id	sid	tid	token	lemma	pos
cana-2747	1	1	communications	communication	NOUN
cana-2747	1	2	on	on	ADP
cana-2747	1	3	applied	apply	VERB
cana-2747	1	4	nonlinear	nonlinear	ADJ
cana-2747	1	5	analysis	analysis	NOUN
cana-2747	1	6	issn	issn	NOUN
cana-2747	1	7	:	:	PUNCT
cana-2747	1	8	1074	1074	NUM
cana-2747	1	9	-	-	PUNCT
cana-2747	1	10	133x	133x	NUM
cana-2747	1	11	vol	vol	NOUN
cana-2747	1	12	32	32	NUM
cana-2747	1	13	no	no	NOUN
cana-2747	1	14	.	.	PUNCT
cana-2747	2	1	4s	4s	NUM
cana-2747	2	2	(	(	PUNCT
cana-2747	2	3	2025	2025	NUM
cana-2747	2	4	)	)	PUNCT
cana-2747	2	5	168	168	NUM
cana-2747	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	2	7	towards	towards	ADP
cana-2747	2	8	improved	improve	VERB
cana-2747	2	9	biometric	biometric	ADJ
cana-2747	2	10	security	security	NOUN
cana-2747	2	11	:	:	PUNCT
cana-2747	2	12	eeg	eeg	NOUN
cana-2747	2	13	-	-	PUNCT
cana-2747	2	14	based	base	VERB
cana-2747	2	15	person	person	NOUN
cana-2747	2	16	identification	identification	NOUN
cana-2747	2	17	enhanced	enhance	VERB
cana-2747	2	18	by	by	ADP
cana-2747	2	19	deep	deep	ADJ
cana-2747	2	20	learning	learning	NOUN
cana-2747	2	21	and	and	CCONJ
cana-2747	2	22	facial	facial	ADJ
cana-2747	2	23	recognition	recognition	NOUN
cana-2747	2	24	shalu	shalu	PROPN
cana-2747	2	25	verma1	verma1	PROPN
cana-2747	2	26	,	,	PUNCT
cana-2747	2	27	sanjeev	sanjeev	PROPN
cana-2747	2	28	indora2	indora2	PROPN
cana-2747	2	29	,	,	PUNCT
cana-2747	2	30	rohtash	rohtash	ADJ
cana-2747	2	31	dhiman3	dhiman3	NOUN
cana-2747	2	32	1research	1research	NUM
cana-2747	2	33	scholar	scholar	NOUN
cana-2747	2	34	,	,	PUNCT
cana-2747	2	35	department	department	NOUN
cana-2747	2	36	of	of	ADP
cana-2747	2	37	computer	computer	NOUN
cana-2747	2	38	science	science	NOUN
cana-2747	2	39	and	and	CCONJ
cana-2747	2	40	engineering	engineering	NOUN
cana-2747	2	41	,	,	PUNCT
cana-2747	2	42	deenbandhu	deenbandhu	NOUN
cana-2747	2	43	,	,	PUNCT
cana-2747	2	44	chhotu	chhotu	PROPN
cana-2747	2	45	ram	ram	PROPN
cana-2747	2	46	university	university	PROPN
cana-2747	2	47	of	of	ADP
cana-2747	2	48	science	science	NOUN
cana-2747	2	49	and	and	CCONJ
cana-2747	2	50	technology	technology	NOUN
cana-2747	2	51	,	,	PUNCT
cana-2747	2	52	murthal	murthal	NOUN
cana-2747	2	53	,	,	PUNCT
cana-2747	2	54	sonepat	sonepat	NOUN
cana-2747	2	55	,	,	PUNCT
cana-2747	2	56	haryana	haryana	PROPN
cana-2747	2	57	,	,	PUNCT
cana-2747	2	58	(	(	PUNCT
cana-2747	2	59	india	india	PROPN
cana-2747	2	60	)	)	PUNCT
cana-2747	2	61	.	.	PUNCT
cana-2747	3	1	2associate	2associate	NUM
cana-2747	3	2	professor	professor	NOUN
cana-2747	3	3	,	,	PUNCT
cana-2747	3	4	department	department	NOUN
cana-2747	3	5	of	of	ADP
cana-2747	3	6	computer	computer	NOUN
cana-2747	3	7	science	science	NOUN
cana-2747	3	8	and	and	CCONJ
cana-2747	3	9	engineering	engineering	NOUN
cana-2747	3	10	,	,	PUNCT
cana-2747	3	11	deenbandhu	deenbandhu	NOUN
cana-2747	3	12	,	,	PUNCT
cana-2747	3	13	chhotu	chhotu	PROPN
cana-2747	3	14	ram	ram	PROPN
cana-2747	3	15	university	university	PROPN
cana-2747	3	16	of	of	ADP
cana-2747	3	17	science	science	NOUN
cana-2747	3	18	and	and	CCONJ
cana-2747	3	19	technology	technology	NOUN
cana-2747	3	20	,	,	PUNCT
cana-2747	3	21	murthal	murthal	NOUN
cana-2747	3	22	,	,	PUNCT
cana-2747	3	23	sonepat	sonepat	NOUN
cana-2747	3	24	,	,	PUNCT
cana-2747	3	25	haryana	haryana	PROPN
cana-2747	3	26	,	,	PUNCT
cana-2747	3	27	(	(	PUNCT
cana-2747	3	28	india	india	PROPN
cana-2747	3	29	)	)	PUNCT
cana-2747	3	30	.	.	PUNCT
cana-2747	4	1	3assistant	3assistant	NUM
cana-2747	4	2	professor	professor	NOUN
cana-2747	4	3	,	,	PUNCT
cana-2747	4	4	department	department	NOUN
cana-2747	4	5	of	of	ADP
cana-2747	4	6	computer	computer	NOUN
cana-2747	4	7	science	science	NOUN
cana-2747	4	8	and	and	CCONJ
cana-2747	4	9	engineering	engineering	NOUN
cana-2747	4	10	,	,	PUNCT
cana-2747	4	11	deenbandhu	deenbandhu	NOUN
cana-2747	4	12	,	,	PUNCT
cana-2747	4	13	chhotu	chhotu	PROPN
cana-2747	4	14	ram	ram	PROPN
cana-2747	4	15	university	university	PROPN
cana-2747	4	16	of	of	ADP
cana-2747	4	17	science	science	NOUN
cana-2747	4	18	and	and	CCONJ
cana-2747	4	19	technology	technology	NOUN
cana-2747	4	20	,	,	PUNCT
cana-2747	4	21	murthal	murthal	NOUN
cana-2747	4	22	,	,	PUNCT
cana-2747	4	23	sonepat	sonepat	NOUN
cana-2747	4	24	,	,	PUNCT
cana-2747	4	25	haryana	haryana	PROPN
cana-2747	4	26	,	,	PUNCT
cana-2747	4	27	(	(	PUNCT
cana-2747	4	28	india	india	PROPN
cana-2747	4	29	)	)	PUNCT
cana-2747	4	30	.	.	PUNCT
cana-2747	5	1	corresponding	correspond	VERB
cana-2747	5	2	email	email	NOUN
cana-2747	5	3	:	:	PUNCT
cana-2747	5	4	19001901010shalu@dcrustm.org	19001901010shalu@dcrustm.org	NUM
cana-2747	5	5	article	article	NOUN
cana-2747	5	6	history	history	NOUN
cana-2747	5	7	:	:	PUNCT
cana-2747	5	8	received	receive	VERB
cana-2747	5	9	:	:	PUNCT
cana-2747	5	10	20	20	NUM
cana-2747	5	11	-	-	SYM
cana-2747	5	12	09	09	NUM
cana-2747	5	13	-	-	PUNCT
cana-2747	5	14	2024	2024	NUM
cana-2747	5	15	revised	revise	VERB
cana-2747	5	16	:	:	PUNCT
cana-2747	5	17	25	25	NUM
cana-2747	5	18	-	-	SYM
cana-2747	5	19	11	11	NUM
cana-2747	5	20	-	-	PUNCT
cana-2747	5	21	2024	2024	NUM
cana-2747	5	22	accepted	accept	VERB
cana-2747	5	23	:	:	PUNCT
cana-2747	5	24	02	02	NUM
cana-2747	5	25	-	-	SYM
cana-2747	5	26	12	12	NUM
cana-2747	5	27	-	-	PUNCT
cana-2747	5	28	2024	2024	NUM
cana-2747	5	29	abstract	abstract	NOUN
cana-2747	5	30	:	:	PUNCT
cana-2747	5	31	due	due	ADP
cana-2747	5	32	to	to	ADP
cana-2747	5	33	their	their	PRON
cana-2747	5	34	inherent	inherent	ADJ
cana-2747	5	35	qualities	quality	NOUN
cana-2747	5	36	of	of	ADP
cana-2747	5	37	being	be	AUX
cana-2747	5	38	secretive	secretive	ADJ
cana-2747	5	39	,	,	PUNCT
cana-2747	5	40	vivid	vivid	ADJ
cana-2747	5	41	,	,	PUNCT
cana-2747	5	42	and	and	CCONJ
cana-2747	5	43	unpredictable	unpredictable	ADJ
cana-2747	5	44	,	,	PUNCT
cana-2747	5	45	electroencephalogram	electroencephalogram	X
cana-2747	5	46	(	(	PUNCT
cana-2747	5	47	eeg	eeg	NOUN
cana-2747	5	48	)	)	PUNCT
cana-2747	5	49	signals	signal	NOUN
cana-2747	5	50	are	be	AUX
cana-2747	5	51	considered	consider	VERB
cana-2747	5	52	a	a	DET
cana-2747	5	53	valuable	valuable	ADJ
cana-2747	5	54	tool	tool	NOUN
cana-2747	5	55	for	for	ADP
cana-2747	5	56	security	security	NOUN
cana-2747	5	57	-	-	PUNCT
cana-2747	5	58	related	relate	VERB
cana-2747	5	59	identification	identification	NOUN
cana-2747	5	60	.	.	PUNCT
cana-2747	6	1	however	however	ADV
cana-2747	6	2	,	,	PUNCT
cana-2747	6	3	research	research	NOUN
cana-2747	6	4	on	on	ADP
cana-2747	6	5	using	use	VERB
cana-2747	6	6	eeg	eeg	NOUN
cana-2747	6	7	signals	signal	NOUN
cana-2747	6	8	for	for	ADP
cana-2747	6	9	person	person	NOUN
cana-2747	6	10	identification	identification	NOUN
cana-2747	6	11	is	be	AUX
cana-2747	6	12	still	still	ADV
cana-2747	6	13	in	in	ADP
cana-2747	6	14	its	its	PRON
cana-2747	6	15	early	early	ADJ
cana-2747	6	16	stages	stage	NOUN
cana-2747	6	17	.	.	PUNCT
cana-2747	7	1	the	the	DET
cana-2747	7	2	challenges	challenge	NOUN
cana-2747	7	3	lie	lie	VERB
cana-2747	7	4	in	in	ADP
cana-2747	7	5	decoding	decode	VERB
cana-2747	7	6	these	these	DET
cana-2747	7	7	signals	signal	NOUN
cana-2747	7	8	accurately	accurately	ADV
cana-2747	7	9	and	and	CCONJ
cana-2747	7	10	implementing	implement	VERB
cana-2747	7	11	effective	effective	ADJ
cana-2747	7	12	eeg	eeg	NOUN
cana-2747	7	13	-	-	PUNCT
cana-2747	7	14	based	base	VERB
cana-2747	7	15	identification	identification	NOUN
cana-2747	7	16	methods	method	NOUN
cana-2747	7	17	.	.	PUNCT
cana-2747	8	1	in	in	ADP
cana-2747	8	2	recent	recent	ADJ
cana-2747	8	3	years	year	NOUN
cana-2747	8	4	,	,	PUNCT
cana-2747	8	5	eeg	eeg	PROPN
cana-2747	8	6	has	have	AUX
cana-2747	8	7	been	be	AUX
cana-2747	8	8	at	at	ADP
cana-2747	8	9	the	the	DET
cana-2747	8	10	forefront	forefront	NOUN
cana-2747	8	11	of	of	ADP
cana-2747	8	12	scientific	scientific	ADJ
cana-2747	8	13	research	research	NOUN
cana-2747	8	14	on	on	ADP
cana-2747	8	15	user	user	NOUN
cana-2747	8	16	authentication	authentication	NOUN
cana-2747	8	17	(	(	PUNCT
cana-2747	8	18	ua	ua	PROPN
cana-2747	8	19	)	)	PUNCT
cana-2747	8	20	,	,	PUNCT
cana-2747	8	21	leading	lead	VERB
cana-2747	8	22	to	to	ADP
cana-2747	8	23	innovative	innovative	ADJ
cana-2747	8	24	experiments	experiment	NOUN
cana-2747	8	25	that	that	PRON
cana-2747	8	26	aim	aim	VERB
cana-2747	8	27	to	to	PART
cana-2747	8	28	identify	identify	VERB
cana-2747	8	29	individuals	individual	NOUN
cana-2747	8	30	based	base	VERB
cana-2747	8	31	on	on	ADP
cana-2747	8	32	their	their	PRON
cana-2747	8	33	unique	unique	ADJ
cana-2747	8	34	brain	brain	NOUN
cana-2747	8	35	activity	activity	NOUN
cana-2747	8	36	in	in	ADP
cana-2747	8	37	specific	specific	ADJ
cana-2747	8	38	usage	usage	NOUN
cana-2747	8	39	scenarios	scenario	NOUN
cana-2747	8	40	.	.	PUNCT
cana-2747	9	1	the	the	DET
cana-2747	9	2	utilization	utilization	NOUN
cana-2747	9	3	of	of	ADP
cana-2747	9	4	eeg	eeg	NOUN
cana-2747	9	5	signals	signal	NOUN
cana-2747	9	6	,	,	PUNCT
cana-2747	9	7	which	which	PRON
cana-2747	9	8	are	be	AUX
cana-2747	9	9	derived	derive	VERB
cana-2747	9	10	from	from	ADP
cana-2747	9	11	brain	brain	NOUN
cana-2747	9	12	activity	activity	NOUN
cana-2747	9	13	,	,	PUNCT
cana-2747	9	14	holds	hold	VERB
cana-2747	9	15	great	great	ADJ
cana-2747	9	16	potential	potential	NOUN
cana-2747	9	17	for	for	ADP
cana-2747	9	18	addressing	address	VERB
cana-2747	9	19	contemporary	contemporary	ADJ
cana-2747	9	20	security	security	NOUN
cana-2747	9	21	concerns	concern	NOUN
cana-2747	9	22	in	in	ADP
cana-2747	9	23	conventional	conventional	ADJ
cana-2747	9	24	knowledge	knowledge	NOUN
cana-2747	9	25	-	-	PUNCT
cana-2747	9	26	based	base	VERB
cana-2747	9	27	user	user	NOUN
cana-2747	9	28	authentication	authentication	NOUN
cana-2747	9	29	,	,	PUNCT
cana-2747	9	30	including	include	VERB
cana-2747	9	31	the	the	DET
cana-2747	9	32	vulnerability	vulnerability	NOUN
cana-2747	9	33	to	to	PART
cana-2747	9	34	shoulder	shoulder	VERB
cana-2747	9	35	surfing	surfing	NOUN
cana-2747	9	36	.	.	PUNCT
cana-2747	10	1	this	this	DET
cana-2747	10	2	research	research	NOUN
cana-2747	10	3	investigates	investigate	VERB
cana-2747	10	4	a	a	DET
cana-2747	10	5	new	new	ADJ
cana-2747	10	6	method	method	NOUN
cana-2747	10	7	for	for	ADP
cana-2747	10	8	person	person	NOUN
cana-2747	10	9	identification	identification	NOUN
cana-2747	10	10	that	that	PRON
cana-2747	10	11	combines	combine	VERB
cana-2747	10	12	electroencephalogram	electroencephalogram	NOUN
cana-2747	10	13	(	(	PUNCT
cana-2747	10	14	eeg	eeg	NOUN
cana-2747	10	15	)	)	PUNCT
cana-2747	10	16	signals	signal	NOUN
cana-2747	10	17	with	with	ADP
cana-2747	10	18	facial	facial	ADJ
cana-2747	10	19	video	video	NOUN
cana-2747	10	20	.	.	PUNCT
cana-2747	11	1	a	a	DET
cana-2747	11	2	hybrid	hybrid	ADJ
cana-2747	11	3	model	model	NOUN
cana-2747	11	4	is	be	AUX
cana-2747	11	5	proposed	propose	VERB
cana-2747	11	6	,	,	PUNCT
cana-2747	11	7	incorporating	incorporate	VERB
cana-2747	11	8	features	feature	NOUN
cana-2747	11	9	from	from	ADP
cana-2747	11	10	both	both	CCONJ
cana-2747	11	11	mobilenet	mobilenet	NOUN
cana-2747	11	12	and	and	CCONJ
cana-2747	11	13	a	a	DET
cana-2747	11	14	convolutional	convolutional	ADJ
cana-2747	11	15	neural	neural	ADJ
cana-2747	11	16	network	network	NOUN
cana-2747	11	17	with	with	ADP
cana-2747	11	18	long	long	ADJ
cana-2747	11	19	short	short	ADJ
cana-2747	11	20	-	-	PUNCT
cana-2747	11	21	term	term	NOUN
cana-2747	11	22	memory	memory	NOUN
cana-2747	11	23	(	(	PUNCT
cana-2747	11	24	lstm	lstm	PROPN
cana-2747	11	25	-	-	PUNCT
cana-2747	11	26	cnn	cnn	PROPN
cana-2747	11	27	)	)	PUNCT
cana-2747	11	28	architecture	architecture	NOUN
cana-2747	11	29	giving	give	VERB
cana-2747	11	30	a	a	DET
cana-2747	11	31	person	person	NOUN
cana-2747	11	32	identification	identification	NOUN
cana-2747	11	33	accuracy	accuracy	NOUN
cana-2747	11	34	of	of	ADP
cana-2747	11	35	99.81	99.81	NUM
cana-2747	11	36	%	%	NOUN
cana-2747	11	37	.	.	PUNCT
cana-2747	12	1	the	the	DET
cana-2747	12	2	model	model	NOUN
cana-2747	12	3	is	be	AUX
cana-2747	12	4	trained	train	VERB
cana-2747	12	5	and	and	CCONJ
cana-2747	12	6	tested	test	VERB
cana-2747	12	7	on	on	ADP
cana-2747	12	8	the	the	DET
cana-2747	12	9	'	'	PUNCT
cana-2747	12	10	deap	deap	ADJ
cana-2747	12	11	'	'	PUNCT
cana-2747	12	12	dataset	dataset	NOUN
cana-2747	12	13	to	to	PART
cana-2747	12	14	identify	identify	VERB
cana-2747	12	15	individuals	individual	NOUN
cana-2747	12	16	by	by	ADP
cana-2747	12	17	leveraging	leverage	VERB
cana-2747	12	18	unique	unique	ADJ
cana-2747	12	19	eeg	eeg	NOUN
cana-2747	12	20	patterns	pattern	NOUN
cana-2747	12	21	and	and	CCONJ
cana-2747	12	22	facial	facial	ADJ
cana-2747	12	23	features	feature	NOUN
cana-2747	12	24	,	,	PUNCT
cana-2747	12	25	thereby	thereby	ADV
cana-2747	12	26	improving	improve	VERB
cana-2747	12	27	biometric	biometric	ADJ
cana-2747	12	28	identification	identification	NOUN
cana-2747	12	29	through	through	ADP
cana-2747	12	30	the	the	DET
cana-2747	12	31	integration	integration	NOUN
cana-2747	12	32	of	of	ADP
cana-2747	12	33	these	these	DET
cana-2747	12	34	insights	insight	NOUN
cana-2747	12	35	.	.	PUNCT
cana-2747	13	1	keywords	keyword	NOUN
cana-2747	13	2	:	:	PUNCT
cana-2747	13	3	biometric	biometric	ADJ
cana-2747	13	4	identification	identification	NOUN
cana-2747	13	5	,	,	PUNCT
cana-2747	13	6	convolutional	convolutional	ADJ
cana-2747	13	7	neural	neural	ADJ
cana-2747	13	8	network(cnn	network(cnn	PROPN
cana-2747	13	9	)	)	PUNCT
cana-2747	13	10	,	,	PUNCT
cana-2747	13	11	long	long	ADV
cana-2747	13	12	shortterm	shortterm	PROPN
cana-2747	13	13	memory(lstm	memory(lstm	PROPN
cana-2747	13	14	)	)	PUNCT
cana-2747	13	15	,	,	PUNCT
cana-2747	13	16	mobilenet	mobilenet	NOUN
cana-2747	13	17	architecture	architecture	NOUN
cana-2747	13	18	.	.	PUNCT
cana-2747	14	1	1	1	X
cana-2747	14	2	.	.	X
