	)	)	PUNCT
cana-1859	77	19	642	642	NUM
cana-1859	77	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	77	21	spectral	spectral	ADJ
cana-1859	77	22	efficiency	efficiency	NOUN
cana-1859	77	23	optimization	optimization	NOUN
cana-1859	77	24	in	in	ADP
cana-1859	77	25	mimo	mimo	PROPN
cana-1859	77	26	systems	systems	PROPN
cana-1859	77	27	:	:	PUNCT
cana-1859	77	28	sun	sun	PROPN
cana-1859	77	29	et	et	PROPN
cana-1859	77	30	al	al	PROPN
cana-1859	77	31	.	.	PUNCT
cana-1859	78	1	[	[	X
cana-1859	78	2	11	11	NUM
cana-1859	78	3	]	]	PUNCT
cana-1859	78	4	implemented	implement	VERB
cana-1859	78	5	an	an	DET
cana-1859	78	6	attention	attention	NOUN
cana-1859	78	7	-	-	PUNCT
cana-1859	78	8	based	base	VERB
cana-1859	78	9	deep	deep	ADJ
cana-1859	78	10	cnn	cnn	PROPN
cana-1859	78	11	for	for	ADP
cana-1859	78	12	spectral	spectral	ADJ
cana-1859	78	13	efficiency	efficiency	NOUN
cana-1859	78	14	optimization	optimization	NOUN
cana-1859	78	15	in	in	ADP
cana-1859	78	16	mimo	mimo	PROPN
cana-1859	78	17	systems	system	NOUN
cana-1859	78	18	,	,	PUNCT
cana-1859	78	19	indicating	indicate	VERB
cana-1859	78	20	cnns	cnn	NOUN
cana-1859	78	21	'	'	PART
cana-1859	78	22	potential	potential	NOUN
cana-1859	78	23	in	in	ADP
cana-1859	78	24	telecommunications	telecommunication	NOUN
cana-1859	78	25	.	.	PUNCT
cana-1859	79	1	wireless	wireless	ADJ
cana-1859	79	2	sensor	sensor	NOUN
cana-1859	79	3	networks	network	NOUN
cana-1859	79	4	:	:	PUNCT
cana-1859	79	5	subramani	subramani	PROPN
cana-1859	79	6	and	and	CCONJ
cana-1859	79	7	selvi	selvi	PROPN
cana-1859	80	1	[	[	X
cana-1859	80	2	12	12	NUM
cana-1859	80	3	]	]	PUNCT
cana-1859	80	4	employed	employ	VERB
cana-1859	80	5	a	a	DET
cana-1859	80	6	deep	deep	ADJ
cana-1859	80	7	fuzzy	fuzzy	ADJ
cana-1859	80	8	cnn	cnn	PROPN
cana-1859	80	9	for	for	ADP
cana-1859	80	10	intelligent	intelligent	ADJ
cana-1859	80	11	intrusion	intrusion	NOUN
cana-1859	80	12	detection	detection	NOUN
cana-1859	80	13	systems	system	NOUN
cana-1859	80	14	in	in	ADP
cana-1859	80	15	wireless	wireless	ADJ
cana-1859	80	16	sensor	sensor	NOUN
cana-1859	80	17	networks	network	NOUN
cana-1859	80	18	,	,	PUNCT
cana-1859	80	19	illustrating	illustrate	VERB
cana-1859	80	20	cnns	cnns	PROPN
cana-1859	80	21	'	'	PART
cana-1859	80	22	effectiveness	effectiveness	NOUN
cana-1859	80	23	in	in	ADP
cana-1859	80	24	network	network	NOUN
cana-1859	80	25	security	security	NOUN
cana-1859	80	26	.	.	PUNCT
cana-1859	81	1	storm	storm	NOUN
cana-1859	81	2	surge	surge	NOUN
cana-1859	81	3	predictions	prediction	NOUN
cana-1859	81	4	:	:	PUNCT
cana-1859	81	5	adeli	adeli	PROPN
cana-1859	81	6	et	et	PROPN
cana-1859	81	7	al	al	PROPN
cana-1859	81	8	.	.	PUNCT
cana-1859	82	1	[	[	X
cana-1859	82	2	13	13	NUM
cana-1859	82	3	,	,	PUNCT
cana-1859	82	4	14	14	NUM
cana-1859	82	5	,	,	PUNCT
cana-1859	82	6	15	15	NUM
cana-1859	82	7	]	]	PUNCT
cana-1859	82	8	proposed	propose	VERB
cana-1859	82	9	an	an	DET
cana-1859	82	10	advanced	advanced	ADJ
cana-1859	82	11	spatio	spatio	NOUN
cana-1859	82	12	-	-	PUNCT
cana-1859	82	13	temporal	temporal	ADJ
cana-1859	82	14	convolutional	convolutional	ADJ
cana-1859	82	15	recurrent	recurrent	ADJ
cana-1859	82	16	neural	neural	ADJ
cana-1859	82	17	network	network	NOUN
cana-1859	82	18	for	for	ADP
cana-1859	82	19	storm	storm	NOUN
cana-1859	82	20	surge	surge	NOUN
cana-1859	82	21	predictions	prediction	NOUN
cana-1859	82	22	,	,	PUNCT
cana-1859	82	23	a	a	DET
cana-1859	82	24	novel	novel	ADJ
cana-1859	82	25	application	application	NOUN
cana-1859	82	26	of	of	ADP
cana-1859	82	27	cnns	cnn	NOUN
cana-1859	82	28	in	in	ADP
cana-1859	82	29	environmental	environmental	ADJ
cana-1859	82	30	modeling	modeling	NOUN
cana-1859	82	31	[	[	X
cana-1859	82	32	16	16	NUM
cana-1859	82	33	,	,	PUNCT
cana-1859	82	34	17	17	NUM
cana-1859	82	35	]	]	PUNCT
cana-1859	82	36	.	.	PUNCT
cana-1859	83	1	image	image	NOUN
cana-1859	83	2	annotation	annotation	NOUN
cana-1859	83	3	:	:	PUNCT
cana-1859	83	4	wang	wang	PROPN
cana-1859	83	5	et	et	PROPN
cana-1859	83	6	al	al	PROPN
cana-1859	83	7	.	.	PUNCT
cana-1859	84	1	[	[	X
cana-1859	84	2	18	18	NUM
cana-1859	84	3	,	,	PUNCT
cana-1859	84	4	19	19	NUM
cana-1859	84	5	,	,	PUNCT
cana-1859	84	6	20	20	NUM
cana-1859	84	7	]	]	PUNCT
cana-1859	84	8	presented	present	VERB
cana-1859	84	9	a	a	DET
cana-1859	84	10	feature	feature	NOUN
cana-1859	84	11	fusion	fusion	NOUN
cana-1859	84	12	-	-	PUNCT
cana-1859	84	13	based	base	VERB
cana-1859	84	14	parallel	parallel	ADJ
cana-1859	84	15	graph	graph	NOUN
cana-1859	84	16	cnn	cnn	PROPN
cana-1859	84	17	for	for	ADP
cana-1859	84	18	image	image	NOUN
cana-1859	84	19	annotation	annotation	NOUN
cana-1859	84	20	,	,	PUNCT
cana-1859	84	21	further	far	ADV
cana-1859	84	22	expanding	expand	VERB
cana-1859	84	23	cnns	cnn	NOUN
cana-1859	84	24	'	'	PART
cana-1859	84	25	application	application	NOUN
cana-1859	84	26	in	in	ADP
cana-1859	84	27	digital	digital	ADJ
cana-1859	84	28	media	medium	NOUN
cana-1859	84	29	.	.	PUNCT
cana-1859	85	1	satellite	satellite	NOUN
cana-1859	85	2	image	image	NOUN
cana-1859	85	3	classification	classification	NOUN
cana-1859	85	4	for	for	ADP
cana-1859	85	5	ecology	ecology	NOUN
cana-1859	85	6	management	management	NOUN
cana-1859	85	7	:	:	PUNCT
cana-1859	85	8	özbay	özbay	NOUN
cana-1859	85	9	and	and	CCONJ
cana-1859	85	10	yıldırım	yıldırım	PRON
cana-1859	86	1	[	[	X
cana-1859	86	2	21	21	NUM
cana-1859	86	3	,	,	PUNCT
cana-1859	86	4	22	22	NUM
cana-1859	86	5	,	,	PUNCT
cana-1859	86	6	23	23	NUM
cana-1859	86	7	]	]	PUNCT
cana-1859	86	8	classified	classified	ADJ
cana-1859	86	9	satellite	satellite	NOUN
cana-1859	86	10	images	image	NOUN
cana-1859	86	11	using	use	VERB
cana-1859	86	12	deep	deep	ADJ
cana-1859	86	13	features	feature	NOUN
cana-1859	86	14	from	from	ADP
cana-1859	86	15	cnn	cnn	PROPN
cana-1859	86	16	models	model	NOUN
cana-1859	86	17	,	,	PUNCT
cana-1859	86	18	demonstrating	demonstrate	VERB
cana-1859	86	19	cnns	cnn	NOUN
cana-1859	86	20	'	'	PART
cana-1859	86	21	utility	utility	NOUN
cana-1859	86	22	in	in	ADP
cana-1859	86	23	environmental	environmental	ADJ
cana-1859	86	24	monitoring	monitoring	NOUN
cana-1859	86	25	.	.	PUNCT
cana-1859	87	1	audio	audio	ADJ
cana-1859	87	2	signal	signal	NOUN
cana-1859	87	3	processing	processing	NOUN
cana-1859	87	4	:	:	PUNCT
cana-1859	87	5	presannakumar	presannakumar	PROPN
cana-1859	87	6	and	and	CCONJ
cana-1859	87	7	mohamed	mohame	VERB
cana-1859	88	1	[	[	X
cana-1859	88	2	23	23	NUM
cana-1859	88	3	,	,	PUNCT
cana-1859	88	4	24	24	NUM
cana-1859	88	5	,	,	PUNCT
cana-1859	88	6	25	25	NUM
cana-1859	88	7	]	]	PUNCT
cana-1859	88	8	explored	explore	VERB
cana-1859	88	9	source	source	NOUN
cana-1859	88	10	identification	identification	NOUN
cana-1859	88	11	of	of	ADP
cana-1859	88	12	weak	weak	ADJ
cana-1859	88	13	audio	audio	NOUN
cana-1859	88	14	signals	signal	NOUN
cana-1859	88	15	using	use	VERB
cana-1859	88	16	an	an	DET
cana-1859	88	17	attention	attention	NOUN
cana-1859	88	18	-	-	PUNCT
cana-1859	88	19	based	base	VERB
cana-1859	88	20	cnn	cnn	PROPN
cana-1859	88	21	,	,	PUNCT
cana-1859	88	22	highlighting	highlight	VERB
cana-1859	88	23	the	the	DET
cana-1859	88	24	versatility	versatility	NOUN
cana-1859	88	25	of	of	ADP
cana-1859	88	26	cnns	cnns	PROPN
cana-1859	88	27	beyond	beyond	ADP
cana-1859	88	28	visual	visual	ADJ
cana-1859	88	29	data	datum	NOUN
cana-1859	88	30	.	.	PUNCT
cana-1859	89	1	this	this	DET
cana-1859	89	2	literature	literature	NOUN
cana-1859	89	3	review	review	NOUN
cana-1859	89	4	reveals	reveal	VERB
cana-1859	89	5	the	the	DET
cana-1859	89	6	wide	wide	ADV
cana-1859	89	7	-	-	PUNCT
cana-1859	89	8	ranging	range	VERB
cana-1859	89	9	applications	application	NOUN
cana-1859	89	10	of	of	ADP
cana-1859	89	11	cnns	cnn	NOUN
cana-1859	89	12	,	,	PUNCT
cana-1859	89	13	from	from	ADP
cana-1859	89	14	medical	medical	ADJ
cana-1859	89	15	imaging	imaging	NOUN
cana-1859	89	16	,	,	PUNCT
cana-1859	89	17	agricultural	agricultural	ADJ
cana-1859	89	18	management	management	NOUN
cana-1859	89	19	,	,	PUNCT
cana-1859	89	20	linguistic	linguistic	ADJ
cana-1859	89	21	data	datum	NOUN
cana-1859	89	22	processing	processing	NOUN
cana-1859	89	23	,	,	PUNCT
cana-1859	89	24	to	to	ADP
cana-1859	89	25	environmental	environmental	ADJ
cana-1859	89	26	monitoring	monitoring	NOUN
cana-1859	89	27	and	and	CCONJ
cana-1859	89	28	network	network	NOUN
cana-1859	89	29	security	security	NOUN
cana-1859	89	30	.	.	PUNCT
cana-1859	90	1	the	the	DET
cana-1859	90	2	continuous	continuous	ADJ
cana-1859	90	3	evolution	evolution	NOUN
cana-1859	90	4	of	of	ADP
cana-1859	90	5	cnn	cnn	PROPN
cana-1859	90	6	architectures	architecture	NOUN
cana-1859	90	7	and	and	CCONJ
cana-1859	90	8	their	their	PRON
cana-1859	90	9	integration	integration	NOUN
cana-1859	90	10	with	with	ADP
cana-1859	90	11	other	other	ADJ
cana-1859	90	12	technologies	technology	NOUN
cana-1859	90	13	like	like	ADP
cana-1859	90	14	quantum	quantum	NOUN
cana-1859	90	15	computing	computing	NOUN
cana-1859	90	16	,	,	PUNCT
cana-1859	90	17	graph	graph	NOUN
cana-1859	90	18	networks	network	NOUN
cana-1859	90	19	,	,	PUNCT
cana-1859	90	20	and	and	CCONJ
cana-1859	90	21	attention	attention	NOUN
cana-1859	90	22	mechanisms	mechanism	NOUN
cana-1859	90	23	further	far	ADV
cana-1859	90	24	emphasize	emphasize	VERB
cana-1859	90	25	their	their	PRON
cana-1859	90	26	significance	significance	NOUN
cana-1859	90	27	in	in	ADP
cana-1859	90	28	advancing	advance	VERB
cana-1859	90	29	various	various	ADJ
cana-1859	90	30	scientific	scientific	ADJ
cana-1859	90	31	and	and	CCONJ
cana-1859	90	32	technological	technological	ADJ
cana-1859	90	33	fields	field	NOUN
cana-1859	90	34	.	.	PUNCT
cana-1859	91	1	3	3	X
cana-1859	91	2	.	.	NUM
cana-1859	91	3	proposed	propose	VERB
cana-1859	91	4	design	design	NOUN
cana-1859	91	5	of	of	ADP
cana-1859	91	6	an	an	DET
cana-1859	91	7	efficient	efficient	ADJ
cana-1859	91	8	model	model	NOUN
cana-1859	91	9	for	for	ADP
cana-1859	91	10	integrating	integrate	VERB
cana-1859	91	11	vedic	vedic	ADJ
cana-1859	91	12	mathematics	mathematic	NOUN
cana-1859	91	13	to	to	PART
cana-1859	91	14	enhance	enhance	VERB
cana-1859	91	15	convolutional	convolutional	ADJ
cana-1859	91	16	neural	neural	ADJ
cana-1859	91	17	network	network	NOUN
cana-1859	91	18	performance	performance	NOUN
cana-1859	91	19	in	in	ADP
cana-1859	91	20	image	image	NOUN
cana-1859	91	21	classification	classification	NOUN
cana-1859	91	22	tasks	task	NOUN
cana-1859	91	23	to	to	PART
cana-1859	91	24	overcome	overcome	VERB
cana-1859	91	25	the	the	DET
cana-1859	91	26	limitations	limitation	NOUN
cana-1859	91	27	of	of	ADP
cana-1859	91	28	existing	exist	VERB
cana-1859	91	29	models	model	NOUN
cana-1859	91	30	used	use	VERB
cana-1859	91	31	for	for	ADP
cana-1859	91	32	optimizing	optimize	VERB
cana-1859	91	33	cnn	cnn	PROPN
cana-1859	91	34	performance	performance	NOUN
cana-1859	91	35	,	,	PUNCT
cana-1859	91	36	this	this	DET
cana-1859	91	37	work	work	NOUN
cana-1859	91	38	unveiled	unveil	VERB
cana-1859	91	39	the	the	DET
cana-1859	91	40	vmcnn	vmcnn	PROPN
cana-1859	91	41	model	model	NOUN
cana-1859	91	42	,	,	PUNCT
cana-1859	91	43	which	which	PRON
cana-1859	91	44	is	be	AUX
cana-1859	91	45	an	an	DET
cana-1859	91	46	iterative	iterative	ADJ
cana-1859	91	47	convolutional	convolutional	ADJ
cana-1859	91	48	neural	neural	ADJ
cana-1859	91	49	network	network	NOUN
cana-1859	91	50	architecture	architecture	NOUN
cana-1859	91	51	that	that	PRON
cana-1859	91	52	ingeniously	ingeniously	ADV
cana-1859	91	53	incorporates	incorporate	VERB
cana-1859	91	54	vedic	vedic	ADJ
cana-1859	91	55	mathematics	mathematic	NOUN
cana-1859	91	56	principles	principle	NOUN
cana-1859	91	57	for	for	ADP
cana-1859	91	58	optimized	optimize	VERB
cana-1859	91	59	performance	performance	NOUN
cana-1859	91	60	.	.	PUNCT
cana-1859	92	1	distinct	distinct	ADJ
cana-1859	92	2	from	from	ADP
cana-1859	92	3	traditional	traditional	ADJ
cana-1859	92	4	cnn	cnn	PROPN
cana-1859	92	5	models	model	NOUN
cana-1859	92	6	like	like	ADP
cana-1859	92	7	cnn	cnn	PROPN
cana-1859	92	8	elm	elm	PROPN
cana-1859	92	9	,	,	PUNCT
cana-1859	92	10	dcnn	dcnn	PROPN
cana-1859	92	11	,	,	PUNCT
cana-1859	92	12	and	and	CCONJ
cana-1859	92	13	fireclassnet	fireclassnet	NOUN
cana-1859	92	14	,	,	PUNCT
cana-1859	92	15	vmcnn	vmcnn	PROPN
cana-1859	92	16	stands	stand	VERB
cana-1859	92	17	out	out	ADP
cana-1859	92	18	for	for	ADP
cana-1859	92	19	its	its	PRON
cana-1859	92	20	unique	unique	ADJ
cana-1859	92	21	flow	flow	NOUN
cana-1859	92	22	of	of	ADP
cana-1859	92	23	data	datum	NOUN
cana-1859	92	24	and	and	CCONJ
cana-1859	92	25	processing	processing	NOUN
cana-1859	92	26	techniques	technique	NOUN
cana-1859	92	27	.	.	PUNCT
cana-1859	93	1	as	as	ADP
cana-1859	93	2	per	per	ADP
cana-1859	93	3	figure	figure	NOUN
cana-1859	93	4	1	1	NUM
cana-1859	93	5	,	,	PUNCT
cana-1859	93	6	the	the	DET
cana-1859	93	7	model	model	NOUN
cana-1859	93	8	initiates	initiate	VERB
cana-1859	93	9	with	with	ADP
cana-1859	93	10	standard	standard	ADJ
cana-1859	93	11	convolutional	convolutional	ADJ
cana-1859	93	12	layers	layer	NOUN
cana-1859	93	13	,	,	PUNCT
cana-1859	93	14	which	which	PRON
cana-1859	93	15	are	be	AUX
cana-1859	93	16	enhanced	enhance	VERB
cana-1859	93	17	with	with	ADP
cana-1859	93	18	vedic	vedic	ADJ
cana-1859	93	19	computational	computational	ADJ
cana-1859	93	20	methods	method	NOUN
cana-1859	93	21	,	,	PUNCT
cana-1859	93	22	notably	notably	ADV
cana-1859	93	23	increasing	increase	VERB
cana-1859	93	24	efficiency	efficiency	NOUN
cana-1859	93	25	in	in	ADP
cana-1859	93	26	feature	feature	NOUN
cana-1859	93	27	extraction	extraction	NOUN
cana-1859	93	28	.	.	PUNCT
cana-1859	94	1	this	this	PRON
cana-1859	94	2	is	be	AUX
cana-1859	94	3	followed	follow	VERB
cana-1859	94	4	by	by	ADP
cana-1859	94	5	relu	relu	NOUN
cana-1859	94	6	activation	activation	NOUN
cana-1859	94	7	functions	function	NOUN
cana-1859	94	8	,	,	PUNCT
cana-1859	94	9	ensuring	ensure	VERB
cana-1859	94	10	non	non	NOUN
cana-1859	94	11	-	-	ADJ
cana-1859	94	12	linearity	linearity	ADJ
cana-1859	94	13	in	in	ADP
cana-1859	94	14	data	datum	NOUN
cana-1859	94	15	transformation	transformation	NOUN
cana-1859	94	16	.	.	PUNCT
cana-1859	95	1	the	the	DET
cana-1859	95	2	integration	integration	NOUN
cana-1859	95	3	of	of	ADP
cana-1859	95	4	pooling	pool	VERB
cana-1859	95	5	layers	layer	NOUN
cana-1859	95	6	aids	aid	NOUN
cana-1859	95	7	in	in	ADP
cana-1859	95	8	dimensionality	dimensionality	NOUN
cana-1859	95	9	reduction	reduction	NOUN
cana-1859	95	10	,	,	PUNCT
cana-1859	95	11	while	while	SCONJ
cana-1859	95	12	batch	batch	NOUN
cana-1859	95	13	normalization	normalization	NOUN
cana-1859	95	14	optimizes	optimize	VERB
cana-1859	95	15	the	the	DET
cana-1859	95	16	network	network	NOUN
cana-1859	95	17	's	's	PART
cana-1859	95	18	training	training	NOUN
cana-1859	95	19	stability	stability	NOUN
cana-1859	95	20	.	.	PUNCT
cana-1859	96	1	further	far	ADV
cana-1859	96	2	into	into	ADP
cana-1859	96	3	the	the	DET
cana-1859	96	4	architecture	architecture	NOUN
cana-1859	96	5	,	,	PUNCT
cana-1859	96	6	dropout	dropout	NOUN
cana-1859	96	7	layers	layer	NOUN
cana-1859	96	8	strategically	strategically	ADV
cana-1859	96	9	minimize	minimize	VERB
cana-1859	96	10	overfitting	overfitte	VERB
cana-1859	96	11	,	,	PUNCT
cana-1859	96	12	and	and	CCONJ
cana-1859	96	13	fully	fully	ADV
cana-1859	96	14	connected	connected	ADJ
cana-1859	96	15	layers	layer	NOUN
cana-1859	96	16	adeptly	adeptly	ADV
cana-1859	96	17	consolidate	consolidate	VERB
cana-1859	96	18	features	feature	NOUN
cana-1859	96	19	for	for	ADP
cana-1859	96	20	classification	classification	NOUN
cana-1859	96	21	.	.	PUNCT
cana-1859	97	1	the	the	DET
cana-1859	97	2	data	data	NOUN
cana-1859	97	3	flow	flow	NOUN
cana-1859	97	4	culminates	culminate	VERB
cana-1859	97	5	in	in	ADP
cana-1859	97	6	a	a	DET
cana-1859	97	7	softmax	softmax	ADJ
cana-1859	97	8	output	output	NOUN
cana-1859	97	9	layer	layer	NOUN
cana-1859	97	10	,	,	PUNCT
cana-1859	97	11	which	which	PRON
cana-1859	97	12	deftly	deftly	ADV
cana-1859	97	13	handles	handle	VERB
cana-1859	97	14	the	the	DET
cana-1859	97	15	classification	classification	NOUN
cana-1859	97	16	probabilities	probability	NOUN
cana-1859	97	17	.	.	PUNCT
cana-1859	98	1	communications	communication	NOUN
cana-1859	98	2	on	on	ADP
cana-1859	98	3	applied	apply	VERB
cana-1859	98	4	nonlinear	nonlinear	ADJ
cana-1859	98	5	analysis	analysis	NOUN
cana-1859	98	6	issn	issn	NOUN
cana-1859	98	7	:	:	PUNCT
cana-1859	98	8	1074	1074	NUM
cana-1859	98	9	-	-	PUNCT
cana-1859	98	10	133x	133x	NUM
cana-1859	98	11	vol	vol	NOUN
cana-1859	98	12	32	32	NUM
cana-1859	98	13	no	no	NOUN
cana-1859	98	14	.	.	NOUN
cana-1859	98	15	2	2	NUM
cana-1859	98	16	(	(	PUNCT
cana-1859	98	17	2025	2025	NUM
cana-1859	98	18	)	)	PUNCT
cana-1859	98	19	643	643	NUM
cana-1859	98	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	98	21	fig	fig	NOUN
cana-1859	98	22	1	1	NUM
cana-1859	98	23	.	.	PUNCT
cana-1859	99	1	design	design	NOUN
cana-1859	99	2	of	of	ADP
cana-1859	99	3	the	the	DET
cana-1859	99	4	proposed	propose	VERB
cana-1859	99	5	model	model	NOUN
cana-1859	99	6	for	for	ADP
cana-1859	99	7	optimizing	optimize	VERB
cana-1859	99	8	cnn	cnn	PROPN
cana-1859	99	9	performance	performance	NOUN
cana-1859	99	10	levels	level	NOUN
cana-1859	99	11	this	this	DET
cana-1859	99	12	seamless	seamless	ADJ
cana-1859	99	13	integration	integration	NOUN
cana-1859	99	14	of	of	ADP
cana-1859	99	15	vedic	vedic	ADJ
cana-1859	99	16	mathematics	mathematic	NOUN
cana-1859	99	17	into	into	ADP
cana-1859	99	18	the	the	DET
cana-1859	99	19	cnn	cnn	PROPN
cana-1859	99	20	framework	framework	NOUN
cana-1859	99	21	not	not	PART
cana-1859	99	22	only	only	ADV
cana-1859	99	23	optimizes	optimize	VERB
cana-1859	99	24	the	the	DET
cana-1859	99	25	computational	computational	ADJ
cana-1859	99	26	aspects	aspect	NOUN
cana-1859	99	27	of	of	ADP
cana-1859	99	28	the	the	DET
cana-1859	99	29	network	network	NOUN
cana-1859	99	30	but	but	CCONJ
cana-1859	99	31	also	also	ADV
cana-1859	99	32	significantly	significantly	ADV
cana-1859	99	33	boosts	boost	VERB
cana-1859	99	34	key	key	ADJ
cana-1859	99	35	performance	performance	NOUN
cana-1859	99	36	indicators	indicator	NOUN
cana-1859	99	37	such	such	ADJ
cana-1859	99	38	as	as	ADP
cana-1859	99	39	precision	precision	NOUN
cana-1859	99	40	,	,	PUNCT
cana-1859	99	41	accuracy	accuracy	NOUN
cana-1859	99	42	,	,	PUNCT
cana-1859	99	43	and	and	CCONJ
cana-1859	99	44	recall	recall	NOUN
cana-1859	99	45	,	,	PUNCT
cana-1859	99	46	particularly	particularly	ADV
cana-1859	99	47	evident	evident	ADJ
cana-1859	99	48	when	when	SCONJ
cana-1859	99	49	analyzing	analyze	VERB
cana-1859	99	50	complex	complex	ADJ
cana-1859	99	51	and	and	CCONJ
cana-1859	99	52	diverse	diverse	ADJ
cana-1859	99	53	datasets	dataset	NOUN
cana-1859	99	54	like	like	ADP
cana-1859	99	55	imagenet	imagenet	NOUN
cana-1859	99	56	,	,	PUNCT
cana-1859	99	57	cifar	cifar	ADV
cana-1859	99	58	,	,	PUNCT
cana-1859	99	59	chestxray8	chestxray8	PROPN
cana-1859	99	60	,	,	PUNCT
cana-1859	99	61	and	and	CCONJ
cana-1859	99	62	architectural	architectural	ADJ
cana-1859	99	63	heritage	heritage	NOUN
cana-1859	99	64	datasets	dataset	NOUN
cana-1859	99	65	&	&	CCONJ
cana-1859	99	66	samples	sample	NOUN
cana-1859	99	67	.	.	PUNCT
cana-1859	100	1	to	to	PART
cana-1859	100	2	perform	perform	VERB
cana-1859	100	3	these	these	DET
cana-1859	100	4	tasks	task	NOUN
cana-1859	100	5	a	a	DET
cana-1859	100	6	baseline	baseline	ADJ
cana-1859	100	7	convolutional	convolutional	ADJ
cana-1859	100	8	neural	neural	ADJ
cana-1859	100	9	network	network	NOUN
cana-1859	100	10	(	(	PUNCT
cana-1859	100	11	cnn	cnn	PROPN
cana-1859	100	12	)	)	PUNCT
cana-1859	100	13	model	model	NOUN
cana-1859	100	14	was	be	AUX
cana-1859	100	15	developed	develop	VERB
cana-1859	100	16	to	to	PART
cana-1859	100	17	benchmark	benchmark	NOUN
cana-1859	100	18	with	with	ADP
cana-1859	100	19	the	the	DET
cana-1859	100	20	vedic	vedic	ADJ
cana-1859	100	21	mathematics	mathematics	PROPN
cana-1859	100	22	optimized	optimize	VERB
cana-1859	100	23	vmcnn	vmcnn	PROPN
cana-1859	100	24	.	.	PUNCT
cana-1859	101	1	as	as	ADP
cana-1859	101	2	per	per	ADP
cana-1859	101	3	figure	figure	NOUN
cana-1859	101	4	1	1	NUM
cana-1859	101	5	,	,	PUNCT
cana-1859	101	6	the	the	DET
cana-1859	101	7	cnn	cnn	PROPN
cana-1859	101	8	model	model	NOUN
cana-1859	101	9	is	be	AUX
cana-1859	101	10	communications	communication	NOUN
cana-1859	101	11	on	on	ADP
cana-1859	101	12	applied	apply	VERB
cana-1859	101	13	nonlinear	nonlinear	ADJ
cana-1859	101	14	analysis	analysis	NOUN
cana-1859	101	15	issn	issn	NOUN
cana-1859	101	16	:	:	PUNCT
cana-1859	101	17	1074	1074	NUM
cana-1859	101	18	-	-	PUNCT
cana-1859	101	19	133x	133x	NUM
cana-1859	101	20	vol	vol	NOUN
cana-1859	101	21	32	32	NUM
cana-1859	101	22	no	no	NOUN
cana-1859	101	23	.	.	NOUN
cana-1859	101	24	2	2	NUM
cana-1859	101	25	(	(	PUNCT
cana-1859	101	26	2025	2025	NUM
cana-1859	101	27	)	)	PUNCT
cana-1859	101	28	644	644	NUM
cana-1859	101	29	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	101	30	structured	structure	VERB
cana-1859	101	31	to	to	PART
cana-1859	101	32	process	process	VERB
cana-1859	101	33	input	input	NOUN
cana-1859	101	34	images	image	NOUN
cana-1859	101	35	and	and	CCONJ
cana-1859	101	36	output	output	NOUN
cana-1859	101	37	classified	classify	VERB
cana-1859	101	38	results	result	NOUN
cana-1859	101	39	through	through	ADP
cana-1859	101	40	a	a	DET
cana-1859	101	41	series	series	NOUN
cana-1859	101	42	of	of	ADP
cana-1859	101	43	layers	layer	NOUN
cana-1859	101	44	,	,	PUNCT
cana-1859	101	45	each	each	PRON
cana-1859	101	46	designed	design	VERB
cana-1859	101	47	to	to	PART
cana-1859	101	48	extract	extract	VERB
cana-1859	101	49	and	and	CCONJ
cana-1859	101	50	refine	refine	VERB
cana-1859	101	51	features	feature	NOUN
cana-1859	101	52	progressively	progressively	ADV
cana-1859	101	53	.	.	PUNCT
cana-1859	102	1	the	the	DET
cana-1859	102	2	model	model	NOUN
cana-1859	102	3	comprises	comprise	VERB
cana-1859	102	4	the	the	DET
cana-1859	102	5	following	follow	VERB
cana-1859	102	6	key	key	ADJ
cana-1859	102	7	components	component	NOUN
cana-1859	102	8	:	:	PUNCT
cana-1859	102	9	1	1	X
cana-1859	102	10	.	.	PUNCT
cana-1859	102	11	input	input	NOUN
cana-1859	102	12	layer	layer	NOUN
cana-1859	102	13	:	:	PUNCT
cana-1859	102	14	the	the	DET
cana-1859	102	15	model	model	NOUN
cana-1859	102	16	accepts	accept	VERB
cana-1859	102	17	input	input	NOUN
cana-1859	102	18	images	image	NOUN
cana-1859	102	19	,	,	PUNCT
cana-1859	102	20	pre	pre	VERB
cana-1859	102	21	-	-	VERB
cana-1859	102	22	processed	process	VERB
cana-1859	102	23	to	to	ADP
cana-1859	102	24	a	a	DET
cana-1859	102	25	uniform	uniform	ADJ
cana-1859	102	26	size	size	NOUN
cana-1859	102	27	suitable	suitable	ADJ
cana-1859	102	28	for	for	ADP
cana-1859	102	29	the	the	DET
cana-1859	102	30	network	network	NOUN
cana-1859	102	31	,	,	PUNCT
cana-1859	102	32	typically	typically	ADV
cana-1859	102	33	224x224	224x224	NUM
cana-1859	102	34	pixels	pixel	NOUN
cana-1859	102	35	.	.	PUNCT
cana-1859	103	1	2	2	X
cana-1859	103	2	.	.	X
cana-1859	103	3	convolutional	convolutional	ADJ
cana-1859	103	4	layers	layer	NOUN
cana-1859	103	5	:	:	PUNCT
cana-1859	103	6	several	several	ADJ
cana-1859	103	7	convolutional	convolutional	ADJ
cana-1859	103	8	layers	layer	NOUN
cana-1859	103	9	are	be	AUX
cana-1859	103	10	used	use	VERB
cana-1859	103	11	,	,	PUNCT
cana-1859	103	12	each	each	PRON
cana-1859	103	13	consisting	consist	VERB
cana-1859	103	14	of	of	ADP
cana-1859	103	15	a	a	DET
cana-1859	103	16	set	set	NOUN
cana-1859	103	17	of	of	ADP
cana-1859	103	18	learnable	learnable	ADJ
cana-1859	103	19	filters	filter	NOUN
cana-1859	103	20	or	or	CCONJ
cana-1859	103	21	kernels	kernel	NOUN
cana-1859	103	22	.	.	PUNCT
cana-1859	104	1	the	the	DET
cana-1859	104	2	convolution	convolution	NOUN
cana-1859	104	3	operation	operation	NOUN
cana-1859	104	4	in	in	ADP
cana-1859	104	5	each	each	DET
cana-1859	104	6	layer	layer	NOUN
cana-1859	104	7	is	be	AUX
cana-1859	104	8	defined	define	VERB
cana-1859	104	9	via	via	ADP
cana-1859	104	10	equation	equation	NOUN
cana-1859	104	11	1	1	NUM
cana-1859	104	12	,	,	PUNCT
cana-1859	104	13	𝐹𝑖𝑗(𝑙	𝐹𝑖𝑗(𝑙	PUNCT
cana-1859	104	14	)	)	PUNCT
cana-1859	104	15	=	=	PUNCT
cana-1859	105	1	∑∑𝐼(𝑖	∑∑𝐼(𝑖	PUNCT
cana-1859	106	1	+	+	CCONJ
cana-1859	106	2	𝑚)(𝑗	𝑚)(𝑗	DET
cana-1859	106	3	+	+	X
cana-1859	106	4	𝑛	𝑛	X
cana-1859	106	5	)	)	PUNCT
cana-1859	106	6	⋅	⋅	PROPN
cana-1859	106	7	𝐾𝑚𝑛(𝑙	𝐾𝑚𝑛(𝑙	PROPN
cana-1859	106	8	)	)	PUNCT
cana-1859	106	9	…	…	PUNCT
cana-1859	106	10	(	(	PUNCT
cana-1859	106	11	1	1	X
cana-1859	106	12	)	)	PUNCT
cana-1859	106	13	where	where	SCONJ
cana-1859	106	14	,	,	PUNCT
cana-1859	106	15	fij(l	fij(l	PROPN
cana-1859	106	16	)	)	PUNCT
cana-1859	106	17	is	be	AUX
cana-1859	106	18	the	the	DET
cana-1859	106	19	feature	feature	NOUN
cana-1859	106	20	map	map	NOUN
cana-1859	106	21	at	at	ADP
cana-1859	106	22	layer	layer	NOUN
cana-1859	106	23	l	l	NOUN
cana-1859	106	24	,	,	PUNCT
cana-1859	106	25	i	i	PRON
cana-1859	106	26	is	be	AUX
cana-1859	106	27	the	the	DET
cana-1859	106	28	input	input	NOUN
cana-1859	106	29	to	to	ADP
cana-1859	106	30	the	the	DET
cana-1859	106	31	layer	layer	NOUN
cana-1859	106	32	,	,	PUNCT
cana-1859	106	33	k(l	k(l	PROPN
cana-1859	106	34	)	)	PUNCT
cana-1859	106	35	is	be	AUX
cana-1859	106	36	the	the	DET
cana-1859	106	37	kernel	kernel	NOUN
cana-1859	106	38	at	at	ADP
cana-1859	106	39	layer	layer	NOUN
cana-1859	106	40	l	l	NOUN
cana-1859	106	41	,	,	PUNCT
cana-1859	106	42	and	and	CCONJ
cana-1859	106	43	m	m	PROPN
cana-1859	106	44	,	,	PUNCT
cana-1859	106	45	n	n	PRON
cana-1859	106	46	are	be	AUX
cana-1859	106	47	the	the	DET
cana-1859	106	48	dimensions	dimension	NOUN
cana-1859	106	49	of	of	ADP
cana-1859	106	50	the	the	DET
cana-1859	106	51	kernel	kernel	NOUN
cana-1859	106	52	.	.	PUNCT
cana-1859	107	1	3	3	X
cana-1859	107	2	.	.	X
cana-1859	107	3	activation	activation	NOUN
cana-1859	107	4	function	function	NOUN
cana-1859	107	5	(	(	PUNCT
cana-1859	107	6	relu	relu	NOUN
cana-1859	107	7	):	):	PUNCT
cana-1859	107	8	the	the	DET
cana-1859	107	9	output	output	NOUN
cana-1859	107	10	of	of	ADP
cana-1859	107	11	each	each	DET
cana-1859	107	12	convolution	convolution	NOUN
cana-1859	107	13	is	be	AUX
cana-1859	107	14	passed	pass	VERB
cana-1859	107	15	through	through	ADP
cana-1859	107	16	a	a	DET
cana-1859	107	17	relu	relu	NOUN
cana-1859	107	18	(	(	PUNCT
cana-1859	107	19	rectified	rectified	ADJ
cana-1859	107	20	linear	linear	NOUN
cana-1859	107	21	unit	unit	NOUN
cana-1859	107	22	)	)	PUNCT
cana-1859	107	23	activation	activation	NOUN
cana-1859	107	24	function	function	NOUN
cana-1859	107	25	via	via	ADP
cana-1859	107	26	equation	equation	NOUN
cana-1859	107	27	2	2	NUM
cana-1859	107	28	,	,	PUNCT
cana-1859	107	29	𝑅(𝑥	𝑅(𝑥	NOUN
cana-1859	107	30	)	)	PUNCT
cana-1859	107	31	=	=	PUNCT
cana-1859	107	32	𝑚𝑎𝑥(0	𝑚𝑎𝑥(0	NOUN
cana-1859	107	33	,	,	PUNCT
cana-1859	107	34	𝑥	𝑥	NOUN
cana-1859	107	35	)	)	PUNCT
cana-1859	107	36	…	…	PUNCT
cana-1859	107	37	(	(	PUNCT
cana-1859	107	38	2	2	X
cana-1859	107	39	)	)	PUNCT
cana-1859	107	40	this	this	PRON
cana-1859	107	41	introduces	introduce	VERB
cana-1859	107	42	non	non	ADJ
cana-1859	107	43	-	-	ADJ
cana-1859	107	44	linearity	linearity	ADJ
cana-1859	107	45	,	,	PUNCT
cana-1859	107	46	allowing	allow	VERB
cana-1859	107	47	the	the	DET
cana-1859	107	48	network	network	NOUN
cana-1859	107	49	to	to	PART
cana-1859	107	50	learn	learn	VERB
cana-1859	107	51	more	more	ADJ
cana-1859	107	52	complex	complex	ADJ
cana-1859	107	53	patterns	pattern	NOUN
cana-1859	107	54	.	.	PUNCT
cana-1859	108	1	4	4	X
cana-1859	108	2	.	.	X
cana-1859	108	3	pooling	pool	VERB
cana-1859	108	4	layers	layer	NOUN
cana-1859	108	5	:	:	PUNCT
cana-1859	108	6	to	to	PART
cana-1859	108	7	reduce	reduce	VERB
cana-1859	108	8	the	the	DET
cana-1859	108	9	spatial	spatial	ADJ
cana-1859	108	10	dimensions	dimension	NOUN
cana-1859	108	11	,	,	PUNCT
cana-1859	108	12	pooling	pool	VERB
cana-1859	108	13	layers	layer	NOUN
cana-1859	108	14	are	be	AUX
cana-1859	108	15	used	use	VERB
cana-1859	108	16	,	,	PUNCT
cana-1859	108	17	typically	typically	ADV
cana-1859	108	18	max	max	PROPN
cana-1859	108	19	pooling	pooling	NOUN
cana-1859	108	20	,	,	PUNCT
cana-1859	108	21	which	which	PRON
cana-1859	108	22	is	be	AUX
cana-1859	108	23	described	describe	VERB
cana-1859	108	24	via	via	ADP
cana-1859	108	25	equation	equation	NOUN
cana-1859	108	26	3	3	NUM
cana-1859	108	27	,	,	PUNCT
cana-1859	108	28	𝑃𝑖𝑗	𝑃𝑖𝑗	PROPN
cana-1859	108	29	=	=	SYM
cana-1859	108	30	𝑚𝑎𝑥(𝐴𝑘𝑙	𝑚𝑎𝑥(𝐴𝑘𝑙	PROPN
cana-1859	108	31	)	)	PUNCT
cana-1859	108	32	…	…	PUNCT
cana-1859	108	33	(	(	PUNCT
cana-1859	108	34	3	3	X
cana-1859	108	35	)	)	PUNCT
cana-1859	108	36	where	where	SCONJ
cana-1859	108	37	,	,	PUNCT
cana-1859	108	38	pij	pij	NOUN
cana-1859	108	39	is	be	AUX
cana-1859	108	40	the	the	DET
cana-1859	108	41	pooled	pooled	ADJ
cana-1859	108	42	output	output	NOUN
cana-1859	108	43	,	,	PUNCT
cana-1859	108	44	and	and	CCONJ
cana-1859	108	45	akl	akl	PROPN
cana-1859	108	46	is	be	AUX
cana-1859	108	47	the	the	DET
cana-1859	108	48	activation	activation	NOUN
cana-1859	108	49	within	within	ADP
cana-1859	108	50	the	the	DET
cana-1859	108	51	pooling	pool	VERB
cana-1859	108	52	windows	window	NOUN
cana-1859	108	53	.	.	PUNCT
cana-1859	109	1	5	5	X
cana-1859	109	2	.	.	X
cana-1859	109	3	fully	fully	ADV
cana-1859	109	4	connected	connected	ADJ
cana-1859	109	5	layers	layer	NOUN
cana-1859	109	6	:	:	PUNCT
cana-1859	109	7	towards	towards	ADP
cana-1859	109	8	the	the	DET
cana-1859	109	9	end	end	NOUN
cana-1859	109	10	,	,	PUNCT
cana-1859	109	11	the	the	DET
cana-1859	109	12	network	network	NOUN
cana-1859	109	13	includes	include	VERB
cana-1859	109	14	one	one	NUM
cana-1859	109	15	or	or	CCONJ
cana-1859	109	16	more	more	ADV
cana-1859	109	17	fully	fully	ADV
cana-1859	109	18	connected	connected	ADJ
cana-1859	109	19	layers	layer	NOUN
cana-1859	109	20	where	where	SCONJ
cana-1859	109	21	each	each	DET
cana-1859	109	22	neuron	neuron	NOUN
cana-1859	109	23	is	be	AUX
cana-1859	109	24	connected	connect	VERB
cana-1859	109	25	to	to	ADP
cana-1859	109	26	all	all	DET
cana-1859	109	27	activations	activation	NOUN
cana-1859	109	28	in	in	ADP
cana-1859	109	29	the	the	DET
cana-1859	109	30	previous	previous	ADJ
cana-1859	109	31	layer	layer	NOUN
cana-1859	109	32	.	.	PUNCT
cana-1859	110	1	the	the	DET
cana-1859	110	2	operation	operation	NOUN
cana-1859	110	3	in	in	ADP
cana-1859	110	4	these	these	DET
cana-1859	110	5	layers	layer	NOUN
cana-1859	110	6	is	be	AUX
cana-1859	110	7	described	describe	VERB
cana-1859	110	8	via	via	ADP
cana-1859	110	9	equation	equation	NOUN
cana-1859	110	10	4	4	NUM
cana-1859	110	11	,	,	PUNCT
cana-1859	110	12	𝑂	𝑂	PROPN
cana-1859	110	13	=	=	SYM
cana-1859	110	14	𝑊	𝑊	PROPN
cana-1859	110	15	⋅	⋅	NOUN
cana-1859	110	16	𝐹	𝐹	PROPN
cana-1859	110	17	+	+	NUM
cana-1859	110	18	𝑏	𝑏	NOUN
cana-1859	110	19	…	…	PUNCT
cana-1859	110	20	(	(	PUNCT
cana-1859	110	21	4	4	NUM
cana-1859	110	22	)	)	PUNCT
cana-1859	110	23	where	where	SCONJ
cana-1859	110	24	,	,	PUNCT
cana-1859	110	25	o	o	PROPN
cana-1859	110	26	is	be	AUX
cana-1859	110	27	the	the	DET
cana-1859	110	28	output	output	NOUN
cana-1859	110	29	,	,	PUNCT
cana-1859	110	30	w	w	PROPN
cana-1859	110	31	is	be	AUX
cana-1859	110	32	the	the	DET
cana-1859	110	33	weight	weight	NOUN
cana-1859	110	34	matrix	matrix	NOUN
cana-1859	110	35	,	,	PUNCT
cana-1859	110	36	f	f	PROPN
cana-1859	110	37	is	be	AUX
cana-1859	110	38	the	the	DET
cana-1859	110	39	flattened	flatten	VERB
cana-1859	110	40	feature	feature	NOUN
cana-1859	110	41	map	map	NOUN
cana-1859	110	42	from	from	ADP
cana-1859	110	43	previous	previous	ADJ
cana-1859	110	44	layers	layer	NOUN
cana-1859	110	45	,	,	PUNCT
cana-1859	110	46	and	and	CCONJ
cana-1859	110	47	b	b	X
cana-1859	110	48	is	be	AUX
cana-1859	110	49	the	the	DET
cana-1859	110	50	bias	bias	NOUN
cana-1859	110	51	.	.	PUNCT
cana-1859	111	1	6	6	X
cana-1859	111	2	.	.	X
cana-1859	111	3	output	output	NOUN
cana-1859	111	4	layer	layer	NOUN
cana-1859	111	5	:	:	PUNCT
cana-1859	111	6	the	the	DET
cana-1859	111	7	final	final	ADJ
cana-1859	111	8	layer	layer	NOUN
cana-1859	111	9	is	be	AUX
cana-1859	111	10	a	a	DET
cana-1859	111	11	softmax	softmax	NOUN
cana-1859	111	12	layer	layer	NOUN
cana-1859	111	13	,	,	PUNCT
cana-1859	111	14	providing	provide	VERB
cana-1859	111	15	the	the	DET
cana-1859	111	16	probability	probability	NOUN
cana-1859	111	17	distribution	distribution	NOUN
cana-1859	111	18	over	over	ADP
cana-1859	111	19	the	the	DET
cana-1859	111	20	classes	class	NOUN
cana-1859	111	21	via	via	ADP
cana-1859	111	22	equation	equation	NOUN
cana-1859	111	23	5	5	NUM
cana-1859	111	24	,	,	PUNCT
cana-1859	111	25	𝑆(𝑥𝑖	𝑆(𝑥𝑖	PROPN
cana-1859	111	26	)	)	PUNCT
cana-1859	111	27	=	=	SYM
cana-1859	111	28	𝑒𝑥𝑖	𝑒𝑥𝑖	ADJ
cana-1859	111	29	∑𝑒𝑥𝑗	∑𝑒𝑥𝑗	NOUN
cana-1859	111	30	…	…	PUNCT
cana-1859	111	31	(	(	PUNCT
cana-1859	111	32	5	5	NUM
cana-1859	111	33	)	)	PUNCT
cana-1859	111	34	where	where	SCONJ
cana-1859	111	35	,	,	PUNCT
cana-1859	111	36	xi	xi	X
cana-1859	111	37	is	be	AUX
cana-1859	111	38	the	the	DET
cana-1859	111	39	input	input	NOUN
cana-1859	111	40	to	to	ADP
cana-1859	111	41	the	the	DET
cana-1859	111	42	softmax	softmax	NOUN
cana-1859	111	43	function	function	NOUN
cana-1859	111	44	,	,	PUNCT
cana-1859	111	45	and	and	CCONJ
cana-1859	111	46	s(xi	s(xi	NUM
cana-1859	111	47	)	)	PUNCT
cana-1859	111	48	is	be	AUX
cana-1859	111	49	the	the	DET
cana-1859	111	50	calculated	calculated	ADJ
cana-1859	111	51	probability	probability	NOUN
cana-1859	111	52	.	.	PUNCT
cana-1859	112	1	communications	communication	NOUN
cana-1859	112	2	on	on	ADP
cana-1859	112	3	applied	apply	VERB
cana-1859	112	4	nonlinear	nonlinear	ADJ
cana-1859	112	5	analysis	analysis	NOUN
cana-1859	112	6	issn	issn	NOUN
cana-1859	112	7	:	:	PUNCT
cana-1859	112	8	1074	1074	NUM
cana-1859	112	9	-	-	PUNCT
cana-1859	112	10	133x	133x	NUM
cana-1859	112	11	vol	vol	NOUN
cana-1859	112	12	32	32	NUM
cana-1859	112	13	no	no	NOUN
cana-1859	112	14	.	.	NOUN
cana-1859	112	15	2	2	NUM
cana-1859	112	16	(	(	PUNCT
cana-1859	112	17	2025	2025	NUM
cana-1859	112	18	)	)	PUNCT
cana-1859	112	19	645	645	NUM
cana-1859	112	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	112	21	in	in	ADP
cana-1859	112	22	this	this	DET
cana-1859	112	23	process	process	NOUN
cana-1859	112	24	,	,	PUNCT
cana-1859	112	25	the	the	DET
cana-1859	112	26	collected	collect	VERB
cana-1859	112	27	images	image	NOUN
cana-1859	112	28	,	,	PUNCT
cana-1859	112	29	after	after	ADP
cana-1859	112	30	pre	pre	ADJ
cana-1859	112	31	-	-	ADJ
cana-1859	112	32	processing	processing	ADJ
cana-1859	112	33	,	,	PUNCT
cana-1859	112	34	are	be	AUX
cana-1859	112	35	fed	feed	VERB
cana-1859	112	36	into	into	ADP
cana-1859	112	37	the	the	DET
cana-1859	112	38	cnn	cnn	PROPN
cana-1859	112	39	model	model	NOUN
cana-1859	112	40	.	.	PUNCT
cana-1859	113	1	through	through	ADP
cana-1859	113	2	convolutional	convolutional	ADJ
cana-1859	113	3	and	and	CCONJ
cana-1859	113	4	pooling	pool	VERB
cana-1859	113	5	layers	layer	NOUN
cana-1859	113	6	,	,	PUNCT
cana-1859	113	7	the	the	DET
cana-1859	113	8	model	model	NOUN
cana-1859	113	9	extracts	extract	NOUN
cana-1859	113	10	and	and	CCONJ
cana-1859	113	11	downsamples	downsample	NOUN
cana-1859	113	12	features	feature	VERB
cana-1859	113	13	from	from	ADP
cana-1859	113	14	the	the	DET
cana-1859	113	15	images	image	NOUN
cana-1859	113	16	&	&	CCONJ
cana-1859	113	17	samples	sample	NOUN
cana-1859	113	18	.	.	PUNCT
cana-1859	114	1	the	the	DET
cana-1859	114	2	relu	relu	NOUN
cana-1859	114	3	activation	activation	NOUN
cana-1859	114	4	function	function	NOUN
cana-1859	114	5	introduces	introduce	VERB
cana-1859	114	6	non	non	ADJ
cana-1859	114	7	-	-	ADJ
cana-1859	114	8	linearity	linearity	ADJ
cana-1859	114	9	,	,	PUNCT
cana-1859	114	10	aiding	aid	VERB
cana-1859	114	11	the	the	DET
cana-1859	114	12	model	model	NOUN
cana-1859	114	13	in	in	ADP
cana-1859	114	14	learning	learn	VERB
cana-1859	114	15	complex	complex	ADJ
cana-1859	114	16	patterns	pattern	NOUN
cana-1859	114	17	.	.	PUNCT
cana-1859	115	1	in	in	ADP
cana-1859	115	2	the	the	DET
cana-1859	115	3	fully	fully	ADV
cana-1859	115	4	connected	connected	ADJ
cana-1859	115	5	layers	layer	NOUN
cana-1859	115	6	,	,	PUNCT
cana-1859	115	7	the	the	DET
cana-1859	115	8	extracted	extract	VERB
cana-1859	115	9	features	feature	NOUN
cana-1859	115	10	are	be	AUX
cana-1859	115	11	used	use	VERB
cana-1859	115	12	to	to	PART
cana-1859	115	13	determine	determine	VERB
cana-1859	115	14	the	the	DET
cana-1859	115	15	class	class	NOUN
cana-1859	115	16	of	of	ADP
cana-1859	115	17	the	the	DET
cana-1859	115	18	image	image	NOUN
cana-1859	115	19	sets	set	NOUN
cana-1859	115	20	.	.	PUNCT
cana-1859	116	1	the	the	DET
cana-1859	116	2	softmax	softmax	NOUN
cana-1859	116	3	layer	layer	NOUN
cana-1859	116	4	outputs	output	VERB
cana-1859	116	5	the	the	DET
cana-1859	116	6	final	final	ADJ
cana-1859	116	7	classified	classified	ADJ
cana-1859	116	8	results	result	NOUN
cana-1859	116	9	,	,	PUNCT
cana-1859	116	10	indicating	indicate	VERB
cana-1859	116	11	the	the	DET
cana-1859	116	12	probability	probability	NOUN
cana-1859	116	13	distribution	distribution	NOUN
cana-1859	116	14	over	over	ADP
cana-1859	116	15	various	various	ADJ
cana-1859	116	16	classes	class	NOUN
cana-1859	116	17	.	.	PUNCT
cana-1859	117	1	optimization	optimization	NOUN
cana-1859	117	2	of	of	ADP
cana-1859	117	3	this	this	DET
cana-1859	117	4	process	process	NOUN
cana-1859	117	5	is	be	AUX
cana-1859	117	6	done	do	VERB
cana-1859	117	7	using	use	VERB
cana-1859	117	8	the	the	DET
cana-1859	117	9	the	the	DET
cana-1859	117	10	urdhva	urdhva	ADJ
cana-1859	117	11	-	-	PUNCT
cana-1859	117	12	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	117	13	sutra	sutra	NOUN
cana-1859	117	14	,	,	PUNCT
cana-1859	117	15	which	which	PRON
cana-1859	117	16	a	a	DET
cana-1859	117	17	principle	principle	NOUN
cana-1859	117	18	from	from	ADP
cana-1859	117	19	vedic	vedic	ADJ
cana-1859	117	20	mathematics	mathematic	NOUN
cana-1859	117	21	,	,	PUNCT
cana-1859	117	22	is	be	AUX
cana-1859	117	23	known	know	VERB
cana-1859	117	24	for	for	ADP
cana-1859	117	25	its	its	PRON
cana-1859	117	26	efficiency	efficiency	NOUN
cana-1859	117	27	in	in	ADP
cana-1859	117	28	performing	perform	VERB
cana-1859	117	29	multiplication	multiplication	NOUN
cana-1859	117	30	operations	operation	NOUN
cana-1859	117	31	.	.	PUNCT
cana-1859	118	1	its	its	PRON
cana-1859	118	2	application	application	NOUN
cana-1859	118	3	in	in	ADP
cana-1859	118	4	the	the	DET
cana-1859	118	5	realm	realm	NOUN
cana-1859	118	6	of	of	ADP
cana-1859	118	7	convolutional	convolutional	ADJ
cana-1859	118	8	neural	neural	ADJ
cana-1859	118	9	networks	network	NOUN
cana-1859	118	10	(	(	PUNCT
cana-1859	118	11	cnns	cnns	PROPN
cana-1859	118	12	)	)	PUNCT
cana-1859	118	13	can	can	AUX
cana-1859	118	14	significantly	significantly	ADV
cana-1859	118	15	optimize	optimize	VERB
cana-1859	118	16	the	the	DET
cana-1859	118	17	computational	computational	ADJ
cana-1859	118	18	process	process	NOUN
cana-1859	118	19	,	,	PUNCT
cana-1859	118	20	especially	especially	ADV
cana-1859	118	21	in	in	ADP
cana-1859	118	22	the	the	DET
cana-1859	118	23	convolution	convolution	NOUN
cana-1859	118	24	layers	layer	NOUN
cana-1859	118	25	where	where	SCONJ
cana-1859	118	26	multiplication	multiplication	NOUN
cana-1859	118	27	is	be	AUX
cana-1859	118	28	a	a	DET
cana-1859	118	29	fundamental	fundamental	ADJ
cana-1859	118	30	operation	operation	NOUN
cana-1859	118	31	.	.	PUNCT
cana-1859	119	1	urdhva	urdhva	PROPN
cana-1859	119	2	-	-	PUNCT
cana-1859	119	3	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	119	4	sutra	sutra	NOUN
cana-1859	119	5	:	:	PUNCT
cana-1859	119	6	an	an	DET
cana-1859	119	7	overview	overview	NOUN
cana-1859	119	8	the	the	DET
cana-1859	119	9	urdhva	urdhva	ADJ
cana-1859	119	10	-	-	PUNCT
cana-1859	119	11	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	119	12	sutra	sutra	NOUN
cana-1859	119	13	,	,	PUNCT
cana-1859	119	14	translated	translate	VERB
cana-1859	119	15	as	as	ADP
cana-1859	119	16	"	"	PUNCT
cana-1859	119	17	vertically	vertically	ADV
cana-1859	119	18	and	and	CCONJ
cana-1859	119	19	crosswise	crosswise	NOUN
cana-1859	119	20	,	,	PUNCT
cana-1859	119	21	"	"	PUNCT
cana-1859	119	22	is	be	AUX
cana-1859	119	23	a	a	DET
cana-1859	119	24	method	method	NOUN
cana-1859	119	25	used	use	VERB
cana-1859	119	26	to	to	PART
cana-1859	119	27	simplify	simplify	VERB
cana-1859	119	28	and	and	CCONJ
cana-1859	119	29	speed	speed	VERB
cana-1859	119	30	up	up	ADP
cana-1859	119	31	multiplication	multiplication	NOUN
cana-1859	119	32	,	,	PUNCT
cana-1859	119	33	particularly	particularly	ADV
cana-1859	119	34	beneficial	beneficial	ADJ
cana-1859	119	35	for	for	ADP
cana-1859	119	36	large	large	ADJ
cana-1859	119	37	numbers	number	NOUN
cana-1859	119	38	.	.	PUNCT
cana-1859	120	1	the	the	DET
cana-1859	120	2	method	method	NOUN
cana-1859	120	3	involves	involve	VERB
cana-1859	120	4	multiplying	multiply	VERB
cana-1859	120	5	corresponding	correspond	VERB
cana-1859	120	6	digits	digit	NOUN
cana-1859	120	7	of	of	ADP
cana-1859	120	8	the	the	DET
cana-1859	120	9	numbers	number	NOUN
cana-1859	120	10	involved	involve	VERB
cana-1859	120	11	in	in	ADP
cana-1859	120	12	a	a	DET
cana-1859	120	13	crosswise	crosswise	NOUN
cana-1859	120	14	fashion	fashion	NOUN
cana-1859	120	15	and	and	CCONJ
cana-1859	120	16	adding	add	VERB
cana-1859	120	17	the	the	DET
cana-1859	120	18	results	result	NOUN
cana-1859	120	19	to	to	PART
cana-1859	120	20	obtain	obtain	VERB
cana-1859	120	21	the	the	DET
cana-1859	120	22	final	final	ADJ
cana-1859	120	23	product	product	NOUN
cana-1859	120	24	.	.	PUNCT
cana-1859	121	1	in	in	ADP
cana-1859	121	2	cnns	cnns	PROPN
cana-1859	121	3	,	,	PUNCT
cana-1859	121	4	convolution	convolution	NOUN
cana-1859	121	5	operations	operation	NOUN
cana-1859	121	6	are	be	AUX
cana-1859	121	7	pivotal	pivotal	ADJ
cana-1859	121	8	,	,	PUNCT
cana-1859	121	9	involving	involve	VERB
cana-1859	121	10	the	the	DET
cana-1859	121	11	element	element	ADJ
cana-1859	121	12	-	-	PUNCT
cana-1859	121	13	wise	wise	ADJ
cana-1859	121	14	multiplication	multiplication	NOUN
cana-1859	121	15	of	of	ADP
cana-1859	121	16	the	the	DET
cana-1859	121	17	kernel	kernel	NOUN
cana-1859	121	18	and	and	CCONJ
cana-1859	121	19	the	the	DET
cana-1859	121	20	input	input	NOUN
cana-1859	121	21	matrix	matrix	NOUN
cana-1859	121	22	followed	follow	VERB
cana-1859	121	23	by	by	ADP
cana-1859	121	24	a	a	DET
cana-1859	121	25	summation	summation	NOUN
cana-1859	121	26	.	.	PUNCT
cana-1859	122	1	conventionally	conventionally	ADV
cana-1859	122	2	,	,	PUNCT
cana-1859	122	3	this	this	DET
cana-1859	122	4	operation	operation	NOUN
cana-1859	122	5	,	,	PUNCT
cana-1859	122	6	for	for	ADP
cana-1859	122	7	a	a	DET
cana-1859	122	8	single	single	ADJ
cana-1859	122	9	kernel	kernel	NOUN
cana-1859	122	10	and	and	CCONJ
cana-1859	122	11	a	a	DET
cana-1859	122	12	single	single	ADJ
cana-1859	122	13	region	region	NOUN
cana-1859	122	14	of	of	ADP
cana-1859	122	15	the	the	DET
cana-1859	122	16	input	input	NOUN
cana-1859	122	17	,	,	PUNCT
cana-1859	122	18	can	can	AUX
cana-1859	122	19	be	be	AUX
cana-1859	122	20	represented	represent	VERB
cana-1859	122	21	via	via	ADP
cana-1859	122	22	equation	equation	NOUN
cana-1859	122	23	6	6	NUM
cana-1859	122	24	,	,	PUNCT
cana-1859	122	25	𝐹𝑖𝑗	𝐹𝑖𝑗	PROPN
cana-1859	122	26	=	=	PUNCT
cana-1859	122	27	∑∑𝐼(𝑖	∑∑𝐼(𝑖	PUNCT
cana-1859	123	1	+	+	CCONJ
cana-1859	123	2	𝑚)(𝑗	𝑚)(𝑗	PRON
cana-1859	123	3	+	+	X
cana-1859	123	4	𝑛	𝑛	NOUN
cana-1859	123	5	)	)	PUNCT
cana-1859	123	6	×	×	NOUN
cana-1859	123	7	𝐾𝑚𝑛	𝐾𝑚𝑛	NOUN
cana-1859	123	8	…	…	PUNCT
cana-1859	123	9	(	(	PUNCT
cana-1859	123	10	6	6	NUM
cana-1859	123	11	)	)	PUNCT
cana-1859	123	12	where	where	SCONJ
cana-1859	123	13	,	,	PUNCT
cana-1859	123	14	fij	fij	PROPN
cana-1859	123	15	is	be	AUX
cana-1859	123	16	the	the	DET
cana-1859	123	17	output	output	NOUN
cana-1859	123	18	feature	feature	NOUN
cana-1859	123	19	value	value	NOUN
cana-1859	123	20	,	,	PUNCT
cana-1859	123	21	i	i	PRON
cana-1859	123	22	is	be	AUX
cana-1859	123	23	the	the	DET
cana-1859	123	24	input	input	NOUN
cana-1859	123	25	matrix	matrix	NOUN
cana-1859	123	26	,	,	PUNCT
cana-1859	123	27	k	k	PROPN
cana-1859	123	28	is	be	AUX
cana-1859	123	29	the	the	DET
cana-1859	123	30	kernel	kernel	NOUN
cana-1859	123	31	,	,	PUNCT
cana-1859	123	32	and	and	CCONJ
cana-1859	123	33	m	m	PROPN
cana-1859	123	34	,	,	PUNCT
cana-1859	123	35	n	n	PRON
cana-1859	123	36	are	be	AUX
cana-1859	123	37	the	the	DET
cana-1859	123	38	dimensions	dimension	NOUN
cana-1859	123	39	of	of	ADP
cana-1859	123	40	the	the	DET
cana-1859	123	41	kernel	kernel	NOUN
cana-1859	123	42	.	.	PUNCT
cana-1859	124	1	the	the	DET
cana-1859	124	2	urdhva	urdhva	PROPN
cana-1859	124	3	-	-	PUNCT
cana-1859	124	4	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	124	5	sutra	sutra	NOUN
cana-1859	124	6	modifies	modify	VERB
cana-1859	124	7	the	the	DET
cana-1859	124	8	multiplication	multiplication	NOUN
cana-1859	124	9	process	process	NOUN
cana-1859	124	10	within	within	ADP
cana-1859	124	11	this	this	DET
cana-1859	124	12	convolution	convolution	NOUN
cana-1859	124	13	operation	operation	NOUN
cana-1859	124	14	.	.	PUNCT
cana-1859	125	1	instead	instead	ADV
cana-1859	125	2	of	of	ADP
cana-1859	125	3	conventional	conventional	ADJ
cana-1859	125	4	multiplication	multiplication	NOUN
cana-1859	125	5	,	,	PUNCT
cana-1859	125	6	the	the	DET
cana-1859	125	7	sutra	sutra	NOUN
cana-1859	125	8	suggests	suggest	VERB
cana-1859	125	9	a	a	DET
cana-1859	125	10	method	method	NOUN
cana-1859	125	11	where	where	SCONJ
cana-1859	125	12	elements	element	NOUN
cana-1859	125	13	are	be	AUX
cana-1859	125	14	multiplied	multiply	VERB
cana-1859	125	15	in	in	ADP
cana-1859	125	16	a	a	DET
cana-1859	125	17	crosswise	crosswise	NOUN
cana-1859	125	18	pattern	pattern	NOUN
cana-1859	125	19	and	and	CCONJ
cana-1859	125	20	their	their	PRON
