id	sid	tid	token	lemma	pos
cana-5954	1	1	communications	communication	NOUN
cana-5954	1	2	on	on	ADP
cana-5954	1	3	applied	apply	VERB
cana-5954	1	4	nonlinear	nonlinear	ADJ
cana-5954	1	5	analysis	analysis	NOUN
cana-5954	1	6	issn	issn	NOUN
cana-5954	1	7	:	:	PUNCT
cana-5954	1	8	1074	1074	NUM
cana-5954	1	9	-	-	PUNCT
cana-5954	1	10	133x	133x	NUM
cana-5954	1	11	vol	vol	VERB
cana-5954	1	12	32	32	NUM
cana-5954	1	13	no	no	NOUN
cana-5954	1	14	.	.	PUNCT
cana-5954	2	1	10s	10	NOUN
cana-5954	2	2	(	(	PUNCT
cana-5954	2	3	2025	2025	NUM
cana-5954	2	4	)	)	PUNCT
cana-5954	2	5	3173	3173	NUM
cana-5954	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	2	7	enhance	enhance	VERB
cana-5954	2	8	deep	deep	ADJ
cana-5954	2	9	learning	learning	NOUN
cana-5954	2	10	-	-	PUNCT
cana-5954	2	11	based	base	VERB
cana-5954	2	12	framworks	framwork	NOUN
cana-5954	2	13	dor	dor	PROPN
cana-5954	2	14	efficient	efficient	ADJ
cana-5954	2	15	covid-19	covid-19	PROPN
cana-5954	2	16	and	and	CCONJ
cana-5954	2	17	pneumonia	pneumonia	NOUN
cana-5954	2	18	detection	detection	NOUN
cana-5954	2	19	jeevan	jeevan	PROPN
cana-5954	2	20	kumar1	kumar1	PROPN
cana-5954	2	21	,	,	PUNCT
cana-5954	2	22	vijay	vijay	NOUN
cana-5954	2	23	pandey2	pandey2	PROPN
cana-5954	2	24	,	,	PUNCT
cana-5954	2	25	rajesh	rajesh	PROPN
cana-5954	2	26	kumar	kumar	PROPN
cana-5954	2	27	tiwari3	tiwari3	PROPN
cana-5954	2	28	department	department	PROPN
cana-5954	2	29	of	of	ADP
cana-5954	2	30	cse1	cse1	PROPN
cana-5954	2	31	,	,	PUNCT
cana-5954	2	32	3	3	NUM
cana-5954	2	33	,	,	PUNCT
cana-5954	2	34	department	department	NOUN
cana-5954	2	35	of	of	ADP
cana-5954	2	36	me2	me2	PROPN
cana-5954	2	37	jut	jut	PROPN
cana-5954	2	38	,	,	PUNCT
cana-5954	2	39	ranchi	ranchi	PROPN
cana-5954	2	40	,	,	PUNCT
cana-5954	2	41	jharkhand	jharkhand	PROPN
cana-5954	2	42	,	,	PUNCT
cana-5954	2	43	india1	india1	PROPN
cana-5954	2	44	,	,	PUNCT
cana-5954	2	45	bit	bit	NOUN
cana-5954	2	46	sindri	sindri	PROPN
cana-5954	2	47	,	,	PUNCT
cana-5954	2	48	jharkhand	jharkhand	PROPN
cana-5954	2	49	,	,	PUNCT
cana-5954	2	50	india2	india2	PROPN
cana-5954	2	51	,	,	PUNCT
cana-5954	2	52	rvscet	rvscet	PROPN
cana-5954	2	53	jamshedpur	jamshedpur	PROPN
cana-5954	2	54	,	,	PUNCT
cana-5954	2	55	jharkhand	jharkhand	PROPN
cana-5954	2	56	,	,	PUNCT
cana-5954	2	57	india3	india3	PROPN
cana-5954	2	58	jeevancse01@gmail.com1	jeevancse01@gmail.com1	PROPN
cana-5954	2	59	,	,	PUNCT
cana-5954	2	60	vpandey.me@bitsindri.ac.in2	vpandey.me@bitsindri.ac.in2	PROPN
cana-5954	2	61	,	,	PUNCT
cana-5954	2	62	rajeshkrtiwari@yahoo.com3	rajeshkrtiwari@yahoo.com3	NOUN
cana-5954	2	63	article	article	NOUN
cana-5954	2	64	history	history	NOUN
cana-5954	2	65	:	:	PUNCT
cana-5954	2	66	received	receive	VERB
cana-5954	2	67	:	:	PUNCT
cana-5954	2	68	02	02	NUM
cana-5954	2	69	-	-	PUNCT
cana-5954	2	70	01	01	NUM
cana-5954	2	71	-	-	PUNCT
cana-5954	2	72	2025	2025	NUM
cana-5954	2	73	revised	revise	VERB
cana-5954	2	74	:	:	PUNCT
cana-5954	2	75	25	25	NUM
cana-5954	2	76	-	-	PUNCT
cana-5954	2	77	02	02	NUM
cana-5954	2	78	-	-	PUNCT
cana-5954	2	79	2025	2025	NUM
cana-5954	2	80	accepted	accept	VERB
cana-5954	2	81	:	:	PUNCT
cana-5954	2	82	20	20	NUM
cana-5954	2	83	-	-	SYM
cana-5954	2	84	03	03	NUM
cana-5954	2	85	-	-	PUNCT
cana-5954	2	86	2025	2025	NUM
cana-5954	2	87	abstract	abstract	NOUN
cana-5954	2	88	:	:	PUNCT
cana-5954	3	1	covid-19	covid-19	PROPN
cana-5954	3	2	,	,	PUNCT
cana-5954	3	3	a	a	DET
cana-5954	3	4	contagious	contagious	ADJ
cana-5954	3	5	disease	disease	NOUN
cana-5954	3	6	caused	cause	VERB
cana-5954	3	7	by	by	ADP
cana-5954	3	8	a	a	DET
cana-5954	3	9	new	new	ADJ
cana-5954	3	10	virus	virus	NOUN
cana-5954	3	11	not	not	PART
cana-5954	3	12	before	before	ADV
cana-5954	3	13	encountered	encounter	VERB
cana-5954	3	14	in	in	ADP
cana-5954	3	15	humans	human	NOUN
cana-5954	3	16	,	,	PUNCT
cana-5954	3	17	has	have	VERB
cana-5954	3	18	clinical	clinical	ADJ
cana-5954	3	19	features	feature	NOUN
cana-5954	3	20	in	in	ADP
cana-5954	3	21	common	common	ADJ
cana-5954	3	22	with	with	ADP
cana-5954	3	23	the	the	DET
cana-5954	3	24	flu	flu	NOUN
cana-5954	3	25	,	,	PUNCT
cana-5954	3	26	displaying	display	VERB
cana-5954	3	27	symptoms	symptom	NOUN
cana-5954	3	28	such	such	ADJ
cana-5954	3	29	as	as	ADP
cana-5954	3	30	cough	cough	NOUN
cana-5954	3	31	and	and	CCONJ
cana-5954	3	32	fever	fever	NOUN
cana-5954	3	33	.	.	PUNCT
cana-5954	4	1	in	in	ADP
cana-5954	4	2	this	this	DET
cana-5954	4	3	research	research	NOUN
cana-5954	4	4	paper	paper	NOUN
cana-5954	4	5	,	,	PUNCT
cana-5954	4	6	we	we	PRON
cana-5954	4	7	introduce	introduce	VERB
cana-5954	4	8	a	a	DET
cana-5954	4	9	deep	deep	ADJ
cana-5954	4	10	learning	learning	NOUN
cana-5954	4	11	approach	approach	NOUN
cana-5954	4	12	to	to	PART
cana-5954	4	13	rapidly	rapidly	ADV
cana-5954	4	14	detect	detect	VERB
cana-5954	4	15	covid-19	covid-19	PROPN
cana-5954	4	16	and	and	CCONJ
cana-5954	4	17	pneumonia	pneumonia	NOUN
cana-5954	4	18	from	from	ADP
cana-5954	4	19	chest	chest	NOUN
cana-5954	4	20	x	x	NOUN
cana-5954	4	21	-	-	NOUN
cana-5954	4	22	ray	ray	NOUN
cana-5954	4	23	images	image	NOUN
cana-5954	4	24	.	.	PUNCT
cana-5954	5	1	using	use	VERB
cana-5954	5	2	new	new	ADJ
cana-5954	5	3	object	object	NOUN
cana-5954	5	4	detection	detection	NOUN
cana-5954	5	5	architecture	architecture	NOUN
cana-5954	5	6	,	,	PUNCT
cana-5954	5	7	which	which	PRON
cana-5954	5	8	was	be	AUX
cana-5954	5	9	trained	train	VERB
cana-5954	5	10	and	and	CCONJ
cana-5954	5	11	tested	test	VERB
cana-5954	5	12	on	on	ADP
cana-5954	5	13	a	a	DET
cana-5954	5	14	5,160	5,160	NUM
cana-5954	5	15	-	-	PUNCT
cana-5954	5	16	image	image	NOUN
cana-5954	5	17	dataset	dataset	NOUN
cana-5954	5	18	,	,	PUNCT
cana-5954	5	19	the	the	DET
cana-5954	5	20	model	model	NOUN
cana-5954	5	21	distinguishes	distinguish	VERB
cana-5954	5	22	between	between	ADP
cana-5954	5	23	non	non	ADJ
cana-5954	5	24	-	-	ADJ
cana-5954	5	25	infected	infected	ADJ
cana-5954	5	26	patients	patient	NOUN
cana-5954	5	27	and	and	CCONJ
cana-5954	5	28	covid-19	covid-19	PROPN
cana-5954	5	29	and	and	CCONJ
cana-5954	5	30	pneumonia	pneumonia	NOUN
cana-5954	5	31	-	-	PUNCT
cana-5954	5	32	affected	affect	VERB
cana-5954	5	33	patients	patient	NOUN
cana-5954	5	34	.	.	PUNCT
cana-5954	6	1	the	the	DET
cana-5954	6	2	new	new	ADJ
cana-5954	6	3	convolutional	convolutional	ADJ
cana-5954	6	4	channel	channel	NOUN
cana-5954	6	5	spatial	spatial	ADJ
cana-5954	6	6	attention	attention	NOUN
cana-5954	6	7	feature	feature	NOUN
cana-5954	6	8	extraction	extraction	NOUN
cana-5954	6	9	model	model	NOUN
cana-5954	6	10	(	(	PUNCT
cana-5954	6	11	ccsafem	ccsafem	PROPN
cana-5954	6	12	)	)	PUNCT
cana-5954	6	13	obtained	obtain	VERB
cana-5954	6	14	an	an	DET
cana-5954	6	15	accuracy	accuracy	NOUN
cana-5954	6	16	of	of	ADP
cana-5954	6	17	98.70	98.70	NUM
cana-5954	6	18	%	%	NOUN
cana-5954	6	19	in	in	ADP
cana-5954	6	20	covid-19	covid-19	PROPN
cana-5954	6	21	and	and	CCONJ
cana-5954	6	22	pneumonia	pneumonia	NOUN
cana-5954	6	23	case	case	NOUN
cana-5954	6	24	classification	classification	NOUN
cana-5954	6	25	.	.	PUNCT
cana-5954	7	1	this	this	PRON
cana-5954	7	2	shows	show	VERB
cana-5954	7	3	the	the	DET
cana-5954	7	4	capability	capability	NOUN
cana-5954	7	5	of	of	ADP
cana-5954	7	6	deep	deep	ADJ
cana-5954	7	7	learning	learning	NOUN
cana-5954	7	8	to	to	PART
cana-5954	7	9	precisely	precisely	ADV
cana-5954	7	10	detect	detect	VERB
cana-5954	7	11	respiratory	respiratory	ADJ
cana-5954	7	12	diseases	disease	NOUN
cana-5954	7	13	,	,	PUNCT
cana-5954	7	14	an	an	DET
cana-5954	7	15	important	important	ADJ
cana-5954	7	16	aspect	aspect	NOUN
cana-5954	7	17	in	in	ADP
cana-5954	7	18	the	the	DET
cana-5954	7	19	battle	battle	NOUN
cana-5954	7	20	against	against	ADP
cana-5954	7	21	covid-19	covid-19	PROPN
cana-5954	7	22	and	and	CCONJ
cana-5954	7	23	pneumonia	pneumonia	NOUN
cana-5954	7	24	.	.	PUNCT
cana-5954	8	1	keywords	keyword	NOUN
cana-5954	8	2	:	:	PUNCT
cana-5954	8	3	convolutional	convolutional	ADJ
cana-5954	8	4	neural	neural	ADJ
cana-5954	8	5	network	network	NOUN
cana-5954	8	6	,	,	PUNCT
cana-5954	8	7	covid19	covid19	NOUN
cana-5954	8	8	,	,	PUNCT
cana-5954	8	9	pneumonia	pneumonia	NOUN
cana-5954	8	10	,	,	PUNCT
cana-5954	8	11	resnet50	resnet50	NOUN
cana-5954	8	12	,	,	PUNCT
cana-5954	8	13	x	x	NOUN
cana-5954	8	14	-	-	NOUN
cana-5954	8	15	ray	ray	NOUN
cana-5954	8	16	images	image	NOUN
cana-5954	8	17	,	,	PUNCT
cana-5954	8	18	deep	deep	ADJ
cana-5954	8	19	learning	learning	NOUN
cana-5954	8	20	.	.	PUNCT
cana-5954	9	1	1	1	X
cana-5954	9	2	.	.	X
cana-5954	9	3	introduction	introduction	NOUN
cana-5954	9	4	toward	toward	ADP
cana-5954	9	5	the	the	DET
cana-5954	9	6	close	close	NOUN
cana-5954	9	7	of	of	ADP
cana-5954	9	8	2019	2019	NUM
cana-5954	9	9	,	,	PUNCT
cana-5954	9	10	a	a	DET
cana-5954	9	11	novel	novel	ADJ
cana-5954	9	12	coronavirus	coronavirus	NOUN
cana-5954	9	13	emerged	emerge	VERB
cana-5954	9	14	in	in	ADP
cana-5954	9	15	wuhan	wuhan	PROPN
cana-5954	9	16	,	,	PUNCT
cana-5954	9	17	china	china	PROPN
cana-5954	9	18	,	,	PUNCT
cana-5954	9	19	subsequently	subsequently	ADV
cana-5954	9	20	named	name	VERB
cana-5954	9	21	covid-19	covid-19	PROPN
cana-5954	9	22	.	.	PUNCT
cana-5954	10	1	the	the	DET
cana-5954	10	2	covid-19	covid-19	PROPN
cana-5954	10	3	has	have	VERB
cana-5954	10	4	a	a	DET
cana-5954	10	5	profound	profound	ADJ
cana-5954	10	6	global	global	ADJ
cana-5954	10	7	impact	impact	NOUN
cana-5954	10	8	,	,	PUNCT
cana-5954	10	9	affecting	affect	VERB
cana-5954	10	10	nearly	nearly	ADV
cana-5954	10	11	every	every	PRON
cana-5954	10	12	part	part	NOUN
cana-5954	10	13	of	of	ADP
cana-5954	10	14	the	the	DET
cana-5954	10	15	world	world	NOUN
cana-5954	10	16	.	.	PUNCT
cana-5954	11	1	notably	notably	ADV
cana-5954	11	2	,	,	PUNCT
cana-5954	11	3	older	old	ADJ
cana-5954	11	4	individuals	individual	NOUN
cana-5954	11	5	are	be	AUX
cana-5954	11	6	disproportionately	disproportionately	ADV
cana-5954	11	7	affected	affect	VERB
cana-5954	11	8	compared	compare	VERB
cana-5954	11	9	to	to	ADP
cana-5954	11	10	their	their	PRON
cana-5954	11	11	younger	young	ADJ
cana-5954	11	12	counterparts	counterpart	NOUN
cana-5954	11	13	.	.	PUNCT
cana-5954	12	1	the	the	DET
cana-5954	12	2	virus	virus	NOUN
cana-5954	12	3	primarily	primarily	ADV
cana-5954	12	4	causes	cause	VERB
cana-5954	12	5	symptoms	symptom	NOUN
cana-5954	12	6	related	relate	VERB
cana-5954	12	7	to	to	ADP
cana-5954	12	8	the	the	DET
cana-5954	12	9	respiratory	respiratory	ADJ
cana-5954	12	10	system	system	NOUN
cana-5954	12	11	,	,	PUNCT
cana-5954	12	12	including	include	VERB
cana-5954	12	13	fever	fever	NOUN
cana-5954	12	14	,	,	PUNCT
cana-5954	12	15	coughing	coughing	NOUN
cana-5954	12	16	,	,	PUNCT
cana-5954	12	17	taste	taste	NOUN
cana-5954	12	18	and	and	CCONJ
cana-5954	12	19	smell	smell	NOUN
cana-5954	12	20	loss	loss	NOUN
cana-5954	12	21	,	,	PUNCT
cana-5954	12	22	and	and	CCONJ
cana-5954	12	23	shortness	shortness	NOUN
cana-5954	12	24	of	of	ADP
cana-5954	12	25	breath	breath	NOUN
cana-5954	12	26	.	.	PUNCT
cana-5954	13	1	these	these	DET
cana-5954	13	2	symptoms	symptom	NOUN
cana-5954	13	3	are	be	AUX
cana-5954	13	4	often	often	ADV
cana-5954	13	5	shared	share	VERB
cana-5954	13	6	with	with	ADP
cana-5954	13	7	other	other	ADJ
cana-5954	13	8	viruses	virus	NOUN
cana-5954	13	9	like	like	ADP
cana-5954	13	10	the	the	DET
cana-5954	13	11	common	common	ADJ
cana-5954	13	12	cold	cold	NOUN
cana-5954	13	13	.	.	PUNCT
cana-5954	14	1	mitigating	mitigate	VERB
cana-5954	14	2	the	the	DET
cana-5954	14	3	spread	spread	NOUN
cana-5954	14	4	of	of	ADP
cana-5954	14	5	the	the	DET
cana-5954	14	6	virus	virus	NOUN
cana-5954	14	7	involves	involve	VERB
cana-5954	14	8	practices	practice	NOUN
cana-5954	14	9	such	such	ADJ
cana-5954	14	10	as	as	ADP
cana-5954	14	11	frequent	frequent	ADJ
cana-5954	14	12	hand	hand	NOUN
cana-5954	14	13	washing	washing	NOUN
cana-5954	14	14	with	with	ADP
cana-5954	14	15	sanitizer	sanitizer	NOUN
cana-5954	14	16	,	,	PUNCT
cana-5954	14	17	wearing	wear	VERB
cana-5954	14	18	masks	mask	NOUN
cana-5954	14	19	,	,	PUNCT
cana-5954	14	20	maintaining	maintain	VERB
cana-5954	14	21	physical	physical	ADJ
cana-5954	14	22	distance	distance	NOUN
cana-5954	14	23	,	,	PUNCT
cana-5954	14	24	and	and	CCONJ
cana-5954	14	25	receiving	receive	VERB
cana-5954	14	26	vaccinations	vaccination	NOUN
cana-5954	14	27	.	.	PUNCT
cana-5954	15	1	covid-19	covid-19	PROPN
cana-5954	15	2	differs	differ	VERB
cana-5954	15	3	from	from	ADP
cana-5954	15	4	other	other	ADJ
cana-5954	15	5	viruses	virus	NOUN
cana-5954	15	6	in	in	ADP
cana-5954	15	7	its	its	PRON
cana-5954	15	8	lengthy	lengthy	ADJ
cana-5954	15	9	incubation	incubation	NOUN
cana-5954	15	10	period	period	NOUN
cana-5954	15	11	,	,	PUNCT
cana-5954	15	12	ranging	range	VERB
cana-5954	15	13	from	from	ADP
cana-5954	15	14	three	three	NUM
cana-5954	15	15	to	to	PART
cana-5954	15	16	thirteen	thirteen	NUM
cana-5954	15	17	days	day	NOUN
cana-5954	15	18	,	,	PUNCT
cana-5954	15	19	with	with	ADP
cana-5954	15	20	an	an	DET
cana-5954	15	21	average	average	ADJ
cana-5954	15	22	onset	onset	NOUN
cana-5954	15	23	of	of	ADP
cana-5954	15	24	symptoms	symptom	NOUN
cana-5954	15	25	occurring	occur	VERB
cana-5954	15	26	around	around	ADV
cana-5954	15	27	five	five	NUM
cana-5954	15	28	to	to	PART
cana-5954	15	29	six	six	NUM
cana-5954	15	30	days	day	NOUN
cana-5954	15	31	after	after	ADP
cana-5954	15	32	exposure	exposure	NOUN
cana-5954	15	33	.	.	PUNCT
cana-5954	16	1	the	the	DET
cana-5954	16	2	convergence	convergence	NOUN
cana-5954	16	3	of	of	ADP
cana-5954	16	4	these	these	DET
cana-5954	16	5	factors	factor	NOUN
cana-5954	16	6	renders	render	VERB
cana-5954	16	7	covid-19	covid-19	PROPN
cana-5954	16	8	particularly	particularly	ADV
cana-5954	16	9	challenging	challenging	ADJ
cana-5954	16	10	to	to	PART
cana-5954	16	11	detect	detect	VERB
cana-5954	16	12	,	,	PUNCT
cana-5954	16	13	trace	trace	NOUN
cana-5954	16	14	,	,	PUNCT
cana-5954	16	15	and	and	CCONJ
cana-5954	16	16	contain	contain	VERB
cana-5954	16	17	,	,	PUNCT
cana-5954	16	18	contributing	contribute	VERB
cana-5954	16	19	to	to	ADP
cana-5954	16	20	its	its	PRON
cana-5954	16	21	rapid	rapid	ADJ
cana-5954	16	22	transmission	transmission	NOUN
cana-5954	16	23	.	.	PUNCT
cana-5954	17	1	globally	globally	ADV
cana-5954	17	2	,	,	PUNCT
cana-5954	17	3	approximately	approximately	ADV
cana-5954	17	4	two	two	NUM
cana-5954	17	5	million	million	NUM
cana-5954	17	6	individuals	individual	NOUN
cana-5954	17	7	are	be	AUX
cana-5954	17	8	affected	affect	VERB
cana-5954	17	9	by	by	ADP
cana-5954	17	10	pneumonia	pneumonia	NOUN
cana-5954	17	11	annually	annually	ADV
cana-5954	17	12	,	,	PUNCT
cana-5954	17	13	with	with	ADP
cana-5954	17	14	the	the	DET
cana-5954	17	15	potential	potential	NOUN
cana-5954	17	16	for	for	ADP
cana-5954	17	17	mortality	mortality	NOUN
cana-5954	17	18	if	if	SCONJ
cana-5954	17	19	left	leave	VERB
cana-5954	17	20	untreated	untreated	ADJ
cana-5954	17	21	.	.	PUNCT
cana-5954	18	1	timely	timely	ADJ
cana-5954	18	2	identification	identification	NOUN
cana-5954	18	3	of	of	ADP
cana-5954	18	4	pneumonia	pneumonia	NOUN
cana-5954	18	5	is	be	AUX
cana-5954	18	6	crucial	crucial	ADJ
cana-5954	18	7	.	.	PUNCT
cana-5954	19	1	for	for	ADP
cana-5954	19	2	accurate	accurate	ADJ
cana-5954	19	3	diagnosis	diagnosis	NOUN
cana-5954	19	4	and	and	CCONJ
cana-5954	19	5	to	to	PART
cana-5954	19	6	minimize	minimize	VERB
cana-5954	19	7	misinterpretation	misinterpretation	NOUN
cana-5954	19	8	,	,	PUNCT
cana-5954	19	9	prompt	prompt	ADJ
cana-5954	19	10	evaluation	evaluation	NOUN
cana-5954	19	11	by	by	ADP
cana-5954	19	12	a	a	DET
cana-5954	19	13	trained	train	VERB
cana-5954	19	14	person	person	NOUN
cana-5954	19	15	using	use	VERB
cana-5954	19	16	chest	chest	NOUN
cana-5954	19	17	xrays	xray	NOUN
cana-5954	19	18	is	be	AUX
cana-5954	19	19	essential	essential	ADJ
cana-5954	19	20	[	[	X
cana-5954	19	21	1	1	NUM
cana-5954	19	22	]	]	PUNCT
cana-5954	19	23	.	.	PUNCT
cana-5954	20	1	pneumonia	pneumonia	NOUN
cana-5954	20	2	can	can	AUX
cana-5954	20	3	range	range	VERB
cana-5954	20	4	from	from	ADP
cana-5954	20	5	mild	mild	ADJ
cana-5954	20	6	to	to	ADP
cana-5954	20	7	severe	severe	ADJ
cana-5954	20	8	,	,	PUNCT
cana-5954	20	9	regardless	regardless	ADV
cana-5954	20	10	of	of	ADP
cana-5954	20	11	the	the	DET
cana-5954	20	12	causative	causative	ADJ
cana-5954	20	13	bacteria	bacteria	NOUN
cana-5954	20	14	,	,	PUNCT
cana-5954	20	15	and	and	CCONJ
cana-5954	20	16	can	can	AUX
cana-5954	20	17	be	be	AUX
cana-5954	20	18	influenced	influence	VERB
cana-5954	20	19	by	by	ADP
cana-5954	20	20	factors	factor	NOUN
cana-5954	20	21	such	such	ADJ
cana-5954	20	22	as	as	ADP
cana-5954	20	23	age	age	NOUN
cana-5954	20	24	and	and	CCONJ
cana-5954	20	25	overall	overall	ADJ
cana-5954	20	26	health	health	NOUN
cana-5954	20	27	.	.	PUNCT
cana-5954	21	1	common	common	ADJ
cana-5954	21	2	symptoms	symptom	NOUN
cana-5954	21	3	include	include	VERB
cana-5954	21	4	cold	cold	ADJ
cana-5954	21	5	and	and	CCONJ
cana-5954	21	6	flu	flu	NOUN
cana-5954	21	7	-	-	PUNCT
cana-5954	21	8	like	like	ADJ
cana-5954	21	9	symptoms	symptom	NOUN
cana-5954	21	10	,	,	PUNCT
cana-5954	21	11	which	which	PRON
cana-5954	21	12	can	can	AUX
cana-5954	21	13	escalate	escalate	VERB
cana-5954	21	14	to	to	ADP
cana-5954	21	15	life	life	NOUN
cana-5954	21	16	-	-	PUNCT
cana-5954	21	17	threatening	threaten	VERB
cana-5954	21	18	conditions	condition	NOUN
cana-5954	21	19	.	.	PUNCT
cana-5954	22	1	other	other	ADJ
cana-5954	22	2	symptoms	symptom	NOUN
cana-5954	22	3	may	may	AUX
cana-5954	22	4	include	include	VERB
cana-5954	22	5	difficulty	difficulty	NOUN
cana-5954	22	6	breathing	breathing	NOUN
cana-5954	22	7	,	,	PUNCT
cana-5954	22	8	chest	chest	NOUN
cana-5954	22	9	pain	pain	NOUN
cana-5954	22	10	,	,	PUNCT
cana-5954	22	11	cough	cough	NOUN
cana-5954	22	12	with	with	ADP
cana-5954	22	13	phlegm	phlegm	NOUN
cana-5954	22	14	,	,	PUNCT
cana-5954	22	15	fatigue	fatigue	NOUN
cana-5954	22	16	,	,	PUNCT
cana-5954	22	17	nausea	nausea	NOUN
cana-5954	22	18	,	,	PUNCT
cana-5954	22	19	vomiting	vomiting	NOUN
cana-5954	22	20	,	,	PUNCT
cana-5954	22	21	shortness	shortness	NOUN
cana-5954	22	22	of	of	ADP
cana-5954	22	23	breath	breath	NOUN
cana-5954	22	24	,	,	PUNCT
cana-5954	22	25	sweating	sweating	NOUN
cana-5954	22	26	,	,	PUNCT
cana-5954	22	27	and	and	CCONJ
cana-5954	22	28	shaking	shake	VERB
cana-5954	22	29	chills	chill	NOUN
cana-5954	22	30	.	.	PUNCT
cana-5954	23	1	the	the	DET
cana-5954	23	2	purpose	purpose	NOUN
cana-5954	23	3	of	of	ADP
cana-5954	23	4	this	this	DET
cana-5954	23	5	study	study	NOUN
cana-5954	23	6	is	be	AUX
cana-5954	23	7	to	to	PART
cana-5954	23	8	improve	improve	VERB
cana-5954	23	9	the	the	DET
cana-5954	23	10	rapid	rapid	ADJ
cana-5954	23	11	and	and	CCONJ
cana-5954	23	12	accurate	accurate	ADJ
cana-5954	23	13	diagnosis	diagnosis	NOUN
cana-5954	23	14	of	of	ADP
cana-5954	23	15	covid-19	covid-19	PROPN
cana-5954	23	16	and	and	CCONJ
cana-5954	23	17	pneumonia	pneumonia	NOUN
cana-5954	23	18	patients	patient	NOUN
cana-5954	23	19	.	.	PUNCT
cana-5954	24	1	the	the	DET
cana-5954	24	2	proposed	propose	VERB
cana-5954	24	3	model	model	NOUN
cana-5954	24	4	made	make	VERB
cana-5954	24	5	use	use	NOUN
cana-5954	24	6	of	of	ADP
cana-5954	24	7	x	x	NOUN
cana-5954	24	8	-	-	NOUN
cana-5954	24	9	ray	ray	NOUN
cana-5954	24	10	images	image	NOUN
cana-5954	24	11	and	and	CCONJ
cana-5954	24	12	mailto	mailto	NOUN
cana-5954	24	13	:	:	PUNCT
cana-5954	24	14	jeevancse01@gmail.com1	jeevancse01@gmail.com1	PROPN
cana-5954	24	15	mailto:vpandey.me@bitsindri.ac.in	mailto:vpandey.me@bitsindri.ac.in	PROPN
cana-5954	24	16	mailto:rajeshkrtiwari@yahoo.com	mailto:rajeshkrtiwari@yahoo.com	PROPN
cana-5954	24	17	communications	communication	NOUN
cana-5954	24	18	on	on	ADP
cana-5954	24	19	applied	apply	VERB
cana-5954	24	20	nonlinear	nonlinear	ADJ
cana-5954	24	21	analysis	analysis	NOUN
cana-5954	24	22	issn	issn	NOUN
cana-5954	24	23	:	:	PUNCT
cana-5954	24	24	1074	1074	NUM
cana-5954	24	25	-	-	PUNCT
cana-5954	24	26	133x	133x	NUM
cana-5954	24	27	vol	vol	VERB
cana-5954	24	28	32	32	NUM
cana-5954	24	29	no	no	NOUN
cana-5954	24	30	.	.	PUNCT
cana-5954	25	1	10s	10	NOUN
cana-5954	25	2	(	(	PUNCT
cana-5954	25	3	2025	2025	NUM
cana-5954	25	4	)	)	PUNCT
cana-5954	25	5	3174	3174	NUM
cana-5954	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	25	7	deep	deep	ADJ
cana-5954	25	8	learning	learning	NOUN
cana-5954	25	9	methods	method	NOUN
cana-5954	25	10	,	,	PUNCT
cana-5954	25	11	including	include	VERB
cana-5954	25	12	cnns	cnn	NOUN
cana-5954	25	13	.	.	PUNCT
cana-5954	26	1	there	there	PRON
cana-5954	26	2	is	be	VERB
cana-5954	26	3	a	a	DET
cana-5954	26	4	pressing	press	VERB
cana-5954	26	5	need	need	NOUN
cana-5954	26	6	for	for	ADP
cana-5954	26	7	a	a	DET
cana-5954	26	8	reliable	reliable	ADJ
cana-5954	26	9	and	and	CCONJ
cana-5954	26	10	precise	precise	ADJ
cana-5954	26	11	solution	solution	NOUN
cana-5954	26	12	to	to	PART
cana-5954	26	13	aid	aid	VERB
cana-5954	26	14	healthcare	healthcare	NOUN
cana-5954	26	15	decision	decision	NOUN
cana-5954	26	16	-	-	PUNCT
cana-5954	26	17	making	making	NOUN
cana-5954	26	18	based	base	VERB
cana-5954	26	19	on	on	ADP
cana-5954	26	20	medical	medical	ADJ
cana-5954	26	21	imaging	imaging	NOUN
cana-5954	26	22	.	.	PUNCT
cana-5954	27	1	the	the	DET
cana-5954	27	2	use	use	NOUN
cana-5954	27	3	of	of	ADP
cana-5954	27	4	deep	deep	ADJ
cana-5954	27	5	learning	learning	NOUN
cana-5954	27	6	techniques	technique	NOUN
cana-5954	27	7	to	to	PART
cana-5954	27	8	help	help	VERB
cana-5954	27	9	treat	treat	VERB
cana-5954	27	10	covid-19	covid-19	PROPN
cana-5954	27	11	and	and	CCONJ
cana-5954	27	12	pneumonia	pneumonia	NOUN
cana-5954	27	13	patients	patient	NOUN
cana-5954	27	14	has	have	AUX
cana-5954	27	15	been	be	AUX
cana-5954	27	16	shown	show	VERB
cana-5954	27	17	to	to	PART
cana-5954	27	18	have	have	VERB
cana-5954	27	19	a	a	DET
cana-5954	27	20	research	research	NOUN
cana-5954	27	21	gap	gap	NOUN
cana-5954	27	22	,	,	PUNCT
cana-5954	27	23	particularly	particularly	ADV
cana-5954	27	24	in	in	ADP
cana-5954	27	25	light	light	NOUN
cana-5954	27	26	of	of	ADP
cana-5954	27	27	the	the	DET
cana-5954	27	28	large	large	ADJ
cana-5954	27	29	number	number	NOUN
cana-5954	27	30	of	of	ADP
cana-5954	27	31	instances	instance	NOUN
cana-5954	27	32	that	that	PRON
cana-5954	27	33	call	call	VERB
cana-5954	27	34	for	for	ADP
cana-5954	27	35	an	an	DET
cana-5954	27	36	automated	automate	VERB
cana-5954	27	37	approach	approach	NOUN
cana-5954	27	38	for	for	ADP
cana-5954	27	39	prompt	prompt	ADJ
cana-5954	27	40	diagnosis	diagnosis	NOUN
cana-5954	27	41	.	.	PUNCT
cana-5954	28	1	1.1	1.1	NUM
cana-5954	28	2	motivation	motivation	NOUN
cana-5954	28	3	for	for	ADP
cana-5954	28	4	the	the	DET
cana-5954	28	5	work	work	NOUN
cana-5954	28	6	the	the	DET
cana-5954	28	7	primary	primary	ADJ
cana-5954	28	8	motivation	motivation	NOUN
cana-5954	28	9	behind	behind	ADP
cana-5954	28	10	this	this	DET
cana-5954	28	11	research	research	NOUN
cana-5954	28	12	is	be	AUX
cana-5954	28	13	to	to	PART
cana-5954	28	14	develop	develop	VERB
cana-5954	28	15	a	a	DET
cana-5954	28	16	predictive	predictive	ADJ
cana-5954	28	17	model	model	NOUN
cana-5954	28	18	for	for	ADP
cana-5954	28	19	covid-19	covid-19	PROPN
cana-5954	28	20	and	and	CCONJ
cana-5954	28	21	pneumonia	pneumonia	NOUN
cana-5954	28	22	occurrence	occurrence	NOUN
cana-5954	28	23	.	.	PUNCT
cana-5954	29	1	identifying	identify	VERB
cana-5954	29	2	the	the	DET
cana-5954	29	3	best	good	ADJ
cana-5954	29	4	classification	classification	NOUN
cana-5954	29	5	method	method	NOUN
cana-5954	29	6	to	to	PART
cana-5954	29	7	forecast	forecast	VERB
cana-5954	29	8	a	a	DET
cana-5954	29	9	patient	patient	NOUN
cana-5954	29	10	's	's	PART
cana-5954	29	11	risk	risk	NOUN
cana-5954	29	12	of	of	ADP
cana-5954	29	13	developing	develop	VERB
cana-5954	29	14	these	these	DET
cana-5954	29	15	illnesses	illness	NOUN
cana-5954	29	16	is	be	AUX
cana-5954	29	17	another	another	DET
cana-5954	29	18	goal	goal	NOUN
cana-5954	29	19	of	of	ADP
cana-5954	29	20	the	the	DET
cana-5954	29	21	project	project	NOUN
cana-5954	29	22	.	.	PUNCT
cana-5954	30	1	even	even	ADV
cana-5954	30	2	if	if	SCONJ
cana-5954	30	3	deep	deep	ADJ
cana-5954	30	4	learning	learning	NOUN
cana-5954	30	5	algorithms	algorithm	NOUN
cana-5954	30	6	are	be	AUX
cana-5954	30	7	frequently	frequently	ADV
cana-5954	30	8	employed	employ	VERB
cana-5954	30	9	for	for	ADP
cana-5954	30	10	these	these	DET
cana-5954	30	11	kinds	kind	NOUN
cana-5954	30	12	of	of	ADP
cana-5954	30	13	tasks	task	NOUN
cana-5954	30	14	,	,	PUNCT
cana-5954	30	15	it	it	PRON
cana-5954	30	16	is	be	AUX
cana-5954	30	17	still	still	ADV
cana-5954	30	18	crucial	crucial	ADJ
cana-5954	30	19	to	to	PART
cana-5954	30	20	maximize	maximize	VERB
cana-5954	30	21	accuracy	accuracy	NOUN
cana-5954	30	22	when	when	SCONJ
cana-5954	30	23	predicting	predict	VERB
cana-5954	30	24	covid-19	covid-19	PROPN
cana-5954	30	25	and	and	CCONJ
cana-5954	30	26	pneumonia.this	pneumonia.this	PRON
cana-5954	30	27	research	research	NOUN
cana-5954	30	28	endeavor	endeavor	NOUN
cana-5954	30	29	seeks	seek	VERB
cana-5954	30	30	to	to	PART
cana-5954	30	31	empower	empower	VERB
cana-5954	30	32	researchers	researcher	NOUN
cana-5954	30	33	and	and	CCONJ
cana-5954	30	34	medical	medical	ADJ
cana-5954	30	35	practitioners	practitioner	NOUN
cana-5954	30	36	to	to	PART
cana-5954	30	37	enhance	enhance	VERB
cana-5954	30	38	diagnostic	diagnostic	ADJ
cana-5954	30	39	capabilities	capability	NOUN
cana-5954	30	40	and	and	CCONJ
cana-5954	30	41	patient	patient	ADJ
cana-5954	30	42	care	care	NOUN
cana-5954	30	43	.	.	PUNCT
cana-5954	31	1	1.2	1.2	NUM
cana-5954	31	2	problem	problem	NOUN
cana-5954	31	3	statement	statement	NOUN
cana-5954	31	4	detecting	detect	VERB
cana-5954	31	5	covid-19	covid-19	PROPN
cana-5954	31	6	and	and	CCONJ
cana-5954	31	7	pneumonia	pneumonia	NOUN
cana-5954	31	8	poses	pose	VERB
cana-5954	31	9	a	a	DET
cana-5954	31	10	significant	significant	ADJ
cana-5954	31	11	challenge	challenge	NOUN
cana-5954	31	12	due	due	ADP
cana-5954	31	13	to	to	ADP
cana-5954	31	14	the	the	DET
cana-5954	31	15	limitations	limitation	NOUN
cana-5954	31	16	of	of	ADP
cana-5954	31	17	available	available	ADJ
cana-5954	31	18	instruments	instrument	NOUN
cana-5954	31	19	,	,	PUNCT
cana-5954	31	20	which	which	PRON
cana-5954	31	21	are	be	AUX
cana-5954	31	22	either	either	CCONJ
cana-5954	31	23	expensive	expensive	ADJ
cana-5954	31	24	or	or	CCONJ
cana-5954	31	25	lack	lack	NOUN
cana-5954	31	26	efficiency	efficiency	NOUN
cana-5954	31	27	in	in	ADP
cana-5954	31	28	accurately	accurately	ADV
cana-5954	31	29	assessing	assess	VERB
cana-5954	31	30	the	the	DET
cana-5954	31	31	likelihood	likelihood	NOUN
cana-5954	31	32	of	of	ADP
cana-5954	31	33	these	these	DET
cana-5954	31	34	diseases	disease	NOUN
cana-5954	31	35	in	in	ADP
cana-5954	31	36	individuals	individual	NOUN
cana-5954	31	37	.	.	PUNCT
cana-5954	32	1	in	in	ADP
cana-5954	32	2	order	order	NOUN
cana-5954	32	3	to	to	PART
cana-5954	32	4	reduce	reduce	VERB
cana-5954	32	5	death	death	NOUN
cana-5954	32	6	rates	rate	NOUN
cana-5954	32	7	and	and	CCONJ
cana-5954	32	8	the	the	DET
cana-5954	32	9	problems	problem	NOUN
cana-5954	32	10	associated	associate	VERB
cana-5954	32	11	with	with	ADP
cana-5954	32	12	these	these	DET
cana-5954	32	13	disorders	disorder	NOUN
cana-5954	32	14	,	,	PUNCT
cana-5954	32	15	early	early	ADJ
cana-5954	32	16	detection	detection	NOUN
cana-5954	32	17	is	be	AUX
cana-5954	32	18	important	important	ADJ
cana-5954	32	19	.	.	PUNCT
cana-5954	33	1	the	the	DET
cana-5954	33	2	main	main	ADJ
cana-5954	33	3	contributions	contribution	NOUN
cana-5954	33	4	of	of	ADP
cana-5954	33	5	our	our	PRON
cana-5954	33	6	research	research	NOUN
cana-5954	33	7	are	be	AUX
cana-5954	33	8	as	as	SCONJ
cana-5954	33	9	follows	follow	VERB
cana-5954	33	10	:	:	PUNCT
cana-5954	33	11	•	•	NUM
cana-5954	33	12	developed	develop	VERB
cana-5954	33	13	a	a	DET
cana-5954	33	14	deep	deep	ADJ
cana-5954	33	15	learning	learning	NOUN
