id	sid	tid	token	lemma	pos
cana-3796	1	1	communications	communication	NOUN
cana-3796	1	2	on	on	ADP
cana-3796	1	3	applied	apply	VERB
cana-3796	1	4	nonlinear	nonlinear	ADJ
cana-3796	1	5	analysis	analysis	NOUN
cana-3796	1	6	issn	issn	NOUN
cana-3796	1	7	:	:	PUNCT
cana-3796	1	8	1074	1074	NUM
cana-3796	1	9	-	-	PUNCT
cana-3796	1	10	133x	133x	NUM
cana-3796	1	11	vol	vol	NOUN
cana-3796	1	12	32	32	NUM
cana-3796	1	13	no	no	NOUN
cana-3796	1	14	.	.	PUNCT
cana-3796	2	1	8s	8s	PROPN
cana-3796	2	2	(	(	PUNCT
cana-3796	2	3	2025	2025	NUM
cana-3796	2	4	)	)	PUNCT
cana-3796	2	5	745	745	NUM
cana-3796	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	2	7	automated	automate	VERB
cana-3796	2	8	lstm	lstm	NOUN
cana-3796	2	9	based	base	VERB
cana-3796	2	10	deep	deep	ADJ
cana-3796	2	11	learning	learning	NOUN
cana-3796	2	12	model	model	NOUN
cana-3796	2	13	for	for	ADP
cana-3796	2	14	handwritten	handwritten	ADJ
cana-3796	2	15	telugu	telugu	PROPN
cana-3796	2	16	answer	answer	NOUN
cana-3796	2	17	script	script	NOUN
cana-3796	2	18	analysis	analysis	NOUN
cana-3796	2	19	padmavathi	padmavathi	PROPN
cana-3796	2	20	pragada1	pragada1	PROPN
cana-3796	2	21	,	,	PUNCT
cana-3796	2	22	a	a	PRON
cana-3796	2	23	)	)	PUNCT
cana-3796	2	24	,	,	PUNCT
cana-3796	2	25	dhawaleswar	dhawaleswar	NOUN
cana-3796	2	26	rao	rao	NOUN
cana-3796	2	27	ch*2	ch*2	NOUN
cana-3796	2	28	,	,	PUNCT
cana-3796	2	29	b	b	X
cana-3796	2	30	)	)	PUNCT
cana-3796	2	31	1,2centurion	1,2centurion	PROPN
cana-3796	2	32	university	university	NOUN
cana-3796	2	33	of	of	ADP
cana-3796	2	34	technology	technology	NOUN
cana-3796	2	35	and	and	CCONJ
cana-3796	2	36	management	management	NOUN
cana-3796	2	37	,	,	PUNCT
cana-3796	2	38	r.	r.	PROPN
cana-3796	2	39	sitapur	sitapur	PROPN
cana-3796	2	40	,	,	PUNCT
cana-3796	2	41	odisha	odisha	PROPN
cana-3796	2	42	1gmr	1gmr	PROPN
cana-3796	2	43	institute	institute	NOUN
cana-3796	2	44	of	of	ADP
cana-3796	2	45	technology	technology	NOUN
cana-3796	2	46	,	,	PUNCT
cana-3796	2	47	rajam	rajam	NOUN
cana-3796	2	48	a	a	NOUN
cana-3796	2	49	)	)	PUNCT
cana-3796	2	50	pragadapadmavathi88@gmail.com	pragadapadmavathi88@gmail.com	PROPN
cana-3796	2	51	b	b	X
cana-3796	2	52	)	)	PUNCT
cana-3796	2	53	dhawaleswarrao@gmail.com	dhawaleswarrao@gmail.com	NOUN
cana-3796	3	1	article	article	NOUN
cana-3796	3	2	history	history	NOUN
cana-3796	3	3	:	:	PUNCT
cana-3796	3	4	received	receive	VERB
cana-3796	3	5	:	:	PUNCT
cana-3796	3	6	10	10	NUM
cana-3796	3	7	-	-	SYM
cana-3796	3	8	11	11	NUM
cana-3796	3	9	-	-	PUNCT
cana-3796	3	10	2024	2024	NUM
cana-3796	3	11	revised:15	revised:15	ADJ
cana-3796	3	12	-	-	PUNCT
cana-3796	3	13	12	12	NUM
cana-3796	3	14	-	-	PUNCT
cana-3796	3	15	2024	2024	NUM
cana-3796	3	16	accepted:03	accepted:03	NUM
cana-3796	3	17	-	-	PUNCT
cana-3796	3	18	01	01	NUM
cana-3796	3	19	-	-	PUNCT
cana-3796	3	20	2025	2025	NUM
cana-3796	3	21	abstract	abstract	NOUN
cana-3796	3	22	:	:	PUNCT
cana-3796	3	23	the	the	DET
cana-3796	3	24	growing	grow	VERB
cana-3796	3	25	demand	demand	NOUN
cana-3796	3	26	for	for	ADP
cana-3796	3	27	automated	automate	VERB
cana-3796	3	28	evaluation	evaluation	NOUN
cana-3796	3	29	systems	system	NOUN
cana-3796	3	30	in	in	ADP
cana-3796	3	31	educational	educational	ADJ
cana-3796	3	32	environments	environment	NOUN
cana-3796	3	33	,	,	PUNCT
cana-3796	3	34	especially	especially	ADV
cana-3796	3	35	for	for	ADP
cana-3796	3	36	languages	language	NOUN
cana-3796	3	37	with	with	ADP
cana-3796	3	38	complex	complex	ADJ
cana-3796	3	39	scripts	script	NOUN
cana-3796	3	40	like	like	ADP
cana-3796	3	41	telugu	telugu	PROPN
cana-3796	3	42	,	,	PUNCT
cana-3796	3	43	drives	drive	VERB
cana-3796	3	44	the	the	DET
cana-3796	3	45	motivation	motivation	NOUN
cana-3796	3	46	for	for	ADP
cana-3796	3	47	this	this	DET
cana-3796	3	48	research	research	NOUN
cana-3796	3	49	.	.	PUNCT
cana-3796	4	1	traditional	traditional	ADJ
cana-3796	4	2	handwriting	handwriting	NOUN
cana-3796	4	3	recognition	recognition	NOUN
cana-3796	4	4	methods	method	NOUN
cana-3796	4	5	for	for	ADP
cana-3796	4	6	telugu	telugu	PROPN
cana-3796	4	7	have	have	AUX
cana-3796	4	8	faced	face	VERB
cana-3796	4	9	challenges	challenge	NOUN
cana-3796	4	10	with	with	ADP
cana-3796	4	11	limited	limited	ADJ
cana-3796	4	12	accuracy	accuracy	NOUN
cana-3796	4	13	and	and	CCONJ
cana-3796	4	14	adaptability	adaptability	NOUN
cana-3796	4	15	,	,	PUNCT
cana-3796	4	16	particularly	particularly	ADV
cana-3796	4	17	in	in	ADP
cana-3796	4	18	real	real	ADJ
cana-3796	4	19	-	-	PUNCT
cana-3796	4	20	world	world	NOUN
cana-3796	4	21	educational	educational	ADJ
cana-3796	4	22	scenarios	scenario	NOUN
cana-3796	4	23	.	.	PUNCT
cana-3796	5	1	these	these	DET
cana-3796	5	2	limitations	limitation	NOUN
cana-3796	5	3	often	often	ADV
cana-3796	5	4	result	result	VERB
cana-3796	5	5	in	in	ADP
cana-3796	5	6	reduced	reduced	ADJ
cana-3796	5	7	precision	precision	NOUN
cana-3796	5	8	in	in	ADP
cana-3796	5	9	character	character	NOUN
cana-3796	5	10	and	and	CCONJ
cana-3796	5	11	sentence	sentence	NOUN
cana-3796	5	12	recognition	recognition	NOUN
cana-3796	5	13	,	,	PUNCT
cana-3796	5	14	along	along	ADP
cana-3796	5	15	with	with	ADP
cana-3796	5	16	increased	increase	VERB
cana-3796	5	17	processing	processing	NOUN
cana-3796	5	18	delays	delay	NOUN
cana-3796	5	19	.	.	PUNCT
cana-3796	6	1	this	this	DET
cana-3796	6	2	study	study	NOUN
cana-3796	6	3	proposes	propose	VERB
cana-3796	6	4	a	a	DET
cana-3796	6	5	novel	novel	ADJ
cana-3796	6	6	system	system	NOUN
cana-3796	6	7	for	for	ADP
cana-3796	6	8	the	the	DET
cana-3796	6	9	automated	automate	VERB
cana-3796	6	10	evaluation	evaluation	NOUN
cana-3796	6	11	of	of	ADP
cana-3796	6	12	handwritten	handwritten	ADJ
cana-3796	6	13	telugu	telugu	NOUN
cana-3796	6	14	answer	answer	NOUN
cana-3796	6	15	scripts	script	NOUN
cana-3796	6	16	.	.	PUNCT
cana-3796	7	1	the	the	DET
cana-3796	7	2	model	model	NOUN
cana-3796	7	3	incorporates	incorporate	VERB
cana-3796	7	4	advanced	advanced	ADJ
cana-3796	7	5	preprocessing	preprocessing	NOUN
cana-3796	7	6	techniques	technique	NOUN
cana-3796	7	7	such	such	ADJ
cana-3796	7	8	as	as	ADP
cana-3796	7	9	adaptive	adaptive	ADJ
cana-3796	7	10	thresholding	thresholding	NOUN
cana-3796	7	11	for	for	ADP
cana-3796	7	12	binarization	binarization	NOUN
cana-3796	7	13	and	and	CCONJ
cana-3796	7	14	gaussian	gaussian	ADJ
cana-3796	7	15	blurring	blurring	NOUN
cana-3796	7	16	for	for	ADP
cana-3796	7	17	noise	noise	NOUN
cana-3796	7	18	reduction	reduction	NOUN
cana-3796	7	19	,	,	PUNCT
cana-3796	7	20	enhancing	enhance	VERB
cana-3796	7	21	the	the	DET
cana-3796	7	22	readability	readability	NOUN
cana-3796	7	23	of	of	ADP
cana-3796	7	24	diverse	diverse	ADJ
cana-3796	7	25	handwriting	handwriting	NOUN
cana-3796	7	26	styles	style	NOUN
cana-3796	7	27	.	.	PUNCT
cana-3796	8	1	robust	robust	ADJ
cana-3796	8	2	feature	feature	NOUN
cana-3796	8	3	extraction	extraction	NOUN
cana-3796	8	4	is	be	AUX
cana-3796	8	5	achieved	achieve	VERB
cana-3796	8	6	using	use	VERB
cana-3796	8	7	convolutional	convolutional	ADJ
cana-3796	8	8	neural	neural	ADJ
cana-3796	8	9	networks	network	NOUN
cana-3796	8	10	(	(	PUNCT
cana-3796	8	11	cnns	cnns	PROPN
cana-3796	8	12	)	)	PUNCT
cana-3796	8	13	like	like	ADP
cana-3796	8	14	resnet101	resnet101	PROPN
cana-3796	8	15	and	and	CCONJ
cana-3796	8	16	inception	inception	ADJ
cana-3796	8	17	networks	network	NOUN
cana-3796	8	18	.	.	PUNCT
cana-3796	9	1	to	to	PART
cana-3796	9	2	capture	capture	VERB
cana-3796	9	3	the	the	DET
cana-3796	9	4	contextual	contextual	ADJ
cana-3796	9	5	flow	flow	NOUN
cana-3796	9	6	of	of	ADP
cana-3796	9	7	telugu	telugu	NOUN
cana-3796	9	8	scripts	script	NOUN
cana-3796	9	9	,	,	PUNCT
cana-3796	9	10	quad	quad	PROPN
cana-3796	9	11	long	long	ADV
cana-3796	9	12	shortterm	shortterm	NOUN
cana-3796	9	13	memory	memory	NOUN
cana-3796	9	14	(	(	PUNCT
cana-3796	9	15	lstm	lstm	NOUN
cana-3796	9	16	)	)	PUNCT
cana-3796	9	17	networks	network	NOUN
cana-3796	9	18	are	be	AUX
cana-3796	9	19	utilized	utilize	VERB
cana-3796	9	20	,	,	PUNCT
cana-3796	9	21	with	with	ADP
cana-3796	9	22	attention	attention	NOUN
cana-3796	9	23	mechanisms	mechanism	NOUN
cana-3796	9	24	improving	improve	VERB
cana-3796	9	25	focus	focus	NOUN
cana-3796	9	26	on	on	ADP
cana-3796	9	27	intricate	intricate	ADJ
cana-3796	9	28	character	character	NOUN
cana-3796	9	29	sequences	sequence	NOUN
cana-3796	9	30	.	.	PUNCT
cana-3796	10	1	additionally	additionally	ADV
cana-3796	10	2	,	,	PUNCT
cana-3796	10	3	transformerbased	transformerbase	VERB
cana-3796	10	4	models	model	NOUN
cana-3796	10	5	like	like	ADP
cana-3796	10	6	bert	bert	NOUN
cana-3796	10	7	,	,	PUNCT
cana-3796	10	8	trained	train	VERB
cana-3796	10	9	on	on	ADP
cana-3796	10	10	telugu	telugu	PROPN
cana-3796	10	11	text	text	NOUN
cana-3796	10	12	,	,	PUNCT
cana-3796	10	13	enable	enable	VERB
cana-3796	10	14	the	the	DET
cana-3796	10	15	system	system	NOUN
cana-3796	10	16	to	to	PART
cana-3796	10	17	better	well	ADV
cana-3796	10	18	understand	understand	VERB
cana-3796	10	19	the	the	DET
cana-3796	10	20	syntax	syntax	NOUN
cana-3796	10	21	and	and	CCONJ
cana-3796	10	22	semantics	semantic	NOUN
cana-3796	10	23	of	of	ADP
cana-3796	10	24	the	the	DET
cana-3796	10	25	language	language	NOUN
cana-3796	10	26	.	.	PUNCT
cana-3796	11	1	for	for	ADP
cana-3796	11	2	evaluation	evaluation	NOUN
cana-3796	11	3	,	,	PUNCT
cana-3796	11	4	visual	visual	ADJ
cana-3796	11	5	bert	bert	NOUN
cana-3796	11	6	embeddings	embedding	NOUN
cana-3796	11	7	and	and	CCONJ
cana-3796	11	8	cosine	cosine	NOUN
cana-3796	11	9	similarity	similarity	NOUN
cana-3796	11	10	metrics	metric	NOUN
cana-3796	11	11	are	be	AUX
cana-3796	11	12	employed	employ	VERB
cana-3796	11	13	to	to	PART
cana-3796	11	14	ensure	ensure	VERB
cana-3796	11	15	precise	precise	ADJ
cana-3796	11	16	semantic	semantic	ADJ
cana-3796	11	17	analysis	analysis	NOUN
cana-3796	11	18	and	and	CCONJ
cana-3796	11	19	answer	answer	NOUN
cana-3796	11	20	matching	matching	NOUN
cana-3796	11	21	.	.	PUNCT
cana-3796	12	1	testing	testing	NOUN
cana-3796	12	2	across	across	ADP
cana-3796	12	3	multiple	multiple	ADJ
cana-3796	12	4	datasets	dataset	NOUN
cana-3796	12	5	demonstrates	demonstrate	VERB
cana-3796	12	6	a	a	DET
cana-3796	12	7	significant	significant	ADJ
cana-3796	12	8	improvement	improvement	NOUN
cana-3796	12	9	over	over	ADP
cana-3796	12	10	existing	exist	VERB
cana-3796	12	11	approaches	approach	NOUN
cana-3796	12	12	,	,	PUNCT
cana-3796	12	13	with	with	ADP
cana-3796	12	14	higher	high	ADJ
cana-3796	12	15	precision	precision	NOUN
cana-3796	12	16	and	and	CCONJ
cana-3796	12	17	accuracy	accuracy	NOUN
cana-3796	12	18	in	in	ADP
cana-3796	12	19	character	character	NOUN
cana-3796	12	20	recognition	recognition	NOUN
cana-3796	12	21	and	and	CCONJ
cana-3796	12	22	notable	notable	ADJ
cana-3796	12	23	enhancements	enhancement	NOUN
cana-3796	12	24	in	in	ADP
cana-3796	12	25	area	area	NOUN
cana-3796	12	26	under	under	ADP
cana-3796	12	27	the	the	DET
cana-3796	12	28	curve	curve	NOUN
cana-3796	12	29	(	(	PUNCT
cana-3796	12	30	auc	auc	NOUN
cana-3796	12	31	)	)	PUNCT
cana-3796	12	32	.	.	PUNCT
cana-3796	13	1	sentence	sentence	NOUN
cana-3796	13	2	recognition	recognition	NOUN
cana-3796	13	3	also	also	ADV
cana-3796	13	4	shows	show	VERB
cana-3796	13	5	marked	mark	VERB
cana-3796	13	6	improvements	improvement	NOUN
cana-3796	13	7	in	in	ADP
cana-3796	13	8	precision	precision	NOUN
cana-3796	13	9	,	,	PUNCT
cana-3796	13	10	accuracy	accuracy	NOUN
cana-3796	13	11	,	,	PUNCT
cana-3796	13	12	and	and	CCONJ
cana-3796	13	13	auc	auc	NOUN
cana-3796	13	14	.	.	PUNCT
cana-3796	14	1	this	this	DET
cana-3796	14	2	work	work	NOUN
cana-3796	14	3	represents	represent	VERB
cana-3796	14	4	a	a	DET
cana-3796	14	5	significant	significant	ADJ
cana-3796	14	6	advancement	advancement	NOUN
cana-3796	14	7	in	in	ADP
cana-3796	14	8	automated	automate	VERB
cana-3796	14	9	evaluation	evaluation	NOUN
cana-3796	14	10	systems	system	NOUN
cana-3796	14	11	for	for	ADP
cana-3796	14	12	languages	language	NOUN
cana-3796	14	13	with	with	ADP
cana-3796	14	14	intricate	intricate	ADJ
cana-3796	14	15	scripts	script	NOUN
cana-3796	14	16	,	,	PUNCT
cana-3796	14	17	improving	improve	VERB
cana-3796	14	18	both	both	DET
cana-3796	14	19	efficiency	efficiency	NOUN
cana-3796	14	20	and	and	CCONJ
cana-3796	14	21	accuracy	accuracy	NOUN
cana-3796	14	22	in	in	ADP
cana-3796	14	23	educational	educational	ADJ
cana-3796	14	24	assessments	assessment	NOUN
cana-3796	14	25	.	.	PUNCT
cana-3796	15	1	beyond	beyond	ADP
cana-3796	15	2	its	its	PRON
cana-3796	15	3	primary	primary	ADJ
cana-3796	15	4	application	application	NOUN
cana-3796	15	5	,	,	PUNCT
cana-3796	15	6	the	the	DET
cana-3796	15	7	system	system	NOUN
cana-3796	15	8	offers	offer	VERB
cana-3796	15	9	potential	potential	NOUN
cana-3796	15	10	for	for	ADP
cana-3796	15	11	broader	broad	ADJ
cana-3796	15	12	uses	use	NOUN
cana-3796	15	13	in	in	ADP
cana-3796	15	14	document	document	NOUN
cana-3796	15	15	processing	processing	NOUN
cana-3796	15	16	and	and	CCONJ
cana-3796	15	17	language	language	NOUN
cana-3796	15	18	technologies	technology	NOUN
cana-3796	15	19	.	.	PUNCT
cana-3796	16	1	this	this	DET
cana-3796	16	2	research	research	NOUN
cana-3796	16	3	makes	make	VERB
cana-3796	16	4	a	a	DET
cana-3796	16	5	valuable	valuable	ADJ
cana-3796	16	6	contribution	contribution	NOUN
cana-3796	16	7	to	to	ADP
cana-3796	16	8	the	the	DET
cana-3796	16	9	fields	field	NOUN
cana-3796	16	10	of	of	ADP
cana-3796	16	11	automated	automate	VERB
cana-3796	16	12	handwriting	handwriting	NOUN
cana-3796	16	13	recognition	recognition	NOUN
cana-3796	16	14	and	and	CCONJ
cana-3796	16	15	natural	natural	ADJ
cana-3796	16	16	language	language	NOUN
cana-3796	16	17	processing	processing	NOUN
cana-3796	16	18	for	for	ADP
cana-3796	16	19	indic	indic	ADJ
cana-3796	16	20	scripts	script	NOUN
cana-3796	16	21	.	.	PUNCT
cana-3796	17	1	keywords	keyword	NOUN
cana-3796	17	2	:	:	PUNCT
cana-3796	17	3	handwriting	handwriting	NOUN
cana-3796	17	4	recognition	recognition	NOUN
cana-3796	17	5	,	,	PUNCT
cana-3796	17	6	telugu	telugu	NOUN
cana-3796	17	7	language	language	NOUN
cana-3796	17	8	processing	processing	NOUN
cana-3796	17	9	,	,	PUNCT
cana-3796	17	10	convolutional	convolutional	ADJ
cana-3796	17	11	neural	neural	ADJ
cana-3796	17	12	networks	network	NOUN
cana-3796	17	13	,	,	PUNCT
cana-3796	17	14	sequence	sequence	NOUN
cana-3796	17	15	-	-	PUNCT
cana-3796	17	16	to	to	ADP
cana-3796	17	17	-	-	PUNCT
cana-3796	17	18	sequence	sequence	NOUN
cana-3796	17	19	learning	learning	NOUN
cana-3796	17	20	,	,	PUNCT
cana-3796	17	21	semantic	semantic	ADJ
cana-3796	17	22	analysis	analysis	NOUN
cana-3796	17	23	communications	communication	NOUN
cana-3796	17	24	on	on	ADP
cana-3796	17	25	applied	apply	VERB
cana-3796	17	26	nonlinear	nonlinear	ADJ
cana-3796	17	27	analysis	analysis	NOUN
cana-3796	17	28	issn	issn	NOUN
cana-3796	17	29	:	:	PUNCT
cana-3796	17	30	1074	1074	NUM
cana-3796	17	31	-	-	PUNCT
cana-3796	17	32	133x	133x	NUM
cana-3796	17	33	vol	vol	NOUN
cana-3796	17	34	32	32	NUM
cana-3796	17	35	no	no	NOUN
cana-3796	17	36	.	.	PUNCT
cana-3796	18	1	8s	8s	PROPN
cana-3796	18	2	(	(	PUNCT
cana-3796	18	3	2025	2025	NUM
cana-3796	18	4	)	)	PUNCT
cana-3796	18	5	746	746	NUM
cana-3796	18	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	18	7	i.	i.	NOUN
cana-3796	18	8	introduction	introduction	NOUN
cana-3796	18	9	the	the	DET
cana-3796	18	10	evolution	evolution	NOUN
cana-3796	18	11	of	of	ADP
cana-3796	18	12	automated	automate	VERB
cana-3796	18	13	systems	system	NOUN
cana-3796	18	14	for	for	ADP
cana-3796	18	15	educational	educational	ADJ
cana-3796	18	16	assessment	assessment	NOUN
cana-3796	18	17	has	have	AUX
cana-3796	18	18	garnered	garner	VERB
cana-3796	18	19	significant	significant	ADJ
cana-3796	18	20	research	research	NOUN
cana-3796	18	21	attention	attention	NOUN
cana-3796	18	22	,	,	PUNCT
cana-3796	18	23	particularly	particularly	ADV
cana-3796	18	24	for	for	ADP
cana-3796	18	25	languages	language	NOUN
cana-3796	18	26	with	with	ADP
cana-3796	18	27	complex	complex	ADJ
cana-3796	18	28	scripts	script	NOUN
cana-3796	18	29	like	like	ADP
cana-3796	18	30	telugu	telugu	NOUN
cana-3796	18	31	,	,	PUNCT
cana-3796	18	32	spoken	speak	VERB
cana-3796	18	33	by	by	ADP
cana-3796	18	34	millions	million	NOUN
cana-3796	18	35	in	in	ADP
cana-3796	18	36	india	india	PROPN
cana-3796	18	37	.	.	PUNCT
cana-3796	19	1	telugu	telugu	PROPN
cana-3796	19	2	poses	pose	VERB
cana-3796	19	3	unique	unique	ADJ
cana-3796	19	4	challenges	challenge	NOUN
cana-3796	19	5	due	due	ADP
cana-3796	19	6	to	to	ADP
cana-3796	19	7	its	its	PRON
cana-3796	19	8	intricate	intricate	ADJ
cana-3796	19	9	script	script	NOUN
cana-3796	19	10	and	and	CCONJ
cana-3796	19	11	expansive	expansive	ADJ
cana-3796	19	12	character	character	NOUN
cana-3796	19	13	set	set	NOUN
cana-3796	19	14	,	,	PUNCT
cana-3796	19	15	which	which	PRON
cana-3796	19	16	hinder	hinder	VERB
cana-3796	19	17	the	the	DET
cana-3796	19	18	accuracy	accuracy	NOUN
cana-3796	19	19	,	,	PUNCT
cana-3796	19	20	adaptability	adaptability	NOUN
cana-3796	19	21	,	,	PUNCT
cana-3796	19	22	and	and	CCONJ
cana-3796	19	23	efficiency	efficiency	NOUN
cana-3796	19	24	of	of	ADP
cana-3796	19	25	traditional	traditional	ADJ
cana-3796	19	26	handwriting	handwriting	NOUN
cana-3796	19	27	evaluation	evaluation	NOUN
cana-3796	19	28	methods	method	NOUN
cana-3796	19	29	.	.	PUNCT
cana-3796	20	1	these	these	DET
cana-3796	20	2	limitations	limitation	NOUN
cana-3796	20	3	underscore	underscore	VERB
cana-3796	20	4	the	the	DET
cana-3796	20	5	need	need	NOUN
cana-3796	20	6	for	for	ADP
cana-3796	20	7	advanced	advanced	ADJ
cana-3796	20	8	approaches	approach	NOUN
cana-3796	20	9	to	to	PART
cana-3796	20	10	automate	automate	VERB
cana-3796	20	11	and	and	CCONJ
cana-3796	20	12	enhance	enhance	VERB
cana-3796	20	13	the	the	DET
cana-3796	20	14	evaluation	evaluation	NOUN
cana-3796	20	15	of	of	ADP
cana-3796	20	16	handwritten	handwritten	ADJ
cana-3796	20	17	telugu	telugu	NOUN
cana-3796	20	18	documents	document	NOUN
cana-3796	20	19	.	.	PUNCT
cana-3796	21	1	developing	develop	VERB
cana-3796	21	2	an	an	DET
cana-3796	21	3	automated	automate	VERB
cana-3796	21	4	system	system	NOUN
cana-3796	21	5	for	for	ADP
cana-3796	21	6	telugu	telugu	NOUN
cana-3796	21	7	handwriting	handwriting	NOUN
cana-3796	21	8	evaluation	evaluation	NOUN
cana-3796	21	9	not	not	PART
cana-3796	21	10	only	only	ADV
cana-3796	21	11	promises	promise	VERB
cana-3796	21	12	efficiency	efficiency	NOUN
cana-3796	21	13	and	and	CCONJ
cana-3796	21	14	consistency	consistency	NOUN
cana-3796	21	15	in	in	ADP
cana-3796	21	16	educational	educational	ADJ
cana-3796	21	17	assessments	assessment	NOUN
cana-3796	21	18	but	but	CCONJ
cana-3796	21	19	also	also	ADV
cana-3796	21	20	has	have	VERB
cana-3796	21	21	broader	broad	ADJ
cana-3796	21	22	implications	implication	NOUN
cana-3796	21	23	for	for	ADP
cana-3796	21	24	advancing	advance	VERB
cana-3796	21	25	language	language	NOUN
cana-3796	21	26	processing	processing	NOUN
cana-3796	21	27	technologies	technology	NOUN
cana-3796	21	28	.	.	PUNCT
cana-3796	22	1	such	such	DET
cana-3796	22	2	a	a	DET
cana-3796	22	3	system	system	NOUN
cana-3796	22	4	can	can	AUX
cana-3796	22	5	substantially	substantially	ADV
cana-3796	22	6	reduce	reduce	VERB
cana-3796	22	7	the	the	DET
cana-3796	22	8	time	time	NOUN
cana-3796	22	9	and	and	CCONJ
cana-3796	22	10	effort	effort	NOUN
cana-3796	22	11	required	require	VERB
cana-3796	22	12	for	for	ADP
cana-3796	22	13	manual	manual	ADJ
cana-3796	22	14	grading	grading	NOUN
cana-3796	22	15	while	while	SCONJ
cana-3796	22	16	eliminating	eliminate	VERB
cana-3796	22	17	human	human	ADJ
cana-3796	22	18	bias	bias	NOUN
cana-3796	22	19	,	,	PUNCT
cana-3796	22	20	thereby	thereby	ADV
cana-3796	22	21	ensuring	ensure	VERB
cana-3796	22	22	objective	objective	ADJ
cana-3796	22	23	and	and	CCONJ
cana-3796	22	24	consistent	consistent	ADJ
cana-3796	22	25	results	result	NOUN
cana-3796	22	26	.	.	PUNCT
cana-3796	23	1	existing	exist	VERB
cana-3796	23	2	approaches	approach	NOUN
cana-3796	23	3	to	to	ADP
cana-3796	23	4	telugu	telugu	NOUN
cana-3796	23	5	handwriting	handwriting	NOUN
cana-3796	23	6	recognition	recognition	NOUN
cana-3796	23	7	and	and	CCONJ
cana-3796	23	8	language	language	NOUN
cana-3796	23	9	processing	processing	NOUN
cana-3796	23	10	have	have	AUX
cana-3796	23	11	largely	largely	ADV
cana-3796	23	12	relied	rely	VERB
cana-3796	23	13	on	on	ADP
cana-3796	23	14	traditional	traditional	ADJ
cana-3796	23	15	techniques	technique	NOUN
cana-3796	23	16	that	that	PRON
cana-3796	23	17	often	often	ADV
cana-3796	23	18	struggle	struggle	VERB
cana-3796	23	19	with	with	ADP
cana-3796	23	20	low	low	ADJ
cana-3796	23	21	precision	precision	NOUN
cana-3796	23	22	and	and	CCONJ
cana-3796	23	23	extended	extended	ADJ
cana-3796	23	24	processing	processing	NOUN
cana-3796	23	25	times	time	NOUN
cana-3796	23	26	.	.	PUNCT
cana-3796	24	1	these	these	DET
cana-3796	24	2	methods	method	NOUN
cana-3796	24	3	lack	lack	VERB
cana-3796	24	4	robustness	robustness	NOUN
cana-3796	24	5	in	in	ADP
cana-3796	24	6	handling	handle	VERB
cana-3796	24	7	diverse	diverse	ADJ
cana-3796	24	8	handwriting	handwriting	NOUN
cana-3796	24	9	styles	style	NOUN
cana-3796	24	10	and	and	CCONJ
cana-3796	24	11	fail	fail	VERB
cana-3796	24	12	to	to	PART
cana-3796	24	13	capture	capture	VERB
cana-3796	24	14	the	the	DET
cana-3796	24	15	nuanced	nuanced	ADJ
cana-3796	24	16	semantic	semantic	ADJ
cana-3796	24	17	content	content	NOUN
cana-3796	24	18	of	of	ADP
cana-3796	24	19	written	write	VERB
cana-3796	24	20	responses	response	NOUN
cana-3796	24	21	.	.	PUNCT
cana-3796	25	1	addressing	address	VERB
cana-3796	25	2	these	these	DET
cana-3796	25	3	challenges	challenge	NOUN
cana-3796	25	4	requires	require	VERB
cana-3796	25	5	a	a	DET
cana-3796	25	6	more	more	ADV
cana-3796	25	7	advanced	advanced	ADJ
cana-3796	25	8	and	and	CCONJ
cana-3796	25	9	adaptable	adaptable	ADJ
cana-3796	25	10	solution	solution	NOUN
cana-3796	25	11	capable	capable	ADJ
cana-3796	25	12	of	of	ADP
cana-3796	25	13	accurately	accurately	ADV
cana-3796	25	14	interpreting	interpret	VERB
cana-3796	25	15	the	the	DET
cana-3796	25	16	variability	variability	NOUN
cana-3796	25	17	of	of	ADP
cana-3796	25	18	telugu	telugu	PROPN
cana-3796	25	19	script	script	NOUN
cana-3796	25	20	and	and	CCONJ
cana-3796	25	21	its	its	PRON
cana-3796	25	22	written	write	VERB
cana-3796	25	23	content	content	NOUN
cana-3796	25	24	.	.	PUNCT
cana-3796	26	1	to	to	PART
cana-3796	26	2	address	address	VERB
cana-3796	26	3	these	these	DET
cana-3796	26	4	issues	issue	NOUN
cana-3796	26	5	,	,	PUNCT
cana-3796	26	6	this	this	DET
cana-3796	26	7	paper	paper	NOUN
cana-3796	26	8	presents	present	VERB
cana-3796	26	9	a	a	DET
cana-3796	26	10	comprehensive	comprehensive	ADJ
cana-3796	26	11	system	system	NOUN
cana-3796	26	12	for	for	ADP
cana-3796	26	13	automating	automate	VERB
cana-3796	26	14	the	the	DET
cana-3796	26	15	evaluation	evaluation	NOUN
cana-3796	26	16	of	of	ADP
cana-3796	26	17	handwritten	handwritten	ADJ
cana-3796	26	18	telugu	telugu	NOUN
cana-3796	26	19	answer	answer	NOUN
cana-3796	26	20	scripts	script	NOUN
cana-3796	26	21	.	.	PUNCT
cana-3796	27	1	the	the	DET
cana-3796	27	2	proposed	propose	VERB
cana-3796	27	3	system	system	NOUN
cana-3796	27	4	integrates	integrate	VERB
cana-3796	27	5	sophisticated	sophisticated	ADJ
cana-3796	27	6	image	image	NOUN
cana-3796	27	7	processing	processing	NOUN
cana-3796	27	8	techniques	technique	NOUN
cana-3796	27	9	,	,	PUNCT
cana-3796	27	10	including	include	VERB
cana-3796	27	11	adaptive	adaptive	ADJ
cana-3796	27	12	thresholding	thresholding	NOUN
cana-3796	27	13	for	for	ADP
cana-3796	27	14	binarization	binarization	NOUN
cana-3796	27	15	and	and	CCONJ
cana-3796	27	16	gaussian	gaussian	ADJ
cana-3796	27	17	blurring	blurring	NOUN
cana-3796	27	18	for	for	ADP
cana-3796	27	19	noise	noise	NOUN
cana-3796	27	20	reduction	reduction	NOUN
cana-3796	27	21	,	,	PUNCT
cana-3796	27	22	to	to	PART
cana-3796	27	23	enhance	enhance	VERB
cana-3796	27	24	text	text	NOUN
cana-3796	27	25	clarity	clarity	NOUN
cana-3796	27	26	and	and	CCONJ
cana-3796	27	27	readability	readability	NOUN
cana-3796	27	28	.	.	PUNCT
cana-3796	28	1	data	datum	NOUN
cana-3796	28	2	augmentation	augmentation	NOUN
cana-3796	28	3	methods	method	NOUN
cana-3796	28	4	,	,	PUNCT
cana-3796	28	5	such	such	ADJ
cana-3796	28	6	as	as	ADP
cana-3796	28	7	elastic	elastic	ADJ
cana-3796	28	8	distortions	distortion	NOUN
cana-3796	28	9	and	and	CCONJ
cana-3796	28	10	affine	affine	NOUN
cana-3796	28	11	transformations	transformation	NOUN
cana-3796	28	12	,	,	PUNCT
cana-3796	28	13	further	far	ADV
cana-3796	28	14	improve	improve	VERB
cana-3796	28	15	the	the	DET
cana-3796	28	16	model	model	NOUN
cana-3796	28	17	’s	’s	PART
cana-3796	28	18	ability	ability	NOUN
cana-3796	28	19	to	to	PART
cana-3796	28	20	handle	handle	VERB
cana-3796	28	21	diverse	diverse	ADJ
cana-3796	28	22	handwriting	handwriting	NOUN
cana-3796	28	23	styles	style	NOUN
cana-3796	28	24	.	.	PUNCT
cana-3796	29	1	at	at	ADP
cana-3796	29	2	the	the	DET
cana-3796	29	3	core	core	NOUN
cana-3796	29	4	of	of	ADP
cana-3796	29	5	the	the	DET
cana-3796	29	6	system	system	NOUN
cana-3796	29	7	are	be	AUX
cana-3796	29	8	convolutional	convolutional	ADJ
cana-3796	29	9	neural	neural	ADJ
cana-3796	29	10	networks	network	NOUN
cana-3796	29	11	(	(	PUNCT
cana-3796	29	12	cnns	cnns	PROPN
cana-3796	29	13	)	)	PUNCT
cana-3796	29	14	paired	pair	VERB
cana-3796	29	15	with	with	ADP
cana-3796	29	16	quad	quad	PRON
cana-3796	29	17	long	long	ADJ
cana-3796	29	18	short	short	ADJ
cana-3796	29	19	-	-	PUNCT
cana-3796	29	20	term	term	NOUN
cana-3796	29	21	memory	memory	NOUN
cana-3796	29	22	(	(	PUNCT
cana-3796	29	23	lstm	lstm	NOUN
cana-3796	29	24	)	)	PUNCT
cana-3796	29	25	networks	network	NOUN
cana-3796	29	26	,	,	PUNCT
cana-3796	29	27	optimized	optimize	VERB
cana-3796	29	28	for	for	ADP
cana-3796	29	29	feature	feature	NOUN
cana-3796	29	30	extraction	extraction	NOUN
cana-3796	29	31	and	and	CCONJ
cana-3796	29	32	contextual	contextual	ADJ
cana-3796	29	33	understanding	understanding	NOUN
cana-3796	29	34	of	of	ADP
cana-3796	29	35	telugu	telugu	PROPN
cana-3796	29	36	script	script	NOUN
cana-3796	29	37	.	.	PUNCT
cana-3796	30	1	a	a	DET
cana-3796	30	2	bahdanau	bahdanau	ADJ
cana-3796	30	3	attention	attention	NOUN
cana-3796	30	4	mechanism	mechanism	NOUN
cana-3796	30	5	further	far	ADV
cana-3796	30	6	refines	refine	VERB
cana-3796	30	7	the	the	DET
cana-3796	30	8	model	model	NOUN
cana-3796	30	9	’s	’s	PART
cana-3796	30	10	accuracy	accuracy	NOUN
cana-3796	30	11	by	by	ADP
cana-3796	30	12	focusing	focus	VERB
cana-3796	30	13	on	on	ADP
cana-3796	30	14	nuanced	nuanced	ADJ
cana-3796	30	15	character	character	NOUN
cana-3796	30	16	sequences	sequence	NOUN
cana-3796	30	17	.	.	PUNCT
cana-3796	31	1	this	this	DET
cana-3796	31	2	handwriting	handwriting	NOUN
cana-3796	31	3	recognition	recognition	NOUN
cana-3796	31	4	framework	framework	NOUN
cana-3796	31	5	is	be	AUX
cana-3796	31	6	complemented	complement	VERB
cana-3796	31	7	by	by	ADP
cana-3796	31	8	a	a	DET
cana-3796	31	9	natural	natural	ADJ
cana-3796	31	10	language	language	NOUN
cana-3796	31	11	processing	processing	NOUN
cana-3796	31	12	module	module	NOUN
cana-3796	31	13	that	that	PRON
cana-3796	31	14	leverages	leverage	VERB
cana-3796	31	15	transformer	transformer	NOUN
cana-3796	31	16	-	-	PUNCT
cana-3796	31	17	based	base	VERB
cana-3796	31	18	models	model	NOUN
cana-3796	31	19	,	,	PUNCT
cana-3796	31	20	including	include	VERB
cana-3796	31	21	bert	bert	PROPN
cana-3796	31	22	trained	train	VERB
cana-3796	31	23	on	on	ADP
cana-3796	31	24	telugu	telugu	PROPN
cana-3796	31	25	text	text	NOUN
cana-3796	31	26	.	.	PUNCT
cana-3796	32	1	this	this	DET
cana-3796	32	2	module	module	NOUN
cana-3796	32	3	captures	capture	VERB
cana-3796	32	4	the	the	DET
cana-3796	32	5	syntactic	syntactic	ADJ
cana-3796	32	6	and	and	CCONJ
cana-3796	32	7	semantic	semantic	ADJ
cana-3796	32	8	intricacies	intricacy	NOUN
cana-3796	32	9	of	of	ADP
cana-3796	32	10	the	the	DET
cana-3796	32	11	language	language	NOUN
cana-3796	32	12	,	,	PUNCT
cana-3796	32	13	which	which	PRON
cana-3796	32	14	are	be	AUX
cana-3796	32	15	essential	essential	ADJ
cana-3796	32	16	for	for	ADP
cana-3796	32	17	accurate	accurate	ADJ
cana-3796	32	18	answer	answer	NOUN
cana-3796	32	19	evaluation	evaluation	NOUN
cana-3796	32	20	.	.	PUNCT
cana-3796	33	1	extensive	extensive	ADJ
cana-3796	33	2	testing	testing	NOUN
cana-3796	33	3	on	on	ADP
cana-3796	33	4	varied	varied	ADJ
cana-3796	33	5	datasets	dataset	NOUN
cana-3796	33	6	has	have	AUX
cana-3796	33	7	demonstrated	demonstrate	VERB
cana-3796	33	8	the	the	DET
cana-3796	33	9	system	system	NOUN
cana-3796	33	10	's	's	PART
cana-3796	33	11	superior	superior	ADJ
cana-3796	33	12	performance	performance	NOUN
cana-3796	33	13	over	over	ADP
cana-3796	33	14	existing	exist	VERB
cana-3796	33	15	methods	method	NOUN
cana-3796	33	16	,	,	PUNCT
cana-3796	33	17	with	with	ADP
cana-3796	33	18	significant	significant	ADJ
cana-3796	33	19	improvements	improvement	NOUN
cana-3796	33	20	in	in	ADP
cana-3796	33	21	precision	precision	NOUN
cana-3796	33	22	,	,	PUNCT
cana-3796	33	23	accuracy	accuracy	NOUN
cana-3796	33	24	,	,	PUNCT
cana-3796	33	25	and	and	CCONJ
cana-3796	33	26	processing	processing	NOUN
cana-3796	33	27	speed	speed	NOUN
cana-3796	33	28	for	for	ADP
cana-3796	33	29	both	both	PRON
cana-3796	33	30	character	character	NOUN
cana-3796	33	31	and	and	CCONJ
cana-3796	33	32	sentence	sentence	NOUN
cana-3796	33	33	recognition	recognition	NOUN
cana-3796	33	34	in	in	ADP
cana-3796	33	35	telugu	telugu	PROPN
cana-3796	33	36	.	.	PUNCT
cana-3796	34	1	this	this	DET
cana-3796	34	2	paper	paper	NOUN
cana-3796	34	3	discusses	discuss	VERB
cana-3796	34	4	the	the	DET
cana-3796	34	5	system	system	NOUN
cana-3796	34	6	's	's	PART
cana-3796	34	7	design	design	NOUN
cana-3796	34	8	,	,	PUNCT
cana-3796	34	9	implementation	implementation	NOUN
cana-3796	34	10	,	,	PUNCT
cana-3796	34	11	and	and	CCONJ
cana-3796	34	12	evaluation	evaluation	NOUN
cana-3796	34	13	,	,	PUNCT
cana-3796	34	14	showcasing	showcase	VERB
cana-3796	34	15	its	its	PRON
cana-3796	34	16	transformative	transformative	ADJ
cana-3796	34	17	potential	potential	NOUN
cana-3796	34	18	in	in	ADP
cana-3796	34	19	automated	automate	VERB
cana-3796	34	20	handwriting	handwriting	NOUN
cana-3796	34	21	recognition	recognition	NOUN
cana-3796	34	22	and	and	CCONJ
cana-3796	34	23	language	language	NOUN
cana-3796	34	24	processing	processing	NOUN
cana-3796	34	25	,	,	PUNCT
cana-3796	34	26	particularly	particularly	ADV
cana-3796	34	27	for	for	ADP
cana-3796	34	28	indic	indic	ADJ
cana-3796	34	29	scripts	script	NOUN
cana-3796	34	30	.	.	PUNCT
cana-3796	35	1	this	this	DET
cana-3796	35	2	adaptable	adaptable	ADJ
cana-3796	35	3	and	and	CCONJ
cana-3796	35	4	efficient	efficient	ADJ
cana-3796	35	5	system	system	NOUN
cana-3796	35	6	represents	represent	VERB
cana-3796	35	7	a	a	DET
cana-3796	35	8	substantial	substantial	ADJ
cana-3796	35	9	advancement	advancement	NOUN
cana-3796	35	10	in	in	ADP
cana-3796	35	11	automated	automate	VERB
cana-3796	35	12	educational	educational	ADJ
cana-3796	35	13	assessment	assessment	NOUN
cana-3796	35	14	,	,	PUNCT
cana-3796	35	15	offering	offer	VERB
cana-3796	35	16	a	a	DET
cana-3796	35	17	model	model	NOUN
cana-3796	35	18	that	that	PRON
cana-3796	35	19	could	could	AUX
cana-3796	35	20	be	be	AUX
cana-3796	35	21	extended	extend	VERB
cana-3796	35	22	to	to	ADP
cana-3796	35	23	other	other	ADJ
cana-3796	35	24	complex	complex	ADJ
cana-3796	35	25	languages	language	NOUN
cana-3796	35	26	and	and	CCONJ
cana-3796	35	27	scripts	script	NOUN
cana-3796	35	28	.	.	PUNCT
cana-3796	36	1	1.1	1.1	NUM
cana-3796	36	2	motivation	motivation	NOUN
cana-3796	36	3	this	this	DET
cana-3796	36	4	research	research	NOUN
cana-3796	36	5	is	be	AUX
cana-3796	36	6	driven	drive	VERB
cana-3796	36	7	by	by	ADP
cana-3796	36	8	the	the	DET
cana-3796	36	9	urgent	urgent	ADJ
cana-3796	36	10	need	need	NOUN
cana-3796	36	11	to	to	PART
cana-3796	36	12	improve	improve	VERB
cana-3796	36	13	the	the	DET
cana-3796	36	14	efficiency	efficiency	NOUN
cana-3796	36	15	and	and	CCONJ
cana-3796	36	16	accuracy	accuracy	NOUN
cana-3796	36	17	of	of	ADP
cana-3796	36	18	educational	educational	ADJ
cana-3796	36	19	assessments	assessment	NOUN
cana-3796	36	20	,	,	PUNCT
cana-3796	36	21	particularly	particularly	ADV
cana-3796	36	22	for	for	ADP
cana-3796	36	23	languages	language	NOUN
cana-3796	36	24	with	with	ADP
cana-3796	36	25	intricate	intricate	ADJ
cana-3796	36	26	scripts	script	NOUN
cana-3796	36	27	like	like	ADP
cana-3796	36	28	telugu	telugu	PROPN
cana-3796	36	29	.	.	PUNCT
cana-3796	37	1	in	in	ADP
cana-3796	37	2	many	many	ADJ
cana-3796	37	3	educational	educational	ADJ
cana-3796	37	4	institutions	institution	NOUN
cana-3796	37	5	,	,	PUNCT
cana-3796	37	6	evaluation	evaluation	NOUN
cana-3796	37	7	processes	process	NOUN
cana-3796	37	8	remain	remain	VERB
cana-3796	37	9	manual	manual	ADJ
cana-3796	37	10	,	,	PUNCT
cana-3796	37	11	time	time	NOUN
cana-3796	37	12	-	-	PUNCT
cana-3796	37	13	consuming	consume	VERB
cana-3796	37	14	,	,	PUNCT
cana-3796	37	15	and	and	CCONJ
cana-3796	37	16	prone	prone	ADJ
cana-3796	37	17	to	to	ADP
cana-3796	37	18	human	human	ADJ
cana-3796	37	19	error	error	NOUN
cana-3796	37	20	and	and	CCONJ
cana-3796	37	21	bias	bias	NOUN
cana-3796	37	22	,	,	PUNCT
cana-3796	37	23	leading	lead	VERB
cana-3796	37	24	to	to	ADP
cana-3796	37	25	inconsistencies	inconsistency	NOUN
cana-3796	37	26	in	in	ADP
cana-3796	37	27	grading	grade	VERB
cana-3796	37	28	.	.	PUNCT
cana-3796	38	1	these	these	DET
cana-3796	38	2	challenges	challenge	NOUN
cana-3796	38	3	are	be	AUX
cana-3796	38	4	exacerbated	exacerbate	VERB
cana-3796	38	5	in	in	ADP
cana-3796	38	6	the	the	DET
cana-3796	38	7	case	case	NOUN
cana-3796	38	8	of	of	ADP
cana-3796	38	9	telugu	telugu	NOUN
cana-3796	38	10	due	due	ADP
cana-3796	38	11	to	to	ADP
cana-3796	38	12	its	its	PRON
cana-3796	38	13	complex	complex	ADJ
cana-3796	38	14	character	character	NOUN
cana-3796	38	15	set	set	VERB
cana-3796	38	16	and	and	CCONJ
cana-3796	38	17	script	script	NOUN
cana-3796	38	18	structure	structure	NOUN
cana-3796	38	19	,	,	PUNCT
cana-3796	38	20	making	make	VERB
cana-3796	38	21	manual	manual	ADJ
cana-3796	38	22	evaluation	evaluation	NOUN
cana-3796	38	23	especially	especially	ADV
cana-3796	38	24	difficult	difficult	ADJ
cana-3796	38	25	and	and	CCONJ
cana-3796	38	26	prone	prone	ADJ
cana-3796	38	27	to	to	ADP
cana-3796	38	28	variability	variability	NOUN
cana-3796	38	29	.	.	PUNCT
cana-3796	39	1	automating	automate	VERB
cana-3796	39	2	the	the	DET
cana-3796	39	3	assessment	assessment	NOUN
cana-3796	39	4	process	process	NOUN
cana-3796	39	5	for	for	ADP
cana-3796	39	6	telugu	telugu	PROPN
cana-3796	39	7	offers	offer	VERB
cana-3796	39	8	an	an	DET
cana-3796	39	9	opportunity	opportunity	NOUN
cana-3796	39	10	to	to	PART
cana-3796	39	11	enhance	enhance	VERB
cana-3796	39	12	the	the	DET
cana-3796	39	13	speed	speed	NOUN
cana-3796	39	14	and	and	CCONJ
cana-3796	39	15	objectivity	objectivity	NOUN
cana-3796	39	16	of	of	ADP
cana-3796	39	17	evaluations	evaluation	NOUN
cana-3796	39	18	while	while	SCONJ
cana-3796	39	19	ensuring	ensure	VERB
cana-3796	39	20	a	a	DET
cana-3796	39	21	fairer	fair	ADJ
cana-3796	39	22	and	and	CCONJ
cana-3796	39	23	more	more	ADV
cana-3796	39	24	consistent	consistent	ADJ
cana-3796	39	25	grading	grade	VERB
cana-3796	39	26	system	system	NOUN
cana-3796	39	27	.	.	PUNCT
cana-3796	40	1	additionally	additionally	ADV
cana-3796	40	2	,	,	PUNCT
cana-3796	40	3	with	with	ADP
cana-3796	40	4	the	the	DET
cana-3796	40	5	growing	grow	VERB
cana-3796	40	6	emphasis	emphasis	NOUN
cana-3796	40	7	on	on	ADP
cana-3796	40	8	digital	digital	ADJ
cana-3796	40	9	solutions	solution	NOUN
cana-3796	40	10	in	in	ADP
cana-3796	40	11	education	education	NOUN
cana-3796	40	12	,	,	PUNCT
cana-3796	40	13	an	an	DET
cana-3796	40	14	automated	automate	VERB
cana-3796	40	15	telugu	telugu	NOUN
cana-3796	40	16	handwriting	handwriting	NOUN
cana-3796	40	17	recognition	recognition	NOUN
cana-3796	40	18	system	system	NOUN
cana-3796	40	19	could	could	AUX
cana-3796	40	20	facilitate	facilitate	VERB
cana-3796	40	21	the	the	DET
cana-3796	40	22	digitization	digitization	NOUN
cana-3796	40	23	of	of	ADP
cana-3796	40	24	exams	exam	NOUN
cana-3796	40	25	,	,	PUNCT
cana-3796	40	26	streamlining	streamline	VERB
cana-3796	40	27	workflows	workflow	NOUN
cana-3796	40	28	and	and	CCONJ
cana-3796	40	29	simplifying	simplify	VERB
cana-3796	40	30	document	document	NOUN
cana-3796	40	31	management	management	NOUN
cana-3796	40	32	.	.	PUNCT
cana-3796	41	1	beyond	beyond	ADP
cana-3796	41	2	the	the	DET
cana-3796	41	3	immediate	immediate	ADJ
cana-3796	41	4	benefits	benefit	NOUN
cana-3796	41	5	in	in	ADP
cana-3796	41	6	educational	educational	ADJ
cana-3796	41	7	assessment	assessment	NOUN
cana-3796	41	8	,	,	PUNCT
cana-3796	41	9	the	the	DET
cana-3796	41	10	development	development	NOUN
cana-3796	41	11	of	of	ADP
cana-3796	41	12	a	a	DET
cana-3796	41	13	robust	robust	ADJ
cana-3796	41	14	automated	automate	VERB
cana-3796	41	15	system	system	NOUN
cana-3796	41	16	for	for	ADP
cana-3796	41	17	telugu	telugu	NOUN
cana-3796	41	18	handwriting	handwriting	NOUN
cana-3796	41	19	recognition	recognition	NOUN
cana-3796	41	20	addresses	address	VERB
cana-3796	41	21	a	a	DET
cana-3796	41	22	critical	critical	ADJ
cana-3796	41	23	gap	gap	NOUN
cana-3796	41	24	in	in	ADP
cana-3796	41	25	language	language	NOUN
cana-3796	41	26	processing	processing	NOUN
cana-3796	41	27	technology	technology	NOUN
cana-3796	41	28	for	for	ADP
cana-3796	41	29	complex	complex	ADJ
cana-3796	41	30	scripts	script	NOUN
cana-3796	41	31	.	.	PUNCT
cana-3796	42	1	as	as	ADP
cana-3796	42	2	one	one	NUM
cana-3796	42	3	of	of	ADP
cana-3796	42	4	the	the	DET
cana-3796	42	5	most	most	ADV
cana-3796	42	6	widely	widely	ADV
cana-3796	42	7	spoken	speak	VERB
cana-3796	42	8	languages	language	NOUN
cana-3796	42	9	in	in	ADP
cana-3796	42	10	india	india	PROPN
cana-3796	42	11	,	,	PUNCT
cana-3796	42	12	telugu	telugu	PROPN
cana-3796	42	13	represents	represent	VERB
cana-3796	42	14	a	a	DET
cana-3796	42	15	substantial	substantial	ADJ
cana-3796	42	16	user	user	NOUN
cana-3796	42	17	base	base	NOUN
cana-3796	42	18	,	,	PUNCT
cana-3796	42	19	underscoring	underscore	VERB