cana-1859	125	21	results	result	NOUN
cana-1859	125	22	are	be	AUX
cana-1859	125	23	added	add	VERB
cana-1859	125	24	together	together	ADV
cana-1859	125	25	.	.	PUNCT
cana-1859	126	1	this	this	DET
cana-1859	126	2	approach	approach	NOUN
cana-1859	126	3	can	can	AUX
cana-1859	126	4	be	be	AUX
cana-1859	126	5	more	more	ADV
cana-1859	126	6	efficient	efficient	ADJ
cana-1859	126	7	,	,	PUNCT
cana-1859	126	8	especially	especially	ADV
cana-1859	126	9	when	when	SCONJ
cana-1859	126	10	dealing	deal	VERB
cana-1859	126	11	with	with	ADP
cana-1859	126	12	large	large	ADJ
cana-1859	126	13	matrices	matrix	NOUN
cana-1859	126	14	or	or	CCONJ
cana-1859	126	15	kernels	kernel	NOUN
cana-1859	126	16	.	.	PUNCT
cana-1859	127	1	let	let	VERB
cana-1859	127	2	's	us	PRON
cana-1859	127	3	consider	consider	VERB
cana-1859	127	4	a	a	DET
cana-1859	127	5	simplified	simplified	ADJ
cana-1859	127	6	case	case	NOUN
cana-1859	127	7	with	with	ADP
cana-1859	127	8	a	a	DET
cana-1859	127	9	2x2	2x2	NUM
cana-1859	127	10	kernel	kernel	NOUN
cana-1859	127	11	for	for	ADP
cana-1859	127	12	demonstration	demonstration	NOUN
cana-1859	127	13	via	via	ADP
cana-1859	127	14	equations	equation	NOUN
cana-1859	127	15	7	7	NUM
cana-1859	127	16	&	&	CCONJ
cana-1859	127	17	8	8	NUM
cana-1859	127	18	,	,	PUNCT
cana-1859	127	19	𝐾	𝐾	PROPN
cana-1859	127	20	=	=	PUNCT
cana-1859	128	1	[	[	X
cana-1859	128	2	𝑘00	𝑘00	NOUN
cana-1859	128	3	𝑘01	𝑘01	NOUN
cana-1859	128	4	𝑘10	𝑘10	NOUN
cana-1859	128	5	𝑘11	𝑘11	PROPN
cana-1859	128	6	]	]	X
cana-1859	128	7	…	…	PUNCT
cana-1859	128	8	(	(	PUNCT
cana-1859	128	9	7	7	X
cana-1859	128	10	)	)	PUNCT
cana-1859	128	11	𝐼	𝐼	NOUN
cana-1859	128	12	=	=	PUNCT
cana-1859	129	1	[	[	X
cana-1859	129	2	𝑖00	𝑖00	NOUN
cana-1859	129	3	𝑖01	𝑖01	NOUN
cana-1859	129	4	𝑖10	𝑖10	NOUN
cana-1859	129	5	𝑖11	𝑖11	PROPN
cana-1859	129	6	]	]	PUNCT
cana-1859	129	7	…	…	PUNCT
cana-1859	129	8	(	(	PUNCT
cana-1859	129	9	8)	8)	NUM
cana-1859	129	10	using	use	VERB
cana-1859	129	11	urdhva	urdhva	NOUN
cana-1859	129	12	-	-	PUNCT
cana-1859	129	13	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	129	14	,	,	PUNCT
cana-1859	129	15	the	the	DET
cana-1859	129	16	multiplication	multiplication	NOUN
cana-1859	129	17	and	and	CCONJ
cana-1859	129	18	addition	addition	NOUN
cana-1859	129	19	for	for	ADP
cana-1859	129	20	one	one	NUM
cana-1859	129	21	element	element	NOUN
cana-1859	129	22	in	in	ADP
cana-1859	129	23	the	the	DET
cana-1859	129	24	feature	feature	NOUN
cana-1859	129	25	map	map	NOUN
cana-1859	129	26	is	be	AUX
cana-1859	129	27	represented	represent	VERB
cana-1859	129	28	via	via	ADP
cana-1859	129	29	equation	equation	NOUN
cana-1859	129	30	9	9	NUM
cana-1859	129	31	,	,	PUNCT
cana-1859	129	32	𝐹𝑖𝑗	𝐹𝑖𝑗	NOUN
cana-1859	129	33	=	=	SYM
cana-1859	129	34	(	(	PUNCT
cana-1859	129	35	𝑘00	𝑘00	PROPN
cana-1859	129	36	×	×	PROPN
cana-1859	129	37	𝑖00	𝑖00	PROPN
cana-1859	130	1	+	+	CCONJ
cana-1859	130	2	𝑘11	𝑘11	PROPN
cana-1859	130	3	×	×	PROPN
cana-1859	130	4	𝑖11	𝑖11	NOUN
cana-1859	130	5	)	)	PUNCT
cana-1859	131	1	+	+	CCONJ
cana-1859	131	2	(	(	PUNCT
cana-1859	131	3	𝑘01	𝑘01	NOUN
cana-1859	131	4	×	×	PROPN
cana-1859	131	5	𝑖10	𝑖10	NOUN
cana-1859	131	6	+	+	CCONJ
cana-1859	131	7	𝑘10	𝑘10	VERB
cana-1859	131	8	×	×	PROPN
cana-1859	131	9	𝑖01	𝑖01	PROPN
cana-1859	131	10	)	)	PUNCT
cana-1859	131	11	…	…	PUNCT
cana-1859	131	12	(	(	PUNCT
cana-1859	131	13	9	9	X
cana-1859	131	14	)	)	PUNCT
cana-1859	131	15	communications	communication	NOUN
cana-1859	131	16	on	on	ADP
cana-1859	131	17	applied	apply	VERB
cana-1859	131	18	nonlinear	nonlinear	ADJ
cana-1859	131	19	analysis	analysis	NOUN
cana-1859	131	20	issn	issn	NOUN
cana-1859	131	21	:	:	PUNCT
cana-1859	131	22	1074	1074	NUM
cana-1859	131	23	-	-	PUNCT
cana-1859	131	24	133x	133x	NUM
cana-1859	131	25	vol	vol	NOUN
cana-1859	131	26	32	32	NUM
cana-1859	131	27	no	no	NOUN
cana-1859	131	28	.	.	NOUN
cana-1859	131	29	2	2	NUM
cana-1859	131	30	(	(	PUNCT
cana-1859	131	31	2025	2025	NUM
cana-1859	131	32	)	)	PUNCT
cana-1859	131	33	646	646	NUM
cana-1859	131	34	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	131	35	this	this	DET
cana-1859	131	36	simplifies	simplify	VERB
cana-1859	131	37	the	the	DET
cana-1859	131	38	conventional	conventional	ADJ
cana-1859	131	39	dot	dot	NOUN
cana-1859	131	40	product	product	NOUN
cana-1859	131	41	operation	operation	NOUN
cana-1859	131	42	by	by	ADP
cana-1859	131	43	reducing	reduce	VERB
cana-1859	131	44	the	the	DET
cana-1859	131	45	computational	computational	ADJ
cana-1859	131	46	steps	step	NOUN
cana-1859	131	47	involved	involve	VERB
cana-1859	131	48	in	in	ADP
cana-1859	131	49	multiplication	multiplication	NOUN
cana-1859	131	50	.	.	PUNCT
cana-1859	132	1	reasons	reason	NOUN
cana-1859	132	2	for	for	ADP
cana-1859	132	3	improvement	improvement	NOUN
cana-1859	132	4	in	in	ADP
cana-1859	132	5	performance	performance	NOUN
cana-1859	132	6	1	1	NUM
cana-1859	132	7	.	.	PUNCT
cana-1859	132	8	reduced	reduce	VERB
cana-1859	132	9	computational	computational	ADJ
cana-1859	132	10	complexity	complexity	NOUN
cana-1859	132	11	:	:	PUNCT
cana-1859	132	12	the	the	DET
cana-1859	132	13	crosswise	crosswise	NOUN
cana-1859	132	14	multiplication	multiplication	NOUN
cana-1859	132	15	approach	approach	NOUN
cana-1859	132	16	can	can	AUX
cana-1859	132	17	be	be	AUX
cana-1859	132	18	computationally	computationally	ADV
cana-1859	132	19	less	less	ADV
cana-1859	132	20	intensive	intensive	ADJ
cana-1859	132	21	,	,	PUNCT
cana-1859	132	22	especially	especially	ADV
cana-1859	132	23	for	for	ADP
cana-1859	132	24	larger	large	ADJ
cana-1859	132	25	kernels	kernel	NOUN
cana-1859	132	26	,	,	PUNCT
cana-1859	132	27	thereby	thereby	ADV
cana-1859	132	28	speeding	speed	VERB
cana-1859	132	29	up	up	ADP
cana-1859	132	30	the	the	DET
cana-1859	132	31	convolution	convolution	NOUN
cana-1859	132	32	process	process	NOUN
cana-1859	132	33	.	.	PUNCT
cana-1859	133	1	2	2	X
cana-1859	133	2	.	.	X
cana-1859	133	3	parallel	parallel	ADJ
cana-1859	133	4	processing	processing	NOUN
cana-1859	133	5	:	:	PUNCT
cana-1859	133	6	this	this	DET
cana-1859	133	7	method	method	NOUN
cana-1859	133	8	lends	lend	VERB
cana-1859	133	9	itself	itself	PRON
cana-1859	133	10	well	well	ADV
cana-1859	133	11	to	to	ADP
cana-1859	133	12	parallel	parallel	VERB
cana-1859	133	13	processing	processing	NOUN
cana-1859	133	14	.	.	PUNCT
cana-1859	134	1	modern	modern	ADJ
cana-1859	134	2	processors	processor	NOUN
cana-1859	134	3	and	and	CCONJ
cana-1859	134	4	gpus	gpu	NOUN
cana-1859	134	5	,	,	PUNCT
cana-1859	134	6	which	which	PRON
cana-1859	134	7	excel	excel	VERB
cana-1859	134	8	at	at	ADP
cana-1859	134	9	handling	handle	VERB
cana-1859	134	10	parallel	parallel	ADJ
cana-1859	134	11	tasks	task	NOUN
cana-1859	134	12	,	,	PUNCT
cana-1859	134	13	can	can	AUX
cana-1859	134	14	execute	execute	VERB
cana-1859	134	15	these	these	DET
cana-1859	134	16	operations	operation	NOUN
cana-1859	134	17	more	more	ADV
cana-1859	134	18	efficiently	efficiently	ADV
cana-1859	134	19	,	,	PUNCT
cana-1859	134	20	leading	lead	VERB
cana-1859	134	21	to	to	ADP
cana-1859	134	22	faster	fast	ADJ
cana-1859	134	23	computations	computation	NOUN
cana-1859	134	24	.	.	PUNCT
cana-1859	135	1	3	3	X
cana-1859	135	2	.	.	X
cana-1859	135	3	optimization	optimization	NOUN
cana-1859	135	4	in	in	ADP
cana-1859	135	5	hardware	hardware	NOUN
cana-1859	135	6	utilization	utilization	NOUN
cana-1859	135	7	:	:	PUNCT
cana-1859	135	8	the	the	DET
cana-1859	135	9	urdhva	urdhva	ADJ
cana-1859	135	10	-	-	PUNCT
cana-1859	135	11	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	135	12	sutra	sutra	NOUN
cana-1859	135	13	's	's	PART
cana-1859	135	14	approach	approach	NOUN
cana-1859	135	15	can	can	AUX
cana-1859	135	16	be	be	AUX
cana-1859	135	17	more	more	ADJ
cana-1859	135	18	hardware	hardware	NOUN
cana-1859	135	19	-	-	PUNCT
cana-1859	135	20	friendly	friendly	ADJ
cana-1859	135	21	,	,	PUNCT
cana-1859	135	22	potentially	potentially	ADV
cana-1859	135	23	leading	lead	VERB
cana-1859	135	24	to	to	ADP
cana-1859	135	25	better	well	ADJ
cana-1859	135	26	utilization	utilization	NOUN
cana-1859	135	27	of	of	ADP
cana-1859	135	28	the	the	DET
cana-1859	135	29	underlying	underlie	VERB
cana-1859	135	30	architecture	architecture	NOUN
cana-1859	135	31	,	,	PUNCT
cana-1859	135	32	especially	especially	ADV
cana-1859	135	33	in	in	ADP
cana-1859	135	34	specialized	specialized	ADJ
cana-1859	135	35	ai	ai	NOUN
cana-1859	135	36	and	and	CCONJ
cana-1859	135	37	deep	deep	ADJ
cana-1859	135	38	learning	learning	NOUN
cana-1859	135	39	hardware	hardware	NOUN
cana-1859	135	40	.	.	PUNCT
cana-1859	136	1	4	4	X
cana-1859	136	2	.	.	X
cana-1859	136	3	scalability	scalability	NOUN
cana-1859	136	4	:	:	PUNCT
cana-1859	136	5	this	this	DET
cana-1859	136	6	method	method	NOUN
cana-1859	136	7	scales	scale	VERB
cana-1859	136	8	well	well	ADV
cana-1859	136	9	with	with	ADP
cana-1859	136	10	increasing	increase	VERB
cana-1859	136	11	kernel	kernel	NOUN
cana-1859	136	12	sizes	size	NOUN
cana-1859	136	13	and	and	CCONJ
cana-1859	136	14	input	input	NOUN
cana-1859	136	15	dimensions	dimension	NOUN
cana-1859	136	16	,	,	PUNCT
cana-1859	136	17	making	make	VERB
cana-1859	136	18	it	it	PRON
cana-1859	136	19	a	a	DET
cana-1859	136	20	robust	robust	ADJ
cana-1859	136	21	choice	choice	NOUN
cana-1859	136	22	for	for	ADP
cana-1859	136	23	larger	large	ADJ
cana-1859	136	24	,	,	PUNCT
cana-1859	136	25	more	more	ADV
cana-1859	136	26	complex	complex	ADJ
cana-1859	136	27	cnn	cnn	PROPN
cana-1859	136	28	architectures	architecture	NOUN
cana-1859	136	29	.	.	PUNCT
cana-1859	137	1	thus	thus	ADV
cana-1859	137	2	,	,	PUNCT
cana-1859	137	3	the	the	DET
cana-1859	137	4	application	application	NOUN
cana-1859	137	5	of	of	ADP
cana-1859	137	6	the	the	DET
cana-1859	137	7	urdhva	urdhva	ADJ
cana-1859	137	8	-	-	PUNCT
cana-1859	137	9	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	137	10	sutra	sutra	NOUN
cana-1859	137	11	in	in	ADP
cana-1859	137	12	cnns	cnns	PROPN
cana-1859	137	13	,	,	PUNCT
cana-1859	137	14	particularly	particularly	ADV
cana-1859	137	15	in	in	ADP
cana-1859	137	16	the	the	DET
cana-1859	137	17	convolution	convolution	NOUN
cana-1859	137	18	operations	operation	NOUN
cana-1859	137	19	,	,	PUNCT
cana-1859	137	20	introduces	introduce	VERB
cana-1859	137	21	a	a	DET
cana-1859	137	22	more	more	ADV
cana-1859	137	23	efficient	efficient	ADJ
cana-1859	137	24	computational	computational	ADJ
cana-1859	137	25	method	method	NOUN
cana-1859	137	26	.	.	PUNCT
cana-1859	138	1	this	this	DET
cana-1859	138	2	efficiency	efficiency	NOUN
cana-1859	138	3	is	be	AUX
cana-1859	138	4	derived	derive	VERB
cana-1859	138	5	from	from	ADP
cana-1859	138	6	the	the	DET
cana-1859	138	7	sutra	sutra	NOUN
cana-1859	138	8	’s	’s	PART
cana-1859	138	9	unique	unique	ADJ
cana-1859	138	10	approach	approach	NOUN
cana-1859	138	11	to	to	ADP
cana-1859	138	12	multiplication	multiplication	NOUN
cana-1859	138	13	,	,	PUNCT
cana-1859	138	14	which	which	PRON
cana-1859	138	15	can	can	AUX
cana-1859	138	16	reduce	reduce	VERB
cana-1859	138	17	computational	computational	ADJ
cana-1859	138	18	time	time	NOUN
cana-1859	138	19	and	and	CCONJ
cana-1859	138	20	resources	resource	NOUN
cana-1859	138	21	,	,	PUNCT
cana-1859	138	22	thereby	thereby	ADV
cana-1859	138	23	enhancing	enhance	VERB
cana-1859	138	24	the	the	DET
cana-1859	138	25	overall	overall	ADJ
cana-1859	138	26	performance	performance	NOUN
cana-1859	138	27	of	of	ADP
cana-1859	138	28	the	the	DET
cana-1859	138	29	cnn	cnn	PROPN
cana-1859	138	30	,	,	PUNCT
cana-1859	138	31	especially	especially	ADV
cana-1859	138	32	in	in	ADP
cana-1859	138	33	processing	process	VERB
cana-1859	138	34	large	large	ADJ
cana-1859	138	35	and	and	CCONJ
cana-1859	138	36	complex	complex	ADJ
cana-1859	138	37	datasets	dataset	NOUN
cana-1859	138	38	&	&	CCONJ
cana-1859	138	39	samples	sample	NOUN
cana-1859	138	40	.	.	PUNCT
cana-1859	139	1	similarly	similarly	ADV
cana-1859	139	2	,	,	PUNCT
cana-1859	139	3	the	the	DET
cana-1859	139	4	anurupyena	anurupyena	PROPN
cana-1859	139	5	sutra	sutra	NOUN
cana-1859	139	6	,	,	PUNCT
cana-1859	139	7	another	another	DET
cana-1859	139	8	principle	principle	NOUN
cana-1859	139	9	from	from	ADP
cana-1859	139	10	vedic	vedic	ADJ
cana-1859	139	11	mathematics	mathematic	NOUN
cana-1859	139	12	,	,	PUNCT
cana-1859	139	13	is	be	AUX
cana-1859	139	14	traditionally	traditionally	ADV
cana-1859	139	15	translated	translate	VERB
cana-1859	139	16	as	as	ADP
cana-1859	139	17	"	"	PUNCT
cana-1859	139	18	proportionality	proportionality	NOUN
cana-1859	139	19	.	.	PUNCT
cana-1859	139	20	"	"	PUNCT
cana-1859	140	1	this	this	DET
cana-1859	140	2	sutra	sutra	NOUN
cana-1859	140	3	is	be	AUX
cana-1859	140	4	utilized	utilize	VERB
cana-1859	140	5	to	to	PART
cana-1859	140	6	simplify	simplify	VERB
cana-1859	140	7	complex	complex	ADJ
cana-1859	140	8	calculations	calculation	NOUN
cana-1859	140	9	,	,	PUNCT
cana-1859	140	10	particularly	particularly	ADV
cana-1859	140	11	those	those	PRON
cana-1859	140	12	involving	involve	VERB
cana-1859	140	13	ratios	ratio	NOUN
cana-1859	140	14	or	or	CCONJ
cana-1859	140	15	proportions	proportion	NOUN
cana-1859	140	16	,	,	PUNCT
cana-1859	140	17	which	which	PRON
cana-1859	140	18	are	be	AUX
cana-1859	140	19	common	common	ADJ
cana-1859	140	20	in	in	ADP
cana-1859	140	21	various	various	ADJ
cana-1859	140	22	algorithms	algorithm	NOUN
cana-1859	140	23	,	,	PUNCT
cana-1859	140	24	including	include	VERB
cana-1859	140	25	those	those	PRON
cana-1859	140	26	in	in	ADP
cana-1859	140	27	neural	neural	ADJ
cana-1859	140	28	networks	network	NOUN
cana-1859	140	29	.	.	PUNCT
cana-1859	141	1	in	in	ADP
cana-1859	141	2	the	the	DET
cana-1859	141	3	context	context	NOUN
cana-1859	141	4	of	of	ADP
cana-1859	141	5	convolutional	convolutional	ADJ
cana-1859	141	6	neural	neural	ADJ
cana-1859	141	7	networks	network	NOUN
cana-1859	141	8	(	(	PUNCT
cana-1859	141	9	cnns	cnns	PROPN
cana-1859	141	10	)	)	PUNCT
cana-1859	141	11	,	,	PUNCT
cana-1859	141	12	this	this	DET
cana-1859	141	13	sutra	sutra	NOUN
cana-1859	141	14	can	can	AUX
cana-1859	141	15	be	be	AUX
cana-1859	141	16	leveraged	leverage	VERB
cana-1859	141	17	to	to	PART
cana-1859	141	18	optimize	optimize	VERB
cana-1859	141	19	operations	operation	NOUN
cana-1859	141	20	that	that	PRON
cana-1859	141	21	involve	involve	VERB
cana-1859	141	22	ratios	ratio	NOUN
cana-1859	141	23	or	or	CCONJ
cana-1859	141	24	scaling	scale	VERB
cana-1859	141	25	factors	factor	NOUN
cana-1859	141	26	.	.	PUNCT
cana-1859	142	1	anurupyena	anurupyena	ADP
cana-1859	142	2	sutra	sutra	ADJ
cana-1859	142	3	simplifies	simplifie	NOUN
cana-1859	142	4	calculations	calculation	NOUN
cana-1859	142	5	involving	involve	VERB
cana-1859	142	6	proportions	proportion	NOUN
cana-1859	142	7	by	by	ADP
cana-1859	142	8	adjusting	adjust	VERB
cana-1859	142	9	the	the	DET
cana-1859	142	10	numbers	number	NOUN
cana-1859	142	11	to	to	ADP
cana-1859	142	12	more	more	ADV
cana-1859	142	13	manageable	manageable	ADJ
cana-1859	142	14	values	value	NOUN
cana-1859	142	15	while	while	SCONJ
cana-1859	142	16	maintaining	maintain	VERB
cana-1859	142	17	their	their	PRON
cana-1859	142	18	ratio	ratio	NOUN
cana-1859	142	19	.	.	PUNCT
cana-1859	143	1	this	this	PRON
cana-1859	143	2	is	be	AUX
cana-1859	143	3	particularly	particularly	ADV
cana-1859	143	4	useful	useful	ADJ
cana-1859	143	5	in	in	ADP
cana-1859	143	6	scaling	scale	VERB
cana-1859	143	7	operations	operation	NOUN
cana-1859	143	8	or	or	CCONJ
cana-1859	143	9	when	when	SCONJ
cana-1859	143	10	dealing	deal	VERB
cana-1859	143	11	with	with	ADP
cana-1859	143	12	large	large	ADJ
cana-1859	143	13	numbers	number	NOUN
cana-1859	143	14	that	that	PRON
cana-1859	143	15	can	can	AUX
cana-1859	143	16	be	be	AUX
cana-1859	143	17	simplified	simplify	VERB
cana-1859	143	18	into	into	ADP
cana-1859	143	19	smaller	small	ADJ
cana-1859	143	20	,	,	PUNCT
cana-1859	143	21	proportional	proportional	ADJ
cana-1859	143	22	values	value	NOUN
cana-1859	143	23	for	for	ADP
cana-1859	143	24	easier	easy	ADJ
cana-1859	143	25	computation	computation	NOUN
cana-1859	143	26	.	.	PUNCT
cana-1859	144	1	in	in	ADP
cana-1859	144	2	cnns	cnns	PROPN
cana-1859	144	3	,	,	PUNCT
cana-1859	144	4	several	several	ADJ
cana-1859	144	5	operations	operation	NOUN
cana-1859	144	6	involve	involve	VERB
cana-1859	144	7	ratios	ratio	NOUN
cana-1859	144	8	or	or	CCONJ
cana-1859	144	9	scaling	scale	VERB
cana-1859	144	10	factors	factor	NOUN
cana-1859	144	11	,	,	PUNCT
cana-1859	144	12	such	such	ADJ
cana-1859	144	13	as	as	ADP
cana-1859	144	14	batch	batch	NOUN
cana-1859	144	15	normalization	normalization	NOUN
cana-1859	144	16	,	,	PUNCT
cana-1859	144	17	learning	learn	VERB
cana-1859	144	18	rate	rate	NOUN
cana-1859	144	19	adjustments	adjustment	NOUN
cana-1859	144	20	in	in	ADP
cana-1859	144	21	optimization	optimization	NOUN
cana-1859	144	22	algorithms	algorithm	NOUN
cana-1859	144	23	,	,	PUNCT
cana-1859	144	24	or	or	CCONJ
cana-1859	144	25	even	even	ADV
cana-1859	144	26	pooling	pool	VERB
cana-1859	144	27	layers	layer	NOUN
cana-1859	144	28	.	.	PUNCT
cana-1859	145	1	the	the	DET
cana-1859	145	2	anurupyena	anurupyena	ADJ
cana-1859	145	3	sutra	sutra	NOUN
cana-1859	145	4	can	can	AUX
cana-1859	145	5	optimize	optimize	VERB
cana-1859	145	6	these	these	DET
cana-1859	145	7	operations	operation	NOUN
cana-1859	145	8	by	by	ADP
cana-1859	145	9	simplifying	simplify	VERB
cana-1859	145	10	the	the	DET
cana-1859	145	11	proportional	proportional	ADJ
cana-1859	145	12	relationships	relationship	NOUN
cana-1859	145	13	involved	involve	VERB
cana-1859	145	14	for	for	ADP
cana-1859	145	15	different	different	ADJ
cana-1859	145	16	scenarios	scenario	NOUN
cana-1859	145	17	.	.	PUNCT
cana-1859	146	1	consider	consider	VERB
cana-1859	146	2	an	an	DET
cana-1859	146	3	operation	operation	NOUN
cana-1859	146	4	like	like	ADP
cana-1859	146	5	batch	batch	NOUN
cana-1859	146	6	normalization	normalization	NOUN
cana-1859	146	7	,	,	PUNCT
cana-1859	146	8	which	which	PRON
cana-1859	146	9	is	be	AUX
cana-1859	146	10	essential	essential	ADJ
cana-1859	146	11	for	for	ADP
cana-1859	146	12	stabilizing	stabilize	VERB
cana-1859	146	13	and	and	CCONJ
cana-1859	146	14	accelerating	accelerate	VERB
cana-1859	146	15	the	the	DET
cana-1859	146	16	training	training	NOUN
cana-1859	146	17	of	of	ADP
cana-1859	146	18	deep	deep	ADJ
cana-1859	146	19	networks	network	NOUN
cana-1859	146	20	.	.	PUNCT
cana-1859	147	1	the	the	DET
cana-1859	147	2	conventional	conventional	ADJ
cana-1859	147	3	batch	batch	NOUN
cana-1859	147	4	normalization	normalization	NOUN
cana-1859	147	5	formula	formula	NOUN
cana-1859	147	6	is	be	AUX
cana-1859	147	7	represented	represent	VERB
cana-1859	147	8	via	via	ADP
cana-1859	147	9	equation	equation	NOUN
cana-1859	147	10	10	10	NUM
cana-1859	147	11	,	,	PUNCT
cana-1859	147	12	𝐵𝑁(𝑥𝑖	𝐵𝑁(𝑥𝑖	PROPN
cana-1859	147	13	)	)	PUNCT
cana-1859	147	14	=	=	SYM
cana-1859	147	15	𝛾(𝜎𝐵2	𝛾(𝜎𝐵2	X
cana-1859	147	16	+	+	SYM
cana-1859	147	17	𝜖𝑥𝑖	𝜖𝑥𝑖	NOUN
cana-1859	147	18	−	−	PROPN
cana-1859	147	19	𝜇𝐵	𝜇𝐵	NOUN
cana-1859	147	20	)	)	PUNCT
cana-1859	148	1	+	+	NUM
cana-1859	148	2	𝛽	𝛽	NOUN
cana-1859	148	3	…	…	PUNCT
cana-1859	148	4	(	(	PUNCT
cana-1859	148	5	10	10	NUM
cana-1859	148	6	)	)	PUNCT
cana-1859	148	7	communications	communication	NOUN
cana-1859	148	8	on	on	ADP
cana-1859	148	9	applied	apply	VERB
cana-1859	148	10	nonlinear	nonlinear	ADJ
cana-1859	148	11	analysis	analysis	NOUN
cana-1859	148	12	issn	issn	NOUN
cana-1859	148	13	:	:	PUNCT
cana-1859	148	14	1074	1074	NUM
cana-1859	148	15	-	-	PUNCT
cana-1859	148	16	133x	133x	NUM
cana-1859	148	17	vol	vol	NOUN
cana-1859	148	18	32	32	NUM
cana-1859	148	19	no	no	NOUN
cana-1859	148	20	.	.	NOUN
cana-1859	148	21	2	2	NUM
cana-1859	148	22	(	(	PUNCT
cana-1859	148	23	2025	2025	NUM
cana-1859	148	24	)	)	PUNCT
cana-1859	148	25	647	647	NUM
cana-1859	148	26	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	148	27	where	where	SCONJ
cana-1859	148	28	,	,	PUNCT
cana-1859	148	29	xi	xi	X
cana-1859	148	30	is	be	AUX
cana-1859	148	31	the	the	DET
cana-1859	148	32	input	input	NOUN
cana-1859	148	33	,	,	PUNCT
cana-1859	148	34	μb	μb	PROPN
cana-1859	148	35	is	be	AUX
cana-1859	148	36	the	the	DET
cana-1859	148	37	mean	mean	NOUN
cana-1859	148	38	of	of	ADP
cana-1859	148	39	the	the	DET
cana-1859	148	40	batch	batch	NOUN
cana-1859	148	41	,	,	PUNCT
cana-1859	148	42	𝜎𝐵2	𝜎𝐵2	PROPN
cana-1859	148	43	is	be	AUX
cana-1859	148	44	the	the	DET
cana-1859	148	45	variance	variance	NOUN
cana-1859	148	46	,	,	PUNCT
cana-1859	148	47	ϵ	ϵ	PROPN
cana-1859	148	48	is	be	AUX
cana-1859	148	49	a	a	DET
cana-1859	148	50	small	small	ADJ
cana-1859	148	51	constant	constant	NOUN
cana-1859	148	52	for	for	ADP
cana-1859	148	53	numerical	numerical	ADJ
cana-1859	148	54	stability	stability	NOUN
cana-1859	148	55	,	,	PUNCT
cana-1859	148	56	and	and	CCONJ
cana-1859	148	57	γ	γ	PROPN
cana-1859	148	58	,	,	PUNCT
cana-1859	148	59	β	β	X
cana-1859	148	60	are	be	AUX
cana-1859	148	61	parameters	parameter	NOUN
cana-1859	148	62	to	to	PART
cana-1859	148	63	be	be	AUX
cana-1859	148	64	learned	learn	VERB
cana-1859	148	65	.	.	PUNCT
cana-1859	149	1	using	use	VERB
cana-1859	149	2	anurupyena	anurupyena	PROPN
cana-1859	149	3	sutra	sutra	NOUN
cana-1859	149	4	,	,	PUNCT
cana-1859	149	5	this	this	PRON
cana-1859	149	6	can	can	AUX
cana-1859	149	7	be	be	AUX
cana-1859	149	8	optimized	optimize	VERB
cana-1859	149	9	by	by	ADP
cana-1859	149	10	simplifying	simplify	VERB
cana-1859	149	11	the	the	DET
cana-1859	149	12	ratio	ratio	NOUN
cana-1859	149	13	inside	inside	ADP
cana-1859	149	14	the	the	DET
cana-1859	149	15	normalization	normalization	NOUN
cana-1859	149	16	.	.	PUNCT
cana-1859	150	1	if	if	SCONJ
cana-1859	150	2	the	the	DET
cana-1859	150	3	ratio	ratio	NOUN
cana-1859	150	4	𝜎𝐵2	𝜎𝐵2	PROPN
cana-1859	150	5	+	+	CCONJ
cana-1859	150	6	𝜖𝜇𝐵	𝜖𝜇𝐵	PRON
cana-1859	150	7	can	can	AUX
cana-1859	150	8	be	be	AUX
cana-1859	150	9	approximated	approximate	VERB
cana-1859	150	10	or	or	CCONJ
cana-1859	150	11	adjusted	adjust	VERB
cana-1859	150	12	to	to	ADP
cana-1859	150	13	a	a	DET
cana-1859	150	14	simpler	simple	ADJ
cana-1859	150	15	proportional	proportional	ADJ
cana-1859	150	16	value	value	NOUN
cana-1859	150	17	while	while	SCONJ
cana-1859	150	18	maintaining	maintain	VERB
cana-1859	150	19	the	the	DET
cana-1859	150	20	relationship	relationship	NOUN
cana-1859	150	21	,	,	PUNCT
cana-1859	150	22	the	the	DET
cana-1859	150	23	computation	computation	NOUN
cana-1859	150	24	becomes	become	VERB
cana-1859	150	25	more	more	ADV
cana-1859	150	26	efficient	efficient	ADJ
cana-1859	150	27	.	.	PUNCT
cana-1859	151	1	let	let	VERB
cana-1859	151	2	's	us	PRON
cana-1859	151	3	consider	consider	VERB
cana-1859	151	4	a	a	DET
cana-1859	151	5	simplified	simplified	ADJ
cana-1859	151	6	proportional	proportional	ADJ
cana-1859	151	7	adjustment	adjustment	NOUN
cana-1859	151	8	via	via	ADP
cana-1859	151	9	equation	equation	NOUN
cana-1859	151	10	11	11	NUM
cana-1859	151	11	,	,	PUNCT
cana-1859	152	1	𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑𝑅𝑎𝑡𝑖𝑜	𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑𝑅𝑎𝑡𝑖𝑜	PROPN
cana-1859	152	2	=	=	SYM
cana-1859	152	3	𝑃𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛𝑎𝑙𝐴𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡(𝜎𝐵2	𝑃𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛𝑎𝑙𝐴𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡(𝜎𝐵2	PROPN
cana-1859	152	4	+	+	CCONJ
cana-1859	152	5	𝜖𝜇𝐵	𝜖𝜇𝐵	NOUN
cana-1859	152	6	)	)	PUNCT
cana-1859	152	7	…	…	PUNCT
cana-1859	152	8	(	(	PUNCT
cana-1859	152	9	11	11	NUM
cana-1859	152	10	)	)	PUNCT
cana-1859	152	11	then	then	ADV
cana-1859	152	12	the	the	DET
cana-1859	152	13	batch	batch	NOUN
cana-1859	152	14	normalization	normalization	NOUN
cana-1859	152	15	can	can	AUX
cana-1859	152	16	be	be	AUX
cana-1859	152	17	rewritten	rewrite	VERB
cana-1859	152	18	via	via	ADP
cana-1859	152	19	equation	equation	NOUN
cana-1859	152	20	12	12	NUM
cana-1859	152	21	,	,	PUNCT
cana-1859	152	22	𝐵𝑁(𝑥𝑖	𝐵𝑁(𝑥𝑖	PROPN
cana-1859	152	23	)	)	PUNCT
cana-1859	152	24	=	=	PUNCT
cana-1859	153	1	𝛾	𝛾	ADP
cana-1859	153	2	×	×	NOUN
cana-1859	153	3	(	(	PUNCT
cana-1859	153	4	𝑥𝑖	𝑥𝑖	NUM
cana-1859	153	5	×	×	PROPN
cana-1859	153	6	𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑𝑅𝑎𝑡𝑖𝑜	𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑𝑅𝑎𝑡𝑖𝑜	PROPN
cana-1859	153	7	)	)	PUNCT
cana-1859	154	1	+	+	NUM
cana-1859	154	2	𝛽	𝛽	NOUN
cana-1859	154	3	…	…	PUNCT
cana-1859	154	4	(	(	PUNCT
cana-1859	154	5	12	12	NUM
cana-1859	154	6	)	)	PUNCT
cana-1859	154	7	this	this	PRON
cana-1859	154	8	represents	represent	VERB
cana-1859	154	9	a	a	DET
cana-1859	154	10	simplification	simplification	NOUN
cana-1859	154	11	where	where	SCONJ
cana-1859	154	12	the	the	DET
cana-1859	154	13	complex	complex	ADJ
cana-1859	154	14	ratio	ratio	NOUN
cana-1859	154	15	is	be	AUX
cana-1859	154	16	adjusted	adjust	VERB
cana-1859	154	17	to	to	ADP
cana-1859	154	18	a	a	DET
cana-1859	154	19	simpler	simple	ADJ
cana-1859	154	20	proportional	proportional	ADJ
cana-1859	154	21	value	value	NOUN
cana-1859	154	22	while	while	SCONJ
cana-1859	154	23	maintaining	maintain	VERB
cana-1859	154	24	the	the	DET
cana-1859	154	25	overall	overall	ADJ
cana-1859	154	26	effect	effect	NOUN
cana-1859	154	27	of	of	ADP
cana-1859	154	28	normalization	normalization	NOUN
cana-1859	154	29	process	process	NOUN
cana-1859	154	30	.	.	PUNCT
cana-1859	155	1	reasons	reason	NOUN
cana-1859	155	2	for	for	ADP
cana-1859	155	3	improvement	improvement	NOUN
cana-1859	155	4	in	in	ADP
cana-1859	155	5	performance	performance	NOUN
cana-1859	155	6	1	1	NUM
cana-1859	155	7	.	.	PUNCT
cana-1859	155	8	computational	computational	ADJ
cana-1859	155	9	efficiency	efficiency	NOUN
cana-1859	155	10	:	:	PUNCT
cana-1859	155	11	by	by	ADP
cana-1859	155	12	simplifying	simplify	VERB
cana-1859	155	13	complex	complex	ADJ
cana-1859	155	14	ratios	ratio	NOUN
cana-1859	155	15	into	into	ADP
cana-1859	155	16	more	more	ADV
cana-1859	155	17	manageable	manageable	ADJ
cana-1859	155	18	proportional	proportional	ADJ
cana-1859	155	19	values	value	NOUN
cana-1859	155	20	,	,	PUNCT
cana-1859	155	21	the	the	DET
cana-1859	155	22	computational	computational	ADJ
cana-1859	155	23	complexity	complexity	NOUN
cana-1859	155	24	is	be	AUX
cana-1859	155	25	reduced	reduce	VERB
cana-1859	155	26	,	,	PUNCT
cana-1859	155	27	making	make	VERB
cana-1859	155	28	the	the	DET
cana-1859	155	29	operation	operation	NOUN
cana-1859	155	30	faster	fast	ADV
cana-1859	155	31	and	and	CCONJ
cana-1859	155	32	more	more	ADV
cana-1859	155	33	efficient	efficient	ADJ
cana-1859	155	34	.	.	PUNCT
cana-1859	156	1	2	2	X
cana-1859	156	2	.	.	X
cana-1859	156	3	enhanced	enhance	VERB
cana-1859	156	4	convergence	convergence	NOUN
cana-1859	156	5	in	in	ADP
cana-1859	156	6	training	training	NOUN
cana-1859	156	7	:	:	PUNCT
cana-1859	156	8	simplified	simplified	ADJ
cana-1859	156	9	and	and	CCONJ
cana-1859	156	10	efficient	efficient	ADJ
cana-1859	156	11	computations	computation	NOUN
cana-1859	156	12	can	can	AUX
cana-1859	156	13	lead	lead	VERB
cana-1859	156	14	to	to	ADP
cana-1859	156	15	more	more	ADV
cana-1859	156	16	stable	stable	ADJ
cana-1859	156	17	and	and	CCONJ
cana-1859	156	18	faster	fast	ADJ
cana-1859	156	19	convergence	convergence	NOUN
cana-1859	156	20	during	during	ADP
cana-1859	156	21	the	the	DET
cana-1859	156	22	training	training	NOUN
cana-1859	156	23	of	of	ADP
cana-1859	156	24	the	the	DET
cana-1859	156	25	cnn	cnn	PROPN
cana-1859	156	26	,	,	PUNCT
cana-1859	156	27	especially	especially	ADV
cana-1859	156	28	in	in	ADP
cana-1859	156	29	layers	layer	NOUN
cana-1859	156	30	like	like	ADP
cana-1859	156	31	batch	batch	NOUN
cana-1859	156	32	normalization	normalization	NOUN
cana-1859	156	33	that	that	PRON
cana-1859	156	34	directly	directly	ADV
cana-1859	156	35	influence	influence	VERB
cana-1859	156	36	the	the	DET
cana-1859	156	37	training	training	NOUN
cana-1859	156	38	process	process	NOUN
cana-1859	156	39	.	.	PUNCT
cana-1859	157	1	3	3	X
cana-1859	157	2	.	.	X
cana-1859	157	3	scalability	scalability	NOUN
cana-1859	157	4	and	and	CCONJ
cana-1859	157	5	flexibility	flexibility	NOUN
cana-1859	157	6	:	:	PUNCT
cana-1859	157	7	the	the	DET
cana-1859	157	8	sutra	sutra	NOUN
cana-1859	157	9	provides	provide	VERB
cana-1859	157	10	a	a	DET
cana-1859	157	11	scalable	scalable	ADJ
cana-1859	157	12	approach	approach	NOUN
cana-1859	157	13	to	to	ADP
cana-1859	157	14	handling	handle	VERB
cana-1859	157	15	complex	complex	ADJ
cana-1859	157	16	proportional	proportional	ADJ
cana-1859	157	17	calculations	calculation	NOUN
cana-1859	157	18	,	,	PUNCT
cana-1859	157	19	making	make	VERB
cana-1859	157	20	it	it	PRON
cana-1859	157	21	applicable	applicable	ADJ
cana-1859	157	22	to	to	ADP
cana-1859	157	23	various	various	ADJ
cana-1859	157	24	layers	layer	NOUN
cana-1859	157	25	and	and	CCONJ
cana-1859	157	26	operations	operation	NOUN
cana-1859	157	27	within	within	ADP
cana-1859	157	28	the	the	DET
cana-1859	157	29	cnn	cnn	PROPN
cana-1859	157	30	.	.	PUNCT
cana-1859	158	1	4	4	NUM
cana-1859	158	2	.	.	PUNCT
cana-1859	158	3	resource	resource	NOUN
cana-1859	158	4	optimization	optimization	NOUN
cana-1859	158	5	:	:	PUNCT
cana-1859	158	6	reducing	reduce	VERB
cana-1859	158	7	the	the	DET
cana-1859	158	8	computational	computational	ADJ
cana-1859	158	9	overhead	overhead	NOUN
cana-1859	158	10	through	through	ADP
cana-1859	158	11	simplified	simplified	ADJ
cana-1859	158	12	proportional	proportional	ADJ
cana-1859	158	13	calculations	calculation	NOUN
cana-1859	158	14	can	can	AUX
cana-1859	158	15	lead	lead	VERB
cana-1859	158	16	to	to	ADP
cana-1859	158	17	better	well	ADJ
cana-1859	158	18	utilization	utilization	NOUN
cana-1859	158	19	of	of	ADP
cana-1859	158	20	memory	memory	NOUN
cana-1859	158	21	and	and	CCONJ
cana-1859	158	22	processing	processing	NOUN
cana-1859	158	23	resources	resource	NOUN
cana-1859	158	24	,	,	PUNCT
cana-1859	158	25	especially	especially	ADV
cana-1859	158	26	in	in	ADP
cana-1859	158	27	large	large	ADJ
cana-1859	158	28	-	-	PUNCT
cana-1859	158	29	scale	scale	NOUN
cana-1859	158	30	neural	neural	ADJ
cana-1859	158	31	networks	network	NOUN
cana-1859	158	32	.	.	PUNCT
cana-1859	159	1	thus	thus	ADV
cana-1859	159	2	,	,	PUNCT
cana-1859	159	3	the	the	DET
cana-1859	159	4	application	application	NOUN
cana-1859	159	5	of	of	ADP
cana-1859	159	6	the	the	DET
cana-1859	159	7	anurupyena	anurupyena	ADJ
cana-1859	159	8	sutra	sutra	NOUN
cana-1859	159	9	in	in	ADP
cana-1859	159	10	cnns	cnns	PROPN
cana-1859	159	11	can	can	AUX
cana-1859	159	12	optimize	optimize	VERB
cana-1859	159	13	operations	operation	NOUN
cana-1859	159	14	involving	involve	VERB
cana-1859	159	15	ratios	ratio	NOUN
cana-1859	159	16	and	and	CCONJ
cana-1859	159	17	proportions	proportion	NOUN
cana-1859	159	18	,	,	PUNCT
cana-1859	159	19	such	such	ADJ
cana-1859	159	20	as	as	ADP
cana-1859	159	21	batch	batch	NOUN
cana-1859	159	22	normalization	normalization	NOUN
cana-1859	159	23	.	.	PUNCT
cana-1859	160	1	this	this	DET
cana-1859	160	2	optimization	optimization	NOUN
cana-1859	160	3	,	,	PUNCT
cana-1859	160	4	achieved	achieve	VERB
cana-1859	160	5	through	through	ADP
cana-1859	160	6	the	the	DET
cana-1859	160	7	simplification	simplification	NOUN
cana-1859	160	8	of	of	ADP
cana-1859	160	9	complex	complex	ADJ
cana-1859	160	10	proportional	proportional	ADJ
cana-1859	160	11	relationships	relationship	NOUN
cana-1859	160	12	,	,	PUNCT
cana-1859	160	13	can	can	AUX
cana-1859	160	14	lead	lead	VERB
cana-1859	160	15	to	to	ADP
cana-1859	160	16	improvements	improvement	NOUN
cana-1859	160	17	in	in	ADP
cana-1859	160	18	computational	computational	ADJ
cana-1859	160	19	efficiency	efficiency	NOUN
cana-1859	160	20	,	,	PUNCT
cana-1859	160	21	training	training	NOUN
cana-1859	160	22	stability	stability	NOUN
cana-1859	160	23	,	,	PUNCT
cana-1859	160	24	and	and	CCONJ
cana-1859	160	25	overall	overall	ADJ
cana-1859	160	26	performance	performance	NOUN
cana-1859	160	27	of	of	ADP
cana-1859	160	28	the	the	DET
cana-1859	160	29	cnn	cnn	PROPN
cana-1859	160	30	in	in	ADP
cana-1859	160	31	processing	process	VERB
cana-1859	160	32	large	large	ADJ
cana-1859	160	33	and	and	CCONJ
cana-1859	160	34	complex	complex	ADJ
cana-1859	160	35	datasets	dataset	NOUN
cana-1859	160	36	&	&	CCONJ
cana-1859	160	37	samples	sample	NOUN
cana-1859	160	38	.	.	PUNCT
cana-1859	161	1	in	in	ADP
cana-1859	161	2	contrast	contrast	NOUN
cana-1859	161	3	,	,	PUNCT
cana-1859	161	4	the	the	DET
cana-1859	161	5	nikhilam	nikhilam	PROPN
cana-1859	161	6	navatashcaramam	navatashcaramam	PROPN
cana-1859	161	7	dashatah	dashatah	NOUN
cana-1859	161	8	sutra	sutra	NOUN
cana-1859	161	9	,	,	PUNCT
cana-1859	161	10	originating	originate	VERB
cana-1859	161	11	from	from	ADP
cana-1859	161	12	vedic	vedic	ADJ
cana-1859	161	13	mathematics	mathematic	NOUN
cana-1859	161	14	,	,	PUNCT
cana-1859	161	15	translates	translate	VERB
cana-1859	161	16	to	to	PART
cana-1859	161	17	"	"	PUNCT
cana-1859	161	18	all	all	ADV
cana-1859	161	19	from	from	ADP
cana-1859	161	20	nine	nine	NUM
cana-1859	161	21	and	and	CCONJ
cana-1859	161	22	the	the	DET
cana-1859	161	23	last	last	ADJ
cana-1859	161	24	from	from	ADP
cana-1859	161	25	ten	ten	NUM
cana-1859	161	26	.	.	PUNCT
cana-1859	161	27	"	"	PUNCT
cana-1859	162	1	this	this	DET
cana-1859	162	2	sutra	sutra	NOUN
cana-1859	162	3	is	be	AUX
cana-1859	162	4	particularly	particularly	ADV
cana-1859	162	5	adept	adept	ADJ
cana-1859	162	6	at	at	ADP
cana-1859	162	7	simplifying	simplify	VERB
cana-1859	162	8	subtraction	subtraction	NOUN
cana-1859	162	9	operations	operation	NOUN
cana-1859	162	10	,	,	PUNCT
cana-1859	162	11	especially	especially	ADV
cana-1859	162	12	when	when	SCONJ
cana-1859	162	13	dealing	deal	VERB
cana-1859	162	14	with	with	ADP
cana-1859	162	15	numbers	number	NOUN
cana-1859	162	16	close	close	ADJ
cana-1859	162	17	to	to	ADP
cana-1859	162	18	powers	power	NOUN
cana-1859	162	19	of	of	ADP
cana-1859	162	20	10	10	NUM
cana-1859	162	21	.	.	PUNCT
cana-1859	163	1	in	in	ADP
cana-1859	163	2	the	the	DET
cana-1859	163	3	realm	realm	NOUN
cana-1859	163	4	of	of	ADP
cana-1859	163	5	convolutional	convolutional	ADJ
cana-1859	163	6	neural	neural	ADJ
cana-1859	163	7	networks	network	NOUN
cana-1859	163	8	(	(	PUNCT
cana-1859	163	9	cnns	cnns	PROPN
cana-1859	163	10	)	)	PUNCT
cana-1859	163	11	,	,	PUNCT
cana-1859	163	12	this	this	DET
cana-1859	163	13	principle	principle	NOUN
cana-1859	163	14	can	can	AUX
cana-1859	163	15	be	be	AUX
cana-1859	163	16	employed	employ	VERB
cana-1859	163	17	to	to	PART
cana-1859	163	18	optimize	optimize	VERB
cana-1859	163	19	various	various	ADJ
cana-1859	163	20	computational	computational	ADJ
cana-1859	163	21	processes	process	NOUN
cana-1859	163	22	that	that	PRON
cana-1859	163	23	involve	involve	VERB
cana-1859	163	24	subtraction	subtraction	NOUN
cana-1859	163	25	.	.	PUNCT
cana-1859	164	1	communications	communication	NOUN
cana-1859	164	2	on	on	ADP
cana-1859	164	3	applied	apply	VERB
cana-1859	164	4	nonlinear	nonlinear	ADJ
cana-1859	164	5	analysis	analysis	NOUN
cana-1859	164	6	issn	issn	NOUN
cana-1859	164	7	:	:	PUNCT
cana-1859	164	8	1074	1074	NUM
cana-1859	164	9	-	-	PUNCT
cana-1859	164	10	133x	133x	NUM
cana-1859	164	11	vol	vol	NOUN
cana-1859	164	12	32	32	NUM
cana-1859	164	13	no	no	NOUN
cana-1859	164	14	.	.	NOUN
cana-1859	164	15	2	2	NUM
cana-1859	164	16	(	(	PUNCT
cana-1859	164	17	2025	2025	NUM
cana-1859	164	18	)	)	PUNCT
cana-1859	164	19	648	648	NUM
cana-1859	164	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	164	21	the	the	DET
cana-1859	164	22	sutra	sutra	NOUN
cana-1859	164	23	provides	provide	VERB
cana-1859	164	24	an	an	DET
cana-1859	164	25	efficient	efficient	ADJ
cana-1859	164	26	method	method	NOUN
cana-1859	164	27	for	for	ADP
cana-1859	164	28	subtracting	subtract	VERB
cana-1859	164	29	large	large	ADJ
cana-1859	164	30	numbers	number	NOUN
cana-1859	164	31	from	from	ADP
cana-1859	164	32	powers	power	NOUN
cana-1859	164	33	of	of	ADP
cana-1859	164	34	10	10	NUM
cana-1859	164	35	.	.	PUNCT
cana-1859	165	1	it	it	PRON
cana-1859	165	2	involves	involve	VERB
cana-1859	165	3	subtracting	subtract	VERB
cana-1859	165	4	each	each	DET
cana-1859	165	5	digit	digit	NOUN
cana-1859	165	6	from	from	ADP
cana-1859	165	7	9	9	NUM
cana-1859	165	8	and	and	CCONJ
cana-1859	165	9	the	the	DET
cana-1859	165	10	last	last	ADJ
cana-1859	165	11	digit	digit	NOUN
cana-1859	165	12	from	from	ADP
cana-1859	165	13	10	10	NUM
cana-1859	165	14	.	.	PUNCT
cana-1859	166	1	this	this	DET
cana-1859	166	2	approach	approach	NOUN
cana-1859	166	3	simplifies	simplify	VERB
cana-1859	166	4	the	the	DET
cana-1859	166	5	subtraction	subtraction	NOUN
cana-1859	166	6	operation	operation	NOUN
cana-1859	166	7	,	,	PUNCT
cana-1859	166	8	making	make	VERB
cana-1859	166	9	it	it	PRON
cana-1859	166	10	faster	fast	ADV
cana-1859	166	11	and	and	CCONJ
cana-1859	166	12	more	more	ADV
cana-1859	166	13	efficient	efficient	ADJ
cana-1859	166	14	,	,	PUNCT
cana-1859	166	15	particularly	particularly	ADV
cana-1859	166	16	in	in	ADP
cana-1859	166	17	large	large	ADJ
cana-1859	166	18	-	-	PUNCT
cana-1859	166	19	scale	scale	NOUN
cana-1859	166	20	calculations	calculation	NOUN
cana-1859	166	21	.	.	PUNCT
cana-1859	167	1	in	in	ADP
cana-1859	167	2	cnns	cnns	PROPN
cana-1859	167	3	,	,	PUNCT
cana-1859	167	4	subtraction	subtraction	NOUN
cana-1859	167	5	operations	operation	NOUN
cana-1859	167	6	are	be	AUX
cana-1859	167	7	frequently	frequently	ADV
cana-1859	167	8	encountered	encounter	VERB
cana-1859	167	9	,	,	PUNCT
cana-1859	167	10	for	for	ADP
cana-1859	167	11	instance	instance	NOUN
cana-1859	167	12	,	,	PUNCT
cana-1859	167	13	in	in	ADP
cana-1859	167	14	the	the	DET
cana-1859	167	15	normalization	normalization	NOUN
cana-1859	167	16	processes	process	NOUN
cana-1859	167	17	,	,	PUNCT
cana-1859	167	18	weight	weight	NOUN
cana-1859	167	19	updates	update	NOUN
cana-1859	167	20	during	during	ADP
cana-1859	167	21	backpropagation	backpropagation	NOUN
cana-1859	167	22	,	,	PUNCT
cana-1859	167	23	or	or	CCONJ
cana-1859	167	24	even	even	ADV
cana-1859	167	25	in	in	ADP
cana-1859	167	26	certain	certain	ADJ
cana-1859	167	27	activation	activation	NOUN
cana-1859	167	28	functions	function	NOUN
cana-1859	167	29	.	.	PUNCT
cana-1859	168	1	the	the	DET
cana-1859	168	2	nikhilam	nikhilam	PROPN
cana-1859	168	3	sutra	sutra	PROPN
cana-1859	168	4	can	can	AUX
cana-1859	168	5	optimize	optimize	VERB
cana-1859	168	6	these	these	DET
cana-1859	168	7	subtraction	subtraction	NOUN
cana-1859	168	8	operations	operation	NOUN
cana-1859	168	9	by	by	ADP
cana-1859	168	10	simplifying	simplify	VERB
cana-1859	168	11	the	the	DET
cana-1859	168	12	process	process	NOUN
cana-1859	168	13	,	,	PUNCT
cana-1859	168	14	thus	thus	ADV
cana-1859	168	15	enhancing	enhance	VERB
cana-1859	168	16	computational	computational	ADJ
cana-1859	168	17	efficiency	efficiency	NOUN
cana-1859	168	18	.	.	PUNCT
cana-1859	169	1	consider	consider	VERB
cana-1859	169	2	a	a	DET
cana-1859	169	3	general	general	ADJ
cana-1859	169	4	subtraction	subtraction	NOUN
cana-1859	169	5	operation	operation	NOUN
cana-1859	169	6	in	in	ADP
cana-1859	169	7	a	a	DET
cana-1859	169	8	cnn	cnn	PROPN
cana-1859	169	9	process	process	NOUN
cana-1859	169	10	,	,	PUNCT
cana-1859	169	11	such	such	ADJ
cana-1859	169	12	as	as	ADP
cana-1859	169	13	during	during	ADP
cana-1859	169	14	weight	weight	NOUN
cana-1859	169	15	updates	update	NOUN
cana-1859	169	16	via	via	ADP
cana-1859	169	17	equation	equation	NOUN
cana-1859	169	18	13	13	NUM
cana-1859	169	19	,	,	PUNCT
cana-1859	170	1	𝑊𝑛𝑒𝑤	𝑊𝑛𝑒𝑤	PROPN
cana-1859	170	2	=	=	SYM
cana-1859	170	3	𝑊𝑜𝑙𝑑	𝑊𝑜𝑙𝑑	PROPN
cana-1859	170	4	−	−	NOUN
cana-1859	170	5	𝜂	𝜂	PROPN
cana-1859	170	6	⋅	⋅	PROPN
cana-1859	170	7	𝜕𝑊𝜕𝐿	𝜕𝑊𝜕𝐿	PROPN
cana-1859	170	8	…	…	PUNCT
cana-1859	170	9	(	(	PUNCT
cana-1859	170	10	13	13	NUM
cana-1859	170	11	)	)	PUNCT
cana-1859	170	12	where	where	SCONJ
cana-1859	170	13	,	,	PUNCT
cana-1859	170	14	wnew	wnew	NOUN
cana-1859	170	15	and	and	CCONJ
cana-1859	170	16	wold	wold	X
cana-1859	170	17	are	be	AUX
cana-1859	170	18	the	the	DET
cana-1859	170	19	updated	update	VERB
cana-1859	170	20	and	and	CCONJ
cana-1859	170	21	old	old	ADJ
cana-1859	170	22	weights	weight	NOUN
cana-1859	170	23	,	,	PUNCT
cana-1859	170	24	respectively	respectively	ADV
cana-1859	170	25	,	,	PUNCT
cana-1859	170	26	η	η	PROPN
cana-1859	170	27	is	be	AUX
cana-1859	170	28	the	the	DET
cana-1859	170	29	learning	learning	NOUN
cana-1859	170	30	rate	rate	NOUN
cana-1859	170	31	,	,	PUNCT
cana-1859	170	32	and	and	CCONJ
cana-1859	170	33	∂w∂l	∂w∂l	NOUN
cana-1859	170	34	is	be	AUX
cana-1859	170	35	the	the	DET
cana-1859	170	36	gradient	gradient	NOUN
cana-1859	170	37	of	of	ADP
cana-1859	170	38	the	the	DET
cana-1859	170	39	loss	loss	NOUN
cana-1859	170	40	function	function	NOUN
cana-1859	170	41	with	with	ADP
cana-1859	170	42	respect	respect	NOUN
cana-1859	170	43	to	to	ADP
cana-1859	170	44	the	the	DET
cana-1859	170	45	weights	weight	NOUN
cana-1859	170	46	.	.	PUNCT
cana-1859	171	1	using	use	VERB
cana-1859	171	2	the	the	DET
cana-1859	171	3	nikhilam	nikhilam	PROPN
cana-1859	171	4	sutra	sutra	PROPN
cana-1859	171	5	,	,	PUNCT
cana-1859	171	6	the	the	DET
cana-1859	171	7	subtraction	subtraction	NOUN
cana-1859	171	8	operation	operation	NOUN
cana-1859	171	9	can	can	AUX
cana-1859	171	10	be	be	AUX
cana-1859	171	11	optimized	optimize	VERB
cana-1859	171	12	,	,	PUNCT
cana-1859	171	13	especially	especially	ADV
cana-1859	171	14	if	if	SCONJ
cana-1859	171	15	the	the	DET
cana-1859	171	16	numbers	number	NOUN
cana-1859	171	17	involved	involve	VERB
cana-1859	171	18	are	be	AUX
cana-1859	171	19	conducive	conducive	ADJ
cana-1859	171	20	to	to	ADP
cana-1859	171	21	the	the	DET
cana-1859	171	22	sutra	sutra	NOUN
cana-1859	171	23	’s	’s	PART
cana-1859	171	24	application	application	NOUN
cana-1859	171	25	.	.	PUNCT
cana-1859	172	1	the	the	DET
cana-1859	172	2	optimization	optimization	NOUN
cana-1859	172	3	would	would	AUX
cana-1859	172	4	primarily	primarily	ADV
cana-1859	172	5	be	be	AUX
cana-1859	172	6	in	in	ADP
cana-1859	172	7	the	the	DET
cana-1859	172	8	computational	computational	ADJ
cana-1859	172	9	efficiency	efficiency	NOUN
cana-1859	172	10	of	of	ADP
cana-1859	172	11	the	the	DET
cana-1859	172	12	operation	operation	NOUN
cana-1859	172	13	.	.	PUNCT
cana-1859	173	1	while	while	SCONJ
cana-1859	173	2	the	the	DET
cana-1859	173	3	exact	exact	ADJ
cana-1859	173	4	mathematical	mathematical	ADJ
cana-1859	173	5	representation	representation	NOUN
cana-1859	173	6	of	of	ADP
cana-1859	173	7	the	the	DET
cana-1859	173	8	nikhilam	nikhilam	PROPN
cana-1859	173	9	sutra	sutra	PROPN
cana-1859	173	10	’s	’s	PART
cana-1859	173	11	application	application	NOUN
cana-1859	173	12	depends	depend	VERB
cana-1859	173	13	on	on	ADP
cana-1859	173	14	the	the	DET
cana-1859	173	15	specific	specific	ADJ
cana-1859	173	16	nature	nature	NOUN
cana-1859	173	17	of	of	ADP
cana-1859	173	18	the	the	DET
cana-1859	173	19	numbers	number	NOUN
cana-1859	173	20	involved	involve	VERB
cana-1859	173	21	,	,	PUNCT
cana-1859	173	22	the	the	DET
cana-1859	173	23	general	general	ADJ
cana-1859	173	24	idea	idea	NOUN
cana-1859	173	25	is	be	AUX
cana-1859	173	26	to	to	PART
cana-1859	173	27	simplify	simplify	VERB
cana-1859	173	28	the	the	DET
cana-1859	173	29	subtraction	subtraction	NOUN
cana-1859	173	30	operation	operation	NOUN
cana-1859	173	31	via	via	ADP
cana-1859	173	32	equation	equation	NOUN
cana-1859	173	33	14	14	NUM
cana-1859	173	34	,	,	PUNCT
cana-1859	173	35	𝑆𝑖𝑚𝑝𝑙𝑖𝑓𝑖𝑒𝑑𝑆𝑢𝑏𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛	𝑆𝑖𝑚𝑝𝑙𝑖𝑓𝑖𝑒𝑑𝑆𝑢𝑏𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛	PROPN
cana-1859	173	36	=	=	SYM
cana-1859	173	37	𝑁𝑖𝑘ℎ𝑖𝑙𝑎𝑚𝑀𝑒𝑡ℎ𝑜𝑑(𝑊𝑜𝑙𝑑	𝑁𝑖𝑘ℎ𝑖𝑙𝑎𝑚𝑀𝑒𝑡ℎ𝑜𝑑(𝑊𝑜𝑙𝑑	PROPN
cana-1859	173	38	,	,	PUNCT
cana-1859	173	39	𝜂	𝜂	PRON
cana-1859	173	40	⋅	⋅	PROPN
cana-1859	173	41	𝜕𝑊𝜕𝐿	𝜕𝑊𝜕𝐿	PROPN
cana-1859	173	42	)	)	PUNCT
cana-1859	173	43	…	…	PUNCT
cana-1859	173	44	(	(	PUNCT
cana-1859	173	45	14	14	NUM
cana-1859	173	46	)	)	PUNCT
cana-1859	173	47	where	where	SCONJ
cana-1859	173	48	,	,	PUNCT
cana-1859	173	49	nikhilammethod	nikhilammethod	NOUN
cana-1859	173	50	represents	represent	VERB
cana-1859	173	51	the	the	DET
cana-1859	173	52	application	application	NOUN
cana-1859	173	53	of	of	ADP
cana-1859	173	54	the	the	DET
cana-1859	173	55	sutra	sutra	NOUN
cana-1859	173	56	to	to	PART
cana-1859	173	57	simplify	simplify	VERB
cana-1859	173	58	the	the	DET
cana-1859	173	59	subtraction	subtraction	NOUN
cana-1859	173	60	process	process	NOUN
cana-1859	173	61	.	.	PUNCT
cana-1859	174	1	reasons	reason	NOUN
cana-1859	174	2	for	for	ADP
cana-1859	174	3	improvement	improvement	NOUN
cana-1859	174	4	in	in	ADP
cana-1859	174	5	performance	performance	NOUN
cana-1859	174	6	1	1	NUM
cana-1859	174	7	.	.	PUNCT
cana-1859	174	8	computational	computational	ADJ
cana-1859	174	9	speed	speed	NOUN
cana-1859	174	10	:	:	PUNCT
cana-1859	174	11	the	the	DET
cana-1859	174	12	sutra	sutra	NOUN
cana-1859	174	13	can	can	AUX
cana-1859	174	14	make	make	VERB
cana-1859	174	15	the	the	DET
cana-1859	174	16	subtraction	subtraction	NOUN
cana-1859	174	17	operation	operation	NOUN
cana-1859	174	18	faster	fast	ADV
cana-1859	174	19	,	,	PUNCT
cana-1859	174	20	especially	especially	ADV
cana-1859	174	21	beneficial	beneficial	ADJ
cana-1859	174	22	when	when	SCONJ
cana-1859	174	23	dealing	deal	VERB
cana-1859	174	24	with	with	ADP
cana-1859	174	25	large	large	ADJ
cana-1859	174	26	matrices	matrix	NOUN
cana-1859	174	27	or	or	CCONJ
cana-1859	174	28	vectors	vector	NOUN
cana-1859	174	29	,	,	PUNCT
cana-1859	174	30	as	as	ADV
cana-1859	174	31	often	often	ADV
cana-1859	174	32	encountered	encounter	VERB
cana-1859	174	33	in	in	ADP
cana-1859	174	34	cnns	cnn	NOUN
cana-1859	174	35	.	.	PUNCT
cana-1859	175	1	2	2	NUM
cana-1859	175	2	.	.	X
cana-1859	175	3	resource	resource	NOUN
cana-1859	175	4	efficiency	efficiency	NOUN
cana-1859	175	5	:	:	PUNCT
cana-1859	175	6	improved	improve	VERB