cana-5954	33	16	methodology	methodology	NOUN
cana-5954	33	17	using	use	VERB
cana-5954	33	18	the	the	DET
cana-5954	33	19	convolutional	convolutional	ADJ
cana-5954	33	20	channel	channel	NOUN
cana-5954	33	21	spatial	spatial	ADJ
cana-5954	33	22	attention	attention	NOUN
cana-5954	33	23	feature	feature	NOUN
cana-5954	33	24	extract	extract	NOUN
cana-5954	33	25	model	model	NOUN
cana-5954	33	26	(	(	PUNCT
cana-5954	33	27	ccsafem	ccsafem	NOUN
cana-5954	33	28	)	)	PUNCT
cana-5954	33	29	for	for	ADP
cana-5954	33	30	accurate	accurate	ADJ
cana-5954	33	31	detection	detection	NOUN
cana-5954	33	32	of	of	ADP
cana-5954	33	33	covid-19	covid-19	PROPN
cana-5954	33	34	and	and	CCONJ
cana-5954	33	35	pneumonia	pneumonia	NOUN
cana-5954	33	36	in	in	ADP
cana-5954	33	37	chest	chest	NOUN
cana-5954	33	38	ct	ct	NUM
cana-5954	33	39	scans	scan	NOUN
cana-5954	33	40	.	.	PUNCT
cana-5954	34	1	•	•	NUM
cana-5954	34	2	integrated	integrate	VERB
cana-5954	34	3	an	an	DET
cana-5954	34	4	attention	attention	NOUN
cana-5954	34	5	mechanism	mechanism	NOUN
cana-5954	34	6	into	into	ADP
cana-5954	34	7	features	feature	NOUN
cana-5954	34	8	extracted	extract	VERB
cana-5954	34	9	from	from	ADP
cana-5954	34	10	resnet	resnet	NOUN
cana-5954	34	11	50	50	NUM
cana-5954	34	12	,	,	PUNCT
cana-5954	34	13	with	with	ADP
cana-5954	34	14	hyper	hyper	ADJ
cana-5954	34	15	parameter	parameter	NOUN
cana-5954	34	16	tuning	tune	VERB
cana-5954	34	17	to	to	PART
cana-5954	34	18	enhance	enhance	VERB
cana-5954	34	19	performance	performance	NOUN
cana-5954	34	20	.	.	PUNCT
cana-5954	35	1	this	this	DET
cana-5954	35	2	paper	paper	NOUN
cana-5954	35	3	is	be	AUX
cana-5954	35	4	organized	organize	VERB
cana-5954	35	5	into	into	ADP
cana-5954	35	6	a	a	DET
cana-5954	35	7	number	number	NOUN
cana-5954	35	8	of	of	ADP
cana-5954	35	9	sub	sub	NOUN
cana-5954	35	10	-	-	NOUN
cana-5954	35	11	sections	section	NOUN
cana-5954	35	12	:	:	PUNCT
cana-5954	35	13	section	section	NOUN
cana-5954	35	14	2	2	NUM
cana-5954	35	15	provides	provide	VERB
cana-5954	35	16	an	an	DET
cana-5954	35	17	extensive	extensive	ADJ
cana-5954	35	18	discussion	discussion	NOUN
cana-5954	35	19	on	on	ADP
cana-5954	35	20	deep	deep	ADJ
cana-5954	35	21	learning	learning	NOUN
cana-5954	35	22	models	model	NOUN
cana-5954	35	23	for	for	ADP
cana-5954	35	24	covid-19	covid-19	PROPN
cana-5954	35	25	and	and	CCONJ
cana-5954	35	26	pneumonia	pneumonia	NOUN
cana-5954	35	27	prediction	prediction	NOUN
cana-5954	35	28	.	.	PUNCT
cana-5954	36	1	the	the	DET
cana-5954	36	2	overview	overview	NOUN
cana-5954	36	3	of	of	ADP
cana-5954	36	4	the	the	DET
cana-5954	36	5	data	datum	NOUN
cana-5954	36	6	,	,	PUNCT
cana-5954	36	7	together	together	ADV
cana-5954	36	8	with	with	ADP
cana-5954	36	9	the	the	DET
cana-5954	36	10	number	number	NOUN
cana-5954	36	11	of	of	ADP
cana-5954	36	12	attributes	attribute	NOUN
cana-5954	36	13	and	and	CCONJ
cana-5954	36	14	their	their	PRON
cana-5954	36	15	descriptions	description	NOUN
cana-5954	36	16	,	,	PUNCT
cana-5954	36	17	is	be	AUX
cana-5954	36	18	explained	explain	VERB
cana-5954	36	19	in	in	ADP
cana-5954	36	20	section	section	NOUN
cana-5954	36	21	3	3	NUM
cana-5954	36	22	.	.	PUNCT
cana-5954	36	23	section	section	NOUN
cana-5954	36	24	4	4	NUM
cana-5954	36	25	includes	include	VERB
cana-5954	36	26	the	the	DET
cana-5954	36	27	results	result	NOUN
cana-5954	36	28	and	and	CCONJ
cana-5954	36	29	analysis	analysis	NOUN
cana-5954	36	30	.	.	PUNCT
cana-5954	37	1	lastly	lastly	ADV
cana-5954	37	2	,	,	PUNCT
cana-5954	37	3	section	section	NOUN
cana-5954	37	4	5	5	NUM
cana-5954	37	5	gives	give	VERB
cana-5954	37	6	the	the	DET
cana-5954	37	7	conclusion	conclusion	NOUN
cana-5954	37	8	of	of	ADP
cana-5954	37	9	the	the	DET
cana-5954	37	10	paper	paper	NOUN
cana-5954	37	11	.	.	PUNCT
cana-5954	38	1	2	2	X
cana-5954	38	2	.	.	X
cana-5954	38	3	related	relate	VERB
cana-5954	38	4	work	work	NOUN
cana-5954	38	5	in	in	ADP
cana-5954	38	6	the	the	DET
cana-5954	38	7	field	field	NOUN
cana-5954	38	8	of	of	ADP
cana-5954	38	9	medical	medical	ADJ
cana-5954	38	10	data	datum	NOUN
cana-5954	38	11	processing	processing	NOUN
cana-5954	38	12	,	,	PUNCT
cana-5954	38	13	data	datum	NOUN
cana-5954	38	14	scientists	scientist	NOUN
cana-5954	38	15	play	play	VERB
cana-5954	38	16	a	a	DET
cana-5954	38	17	vital	vital	ADJ
cana-5954	38	18	role	role	NOUN
cana-5954	38	19	in	in	ADP
cana-5954	38	20	advancing	advance	VERB
cana-5954	38	21	medical	medical	ADJ
cana-5954	38	22	sciences	science	NOUN
cana-5954	38	23	through	through	ADP
cana-5954	38	24	their	their	PRON
cana-5954	38	25	significant	significant	ADJ
cana-5954	38	26	contributions	contribution	NOUN
cana-5954	38	27	.	.	PUNCT
cana-5954	39	1	they	they	PRON
cana-5954	39	2	employ	employ	VERB
cana-5954	39	3	deep	deep	ADJ
cana-5954	39	4	learning	learning	NOUN
cana-5954	39	5	,	,	PUNCT
cana-5954	39	6	machine	machine	NOUN
cana-5954	39	7	learning	learning	NOUN
cana-5954	39	8	,	,	PUNCT
cana-5954	39	9	and	and	CCONJ
cana-5954	39	10	data	datum	NOUN
cana-5954	39	11	extraction	extraction	NOUN
cana-5954	39	12	techniques	technique	NOUN
cana-5954	39	13	extensively	extensively	ADV
cana-5954	39	14	to	to	PART
cana-5954	39	15	extract	extract	VERB
cana-5954	39	16	specific	specific	ADJ
cana-5954	39	17	features	feature	NOUN
cana-5954	39	18	from	from	ADP
cana-5954	39	19	image	image	NOUN
cana-5954	39	20	datasets	dataset	NOUN
cana-5954	39	21	,	,	PUNCT
cana-5954	39	22	facilitating	facilitate	VERB
cana-5954	39	23	disease	disease	NOUN
cana-5954	39	24	diagnosis	diagnosis	NOUN
cana-5954	39	25	and	and	CCONJ
cana-5954	39	26	prediction	prediction	NOUN
cana-5954	39	27	.	.	PUNCT
cana-5954	40	1	as	as	SCONJ
cana-5954	40	2	shown	show	VERB
cana-5954	40	3	in	in	ADP
cana-5954	40	4	table	table	NOUN
cana-5954	40	5	1	1	NUM
cana-5954	40	6	.	.	PUNCT
cana-5954	40	7	table	table	NOUN
cana-5954	40	8	1	1	NUM
cana-5954	40	9	.	.	PUNCT
cana-5954	40	10	existing	exist	VERB
cana-5954	40	11	literature	literature	NOUN
cana-5954	40	12	review	review	NOUN
cana-5954	40	13	author	author	NOUN
cana-5954	40	14	&	&	CCONJ
cana-5954	40	15	reference	reference	PROPN
cana-5954	40	16	year	year	NOUN
cana-5954	40	17	method	method	NOUN
cana-5954	40	18	used	use	VERB
cana-5954	40	19	description	description	NOUN
cana-5954	40	20	wang	wang	PROPN
cana-5954	40	21	et	et	PROPN
cana-5954	40	22	al	al	PROPN
cana-5954	40	23	.	.	PUNCT
cana-5954	41	1	[	[	X
cana-5954	41	2	2	2	NUM
cana-5954	41	3	]	]	SYM
cana-5954	41	4	2020	2020	NUM
cana-5954	41	5	cnn	cnn	PROPN
cana-5954	41	6	radiographs	radiograph	NOUN
cana-5954	41	7	of	of	ADP
cana-5954	41	8	pneumonia	pneumonia	NOUN
cana-5954	41	9	patients	patient	NOUN
cana-5954	41	10	along	along	ADP
cana-5954	41	11	with	with	ADP
cana-5954	41	12	ct	ct	NUM
cana-5954	41	13	images	image	NOUN
cana-5954	41	14	of	of	ADP
cana-5954	41	15	covid19	covid19	NOUN
cana-5954	41	16	-	-	PUNCT
cana-5954	41	17	positive	positive	ADJ
cana-5954	41	18	patients	patient	NOUN
cana-5954	41	19	are	be	AUX
cana-5954	41	20	fed	feed	VERB
cana-5954	41	21	into	into	ADP
cana-5954	41	22	deep	deep	ADJ
cana-5954	41	23	learning	learning	NOUN
cana-5954	41	24	algorithm	algorithm	NOUN
cana-5954	41	25	architecture	architecture	NOUN
cana-5954	41	26	.	.	PUNCT
cana-5954	42	1	communications	communication	NOUN
cana-5954	42	2	on	on	ADP
cana-5954	42	3	applied	apply	VERB
cana-5954	42	4	nonlinear	nonlinear	ADJ
cana-5954	42	5	analysis	analysis	NOUN
cana-5954	42	6	issn	issn	NOUN
cana-5954	42	7	:	:	PUNCT
cana-5954	42	8	1074	1074	NUM
cana-5954	42	9	-	-	PUNCT
cana-5954	42	10	133x	133x	NUM
cana-5954	42	11	vol	vol	VERB
cana-5954	42	12	32	32	NUM
cana-5954	42	13	no	no	NOUN
cana-5954	42	14	.	.	PUNCT
cana-5954	43	1	10s	10	NOUN
cana-5954	43	2	(	(	PUNCT
cana-5954	43	3	2025	2025	NUM
cana-5954	43	4	)	)	PUNCT
cana-5954	43	5	3175	3175	NUM
cana-5954	44	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	44	2	xiaowei	xiaowei	PROPN
cana-5954	44	3	et	et	PROPN
cana-5954	44	4	al	al	PROPN
cana-5954	45	1	[	[	X
cana-5954	45	2	3	3	NUM
cana-5954	45	3	]	]	SYM
cana-5954	45	4	2020	2020	NUM
cana-5954	45	5	pulmonary	pulmonary	NOUN
cana-5954	45	6	ct	ct	PROPN
cana-5954	45	7	scans	scan	NOUN
cana-5954	45	8	and	and	CCONJ
cana-5954	45	9	several	several	ADJ
cana-5954	45	10	cnn	cnn	PROPN
cana-5954	45	11	several	several	ADJ
cana-5954	45	12	cnn	cnn	PROPN
cana-5954	45	13	models	model	NOUN
cana-5954	45	14	and	and	CCONJ
cana-5954	45	15	pulmonary	pulmonary	ADJ
cana-5954	45	16	ct	ct	PROPN
cana-5954	45	17	scans	scan	NOUN
cana-5954	45	18	are	be	AUX
cana-5954	45	19	used	use	VERB
cana-5954	45	20	in	in	ADP
cana-5954	45	21	this	this	DET
cana-5954	45	22	model	model	NOUN
cana-5954	45	23	's	's	PART
cana-5954	45	24	execution	execution	NOUN
cana-5954	45	25	.	.	PUNCT
cana-5954	46	1	netzahualcoyotl	netzahualcoyotl	PROPN
cana-5954	46	2	hernandez‑cruz	hernandez‑cruz	PROPN
cana-5954	47	1	[	[	X
cana-5954	47	2	4	4	NUM
cana-5954	47	3	]	]	SYM
cana-5954	47	4	2021	2021	NUM
cana-5954	47	5	neural	neural	ADJ
cana-5954	47	6	style	style	NOUN
cana-5954	47	7	transfer	transfer	NOUN
cana-5954	47	8	it	it	PRON
cana-5954	47	9	shows	show	VERB
cana-5954	47	10	the	the	DET
cana-5954	47	11	cycle	cycle	NOUN
cana-5954	47	12	-	-	PUNCT
cana-5954	47	13	generative	generative	ADJ
cana-5954	47	14	adversarial	adversarial	ADJ
cana-5954	47	15	network	network	NOUN
cana-5954	47	16	's	's	PART
cana-5954	47	17	effectiveness	effectiveness	NOUN
cana-5954	47	18	,	,	PUNCT
cana-5954	47	19	which	which	PRON
cana-5954	47	20	is	be	AUX
cana-5954	47	21	pervasive	pervasive	ADJ
cana-5954	47	22	in	in	ADP
cana-5954	47	23	neural	neural	ADJ
cana-5954	47	24	style	style	NOUN
cana-5954	47	25	transfer	transfer	NOUN
cana-5954	47	26	.	.	PUNCT
cana-5954	48	1	shah	shah	PROPN
cana-5954	48	2	siddiqui	siddiqui	PROPN
cana-5954	48	3	et	et	PROPN
cana-5954	48	4	al	al	PROPN
cana-5954	49	1	[	[	X
cana-5954	49	2	5	5	NUM
cana-5954	49	3	]	]	PUNCT
cana-5954	49	4	2022	2022	NUM
cana-5954	49	5	cnn	cnn	PROPN
cana-5954	49	6	the	the	DET
cana-5954	49	7	purpose	purpose	NOUN
cana-5954	49	8	of	of	ADP
cana-5954	49	9	classifying	classify	VERB
cana-5954	49	10	and	and	CCONJ
cana-5954	49	11	identifying	identify	VERB
cana-5954	49	12	covid-19	covid-19	PROPN
cana-5954	49	13	in	in	ADP
cana-5954	49	14	x	x	NOUN
cana-5954	49	15	-	-	NOUN
cana-5954	49	16	ray	ray	NOUN
cana-5954	49	17	and	and	CCONJ
cana-5954	49	18	ct	ct	NUM
cana-5954	49	19	pictures	picture	NOUN
cana-5954	49	20	,	,	PUNCT
cana-5954	49	21	cnns	cnns	PROPN
cana-5954	49	22	are	be	AUX
cana-5954	49	23	the	the	DET
cana-5954	49	24	most	most	ADV
cana-5954	49	25	widely	widely	ADV
cana-5954	49	26	utilised	utilise	VERB
cana-5954	49	27	deep	deep	ADJ
cana-5954	49	28	learning	learning	NOUN
cana-5954	49	29	architecture	architecture	NOUN
cana-5954	49	30	.	.	PUNCT
cana-5954	50	1	rajit	rajit	PROPN
cana-5954	50	2	nair	nair	PROPN
cana-5954	50	3	et	et	PROPN
cana-5954	50	4	al	al	PROPN
cana-5954	51	1	[	[	X
cana-5954	51	2	6	6	NUM
cana-5954	51	3	]	]	SYM
cana-5954	51	4	2021	2021	NUM
cana-5954	51	5	resnet	resnet	NOUN
cana-5954	51	6	50	50	NUM
cana-5954	51	7	carried	carry	VERB
cana-5954	51	8	out	out	ADP
cana-5954	51	9	a	a	DET
cana-5954	51	10	multicenter	multicenter	NOUN
cana-5954	51	11	,	,	PUNCT
cana-5954	51	12	retrospective	retrospective	ADJ
cana-5954	51	13	research	research	NOUN
cana-5954	51	14	to	to	PART
cana-5954	51	15	identify	identify	VERB
cana-5954	51	16	covid-19	covid-19	PROPN
cana-5954	51	17	by	by	ADP
cana-5954	51	18	extracting	extract	VERB
cana-5954	51	19	visual	visual	ADJ
cana-5954	51	20	features	feature	NOUN
cana-5954	51	21	from	from	ADP
cana-5954	51	22	volumetric	volumetric	ADJ
cana-5954	51	23	chest	chest	NOUN
cana-5954	51	24	ct	ct	NUM
cana-5954	51	25	scans	scan	NOUN
cana-5954	51	26	.	.	PUNCT
cana-5954	52	1	mohammad	mohammad	PROPN
cana-5954	52	2	farukh	farukh	PROPN
cana-5954	52	3	hashmi	hashmi	PROPN
cana-5954	52	4	et	et	PROPN
cana-5954	52	5	al	al	PROPN
cana-5954	53	1	[	[	X
cana-5954	53	2	7	7	NUM
cana-5954	53	3	]	]	SYM
cana-5954	53	4	2021	2021	NUM
cana-5954	53	5	resnet50	resnet50	NOUN
cana-5954	53	6	the	the	DET
cana-5954	53	7	suggested	suggest	VERB
cana-5954	53	8	model	model	NOUN
cana-5954	53	9	has	have	VERB
cana-5954	53	10	the	the	DET
cana-5954	53	11	potential	potential	NOUN
cana-5954	53	12	to	to	PART
cana-5954	53	13	assist	assist	VERB
cana-5954	53	14	in	in	ADP
cana-5954	53	15	disease	disease	NOUN
cana-5954	53	16	detection	detection	NOUN
cana-5954	53	17	and	and	CCONJ
cana-5954	53	18	support	support	NOUN
cana-5954	53	19	radiologists	radiologist	NOUN
cana-5954	53	20	in	in	ADP
cana-5954	53	21	their	their	PRON
cana-5954	53	22	clinical	clinical	ADJ
cana-5954	53	23	decisionmaking	decisionmaking	NOUN
cana-5954	53	24	.	.	PUNCT
cana-5954	54	1	zhenjia	zhenjia	NOUN
cana-5954	54	2	yue[8	yue[8	PROPN
cana-5954	54	3	]	]	SYM
cana-5954	54	4	2020	2020	NUM
cana-5954	54	5	cnn	cnn	PROPN
cana-5954	54	6	in	in	ADP
cana-5954	54	7	terms	term	NOUN
cana-5954	54	8	of	of	ADP
cana-5954	54	9	image	image	NOUN
cana-5954	54	10	identification	identification	NOUN
cana-5954	54	11	,	,	PUNCT
cana-5954	54	12	cnns	cnn	NOUN
cana-5954	54	13	have	have	AUX
cana-5954	54	14	outperformed	outperform	VERB
cana-5954	54	15	humans	human	NOUN
cana-5954	54	16	,	,	PUNCT
cana-5954	54	17	and	and	CCONJ
cana-5954	54	18	artificial	artificial	ADJ
cana-5954	54	19	intelligence	intelligence	NOUN
cana-5954	54	20	recognition	recognition	NOUN
cana-5954	54	21	is	be	AUX
cana-5954	54	22	highly	highly	ADV
cana-5954	54	23	quick	quick	ADJ
cana-5954	54	24	.	.	PUNCT
cana-5954	55	1	aakash	aakash	NOUN
cana-5954	55	2	shah	shah	NOUN
cana-5954	56	1	[	[	X
cana-5954	56	2	9	9	NUM
cana-5954	56	3	]	]	SYM
cana-5954	56	4	2022	2022	NUM
cana-5954	56	5	cnn	cnn	PROPN
cana-5954	56	6	using	use	VERB
cana-5954	56	7	chest	chest	NOUN
cana-5954	56	8	ct	ct	PROPN
cana-5954	56	9	and	and	CCONJ
cana-5954	56	10	x	x	NOUN
cana-5954	56	11	-	-	NOUN
cana-5954	56	12	ray	ray	NOUN
cana-5954	56	13	images	image	NOUN
cana-5954	56	14	to	to	PART
cana-5954	56	15	distinguish	distinguish	VERB
cana-5954	56	16	between	between	ADP
cana-5954	56	17	covid-19	covid-19	PROPN
cana-5954	56	18	and	and	CCONJ
cana-5954	56	19	pneumonia	pneumonia	NOUN
cana-5954	56	20	.	.	PUNCT
cana-5954	57	1	puneet	puneet	PROPN
cana-5954	57	2	gupta	gupta	PROPN
cana-5954	57	3	[	[	X
cana-5954	57	4	10	10	NUM
cana-5954	57	5	]	]	SYM
cana-5954	57	6	2021	2021	NUM
cana-5954	57	7	cnn	cnn	NOUN
cana-5954	57	8	the	the	DET
cana-5954	57	9	capabilities	capability	NOUN
cana-5954	57	10	of	of	ADP
cana-5954	57	11	cnn	cnn	PROPN
cana-5954	57	12	models	model	NOUN
cana-5954	57	13	that	that	PRON
cana-5954	57	14	have	have	AUX
cana-5954	57	15	already	already	ADV
cana-5954	57	16	been	be	AUX
cana-5954	57	17	trained	train	VERB
cana-5954	57	18	,	,	PUNCT
cana-5954	57	19	which	which	PRON
cana-5954	57	20	are	be	AUX
cana-5954	57	21	used	use	VERB
cana-5954	57	22	as	as	ADP
cana-5954	57	23	feature	feature	NOUN
cana-5954	57	24	extractors	extractor	NOUN
cana-5954	57	25	and	and	CCONJ
cana-5954	57	26	then	then	ADV
cana-5954	57	27	classified	classify	VERB
cana-5954	57	28	diverse	diverse	ADJ
cana-5954	57	29	chest	chest	NOUN
cana-5954	57	30	x	x	NOUN
cana-5954	57	31	-	-	NOUN
cana-5954	57	32	rays	ray	NOUN
cana-5954	57	33	into	into	ADP
cana-5954	57	34	abnormal	abnormal	ADJ
cana-5954	57	35	and	and	CCONJ
cana-5954	57	36	normal	normal	ADJ
cana-5954	57	37	categories	category	NOUN
cana-5954	57	38	.	.	PUNCT
cana-5954	58	1	avnish	avnish	ADJ
cana-5954	58	2	panwar[11	panwar[11	NOUN
cana-5954	58	3	]	]	X
cana-5954	58	4	2021	2021	NUM
cana-5954	58	5	cnn	cnn	PROPN
cana-5954	58	6	several	several	ADJ
cana-5954	58	7	machine	machine	NOUN
cana-5954	58	8	learning	learn	VERB
cana-5954	58	9	classifiers	classifier	NOUN
cana-5954	58	10	were	be	AUX
cana-5954	58	11	trained	train	VERB
cana-5954	58	12	to	to	PART
cana-5954	58	13	classify	classify	VERB
cana-5954	58	14	chest	chest	NOUN
cana-5954	58	15	radiographs	radiograph	NOUN
cana-5954	58	16	as	as	ADP
cana-5954	58	17	either	either	CCONJ
cana-5954	58	18	normal	normal	ADJ
cana-5954	58	19	,	,	PUNCT
cana-5954	58	20	pneumonia	pneumonia	NOUN
cana-5954	58	21	,	,	PUNCT
cana-5954	58	22	or	or	CCONJ
cana-5954	58	23	covid-19	covid-19	PROPN
cana-5954	58	24	positive	positive	ADJ
cana-5954	58	25	.	.	PUNCT
cana-5954	59	1	waleed	waleed	PROPN
cana-5954	59	2	al	al	PROPN
cana-5954	59	3	shehri	shehri	PROPN
cana-5954	60	1	[	[	X
cana-5954	60	2	12	12	NUM
cana-5954	60	3	]	]	PUNCT
cana-5954	60	4	2022	2022	NUM
cana-5954	60	5	cnn	cnn	PROPN
cana-5954	60	6	processed	process	VERB
cana-5954	60	7	x	x	NOUN
cana-5954	60	8	-	-	NOUN
cana-5954	60	9	ray	ray	NOUN
cana-5954	60	10	and	and	CCONJ
cana-5954	60	11	ct	ct	NOUN
cana-5954	60	12	scan	scan	ADJ
cana-5954	60	13	pictures	picture	NOUN
cana-5954	60	14	using	use	VERB
cana-5954	60	15	darknet	darknet	PROPN
cana-5954	60	16	and	and	CCONJ
cana-5954	60	17	pre	pre	VERB
cana-5954	60	18	-	-	ADJ
cana-5954	60	19	implemented	implement	VERB
cana-5954	60	20	convolutional	convolutional	ADJ
cana-5954	60	21	neural	neural	ADJ
cana-5954	60	22	networks	network	NOUN
cana-5954	60	23	.	.	PUNCT
cana-5954	61	1	communications	communication	NOUN
cana-5954	61	2	on	on	ADP
cana-5954	61	3	applied	apply	VERB
cana-5954	61	4	nonlinear	nonlinear	ADJ
cana-5954	61	5	analysis	analysis	NOUN
cana-5954	61	6	issn	issn	NOUN
cana-5954	61	7	:	:	PUNCT
cana-5954	61	8	1074	1074	NUM
cana-5954	61	9	-	-	PUNCT
cana-5954	61	10	133x	133x	NUM
cana-5954	61	11	vol	vol	VERB
cana-5954	61	12	32	32	NUM
cana-5954	61	13	no	no	NOUN
cana-5954	61	14	.	.	PUNCT
cana-5954	62	1	10s	10	NOUN
cana-5954	62	2	(	(	PUNCT
cana-5954	62	3	2025	2025	NUM
cana-5954	62	4	)	)	PUNCT
cana-5954	62	5	3176	3176	NUM
cana-5954	62	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	62	7	3	3	X
cana-5954	62	8	.	.	PUNCT
cana-5954	62	9	materials	material	NOUN
cana-5954	62	10	and	and	CCONJ
cana-5954	62	11	methods	method	NOUN
cana-5954	62	12	compared	compare	VERB
cana-5954	62	13	to	to	ADP
cana-5954	62	14	smaller	small	ADJ
cana-5954	62	15	datasets	dataset	NOUN
cana-5954	62	16	,	,	PUNCT
cana-5954	62	17	deep	deep	ADJ
cana-5954	62	18	learning	learning	NOUN
cana-5954	62	19	consistently	consistently	ADV
cana-5954	62	20	performs	perform	VERB
cana-5954	62	21	better	well	ADV
cana-5954	62	22	when	when	SCONJ
cana-5954	62	23	trained	train	VERB
cana-5954	62	24	on	on	ADP
cana-5954	62	25	larger	large	ADJ
cana-5954	62	26	ones	one	NOUN
cana-5954	62	27	.	.	PUNCT
cana-5954	63	1	despite	despite	SCONJ
cana-5954	63	2	the	the	DET
cana-5954	63	3	prevalence	prevalence	NOUN
cana-5954	63	4	of	of	ADP
cana-5954	63	5	covid-19	covid-19	PROPN
cana-5954	63	6	and	and	CCONJ
cana-5954	63	7	pneumonia	pneumonia	NOUN
cana-5954	63	8	,	,	PUNCT
cana-5954	63	9	there	there	PRON
cana-5954	63	10	are	be	VERB
cana-5954	63	11	very	very	ADV
cana-5954	63	12	few	few	ADJ
cana-5954	63	13	publicly	publicly	ADV
cana-5954	63	14	available	available	ADJ
cana-5954	63	15	chest	chest	NOUN
cana-5954	63	16	x	x	NOUN
cana-5954	63	17	-	-	NOUN
cana-5954	63	18	ray	ray	NOUN
cana-5954	63	19	images	image	NOUN
cana-5954	63	20	.	.	PUNCT
cana-5954	64	1	in	in	ADP
cana-5954	64	2	order	order	NOUN
cana-5954	64	3	to	to	PART
cana-5954	64	4	tackle	tackle	VERB
cana-5954	64	5	this	this	DET
cana-5954	64	6	problem	problem	NOUN
cana-5954	64	7	,	,	PUNCT
cana-5954	64	8	researchers	researcher	NOUN
cana-5954	64	9	have	have	AUX
cana-5954	64	10	assembled	assemble	VERB
cana-5954	64	11	a	a	DET
cana-5954	64	12	sizable	sizable	ADJ
cana-5954	64	13	dataset	dataset	NOUN
cana-5954	64	14	of	of	ADP
cana-5954	64	15	chest	chest	NOUN
cana-5954	64	16	x	x	NOUN
cana-5954	64	17	-	-	NOUN
cana-5954	64	18	ray	ray	NOUN
cana-5954	64	19	images	image	NOUN
cana-5954	64	20	[	[	X
cana-5954	64	21	13	13	NUM
cana-5954	64	22	]	]	PUNCT
cana-5954	64	23	,	,	PUNCT
cana-5954	64	24	which	which	PRON
cana-5954	64	25	they	they	PRON
cana-5954	64	26	have	have	AUX
cana-5954	64	27	complemented	complement	VERB
cana-5954	64	28	with	with	ADP
cana-5954	64	29	easily	easily	ADV
cana-5954	64	30	accessible	accessible	ADJ
cana-5954	64	31	normal	normal	ADJ
cana-5954	64	32	and	and	CCONJ
cana-5954	64	33	pneumonia	pneumonia	NOUN
cana-5954	64	34	images	image	NOUN
cana-5954	64	35	for	for	ADP
cana-5954	64	36	training	training	NOUN
cana-5954	64	37	and	and	CCONJ
cana-5954	64	38	testing	testing	NOUN
cana-5954	64	39	examination	examination	NOUN
cana-5954	64	40	.	.	PUNCT
cana-5954	65	1	the	the	DET
cana-5954	65	2	proposed	propose	VERB
cana-5954	65	3	deep	deep	ADJ
cana-5954	65	4	learning	learning	NOUN
cana-5954	65	5	model	model	NOUN
cana-5954	65	6	and	and	CCONJ
cana-5954	65	7	the	the	DET
cana-5954	65	8	datasets	dataset	NOUN
cana-5954	65	9	used	use	VERB
cana-5954	65	10	for	for	ADP
cana-5954	65	11	predictive	predictive	ADJ
cana-5954	65	12	analysis	analysis	NOUN
cana-5954	65	13	are	be	AUX
cana-5954	65	14	the	the	DET
cana-5954	65	15	two	two	NUM
cana-5954	65	16	main	main	ADJ
cana-5954	65	17	features	feature	NOUN
cana-5954	65	18	of	of	ADP
cana-5954	65	19	this	this	DET
cana-5954	65	20	research	research	NOUN
cana-5954	65	21	.	.	PUNCT
cana-5954	66	1	3.1	3.1	NUM
cana-5954	66	2	dataset	dataset	NOUN
cana-5954	66	3	collection	collection	NOUN
cana-5954	66	4	the	the	DET
cana-5954	66	5	database	database	NOUN
cana-5954	66	6	included	include	VERB
cana-5954	66	7	normal	normal	ADJ
cana-5954	66	8	chest	chest	NOUN
cana-5954	66	9	x	x	NOUN
cana-5954	66	10	-	-	NOUN
cana-5954	66	11	rays	ray	NOUN
cana-5954	66	12	as	as	ADV
cana-5954	66	13	well	well	ADV
cana-5954	66	14	as	as	ADP
cana-5954	66	15	images	image	NOUN
cana-5954	66	16	of	of	ADP
cana-5954	66	17	covid-19	covid-19	PROPN
cana-5954	66	18	and	and	CCONJ
cana-5954	66	19	pneumonia	pneumonia	NOUN
cana-5954	66	20	[	[	X
cana-5954	66	21	15	15	NUM
cana-5954	66	22	]	]	PUNCT
cana-5954	66	23	.	.	PUNCT
cana-5954	67	1	the	the	DET
cana-5954	67	2	popular	popular	ADJ
cana-5954	67	3	kaggle	kaggle	NOUN
cana-5954	67	4	chest	chest	NOUN
cana-5954	67	5	x	x	NOUN
cana-5954	67	6	-	-	NOUN
cana-5954	67	7	ray	ray	NOUN
cana-5954	67	8	database	database	NOUN
cana-5954	67	9	has	have	VERB
cana-5954	67	10	5,160	5,160	NUM
cana-5954	67	11	resolutions	resolution	NOUN
cana-5954	67	12	ranging	range	VERB
cana-5954	67	13	from	from	ADP
cana-5954	67	14	800	800	NUM
cana-5954	67	15	to	to	ADP
cana-5954	67	16	1900	1900	NUM
cana-5954	67	17	pixels	pixel	NOUN
cana-5954	67	18	,	,	PUNCT
cana-5954	67	19	showing	show	VERB
cana-5954	67	20	both	both	CCONJ
cana-5954	67	21	bacterial	bacterial	ADJ
cana-5954	67	22	and	and	CCONJ
cana-5954	67	23	viral	viral	ADJ
cana-5954	67	24	pneumonia	pneumonia	NOUN
cana-5954	67	25	as	as	ADV
cana-5954	67	26	well	well	ADV
cana-5954	67	27	as	as	ADP
cana-5954	67	28	normal	normal	ADJ
cana-5954	67	29	or	or	CCONJ
cana-5954	67	30	healthy	healthy	ADJ
cana-5954	67	31	instances	instance	NOUN
cana-5954	67	32	.	.	PUNCT
cana-5954	68	1	this	this	DET
cana-5954	68	2	source	source	NOUN
cana-5954	68	3	provided	provide	VERB
cana-5954	68	4	chest	chest	NOUN
cana-5954	68	5	x	x	NOUN
cana-5954	68	6	-	-	NOUN
cana-5954	68	7	ray	ray	NOUN
cana-5954	68	8	pictures	picture	NOUN
cana-5954	68	9	for	for	ADP
cana-5954	68	10	covid-19	covid-19	PROPN
cana-5954	68	11	,	,	PUNCT
cana-5954	68	12	normal	normal	ADJ
cana-5954	68	13	,	,	PUNCT
cana-5954	68	14	and	and	CCONJ
cana-5954	68	15	pneumonia	pneumonia	NOUN
cana-5954	68	16	cases	case	NOUN
cana-5954	68	17	,	,	PUNCT
cana-5954	68	18	which	which	PRON
cana-5954	68	19	were	be	AUX
cana-5954	68	20	used	use	VERB
cana-5954	68	21	in	in	ADP
cana-5954	68	22	the	the	DET
cana-5954	68	23	creation	creation	NOUN
cana-5954	68	24	of	of	ADP
cana-5954	68	25	the	the	DET
cana-5954	68	26	most	most	ADV
cana-5954	68	27	recent	recent	ADJ
cana-5954	68	28	database	database	NOUN
cana-5954	68	29	collection	collection	NOUN
cana-5954	69	1	[	[	X
cana-5954	69	2	13	13	NUM
cana-5954	69	3	,	,	PUNCT
cana-5954	69	4	14	14	NUM
cana-5954	69	5	]	]	PUNCT
cana-5954	69	6	.	.	PUNCT
cana-5954	70	1	the	the	DET
cana-5954	70	2	database	database	NOUN
cana-5954	70	3	consists	consist	VERB
cana-5954	70	4	of	of	ADP
cana-5954	70	5	5,160	5,160	NUM
cana-5954	70	6	images	image	NOUN
cana-5954	70	7	categorized	categorize	VERB
cana-5954	70	8	into	into	ADP
cana-5954	70	9	three	three	NUM
cana-5954	70	10	classes	class	NOUN
cana-5954	70	11	,	,	PUNCT
cana-5954	70	12	with	with	ADP
cana-5954	70	13	a	a	DET
cana-5954	70	14	batch	batch	NOUN
cana-5954	70	15	size	size	NOUN
cana-5954	70	16	set	set	VERB
cana-5954	70	17	at	at	ADP
cana-5954	70	18	20	20	NUM
cana-5954	70	19	.	.	PUNCT
cana-5954	71	1	the	the	DET
cana-5954	71	2	training	training	NOUN
cana-5954	71	3	,	,	PUNCT
cana-5954	71	4	validation	validation	NOUN
cana-5954	71	5	,	,	PUNCT
cana-5954	71	6	and	and	CCONJ
cana-5954	71	7	testing	test	VERB
cana-5954	71	8	data	datum	NOUN
cana-5954	71	9	for	for	ADP
cana-5954	71	10	the	the	DET
cana-5954	71	11	database	database	NOUN
cana-5954	71	12	collection	collection	NOUN
cana-5954	71	13	are	be	AUX
cana-5954	71	14	graphically	graphically	ADV
cana-5954	71	15	shown	show	VERB
cana-5954	71	16	the	the	DET
cana-5954	71	17	following	follow	VERB
cana-5954	71	18	figure	figure	NOUN
cana-5954	71	19	1	1	NUM
cana-5954	71	20	.	.	PUNCT
cana-5954	72	1	fig.1	fig.1	X
cana-5954	72	2	.	.	PUNCT
cana-5954	73	1	graphically	graphically	ADV
cana-5954	73	2	represent	represent	VERB
cana-5954	73	3	dataset	dataset	VERB
cana-5954	73	4	the	the	DET
cana-5954	73	5	training	training	NOUN
cana-5954	73	6	directory	directory	NOUN
cana-5954	73	7	contains	contain	VERB
cana-5954	73	8	3,424	3,424	NUM
cana-5954	73	9	files	file	NOUN
cana-5954	73	10	in	in	ADP
cana-5954	73	11	the	the	DET
cana-5954	73	12	pneumonia	pneumonia	NOUN
cana-5954	73	13	category	category	NOUN
cana-5954	73	14	,	,	PUNCT
cana-5954	73	15	1,276	1,276	NUM
cana-5954	73	16	files	file	NOUN
cana-5954	73	17	in	in	ADP
cana-5954	73	18	the	the	DET
cana-5954	73	19	normal	normal	ADJ
cana-5954	73	20	category	category	NOUN
cana-5954	73	21	,	,	PUNCT
cana-5954	73	22	and	and	CCONJ
cana-5954	73	23	460	460	NUM
cana-5954	73	24	files	file	NOUN
cana-5954	73	25	in	in	ADP
cana-5954	73	26	the	the	DET
cana-5954	73	27	covid-19	covid-19	PROPN
cana-5954	73	28	category	category	NOUN
cana-5954	73	29	.	.	PUNCT
cana-5954	74	1	in	in	ADP
cana-5954	74	2	the	the	DET
cana-5954	74	3	validation	validation	NOUN
cana-5954	74	4	directory	directory	NOUN
cana-5954	74	5	,	,	PUNCT
cana-5954	74	6	there	there	PRON
cana-5954	74	7	are	be	VERB
cana-5954	74	8	428	428	NUM
cana-5954	74	9	files	file	NOUN
cana-5954	74	10	for	for	ADP
cana-5954	74	11	pneumonia	pneumonia	NOUN
cana-5954	74	12	,	,	PUNCT
cana-5954	74	13	158	158	NUM
cana-5954	74	14	files	file	NOUN
cana-5954	74	15	for	for	ADP
cana-5954	74	16	normal	normal	ADJ
cana-5954	74	17	,	,	PUNCT
cana-5954	74	18	and	and	CCONJ
cana-5954	74	19	58	58	NUM
cana-5954	74	20	files	file	NOUN
cana-5954	74	21	for	for	ADP
cana-5954	74	22	covid-19	covid-19	PROPN
cana-5954	74	23	.	.	PUNCT
cana-5954	75	1	the	the	DET
cana-5954	75	2	testing	testing	NOUN
cana-5954	75	3	directory	directory	NOUN
cana-5954	75	4	includes	include	VERB
cana-5954	75	5	427	427	NUM
cana-5954	75	6	files	file	NOUN
cana-5954	75	7	for	for	ADP
cana-5954	75	8	pneumonia	pneumonia	NOUN
cana-5954	75	9	,	,	PUNCT
cana-5954	75	10	159	159	NUM
cana-5954	75	11	files	file	NOUN
cana-5954	75	12	for	for	ADP
cana-5954	75	13	normal	normal	ADJ
cana-5954	75	14	,	,	PUNCT
cana-5954	75	15	and	and	CCONJ
cana-5954	75	16	58	58	NUM
cana-5954	75	17	files	file	NOUN
cana-5954	75	18	for	for	ADP
cana-5954	75	19	covid-19	covid-19	PROPN
cana-5954	75	20	.	.	PUNCT
cana-5954	76	1	with	with	ADP
cana-5954	76	2	a	a	DET
cana-5954	76	3	batch	batch	NOUN
cana-5954	76	4	size	size	NOUN
cana-5954	76	5	of	of	ADP
cana-5954	76	6	20	20	NUM
cana-5954	76	7	,	,	PUNCT
cana-5954	76	8	a	a	DET
cana-5954	76	9	total	total	NOUN
cana-5954	76	10	of	of	ADP
cana-5954	76	11	5,160	5,160	NUM
cana-5954	76	12	images	image	NOUN