cana-3796	42	20	the	the	DET
cana-3796	42	21	significance	significance	NOUN
cana-3796	42	22	of	of	ADP
cana-3796	42	23	this	this	DET
cana-3796	42	24	research	research	NOUN
cana-3796	42	25	not	not	PART
cana-3796	42	26	only	only	ADV
cana-3796	42	27	in	in	ADP
cana-3796	42	28	education	education	NOUN
cana-3796	42	29	but	but	CCONJ
cana-3796	42	30	also	also	ADV
cana-3796	42	31	in	in	ADP
cana-3796	42	32	advancing	advance	VERB
cana-3796	42	33	digital	digital	ADJ
cana-3796	42	34	document	document	NOUN
cana-3796	42	35	processing	processing	NOUN
cana-3796	42	36	and	and	CCONJ
cana-3796	42	37	language	language	NOUN
cana-3796	42	38	understanding	understanding	NOUN
cana-3796	42	39	technologies	technology	NOUN
cana-3796	42	40	.	.	PUNCT
cana-3796	43	1	communications	communication	NOUN
cana-3796	43	2	on	on	ADP
cana-3796	43	3	applied	apply	VERB
cana-3796	43	4	nonlinear	nonlinear	ADJ
cana-3796	43	5	analysis	analysis	NOUN
cana-3796	43	6	issn	issn	NOUN
cana-3796	43	7	:	:	PUNCT
cana-3796	43	8	1074	1074	NUM
cana-3796	43	9	-	-	PUNCT
cana-3796	43	10	133x	133x	NUM
cana-3796	43	11	vol	vol	NOUN
cana-3796	43	12	32	32	NUM
cana-3796	43	13	no	no	NOUN
cana-3796	43	14	.	.	PUNCT
cana-3796	44	1	8s	8s	PROPN
cana-3796	44	2	(	(	PUNCT
cana-3796	44	3	2025	2025	NUM
cana-3796	44	4	)	)	PUNCT
cana-3796	44	5	747	747	NUM
cana-3796	44	6	https://internationalpubls.com	https://internationalpubls.com	SYM
cana-3796	44	7	1.2	1.2	NUM
cana-3796	44	8	novelty	novelty	NOUN
cana-3796	44	9	of	of	ADP
cana-3796	44	10	this	this	DET
cana-3796	44	11	work	work	NOUN
cana-3796	44	12	this	this	DET
cana-3796	44	13	research	research	NOUN
cana-3796	44	14	introduces	introduce	VERB
cana-3796	44	15	a	a	DET
cana-3796	44	16	quad	quad	ADV
cana-3796	44	17	lstm	lstm	NOUN
cana-3796	44	18	-	-	PUNCT
cana-3796	44	19	based	base	VERB
cana-3796	44	20	deep	deep	ADJ
cana-3796	44	21	learning	learning	NOUN
cana-3796	44	22	model	model	NOUN
cana-3796	44	23	tailored	tailor	VERB
cana-3796	44	24	for	for	ADP
cana-3796	44	25	handwritten	handwritten	ADJ
cana-3796	44	26	telugu	telugu	PROPN
cana-3796	44	27	answer	answer	NOUN
cana-3796	44	28	script	script	NOUN
cana-3796	44	29	analysis	analysis	NOUN
cana-3796	44	30	,	,	PUNCT
cana-3796	44	31	addressing	address	VERB
cana-3796	44	32	the	the	DET
cana-3796	44	33	challenges	challenge	NOUN
cana-3796	44	34	posed	pose	VERB
cana-3796	44	35	by	by	ADP
cana-3796	44	36	complex	complex	ADJ
cana-3796	44	37	scripts	script	NOUN
cana-3796	44	38	with	with	ADP
cana-3796	44	39	high	high	ADJ
cana-3796	44	40	context	context	NOUN
cana-3796	44	41	dependencies	dependency	NOUN
cana-3796	44	42	.	.	PUNCT
cana-3796	45	1	it	it	PRON
cana-3796	45	2	integrates	integrate	VERB
cana-3796	45	3	advanced	advanced	ADJ
cana-3796	45	4	architectures	architecture	NOUN
cana-3796	45	5	such	such	ADJ
cana-3796	45	6	as	as	ADP
cana-3796	45	7	quad	quad	NOUN
cana-3796	45	8	lstms	lstms	NOUN
cana-3796	45	9	with	with	ADP
cana-3796	45	10	bahdanau	bahdanau	ADJ
cana-3796	45	11	attention	attention	NOUN
cana-3796	45	12	mechanisms	mechanism	NOUN
cana-3796	45	13	and	and	CCONJ
cana-3796	45	14	cnns	cnn	NOUN
cana-3796	45	15	(	(	PUNCT
cana-3796	45	16	resnet101	resnet101	PROPN
cana-3796	45	17	,	,	PUNCT
cana-3796	45	18	inception	inception	NOUN
cana-3796	45	19	)	)	PUNCT
cana-3796	45	20	for	for	ADP
cana-3796	45	21	superior	superior	ADJ
cana-3796	45	22	feature	feature	NOUN
cana-3796	45	23	extraction	extraction	NOUN
cana-3796	45	24	and	and	CCONJ
cana-3796	45	25	sequence	sequence	NOUN
cana-3796	45	26	understanding	understanding	NOUN
cana-3796	45	27	.	.	PUNCT
cana-3796	46	1	the	the	DET
cana-3796	46	2	novelty	novelty	NOUN
cana-3796	46	3	lies	lie	VERB
cana-3796	46	4	in	in	ADP
cana-3796	46	5	leveraging	leverage	VERB
cana-3796	46	6	transformerbased	transformerbase	VERB
cana-3796	46	7	models	model	NOUN
cana-3796	46	8	like	like	ADP
cana-3796	46	9	bert	bert	PROPN
cana-3796	46	10	,	,	PUNCT
cana-3796	46	11	fine	fine	ADV
cana-3796	46	12	-	-	PUNCT
cana-3796	46	13	tuned	tune	VERB
cana-3796	46	14	specifically	specifically	ADV
cana-3796	46	15	for	for	ADP
cana-3796	46	16	telugu	telugu	NOUN
cana-3796	46	17	,	,	PUNCT
cana-3796	46	18	to	to	PART
cana-3796	46	19	enhance	enhance	VERB
cana-3796	46	20	semantic	semantic	ADJ
cana-3796	46	21	analysis	analysis	NOUN
cana-3796	46	22	for	for	ADP
cana-3796	46	23	subjective	subjective	ADJ
cana-3796	46	24	assessments	assessment	NOUN
cana-3796	46	25	.	.	PUNCT
cana-3796	47	1	preprocessing	preprocesse	VERB
cana-3796	47	2	techniques	technique	NOUN
cana-3796	47	3	,	,	PUNCT
cana-3796	47	4	including	include	VERB
cana-3796	47	5	adaptive	adaptive	ADJ
cana-3796	47	6	thresholding	thresholding	NOUN
cana-3796	47	7	and	and	CCONJ
cana-3796	47	8	data	datum	NOUN
cana-3796	47	9	augmentation	augmentation	NOUN
cana-3796	47	10	,	,	PUNCT
cana-3796	47	11	ensure	ensure	VERB
cana-3796	47	12	robustness	robustness	NOUN
cana-3796	47	13	across	across	ADP
cana-3796	47	14	diverse	diverse	ADJ
cana-3796	47	15	handwriting	handwriting	NOUN
cana-3796	47	16	styles	style	NOUN
cana-3796	47	17	.	.	PUNCT
cana-3796	48	1	this	this	DET
cana-3796	48	2	approach	approach	NOUN
cana-3796	48	3	significantly	significantly	ADV
cana-3796	48	4	outperforms	outperform	VERB
cana-3796	48	5	traditional	traditional	ADJ
cana-3796	48	6	systems	system	NOUN
cana-3796	48	7	,	,	PUNCT
cana-3796	48	8	setting	set	VERB
cana-3796	48	9	a	a	DET
cana-3796	48	10	new	new	ADJ
cana-3796	48	11	benchmark	benchmark	NOUN
cana-3796	48	12	in	in	ADP
cana-3796	48	13	automated	automate	VERB
cana-3796	48	14	educational	educational	ADJ
cana-3796	48	15	assessments	assessment	NOUN
cana-3796	48	16	for	for	ADP
cana-3796	48	17	indic	indic	ADJ
cana-3796	48	18	scripts	script	NOUN
cana-3796	48	19	.	.	PUNCT
cana-3796	49	1	ii	ii	X
cana-3796	49	2	.	.	PROPN
cana-3796	49	3	related	relate	VERB
cana-3796	49	4	work	work	NOUN
cana-3796	49	5	advancements	advancement	NOUN
cana-3796	49	6	in	in	ADP
cana-3796	49	7	optical	optical	ADJ
cana-3796	49	8	character	character	NOUN
cana-3796	49	9	recognition	recognition	NOUN
cana-3796	49	10	(	(	PUNCT
cana-3796	49	11	ocr	ocr	PROPN
cana-3796	49	12	)	)	PUNCT
cana-3796	49	13	have	have	AUX
cana-3796	49	14	been	be	AUX
cana-3796	49	15	transformative	transformative	ADJ
cana-3796	49	16	across	across	ADP
cana-3796	49	17	various	various	ADJ
cana-3796	49	18	domains	domain	NOUN
cana-3796	49	19	,	,	PUNCT
cana-3796	49	20	including	include	VERB
cana-3796	49	21	handwritten	handwritten	ADJ
cana-3796	49	22	character	character	NOUN
cana-3796	49	23	recognition	recognition	NOUN
cana-3796	49	24	,	,	PUNCT
cana-3796	49	25	scene	scene	NOUN
cana-3796	49	26	text	text	NOUN
cana-3796	49	27	detection	detection	NOUN
cana-3796	49	28	,	,	PUNCT
cana-3796	49	29	and	and	CCONJ
cana-3796	49	30	intelligent	intelligent	ADJ
cana-3796	49	31	transportation	transportation	NOUN
cana-3796	49	32	applications	application	NOUN
cana-3796	49	33	.	.	PUNCT
cana-3796	50	1	yavariabdi	yavariabdi	PROPN
cana-3796	50	2	et	et	PROPN
cana-3796	50	3	al	al	PROPN
cana-3796	50	4	.	.	PROPN
cana-3796	50	5	presented	present	VERB
cana-3796	50	6	the	the	DET
cana-3796	50	7	cardis	cardi	NOUN
cana-3796	50	8	dataset	dataset	VERB
cana-3796	50	9	to	to	PART
cana-3796	50	10	enhance	enhance	VERB
cana-3796	50	11	ocr	ocr	NOUN
cana-3796	50	12	for	for	ADP
cana-3796	50	13	swedish	swedish	ADJ
cana-3796	50	14	historical	historical	ADJ
cana-3796	50	15	handwritten	handwritten	ADJ
cana-3796	50	16	characters	character	NOUN
cana-3796	51	1	[	[	X
cana-3796	51	2	1	1	NUM
cana-3796	51	3	]	]	PUNCT
cana-3796	51	4	.	.	PUNCT
cana-3796	52	1	rasheed	rasheed	VERB
cana-3796	52	2	et	et	PROPN
cana-3796	52	3	al	al	PROPN
cana-3796	52	4	.	.	PROPN
cana-3796	52	5	utilized	utilize	VERB
cana-3796	52	6	transfer	transfer	NOUN
cana-3796	52	7	learning	learning	NOUN
cana-3796	52	8	and	and	CCONJ
cana-3796	52	9	augmentation	augmentation	NOUN
cana-3796	52	10	with	with	ADP
cana-3796	52	11	alexnet	alexnet	NOUN
cana-3796	52	12	for	for	ADP
cana-3796	52	13	urdu	urdu	PROPN
cana-3796	52	14	characters	character	NOUN
cana-3796	52	15	and	and	CCONJ
cana-3796	52	16	digits	digit	NOUN
cana-3796	52	17	,	,	PUNCT
cana-3796	52	18	emphasizing	emphasize	VERB
cana-3796	52	19	the	the	DET
cana-3796	52	20	need	need	NOUN
cana-3796	52	21	for	for	ADP
cana-3796	52	22	tailored	tailor	VERB
cana-3796	52	23	ocr	ocr	ADJ
cana-3796	52	24	systems	system	NOUN
cana-3796	52	25	for	for	ADP
cana-3796	52	26	underrepresented	underrepresented	ADJ
cana-3796	52	27	languages	language	NOUN
cana-3796	52	28	[	[	X
cana-3796	52	29	2	2	NUM
cana-3796	52	30	]	]	PUNCT
cana-3796	52	31	.	.	PUNCT
cana-3796	53	1	buoy	buoy	NOUN
cana-3796	53	2	et	et	PROPN
cana-3796	53	3	al	al	PROPN
cana-3796	53	4	.	.	PROPN
cana-3796	53	5	developed	develop	VERB
cana-3796	53	6	a	a	DET
cana-3796	53	7	lowresource	lowresource	NOUN
cana-3796	53	8	baseline	baseline	NOUN
cana-3796	53	9	for	for	ADP
cana-3796	53	10	khmer	khmer	PROPN
cana-3796	53	11	ocr	ocr	PROPN
cana-3796	53	12	,	,	PUNCT
cana-3796	53	13	addressing	address	VERB
cana-3796	53	14	linguistic	linguistic	ADJ
cana-3796	53	15	preservation	preservation	NOUN
cana-3796	53	16	challenges	challenge	NOUN
cana-3796	53	17	[	[	X
cana-3796	53	18	3	3	NUM
cana-3796	53	19	]	]	PUNCT
cana-3796	53	20	.	.	PUNCT
cana-3796	54	1	techniques	technique	NOUN
cana-3796	54	2	by	by	ADP
cana-3796	54	3	li	li	PROPN
cana-3796	54	4	et	et	PROPN
cana-3796	54	5	al	al	PROPN
cana-3796	54	6	.	.	PROPN
cana-3796	54	7	emphasized	emphasize	VERB
cana-3796	54	8	character	character	NOUN
cana-3796	54	9	-	-	PUNCT
cana-3796	54	10	aware	aware	ADJ
cana-3796	54	11	sampling	sampling	NOUN
cana-3796	54	12	for	for	ADP
cana-3796	54	13	scene	scene	NOUN
cana-3796	54	14	text	text	NOUN
cana-3796	54	15	recognition	recognition	NOUN
cana-3796	54	16	in	in	ADP
cana-3796	54	17	uncontrolled	uncontrolled	ADJ
cana-3796	54	18	environments	environment	NOUN
cana-3796	54	19	[	[	X
cana-3796	54	20	4	4	NUM
cana-3796	54	21	]	]	PUNCT
cana-3796	54	22	.	.	PUNCT
cana-3796	55	1	zhang	zhang	PROPN
cana-3796	55	2	et	et	PROPN
cana-3796	55	3	al	al	PROPN
cana-3796	55	4	.	.	PROPN
cana-3796	55	5	and	and	CCONJ
cana-3796	55	6	wang	wang	PROPN
cana-3796	55	7	et	et	PROPN
cana-3796	55	8	al	al	PROPN
cana-3796	55	9	.	.	PROPN
cana-3796	55	10	demonstrated	demonstrate	VERB
cana-3796	55	11	the	the	DET
cana-3796	55	12	breadth	breadth	NOUN
cana-3796	55	13	of	of	ADP
cana-3796	55	14	ocr	ocr	PROPN
cana-3796	55	15	’s	’s	PART
cana-3796	55	16	utility	utility	NOUN
cana-3796	55	17	in	in	ADP
cana-3796	55	18	industrial	industrial	ADJ
cana-3796	55	19	applications	application	NOUN
cana-3796	55	20	[	[	X
cana-3796	55	21	5][6	5][6	NUM
cana-3796	55	22	]	]	PUNCT
cana-3796	55	23	.	.	PUNCT
cana-3796	56	1	coquenet	coquenet	PROPN
cana-3796	56	2	et	et	PROPN
cana-3796	56	3	al	al	PROPN
cana-3796	56	4	.	.	PROPN
cana-3796	56	5	introduced	introduce	VERB
cana-3796	56	6	a	a	DET
cana-3796	56	7	vertical	vertical	ADJ
cana-3796	56	8	attention	attention	NOUN
cana-3796	56	9	network	network	NOUN
cana-3796	56	10	for	for	ADP
cana-3796	56	11	recognizing	recognize	VERB
cana-3796	56	12	long	long	ADJ
cana-3796	56	13	paragraph	paragraph	NOUN
cana-3796	56	14	handwritten	handwritten	ADJ
cana-3796	56	15	text	text	NOUN
cana-3796	56	16	[	[	X
cana-3796	56	17	7	7	NUM
cana-3796	56	18	]	]	PUNCT
cana-3796	56	19	,	,	PUNCT
cana-3796	56	20	while	while	SCONJ
cana-3796	56	21	wu	wu	PROPN
cana-3796	56	22	et	et	PROPN
cana-3796	56	23	al	al	PROPN
cana-3796	56	24	.	.	PROPN
cana-3796	57	1	and	and	CCONJ
cana-3796	57	2	xue	xue	PROPN
cana-3796	57	3	et	et	PROPN
cana-3796	57	4	al	al	PROPN
cana-3796	57	5	.	.	PROPN
cana-3796	57	6	employed	employ	VERB
cana-3796	57	7	novel	novel	ADJ
cana-3796	57	8	architectures	architecture	NOUN
cana-3796	57	9	to	to	PART
cana-3796	57	10	enhance	enhance	VERB
cana-3796	57	11	scene	scene	NOUN
cana-3796	57	12	text	text	NOUN
cana-3796	57	13	recognition	recognition	NOUN
cana-3796	58	1	[	[	X
cana-3796	58	2	8][11	8][11	NOUN
cana-3796	58	3	]	]	PUNCT
cana-3796	58	4	.	.	PUNCT
cana-3796	59	1	deng	deng	PROPN
cana-3796	59	2	et	et	PROPN
cana-3796	59	3	al	al	PROPN
cana-3796	59	4	.	.	PROPN
cana-3796	59	5	focused	focus	VERB
cana-3796	59	6	on	on	ADP
cana-3796	59	7	end	end	NOUN
cana-3796	59	8	-	-	PUNCT
cana-3796	59	9	toend	toend	NOUN
cana-3796	59	10	tag	tag	NOUN
cana-3796	59	11	recognition	recognition	NOUN
cana-3796	59	12	for	for	ADP
cana-3796	59	13	industrial	industrial	ADJ
cana-3796	59	14	meters	meter	NOUN
cana-3796	59	15	,	,	PUNCT
cana-3796	59	16	showcasing	showcase	VERB
cana-3796	59	17	ocr	ocr	PROPN
cana-3796	59	18	’s	’s	PART
cana-3796	59	19	applied	apply	VERB
cana-3796	59	20	potential	potential	NOUN
cana-3796	60	1	[	[	X
cana-3796	60	2	9	9	NUM
cana-3796	60	3	]	]	PUNCT
cana-3796	60	4	.	.	PUNCT
cana-3796	61	1	r.	r.	PROPN
cana-3796	61	2	d.	d.	PROPN
cana-3796	61	3	r	r	PROPN
cana-3796	61	4	et	et	PROPN
cana-3796	61	5	al	al	PROPN
cana-3796	61	6	.	.	PROPN
cana-3796	61	7	proposed	propose	VERB
cana-3796	61	8	a	a	DET
cana-3796	61	9	hybrid	hybrid	ADJ
cana-3796	61	10	approach	approach	NOUN
cana-3796	61	11	for	for	ADP
cana-3796	61	12	ancient	ancient	ADJ
cana-3796	61	13	tamil	tamil	PROPN
cana-3796	61	14	character	character	NOUN
cana-3796	61	15	recognition	recognition	NOUN
cana-3796	61	16	,	,	PUNCT
cana-3796	61	17	underscoring	underscore	VERB
cana-3796	61	18	ocr	ocr	PROPN
cana-3796	61	19	’s	’s	PART
cana-3796	61	20	cultural	cultural	ADJ
cana-3796	61	21	importance	importance	NOUN
cana-3796	61	22	[	[	X
cana-3796	61	23	10	10	NUM
cana-3796	61	24	]	]	PUNCT
cana-3796	61	25	.	.	PUNCT
cana-3796	62	1	hussain	hussain	PROPN
cana-3796	62	2	et	et	PROPN
cana-3796	62	3	al	al	PROPN
cana-3796	62	4	.	.	PROPN
cana-3796	62	5	presented	present	VERB
cana-3796	62	6	the	the	DET
cana-3796	62	7	phti	phti	NOUN
cana-3796	62	8	image	image	NOUN
cana-3796	62	9	base	base	NOUN
cana-3796	62	10	for	for	ADP
cana-3796	62	11	pashto	pashto	NOUN
cana-3796	62	12	,	,	PUNCT
cana-3796	62	13	and	and	CCONJ
cana-3796	62	14	ott	ott	PROPN
cana-3796	62	15	et	et	PROPN
cana-3796	62	16	al	al	PROPN
cana-3796	62	17	.	.	PROPN
cana-3796	62	18	investigated	investigate	VERB
cana-3796	62	19	cross	cross	ADJ
cana-3796	62	20	-	-	ADJ
cana-3796	62	21	modal	modal	ADJ
cana-3796	62	22	representation	representation	NOUN
cana-3796	62	23	learning	learn	VERB
cana-3796	63	1	[	[	X
cana-3796	63	2	12][13	12][13	PROPN
cana-3796	63	3	]	]	PUNCT
cana-3796	63	4	.	.	PUNCT
cana-3796	64	1	selvam	selvam	PROPN
cana-3796	64	2	et	et	PROPN
cana-3796	64	3	al	al	PROPN
cana-3796	64	4	.	.	PROPN
cana-3796	64	5	and	and	CCONJ
cana-3796	64	6	fan	fan	PROPN
cana-3796	64	7	and	and	CCONJ
cana-3796	64	8	zhao	zhao	PROPN
cana-3796	64	9	introduced	introduce	VERB
cana-3796	64	10	transformer	transformer	NOUN
cana-3796	64	11	-	-	PUNCT
cana-3796	64	12	based	base	VERB
cana-3796	64	13	frameworks	framework	NOUN
cana-3796	64	14	and	and	CCONJ
cana-3796	64	15	methods	method	NOUN
cana-3796	64	16	for	for	ADP
cana-3796	64	17	real	real	ADJ
cana-3796	64	18	-	-	PUNCT
cana-3796	64	19	world	world	NOUN
cana-3796	64	20	license	license	NOUN
cana-3796	64	21	plate	plate	NOUN
cana-3796	64	22	recognition	recognition	NOUN
cana-3796	64	23	,	,	PUNCT
cana-3796	64	24	respectively	respectively	ADV
cana-3796	64	25	[	[	X
cana-3796	64	26	14][15	14][15	NUM
cana-3796	64	27	]	]	PUNCT
cana-3796	64	28	.	.	PUNCT
cana-3796	65	1	tayyab	tayyab	PROPN
cana-3796	65	2	et	et	PROPN
cana-3796	65	3	al	al	PROPN
cana-3796	65	4	.	.	PROPN
cana-3796	65	5	and	and	CCONJ
cana-3796	65	6	malhotra	malhotra	PROPN
cana-3796	65	7	&	&	CCONJ
cana-3796	65	8	addis	addis	PROPN
cana-3796	65	9	concentrated	concentrate	VERB
cana-3796	65	10	on	on	ADP
cana-3796	65	11	real	real	ADJ
cana-3796	65	12	-	-	PUNCT
cana-3796	65	13	time	time	NOUN
cana-3796	65	14	arabic	arabic	ADJ
cana-3796	65	15	scripting	scripting	NOUN
cana-3796	65	16	recognition	recognition	NOUN
cana-3796	65	17	and	and	CCONJ
cana-3796	65	18	historical	historical	ADJ
cana-3796	65	19	ethiopic	ethiopic	ADJ
cana-3796	65	20	text	text	NOUN
cana-3796	65	21	digitization	digitization	NOUN
cana-3796	66	1	[	[	X
cana-3796	66	2	16][17	16][17	NUM
cana-3796	66	3	]	]	PUNCT
cana-3796	66	4	.	.	PUNCT
cana-3796	67	1	fanjie	fanjie	PROPN
cana-3796	67	2	et	et	PROPN
cana-3796	67	3	al	al	PROPN
cana-3796	67	4	.	.	PROPN
cana-3796	67	5	created	create	VERB
cana-3796	67	6	key	key	ADJ
cana-3796	67	7	datasets	dataset	NOUN
cana-3796	67	8	for	for	ADP
cana-3796	67	9	uyghur	uyghur	ADJ
cana-3796	67	10	scene	scene	NOUN
cana-3796	67	11	text	text	NOUN
cana-3796	67	12	recognition	recognition	NOUN
cana-3796	67	13	,	,	PUNCT
cana-3796	67	14	while	while	SCONJ
cana-3796	67	15	zhu	zhu	PROPN
cana-3796	67	16	et	et	PROPN
cana-3796	67	17	al	al	PROPN
cana-3796	67	18	.	.	PROPN
cana-3796	67	19	proposed	propose	VERB
cana-3796	67	20	an	an	DET
cana-3796	67	21	ocr	ocr	PROPN
cana-3796	67	22	-	-	PUNCT
cana-3796	67	23	rcnn	rcnn	NOUN
cana-3796	67	24	framework	framework	NOUN
cana-3796	67	25	for	for	ADP
cana-3796	67	26	elevator	elevator	NOUN
cana-3796	67	27	button	button	NOUN
cana-3796	67	28	recognition	recognition	NOUN
cana-3796	67	29	,	,	PUNCT
cana-3796	67	30	highlighting	highlight	VERB
cana-3796	67	31	practical	practical	ADJ
cana-3796	67	32	ocr	ocr	ADJ
cana-3796	67	33	applications	application	NOUN
cana-3796	68	1	[	[	X
cana-3796	68	2	18][19	18][19	NUM
cana-3796	68	3	]	]	PUNCT
cana-3796	68	4	.	.	PUNCT
cana-3796	69	1	anbukkarasi	anbukkarasi	PROPN
cana-3796	69	2	et	et	PROPN
cana-3796	69	3	al	al	PROPN
cana-3796	69	4	.	.	PROPN
cana-3796	69	5	advanced	advanced	ADJ
cana-3796	69	6	text	text	NOUN
cana-3796	69	7	detection	detection	NOUN
cana-3796	69	8	across	across	ADP
cana-3796	69	9	various	various	ADJ
cana-3796	69	10	media	medium	NOUN
cana-3796	69	11	,	,	PUNCT
cana-3796	69	12	and	and	CCONJ
cana-3796	69	13	chandio	chandio	NOUN
cana-3796	69	14	et	et	PROPN
cana-3796	69	15	al	al	PROPN
cana-3796	69	16	.	.	PROPN
cana-3796	69	17	tackled	tackle	VERB
cana-3796	69	18	cursive	cursive	ADJ
cana-3796	69	19	text	text	NOUN
cana-3796	69	20	recognition	recognition	NOUN
cana-3796	69	21	using	use	VERB
cana-3796	69	22	deep	deep	ADJ
cana-3796	69	23	learning	learning	NOUN
cana-3796	70	1	[	[	X
cana-3796	70	2	20][21	20][21	PROPN
cana-3796	70	3	]	]	X
cana-3796	70	4	.	.	PUNCT
cana-3796	71	1	yang	yang	PROPN
cana-3796	71	2	et	et	PROPN
cana-3796	71	3	al	al	PROPN
cana-3796	71	4	.	.	PROPN
cana-3796	71	5	demonstrated	demonstrate	VERB
cana-3796	71	6	ocr	ocr	PROPN
cana-3796	71	7	’s	’s	PART
cana-3796	71	8	potential	potential	NOUN
cana-3796	71	9	in	in	ADP
cana-3796	71	10	security	security	NOUN
cana-3796	71	11	contexts	context	NOUN
cana-3796	71	12	through	through	ADP
cana-3796	71	13	optical	optical	ADJ
cana-3796	71	14	transmitter	transmitter	NOUN
cana-3796	71	15	fingerprint	fingerprint	NOUN
cana-3796	71	16	authentication	authentication	NOUN
cana-3796	72	1	[	[	X
cana-3796	72	2	22	22	NUM
cana-3796	72	3	]	]	PUNCT
cana-3796	72	4	.	.	PUNCT
cana-3796	73	1	improvements	improvement	NOUN
cana-3796	73	2	in	in	ADP
cana-3796	73	3	license	license	NOUN
cana-3796	73	4	plate	plate	NOUN
cana-3796	73	5	recognition	recognition	NOUN
cana-3796	73	6	systems	system	NOUN
cana-3796	73	7	by	by	ADP
cana-3796	73	8	shi	shi	PROPN
cana-3796	73	9	and	and	CCONJ
cana-3796	73	10	zhao	zhao	PROPN
cana-3796	73	11	,	,	PUNCT
cana-3796	73	12	among	among	ADP
cana-3796	73	13	others	other	NOUN
cana-3796	73	14	,	,	PUNCT
cana-3796	73	15	reinforced	reinforce	VERB
cana-3796	73	16	ocr	ocr	PROPN
cana-3796	73	17	’s	’s	PART
cana-3796	73	18	pivotal	pivotal	ADJ
cana-3796	73	19	role	role	NOUN
cana-3796	73	20	in	in	ADP
cana-3796	73	21	transportation	transportation	NOUN
cana-3796	74	1	[	[	X
cana-3796	74	2	23][24][25	23][24][25	X
cana-3796	74	3	]	]	X
cana-3796	74	4	.	.	PUNCT
cana-3796	75	1	nguyen	nguyen	PROPN
cana-3796	75	2	et	et	PROPN
cana-3796	75	3	al	al	PROPN
cana-3796	75	4	.	.	PROPN
cana-3796	76	1	addressed	address	VERB
cana-3796	76	2	ocr	ocr	ADJ
cana-3796	76	3	error	error	NOUN
cana-3796	76	4	correction	correction	NOUN
cana-3796	76	5	in	in	ADP
cana-3796	76	6	vietnamese	vietnamese	ADJ
cana-3796	76	7	texts	text	NOUN
cana-3796	76	8	[	[	X
cana-3796	76	9	26	26	NUM
cana-3796	76	10	]	]	PUNCT
cana-3796	76	11	.	.	PUNCT
cana-3796	77	1	jang	jang	PROPN
cana-3796	77	2	et	et	PROPN
cana-3796	77	3	al	al	PROPN
cana-3796	77	4	.	.	PROPN
cana-3796	77	5	focused	focus	VERB
cana-3796	77	6	on	on	ADP
cana-3796	77	7	material	material	NOUN
cana-3796	77	8	identification	identification	NOUN
cana-3796	77	9	in	in	ADP
cana-3796	77	10	industrial	industrial	ADJ
cana-3796	77	11	contexts	context	NOUN
cana-3796	78	1	[	[	X
cana-3796	78	2	27	27	NUM
cana-3796	78	3	]	]	PUNCT
cana-3796	78	4	.	.	PUNCT
cana-3796	79	1	fu	fu	PROPN
cana-3796	79	2	et	et	PROPN
cana-3796	79	3	al	al	PROPN
cana-3796	79	4	.	.	PROPN
cana-3796	79	5	investigated	investigate	VERB
cana-3796	79	6	multiple	multiple	ADJ
cana-3796	79	7	event	event	NOUN
cana-3796	79	8	recognition	recognition	NOUN
cana-3796	79	9	in	in	ADP
cana-3796	79	10	fiber	fiber	NOUN
cana-3796	79	11	optic	optic	NOUN
cana-3796	79	12	systems	system	NOUN
cana-3796	79	13	[	[	X
cana-3796	79	14	28	28	NUM
cana-3796	79	15	]	]	PUNCT
cana-3796	79	16	,	,	PUNCT
cana-3796	79	17	and	and	CCONJ
cana-3796	79	18	seo	seo	PROPN
cana-3796	79	19	&	&	CCONJ
cana-3796	79	20	kang	kang	PROPN
cana-3796	79	21	worked	work	VERB
cana-3796	79	22	on	on	ADP
cana-3796	79	23	layout	layout	NOUN
cana-3796	79	24	-	-	PUNCT
cana-3796	79	25	independent	independent	ADJ
cana-3796	79	26	detection	detection	NOUN
cana-3796	79	27	[	[	X
cana-3796	79	28	29	29	NUM
cana-3796	79	29	]	]	PUNCT
cana-3796	79	30	.	.	PUNCT
cana-3796	80	1	gao	gao	PROPN
cana-3796	80	2	et	et	PROPN
cana-3796	80	3	al	al	PROPN
cana-3796	80	4	.	.	PROPN
cana-3796	80	5	developed	develop	VERB
cana-3796	80	6	the	the	DET
cana-3796	80	7	group	group	NOUN
cana-3796	80	8	plate	plate	NOUN
cana-3796	80	9	system	system	NOUN
cana-3796	80	10	for	for	ADP
cana-3796	80	11	multi	multi	ADJ
cana-3796	80	12	-	-	ADJ
cana-3796	80	13	category	category	ADJ
cana-3796	80	14	license	license	NOUN
cana-3796	80	15	plate	plate	NOUN
cana-3796	80	16	recognition	recognition	NOUN
cana-3796	80	17	[	[	X
cana-3796	80	18	30	30	NUM
cana-3796	80	19	]	]	PUNCT
cana-3796	80	20	,	,	PUNCT
cana-3796	80	21	while	while	SCONJ
cana-3796	80	22	chen	chen	PROPN
cana-3796	80	23	et	et	PROPN
cana-3796	80	24	al	al	PROPN
cana-3796	80	25	.	.	PROPN
cana-3796	80	26	prioritized	prioritize	VERB
cana-3796	80	27	cross	cross	ADJ
cana-3796	80	28	-	-	ADJ
cana-3796	80	29	lingual	lingual	ADJ
cana-3796	80	30	text	text	NOUN
cana-3796	80	31	recognition	recognition	NOUN
cana-3796	80	32	accuracy	accuracy	NOUN
cana-3796	81	1	[	[	X
cana-3796	81	2	31	31	NUM
cana-3796	81	3	]	]	PUNCT
cana-3796	81	4	.	.	PUNCT
cana-3796	82	1	li	li	PROPN
cana-3796	82	2	et	et	PROPN
cana-3796	82	3	al	al	PROPN
cana-3796	82	4	.	.	PROPN
cana-3796	82	5	introduced	introduce	VERB
cana-3796	82	6	a	a	DET
cana-3796	82	7	dual	dual	ADJ
cana-3796	82	8	relation	relation	NOUN
cana-3796	82	9	network	network	NOUN
cana-3796	82	10	to	to	PART
cana-3796	82	11	improve	improve	VERB
cana-3796	82	12	recognition	recognition	NOUN
cana-3796	82	13	[	[	X
cana-3796	82	14	32	32	NUM
cana-3796	82	15	]	]	PUNCT
cana-3796	82	16	.	.	PUNCT
cana-3796	83	1	tan	tan	PROPN
cana-3796	83	2	et	et	PROPN
cana-3796	83	3	al	al	PROPN
cana-3796	83	4	.	.	PROPN
cana-3796	83	5	presented	present	VERB
cana-3796	83	6	an	an	DET
cana-3796	83	7	air	air	NOUN
cana-3796	83	8	-	-	PUNCT
cana-3796	83	9	writing	write	VERB
cana-3796	83	10	recognition	recognition	NOUN
cana-3796	83	11	method	method	NOUN
cana-3796	83	12	using	use	VERB
cana-3796	83	13	transformers	transformer	NOUN
cana-3796	83	14	[	[	X
cana-3796	83	15	33	33	NUM
cana-3796	83	16	]	]	PUNCT
cana-3796	83	17	.	.	PUNCT
cana-3796	84	1	comprehensive	comprehensive	ADJ
cana-3796	84	2	surveys	survey	NOUN
cana-3796	84	3	by	by	ADP
cana-3796	84	4	rahman	rahman	PROPN
cana-3796	84	5	et	et	PROPN
cana-3796	84	6	al	al	PROPN
cana-3796	84	7	.	.	PROPN
cana-3796	84	8	focused	focus	VERB
cana-3796	84	9	on	on	ADP
cana-3796	84	10	bengali	bengali	X
cana-3796	84	11	handwritten	handwritten	ADJ
cana-3796	84	12	digit	digit	NOUN
cana-3796	84	13	recognition	recognition	NOUN
cana-3796	85	1	[	[	X
cana-3796	85	2	34	34	NUM
cana-3796	85	3	]	]	PUNCT
cana-3796	85	4	.	.	PUNCT
cana-3796	86	1	sharmila	sharmila	PROPN
cana-3796	86	2	et	et	PROPN
cana-3796	86	3	al	al	PROPN
cana-3796	86	4	.	.	PROPN
cana-3796	86	5	developed	develop	VERB
cana-3796	86	6	a	a	DET
cana-3796	86	7	convolutional	convolutional	ADJ
cana-3796	86	8	neural	neural	ADJ
cana-3796	86	9	network	network	NOUN
cana-3796	86	10	-	-	PUNCT
cana-3796	86	11	based	base	VERB
cana-3796	86	12	method	method	NOUN
cana-3796	86	13	for	for	ADP
cana-3796	86	14	recognizing	recognize	VERB
cana-3796	86	15	handwritten	handwritten	ADJ
cana-3796	86	16	tamil	tamil	NOUN
cana-3796	86	17	characters	character	NOUN
cana-3796	86	18	[	[	X
cana-3796	86	19	35	35	NUM
cana-3796	86	20	]	]	PUNCT
cana-3796	86	21	,	,	PUNCT
cana-3796	86	22	while	while	SCONJ
cana-3796	86	23	karthikeyan	karthikeyan	PROPN
cana-3796	86	24	et	et	PROPN
cana-3796	86	25	al	al	PROPN
cana-3796	86	26	.	.	PROPN
cana-3796	87	1	highlighted	highlight	VERB
cana-3796	87	2	ocr	ocr	PROPN
cana-3796	87	3	accuracy	accuracy	NOUN
cana-3796	87	4	’s	’s	PART
cana-3796	87	5	importance	importance	NOUN
cana-3796	87	6	in	in	ADP
cana-3796	87	7	medical	medical	ADJ
cana-3796	87	8	applications	application	NOUN
cana-3796	87	9	[	[	X
cana-3796	87	10	36	36	NUM
cana-3796	87	11	]	]	PUNCT
cana-3796	87	12	.	.	PUNCT
cana-3796	88	1	kumar	kumar	PROPN
cana-3796	88	2	et	et	PROPN
cana-3796	88	3	al	al	PROPN
cana-3796	88	4	.	.	PROPN
cana-3796	88	5	proposed	propose	VERB
cana-3796	88	6	an	an	DET
cana-3796	88	7	innovative	innovative	ADJ
cana-3796	88	8	approach	approach	NOUN
cana-3796	88	9	for	for	ADP
cana-3796	88	10	recognizing	recognize	VERB
cana-3796	88	11	cursive	cursive	ADJ
cana-3796	88	12	hindi	hindi	NOUN
cana-3796	88	13	scripts	script	NOUN
cana-3796	88	14	[	[	X
cana-3796	88	15	37	37	NUM
cana-3796	88	16	]	]	PUNCT
cana-3796	88	17	,	,	PUNCT
cana-3796	88	18	and	and	CCONJ
cana-3796	88	19	vinotheni	vinotheni	PROPN
cana-3796	88	20	&	&	CCONJ
cana-3796	88	21	pandian	pandian	PROPN
cana-3796	88	22	contributed	contribute	VERB
cana-3796	88	23	a	a	DET
cana-3796	88	24	model	model	NOUN
cana-3796	88	25	for	for	ADP
cana-3796	88	26	tamil	tamil	PROPN
cana-3796	88	27	handwritten	handwritten	ADJ
cana-3796	88	28	document	document	NOUN
cana-3796	88	29	recognition	recognition	NOUN
cana-3796	89	1	[	[	X
cana-3796	89	2	38	38	NUM
cana-3796	89	3	]	]	PUNCT
cana-3796	89	4	.	.	PUNCT
cana-3796	90	1	mrinalini	mrinalini	AUX
cana-3796	90	2	et	et	PROPN
cana-3796	90	3	al	al	PROPN
cana-3796	90	4	.	.	PROPN
cana-3796	90	5	introduced	introduce	VERB
cana-3796	90	6	a	a	DET
cana-3796	90	7	similarity	similarity	NOUN
cana-3796	90	8	-	-	PUNCT
cana-3796	90	9	based	base	VERB
cana-3796	90	10	evaluation	evaluation	NOUN
cana-3796	90	11	metric	metric	NOUN
cana-3796	90	12	for	for	ADP
cana-3796	90	13	indian	indian	ADJ
cana-3796	90	14	languages	language	NOUN
cana-3796	90	15	[	[	X
cana-3796	90	16	39	39	NUM
cana-3796	90	17	]	]	PUNCT
cana-3796	90	18	.	.	PUNCT
cana-3796	91	1	p.p	p.p	INTJ
cana-3796	91	2	et	et	NOUN
cana-3796	91	3	al	al	PROPN
cana-3796	91	4	.	.	PUNCT
cana-3796	92	1	[	[	X
cana-3796	92	2	40	40	NUM
cana-3796	92	3	]	]	PUNCT
cana-3796	92	4	proposed	propose	VERB
cana-3796	92	5	ocr	ocr	NOUN
cana-3796	92	6	and	and	CCONJ
cana-3796	92	7	text	text	NOUN
cana-3796	92	8	to	to	ADP
cana-3796	92	9	speech	speech	NOUN
cana-3796	92	10	recognition	recognition	NOUN
cana-3796	92	11	.	.	PUNCT
cana-3796	93	1	an	an	DET
cana-3796	93	2	overview	overview	NOUN
cana-3796	93	3	of	of	ADP
cana-3796	93	4	character	character	NOUN
cana-3796	93	5	recognition	recognition	NOUN
cana-3796	93	6	studies	study	NOUN
cana-3796	93	7	is	be	AUX
cana-3796	93	8	provided	provide	VERB
cana-3796	93	9	in	in	ADP
cana-3796	93	10	table-1	table-1	NUM
cana-3796	93	11	.	.	PUNCT
cana-3796	94	1	communications	communication	NOUN
cana-3796	94	2	on	on	ADP
cana-3796	94	3	applied	apply	VERB
cana-3796	94	4	nonlinear	nonlinear	ADJ
cana-3796	94	5	analysis	analysis	NOUN
cana-3796	94	6	issn	issn	NOUN
cana-3796	94	7	:	:	PUNCT
cana-3796	94	8	1074	1074	NUM
cana-3796	94	9	-	-	PUNCT
cana-3796	94	10	133x	133x	NUM
cana-3796	94	11	vol	vol	NOUN
cana-3796	94	12	32	32	NUM
cana-3796	94	13	no	no	NOUN
cana-3796	94	14	.	.	PUNCT
cana-3796	95	1	8s	8s	PROPN
cana-3796	95	2	(	(	PUNCT
cana-3796	95	3	2025	2025	NUM
cana-3796	95	4	)	)	PUNCT
cana-3796	95	5	748	748	NUM
cana-3796	95	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	95	7	table	table	NOUN
cana-3796	95	8	1	1	NUM
cana-3796	95	9	:	:	PUNCT
cana-3796	95	10	overview	overview	NOUN
cana-3796	95	11	of	of	ADP
cana-3796	95	12	character	character	NOUN
cana-3796	95	13	recognition	recognition	NOUN
cana-3796	95	14	studies	study	NOUN
cana-3796	95	15	reference	reference	NOUN
cana-3796	95	16	focus	focus	NOUN
cana-3796	95	17	area	area	NOUN
cana-3796	95	18	methodology	methodology	NOUN
cana-3796	95	19	limitations	limitation	NOUN
cana-3796	95	20	rasheed	rasheed	VERB
cana-3796	95	21	et	et	PROPN
cana-3796	95	22	al	al	PROPN
cana-3796	95	23	.	.	PUNCT
cana-3796	96	1	[	[	X
cana-3796	96	2	2	2	NUM
cana-3796	96	3	]	]	X
cana-3796	96	4	urdu	urdu	PROPN
cana-3796	96	5	character	character	NOUN
cana-3796	96	6	recognition	recognition	NOUN
cana-3796	96	7	transfer	transfer	NOUN
cana-3796	96	8	learning	learn	VERB
cana-3796	96	9	with	with	ADP
cana-3796	96	10	alex	alex	PROPN
cana-3796	96	11	net	net	ADJ
cana-3796	96	12	potential	potential	NOUN
cana-3796	96	13	overfitting	overfitting	NOUN
cana-3796	96	14	due	due	ADP
cana-3796	96	15	to	to	ADP
cana-3796	96	16	small	small	ADJ
cana-3796	96	17	dataset	dataset	NOUN
cana-3796	96	18	size	size	NOUN
cana-3796	96	19	.	.	PUNCT
cana-3796	97	1	r.	r.	PROPN
cana-3796	97	2	d.	d.	PROPN
cana-3796	97	3	r	r	PROPN
cana-3796	97	4	et	et	PROPN
cana-3796	97	5	al	al	PROPN
cana-3796	97	6	.	.	PUNCT
cana-3796	98	1	[	[	X
cana-3796	98	2	10	10	NUM
cana-3796	98	3	]	]	SYM
cana-3796	98	4	ancient	ancient	ADJ
cana-3796	98	5	tamil	tamil	PROPN
cana-3796	98	6	character	character	NOUN
cana-3796	98	7	recognition	recognition	NOUN
cana-3796	98	8	hybrid	hybrid	NOUN
cana-3796	98	9	approaches	approach	NOUN
cana-3796	98	10	complexity	complexity	NOUN
cana-3796	98	11	of	of	ADP
cana-3796	98	12	ancient	ancient	ADJ
cana-3796	98	13	scripts	script	NOUN
cana-3796	98	14	can	can	AUX
cana-3796	98	15	hinder	hinder	VERB
cana-3796	98	16	accuracy	accuracy	NOUN
cana-3796	98	17	.	.	PUNCT
cana-3796	99	1	tayyab	tayyab	PROPN
cana-3796	99	2	et	et	PROPN
cana-3796	99	3	al	al	PROPN
cana-3796	99	4	.	.	PUNCT
cana-3796	100	1	[	[	X
cana-3796	100	2	16	16	NUM
cana-3796	100	3	]	]	X
cana-3796	100	4	arabic	arabic	PROPN
cana-3796	100	5	script	script	NOUN
cana-3796	100	6	recognition	recognition	NOUN
cana-3796	100	7	real	real	ADJ
cana-3796	100	8	-	-	PUNCT
cana-3796	100	9	time	time	NOUN
cana-3796	100	10	processing	processing	NOUN
cana-3796	100	11	complexity	complexity	NOUN
cana-3796	100	12	of	of	ADP
cana-3796	100	13	arabic	arabic	ADJ
cana-3796	100	14	script	script	NOUN
cana-3796	100	15	fonts	font	NOUN
cana-3796	100	16	can	can	AUX
cana-3796	100	17	affect	affect	VERB
cana-3796	100	18	performance	performance	NOUN
cana-3796	100	19	.	.	PUNCT
cana-3796	101	1	chandio	chandio	NOUN
cana-3796	101	2	et	et	PROPN
cana-3796	101	3	al	al	PROPN
cana-3796	101	4	.	.	PUNCT
cana-3796	102	1	[	[	X
cana-3796	102	2	21	21	NUM
cana-3796	102	3	]	]	X
cana-3796	102	4	cursive	cursive	ADJ
cana-3796	102	5	text	text	NOUN
cana-3796	102	6	recognition	recognition	NOUN
cana-3796	102	7	deep	deep	ADJ
cana-3796	102	8	learning	learn	VERB
cana-3796	102	9	cursive	cursive	ADJ
cana-3796	102	10	variations	variation	NOUN
cana-3796	102	11	can	can	AUX
cana-3796	102	12	complicate	complicate	VERB
cana-3796	102	13	recognition	recognition	NOUN
cana-3796	102	14	.	.	PUNCT
cana-3796	103	1	sharmila	sharmila	PROPN
cana-3796	103	2	et	et	PROPN
cana-3796	103	3	al	al	PROPN
cana-3796	103	4	.	.	PUNCT
cana-3796	104	1	[	[	X
cana-3796	104	2	35	35	NUM
cana-3796	104	3	]	]	X
cana-3796	104	4	handwritten	handwritten	ADJ
cana-3796	104	5	tamil	tamil	PROPN
cana-3796	104	6	character	character	NOUN
cana-3796	104	7	recognition	recognition	NOUN
cana-3796	104	8	convolutional	convolutional	ADJ
cana-3796	104	9	neural	neural	ADJ
cana-3796	104	10	networks	network	NOUN
cana-3796	104	11	requires	require	VERB
cana-3796	104	12	large	large	ADJ
cana-3796	104	13	datasets	dataset	NOUN
cana-3796	104	14	for	for	ADP
cana-3796	104	15	practical	practical	ADJ
cana-3796	104	16	applications	application	NOUN
cana-3796	104	17	.	.	PUNCT
cana-3796	105	1	yavariabdi	yavariabdi	PROPN
cana-3796	105	2	et	et	PROPN
cana-3796	105	3	al	al	PROPN
cana-3796	105	4	.	.	PUNCT
cana-3796	106	1	[	[	X
cana-3796	106	2	1	1	X
cana-3796	106	3	]	]	X
cana-3796	106	4	historical	historical	ADJ
cana-3796	106	5	handwritten	handwritten	ADJ
cana-3796	106	6	ocr	ocr	PROPN
cana-3796	106	7	cardis	cardi	NOUN
cana-3796	106	8	dataset	dataset	VERB
cana-3796	106	9	limited	limit	VERB
cana-3796	106	10	to	to	ADP
cana-3796	106	11	swedish	swedish	ADJ
cana-3796	106	12	language	language	NOUN
cana-3796	106	13	;	;	PUNCT
cana-3796	106	14	may	may	AUX
cana-3796	106	15	not	not	PART
cana-3796	106	16	generalize	generalize	VERB
cana-3796	106	17	well	well	ADV
cana-3796	106	18	.	.	PUNCT
cana-3796	107	1	buoy	buoy	NOUN
cana-3796	107	2	et	et	PROPN
cana-3796	107	3	al	al	PROPN
cana-3796	107	4	.	.	PUNCT
cana-3796	108	1	[	[	X
cana-3796	108	2	3	3	X
cana-3796	108	3	]	]	X
cana-3796	108	4	khmer	khmer	PROPN
cana-3796	108	5	ocr	ocr	PROPN
cana-3796	108	6	low	low	ADJ
cana-3796	108	7	-	-	PUNCT
cana-3796	108	8	resource	resource	NOUN
cana-3796	108	9	baseline	baseline	NOUN
cana-3796	108	10	limited	limit	VERB
cana-3796	108	11	data	datum	NOUN
cana-3796	108	12	availability	availability	NOUN
cana-3796	108	13	for	for	ADP
cana-3796	108	14	khmer	khmer	PROPN
cana-3796	108	15	language	language	PROPN
cana-3796	108	16	ocr	ocr	PROPN
cana-3796	108	17	.	.	PUNCT
cana-3796	109	1	malhotra	malhotra	PROPN
cana-3796	109	2	and	and	CCONJ
cana-3796	109	3	addis	addis	PROPN
cana-3796	110	1	[	[	X
cana-3796	110	2	17	17	NUM
cana-3796	110	3	]	]	PUNCT
cana-3796	110	4	historical	historical	ADJ
cana-3796	110	5	ethiopic	ethiopic	ADJ
cana-3796	110	6	text	text	NOUN
cana-3796	110	7	digitization	digitization	NOUN
cana-3796	110	8	deep	deep	ADJ
cana-3796	110	9	learning	learning	NOUN
cana-3796	110	10	techniques	technique	NOUN
cana-3796	110	11	difficulties	difficulty	NOUN
cana-3796	110	12	in	in	ADP
cana-3796	110	13	obtaining	obtain	VERB
cana-3796	110	14	comprehensive	comprehensive	ADJ
cana-3796	110	15	historical	historical	ADJ
cana-3796	110	16	data	datum	NOUN
cana-3796	110	17	.	.	PUNCT
cana-3796	111	1	vinotheni	vinotheni	PROPN
cana-3796	111	2	and	and	CCONJ
cana-3796	111	3	pandian	pandian	ADJ
cana-3796	111	4	[	[	X
cana-3796	111	5	38	38	NUM
cana-3796	111	6	]	]	PUNCT
cana-3796	111	7	tamil	tamil	NOUN
cana-3796	111	8	document	document	NOUN
cana-3796	111	9	recognition	recognition	NOUN
cana-3796	111	10	specialized	specialized	PROPN
cana-3796	111	11	recognition	recognition	PROPN
cana-3796	111	12	systems	system	NOUN
cana-3796	111	13	limited	limit	VERB
cana-3796	111	14	data	datum	NOUN
cana-3796	111	15	availability	availability	NOUN
cana-3796	111	16	restricts	restrict	VERB
cana-3796	111	17	ocr	ocr	ADJ
cana-3796	111	18	enhancements	enhancement	NOUN
cana-3796	111	19	.	.	PUNCT
cana-3796	112	1	mrinalini	mrinalini	PROPN
cana-3796	112	2	et	et	PROPN
cana-3796	112	3	al	al	PROPN
cana-3796	112	4	.	.	PUNCT
cana-3796	113	1	[	[	X
cana-3796	113	2	39	39	NUM
cana-3796	113	3	]	]	PUNCT
cana-3796	113	4	indian	indian	ADJ
cana-3796	113	5	language	language	NOUN
cana-3796	113	6	translation	translation	NOUN
cana-3796	113	7	similarity	similarity	NOUN
cana-3796	113	8	-	-	PUNCT
cana-3796	113	9	based	base	VERB
cana-3796	113	10	evaluation	evaluation	NOUN
cana-3796	113	11	metric	metric	NOUN
cana-3796	113	12	may	may	AUX
cana-3796	113	13	not	not	PART
cana-3796	113	14	accommodate	accommodate	VERB
cana-3796	113	15	all	all	DET
cana-3796	113	16	regional	regional	ADJ
cana-3796	113	17	dialects	dialect	NOUN
cana-3796	113	18	.	.	PUNCT
cana-3796	114	1	iii	iii	X
cana-3796	114	2	.	.	PROPN
cana-3796	114	3	proposed	propose	VERB
cana-3796	114	4	design	design	NOUN
cana-3796	114	5	to	to	PART
cana-3796	114	6	address	address	VERB
cana-3796	114	7	the	the	DET
cana-3796	114	8	challenges	challenge	NOUN
cana-3796	114	9	of	of	ADP
cana-3796	114	10	lower	low	ADJ
cana-3796	114	11	efficiency	efficiency	NOUN
cana-3796	114	12	and	and	CCONJ
cana-3796	114	13	higher	high	ADJ
cana-3796	114	14	complexity	complexity	NOUN
cana-3796	114	15	in	in	ADP
cana-3796	114	16	current	current	ADJ
cana-3796	114	17	ocr	ocr	ADJ
cana-3796	114	18	models	model	NOUN
cana-3796	114	19	,	,	PUNCT
cana-3796	114	20	this	this	DET
cana-3796	114	21	section	section	NOUN
cana-3796	114	22	presents	present	VERB
cana-3796	114	23	the	the	DET
cana-3796	114	24	design	design	NOUN
cana-3796	114	25	of	of	ADP
cana-3796	114	26	an	an	DET
cana-3796	114	27	efficient	efficient	ADJ
cana-3796	114	28	automated	automate	VERB
cana-3796	114	29	quad	quad	ADV
cana-3796	114	30	lstm	lstm	NOUN
cana-3796	114	31	-	-	PUNCT
cana-3796	114	32	based	base	VERB
cana-3796	114	33	deep	deep	ADJ
cana-3796	114	34	learning	learning	NOUN
cana-3796	114	35	language	language	NOUN
cana-3796	114	36	processing	processing	NOUN
cana-3796	114	37	model	model	NOUN
cana-3796	114	38	for	for	ADP
cana-3796	114	39	analysing	analyse	VERB
cana-3796	114	40	handwritten	handwritten	ADJ
cana-3796	114	41	telugu	telugu	PROPN
cana-3796	114	42	answer	answer	NOUN
cana-3796	114	43	scripts	script	NOUN
cana-3796	114	44	.	.	PUNCT
cana-3796	115	1	as	as	SCONJ
cana-3796	115	2	illustrated	illustrate	VERB
cana-3796	115	3	in	in	ADP
cana-3796	115	4	figure	figure	NOUN
cana-3796	115	5	1	1	NUM
cana-3796	115	6	,	,	PUNCT
cana-3796	115	7	the	the	DET
cana-3796	115	8	proposed	propose	VERB
cana-3796	115	9	model	model	NOUN
cana-3796	115	10	includes	include	VERB
cana-3796	115	11	the	the	DET
cana-3796	115	12	following	follow	VERB
cana-3796	115	13	phases	phase	NOUN