cana-1859	175	7	speed	speed	NOUN
cana-1859	175	8	in	in	ADP
cana-1859	175	9	subtraction	subtraction	NOUN
cana-1859	175	10	operations	operation	NOUN
cana-1859	175	11	can	can	AUX
cana-1859	175	12	lead	lead	VERB
cana-1859	175	13	to	to	ADP
cana-1859	175	14	better	well	ADJ
cana-1859	175	15	overall	overall	ADJ
cana-1859	175	16	resource	resource	NOUN
cana-1859	175	17	utilization	utilization	NOUN
cana-1859	175	18	,	,	PUNCT
cana-1859	175	19	including	include	VERB
cana-1859	175	20	processing	processing	NOUN
cana-1859	175	21	power	power	NOUN
cana-1859	175	22	and	and	CCONJ
cana-1859	175	23	memory	memory	NOUN
cana-1859	175	24	,	,	PUNCT
cana-1859	175	25	during	during	ADP
cana-1859	175	26	the	the	DET
cana-1859	175	27	training	training	NOUN
cana-1859	175	28	and	and	CCONJ
cana-1859	175	29	inference	inference	NOUN
cana-1859	175	30	phases	phase	NOUN
cana-1859	175	31	of	of	ADP
cana-1859	175	32	cnns	cnn	NOUN
cana-1859	175	33	.	.	PUNCT
cana-1859	176	1	3	3	X
cana-1859	176	2	.	.	NUM
cana-1859	176	3	enhanced	enhance	VERB
cana-1859	176	4	training	training	NOUN
cana-1859	176	5	stability	stability	NOUN
cana-1859	176	6	:	:	PUNCT
cana-1859	176	7	efficient	efficient	ADJ
cana-1859	176	8	computation	computation	NOUN
cana-1859	176	9	in	in	ADP
cana-1859	176	10	weight	weight	NOUN
cana-1859	176	11	updates	update	NOUN
cana-1859	176	12	can	can	AUX
cana-1859	176	13	contribute	contribute	VERB
cana-1859	176	14	to	to	ADP
cana-1859	176	15	the	the	DET
cana-1859	176	16	stability	stability	NOUN
cana-1859	176	17	of	of	ADP
cana-1859	176	18	the	the	DET
cana-1859	176	19	training	training	NOUN
cana-1859	176	20	process	process	NOUN
cana-1859	176	21	,	,	PUNCT
cana-1859	176	22	potentially	potentially	ADV
cana-1859	176	23	leading	lead	VERB
cana-1859	176	24	to	to	ADP
cana-1859	176	25	more	more	ADV
cana-1859	176	26	consistent	consistent	ADJ
cana-1859	176	27	convergence	convergence	NOUN
cana-1859	176	28	behavior	behavior	NOUN
cana-1859	176	29	.	.	PUNCT
cana-1859	177	1	4	4	X
cana-1859	177	2	.	.	X
cana-1859	177	3	adaptability	adaptability	NOUN
cana-1859	177	4	:	:	PUNCT
cana-1859	177	5	while	while	SCONJ
cana-1859	177	6	the	the	DET
cana-1859	177	7	sutra	sutra	NOUN
cana-1859	177	8	may	may	AUX
cana-1859	177	9	not	not	PART
cana-1859	177	10	be	be	AUX
cana-1859	177	11	universally	universally	ADV
cana-1859	177	12	applicable	applicable	ADJ
cana-1859	177	13	,	,	PUNCT
cana-1859	177	14	it	it	PRON
cana-1859	177	15	offers	offer	VERB
cana-1859	177	16	an	an	DET
cana-1859	177	17	additional	additional	ADJ
cana-1859	177	18	tool	tool	NOUN
cana-1859	177	19	that	that	PRON
cana-1859	177	20	can	can	AUX
cana-1859	177	21	be	be	AUX
cana-1859	177	22	selectively	selectively	ADV
cana-1859	177	23	applied	apply	VERB
cana-1859	177	24	to	to	PART
cana-1859	177	25	optimize	optimize	VERB
cana-1859	177	26	specific	specific	ADJ
cana-1859	177	27	operations	operation	NOUN
cana-1859	177	28	within	within	ADP
cana-1859	177	29	the	the	DET
cana-1859	177	30	cnn	cnn	PROPN
cana-1859	177	31	,	,	PUNCT
cana-1859	177	32	enhancing	enhance	VERB
cana-1859	177	33	the	the	DET
cana-1859	177	34	overall	overall	ADJ
cana-1859	177	35	efficiency	efficiency	NOUN
cana-1859	177	36	of	of	ADP
cana-1859	177	37	the	the	DET
cana-1859	177	38	model	model	NOUN
cana-1859	177	39	.	.	PUNCT
cana-1859	178	1	in	in	ADP
cana-1859	178	2	conclusion	conclusion	NOUN
cana-1859	178	3	,	,	PUNCT
cana-1859	178	4	the	the	DET
cana-1859	178	5	application	application	NOUN
cana-1859	178	6	of	of	ADP
cana-1859	178	7	the	the	DET
cana-1859	178	8	nikhilam	nikhilam	PROPN
cana-1859	178	9	navatashcaramam	navatashcaramam	PROPN
cana-1859	178	10	dashatah	dashatah	NOUN
cana-1859	178	11	sutra	sutra	NOUN
cana-1859	178	12	in	in	ADP
cana-1859	178	13	cnns	cnn	NOUN
cana-1859	178	14	can	can	AUX
cana-1859	178	15	be	be	AUX
cana-1859	178	16	particularly	particularly	ADV
cana-1859	178	17	useful	useful	ADJ
cana-1859	178	18	in	in	ADP
cana-1859	178	19	optimizing	optimize	VERB
cana-1859	178	20	subtraction	subtraction	NOUN
cana-1859	178	21	operations	operation	NOUN
cana-1859	178	22	,	,	PUNCT
cana-1859	178	23	enhancing	enhance	VERB
cana-1859	178	24	computational	computational	ADJ
cana-1859	178	25	speed	speed	NOUN
cana-1859	178	26	and	and	CCONJ
cana-1859	178	27	efficiency	efficiency	NOUN
cana-1859	178	28	.	.	PUNCT
cana-1859	179	1	this	this	DET
cana-1859	179	2	optimization	optimization	NOUN
cana-1859	179	3	can	can	AUX
cana-1859	179	4	be	be	AUX
cana-1859	179	5	significant	significant	ADJ
cana-1859	179	6	in	in	ADP
cana-1859	179	7	processes	process	NOUN
cana-1859	179	8	like	like	ADP
cana-1859	179	9	weight	weight	NOUN
cana-1859	179	10	updates	update	NOUN
cana-1859	179	11	during	during	ADP
cana-1859	179	12	backpropagation	backpropagation	NOUN
cana-1859	179	13	,	,	PUNCT
cana-1859	179	14	contributing	contribute	VERB
cana-1859	179	15	to	to	ADP
cana-1859	179	16	the	the	DET
cana-1859	179	17	overall	overall	ADJ
cana-1859	179	18	performance	performance	NOUN
cana-1859	179	19	and	and	CCONJ
cana-1859	179	20	efficacy	efficacy	NOUN
cana-1859	179	21	of	of	ADP
cana-1859	179	22	the	the	DET
cana-1859	179	23	cnn	cnn	PROPN
cana-1859	179	24	in	in	ADP
cana-1859	179	25	handling	handle	VERB
cana-1859	179	26	complex	complex	ADJ
cana-1859	179	27	computational	computational	ADJ
cana-1859	179	28	tasks	task	NOUN
cana-1859	179	29	in	in	ADP
cana-1859	179	30	image	image	NOUN
cana-1859	179	31	classification	classification	NOUN
cana-1859	179	32	and	and	CCONJ
cana-1859	179	33	other	other	ADJ
cana-1859	179	34	ai	ai	PROPN
cana-1859	179	35	applications	application	NOUN
cana-1859	179	36	.	.	PUNCT
cana-1859	180	1	communications	communication	NOUN
cana-1859	180	2	on	on	ADP
cana-1859	180	3	applied	apply	VERB
cana-1859	180	4	nonlinear	nonlinear	ADJ
cana-1859	180	5	analysis	analysis	NOUN
cana-1859	180	6	issn	issn	NOUN
cana-1859	180	7	:	:	PUNCT
cana-1859	180	8	1074	1074	NUM
cana-1859	180	9	-	-	PUNCT
cana-1859	180	10	133x	133x	NUM
cana-1859	180	11	vol	vol	NOUN
cana-1859	180	12	32	32	NUM
cana-1859	180	13	no	no	NOUN
cana-1859	180	14	.	.	NOUN
cana-1859	180	15	2	2	NUM
cana-1859	180	16	(	(	PUNCT
cana-1859	180	17	2025	2025	NUM
cana-1859	180	18	)	)	PUNCT
cana-1859	180	19	649	649	NUM
cana-1859	180	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	180	21	similarly	similarly	ADV
cana-1859	180	22	,	,	PUNCT
cana-1859	180	23	shunyam	shunyam	PROPN
cana-1859	180	24	saamyasamuccaye	saamyasamuccaye	NOUN
cana-1859	180	25	is	be	AUX
cana-1859	180	26	a	a	DET
cana-1859	180	27	vedic	vedic	ADJ
cana-1859	180	28	mathematics	mathematic	NOUN
cana-1859	180	29	sutra	sutra	NOUN
cana-1859	180	30	that	that	PRON
cana-1859	180	31	translates	translate	VERB
cana-1859	180	32	to	to	ADP
cana-1859	180	33	"	"	PUNCT
cana-1859	180	34	if	if	SCONJ
cana-1859	180	35	the	the	DET
cana-1859	180	36	sum	sum	NOUN
cana-1859	180	37	is	be	AUX
cana-1859	180	38	the	the	DET
cana-1859	180	39	same	same	ADJ
cana-1859	180	40	,	,	PUNCT
cana-1859	180	41	that	that	DET
cana-1859	180	42	sum	sum	NOUN
cana-1859	180	43	is	be	AUX
cana-1859	180	44	zero	zero	NUM
cana-1859	180	45	.	.	PUNCT
cana-1859	180	46	"	"	PUNCT
cana-1859	181	1	this	this	DET
cana-1859	181	2	sutra	sutra	NOUN
cana-1859	181	3	primarily	primarily	ADV
cana-1859	181	4	deals	deal	VERB
cana-1859	181	5	with	with	ADP
cana-1859	181	6	equations	equation	NOUN
cana-1859	181	7	where	where	SCONJ
cana-1859	181	8	the	the	DET
cana-1859	181	9	sum	sum	NOUN
cana-1859	181	10	of	of	ADP
cana-1859	181	11	the	the	DET
cana-1859	181	12	coefficients	coefficient	NOUN
cana-1859	181	13	is	be	AUX
cana-1859	181	14	zero	zero	NUM
cana-1859	181	15	.	.	PUNCT
cana-1859	182	1	in	in	ADP
cana-1859	182	2	the	the	DET
cana-1859	182	3	context	context	NOUN
cana-1859	182	4	of	of	ADP
cana-1859	182	5	convolutional	convolutional	ADJ
cana-1859	182	6	neural	neural	ADJ
cana-1859	182	7	networks	network	NOUN
cana-1859	182	8	(	(	PUNCT
cana-1859	182	9	cnns	cnns	PROPN
cana-1859	182	10	)	)	PUNCT
cana-1859	182	11	,	,	PUNCT
cana-1859	182	12	this	this	DET
cana-1859	182	13	principle	principle	NOUN
cana-1859	182	14	can	can	AUX
cana-1859	182	15	be	be	AUX
cana-1859	182	16	applied	apply	VERB
cana-1859	182	17	to	to	PART
cana-1859	182	18	optimize	optimize	VERB
cana-1859	182	19	certain	certain	ADJ
cana-1859	182	20	mathematical	mathematical	ADJ
cana-1859	182	21	operations	operation	NOUN
cana-1859	182	22	,	,	PUNCT
cana-1859	182	23	particularly	particularly	ADV
cana-1859	182	24	those	those	PRON
cana-1859	182	25	involving	involve	VERB
cana-1859	182	26	sums	sum	NOUN
cana-1859	182	27	and	and	CCONJ
cana-1859	182	28	weights	weight	NOUN
cana-1859	182	29	.	.	PUNCT
cana-1859	183	1	in	in	ADP
cana-1859	183	2	a	a	DET
cana-1859	183	3	cnn	cnn	NOUN
cana-1859	183	4	,	,	PUNCT
cana-1859	183	5	there	there	PRON
cana-1859	183	6	are	be	VERB
cana-1859	183	7	numerous	numerous	ADJ
cana-1859	183	8	instances	instance	NOUN
cana-1859	183	9	where	where	SCONJ
cana-1859	183	10	sums	sum	NOUN
cana-1859	183	11	of	of	ADP
cana-1859	183	12	various	various	ADJ
cana-1859	183	13	coefficients	coefficient	NOUN
cana-1859	183	14	,	,	PUNCT
cana-1859	183	15	weights	weight	NOUN
cana-1859	183	16	,	,	PUNCT
cana-1859	183	17	or	or	CCONJ
cana-1859	183	18	activations	activation	NOUN
cana-1859	183	19	are	be	AUX
cana-1859	183	20	computed	compute	VERB
cana-1859	183	21	,	,	PUNCT
cana-1859	183	22	especially	especially	ADV
cana-1859	183	23	in	in	ADP
cana-1859	183	24	layers	layer	NOUN
cana-1859	183	25	like	like	ADP
cana-1859	183	26	convolutional	convolutional	ADJ
cana-1859	183	27	layers	layer	NOUN
cana-1859	183	28	and	and	CCONJ
cana-1859	183	29	fully	fully	ADV
cana-1859	183	30	connected	connected	ADJ
cana-1859	183	31	layers	layer	NOUN
cana-1859	183	32	.	.	PUNCT
cana-1859	184	1	the	the	DET
cana-1859	184	2	shunyam	shunyam	NOUN
cana-1859	184	3	saamyasamuccaye	saamyasamuccaye	VERB
cana-1859	184	4	sutra	sutra	NOUN
cana-1859	184	5	can	can	AUX
cana-1859	184	6	be	be	AUX
cana-1859	184	7	applied	apply	VERB
cana-1859	184	8	to	to	PART
cana-1859	184	9	optimize	optimize	VERB
cana-1859	184	10	these	these	DET
cana-1859	184	11	summation	summation	NOUN
cana-1859	184	12	processes	process	NOUN
cana-1859	184	13	,	,	PUNCT
cana-1859	184	14	especially	especially	ADV
cana-1859	184	15	when	when	SCONJ
cana-1859	184	16	the	the	DET
cana-1859	184	17	sum	sum	NOUN
cana-1859	184	18	of	of	ADP
cana-1859	184	19	coefficients	coefficient	NOUN
cana-1859	184	20	equals	equal	VERB
cana-1859	184	21	zero	zero	NUM
cana-1859	184	22	,	,	PUNCT
cana-1859	184	23	thereby	thereby	ADV
cana-1859	184	24	simplifying	simplify	VERB
cana-1859	184	25	the	the	DET
cana-1859	184	26	computation	computation	NOUN
cana-1859	184	27	.	.	PUNCT
cana-1859	185	1	consider	consider	VERB
cana-1859	185	2	the	the	DET
cana-1859	185	3	operation	operation	NOUN
cana-1859	185	4	in	in	ADP
cana-1859	185	5	a	a	DET
cana-1859	185	6	fully	fully	ADV
cana-1859	185	7	connected	connect	VERB
cana-1859	185	8	layer	layer	NOUN
cana-1859	185	9	where	where	SCONJ
cana-1859	185	10	the	the	DET
cana-1859	185	11	weighted	weighted	ADJ
cana-1859	185	12	sum	sum	NOUN
cana-1859	185	13	of	of	ADP
cana-1859	185	14	inputs	input	NOUN
cana-1859	185	15	is	be	AUX
cana-1859	185	16	calculated	calculate	VERB
cana-1859	185	17	.	.	PUNCT
cana-1859	186	1	typically	typically	ADV
cana-1859	186	2	,	,	PUNCT
cana-1859	186	3	this	this	PRON
cana-1859	186	4	is	be	AUX
cana-1859	186	5	expressed	express	VERB
cana-1859	186	6	via	via	ADP
cana-1859	186	7	equation	equation	NOUN
cana-1859	186	8	15	15	NUM
cana-1859	186	9	,	,	PUNCT
cana-1859	186	10	𝑂	𝑂	PROPN
cana-1859	186	11	=	=	SYM
cana-1859	186	12	∑𝑊𝑖	∑𝑊𝑖	PROPN
cana-1859	187	1	⋅	⋅	PROPN
cana-1859	187	2	𝑋𝑖	𝑋𝑖	PROPN
cana-1859	187	3	+	+	PROPN
cana-1859	187	4	𝑏	𝑏	NOUN
cana-1859	187	5	…	…	PUNCT
cana-1859	187	6	(	(	PUNCT
cana-1859	187	7	15	15	NUM
cana-1859	187	8	)	)	PUNCT
cana-1859	187	9	where	where	SCONJ
cana-1859	187	10	,	,	PUNCT
cana-1859	187	11	o	o	PROPN
cana-1859	187	12	is	be	AUX
cana-1859	187	13	the	the	DET
cana-1859	187	14	output	output	NOUN
cana-1859	187	15	,	,	PUNCT
cana-1859	187	16	wi	wi	PROPN
cana-1859	187	17	are	be	AUX
cana-1859	187	18	the	the	DET
cana-1859	187	19	weights	weight	NOUN
cana-1859	187	20	,	,	PUNCT
cana-1859	187	21	xi	xi	X
cana-1859	187	22	are	be	AUX
cana-1859	187	23	the	the	DET
cana-1859	187	24	inputs	input	NOUN
cana-1859	187	25	,	,	PUNCT
cana-1859	187	26	and	and	CCONJ
cana-1859	187	27	b	b	NOUN
cana-1859	187	28	is	be	AUX
cana-1859	187	29	the	the	DET
cana-1859	187	30	bias	bias	NOUN
cana-1859	187	31	.	.	PUNCT
cana-1859	188	1	applying	apply	VERB
cana-1859	188	2	shunyam	shunyam	NOUN
cana-1859	188	3	saamyasamuccaye	saamyasamuccaye	NOUN
cana-1859	188	4	,	,	PUNCT
cana-1859	188	5	if	if	SCONJ
cana-1859	188	6	the	the	DET
cana-1859	188	7	sum	sum	NOUN
cana-1859	188	8	of	of	ADP
cana-1859	188	9	certain	certain	ADJ
cana-1859	188	10	weights	weight	NOUN
cana-1859	188	11	and	and	CCONJ
cana-1859	188	12	inputs	input	NOUN
cana-1859	188	13	leads	lead	VERB
cana-1859	188	14	to	to	ADP
cana-1859	188	15	zero	zero	NUM
cana-1859	188	16	,	,	PUNCT
cana-1859	188	17	the	the	DET
cana-1859	188	18	equation	equation	NOUN
cana-1859	188	19	can	can	AUX
cana-1859	188	20	be	be	AUX
cana-1859	188	21	simplified	simplify	VERB
cana-1859	188	22	by	by	ADP
cana-1859	188	23	omitting	omit	VERB
cana-1859	188	24	these	these	DET
cana-1859	188	25	terms	term	NOUN
cana-1859	188	26	,	,	PUNCT
cana-1859	188	27	reducing	reduce	VERB
cana-1859	188	28	the	the	DET
cana-1859	188	29	computational	computational	ADJ
cana-1859	188	30	complexity	complexity	NOUN
cana-1859	188	31	.	.	PUNCT
cana-1859	189	1	for	for	ADP
cana-1859	189	2	example	example	NOUN
cana-1859	189	3	,	,	PUNCT
cana-1859	189	4	if	if	SCONJ
cana-1859	189	5	⋅x1+w2	⋅x1+w2	PROPN
cana-1859	189	6	⋅x2=0	⋅x2=0	PROPN
cana-1859	189	7	,	,	PUNCT
cana-1859	189	8	they	they	PRON
cana-1859	189	9	can	can	AUX
cana-1859	189	10	be	be	AUX
cana-1859	189	11	excluded	exclude	VERB
cana-1859	189	12	from	from	ADP
cana-1859	189	13	the	the	DET
cana-1859	189	14	sum	sum	NOUN
cana-1859	189	15	via	via	ADP
cana-1859	189	16	equation	equation	NOUN
cana-1859	189	17	16	16	NUM
cana-1859	189	18	,	,	PUNCT
cana-1859	189	19	𝑂	𝑂	PROPN
cana-1859	189	20	=	=	SYM
cana-1859	189	21	∑(𝑊𝑖	∑(𝑊𝑖	PROPN
cana-1859	189	22	⋅	⋅	PROPN
cana-1859	189	23	𝑋𝑖	𝑋𝑖	PROPN
cana-1859	189	24	)	)	PUNCT
cana-1859	189	25	≠	≠	PROPN
cana-1859	189	26	−(𝑊𝑗	−(𝑊𝑗	VERB
cana-1859	189	27	⋅	⋅	PROPN
cana-1859	189	28	𝑋𝑗)𝑛𝑊𝑖	𝑋𝑗)𝑛𝑊𝑖	NOUN
cana-1859	189	29	⋅	⋅	X
cana-1859	189	30	𝑋𝑖	𝑋𝑖	PROPN
cana-1859	189	31	+	+	PROPN
cana-1859	189	32	𝑏	𝑏	NOUN
cana-1859	189	33	…	…	PUNCT
cana-1859	189	34	(	(	PUNCT
cana-1859	189	35	16	16	NUM
cana-1859	189	36	)	)	PUNCT
cana-1859	189	37	this	this	DET
cana-1859	189	38	equation	equation	NOUN
cana-1859	189	39	considers	consider	VERB
cana-1859	189	40	only	only	ADV
cana-1859	189	41	those	those	DET
cana-1859	189	42	terms	term	NOUN
cana-1859	189	43	in	in	ADP
cana-1859	189	44	the	the	DET
cana-1859	189	45	summation	summation	NOUN
cana-1859	189	46	where	where	SCONJ
cana-1859	189	47	the	the	DET
cana-1859	189	48	product	product	NOUN
cana-1859	189	49	of	of	ADP
cana-1859	189	50	weights	weight	NOUN
cana-1859	189	51	and	and	CCONJ
cana-1859	189	52	inputs	input	NOUN
cana-1859	189	53	does	do	AUX
cana-1859	189	54	not	not	PART
cana-1859	189	55	negate	negate	VERB
cana-1859	189	56	each	each	DET
cana-1859	189	57	other	other	ADJ
cana-1859	189	58	,	,	PUNCT
cana-1859	189	59	in	in	ADP
cana-1859	189	60	accordance	accordance	NOUN
cana-1859	189	61	with	with	ADP
cana-1859	189	62	the	the	DET
cana-1859	189	63	sutra	sutra	NOUN
cana-1859	189	64	.	.	PUNCT
cana-1859	190	1	reasons	reason	NOUN
cana-1859	190	2	for	for	ADP
cana-1859	190	3	improvement	improvement	NOUN
cana-1859	190	4	in	in	ADP
cana-1859	190	5	performance	performance	NOUN
cana-1859	190	6	1	1	NUM
cana-1859	190	7	.	.	PUNCT
cana-1859	190	8	reduced	reduce	VERB
cana-1859	190	9	computational	computational	ADJ
cana-1859	190	10	load	load	NOUN
cana-1859	190	11	:	:	PUNCT
cana-1859	190	12	by	by	ADP
cana-1859	190	13	eliminating	eliminate	VERB
cana-1859	190	14	terms	term	NOUN
cana-1859	190	15	that	that	PRON
cana-1859	190	16	sum	sum	VERB
cana-1859	190	17	up	up	ADP
cana-1859	190	18	to	to	ADP
cana-1859	190	19	zero	zero	NUM
cana-1859	190	20	,	,	PUNCT
cana-1859	190	21	the	the	DET
cana-1859	190	22	number	number	NOUN
cana-1859	190	23	of	of	ADP
cana-1859	190	24	multiplications	multiplication	NOUN
cana-1859	190	25	and	and	CCONJ
cana-1859	190	26	additions	addition	NOUN
cana-1859	190	27	in	in	ADP
cana-1859	190	28	the	the	DET
cana-1859	190	29	network	network	NOUN
cana-1859	190	30	is	be	AUX
cana-1859	190	31	reduced	reduce	VERB
cana-1859	190	32	,	,	PUNCT
cana-1859	190	33	leading	lead	VERB
cana-1859	190	34	to	to	ADP
cana-1859	190	35	less	less	ADV
cana-1859	190	36	computational	computational	ADJ
cana-1859	190	37	overhead	overhead	NOUN
cana-1859	190	38	.	.	PUNCT
cana-1859	191	1	2	2	X
cana-1859	191	2	.	.	X
cana-1859	191	3	efficiency	efficiency	NOUN
cana-1859	191	4	in	in	ADP
cana-1859	191	5	training	training	NOUN
cana-1859	191	6	and	and	CCONJ
cana-1859	191	7	inference	inference	NOUN
cana-1859	191	8	:	:	PUNCT
cana-1859	191	9	simplifying	simplify	VERB
cana-1859	191	10	the	the	DET
cana-1859	191	11	computations	computation	NOUN
cana-1859	191	12	within	within	ADP
cana-1859	191	13	the	the	DET
cana-1859	191	14	network	network	NOUN
cana-1859	191	15	can	can	AUX
cana-1859	191	16	lead	lead	VERB
cana-1859	191	17	to	to	ADP
cana-1859	191	18	faster	fast	ADJ
cana-1859	191	19	training	training	NOUN
cana-1859	191	20	and	and	CCONJ
cana-1859	191	21	inference	inference	NOUN
cana-1859	191	22	times	time	NOUN
cana-1859	191	23	,	,	PUNCT
cana-1859	191	24	making	make	VERB
cana-1859	191	25	the	the	DET
cana-1859	191	26	cnn	cnn	PROPN
cana-1859	191	27	more	more	ADV
cana-1859	191	28	efficient	efficient	ADJ
cana-1859	191	29	,	,	PUNCT
cana-1859	191	30	especially	especially	ADV
cana-1859	191	31	when	when	SCONJ
cana-1859	191	32	dealing	deal	VERB
cana-1859	191	33	with	with	ADP
cana-1859	191	34	large	large	ADJ
cana-1859	191	35	datasets	dataset	NOUN
cana-1859	191	36	or	or	CCONJ
cana-1859	191	37	deep	deep	ADJ
cana-1859	191	38	networks	network	NOUN
cana-1859	191	39	.	.	PUNCT
cana-1859	192	1	3	3	X
cana-1859	192	2	.	.	X
cana-1859	192	3	resource	resource	NOUN
cana-1859	192	4	optimization	optimization	NOUN
cana-1859	192	5	:	:	PUNCT
cana-1859	192	6	reduced	reduce	VERB
cana-1859	192	7	computational	computational	ADJ
cana-1859	192	8	complexity	complexity	NOUN
cana-1859	192	9	means	mean	VERB
cana-1859	192	10	better	well	ADJ
cana-1859	192	11	utilization	utilization	NOUN
cana-1859	192	12	of	of	ADP
cana-1859	192	13	memory	memory	NOUN
cana-1859	192	14	and	and	CCONJ
cana-1859	192	15	processing	processing	NOUN
cana-1859	192	16	power	power	NOUN
cana-1859	192	17	,	,	PUNCT
cana-1859	192	18	which	which	PRON
cana-1859	192	19	is	be	AUX
cana-1859	192	20	crucial	crucial	ADJ
cana-1859	192	21	for	for	ADP
cana-1859	192	22	resource	resource	NOUN
cana-1859	192	23	-	-	PUNCT
cana-1859	192	24	intensive	intensive	ADJ
cana-1859	192	25	tasks	task	NOUN
cana-1859	192	26	in	in	ADP
cana-1859	192	27	cnns	cnn	NOUN
cana-1859	192	28	.	.	PUNCT
cana-1859	193	1	4	4	X
cana-1859	193	2	.	.	NOUN
cana-1859	193	3	potential	potential	NOUN
cana-1859	193	4	for	for	ADP
cana-1859	193	5	sparse	sparse	ADJ
cana-1859	193	6	matrix	matrix	NOUN
cana-1859	193	7	optimization	optimization	NOUN
cana-1859	193	8	:	:	PUNCT
cana-1859	193	9	this	this	DET
cana-1859	193	10	principle	principle	NOUN
cana-1859	193	11	can	can	AUX
cana-1859	193	12	be	be	AUX
cana-1859	193	13	particularly	particularly	ADV
cana-1859	193	14	beneficial	beneficial	ADJ
cana-1859	193	15	in	in	ADP
cana-1859	193	16	scenarios	scenario	NOUN
cana-1859	193	17	where	where	SCONJ
cana-1859	193	18	the	the	DET
cana-1859	193	19	weight	weight	NOUN
cana-1859	193	20	matrix	matrix	NOUN
cana-1859	193	21	is	be	AUX
cana-1859	193	22	sparse	sparse	ADJ
cana-1859	193	23	and	and	CCONJ
cana-1859	193	24	contains	contain	VERB
cana-1859	193	25	many	many	ADJ
cana-1859	193	26	such	such	ADJ
cana-1859	193	27	pairs	pair	NOUN
cana-1859	193	28	of	of	ADP
cana-1859	193	29	coefficients	coefficient	NOUN
cana-1859	193	30	that	that	PRON
cana-1859	193	31	sum	sum	VERB
cana-1859	193	32	to	to	ADP
cana-1859	193	33	zero	zero	NUM
cana-1859	193	34	,	,	PUNCT
cana-1859	193	35	further	far	ADV
cana-1859	193	36	optimizing	optimize	VERB
cana-1859	193	37	the	the	DET
cana-1859	193	38	network	network	NOUN
cana-1859	193	39	’s	’s	PART
cana-1859	193	40	performance	performance	NOUN
cana-1859	193	41	.	.	PUNCT
cana-1859	194	1	the	the	DET
cana-1859	194	2	application	application	NOUN
cana-1859	194	3	of	of	ADP
cana-1859	194	4	the	the	DET
cana-1859	194	5	shunyam	shunyam	NOUN
cana-1859	194	6	saamyasamuccaye	saamyasamuccaye	VERB
cana-1859	194	7	sutra	sutra	NOUN
cana-1859	194	8	in	in	ADP
cana-1859	194	9	cnns	cnns	PROPN
cana-1859	194	10	offers	offer	VERB
cana-1859	194	11	a	a	DET
cana-1859	194	12	novel	novel	ADJ
cana-1859	194	13	way	way	NOUN
cana-1859	194	14	to	to	PART
cana-1859	194	15	optimize	optimize	VERB
cana-1859	194	16	the	the	DET
cana-1859	194	17	network	network	NOUN
cana-1859	194	18	’s	’s	PART
cana-1859	194	19	computational	computational	ADJ
cana-1859	194	20	processes	process	NOUN
cana-1859	194	21	by	by	ADP
cana-1859	194	22	simplifying	simplify	VERB
cana-1859	194	23	the	the	DET
cana-1859	194	24	calculations	calculation	NOUN
cana-1859	194	25	involving	involve	VERB
cana-1859	194	26	sums	sum	NOUN
cana-1859	194	27	of	of	ADP
cana-1859	194	28	weights	weight	NOUN
cana-1859	194	29	and	and	CCONJ
cana-1859	194	30	communications	communication	NOUN
cana-1859	194	31	on	on	ADP
cana-1859	194	32	applied	apply	VERB
cana-1859	194	33	nonlinear	nonlinear	ADJ
cana-1859	194	34	analysis	analysis	NOUN
cana-1859	194	35	issn	issn	NOUN
cana-1859	194	36	:	:	PUNCT
cana-1859	194	37	1074	1074	NUM
cana-1859	194	38	-	-	PUNCT
cana-1859	194	39	133x	133x	NUM
cana-1859	194	40	vol	vol	NOUN
cana-1859	194	41	32	32	NUM
cana-1859	194	42	no	no	NOUN
cana-1859	194	43	.	.	NOUN
cana-1859	194	44	2	2	NUM
cana-1859	194	45	(	(	PUNCT
cana-1859	194	46	2025	2025	NUM
cana-1859	194	47	)	)	PUNCT
cana-1859	194	48	650	650	NUM
cana-1859	194	49	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	194	50	inputs	input	NOUN
cana-1859	194	51	.	.	PUNCT
cana-1859	195	1	this	this	DET
cana-1859	195	2	optimization	optimization	NOUN
cana-1859	195	3	can	can	AUX
cana-1859	195	4	lead	lead	VERB
cana-1859	195	5	to	to	ADP
cana-1859	195	6	significant	significant	ADJ
cana-1859	195	7	improvements	improvement	NOUN
cana-1859	195	8	in	in	ADP
cana-1859	195	9	the	the	DET
cana-1859	195	10	efficiency	efficiency	NOUN
cana-1859	195	11	,	,	PUNCT
cana-1859	195	12	speed	speed	NOUN
cana-1859	195	13	,	,	PUNCT
cana-1859	195	14	and	and	CCONJ
cana-1859	195	15	resource	resource	NOUN
cana-1859	195	16	utilization	utilization	NOUN
cana-1859	195	17	of	of	ADP
cana-1859	195	18	cnns	cnn	NOUN
cana-1859	195	19	,	,	PUNCT
cana-1859	195	20	particularly	particularly	ADV
cana-1859	195	21	beneficial	beneficial	ADJ
cana-1859	195	22	in	in	ADP
cana-1859	195	23	large	large	ADJ
cana-1859	195	24	-	-	PUNCT
cana-1859	195	25	scale	scale	NOUN
cana-1859	195	26	and	and	CCONJ
cana-1859	195	27	complex	complex	ADJ
cana-1859	195	28	image	image	NOUN
cana-1859	195	29	processing	processing	NOUN
cana-1859	195	30	tasks	task	NOUN
cana-1859	195	31	.	.	PUNCT
cana-1859	196	1	in	in	ADP
cana-1859	196	2	contrast	contrast	NOUN
cana-1859	196	3	,	,	PUNCT
cana-1859	196	4	paravartya	paravartya	ADJ
cana-1859	196	5	yojayet	yojayet	NOUN
cana-1859	196	6	is	be	AUX
cana-1859	196	7	a	a	DET
cana-1859	196	8	principle	principle	NOUN
cana-1859	196	9	from	from	ADP
cana-1859	196	10	vedic	vedic	ADJ
cana-1859	196	11	mathematics	mathematic	NOUN
cana-1859	196	12	that	that	PRON
cana-1859	196	13	translates	translate	VERB
cana-1859	196	14	to	to	ADP
cana-1859	196	15	"	"	PUNCT
cana-1859	196	16	transpose	transpose	VERB
cana-1859	196	17	and	and	CCONJ
cana-1859	196	18	adjust	adjust	VERB
cana-1859	196	19	.	.	PUNCT
cana-1859	196	20	"	"	PUNCT
cana-1859	197	1	this	this	DET
cana-1859	197	2	sutra	sutra	NOUN
cana-1859	197	3	is	be	AUX
cana-1859	197	4	typically	typically	ADV
cana-1859	197	5	used	use	VERB
cana-1859	197	6	for	for	ADP
cana-1859	197	7	solving	solve	VERB
cana-1859	197	8	linear	linear	ADJ
cana-1859	197	9	equations	equation	NOUN
cana-1859	197	10	and	and	CCONJ
cana-1859	197	11	can	can	AUX
cana-1859	197	12	be	be	AUX
cana-1859	197	13	interpreted	interpret	VERB
cana-1859	197	14	in	in	ADP
cana-1859	197	15	the	the	DET
cana-1859	197	16	context	context	NOUN
cana-1859	197	17	of	of	ADP
cana-1859	197	18	neural	neural	ADJ
cana-1859	197	19	networks	network	NOUN
cana-1859	197	20	as	as	ADP
cana-1859	197	21	a	a	DET
cana-1859	197	22	method	method	NOUN
cana-1859	197	23	for	for	ADP
cana-1859	197	24	rearranging	rearrange	VERB
cana-1859	197	25	or	or	CCONJ
cana-1859	197	26	transforming	transform	VERB
cana-1859	197	27	equations	equation	NOUN
cana-1859	197	28	to	to	PART
cana-1859	197	29	simplify	simplify	VERB
cana-1859	197	30	calculations	calculation	NOUN
cana-1859	197	31	.	.	PUNCT
cana-1859	198	1	in	in	ADP
cana-1859	198	2	convolutional	convolutional	ADJ
cana-1859	198	3	neural	neural	ADJ
cana-1859	198	4	networks	network	NOUN
cana-1859	198	5	(	(	PUNCT
cana-1859	198	6	cnns	cnns	PROPN
cana-1859	198	7	)	)	PUNCT
cana-1859	198	8	,	,	PUNCT
cana-1859	198	9	this	this	PRON
cana-1859	198	10	can	can	AUX
cana-1859	198	11	be	be	AUX
cana-1859	198	12	applied	apply	VERB
cana-1859	198	13	in	in	ADP
cana-1859	198	14	the	the	DET
cana-1859	198	15	optimization	optimization	NOUN
cana-1859	198	16	of	of	ADP
cana-1859	198	17	various	various	ADJ
cana-1859	198	18	operations	operation	NOUN
cana-1859	198	19	,	,	PUNCT
cana-1859	198	20	especially	especially	ADV
cana-1859	198	21	those	those	PRON
cana-1859	198	22	involving	involve	VERB
cana-1859	198	23	matrix	matrix	NOUN
cana-1859	198	24	transformations	transformation	NOUN
cana-1859	198	25	and	and	CCONJ
cana-1859	198	26	linear	linear	ADJ
cana-1859	198	27	equations	equation	NOUN
cana-1859	198	28	.	.	PUNCT
cana-1859	199	1	cnns	cnns	PROPN
cana-1859	199	2	involve	involve	VERB
cana-1859	199	3	numerous	numerous	ADJ
cana-1859	199	4	linear	linear	ADJ
cana-1859	199	5	and	and	CCONJ
cana-1859	199	6	non	non	ADJ
cana-1859	199	7	-	-	ADJ
cana-1859	199	8	linear	linear	ADJ
cana-1859	199	9	transformations	transformation	NOUN
cana-1859	199	10	,	,	PUNCT
cana-1859	199	11	especially	especially	ADV
cana-1859	199	12	in	in	ADP
cana-1859	199	13	fully	fully	ADV
cana-1859	199	14	connected	connected	ADJ
cana-1859	199	15	layers	layer	NOUN
cana-1859	199	16	and	and	CCONJ
cana-1859	199	17	convolutional	convolutional	ADJ
cana-1859	199	18	layers	layer	NOUN
cana-1859	199	19	.	.	PUNCT
cana-1859	200	1	the	the	DET
cana-1859	200	2	paravartya	paravartya	ADJ
cana-1859	200	3	yojayet	yojayet	NOUN
cana-1859	200	4	sutra	sutra	NOUN
cana-1859	200	5	can	can	AUX
cana-1859	200	6	be	be	AUX
cana-1859	200	7	applied	apply	VERB
cana-1859	200	8	to	to	PART
cana-1859	200	9	optimize	optimize	VERB
cana-1859	200	10	these	these	DET
cana-1859	200	11	transformations	transformation	NOUN
cana-1859	200	12	by	by	ADP
cana-1859	200	13	rearranging	rearrange	VERB
cana-1859	200	14	the	the	DET
cana-1859	200	15	elements	element	NOUN
cana-1859	200	16	of	of	ADP
cana-1859	200	17	matrices	matrix	NOUN
cana-1859	200	18	or	or	CCONJ
cana-1859	200	19	adjusting	adjust	VERB
cana-1859	200	20	the	the	DET
cana-1859	200	21	operations	operation	NOUN
cana-1859	200	22	to	to	PART
cana-1859	200	23	reduce	reduce	VERB
cana-1859	200	24	computational	computational	ADJ
cana-1859	200	25	complexity	complexity	NOUN
cana-1859	200	26	.	.	PUNCT
cana-1859	201	1	consider	consider	VERB
cana-1859	201	2	a	a	DET
cana-1859	201	3	fully	fully	ADV
cana-1859	201	4	connected	connect	VERB
cana-1859	201	5	layer	layer	NOUN
cana-1859	201	6	where	where	SCONJ
cana-1859	201	7	the	the	DET
cana-1859	201	8	output	output	NOUN
cana-1859	201	9	is	be	AUX
cana-1859	201	10	calculated	calculate	VERB
cana-1859	201	11	as	as	ADP
cana-1859	201	12	a	a	DET
cana-1859	201	13	weighted	weighted	ADJ
cana-1859	201	14	sum	sum	NOUN
cana-1859	201	15	of	of	ADP
cana-1859	201	16	inputs	input	NOUN
cana-1859	201	17	,	,	PUNCT
cana-1859	201	18	typically	typically	ADV
cana-1859	201	19	expressed	express	VERB
cana-1859	201	20	via	via	ADP
cana-1859	201	21	equation	equation	NOUN
cana-1859	201	22	17	17	NUM
cana-1859	201	23	,	,	PUNCT
cana-1859	201	24	𝑂	𝑂	PROPN
cana-1859	201	25	=	=	SYM
cana-1859	201	26	𝑊	𝑊	PROPN
cana-1859	201	27	⋅	⋅	PROPN
cana-1859	201	28	𝑋	𝑋	NOUN
cana-1859	201	29	+	+	CCONJ
cana-1859	201	30	𝑏	𝑏	NOUN
cana-1859	201	31	…	…	PUNCT
cana-1859	201	32	(	(	PUNCT
cana-1859	201	33	17	17	NUM
cana-1859	201	34	)	)	PUNCT
cana-1859	201	35	where	where	SCONJ
cana-1859	201	36	,	,	PUNCT
cana-1859	201	37	o	o	PROPN
cana-1859	201	38	is	be	AUX
cana-1859	201	39	the	the	DET
cana-1859	201	40	output	output	NOUN
cana-1859	201	41	,	,	PUNCT
cana-1859	201	42	w	w	PROPN
cana-1859	201	43	is	be	AUX
cana-1859	201	44	the	the	DET
cana-1859	201	45	weight	weight	NOUN
cana-1859	201	46	matrix	matrix	NOUN
cana-1859	201	47	,	,	PUNCT
cana-1859	201	48	x	x	X
cana-1859	201	49	is	be	AUX
cana-1859	201	50	the	the	DET
cana-1859	201	51	input	input	NOUN
cana-1859	201	52	vector	vector	NOUN
cana-1859	201	53	,	,	PUNCT
cana-1859	201	54	and	and	CCONJ
cana-1859	201	55	b	b	NOUN
cana-1859	201	56	is	be	AUX
cana-1859	201	57	the	the	DET
cana-1859	201	58	bias	bias	NOUN
cana-1859	201	59	.	.	PUNCT
cana-1859	202	1	using	use	VERB
cana-1859	202	2	the	the	DET
cana-1859	202	3	paravartya	paravartya	ADJ
cana-1859	202	4	yojayet	yojayet	NOUN
cana-1859	202	5	sutra	sutra	NOUN
cana-1859	202	6	,	,	PUNCT
cana-1859	202	7	we	we	PRON
cana-1859	202	8	rearrange	rearrange	VERB
cana-1859	202	9	this	this	DET
cana-1859	202	10	equation	equation	NOUN
cana-1859	202	11	to	to	PART
cana-1859	202	12	optimize	optimize	VERB
cana-1859	202	13	the	the	DET
cana-1859	202	14	computation	computation	NOUN
cana-1859	202	15	,	,	PUNCT
cana-1859	202	16	especially	especially	ADV
cana-1859	202	17	if	if	SCONJ
cana-1859	202	18	the	the	DET
cana-1859	202	19	matrix	matrix	NOUN
cana-1859	202	20	w	w	NOUN
cana-1859	202	21	or	or	CCONJ
cana-1859	202	22	vector	vector	NOUN
cana-1859	202	23	x	x	PUNCT
cana-1859	202	24	has	have	VERB
cana-1859	202	25	special	special	ADJ
cana-1859	202	26	properties	property	NOUN
cana-1859	202	27	that	that	PRON
cana-1859	202	28	allow	allow	VERB
cana-1859	202	29	for	for	ADP
cana-1859	202	30	simplification	simplification	NOUN
cana-1859	202	31	.	.	PUNCT
cana-1859	203	1	suppose	suppose	VERB
cana-1859	203	2	�	�	PROPN
cana-1859	203	3	w	w	PROPN
cana-1859	203	4	is	be	AUX
cana-1859	203	5	a	a	DET
cana-1859	203	6	matrix	matrix	NOUN
cana-1859	203	7	that	that	PRON
cana-1859	203	8	can	can	AUX
cana-1859	203	9	be	be	AUX
cana-1859	203	10	decomposed	decompose	VERB
cana-1859	203	11	or	or	CCONJ
cana-1859	203	12	rearranged	rearrange	VERB
cana-1859	203	13	into	into	ADP
cana-1859	203	14	simpler	simple	ADJ
cana-1859	203	15	matrices	matrix	NOUN
cana-1859	203	16	for	for	ADP
cana-1859	203	17	efficient	efficient	ADJ
cana-1859	203	18	computation	computation	NOUN
cana-1859	203	19	,	,	PUNCT
cana-1859	203	20	say	say	VERB
cana-1859	203	21	w	w	NOUN
cana-1859	203	22	=	=	NOUN
cana-1859	203	23	a⋅b	a⋅b	ADJ
cana-1859	203	24	,	,	PUNCT
cana-1859	203	25	where	where	SCONJ
cana-1859	203	26	a	a	PRON
cana-1859	203	27	and	and	CCONJ
cana-1859	203	28	b	b	NOUN
cana-1859	203	29	are	be	AUX
cana-1859	203	30	matrices	matrix	NOUN
cana-1859	203	31	with	with	ADP
cana-1859	203	32	properties	property	NOUN
cana-1859	203	33	that	that	PRON
cana-1859	203	34	simplify	simplify	VERB
cana-1859	203	35	multiplication	multiplication	NOUN
cana-1859	203	36	.	.	PUNCT
cana-1859	204	1	the	the	DET
cana-1859	204	2	output	output	NOUN
cana-1859	204	3	process	process	NOUN
cana-1859	204	4	is	be	AUX
cana-1859	204	5	then	then	ADV
cana-1859	204	6	represented	represent	VERB
cana-1859	204	7	via	via	ADP
cana-1859	204	8	equation	equation	NOUN
cana-1859	204	9	18	18	NUM
cana-1859	204	10	,	,	PUNCT
cana-1859	204	11	𝑂	𝑂	NOUN
cana-1859	204	12	=	=	SYM
cana-1859	204	13	(	(	PUNCT
cana-1859	204	14	𝐴	𝐴	PROPN
cana-1859	204	15	⋅	⋅	PROPN
cana-1859	204	16	𝐵	𝐵	PROPN
cana-1859	204	17	)	)	PUNCT
cana-1859	204	18	⋅	⋅	PROPN
cana-1859	204	19	𝑋	𝑋	PROPN
cana-1859	204	20	+	+	CCONJ
cana-1859	204	21	𝑏	𝑏	NOUN
cana-1859	204	22	…	…	PUNCT
cana-1859	204	23	(	(	PUNCT
cana-1859	204	24	18	18	NUM
cana-1859	204	25	)	)	PUNCT
cana-1859	204	26	this	this	DET
cana-1859	204	27	decomposition	decomposition	NOUN
cana-1859	204	28	can	can	AUX
cana-1859	204	29	significantly	significantly	ADV
cana-1859	204	30	simplify	simplify	VERB
cana-1859	204	31	the	the	DET
cana-1859	204	32	computation	computation	NOUN
cana-1859	204	33	if	if	SCONJ
cana-1859	204	34	,	,	PUNCT
cana-1859	204	35	for	for	ADP
cana-1859	204	36	example	example	NOUN
cana-1859	204	37	,	,	PUNCT
cana-1859	204	38	a	a	PRON
cana-1859	204	39	and	and	CCONJ
cana-1859	204	40	b	b	NOUN
cana-1859	204	41	are	be	AUX
cana-1859	204	42	sparse	sparse	ADJ
cana-1859	204	43	matrices	matrix	NOUN
cana-1859	204	44	or	or	CCONJ
cana-1859	204	45	have	have	VERB
cana-1859	204	46	other	other	ADJ
cana-1859	204	47	properties	property	NOUN
cana-1859	204	48	that	that	PRON
cana-1859	204	49	make	make	VERB
cana-1859	204	50	multiplication	multiplication	NOUN
cana-1859	204	51	with	with	ADP
cana-1859	204	52	x	x	X
cana-1859	204	53	less	less	ADV
cana-1859	204	54	computationally	computationally	ADV
cana-1859	204	55	intensive	intensive	ADJ
cana-1859	204	56	than	than	ADP
cana-1859	204	57	the	the	DET
cana-1859	204	58	original	original	ADJ
cana-1859	204	59	w.	w.	NOUN
cana-1859	204	60	reasons	reason	NOUN
cana-1859	204	61	for	for	ADP
cana-1859	204	62	improvement	improvement	NOUN
cana-1859	204	63	in	in	ADP
cana-1859	204	64	performance	performance	NOUN
cana-1859	204	65	1	1	NUM
cana-1859	204	66	.	.	PUNCT
cana-1859	204	67	computational	computational	ADJ
cana-1859	204	68	efficiency	efficiency	NOUN
cana-1859	204	69	:	:	PUNCT
cana-1859	204	70	decomposing	decompose	VERB
cana-1859	204	71	or	or	CCONJ
cana-1859	204	72	rearranging	rearrange	VERB
cana-1859	204	73	matrices	matrix	NOUN
cana-1859	204	74	can	can	AUX
cana-1859	204	75	lead	lead	VERB
cana-1859	204	76	to	to	ADP
cana-1859	204	77	more	more	ADV
cana-1859	204	78	efficient	efficient	ADJ
cana-1859	204	79	computations	computation	NOUN
cana-1859	204	80	,	,	PUNCT
cana-1859	204	81	especially	especially	ADV
cana-1859	204	82	when	when	SCONJ
cana-1859	204	83	the	the	DET
cana-1859	204	84	new	new	ADJ
cana-1859	204	85	matrices	matrix	NOUN
cana-1859	204	86	have	have	VERB
cana-1859	204	87	properties	property	NOUN
cana-1859	204	88	that	that	PRON
cana-1859	204	89	simplify	simplify	VERB
cana-1859	204	90	multiplication	multiplication	NOUN
cana-1859	204	91	(	(	PUNCT
cana-1859	204	92	like	like	ADP
cana-1859	204	93	sparsity	sparsity	NOUN
cana-1859	204	94	or	or	CCONJ
cana-1859	204	95	lower	low	ADJ
cana-1859	204	96	dimensionality	dimensionality	NOUN
cana-1859	204	97	)	)	PUNCT
cana-1859	204	98	.	.	PUNCT
cana-1859	205	1	2	2	X
cana-1859	205	2	.	.	X
cana-1859	205	3	reduced	reduce	VERB
cana-1859	205	4	complexity	complexity	NOUN
cana-1859	205	5	in	in	ADP
cana-1859	205	6	matrix	matrix	NOUN
cana-1859	205	7	operations	operation	NOUN
cana-1859	205	8	:	:	PUNCT
cana-1859	205	9	simplified	simplify	VERB
cana-1859	205	10	matrix	matrix	NOUN
cana-1859	205	11	operations	operation	NOUN
cana-1859	205	12	can	can	AUX
cana-1859	205	13	decrease	decrease	VERB
cana-1859	205	14	the	the	DET
cana-1859	205	15	time	time	NOUN
cana-1859	205	16	complexity	complexity	NOUN
cana-1859	205	17	of	of	ADP
cana-1859	205	18	operations	operation	NOUN
cana-1859	205	19	within	within	ADP
cana-1859	205	20	the	the	DET
cana-1859	205	21	network	network	NOUN
cana-1859	205	22	,	,	PUNCT
cana-1859	205	23	particularly	particularly	ADV
cana-1859	205	24	in	in	ADP
cana-1859	205	25	fully	fully	ADV
cana-1859	205	26	connected	connected	ADJ
cana-1859	205	27	layers	layer	NOUN
cana-1859	205	28	where	where	SCONJ
cana-1859	205	29	matrix	matrix	NOUN
cana-1859	205	30	multiplications	multiplication	NOUN
cana-1859	205	31	are	be	AUX
cana-1859	205	32	prevalent	prevalent	ADJ
cana-1859	205	33	.	.	PUNCT
cana-1859	206	1	3	3	X
cana-1859	206	2	.	.	NOUN
cana-1859	206	3	optimized	optimize	VERB
cana-1859	206	4	resource	resource	NOUN
cana-1859	206	5	utilization	utilization	NOUN
cana-1859	206	6	:	:	PUNCT
cana-1859	206	7	efficient	efficient	ADJ
cana-1859	206	8	matrix	matrix	NOUN
cana-1859	206	9	operations	operation	NOUN
cana-1859	206	10	can	can	AUX
cana-1859	206	11	lead	lead	VERB
cana-1859	206	12	to	to	ADP
cana-1859	206	13	better	well	ADJ
cana-1859	206	14	utilization	utilization	NOUN
cana-1859	206	15	of	of	ADP
cana-1859	206	16	computational	computational	ADJ
cana-1859	206	17	resources	resource	NOUN
cana-1859	206	18	,	,	PUNCT
cana-1859	206	19	including	include	VERB
cana-1859	206	20	memory	memory	NOUN
cana-1859	206	21	and	and	CCONJ
cana-1859	206	22	processing	processing	NOUN
cana-1859	206	23	power	power	NOUN
cana-1859	206	24	,	,	PUNCT
cana-1859	206	25	which	which	PRON
cana-1859	206	26	is	be	AUX
cana-1859	206	27	vital	vital	ADJ
cana-1859	206	28	for	for	ADP
cana-1859	206	29	training	training	NOUN
cana-1859	206	30	and	and	CCONJ
cana-1859	206	31	deploying	deploy	VERB
cana-1859	206	32	large	large	ADJ
cana-1859	206	33	-	-	PUNCT
cana-1859	206	34	scale	scale	NOUN
cana-1859	206	35	cnns	cnn	NOUN
cana-1859	206	36	.	.	PUNCT
cana-1859	207	1	communications	communication	NOUN
cana-1859	207	2	on	on	ADP
cana-1859	207	3	applied	apply	VERB
cana-1859	207	4	nonlinear	nonlinear	ADJ
cana-1859	207	5	analysis	analysis	NOUN
cana-1859	207	6	issn	issn	NOUN
cana-1859	207	7	:	:	PUNCT
cana-1859	207	8	1074	1074	NUM
cana-1859	207	9	-	-	PUNCT
cana-1859	207	10	133x	133x	NUM
cana-1859	207	11	vol	vol	NOUN
cana-1859	207	12	32	32	NUM
cana-1859	207	13	no	no	NOUN
cana-1859	207	14	.	.	NOUN
cana-1859	207	15	2	2	NUM
cana-1859	207	16	(	(	PUNCT
cana-1859	207	17	2025	2025	NUM
cana-1859	207	18	)	)	PUNCT
cana-1859	207	19	651	651	NUM
cana-1859	207	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	207	21	4	4	NUM
cana-1859	207	22	.	.	PUNCT
cana-1859	207	23	enhanced	enhance	VERB
cana-1859	207	24	scalability	scalability	NOUN
cana-1859	207	25	:	:	PUNCT
cana-1859	207	26	such	such	ADJ
cana-1859	207	27	optimizations	optimization	NOUN
cana-1859	207	28	can	can	AUX
cana-1859	207	29	make	make	VERB
cana-1859	207	30	the	the	DET
cana-1859	207	31	network	network	NOUN
cana-1859	207	32	more	more	ADV
cana-1859	207	33	scalable	scalable	ADJ
cana-1859	207	34	,	,	PUNCT
cana-1859	207	35	handling	handle	VERB
cana-1859	207	36	larger	large	ADJ
cana-1859	207	37	input	input	NOUN
cana-1859	207	38	sizes	size	NOUN
cana-1859	207	39	or	or	CCONJ
cana-1859	207	40	more	more	ADJ
cana-1859	207	41	complex	complex	ADJ
cana-1859	207	42	architectures	architecture	NOUN
cana-1859	207	43	more	more	ADV
cana-1859	207	44	efficiently	efficiently	ADV
cana-1859	207	45	.	.	PUNCT
cana-1859	208	1	the	the	DET
cana-1859	208	2	application	application	NOUN
cana-1859	208	3	of	of	ADP
cana-1859	208	4	the	the	DET
cana-1859	208	5	paravartya	paravartya	ADJ
cana-1859	208	6	yojayet	yojayet	NOUN
cana-1859	208	7	sutra	sutra	NOUN
cana-1859	208	8	in	in	ADP
cana-1859	208	9	cnns	cnns	PROPN
cana-1859	208	10	presents	present	VERB
cana-1859	208	11	a	a	DET
cana-1859	208	12	unique	unique	ADJ
cana-1859	208	13	approach	approach	NOUN
cana-1859	208	14	to	to	ADP
cana-1859	208	15	optimizing	optimize	VERB
cana-1859	208	16	the	the	DET
cana-1859	208	17	network	network	NOUN
cana-1859	208	18	’s	’s	PART
cana-1859	208	19	computational	computational	ADJ
cana-1859	208	20	processes	process	NOUN
cana-1859	208	21	.	.	PUNCT
cana-1859	209	1	by	by	ADP
cana-1859	209	2	rearranging	rearrange	VERB
cana-1859	209	3	and	and	CCONJ
cana-1859	209	4	adjusting	adjust	VERB
cana-1859	209	5	the	the	DET
cana-1859	209	6	elements	element	NOUN
cana-1859	209	7	within	within	ADP
cana-1859	209	8	the	the	DET
cana-1859	209	9	network	network	NOUN
cana-1859	209	10	’s	’s	PART
cana-1859	209	11	linear	linear	PROPN
cana-1859	209	12	equations	equation	NOUN
cana-1859	209	13	,	,	PUNCT
cana-1859	209	14	this	this	DET
cana-1859	209	15	principle	principle	NOUN
cana-1859	209	16	can	can	AUX
cana-1859	209	17	lead	lead	VERB
cana-1859	209	18	to	to	ADP
cana-1859	209	19	improvements	improvement	NOUN
cana-1859	209	20	in	in	ADP
cana-1859	209	21	computational	computational	ADJ
cana-1859	209	22	efficiency	efficiency	NOUN
cana-1859	209	23	,	,	PUNCT
cana-1859	209	24	resource	resource	NOUN
cana-1859	209	25	optimization	optimization	NOUN
cana-1859	209	26	,	,	PUNCT
cana-1859	209	27	and	and	CCONJ
cana-1859	209	28	scalability	scalability	NOUN
cana-1859	209	29	,	,	PUNCT
cana-1859	209	30	making	make	VERB
cana-1859	209	31	it	it	PRON
cana-1859	209	32	particularly	particularly	ADV
cana-1859	209	33	valuable	valuable	ADJ
cana-1859	209	34	for	for	ADP
cana-1859	209	35	complex	complex	ADJ
cana-1859	209	36	and	and	CCONJ
cana-1859	209	37	large	large	ADJ
cana-1859	209	38	-	-	PUNCT
cana-1859	209	39	scale	scale	NOUN
cana-1859	209	40	image	image	NOUN
cana-1859	209	41	processing	processing	NOUN
cana-1859	209	42	tasks	task	NOUN
cana-1859	209	43	in	in	ADP
cana-1859	209	44	cnns	cnn	NOUN
cana-1859	209	45	.	.	PUNCT
cana-1859	210	1	similarly	similarly	ADV
cana-1859	210	2	,	,	PUNCT
cana-1859	210	3	sankalana	sankalana	ADJ
cana-1859	210	4	-	-	PUNCT
cana-1859	210	5	vyavakalanabhyam	vyavakalanabhyam	NOUN
cana-1859	210	6	is	be	AUX
cana-1859	210	7	a	a	DET
cana-1859	210	8	principle	principle	NOUN
cana-1859	210	9	from	from	ADP
cana-1859	210	10	vedic	vedic	ADJ
cana-1859	210	11	mathematics	mathematic	NOUN
cana-1859	210	12	that	that	PRON
cana-1859	210	13	translates	translate	VERB
cana-1859	210	14	to	to	PART
cana-1859	210	15	"	"	PUNCT
cana-1859	210	16	by	by	ADP
cana-1859	210	17	addition	addition	NOUN
cana-1859	210	18	and	and	CCONJ
cana-1859	210	19	by	by	ADP
cana-1859	210	20	subtraction	subtraction	NOUN
cana-1859	210	21	.	.	PUNCT
cana-1859	210	22	"	"	PUNCT
cana-1859	211	1	this	this	DET
cana-1859	211	2	sutra	sutra	NOUN
cana-1859	211	3	can	can	AUX
cana-1859	211	4	be	be	AUX
cana-1859	211	5	applied	apply	VERB
cana-1859	211	6	in	in	ADP
cana-1859	211	7	the	the	DET
cana-1859	211	8	context	context	NOUN
cana-1859	211	9	of	of	ADP
cana-1859	211	10	convolutional	convolutional	ADJ
cana-1859	211	11	neural	neural	ADJ
cana-1859	211	12	networks	network	NOUN
cana-1859	211	13	(	(	PUNCT
cana-1859	211	14	cnns	cnns	PROPN
cana-1859	211	15	)	)	PUNCT
cana-1859	211	16	to	to	PART
cana-1859	211	17	optimize	optimize	VERB
cana-1859	211	18	the	the	DET
cana-1859	211	19	network	network	NOUN
cana-1859	211	20	's	's	PART
cana-1859	211	21	operations	operation	NOUN
cana-1859	211	22	,	,	PUNCT
cana-1859	211	23	particularly	particularly	ADV
cana-1859	211	24	in	in	ADP
cana-1859	211	25	the	the	DET
cana-1859	211	26	forward	forward	ADJ
cana-1859	211	27	and	and	CCONJ
cana-1859	211	28	backward	backward	ADJ
cana-1859	211	29	passes	pass	NOUN
cana-1859	211	30	.	.	PUNCT
cana-1859	212	1	it	it	PRON
cana-1859	212	2	involves	involve	VERB
cana-1859	212	3	modifying	modify	VERB
cana-1859	212	4	equations	equation	NOUN
cana-1859	212	5	to	to	PART
cana-1859	212	6	simplify	simplify	VERB
cana-1859	212	7	calculations	calculation	NOUN
cana-1859	212	8	and	and	CCONJ
cana-1859	212	9	improve	improve	VERB
cana-1859	212	10	computational	computational	ADJ
cana-1859	212	11	efficiency	efficiency	NOUN
cana-1859	212	12	.	.	PUNCT
cana-1859	213	1	in	in	ADP
cana-1859	213	2	cnns	cnns	PROPN
cana-1859	213	3	,	,	PUNCT
cana-1859	213	4	various	various	ADJ
cana-1859	213	5	operations	operation	NOUN
cana-1859	213	6	involve	involve	VERB
cana-1859	213	7	summation	summation	NOUN
cana-1859	213	8	and	and	CCONJ
cana-1859	213	9	subtraction	subtraction	NOUN
cana-1859	213	10	of	of	ADP
cana-1859	213	11	values	value	NOUN
cana-1859	213	12	,	,	PUNCT
cana-1859	213	13	such	such	ADJ
cana-1859	213	14	as	as	ADP
cana-1859	213	15	element	element	ADJ
cana-1859	213	16	-	-	ADJ
cana-1859	213	17	wise	wise	ADJ
cana-1859	213	18	addition	addition	NOUN
cana-1859	213	19	and	and	CCONJ
cana-1859	213	20	subtraction	subtraction	NOUN
cana-1859	213	21	in	in	ADP
cana-1859	213	22	convolutional	convolutional	ADJ
cana-1859	213	23	layers	layer	NOUN
cana-1859	213	24	,	,	PUNCT
cana-1859	213	25	pooling	pool	VERB
cana-1859	213	26	layers	layer	NOUN
cana-1859	213	27	,	,	PUNCT
cana-1859	213	28	and	and	CCONJ
cana-1859	213	29	activation	activation	NOUN
cana-1859	213	30	functions	function	NOUN
cana-1859	213	31	.	.	PUNCT
cana-1859	214	1	the	the	DET
cana-1859	214	2	sankalana	sankalana	PROPN
cana-1859	214	3	-	-	PUNCT
cana-1859	214	4	vyavakalanabhyam	vyavakalanabhyam	NOUN
cana-1859	214	5	sutra	sutra	NOUN
cana-1859	214	6	can	can	AUX
cana-1859	214	7	be	be	AUX
cana-1859	214	8	applied	apply	VERB
cana-1859	214	9	to	to	PART
cana-1859	214	10	optimize	optimize	VERB
cana-1859	214	11	these	these	DET
cana-1859	214	12	operations	operation	NOUN
cana-1859	214	13	by	by	ADP
cana-1859	214	14	rearranging	rearrange	VERB
cana-1859	214	15	and	and	CCONJ
cana-1859	214	16	simplifying	simplify	VERB
cana-1859	214	17	equations	equation	NOUN
cana-1859	214	18	.	.	PUNCT
cana-1859	215	1	consider	consider	VERB
cana-1859	215	2	an	an	DET
cana-1859	215	3	example	example	NOUN
cana-1859	215	4	of	of	ADP
cana-1859	215	5	the	the	DET
cana-1859	215	6	forward	forward	ADJ
cana-1859	215	7	pass	pass	NOUN
cana-1859	215	8	in	in	ADP
cana-1859	215	9	a	a	DET
cana-1859	215	10	cnn	cnn	NOUN
cana-1859	215	11	where	where	SCONJ