cana-2747	14	3	introduction	introduction	NOUN
cana-2747	14	4	in	in	ADP
cana-2747	14	5	recent	recent	ADJ
cana-2747	14	6	times	time	NOUN
cana-2747	14	7	,	,	PUNCT
cana-2747	14	8	rapid	rapid	ADJ
cana-2747	14	9	advancements	advancement	NOUN
cana-2747	14	10	in	in	ADP
cana-2747	14	11	biometrics	biometric	NOUN
cana-2747	14	12	,	,	PUNCT
cana-2747	14	13	forensics	forensic	NOUN
cana-2747	14	14	,	,	PUNCT
cana-2747	14	15	and	and	CCONJ
cana-2747	14	16	informatics	informatic	NOUN
cana-2747	14	17	have	have	AUX
cana-2747	14	18	created	create	VERB
cana-2747	14	19	a	a	DET
cana-2747	14	20	conducive	conducive	ADJ
cana-2747	14	21	environment	environment	NOUN
cana-2747	14	22	for	for	ADP
cana-2747	14	23	safeguarding	safeguard	VERB
cana-2747	14	24	personal	personal	ADJ
cana-2747	14	25	privacy	privacy	NOUN
cana-2747	14	26	and	and	CCONJ
cana-2747	14	27	public	public	ADJ
cana-2747	14	28	security[1	security[1	PROPN
cana-2747	14	29	]	]	PUNCT
cana-2747	14	30	.	.	PUNCT
cana-2747	15	1	among	among	ADP
cana-2747	15	2	these	these	DET
cana-2747	15	3	developments	development	NOUN
cana-2747	15	4	,	,	PUNCT
cana-2747	15	5	biometric	biometric	ADJ
cana-2747	15	6	technology	technology	NOUN
cana-2747	15	7	has	have	AUX
cana-2747	15	8	emerged	emerge	VERB
cana-2747	15	9	as	as	ADP
cana-2747	15	10	a	a	DET
cana-2747	15	11	vital	vital	ADJ
cana-2747	15	12	tool	tool	NOUN
cana-2747	15	13	for	for	ADP
cana-2747	15	14	verifying	verify	VERB
cana-2747	15	15	individuals	individual	NOUN
cana-2747	15	16	'	'	PART
cana-2747	15	17	identities	identity	NOUN
cana-2747	15	18	.	.	PUNCT
cana-2747	16	1	biometrics	biometric	NOUN
cana-2747	16	2	involves	involve	VERB
cana-2747	16	3	the	the	DET
cana-2747	16	4	recognition	recognition	NOUN
cana-2747	16	5	of	of	ADP
cana-2747	16	6	people	people	NOUN
cana-2747	16	7	based	base	VERB
cana-2747	16	8	on	on	ADP
cana-2747	16	9	their	their	PRON
cana-2747	16	10	physiological	physiological	ADJ
cana-2747	16	11	or	or	CCONJ
cana-2747	16	12	behavioral	behavioral	ADJ
cana-2747	16	13	traits	trait	NOUN
cana-2747	16	14	,	,	PUNCT
cana-2747	16	15	including	include	VERB
cana-2747	16	16	features	feature	NOUN
cana-2747	16	17	like	like	ADP
cana-2747	16	18	face[2	face[2	PROPN
cana-2747	16	19	]	]	PUNCT
cana-2747	16	20	,	,	PUNCT
cana-2747	16	21	fingerprints[3	fingerprints[3	PROPN
cana-2747	16	22	]	]	X
cana-2747	16	23	,	,	PUNCT
cana-2747	16	24	iris	iris	NOUN
cana-2747	16	25	patterns[4	patterns[4	NOUN
cana-2747	16	26	]	]	NOUN
cana-2747	16	27	,	,	PUNCT
cana-2747	16	28	gait[5	gait[5	NOUN
cana-2747	16	29	]	]	X
cana-2747	16	30	,	,	PUNCT
cana-2747	16	31	signature[6	signature[6	NOUN
cana-2747	16	32	]	]	PUNCT
cana-2747	16	33	,	,	PUNCT
cana-2747	16	34	and	and	CCONJ
cana-2747	16	35	voice[7	voice[7	PROPN
cana-2747	16	36	]	]	PUNCT
cana-2747	16	37	.	.	PUNCT
cana-2747	17	1	biometric	biometric	ADJ
cana-2747	17	2	technologies	technology	NOUN
cana-2747	17	3	have	have	AUX
cana-2747	17	4	seamlessly	seamlessly	ADV
cana-2747	17	5	integrated	integrate	VERB
cana-2747	17	6	into	into	ADP
cana-2747	17	7	our	our	PRON
cana-2747	17	8	daily	daily	ADJ
cana-2747	17	9	lives	life	NOUN
cana-2747	17	10	,	,	PUNCT
cana-2747	17	11	finding	find	VERB
cana-2747	17	12	applications	application	NOUN
cana-2747	17	13	in	in	ADP
cana-2747	17	14	various	various	ADJ
cana-2747	17	15	fields	field	NOUN
cana-2747	17	16	.	.	PUNCT
cana-2747	18	1	for	for	ADP
cana-2747	18	2	instance	instance	NOUN
cana-2747	18	3	,	,	PUNCT
cana-2747	18	4	smart	smart	ADJ
cana-2747	18	5	phones	phone	NOUN
cana-2747	18	6	incorporate	incorporate	VERB
cana-2747	18	7	facial[8	facial[8	NOUN
cana-2747	18	8	]	]	PUNCT
cana-2747	18	9	and	and	CCONJ
cana-2747	18	10	fingerprint	fingerprint	NOUN
cana-2747	18	11	recognition	recognition	NOUN
cana-2747	18	12	for	for	ADP
cana-2747	18	13	security	security	NOUN
cana-2747	18	14	,	,	PUNCT
cana-2747	18	15	while	while	SCONJ
cana-2747	18	16	airport	airport	NOUN
cana-2747	18	17	security[9	security[9	NOUN
cana-2747	18	18	]	]	PUNCT
cana-2747	18	19	relies	rely	VERB
cana-2747	18	20	on	on	ADP
cana-2747	18	21	biometrics	biometric	NOUN
cana-2747	18	22	for	for	ADP
cana-2747	18	23	passport	passport	NOUN
cana-2747	18	24	control	control	NOUN
cana-2747	18	25	,	,	PUNCT
cana-2747	18	26	among	among	ADP
cana-2747	18	27	other	other	ADJ
cana-2747	18	28	uses	use	NOUN
cana-2747	18	29	.	.	PUNCT
cana-2747	19	1	the	the	DET
cana-2747	19	2	widespread	widespread	ADJ
cana-2747	19	3	adoption	adoption	NOUN
cana-2747	19	4	of	of	ADP
cana-2747	19	5	biometric	biometric	ADJ
cana-2747	19	6	systems	system	NOUN
cana-2747	19	7	depends	depend	VERB
cana-2747	19	8	on	on	ADP
cana-2747	19	9	the	the	DET
cana-2747	19	10	assurance	assurance	NOUN
cana-2747	19	11	of	of	ADP
cana-2747	19	12	reliable	reliable	ADJ
cana-2747	19	13	recognition	recognition	NOUN
cana-2747	19	14	processes	process	NOUN
cana-2747	19	15	and	and	CCONJ
cana-2747	19	16	the	the	DET
cana-2747	19	17	secure	secure	ADJ
cana-2747	19	18	management	management	NOUN
cana-2747	19	19	of	of	ADP
cana-2747	19	20	the	the	DET
cana-2747	19	21	mailto:19001901010shalu@dcrustm.org	mailto:19001901010shalu@dcrustm.org	ADJ
cana-2747	19	22	communications	communication	NOUN
cana-2747	19	23	on	on	ADP
cana-2747	19	24	applied	apply	VERB
cana-2747	19	25	nonlinear	nonlinear	ADJ
cana-2747	19	26	analysis	analysis	NOUN
cana-2747	19	27	issn	issn	NOUN
cana-2747	19	28	:	:	PUNCT
cana-2747	19	29	1074	1074	NUM
cana-2747	19	30	-	-	PUNCT
cana-2747	19	31	133x	133x	NUM
cana-2747	19	32	vol	vol	NOUN
cana-2747	19	33	32	32	NUM
cana-2747	19	34	no	no	NOUN
cana-2747	19	35	.	.	PUNCT
cana-2747	20	1	4s	4s	NUM
cana-2747	20	2	(	(	PUNCT
cana-2747	20	3	2025	2025	NUM
cana-2747	20	4	)	)	PUNCT
cana-2747	20	5	169	169	NUM
cana-2747	20	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2747	20	7	generated	generate	VERB
cana-2747	20	8	data	datum	NOUN
cana-2747	20	9	.	.	PUNCT
cana-2747	21	1	therefore	therefore	ADV
cana-2747	21	2	,	,	PUNCT
cana-2747	21	3	ensuring	ensure	VERB
cana-2747	21	4	privacy	privacy	NOUN
cana-2747	21	5	and	and	CCONJ
cana-2747	21	6	security	security	NOUN
cana-2747	21	7	has	have	AUX
cana-2747	21	8	become	become	VERB
cana-2747	21	9	pivotal	pivotal	ADJ
cana-2747	21	10	for	for	ADP
cana-2747	21	11	the	the	DET
cana-2747	21	12	success	success	NOUN
cana-2747	21	13	of	of	ADP
cana-2747	21	14	biometrics	biometric	NOUN
cana-2747	21	15	,	,	PUNCT
cana-2747	21	16	alongside	alongside	ADP
cana-2747	21	17	its	its	PRON
cana-2747	21	18	high	high	ADJ
cana-2747	21	19	accuracy	accuracy	NOUN
cana-2747	21	20	.	.	PUNCT
cana-2747	22	1	in	in	ADP
cana-2747	22	2	an	an	DET
cana-2747	22	3	era	era	NOUN
cana-2747	22	4	where	where	SCONJ
cana-2747	22	5	personal	personal	ADJ
cana-2747	22	6	information	information	NOUN
cana-2747	22	7	is	be	AUX
cana-2747	22	8	increasingly	increasingly	ADV
cana-2747	22	9	digitized[10	digitized[10	ADJ
cana-2747	22	10	]	]	PUNCT
cana-2747	22	11	and	and	CCONJ
cana-2747	22	12	shared	share	VERB
cana-2747	22	13	,	,	PUNCT
cana-2747	22	14	maintaining	maintain	VERB
cana-2747	22	15	the	the	DET
cana-2747	22	16	trust	trust	NOUN
cana-2747	22	17	of	of	ADP
cana-2747	22	18	individuals	individual	NOUN
cana-2747	22	19	in	in	ADP
cana-2747	22	20	biometric	biometric	ADJ
cana-2747	22	21	technology	technology	NOUN
cana-2747	22	22	is	be	AUX
cana-2747	22	23	essential	essential	ADJ
cana-2747	22	24	.	.	PUNCT
cana-2747	23	1	biometrics	biometric	NOUN
cana-2747	23	2	has	have	VERB
cana-2747	23	3	the	the	DET
cana-2747	23	4	potential	potential	NOUN
cana-2747	23	5	to	to	PART
cana-2747	23	6	improve	improve	VERB
cana-2747	23	7	security	security	NOUN
cana-2747	23	8	,	,	PUNCT
cana-2747	23	9	but	but	CCONJ
cana-2747	23	10	it	it	PRON
cana-2747	23	11	also	also	ADV
cana-2747	23	12	raises	raise	VERB
cana-2747	23	13	important	important	ADJ
cana-2747	23	14	concerns	concern	NOUN
cana-2747	23	15	about	about	ADP
cana-2747	23	16	protecting	protect	VERB
cana-2747	23	17	sensitive	sensitive	ADJ
cana-2747	23	18	data	datum	NOUN
cana-2747	23	19	and	and	CCONJ
cana-2747	23	20	preventing	prevent	VERB
cana-2747	23	21	unauthorized	unauthorized	ADJ
cana-2747	23	22	access[11	access[11	NOUN
cana-2747	23	23	]	]	PUNCT
cana-2747	23	24	.	.	PUNCT
cana-2747	24	1	the	the	DET
cana-2747	24	2	evolving	evolve	VERB
cana-2747	24	3	relationship	relationship	NOUN
cana-2747	24	4	between	between	ADP
cana-2747	24	5	biometrics	biometric	NOUN
cana-2747	24	6	,	,	PUNCT
cana-2747	24	7	privacy	privacy	NOUN
cana-2747	24	8	,	,	PUNCT
cana-2747	24	9	and	and	CCONJ
cana-2747	24	10	security	security	NOUN
cana-2747	24	11	highlights	highlight	NOUN
cana-2747	24	12	the	the	DET
cana-2747	24	13	crucial	crucial	ADJ
cana-2747	24	14	need	need	NOUN
cana-2747	24	15	for	for	ADP
cana-2747	24	16	ethical	ethical	ADJ
cana-2747	24	17	and	and	CCONJ
cana-2747	24	18	secure	secure	ADJ
cana-2747	24	19	practices	practice	NOUN
cana-2747	24	20	.	.	PUNCT
cana-2747	25	1	balancing	balance	VERB
cana-2747	25	2	individual	individual	ADJ
cana-2747	25	3	privacy	privacy	NOUN
cana-2747	25	4	with	with	ADP
cana-2747	25	5	public	public	ADJ
cana-2747	25	6	safety	safety	NOUN
cana-2747	25	7	remains	remain	VERB
cana-2747	25	8	a	a	DET
cana-2747	25	9	key	key	ADJ
cana-2747	25	10	challenge	challenge	NOUN
cana-2747	25	11	in	in	ADP
cana-2747	25	12	our	our	PRON
cana-2747	25	13	digital	digital	ADJ
cana-2747	25	14	world	world	NOUN
cana-2747	25	15	.	.	PUNCT
cana-2747	26	1	biometric	biometric	ADJ
cana-2747	26	2	technology	technology	NOUN
cana-2747	26	3	plays	play	VERB
cana-2747	26	4	a	a	DET
cana-2747	26	5	significant	significant	ADJ
cana-2747	26	6	role	role	NOUN
cana-2747	26	7	in	in	ADP
cana-2747	26	8	this	this	DET
cana-2747	26	9	landscape	landscape	NOUN
cana-2747	26	10	,	,	PUNCT
cana-2747	26	11	serving	serve	VERB
cana-2747	26	12	as	as	ADP
cana-2747	26	13	a	a	DET
cana-2747	26	14	tool	tool	NOUN
cana-2747	26	15	to	to	PART
cana-2747	26	16	protect	protect	VERB
cana-2747	26	17	both	both	PRON
cana-2747	26	18	personal	personal	ADJ
cana-2747	26	19	freedoms	freedom	NOUN
cana-2747	26	20	and	and	CCONJ
cana-2747	26	21	collective	collective	ADJ
cana-2747	26	22	well	well	ADV
cana-2747	26	23	-	-	PUNCT
cana-2747	26	24	being[12].traditional	being[12].traditional	ADJ
cana-2747	26	25	approaches	approach	NOUN
cana-2747	26	26	to	to	ADP
cana-2747	26	27	eeg	eeg	NOUN
cana-2747	26	28	-	-	PUNCT
cana-2747	26	29	based	base	VERB
cana-2747	26	30	person	person	NOUN
cana-2747	26	31	identification	identification	NOUN
cana-2747	26	32	typically	typically	ADV
cana-2747	26	33	involve	involve	VERB
cana-2747	26	34	two	two	NUM
cana-2747	26	35	key	key	ADJ
cana-2747	26	36	steps	step	NOUN
cana-2747	26	37	:	:	PUNCT
cana-2747	26	38	feature	feature	NOUN
cana-2747	26	39	representation	representation	NOUN
cana-2747	26	40	and	and	CCONJ
cana-2747	26	41	classifier	classifier	NOUN
cana-2747	26	42	training	training	NOUN
cana-2747	26	43	.	.	PUNCT
cana-2747	27	1	deep	deep	ADJ
cana-2747	27	2	learning	learning	NOUN
cana-2747	27	3	has	have	AUX
cana-2747	27	4	revolutionized	revolutionize	VERB
cana-2747	27	5	the	the	DET
cana-2747	27	6	field	field	NOUN
cana-2747	27	7	,	,	PUNCT
cana-2747	27	8	with	with	ADP
cana-2747	27	9	various	various	ADJ
cana-2747	27	10	neural	neural	ADJ
cana-2747	27	11	networks	network	NOUN
cana-2747	27	12	taking	take	VERB
cana-2747	27	13	center	center	ADJ
cana-2747	27	14	stage	stage	NOUN
cana-2747	27	15	in	in	ADP
cana-2747	27	16	research	research	NOUN
cana-2747	27	17	.	.	PUNCT
cana-2747	28	1	some	some	DET
cana-2747	28	2	researchers	researcher	NOUN
cana-2747	28	3	opt	opt	VERB
cana-2747	28	4	for	for	ADP
cana-2747	28	5	an	an	DET
cana-2747	28	6	end	end	NOUN
cana-2747	28	7	-	-	PUNCT
cana-2747	28	8	to	to	ADP
cana-2747	28	9	-	-	PUNCT
cana-2747	28	10	end	end	NOUN
cana-2747	28	11	approach	approach	NOUN
cana-2747	28	12	,	,	PUNCT
cana-2747	28	13	combining	combine	VERB
cana-2747	28	14	feature	feature	NOUN
cana-2747	28	15	representation	representation	NOUN
cana-2747	28	16	and	and	CCONJ
cana-2747	28	17	classification	classification	NOUN
cana-2747	28	18	within	within	ADP
cana-2747	28	19	a	a	DET
cana-2747	28	20	single	single	ADJ
cana-2747	28	21	framework	framework	NOUN
cana-2747	28	22	.	.	PUNCT
cana-2747	29	1	others	other	NOUN
cana-2747	29	2	leverage	leverage	VERB
cana-2747	29	3	deep	deep	ADJ
cana-2747	29	4	learning	learning	NOUN
cana-2747	29	5	models	model	NOUN
cana-2747	29	6	specifically	specifically	ADV
cana-2747	29	7	for	for	ADP
cana-2747	29	8	classification	classification	NOUN
cana-2747	29	9	,	,	PUNCT
cana-2747	29	10	applying	apply	VERB
cana-2747	29	11	them	they	PRON
cana-2747	29	12	to	to	PART
cana-2747	29	13	independently	independently	ADV
cana-2747	29	14	developed	develop	VERB
cana-2747	29	15	feature	feature	NOUN
cana-2747	29	16	spaces[13	spaces[13	NOUN
cana-2747	29	17	]	]	PUNCT
cana-2747	29	18	.	.	PUNCT
cana-2747	30	1	biometric	biometric	ADJ
cana-2747	30	2	identification	identification	NOUN
cana-2747	30	3	is	be	AUX
cana-2747	30	4	a	a	DET
cana-2747	30	5	critical	critical	ADJ
cana-2747	30	6	aspect	aspect	NOUN
cana-2747	30	7	of	of	ADP
cana-2747	30	8	security	security	NOUN
cana-2747	30	9	systems	system	NOUN
cana-2747	30	10	,	,	PUNCT
cana-2747	30	11	and	and	CCONJ
cana-2747	30	12	recent	recent	ADJ
cana-2747	30	13	advancements	advancement	NOUN
cana-2747	30	14	have	have	AUX
cana-2747	30	15	seen	see	VERB
cana-2747	30	16	a	a	DET
cana-2747	30	17	surge	surge	NOUN
cana-2747	30	18	in	in	ADP
cana-2747	30	19	research	research	NOUN
cana-2747	30	20	exploring	explore	VERB
cana-2747	30	21	novel	novel	ADJ
cana-2747	30	22	modalities	modality	NOUN
cana-2747	30	23	.	.	PUNCT
cana-2747	31	1	this	this	DET
cana-2747	31	2	paper	paper	NOUN
cana-2747	31	3	introduces	introduce	VERB
cana-2747	31	4	a	a	DET
cana-2747	31	5	hybrid	hybrid	ADJ
cana-2747	31	6	model	model	NOUN