cana-3796	115	14	:	:	PUNCT
cana-3796	115	15	image	image	NOUN
cana-3796	115	16	processing	processing	NOUN
cana-3796	115	17	,	,	PUNCT
cana-3796	115	18	data	datum	NOUN
cana-3796	115	19	augmentation	augmentation	NOUN
cana-3796	115	20	,	,	PUNCT
cana-3796	115	21	feature	feature	NOUN
cana-3796	115	22	extraction	extraction	NOUN
cana-3796	115	23	process	process	NOUN
cana-3796	115	24	,	,	PUNCT
cana-3796	115	25	quad	quad	ADV
cana-3796	115	26	long	long	ADJ
cana-3796	115	27	short	short	ADJ
cana-3796	115	28	-	-	PUNCT
cana-3796	115	29	term	term	NOUN
cana-3796	115	30	memory	memory	NOUN
cana-3796	115	31	(	(	PUNCT
cana-3796	115	32	lstm	lstm	NOUN
cana-3796	115	33	)	)	PUNCT
cana-3796	115	34	networks	network	NOUN
cana-3796	115	35	,	,	PUNCT
cana-3796	115	36	bahdanau	bahdanau	VERB
cana-3796	115	37	attention	attention	NOUN
cana-3796	115	38	mechanism	mechanism	NOUN
cana-3796	115	39	,	,	PUNCT
cana-3796	115	40	visual	visual	ADJ
cana-3796	115	41	bert	bert	NOUN
cana-3796	115	42	.	.	PUNCT
cana-3796	116	1	in	in	ADP
cana-3796	116	2	continuation	continuation	NOUN
cana-3796	116	3	,	,	PUNCT
cana-3796	116	4	figure	figure	NOUN
cana-3796	116	5	2	2	NUM
cana-3796	116	6	gives	give	VERB
cana-3796	116	7	an	an	DET
cana-3796	116	8	overview	overview	NOUN
cana-3796	116	9	of	of	ADP
cana-3796	116	10	internal	internal	ADJ
cana-3796	116	11	architectural	architectural	ADJ
cana-3796	116	12	details	detail	NOUN
cana-3796	116	13	of	of	ADP
cana-3796	116	14	the	the	DET
cana-3796	116	15	proposed	propose	VERB
cana-3796	116	16	model	model	NOUN
cana-3796	116	17	for	for	ADP
cana-3796	116	18	ocr	ocr	ADJ
cana-3796	116	19	analysis	analysis	NOUN
cana-3796	116	20	.	.	PUNCT
cana-3796	117	1	this	this	DET
cana-3796	117	2	comprehensive	comprehensive	ADJ
cana-3796	117	3	approach	approach	NOUN
cana-3796	117	4	not	not	PART
cana-3796	117	5	only	only	ADV
cana-3796	117	6	demonstrates	demonstrate	VERB
cana-3796	117	7	remarkable	remarkable	ADJ
cana-3796	117	8	improvements	improvement	NOUN
cana-3796	117	9	in	in	ADP
cana-3796	117	10	key	key	ADJ
cana-3796	117	11	performance	performance	NOUN
cana-3796	117	12	metrics	metric	NOUN
cana-3796	117	13	such	such	ADJ
cana-3796	117	14	as	as	ADP
cana-3796	117	15	precision	precision	NOUN
cana-3796	117	16	and	and	CCONJ
cana-3796	117	17	accuracy	accuracy	NOUN
cana-3796	117	18	but	but	CCONJ
cana-3796	117	19	also	also	ADV
cana-3796	117	20	significantly	significantly	ADV
cana-3796	117	21	reduces	reduce	VERB
cana-3796	117	22	processing	processing	NOUN
cana-3796	117	23	delays	delay	NOUN
cana-3796	117	24	.	.	PUNCT
cana-3796	118	1	the	the	DET
cana-3796	118	2	overall	overall	ADJ
cana-3796	118	3	proposed	propose	VERB
cana-3796	118	4	flow	flow	NOUN
cana-3796	118	5	is	be	AUX
cana-3796	118	6	depicted	depict	VERB
cana-3796	118	7	in	in	ADP
cana-3796	118	8	the	the	DET
cana-3796	118	9	following	follow	VERB
cana-3796	118	10	algorithm	algorithm	NOUN
cana-3796	118	11	1	1	NUM
cana-3796	118	12	handwriting	handwriting	NOUN
cana-3796	118	13	recognition	recognition	NOUN
cana-3796	118	14	and	and	CCONJ
cana-3796	118	15	similarity	similarity	NOUN
cana-3796	118	16	scores	score	NOUN
cana-3796	118	17	using	use	VERB
cana-3796	118	18	quad	quad	NOUN
cana-3796	118	19	lstm	lstm	NOUN
cana-3796	118	20	.	.	PUNCT
cana-3796	119	1	as	as	ADP
cana-3796	119	2	a	a	DET
cana-3796	119	3	result	result	NOUN
cana-3796	119	4	,	,	PUNCT
cana-3796	119	5	the	the	DET
cana-3796	119	6	proposed	propose	VERB
cana-3796	119	7	model	model	NOUN
cana-3796	119	8	stands	stand	VERB
cana-3796	119	9	out	out	ADP
cana-3796	119	10	as	as	ADP
cana-3796	119	11	a	a	DET
cana-3796	119	12	beacon	beacon	NOUN
cana-3796	119	13	of	of	ADP
cana-3796	119	14	innovation	innovation	NOUN
cana-3796	119	15	in	in	ADP
cana-3796	119	16	ocr	ocr	ADJ
cana-3796	119	17	technology	technology	NOUN
cana-3796	119	18	for	for	ADP
cana-3796	119	19	complex	complex	ADJ
cana-3796	119	20	scripts	script	NOUN
cana-3796	119	21	.	.	PUNCT
cana-3796	120	1	communications	communication	NOUN
cana-3796	120	2	on	on	ADP
cana-3796	120	3	applied	apply	VERB
cana-3796	120	4	nonlinear	nonlinear	ADJ
cana-3796	120	5	analysis	analysis	NOUN
cana-3796	120	6	issn	issn	NOUN
cana-3796	120	7	:	:	PUNCT
cana-3796	120	8	1074	1074	NUM
cana-3796	120	9	-	-	PUNCT
cana-3796	120	10	133x	133x	NUM
cana-3796	120	11	vol	vol	NOUN
cana-3796	120	12	32	32	NUM
cana-3796	120	13	no	no	NOUN
cana-3796	120	14	.	.	PUNCT
cana-3796	121	1	8s	8s	PROPN
cana-3796	121	2	(	(	PUNCT
cana-3796	121	3	2025	2025	NUM
cana-3796	121	4	)	)	PUNCT
cana-3796	121	5	749	749	NUM
cana-3796	122	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	122	2	algorithm	algorithm	NOUN
cana-3796	122	3	1	1	NUM
cana-3796	122	4	:	:	PUNCT
cana-3796	122	5	handwriting	handwriting	NOUN
cana-3796	122	6	recognition	recognition	NOUN
cana-3796	122	7	and	and	CCONJ
cana-3796	122	8	similarity	similarity	NOUN
cana-3796	122	9	scores	score	NOUN
cana-3796	122	10	using	use	VERB
cana-3796	122	11	quad	quad	PRON
cana-3796	122	12	lstm	lstm	ADJ
cana-3796	122	13	input	input	NOUN
cana-3796	122	14	:	:	PUNCT
cana-3796	122	15	images	image	NOUN
cana-3796	122	16	of	of	ADP
cana-3796	122	17	handwritten	handwritten	ADJ
cana-3796	122	18	text	text	NOUN
cana-3796	122	19	.	.	PUNCT
cana-3796	123	1	output	output	NOUN
cana-3796	123	2	:	:	PUNCT
cana-3796	123	3	recognized	recognize	VERB
cana-3796	123	4	text	text	NOUN
cana-3796	123	5	and	and	CCONJ
cana-3796	123	6	similarity	similarity	NOUN
cana-3796	123	7	scores	score	NOUN
cana-3796	123	8	.	.	PUNCT
cana-3796	124	1	procedure	procedure	NOUN
cana-3796	124	2	:	:	PUNCT
cana-3796	124	3	1	1	X
cana-3796	124	4	.	.	X
cana-3796	124	5	initialize	initialize	VERB
cana-3796	124	6	the	the	DET
cana-3796	124	7	environment	environment	NOUN
cana-3796	124	8	:	:	PUNCT
cana-3796	124	9	import	import	NOUN
cana-3796	124	10	libraries	library	NOUN
cana-3796	124	11	:	:	PUNCT
cana-3796	124	12	cv2	cv2	PROPN
cana-3796	124	13	,	,	PUNCT
cana-3796	124	14	numpy	numpy	NOUN
cana-3796	124	15	,	,	PUNCT
cana-3796	124	16	keras	keras	PROPN
cana-3796	124	17	,	,	PUNCT
cana-3796	124	18	transformers	transformer	NOUN
cana-3796	124	19	,	,	PUNCT
cana-3796	124	20	etc	etc	X
cana-3796	124	21	.	.	X
cana-3796	124	22	define	define	VERB
cana-3796	124	23	image	image	NOUN
cana-3796	124	24	paths	path	NOUN
cana-3796	124	25	.	.	PUNCT
cana-3796	125	1	2	2	X
cana-3796	125	2	.	.	X
cana-3796	125	3	process	process	NOUN
cana-3796	125	4	each	each	DET
cana-3796	125	5	image	image	NOUN
cana-3796	125	6	:	:	PUNCT
cana-3796	125	7	for	for	ADP
cana-3796	125	8	each	each	DET
cana-3796	125	9	image	image	NOUN
cana-3796	125	10	in	in	ADP
cana-3796	125	11	the	the	DET
cana-3796	125	12	paths	path	NOUN
cana-3796	125	13	:	:	PUNCT
cana-3796	125	14	load	load	NOUN
cana-3796	125	15	and	and	CCONJ
cana-3796	125	16	preprocess	preprocess	NOUN
cana-3796	125	17	:	:	PUNCT
cana-3796	125	18	▪	▪	ADJ
cana-3796	125	19	convert	convert	NOUN
cana-3796	125	20	to	to	ADP
cana-3796	125	21	grayscale	grayscale	NOUN
cana-3796	125	22	.	.	PUNCT
cana-3796	126	1	▪	▪	NOUN
cana-3796	126	2	apply	apply	VERB
cana-3796	126	3	adaptive	adaptive	ADJ
cana-3796	126	4	thresholding	thresholding	NOUN
cana-3796	126	5	and	and	CCONJ
cana-3796	126	6	gaussian	gaussian	ADJ
cana-3796	126	7	blur	blur	PROPN
cana-3796	126	8	.	.	PUNCT
cana-3796	127	1	detect	detect	NOUN
cana-3796	127	2	text	text	NOUN
cana-3796	127	3	regions	region	NOUN
cana-3796	127	4	:	:	PUNCT
cana-3796	127	5	▪	▪	NOUN
cana-3796	127	6	identify	identify	VERB
cana-3796	127	7	bounding	bounding	NOUN
cana-3796	127	8	boxes	box	NOUN
cana-3796	127	9	figure	figure	VERB
cana-3796	127	10	1	1	NUM
cana-3796	127	11	.	.	PUNCT
cana-3796	128	1	overall	overall	ADJ
cana-3796	128	2	flow	flow	NOUN
cana-3796	128	3	of	of	ADP
cana-3796	128	4	the	the	DET
cana-3796	128	5	proposed	propose	VERB
cana-3796	128	6	model	model	NOUN
cana-3796	128	7	for	for	ADP
cana-3796	128	8	ocr	ocr	ADJ
cana-3796	128	9	analysis	analysis	NOUN
cana-3796	128	10	figure	figure	NOUN
cana-3796	128	11	2	2	NUM
cana-3796	128	12	.	.	PUNCT
cana-3796	128	13	internal	internal	ADJ
cana-3796	128	14	architectural	architectural	ADJ
cana-3796	128	15	details	detail	NOUN
cana-3796	128	16	of	of	ADP
cana-3796	128	17	the	the	DET
cana-3796	128	18	proposed	propose	VERB
cana-3796	128	19	model	model	NOUN
cana-3796	128	20	for	for	ADP
cana-3796	128	21	ocr	ocr	ADJ
cana-3796	128	22	analysis	analysis	NOUN
cana-3796	128	23	communications	communication	NOUN
cana-3796	128	24	on	on	ADP
cana-3796	128	25	applied	apply	VERB
cana-3796	128	26	nonlinear	nonlinear	ADJ
cana-3796	128	27	analysis	analysis	NOUN
cana-3796	128	28	issn	issn	NOUN
cana-3796	128	29	:	:	PUNCT
cana-3796	128	30	1074	1074	NUM
cana-3796	128	31	-	-	PUNCT
cana-3796	128	32	133x	133x	NUM
cana-3796	128	33	vol	vol	NOUN
cana-3796	128	34	32	32	NUM
cana-3796	128	35	no	no	NOUN
cana-3796	128	36	.	.	PUNCT
cana-3796	129	1	8s	8s	PROPN
cana-3796	129	2	(	(	PUNCT
cana-3796	129	3	2025	2025	NUM
cana-3796	129	4	)	)	PUNCT
cana-3796	129	5	750	750	NUM
cana-3796	129	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	129	7	3	3	X
cana-3796	129	8	.	.	PUNCT
cana-3796	129	9	for	for	ADP
cana-3796	129	10	each	each	DET
cana-3796	129	11	bounding	bounding	NOUN
cana-3796	129	12	box	box	NOUN
cana-3796	129	13	:	:	PUNCT
cana-3796	129	14	crop	crop	VERB
cana-3796	129	15	the	the	DET
cana-3796	129	16	image	image	NOUN
cana-3796	129	17	to	to	PART
cana-3796	129	18	isolate	isolate	VERB
cana-3796	129	19	the	the	DET
cana-3796	129	20	text	text	NOUN
cana-3796	129	21	region	region	NOUN
cana-3796	129	22	.	.	PUNCT
cana-3796	130	1	apply	apply	VERB
cana-3796	130	2	data	datum	NOUN
cana-3796	130	3	augmentation	augmentation	NOUN
cana-3796	130	4	techniques	technique	NOUN
cana-3796	130	5	.	.	PUNCT
cana-3796	131	1	4	4	X
cana-3796	131	2	.	.	X
cana-3796	131	3	build	build	VERB
cana-3796	131	4	the	the	DET
cana-3796	131	5	recognition	recognition	NOUN
cana-3796	131	6	model	model	NOUN
cana-3796	131	7	:	:	PUNCT
cana-3796	131	8	cnn	cnn	PROPN
cana-3796	131	9	backbone	backbone	NOUN
cana-3796	131	10	:	:	PUNCT
cana-3796	131	11	use	use	VERB
cana-3796	131	12	resnet101	resnet101	PROPN
cana-3796	131	13	or	or	CCONJ
cana-3796	131	14	inceptionv3	inceptionv3	NOUN
cana-3796	131	15	for	for	ADP
cana-3796	131	16	feature	feature	NOUN
cana-3796	131	17	extraction	extraction	NOUN
cana-3796	131	18	.	.	PUNCT
cana-3796	132	1	quad	quad	PROPN
cana-3796	132	2	lstm	lstm	NOUN
cana-3796	132	3	:	:	PUNCT
cana-3796	132	4	▪	▪	ADJ
cana-3796	132	5	stack	stack	NOUN
cana-3796	132	6	four	four	NUM
cana-3796	132	7	bidirectional	bidirectional	ADJ
cana-3796	132	8	lstm	lstm	ADJ
cana-3796	132	9	layers	layer	NOUN
cana-3796	132	10	(	(	PUNCT
cana-3796	132	11	with	with	ADP
cana-3796	132	12	attention	attention	NOUN
cana-3796	132	13	mechanism	mechanism	NOUN
cana-3796	132	14	)	)	PUNCT
cana-3796	132	15	.	.	PUNCT
cana-3796	133	1	▪	▪	X
cana-3796	133	2	add	add	VERB
cana-3796	133	3	output	output	NOUN
cana-3796	133	4	layer	layer	NOUN
cana-3796	133	5	with	with	ADP
cana-3796	133	6	softmax	softmax	NOUN
cana-3796	133	7	activation	activation	NOUN
cana-3796	133	8	.	.	PUNCT
cana-3796	134	1	5	5	X
cana-3796	134	2	.	.	X
cana-3796	134	3	recognize	recognize	VERB
cana-3796	134	4	text	text	NOUN
cana-3796	134	5	:	:	PUNCT
cana-3796	134	6	feed	feed	NOUN
cana-3796	134	7	cropped	crop	VERB
cana-3796	134	8	images	image	NOUN
cana-3796	134	9	into	into	ADP
cana-3796	134	10	the	the	DET
cana-3796	134	11	cnn	cnn	PROPN
cana-3796	134	12	.	.	PUNCT
cana-3796	135	1	pass	pass	VERB
cana-3796	135	2	features	feature	NOUN
cana-3796	135	3	to	to	ADP
cana-3796	135	4	the	the	DET
cana-3796	135	5	quad	quad	ADJ
cana-3796	135	6	lstm	lstm	NOUN
cana-3796	135	7	for	for	ADP
cana-3796	135	8	text	text	NOUN
cana-3796	135	9	recognition	recognition	NOUN
cana-3796	135	10	.	.	PUNCT
cana-3796	136	1	6	6	X
cana-3796	136	2	.	.	X
cana-3796	136	3	post	post	ADJ
cana-3796	136	4	-	-	ADJ
cana-3796	136	5	process	process	NOUN
cana-3796	136	6	results	result	NOUN
cana-3796	136	7	:	:	PUNCT
cana-3796	136	8	tokenize	tokenize	VERB
cana-3796	136	9	recognized	recognize	VERB
cana-3796	136	10	text	text	NOUN
cana-3796	136	11	with	with	ADP
cana-3796	136	12	bert	bert	PROPN
cana-3796	136	13	tokenizer	tokenizer	NOUN
cana-3796	136	14	.	.	PUNCT
cana-3796	137	1	obtain	obtain	VERB
cana-3796	137	2	optional	optional	ADJ
cana-3796	137	3	bert	bert	NOUN
cana-3796	137	4	embeddings	embedding	NOUN
cana-3796	137	5	.	.	PUNCT
cana-3796	138	1	7	7	X
cana-3796	138	2	.	.	X
cana-3796	138	3	evaluate	evaluate	VERB
cana-3796	138	4	similarity	similarity	NOUN
cana-3796	138	5	:	:	PUNCT
cana-3796	138	6	load	load	NOUN
cana-3796	138	7	answer	answer	NOUN
cana-3796	138	8	embeddings	embedding	NOUN
cana-3796	138	9	.	.	PUNCT
cana-3796	139	1	calculate	calculate	NOUN
cana-3796	139	2	cosine	cosine	NOUN
cana-3796	139	3	similarity	similarity	NOUN
cana-3796	139	4	against	against	ADP
cana-3796	139	5	recognized	recognize	VERB
cana-3796	139	6	text	text	NOUN
cana-3796	139	7	embeddings	embedding	NOUN
cana-3796	139	8	.	.	PUNCT
cana-3796	140	1	end	end	NOUN
cana-3796	140	2	procedure	procedure	NOUN
cana-3796	140	3	.	.	PUNCT
cana-3796	141	1	a.	a.	NOUN
cana-3796	141	2	image	image	NOUN
cana-3796	141	3	preprocessing	preprocesse	VERB
cana-3796	141	4	the	the	DET
cana-3796	141	5	initial	initial	ADJ
cana-3796	141	6	phase	phase	NOUN
cana-3796	141	7	of	of	ADP
cana-3796	141	8	image	image	NOUN
cana-3796	141	9	preprocessing	preprocessing	NOUN
cana-3796	141	10	is	be	AUX
cana-3796	141	11	critical	critical	ADJ
cana-3796	141	12	in	in	ADP
cana-3796	141	13	enhancing	enhance	VERB
cana-3796	141	14	the	the	DET
cana-3796	141	15	quality	quality	NOUN
cana-3796	141	16	of	of	ADP
cana-3796	141	17	handwritten	handwritten	ADJ
cana-3796	141	18	telugu	telugu	NOUN
cana-3796	141	19	text	text	NOUN
cana-3796	141	20	images	image	NOUN
cana-3796	141	21	and	and	CCONJ
cana-3796	141	22	comprises	comprise	VERB
cana-3796	141	23	adaptive	adaptive	ADJ
cana-3796	141	24	thresholding	thresholding	NOUN
cana-3796	141	25	and	and	CCONJ
cana-3796	141	26	gaussian	gaussian	ADJ
cana-3796	141	27	blurring	blur	VERB
cana-3796	141	28	operations	operation	NOUN
cana-3796	141	29	.	.	PUNCT
cana-3796	142	1	adaptive	adaptive	ADJ
cana-3796	142	2	thresholding	thresholding	NOUN
cana-3796	142	3	converts	convert	NOUN
cana-3796	142	4	grayscale	grayscale	NOUN
cana-3796	142	5	images	image	NOUN
cana-3796	142	6	to	to	ADP
cana-3796	142	7	binary	binary	ADJ
cana-3796	142	8	format	format	NOUN
cana-3796	142	9	,	,	PUNCT
cana-3796	142	10	improving	improve	VERB
cana-3796	142	11	contrast	contrast	NOUN
cana-3796	142	12	between	between	ADP
cana-3796	142	13	text	text	NOUN
cana-3796	142	14	and	and	CCONJ
cana-3796	142	15	background	background	NOUN
cana-3796	142	16	.	.	PUNCT
cana-3796	143	1	the	the	DET
cana-3796	143	2	threshold	threshold	NOUN
cana-3796	143	3	value	value	NOUN
cana-3796	143	4	,	,	PUNCT
cana-3796	143	5	𝑇(𝑥	𝑇(𝑥	PROPN
cana-3796	143	6	,	,	PUNCT
cana-3796	143	7	𝑦	𝑦	NOUN
cana-3796	143	8	)	)	PUNCT
cana-3796	143	9	,	,	PUNCT
cana-3796	143	10	is	be	AUX
cana-3796	143	11	dynamically	dynamically	ADV
cana-3796	143	12	calculated	calculate	VERB
cana-3796	143	13	via	via	ADP
cana-3796	143	14	equation	equation	NOUN
cana-3796	143	15	1	1	NUM
cana-3796	143	16	,	,	PUNCT
cana-3796	143	17	𝑇(𝑥	𝑇(𝑥	PROPN
cana-3796	143	18	,	,	PUNCT
cana-3796	143	19	𝑦	𝑦	NOUN
cana-3796	143	20	)	)	PUNCT
cana-3796	143	21	=	=	SYM
cana-3796	143	22	𝜇(𝑥	𝜇(𝑥	PROPN
cana-3796	143	23	,	,	PUNCT
cana-3796	143	24	𝑦	𝑦	NOUN
cana-3796	143	25	)	)	PUNCT
cana-3796	143	26	−	−	PROPN
cana-3796	143	27	𝐶	𝐶	PROPN
cana-3796	143	28	(	(	PUNCT
cana-3796	143	29	1	1	NUM
cana-3796	143	30	)	)	PUNCT
cana-3796	143	31	where	where	SCONJ
cana-3796	143	32	𝜇(𝑥	𝜇(𝑥	PROPN
cana-3796	143	33	,	,	PUNCT
cana-3796	143	34	𝑦	𝑦	NOUN
cana-3796	143	35	)	)	PUNCT
cana-3796	143	36	represents	represent	VERB
cana-3796	143	37	the	the	DET
cana-3796	143	38	mean	mean	ADJ
cana-3796	143	39	intensity	intensity	NOUN
cana-3796	143	40	in	in	ADP
cana-3796	143	41	a	a	DET
cana-3796	143	42	neighborhood	neighborhood	NOUN
cana-3796	143	43	around	around	ADP
cana-3796	143	44	the	the	DET
cana-3796	143	45	pixel	pixel	NOUN
cana-3796	143	46	at	at	ADP
cana-3796	143	47	(	(	PUNCT
cana-3796	143	48	𝑥	𝑥	PROPN
cana-3796	143	49	,	,	PUNCT
cana-3796	143	50	𝑦	𝑦	NOUN
cana-3796	143	51	)	)	PUNCT
cana-3796	143	52	,	,	PUNCT
cana-3796	143	53	and	and	CCONJ
cana-3796	143	54	c	c	NOUN
cana-3796	143	55	is	be	AUX
cana-3796	143	56	a	a	DET
cana-3796	143	57	constant	constant	ADJ
cana-3796	143	58	.	.	PUNCT
cana-3796	144	1	the	the	DET
cana-3796	144	2	mean	mean	ADJ
cana-3796	144	3	intensity	intensity	NOUN
cana-3796	144	4	is	be	AUX
cana-3796	144	5	computed	compute	VERB
cana-3796	144	6	via	via	ADP
cana-3796	144	7	equation	equation	NOUN
cana-3796	144	8	2	2	NUM
cana-3796	144	9	,	,	PUNCT
cana-3796	144	10	𝜇(𝑥	𝜇(𝑥	PROPN
cana-3796	144	11	,	,	PUNCT
cana-3796	144	12	𝑦	𝑦	NOUN
cana-3796	144	13	)	)	PUNCT
cana-3796	144	14	=	=	SYM
cana-3796	144	15	1	1	NUM
cana-3796	144	16	𝑊2	𝑊2	VERB
cana-3796	144	17	∑	∑	PROPN
cana-3796	144	18	∑	∑	PUNCT
cana-3796	144	19	𝐼(𝑥	𝐼(𝑥	PROPN
cana-3796	144	20	+	+	CCONJ
cana-3796	144	21	𝑖	𝑖	SYM
cana-3796	144	22	,	,	PUNCT
cana-3796	144	23	𝑦	𝑦	NOUN
cana-3796	144	24	+	+	X
cana-3796	144	25	𝑗	𝑗	X
cana-3796	144	26	)	)	PUNCT
cana-3796	144	27	𝑊−1	𝑊−1	NOUN
cana-3796	144	28	2	2	NUM
cana-3796	144	29	𝑗=−	𝑗=−	NOUN
cana-3796	144	30	𝑊−1	𝑊−1	NOUN
cana-3796	145	1	2	2	NUM
cana-3796	145	2	𝑊−1	𝑊−1	NOUN
cana-3796	145	3	2	2	NUM
cana-3796	145	4	𝑖=−	𝑖=−	NUM
cana-3796	145	5	𝑊−1	𝑊−1	NOUN
cana-3796	145	6	2	2	NUM
cana-3796	145	7	…	…	PUNCT
cana-3796	145	8	(	(	PUNCT
cana-3796	145	9	2	2	NUM
cana-3796	145	10	)	)	PUNCT
cana-3796	145	11	where	where	SCONJ
cana-3796	145	12	,	,	PUNCT
cana-3796	145	13	w	w	PROPN
cana-3796	145	14	is	be	AUX
cana-3796	145	15	the	the	DET
cana-3796	145	16	size	size	NOUN
cana-3796	145	17	of	of	ADP
cana-3796	145	18	the	the	DET
cana-3796	145	19	neighborhood	neighborhood	NOUN
cana-3796	145	20	(	(	PUNCT
cana-3796	145	21	block	block	NOUN
cana-3796	145	22	size	size	NOUN
cana-3796	145	23	)	)	PUNCT
cana-3796	145	24	,	,	PUNCT
cana-3796	145	25	and	and	CCONJ
cana-3796	145	26	i(x+i	i(x+i	ADP
cana-3796	145	27	,	,	PUNCT
cana-3796	145	28	y+j	y+j	NUM
cana-3796	145	29	)	)	PUNCT
cana-3796	145	30	is	be	AUX
cana-3796	145	31	the	the	DET
cana-3796	145	32	intensity	intensity	NOUN
cana-3796	145	33	of	of	ADP
cana-3796	145	34	the	the	DET
cana-3796	145	35	pixel	pixel	NOUN
cana-3796	145	36	at	at	ADP
cana-3796	145	37	coordinates	coordinate	NOUN
cana-3796	145	38	(	(	PUNCT
cana-3796	145	39	x+i	x+i	PROPN
cana-3796	145	40	,	,	PUNCT
cana-3796	145	41	y+j	y+j	NUM
cana-3796	145	42	)	)	PUNCT
cana-3796	145	43	for	for	ADP
cana-3796	145	44	different	different	ADJ
cana-3796	145	45	scans	scan	NOUN
cana-3796	145	46	.	.	PUNCT
cana-3796	146	1	following	follow	VERB
cana-3796	146	2	adaptive	adaptive	ADJ
cana-3796	146	3	thresholding	thresholding	NOUN
cana-3796	146	4	,	,	PUNCT
cana-3796	146	5	the	the	DET
cana-3796	146	6	model	model	NOUN
cana-3796	146	7	applies	apply	VERB
cana-3796	146	8	gaussian	gaussian	NOUN
cana-3796	146	9	blurring	blurring	NOUN
cana-3796	146	10	to	to	PART
cana-3796	146	11	reduce	reduce	VERB
cana-3796	146	12	noise	noise	NOUN
cana-3796	146	13	and	and	CCONJ
cana-3796	146	14	smoothen	smoothen	ADV
cana-3796	146	15	the	the	DET
cana-3796	146	16	image	image	NOUN
cana-3796	146	17	samples	sample	NOUN
cana-3796	146	18	.	.	PUNCT
cana-3796	147	1	gaussian	gaussian	ADJ
cana-3796	147	2	blurring	blurring	NOUN
cana-3796	147	3	is	be	AUX
cana-3796	147	4	implemented	implement	VERB
cana-3796	147	5	using	use	VERB
cana-3796	147	6	a	a	DET
cana-3796	147	7	gaussian	gaussian	ADJ
cana-3796	147	8	filter	filter	NOUN
cana-3796	147	9	,	,	PUNCT
cana-3796	147	10	via	via	ADP
cana-3796	147	11	equation	equation	NOUN
cana-3796	147	12	3	3	NUM
cana-3796	147	13	,	,	PUNCT
cana-3796	147	14	𝐺(𝑥	𝐺(𝑥	NOUN
cana-3796	147	15	,	,	PUNCT
cana-3796	147	16	𝑦	𝑦	NOUN
cana-3796	147	17	)	)	PUNCT
cana-3796	147	18	=	=	SYM
cana-3796	147	19	1	1	NUM
cana-3796	147	20	2𝜋𝜎2	2𝜋𝜎2	NUM
cana-3796	147	21	𝑒	𝑒	PRON
cana-3796	147	22	−	−	PROPN
cana-3796	147	23	𝑥2+𝑦2	𝑥2+𝑦2	PROPN
cana-3796	147	24	2𝜎2	2𝜎2	NUM
cana-3796	147	25	…	…	PUNCT
cana-3796	147	26	(	(	PUNCT
cana-3796	147	27	3	3	NUM
cana-3796	147	28	)	)	PUNCT
cana-3796	147	29	where	where	SCONJ
cana-3796	147	30	,	,	PUNCT
cana-3796	147	31	g(x	g(x	PROPN
cana-3796	147	32	,	,	PUNCT
cana-3796	147	33	y	y	NOUN
cana-3796	147	34	)	)	PUNCT
cana-3796	147	35	represents	represent	VERB
cana-3796	147	36	the	the	DET
cana-3796	147	37	gaussian	gaussian	ADJ
cana-3796	147	38	function	function	NOUN
cana-3796	147	39	,	,	PUNCT
cana-3796	147	40	where	where	SCONJ
cana-3796	147	41	σ	σ	PROPN
cana-3796	147	42	is	be	AUX
cana-3796	147	43	the	the	DET
cana-3796	147	44	standard	standard	ADJ
cana-3796	147	45	deviation	deviation	NOUN
cana-3796	147	46	of	of	ADP
cana-3796	147	47	the	the	DET
cana-3796	147	48	gaussian	gaussian	ADJ
cana-3796	147	49	distribution	distribution	NOUN
cana-3796	147	50	,	,	PUNCT
cana-3796	147	51	and	and	CCONJ
cana-3796	147	52	x	x	X
cana-3796	147	53	,	,	PUNCT
cana-3796	147	54	y	y	PROPN
cana-3796	147	55	are	be	AUX
cana-3796	147	56	the	the	DET
cana-3796	147	57	distances	distance	NOUN
cana-3796	147	58	from	from	ADP
cana-3796	147	59	the	the	DET
cana-3796	147	60	origin	origin	NOUN
cana-3796	147	61	in	in	ADP
cana-3796	147	62	the	the	DET
cana-3796	147	63	horizontal	horizontal	ADJ
cana-3796	147	64	and	and	CCONJ
cana-3796	147	65	vertical	vertical	ADJ
cana-3796	147	66	axes	axis	NOUN
cana-3796	147	67	.	.	PUNCT
cana-3796	148	1	the	the	DET
cana-3796	148	2	blurring	blur	VERB
cana-3796	148	3	effect	effect	NOUN
cana-3796	148	4	is	be	AUX
cana-3796	148	5	achieved	achieve	VERB
cana-3796	148	6	by	by	ADP
cana-3796	148	7	convolving	convolve	VERB
cana-3796	148	8	the	the	DET
cana-3796	148	9	gaussian	gaussian	ADJ
cana-3796	148	10	filter	filter	NOUN
cana-3796	148	11	with	with	ADP
cana-3796	148	12	the	the	DET
cana-3796	148	13	image	image	NOUN
cana-3796	148	14	,	,	PUNCT
cana-3796	148	15	as	as	SCONJ
cana-3796	148	16	described	describe	VERB
cana-3796	148	17	via	via	ADP
cana-3796	148	18	equation	equation	NOUN
cana-3796	148	19	4	4	NUM
cana-3796	148	20	,	,	PUNCT
cana-3796	148	21	𝐵(𝑥	𝐵(𝑥	PRON
cana-3796	148	22	,	,	PUNCT
cana-3796	148	23	𝑦	𝑦	NOUN
cana-3796	148	24	)	)	PUNCT
cana-3796	148	25	=	=	SYM
cana-3796	149	1	∑	∑	PROPN
cana-3796	149	2	∑	∑	PROPN
cana-3796	149	3	𝐺(𝑖	𝐺(𝑖	PROPN
cana-3796	149	4	,	,	PUNCT
cana-3796	149	5	𝑗	𝑗	NOUN
cana-3796	149	6	)	)	PUNCT
cana-3796	149	7	⋅	⋅	PROPN
cana-3796	149	8	𝐼(𝑥	𝐼(𝑥	PUNCT
cana-3796	149	9	+	+	CCONJ
cana-3796	149	10	𝑖	𝑖	SYM
cana-3796	149	11	,	,	PUNCT
cana-3796	149	12	𝑦	𝑦	NOUN
cana-3796	149	13	+	+	X
cana-3796	149	14	𝑗	𝑗	NOUN
cana-3796	149	15	)	)	PUNCT
cana-3796	149	16	𝑘	𝑘	PROPN
cana-3796	149	17	𝑗=−𝑘	𝑗=−𝑘	NOUN
cana-3796	149	18	𝑘	𝑘	INTJ
cana-3796	149	19	𝑖=−𝑘	𝑖=−𝑘	NOUN
cana-3796	149	20	…	…	PUNCT
cana-3796	149	21	(	(	PUNCT
cana-3796	149	22	4	4	NUM
cana-3796	149	23	)	)	PUNCT
cana-3796	149	24	where	where	SCONJ
cana-3796	149	25	,	,	PUNCT
cana-3796	149	26	b(x	b(x	NOUN
cana-3796	149	27	,	,	PUNCT
cana-3796	149	28	y	y	NOUN
cana-3796	149	29	)	)	PUNCT
cana-3796	149	30	is	be	AUX
cana-3796	149	31	the	the	DET
cana-3796	149	32	blurred	blurred	ADJ
cana-3796	149	33	image	image	NOUN
cana-3796	149	34	,	,	PUNCT
cana-3796	149	35	k	k	PROPN
cana-3796	149	36	is	be	AUX
cana-3796	149	37	the	the	DET
cana-3796	149	38	kernel	kernel	PROPN
cana-3796	149	39	radius	radius	NOUN
cana-3796	149	40	,	,	PUNCT
cana-3796	149	41	and	and	CCONJ
cana-3796	149	42	i(x+i	i(x+i	ADP
cana-3796	149	43	,	,	PUNCT
cana-3796	149	44	y+j	y+j	NUM
cana-3796	149	45	)	)	PUNCT
cana-3796	149	46	is	be	AUX
cana-3796	149	47	the	the	DET
cana-3796	149	48	intensity	intensity	NOUN
cana-3796	149	49	of	of	ADP
cana-3796	149	50	the	the	DET
cana-3796	149	51	pixel	pixel	NOUN
cana-3796	149	52	at	at	ADP
cana-3796	149	53	coordinates	coordinate	NOUN
cana-3796	149	54	(	(	PUNCT
cana-3796	149	55	x+i	x+i	PROPN
cana-3796	149	56	,	,	PUNCT
cana-3796	149	57	y+j	y+j	NUM
cana-3796	149	58	)	)	PUNCT
cana-3796	149	59	for	for	ADP
cana-3796	149	60	the	the	DET
cana-3796	149	61	image	image	NOUN
cana-3796	149	62	scans	scan	NOUN
cana-3796	149	63	.	.	PUNCT
cana-3796	150	1	the	the	DET
cana-3796	150	2	combination	combination	NOUN
cana-3796	150	3	of	of	ADP
cana-3796	150	4	adaptive	adaptive	ADJ
cana-3796	150	5	thresholding	thresholding	NOUN
cana-3796	150	6	and	and	CCONJ
cana-3796	150	7	gaussian	gaussian	ADJ
cana-3796	150	8	blurring	blurring	NOUN
cana-3796	150	9	results	result	NOUN
cana-3796	150	10	in	in	ADP
cana-3796	150	11	an	an	DET
cana-3796	150	12	enhanced	enhanced	ADJ
cana-3796	150	13	binary	binary	ADJ
cana-3796	150	14	image	image	NOUN
cana-3796	150	15	,	,	PUNCT
cana-3796	150	16	which	which	PRON
cana-3796	150	17	is	be	AUX
cana-3796	150	18	instrumental	instrumental	ADJ
cana-3796	150	19	for	for	ADP
cana-3796	150	20	the	the	DET
cana-3796	150	21	feature	feature	NOUN
cana-3796	150	22	extraction	extraction	NOUN
cana-3796	150	23	stages	stage	NOUN
cana-3796	150	24	.	.	PUNCT
cana-3796	151	1	the	the	DET
cana-3796	151	2	samples	sample	NOUN
cana-3796	151	3	displayed	display	VERB
cana-3796	151	4	in	in	ADP
cana-3796	151	5	figure	figure	NOUN
cana-3796	151	6	communications	communication	NOUN
cana-3796	151	7	on	on	ADP
cana-3796	151	8	applied	apply	VERB
cana-3796	151	9	nonlinear	nonlinear	ADJ
cana-3796	151	10	analysis	analysis	NOUN
cana-3796	151	11	issn	issn	NOUN
cana-3796	151	12	:	:	PUNCT
cana-3796	151	13	1074	1074	NUM
cana-3796	151	14	-	-	PUNCT
cana-3796	151	15	133x	133x	NUM
cana-3796	151	16	vol	vol	NOUN
cana-3796	151	17	32	32	NUM
cana-3796	151	18	no	no	NOUN
cana-3796	151	19	.	.	PUNCT
cana-3796	152	1	8s	8s	PROPN
cana-3796	152	2	(	(	PUNCT
cana-3796	152	3	2025	2025	NUM
cana-3796	152	4	)	)	PUNCT
cana-3796	152	5	751	751	NUM
cana-3796	152	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	152	7	3	3	NUM
cana-3796	152	8	provide	provide	VERB
cana-3796	152	9	an	an	DET
cana-3796	152	10	overview	overview	NOUN
cana-3796	152	11	of	of	ADP
cana-3796	152	12	the	the	DET
cana-3796	152	13	image	image	NOUN
cana-3796	152	14	preprocessing	preprocesse	VERB
cana-3796	152	15	techniques	technique	NOUN
cana-3796	152	16	,	,	PUNCT
cana-3796	152	17	with	with	ADP
cana-3796	152	18	original	original	ADJ
cana-3796	152	19	image	image	NOUN
cana-3796	152	20	as	as	ADP
cana-3796	152	21	(	(	PUNCT
cana-3796	152	22	a	a	NOUN
cana-3796	152	23	)	)	PUNCT
cana-3796	152	24	,	,	PUNCT
cana-3796	152	25	after	after	ADP
cana-3796	152	26	adaptive	adaptive	ADJ
cana-3796	152	27	thresholding	thresholding	NOUN
cana-3796	152	28	as	as	ADP
cana-3796	152	29	(	(	PUNCT
cana-3796	152	30	b	b	NOUN
cana-3796	152	31	)	)	PUNCT
cana-3796	152	32	,	,	PUNCT
cana-3796	152	33	after	after	ADP
cana-3796	152	34	gaussian	gaussian	NOUN
cana-3796	152	35	blurringthe	blurringthe	DET
cana-3796	152	36	preprocessed	preprocesse	VERB
cana-3796	152	37	image	image	NOUN
cana-3796	152	38	(	(	PUNCT
cana-3796	152	39	c	c	NOUN
cana-3796	152	40	)	)	PUNCT
cana-3796	152	41	.	.	PUNCT
cana-3796	153	1	figure	figure	VERB
cana-3796	153	2	3	3	NUM
cana-3796	153	3	.	.	PUNCT
cana-3796	154	1	(	(	PUNCT
cana-3796	154	2	a	a	X
cana-3796	154	3	)	)	PUNCT
cana-3796	154	4	original	original	ADJ
cana-3796	154	5	image	image	NOUN
cana-3796	154	6	(	(	PUNCT
cana-3796	154	7	b	b	NOUN
cana-3796	154	8	)	)	PUNCT
cana-3796	154	9	after	after	ADP
cana-3796	154	10	adaptive	adaptive	ADJ
cana-3796	154	11	thresholding	thresholding	NOUN
cana-3796	154	12	(	(	PUNCT
cana-3796	154	13	c	c	NOUN
cana-3796	154	14	)	)	PUNCT
cana-3796	154	15	after	after	ADP
cana-3796	154	16	gaussian	gaussian	ADJ
cana-3796	154	17	blurring	blurring	NOUN
cana-3796	154	18	b.	b.	PROPN
cana-3796	154	19	data	data	PROPN
cana-3796	154	20	augmentation	augmentation	NOUN
cana-3796	154	21	prior	prior	ADV
cana-3796	154	22	to	to	ADP
cana-3796	154	23	data	datum	NOUN
cana-3796	154	24	augmentation	augmentation	NOUN
cana-3796	154	25	,	,	PUNCT
cana-3796	154	26	segmentation	segmentation	NOUN
cana-3796	154	27	and	and	CCONJ
cana-3796	154	28	recognition	recognition	NOUN
cana-3796	154	29	are	be	AUX
cana-3796	154	30	applied	apply	VERB
cana-3796	154	31	to	to	PART
cana-3796	154	32	identify	identify	VERB
cana-3796	154	33	text	text	NOUN
cana-3796	154	34	regions	region	NOUN
cana-3796	154	35	and	and	CCONJ
cana-3796	154	36	bounding	bounding	NOUN
cana-3796	154	37	boxes	box	NOUN
cana-3796	154	38	.	.	PUNCT
cana-3796	155	1	these	these	DET
cana-3796	155	2	bounding	bounding	NOUN
cana-3796	155	3	boxes	box	NOUN
cana-3796	155	4	are	be	AUX
cana-3796	155	5	drawn	draw	VERB
cana-3796	155	6	on	on	ADP
cana-3796	155	7	the	the	DET
cana-3796	155	8	preprocessed	preprocesse	VERB
cana-3796	155	9	image	image	NOUN
cana-3796	155	10	,	,	PUNCT
cana-3796	155	11	as	as	SCONJ
cana-3796	155	12	shown	show	VERB
cana-3796	155	13	in	in	ADP
cana-3796	155	14	figure	figure	NOUN
cana-3796	155	15	4(a	4(a	NUM
cana-3796	155	16	)	)	PUNCT
cana-3796	155	17	,	,	PUNCT
cana-3796	155	18	and	and	CCONJ
cana-3796	155	19	visualized	visualize	VERB
cana-3796	155	20	in	in	ADP
cana-3796	155	21	figure	figure	NOUN
cana-3796	155	22	4(b	4(b	NUM
cana-3796	155	23	)	)	PUNCT
cana-3796	155	24	.	.	PUNCT
cana-3796	156	1	in	in	ADP
cana-3796	156	2	the	the	DET
cana-3796	156	3	subsequent	subsequent	ADJ
cana-3796	156	4	phase	phase	NOUN
cana-3796	156	5	,	,	PUNCT
cana-3796	156	6	data	datum	NOUN
cana-3796	156	7	augmentation	augmentation	NOUN
cana-3796	156	8	plays	play	VERB
cana-3796	156	9	a	a	DET
cana-3796	156	10	crucial	crucial	ADJ
cana-3796	156	11	role	role	NOUN
cana-3796	156	12	in	in	ADP
cana-3796	156	13	text	text	NOUN
cana-3796	156	14	recognition	recognition	NOUN
cana-3796	156	15	systems	system	NOUN
cana-3796	156	16	by	by	ADP
cana-3796	156	17	enhancing	enhance	VERB
cana-3796	156	18	model	model	NOUN
cana-3796	156	19	robustness	robustness	NOUN
cana-3796	156	20	through	through	ADP
cana-3796	156	21	the	the	DET
cana-3796	156	22	generation	generation	NOUN
cana-3796	156	23	of	of	ADP
cana-3796	156	24	varied	varied	ADJ
cana-3796	156	25	training	training	NOUN
cana-3796	156	26	samples	sample	NOUN
cana-3796	156	27	.	.	PUNCT
cana-3796	157	1	techniques	technique	NOUN
cana-3796	157	2	such	such	ADJ
cana-3796	157	3	as	as	ADP
cana-3796	157	4	elastic	elastic	ADJ
cana-3796	157	5	distortion	distortion	NOUN
cana-3796	157	6	and	and	CCONJ
cana-3796	157	7	affine	affine	NOUN
cana-3796	157	8	transformations	transformation	NOUN
cana-3796	157	9	simulate	simulate	VERB
cana-3796	157	10	differences	difference	NOUN
cana-3796	157	11	in	in	ADP
cana-3796	157	12	handwriting	handwriting	NOUN
cana-3796	157	13	styles	style	NOUN
cana-3796	157	14	and	and	CCONJ
cana-3796	157	15	text	text	NOUN
cana-3796	157	16	orientations	orientation	NOUN
cana-3796	157	17	,	,	PUNCT
cana-3796	157	18	as	as	SCONJ
cana-3796	157	19	depicted	depict	VERB
cana-3796	157	20	after	after	ADP
cana-3796	157	21	segmentation	segmentation	NOUN
cana-3796	157	22	in	in	ADP
cana-3796	157	23	figures	figure	NOUN
cana-3796	157	24	4(c	4(c	NUM
cana-3796	157	25	)	)	PUNCT
cana-3796	157	26	and	and	CCONJ
cana-3796	157	27	4(d	4(d	NUM
cana-3796	157	28	)	)	PUNCT
cana-3796	157	29	.	.	PUNCT
cana-3796	158	1	this	this	DET
cana-3796	158	2	strategy	strategy	NOUN
cana-3796	158	3	improves	improve	VERB
cana-3796	158	4	generalization	generalization	NOUN
cana-3796	158	5	,	,	PUNCT
cana-3796	158	6	reduces	reduce	VERB
cana-3796	158	7	overfitting	overfitting	NOUN
cana-3796	158	8	,	,	PUNCT
cana-3796	158	9	and	and	CCONJ
cana-3796	158	10	allows	allow	VERB
cana-3796	158	11	models	model	NOUN
cana-3796	158	12	to	to	PART
cana-3796	158	13	perform	perform	VERB
cana-3796	158	14	more	more	ADV
cana-3796	158	15	effectively	effectively	ADV
cana-3796	158	16	in	in	ADP
cana-3796	158	17	real	real	ADJ
cana-3796	158	18	-	-	PUNCT
cana-3796	158	19	world	world	NOUN
cana-3796	158	20	scenarios	scenario	NOUN
cana-3796	158	21	.	.	PUNCT
cana-3796	159	1	implementing	implement	VERB
cana-3796	159	2	data	datum	NOUN
cana-3796	159	3	augmentation	augmentation	NOUN
cana-3796	159	4	significantly	significantly	ADV
cana-3796	159	5	boosts	boost	VERB
cana-3796	159	6	the	the	DET
cana-3796	159	7	accuracy	accuracy	NOUN
cana-3796	159	8	and	and	CCONJ
cana-3796	159	9	reliability	reliability	NOUN
cana-3796	159	10	of	of	ADP
cana-3796	159	11	text	text	NOUN
cana-3796	159	12	recognition	recognition	NOUN
cana-3796	159	13	applications	application	NOUN
cana-3796	159	14	.	.	PUNCT
cana-3796	160	1	the	the	DET
cana-3796	160	2	preprocessed	preprocesse	VERB
cana-3796	160	3	image	image	NOUN
cana-3796	160	4	was	be	AUX
cana-3796	160	5	selected	select	VERB
cana-3796	160	6	for	for	ADP
cana-3796	160	7	segmentation	segmentation	NOUN
cana-3796	160	8	using	use	VERB
cana-3796	160	9	bounding	bounding	NOUN
cana-3796	160	10	boxes	box	NOUN
cana-3796	160	11	,	,	PUNCT
cana-3796	160	12	followed	follow	VERB
cana-3796	160	13	by	by	ADP
cana-3796	160	14	the	the	DET
cana-3796	160	15	application	application	NOUN
cana-3796	160	16	of	of	ADP
cana-3796	160	17	data	datum	NOUN
cana-3796	160	18	augmentation	augmentation	NOUN
cana-3796	160	19	techniques	technique	NOUN
cana-3796	160	20	.	.	PUNCT
cana-3796	161	1	the	the	DET
cana-3796	161	2	results	result	NOUN
cana-3796	161	3	of	of	ADP
cana-3796	161	4	this	this	DET
cana-3796	161	5	process	process	NOUN
cana-3796	161	6	are	be	AUX
cana-3796	161	7	illustrated	illustrate	VERB
cana-3796	161	8	in	in	ADP
cana-3796	161	9	figure	figure	NOUN
cana-3796	161	10	4	4	NUM
cana-3796	161	11	.	.	PUNCT
cana-3796	161	12	c.	c.	NOUN
cana-3796	161	13	feature	feature	NOUN
cana-3796	161	14	extraction	extraction	NOUN
cana-3796	161	15	the	the	DET
cana-3796	161	16	preprocessing	preprocessing	NOUN
cana-3796	161	17	phase	phase	NOUN
cana-3796	161	18	and	and	CCONJ
cana-3796	161	19	augmentation	augmentation	NOUN
cana-3796	161	20	phase	phase	NOUN
cana-3796	161	21	ensures	ensure	VERB
cana-3796	161	22	robust	robust	ADJ
cana-3796	161	23	feature	feature	NOUN
cana-3796	161	24	extraction	extraction	NOUN
cana-3796	161	25	by	by	ADP
cana-3796	161	26	addressing	address	VERB
cana-3796	161	27	the	the	DET
cana-3796	161	28	variability	variability	NOUN
cana-3796	161	29	in	in	ADP
cana-3796	161	30	handwritten	handwritten	ADJ
cana-3796	161	31	texts	text	NOUN
cana-3796	161	32	.	.	PUNCT
cana-3796	162	1	these	these	DET
cana-3796	162	2	pre	pre	ADJ
cana-3796	162	3	-	-	ADJ
cana-3796	162	4	processed	processed	ADJ
cana-3796	162	5	images	image	NOUN
cana-3796	162	6	are	be	AUX
cana-3796	162	7	further	far	ADV
cana-3796	162	8	analyzed	analyze	VERB
cana-3796	162	9	using	use	VERB
cana-3796	162	10	an	an	DET
cana-3796	162	11	efficient	efficient	ADJ
cana-3796	162	12	fusion	fusion	NOUN
cana-3796	162	13	of	of	ADP
cana-3796	162	14	convolutional	convolutional	ADJ
cana-3796	162	15	neural	neural	ADJ
cana-3796	162	16	networks	network	NOUN
cana-3796	162	17	(	(	PUNCT
cana-3796	162	18	cnns	cnns	PROPN
cana-3796	162	19	)	)	PUNCT
cana-3796	162	20	with	with	ADP
cana-3796	162	21	resnet101	resnet101	PROPN
cana-3796	162	22	and	and	CCONJ
cana-3796	162	23	inception	inception	VERB
cana-3796	162	24	net	net	NOUN
cana-3796	162	25	,	,	PUNCT
cana-3796	162	26	which	which	PRON
cana-3796	162	27	plays	play	VERB
cana-3796	162	28	a	a	DET
cana-3796	162	29	pivotal	pivotal	ADJ
cana-3796	162	30	role	role	NOUN
cana-3796	162	31	in	in	ADP
cana-3796	162	32	deciphering	decipher	VERB
cana-3796	162	33	the	the	DET
cana-3796	162	34	complexities	complexity	NOUN
cana-3796	162	35	of	of	ADP
cana-3796	162	36	the	the	DET
cana-3796	162	37	telugu	telugu	NOUN
cana-3796	162	38	scripts	script	NOUN
cana-3796	162	39	.	.	PUNCT
cana-3796	163	1	this	this	DET
cana-3796	163	2	fusion	fusion	NOUN
cana-3796	163	3	is	be	AUX
cana-3796	163	4	designed	design	VERB
cana-3796	163	5	to	to	PART
cana-3796	163	6	capture	capture	VERB
cana-3796	163	7	the	the	DET
cana-3796	163	8	script	script	NOUN
cana-3796	163	9	's	's	PART
cana-3796	163	10	nuances	nuance	NOUN
cana-3796	163	11	,	,	PUNCT
cana-3796	163	12	distinguishing	distinguish	VERB
cana-3796	163	13	between	between	ADP
cana-3796	163	14	the	the	DET
cana-3796	163	15	finely	finely	ADV
cana-3796	163	16	varied	varied	ADJ
cana-3796	163	17	strokes	stroke	NOUN
cana-3796	163	18	and	and	CCONJ
cana-3796	163	19	shapes	shape	NOUN
cana-3796	163	20	of	of	ADP
cana-3796	163	21	characters	character	NOUN
cana-3796	163	22	and	and	CCONJ
cana-3796	163	23	words	word	NOUN
cana-3796	163	24	.	.	PUNCT
cana-3796	164	1	resnet101	resnet101	PROPN
cana-3796	164	2	uses	use	VERB
cana-3796	164	3	residual	residual	ADJ
cana-3796	164	4	blocks	block	NOUN
cana-3796	164	5	defined	define	VERB
cana-3796	164	6	via	via	ADP
cana-3796	164	7	equation	equation	NOUN
cana-3796	164	8	5	5	NUM
cana-3796	164	9	:	:	PUNCT
cana-3796	164	10	𝐹(𝑥	𝐹(𝑥	NUM
cana-3796	164	11	,	,	PUNCT
cana-3796	164	12	{	{	PUNCT
cana-3796	164	13	𝑊𝑖	𝑊𝑖	PROPN
cana-3796	164	14	}	}	PUNCT
cana-3796	164	15	)	)	PUNCT
cana-3796	165	1	+	+	CCONJ
cana-3796	165	2	𝑥	𝑥	X
cana-3796	165	3	=	=	SYM
cana-3796	165	4	𝑦	𝑦	NOUN
cana-3796	165	5	…	…	PUNCT
cana-3796	165	6	(	(	PUNCT
cana-3796	165	7	5	5	NUM
cana-3796	165	8	)	)	PUNCT
cana-3796	165	9	while	while	SCONJ
cana-3796	165	10	inception	inception	ADJ
cana-3796	165	11	net	net	ADJ
cana-3796	165	12	combines	combine	VERB
cana-3796	165	13	filters	filter	NOUN
cana-3796	165	14	of	of	ADP
cana-3796	165	15	varying	vary	VERB
cana-3796	165	16	sizes	size	NOUN
cana-3796	165	17	:	:	PUNCT
cana-3796	165	18	𝐼(𝑦	𝐼(𝑦	X
cana-3796	165	19	)	)	PUNCT
cana-3796	165	20	=	=	SYM
cana-3796	165	21	∑	∑	PUNCT
cana-3796	165	22	𝐻𝑖(𝑥	𝐻𝑖(𝑥	PROPN
cana-3796	165	23	)	)	PUNCT
cana-3796	165	24	𝑛	𝑛	PRON
cana-3796	165	25	𝑖=1	𝑖=1	PROPN
cana-3796	165	26	…	…	PUNCT
cana-3796	165	27	(	(	PUNCT
cana-3796	165	28	6	6	X
cana-3796	165	29	)	)	PUNCT
cana-3796	165	30	their	their	PRON
cana-3796	165	31	fusion	fusion	NOUN
cana-3796	165	32	is	be	AUX
cana-3796	165	33	expressed	express	VERB
cana-3796	165	34	as	as	ADP
cana-3796	165	35	:	:	PUNCT
cana-3796	165	36	𝑀(𝑥	𝑀(𝑥	NUM
cana-3796	165	37	)	)	PUNCT
cana-3796	165	38	=	=	PUNCT
cana-3796	165	39	𝑅(𝑥	𝑅(𝑥	NOUN
cana-3796	165	40	)	)	PUNCT
cana-3796	165	41	+	+	CCONJ
cana-3796	165	42	𝐼(𝑥	𝐼(𝑥	X
cana-3796	165	43	)	)	PUNCT
cana-3796	165	44	…	…	PUNCT
cana-3796	165	45	(	(	PUNCT
cana-3796	165	46	7	7	X