cana-5954	76	13	across	across	ADP
cana-5954	76	14	three	three	NUM
cana-5954	76	15	classes	class	NOUN
cana-5954	76	16	were	be	AUX
cana-5954	76	17	found	find	VERB
cana-5954	76	18	.	.	PUNCT
cana-5954	77	1	3.2	3.2	NUM
cana-5954	77	2	features	feature	VERB
cana-5954	77	3	processing	processing	NOUN
cana-5954	77	4	in	in	ADP
cana-5954	77	5	the	the	DET
cana-5954	77	6	features	feature	NOUN
cana-5954	77	7	processing	process	VERB
cana-5954	77	8	various	various	ADJ
cana-5954	77	9	techniques	technique	NOUN
cana-5954	77	10	such	such	ADJ
cana-5954	77	11	as	as	ADP
cana-5954	77	12	grouping	grouping	NOUN
cana-5954	77	13	,	,	PUNCT
cana-5954	77	14	average	average	ADJ
cana-5954	77	15	pooling	pooling	NOUN
cana-5954	77	16	(	(	PUNCT
cana-5954	77	17	avgpool	avgpool	PROPN
cana-5954	77	18	)	)	PUNCT
cana-5954	77	19	,	,	PUNCT
cana-5954	77	20	maximum	maximum	ADJ
cana-5954	77	21	pooling	pooling	NOUN
cana-5954	77	22	(	(	PUNCT
cana-5954	77	23	maxpool	maxpool	NOUN
cana-5954	77	24	)	)	PUNCT
cana-5954	77	25	,	,	PUNCT
cana-5954	77	26	group	group	NOUN
cana-5954	77	27	normalization	normalization	NOUN
cana-5954	77	28	(	(	PUNCT
cana-5954	77	29	groupnorm	groupnorm	NOUN
cana-5954	77	30	)	)	PUNCT
cana-5954	78	1	[	[	X
cana-5954	78	2	16	16	NUM
cana-5954	78	3	]	]	PUNCT
cana-5954	78	4	,	,	PUNCT
cana-5954	78	5	and	and	CCONJ
cana-5954	78	6	other	other	ADJ
cana-5954	78	7	procedures	procedure	NOUN
cana-5954	78	8	to	to	PART
cana-5954	78	9	tackle	tackle	VERB
cana-5954	78	10	the	the	DET
cana-5954	78	11	communications	communication	NOUN
cana-5954	78	12	on	on	ADP
cana-5954	78	13	applied	apply	VERB
cana-5954	78	14	nonlinear	nonlinear	ADJ
cana-5954	78	15	analysis	analysis	NOUN
cana-5954	78	16	issn	issn	NOUN
cana-5954	78	17	:	:	PUNCT
cana-5954	78	18	1074	1074	NUM
cana-5954	78	19	-	-	PUNCT
cana-5954	78	20	133x	133x	NUM
cana-5954	78	21	vol	vol	VERB
cana-5954	78	22	32	32	NUM
cana-5954	78	23	no	no	NOUN
cana-5954	78	24	.	.	PUNCT
cana-5954	79	1	10s	10	NOUN
cana-5954	79	2	(	(	PUNCT
cana-5954	79	3	2025	2025	NUM
cana-5954	79	4	)	)	PUNCT
cana-5954	79	5	3177	3177	NUM
cana-5954	79	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5954	79	7	aforementioned	aforementione	VERB
cana-5954	79	8	challenges	challenge	NOUN
cana-5954	79	9	.	.	PUNCT
cana-5954	80	1	the	the	DET
cana-5954	80	2	concept	concept	NOUN
cana-5954	80	3	of	of	ADP
cana-5954	80	4	grouping	grouping	NOUN
cana-5954	80	5	was	be	AUX
cana-5954	80	6	initially	initially	ADV
cana-5954	80	7	introduced	introduce	VERB
cana-5954	80	8	by	by	ADP
cana-5954	80	9	alexnet	alexnet	NOUN
cana-5954	80	10	[	[	X
cana-5954	80	11	17	17	NUM
cana-5954	80	12	]	]	PUNCT
cana-5954	80	13	and	and	CCONJ
cana-5954	80	14	later	later	ADV
cana-5954	80	15	evolved	evolve	VERB
cana-5954	80	16	into	into	ADP
cana-5954	80	17	modern	modern	ADJ
cana-5954	80	18	grouping	grouping	NOUN
cana-5954	80	19	convolution	convolution	NOUN
cana-5954	80	20	.	.	PUNCT
cana-5954	81	1	convolutional	convolutional	ADJ
cana-5954	81	2	grouping	grouping	NOUN
cana-5954	81	3	divides	divide	VERB
cana-5954	81	4	the	the	DET
cana-5954	81	5	feature	feature	NOUN
cana-5954	81	6	map	map	NOUN
cana-5954	81	7	f	f	PROPN
cana-5954	81	8	into	into	ADP
cana-5954	81	9	g	g	PROPN
cana-5954	81	10	groups	group	NOUN
cana-5954	81	11	,	,	PUNCT
cana-5954	81	12	unlike	unlike	ADP
cana-5954	81	13	conventional	conventional	ADJ
cana-5954	81	14	convolution	convolution	NOUN
cana-5954	81	15	,	,	PUNCT
cana-5954	81	16	where	where	SCONJ
cana-5954	81	17	the	the	DET
cana-5954	81	18	weight	weight	NOUN
cana-5954	81	19	term	term	NOUN
cana-5954	81	20	is	be	AUX
cana-5954	81	21	considered	consider	VERB
cana-5954	81	22	as	as	ADP
cana-5954	81	23	c	c	PROPN
cana-5954	81	24	in	in	ADP
cana-5954	81	25	×k×k×cout	×k×k×cout	NOUN
cana-5954	81	26	for	for	ADP
cana-5954	81	27	an	an	DET
cana-5954	81	28	input	input	NOUN
cana-5954	81	29	feature	feature	NOUN
cana-5954	81	30	map	map	NOUN
cana-5954	81	31	f	f	PROPN
cana-5954	81	32	ϵ	ϵ	X
cana-5954	82	1	[	[	X
cana-5954	82	2	c	c	X
cana-5954	82	3	/	/	SYM
cana-5954	82	4	g	g	NOUN
cana-5954	82	5	,	,	PUNCT
cana-5954	82	6	h	h	NOUN
cana-5954	82	7	,	,	PUNCT
cana-5954	82	8	w	w	NOUN
cana-5954	82	9	]	]	X
cana-5954	82	10	.	.	PUNCT
cana-5954	83	1	there	there	PRON
cana-5954	83	2	are	be	VERB
cana-5954	83	3	g	g	PROPN
cana-5954	83	4	feature	feature	NOUN
cana-5954	83	5	maps	map	NOUN
cana-5954	83	6	in	in	ADP
cana-5954	83	7	total	total	NOUN
cana-5954	83	8	as	as	SCONJ
cana-5954	83	9	each	each	DET
cana-5954	83	10	group	group	NOUN
cana-5954	83	11	creates	create	VERB
cana-5954	83	12	its	its	PRON
cana-5954	83	13	own	own	ADJ
cana-5954	83	14	feature	feature	NOUN
cana-5954	83	15	map	map	NOUN
cana-5954	83	16	.	.	PUNCT
cana-5954	84	1	all	all	DET
cana-5954	84	2	these	these	DET
cana-5954	84	3	categories	category	NOUN
cana-5954	84	4	make	make	VERB
cana-5954	84	5	use	use	NOUN
cana-5954	84	6	of	of	ADP
cana-5954	84	7	a	a	DET
cana-5954	84	8	uniform	uniform	ADJ
cana-5954	84	9	convolution	convolution	NOUN
cana-5954	84	10	kernel	kernel	NOUN
cana-5954	84	11	with	with	ADP
cana-5954	84	12	size	size	NOUN
cana-5954	84	13	k×k×c	k×k×c	NOUN
cana-5954	84	14	/	/	SYM
cana-5954	84	15	g	g	NOUN
cana-5954	84	16	,	,	PUNCT
cana-5954	84	17	and	and	CCONJ
cana-5954	84	18	the	the	DET
cana-5954	84	19	size	size	NOUN
cana-5954	84	20	of	of	ADP
cana-5954	84	21	each	each	DET
cana-5954	84	22	group	group	NOUN
cana-5954	84	23	is	be	AUX
cana-5954	84	24	represented	represent	VERB
cana-5954	84	25	by	by	ADP
cana-5954	84	26	f	f	PROPN
cana-5954	84	27	ϵ	ϵ	X
cana-5954	85	1	[	[	X
cana-5954	85	2	c	c	X
cana-5954	85	3	/	/	SYM
cana-5954	85	4	g	g	NOUN
cana-5954	85	5	,	,	PUNCT
cana-5954	85	6	h	h	NOUN
cana-5954	85	7	,	,	PUNCT
cana-5954	85	8	w	w	NOUN
cana-5954	85	9	]	]	PUNCT
cana-5954	85	10	.	.	PUNCT
cana-5954	86	1	parameter	parameter	NOUN
cana-5954	86	2	number	number	NOUN
cana-5954	86	3	for	for	ADP
cana-5954	86	4	grouped	group	VERB
cana-5954	86	5	convolution	convolution	NOUN
cana-5954	86	6	is	be	AUX
cana-5954	86	7	then	then	ADV
cana-5954	86	8	given	give	VERB
cana-5954	86	9	by	by	ADP
cana-5954	86	10	cin×k×k×cout	cin×k×k×cout	NOUN
cana-5954	86	11	/	/	SYM
cana-5954	86	12	g.	g.	PROPN
cana-5954	86	13	our	our	PRON
cana-5954	86	14	model	model	NOUN
cana-5954	86	15	employs	employ	VERB
cana-5954	86	16	the	the	DET
cana-5954	86	17	concept	concept	NOUN
cana-5954	86	18	of	of	ADP
cana-5954	86	19	grouping	group	VERB
cana-5954	86	20	to	to	PART
cana-5954	86	21	divide	divide	VERB
cana-5954	86	22	the	the	DET
cana-5954	86	23	feature	feature	NOUN
cana-5954	86	24	map	map	NOUN
cana-5954	86	25	,	,	PUNCT
cana-5954	86	26	effectively	effectively	ADV
cana-5954	86	27	reducing	reduce	VERB
cana-5954	86	28	extra	extra	ADJ
cana-5954	86	29	parameters	parameter	NOUN
cana-5954	86	30	.	.	PUNCT
cana-5954	87	1	downsampling	downsample	VERB
cana-5954	87	2	is	be	AUX
cana-5954	87	3	achieved	achieve	VERB
cana-5954	87	4	through	through	ADP
cana-5954	87	5	pooling	pooling	NOUN
cana-5954	87	6	,	,	PUNCT
cana-5954	87	7	which	which	PRON
cana-5954	87	8	helps	help	VERB
cana-5954	87	9	retain	retain	VERB
cana-5954	87	10	overall	overall	ADJ
cana-5954	87	11	feature	feature	NOUN
cana-5954	87	12	information	information	NOUN
cana-5954	87	13	while	while	SCONJ
cana-5954	87	14	reducing	reduce	VERB
cana-5954	87	15	calculation	calculation	NOUN
cana-5954	87	16	parameters	parameter	NOUN
cana-5954	87	17	and	and	CCONJ
cana-5954	87	18	speeding	speed	VERB
cana-5954	87	19	up	up	ADP
cana-5954	87	20	computation	computation	NOUN
cana-5954	87	21	,	,	PUNCT
cana-5954	87	22	particularly	particularly	ADV
cana-5954	87	23	beneficial	beneficial	ADJ
cana-5954	87	24	for	for	ADP
cana-5954	87	25	handling	handle	VERB
cana-5954	87	26	large	large	ADJ
cana-5954	87	27	feature	feature	NOUN
cana-5954	87	28	maps	map	NOUN
cana-5954	87	29	.	.	PUNCT
cana-5954	88	1	given	give	VERB
cana-5954	88	2	the	the	DET
cana-5954	88	3	immense	immense	ADJ
cana-5954	88	4	input	input	NOUN
cana-5954	88	5	image	image	NOUN
cana-5954	88	6	data	datum	NOUN
cana-5954	88	7	in	in	ADP
cana-5954	88	8	these	these	DET
cana-5954	88	9	tasks	task	NOUN
cana-5954	88	10	,	,	PUNCT
cana-5954	88	11	big	big	ADJ
cana-5954	88	12	batches	batch	NOUN
cana-5954	88	13	often	often	ADV
cana-5954	88	14	fail	fail	VERB
cana-5954	88	15	to	to	PART
cana-5954	88	16	perform	perform	VERB
cana-5954	88	17	effectively	effectively	ADV
cana-5954	88	18	,	,	PUNCT
cana-5954	88	19	leading	lead	VERB
cana-5954	88	20	to	to	ADP
cana-5954	88	21	batch	batch	NOUN
cana-5954	88	22	sizes	size	NOUN
cana-5954	88	23	typically	typically	ADV
cana-5954	88	24	ranging	range	VERB
cana-5954	88	25	from	from	ADP
cana-5954	88	26	1	1	NUM
cana-5954	88	27	to	to	ADP
cana-5954	88	28	4	4	NUM
cana-5954	88	29	in	in	ADP
cana-5954	88	30	deep	deep	ADJ
cana-5954	88	31	learning	learning	NOUN
cana-5954	88	32	applications	application	NOUN
cana-5954	88	33	.	.	PUNCT
cana-5954	89	1	groupnorm	groupnorm	NOUN
cana-5954	90	1	[	[	X
cana-5954	90	2	16	16	NUM
cana-5954	90	3	]	]	PUNCT
cana-5954	90	4	serves	serve	VERB
cana-5954	90	5	as	as	ADP
cana-5954	90	6	a	a	DET
cana-5954	90	7	normalization	normalization	NOUN
cana-5954	90	8	technique	technique	NOUN
cana-5954	90	9	,	,	PUNCT
cana-5954	90	10	differing	differ	VERB
cana-5954	90	11	from	from	ADP
cana-5954	90	12	bn	bn	PROPN
cana-5954	90	13	(	(	PUNCT
cana-5954	90	14	batch	batch	NOUN
cana-5954	90	15	normalization	normalization	NOUN
cana-5954	90	16	)	)	PUNCT
cana-5954	90	17	.	.	PUNCT
cana-5954	91	1	under	under	ADP
cana-5954	91	2	significant	significant	ADJ
cana-5954	91	3	batch	batch	NOUN
cana-5954	91	4	sizes	size	NOUN
cana-5954	91	5	,	,	PUNCT
cana-5954	91	6	groupnorm	groupnorm	NOUN
cana-5954	91	7	exhibits	exhibit	VERB
cana-5954	91	8	a	a	DET
cana-5954	91	9	similar	similar	ADJ
cana-5954	91	10	error	error	NOUN
cana-5954	91	11	rate	rate	NOUN
cana-5954	91	12	to	to	ADP
cana-5954	91	13	bn	bn	NOUN
cana-5954	91	14	,	,	PUNCT
cana-5954	91	15	but	but	CCONJ
cana-5954	91	16	it	it	PRON
cana-5954	91	17	outperforms	outperform	VERB
cana-5954	91	18	bn	bn	INTJ
cana-5954	91	19	by	by	ADP
cana-5954	91	20	approximately	approximately	ADV
cana-5954	91	21	10	10	NUM
cana-5954	91	22	%	%	NOUN
cana-5954	91	23	under	under	ADP
cana-5954	91	24	small	small	ADJ
cana-5954	91	25	batch	batch	NOUN
cana-5954	91	26	sizes	size	NOUN
cana-5954	91	27	,	,	PUNCT
cana-5954	91	28	notably	notably	ADV
cana-5954	91	29	enhancing	enhance	VERB
cana-5954	91	30	the	the	DET
cana-5954	91	31	model	model	NOUN
cana-5954	91	32	's	's	PART
cana-5954	91	33	detection	detection	NOUN
cana-5954	91	34	accuracy	accuracy	NOUN
cana-5954	91	35	.	.	PUNCT
cana-5954	92	1	moreover	moreover	ADV
cana-5954	92	2	,	,	PUNCT
cana-5954	92	3	transmitting	transmit	VERB
cana-5954	92	4	feature	feature	NOUN
cana-5954	92	5	map	map	NOUN
cana-5954	92	6	information	information	NOUN
cana-5954	92	7	among	among	ADP
cana-5954	92	8	different	different	ADJ
cana-5954	92	9	groups	group	NOUN
cana-5954	92	10	is	be	AUX
cana-5954	92	11	essential	essential	ADJ
cana-5954	92	12	.	.	PUNCT
cana-5954	93	1	without	without	ADP
cana-5954	93	2	shared	shared	ADJ
cana-5954	93	3	information	information	NOUN
cana-5954	93	4	,	,	PUNCT
cana-5954	93	5	the	the	DET
cana-5954	93	6	network	network	NOUN
cana-5954	93	7	's	's	PART
cana-5954	93	8	feature	feature	NOUN
cana-5954	93	9	extraction	extraction	NOUN
cana-5954	93	10	capacity	capacity	NOUN
cana-5954	93	11	becomes	become	VERB
cana-5954	93	12	restricted	restrict	VERB
cana-5954	93	13	,	,	PUNCT
cana-5954	93	14	hindering	hinder	VERB
cana-5954	93	15	the	the	DET
cana-5954	93	16	desired	desire	VERB
cana-5954	93	17	outcomes	outcome	NOUN
cana-5954	93	18	.	.	PUNCT
cana-5954	94	1	to	to	PART
cana-5954	94	2	enable	enable	VERB
cana-5954	94	3	feature	feature	NOUN
cana-5954	94	4	communication	communication	NOUN
cana-5954	94	5	within	within	ADP
cana-5954	94	6	each	each	DET
cana-5954	94	7	group	group	NOUN
cana-5954	94	8	,	,	PUNCT
cana-5954	94	9	we	we	PRON
cana-5954	94	10	employ	employ	VERB
cana-5954	94	11	the	the	DET
cana-5954	94	12	channel	channel	NOUN
cana-5954	94	13	shuffle	shuffle	NOUN
cana-5954	95	1	[	[	X
cana-5954	95	2	18	18	NUM
cana-5954	95	3	]	]	PUNCT
cana-5954	95	4	operation	operation	NOUN
cana-5954	95	5	,	,	PUNCT
cana-5954	95	6	reorganizing	reorganize	VERB
cana-5954	95	7	features	feature	NOUN
cana-5954	95	8	to	to	PART
cana-5954	95	9	facilitate	facilitate	VERB
cana-5954	95	10	information	information	NOUN
cana-5954	95	11	flow	flow	NOUN
cana-5954	95	12	between	between	ADP
cana-5954	95	13	groups	group	NOUN
cana-5954	95	14	.	.	PUNCT
cana-5954	96	1	3.3	3.3	NUM
cana-5954	96	2	attention	attention	NOUN
cana-5954	96	3	mechanism	mechanism	NOUN
cana-5954	96	4	attention	attention	NOUN
cana-5954	96	5	models	model	NOUN
cana-5954	96	6	have	have	AUX
cana-5954	96	7	been	be	AUX
cana-5954	96	8	used	use	VERB
cana-5954	96	9	extensively	extensively	ADV
cana-5954	96	10	in	in	ADP
cana-5954	96	11	most	most	ADJ
cana-5954	96	12	deep	deep	ADJ
cana-5954	96	13	learning	learning	NOUN
cana-5954	96	14	problems	problem	NOUN
cana-5954	96	15	in	in	ADP
cana-5954	96	16	recent	recent	ADJ
cana-5954	96	17	years	year	NOUN
cana-5954	96	18	.	.	PUNCT
cana-5954	97	1	speech	speech	NOUN
cana-5954	97	2	recognition	recognition	NOUN
cana-5954	97	3	,	,	PUNCT
cana-5954	97	4	image	image	NOUN
cana-5954	97	5	processing	processing	NOUN
cana-5954	97	6	,	,	PUNCT
cana-5954	97	7	natural	natural	ADJ
cana-5954	97	8	language	language	NOUN
cana-5954	97	9	processing	processing	NOUN
cana-5954	97	10	,	,	PUNCT
cana-5954	97	11	and	and	CCONJ
cana-5954	97	12	other	other	ADJ
cana-5954	97	13	applications	application	NOUN
cana-5954	97	14	all	all	PRON
cana-5954	97	15	make	make	VERB
cana-5954	97	16	use	use	NOUN
cana-5954	97	17	of	of	ADP
cana-5954	97	18	the	the	DET
cana-5954	97	19	visual	visual	ADJ
cana-5954	97	20	attention	attention	NOUN
cana-5954	97	21	mechanism	mechanism	NOUN
cana-5954	97	22	.	.	PUNCT
cana-5954	98	1	it	it	PRON
cana-5954	98	2	shows	show	VERB
cana-5954	98	3	a	a	DET
cana-5954	98	4	special	special	ADJ
cana-5954	98	5	signal	signal	NOUN
cana-5954	98	6	processing	processing	NOUN
cana-5954	98	7	technique	technique	NOUN
cana-5954	98	8	that	that	PRON
cana-5954	98	9	exists	exist	VERB
cana-5954	98	10	in	in	ADP
cana-5954	98	11	human	human	ADJ
cana-5954	98	12	vision	vision	NOUN
cana-5954	98	13	.	.	PUNCT
cana-5954	99	1	in	in	ADP
cana-5954	99	2	order	order	NOUN
cana-5954	99	3	to	to	PART
cana-5954	99	4	obtain	obtain	VERB
cana-5954	99	5	extensive	extensive	ADJ
cana-5954	99	6	knowledge	knowledge	NOUN
cana-5954	99	7	while	while	SCONJ
cana-5954	99	8	eliminating	eliminate	VERB
cana-5954	99	9	unnecessary	unnecessary	ADJ
cana-5954	99	10	data	datum	NOUN
cana-5954	99	11	,	,	PUNCT
cana-5954	99	12	the	the	DET
cana-5954	99	13	human	human	ADJ
cana-5954	99	14	brain	brain	NOUN
cana-5954	99	15	quickly	quickly	ADV
cana-5954	99	16	analyses	analyse	VERB
cana-5954	99	17	complete	complete	ADJ
cana-5954	99	18	images	image	NOUN
cana-5954	99	19	,	,	PUNCT
cana-5954	99	20	selecting	select	VERB
cana-5954	99	21	key	key	ADJ
cana-5954	99	22	spots	spot	NOUN
cana-5954	99	23	or	or	CCONJ
cana-5954	99	24	areas	area	NOUN
cana-5954	99	25	of	of	ADP
cana-5954	99	26	interest	interest	NOUN
cana-5954	99	27	.	.	PUNCT
cana-5954	100	1	it	it	PRON
cana-5954	100	2	then	then	ADV
cana-5954	100	3	devotes	devote	VERB
cana-5954	100	4	more	more	ADJ
cana-5954	100	5	attentional	attentional	ADJ
cana-5954	100	6	resources	resource	NOUN
cana-5954	100	7	to	to	ADP
cana-5954	100	8	these	these	DET
cana-5954	100	9	areas	area	NOUN
cana-5954	100	10	.	.	PUNCT
cana-5954	101	1	by	by	ADP
cana-5954	101	2	compressing	compress	VERB
cana-5954	101	3	features	feature	NOUN
cana-5954	101	4	using	use	VERB
cana-5954	101	5	a	a	DET
cana-5954	101	6	squeeze	squeeze	NOUN
cana-5954	101	7	operation	operation	NOUN
cana-5954	101	8	and	and	CCONJ
cana-5954	101	9	then	then	ADV
cana-5954	101	10	restoring	restore	VERB
cana-5954	101	11	them	they	PRON
cana-5954	101	12	to	to	ADP
cana-5954	101	13	their	their	PRON
cana-5954	101	14	original	original	ADJ
cana-5954	101	15	dimensions	dimension	NOUN
cana-5954	101	16	using	use	VERB
cana-5954	101	17	two	two	NUM
cana-5954	101	18	fully	fully	ADV
cana-5954	101	19	linked	link	VERB
cana-5954	101	20	layers	layer	NOUN
cana-5954	101	21	,	,	PUNCT
cana-5954	101	22	senet	senet	NOUN
cana-5954	101	23	[	[	X
cana-5954	101	24	19	19	NUM
cana-5954	101	25	]	]	PUNCT
cana-5954	101	26	is	be	AUX
cana-5954	101	27	able	able	ADJ
cana-5954	101	28	to	to	PART
cana-5954	101	29	capture	capture	VERB
cana-5954	101	30	channel	channel	NOUN
cana-5954	101	31	-	-	PUNCT
cana-5954	101	32	wise	wise	ADJ
cana-5954	101	33	relationships	relationship	NOUN
cana-5954	101	34	.	.	PUNCT
cana-5954	102	1	by	by	ADP
cana-5954	102	2	adaptively	adaptively	ADV
cana-5954	102	3	setting	set	VERB
cana-5954	102	4	the	the	DET
cana-5954	102	5	size	size	NOUN
cana-5954	102	6	of	of	ADP
cana-5954	102	7	a	a	DET
cana-5954	102	8	1	1	NUM
cana-5954	102	9	-	-	PUNCT
cana-5954	102	10	d	d	NOUN
cana-5954	102	11	convolution	convolution	NOUN
cana-5954	102	12	field	field	NOUN
cana-5954	102	13	to	to	PART
cana-5954	102	14	estimate	estimate	VERB
cana-5954	102	15	local	local	ADJ
cana-5954	102	16	cross	cross	ADJ
cana-5954	102	17	-	-	ADJ
cana-5954	102	18	channel	channel	ADJ
cana-5954	102	19	interactions	interaction	NOUN
cana-5954	102	20	,	,	PUNCT
cana-5954	102	21	ecanet	ecanet	NOUN
cana-5954	103	1	[	[	X
cana-5954	103	2	20	20	NUM
cana-5954	103	3	]	]	PUNCT
cana-5954	103	4	improves	improve	VERB
cana-5954	103	5	on	on	ADP
cana-5954	103	6	this	this	DET
cana-5954	103	7	method	method	NOUN
cana-5954	103	8	.	.	PUNCT
cana-5954	104	1	while	while	SCONJ
cana-5954	104	2	ccnet	ccnet	VERB
cana-5954	104	3	[	[	X
cana-5954	104	4	22	22	NUM
cana-5954	104	5	]	]	PUNCT
cana-5954	104	6	lowers	lower	VERB
cana-5954	104	7	processing	processing	NOUN
cana-5954	104	8	costs	cost	NOUN
cana-5954	104	9	by	by	ADP
cana-5954	104	10	restricting	restrict	VERB
cana-5954	104	11	calculations	calculation	NOUN
cana-5954	104	12	to	to	ADP
cana-5954	104	13	the	the	DET
cana-5954	104	14	same	same	ADJ
cana-5954	104	15	rows	row	NOUN
cana-5954	104	16	and	and	CCONJ
cana-5954	104	17	columns	column	NOUN
cana-5954	104	18	,	,	PUNCT
cana-5954	104	19	non	non	ADJ
cana-5954	104	20	-	-	ADJ
cana-5954	104	21	local	local	ADJ
cana-5954	104	22	neural	neural	ADJ
cana-5954	104	23	networks	network	NOUN
cana-5954	104	24	address	address	VERB
cana-5954	104	25	remote	remote	ADJ
cana-5954	104	26	dependencies	dependency	NOUN
cana-5954	104	27	by	by	ADP
cana-5954	104	28	estimating	estimate	VERB
cana-5954	104	29	interactions	interaction	NOUN
cana-5954	104	30	between	between	ADP
cana-5954	104	31	any	any	DET
cana-5954	104	32	two	two	NUM
cana-5954	104	33	points	point	NOUN
cana-5954	104	34	in	in	ADP
cana-5954	104	35	the	the	DET
cana-5954	104	36	image[21	image[21	NOUN
cana-5954	104	37	]	]	PUNCT
cana-5954	104	38	.	.	PUNCT
cana-5954	105	1	channel	channel	NOUN
cana-5954	105	2	and	and	CCONJ
cana-5954	105	3	spatial	spatial	ADJ
cana-5954	105	4	attention	attention	NOUN
cana-5954	105	5	processes	process	NOUN
cana-5954	105	6	are	be	AUX
cana-5954	105	7	combined	combine	VERB
cana-5954	105	8	in	in	ADP
cana-5954	105	9	cbam	cbam	NOUN
cana-5954	105	10	[	[	X
cana-5954	105	11	23	23	NUM
cana-5954	105	12	]	]	PUNCT
cana-5954	105	13	and	and	CCONJ
cana-5954	105	14	gcnet	gcnet	ADJ
cana-5954	106	1	[	[	X
cana-5954	106	2	24	24	NUM
cana-5954	106	3	]	]	PUNCT
cana-5954	106	4	to	to	PART
cana-5954	106	5	achieve	achieve	VERB
cana-5954	106	6	significant	significant	ADJ
cana-5954	106	7	gains	gain	NOUN
cana-5954	106	8	.	.	PUNCT
cana-5954	107	1	3.4	3.4	NUM
cana-5954	107	2	proposed	propose	VERB
cana-5954	107	3	model	model	ADJ
cana-5954	107	4	-	-	PUNCT
cana-5954	107	5	convolutional	convolutional	ADJ
cana-5954	107	6	channel	channel	NOUN
cana-5954	107	7	spatial	spatial	ADJ
cana-5954	107	8	attention	attention	NOUN
cana-5954	107	9	feature	feature	NOUN
cana-5954	107	10	extract	extract	NOUN
cana-5954	107	11	model	model	NOUN
cana-5954	107	12	(	(	PUNCT
cana-5954	107	13	ccsafem	ccsafem	PROPN
cana-5954	107	14	)	)	PUNCT
cana-5954	107	15	a	a	DET
cana-5954	107	16	cnn	cnn	PROPN
cana-5954	107	17	is	be	AUX
cana-5954	107	18	composed	compose	VERB
cana-5954	107	19	of	of	ADP
cana-5954	107	20	by	by	ADP
cana-5954	107	21	several	several	ADJ
cana-5954	107	22	smaller	small	ADJ
cana-5954	107	23	units	unit	NOUN
cana-5954	107	24	organised	organise	VERB
cana-5954	107	25	in	in	ADP
cana-5954	107	26	a	a	DET
cana-5954	107	27	layered	layered	ADJ
cana-5954	107	28	design	design	NOUN
cana-5954	107	29	,	,	PUNCT
cana-5954	107	30	called	call	VERB
cana-5954	107	31	nodes	node	NOUN
cana-5954	107	32	or	or	CCONJ
cana-5954	107	33	neurones	neurone	NOUN
cana-5954	107	34	.	.	PUNCT
cana-5954	108	1	during	during	ADP
cana-5954	108	2	model	model	NOUN
cana-5954	108	3	training	training	NOUN
cana-5954	108	4	,	,	PUNCT
cana-5954	108	5	these	these	DET
cana-5954	108	6	nodes	node	NOUN
cana-5954	108	7	'	'	PART
cana-5954	108	8	weights	weight	NOUN
cana-5954	108	9	are	be	AUX
cana-5954	108	10	modified	modify	VERB
cana-5954	108	11	using	use	VERB
cana-5954	108	12	optimisation	optimisation	NOUN
cana-5954	108	13	strategies	strategy	NOUN
cana-5954	108	14	like	like	ADP
cana-5954	108	15	backpropagation	backpropagation	NOUN
cana-5954	108	16	.	.	PUNCT
cana-5954	109	1	convolutional	convolutional	ADJ
cana-5954	109	2	(	(	PUNCT
cana-5954	109	3	feature	feature	NOUN
cana-5954	109	4	extraction	extraction	NOUN
cana-5954	109	5	)	)	PUNCT
cana-5954	109	6	and	and	CCONJ
cana-5954	109	7	classification	classification	NOUN
cana-5954	109	8	are	be	AUX
cana-5954	109	9	two	two	NUM
cana-5954	109	10	fundamental	fundamental	ADJ
cana-5954	109	11	components	component	NOUN
cana-5954	109	12	of	of	ADP
cana-5954	109	13	any	any	DET
cana-5954	109	14	cnn	cnn	PROPN
cana-5954	109	15	model	model	NOUN
cana-5954	109	16	.	.	PUNCT
cana-5954	110	1	this	this	DET
cana-5954	110	2	research	research	NOUN
cana-5954	110	3	aims	aim	VERB
cana-5954	110	4	to	to	PART
cana-5954	110	5	utilize	utilize	VERB
cana-5954	110	6	chest	chest	NOUN
cana-5954	110	7	x	x	NOUN
cana-5954	110	8	-	-	NOUN
cana-5954	110	9	ray	ray	NOUN
cana-5954	110	10	images	image	NOUN
cana-5954	110	11	in	in	ADP
cana-5954	110	12	developing	develop	VERB
cana-5954	110	13	a	a	DET
cana-5954	110	14	model	model	NOUN
cana-5954	110	15	for	for	ADP
cana-5954	110	16	predicting	predict	VERB
cana-5954	110	17	covid-19	covid-19	PROPN
cana-5954	110	18	and	and	CCONJ
cana-5954	110	19	pneumonia	pneumonia	NOUN
cana-5954	110	20	.	.	PUNCT
cana-5954	111	1	this	this	PRON
cana-5954	111	2	is	be	AUX
cana-5954	111	3	largely	largely	ADV
cana-5954	111	4	attributed	attribute	VERB
cana-5954	111	5	to	to	ADP
cana-5954	111	6	the	the	DET
cana-5954	111	7	utilization	utilization	NOUN
cana-5954	111	8	of	of	ADP
cana-5954	111	9	various	various	ADJ
cana-5954	111	10	layers	layer	NOUN
cana-5954	111	11	and	and	CCONJ
cana-5954	111	12	numerous	numerous	ADJ
cana-5954	111	13	neurons	neuron	NOUN
cana-5954	111	14	within	within	ADP
cana-5954	111	15	the	the	DET
cana-5954	111	16	model	model	NOUN
cana-5954	111	17	to	to	PART
cana-5954	111	18	process	process	VERB
cana-5954	111	19	different	different	ADJ
cana-5954	111	20	components	component	NOUN
cana-5954	111	21	of	of	ADP
cana-5954	111	22	the	the	DET
cana-5954	111	23	image	image	NOUN
cana-5954	111	24	.	.	PUNCT
cana-5954	112	1	such	such	ADJ
cana-5954	112	2	communications	communication	NOUN
cana-5954	112	3	on	on	ADP
cana-5954	112	4	applied	apply	VERB
cana-5954	112	5	nonlinear	nonlinear	ADJ
cana-5954	112	6	analysis	analysis	NOUN
cana-5954	112	7	issn	issn	NOUN
cana-5954	112	8	:	:	PUNCT
cana-5954	112	9	1074	1074	NUM
cana-5954	112	10	-	-	PUNCT
cana-5954	112	11	133x	133x	NUM
cana-5954	112	12	vol	vol	VERB
cana-5954	112	13	32	32	NUM
cana-5954	112	14	no	no	NOUN
cana-5954	112	15	.	.	PUNCT
cana-5954	113	1	10s	10	NOUN
cana-5954	113	2	(	(	PUNCT
cana-5954	113	3	2025	2025	NUM
cana-5954	113	4	)	)	PUNCT
cana-5954	113	5	3178	3178	NUM
cana-5954	113	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	113	7	layer	layer	NOUN
cana-5954	113	8	and	and	CCONJ
cana-5954	113	9	neuron	neuron	PROPN
cana-5954	113	10	configurations	configuration	NOUN
cana-5954	113	11	are	be	AUX
cana-5954	113	12	instrumental	instrumental	ADJ
cana-5954	113	13	in	in	ADP
cana-5954	113	14	achieving	achieve	VERB
cana-5954	113	15	improved	improved	ADJ
cana-5954	113	16	classification	classification	NOUN
cana-5954	113	17	results	result	NOUN
cana-5954	113	18	.	.	PUNCT
cana-5954	114	1	it	it	PRON
cana-5954	114	2	effectively	effectively	ADV
cana-5954	114	3	captures	capture	VERB
cana-5954	114	4	representative	representative	ADJ
cana-5954	114	5	features	feature	NOUN
cana-5954	114	6	from	from	ADP
cana-5954	114	7	both	both	CCONJ
cana-5954	114	8	local	local	ADJ
cana-5954	114	9	and	and	CCONJ
cana-5954	114	10	3d	3d	NUM
cana-5954	114	11	dimensions	dimension	NOUN
cana-5954	114	12	.	.	PUNCT
cana-5954	115	1	the	the	DET
cana-5954	115	2	ccsafem	ccsafem	NOUN
cana-5954	115	3	system	system	NOUN
cana-5954	115	4	comprises	comprise	VERB
cana-5954	115	5	a	a	DET
cana-5954	115	6	backbone	backbone	NOUN
cana-5954	115	7	restnet50	restnet50	NOUN
cana-5954	116	1	[	[	X
cana-5954	116	2	25	25	NUM
cana-5954	116	3	]	]	PUNCT
cana-5954	116	4	,	,	PUNCT
cana-5954	116	5	which	which	PRON
cana-5954	116	6	processes	process	VERB
cana-5954	116	7	input	input	NOUN
cana-5954	116	8	from	from	ADP
cana-5954	116	9	multiple	multiple	ADJ
cana-5954	116	10	ct	ct	PROPN
cana-5954	116	11	trunks	trunk	NOUN
cana-5954	116	12	and	and	CCONJ
cana-5954	116	13	facilitates	facilitate	VERB
cana-5954	116	14	their	their	PRON
cana-5954	116	15	respective	respective	ADJ
cana-5954	116	16	functionalities	functionality	NOUN
cana-5954	116	17	.	.	PUNCT
cana-5954	117	1	extracted	extract	VERB
cana-5954	117	2	features	feature	NOUN
cana-5954	117	3	are	be	AUX
cana-5954	117	4	then	then	ADV
cana-5954	117	5	amalgamated	amalgamate	VERB
cana-5954	117	6	through	through	ADP
cana-5954	117	7	a	a	DET
cana-5954	117	8	pooling	pooling	NOUN
cana-5954	117	9	process	process	NOUN
cana-5954	117	10	across	across	ADP
cana-5954	117	11	all	all	DET
cana-5954	117	12	slices	slice	NOUN
cana-5954	117	13	.	.	PUNCT
cana-5954	118	1	subsequently	subsequently	ADV
cana-5954	118	2	,	,	PUNCT
cana-5954	118	3	a	a	DET
cana-5954	118	4	fully	fully	ADV
cana-5954	118	5	connected	connect	VERB
cana-5954	118	6	layer	layer	NOUN
cana-5954	118	7	with	with	ADP
cana-5954	118	8	softmax	softmax	ADJ
cana-5954	118	9	activation	activation	NOUN
cana-5954	118	10	is	be	AUX
cana-5954	118	11	employed	employ	VERB
cana-5954	118	12	for	for	ADP
cana-5954	118	13	each	each	DET
cana-5954	118	14	class	class	NOUN
cana-5954	118	15	in	in	ADP
cana-5954	118	16	the	the	DET
cana-5954	118	17	final	final	ADJ
cana-5954	118	18	feature	feature	NOUN
cana-5954	118	19	map	map	NOUN
cana-5954	118	20	.	.	PUNCT
cana-5954	119	1	for	for	ADP
cana-5954	119	2	preprocessing	preprocessing	NOUN
cana-5954	119	3	and	and	CCONJ
cana-5954	119	4	lung	lung	NOUN
cana-5954	119	5	region	region	NOUN
cana-5954	119	6	removal	removal	NOUN
cana-5954	119	7	,	,	PUNCT
cana-5954	119	8	a	a	DET
cana-5954	119	9	unit	unit	NOUN
cana-5954	119	10	-	-	PUNCT
cana-5954	119	11	based	base	VERB
cana-5954	119	12	segmentation	segmentation	NOUN
cana-5954	119	13	method	method	NOUN
cana-5954	119	14	is	be	AUX
cana-5954	119	15	utilized	utilize	VERB
cana-5954	119	16	due	due	ADP
cana-5954	119	17	to	to	ADP
cana-5954	119	18	the	the	DET
cana-5954	119	19	focal	focal	ADJ
cana-5954	119	20	area	area	NOUN
cana-5954	119	21	of	of	ADP
cana-5954	119	22	concern	concern	NOUN
cana-5954	119	23	in	in	ADP
cana-5954	119	24	3d	3d	PROPN
cana-5954	119	25	ct	ct	PROPN
cana-5954	119	26	scans	scan	NOUN
cana-5954	120	1	[	[	X
cana-5954	120	2	26	26	NUM
cana-5954	120	3	]	]	PUNCT
cana-5954	120	4	.	.	PUNCT
cana-5954	121	1	the	the	DET