cana-1859	215	12	the	the	DET
cana-1859	215	13	output	output	NOUN
cana-1859	215	14	of	of	ADP
cana-1859	215	15	a	a	DET
cana-1859	215	16	convolutional	convolutional	ADJ
cana-1859	215	17	layer	layer	NOUN
cana-1859	215	18	is	be	AUX
cana-1859	215	19	calculated	calculate	VERB
cana-1859	215	20	via	via	ADP
cana-1859	215	21	equation	equation	NOUN
cana-1859	215	22	19	19	NUM
cana-1859	215	23	,	,	PUNCT
cana-1859	215	24	𝑂	𝑂	PROPN
cana-1859	215	25	=	=	SYM
cana-1859	215	26	𝐴𝑐𝑡𝑖𝑣𝑎𝑡𝑖𝑜𝑛(𝑊	𝐴𝑐𝑡𝑖𝑣𝑎𝑡𝑖𝑜𝑛(𝑊	PROPN
cana-1859	215	27	⋅	⋅	PROPN
cana-1859	215	28	𝑋	𝑋	NOUN
cana-1859	215	29	+	+	CCONJ
cana-1859	215	30	𝑏	𝑏	NOUN
cana-1859	215	31	)	)	PUNCT
cana-1859	215	32	…	…	PUNCT
cana-1859	215	33	(	(	PUNCT
cana-1859	215	34	19	19	NUM
cana-1859	215	35	)	)	PUNCT
cana-1859	215	36	where	where	SCONJ
cana-1859	215	37	,	,	PUNCT
cana-1859	215	38	o	o	PROPN
cana-1859	215	39	is	be	AUX
cana-1859	215	40	the	the	DET
cana-1859	215	41	output	output	NOUN
cana-1859	215	42	,	,	PUNCT
cana-1859	215	43	w	w	PROPN
cana-1859	215	44	is	be	AUX
cana-1859	215	45	the	the	DET
cana-1859	215	46	weight	weight	NOUN
cana-1859	215	47	tensor	tensor	NOUN
cana-1859	215	48	,	,	PUNCT
cana-1859	215	49	x	x	X
cana-1859	215	50	is	be	AUX
cana-1859	215	51	the	the	DET
cana-1859	215	52	input	input	NOUN
cana-1859	215	53	tensor	tensor	NOUN
cana-1859	215	54	,	,	PUNCT
cana-1859	215	55	b	b	PROPN
cana-1859	215	56	is	be	AUX
cana-1859	215	57	the	the	DET
cana-1859	215	58	bias	bias	NOUN
cana-1859	215	59	tensor	tensor	NOUN
cana-1859	215	60	,	,	PUNCT
cana-1859	215	61	and	and	CCONJ
cana-1859	215	62	activation	activation	NOUN
cana-1859	215	63	represents	represent	VERB
cana-1859	215	64	the	the	DET
cana-1859	215	65	activation	activation	NOUN
cana-1859	215	66	function	function	NOUN
cana-1859	215	67	.	.	PUNCT
cana-1859	216	1	using	use	VERB
cana-1859	216	2	the	the	DET
cana-1859	216	3	sankalana	sankalana	ADJ
cana-1859	216	4	-	-	PUNCT
cana-1859	216	5	vyavakalanabhyam	vyavakalanabhyam	ADJ
cana-1859	216	6	sutra	sutra	NOUN
cana-1859	216	7	,	,	PUNCT
cana-1859	216	8	we	we	PRON
cana-1859	216	9	can	can	AUX
cana-1859	216	10	modify	modify	VERB
cana-1859	216	11	this	this	DET
cana-1859	216	12	process	process	NOUN
cana-1859	216	13	to	to	PART
cana-1859	216	14	simplify	simplify	VERB
cana-1859	216	15	calculations	calculation	NOUN
cana-1859	216	16	via	via	ADP
cana-1859	216	17	equation	equation	NOUN
cana-1859	216	18	20	20	NUM
cana-1859	216	19	,	,	PUNCT
cana-1859	216	20	𝑂	𝑂	PROPN
cana-1859	216	21	=	=	SYM
cana-1859	216	22	𝐴𝑐𝑡𝑖𝑣𝑎𝑡𝑖𝑜𝑛(𝑊	𝐴𝑐𝑡𝑖𝑣𝑎𝑡𝑖𝑜𝑛(𝑊	PROPN
cana-1859	216	23	⋅	⋅	PROPN
cana-1859	216	24	𝑋	𝑋	PROPN
cana-1859	216	25	)	)	PUNCT
cana-1859	216	26	+	+	NUM
cana-1859	217	1	𝐴𝑐𝑡𝑖𝑣𝑎𝑡𝑖𝑜𝑛(𝑏	𝐴𝑐𝑡𝑖𝑣𝑎𝑡𝑖𝑜𝑛(𝑏	NOUN
cana-1859	217	2	)	)	PUNCT
cana-1859	217	3	…	…	PUNCT
cana-1859	217	4	(	(	PUNCT
cana-1859	217	5	20	20	NUM
cana-1859	217	6	)	)	PUNCT
cana-1859	217	7	this	this	DET
cana-1859	217	8	modification	modification	NOUN
cana-1859	217	9	separates	separate	VERB
cana-1859	217	10	the	the	DET
cana-1859	217	11	addition	addition	NOUN
cana-1859	217	12	operation	operation	NOUN
cana-1859	217	13	into	into	ADP
cana-1859	217	14	two	two	NUM
cana-1859	217	15	separate	separate	ADJ
cana-1859	217	16	activation	activation	NOUN
cana-1859	217	17	functions	function	NOUN
cana-1859	217	18	,	,	PUNCT
cana-1859	217	19	reducing	reduce	VERB
cana-1859	217	20	the	the	DET
cana-1859	217	21	complexity	complexity	NOUN
cana-1859	217	22	of	of	ADP
cana-1859	217	23	the	the	DET
cana-1859	217	24	calculation	calculation	NOUN
cana-1859	217	25	.	.	PUNCT
cana-1859	218	1	reasons	reason	NOUN
cana-1859	218	2	for	for	ADP
cana-1859	218	3	improvement	improvement	NOUN
cana-1859	218	4	in	in	ADP
cana-1859	218	5	performance	performance	NOUN
cana-1859	218	6	are	be	AUX
cana-1859	218	7	as	as	SCONJ
cana-1859	218	8	follows	follow	NOUN
cana-1859	218	9	,	,	PUNCT
cana-1859	218	10	1	1	X
cana-1859	218	11	.	.	PUNCT
cana-1859	218	12	computational	computational	ADJ
cana-1859	218	13	efficiency	efficiency	NOUN
cana-1859	218	14	:	:	PUNCT
cana-1859	218	15	separating	separate	VERB
cana-1859	218	16	the	the	DET
cana-1859	218	17	addition	addition	NOUN
cana-1859	218	18	operation	operation	NOUN
cana-1859	218	19	into	into	ADP
cana-1859	218	20	individual	individual	ADJ
cana-1859	218	21	activation	activation	NOUN
cana-1859	218	22	functions	function	NOUN
cana-1859	218	23	can	can	AUX
cana-1859	218	24	simplify	simplify	VERB
cana-1859	218	25	and	and	CCONJ
cana-1859	218	26	parallelize	parallelize	VERB
cana-1859	218	27	computations	computation	NOUN
cana-1859	218	28	,	,	PUNCT
cana-1859	218	29	leading	lead	VERB
cana-1859	218	30	to	to	ADP
cana-1859	218	31	faster	fast	ADV
cana-1859	218	32	forward	forward	ADV
cana-1859	218	33	passes	pass	VERB
cana-1859	218	34	in	in	ADP
cana-1859	218	35	the	the	DET
cana-1859	218	36	network	network	NOUN
cana-1859	218	37	.	.	PUNCT
cana-1859	219	1	2	2	X
cana-1859	219	2	.	.	X
cana-1859	219	3	reduced	reduce	VERB
cana-1859	219	4	complexity	complexity	NOUN
cana-1859	219	5	:	:	PUNCT
cana-1859	219	6	the	the	DET
cana-1859	219	7	modified	modify	VERB
cana-1859	219	8	equation	equation	NOUN
cana-1859	219	9	reduces	reduce	VERB
cana-1859	219	10	the	the	DET
cana-1859	219	11	computational	computational	ADJ
cana-1859	219	12	complexity	complexity	NOUN
cana-1859	219	13	of	of	ADP
cana-1859	219	14	the	the	DET
cana-1859	219	15	forward	forward	ADJ
cana-1859	219	16	pass	pass	NOUN
cana-1859	219	17	,	,	PUNCT
cana-1859	219	18	making	make	VERB
cana-1859	219	19	it	it	PRON
cana-1859	219	20	more	more	ADV
cana-1859	219	21	efficient	efficient	ADJ
cana-1859	219	22	,	,	PUNCT
cana-1859	219	23	especially	especially	ADV
cana-1859	219	24	on	on	ADP
cana-1859	219	25	hardware	hardware	NOUN
cana-1859	219	26	accelerators	accelerator	NOUN
cana-1859	219	27	like	like	ADP
cana-1859	219	28	gpus	gpu	NOUN
cana-1859	219	29	and	and	CCONJ
cana-1859	219	30	tpus	tpus	PROPN
cana-1859	219	31	.	.	PROPN
cana-1859	219	32	3	3	NUM
cana-1859	219	33	.	.	NUM
cana-1859	219	34	enhanced	enhance	VERB
cana-1859	219	35	gradient	gradient	ADJ
cana-1859	219	36	flow	flow	NOUN
cana-1859	219	37	:	:	PUNCT
cana-1859	219	38	in	in	ADP
cana-1859	219	39	the	the	DET
cana-1859	219	40	backward	backward	ADJ
cana-1859	219	41	pass	pass	NOUN
cana-1859	219	42	(	(	PUNCT
cana-1859	219	43	during	during	ADP
cana-1859	219	44	training	training	NOUN
cana-1859	219	45	)	)	PUNCT
cana-1859	219	46	,	,	PUNCT
cana-1859	219	47	simplifying	simplify	VERB
cana-1859	219	48	the	the	DET
cana-1859	219	49	equations	equation	NOUN
cana-1859	219	50	can	can	AUX
cana-1859	219	51	lead	lead	VERB
cana-1859	219	52	to	to	ADP
cana-1859	219	53	more	more	ADV
cana-1859	219	54	straightforward	straightforward	ADJ
cana-1859	219	55	gradient	gradient	NOUN
cana-1859	219	56	calculations	calculation	NOUN
cana-1859	219	57	,	,	PUNCT
cana-1859	219	58	improving	improve	VERB
cana-1859	219	59	the	the	DET
cana-1859	219	60	stability	stability	NOUN
cana-1859	219	61	and	and	CCONJ
cana-1859	219	62	convergence	convergence	NOUN
cana-1859	219	63	of	of	ADP
cana-1859	219	64	the	the	DET
cana-1859	219	65	training	training	NOUN
cana-1859	219	66	process	process	NOUN
cana-1859	219	67	.	.	PUNCT
cana-1859	220	1	4	4	X
cana-1859	220	2	.	.	X
cana-1859	220	3	resource	resource	NOUN
cana-1859	220	4	utilization	utilization	NOUN
cana-1859	220	5	:	:	PUNCT
cana-1859	220	6	efficient	efficient	ADJ
cana-1859	220	7	operations	operation	NOUN
cana-1859	220	8	reduce	reduce	VERB
cana-1859	220	9	memory	memory	NOUN
cana-1859	220	10	consumption	consumption	NOUN
cana-1859	220	11	and	and	CCONJ
cana-1859	220	12	improve	improve	VERB
cana-1859	220	13	resource	resource	NOUN
cana-1859	220	14	utilization	utilization	NOUN
cana-1859	220	15	,	,	PUNCT
cana-1859	220	16	allowing	allow	VERB
cana-1859	220	17	for	for	ADP
cana-1859	220	18	larger	large	ADJ
cana-1859	220	19	and	and	CCONJ
cana-1859	220	20	more	more	ADV
cana-1859	220	21	complex	complex	ADJ
cana-1859	220	22	cnn	cnn	PROPN
cana-1859	220	23	architectures	architecture	NOUN
cana-1859	220	24	.	.	PUNCT
cana-1859	221	1	communications	communication	NOUN
cana-1859	221	2	on	on	ADP
cana-1859	221	3	applied	apply	VERB
cana-1859	221	4	nonlinear	nonlinear	ADJ
cana-1859	221	5	analysis	analysis	NOUN
cana-1859	221	6	issn	issn	NOUN
cana-1859	221	7	:	:	PUNCT
cana-1859	221	8	1074	1074	NUM
cana-1859	221	9	-	-	PUNCT
cana-1859	221	10	133x	133x	NUM
cana-1859	221	11	vol	vol	NOUN
cana-1859	221	12	32	32	NUM
cana-1859	221	13	no	no	NOUN
cana-1859	221	14	.	.	NOUN
cana-1859	221	15	2	2	NUM
cana-1859	221	16	(	(	PUNCT
cana-1859	221	17	2025	2025	NUM
cana-1859	221	18	)	)	PUNCT
cana-1859	221	19	652	652	NUM
cana-1859	221	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	221	21	thus	thus	ADV
cana-1859	221	22	,	,	PUNCT
cana-1859	221	23	the	the	DET
cana-1859	221	24	application	application	NOUN
cana-1859	221	25	of	of	ADP
cana-1859	221	26	the	the	DET
cana-1859	221	27	sankalana	sankalana	ADJ
cana-1859	221	28	-	-	PUNCT
cana-1859	221	29	vyavakalanabhyam	vyavakalanabhyam	ADJ
cana-1859	221	30	sutra	sutra	NOUN
cana-1859	221	31	in	in	ADP
cana-1859	221	32	cnns	cnns	PROPN
cana-1859	221	33	offers	offer	VERB
cana-1859	221	34	a	a	DET
cana-1859	221	35	valuable	valuable	ADJ
cana-1859	221	36	approach	approach	NOUN
cana-1859	221	37	to	to	PART
cana-1859	221	38	optimize	optimize	VERB
cana-1859	221	39	network	network	NOUN
cana-1859	221	40	operations	operation	NOUN
cana-1859	221	41	.	.	PUNCT
cana-1859	222	1	by	by	ADP
cana-1859	222	2	rearranging	rearrange	VERB
cana-1859	222	3	and	and	CCONJ
cana-1859	222	4	simplifying	simplify	VERB
cana-1859	222	5	equations	equation	NOUN
cana-1859	222	6	involving	involve	VERB
cana-1859	222	7	addition	addition	NOUN
cana-1859	222	8	and	and	CCONJ
cana-1859	222	9	subtraction	subtraction	NOUN
cana-1859	222	10	,	,	PUNCT
cana-1859	222	11	this	this	DET
cana-1859	222	12	principle	principle	NOUN
cana-1859	222	13	can	can	AUX
cana-1859	222	14	lead	lead	VERB
cana-1859	222	15	to	to	ADP
cana-1859	222	16	improvements	improvement	NOUN
cana-1859	222	17	in	in	ADP
cana-1859	222	18	computational	computational	ADJ
cana-1859	222	19	efficiency	efficiency	NOUN
cana-1859	222	20	,	,	PUNCT
cana-1859	222	21	reduced	reduce	VERB
cana-1859	222	22	complexity	complexity	NOUN
cana-1859	222	23	,	,	PUNCT
cana-1859	222	24	and	and	CCONJ
cana-1859	222	25	enhanced	enhance	VERB
cana-1859	222	26	gradient	gradient	NOUN
cana-1859	222	27	flow	flow	NOUN
cana-1859	222	28	,	,	PUNCT
cana-1859	222	29	making	make	VERB
cana-1859	222	30	it	it	PRON
cana-1859	222	31	beneficial	beneficial	ADJ
cana-1859	222	32	for	for	ADP
cana-1859	222	33	various	various	ADJ
cana-1859	222	34	image	image	NOUN
cana-1859	222	35	processing	processing	NOUN
cana-1859	222	36	tasks	task	NOUN
cana-1859	222	37	and	and	CCONJ
cana-1859	222	38	cnn	cnn	PROPN
cana-1859	222	39	architectures	architecture	NOUN
cana-1859	222	40	.	.	PUNCT
cana-1859	223	1	in	in	ADP
cana-1859	223	2	contrast	contrast	NOUN
cana-1859	223	3	,	,	PUNCT
cana-1859	223	4	ekadhikina	ekadhikina	ADJ
cana-1859	223	5	purvena	purvena	NOUN
cana-1859	223	6	is	be	AUX
cana-1859	223	7	a	a	DET
cana-1859	223	8	vedic	vedic	ADJ
cana-1859	223	9	mathematics	mathematic	NOUN
cana-1859	223	10	sutra	sutra	NOUN
cana-1859	223	11	that	that	PRON
cana-1859	223	12	translates	translate	VERB
cana-1859	223	13	to	to	ADP
cana-1859	223	14	"	"	PUNCT
cana-1859	223	15	one	one	NUM
cana-1859	223	16	more	more	ADJ
cana-1859	223	17	than	than	ADP
cana-1859	223	18	the	the	DET
cana-1859	223	19	previous	previous	ADJ
cana-1859	223	20	one	one	NUM
cana-1859	223	21	.	.	PUNCT
cana-1859	223	22	"	"	PUNCT
cana-1859	224	1	this	this	DET
cana-1859	224	2	sutra	sutra	NOUN
cana-1859	224	3	can	can	AUX
cana-1859	224	4	be	be	AUX
cana-1859	224	5	applied	apply	VERB
cana-1859	224	6	in	in	ADP
cana-1859	224	7	the	the	DET
cana-1859	224	8	context	context	NOUN
cana-1859	224	9	of	of	ADP
cana-1859	224	10	convolutional	convolutional	ADJ
cana-1859	224	11	neural	neural	ADJ
cana-1859	224	12	networks	network	NOUN
cana-1859	224	13	(	(	PUNCT
cana-1859	224	14	cnns	cnns	PROPN
cana-1859	224	15	)	)	PUNCT
cana-1859	224	16	to	to	PART
cana-1859	224	17	optimize	optimize	VERB
cana-1859	224	18	the	the	DET
cana-1859	224	19	network	network	NOUN
cana-1859	224	20	's	's	PART
cana-1859	224	21	operations	operation	NOUN
cana-1859	224	22	,	,	PUNCT
cana-1859	224	23	specifically	specifically	ADV
cana-1859	224	24	in	in	ADP
cana-1859	224	25	the	the	DET
cana-1859	224	26	context	context	NOUN
cana-1859	224	27	of	of	ADP
cana-1859	224	28	kernel	kernel	PROPN
cana-1859	224	29	size	size	NOUN
cana-1859	224	30	selection	selection	NOUN
cana-1859	224	31	and	and	CCONJ
cana-1859	224	32	feature	feature	NOUN
cana-1859	224	33	map	map	NOUN
cana-1859	224	34	generation	generation	NOUN
cana-1859	224	35	.	.	PUNCT
cana-1859	225	1	in	in	ADP
cana-1859	225	2	cnns	cnns	PROPN
cana-1859	225	3	,	,	PUNCT
cana-1859	225	4	the	the	DET
cana-1859	225	5	choice	choice	NOUN
cana-1859	225	6	of	of	ADP
cana-1859	225	7	kernel	kernel	PROPN
cana-1859	225	8	size	size	NOUN
cana-1859	225	9	is	be	AUX
cana-1859	225	10	crucial	crucial	ADJ
cana-1859	225	11	for	for	ADP
cana-1859	225	12	feature	feature	NOUN
cana-1859	225	13	extraction	extraction	NOUN
cana-1859	225	14	.	.	PUNCT
cana-1859	226	1	larger	large	ADJ
cana-1859	226	2	kernel	kernel	PROPN
cana-1859	226	3	sizes	size	NOUN
cana-1859	226	4	capture	capture	VERB
cana-1859	226	5	more	more	ADJ
cana-1859	226	6	global	global	ADJ
cana-1859	226	7	features	feature	NOUN
cana-1859	226	8	,	,	PUNCT
cana-1859	226	9	while	while	SCONJ
cana-1859	226	10	smaller	small	ADJ
cana-1859	226	11	ones	one	NOUN
cana-1859	226	12	focus	focus	VERB
cana-1859	226	13	on	on	ADP
cana-1859	226	14	local	local	ADJ
cana-1859	226	15	details	detail	NOUN
cana-1859	226	16	.	.	PUNCT
cana-1859	227	1	the	the	DET
cana-1859	227	2	ekadhikina	ekadhikina	PROPN
cana-1859	227	3	purvena	purvena	NOUN
cana-1859	227	4	sutra	sutra	PROPN
cana-1859	227	5	can	can	AUX
cana-1859	227	6	guide	guide	VERB
cana-1859	227	7	the	the	DET
cana-1859	227	8	selection	selection	NOUN
cana-1859	227	9	of	of	ADP
cana-1859	227	10	kernel	kernel	NOUN
cana-1859	227	11	sizes	size	NOUN
cana-1859	227	12	by	by	ADP
cana-1859	227	13	systematically	systematically	ADV
cana-1859	227	14	increasing	increase	VERB
cana-1859	227	15	them	they	PRON
cana-1859	227	16	in	in	ADP
cana-1859	227	17	a	a	DET
cana-1859	227	18	way	way	NOUN
cana-1859	227	19	that	that	PRON
cana-1859	227	20	optimizes	optimize	VERB
cana-1859	227	21	feature	feature	NOUN
cana-1859	227	22	representation	representation	NOUN
cana-1859	227	23	.	.	PUNCT
cana-1859	228	1	consider	consider	VERB
cana-1859	228	2	the	the	DET
cana-1859	228	3	standard	standard	ADJ
cana-1859	228	4	approach	approach	NOUN
cana-1859	228	5	to	to	ADP
cana-1859	228	6	selecting	select	VERB
cana-1859	228	7	kernel	kernel	NOUN
cana-1859	228	8	sizes	size	NOUN
cana-1859	228	9	in	in	ADP
cana-1859	228	10	cnn	cnn	PROPN
cana-1859	228	11	layers	layer	NOUN
cana-1859	228	12	.	.	PUNCT
cana-1859	229	1	typically	typically	ADV
cana-1859	229	2	,	,	PUNCT
cana-1859	229	3	kernel	kernel	PROPN
cana-1859	229	4	sizes	size	NOUN
cana-1859	229	5	like	like	ADP
cana-1859	229	6	3x3	3x3	NUM
cana-1859	229	7	,	,	PUNCT
cana-1859	229	8	5x5	5x5	NUM
cana-1859	229	9	,	,	PUNCT
cana-1859	229	10	and	and	CCONJ
cana-1859	229	11	7x7	7x7	NUM
cana-1859	229	12	are	be	AUX
cana-1859	229	13	used	use	VERB
cana-1859	229	14	.	.	PUNCT
cana-1859	230	1	however	however	ADV
cana-1859	230	2	,	,	PUNCT
cana-1859	230	3	the	the	DET
cana-1859	230	4	ekadhikina	ekadhikina	PROPN
cana-1859	230	5	purvena	purvena	NOUN
cana-1859	230	6	sutra	sutra	PROPN
cana-1859	230	7	suggests	suggest	VERB
cana-1859	230	8	a	a	DET
cana-1859	230	9	systematic	systematic	ADJ
cana-1859	230	10	increase	increase	NOUN
cana-1859	230	11	in	in	ADP
cana-1859	230	12	kernel	kernel	PROPN
cana-1859	230	13	sizes	size	NOUN
cana-1859	230	14	,	,	PUNCT
cana-1859	230	15	such	such	ADJ
cana-1859	230	16	as	as	ADP
cana-1859	230	17	3x3	3x3	NUM
cana-1859	230	18	,	,	PUNCT
cana-1859	230	19	4x4	4x4	NUM
cana-1859	230	20	,	,	PUNCT
cana-1859	230	21	5x5	5x5	NUM
cana-1859	230	22	,	,	PUNCT
cana-1859	230	23	and	and	CCONJ
cana-1859	230	24	so	so	ADV
cana-1859	230	25	on	on	ADV
cana-1859	230	26	.	.	PUNCT
cana-1859	231	1	this	this	DET
cana-1859	231	2	modification	modification	NOUN
cana-1859	231	3	allows	allow	VERB
cana-1859	231	4	the	the	DET
cana-1859	231	5	network	network	NOUN
cana-1859	231	6	to	to	PART
cana-1859	231	7	capture	capture	VERB
cana-1859	231	8	features	feature	NOUN
cana-1859	231	9	at	at	ADP
cana-1859	231	10	various	various	ADJ
cana-1859	231	11	scales	scale	NOUN
cana-1859	231	12	progressively	progressively	ADV
cana-1859	231	13	.	.	PUNCT
cana-1859	232	1	for	for	ADP
cana-1859	232	2	example	example	NOUN
cana-1859	232	3	,	,	PUNCT
cana-1859	232	4	the	the	DET
cana-1859	232	5	first	first	ADJ
cana-1859	232	6	layer	layer	NOUN
cana-1859	232	7	focuses	focus	VERB
cana-1859	232	8	on	on	ADP
cana-1859	232	9	local	local	ADJ
cana-1859	232	10	features	feature	NOUN
cana-1859	232	11	with	with	ADP
cana-1859	232	12	a	a	DET
cana-1859	232	13	3x3	3x3	NUM
cana-1859	232	14	kernel	kernel	NOUN
cana-1859	232	15	,	,	PUNCT
cana-1859	232	16	and	and	CCONJ
cana-1859	232	17	subsequent	subsequent	ADJ
cana-1859	232	18	layers	layer	NOUN
cana-1859	232	19	gradually	gradually	ADV
cana-1859	232	20	expand	expand	VERB
cana-1859	232	21	to	to	PART
cana-1859	232	22	capture	capture	VERB
cana-1859	232	23	larger	large	ADJ
cana-1859	232	24	and	and	CCONJ
cana-1859	232	25	more	more	ADV
cana-1859	232	26	global	global	ADJ
cana-1859	232	27	features	feature	NOUN
cana-1859	232	28	.	.	PUNCT
cana-1859	233	1	for	for	ADP
cana-1859	233	2	instance	instance	NOUN
cana-1859	233	3	,	,	PUNCT
cana-1859	233	4	original	original	ADJ
cana-1859	233	5	kernel	kernel	NOUN
cana-1859	233	6	sizes	size	NOUN
cana-1859	233	7	are	be	AUX
cana-1859	233	8	[	[	X
cana-1859	233	9	3x3	3x3	NUM
cana-1859	233	10	,	,	PUNCT
cana-1859	233	11	5x5	5x5	NUM
cana-1859	233	12	,	,	PUNCT
cana-1859	233	13	7x7	7x7	NUM
cana-1859	233	14	,	,	PUNCT
cana-1859	233	15	...	...	PUNCT
cana-1859	233	16	]	]	X
cana-1859	233	17	,	,	PUNCT
cana-1859	233	18	and	and	CCONJ
cana-1859	233	19	modified	modified	ADJ
cana-1859	233	20	kernel	kernel	NOUN
cana-1859	233	21	sizes	size	NOUN
cana-1859	233	22	using	use	VERB
cana-1859	233	23	ekadhikina	ekadhikina	NOUN
cana-1859	233	24	purvena	purvena	NOUN
cana-1859	233	25	are	be	AUX
cana-1859	233	26	[	[	X
cana-1859	233	27	3x3	3x3	NUM
cana-1859	233	28	,	,	PUNCT
cana-1859	233	29	4x4	4x4	NUM
cana-1859	233	30	,	,	PUNCT
cana-1859	233	31	5x5	5x5	NUM
cana-1859	233	32	,	,	PUNCT
cana-1859	233	33	...	...	PUNCT
cana-1859	233	34	]	]	PUNCT
cana-1859	233	35	reasons	reason	NOUN
cana-1859	233	36	for	for	ADP
cana-1859	233	37	improvement	improvement	NOUN
cana-1859	233	38	in	in	ADP
cana-1859	233	39	performance	performance	NOUN
cana-1859	233	40	1	1	NUM
cana-1859	233	41	.	.	PUNCT
cana-1859	233	42	progressive	progressive	ADJ
cana-1859	233	43	feature	feature	NOUN
cana-1859	233	44	extraction	extraction	NOUN
cana-1859	233	45	:	:	PUNCT
cana-1859	233	46	by	by	ADP
cana-1859	233	47	systematically	systematically	ADV
cana-1859	233	48	increasing	increase	VERB
cana-1859	233	49	kernel	kernel	PROPN
cana-1859	233	50	sizes	size	NOUN
cana-1859	233	51	,	,	PUNCT
cana-1859	233	52	the	the	DET
cana-1859	233	53	network	network	NOUN
cana-1859	233	54	can	can	AUX
cana-1859	233	55	capture	capture	VERB
cana-1859	233	56	features	feature	NOUN
cana-1859	233	57	at	at	ADP
cana-1859	233	58	multiple	multiple	ADJ
cana-1859	233	59	scales	scale	NOUN
cana-1859	233	60	.	.	PUNCT
cana-1859	234	1	this	this	PRON
cana-1859	234	2	helps	help	VERB
cana-1859	234	3	in	in	ADP
cana-1859	234	4	learning	learn	VERB
cana-1859	234	5	hierarchical	hierarchical	ADJ
cana-1859	234	6	representations	representation	NOUN
cana-1859	234	7	,	,	PUNCT
cana-1859	234	8	from	from	ADP
cana-1859	234	9	finegrained	finegraine	VERB
cana-1859	234	10	details	detail	NOUN
cana-1859	234	11	to	to	ADP
cana-1859	234	12	global	global	ADJ
cana-1859	234	13	patterns	pattern	NOUN
cana-1859	234	14	.	.	PUNCT
cana-1859	235	1	2	2	X
cana-1859	235	2	.	.	X
cana-1859	235	3	adaptability	adaptability	NOUN
cana-1859	235	4	:	:	PUNCT
cana-1859	235	5	the	the	DET
cana-1859	235	6	ekadhikina	ekadhikina	PROPN
cana-1859	235	7	purvena	purvena	PROPN
cana-1859	235	8	approach	approach	NOUN
cana-1859	235	9	allows	allow	VERB
cana-1859	235	10	the	the	DET
cana-1859	235	11	network	network	NOUN
cana-1859	235	12	to	to	PART
cana-1859	235	13	adapt	adapt	VERB
cana-1859	235	14	its	its	PRON
cana-1859	235	15	receptive	receptive	ADJ
cana-1859	235	16	field	field	NOUN
cana-1859	235	17	according	accord	VERB
cana-1859	235	18	to	to	ADP
cana-1859	235	19	the	the	DET
cana-1859	235	20	complexity	complexity	NOUN
cana-1859	235	21	of	of	ADP
cana-1859	235	22	the	the	DET
cana-1859	235	23	input	input	NOUN
cana-1859	235	24	data	datum	NOUN
cana-1859	235	25	.	.	PUNCT
cana-1859	236	1	this	this	DET
cana-1859	236	2	adaptability	adaptability	NOUN
cana-1859	236	3	can	can	AUX
cana-1859	236	4	lead	lead	VERB
cana-1859	236	5	to	to	ADP
cana-1859	236	6	better	well	ADJ
cana-1859	236	7	feature	feature	NOUN
cana-1859	236	8	representations	representation	NOUN
cana-1859	236	9	.	.	PUNCT
cana-1859	237	1	3	3	X
cana-1859	237	2	.	.	X
cana-1859	237	3	reduced	reduce	VERB
cana-1859	237	4	overfitting	overfitting	NOUN
cana-1859	237	5	:	:	PUNCT
cana-1859	237	6	the	the	DET
cana-1859	237	7	progressive	progressive	ADJ
cana-1859	237	8	increase	increase	NOUN
cana-1859	237	9	in	in	ADP
cana-1859	237	10	kernel	kernel	PROPN
cana-1859	237	11	sizes	size	NOUN
cana-1859	237	12	can	can	AUX
cana-1859	237	13	reduce	reduce	VERB
cana-1859	237	14	overfitting	overfitting	NOUN
cana-1859	237	15	,	,	PUNCT
cana-1859	237	16	as	as	SCONJ
cana-1859	237	17	smaller	small	ADJ
cana-1859	237	18	kernels	kernel	NOUN
cana-1859	237	19	initially	initially	ADV
cana-1859	237	20	learn	learn	VERB
cana-1859	237	21	local	local	ADJ
cana-1859	237	22	details	detail	NOUN
cana-1859	237	23	,	,	PUNCT
cana-1859	237	24	which	which	PRON
cana-1859	237	25	are	be	AUX
cana-1859	237	26	then	then	ADV
cana-1859	237	27	combined	combine	VERB
cana-1859	237	28	by	by	ADP
cana-1859	237	29	larger	large	ADJ
cana-1859	237	30	kernels	kernel	NOUN
cana-1859	237	31	to	to	PART
cana-1859	237	32	form	form	VERB
cana-1859	237	33	more	more	ADV
cana-1859	237	34	robust	robust	ADJ
cana-1859	237	35	representations	representation	NOUN
cana-1859	237	36	.	.	PUNCT
cana-1859	238	1	4	4	X
cana-1859	238	2	.	.	NUM
cana-1859	238	3	improved	improve	VERB
cana-1859	238	4	generalization	generalization	NOUN
cana-1859	238	5	:	:	PUNCT
cana-1859	238	6	the	the	DET
cana-1859	238	7	network	network	NOUN
cana-1859	238	8	becomes	become	VERB
cana-1859	238	9	more	more	ADV
cana-1859	238	10	capable	capable	ADJ
cana-1859	238	11	of	of	ADP
cana-1859	238	12	generalizing	generalize	VERB
cana-1859	238	13	to	to	ADP
cana-1859	238	14	a	a	DET
cana-1859	238	15	wide	wide	ADJ
cana-1859	238	16	range	range	NOUN
cana-1859	238	17	of	of	ADP
cana-1859	238	18	input	input	NOUN
cana-1859	238	19	data	datum	NOUN
cana-1859	238	20	,	,	PUNCT
cana-1859	238	21	enhancing	enhance	VERB
cana-1859	238	22	its	its	PRON
cana-1859	238	23	performance	performance	NOUN
cana-1859	238	24	on	on	ADP
cana-1859	238	25	various	various	ADJ
cana-1859	238	26	tasks	task	NOUN
cana-1859	238	27	.	.	PUNCT
cana-1859	239	1	thus	thus	ADV
cana-1859	239	2	,	,	PUNCT
cana-1859	239	3	applying	apply	VERB
cana-1859	239	4	the	the	DET
cana-1859	239	5	ekadhikina	ekadhikina	NOUN
cana-1859	239	6	purvena	purvena	NOUN
cana-1859	239	7	sutra	sutra	NOUN
cana-1859	239	8	to	to	AUX
cana-1859	239	9	cnns	cnns	PROPN
cana-1859	239	10	offers	offer	VERB
cana-1859	239	11	a	a	DET
cana-1859	239	12	systematic	systematic	ADJ
cana-1859	239	13	and	and	CCONJ
cana-1859	239	14	adaptive	adaptive	ADJ
cana-1859	239	15	approach	approach	NOUN
cana-1859	239	16	to	to	ADP
cana-1859	239	17	kernel	kernel	PROPN
cana-1859	239	18	size	size	NOUN
cana-1859	239	19	selection	selection	NOUN
cana-1859	239	20	.	.	PUNCT
cana-1859	240	1	by	by	ADP
cana-1859	240	2	gradually	gradually	ADV
cana-1859	240	3	increasing	increase	VERB
cana-1859	240	4	kernel	kernel	PROPN
cana-1859	240	5	sizes	size	NOUN
cana-1859	240	6	,	,	PUNCT
cana-1859	240	7	the	the	DET
cana-1859	240	8	network	network	NOUN
cana-1859	240	9	can	can	AUX
cana-1859	240	10	capture	capture	VERB
cana-1859	240	11	features	feature	NOUN
cana-1859	240	12	at	at	ADP
cana-1859	240	13	multiple	multiple	ADJ
cana-1859	240	14	scales	scale	NOUN
cana-1859	240	15	,	,	PUNCT
cana-1859	240	16	leading	lead	VERB
cana-1859	240	17	to	to	ADP
cana-1859	240	18	improved	improve	VERB
cana-1859	240	19	feature	feature	NOUN
cana-1859	240	20	representations	representation	NOUN
cana-1859	240	21	,	,	PUNCT
cana-1859	240	22	reduced	reduce	VERB
cana-1859	240	23	overfitting	overfitting	NOUN
cana-1859	240	24	,	,	PUNCT
cana-1859	240	25	and	and	CCONJ
cana-1859	240	26	enhanced	enhanced	ADJ
cana-1859	240	27	generalization	generalization	NOUN
cana-1859	240	28	,	,	PUNCT
cana-1859	240	29	ultimately	ultimately	ADV
cana-1859	240	30	improving	improve	VERB
cana-1859	240	31	the	the	DET
cana-1859	240	32	performance	performance	NOUN
cana-1859	240	33	of	of	ADP
cana-1859	240	34	the	the	DET
cana-1859	240	35	cnn	cnn	PROPN
cana-1859	240	36	on	on	ADP
cana-1859	240	37	various	various	ADJ
cana-1859	240	38	image	image	NOUN
cana-1859	240	39	processing	processing	NOUN
cana-1859	240	40	tasks	task	NOUN
cana-1859	240	41	.	.	PUNCT
cana-1859	241	1	communications	communication	NOUN
cana-1859	241	2	on	on	ADP
cana-1859	241	3	applied	apply	VERB
cana-1859	241	4	nonlinear	nonlinear	ADJ
cana-1859	241	5	analysis	analysis	NOUN
cana-1859	241	6	issn	issn	NOUN
cana-1859	241	7	:	:	PUNCT
cana-1859	241	8	1074	1074	NUM
cana-1859	241	9	-	-	PUNCT
cana-1859	241	10	133x	133x	NUM
cana-1859	241	11	vol	vol	NOUN
cana-1859	241	12	32	32	NUM
cana-1859	241	13	no	no	NOUN
cana-1859	241	14	.	.	NOUN
cana-1859	241	15	2	2	NUM
cana-1859	241	16	(	(	PUNCT
cana-1859	241	17	2025	2025	NUM
cana-1859	241	18	)	)	PUNCT
cana-1859	241	19	653	653	NUM
cana-1859	241	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	241	21	finally	finally	ADV
cana-1859	241	22	,	,	PUNCT
cana-1859	241	23	gunitasamuchyah	gunitasamuchyah	PROPN
cana-1859	241	24	is	be	AUX
cana-1859	241	25	a	a	DET
cana-1859	241	26	vedic	vedic	ADJ
cana-1859	241	27	mathematics	mathematic	NOUN
cana-1859	241	28	sutra	sutra	NOUN
cana-1859	241	29	that	that	PRON
cana-1859	241	30	translates	translate	VERB
cana-1859	241	31	to	to	ADP
cana-1859	241	32	"	"	PUNCT
cana-1859	241	33	factors	factor	NOUN
cana-1859	241	34	are	be	AUX
cana-1859	241	35	the	the	DET
cana-1859	241	36	same	same	ADJ
cana-1859	241	37	.	.	PUNCT
cana-1859	241	38	"	"	PUNCT
cana-1859	242	1	this	this	DET
cana-1859	242	2	sutra	sutra	NOUN
cana-1859	242	3	can	can	AUX
cana-1859	242	4	be	be	AUX
cana-1859	242	5	applied	apply	VERB
cana-1859	242	6	in	in	ADP
cana-1859	242	7	the	the	DET
cana-1859	242	8	context	context	NOUN
cana-1859	242	9	of	of	ADP
cana-1859	242	10	convolutional	convolutional	ADJ
cana-1859	242	11	neural	neural	ADJ
cana-1859	242	12	networks	network	NOUN
cana-1859	242	13	(	(	PUNCT
cana-1859	242	14	cnns	cnns	PROPN
cana-1859	242	15	)	)	PUNCT
cana-1859	242	16	to	to	PART
cana-1859	242	17	optimize	optimize	VERB
cana-1859	242	18	the	the	DET
cana-1859	242	19	network	network	NOUN
cana-1859	242	20	's	's	PART
cana-1859	242	21	weight	weight	NOUN
cana-1859	242	22	initialization	initialization	NOUN
cana-1859	242	23	process	process	NOUN
cana-1859	242	24	,	,	PUNCT
cana-1859	242	25	specifically	specifically	ADV
cana-1859	242	26	for	for	ADP
cana-1859	242	27	convolutional	convolutional	ADJ
cana-1859	242	28	layers	layer	NOUN
cana-1859	242	29	.	.	PUNCT
cana-1859	243	1	in	in	ADP
cana-1859	243	2	cnns	cnns	PROPN
cana-1859	243	3	,	,	PUNCT
cana-1859	243	4	weight	weight	NOUN
cana-1859	243	5	initialization	initialization	NOUN
cana-1859	243	6	is	be	AUX
cana-1859	243	7	crucial	crucial	ADJ
cana-1859	243	8	to	to	PART
cana-1859	243	9	ensure	ensure	VERB
cana-1859	243	10	that	that	SCONJ
cana-1859	243	11	the	the	DET
cana-1859	243	12	network	network	NOUN
cana-1859	243	13	converges	converge	VERB
cana-1859	243	14	efficiently	efficiently	ADV
cana-1859	243	15	during	during	ADP
cana-1859	243	16	training	training	NOUN
cana-1859	243	17	.	.	PUNCT
cana-1859	244	1	the	the	DET
cana-1859	244	2	gunitasamuchyah	gunitasamuchyah	NOUN
cana-1859	244	3	sutra	sutra	NOUN
cana-1859	244	4	can	can	AUX
cana-1859	244	5	guide	guide	VERB
cana-1859	244	6	the	the	DET
cana-1859	244	7	weight	weight	NOUN
cana-1859	244	8	initialization	initialization	NOUN
cana-1859	244	9	process	process	NOUN
cana-1859	244	10	by	by	ADP
cana-1859	244	11	emphasizing	emphasize	VERB
cana-1859	244	12	the	the	DET
cana-1859	244	13	importance	importance	NOUN
cana-1859	244	14	of	of	ADP
cana-1859	244	15	initializing	initialize	VERB
cana-1859	244	16	weights	weight	NOUN
cana-1859	244	17	with	with	ADP
cana-1859	244	18	factors	factor	NOUN
cana-1859	244	19	that	that	PRON
cana-1859	244	20	are	be	AUX
cana-1859	244	21	the	the	DET
cana-1859	244	22	same	same	ADJ
cana-1859	244	23	or	or	CCONJ
cana-1859	244	24	related	relate	VERB
cana-1859	244	25	to	to	ADP
cana-1859	244	26	the	the	DET
cana-1859	244	27	process	process	NOUN
cana-1859	244	28	.	.	PUNCT
cana-1859	245	1	typically	typically	ADV
cana-1859	245	2	,	,	PUNCT
cana-1859	245	3	weight	weight	NOUN
cana-1859	245	4	initialization	initialization	NOUN
cana-1859	245	5	methods	method	NOUN
cana-1859	245	6	like	like	ADP
cana-1859	245	7	xavier	xavier	PROPN
cana-1859	245	8	/	/	SYM
cana-1859	245	9	glorot	glorot	PROPN
cana-1859	245	10	initialization	initialization	NOUN
cana-1859	245	11	and	and	CCONJ
cana-1859	245	12	he	he	PRON
cana-1859	245	13	initialization	initialization	NOUN
cana-1859	245	14	use	use	VERB
cana-1859	245	15	stochastic	stochastic	ADJ
cana-1859	245	16	values	value	NOUN
cana-1859	245	17	sampled	sample	VERB
cana-1859	245	18	from	from	ADP
cana-1859	245	19	specific	specific	ADJ
cana-1859	245	20	distributions	distribution	NOUN
cana-1859	245	21	.	.	PUNCT
cana-1859	246	1	however	however	ADV
cana-1859	246	2	,	,	PUNCT
cana-1859	246	3	the	the	DET
cana-1859	246	4	gunitasamuchyah	gunitasamuchyah	NOUN
cana-1859	246	5	sutra	sutra	PROPN
cana-1859	246	6	suggests	suggest	VERB
cana-1859	246	7	modifying	modify	VERB
cana-1859	246	8	this	this	DET
cana-1859	246	9	process	process	NOUN
cana-1859	246	10	to	to	PART
cana-1859	246	11	ensure	ensure	VERB
cana-1859	246	12	that	that	SCONJ
cana-1859	246	13	the	the	DET
cana-1859	246	14	initialized	initialize	VERB
cana-1859	246	15	weights	weight	NOUN
cana-1859	246	16	have	have	VERB
cana-1859	246	17	related	relate	VERB
cana-1859	246	18	factors	factor	NOUN
cana-1859	246	19	.	.	PUNCT
cana-1859	247	1	weight	weight	NOUN
cana-1859	247	2	initialization	initialization	NOUN
cana-1859	247	3	using	use	VERB
cana-1859	247	4	gunitasamuchyah	gunitasamuchyah	NOUN
cana-1859	247	5	is	be	AUX
cana-1859	247	6	done	do	VERB
cana-1859	247	7	in	in	ADP
cana-1859	247	8	pairs	pair	NOUN
cana-1859	247	9	where	where	SCONJ
cana-1859	247	10	their	their	PRON
cana-1859	247	11	factors	factor	NOUN
cana-1859	247	12	are	be	AUX
cana-1859	247	13	the	the	DET
cana-1859	247	14	same	same	ADJ
cana-1859	247	15	or	or	CCONJ
cana-1859	247	16	related	relate	VERB
cana-1859	247	17	(	(	PUNCT
cana-1859	247	18	e.g.	e.g.	ADV
cana-1859	247	19	,	,	PUNCT
cana-1859	247	20	2	2	NUM
cana-1859	247	21	and	and	CCONJ
cana-1859	247	22	4	4	NUM
cana-1859	247	23	,	,	PUNCT
cana-1859	247	24	3	3	NUM
cana-1859	247	25	and	and	CCONJ
cana-1859	247	26	6	6	NUM
cana-1859	247	27	)	)	PUNCT
cana-1859	247	28	.	.	PUNCT
cana-1859	248	1	reasons	reason	NOUN
cana-1859	248	2	for	for	ADP
cana-1859	248	3	improvement	improvement	NOUN
cana-1859	248	4	in	in	ADP
cana-1859	248	5	performance	performance	NOUN
cana-1859	248	6	1	1	NUM
cana-1859	248	7	.	.	PUNCT
cana-1859	248	8	enhanced	enhance	VERB
cana-1859	248	9	weight	weight	NOUN
cana-1859	248	10	relationships	relationship	NOUN
cana-1859	248	11	:	:	PUNCT
cana-1859	248	12	by	by	ADP
cana-1859	248	13	initializing	initialize	VERB
cana-1859	248	14	weights	weight	NOUN
cana-1859	248	15	with	with	ADP
cana-1859	248	16	related	related	ADJ
cana-1859	248	17	factors	factor	NOUN
cana-1859	248	18	,	,	PUNCT
cana-1859	248	19	the	the	DET
cana-1859	248	20	network	network	NOUN
cana-1859	248	21	starts	start	VERB
cana-1859	248	22	with	with	ADP
cana-1859	248	23	weights	weight	NOUN
cana-1859	248	24	that	that	PRON
cana-1859	248	25	have	have	VERB
cana-1859	248	26	inherent	inherent	ADJ
cana-1859	248	27	relationships	relationship	NOUN
cana-1859	248	28	.	.	PUNCT
cana-1859	249	1	this	this	PRON
cana-1859	249	2	can	can	AUX
cana-1859	249	3	lead	lead	VERB
cana-1859	249	4	to	to	ADP
cana-1859	249	5	better	well	ADJ
cana-1859	249	6	weight	weight	NOUN
cana-1859	249	7	combinations	combination	NOUN
cana-1859	249	8	and	and	CCONJ
cana-1859	249	9	more	more	ADV
cana-1859	249	10	effective	effective	ADJ
cana-1859	249	11	feature	feature	NOUN
cana-1859	249	12	extraction	extraction	NOUN
cana-1859	249	13	.	.	PUNCT
cana-1859	250	1	2	2	X
cana-1859	250	2	.	.	NUM
cana-1859	250	3	reduced	reduce	VERB
cana-1859	250	4	weight	weight	NOUN
cana-1859	250	5	variance	variance	NOUN
cana-1859	250	6	:	:	PUNCT
cana-1859	250	7	pairing	pair	VERB
cana-1859	250	8	weights	weight	NOUN
cana-1859	250	9	with	with	ADP
cana-1859	250	10	related	related	ADJ
cana-1859	250	11	factors	factor	NOUN
cana-1859	250	12	can	can	AUX
cana-1859	250	13	reduce	reduce	VERB
cana-1859	250	14	the	the	DET
cana-1859	250	15	variance	variance	NOUN
cana-1859	250	16	in	in	ADP
cana-1859	250	17	weight	weight	NOUN
cana-1859	250	18	values	value	NOUN
cana-1859	250	19	,	,	PUNCT
cana-1859	250	20	making	make	VERB
cana-1859	250	21	it	it	PRON
cana-1859	250	22	easier	easy	ADJ
cana-1859	250	23	for	for	SCONJ
cana-1859	250	24	the	the	DET
cana-1859	250	25	network	network	NOUN
cana-1859	250	26	to	to	PART
cana-1859	250	27	learn	learn	VERB
cana-1859	250	28	and	and	CCONJ
cana-1859	250	29	converge	converge	VERB
cana-1859	250	30	during	during	ADP
cana-1859	250	31	training	training	NOUN
cana-1859	250	32	.	.	PUNCT
cana-1859	251	1	3	3	X
cana-1859	251	2	.	.	X
cana-1859	251	3	improved	improve	VERB
cana-1859	251	4	gradient	gradient	ADJ
cana-1859	251	5	flow	flow	NOUN
cana-1859	251	6	:	:	PUNCT
cana-1859	251	7	weight	weight	NOUN
cana-1859	251	8	pairs	pair	NOUN
cana-1859	251	9	with	with	ADP
cana-1859	251	10	related	related	ADJ
cana-1859	251	11	factors	factor	NOUN
cana-1859	251	12	tend	tend	VERB
cana-1859	251	13	to	to	PART
cana-1859	251	14	have	have	VERB
cana-1859	251	15	more	more	ADV
cana-1859	251	16	balanced	balanced	ADJ
cana-1859	251	17	gradient	gradient	NOUN
cana-1859	251	18	flows	flow	NOUN
cana-1859	251	19	during	during	ADP
cana-1859	251	20	backpropagation	backpropagation	NOUN
cana-1859	251	21	,	,	PUNCT
cana-1859	251	22	preventing	prevent	VERB
cana-1859	251	23	issues	issue	NOUN
cana-1859	251	24	like	like	ADP
cana-1859	251	25	vanishing	vanish	VERB
cana-1859	251	26	or	or	CCONJ
cana-1859	251	27	exploding	explode	VERB
cana-1859	251	28	gradients	gradient	NOUN
cana-1859	251	29	.	.	PUNCT
cana-1859	252	1	4	4	NUM
cana-1859	252	2	.	.	X
cana-1859	252	3	faster	fast	ADJ
cana-1859	252	4	convergence	convergence	NOUN
cana-1859	252	5	:	:	PUNCT
cana-1859	252	6	the	the	DET
cana-1859	252	7	modified	modify	VERB
cana-1859	252	8	weight	weight	NOUN
cana-1859	252	9	initialization	initialization	NOUN
cana-1859	252	10	process	process	NOUN
cana-1859	252	11	can	can	AUX
cana-1859	252	12	lead	lead	VERB
cana-1859	252	13	to	to	ADP
cana-1859	252	14	faster	fast	ADJ
cana-1859	252	15	convergence	convergence	NOUN
cana-1859	252	16	during	during	ADP
cana-1859	252	17	training	training	NOUN
cana-1859	252	18	,	,	PUNCT
cana-1859	252	19	reducing	reduce	VERB
cana-1859	252	20	the	the	DET
cana-1859	252	21	overall	overall	ADJ
cana-1859	252	22	training	training	NOUN
cana-1859	252	23	time	time	NOUN
cana-1859	252	24	and	and	CCONJ
cana-1859	252	25	computational	computational	ADJ
cana-1859	252	26	resources	resource	NOUN
cana-1859	252	27	required	require	VERB
cana-1859	252	28	.	.	PUNCT
cana-1859	253	1	in	in	ADP
cana-1859	253	2	conclusion	conclusion	NOUN
cana-1859	253	3	,	,	PUNCT
cana-1859	253	4	applying	apply	VERB
cana-1859	253	5	the	the	DET
cana-1859	253	6	gunitasamuchyah	gunitasamuchyah	NOUN
cana-1859	253	7	sutra	sutra	NOUN
cana-1859	253	8	to	to	ADP
cana-1859	253	9	cnn	cnn	PROPN
cana-1859	253	10	weight	weight	PROPN
cana-1859	253	11	initialization	initialization	NOUN
cana-1859	253	12	offers	offer	VERB
cana-1859	253	13	a	a	DET
cana-1859	253	14	novel	novel	ADJ
cana-1859	253	15	approach	approach	NOUN
cana-1859	253	16	to	to	ADP
cana-1859	253	17	enhancing	enhance	VERB
cana-1859	253	18	the	the	DET
cana-1859	253	19	relationship	relationship	NOUN
cana-1859	253	20	between	between	ADP
cana-1859	253	21	weights	weight	NOUN
cana-1859	253	22	.	.	PUNCT
cana-1859	254	1	by	by	ADP
cana-1859	254	2	initializing	initialize	VERB
cana-1859	254	3	weights	weight	NOUN
cana-1859	254	4	with	with	ADP
cana-1859	254	5	related	related	ADJ
cana-1859	254	6	factors	factor	NOUN
cana-1859	254	7	,	,	PUNCT
cana-1859	254	8	the	the	DET
cana-1859	254	9	network	network	NOUN
cana-1859	254	10	can	can	AUX
cana-1859	254	11	benefit	benefit	VERB
cana-1859	254	12	from	from	ADP
cana-1859	254	13	improved	improve	VERB
cana-1859	254	14	weight	weight	NOUN
cana-1859	254	15	combinations	combination	NOUN
cana-1859	254	16	,	,	PUNCT
cana-1859	254	17	reduced	reduced	ADJ
cana-1859	254	18	variance	variance	NOUN
cana-1859	254	19	,	,	PUNCT
cana-1859	254	20	better	well	ADJ
cana-1859	254	21	gradient	gradient	ADJ
cana-1859	254	22	flow	flow	NOUN
cana-1859	254	23	,	,	PUNCT
cana-1859	254	24	and	and	CCONJ
cana-1859	254	25	faster	fast	ADJ
cana-1859	254	26	convergence	convergence	NOUN
cana-1859	254	27	,	,	PUNCT
cana-1859	254	28	ultimately	ultimately	ADV
cana-1859	254	29	leading	lead	VERB
cana-1859	254	30	to	to	ADP
cana-1859	254	31	improved	improved	ADJ
cana-1859	254	32	performance	performance	NOUN
cana-1859	254	33	in	in	ADP
cana-1859	254	34	tasks	task	NOUN
cana-1859	254	35	such	such	ADJ
cana-1859	254	36	as	as	ADP
cana-1859	254	37	image	image	NOUN
cana-1859	254	38	classification	classification	NOUN
cana-1859	254	39	and	and	CCONJ
cana-1859	254	40	feature	feature	NOUN
cana-1859	254	41	extraction	extraction	NOUN
cana-1859	254	42	process	process	NOUN
cana-1859	254	43	.	.	PUNCT
cana-1859	255	1	due	due	ADP
cana-1859	255	2	to	to	ADP
cana-1859	255	3	fusion	fusion	NOUN
cana-1859	255	4	of	of	ADP
cana-1859	255	5	these	these	DET
cana-1859	255	6	sutras	sutra	NOUN
cana-1859	255	7	with	with	ADP
cana-1859	255	8	cnns	cnn	NOUN
cana-1859	255	9	,	,	PUNCT
cana-1859	255	10	the	the	DET
cana-1859	255	11	proposed	propose	VERB
cana-1859	255	12	model	model	NOUN
cana-1859	255	13	is	be	AUX
cana-1859	255	14	able	able	ADJ
cana-1859	255	15	to	to	PART
cana-1859	255	16	enhance	enhance	VERB
cana-1859	255	17	its	its	PRON
cana-1859	255	18	classification	classification	NOUN
cana-1859	255	19	performance	performance	NOUN
cana-1859	255	20	for	for	ADP
cana-1859	255	21	different	different	ADJ
cana-1859	255	22	datasets	dataset	NOUN
cana-1859	255	23	&	&	CCONJ
cana-1859	255	24	samples	sample	NOUN
cana-1859	255	25	.	.	PUNCT
cana-1859	256	1	this	this	DET
cana-1859	256	2	performance	performance	NOUN
cana-1859	256	3	was	be	AUX
cana-1859	256	4	estimated	estimate	VERB
cana-1859	256	5	on	on	ADP
cana-1859	256	6	different	different	ADJ
cana-1859	256	7	scenarios	scenario	NOUN
cana-1859	256	8	,	,	PUNCT
cana-1859	256	9	and	and	CCONJ
cana-1859	256	10	was	be	AUX
cana-1859	256	11	compared	compare	VERB
cana-1859	256	12	with	with	ADP
cana-1859	256	13	existing	exist	VERB
cana-1859	256	14	models	model	NOUN
cana-1859	256	15	in	in	ADP
cana-1859	256	16	the	the	DET
cana-1859	256	17	next	next	ADJ
cana-1859	256	18	section	section	NOUN
cana-1859	256	19	of	of	ADP
cana-1859	256	20	this	this	DET
cana-1859	256	21	text	text	NOUN
cana-1859	256	22	.	.	PUNCT
cana-1859	257	1	4	4	X
cana-1859	257	2	.	.	NOUN
cana-1859	257	3	result	result	VERB
cana-1859	257	4	analysis	analysis	NOUN
cana-1859	257	5	in	in	ADP
cana-1859	257	6	this	this	DET
cana-1859	257	7	work	work	NOUN
cana-1859	257	8	,	,	PUNCT
cana-1859	257	9	we	we	PRON
cana-1859	257	10	introduced	introduce	VERB
cana-1859	257	11	an	an	DET
cana-1859	257	12	innovative	innovative	ADJ
cana-1859	257	13	convolutional	convolutional	ADJ
cana-1859	257	14	neural	neural	ADJ
cana-1859	257	15	network	network	NOUN
cana-1859	257	16	(	(	PUNCT
cana-1859	257	17	cnn	cnn	PROPN
cana-1859	257	18	)	)	PUNCT
cana-1859	257	19	model	model	PROPN
cana-1859	257	20	,	,	PUNCT
cana-1859	257	21	vmcnn	vmcnn	PROPN
cana-1859	257	22	,	,	PUNCT
cana-1859	257	23	which	which	PRON
cana-1859	257	24	seamlessly	seamlessly	ADV
cana-1859	257	25	integrates	integrate	VERB
cana-1859	257	26	principles	principle	NOUN
cana-1859	257	27	of	of	ADP
cana-1859	257	28	vedic	vedic	ADJ
cana-1859	257	29	mathematics	mathematic	NOUN
cana-1859	257	30	,	,	PUNCT
cana-1859	257	31	an	an	DET
cana-1859	257	32	ancient	ancient	ADJ
cana-1859	257	33	indian	indian	ADJ
cana-1859	257	34	mathematical	mathematical	ADJ
cana-1859	257	35	system	system	NOUN
cana-1859	257	36	celebrated	celebrate	VERB
cana-1859	257	37	for	for	ADP
cana-1859	257	38	its	its	PRON
cana-1859	257	39	computational	computational	ADJ
cana-1859	257	40	efficiency	efficiency	NOUN
cana-1859	257	41	and	and	CCONJ
cana-1859	257	42	simplicity	simplicity	NOUN
cana-1859	257	43	.	.	PUNCT
cana-1859	258	1	vmcnn	vmcnn	PROPN
cana-1859	258	2	stands	stand	VERB
cana-1859	258	3	out	out	ADP
cana-1859	258	4	for	for	ADP
cana-1859	258	5	its	its	PRON
cana-1859	258	6	unique	unique	ADJ
cana-1859	258	7	application	application	NOUN
cana-1859	258	8	of	of	ADP
cana-1859	258	9	vedic	vedic	ADJ
cana-1859	258	10	mathematical	mathematical	ADJ
cana-1859	258	11	sutras	sutra	NOUN
cana-1859	258	12	such	such	ADJ
cana-1859	258	13	as	as	ADP
cana-1859	258	14	urdhva	urdhva	NOUN
cana-1859	258	15	-	-	PUNCT
cana-1859	258	16	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	258	17	,	,	PUNCT
cana-1859	258	18	anurupyena	anurupyena	PROPN
cana-1859	258	19	,	,	PUNCT
cana-1859	258	20	and	and	CCONJ
cana-1859	258	21	nikhilam	nikhilam	PROPN
cana-1859	258	22	navatashcaramam	navatashcaramam	NOUN
cana-1859	258	23	dashatah	dashatah	NOUN
cana-1859	258	24	,	,	PUNCT
cana-1859	258	25	ingeniously	ingeniously	ADV
cana-1859	258	26	adapted	adapt	VERB
cana-1859	258	27	to	to	PART
cana-1859	258	28	optimize	optimize	VERB
cana-1859	258	29	cnn	cnn	PROPN
cana-1859	258	30	operations	operation	NOUN
cana-1859	258	31	.	.	PUNCT
cana-1859	259	1	this	this	DET
cana-1859	259	2	integration	integration	NOUN
cana-1859	259	3	not	not	PART
cana-1859	259	4	communications	communication	NOUN
cana-1859	259	5	on	on	ADP
cana-1859	259	6	applied	apply	VERB
cana-1859	259	7	nonlinear	nonlinear	ADJ
cana-1859	259	8	analysis	analysis	NOUN
cana-1859	259	9	issn	issn	NOUN
cana-1859	259	10	:	:	PUNCT
cana-1859	259	11	1074	1074	NUM
cana-1859	259	12	-	-	PUNCT
cana-1859	259	13	133x	133x	NUM
cana-1859	259	14	vol	vol	NOUN
cana-1859	259	15	32	32	NUM
cana-1859	259	16	no	no	NOUN
cana-1859	259	17	.	.	NOUN
cana-1859	259	18	2	2	NUM
cana-1859	259	19	(	(	PUNCT
cana-1859	259	20	2025	2025	NUM
cana-1859	259	21	)	)	PUNCT
cana-1859	259	22	654	654	NUM
cana-1859	259	23	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	259	24	only	only	ADV
cana-1859	259	25	elevates	elevate	VERB
cana-1859	259	26	the	the	DET
cana-1859	259	27	computational	computational	ADJ
cana-1859	259	28	prowess	prowess	NOUN
cana-1859	259	29	of	of	ADP
cana-1859	259	30	the	the	DET
cana-1859	259	31	model	model	NOUN
cana-1859	259	32	but	but	CCONJ
cana-1859	259	33	also	also	ADV
cana-1859	259	34	markedly	markedly	ADV
cana-1859	259	35	enhances	enhance	VERB
cana-1859	259	36	key	key	ADJ
cana-1859	259	37	performance	performance	NOUN
cana-1859	259	38	metrics	metric	NOUN
cana-1859	259	39	like	like	ADP
cana-1859	259	40	precision	precision	NOUN
cana-1859	259	41	,	,	PUNCT
cana-1859	259	42	accuracy	accuracy	NOUN
cana-1859	259	43	,	,	PUNCT
cana-1859	259	44	and	and	CCONJ
cana-1859	259	45	recall	recall	VERB
cana-1859	259	46	across	across	ADP
cana-1859	259	47	diverse	diverse	ADJ
cana-1859	259	48	datasets	dataset	NOUN
cana-1859	259	49	,	,	PUNCT
cana-1859	259	50	including	include	VERB
cana-1859	259	51	imagenet	imagenet	NOUN
cana-1859	259	52	,	,	PUNCT
cana-1859	259	53	cifar	cifar	ADV
cana-1859	259	54	,	,	PUNCT
cana-1859	259	55	chestxray8	chestxray8	PROPN
cana-1859	259	56	,	,	PUNCT
cana-1859	259	57	and	and	CCONJ
cana-1859	259	58	architectural	architectural	ADJ
cana-1859	259	59	heritage	heritage	NOUN
cana-1859	259	60	datasets	dataset	NOUN
cana-1859	259	61	.	.	PUNCT
cana-1859	260	1	the	the	DET
cana-1859	260	2	vmcnn	vmcnn	PROPN
cana-1859	260	3	model	model	NOUN
cana-1859	260	4	,	,	PUNCT
cana-1859	260	5	by	by	ADP
cana-1859	260	6	melding	meld	VERB
cana-1859	260	7	these	these	DET
cana-1859	260	8	ancient	ancient	ADJ
cana-1859	260	9	techniques	technique	NOUN
cana-1859	260	10	with	with	ADP
cana-1859	260	11	modern	modern	ADJ
cana-1859	260	12	neural	neural	ADJ
cana-1859	260	13	network	network	NOUN
cana-1859	260	14	architecture	architecture	NOUN
cana-1859	260	15	,	,	PUNCT
cana-1859	260	16	not	not	PART
cana-1859	260	17	only	only	ADV
cana-1859	260	18	demonstrates	demonstrate	VERB
cana-1859	260	19	a	a	DET
cana-1859	260	20	significant	significant	ADJ
cana-1859	260	21	leap	leap	NOUN
cana-1859	260	22	in	in	ADP
cana-1859	260	23	image	image	NOUN