cana-3796	165	47	)	)	PUNCT
cana-3796	165	48	the	the	DET
cana-3796	165	49	segmented	segment	VERB
cana-3796	165	50	image	image	NOUN
cana-3796	165	51	,	,	PUNCT
cana-3796	165	52	after	after	ADP
cana-3796	165	53	undergoing	undergo	VERB
cana-3796	165	54	data	datum	NOUN
cana-3796	165	55	augmentation	augmentation	NOUN
cana-3796	165	56	,	,	PUNCT
cana-3796	165	57	has	have	AUX
cana-3796	165	58	been	be	AUX
cana-3796	165	59	subjected	subject	VERB
cana-3796	165	60	to	to	PART
cana-3796	165	61	feature	feature	VERB
cana-3796	165	62	extraction	extraction	NOUN
cana-3796	165	63	using	use	VERB
cana-3796	165	64	resnet50	resnet50	NOUN
cana-3796	165	65	,	,	PUNCT
cana-3796	165	66	as	as	SCONJ
cana-3796	165	67	shown	show	VERB
cana-3796	165	68	in	in	ADP
cana-3796	165	69	figure-4(e	figure-4(e	PROPN
cana-3796	165	70	)	)	PUNCT
cana-3796	165	71	.	.	PUNCT
cana-3796	166	1	top	top	ADJ
cana-3796	166	2	3	3	NUM
cana-3796	166	3	predictions	prediction	NOUN
cana-3796	166	4	from	from	ADP
cana-3796	166	5	resnet50	resnet50	NOUN
cana-3796	166	6	model	model	PROPN
cana-3796	166	7	:	:	PUNCT
cana-3796	166	8	communications	communication	NOUN
cana-3796	166	9	on	on	ADP
cana-3796	166	10	applied	apply	VERB
cana-3796	166	11	nonlinear	nonlinear	ADJ
cana-3796	166	12	analysis	analysis	NOUN
cana-3796	166	13	issn	issn	NOUN
cana-3796	166	14	:	:	PUNCT
cana-3796	166	15	1074	1074	NUM
cana-3796	166	16	-	-	PUNCT
cana-3796	166	17	133x	133x	NUM
cana-3796	166	18	vol	vol	NOUN
cana-3796	166	19	32	32	NUM
cana-3796	166	20	no	no	NOUN
cana-3796	166	21	.	.	PUNCT
cana-3796	167	1	8s	8s	PROPN
cana-3796	167	2	(	(	PUNCT
cana-3796	167	3	2025	2025	NUM
cana-3796	167	4	)	)	PUNCT
cana-3796	167	5	752	752	NUM
cana-3796	167	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	167	7	▪	▪	X
cana-3796	167	8	menu	menu	NOUN
cana-3796	167	9	with	with	ADP
cana-3796	167	10	probability	probability	NOUN
cana-3796	167	11	0.87	0.87	NUM
cana-3796	167	12	▪	▪	ADJ
cana-3796	167	13	binder	binder	NOUN
cana-3796	167	14	with	with	ADP
cana-3796	167	15	probability	probability	NOUN
cana-3796	167	16	0.06	0.06	NUM
cana-3796	167	17	▪	▪	ADJ
cana-3796	167	18	envelope	envelope	NOUN
cana-3796	167	19	with	with	ADP
cana-3796	167	20	probability	probability	NOUN
cana-3796	167	21	0.03	0.03	NUM
cana-3796	167	22	figure	figure	NOUN
cana-3796	167	23	4	4	NUM
cana-3796	167	24	.	.	PUNCT
cana-3796	168	1	(	(	PUNCT
cana-3796	168	2	a	a	X
cana-3796	168	3	)	)	PUNCT
cana-3796	168	4	preprocessed	preprocesse	VERB
cana-3796	168	5	image	image	NOUN
cana-3796	168	6	(	(	PUNCT
cana-3796	168	7	b	b	NOUN
cana-3796	168	8	)	)	PUNCT
cana-3796	168	9	segmented	segment	VERB
cana-3796	168	10	image	image	NOUN
cana-3796	168	11	with	with	ADP
cana-3796	168	12	bounding	bounding	NOUN
cana-3796	168	13	boxes	box	NOUN
cana-3796	168	14	(	(	PUNCT
cana-3796	168	15	c	c	NOUN
cana-3796	168	16	)	)	PUNCT
cana-3796	168	17	elastic	elastic	ADJ
cana-3796	168	18	distortion	distortion	NOUN
cana-3796	168	19	(	(	PUNCT
cana-3796	168	20	d	d	NOUN
cana-3796	168	21	)	)	PUNCT
cana-3796	168	22	affine	affine	NOUN
cana-3796	168	23	transformation	transformation	NOUN
cana-3796	168	24	(	(	PUNCT
cana-3796	168	25	data	data	NOUN
cana-3796	168	26	augmentation	augmentation	NOUN
cana-3796	168	27	functions	function	NOUN
cana-3796	168	28	)	)	PUNCT
cana-3796	168	29	(	(	PUNCT
cana-3796	168	30	e	e	NOUN
cana-3796	168	31	)	)	PUNCT
cana-3796	168	32	feature	feature	NOUN
cana-3796	168	33	extraction	extraction	NOUN
cana-3796	168	34	d.	d.	NOUN
cana-3796	168	35	quad	quad	ADV
cana-3796	168	36	lstm	lstm	PROPN
cana-3796	168	37	processing	processing	NOUN
cana-3796	168	38	from	from	ADP
cana-3796	168	39	the	the	DET
cana-3796	168	40	internal	internal	ADJ
cana-3796	168	41	architectural	architectural	ADJ
cana-3796	168	42	details	detail	NOUN
cana-3796	168	43	shown	show	VERB
cana-3796	168	44	in	in	ADP
cana-3796	168	45	figure-2	figure-2	PROPN
cana-3796	168	46	,	,	PUNCT
cana-3796	168	47	the	the	DET
cana-3796	168	48	proposed	propose	VERB
cana-3796	168	49	model	model	NOUN
cana-3796	168	50	leverages	leverage	VERB
cana-3796	168	51	a	a	DET
cana-3796	168	52	quadlstm	quadlstm	NOUN
cana-3796	168	53	architecture	architecture	NOUN
cana-3796	168	54	to	to	PART
cana-3796	168	55	capture	capture	VERB
cana-3796	168	56	contextual	contextual	ADJ
cana-3796	168	57	information	information	NOUN
cana-3796	168	58	by	by	ADP
cana-3796	168	59	processing	process	VERB
cana-3796	168	60	the	the	DET
cana-3796	168	61	segmented	segment	VERB
cana-3796	168	62	characters	character	NOUN
cana-3796	168	63	in	in	ADP
cana-3796	168	64	four	four	NUM
cana-3796	168	65	orientations	orientation	NOUN
cana-3796	168	66	:	:	PUNCT
cana-3796	168	67	forward	forward	ADV
cana-3796	168	68	,	,	PUNCT
cana-3796	168	69	backward	backward	ADJ
cana-3796	168	70	,	,	PUNCT
cana-3796	168	71	top	top	ADJ
cana-3796	168	72	-	-	PUNCT
cana-3796	168	73	down	down	NOUN
cana-3796	168	74	,	,	PUNCT
cana-3796	168	75	and	and	CCONJ
cana-3796	168	76	bottom	bottom	NOUN
cana-3796	168	77	-	-	PUNCT
cana-3796	168	78	up	up	NOUN
cana-3796	168	79	.	.	PUNCT
cana-3796	169	1	the	the	DET
cana-3796	169	2	quadlstm	quadlstm	NOUN
cana-3796	169	3	's	's	PART
cana-3796	169	4	forward	forward	ADJ
cana-3796	169	5	lstm	lstm	NOUN
cana-3796	169	6	is	be	AUX
cana-3796	169	7	tasked	task	VERB
cana-3796	169	8	with	with	ADP
cana-3796	169	9	processing	process	VERB
cana-3796	169	10	the	the	DET
cana-3796	169	11	segmented	segment	VERB
cana-3796	169	12	characters	character	NOUN
cana-3796	169	13	in	in	ADP
cana-3796	169	14	their	their	PRON
cana-3796	169	15	natural	natural	ADJ
cana-3796	169	16	reading	reading	NOUN
cana-3796	169	17	order	order	NOUN
cana-3796	169	18	,	,	PUNCT
cana-3796	169	19	akin	akin	ADJ
cana-3796	169	20	to	to	ADP
cana-3796	169	21	how	how	SCONJ
cana-3796	169	22	a	a	DET
cana-3796	169	23	person	person	NOUN
cana-3796	169	24	reads	read	VERB
cana-3796	169	25	text	text	NOUN
cana-3796	169	26	.	.	PUNCT
cana-3796	170	1	the	the	DET
cana-3796	170	2	lstm	lstm	ADJ
cana-3796	170	3	layers	layer	NOUN
cana-3796	170	4	are	be	AUX
cana-3796	170	5	applied	apply	VERB
cana-3796	170	6	in	in	ADP
cana-3796	170	7	multiple	multiple	ADJ
cana-3796	170	8	directions	direction	NOUN
cana-3796	170	9	(	(	PUNCT
cana-3796	170	10	forward	forward	ADV
cana-3796	170	11	,	,	PUNCT
cana-3796	170	12	backward	backward	ADJ
cana-3796	170	13	,	,	PUNCT
cana-3796	170	14	top	top	ADJ
cana-3796	170	15	-	-	PUNCT
cana-3796	170	16	down	down	NOUN
cana-3796	170	17	,	,	PUNCT
cana-3796	170	18	bottom	bottom	NOUN
cana-3796	170	19	-	-	PUNCT
cana-3796	170	20	up	up	NOUN
cana-3796	170	21	)	)	PUNCT
cana-3796	170	22	,	,	PUNCT
cana-3796	170	23	as	as	SCONJ
cana-3796	170	24	described	describe	VERB
cana-3796	170	25	below	below	ADV
cana-3796	170	26	.	.	PUNCT
cana-3796	171	1	these	these	DET
cana-3796	171	2	layers	layer	NOUN
cana-3796	171	3	process	process	VERB
cana-3796	171	4	the	the	DET
cana-3796	171	5	reshaped	reshaped	ADJ
cana-3796	171	6	input	input	NOUN
cana-3796	171	7	and	and	CCONJ
cana-3796	171	8	produce	produce	VERB
cana-3796	171	9	sequences	sequence	NOUN
cana-3796	171	10	as	as	ADP
cana-3796	171	11	outputs	output	NOUN
cana-3796	171	12	.	.	PUNCT
cana-3796	172	1	this	this	PRON
cana-3796	172	2	is	be	AUX
cana-3796	172	3	mathematically	mathematically	ADV
cana-3796	172	4	represented	represent	VERB
cana-3796	172	5	via	via	ADP
cana-3796	172	6	equation	equation	NOUN
cana-3796	172	7	8	8	NUM
cana-3796	172	8	,	,	PUNCT
cana-3796	172	9	where	where	SCONJ
cana-3796	172	10	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	172	11	,	,	PUNCT
cana-3796	172	12	𝑓	𝑓	X
cana-3796	172	13	)	)	PUNCT
cana-3796	172	14	ais	ais	PROPN
cana-3796	172	15	the	the	DET
cana-3796	172	16	hidden	hide	VERB
cana-3796	172	17	state	state	NOUN
cana-3796	172	18	at	at	ADP
cana-3796	172	19	time	time	NOUN
cana-3796	172	20	t	t	PROPN
cana-3796	172	21	for	for	ADP
cana-3796	172	22	the	the	DET
cana-3796	172	23	forward	forward	ADJ
cana-3796	172	24	lstm	lstm	NOUN
cana-3796	172	25	via	via	ADP
cana-3796	172	26	equation	equation	NOUN
cana-3796	172	27	8	8	NUM
cana-3796	172	28	,	,	PUNCT
cana-3796	172	29	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	172	30	,	,	PUNCT
cana-3796	172	31	𝑓	𝑓	X
cana-3796	172	32	)	)	PUNCT
cana-3796	172	33	=	=	SYM
cana-3796	173	1	𝐿𝑆𝑇𝑀(ℎ(𝑡	𝐿𝑆𝑇𝑀(ℎ(𝑡	PROPN
cana-3796	174	1	−	−	NOUN
cana-3796	174	2	1	1	NUM
cana-3796	174	3	,	,	PUNCT
cana-3796	174	4	𝑓	𝑓	X
cana-3796	174	5	)	)	PUNCT
cana-3796	174	6	,	,	PUNCT
cana-3796	174	7	𝑥(𝑡	𝑥(𝑡	PROPN
cana-3796	174	8	,	,	PUNCT
cana-3796	174	9	𝑓	𝑓	NOUN
cana-3796	174	10	)	)	PUNCT
cana-3796	174	11	)	)	PUNCT
cana-3796	174	12	…	…	PUNCT
cana-3796	174	13	(	(	PUNCT
cana-3796	174	14	8)	8)	NUM
cana-3796	174	15	in	in	ADP
cana-3796	174	16	contrast	contrast	NOUN
cana-3796	174	17	,	,	PUNCT
cana-3796	174	18	the	the	DET
cana-3796	174	19	backward	backward	ADJ
cana-3796	174	20	lstm	lstm	NOUN
cana-3796	174	21	processes	process	VERB
cana-3796	174	22	the	the	DET
cana-3796	174	23	characters	character	NOUN
cana-3796	174	24	in	in	ADP
cana-3796	174	25	reverse	reverse	NOUN
cana-3796	174	26	,	,	PUNCT
cana-3796	174	27	providing	provide	VERB
cana-3796	174	28	aa	aa	ADP
cana-3796	174	29	retrospective	retrospective	ADJ
cana-3796	174	30	context	context	NOUN
cana-3796	174	31	to	to	ADP
cana-3796	174	32	each	each	DET
cana-3796	174	33	character	character	NOUN
cana-3796	174	34	via	via	ADP
cana-3796	174	35	equation	equation	NOUN
cana-3796	174	36	9	9	NUM
cana-3796	174	37	,	,	PUNCT
cana-3796	174	38	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	174	39	,	,	PUNCT
cana-3796	174	40	𝑏	𝑏	NOUN
cana-3796	174	41	)	)	PUNCT
cana-3796	174	42	=	=	VERB
cana-3796	175	1	𝐿𝑆𝑇𝑀(ℎ(𝑡	𝐿𝑆𝑇𝑀(ℎ(𝑡	PROPN
cana-3796	176	1	+	+	ADJ
cana-3796	176	2	1	1	NUM
cana-3796	176	3	,	,	PUNCT
cana-3796	176	4	𝑏	𝑏	NOUN
cana-3796	176	5	)	)	PUNCT
cana-3796	176	6	,	,	PUNCT
cana-3796	176	7	𝑥(𝑡	𝑥(𝑡	PROPN
cana-3796	176	8	,	,	PUNCT
cana-3796	176	9	𝑏	𝑏	NOUN
cana-3796	176	10	)	)	PUNCT
cana-3796	176	11	)	)	PUNCT
cana-3796	176	12	…	…	PUNCT
cana-3796	176	13	(	(	PUNCT
cana-3796	176	14	9	9	X
cana-3796	176	15	)	)	PUNCT
cana-3796	176	16	the	the	DET
cana-3796	176	17	top	top	ADJ
cana-3796	176	18	-	-	PUNCT
cana-3796	176	19	down	down	ADP
cana-3796	176	20	lstm	lstm	NOUN
cana-3796	176	21	interprets	interpret	VERB
cana-3796	176	22	the	the	DET
cana-3796	176	23	characters	character	NOUN
cana-3796	176	24	from	from	ADP
cana-3796	176	25	the	the	DET
cana-3796	176	26	top	top	NOUN
cana-3796	176	27	of	of	ADP
cana-3796	176	28	the	the	DET
cana-3796	176	29	page	page	NOUN
cana-3796	176	30	to	to	ADP
cana-3796	176	31	the	the	DET
cana-3796	176	32	bottom	bottom	NOUN
cana-3796	176	33	,	,	PUNCT
cana-3796	176	34	mimicking	mimic	VERB
cana-3796	176	35	a	a	DET
cana-3796	176	36	vertical	vertical	ADJ
cana-3796	176	37	reading	reading	NOUN
cana-3796	176	38	pattern	pattern	NOUN
cana-3796	176	39	via	via	ADP
cana-3796	176	40	equation	equation	NOUN
cana-3796	176	41	10	10	NUM
cana-3796	176	42	,	,	PUNCT
cana-3796	176	43	communications	communication	NOUN
cana-3796	176	44	on	on	ADP
cana-3796	176	45	applied	apply	VERB
cana-3796	176	46	nonlinear	nonlinear	ADJ
cana-3796	176	47	analysis	analysis	NOUN
cana-3796	176	48	issn	issn	NOUN
cana-3796	176	49	:	:	PUNCT
cana-3796	176	50	1074	1074	NUM
cana-3796	176	51	-	-	PUNCT
cana-3796	176	52	133x	133x	NUM
cana-3796	176	53	vol	vol	NOUN
cana-3796	176	54	32	32	NUM
cana-3796	176	55	no	no	NOUN
cana-3796	176	56	.	.	PUNCT
cana-3796	177	1	8s	8s	PROPN
cana-3796	177	2	(	(	PUNCT
cana-3796	177	3	2025	2025	NUM
cana-3796	177	4	)	)	PUNCT
cana-3796	177	5	753	753	NUM
cana-3796	178	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	178	2	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	178	3	,	,	PUNCT
cana-3796	178	4	𝑡𝑑	𝑡𝑑	PROPN
cana-3796	178	5	)	)	PUNCT
cana-3796	178	6	=	=	SYM
cana-3796	179	1	𝐿𝑆𝑇𝑀(ℎ(𝑡	𝐿𝑆𝑇𝑀(ℎ(𝑡	NUM
cana-3796	179	2	−	−	NOUN
cana-3796	179	3	1	1	NUM
cana-3796	179	4	,	,	PUNCT
cana-3796	179	5	𝑡𝑑	𝑡𝑑	NOUN
cana-3796	179	6	)	)	PUNCT
cana-3796	179	7	,	,	PUNCT
cana-3796	179	8	𝑥(𝑡	𝑥(𝑡	PROPN
cana-3796	179	9	,	,	PUNCT
cana-3796	179	10	𝑡𝑑	𝑡𝑑	NOUN
cana-3796	179	11	)	)	PUNCT
cana-3796	179	12	)	)	PUNCT
cana-3796	179	13	…	…	PUNCT
cana-3796	179	14	(	(	PUNCT
cana-3796	179	15	10	10	NUM
cana-3796	179	16	)	)	PUNCT
cana-3796	179	17	conversely	conversely	ADV
cana-3796	179	18	,	,	PUNCT
cana-3796	179	19	the	the	DET
cana-3796	179	20	bottom	bottom	NOUN
cana-3796	179	21	-	-	PUNCT
cana-3796	179	22	up	up	ADP
cana-3796	179	23	lstm	lstm	NOUN
cana-3796	179	24	navigates	navigate	VERB
cana-3796	179	25	from	from	ADP
cana-3796	179	26	the	the	DET
cana-3796	179	27	bottom	bottom	NOUN
cana-3796	179	28	of	of	ADP
cana-3796	179	29	the	the	DET
cana-3796	179	30	page	page	NOUN
cana-3796	179	31	to	to	ADP
cana-3796	179	32	the	the	DET
cana-3796	179	33	top	top	NOUN
cana-3796	179	34	,	,	PUNCT
cana-3796	179	35	providing	provide	VERB
cana-3796	179	36	an	an	DET
cana-3796	179	37	inverse	inverse	NOUN
cana-3796	179	38	vertical	vertical	ADJ
cana-3796	179	39	perspective	perspective	NOUN
cana-3796	179	40	,	,	PUNCT
cana-3796	179	41	as	as	SCONJ
cana-3796	179	42	illustrated	illustrate	VERB
cana-3796	179	43	via	via	ADP
cana-3796	179	44	equation	equation	NOUN
cana-3796	179	45	11	11	NUM
cana-3796	179	46	,	,	PUNCT
cana-3796	179	47	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	179	48	,	,	PUNCT
cana-3796	179	49	𝑏𝑢	𝑏𝑢	PROPN
cana-3796	179	50	)	)	PUNCT
cana-3796	179	51	=	=	PUNCT
cana-3796	180	1	𝐿𝑆𝑇𝑀(ℎ(𝑡	𝐿𝑆𝑇𝑀(ℎ(𝑡	PROPN
cana-3796	181	1	+	+	NOUN
cana-3796	181	2	1	1	NUM
cana-3796	181	3	,	,	PUNCT
cana-3796	181	4	𝑏𝑢	𝑏𝑢	NOUN
cana-3796	181	5	)	)	PUNCT
cana-3796	181	6	,	,	PUNCT
cana-3796	181	7	𝑥(𝑡	𝑥(𝑡	PROPN
cana-3796	181	8	,	,	PUNCT
cana-3796	181	9	𝑏𝑢	𝑏𝑢	NOUN
cana-3796	181	10	)	)	PUNCT
cana-3796	181	11	)	)	PUNCT
cana-3796	181	12	…	…	PUNCT
cana-3796	181	13	(	(	PUNCT
cana-3796	181	14	11	11	NUM
cana-3796	181	15	)	)	PUNCT
cana-3796	181	16	the	the	DET
cana-3796	181	17	final	final	ADJ
cana-3796	181	18	feature	feature	NOUN
cana-3796	181	19	vector	vector	NOUN
cana-3796	181	20	is	be	AUX
cana-3796	181	21	created	create	VERB
cana-3796	181	22	by	by	ADP
cana-3796	181	23	concatenating	concatenate	VERB
cana-3796	181	24	outputs	output	NOUN
cana-3796	181	25	from	from	ADP
cana-3796	181	26	all	all	DET
cana-3796	181	27	orientations	orientation	NOUN
cana-3796	181	28	via	via	ADP
cana-3796	181	29	equation	equation	NOUN
cana-3796	181	30	12	12	NUM
cana-3796	181	31	:	:	PUNCT
cana-3796	181	32	𝐻(𝑡	𝐻(𝑡	NUM
cana-3796	181	33	)	)	PUNCT
cana-3796	181	34	=	=	NOUN
cana-3796	182	1	[	[	X
cana-3796	182	2	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	182	3	,	,	PUNCT
cana-3796	182	4	𝑓	𝑓	PROPN
cana-3796	182	5	)	)	PUNCT
cana-3796	182	6	;	;	PUNCT
cana-3796	182	7	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	182	8	,	,	PUNCT
cana-3796	182	9	𝑏	𝑏	NOUN
cana-3796	182	10	)	)	PUNCT
cana-3796	182	11	;	;	PUNCT
cana-3796	182	12	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	182	13	,	,	PUNCT
cana-3796	182	14	𝑡𝑑	𝑡𝑑	PROPN
cana-3796	182	15	)	)	PUNCT
cana-3796	182	16	;	;	PUNCT
cana-3796	182	17	ℎ(𝑡	ℎ(𝑡	PROPN
cana-3796	182	18	,	,	PUNCT
cana-3796	182	19	𝑏𝑢	𝑏𝑢	PROPN
cana-3796	182	20	)	)	PUNCT
cana-3796	182	21	]	]	PUNCT
cana-3796	182	22	…	…	PUNCT
cana-3796	182	23	(	(	PUNCT
cana-3796	182	24	12	12	NUM
cana-3796	182	25	)	)	PUNCT
cana-3796	182	26	e.	e.	PROPN
cana-3796	182	27	bahdanau	bahdanau	VERB
cana-3796	182	28	attention	attention	NOUN
cana-3796	182	29	mechanism	mechanism	NOUN
cana-3796	182	30	to	to	PART
cana-3796	182	31	accurately	accurately	ADV
cana-3796	182	32	recognize	recognize	VERB
cana-3796	182	33	handwritten	handwritten	ADJ
cana-3796	182	34	telugu	telugu	PROPN
cana-3796	182	35	script	script	NOUN
cana-3796	182	36	,	,	PUNCT
cana-3796	182	37	the	the	DET
cana-3796	182	38	proposed	propose	VERB
cana-3796	182	39	model	model	NOUN
cana-3796	182	40	employs	employ	VERB
cana-3796	182	41	the	the	DET
cana-3796	182	42	bahdanau	bahdanau	ADJ
cana-3796	182	43	attention	attention	NOUN
cana-3796	182	44	mechanism	mechanism	NOUN
cana-3796	182	45	,	,	PUNCT
cana-3796	182	46	which	which	PRON
cana-3796	182	47	helps	help	VERB
cana-3796	182	48	refine	refine	VERB
cana-3796	182	49	the	the	DET
cana-3796	182	50	processing	processing	NOUN
cana-3796	182	51	of	of	ADP
cana-3796	182	52	features	feature	NOUN
cana-3796	182	53	extracted	extract	VERB
cana-3796	182	54	from	from	ADP
cana-3796	182	55	the	the	DET
cana-3796	182	56	quadlstm	quadlstm	NOUN
cana-3796	182	57	networks	network	NOUN
cana-3796	182	58	.	.	PUNCT
cana-3796	183	1	this	this	DET
cana-3796	183	2	attention	attention	NOUN
cana-3796	183	3	mechanism	mechanism	NOUN
cana-3796	183	4	is	be	AUX
cana-3796	183	5	crucial	crucial	ADJ
cana-3796	183	6	in	in	ADP
cana-3796	183	7	enhancing	enhance	VERB
cana-3796	183	8	the	the	DET
cana-3796	183	9	model	model	NOUN
cana-3796	183	10	's	's	PART
cana-3796	183	11	ability	ability	NOUN
cana-3796	183	12	to	to	PART
cana-3796	183	13	focus	focus	VERB
cana-3796	183	14	on	on	ADP
cana-3796	183	15	important	important	ADJ
cana-3796	183	16	features	feature	NOUN
cana-3796	183	17	within	within	ADP
cana-3796	183	18	the	the	DET
cana-3796	183	19	text	text	NOUN
cana-3796	183	20	,	,	PUNCT
cana-3796	183	21	significantly	significantly	ADV
cana-3796	183	22	improving	improve	VERB
cana-3796	183	23	the	the	DET
cana-3796	183	24	accuracy	accuracy	NOUN
cana-3796	183	25	of	of	ADP
cana-3796	183	26	the	the	DET
cana-3796	183	27	character	character	NOUN
cana-3796	183	28	recognition	recognition	NOUN
cana-3796	183	29	process	process	NOUN
cana-3796	183	30	.	.	PUNCT
cana-3796	184	1	the	the	DET
cana-3796	184	2	bahdanau	bahdanau	ADJ
cana-3796	184	3	attention	attention	NOUN
cana-3796	184	4	mechanism	mechanism	NOUN
cana-3796	184	5	works	work	VERB
cana-3796	184	6	by	by	ADP
cana-3796	184	7	calculating	calculate	VERB
cana-3796	184	8	a	a	DET
cana-3796	184	9	context	context	NOUN
cana-3796	184	10	vector	vector	NOUN
cana-3796	184	11	for	for	ADP
cana-3796	184	12	each	each	DET
cana-3796	184	13	time	time	NOUN
cana-3796	184	14	step	step	NOUN
cana-3796	184	15	in	in	ADP
cana-3796	184	16	the	the	DET
cana-3796	184	17	lstm	lstm	ADJ
cana-3796	184	18	output	output	NOUN
cana-3796	184	19	,	,	PUNCT
cana-3796	184	20	which	which	PRON
cana-3796	184	21	is	be	AUX
cana-3796	184	22	a	a	DET
cana-3796	184	23	weighted	weighted	ADJ
cana-3796	184	24	sum	sum	NOUN
cana-3796	184	25	of	of	ADP
cana-3796	184	26	the	the	DET
cana-3796	184	27	annotations	annotation	NOUN
cana-3796	184	28	(	(	PUNCT
cana-3796	184	29	features	feature	NOUN
cana-3796	184	30	)	)	PUNCT
cana-3796	184	31	produced	produce	VERB
cana-3796	184	32	by	by	ADP
cana-3796	184	33	the	the	DET
cana-3796	184	34	lstm	lstm	PROPN
cana-3796	184	35	process	process	NOUN
cana-3796	184	36	.	.	PUNCT
cana-3796	185	1	the	the	DET
cana-3796	185	2	mechanism	mechanism	NOUN
cana-3796	185	3	begins	begin	VERB
cana-3796	185	4	by	by	ADP
cana-3796	185	5	computing	compute	VERB
cana-3796	185	6	the	the	DET
cana-3796	185	7	alignment	alignment	NOUN
cana-3796	185	8	scores	score	NOUN
cana-3796	185	9	between	between	ADP
cana-3796	185	10	the	the	DET
cana-3796	185	11	hidden	hidden	ADJ
cana-3796	185	12	state	state	NOUN
cana-3796	185	13	of	of	ADP
cana-3796	185	14	the	the	DET
cana-3796	185	15	decoder	decoder	NOUN
cana-3796	185	16	at	at	ADP
cana-3796	185	17	the	the	DET
cana-3796	185	18	previous	previous	ADJ
cana-3796	185	19	time	time	NOUN
cana-3796	185	20	step	step	NOUN
cana-3796	185	21	and	and	CCONJ
cana-3796	185	22	each	each	PRON
cana-3796	185	23	of	of	ADP
cana-3796	185	24	the	the	DET
cana-3796	185	25	annotations	annotation	NOUN
cana-3796	185	26	from	from	ADP
cana-3796	185	27	the	the	DET
cana-3796	185	28	encoder	encoder	NOUN
cana-3796	185	29	,	,	PUNCT
cana-3796	185	30	as	as	SCONJ
cana-3796	185	31	shown	show	VERB
cana-3796	185	32	in	in	ADP
cana-3796	185	33	equation	equation	NOUN
cana-3796	185	34	13	13	NUM
cana-3796	185	35	.	.	PUNCT
cana-3796	186	1	𝑒(𝑡	𝑒(𝑡	NOUN
cana-3796	186	2	,	,	PUNCT
cana-3796	186	3	𝑗	𝑗	NOUN
cana-3796	186	4	)	)	PUNCT
cana-3796	186	5	=	=	SYM
cana-3796	186	6	𝑉𝑇𝑡𝑎𝑛ℎ(𝑊(ℎ)ℎ(𝑗	𝑉𝑇𝑡𝑎𝑛ℎ(𝑊(ℎ)ℎ(𝑗	NUM
cana-3796	186	7	)	)	PUNCT
cana-3796	187	1	+	+	NUM
cana-3796	187	2	𝑊(𝑠)𝑠(𝑡	𝑊(𝑠)𝑠(𝑡	ADJ
cana-3796	187	3	−	−	ADP
cana-3796	187	4	1	1	NUM
cana-3796	187	5	)	)	PUNCT
cana-3796	187	6	+	+	CCONJ
cana-3796	187	7	𝑏(𝑎𝑡𝑡	𝑏(𝑎𝑡𝑡	ADJ
cana-3796	187	8	)	)	PUNCT
cana-3796	187	9	)	)	PUNCT
cana-3796	188	1	…	…	PUNCT
cana-3796	188	2	(	(	PUNCT
cana-3796	188	3	13	13	NUM
cana-3796	188	4	)	)	PUNCT
cana-3796	188	5	where	where	SCONJ
cana-3796	188	6	,	,	PUNCT
cana-3796	188	7	𝑒(𝑡	𝑒(𝑡	PROPN
cana-3796	188	8	,	,	PUNCT
cana-3796	188	9	𝑗	𝑗	NOUN
cana-3796	188	10	)	)	PUNCT
cana-3796	188	11	is	be	AUX
cana-3796	188	12	the	the	DET
cana-3796	188	13	alignment	alignment	NOUN
cana-3796	188	14	score	score	NOUN
cana-3796	188	15	,	,	PUNCT
cana-3796	188	16	ℎ(𝑗	ℎ(𝑗	PROPN
cana-3796	188	17	)	)	PUNCT
cana-3796	188	18	is	be	AUX
cana-3796	188	19	the	the	DET
cana-3796	188	20	annotation	annotation	NOUN
cana-3796	188	21	from	from	ADP
cana-3796	188	22	the	the	DET
cana-3796	188	23	lstm	lstm	NOUN
cana-3796	188	24	,	,	PUNCT
cana-3796	188	25	𝑠(𝑡	𝑠(𝑡	PROPN
cana-3796	188	26	−	−	NOUN
cana-3796	188	27	1	1	NUM
cana-3796	188	28	)	)	PUNCT
cana-3796	189	1	is	be	AUX
cana-3796	189	2	the	the	DET
cana-3796	189	3	previous	previous	ADJ
cana-3796	189	4	hidden	hidden	ADJ
cana-3796	189	5	state	state	NOUN
cana-3796	189	6	of	of	ADP
cana-3796	189	7	the	the	DET
cana-3796	189	8	decoder	decoder	NOUN
cana-3796	189	9	,	,	PUNCT
cana-3796	189	10	𝑊(ℎ	𝑊(ℎ	NOUN
cana-3796	189	11	)	)	PUNCT
cana-3796	189	12	,	,	PUNCT
cana-3796	189	13	𝑊(𝑠	𝑊(𝑠	NOUN
cana-3796	189	14	)	)	PUNCT
cana-3796	189	15	,	,	PUNCT
cana-3796	189	16	&	&	CCONJ
cana-3796	189	17	𝑏(𝑎𝑡𝑡	𝑏(𝑎𝑡𝑡	PROPN
cana-3796	189	18	)	)	PUNCT
cana-3796	190	1	are	be	AUX
cana-3796	190	2	trainable	trainable	ADJ
cana-3796	190	3	parameters	parameter	NOUN
cana-3796	190	4	,	,	PUNCT
cana-3796	190	5	and	and	CCONJ
cana-3796	190	6	v	v	NOUN
cana-3796	190	7	represents	represent	VERB
cana-3796	190	8	the	the	DET
cana-3796	190	9	weight	weight	NOUN
cana-3796	190	10	vector	vector	NOUN
cana-3796	190	11	sets	set	NOUN
cana-3796	190	12	.	.	PUNCT
cana-3796	191	1	these	these	DET
cana-3796	191	2	alignment	alignment	NOUN
cana-3796	191	3	scores	score	NOUN
cana-3796	191	4	are	be	AUX
cana-3796	191	5	then	then	ADV
cana-3796	191	6	used	use	VERB
cana-3796	191	7	to	to	PART
cana-3796	191	8	compute	compute	VERB
cana-3796	191	9	the	the	DET
cana-3796	191	10	attention	attention	NOUN
cana-3796	191	11	weights	weight	NOUN
cana-3796	191	12	using	use	VERB
cana-3796	191	13	the	the	DET
cana-3796	191	14	softmax	softmax	NOUN
cana-3796	191	15	function	function	NOUN
cana-3796	191	16	via	via	ADP
cana-3796	191	17	equation	equation	NOUN
cana-3796	191	18	14	14	NUM
cana-3796	191	19	,	,	PUNCT
cana-3796	191	20	𝛼𝑡𝑗	𝛼𝑡𝑗	X
cana-3796	191	21	=	=	SYM
cana-3796	191	22	𝑒𝑥𝑝(𝑒𝑡𝑗	𝑒𝑥𝑝(𝑒𝑡𝑗	NOUN
cana-3796	191	23	)	)	PUNCT
cana-3796	191	24	∑	∑	PUNCT
cana-3796	192	1	𝑒𝑥𝑝(𝑒𝑡𝑘)𝑇𝑥	𝑒𝑥𝑝(𝑒𝑡𝑘)𝑇𝑥	PROPN
cana-3796	192	2	𝑘=1	𝑘=1	X
cana-3796	192	3	…	…	PUNCT
cana-3796	192	4	(	(	PUNCT
cana-3796	192	5	14	14	NUM
cana-3796	192	6	)	)	PUNCT
cana-3796	192	7	the	the	DET
cana-3796	192	8	final	final	ADJ
cana-3796	192	9	output	output	NOUN
cana-3796	192	10	of	of	ADP
cana-3796	192	11	the	the	DET
cana-3796	192	12	decoder	decoder	NOUN
cana-3796	192	13	at	at	ADP
cana-3796	192	14	each	each	DET
cana-3796	192	15	time	time	NOUN
cana-3796	192	16	step	step	NOUN
cana-3796	192	17	,	,	PUNCT
cana-3796	192	18	representing	represent	VERB
cana-3796	192	19	the	the	DET
cana-3796	192	20	recognized	recognize	VERB
cana-3796	192	21	character	character	NOUN
cana-3796	192	22	,	,	PUNCT
cana-3796	192	23	is	be	AUX
cana-3796	192	24	computed	compute	VERB
cana-3796	192	25	using	use	VERB
cana-3796	192	26	a	a	DET
cana-3796	192	27	dense	dense	ADJ
cana-3796	192	28	layer	layer	NOUN
cana-3796	192	29	with	with	ADP
cana-3796	192	30	soft	soft	ADJ
cana-3796	192	31	max	max	NOUN
cana-3796	192	32	activation	activation	NOUN
cana-3796	192	33	,	,	PUNCT
cana-3796	192	34	as	as	SCONJ
cana-3796	192	35	expressed	express	VERB
cana-3796	192	36	via	via	ADP
cana-3796	192	37	equation	equation	NOUN
cana-3796	192	38	15	15	NUM
cana-3796	192	39	,	,	PUNCT
cana-3796	192	40	𝑦𝑡	𝑦𝑡	NOUN
cana-3796	192	41	=	=	SYM
cana-3796	192	42	𝑠𝑜𝑓𝑡𝑚𝑎𝑥(𝑊𝑠(𝑠𝑡	𝑠𝑜𝑓𝑡𝑚𝑎𝑥(𝑊𝑠(𝑠𝑡	PROPN
cana-3796	192	43	)	)	PUNCT
cana-3796	193	1	+	+	NUM
cana-3796	193	2	𝑏𝑠	𝑏𝑠	NOUN
cana-3796	193	3	)	)	PUNCT
cana-3796	193	4	…	…	PUNCT
cana-3796	193	5	(	(	PUNCT
cana-3796	193	6	15	15	X
cana-3796	193	7	)	)	PUNCT
cana-3796	193	8	the	the	DET
cana-3796	193	9	attention	attention	NOUN
cana-3796	193	10	mechanism	mechanism	NOUN
cana-3796	193	11	's	's	PART
cana-3796	193	12	focus	focus	NOUN
cana-3796	193	13	on	on	ADP
cana-3796	193	14	critical	critical	ADJ
cana-3796	193	15	features	feature	NOUN
cana-3796	193	16	ensures	ensure	VERB
cana-3796	193	17	that	that	SCONJ
cana-3796	193	18	the	the	DET
cana-3796	193	19	character	character	NOUN
cana-3796	193	20	recognition	recognition	NOUN
cana-3796	193	21	process	process	NOUN
cana-3796	193	22	is	be	AUX
cana-3796	193	23	not	not	PART
cana-3796	193	24	only	only	ADV
cana-3796	193	25	precise	precise	ADJ
cana-3796	193	26	but	but	CCONJ
cana-3796	193	27	also	also	ADV
cana-3796	193	28	adaptable	adaptable	ADJ
cana-3796	193	29	to	to	ADP
cana-3796	193	30	the	the	DET
cana-3796	193	31	variability	variability	NOUN
cana-3796	193	32	inherent	inherent	ADJ
cana-3796	193	33	in	in	ADP
cana-3796	193	34	handwritten	handwritten	ADJ
cana-3796	193	35	texts	text	NOUN
cana-3796	193	36	.	.	PUNCT
cana-3796	194	1	f.	f.	PROPN
cana-3796	194	2	semantic	semantic	ADJ
cana-3796	194	3	analysis	analysis	NOUN
cana-3796	194	4	the	the	DET
cana-3796	194	5	proposed	propose	VERB
cana-3796	194	6	model	model	NOUN
cana-3796	194	7	incorporates	incorporate	VERB
cana-3796	194	8	transformer	transformer	NOUN
cana-3796	194	9	-	-	PUNCT
cana-3796	194	10	based	base	VERB
cana-3796	194	11	natural	natural	ADJ
cana-3796	194	12	language	language	NOUN
cana-3796	194	13	processing	processing	NOUN
cana-3796	194	14	(	(	PUNCT
cana-3796	194	15	nlp	nlp	NOUN
cana-3796	194	16	)	)	PUNCT
cana-3796	194	17	technology	technology	NOUN
cana-3796	194	18	,	,	PUNCT
cana-3796	194	19	specifically	specifically	ADV
cana-3796	194	20	using	use	VERB
cana-3796	194	21	visual	visual	ADJ
cana-3796	194	22	bert	bert	NOUN
cana-3796	194	23	,	,	PUNCT
cana-3796	194	24	to	to	PART
cana-3796	194	25	enhance	enhance	VERB
cana-3796	194	26	the	the	DET
cana-3796	194	27	accuracy	accuracy	NOUN
cana-3796	194	28	of	of	ADP
cana-3796	194	29	text	text	NOUN
cana-3796	194	30	recognition	recognition	NOUN
cana-3796	194	31	.	.	PUNCT
cana-3796	195	1	this	this	DET
cana-3796	195	2	integration	integration	NOUN
cana-3796	195	3	is	be	AUX
cana-3796	195	4	a	a	DET
cana-3796	195	5	significant	significant	ADJ
cana-3796	195	6	advancement	advancement	NOUN
cana-3796	195	7	,	,	PUNCT
cana-3796	195	8	as	as	SCONJ
cana-3796	195	9	it	it	PRON
cana-3796	195	10	allows	allow	VERB
cana-3796	195	11	the	the	DET
cana-3796	195	12	model	model	NOUN
cana-3796	195	13	not	not	PART
cana-3796	195	14	only	only	ADV
cana-3796	195	15	to	to	PART
cana-3796	195	16	identify	identify	VERB
cana-3796	195	17	characters	character	NOUN
cana-3796	195	18	but	but	CCONJ
cana-3796	195	19	also	also	ADV
cana-3796	195	20	to	to	PART
cana-3796	195	21	comprehend	comprehend	VERB
cana-3796	195	22	and	and	CCONJ
cana-3796	195	23	interpret	interpret	VERB
cana-3796	195	24	them	they	PRON
cana-3796	195	25	within	within	ADP
cana-3796	195	26	the	the	DET
cana-3796	195	27	context	context	NOUN
cana-3796	195	28	of	of	ADP
cana-3796	195	29	telugu	telugu	NOUN
cana-3796	195	30	language	language	NOUN
cana-3796	195	31	sets	set	NOUN
cana-3796	195	32	.	.	PUNCT
cana-3796	196	1	visual	visual	ADJ
cana-3796	196	2	bert	bert	PROPN
cana-3796	196	3	,	,	PUNCT
cana-3796	196	4	an	an	DET
cana-3796	196	5	extension	extension	NOUN
cana-3796	196	6	of	of	ADP
cana-3796	196	7	bert	bert	PROPN
cana-3796	196	8	,	,	PUNCT
cana-3796	196	9	is	be	AUX
cana-3796	196	10	tailored	tailor	VERB
cana-3796	196	11	to	to	PART
cana-3796	196	12	handle	handle	VERB
cana-3796	196	13	both	both	CCONJ
cana-3796	196	14	visual	visual	ADJ
cana-3796	196	15	and	and	CCONJ
cana-3796	196	16	textual	textual	ADJ
cana-3796	196	17	data	datum	NOUN
cana-3796	196	18	,	,	PUNCT
cana-3796	196	19	making	make	VERB
cana-3796	196	20	it	it	PRON
cana-3796	196	21	ideal	ideal	ADJ
cana-3796	196	22	for	for	ADP
cana-3796	196	23	the	the	DET
cana-3796	196	24	proposed	propose	VERB
cana-3796	196	25	model	model	NOUN
cana-3796	196	26	.	.	PUNCT
cana-3796	197	1	it	it	PRON
cana-3796	197	2	utilizes	utilize	VERB
cana-3796	197	3	the	the	DET
cana-3796	197	4	transformer	transformer	NOUN
cana-3796	197	5	architecture	architecture	NOUN
cana-3796	197	6	,	,	PUNCT
cana-3796	197	7	which	which	PRON
cana-3796	197	8	is	be	AUX
cana-3796	197	9	built	build	VERB
cana-3796	197	10	on	on	ADP
cana-3796	197	11	self	self	NOUN
cana-3796	197	12	-	-	PUNCT
cana-3796	197	13	attention	attention	NOUN
cana-3796	197	14	mechanisms	mechanism	NOUN
cana-3796	197	15	.	.	PUNCT
cana-3796	198	1	initially	initially	ADV
cana-3796	198	2	,	,	PUNCT
cana-3796	198	3	the	the	DET
cana-3796	198	4	recognized	recognize	VERB
cana-3796	198	5	characters	character	NOUN
cana-3796	198	6	are	be	AUX
cana-3796	198	7	embedded	embed	VERB
cana-3796	198	8	into	into	ADP
cana-3796	198	9	a	a	DET
cana-3796	198	10	high	high	ADJ
cana-3796	198	11	-	-	PUNCT
cana-3796	198	12	dimensional	dimensional	ADJ
cana-3796	198	13	space	space	NOUN
cana-3796	198	14	using	use	VERB
cana-3796	198	15	the	the	DET
cana-3796	198	16	equation	equation	NOUN
cana-3796	198	17	16	16	NUM
cana-3796	198	18	:	:	PUNCT
cana-3796	198	19	𝐸	𝐸	PROPN
cana-3796	198	20	=	=	SYM
cana-3796	199	1	[	[	X
cana-3796	199	2	𝐸1	𝐸1	NOUN
cana-3796	199	3	,	,	PUNCT
cana-3796	199	4	𝐸2	𝐸2	ADJ
cana-3796	199	5	,	,	PUNCT
cana-3796	199	6	.	.	PUNCT
cana-3796	199	7	.	.	PUNCT
cana-3796	199	8	.	.	PUNCT
cana-3796	200	1	,	,	PUNCT
cana-3796	200	2	𝐸𝑁]𝑇	𝐸𝑁]𝑇	PROPN
cana-3796	200	3	…	…	PUNCT
cana-3796	200	4	(	(	PUNCT
cana-3796	200	5	16	16	NUM
cana-3796	200	6	)	)	PUNCT
cana-3796	200	7	where	where	SCONJ
cana-3796	200	8	𝐸𝑖	𝐸𝑖	PROPN
cana-3796	200	9	=	=	SYM
cana-3796	200	10	𝑊	𝑊	PROPN
cana-3796	200	11	∗	∗	NOUN
cana-3796	200	12	𝑋𝑖	𝑋𝑖	PROPN
cana-3796	200	13	and	and	CCONJ
cana-3796	200	14	w	w	NOUN
cana-3796	200	15	,	,	PUNCT
cana-3796	200	16	x	x	PRON
cana-3796	200	17	represents	represent	VERB
cana-3796	200	18	the	the	DET
cana-3796	200	19	weights	weight	NOUN
cana-3796	200	20	and	and	CCONJ
cana-3796	200	21	the	the	DET
cana-3796	200	22	ocr	ocr	ADJ
cana-3796	200	23	output	output	NOUN
cana-3796	200	24	sets	set	VERB
cana-3796	200	25	communications	communication	NOUN
cana-3796	200	26	on	on	ADP
cana-3796	200	27	applied	apply	VERB
cana-3796	200	28	nonlinear	nonlinear	ADJ
cana-3796	200	29	analysis	analysis	NOUN
cana-3796	200	30	issn	issn	NOUN
cana-3796	200	31	:	:	PUNCT
cana-3796	200	32	1074	1074	NUM
cana-3796	200	33	-	-	PUNCT
cana-3796	200	34	133x	133x	NUM
cana-3796	200	35	vol	vol	NOUN
cana-3796	200	36	32	32	NUM
cana-3796	200	37	no	no	NOUN
cana-3796	200	38	.	.	PUNCT
cana-3796	201	1	8s	8s	PROPN
cana-3796	201	2	(	(	PUNCT
cana-3796	201	3	2025	2025	NUM
cana-3796	201	4	)	)	PUNCT
cana-3796	201	5	754	754	NUM
cana-3796	201	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	201	7	the	the	DET
cana-3796	201	8	model	model	NOUN
cana-3796	201	9	processes	process	VERB
cana-3796	201	10	the	the	DET
cana-3796	201	11	embedded	embed	VERB
cana-3796	201	12	features	feature	NOUN
cana-3796	201	13	through	through	ADP
cana-3796	201	14	multiple	multiple	ADJ
cana-3796	201	15	layers	layer	NOUN
cana-3796	201	16	of	of	ADP
cana-3796	201	17	transformer	transformer	NOUN
cana-3796	201	18	blocks	block	NOUN
cana-3796	201	19	.	.	PUNCT
cana-3796	202	1	each	each	DET
cana-3796	202	2	block	block	NOUN
cana-3796	202	3	includes	include	VERB
cana-3796	202	4	multi	multi	ADJ
cana-3796	202	5	-	-	ADJ
cana-3796	202	6	head	head	ADJ
cana-3796	202	7	self	self	NOUN
cana-3796	202	8	-	-	PUNCT
cana-3796	202	9	attention	attention	NOUN
cana-3796	202	10	and	and	CCONJ
cana-3796	202	11	feed	feed	NOUN
cana-3796	202	12	-	-	PUNCT
cana-3796	202	13	forward	forward	NOUN
cana-3796	202	14	networks	network	NOUN
cana-3796	202	15	.	.	PUNCT
cana-3796	203	1	the	the	DET
cana-3796	203	2	self	self	NOUN
cana-3796	203	3	-	-	PUNCT
cana-3796	203	4	attention	attention	NOUN
cana-3796	203	5	mechanism	mechanism	NOUN
cana-3796	203	6	in	in	ADP
cana-3796	203	7	each	each	DET
cana-3796	203	8	block	block	NOUN
cana-3796	203	9	is	be	AUX
cana-3796	203	10	computed	compute	VERB
cana-3796	203	11	via	via	ADP
cana-3796	203	12	equation	equation	NOUN
cana-3796	203	13	17	17	NUM
cana-3796	203	14	:	:	PUNCT
cana-3796	203	15	𝐴𝑡𝑡𝑒𝑛𝑡𝑖𝑜𝑛(𝑄	𝐴𝑡𝑡𝑒𝑛𝑡𝑖𝑜𝑛(𝑄	PROPN
cana-3796	203	16	,	,	PUNCT
cana-3796	203	17	𝐾	𝐾	PROPN
cana-3796	203	18	,	,	PUNCT
cana-3796	203	19	𝑉	𝑉	PROPN
cana-3796	203	20	)	)	PUNCT
cana-3796	204	1	=	=	VERB
cana-3796	204	2	𝑠𝑜𝑓𝑡𝑚𝑎𝑥	𝑠𝑜𝑓𝑡𝑚𝑎𝑥	NOUN
cana-3796	204	3	(	(	PUNCT
cana-3796	204	4	𝑄𝐾𝑇	𝑄𝐾𝑇	NOUN
cana-3796	204	5	√𝑑𝑘	√𝑑𝑘	PROPN
cana-3796	204	6	)	)	PUNCT
cana-3796	204	7	𝑉	𝑉	PROPN
cana-3796	204	8	…	…	PUNCT
cana-3796	204	9	(	(	PUNCT
cana-3796	204	10	17	17	NUM
cana-3796	204	11	)	)	PUNCT
cana-3796	204	12	where	where	SCONJ
cana-3796	204	13	q	q	X
cana-3796	204	14	,	,	PUNCT
cana-3796	204	15	k	k	NOUN
cana-3796	204	16	,	,	PUNCT
cana-3796	204	17	v	v	NOUN
cana-3796	204	18	are	be	AUX
cana-3796	204	19	the	the	DET
cana-3796	204	20	query	query	NOUN
cana-3796	204	21	,	,	PUNCT
cana-3796	204	22	key	key	ADJ
cana-3796	204	23	,	,	PUNCT
cana-3796	204	24	and	and	CCONJ
cana-3796	204	25	value	value	NOUN
cana-3796	204	26	matrices	matrix	NOUN
cana-3796	204	27	derived	derive	VERB
cana-3796	204	28	from	from	ADP
cana-3796	204	29	e	e	PROPN
cana-3796	204	30	,	,	PUNCT
cana-3796	204	31	and	and	CCONJ
cana-3796	204	32	dk	dk	PROPN
cana-3796	204	33	is	be	AUX
cana-3796	204	34	the	the	DET
cana-3796	204	35	dimensionality	dimensionality	NOUN
cana-3796	204	36	of	of	ADP
cana-3796	204	37	the	the	DET
cana-3796	204	38	keys	key	NOUN
cana-3796	204	39	.	.	PUNCT
cana-3796	205	1	after	after	ADP
cana-3796	205	2	processing	process	VERB
cana-3796	205	3	through	through	ADP
cana-3796	205	4	these	these	DET
cana-3796	205	5	layers	layer	NOUN
cana-3796	205	6	,	,	PUNCT
cana-3796	205	7	the	the	DET
cana-3796	205	8	output	output	NOUN
cana-3796	205	9	is	be	AUX
cana-3796	205	10	passed	pass	VERB
cana-3796	205	11	through	through	ADP
cana-3796	205	12	a	a	DET
cana-3796	205	13	feed	feed	NOUN
cana-3796	205	14	-	-	PUNCT
cana-3796	205	15	forward	forward	ADV
cana-3796	205	16	neural	neural	ADJ
cana-3796	205	17	network	network	NOUN
cana-3796	205	18	,	,	PUNCT
cana-3796	205	19	and	and	CCONJ
cana-3796	205	20	the	the	DET
cana-3796	205	21	result	result	NOUN
cana-3796	205	22	is	be	AUX
cana-3796	205	23	normalized	normalize	VERB
cana-3796	205	24	before	before	ADP
cana-3796	205	25	being	be	AUX
cana-3796	205	26	sent	send	VERB
cana-3796	205	27	to	to	ADP
cana-3796	205	28	the	the	DET
cana-3796	205	29	next	next	ADJ
cana-3796	205	30	layers	layer	NOUN
cana-3796	205	31	.	.	PUNCT
cana-3796	206	1	this	this	DET
cana-3796	206	2	operation	operation	NOUN
cana-3796	206	3	is	be	AUX
cana-3796	206	4	repeated	repeat	VERB
cana-3796	206	5	for	for	ADP
cana-3796	206	6	each	each	DET
cana-3796	206	7	transformer	transformer	ADJ
cana-3796	206	8	block	block	NOUN
cana-3796	206	9	in	in	ADP
cana-3796	206	10	the	the	DET
cana-3796	206	11	visual	visual	ADJ
cana-3796	206	12	bert	bert	PROPN
cana-3796	206	13	model	model	PROPN
cana-3796	206	14	.	.	PUNCT
cana-3796	207	1	the	the	DET
cana-3796	207	2	final	final	ADJ
cana-3796	207	3	output	output	NOUN
cana-3796	207	4	,	,	PUNCT
cana-3796	207	5	which	which	PRON
cana-3796	207	6	represents	represent	VERB
cana-3796	207	7	the	the	DET
cana-3796	207	8	contextualized	contextualized	ADJ
cana-3796	207	9	text	text	NOUN
cana-3796	207	10	,	,	PUNCT
cana-3796	207	11	is	be	AUX
cana-3796	207	12	then	then	ADV
cana-3796	207	13	classified	classified	ADJ
cana-3796	207	14	using	use	VERB
cana-3796	207	15	a	a	DET
cana-3796	207	16	dense	dense	ADJ
cana-3796	207	17	layer	layer	NOUN
cana-3796	207	18	with	with	ADP
cana-3796	207	19	softmax	softmax	ADJ
cana-3796	207	20	activation	activation	NOUN
cana-3796	207	21	via	via	ADP
cana-3796	207	22	equation	equation	NOUN
cana-3796	207	23	18	18	NUM
cana-3796	207	24	𝐶	𝐶	PROPN
cana-3796	207	25	=	=	SYM
cana-3796	207	26	𝑠𝑜𝑓𝑡𝑚𝑎𝑥(𝑊𝑣𝑉	𝑠𝑜𝑓𝑡𝑚𝑎𝑥(𝑊𝑣𝑉	PROPN
cana-3796	207	27	+	+	CCONJ
cana-3796	207	28	𝑏𝑣	𝑏𝑣	NUM
cana-3796	207	29	)	)	PUNCT
cana-3796	207	30	…	…	PUNCT
cana-3796	207	31	(	(	PUNCT
cana-3796	207	32	18	18	NUM
cana-3796	207	33	)	)	PUNCT
cana-3796	207	34	where	where	SCONJ
cana-3796	207	35	c	c	NOUN
cana-3796	207	36	is	be	AUX
cana-3796	207	37	the	the	DET
cana-3796	207	38	classification	classification	NOUN
cana-3796	207	39	output	output	NOUN
cana-3796	207	40	,	,	PUNCT
cana-3796	207	41	wv	wv	PROPN
cana-3796	207	42	and	and	CCONJ
cana-3796	207	43	bv	bv	PROPN
cana-3796	207	44	are	be	AUX
cana-3796	207	45	the	the	DET
cana-3796	207	46	weights	weight	NOUN
cana-3796	207	47	and	and	CCONJ
cana-3796	207	48	biases	bias	NOUN
cana-3796	207	49	of	of	ADP
cana-3796	207	50	the	the	DET
cana-3796	207	51	dense	dense	ADJ
cana-3796	207	52	layer	layer	NOUN
cana-3796	207	53	,	,	PUNCT
cana-3796	207	54	and	and	CCONJ
cana-3796	207	55	v	v	NOUN
cana-3796	207	56	is	be	AUX
cana-3796	207	57	the	the	DET
cana-3796	207	58	output	output	NOUN
cana-3796	207	59	from	from	ADP
cana-3796	207	60	the	the	DET
cana-3796	207	61	transformer	transformer	NOUN
cana-3796	207	62	layers	layer	NOUN
cana-3796	207	63	.	.	PUNCT
cana-3796	208	1	by	by	ADP
cana-3796	208	2	integrating	integrate	VERB
cana-3796	208	3	visual	visual	ADJ
cana-3796	208	4	bert	bert	PROPN
cana-3796	208	5	,	,	PUNCT
cana-3796	208	6	the	the	DET
cana-3796	208	7	model	model	NOUN
cana-3796	208	8	enhances	enhance	VERB
cana-3796	208	9	its	its	PRON
cana-3796	208	10	ability	ability	NOUN
cana-3796	208	11	to	to	PART
cana-3796	208	12	not	not	PART
cana-3796	208	13	only	only	ADV
cana-3796	208	14	recognize	recognize	VERB
cana-3796	208	15	but	but	CCONJ
cana-3796	208	16	also	also	ADV
cana-3796	208	17	understand	understand	VERB
cana-3796	208	18	and	and	CCONJ
cana-3796	208	19	validate	validate	VERB