cana-5954	121	2	preprocessed	preprocesse	VERB
cana-5954	121	3	image	image	NOUN
cana-5954	121	4	is	be	AUX
cana-5954	121	5	then	then	ADV
cana-5954	121	6	fed	feed	VERB
cana-5954	121	7	into	into	ADP
cana-5954	121	8	the	the	DET
cana-5954	121	9	ccsafem	ccsafem	NOUN
cana-5954	121	10	for	for	ADP
cana-5954	121	11	forecasting	forecasting	NOUN
cana-5954	121	12	.	.	PUNCT
cana-5954	122	1	in	in	ADP
cana-5954	122	2	this	this	DET
cana-5954	122	3	process	process	NOUN
cana-5954	122	4	,	,	PUNCT
cana-5954	122	5	a	a	DET
cana-5954	122	6	resnet-50	resnet-50	PROPN
cana-5954	122	7	model	model	NOUN
cana-5954	122	8	serves	serve	VERB
cana-5954	122	9	as	as	ADP
cana-5954	122	10	the	the	DET
cana-5954	122	11	backbone	backbone	NOUN
cana-5954	122	12	,	,	PUNCT
cana-5954	122	13	employing	employ	VERB
cana-5954	122	14	the	the	DET
cana-5954	122	15	max	max	PROPN
cana-5954	122	16	pooling	pooling	NOUN
cana-5954	122	17	approach	approach	NOUN
cana-5954	122	18	with	with	ADP
cana-5954	122	19	shared	share	VERB
cana-5954	122	20	weights	weight	NOUN
cana-5954	122	21	.	.	PUNCT
cana-5954	123	1	the	the	DET
cana-5954	123	2	proposed	propose	VERB
cana-5954	123	3	ccsafem	ccsafem	NOUN
cana-5954	123	4	conducts	conduct	VERB
cana-5954	123	5	multiclass	multiclass	ADJ
cana-5954	123	6	classification	classification	NOUN
cana-5954	123	7	,	,	PUNCT
cana-5954	123	8	distinguishing	distinguish	VERB
cana-5954	123	9	between	between	ADP
cana-5954	123	10	normal	normal	ADJ
cana-5954	123	11	,	,	PUNCT
cana-5954	123	12	covid-19	covid-19	PROPN
cana-5954	123	13	,	,	PUNCT
cana-5954	123	14	and	and	CCONJ
cana-5954	123	15	pneumonia	pneumonia	NOUN
cana-5954	123	16	cases	case	NOUN
cana-5954	123	17	,	,	PUNCT
cana-5954	123	18	as	as	SCONJ
cana-5954	123	19	illustrated	illustrate	VERB
cana-5954	123	20	in	in	ADP
cana-5954	123	21	figure	figure	NOUN
cana-5954	123	22	2	2	NUM
cana-5954	123	23	.	.	PUNCT
cana-5954	124	1	this	this	DET
cana-5954	124	2	architecture	architecture	NOUN
cana-5954	124	3	represents	represent	VERB
cana-5954	124	4	deep	deep	ADJ
cana-5954	124	5	learning	learning	NOUN
cana-5954	124	6	model	model	NOUN
cana-5954	124	7	architecture	architecture	NOUN
cana-5954	124	8	for	for	ADP
cana-5954	124	9	classifying	classify	VERB
cana-5954	124	10	medical	medical	ADJ
cana-5954	124	11	images	image	NOUN
cana-5954	124	12	into	into	ADP
cana-5954	124	13	the	the	DET
cana-5954	124	14	categories	category	NOUN
cana-5954	124	15	of	of	ADP
cana-5954	124	16	covid-19	covid-19	PROPN
cana-5954	124	17	,	,	PUNCT
cana-5954	124	18	pneumonia	pneumonia	NOUN
cana-5954	124	19	and	and	CCONJ
cana-5954	124	20	normal	normal	ADJ
cana-5954	124	21	,	,	PUNCT
cana-5954	124	22	using	use	VERB
cana-5954	124	23	a	a	DET
cana-5954	124	24	combination	combination	NOUN
cana-5954	124	25	of	of	ADP
cana-5954	124	26	resnet-50	resnet-50	NOUN
cana-5954	124	27	,	,	PUNCT
cana-5954	124	28	attention	attention	NOUN
cana-5954	124	29	mechanisms	mechanism	NOUN
cana-5954	124	30	,	,	PUNCT
cana-5954	124	31	and	and	CCONJ
cana-5954	124	32	deep	deep	ADJ
cana-5954	124	33	learning	learn	VERB
cana-5954	124	34	layers	layer	NOUN
cana-5954	124	35	.	.	PUNCT
cana-5954	125	1	3.5	3.5	NUM
cana-5954	125	2	convolutional	convolutional	ADJ
cana-5954	125	3	channel	channel	NOUN
cana-5954	125	4	spatial	spatial	ADJ
cana-5954	125	5	attention	attention	NOUN
cana-5954	125	6	feature	feature	NOUN
cana-5954	125	7	extract	extract	NOUN
cana-5954	125	8	model	model	NOUN
cana-5954	125	9	(	(	PUNCT
cana-5954	125	10	ccsafem	ccsafem	PROPN
cana-5954	125	11	)	)	PUNCT
cana-5954	125	12	csafm	csafm	VERB
cana-5954	125	13	first	first	ADV
cana-5954	125	14	draws	draw	VERB
cana-5954	125	15	out	out	ADP
cana-5954	125	16	world	world	NOUN
cana-5954	125	17	features	feature	VERB
cana-5954	125	18	x	x	PUNCT
cana-5954	125	19	from	from	ADP
cana-5954	125	20	intermediate	intermediate	ADJ
cana-5954	125	21	feature	feature	NOUN
cana-5954	125	22	map	map	NOUN
cana-5954	126	1	f	f	PROPN
cana-5954	127	1	ϵ	ϵ	X
cana-5954	127	2	rc×h×w	rc×h×w	PROPN
cana-5954	127	3	,	,	PUNCT
cana-5954	127	4	where	where	SCONJ
cana-5954	127	5	c	c	PROPN
cana-5954	127	6	refers	refer	VERB
cana-5954	127	7	to	to	ADP
cana-5954	127	8	the	the	DET
cana-5954	127	9	amount	amount	NOUN
cana-5954	127	10	of	of	ADP
cana-5954	127	11	channels	channel	NOUN
cana-5954	127	12	and	and	CCONJ
cana-5954	127	13	h	h	NOUN
cana-5954	127	14	and	and	CCONJ
cana-5954	127	15	w	w	AUX
cana-5954	127	16	represent	represent	VERB
cana-5954	127	17	the	the	DET
cana-5954	127	18	spatial	spatial	ADJ
cana-5954	127	19	height	height	NOUN
cana-5954	127	20	and	and	CCONJ
cana-5954	127	21	width	width	ADJ
cana-5954	127	22	,	,	PUNCT
cana-5954	127	23	respectively	respectively	ADV
cana-5954	127	24	,	,	PUNCT
cana-5954	127	25	in	in	ADP
cana-5954	127	26	order	order	NOUN
cana-5954	127	27	to	to	PART
cana-5954	127	28	have	have	AUX
cana-5954	127	29	optimized	optimize	VERB
cana-5954	127	30	feature	feature	NOUN
cana-5954	127	31	representation	representation	NOUN
cana-5954	127	32	and	and	CCONJ
cana-5954	127	33	extraction	extraction	NOUN
cana-5954	127	34	.	.	PUNCT
cana-5954	128	1	by	by	ADP
cana-5954	128	2	combining	combine	VERB
cana-5954	128	3	the	the	DET
cana-5954	128	4	sub	sub	NOUN
cana-5954	128	5	-	-	ADJ
cana-5954	128	6	feature	feature	ADJ
cana-5954	128	7	xk	xk	NOUN
cana-5954	128	8	with	with	ADP
cana-5954	128	9	the	the	DET
cana-5954	128	10	global	global	ADJ
cana-5954	128	11	feature	feature	NOUN
cana-5954	128	12	information	information	NOUN
cana-5954	128	13	,	,	PUNCT
cana-5954	128	14	this	this	DET
cana-5954	128	15	phase	phase	NOUN
cana-5954	128	16	seeks	seek	VERB
cana-5954	128	17	to	to	PART
cana-5954	128	18	improve	improve	VERB
cana-5954	128	19	the	the	DET
cana-5954	128	20	quality	quality	NOUN
cana-5954	128	21	of	of	ADP
cana-5954	128	22	the	the	DET
cana-5954	128	23	extracted	extract	VERB
cana-5954	128	24	features	feature	NOUN
cana-5954	128	25	.	.	PUNCT
cana-5954	129	1	consequently	consequently	ADV
cana-5954	129	2	,	,	PUNCT
cana-5954	129	3	it	it	PRON
cana-5954	129	4	enables	enable	VERB
cana-5954	129	5	improved	improved	ADJ
cana-5954	129	6	exchange	exchange	NOUN
cana-5954	129	7	and	and	CCONJ
cana-5954	129	8	circulation	circulation	NOUN
cana-5954	129	9	of	of	ADP
cana-5954	129	10	information	information	NOUN
cana-5954	129	11	when	when	SCONJ
cana-5954	129	12	channel	channel	NOUN
cana-5954	129	13	and	and	CCONJ
cana-5954	129	14	spatial	spatial	ADJ
cana-5954	129	15	attention	attention	NOUN
cana-5954	129	16	are	be	AUX
cana-5954	129	17	fused	fuse	VERB
cana-5954	129	18	.	.	PUNCT
cana-5954	130	1	in	in	ADP
cana-5954	130	2	particular	particular	ADJ
cana-5954	130	3	,	,	PUNCT
cana-5954	130	4	xk1	xk1	PROPN
cana-5954	130	5	,	,	PUNCT
cana-5954	130	6	xk2	xk2	NOUN
cana-5954	130	7	ϵ	ϵ	PROPN
cana-5954	130	8	rc/2g×h×w	rc/2g×h×w	PROPN
cana-5954	130	9	,	,	PUNCT
cana-5954	130	10	the	the	DET
cana-5954	130	11	importance	importance	NOUN
cana-5954	130	12	coefficients	coefficient	VERB
cana-5954	130	13	for	for	ADP
cana-5954	130	14	each	each	DET
cana-5954	130	15	subfeature	subfeature	NOUN
cana-5954	130	16	are	be	AUX
cana-5954	130	17	then	then	ADV
cana-5954	130	18	calculated	calculate	VERB
cana-5954	130	19	using	use	VERB
cana-5954	130	20	an	an	DET
cana-5954	130	21	attention	attention	NOUN
cana-5954	130	22	module	module	NOUN
cana-5954	130	23	.	.	PUNCT
cana-5954	131	1	after	after	ADP
cana-5954	131	2	combining	combine	VERB
cana-5954	131	3	all	all	PRON
cana-5954	131	4	of	of	ADP
cana-5954	131	5	the	the	DET
cana-5954	131	6	sub	sub	NOUN
cana-5954	131	7	-	-	NOUN
cana-5954	131	8	features	feature	NOUN
cana-5954	131	9	,	,	PUNCT
cana-5954	131	10	additional	additional	ADJ
cana-5954	131	11	processing	processing	NOUN
cana-5954	131	12	is	be	AUX
cana-5954	131	13	done	do	VERB
cana-5954	131	14	to	to	PART
cana-5954	131	15	allow	allow	VERB
cana-5954	131	16	information	information	NOUN
cana-5954	131	17	to	to	PART
cana-5954	131	18	flow	flow	VERB
cana-5954	131	19	across	across	ADP
cana-5954	131	20	groups	group	NOUN
cana-5954	131	21	along	along	ADP
cana-5954	131	22	the	the	DET
cana-5954	131	23	channel	channel	NOUN
cana-5954	131	24	dimension	dimension	NOUN
cana-5954	131	25	.	.	PUNCT
cana-5954	132	1	a	a	DET
cana-5954	132	2	thorough	thorough	ADJ
cana-5954	132	3	explanation	explanation	NOUN
cana-5954	132	4	of	of	ADP
cana-5954	132	5	each	each	DET
cana-5954	132	6	attention	attention	NOUN
cana-5954	132	7	module	module	NOUN
cana-5954	132	8	is	be	AUX
cana-5954	132	9	given	give	VERB
cana-5954	132	10	in	in	ADP
cana-5954	132	11	the	the	DET
cana-5954	132	12	sections	section	NOUN
cana-5954	132	13	that	that	PRON
cana-5954	132	14	follow	follow	VERB
cana-5954	132	15	.	.	PUNCT
cana-5954	133	1	3.5.1	3.5.1	NUM
cana-5954	133	2	channel	channel	NOUN
cana-5954	133	3	attention	attention	NOUN
cana-5954	133	4	module	module	NOUN
cana-5954	133	5	in	in	ADP
cana-5954	133	6	simulating	simulate	VERB
cana-5954	133	7	how	how	SCONJ
cana-5954	133	8	individuals	individual	NOUN
cana-5954	133	9	choose	choose	VERB
cana-5954	133	10	the	the	DET
cana-5954	133	11	objects	object	NOUN
cana-5954	133	12	to	to	PART
cana-5954	133	13	attend	attend	VERB
cana-5954	133	14	to	to	ADP
cana-5954	133	15	,	,	PUNCT
cana-5954	133	16	the	the	DET
cana-5954	133	17	attention	attention	NOUN
cana-5954	133	18	mechanism	mechanism	NOUN
cana-5954	133	19	is	be	AUX
cana-5954	133	20	inspired	inspire	VERB
cana-5954	133	21	by	by	ADP
cana-5954	133	22	the	the	DET
cana-5954	133	23	human	human	ADJ
cana-5954	133	24	visual	visual	ADJ
cana-5954	133	25	attention	attention	NOUN
cana-5954	133	26	system	system	NOUN
cana-5954	133	27	.	.	PUNCT
cana-5954	134	1	the	the	DET
cana-5954	134	2	primary	primary	ADJ
cana-5954	134	3	goal	goal	NOUN
cana-5954	134	4	of	of	ADP
cana-5954	134	5	channel	channel	NOUN
cana-5954	134	6	attention	attention	NOUN
cana-5954	134	7	is	be	AUX
cana-5954	134	8	to	to	PART
cana-5954	134	9	pinpoint	pinpoint	VERB
cana-5954	134	10	an	an	DET
cana-5954	134	11	input	input	NOUN
cana-5954	134	12	image	image	NOUN
cana-5954	134	13	's	's	PART
cana-5954	134	14	most	most	ADV
cana-5954	134	15	important	important	ADJ
cana-5954	134	16	features	feature	NOUN
cana-5954	134	17	.	.	PUNCT
cana-5954	135	1	according	accord	VERB
cana-5954	135	2	to	to	ADP
cana-5954	135	3	cbam	cbam	NOUN
cana-5954	135	4	[	[	X
cana-5954	135	5	23	23	NUM
cana-5954	135	6	]	]	PUNCT
cana-5954	135	7	,	,	PUNCT
cana-5954	135	8	combining	combine	VERB
cana-5954	135	9	max	max	PROPN
cana-5954	135	10	-	-	PUNCT
cana-5954	135	11	pooled	pool	VERB
cana-5954	135	12	and	and	CCONJ
cana-5954	135	13	averagepooled	averagepooled	ADJ
cana-5954	135	14	features	feature	NOUN
cana-5954	135	15	yields	yield	NOUN
cana-5954	135	16	a	a	DET
cana-5954	135	17	much	much	ADV
cana-5954	135	18	more	more	ADV
cana-5954	135	19	potent	potent	ADJ
cana-5954	135	20	network	network	NOUN
cana-5954	135	21	representation	representation	NOUN
cana-5954	135	22	than	than	ADP
cana-5954	135	23	applying	apply	VERB
cana-5954	135	24	each	each	DET
cana-5954	135	25	technique	technique	NOUN
cana-5954	135	26	separately	separately	ADV
cana-5954	135	27	.	.	PUNCT
cana-5954	136	1	this	this	PRON
cana-5954	136	2	is	be	AUX
cana-5954	136	3	supported	support	VERB
cana-5954	136	4	by	by	ADP
cana-5954	136	5	empirical	empirical	ADJ
cana-5954	136	6	data	datum	NOUN
cana-5954	136	7	.	.	PUNCT
cana-5954	137	1	in	in	ADP
cana-5954	137	2	order	order	NOUN
cana-5954	137	3	to	to	PART
cana-5954	137	4	extract	extract	VERB
cana-5954	137	5	global	global	ADJ
cana-5954	137	6	information	information	NOUN
cana-5954	137	7	from	from	ADP
cana-5954	137	8	a	a	DET
cana-5954	137	9	feature	feature	NOUN
cana-5954	137	10	map	map	NOUN
cana-5954	137	11	,	,	PUNCT
cana-5954	137	12	we	we	PRON
cana-5954	137	13	first	first	ADV
cana-5954	137	14	create	create	VERB
cana-5954	137	15	two	two	NUM
cana-5954	137	16	different	different	ADJ
cana-5954	137	17	descriptors	descriptor	NOUN
cana-5954	137	18	:	:	PUNCT
cana-5954	137	19	xc	xc	PROPN
cana-5954	137	20	avg	avg	PROPN
cana-5954	137	21	and	and	CCONJ
cana-5954	137	22	xc	xc	PROPN
cana-5954	137	23	max	max	PROPN
cana-5954	137	24	by	by	ADP
cana-5954	137	25	using	use	VERB
cana-5954	137	26	the	the	DET
cana-5954	137	27	average	average	ADJ
cana-5954	137	28	pooling	pooling	NOUN
cana-5954	137	29	and	and	CCONJ
cana-5954	137	30	max	max	PROPN
cana-5954	137	31	pooling	pooling	NOUN
cana-5954	137	32	approaches	approach	NOUN
cana-5954	137	33	.	.	PUNCT
cana-5954	138	1	a	a	DET
cana-5954	138	2	channel	channel	NOUN
cana-5954	138	3	attention	attention	NOUN
cana-5954	138	4	map	map	NOUN
cana-5954	138	5	is	be	AUX
cana-5954	138	6	then	then	ADV
cana-5954	138	7	created	create	VERB
cana-5954	138	8	by	by	ADP
cana-5954	138	9	processing	process	VERB
cana-5954	138	10	these	these	DET
cana-5954	138	11	descriptors	descriptor	NOUN
cana-5954	138	12	via	via	ADP
cana-5954	138	13	a	a	DET
cana-5954	138	14	scale	scale	NOUN
cana-5954	138	15	network	network	NOUN
cana-5954	138	16	;	;	PUNCT
cana-5954	138	17	this	this	PRON
cana-5954	138	18	is	be	AUX
cana-5954	138	19	shown	show	VERB
cana-5954	138	20	as	as	ADP
cana-5954	138	21	mc	mc	PROPN
cana-5954	138	22	ϵ	ϵ	PROPN
cana-5954	138	23	rc/2g×1×1	rc/2g×1×1	PROPN
cana-5954	138	24	.	.	PUNCT
cana-5954	139	1	in	in	ADP
cana-5954	139	2	order	order	NOUN
cana-5954	139	3	to	to	PART
cana-5954	139	4	facilitate	facilitate	VERB
cana-5954	139	5	element	element	ADJ
cana-5954	139	6	-	-	ADJ
cana-5954	139	7	wise	wise	ADJ
cana-5954	139	8	summing	sum	VERB
cana-5954	139	9	with	with	ADP
cana-5954	139	10	subfeatures	subfeature	NOUN
cana-5954	139	11	,	,	PUNCT
cana-5954	139	12	this	this	DET
cana-5954	139	13	map	map	NOUN
cana-5954	139	14	is	be	AUX
cana-5954	139	15	used	use	VERB
cana-5954	139	16	to	to	PART
cana-5954	139	17	restructure	restructure	VERB
cana-5954	139	18	x.	x.	NOUN
cana-5954	140	1	the	the	DET
cana-5954	140	2	average	average	ADJ
cana-5954	140	3	pooling	pooling	NOUN
cana-5954	140	4	and	and	CCONJ
cana-5954	140	5	max	max	PROPN
cana-5954	140	6	pooling	pooling	NOUN
cana-5954	140	7	methods	method	NOUN
cana-5954	140	8	are	be	AUX
cana-5954	140	9	then	then	ADV
cana-5954	140	10	applied	apply	VERB
cana-5954	140	11	to	to	ADP
cana-5954	140	12	each	each	DET
cana-5954	140	13	branch	branch	NOUN
cana-5954	140	14	for	for	ADP
cana-5954	140	15	every	every	DET
cana-5954	140	16	sub	sub	ADJ
cana-5954	140	17	-	-	ADJ
cana-5954	140	18	feature	feature	ADJ
cana-5954	140	19	xk	xk	PROPN
cana-5954	140	20	.	.	PUNCT
cana-5954	141	1	the	the	DET
cana-5954	141	2	figure	figure	NOUN
cana-5954	141	3	3	3	NUM
cana-5954	141	4	diagram	diagram	NOUN
cana-5954	141	5	represents	represent	VERB
cana-5954	141	6	a	a	DET
cana-5954	141	7	channel	channel	NOUN
cana-5954	141	8	attention	attention	NOUN
cana-5954	141	9	mechanism	mechanism	NOUN
cana-5954	141	10	typically	typically	ADV
cana-5954	141	11	used	use	VERB
cana-5954	141	12	in	in	ADP
cana-5954	141	13	cnns	cnn	NOUN
cana-5954	141	14	for	for	ADP
cana-5954	141	15	enhancing	enhance	VERB
cana-5954	141	16	the	the	DET
cana-5954	141	17	feature	feature	NOUN
cana-5954	141	18	representation	representation	NOUN
cana-5954	141	19	by	by	ADP
cana-5954	141	20	focusing	focus	VERB
cana-5954	141	21	on	on	ADP
cana-5954	141	22	important	important	ADJ
cana-5954	141	23	channels	channel	NOUN
cana-5954	141	24	.	.	PUNCT
cana-5954	142	1	communications	communication	NOUN
cana-5954	142	2	on	on	ADP
cana-5954	142	3	applied	apply	VERB
cana-5954	142	4	nonlinear	nonlinear	ADJ
cana-5954	142	5	analysis	analysis	NOUN
cana-5954	142	6	issn	issn	NOUN
cana-5954	142	7	:	:	PUNCT
cana-5954	142	8	1074	1074	NUM
cana-5954	142	9	-	-	PUNCT
cana-5954	142	10	133x	133x	NUM
cana-5954	142	11	vol	vol	VERB
cana-5954	142	12	32	32	NUM
cana-5954	142	13	no	no	NOUN
cana-5954	142	14	.	.	PUNCT
cana-5954	143	1	10s	10	NOUN
cana-5954	143	2	(	(	PUNCT
cana-5954	143	3	2025	2025	NUM
cana-5954	143	4	)	)	PUNCT
cana-5954	143	5	3179	3179	NUM
cana-5954	143	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	143	7	fig	fig	NOUN
cana-5954	143	8	.	.	PUNCT
cana-5954	144	1	2	2	X
cana-5954	144	2	.	.	X
cana-5954	144	3	architecture	architecture	NOUN
cana-5954	144	4	of	of	ADP
cana-5954	144	5	ccsafem	ccsafem	NOUN
cana-5954	144	6	3.5.2	3.5.2	NUM
cana-5954	144	7	spatial	spatial	ADJ
cana-5954	144	8	attention	attention	NOUN
cana-5954	144	9	module	module	NOUN
cana-5954	144	10	spatial	spatial	ADJ
cana-5954	144	11	attention	attention	NOUN
cana-5954	144	12	focusses	focusse	NOUN
cana-5954	144	13	on	on	ADP
cana-5954	144	14	specific	specific	ADJ
cana-5954	144	15	regions	region	NOUN
cana-5954	144	16	of	of	ADP
cana-5954	144	17	the	the	DET
cana-5954	144	18	feature	feature	NOUN
cana-5954	144	19	map	map	NOUN
cana-5954	144	20	,	,	PUNCT
cana-5954	144	21	identifying	identify	VERB
cana-5954	144	22	the	the	DET
cana-5954	144	23	locations	location	NOUN
cana-5954	144	24	of	of	ADP
cana-5954	144	25	important	important	ADJ
cana-5954	144	26	information	information	NOUN
cana-5954	144	27	.	.	PUNCT
cana-5954	145	1	in	in	ADP
cana-5954	145	2	contrast	contrast	NOUN
cana-5954	145	3	,	,	PUNCT
cana-5954	145	4	channel	channel	NOUN
cana-5954	145	5	attention	attention	NOUN
cana-5954	145	6	emphasizes	emphasize	VERB
cana-5954	145	7	the	the	DET
cana-5954	145	8	important	important	ADJ
cana-5954	145	9	features	feature	NOUN
cana-5954	145	10	within	within	ADP
cana-5954	145	11	the	the	DET
cana-5954	145	12	feature	feature	NOUN
cana-5954	145	13	map	map	NOUN
cana-5954	145	14	,	,	PUNCT
cana-5954	145	15	highlighting	highlight	VERB
cana-5954	145	16	the	the	DET
cana-5954	145	17	most	most	ADV
cana-5954	145	18	significant	significant	ADJ
cana-5954	145	19	aspects	aspect	NOUN
cana-5954	145	20	.	.	PUNCT
cana-5954	146	1	to	to	PART
cana-5954	146	2	compute	compute	VERB
cana-5954	146	3	spatial	spatial	ADJ
cana-5954	146	4	attention	attention	NOUN
cana-5954	146	5	,	,	PUNCT
cana-5954	146	6	we	we	PRON
cana-5954	146	7	use	use	VERB
cana-5954	146	8	group	group	NOUN
cana-5954	146	9	normalization	normalization	NOUN
cana-5954	146	10	(	(	PUNCT
cana-5954	146	11	gn	gn	PROPN
cana-5954	146	12	)	)	PUNCT
cana-5954	147	1	[	[	X
cana-5954	147	2	16	16	NUM
cana-5954	147	3	]	]	PUNCT
cana-5954	147	4	across	across	ADP
cana-5954	147	5	two	two	NUM
cana-5954	147	6	branches	branch	NOUN
cana-5954	147	7	,	,	PUNCT
cana-5954	147	8	xk1	xk1	PROPN
cana-5954	147	9	and	and	CCONJ
cana-5954	147	10	xk2	xk2	PROPN
cana-5954	147	11	,	,	PUNCT
cana-5954	147	12	reducing	reduce	VERB
cana-5954	147	13	the	the	DET
cana-5954	147	14	computational	computational	ADJ
cana-5954	147	15	burden	burden	NOUN
cana-5954	147	16	.	.	PUNCT
cana-5954	148	1	fig.3	fig.3	ADJ
cana-5954	148	2	.	.	PUNCT
cana-5954	148	3	architecture	architecture	NOUN
cana-5954	148	4	of	of	ADP
cana-5954	148	5	channel	channel	NOUN
cana-5954	148	6	attention	attention	NOUN
cana-5954	148	7	module	module	NOUN
cana-5954	148	8	communications	communication	NOUN
cana-5954	148	9	on	on	ADP
cana-5954	148	10	applied	apply	VERB
cana-5954	148	11	nonlinear	nonlinear	ADJ
cana-5954	148	12	analysis	analysis	NOUN
cana-5954	148	13	issn	issn	NOUN
cana-5954	148	14	:	:	PUNCT
cana-5954	148	15	1074	1074	NUM
cana-5954	148	16	-	-	PUNCT
cana-5954	148	17	133x	133x	NUM
cana-5954	148	18	vol	vol	VERB
cana-5954	148	19	32	32	NUM
cana-5954	148	20	no	no	NOUN
cana-5954	148	21	.	.	PUNCT
cana-5954	149	1	10s	10	NOUN
cana-5954	149	2	(	(	PUNCT
cana-5954	149	3	2025	2025	NUM
cana-5954	149	4	)	)	PUNCT
cana-5954	149	5	3180	3180	NUM
cana-5954	149	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	150	1	the	the	DET
cana-5954	150	2	two	two	NUM
cana-5954	150	3	branches	branch	NOUN
cana-5954	150	4	are	be	AUX
cana-5954	150	5	combined	combine	VERB
cana-5954	150	6	to	to	PART
cana-5954	150	7	match	match	VERB
cana-5954	150	8	the	the	DET
cana-5954	150	9	number	number	NOUN
cana-5954	150	10	of	of	ADP
cana-5954	150	11	channels	channel	NOUN
cana-5954	150	12	with	with	ADP
cana-5954	150	13	the	the	DET
cana-5954	150	14	inputs	input	NOUN
cana-5954	150	15	after	after	SCONJ
cana-5954	150	16	these	these	DET
cana-5954	150	17	parameters	parameter	NOUN
cana-5954	150	18	have	have	AUX
cana-5954	150	19	been	be	AUX
cana-5954	150	20	defined	define	VERB
cana-5954	150	21	.	.	PUNCT
cana-5954	151	1	once	once	ADV
cana-5954	151	2	fused	fuse	VERB
cana-5954	151	3	,	,	PUNCT
cana-5954	151	4	all	all	PRON
cana-5954	151	5	sub	sub	NOUN
cana-5954	151	6	-	-	NOUN
cana-5954	151	7	features	feature	NOUN
cana-5954	151	8	are	be	AUX
cana-5954	151	9	combined	combine	VERB
cana-5954	151	10	.	.	PUNCT
cana-5954	152	1	we	we	PRON
cana-5954	152	2	use	use	VERB
cana-5954	152	3	an	an	DET
cana-5954	152	4	operator	operator	NOUN
cana-5954	152	5	called	call	VERB
cana-5954	152	6	"	"	PUNCT
cana-5954	152	7	shuffle	shuffle	NOUN
cana-5954	152	8	"	"	PUNCT
cana-5954	152	9	to	to	PART
cana-5954	152	10	allow	allow	VERB
cana-5954	152	11	the	the	DET
cana-5954	152	12	interchange	interchange	NOUN
cana-5954	152	13	of	of	ADP
cana-5954	152	14	cross	cross	ADJ
cana-5954	152	15	-	-	ADJ
cana-5954	152	16	group	group	ADJ
cana-5954	152	17	information	information	NOUN
cana-5954	152	18	along	along	ADP
cana-5954	152	19	the	the	DET
cana-5954	152	20	channel	channel	NOUN
cana-5954	152	21	dimension	dimension	NOUN
cana-5954	152	22	[	[	X
cana-5954	152	23	27	27	NUM
cana-5954	152	24	]	]	PUNCT
cana-5954	152	25	.	.	PUNCT
cana-5954	153	1	the	the	DET
cana-5954	153	2	feature	feature	NOUN
cana-5954	153	3	x	x	X
cana-5954	153	4	and	and	CCONJ
cana-5954	153	5	the	the	DET
cana-5954	153	6	csafm	csafm	NOUN
cana-5954	153	7	module	module	NOUN
cana-5954	153	8	's	's	PART
cana-5954	153	9	output	output	NOUN
cana-5954	153	10	are	be	AUX
cana-5954	153	11	the	the	DET
cana-5954	153	12	same	same	ADJ
cana-5954	153	13	size	size	NOUN
cana-5954	153	14	.	.	PUNCT
cana-5954	154	1	we	we	PRON
cana-5954	154	2	mostly	mostly	ADV
cana-5954	154	3	use	use	VERB
cana-5954	154	4	the	the	DET
cana-5954	154	5	faster	fast	ADJ
cana-5954	154	6	r	r	NOUN
cana-5954	154	7	-	-	PUNCT
cana-5954	154	8	cnn	cnn	NOUN
cana-5954	154	9	[	[	X
cana-5954	154	10	28	28	NUM
cana-5954	154	11	]	]	PUNCT
cana-5954	154	12	architecture	architecture	NOUN
cana-5954	154	13	as	as	ADP
cana-5954	154	14	the	the	DET
cana-5954	154	15	detector	detector	NOUN
cana-5954	154	16	in	in	ADP
cana-5954	154	17	our	our	PRON
cana-5954	154	18	experiments	experiment	NOUN
cana-5954	154	19	,	,	PUNCT
cana-5954	154	20	using	use	VERB
cana-5954	154	21	frameworks	framework	NOUN
cana-5954	154	22	resnet50	resnet50	NOUN
cana-5954	154	23	.	.	PUNCT
cana-5954	155	1	the	the	DET
cana-5954	155	2	figure	figure	NOUN
cana-5954	155	3	4	4	NUM
cana-5954	155	4	illustrates	illustrate	VERB
cana-5954	155	5	a	a	DET
cana-5954	155	6	spatial	spatial	ADJ
cana-5954	155	7	attention	attention	NOUN
cana-5954	155	8	mechanism	mechanism	NOUN
cana-5954	155	9	that	that	PRON
cana-5954	155	10	is	be	AUX
cana-5954	155	11	applied	apply	VERB
cana-5954	155	12	to	to	ADP
cana-5954	155	13	the	the	DET
cana-5954	155	14	channel	channel	NOUN
cana-5954	155	15	-	-	PUNCT
cana-5954	155	16	refined	refine	VERB
cana-5954	155	17	feature	feature	NOUN
cana-5954	155	18	.	.	PUNCT
cana-5954	156	1	fig.4	fig.4	PROPN
cana-5954	156	2	.	.	PUNCT
cana-5954	156	3	architecture	architecture	NOUN
cana-5954	156	4	of	of	ADP
cana-5954	156	5	spatial	spatial	ADJ
cana-5954	156	6	attention	attention	NOUN
cana-5954	156	7	module	module	NOUN
cana-5954	156	8	this	this	DET
cana-5954	156	9	spatial	spatial	ADJ
cana-5954	156	10	attention	attention	NOUN
cana-5954	156	11	mechanism	mechanism	NOUN
cana-5954	156	12	allows	allow	VERB
cana-5954	156	13	the	the	DET
cana-5954	156	14	network	network	NOUN
cana-5954	156	15	to	to	PART
cana-5954	156	16	concentrate	concentrate	VERB
cana-5954	156	17	on	on	ADP
cana-5954	156	18	both	both	CCONJ
cana-5954	156	19	important	important	ADJ
cana-5954	156	20	spatial	spatial	ADJ
cana-5954	156	21	regions	region	NOUN
cana-5954	156	22	and	and	CCONJ
cana-5954	156	23	crucial	crucial	ADJ
cana-5954	156	24	channels	channel	NOUN
cana-5954	156	25	inside	inside	ADP
cana-5954	156	26	each	each	DET
cana-5954	156	27	feature	feature	NOUN
cana-5954	156	28	map	map	NOUN
cana-5954	156	29	,	,	PUNCT
cana-5954	156	30	which	which	PRON
cana-5954	156	31	improves	improve	VERB
cana-5954	156	32	on	on	ADP
cana-5954	156	33	the	the	DET
cana-5954	156	34	prior	prior	ADJ
cana-5954	156	35	channel	channel	NOUN
cana-5954	156	36	attention	attention	NOUN
cana-5954	156	37	method	method	NOUN
cana-5954	156	38	.	.	PUNCT
cana-5954	157	1	the	the	DET
cana-5954	157	2	network	network	NOUN
cana-5954	157	3	performs	perform	VERB
cana-5954	157	4	better	well	ADV
cana-5954	157	5	because	because	SCONJ
cana-5954	157	6	to	to	ADP
cana-5954	157	7	this	this	DET
cana-5954	157	8	dual	dual	ADJ
cana-5954	157	9	attention	attention	NOUN
cana-5954	157	10	approach	approach	NOUN
cana-5954	157	11	.	.	PUNCT
cana-5954	158	1	3.6	3.6	NUM
cana-5954	158	2	process	process	NOUN
cana-5954	158	3	diagram	diagram	NOUN
cana-5954	158	4	this	this	DET
cana-5954	158	5	figure	figure	NOUN
cana-5954	158	6	5	5	NUM
cana-5954	158	7	,	,	PUNCT
cana-5954	158	8	clearly	clearly	ADV
cana-5954	158	9	illustrates	illustrate	VERB
cana-5954	158	10	each	each	DET
cana-5954	158	11	stage	stage	NOUN
cana-5954	158	12	of	of	ADP
cana-5954	158	13	the	the	DET
cana-5954	158	14	procedure	procedure	NOUN
cana-5954	158	15	,	,	PUNCT
cana-5954	158	16	from	from	ADP
cana-5954	158	17	parameter	parameter	NOUN
cana-5954	158	18	definition	definition	NOUN
cana-5954	158	19	to	to	ADP
cana-5954	158	20	experimental	experimental	ADJ
cana-5954	158	21	setup	setup	NOUN
cana-5954	158	22	.	.	PUNCT
cana-5954	159	1	a	a	DET
cana-5954	159	2	process	process	NOUN
cana-5954	159	3	flow	flow	NOUN
cana-5954	159	4	is	be	AUX
cana-5954	159	5	indicated	indicate	VERB
cana-5954	159	6	by	by	ADP
cana-5954	159	7	arrows	arrow	NOUN
cana-5954	159	8	,	,	PUNCT
cana-5954	159	9	and	and	CCONJ
cana-5954	159	10	each	each	DET
cana-5954	159	11	box	box	NOUN
cana-5954	159	12	indicates	indicate	VERB
cana-5954	159	13	a	a	DET
cana-5954	159	14	crucial	crucial	ADJ
cana-5954	159	15	phase	phase	NOUN
cana-5954	159	16	.	.	PUNCT
cana-5954	160	1	understanding	understand	VERB
cana-5954	160	2	how	how	SCONJ
cana-5954	160	3	each	each	DET
cana-5954	160	4	component	component	NOUN
cana-5954	160	5	of	of	ADP
cana-5954	160	6	the	the	DET
cana-5954	160	7	system	system	NOUN
cana-5954	160	8	contributes	contribute	VERB
cana-5954	160	9	to	to	ADP
cana-5954	160	10	its	its	PRON
cana-5954	160	11	overall	overall	ADJ
cana-5954	160	12	performance	performance	NOUN
cana-5954	160	13	is	be	AUX
cana-5954	160	14	made	make	VERB
cana-5954	160	15	easier	easy	ADJ
cana-5954	160	16	with	with	ADP
cana-5954	160	17	the	the	DET
cana-5954	160	18	help	help	NOUN
cana-5954	160	19	of	of	ADP
cana-5954	160	20	this	this	DET
cana-5954	160	21	format	format	NOUN
cana-5954	160	22	.	.	PUNCT
cana-5954	161	1	3.7	3.7	NUM
cana-5954	161	2	algorithms	algorithm	NOUN
cana-5954	161	3	of	of	ADP
cana-5954	161	4	the	the	DET
cana-5954	161	5	proposed	propose	VERB
cana-5954	161	6	model	model	NOUN
cana-5954	161	7	the	the	DET
cana-5954	161	8	proposed	propose	VERB
cana-5954	161	9	model	model	NOUN
cana-5954	161	10	's	's	PART
cana-5954	161	11	algorithms	algorithm	NOUN
cana-5954	161	12	encompass	encompass	VERB
cana-5954	161	13	a	a	DET
cana-5954	161	14	series	series	NOUN
cana-5954	161	15	of	of	ADP
cana-5954	161	16	computational	computational	ADJ
cana-5954	161	17	procedures	procedure	NOUN
cana-5954	161	18	designed	design	VERB
cana-5954	161	19	to	to	PART
cana-5954	161	20	achieve	achieve	VERB
cana-5954	161	21	specific	specific	ADJ
cana-5954	161	22	tasks	task	NOUN
cana-5954	161	23	.	.	PUNCT
cana-5954	162	1	these	these	DET
cana-5954	162	2	algorithms	algorithm	NOUN
cana-5954	162	3	are	be	AUX
cana-5954	162	4	meticulously	meticulously	ADV
cana-5954	162	5	crafted	craft	VERB
cana-5954	162	6	to	to	PART
cana-5954	162	7	address	address	VERB