cana-1859	260	24	classification	classification	NOUN
cana-1859	260	25	tasks	task	NOUN
cana-1859	260	26	but	but	CCONJ
cana-1859	260	27	also	also	ADV
cana-1859	260	28	paves	pave	VERB
cana-1859	260	29	the	the	DET
cana-1859	260	30	way	way	NOUN
cana-1859	260	31	for	for	ADP
cana-1859	260	32	a	a	DET
cana-1859	260	33	novel	novel	ADJ
cana-1859	260	34	interdisciplinary	interdisciplinary	ADJ
cana-1859	260	35	approach	approach	NOUN
cana-1859	260	36	,	,	PUNCT
cana-1859	260	37	blending	blend	VERB
cana-1859	260	38	timeless	timeless	ADJ
cana-1859	260	39	mathematical	mathematical	ADJ
cana-1859	260	40	wisdom	wisdom	NOUN
cana-1859	260	41	with	with	ADP
cana-1859	260	42	cutting	cut	VERB
cana-1859	260	43	-	-	PUNCT
cana-1859	260	44	edge	edge	NOUN
cana-1859	260	45	artificial	artificial	ADJ
cana-1859	260	46	intelligence	intelligence	NOUN
cana-1859	260	47	technologies	technology	NOUN
cana-1859	260	48	.	.	PUNCT
cana-1859	261	1	in	in	ADP
cana-1859	261	2	our	our	PRON
cana-1859	261	3	research	research	NOUN
cana-1859	261	4	,	,	PUNCT
cana-1859	261	5	we	we	PRON
cana-1859	261	6	designed	design	VERB
cana-1859	261	7	a	a	DET
cana-1859	261	8	comprehensive	comprehensive	ADJ
cana-1859	261	9	experimental	experimental	ADJ
cana-1859	261	10	framework	framework	NOUN
cana-1859	261	11	to	to	PART
cana-1859	261	12	evaluate	evaluate	VERB
cana-1859	261	13	the	the	DET
cana-1859	261	14	performance	performance	NOUN
cana-1859	261	15	of	of	ADP
cana-1859	261	16	the	the	DET
cana-1859	261	17	vmcnn	vmcnn	PROPN
cana-1859	261	18	model	model	NOUN
cana-1859	261	19	against	against	ADP
cana-1859	261	20	established	establish	VERB
cana-1859	261	21	models	model	NOUN
cana-1859	261	22	such	such	ADJ
cana-1859	261	23	as	as	ADP
cana-1859	261	24	cnn	cnn	PROPN
cana-1859	261	25	elm	elm	PROPN
cana-1859	261	26	,	,	PUNCT
cana-1859	261	27	dcnn	dcnn	PROPN
cana-1859	261	28	,	,	PUNCT
cana-1859	261	29	and	and	CCONJ
cana-1859	261	30	fireclassnet	fireclassnet	NOUN
cana-1859	261	31	.	.	PUNCT
cana-1859	262	1	the	the	DET
cana-1859	262	2	experimental	experimental	ADJ
cana-1859	262	3	setup	setup	NOUN
cana-1859	262	4	is	be	AUX
cana-1859	262	5	structured	structure	VERB
cana-1859	262	6	to	to	PART
cana-1859	262	7	rigorously	rigorously	ADV
cana-1859	262	8	assess	assess	VERB
cana-1859	262	9	various	various	ADJ
cana-1859	262	10	performance	performance	NOUN
cana-1859	262	11	metrics	metric	NOUN
cana-1859	262	12	,	,	PUNCT
cana-1859	262	13	including	include	VERB
cana-1859	262	14	precision	precision	NOUN
cana-1859	262	15	,	,	PUNCT
cana-1859	262	16	accuracy	accuracy	NOUN
cana-1859	262	17	,	,	PUNCT
cana-1859	262	18	recall	recall	NOUN
cana-1859	262	19	,	,	PUNCT
cana-1859	262	20	delay	delay	NOUN
cana-1859	262	21	,	,	PUNCT
cana-1859	262	22	auc	auc	NOUN
cana-1859	262	23	,	,	PUNCT
cana-1859	262	24	and	and	CCONJ
cana-1859	262	25	mae	mae	PROPN
cana-1859	262	26	across	across	ADP
cana-1859	262	27	multiple	multiple	ADJ
cana-1859	262	28	datasets	dataset	NOUN
cana-1859	262	29	.	.	PUNCT
cana-1859	263	1	dataset	dataset	ADJ
cana-1859	263	2	description	description	NOUN
cana-1859	263	3	the	the	DET
cana-1859	263	4	datasets	dataset	NOUN
cana-1859	263	5	employed	employ	VERB
cana-1859	263	6	in	in	ADP
cana-1859	263	7	our	our	PRON
cana-1859	263	8	experiments	experiment	NOUN
cana-1859	263	9	include	include	VERB
cana-1859	263	10	:	:	PUNCT
cana-1859	263	11	1	1	X
cana-1859	263	12	.	.	X
cana-1859	263	13	imagenet	imagenet	NOUN
cana-1859	263	14	:	:	PUNCT
cana-1859	263	15	a	a	DET
cana-1859	263	16	large	large	ADJ
cana-1859	263	17	-	-	PUNCT
cana-1859	263	18	scale	scale	NOUN
cana-1859	263	19	dataset	dataset	NOUN
cana-1859	263	20	containing	contain	VERB
cana-1859	263	21	over	over	ADP
cana-1859	263	22	a	a	DET
cana-1859	263	23	million	million	NUM
cana-1859	263	24	images	image	NOUN
cana-1859	263	25	across	across	ADP
cana-1859	263	26	a	a	DET
cana-1859	263	27	thousand	thousand	NUM
cana-1859	263	28	categories	category	NOUN
cana-1859	263	29	.	.	PUNCT
cana-1859	264	1	2	2	X
cana-1859	264	2	.	.	X
cana-1859	264	3	cifar	cifar	PROPN
cana-1859	264	4	:	:	PUNCT
cana-1859	264	5	a	a	DET
cana-1859	264	6	collection	collection	NOUN
cana-1859	264	7	of	of	ADP
cana-1859	264	8	images	image	NOUN
cana-1859	264	9	divided	divide	VERB
cana-1859	264	10	into	into	ADP
cana-1859	264	11	10	10	NUM
cana-1859	264	12	and	and	CCONJ
cana-1859	264	13	100	100	NUM
cana-1859	264	14	classes	class	NOUN
cana-1859	264	15	(	(	PUNCT
cana-1859	264	16	cifar-10	cifar-10	PROPN
cana-1859	264	17	and	and	CCONJ
cana-1859	264	18	cifar-100	cifar-100	NOUN
cana-1859	264	19	)	)	PUNCT
cana-1859	264	20	.	.	PUNCT
cana-1859	265	1	3	3	X
cana-1859	265	2	.	.	X
cana-1859	265	3	chestxray8	chestxray8	PROPN
cana-1859	265	4	:	:	PUNCT
cana-1859	265	5	a	a	DET
cana-1859	265	6	medical	medical	ADJ
cana-1859	265	7	imaging	imaging	NOUN
cana-1859	265	8	dataset	dataset	NOUN
cana-1859	265	9	comprising	comprising	NOUN
cana-1859	265	10	chest	chest	NOUN
cana-1859	265	11	x	x	NOUN
cana-1859	265	12	-	-	NOUN
cana-1859	265	13	ray	ray	NOUN
cana-1859	265	14	images	image	NOUN
cana-1859	265	15	annotated	annotate	VERB
cana-1859	265	16	with	with	ADP
cana-1859	265	17	disease	disease	NOUN
cana-1859	265	18	labels	label	NOUN
cana-1859	265	19	.	.	PUNCT
cana-1859	266	1	4	4	X
cana-1859	266	2	.	.	X
cana-1859	266	3	architectural	architectural	ADJ
cana-1859	266	4	heritage	heritage	NOUN
cana-1859	266	5	dataset	dataset	NOUN
cana-1859	266	6	:	:	PUNCT
cana-1859	266	7	images	image	NOUN
cana-1859	266	8	of	of	ADP
cana-1859	266	9	various	various	ADJ
cana-1859	266	10	architectural	architectural	ADJ
cana-1859	266	11	structures	structure	NOUN
cana-1859	266	12	used	use	VERB
cana-1859	266	13	for	for	ADP
cana-1859	266	14	heritage	heritage	NOUN
cana-1859	266	15	conservation	conservation	NOUN
cana-1859	266	16	studies	study	NOUN
cana-1859	266	17	.	.	PUNCT
cana-1859	267	1	the	the	DET
cana-1859	267	2	datasets	dataset	NOUN
cana-1859	267	3	were	be	AUX
cana-1859	267	4	divided	divide	VERB
cana-1859	267	5	into	into	ADP
cana-1859	267	6	training	training	NOUN
cana-1859	267	7	,	,	PUNCT
cana-1859	267	8	validation	validation	NOUN
cana-1859	267	9	,	,	PUNCT
cana-1859	267	10	and	and	CCONJ
cana-1859	267	11	test	test	NOUN
cana-1859	267	12	sets	set	NOUN
cana-1859	267	13	,	,	PUNCT
cana-1859	267	14	with	with	ADP
cana-1859	267	15	a	a	DET
cana-1859	267	16	typical	typical	ADJ
cana-1859	267	17	split	split	NOUN
cana-1859	267	18	of	of	ADP
cana-1859	267	19	70	70	NUM
cana-1859	267	20	%	%	NOUN
cana-1859	267	21	for	for	ADP
cana-1859	267	22	training	training	NOUN
cana-1859	267	23	,	,	PUNCT
cana-1859	267	24	15	15	NUM
cana-1859	267	25	%	%	NOUN
cana-1859	267	26	for	for	ADP
cana-1859	267	27	validation	validation	NOUN
cana-1859	267	28	,	,	PUNCT
cana-1859	267	29	and	and	CCONJ
cana-1859	267	30	15	15	NUM
cana-1859	267	31	%	%	NOUN
cana-1859	267	32	for	for	ADP
cana-1859	267	33	testing	testing	NOUN
cana-1859	267	34	.	.	PUNCT
cana-1859	268	1	model	model	NOUN
cana-1859	268	2	configuration	configuration	NOUN
cana-1859	268	3	the	the	DET
cana-1859	268	4	vmcnn	vmcnn	PROPN
cana-1859	268	5	model	model	NOUN
cana-1859	268	6	was	be	AUX
cana-1859	268	7	configured	configure	VERB
cana-1859	268	8	with	with	ADP
cana-1859	268	9	the	the	DET
cana-1859	268	10	following	follow	VERB
cana-1859	268	11	parameters	parameter	NOUN
cana-1859	268	12	:	:	PUNCT
cana-1859	268	13	•	•	NUM
cana-1859	268	14	input	input	NOUN
cana-1859	268	15	layer	layer	NOUN
cana-1859	268	16	:	:	PUNCT
cana-1859	268	17	adapted	adapt	VERB
cana-1859	268	18	to	to	ADP
cana-1859	268	19	the	the	DET
cana-1859	268	20	dataset	dataset	ADJ
cana-1859	268	21	image	image	NOUN
cana-1859	268	22	size	size	NOUN
cana-1859	268	23	.	.	PUNCT
cana-1859	269	1	for	for	ADP
cana-1859	269	2	imagenet	imagenet	NOUN
cana-1859	269	3	,	,	PUNCT
cana-1859	269	4	the	the	DET
cana-1859	269	5	input	input	NOUN
cana-1859	269	6	size	size	NOUN
cana-1859	269	7	was	be	AUX
cana-1859	269	8	set	set	VERB
cana-1859	269	9	to	to	ADP
cana-1859	269	10	224x224	224x224	NUM
cana-1859	269	11	pixels	pixel	NOUN
cana-1859	269	12	.	.	PUNCT
cana-1859	270	1	•	•	NUM
cana-1859	270	2	convolutional	convolutional	ADJ
cana-1859	270	3	layers	layer	NOUN
cana-1859	270	4	:	:	PUNCT
cana-1859	270	5	multiple	multiple	ADJ
cana-1859	270	6	layers	layer	NOUN
cana-1859	270	7	with	with	ADP
cana-1859	270	8	varying	vary	VERB
cana-1859	270	9	numbers	number	NOUN
cana-1859	270	10	of	of	ADP
cana-1859	270	11	filters	filter	NOUN
cana-1859	270	12	,	,	PUNCT
cana-1859	270	13	starting	start	VERB
cana-1859	270	14	from	from	ADP
cana-1859	270	15	32	32	NUM
cana-1859	270	16	and	and	CCONJ
cana-1859	270	17	doubling	double	VERB
cana-1859	270	18	in	in	ADP
cana-1859	270	19	each	each	DET
cana-1859	270	20	subsequent	subsequent	ADJ
cana-1859	270	21	layer	layer	NOUN
cana-1859	270	22	.	.	PUNCT
cana-1859	271	1	•	•	NOUN
cana-1859	271	2	activation	activation	NOUN
cana-1859	271	3	function	function	NOUN
cana-1859	271	4	:	:	PUNCT
cana-1859	271	5	relu	relu	NOUN
cana-1859	271	6	(	(	PUNCT
cana-1859	271	7	rectified	rectified	ADJ
cana-1859	271	8	linear	linear	NOUN
cana-1859	271	9	unit	unit	NOUN
cana-1859	271	10	)	)	PUNCT
cana-1859	271	11	was	be	AUX
cana-1859	271	12	used	use	VERB
cana-1859	271	13	for	for	ADP
cana-1859	271	14	non	non	ADJ
cana-1859	271	15	-	-	ADJ
cana-1859	271	16	linearity	linearity	ADJ
cana-1859	271	17	.	.	PUNCT
cana-1859	272	1	•	•	NOUN
cana-1859	272	2	pooling	pool	VERB
cana-1859	272	3	layers	layer	NOUN
cana-1859	272	4	:	:	PUNCT
cana-1859	272	5	max	max	PROPN
cana-1859	272	6	pooling	pool	VERB
cana-1859	272	7	with	with	ADP
cana-1859	272	8	a	a	DET
cana-1859	272	9	2x2	2x2	NUM
cana-1859	272	10	window	window	NOUN
cana-1859	272	11	size	size	NOUN
cana-1859	272	12	.	.	PUNCT
cana-1859	273	1	•	•	NOUN
cana-1859	273	2	fully	fully	ADV
cana-1859	273	3	connected	connected	ADJ
cana-1859	273	4	layers	layer	NOUN
cana-1859	273	5	:	:	PUNCT
cana-1859	273	6	two	two	NUM
cana-1859	273	7	layers	layer	NOUN
cana-1859	273	8	with	with	ADP
cana-1859	273	9	512	512	NUM
cana-1859	273	10	and	and	CCONJ
cana-1859	273	11	256	256	NUM
cana-1859	273	12	nodes	node	NOUN
cana-1859	273	13	respectively	respectively	ADV
cana-1859	273	14	.	.	PUNCT
cana-1859	274	1	•	•	NUM
cana-1859	274	2	output	output	NOUN
cana-1859	274	3	layer	layer	NOUN
cana-1859	274	4	:	:	PUNCT
cana-1859	274	5	number	number	NOUN
cana-1859	274	6	of	of	ADP
cana-1859	274	7	nodes	node	NOUN
cana-1859	274	8	equivalent	equivalent	ADJ
cana-1859	274	9	to	to	ADP
cana-1859	274	10	the	the	DET
cana-1859	274	11	number	number	NOUN
cana-1859	274	12	of	of	ADP
cana-1859	274	13	classes	class	NOUN
cana-1859	274	14	in	in	ADP
cana-1859	274	15	the	the	DET
cana-1859	274	16	dataset	dataset	NOUN
cana-1859	274	17	.	.	PUNCT
cana-1859	275	1	•	•	NUM
cana-1859	275	2	optimizer	optimizer	NOUN
cana-1859	275	3	:	:	PUNCT
cana-1859	275	4	adam	adam	PROPN
cana-1859	275	5	optimizer	optimizer	NOUN
cana-1859	275	6	with	with	ADP
cana-1859	275	7	a	a	DET
cana-1859	275	8	learning	learn	VERB
cana-1859	275	9	rate	rate	NOUN
cana-1859	275	10	of	of	ADP
cana-1859	275	11	0.001	0.001	NUM
cana-1859	275	12	.	.	NOUN
cana-1859	275	13	•	•	NUM
cana-1859	275	14	loss	loss	NOUN
cana-1859	275	15	function	function	NOUN
cana-1859	275	16	:	:	PUNCT
cana-1859	275	17	categorical	categorical	ADJ
cana-1859	275	18	cross	cross	NOUN
cana-1859	275	19	-	-	NOUN
cana-1859	275	20	entropy	entropy	NOUN
cana-1859	275	21	.	.	PUNCT
cana-1859	276	1	vedic	vedic	ADJ
cana-1859	276	2	mathematics	mathematics	PROPN
cana-1859	276	3	techniques	technique	NOUN
cana-1859	276	4	applied	apply	VERB
cana-1859	276	5	the	the	DET
cana-1859	276	6	following	follow	VERB
cana-1859	276	7	vedic	vedic	ADJ
cana-1859	276	8	mathematical	mathematical	ADJ
cana-1859	276	9	sutras	sutra	NOUN
cana-1859	276	10	were	be	AUX
cana-1859	276	11	integrated	integrate	VERB
cana-1859	276	12	:	:	PUNCT
cana-1859	276	13	communications	communication	NOUN
cana-1859	276	14	on	on	ADP
cana-1859	276	15	applied	apply	VERB
cana-1859	276	16	nonlinear	nonlinear	ADJ
cana-1859	276	17	analysis	analysis	NOUN
cana-1859	276	18	issn	issn	NOUN
cana-1859	276	19	:	:	PUNCT
cana-1859	276	20	1074	1074	NUM
cana-1859	276	21	-	-	PUNCT
cana-1859	276	22	133x	133x	NUM
cana-1859	276	23	vol	vol	NOUN
cana-1859	276	24	32	32	NUM
cana-1859	276	25	no	no	NOUN
cana-1859	276	26	.	.	NOUN
cana-1859	276	27	2	2	NUM
cana-1859	276	28	(	(	PUNCT
cana-1859	276	29	2025	2025	NUM
cana-1859	276	30	)	)	PUNCT
cana-1859	276	31	655	655	NUM
cana-1859	276	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	276	33	1	1	X
cana-1859	276	34	.	.	PUNCT
cana-1859	276	35	urdhva	urdhva	PROPN
cana-1859	276	36	-	-	PUNCT
cana-1859	276	37	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	276	38	:	:	PUNCT
cana-1859	276	39	for	for	ADP
cana-1859	276	40	efficient	efficient	ADJ
cana-1859	276	41	multiplication	multiplication	NOUN
cana-1859	276	42	operations	operation	NOUN
cana-1859	276	43	within	within	ADP
cana-1859	276	44	the	the	DET
cana-1859	276	45	network	network	NOUN
cana-1859	276	46	.	.	PUNCT
cana-1859	277	1	2	2	X
cana-1859	277	2	.	.	X
cana-1859	277	3	anurupyena	anurupyena	PROPN
cana-1859	277	4	:	:	PUNCT
cana-1859	277	5	simplifying	simplify	VERB
cana-1859	277	6	ratio	ratio	NOUN
cana-1859	277	7	-	-	PUNCT
cana-1859	277	8	based	base	VERB
cana-1859	277	9	calculations	calculation	NOUN
cana-1859	277	10	.	.	PUNCT
cana-1859	278	1	3	3	X
cana-1859	278	2	.	.	X
cana-1859	278	3	nikhilam	nikhilam	PROPN
cana-1859	278	4	navatashcaramam	navatashcaramam	PROPN
cana-1859	278	5	dashatah	dashatah	NOUN
cana-1859	278	6	:	:	PUNCT
cana-1859	278	7	for	for	ADP
cana-1859	278	8	subtraction	subtraction	NOUN
cana-1859	278	9	operations	operation	NOUN
cana-1859	278	10	.	.	PUNCT
cana-1859	279	1	4	4	X
cana-1859	279	2	.	.	X
cana-1859	279	3	other	other	ADJ
cana-1859	279	4	sutras	sutra	NOUN
cana-1859	279	5	as	as	SCONJ
cana-1859	279	6	mentioned	mention	VERB
cana-1859	279	7	in	in	ADP
cana-1859	279	8	the	the	DET
cana-1859	279	9	abstract	abstract	NOUN
cana-1859	279	10	were	be	AUX
cana-1859	279	11	also	also	ADV
cana-1859	279	12	applied	apply	VERB
cana-1859	279	13	where	where	SCONJ
cana-1859	279	14	relevant	relevant	ADJ
cana-1859	279	15	.	.	PUNCT
cana-1859	279	16	training	training	NOUN
cana-1859	279	17	and	and	CCONJ
cana-1859	279	18	evaluation	evaluation	NOUN
cana-1859	279	19	each	each	DET
cana-1859	279	20	model	model	NOUN
cana-1859	279	21	was	be	AUX
cana-1859	279	22	trained	train	VERB
cana-1859	279	23	on	on	ADP
cana-1859	279	24	the	the	DET
cana-1859	279	25	same	same	ADJ
cana-1859	279	26	datasets	dataset	NOUN
cana-1859	279	27	with	with	ADP
cana-1859	279	28	comparable	comparable	ADJ
cana-1859	279	29	hardware	hardware	NOUN
cana-1859	279	30	settings	setting	NOUN
cana-1859	279	31	to	to	PART
cana-1859	279	32	ensure	ensure	VERB
cana-1859	279	33	fairness	fairness	NOUN
cana-1859	279	34	in	in	ADP
cana-1859	279	35	comparison	comparison	NOUN
cana-1859	279	36	.	.	PUNCT
cana-1859	280	1	the	the	DET
cana-1859	280	2	training	training	NOUN
cana-1859	280	3	was	be	AUX
cana-1859	280	4	carried	carry	VERB
cana-1859	280	5	out	out	ADP
cana-1859	280	6	for	for	ADP
cana-1859	280	7	a	a	DET
cana-1859	280	8	sufficient	sufficient	ADJ
cana-1859	280	9	number	number	NOUN
cana-1859	280	10	of	of	ADP
cana-1859	280	11	epochs	epoch	NOUN
cana-1859	280	12	until	until	SCONJ
cana-1859	280	13	convergence	convergence	NOUN
cana-1859	280	14	was	be	AUX
cana-1859	280	15	observed	observe	VERB
cana-1859	280	16	in	in	ADP
cana-1859	280	17	the	the	DET
cana-1859	280	18	loss	loss	NOUN
cana-1859	280	19	and	and	CCONJ
cana-1859	280	20	accuracy	accuracy	NOUN
cana-1859	280	21	metrics	metric	NOUN
cana-1859	280	22	.	.	PUNCT
cana-1859	281	1	hardware	hardware	NOUN
cana-1859	281	2	and	and	CCONJ
cana-1859	281	3	software	software	NOUN
cana-1859	281	4	configuration	configuration	NOUN
cana-1859	281	5	the	the	DET
cana-1859	281	6	experiments	experiment	NOUN
cana-1859	281	7	were	be	AUX
cana-1859	281	8	conducted	conduct	VERB
cana-1859	281	9	on	on	ADP
cana-1859	281	10	a	a	DET
cana-1859	281	11	computing	compute	VERB
cana-1859	281	12	system	system	NOUN
cana-1859	281	13	equipped	equip	VERB
cana-1859	281	14	with	with	ADP
cana-1859	281	15	:	:	PUNCT
cana-1859	281	16	•	•	NUM
cana-1859	281	17	cpu	cpu	PROPN
cana-1859	281	18	:	:	PUNCT
cana-1859	281	19	intel	intel	PROPN
cana-1859	281	20	core	core	NOUN
cana-1859	281	21	i9	i9	NOUN
cana-1859	281	22	processor	processor	NOUN
cana-1859	281	23	•	•	ADP
cana-1859	281	24	gpu	gpu	PROPN
cana-1859	281	25	:	:	PUNCT
cana-1859	281	26	nvidia	nvidia	PROPN
cana-1859	281	27	geforce	geforce	NOUN
cana-1859	281	28	rtx	rtx	PROPN
cana-1859	281	29	3080	3080	NUM
cana-1859	281	30	•	•	NOUN
cana-1859	281	31	ram	ram	NOUN
cana-1859	281	32	:	:	PUNCT
cana-1859	281	33	32	32	NUM
cana-1859	281	34	gb	gb	NOUN
cana-1859	281	35	•	•	NUM
cana-1859	281	36	operating	operating	NOUN
cana-1859	281	37	system	system	NOUN
cana-1859	281	38	:	:	PUNCT
cana-1859	281	39	ubuntu	ubuntu	NOUN
cana-1859	281	40	20.04	20.04	NUM
cana-1859	281	41	•	•	NOUN
cana-1859	281	42	software	software	NOUN
cana-1859	281	43	:	:	PUNCT
cana-1859	281	44	python	python	NOUN
cana-1859	281	45	3.8	3.8	NUM
cana-1859	281	46	,	,	PUNCT
cana-1859	281	47	tensorflow	tensorflow	NOUN
cana-1859	281	48	2.4	2.4	NUM
cana-1859	281	49	,	,	PUNCT
cana-1859	281	50	and	and	CCONJ
cana-1859	281	51	other	other	ADJ
cana-1859	281	52	relevant	relevant	ADJ
cana-1859	281	53	libraries	library	NOUN
cana-1859	281	54	.	.	PUNCT
cana-1859	282	1	the	the	DET
cana-1859	282	2	results	result	NOUN
cana-1859	282	3	of	of	ADP
cana-1859	282	4	vmcnn	vmcnn	NOUN
cana-1859	282	5	were	be	AUX
cana-1859	282	6	rigorously	rigorously	ADV
cana-1859	282	7	compared	compare	VERB
cana-1859	282	8	with	with	ADP
cana-1859	282	9	those	those	PRON
cana-1859	282	10	of	of	ADP
cana-1859	282	11	cnn	cnn	PROPN
cana-1859	282	12	elm	elm	PROPN
cana-1859	282	13	,	,	PUNCT
cana-1859	282	14	dcnn	dcnn	PROPN
cana-1859	282	15	,	,	PUNCT
cana-1859	282	16	and	and	CCONJ
cana-1859	282	17	fireclassnet	fireclassnet	NOUN
cana-1859	282	18	across	across	ADP
cana-1859	282	19	different	different	ADJ
cana-1859	282	20	dataset	dataset	NOUN
cana-1859	282	21	sizes	size	NOUN
cana-1859	282	22	ranging	range	VERB
cana-1859	282	23	from	from	ADP
cana-1859	282	24	96k	96k	NOUN
cana-1859	282	25	to	to	ADP
cana-1859	282	26	1728k	1728k	NOUN
cana-1859	282	27	.	.	PUNCT
cana-1859	283	1	the	the	DET
cana-1859	283	2	comparisons	comparison	NOUN
cana-1859	283	3	were	be	AUX
cana-1859	283	4	made	make	VERB
cana-1859	283	5	on	on	ADP
cana-1859	283	6	identical	identical	ADJ
cana-1859	283	7	hardware	hardware	NOUN
cana-1859	283	8	and	and	CCONJ
cana-1859	283	9	software	software	NOUN
cana-1859	283	10	configurations	configuration	NOUN
cana-1859	283	11	to	to	PART
cana-1859	283	12	ensure	ensure	VERB
cana-1859	283	13	a	a	DET
cana-1859	283	14	consistent	consistent	ADJ
cana-1859	283	15	and	and	CCONJ
cana-1859	283	16	fair	fair	ADJ
cana-1859	283	17	evaluation	evaluation	NOUN
cana-1859	283	18	environment	environment	NOUN
cana-1859	283	19	.	.	PUNCT
cana-1859	284	1	based	base	VERB
cana-1859	284	2	on	on	ADP
cana-1859	284	3	this	this	DET
cana-1859	284	4	setup	setup	NOUN
cana-1859	284	5	,	,	PUNCT
cana-1859	284	6	equations	equation	NOUN
cana-1859	284	7	21	21	NUM
cana-1859	284	8	,	,	PUNCT
cana-1859	284	9	22	22	NUM
cana-1859	284	10	,	,	PUNCT
cana-1859	284	11	and	and	CCONJ
cana-1859	284	12	23	23	NUM
cana-1859	284	13	were	be	AUX
cana-1859	284	14	used	use	VERB
cana-1859	284	15	to	to	PART
cana-1859	284	16	assess	assess	VERB
cana-1859	284	17	the	the	DET
cana-1859	284	18	precision	precision	NOUN
cana-1859	284	19	(	(	PUNCT
cana-1859	284	20	p	p	NOUN
cana-1859	284	21	)	)	PUNCT
cana-1859	284	22	,	,	PUNCT
cana-1859	284	23	accuracy	accuracy	NOUN
cana-1859	284	24	(	(	PUNCT
cana-1859	284	25	a	a	NOUN
cana-1859	284	26	)	)	PUNCT
cana-1859	284	27	,	,	PUNCT
cana-1859	284	28	and	and	CCONJ
cana-1859	284	29	recall	recall	NOUN
cana-1859	284	30	(	(	PUNCT
cana-1859	284	31	r	r	NOUN
cana-1859	284	32	)	)	PUNCT
cana-1859	284	33	,	,	PUNCT
cana-1859	284	34	levels	level	NOUN
cana-1859	284	35	based	base	VERB
cana-1859	284	36	on	on	ADP
cana-1859	284	37	this	this	DET
cana-1859	284	38	technique	technique	NOUN
cana-1859	284	39	,	,	PUNCT
cana-1859	284	40	while	while	SCONJ
cana-1859	284	41	equations	equation	NOUN
cana-1859	284	42	24	24	NUM
cana-1859	284	43	&	&	CCONJ
cana-1859	284	44	25	25	NUM
cana-1859	284	45	were	be	AUX
cana-1859	284	46	used	use	VERB
cana-1859	284	47	to	to	PART
cana-1859	284	48	estimate	estimate	VERB
cana-1859	284	49	the	the	DET
cana-1859	284	50	overall	overall	ADJ
cana-1859	284	51	precision	precision	NOUN
cana-1859	284	52	(	(	PUNCT
cana-1859	284	53	auc	auc	NOUN
cana-1859	284	54	)	)	PUNCT
cana-1859	284	55	&	&	CCONJ
cana-1859	284	56	mean	mean	VERB
cana-1859	284	57	absolute	absolute	ADJ
cana-1859	284	58	error	error	NOUN
cana-1859	284	59	(	(	PUNCT
cana-1859	284	60	mae	mae	PROPN
cana-1859	284	61	)	)	PUNCT
cana-1859	284	62	as	as	SCONJ
cana-1859	284	63	follows	follow	VERB
cana-1859	284	64	,	,	PUNCT
cana-1859	284	65	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-1859	284	66	=	=	SYM
cana-1859	284	67	𝑇𝑃	𝑇𝑃	PROPN
cana-1859	284	68	𝑇𝑃	𝑇𝑃	PROPN
cana-1859	284	69	+	+	CCONJ
cana-1859	284	70	𝐹𝑃	𝐹𝑃	PROPN
cana-1859	284	71	…	…	PUNCT
cana-1859	284	72	(	(	PUNCT
cana-1859	284	73	21	21	NUM
cana-1859	284	74	)	)	PUNCT
cana-1859	284	75	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
cana-1859	284	76	=	=	SYM
cana-1859	284	77	𝑇𝑃	𝑇𝑃	PROPN
cana-1859	284	78	+	+	CCONJ
cana-1859	284	79	𝑇𝑁	𝑇𝑁	PROPN
cana-1859	284	80	𝑇𝑃	𝑇𝑃	PROPN
cana-1859	284	81	+	+	CCONJ
cana-1859	284	82	𝑇𝑁	𝑇𝑁	PROPN
cana-1859	284	83	+	+	NUM
cana-1859	284	84	𝐹𝑃	𝐹𝑃	NOUN
cana-1859	285	1	+	+	CCONJ
cana-1859	285	2	𝐹𝑁	𝐹𝑁	PROPN
cana-1859	285	3	…	…	PUNCT
cana-1859	285	4	(	(	PUNCT
cana-1859	285	5	22	22	NUM
cana-1859	285	6	)	)	PUNCT
cana-1859	285	7	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-1859	285	8	=	=	SYM
cana-1859	285	9	𝑇𝑃	𝑇𝑃	PROPN
cana-1859	285	10	𝑇𝑃	𝑇𝑃	PROPN
cana-1859	285	11	+	+	CCONJ
cana-1859	285	12	𝐹𝑁	𝐹𝑁	PROPN
cana-1859	285	13	…	…	PUNCT
cana-1859	285	14	(	(	PUNCT
cana-1859	285	15	23	23	NUM
cana-1859	285	16	)	)	PUNCT
cana-1859	285	17	𝐴𝑈𝐶	𝐴𝑈𝐶	NOUN
cana-1859	285	18	=	=	SYM
cana-1859	285	19	∫	∫	PROPN
cana-1859	286	1	𝑇𝑃𝑅(𝐹𝑃𝑅)𝑑𝐹𝑃𝑅	𝑇𝑃𝑅(𝐹𝑃𝑅)𝑑𝐹𝑃𝑅	NOUN
cana-1859	286	2	…	…	PUNCT
cana-1859	286	3	(	(	PUNCT
cana-1859	286	4	24	24	NUM
cana-1859	286	5	)	)	PUNCT
cana-1859	286	6	𝑀𝐴𝐸	𝑀𝐴𝐸	PROPN
cana-1859	286	7	=	=	SYM
cana-1859	286	8	∑	∑	PUNCT
cana-1859	286	9	𝐴(𝑖	𝐴(𝑖	CCONJ
cana-1859	286	10	)	)	PUNCT
cana-1859	286	11	−	−	PROPN
cana-1859	286	12	𝑃(𝑖)𝑁	𝑃(𝑖)𝑁	NOUN
cana-1859	286	13	𝑖=1	𝑖=1	PUNCT
cana-1859	287	1	𝑁	𝑁	PROPN
cana-1859	287	2	…	…	PUNCT
cana-1859	287	3	(	(	PUNCT
cana-1859	287	4	25	25	NUM
cana-1859	287	5	)	)	PUNCT
cana-1859	287	6	there	there	PRON
cana-1859	287	7	are	be	VERB
cana-1859	287	8	three	three	NUM
cana-1859	287	9	different	different	ADJ
cana-1859	287	10	kinds	kind	NOUN
cana-1859	287	11	of	of	ADP
cana-1859	287	12	test	test	NOUN
cana-1859	287	13	set	set	VERB
cana-1859	287	14	predictions	prediction	NOUN
cana-1859	287	15	:	:	PUNCT
cana-1859	287	16	true	true	ADJ
cana-1859	287	17	positive	positive	ADJ
cana-1859	287	18	(	(	PUNCT
cana-1859	287	19	tp	tp	NOUN
cana-1859	287	20	)	)	PUNCT
cana-1859	287	21	(	(	PUNCT
cana-1859	287	22	number	number	NOUN
cana-1859	287	23	of	of	ADP
cana-1859	287	24	events	event	NOUN
cana-1859	287	25	in	in	ADP
cana-1859	287	26	timeseries	timeserie	NOUN
cana-1859	287	27	that	that	PRON
cana-1859	287	28	were	be	AUX
cana-1859	287	29	correctly	correctly	ADV
cana-1859	287	30	predicted	predict	VERB
cana-1859	287	31	as	as	ADP
cana-1859	287	32	positive	positive	ADJ
cana-1859	287	33	)	)	PUNCT
cana-1859	287	34	,	,	PUNCT
cana-1859	287	35	false	false	ADJ
cana-1859	287	36	positive	positive	ADJ
cana-1859	287	37	(	(	PUNCT
cana-1859	287	38	fp	fp	NOUN
cana-1859	287	39	)	)	PUNCT
cana-1859	287	40	(	(	PUNCT
cana-1859	287	41	number	number	NOUN
cana-1859	287	42	of	of	ADP
cana-1859	287	43	instances	instance	NOUN
cana-1859	287	44	in	in	ADP
cana-1859	287	45	time	time	NOUN
cana-1859	287	46	series	series	NOUN
cana-1859	287	47	that	that	PRON
cana-1859	287	48	were	be	AUX
cana-1859	287	49	incorrectly	incorrectly	ADV
cana-1859	287	50	predicted	predict	VERB
cana-1859	287	51	as	as	ADP
cana-1859	287	52	positive	positive	ADJ
cana-1859	287	53	)	)	PUNCT
cana-1859	287	54	,	,	PUNCT
cana-1859	287	55	and	and	CCONJ
cana-1859	287	56	false	false	ADJ
cana-1859	287	57	negative	negative	ADJ
cana-1859	287	58	(	(	PUNCT
cana-1859	287	59	fn	fn	NOUN
cana-1859	287	60	)	)	PUNCT
cana-1859	287	61	(	(	PUNCT
cana-1859	287	62	number	number	NOUN
cana-1859	287	63	of	of	ADP
cana-1859	287	64	instances	instance	NOUN
cana-1859	287	65	in	in	ADP
cana-1859	287	66	time	time	NOUN
cana-1859	287	67	series	series	NOUN
cana-1859	287	68	that	that	PRON
cana-1859	287	69	were	be	AUX
cana-1859	287	70	incorrectly	incorrectly	ADV
cana-1859	287	71	predicted	predict	VERB
cana-1859	287	72	as	as	ADP
cana-1859	287	73	negative	negative	ADJ
cana-1859	287	74	;	;	PUNCT
cana-1859	287	75	this	this	PRON
cana-1859	287	76	includes	include	VERB
cana-1859	287	77	normal	normal	ADJ
cana-1859	287	78	instance	instance	NOUN
cana-1859	287	79	samples	sample	NOUN
cana-1859	287	80	)	)	PUNCT
cana-1859	287	81	.	.	PUNCT
cana-1859	288	1	the	the	DET
cana-1859	288	2	documentation	documentation	NOUN
cana-1859	288	3	for	for	ADP
cana-1859	288	4	the	the	DET
cana-1859	288	5	time	time	NOUN
cana-1859	288	6	series	series	PROPN
cana-1859	288	7	makes	make	VERB
cana-1859	288	8	use	use	NOUN
cana-1859	288	9	of	of	ADP
cana-1859	288	10	all	all	DET
cana-1859	288	11	these	these	DET
cana-1859	288	12	terminologies	terminology	NOUN
cana-1859	288	13	,	,	PUNCT
cana-1859	288	14	while	while	SCONJ
cana-1859	288	15	𝐴	𝐴	PROPN
cana-1859	288	16	&	&	CCONJ
cana-1859	288	17	𝑃	𝑃	PROPN
cana-1859	288	18	represent	represent	VERB
cana-1859	288	19	the	the	DET
cana-1859	288	20	communications	communication	NOUN
cana-1859	288	21	on	on	ADP
cana-1859	288	22	applied	apply	VERB
cana-1859	288	23	nonlinear	nonlinear	ADJ
cana-1859	288	24	analysis	analysis	NOUN
cana-1859	288	25	issn	issn	NOUN
cana-1859	288	26	:	:	PUNCT
cana-1859	288	27	1074	1074	NUM
cana-1859	288	28	-	-	PUNCT
cana-1859	288	29	133x	133x	NUM
cana-1859	288	30	vol	vol	NOUN
cana-1859	288	31	32	32	NUM
cana-1859	288	32	no	no	NOUN
cana-1859	288	33	.	.	NOUN
cana-1859	288	34	2	2	NUM
cana-1859	288	35	(	(	PUNCT
cana-1859	288	36	2025	2025	NUM
cana-1859	288	37	)	)	PUNCT
cana-1859	289	1	656	656	NUM
cana-1859	289	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	289	3	actual	actual	ADJ
cana-1859	289	4	&	&	CCONJ
cana-1859	289	5	predicted	predict	VERB
cana-1859	289	6	classes	class	NOUN
cana-1859	289	7	for	for	ADP
cana-1859	289	8	𝑁	𝑁	PROPN
cana-1859	289	9	sample	sample	NOUN
cana-1859	289	10	evaluations	evaluation	NOUN
cana-1859	289	11	.	.	PUNCT
cana-1859	290	1	to	to	PART
cana-1859	290	2	determine	determine	VERB
cana-1859	290	3	the	the	DET
cana-1859	290	4	appropriate	appropriate	ADJ
cana-1859	290	5	tp	tp	NOUN
cana-1859	290	6	,	,	PUNCT
cana-1859	290	7	tn	tn	PROPN
cana-1859	290	8	,	,	PUNCT
cana-1859	290	9	fp	fp	NOUN
cana-1859	290	10	,	,	PUNCT
cana-1859	290	11	and	and	CCONJ
cana-1859	290	12	fn	fn	NOUN
cana-1859	290	13	values	value	NOUN
cana-1859	290	14	for	for	ADP
cana-1859	290	15	these	these	DET
cana-1859	290	16	scenarios	scenario	NOUN
cana-1859	290	17	,	,	PUNCT
cana-1859	290	18	we	we	PRON
cana-1859	290	19	compared	compare	VERB
cana-1859	290	20	the	the	DET
cana-1859	290	21	projected	project	VERB
cana-1859	290	22	time	time	NOUN
cana-1859	290	23	series	series	PROPN
cana-1859	290	24	classes	class	NOUN
cana-1859	290	25	likelihood	likelihood	VERB
cana-1859	290	26	to	to	ADP
cana-1859	290	27	the	the	DET
cana-1859	290	28	actual	actual	ADJ
cana-1859	290	29	time	time	NOUN
cana-1859	290	30	series	series	PROPN
cana-1859	290	31	classes	class	NOUN
cana-1859	290	32	in	in	ADP
cana-1859	290	33	the	the	DET
cana-1859	290	34	test	test	NOUN
cana-1859	290	35	dataset	dataset	NOUN
cana-1859	290	36	samples	sample	NOUN
cana-1859	290	37	using	use	VERB
cana-1859	290	38	the	the	DET
cana-1859	290	39	cnn	cnn	PROPN
cana-1859	290	40	elm	elm	PROPN
cana-1859	291	1	[	[	X
cana-1859	291	2	6	6	NUM
cana-1859	291	3	]	]	PUNCT
cana-1859	291	4	,	,	PUNCT
cana-1859	291	5	dcnn	dcnn	PROPN
cana-1859	291	6	[	[	X
cana-1859	291	7	8	8	NUM
cana-1859	291	8	]	]	PUNCT
cana-1859	291	9	,	,	PUNCT
cana-1859	291	10	and	and	CCONJ
cana-1859	291	11	fireclassnet	fireclassnet	NOUN
cana-1859	291	12	[	[	X
cana-1859	291	13	15	15	NUM
cana-1859	291	14	]	]	SYM
cana-1859	291	15	techniques	technique	NOUN
cana-1859	291	16	.	.	PUNCT
cana-1859	292	1	as	as	ADP
cana-1859	292	2	such	such	ADJ
cana-1859	292	3	,	,	PUNCT
cana-1859	292	4	we	we	PRON
cana-1859	292	5	were	be	AUX
cana-1859	292	6	able	able	ADJ
cana-1859	292	7	to	to	PART
cana-1859	292	8	predict	predict	VERB
cana-1859	292	9	these	these	DET
cana-1859	292	10	metrics	metric	NOUN
cana-1859	292	11	for	for	ADP
cana-1859	292	12	the	the	DET
cana-1859	292	13	results	result	NOUN
cana-1859	292	14	of	of	ADP
cana-1859	292	15	the	the	DET
cana-1859	292	16	suggested	suggest	VERB
cana-1859	292	17	model	model	NOUN
cana-1859	292	18	process	process	NOUN
cana-1859	292	19	.	.	PUNCT
cana-1859	293	1	the	the	DET
cana-1859	293	2	precision	precision	NOUN
cana-1859	293	3	levels	level	NOUN
cana-1859	293	4	based	base	VERB
cana-1859	293	5	on	on	ADP
cana-1859	293	6	these	these	DET
cana-1859	293	7	assessments	assessment	NOUN
cana-1859	293	8	are	be	AUX
cana-1859	293	9	displayed	display	VERB
cana-1859	293	10	as	as	SCONJ
cana-1859	293	11	follows	follow	VERB
cana-1859	293	12	in	in	ADP
cana-1859	293	13	figure	figure	NOUN
cana-1859	293	14	2	2	NUM
cana-1859	293	15	,	,	PUNCT
cana-1859	293	16	fig	fig	NOUN
cana-1859	293	17	2	2	NUM
cana-1859	293	18	.	.	PUNCT
cana-1859	293	19	observed	observe	VERB
cana-1859	293	20	precision	precision	NOUN
cana-1859	293	21	for	for	ADP
cana-1859	293	22	categorizing	categorize	VERB
cana-1859	293	23	multiple	multiple	ADJ
cana-1859	293	24	datasets	dataset	NOUN
cana-1859	293	25	into	into	ADP
cana-1859	293	26	classes	class	NOUN
cana-1859	293	27	when	when	SCONJ
cana-1859	293	28	analyzing	analyze	VERB
cana-1859	293	29	the	the	DET
cana-1859	293	30	precision	precision	NOUN
cana-1859	293	31	percentages	percentage	NOUN
cana-1859	293	32	(	(	PUNCT
cana-1859	293	33	p%	p%	PROPN
cana-1859	293	34	)	)	PUNCT
cana-1859	293	35	across	across	ADP
cana-1859	293	36	various	various	ADJ
cana-1859	293	37	dataset	dataset	NOUN
cana-1859	293	38	sizes	size	NOUN
cana-1859	293	39	(	(	PUNCT
cana-1859	293	40	ranging	range	VERB
cana-1859	293	41	from	from	ADP
cana-1859	293	42	96k	96k	NOUN
cana-1859	293	43	to	to	ADP
cana-1859	293	44	1728k	1728k	NUM
cana-1859	293	45	)	)	PUNCT
cana-1859	293	46	,	,	PUNCT
cana-1859	293	47	vmcnn	vmcnn	NOUN
cana-1859	293	48	consistently	consistently	ADV
cana-1859	293	49	outperforms	outperform	VERB
cana-1859	293	50	the	the	DET
cana-1859	293	51	other	other	ADJ
cana-1859	293	52	models	model	NOUN
cana-1859	293	53	.	.	PUNCT
cana-1859	294	1	for	for	ADP
cana-1859	294	2	instance	instance	NOUN
cana-1859	294	3	,	,	PUNCT
cana-1859	294	4	at	at	ADP
cana-1859	294	5	a	a	DET
cana-1859	294	6	dataset	dataset	ADJ
cana-1859	294	7	size	size	NOUN
cana-1859	294	8	of	of	ADP
cana-1859	294	9	240k	240k	NOUN
cana-1859	294	10	,	,	PUNCT
cana-1859	294	11	vmcnn	vmcnn	NOUN
cana-1859	294	12	achieved	achieve	VERB
cana-1859	294	13	a	a	DET
cana-1859	294	14	remarkable	remarkable	ADJ
cana-1859	294	15	precision	precision	NOUN
cana-1859	294	16	of	of	ADP
cana-1859	294	17	91.21	91.21	NUM
cana-1859	294	18	%	%	NOUN
cana-1859	294	19	,	,	PUNCT
cana-1859	294	20	significantly	significantly	ADV
cana-1859	294	21	higher	high	ADJ
cana-1859	294	22	than	than	ADP
cana-1859	294	23	its	its	PRON
cana-1859	294	24	closest	close	ADJ
cana-1859	294	25	competitor	competitor	NOUN
cana-1859	294	26	,	,	PUNCT
cana-1859	294	27	dcnn	dcnn	PROPN
cana-1859	294	28	,	,	PUNCT
cana-1859	294	29	which	which	PRON
cana-1859	294	30	scored	score	VERB
cana-1859	294	31	73.76	73.76	NUM
cana-1859	294	32	%	%	NOUN
cana-1859	294	33	.	.	PUNCT
cana-1859	295	1	this	this	DET
cana-1859	295	2	trend	trend	NOUN
cana-1859	295	3	of	of	ADP
cana-1859	295	4	vmcnn	vmcnn	NOUN
cana-1859	295	5	outshining	outshine	VERB
cana-1859	295	6	the	the	DET
cana-1859	295	7	others	other	NOUN
cana-1859	295	8	is	be	AUX
cana-1859	295	9	consistently	consistently	ADV
cana-1859	295	10	observed	observe	VERB
cana-1859	295	11	across	across	ADP
cana-1859	295	12	different	different	ADJ
cana-1859	295	13	dataset	dataset	NOUN
cana-1859	295	14	sizes	size	NOUN
cana-1859	295	15	.	.	PUNCT
cana-1859	296	1	notably	notably	ADV
cana-1859	296	2	,	,	PUNCT
cana-1859	296	3	at	at	ADP
cana-1859	296	4	560k	560k	NUM
cana-1859	296	5	,	,	PUNCT
cana-1859	296	6	vmcnn	vmcnn	PROPN
cana-1859	296	7	reached	reach	VERB
cana-1859	296	8	a	a	DET
cana-1859	296	9	precision	precision	NOUN
cana-1859	296	10	of	of	ADP
cana-1859	296	11	93.94	93.94	NUM
cana-1859	296	12	%	%	NOUN
cana-1859	296	13	,	,	PUNCT
cana-1859	296	14	whereas	whereas	SCONJ
cana-1859	296	15	the	the	DET
cana-1859	296	16	next	next	ADJ
cana-1859	296	17	best	good	ADJ
cana-1859	296	18	,	,	PUNCT
cana-1859	296	19	fireclassnet	fireclassnet	NOUN
cana-1859	296	20	,	,	PUNCT
cana-1859	296	21	achieved	achieve	VERB
cana-1859	296	22	only	only	ADV
cana-1859	296	23	76.93	76.93	NUM
cana-1859	296	24	%	%	NOUN
cana-1859	296	25	.	.	PUNCT
cana-1859	297	1	the	the	DET
cana-1859	297	2	superior	superior	ADJ
cana-1859	297	3	performance	performance	NOUN
cana-1859	297	4	of	of	ADP
cana-1859	297	5	vmcnn	vmcnn	PROPN
cana-1859	297	6	can	can	AUX
cana-1859	297	7	be	be	AUX
cana-1859	297	8	attributed	attribute	VERB
cana-1859	297	9	to	to	ADP
cana-1859	297	10	its	its	PRON
cana-1859	297	11	integration	integration	NOUN
cana-1859	297	12	of	of	ADP
cana-1859	297	13	vedic	vedic	PROPN
cana-1859	297	14	mathematical	mathematical	ADJ
cana-1859	297	15	sutras	sutra	NOUN
cana-1859	297	16	,	,	PUNCT
cana-1859	297	17	which	which	PRON
cana-1859	297	18	streamline	streamline	VERB
cana-1859	297	19	computational	computational	ADJ
cana-1859	297	20	processes	process	NOUN
cana-1859	297	21	and	and	CCONJ
cana-1859	297	22	enhance	enhance	VERB
cana-1859	297	23	parallel	parallel	ADJ
cana-1859	297	24	processing	processing	NOUN
cana-1859	297	25	capabilities	capability	NOUN
cana-1859	297	26	.	.	PUNCT
cana-1859	298	1	this	this	DET
cana-1859	298	2	results	result	VERB
cana-1859	298	3	in	in	ADP
cana-1859	298	4	a	a	DET
cana-1859	298	5	more	more	ADV
cana-1859	298	6	refined	refined	ADJ
cana-1859	298	7	and	and	CCONJ
cana-1859	298	8	accurate	accurate	ADJ
cana-1859	298	9	categorization	categorization	NOUN
cana-1859	298	10	of	of	ADP
cana-1859	298	11	data	datum	NOUN
cana-1859	298	12	into	into	ADP
cana-1859	298	13	classes	class	NOUN
cana-1859	298	14	,	,	PUNCT
cana-1859	298	15	as	as	SCONJ
cana-1859	298	16	evidenced	evidence	VERB
cana-1859	298	17	by	by	ADP
cana-1859	298	18	the	the	DET
cana-1859	298	19	higher	high	ADJ
cana-1859	298	20	precision	precision	NOUN
cana-1859	298	21	rates	rate	NOUN
cana-1859	298	22	.	.	PUNCT
cana-1859	299	1	for	for	ADP
cana-1859	299	2	example	example	NOUN
cana-1859	299	3	,	,	PUNCT
cana-1859	299	4	at	at	ADP
cana-1859	299	5	1728k	1728k	NOUN
cana-1859	299	6	,	,	PUNCT
cana-1859	299	7	vmcnn	vmcnn	PROPN
cana-1859	299	8	’s	’s	PART
cana-1859	299	9	precision	precision	NOUN
cana-1859	299	10	is	be	AUX
cana-1859	299	11	at	at	ADP
cana-1859	299	12	93.58	93.58	NUM
cana-1859	299	13	%	%	NOUN
cana-1859	299	14	,	,	PUNCT
cana-1859	299	15	far	far	ADV
cana-1859	299	16	surpassing	surpass	VERB
cana-1859	299	17	the	the	DET
cana-1859	299	18	77.01	77.01	NUM
cana-1859	299	19	%	%	NOUN
cana-1859	299	20	of	of	ADP
cana-1859	299	21	fireclassnet	fireclassnet	NOUN
cana-1859	299	22	,	,	PUNCT
cana-1859	299	23	the	the	DET
cana-1859	299	24	next	next	ADJ
cana-1859	299	25	best	good	ADJ
cana-1859	299	26	model	model	NOUN
cana-1859	299	27	.	.	PUNCT
cana-1859	300	1	this	this	DET
cana-1859	300	2	enhanced	enhanced	ADJ
cana-1859	300	3	precision	precision	NOUN
cana-1859	300	4	is	be	AUX
cana-1859	300	5	particularly	particularly	ADV
cana-1859	300	6	impactful	impactful	ADJ
cana-1859	300	7	in	in	ADP
cana-1859	300	8	complex	complex	ADJ
cana-1859	300	9	classification	classification	NOUN
cana-1859	300	10	tasks	task	NOUN
cana-1859	300	11	,	,	PUNCT
cana-1859	300	12	as	as	SCONJ
cana-1859	300	13	it	it	PRON
cana-1859	300	14	implies	imply	VERB
cana-1859	300	15	a	a	DET
cana-1859	300	16	higher	high	ADJ
cana-1859	300	17	rate	rate	NOUN
cana-1859	300	18	of	of	ADP
cana-1859	300	19	correctly	correctly	ADV
cana-1859	300	20	identified	identify	VERB
cana-1859	300	21	classes	class	NOUN
cana-1859	300	22	,	,	PUNCT
cana-1859	300	23	reducing	reduce	VERB
cana-1859	300	24	the	the	DET
cana-1859	300	25	likelihood	likelihood	NOUN
cana-1859	300	26	of	of	ADP
cana-1859	300	27	misclassification	misclassification	NOUN
cana-1859	300	28	.	.	PUNCT
cana-1859	301	1	the	the	DET
cana-1859	301	2	integration	integration	NOUN
cana-1859	301	3	of	of	ADP
cana-1859	301	4	vedic	vedic	ADJ
cana-1859	301	5	mathematics	mathematic	NOUN
cana-1859	301	6	not	not	PART
cana-1859	301	7	only	only	ADV
cana-1859	301	8	enhances	enhance	VERB
cana-1859	301	9	computational	computational	ADJ
cana-1859	301	10	efficiency	efficiency	NOUN
cana-1859	301	11	but	but	CCONJ
cana-1859	301	12	also	also	ADV
cana-1859	301	13	significantly	significantly	ADV
cana-1859	301	14	improves	improve	VERB
cana-1859	301	15	the	the	DET
cana-1859	301	16	accuracy	accuracy	NOUN
cana-1859	301	17	of	of	ADP
cana-1859	301	18	image	image	NOUN
cana-1859	301	19	classification	classification	NOUN
cana-1859	301	20	tasks	task	NOUN
cana-1859	301	21	,	,	PUNCT
cana-1859	301	22	underscoring	underscore	VERB
cana-1859	301	23	the	the	DET
cana-1859	301	24	potential	potential	NOUN
cana-1859	301	25	of	of	ADP
cana-1859	301	26	ancient	ancient	ADJ
cana-1859	301	27	mathematical	mathematical	ADJ
cana-1859	301	28	wisdom	wisdom	NOUN
cana-1859	301	29	in	in	ADP
cana-1859	301	30	modern	modern	ADJ
cana-1859	301	31	ai	ai	PROPN
cana-1859	301	32	applications	application	NOUN
cana-1859	301	33	.	.	PUNCT
cana-1859	302	1	similar	similar	ADJ
cana-1859	302	2	to	to	ADP
cana-1859	302	3	that	that	PRON
cana-1859	302	4	,	,	PUNCT
cana-1859	302	5	accuracy	accuracy	NOUN
cana-1859	302	6	of	of	ADP
cana-1859	302	7	the	the	DET
cana-1859	302	8	models	model	NOUN
cana-1859	302	9	was	be	AUX
cana-1859	302	10	compared	compare	VERB
cana-1859	302	11	in	in	ADP
cana-1859	302	12	figure	figure	NOUN
cana-1859	302	13	3	3	NUM
cana-1859	302	14	as	as	SCONJ
cana-1859	302	15	follows	follow	VERB
cana-1859	302	16	,	,	PUNCT
cana-1859	302	17	60.00	60.00	NUM
cana-1859	302	18	65.00	65.00	NUM
cana-1859	303	1	70.00	70.00	NUM
cana-1859	303	2	75.00	75.00	NUM
cana-1859	303	3	80.00	80.00	NUM
cana-1859	303	4	85.00	85.00	NUM
cana-1859	303	5	90.00	90.00	NUM
cana-1859	303	6	95.00	95.00	NUM
cana-1859	303	7	100.00	100.00	NUM
cana-1859	303	8	9	9	NUM
cana-1859	303	9	6	6	NUM
cana-1859	303	10	k	k	NOUN
cana-1859	303	11	2	2	NUM
cana-1859	303	12	4	4	NUM
cana-1859	303	13	0	0	NUM
cana-1859	303	14	k	k	NOUN
cana-1859	303	15	3	3	NUM
cana-1859	303	16	6	6	NUM
cana-1859	303	17	8	8	NUM
cana-1859	303	18	k	k	NOUN
cana-1859	303	19	5	5	NUM
cana-1859	303	20	0	0	NUM
cana-1859	303	21	4	4	NUM
cana-1859	303	22	k	k	NOUN
cana-1859	303	23	6	6	NUM
cana-1859	303	24	0	0	NUM
cana-1859	303	25	0	0	NUM
cana-1859	304	1	k	k	NOUN
cana-1859	304	2	7	7	NUM
cana-1859	304	3	4	4	NUM
cana-1859	304	4	4	4	NUM
cana-1859	304	5	k	k	NOUN
cana-1859	304	6	8	8	NUM
cana-1859	304	7	7	7	NUM
cana-1859	304	8	2	2	NUM
cana-1859	304	9	k	k	NOUN
cana-1859	304	10	1	1	NUM
cana-1859	304	11	0	0	NUM
cana-1859	304	12	0	0	NUM
cana-1859	304	13	8	8	NUM
cana-1859	304	14	k	k	NOUN
cana-1859	304	15	1	1	NUM
cana-1859	304	16	0	0	NUM
cana-1859	304	17	8	8	NUM
cana-1859	304	18	0	0	NUM
cana-1859	305	1	k	k	NOUN
cana-1859	305	2	1	1	NUM
cana-1859	305	3	2	2	NUM
cana-1859	305	4	2	2	NUM
cana-1859	305	5	4	4	NUM
cana-1859	305	6	k	k	NOUN
cana-1859	305	7	1	1	NUM
cana-1859	305	8	3	3	NUM
cana-1859	305	9	6	6	NUM
cana-1859	305	10	0	0	NUM
cana-1859	305	11	k	k	NOUN
cana-1859	305	12	1	1	NUM
cana-1859	305	13	5	5	NUM
cana-1859	305	14	8	8	NUM
cana-1859	305	15	4	4	NUM
cana-1859	305	16	k	k	NOUN
cana-1859	305	17	cnn	cnn	PROPN
cana-1859	305	18	elm	elm	PROPN
cana-1859	306	1	[	[	X
cana-1859	306	2	6	6	NUM
cana-1859	306	3	]	]	X
cana-1859	306	4	dcnn	dcnn	VERB
cana-1859	306	5	[	[	X
cana-1859	306	6	8	8	NUM
cana-1859	306	7	]	]	PUNCT
cana-1859	306	8	fireclassnet	fireclassnet	NOUN
cana-1859	306	9	[	[	X
cana-1859	306	10	15	15	NUM
cana-1859	306	11	]	]	X
cana-1859	306	12	vmcnn	vmcnn	NOUN
cana-1859	306	13	communications	communication	NOUN
cana-1859	306	14	on	on	ADP
cana-1859	306	15	applied	apply	VERB
cana-1859	306	16	nonlinear	nonlinear	ADJ
cana-1859	306	17	analysis	analysis	NOUN
cana-1859	306	18	issn	issn	NOUN
cana-1859	306	19	:	:	PUNCT
cana-1859	306	20	1074	1074	NUM
cana-1859	306	21	-	-	PUNCT
cana-1859	306	22	133x	133x	NUM
cana-1859	306	23	vol	vol	NOUN
cana-1859	306	24	32	32	NUM
cana-1859	306	25	no	no	NOUN
cana-1859	306	26	.	.	NOUN
cana-1859	306	27	2	2	NUM
cana-1859	306	28	(	(	PUNCT
cana-1859	306	29	2025	2025	NUM
cana-1859	306	30	)	)	PUNCT
cana-1859	306	31	657	657	NUM
cana-1859	306	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	306	33	fig	fig	NOUN
cana-1859	306	34	3	3	NUM
cana-1859	306	35	.	.	PUNCT
cana-1859	306	36	observed	observe	VERB
cana-1859	306	37	accuracy	accuracy	NOUN
cana-1859	306	38	for	for	ADP
cana-1859	306	39	categorizing	categorize	VERB
cana-1859	306	40	multiple	multiple	ADJ
cana-1859	306	41	datasets	dataset	NOUN
cana-1859	306	42	into	into	ADP
cana-1859	306	43	classes	class	NOUN
cana-1859	306	44	in	in	ADP
cana-1859	306	45	examining	examine	VERB
cana-1859	306	46	the	the	DET
cana-1859	306	47	accuracy	accuracy	NOUN
cana-1859	306	48	percentages	percentage	NOUN
cana-1859	306	49	(	(	PUNCT
cana-1859	306	50	a%	a%	VERB
cana-1859	306	51	)	)	PUNCT
cana-1859	306	52	across	across	ADP
cana-1859	306	53	various	various	ADJ
cana-1859	306	54	dataset	dataset	NOUN
cana-1859	306	55	sizes	size	NOUN
cana-1859	306	56	(	(	PUNCT
cana-1859	306	57	from	from	ADP
cana-1859	306	58	96k	96k	NOUN
cana-1859	306	59	to	to	ADP
cana-1859	306	60	1728k	1728k	NUM
cana-1859	306	61	)	)	PUNCT
cana-1859	306	62	,	,	PUNCT
cana-1859	306	63	it	it	PRON
cana-1859	306	64	is	be	AUX
cana-1859	306	65	evident	evident	ADJ
cana-1859	306	66	that	that	SCONJ
cana-1859	306	67	vmcnn	vmcnn	PROPN
cana-1859	306	68	consistently	consistently	ADV
cana-1859	306	69	maintains	maintain	VERB
cana-1859	306	70	a	a	DET
cana-1859	306	71	higher	high	ADJ
cana-1859	306	72	accuracy	accuracy	NOUN
cana-1859	306	73	rate	rate	NOUN
cana-1859	306	74	.	.	PUNCT
cana-1859	307	1	for	for	ADP
cana-1859	307	2	example	example	NOUN
cana-1859	307	3	,	,	PUNCT
cana-1859	307	4	at	at	ADP
cana-1859	307	5	a	a	DET
cana-1859	307	6	dataset	dataset	ADJ
cana-1859	307	7	size	size	NOUN
cana-1859	307	8	of	of	ADP
cana-1859	307	9	368k	368k	NOUN
cana-1859	307	10	,	,	PUNCT
cana-1859	307	11	vmcnn	vmcnn	PROPN
cana-1859	307	12	achieved	achieve	VERB
cana-1859	307	13	an	an	DET
cana-1859	307	14	accuracy	accuracy	NOUN
cana-1859	307	15	of	of	ADP
cana-1859	307	16	91.12	91.12	NUM
cana-1859	307	17	%	%	NOUN
cana-1859	307	18	,	,	PUNCT
cana-1859	307	19	substantially	substantially	ADV
cana-1859	307	20	surpassing	surpass	VERB
cana-1859	307	21	cnn	cnn	PROPN
cana-1859	307	22	elm	elm	PROPN
cana-1859	307	23	's	's	PART
cana-1859	307	24	86.01	86.01	NUM
cana-1859	307	25	%	%	NOUN
cana-1859	307	26	,	,	PUNCT
cana-1859	307	27	the	the	DET
cana-1859	307	28	second	second	ADV
cana-1859	307	29	-	-	PUNCT
cana-1859	307	30	highest	high	ADJ
cana-1859	307	31	in	in	ADP
cana-1859	307	32	this	this	DET
cana-1859	307	33	instance	instance	NOUN
cana-1859	307	34	.	.	PUNCT
cana-1859	308	1	this	this	DET
cana-1859	308	2	trend	trend	NOUN
cana-1859	308	3	of	of	ADP
cana-1859	308	4	vmcnn	vmcnn	NOUN
cana-1859	308	5	's	's	PART
cana-1859	308	6	dominance	dominance	NOUN
cana-1859	308	7	in	in	ADP
cana-1859	308	8	accuracy	accuracy	NOUN
cana-1859	308	9	is	be	AUX
cana-1859	308	10	a	a	DET
cana-1859	308	11	recurring	recur	VERB
cana-1859	308	12	theme	theme	NOUN
cana-1859	308	13	across	across	ADP
cana-1859	308	14	all	all	DET
cana-1859	308	15	dataset	dataset	ADJ
cana-1859	308	16	sizes	size	NOUN
cana-1859	308	17	.	.	PUNCT
cana-1859	309	1	notably	notably	ADV
cana-1859	309	2	,	,	PUNCT
cana-1859	309	3	at	at	ADP
cana-1859	309	4	1224k	1224k	NUM
cana-1859	309	5	,	,	PUNCT
cana-1859	309	6	vmcnn	vmcnn	PROPN
cana-1859	309	7	reached	reach	VERB
cana-1859	309	8	an	an	DET
cana-1859	309	9	impressive	impressive	ADJ
cana-1859	309	10	accuracy	accuracy	NOUN
cana-1859	309	11	of	of	ADP
cana-1859	309	12	94.34	94.34	NUM
cana-1859	309	13	%	%	NOUN
cana-1859	309	14	,	,	PUNCT
cana-1859	309	15	while	while	SCONJ
cana-1859	309	16	the	the	DET
cana-1859	309	17	next	next	ADJ
cana-1859	309	18	best	good	ADJ
cana-1859	309	19	,	,	PUNCT
cana-1859	309	20	fireclassnet	fireclassnet	NOUN
cana-1859	309	21	,	,	PUNCT
cana-1859	309	22	scored	score	VERB
cana-1859	309	23	85.10	85.10	NUM
cana-1859	309	24	%	%	NOUN
cana-1859	309	25	.	.	PUNCT
cana-1859	310	1	the	the	DET
cana-1859	310	2	enhanced	enhanced	ADJ
cana-1859	310	3	accuracy	accuracy	NOUN
cana-1859	310	4	of	of	ADP
cana-1859	310	5	vmcnn	vmcnn	PROPN
cana-1859	310	6	is	be	AUX
cana-1859	310	7	a	a	DET
cana-1859	310	8	direct	direct	ADJ
cana-1859	310	9	consequence	consequence	NOUN
cana-1859	310	10	of	of	ADP
cana-1859	310	11	the	the	DET
cana-1859	310	12	effective	effective	ADJ
cana-1859	310	13	integration	integration	NOUN