cana-2747	31	7	that	that	PRON
cana-2747	31	8	integrates	integrate	VERB
cana-2747	31	9	eeg	eeg	NOUN
cana-2747	31	10	and	and	CCONJ
cana-2747	31	11	facial	facial	ADJ
cana-2747	31	12	data	datum	NOUN
cana-2747	31	13	for	for	ADP
cana-2747	31	14	person	person	NOUN
cana-2747	31	15	identification	identification	NOUN
cana-2747	31	16	.	.	PUNCT
cana-2747	32	1	the	the	DET
cana-2747	32	2	motivation	motivation	NOUN
cana-2747	32	3	behind	behind	ADP
cana-2747	32	4	this	this	DET
cana-2747	32	5	approach	approach	NOUN
cana-2747	32	6	lies	lie	VERB
cana-2747	32	7	in	in	ADP
cana-2747	32	8	the	the	DET
cana-2747	32	9	potential	potential	ADJ
cana-2747	32	10	synergy	synergy	NOUN
cana-2747	32	11	between	between	ADP
cana-2747	32	12	temporal	temporal	ADJ
cana-2747	32	13	eeg	eeg	NOUN
cana-2747	32	14	patterns	pattern	NOUN
cana-2747	32	15	and	and	CCONJ
cana-2747	32	16	spatial	spatial	ADJ
cana-2747	32	17	facial	facial	ADJ
cana-2747	32	18	features	feature	NOUN
cana-2747	32	19	.	.	PUNCT
cana-2747	33	1	in	in	ADP
cana-2747	33	2	the	the	DET
cana-2747	33	3	context	context	NOUN
cana-2747	33	4	of	of	ADP
cana-2747	33	5	classical	classical	ADJ
cana-2747	33	6	machine	machine	NOUN
cana-2747	33	7	learning	learn	VERB
cana-2747	33	8	techniques	technique	NOUN
cana-2747	33	9	,	,	PUNCT
cana-2747	33	10	merely	merely	ADV
cana-2747	33	11	adding	add	VERB
cana-2747	33	12	more	more	ADJ
cana-2747	33	13	features	feature	NOUN
cana-2747	33	14	will	will	AUX
cana-2747	33	15	unavoidably	unavoidably	ADV
cana-2747	33	16	expand	expand	VERB
cana-2747	33	17	the	the	DET
cana-2747	33	18	dimension	dimension	NOUN
cana-2747	33	19	of	of	ADP
cana-2747	33	20	the	the	DET
cana-2747	33	21	machine	machine	NOUN
cana-2747	33	22	learning	learning	NOUN
cana-2747	33	23	model	model	NOUN
cana-2747	33	24	.	.	PUNCT
cana-2747	34	1	this	this	PRON
cana-2747	34	2	becomes	becomes	AUX
cana-2747	34	3	particularly	particularly	ADV
cana-2747	34	4	pronounced	pronounce	VERB
cana-2747	34	5	when	when	SCONJ
cana-2747	34	6	substantial	substantial	ADJ
cana-2747	34	7	redundancy	redundancy	NOUN
cana-2747	34	8	exists	exist	VERB
cana-2747	34	9	among	among	ADP
cana-2747	34	10	different	different	ADJ
cana-2747	34	11	features	feature	NOUN
cana-2747	34	12	,	,	PUNCT
cana-2747	34	13	causing	cause	VERB
cana-2747	34	14	the	the	DET
cana-2747	34	15	model	model	NOUN
cana-2747	34	16	's	's	PART
cana-2747	34	17	complexity	complexity	NOUN
cana-2747	34	18	to	to	PART
cana-2747	34	19	far	far	ADV
cana-2747	34	20	exceed	exceed	VERB
cana-2747	34	21	the	the	DET
cana-2747	34	22	actual	actual	ADJ
cana-2747	34	23	feature	feature	NOUN
cana-2747	34	24	dimension	dimension	NOUN
cana-2747	34	25	.	.	PUNCT
cana-2747	35	1	as	as	ADP
cana-2747	35	2	a	a	DET
cana-2747	35	3	consequence	consequence	NOUN
cana-2747	35	4	,	,	PUNCT
cana-2747	35	5	over	over	ADP
cana-2747	35	6	fitting	fitting	ADJ
cana-2747	35	7	may	may	AUX
cana-2747	35	8	arise	arise	VERB
cana-2747	35	9	.	.	PUNCT
cana-2747	36	1	fig.1	fig.1	INTJ
cana-2747	36	2	.	.	PUNCT
cana-2747	37	1	the	the	DET
cana-2747	37	2	deep	deep	ADJ
cana-2747	37	3	learning	learning	NOUN
cana-2747	37	4	-	-	PUNCT
cana-2747	37	5	based	base	VERB
cana-2747	37	6	network	network	NOUN
cana-2747	37	7	structure	structure	NOUN
cana-2747	37	8	for	for	ADP
cana-2747	37	9	integrated	integrate	VERB
cana-2747	37	10	facial	facial	ADJ
cana-2747	37	11	recognition	recognition	NOUN
cana-2747	37	12	and	and	CCONJ
cana-2747	37	13	eeg	eeg	NOUN
cana-2747	37	14	the	the	DET
cana-2747	37	15	study	study	NOUN
cana-2747	37	16	's	's	PART
cana-2747	37	17	significant	significant	ADJ
cana-2747	37	18	contributions	contribution	NOUN
cana-2747	37	19	are	be	AUX
cana-2747	37	20	summarised	summarise	VERB
cana-2747	37	21	here	here	ADV
cana-2747	37	22	.	.	PUNCT
cana-2747	38	1	1	1	X
cana-2747	38	2	)	)	PUNCT
cana-2747	38	3	this	this	DET
cana-2747	38	4	paper	paper	NOUN
cana-2747	38	5	proposes	propose	VERB
cana-2747	38	6	an	an	DET
cana-2747	38	7	eeg	eeg	NOUN
cana-2747	38	8	-	-	PUNCT
cana-2747	38	9	based	base	VERB
cana-2747	38	10	person	person	NOUN
cana-2747	38	11	identification	identification	NOUN
cana-2747	38	12	(	(	PUNCT
cana-2747	38	13	pi	pi	NOUN
cana-2747	38	14	)	)	PUNCT
cana-2747	38	15	strategy	strategy	NOUN
cana-2747	38	16	based	base	VERB
cana-2747	38	17	on	on	ADP
cana-2747	38	18	deep	deep	ADJ
cana-2747	38	19	learning	learning	NOUN
cana-2747	38	20	with	with	ADP
cana-2747	38	21	cnn	cnn	PROPN
cana-2747	38	22	-	-	PUNCT
cana-2747	38	23	lstm	lstm	PROPN
cana-2747	38	24	and	and	CCONJ
cana-2747	38	25	mobilenet	mobilenet	NOUN
cana-2747	38	26	algorithms	algorithm	NOUN
cana-2747	38	27	.	.	PUNCT
cana-2747	39	1	2	2	X
cana-2747	39	2	)	)	PUNCT
cana-2747	39	3	the	the	DET
cana-2747	39	4	proposed	propose	VERB
cana-2747	39	5	approach	approach	NOUN
cana-2747	39	6	demonstrates	demonstrate	VERB
cana-2747	39	7	improvement	improvement	NOUN
cana-2747	39	8	in	in	ADP
cana-2747	39	9	accuracy	accuracy	NOUN
cana-2747	39	10	for	for	ADP
cana-2747	39	11	user	user	NOUN
cana-2747	39	12	identification	identification	NOUN
cana-2747	39	13	through	through	ADP
cana-2747	39	14	the	the	DET
cana-2747	39	15	fusion	fusion	NOUN
cana-2747	39	16	of	of	ADP
cana-2747	39	17	biometric	biometric	ADJ
cana-2747	39	18	traits	trait	NOUN
cana-2747	39	19	with	with	ADP
cana-2747	39	20	the	the	DET
cana-2747	39	21	utilization	utilization	NOUN
cana-2747	39	22	of	of	ADP
cana-2747	39	23	deep	deep	ADJ
cana-2747	39	24	learning	learning	NOUN
cana-2747	39	25	techniques	technique	NOUN
cana-2747	39	26	.	.	PUNCT
cana-2747	40	1	communications	communication	NOUN
cana-2747	40	2	on	on	ADP
cana-2747	40	3	applied	apply	VERB
cana-2747	40	4	nonlinear	nonlinear	ADJ
cana-2747	40	5	analysis	analysis	NOUN
cana-2747	40	6	issn	issn	NOUN
cana-2747	40	7	:	:	PUNCT
cana-2747	40	8	1074	1074	NUM
cana-2747	40	9	-	-	PUNCT
cana-2747	40	10	133x	133x	NUM
cana-2747	40	11	vol	vol	NOUN
cana-2747	40	12	32	32	NUM
cana-2747	40	13	no	no	NOUN
cana-2747	40	14	.	.	PUNCT
cana-2747	41	1	4s	4s	NUM
cana-2747	41	2	(	(	PUNCT
cana-2747	41	3	2025	2025	NUM
cana-2747	41	4	)	)	PUNCT
cana-2747	41	5	170	170	NUM
cana-2747	41	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	41	7	time	time	NOUN
cana-2747	41	8	distributed	distribute	VERB
cana-2747	41	9	2d	2d	PROPN
cana-2747	41	10	-	-	PUNCT
cana-2747	41	11	cnn	cnn	PROPN
cana-2747	41	12	flattened	flatten	VERB
cana-2747	41	13	lstm	lstm	ADJ
cana-2747	41	14	dense	dense	ADJ
cana-2747	41	15	output	output	NOUN
cana-2747	41	16	fig	fig	NOUN
cana-2747	41	17	.	.	PUNCT
cana-2747	42	1	2	2	X
cana-2747	42	2	.	.	X
cana-2747	42	3	implementation	implementation	NOUN
cana-2747	42	4	of	of	ADP
cana-2747	42	5	the	the	DET
cana-2747	42	6	cascade	cascade	NOUN
cana-2747	42	7	cnn	cnn	PROPN
cana-2747	42	8	-	-	PUNCT
cana-2747	42	9	lstm	lstm	ADJ
cana-2747	42	10	-	-	PUNCT
cana-2747	42	11	mobilenet	mobilenet	NOUN
cana-2747	42	12	model[14	model[14	X
cana-2747	42	13	]	]	PUNCT
cana-2747	42	14	according	accord	VERB
cana-2747	42	15	to	to	ADP
cana-2747	42	16	eeg	eeg	PROPN
cana-2747	42	17	&	&	CCONJ
cana-2747	42	18	face	face	NOUN
cana-2747	42	19	videos	video	NOUN
cana-2747	42	20	2	2	NUM
cana-2747	42	21	.	.	PUNCT
cana-2747	42	22	literature	literature	NOUN
cana-2747	42	23	survey	survey	NOUN
cana-2747	42	24	recently	recently	ADV
cana-2747	42	25	,	,	PUNCT
cana-2747	42	26	there	there	PRON
cana-2747	42	27	has	have	AUX
cana-2747	42	28	been	be	AUX
cana-2747	42	29	increasing	increase	VERB
cana-2747	42	30	interest	interest	NOUN
cana-2747	42	31	in	in	ADP
cana-2747	42	32	eeg	eeg	NOUN
cana-2747	42	33	-	-	PUNCT
cana-2747	42	34	based	base	VERB
cana-2747	42	35	person	person	NOUN
cana-2747	42	36	identification	identification	NOUN
cana-2747	42	37	(	(	PUNCT
cana-2747	42	38	pi)[15	pi)[15	PROPN
cana-2747	42	39	]	]	X
cana-2747	42	40	.	.	PUNCT
cana-2747	43	1	eeg	eeg	NOUN
cana-2747	43	2	-	-	PUNCT
cana-2747	43	3	based	base	VERB
cana-2747	43	4	pi	pi	NOUN
cana-2747	43	5	methods	method	NOUN
cana-2747	43	6	use	use	VERB
cana-2747	43	7	two	two	NUM
cana-2747	43	8	types	type	NOUN
cana-2747	43	9	of	of	ADP
cana-2747	43	10	algorithms	algorithm	NOUN
cana-2747	43	11	:	:	PUNCT
cana-2747	43	12	standard	standard	ADJ
cana-2747	43	13	machine	machine	NOUN
cana-2747	43	14	learning	learning	NOUN
cana-2747	43	15	and	and	CCONJ
cana-2747	43	16	deep	deep	ADJ
cana-2747	43	17	learning	learning	NOUN
cana-2747	43	18	.	.	PUNCT
cana-2747	44	1	machine	machine	NOUN
cana-2747	44	2	learning	learn	VERB
cana-2747	44	3	techniques	technique	NOUN
cana-2747	44	4	,	,	PUNCT
cana-2747	44	5	including	include	VERB
cana-2747	44	6	support	support	NOUN
cana-2747	44	7	vector	vector	NOUN
cana-2747	44	8	machines	machine	NOUN
cana-2747	44	9	(	(	PUNCT
cana-2747	44	10	svm	svm	PROPN
cana-2747	44	11	)	)	PUNCT
cana-2747	44	12	,	,	PUNCT
cana-2747	44	13	random	random	ADJ
cana-2747	44	14	forests	forest	NOUN
cana-2747	44	15	,	,	PUNCT
cana-2747	44	16	and	and	CCONJ
cana-2747	44	17	k	k	X
cana-2747	44	18	-	-	PUNCT
cana-2747	44	19	nearest	near	ADJ
cana-2747	44	20	neighbours	neighbour	NOUN
cana-2747	44	21	(	(	PUNCT
cana-2747	44	22	knn	knn	PROPN
cana-2747	44	23	)	)	PUNCT
cana-2747	44	24	,	,	PUNCT
cana-2747	44	25	are	be	AUX
cana-2747	44	26	commonly	commonly	ADV
cana-2747	44	27	used	use	VERB
cana-2747	44	28	in	in	ADP
cana-2747	44	29	eeg	eeg	NOUN
cana-2747	44	30	-	-	PUNCT
cana-2747	44	31	based	base	VERB
cana-2747	44	32	pi	pi	NOUN
cana-2747	44	33	.	.	PUNCT
cana-2747	45	1	deep	deep	ADJ
cana-2747	45	2	learning	learning	NOUN
cana-2747	45	3	(	(	PUNCT
cana-2747	45	4	dl	dl	INTJ
cana-2747	45	5	)	)	PUNCT
cana-2747	45	6	is	be	AUX
cana-2747	45	7	increasingly	increasingly	ADV
cana-2747	45	8	being	be	AUX
cana-2747	45	9	used	use	VERB
cana-2747	45	10	for	for	ADP
cana-2747	45	11	eeg	eeg	NOUN
cana-2747	45	12	-	-	PUNCT
cana-2747	45	13	based	base	VERB
cana-2747	45	14	pi	pi	NOUN
cana-2747	45	15	,	,	PUNCT
cana-2747	45	16	following	follow	VERB
cana-2747	45	17	its	its	PRON
cana-2747	45	18	great	great	ADJ
cana-2747	45	19	success	success	NOUN
cana-2747	45	20	in	in	ADP
cana-2747	45	21	several	several	ADJ
cana-2747	45	22	sectors	sector	NOUN
cana-2747	45	23	.	.	PUNCT
cana-2747	46	1	dl	dl	PROPN
cana-2747	46	2	models	model	NOUN
cana-2747	46	3	are	be	AUX
cana-2747	46	4	being	be	AUX
cana-2747	46	5	increasingly	increasingly	ADV
cana-2747	46	6	incorporated	incorporate	VERB
cana-2747	46	7	into	into	ADP
cana-2747	46	8	eeg	eeg	NOUN
cana-2747	46	9	-	-	PUNCT
cana-2747	46	10	based	base	VERB
cana-2747	46	11	pi	pi	NOUN
cana-2747	46	12	research	research	NOUN
cana-2747	46	13	,	,	PUNCT
cana-2747	46	14	often	often	ADV
cana-2747	46	15	involving	involve	VERB
cana-2747	46	16	fine	fine	ADV
cana-2747	46	17	-	-	PUNCT
cana-2747	46	18	tuning	tune	VERB
cana-2747	46	19	parameters	parameter	NOUN
cana-2747	46	20	or	or	CCONJ
cana-2747	46	21	redesigning	redesign	VERB
cana-2747	46	22	architectures	architecture	NOUN
cana-2747	46	23	,	,	PUNCT
cana-2747	46	24	including	include	VERB
cana-2747	46	25	cnns	cnn	NOUN
cana-2747	46	26	)	)	PUNCT
cana-2747	46	27	and	and	CCONJ
cana-2747	46	28	lstm	lstm	NOUN
cana-2747	46	29	networks	network	NOUN
cana-2747	46	30	.	.	PUNCT
cana-2747	47	1	in	in	ADP
cana-2747	47	2	2019	2019	NUM
cana-2747	47	3	,	,	PUNCT
cana-2747	47	4	banee	banee	NOUN
cana-2747	47	5	bandana	bandana	VERB
cana-2747	47	6	das	das	PROPN
cana-2747	47	7	and	and	CCONJ
cana-2747	47	8	colleagues[16	colleagues[16	PROPN
cana-2747	47	9	]	]	PUNCT
cana-2747	47	10	developed	develop	VERB
cana-2747	47	11	a	a	DET
cana-2747	47	12	technique	technique	NOUN
cana-2747	47	13	to	to	PART
cana-2747	47	14	identify	identify	VERB
cana-2747	47	15	persons	person	NOUN
cana-2747	47	16	using	use	VERB
cana-2747	47	17	eeg	eeg	NOUN
cana-2747	47	18	waves	wave	NOUN
cana-2747	47	19	.	.	PUNCT
cana-2747	48	1	the	the	DET
cana-2747	48	2	system	system	NOUN
cana-2747	48	3	used	use	VERB
cana-2747	48	4	convolutional	convolutional	ADJ
cana-2747	48	5	neural	neural	ADJ
cana-2747	48	6	networks	network	NOUN
cana-2747	48	7	(	(	PUNCT
cana-2747	48	8	cnns	cnns	PROPN
cana-2747	48	9	)	)	PUNCT
cana-2747	48	10	to	to	PART
cana-2747	48	11	extract	extract	VERB
cana-2747	48	12	spatial	spatial	ADJ
cana-2747	48	13	features	feature	NOUN
cana-2747	48	14	from	from	ADP
cana-2747	48	15	raw	raw	ADJ
cana-2747	48	16	data	datum	NOUN
cana-2747	48	17	,	,	PUNCT
cana-2747	48	18	resulting	result	VERB
cana-2747	48	19	in	in	ADP
cana-2747	48	20	robust	robust	ADJ
cana-2747	48	21	and	and	CCONJ
cana-2747	48	22	informative	informative	ADJ
cana-2747	48	23	results	result	NOUN
cana-2747	48	24	.	.	PUNCT
cana-2747	49	1	the	the	DET
cana-2747	49	2	features	feature	NOUN
cana-2747	49	3	were	be	AUX
cana-2747	49	4	fed	feed	VERB
cana-2747	49	5	into	into	ADP
cana-2747	49	6	an	an	DET
cana-2747	49	7	lstm	lstm	NOUN
cana-2747	49	8	to	to	PART
cana-2747	49	9	manage	manage	VERB
cana-2747	49	10	temporal	temporal	ADJ
cana-2747	49	11	data	datum	NOUN
cana-2747	49	12	and	and	CCONJ
cana-2747	49	13	identify	identify	VERB
cana-2747	49	14	it	it	PRON
cana-2747	49	15	.	.	PUNCT
cana-2747	50	1	the	the	DET
cana-2747	50	2	method	method	NOUN
cana-2747	50	3	achieved	achieve	VERB
cana-2747	50	4	outstanding	outstanding	ADJ
cana-2747	50	5	accuracy	accuracy	NOUN
cana-2747	50	6	rates	rate	NOUN
cana-2747	50	7	of	of	ADP
cana-2747	50	8	99.95	99.95	NUM
cana-2747	50	9	%	%	NOUN
cana-2747	50	10	and	and	CCONJ
cana-2747	50	11	98	98	NUM
cana-2747	50	12	%	%	NOUN
cana-2747	50	13	for	for	ADP
cana-2747	50	14	individual	individual	ADJ
cana-2747	50	15	identification	identification	NOUN
cana-2747	50	16	.	.	PUNCT
cana-2747	51	1	yingnan	yingnan	PRON
cana-2747	51	2	sun	sun	PROPN
cana-2747	51	3	and	and	CCONJ
cana-2747	51	4	colleagues[17	colleagues[17	PROPN
cana-2747	51	5	]	]	PUNCT
cana-2747	51	6	created	create	VERB
cana-2747	51	7	a	a	DET