cana-5954	162	8	the	the	DET
cana-5954	162	9	objectives	objective	NOUN
cana-5954	162	10	outlined	outline	VERB
cana-5954	162	11	within	within	ADP
cana-5954	162	12	the	the	DET
cana-5954	162	13	model	model	NOUN
cana-5954	162	14	's	's	PART
cana-5954	162	15	framework	framework	NOUN
cana-5954	162	16	.	.	PUNCT
cana-5954	163	1	algorithm	algorithm	NOUN
cana-5954	163	2	1	1	NUM
cana-5954	163	3	:	:	PUNCT
cana-5954	163	4	channel_attention	channel_attention	NOUN
cana-5954	163	5	(	(	PUNCT
cana-5954	163	6	input	input	NOUN
cana-5954	163	7	:	:	PUNCT
cana-5954	163	8	fc	fc	PROPN
cana-5954	164	1	=	=	PUNCT
cana-5954	164	2	h	h	NOUN
cana-5954	164	3	x	x	X
cana-5954	165	1	w	w	NOUN
cana-5954	165	2	x	x	SYM
cana-5954	165	3	c	c	NOUN
cana-5954	165	4	)	)	PUNCT
cana-5954	165	5	{	{	PUNCT
cana-5954	166	1	channel	channel	PROPN
cana-5954	166	2	←	←	PROPN
cana-5954	166	3	fc	fc	PROPN
cana-5954	166	4	.	.	PROPN
cana-5954	166	5	get_shape	get_shape	NOUN
cana-5954	166	6	(	(	PUNCT
cana-5954	166	7	)	)	PUNCT
cana-5954	167	1	[	[	X
cana-5954	167	2	-1	-1	X
cana-5954	167	3	]	]	X
cana-5954	167	4	avg_pool←	avg_pool←	NOUN
cana-5954	167	5	gloval_avg_pooling	gloval_avg_poole	VERB
cana-5954	167	6	(	(	PUNCT
cana-5954	167	7	)	)	PUNCT
cana-5954	167	8	(	(	PUNCT
cana-5954	167	9	fc	fc	X
cana-5954	167	10	)	)	PUNCT
cana-5954	167	11	max_pool←	max_pool←	PROPN
cana-5954	167	12	gloval_max_pooling	gloval_max_poole	VERB
cana-5954	167	13	3d	3d	NOUN
cana-5954	167	14	(	(	PUNCT
cana-5954	167	15	)	)	PUNCT
cana-5954	167	16	(	(	PUNCT
cana-5954	167	17	fc	fc	X
cana-5954	167	18	)	)	PUNCT
cana-5954	167	19	fca	fca	PROPN
cana-5954	167	20	=	=	AUX
cana-5954	167	21	add	add	VERB
cana-5954	167	22	(	(	PUNCT
cana-5954	167	23	)	)	PUNCT
cana-5954	168	1	[	[	X
cana-5954	168	2	avg_pool	avg_pool	NOUN
cana-5954	168	3	+	+	NOUN
cana-5954	168	4	max_pool	max_pool	NOUN
cana-5954	168	5	]	]	X
cana-5954	168	6	return	return	NOUN
cana-5954	168	7	(	(	PUNCT
cana-5954	168	8	fca	fca	PROPN
cana-5954	168	9	)	)	PUNCT
cana-5954	168	10	}	}	PUNCT
cana-5954	168	11	communications	communication	NOUN
cana-5954	168	12	on	on	ADP
cana-5954	168	13	applied	apply	VERB
cana-5954	168	14	nonlinear	nonlinear	ADJ
cana-5954	168	15	analysis	analysis	NOUN
cana-5954	168	16	issn	issn	NOUN
cana-5954	168	17	:	:	PUNCT
cana-5954	168	18	1074	1074	NUM
cana-5954	168	19	-	-	PUNCT
cana-5954	168	20	133x	133x	NUM
cana-5954	168	21	vol	vol	VERB
cana-5954	168	22	32	32	NUM
cana-5954	168	23	no	no	NOUN
cana-5954	168	24	.	.	PUNCT
cana-5954	169	1	10s	10	NOUN
cana-5954	169	2	(	(	PUNCT
cana-5954	169	3	2025	2025	NUM
cana-5954	169	4	)	)	PUNCT
cana-5954	169	5	3181	3181	NUM
cana-5954	169	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	169	7	fig.5	fig.5	PROPN
cana-5954	169	8	.	.	PUNCT
cana-5954	169	9	architecture	architecture	NOUN
cana-5954	169	10	of	of	ADP
cana-5954	169	11	process	process	NOUN
cana-5954	169	12	diagram	diagram	NOUN
cana-5954	169	13	algorithm1	algorithm1	PROPN
cana-5954	169	14	,	,	PUNCT
cana-5954	169	15	channel_attention	channel_attention	NOUN
cana-5954	169	16	,	,	PUNCT
cana-5954	169	17	is	be	AUX
cana-5954	169	18	designed	design	VERB
cana-5954	169	19	to	to	PART
cana-5954	169	20	compute	compute	VERB
cana-5954	169	21	the	the	DET
cana-5954	169	22	channel	channel	NOUN
cana-5954	169	23	attention	attention	NOUN
cana-5954	169	24	vector	vector	NOUN
cana-5954	169	25	for	for	ADP
cana-5954	169	26	a	a	DET
cana-5954	169	27	given	give	VERB
cana-5954	169	28	feature	feature	NOUN
cana-5954	169	29	map	map	NOUN
cana-5954	169	30	fc	fc	PROPN
cana-5954	169	31	.	.	PUNCT
cana-5954	170	1	the	the	DET
cana-5954	170	2	global	global	ADJ
cana-5954	170	3	average	average	ADJ
cana-5954	170	4	pooling	pooling	NOUN
cana-5954	170	5	and	and	CCONJ
cana-5954	170	6	global	global	ADJ
cana-5954	170	7	max	max	PROPN
cana-5954	170	8	pooling	pooling	PROPN
cana-5954	170	9	,	,	PUNCT
cana-5954	170	10	which	which	PRON
cana-5954	170	11	reflect	reflect	VERB
cana-5954	170	12	the	the	DET
cana-5954	170	13	average	average	ADJ
cana-5954	170	14	and	and	CCONJ
cana-5954	170	15	maximum	maximum	ADJ
cana-5954	170	16	activation	activation	NOUN
cana-5954	170	17	values	value	NOUN
cana-5954	170	18	across	across	ADP
cana-5954	170	19	each	each	DET
cana-5954	170	20	channel	channel	NOUN
cana-5954	170	21	,	,	PUNCT
cana-5954	170	22	respectively	respectively	ADV
cana-5954	170	23	.	.	PUNCT
cana-5954	171	1	different	different	ADJ
cana-5954	171	2	facets	facet	NOUN
cana-5954	171	3	of	of	ADP
cana-5954	171	4	channel	channel	NOUN
cana-5954	171	5	-	-	PUNCT
cana-5954	171	6	wise	wise	ADJ
cana-5954	171	7	information	information	NOUN
cana-5954	171	8	are	be	AUX
cana-5954	171	9	captured	capture	VERB
cana-5954	171	10	by	by	ADP
cana-5954	171	11	these	these	DET
cana-5954	171	12	two	two	NUM
cana-5954	171	13	pooling	pool	VERB
cana-5954	171	14	procedures	procedure	NOUN
cana-5954	171	15	.	.	PUNCT
cana-5954	172	1	the	the	DET
cana-5954	172	2	channel	channel	NOUN
cana-5954	172	3	attention	attention	NOUN
cana-5954	172	4	vector	vector	NOUN
cana-5954	172	5	is	be	AUX
cana-5954	172	6	then	then	ADV
cana-5954	172	7	communications	communication	NOUN
cana-5954	172	8	on	on	ADP
cana-5954	172	9	applied	apply	VERB
cana-5954	172	10	nonlinear	nonlinear	ADJ
cana-5954	172	11	analysis	analysis	NOUN
cana-5954	172	12	issn	issn	NOUN
cana-5954	172	13	:	:	PUNCT
cana-5954	172	14	1074	1074	NUM
cana-5954	172	15	-	-	PUNCT
cana-5954	172	16	133x	133x	NUM
cana-5954	172	17	vol	vol	VERB
cana-5954	172	18	32	32	NUM
cana-5954	172	19	no	no	NOUN
cana-5954	172	20	.	.	PUNCT
cana-5954	173	1	10s	10	NOUN
cana-5954	173	2	(	(	PUNCT
cana-5954	173	3	2025	2025	NUM
cana-5954	173	4	)	)	PUNCT
cana-5954	173	5	3182	3182	NUM
cana-5954	173	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5954	173	7	created	create	VERB
cana-5954	173	8	by	by	ADP
cana-5954	173	9	combining	combine	VERB
cana-5954	173	10	the	the	DET
cana-5954	173	11	outcomes	outcome	NOUN
cana-5954	173	12	of	of	ADP
cana-5954	173	13	each	each	DET
cana-5954	173	14	channel	channel	NOUN
cana-5954	173	15	.	.	PUNCT
cana-5954	174	1	the	the	DET
cana-5954	174	2	meaning	meaning	NOUN
cana-5954	174	3	of	of	ADP
cana-5954	174	4	every	every	DET
cana-5954	174	5	channel	channel	NOUN
cana-5954	174	6	in	in	ADP
cana-5954	174	7	the	the	DET
cana-5954	174	8	feature	feature	NOUN
cana-5954	174	9	map	map	NOUN
cana-5954	174	10	is	be	AUX
cana-5954	174	11	captured	capture	VERB
cana-5954	174	12	in	in	ADP
cana-5954	174	13	this	this	DET
cana-5954	174	14	vector	vector	NOUN
cana-5954	174	15	.	.	PUNCT
cana-5954	175	1	algorithm	algorithm	NOUN
cana-5954	175	2	2	2	NUM
cana-5954	175	3	:	:	PUNCT
cana-5954	175	4	special	special	ADJ
cana-5954	175	5	_	_	NOUN
cana-5954	175	6	attention	attention	NOUN
cana-5954	175	7	(	(	PUNCT
cana-5954	175	8	input	input	NOUN
cana-5954	175	9	:	:	PUNCT
cana-5954	175	10	fc	fc	PROPN
cana-5954	175	11	'	'	PUNCT
cana-5954	175	12	)	)	PUNCT
cana-5954	175	13	{	{	PUNCT
cana-5954	175	14	avg_pool←	avg_pool←	NOUN
cana-5954	175	15	avg_pool	avg_pool	NOUN
cana-5954	175	16	(	(	PUNCT
cana-5954	175	17	fc	fc	NOUN
cana-5954	175	18	'	'	PART
cana-5954	175	19	)	)	PUNCT
cana-5954	175	20	max_pool←	max_pool←	PROPN
cana-5954	175	21	max_pool	max_pool	NOUN
cana-5954	175	22	(	(	PUNCT
cana-5954	175	23	fc	fc	INTJ
cana-5954	175	24	'	'	NUM
cana-5954	175	25	)	)	PUNCT
cana-5954	175	26	c	c	PROPN
cana-5954	175	27	concatenate	concatenate	PROPN
cana-5954	175	28	←	←	PROPN
cana-5954	175	29	concatenate	concatenate	PROPN
cana-5954	175	30	(	(	PUNCT
cana-5954	175	31	)	)	PUNCT
cana-5954	176	1	[	[	X
cana-5954	176	2	avg_pool	avg_pool	NOUN
cana-5954	176	3	,	,	PUNCT
cana-5954	176	4	max_pool	max_pool	X
cana-5954	176	5	]	]	X
cana-5954	176	6	f	f	PROPN
cana-5954	176	7	resultant	resultant	VERB
cana-5954	176	8	←	←	PROPN
cana-5954	176	9	conv	conv	PROPN
cana-5954	176	10	3d	3d	PROPN
cana-5954	176	11	(	(	PUNCT
cana-5954	176	12	f	f	PROPN
cana-5954	176	13	concatenate	concatenate	PROPN
cana-5954	176	14	)	)	PUNCT
cana-5954	176	15	return	return	NOUN
cana-5954	176	16	(	(	PUNCT
cana-5954	176	17	f	f	PROPN
cana-5954	176	18	resultant	resultant	NOUN
cana-5954	176	19	)	)	PUNCT
cana-5954	176	20	}	}	PUNCT
cana-5954	176	21	conv	conv	ADJ
cana-5954	176	22	3d	3d	NOUN
cana-5954	176	23	(	(	PUNCT
cana-5954	176	24	filler	filler	NOUN
cana-5954	176	25	=	=	SYM
cana-5954	176	26	1	1	NUM
cana-5954	176	27	,	,	PUNCT
cana-5954	176	28	kernel_size	kernel_size	PROPN
cana-5954	176	29	=	=	SYM
cana-5954	176	30	7x7	7x7	NUM
cana-5954	176	31	,	,	PUNCT
cana-5954	176	32	stride	stride	NOUN
cana-5954	176	33	=	=	SYM
cana-5954	176	34	1	1	NUM
cana-5954	176	35	,	,	PUNCT
cana-5954	176	36	padding	padding	NOUN
cana-5954	176	37	=	=	SYM
cana-5954	176	38	‘	'	PUNCT
cana-5954	176	39	same	same	ADJ
cana-5954	176	40	’	'	PUNCT
cana-5954	176	41	,	,	PUNCT
cana-5954	176	42	activation	activation	NOUN
cana-5954	176	43	=	=	SYM
cana-5954	176	44	‘	'	PUNCT
cana-5954	176	45	sigmoid	sigmoid	NOUN
cana-5954	176	46	’	'	PUNCT
cana-5954	176	47	)	)	PUNCT
cana-5954	177	1	the	the	DET
cana-5954	177	2	spatial_attention	spatial_attention	NOUN
cana-5954	177	3	algorithm	algorithm	NOUN
cana-5954	177	4	2	2	NUM
cana-5954	177	5	is	be	AUX
cana-5954	177	6	intended	intend	VERB
cana-5954	177	7	to	to	PART
cana-5954	177	8	calculate	calculate	VERB
cana-5954	177	9	spatial	spatial	ADJ
cana-5954	177	10	attention	attention	NOUN
cana-5954	177	11	for	for	ADP
cana-5954	177	12	an	an	DET
cana-5954	177	13	input	input	NOUN
cana-5954	177	14	feature	feature	NOUN
cana-5954	177	15	map	map	NOUN
cana-5954	177	16	fc	fc	INTJ
cana-5954	177	17	'	'	PUNCT
cana-5954	177	18	.	.	PUNCT
cana-5954	178	1	the	the	DET
cana-5954	178	2	max	max	PROPN
cana-5954	178	3	pooling	pooling	NOUN
cana-5954	178	4	and	and	CCONJ
cana-5954	178	5	average	average	ADJ
cana-5954	178	6	pooling	pool	VERB
cana-5954	178	7	fc	fc	NOUN
cana-5954	178	8	'	'	PUNCT
cana-5954	178	9	of	of	ADP
cana-5954	178	10	the	the	DET
cana-5954	178	11	feature	feature	NOUN
cana-5954	178	12	map	map	NOUN
cana-5954	178	13	are	be	AUX
cana-5954	178	14	first	first	ADV
cana-5954	178	15	calculated	calculate	VERB
cana-5954	178	16	.	.	PUNCT
cana-5954	179	1	these	these	DET
cana-5954	179	2	pooling	pool	VERB
cana-5954	179	3	extract	extract	VERB
cana-5954	179	4	spatial	spatial	ADJ
cana-5954	179	5	information	information	NOUN
cana-5954	179	6	by	by	ADP
cana-5954	179	7	calculating	calculate	VERB
cana-5954	179	8	the	the	DET
cana-5954	179	9	average	average	ADJ
cana-5954	179	10	and	and	CCONJ
cana-5954	179	11	maximum	maximum	ADJ
cana-5954	179	12	activation	activation	NOUN
cana-5954	179	13	values	value	NOUN
cana-5954	179	14	in	in	ADP
cana-5954	179	15	each	each	DET
cana-5954	179	16	spatial	spatial	ADJ
cana-5954	179	17	region	region	NOUN
cana-5954	179	18	.	.	PUNCT
cana-5954	180	1	max	max	PROPN
cana-5954	180	2	pooling	pooling	NOUN
cana-5954	180	3	and	and	CCONJ
cana-5954	180	4	average	average	ADJ
cana-5954	180	5	pooling	pooling	NOUN
cana-5954	180	6	outputs	output	NOUN
cana-5954	180	7	are	be	AUX
cana-5954	180	8	concatenated	concatenate	VERB
cana-5954	180	9	along	along	ADP
cana-5954	180	10	the	the	DET
cana-5954	180	11	channel	channel	NOUN
cana-5954	180	12	dimension	dimension	NOUN
cana-5954	180	13	.	.	PUNCT
cana-5954	181	1	this	this	DET
cana-5954	181	2	concatenated	concatenate	VERB
cana-5954	181	3	feature	feature	NOUN
cana-5954	181	4	map	map	NOUN
cana-5954	181	5	is	be	AUX
cana-5954	181	6	then	then	ADV
cana-5954	181	7	subjected	subject	VERB
cana-5954	181	8	to	to	ADP
cana-5954	181	9	a	a	DET
cana-5954	181	10	3d	3d	NUM
cana-5954	181	11	convolution	convolution	NOUN
cana-5954	181	12	operation	operation	NOUN
cana-5954	181	13	with	with	ADP
cana-5954	181	14	a	a	DET
cana-5954	181	15	kernel	kernel	NOUN
cana-5954	181	16	size	size	NOUN
cana-5954	181	17	of	of	ADP
cana-5954	181	18	7x7	7x7	NUM
cana-5954	181	19	,	,	PUNCT
cana-5954	181	20	a	a	DET
cana-5954	181	21	stride	stride	NOUN
cana-5954	181	22	of	of	ADP
cana-5954	181	23	1	1	NUM
cana-5954	181	24	,	,	PUNCT
cana-5954	181	25	and	and	CCONJ
cana-5954	181	26	'	'	PUNCT
cana-5954	181	27	same	same	ADJ
cana-5954	181	28	'	'	PUNCT
cana-5954	181	29	padding	padding	NOUN
cana-5954	181	30	.	.	PUNCT
cana-5954	182	1	a	a	DET
cana-5954	182	2	sigmoid	sigmoid	NOUN
cana-5954	182	3	activation	activation	NOUN
cana-5954	182	4	function	function	NOUN
cana-5954	182	5	,	,	PUNCT
cana-5954	182	6	which	which	PRON
cana-5954	182	7	limits	limit	VERB
cana-5954	182	8	the	the	DET
cana-5954	182	9	output	output	NOUN
cana-5954	182	10	values	value	NOUN
cana-5954	182	11	between	between	ADP
cana-5954	182	12	0	0	NUM
cana-5954	182	13	and	and	CCONJ
cana-5954	182	14	1	1	NUM
cana-5954	182	15	,	,	PUNCT
cana-5954	182	16	is	be	AUX
cana-5954	182	17	used	use	VERB
cana-5954	182	18	to	to	PART
cana-5954	182	19	represent	represent	VERB
cana-5954	182	20	the	the	DET
cana-5954	182	21	attention	attention	NOUN
cana-5954	182	22	weights	weight	NOUN
cana-5954	182	23	for	for	ADP
cana-5954	182	24	various	various	ADJ
cana-5954	182	25	spatial	spatial	ADJ
cana-5954	182	26	regions	region	NOUN
cana-5954	182	27	following	follow	VERB
cana-5954	182	28	the	the	DET
cana-5954	182	29	convolution	convolution	NOUN
cana-5954	182	30	operation	operation	NOUN
cana-5954	182	31	.	.	PUNCT
cana-5954	183	1	the	the	DET
cana-5954	183	2	resulting	result	VERB
cana-5954	183	3	feature	feature	NOUN
cana-5954	183	4	map	map	NOUN
cana-5954	183	5	with	with	ADP
cana-5954	183	6	spatial	spatial	ADJ
cana-5954	183	7	attention	attention	NOUN
cana-5954	183	8	information	information	NOUN
cana-5954	183	9	is	be	AUX
cana-5954	183	10	finally	finally	ADV
cana-5954	183	11	returned	return	VERB
cana-5954	183	12	.	.	PUNCT
cana-5954	184	1	algorithm	algorithm	NOUN
cana-5954	184	2	3	3	NUM
cana-5954	184	3	:	:	PUNCT
cana-5954	184	4	cnn_model_creation	cnn_model_creation	NOUN
cana-5954	184	5	(	(	PUNCT
cana-5954	184	6	input_shape	input_shape	PROPN
cana-5954	184	7	,	,	PUNCT
cana-5954	184	8	num_classes	num_classe	VERB
cana-5954	184	9	=	=	NOUN
cana-5954	184	10	3	3	X
cana-5954	184	11	)	)	PUNCT
cana-5954	184	12	{	{	PUNCT
cana-5954	184	13	base_model	base_model	PROPN
cana-5954	184	14	←	←	PROPN
cana-5954	184	15	resnet	resnet	VERB
cana-5954	184	16	50	50	NUM
cana-5954	184	17	(	(	PUNCT
cana-5954	184	18	input_shape	input_shape	PROPN
cana-5954	184	19	,	,	PUNCT
cana-5954	184	20	include_top	include_top	ADJ
cana-5954	184	21	=	=	PUNCT
cana-5954	184	22	‘	'	PUNCT
cana-5954	184	23	false	false	ADJ
cana-5954	184	24	’	'	PUNCT
cana-5954	184	25	)	)	PUNCT
cana-5954	185	1	f	f	PROPN
cana-5954	185	2	resnet	resnet	VERB
cana-5954	185	3	50	50	NUM
cana-5954	185	4	←	←	PROPN
cana-5954	185	5	base_model	base_model	PROPN
cana-5954	185	6	.	.	PUNCT
cana-5954	186	1	output	output	PROPN
cana-5954	186	2	fca	fca	PROPN
cana-5954	186	3	←	←	PROPN
cana-5954	186	4	channel	channel	PROPN
cana-5954	186	5	_	_	NOUN
cana-5954	186	6	attention	attention	NOUN
cana-5954	186	7	(	(	PUNCT
cana-5954	186	8	f	f	PROPN
cana-5954	186	9	resnet	resnet	VERB
cana-5954	186	10	50	50	NUM
cana-5954	186	11	)	)	PUNCT
cana-5954	186	12	f	f	PROPN
cana-5954	186	13	resultant	resultant	VERB
cana-5954	186	14	←	←	PROPN
cana-5954	186	15	special_attention	special_attention	PROPN
cana-5954	186	16	(	(	PUNCT
cana-5954	186	17	fca	fca	PROPN
cana-5954	186	18	)	)	PUNCT
cana-5954	186	19	x	x	PROPN
cana-5954	186	20	←	←	PROPN
cana-5954	186	21	layer.dense1	layer.dense1	PROPN
cana-5954	186	22	(	(	PUNCT
cana-5954	186	23	64	64	NUM
cana-5954	186	24	)	)	PUNCT
cana-5954	186	25	(	(	PUNCT
cana-5954	186	26	f	f	PROPN
cana-5954	186	27	resultant	resultant	NOUN
cana-5954	186	28	)	)	PUNCT
cana-5954	186	29	x	x	SYM
cana-5954	186	30	←	←	PROPN
cana-5954	186	31	layer.dense2	layer.dense2	PROPN
cana-5954	186	32	(	(	PUNCT
cana-5954	186	33	32	32	NUM
cana-5954	186	34	)	)	PUNCT
cana-5954	186	35	(	(	PUNCT
cana-5954	186	36	x	x	X
cana-5954	186	37	)	)	PUNCT
cana-5954	186	38	prediction	prediction	NOUN
cana-5954	186	39	←	←	PROPN
cana-5954	186	40	layer.dense	layer.dense	PROPN
cana-5954	186	41	(	(	PUNCT
cana-5954	186	42	3	3	NUM
cana-5954	186	43	,	,	PUNCT
cana-5954	186	44	activation	activation	NOUN
cana-5954	186	45	=	=	SYM
cana-5954	186	46	‘	'	PUNCT
cana-5954	186	47	softmax	softmax	NOUN
cana-5954	186	48	’	'	PUNCT
cana-5954	186	49	)	)	PUNCT
cana-5954	186	50	(	(	PUNCT
cana-5954	186	51	x	x	X
cana-5954	186	52	)	)	PUNCT
cana-5954	186	53	model	model	NOUN
cana-5954	186	54	←	←	PROPN
cana-5954	186	55	model	model	PROPN
cana-5954	186	56	(	(	PUNCT
cana-5954	186	57	input_shape	input_shape	PROPN
cana-5954	186	58	,	,	PUNCT
cana-5954	186	59	prediction	prediction	NOUN
cana-5954	186	60	)	)	PUNCT
cana-5954	186	61	return	return	NOUN
cana-5954	186	62	(	(	PUNCT
cana-5954	186	63	model	model	NOUN
cana-5954	186	64	)	)	PUNCT
cana-5954	186	65	}	}	PUNCT
cana-5954	186	66	communications	communication	NOUN
cana-5954	186	67	on	on	ADP
cana-5954	186	68	applied	apply	VERB
cana-5954	186	69	nonlinear	nonlinear	ADJ
cana-5954	186	70	analysis	analysis	NOUN
cana-5954	186	71	issn	issn	NOUN
cana-5954	186	72	:	:	PUNCT
cana-5954	186	73	1074	1074	NUM
cana-5954	186	74	-	-	PUNCT
cana-5954	186	75	133x	133x	NUM
cana-5954	186	76	vol	vol	VERB
cana-5954	186	77	32	32	NUM
cana-5954	186	78	no	no	NOUN
cana-5954	186	79	.	.	PUNCT
cana-5954	187	1	10s	10	NOUN
cana-5954	187	2	(	(	PUNCT
cana-5954	187	3	2025	2025	NUM
cana-5954	187	4	)	)	PUNCT
cana-5954	187	5	3183	3183	NUM
cana-5954	187	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	188	1	the	the	DET
cana-5954	188	2	algorithm	algorithm	NOUN
cana-5954	188	3	3	3	NUM
cana-5954	188	4	,	,	PUNCT
cana-5954	188	5	cnn_model_creation	cnn_model_creation	NOUN
cana-5954	188	6	,	,	PUNCT
cana-5954	188	7	outlines	outline	VERB
cana-5954	188	8	the	the	DET
cana-5954	188	9	procedure	procedure	NOUN
cana-5954	188	10	for	for	ADP
cana-5954	188	11	creating	create	VERB
cana-5954	188	12	a	a	DET
cana-5954	188	13	cnn	cnn	NOUN
cana-5954	188	14	model	model	NOUN
cana-5954	188	15	for	for	ADP
cana-5954	188	16	classification	classification	NOUN
cana-5954	188	17	tasks	task	NOUN
cana-5954	188	18	.	.	PUNCT
cana-5954	189	1	firstly	firstly	ADV
cana-5954	189	2	,	,	PUNCT
cana-5954	189	3	the	the	DET
cana-5954	189	4	base	base	PROPN
cana-5954	189	5	resnet50	resnet50	NOUN
cana-5954	189	6	model	model	NOUN
cana-5954	189	7	is	be	AUX
cana-5954	189	8	instantiated	instantiate	VERB
cana-5954	189	9	with	with	ADP
cana-5954	189	10	specified	specify	VERB
cana-5954	189	11	input	input	NOUN
cana-5954	189	12	shape	shape	NOUN
cana-5954	189	13	and	and	CCONJ
cana-5954	189	14	without	without	ADP
cana-5954	189	15	the	the	DET
cana-5954	189	16	top	top	ADJ
cana-5954	189	17	classification	classification	NOUN
cana-5954	189	18	layers	layer	NOUN
cana-5954	189	19	.	.	PUNCT
cana-5954	190	1	then	then	ADV
cana-5954	190	2	,	,	PUNCT
cana-5954	190	3	the	the	DET
cana-5954	190	4	output	output	NOUN
cana-5954	190	5	feature	feature	NOUN
cana-5954	190	6	map	map	NOUN
cana-5954	190	7	from	from	ADP
cana-5954	190	8	resnet50	resnet50	NOUN
cana-5954	190	9	is	be	AUX
cana-5954	190	10	processed	process	VERB
cana-5954	190	11	through	through	ADP
cana-5954	190	12	the	the	DET
cana-5954	190	13	channel_attention	channel_attention	NOUN
cana-5954	190	14	algorithm	algorithm	NOUN
cana-5954	190	15	to	to	PART
cana-5954	190	16	compute	compute	VERB
cana-5954	190	17	channel	channel	NOUN
cana-5954	190	18	attention	attention	NOUN
cana-5954	190	19	.	.	PUNCT
cana-5954	191	1	in	in	ADP
cana-5954	191	2	order	order	NOUN
cana-5954	191	3	to	to	PART
cana-5954	191	4	incorporate	incorporate	VERB
cana-5954	191	5	spatial	spatial	ADJ
cana-5954	191	6	attention	attention	NOUN
cana-5954	191	7	,	,	PUNCT
cana-5954	191	8	the	the	DET
cana-5954	191	9	feature	feature	NOUN
cana-5954	191	10	map	map	NOUN
cana-5954	191	11	with	with	ADP
cana-5954	191	12	channel	channel	NOUN
cana-5954	191	13	attention	attention	NOUN
cana-5954	191	14	is	be	AUX
cana-5954	191	15	then	then	ADV
cana-5954	191	16	subjected	subject	VERB
cana-5954	191	17	to	to	ADP
cana-5954	191	18	the	the	DET
cana-5954	191	19	spatial_attention	spatial_attention	NOUN
cana-5954	191	20	algorithm	algorithm	NOUN
cana-5954	191	21	.	.	PUNCT
cana-5954	192	1	for	for	ADP
cana-5954	192	2	additional	additional	ADJ
cana-5954	192	3	feature	feature	NOUN
cana-5954	192	4	extraction	extraction	NOUN
cana-5954	192	5	and	and	CCONJ
cana-5954	192	6	dimensionality	dimensionality	NOUN
cana-5954	192	7	reduction	reduction	NOUN
cana-5954	192	8	,	,	PUNCT
cana-5954	192	9	the	the	DET
cana-5954	192	10	resultant	resultant	NOUN
cana-5954	192	11	feature	feature	NOUN
cana-5954	192	12	map	map	NOUN
cana-5954	192	13	is	be	AUX
cana-5954	192	14	subsequently	subsequently	ADV
cana-5954	192	15	processed	process	VERB
cana-5954	192	16	through	through	ADP
cana-5954	192	17	completely	completely	ADV
cana-5954	192	18	connected	connected	ADJ
cana-5954	192	19	layers	layer	NOUN
cana-5954	192	20	.	.	PUNCT
cana-5954	193	1	the	the	DET
cana-5954	193	2	model	model	NOUN
cana-5954	193	3	is	be	AUX
cana-5954	193	4	constructed	construct	VERB
cana-5954	193	5	using	use	VERB
cana-5954	193	6	the	the	DET
cana-5954	193	7	input	input	NOUN
cana-5954	193	8	shape	shape	NOUN
cana-5954	193	9	and	and	CCONJ
cana-5954	193	10	the	the	DET
cana-5954	193	11	final	final	ADJ
cana-5954	193	12	prediction	prediction	NOUN
cana-5954	193	13	layer	layer	NOUN
cana-5954	193	14	,	,	PUNCT
cana-5954	193	15	and	and	CCONJ
cana-5954	193	16	a	a	DET
cana-5954	193	17	dense	dense	ADJ
cana-5954	193	18	layer	layer	NOUN
cana-5954	193	19	with	with	ADP
cana-5954	193	20	softmax	softmax	ADJ
cana-5954	193	21	activation	activation	NOUN
cana-5954	193	22	is	be	AUX
cana-5954	193	23	added	add	VERB
cana-5954	193	24	for	for	ADP
cana-5954	193	25	classification	classification	NOUN
cana-5954	193	26	.	.	PUNCT
cana-5954	194	1	algorithm	algorithm	NOUN
cana-5954	194	2	4	4	NUM
cana-5954	194	3	:	:	PUNCT
cana-5954	194	4	training	training	NOUN
cana-5954	194	5	&	&	CCONJ
cana-5954	194	6	testing	testing	NOUN
cana-5954	194	7	{	{	PUNCT
cana-5954	194	8	input	input	NOUN
cana-5954	194	9	:	:	PUNCT
cana-5954	194	10	training	training	NOUN
cana-5954	194	11	,	,	PUNCT
cana-5954	194	12	validation	validation	NOUN
cana-5954	194	13	data	datum	NOUN
cana-5954	194	14	epoch	epoch	PROPN
cana-5954	194	15	←	←	PROPN
cana-5954	194	16	50	50	NUM
cana-5954	194	17	,	,	PUNCT
cana-5954	194	18	batch	batch	VERB
cana-5954	194	19	←	←	PROPN
cana-5954	194	20	20	20	NUM
cana-5954	194	21	for	for	ADP
cana-5954	194	22	epoch	epoch	NOUN
cana-5954	194	23	1	1	NUM
cana-5954	194	24	to	to	ADP
cana-5954	194	25	50	50	NUM
cana-5954	194	26	:	:	PUNCT
cana-5954	194	27	for	for	ADP
cana-5954	194	28	each	each	DET
cana-5954	194	29	batch	batch	NOUN
cana-5954	194	30	in	in	ADP
cana-5954	194	31	training	training	NOUN
cana-5954	194	32	dataset	dataset	NOUN
cana-5954	194	33	feature	feature	NOUN
cana-5954	194	34	_	_	PRON
cana-5954	194	35	extraction	extraction	NOUN
cana-5954	194	36	(	(	PUNCT
cana-5954	194	37	model	model	NOUN
cana-5954	194	38	)	)	PUNCT
cana-5954	194	39	back_propogation	back_propogation	NOUN
cana-5954	194	40	,	,	PUNCT
cana-5954	194	41	calculate	calculate	VERB
cana-5954	194	42	the	the	DET
cana-5954	194	43	gradient	gradient	NOUN
cana-5954	194	44	δl	δl	AUX
cana-5954	194	45	update	update	VERB
cana-5954	194	46	the	the	DET
cana-5954	194	47	model	model	NOUN
cana-5954	194	48	parameter	parameter	PROPN
cana-5954	194	49	w	w	PROPN
cana-5954	194	50	:	:	PUNCT
cana-5954	194	51	w	w	NOUN
cana-5954	194	52	-	-	PUNCT
cana-5954	194	53	α	α	PRON
cana-5954	194	54	δl	δl	PROPN
cana-5954	194	55	//	//	NUM
cana-5954	194	56	α←	α←	PRON
cana-5954	194	57	learning	learn	VERB
cana-5954	194	58	rate	rate	NOUN
cana-5954	194	59	save	save	VERB
cana-5954	194	60	the	the	DET
cana-5954	194	61	trained	train	VERB
cana-5954	194	62	model	model	NOUN
cana-5954	194	63	model	model	NOUN
cana-5954	194	64	testing	testing	NOUN
cana-5954	194	65	initialize	initialize	VERB
cana-5954	194	66	the	the	DET
cana-5954	194	67	model	model	NOUN
cana-5954	194	68	&	&	CCONJ
cana-5954	194	69	load	load	VERB
cana-5954	194	70	the	the	DET
cana-5954	194	71	parameter	parameter	NOUN
cana-5954	194	72	test	test	NOUN
cana-5954	195	1	_	_	DET
cana-5954	195	2	prediction	prediction	NOUN
cana-5954	195	3	←	←	PROPN
cana-5954	195	4	model	model	NOUN
cana-5954	195	5	(	(	PUNCT
cana-5954	195	6	test_data	test_data	NOUN
cana-5954	195	7	)	)	PUNCT
cana-5954	195	8	return	return	NOUN
cana-5954	195	9	(	(	PUNCT
cana-5954	195	10	test_prediction	test_prediction	NOUN
cana-5954	195	11	)	)	PUNCT
cana-5954	195	12	}	}	PUNCT
cana-5954	195	13	algorithm	algorithm	NOUN
cana-5954	195	14	4	4	NUM
cana-5954	195	15	illustrates	illustrate	VERB
cana-5954	195	16	the	the	DET
cana-5954	195	17	training	training	NOUN
cana-5954	195	18	and	and	CCONJ
cana-5954	195	19	testing	testing	NOUN
cana-5954	195	20	of	of	ADP
cana-5954	195	21	a	a	DET
cana-5954	195	22	cnn	cnn	NOUN
cana-5954	195	23	—	—	PUNCT
cana-5954	195	24	a	a	DET
cana-5954	195	25	deep	deep	ADJ
cana-5954	195	26	learning	learning	NOUN
cana-5954	195	27	model	model	NOUN
cana-5954	195	28	—	—	PUNCT
cana-5954	195	29	for	for	ADP
cana-5954	195	30	classification	classification	NOUN
cana-5954	195	31	.	.	PUNCT
cana-5954	196	1	the	the	DET
cana-5954	196	2	model	model	NOUN
cana-5954	196	3	is	be	AUX
cana-5954	196	4	trained	train	VERB
cana-5954	196	5	initially	initially	ADV
cana-5954	196	6	on	on	ADP
cana-5954	196	7	batches	batch	NOUN
cana-5954	196	8	of	of	ADP
cana-5954	196	9	the	the	DET
cana-5954	196	10	training	training	NOUN
cana-5954	196	11	data	datum	NOUN
cana-5954	196	12	by	by	ADP
cana-5954	196	13	going	go	VERB
cana-5954	196	14	through	through	ADP
cana-5954	196	15	a	a	DET
cana-5954	196	16	set	set	ADJ
cana-5954	196	17	number	number	NOUN
cana-5954	196	18	of	of	ADP
cana-5954	196	19	epochs	epoch	NOUN
cana-5954	196	20	.	.	PUNCT
cana-5954	197	1	for	for	ADP
cana-5954	197	2	each	each	DET
cana-5954	197	3	batch	batch	NOUN
cana-5954	197	4	,	,	PUNCT
cana-5954	197	5	features	feature	NOUN
cana-5954	197	6	are	be	AUX
cana-5954	197	7	extracted	extract	VERB
cana-5954	197	8	using	use	VERB
cana-5954	197	9	the	the	DET
cana-5954	197	10	previously	previously	ADV
cana-5954	197	11	constructed	construct	VERB
cana-5954	197	12	cnn	cnn	PROPN
cana-5954	197	13	model	model	NOUN
cana-5954	197	14	.	.	PUNCT
cana-5954	198	1	the	the	DET
cana-5954	198	2	derivative	derivative	NOUN
cana-5954	198	3	of	of	ADP
cana-5954	198	4	the	the	DET
cana-5954	198	5	loss	loss	NOUN
cana-5954	198	6	function	function	NOUN
cana-5954	198	7	with	with	ADP
cana-5954	198	8	respect	respect	NOUN
cana-5954	198	9	to	to	ADP
cana-5954	198	10	model	model	NOUN
cana-5954	198	11	parameters	parameter	NOUN
cana-5954	198	12	is	be	AUX
cana-5954	198	13	calculated	calculate	VERB
cana-5954	198	14	by	by	ADP
cana-5954	198	15	backpropagation	backpropagation	NOUN
cana-5954	198	16	.	.	PUNCT
cana-5954	199	1	gradient	gradient	ADJ
cana-5954	199	2	descent	descent	NOUN
cana-5954	199	3	is	be	AUX
cana-5954	199	4	employed	employ	VERB
cana-5954	199	5	to	to	PART
cana-5954	199	6	update	update	VERB
cana-5954	199	7	these	these	DET
cana-5954	199	8	parameters	parameter	NOUN
cana-5954	199	9	,	,	PUNCT
cana-5954	199	10	the	the	DET
cana-5954	199	11	learning	learning	NOUN
cana-5954	199	12	rate	rate	NOUN
cana-5954	199	13	controlling	control	VERB
cana-5954	199	14	the	the	DET
cana-5954	199	15	step	step	NOUN
cana-5954	199	16	size	size	NOUN
cana-5954	199	17	of	of	ADP
cana-5954	199	18	the	the	DET
cana-5954	199	19	updates	update	NOUN
cana-5954	199	20	.	.	PUNCT
cana-5954	200	1	after	after	ADP
cana-5954	200	2	training	training	NOUN
cana-5954	200	3	,	,	PUNCT
cana-5954	200	4	the	the	DET
cana-5954	200	5	model	model	NOUN
cana-5954	200	6	is	be	AUX
cana-5954	200	7	stored	store	VERB
cana-5954	200	8	for	for	ADP
cana-5954	200	9	further	further	ADJ
cana-5954	200	10	use	use	NOUN
cana-5954	200	11	.	.	PUNCT
cana-5954	201	1	the	the	DET
cana-5954	201	2	stored	store	VERB