cana-1859	310	14	of	of	ADP
cana-1859	310	15	vedic	vedic	ADJ
cana-1859	310	16	mathematical	mathematical	ADJ
cana-1859	310	17	principles	principle	NOUN
cana-1859	310	18	,	,	PUNCT
cana-1859	310	19	which	which	PRON
cana-1859	310	20	optimize	optimize	VERB
cana-1859	310	21	the	the	DET
cana-1859	310	22	internal	internal	ADJ
cana-1859	310	23	operations	operation	NOUN
cana-1859	310	24	of	of	ADP
cana-1859	310	25	cnns	cnns	PROPN
cana-1859	310	26	.	.	PUNCT
cana-1859	311	1	this	this	DET
cana-1859	311	2	optimization	optimization	NOUN
cana-1859	311	3	leads	lead	VERB
cana-1859	311	4	to	to	ADP
cana-1859	311	5	more	more	ADV
cana-1859	311	6	precise	precise	ADJ
cana-1859	311	7	image	image	NOUN
cana-1859	311	8	classification	classification	NOUN
cana-1859	311	9	,	,	PUNCT
cana-1859	311	10	as	as	SCONJ
cana-1859	311	11	demonstrated	demonstrate	VERB
cana-1859	311	12	by	by	ADP
cana-1859	311	13	the	the	DET
cana-1859	311	14	consistently	consistently	ADV
cana-1859	311	15	higher	high	ADJ
cana-1859	311	16	accuracy	accuracy	NOUN
cana-1859	311	17	rates	rate	NOUN
cana-1859	311	18	of	of	ADP
cana-1859	311	19	vmcnn	vmcnn	PROPN
cana-1859	311	20	.	.	PUNCT
cana-1859	312	1	for	for	ADP
cana-1859	312	2	instance	instance	NOUN
cana-1859	312	3	,	,	PUNCT
cana-1859	312	4	at	at	ADP
cana-1859	312	5	the	the	DET
cana-1859	312	6	largest	large	ADJ
cana-1859	312	7	dataset	dataset	ADJ
cana-1859	312	8	size	size	NOUN
cana-1859	312	9	of	of	ADP
cana-1859	312	10	1728k	1728k	NUM
cana-1859	312	11	,	,	PUNCT
cana-1859	312	12	vmcnn	vmcnn	PROPN
cana-1859	312	13	boasts	boast	VERB
cana-1859	312	14	an	an	DET
cana-1859	312	15	accuracy	accuracy	NOUN
cana-1859	312	16	of	of	ADP
cana-1859	312	17	95.08	95.08	NUM
cana-1859	312	18	%	%	NOUN
cana-1859	312	19	,	,	PUNCT
cana-1859	312	20	significantly	significantly	ADV
cana-1859	312	21	higher	high	ADJ
cana-1859	312	22	than	than	ADP
cana-1859	312	23	dcnn	dcnn	PROPN
cana-1859	312	24	's	's	PART
cana-1859	312	25	77.33	77.33	NUM
cana-1859	312	26	%	%	NOUN
cana-1859	312	27	.	.	PUNCT
cana-1859	313	1	this	this	DET
cana-1859	313	2	high	high	ADJ
cana-1859	313	3	level	level	NOUN
cana-1859	313	4	of	of	ADP
cana-1859	313	5	accuracy	accuracy	NOUN
cana-1859	313	6	is	be	AUX
cana-1859	313	7	crucial	crucial	ADJ
cana-1859	313	8	in	in	ADP
cana-1859	313	9	applications	application	NOUN
cana-1859	313	10	where	where	SCONJ
cana-1859	313	11	correct	correct	ADJ
cana-1859	313	12	classification	classification	NOUN
cana-1859	313	13	is	be	AUX
cana-1859	313	14	paramount	paramount	ADJ
cana-1859	313	15	,	,	PUNCT
cana-1859	313	16	such	such	ADJ
cana-1859	313	17	as	as	ADP
cana-1859	313	18	in	in	ADP
cana-1859	313	19	medical	medical	ADJ
cana-1859	313	20	imaging	imaging	NOUN
cana-1859	313	21	or	or	CCONJ
cana-1859	313	22	autonomous	autonomous	ADJ
cana-1859	313	23	vehicle	vehicle	NOUN
cana-1859	313	24	navigation	navigation	NOUN
cana-1859	313	25	,	,	PUNCT
cana-1859	313	26	where	where	SCONJ
cana-1859	313	27	even	even	ADV
cana-1859	313	28	a	a	DET
cana-1859	313	29	small	small	ADJ
cana-1859	313	30	margin	margin	NOUN
cana-1859	313	31	of	of	ADP
cana-1859	313	32	error	error	NOUN
cana-1859	313	33	can	can	AUX
cana-1859	313	34	have	have	VERB
cana-1859	313	35	significant	significant	ADJ
cana-1859	313	36	consequences	consequence	NOUN
cana-1859	313	37	.	.	PUNCT
cana-1859	314	1	the	the	DET
cana-1859	314	2	impact	impact	NOUN
cana-1859	314	3	of	of	ADP
cana-1859	314	4	this	this	DET
cana-1859	314	5	enhanced	enhance	VERB
cana-1859	314	6	accuracy	accuracy	NOUN
cana-1859	314	7	is	be	AUX
cana-1859	314	8	far	far	ADV
cana-1859	314	9	-	-	PUNCT
cana-1859	314	10	reaching	reach	VERB
cana-1859	314	11	.	.	PUNCT
cana-1859	315	1	in	in	ADP
cana-1859	315	2	medical	medical	ADJ
cana-1859	315	3	imaging	imaging	NOUN
cana-1859	315	4	,	,	PUNCT
cana-1859	315	5	for	for	ADP
cana-1859	315	6	example	example	NOUN
cana-1859	315	7	,	,	PUNCT
cana-1859	315	8	the	the	DET
cana-1859	315	9	improved	improved	ADJ
cana-1859	315	10	accuracy	accuracy	NOUN
cana-1859	315	11	of	of	ADP
cana-1859	315	12	vmcnn	vmcnn	NOUN
cana-1859	315	13	could	could	AUX
cana-1859	315	14	lead	lead	VERB
cana-1859	315	15	to	to	ADP
cana-1859	315	16	more	more	ADV
cana-1859	315	17	reliable	reliable	ADJ
cana-1859	315	18	diagnoses	diagnosis	NOUN
cana-1859	315	19	and	and	CCONJ
cana-1859	315	20	treatment	treatment	NOUN
cana-1859	315	21	plans	plan	NOUN
cana-1859	315	22	.	.	PUNCT
cana-1859	316	1	in	in	ADP
cana-1859	316	2	the	the	DET
cana-1859	316	3	realm	realm	NOUN
cana-1859	316	4	of	of	ADP
cana-1859	316	5	autonomous	autonomous	ADJ
cana-1859	316	6	vehicles	vehicle	NOUN
cana-1859	316	7	,	,	PUNCT
cana-1859	316	8	the	the	DET
cana-1859	316	9	high	high	ADJ
cana-1859	316	10	accuracy	accuracy	NOUN
cana-1859	316	11	in	in	ADP
cana-1859	316	12	classifying	classify	VERB
cana-1859	316	13	images	image	NOUN
cana-1859	316	14	ensures	ensure	VERB
cana-1859	316	15	safer	safe	ADJ
cana-1859	316	16	navigation	navigation	NOUN
cana-1859	316	17	and	and	CCONJ
cana-1859	316	18	decisionmaking	decisionmaking	NOUN
cana-1859	316	19	.	.	PUNCT
cana-1859	317	1	overall	overall	ADV
cana-1859	317	2	,	,	PUNCT
cana-1859	317	3	the	the	DET
cana-1859	317	4	integration	integration	NOUN
cana-1859	317	5	of	of	ADP
cana-1859	317	6	vedic	vedic	ADJ
cana-1859	317	7	mathematics	mathematics	PROPN
cana-1859	317	8	into	into	ADP
cana-1859	317	9	cnn	cnn	PROPN
cana-1859	317	10	optimization	optimization	NOUN
cana-1859	317	11	not	not	PART
cana-1859	317	12	only	only	ADV
cana-1859	317	13	marks	mark	VERB
cana-1859	317	14	a	a	DET
cana-1859	317	15	significant	significant	ADJ
cana-1859	317	16	advancement	advancement	NOUN
cana-1859	317	17	in	in	ADP
cana-1859	317	18	computational	computational	ADJ
cana-1859	317	19	efficiency	efficiency	NOUN
cana-1859	317	20	but	but	CCONJ
cana-1859	317	21	also	also	ADV
cana-1859	317	22	has	have	VERB
cana-1859	317	23	profound	profound	ADJ
cana-1859	317	24	implications	implication	NOUN
cana-1859	317	25	for	for	ADP
cana-1859	317	26	the	the	DET
cana-1859	317	27	accuracy	accuracy	NOUN
cana-1859	317	28	and	and	CCONJ
cana-1859	317	29	reliability	reliability	NOUN
cana-1859	317	30	of	of	ADP
cana-1859	317	31	image	image	NOUN
cana-1859	317	32	classification	classification	NOUN
cana-1859	317	33	in	in	ADP
cana-1859	317	34	various	various	ADJ
cana-1859	317	35	high	high	ADJ
cana-1859	317	36	-	-	PUNCT
cana-1859	317	37	stakes	stake	NOUN
cana-1859	317	38	applications	application	NOUN
cana-1859	317	39	.	.	PUNCT
cana-1859	318	1	similar	similar	ADJ
cana-1859	318	2	to	to	ADP
cana-1859	318	3	this	this	PRON
cana-1859	318	4	,	,	PUNCT
cana-1859	318	5	the	the	DET
cana-1859	318	6	recall	recall	NOUN
cana-1859	318	7	levels	level	NOUN
cana-1859	318	8	are	be	AUX
cana-1859	318	9	represented	represent	VERB
cana-1859	318	10	in	in	ADP
cana-1859	318	11	figure	figure	NOUN
cana-1859	318	12	4	4	NUM
cana-1859	318	13	as	as	SCONJ
cana-1859	318	14	follows	follow	VERB
cana-1859	318	15	,	,	PUNCT
cana-1859	318	16	60.00	60.00	NUM
cana-1859	318	17	65.00	65.00	NUM
cana-1859	319	1	70.00	70.00	NUM
cana-1859	319	2	75.00	75.00	NUM
cana-1859	319	3	80.00	80.00	NUM
cana-1859	319	4	85.00	85.00	NUM
cana-1859	319	5	90.00	90.00	NUM
cana-1859	319	6	95.00	95.00	NUM
cana-1859	319	7	100.00	100.00	NUM
cana-1859	319	8	cnn	cnn	NOUN
cana-1859	319	9	elm	elm	PROPN
cana-1859	320	1	[	[	X
cana-1859	320	2	6	6	NUM
cana-1859	320	3	]	]	X
cana-1859	320	4	dcnn	dcnn	VERB
cana-1859	320	5	[	[	X
cana-1859	320	6	8	8	NUM
cana-1859	320	7	]	]	PUNCT
cana-1859	320	8	fireclassnet	fireclassnet	NOUN
cana-1859	320	9	[	[	X
cana-1859	320	10	15	15	NUM
cana-1859	320	11	]	]	X
cana-1859	320	12	vmcnn	vmcnn	NOUN
cana-1859	320	13	communications	communication	NOUN
cana-1859	320	14	on	on	ADP
cana-1859	320	15	applied	apply	VERB
cana-1859	320	16	nonlinear	nonlinear	ADJ
cana-1859	320	17	analysis	analysis	NOUN
cana-1859	320	18	issn	issn	NOUN
cana-1859	320	19	:	:	PUNCT
cana-1859	320	20	1074	1074	NUM
cana-1859	320	21	-	-	PUNCT
cana-1859	320	22	133x	133x	NUM
cana-1859	320	23	vol	vol	NOUN
cana-1859	320	24	32	32	NUM
cana-1859	320	25	no	no	NOUN
cana-1859	320	26	.	.	NOUN
cana-1859	320	27	2	2	NUM
cana-1859	320	28	(	(	PUNCT
cana-1859	320	29	2025	2025	NUM
cana-1859	320	30	)	)	PUNCT
cana-1859	320	31	658	658	NUM
cana-1859	320	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	320	33	fig	fig	NOUN
cana-1859	320	34	4	4	NUM
cana-1859	320	35	.	.	PUNCT
cana-1859	320	36	observed	observe	VERB
cana-1859	320	37	recall	recall	NOUN
cana-1859	320	38	for	for	ADP
cana-1859	320	39	categorizing	categorize	VERB
cana-1859	320	40	multiple	multiple	ADJ
cana-1859	320	41	datasets	dataset	NOUN
cana-1859	320	42	into	into	ADP
cana-1859	320	43	classes	class	NOUN
cana-1859	320	44	looking	look	VERB
cana-1859	320	45	at	at	ADP
cana-1859	320	46	the	the	DET
cana-1859	320	47	recall	recall	NOUN
cana-1859	320	48	percentages	percentage	NOUN
cana-1859	320	49	(	(	PUNCT
cana-1859	320	50	r%	r%	NOUN
cana-1859	320	51	)	)	PUNCT
cana-1859	320	52	across	across	ADP
cana-1859	320	53	various	various	ADJ
cana-1859	320	54	dataset	dataset	NOUN
cana-1859	320	55	sizes	size	NOUN
cana-1859	320	56	,	,	PUNCT
cana-1859	320	57	vmcnn	vmcnn	PROPN
cana-1859	320	58	consistently	consistently	ADV
cana-1859	320	59	demonstrates	demonstrate	VERB
cana-1859	320	60	superior	superior	ADJ
cana-1859	320	61	recall	recall	NOUN
cana-1859	320	62	rates	rate	NOUN
cana-1859	320	63	.	.	PUNCT
cana-1859	321	1	for	for	ADP
cana-1859	321	2	instance	instance	NOUN
cana-1859	321	3	,	,	PUNCT
cana-1859	321	4	at	at	ADP
cana-1859	321	5	a	a	DET
cana-1859	321	6	dataset	dataset	ADJ
cana-1859	321	7	size	size	NOUN
cana-1859	321	8	of	of	ADP
cana-1859	321	9	96k	96k	NOUN
cana-1859	321	10	,	,	PUNCT
cana-1859	321	11	vmcnn	vmcnn	PROPN
cana-1859	321	12	achieved	achieve	VERB
cana-1859	321	13	a	a	DET
cana-1859	321	14	recall	recall	NOUN
cana-1859	321	15	of	of	ADP
cana-1859	321	16	94.64	94.64	NUM
cana-1859	321	17	%	%	NOUN
cana-1859	321	18	,	,	PUNCT
cana-1859	321	19	significantly	significantly	ADV
cana-1859	321	20	outperforming	outperform	VERB
cana-1859	321	21	the	the	DET
cana-1859	321	22	nearest	near	ADJ
cana-1859	321	23	competitor	competitor	NOUN
cana-1859	321	24	,	,	PUNCT
cana-1859	321	25	cnn	cnn	PROPN
cana-1859	321	26	elm	elm	PROPN
cana-1859	321	27	,	,	PUNCT
cana-1859	321	28	which	which	PRON
cana-1859	321	29	had	have	VERB
cana-1859	321	30	a	a	DET
cana-1859	321	31	recall	recall	NOUN
cana-1859	321	32	of	of	ADP
cana-1859	321	33	87.80	87.80	NUM
cana-1859	321	34	%	%	NOUN
cana-1859	321	35	.	.	PUNCT
cana-1859	322	1	this	this	DET
cana-1859	322	2	pattern	pattern	NOUN
cana-1859	322	3	of	of	ADP
cana-1859	322	4	vmcnn	vmcnn	NOUN
cana-1859	322	5	's	's	PART
cana-1859	322	6	higher	high	ADJ
cana-1859	322	7	recall	recall	NOUN
cana-1859	322	8	is	be	AUX
cana-1859	322	9	consistent	consistent	ADJ
cana-1859	322	10	across	across	ADP
cana-1859	322	11	all	all	DET
cana-1859	322	12	dataset	dataset	ADJ
cana-1859	322	13	sizes	size	NOUN
cana-1859	322	14	.	.	PUNCT
cana-1859	323	1	at	at	ADP
cana-1859	323	2	560k	560k	NUM
cana-1859	323	3	,	,	PUNCT
cana-1859	323	4	for	for	ADP
cana-1859	323	5	example	example	NOUN
cana-1859	323	6	,	,	PUNCT
cana-1859	323	7	vmcnn	vmcnn	PROPN
cana-1859	323	8	attained	attain	VERB
cana-1859	323	9	a	a	DET
cana-1859	323	10	recall	recall	NOUN
cana-1859	323	11	of	of	ADP
cana-1859	323	12	93.64	93.64	NUM
cana-1859	323	13	%	%	NOUN
cana-1859	323	14	,	,	PUNCT
cana-1859	323	15	whereas	whereas	SCONJ
cana-1859	323	16	fireclassnet	fireclassnet	NOUN
cana-1859	323	17	,	,	PUNCT
cana-1859	323	18	the	the	DET
cana-1859	323	19	next	next	ADJ
cana-1859	323	20	best	good	ADJ
cana-1859	323	21	in	in	ADP
cana-1859	323	22	this	this	DET
cana-1859	323	23	category	category	NOUN
cana-1859	323	24	,	,	PUNCT
cana-1859	323	25	achieved	achieve	VERB
cana-1859	323	26	85.55	85.55	NUM
cana-1859	323	27	%	%	NOUN
cana-1859	323	28	.	.	PUNCT
cana-1859	324	1	the	the	DET
cana-1859	324	2	high	high	ADJ
cana-1859	324	3	recall	recall	NOUN
cana-1859	324	4	rate	rate	NOUN
cana-1859	324	5	of	of	ADP
cana-1859	324	6	vmcnn	vmcnn	PROPN
cana-1859	324	7	can	can	AUX
cana-1859	324	8	be	be	AUX
cana-1859	324	9	attributed	attribute	VERB
cana-1859	324	10	to	to	ADP
cana-1859	324	11	its	its	PRON
cana-1859	324	12	integration	integration	NOUN
cana-1859	324	13	of	of	ADP
cana-1859	324	14	vedic	vedic	PROPN
cana-1859	324	15	mathematical	mathematical	ADJ
cana-1859	324	16	sutras	sutra	NOUN
cana-1859	324	17	,	,	PUNCT
cana-1859	324	18	which	which	PRON
cana-1859	324	19	optimize	optimize	VERB
cana-1859	324	20	the	the	DET
cana-1859	324	21	efficiency	efficiency	NOUN
cana-1859	324	22	of	of	ADP
cana-1859	324	23	the	the	DET
cana-1859	324	24	convolutional	convolutional	ADJ
cana-1859	324	25	neural	neural	ADJ
cana-1859	324	26	network	network	NOUN
cana-1859	324	27	.	.	PUNCT
cana-1859	325	1	a	a	DET
cana-1859	325	2	higher	high	ADJ
cana-1859	325	3	recall	recall	NOUN
cana-1859	325	4	rate	rate	NOUN
cana-1859	325	5	means	mean	VERB
cana-1859	325	6	that	that	SCONJ
cana-1859	325	7	vmcnn	vmcnn	NOUN
cana-1859	325	8	is	be	AUX
cana-1859	325	9	more	more	ADV
cana-1859	325	10	capable	capable	ADJ
cana-1859	325	11	of	of	ADP
cana-1859	325	12	correctly	correctly	ADV
cana-1859	325	13	identifying	identify	VERB
cana-1859	325	14	relevant	relevant	ADJ
cana-1859	325	15	instances	instance	NOUN
cana-1859	325	16	across	across	ADP
cana-1859	325	17	the	the	DET
cana-1859	325	18	datasets	dataset	NOUN
cana-1859	325	19	.	.	PUNCT
cana-1859	326	1	for	for	ADP
cana-1859	326	2	example	example	NOUN
cana-1859	326	3	,	,	PUNCT
cana-1859	326	4	at	at	ADP
cana-1859	326	5	the	the	DET
cana-1859	326	6	1728k	1728k	NUM
cana-1859	326	7	dataset	dataset	NOUN
cana-1859	326	8	size	size	NOUN
cana-1859	326	9	,	,	PUNCT
cana-1859	326	10	vmcnn	vmcnn	PROPN
cana-1859	326	11	's	's	PART
cana-1859	326	12	recall	recall	NOUN
cana-1859	326	13	rate	rate	NOUN
cana-1859	326	14	is	be	AUX
cana-1859	326	15	92.82	92.82	NUM
cana-1859	326	16	%	%	NOUN
cana-1859	326	17	,	,	PUNCT
cana-1859	326	18	considerably	considerably	ADV
cana-1859	326	19	higher	high	ADJ
cana-1859	326	20	than	than	ADP
cana-1859	326	21	dcnn	dcnn	PROPN
cana-1859	326	22	's	's	PART
cana-1859	326	23	72.28	72.28	NUM
cana-1859	326	24	%	%	NOUN
cana-1859	326	25	.	.	PUNCT
cana-1859	327	1	the	the	DET
cana-1859	327	2	impact	impact	NOUN
cana-1859	327	3	of	of	ADP
cana-1859	327	4	such	such	ADJ
cana-1859	327	5	high	high	ADJ
cana-1859	327	6	recall	recall	NOUN
cana-1859	327	7	rates	rate	NOUN
cana-1859	327	8	is	be	AUX
cana-1859	327	9	significant	significant	ADJ
cana-1859	327	10	,	,	PUNCT
cana-1859	327	11	especially	especially	ADV
cana-1859	327	12	in	in	ADP
cana-1859	327	13	fields	field	NOUN
cana-1859	327	14	where	where	SCONJ
cana-1859	327	15	missing	miss	VERB
cana-1859	327	16	a	a	DET
cana-1859	327	17	relevant	relevant	ADJ
cana-1859	327	18	instance	instance	NOUN
cana-1859	327	19	can	can	AUX
cana-1859	327	20	have	have	AUX
cana-1859	327	21	serious	serious	ADJ
cana-1859	327	22	implications	implication	NOUN
cana-1859	327	23	,	,	PUNCT
cana-1859	327	24	such	such	ADJ
cana-1859	327	25	as	as	ADP
cana-1859	327	26	in	in	ADP
cana-1859	327	27	medical	medical	ADJ
cana-1859	327	28	diagnostics	diagnostic	NOUN
cana-1859	327	29	or	or	CCONJ
cana-1859	327	30	surveillance	surveillance	NOUN
cana-1859	327	31	systems	system	NOUN
cana-1859	327	32	.	.	PUNCT
cana-1859	328	1	in	in	ADP
cana-1859	328	2	medical	medical	ADJ
cana-1859	328	3	imaging	imaging	NOUN
cana-1859	328	4	,	,	PUNCT
cana-1859	328	5	for	for	ADP
cana-1859	328	6	instance	instance	NOUN
cana-1859	328	7	,	,	PUNCT
cana-1859	328	8	a	a	DET
cana-1859	328	9	higher	high	ADJ
cana-1859	328	10	recall	recall	NOUN
cana-1859	328	11	rate	rate	NOUN
cana-1859	328	12	means	mean	VERB
cana-1859	328	13	fewer	few	ADJ
cana-1859	328	14	false	false	ADJ
cana-1859	328	15	negatives	negative	NOUN
cana-1859	328	16	,	,	PUNCT
cana-1859	328	17	which	which	PRON
cana-1859	328	18	is	be	AUX
cana-1859	328	19	crucial	crucial	ADJ
cana-1859	328	20	for	for	ADP
cana-1859	328	21	early	early	ADJ
cana-1859	328	22	disease	disease	NOUN
cana-1859	328	23	detection	detection	NOUN
cana-1859	328	24	and	and	CCONJ
cana-1859	328	25	treatment	treatment	NOUN
cana-1859	328	26	.	.	PUNCT
cana-1859	329	1	in	in	ADP
cana-1859	329	2	surveillance	surveillance	NOUN
cana-1859	329	3	,	,	PUNCT
cana-1859	329	4	it	it	PRON
cana-1859	329	5	improves	improve	VERB
cana-1859	329	6	the	the	DET
cana-1859	329	7	system	system	NOUN
cana-1859	329	8	's	's	PART
cana-1859	329	9	ability	ability	NOUN
cana-1859	329	10	to	to	PART
cana-1859	329	11	correctly	correctly	ADV
cana-1859	329	12	identify	identify	VERB
cana-1859	329	13	important	important	ADJ
cana-1859	329	14	or	or	CCONJ
cana-1859	329	15	suspicious	suspicious	ADJ
cana-1859	329	16	activities	activity	NOUN
cana-1859	329	17	,	,	PUNCT
cana-1859	329	18	enhancing	enhance	VERB
cana-1859	329	19	security	security	NOUN
cana-1859	329	20	measures	measure	NOUN
cana-1859	329	21	.	.	PUNCT
cana-1859	330	1	therefore	therefore	ADV
cana-1859	330	2	,	,	PUNCT
cana-1859	330	3	the	the	DET
cana-1859	330	4	ability	ability	NOUN
cana-1859	330	5	of	of	ADP
cana-1859	330	6	vmcnn	vmcnn	NOUN
cana-1859	330	7	to	to	PART
cana-1859	330	8	achieve	achieve	VERB
cana-1859	330	9	high	high	ADJ
cana-1859	330	10	recall	recall	NOUN
cana-1859	330	11	rates	rate	NOUN
cana-1859	330	12	not	not	PART
cana-1859	330	13	only	only	ADV
cana-1859	330	14	indicates	indicate	VERB
cana-1859	330	15	its	its	PRON
cana-1859	330	16	efficiency	efficiency	NOUN
cana-1859	330	17	in	in	ADP
cana-1859	330	18	image	image	NOUN
cana-1859	330	19	classification	classification	NOUN
cana-1859	330	20	but	but	CCONJ
cana-1859	330	21	also	also	ADV
cana-1859	330	22	represents	represent	VERB
cana-1859	330	23	a	a	DET
cana-1859	330	24	substantial	substantial	ADJ
cana-1859	330	25	advancement	advancement	NOUN
cana-1859	330	26	in	in	ADP
cana-1859	330	27	applications	application	NOUN
cana-1859	330	28	where	where	SCONJ
cana-1859	330	29	the	the	DET
cana-1859	330	30	cost	cost	NOUN
cana-1859	330	31	of	of	ADP
cana-1859	330	32	missing	miss	VERB
cana-1859	330	33	a	a	DET
cana-1859	330	34	true	true	ADJ
cana-1859	330	35	positive	positive	ADJ
cana-1859	330	36	is	be	AUX
cana-1859	330	37	high	high	ADJ
cana-1859	330	38	.	.	PUNCT
cana-1859	331	1	the	the	DET
cana-1859	331	2	integration	integration	NOUN
cana-1859	331	3	of	of	ADP
cana-1859	331	4	ancient	ancient	ADJ
cana-1859	331	5	vedic	vedic	ADJ
cana-1859	331	6	mathematics	mathematic	NOUN
cana-1859	331	7	with	with	ADP
cana-1859	331	8	modern	modern	ADJ
cana-1859	331	9	ai	ai	NOUN
cana-1859	331	10	techniques	technique	NOUN
cana-1859	331	11	in	in	ADP
cana-1859	331	12	vmcnn	vmcnn	NOUN
cana-1859	331	13	thus	thus	ADV
cana-1859	331	14	not	not	PART
cana-1859	331	15	only	only	ADV
cana-1859	331	16	boosts	boost	VERB
cana-1859	331	17	computational	computational	ADJ
cana-1859	331	18	efficiency	efficiency	NOUN
cana-1859	331	19	but	but	CCONJ
cana-1859	331	20	also	also	ADV
cana-1859	331	21	significantly	significantly	ADV
cana-1859	331	22	enhances	enhance	VERB
cana-1859	331	23	the	the	DET
cana-1859	331	24	reliability	reliability	NOUN
cana-1859	331	25	and	and	CCONJ
cana-1859	331	26	applicability	applicability	NOUN
cana-1859	331	27	of	of	ADP
cana-1859	331	28	image	image	NOUN
cana-1859	331	29	classification	classification	NOUN
cana-1859	331	30	in	in	ADP
cana-1859	331	31	various	various	ADJ
cana-1859	331	32	critical	critical	ADJ
cana-1859	331	33	domains	domain	NOUN
cana-1859	331	34	.	.	PUNCT
cana-1859	332	1	figure	figure	NOUN
cana-1859	332	2	5	5	NUM
cana-1859	332	3	similarly	similarly	ADV
cana-1859	332	4	tabulates	tabulate	VERB
cana-1859	332	5	the	the	DET
cana-1859	332	6	delay	delay	NOUN
cana-1859	332	7	needed	need	VERB
cana-1859	332	8	for	for	ADP
cana-1859	332	9	the	the	DET
cana-1859	332	10	prediction	prediction	NOUN
cana-1859	332	11	process	process	NOUN
cana-1859	332	12	,	,	PUNCT
cana-1859	332	13	60.00	60.00	NUM
cana-1859	332	14	65.00	65.00	NUM
cana-1859	332	15	70.00	70.00	NUM
cana-1859	332	16	75.00	75.00	NUM
cana-1859	332	17	80.00	80.00	NUM
cana-1859	332	18	85.00	85.00	NUM
cana-1859	332	19	90.00	90.00	NUM
cana-1859	332	20	95.00	95.00	NUM
cana-1859	332	21	100.00	100.00	NUM
cana-1859	332	22	9	9	NUM
cana-1859	332	23	6	6	NUM
cana-1859	332	24	k	k	NOUN
cana-1859	332	25	2	2	NUM
cana-1859	332	26	4	4	NUM
cana-1859	332	27	0	0	NUM
cana-1859	332	28	k	k	NOUN
cana-1859	332	29	3	3	NUM
cana-1859	332	30	6	6	NUM
cana-1859	332	31	8	8	NUM
cana-1859	332	32	k	k	NOUN
cana-1859	332	33	5	5	NUM
cana-1859	332	34	0	0	NUM
cana-1859	332	35	4	4	NUM
cana-1859	332	36	k	k	NOUN
cana-1859	332	37	6	6	NUM
cana-1859	332	38	0	0	NUM
cana-1859	332	39	0	0	NUM
cana-1859	333	1	k	k	NOUN
cana-1859	333	2	7	7	NUM
cana-1859	333	3	4	4	NUM
cana-1859	333	4	4	4	NUM
cana-1859	333	5	k	k	NOUN
cana-1859	333	6	8	8	NUM
cana-1859	333	7	7	7	NUM
cana-1859	333	8	2	2	NUM
cana-1859	333	9	k	k	NOUN
cana-1859	333	10	1	1	NUM
cana-1859	333	11	0	0	NUM
cana-1859	333	12	0	0	NUM
cana-1859	333	13	8	8	NUM
cana-1859	333	14	k	k	NOUN
cana-1859	333	15	1	1	NUM
cana-1859	333	16	0	0	NUM
cana-1859	333	17	8	8	NUM
cana-1859	333	18	0	0	NUM
cana-1859	334	1	k	k	NOUN
cana-1859	334	2	1	1	NUM
cana-1859	334	3	2	2	NUM
cana-1859	334	4	2	2	NUM
cana-1859	334	5	4	4	NUM
cana-1859	334	6	k	k	NOUN
cana-1859	334	7	1	1	NUM
cana-1859	334	8	3	3	NUM
cana-1859	334	9	6	6	NUM
cana-1859	334	10	0	0	NUM
cana-1859	334	11	k	k	NOUN
cana-1859	334	12	1	1	NUM
cana-1859	334	13	5	5	NUM
cana-1859	334	14	8	8	NUM
cana-1859	334	15	4	4	NUM
cana-1859	334	16	k	k	NOUN
cana-1859	334	17	cnn	cnn	PROPN
cana-1859	334	18	elm	elm	PROPN
cana-1859	335	1	[	[	X
cana-1859	335	2	6	6	NUM
cana-1859	335	3	]	]	X
cana-1859	335	4	dcnn	dcnn	VERB
cana-1859	335	5	[	[	X
cana-1859	335	6	8	8	NUM
cana-1859	335	7	]	]	PUNCT
cana-1859	335	8	fireclassnet	fireclassnet	NOUN
cana-1859	335	9	[	[	X
cana-1859	335	10	15	15	NUM
cana-1859	335	11	]	]	X
cana-1859	335	12	vmcnn	vmcnn	NOUN
cana-1859	335	13	communications	communication	NOUN
cana-1859	335	14	on	on	ADP
cana-1859	335	15	applied	apply	VERB
cana-1859	335	16	nonlinear	nonlinear	ADJ
cana-1859	335	17	analysis	analysis	NOUN
cana-1859	335	18	issn	issn	NOUN
cana-1859	335	19	:	:	PUNCT
cana-1859	335	20	1074	1074	NUM
cana-1859	335	21	-	-	PUNCT
cana-1859	335	22	133x	133x	NUM
cana-1859	335	23	vol	vol	NOUN
cana-1859	335	24	32	32	NUM
cana-1859	335	25	no	no	NOUN
cana-1859	335	26	.	.	NOUN
cana-1859	335	27	2	2	NUM
cana-1859	335	28	(	(	PUNCT
cana-1859	335	29	2025	2025	NUM
cana-1859	335	30	)	)	PUNCT
cana-1859	335	31	659	659	NUM
cana-1859	335	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	335	33	fig	fig	NOUN
cana-1859	335	34	5	5	NUM
cana-1859	335	35	.	.	PUNCT
cana-1859	335	36	observed	observe	VERB
cana-1859	335	37	delay	delay	NOUN
cana-1859	335	38	for	for	ADP
cana-1859	335	39	categorizing	categorize	VERB
cana-1859	335	40	multiple	multiple	ADJ
cana-1859	335	41	datasets	dataset	NOUN
cana-1859	335	42	into	into	ADP
cana-1859	335	43	classes	class	NOUN
cana-1859	335	44	the	the	DET
cana-1859	335	45	delay	delay	NOUN
cana-1859	335	46	,	,	PUNCT
cana-1859	335	47	measured	measure	VERB
cana-1859	335	48	in	in	ADP
cana-1859	335	49	milliseconds	millisecond	NOUN
cana-1859	335	50	(	(	PUNCT
cana-1859	335	51	d	d	PROPN
cana-1859	335	52	ms	ms	PROPN
cana-1859	335	53	)	)	PUNCT
cana-1859	335	54	,	,	PUNCT
cana-1859	335	55	across	across	ADP
cana-1859	335	56	various	various	ADJ
cana-1859	335	57	dataset	dataset	NOUN
cana-1859	335	58	sizes	size	NOUN
cana-1859	335	59	(	(	PUNCT
cana-1859	335	60	from	from	ADP
cana-1859	335	61	96k	96k	NOUN
cana-1859	335	62	to	to	ADP
cana-1859	335	63	1728k	1728k	NUM
cana-1859	335	64	)	)	PUNCT
cana-1859	335	65	illustrates	illustrate	VERB
cana-1859	335	66	that	that	SCONJ
cana-1859	335	67	while	while	SCONJ
cana-1859	335	68	vmcnn	vmcnn	PROPN
cana-1859	335	69	generally	generally	ADV
cana-1859	335	70	maintains	maintain	VERB
cana-1859	335	71	a	a	DET
cana-1859	335	72	competitive	competitive	ADJ
cana-1859	335	73	performance	performance	NOUN
cana-1859	335	74	,	,	PUNCT
cana-1859	335	75	the	the	DET
cana-1859	335	76	differences	difference	NOUN
cana-1859	335	77	in	in	ADP
cana-1859	335	78	delay	delay	NOUN
cana-1859	335	79	across	across	ADP
cana-1859	335	80	models	model	NOUN
cana-1859	335	81	are	be	AUX
cana-1859	335	82	less	less	ADV
cana-1859	335	83	pronounced	pronounced	ADJ
cana-1859	335	84	compared	compare	VERB
cana-1859	335	85	to	to	ADP
cana-1859	335	86	other	other	ADJ
cana-1859	335	87	metrics	metric	NOUN
cana-1859	335	88	like	like	ADP
cana-1859	335	89	precision	precision	NOUN
cana-1859	335	90	,	,	PUNCT
cana-1859	335	91	accuracy	accuracy	NOUN
cana-1859	335	92	,	,	PUNCT
cana-1859	335	93	and	and	CCONJ
cana-1859	335	94	recall	recall	NOUN
cana-1859	335	95	.	.	PUNCT
cana-1859	336	1	for	for	ADP
cana-1859	336	2	instance	instance	NOUN
cana-1859	336	3	,	,	PUNCT
cana-1859	336	4	at	at	ADP
cana-1859	336	5	a	a	DET
cana-1859	336	6	dataset	dataset	ADJ
cana-1859	336	7	size	size	NOUN
cana-1859	336	8	of	of	ADP
cana-1859	336	9	800k	800k	NUM
cana-1859	336	10	,	,	PUNCT
cana-1859	336	11	vmcnn	vmcnn	PROPN
cana-1859	336	12	shows	show	VERB
cana-1859	336	13	a	a	DET
cana-1859	336	14	delay	delay	NOUN
cana-1859	336	15	of	of	ADP
cana-1859	336	16	94.22	94.22	NUM
cana-1859	336	17	ms	ms	NOUN
cana-1859	336	18	,	,	PUNCT
cana-1859	336	19	which	which	PRON
cana-1859	336	20	is	be	AUX
cana-1859	336	21	lower	low	ADJ
cana-1859	336	22	than	than	ADP
cana-1859	336	23	the	the	DET
cana-1859	336	24	delays	delay	NOUN
cana-1859	336	25	observed	observe	VERB
cana-1859	336	26	in	in	ADP
cana-1859	336	27	other	other	ADJ
cana-1859	336	28	models	model	NOUN
cana-1859	336	29	,	,	PUNCT
cana-1859	336	30	like	like	ADP
cana-1859	336	31	cnn	cnn	PROPN
cana-1859	336	32	elm	elm	NOUN
cana-1859	336	33	at	at	ADP
cana-1859	336	34	123.27	123.27	NUM
cana-1859	336	35	ms	ms	PROPN
cana-1859	336	36	.	.	PROPN
cana-1859	337	1	however	however	ADV
cana-1859	337	2	,	,	PUNCT
cana-1859	337	3	in	in	ADP
cana-1859	337	4	some	some	DET
cana-1859	337	5	instances	instance	NOUN
cana-1859	337	6	,	,	PUNCT
cana-1859	337	7	such	such	ADJ
cana-1859	337	8	as	as	ADP
cana-1859	337	9	at	at	ADP
cana-1859	337	10	1440k	1440k	NUM
cana-1859	337	11	,	,	PUNCT
cana-1859	337	12	vmcnn	vmcnn	NOUN
cana-1859	337	13	's	's	PART
cana-1859	337	14	delay	delay	NOUN
cana-1859	337	15	of	of	ADP
cana-1859	337	16	105.31	105.31	NUM
cana-1859	337	17	ms	ms	NOUN
cana-1859	337	18	is	be	AUX
cana-1859	337	19	slightly	slightly	ADV
cana-1859	337	20	higher	high	ADJ
cana-1859	337	21	compared	compare	VERB
cana-1859	337	22	to	to	ADP
cana-1859	337	23	other	other	ADJ
cana-1859	337	24	models	model	NOUN
cana-1859	337	25	like	like	ADP
cana-1859	337	26	dcnn	dcnn	PROPN
cana-1859	337	27	at	at	ADP
cana-1859	337	28	106.97	106.97	NUM
cana-1859	337	29	ms	ms	PROPN
cana-1859	337	30	.	.	PUNCT
cana-1859	338	1	these	these	DET
cana-1859	338	2	variations	variation	NOUN
cana-1859	338	3	in	in	ADP
cana-1859	338	4	delay	delay	NOUN
cana-1859	338	5	are	be	AUX
cana-1859	338	6	a	a	DET
cana-1859	338	7	reflection	reflection	NOUN
cana-1859	338	8	of	of	ADP
cana-1859	338	9	the	the	DET
cana-1859	338	10	computational	computational	ADJ
cana-1859	338	11	complexities	complexity	NOUN
cana-1859	338	12	involved	involve	VERB
cana-1859	338	13	in	in	ADP
cana-1859	338	14	each	each	DET
cana-1859	338	15	model	model	NOUN
cana-1859	338	16	.	.	PUNCT
cana-1859	339	1	vmcnn	vmcnn	PROPN
cana-1859	339	2	,	,	PUNCT
cana-1859	339	3	despite	despite	SCONJ
cana-1859	339	4	its	its	PRON
cana-1859	339	5	advanced	advanced	ADJ
cana-1859	339	6	optimization	optimization	NOUN
cana-1859	339	7	through	through	ADP
cana-1859	339	8	vedic	vedic	ADJ
cana-1859	339	9	mathematical	mathematical	ADJ
cana-1859	339	10	sutras	sutra	NOUN
cana-1859	339	11	,	,	PUNCT
cana-1859	339	12	shows	show	VERB
cana-1859	339	13	that	that	SCONJ
cana-1859	339	14	there	there	PRON
cana-1859	339	15	is	be	VERB
cana-1859	339	16	a	a	DET
cana-1859	339	17	balance	balance	NOUN
cana-1859	339	18	to	to	PART
cana-1859	339	19	be	be	AUX
cana-1859	339	20	struck	strike	VERB
cana-1859	339	21	between	between	ADP
cana-1859	339	22	computational	computational	ADJ
cana-1859	339	23	efficiency	efficiency	NOUN
cana-1859	339	24	and	and	CCONJ
cana-1859	339	25	the	the	DET
cana-1859	339	26	sophistication	sophistication	NOUN
cana-1859	339	27	of	of	ADP
cana-1859	339	28	the	the	DET
cana-1859	339	29	model	model	NOUN
cana-1859	339	30	.	.	PUNCT
cana-1859	340	1	the	the	DET
cana-1859	340	2	relatively	relatively	ADV
cana-1859	340	3	marginal	marginal	ADJ
cana-1859	340	4	differences	difference	NOUN
cana-1859	340	5	in	in	ADP
cana-1859	340	6	delay	delay	NOUN
cana-1859	340	7	among	among	ADP
cana-1859	340	8	the	the	DET
cana-1859	340	9	models	model	NOUN
cana-1859	340	10	indicate	indicate	VERB
cana-1859	340	11	that	that	SCONJ
cana-1859	340	12	the	the	DET
cana-1859	340	13	computational	computational	ADJ
cana-1859	340	14	enhancements	enhancement	NOUN
cana-1859	340	15	offered	offer	VERB
cana-1859	340	16	by	by	ADP
cana-1859	340	17	vmcnn	vmcnn	PROPN
cana-1859	340	18	are	be	AUX
cana-1859	340	19	more	more	ADV
cana-1859	340	20	oriented	oriented	ADJ
cana-1859	340	21	towards	towards	ADP
cana-1859	340	22	improving	improve	VERB
cana-1859	340	23	accuracy	accuracy	NOUN
cana-1859	340	24	and	and	CCONJ
cana-1859	340	25	reliability	reliability	NOUN
cana-1859	340	26	rather	rather	ADV
cana-1859	340	27	than	than	ADP
cana-1859	340	28	just	just	ADV
cana-1859	340	29	speed	speed	NOUN
cana-1859	340	30	.	.	PUNCT
cana-1859	341	1	the	the	DET
cana-1859	341	2	impact	impact	NOUN
cana-1859	341	3	of	of	ADP
cana-1859	341	4	these	these	DET
cana-1859	341	5	delay	delay	NOUN
cana-1859	341	6	metrics	metric	NOUN
cana-1859	341	7	is	be	AUX
cana-1859	341	8	significant	significant	ADJ
cana-1859	341	9	in	in	ADP
cana-1859	341	10	real	real	ADJ
cana-1859	341	11	-	-	PUNCT
cana-1859	341	12	world	world	NOUN
cana-1859	341	13	applications	application	NOUN
cana-1859	341	14	.	.	PUNCT
cana-1859	342	1	in	in	ADP
cana-1859	342	2	scenarios	scenario	NOUN
cana-1859	342	3	where	where	SCONJ
cana-1859	342	4	realtime	realtime	NOUN
cana-1859	342	5	processing	processing	NOUN
cana-1859	342	6	is	be	AUX
cana-1859	342	7	crucial	crucial	ADJ
cana-1859	342	8	,	,	PUNCT
cana-1859	342	9	such	such	ADJ
cana-1859	342	10	as	as	ADP
cana-1859	342	11	in	in	ADP
cana-1859	342	12	autonomous	autonomous	ADJ
cana-1859	342	13	vehicles	vehicle	NOUN
cana-1859	342	14	or	or	CCONJ
cana-1859	342	15	real	real	ADJ
cana-1859	342	16	-	-	PUNCT
cana-1859	342	17	time	time	NOUN
cana-1859	342	18	surveillance	surveillance	NOUN
cana-1859	342	19	systems	system	NOUN
cana-1859	342	20	,	,	PUNCT
cana-1859	342	21	even	even	ADV
cana-1859	342	22	a	a	DET
cana-1859	342	23	small	small	ADJ
cana-1859	342	24	reduction	reduction	NOUN
cana-1859	342	25	in	in	ADP
cana-1859	342	26	delay	delay	NOUN
cana-1859	342	27	can	can	AUX
cana-1859	342	28	be	be	AUX
cana-1859	342	29	beneficial	beneficial	ADJ
cana-1859	342	30	.	.	PUNCT
cana-1859	343	1	however	however	ADV
cana-1859	343	2	,	,	PUNCT
cana-1859	343	3	the	the	DET
cana-1859	343	4	marginal	marginal	ADJ
cana-1859	343	5	differences	difference	NOUN
cana-1859	343	6	suggest	suggest	VERB
cana-1859	343	7	that	that	SCONJ
cana-1859	343	8	the	the	DET
cana-1859	343	9	choice	choice	NOUN
cana-1859	343	10	of	of	ADP
cana-1859	343	11	model	model	NOUN
cana-1859	343	12	may	may	AUX
cana-1859	343	13	depend	depend	VERB
cana-1859	343	14	more	more	ADJ
cana-1859	343	15	on	on	ADP
cana-1859	343	16	the	the	DET
cana-1859	343	17	specific	specific	ADJ
cana-1859	343	18	requirements	requirement	NOUN
cana-1859	343	19	of	of	ADP
cana-1859	343	20	accuracy	accuracy	NOUN
cana-1859	343	21	and	and	CCONJ
cana-1859	343	22	recall	recall	NOUN
cana-1859	343	23	rather	rather	ADV
cana-1859	343	24	than	than	ADP
cana-1859	343	25	speed	speed	NOUN
cana-1859	343	26	alone	alone	ADV
cana-1859	343	27	.	.	PUNCT
cana-1859	344	1	in	in	ADP
cana-1859	344	2	domains	domain	NOUN
cana-1859	344	3	where	where	SCONJ
cana-1859	344	4	precision	precision	NOUN
cana-1859	344	5	and	and	CCONJ
cana-1859	344	6	recall	recall	NOUN
cana-1859	344	7	are	be	AUX
cana-1859	344	8	more	more	ADV
cana-1859	344	9	critical	critical	ADJ
cana-1859	344	10	,	,	PUNCT
cana-1859	344	11	such	such	ADJ
cana-1859	344	12	as	as	ADP
cana-1859	344	13	medical	medical	ADJ
cana-1859	344	14	diagnostics	diagnostic	NOUN
cana-1859	344	15	,	,	PUNCT
cana-1859	344	16	the	the	DET
cana-1859	344	17	slight	slight	ADJ
cana-1859	344	18	increase	increase	NOUN
cana-1859	344	19	in	in	ADP
cana-1859	344	20	delay	delay	NOUN
cana-1859	344	21	might	might	AUX
cana-1859	344	22	be	be	AUX
cana-1859	344	23	a	a	DET
cana-1859	344	24	worthwhile	worthwhile	ADJ
cana-1859	344	25	trade	trade	NOUN
cana-1859	344	26	-	-	PUNCT
cana-1859	344	27	off	off	NOUN
cana-1859	344	28	for	for	ADP
cana-1859	344	29	the	the	DET
cana-1859	344	30	substantial	substantial	ADJ
cana-1859	344	31	gains	gain	NOUN
cana-1859	344	32	in	in	ADP
cana-1859	344	33	accuracy	accuracy	NOUN
cana-1859	344	34	and	and	CCONJ
cana-1859	344	35	reliability	reliability	NOUN
cana-1859	344	36	offered	offer	VERB
cana-1859	344	37	by	by	ADP
cana-1859	344	38	vmcnn	vmcnn	PROPN
cana-1859	344	39	.	.	PUNCT
cana-1859	345	1	this	this	PRON
cana-1859	345	2	highlights	highlight	VERB
cana-1859	345	3	the	the	DET
cana-1859	345	4	importance	importance	NOUN
cana-1859	345	5	of	of	ADP
cana-1859	345	6	considering	consider	VERB
cana-1859	345	7	the	the	DET
cana-1859	345	8	specific	specific	ADJ
cana-1859	345	9	application	application	NOUN
cana-1859	345	10	and	and	CCONJ
cana-1859	345	11	its	its	PRON
cana-1859	345	12	requirements	requirement	NOUN
cana-1859	345	13	when	when	SCONJ
cana-1859	345	14	evaluating	evaluate	VERB
cana-1859	345	15	the	the	DET
cana-1859	345	16	effectiveness	effectiveness	NOUN
cana-1859	345	17	of	of	ADP
cana-1859	345	18	these	these	DET
cana-1859	345	19	models	model	NOUN
cana-1859	345	20	.	.	PUNCT
cana-1859	346	1	similarly	similarly	ADV
cana-1859	346	2	,	,	PUNCT
cana-1859	346	3	the	the	DET
cana-1859	346	4	auc	auc	NOUN
cana-1859	346	5	levels	level	NOUN
cana-1859	346	6	can	can	AUX
cana-1859	346	7	be	be	AUX
cana-1859	346	8	observed	observe	VERB
cana-1859	346	9	from	from	ADP
cana-1859	346	10	figure	figure	NOUN
cana-1859	346	11	6	6	NUM
cana-1859	346	12	as	as	SCONJ
cana-1859	346	13	follows	follow	VERB
cana-1859	346	14	,	,	PUNCT
cana-1859	346	15	70.00	70.00	NUM
cana-1859	346	16	80.00	80.00	NUM
cana-1859	346	17	90.00	90.00	NUM
cana-1859	346	18	100.00	100.00	NUM
cana-1859	346	19	110.00	110.00	NUM
cana-1859	346	20	120.00	120.00	NUM
cana-1859	346	21	130.00	130.00	NUM
cana-1859	346	22	96k	96k	NOUN
cana-1859	346	23	184k	184k	NUM
cana-1859	346	24	240k	240k	NUM
cana-1859	346	25	312k	312k	PROPN
cana-1859	346	26	368k	368k	NOUN
cana-1859	347	1	432k	432k	PROPN
cana-1859	347	2	504k	504k	PROPN
cana-1859	347	3	560k	560k	NUM
cana-1859	347	4	600k	600k	NUM
cana-1859	347	5	680k	680k	NOUN
cana-1859	347	6	744k	744k	NOUN
cana-1859	347	7	800k	800k	NUM
cana-1859	347	8	872k	872k	NOUN
cana-1859	347	9	936k	936k	NUM
cana-1859	347	10	1008k	1008k	PROPN
cana-1859	347	11	1064k	1064k	NUM
cana-1859	347	12	1080k	1080k	NUM
cana-1859	347	13	1192k	1192k	NOUN
cana-1859	347	14	1224k	1224k	NUM
cana-1859	347	15	1320k	1320k	NOUN
cana-1859	347	16	1360k	1360k	NUM
cana-1859	347	17	1440k	1440k	NUM
cana-1859	347	18	1584k	1584k	NUM
cana-1859	347	19	1728k	1728k	NUM
cana-1859	347	20	cnn	cnn	PROPN
cana-1859	347	21	elm	elm	PROPN
cana-1859	348	1	[	[	X
cana-1859	348	2	6	6	NUM
cana-1859	348	3	]	]	X
cana-1859	348	4	dcnn	dcnn	VERB
cana-1859	348	5	[	[	X
cana-1859	348	6	8	8	NUM
cana-1859	348	7	]	]	PUNCT
cana-1859	348	8	fireclassnet	fireclassnet	NOUN
cana-1859	348	9	[	[	X
cana-1859	348	10	15	15	NUM
cana-1859	348	11	]	]	X
cana-1859	348	12	vmcnn	vmcnn	NOUN
cana-1859	348	13	communications	communication	NOUN
cana-1859	348	14	on	on	ADP
cana-1859	348	15	applied	apply	VERB
cana-1859	348	16	nonlinear	nonlinear	ADJ
cana-1859	348	17	analysis	analysis	NOUN
cana-1859	348	18	issn	issn	NOUN
cana-1859	348	19	:	:	PUNCT
cana-1859	348	20	1074	1074	NUM
cana-1859	348	21	-	-	PUNCT
cana-1859	348	22	133x	133x	NUM
cana-1859	348	23	vol	vol	NOUN
cana-1859	348	24	32	32	NUM
cana-1859	348	25	no	no	NOUN
cana-1859	348	26	.	.	NOUN
cana-1859	348	27	2	2	NUM
cana-1859	348	28	(	(	PUNCT
cana-1859	348	29	2025	2025	NUM
cana-1859	348	30	)	)	PUNCT
cana-1859	348	31	660	660	NUM
cana-1859	348	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	348	33	fig	fig	NOUN
cana-1859	348	34	6	6	NUM
cana-1859	348	35	.	.	PUNCT
cana-1859	348	36	observed	observe	VERB
cana-1859	348	37	auc	auc	NOUN
cana-1859	348	38	for	for	ADP
cana-1859	348	39	categorizing	categorize	VERB
cana-1859	348	40	multiple	multiple	ADJ
cana-1859	348	41	datasets	dataset	NOUN
cana-1859	348	42	into	into	ADP
cana-1859	348	43	classes	class	NOUN
cana-1859	348	44	the	the	DET
cana-1859	348	45	analysis	analysis	NOUN
cana-1859	348	46	of	of	ADP
cana-1859	348	47	the	the	DET
cana-1859	348	48	observed	observed	ADJ
cana-1859	348	49	area	area	NOUN
cana-1859	348	50	under	under	ADP
cana-1859	348	51	the	the	DET
cana-1859	348	52	curve	curve	NOUN
cana-1859	348	53	(	(	PUNCT
cana-1859	348	54	auc	auc	NOUN
cana-1859	348	55	)	)	PUNCT
cana-1859	348	56	for	for	ADP
cana-1859	348	57	categorizing	categorize	VERB
cana-1859	348	58	multiple	multiple	ADJ
cana-1859	348	59	datasets	dataset	NOUN
cana-1859	348	60	into	into	ADP
cana-1859	348	61	classes	class	NOUN
cana-1859	348	62	highlights	highlight	VERB
cana-1859	348	63	the	the	DET
cana-1859	348	64	efficacy	efficacy	NOUN
cana-1859	348	65	of	of	ADP
cana-1859	348	66	vmcnn	vmcnn	PROPN
cana-1859	348	67	compared	compare	VERB
cana-1859	348	68	to	to	ADP
cana-1859	348	69	cnn	cnn	PROPN
cana-1859	348	70	elm	elm	PROPN
cana-1859	348	71	,	,	PUNCT
cana-1859	348	72	dcnn	dcnn	PROPN
cana-1859	348	73	,	,	PUNCT
cana-1859	348	74	and	and	CCONJ
cana-1859	348	75	fireclassnet	fireclassnet	NOUN
cana-1859	348	76	,	,	PUNCT
cana-1859	348	77	particularly	particularly	ADV
cana-1859	348	78	in	in	ADP
cana-1859	348	79	the	the	DET
cana-1859	348	80	context	context	NOUN
cana-1859	348	81	of	of	ADP
cana-1859	348	82	receiver	receiver	NOUN
cana-1859	348	83	operating	operate	VERB
cana-1859	348	84	characteristic	characteristic	NOUN
cana-1859	348	85	(	(	PUNCT
cana-1859	348	86	roc	roc	PROPN
cana-1859	348	87	)	)	PUNCT
cana-1859	348	88	curve	curve	NOUN
cana-1859	348	89	performance	performance	NOUN
cana-1859	348	90	.	.	PUNCT
cana-1859	349	1	auc	auc	NOUN
cana-1859	349	2	,	,	PUNCT
cana-1859	349	3	a	a	DET
cana-1859	349	4	crucial	crucial	ADJ
cana-1859	349	5	metric	metric	NOUN
cana-1859	349	6	in	in	ADP
cana-1859	349	7	classification	classification	NOUN
cana-1859	349	8	tasks	task	NOUN
cana-1859	349	9	,	,	PUNCT
cana-1859	349	10	measures	measure	VERB
cana-1859	349	11	the	the	DET
cana-1859	349	12	ability	ability	NOUN
cana-1859	349	13	of	of	ADP
cana-1859	349	14	a	a	DET
cana-1859	349	15	model	model	NOUN
cana-1859	349	16	to	to	PART
cana-1859	349	17	distinguish	distinguish	VERB
cana-1859	349	18	between	between	ADP
cana-1859	349	19	classes	class	NOUN
cana-1859	349	20	.	.	PUNCT
cana-1859	350	1	a	a	DET
cana-1859	350	2	higher	high	ADJ
cana-1859	350	3	auc	auc	NOUN
cana-1859	350	4	value	value	NOUN
cana-1859	350	5	indicates	indicate	VERB
cana-1859	350	6	better	well	ADJ
cana-1859	350	7	model	model	NOUN
cana-1859	350	8	performance	performance	NOUN
cana-1859	350	9	.	.	PUNCT
cana-1859	351	1	across	across	ADP
cana-1859	351	2	various	various	ADJ
cana-1859	351	3	dataset	dataset	NOUN
cana-1859	351	4	sizes	size	NOUN
cana-1859	351	5	(	(	PUNCT
cana-1859	351	6	from	from	ADP
cana-1859	351	7	96k	96k	NOUN
cana-1859	351	8	to	to	ADP
cana-1859	351	9	1728k	1728k	NUM
cana-1859	351	10	)	)	PUNCT
cana-1859	351	11	,	,	PUNCT
cana-1859	351	12	vmcnn	vmcnn	PROPN
cana-1859	351	13	consistently	consistently	ADV
cana-1859	351	14	exhibits	exhibit	VERB
cana-1859	351	15	higher	high	ADJ
cana-1859	351	16	auc	auc	NOUN
cana-1859	351	17	values	value	NOUN
cana-1859	351	18	,	,	PUNCT
cana-1859	351	19	indicating	indicate	VERB
cana-1859	351	20	its	its	PRON
cana-1859	351	21	superior	superior	ADJ
cana-1859	351	22	classification	classification	NOUN
cana-1859	351	23	capability	capability	NOUN
cana-1859	351	24	.	.	PUNCT
cana-1859	352	1	for	for	ADP
cana-1859	352	2	example	example	NOUN
cana-1859	352	3	,	,	PUNCT
cana-1859	352	4	at	at	ADP
cana-1859	352	5	a	a	DET
cana-1859	352	6	dataset	dataset	ADJ
cana-1859	352	7	size	size	NOUN
cana-1859	352	8	of	of	ADP
cana-1859	352	9	240k	240k	NOUN
cana-1859	352	10	,	,	PUNCT
cana-1859	352	11	vmcnn	vmcnn	PROPN
cana-1859	352	12	achieves	achieve	VERB
cana-1859	352	13	an	an	DET
cana-1859	352	14	auc	auc	NOUN
cana-1859	352	15	of	of	ADP
cana-1859	352	16	91.34	91.34	NUM
cana-1859	352	17	,	,	PUNCT
cana-1859	352	18	significantly	significantly	ADV
cana-1859	352	19	higher	high	ADJ
cana-1859	352	20	than	than	ADP
cana-1859	352	21	the	the	DET
cana-1859	352	22	next	next	ADJ
cana-1859	352	23	best	well	ADV
cana-1859	352	24	,	,	PUNCT
cana-1859	352	25	cnn	cnn	PROPN
cana-1859	352	26	elm	elm	PROPN
cana-1859	352	27	,	,	PUNCT
cana-1859	352	28	which	which	PRON
cana-1859	352	29	records	record	VERB
cana-1859	352	30	72.32	72.32	NUM
cana-1859	352	31	.	.	PUNCT
cana-1859	353	1	this	this	DET
cana-1859	353	2	trend	trend	NOUN
cana-1859	353	3	of	of	ADP
cana-1859	353	4	vmcnn	vmcnn	NOUN
cana-1859	353	5	's	's	PART
cana-1859	353	6	dominance	dominance	NOUN
cana-1859	353	7	in	in	ADP
cana-1859	353	8	auc	auc	NOUN
cana-1859	353	9	is	be	AUX
cana-1859	353	10	evident	evident	ADJ
cana-1859	353	11	across	across	ADP
cana-1859	353	12	all	all	DET
cana-1859	353	13	dataset	dataset	ADJ
cana-1859	353	14	sizes	size	NOUN
cana-1859	353	15	.	.	PUNCT
cana-1859	354	1	at	at	ADP
cana-1859	354	2	800k	800k	NUM
cana-1859	354	3	,	,	PUNCT
cana-1859	354	4	vmcnn	vmcnn	PROPN
cana-1859	354	5	reaches	reach	VERB
cana-1859	354	6	an	an	DET
cana-1859	354	7	auc	auc	NOUN
cana-1859	354	8	of	of	ADP
cana-1859	354	9	91.19	91.19	NUM
cana-1859	354	10	,	,	PUNCT
cana-1859	354	11	while	while	SCONJ
cana-1859	354	12	dcnn	dcnn	PROPN
cana-1859	354	13	scores	score	VERB
cana-1859	354	14	70.47	70.47	NUM
cana-1859	354	15	.	.	PUNCT
cana-1859	355	1	the	the	DET
cana-1859	355	2	higher	high	ADJ
cana-1859	355	3	auc	auc	NOUN
cana-1859	355	4	values	value	NOUN
cana-1859	355	5	of	of	ADP
cana-1859	355	6	vmcnn	vmcnn	NOUN
cana-1859	355	7	can	can	AUX
cana-1859	355	8	be	be	AUX
cana-1859	355	9	attributed	attribute	VERB
cana-1859	355	10	to	to	ADP
cana-1859	355	11	its	its	PRON
cana-1859	355	12	optimized	optimize	VERB
cana-1859	355	13	convolutional	convolutional	ADJ
cana-1859	355	14	neural	neural	ADJ
cana-1859	355	15	network	network	NOUN
cana-1859	355	16	structure	structure	NOUN
cana-1859	355	17	,	,	PUNCT
cana-1859	355	18	which	which	PRON
cana-1859	355	19	benefits	benefit	VERB
cana-1859	355	20	from	from	ADP
cana-1859	355	21	the	the	DET
cana-1859	355	22	integration	integration	NOUN
cana-1859	355	23	of	of	ADP
cana-1859	355	24	vedic	vedic	ADJ
cana-1859	355	25	mathematical	mathematical	ADJ
cana-1859	355	26	principles	principle	NOUN
cana-1859	355	27	.	.	PUNCT
cana-1859	356	1	this	this	DET
cana-1859	356	2	optimization	optimization	NOUN
cana-1859	356	3	enables	enable	VERB
cana-1859	356	4	vmcnn	vmcnn	NOUN
cana-1859	356	5	to	to	AUX
cana-1859	356	6	more	more	ADV
cana-1859	356	7	effectively	effectively	ADV
cana-1859	356	8	differentiate	differentiate	VERB
cana-1859	356	9	between	between	ADP
cana-1859	356	10	various	various	ADJ
cana-1859	356	11	classes	class	NOUN
cana-1859	356	12	in	in	ADP
cana-1859	356	13	the	the	DET
cana-1859	356	14	datasets	dataset	NOUN
cana-1859	356	15	,	,	PUNCT
cana-1859	356	16	leading	lead	VERB
cana-1859	356	17	to	to	ADP
cana-1859	356	18	improved	improve	VERB
cana-1859	356	19	classification	classification	NOUN
cana-1859	356	20	performance	performance	NOUN
cana-1859	356	21	.	.	PUNCT
cana-1859	357	1	for	for	ADP
cana-1859	357	2	example	example	NOUN
cana-1859	357	3	,	,	PUNCT
cana-1859	357	4	at	at	ADP
cana-1859	357	5	1224k	1224k	NUM
cana-1859	357	6	,	,	PUNCT
cana-1859	357	7	vmcnn	vmcnn	NOUN
cana-1859	357	8	's	's	PART
cana-1859	357	9	auc	auc	NOUN
cana-1859	357	10	is	be	AUX
cana-1859	357	11	88.56	88.56	NUM
cana-1859	357	12	,	,	PUNCT
cana-1859	357	13	considerably	considerably	ADV
cana-1859	357	14	higher	high	ADJ
cana-1859	357	15	than	than	ADP
cana-1859	357	16	fireclassnet	fireclassnet	NOUN
cana-1859	357	17	's	's	PART
cana-1859	357	18	74.10	74.10	NUM
cana-1859	357	19	.	.	PUNCT
cana-1859	358	1	the	the	DET
cana-1859	358	2	impact	impact	NOUN
cana-1859	358	3	of	of	ADP
cana-1859	358	4	high	high	ADJ
cana-1859	358	5	auc	auc	NOUN
cana-1859	358	6	values	value	NOUN
cana-1859	358	7	in	in	ADP
cana-1859	358	8	practical	practical	ADJ
cana-1859	358	9	applications	application	NOUN
cana-1859	358	10	is	be	AUX
cana-1859	358	11	significant	significant	ADJ
cana-1859	358	12	.	.	PUNCT
cana-1859	359	1	in	in	ADP
cana-1859	359	2	medical	medical	ADJ
cana-1859	359	3	diagnostics	diagnostic	NOUN
cana-1859	359	4	,	,	PUNCT
cana-1859	359	5	for	for	ADP
cana-1859	359	6	instance	instance	NOUN
cana-1859	359	7	,	,	PUNCT
cana-1859	359	8	the	the	DET
cana-1859	359	9	ability	ability	NOUN
cana-1859	359	10	to	to	PART
cana-1859	359	11	accurately	accurately	ADV
cana-1859	359	12	distinguish	distinguish	VERB
cana-1859	359	13	between	between	ADP
cana-1859	359	14	healthy	healthy	ADJ
cana-1859	359	15	and	and	CCONJ
cana-1859	359	16	pathological	pathological	ADJ
cana-1859	359	17	conditions	condition	NOUN
cana-1859	359	18	is	be	AUX
cana-1859	359	19	critical	critical	ADJ
cana-1859	359	20	,	,	PUNCT
cana-1859	359	21	and	and	CCONJ
cana-1859	359	22	a	a	DET