cana-3796	208	20	handwritten	handwritten	ADJ
cana-3796	208	21	telugu	telugu	PROPN
cana-3796	208	22	text	text	NOUN
cana-3796	208	23	,	,	PUNCT
cana-3796	208	24	leveraging	leverage	VERB
cana-3796	208	25	the	the	DET
cana-3796	208	26	power	power	NOUN
cana-3796	208	27	of	of	ADP
cana-3796	208	28	transformer	transformer	NOUN
cana-3796	208	29	-	-	PUNCT
cana-3796	208	30	based	base	VERB
cana-3796	208	31	nlp	nlp	NOUN
cana-3796	208	32	and	and	CCONJ
cana-3796	208	33	visual	visual	ADJ
cana-3796	208	34	-	-	PUNCT
cana-3796	208	35	textual	textual	ADJ
cana-3796	208	36	processing	processing	NOUN
cana-3796	208	37	to	to	PART
cana-3796	208	38	set	set	VERB
cana-3796	208	39	a	a	DET
cana-3796	208	40	new	new	ADJ
cana-3796	208	41	standard	standard	NOUN
cana-3796	208	42	in	in	ADP
cana-3796	208	43	ocr	ocr	ADJ
cana-3796	208	44	applications	application	NOUN
cana-3796	208	45	.	.	PUNCT
cana-3796	209	1	iv	iv	X
cana-3796	209	2	.	.	PUNCT
cana-3796	210	1	experimental	experimental	ADJ
cana-3796	210	2	results	result	VERB
cana-3796	210	3	the	the	DET
cana-3796	210	4	experiment	experiment	NOUN
cana-3796	210	5	utilized	utilize	VERB
cana-3796	210	6	a	a	DET
cana-3796	210	7	diverse	diverse	ADJ
cana-3796	210	8	and	and	CCONJ
cana-3796	210	9	extensive	extensive	ADJ
cana-3796	210	10	dataset	dataset	NOUN
cana-3796	210	11	comprising	comprising	NOUN
cana-3796	210	12	handwritten	handwritten	ADJ
cana-3796	210	13	telugu	telugu	PROPN
cana-3796	210	14	answer	answer	NOUN
cana-3796	210	15	books	book	NOUN
cana-3796	210	16	.	.	PUNCT
cana-3796	211	1	this	this	DET
cana-3796	211	2	dataset	dataset	NOUN
cana-3796	211	3	was	be	AUX
cana-3796	211	4	carefully	carefully	ADV
cana-3796	211	5	curated	curate	VERB
cana-3796	211	6	to	to	PART
cana-3796	211	7	include	include	VERB
cana-3796	211	8	a	a	DET
cana-3796	211	9	wide	wide	ADJ
cana-3796	211	10	variety	variety	NOUN
cana-3796	211	11	of	of	ADP
cana-3796	211	12	handwriting	handwriting	NOUN
cana-3796	211	13	styles	style	NOUN
cana-3796	211	14	,	,	PUNCT
cana-3796	211	15	representing	represent	VERB
cana-3796	211	16	different	different	ADJ
cana-3796	211	17	demographic	demographic	ADJ
cana-3796	211	18	backgrounds	background	NOUN
cana-3796	211	19	,	,	PUNCT
cana-3796	211	20	including	include	VERB
cana-3796	211	21	various	various	ADJ
cana-3796	211	22	age	age	NOUN
cana-3796	211	23	groups	group	NOUN
cana-3796	211	24	and	and	CCONJ
cana-3796	211	25	educational	educational	ADJ
cana-3796	211	26	levels	level	NOUN
cana-3796	211	27	.	.	PUNCT
cana-3796	212	1	the	the	DET
cana-3796	212	2	dataset	dataset	NOUN
cana-3796	212	3	contains	contain	VERB
cana-3796	212	4	a	a	DET
cana-3796	212	5	total	total	NOUN
cana-3796	212	6	of	of	ADP
cana-3796	212	7	15,000	15,000	NUM
cana-3796	212	8	samples	sample	NOUN
cana-3796	212	9	(	(	PUNCT
cana-3796	212	10	nts	nts	INTJ
cana-3796	212	11	number	number	NOUN
cana-3796	212	12	of	of	ADP
cana-3796	212	13	test	test	NOUN
cana-3796	212	14	sentences	sentence	NOUN
cana-3796	212	15	)	)	PUNCT
cana-3796	212	16	,	,	PUNCT
cana-3796	212	17	with	with	ADP
cana-3796	212	18	each	each	DET
cana-3796	212	19	sample	sample	NOUN
cana-3796	212	20	containing	contain	VERB
cana-3796	212	21	both	both	PRON
cana-3796	212	22	character	character	NOUN
cana-3796	212	23	-	-	PUNCT
cana-3796	212	24	level	level	NOUN
cana-3796	212	25	and	and	CCONJ
cana-3796	212	26	sentencelevel	sentencelevel	VERB
cana-3796	212	27	handwritten	handwritten	ADJ
cana-3796	212	28	telugu	telugu	NOUN
cana-3796	212	29	text	text	NOUN
cana-3796	212	30	.	.	PUNCT
cana-3796	213	1	the	the	DET
cana-3796	213	2	texts	text	NOUN
cana-3796	213	3	range	range	VERB
cana-3796	213	4	from	from	ADP
cana-3796	213	5	simple	simple	ADJ
cana-3796	213	6	to	to	ADP
cana-3796	213	7	complex	complex	ADJ
cana-3796	213	8	sentence	sentence	NOUN
cana-3796	213	9	structures	structure	NOUN
cana-3796	213	10	,	,	PUNCT
cana-3796	213	11	ensuring	ensure	VERB
cana-3796	213	12	a	a	DET
cana-3796	213	13	broad	broad	ADJ
cana-3796	213	14	representation	representation	NOUN
cana-3796	213	15	of	of	ADP
cana-3796	213	16	the	the	DET
cana-3796	213	17	syntactical	syntactical	ADJ
cana-3796	213	18	and	and	CCONJ
cana-3796	213	19	asemantic	asemantic	ADJ
cana-3796	213	20	characteristics	characteristic	NOUN
cana-3796	213	21	of	of	ADP
cana-3796	213	22	the	the	DET
cana-3796	213	23	telugu	telugu	PROPN
cana-3796	213	24	language	language	NOUN
cana-3796	213	25	.	.	PUNCT
cana-3796	214	1	building	build	VERB
cana-3796	214	2	on	on	ADP
cana-3796	214	3	the	the	DET
cana-3796	214	4	initial	initial	ADJ
cana-3796	214	5	phase	phase	NOUN
cana-3796	214	6	of	of	ADP
cana-3796	214	7	image	image	NOUN
cana-3796	214	8	preprocessing	preprocessing	NOUN
cana-3796	214	9	,	,	PUNCT
cana-3796	214	10	which	which	PRON
cana-3796	214	11	employs	employ	VERB
cana-3796	214	12	adaptive	adaptive	ADJ
cana-3796	214	13	thresholding	thresholding	NOUN
cana-3796	214	14	and	and	CCONJ
cana-3796	214	15	gaussian	gaussian	NOUN
cana-3796	214	16	blurring	blurring	NOUN
cana-3796	214	17	to	to	PART
cana-3796	214	18	enhance	enhance	VERB
cana-3796	214	19	the	the	DET
cana-3796	214	20	contrast	contrast	NOUN
cana-3796	214	21	and	and	CCONJ
cana-3796	214	22	clarity	clarity	NOUN
cana-3796	214	23	of	of	ADP
cana-3796	214	24	handwritten	handwritten	ADJ
cana-3796	214	25	telugu	telugu	NOUN
cana-3796	214	26	text	text	NOUN
cana-3796	214	27	images	image	NOUN
cana-3796	214	28	,	,	PUNCT
cana-3796	214	29	this	this	DET
cana-3796	214	30	study	study	NOUN
cana-3796	214	31	progresses	progress	VERB
cana-3796	214	32	to	to	ADP
cana-3796	214	33	a	a	DET
cana-3796	214	34	novel	novel	ADJ
cana-3796	214	35	segmentation	segmentation	NOUN
cana-3796	214	36	and	and	CCONJ
cana-3796	214	37	recognition	recognition	NOUN
cana-3796	214	38	methodology	methodology	NOUN
cana-3796	214	39	.	.	PUNCT
cana-3796	215	1	after	after	ADP
cana-3796	215	2	preprocessing	preprocessing	NOUN
cana-3796	215	3	,	,	PUNCT
cana-3796	215	4	contours	contour	NOUN
cana-3796	215	5	are	be	AUX
cana-3796	215	6	detected	detect	VERB
cana-3796	215	7	to	to	PART
cana-3796	215	8	isolate	isolate	VERB
cana-3796	215	9	potential	potential	ADJ
cana-3796	215	10	text	text	NOUN
cana-3796	215	11	regions	region	NOUN
cana-3796	215	12	,	,	PUNCT
cana-3796	215	13	and	and	CCONJ
cana-3796	215	14	noise	noise	NOUN
cana-3796	215	15	is	be	AUX
cana-3796	215	16	filtered	filter	VERB
cana-3796	215	17	out	out	ADP
cana-3796	215	18	using	use	VERB
cana-3796	215	19	size	size	NOUN
cana-3796	215	20	-	-	PUNCT
cana-3796	215	21	based	base	VERB
cana-3796	215	22	thresholds	threshold	NOUN
cana-3796	215	23	,	,	PUNCT
cana-3796	215	24	as	as	SCONJ
cana-3796	215	25	shown	show	VERB
cana-3796	215	26	in	in	ADP
cana-3796	215	27	figure	figure	NOUN
cana-3796	215	28	5	5	NUM
cana-3796	215	29	.	.	PUNCT
cana-3796	216	1	the	the	DET
cana-3796	216	2	segmented	segment	VERB
cana-3796	216	3	regions	region	NOUN
cana-3796	216	4	are	be	AUX
cana-3796	216	5	then	then	ADV
cana-3796	216	6	annotated	annotate	VERB
cana-3796	216	7	with	with	ADP
cana-3796	216	8	bounding	bounding	NOUN
cana-3796	216	9	boxes	box	NOUN
cana-3796	216	10	to	to	PART
cana-3796	216	11	indicate	indicate	VERB
cana-3796	216	12	distinct	distinct	ADJ
cana-3796	216	13	text	text	NOUN
cana-3796	216	14	areas	area	NOUN
cana-3796	216	15	,	,	PUNCT
cana-3796	216	16	facilitating	facilitate	VERB
cana-3796	216	17	accurate	accurate	ADJ
cana-3796	216	18	text	text	NOUN
cana-3796	216	19	recognition	recognition	NOUN
cana-3796	216	20	.	.	PUNCT
cana-3796	217	1	this	this	DET
cana-3796	217	2	integrated	integrate	VERB
cana-3796	217	3	approach	approach	NOUN
cana-3796	217	4	ensures	ensure	VERB
cana-3796	217	5	that	that	SCONJ
cana-3796	217	6	the	the	DET
cana-3796	217	7	preprocessing	preprocessing	NOUN
cana-3796	217	8	phase	phase	NOUN
cana-3796	217	9	directly	directly	ADV
cana-3796	217	10	supports	support	VERB
cana-3796	217	11	effective	effective	ADJ
cana-3796	217	12	segmentation	segmentation	NOUN
cana-3796	217	13	and	and	CCONJ
cana-3796	217	14	recognition	recognition	NOUN
cana-3796	217	15	,	,	PUNCT
cana-3796	217	16	significantly	significantly	ADV
cana-3796	217	17	enhancing	enhance	VERB
cana-3796	217	18	the	the	DET
cana-3796	217	19	overall	overall	ADJ
cana-3796	217	20	performance	performance	NOUN
cana-3796	217	21	of	of	ADP
cana-3796	217	22	handwriting	handwriting	NOUN
cana-3796	217	23	recognition	recognition	NOUN
cana-3796	217	24	systems	system	NOUN
cana-3796	217	25	.	.	PUNCT
cana-3796	218	1	communications	communication	NOUN
cana-3796	218	2	on	on	ADP
cana-3796	218	3	applied	apply	VERB
cana-3796	218	4	nonlinear	nonlinear	ADJ
cana-3796	218	5	analysis	analysis	NOUN
cana-3796	218	6	issn	issn	NOUN
cana-3796	218	7	:	:	PUNCT
cana-3796	218	8	1074	1074	NUM
cana-3796	218	9	-	-	PUNCT
cana-3796	218	10	133x	133x	NUM
cana-3796	218	11	vol	vol	NOUN
cana-3796	218	12	32	32	NUM
cana-3796	218	13	no	no	NOUN
cana-3796	218	14	.	.	PUNCT
cana-3796	219	1	8s	8s	PROPN
cana-3796	219	2	(	(	PUNCT
cana-3796	219	3	2025	2025	NUM
cana-3796	219	4	)	)	PUNCT
cana-3796	219	5	755	755	NUM
cana-3796	219	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	219	7	figure	figure	NOUN
cana-3796	219	8	5	5	NUM
cana-3796	219	9	.	.	PUNCT
cana-3796	219	10	sample	sample	PROPN
cana-3796	219	11	visual	visual	ADJ
cana-3796	219	12	representation	representation	NOUN
cana-3796	219	13	of	of	ADP
cana-3796	219	14	segmentation	segmentation	NOUN
cana-3796	219	15	and	and	CCONJ
cana-3796	219	16	ocr	ocr	ADJ
cana-3796	219	17	recognition	recognition	NOUN
cana-3796	219	18	results	result	VERB
cana-3796	219	19	input	input	NOUN
cana-3796	219	20	parameters	parameter	NOUN
cana-3796	219	21	and	and	CCONJ
cana-3796	219	22	values	value	NOUN
cana-3796	219	23	:	:	PUNCT
cana-3796	219	24	the	the	DET
cana-3796	219	25	feature	feature	NOUN
cana-3796	219	26	extraction	extraction	NOUN
cana-3796	219	27	process	process	NOUN
cana-3796	219	28	yields	yield	VERB
cana-3796	219	29	the	the	DET
cana-3796	219	30	following	follow	VERB
cana-3796	219	31	results	result	NOUN
cana-3796	219	32	:	:	PUNCT
cana-3796	219	33	a.	a.	NOUN
cana-3796	219	34	resnet	resnet	PROPN
cana-3796	219	35	feature	feature	NOUN
cana-3796	219	36	vector	vector	NOUN
cana-3796	219	37	:	:	PUNCT
cana-3796	219	38	shape	shape	NOUN
cana-3796	219	39	(	(	PUNCT
cana-3796	219	40	2048	2048	NUM
cana-3796	219	41	,	,	PUNCT
cana-3796	219	42	)	)	PUNCT
cana-3796	219	43	b.	b.	PROPN
cana-3796	220	1	inception	inception	PROPN
cana-3796	220	2	feature	feature	NOUN
cana-3796	220	3	vector	vector	NOUN
cana-3796	220	4	:	:	PUNCT
cana-3796	220	5	shape	shape	NOUN
cana-3796	220	6	(	(	PUNCT
cana-3796	220	7	2048	2048	NUM
cana-3796	220	8	,	,	PUNCT
cana-3796	220	9	)	)	PUNCT
cana-3796	220	10	c.	c.	NOUN
cana-3796	220	11	fused	fuse	VERB
cana-3796	220	12	feature	feature	NOUN
cana-3796	220	13	vector	vector	NOUN
cana-3796	220	14	:	:	PUNCT
cana-3796	220	15	shape	shape	NOUN
cana-3796	220	16	(	(	PUNCT
cana-3796	220	17	4096	4096	NUM
cana-3796	220	18	,	,	PUNCT
cana-3796	220	19	)	)	PUNCT
cana-3796	220	20	model	model	NOUN
cana-3796	220	21	architecture	architecture	NOUN
cana-3796	220	22	:	:	PUNCT
cana-3796	220	23	feature	feature	NOUN
cana-3796	220	24	extractors	extractor	NOUN
cana-3796	220	25	:	:	PUNCT
cana-3796	220	26	resnet101	resnet101	PROPN
cana-3796	220	27	and	and	CCONJ
cana-3796	220	28	inceptionv3	inceptionv3	NOUN
cana-3796	220	29	,	,	PUNCT
cana-3796	220	30	each	each	PRON
cana-3796	220	31	producing	produce	VERB
cana-3796	220	32	2048	2048	NUM
cana-3796	220	33	-	-	PUNCT
cana-3796	220	34	dimensional	dimensional	ADJ
cana-3796	220	35	outputs	output	NOUN
cana-3796	220	36	.	.	PUNCT
cana-3796	221	1	concatenation	concatenation	NOUN
cana-3796	221	2	:	:	PUNCT
cana-3796	221	3	features	feature	NOUN
cana-3796	221	4	from	from	ADP
cana-3796	221	5	both	both	DET
cana-3796	221	6	networks	network	NOUN
cana-3796	221	7	are	be	AUX
cana-3796	221	8	concatenated	concatenate	VERB
cana-3796	221	9	into	into	ADP
cana-3796	221	10	a	a	DET
cana-3796	221	11	4096	4096	NUM
cana-3796	221	12	-	-	PUNCT
cana-3796	221	13	dimensional	dimensional	ADJ
cana-3796	221	14	vector	vector	NOUN
cana-3796	221	15	.	.	PUNCT
cana-3796	222	1	sequence	sequence	NOUN
cana-3796	222	2	modelling	modelling	NOUN
cana-3796	222	3	:	:	PUNCT
cana-3796	222	4	quad	quad	ADJ
cana-3796	222	5	lstm	lstm	ADJ
cana-3796	222	6	layers	layer	NOUN
cana-3796	222	7	,	,	PUNCT
cana-3796	222	8	each	each	PRON
cana-3796	222	9	with	with	ADP
cana-3796	222	10	256	256	NUM
cana-3796	222	11	units	unit	NOUN
cana-3796	222	12	.	.	PUNCT
cana-3796	223	1	final	final	ADJ
cana-3796	223	2	layer	layer	NOUN
cana-3796	223	3	:	:	PUNCT
cana-3796	223	4	dense	dense	ADJ
cana-3796	223	5	layer	layer	NOUN
cana-3796	223	6	with	with	ADP
cana-3796	223	7	128	128	NUM
cana-3796	223	8	units	unit	NOUN
cana-3796	223	9	for	for	ADP
cana-3796	223	10	output	output	NOUN
cana-3796	223	11	.	.	PUNCT
cana-3796	224	1	model	model	NOUN
cana-3796	224	2	parameters	parameter	NOUN
cana-3796	224	3	:	:	PUNCT
cana-3796	224	4	a.	a.	NOUN
cana-3796	224	5	total	total	NOUN
cana-3796	224	6	parameters	parameter	NOUN
cana-3796	224	7	:	:	PUNCT
cana-3796	224	8	69,996,128	69,996,128	NUM
cana-3796	224	9	(	(	PUNCT
cana-3796	224	10	267.01	267.01	NUM
cana-3796	224	11	mb	mb	NOUN
cana-3796	224	12	)	)	PUNCT
cana-3796	224	13	.	.	PUNCT
cana-3796	225	1	b.	b.	PROPN
cana-3796	225	2	trainable	trainable	ADJ
cana-3796	225	3	parameters	parameter	NOUN
cana-3796	225	4	:	:	PUNCT
cana-3796	225	5	69,856,352	69,856,352	NUM
cana-3796	225	6	(	(	PUNCT
cana-3796	225	7	266.48	266.48	NUM
cana-3796	225	8	mb	mb	NOUN
cana-3796	225	9	)	)	PUNCT
cana-3796	225	10	.	.	PUNCT
cana-3796	226	1	c.	c.	PROPN
cana-3796	226	2	non	non	ADJ
cana-3796	226	3	-	-	ADJ
cana-3796	226	4	trainable	trainable	ADJ
cana-3796	226	5	parameters	parameter	NOUN
cana-3796	226	6	:	:	PUNCT
cana-3796	226	7	139,776	139,776	NUM
cana-3796	226	8	(	(	PUNCT
cana-3796	226	9	546.00	546.00	NUM
cana-3796	226	10	kb	kb	NOUN
cana-3796	226	11	)	)	PUNCT
cana-3796	226	12	.	.	PUNCT
cana-3796	227	1	performance	performance	NOUN
cana-3796	227	2	of	of	ADP
cana-3796	227	3	character	character	NOUN
cana-3796	227	4	recognition	recognition	NOUN
cana-3796	227	5	operations	operation	NOUN
cana-3796	227	6	:	:	PUNCT
cana-3796	227	7	the	the	DET
cana-3796	227	8	experimental	experimental	ADJ
cana-3796	227	9	setup	setup	NOUN
cana-3796	227	10	was	be	AUX
cana-3796	227	11	designed	design	VERB
cana-3796	227	12	to	to	PART
cana-3796	227	13	rigorously	rigorously	ADV
cana-3796	227	14	test	test	VERB
cana-3796	227	15	the	the	DET
cana-3796	227	16	proposed	propose	VERB
cana-3796	227	17	model	model	NOUN
cana-3796	227	18	against	against	ADP
cana-3796	227	19	various	various	ADJ
cana-3796	227	20	benchmarks	benchmark	NOUN
cana-3796	227	21	and	and	CCONJ
cana-3796	227	22	existing	exist	VERB
cana-3796	227	23	models	model	NOUN
cana-3796	227	24	,	,	PUNCT
cana-3796	227	25	ensuring	ensure	VERB
cana-3796	227	26	ana	ana	PROPN
cana-3796	227	27	comprehensive	comprehensive	ADJ
cana-3796	227	28	evaluation	evaluation	NOUN
cana-3796	227	29	of	of	ADP
cana-3796	227	30	its	its	PRON
cana-3796	227	31	efficacy	efficacy	NOUN
cana-3796	227	32	in	in	ADP
cana-3796	227	33	recognizing	recognize	VERB
cana-3796	227	34	and	and	CCONJ
cana-3796	227	35	processing	process	VERB
cana-3796	227	36	handwritten	handwritten	ADJ
cana-3796	227	37	telugu	telugu	NOUN
cana-3796	227	38	text	text	NOUN
cana-3796	227	39	.	.	PUNCT
cana-3796	228	1	the	the	DET
cana-3796	228	2	diversity	diversity	NOUN
cana-3796	228	3	in	in	ADP
cana-3796	228	4	the	the	DET
cana-3796	228	5	dataset	dataset	NOUN
cana-3796	228	6	,	,	PUNCT
cana-3796	228	7	along	along	ADP
cana-3796	228	8	with	with	ADP
cana-3796	228	9	the	the	DET
cana-3796	228	10	detailed	detailed	ADJ
cana-3796	228	11	specification	specification	NOUN
cana-3796	228	12	of	of	ADP
cana-3796	228	13	input	input	NOUN
cana-3796	228	14	parameters	parameter	NOUN
cana-3796	228	15	,	,	PUNCT
cana-3796	228	16	provided	provide	VERB
cana-3796	228	17	ana	ana	PROPN
cana-3796	228	18	robust	robust	ADJ
cana-3796	228	19	framework	framework	NOUN
cana-3796	228	20	for	for	ADP
cana-3796	228	21	assessing	assess	VERB
cana-3796	228	22	the	the	DET
cana-3796	228	23	model	model	NOUN
cana-3796	228	24	’s	’s	PART
cana-3796	228	25	performance	performance	NOUN
cana-3796	228	26	across	across	ADP
cana-3796	228	27	multiple	multiple	ADJ
cana-3796	228	28	dimensions	dimension	NOUN
cana-3796	228	29	.	.	PUNCT
cana-3796	229	1	based	base	VERB
cana-3796	229	2	on	on	ADP
cana-3796	229	3	this	this	DET
cana-3796	229	4	strategy	strategy	NOUN
cana-3796	229	5	,	,	PUNCT
cana-3796	229	6	the	the	DET
cana-3796	229	7	precision	precision	NOUN
cana-3796	229	8	(	(	PUNCT
cana-3796	229	9	p	p	NOUN
cana-3796	229	10	)	)	PUNCT
cana-3796	229	11	,	,	PUNCT
cana-3796	229	12	accuracy	accuracy	NOUN
cana-3796	229	13	(	(	PUNCT
cana-3796	229	14	a	a	DET
cana-3796	229	15	)	)	PUNCT
cana-3796	229	16	levels	level	NOUN
cana-3796	229	17	were	be	AUX
cana-3796	229	18	estimated	estimate	VERB
cana-3796	229	19	via	via	ADP
cana-3796	229	20	equations	equation	NOUN
cana-3796	229	21	19	19	NUM
cana-3796	229	22	and	and	CCONJ
cana-3796	229	23	20	20	NUM
cana-3796	229	24	as	as	SCONJ
cana-3796	229	25	follows	follow	VERB
cana-3796	229	26	,	,	PUNCT
cana-3796	229	27	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-3796	229	28	=	=	SYM
cana-3796	229	29	𝑇𝑃	𝑇𝑃	PROPN
cana-3796	229	30	𝑇𝑃	𝑇𝑃	PROPN
cana-3796	229	31	+	+	CCONJ
cana-3796	229	32	𝐹𝑃	𝐹𝑃	PROPN
cana-3796	229	33	…	…	PUNCT
cana-3796	229	34	(	(	PUNCT
cana-3796	229	35	19	19	NUM
cana-3796	229	36	)	)	PUNCT
cana-3796	229	37	communications	communication	NOUN
cana-3796	229	38	on	on	ADP
cana-3796	229	39	applied	apply	VERB
cana-3796	229	40	nonlinear	nonlinear	ADJ
cana-3796	229	41	analysis	analysis	NOUN
cana-3796	229	42	issn	issn	NOUN
cana-3796	229	43	:	:	PUNCT
cana-3796	229	44	1074	1074	NUM
cana-3796	229	45	-	-	PUNCT
cana-3796	229	46	133x	133x	NUM
cana-3796	229	47	vol	vol	NOUN
cana-3796	229	48	32	32	NUM
cana-3796	229	49	no	no	NOUN
cana-3796	229	50	.	.	PUNCT
cana-3796	230	1	8s	8s	PROPN
cana-3796	230	2	(	(	PUNCT
cana-3796	230	3	2025	2025	NUM
cana-3796	230	4	)	)	PUNCT
cana-3796	230	5	756	756	NUM
cana-3796	231	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	231	2	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
cana-3796	231	3	=	=	SYM
cana-3796	231	4	𝑇𝑃	𝑇𝑃	PROPN
cana-3796	231	5	+	+	CCONJ
cana-3796	231	6	𝑇𝑁	𝑇𝑁	PROPN
cana-3796	231	7	𝑇𝑃	𝑇𝑃	PROPN
cana-3796	231	8	+	+	CCONJ
cana-3796	231	9	𝑇𝑁	𝑇𝑁	PROPN
cana-3796	231	10	+	+	NUM
cana-3796	231	11	𝐹𝑃	𝐹𝑃	NOUN
cana-3796	231	12	+	+	CCONJ
cana-3796	231	13	𝐹𝑁	𝐹𝑁	PROPN
cana-3796	231	14	…	…	PUNCT
cana-3796	231	15	(	(	PUNCT
cana-3796	231	16	20	20	NUM
cana-3796	231	17	)	)	PUNCT
cana-3796	231	18	where	where	SCONJ
cana-3796	231	19	,	,	PUNCT
cana-3796	231	20	true	true	ADJ
cana-3796	231	21	positive	positive	ADJ
cana-3796	231	22	(	(	PUNCT
cana-3796	231	23	tp	tp	NOUN
cana-3796	231	24	):	):	PUNCT
cana-3796	231	25	the	the	DET
cana-3796	231	26	number	number	NOUN
cana-3796	231	27	of	of	ADP
cana-3796	231	28	instances	instance	NOUN
cana-3796	231	29	correctly	correctly	ADV
cana-3796	231	30	predicted	predict	VERB
cana-3796	231	31	as	as	ADP
cana-3796	231	32	positive	positive	ADJ
cana-3796	231	33	(	(	PUNCT
cana-3796	231	34	correct	correct	ADJ
cana-3796	231	35	)	)	PUNCT
cana-3796	231	36	in	in	ADP
cana-3796	231	37	the	the	DET
cana-3796	231	38	test	test	NOUN
cana-3796	231	39	set	set	NOUN
cana-3796	231	40	,	,	PUNCT
cana-3796	231	41	true	true	ADJ
cana-3796	231	42	negative	negative	ADJ
cana-3796	231	43	(	(	PUNCT
cana-3796	231	44	tn	tn	NOUN
cana-3796	231	45	):	):	PUNCT
cana-3796	231	46	the	the	DET
cana-3796	231	47	number	number	NOUN
cana-3796	231	48	of	of	ADP
cana-3796	231	49	instances	instance	NOUN
cana-3796	231	50	correctly	correctly	ADV
cana-3796	231	51	predicted	predict	VERB
cana-3796	231	52	as	as	ADP
cana-3796	231	53	negative	negative	ADJ
cana-3796	231	54	(	(	PUNCT
cana-3796	231	55	incorrect	incorrect	ADJ
cana-3796	231	56	)	)	PUNCT
cana-3796	231	57	in	in	ADP
cana-3796	231	58	the	the	DET
cana-3796	231	59	test	test	NOUN
cana-3796	231	60	set	set	NOUN
cana-3796	231	61	,	,	PUNCT
cana-3796	231	62	false	false	ADJ
cana-3796	231	63	positive	positive	ADJ
cana-3796	231	64	(	(	PUNCT
cana-3796	231	65	fp	fp	NOUN
cana-3796	231	66	):	):	PUNCT
cana-3796	231	67	the	the	DET
cana-3796	231	68	number	number	NOUN
cana-3796	231	69	of	of	ADP
cana-3796	231	70	instances	instance	NOUN
cana-3796	231	71	incorrectly	incorrectly	ADV
cana-3796	231	72	predicted	predict	VERB
cana-3796	231	73	as	as	ADP
cana-3796	231	74	positive	positive	ADJ
cana-3796	231	75	(	(	PUNCT
cana-3796	231	76	correct	correct	ADJ
cana-3796	231	77	)	)	PUNCT
cana-3796	231	78	when	when	SCONJ
cana-3796	231	79	they	they	PRON
cana-3796	231	80	are	be	AUX
cana-3796	231	81	actually	actually	ADV
cana-3796	231	82	negative	negative	ADJ
cana-3796	231	83	(	(	PUNCT
cana-3796	231	84	incorrect	incorrect	ADJ
cana-3796	231	85	)	)	PUNCT
cana-3796	231	86	in	in	ADP
cana-3796	231	87	the	the	DET
cana-3796	231	88	test	test	NOUN
cana-3796	231	89	set	set	NOUN
cana-3796	231	90	,	,	PUNCT
cana-3796	231	91	and	and	CCONJ
cana-3796	231	92	false	false	ADJ
cana-3796	231	93	negative	negative	ADJ
cana-3796	231	94	(	(	PUNCT
cana-3796	231	95	fn	fn	NOUN
cana-3796	231	96	):	):	PUNCT
cana-3796	231	97	the	the	DET
cana-3796	231	98	number	number	NOUN
cana-3796	231	99	of	of	ADP
cana-3796	231	100	instances	instance	NOUN
cana-3796	231	101	incorrectly	incorrectly	ADV
cana-3796	231	102	predicted	predict	VERB
cana-3796	231	103	as	as	ADP
cana-3796	231	104	negative	negative	ADJ
cana-3796	231	105	(	(	PUNCT
cana-3796	231	106	incorrect	incorrect	ADJ
cana-3796	231	107	)	)	PUNCT
cana-3796	231	108	when	when	SCONJ
cana-3796	231	109	they	they	PRON
cana-3796	231	110	are	be	AUX
cana-3796	231	111	actually	actually	ADV
cana-3796	231	112	positive	positive	ADJ
cana-3796	231	113	(	(	PUNCT
cana-3796	231	114	correct	correct	ADJ
cana-3796	231	115	)	)	PUNCT
cana-3796	231	116	in	in	ADP
cana-3796	231	117	the	the	DET
cana-3796	231	118	test	test	NOUN
cana-3796	231	119	sets	set	NOUN
cana-3796	231	120	.	.	PUNCT
cana-3796	232	1	based	base	VERB
cana-3796	232	2	on	on	ADP
cana-3796	232	3	this	this	DET
cana-3796	232	4	analysis	analysis	NOUN
cana-3796	232	5	,	,	PUNCT
cana-3796	232	6	the	the	DET
cana-3796	232	7	precision	precision	NOUN
cana-3796	232	8	obtained	obtain	VERB
cana-3796	232	9	during	during	ADP
cana-3796	232	10	character	character	NOUN
cana-3796	232	11	recognition	recognition	NOUN
cana-3796	232	12	operations	operation	NOUN
cana-3796	232	13	was	be	AUX
cana-3796	232	14	compared	compare	VERB
cana-3796	232	15	with	with	ADP
cana-3796	232	16	two	two	NUM
cana-3796	232	17	level	level	NOUN
cana-3796	232	18	rectification	rectification	NOUN
cana-3796	232	19	attention	attention	NOUN
cana-3796	232	20	network	network	NOUN
cana-3796	232	21	(	(	PUNCT
cana-3796	232	22	tlran	tlran	NOUN
cana-3796	232	23	)	)	PUNCT
cana-3796	233	1	[	[	X
cana-3796	233	2	8	8	NUM
cana-3796	233	3	]	]	PUNCT
cana-3796	233	4	,	,	PUNCT
cana-3796	233	5	end	end	NOUN
cana-3796	233	6	-	-	PUNCT
cana-3796	233	7	to	to	ADP
cana-3796	233	8	-	-	PUNCT
cana-3796	233	9	end	end	NOUN
cana-3796	233	10	deep	deep	ADJ
cana-3796	233	11	-	-	PUNCT
cana-3796	233	12	learning	learn	VERB
cana-3796	233	13	(	(	PUNCT
cana-3796	233	14	eedl	eedl	PROPN
cana-3796	233	15	)	)	PUNCT
cana-3796	234	1	[	[	X
cana-3796	234	2	38	38	NUM
cana-3796	234	3	]	]	PUNCT
cana-3796	234	4	and	and	CCONJ
cana-3796	234	5	deep	deep	ADJ
cana-3796	234	6	convolutional	convolutional	ADJ
cana-3796	234	7	neural	neural	ADJ
cana-3796	234	8	network	network	NOUN
cana-3796	234	9	(	(	PUNCT
cana-3796	234	10	dcnn	dcnn	PROPN
cana-3796	234	11	)	)	PUNCT
cana-3796	235	1	[	[	X
cana-3796	235	2	6	6	NUM
cana-3796	235	3	]	]	PUNCT
cana-3796	235	4	,	,	PUNCT
cana-3796	235	5	and	and	CCONJ
cana-3796	235	6	can	can	AUX
cana-3796	235	7	be	be	AUX
cana-3796	235	8	observed	observe	VERB
cana-3796	235	9	from	from	ADP
cana-3796	235	10	table	table	NOUN
cana-3796	235	11	2	2	NUM
cana-3796	235	12	as	as	SCONJ
cana-3796	235	13	follows	follow	VERB
cana-3796	235	14	,	,	PUNCT
cana-3796	235	15	table	table	NOUN
cana-3796	235	16	2	2	NUM
cana-3796	235	17	:	:	PUNCT
cana-3796	235	18	precision	precision	NOUN
cana-3796	235	19	comparison	comparison	NOUN
cana-3796	235	20	of	of	ADP
cana-3796	235	21	character	character	NOUN
cana-3796	235	22	recognition	recognition	NOUN
cana-3796	235	23	models	model	NOUN
cana-3796	235	24	across	across	ADP
cana-3796	235	25	dataset	dataset	ADJ
cana-3796	235	26	sizes	size	NOUN
cana-3796	235	27	dataset	dataset	VERB
cana-3796	235	28	size	size	NOUN
cana-3796	235	29	(	(	PUNCT
cana-3796	235	30	nts	nt	NOUN
cana-3796	235	31	)	)	PUNCT
cana-3796	235	32	tlran	tlran	NOUN
cana-3796	236	1	[	[	X
cana-3796	236	2	8	8	NUM
cana-3796	236	3	]	]	SYM
cana-3796	236	4	precision	precision	NOUN
cana-3796	236	5	eedl	eedl	PROPN
cana-3796	236	6	[	[	X
cana-3796	236	7	38	38	NUM
cana-3796	236	8	]	]	PUNCT
cana-3796	236	9	precision	precision	NOUN
cana-3796	236	10	dcnn	dcnn	VERB
cana-3796	236	11	[	[	X
cana-3796	236	12	6	6	NUM
cana-3796	236	13	]	]	PUNCT
cana-3796	236	14	precision	precision	NOUN
cana-3796	236	15	proposed	propose	VERB
cana-3796	236	16	model	model	NOUN
cana-3796	236	17	precision	precision	NOUN
cana-3796	236	18	1.2k	1.2k	NUM
cana-3796	236	19	3k	3k	NUM
cana-3796	236	20	80	80	NUM
cana-3796	236	21	%	%	NOUN
cana-3796	236	22	85	85	NUM
cana-3796	236	23	%	%	NOUN
cana-3796	236	24	~82	~82	NUM
cana-3796	236	25	%	%	NOUN
cana-3796	236	26	86	86	NUM
cana-3796	236	27	%	%	NOUN
cana-3796	236	28	85	85	NUM
cana-3796	236	29	%	%	NOUN
cana-3796	236	30	87	87	NUM
cana-3796	236	31	%	%	NOUN
cana-3796	236	32	91.55	91.55	NUM
cana-3796	236	33	%	%	NOUN
cana-3796	236	34	92.12	92.12	NUM
cana-3796	236	35	%	%	NOUN
cana-3796	236	36	3.5k	3.5k	NUM
cana-3796	236	37	7.8k	7.8k	NUM
cana-3796	236	38	79	79	NUM
cana-3796	236	39	%	%	NOUN
cana-3796	236	40	85	85	NUM
cana-3796	236	41	%	%	NOUN
cana-3796	236	42	83	83	NUM
cana-3796	236	43	%	%	NOUN
cana-3796	236	44	87	87	NUM
cana-3796	236	45	%	%	NOUN
cana-3796	236	46	82	82	NUM
cana-3796	236	47	%	%	NOUN
cana-3796	236	48	88	88	NUM
cana-3796	236	49	%	%	NOUN
cana-3796	236	50	89.71	89.71	NUM
cana-3796	236	51	%	%	NOUN
cana-3796	236	52	97.79	97.79	NUM
cana-3796	236	53	%	%	NOUN
cana-3796	236	54	8k	8k	NOUN
cana-3796	236	55	11.5k	11.5k	NUM
cana-3796	236	56	84	84	NUM
cana-3796	236	57	%	%	NOUN
cana-3796	236	58	88	88	NUM
cana-3796	236	59	%	%	NOUN
cana-3796	236	60	86	86	NUM
cana-3796	236	61	%	%	NOUN
cana-3796	236	62	89	89	NUM
cana-3796	236	63	%	%	NOUN
cana-3796	236	64	83	83	NUM
cana-3796	236	65	%	%	NOUN
cana-3796	236	66	87	87	NUM
cana-3796	236	67	%	%	NOUN
cana-3796	236	68	95	95	NUM
cana-3796	236	69	%	%	NOUN
cana-3796	236	70	99.33	99.33	NUM
cana-3796	236	71	%	%	NOUN
cana-3796	236	72	12k	12k	NOUN
cana-3796	236	73	15k	15k	NOUN
cana-3796	236	74	~85	~85	NOUN
cana-3796	236	75	%	%	NOUN
cana-3796	236	76	88	88	NUM
cana-3796	236	77	%	%	NOUN
cana-3796	236	78	~87	~87	NOUN
cana-3796	236	79	%	%	NOUN
cana-3796	236	80	90	90	NUM
cana-3796	236	81	%	%	NOUN
cana-3796	236	82	~86	~86	NOUN
cana-3796	236	83	%	%	NOUN
cana-3796	236	84	89	89	NUM
cana-3796	236	85	%	%	NOUN
cana-3796	236	86	94	94	NUM
cana-3796	236	87	%	%	NOUN
cana-3796	236	88	99	99	NUM
cana-3796	236	89	%	%	NOUN
cana-3796	236	90	in	in	ADP
cana-3796	236	91	the	the	DET
cana-3796	236	92	initial	initial	ADJ
cana-3796	236	93	phase	phase	NOUN
cana-3796	236	94	(	(	PUNCT
cana-3796	236	95	1.2k–3k	1.2k–3k	NUM
cana-3796	236	96	nts	nt	NOUN
cana-3796	236	97	)	)	PUNCT
cana-3796	236	98	,	,	PUNCT
cana-3796	236	99	the	the	DET
cana-3796	236	100	proposed	propose	VERB
cana-3796	236	101	model	model	NOUN
cana-3796	236	102	's	's	PART
cana-3796	236	103	accuracy	accuracy	NOUN
cana-3796	236	104	fluctuates	fluctuate	NOUN
cana-3796	236	105	,	,	PUNCT
cana-3796	236	106	starting	start	VERB
cana-3796	236	107	at	at	ADP
cana-3796	236	108	84.33	84.33	NUM
cana-3796	236	109	%	%	NOUN
cana-3796	236	110	at	at	ADP
cana-3796	236	111	1.2k	1.2k	NUM
cana-3796	236	112	nts	nt	NOUN
cana-3796	236	113	and	and	CCONJ
cana-3796	236	114	stabilizing	stabilize	VERB
cana-3796	236	115	around	around	ADV
cana-3796	236	116	82	82	NUM
cana-3796	236	117	%	%	NOUN
cana-3796	236	118	by	by	ADP
cana-3796	236	119	3k	3k	PROPN
cana-3796	236	120	nts	nt	NOUN
cana-3796	236	121	,	,	PUNCT
cana-3796	236	122	reflecting	reflect	VERB
cana-3796	236	123	its	its	PRON
cana-3796	236	124	learning	learn	VERB
cana-3796	236	125	curve	curve	NOUN
cana-3796	236	126	and	and	CCONJ
cana-3796	236	127	adaptation	adaptation	NOUN
cana-3796	236	128	to	to	ADP
cana-3796	236	129	telugu	telugu	NOUN
cana-3796	236	130	handwriting	handwriting	NOUN
cana-3796	236	131	styles	style	NOUN
cana-3796	236	132	.	.	PUNCT
cana-3796	237	1	in	in	ADP
cana-3796	237	2	the	the	DET
cana-3796	237	3	mid	mid	ADJ
cana-3796	237	4	-	-	ADJ
cana-3796	237	5	range	range	ADJ
cana-3796	237	6	datasets	dataset	NOUN
cana-3796	237	7	(	(	PUNCT
cana-3796	237	8	3.5k–7.8k	3.5k–7.8k	NUM
cana-3796	237	9	nts	nt	NOUN
cana-3796	237	10	)	)	PUNCT
cana-3796	237	11	,	,	PUNCT
cana-3796	237	12	the	the	DET
cana-3796	237	13	model	model	NOUN
cana-3796	237	14	consistently	consistently	ADV
cana-3796	237	15	outperforms	outperform	VERB
cana-3796	237	16	others	other	NOUN
cana-3796	237	17	,	,	PUNCT
cana-3796	237	18	achieving	achieve	VERB
cana-3796	237	19	92.49	92.49	NUM
cana-3796	237	20	%	%	NOUN
cana-3796	237	21	accuracy	accuracy	NOUN
cana-3796	237	22	at	at	ADP
cana-3796	237	23	7.8k	7.8k	PROPN
cana-3796	237	24	nts	nt	NOUN
cana-3796	237	25	,	,	PUNCT
cana-3796	237	26	highlighting	highlight	VERB
cana-3796	237	27	its	its	PRON
cana-3796	237	28	robust	robust	ADJ
cana-3796	237	29	feature	feature	NOUN
cana-3796	237	30	extraction	extraction	NOUN
cana-3796	237	31	through	through	ADP
cana-3796	237	32	convolutional	convolutional	ADJ
cana-3796	237	33	neural	neural	ADJ
cana-3796	237	34	networks	network	NOUN
cana-3796	237	35	and	and	CCONJ
cana-3796	237	36	quad	quad	ADJ
cana-3796	237	37	lstm	lstm	ADJ
cana-3796	237	38	integration	integration	NOUN
cana-3796	237	39	.	.	PUNCT
cana-3796	238	1	for	for	ADP
cana-3796	238	2	larger	large	ADJ
cana-3796	238	3	datasets	dataset	NOUN
cana-3796	238	4	(	(	PUNCT
cana-3796	238	5	8k–15k	8k–15k	ADJ
cana-3796	238	6	nts	nt	NOUN
cana-3796	238	7	)	)	PUNCT
cana-3796	238	8	,	,	PUNCT
cana-3796	238	9	the	the	DET
cana-3796	238	10	proposed	propose	VERB
cana-3796	238	11	model	model	NOUN
cana-3796	238	12	excels	excel	VERB
cana-3796	238	13	with	with	ADP
cana-3796	238	14	accuracies	accuracy	NOUN
cana-3796	238	15	consistently	consistently	ADV
cana-3796	238	16	above	above	ADP
cana-3796	238	17	90	90	NUM
cana-3796	238	18	%	%	NOUN
cana-3796	238	19	,	,	PUNCT
cana-3796	238	20	peaking	peak	VERB
cana-3796	238	21	at	at	ADP
cana-3796	238	22	96.66	96.66	NUM
cana-3796	238	23	%	%	NOUN
cana-3796	238	24	at	at	ADP
cana-3796	238	25	14k	14k	NOUN
cana-3796	238	26	nts	nt	NOUN
cana-3796	238	27	.	.	PUNCT
cana-3796	239	1	this	this	PRON
cana-3796	239	2	demonstrates	demonstrate	VERB
cana-3796	239	3	its	its	PRON
cana-3796	239	4	scalability	scalability	NOUN
cana-3796	239	5	and	and	CCONJ
cana-3796	239	6	ability	ability	NOUN
cana-3796	239	7	to	to	PART
cana-3796	239	8	handle	handle	VERB
cana-3796	239	9	complex	complex	ADJ
cana-3796	239	10	data	datum	NOUN
cana-3796	239	11	effectively	effectively	ADV
cana-3796	239	12	,	,	PUNCT
cana-3796	239	13	aided	aid	VERB
cana-3796	239	14	by	by	ADP
cana-3796	239	15	techniques	technique	NOUN
cana-3796	239	16	such	such	ADJ
cana-3796	239	17	as	as	ADP
cana-3796	239	18	bahdanau	bahdanau	ADJ
cana-3796	239	19	attention	attention	NOUN
cana-3796	239	20	and	and	CCONJ
cana-3796	239	21	transformer	transformer	NOUN
cana-3796	239	22	-	-	PUNCT
cana-3796	239	23	based	base	VERB
cana-3796	239	24	nlp	nlp	NOUN
cana-3796	239	25	models	model	NOUN
cana-3796	239	26	.	.	PUNCT
cana-3796	240	1	these	these	DET
cana-3796	240	2	high	high	ADJ
cana-3796	240	3	accuracy	accuracy	NOUN
cana-3796	240	4	levels	level	NOUN
cana-3796	240	5	are	be	AUX
cana-3796	240	6	crucial	crucial	ADJ
cana-3796	240	7	for	for	ADP
cana-3796	240	8	ocr	ocr	PROPN
cana-3796	240	9	applications	application	NOUN
cana-3796	240	10	,	,	PUNCT
cana-3796	240	11	ensuring	ensure	VERB
cana-3796	240	12	precise	precise	ADJ
cana-3796	240	13	recognition	recognition	NOUN
cana-3796	240	14	of	of	ADP
cana-3796	240	15	telugu	telugu	PROPN
cana-3796	240	16	script	script	NOUN
cana-3796	240	17	,	,	PUNCT
cana-3796	240	18	particularly	particularly	ADV
cana-3796	240	19	for	for	ADP
cana-3796	240	20	the	the	DET
cana-3796	240	21	automated	automate	VERB
cana-3796	240	22	evaluation	evaluation	NOUN
cana-3796	240	23	of	of	ADP
cana-3796	240	24	handwritten	handwritten	ADJ
cana-3796	240	25	documents	document	NOUN
cana-3796	240	26	as	as	SCONJ
cana-3796	240	27	shown	show	VERB
cana-3796	240	28	in	in	ADP
cana-3796	240	29	table	table	NOUN
cana-3796	240	30	3	3	NUM
cana-3796	240	31	furthermore	furthermore	ADV
cana-3796	240	32	,	,	PUNCT
cana-3796	240	33	its	its	PRON
cana-3796	240	34	strong	strong	ADJ
cana-3796	240	35	performance	performance	NOUN
cana-3796	240	36	enables	enable	VERB
cana-3796	240	37	broader	broad	ADJ
cana-3796	240	38	applications	application	NOUN
cana-3796	240	39	,	,	PUNCT
cana-3796	240	40	such	such	ADJ
cana-3796	240	41	as	as	ADP
cana-3796	240	42	document	document	NOUN
cana-3796	240	43	digitization	digitization	NOUN
cana-3796	240	44	.	.	PUNCT
cana-3796	241	1	table	table	NOUN
cana-3796	241	2	3	3	NUM
cana-3796	241	3	:	:	PUNCT
cana-3796	241	4	accuracy	accuracy	NOUN
cana-3796	241	5	comparison	comparison	NOUN
cana-3796	241	6	of	of	ADP
cana-3796	241	7	telugu	telugu	PROPN
cana-3796	241	8	character	character	NOUN
cana-3796	241	9	recognition	recognition	NOUN
cana-3796	241	10	models	model	NOUN
cana-3796	241	11	dataset	dataset	VERB
cana-3796	241	12	size	size	NOUN
cana-3796	241	13	(	(	PUNCT
cana-3796	241	14	nts	nt	NOUN
cana-3796	241	15	)	)	PUNCT
cana-3796	241	16	tlran	tlran	NOUN
cana-3796	241	17	[	[	X
cana-3796	241	18	8	8	NUM
cana-3796	241	19	]	]	SYM
cana-3796	241	20	accuracy	accuracy	NOUN
cana-3796	241	21	(	(	PUNCT
cana-3796	241	22	%	%	INTJ
cana-3796	241	23	)	)	PUNCT
cana-3796	241	24	eedl	eedl	PROPN
cana-3796	242	1	[	[	X
cana-3796	242	2	38	38	NUM
cana-3796	242	3	]	]	SYM
cana-3796	242	4	accuracy	accuracy	NOUN
cana-3796	242	5	(	(	PUNCT
cana-3796	242	6	%	%	INTJ
cana-3796	242	7	)	)	PUNCT
cana-3796	242	8	dcnn	dcnn	PROPN
cana-3796	243	1	[	[	X
cana-3796	243	2	6	6	NUM
cana-3796	243	3	]	]	SYM
cana-3796	243	4	accuracy	accuracy	NOUN
cana-3796	243	5	(	(	PUNCT
cana-3796	243	6	%	%	INTJ
cana-3796	243	7	)	)	PUNCT
cana-3796	243	8	proposed	propose	VERB
cana-3796	243	9	model	model	NOUN
cana-3796	243	10	accuracy	accuracy	NOUN
cana-3796	243	11	(	(	PUNCT
cana-3796	243	12	%	%	INTJ
cana-3796	243	13	)	)	PUNCT
cana-3796	243	14	1.2k	1.2k	NUM
cana-3796	243	15	85.41	85.41	NUM
cana-3796	243	16	79.66	79.66	NUM
cana-3796	243	17	72.85	72.85	NUM
cana-3796	243	18	84.33	84.33	NUM
cana-3796	243	19	2.4k	2.4k	NUM
cana-3796	243	20	86.32	86.32	NUM
cana-3796	243	21	80.44	80.44	NUM
cana-3796	243	22	74.12	74.12	NUM
cana-3796	243	23	85.22	85.22	NUM
cana-3796	243	24	3.5k	3.5k	NUM
cana-3796	243	25	87.74	87.74	NUM
cana-3796	243	26	81.77	81.77	NUM
cana-3796	243	27	75.66	75.66	NUM
cana-3796	243	28	89.23	89.23	NUM
cana-3796	243	29	4.8k	4.8k	NUM
cana-3796	243	30	88.61	88.61	NUM
cana-3796	243	31	83.11	83.11	NUM
cana-3796	243	32	77.54	77.54	NUM
cana-3796	243	33	90.11	90.11	NUM
cana-3796	243	34	6k	6k	NOUN
cana-3796	243	35	89.22	89.22	NUM
cana-3796	243	36	84.56	84.56	NUM
cana-3796	243	37	79.23	79.23	NUM
cana-3796	243	38	91.00	91.00	NUM
cana-3796	243	39	7.8k	7.8k	NUM
cana-3796	243	40	90.45	90.45	NUM
cana-3796	243	41	85.88	85.88	NUM
cana-3796	243	42	81.41	81.41	NUM
cana-3796	243	43	92.49	92.49	NUM
cana-3796	243	44	9.7k	9.7k	NUM
cana-3796	243	45	91.66	91.66	NUM
cana-3796	243	46	87.31	87.31	NUM
cana-3796	243	47	83.22	83.22	NUM
cana-3796	243	48	94.33	94.33	NUM
cana-3796	243	49	10.8k	10.8k	NUM
cana-3796	243	50	92.32	92.32	NUM
cana-3796	243	51	88.44	88.44	NUM
cana-3796	243	52	85.44	85.44	NUM
cana-3796	243	53	95.55	95.55	NUM
cana-3796	243	54	12k	12k	PROPN
cana-3796	243	55	93.41	93.41	NUM
cana-3796	243	56	89.77	89.77	NUM
cana-3796	243	57	86.33	86.33	NUM
cana-3796	243	58	96.00	96.00	NUM
cana-3796	243	59	14.5k	14.5k	NUM
cana-3796	243	60	94.22	94.22	NUM
cana-3796	243	61	90.66	90.66	NUM
cana-3796	243	62	87.55	87.55	NUM
cana-3796	243	63	96.66	96.66	NUM
cana-3796	243	64	the	the	DET
cana-3796	243	65	following	follow	VERB
cana-3796	243	66	figure	figure	NOUN
cana-3796	243	67	6	6	NUM
cana-3796	243	68	highlights	highlight	NOUN
cana-3796	243	69	the	the	DET
cana-3796	243	70	auc	auc	ADJ
cana-3796	243	71	levels	level	NOUN
cana-3796	243	72	across	across	ADP
cana-3796	243	73	various	various	ADJ
cana-3796	243	74	dataset	dataset	NOUN
cana-3796	243	75	sizes	size	NOUN
cana-3796	243	76	(	(	PUNCT
cana-3796	243	77	nts	nt	NOUN
cana-3796	243	78	)	)	PUNCT
cana-3796	243	79	,	,	PUNCT
cana-3796	243	80	revealing	reveal	VERB
cana-3796	243	81	distinct	distinct	ADJ
cana-3796	243	82	trends	trend	NOUN
cana-3796	243	83	.	.	PUNCT
cana-3796	244	1	for	for	ADP
cana-3796	244	2	smaller	small	ADJ
cana-3796	244	3	datasets	dataset	NOUN
cana-3796	244	4	(	(	PUNCT
cana-3796	244	5	1.2k–3k	1.2k–3k	NUM
cana-3796	244	6	nts	nt	NOUN
cana-3796	244	7	)	)	PUNCT
cana-3796	244	8	,	,	PUNCT
cana-3796	244	9	the	the	DET
cana-3796	244	10	proposed	propose	VERB
cana-3796	244	11	model	model	NOUN
cana-3796	244	12	demonstrates	demonstrate	VERB
cana-3796	244	13	strong	strong	ADJ
cana-3796	244	14	discriminative	discriminative	NOUN
cana-3796	244	15	ability	ability	NOUN
cana-3796	244	16	,	,	PUNCT
cana-3796	244	17	with	with	ADP
cana-3796	244	18	communications	communication	NOUN
cana-3796	244	19	on	on	ADP
cana-3796	244	20	applied	apply	VERB
cana-3796	244	21	nonlinear	nonlinear	ADJ
cana-3796	244	22	analysis	analysis	NOUN
cana-3796	244	23	issn	issn	NOUN
cana-3796	244	24	:	:	PUNCT
cana-3796	244	25	1074	1074	NUM
cana-3796	244	26	-	-	PUNCT
cana-3796	244	27	133x	133x	NUM
cana-3796	244	28	vol	vol	NOUN
cana-3796	244	29	32	32	NUM
cana-3796	244	30	no	no	NOUN
cana-3796	244	31	.	.	PUNCT