cana-5954	201	3	model	model	NOUN
cana-5954	201	4	is	be	AUX
cana-5954	201	5	loaded	load	VERB
cana-5954	201	6	with	with	ADP
cana-5954	201	7	its	its	PRON
cana-5954	201	8	pre	pre	ADJ
cana-5954	201	9	-	-	ADJ
cana-5954	201	10	trained	train	VERB
cana-5954	201	11	parameters	parameter	NOUN
cana-5954	201	12	for	for	ADP
cana-5954	201	13	assessment	assessment	NOUN
cana-5954	201	14	during	during	ADP
cana-5954	201	15	testing	testing	NOUN
cana-5954	201	16	.	.	PUNCT
cana-5954	202	1	inference	inference	NOUN
cana-5954	202	2	is	be	AUX
cana-5954	202	3	then	then	ADV
cana-5954	202	4	performed	perform	VERB
cana-5954	202	5	on	on	ADP
cana-5954	202	6	the	the	DET
cana-5954	202	7	test	test	NOUN
cana-5954	202	8	dataset	dataset	VERB
cana-5954	202	9	to	to	PART
cana-5954	202	10	generate	generate	VERB
cana-5954	202	11	predictions	prediction	NOUN
cana-5954	202	12	.	.	PUNCT
cana-5954	203	1	finally	finally	ADV
cana-5954	203	2	,	,	PUNCT
cana-5954	203	3	the	the	DET
cana-5954	203	4	algorithm	algorithm	NOUN
cana-5954	203	5	returns	return	VERB
cana-5954	203	6	the	the	DET
cana-5954	203	7	predictions	prediction	NOUN
cana-5954	203	8	made	make	VERB
cana-5954	203	9	by	by	ADP
cana-5954	203	10	the	the	DET
cana-5954	203	11	model	model	NOUN
cana-5954	203	12	on	on	ADP
cana-5954	203	13	the	the	DET
cana-5954	203	14	test	test	NOUN
cana-5954	203	15	data	datum	NOUN
cana-5954	203	16	.	.	PUNCT
cana-5954	204	1	communications	communication	NOUN
cana-5954	204	2	on	on	ADP
cana-5954	204	3	applied	apply	VERB
cana-5954	204	4	nonlinear	nonlinear	ADJ
cana-5954	204	5	analysis	analysis	NOUN
cana-5954	204	6	issn	issn	NOUN
cana-5954	204	7	:	:	PUNCT
cana-5954	204	8	1074	1074	NUM
cana-5954	204	9	-	-	PUNCT
cana-5954	204	10	133x	133x	NUM
cana-5954	204	11	vol	vol	VERB
cana-5954	204	12	32	32	NUM
cana-5954	204	13	no	no	NOUN
cana-5954	204	14	.	.	PUNCT
cana-5954	205	1	10s	10	NOUN
cana-5954	205	2	(	(	PUNCT
cana-5954	205	3	2025	2025	NUM
cana-5954	205	4	)	)	PUNCT
cana-5954	205	5	3184	3184	NUM
cana-5954	205	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	205	7	4	4	X
cana-5954	205	8	.	.	PUNCT
cana-5954	205	9	results	result	VERB
cana-5954	205	10	analysis	analysis	NOUN
cana-5954	205	11	the	the	DET
cana-5954	205	12	primary	primary	ADJ
cana-5954	205	13	programming	programming	NOUN
cana-5954	205	14	language	language	NOUN
cana-5954	205	15	utilized	utilize	VERB
cana-5954	205	16	in	in	ADP
cana-5954	205	17	the	the	DET
cana-5954	205	18	experiment	experiment	NOUN
cana-5954	205	19	was	be	AUX
cana-5954	205	20	python	python	NOUN
cana-5954	205	21	3.6	3.6	NUM
cana-5954	205	22	,	,	PUNCT
cana-5954	205	23	which	which	PRON
cana-5954	205	24	was	be	AUX
cana-5954	205	25	conducted	conduct	VERB
cana-5954	205	26	on	on	ADP
cana-5954	205	27	a	a	DET
cana-5954	205	28	64	64	NUM
cana-5954	205	29	-	-	PUNCT
cana-5954	205	30	bit	bit	NOUN
cana-5954	205	31	version	version	NOUN
cana-5954	205	32	of	of	ADP
cana-5954	205	33	windows	window	NOUN
cana-5954	205	34	10	10	NUM
cana-5954	205	35	.	.	PUNCT
cana-5954	206	1	keras	keras	PROPN
cana-5954	206	2	was	be	AUX
cana-5954	206	3	the	the	DET
cana-5954	206	4	backend	backend	NOUN
cana-5954	206	5	for	for	ADP
cana-5954	206	6	the	the	DET
cana-5954	206	7	tensorflow	tensorflow	NOUN
cana-5954	206	8	framework	framework	NOUN
cana-5954	206	9	,	,	PUNCT
cana-5954	206	10	and	and	CCONJ
cana-5954	206	11	it	it	PRON
cana-5954	206	12	was	be	AUX
cana-5954	206	13	utilized	utilize	VERB
cana-5954	206	14	for	for	ADP
cana-5954	206	15	model	model	NOUN
cana-5954	206	16	construction	construction	NOUN
cana-5954	206	17	as	as	ADV
cana-5954	206	18	well	well	ADV
cana-5954	206	19	as	as	ADP
cana-5954	206	20	training	training	NOUN
cana-5954	206	21	.	.	PUNCT
cana-5954	207	1	the	the	DET
cana-5954	207	2	implementation	implementation	NOUN
cana-5954	207	3	was	be	AUX
cana-5954	207	4	done	do	VERB
cana-5954	207	5	on	on	ADP
cana-5954	207	6	a	a	DET
cana-5954	207	7	machine	machine	NOUN
cana-5954	207	8	with	with	ADP
cana-5954	207	9	an	an	DET
cana-5954	207	10	intel	intel	PROPN
cana-5954	207	11	®	®	NOUN
cana-5954	207	12	core	core	NOUN
cana-5954	207	13	™	™	ADJ
cana-5954	207	14	i7	i7	NOUN
cana-5954	207	15	-	-	PUNCT
cana-5954	207	16	8700	8700	NUM
cana-5954	207	17	cpu	cpu	NOUN
cana-5954	207	18	at	at	ADP
cana-5954	207	19	4.60ghz	4.60ghz	NUM
cana-5954	207	20	,	,	PUNCT
cana-5954	207	21	a	a	DET
cana-5954	207	22	12	12	NUM
cana-5954	207	23	mb	mb	ADP
cana-5954	207	24	cache	cache	NOUN
cana-5954	207	25	,	,	PUNCT
cana-5954	207	26	and	and	CCONJ
cana-5954	207	27	16	16	NUM
cana-5954	207	28	gb	gb	NOUN
cana-5954	207	29	of	of	ADP
cana-5954	207	30	ram	ram	NOUN
cana-5954	207	31	.	.	PUNCT
cana-5954	208	1	the	the	DET
cana-5954	208	2	assessment	assessment	NOUN
cana-5954	208	3	of	of	ADP
cana-5954	208	4	the	the	DET
cana-5954	208	5	resnet50	resnet50	NOUN
cana-5954	208	6	cnn	cnn	PROPN
cana-5954	208	7	model	model	NOUN
cana-5954	208	8	was	be	AUX
cana-5954	208	9	conducted	conduct	VERB
cana-5954	208	10	using	use	VERB
cana-5954	208	11	a	a	DET
cana-5954	208	12	batch	batch	NOUN
cana-5954	208	13	size	size	NOUN
cana-5954	208	14	of	of	ADP
cana-5954	208	15	20	20	NUM
cana-5954	208	16	and	and	CCONJ
cana-5954	208	17	over	over	ADP
cana-5954	208	18	100	100	NUM
cana-5954	208	19	epochs	epoch	NOUN
cana-5954	208	20	.	.	PUNCT
cana-5954	209	1	the	the	DET
cana-5954	209	2	evaluation	evaluation	NOUN
cana-5954	209	3	metrics	metric	NOUN
cana-5954	209	4	and	and	CCONJ
cana-5954	209	5	performance	performance	NOUN
cana-5954	209	6	results	result	NOUN
cana-5954	209	7	were	be	AUX
cana-5954	209	8	recorded	record	VERB
cana-5954	209	9	accordingly	accordingly	ADV
cana-5954	209	10	.	.	PUNCT
cana-5954	210	1	the	the	DET
cana-5954	210	2	plot	plot	NOUN
cana-5954	210	3	illustrates	illustrate	VERB
cana-5954	210	4	the	the	DET
cana-5954	210	5	iterative	iterative	NOUN
cana-5954	210	6	steps	step	NOUN
cana-5954	210	7	involved	involve	VERB
cana-5954	210	8	in	in	ADP
cana-5954	210	9	feature	feature	NOUN
cana-5954	210	10	extraction	extraction	NOUN
cana-5954	210	11	from	from	ADP
cana-5954	210	12	the	the	DET
cana-5954	210	13	images	image	NOUN
cana-5954	210	14	during	during	ADP
cana-5954	210	15	model	model	NOUN
cana-5954	210	16	training	training	NOUN
cana-5954	210	17	.	.	PUNCT
cana-5954	211	1	a	a	DET
cana-5954	211	2	remarkable	remarkable	ADJ
cana-5954	211	3	accuracy	accuracy	NOUN
cana-5954	211	4	of	of	ADP
cana-5954	211	5	98.70	98.70	NUM
cana-5954	211	6	%	%	NOUN
cana-5954	211	7	is	be	AUX
cana-5954	211	8	shown	show	VERB
cana-5954	211	9	by	by	ADP
cana-5954	211	10	the	the	DET
cana-5954	211	11	results	result	NOUN
cana-5954	211	12	.	.	PUNCT
cana-5954	212	1	4.1	4.1	NUM
cana-5954	212	2	x	x	NOUN
cana-5954	212	3	-	-	NOUN
cana-5954	212	4	ray	ray	NOUN
cana-5954	212	5	image	image	NOUN
cana-5954	212	6	after	after	ADP
cana-5954	212	7	training	training	NOUN
cana-5954	212	8	and	and	CCONJ
cana-5954	212	9	testing	test	VERB
cana-5954	212	10	a	a	DET
cana-5954	212	11	grid	grid	NOUN
cana-5954	212	12	of	of	ADP
cana-5954	212	13	chest	chest	NOUN
cana-5954	212	14	x	x	NOUN
cana-5954	212	15	-	-	NOUN
cana-5954	212	16	ray	ray	NOUN
cana-5954	212	17	pictures	picture	NOUN
cana-5954	212	18	classified	classify	VERB
cana-5954	212	19	as	as	ADP
cana-5954	212	20	covid-19	covid-19	PROPN
cana-5954	212	21	,	,	PUNCT
cana-5954	212	22	pneumonia	pneumonia	NOUN
cana-5954	212	23	,	,	PUNCT
cana-5954	212	24	and	and	CCONJ
cana-5954	212	25	normal	normal	ADJ
cana-5954	212	26	is	be	AUX
cana-5954	212	27	displayed	display	VERB
cana-5954	212	28	in	in	ADP
cana-5954	212	29	the	the	DET
cana-5954	212	30	image	image	NOUN
cana-5954	212	31	.	.	PUNCT
cana-5954	213	1	the	the	DET
cana-5954	213	2	training	training	NOUN
cana-5954	213	3	and	and	CCONJ
cana-5954	213	4	testing	testing	NOUN
cana-5954	213	5	procedure	procedure	NOUN
cana-5954	213	6	of	of	ADP
cana-5954	213	7	the	the	DET
cana-5954	213	8	suggested	suggest	VERB
cana-5954	213	9	model	model	NOUN
cana-5954	213	10	for	for	ADP
cana-5954	213	11	grouping	group	VERB
cana-5954	213	12	chest	chest	NOUN
cana-5954	213	13	x	x	NOUN
cana-5954	213	14	-	-	NOUN
cana-5954	213	15	rays	ray	NOUN
cana-5954	213	16	into	into	ADP
cana-5954	213	17	these	these	DET
cana-5954	213	18	three	three	NUM
cana-5954	213	19	categories	category	NOUN
cana-5954	213	20	is	be	AUX
cana-5954	213	21	depicted	depict	VERB
cana-5954	213	22	in	in	ADP
cana-5954	213	23	figure	figure	NOUN
cana-5954	213	24	6	6	NUM
cana-5954	213	25	,	,	PUNCT
cana-5954	213	26	which	which	PRON
cana-5954	213	27	also	also	ADV
cana-5954	213	28	shows	show	VERB
cana-5954	213	29	the	the	DET
cana-5954	213	30	x	x	ADJ
cana-5954	213	31	-	-	NOUN
cana-5954	213	32	ray	ray	NOUN
cana-5954	213	33	picture	picture	NOUN
cana-5954	213	34	analysis	analysis	NOUN
cana-5954	213	35	.	.	PUNCT
cana-5954	214	1	firstly	firstly	ADV
cana-5954	214	2	,	,	PUNCT
cana-5954	214	3	the	the	DET
cana-5954	214	4	x	x	NOUN
cana-5954	214	5	-	-	NOUN
cana-5954	214	6	rays	ray	NOUN
cana-5954	214	7	labeled	label	VERB
cana-5954	214	8	normal	normal	ADJ
cana-5954	214	9	show	show	VERB
cana-5954	214	10	healthy	healthy	ADJ
cana-5954	214	11	lungs	lung	NOUN
cana-5954	214	12	without	without	ADP
cana-5954	214	13	any	any	DET
cana-5954	214	14	signs	sign	NOUN
cana-5954	214	15	of	of	ADP
cana-5954	214	16	infection	infection	NOUN
cana-5954	214	17	.	.	PUNCT
cana-5954	215	1	secondly	secondly	ADV
cana-5954	215	2	,	,	PUNCT
cana-5954	215	3	the	the	DET
cana-5954	215	4	x	x	NOUN
cana-5954	215	5	-	-	NOUN
cana-5954	215	6	rays	ray	NOUN
cana-5954	215	7	labeled	label	VERB
cana-5954	215	8	pneumonia	pneumonia	NOUN
cana-5954	215	9	show	show	VERB
cana-5954	215	10	signs	sign	NOUN
cana-5954	215	11	of	of	ADP
cana-5954	215	12	lung	lung	NOUN
cana-5954	215	13	infection	infection	NOUN
cana-5954	215	14	,	,	PUNCT
cana-5954	215	15	characterized	characterize	VERB
cana-5954	215	16	by	by	ADP
cana-5954	215	17	the	the	DET
cana-5954	215	18	presence	presence	NOUN
cana-5954	215	19	of	of	ADP
cana-5954	215	20	fluid	fluid	NOUN
cana-5954	215	21	or	or	CCONJ
cana-5954	215	22	inflammation	inflammation	NOUN
cana-5954	215	23	.	.	PUNCT
cana-5954	216	1	finally	finally	ADV
cana-5954	216	2	,	,	PUNCT
cana-5954	216	3	the	the	DET
cana-5954	216	4	x	x	NOUN
cana-5954	216	5	-	-	NOUN
cana-5954	216	6	rays	ray	NOUN
cana-5954	216	7	labeled	label	VERB
cana-5954	216	8	covid	covid	PROPN
cana-5954	216	9	likely	likely	ADV
cana-5954	216	10	show	show	VERB
cana-5954	216	11	the	the	DET
cana-5954	216	12	typical	typical	ADJ
cana-5954	216	13	patterns	pattern	NOUN
cana-5954	216	14	of	of	ADP
cana-5954	216	15	lung	lung	NOUN
cana-5954	216	16	involvement	involvement	NOUN
cana-5954	216	17	seen	see	VERB
cana-5954	216	18	in	in	ADP
cana-5954	216	19	covid-19	covid-19	PROPN
cana-5954	216	20	patients	patient	NOUN
cana-5954	216	21	.	.	PUNCT
cana-5954	217	1	fig.6	fig.6	PROPN
cana-5954	217	2	.	.	PUNCT
cana-5954	218	1	chest	chest	NOUN
cana-5954	218	2	x	x	NOUN
cana-5954	218	3	-	-	NOUN
cana-5954	218	4	rays	ray	NOUN
cana-5954	218	5	images	image	VERB
cana-5954	218	6	analysis	analysis	NOUN
cana-5954	218	7	4.2	4.2	NUM
cana-5954	218	8	performance	performance	NOUN
cana-5954	218	9	of	of	ADP
cana-5954	218	10	model	model	NOUN
cana-5954	218	11	over	over	ADP
cana-5954	218	12	10	10	NUM
cana-5954	218	13	,	,	PUNCT
cana-5954	218	14	30	30	NUM
cana-5954	218	15	&	&	CCONJ
cana-5954	218	16	50	50	NUM
cana-5954	218	17	epochs	epoch	NOUN
cana-5954	218	18	training	training	NOUN
cana-5954	218	19	and	and	CCONJ
cana-5954	218	20	validation	validation	NOUN
cana-5954	218	21	metrics	metric	NOUN
cana-5954	218	22	are	be	AUX
cana-5954	218	23	compared	compare	VERB
cana-5954	218	24	in	in	ADP
cana-5954	218	25	the	the	DET
cana-5954	218	26	graph	graph	NOUN
cana-5954	218	27	.	.	PUNCT
cana-5954	219	1	whereas	whereas	SCONJ
cana-5954	219	2	figure	figure	NOUN
cana-5954	219	3	7(a	7(a	NUM
cana-5954	219	4	)	)	PUNCT
cana-5954	219	5	presents	present	VERB
cana-5954	219	6	the	the	DET
cana-5954	219	7	training	training	NOUN
cana-5954	219	8	and	and	CCONJ
cana-5954	219	9	validation	validation	NOUN
cana-5954	219	10	loss	loss	NOUN
cana-5954	219	11	,	,	PUNCT
cana-5954	219	12	figure	figure	NOUN
cana-5954	219	13	7(b	7(b	NOUN
cana-5954	219	14	)	)	PUNCT
cana-5954	219	15	presents	present	VERB
cana-5954	219	16	the	the	DET
cana-5954	219	17	training	training	NOUN
cana-5954	219	18	and	and	CCONJ
cana-5954	219	19	validation	validation	NOUN
cana-5954	219	20	accuracy	accuracy	NOUN
cana-5954	219	21	.	.	PUNCT
cana-5954	220	1	as	as	SCONJ
cana-5954	220	2	summarized	summarize	VERB
cana-5954	220	3	in	in	ADP
cana-5954	220	4	table	table	NOUN
cana-5954	220	5	2	2	NUM
cana-5954	220	6	,	,	PUNCT
cana-5954	220	7	the	the	DET
cana-5954	220	8	data	datum	NOUN
cana-5954	220	9	indicates	indicate	VERB
cana-5954	220	10	the	the	DET
cana-5954	220	11	results	result	NOUN
cana-5954	220	12	of	of	ADP
cana-5954	220	13	training	training	NOUN
cana-5954	220	14	a	a	DET
cana-5954	220	15	deep	deep	ADJ
cana-5954	220	16	learning	learning	NOUN
cana-5954	220	17	model	model	NOUN
cana-5954	220	18	for	for	ADP
cana-5954	220	19	10	10	NUM
cana-5954	220	20	,	,	PUNCT
cana-5954	220	21	30	30	NUM
cana-5954	220	22	,	,	PUNCT
cana-5954	220	23	and	and	CCONJ
cana-5954	220	24	50	50	NUM
cana-5954	220	25	epochs	epoch	NOUN
cana-5954	220	26	,	,	PUNCT
cana-5954	220	27	along	along	ADP
cana-5954	220	28	with	with	ADP
cana-5954	220	29	corresponding	correspond	VERB
cana-5954	220	30	metrics	metric	NOUN
cana-5954	220	31	for	for	ADP
cana-5954	220	32	training	training	NOUN
cana-5954	220	33	accuracy	accuracy	NOUN
cana-5954	220	34	,	,	PUNCT
cana-5954	220	35	validation	validation	NOUN
cana-5954	220	36	accuracy	accuracy	NOUN
cana-5954	220	37	,	,	PUNCT
cana-5954	220	38	training	training	NOUN
cana-5954	220	39	loss	loss	NOUN
cana-5954	220	40	,	,	PUNCT
cana-5954	220	41	and	and	CCONJ
cana-5954	220	42	validation	validation	NOUN
cana-5954	220	43	loss	loss	NOUN
cana-5954	220	44	.	.	PUNCT
cana-5954	221	1	communications	communication	NOUN
cana-5954	221	2	on	on	ADP
cana-5954	221	3	applied	apply	VERB
cana-5954	221	4	nonlinear	nonlinear	ADJ
cana-5954	221	5	analysis	analysis	NOUN
cana-5954	221	6	issn	issn	NOUN
cana-5954	221	7	:	:	PUNCT
cana-5954	221	8	1074	1074	NUM
cana-5954	221	9	-	-	PUNCT
cana-5954	221	10	133x	133x	NUM
cana-5954	221	11	vol	vol	VERB
cana-5954	221	12	32	32	NUM
cana-5954	221	13	no	no	NOUN
cana-5954	221	14	.	.	PUNCT
cana-5954	222	1	10s	10	NOUN
cana-5954	222	2	(	(	PUNCT
cana-5954	222	3	2025	2025	NUM
cana-5954	222	4	)	)	PUNCT
cana-5954	222	5	3185	3185	NUM
cana-5954	222	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	222	7	(	(	PUNCT
cana-5954	222	8	a	a	NOUN
cana-5954	222	9	)	)	PUNCT
cana-5954	222	10	(	(	PUNCT
cana-5954	222	11	b	b	X
cana-5954	222	12	)	)	PUNCT
cana-5954	222	13	fig.7	fig.7	ADV
cana-5954	222	14	.	.	PUNCT
cana-5954	223	1	(	(	PUNCT
cana-5954	223	2	a	a	X
cana-5954	223	3	)	)	PUNCT
cana-5954	223	4	and	and	CCONJ
cana-5954	223	5	(	(	PUNCT
cana-5954	223	6	b	b	X
cana-5954	223	7	)	)	PUNCT
cana-5954	223	8	shows	show	VERB
cana-5954	223	9	two	two	NUM
cana-5954	223	10	graphs	graph	NOUN
cana-5954	223	11	comparing	compare	VERB
cana-5954	223	12	training	training	NOUN
cana-5954	223	13	and	and	CCONJ
cana-5954	223	14	validation	validation	NOUN
cana-5954	223	15	metrics	metric	NOUN
cana-5954	223	16	over	over	ADP
cana-5954	223	17	10	10	NUM
cana-5954	223	18	,	,	PUNCT
cana-5954	223	19	30	30	NUM
cana-5954	223	20	,	,	PUNCT
cana-5954	223	21	&	&	CCONJ
cana-5954	223	22	50	50	NUM
cana-5954	223	23	epochs	epoch	NOUN
cana-5954	223	24	table	table	NOUN
cana-5954	223	25	2	2	NUM
cana-5954	223	26	.	.	PUNCT
cana-5954	223	27	represents	represent	VERB
cana-5954	223	28	the	the	DET
cana-5954	223	29	results	result	NOUN
cana-5954	223	30	of	of	ADP
cana-5954	223	31	training	training	NOUN
cana-5954	223	32	of	of	ADP
cana-5954	223	33	deep	deep	ADJ
cana-5954	223	34	learning	learning	NOUN
cana-5954	223	35	model	model	NOUN
cana-5954	223	36	over	over	ADP
cana-5954	223	37	10	10	NUM
cana-5954	223	38	,	,	PUNCT
cana-5954	223	39	30	30	NUM
cana-5954	223	40	,	,	PUNCT
cana-5954	223	41	and	and	CCONJ
cana-5954	223	42	50	50	NUM
cana-5954	223	43	epochs	epoch	NOUN
cana-5954	223	44	parameters	parameter	NOUN
cana-5954	223	45	10	10	NUM
cana-5954	223	46	epochs	epoch	NOUN
cana-5954	223	47	30	30	NUM
cana-5954	223	48	epochs	epoch	NOUN
cana-5954	223	49	50	50	NUM
cana-5954	223	50	epochs	epoch	NOUN
cana-5954	223	51	training	train	VERB
cana-5954	223	52	loss	loss	NOUN
cana-5954	223	53	0.25	0.25	NUM
cana-5954	223	54	0.15	0.15	NUM
cana-5954	223	55	0.10	0.10	NUM
cana-5954	223	56	validation	validation	NOUN
cana-5954	223	57	loss	loss	NOUN
cana-5954	223	58	0.25	0.25	NUM
cana-5954	223	59	0.17	0.17	NUM
cana-5954	223	60	0.15	0.15	NUM
cana-5954	223	61	training	training	NOUN
cana-5954	223	62	accuracy	accuracy	NOUN
cana-5954	223	63	0.91	0.91	NUM
cana-5954	223	64	0.95	0.95	NUM
cana-5954	223	65	0.987	0.987	NUM
cana-5954	223	66	validation	validation	NOUN
cana-5954	223	67	accuracy	accuracy	NOUN
cana-5954	223	68	0.93	0.93	NUM
cana-5954	223	69	0.94	0.94	NUM
cana-5954	223	70	0.97	0.97	NUM
cana-5954	223	71	4.3	4.3	NUM
cana-5954	223	72	classification	classification	NOUN
cana-5954	223	73	report	report	NOUN
cana-5954	223	74	the	the	DET
cana-5954	223	75	table	table	NOUN
cana-5954	223	76	3	3	NUM
cana-5954	223	77	appears	appear	VERB
cana-5954	223	78	to	to	PART
cana-5954	223	79	be	be	AUX
cana-5954	223	80	an	an	DET
cana-5954	223	81	evaluation	evaluation	NOUN
cana-5954	223	82	report	report	NOUN
cana-5954	223	83	for	for	ADP
cana-5954	223	84	a	a	DET
cana-5954	223	85	classification	classification	NOUN
cana-5954	223	86	model	model	NOUN
cana-5954	223	87	,	,	PUNCT
cana-5954	223	88	possibly	possibly	ADV
cana-5954	223	89	for	for	ADP
cana-5954	223	90	predicting	predict	VERB
cana-5954	223	91	covid	covid	PROPN
cana-5954	223	92	,	,	PUNCT
cana-5954	223	93	normal	normal	ADJ
cana-5954	223	94	,	,	PUNCT
cana-5954	223	95	and	and	CCONJ
cana-5954	223	96	pneumonia	pneumonia	NOUN
cana-5954	223	97	classes	class	NOUN
cana-5954	223	98	.	.	PUNCT
cana-5954	224	1	communications	communication	NOUN
cana-5954	224	2	on	on	ADP
cana-5954	224	3	applied	apply	VERB
cana-5954	224	4	nonlinear	nonlinear	ADJ
cana-5954	224	5	analysis	analysis	NOUN
cana-5954	224	6	issn	issn	NOUN
cana-5954	224	7	:	:	PUNCT
cana-5954	224	8	1074	1074	NUM
cana-5954	224	9	-	-	PUNCT
cana-5954	224	10	133x	133x	NUM
cana-5954	224	11	vol	vol	VERB
cana-5954	224	12	32	32	NUM
cana-5954	224	13	no	no	NOUN
cana-5954	224	14	.	.	PUNCT
cana-5954	225	1	10s	10	NOUN
cana-5954	225	2	(	(	PUNCT
cana-5954	225	3	2025	2025	NUM
cana-5954	225	4	)	)	PUNCT
cana-5954	225	5	3186	3186	NUM
cana-5954	225	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	225	7	table	table	NOUN
cana-5954	225	8	3	3	NUM
cana-5954	225	9	.	.	PUNCT
cana-5954	225	10	evaluation	evaluation	NOUN
cana-5954	225	11	report	report	NOUN
cana-5954	225	12	of	of	ADP
cana-5954	225	13	classification	classification	NOUN
cana-5954	225	14	model	model	NOUN
cana-5954	225	15	precision	precision	NOUN
cana-5954	225	16	recall	recall	NOUN
cana-5954	225	17	f1	f1	NOUN
cana-5954	225	18	-	-	PUNCT
cana-5954	225	19	score	score	NOUN
cana-5954	225	20	support	support	NOUN
cana-5954	225	21	covid-19	covid-19	PROPN
cana-5954	225	22	1.00	1.00	NUM
cana-5954	225	23	0.98	0.98	NUM
cana-5954	225	24	0.99	0.99	NUM
cana-5954	225	25	163	163	NUM
cana-5954	225	26	normal	normal	ADJ
cana-5954	225	27	0.99	0.99	NUM
cana-5954	225	28	0.96	0.96	NUM
cana-5954	225	29	0.97	0.97	NUM
cana-5954	225	30	180	180	NUM
cana-5954	225	31	pnemonia	pnemonia	NOUN
cana-5954	225	32	0.95	0.95	NUM
cana-5954	225	33	0.99	0.99	NUM
cana-5954	225	34	0.97	0.97	NUM
cana-5954	225	35	180	180	NUM
cana-5954	225	36	accuracy	accuracy	NOUN
cana-5954	225	37	0.98	0.98	NUM
cana-5954	225	38	523	523	NUM
cana-5954	225	39	macro	macro	NOUN
cana-5954	225	40	avg	avg	NOUN
cana-5954	225	41	0.98	0.98	NUM
cana-5954	225	42	0.98	0.98	NUM
cana-5954	225	43	0.98	0.98	NUM
cana-5954	225	44	523	523	NUM
cana-5954	225	45	weighted	weight	VERB
cana-5954	225	46	avg	avg	NOUN
cana-5954	225	47	0.98	0.98	NUM
cana-5954	225	48	0.98	0.98	NUM
cana-5954	225	49	0.98	0.98	NUM
cana-5954	225	50	523	523	NUM
cana-5954	225	51	4.4	4.4	NUM
cana-5954	225	52	confusion	confusion	NOUN
cana-5954	225	53	matrix	matrix	NOUN
cana-5954	225	54	a	a	DET
cana-5954	225	55	confusion	confusion	NOUN
cana-5954	225	56	matrix	matrix	NOUN
cana-5954	225	57	showing	show	VERB
cana-5954	225	58	a	a	DET
cana-5954	225	59	classification	classification	NOUN
cana-5954	225	60	model	model	NOUN
cana-5954	225	61	's	's	PART
cana-5954	225	62	performance	performance	NOUN
cana-5954	225	63	across	across	ADP
cana-5954	225	64	three	three	NUM
cana-5954	225	65	categories	category	NOUN
cana-5954	225	66	covid	covid	NOUN
cana-5954	225	67	,	,	PUNCT
cana-5954	225	68	normal	normal	ADJ
cana-5954	225	69	,	,	PUNCT
cana-5954	225	70	and	and	CCONJ
cana-5954	225	71	pneumonia	pneumonia	NOUN
cana-5954	225	72	is	be	AUX
cana-5954	225	73	shown	show	VERB
cana-5954	225	74	in	in	ADP
cana-5954	225	75	figure	figure	NOUN
cana-5954	225	76	8	8	NUM
cana-5954	225	77	.	.	PUNCT
cana-5954	226	1	the	the	DET
cana-5954	226	2	projected	project	VERB
cana-5954	226	3	labels	label	NOUN
cana-5954	226	4	covid	covid	PROPN
cana-5954	226	5	,	,	PUNCT
cana-5954	226	6	normal	normal	ADJ
cana-5954	226	7	,	,	PUNCT
cana-5954	226	8	and	and	CCONJ
cana-5954	226	9	pneumonia	pneumonia	NOUN
cana-5954	226	10	are	be	AUX
cana-5954	226	11	shown	show	VERB
cana-5954	226	12	on	on	ADP
cana-5954	226	13	the	the	DET
cana-5954	226	14	xand	xand	PROPN
cana-5954	226	15	y	y	PROPN
cana-5954	226	16	-	-	PUNCT
cana-5954	226	17	axes	axis	NOUN
cana-5954	226	18	.	.	PUNCT
cana-5954	227	1	the	the	DET
cana-5954	227	2	values	value	NOUN
cana-5954	227	3	in	in	ADP
cana-5954	227	4	table	table	NOUN
cana-5954	227	5	4	4	NUM
cana-5954	227	6	are	be	AUX
cana-5954	227	7	as	as	SCONJ
cana-5954	227	8	follows	follow	VERB
cana-5954	227	9	:	:	PUNCT
cana-5954	227	10	fig	fig	NOUN
cana-5954	227	11	.8.visualizing	.8.visualize	VERB
cana-5954	227	12	the	the	DET
cana-5954	227	13	performance	performance	NOUN
cana-5954	227	14	of	of	ADP
cana-5954	227	15	a	a	DET
cana-5954	227	16	classification	classification	NOUN
cana-5954	227	17	model	model	NOUN
cana-5954	227	18	table	table	NOUN
cana-5954	227	19	4	4	NUM
cana-5954	227	20	.	.	PUNCT
cana-5954	227	21	predicted	predict	VERB
cana-5954	227	22	labels	label	NOUN
cana-5954	227	23	sl	sl	VERB
cana-5954	227	24	no	no	DET
cana-5954	227	25	labels	label	NOUN
cana-5954	227	26	covid-19	covid-19	PROPN
cana-5954	227	27	normal	normal	ADJ
cana-5954	227	28	pneumonia	pneumonia	NOUN
cana-5954	227	29	1	1	NUM
cana-5954	227	30	.	.	PUNCT
cana-5954	228	1	predicted	predict	VERB
cana-5954	228	2	covid	covid	PROPN
cana-5954	228	3	:	:	PUNCT
cana-5954	228	4	160	160	NUM
cana-5954	228	5	covid	covid	NOUN
cana-5954	228	6	:	:	PUNCT
cana-5954	228	7	0	0	PUNCT
cana-5954	228	8	covid	covid	NOUN
cana-5954	228	9	:	:	PUNCT
cana-5954	228	10	0	0	NUM
cana-5954	229	1	2	2	X
cana-5954	229	2	.	.	PUNCT
cana-5954	229	3	predicted	predict	VERB
cana-5954	229	4	normal	normal	ADJ
cana-5954	229	5	:	:	PUNCT
cana-5954	229	6	1	1	NUM
cana-5954	229	7	normal	normal	ADJ
cana-5954	229	8	:	:	PUNCT
cana-5954	229	9	173	173	NUM
cana-5954	229	10	normal	normal	ADJ
cana-5954	229	11	:	:	PUNCT
cana-5954	229	12	1	1	NUM
cana-5954	229	13	3	3	NUM
cana-5954	229	14	predicted	predict	VERB
cana-5954	229	15	pneumonia	pneumonia	NOUN
cana-5954	229	16	:	:	PUNCT
cana-5954	229	17	2	2	NUM
cana-5954	229	18	pneumonia	pneumonia	NOUN
cana-5954	229	19	:	:	PUNCT
cana-5954	229	20	7	7	NUM
cana-5954	229	21	pneumonia	pneumonia	NOUN
cana-5954	229	22	:	:	PUNCT
cana-5954	229	23	179	179	NUM
cana-5954	229	24	4.5	4.5	NUM
cana-5954	229	25	sensitivity	sensitivity	NOUN
cana-5954	229	26	and	and	CCONJ
cana-5954	229	27	specificity	specificity	NOUN
cana-5954	229	28	report	report	VERB
cana-5954	229	29	the	the	DET
cana-5954	229	30	table	table	NOUN
cana-5954	229	31	5	5	NUM
cana-5954	229	32	describes	describe	VERB
cana-5954	229	33	the	the	DET
cana-5954	229	34	sensitivity	sensitivity	NOUN
cana-5954	229	35	(	(	PUNCT
cana-5954	229	36	recall	recall	NOUN
cana-5954	229	37	)	)	PUNCT
cana-5954	229	38	and	and	CCONJ
cana-5954	229	39	specificity	specificity	NOUN
cana-5954	229	40	of	of	ADP
cana-5954	229	41	a	a	DET
cana-5954	229	42	classification	classification	NOUN
cana-5954	229	43	model	model	NOUN
cana-5954	229	44	for	for	ADP
cana-5954	229	45	each	each	DET
cana-5954	229	46	class	class	NOUN
cana-5954	229	47	.	.	PUNCT
cana-5954	230	1	communications	communication	NOUN
cana-5954	230	2	on	on	ADP
cana-5954	230	3	applied	apply	VERB
cana-5954	230	4	nonlinear	nonlinear	ADJ
cana-5954	230	5	analysis	analysis	NOUN
cana-5954	230	6	issn	issn	NOUN
cana-5954	230	7	:	:	PUNCT
cana-5954	230	8	1074	1074	NUM
cana-5954	230	9	-	-	PUNCT
cana-5954	230	10	133x	133x	NUM
cana-5954	230	11	vol	vol	VERB
cana-5954	230	12	32	32	NUM
cana-5954	230	13	no	no	NOUN
cana-5954	230	14	.	.	PUNCT
cana-5954	231	1	10s	10	NOUN
cana-5954	231	2	(	(	PUNCT
cana-5954	231	3	2025	2025	NUM
cana-5954	231	4	)	)	PUNCT
cana-5954	231	5	3187	3187	NUM
cana-5954	231	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	231	7	table	table	NOUN
cana-5954	231	8	5	5	NUM
cana-5954	231	9	.	.	PUNCT
cana-5954	231	10	describes	describe	VERB
cana-5954	231	11	the	the	DET
cana-5954	231	12	sensitivity	sensitivity	NOUN
cana-5954	231	13	and	and	CCONJ
cana-5954	231	14	specificity	specificity	NOUN
cana-5954	231	15	class	class	NOUN
cana-5954	231	16	sensitivity	sensitivity	NOUN
cana-5954	231	17	(	(	PUNCT
cana-5954	231	18	recall	recall	NOUN
cana-5954	231	19	)	)	PUNCT
cana-5954	231	20	specificity	specificity	NOUN
cana-5954	231	21	covid	covid	VERB
cana-5954	231	22	0.98	0.98	NUM
cana-5954	231	23	1.00	1.00	NUM
cana-5954	231	24	normal	normal	ADJ
cana-5954	231	25	0.96	0.96	NUM
cana-5954	231	26	0.99	0.99	NUM
cana-5954	231	27	pneumonia	pneumonia	NOUN
cana-5954	231	28	0.99	0.99	NUM
cana-5954	231	29	0.97	0.97	NUM
cana-5954	231	30	(	(	PUNCT
cana-5954	231	31	a	a	PRON
cana-5954	231	32	)	)	PUNCT
cana-5954	231	33	sensitivity	sensitivity	NOUN
cana-5954	231	34	:	:	PUNCT
cana-5954	231	35	the	the	DET
cana-5954	231	36	ratio	ratio	NOUN
cana-5954	231	37	of	of	ADP
cana-5954	231	38	actual	actual	ADJ
cana-5954	231	39	positive	positive	ADJ
cana-5954	231	40	cases	case	NOUN
cana-5954	231	41	correctly	correctly	ADV
cana-5954	231	42	identified	identify	VERB
cana-5954	231	43	by	by	ADP
cana-5954	231	44	the	the	DET
cana-5954	231	45	model	model	NOUN
cana-5954	231	46	is	be	AUX
cana-5954	231	47	indicated	indicate	VERB
cana-5954	231	48	by	by	ADP
cana-5954	231	49	this	this	DET
cana-5954	231	50	measure	measure	NOUN
cana-5954	231	51	:	:	PUNCT
cana-5954	231	52	98	98	NUM
cana-5954	231	53	%	%	NOUN
cana-5954	231	54	of	of	ADP
cana-5954	231	55	all	all	DET
cana-5954	231	56	actual	actual	ADJ
cana-5954	231	57	covid-19	covid-19	PROPN
cana-5954	231	58	cases	case	NOUN
cana-5954	231	59	are	be	AUX
cana-5954	231	60	rightly	rightly	ADV
cana-5954	231	61	identified	identify	VERB
cana-5954	231	62	by	by	ADP
cana-5954	231	63	the	the	DET
cana-5954	231	64	model	model	NOUN
cana-5954	231	65	.	.	PUNCT
cana-5954	232	1	this	this	DET
cana-5954	232	2	model	model	NOUN
cana-5954	232	3	also	also	ADV
cana-5954	232	4	correctly	correctly	ADV
cana-5954	232	5	classifies	classify	VERB
cana-5954	232	6	96	96	NUM
cana-5954	232	7	%	%	NOUN
cana-5954	232	8	of	of	ADP
cana-5954	232	9	all	all	DET
cana-5954	232	10	true	true	ADJ
cana-5954	232	11	normal	normal	ADJ
cana-5954	232	12	instances	instance	NOUN
cana-5954	232	13	and	and	CCONJ
cana-5954	232	14	classifies	classify	VERB
cana-5954	232	15	99	99	NUM
cana-5954	232	16	%	%	NOUN
cana-5954	232	17	of	of	ADP
cana-5954	232	18	all	all	DET
cana-5954	232	19	cases	case	NOUN
cana-5954	232	20	of	of	ADP
cana-5954	232	21	actual	actual	ADJ