cana-2747	51	8	one	one	NUM
cana-2747	51	9	-	-	PUNCT
cana-2747	51	10	dimensional	dimensional	ADJ
cana-2747	51	11	convolutional	convolutional	ADJ
cana-2747	51	12	long	long	ADJ
cana-2747	51	13	short	short	ADJ
cana-2747	51	14	-	-	PUNCT
cana-2747	51	15	term	term	NOUN
cana-2747	51	16	memory	memory	NOUN
cana-2747	51	17	neural	neural	ADJ
cana-2747	51	18	networkaverage	networkaverage	NOUN
cana-2747	51	19	pooling	pool	VERB
cana-2747	51	20	dense	dense	ADJ
cana-2747	51	21	layer	layer	NOUN
cana-2747	51	22	communications	communication	NOUN
cana-2747	51	23	on	on	ADP
cana-2747	51	24	applied	apply	VERB
cana-2747	51	25	nonlinear	nonlinear	ADJ
cana-2747	51	26	analysis	analysis	NOUN
cana-2747	51	27	issn	issn	NOUN
cana-2747	51	28	:	:	PUNCT
cana-2747	51	29	1074	1074	NUM
cana-2747	51	30	-	-	PUNCT
cana-2747	51	31	133x	133x	NUM
cana-2747	51	32	vol	vol	NOUN
cana-2747	51	33	32	32	NUM
cana-2747	51	34	no	no	NOUN
cana-2747	51	35	.	.	PUNCT
cana-2747	52	1	4s	4s	NUM
cana-2747	52	2	(	(	PUNCT
cana-2747	52	3	2025	2025	NUM
cana-2747	52	4	)	)	PUNCT
cana-2747	52	5	171	171	NUM
cana-2747	52	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	52	7	based	base	VERB
cana-2747	52	8	eeg	eeg	PROPN
cana-2747	52	9	signal	signal	NOUN
cana-2747	52	10	-	-	PUNCT
cana-2747	52	11	based	base	VERB
cana-2747	52	12	user	user	NOUN
cana-2747	52	13	recognition	recognition	NOUN
cana-2747	52	14	system	system	NOUN
cana-2747	52	15	.	.	PUNCT
cana-2747	53	1	during	during	ADP
cana-2747	53	2	the	the	DET
cana-2747	53	3	training	training	NOUN
cana-2747	53	4	process	process	NOUN
cana-2747	53	5	,	,	PUNCT
cana-2747	53	6	eeg	eeg	PROPN
cana-2747	53	7	data	datum	NOUN
cana-2747	53	8	from	from	ADP
cana-2747	53	9	electrodes	electrode	NOUN
cana-2747	53	10	ranging	range	VERB
cana-2747	53	11	from	from	ADP
cana-2747	53	12	4	4	NUM
cana-2747	53	13	,	,	PUNCT
cana-2747	53	14	16	16	NUM
cana-2747	53	15	,	,	PUNCT
cana-2747	53	16	32	32	NUM
cana-2747	53	17	,	,	PUNCT
cana-2747	53	18	to	to	ADP
cana-2747	53	19	64	64	NUM
cana-2747	53	20	were	be	AUX
cana-2747	53	21	input	input	NOUN
cana-2747	53	22	into	into	ADP
cana-2747	53	23	the	the	DET
cana-2747	53	24	network	network	NOUN
cana-2747	53	25	.	.	PUNCT
cana-2747	54	1	the	the	DET
cana-2747	54	2	results	result	NOUN
cana-2747	54	3	revealed	reveal	VERB
cana-2747	54	4	that	that	SCONJ
cana-2747	54	5	an	an	DET
cana-2747	54	6	optimal	optimal	ADJ
cana-2747	54	7	classification	classification	NOUN
cana-2747	54	8	accuracy	accuracy	NOUN
cana-2747	54	9	of	of	ADP
cana-2747	54	10	99.58	99.58	NUM
cana-2747	54	11	%	%	NOUN
cana-2747	54	12	was	be	AUX
cana-2747	54	13	attained	attain	VERB
cana-2747	54	14	with	with	ADP
cana-2747	54	15	16	16	NUM
cana-2747	54	16	electrodes	electrode	NOUN
cana-2747	54	17	.	.	PUNCT
cana-2747	55	1	emanuele	emanuele	PROPN
cana-2747	55	2	maiorana	maiorana	PROPN
cana-2747	56	1	[	[	X
cana-2747	56	2	18	18	NUM
cana-2747	56	3	]	]	PUNCT
cana-2747	56	4	presented	present	VERB
cana-2747	56	5	a	a	DET
cana-2747	56	6	deep	deep	ADJ
cana-2747	56	7	learning	learning	NOUN
cana-2747	56	8	method	method	NOUN
cana-2747	56	9	that	that	PRON
cana-2747	56	10	uses	use	VERB
cana-2747	56	11	siamese	siamese	ADJ
cana-2747	56	12	convolutional	convolutional	ADJ
cana-2747	56	13	neural	neural	ADJ
cana-2747	56	14	networks	network	NOUN
cana-2747	56	15	to	to	PART
cana-2747	56	16	analyze	analyze	VERB
cana-2747	56	17	eeg	eeg	NOUN
cana-2747	56	18	data	datum	NOUN
cana-2747	56	19	from	from	ADP
cana-2747	56	20	45	45	NUM
cana-2747	56	21	subjects	subject	NOUN
cana-2747	56	22	in	in	ADP
cana-2747	56	23	a	a	DET
cana-2747	56	24	multisession	multisession	NOUN
cana-2747	56	25	database	database	NOUN
cana-2747	56	26	.	.	PUNCT
cana-2747	57	1	the	the	DET
cana-2747	57	2	results	result	NOUN
cana-2747	57	3	suggest	suggest	VERB
cana-2747	57	4	a	a	DET
cana-2747	57	5	promising	promising	ADJ
cana-2747	57	6	potential	potential	NOUN
cana-2747	57	7	for	for	ADP
cana-2747	57	8	applying	apply	VERB
cana-2747	57	9	eeg	eeg	NOUN
cana-2747	57	10	-	-	PUNCT
cana-2747	57	11	based	base	VERB
cana-2747	57	12	biometric	biometric	ADJ
cana-2747	57	13	verification	verification	NOUN
cana-2747	57	14	across	across	ADP
cana-2747	57	15	different	different	ADJ
cana-2747	57	16	tasks	task	NOUN
cana-2747	57	17	.	.	PUNCT
cana-2747	58	1	in	in	ADP
cana-2747	58	2	2022	2022	NUM
cana-2747	58	3	,	,	PUNCT
cana-2747	58	4	alyasseri	alyasseri	NOUN
cana-2747	58	5	z	z	PROPN
cana-2747	59	1	[	[	X
cana-2747	59	2	19	19	NUM
cana-2747	59	3	]	]	PUNCT
cana-2747	59	4	introduced	introduce	VERB
cana-2747	59	5	a	a	DET
cana-2747	59	6	methodology	methodology	NOUN
cana-2747	59	7	that	that	PRON
cana-2747	59	8	integrates	integrate	VERB
cana-2747	59	9	the	the	DET
cana-2747	59	10	gray	gray	ADJ
cana-2747	59	11	wolf	wolf	NOUN
cana-2747	59	12	optimizer	optimizer	NOUN
cana-2747	59	13	(	(	PUNCT
cana-2747	59	14	bgwo	bgwo	PROPN
cana-2747	59	15	)	)	PUNCT
cana-2747	59	16	with	with	ADP
cana-2747	59	17	a	a	DET
cana-2747	59	18	support	support	NOUN
cana-2747	59	19	vector	vector	NOUN
cana-2747	59	20	machine	machine	NOUN
cana-2747	59	21	classifier	classifier	NOUN
cana-2747	59	22	employing	employ	VERB
cana-2747	59	23	a	a	DET
cana-2747	59	24	radial	radial	ADJ
cana-2747	59	25	basis	basis	NOUN
cana-2747	59	26	function	function	NOUN
cana-2747	59	27	kernel	kernel	NOUN
cana-2747	59	28	(	(	PUNCT
cana-2747	59	29	svm	svm	PROPN
cana-2747	59	30	-	-	PUNCT
cana-2747	59	31	rbf	rbf	PROPN
cana-2747	59	32	)	)	PUNCT
cana-2747	59	33	for	for	ADP
cana-2747	59	34	biometric	biometric	ADJ
cana-2747	59	35	human	human	ADJ
cana-2747	59	36	identification	identification	NOUN
cana-2747	59	37	utilizing	utilize	VERB
cana-2747	59	38	eeg	eeg	NOUN
cana-2747	59	39	data	datum	NOUN
cana-2747	59	40	.	.	PUNCT
cana-2747	60	1	this	this	DET
cana-2747	60	2	methodology	methodology	NOUN
cana-2747	60	3	attained	attain	VERB
cana-2747	60	4	an	an	DET
cana-2747	60	5	accuracy	accuracy	NOUN
cana-2747	60	6	rate	rate	NOUN
cana-2747	60	7	of	of	ADP
cana-2747	60	8	94.13	94.13	NUM
cana-2747	60	9	%	%	NOUN
cana-2747	60	10	while	while	SCONJ
cana-2747	60	11	utilizing	utilize	VERB
cana-2747	60	12	just	just	ADV
cana-2747	60	13	23	23	NUM
cana-2747	60	14	sensors	sensor	NOUN
cana-2747	60	15	and	and	CCONJ
cana-2747	60	16	5	5	NUM
cana-2747	60	17	autoregressive	autoregressive	ADJ
cana-2747	60	18	coefficients	coefficient	NOUN
cana-2747	60	19	.	.	PUNCT
cana-2747	61	1	dropout	dropout	NOUN
cana-2747	61	2	layer	layer	NOUN
cana-2747	61	3	(	(	PUNCT
cana-2747	61	4	rate=0.2	rate=0.2	NOUN
cana-2747	61	5	)	)	PUNCT
cana-2747	61	6	activation=”relu	activation=”relu	PROPN
cana-2747	61	7	”	"	PUNCT
cana-2747	61	8	“	"	PUNCT
cana-2747	61	9	relu	relu	NOUN
cana-2747	61	10	”	"	PUNCT
cana-2747	61	11	“	"	PUNCT
cana-2747	61	12	softmax	softmax	X
cana-2747	61	13	”	"	PUNCT
cana-2747	61	14	fig	fig	NOUN
cana-2747	61	15	.	.	PUNCT
cana-2747	62	1	3.flowchart	3.flowchart	NUM
cana-2747	62	2	for	for	ADP
cana-2747	62	3	hybrid	hybrid	ADJ
cana-2747	62	4	proposed	propose	VERB
cana-2747	62	5	technique	technique	NOUN
cana-2747	62	6	cnn+lstm+mobilenet	cnn+lstm+mobilenet	NOUN
cana-2747	62	7	3	3	X
cana-2747	62	8	.	.	X
cana-2747	62	9	deep	deep	ADJ
cana-2747	62	10	learning	learning	NOUN
cana-2747	62	11	approach	approach	NOUN
cana-2747	62	12	to	to	ADP
cana-2747	62	13	eeg	eeg	PROPN
cana-2747	62	14	in	in	ADP
cana-2747	62	15	recent	recent	ADJ
cana-2747	62	16	years	year	NOUN
cana-2747	62	17	,	,	PUNCT
cana-2747	62	18	the	the	DET
cana-2747	62	19	application	application	NOUN
cana-2747	62	20	of	of	ADP
cana-2747	62	21	deep	deep	ADJ
cana-2747	62	22	learning	learning	NOUN
cana-2747	62	23	(	(	PUNCT
cana-2747	62	24	dl	dl	NOUN
cana-2747	62	25	)	)	PUNCT
cana-2747	62	26	techniques	technique	NOUN
cana-2747	62	27	for	for	ADP
cana-2747	62	28	classifying	classify	VERB
cana-2747	62	29	eeg	eeg	NOUN
cana-2747	62	30	signals	signal	NOUN
cana-2747	62	31	—	—	PUNCT
cana-2747	62	32	biopotentials	biopotential	NOUN
cana-2747	62	33	recorded	record	VERB
cana-2747	62	34	from	from	ADP
cana-2747	62	35	the	the	DET
cana-2747	62	36	scalp	scalp	NOUN
cana-2747	62	37	over	over	ADP
cana-2747	62	38	time	time	NOUN
cana-2747	62	39	—	—	PUNCT
cana-2747	62	40	has	have	AUX
cana-2747	62	41	seen	see	VERB
cana-2747	62	42	a	a	DET
cana-2747	62	43	substantial	substantial	ADJ
cana-2747	62	44	increase	increase	NOUN
cana-2747	62	45	.	.	PUNCT
cana-2747	63	1	researchers	researcher	NOUN
cana-2747	63	2	frequently	frequently	ADV
cana-2747	63	3	employ	employ	VERB
cana-2747	63	4	dl	dl	PROPN
cana-2747	63	5	architectures	architecture	NOUN
cana-2747	63	6	to	to	PART
cana-2747	63	7	capture	capture	VERB
cana-2747	63	8	both	both	CCONJ
cana-2747	63	9	the	the	DET
cana-2747	63	10	spatial	spatial	ADJ
cana-2747	63	11	and	and	CCONJ
cana-2747	63	12	temporal	temporal	ADJ
cana-2747	63	13	features	feature	NOUN
cana-2747	63	14	of	of	ADP
cana-2747	63	15	these	these	DET
cana-2747	63	16	signals	signal	NOUN
cana-2747	63	17	[	[	X
cana-2747	63	18	16	16	NUM
cana-2747	63	19	]	]	PUNCT
cana-2747	63	20	.	.	PUNCT
cana-2747	64	1	a	a	DET
cana-2747	64	2	typical	typical	ADJ
cana-2747	64	3	approach	approach	NOUN
cana-2747	64	4	involves	involve	VERB
cana-2747	64	5	using	use	VERB
cana-2747	64	6	a	a	DET
cana-2747	64	7	combination	combination	NOUN
cana-2747	64	8	of	of	ADP
cana-2747	64	9	cnns	cnn	NOUN
cana-2747	64	10	followed	follow	VERB
cana-2747	64	11	by	by	ADP
cana-2747	64	12	recurrent	recurrent	ADJ
cana-2747	64	13	neural	neural	ADJ
cana-2747	64	14	networks	network	NOUN
cana-2747	64	15	rnns	rnn	NOUN
cana-2747	64	16	,	,	PUNCT
cana-2747	64	17	such	such	ADJ
cana-2747	64	18	as	as	ADP
cana-2747	64	19	long	long	ADJ
cana-2747	64	20	short	short	ADJ
cana-2747	64	21	-	-	PUNCT
cana-2747	64	22	term	term	NOUN
cana-2747	64	23	memory	memory	NOUN
cana-2747	64	24	(	(	PUNCT
cana-2747	64	25	lstm	lstm	NOUN
cana-2747	64	26	)	)	PUNCT
cana-2747	64	27	networks	network	NOUN
cana-2747	64	28	.	.	PUNCT
cana-2747	65	1	this	this	DET
cana-2747	65	2	layered	layered	ADJ
cana-2747	65	3	architecture	architecture	NOUN
cana-2747	65	4	leverages	leverage	VERB
cana-2747	65	5	the	the	DET
cana-2747	65	6	hierarchical	hierarchical	ADJ
cana-2747	65	7	structure	structure	NOUN
cana-2747	65	8	of	of	ADP
cana-2747	65	9	neural	neural	ADJ
cana-2747	65	10	networks	network	NOUN
cana-2747	65	11	,	,	PUNCT
cana-2747	65	12	where	where	SCONJ
cana-2747	65	13	earlier	early	ADJ
cana-2747	65	14	layers	layer	NOUN
cana-2747	65	15	extract	extract	VERB
cana-2747	65	16	features	feature	NOUN
cana-2747	65	17	that	that	PRON
cana-2747	65	18	are	be	AUX
cana-2747	65	19	processed	process	VERB
cana-2747	65	20	by	by	ADP
cana-2747	65	21	later	later	ADJ
cana-2747	65	22	layers	layer	NOUN
cana-2747	65	23	.	.	PUNCT
cana-2747	66	1	cnns	cnns	PROPN
cana-2747	66	2	are	be	AUX
cana-2747	66	3	often	often	ADV
cana-2747	66	4	used	use	VERB
cana-2747	66	5	as	as	ADP
cana-2747	66	6	the	the	DET
cana-2747	66	7	initial	initial	ADJ
cana-2747	66	8	layers	layer	NOUN
cana-2747	66	9	in	in	ADP
cana-2747	66	10	deep	deep	ADJ
cana-2747	66	11	learning	learning	NOUN
cana-2747	66	12	models	model	NOUN
cana-2747	66	13	to	to	PART
cana-2747	66	14	capture	capture	VERB
cana-2747	66	15	significant	significant	ADJ
cana-2747	66	16	patterns	pattern	NOUN
cana-2747	66	17	or	or	CCONJ
cana-2747	66	18	features[20	features[20	NOUN
cana-2747	66	19	]	]	PUNCT
cana-2747	66	20	.	.	PUNCT
cana-2747	67	1	a	a	DET
cana-2747	67	2	key	key	ADJ
cana-2747	67	3	feature	feature	NOUN
cana-2747	67	4	of	of	ADP
cana-2747	67	5	cnns	cnn	NOUN
cana-2747	67	6	is	be	AUX
cana-2747	67	7	their	their	PRON
cana-2747	67	8	use	use	NOUN
cana-2747	67	9	of	of	ADP
cana-2747	67	10	convolution	convolution	NOUN
cana-2747	67	11	operations	operation	NOUN
cana-2747	67	12	with	with	ADP
cana-2747	67	13	small	small	ADJ
cana-2747	67	14	filter	filter	NOUN
cana-2747	67	15	patches	patch	NOUN
cana-2747	67	16	(	(	PUNCT
cana-2747	67	17	kernels	kernels	PROPN
cana-2747	67	18	)	)	PUNCT
cana-2747	67	19	.	.	PUNCT
cana-2747	68	1	these	these	DET
cana-2747	68	2	filters	filter	NOUN
cana-2747	68	3	learn	learn	VERB
cana-2747	68	4	local	local	ADJ
cana-2747	68	5	patterns	pattern	NOUN
cana-2747	68	6	on	on	ADP
cana-2747	68	7	their	their	PRON
cana-2747	68	8	own	own	ADJ
cana-2747	68	9	,	,	PUNCT
cana-2747	68	10	and	and	CCONJ
cana-2747	68	11	when	when	SCONJ
cana-2747	68	12	multiple	multiple	ADJ
cana-2747	68	13	cnn	cnn	PROPN
cana-2747	68	14	layers	layer	NOUN
cana-2747	68	15	are	be	AUX
cana-2747	68	16	stacked	stack	VERB
cana-2747	68	17	,	,	PUNCT
cana-2747	68	18	they	they	PRON
cana-2747	68	19	combine	combine	VERB
cana-2747	68	20	these	these	DET
cana-2747	68	21	patterns	pattern	NOUN
cana-2747	68	22	to	to	PART
cana-2747	68	23	create	create	VERB
cana-2747	68	24	more	more	ADJ
cana-2747	68	25	complex	complex	ADJ
cana-2747	68	26	features	feature	NOUN
cana-2747	68	27	.	.	PUNCT
cana-2747	69	1	within	within	ADP
cana-2747	69	2	this	this	DET
cana-2747	69	3	stack	stack	NOUN
cana-2747	69	4	,	,	PUNCT
cana-2747	69	5	pooling	pool	VERB
cana-2747	69	6	layers	layer	NOUN
cana-2747	69	7	are	be	AUX
cana-2747	69	8	often	often	ADV
cana-2747	69	9	added	add	VERB
cana-2747	69	10	to	to	PART
cana-2747	69	11	reduce	reduce	VERB
cana-2747	69	12	the	the	DET
cana-2747	69	13	dimensionality	dimensionality	NOUN
cana-2747	69	14	by	by	ADP
cana-2747	69	15	retaining	retain	VERB
cana-2747	69	16	only	only	ADV
cana-2747	69	17	the	the	DET
cana-2747	69	18	maximum	maximum	ADJ
cana-2747	69	19	value	value	NOUN
cana-2747	69	20	from	from	ADP
cana-2747	69	21	each	each	DET
cana-2747	69	22	small	small	ADJ
cana-2747	69	23	region	region	NOUN
cana-2747	69	24	,	,	PUNCT
cana-2747	69	25	allowing	allow	VERB
cana-2747	69	26	subsequent	subsequent	ADJ
cana-2747	69	27	convolutional	convolutional	ADJ
cana-2747	69	28	layers	layer	NOUN