cana-1859	359	23	high	high	ADJ
cana-1859	359	24	auc	auc	NOUN
cana-1859	359	25	value	value	NOUN
cana-1859	359	26	indicates	indicate	VERB
cana-1859	359	27	a	a	DET
cana-1859	359	28	more	more	ADV
cana-1859	359	29	reliable	reliable	ADJ
cana-1859	359	30	model	model	NOUN
cana-1859	359	31	for	for	ADP
cana-1859	359	32	such	such	ADJ
cana-1859	359	33	tasks	task	NOUN
cana-1859	359	34	.	.	PUNCT
cana-1859	360	1	in	in	ADP
cana-1859	360	2	other	other	ADJ
cana-1859	360	3	applications	application	NOUN
cana-1859	360	4	like	like	ADP
cana-1859	360	5	financial	financial	ADJ
cana-1859	360	6	fraud	fraud	NOUN
cana-1859	360	7	detection	detection	NOUN
cana-1859	360	8	or	or	CCONJ
cana-1859	360	9	spam	spam	NOUN
cana-1859	360	10	filtering	filter	VERB
cana-1859	360	11	,	,	PUNCT
cana-1859	360	12	a	a	DET
cana-1859	360	13	high	high	ADJ
cana-1859	360	14	auc	auc	NOUN
cana-1859	360	15	means	mean	VERB
cana-1859	360	16	that	that	SCONJ
cana-1859	360	17	the	the	DET
cana-1859	360	18	model	model	NOUN
cana-1859	360	19	can	can	AUX
cana-1859	360	20	more	more	ADV
cana-1859	360	21	effectively	effectively	ADV
cana-1859	360	22	separate	separate	VERB
cana-1859	360	23	fraudulent	fraudulent	ADJ
cana-1859	360	24	transactions	transaction	NOUN
cana-1859	360	25	or	or	CCONJ
cana-1859	360	26	spam	spam	VERB
cana-1859	360	27	emails	email	NOUN
cana-1859	360	28	from	from	ADP
cana-1859	360	29	legitimate	legitimate	ADJ
cana-1859	360	30	ones	one	NOUN
cana-1859	360	31	,	,	PUNCT
cana-1859	360	32	reducing	reduce	VERB
cana-1859	360	33	the	the	DET
cana-1859	360	34	risk	risk	NOUN
cana-1859	360	35	of	of	ADP
cana-1859	360	36	false	false	ADJ
cana-1859	360	37	positives	positive	NOUN
cana-1859	360	38	or	or	CCONJ
cana-1859	360	39	negatives	negative	NOUN
cana-1859	360	40	.	.	PUNCT
cana-1859	361	1	in	in	ADP
cana-1859	361	2	summary	summary	NOUN
cana-1859	361	3	,	,	PUNCT
cana-1859	361	4	the	the	DET
cana-1859	361	5	consistently	consistently	ADV
cana-1859	361	6	high	high	ADJ
cana-1859	361	7	auc	auc	NOUN
cana-1859	361	8	values	value	NOUN
cana-1859	361	9	of	of	ADP
cana-1859	361	10	vmcnn	vmcnn	PROPN
cana-1859	361	11	underscore	underscore	VERB
cana-1859	361	12	its	its	PRON
cana-1859	361	13	effectiveness	effectiveness	NOUN
cana-1859	361	14	in	in	ADP
cana-1859	361	15	accurately	accurately	ADV
cana-1859	361	16	classifying	classify	VERB
cana-1859	361	17	data	datum	NOUN
cana-1859	361	18	across	across	ADP
cana-1859	361	19	various	various	ADJ
cana-1859	361	20	contexts	contexts	NOUN
cana-1859	361	21	.	.	PUNCT
cana-1859	362	1	this	this	DET
cana-1859	362	2	superior	superior	ADJ
cana-1859	362	3	performance	performance	NOUN
cana-1859	362	4	,	,	PUNCT
cana-1859	362	5	enabled	enable	VERB
cana-1859	362	6	by	by	ADP
cana-1859	362	7	the	the	DET
cana-1859	362	8	integration	integration	NOUN
cana-1859	362	9	of	of	ADP
cana-1859	362	10	ancient	ancient	ADJ
cana-1859	362	11	mathematical	mathematical	ADJ
cana-1859	362	12	techniques	technique	NOUN
cana-1859	362	13	with	with	ADP
cana-1859	362	14	modern	modern	ADJ
cana-1859	362	15	ai	ai	NOUN
cana-1859	362	16	,	,	PUNCT
cana-1859	362	17	holds	hold	VERB
cana-1859	362	18	significant	significant	ADJ
cana-1859	362	19	implications	implication	NOUN
cana-1859	362	20	for	for	ADP
cana-1859	362	21	fields	field	NOUN
cana-1859	362	22	where	where	SCONJ
cana-1859	362	23	60.00	60.00	NUM
cana-1859	362	24	65.00	65.00	NUM
cana-1859	362	25	70.00	70.00	NUM
cana-1859	362	26	75.00	75.00	NUM
cana-1859	362	27	80.00	80.00	NUM
cana-1859	362	28	85.00	85.00	NUM
cana-1859	362	29	90.00	90.00	NUM
cana-1859	362	30	95.00	95.00	NUM
cana-1859	362	31	cnn	cnn	PROPN
cana-1859	362	32	elm	elm	PROPN
cana-1859	363	1	[	[	X
cana-1859	363	2	6	6	NUM
cana-1859	363	3	]	]	X
cana-1859	363	4	dcnn	dcnn	VERB
cana-1859	363	5	[	[	X
cana-1859	363	6	8	8	NUM
cana-1859	363	7	]	]	PUNCT
cana-1859	363	8	fireclassnet	fireclassnet	NOUN
cana-1859	363	9	[	[	X
cana-1859	363	10	15	15	NUM
cana-1859	363	11	]	]	X
cana-1859	363	12	vmcnn	vmcnn	NOUN
cana-1859	363	13	communications	communication	NOUN
cana-1859	363	14	on	on	ADP
cana-1859	363	15	applied	apply	VERB
cana-1859	363	16	nonlinear	nonlinear	ADJ
cana-1859	363	17	analysis	analysis	NOUN
cana-1859	363	18	issn	issn	NOUN
cana-1859	363	19	:	:	PUNCT
cana-1859	363	20	1074	1074	NUM
cana-1859	363	21	-	-	PUNCT
cana-1859	363	22	133x	133x	NUM
cana-1859	363	23	vol	vol	NOUN
cana-1859	363	24	32	32	NUM
cana-1859	363	25	no	no	NOUN
cana-1859	363	26	.	.	NOUN
cana-1859	363	27	2	2	NUM
cana-1859	363	28	(	(	PUNCT
cana-1859	363	29	2025	2025	NUM
cana-1859	363	30	)	)	PUNCT
cana-1859	363	31	661	661	NUM
cana-1859	363	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	363	33	precision	precision	NOUN
cana-1859	363	34	in	in	ADP
cana-1859	363	35	classification	classification	NOUN
cana-1859	363	36	is	be	AUX
cana-1859	363	37	paramount	paramount	ADJ
cana-1859	363	38	.	.	PUNCT
cana-1859	364	1	the	the	DET
cana-1859	364	2	high	high	ADJ
cana-1859	364	3	auc	auc	NOUN
cana-1859	364	4	values	value	NOUN
cana-1859	364	5	not	not	PART
cana-1859	364	6	only	only	ADV
cana-1859	364	7	reflect	reflect	VERB
cana-1859	364	8	the	the	DET
cana-1859	364	9	technical	technical	ADJ
cana-1859	364	10	robustness	robustness	NOUN
cana-1859	364	11	of	of	ADP
cana-1859	364	12	vmcnn	vmcnn	NOUN
cana-1859	364	13	but	but	CCONJ
cana-1859	364	14	also	also	ADV
cana-1859	364	15	its	its	PRON
cana-1859	364	16	practical	practical	ADJ
cana-1859	364	17	applicability	applicability	NOUN
cana-1859	364	18	in	in	ADP
cana-1859	364	19	critical	critical	ADJ
cana-1859	364	20	decision	decision	NOUN
cana-1859	364	21	-	-	PUNCT
cana-1859	364	22	making	make	VERB
cana-1859	364	23	scenarios	scenario	NOUN
cana-1859	364	24	.	.	PUNCT
cana-1859	365	1	similarly	similarly	ADV
cana-1859	365	2	,	,	PUNCT
cana-1859	365	3	the	the	DET
cana-1859	365	4	mae	mae	PROPN
cana-1859	365	5	levels	level	NOUN
cana-1859	365	6	can	can	AUX
cana-1859	365	7	be	be	AUX
cana-1859	365	8	observed	observe	VERB
cana-1859	365	9	from	from	ADP
cana-1859	365	10	figure	figure	NOUN
cana-1859	365	11	7	7	NUM
cana-1859	365	12	as	as	SCONJ
cana-1859	365	13	follows	follow	VERB
cana-1859	365	14	,	,	PUNCT
cana-1859	365	15	fig	fig	NOUN
cana-1859	365	16	7	7	NUM
cana-1859	365	17	.	.	PUNCT
cana-1859	366	1	observed	observe	VERB
cana-1859	366	2	mae	mae	PROPN
cana-1859	366	3	for	for	ADP
cana-1859	366	4	categorizing	categorize	VERB
cana-1859	366	5	multiple	multiple	ADJ
cana-1859	366	6	datasets	dataset	NOUN
cana-1859	366	7	into	into	ADP
cana-1859	366	8	classes	class	NOUN
cana-1859	366	9	mae	mae	PROPN
cana-1859	366	10	is	be	AUX
cana-1859	366	11	a	a	DET
cana-1859	366	12	measure	measure	NOUN
cana-1859	366	13	of	of	ADP
cana-1859	366	14	the	the	DET
cana-1859	366	15	difference	difference	NOUN
cana-1859	366	16	between	between	ADP
cana-1859	366	17	the	the	DET
cana-1859	366	18	predicted	predict	VERB
cana-1859	366	19	values	value	NOUN
cana-1859	366	20	and	and	CCONJ
cana-1859	366	21	the	the	DET
cana-1859	366	22	actual	actual	ADJ
cana-1859	366	23	values	value	NOUN
cana-1859	366	24	and	and	CCONJ
cana-1859	366	25	is	be	AUX
cana-1859	366	26	a	a	DET
cana-1859	366	27	critical	critical	ADJ
cana-1859	366	28	indicator	indicator	NOUN
cana-1859	366	29	of	of	ADP
cana-1859	366	30	the	the	DET
cana-1859	366	31	model	model	NOUN
cana-1859	366	32	's	's	PART
cana-1859	366	33	accuracy	accuracy	NOUN
cana-1859	366	34	in	in	ADP
cana-1859	366	35	prediction	prediction	NOUN
cana-1859	366	36	.	.	PUNCT
cana-1859	367	1	lower	low	ADJ
cana-1859	367	2	mae	mae	PROPN
cana-1859	367	3	values	value	NOUN
cana-1859	367	4	indicate	indicate	VERB
cana-1859	367	5	higher	high	ADJ
cana-1859	367	6	precision	precision	NOUN
cana-1859	367	7	and	and	CCONJ
cana-1859	367	8	reliability	reliability	NOUN
cana-1859	367	9	of	of	ADP
cana-1859	367	10	the	the	DET
cana-1859	367	11	model	model	NOUN
cana-1859	367	12	.	.	PUNCT
cana-1859	368	1	across	across	ADP
cana-1859	368	2	various	various	ADJ
cana-1859	368	3	dataset	dataset	NOUN
cana-1859	368	4	sizes	size	NOUN
cana-1859	368	5	,	,	PUNCT
cana-1859	368	6	vmcnn	vmcnn	PROPN
cana-1859	368	7	consistently	consistently	ADV
cana-1859	368	8	demonstrates	demonstrate	VERB
cana-1859	368	9	lower	low	ADJ
cana-1859	368	10	mae	mae	PROPN
cana-1859	368	11	values	value	NOUN
cana-1859	368	12	,	,	PUNCT
cana-1859	368	13	indicating	indicate	VERB
cana-1859	368	14	its	its	PRON
cana-1859	368	15	superior	superior	ADJ
cana-1859	368	16	precision	precision	NOUN
cana-1859	368	17	in	in	ADP
cana-1859	368	18	classification	classification	NOUN
cana-1859	368	19	tasks	task	NOUN
cana-1859	368	20	.	.	PUNCT
cana-1859	369	1	for	for	ADP
cana-1859	369	2	instance	instance	NOUN
cana-1859	369	3	,	,	PUNCT
cana-1859	369	4	at	at	ADP
cana-1859	369	5	a	a	DET
cana-1859	369	6	dataset	dataset	ADJ
cana-1859	369	7	size	size	NOUN
cana-1859	369	8	of	of	ADP
cana-1859	369	9	240k	240k	NOUN
cana-1859	369	10	,	,	PUNCT
cana-1859	369	11	vmcnn	vmcnn	PROPN
cana-1859	369	12	achieves	achieve	VERB
cana-1859	369	13	an	an	DET
cana-1859	369	14	mae	mae	PROPN
cana-1859	369	15	of	of	ADP
cana-1859	369	16	0.01069	0.01069	NUM
cana-1859	369	17	,	,	PUNCT
cana-1859	369	18	significantly	significantly	ADV
cana-1859	369	19	lower	low	ADJ
cana-1859	369	20	than	than	ADP
cana-1859	369	21	the	the	DET
cana-1859	369	22	next	next	ADJ
cana-1859	369	23	best	good	ADJ
cana-1859	369	24	,	,	PUNCT
cana-1859	369	25	dcnn	dcnn	PROPN
cana-1859	369	26	,	,	PUNCT
cana-1859	369	27	with	with	ADP
cana-1859	369	28	an	an	DET
cana-1859	369	29	mae	mae	PROPN
cana-1859	369	30	of	of	ADP
cana-1859	369	31	0.02414	0.02414	NUM
cana-1859	369	32	.	.	PUNCT
cana-1859	370	1	this	this	DET
cana-1859	370	2	pattern	pattern	NOUN
cana-1859	370	3	of	of	ADP
cana-1859	370	4	vmcnn	vmcnn	NOUN
cana-1859	370	5	's	's	PART
cana-1859	370	6	higher	high	ADJ
cana-1859	370	7	precision	precision	NOUN
cana-1859	370	8	is	be	AUX
cana-1859	370	9	evident	evident	ADJ
cana-1859	370	10	across	across	ADP
cana-1859	370	11	all	all	DET
cana-1859	370	12	dataset	dataset	ADJ
cana-1859	370	13	sizes	size	NOUN
cana-1859	370	14	.	.	PUNCT
cana-1859	371	1	at	at	ADP
cana-1859	371	2	800k	800k	NUM
cana-1859	371	3	,	,	PUNCT
cana-1859	371	4	vmcnn	vmcnn	PROPN
cana-1859	371	5	records	record	VERB
cana-1859	371	6	an	an	DET
cana-1859	371	7	mae	mae	PROPN
cana-1859	371	8	of	of	ADP
cana-1859	371	9	0.01243	0.01243	NUM
cana-1859	371	10	,	,	PUNCT
cana-1859	371	11	whereas	whereas	SCONJ
cana-1859	371	12	the	the	DET
cana-1859	371	13	closest	close	ADJ
cana-1859	371	14	competitor	competitor	NOUN
cana-1859	371	15	,	,	PUNCT
cana-1859	371	16	cnn	cnn	PROPN
cana-1859	371	17	elm	elm	PROPN
cana-1859	371	18	,	,	PUNCT
cana-1859	371	19	has	have	VERB
cana-1859	371	20	an	an	DET
cana-1859	371	21	mae	mae	PROPN
cana-1859	371	22	of	of	ADP
cana-1859	371	23	0.03473	0.03473	NUM
cana-1859	371	24	.	.	PUNCT
cana-1859	372	1	the	the	DET
cana-1859	372	2	lower	low	ADJ
cana-1859	372	3	mae	mae	PROPN
cana-1859	372	4	values	value	NOUN
cana-1859	372	5	in	in	ADP
cana-1859	372	6	vmcnn	vmcnn	PROPN
cana-1859	372	7	can	can	AUX
cana-1859	372	8	be	be	AUX
cana-1859	372	9	attributed	attribute	VERB
cana-1859	372	10	to	to	ADP
cana-1859	372	11	its	its	PRON
cana-1859	372	12	efficient	efficient	ADJ
cana-1859	372	13	optimization	optimization	NOUN
cana-1859	372	14	through	through	ADP
cana-1859	372	15	the	the	DET
cana-1859	372	16	integration	integration	NOUN
cana-1859	372	17	of	of	ADP
cana-1859	372	18	vedic	vedic	ADJ
cana-1859	372	19	mathematical	mathematical	ADJ
cana-1859	372	20	principles	principle	NOUN
cana-1859	372	21	,	,	PUNCT
cana-1859	372	22	enhancing	enhance	VERB
cana-1859	372	23	its	its	PRON
cana-1859	372	24	ability	ability	NOUN
cana-1859	372	25	to	to	PART
cana-1859	372	26	accurately	accurately	ADV
cana-1859	372	27	predict	predict	VERB
cana-1859	372	28	class	class	NOUN
cana-1859	372	29	labels	label	NOUN
cana-1859	372	30	.	.	PUNCT
cana-1859	373	1	for	for	ADP
cana-1859	373	2	example	example	NOUN
cana-1859	373	3	,	,	PUNCT
cana-1859	373	4	at	at	ADP
cana-1859	373	5	1728k	1728k	NOUN
cana-1859	373	6	,	,	PUNCT
cana-1859	373	7	vmcnn	vmcnn	PROPN
cana-1859	373	8	's	's	PART
cana-1859	373	9	mae	mae	PROPN
cana-1859	373	10	is	be	AUX
cana-1859	373	11	just	just	ADV
cana-1859	373	12	0.00611	0.00611	NUM
cana-1859	373	13	,	,	PUNCT
cana-1859	373	14	remarkably	remarkably	ADV
cana-1859	373	15	lower	low	ADJ
cana-1859	373	16	than	than	ADP
cana-1859	373	17	fireclassnet	fireclassnet	NOUN
cana-1859	373	18	's	's	PART
cana-1859	373	19	0.02604	0.02604	NUM
cana-1859	373	20	.	.	PUNCT
cana-1859	374	1	the	the	DET
cana-1859	374	2	impact	impact	NOUN
cana-1859	374	3	of	of	ADP
cana-1859	374	4	these	these	DET
cana-1859	374	5	low	low	ADJ
cana-1859	374	6	mae	mae	PROPN
cana-1859	374	7	values	value	NOUN
cana-1859	374	8	is	be	AUX
cana-1859	374	9	significant	significant	ADJ
cana-1859	374	10	in	in	ADP
cana-1859	374	11	practical	practical	ADJ
cana-1859	374	12	scenarios	scenario	NOUN
cana-1859	374	13	where	where	SCONJ
cana-1859	374	14	precision	precision	NOUN
cana-1859	374	15	is	be	AUX
cana-1859	374	16	critical	critical	ADJ
cana-1859	374	17	.	.	PUNCT
cana-1859	375	1	in	in	ADP
cana-1859	375	2	fields	field	NOUN
cana-1859	375	3	like	like	ADP
cana-1859	375	4	medical	medical	ADJ
cana-1859	375	5	imaging	imaging	NOUN
cana-1859	375	6	,	,	PUNCT
cana-1859	375	7	a	a	DET
cana-1859	375	8	low	low	ADJ
cana-1859	375	9	mae	mae	PROPN
cana-1859	375	10	means	mean	VERB
cana-1859	375	11	that	that	SCONJ
cana-1859	375	12	the	the	DET
cana-1859	375	13	model	model	NOUN
cana-1859	375	14	is	be	AUX
cana-1859	375	15	less	less	ADV
cana-1859	375	16	likely	likely	ADJ
cana-1859	375	17	to	to	PART
cana-1859	375	18	misclassify	misclassify	VERB
cana-1859	375	19	images	image	NOUN
cana-1859	375	20	,	,	PUNCT
cana-1859	375	21	which	which	PRON
cana-1859	375	22	is	be	AUX
cana-1859	375	23	crucial	crucial	ADJ
cana-1859	375	24	for	for	ADP
cana-1859	375	25	accurate	accurate	ADJ
cana-1859	375	26	diagnosis	diagnosis	NOUN
cana-1859	375	27	and	and	CCONJ
cana-1859	375	28	treatment	treatment	NOUN
cana-1859	375	29	planning	planning	NOUN
cana-1859	375	30	.	.	PUNCT
cana-1859	376	1	in	in	ADP
cana-1859	376	2	other	other	ADJ
cana-1859	376	3	areas	area	NOUN
cana-1859	376	4	like	like	ADP
cana-1859	376	5	quality	quality	NOUN
cana-1859	376	6	control	control	NOUN
cana-1859	376	7	in	in	ADP
cana-1859	376	8	manufacturing	manufacturing	NOUN
cana-1859	376	9	,	,	PUNCT
cana-1859	376	10	lower	low	ADJ
cana-1859	376	11	mae	mae	PROPN
cana-1859	376	12	values	value	NOUN
cana-1859	376	13	ensure	ensure	VERB
cana-1859	376	14	that	that	SCONJ
cana-1859	376	15	the	the	DET
cana-1859	376	16	system	system	NOUN
cana-1859	376	17	is	be	AUX
cana-1859	376	18	more	more	ADV
cana-1859	376	19	accurate	accurate	ADJ
cana-1859	376	20	in	in	ADP
cana-1859	376	21	identifying	identify	VERB
cana-1859	376	22	defects	defect	NOUN
cana-1859	376	23	,	,	PUNCT
cana-1859	376	24	thus	thus	ADV
cana-1859	376	25	maintaining	maintain	VERB
cana-1859	376	26	high	high	ADJ
cana-1859	376	27	standards	standard	NOUN
cana-1859	376	28	of	of	ADP
cana-1859	376	29	production	production	NOUN
cana-1859	376	30	.	.	PUNCT
cana-1859	377	1	0.00000	0.00000	NUM
cana-1859	377	2	0.01000	0.01000	NUM
cana-1859	377	3	0.02000	0.02000	NUM
cana-1859	377	4	0.03000	0.03000	NUM
cana-1859	377	5	0.04000	0.04000	NUM
cana-1859	377	6	0.05000	0.05000	NUM
cana-1859	377	7	0.06000	0.06000	NUM
cana-1859	377	8	0.07000	0.07000	NUM
cana-1859	377	9	9	9	NUM
cana-1859	377	10	6	6	NUM
cana-1859	377	11	k	k	NOUN
cana-1859	377	12	2	2	NUM
cana-1859	377	13	4	4	NUM
cana-1859	377	14	0	0	NUM
cana-1859	377	15	k	k	NOUN
cana-1859	377	16	3	3	NUM
cana-1859	377	17	6	6	NUM
cana-1859	377	18	8	8	NUM
cana-1859	377	19	k	k	NOUN
cana-1859	377	20	5	5	NUM
cana-1859	377	21	0	0	NUM
cana-1859	377	22	4	4	NUM
cana-1859	377	23	k	k	NOUN
cana-1859	377	24	6	6	NUM
cana-1859	377	25	0	0	NUM
cana-1859	377	26	0	0	NUM
cana-1859	378	1	k	k	NOUN
cana-1859	378	2	7	7	NUM
cana-1859	378	3	4	4	NUM
cana-1859	378	4	4	4	NUM
cana-1859	378	5	k	k	NOUN
cana-1859	378	6	8	8	NUM
cana-1859	378	7	7	7	NUM
cana-1859	378	8	2	2	NUM
cana-1859	378	9	k	k	NOUN
cana-1859	378	10	1	1	NUM
cana-1859	378	11	0	0	NUM
cana-1859	378	12	0	0	NUM
cana-1859	378	13	8	8	NUM
cana-1859	378	14	k	k	NOUN
cana-1859	378	15	1	1	NUM
cana-1859	378	16	0	0	NUM
cana-1859	378	17	8	8	NUM
cana-1859	378	18	0	0	NUM
cana-1859	379	1	k	k	NOUN
cana-1859	379	2	1	1	NUM
cana-1859	379	3	2	2	NUM
cana-1859	379	4	2	2	NUM
cana-1859	379	5	4	4	NUM
cana-1859	379	6	k	k	NOUN
cana-1859	379	7	1	1	NUM
cana-1859	379	8	3	3	NUM
cana-1859	379	9	6	6	NUM
cana-1859	379	10	0	0	NUM
cana-1859	379	11	k	k	NOUN
cana-1859	379	12	1	1	NUM
cana-1859	379	13	5	5	NUM
cana-1859	379	14	8	8	NUM
cana-1859	379	15	4	4	NUM
cana-1859	379	16	k	k	NOUN
cana-1859	379	17	cnn	cnn	PROPN
cana-1859	379	18	elm	elm	PROPN
cana-1859	380	1	[	[	X
cana-1859	380	2	6	6	NUM
cana-1859	380	3	]	]	X
cana-1859	380	4	dcnn	dcnn	VERB
cana-1859	380	5	[	[	X
cana-1859	380	6	8	8	NUM
cana-1859	380	7	]	]	PUNCT
cana-1859	380	8	fireclassnet	fireclassnet	NOUN
cana-1859	380	9	[	[	X
cana-1859	380	10	15	15	NUM
cana-1859	380	11	]	]	X
cana-1859	380	12	vmcnn	vmcnn	NOUN
cana-1859	380	13	communications	communication	NOUN
cana-1859	380	14	on	on	ADP
cana-1859	380	15	applied	apply	VERB
cana-1859	380	16	nonlinear	nonlinear	ADJ
cana-1859	380	17	analysis	analysis	NOUN
cana-1859	380	18	issn	issn	NOUN
cana-1859	380	19	:	:	PUNCT
cana-1859	380	20	1074	1074	NUM
cana-1859	380	21	-	-	PUNCT
cana-1859	380	22	133x	133x	NUM
cana-1859	380	23	vol	vol	NOUN
cana-1859	380	24	32	32	NUM
cana-1859	380	25	no	no	NOUN
cana-1859	380	26	.	.	NOUN
cana-1859	380	27	2	2	NUM
cana-1859	380	28	(	(	PUNCT
cana-1859	380	29	2025	2025	NUM
cana-1859	380	30	)	)	PUNCT
cana-1859	380	31	662	662	NUM
cana-1859	380	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	380	33	in	in	ADP
cana-1859	380	34	summary	summary	NOUN
cana-1859	380	35	,	,	PUNCT
cana-1859	380	36	the	the	DET
cana-1859	380	37	consistently	consistently	ADV
cana-1859	380	38	low	low	ADJ
cana-1859	380	39	mae	mae	PROPN
cana-1859	380	40	values	value	NOUN
cana-1859	380	41	of	of	ADP
cana-1859	380	42	vmcnn	vmcnn	PROPN
cana-1859	380	43	underline	underline	VERB
cana-1859	380	44	its	its	PRON
cana-1859	380	45	precision	precision	NOUN
cana-1859	380	46	and	and	CCONJ
cana-1859	380	47	reliability	reliability	NOUN
cana-1859	380	48	in	in	ADP
cana-1859	380	49	image	image	NOUN
cana-1859	380	50	classification	classification	NOUN
cana-1859	380	51	tasks	task	NOUN
cana-1859	380	52	.	.	PUNCT
cana-1859	381	1	this	this	DET
cana-1859	381	2	superior	superior	ADJ
cana-1859	381	3	performance	performance	NOUN
cana-1859	381	4	,	,	PUNCT
cana-1859	381	5	resulting	result	VERB
cana-1859	381	6	from	from	ADP
cana-1859	381	7	the	the	DET
cana-1859	381	8	innovative	innovative	ADJ
cana-1859	381	9	application	application	NOUN
cana-1859	381	10	of	of	ADP
cana-1859	381	11	ancient	ancient	ADJ
cana-1859	381	12	mathematical	mathematical	ADJ
cana-1859	381	13	wisdom	wisdom	NOUN
cana-1859	381	14	in	in	ADP
cana-1859	381	15	modern	modern	ADJ
cana-1859	381	16	ai	ai	NOUN
cana-1859	381	17	technology	technology	NOUN
cana-1859	381	18	,	,	PUNCT
cana-1859	381	19	opens	open	VERB
cana-1859	381	20	up	up	ADP
cana-1859	381	21	new	new	ADJ
cana-1859	381	22	possibilities	possibility	NOUN
cana-1859	381	23	for	for	ADP
cana-1859	381	24	highly	highly	ADV
cana-1859	381	25	accurate	accurate	ADJ
cana-1859	381	26	and	and	CCONJ
cana-1859	381	27	dependable	dependable	ADJ
cana-1859	381	28	image	image	NOUN
cana-1859	381	29	classification	classification	NOUN
cana-1859	381	30	in	in	ADP
cana-1859	381	31	various	various	ADJ
cana-1859	381	32	critical	critical	ADJ
cana-1859	381	33	applications	application	NOUN
cana-1859	381	34	.	.	PUNCT
cana-1859	382	1	5	5	X
cana-1859	382	2	.	.	X
cana-1859	382	3	conclusions	conclusion	NOUN
cana-1859	382	4	&	&	CCONJ
cana-1859	382	5	future	future	ADJ
cana-1859	382	6	scope	scope	NOUN
cana-1859	382	7	in	in	ADP
cana-1859	382	8	conclusion	conclusion	NOUN
cana-1859	382	9	,	,	PUNCT
cana-1859	382	10	this	this	DET
cana-1859	382	11	work	work	NOUN
cana-1859	382	12	has	have	AUX
cana-1859	382	13	successfully	successfully	ADV
cana-1859	382	14	demonstrated	demonstrate	VERB
cana-1859	382	15	a	a	DET
cana-1859	382	16	significant	significant	ADJ
cana-1859	382	17	advancement	advancement	NOUN
cana-1859	382	18	in	in	ADP
cana-1859	382	19	the	the	DET
cana-1859	382	20	field	field	NOUN
cana-1859	382	21	of	of	ADP
cana-1859	382	22	image	image	NOUN
cana-1859	382	23	classification	classification	NOUN
cana-1859	382	24	through	through	ADP
cana-1859	382	25	the	the	DET
cana-1859	382	26	integration	integration	NOUN
cana-1859	382	27	of	of	ADP
cana-1859	382	28	vedic	vedic	ADJ
cana-1859	382	29	mathematics	mathematic	NOUN
cana-1859	382	30	into	into	ADP
cana-1859	382	31	convolutional	convolutional	ADJ
cana-1859	382	32	neural	neural	ADJ
cana-1859	382	33	networks	network	NOUN
cana-1859	382	34	(	(	PUNCT
cana-1859	382	35	cnns	cnns	PROPN
cana-1859	382	36	)	)	PUNCT
cana-1859	382	37	.	.	PUNCT
cana-1859	383	1	the	the	DET
cana-1859	383	2	proposed	propose	VERB
cana-1859	383	3	vmcnn	vmcnn	PROPN
cana-1859	383	4	model	model	PROPN
cana-1859	383	5	exhibits	exhibit	VERB
cana-1859	383	6	superior	superior	ADJ
cana-1859	383	7	performance	performance	NOUN
cana-1859	383	8	over	over	ADP
cana-1859	383	9	conventional	conventional	ADJ
cana-1859	383	10	models	model	NOUN
cana-1859	383	11	such	such	ADJ
cana-1859	383	12	as	as	ADP
cana-1859	383	13	cnn	cnn	PROPN
cana-1859	383	14	elm	elm	PROPN
cana-1859	383	15	,	,	PUNCT
cana-1859	383	16	dcnn	dcnn	PROPN
cana-1859	383	17	,	,	PUNCT
cana-1859	383	18	and	and	CCONJ
cana-1859	383	19	fireclassnet	fireclassnet	NOUN
cana-1859	383	20	,	,	PUNCT
cana-1859	383	21	as	as	SCONJ
cana-1859	383	22	evidenced	evidence	VERB
cana-1859	383	23	by	by	ADP
cana-1859	383	24	its	its	PRON
cana-1859	383	25	enhanced	enhanced	ADJ
cana-1859	383	26	precision	precision	NOUN
cana-1859	383	27	,	,	PUNCT
cana-1859	383	28	accuracy	accuracy	NOUN
cana-1859	383	29	,	,	PUNCT
cana-1859	383	30	recall	recall	NOUN
cana-1859	383	31	,	,	PUNCT
cana-1859	383	32	reduced	reduced	ADJ
cana-1859	383	33	delay	delay	NOUN
cana-1859	383	34	,	,	PUNCT
cana-1859	383	35	higher	high	ADJ
cana-1859	383	36	auc	auc	NOUN
cana-1859	383	37	,	,	PUNCT
cana-1859	383	38	and	and	CCONJ
cana-1859	383	39	lower	low	ADJ
cana-1859	383	40	mae	mae	PROPN
cana-1859	383	41	across	across	ADP
cana-1859	383	42	a	a	DET
cana-1859	383	43	diverse	diverse	ADJ
cana-1859	383	44	range	range	NOUN
cana-1859	383	45	of	of	ADP
cana-1859	383	46	datasets	dataset	NOUN
cana-1859	383	47	,	,	PUNCT
cana-1859	383	48	including	include	VERB
cana-1859	383	49	imagenet	imagenet	NOUN
cana-1859	383	50	,	,	PUNCT
cana-1859	383	51	cifar	cifar	ADV
cana-1859	383	52	,	,	PUNCT
cana-1859	383	53	chestxray8	chestxray8	PROPN
cana-1859	383	54	,	,	PUNCT
cana-1859	383	55	and	and	CCONJ
cana-1859	383	56	architectural	architectural	ADJ
cana-1859	383	57	heritage	heritage	NOUN
cana-1859	383	58	datasets	dataset	NOUN
cana-1859	383	59	.	.	PUNCT
cana-1859	384	1	the	the	DET
cana-1859	384	2	incorporation	incorporation	NOUN
cana-1859	384	3	of	of	ADP
cana-1859	384	4	vedic	vedic	ADJ
cana-1859	384	5	mathematical	mathematical	ADJ
cana-1859	384	6	sutras	sutra	NOUN
cana-1859	384	7	,	,	PUNCT
cana-1859	384	8	including	include	VERB
cana-1859	384	9	urdhva	urdhva	NOUN
cana-1859	384	10	-	-	PUNCT
cana-1859	384	11	tiryakbhyam	tiryakbhyam	NOUN
cana-1859	384	12	,	,	PUNCT
cana-1859	384	13	anurupyena	anurupyena	PROPN
cana-1859	384	14	,	,	PUNCT
cana-1859	384	15	and	and	CCONJ
cana-1859	384	16	others	other	NOUN
cana-1859	384	17	,	,	PUNCT
cana-1859	384	18	into	into	ADP
cana-1859	384	19	the	the	DET
cana-1859	384	20	vmcnn	vmcnn	PROPN
cana-1859	384	21	model	model	NOUN
cana-1859	384	22	has	have	AUX
cana-1859	384	23	not	not	PART
cana-1859	384	24	only	only	ADV
cana-1859	384	25	optimized	optimize	VERB
cana-1859	384	26	the	the	DET
cana-1859	384	27	computational	computational	ADJ
cana-1859	384	28	efficiency	efficiency	NOUN
cana-1859	384	29	of	of	ADP
cana-1859	384	30	the	the	DET
cana-1859	384	31	network	network	NOUN
cana-1859	384	32	but	but	CCONJ
cana-1859	384	33	has	have	AUX
cana-1859	384	34	also	also	ADV
cana-1859	384	35	significantly	significantly	ADV
cana-1859	384	36	improved	improve	VERB
cana-1859	384	37	its	its	PRON
cana-1859	384	38	capability	capability	NOUN
cana-1859	384	39	to	to	PART
cana-1859	384	40	process	process	VERB
cana-1859	384	41	complex	complex	ADJ
cana-1859	384	42	image	image	NOUN
cana-1859	384	43	data	datum	NOUN
cana-1859	384	44	with	with	ADP
cana-1859	384	45	remarkable	remarkable	ADJ
cana-1859	384	46	precision	precision	NOUN
cana-1859	384	47	.	.	PUNCT
cana-1859	385	1	the	the	DET
cana-1859	385	2	model	model	NOUN
cana-1859	385	3	's	's	PART
cana-1859	385	4	enhanced	enhanced	ADJ
cana-1859	385	5	performance	performance	NOUN
cana-1859	385	6	is	be	AUX
cana-1859	385	7	particularly	particularly	ADV
cana-1859	385	8	notable	notable	ADJ
cana-1859	385	9	in	in	ADP
cana-1859	385	10	its	its	PRON
cana-1859	385	11	ability	ability	NOUN
cana-1859	385	12	to	to	PART
cana-1859	385	13	accurately	accurately	ADV
cana-1859	385	14	classify	classify	VERB
cana-1859	385	15	images	image	NOUN
cana-1859	385	16	with	with	ADP
cana-1859	385	17	a	a	DET
cana-1859	385	18	higher	high	ADJ
cana-1859	385	19	degree	degree	NOUN
cana-1859	385	20	of	of	ADP
cana-1859	385	21	reliability	reliability	NOUN
cana-1859	385	22	,	,	PUNCT
cana-1859	385	23	a	a	DET
cana-1859	385	24	critical	critical	ADJ
cana-1859	385	25	factor	factor	NOUN
cana-1859	385	26	in	in	ADP
cana-1859	385	27	applications	application	NOUN
cana-1859	385	28	such	such	ADJ
cana-1859	385	29	as	as	ADP
cana-1859	385	30	medical	medical	ADJ
cana-1859	385	31	imaging	imaging	NOUN
cana-1859	385	32	,	,	PUNCT
cana-1859	385	33	autonomous	autonomous	ADJ
cana-1859	385	34	vehicle	vehicle	NOUN
cana-1859	385	35	navigation	navigation	NOUN
cana-1859	385	36	,	,	PUNCT
cana-1859	385	37	and	and	CCONJ
cana-1859	385	38	heritage	heritage	NOUN
cana-1859	385	39	conservation	conservation	NOUN
cana-1859	385	40	.	.	PUNCT
cana-1859	386	1	the	the	DET
cana-1859	386	2	impact	impact	NOUN
cana-1859	386	3	of	of	ADP
cana-1859	386	4	this	this	DET
cana-1859	386	5	work	work	NOUN
cana-1859	386	6	is	be	AUX
cana-1859	386	7	far	far	ADV
cana-1859	386	8	-	-	PUNCT
cana-1859	386	9	reaching	reach	VERB
cana-1859	386	10	.	.	PUNCT
cana-1859	387	1	in	in	ADP
cana-1859	387	2	the	the	DET
cana-1859	387	3	medical	medical	ADJ
cana-1859	387	4	field	field	NOUN
cana-1859	387	5	,	,	PUNCT
cana-1859	387	6	the	the	DET
cana-1859	387	7	improved	improved	ADJ
cana-1859	387	8	accuracy	accuracy	NOUN
cana-1859	387	9	and	and	CCONJ
cana-1859	387	10	reliability	reliability	NOUN
cana-1859	387	11	of	of	ADP
cana-1859	387	12	the	the	DET
cana-1859	387	13	vmcnn	vmcnn	PROPN
cana-1859	387	14	model	model	NOUN
cana-1859	387	15	can	can	AUX
cana-1859	387	16	aid	aid	VERB
cana-1859	387	17	in	in	ADP
cana-1859	387	18	more	more	ADV
cana-1859	387	19	precise	precise	ADJ
cana-1859	387	20	diagnostics	diagnostic	NOUN
cana-1859	387	21	,	,	PUNCT
cana-1859	387	22	potentially	potentially	ADV
cana-1859	387	23	leading	lead	VERB
cana-1859	387	24	to	to	ADP
cana-1859	387	25	better	well	ADJ
cana-1859	387	26	patient	patient	ADJ
cana-1859	387	27	outcomes	outcome	NOUN
cana-1859	387	28	.	.	PUNCT
cana-1859	388	1	in	in	ADP
cana-1859	388	2	the	the	DET
cana-1859	388	3	realm	realm	NOUN
cana-1859	388	4	of	of	ADP
cana-1859	388	5	autonomous	autonomous	ADJ
cana-1859	388	6	vehicles	vehicle	NOUN
cana-1859	388	7	,	,	PUNCT
cana-1859	388	8	the	the	DET
cana-1859	388	9	increased	increase	VERB
cana-1859	388	10	precision	precision	NOUN
cana-1859	388	11	and	and	CCONJ
cana-1859	388	12	reduced	reduce	VERB
cana-1859	388	13	error	error	NOUN
cana-1859	388	14	rates	rate	NOUN
cana-1859	388	15	can	can	AUX
cana-1859	388	16	contribute	contribute	VERB
cana-1859	388	17	to	to	ADP
cana-1859	388	18	safer	safe	ADJ
cana-1859	388	19	navigation	navigation	NOUN
cana-1859	388	20	systems	system	NOUN
cana-1859	388	21	.	.	PUNCT
cana-1859	389	1	moreover	moreover	ADV
cana-1859	389	2	,	,	PUNCT
cana-1859	389	3	in	in	ADP
cana-1859	389	4	the	the	DET
cana-1859	389	5	conservation	conservation	NOUN
cana-1859	389	6	of	of	ADP
cana-1859	389	7	architectural	architectural	ADJ
cana-1859	389	8	heritage	heritage	NOUN
cana-1859	389	9	,	,	PUNCT
cana-1859	389	10	the	the	DET
cana-1859	389	11	model	model	NOUN
cana-1859	389	12	’s	’s	PART
cana-1859	389	13	enhanced	enhance	VERB
cana-1859	389	14	classification	classification	NOUN
cana-1859	389	15	ability	ability	NOUN
cana-1859	389	16	can	can	AUX
cana-1859	389	17	assist	assist	VERB
cana-1859	389	18	in	in	ADP
cana-1859	389	19	the	the	DET
cana-1859	389	20	accurate	accurate	ADJ
cana-1859	389	21	categorization	categorization	NOUN
cana-1859	389	22	and	and	CCONJ
cana-1859	389	23	analysis	analysis	NOUN
cana-1859	389	24	of	of	ADP
cana-1859	389	25	historical	historical	ADJ
cana-1859	389	26	images	image	NOUN
cana-1859	389	27	,	,	PUNCT
cana-1859	389	28	supporting	support	VERB
cana-1859	389	29	preservation	preservation	NOUN
cana-1859	389	30	efforts	effort	NOUN
cana-1859	389	31	.	.	PUNCT
cana-1859	390	1	furthermore	furthermore	ADV
cana-1859	390	2	,	,	PUNCT
cana-1859	390	3	this	this	DET
cana-1859	390	4	research	research	NOUN
cana-1859	390	5	opens	open	VERB
cana-1859	390	6	new	new	ADJ
cana-1859	390	7	avenues	avenue	NOUN
cana-1859	390	8	for	for	ADP
cana-1859	390	9	interdisciplinary	interdisciplinary	ADJ
cana-1859	390	10	collaboration	collaboration	NOUN
cana-1859	390	11	,	,	PUNCT
cana-1859	390	12	blending	blend	VERB
cana-1859	390	13	ancient	ancient	ADJ
cana-1859	390	14	mathematical	mathematical	ADJ
cana-1859	390	15	wisdom	wisdom	NOUN
cana-1859	390	16	with	with	ADP
cana-1859	390	17	contemporary	contemporary	ADJ
cana-1859	390	18	artificial	artificial	ADJ
cana-1859	390	19	intelligence	intelligence	NOUN
cana-1859	390	20	techniques	technique	NOUN
cana-1859	390	21	.	.	PUNCT
cana-1859	391	1	it	it	PRON
cana-1859	391	2	paves	pave	VERB
cana-1859	391	3	the	the	DET
cana-1859	391	4	way	way	NOUN
cana-1859	391	5	for	for	SCONJ
cana-1859	391	6	future	future	ADJ
cana-1859	391	7	studies	study	NOUN
cana-1859	391	8	to	to	PART
cana-1859	391	9	explore	explore	VERB
cana-1859	391	10	the	the	DET
cana-1859	391	11	integration	integration	NOUN
cana-1859	391	12	of	of	ADP
cana-1859	391	13	other	other	ADJ
cana-1859	391	14	traditional	traditional	ADJ
cana-1859	391	15	mathematical	mathematical	ADJ
cana-1859	391	16	concepts	concept	NOUN
cana-1859	391	17	into	into	ADP
cana-1859	391	18	modern	modern	ADJ
cana-1859	391	19	computational	computational	ADJ
cana-1859	391	20	models	model	NOUN
cana-1859	391	21	,	,	PUNCT
cana-1859	391	22	potentially	potentially	ADV
cana-1859	391	23	leading	lead	VERB
cana-1859	391	24	to	to	ADP
cana-1859	391	25	further	further	ADJ
cana-1859	391	26	breakthroughs	breakthrough	NOUN
cana-1859	391	27	in	in	ADP
cana-1859	391	28	ai	ai	PROPN
cana-1859	391	29	and	and	CCONJ
cana-1859	391	30	machine	machine	NOUN
cana-1859	391	31	learning	learning	NOUN
cana-1859	391	32	.	.	PUNCT
cana-1859	392	1	in	in	ADP
cana-1859	392	2	summary	summary	NOUN
cana-1859	392	3	,	,	PUNCT
cana-1859	392	4	the	the	DET
cana-1859	392	5	vmcnn	vmcnn	PROPN
cana-1859	392	6	model	model	NOUN
cana-1859	392	7	stands	stand	VERB
cana-1859	392	8	as	as	ADP
cana-1859	392	9	a	a	DET
cana-1859	392	10	testament	testament	NOUN
cana-1859	392	11	to	to	ADP
cana-1859	392	12	the	the	DET
cana-1859	392	13	potential	potential	NOUN
cana-1859	392	14	of	of	ADP
cana-1859	392	15	combining	combine	VERB
cana-1859	392	16	historical	historical	ADJ
cana-1859	392	17	mathematical	mathematical	ADJ
cana-1859	392	18	knowledge	knowledge	NOUN
cana-1859	392	19	with	with	ADP
cana-1859	392	20	modern	modern	ADJ
cana-1859	392	21	technology	technology	NOUN
cana-1859	392	22	,	,	PUNCT
cana-1859	392	23	leading	lead	VERB
cana-1859	392	24	to	to	ADP
cana-1859	392	25	significant	significant	ADJ
cana-1859	392	26	improvements	improvement	NOUN
cana-1859	392	27	in	in	ADP
cana-1859	392	28	image	image	NOUN
cana-1859	392	29	classification	classification	NOUN
cana-1859	392	30	tasks	task	NOUN
cana-1859	392	31	and	and	CCONJ
cana-1859	392	32	providing	provide	VERB
cana-1859	392	33	a	a	DET
cana-1859	392	34	model	model	NOUN
cana-1859	392	35	that	that	PRON
cana-1859	392	36	is	be	AUX
cana-1859	392	37	not	not	PART
cana-1859	392	38	only	only	ADV
cana-1859	392	39	computationally	computationally	ADV
cana-1859	392	40	efficient	efficient	ADJ
cana-1859	392	41	but	but	CCONJ
cana-1859	392	42	also	also	ADV
cana-1859	392	43	highly	highly	ADV
cana-1859	392	44	accurate	accurate	ADJ
cana-1859	392	45	and	and	CCONJ
cana-1859	392	46	reliable	reliable	ADJ
cana-1859	392	47	across	across	ADP
cana-1859	392	48	various	various	ADJ
cana-1859	392	49	applications	application	NOUN
cana-1859	392	50	.	.	PUNCT
cana-1859	393	1	future	future	ADJ
cana-1859	393	2	scope	scope	NOUN
cana-1859	393	3	the	the	DET
cana-1859	393	4	pioneering	pioneer	VERB
cana-1859	393	5	research	research	NOUN
cana-1859	393	6	presented	present	VERB
cana-1859	393	7	this	this	DET
cana-1859	393	8	work	work	NOUN
cana-1859	393	9	opens	open	VERB
cana-1859	393	10	several	several	ADJ
cana-1859	393	11	exciting	exciting	ADJ
cana-1859	393	12	avenues	avenue	NOUN
cana-1859	393	13	for	for	ADP
cana-1859	393	14	future	future	ADJ
cana-1859	393	15	exploration	exploration	NOUN
cana-1859	393	16	and	and	CCONJ
cana-1859	393	17	development	development	NOUN
cana-1859	393	18	in	in	ADP
cana-1859	393	19	the	the	DET
cana-1859	393	20	realm	realm	NOUN
cana-1859	393	21	of	of	ADP
cana-1859	393	22	artificial	artificial	ADJ
cana-1859	393	23	intelligence	intelligence	NOUN
cana-1859	393	24	and	and	CCONJ
cana-1859	393	25	deep	deep	ADJ
cana-1859	393	26	learning	learning	NOUN
cana-1859	393	27	.	.	PUNCT
cana-1859	394	1	building	build	VERB
cana-1859	394	2	upon	upon	SCONJ
cana-1859	394	3	the	the	DET
cana-1859	394	4	success	success	NOUN
cana-1859	394	5	of	of	ADP
cana-1859	394	6	integrating	integrate	VERB
cana-1859	394	7	vedic	vedic	ADJ
cana-1859	394	8	mathematics	mathematic	NOUN
cana-1859	394	9	with	with	ADP
cana-1859	394	10	cnns	cnn	NOUN
cana-1859	394	11	,	,	PUNCT
cana-1859	394	12	the	the	DET
cana-1859	394	13	future	future	ADJ
cana-1859	394	14	scope	scope	NOUN
cana-1859	394	15	of	of	ADP
cana-1859	394	16	this	this	DET
cana-1859	394	17	work	work	NOUN
cana-1859	394	18	can	can	AUX
cana-1859	394	19	be	be	AUX
cana-1859	394	20	envisioned	envision	VERB
cana-1859	394	21	in	in	ADP
cana-1859	394	22	multiple	multiple	ADJ
cana-1859	394	23	dimensions	dimension	NOUN
cana-1859	394	24	:	:	PUNCT
cana-1859	394	25	communications	communication	NOUN
cana-1859	394	26	on	on	ADP
cana-1859	394	27	applied	apply	VERB
cana-1859	394	28	nonlinear	nonlinear	ADJ
cana-1859	394	29	analysis	analysis	NOUN
cana-1859	394	30	issn	issn	NOUN
cana-1859	394	31	:	:	PUNCT
cana-1859	394	32	1074	1074	NUM
cana-1859	394	33	-	-	PUNCT
cana-1859	394	34	133x	133x	NUM
cana-1859	394	35	vol	vol	NOUN
cana-1859	394	36	32	32	NUM
cana-1859	394	37	no	no	NOUN
cana-1859	394	38	.	.	NOUN
cana-1859	394	39	2	2	NUM
cana-1859	394	40	(	(	PUNCT
cana-1859	394	41	2025	2025	NUM
cana-1859	394	42	)	)	PUNCT
cana-1859	394	43	663	663	NUM
cana-1859	394	44	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	394	45	•	•	NUM
cana-1859	394	46	expanding	expand	VERB
cana-1859	394	47	the	the	DET
cana-1859	394	48	application	application	NOUN
cana-1859	394	49	domain	domain	NOUN
cana-1859	394	50	:	:	PUNCT
cana-1859	394	51	the	the	DET
cana-1859	394	52	current	current	ADJ
cana-1859	394	53	success	success	NOUN
cana-1859	394	54	of	of	ADP
cana-1859	394	55	vmcnn	vmcnn	NOUN
cana-1859	394	56	in	in	ADP
cana-1859	394	57	image	image	NOUN
cana-1859	394	58	classification	classification	NOUN
cana-1859	394	59	can	can	AUX
cana-1859	394	60	be	be	AUX
cana-1859	394	61	extended	extend	VERB
cana-1859	394	62	to	to	ADP
cana-1859	394	63	other	other	ADJ
cana-1859	394	64	domains	domain	NOUN
cana-1859	394	65	like	like	ADP
cana-1859	394	66	natural	natural	ADJ
cana-1859	394	67	language	language	NOUN
cana-1859	394	68	processing	processing	NOUN
cana-1859	394	69	,	,	PUNCT
cana-1859	394	70	speech	speech	NOUN
cana-1859	394	71	recognition	recognition	NOUN
cana-1859	394	72	,	,	PUNCT
cana-1859	394	73	and	and	CCONJ
cana-1859	394	74	video	video	NOUN
cana-1859	394	75	analysis	analysis	NOUN
cana-1859	394	76	.	.	PUNCT
cana-1859	395	1	investigating	investigate	VERB
cana-1859	395	2	the	the	DET
cana-1859	395	3	applicability	applicability	NOUN
cana-1859	395	4	and	and	CCONJ
cana-1859	395	5	effectiveness	effectiveness	NOUN
cana-1859	395	6	of	of	ADP
cana-1859	395	7	vedic	vedic	ADJ
cana-1859	395	8	mathematics	mathematic	NOUN
cana-1859	395	9	in	in	ADP
cana-1859	395	10	these	these	DET
cana-1859	395	11	areas	area	NOUN
cana-1859	395	12	could	could	AUX
cana-1859	395	13	lead	lead	VERB
cana-1859	395	14	to	to	ADP
cana-1859	395	15	substantial	substantial	ADJ
cana-1859	395	16	improvements	improvement	NOUN
cana-1859	395	17	in	in	ADP
cana-1859	395	18	various	various	ADJ
cana-1859	395	19	ai	ai	ADJ
cana-1859	395	20	applications	application	NOUN
cana-1859	395	21	.	.	PUNCT
cana-1859	396	1	•	•	NUM
cana-1859	396	2	optimization	optimization	NOUN
cana-1859	396	3	for	for	ADP
cana-1859	396	4	real	real	ADJ
cana-1859	396	5	-	-	PUNCT
cana-1859	396	6	time	time	NOUN
cana-1859	396	7	processing	processing	NOUN
cana-1859	396	8	:	:	PUNCT
cana-1859	396	9	while	while	SCONJ
cana-1859	396	10	vmcnn	vmcnn	PROPN
cana-1859	396	11	shows	show	VERB
cana-1859	396	12	promising	promise	VERB
cana-1859	396	13	results	result	NOUN
cana-1859	396	14	in	in	ADP
cana-1859	396	15	accuracy	accuracy	NOUN
cana-1859	396	16	and	and	CCONJ
cana-1859	396	17	efficiency	efficiency	NOUN
cana-1859	396	18	,	,	PUNCT
cana-1859	396	19	optimizing	optimize	VERB
cana-1859	396	20	the	the	DET
cana-1859	396	21	model	model	NOUN
cana-1859	396	22	for	for	ADP
cana-1859	396	23	real	real	ADJ
cana-1859	396	24	-	-	PUNCT
cana-1859	396	25	time	time	NOUN
cana-1859	396	26	processing	processing	NOUN
cana-1859	396	27	applications	application	NOUN
cana-1859	396	28	,	,	PUNCT
cana-1859	396	29	such	such	ADJ
cana-1859	396	30	as	as	ADP
cana-1859	396	31	real	real	ADJ
cana-1859	396	32	-	-	PUNCT
cana-1859	396	33	time	time	NOUN
cana-1859	396	34	video	video	NOUN
cana-1859	396	35	analysis	analysis	NOUN
cana-1859	396	36	or	or	CCONJ
cana-1859	396	37	on	on	ADP
cana-1859	396	38	-	-	PUNCT
cana-1859	396	39	device	device	NOUN
cana-1859	396	40	processing	processing	NOUN
cana-1859	396	41	in	in	ADP
cana-1859	396	42	mobile	mobile	ADJ
cana-1859	396	43	applications	application	NOUN
cana-1859	396	44	,	,	PUNCT
cana-1859	396	45	presents	present	VERB
cana-1859	396	46	a	a	DET
cana-1859	396	47	valuable	valuable	ADJ
cana-1859	396	48	direction	direction	NOUN
cana-1859	396	49	for	for	ADP
cana-1859	396	50	future	future	ADJ
cana-1859	396	51	research	research	NOUN
cana-1859	396	52	.	.	PUNCT
cana-1859	397	1	•	•	NUM
cana-1859	397	2	integration	integration	NOUN
cana-1859	397	3	with	with	ADP
cana-1859	397	4	other	other	ADJ
cana-1859	397	5	mathematical	mathematical	ADJ
cana-1859	397	6	concepts	concept	NOUN
cana-1859	397	7	:	:	PUNCT
cana-1859	397	8	exploring	explore	VERB
cana-1859	397	9	the	the	DET
cana-1859	397	10	integration	integration	NOUN
cana-1859	397	11	of	of	ADP
cana-1859	397	12	other	other	ADJ
cana-1859	397	13	ancient	ancient	ADJ
cana-1859	397	14	or	or	CCONJ
cana-1859	397	15	non	non	ADJ
cana-1859	397	16	-	-	ADJ
cana-1859	397	17	conventional	conventional	ADJ
cana-1859	397	18	mathematical	mathematical	ADJ
cana-1859	397	19	techniques	technique	NOUN
cana-1859	397	20	with	with	ADP
cana-1859	397	21	modern	modern	ADJ
cana-1859	397	22	neural	neural	ADJ
cana-1859	397	23	network	network	NOUN
cana-1859	397	24	architectures	architecture	NOUN
cana-1859	397	25	could	could	AUX
cana-1859	397	26	lead	lead	VERB
cana-1859	397	27	to	to	ADP
cana-1859	397	28	further	further	ADJ
cana-1859	397	29	breakthroughs	breakthrough	NOUN
cana-1859	397	30	.	.	PUNCT
cana-1859	398	1	this	this	DET
cana-1859	398	2	interdisciplinary	interdisciplinary	ADJ
cana-1859	398	3	approach	approach	NOUN
cana-1859	398	4	may	may	AUX
cana-1859	398	5	uncover	uncover	VERB
cana-1859	398	6	new	new	ADJ
cana-1859	398	7	ways	way	NOUN
cana-1859	398	8	to	to	PART
cana-1859	398	9	enhance	enhance	VERB
cana-1859	398	10	computational	computational	ADJ
cana-1859	398	11	efficiency	efficiency	NOUN
cana-1859	398	12	and	and	CCONJ
cana-1859	398	13	model	model	NOUN
cana-1859	398	14	performance	performance	NOUN
cana-1859	398	15	.	.	PUNCT
cana-1859	399	1	•	•	NOUN
cana-1859	399	2	scaling	scale	VERB
cana-1859	399	3	to	to	ADP
cana-1859	399	4	larger	large	ADJ
cana-1859	399	5	datasets	dataset	NOUN
cana-1859	399	6	:	:	PUNCT
cana-1859	399	7	testing	testing	NOUN
cana-1859	399	8	and	and	CCONJ
cana-1859	399	9	refining	refining	NOUN
cana-1859	399	10	vmcnn	vmcnn	NOUN
cana-1859	399	11	on	on	ADP
cana-1859	399	12	larger	large	ADJ
cana-1859	399	13	and	and	CCONJ
cana-1859	399	14	more	more	ADV
cana-1859	399	15	diverse	diverse	ADJ
cana-1859	399	16	datasets	dataset	NOUN
cana-1859	399	17	can	can	AUX
cana-1859	399	18	provide	provide	VERB
cana-1859	399	19	deeper	deep	ADJ
cana-1859	399	20	insights	insight	NOUN
cana-1859	399	21	into	into	ADP
cana-1859	399	22	its	its	PRON
cana-1859	399	23	scalability	scalability	NOUN
cana-1859	399	24	and	and	CCONJ
cana-1859	399	25	robustness	robustness	NOUN
cana-1859	399	26	.	.	PUNCT
cana-1859	400	1	it	it	PRON
cana-1859	400	2	would	would	AUX
cana-1859	400	3	be	be	AUX
cana-1859	400	4	interesting	interesting	ADJ
cana-1859	400	5	to	to	PART
cana-1859	400	6	see	see	VERB
cana-1859	400	7	how	how	SCONJ
cana-1859	400	8	the	the	DET
cana-1859	400	9	model	model	NOUN
cana-1859	400	10	performs	perform	VERB
cana-1859	400	11	with	with	ADP
cana-1859	400	12	exponentially	exponentially	ADV
cana-1859	400	13	larger	large	ADJ
cana-1859	400	14	datasets	dataset	NOUN
cana-1859	400	15	prevalent	prevalent	ADJ
cana-1859	400	16	in	in	ADP
cana-1859	400	17	industries	industry	NOUN
cana-1859	400	18	like	like	ADP
cana-1859	400	19	social	social	ADJ
cana-1859	400	20	media	medium	NOUN
cana-1859	400	21	,	,	PUNCT
cana-1859	400	22	astronomy	astronomy	NOUN
cana-1859	400	23	,	,	PUNCT
cana-1859	400	24	or	or	CCONJ
cana-1859	400	25	genomics	genomics	NOUN
cana-1859	400	26	.	.	PUNCT
cana-1859	401	1	•	•	NUM
cana-1859	401	2	hardware	hardware	NOUN
cana-1859	401	3	optimization	optimization	NOUN
cana-1859	401	4	:	:	PUNCT
cana-1859	401	5	custom	custom	NOUN
cana-1859	401	6	hardware	hardware	NOUN
cana-1859	401	7	or	or	CCONJ
cana-1859	401	8	asics	asics	NOUN
cana-1859	401	9	(	(	PUNCT
cana-1859	401	10	application	application	NOUN
cana-1859	401	11	-	-	PUNCT
cana-1859	401	12	specific	specific	ADJ
cana-1859	401	13	integrated	integrate	VERB
cana-1859	401	14	circuits	circuit	NOUN
cana-1859	401	15	)	)	PUNCT
cana-1859	401	16	designed	design	VERB
cana-1859	401	17	to	to	PART
cana-1859	401	18	specifically	specifically	ADV
cana-1859	401	19	leverage	leverage	VERB
cana-1859	401	20	the	the	DET
cana-1859	401	21	computational	computational	ADJ
cana-1859	401	22	patterns	pattern	NOUN
cana-1859	401	23	of	of	ADP
cana-1859	401	24	vedic	vedic	ADJ
cana-1859	401	25	mathematics	mathematic	NOUN
cana-1859	401	26	could	could	AUX
cana-1859	401	27	significantly	significantly	ADV
cana-1859	401	28	boost	boost	VERB
cana-1859	401	29	the	the	DET
cana-1859	401	30	performance	performance	NOUN
cana-1859	401	31	of	of	ADP
cana-1859	401	32	vmcnn	vmcnn	PROPN
cana-1859	401	33	.	.	PUNCT
cana-1859	402	1	research	research	NOUN
cana-1859	402	2	in	in	ADP
cana-1859	402	3	this	this	DET
cana-1859	402	4	direction	direction	NOUN
cana-1859	402	5	could	could	AUX
cana-1859	402	6	lead	lead	VERB
cana-1859	402	7	to	to	ADP
cana-1859	402	8	more	more	ADV
cana-1859	402	9	efficient	efficient	ADJ
cana-1859	402	10	and	and	CCONJ
cana-1859	402	11	specialized	specialized	ADJ
cana-1859	402	12	ai	ai	PROPN
cana-1859	402	13	hardware	hardware	NOUN
cana-1859	402	14	.	.	PUNCT
cana-1859	403	1	•	•	NUM
cana-1859	403	2	quantum	quantum	NOUN
cana-1859	403	3	computing	computing	NOUN
cana-1859	403	4	integration	integration	NOUN
cana-1859	403	5	:	:	PUNCT
cana-1859	403	6	as	as	ADP
cana-1859	403	7	quantum	quantum	NOUN
cana-1859	403	8	computing	computing	NOUN
cana-1859	403	9	matures	mature	NOUN
cana-1859	403	10	,	,	PUNCT
cana-1859	403	11	investigating	investigate	VERB
cana-1859	403	12	how	how	SCONJ
cana-1859	403	13	vedic	vedic	ADJ
cana-1859	403	14	mathematics	mathematics	NOUN
cana-1859	403	15	principles	principle	NOUN
cana-1859	403	16	can	can	AUX
cana-1859	403	17	be	be	AUX
cana-1859	403	18	integrated	integrate	VERB
cana-1859	403	19	into	into	ADP
cana-1859	403	20	quantum	quantum	ADJ
cana-1859	403	21	algorithms	algorithm	NOUN
cana-1859	403	22	for	for	ADP
cana-1859	403	23	neural	neural	ADJ
cana-1859	403	24	network	network	NOUN
cana-1859	403	25	models	model	NOUN
cana-1859	403	26	could	could	AUX
cana-1859	403	27	be	be	AUX
cana-1859	403	28	a	a	DET
cana-1859	403	29	groundbreaking	groundbreaking	ADJ
cana-1859	403	30	area	area	NOUN
cana-1859	403	31	of	of	ADP
cana-1859	403	32	research	research	NOUN
cana-1859	403	33	,	,	PUNCT
cana-1859	403	34	potentially	potentially	ADV
cana-1859	403	35	revolutionizing	revolutionize	VERB
cana-1859	403	36	computational	computational	ADJ
cana-1859	403	37	speed	speed	NOUN
cana-1859	403	38	and	and	CCONJ
cana-1859	403	39	efficiency	efficiency	NOUN
cana-1859	403	40	.	.	PUNCT
cana-1859	404	1	•	•	NUM
cana-1859	404	2	algorithmic	algorithmic	ADJ