cana-3796	245	1	8s	8s	PROPN
cana-3796	245	2	(	(	PUNCT
cana-3796	245	3	2025	2025	NUM
cana-3796	245	4	)	)	PUNCT
cana-3796	245	5	757	757	NUM
cana-3796	245	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	245	7	auc	auc	NOUN
cana-3796	245	8	levels	level	NOUN
cana-3796	245	9	ranging	range	VERB
cana-3796	245	10	from	from	ADP
cana-3796	245	11	82.80	82.80	NUM
cana-3796	245	12	%	%	NOUN
cana-3796	245	13	to	to	ADP
cana-3796	245	14	88.15	88.15	NUM
cana-3796	245	15	%	%	NOUN
cana-3796	245	16	,	,	PUNCT
cana-3796	245	17	indicating	indicate	VERB
cana-3796	245	18	its	its	PRON
cana-3796	245	19	effectiveness	effectiveness	NOUN
cana-3796	245	20	in	in	ADP
cana-3796	245	21	distinguishing	distinguish	VERB
cana-3796	245	22	correctly	correctly	ADV
cana-3796	245	23	and	and	CCONJ
cana-3796	245	24	incorrectly	incorrectly	ADV
cana-3796	245	25	recognized	recognize	VERB
cana-3796	245	26	characters	character	NOUN
cana-3796	245	27	.	.	PUNCT
cana-3796	246	1	this	this	DET
cana-3796	246	2	performance	performance	NOUN
cana-3796	246	3	is	be	AUX
cana-3796	246	4	supported	support	VERB
cana-3796	246	5	by	by	ADP
cana-3796	246	6	advanced	advanced	ADJ
cana-3796	246	7	neural	neural	ADJ
cana-3796	246	8	networks	network	NOUN
cana-3796	246	9	and	and	CCONJ
cana-3796	246	10	image	image	NOUN
cana-3796	246	11	preprocessing	preprocessing	NOUN
cana-3796	246	12	techniques	technique	NOUN
cana-3796	246	13	.	.	PUNCT
cana-3796	247	1	in	in	ADP
cana-3796	247	2	the	the	DET
cana-3796	247	3	mid	mid	ADJ
cana-3796	247	4	-	-	ADJ
cana-3796	247	5	range	range	ADJ
cana-3796	247	6	datasets	dataset	NOUN
cana-3796	247	7	(	(	PUNCT
cana-3796	247	8	3.5k–7.8k	3.5k–7.8k	NUM
cana-3796	247	9	nts	nt	NOUN
cana-3796	247	10	)	)	PUNCT
cana-3796	247	11	,	,	PUNCT
cana-3796	247	12	auc	auc	NOUN
cana-3796	247	13	levels	level	NOUN
cana-3796	247	14	exhibit	exhibit	VERB
cana-3796	247	15	minor	minor	ADJ
cana-3796	247	16	fluctuations	fluctuation	NOUN
cana-3796	247	17	but	but	CCONJ
cana-3796	247	18	remain	remain	VERB
cana-3796	247	19	competitive	competitive	ADJ
cana-3796	247	20	.	.	PUNCT
cana-3796	248	1	for	for	ADP
cana-3796	248	2	instance	instance	NOUN
cana-3796	248	3	,	,	PUNCT
cana-3796	248	4	at	at	ADP
cana-3796	248	5	7.2k	7.2k	NOUN
cana-3796	248	6	nts	nt	NOUN
cana-3796	248	7	,	,	PUNCT
cana-3796	248	8	the	the	DET
cana-3796	248	9	model	model	NOUN
cana-3796	248	10	achieves	achieve	VERB
cana-3796	248	11	an	an	DET
cana-3796	248	12	auc	auc	NOUN
cana-3796	248	13	of	of	ADP
cana-3796	248	14	91.41	91.41	NUM
cana-3796	248	15	%	%	NOUN
cana-3796	248	16	,	,	PUNCT
cana-3796	248	17	showcasing	showcase	VERB
cana-3796	248	18	its	its	PRON
cana-3796	248	19	adaptability	adaptability	NOUN
cana-3796	248	20	to	to	ADP
cana-3796	248	21	various	various	ADJ
cana-3796	248	22	handwriting	handwriting	NOUN
cana-3796	248	23	styles	style	NOUN
cana-3796	248	24	and	and	CCONJ
cana-3796	248	25	complexities	complexity	NOUN
cana-3796	248	26	.	.	PUNCT
cana-3796	249	1	for	for	ADP
cana-3796	249	2	larger	large	ADJ
cana-3796	249	3	datasets	dataset	NOUN
cana-3796	249	4	(	(	PUNCT
cana-3796	249	5	8k–15k	8k–15k	ADJ
cana-3796	249	6	nts	nt	NOUN
cana-3796	249	7	)	)	PUNCT
cana-3796	249	8	,	,	PUNCT
cana-3796	249	9	the	the	DET
cana-3796	249	10	proposed	propose	VERB
cana-3796	249	11	model	model	NOUN
cana-3796	249	12	consistently	consistently	ADV
cana-3796	249	13	maintains	maintain	VERB
cana-3796	249	14	high	high	ADJ
cana-3796	249	15	auc	auc	NOUN
cana-3796	249	16	levels	level	NOUN
cana-3796	249	17	,	,	PUNCT
cana-3796	249	18	often	often	ADV
cana-3796	249	19	exceeding	exceed	VERB
cana-3796	249	20	90	90	NUM
cana-3796	249	21	%	%	NOUN
cana-3796	249	22	.	.	PUNCT
cana-3796	250	1	at	at	ADP
cana-3796	250	2	13.5k	13.5k	NUM
cana-3796	250	3	nts	nt	NOUN
cana-3796	250	4	,	,	PUNCT
cana-3796	250	5	the	the	DET
cana-3796	250	6	model	model	NOUN
cana-3796	250	7	reaches	reach	VERB
cana-3796	250	8	its	its	PRON
cana-3796	250	9	peak	peak	NOUN
cana-3796	250	10	auc	auc	NOUN
cana-3796	250	11	of	of	ADP
cana-3796	250	12	96.76	96.76	NUM
cana-3796	250	13	%	%	NOUN
cana-3796	250	14	,	,	PUNCT
cana-3796	250	15	demonstrating	demonstrate	VERB
cana-3796	250	16	its	its	PRON
cana-3796	250	17	scalability	scalability	NOUN
cana-3796	250	18	and	and	CCONJ
cana-3796	250	19	proficiency	proficiency	NOUN
cana-3796	250	20	in	in	ADP
cana-3796	250	21	handling	handle	VERB
cana-3796	250	22	complex	complex	ADJ
cana-3796	250	23	data	datum	NOUN
cana-3796	250	24	through	through	ADP
cana-3796	250	25	deep	deep	ADJ
cana-3796	250	26	learning	learning	NOUN
cana-3796	250	27	and	and	CCONJ
cana-3796	250	28	contextual	contextual	ADJ
cana-3796	250	29	analysis	analysis	NOUN
cana-3796	250	30	techniques	technique	NOUN
cana-3796	250	31	.	.	PUNCT
cana-3796	251	1	these	these	DET
cana-3796	251	2	auc	auc	ADJ
cana-3796	251	3	levels	level	NOUN
cana-3796	251	4	are	be	AUX
cana-3796	251	5	crucial	crucial	ADJ
cana-3796	251	6	for	for	SCONJ
cana-3796	251	7	ocr	ocr	NOUN
cana-3796	251	8	processes	process	NOUN
cana-3796	251	9	involving	involve	VERB
cana-3796	251	10	complex	complex	ADJ
cana-3796	251	11	scripts	script	NOUN
cana-3796	251	12	like	like	ADP
cana-3796	251	13	telugu	telugu	PROPN
cana-3796	251	14	,	,	PUNCT
cana-3796	251	15	ensuring	ensure	VERB
cana-3796	251	16	accurate	accurate	ADJ
cana-3796	251	17	discrimination	discrimination	NOUN
cana-3796	251	18	between	between	ADP
cana-3796	251	19	correct	correct	ADJ
cana-3796	251	20	and	and	CCONJ
cana-3796	251	21	incorrect	incorrect	ADJ
cana-3796	251	22	character	character	NOUN
cana-3796	251	23	recognition	recognition	NOUN
cana-3796	251	24	.	.	PUNCT
cana-3796	252	1	such	such	ADJ
cana-3796	252	2	precision	precision	NOUN
cana-3796	252	3	is	be	AUX
cana-3796	252	4	essential	essential	ADJ
cana-3796	252	5	for	for	ADP
cana-3796	252	6	applications	application	NOUN
cana-3796	252	7	like	like	ADP
cana-3796	252	8	automated	automate	VERB
cana-3796	252	9	assessments	assessment	NOUN
cana-3796	252	10	and	and	CCONJ
cana-3796	252	11	document	document	NOUN
cana-3796	252	12	digitization	digitization	NOUN
cana-3796	252	13	.	.	PUNCT
cana-3796	253	1	the	the	DET
cana-3796	253	2	ability	ability	NOUN
cana-3796	253	3	of	of	ADP
cana-3796	253	4	the	the	DET
cana-3796	253	5	proposed	propose	VERB
cana-3796	253	6	model	model	NOUN
cana-3796	253	7	to	to	PART
cana-3796	253	8	sustain	sustain	VERB
cana-3796	253	9	high	high	ADJ
cana-3796	253	10	auc	auc	NOUN
cana-3796	253	11	levels	level	NOUN
cana-3796	253	12	across	across	ADP
cana-3796	253	13	different	different	ADJ
cana-3796	253	14	dataset	dataset	NOUN
cana-3796	253	15	sizes	size	NOUN
cana-3796	253	16	highlights	highlight	VERB
cana-3796	253	17	its	its	PRON
cana-3796	253	18	adaptability	adaptability	NOUN
cana-3796	253	19	and	and	CCONJ
cana-3796	253	20	reliability	reliability	NOUN
cana-3796	253	21	for	for	ADP
cana-3796	253	22	various	various	ADJ
cana-3796	253	23	applications	application	NOUN
cana-3796	253	24	,	,	PUNCT
cana-3796	253	25	from	from	ADP
cana-3796	253	26	real	real	ADJ
cana-3796	253	27	-	-	PUNCT
cana-3796	253	28	time	time	NOUN
cana-3796	253	29	character	character	NOUN
cana-3796	253	30	recognition	recognition	NOUN
cana-3796	253	31	in	in	ADP
cana-3796	253	32	consumer	consumer	NOUN
cana-3796	253	33	tools	tool	NOUN
cana-3796	253	34	to	to	ADP
cana-3796	253	35	large	large	ADJ
cana-3796	253	36	-	-	PUNCT
cana-3796	253	37	scale	scale	NOUN
cana-3796	253	38	processing	processing	NOUN
cana-3796	253	39	of	of	ADP
cana-3796	253	40	historical	historical	ADJ
cana-3796	253	41	documents	document	NOUN
cana-3796	253	42	.	.	PUNCT
cana-3796	254	1	figure	figure	VERB
cana-3796	254	2	6	6	NUM
cana-3796	254	3	:	:	PUNCT
cana-3796	254	4	auc	auc	NOUN
cana-3796	254	5	levels	level	NOUN
cana-3796	254	6	for	for	ADP
cana-3796	254	7	the	the	DET
cana-3796	254	8	telugu	telugu	PROPN
cana-3796	254	9	character	character	NOUN
cana-3796	254	10	recognition	recognition	NOUN
cana-3796	254	11	process	process	NOUN
cana-3796	254	12	performance	performance	NOUN
cana-3796	254	13	of	of	ADP
cana-3796	254	14	sentence	sentence	NOUN
cana-3796	254	15	recognition	recognition	NOUN
cana-3796	254	16	operations	operation	NOUN
cana-3796	254	17	the	the	DET
cana-3796	254	18	proposed	propose	VERB
cana-3796	254	19	model	model	NOUN
cana-3796	254	20	also	also	ADV
cana-3796	254	21	assists	assist	VERB
cana-3796	254	22	in	in	ADP
cana-3796	254	23	improving	improve	VERB
cana-3796	254	24	the	the	DET
cana-3796	254	25	sentence	sentence	NOUN
cana-3796	254	26	recognition	recognition	NOUN
cana-3796	254	27	capabilities	capability	NOUN
cana-3796	254	28	for	for	ADP
cana-3796	254	29	telugu	telugu	NOUN
cana-3796	254	30	language	language	NOUN
cana-3796	254	31	image	image	NOUN
cana-3796	254	32	sets	set	NOUN
cana-3796	254	33	.	.	PUNCT
cana-3796	255	1	similar	similar	ADJ
cana-3796	255	2	to	to	ADP
cana-3796	255	3	previous	previous	ADJ
cana-3796	255	4	performance	performance	NOUN
cana-3796	255	5	analysis	analysis	NOUN
cana-3796	255	6	,	,	PUNCT
cana-3796	255	7	these	these	DET
cana-3796	255	8	capabilities	capability	NOUN
cana-3796	255	9	are	be	AUX
cana-3796	255	10	evaluated	evaluate	VERB
cana-3796	255	11	in	in	ADP
cana-3796	255	12	terms	term	NOUN
cana-3796	255	13	of	of	ADP
cana-3796	255	14	precision	precision	NOUN
cana-3796	255	15	,	,	PUNCT
cana-3796	255	16	accuracy	accuracy	NOUN
cana-3796	255	17	,	,	PUNCT
cana-3796	255	18	auc	auc	NOUN
cana-3796	255	19	levels	level	NOUN
cana-3796	255	20	.	.	PUNCT
cana-3796	256	1	based	base	VERB
cana-3796	256	2	on	on	ADP
cana-3796	256	3	this	this	DET
cana-3796	256	4	process	process	NOUN
cana-3796	256	5	,	,	PUNCT
cana-3796	256	6	the	the	DET
cana-3796	256	7	precision	precision	NOUN
cana-3796	256	8	levels	level	NOUN
cana-3796	256	9	for	for	ADP
cana-3796	256	10	sentence	sentence	NOUN
cana-3796	256	11	recognition	recognition	NOUN
cana-3796	256	12	can	can	AUX
cana-3796	256	13	be	be	AUX
cana-3796	256	14	observed	observe	VERB
cana-3796	256	15	in	in	ADP
cana-3796	256	16	the	the	DET
cana-3796	256	17	table	table	NOUN
cana-3796	256	18	4	4	NUM
cana-3796	256	19	as	as	SCONJ
cana-3796	256	20	follows	follow	VERB
cana-3796	256	21	:	:	PUNCT
cana-3796	256	22	table	table	NOUN
cana-3796	256	23	4	4	NUM
cana-3796	256	24	:	:	PUNCT
cana-3796	256	25	precision	precision	NOUN
cana-3796	256	26	levels	level	NOUN
cana-3796	256	27	for	for	ADP
cana-3796	256	28	sentence	sentence	NOUN
cana-3796	256	29	recognition	recognition	NOUN
cana-3796	256	30	nts	nt	NOUN
cana-3796	256	31	p	p	X
cana-3796	256	32	(	(	PUNCT
cana-3796	256	33	%	%	INTJ
cana-3796	256	34	)	)	PUNCT
cana-3796	257	1	p	p	NOUN
cana-3796	257	2	(	(	PUNCT
cana-3796	257	3	%	%	INTJ
cana-3796	257	4	)	)	PUNCT
cana-3796	257	5	p	p	NOUN
cana-3796	257	6	(	(	PUNCT
cana-3796	257	7	%	%	INTJ
cana-3796	257	8	)	)	PUNCT
cana-3796	258	1	p	p	NOUN
cana-3796	258	2	(	(	PUNCT
cana-3796	258	3	%	%	NOUN
cana-3796	258	4	)	)	PUNCT
cana-3796	258	5	tlran	tlran	NOUN
cana-3796	259	1	[	[	X
cana-3796	259	2	8	8	NUM
cana-3796	259	3	]	]	PUNCT
cana-3796	259	4	eedl	eedl	PROPN
cana-3796	260	1	[	[	X
cana-3796	260	2	38	38	NUM
cana-3796	260	3	]	]	PUNCT
cana-3796	260	4	dcnn	dcnn	VERB
cana-3796	261	1	[	[	X
cana-3796	261	2	6	6	NUM
cana-3796	261	3	]	]	PUNCT
cana-3796	261	4	proposed	propose	VERB
cana-3796	261	5	1.2k	1.2k	NUM
cana-3796	261	6	76.76	76.76	NUM
cana-3796	261	7	73.55	73.55	NUM
cana-3796	261	8	79.11	79.11	NUM
cana-3796	261	9	90.14	90.14	NUM
cana-3796	261	10	4.3k	4.3k	NUM
cana-3796	261	11	79.75	79.75	NUM
cana-3796	261	12	82.02	82.02	NUM
cana-3796	261	13	83.73	83.73	NUM
cana-3796	261	14	80.62	80.62	NUM
cana-3796	261	15	6k	6k	NOUN
cana-3796	261	16	81.89	81.89	NUM
cana-3796	261	17	78.19	78.19	NUM
cana-3796	261	18	71.99	71.99	NUM
cana-3796	261	19	86.89	86.89	NUM
cana-3796	261	20	9k	9k	NUM
cana-3796	261	21	77.24	77.24	NUM
cana-3796	261	22	76.87	76.87	NUM
cana-3796	261	23	83.45	83.45	NUM
cana-3796	261	24	88.11	88.11	NUM
cana-3796	261	25	14.5k	14.5k	NUM
cana-3796	261	26	86.93	86.93	NUM
cana-3796	261	27	83.20	83.20	NUM
cana-3796	261	28	75.96	75.96	NUM
cana-3796	261	29	92.94	92.94	NUM
cana-3796	261	30	15k	15k	NOUN
cana-3796	261	31	88.05	88.05	NUM
cana-3796	261	32	85.71	85.71	NUM
cana-3796	261	33	81.20	81.20	NUM
cana-3796	261	34	94.06	94.06	NUM
cana-3796	261	35	communications	communication	NOUN
cana-3796	261	36	on	on	ADP
cana-3796	261	37	applied	apply	VERB
cana-3796	261	38	nonlinear	nonlinear	ADJ
cana-3796	261	39	analysis	analysis	NOUN
cana-3796	261	40	issn	issn	NOUN
cana-3796	261	41	:	:	PUNCT
cana-3796	261	42	1074	1074	NUM
cana-3796	261	43	-	-	PUNCT
cana-3796	261	44	133x	133x	NUM
cana-3796	261	45	vol	vol	NOUN
cana-3796	261	46	32	32	NUM
cana-3796	261	47	no	no	NOUN
cana-3796	261	48	.	.	PUNCT
cana-3796	262	1	8s	8s	PROPN
cana-3796	262	2	(	(	PUNCT
cana-3796	262	3	2025	2025	NUM
cana-3796	262	4	)	)	PUNCT
cana-3796	262	5	758	758	NUM
cana-3796	262	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	262	7	table	table	NOUN
cana-3796	262	8	5	5	NUM
cana-3796	262	9	:	:	PUNCT
cana-3796	262	10	accuracy	accuracy	NOUN
cana-3796	262	11	levels	level	NOUN
cana-3796	262	12	for	for	ADP
cana-3796	262	13	the	the	DET
cana-3796	262	14	telugu	telugu	PROPN
cana-3796	262	15	sentence	sentence	NOUN
cana-3796	262	16	recognition	recognition	NOUN
cana-3796	262	17	process	process	NOUN
cana-3796	262	18	as	as	SCONJ
cana-3796	262	19	shown	show	VERB
cana-3796	262	20	in	in	ADP
cana-3796	262	21	table	table	NOUN
cana-3796	262	22	5	5	NUM
cana-3796	262	23	,	,	PUNCT
cana-3796	262	24	in	in	ADP
cana-3796	262	25	smaller	small	ADJ
cana-3796	262	26	datasets	dataset	NOUN
cana-3796	262	27	(	(	PUNCT
cana-3796	262	28	1.2k	1.2k	NUM
cana-3796	262	29	nts	nt	NOUN
cana-3796	262	30	)	)	PUNCT
cana-3796	262	31	,	,	PUNCT
cana-3796	262	32	the	the	DET
cana-3796	262	33	proposed	propose	VERB
cana-3796	262	34	model	model	NOUN
cana-3796	262	35	demonstrates	demonstrate	VERB
cana-3796	262	36	impressive	impressive	ADJ
cana-3796	262	37	performance	performance	NOUN
cana-3796	262	38	with	with	ADP
cana-3796	262	39	an	an	DET
cana-3796	262	40	accuracy	accuracy	NOUN
cana-3796	262	41	of	of	ADP
cana-3796	262	42	88.18	88.18	NUM
cana-3796	262	43	%	%	NOUN
cana-3796	262	44	,	,	PUNCT
cana-3796	262	45	outperforming	outperform	VERB
cana-3796	262	46	other	other	ADJ
cana-3796	262	47	methods	method	NOUN
cana-3796	262	48	such	such	ADJ
cana-3796	262	49	as	as	ADP
cana-3796	262	50	tlran	tlran	NOUN
cana-3796	262	51	(	(	PUNCT
cana-3796	262	52	87.42	87.42	NUM
cana-3796	262	53	%	%	NOUN
cana-3796	262	54	)	)	PUNCT
cana-3796	262	55	and	and	CCONJ
cana-3796	262	56	dcnn	dcnn	PROPN
cana-3796	262	57	(	(	PUNCT
cana-3796	262	58	68.40	68.40	NUM
cana-3796	262	59	%	%	NOUN
cana-3796	262	60	)	)	PUNCT
cana-3796	262	61	.	.	PUNCT
cana-3796	263	1	as	as	SCONJ
cana-3796	263	2	the	the	DET
cana-3796	263	3	dataset	dataset	NOUN
cana-3796	263	4	size	size	NOUN
cana-3796	263	5	increases	increase	VERB
cana-3796	263	6	to	to	ADP
cana-3796	263	7	4.3k	4.3k	NUM
cana-3796	263	8	nts	nt	NOUN
cana-3796	263	9	,	,	PUNCT
cana-3796	263	10	the	the	DET
cana-3796	263	11	proposed	propose	VERB
cana-3796	263	12	model	model	NOUN
cana-3796	263	13	maintains	maintain	VERB
cana-3796	263	14	competitive	competitive	ADJ
cana-3796	263	15	accuracy	accuracy	NOUN
cana-3796	263	16	at	at	ADP
cana-3796	263	17	81.94	81.94	NUM
cana-3796	263	18	%	%	NOUN
cana-3796	263	19	,	,	PUNCT
cana-3796	263	20	compared	compare	VERB
cana-3796	263	21	to	to	ADP
cana-3796	263	22	tlran	tlran	NOUN
cana-3796	263	23	,	,	PUNCT
cana-3796	263	24	which	which	PRON
cana-3796	263	25	registers	register	VERB
cana-3796	263	26	80.15	80.15	NUM
cana-3796	263	27	%	%	NOUN
cana-3796	263	28	.	.	PUNCT
cana-3796	264	1	at	at	ADP
cana-3796	264	2	6k	6k	PROPN
cana-3796	264	3	nts	nt	NOUN
cana-3796	264	4	,	,	PUNCT
cana-3796	264	5	the	the	DET
cana-3796	264	6	proposed	propose	VERB
cana-3796	264	7	model	model	NOUN
cana-3796	264	8	achieves	achieve	VERB
cana-3796	264	9	an	an	DET
cana-3796	264	10	accuracy	accuracy	NOUN
cana-3796	264	11	of	of	ADP
cana-3796	264	12	81.83	81.83	NUM
cana-3796	264	13	%	%	NOUN
cana-3796	264	14	,	,	PUNCT
cana-3796	264	15	while	while	SCONJ
cana-3796	264	16	tlran	tlran	NOUN
cana-3796	264	17	shows	show	VERB
cana-3796	264	18	a	a	DET
cana-3796	264	19	slightly	slightly	ADV
cana-3796	264	20	higher	high	ADJ
cana-3796	264	21	accuracy	accuracy	NOUN
cana-3796	264	22	of	of	ADP
cana-3796	264	23	84.77	84.77	NUM
cana-3796	264	24	%	%	NOUN
cana-3796	264	25	.	.	PUNCT
cana-3796	265	1	at	at	ADP
cana-3796	265	2	9k	9k	PROPN
cana-3796	265	3	nts	nt	NOUN
cana-3796	265	4	,	,	PUNCT
cana-3796	265	5	the	the	DET
cana-3796	265	6	proposed	propose	VERB
cana-3796	265	7	model	model	NOUN
cana-3796	265	8	reaches	reach	VERB
cana-3796	265	9	an	an	DET
cana-3796	265	10	impressive	impressive	ADJ
cana-3796	265	11	accuracy	accuracy	NOUN
cana-3796	265	12	of	of	ADP
cana-3796	265	13	93.14	93.14	NUM
cana-3796	265	14	%	%	NOUN
cana-3796	265	15	,	,	PUNCT
cana-3796	265	16	surpassing	surpass	VERB
cana-3796	265	17	all	all	DET
cana-3796	265	18	other	other	ADJ
cana-3796	265	19	methods	method	NOUN
cana-3796	265	20	,	,	PUNCT
cana-3796	265	21	including	include	VERB
cana-3796	265	22	eedl	eedl	PROPN
cana-3796	265	23	(	(	PUNCT
cana-3796	265	24	77.22	77.22	NUM
cana-3796	265	25	%	%	NOUN
cana-3796	265	26	)	)	PUNCT
cana-3796	265	27	and	and	CCONJ
cana-3796	265	28	dcnn	dcnn	PROPN
cana-3796	265	29	(	(	PUNCT
cana-3796	265	30	78.07	78.07	NUM
cana-3796	265	31	%	%	NOUN
cana-3796	265	32	)	)	PUNCT
cana-3796	265	33	.	.	PUNCT
cana-3796	266	1	in	in	ADP
cana-3796	266	2	larger	large	ADJ
cana-3796	266	3	datasets	dataset	NOUN
cana-3796	266	4	,	,	PUNCT
cana-3796	266	5	such	such	ADJ
cana-3796	266	6	as	as	ADP
cana-3796	266	7	at	at	ADP
cana-3796	266	8	14.5k	14.5k	NUM
cana-3796	266	9	nts	nt	NOUN
cana-3796	266	10	,	,	PUNCT
cana-3796	266	11	the	the	DET
cana-3796	266	12	proposed	propose	VERB
cana-3796	266	13	model	model	NOUN
cana-3796	266	14	records	record	VERB
cana-3796	266	15	an	an	DET
cana-3796	266	16	accuracy	accuracy	NOUN
cana-3796	266	17	of	of	ADP
cana-3796	266	18	91.53	91.53	NUM
cana-3796	266	19	%	%	NOUN
cana-3796	266	20	,	,	PUNCT
cana-3796	266	21	while	while	SCONJ
cana-3796	266	22	tlran	tlran	NOUN
cana-3796	266	23	shows	show	VERB
cana-3796	266	24	a	a	DET
cana-3796	266	25	lower	low	ADJ
cana-3796	266	26	accuracy	accuracy	NOUN
cana-3796	266	27	of	of	ADP
cana-3796	266	28	74.35	74.35	NUM
cana-3796	266	29	%	%	NOUN
cana-3796	266	30	.	.	PUNCT
cana-3796	267	1	finally	finally	ADV
cana-3796	267	2	,	,	PUNCT
cana-3796	267	3	at	at	ADP
cana-3796	267	4	15k	15k	NOUN
cana-3796	267	5	nts	nt	NOUN
cana-3796	267	6	,	,	PUNCT
cana-3796	267	7	the	the	DET
cana-3796	267	8	proposed	propose	VERB
cana-3796	267	9	model	model	NOUN
cana-3796	267	10	achieves	achieve	VERB
cana-3796	267	11	an	an	DET
cana-3796	267	12	outstanding	outstanding	ADJ
cana-3796	267	13	accuracy	accuracy	NOUN
cana-3796	267	14	of	of	ADP
cana-3796	267	15	97.73	97.73	NUM
cana-3796	267	16	%	%	NOUN
cana-3796	267	17	,	,	PUNCT
cana-3796	267	18	significantly	significantly	ADV
cana-3796	267	19	outperforming	outperforming	NOUN
cana-3796	267	20	tlran	tlran	NOUN
cana-3796	267	21	(	(	PUNCT
cana-3796	267	22	83.00	83.00	NUM
cana-3796	267	23	%	%	NOUN
cana-3796	267	24	)	)	PUNCT
cana-3796	267	25	,	,	PUNCT
cana-3796	267	26	eedl	eedl	PROPN
cana-3796	267	27	(	(	PUNCT
cana-3796	267	28	86.73	86.73	NUM
cana-3796	267	29	%	%	NOUN
cana-3796	267	30	)	)	PUNCT
cana-3796	267	31	,	,	PUNCT
cana-3796	267	32	and	and	CCONJ
cana-3796	267	33	dcnn	dcnn	PROPN
cana-3796	267	34	(	(	PUNCT
cana-3796	267	35	82.57	82.57	NUM
cana-3796	267	36	%	%	NOUN
cana-3796	267	37	)	)	PUNCT
cana-3796	267	38	,	,	PUNCT
cana-3796	267	39	demonstrating	demonstrate	VERB
cana-3796	267	40	its	its	PRON
cana-3796	267	41	robustness	robustness	NOUN
cana-3796	267	42	and	and	CCONJ
cana-3796	267	43	effectiveness	effectiveness	NOUN
cana-3796	267	44	across	across	ADP
cana-3796	267	45	increasing	increase	VERB
cana-3796	267	46	dataset	dataset	ADJ
cana-3796	267	47	sizes	size	NOUN
cana-3796	267	48	.	.	PUNCT
cana-3796	268	1	similarly	similarly	ADV
cana-3796	268	2	,	,	PUNCT
cana-3796	268	3	the	the	DET
cana-3796	268	4	auc	auc	NOUN
cana-3796	268	5	levels	level	NOUN
cana-3796	268	6	observed	observe	VERB
cana-3796	268	7	in	in	ADP
cana-3796	268	8	figure	figure	NOUN
cana-3796	268	9	7	7	NUM
cana-3796	268	10	show	show	VERB
cana-3796	268	11	the	the	DET
cana-3796	268	12	following	follow	VERB
cana-3796	268	13	trends	trend	NOUN
cana-3796	268	14	:	:	PUNCT
cana-3796	268	15	in	in	ADP
cana-3796	268	16	the	the	DET
cana-3796	268	17	initial	initial	ADJ
cana-3796	268	18	data	datum	NOUN
cana-3796	268	19	ranges	range	NOUN
cana-3796	268	20	(	(	PUNCT
cana-3796	268	21	1.2k	1.2k	NUM
cana-3796	268	22	to	to	ADP
cana-3796	268	23	3k	3k	PROPN
cana-3796	268	24	nts	nt	NOUN
cana-3796	268	25	)	)	PUNCT
cana-3796	268	26	,	,	PUNCT
cana-3796	268	27	the	the	DET
cana-3796	268	28	proposed	propose	VERB
cana-3796	268	29	model	model	NOUN
cana-3796	268	30	exhibits	exhibit	VERB
cana-3796	268	31	a	a	DET
cana-3796	268	32	fluctuating	fluctuate	VERB
cana-3796	268	33	yet	yet	ADV
cana-3796	268	34	promising	promising	ADJ
cana-3796	268	35	trend	trend	NOUN
cana-3796	268	36	in	in	ADP
cana-3796	268	37	auc	auc	NOUN
cana-3796	268	38	,	,	PUNCT
cana-3796	268	39	peaking	peak	VERB
cana-3796	268	40	at	at	ADP
cana-3796	268	41	82.33	82.33	NUM
cana-3796	268	42	%	%	NOUN
cana-3796	268	43	at	at	ADP
cana-3796	268	44	1.8k	1.8k	NUM
cana-3796	268	45	nts	nt	NOUN
cana-3796	268	46	.	.	PUNCT
cana-3796	269	1	this	this	DET
cana-3796	269	2	variation	variation	NOUN
cana-3796	269	3	suggests	suggest	VERB
cana-3796	269	4	that	that	SCONJ
cana-3796	269	5	while	while	SCONJ
cana-3796	269	6	the	the	DET
cana-3796	269	7	proposed	propose	VERB
cana-3796	269	8	model	model	NOUN
cana-3796	269	9	is	be	AUX
cana-3796	269	10	generally	generally	ADV
cana-3796	269	11	proficient	proficient	ADJ
cana-3796	269	12	in	in	ADP
cana-3796	269	13	distinguishing	distinguish	VERB
cana-3796	269	14	between	between	ADP
cana-3796	269	15	accurate	accurate	ADJ
cana-3796	269	16	and	and	CCONJ
cana-3796	269	17	inaccurate	inaccurate	ADJ
cana-3796	269	18	sentence	sentence	NOUN
cana-3796	269	19	recognitions	recognition	NOUN
cana-3796	269	20	,	,	PUNCT
cana-3796	269	21	its	its	PRON
cana-3796	269	22	performance	performance	NOUN
cana-3796	269	23	may	may	AUX
cana-3796	269	24	vary	vary	VERB
cana-3796	269	25	depending	depend	VERB
cana-3796	269	26	on	on	ADP
cana-3796	269	27	specific	specific	ADJ
cana-3796	269	28	dataset	dataset	NOUN
cana-3796	269	29	characteristics	characteristic	NOUN
cana-3796	269	30	,	,	PUNCT
cana-3796	269	31	such	such	ADJ
cana-3796	269	32	as	as	ADP
cana-3796	269	33	the	the	DET
cana-3796	269	34	complexity	complexity	NOUN
cana-3796	269	35	of	of	ADP
cana-3796	269	36	sentence	sentence	NOUN
cana-3796	269	37	structures	structure	NOUN
cana-3796	269	38	or	or	CCONJ
cana-3796	269	39	variability	variability	NOUN
cana-3796	269	40	in	in	ADP
cana-3796	269	41	handwriting	handwriting	NOUN
cana-3796	269	42	styles	style	NOUN
cana-3796	269	43	.	.	PUNCT
cana-3796	270	1	as	as	SCONJ
cana-3796	270	2	dataset	dataset	ADJ
cana-3796	270	3	sizes	size	NOUN
cana-3796	270	4	increase	increase	VERB
cana-3796	270	5	(	(	PUNCT
cana-3796	270	6	3.5k	3.5k	NUM
cana-3796	270	7	to	to	ADP
cana-3796	270	8	7.8k	7.8k	NUM
cana-3796	270	9	nts	nt	NOUN
cana-3796	270	10	)	)	PUNCT
cana-3796	270	11	,	,	PUNCT
cana-3796	270	12	the	the	DET
cana-3796	270	13	proposed	propose	VERB
cana-3796	270	14	model	model	NOUN
cana-3796	270	15	's	's	PART
cana-3796	270	16	auc	auc	NOUN
cana-3796	270	17	levels	level	NOUN
cana-3796	270	18	exhibit	exhibit	VERB
cana-3796	270	19	both	both	DET
cana-3796	270	20	fluctuations	fluctuation	NOUN
cana-3796	270	21	and	and	CCONJ
cana-3796	270	22	peaks	peak	NOUN
cana-3796	270	23	.	.	PUNCT
cana-3796	271	1	notably	notably	ADV
cana-3796	271	2	,	,	PUNCT
cana-3796	271	3	at	at	ADP
cana-3796	271	4	3.5k	3.5k	NUM
cana-3796	271	5	nts	nt	NOUN
cana-3796	271	6	,	,	PUNCT
cana-3796	271	7	the	the	DET
cana-3796	271	8	model	model	NOUN
cana-3796	271	9	achieves	achieve	VERB
cana-3796	271	10	an	an	DET
cana-3796	271	11	auc	auc	NOUN
cana-3796	271	12	of	of	ADP
cana-3796	271	13	84.94	84.94	NUM
cana-3796	271	14	%	%	NOUN
cana-3796	271	15	,	,	PUNCT
cana-3796	271	16	demonstrating	demonstrate	VERB
cana-3796	271	17	its	its	PRON
cana-3796	271	18	strong	strong	ADJ
cana-3796	271	19	capability	capability	NOUN
cana-3796	271	20	to	to	PART
cana-3796	271	21	discriminate	discriminate	VERB
cana-3796	271	22	sentences	sentence	NOUN
cana-3796	271	23	accurately	accurately	ADV
cana-3796	271	24	.	.	PUNCT
cana-3796	272	1	however	however	ADV
cana-3796	272	2	,	,	PUNCT
cana-3796	272	3	there	there	PRON
cana-3796	272	4	are	be	VERB
cana-3796	272	5	instances	instance	NOUN
cana-3796	272	6	,	,	PUNCT
cana-3796	272	7	such	such	ADJ
cana-3796	272	8	as	as	ADP
cana-3796	272	9	at	at	ADP
cana-3796	272	10	4.3k	4.3k	NUM
cana-3796	272	11	nts	nt	NOUN
cana-3796	272	12	,	,	PUNCT
cana-3796	272	13	where	where	SCONJ
cana-3796	272	14	its	its	PRON
cana-3796	272	15	performance	performance	NOUN
cana-3796	272	16	slightly	slightly	ADV
cana-3796	272	17	dips	dip	VERB
cana-3796	272	18	to	to	ADP
cana-3796	272	19	77.83	77.83	NUM
cana-3796	272	20	%	%	NOUN
cana-3796	272	21	.	.	PUNCT
cana-3796	273	1	this	this	DET
cana-3796	273	2	dip	dip	NOUN
cana-3796	273	3	may	may	AUX
cana-3796	273	4	be	be	AUX
cana-3796	273	5	due	due	ADJ
cana-3796	273	6	to	to	ADP
cana-3796	273	7	the	the	DET
cana-3796	273	8	model	model	NOUN
cana-3796	273	9	adjusting	adjust	VERB
cana-3796	273	10	to	to	ADP
cana-3796	273	11	the	the	DET
cana-3796	273	12	increased	increase	VERB
cana-3796	273	13	complexity	complexity	NOUN
cana-3796	273	14	and	and	CCONJ
cana-3796	273	15	diversity	diversity	NOUN
cana-3796	273	16	within	within	ADP
cana-3796	273	17	the	the	DET
cana-3796	273	18	larger	large	ADJ
cana-3796	273	19	datasets	dataset	NOUN
cana-3796	273	20	.	.	PUNCT
cana-3796	274	1	figure	figure	NOUN
cana-3796	274	2	7	7	NUM
cana-3796	274	3	.	.	PUNCT
cana-3796	274	4	auc	auc	NOUN
cana-3796	274	5	levels	level	NOUN
cana-3796	274	6	for	for	ADP
cana-3796	274	7	the	the	DET
cana-3796	274	8	telugu	telugu	PROPN
cana-3796	274	9	sentence	sentence	NOUN
cana-3796	274	10	recognition	recognition	NOUN
cana-3796	274	11	process	process	NOUN
cana-3796	274	12	60.00	60.00	NUM
cana-3796	274	13	65.00	65.00	NUM
cana-3796	274	14	70.00	70.00	NUM
cana-3796	274	15	75.00	75.00	NUM
cana-3796	274	16	80.00	80.00	NUM
cana-3796	274	17	85.00	85.00	NUM
cana-3796	274	18	90.00	90.00	NUM
cana-3796	274	19	95.00	95.00	NUM
cana-3796	274	20	1	1	NUM
cana-3796	274	21	.	.	PUNCT
cana-3796	274	22	2k	2k	NUM
cana-3796	274	23	1	1	NUM
cana-3796	274	24	.	.	PUNCT
cana-3796	274	25	8k	8k	PROPN
cana-3796	274	26	2	2	NUM
cana-3796	274	27	.	.	PUNCT
cana-3796	275	1	4k	4k	NOUN
cana-3796	275	2	3	3	NUM
cana-3796	275	3	k	k	NOUN
cana-3796	275	4	3	3	X
cana-3796	275	5	.	.	PUNCT
cana-3796	275	6	5k	5k	NUM
cana-3796	275	7	4	4	NUM
cana-3796	275	8	.	.	PUNCT
cana-3796	275	9	3k	3k	PROPN
cana-3796	275	10	4	4	NUM
cana-3796	275	11	.	.	X
cana-3796	275	12	8k	8k	NUM
cana-3796	275	13	5	5	NUM
cana-3796	276	1	k	k	NOUN
cana-3796	276	2	6	6	NUM
cana-3796	276	3	k	k	NOUN
cana-3796	276	4	6	6	NUM
cana-3796	276	5	.	.	PUNCT
cana-3796	276	6	5k	5k	NUM
cana-3796	276	7	7	7	NUM
cana-3796	276	8	.	.	PUNCT
cana-3796	276	9	2k	2k	NOUN
cana-3796	276	10	7	7	NUM
cana-3796	276	11	.	.	X
cana-3796	276	12	8k	8k	NUM
cana-3796	276	13	8	8	NUM
cana-3796	277	1	k	k	NOUN
cana-3796	277	2	9	9	NUM
cana-3796	277	3	k	k	NOUN
cana-3796	277	4	9	9	NUM
cana-3796	277	5	.	.	PUNCT
cana-3796	277	6	7k	7k	NOUN
cana-3796	277	7	10	10	NUM
cana-3796	278	1	.2	.2	NUM
cana-3796	278	2	k	k	PROPN
cana-3796	279	1	10	10	NUM
cana-3796	279	2	.8	.8	NUM
cana-3796	279	3	k	k	PROPN
cana-3796	280	1	11	11	NUM
cana-3796	280	2	.5	.5	NUM
cana-3796	281	1	k	k	NOUN
cana-3796	281	2	12	12	NUM
cana-3796	281	3	k	k	NOUN
cana-3796	281	4	12	12	NUM
cana-3796	281	5	.5	.5	NUM
cana-3796	282	1	k	k	NOUN
cana-3796	282	2	13	13	NUM
cana-3796	282	3	.5	.5	NUM
cana-3796	283	1	k	k	NOUN
cana-3796	283	2	14	14	NUM
cana-3796	284	1	k	k	PROPN
cana-3796	284	2	14	14	NUM
cana-3796	284	3	.5	.5	NUM
cana-3796	285	1	k	k	SYM
cana-3796	285	2	15	15	NUM
cana-3796	285	3	k	k	NOUN
cana-3796	285	4	tlran	tlran	NOUN
cana-3796	285	5	[	[	X
cana-3796	285	6	8	8	NUM
cana-3796	285	7	]	]	PUNCT
cana-3796	285	8	eedl	eedl	PROPN
cana-3796	286	1	[	[	X
cana-3796	286	2	38	38	NUM
cana-3796	286	3	]	]	PUNCT
cana-3796	286	4	dcnn	dcnn	VERB
cana-3796	287	1	[	[	X
cana-3796	287	2	6	6	NUM
cana-3796	287	3	]	]	PUNCT
cana-3796	287	4	proposed	propose	VERB
cana-3796	287	5	nts	nts	PROPN
cana-3796	287	6	tlran	tlran	NOUN
cana-3796	287	7	(	(	PUNCT
cana-3796	287	8	%	%	INTJ
cana-3796	287	9	)	)	PUNCT
cana-3796	287	10	eedl	eedl	PROPN
cana-3796	287	11	(	(	PUNCT
cana-3796	287	12	%	%	INTJ
cana-3796	287	13	)	)	PUNCT
cana-3796	287	14	dcnn	dcnn	PROPN
cana-3796	287	15	(	(	PUNCT
cana-3796	287	16	%	%	INTJ
cana-3796	287	17	)	)	PUNCT
cana-3796	287	18	proposed	propose	VERB
cana-3796	287	19	(	(	PUNCT
cana-3796	287	20	%	%	INTJ
cana-3796	287	21	)	)	PUNCT
cana-3796	287	22	1.2k	1.2k	NUM
cana-3796	287	23	87.42	87.42	NUM
cana-3796	287	24	76.19	76.19	NUM
cana-3796	287	25	68.40	68.40	NUM
cana-3796	287	26	88.18	88.18	NUM
cana-3796	287	27	4.3k	4.3k	NUM
cana-3796	287	28	80.15	80.15	NUM
cana-3796	287	29	76.14	76.14	NUM
cana-3796	287	30	74.80	74.80	NUM
cana-3796	287	31	81.94	81.94	NUM
cana-3796	287	32	6k	6k	NOUN
cana-3796	287	33	84.77	84.77	NUM
cana-3796	287	34	75.02	75.02	NUM
cana-3796	287	35	68.72	68.72	NUM
cana-3796	287	36	81.83	81.83	NUM
cana-3796	287	37	9k	9k	NUM
cana-3796	287	38	92.82	92.82	NUM
cana-3796	287	39	77.22	77.22	NUM
cana-3796	287	40	78.07	78.07	NUM
cana-3796	287	41	93.14	93.14	NUM
cana-3796	287	42	14.5k	14.5k	NUM
cana-3796	287	43	74.35	74.35	NUM
cana-3796	287	44	83.26	83.26	NUM
cana-3796	287	45	81.76	81.76	NUM
cana-3796	287	46	91.53	91.53	NUM
cana-3796	287	47	15k	15k	NOUN
cana-3796	287	48	83.00	83.00	NUM
cana-3796	287	49	86.73	86.73	NUM
cana-3796	287	50	82.57	82.57	NUM
cana-3796	287	51	97.73	97.73	NUM
cana-3796	287	52	communications	communication	NOUN
cana-3796	287	53	on	on	ADP
cana-3796	287	54	applied	apply	VERB
cana-3796	287	55	nonlinear	nonlinear	ADJ
cana-3796	287	56	analysis	analysis	NOUN
cana-3796	287	57	issn	issn	NOUN
cana-3796	287	58	:	:	PUNCT
cana-3796	287	59	1074	1074	NUM
cana-3796	287	60	-	-	PUNCT
cana-3796	287	61	133x	133x	NUM
cana-3796	287	62	vol	vol	NOUN
cana-3796	287	63	32	32	NUM
cana-3796	287	64	no	no	NOUN
cana-3796	287	65	.	.	PUNCT
cana-3796	288	1	8s	8s	PROPN
cana-3796	288	2	(	(	PUNCT
cana-3796	288	3	2025	2025	NUM
cana-3796	288	4	)	)	PUNCT
cana-3796	288	5	759	759	NUM
cana-3796	288	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	288	7	in	in	ADP
cana-3796	288	8	the	the	DET
cana-3796	288	9	larger	large	ADJ
cana-3796	288	10	datasets	dataset	NOUN
cana-3796	288	11	(	(	PUNCT
cana-3796	288	12	8k	8k	NOUN
cana-3796	288	13	to	to	ADP
cana-3796	288	14	15k	15k	NOUN
cana-3796	288	15	nts	nt	NOUN
cana-3796	288	16	)	)	PUNCT
cana-3796	288	17	,	,	PUNCT
cana-3796	288	18	proposed	propose	VERB
cana-3796	288	19	model	model	NOUN
cana-3796	288	20	maintains	maintain	VERB
cana-3796	288	21	relatively	relatively	ADV
cana-3796	288	22	high	high	ADJ
cana-3796	288	23	auc	auc	NOUN
cana-3796	288	24	levels	level	NOUN
cana-3796	288	25	,	,	PUNCT
cana-3796	288	26	often	often	ADV
cana-3796	288	27	surpassing	surpass	VERB
cana-3796	288	28	80	80	NUM
cana-3796	288	29	%	%	NOUN
cana-3796	288	30	.	.	PUNCT
cana-3796	289	1	the	the	DET
cana-3796	289	2	model	model	NOUN
cana-3796	289	3	's	's	PART
cana-3796	289	4	peak	peak	NOUN
cana-3796	289	5	performance	performance	NOUN
cana-3796	289	6	at	at	ADP
cana-3796	289	7	13.5k	13.5k	NUM
cana-3796	289	8	nts	nt	NOUN
cana-3796	289	9	with	with	ADP
cana-3796	289	10	an	an	DET
cana-3796	289	11	auc	auc	NOUN
cana-3796	289	12	of	of	ADP
cana-3796	289	13	92.06	92.06	NUM
cana-3796	289	14	%	%	NOUN
cana-3796	289	15	is	be	AUX
cana-3796	289	16	particularly	particularly	ADV
cana-3796	289	17	noteworthy	noteworthy	ADJ
cana-3796	289	18	,	,	PUNCT
cana-3796	289	19	underscoring	underscore	VERB
cana-3796	289	20	its	its	PRON
cana-3796	289	21	ability	ability	NOUN
cana-3796	289	22	to	to	PART
cana-3796	289	23	accurately	accurately	ADV
cana-3796	289	24	discriminate	discriminate	VERB
cana-3796	289	25	between	between	ADP
cana-3796	289	26	correct	correct	ADJ
cana-3796	289	27	and	and	CCONJ
cana-3796	289	28	incorrect	incorrect	ADJ
cana-3796	289	29	sentence	sentence	NOUN
cana-3796	289	30	recognitions	recognition	NOUN
cana-3796	289	31	in	in	ADP
cana-3796	289	32	extensive	extensive	ADJ
cana-3796	289	33	datasets	dataset	NOUN
cana-3796	289	34	&	&	CCONJ
cana-3796	289	35	samples	sample	NOUN
cana-3796	289	36	.	.	PUNCT
cana-3796	290	1	this	this	PRON
cana-3796	290	2	indicates	indicate	VERB
cana-3796	290	3	the	the	DET
cana-3796	290	4	model	model	NOUN
cana-3796	290	5	's	's	PART
cana-3796	290	6	advanced	advanced	ADJ
cana-3796	290	7	capabilities	capability	NOUN
cana-3796	290	8	in	in	ADP
cana-3796	290	9	processing	processing	NOUN
cana-3796	290	10	and	and	CCONJ
cana-3796	290	11	understanding	understand	VERB
cana-3796	290	12	the	the	DET
cana-3796	290	13	telugu	telugu	PROPN
cana-3796	290	14	script	script	NOUN
cana-3796	290	15	at	at	ADP
cana-3796	290	16	a	a	DET
cana-3796	290	17	broader	broad	ADJ
cana-3796	290	18	scale	scale	NOUN
cana-3796	290	19	for	for	ADP
cana-3796	290	20	different	different	ADJ
cana-3796	290	21	scenarios	scenario	NOUN
cana-3796	290	22	v.	v.	ADP
cana-3796	290	23	conclusion	conclusion	NOUN
cana-3796	290	24	&	&	CCONJ
cana-3796	290	25	future	future	ADJ
cana-3796	290	26	scope	scope	NOUN
cana-3796	290	27	the	the	DET
cana-3796	290	28	research	research	NOUN
cana-3796	290	29	presented	present	VERB
cana-3796	290	30	in	in	ADP
cana-3796	290	31	this	this	DET
cana-3796	290	32	work	work	NOUN
cana-3796	290	33	marks	mark	VERB
cana-3796	290	34	a	a	DET
cana-3796	290	35	significant	significant	ADJ
cana-3796	290	36	advancement	advancement	NOUN
cana-3796	290	37	in	in	ADP
cana-3796	290	38	the	the	DET
cana-3796	290	39	field	field	NOUN
cana-3796	290	40	of	of	ADP
cana-3796	290	41	optical	optical	ADJ
cana-3796	290	42	character	character	NOUN
cana-3796	290	43	recognition	recognition	NOUN
cana-3796	290	44	(	(	PUNCT
cana-3796	290	45	ocr	ocr	NOUN
cana-3796	290	46	)	)	PUNCT
cana-3796	290	47	for	for	ADP
cana-3796	290	48	languages	language	NOUN
cana-3796	290	49	with	with	ADP
cana-3796	290	50	complex	complex	ADJ
cana-3796	290	51	scripts	script	NOUN
cana-3796	290	52	like	like	ADP
cana-3796	290	53	telugu	telugu	PROPN
cana-3796	290	54	.	.	PUNCT
cana-3796	291	1	the	the	DET
cana-3796	291	2	study	study	NOUN
cana-3796	291	3	successfully	successfully	ADV
cana-3796	291	4	introduces	introduce	VERB
cana-3796	291	5	and	and	CCONJ
cana-3796	291	6	evaluates	evaluate	VERB
cana-3796	291	7	an	an	DET
cana-3796	291	8	innovative	innovative	ADJ
cana-3796	291	9	model	model	NOUN
cana-3796	291	10	that	that	PRON
cana-3796	291	11	integrates	integrate	VERB
cana-3796	291	12	advanced	advanced	ADJ
cana-3796	291	13	image	image	NOUN
cana-3796	291	14	preprocessing	preprocesse	VERB
cana-3796	291	15	techniques	technique	NOUN
cana-3796	291	16	,	,	PUNCT
cana-3796	291	17	convolutional	convolutional	ADJ
cana-3796	291	18	neural	neural	ADJ
cana-3796	291	19	networks	network	NOUN
cana-3796	291	20	(	(	PUNCT
cana-3796	291	21	cnns	cnns	PROPN
cana-3796	291	22	)	)	PUNCT
cana-3796	291	23	,	,	PUNCT
cana-3796	291	24	quad	quad	PROPN
cana-3796	291	25	long	long	ADJ
cana-3796	291	26	short	short	ADJ
cana-3796	291	27	-	-	PUNCT
cana-3796	291	28	term	term	NOUN
cana-3796	291	29	memory	memory	NOUN
cana-3796	291	30	(	(	PUNCT
cana-3796	291	31	lstm	lstm	NOUN
cana-3796	291	32	)	)	PUNCT
cana-3796	291	33	networks	network	NOUN
cana-3796	291	34	,	,	PUNCT
cana-3796	291	35	and	and	CCONJ
cana-3796	291	36	transformer	transformer	NOUN
cana-3796	291	37	-	-	PUNCT
cana-3796	291	38	based	base	VERB
cana-3796	291	39	natural	natural	ADJ
cana-3796	291	40	language	language	NOUN
cana-3796	291	41	processing	processing	NOUN
cana-3796	291	42	(	(	PUNCT
cana-3796	291	43	nlp	nlp	NOUN
cana-3796	291	44	)	)	PUNCT
cana-3796	291	45	models	model	NOUN
cana-3796	291	46	.	.	PUNCT
cana-3796	292	1	the	the	DET
cana-3796	292	2	results	result	NOUN
cana-3796	292	3	from	from	ADP
cana-3796	292	4	extensive	extensive	ADJ
cana-3796	292	5	testing	testing	NOUN
cana-3796	292	6	on	on	ADP
cana-3796	292	7	a	a	DET
cana-3796	292	8	diverse	diverse	ADJ
cana-3796	292	9	and	and	CCONJ
cana-3796	292	10	comprehensive	comprehensive	ADJ
cana-3796	292	11	dataset	dataset	NOUN
cana-3796	292	12	of	of	ADP
cana-3796	292	13	handwritten	handwritten	ADJ
cana-3796	292	14	telugu	telugu	PROPN
cana-3796	292	15	answer	answer	NOUN
cana-3796	292	16	books	book	NOUN
cana-3796	292	17	demonstrate	demonstrate	VERB
cana-3796	292	18	the	the	DET
cana-3796	292	19	model	model	NOUN
cana-3796	292	20	's	's	PART
cana-3796	292	21	superior	superior	ADJ
cana-3796	292	22	performance	performance	NOUN
cana-3796	292	23	in	in	ADP
cana-3796	292	24	both	both	DET
cana-3796	292	25	character	character	NOUN
cana-3796	292	26	and	and	CCONJ
cana-3796	292	27	sentence	sentence	NOUN
cana-3796	292	28	recognition	recognition	NOUN
cana-3796	292	29	tasks	task	NOUN
cana-3796	292	30	.	.	PUNCT
cana-3796	293	1	notably	notably	ADV
cana-3796	293	2	,	,	PUNCT
cana-3796	293	3	the	the	DET
cana-3796	293	4	proposed	propose	VERB
cana-3796	293	5	model	model	NOUN
cana-3796	293	6	achieved	achieve	VERB
cana-3796	293	7	improvements	improvement	NOUN
cana-3796	293	8	in	in	ADP
cana-3796	293	9	precision	precision	NOUN
cana-3796	293	10	and	and	CCONJ
cana-3796	293	11	accuracy	accuracy	NOUN
cana-3796	293	12	,	,	PUNCT
cana-3796	293	13	alongside	alongside	ADP
cana-3796	293	14	a	a	DET
cana-3796	293	15	reduction	reduction	NOUN
cana-3796	293	16	in	in	ADP
cana-3796	293	17	delay	delay	NOUN
cana-3796	293	18	times	time	NOUN
cana-3796	293	19	for	for	ADP
cana-3796	293	20	character	character	NOUN
cana-3796	293	21	recognition	recognition	NOUN
cana-3796	293	22	,	,	PUNCT
cana-3796	293	23	compared	compare	VERB
cana-3796	293	24	to	to	ADP
cana-3796	293	25	existing	exist	VERB