cana-2747	69	29	to	to	PART
cana-2747	69	30	operate	operate	VERB
cana-2747	69	31	on	on	ADP
cana-2747	69	32	a	a	DET
cana-2747	69	33	different	different	ADJ
cana-2747	69	34	scale	scale	NOUN
cana-2747	69	35	.	.	PUNCT
cana-2747	70	1	the	the	DET
cana-2747	70	2	features	feature	NOUN
cana-2747	70	3	extracted	extract	VERB
cana-2747	70	4	by	by	ADP
cana-2747	70	5	cnns	cnn	NOUN
cana-2747	70	6	can	can	AUX
cana-2747	70	7	then	then	ADV
cana-2747	70	8	be	be	AUX
cana-2747	70	9	used	use	VERB
cana-2747	70	10	as	as	ADP
cana-2747	70	11	input	input	NOUN
cana-2747	70	12	for	for	ADP
cana-2747	70	13	other	other	ADJ
cana-2747	70	14	network	network	NOUN
cana-2747	70	15	architectures	architecture	NOUN
cana-2747	70	16	,	,	PUNCT
cana-2747	70	17	aiding	aid	VERB
cana-2747	70	18	tasks	task	NOUN
cana-2747	70	19	like	like	ADP
cana-2747	70	20	object	object	NOUN
cana-2747	70	21	detection	detection	NOUN
cana-2747	70	22	deap	deap	NOUN
cana-2747	70	23	dataset	dataset	NOUN
cana-2747	70	24	standardize	standardize	VERB
cana-2747	70	25	the	the	DET
cana-2747	70	26	data	datum	NOUN
cana-2747	70	27	exploratory	exploratory	ADJ
cana-2747	70	28	analysis	analysis	NOUN
cana-2747	70	29	of	of	ADP
cana-2747	70	30	video	video	NOUN
cana-2747	70	31	data	datum	NOUN
cana-2747	70	32	exploratory	exploratory	ADJ
cana-2747	70	33	analysis	analysis	NOUN
cana-2747	70	34	of	of	ADP
cana-2747	70	35	eeg	eeg	NOUN
cana-2747	70	36	data	datum	NOUN
cana-2747	70	37	face	face	VERB
cana-2747	70	38	feature	feature	NOUN
cana-2747	70	39	extraction	extraction	NOUN
cana-2747	70	40	using	use	VERB
cana-2747	70	41	pretrained	pretraine	VERB
cana-2747	70	42	mobilenet	mobilenet	NOUN
cana-2747	70	43	architecture	architecture	NOUN
cana-2747	70	44	data	datum	NOUN
cana-2747	70	45	transformation	transformation	NOUN
cana-2747	70	46	into	into	ADP
cana-2747	70	47	2d	2d	PROPN
cana-2747	70	48	mesh	mesh	NOUN
cana-2747	70	49	(	(	PUNCT
cana-2747	70	50	shape	shape	NOUN
cana-2747	70	51	9×9	9×9	NUM
cana-2747	70	52	)	)	PUNCT
cana-2747	70	53	frames	frame	NOUN
cana-2747	70	54	normalize	normalize	VERB
cana-2747	70	55	the	the	DET
cana-2747	70	56	images	image	NOUN
cana-2747	70	57	range	range	NOUN
cana-2747	70	58	of	of	ADP
cana-2747	70	59	[	[	X
cana-2747	70	60	0	0	NUM
cana-2747	70	61	,	,	PUNCT
cana-2747	70	62	255	255	NUM
cana-2747	70	63	]	]	PUNCT
cana-2747	70	64	to	to	ADP
cana-2747	70	65	[	[	X
cana-2747	70	66	-1	-1	INTJ
cana-2747	70	67	,	,	PUNCT
cana-2747	70	68	1	1	NUM
cana-2747	70	69	]	]	PUNCT
cana-2747	70	70	.	.	PUNCT
cana-2747	71	1	frames	frame	NOUN
cana-2747	71	2	extracted	extract	VERB
cana-2747	71	3	(	(	PUNCT
cana-2747	71	4	person	person	NOUN
cana-2747	71	5	(	(	PUNCT
cana-2747	71	6	22	22	NUM
cana-2747	71	7	)	)	PUNCT
cana-2747	71	8	,	,	PUNCT
cana-2747	71	9	number	number	NOUN
cana-2747	71	10	of	of	ADP
cana-2747	71	11	frames	frame	NOUN
cana-2747	71	12	(	(	PUNCT
cana-2747	71	13	6),video(40	6),video(40	NUM
cana-2747	71	14	)	)	PUNCT
cana-2747	71	15	)	)	PUNCT
cana-2747	71	16	feature	feature	NOUN
cana-2747	71	17	extraction	extraction	NOUN
cana-2747	71	18	using	use	VERB
cana-2747	71	19	cnnlstm	cnnlstm	PROPN
cana-2747	71	20	d	d	PROPN
cana-2747	71	21	e	e	PROPN
cana-2747	71	22	n	n	X
cana-2747	71	23	s	s	PROPN
cana-2747	71	24	e	e	X
cana-2747	71	25	l	l	X
cana-2747	71	26	a	a	X
cana-2747	71	27	y	y	NOUN
cana-2747	71	28	e	e	NOUN
cana-2747	71	29	r	r	NOUN
cana-2747	71	30	d	d	PROPN
cana-2747	71	31	e	e	PROPN
cana-2747	71	32	n	n	NOUN
cana-2747	71	33	s	s	PROPN
cana-2747	71	34	e	e	X
cana-2747	71	35	l	l	X
cana-2747	71	36	a	a	X
cana-2747	71	37	y	y	NOUN
cana-2747	71	38	e	e	NOUN
cana-2747	71	39	r	r	NOUN
cana-2747	71	40	d	d	PROPN
cana-2747	71	41	e	e	PROPN
cana-2747	71	42	n	n	NOUN
cana-2747	71	43	s	s	PROPN
cana-2747	71	44	e	e	X
cana-2747	71	45	l	l	X
cana-2747	71	46	a	a	X
cana-2747	71	47	y	y	NOUN
cana-2747	71	48	e	e	NOUN
cana-2747	71	49	r	r	NOUN
cana-2747	71	50	c	c	NOUN
cana-2747	71	51	o	o	NOUN
cana-2747	72	1	n	n	ADP
cana-2747	72	2	c	c	PROPN
cana-2747	72	3	a	a	DET
cana-2747	72	4	t	t	X
cana-2747	72	5	e	e	NOUN
cana-2747	72	6	n	n	CCONJ
cana-2747	72	7	a	a	DET
cana-2747	72	8	t	t	NOUN
cana-2747	72	9	e	e	NOUN
cana-2747	72	10	l	l	NOUN
cana-2747	72	11	a	a	PROPN
cana-2747	72	12	y	y	PROPN
cana-2747	72	13	e	e	NOUN
cana-2747	72	14	r	r	NOUN
cana-2747	72	15	communications	communication	NOUN
cana-2747	72	16	on	on	ADP
cana-2747	72	17	applied	apply	VERB
cana-2747	72	18	nonlinear	nonlinear	ADJ
cana-2747	72	19	analysis	analysis	NOUN
cana-2747	72	20	issn	issn	NOUN
cana-2747	72	21	:	:	PUNCT
cana-2747	72	22	1074	1074	NUM
cana-2747	72	23	-	-	PUNCT
cana-2747	72	24	133x	133x	NUM
cana-2747	72	25	vol	vol	NOUN
cana-2747	72	26	32	32	NUM
cana-2747	72	27	no	no	NOUN
cana-2747	72	28	.	.	PUNCT
cana-2747	73	1	4s	4s	NUM
cana-2747	73	2	(	(	PUNCT
cana-2747	73	3	2025	2025	NUM
cana-2747	73	4	)	)	PUNCT
cana-2747	73	5	172	172	NUM
cana-2747	73	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	73	7	or	or	CCONJ
cana-2747	73	8	semantic	semantic	ADJ
cana-2747	73	9	segmentation	segmentation	NOUN
cana-2747	73	10	.	.	PUNCT
cana-2747	74	1	in	in	ADP
cana-2747	74	2	the	the	DET
cana-2747	74	3	context	context	NOUN
cana-2747	74	4	of	of	ADP
cana-2747	74	5	eeg	eeg	NOUN
cana-2747	74	6	signals	signal	NOUN
cana-2747	74	7	,	,	PUNCT
cana-2747	74	8	lstms	lstms	NOUN
cana-2747	74	9	,	,	PUNCT
cana-2747	74	10	which	which	PRON
cana-2747	74	11	take	take	VERB
cana-2747	74	12	input	input	NOUN
cana-2747	74	13	from	from	ADP
cana-2747	74	14	the	the	DET
cana-2747	74	15	local	local	ADJ
cana-2747	74	16	features	feature	NOUN
cana-2747	74	17	learned	learn	VERB
cana-2747	74	18	by	by	ADP
cana-2747	74	19	cnns	cnn	NOUN
cana-2747	74	20	,	,	PUNCT
cana-2747	74	21	excel	excel	VERB
cana-2747	74	22	at	at	ADP
cana-2747	74	23	capturing	capture	VERB
cana-2747	74	24	temporal	temporal	ADJ
cana-2747	74	25	information.[14]wilaiprasitporn	information.[14]wilaiprasitporn	VERB
cana-2747	74	26	et	et	NOUN
cana-2747	74	27	al	al	PROPN
cana-2747	74	28	focus	focus	VERB
cana-2747	74	29	on	on	ADP
cana-2747	74	30	improving	improve	VERB
cana-2747	74	31	eeg	eeg	NOUN
cana-2747	74	32	-	-	PUNCT
cana-2747	74	33	based	base	VERB
cana-2747	74	34	identification	identification	NOUN
cana-2747	74	35	using	use	VERB
cana-2747	74	36	deep	deep	ADJ
cana-2747	74	37	learning	learning	NOUN
cana-2747	74	38	,	,	PUNCT
cana-2747	74	39	especially	especially	ADV
cana-2747	74	40	while	while	SCONJ
cana-2747	74	41	people	people	NOUN
cana-2747	74	42	are	be	AUX
cana-2747	74	43	in	in	ADP
cana-2747	74	44	different	different	ADJ
cana-2747	74	45	emotional	emotional	ADJ
cana-2747	74	46	states	state	NOUN
cana-2747	74	47	(	(	PUNCT
cana-2747	74	48	affective	affective	NOUN
cana-2747	74	49	eeg	eeg	NOUN
cana-2747	74	50	)	)	PUNCT
cana-2747	74	51	and	and	CCONJ
cana-2747	74	52	uses	use	VERB
cana-2747	74	53	a	a	DET
cana-2747	74	54	mix	mix	NOUN
cana-2747	74	55	of	of	ADP
cana-2747	74	56	cnns	cnn	NOUN
cana-2747	74	57	,	,	PUNCT
cana-2747	74	58	rnns	rnn	NOUN
cana-2747	74	59	to	to	PART
cana-2747	74	60	analyze	analyze	VERB
cana-2747	74	61	both	both	CCONJ
cana-2747	74	62	the	the	DET
cana-2747	74	63	spatial	spatial	ADJ
cana-2747	74	64	and	and	CCONJ
cana-2747	74	65	temporal	temporal	ADJ
cana-2747	74	66	aspects	aspect	NOUN
cana-2747	74	67	of	of	ADP
cana-2747	74	68	eeg	eeg	NOUN
cana-2747	74	69	signals	signal	NOUN
cana-2747	74	70	.	.	PUNCT
cana-2747	75	1	utilizing	utilize	VERB
cana-2747	75	2	biometric	biometric	ADJ
cana-2747	75	3	methods	method	NOUN
cana-2747	75	4	like	like	ADP
cana-2747	75	5	eeg	eeg	PROPN
cana-2747	75	6	is	be	AUX
cana-2747	75	7	vital	vital	ADJ
cana-2747	75	8	for	for	ADP
cana-2747	75	9	robust	robust	ADJ
cana-2747	75	10	person	person	NOUN
cana-2747	75	11	recognition	recognition	NOUN
cana-2747	75	12	,	,	PUNCT
cana-2747	75	13	addressing	address	VERB
cana-2747	75	14	vulnerabilities	vulnerability	NOUN
cana-2747	75	15	in	in	ADP
cana-2747	75	16	traditional	traditional	ADJ
cana-2747	75	17	modalities	modality	NOUN
cana-2747	75	18	.	.	PUNCT
cana-2747	76	1	existing	exist	VERB
cana-2747	76	2	eeg	eeg	NOUN
cana-2747	76	3	approaches	approach	NOUN
cana-2747	76	4	face	face	VERB
cana-2747	76	5	limitations	limitation	NOUN
cana-2747	76	6	in	in	ADP
cana-2747	76	7	scalability	scalability	NOUN
cana-2747	76	8	and	and	CCONJ
cana-2747	76	9	generalization	generalization	NOUN
cana-2747	76	10	.	.	PUNCT
cana-2747	77	1	alsumari	alsumari	PROPN
cana-2747	77	2	et	et	PROPN
cana-2747	77	3	al	al	PROPN
cana-2747	78	1	[	[	X
cana-2747	78	2	21	21	NUM
cana-2747	78	3	]	]	PUNCT
cana-2747	78	4	introduce	introduce	VERB
cana-2747	78	5	a	a	DET
cana-2747	78	6	lightweight	lightweight	ADJ
cana-2747	78	7	cnn	cnn	PROPN
cana-2747	78	8	model	model	NOUN
cana-2747	78	9	,	,	PUNCT
cana-2747	78	10	achieving	achieve	VERB
cana-2747	78	11	high	high	ADJ
cana-2747	78	12	identification	identification	NOUN
cana-2747	78	13	accuracy	accuracy	NOUN
cana-2747	78	14	and	and	CCONJ
cana-2747	78	15	authentication	authentication	NOUN
cana-2747	78	16	performance	performance	NOUN
cana-2747	78	17	with	with	ADP
cana-2747	78	18	minimal	minimal	ADJ
cana-2747	78	19	eeg	eeg	NOUN
cana-2747	78	20	data	datum	NOUN
cana-2747	78	21	,	,	PUNCT
cana-2747	78	22	promising	promise	VERB
cana-2747	78	23	real	real	ADJ
cana-2747	78	24	-	-	PUNCT
cana-2747	78	25	world	world	NOUN
cana-2747	78	26	application	application	NOUN
cana-2747	78	27	in	in	ADP
cana-2747	78	28	biometric	biometric	ADJ
cana-2747	78	29	security	security	NOUN
cana-2747	78	30	systems	system	NOUN
cana-2747	78	31	.	.	PUNCT
cana-2747	79	1	zhang	zhang	PROPN
cana-2747	79	2	et	et	PROPN
cana-2747	79	3	al.[22	al.[22	PROPN
cana-2747	79	4	]	]	PUNCT
cana-2747	79	5	attempted	attempt	VERB
cana-2747	79	6	to	to	PART
cana-2747	79	7	use	use	VERB
cana-2747	79	8	a	a	DET
cana-2747	79	9	3d	3d	NUM
cana-2747	79	10	cnn	cnn	NOUN
cana-2747	79	11	to	to	PART
cana-2747	79	12	directly	directly	ADV
cana-2747	79	13	capture	capture	VERB
cana-2747	79	14	spatiotemporal	spatiotemporal	ADJ
cana-2747	79	15	information	information	NOUN
cana-2747	79	16	in	in	ADP
cana-2747	79	17	a	a	DET
cana-2747	79	18	single	single	ADJ
cana-2747	79	19	layer	layer	NOUN
cana-2747	79	20	.	.	PUNCT
cana-2747	80	1	however	however	ADV
cana-2747	80	2	,	,	PUNCT
cana-2747	80	3	their	their	PRON
cana-2747	80	4	results	result	NOUN
cana-2747	80	5	were	be	AUX
cana-2747	80	6	slightly	slightly	ADV
cana-2747	80	7	inferior	inferior	ADJ
cana-2747	80	8	to	to	ADP
cana-2747	80	9	those	those	PRON
cana-2747	80	10	achieved	achieve	VERB
cana-2747	80	11	with	with	ADP
cana-2747	80	12	the	the	DET
cana-2747	80	13	combined	combined	ADJ
cana-2747	80	14	cnn	cnn	PROPN
cana-2747	80	15	-	-	PUNCT
cana-2747	80	16	lstm	lstm	PROPN
cana-2747	80	17	model	model	NOUN
cana-2747	80	18	.	.	PUNCT
cana-2747	81	1	this	this	DET
cana-2747	81	2	difference	difference	NOUN
cana-2747	81	3	may	may	AUX
cana-2747	81	4	be	be	AUX
cana-2747	81	5	due	due	ADJ
cana-2747	81	6	to	to	ADP
cana-2747	81	7	the	the	DET
cana-2747	81	8	fact	fact	NOUN
cana-2747	81	9	that	that	SCONJ
cana-2747	81	10	lstms	lstms	NOUN
cana-2747	81	11	are	be	AUX
cana-2747	81	12	generally	generally	ADV
cana-2747	81	13	more	more	ADV
cana-2747	81	14	effective	effective	ADJ
cana-2747	81	15	at	at	ADP
cana-2747	81	16	handling	handle	VERB
cana-2747	81	17	temporal	temporal	ADJ
cana-2747	81	18	information	information	NOUN
cana-2747	81	19	.	.	PUNCT
cana-2747	82	1	lstms	lstms	PROPN
cana-2747	82	2	can	can	AUX
cana-2747	82	3	selectively	selectively	ADV
cana-2747	82	4	retain	retain	VERB
cana-2747	82	5	or	or	CCONJ
cana-2747	82	6	discard	discard	VERB
cana-2747	82	7	information	information	NOUN
cana-2747	82	8	based	base	VERB
cana-2747	82	9	on	on	ADP
cana-2747	82	10	context	context	NOUN
cana-2747	82	11	,	,	PUNCT
cana-2747	82	12	which	which	PRON
cana-2747	82	13	is	be	AUX
cana-2747	82	14	crucial	crucial	ADJ
cana-2747	82	15	for	for	ADP
cana-2747	82	16	processing	process	VERB
cana-2747	82	17	sequential	sequential	ADJ
cana-2747	82	18	data	datum	NOUN
cana-2747	82	19	.	.	PUNCT
cana-2747	83	1	as	as	ADP
cana-2747	83	2	a	a	DET
cana-2747	83	3	specialized	specialized	ADJ
cana-2747	83	4	type	type	NOUN
cana-2747	83	5	of	of	ADP
cana-2747	83	6	recurrent	recurrent	ADJ
cana-2747	83	7	neural	neural	ADJ
cana-2747	83	8	network	network	NOUN
cana-2747	83	9	(	(	PUNCT
cana-2747	83	10	rnn	rnn	PROPN
cana-2747	83	11	)	)	PUNCT
cana-2747	83	12	,	,	PUNCT
cana-2747	83	13	lstms	lstms	PROPN
cana-2747	83	14	are	be	AUX
cana-2747	83	15	designed	design	VERB
cana-2747	83	16	to	to	PART
cana-2747	83	17	manage	manage	VERB
cana-2747	83	18	longrange	longrange	ADJ
cana-2747	83	19	dependencies	dependency	NOUN
cana-2747	83	20	in	in	ADP
cana-2747	83	21	time	time	NOUN
cana-2747	83	22	-	-	PUNCT
cana-2747	83	23	series	series	NOUN
cana-2747	83	24	data	datum	NOUN
cana-2747	83	25	.	.	PUNCT
cana-2747	84	1	in	in	ADP
cana-2747	84	2	this	this	DET
cana-2747	84	3	context	context	NOUN
cana-2747	84	4	,	,	PUNCT
cana-2747	84	5	lstms	lstms	ADJ
cana-2747	84	6	use	use	VERB
cana-2747	84	7	rectified	rectify	VERB
cana-2747	84	8	linear	linear	ADJ
cana-2747	84	9	unit	unit	NOUN
cana-2747	84	10	(	(	PUNCT
cana-2747	84	11	relu	relu	NOUN
cana-2747	84	12	)	)	PUNCT
cana-2747	84	13	activation	activation	NOUN
cana-2747	84	14	functions	function	NOUN
cana-2747	84	15	,	,	PUNCT
cana-2747	84	16	which	which	PRON
cana-2747	84	17	provide	provide	VERB
cana-2747	84	18	several	several	ADJ
cana-2747	84	19	benefits	benefit	NOUN
cana-2747	84	20	over	over	ADP
cana-2747	84	21	traditional	traditional	ADJ
cana-2747	84	22	functions	function	NOUN
cana-2747	84	23	like	like	ADP
cana-2747	84	24	tanh	tanh	NOUN
cana-2747	84	25	.	.	PUNCT
cana-2747	85	1	the	the	DET
cana-2747	85	2	lstm	lstm	PROPN
cana-2747	85	3	unit	unit	NOUN
cana-2747	85	4	's	's	PART
cana-2747	85	5	output	output	NOUN