cana-5954	232	22	pneumonia	pneumonia	NOUN
cana-5954	232	23	with	with	ADP
cana-5954	232	24	aucs	aucs	NOUN
cana-5954	232	25	of	of	ADP
cana-5954	232	26	1.00	1.00	NUM
cana-5954	232	27	;	;	PUNCT
cana-5954	232	28	this	this	DET
cana-5954	232	29	outstanding	outstanding	ADJ
cana-5954	232	30	performance	performance	NOUN
cana-5954	232	31	reflects	reflect	VERB
cana-5954	232	32	almost	almost	ADV
cana-5954	232	33	perfect	perfect	ADJ
cana-5954	232	34	classification	classification	NOUN
cana-5954	232	35	.	.	PUNCT
cana-5954	233	1	(	(	PUNCT
cana-5954	233	2	b	b	X
cana-5954	233	3	)	)	PUNCT
cana-5954	233	4	specificity	specificity	NOUN
cana-5954	233	5	:	:	PUNCT
cana-5954	233	6	this	this	DET
cana-5954	233	7	measure	measure	NOUN
cana-5954	233	8	indicates	indicate	VERB
cana-5954	233	9	the	the	DET
cana-5954	233	10	percentage	percentage	NOUN
cana-5954	233	11	of	of	ADP
cana-5954	233	12	actual	actual	ADJ
cana-5954	233	13	negative	negative	ADJ
cana-5954	233	14	cases	case	NOUN
cana-5954	233	15	that	that	SCONJ
cana-5954	233	16	the	the	DET
cana-5954	233	17	model	model	NOUN
cana-5954	233	18	correctly	correctly	ADV
cana-5954	233	19	labeled	label	VERB
cana-5954	233	20	:	:	PUNCT
cana-5954	233	21	100	100	NUM
cana-5954	233	22	%	%	NOUN
cana-5954	233	23	of	of	ADP
cana-5954	233	24	all	all	DET
cana-5954	233	25	non	non	ADJ
cana-5954	233	26	-	-	ADJ
cana-5954	233	27	covid-19	covid-19	ADJ
cana-5954	233	28	cases	case	NOUN
cana-5954	233	29	are	be	AUX
cana-5954	233	30	correctly	correctly	ADV
cana-5954	233	31	classified	classify	VERB
cana-5954	233	32	by	by	ADP
cana-5954	233	33	the	the	DET
cana-5954	233	34	model	model	NOUN
cana-5954	233	35	.	.	PUNCT
cana-5954	234	1	this	this	DET
cana-5954	234	2	model	model	NOUN
cana-5954	234	3	provides	provide	VERB
cana-5954	234	4	99	99	NUM
cana-5954	234	5	%	%	NOUN
cana-5954	234	6	of	of	ADP
cana-5954	234	7	the	the	DET
cana-5954	234	8	total	total	ADJ
cana-5954	234	9	cases	case	NOUN
cana-5954	234	10	not	not	PART
cana-5954	234	11	normal	normal	ADJ
cana-5954	234	12	are	be	AUX
cana-5954	234	13	appropriately	appropriately	ADV
cana-5954	234	14	detected	detect	VERB
cana-5954	234	15	by	by	ADP
cana-5954	234	16	the	the	DET
cana-5954	234	17	model	model	NOUN
cana-5954	234	18	.	.	PUNCT
cana-5954	235	1	the	the	DET
cana-5954	235	2	model	model	NOUN
cana-5954	235	3	correctly	correctly	ADV
cana-5954	235	4	identifies	identify	VERB
cana-5954	235	5	97	97	NUM
cana-5954	235	6	%	%	NOUN
cana-5954	235	7	of	of	ADP
cana-5954	235	8	all	all	DET
cana-5954	235	9	non	non	ADJ
cana-5954	235	10	-	-	ADJ
cana-5954	235	11	pneumonia	pneumonia	ADJ
cana-5954	235	12	diagnoses	diagnosis	NOUN
cana-5954	235	13	.	.	PUNCT
cana-5954	236	1	4.6	4.6	NUM
cana-5954	236	2	comparative	comparative	ADJ
cana-5954	236	3	result	result	NOUN
cana-5954	236	4	of	of	ADP
cana-5954	236	5	different	different	ADJ
cana-5954	236	6	models	model	NOUN
cana-5954	236	7	comparison	comparison	NOUN
cana-5954	236	8	of	of	ADP
cana-5954	236	9	various	various	ADJ
cana-5954	236	10	deep	deep	ADJ
cana-5954	236	11	learning	learning	NOUN
cana-5954	236	12	models	model	NOUN
cana-5954	236	13	in	in	ADP
cana-5954	236	14	detecting	detect	VERB
cana-5954	236	15	diseases	disease	NOUN
cana-5954	236	16	such	such	ADJ
cana-5954	236	17	as	as	ADP
cana-5954	236	18	covid-19	covid-19	PROPN
cana-5954	236	19	and	and	CCONJ
cana-5954	236	20	pneumonia	pneumonia	NOUN
cana-5954	236	21	is	be	AUX
cana-5954	236	22	presented	present	VERB
cana-5954	236	23	in	in	ADP
cana-5954	236	24	table	table	NOUN
cana-5954	236	25	6	6	NUM
cana-5954	236	26	.	.	PUNCT
cana-5954	237	1	accuracy	accuracy	NOUN
cana-5954	237	2	and	and	CCONJ
cana-5954	237	3	loss	loss	NOUN
cana-5954	237	4	are	be	AUX
cana-5954	237	5	employed	employ	VERB
cana-5954	237	6	to	to	PART
cana-5954	237	7	measure	measure	VERB
cana-5954	237	8	the	the	DET
cana-5954	237	9	performance	performance	NOUN
cana-5954	237	10	of	of	ADP
cana-5954	237	11	the	the	DET
cana-5954	237	12	models	model	NOUN
cana-5954	237	13	during	during	ADP
cana-5954	237	14	training	training	NOUN
cana-5954	237	15	and	and	CCONJ
cana-5954	237	16	validation	validation	NOUN
cana-5954	237	17	.	.	PUNCT
cana-5954	238	1	the	the	DET
cana-5954	238	2	suggested	suggested	ADJ
cana-5954	238	3	model	model	NOUN
cana-5954	238	4	,	,	PUNCT
cana-5954	238	5	resnet50	resnet50	NOUN
cana-5954	238	6	,	,	PUNCT
cana-5954	238	7	inception	inception	PROPN
cana-5954	238	8	v3	v3	PROPN
cana-5954	238	9	,	,	PUNCT
cana-5954	238	10	resnet-18	resnet-18	PROPN
cana-5954	238	11	,	,	PUNCT
cana-5954	238	12	resnet50	resnet50	NOUN
cana-5954	238	13	coupled	couple	VERB
cana-5954	238	14	with	with	ADP
cana-5954	238	15	svm	svm	PROPN
cana-5954	238	16	,	,	PUNCT
cana-5954	238	17	and	and	CCONJ
cana-5954	238	18	all	all	DET
cana-5954	238	19	other	other	ADJ
cana-5954	238	20	models	model	NOUN
cana-5954	238	21	were	be	AUX
cana-5954	238	22	run	run	VERB
cana-5954	238	23	for	for	ADP
cana-5954	238	24	50	50	NUM
cana-5954	238	25	epochs	epoch	NOUN
cana-5954	238	26	in	in	ADP
cana-5954	238	27	order	order	NOUN
cana-5954	238	28	to	to	PART
cana-5954	238	29	assess	assess	VERB
cana-5954	238	30	validation	validation	NOUN
cana-5954	238	31	metrics	metric	NOUN
cana-5954	238	32	and	and	CCONJ
cana-5954	238	33	accuracy	accuracy	NOUN
cana-5954	238	34	.	.	PUNCT
cana-5954	239	1	the	the	DET
cana-5954	239	2	proposed	propose	VERB
cana-5954	239	3	approach	approach	NOUN
cana-5954	239	4	performed	perform	VERB
cana-5954	239	5	better	well	ADV
cana-5954	239	6	than	than	ADP
cana-5954	239	7	the	the	DET
cana-5954	239	8	other	other	ADJ
cana-5954	239	9	models	model	NOUN
cana-5954	239	10	,	,	PUNCT
cana-5954	239	11	according	accord	VERB
cana-5954	239	12	to	to	ADP
cana-5954	239	13	the	the	DET
cana-5954	239	14	results	result	NOUN
cana-5954	239	15	shown	show	VERB
cana-5954	239	16	in	in	ADP
cana-5954	239	17	table	table	NOUN
cana-5954	239	18	6	6	NUM
cana-5954	239	19	.	.	PUNCT
cana-5954	239	20	table	table	NOUN
cana-5954	239	21	6	6	NUM
cana-5954	239	22	.	.	PUNCT
cana-5954	239	23	comparative	comparative	ADJ
cana-5954	239	24	result	result	NOUN
cana-5954	239	25	of	of	ADP
cana-5954	239	26	different	different	ADJ
cana-5954	239	27	models	model	NOUN
cana-5954	239	28	for	for	ADP
cana-5954	239	29	covid-19	covid-19	PROPN
cana-5954	239	30	and	and	CCONJ
cana-5954	239	31	pneumonia	pneumonia	NOUN
cana-5954	239	32	model	model	NOUN
cana-5954	239	33	accuracy	accuracy	NOUN
cana-5954	239	34	(	(	PUNCT
cana-5954	239	35	train	train	NOUN
cana-5954	239	36	)	)	PUNCT
cana-5954	239	37	loss	loss	NOUN
cana-5954	239	38	(	(	PUNCT
cana-5954	239	39	train	train	NOUN
cana-5954	239	40	)	)	PUNCT
cana-5954	239	41	accuracy	accuracy	NOUN
cana-5954	239	42	(	(	PUNCT
cana-5954	239	43	val	val	NOUN
cana-5954	239	44	)	)	PUNCT
cana-5954	239	45	loss	loss	NOUN
cana-5954	239	46	(	(	PUNCT
cana-5954	239	47	val	val	NOUN
cana-5954	239	48	)	)	PUNCT
cana-5954	239	49	resnet50	resnet50	NOUN
cana-5954	239	50	96.87	96.87	NUM
cana-5954	239	51	0.0310	0.0310	NUM
cana-5954	239	52	96.60	96.60	NUM
cana-5954	239	53	0.0511	0.0511	NUM
cana-5954	239	54	inception	inception	NOUN
cana-5954	239	55	v3	v3	PROPN
cana-5954	239	56	97.36	97.36	NUM
cana-5954	239	57	0.0412	0.0412	NUM
cana-5954	239	58	96.30	96.30	NUM
cana-5954	239	59	0.0701	0.0701	NUM
cana-5954	239	60	resnet-18	resnet-18	SYM
cana-5954	239	61	97.61	97.61	NUM
cana-5954	239	62	0.0311	0.0311	NUM
cana-5954	239	63	97.51	97.51	NUM
cana-5954	239	64	0.1254	0.1254	NUM
cana-5954	239	65	resnet50	resnet50	NOUN
cana-5954	239	66	&	&	CCONJ
cana-5954	239	67	svm	svm	VERB
cana-5954	239	68	97.80	97.80	NUM
cana-5954	239	69	0.0412	0.0412	NUM
cana-5954	239	70	96.98	96.98	NUM
cana-5954	239	71	0.0131	0.0131	NUM
cana-5954	239	72	proposed	propose	VERB
cana-5954	239	73	method	method	NOUN
cana-5954	239	74	98.10	98.10	NUM
cana-5954	239	75	0.0415	0.0415	NUM
cana-5954	239	76	97.91	97.91	NUM
cana-5954	239	77	0.1217	0.1217	NUM
cana-5954	239	78	4.7	4.7	NUM
cana-5954	239	79	comparative	comparative	ADJ
cana-5954	239	80	analysis	analysis	NOUN
cana-5954	239	81	the	the	DET
cana-5954	239	82	suggested	suggest	VERB
cana-5954	239	83	framework	framework	NOUN
cana-5954	239	84	is	be	AUX
cana-5954	239	85	evaluated	evaluate	VERB
cana-5954	239	86	against	against	ADP
cana-5954	239	87	other	other	ADJ
cana-5954	239	88	models	model	NOUN
cana-5954	239	89	.	.	PUNCT
cana-5954	240	1	a	a	DET
cana-5954	240	2	comparison	comparison	NOUN
cana-5954	240	3	of	of	ADP
cana-5954	240	4	the	the	DET
cana-5954	240	5	suggested	suggest	VERB
cana-5954	240	6	and	and	CCONJ
cana-5954	240	7	current	current	ADJ
cana-5954	240	8	methods	method	NOUN
cana-5954	240	9	is	be	AUX
cana-5954	240	10	given	give	VERB
cana-5954	240	11	in	in	ADP
cana-5954	240	12	table	table	NOUN
cana-5954	240	13	7	7	NUM
cana-5954	240	14	.	.	PUNCT
cana-5954	240	15	communications	communication	NOUN
cana-5954	240	16	on	on	ADP
cana-5954	240	17	applied	apply	VERB
cana-5954	240	18	nonlinear	nonlinear	ADJ
cana-5954	240	19	analysis	analysis	NOUN
cana-5954	240	20	issn	issn	NOUN
cana-5954	240	21	:	:	PUNCT
cana-5954	240	22	1074	1074	NUM
cana-5954	240	23	-	-	PUNCT
cana-5954	240	24	133x	133x	NUM
cana-5954	240	25	vol	vol	VERB
cana-5954	240	26	32	32	NUM
cana-5954	240	27	no	no	NOUN
cana-5954	240	28	.	.	PUNCT
cana-5954	241	1	10s	10	NOUN
cana-5954	241	2	(	(	PUNCT
cana-5954	241	3	2025	2025	NUM
cana-5954	241	4	)	)	PUNCT
cana-5954	241	5	3188	3188	NUM
cana-5954	241	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	241	7	table	table	NOUN
cana-5954	241	8	7	7	NUM
cana-5954	241	9	.	.	PUNCT
cana-5954	241	10	comparative	comparative	ADJ
cana-5954	241	11	study	study	NOUN
cana-5954	241	12	of	of	ADP
cana-5954	241	13	existing	exist	VERB
cana-5954	241	14	methods	method	NOUN
cana-5954	241	15	with	with	ADP
cana-5954	241	16	proposed	propose	VERB
cana-5954	241	17	method	method	NOUN
cana-5954	241	18	sl.no	sl.no	NOUN
cana-5954	241	19	author	author	NOUN
cana-5954	241	20	and	and	CCONJ
cana-5954	241	21	references	reference	NOUN
cana-5954	241	22	methodology	methodology	NOUN
cana-5954	241	23	overall	overall	ADJ
cana-5954	241	24	test	test	NOUN
cana-5954	241	25	accuracy	accuracy	NOUN
cana-5954	241	26	01	01	NUM
cana-5954	241	27	mohammad	mohammad	PROPN
cana-5954	241	28	farukh	farukh	PROPN
cana-5954	241	29	hashmi	hashmi	PROPN
cana-5954	241	30	et.al	et.al	PROPN
cana-5954	242	1	[	[	X
cana-5954	242	2	07	07	NUM
cana-5954	242	3	]	]	PUNCT
cana-5954	242	4	resnet50	resnet50	NOUN
cana-5954	242	5	98.14	98.14	NUM
cana-5954	242	6	02	02	NUM
cana-5954	242	7	avnish	avnish	ADJ
cana-5954	242	8	panwar	panwar	ADJ
cana-5954	242	9	et.al	et.al	PROPN
cana-5954	243	1	[	[	X
cana-5954	243	2	11	11	NUM
cana-5954	243	3	]	]	PUNCT
cana-5954	243	4	inception	inception	PROPN
cana-5954	243	5	v3	v3	PROPN
cana-5954	243	6	88.80	88.80	NUM
cana-5954	243	7	03	03	NUM
cana-5954	243	8	xuan	xuan	PROPN
cana-5954	243	9	cai	cai	PROPN
cana-5954	243	10	et.al	et.al	PROPN
cana-5954	244	1	[	[	X
cana-5954	244	2	29	29	NUM
cana-5954	244	3	]	]	PUNCT
cana-5954	244	4	resnet-18	resnet-18	PROPN
cana-5954	244	5	94.30	94.30	NUM
cana-5954	244	6	04	04	NUM
cana-5954	244	7	vamsidhar	vamsidhar	ADJ
cana-5954	244	8	enireddy	enireddy	ADJ
cana-5954	244	9	et.al	et.al	PROPN
cana-5954	244	10	[	[	X
cana-5954	244	11	30	30	NUM
cana-5954	244	12	]	]	PUNCT
cana-5954	244	13	resnet50	resnet50	NOUN
cana-5954	244	14	and	and	CCONJ
cana-5954	244	15	svm	svm	VERB
cana-5954	244	16	94.00	94.00	NUM
cana-5954	244	17	05	05	NUM
cana-5954	244	18	proposed	propose	VERB
cana-5954	244	19	method	method	NOUN
cana-5954	244	20	ccsafem	ccsafem	NOUN
cana-5954	244	21	98.70	98.70	NUM
cana-5954	244	22	5	5	NUM
cana-5954	244	23	.	.	PUNCT
cana-5954	244	24	conclusion	conclusion	NOUN
cana-5954	244	25	as	as	SCONJ
cana-5954	244	26	the	the	DET
cana-5954	244	27	results	result	NOUN
cana-5954	244	28	of	of	ADP
cana-5954	244	29	this	this	DET
cana-5954	244	30	research	research	NOUN
cana-5954	244	31	indicate	indicate	VERB
cana-5954	244	32	,	,	PUNCT
cana-5954	244	33	the	the	DET
cana-5954	244	34	resnet50	resnet50	NOUN
cana-5954	244	35	cnn	cnn	PROPN
cana-5954	244	36	model	model	NOUN
cana-5954	244	37	has	have	AUX
cana-5954	244	38	demonstrated	demonstrate	VERB
cana-5954	244	39	encouraging	encouraging	ADJ
cana-5954	244	40	performance	performance	NOUN
cana-5954	244	41	in	in	ADP
cana-5954	244	42	separating	separate	VERB
cana-5954	244	43	covid-19	covid-19	PROPN
cana-5954	244	44	and	and	CCONJ
cana-5954	244	45	pneumonia	pneumonia	NOUN
cana-5954	244	46	from	from	ADP
cana-5954	244	47	x	x	NOUN
cana-5954	244	48	-	-	NOUN
cana-5954	244	49	ray	ray	NOUN
cana-5954	244	50	images	image	NOUN
cana-5954	244	51	.	.	PUNCT
cana-5954	245	1	in	in	ADP
cana-5954	245	2	addition	addition	NOUN
cana-5954	245	3	to	to	ADP
cana-5954	245	4	predicting	predict	VERB
cana-5954	245	5	with	with	ADP
cana-5954	245	6	accuracy	accuracy	NOUN
cana-5954	245	7	the	the	DET
cana-5954	245	8	presence	presence	NOUN
cana-5954	245	9	or	or	CCONJ
cana-5954	245	10	absence	absence	NOUN
cana-5954	245	11	of	of	ADP
cana-5954	245	12	covid-19	covid-19	PROPN
cana-5954	245	13	and	and	CCONJ
cana-5954	245	14	pneumonia	pneumonia	NOUN
cana-5954	245	15	,	,	PUNCT
cana-5954	245	16	the	the	DET
cana-5954	245	17	cnn	cnn	PROPN
cana-5954	245	18	model	model	NOUN
cana-5954	245	19	developed	develop	VERB
cana-5954	245	20	in	in	ADP
cana-5954	245	21	this	this	DET
cana-5954	245	22	research	research	NOUN
cana-5954	245	23	extracts	extract	VERB
cana-5954	245	24	information	information	NOUN
cana-5954	245	25	from	from	ADP
cana-5954	245	26	x	x	ADJ
cana-5954	245	27	-	-	NOUN
cana-5954	245	28	ray	ray	NOUN
cana-5954	245	29	images	image	NOUN
cana-5954	245	30	effectively	effectively	ADV
cana-5954	245	31	.	.	PUNCT
cana-5954	246	1	the	the	DET
cana-5954	246	2	methods	method	NOUN
cana-5954	246	3	designed	design	VERB
cana-5954	246	4	in	in	ADP
cana-5954	246	5	this	this	DET
cana-5954	246	6	research	research	NOUN
cana-5954	246	7	enable	enable	VERB
cana-5954	246	8	more	more	ADV
cana-5954	246	9	accurate	accurate	ADJ
cana-5954	246	10	covid-19	covid-19	PROPN
cana-5954	246	11	and	and	CCONJ
cana-5954	246	12	pneumonia	pneumonia	NOUN
cana-5954	246	13	prediction	prediction	NOUN
cana-5954	246	14	,	,	PUNCT
cana-5954	246	15	with	with	ADP
cana-5954	246	16	a	a	DET
cana-5954	246	17	staggering	staggering	ADJ
cana-5954	246	18	98.70	98.70	NUM
cana-5954	246	19	%	%	NOUN
cana-5954	246	20	accuracy	accuracy	NOUN
cana-5954	246	21	rate	rate	NOUN
cana-5954	246	22	.	.	PUNCT
cana-5954	247	1	cnn	cnn	PROPN
cana-5954	247	2	models	model	NOUN
cana-5954	247	3	can	can	AUX
cana-5954	247	4	be	be	AUX
cana-5954	247	5	improved	improve	VERB
cana-5954	247	6	even	even	ADV
cana-5954	247	7	further	far	ADV
cana-5954	247	8	in	in	ADP
cana-5954	247	9	the	the	DET
cana-5954	247	10	future	future	NOUN
cana-5954	247	11	by	by	ADP
cana-5954	247	12	trying	try	VERB
cana-5954	247	13	out	out	ADP
cana-5954	247	14	various	various	ADJ
cana-5954	247	15	transfer	transfer	NOUN
cana-5954	247	16	learning	learning	NOUN
cana-5954	247	17	methods	method	NOUN
cana-5954	247	18	and	and	CCONJ
cana-5954	247	19	tuning	tune	VERB
cana-5954	247	20	hyperparameters	hyperparameter	NOUN
cana-5954	247	21	.	.	PUNCT
cana-5954	248	1	references	reference	NOUN
cana-5954	248	2	[	[	X
cana-5954	248	3	1	1	NUM
cana-5954	248	4	]	]	PUNCT
cana-5954	248	5	.	.	PUNCT
cana-5954	249	1	stephen	stephen	PROPN
cana-5954	249	2	,	,	PUNCT
cana-5954	249	3	o.	o.	PROPN
cana-5954	249	4	,	,	PUNCT
cana-5954	249	5	sain	sain	PROPN
cana-5954	249	6	,	,	PUNCT
cana-5954	249	7	m.	m.	NOUN
cana-5954	249	8	,	,	PUNCT
cana-5954	249	9	maduh	maduh	NOUN
cana-5954	249	10	,	,	PUNCT
cana-5954	249	11	u.	u.	PROPN
cana-5954	249	12	j.	j.	PROPN
cana-5954	249	13	,	,	PUNCT
cana-5954	249	14	&	&	CCONJ
cana-5954	249	15	jeong	jeong	PROPN
cana-5954	249	16	,	,	PUNCT
cana-5954	249	17	d.	d.	PROPN
cana-5954	249	18	u	u	PROPN
cana-5954	249	19	,	,	PUNCT
cana-5954	249	20	“	"	PUNCT
cana-5954	249	21	an	an	DET
cana-5954	249	22	efficient	efficient	ADJ
cana-5954	249	23	deep	deep	ADJ
cana-5954	249	24	learning	learning	NOUN
cana-5954	249	25	approaches	approach	NOUN
cana-5954	249	26	to	to	ADP
cana-5954	249	27	pneumonia	pneumonia	NOUN
cana-5954	249	28	classification	classification	NOUN
cana-5954	249	29	in	in	ADP
cana-5954	249	30	healthcare	healthcare	PROPN
cana-5954	249	31	”	"	PUNCT
cana-5954	249	32	,	,	PUNCT
cana-5954	249	33	journal	journal	NOUN
cana-5954	249	34	of	of	ADP
cana-5954	249	35	healthcare	healthcare	PROPN
cana-5954	249	36	engineering	engineering	PROPN
cana-5954	249	37	,	,	PUNCT
cana-5954	249	38	(	(	PUNCT
cana-5954	249	39	2019	2019	NUM
cana-5954	249	40	)	)	PUNCT
cana-5954	249	41	.	.	PUNCT
cana-5954	250	1	[	[	X
cana-5954	250	2	2	2	NUM
cana-5954	250	3	]	]	PUNCT
cana-5954	250	4	.	.	PUNCT
cana-5954	251	1	shuai	shuai	PROPN
cana-5954	251	2	wang	wang	PROPN
cana-5954	251	3	,	,	PUNCT
cana-5954	251	4	bo	bo	PROPN
cana-5954	251	5	kang	kang	PROPN
cana-5954	251	6	,	,	PUNCT
cana-5954	251	7	jinlu	jinlu	PROPN
cana-5954	251	8	ma	ma	PROPN
cana-5954	251	9	,	,	PUNCT
cana-5954	251	10	xianjun	xianjun	PROPN
cana-5954	251	11	zeng	zeng	PROPN
cana-5954	251	12	,	,	PUNCT
cana-5954	251	13	mingming	mingming	PROPN
cana-5954	251	14	xiao	xiao	PROPN
cana-5954	251	15	,	,	PUNCT
cana-5954	251	16	jia	jia	PROPN
cana-5954	251	17	guo	guo	PROPN
cana-5954	251	18	,	,	PUNCT
cana-5954	251	19	mengjiao	mengjiao	NOUN
cana-5954	251	20	cai	cai	PROPN
cana-5954	251	21	et	et	PROPN
cana-5954	251	22	al	al	PROPN
cana-5954	251	23	,	,	PUNCT
cana-5954	251	24	“	"	PUNCT
cana-5954	251	25	a	a	DET
cana-5954	251	26	deep	deep	ADJ
cana-5954	251	27	learning	learning	NOUN
cana-5954	251	28	algorithm	algorithm	NOUN
cana-5954	251	29	using	use	VERB
cana-5954	251	30	ct	ct	NUM
cana-5954	251	31	images	image	NOUN
cana-5954	251	32	to	to	PART
cana-5954	251	33	screen	screen	VERB
cana-5954	251	34	for	for	ADP
cana-5954	251	35	corona	corona	NOUN
cana-5954	251	36	virus	virus	NOUN
cana-5954	251	37	disease	disease	NOUN
cana-5954	251	38	(	(	PUNCT
cana-5954	251	39	covid-19	covid-19	PROPN
cana-5954	251	40	)	)	PUNCT
cana-5954	251	41	”	"	PUNCT
cana-5954	251	42	,	,	PUNCT
cana-5954	251	43	medrxiv	medrxiv	X
cana-5954	251	44	(	(	PUNCT
cana-5954	251	45	2020	2020	NUM
cana-5954	251	46	)	)	PUNCT
cana-5954	251	47	.	.	PUNCT
cana-5954	252	1	[	[	X
cana-5954	252	2	3].xiaowei	3].xiaowei	NUM
cana-5954	252	3	xu	xu	PROPN
cana-5954	252	4	,	,	PUNCT
cana-5954	252	5	xiangao	xiangao	PROPN
cana-5954	252	6	jiang	jiang	PROPN
cana-5954	252	7	,	,	PUNCT
cana-5954	252	8	chunlian	chunlian	PROPN
cana-5954	252	9	ma	ma	PROPN
cana-5954	252	10	,	,	PUNCT
cana-5954	252	11	peng	peng	PROPN
cana-5954	252	12	du	du	PROPN
cana-5954	252	13	,	,	PUNCT
cana-5954	252	14	xukun	xukun	PROPN
cana-5954	252	15	li	li	PROPN
cana-5954	252	16	,	,	PUNCT
cana-5954	252	17	shuangzhi	shuangzhi	PROPN
cana-5954	252	18	lv	lv	PROPN
cana-5954	252	19	,	,	PUNCT
cana-5954	252	20	liang	liang	PROPN
cana-5954	252	21	yu	yu	PROPN
cana-5954	252	22	et	et	PROPN
cana-5954	252	23	al	al	PROPN
cana-5954	252	24	,	,	PUNCT
cana-5954	252	25	“	"	PUNCT
cana-5954	252	26	a	a	DET
cana-5954	252	27	deep	deep	ADJ
cana-5954	252	28	learning	learning	NOUN
cana-5954	252	29	system	system	NOUN
cana-5954	252	30	to	to	PART
cana-5954	252	31	screen	screen	VERB
cana-5954	252	32	novel	novel	ADJ
cana-5954	252	33	coronavirus	coronavirus	NOUN
cana-5954	252	34	disease	disease	NOUN
cana-5954	252	35	2019	2019	NUM
cana-5954	252	36	pneumonia	pneumonia	NOUN
cana-5954	252	37	”	"	PUNCT
cana-5954	252	38	,	,	PUNCT
cana-5954	252	39	engineering	engineer	VERB
cana-5954	252	40	6	6	NUM
cana-5954	252	41	,	,	PUNCT
cana-5954	252	42	no	no	INTJ
cana-5954	252	43	.	.	NOUN
cana-5954	252	44	10	10	NUM
cana-5954	252	45	(	(	PUNCT
cana-5954	252	46	2020	2020	NUM
cana-5954	252	47	)	)	PUNCT
cana-5954	252	48	.	.	PUNCT
cana-5954	253	1	[	[	X
cana-5954	253	2	4	4	NUM
cana-5954	253	3	]	]	PUNCT
cana-5954	253	4	.	.	PUNCT
cana-5954	254	1	netzahualcoyotl	netzahualcoyotl	PROPN
cana-5954	254	2	hernandez‑cruz	hernandez‑cruz	PROPN
cana-5954	254	3	,	,	PUNCT
cana-5954	254	4	david	david	PROPN
cana-5954	254	5	cato	cato	PROPN
cana-5954	254	6	,	,	PUNCT
cana-5954	254	7	jesus	jesus	PROPN
cana-5954	254	8	favela	favela	PROPN
cana-5954	254	9	,	,	PUNCT
cana-5954	254	10	“	"	PUNCT
cana-5954	254	11	neural	neural	ADJ
cana-5954	254	12	style	style	NOUN
cana-5954	254	13	transfer	transfer	NOUN
cana-5954	254	14	as	as	ADP
cana-5954	254	15	data	datum	NOUN
cana-5954	254	16	augmentation	augmentation	NOUN
cana-5954	254	17	for	for	ADP
cana-5954	254	18	improving	improve	VERB
cana-5954	254	19	covid‑19	covid‑19	PROPN
cana-5954	254	20	diagnosis	diagnosis	NOUN
cana-5954	254	21	classification	classification	NOUN
cana-5954	254	22	”	"	PUNCT
cana-5954	254	23	,	,	PUNCT
cana-5954	254	24	sn	sn	PROPN
cana-5954	254	25	computer	computer	NOUN
cana-5954	254	26	science	science	NOUN
cana-5954	254	27	(	(	PUNCT
cana-5954	254	28	2021	2021	NUM
cana-5954	254	29	)	)	PUNCT
cana-5954	254	30	.	.	PUNCT
cana-5954	255	1	https://doi.org/10.1007/s42979-021-00795-2	https://doi.org/10.1007/s42979-021-00795-2	NUM
cana-5954	256	1	[	[	X
cana-5954	256	2	5	5	NUM
cana-5954	256	3	]	]	PUNCT
cana-5954	256	4	.	.	PUNCT
cana-5954	257	1	shah	shah	PROPN
cana-5954	257	2	siddiqui	siddiqui	PROPN
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cana-5954	257	4	al	al	PROPN
cana-5954	257	5	.	.	PROPN
cana-5954	257	6	:	:	PUNCT
cana-5954	258	1	deep	deep	ADJ
cana-5954	258	2	learning	learning	NOUN
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cana-5954	258	4	for	for	ADP
cana-5954	258	5	the	the	DET
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cana-5954	258	7	and	and	CCONJ
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cana-5954	258	9	of	of	ADP
cana-5954	258	10	covid‑19	covid‑19	PROPN
cana-5954	258	11	,	,	PUNCT
cana-5954	258	12	“	"	PUNCT
cana-5954	258	13	a	a	DET
cana-5954	258	14	systematic	systematic	ADJ
cana-5954	258	15	review	review	NOUN
cana-5954	258	16	”	"	PUNCT
cana-5954	258	17	,	,	PUNCT
cana-5954	258	18	sn	sn	PROPN
cana-5954	258	19	computer	computer	NOUN
cana-5954	258	20	science	science	NOUN
cana-5954	258	21	(	(	PUNCT
cana-5954	258	22	2022	2022	NUM
cana-5954	258	23	)	)	PUNCT
cana-5954	258	24	.	.	PUNCT
cana-5954	259	1	https://doi.org/10.1007/s42979-02201326-3	https://doi.org/10.1007/s42979-02201326-3	PROPN
cana-5954	260	1	[	[	X
cana-5954	260	2	6	6	NUM
cana-5954	260	3	]	]	PUNCT
cana-5954	260	4	.	.	PUNCT
cana-5954	261	1	rajit	rajit	PROPN
cana-5954	261	2	nair	nair	PROPN
cana-5954	261	3	et	et	PROPN
cana-5954	261	4	al	al	PROPN
cana-5954	261	5	,	,	PUNCT
cana-5954	261	6	“	"	PUNCT
cana-5954	261	7	deep	deep	ADJ
cana-5954	261	8	learning	learning	NOUN
cana-5954	261	9	-	-	PUNCT
cana-5954	261	10	based	base	VERB
cana-5954	261	11	covid-19	covid-19	PROPN
cana-5954	261	12	detection	detection	NOUN
cana-5954	261	13	system	system	NOUN
cana-5954	261	14	using	use	VERB
cana-5954	261	15	pulmonary	pulmonary	ADJ
cana-5954	261	16	ct	ct	PROPN
cana-5954	261	17	scans	scan	NOUN
cana-5954	261	18	”	"	PUNCT
cana-5954	261	19	,	,	PUNCT
cana-5954	261	20	turkish	turkish	ADJ
cana-5954	261	21	journal	journal	NOUN
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cana-5954	261	23	electrical	electrical	ADJ
cana-5954	261	24	engineering	engineering	NOUN
cana-5954	261	25	and	and	CCONJ
cana-5954	261	26	computer	computer	NOUN
cana-5954	261	27	sciences	science	NOUN
cana-5954	261	28	:	:	PUNCT
cana-5954	261	29	vol	vol	NOUN
cana-5954	261	30	.	.	PROPN
cana-5954	262	1	29	29	NUM
cana-5954	262	2	:	:	PUNCT
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cana-5954	262	4	.	.	NOUN
cana-5954	262	5	8	8	NUM
cana-5954	262	6	,	,	PUNCT
cana-5954	262	7	article	article	NOUN
cana-5954	262	8	9	9	NUM
cana-5954	262	9	,	,	PUNCT
cana-5954	262	10	(	(	PUNCT
cana-5954	262	11	2021	2021	NUM
cana-5954	262	12	)	)	PUNCT
cana-5954	262	13	.	.	PUNCT
cana-5954	263	1	https://doi.org/10.3906/elk-2105-243	https://doi.org/10.3906/elk-2105-243	NOUN
cana-5954	263	2	communications	communication	NOUN
cana-5954	263	3	on	on	ADP
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cana-5954	263	5	nonlinear	nonlinear	ADJ
cana-5954	263	6	analysis	analysis	NOUN
cana-5954	263	7	issn	issn	NOUN
cana-5954	263	8	:	:	PUNCT
cana-5954	263	9	1074	1074	NUM
cana-5954	263	10	-	-	PUNCT
cana-5954	263	11	133x	133x	NUM
cana-5954	263	12	vol	vol	VERB
cana-5954	263	13	32	32	NUM
cana-5954	263	14	no	no	NOUN
cana-5954	263	15	.	.	PUNCT
cana-5954	264	1	10s	10	NOUN
cana-5954	264	2	(	(	PUNCT
cana-5954	264	3	2025	2025	NUM
cana-5954	264	4	)	)	PUNCT
cana-5954	264	5	3189	3189	NUM
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cana-5954	265	1	[	[	X
cana-5954	265	2	7	7	NUM
cana-5954	265	3	]	]	PUNCT
cana-5954	265	4	.	.	PUNCT
cana-5954	266	1	mohammad	mohammad	PROPN
cana-5954	266	2	farukh	farukh	PROPN
cana-5954	266	3	hashmi	hashmi	PROPN
cana-5954	266	4	et	et	PROPN
cana-5954	266	5	al	al	PROPN
cana-5954	266	6	,	,	PUNCT
cana-5954	266	7	“	"	PUNCT
cana-5954	266	8	pneumonia	pneumonia	NOUN
cana-5954	266	9	detection	detection	NOUN
cana-5954	266	10	in	in	ADP
cana-5954	266	11	chest	chest	NOUN
cana-5954	266	12	x	x	NOUN
cana-5954	266	13	-	-	NOUN
cana-5954	266	14	ray	ray	NOUN
cana-5954	266	15	images	image	NOUN
cana-5954	266	16	using	use	VERB
cana-5954	266	17	compound	compound	NOUN
cana-5954	266	18	scaled	scale	VERB
cana-5954	266	19	deep	deep	ADJ
cana-5954	266	20	learning	learning	NOUN
cana-5954	266	21	model	model	NOUN
cana-5954	266	22	”	"	PUNCT
cana-5954	266	23	,	,	PUNCT
cana-5954	266	24	automatika	automatika	NOUN
cana-5954	266	25	,	,	PUNCT
cana-5954	266	26	62:3	62:3	NOUN
cana-5954	266	27	-	-	SYM
cana-5954	266	28	4	4	NUM
cana-5954	266	29	,	,	PUNCT
cana-5954	266	30	397	397	NUM
cana-5954	266	31	-	-	SYM
cana-5954	266	32	406	406	NUM
cana-5954	266	33	,	,	PUNCT
cana-5954	266	34	(	(	PUNCT
cana-5954	266	35	2021	2021	NUM
cana-5954	266	36	)	)	PUNCT
cana-5954	266	37	.	.	PUNCT
cana-5954	267	1	https://doi.org/	https://doi.org/	VERB
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cana-5954	268	1	[	[	X
cana-5954	268	2	8	8	NUM
cana-5954	268	3	]	]	PUNCT
cana-5954	268	4	.	.	PUNCT
cana-5954	269	1	zhenjia	zhenjia	PROPN
cana-5954	269	2	yue	yue	PROPN
cana-5954	269	3	,	,	PUNCT
cana-5954	269	4	“	"	PUNCT
cana-5954	269	5	comparison	comparison	NOUN
cana-5954	269	6	and	and	CCONJ
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cana-5954	269	8	of	of	ADP
cana-5954	269	9	deep	deep	ADJ
cana-5954	269	10	learning	learning	NOUN
cana-5954	269	11	models	model	NOUN
cana-5954	269	12	for	for	ADP
cana-5954	269	13	the	the	DET
cana-5954	269	14	diagnosis	diagnosis	NOUN
cana-5954	269	15	of	of	ADP
cana-5954	269	16	pneumonia	pneumonia	NOUN
cana-5954	269	17	”	"	PUNCT
cana-5954	269	18	,	,	PUNCT
cana-5954	269	19	hindawi	hindawi	ADJ
cana-5954	269	20	computational	computational	ADJ
cana-5954	269	21	intelligence	intelligence	NOUN
cana-5954	269	22	and	and	CCONJ
cana-5954	269	23	neuroscience	neuroscience	NOUN
cana-5954	269	24	volume	volume	NOUN
cana-5954	269	25	,	,	PUNCT
cana-5954	269	26	(	(	PUNCT
cana-5954	269	27	2020	2020	NUM
cana-5954	269	28	)	)	PUNCT
cana-5954	269	29	.	.	PUNCT
cana-5954	270	1	https://doi.org/10.1155/2020/8876798	https://doi.org/10.1155/2020/8876798	PROPN
cana-5954	271	1	[	[	X
cana-5954	271	2	9	9	NUM
cana-5954	271	3	]	]	PUNCT
cana-5954	271	4	.	.	PUNCT
cana-5954	272	1	aakash	aakash	PROPN
cana-5954	272	2	shah	shah	PROPN
cana-5954	272	3	,	,	PUNCT
cana-5954	272	4	manan	manan	PROPN
cana-5954	272	5	shah	shah	NOUN
cana-5954	272	6	,	,	PUNCT
cana-5954	272	7	“	"	PUNCT
cana-5954	272	8	advancement	advancement	NOUN
cana-5954	272	9	of	of	ADP
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cana-5954	272	11	learning	learning	NOUN
cana-5954	272	12	in	in	ADP
cana-5954	272	13	pneumonia	pneumonia	NOUN
cana-5954	272	14	/	/	SYM
cana-5954	272	15	covid19	covid19	NOUN
cana-5954	272	16	classification	classification	NOUN
cana-5954	272	17	and	and	CCONJ