cana-3796	293	26	methods	method	NOUN
cana-3796	293	27	such	such	ADJ
cana-3796	293	28	as	as	ADP
cana-3796	293	29	tlran	tlran	NOUN
cana-3796	293	30	[	[	X
cana-3796	293	31	8	8	NUM
cana-3796	293	32	]	]	PUNCT
cana-3796	293	33	,	,	PUNCT
cana-3796	293	34	eedl	eedl	PROPN
cana-3796	294	1	[	[	X
cana-3796	294	2	38	38	NUM
cana-3796	294	3	]	]	PUNCT
cana-3796	294	4	,	,	PUNCT
cana-3796	294	5	and	and	CCONJ
cana-3796	294	6	dcnn	dcnn	VERB
cana-3796	295	1	[	[	X
cana-3796	295	2	6	6	NUM
cana-3796	295	3	]	]	PUNCT
cana-3796	295	4	.	.	PUNCT
cana-3796	296	1	the	the	DET
cana-3796	296	2	model	model	NOUN
cana-3796	296	3	also	also	ADV
cana-3796	296	4	excelled	excel	VERB
cana-3796	296	5	in	in	ADP
cana-3796	296	6	sentence	sentence	NOUN
cana-3796	296	7	recognition	recognition	NOUN
cana-3796	296	8	tasks	task	NOUN
cana-3796	296	9	,	,	PUNCT
cana-3796	296	10	showcasing	showcase	VERB
cana-3796	296	11	high	high	ADJ
cana-3796	296	12	precision	precision	NOUN
cana-3796	296	13	and	and	CCONJ
cana-3796	296	14	accuracy	accuracy	NOUN
cana-3796	296	15	,	,	PUNCT
cana-3796	296	16	thus	thus	ADV
cana-3796	296	17	confirming	confirm	VERB
cana-3796	296	18	its	its	PRON
cana-3796	296	19	effectiveness	effectiveness	NOUN
cana-3796	296	20	in	in	ADP
cana-3796	296	21	understanding	understanding	NOUN
cana-3796	296	22	and	and	CCONJ
cana-3796	296	23	processing	processing	NOUN
cana-3796	296	24	complex	complex	ADJ
cana-3796	296	25	sentence	sentence	NOUN
cana-3796	296	26	structures	structure	NOUN
cana-3796	296	27	.	.	PUNCT
cana-3796	297	1	impacts	impact	NOUN
cana-3796	297	2	of	of	ADP
cana-3796	297	3	this	this	DET
cana-3796	297	4	work	work	NOUN
cana-3796	297	5	:	:	PUNCT
cana-3796	298	1	1	1	X
cana-3796	298	2	.	.	PUNCT
cana-3796	299	1	the	the	DET
cana-3796	299	2	model	model	NOUN
cana-3796	299	3	's	's	PART
cana-3796	299	4	high	high	ADJ
cana-3796	299	5	accuracy	accuracy	NOUN
cana-3796	299	6	and	and	CCONJ
cana-3796	299	7	efficiency	efficiency	NOUN
cana-3796	299	8	in	in	ADP
cana-3796	299	9	processing	process	VERB
cana-3796	299	10	handwritten	handwritten	ADJ
cana-3796	299	11	text	text	NOUN
cana-3796	299	12	offer	offer	VERB
cana-3796	299	13	a	a	DET
cana-3796	299	14	promising	promising	ADJ
cana-3796	299	15	solution	solution	NOUN
cana-3796	299	16	for	for	ADP
cana-3796	299	17	automating	automate	VERB
cana-3796	299	18	the	the	DET
cana-3796	299	19	evaluation	evaluation	NOUN
cana-3796	299	20	of	of	ADP
cana-3796	299	21	answer	answer	NOUN
cana-3796	299	22	books	book	NOUN
cana-3796	299	23	in	in	ADP
cana-3796	299	24	educational	educational	ADJ
cana-3796	299	25	settings	setting	NOUN
cana-3796	299	26	.	.	PUNCT
cana-3796	300	1	this	this	PRON
cana-3796	300	2	can	can	AUX
cana-3796	300	3	significantly	significantly	ADV
cana-3796	300	4	reduce	reduce	VERB
cana-3796	300	5	the	the	DET
cana-3796	300	6	time	time	NOUN
cana-3796	300	7	and	and	CCONJ
cana-3796	300	8	resources	resource	NOUN
cana-3796	300	9	spent	spend	VERB
cana-3796	300	10	on	on	ADP
cana-3796	300	11	manual	manual	ADJ
cana-3796	300	12	grading	grading	NOUN
cana-3796	300	13	,	,	PUNCT
cana-3796	300	14	while	while	SCONJ
cana-3796	300	15	also	also	ADV
cana-3796	300	16	providing	provide	VERB
cana-3796	300	17	a	a	DET
cana-3796	300	18	fair	fair	ADJ
cana-3796	300	19	and	and	CCONJ
cana-3796	300	20	unbiased	unbiased	ADJ
cana-3796	300	21	assessment	assessment	NOUN
cana-3796	300	22	.	.	PUNCT
cana-3796	301	1	2	2	X
cana-3796	301	2	.	.	X
cana-3796	301	3	the	the	DET
cana-3796	301	4	proposed	propose	VERB
cana-3796	301	5	model	model	NOUN
cana-3796	301	6	's	's	PART
cana-3796	301	7	ability	ability	NOUN
cana-3796	301	8	to	to	PART
cana-3796	301	9	accurately	accurately	ADV
cana-3796	301	10	recognize	recognize	VERB
cana-3796	301	11	and	and	CCONJ
cana-3796	301	12	process	process	VERB
cana-3796	301	13	handwritten	handwritten	ADJ
cana-3796	301	14	telugu	telugu	NOUN
cana-3796	301	15	text	text	NOUN
cana-3796	301	16	paves	pave	VERB
cana-3796	301	17	the	the	DET
cana-3796	301	18	way	way	NOUN
cana-3796	301	19	for	for	ADP
cana-3796	301	20	digitizing	digitize	VERB
cana-3796	301	21	historical	historical	ADJ
cana-3796	301	22	manuscripts	manuscript	NOUN
cana-3796	301	23	and	and	CCONJ
cana-3796	301	24	documents	document	NOUN
cana-3796	301	25	,	,	PUNCT
cana-3796	301	26	thus	thus	ADV
cana-3796	301	27	preserving	preserve	VERB
cana-3796	301	28	cultural	cultural	ADJ
cana-3796	301	29	heritage	heritage	NOUN
cana-3796	301	30	and	and	CCONJ
cana-3796	301	31	making	make	VERB
cana-3796	301	32	it	it	PRON
cana-3796	301	33	more	more	ADV
cana-3796	301	34	accessible	accessible	ADJ
cana-3796	301	35	.	.	PUNCT
cana-3796	302	1	3	3	X
cana-3796	302	2	.	.	X
cana-3796	302	3	the	the	DET
cana-3796	302	4	model	model	NOUN
cana-3796	302	5	's	's	PART
cana-3796	302	6	successful	successful	ADJ
cana-3796	302	7	integration	integration	NOUN
cana-3796	302	8	of	of	ADP
cana-3796	302	9	advanced	advanced	ADJ
cana-3796	302	10	nlp	nlp	NOUN
cana-3796	302	11	techniques	technique	NOUN
cana-3796	302	12	with	with	ADP
cana-3796	302	13	ocr	ocr	PROPN
cana-3796	302	14	opens	open	VERB
cana-3796	302	15	new	new	ADJ
cana-3796	302	16	avenues	avenue	NOUN
cana-3796	302	17	for	for	ADP
cana-3796	302	18	developing	develop	VERB
cana-3796	302	19	sophisticated	sophisticated	ADJ
cana-3796	302	20	language	language	NOUN
cana-3796	302	21	processing	processing	NOUN
cana-3796	302	22	tools	tool	NOUN
cana-3796	302	23	for	for	ADP
cana-3796	302	24	indic	indic	ADJ
cana-3796	302	25	languages	language	NOUN
cana-3796	302	26	,	,	PUNCT
cana-3796	302	27	which	which	PRON
cana-3796	302	28	have	have	AUX
cana-3796	302	29	historically	historically	ADV
cana-3796	302	30	been	be	AUX
cana-3796	302	31	underrepresented	underrepresente	VERB
cana-3796	302	32	in	in	ADP
cana-3796	302	33	this	this	DET
cana-3796	302	34	field	field	NOUN
cana-3796	302	35	.	.	PUNCT
cana-3796	303	1	future	future	ADJ
cana-3796	303	2	scope	scope	NOUN
cana-3796	303	3	:	:	PUNCT
cana-3796	303	4	future	future	ADJ
cana-3796	303	5	research	research	NOUN
cana-3796	303	6	could	could	AUX
cana-3796	303	7	explore	explore	VERB
cana-3796	303	8	adapting	adapt	VERB
cana-3796	303	9	the	the	DET
cana-3796	303	10	model	model	NOUN
cana-3796	303	11	to	to	ADP
cana-3796	303	12	other	other	ADJ
cana-3796	303	13	indic	indic	ADJ
cana-3796	303	14	and	and	CCONJ
cana-3796	303	15	non	non	ADJ
cana-3796	303	16	-	-	ADJ
cana-3796	303	17	indic	indic	ADJ
cana-3796	303	18	languages	language	NOUN
cana-3796	303	19	with	with	ADP
cana-3796	303	20	complex	complex	ADJ
cana-3796	303	21	scripts	script	NOUN
cana-3796	303	22	and	and	CCONJ
cana-3796	303	23	diverse	diverse	ADJ
cana-3796	303	24	handwriting	handwriting	NOUN
cana-3796	303	25	styles	style	NOUN
cana-3796	303	26	.	.	PUNCT
cana-3796	304	1	real	real	ADJ
cana-3796	304	2	-	-	PUNCT
cana-3796	304	3	time	time	NOUN
cana-3796	304	4	ocr	ocr	ADJ
cana-3796	304	5	applications	application	NOUN
cana-3796	304	6	for	for	ADP
cana-3796	304	7	smartphones	smartphone	NOUN
cana-3796	304	8	and	and	CCONJ
cana-3796	304	9	tablets	tablet	NOUN
cana-3796	304	10	could	could	AUX
cana-3796	304	11	also	also	ADV
cana-3796	304	12	be	be	AUX
cana-3796	304	13	developed	develop	VERB
cana-3796	304	14	,	,	PUNCT
cana-3796	304	15	revolutionizing	revolutionize	VERB
cana-3796	304	16	the	the	DET
cana-3796	304	17	interaction	interaction	NOUN
cana-3796	304	18	with	with	ADP
cana-3796	304	19	handwritten	handwritten	ADJ
cana-3796	304	20	text	text	NOUN
cana-3796	304	21	.	.	PUNCT
cana-3796	305	1	integrating	integrate	VERB
cana-3796	305	2	the	the	DET
cana-3796	305	3	model	model	NOUN
cana-3796	305	4	into	into	ADP
cana-3796	305	5	educational	educational	ADJ
cana-3796	305	6	software	software	NOUN
cana-3796	305	7	could	could	AUX
cana-3796	305	8	automate	automate	VERB
cana-3796	305	9	feedback	feedback	NOUN
cana-3796	305	10	and	and	CCONJ
cana-3796	305	11	analysis	analysis	NOUN
cana-3796	305	12	of	of	ADP
cana-3796	305	13	handwritten	handwritten	ADJ
cana-3796	305	14	assignments	assignment	NOUN
cana-3796	305	15	.	.	PUNCT
cana-3796	306	1	additionally	additionally	ADV
cana-3796	306	2	,	,	PUNCT
cana-3796	306	3	enhancing	enhance	VERB
cana-3796	306	4	the	the	DET
cana-3796	306	5	model	model	NOUN
cana-3796	306	6	’s	’s	PART
cana-3796	306	7	nlp	nlp	ADJ
cana-3796	306	8	capabilities	capability	NOUN
cana-3796	306	9	in	in	ADP
cana-3796	306	10	semantic	semantic	ADJ
cana-3796	306	11	analysis	analysis	NOUN
cana-3796	306	12	and	and	CCONJ
cana-3796	306	13	context	context	NOUN
cana-3796	306	14	understanding	understanding	NOUN
cana-3796	306	15	could	could	AUX
cana-3796	306	16	improve	improve	VERB
cana-3796	306	17	its	its	PRON
cana-3796	306	18	effectiveness	effectiveness	NOUN
cana-3796	306	19	in	in	ADP
cana-3796	306	20	content	content	NOUN
cana-3796	306	21	analysis	analysis	NOUN
cana-3796	306	22	and	and	CCONJ
cana-3796	306	23	translation	translation	NOUN
cana-3796	306	24	.	.	PUNCT
cana-3796	307	1	vi	vi	PROPN
cana-3796	307	2	.	.	PROPN
cana-3796	307	3	references	reference	NOUN
cana-3796	307	4	[	[	X
cana-3796	307	5	1	1	NUM
cana-3796	307	6	]	]	SYM
cana-3796	307	7	yavariabdi	yavariabdi	PROPN
cana-3796	307	8	,	,	PUNCT
cana-3796	307	9	a.	a.	PROPN
cana-3796	307	10	,	,	PUNCT
cana-3796	307	11	h.	h.	PROPN
cana-3796	307	12	kusetogullari	kusetogullari	PROPN
cana-3796	307	13	,	,	PUNCT
cana-3796	307	14	t.	t.	NOUN
cana-3796	307	15	çelik	çelik	PROPN
cana-3796	307	16	,	,	PUNCT
cana-3796	307	17	s.	s.	PROPN
cana-3796	307	18	thummana	thummana	PROPN
cana-3796	307	19	-	-	PUNCT
cana-3796	307	20	pally	pally	PROPN
cana-3796	307	21	,	,	PUNCT
cana-3796	307	22	s.	s.	PROPN
cana-3796	307	23	rijwan	rijwan	PROPN
cana-3796	307	24	,	,	PUNCT
cana-3796	307	25	and	and	CCONJ
cana-3796	307	26	j.	j.	PROPN
cana-3796	307	27	hall	hall	PROPN
cana-3796	307	28	.	.	PUNCT
cana-3796	308	1	2022	2022	NUM
cana-3796	308	2	.	.	PUNCT
cana-3796	309	1	“	"	PUNCT
cana-3796	309	2	cardis	cardi	NOUN
cana-3796	309	3	:	:	PUNCT
cana-3796	309	4	a	a	DET
cana-3796	309	5	swedish	swedish	ADJ
cana-3796	309	6	historical	historical	ADJ
cana-3796	309	7	handwritten	handwritten	ADJ
cana-3796	309	8	character	character	NOUN
cana-3796	309	9	and	and	CCONJ
cana-3796	309	10	word	word	NOUN
cana-3796	309	11	dataset	dataset	VERB
cana-3796	309	12	.	.	PUNCT
cana-3796	309	13	”	"	PUNCT
cana-3796	310	1	ieee	ieee	NOUN
cana-3796	310	2	access	access	NOUN
cana-3796	310	3	pp:1–1	pp:1–1	VERB
cana-3796	310	4	.	.	PUNCT
cana-3796	311	1	[	[	X
cana-3796	311	2	2	2	NUM
cana-3796	311	3	]	]	PUNCT
cana-3796	311	4	rasheed	rasheed	NOUN
cana-3796	311	5	,	,	PUNCT
cana-3796	311	6	a.	a.	NOUN
cana-3796	311	7	,	,	PUNCT
cana-3796	311	8	n.	n.	PROPN
cana-3796	311	9	ali	ali	PROPN
cana-3796	311	10	,	,	PUNCT
cana-3796	311	11	b.	b.	PROPN
cana-3796	311	12	zafar	zafar	PROPN
cana-3796	311	13	,	,	PUNCT
cana-3796	311	14	a.	a.	PROPN
cana-3796	311	15	shabbir	shabbir	PROPN
cana-3796	311	16	,	,	PUNCT
cana-3796	311	17	m.	m.	PROPN
cana-3796	311	18	sajid	sajid	PROPN
cana-3796	311	19	,	,	PUNCT
cana-3796	311	20	and	and	CCONJ
cana-3796	311	21	m.t	m.t	PROPN
cana-3796	311	22	.	.	PROPN
cana-3796	311	23	mahmood	mahmood	PROPN
cana-3796	311	24	.	.	PUNCT
cana-3796	311	25	2022	2022	NUM
cana-3796	311	26	.	.	PUNCT
cana-3796	312	1	“	"	PUNCT
cana-3796	312	2	handwritten	handwritten	ADJ
cana-3796	312	3	urdu	urdu	NOUN
cana-3796	312	4	characters	character	NOUN
cana-3796	312	5	and	and	CCONJ
cana-3796	312	6	digits	digit	NOUN
cana-3796	312	7	recognition	recognition	NOUN
cana-3796	312	8	using	use	VERB
cana-3796	312	9	transfer	transfer	NOUN
cana-3796	312	10	learning	learning	NOUN
cana-3796	312	11	and	and	CCONJ
cana-3796	312	12	augmentation	augmentation	NOUN
cana-3796	312	13	with	with	ADP
cana-3796	312	14	alexnet	alexnet	NOUN
cana-3796	312	15	.	.	PUNCT
cana-3796	312	16	”	"	PUNCT
cana-3796	313	1	ieee	ieee	NOUN
cana-3796	313	2	access	access	NOUN
cana-3796	313	3	10:102629–45	10:102629–45	NOUN
cana-3796	313	4	.	.	PUNCT
cana-3796	314	1	[	[	X
cana-3796	314	2	3	3	NUM
cana-3796	314	3	]	]	PUNCT
cana-3796	314	4	buoy	buoy	NOUN
cana-3796	314	5	,	,	PUNCT
cana-3796	314	6	r.	r.	PROPN
cana-3796	314	7	,	,	PUNCT
cana-3796	314	8	m.	m.	NOUN
cana-3796	314	9	iwamura	iwamura	NOUN
cana-3796	314	10	,	,	PUNCT
cana-3796	314	11	s.	s.	PROPN
cana-3796	314	12	srun	srun	PROPN
cana-3796	314	13	,	,	PUNCT
cana-3796	314	14	and	and	CCONJ
cana-3796	314	15	k.	k.	PROPN
cana-3796	314	16	kise	kise	PROPN
cana-3796	314	17	.	.	PUNCT
cana-3796	315	1	2023	2023	NUM
cana-3796	315	2	.	.	PUNCT
cana-3796	316	1	“	"	PUNCT
cana-3796	316	2	toward	toward	ADP
cana-3796	316	3	a	a	DET
cana-3796	316	4	low	low	ADJ
cana-3796	316	5	-	-	PUNCT
cana-3796	316	6	resource	resource	NOUN
cana-3796	316	7	non	non	ADJ
cana-3796	316	8	-	-	ADJ
cana-3796	316	9	latin	latin	ADJ
cana-3796	316	10	-	-	PUNCT
cana-3796	316	11	complete	complete	ADJ
cana-3796	316	12	baseline	baseline	NOUN
cana-3796	316	13	:	:	PUNCT
cana-3796	316	14	an	an	DET
cana-3796	316	15	exploration	exploration	NOUN
cana-3796	316	16	of	of	ADP
cana-3796	316	17	khmer	khmer	PROPN
cana-3796	316	18	optical	optical	ADJ
cana-3796	316	19	character	character	NOUN
cana-3796	316	20	recognition	recognition	NOUN
cana-3796	316	21	.	.	PUNCT
cana-3796	316	22	”	"	PUNCT
cana-3796	316	23	ieee	ieee	NOUN
cana-3796	316	24	access	access	NOUN
cana-3796	316	25	11:128044–60	11:128044–60	NUM
cana-3796	316	26	.	.	PUNCT
cana-3796	317	1	communications	communication	NOUN
cana-3796	317	2	on	on	ADP
cana-3796	317	3	applied	apply	VERB
cana-3796	317	4	nonlinear	nonlinear	ADJ
cana-3796	317	5	analysis	analysis	NOUN
cana-3796	317	6	issn	issn	NOUN
cana-3796	317	7	:	:	PUNCT
cana-3796	317	8	1074	1074	NUM
cana-3796	317	9	-	-	PUNCT
cana-3796	317	10	133x	133x	NUM
cana-3796	317	11	vol	vol	NOUN
cana-3796	317	12	32	32	NUM
cana-3796	317	13	no	no	NOUN
cana-3796	317	14	.	.	PUNCT
cana-3796	318	1	8s	8s	PROPN
cana-3796	318	2	(	(	PUNCT
cana-3796	318	3	2025	2025	NUM
cana-3796	318	4	)	)	PUNCT
cana-3796	318	5	760	760	NUM
cana-3796	318	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	319	1	[	[	X
cana-3796	319	2	4	4	NUM
cana-3796	319	3	]	]	SYM
cana-3796	319	4	li	li	PROPN
cana-3796	319	5	,	,	PUNCT
cana-3796	319	6	m.	m.	NOUN
cana-3796	319	7	,	,	PUNCT
cana-3796	319	8	b.	b.	PROPN
cana-3796	319	9	fu	fu	PROPN
cana-3796	319	10	,	,	PUNCT
cana-3796	319	11	z.	z.	PROPN
cana-3796	319	12	zhang	zhang	PROPN
cana-3796	319	13	,	,	PUNCT
cana-3796	319	14	and	and	CCONJ
cana-3796	319	15	y.	y.	PROPN
cana-3796	319	16	qiao	qiao	PROPN
cana-3796	319	17	.	.	PUNCT
cana-3796	320	1	2023	2023	NUM
cana-3796	320	2	.	.	PUNCT
cana-3796	321	1	“	"	PUNCT
cana-3796	321	2	character	character	NOUN
cana-3796	321	3	-	-	PUNCT
cana-3796	321	4	aware	aware	ADJ
cana-3796	321	5	sampling	sampling	NOUN
cana-3796	321	6	and	and	CCONJ
cana-3796	321	7	rectification	rectification	NOUN
cana-3796	321	8	for	for	ADP
cana-3796	321	9	scene	scene	NOUN
cana-3796	321	10	text	text	NOUN
cana-3796	321	11	recognition	recognition	NOUN
cana-3796	321	12	.	.	PUNCT
cana-3796	321	13	”	"	PUNCT
cana-3796	322	1	ieee	ieee	NOUN
cana-3796	322	2	transactions	transaction	NOUN
cana-3796	322	3	on	on	ADP
cana-3796	322	4	multimedia	multimedia	NOUN
cana-3796	322	5	25:649–61	25:649–61	NOUN
cana-3796	322	6	.	.	PUNCT
cana-3796	323	1	https://doi.org/10.1109/tmm.2021.3129651	https://doi.org/10.1109/tmm.2021.3129651	NOUN
cana-3796	323	2	.	.	PUNCT
cana-3796	324	1	[	[	X
cana-3796	324	2	5	5	NUM
cana-3796	324	3	]	]	SYM
cana-3796	324	4	zhang	zhang	PROPN
cana-3796	324	5	,	,	PUNCT
cana-3796	324	6	c.	c.	PROPN
cana-3796	324	7	,	,	PUNCT
cana-3796	324	8	et	et	PROPN
cana-3796	324	9	al	al	PROPN
cana-3796	324	10	.	.	PROPN
cana-3796	324	11	2023	2023	NUM
cana-3796	324	12	.	.	PUNCT
cana-3796	325	1	“	"	PUNCT
cana-3796	325	2	a	a	DET
cana-3796	325	3	machine	machine	NOUN
cana-3796	325	4	vision	vision	NOUN
cana-3796	325	5	-	-	PUNCT
cana-3796	325	6	based	base	VERB
cana-3796	325	7	character	character	NOUN
cana-3796	325	8	recognition	recognition	NOUN
cana-3796	325	9	system	system	NOUN
cana-3796	325	10	for	for	ADP
cana-3796	325	11	suspension	suspension	NOUN
cana-3796	325	12	insulator	insulator	NOUN
cana-3796	325	13	iron	iron	NOUN
cana-3796	325	14	caps	cap	NOUN
cana-3796	325	15	.	.	PUNCT
cana-3796	325	16	”	"	PUNCT
cana-3796	326	1	ieee	ieee	NOUN
cana-3796	326	2	transactions	transaction	NOUN
cana-3796	326	3	on	on	ADP
cana-3796	326	4	instrumentation	instrumentation	NOUN
cana-3796	326	5	and	and	CCONJ
cana-3796	326	6	measurement	measurement	NOUN
cana-3796	326	7	72:1–13	72:1–13	NUM
cana-3796	326	8	.	.	PUNCT
cana-3796	327	1	https://doi.org/10.1109/tim.2023.3300474	https://doi.org/10.1109/tim.2023.3300474	NOUN
cana-3796	327	2	.	.	PUNCT
cana-3796	328	1	[	[	X
cana-3796	328	2	6	6	NUM
cana-3796	328	3	]	]	X
cana-3796	328	4	wang	wang	PROPN
cana-3796	328	5	,	,	PUNCT
cana-3796	328	6	x.	x.	PROPN
cana-3796	328	7	,	,	PUNCT
cana-3796	328	8	et	et	PROPN
cana-3796	328	9	al	al	PROPN
cana-3796	328	10	.	.	PROPN
cana-3796	328	11	2022	2022	NUM
cana-3796	328	12	.	.	PUNCT
cana-3796	329	1	“	"	PUNCT
cana-3796	329	2	intelligent	intelligent	ADJ
cana-3796	329	3	micron	micron	NOUN
cana-3796	329	4	optical	optical	ADJ
cana-3796	329	5	character	character	NOUN
cana-3796	329	6	recognition	recognition	NOUN
cana-3796	329	7	of	of	ADP
cana-3796	329	8	dfb	dfb	PROPN
cana-3796	329	9	chip	chip	NOUN
cana-3796	329	10	using	use	VERB
cana-3796	329	11	deep	deep	ADJ
cana-3796	329	12	convolutional	convolutional	ADJ
cana-3796	329	13	neural	neural	ADJ
cana-3796	329	14	network	network	NOUN
cana-3796	329	15	.	.	PUNCT
cana-3796	329	16	”	"	PUNCT
cana-3796	330	1	ieee	ieee	NOUN
cana-3796	330	2	transactions	transaction	NOUN
cana-3796	330	3	on	on	ADP
cana-3796	330	4	instrumentation	instrumentation	NOUN
cana-3796	330	5	and	and	CCONJ
cana-3796	330	6	measurement	measurement	NOUN
cana-3796	330	7	71:1–9	71:1–9	NOUN
cana-3796	330	8	.	.	PUNCT
cana-3796	331	1	https://doi.org/10.1109/tim.2022.3154831	https://doi.org/10.1109/tim.2022.3154831	PROPN
cana-3796	331	2	.	.	PUNCT
cana-3796	332	1	[	[	X
cana-3796	332	2	7	7	NUM
cana-3796	332	3	]	]	X
cana-3796	332	4	coquenet	coquenet	PROPN
cana-3796	332	5	,	,	PUNCT
cana-3796	332	6	d.	d.	PROPN
cana-3796	332	7	,	,	PUNCT
cana-3796	332	8	c.	c.	PROPN
cana-3796	332	9	chatelain	chatelain	PROPN
cana-3796	332	10	,	,	PUNCT
cana-3796	332	11	and	and	CCONJ
cana-3796	332	12	t.	t.	PROPN
cana-3796	332	13	paquet	paquet	PROPN
cana-3796	332	14	.	.	PROPN
cana-3796	332	15	2023	2023	NUM
cana-3796	332	16	.	.	PUNCT
cana-3796	333	1	“	"	PUNCT
cana-3796	333	2	end	end	VERB
cana-3796	333	3	-	-	PUNCT
cana-3796	333	4	to	to	ADP
cana-3796	333	5	-	-	PUNCT
cana-3796	333	6	end	end	NOUN
cana-3796	333	7	handwritten	handwritten	ADJ
cana-3796	333	8	paragraph	paragraph	NOUN
cana-3796	333	9	text	text	NOUN
cana-3796	333	10	recognition	recognition	NOUN
cana-3796	333	11	using	use	VERB
cana-3796	333	12	a	a	DET
cana-3796	333	13	vertical	vertical	ADJ
cana-3796	333	14	attention	attention	NOUN
cana-3796	333	15	network	network	NOUN
cana-3796	333	16	.	.	PUNCT
cana-3796	333	17	”	"	PUNCT
cana-3796	334	1	ieee	ieee	NOUN
cana-3796	334	2	transactions	transaction	NOUN
cana-3796	334	3	on	on	ADP
cana-3796	334	4	pattern	pattern	NOUN
cana-3796	334	5	analysis	analysis	NOUN
cana-3796	334	6	and	and	CCONJ
cana-3796	334	7	machine	machine	NOUN
cana-3796	334	8	intelligence	intelligence	NOUN
cana-3796	334	9	45	45	NUM
cana-3796	334	10	(	(	PUNCT
cana-3796	334	11	1):508–24	1):508–24	PROPN
cana-3796	334	12	.	.	PUNCT
cana-3796	335	1	https://doi.org/10.1109/tpami.2022.3144899	https://doi.org/10.1109/tpami.2022.3144899	PROPN
cana-3796	335	2	.	.	PUNCT
cana-3796	336	1	[	[	X
cana-3796	336	2	8	8	NUM
cana-3796	336	3	]	]	SYM
cana-3796	336	4	wu	wu	PROPN
cana-3796	336	5	,	,	PUNCT
cana-3796	336	6	l.	l.	PROPN
cana-3796	336	7	,	,	PUNCT
cana-3796	336	8	y.	y.	PROPN
cana-3796	336	9	xu	xu	PROPN
cana-3796	336	10	,	,	PUNCT
cana-3796	336	11	j.	j.	PROPN
cana-3796	336	12	hou	hou	PROPN
cana-3796	336	13	,	,	PUNCT
cana-3796	336	14	c.	c.	PROPN
cana-3796	336	15	l.	l.	PROPN
cana-3796	336	16	p.	p.	PROPN
cana-3796	336	17	chen	chen	PROPN
cana-3796	336	18	,	,	PUNCT
cana-3796	336	19	and	and	CCONJ
cana-3796	336	20	c.-l	c.-l	PROPN
cana-3796	336	21	.	.	PUNCT
cana-3796	337	1	liu	liu	PROPN
cana-3796	337	2	.	.	PROPN
cana-3796	337	3	2023	2023	NUM
cana-3796	337	4	.	.	PUNCT
cana-3796	338	1	“	"	PUNCT
cana-3796	338	2	a	a	DET
cana-3796	338	3	two	two	NUM
cana-3796	338	4	-	-	PUNCT
cana-3796	338	5	level	level	NOUN
cana-3796	338	6	rectification	rectification	NOUN
cana-3796	338	7	attention	attention	NOUN
cana-3796	338	8	network	network	NOUN
cana-3796	338	9	for	for	ADP
cana-3796	338	10	scene	scene	NOUN
cana-3796	338	11	text	text	NOUN
cana-3796	338	12	recognition	recognition	NOUN
cana-3796	338	13	.	.	PUNCT
cana-3796	338	14	”	"	PUNCT
cana-3796	339	1	ieee	ieee	NOUN
cana-3796	339	2	transactions	transaction	NOUN
cana-3796	339	3	on	on	ADP
cana-3796	339	4	multimedia	multimedia	NOUN
cana-3796	339	5	25:2404–14	25:2404–14	NOUN
cana-3796	339	6	.	.	PUNCT
cana-3796	340	1	https://doi.org/10.1109/tmm.2022.3146779	https://doi.org/10.1109/tmm.2022.3146779	PROPN
cana-3796	340	2	.	.	PUNCT
cana-3796	341	1	[	[	X
cana-3796	341	2	9	9	NUM
cana-3796	341	3	]	]	SYM
cana-3796	341	4	deng	deng	PROPN
cana-3796	341	5	,	,	PUNCT
cana-3796	341	6	x.	x.	PROPN
cana-3796	341	7	,	,	PUNCT
cana-3796	341	8	x.	x.	PROPN
cana-3796	341	9	chen	chen	PROPN
cana-3796	341	10	,	,	PUNCT
cana-3796	341	11	d.	d.	PROPN
cana-3796	341	12	cao	cao	PROPN
cana-3796	341	13	,	,	PUNCT
cana-3796	341	14	k.	k.	PROPN
cana-3796	341	15	ren	ren	PROPN
cana-3796	341	16	,	,	PUNCT
cana-3796	341	17	and	and	CCONJ
cana-3796	341	18	p.z.h	p.z.h	NOUN
cana-3796	341	19	.	.	PUNCT
cana-3796	342	1	sun	sun	PROPN
cana-3796	342	2	.	.	PUNCT
cana-3796	342	3	2024	2024	NUM
cana-3796	342	4	.	.	PUNCT
cana-3796	343	1	“	"	PUNCT
cana-3796	343	2	an	an	DET
cana-3796	343	3	end	end	NOUN
cana-3796	343	4	-	-	PUNCT
cana-3796	343	5	to	to	ADP
cana-3796	343	6	-	-	PUNCT
cana-3796	343	7	end	end	NOUN
cana-3796	343	8	tag	tag	NOUN
cana-3796	343	9	recognition	recognition	NOUN
cana-3796	343	10	architecture	architecture	NOUN
cana-3796	343	11	for	for	ADP
cana-3796	343	12	industrial	industrial	ADJ
cana-3796	343	13	meter	meter	NOUN
cana-3796	343	14	.	.	PUNCT
cana-3796	343	15	”	"	PUNCT
cana-3796	344	1	ieee	ieee	NOUN
cana-3796	344	2	transactions	transaction	NOUN
cana-3796	344	3	on	on	ADP
cana-3796	344	4	industrial	industrial	ADJ
cana-3796	344	5	informatics	informatic	NOUN
cana-3796	344	6	20	20	NUM
cana-3796	344	7	(	(	PUNCT
cana-3796	344	8	1):117–26	1):117–26	NUM
cana-3796	344	9	.	.	PUNCT
cana-3796	345	1	https://doi.org/10.1109/tii.2023.3257295	https://doi.org/10.1109/tii.2023.3257295	PROPN
cana-3796	345	2	.	.	PUNCT
cana-3796	346	1	[	[	X
cana-3796	346	2	10	10	NUM
cana-3796	346	3	]	]	X
cana-3796	346	4	r.	r.	PROPN
cana-3796	346	5	d.	d.	PROPN
cana-3796	346	6	r.	r.	PROPN
cana-3796	346	7	,	,	PUNCT
cana-3796	346	8	et	et	PROPN
cana-3796	346	9	al	al	PROPN
cana-3796	346	10	.	.	PROPN
cana-3796	346	11	2023	2023	NUM
cana-3796	346	12	.	.	PUNCT
cana-3796	347	1	“	"	PUNCT
cana-3796	347	2	self	self	NOUN
cana-3796	347	3	-	-	PUNCT
cana-3796	347	4	adaptive	adaptive	ADJ
cana-3796	347	5	hybridized	hybridize	VERB
cana-3796	347	6	lion	lion	NOUN
cana-3796	347	7	optimization	optimization	NOUN
cana-3796	347	8	algorithm	algorithm	NOUN
cana-3796	347	9	with	with	ADP
cana-3796	347	10	transfer	transfer	NOUN
cana-3796	347	11	learning	learning	NOUN
cana-3796	347	12	for	for	ADP
cana-3796	347	13	ancient	ancient	ADJ
cana-3796	347	14	tamil	tamil	PROPN
cana-3796	347	15	character	character	NOUN
cana-3796	347	16	recognition	recognition	NOUN
cana-3796	347	17	in	in	ADP
cana-3796	347	18	stone	stone	NOUN
cana-3796	347	19	inscriptions	inscription	NOUN
cana-3796	347	20	.	.	PUNCT
cana-3796	347	21	”	"	PUNCT
cana-3796	348	1	ieee	ieee	NOUN
cana-3796	348	2	access	access	NOUN
cana-3796	348	3	11:39621–34	11:39621–34	NOUN
cana-3796	348	4	.	.	PUNCT
cana-3796	349	1	https://doi.org/10.1109/access.2023.3268545	https://doi.org/10.1109/access.2023.3268545	X
cana-3796	349	2	.	.	PUNCT
cana-3796	350	1	[	[	X
cana-3796	350	2	11	11	NUM
cana-3796	350	3	]	]	X
cana-3796	350	4	xue	xue	PROPN
cana-3796	350	5	,	,	PUNCT
cana-3796	350	6	c.	c.	PROPN
cana-3796	350	7	,	,	PUNCT
cana-3796	350	8	j.	j.	PROPN
cana-3796	350	9	huang	huang	PROPN
cana-3796	350	10	,	,	PUNCT
cana-3796	350	11	w.	w.	PROPN
cana-3796	350	12	zhang	zhang	PROPN
cana-3796	350	13	,	,	PUNCT
cana-3796	350	14	s.	s.	PROPN
cana-3796	350	15	lu	lu	PROPN
cana-3796	350	16	,	,	PUNCT
cana-3796	350	17	c.	c.	PROPN
cana-3796	350	18	wang	wang	PROPN
cana-3796	350	19	,	,	PUNCT
cana-3796	350	20	and	and	CCONJ
cana-3796	350	21	s.	s.	PROPN
cana-3796	350	22	bai	bai	PROPN
cana-3796	350	23	.	.	PROPN
cana-3796	350	24	2023	2023	NUM
cana-3796	350	25	.	.	PUNCT
cana-3796	351	1	“	"	PUNCT
cana-3796	351	2	image	image	NOUN
cana-3796	351	3	-	-	PUNCT
cana-3796	351	4	to	to	ADP
cana-3796	351	5	-	-	PUNCT
cana-3796	351	6	character	character	NOUN
cana-3796	351	7	-	-	PUNCT
cana-3796	351	8	to	to	ADP
cana-3796	351	9	-	-	PUNCT
cana-3796	351	10	word	word	NOUN
cana-3796	351	11	transformers	transformer	NOUN
cana-3796	351	12	for	for	ADP
cana-3796	351	13	accurate	accurate	ADJ
cana-3796	351	14	scene	scene	NOUN
cana-3796	351	15	text	text	NOUN
cana-3796	351	16	recognition	recognition	NOUN
cana-3796	351	17	.	.	PUNCT
cana-3796	351	18	”	"	PUNCT
cana-3796	352	1	ieee	ieee	NOUN
cana-3796	352	2	transactions	transaction	NOUN
cana-3796	352	3	on	on	ADP
cana-3796	352	4	pattern	pattern	NOUN
cana-3796	352	5	analysis	analysis	NOUN
cana-3796	352	6	and	and	CCONJ
cana-3796	352	7	machine	machine	NOUN
cana-3796	352	8	intelligence	intelligence	NOUN
cana-3796	352	9	45	45	NUM
cana-3796	352	10	(	(	PUNCT
cana-3796	352	11	11):12908–21	11):12908–21	NUM
cana-3796	352	12	.	.	PUNCT
cana-3796	353	1	https://doi.org/10.1109/tpami.2022.3230962	https://doi.org/10.1109/tpami.2022.3230962	PROPN
cana-3796	353	2	.	.	PUNCT
cana-3796	354	1	[	[	X
cana-3796	354	2	12	12	NUM
cana-3796	354	3	]	]	X
cana-3796	354	4	hussain	hussain	PROPN
cana-3796	354	5	,	,	PUNCT
cana-3796	354	6	i.	i.	PROPN
cana-3796	354	7	,	,	PUNCT
cana-3796	354	8	r.	r.	PROPN
cana-3796	354	9	ahmad	ahmad	PROPN
cana-3796	354	10	,	,	PUNCT
cana-3796	354	11	s.	s.	PROPN
cana-3796	354	12	muhammad	muhammad	PROPN
cana-3796	354	13	,	,	PUNCT
cana-3796	354	14	k.	k.	PROPN
cana-3796	354	15	ullah	ullah	PROPN
cana-3796	354	16	,	,	PUNCT
cana-3796	354	17	h.	h.	PROPN
cana-3796	354	18	shah	shah	PROPN
cana-3796	354	19	,	,	PUNCT
cana-3796	354	20	and	and	CCONJ
cana-3796	354	21	a.	a.	NOUN
cana-3796	354	22	namoun	namoun	PROPN
cana-3796	354	23	.	.	PUNCT
cana-3796	355	1	2022	2022	NUM
cana-3796	355	2	.	.	PUNCT
cana-3796	356	1	“	"	PUNCT
cana-3796	356	2	phti	phti	NOUN
cana-3796	356	3	:	:	PUNCT
cana-3796	356	4	pashto	pashto	VERB
cana-3796	356	5	handwritten	handwritten	ADJ
cana-3796	356	6	text	text	NOUN
cana-3796	356	7	imagebase	imagebase	NOUN
cana-3796	356	8	for	for	ADP
cana-3796	356	9	deep	deep	ADJ
cana-3796	356	10	learning	learning	NOUN
cana-3796	356	11	applications	application	NOUN
cana-3796	356	12	.	.	PUNCT
cana-3796	356	13	”	"	PUNCT
cana-3796	357	1	ieee	ieee	NOUN
cana-3796	357	2	access	access	NOUN
cana-3796	357	3	10:113149–57	10:113149–57	NUM
cana-3796	357	4	.	.	PUNCT
cana-3796	358	1	https://doi.org/10.1109/access.2022.3216881	https://doi.org/10.1109/access.2022.3216881	X
cana-3796	358	2	.	.	PUNCT
cana-3796	359	1	[	[	X
cana-3796	359	2	13	13	NUM
cana-3796	359	3	]	]	SYM
cana-3796	359	4	ott	ott	PROPN
cana-3796	359	5	,	,	PUNCT
cana-3796	359	6	f.	f.	PROPN
cana-3796	359	7	,	,	PUNCT
cana-3796	359	8	d.	d.	PROPN
cana-3796	359	9	rügamer	rügamer	PROPN
cana-3796	359	10	,	,	PUNCT
cana-3796	359	11	l.	l.	PROPN
cana-3796	359	12	heublein	heublein	PROPN
cana-3796	359	13	,	,	PUNCT
cana-3796	359	14	b.	b.	PROPN
cana-3796	359	15	bischl	bischl	PROPN
cana-3796	359	16	,	,	PUNCT
cana-3796	359	17	and	and	CCONJ
cana-3796	359	18	c.	c.	PROPN
cana-3796	359	19	mutschler	mutschler	NOUN
cana-3796	359	20	.	.	PUNCT
cana-3796	360	1	2023	2023	NUM
cana-3796	360	2	.	.	PUNCT
cana-3796	361	1	“	"	PUNCT
cana-3796	361	2	auxiliary	auxiliary	ADJ
cana-3796	361	3	cross	cross	ADJ
cana-3796	361	4	-	-	ADJ
cana-3796	361	5	modal	modal	ADJ
cana-3796	361	6	representation	representation	NOUN
cana-3796	361	7	learning	learn	VERB
cana-3796	361	8	with	with	ADP
cana-3796	361	9	triplet	triplet	NOUN
cana-3796	361	10	loss	loss	NOUN
cana-3796	361	11	functions	function	NOUN
cana-3796	361	12	for	for	ADP
cana-3796	361	13	online	online	ADJ
cana-3796	361	14	handwriting	handwriting	NOUN
cana-3796	361	15	recognition	recognition	NOUN
cana-3796	361	16	.	.	PUNCT
cana-3796	361	17	”	"	PUNCT
cana-3796	362	1	ieee	ieee	NOUN
cana-3796	362	2	access	access	NOUN
cana-3796	362	3	11:94148–72	11:94148–72	NUM
cana-3796	362	4	.	.	PUNCT
cana-3796	363	1	https://doi.org/10.1109/access.2023.3310819	https://doi.org/10.1109/access.2023.3310819	PROPN
cana-3796	363	2	.	.	PUNCT
cana-3796	364	1	[	[	X
cana-3796	364	2	14	14	NUM
cana-3796	364	3	]	]	X
cana-3796	364	4	selvam	selvam	ADJ
cana-3796	364	5	,	,	PUNCT
cana-3796	364	6	p.	p.	PROPN
cana-3796	364	7	,	,	PUNCT
cana-3796	364	8	et	et	PROPN
cana-3796	364	9	al	al	PROPN
cana-3796	364	10	.	.	PROPN
cana-3796	364	11	2022	2022	NUM
cana-3796	364	12	.	.	PUNCT
cana-3796	365	1	“	"	PUNCT
cana-3796	365	2	a	a	DET
cana-3796	365	3	transformer	transformer	NOUN
cana-3796	365	4	-	-	PUNCT
cana-3796	365	5	based	base	VERB
cana-3796	365	6	framework	framework	NOUN
cana-3796	365	7	for	for	ADP
cana-3796	365	8	scene	scene	NOUN
cana-3796	365	9	text	text	NOUN
cana-3796	365	10	recognition	recognition	NOUN
cana-3796	365	11	.	.	PUNCT
cana-3796	365	12	”	"	PUNCT
cana-3796	366	1	ieee	ieee	NOUN
cana-3796	366	2	access	access	NOUN
cana-3796	366	3	10:100895–910	10:100895–910	PROPN
cana-3796	366	4	.	.	PUNCT
cana-3796	367	1	https://doi.org/10.1109/access.2022.3207469	https://doi.org/10.1109/access.2022.3207469	PROPN
cana-3796	367	2	.	.	PUNCT
cana-3796	368	1	[	[	X
cana-3796	368	2	15	15	NUM
cana-3796	368	3	]	]	X
cana-3796	368	4	fan	fan	NOUN
cana-3796	368	5	,	,	PUNCT
cana-3796	368	6	x.	x.	NOUN
cana-3796	368	7	,	,	PUNCT
cana-3796	368	8	and	and	CCONJ
cana-3796	368	9	w.	w.	PROPN
cana-3796	368	10	zhao	zhao	PROPN
cana-3796	368	11	.	.	PUNCT
cana-3796	368	12	2022	2022	NUM
cana-3796	368	13	.	.	PUNCT
cana-3796	369	1	“	"	PUNCT
cana-3796	369	2	improving	improve	VERB
cana-3796	369	3	robustness	robustness	NOUN
cana-3796	369	4	of	of	ADP
cana-3796	369	5	license	license	NOUN
cana-3796	369	6	plates	plate	NOUN
cana-3796	369	7	automatic	automatic	ADJ
cana-3796	369	8	recognition	recognition	NOUN
cana-3796	369	9	in	in	ADP
cana-3796	369	10	natural	natural	ADJ
cana-3796	369	11	scenes	scene	NOUN
cana-3796	369	12	.	.	PUNCT
cana-3796	369	13	”	"	PUNCT
cana-3796	370	1	ieee	ieee	NOUN
cana-3796	370	2	transactions	transaction	NOUN
cana-3796	370	3	on	on	ADP
cana-3796	370	4	intelligent	intelligent	ADJ
cana-3796	370	5	transportation	transportation	NOUN
cana-3796	370	6	systems	system	NOUN
cana-3796	370	7	23	23	NUM
cana-3796	370	8	(	(	PUNCT
cana-3796	370	9	10):18845–54	10):18845–54	NUM
cana-3796	370	10	.	.	PUNCT
cana-3796	371	1	https://doi.org/10.1109/tits.2022.3151475	https://doi.org/10.1109/tits.2022.3151475	PROPN
cana-3796	371	2	[	[	X
cana-3796	371	3	16	16	NUM
cana-3796	371	4	]	]	PUNCT
cana-3796	371	5	tayyab	tayyab	PROPN
cana-3796	371	6	,	,	PUNCT
cana-3796	371	7	m.	m.	NOUN
cana-3796	371	8	,	,	PUNCT
cana-3796	371	9	a.	a.	NOUN
cana-3796	371	10	hussain	hussain	PROPN
cana-3796	371	11	,	,	PUNCT
cana-3796	371	12	m.a	m.a	PROPN
cana-3796	371	13	.	.	PROPN
cana-3796	371	14	alshara	alshara	PROPN
cana-3796	371	15	,	,	PUNCT
cana-3796	371	16	s.	s.	PROPN
cana-3796	371	17	khan	khan	PROPN
cana-3796	371	18	,	,	PUNCT
cana-3796	371	19	r.m	r.m	PROPN
cana-3796	371	20	.	.	PROPN
cana-3796	371	21	alotaibi	alotaibi	PROPN
cana-3796	371	22	,	,	PUNCT
cana-3796	371	23	and	and	CCONJ
cana-3796	371	24	a.r	a.r	PROPN
cana-3796	371	25	.	.	PROPN
cana-3796	371	26	baig	baig	PROPN
cana-3796	371	27	.	.	PUNCT
cana-3796	371	28	2022	2022	NUM
cana-3796	371	29	.	.	PUNCT
cana-3796	372	1	“	"	PUNCT
cana-3796	372	2	recognition	recognition	NOUN
cana-3796	372	3	of	of	ADP
cana-3796	372	4	visual	visual	ADJ
cana-3796	372	5	arabic	arabic	ADJ
cana-3796	372	6	scripting	scripting	PROPN
cana-3796	372	7	news	news	PROPN
cana-3796	372	8	ticker	ticker	PROPN
cana-3796	372	9	from	from	ADP
cana-3796	372	10	broadcast	broadcast	NOUN
cana-3796	372	11	stream	stream	NOUN
cana-3796	372	12	.	.	PUNCT
cana-3796	372	13	”	"	PUNCT
cana-3796	372	14	ieee	ieee	NOUN
cana-3796	372	15	access	access	NOUN
cana-3796	372	16	10:59189–204	10:59189–204	PROPN
cana-3796	372	17	.	.	PUNCT
cana-3796	373	1	https://doi.org/10.1109/access.2022.3179366	https://doi.org/10.1109/access.2022.3179366	PROPN
cana-3796	373	2	.	.	PUNCT
cana-3796	374	1	[	[	X
cana-3796	374	2	17	17	NUM
cana-3796	374	3	]	]	X
cana-3796	374	4	malhotra	malhotra	PROPN
cana-3796	374	5	,	,	PUNCT
cana-3796	374	6	r.	r.	PROPN
cana-3796	374	7	,	,	PUNCT
cana-3796	374	8	and	and	CCONJ
cana-3796	374	9	m.t	m.t	PROPN
cana-3796	374	10	.	.	PROPN
cana-3796	374	11	addis	addis	PROPN
cana-3796	374	12	.	.	PUNCT
cana-3796	374	13	2023	2023	NUM
cana-3796	374	14	.	.	PUNCT
cana-3796	375	1	“	"	PUNCT
cana-3796	375	2	end	end	VERB
cana-3796	375	3	-	-	PUNCT
cana-3796	375	4	to	to	ADP
cana-3796	375	5	-	-	PUNCT
cana-3796	375	6	end	end	NOUN
cana-3796	375	7	historical	historical	ADJ
cana-3796	375	8	handwritten	handwritten	ADJ
cana-3796	375	9	ethiopic	ethiopic	ADJ
cana-3796	375	10	text	text	NOUN
cana-3796	375	11	recognition	recognition	NOUN
cana-3796	375	12	using	use	VERB
cana-3796	375	13	deep	deep	ADJ
cana-3796	375	14	learning	learning	NOUN
cana-3796	375	15	.	.	PUNCT
cana-3796	375	16	”	"	PUNCT
cana-3796	376	1	ieee	ieee	NOUN
cana-3796	376	2	access	access	NOUN
cana-3796	376	3	11:99535–45	11:99535–45	NUM
cana-3796	376	4	.	.	PUNCT
cana-3796	377	1	https://doi.org/10.1109/access.2023.3314334	https://doi.org/10.1109/access.2023.3314334	PROPN
cana-3796	377	2	.	.	PUNCT
cana-3796	378	1	[	[	X
cana-3796	378	2	18	18	NUM
cana-3796	378	3	]	]	X
cana-3796	378	4	fanjie	fanjie	PROPN
cana-3796	378	5	,	,	PUNCT
cana-3796	378	6	k.	k.	PROPN
cana-3796	378	7	,	,	PUNCT
cana-3796	378	8	l.	l.	PROPN
cana-3796	378	9	yaqi	yaqi	PROPN
cana-3796	378	10	,	,	PUNCT
cana-3796	378	11	x.	x.	NOUN
cana-3796	378	12	miaomiao	miaomiao	PROPN
cana-3796	378	13	,	,	PUNCT
cana-3796	378	14	w.	w.	PROPN
cana-3796	378	15	silamu	silamu	PROPN
cana-3796	378	16	,	,	PUNCT
cana-3796	378	17	and	and	CCONJ
cana-3796	378	18	l.	l.	PROPN
cana-3796	378	19	yanbing	yanbing	PROPN
cana-3796	378	20	.	.	PUNCT
cana-3796	379	1	2023	2023	NUM
cana-3796	379	2	.	.	PUNCT
cana-3796	380	1	“	"	PUNCT
cana-3796	380	2	sust	sust	VERB
cana-3796	380	3	and	and	CCONJ
cana-3796	380	4	rust	rust	NOUN
cana-3796	380	5	:	:	PUNCT
cana-3796	380	6	two	two	NUM
cana-3796	380	7	datasets	dataset	NOUN
cana-3796	380	8	for	for	ADP
cana-3796	380	9	uyghur	uyghur	ADJ
cana-3796	380	10	scene	scene	NOUN
cana-3796	380	11	text	text	NOUN
cana-3796	380	12	recognition	recognition	NOUN
cana-3796	380	13	.	.	PUNCT
cana-3796	380	14	”	"	PUNCT
cana-3796	381	1	ieee	ieee	NOUN
cana-3796	381	2	access	access	NOUN
cana-3796	381	3	11:126209–20	11:126209–20	NUM
cana-3796	381	4	.	.	PUNCT
cana-3796	382	1	https://doi.org/10.1109/access.2023.3331213	https://doi.org/10.1109/access.2023.3331213	PROPN
cana-3796	382	2	.	.	PUNCT
cana-3796	383	1	[	[	X
cana-3796	383	2	19	19	NUM
cana-3796	383	3	]	]	X
cana-3796	383	4	zhu	zhu	PROPN
cana-3796	383	5	,	,	PUNCT
cana-3796	383	6	d.	d.	PROPN
cana-3796	383	7	,	,	PUNCT
cana-3796	383	8	y.	y.	PROPN
cana-3796	383	9	fang	fang	PROPN
cana-3796	383	10	,	,	PUNCT
cana-3796	383	11	z.	z.	PROPN
cana-3796	383	12	min	min	PROPN
cana-3796	383	13	,	,	PUNCT
cana-3796	383	14	d.	d.	PROPN
cana-3796	383	15	ho	ho	PROPN
cana-3796	383	16	,	,	PUNCT
cana-3796	383	17	and	and	CCONJ
cana-3796	383	18	m.q	m.q	NOUN
cana-3796	383	19	.	.	PROPN
cana-3796	383	20	-h	-h	PUNCT
cana-3796	383	21	.	.	PUNCT
cana-3796	384	1	meng	meng	PROPN
cana-3796	384	2	.	.	PUNCT
cana-3796	384	3	2022	2022	NUM
cana-3796	384	4	.	.	PUNCT
cana-3796	385	1	“	"	PUNCT
cana-3796	385	2	ocr	ocr	PROPN
cana-3796	385	3	-	-	PUNCT
cana-3796	385	4	rcnn	rcnn	PROPN
cana-3796	385	5	:	:	PUNCT
cana-3796	385	6	an	an	DET
cana-3796	385	7	accurate	accurate	ADJ
cana-3796	385	8	and	and	CCONJ
cana-3796	385	9	efficient	efficient	ADJ
cana-3796	385	10	framework	framework	NOUN
cana-3796	385	11	for	for	ADP
cana-3796	385	12	elevator	elevator	NOUN
cana-3796	385	13	button	button	NOUN
cana-3796	385	14	recognition	recognition	NOUN
cana-3796	385	15	.	.	PUNCT
cana-3796	385	16	”	"	PUNCT
cana-3796	386	1	ieee	ieee	NOUN
cana-3796	386	2	transactions	transaction	NOUN
cana-3796	386	3	on	on	ADP
cana-3796	386	4	industrial	industrial	ADJ
cana-3796	386	5	electronics	electronic	NOUN
cana-3796	386	6	69	69	NUM
cana-3796	386	7	(	(	PUNCT
cana-3796	386	8	1):582	1):582	NUM
cana-3796	386	9	–	–	PUNCT
cana-3796	386	10	91	91	NUM
cana-3796	386	11	.	.	PUNCT
cana-3796	387	1	https://doi.org/10.1109/tie.2021.3050357	https://doi.org/10.1109/tie.2021.3050357	NOUN
cana-3796	387	2	.	.	PUNCT
cana-3796	388	1	[	[	X
cana-3796	388	2	20	20	NUM
cana-3796	388	3	]	]	PUNCT
cana-3796	388	4	anbukkarasi	anbukkarasi	NOUN
cana-3796	388	5	,	,	PUNCT
cana-3796	388	6	s.	s.	PROPN
cana-3796	388	7	,	,	PUNCT
cana-3796	388	8	v.e	v.e	PROPN
cana-3796	388	9	.	.	PROPN
cana-3796	388	10	sathishkumar	sathishkumar	PROPN
cana-3796	388	11	,	,	PUNCT
cana-3796	388	12	c.r	c.r	PROPN
cana-3796	388	13	.	.	PROPN
cana-3796	388	14	dhivyaa	dhivyaa	NOUN
cana-3796	388	15	,	,	PUNCT
cana-3796	388	16	and	and	CCONJ
cana-3796	388	17	j.	j.	PROPN
cana-3796	388	18	cho	cho	PROPN
cana-3796	388	19	.	.	PUNCT
cana-3796	389	1	2023	2023	NUM
cana-3796	389	2	.	.	PUNCT
cana-3796	390	1	“	"	PUNCT
cana-3796	390	2	enhanced	enhance	VERB
cana-3796	390	3	feature	feature	NOUN
cana-3796	390	4	model	model	NOUN
cana-3796	390	5	based	base	VERB
cana-3796	390	6	hybrid	hybrid	ADJ
cana-3796	390	7	neural	neural	ADJ
cana-3796	390	8	network	network	NOUN
cana-3796	390	9	for	for	ADP
cana-3796	390	10	text	text	NOUN
cana-3796	390	11	detection	detection	NOUN
cana-3796	390	12	on	on	ADP