cana-2747	85	6	is	be	AUX
cana-2747	85	7	calculated	calculate	VERB
cana-2747	85	8	using	use	VERB
cana-2747	85	9	the	the	DET
cana-2747	85	10	forget	forget	NOUN
cana-2747	85	11	gate	gate	NOUN
cana-2747	85	12	,	,	PUNCT
cana-2747	85	13	input	input	NOUN
cana-2747	85	14	gate	gate	NOUN
cana-2747	85	15	,	,	PUNCT
cana-2747	85	16	and	and	CCONJ
cana-2747	85	17	relu	relu	NOUN
cana-2747	85	18	activation	activation	NOUN
cana-2747	85	19	functions	function	NOUN
cana-2747	85	20	.	.	PUNCT
cana-2747	86	1	1	1	X
cana-2747	86	2	.	.	X
cana-2747	86	3	cell	cell	NOUN
cana-2747	86	4	state	state	PROPN
cana-2747	86	5	𝒄𝒕and	𝒄𝒕and	CCONJ
cana-2747	86	6	gates	gates	PROPN
cana-2747	86	7	:	:	PUNCT
cana-2747	86	8	the	the	DET
cana-2747	86	9	lstm	lstm	PROPN
cana-2747	86	10	unit	unit	NOUN
cana-2747	86	11	maintains	maintain	VERB
cana-2747	86	12	a	a	DET
cana-2747	86	13	cell	cell	NOUN
cana-2747	86	14	state	state	NOUN
cana-2747	86	15	𝑐𝑡	𝑐𝑡	INTJ
cana-2747	86	16	that	that	PRON
cana-2747	86	17	acts	act	VERB
cana-2747	86	18	as	as	ADP
cana-2747	86	19	its	its	PRON
cana-2747	86	20	memory	memory	NOUN
cana-2747	86	21	.	.	PUNCT
cana-2747	87	1	gates	gate	NOUN
cana-2747	87	2	,	,	PUNCT
cana-2747	87	3	including	include	VERB
cana-2747	87	4	the	the	DET
cana-2747	87	5	forget	forget	PROPN
cana-2747	87	6	gate	gate	PROPN
cana-2747	87	7	𝑓𝑡	𝑓𝑡	PROPN
cana-2747	87	8	,	,	PUNCT
cana-2747	87	9	input	input	NOUN
cana-2747	87	10	gate	gate	NOUN
cana-2747	87	11	𝑖𝑡	𝑖𝑡	NOUN
cana-2747	87	12	,	,	PUNCT
cana-2747	87	13	and	and	CCONJ
cana-2747	87	14	output	output	NOUN
cana-2747	87	15	gate	gate	PROPN
cana-2747	87	16	𝑜𝑡	𝑜𝑡	PROPN
cana-2747	87	17	,	,	PUNCT
cana-2747	87	18	manage	manage	VERB
cana-2747	87	19	the	the	DET
cana-2747	87	20	flow	flow	NOUN
cana-2747	87	21	of	of	ADP
cana-2747	87	22	information	information	NOUN
cana-2747	87	23	within	within	ADP
cana-2747	87	24	the	the	DET
cana-2747	87	25	lstm	lstm	NOUN
cana-2747	87	26	:	:	PUNCT
cana-2747	87	27	forget	forget	VERB
cana-2747	87	28	gate	gate	PROPN
cana-2747	87	29	(	(	PUNCT
cana-2747	87	30	𝑓𝑡	𝑓𝑡	PROPN
cana-2747	87	31	):	):	PUNCT
cana-2747	87	32	decides	decide	VERB
cana-2747	87	33	which	which	DET
cana-2747	87	34	information	information	NOUN
cana-2747	87	35	from	from	ADP
cana-2747	87	36	the	the	DET
cana-2747	87	37	previous	previous	ADJ
cana-2747	87	38	cell	cell	NOUN
cana-2747	87	39	state𝑐𝑡−1	state𝑐𝑡−1	NUM
cana-2747	87	40	should	should	AUX
cana-2747	87	41	be	be	AUX
cana-2747	87	42	removed	remove	VERB
cana-2747	87	43	.	.	PUNCT
cana-2747	88	1	input	input	NOUN
cana-2747	88	2	gate	gate	NOUN
cana-2747	88	3	(	(	PUNCT
cana-2747	88	4	𝑖𝑡	𝑖𝑡	NOUN
cana-2747	88	5	):	):	PUNCT
cana-2747	88	6	determines	determine	NOUN
cana-2747	88	7	which	which	PRON
cana-2747	88	8	new	new	ADJ
cana-2747	88	9	information	information	NOUN
cana-2747	88	10	should	should	AUX
cana-2747	88	11	be	be	AUX
cana-2747	88	12	added	add	VERB
cana-2747	88	13	to	to	ADP
cana-2747	88	14	the	the	DET
cana-2747	88	15	current	current	ADJ
cana-2747	88	16	cell	cell	NOUN
cana-2747	88	17	state	state	NOUN
cana-2747	88	18	𝑐𝑡.	𝑐𝑡.	PROPN
cana-2747	88	19	output	output	NOUN
cana-2747	88	20	gate	gate	NOUN
cana-2747	88	21	(	(	PUNCT
cana-2747	88	22	𝑜𝑡	𝑜𝑡	PROPN
cana-2747	88	23	):	):	PUNCT
cana-2747	88	24	regregulates	regregulate	NOUN
cana-2747	88	25	which	which	PRON
cana-2747	88	26	parts	part	NOUN
cana-2747	88	27	of	of	ADP
cana-2747	88	28	the	the	DET
cana-2747	88	29	cell	cell	NOUN
cana-2747	88	30	state	state	NOUN
cana-2747	88	31	contribute	contribute	VERB
cana-2747	88	32	to	to	ADP
cana-2747	88	33	the	the	DET
cana-2747	88	34	output	output	NOUN
cana-2747	88	35	ℎ𝑡.	ℎ𝑡.	NOUN
cana-2747	88	36	2	2	NUM
cana-2747	88	37	.	.	PUNCT
cana-2747	88	38	equations	equation	NOUN
cana-2747	88	39	for	for	ADP
cana-2747	88	40	lstm	lstm	ADJ
cana-2747	88	41	operations	operation	NOUN
cana-2747	88	42	with	with	ADP
cana-2747	88	43	relu	relu	NOUN
cana-2747	88	44	:	:	PUNCT
cana-2747	88	45	the	the	DET
cana-2747	88	46	cell	cell	NOUN
cana-2747	88	47	state	state	NOUN
cana-2747	88	48	𝑐𝑡	𝑐𝑡	INTJ
cana-2747	88	49	is	be	AUX
cana-2747	88	50	updated	update	VERB
cana-2747	88	51	using	use	VERB
cana-2747	88	52	the	the	DET
cana-2747	88	53	forget	forget	PROPN
cana-2747	88	54	gate	gate	PROPN
cana-2747	88	55	𝑓𝑡	𝑓𝑡	PROPN
cana-2747	88	56	,	,	PUNCT
cana-2747	88	57	input	input	NOUN
cana-2747	88	58	gate	gate	NOUN
cana-2747	88	59	𝑖𝑡	𝑖𝑡	NOUN
cana-2747	88	60	,	,	PUNCT
cana-2747	88	61	and	and	CCONJ
cana-2747	88	62	a	a	DET
cana-2747	88	63	candidate	candidate	NOUN
cana-2747	88	64	update	update	NOUN
cana-2747	88	65	𝑐𝑡	𝑐𝑡	INTJ
cana-2747	88	66	^	^	PUNCT
cana-2747	88	67	(	(	PUNCT
cana-2747	88	68	computed	compute	VERB
cana-2747	88	69	using	use	VERB
cana-2747	88	70	relu	relu	NOUN
cana-2747	88	71	activation	activation	NOUN
cana-2747	88	72	):	):	PUNCT
cana-2747	88	73	𝑓𝑡	𝑓𝑡	PROPN
cana-2747	88	74	=	=	PUNCT
cana-2747	88	75	𝜎൫𝑤𝑓.ൣℎ𝑡−1,𝑥𝑡൧	𝜎൫𝑤𝑓.ൣℎ𝑡−1,𝑥𝑡൧	PROPN
cana-2747	88	76	+	+	CCONJ
cana-2747	88	77	𝑏𝑓൯	𝑏𝑓൯	PROPN
cana-2747	88	78	(	(	PUNCT
cana-2747	88	79	1	1	NUM
cana-2747	88	80	)	)	PUNCT
cana-2747	88	81	𝑖𝑡	𝑖𝑡	NOUN
cana-2747	89	1	=	=	PUNCT
cana-2747	89	2	𝜎൫𝑤𝑖.ൣℎ𝑡−1,𝑥𝑡൧	𝜎൫𝑤𝑖.ൣℎ𝑡−1,𝑥𝑡൧	NOUN
cana-2747	89	3	+	+	CCONJ
cana-2747	89	4	𝑏𝑖൯	𝑏𝑖൯	NOUN
cana-2747	89	5	(	(	PUNCT
cana-2747	89	6	2	2	NUM
cana-2747	89	7	)	)	PUNCT
cana-2747	89	8	𝑐𝑡	𝑐𝑡	ADV
cana-2747	89	9	^	^	PUNCT
cana-2747	89	10	=	=	SYM
cana-2747	89	11	𝑅𝑒𝐿𝑈(𝑤𝑐.ൣℎ𝑡−1,𝑥𝑡൧	𝑅𝑒𝐿𝑈(𝑤𝑐.ൣℎ𝑡−1,𝑥𝑡൧	NOUN
cana-2747	89	12	+	+	CCONJ
cana-2747	89	13	𝑏𝑐	𝑏𝑐	X
cana-2747	89	14	)	)	PUNCT
cana-2747	89	15	(	(	PUNCT
cana-2747	89	16	3	3	X
cana-2747	89	17	)	)	PUNCT
cana-2747	89	18	𝑐𝑡	𝑐𝑡	ADP
cana-2747	89	19	=	=	SYM
cana-2747	89	20	𝑓𝑡	𝑓𝑡	PROPN
cana-2747	89	21	°	°	PROPN
cana-2747	89	22	𝑐𝑡−1	𝑐𝑡−1	PROPN
cana-2747	89	23	+	+	CCONJ
cana-2747	89	24	𝑖𝑡	𝑖𝑡	NOUN
cana-2747	89	25	°	°	ADV
cana-2747	89	26	𝑐𝑡	𝑐𝑡	ADV
cana-2747	89	27	^	^	PUNCT
cana-2747	89	28	(	(	PUNCT
cana-2747	89	29	4	4	X
cana-2747	89	30	)	)	PUNCT
cana-2747	89	31	where𝑤𝑓,𝑤𝑖,𝑤𝑐,are	where𝑤𝑓,𝑤𝑖,𝑤𝑐,are	NOUN
cana-2747	89	32	weight	weight	NOUN
cana-2747	89	33	matrix,ℎ𝑡−1,previous	matrix,ℎ𝑡−1,previous	ADJ
cana-2747	89	34	hidden	hide	VERB
cana-2747	89	35	state	state	NOUN
cana-2747	89	36	and	and	CCONJ
cana-2747	89	37	𝑥𝑡	𝑥𝑡	ADV
cana-2747	89	38	with	with	ADP
cana-2747	89	39	various𝑏𝑓𝑏𝑖𝑏𝑐	various𝑏𝑓𝑏𝑖𝑏𝑐	NOUN
cana-2747	89	40	bias	bias	NOUN
cana-2747	89	41	terms.𝑐𝑡	terms.𝑐𝑡	PROPN
cana-2747	89	42	^	^	PUNCT
cana-2747	89	43	represents	represent	VERB
cana-2747	89	44	candidate	candidate	NOUN
cana-2747	89	45	cell	cell	NOUN
cana-2747	89	46	update	update	NOUN
cana-2747	89	47	.	.	PUNCT
cana-2747	90	1	communications	communication	NOUN
cana-2747	90	2	on	on	ADP
cana-2747	90	3	applied	apply	VERB
cana-2747	90	4	nonlinear	nonlinear	ADJ
cana-2747	90	5	analysis	analysis	NOUN
cana-2747	90	6	issn	issn	NOUN
cana-2747	90	7	:	:	PUNCT
cana-2747	90	8	1074	1074	NUM
cana-2747	90	9	-	-	PUNCT
cana-2747	90	10	133x	133x	NUM
cana-2747	90	11	vol	vol	NOUN
cana-2747	90	12	32	32	NUM
cana-2747	90	13	no	no	NOUN
cana-2747	90	14	.	.	PUNCT
cana-2747	91	1	4s	4s	NUM
cana-2747	91	2	(	(	PUNCT
cana-2747	91	3	2025	2025	NUM
cana-2747	91	4	)	)	PUNCT
cana-2747	91	5	173	173	NUM
cana-2747	91	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	91	7	3	3	X
cana-2747	91	8	.	.	PUNCT
cana-2747	91	9	hidden	hide	VERB
cana-2747	91	10	state	state	NOUN
cana-2747	91	11	𝒉𝒕computation	𝒉𝒕computation	NOUN
cana-2747	91	12	:	:	PUNCT
cana-2747	91	13	the	the	DET
cana-2747	91	14	output	output	NOUN
cana-2747	91	15	gate	gate	NOUN
cana-2747	91	16	𝑜𝑡modulates	𝑜𝑡modulate	VERB
cana-2747	91	17	the	the	DET
cana-2747	91	18	cell	cell	NOUN
cana-2747	91	19	state𝑐𝑡before	state𝑐𝑡before	ADJ
cana-2747	91	20	passing	pass	VERB
cana-2747	91	21	it	it	PRON
cana-2747	91	22	through	through	ADP
cana-2747	91	23	relu	relu	NOUN
cana-2747	91	24	activation	activation	NOUN
cana-2747	91	25	to	to	PART
cana-2747	91	26	compute	compute	VERB
cana-2747	91	27	the	the	DET
cana-2747	91	28	hidden	hidden	ADJ
cana-2747	91	29	state	state	NOUN
cana-2747	91	30	ℎ𝑡	ℎ𝑡	NOUN
cana-2747	91	31	:	:	PUNCT
cana-2747	91	32	𝑜𝑡	𝑜𝑡	PROPN
cana-2747	91	33	=	=	SYM
cana-2747	91	34	𝜎൫𝑤𝑜.ൣℎ𝑡−1,𝑥𝑡൧	𝜎൫𝑤𝑜.ൣℎ𝑡−1,𝑥𝑡൧	NOUN
cana-2747	91	35	+	+	CCONJ
cana-2747	91	36	𝑏𝑜൯	𝑏𝑜൯	PROPN
cana-2747	91	37	(	(	PUNCT
cana-2747	91	38	5	5	NUM
cana-2747	91	39	)	)	PUNCT
cana-2747	91	40	ℎ𝑡	ℎ𝑡	NOUN
cana-2747	91	41	=	=	PUNCT
cana-2747	91	42	𝑜𝑡	𝑜𝑡	NOUN
cana-2747	91	43	°	°	NOUN
cana-2747	91	44	𝑅𝑒𝐿𝑈(𝑐𝑡	𝑅𝑒𝐿𝑈(𝑐𝑡	NUM
cana-2747	91	45	)	)	PUNCT
cana-2747	91	46	(	(	PUNCT
cana-2747	91	47	6	6	X
cana-2747	91	48	)	)	PUNCT
cana-2747	91	49	ℎ𝑡	ℎ𝑡	NOUN
cana-2747	91	50	denotes	denote	VERB
cana-2747	91	51	the	the	DET
cana-2747	91	52	current	current	ADJ
cana-2747	91	53	hidden	hide	VERB
cana-2747	91	54	state	state	NOUN
cana-2747	91	55	at	at	ADP
cana-2747	91	56	time	time	NOUN
cana-2747	91	57	step	step	NOUN
cana-2747	91	58	t	t	PROPN
cana-2747	91	59	and	and	CCONJ
cana-2747	91	60	𝑜𝑡	𝑜𝑡	PROPN
cana-2747	91	61	is	be	AUX
cana-2747	91	62	output	output	NOUN
cana-2747	91	63	of	of	ADP
cana-2747	91	64	gate	gate	NOUN
cana-2747	91	65	output	output	NOUN
cana-2747	91	66	.	.	PUNCT
cana-2747	92	1	relu	relu	NOUN
cana-2747	92	2	is	be	AUX
cana-2747	92	3	a	a	DET
cana-2747	92	4	rectified	rectified	ADJ
cana-2747	92	5	linear	linear	NOUN
cana-2747	92	6	unit	unit	NOUN
cana-2747	92	7	used	use	VERB
cana-2747	92	8	as	as	ADP
cana-2747	92	9	an	an	DET
cana-2747	92	10	activation	activation	NOUN
cana-2747	92	11	function	function	NOUN
cana-2747	92	12	.	.	PUNCT
cana-2747	93	1	𝑐𝑡	𝑐𝑡	PROPN
cana-2747	93	2	represents	represent	VERB
cana-2747	93	3	the	the	DET
cana-2747	93	4	current	current	ADJ
cana-2747	93	5	cell	cell	NOUN
cana-2747	93	6	state	state	NOUN
cana-2747	93	7	,	,	PUNCT
cana-2747	93	8	°	°	ADP
cana-2747	93	9	shows	show	VERB
cana-2747	93	10	element	element	ADJ
cana-2747	93	11	-	-	ADJ
cana-2747	93	12	wise	wise	ADJ
cana-2747	93	13	multiplication	multiplication	NOUN
cana-2747	93	14	operation	operation	NOUN
cana-2747	93	15	.	.	PUNCT
cana-2747	94	1	advantages	advantage	NOUN
cana-2747	94	2	of	of	ADP
cana-2747	94	3	relu	relu	NOUN
cana-2747	94	4	in	in	ADP
cana-2747	94	5	lstms	lstms	ADJ
cana-2747	94	6	non	non	ADJ
cana-2747	94	7	-	-	ADJ
cana-2747	94	8	saturating	saturate	VERB
cana-2747	94	9	activation	activation	NOUN
cana-2747	94	10	:	:	PUNCT
cana-2747	94	11	relu	relu	NOUN
cana-2747	94	12	does	do	AUX
cana-2747	94	13	not	not	PART
cana-2747	94	14	suffer	suffer	VERB
cana-2747	94	15	from	from	ADP
cana-2747	94	16	the	the	DET
cana-2747	94	17	vanishing	vanish	VERB
cana-2747	94	18	gradient	gradient	NOUN
cana-2747	94	19	problem	problem	NOUN
cana-2747	94	20	encountered	encounter	VERB
cana-2747	94	21	with	with	ADP
cana-2747	94	22	tanh	tanh	NOUN
cana-2747	94	23	or	or	CCONJ
cana-2747	94	24	sigmoid	sigmoid	NOUN
cana-2747	94	25	activations	activation	NOUN
cana-2747	94	26	,	,	PUNCT
cana-2747	94	27	which	which	PRON
cana-2747	94	28	accelerates	accelerate	VERB
cana-2747	94	29	convergence	convergence	NOUN
cana-2747	94	30	during	during	ADP
cana-2747	94	31	training	training	NOUN
cana-2747	94	32	.	.	PUNCT
cana-2747	95	1	sparse	sparse	ADJ
cana-2747	95	2	activation	activation	NOUN
cana-2747	95	3	:	:	PUNCT
cana-2747	95	4	relu	relu	NOUN
cana-2747	95	5	activations	activation	NOUN
cana-2747	95	6	are	be	AUX
cana-2747	95	7	sparser	sparse	ADJ
cana-2747	95	8	compared	compare	VERB
cana-2747	95	9	to	to	ADP
cana-2747	95	10	sigmoid	sigmoid	NOUN
cana-2747	95	11	or	or	CCONJ
cana-2747	95	12	tanh	tanh	NOUN
cana-2747	95	13	,	,	PUNCT
cana-2747	95	14	promoting	promote	VERB
cana-2747	95	15	faster	fast	ADJ
cana-2747	95	16	computation	computation	NOUN
cana-2747	95	17	and	and	CCONJ
cana-2747	95	18	improved	improved	ADJ
cana-2747	95	19	network	network	NOUN
cana-2747	95	20	efficiency	efficiency	NOUN
cana-2747	95	21	.	.	PUNCT
cana-2747	96	1	stability	stability	NOUN
cana-2747	96	2	and	and	CCONJ
cana-2747	96	3	expressiveness	expressiveness	NOUN
cana-2747	96	4	:	:	PUNCT
cana-2747	96	5	the	the	DET
cana-2747	96	6	linear	linear	ADJ
cana-2747	96	7	nature	nature	NOUN
cana-2747	96	8	of	of	ADP
cana-2747	96	9	relu	relu	NOUN
cana-2747	96	10	allows	allow	VERB
cana-2747	96	11	lstms	lstms	ADJ
cana-2747	96	12	to	to	PART
cana-2747	96	13	model	model	VERB
cana-2747	96	14	complex	complex	ADJ
cana-2747	96	15	non	non	ADJ
cana-2747	96	16	-	-	ADJ
cana-2747	96	17	linear	linear	ADJ
cana-2747	96	18	relationships	relationship	NOUN
cana-2747	96	19	more	more	ADV
cana-2747	96	20	effectively	effectively	ADV
cana-2747	96	21	,	,	PUNCT
cana-2747	96	22	enhancing	enhance	VERB
cana-2747	96	23	the	the	DET
cana-2747	96	24	network	network	NOUN
cana-2747	96	25	3	3	NUM
cana-2747	96	26	.	.	PUNCT
cana-2747	96	27	materials	material	NOUN
cana-2747	96	28	and	and	CCONJ
cana-2747	96	29	methods	method	NOUN
cana-2747	96	30	in	in	ADP
cana-2747	96	31	this	this	DET
cana-2747	96	32	segment	segment	NOUN
cana-2747	96	33	,	,	PUNCT
cana-2747	96	34	we	we	PRON
cana-2747	96	35	initially	initially	ADV
cana-2747	96	36	presented	present	VERB
cana-2747	96	37	the	the	DET
cana-2747	96	38	deap	deap	ADJ
cana-2747	96	39	affective	affective	NOUN
cana-2747	96	40	eeg	eeg	NOUN
cana-2747	96	41	dataset	dataset	NOUN
cana-2747	97	1	[	[	X
cana-2747	97	2	23	23	NUM
cana-2747	97	3	]	]	PUNCT
cana-2747	97	4	,	,	PUNCT
cana-2747	97	5	which	which	PRON
cana-2747	97	6	served	serve	VERB
cana-2747	97	7	as	as	ADP
cana-2747	97	8	the	the	DET
cana-2747	97	9	foundation	foundation	NOUN
cana-2747	97	10	for	for	ADP
cana-2747	97	11	our	our	PRON
cana-2747	97	12	experimental	experimental	ADJ
cana-2747	97	13	investigations	investigation	NOUN
cana-2747	97	14	,	,	PUNCT
cana-2747	97	15	alongside	alongside	ADP
cana-2747	97	16	outlining	outline	VERB
cana-2747	97	17	the	the	DET
cana-2747	97	18	preprocessing	preprocessing	NOUN
cana-2747	97	19	procedures	procedure	NOUN