cana-5954	272	18	localization	localization	NOUN
cana-5954	272	19	:	:	PUNCT
cana-5954	272	20	a	a	DET
cana-5954	272	21	systematic	systematic	ADJ
cana-5954	272	22	review	review	NOUN
cana-5954	272	23	with	with	ADP
cana-5954	272	24	qualitative	qualitative	ADJ
cana-5954	272	25	and	and	CCONJ
cana-5954	272	26	quantitative	quantitative	ADJ
cana-5954	272	27	analysis	analysis	NOUN
cana-5954	272	28	”	"	PUNCT
cana-5954	272	29	,	,	PUNCT
cana-5954	272	30	chronic	chronic	ADJ
cana-5954	272	31	diseases	disease	NOUN
cana-5954	272	32	and	and	CCONJ
cana-5954	272	33	translational	translational	ADJ
cana-5954	272	34	medicine	medicine	NOUN
cana-5954	272	35	,	,	PUNCT
cana-5954	272	36	(	(	PUNCT
cana-5954	272	37	2022	2022	NUM
cana-5954	272	38	)	)	PUNCT
cana-5954	272	39	.	.	PUNCT
cana-5954	273	1	https://doi.org/	https://doi.org/	VERB
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cana-5954	273	3	/	/	SYM
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cana-5954	274	1	[	[	X
cana-5954	274	2	10	10	NUM
cana-5954	274	3	]	]	PUNCT
cana-5954	274	4	.	.	PUNCT
cana-5954	275	1	puneet	puneet	PROPN
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cana-5954	275	3	,	,	PUNCT
cana-5954	275	4	“	"	PUNCT
cana-5954	275	5	pneumonia	pneumonia	NOUN
cana-5954	275	6	detection	detection	NOUN
cana-5954	275	7	using	use	VERB
cana-5954	275	8	convolutional	convolutional	ADJ
cana-5954	275	9	neural	neural	ADJ
cana-5954	275	10	networks	network	NOUN
cana-5954	275	11	”	"	PUNCT
cana-5954	275	12	,	,	PUNCT
cana-5954	275	13	international	international	ADJ
cana-5954	275	14	journal	journal	NOUN
cana-5954	275	15	for	for	ADP
cana-5954	275	16	modern	modern	ADJ
cana-5954	275	17	trends	trend	NOUN
cana-5954	275	18	in	in	ADP
cana-5954	275	19	science	science	NOUN
cana-5954	275	20	and	and	CCONJ
cana-5954	275	21	technology	technology	NOUN
cana-5954	275	22	,	,	PUNCT
cana-5954	275	23	(	(	PUNCT
cana-5954	275	24	2021	2021	NUM
cana-5954	275	25	)	)	PUNCT
cana-5954	275	26	.	.	PUNCT
cana-5954	276	1	https://doi.org/10.46501/ijmtst070117	https://doi.org/10.46501/ijmtst070117	PROPN
cana-5954	277	1	[	[	X
cana-5954	277	2	11	11	NUM
cana-5954	277	3	]	]	PUNCT
cana-5954	277	4	.	.	PUNCT
cana-5954	278	1	avnish	avnish	PROPN
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cana-5954	278	3	et	et	PROPN
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cana-5954	278	5	,	,	PUNCT
cana-5954	278	6	“	"	PUNCT
cana-5954	278	7	deep	deep	ADJ
cana-5954	278	8	learning	learning	NOUN
cana-5954	278	9	techniques	technique	NOUN
cana-5954	278	10	for	for	ADP
cana-5954	278	11	the	the	DET
cana-5954	278	12	real	real	ADJ
cana-5954	278	13	time	time	NOUN
cana-5954	278	14	detection	detection	NOUN
cana-5954	278	15	of	of	ADP
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cana-5954	278	17	and	and	CCONJ
cana-5954	278	18	pneumonia	pneumonia	NOUN
cana-5954	278	19	using	use	VERB
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cana-5954	278	22	”	"	PUNCT
cana-5954	278	23	,	,	PUNCT
cana-5954	278	24	ieee	ieee	NOUN
cana-5954	278	25	,	,	PUNCT
cana-5954	278	26	(	(	PUNCT
cana-5954	278	27	2021	2021	NUM
cana-5954	278	28	)	)	PUNCT
cana-5954	278	29	.	.	PUNCT
cana-5954	279	1	https://doi.org/	https://doi.org/	VERB
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cana-5954	279	3	/	/	SYM
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cana-5954	280	2	12	12	NUM
cana-5954	280	3	]	]	PUNCT
cana-5954	280	4	.	.	PUNCT
cana-5954	281	1	waleed	waleed	PROPN
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cana-5954	281	5	“	"	PUNCT
cana-5954	281	6	a	a	DET
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cana-5954	281	16	"	"	PUNCT
cana-5954	281	17	,	,	PUNCT
cana-5954	281	18	mdpi	mdpi	PROPN
cana-5954	281	19	,	,	PUNCT
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cana-5954	281	21	,	,	PUNCT
cana-5954	281	22	(	(	PUNCT
cana-5954	281	23	2022	2022	NUM
cana-5954	281	24	)	)	PUNCT
cana-5954	281	25	.	.	PUNCT
cana-5954	282	1	https://doi.org/10.3390/su141912222	https://doi.org/10.3390/su141912222	PUNCT
cana-5954	283	1	[	[	X
cana-5954	283	2	13	13	NUM
cana-5954	283	3	]	]	PUNCT
cana-5954	283	4	.	.	PUNCT
cana-5954	283	5	j.	j.	PROPN
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cana-5954	283	8	.	.	PUNCT
cana-5954	284	1	“	"	PUNCT
cana-5954	284	2	covid	covid	ADJ
cana-5954	284	3	-	-	PUNCT
cana-5954	284	4	chestxray	chestxray	ADJ
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cana-5954	284	7	”	"	PUNCT
cana-5954	284	8	,	,	PUNCT
cana-5954	284	9	(	(	PUNCT
cana-5954	284	10	2020	2020	NUM
cana-5954	284	11	)	)	PUNCT
cana-5954	284	12	.	.	PUNCT
cana-5954	285	1	https://github.com/ieee8023/covid-chestxray-dataset	https://github.com/ieee8023/covid-chestxray-dataset	PUNCT
cana-5954	286	1	[	[	X
cana-5954	286	2	14	14	NUM
cana-5954	286	3	]	]	PUNCT
cana-5954	286	4	.	.	PUNCT
cana-5954	287	1	d.	d.	PROPN
cana-5954	287	2	demner	demner	PROPN
cana-5954	287	3	-	-	PUNCT
cana-5954	287	4	fushman	fushman	PROPN
cana-5954	287	5	,	,	PUNCT
cana-5954	287	6	m.d	m.d	PROPN
cana-5954	287	7	.	.	PROPN
cana-5954	287	8	kohli	kohli	PROPN
cana-5954	287	9	,	,	PUNCT
cana-5954	287	10	m.b	m.b	PROPN
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cana-5954	287	13	,	,	PUNCT
cana-5954	287	14	s.e	s.e	PROPN
cana-5954	287	15	.	.	PROPN
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cana-5954	287	17	,	,	PUNCT
cana-5954	287	18	l.	l.	PROPN
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cana-5954	287	21	s.	s.	PROPN
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cana-5954	287	23	,	,	PUNCT
cana-5954	287	24	g.r	g.r	PROPN
cana-5954	287	25	.	.	PROPN
cana-5954	287	26	thoma	thoma	PROPN
cana-5954	287	27	,	,	PUNCT
cana-5954	287	28	and	and	CCONJ
cana-5954	287	29	c.j	c.j	PROPN
cana-5954	287	30	.	.	PROPN
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cana-5954	287	33	“	"	PUNCT
cana-5954	287	34	preparing	prepare	VERB
cana-5954	287	35	a	a	DET
cana-5954	287	36	collection	collection	NOUN
cana-5954	287	37	of	of	ADP
cana-5954	287	38	radiology	radiology	NOUN
cana-5954	287	39	examinations	examination	NOUN
cana-5954	287	40	for	for	ADP
cana-5954	287	41	distribution	distribution	NOUN
cana-5954	287	42	and	and	CCONJ
cana-5954	287	43	retrieval	retrieval	NOUN
cana-5954	287	44	”	"	PUNCT
cana-5954	287	45	,	,	PUNCT
cana-5954	287	46	j	j	PROPN
cana-5954	287	47	am	be	AUX
cana-5954	287	48	med	me	VERB
cana-5954	287	49	inform	inform	NOUN
cana-5954	287	50	assoc	assoc	NOUN
cana-5954	287	51	,	,	PUNCT
cana-5954	287	52	(	(	PUNCT
cana-5954	287	53	2016	2016	NUM
cana-5954	287	54	)	)	PUNCT
cana-5954	287	55	.	.	PUNCT
cana-5954	288	1	https://doi	https://doi	ADV
cana-5954	288	2	:	:	PUNCT
cana-5954	288	3	10.1093	10.1093	NUM
cana-5954	288	4	/	/	SYM
cana-5954	288	5	jamia	jamia	PROPN
cana-5954	288	6	/	/	SYM
cana-5954	288	7	ocv080	ocv080	PROPN
cana-5954	288	8	.	.	PUNCT
cana-5954	289	1	epub	epub	PROPN
cana-5954	289	2	2015	2015	NUM
cana-5954	289	3	jul	jul	NOUN
cana-5954	289	4	1	1	NUM
cana-5954	290	1	[	[	X
cana-5954	290	2	15	15	NUM
cana-5954	290	3	]	]	PUNCT
cana-5954	290	4	.	.	PUNCT
cana-5954	290	5	alqudah	alqudah	PROPN
cana-5954	290	6	,	,	PUNCT
cana-5954	290	7	ali	ali	PROPN
cana-5954	290	8	mohammad	mohammad	PROPN
cana-5954	290	9	;	;	PUNCT
cana-5954	290	10	qazan	qazan	X
cana-5954	290	11	,	,	PUNCT
cana-5954	290	12	shoroq	shoroq	VERB
cana-5954	290	13	,	,	PUNCT
cana-5954	290	14	“	"	PUNCT
cana-5954	290	15	augmented	augment	VERB
cana-5954	290	16	covid-19	covid-19	PROPN
cana-5954	290	17	x	x	PROPN
cana-5954	290	18	-	-	NOUN
cana-5954	290	19	ray	ray	NOUN
cana-5954	290	20	images	image	NOUN
cana-5954	290	21	dataset	dataset	NOUN
cana-5954	290	22	”	"	PUNCT
cana-5954	290	23	,	,	PUNCT
cana-5954	290	24	mendeley	mendeley	PROPN
cana-5954	290	25	data	data	PROPN
cana-5954	290	26	,	,	PUNCT
cana-5954	290	27	(	(	PUNCT
cana-5954	290	28	2020	2020	NUM
cana-5954	290	29	)	)	PUNCT
cana-5954	290	30	.	.	PUNCT
cana-5954	291	1	http://dx.doi.org/10.17632/2fxz4px6d8.4	http://dx.doi.org/10.17632/2fxz4px6d8.4	PART
cana-5954	292	1	[	[	X
cana-5954	292	2	16	16	NUM
cana-5954	292	3	]	]	PUNCT
cana-5954	292	4	.	.	PUNCT
cana-5954	293	1	wu	wu	PROPN
cana-5954	293	2	y	y	PROPN
cana-5954	293	3	,	,	PUNCT
cana-5954	293	4	he	he	PRON
cana-5954	293	5	k	k	NOUN
cana-5954	293	6	,	,	PUNCT
cana-5954	293	7	“	"	PUNCT
cana-5954	293	8	group	group	NOUN
cana-5954	293	9	normalization	normalization	NOUN
cana-5954	293	10	”	"	PUNCT
cana-5954	293	11	,	,	PUNCT
cana-5954	293	12	proceedings	proceeding	NOUN
cana-5954	293	13	of	of	ADP
cana-5954	293	14	the	the	DET
cana-5954	293	15	european	european	PROPN
cana-5954	293	16	conference	conference	PROPN
cana-5954	293	17	on	on	ADP
cana-5954	293	18	computer	computer	NOUN
cana-5954	293	19	vision	vision	NOUN
cana-5954	293	20	(	(	PUNCT
cana-5954	293	21	eccv	eccv	ADV
cana-5954	293	22	)	)	PUNCT
cana-5954	293	23	,	,	PUNCT
cana-5954	293	24	(	(	PUNCT
cana-5954	293	25	2018	2018	NUM
cana-5954	293	26	)	)	PUNCT
cana-5954	293	27	.	.	PUNCT
cana-5954	294	1	[	[	X
cana-5954	294	2	17	17	NUM
cana-5954	294	3	]	]	PUNCT
cana-5954	294	4	.	.	PUNCT
cana-5954	295	1	krizhevsky	krizhevsky	PROPN
cana-5954	295	2	a	a	PROPN
cana-5954	295	3	,	,	PUNCT
cana-5954	295	4	sutskever	sutskever	VERB
cana-5954	295	5	i	i	PRON
cana-5954	295	6	,	,	PUNCT
cana-5954	295	7	hinton	hinton	PROPN
cana-5954	295	8	g	g	PROPN
cana-5954	295	9	e	e	PROPN
cana-5954	295	10	,	,	PUNCT
cana-5954	295	11	“	"	PUNCT
cana-5954	295	12	imagenet	imagenet	NOUN
cana-5954	295	13	classification	classification	NOUN
cana-5954	295	14	with	with	ADP
cana-5954	295	15	deep	deep	ADJ
cana-5954	295	16	convolutional	convolutional	ADJ
cana-5954	295	17	neural	neural	ADJ
cana-5954	295	18	networks	network	NOUN
cana-5954	295	19	”	"	PUNCT
cana-5954	295	20	,	,	PUNCT
cana-5954	295	21	advances	advance	NOUN
cana-5954	295	22	in	in	ADP
cana-5954	295	23	neural	neural	ADJ
cana-5954	295	24	information	information	NOUN
cana-5954	295	25	processing	processing	NOUN
cana-5954	295	26	systems	system	NOUN
cana-5954	295	27	,	,	PUNCT
cana-5954	295	28	2012	2012	NUM
cana-5954	295	29	.	.	PUNCT
cana-5954	296	1	[	[	X
cana-5954	296	2	18	18	NUM
cana-5954	296	3	]	]	PUNCT
cana-5954	296	4	.	.	PUNCT
cana-5954	297	1	zhang	zhang	PROPN
cana-5954	297	2	x	x	PROPN
cana-5954	297	3	,	,	PUNCT
cana-5954	297	4	zhou	zhou	PROPN
cana-5954	297	5	x	x	PROPN
cana-5954	297	6	,	,	PUNCT
cana-5954	297	7	lin	lin	PROPN
cana-5954	297	8	m	m	PROPN
cana-5954	297	9	,	,	PUNCT
cana-5954	297	10	et	et	PROPN
cana-5954	297	11	al	al	PROPN
cana-5954	297	12	,	,	PUNCT
cana-5954	297	13	“	"	PUNCT
cana-5954	297	14	shufflenet	shufflenet	NOUN
cana-5954	297	15	:	:	PUNCT
cana-5954	297	16	an	an	DET
cana-5954	297	17	extremely	extremely	ADV
cana-5954	297	18	efficient	efficient	ADJ
cana-5954	297	19	convolutional	convolutional	ADJ
cana-5954	297	20	neural	neural	ADJ
cana-5954	297	21	network	network	NOUN
cana-5954	297	22	for	for	ADP
cana-5954	297	23	mobile	mobile	ADJ
cana-5954	297	24	devices	device	NOUN
cana-5954	297	25	”	"	PUNCT
cana-5954	297	26	,	,	PUNCT
cana-5954	297	27	proceedings	proceeding	NOUN
cana-5954	297	28	of	of	ADP
cana-5954	297	29	the	the	DET
cana-5954	297	30	ieee	ieee	NOUN
cana-5954	297	31	conference	conference	NOUN
cana-5954	297	32	on	on	ADP
cana-5954	297	33	computer	computer	NOUN
cana-5954	297	34	vision	vision	NOUN
cana-5954	297	35	and	and	CCONJ
cana-5954	297	36	pattern	pattern	NOUN
cana-5954	297	37	recognition	recognition	NOUN
cana-5954	297	38	,	,	PUNCT
cana-5954	297	39	(	(	PUNCT
cana-5954	297	40	2018	2018	NUM
cana-5954	297	41	)	)	PUNCT
cana-5954	297	42	.	.	PUNCT
cana-5954	298	1	[	[	X
cana-5954	298	2	19	19	NUM
cana-5954	298	3	]	]	PUNCT
cana-5954	298	4	.	.	PUNCT
cana-5954	299	1	hu	hu	PROPN
cana-5954	300	1	j	j	PROPN
cana-5954	300	2	,	,	PUNCT
cana-5954	300	3	shen	shen	PROPN
cana-5954	300	4	l	l	PROPN
cana-5954	300	5	,	,	PUNCT
cana-5954	300	6	sun	sun	NOUN
cana-5954	300	7	g	g	NOUN
cana-5954	300	8	,	,	PUNCT
cana-5954	300	9	“	"	PUNCT
cana-5954	300	10	squeeze	squeeze	NOUN
cana-5954	300	11	-	-	PUNCT
cana-5954	300	12	and	and	CCONJ
cana-5954	300	13	-	-	PUNCT
cana-5954	300	14	excitation	excitation	NOUN
cana-5954	300	15	networks	network	NOUN
cana-5954	300	16	”	"	PUNCT
cana-5954	300	17	,	,	PUNCT
cana-5954	300	18	proceedings	proceeding	NOUN
cana-5954	300	19	of	of	ADP
cana-5954	300	20	the	the	DET
cana-5954	300	21	ieee	ieee	NOUN
cana-5954	300	22	conference	conference	NOUN
cana-5954	300	23	on	on	ADP
cana-5954	300	24	computer	computer	NOUN
cana-5954	300	25	vision	vision	NOUN
cana-5954	300	26	and	and	CCONJ
cana-5954	300	27	pattern	pattern	NOUN
cana-5954	300	28	recognition	recognition	NOUN
cana-5954	300	29	,	,	PUNCT
cana-5954	300	30	(	(	PUNCT
cana-5954	300	31	2018	2018	NUM
cana-5954	300	32	)	)	PUNCT
cana-5954	300	33	.	.	PUNCT
cana-5954	301	1	https://doi.org/10.1155/2020/8876798	https://doi.org/10.1155/2020/8876798	PROPN
cana-5954	301	2	https://doi/	https://doi/	X
cana-5954	301	3	communications	communication	NOUN
cana-5954	301	4	on	on	ADP
cana-5954	301	5	applied	apply	VERB
cana-5954	301	6	nonlinear	nonlinear	ADJ
cana-5954	301	7	analysis	analysis	NOUN
cana-5954	301	8	issn	issn	NOUN
cana-5954	301	9	:	:	PUNCT
cana-5954	301	10	1074	1074	NUM
cana-5954	301	11	-	-	PUNCT
cana-5954	301	12	133x	133x	NUM
cana-5954	301	13	vol	vol	VERB
cana-5954	301	14	32	32	NUM
cana-5954	301	15	no	no	NOUN
cana-5954	301	16	.	.	PUNCT
cana-5954	302	1	10s	10	NOUN
cana-5954	302	2	(	(	PUNCT
cana-5954	302	3	2025	2025	NUM
cana-5954	302	4	)	)	PUNCT
cana-5954	302	5	3190	3190	NUM
cana-5954	302	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5954	303	1	[	[	X
cana-5954	303	2	20	20	NUM
cana-5954	303	3	]	]	PUNCT
cana-5954	303	4	.	.	PUNCT
cana-5954	304	1	qilong	qilong	PROPN
cana-5954	304	2	wang	wang	PROPN
cana-5954	304	3	,	,	PUNCT
cana-5954	304	4	banggu	banggu	PROPN
cana-5954	304	5	wu	wu	PROPN
cana-5954	304	6	,	,	PUNCT
cana-5954	304	7	pengfei	pengfei	PROPN
cana-5954	304	8	zhu	zhu	PROPN
cana-5954	304	9	,	,	PUNCT
cana-5954	304	10	peihua	peihua	PROPN
cana-5954	304	11	li	li	PROPN
cana-5954	304	12	,	,	PUNCT
cana-5954	304	13	wangmeng	wangmeng	PROPN
cana-5954	304	14	zuo	zuo	PROPN
cana-5954	304	15	,	,	PUNCT
cana-5954	304	16	and	and	CCONJ
cana-5954	304	17	qinghua	qinghua	PROPN
cana-5954	304	18	hu	hu	PROPN
cana-5954	304	19	,	,	PUNCT
cana-5954	304	20	“	"	PUNCT
cana-5954	304	21	ecanet	ecanet	ADJ
cana-5954	304	22	:	:	PUNCT
cana-5954	304	23	efficient	efficient	ADJ
cana-5954	304	24	channel	channel	NOUN
cana-5954	304	25	attention	attention	NOUN
cana-5954	304	26	for	for	ADP
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cana-5954	304	28	convolutional	convolutional	ADJ
cana-5954	304	29	neural	neural	ADJ
cana-5954	304	30	networks	network	NOUN
cana-5954	304	31	”	"	PUNCT
cana-5954	304	32	,	,	PUNCT
cana-5954	304	33	ieee	ieee	NOUN
cana-5954	304	34	/	/	SYM
cana-5954	304	35	cvf	cvf	NOUN
cana-5954	304	36	conference	conference	NOUN
cana-5954	304	37	on	on	ADP
cana-5954	304	38	computer	computer	NOUN
cana-5954	304	39	vision	vision	NOUN
cana-5954	304	40	and	and	CCONJ
cana-5954	304	41	pattern	pattern	NOUN
cana-5954	304	42	recognition	recognition	NOUN
cana-5954	304	43	,	,	PUNCT
cana-5954	304	44	cvpr	cvpr	NOUN
cana-5954	304	45	(	(	PUNCT
cana-5954	304	46	2020	2020	NUM
cana-5954	304	47	)	)	PUNCT
cana-5954	304	48	.	.	PUNCT
cana-5954	305	1	[	[	X
cana-5954	305	2	21	21	NUM
cana-5954	305	3	]	]	PUNCT
cana-5954	305	4	.	.	PUNCT
cana-5954	306	1	wang	wang	PROPN
cana-5954	306	2	x	x	PROPN
cana-5954	306	3	,	,	PUNCT
cana-5954	306	4	girshick	girshick	ADJ
cana-5954	306	5	r	r	NOUN
cana-5954	306	6	,	,	PUNCT
cana-5954	306	7	gupta	gupta	PROPN
cana-5954	306	8	a	a	PRON
cana-5954	306	9	,	,	PUNCT
cana-5954	306	10	“	"	PUNCT
cana-5954	306	11	non	non	ADJ
cana-5954	306	12	-	-	ADJ
cana-5954	306	13	local	local	ADJ
cana-5954	306	14	neural	neural	ADJ
cana-5954	306	15	networks	network	NOUN
cana-5954	306	16	”	"	PUNCT
cana-5954	306	17	,	,	PUNCT
cana-5954	306	18	proceedings	proceeding	NOUN
cana-5954	306	19	of	of	ADP
cana-5954	306	20	the	the	DET
cana-5954	306	21	ieee	ieee	NOUN
cana-5954	306	22	conference	conference	NOUN
cana-5954	306	23	on	on	ADP
cana-5954	306	24	computer	computer	NOUN
cana-5954	306	25	vision	vision	NOUN
cana-5954	306	26	and	and	CCONJ
cana-5954	306	27	pattern	pattern	NOUN
cana-5954	306	28	recognition	recognition	NOUN
cana-5954	306	29	.	.	PUNCT
cana-5954	307	1	(	(	PUNCT
cana-5954	307	2	2018	2018	NUM
cana-5954	307	3	)	)	PUNCT
cana-5954	307	4	.	.	PUNCT
cana-5954	308	1	[	[	X
cana-5954	308	2	22	22	NUM
cana-5954	308	3	]	]	PUNCT
cana-5954	308	4	.	.	PUNCT
cana-5954	309	1	huang	huang	PROPN
cana-5954	309	2	z	z	PROPN
cana-5954	309	3	,	,	PUNCT
cana-5954	309	4	wang	wang	PROPN
cana-5954	309	5	x	x	PROPN
cana-5954	309	6	,	,	PUNCT
cana-5954	309	7	huang	huang	PROPN
cana-5954	309	8	l	l	PROPN
cana-5954	309	9	,	,	PUNCT
cana-5954	309	10	“	"	PUNCT
cana-5954	309	11	criss	criss	ADJ
cana-5954	309	12	-	-	PUNCT
cana-5954	309	13	cross	cross	NOUN
cana-5954	309	14	attention	attention	NOUN
cana-5954	309	15	for	for	ADP
cana-5954	309	16	semantic	semantic	ADJ
cana-5954	309	17	segmentation	segmentation	NOUN
cana-5954	309	18	”	"	PUNCT
cana-5954	309	19	,	,	PUNCT
cana-5954	309	20	proceedings	proceeding	NOUN
cana-5954	309	21	of	of	ADP
cana-5954	309	22	the	the	DET
cana-5954	309	23	ieee	ieee	NOUN
cana-5954	309	24	/	/	SYM
cana-5954	309	25	cvf	cvf	NOUN
cana-5954	309	26	international	international	ADJ
cana-5954	309	27	conference	conference	NOUN
cana-5954	309	28	on	on	ADP
cana-5954	309	29	computer	computer	NOUN
cana-5954	309	30	vision	vision	NOUN
cana-5954	309	31	,	,	PUNCT
cana-5954	309	32	(	(	PUNCT
cana-5954	309	33	2019	2019	NUM
cana-5954	309	34	)	)	PUNCT
cana-5954	309	35	.	.	PUNCT
cana-5954	310	1	[	[	X
cana-5954	310	2	23	23	NUM
cana-5954	310	3	]	]	PUNCT
cana-5954	310	4	.	.	PUNCT
cana-5954	311	1	woo	woo	PROPN
cana-5954	311	2	s	s	PROPN
cana-5954	311	3	,	,	PUNCT
cana-5954	311	4	park	park	PROPN
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cana-5954	311	6	,	,	PUNCT
cana-5954	311	7	lee	lee	PROPN
cana-5954	311	8	j	j	PROPN
cana-5954	311	9	y	y	PROPN
cana-5954	311	10	,	,	PUNCT
cana-5954	311	11	“	"	PUNCT
cana-5954	311	12	convolutional	convolutional	ADJ
cana-5954	311	13	block	block	NOUN
cana-5954	311	14	attention	attention	NOUN
cana-5954	311	15	module	module	NOUN
cana-5954	311	16	”	"	PUNCT
cana-5954	311	17	,	,	PUNCT
cana-5954	311	18	proceedings	proceeding	NOUN
cana-5954	311	19	of	of	ADP
cana-5954	311	20	the	the	DET
cana-5954	311	21	european	european	PROPN
cana-5954	311	22	conference	conference	PROPN
cana-5954	311	23	on	on	ADP
cana-5954	311	24	computer	computer	NOUN
cana-5954	311	25	vision	vision	NOUN
cana-5954	311	26	(	(	PUNCT
cana-5954	311	27	eccv	eccv	ADV
cana-5954	311	28	)	)	PUNCT
cana-5954	311	29	,	,	PUNCT
cana-5954	311	30	(	(	PUNCT
cana-5954	311	31	2018	2018	NUM
cana-5954	311	32	)	)	PUNCT
cana-5954	311	33	.	.	PUNCT
cana-5954	312	1	[	[	X
cana-5954	312	2	24	24	NUM
cana-5954	312	3	]	]	PUNCT
cana-5954	312	4	.	.	PUNCT
cana-5954	313	1	cao	cao	PROPN
cana-5954	313	2	y	y	PROPN
cana-5954	313	3	,	,	PUNCT
cana-5954	313	4	xu	xu	PROPN
cana-5954	313	5	j	j	PROPN
cana-5954	313	6	,	,	PUNCT
cana-5954	313	7	lin	lin	PROPN
cana-5954	313	8	s	s	PART
cana-5954	313	9	,	,	PUNCT
cana-5954	313	10	“	"	PUNCT
cana-5954	313	11	non	non	ADJ
cana-5954	313	12	-	-	ADJ
cana-5954	313	13	local	local	ADJ
cana-5954	313	14	networks	network	NOUN
cana-5954	313	15	meet	meet	VERB
cana-5954	313	16	squeeze	squeeze	NOUN
cana-5954	313	17	-	-	PUNCT
cana-5954	313	18	excitation	excitation	NOUN
cana-5954	313	19	networks	network	NOUN
cana-5954	313	20	and	and	CCONJ
cana-5954	313	21	beyond	beyond	ADP
cana-5954	313	22	”	"	PUNCT
cana-5954	313	23	,	,	PUNCT
cana-5954	313	24	proceedings	proceeding	NOUN
cana-5954	313	25	of	of	ADP
cana-5954	313	26	the	the	DET
cana-5954	313	27	ieee	ieee	NOUN
cana-5954	313	28	/	/	SYM
cana-5954	313	29	cvf	cvf	NOUN
cana-5954	313	30	international	international	ADJ
cana-5954	313	31	conference	conference	NOUN
cana-5954	313	32	on	on	ADP
cana-5954	313	33	computer	computer	NOUN
cana-5954	313	34	vision	vision	NOUN
cana-5954	313	35	workshops	workshop	NOUN
cana-5954	313	36	(	(	PUNCT
cana-5954	313	37	2019	2019	NUM
cana-5954	313	38	)	)	PUNCT
cana-5954	313	39	.	.	PUNCT
cana-5954	314	1	[	[	X
cana-5954	314	2	25	25	NUM
cana-5954	314	3	]	]	PUNCT
cana-5954	314	4	.	.	PUNCT
cana-5954	315	1	liu	liu	PROPN
cana-5954	315	2	w	w	PROPN
cana-5954	315	3	,	,	PUNCT
cana-5954	315	4	anguelov	anguelov	NOUN
cana-5954	315	5	d	d	NOUN
cana-5954	315	6	,	,	PUNCT
cana-5954	315	7	erhan	erhan	ADP
cana-5954	315	8	d	d	PROPN
cana-5954	315	9	,	,	PUNCT
cana-5954	315	10	“	"	PUNCT
cana-5954	315	11	single	single	ADJ
cana-5954	315	12	shot	shot	NOUN
cana-5954	315	13	multibox	multibox	NOUN
cana-5954	315	14	detector	detector	NOUN
cana-5954	315	15	”	"	PUNCT
cana-5954	315	16	,	,	PUNCT
cana-5954	315	17	european	european	ADJ
cana-5954	315	18	conference	conference	NOUN
cana-5954	315	19	on	on	ADP
cana-5954	315	20	computer	computer	NOUN
cana-5954	315	21	vision	vision	NOUN
cana-5954	315	22	.	.	PUNCT
cana-5954	315	23	,	,	PUNCT
cana-5954	315	24	springer	springer	NOUN
cana-5954	315	25	,	,	PUNCT
cana-5954	315	26	cham	cham	PROPN
cana-5954	315	27	,	,	PUNCT
cana-5954	315	28	(	(	PUNCT
cana-5954	315	29	2016	2016	NUM
cana-5954	315	30	)	)	PUNCT
cana-5954	315	31	.	.	PUNCT
cana-5954	316	1	[	[	X
cana-5954	316	2	26	26	NUM
cana-5954	316	3	]	]	PUNCT
cana-5954	316	4	.	.	PUNCT
cana-5954	317	1	lin	lin	PROPN
cana-5954	317	2	t	t	PROPN
cana-5954	317	3	y	y	PROPN
cana-5954	317	4	,	,	PUNCT
cana-5954	317	5	goyal	goyal	PROPN
cana-5954	317	6	p	p	NOUN
cana-5954	317	7	,	,	PUNCT
cana-5954	317	8	girshick	girshick	ADJ
cana-5954	317	9	r	r	NOUN
cana-5954	317	10	,	,	PUNCT
cana-5954	317	11	“	"	PUNCT
cana-5954	317	12	focal	focal	ADJ
cana-5954	317	13	loss	loss	NOUN
cana-5954	317	14	for	for	ADP
cana-5954	317	15	dense	dense	ADJ
cana-5954	317	16	object	object	NOUN
cana-5954	317	17	detection	detection	NOUN
cana-5954	317	18	”	"	PUNCT
cana-5954	317	19	,	,	PUNCT
cana-5954	317	20	proceedings	proceeding	NOUN
cana-5954	317	21	of	of	ADP
cana-5954	317	22	the	the	DET
cana-5954	317	23	ieee	ieee	NOUN
cana-5954	317	24	international	international	PROPN
cana-5954	317	25	conference	conference	NOUN
cana-5954	317	26	on	on	ADP
cana-5954	317	27	computer	computer	NOUN
cana-5954	317	28	vision	vision	NOUN
cana-5954	317	29	,	,	PUNCT
cana-5954	317	30	(	(	PUNCT
cana-5954	317	31	2017	2017	NUM
cana-5954	317	32	)	)	PUNCT
cana-5954	318	1	[	[	X
cana-5954	318	2	27	27	NUM
cana-5954	318	3	]	]	PUNCT
cana-5954	318	4	.	.	PUNCT
cana-5954	319	1	ma	ma	PROPN
cana-5954	319	2	n	n	PROPN
cana-5954	319	3	,	,	PUNCT
cana-5954	319	4	zhang	zhang	PROPN
cana-5954	319	5	x	x	PROPN
cana-5954	319	6	,	,	PUNCT
cana-5954	319	7	zheng	zheng	PROPN
cana-5954	319	8	h	h	PROPN
cana-5954	319	9	t	t	PROPN
cana-5954	319	10	,	,	PUNCT
cana-5954	319	11	“	"	PUNCT
cana-5954	319	12	practical	practical	ADJ
cana-5954	319	13	guidelines	guideline	NOUN
cana-5954	319	14	for	for	ADP
cana-5954	319	15	efficient	efficient	ADJ
cana-5954	319	16	cnn	cnn	PROPN
cana-5954	319	17	architecture	architecture	NOUN
cana-5954	319	18	design	design	NOUN
cana-5954	319	19	”	"	PUNCT
cana-5954	319	20	,	,	PUNCT
cana-5954	319	21	proceedings	proceeding	NOUN
cana-5954	319	22	of	of	ADP
cana-5954	319	23	the	the	DET
cana-5954	319	24	european	european	PROPN
cana-5954	319	25	conference	conference	PROPN
cana-5954	319	26	on	on	ADP
cana-5954	319	27	computer	computer	NOUN
cana-5954	319	28	vision	vision	NOUN
cana-5954	319	29	(	(	PUNCT
cana-5954	319	30	eccv	eccv	ADV
cana-5954	319	31	)	)	PUNCT
cana-5954	319	32	,	,	PUNCT
cana-5954	319	33	(	(	PUNCT
cana-5954	319	34	2018	2018	NUM
cana-5954	319	35	)	)	PUNCT
cana-5954	319	36	.	.	PUNCT
cana-5954	320	1	[	[	X
cana-5954	320	2	28	28	NUM
cana-5954	320	3	]	]	PUNCT
cana-5954	320	4	.	.	PUNCT
cana-5954	321	1	ren	ren	PROPN
cana-5954	321	2	s	s	PROPN
cana-5954	321	3	,	,	PUNCT
cana-5954	321	4	he	he	PRON
cana-5954	321	5	k	k	NOUN
cana-5954	321	6	,	,	PUNCT
cana-5954	321	7	girshick	girshick	ADJ
cana-5954	321	8	r	r	NOUN
cana-5954	321	9	,	,	PUNCT
cana-5954	321	10	“	"	PUNCT
cana-5954	321	11	towards	towards	ADP
cana-5954	321	12	real	real	ADJ
cana-5954	321	13	-	-	PUNCT
cana-5954	321	14	time	time	NOUN
cana-5954	321	15	object	object	NOUN
cana-5954	321	16	detection	detection	NOUN
cana-5954	321	17	with	with	ADP
cana-5954	321	18	region	region	NOUN
cana-5954	321	19	proposal	proposal	NOUN
cana-5954	321	20	networks	network	NOUN
cana-5954	321	21	”	"	PUNCT
cana-5954	321	22	,	,	PUNCT
cana-5954	321	23	advances	advance	NOUN
cana-5954	321	24	in	in	ADP
cana-5954	321	25	neural	neural	ADJ
cana-5954	321	26	information	information	NOUN
cana-5954	321	27	processing	processing	NOUN
cana-5954	321	28	systems	system	NOUN
cana-5954	321	29	,	,	PUNCT
cana-5954	321	30	(	(	PUNCT
cana-5954	321	31	2015	2015	NUM
cana-5954	321	32	)	)	PUNCT
cana-5954	321	33	.	.	PUNCT
cana-5954	322	1	[	[	X
cana-5954	322	2	29	29	NUM
cana-5954	322	3	]	]	PUNCT
cana-5954	322	4	.	.	PUNCT
cana-5954	323	1	xuan	xuan	PROPN
cana-5954	323	2	cai	cai	PROPN
cana-5954	323	3	,	,	PUNCT
cana-5954	323	4	yifan	yifan	PROPN
cana-5954	323	5	wang	wang	PROPN
cana-5954	323	6	,	,	PUNCT
cana-5954	323	7	xiaoqing	xiaoqing	PROPN
cana-5954	323	8	sun	sun	PROPN
cana-5954	323	9	,	,	PUNCT
cana-5954	323	10	wentao	wentao	PROPN
cana-5954	323	11	liu	liu	PROPN
cana-5954	323	12	,	,	PUNCT
cana-5954	323	13	yuyang	yuyang	PROPN
cana-5954	323	14	tang	tang	PROPN
cana-5954	323	15	,	,	PUNCT
cana-5954	323	16	wenbo	wenbo	PROPN
cana-5954	323	17	li	li	PROPN
cana-5954	323	18	,	,	PUNCT
cana-5954	323	19	“	"	PUNCT
cana-5954	323	20	comparing	compare	VERB
cana-5954	323	21	the	the	DET
cana-5954	323	22	performance	performance	NOUN
cana-5954	323	23	of	of	ADP
cana-5954	323	24	resnets	resnet	NOUN
cana-5954	323	25	on	on	ADP
cana-5954	323	26	covid-19	covid-19	PROPN
cana-5954	323	27	diagnosis	diagnosis	NOUN
cana-5954	323	28	using	use	VERB
cana-5954	323	29	ct	ct	NUM
cana-5954	323	30	scans	scan	NOUN
cana-5954	323	31	”	"	PUNCT
cana-5954	323	32	,	,	PUNCT
cana-5954	323	33	ieee	ieee	NOUN
cana-5954	323	34	,	,	PUNCT
cana-5954	323	35	(	(	PUNCT
cana-5954	323	36	2020	2020	NUM
cana-5954	323	37	)	)	PUNCT
cana-5954	323	38	.	.	PUNCT
cana-5954	324	1	[	[	X
cana-5954	324	2	30	30	NUM
cana-5954	324	3	]	]	PUNCT
cana-5954	324	4	.	.	PUNCT
cana-5954	325	1	vamsidhar	vamsidhar	PROPN
cana-5954	325	2	enireddy	enireddy	PROPN
cana-5954	325	3	,	,	PUNCT
cana-5954	325	4	mathe	mathe	PROPN
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cana-5954	325	6	kenny	kenny	PROPN
cana-5954	325	7	kumar	kumar	PROPN
cana-5954	325	8	,	,	PUNCT
cana-5954	325	9	babitha	babitha	PROPN
cana-5954	325	10	donepudi	donepudi	PROPN
cana-5954	325	11	,	,	PUNCT
cana-5954	325	12	c	c	PROPN
cana-5954	325	13	karthikeyan	karthikeyan	X
cana-5954	325	14	,	,	PUNCT
cana-5954	325	15	“	"	PUNCT
cana-5954	325	16	detection	detection	NOUN
cana-5954	325	17	of	of	ADP
cana-5954	325	18	covid-19	covid-19	PROPN
cana-5954	325	19	using	use	VERB
cana-5954	325	20	hybrid	hybrid	ADJ
cana-5954	325	21	resnet	resnet	NOUN
cana-5954	325	22	and	and	CCONJ
cana-5954	325	23	svm	svm	ADJ
cana-5954	325	24	”	"	PUNCT
cana-5954	325	25	,	,	PUNCT
cana-5954	325	26	iop	iop	PROPN
cana-5954	325	27	conf	conf	NOUN
cana-5954	325	28	.	.	PUNCT
cana-5954	326	1	series	series	NOUN
cana-5954	326	2	,	,	PUNCT
cana-5954	326	3	materials	material	NOUN
cana-5954	326	4	science	science	NOUN
cana-5954	326	5	and	and	CCONJ
cana-5954	326	6	engineering	engineering	NOUN
cana-5954	326	7	993	993	NUM
cana-5954	326	8	,	,	PUNCT
cana-5954	326	9	(	(	PUNCT
cana-5954	326	10	2020	2020	NUM
cana-5954	326	11	)	)	PUNCT
cana-5954	326	12	.	.	PUNCT
cana-5954	327	1	http://doi:10.1088/1757	http://doi:10.1088/1757	PROPN
cana-5954	327	2	-	-	PUNCT
cana-5954	327	3	899x/993/1/012046	899x/993/1/012046	NUM