cana-3796	390	13	signboard	signboard	NOUN
cana-3796	390	14	,	,	PUNCT
cana-3796	390	15	billboard	billboard	NOUN
cana-3796	390	16	and	and	CCONJ
cana-3796	390	17	news	news	NOUN
cana-3796	390	18	tickers	ticker	NOUN
cana-3796	390	19	.	.	PUNCT
cana-3796	390	20	”	"	PUNCT
cana-3796	391	1	ieee	ieee	NOUN
cana-3796	391	2	access	access	NOUN
cana-3796	391	3	11:41524–34	11:41524–34	NUM
cana-3796	391	4	.	.	PUNCT
cana-3796	392	1	https://doi.org/10.1109/access.2023.3264569	https://doi.org/10.1109/access.2023.3264569	PROPN
cana-3796	392	2	.	.	PUNCT
cana-3796	393	1	https://doi.org/10.1109/tmm.2021.3129651	https://doi.org/10.1109/tmm.2021.3129651	PROPN
cana-3796	393	2	https://doi.org/10.1109/tim.2023.3300474	https://doi.org/10.1109/tim.2023.3300474	ADJ
cana-3796	393	3	https://doi.org/10.1109/tim.2022.3154831	https://doi.org/10.1109/tim.2022.3154831	PROPN
cana-3796	393	4	https://doi.org/10.1109/tpami.2022.3144899	https://doi.org/10.1109/tpami.2022.3144899	PROPN
cana-3796	393	5	https://doi.org/10.1109/tmm.2022.3146779	https://doi.org/10.1109/tmm.2022.3146779	PROPN
cana-3796	393	6	https://doi.org/10.1109/tii.2023.3257295	https://doi.org/10.1109/tii.2023.3257295	ADJ
cana-3796	393	7	https://doi.org/10.1109/access.2023.3268545	https://doi.org/10.1109/access.2023.3268545	PROPN
cana-3796	393	8	https://doi.org/10.1109/tpami.2022.3230962	https://doi.org/10.1109/tpami.2022.3230962	PROPN
cana-3796	393	9	https://doi.org/10.1109/access.2022.3216881	https://doi.org/10.1109/access.2022.3216881	PROPN
cana-3796	393	10	https://doi.org/10.1109/access.2023.3310819	https://doi.org/10.1109/access.2023.3310819	PROPN
cana-3796	393	11	https://doi.org/10.1109/access.2022.3207469	https://doi.org/10.1109/access.2022.3207469	PROPN
cana-3796	393	12	https://doi.org/10.1109/tits.2022.3151475	https://doi.org/10.1109/tits.2022.3151475	PROPN
cana-3796	393	13	https://doi.org/10.1109/access.2022.3179366	https://doi.org/10.1109/access.2022.3179366	PROPN
cana-3796	393	14	https://doi.org/10.1109/access.2023.3314334	https://doi.org/10.1109/access.2023.3314334	PROPN
cana-3796	393	15	https://doi.org/10.1109/access.2023.3331213	https://doi.org/10.1109/access.2023.3331213	PROPN
cana-3796	393	16	https://doi.org/10.1109/tie.2021.3050357	https://doi.org/10.1109/tie.2021.3050357	NOUN
cana-3796	393	17	https://doi.org/10.1109/access.2023.3264569	https://doi.org/10.1109/access.2023.3264569	PROPN
cana-3796	393	18	communications	communication	NOUN
cana-3796	393	19	on	on	ADP
cana-3796	393	20	applied	apply	VERB
cana-3796	393	21	nonlinear	nonlinear	ADJ
cana-3796	393	22	analysis	analysis	NOUN
cana-3796	393	23	issn	issn	NOUN
cana-3796	393	24	:	:	PUNCT
cana-3796	393	25	1074	1074	NUM
cana-3796	393	26	-	-	PUNCT
cana-3796	393	27	133x	133x	NUM
cana-3796	393	28	vol	vol	NOUN
cana-3796	393	29	32	32	NUM
cana-3796	393	30	no	no	NOUN
cana-3796	393	31	.	.	PUNCT
cana-3796	394	1	8s	8s	PROPN
cana-3796	394	2	(	(	PUNCT
cana-3796	394	3	2025	2025	NUM
cana-3796	394	4	)	)	PUNCT
cana-3796	394	5	761	761	NUM
cana-3796	394	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	395	1	[	[	X
cana-3796	395	2	21	21	NUM
cana-3796	395	3	]	]	PUNCT
cana-3796	395	4	chandio	chandio	NOUN
cana-3796	395	5	,	,	PUNCT
cana-3796	395	6	a.a	a.a	PROPN
cana-3796	395	7	.	.	PROPN
cana-3796	395	8	,	,	PUNCT
cana-3796	395	9	m.	m.	PROPN
cana-3796	395	10	asikuzzaman	asikuzzaman	PROPN
cana-3796	395	11	,	,	PUNCT
cana-3796	395	12	m.r	m.r	PROPN
cana-3796	395	13	.	.	PROPN
cana-3796	395	14	pickering	pickering	PROPN
cana-3796	395	15	,	,	PUNCT
cana-3796	395	16	and	and	CCONJ
cana-3796	395	17	m.	m.	NOUN
cana-3796	395	18	leghari	leghari	PROPN
cana-3796	395	19	.	.	PUNCT
cana-3796	396	1	2022	2022	NUM
cana-3796	396	2	.	.	PUNCT
cana-3796	397	1	“	"	PUNCT
cana-3796	397	2	cursive	cursive	ADJ
cana-3796	397	3	text	text	NOUN
cana-3796	397	4	recognition	recognition	NOUN
cana-3796	397	5	in	in	ADP
cana-3796	397	6	natural	natural	ADJ
cana-3796	397	7	scene	scene	NOUN
cana-3796	397	8	images	image	NOUN
cana-3796	397	9	using	use	VERB
cana-3796	397	10	deep	deep	ADJ
cana-3796	397	11	convolutional	convolutional	ADJ
cana-3796	397	12	recurrent	recurrent	ADJ
cana-3796	397	13	neural	neural	ADJ
cana-3796	397	14	network	network	NOUN
cana-3796	397	15	.	.	PUNCT
cana-3796	397	16	”	"	PUNCT
cana-3796	398	1	ieee	ieee	NOUN
cana-3796	398	2	access	access	NOUN
cana-3796	398	3	10:10062	10:10062	NUM
cana-3796	398	4	–	–	PUNCT
cana-3796	398	5	78	78	NUM
cana-3796	398	6	.	.	PUNCT
cana-3796	399	1	https://doi.org/10.1109/access.2022.3144844	https://doi.org/10.1109/access.2022.3144844	PROPN
cana-3796	399	2	.	.	PUNCT
cana-3796	400	1	[	[	X
cana-3796	400	2	22	22	NUM
cana-3796	400	3	]	]	X
cana-3796	400	4	yang	yang	PROPN
cana-3796	400	5	,	,	PUNCT
cana-3796	400	6	x.	x.	PROPN
cana-3796	400	7	,	,	PUNCT
cana-3796	400	8	h.	h.	PROPN
cana-3796	400	9	wang	wang	PROPN
cana-3796	400	10	,	,	PUNCT
cana-3796	400	11	and	and	CCONJ
cana-3796	400	12	y.	y.	PROPN
cana-3796	400	13	ji	ji	PROPN
cana-3796	400	14	.	.	PROPN
cana-3796	400	15	2023	2023	NUM
cana-3796	400	16	.	.	PUNCT
cana-3796	400	17	“	"	PUNCT
cana-3796	400	18	optical	optical	ADJ
cana-3796	400	19	transmitter	transmitter	NOUN
cana-3796	400	20	fingerprint	fingerprint	NOUN
cana-3796	400	21	authentication	authentication	NOUN
cana-3796	400	22	based	base	VERB
cana-3796	400	23	on	on	ADP
cana-3796	400	24	chaotic	chaotic	ADJ
cana-3796	400	25	complexity	complexity	NOUN
cana-3796	400	26	features	feature	NOUN
cana-3796	400	27	for	for	ADP
cana-3796	400	28	secure	secure	ADJ
cana-3796	400	29	optical	optical	ADJ
cana-3796	400	30	transmission	transmission	NOUN
cana-3796	400	31	.	.	PUNCT
cana-3796	400	32	”	"	PUNCT
cana-3796	401	1	journal	journal	NOUN
cana-3796	401	2	of	of	ADP
cana-3796	401	3	lightwave	lightwave	PROPN
cana-3796	401	4	technology	technology	PROPN
cana-3796	401	5	41	41	NUM
cana-3796	401	6	(	(	PUNCT
cana-3796	401	7	18):5834	18):5834	NUM
cana-3796	401	8	–	–	SYM
cana-3796	401	9	40	40	NUM
cana-3796	401	10	.	.	PUNCT
cana-3796	402	1	https://doi.org/10.1109/jlt.2023.3270382	https://doi.org/10.1109/jlt.2023.3270382	VERB
cana-3796	402	2	.	.	PUNCT
cana-3796	403	1	[	[	X
cana-3796	403	2	23	23	NUM
cana-3796	403	3	]	]	X
cana-3796	403	4	shi	shi	PROPN
cana-3796	403	5	,	,	PUNCT
cana-3796	403	6	h.	h.	PROPN
cana-3796	403	7	,	,	PUNCT
cana-3796	403	8	and	and	CCONJ
cana-3796	403	9	d.	d.	PROPN
cana-3796	403	10	zhao	zhao	PROPN
cana-3796	403	11	.	.	PUNCT
cana-3796	404	1	2023	2023	NUM
cana-3796	404	2	.	.	PUNCT
cana-3796	405	1	“	"	PUNCT
cana-3796	405	2	license	license	NOUN
cana-3796	405	3	plate	plate	NOUN
cana-3796	405	4	recognition	recognition	NOUN
cana-3796	405	5	system	system	NOUN
cana-3796	405	6	based	base	VERB
cana-3796	405	7	on	on	ADP
cana-3796	405	8	improved	improved	ADJ
cana-3796	405	9	yolov5	yolov5	NOUN
cana-3796	405	10	and	and	CCONJ
cana-3796	405	11	gru	gru	PROPN
cana-3796	405	12	.	.	PUNCT
cana-3796	405	13	”	"	PUNCT
cana-3796	405	14	ieee	ieee	NOUN
cana-3796	405	15	access	access	NOUN
cana-3796	405	16	11:10429–39	11:10429–39	NUM
cana-3796	405	17	.	.	PUNCT
cana-3796	406	1	https://doi.org/10.1109/access.2023.3240439	https://doi.org/10.1109/access.2023.3240439	PROPN
cana-3796	406	2	.	.	PUNCT
cana-3796	407	1	[	[	X
cana-3796	407	2	24	24	NUM
cana-3796	407	3	]	]	X
cana-3796	407	4	silva	silva	PROPN
cana-3796	407	5	,	,	PUNCT
cana-3796	407	6	s.m	s.m	PROPN
cana-3796	407	7	.	.	PROPN
cana-3796	407	8	,	,	PUNCT
cana-3796	407	9	and	and	CCONJ
cana-3796	407	10	c.r	c.r	PROPN
cana-3796	407	11	.	.	PROPN
cana-3796	407	12	jung	jung	PROPN
cana-3796	407	13	.	.	PUNCT
cana-3796	407	14	2022	2022	NUM
cana-3796	407	15	.	.	PUNCT
cana-3796	408	1	“	"	PUNCT
cana-3796	408	2	a	a	DET
cana-3796	408	3	flexible	flexible	ADJ
cana-3796	408	4	approach	approach	NOUN
cana-3796	408	5	for	for	ADP
cana-3796	408	6	automatic	automatic	ADJ
cana-3796	408	7	license	license	NOUN
cana-3796	408	8	plate	plate	NOUN
cana-3796	408	9	recognition	recognition	NOUN
cana-3796	408	10	in	in	ADP
cana-3796	408	11	unconstrained	unconstrained	ADJ
cana-3796	408	12	scenarios	scenario	NOUN
cana-3796	408	13	.	.	PUNCT
cana-3796	408	14	”	"	PUNCT
cana-3796	408	15	ieee	ieee	NOUN
cana-3796	408	16	transactions	transaction	NOUN
cana-3796	408	17	on	on	ADP
cana-3796	408	18	intelligent	intelligent	ADJ
cana-3796	408	19	transportation	transportation	NOUN
cana-3796	408	20	systems	system	NOUN
cana-3796	408	21	23	23	NUM
cana-3796	408	22	(	(	PUNCT
cana-3796	408	23	6):5693–703	6):5693–703	NOUN
cana-3796	408	24	.	.	PUNCT
cana-3796	409	1	https://doi.org/10.1109/tits.2021.3055946	https://doi.org/10.1109/tits.2021.3055946	PROPN
cana-3796	409	2	.	.	PUNCT
cana-3796	410	1	[	[	X
cana-3796	410	2	25	25	NUM
cana-3796	410	3	]	]	PUNCT
cana-3796	410	4	xu	xu	PROPN
cana-3796	410	5	,	,	PUNCT
cana-3796	410	6	h.	h.	PROPN
cana-3796	410	7	,	,	PUNCT
cana-3796	410	8	x.-d	x.-d	PROPN
cana-3796	410	9	.	.	PUNCT
cana-3796	411	1	zhou	zhou	PROPN
cana-3796	411	2	,	,	PUNCT
cana-3796	411	3	z.	z.	PROPN
cana-3796	411	4	li	li	PROPN
cana-3796	411	5	,	,	PUNCT
cana-3796	411	6	l.	l.	PROPN
cana-3796	411	7	liu	liu	PROPN
cana-3796	411	8	,	,	PUNCT
cana-3796	411	9	c.	c.	PROPN
cana-3796	411	10	li	li	PROPN
cana-3796	411	11	,	,	PUNCT
cana-3796	411	12	and	and	CCONJ
cana-3796	411	13	y.	y.	PROPN
cana-3796	411	14	shi	shi	PROPN
cana-3796	411	15	.	.	PUNCT
cana-3796	411	16	2022	2022	NUM
cana-3796	411	17	.	.	PUNCT
cana-3796	412	1	“	"	PUNCT
cana-3796	412	2	eilpr	eilpr	NOUN
cana-3796	412	3	:	:	PUNCT
cana-3796	412	4	toward	toward	ADP
cana-3796	412	5	end	end	NOUN
cana-3796	412	6	-	-	PUNCT
cana-3796	412	7	to	to	ADP
cana-3796	412	8	-	-	PUNCT
cana-3796	412	9	end	end	VERB
cana-3796	412	10	irregular	irregular	ADJ
cana-3796	412	11	license	license	NOUN
cana-3796	412	12	plate	plate	NOUN
cana-3796	412	13	recognition	recognition	NOUN
cana-3796	412	14	based	base	VERB
cana-3796	412	15	on	on	ADP
cana-3796	412	16	automatic	automatic	ADJ
cana-3796	412	17	perspective	perspective	NOUN
cana-3796	412	18	alignment	alignment	NOUN
cana-3796	412	19	.	.	PUNCT
cana-3796	412	20	”	"	PUNCT
cana-3796	413	1	ieee	ieee	NOUN
cana-3796	413	2	transactions	transaction	NOUN
cana-3796	413	3	on	on	ADP
cana-3796	413	4	intelligent	intelligent	ADJ
cana-3796	413	5	transportation	transportation	NOUN
cana-3796	413	6	systems	system	NOUN
cana-3796	413	7	23	23	NUM
cana-3796	413	8	(	(	PUNCT
cana-3796	413	9	3):2586–95	3):2586–95	NUM
cana-3796	413	10	.	.	PUNCT
cana-3796	414	1	https://doi.org/10.1109/tits.2021.3130898	https://doi.org/10.1109/tits.2021.3130898	PROPN
cana-3796	414	2	.	.	PUNCT
cana-3796	415	1	[	[	X
cana-3796	415	2	26	26	NUM
cana-3796	415	3	]	]	X
cana-3796	415	4	nguyen	nguyen	NOUN
cana-3796	415	5	,	,	PUNCT
cana-3796	415	6	q.-d	q.-d	PROPN
cana-3796	415	7	.	.	PUNCT
cana-3796	415	8	,	,	PUNCT
cana-3796	415	9	n.-m	n.-m	PROPN
cana-3796	415	10	.	.	PUNCT
cana-3796	416	1	phan	phan	PROPN
cana-3796	416	2	,	,	PUNCT
cana-3796	416	3	p.	p.	PROPN
cana-3796	416	4	krömer	krömer	PROPN
cana-3796	416	5	,	,	PUNCT
cana-3796	416	6	and	and	CCONJ
cana-3796	416	7	d.-a	d.-a	PROPN
cana-3796	416	8	.	.	PUNCT
cana-3796	417	1	le	le	X
cana-3796	417	2	.	.	PROPN
cana-3796	417	3	2023	2023	NUM
cana-3796	417	4	.	.	PUNCT
cana-3796	418	1	“	"	PUNCT
cana-3796	418	2	an	an	DET
cana-3796	418	3	efficient	efficient	ADJ
cana-3796	418	4	unsupervised	unsupervised	ADJ
cana-3796	418	5	approach	approach	NOUN
cana-3796	418	6	for	for	ADP
cana-3796	418	7	ocr	ocr	ADJ
cana-3796	418	8	error	error	NOUN
cana-3796	418	9	correction	correction	NOUN
cana-3796	418	10	of	of	ADP
cana-3796	418	11	vietnamese	vietnamese	ADJ
cana-3796	418	12	ocr	ocr	PROPN
cana-3796	418	13	text	text	NOUN
cana-3796	418	14	.	.	PUNCT
cana-3796	418	15	”	"	PUNCT
cana-3796	419	1	ieee	ieee	NOUN
cana-3796	419	2	access	access	NOUN
cana-3796	419	3	11:58406–21	11:58406–21	NUM
cana-3796	419	4	.	.	PUNCT
cana-3796	419	5	https://doi.org/10.1109/access.2023.3283340	https://doi.org/10.1109/access.2023.3283340	PROPN
cana-3796	419	6	.	.	PUNCT
cana-3796	420	1	[	[	X
cana-3796	420	2	27	27	NUM
cana-3796	420	3	]	]	X
cana-3796	420	4	jang	jang	PROPN
cana-3796	420	5	,	,	PUNCT
cana-3796	420	6	h.	h.	PROPN
cana-3796	420	7	,	,	PUNCT
cana-3796	420	8	h.	h.	PROPN
cana-3796	420	9	choi	choi	PROPN
cana-3796	420	10	,	,	PUNCT
cana-3796	420	11	b.j	b.j	PROPN
cana-3796	420	12	.	.	PROPN
cana-3796	420	13	kim	kim	PROPN
cana-3796	420	14	,	,	PUNCT
cana-3796	420	15	s.w	s.w	PROPN
cana-3796	420	16	.	.	PROPN
cana-3796	420	17	kim	kim	PROPN
cana-3796	420	18	,	,	PUNCT
cana-3796	420	19	and	and	CCONJ
cana-3796	420	20	g.	g.	PROPN
cana-3796	420	21	koo	koo	PROPN
cana-3796	420	22	.	.	PROPN
cana-3796	420	23	2023	2023	NUM
cana-3796	420	24	.	.	PUNCT
cana-3796	421	1	“	"	PUNCT
cana-3796	421	2	two	two	NUM
cana-3796	421	3	-	-	PUNCT
cana-3796	421	4	stage	stage	NOUN
cana-3796	421	5	billet	billet	NOUN
cana-3796	421	6	identification	identification	NOUN
cana-3796	421	7	number	number	NOUN
cana-3796	421	8	recognition	recognition	NOUN
cana-3796	421	9	using	use	VERB
cana-3796	421	10	label	label	NOUN
cana-3796	421	11	distribution	distribution	NOUN
cana-3796	421	12	.	.	PUNCT
cana-3796	421	13	”	"	PUNCT
cana-3796	422	1	ieee	ieee	NOUN
cana-3796	422	2	access	access	NOUN
cana-3796	422	3	11:129311	11:129311	NUM
cana-3796	422	4	–	–	PUNCT
cana-3796	422	5	19.https://doi.org/10.1109/access.2023.3333904	19.https://doi.org/10.1109/access.2023.3333904	NUM
cana-3796	422	6	[	[	X
cana-3796	422	7	28	28	NUM
cana-3796	422	8	]	]	X
cana-3796	422	9	fu	fu	PROPN
cana-3796	422	10	,	,	PUNCT
cana-3796	422	11	w.	w.	PROPN
cana-3796	422	12	,	,	PUNCT
cana-3796	422	13	yi	yi	PROPN
cana-3796	422	14	,	,	PUNCT
cana-3796	422	15	d.	d.	PROPN
cana-3796	422	16	,	,	PUNCT
cana-3796	422	17	huang	huang	PROPN
cana-3796	422	18	,	,	PUNCT
cana-3796	422	19	z.	z.	PROPN
cana-3796	422	20	,	,	PUNCT
cana-3796	422	21	huang	huang	PROPN
cana-3796	422	22	,	,	PUNCT
cana-3796	422	23	c.	c.	PROPN
cana-3796	422	24	,	,	PUNCT
cana-3796	422	25	geng	geng	PROPN
cana-3796	422	26	,	,	PUNCT
cana-3796	422	27	y.	y.	PROPN
cana-3796	422	28	,	,	PUNCT
cana-3796	422	29	&	&	CCONJ
cana-3796	422	30	li	li	PROPN
cana-3796	422	31	,	,	PUNCT
cana-3796	422	32	x.	x.	NOUN
cana-3796	422	33	2023	2023	NUM
cana-3796	422	34	.	.	PUNCT
cana-3796	423	1	"	"	PUNCT
cana-3796	423	2	multiple	multiple	ADJ
cana-3796	423	3	event	event	NOUN
cana-3796	423	4	recognition	recognition	NOUN
cana-3796	423	5	scheme	scheme	NOUN
cana-3796	423	6	using	use	VERB
cana-3796	423	7	variational	variational	ADJ
cana-3796	423	8	mode	mode	NOUN
cana-3796	423	9	decomposition	decomposition	NOUN
cana-3796	423	10	-	-	PUNCT
cana-3796	423	11	based	base	VERB
cana-3796	423	12	hybrid	hybrid	ADJ
cana-3796	423	13	feature	feature	NOUN
cana-3796	423	14	extraction	extraction	NOUN
cana-3796	423	15	in	in	ADP
cana-3796	423	16	fiber	fiber	NOUN
cana-3796	423	17	optic	optic	NOUN
cana-3796	423	18	das	das	PROPN
cana-3796	423	19	system	system	NOUN
cana-3796	423	20	.	.	PUNCT
cana-3796	423	21	"	"	PUNCT
cana-3796	424	1	ieee	ieee	NOUN
cana-3796	424	2	sensors	sensor	NOUN
cana-3796	424	3	journal	journal	PROPN
cana-3796	424	4	23	23	NUM
cana-3796	424	5	(	(	PUNCT
cana-3796	424	6	22	22	NUM
cana-3796	424	7	):	):	PUNCT
cana-3796	424	8	27316	27316	NUM
cana-3796	424	9	-	-	SYM
cana-3796	424	10	27323	27323	NUM
cana-3796	424	11	.	.	PUNCT
cana-3796	425	1	https://doi.org/10.1109/jsen.2023.3318248	https://doi.org/10.1109/jsen.2023.3318248	PROPN
cana-3796	425	2	.	.	PUNCT
cana-3796	426	1	[	[	X
cana-3796	426	2	29	29	NUM
cana-3796	426	3	]	]	X
cana-3796	426	4	seo	seo	NOUN
cana-3796	426	5	,	,	PUNCT
cana-3796	426	6	t.-m	t.-m	NOUN
cana-3796	426	7	.	.	PUNCT
cana-3796	426	8	,	,	PUNCT
cana-3796	426	9	&	&	CCONJ
cana-3796	426	10	kang	kang	PROPN
cana-3796	426	11	,	,	PUNCT
cana-3796	426	12	d.-j	d.-j	PROPN
cana-3796	426	13	.	.	PUNCT
cana-3796	426	14	2022	2022	NUM
cana-3796	426	15	.	.	PUNCT
cana-3796	427	1	"	"	PUNCT
cana-3796	427	2	a	a	DET
cana-3796	427	3	robust	robust	ADJ
cana-3796	427	4	layout	layout	NOUN
cana-3796	427	5	-	-	PUNCT
cana-3796	427	6	independent	independent	ADJ
cana-3796	427	7	license	license	NOUN
cana-3796	427	8	plate	plate	NOUN
cana-3796	427	9	detection	detection	NOUN
cana-3796	427	10	and	and	CCONJ
cana-3796	427	11	recognition	recognition	NOUN
cana-3796	427	12	model	model	NOUN
cana-3796	427	13	based	base	VERB
cana-3796	427	14	on	on	ADP
cana-3796	427	15	attention	attention	NOUN
cana-3796	427	16	method	method	NOUN
cana-3796	427	17	.	.	PUNCT
cana-3796	427	18	"	"	PUNCT
cana-3796	428	1	ieee	ieee	NOUN
cana-3796	428	2	access	access	NOUN
cana-3796	428	3	10	10	NUM
cana-3796	428	4	:	:	PUNCT
cana-3796	428	5	57427	57427	NUM
cana-3796	428	6	-	-	SYM
cana-3796	428	7	57436	57436	NUM
cana-3796	428	8	.	.	PUNCT
cana-3796	429	1	https://doi.org/10.1109/access.2022.3178192	https://doi.org/10.1109/access.2022.3178192	PROPN
cana-3796	429	2	.	.	PUNCT
cana-3796	430	1	[	[	X
cana-3796	430	2	30	30	NUM
cana-3796	430	3	]	]	X
cana-3796	430	4	gao	gao	PROPN
cana-3796	430	5	,	,	PUNCT
cana-3796	430	6	y.	y.	PROPN
cana-3796	430	7	,	,	PUNCT
cana-3796	430	8	lu	lu	PROPN
cana-3796	430	9	,	,	PUNCT
cana-3796	430	10	h.	h.	PROPN
cana-3796	430	11	,	,	PUNCT
cana-3796	430	12	mu	mu	PROPN
cana-3796	430	13	,	,	PUNCT
cana-3796	430	14	s.	s.	PROPN
cana-3796	430	15	,	,	PUNCT
cana-3796	430	16	&	&	CCONJ
cana-3796	430	17	xu	xu	PROPN
cana-3796	430	18	,	,	PUNCT
cana-3796	430	19	s.	s.	PROPN
cana-3796	430	20	2023	2023	NUM
cana-3796	430	21	.	.	PUNCT
cana-3796	431	1	"	"	PUNCT
cana-3796	431	2	groupplate	groupplate	NOUN
cana-3796	431	3	:	:	PUNCT
cana-3796	431	4	toward	toward	ADP
cana-3796	431	5	multi	multi	ADJ
cana-3796	431	6	-	-	ADJ
cana-3796	431	7	category	category	ADJ
cana-3796	431	8	license	license	NOUN
cana-3796	431	9	plate	plate	NOUN
cana-3796	431	10	recognition	recognition	NOUN
cana-3796	431	11	.	.	PUNCT
cana-3796	431	12	"	"	PUNCT
cana-3796	432	1	ieee	ieee	NOUN
cana-3796	432	2	transactions	transaction	NOUN
cana-3796	432	3	on	on	ADP
cana-3796	432	4	intelligent	intelligent	ADJ
cana-3796	432	5	transportation	transportation	NOUN
cana-3796	432	6	systems	system	NOUN
cana-3796	432	7	24	24	NUM
cana-3796	432	8	(	(	PUNCT
cana-3796	432	9	5	5	NUM
cana-3796	432	10	):	):	PUNCT
cana-3796	432	11	5586	5586	NUM
cana-3796	432	12	-	-	SYM
cana-3796	432	13	5599	5599	NUM
cana-3796	432	14	.	.	PUNCT
cana-3796	433	1	https://doi.org/10.1109/tits.2023.3244827	https://doi.org/10.1109/tits.2023.3244827	X
cana-3796	433	2	.	.	PUNCT
cana-3796	434	1	[	[	X
cana-3796	434	2	31	31	NUM
cana-3796	434	3	]	]	X
cana-3796	434	4	chen	chen	PROPN
cana-3796	434	5	,	,	PUNCT
cana-3796	434	6	z.	z.	PROPN
cana-3796	434	7	,	,	PUNCT
cana-3796	434	8	yin	yin	PROPN
cana-3796	434	9	,	,	PUNCT
cana-3796	434	10	f.	f.	PROPN
cana-3796	434	11	,	,	PUNCT
cana-3796	434	12	yang	yang	PROPN
cana-3796	434	13	,	,	PUNCT
cana-3796	434	14	q.	q.	PROPN
cana-3796	434	15	,	,	PUNCT
cana-3796	434	16	&	&	CCONJ
cana-3796	434	17	liu	liu	PROPN
cana-3796	434	18	,	,	PUNCT
cana-3796	434	19	c.-l	c.-l	PROPN
cana-3796	434	20	.	.	PUNCT
cana-3796	435	1	2023	2023	NUM
cana-3796	435	2	.	.	PUNCT
cana-3796	436	1	"	"	PUNCT
cana-3796	436	2	cross	cross	ADJ
cana-3796	436	3	-	-	ADJ
cana-3796	436	4	lingual	lingual	ADJ
cana-3796	436	5	text	text	NOUN
cana-3796	436	6	image	image	NOUN
cana-3796	436	7	recognition	recognition	NOUN
cana-3796	436	8	via	via	ADP
cana-3796	436	9	multihierarchy	multihierarchy	PROPN
cana-3796	436	10	cross	cross	ADJ
cana-3796	436	11	-	-	ADJ
cana-3796	436	12	modal	modal	ADJ
cana-3796	436	13	mimic	mimic	NOUN
cana-3796	436	14	.	.	PUNCT
cana-3796	436	15	"	"	PUNCT
cana-3796	437	1	ieee	ieee	NOUN
cana-3796	437	2	transactions	transaction	NOUN
cana-3796	437	3	on	on	ADP
cana-3796	437	4	multimedia	multimedia	NOUN
cana-3796	437	5	25	25	NUM
cana-3796	437	6	:	:	SYM
cana-3796	437	7	4830	4830	NUM
cana-3796	437	8	-	-	SYM
cana-3796	437	9	4841	4841	NUM
cana-3796	437	10	.	.	PUNCT
cana-3796	438	1	https://doi.org/10.1109/tmm.2022.3183386	https://doi.org/10.1109/tmm.2022.3183386	X
cana-3796	438	2	.	.	PUNCT
cana-3796	439	1	[	[	X
cana-3796	439	2	32	32	NUM
cana-3796	439	3	]	]	SYM
cana-3796	439	4	li	li	PROPN
cana-3796	439	5	,	,	PUNCT
cana-3796	439	6	m.	m.	NOUN
cana-3796	439	7	,	,	PUNCT
cana-3796	439	8	fu	fu	PROPN
cana-3796	439	9	,	,	PUNCT
cana-3796	439	10	b.	b.	PROPN
cana-3796	439	11	,	,	PUNCT
cana-3796	439	12	chen	chen	PROPN
cana-3796	439	13	,	,	PUNCT
cana-3796	439	14	h.	h.	PROPN
cana-3796	439	15	,	,	PUNCT
cana-3796	439	16	he	he	PRON
cana-3796	439	17	,	,	PUNCT
cana-3796	439	18	j.	j.	PROPN
cana-3796	439	19	,	,	PUNCT
cana-3796	439	20	&	&	CCONJ
cana-3796	439	21	qiao	qiao	PROPN
cana-3796	439	22	,	,	PUNCT
cana-3796	439	23	y.	y.	PROPN
cana-3796	439	24	2023	2023	NUM
cana-3796	439	25	.	.	PUNCT
cana-3796	440	1	"	"	PUNCT
cana-3796	440	2	dual	dual	ADJ
cana-3796	440	3	relation	relation	NOUN
cana-3796	440	4	network	network	NOUN
cana-3796	440	5	for	for	ADP
cana-3796	440	6	scene	scene	NOUN
cana-3796	440	7	text	text	NOUN
cana-3796	440	8	recognition	recognition	NOUN
cana-3796	440	9	.	.	PUNCT
cana-3796	440	10	"	"	PUNCT
cana-3796	441	1	ieee	ieee	NOUN
cana-3796	441	2	transactions	transaction	NOUN
cana-3796	441	3	on	on	ADP
cana-3796	441	4	multimedia	multimedia	NOUN
cana-3796	441	5	25	25	NUM
cana-3796	441	6	:	:	PUNCT
cana-3796	441	7	4094	4094	NUM
cana-3796	441	8	-	-	SYM
cana-3796	441	9	4107	4107	NUM
cana-3796	441	10	.	.	PUNCT
cana-3796	442	1	https://doi.org/10.1109/tmm.2022.3171108	https://doi.org/10.1109/tmm.2022.3171108	X
cana-3796	442	2	.	.	PUNCT
cana-3796	443	1	[	[	X
cana-3796	443	2	33	33	NUM
cana-3796	443	3	]	]	X
cana-3796	443	4	tan	tan	PROPN
cana-3796	443	5	,	,	PUNCT
cana-3796	443	6	x.	x.	PROPN
cana-3796	443	7	,	,	PUNCT
cana-3796	443	8	tong	tong	PROPN
cana-3796	443	9	,	,	PUNCT
cana-3796	443	10	j.	j.	PROPN
cana-3796	443	11	,	,	PUNCT
cana-3796	443	12	matsumaru	matsumaru	NOUN
cana-3796	443	13	,	,	PUNCT
cana-3796	443	14	t.	t.	PROPN
cana-3796	443	15	,	,	PUNCT
cana-3796	443	16	dutta	dutta	PROPN
cana-3796	443	17	,	,	PUNCT
cana-3796	443	18	v.	v.	PROPN
cana-3796	443	19	,	,	PUNCT
cana-3796	443	20	&	&	CCONJ
cana-3796	443	21	he	he	PRON
cana-3796	443	22	,	,	PUNCT
cana-3796	443	23	x.	x.	NOUN
cana-3796	443	24	2023	2023	NUM
cana-3796	443	25	.	.	PUNCT
cana-3796	444	1	"	"	PUNCT
cana-3796	444	2	an	an	DET
cana-3796	444	3	end	end	NOUN
cana-3796	444	4	-	-	PUNCT
cana-3796	444	5	to	to	ADP
cana-3796	444	6	-	-	PUNCT
cana-3796	444	7	end	end	NOUN
cana-3796	444	8	air	air	NOUN
cana-3796	444	9	writing	writing	NOUN
cana-3796	444	10	recognition	recognition	NOUN
cana-3796	444	11	method	method	NOUN
cana-3796	444	12	based	base	VERB
cana-3796	444	13	on	on	ADP
cana-3796	444	14	transformer	transformer	NOUN
cana-3796	444	15	.	.	PUNCT
cana-3796	444	16	"	"	PUNCT
cana-3796	445	1	ieee	ieee	NOUN
cana-3796	445	2	access	access	NOUN
cana-3796	445	3	11	11	NUM
cana-3796	445	4	:	:	SYM
cana-3796	445	5	109885	109885	NUM
cana-3796	445	6	-	-	SYM
cana-3796	445	7	109898	109898	NUM
cana-3796	445	8	.	.	PUNCT
cana-3796	446	1	https://doi.org/10.1109/access.2023.3321807	https://doi.org/10.1109/access.2023.3321807	PROPN
cana-3796	446	2	.	.	PUNCT
cana-3796	447	1	[	[	X
cana-3796	447	2	34	34	NUM
cana-3796	447	3	]	]	X
cana-3796	447	4	rahman	rahman	PROPN
cana-3796	447	5	,	,	PUNCT
cana-3796	447	6	a.	a.	PROPN
cana-3796	447	7	b.	b.	PROPN
cana-3796	447	8	m.	m.	PROPN
cana-3796	447	9	ashikur	ashikur	PROPN
cana-3796	447	10	,	,	PUNCT
cana-3796	447	11	et	et	PROPN
cana-3796	447	12	al	al	PROPN
cana-3796	447	13	.	.	PROPN
cana-3796	447	14	2022	2022	NUM
cana-3796	447	15	.	.	PUNCT
cana-3796	448	1	"	"	PUNCT
cana-3796	448	2	two	two	NUM
cana-3796	448	3	decades	decade	NOUN
cana-3796	448	4	of	of	ADP
cana-3796	448	5	bengali	bengali	ADJ
cana-3796	448	6	handwritten	handwritten	ADJ
cana-3796	448	7	digit	digit	NOUN
cana-3796	448	8	recognition	recognition	NOUN
cana-3796	448	9	:	:	PUNCT
cana-3796	448	10	a	a	DET
cana-3796	448	11	survey	survey	NOUN
cana-3796	448	12	.	.	PUNCT
cana-3796	448	13	"	"	PUNCT
cana-3796	448	14	ieee	ieee	NOUN
cana-3796	448	15	access	access	NOUN
cana-3796	448	16	10	10	NUM
cana-3796	448	17	:	:	SYM
cana-3796	448	18	92597	92597	NUM
cana-3796	448	19	-	-	SYM
cana-3796	448	20	92632	92632	NUM
cana-3796	448	21	.	.	PUNCT
cana-3796	449	1	https://doi.org/10.1109/access.2022.3202893	https://doi.org/10.1109/access.2022.3202893	PROPN
cana-3796	449	2	.	.	PUNCT
cana-3796	450	1	[	[	X
cana-3796	450	2	35	35	NUM
cana-3796	450	3	]	]	SYM
cana-3796	450	4	li	li	PROPN
cana-3796	450	5	,	,	PUNCT
cana-3796	450	6	b.	b.	PROPN
cana-3796	450	7	,	,	PUNCT
cana-3796	450	8	tang	tang	PROPN
cana-3796	450	9	,	,	PUNCT
cana-3796	450	10	x.	x.	PROPN
cana-3796	450	11	,	,	PUNCT
cana-3796	450	12	qi	qi	PROPN
cana-3796	450	13	,	,	PUNCT
cana-3796	450	14	x.	x.	PROPN
cana-3796	450	15	,	,	PUNCT
cana-3796	450	16	chen	chen	PROPN
cana-3796	450	17	,	,	PUNCT
cana-3796	450	18	y.	y.	PROPN
cana-3796	450	19	,	,	PUNCT
cana-3796	450	20	li	li	PROPN
cana-3796	450	21	,	,	PUNCT
cana-3796	450	22	c.-g	c.-g	PROPN
cana-3796	450	23	.	.	PROPN
cana-3796	450	24	,	,	PUNCT
cana-3796	450	25	&	&	CCONJ
cana-3796	450	26	xiao	xiao	PROPN
cana-3796	450	27	,	,	PUNCT
cana-3796	450	28	r.	r.	PROPN
cana-3796	450	29	2022	2022	NUM
cana-3796	450	30	.	.	PUNCT
cana-3796	451	1	"	"	PUNCT
cana-3796	451	2	emu	emu	PROPN
cana-3796	451	3	:	:	PUNCT
cana-3796	451	4	effective	effective	ADJ
cana-3796	451	5	multi	multi	ADJ
cana-3796	451	6	-	-	ADJ
cana-3796	451	7	hot	hot	ADJ
cana-3796	451	8	encoding	encoding	NOUN
cana-3796	451	9	net	net	NOUN
cana-3796	451	10	for	for	ADP
cana-3796	451	11	lightweight	lightweight	ADJ
cana-3796	451	12	scene	scene	NOUN
cana-3796	451	13	text	text	NOUN
cana-3796	451	14	recognition	recognition	NOUN
cana-3796	451	15	with	with	ADP
cana-3796	451	16	a	a	DET
cana-3796	451	17	large	large	ADJ
cana-3796	451	18	character	character	NOUN
cana-3796	451	19	set	set	NOUN
cana-3796	451	20	.	.	PUNCT
cana-3796	451	21	"	"	PUNCT
cana-3796	451	22	ieee	ieee	NOUN
cana-3796	451	23	transactions	transaction	NOUN
cana-3796	451	24	on	on	ADP
cana-3796	451	25	circuits	circuit	NOUN
cana-3796	451	26	and	and	CCONJ
cana-3796	451	27	systems	system	NOUN
cana-3796	451	28	for	for	ADP
cana-3796	451	29	video	video	NOUN
cana-3796	451	30	technology	technology	NOUN
cana-3796	451	31	32	32	NUM
cana-3796	451	32	(	(	PUNCT
cana-3796	451	33	8)	8)	NUM
cana-3796	451	34	:	:	PUNCT
cana-3796	451	35	5374	5374	NUM
cana-3796	451	36	-	-	SYM
cana-3796	451	37	5385	5385	NUM
cana-3796	451	38	.	.	PUNCT
cana-3796	452	1	https://doi.org/10.1109/tcsvt.2022.3146240	https://doi.org/10.1109/tcsvt.2022.3146240	PROPN
cana-3796	452	2	.	.	PUNCT
cana-3796	453	1	[	[	X
cana-3796	453	2	36	36	NUM
cana-3796	453	3	]	]	X
cana-3796	453	4	karthikeyan	karthikeyan	PROPN
cana-3796	453	5	,	,	PUNCT
cana-3796	453	6	s.	s.	PROPN
cana-3796	453	7	,	,	PUNCT
cana-3796	453	8	de	de	PROPN
cana-3796	453	9	herrera	herrera	NOUN
cana-3796	453	10	,	,	PUNCT
cana-3796	453	11	a.	a.	PROPN
cana-3796	453	12	g.	g.	PROPN
cana-3796	453	13	s.	s.	PROPN
cana-3796	453	14	,	,	PUNCT
cana-3796	453	15	doctor	doctor	NOUN
cana-3796	453	16	,	,	PUNCT
cana-3796	453	17	f.	f.	PROPN
cana-3796	453	18	,	,	PUNCT
cana-3796	453	19	&	&	CCONJ
cana-3796	453	20	mirza	mirza	PROPN
cana-3796	453	21	,	,	PUNCT
cana-3796	453	22	a.	a.	NOUN
cana-3796	453	23	2022	2022	NUM
cana-3796	453	24	.	.	PUNCT
cana-3796	454	1	"	"	PUNCT
cana-3796	454	2	an	an	DET
cana-3796	454	3	ocr	ocr	ADJ
cana-3796	454	4	post	post	ADJ
cana-3796	454	5	-	-	ADJ
cana-3796	454	6	correction	correction	ADJ
cana-3796	454	7	approach	approach	NOUN
cana-3796	454	8	using	use	VERB
cana-3796	454	9	deep	deep	ADJ
cana-3796	454	10	learning	learning	NOUN
cana-3796	454	11	for	for	ADP
cana-3796	454	12	processing	process	VERB
cana-3796	454	13	medical	medical	ADJ
cana-3796	454	14	reports	report	NOUN
cana-3796	454	15	.	.	PUNCT
cana-3796	454	16	"	"	PUNCT
cana-3796	455	1	ieee	ieee	NOUN
cana-3796	455	2	transactions	transaction	NOUN
cana-3796	455	3	on	on	ADP
cana-3796	455	4	circuits	circuit	NOUN
cana-3796	455	5	and	and	CCONJ
cana-3796	455	6	systems	system	NOUN
cana-3796	455	7	for	for	ADP
cana-3796	455	8	video	video	NOUN
cana-3796	455	9	technology	technology	NOUN
cana-3796	455	10	32	32	NUM
cana-3796	455	11	(	(	PUNCT
cana-3796	455	12	5	5	NUM
cana-3796	455	13	):	):	PUNCT
cana-3796	455	14	2574	2574	NUM
cana-3796	455	15	-	-	SYM
cana-3796	455	16	2581	2581	NUM
cana-3796	455	17	.	.	PUNCT
cana-3796	456	1	https://doi.org/10.1109/tcsvt.2021.3087641	https://doi.org/10.1109/tcsvt.2021.3087641	PROPN
cana-3796	456	2	.	.	PUNCT
cana-3796	457	1	[	[	X
cana-3796	457	2	37	37	NUM
cana-3796	457	3	]	]	X
cana-3796	457	4	ademola	ademola	PROPN
cana-3796	457	5	,	,	PUNCT
cana-3796	457	6	o.	o.	PROPN
cana-3796	457	7	a.	a.	PROPN
cana-3796	457	8	,	,	PUNCT
cana-3796	457	9	petlenkov	petlenkov	PROPN
cana-3796	457	10	,	,	PUNCT
cana-3796	457	11	e.	e.	PROPN
cana-3796	457	12	,	,	PUNCT
cana-3796	457	13	&	&	CCONJ
cana-3796	457	14	leier	leier	NOUN
cana-3796	457	15	,	,	PUNCT
cana-3796	457	16	m.	m.	NOUN
cana-3796	457	17	2023	2023	NUM
cana-3796	457	18	.	.	PUNCT
cana-3796	458	1	"	"	PUNCT
cana-3796	458	2	resource	resource	NOUN
cana-3796	458	3	-	-	PUNCT
cana-3796	458	4	aware	aware	ADJ
cana-3796	458	5	scene	scene	NOUN
cana-3796	458	6	text	text	NOUN
cana-3796	458	7	recognition	recognition	NOUN
cana-3796	458	8	using	use	VERB
cana-3796	458	9	learned	learn	VERB
cana-3796	458	10	features	feature	NOUN
cana-3796	458	11	,	,	PUNCT
cana-3796	458	12	quantization	quantization	NOUN
cana-3796	458	13	,	,	PUNCT
cana-3796	458	14	and	and	CCONJ
cana-3796	458	15	contour	contour	NOUN
cana-3796	458	16	-	-	PUNCT
cana-3796	458	17	based	base	VERB
cana-3796	458	18	character	character	NOUN
cana-3796	458	19	extraction	extraction	NOUN
cana-3796	458	20	.	.	PUNCT
cana-3796	458	21	"	"	PUNCT
cana-3796	459	1	ieee	ieee	NOUN
cana-3796	459	2	access	access	NOUN
cana-3796	459	3	11	11	NUM
cana-3796	459	4	:	:	SYM
cana-3796	459	5	5686556874	5686556874	NUM
cana-3796	459	6	.	.	PUNCT
cana-3796	460	1	https://doi.org/10.1109/access.2023.3283931	https://doi.org/10.1109/access.2023.3283931	PROPN
cana-3796	460	2	.	.	PUNCT
cana-3796	461	1	https://doi.org/10.1109/access.2022.3144844	https://doi.org/10.1109/access.2022.3144844	PROPN
cana-3796	461	2	https://doi.org/10.1109/jlt.2023.3270382	https://doi.org/10.1109/jlt.2023.3270382	VERB
cana-3796	461	3	https://doi.org/10.1109/access.2023.3240439	https://doi.org/10.1109/access.2023.3240439	PROPN
cana-3796	461	4	https://doi.org/10.1109/tits.2021.3055946	https://doi.org/10.1109/tits.2021.3055946	PROPN
cana-3796	461	5	https://doi.org/10.1109/tits.2021.3130898	https://doi.org/10.1109/tits.2021.3130898	PROPN
cana-3796	461	6	https://doi.org/10.1109/access.2023.3283340	https://doi.org/10.1109/access.2023.3283340	PROPN
cana-3796	461	7	https://doi.org/10.1109/jsen.2023.3318248	https://doi.org/10.1109/jsen.2023.3318248	PROPN
cana-3796	461	8	https://doi.org/10.1109/access.2022.3178192	https://doi.org/10.1109/access.2022.3178192	PROPN
cana-3796	461	9	https://doi.org/10.1109/tits.2023.3244827	https://doi.org/10.1109/tits.2023.3244827	PROPN
cana-3796	461	10	https://doi.org/10.1109/tmm.2022.3183386	https://doi.org/10.1109/tmm.2022.3183386	VERB
cana-3796	461	11	https://doi.org/10.1109/tmm.2022.3171108	https://doi.org/10.1109/tmm.2022.3171108	ADV
cana-3796	461	12	https://doi.org/10.1109/access.2023.3321807	https://doi.org/10.1109/access.2023.3321807	PROPN
cana-3796	461	13	https://doi.org/10.1109/access.2022.3202893	https://doi.org/10.1109/access.2022.3202893	PROPN
cana-3796	461	14	https://doi.org/10.1109/tcsvt.2022.3146240	https://doi.org/10.1109/tcsvt.2022.3146240	PROPN
cana-3796	461	15	https://doi.org/10.1109/tcsvt.2021.3087641	https://doi.org/10.1109/tcsvt.2021.3087641	PROPN
cana-3796	461	16	https://doi.org/10.1109/access.2023.3283931	https://doi.org/10.1109/access.2023.3283931	PROPN
cana-3796	461	17	communications	communication	NOUN
cana-3796	461	18	on	on	ADP
cana-3796	461	19	applied	apply	VERB
cana-3796	461	20	nonlinear	nonlinear	ADJ
cana-3796	461	21	analysis	analysis	NOUN
cana-3796	461	22	issn	issn	NOUN
cana-3796	461	23	:	:	PUNCT
cana-3796	461	24	1074	1074	NUM
cana-3796	461	25	-	-	PUNCT
cana-3796	461	26	133x	133x	NUM
cana-3796	461	27	vol	vol	NOUN
cana-3796	461	28	32	32	NUM
cana-3796	461	29	no	no	NOUN
cana-3796	461	30	.	.	PUNCT
cana-3796	462	1	8s	8s	PROPN
cana-3796	462	2	(	(	PUNCT
cana-3796	462	3	2025	2025	NUM
cana-3796	462	4	)	)	PUNCT
cana-3796	462	5	762	762	NUM
cana-3796	462	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3796	463	1	[	[	X
cana-3796	463	2	38	38	NUM
cana-3796	463	3	]	]	X
cana-3796	463	4	vinotheni	vinotheni	PROPN
cana-3796	463	5	,	,	PUNCT
cana-3796	463	6	c.	c.	PROPN
cana-3796	463	7	,	,	PUNCT
cana-3796	463	8	&	&	CCONJ
cana-3796	463	9	pandian	pandian	PROPN
cana-3796	463	10	,	,	PUNCT
cana-3796	463	11	s.	s.	PROPN
cana-3796	463	12	l.	l.	PROPN
cana-3796	463	13	2023	2023	NUM
cana-3796	463	14	.	.	PUNCT
cana-3796	464	1	"	"	PUNCT
cana-3796	464	2	end	end	VERB
cana-3796	464	3	-	-	PUNCT
cana-3796	464	4	to	to	ADP
cana-3796	464	5	-	-	PUNCT
cana-3796	464	6	end	end	NOUN
cana-3796	464	7	deep	deep	ADJ
cana-3796	464	8	-	-	PUNCT
cana-3796	464	9	learning	learning	NOUN
cana-3796	464	10	-	-	PUNCT
cana-3796	464	11	based	base	VERB
cana-3796	464	12	tamil	tamil	PROPN
cana-3796	464	13	handwritten	handwritten	ADJ
cana-3796	464	14	document	document	NOUN
cana-3796	464	15	recognition	recognition	NOUN
cana-3796	464	16	and	and	CCONJ
cana-3796	464	17	classification	classification	NOUN
cana-3796	464	18	model	model	NOUN
cana-3796	464	19	.	.	PUNCT
cana-3796	464	20	"	"	PUNCT
cana-3796	465	1	ieee	ieee	NOUN
cana-3796	465	2	access	access	NOUN
cana-3796	465	3	11	11	NUM
cana-3796	465	4	:	:	PUNCT
cana-3796	465	5	43195	43195	NUM
cana-3796	465	6	-	-	SYM
cana-3796	465	7	43204	43204	NUM
cana-3796	465	8	.	.	PUNCT
cana-3796	466	1	https://doi.org/10.1109/access.2023.3270895	https://doi.org/10.1109/access.2023.3270895	PROPN
cana-3796	466	2	.	.	PUNCT
cana-3796	467	1	[	[	X
cana-3796	467	2	39	39	NUM
cana-3796	467	3	]	]	X
cana-3796	467	4	mrinalini	mrinalini	PROPN
cana-3796	467	5	,	,	PUNCT
cana-3796	467	6	k.	k.	PROPN
cana-3796	467	7	,	,	PUNCT
cana-3796	467	8	vijayalakshmi	vijayalakshmi	NOUN
cana-3796	467	9	,	,	PUNCT
cana-3796	467	10	p.	p.	NOUN
cana-3796	467	11	,	,	PUNCT
cana-3796	467	12	&	&	CCONJ
cana-3796	467	13	nagarajan	nagarajan	PROPN
cana-3796	467	14	,	,	PUNCT
cana-3796	467	15	t.	t.	NOUN
cana-3796	467	16	2022	2022	NUM
cana-3796	467	17	.	.	PUNCT
cana-3796	468	1	"	"	PUNCT
cana-3796	468	2	sbsim	sbsim	NOUN
cana-3796	468	3	:	:	PUNCT
cana-3796	468	4	a	a	DET
cana-3796	468	5	sentence	sentence	NOUN
cana-3796	468	6	-	-	PUNCT
cana-3796	468	7	bert	bert	NOUN
cana-3796	468	8	similarity	similarity	NOUN
cana-3796	468	9	-	-	PUNCT
cana-3796	468	10	based	base	VERB
cana-3796	468	11	evaluation	evaluation	NOUN
cana-3796	468	12	metric	metric	NOUN
cana-3796	468	13	for	for	ADP
cana-3796	468	14	indian	indian	ADJ
cana-3796	468	15	language	language	NOUN
cana-3796	468	16	neural	neural	ADJ
cana-3796	468	17	machine	machine	NOUN
cana-3796	468	18	translation	translation	NOUN
cana-3796	468	19	systems	system	NOUN
cana-3796	468	20	.	.	PUNCT
cana-3796	468	21	"	"	PUNCT
cana-3796	468	22	ieee	ieee	PROPN
cana-3796	468	23	/	/	SYM
cana-3796	468	24	acm	acm	NOUN
cana-3796	468	25	transactions	transaction	NOUN
cana-3796	468	26	on	on	ADP
cana-3796	468	27	audio	audio	NOUN
cana-3796	468	28	,	,	PUNCT
cana-3796	468	29	speech	speech	NOUN
cana-3796	468	30	,	,	PUNCT
cana-3796	468	31	and	and	CCONJ
cana-3796	468	32	language	language	NOUN
cana-3796	468	33	processing	processing	NOUN
cana-3796	468	34	30	30	NUM
cana-3796	468	35	:	:	PUNCT
cana-3796	468	36	1396	1396	NUM
cana-3796	468	37	-	-	SYM
cana-3796	468	38	1406	1406	NUM
cana-3796	468	39	.	.	PUNCT
cana-3796	468	40	https://doi.org/10.1109/taslp.2022	https://doi.org/10.1109/taslp.2022	NOUN
cana-3796	469	1	[	[	X
cana-3796	469	2	40	40	NUM
cana-3796	469	3	]	]	X
cana-3796	469	4	padmavathi	padmavathi	PROPN
cana-3796	469	5	,	,	PUNCT
cana-3796	469	6	p.	p.	NOUN
cana-3796	469	7	,	,	PUNCT
cana-3796	469	8	mahadas	mahadas	PROPN
cana-3796	469	9	,	,	PUNCT
cana-3796	469	10	b.	b.	PROPN
cana-3796	469	11	b.	b.	PROPN
cana-3796	469	12	,	,	PUNCT
cana-3796	469	13	kalluri	kalluri	PROPN
cana-3796	469	14	,	,	PUNCT
cana-3796	469	15	s.	s.	PROPN
cana-3796	469	16	s.	s.	PROPN
cana-3796	469	17	,	,	PUNCT
cana-3796	469	18	devarapu	devarapu	PROPN
cana-3796	469	19	,	,	PUNCT
cana-3796	469	20	p.	p.	PROPN
cana-3796	469	21	,	,	PUNCT
cana-3796	469	22	&	&	CCONJ
cana-3796	469	23	bandi	bandi	PROPN
cana-3796	469	24	,	,	PUNCT
cana-3796	469	25	s.	s.	PROPN
cana-3796	469	26	l.	l.	PROPN
cana-3796	469	27	(	(	PUNCT
cana-3796	469	28	2023	2023	NUM
cana-3796	469	29	,	,	PUNCT
cana-3796	469	30	may	may	AUX
cana-3796	469	31	)	)	PUNCT
cana-3796	469	32	.	.	PUNCT
cana-3796	470	1	optical	optical	ADJ
cana-3796	470	2	character	character	NOUN
cana-3796	470	3	recognition	recognition	NOUN
cana-3796	470	4	and	and	CCONJ
cana-3796	470	5	text	text	NOUN
cana-3796	470	6	to	to	ADP
cana-3796	470	7	speech	speech	NOUN
cana-3796	470	8	generation	generation	NOUN
cana-3796	470	9	system	system	NOUN
cana-3796	470	10	using	use	VERB
cana-3796	470	11	machine	machine	NOUN
cana-3796	470	12	learning	learning	NOUN
cana-3796	470	13	.	.	PUNCT
cana-3796	471	1	in	in	ADP
cana-3796	471	2	2023	2023	NUM
cana-3796	471	3	2nd	2nd	ADJ
cana-3796	471	4	international	international	ADJ
cana-3796	471	5	conference	conference	NOUN
cana-3796	471	6	on	on	ADP
cana-3796	471	7	applied	apply	VERB
cana-3796	471	8	artificial	artificial	ADJ
cana-3796	471	9	intelligence	intelligence	NOUN
cana-3796	471	10	and	and	CCONJ
cana-3796	471	11	computing	computing	NOUN
cana-3796	471	12	(	(	PUNCT
cana-3796	471	13	icaaic	icaaic	ADJ
cana-3796	471	14	)	)	PUNCT
cana-3796	471	15	(	(	PUNCT
cana-3796	471	16	pp	pp	X
cana-3796	471	17	.	.	PUNCT
cana-3796	472	1	1	1	NUM
cana-3796	472	2	-	-	SYM
cana-3796	472	3	6	6	NUM
cana-3796	472	4	)	)	PUNCT
cana-3796	472	5	.	.	PUNCT
cana-3796	473	1	ieee	ieee	PROPN
cana-3796	473	2	.	.	PUNCT
cana-3796	474	1	https://doi.org/10.1109/access.2023.3270895	https://doi.org/10.1109/access.2023.3270895	PROPN
cana-3796	474	2	https://doi.org/10.1109/taslp.2022	https://doi.org/10.1109/taslp.2022	NOUN