cana-2747	97	20	integral	integral	ADJ
cana-2747	97	21	to	to	ADP
cana-2747	97	22	our	our	PRON
cana-2747	97	23	solution	solution	NOUN
cana-2747	97	24	.	.	PUNCT
cana-2747	98	1	given	give	VERB
cana-2747	98	2	that	that	DET
cana-2747	98	3	deap	deap	NOUN
cana-2747	98	4	was	be	AUX
cana-2747	98	5	primarily	primarily	ADV
cana-2747	98	6	crafted	craft	VERB
cana-2747	98	7	for	for	ADP
cana-2747	98	8	mental	mental	ADJ
cana-2747	98	9	state	state	NOUN
cana-2747	98	10	classification	classification	NOUN
cana-2747	98	11	,	,	PUNCT
cana-2747	98	12	we	we	PRON
cana-2747	98	13	detailed	detail	VERB
cana-2747	98	14	our	our	PRON
cana-2747	98	15	approach	approach	NOUN
cana-2747	98	16	to	to	ADP
cana-2747	98	17	partitioning	partition	VERB
cana-2747	98	18	the	the	DET
cana-2747	98	19	data	datum	NOUN
cana-2747	98	20	to	to	PART
cana-2747	98	21	suit	suit	VERB
cana-2747	98	22	the	the	DET
cana-2747	98	23	demands	demand	NOUN
cana-2747	98	24	of	of	ADP
cana-2747	98	25	the	the	DET
cana-2747	98	26	pi	pi	PROPN
cana-2747	98	27	task	task	PROPN
cana-2747	98	28	.	.	PUNCT
cana-2747	99	1	subsequently	subsequently	ADV
cana-2747	99	2	,	,	PUNCT
cana-2747	99	3	we	we	PRON
cana-2747	99	4	elaborated	elaborate	VERB
cana-2747	99	5	on	on	ADP
cana-2747	99	6	the	the	DET
cana-2747	99	7	conceptualization	conceptualization	NOUN
cana-2747	99	8	and	and	CCONJ
cana-2747	99	9	execution	execution	NOUN
cana-2747	99	10	of	of	ADP
cana-2747	99	11	our	our	PRON
cana-2747	99	12	proposed	propose	VERB
cana-2747	99	13	deep	deep	ADJ
cana-2747	99	14	learning	learning	NOUN
cana-2747	99	15	(	(	PUNCT
cana-2747	99	16	dl	dl	NOUN
cana-2747	99	17	)	)	PUNCT
cana-2747	99	18	methodology	methodology	NOUN
cana-2747	99	19	.	.	PUNCT
cana-2747	100	1	a.	a.	NOUN
cana-2747	100	2	data	data	PROPN
cana-2747	100	3	set	set	VERB
cana-2747	100	4	:	:	PUNCT
cana-2747	100	5	in	in	ADP
cana-2747	100	6	this	this	DET
cana-2747	100	7	study	study	NOUN
cana-2747	100	8	,	,	PUNCT
cana-2747	100	9	we	we	PRON
cana-2747	100	10	carried	carry	VERB
cana-2747	100	11	out	out	ADP
cana-2747	100	12	experiments	experiment	NOUN
cana-2747	100	13	with	with	ADP
cana-2747	100	14	the	the	DET
cana-2747	100	15	deap	deap	ADJ
cana-2747	100	16	affective	affective	PROPN
cana-2747	100	17	eeg	eeg	PROPN
cana-2747	100	18	dataset	dataset	NOUN
cana-2747	100	19	,	,	PUNCT
cana-2747	100	20	which	which	PRON
cana-2747	100	21	is	be	AUX
cana-2747	100	22	a	a	DET
cana-2747	100	23	widely	widely	ADV
cana-2747	100	24	established	establish	VERB
cana-2747	100	25	benchmark	benchmark	NOUN
cana-2747	100	26	for	for	ADP
cana-2747	100	27	emotion	emotion	NOUN
cana-2747	100	28	and	and	CCONJ
cana-2747	100	29	recognition	recognition	NOUN
cana-2747	100	30	tasks	task	NOUN
cana-2747	100	31	.	.	PUNCT
cana-2747	101	1	thirty	thirty	NUM
cana-2747	101	2	-	-	PUNCT
cana-2747	101	3	two	two	NUM
cana-2747	101	4	individuals	individual	NOUN
cana-2747	101	5	of	of	ADP
cana-2747	101	6	sound	sound	ADJ
cana-2747	101	7	health	health	NOUN
cana-2747	101	8	were	be	AUX
cana-2747	101	9	recruited	recruit	VERB
cana-2747	101	10	to	to	PART
cana-2747	101	11	partake	partake	VERB
cana-2747	101	12	in	in	ADP
cana-2747	101	13	the	the	DET
cana-2747	101	14	experiment	experiment	NOUN
cana-2747	101	15	.	.	PUNCT
cana-2747	102	1	their	their	PRON
cana-2747	102	2	task	task	NOUN
cana-2747	102	3	is	be	AUX
cana-2747	102	4	to	to	PART
cana-2747	102	5	watch	watch	VERB
cana-2747	102	6	emotionally	emotionally	ADV
cana-2747	102	7	charged	charge	VERB
cana-2747	102	8	music	music	NOUN
cana-2747	102	9	videos	video	NOUN
cana-2747	102	10	and	and	CCONJ
cana-2747	102	11	provided	provide	VERB
cana-2747	102	12	subjective	subjective	ADJ
cana-2747	102	13	ratings	rating	NOUN
cana-2747	102	14	of	of	ADP
cana-2747	102	15	valence	valence	NOUN
cana-2747	102	16	and	and	CCONJ
cana-2747	102	17	arousal	arousal	NOUN
cana-2747	102	18	for	for	ADP
cana-2747	102	19	forty	forty	NUM
cana-2747	102	20	video	video	NOUN
cana-2747	102	21	clips	clip	NOUN
cana-2747	102	22	while	while	SCONJ
cana-2747	102	23	their	their	PRON
cana-2747	102	24	eeg	eeg	NOUN
cana-2747	102	25	data	datum	NOUN
cana-2747	102	26	was	be	AUX
cana-2747	102	27	collected	collect	VERB
cana-2747	102	28	.	.	PUNCT
cana-2747	103	1	a	a	DET
cana-2747	103	2	detailed	detailed	ADJ
cana-2747	103	3	summary	summary	NOUN
cana-2747	103	4	of	of	ADP
cana-2747	103	5	data	datum	NOUN
cana-2747	103	6	is	be	AUX
cana-2747	103	7	given	give	VERB
cana-2747	103	8	in	in	ADP
cana-2747	103	9	further	further	ADJ
cana-2747	103	10	steps	step	NOUN
cana-2747	103	11	.	.	PUNCT
cana-2747	104	1	•	•	NOUN
cana-2747	104	2	the	the	DET
cana-2747	104	3	sampling	sample	VERB
cana-2747	104	4	data	datum	NOUN
cana-2747	104	5	sample	sample	NOUN
cana-2747	104	6	frequency	frequency	NOUN
cana-2747	104	7	was	be	AUX
cana-2747	104	8	decreased	decrease	VERB
cana-2747	104	9	to	to	ADP
cana-2747	104	10	128	128	NUM
cana-2747	104	11	hz	hz	NOUN
cana-2747	104	12	.	.	PROPN
cana-2747	104	13	•	•	PROPN
cana-2747	104	14	eog	eog	PROPN
cana-2747	104	15	(	(	PUNCT
cana-2747	104	16	electrooculogram	electrooculogram	NOUN
cana-2747	104	17	)	)	PUNCT
cana-2747	104	18	artefacts	artefact	NOUN
cana-2747	104	19	were	be	AUX
cana-2747	104	20	eliminated	eliminate	VERB
cana-2747	104	21	.	.	PUNCT
cana-2747	105	1	•	•	NUM
cana-2747	105	2	applying	apply	VERB
cana-2747	105	3	a	a	DET
cana-2747	105	4	bandpass	bandpass	NOUN
cana-2747	105	5	filter	filter	NOUN
cana-2747	105	6	with	with	ADP
cana-2747	105	7	a	a	DET
cana-2747	105	8	range	range	NOUN
cana-2747	105	9	of	of	ADP
cana-2747	105	10	4.0	4.0	NUM
cana-2747	105	11	hz	hz	VERB
cana-2747	105	12	to	to	ADP
cana-2747	105	13	45.0	45.0	NUM
cana-2747	105	14	hz	hz	NOUN
cana-2747	105	15	.	.	PROPN
cana-2747	105	16	•	•	NUM
cana-2747	105	17	by	by	ADP
cana-2747	105	18	averaging	average	VERB
cana-2747	105	19	the	the	DET
cana-2747	105	20	data	datum	NOUN
cana-2747	105	21	to	to	ADP
cana-2747	105	22	a	a	DET
cana-2747	105	23	common	common	ADJ
cana-2747	105	24	reference	reference	NOUN
cana-2747	105	25	point	point	NOUN
cana-2747	105	26	,	,	PUNCT
cana-2747	105	27	the	the	DET
cana-2747	105	28	data	datum	NOUN
cana-2747	105	29	was	be	AUX
cana-2747	105	30	normalised	normalise	VERB
cana-2747	105	31	.	.	PUNCT
cana-2747	106	1	•	•	NUM
cana-2747	106	2	after	after	ADP
cana-2747	106	3	discarding	discard	VERB
cana-2747	106	4	the	the	DET
cana-2747	106	5	baseline	baseline	ADJ
cana-2747	106	6	3	3	NUM
cana-2747	106	7	-	-	PUNCT
cana-2747	106	8	second	second	NOUN
cana-2747	106	9	trial	trial	NOUN
cana-2747	106	10	,	,	PUNCT
cana-2747	106	11	the	the	DET
cana-2747	106	12	data	datum	NOUN
cana-2747	106	13	was	be	AUX
cana-2747	106	14	segmented	segment	VERB
cana-2747	106	15	into	into	ADP
cana-2747	106	16	60	60	NUM
cana-2747	106	17	-	-	PUNCT
cana-2747	106	18	second	second	NOUN
cana-2747	106	19	trials	trial	NOUN
cana-2747	106	20	.	.	PUNCT
cana-2747	107	1	most	most	ADJ
cana-2747	107	2	of	of	ADP
cana-2747	107	3	the	the	DET
cana-2747	107	4	researchers	researcher	NOUN
cana-2747	107	5	have	have	AUX
cana-2747	107	6	been	be	AUX
cana-2747	107	7	using	use	VERB
cana-2747	107	8	this	this	DET
cana-2747	107	9	dataset	dataset	NOUN
cana-2747	107	10	for	for	ADP
cana-2747	107	11	human	human	ADJ
cana-2747	107	12	emotion	emotion	NOUN
cana-2747	107	13	classification	classification	NOUN
cana-2747	107	14	.	.	PUNCT
cana-2747	108	1	however	however	ADV
cana-2747	108	2	,	,	PUNCT
cana-2747	108	3	we	we	PRON
cana-2747	108	4	used	use	VERB
cana-2747	108	5	this	this	DET
cana-2747	108	6	dataset	dataset	NOUN
cana-2747	108	7	to	to	PART
cana-2747	108	8	study	study	VERB
cana-2747	108	9	eeg	eeg	NOUN
cana-2747	108	10	-	-	PUNCT
cana-2747	108	11	based	base	VERB
cana-2747	108	12	person	person	NOUN
cana-2747	108	13	identification	identification	NOUN
cana-2747	108	14	.	.	PUNCT
cana-2747	109	1	communications	communication	NOUN
cana-2747	109	2	on	on	ADP
cana-2747	109	3	applied	apply	VERB
cana-2747	109	4	nonlinear	nonlinear	ADJ
cana-2747	109	5	analysis	analysis	NOUN
cana-2747	109	6	issn	issn	NOUN
cana-2747	109	7	:	:	PUNCT
cana-2747	109	8	1074	1074	NUM
cana-2747	109	9	-	-	PUNCT
cana-2747	109	10	133x	133x	NUM
cana-2747	109	11	vol	vol	NOUN
cana-2747	109	12	32	32	NUM
cana-2747	109	13	no	no	NOUN
cana-2747	109	14	.	.	PUNCT
cana-2747	110	1	4s	4s	NUM
cana-2747	110	2	(	(	PUNCT
cana-2747	110	3	2025	2025	NUM
cana-2747	110	4	)	)	PUNCT
cana-2747	110	5	174	174	NUM
cana-2747	110	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	110	7	b.	b.	PROPN
cana-2747	110	8	data	data	PROPN
cana-2747	110	9	organization	organization	PROPN
cana-2747	110	10	:	:	PUNCT
cana-2747	110	11	•	•	ADP
cana-2747	110	12	there	there	PRON
cana-2747	110	13	are	be	VERB
cana-2747	110	14	32	32	NUM
cana-2747	110	15	persons	person	NOUN
cana-2747	110	16	(	(	PUNCT
cana-2747	110	17	or	or	CCONJ
cana-2747	110	18	subjects	subject	NOUN
cana-2747	110	19	)	)	PUNCT
cana-2747	110	20	in	in	ADP
cana-2747	110	21	the	the	DET
cana-2747	110	22	dataset	dataset	NOUN
cana-2747	110	23	.	.	PUNCT
cana-2747	111	1	•	•	NOUN
cana-2747	111	2	each	each	DET
cana-2747	111	3	person	person	NOUN
cana-2747	111	4	performed	perform	VERB
cana-2747	111	5	40	40	NUM
cana-2747	111	6	trials	trial	NOUN
cana-2747	111	7	,	,	PUNCT
cana-2747	111	8	possibly	possibly	ADV
cana-2747	111	9	in	in	ADP
cana-2747	111	10	an	an	DET
cana-2747	111	11	experimental	experimental	ADJ
cana-2747	111	12	task	task	NOUN
cana-2747	111	13	or	or	CCONJ
cana-2747	111	14	study	study	NOUN
cana-2747	111	15	.	.	PUNCT
cana-2747	112	1	•	•	NUM
cana-2747	112	2	the	the	DET
cana-2747	112	3	eeg	eeg	PROPN
cana-2747	112	4	data	datum	NOUN
cana-2747	112	5	was	be	AUX
cana-2747	112	6	collected	collect	VERB
cana-2747	112	7	from	from	ADP
cana-2747	112	8	40	40	NUM
cana-2747	112	9	channels	channel	NOUN
cana-2747	112	10	,	,	PUNCT
cana-2747	112	11	which	which	PRON
cana-2747	112	12	could	could	AUX
cana-2747	112	13	represent	represent	VERB
cana-2747	112	14	different	different	ADJ
cana-2747	112	15	electrode	electrode	NOUN
cana-2747	112	16	placements	placement	NOUN
cana-2747	112	17	on	on	ADP
cana-2747	112	18	the	the	DET
cana-2747	112	19	scalp	scalp	NOUN
cana-2747	112	20	.	.	PUNCT
cana-2747	113	1	c.data	c.data	PROPN
cana-2747	113	2	segmentation	segmentation	NOUN
cana-2747	113	3	:	:	PUNCT
cana-2747	113	4	•	•	ADP
cana-2747	113	5	the	the	DET
cana-2747	113	6	continuous	continuous	ADJ
cana-2747	113	7	eeg	eeg	NOUN
cana-2747	113	8	data	datum	NOUN
cana-2747	113	9	for	for	ADP
cana-2747	113	10	each	each	DET
cana-2747	113	11	trial	trial	NOUN
cana-2747	113	12	is	be	AUX
cana-2747	113	13	segmented	segment	VERB
cana-2747	113	14	into	into	ADP
cana-2747	113	15	fixed	fix	VERB
cana-2747	113	16	-	-	PUNCT
cana-2747	113	17	size	size	NOUN
cana-2747	113	18	chunks	chunk	NOUN
cana-2747	113	19	.	.	PUNCT
cana-2747	114	1	•	•	NOUN
cana-2747	114	2	each	each	DET
cana-2747	114	3	trial	trial	NOUN
cana-2747	114	4	is	be	AUX
cana-2747	114	5	segmented	segment	VERB
cana-2747	114	6	into	into	ADP
cana-2747	114	7	a	a	DET
cana-2747	114	8	60	60	NUM
cana-2747	114	9	-	-	PUNCT
cana-2747	114	10	second	second	NOUN
cana-2747	114	11	period	period	NOUN
cana-2747	114	12	and	and	CCONJ
cana-2747	114	13	a	a	DET
cana-2747	114	14	3	3	NUM
cana-2747	114	15	-	-	PUNCT
cana-2747	114	16	second	second	ADJ
cana-2747	114	17	pre	pre	ADJ
cana-2747	114	18	-	-	ADJ
cana-2747	114	19	trial	trial	ADJ
cana-2747	114	20	baseline	baseline	NOUN
cana-2747	114	21	.	.	PUNCT
cana-2747	115	1	•	•	CCONJ
cana-2747	115	2	the	the	DET
cana-2747	115	3	baseline	baseline	ADJ
cana-2747	115	4	segment	segment	NOUN
cana-2747	115	5	(	(	PUNCT
cana-2747	115	6	3	3	NUM
cana-2747	115	7	seconds	second	NOUN
cana-2747	115	8	)	)	PUNCT
cana-2747	115	9	serves	serve	VERB
cana-2747	115	10	as	as	ADP
cana-2747	115	11	the	the	DET
cana-2747	115	12	reference	reference	NOUN
cana-2747	115	13	or	or	CCONJ
cana-2747	115	14	initial	initial	ADJ
cana-2747	115	15	period	period	NOUN
cana-2747	115	16	before	before	ADP
cana-2747	115	17	any	any	DET
cana-2747	115	18	stimulus	stimulus	NOUN
cana-2747	115	19	or	or	CCONJ
cana-2747	115	20	event	event	NOUN
cana-2747	115	21	occurs	occur	VERB
cana-2747	115	22	.	.	PUNCT
cana-2747	116	1	d.	d.	PROPN
cana-2747	116	2	data	data	PROPN
cana-2747	116	3	sampling	sample	VERB
cana-2747	116	4	rate	rate	NOUN
cana-2747	116	5	:	:	PUNCT
cana-2747	116	6	the	the	DET
cana-2747	116	7	eeg	eeg	NOUN
cana-2747	116	8	data	datum	NOUN
cana-2747	116	9	is	be	AUX
cana-2747	116	10	sampled	sample	VERB
cana-2747	116	11	at	at	ADP
cana-2747	116	12	a	a	DET
cana-2747	116	13	rate	rate	NOUN
cana-2747	116	14	of	of	ADP
cana-2747	116	15	128	128	NUM
cana-2747	116	16	hz	hz	VERB
cana-2747	116	17	,	,	PUNCT
cana-2747	116	18	resulting	result	VERB
cana-2747	116	19	in	in	ADP
cana-2747	116	20	128	128	NUM
cana-2747	116	21	data	datum	NOUN
cana-2747	116	22	points	point	NOUN
cana-2747	116	23	(	(	PUNCT
cana-2747	116	24	samples	sample	NOUN
cana-2747	116	25	)	)	PUNCT
cana-2747	116	26	per	per	ADP
cana-2747	116	27	second	second	NOUN
cana-2747	116	28	for	for	ADP
cana-2747	116	29	each	each	DET
cana-2747	116	30	channel	channel	NOUN
cana-2747	116	31	.	.	PUNCT
cana-2747	117	1	e.	e.	PROPN
cana-2747	117	2	calculation	calculation	NOUN
cana-2747	117	3	of	of	ADP
cana-2747	117	4	samples	sample	NOUN
cana-2747	117	5	per	per	ADP
cana-2747	117	6	trial	trial	NOUN
cana-2747	117	7	:	:	PUNCT
cana-2747	117	8	•	•	ADP
cana-2747	117	9	for	for	ADP
cana-2747	117	10	each	each	DET
cana-2747	117	11	trial	trial	NOUN
cana-2747	117	12	,	,	PUNCT
cana-2747	117	13	the	the	DET
cana-2747	117	14	duration	duration	NOUN
cana-2747	117	15	is	be	AUX
cana-2747	117	16	63	63	NUM
cana-2747	117	17	seconds	second	NOUN
cana-2747	117	18	(	(	PUNCT
cana-2747	117	19	60	60	NUM
cana-2747	117	20	seconds	second	NOUN
cana-2747	117	21	trial	trial	NOUN
cana-2747	117	22	+	+	CCONJ