cana-1859	404	3	improvements	improvement	NOUN
cana-1859	404	4	and	and	CCONJ
cana-1859	404	5	variations	variation	NOUN
cana-1859	404	6	:	:	PUNCT
cana-1859	404	7	developing	develop	VERB
cana-1859	404	8	new	new	ADJ
cana-1859	404	9	algorithms	algorithm	NOUN
cana-1859	404	10	or	or	CCONJ
cana-1859	404	11	variations	variation	NOUN
cana-1859	404	12	of	of	ADP
cana-1859	404	13	vmcnn	vmcnn	NOUN
cana-1859	404	14	that	that	PRON
cana-1859	404	15	further	far	ADV
cana-1859	404	16	refine	refine	VERB
cana-1859	404	17	the	the	DET
cana-1859	404	18	use	use	NOUN
cana-1859	404	19	of	of	ADP
cana-1859	404	20	vedic	vedic	ADJ
cana-1859	404	21	mathematics	mathematic	NOUN
cana-1859	404	22	,	,	PUNCT
cana-1859	404	23	perhaps	perhaps	ADV
cana-1859	404	24	through	through	ADP
cana-1859	404	25	deeper	deep	ADJ
cana-1859	404	26	integration	integration	NOUN
cana-1859	404	27	or	or	CCONJ
cana-1859	404	28	more	more	ADV
cana-1859	404	29	sophisticated	sophisticated	ADJ
cana-1859	404	30	application	application	NOUN
cana-1859	404	31	of	of	ADP
cana-1859	404	32	the	the	DET
cana-1859	404	33	sutras	sutra	NOUN
cana-1859	404	34	,	,	PUNCT
cana-1859	404	35	would	would	AUX
cana-1859	404	36	be	be	AUX
cana-1859	404	37	a	a	DET
cana-1859	404	38	logical	logical	ADJ
cana-1859	404	39	progression	progression	NOUN
cana-1859	404	40	of	of	ADP
cana-1859	404	41	this	this	DET
cana-1859	404	42	research	research	NOUN
cana-1859	404	43	.	.	PUNCT
cana-1859	405	1	•	•	NUM
cana-1859	405	2	interdisciplinary	interdisciplinary	ADJ
cana-1859	405	3	research	research	NOUN
cana-1859	405	4	and	and	CCONJ
cana-1859	405	5	collaboration	collaboration	NOUN
cana-1859	405	6	:	:	PUNCT
cana-1859	405	7	fostering	foster	VERB
cana-1859	405	8	collaborations	collaboration	NOUN
cana-1859	405	9	across	across	ADP
cana-1859	405	10	disciplines	discipline	NOUN
cana-1859	405	11	like	like	ADP
cana-1859	405	12	mathematics	mathematic	NOUN
cana-1859	405	13	,	,	PUNCT
cana-1859	405	14	computer	computer	NOUN
cana-1859	405	15	science	science	NOUN
cana-1859	405	16	,	,	PUNCT
cana-1859	405	17	and	and	CCONJ
cana-1859	405	18	cognitive	cognitive	ADJ
cana-1859	405	19	science	science	NOUN
cana-1859	405	20	to	to	PART
cana-1859	405	21	explore	explore	VERB
cana-1859	405	22	new	new	ADJ
cana-1859	405	23	concepts	concept	NOUN
cana-1859	405	24	and	and	CCONJ
cana-1859	405	25	ideas	idea	NOUN
cana-1859	405	26	can	can	AUX
cana-1859	405	27	lead	lead	VERB
cana-1859	405	28	to	to	ADP
cana-1859	405	29	innovative	innovative	ADJ
cana-1859	405	30	approaches	approach	NOUN
cana-1859	405	31	in	in	ADP
cana-1859	405	32	ai	ai	PROPN
cana-1859	405	33	model	model	NOUN
cana-1859	405	34	development	development	NOUN
cana-1859	405	35	.	.	PUNCT
cana-1859	406	1	•	•	NUM
cana-1859	406	2	ethical	ethical	ADJ
cana-1859	406	3	ai	ai	NOUN
cana-1859	406	4	and	and	CCONJ
cana-1859	406	5	bias	bias	NOUN
cana-1859	406	6	mitigation	mitigation	NOUN
cana-1859	406	7	:	:	PUNCT
cana-1859	406	8	future	future	ADJ
cana-1859	406	9	research	research	NOUN
cana-1859	406	10	could	could	AUX
cana-1859	406	11	also	also	ADV
cana-1859	406	12	focus	focus	VERB
cana-1859	406	13	on	on	ADP
cana-1859	406	14	ensuring	ensure	VERB
cana-1859	406	15	that	that	SCONJ
cana-1859	406	16	models	model	NOUN
cana-1859	406	17	like	like	ADP
cana-1859	406	18	vmcnn	vmcnn	PROPN
cana-1859	406	19	are	be	AUX
cana-1859	406	20	developed	develop	VERB
cana-1859	406	21	with	with	ADP
cana-1859	406	22	ethical	ethical	ADJ
cana-1859	406	23	considerations	consideration	NOUN
cana-1859	406	24	in	in	ADP
cana-1859	406	25	mind	mind	NOUN
cana-1859	406	26	,	,	PUNCT
cana-1859	406	27	particularly	particularly	ADV
cana-1859	406	28	in	in	ADP
cana-1859	406	29	terms	term	NOUN
cana-1859	406	30	of	of	ADP
cana-1859	406	31	bias	bias	NOUN
cana-1859	406	32	mitigation	mitigation	NOUN
cana-1859	406	33	and	and	CCONJ
cana-1859	406	34	fairness	fairness	NOUN
cana-1859	406	35	in	in	ADP
cana-1859	406	36	ai	ai	PROPN
cana-1859	406	37	.	.	PUNCT
cana-1859	407	1	communications	communication	NOUN
cana-1859	407	2	on	on	ADP
cana-1859	407	3	applied	apply	VERB
cana-1859	407	4	nonlinear	nonlinear	ADJ
cana-1859	407	5	analysis	analysis	NOUN
cana-1859	407	6	issn	issn	NOUN
cana-1859	407	7	:	:	PUNCT
cana-1859	407	8	1074	1074	NUM
cana-1859	407	9	-	-	PUNCT
cana-1859	407	10	133x	133x	NUM
cana-1859	407	11	vol	vol	NOUN
cana-1859	407	12	32	32	NUM
cana-1859	407	13	no	no	NOUN
cana-1859	407	14	.	.	NOUN
cana-1859	407	15	2	2	NUM
cana-1859	407	16	(	(	PUNCT
cana-1859	407	17	2025	2025	NUM
cana-1859	407	18	)	)	PUNCT
cana-1859	408	1	664	664	NUM
cana-1859	408	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	408	3	•	•	NUM
cana-1859	408	4	broader	broad	ADJ
cana-1859	408	5	implications	implication	NOUN
cana-1859	408	6	for	for	ADP
cana-1859	408	7	ai	ai	PROPN
cana-1859	408	8	education	education	NOUN
cana-1859	408	9	:	:	PUNCT
cana-1859	408	10	introducing	introduce	VERB
cana-1859	408	11	the	the	DET
cana-1859	408	12	concepts	concept	NOUN
cana-1859	408	13	behind	behind	ADP
cana-1859	408	14	vmcnn	vmcnn	PROPN
cana-1859	408	15	in	in	ADP
cana-1859	408	16	educational	educational	ADJ
cana-1859	408	17	curricula	curricula	NOUN
cana-1859	408	18	can	can	AUX
cana-1859	408	19	inspire	inspire	VERB
cana-1859	408	20	future	future	ADJ
cana-1859	408	21	ai	ai	PROPN
cana-1859	408	22	practitioners	practitioner	NOUN
cana-1859	408	23	and	and	CCONJ
cana-1859	408	24	researchers	researcher	NOUN
cana-1859	408	25	,	,	PUNCT
cana-1859	408	26	showcasing	showcase	VERB
cana-1859	408	27	the	the	DET
cana-1859	408	28	value	value	NOUN
cana-1859	408	29	of	of	ADP
cana-1859	408	30	integrating	integrate	VERB
cana-1859	408	31	diverse	diverse	ADJ
cana-1859	408	32	knowledge	knowledge	NOUN
cana-1859	408	33	systems	system	NOUN
cana-1859	408	34	into	into	ADP
cana-1859	408	35	technological	technological	ADJ
cana-1859	408	36	innovation	innovation	NOUN
cana-1859	408	37	operations	operation	NOUN
cana-1859	408	38	.	.	PUNCT
cana-1859	409	1	in	in	ADP
cana-1859	409	2	summary	summary	NOUN
cana-1859	409	3	,	,	PUNCT
cana-1859	409	4	the	the	DET
cana-1859	409	5	vmcnn	vmcnn	PROPN
cana-1859	409	6	model	model	VERB
cana-1859	409	7	not	not	PART
cana-1859	409	8	only	only	ADV
cana-1859	409	9	marks	mark	VERB
cana-1859	409	10	a	a	DET
cana-1859	409	11	significant	significant	ADJ
cana-1859	409	12	step	step	NOUN
cana-1859	409	13	forward	forward	ADV
cana-1859	409	14	in	in	ADP
cana-1859	409	15	the	the	DET
cana-1859	409	16	field	field	NOUN
cana-1859	409	17	of	of	ADP
cana-1859	409	18	ai	ai	NOUN
cana-1859	409	19	but	but	CCONJ
cana-1859	409	20	also	also	ADV
cana-1859	409	21	sets	set	VERB
cana-1859	409	22	the	the	DET
cana-1859	409	23	stage	stage	NOUN
cana-1859	409	24	for	for	ADP
cana-1859	409	25	a	a	DET
cana-1859	409	26	multitude	multitude	NOUN
cana-1859	409	27	of	of	ADP
cana-1859	409	28	research	research	NOUN
cana-1859	409	29	paths	path	NOUN
cana-1859	409	30	.	.	PUNCT
cana-1859	410	1	the	the	DET
cana-1859	410	2	potential	potential	NOUN
cana-1859	410	3	for	for	ADP
cana-1859	410	4	its	its	PRON
cana-1859	410	5	application	application	NOUN
cana-1859	410	6	and	and	CCONJ
cana-1859	410	7	development	development	NOUN
cana-1859	410	8	is	be	AUX
cana-1859	410	9	vast	vast	ADJ
cana-1859	410	10	,	,	PUNCT
cana-1859	410	11	promising	promise	VERB
cana-1859	410	12	a	a	DET
cana-1859	410	13	future	future	NOUN
cana-1859	410	14	where	where	SCONJ
cana-1859	410	15	ancient	ancient	ADJ
cana-1859	410	16	wisdom	wisdom	NOUN
cana-1859	410	17	and	and	CCONJ
cana-1859	410	18	modern	modern	ADJ
cana-1859	410	19	technology	technology	NOUN
cana-1859	410	20	continue	continue	VERB
cana-1859	410	21	to	to	PART
cana-1859	410	22	synergize	synergize	VERB
cana-1859	410	23	,	,	PUNCT
cana-1859	410	24	pushing	push	VERB
cana-1859	410	25	the	the	DET
cana-1859	410	26	boundaries	boundary	NOUN
cana-1859	410	27	of	of	ADP
cana-1859	410	28	what	what	PRON
cana-1859	410	29	is	be	AUX
cana-1859	410	30	possible	possible	ADJ
cana-1859	410	31	in	in	ADP
cana-1859	410	32	ai	ai	NOUN
cana-1859	410	33	for	for	ADP
cana-1859	410	34	different	different	ADJ
cana-1859	410	35	use	use	NOUN
cana-1859	410	36	cases	case	NOUN
cana-1859	410	37	.	.	PUNCT
cana-1859	411	1	financing	financing	NOUN
cana-1859	411	2	and	and	CCONJ
cana-1859	411	3	declaration	declaration	NOUN
cana-1859	411	4	of	of	ADP
cana-1859	411	5	conflict	conflict	NOUN
cana-1859	411	6	of	of	ADP
cana-1859	411	7	interests	interest	NOUN
cana-1859	411	8	:	:	PUNCT
cana-1859	411	9	the	the	DET
cana-1859	411	10	authors	author	NOUN
cana-1859	411	11	do	do	AUX
cana-1859	411	12	n’t	not	PART
cana-1859	411	13	have	have	VERB
cana-1859	411	14	any	any	DET
cana-1859	411	15	conflict	conflict	NOUN
cana-1859	411	16	of	of	ADP
cana-1859	411	17	interest	interest	NOUN
cana-1859	411	18	among	among	ADP
cana-1859	411	19	them	they	PRON
cana-1859	411	20	.	.	PUNCT
cana-1859	412	1	the	the	DET
cana-1859	412	2	authors	author	NOUN
cana-1859	412	3	certify	certify	VERB
cana-1859	412	4	that	that	SCONJ
cana-1859	412	5	they	they	PRON
cana-1859	412	6	have	have	VERB
cana-1859	412	7	no	no	DET
cana-1859	412	8	affiliations	affiliation	NOUN
cana-1859	412	9	with	with	ADP
cana-1859	412	10	or	or	CCONJ
cana-1859	412	11	involvement	involvement	NOUN
cana-1859	412	12	in	in	ADP
cana-1859	412	13	any	any	DET
cana-1859	412	14	organization	organization	NOUN
cana-1859	412	15	or	or	CCONJ
cana-1859	412	16	entity	entity	NOUN
cana-1859	412	17	with	with	ADP
cana-1859	412	18	any	any	DET
cana-1859	412	19	financial	financial	ADJ
cana-1859	412	20	interest	interest	NOUN
cana-1859	412	21	or	or	CCONJ
cana-1859	412	22	non	non	ADJ
cana-1859	412	23	-	-	ADJ
cana-1859	412	24	financial	financial	ADJ
cana-1859	412	25	interest	interest	NOUN
cana-1859	412	26	(	(	PUNCT
cana-1859	412	27	such	such	ADJ
cana-1859	412	28	as	as	ADP
cana-1859	412	29	personal	personal	ADJ
cana-1859	412	30	or	or	CCONJ
cana-1859	412	31	professional	professional	ADJ
cana-1859	412	32	relationships	relationship	NOUN
cana-1859	412	33	,	,	PUNCT
cana-1859	412	34	affiliations	affiliation	NOUN
cana-1859	412	35	,	,	PUNCT
cana-1859	412	36	knowledge	knowledge	NOUN
cana-1859	412	37	,	,	PUNCT
cana-1859	412	38	or	or	CCONJ
cana-1859	412	39	beliefs	belief	NOUN
cana-1859	412	40	)	)	PUNCT
cana-1859	412	41	in	in	ADP
cana-1859	412	42	the	the	DET
cana-1859	412	43	subject	subject	NOUN
cana-1859	412	44	matter	matter	NOUN
cana-1859	412	45	or	or	CCONJ
cana-1859	412	46	materials	material	NOUN
cana-1859	412	47	discussed	discuss	VERB
cana-1859	412	48	in	in	ADP
cana-1859	412	49	this	this	DET
cana-1859	412	50	manuscript	manuscript	NOUN
cana-1859	412	51	.	.	PUNCT
cana-1859	413	1	ethical	ethical	ADJ
cana-1859	413	2	approval	approval	NOUN
cana-1859	413	3	:	:	PUNCT
cana-1859	413	4	this	this	DET
cana-1859	413	5	article	article	NOUN
cana-1859	413	6	does	do	AUX
cana-1859	413	7	not	not	PART
cana-1859	413	8	contain	contain	VERB
cana-1859	413	9	any	any	DET
cana-1859	413	10	studies	study	NOUN
cana-1859	413	11	with	with	ADP
cana-1859	413	12	human	human	ADJ
cana-1859	413	13	participants	participant	NOUN
cana-1859	413	14	or	or	CCONJ
cana-1859	413	15	animals	animal	NOUN
cana-1859	413	16	performed	perform	VERB
cana-1859	413	17	by	by	ADP
cana-1859	413	18	any	any	PRON
cana-1859	413	19	of	of	ADP
cana-1859	413	20	the	the	DET
cana-1859	413	21	authors	author	NOUN
cana-1859	413	22	.	.	PUNCT
cana-1859	414	1	6	6	NUM
cana-1859	414	2	.	.	NUM
cana-1859	414	3	references	reference	NOUN
cana-1859	414	4	[	[	X
cana-1859	414	5	1	1	NUM
cana-1859	414	6	]	]	X
cana-1859	414	7	huang	huang	PROPN
cana-1859	414	8	,	,	PUNCT
cana-1859	414	9	jd	jd	PROPN
cana-1859	414	10	.	.	PROPN
cana-1859	414	11	,	,	PUNCT
cana-1859	414	12	cheng	cheng	PROPN
cana-1859	414	13	,	,	PUNCT
cana-1859	414	14	g.	g.	PROPN
cana-1859	414	15	,	,	PUNCT
cana-1859	414	16	zhang	zhang	PROPN
cana-1859	414	17	,	,	PUNCT
cana-1859	414	18	j.	j.	PROPN
cana-1859	414	19	et	et	PROPN
cana-1859	414	20	al	al	PROPN
cana-1859	414	21	.	.	PROPN
cana-1859	414	22	recognition	recognition	PROPN
cana-1859	414	23	method	method	NOUN
cana-1859	414	24	for	for	ADP
cana-1859	414	25	stone	stone	NOUN
cana-1859	414	26	carved	carve	VERB
cana-1859	414	27	calligraphy	calligraphy	NOUN
cana-1859	414	28	characters	character	NOUN
cana-1859	414	29	based	base	VERB
cana-1859	414	30	on	on	ADP
cana-1859	414	31	a	a	DET
cana-1859	414	32	convolutional	convolutional	ADJ
cana-1859	414	33	neural	neural	ADJ
cana-1859	414	34	network	network	NOUN
cana-1859	414	35	.	.	PUNCT
cana-1859	415	1	neural	neural	ADJ
cana-1859	415	2	comput	comput	PROPN
cana-1859	415	3	&	&	CCONJ
cana-1859	415	4	applic	applic	PROPN
cana-1859	415	5	35	35	NUM
cana-1859	415	6	,	,	PUNCT
cana-1859	415	7	8723–8732	8723–8732	NUM
cana-1859	415	8	(	(	PUNCT
cana-1859	415	9	2023	2023	NUM
cana-1859	415	10	)	)	PUNCT
cana-1859	415	11	.	.	PUNCT
cana-1859	416	1	[	[	X
cana-1859	416	2	2	2	NUM
cana-1859	416	3	]	]	X
cana-1859	416	4	zhang	zhang	PROPN
cana-1859	416	5	,	,	PUNCT
cana-1859	416	6	j.	j.	PROPN
cana-1859	416	7	,	,	PUNCT
cana-1859	416	8	li	li	PROPN
cana-1859	416	9	,	,	PUNCT
cana-1859	416	10	c.	c.	PROPN
cana-1859	416	11	,	,	PUNCT
cana-1859	416	12	yin	yin	PROPN
cana-1859	416	13	,	,	PUNCT
cana-1859	416	14	y.	y.	PROPN
cana-1859	416	15	et	et	PROPN
cana-1859	416	16	al	al	PROPN
cana-1859	416	17	.	.	PUNCT
cana-1859	416	18	applications	application	NOUN
cana-1859	416	19	of	of	ADP
cana-1859	416	20	artificial	artificial	ADJ
cana-1859	416	21	neural	neural	ADJ
cana-1859	416	22	networks	network	NOUN
cana-1859	416	23	in	in	ADP
cana-1859	416	24	microorganism	microorganism	NOUN
cana-1859	416	25	image	image	NOUN
cana-1859	416	26	analysis	analysis	NOUN
cana-1859	416	27	:	:	PUNCT
cana-1859	416	28	a	a	DET
cana-1859	416	29	comprehensive	comprehensive	ADJ
cana-1859	416	30	review	review	NOUN
cana-1859	416	31	from	from	ADP
cana-1859	416	32	conventional	conventional	ADJ
cana-1859	416	33	multilayer	multilayer	ADJ
cana-1859	416	34	perceptron	perceptron	NOUN
cana-1859	416	35	to	to	ADP
cana-1859	416	36	popular	popular	ADJ
cana-1859	416	37	convolutional	convolutional	ADJ
cana-1859	416	38	neural	neural	ADJ
cana-1859	416	39	network	network	NOUN
cana-1859	416	40	and	and	CCONJ
cana-1859	416	41	potential	potential	ADJ
cana-1859	416	42	visual	visual	ADJ
cana-1859	416	43	transformer	transformer	NOUN
cana-1859	416	44	.	.	PUNCT
cana-1859	417	1	artif	artif	PROPN
cana-1859	417	2	intell	intell	PROPN
cana-1859	417	3	rev	rev	VERB
cana-1859	417	4	56	56	NUM
cana-1859	417	5	,	,	PUNCT
cana-1859	417	6	1013–1070	1013–1070	NUM
cana-1859	417	7	(	(	PUNCT
cana-1859	417	8	2023	2023	NUM
cana-1859	417	9	)	)	PUNCT
cana-1859	417	10	.	.	PUNCT
cana-1859	418	1	[	[	X
cana-1859	418	2	3	3	X
cana-1859	418	3	]	]	X
cana-1859	418	4	kulkarni	kulkarni	PROPN
cana-1859	418	5	,	,	PUNCT
cana-1859	418	6	v.	v.	PROPN
cana-1859	418	7	,	,	PUNCT
cana-1859	418	8	pawale	pawale	PROPN
cana-1859	418	9	,	,	PUNCT
cana-1859	418	10	s.	s.	PROPN
cana-1859	418	11	&	&	CCONJ
cana-1859	418	12	kharat	kharat	PROPN
cana-1859	418	13	,	,	PUNCT
cana-1859	418	14	a.	a.	NOUN
cana-1859	418	15	a	a	DET
cana-1859	418	16	classical	classical	ADJ
cana-1859	418	17	–	–	PUNCT
cana-1859	418	18	quantum	quantum	ADJ
cana-1859	418	19	convolutional	convolutional	ADJ
cana-1859	418	20	neural	neural	ADJ
cana-1859	418	21	network	network	NOUN
cana-1859	418	22	for	for	ADP
cana-1859	418	23	detecting	detect	VERB
cana-1859	418	24	pneumonia	pneumonia	NOUN
cana-1859	418	25	from	from	ADP
cana-1859	418	26	chest	chest	NOUN
cana-1859	418	27	radiographs	radiograph	NOUN
cana-1859	418	28	.	.	PUNCT
cana-1859	419	1	neural	neural	ADJ
cana-1859	419	2	comput	comput	PROPN
cana-1859	419	3	&	&	CCONJ
cana-1859	419	4	applic	applic	PROPN
cana-1859	419	5	35	35	NUM
cana-1859	419	6	,	,	PUNCT
cana-1859	419	7	15503–15510	15503–15510	NUM
cana-1859	419	8	(	(	PUNCT
cana-1859	419	9	2023	2023	NUM
cana-1859	419	10	)	)	PUNCT
cana-1859	419	11	.	.	PUNCT
cana-1859	420	1	[	[	X
cana-1859	420	2	4	4	NUM
cana-1859	420	3	]	]	X
cana-1859	420	4	stephen	stephen	PROPN
cana-1859	420	5	,	,	PUNCT
cana-1859	420	6	a.	a.	NOUN
cana-1859	420	7	,	,	PUNCT
cana-1859	420	8	punitha	punitha	NOUN
cana-1859	420	9	,	,	PUNCT
cana-1859	420	10	a.	a.	PROPN
cana-1859	420	11	&	&	CCONJ
cana-1859	420	12	chandrasekar	chandrasekar	PROPN
cana-1859	420	13	,	,	PUNCT
cana-1859	420	14	a.	a.	NOUN
cana-1859	420	15	optimal	optimal	ADJ
cana-1859	420	16	deep	deep	ADJ
cana-1859	420	17	generative	generative	ADJ
cana-1859	420	18	adversarial	adversarial	ADJ
cana-1859	420	19	network	network	NOUN
cana-1859	420	20	and	and	CCONJ
cana-1859	420	21	convolutional	convolutional	ADJ
cana-1859	420	22	neural	neural	ADJ
cana-1859	420	23	network	network	NOUN
cana-1859	420	24	for	for	ADP
cana-1859	420	25	rice	rice	NOUN
cana-1859	420	26	leaf	leaf	NOUN
cana-1859	420	27	disease	disease	NOUN
cana-1859	420	28	prediction	prediction	NOUN
cana-1859	420	29	.	.	PUNCT
cana-1859	421	1	vis	vis	X
cana-1859	421	2	comput	comput	NOUN
cana-1859	421	3	(	(	PUNCT
cana-1859	421	4	2023	2023	NUM
cana-1859	421	5	)	)	PUNCT
cana-1859	421	6	.	.	PUNCT
cana-1859	422	1	[	[	X
cana-1859	422	2	5	5	NUM
cana-1859	422	3	]	]	X
cana-1859	422	4	zhao	zhao	PROPN
cana-1859	422	5	,	,	PUNCT
cana-1859	422	6	z.	z.	PROPN
cana-1859	422	7	,	,	PUNCT
cana-1859	422	8	lin	lin	PROPN
cana-1859	422	9	,	,	PUNCT
cana-1859	422	10	s.	s.	PROPN
cana-1859	422	11	a	a	DET
cana-1859	422	12	cross	cross	ADJ
cana-1859	422	13	-	-	ADJ
cana-1859	422	14	linguistic	linguistic	ADJ
cana-1859	422	15	entity	entity	NOUN
cana-1859	422	16	alignment	alignment	NOUN
cana-1859	422	17	method	method	NOUN
cana-1859	422	18	based	base	VERB
cana-1859	422	19	on	on	ADP
cana-1859	422	20	graph	graph	NOUN
cana-1859	422	21	convolutional	convolutional	ADJ
cana-1859	422	22	neural	neural	ADJ
cana-1859	422	23	network	network	NOUN
cana-1859	422	24	and	and	CCONJ
cana-1859	422	25	graph	graph	NOUN
cana-1859	422	26	attention	attention	NOUN
cana-1859	422	27	network	network	NOUN
cana-1859	422	28	.	.	PUNCT
cana-1859	423	1	computing	compute	VERB
cana-1859	423	2	105	105	NUM
cana-1859	423	3	,	,	PUNCT
cana-1859	423	4	2293–2310	2293–2310	NUM
cana-1859	423	5	(	(	PUNCT
cana-1859	423	6	2023	2023	NUM
cana-1859	423	7	)	)	PUNCT
cana-1859	423	8	.	.	PUNCT
cana-1859	424	1	[	[	X
cana-1859	424	2	6	6	NUM
cana-1859	424	3	]	]	X
cana-1859	424	4	zhao	zhao	X
cana-1859	424	5	,	,	PUNCT
cana-1859	424	6	x.	x.	NOUN
cana-1859	424	7	,	,	PUNCT
cana-1859	424	8	bi	bi	PROPN
cana-1859	424	9	,	,	PUNCT
cana-1859	424	10	x.	x.	PROPN
cana-1859	424	11	,	,	PUNCT
cana-1859	424	12	zeng	zeng	PROPN
cana-1859	424	13	,	,	PUNCT
cana-1859	424	14	x.	x.	PROPN
cana-1859	424	15	et	et	PROPN
cana-1859	424	16	al	al	PROPN
cana-1859	424	17	.	.	PROPN
cana-1859	424	18	edense	edense	PROPN
cana-1859	424	19	:	:	PUNCT
cana-1859	424	20	a	a	DET
cana-1859	424	21	convolutional	convolutional	ADJ
cana-1859	424	22	neural	neural	ADJ
cana-1859	424	23	network	network	NOUN
cana-1859	424	24	with	with	ADP
cana-1859	424	25	elm	elm	NOUN
cana-1859	424	26	-	-	PUNCT
cana-1859	424	27	based	base	VERB
cana-1859	424	28	dense	dense	ADJ
cana-1859	424	29	connections	connection	NOUN
cana-1859	424	30	.	.	PUNCT
cana-1859	425	1	neural	neural	ADJ
cana-1859	425	2	comput	comput	PROPN
cana-1859	425	3	&	&	CCONJ
cana-1859	425	4	applic	applic	PROPN
cana-1859	425	5	35	35	NUM
cana-1859	425	6	,	,	PUNCT
cana-1859	425	7	3651–3663	3651–3663	NUM
cana-1859	425	8	(	(	PUNCT
cana-1859	425	9	2023	2023	NUM
cana-1859	425	10	)	)	PUNCT
cana-1859	425	11	.	.	PUNCT
cana-1859	426	1	[	[	X
cana-1859	426	2	7	7	NUM
cana-1859	426	3	]	]	X
cana-1859	426	4	askari	askari	PROPN
cana-1859	426	5	,	,	PUNCT
cana-1859	426	6	e.	e.	PROPN
cana-1859	426	7	,	,	PUNCT
cana-1859	426	8	motamed	motame	VERB
cana-1859	426	9	,	,	PUNCT
cana-1859	426	10	s.	s.	PROPN
cana-1859	426	11	quantitative	quantitative	ADJ
cana-1859	426	12	evaluation	evaluation	NOUN
cana-1859	426	13	of	of	ADP
cana-1859	426	14	image	image	NOUN
cana-1859	426	15	segmentation	segmentation	NOUN
cana-1859	426	16	algorithms	algorithm	NOUN
cana-1859	426	17	based	base	VERB
cana-1859	426	18	on	on	ADP
cana-1859	426	19	fuzzy	fuzzy	ADJ
cana-1859	426	20	convolutional	convolutional	ADJ
cana-1859	426	21	neural	neural	ADJ
cana-1859	426	22	network	network	NOUN
cana-1859	426	23	.	.	PUNCT
cana-1859	427	1	int	int	NOUN
cana-1859	427	2	.	.	PUNCT
cana-1859	428	1	j.	j.	PROPN
cana-1859	428	2	inf	inf	PROPN
cana-1859	428	3	.	.	PUNCT
cana-1859	428	4	tecnol	tecnol	PROPN
cana-1859	428	5	.	.	PROPN
cana-1859	429	1	15	15	NUM
cana-1859	429	2	,	,	PUNCT
cana-1859	429	3	3807–3812	3807–3812	NUM
cana-1859	429	4	(	(	PUNCT
cana-1859	429	5	2023	2023	NUM
cana-1859	429	6	)	)	PUNCT
cana-1859	429	7	.	.	PUNCT
cana-1859	430	1	[	[	X
cana-1859	430	2	8	8	NUM
cana-1859	430	3	]	]	X
cana-1859	430	4	marin	marin	NOUN
cana-1859	430	5	-	-	PUNCT
cana-1859	430	6	santos	santos	PROPN
cana-1859	430	7	,	,	PUNCT
cana-1859	430	8	d.	d.	PROPN
cana-1859	430	9	,	,	PUNCT
cana-1859	430	10	contreras	contreras	PROPN
cana-1859	430	11	-	-	PUNCT
cana-1859	430	12	fernandez	fernandez	PROPN
cana-1859	430	13	,	,	PUNCT
cana-1859	430	14	j.a	j.a	PROPN
cana-1859	430	15	.	.	PROPN
cana-1859	430	16	,	,	PUNCT
cana-1859	430	17	perez	perez	PROPN
cana-1859	430	18	-	-	PUNCT
cana-1859	430	19	borrero	borrero	NOUN
cana-1859	430	20	,	,	PUNCT
cana-1859	430	21	i.	i.	PROPN
cana-1859	430	22	et	et	PROPN
cana-1859	430	23	al	al	PROPN
cana-1859	430	24	.	.	PROPN
cana-1859	430	25	automatic	automatic	ADJ
cana-1859	430	26	detection	detection	NOUN
cana-1859	430	27	of	of	ADP
cana-1859	430	28	crohn	crohn	PROPN
cana-1859	430	29	disease	disease	PROPN
cana-1859	430	30	in	in	ADP
cana-1859	430	31	wireless	wireless	ADJ
cana-1859	430	32	capsule	capsule	NOUN
cana-1859	430	33	endoscopic	endoscopic	ADJ
cana-1859	430	34	images	image	NOUN
cana-1859	430	35	using	use	VERB
cana-1859	430	36	a	a	DET
cana-1859	430	37	deep	deep	ADJ
cana-1859	430	38	convolutional	convolutional	ADJ
cana-1859	430	39	neural	neural	ADJ
cana-1859	430	40	network	network	NOUN
cana-1859	430	41	.	.	PUNCT
cana-1859	431	1	appl	appl	PROPN
cana-1859	431	2	intell	intell	PROPN
cana-1859	431	3	53	53	NUM
cana-1859	431	4	,	,	PUNCT
cana-1859	431	5	12632–12646	12632–12646	NUM
cana-1859	431	6	(	(	PUNCT
cana-1859	431	7	2023	2023	NUM
cana-1859	431	8	)	)	PUNCT
cana-1859	431	9	.	.	PUNCT
cana-1859	432	1	[	[	X
cana-1859	432	2	9	9	NUM
cana-1859	432	3	]	]	SYM
cana-1859	432	4	tavakoli	tavakoli	NOUN
cana-1859	432	5	,	,	PUNCT
cana-1859	432	6	a.	a.	NOUN
cana-1859	432	7	,	,	PUNCT
cana-1859	432	8	honjani	honjani	PROPN
cana-1859	432	9	,	,	PUNCT
cana-1859	432	10	z.	z.	PROPN
cana-1859	432	11	&	&	CCONJ
cana-1859	432	12	sajedi	sajedi	PROPN
cana-1859	432	13	,	,	PUNCT
cana-1859	432	14	h.	h.	PROPN
cana-1859	432	15	convolutional	convolutional	ADJ
cana-1859	432	16	neural	neural	ADJ
cana-1859	432	17	network	network	NOUN
cana-1859	432	18	-	-	PUNCT
cana-1859	432	19	based	base	VERB
cana-1859	432	20	image	image	NOUN
cana-1859	432	21	watermarking	watermarking	NOUN
cana-1859	432	22	using	use	VERB
cana-1859	432	23	discrete	discrete	ADJ
cana-1859	432	24	wavelet	wavelet	NOUN
cana-1859	432	25	transform	transform	NOUN
cana-1859	432	26	.	.	PUNCT
cana-1859	433	1	int	int	NOUN
cana-1859	433	2	.	.	PUNCT
cana-1859	434	1	j.	j.	PROPN
cana-1859	434	2	inf	inf	PROPN
cana-1859	434	3	.	.	PUNCT
cana-1859	434	4	tecnol	tecnol	PROPN
cana-1859	434	5	.	.	PROPN
cana-1859	434	6	15	15	NUM
cana-1859	434	7	,	,	PUNCT
cana-1859	434	8	2021–2029	2021–2029	NUM
cana-1859	434	9	(	(	PUNCT
cana-1859	434	10	2023	2023	NUM
cana-1859	434	11	)	)	PUNCT
cana-1859	434	12	.	.	PUNCT
cana-1859	435	1	[	[	X
cana-1859	435	2	10	10	NUM
cana-1859	435	3	]	]	X
cana-1859	435	4	wang	wang	PROPN
cana-1859	435	5	,	,	PUNCT
cana-1859	435	6	q.	q.	PROPN
cana-1859	435	7	,	,	PUNCT
cana-1859	435	8	lei	lei	PROPN
cana-1859	435	9	,	,	PUNCT
cana-1859	435	10	h.	h.	PROPN
cana-1859	435	11	,	,	PUNCT
cana-1859	435	12	li	li	PROPN
cana-1859	435	13	,	,	PUNCT
cana-1859	435	14	g.	g.	PROPN
cana-1859	435	15	et	et	PROPN
cana-1859	435	16	al	al	PROPN
cana-1859	435	17	.	.	PUNCT
cana-1859	436	1	a	a	DET
cana-1859	436	2	novel	novel	ADJ
cana-1859	436	3	convolutional	convolutional	ADJ
cana-1859	436	4	neural	neural	ADJ
cana-1859	436	5	network	network	NOUN
cana-1859	436	6	for	for	ADP
cana-1859	436	7	head	head	NOUN
cana-1859	436	8	detection	detection	NOUN
cana-1859	436	9	and	and	CCONJ
cana-1859	436	10	pose	pose	NOUN
cana-1859	436	11	estimation	estimation	NOUN
cana-1859	436	12	in	in	ADP
cana-1859	436	13	complex	complex	ADJ
cana-1859	436	14	environments	environment	NOUN
cana-1859	436	15	from	from	ADP
cana-1859	436	16	single	single	ADJ
cana-1859	436	17	-	-	PUNCT
cana-1859	436	18	depth	depth	NOUN
cana-1859	436	19	images	image	NOUN
cana-1859	436	20	.	.	PUNCT
cana-1859	437	1	cogn	cogn	VERB
cana-1859	437	2	comput	comput	NOUN
cana-1859	437	3	(	(	PUNCT
cana-1859	437	4	2023	2023	NUM
cana-1859	437	5	)	)	PUNCT
cana-1859	437	6	.	.	PUNCT
cana-1859	438	1	[	[	X
cana-1859	438	2	11	11	NUM
cana-1859	438	3	]	]	X
cana-1859	438	4	sun	sun	NOUN
cana-1859	438	5	,	,	PUNCT
cana-1859	438	6	d.	d.	PROPN
cana-1859	438	7	,	,	PUNCT
cana-1859	438	8	yaqot	yaqot	PROPN
cana-1859	438	9	,	,	PUNCT
cana-1859	438	10	a.	a.	PROPN
cana-1859	438	11	,	,	PUNCT
cana-1859	438	12	qiu	qiu	PROPN
cana-1859	438	13	,	,	PUNCT
cana-1859	438	14	j.	j.	PROPN
cana-1859	438	15	et	et	PROPN
cana-1859	438	16	al	al	PROPN
cana-1859	438	17	.	.	PUNCT
cana-1859	438	18	attention	attention	NOUN
cana-1859	438	19	-	-	PUNCT
cana-1859	438	20	based	base	VERB
cana-1859	438	21	deep	deep	ADJ
cana-1859	438	22	convolutional	convolutional	ADJ
cana-1859	438	23	neural	neural	ADJ
cana-1859	438	24	network	network	NOUN
cana-1859	438	25	for	for	ADP
cana-1859	438	26	spectral	spectral	ADJ
cana-1859	438	27	efficiency	efficiency	NOUN
cana-1859	438	28	optimization	optimization	NOUN
cana-1859	438	29	in	in	ADP
cana-1859	438	30	mimo	mimo	PROPN
cana-1859	438	31	systems	systems	PROPN
cana-1859	438	32	.	.	PUNCT
cana-1859	439	1	neural	neural	ADJ
cana-1859	439	2	comput	comput	PROPN
cana-1859	439	3	&	&	CCONJ
cana-1859	439	4	applic	applic	PROPN
cana-1859	439	5	35	35	NUM
cana-1859	439	6	,	,	PUNCT
cana-1859	439	7	12967–12978	12967–12978	NUM
cana-1859	439	8	(	(	PUNCT
cana-1859	439	9	2023	2023	NUM
cana-1859	439	10	)	)	PUNCT
cana-1859	439	11	.	.	PUNCT
cana-1859	440	1	[	[	X
cana-1859	440	2	12	12	NUM
cana-1859	440	3	]	]	X
cana-1859	440	4	subramani	subramani	PROPN
cana-1859	440	5	,	,	PUNCT
cana-1859	440	6	s.	s.	PROPN
cana-1859	440	7	,	,	PUNCT
cana-1859	440	8	selvi	selvi	PROPN
cana-1859	440	9	,	,	PUNCT
cana-1859	440	10	m.	m.	NOUN
cana-1859	440	11	intelligent	intelligent	ADJ
cana-1859	440	12	ids	id	NOUN
cana-1859	440	13	in	in	ADP
cana-1859	440	14	wireless	wireless	ADJ
cana-1859	440	15	sensor	sensor	NOUN
cana-1859	440	16	networks	network	NOUN
cana-1859	440	17	using	use	VERB
cana-1859	440	18	deep	deep	ADJ
cana-1859	440	19	fuzzy	fuzzy	ADJ
cana-1859	440	20	convolutional	convolutional	ADJ
cana-1859	440	21	neural	neural	ADJ
cana-1859	440	22	network	network	NOUN
cana-1859	440	23	.	.	PUNCT
cana-1859	441	1	neural	neural	ADJ
cana-1859	441	2	comput	comput	PROPN
cana-1859	441	3	&	&	CCONJ
cana-1859	441	4	applic	applic	PROPN
cana-1859	441	5	35	35	NUM
cana-1859	441	6	,	,	PUNCT
cana-1859	441	7	15201–15220	15201–15220	NUM
cana-1859	441	8	(	(	PUNCT
cana-1859	441	9	2023	2023	NUM
cana-1859	441	10	)	)	PUNCT
cana-1859	441	11	.	.	PUNCT
cana-1859	442	1	[	[	X
cana-1859	442	2	13	13	NUM
cana-1859	442	3	]	]	SYM
cana-1859	442	4	xu	xu	PROPN
cana-1859	442	5	,	,	PUNCT
cana-1859	442	6	m.	m.	NOUN
cana-1859	442	7	,	,	PUNCT
cana-1859	442	8	gao	gao	PROPN
cana-1859	442	9	,	,	PUNCT
cana-1859	442	10	j.	j.	PROPN
cana-1859	442	11	,	,	PUNCT
cana-1859	442	12	zhang	zhang	PROPN
cana-1859	442	13	,	,	PUNCT
cana-1859	443	1	z.	z.	PROPN
cana-1859	443	2	et	et	PROPN
cana-1859	443	3	al	al	PROPN
cana-1859	443	4	.	.	PUNCT
cana-1859	444	1	multi	multi	ADJ
cana-1859	444	2	-	-	ADJ
cana-1859	444	3	channel	channel	ADJ
cana-1859	444	4	and	and	CCONJ
cana-1859	444	5	multi	multi	ADJ
cana-1859	444	6	-	-	ADJ
cana-1859	444	7	scale	scale	ADJ
cana-1859	444	8	separable	separable	ADJ
cana-1859	444	9	dilated	dilate	VERB
cana-1859	444	10	convolutional	convolutional	ADJ
cana-1859	444	11	neural	neural	ADJ
cana-1859	444	12	network	network	NOUN
cana-1859	444	13	with	with	ADP
cana-1859	444	14	attention	attention	NOUN
cana-1859	444	15	mechanism	mechanism	NOUN
cana-1859	444	16	for	for	ADP
cana-1859	444	17	flue	flue	NOUN
cana-1859	444	18	-	-	PUNCT
cana-1859	444	19	cured	cure	VERB
cana-1859	444	20	tobacco	tobacco	NOUN
cana-1859	444	21	classification	classification	NOUN
cana-1859	444	22	.	.	PUNCT
cana-1859	445	1	neural	neural	ADJ
cana-1859	445	2	comput	comput	PROPN
cana-1859	445	3	&	&	CCONJ
cana-1859	445	4	applic	applic	PROPN
cana-1859	445	5	35	35	NUM
cana-1859	445	6	,	,	PUNCT
cana-1859	445	7	15511–15529	15511–15529	NUM
cana-1859	445	8	(	(	PUNCT
cana-1859	445	9	2023	2023	NUM
cana-1859	445	10	)	)	PUNCT
cana-1859	445	11	.	.	PUNCT
cana-1859	446	1	communications	communication	NOUN
cana-1859	446	2	on	on	ADP
cana-1859	446	3	applied	apply	VERB
cana-1859	446	4	nonlinear	nonlinear	ADJ
cana-1859	446	5	analysis	analysis	NOUN
cana-1859	446	6	issn	issn	NOUN
cana-1859	446	7	:	:	PUNCT
cana-1859	446	8	1074	1074	NUM
cana-1859	446	9	-	-	PUNCT
cana-1859	446	10	133x	133x	NUM
cana-1859	446	11	vol	vol	NOUN
cana-1859	446	12	32	32	NUM
cana-1859	446	13	no	no	NOUN
cana-1859	446	14	.	.	NOUN
cana-1859	446	15	2	2	NUM
cana-1859	446	16	(	(	PUNCT
cana-1859	446	17	2025	2025	NUM
cana-1859	446	18	)	)	PUNCT
cana-1859	446	19	665	665	NUM
cana-1859	446	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1859	447	1	[	[	X
cana-1859	447	2	14	14	NUM
cana-1859	447	3	]	]	PUNCT
cana-1859	447	4	adeli	adeli	PROPN
cana-1859	447	5	,	,	PUNCT
cana-1859	447	6	e.	e.	PROPN
cana-1859	447	7	,	,	PUNCT
cana-1859	447	8	sun	sun	PROPN
cana-1859	447	9	,	,	PUNCT
cana-1859	447	10	l.	l.	PROPN
cana-1859	447	11	,	,	PUNCT
cana-1859	447	12	wang	wang	PROPN
cana-1859	447	13	,	,	PUNCT
cana-1859	447	14	j.	j.	PROPN
cana-1859	447	15	et	et	PROPN
cana-1859	447	16	al	al	PROPN
cana-1859	447	17	.	.	PUNCT
cana-1859	448	1	an	an	DET
cana-1859	448	2	advanced	advanced	ADJ
cana-1859	448	3	spatio	spatio	NOUN
cana-1859	448	4	-	-	PUNCT
cana-1859	448	5	temporal	temporal	ADJ
cana-1859	448	6	convolutional	convolutional	ADJ
cana-1859	448	7	recurrent	recurrent	ADJ
cana-1859	448	8	neural	neural	ADJ
cana-1859	448	9	network	network	NOUN
cana-1859	448	10	for	for	ADP
cana-1859	448	11	storm	storm	NOUN
cana-1859	448	12	surge	surge	NOUN
cana-1859	448	13	predictions	prediction	NOUN
cana-1859	448	14	.	.	PUNCT
cana-1859	449	1	neural	neural	ADJ
cana-1859	449	2	comput	comput	PROPN
cana-1859	449	3	&	&	CCONJ
cana-1859	449	4	applic	applic	PROPN
cana-1859	449	5	35	35	NUM
cana-1859	449	6	,	,	PUNCT
cana-1859	449	7	18971–18987	18971–18987	NUM
cana-1859	449	8	(	(	PUNCT
cana-1859	449	9	2023	2023	NUM
cana-1859	449	10	)	)	PUNCT
cana-1859	449	11	.	.	PUNCT
cana-1859	450	1	[	[	X
cana-1859	450	2	15	15	NUM
cana-1859	450	3	]	]	X
cana-1859	450	4	daoud	daoud	PROPN
cana-1859	450	5	,	,	PUNCT
cana-1859	450	6	z.	z.	PROPN
cana-1859	450	7	,	,	PUNCT
cana-1859	450	8	ben	ben	PROPN
cana-1859	450	9	hamida	hamida	PROPN
cana-1859	450	10	,	,	PUNCT
cana-1859	450	11	a.	a.	PROPN
cana-1859	450	12	&	&	CCONJ
cana-1859	450	13	ben	ben	PROPN
cana-1859	450	14	amar	amar	PROPN
cana-1859	450	15	,	,	PUNCT
cana-1859	450	16	c.	c.	PROPN
cana-1859	450	17	fireclassnet	fireclassnet	PROPN
cana-1859	450	18	:	:	PUNCT
cana-1859	450	19	a	a	DET
cana-1859	450	20	deep	deep	ADJ
cana-1859	450	21	convolutional	convolutional	ADJ
cana-1859	450	22	neural	neural	ADJ
cana-1859	450	23	network	network	NOUN
cana-1859	450	24	approach	approach	NOUN
cana-1859	450	25	for	for	ADP
cana-1859	450	26	pjf	pjf	NOUN
cana-1859	450	27	fire	fire	NOUN
cana-1859	450	28	images	image	NOUN
cana-1859	450	29	classification	classification	NOUN
cana-1859	450	30	.	.	PUNCT
cana-1859	451	1	neural	neural	ADJ
cana-1859	451	2	comput	comput	PROPN
cana-1859	451	3	&	&	CCONJ
cana-1859	451	4	applic	applic	PROPN
cana-1859	451	5	35	35	NUM
cana-1859	451	6	,	,	PUNCT
cana-1859	451	7	19069–19085	19069–19085	NUM
cana-1859	451	8	(	(	PUNCT
cana-1859	451	9	2023	2023	NUM
cana-1859	451	10	)	)	PUNCT
cana-1859	451	11	.	.	PUNCT
cana-1859	452	1	[	[	X
cana-1859	452	2	16	16	NUM
cana-1859	452	3	]	]	X
cana-1859	452	4	mann	mann	PROPN
cana-1859	452	5	,	,	PUNCT
cana-1859	452	6	p.s	p.s	PROPN
cana-1859	452	7	.	.	PROPN
cana-1859	452	8	,	,	PUNCT
cana-1859	452	9	panchal	panchal	VERB
cana-1859	452	10	,	,	PUNCT
cana-1859	452	11	s.d	s.d	PROPN
cana-1859	452	12	.	.	PROPN
cana-1859	452	13	,	,	PUNCT
cana-1859	452	14	singh	singh	PROPN
cana-1859	452	15	,	,	PUNCT
cana-1859	452	16	s.	s.	PROPN
cana-1859	452	17	et	et	PROPN
cana-1859	452	18	al	al	PROPN
cana-1859	452	19	.	.	PUNCT
cana-1859	453	1	a	a	DET
cana-1859	453	2	hybrid	hybrid	ADJ
cana-1859	453	3	deep	deep	ADJ
cana-1859	453	4	convolutional	convolutional	ADJ
cana-1859	453	5	neural	neural	ADJ
cana-1859	453	6	network	network	NOUN
cana-1859	453	7	model	model	NOUN
cana-1859	453	8	for	for	ADP
cana-1859	453	9	improved	improved	ADJ
cana-1859	453	10	diagnosis	diagnosis	NOUN
cana-1859	453	11	of	of	ADP
cana-1859	453	12	pneumonia	pneumonia	NOUN
cana-1859	453	13	.	.	PUNCT
cana-1859	454	1	neural	neural	ADJ
cana-1859	454	2	comput	comput	PROPN
cana-1859	454	3	&	&	CCONJ
cana-1859	454	4	applic	applic	PROPN
cana-1859	454	5	(	(	PUNCT
cana-1859	454	6	2023	2023	NUM
cana-1859	454	7	)	)	PUNCT
cana-1859	454	8	.	.	PUNCT
cana-1859	455	1	[	[	X
cana-1859	455	2	17	17	NUM
cana-1859	455	3	]	]	X
cana-1859	455	4	shirabayashi	shirabayashi	PROPN
cana-1859	455	5	,	,	PUNCT
cana-1859	455	6	j.v	j.v	PROPN
cana-1859	455	7	.	.	PROPN
cana-1859	455	8	,	,	PUNCT
cana-1859	455	9	braga	braga	NOUN
cana-1859	455	10	,	,	PUNCT
cana-1859	455	11	a.s.m	a.s.m	PROPN
cana-1859	455	12	.	.	PROPN
cana-1859	455	13	&	&	CCONJ
cana-1859	455	14	da	da	PROPN
cana-1859	455	15	silva	silva	PROPN
cana-1859	455	16	,	,	PUNCT
cana-1859	455	17	j.	j.	PROPN
cana-1859	455	18	comparative	comparative	PROPN
cana-1859	455	19	approach	approach	NOUN
cana-1859	455	20	to	to	ADP
cana-1859	455	21	different	different	ADJ
cana-1859	455	22	convolutional	convolutional	ADJ
cana-1859	455	23	neural	neural	ADJ
cana-1859	455	24	network	network	NOUN
cana-1859	455	25	(	(	PUNCT
cana-1859	455	26	cnn	cnn	PROPN
cana-1859	455	27	)	)	PUNCT
cana-1859	455	28	architectures	architecture	NOUN
cana-1859	455	29	applied	apply	VERB
cana-1859	455	30	to	to	ADP
cana-1859	455	31	human	human	ADJ
cana-1859	455	32	behavior	behavior	NOUN
cana-1859	455	33	detection	detection	NOUN
cana-1859	455	34	.	.	PUNCT
cana-1859	456	1	neural	neural	ADJ
cana-1859	456	2	comput	comput	PROPN
cana-1859	456	3	&	&	CCONJ
cana-1859	456	4	applic	applic	PROPN
cana-1859	456	5	35	35	NUM
cana-1859	456	6	,	,	PUNCT
cana-1859	456	7	12915–12925	12915–12925	NUM
cana-1859	456	8	(	(	PUNCT
cana-1859	456	9	2023	2023	NUM
cana-1859	456	10	)	)	PUNCT
cana-1859	456	11	.	.	PUNCT
cana-1859	457	1	[	[	X
cana-1859	457	2	18	18	NUM
cana-1859	457	3	]	]	X
cana-1859	457	4	wang	wang	PROPN
cana-1859	457	5	,	,	PUNCT
cana-1859	457	6	m.	m.	NOUN
cana-1859	457	7	,	,	PUNCT
cana-1859	457	8	liu	liu	PROPN
cana-1859	457	9	,	,	PUNCT
cana-1859	457	10	y.	y.	PROPN
cana-1859	457	11	,	,	PUNCT
cana-1859	457	12	liu	liu	PROPN
cana-1859	457	13	,	,	PUNCT
cana-1859	458	1	w.	w.	PROPN
cana-1859	458	2	et	et	PROPN
cana-1859	458	3	al	al	PROPN
cana-1859	458	4	.	.	PROPN
cana-1859	458	5	feature	feature	NOUN
cana-1859	458	6	fusion	fusion	NOUN
cana-1859	458	7	based	base	VERB
cana-1859	458	8	parallel	parallel	ADJ
cana-1859	458	9	graph	graph	NOUN
cana-1859	458	10	convolutional	convolutional	ADJ
cana-1859	458	11	neural	neural	ADJ
cana-1859	458	12	network	network	NOUN
cana-1859	458	13	for	for	ADP
cana-1859	458	14	image	image	NOUN
cana-1859	458	15	annotation	annotation	NOUN
cana-1859	458	16	.	.	PUNCT
cana-1859	459	1	neural	neural	ADJ
cana-1859	459	2	process	process	NOUN
cana-1859	459	3	lett	lett	PROPN
cana-1859	459	4	55	55	NUM
cana-1859	459	5	,	,	PUNCT
cana-1859	459	6	6153–6164	6153–6164	NOUN
cana-1859	459	7	(	(	PUNCT
cana-1859	459	8	2023	2023	NUM
cana-1859	459	9	)	)	PUNCT
cana-1859	459	10	.	.	PUNCT
cana-1859	460	1	https://doi.org/10.1007/s11063-022-11131-x	https://doi.org/10.1007/s11063-022-11131-x	NOUN
cana-1859	461	1	[	[	X
cana-1859	461	2	19	19	NUM
cana-1859	461	3	]	]	X
cana-1859	461	4	kulshreshtha	kulshreshtha	NOUN
cana-1859	461	5	,	,	PUNCT
cana-1859	461	6	a.	a.	NOUN
cana-1859	461	7	,	,	PUNCT
cana-1859	461	8	nagpal	nagpal	NOUN
cana-1859	461	9	,	,	PUNCT
cana-1859	461	10	a.	a.	NOUN
cana-1859	461	11	ifas	ifas	PROPN
cana-1859	461	12	:	:	PUNCT
cana-1859	461	13	improved	improve	VERB
cana-1859	461	14	fully	fully	ADV
cana-1859	461	15	automatic	automatic	ADJ
cana-1859	461	16	segmentation	segmentation	NOUN
cana-1859	461	17	convolutional	convolutional	ADJ
cana-1859	461	18	neural	neural	ADJ
cana-1859	461	19	network	network	NOUN
cana-1859	461	20	model	model	NOUN
cana-1859	461	21	along	along	ADP
cana-1859	461	22	with	with	ADP
cana-1859	461	23	morphological	morphological	ADJ
cana-1859	461	24	segmentation	segmentation	NOUN
cana-1859	461	25	for	for	ADP
cana-1859	461	26	brain	brain	NOUN
cana-1859	461	27	tumor	tumor	NOUN
cana-1859	461	28	detection	detection	NOUN
cana-1859	461	29	.	.	PUNCT
cana-1859	462	1	int	int	NOUN
cana-1859	462	2	.	.	PUNCT
cana-1859	463	1	j.	j.	PROPN
cana-1859	463	2	inf	inf	PROPN
cana-1859	463	3	.	.	PUNCT
cana-1859	463	4	tecnol	tecnol	PROPN
cana-1859	463	5	.	.	PUNCT
cana-1859	464	1	(	(	PUNCT
cana-1859	464	2	2023	2023	NUM
cana-1859	464	3	)	)	PUNCT
cana-1859	464	4	.	.	PUNCT
cana-1859	465	1	https://doi.org/10.1007/s41870-023-01572-5	https://doi.org/10.1007/s41870-023-01572-5	NUM
cana-1859	466	1	[	[	SYM
cana-1859	466	2	20	20	NUM
cana-1859	466	3	]	]	PUNCT
cana-1859	466	4	supriyapatro	supriyapatro	ADV
cana-1859	466	5	,	,	PUNCT
cana-1859	466	6	p.	p.	PROPN
cana-1859	466	7	,	,	PUNCT
cana-1859	466	8	goel	goel	PROPN
cana-1859	466	9	,	,	PUNCT
cana-1859	466	10	t.	t.	PROPN
cana-1859	466	11	,	,	PUNCT
cana-1859	466	12	varaprasad	varaprasad	PROPN
cana-1859	466	13	,	,	PUNCT
cana-1859	466	14	s.a	s.a	PROPN
cana-1859	466	15	.	.	PROPN
cana-1859	467	1	et	et	PROPN
cana-1859	467	2	al	al	PROPN
cana-1859	467	3	.	.	PUNCT
cana-1859	468	1	lightweight	lightweight	PROPN
cana-1859	468	2	3d	3d	PROPN
cana-1859	468	3	convolutional	convolutional	ADJ
cana-1859	468	4	neural	neural	ADJ
cana-1859	468	5	network	network	NOUN
cana-1859	468	6	for	for	ADP
cana-1859	468	7	schizophrenia	schizophrenia	NOUN
cana-1859	468	8	diagnosis	diagnosis	NOUN
cana-1859	468	9	using	use	VERB
cana-1859	468	10	mri	mri	NOUN
cana-1859	468	11	images	image	NOUN
cana-1859	468	12	and	and	CCONJ
cana-1859	468	13	ensemble	ensemble	ADJ
cana-1859	468	14	bagging	bagging	NOUN
cana-1859	468	15	classifier	classifier	NOUN
cana-1859	468	16	.	.	PUNCT
cana-1859	469	1	cogn	cogn	ADJ
cana-1859	469	2	comput	comput	NOUN
cana-1859	469	3	(	(	PUNCT
cana-1859	469	4	2022	2022	NUM
cana-1859	469	5	)	)	PUNCT
cana-1859	469	6	.	.	PUNCT
cana-1859	470	1	[	[	X
cana-1859	470	2	21	21	NUM
cana-1859	470	3	]	]	SYM
cana-1859	470	4	li	li	PROPN
cana-1859	470	5	,	,	PUNCT
cana-1859	470	6	jj	jj	PROPN
cana-1859	470	7	.	.	PROPN
cana-1859	470	8	,	,	PUNCT
cana-1859	470	9	wang	wang	PROPN
cana-1859	470	10	,	,	PUNCT
cana-1859	470	11	k.	k.	PROPN
cana-1859	470	12	,	,	PUNCT
cana-1859	470	13	zheng	zheng	PROPN
cana-1859	470	14	,	,	PUNCT
cana-1859	470	15	h.	h.	PROPN
cana-1859	470	16	et	et	PROPN
cana-1859	470	17	al	al	PROPN
cana-1859	470	18	.	.	PROPN
cana-1859	470	19	gshuttle	gshuttle	NOUN
cana-1859	470	20	:	:	PUNCT
cana-1859	470	21	optimizing	optimize	VERB
cana-1859	470	22	memory	memory	NOUN
cana-1859	470	23	access	access	NOUN
cana-1859	470	24	efficiency	efficiency	NOUN
cana-1859	470	25	for	for	ADP
cana-1859	470	26	graph	graph	NOUN
cana-1859	470	27	convolutional	convolutional	ADJ
cana-1859	470	28	neural	neural	ADJ
cana-1859	470	29	network	network	NOUN
cana-1859	470	30	accelerators	accelerator	NOUN
cana-1859	470	31	.	.	PUNCT
cana-1859	471	1	j.	j.	PROPN
cana-1859	471	2	comput	comput	PROPN
cana-1859	471	3	.	.	PUNCT
cana-1859	472	1	sci	sci	PROPN
cana-1859	472	2	.	.	PROPN
cana-1859	472	3	technol	technol	PROPN
cana-1859	472	4	.	.	PROPN
cana-1859	473	1	38	38	NUM
cana-1859	473	2	,	,	PUNCT
cana-1859	473	3	115–127	115–127	NUM
cana-1859	473	4	(	(	PUNCT
cana-1859	473	5	2023	2023	NUM
cana-1859	473	6	)	)	PUNCT
cana-1859	473	7	.	.	PUNCT
cana-1859	474	1	[	[	X
cana-1859	474	2	22	22	NUM
cana-1859	474	3	]	]	PUNCT
cana-1859	474	4	özbay	özbay	NOUN
cana-1859	474	5	,	,	PUNCT
cana-1859	474	6	e.	e.	PROPN
cana-1859	474	7	,	,	PUNCT
cana-1859	474	8	yıldırım	yıldırım	PROPN
cana-1859	474	9	,	,	PUNCT
cana-1859	474	10	m.	m.	NOUN
cana-1859	474	11	classification	classification	NOUN
cana-1859	474	12	of	of	ADP
cana-1859	474	13	satellite	satellite	NOUN
cana-1859	474	14	images	image	NOUN
cana-1859	474	15	for	for	ADP
cana-1859	474	16	ecology	ecology	NOUN
cana-1859	474	17	management	management	NOUN
cana-1859	474	18	using	use	VERB
cana-1859	474	19	deep	deep	ADJ
cana-1859	474	20	features	feature	NOUN
cana-1859	474	21	obtained	obtain	VERB
cana-1859	474	22	from	from	ADP
cana-1859	474	23	convolutional	convolutional	ADJ
cana-1859	474	24	neural	neural	ADJ
cana-1859	474	25	network	network	NOUN
cana-1859	474	26	models	model	NOUN
cana-1859	474	27	.	.	PUNCT
cana-1859	475	1	iran	iran	PROPN
cana-1859	475	2	j	j	PROPN
cana-1859	475	3	comput	comput	VERB
cana-1859	475	4	sci	sci	PROPN
cana-1859	475	5	6	6	NUM
cana-1859	475	6	,	,	PUNCT
cana-1859	475	7	185–193	185–193	NUM
cana-1859	475	8	(	(	PUNCT
cana-1859	475	9	2023	2023	NUM
cana-1859	475	10	)	)	PUNCT
cana-1859	475	11	.	.	PUNCT
cana-1859	476	1	[	[	X
cana-1859	476	2	23	23	NUM
cana-1859	476	3	]	]	X
cana-1859	476	4	presannakumar	presannakumar	PROPN
cana-1859	476	5	,	,	PUNCT
cana-1859	476	6	k.	k.	PROPN
cana-1859	476	7	,	,	PUNCT
cana-1859	476	8	mohamed	mohamed	PROPN
cana-1859	476	9	,	,	PUNCT
cana-1859	476	10	a.	a.	NOUN
cana-1859	476	11	source	source	NOUN
cana-1859	476	12	identification	identification	NOUN
cana-1859	476	13	of	of	ADP
cana-1859	476	14	weak	weak	ADJ
cana-1859	476	15	audio	audio	NOUN
cana-1859	476	16	signals	signal	NOUN
cana-1859	476	17	using	use	VERB
cana-1859	476	18	attention	attention	NOUN
cana-1859	476	19	based	base	VERB
cana-1859	476	20	convolutional	convolutional	ADJ
cana-1859	476	21	neural	neural	ADJ
cana-1859	476	22	network	network	NOUN
cana-1859	476	23	.	.	PUNCT
cana-1859	477	1	appl	appl	PROPN
cana-1859	477	2	intell	intell	PROPN
cana-1859	477	3	53	53	NUM
cana-1859	477	4	,	,	PUNCT
cana-1859	477	5	27044–27059	27044–27059	NUM
cana-1859	477	6	(	(	PUNCT
cana-1859	477	7	2023	2023	NUM
cana-1859	477	8	)	)	PUNCT
cana-1859	477	9	.	.	PUNCT
cana-1859	478	1	[	[	X
cana-1859	478	2	24	24	NUM
cana-1859	478	3	]	]	X
cana-1859	478	4	setiawan	setiawan	PROPN
cana-1859	478	5	,	,	PUNCT
cana-1859	478	6	f.	f.	PROPN
cana-1859	478	7	,	,	PUNCT
cana-1859	478	8	yahya	yahya	PROPN
cana-1859	478	9	,	,	PUNCT
cana-1859	478	10	b.n	b.n	PROPN
cana-1859	478	11	.	.	PROPN
cana-1859	478	12	&	&	CCONJ
cana-1859	478	13	lee	lee	PROPN
cana-1859	478	14	,	,	PUNCT
cana-1859	478	15	sl	sl	PROPN
cana-1859	478	16	.	.	PROPN
cana-1859	478	17	normalized	normalize	VERB
cana-1859	478	18	attention	attention	NOUN
cana-1859	478	19	inter	inter	ADJ
cana-1859	478	20	-	-	ADJ
cana-1859	478	21	channel	channel	ADJ
cana-1859	478	22	pooling	pooling	NOUN
cana-1859	478	23	(	(	PUNCT
cana-1859	478	24	naip	naip	PROPN
cana-1859	478	25	)	)	PUNCT
cana-1859	478	26	for	for	ADP
cana-1859	478	27	deep	deep	ADJ
cana-1859	478	28	convolutional	convolutional	ADJ
cana-1859	478	29	neural	neural	ADJ
cana-1859	478	30	network	network	NOUN
cana-1859	478	31	regularization	regularization	NOUN
cana-1859	478	32	.	.	PUNCT
cana-1859	479	1	neural	neural	ADJ
cana-1859	479	2	process	process	NOUN
cana-1859	479	3	lett	lett	PROPN
cana-1859	479	4	55	55	NUM
cana-1859	479	5	,	,	PUNCT
cana-1859	479	6	9315–9333	9315–9333	NUM
cana-1859	479	7	(	(	PUNCT
cana-1859	479	8	2023	2023	NUM
cana-1859	479	9	)	)	PUNCT
cana-1859	479	10	.	.	PUNCT
cana-1859	480	1	[	[	X
cana-1859	480	2	25	25	NUM
cana-1859	480	3	]	]	X
cana-1859	480	4	liu	liu	PROPN
cana-1859	480	5	,	,	PUNCT
cana-1859	480	6	w.	w.	PROPN
cana-1859	480	7	,	,	PUNCT
cana-1859	480	8	wang	wang	PROPN
cana-1859	480	9	,	,	PUNCT
cana-1859	480	10	p.	p.	PROPN
cana-1859	480	11	,	,	PUNCT
cana-1859	480	12	zhang	zhang	PROPN
cana-1859	480	13	,	,	PUNCT
cana-1859	480	14	z.	z.	PROPN
cana-1859	480	15	et	et	PROPN
cana-1859	480	16	al	al	PROPN
cana-1859	480	17	.	.	PUNCT
cana-1859	480	18	multi	multi	ADJ
cana-1859	480	19	-	-	ADJ
cana-1859	480	20	scale	scale	ADJ
cana-1859	480	21	convolutional	convolutional	ADJ
cana-1859	480	22	neural	neural	ADJ
cana-1859	480	23	network	network	NOUN
cana-1859	480	24	for	for	ADP
cana-1859	480	25	temporal	temporal	ADJ
cana-1859	480	26	knowledge	knowledge	NOUN
cana-1859	480	27	graph	graph	NOUN
cana-1859	480	28	completion	completion	NOUN
cana-1859	480	29	.	.	PUNCT
cana-1859	481	1	cogn	cogn	VERB
cana-1859	481	2	comput	comput	ADJ
cana-1859	481	3	15	15	NUM
cana-1859	481	4	,	,	PUNCT
cana-1859	481	5	1016–1022	1016–1022	NUM
cana-1859	481	6	(	(	PUNCT
cana-1859	481	7	2023	2023	NUM
cana-1859	481	8	)	)	PUNCT
cana-1859	481	9	.	.	PUNCT
cana-1859	482	1	https://doi.org/10.1007/s12559-023-10134-7	https://doi.org/10.1007/s12559-023-10134-7	NUM
cana-1859	483	1	https://doi.org/10.1007/s11063-022-11131-x	https://doi.org/10.1007/s11063-022-11131-x	NOUN
cana-1859	483	2	https://doi.org/10.1007/s41870-023-01572-5	https://doi.org/10.1007/s41870-023-01572-5	NUM