cana-2747	117	23	3	3	NUM
cana-2747	117	24	seconds	second	NOUN
cana-2747	117	25	baseline	baseline	NOUN
cana-2747	117	26	)	)	PUNCT
cana-2747	117	27	.	.	PUNCT
cana-2747	118	1	•	•	NOUN
cana-2747	118	2	since	since	SCONJ
cana-2747	118	3	the	the	DET
cana-2747	118	4	data	data	NOUN
cana-2747	118	5	is	be	AUX
cana-2747	118	6	recorded	record	VERB
cana-2747	118	7	at	at	ADP
cana-2747	118	8	128hz	128hz	NOUN
cana-2747	118	9	,	,	PUNCT
cana-2747	118	10	there	there	PRON
cana-2747	118	11	are	be	VERB
cana-2747	118	12	128	128	NUM
cana-2747	118	13	data	datum	NOUN
cana-2747	118	14	points	point	NOUN
cana-2747	118	15	(	(	PUNCT
cana-2747	118	16	samples	sample	NOUN
cana-2747	118	17	)	)	PUNCT
cana-2747	118	18	for	for	ADP
cana-2747	118	19	each	each	DET
cana-2747	118	20	second	second	NOUN
cana-2747	118	21	of	of	ADP
cana-2747	118	22	recording	recording	NOUN
cana-2747	118	23	.	.	PUNCT
cana-2747	119	1	•	•	NUM
cana-2747	119	2	therefore	therefore	ADV
cana-2747	119	3	,	,	PUNCT
cana-2747	119	4	for	for	ADP
cana-2747	119	5	each	each	DET
cana-2747	119	6	trial	trial	NOUN
cana-2747	119	7	,	,	PUNCT
cana-2747	119	8	there	there	PRON
cana-2747	119	9	are	be	VERB
cana-2747	119	10	63	63	NUM
cana-2747	119	11	seconds	second	NOUN
cana-2747	119	12	x	x	NOUN
cana-2747	119	13	128hz	128hz	ADJ
cana-2747	119	14	=	=	SYM
cana-2747	119	15	8064	8064	NUM
cana-2747	119	16	samples	sample	NOUN
cana-2747	119	17	.	.	PUNCT
cana-2747	120	1	f.	f.	PROPN
cana-2747	120	2	data	data	PROPN
cana-2747	120	3	:	:	PUNCT
cana-2747	120	4	•	•	NUM
cana-2747	120	5	a	a	DET
cana-2747	120	6	4	4	NUM
cana-2747	120	7	-	-	PUNCT
cana-2747	120	8	dimensional	dimensional	ADJ
cana-2747	120	9	array	array	NOUN
cana-2747	120	10	of	of	ADP
cana-2747	120	11	shapes	shape	NOUN
cana-2747	120	12	(	(	PUNCT
cana-2747	120	13	32	32	NUM
cana-2747	120	14	,	,	PUNCT
cana-2747	120	15	40	40	NUM
cana-2747	120	16	,	,	PUNCT
cana-2747	120	17	40	40	NUM
cana-2747	120	18	,	,	PUNCT
cana-2747	120	19	8064	8064	NUM
cana-2747	120	20	)	)	PUNCT
cana-2747	120	21	.	.	PUNCT
cana-2747	121	1	•	•	NUM
cana-2747	121	2	the	the	DET
cana-2747	121	3	first	first	ADJ
cana-2747	121	4	dimension	dimension	NOUN
cana-2747	121	5	represents	represent	VERB
cana-2747	121	6	the	the	DET
cana-2747	121	7	32	32	NUM
cana-2747	121	8	persons	person	NOUN
cana-2747	121	9	(	(	PUNCT
cana-2747	121	10	subjects	subject	NOUN
cana-2747	121	11	)	)	PUNCT
cana-2747	121	12	in	in	ADP
cana-2747	121	13	the	the	DET
cana-2747	121	14	dataset	dataset	NOUN
cana-2747	121	15	.	.	PUNCT
cana-2747	122	1	•	•	NUM
cana-2747	122	2	the	the	DET
cana-2747	122	3	second	second	ADJ
cana-2747	122	4	dimension	dimension	NOUN
cana-2747	122	5	represents	represent	VERB
cana-2747	122	6	the	the	DET
cana-2747	122	7	40	40	NUM
cana-2747	122	8	trials	trial	NOUN
cana-2747	122	9	performed	perform	VERB
cana-2747	122	10	by	by	ADP
cana-2747	122	11	each	each	DET
cana-2747	122	12	person	person	NOUN
cana-2747	122	13	.	.	PUNCT
cana-2747	123	1	•	•	NUM
cana-2747	123	2	the	the	DET
cana-2747	123	3	third	third	ADJ
cana-2747	123	4	dimension	dimension	NOUN
cana-2747	123	5	represents	represent	VERB
cana-2747	123	6	the	the	DET
cana-2747	123	7	40	40	NUM
cana-2747	123	8	eeg	eeg	NOUN
cana-2747	123	9	channels	channel	NOUN
cana-2747	123	10	.	.	PUNCT
cana-2747	124	1	•	•	NUM
cana-2747	124	2	the	the	DET
cana-2747	124	3	fourth	fourth	ADJ
cana-2747	124	4	dimension	dimension	NOUN
cana-2747	124	5	represents	represent	VERB
cana-2747	124	6	the	the	DET
cana-2747	124	7	8064	8064	NUM
cana-2747	124	8	samples	sample	NOUN
cana-2747	124	9	for	for	ADP
cana-2747	124	10	each	each	DET
cana-2747	124	11	trial	trial	NOUN
cana-2747	124	12	.	.	PUNCT
cana-2747	125	1	g.	g.	PROPN
cana-2747	125	2	data	data	PROPN
cana-2747	125	3	transformation	transformation	NOUN
cana-2747	125	4	based	base	VERB
cana-2747	125	5	on	on	ADP
cana-2747	125	6	the	the	DET
cana-2747	125	7	provided	provide	VERB
cana-2747	125	8	information	information	NOUN
cana-2747	125	9	,	,	PUNCT
cana-2747	125	10	the	the	DET
cana-2747	125	11	data	data	NOUN
cana-2747	125	12	transformation	transformation	NOUN
cana-2747	125	13	involves	involve	VERB
cana-2747	125	14	mapping	map	VERB
cana-2747	125	15	eeg	eeg	NOUN
cana-2747	125	16	data	datum	NOUN
cana-2747	125	17	to	to	ADP
cana-2747	125	18	a	a	DET
cana-2747	125	19	9x9	9x9	NUM
cana-2747	125	20	image	image	NOUN
cana-2747	125	21	plane	plane	NOUN
cana-2747	125	22	for	for	ADP
cana-2747	125	23	person	person	NOUN
cana-2747	125	24	identification	identification	NOUN
cana-2747	125	25	using	use	VERB
cana-2747	125	26	short	short	ADJ
cana-2747	125	27	-	-	PUNCT
cana-2747	125	28	length	length	NOUN
cana-2747	125	29	eeg	eeg	NOUN
cana-2747	125	30	segments	segment	NOUN
cana-2747	125	31	.	.	PUNCT
cana-2747	126	1	h.	h.	PROPN
cana-2747	126	2	eeg	eeg	PROPN
cana-2747	126	3	data	data	PROPN
cana-2747	126	4	segmentation	segmentation	NOUN
cana-2747	126	5	:	:	PUNCT
cana-2747	126	6	•	•	ADP
cana-2747	126	7	each	each	DET
cana-2747	126	8	eeg	eeg	NOUN
cana-2747	126	9	trial	trial	NOUN
cana-2747	126	10	is	be	AUX
cana-2747	126	11	originally	originally	ADV
cana-2747	126	12	60	60	NUM
cana-2747	126	13	seconds	second	NOUN
cana-2747	126	14	long	long	ADJ
cana-2747	126	15	(	(	PUNCT
cana-2747	126	16	7680	7680	NUM
cana-2747	126	17	samples	sample	NOUN
cana-2747	126	18	after	after	ADP
cana-2747	126	19	removing	remove	VERB
cana-2747	126	20	the	the	DET
cana-2747	126	21	3	3	NUM
cana-2747	126	22	-	-	PUNCT
cana-2747	126	23	second	second	ADJ
cana-2747	126	24	pretrial	pretrial	ADJ
cana-2747	126	25	baseline	baseline	NOUN
cana-2747	126	26	)	)	PUNCT
cana-2747	126	27	.	.	PUNCT
cana-2747	127	1	•	•	NUM
cana-2747	127	2	the	the	DET
cana-2747	127	3	60	60	NUM
cana-2747	127	4	-	-	PUNCT
cana-2747	127	5	second	second	NOUN
cana-2747	127	6	trial	trial	NOUN
cana-2747	127	7	is	be	AUX
cana-2747	127	8	further	far	ADV
cana-2747	127	9	divided	divide	VERB
cana-2747	127	10	into	into	ADP
cana-2747	127	11	6	6	NUM
cana-2747	127	12	equal	equal	ADJ
cana-2747	127	13	parts	part	NOUN
cana-2747	127	14	,	,	PUNCT
cana-2747	127	15	each	each	PRON
cana-2747	127	16	of	of	ADP
cana-2747	127	17	10	10	NUM
cana-2747	127	18	seconds	second	NOUN
cana-2747	127	19	in	in	ADP
cana-2747	127	20	duration	duration	NOUN
cana-2747	127	21	.	.	PUNCT
cana-2747	128	1	these	these	DET
cana-2747	128	2	10	10	NUM
cana-2747	128	3	-	-	PUNCT
cana-2747	128	4	second	second	ADJ
cana-2747	128	5	segments	segment	NOUN
cana-2747	128	6	are	be	AUX
cana-2747	128	7	referred	refer	VERB
cana-2747	128	8	to	to	ADP
cana-2747	128	9	as	as	ADP
cana-2747	128	10	"	"	PUNCT
cana-2747	128	11	subsamples	subsample	NOUN
cana-2747	128	12	.	.	PUNCT
cana-2747	128	13	"	"	PUNCT
cana-2747	129	1	communications	communication	NOUN
cana-2747	129	2	on	on	ADP
cana-2747	129	3	applied	apply	VERB
cana-2747	129	4	nonlinear	nonlinear	ADJ
cana-2747	129	5	analysis	analysis	NOUN
cana-2747	129	6	issn	issn	NOUN
cana-2747	129	7	:	:	PUNCT
cana-2747	129	8	1074	1074	NUM
cana-2747	129	9	-	-	PUNCT
cana-2747	129	10	133x	133x	NUM
cana-2747	129	11	vol	vol	NOUN
cana-2747	129	12	32	32	NUM
cana-2747	129	13	no	no	NOUN
cana-2747	129	14	.	.	PUNCT
cana-2747	130	1	4s	4s	NUM
cana-2747	130	2	(	(	PUNCT
cana-2747	130	3	2025	2025	NUM
cana-2747	130	4	)	)	PUNCT
cana-2747	130	5	175	175	NUM
cana-2747	130	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	130	7	•	•	NOUN
cana-2747	130	8	each	each	DET
cana-2747	130	9	10	10	NUM
cana-2747	130	10	-	-	PUNCT
cana-2747	130	11	second	second	ADJ
cana-2747	130	12	subsample	subsample	NOUN
cana-2747	130	13	contains	contain	VERB
cana-2747	130	14	1280	1280	NUM
cana-2747	130	15	eeg	eeg	PROPN
cana-2747	130	16	data	datum	NOUN
cana-2747	130	17	points	point	NOUN
cana-2747	130	18	(	(	PUNCT
cana-2747	130	19	10	10	NUM
cana-2747	130	20	seconds	second	NOUN
cana-2747	130	21	×	×	NOUN
cana-2747	130	22	128	128	NUM
cana-2747	130	23	hz	hz	VERB
cana-2747	130	24	sampling	sample	VERB
cana-2747	130	25	rate	rate	NOUN
cana-2747	130	26	)	)	PUNCT
cana-2747	130	27	.	.	PUNCT
cana-2747	131	1	i.	i.	PROPN
cana-2747	131	2	mapping	mapping	NOUN
cana-2747	131	3	to	to	ADP
cana-2747	131	4	9x9	9x9	NUM
cana-2747	131	5	image	image	NOUN
cana-2747	131	6	plane	plane	NOUN
cana-2747	131	7	:	:	PUNCT
cana-2747	131	8	•	•	ADP
cana-2747	131	9	to	to	PART
cana-2747	131	10	convert	convert	VERB
cana-2747	131	11	each	each	DET
cana-2747	131	12	10	10	NUM
cana-2747	131	13	-	-	PUNCT
cana-2747	131	14	second	second	ADJ
cana-2747	131	15	subsample	subsample	NOUN
cana-2747	131	16	into	into	ADP
cana-2747	131	17	an	an	DET
cana-2747	131	18	image	image	NOUN
cana-2747	131	19	representation	representation	NOUN
cana-2747	131	20	,	,	PUNCT
cana-2747	131	21	they	they	PRON
cana-2747	131	22	are	be	AUX
cana-2747	131	23	mapped	map	VERB
cana-2747	131	24	to	to	ADP
cana-2747	131	25	a	a	DET
cana-2747	131	26	9x9	9x9	NUM
cana-2747	131	27	image	image	NOUN
cana-2747	131	28	plane	plane	NOUN
cana-2747	131	29	.	.	PUNCT
cana-2747	132	1	•	•	NUM
cana-2747	132	2	the	the	DET
cana-2747	132	3	9x9	9x9	NUM
cana-2747	132	4	image	image	NOUN
cana-2747	132	5	plane	plane	NOUN
cana-2747	132	6	likely	likely	ADV
cana-2747	132	7	represents	represent	VERB
cana-2747	132	8	a	a	DET
cana-2747	132	9	grid	grid	NOUN
cana-2747	132	10	of	of	ADP
cana-2747	132	11	9	9	NUM
cana-2747	132	12	rows	row	NOUN
cana-2747	132	13	and	and	CCONJ
cana-2747	132	14	9	9	NUM
cana-2747	132	15	columns	column	NOUN
cana-2747	132	16	shown	show	VERB
cana-2747	132	17	in	in	ADP
cana-2747	132	18	fig	fig	NOUN
cana-2747	132	19	4	4	NUM
cana-2747	132	20	.	.	NOUN
cana-2747	133	1	•	•	NOUN
cana-2747	134	1	each	each	DET
cana-2747	134	2	data	datum	NOUN
cana-2747	134	3	point	point	NOUN
cana-2747	134	4	of	of	ADP
cana-2747	134	5	the	the	DET
cana-2747	134	6	10	10	NUM
cana-2747	134	7	-	-	PUNCT
cana-2747	134	8	second	second	ADJ
cana-2747	134	9	subsample	subsample	NOUN
cana-2747	134	10	is	be	AUX
cana-2747	134	11	mapped	map	VERB
cana-2747	134	12	to	to	ADP
cana-2747	134	13	a	a	DET
cana-2747	134	14	corresponding	corresponding	ADJ
cana-2747	134	15	position	position	NOUN
cana-2747	134	16	in	in	ADP
cana-2747	134	17	the	the	DET
cana-2747	134	18	9x9	9x9	NUM
cana-2747	134	19	grid	grid	NOUN
cana-2747	134	20	as	as	SCONJ
cana-2747	134	21	shown	show	VERB
cana-2747	134	22	in	in	ADP
cana-2747	134	23	figure	figure	NOUN
cana-2747	134	24	4	4	NUM
cana-2747	134	25	.	.	PUNCT
cana-2747	134	26	j.	j.	PROPN
cana-2747	134	27	data	data	PROPN
cana-2747	134	28	and	and	CCONJ
cana-2747	134	29	label	label	NOUN
cana-2747	134	30	structure	structure	NOUN
cana-2747	134	31	:	:	PUNCT
cana-2747	134	32	•	•	ADP
cana-2747	134	33	the	the	DET
cana-2747	134	34	data	datum	NOUN
cana-2747	134	35	consists	consist	VERB
cana-2747	134	36	of	of	ADP
cana-2747	134	37	eeg	eeg	NOUN
cana-2747	134	38	subsamples	subsample	NOUN
cana-2747	134	39	from	from	ADP
cana-2747	134	40	multiple	multiple	ADJ
cana-2747	134	41	participants	participant	NOUN
cana-2747	134	42	.	.	PUNCT
cana-2747	135	1	•	•	NUM
cana-2747	135	2	for	for	ADP
cana-2747	135	3	each	each	DET
cana-2747	135	4	participant	participant	NOUN
cana-2747	135	5	,	,	PUNCT
cana-2747	135	6	there	there	PRON
cana-2747	135	7	are	be	VERB
cana-2747	135	8	30	30	NUM
cana-2747	135	9	subsamples	subsample	NOUN
cana-2747	135	10	(	(	PUNCT
cana-2747	135	11	6	6	NUM
cana-2747	135	12	subsamples	subsample	NOUN
cana-2747	135	13	×	×	NOUN
cana-2747	135	14	5	5	NUM
cana-2747	135	15	trials	trial	NOUN
cana-2747	135	16	)	)	PUNCT
cana-2747	135	17	for	for	ADP
cana-2747	135	18	each	each	DET
cana-2747	135	19	affective	affective	ADJ
cana-2747	135	20	state	state	NOUN
cana-2747	135	21	or	or	CCONJ
cana-2747	135	22	condition	condition	NOUN
cana-2747	135	23	.	.	PUNCT
cana-2747	136	1	the	the	DET
cana-2747	136	2	data	data	NOUN
cana-2747	136	3	is	be	AUX
cana-2747	136	4	structured	structure	VERB
cana-2747	136	5	as	as	SCONJ
cana-2747	136	6	follows	follow	VERB
cana-2747	136	7	:	:	PUNCT
cana-2747	136	8	•	•	NUM
cana-2747	136	9	data	datum	NOUN
cana-2747	136	10	:	:	PUNCT
cana-2747	136	11	(	(	PUNCT
cana-2747	136	12	number	number	NOUN
cana-2747	136	13	of	of	ADP
cana-2747	136	14	participants	participant	NOUN
cana-2747	136	15	)	)	PUNCT
cana-2747	136	16	×	×	NOUN
cana-2747	136	17	30	30	NUM
cana-2747	136	18	subsamples	subsample	NOUN
cana-2747	136	19	×	×	NOUN
cana-2747	136	20	1280	1280	NUM
cana-2747	136	21	eeg	eeg	NOUN
cana-2747	136	22	data	datum	NOUN
cana-2747	136	23	points	point	NOUN
cana-2747	136	24	(	(	PUNCT
cana-2747	136	25	10	10	NUM
cana-2747	136	26	seconds	second	NOUN
cana-2747	136	27	at	at	ADP
cana-2747	136	28	a	a	DET
cana-2747	136	29	128	128	NUM
cana-2747	136	30	hz	hz	VERB
cana-2747	136	31	sampling	sample	VERB
cana-2747	136	32	rate	rate	NOUN
cana-2747	136	33	)	)	PUNCT
cana-2747	136	34	.	.	PUNCT
cana-2747	137	1	•	•	NUM
cana-2747	137	2	label	label	NOUN
cana-2747	137	3	:	:	PUNCT
cana-2747	137	4	(	(	PUNCT
cana-2747	137	5	number	number	NOUN
cana-2747	137	6	of	of	ADP
cana-2747	137	7	participants	participant	NOUN
cana-2747	137	8	)	)	PUNCT
cana-2747	137	9	×	×	NOUN
cana-2747	137	10	30	30	NUM
cana-2747	137	11	subsamples	subsample	NOUN
cana-2747	137	12	×	×	NOUN
cana-2747	137	13	1	1	NUM
cana-2747	137	14	(	(	PUNCT
cana-2747	137	15	participant	participant	NOUN
cana-2747	137	16	's	's	PART
cana-2747	137	17	i	i	PROPN
cana-2747	137	18	d	d	PROPN
cana-2747	137	19	)	)	PUNCT
cana-2747	137	20	.	.	PUNCT
cana-2747	138	1	k.	k.	PROPN
cana-2747	138	2	person	person	PROPN
cana-2747	138	3	identification	identification	NOUN
cana-2747	138	4	:	:	PUNCT
cana-2747	138	5	•	•	ADP
cana-2747	138	6	the	the	DET
cana-2747	138	7	analysis	analysis	NOUN
cana-2747	138	8	aims	aim	VERB
cana-2747	138	9	to	to	PART
cana-2747	138	10	identify	identify	VERB
cana-2747	138	11	individuals	individual	NOUN
cana-2747	138	12	based	base	VERB
cana-2747	138	13	on	on	ADP
cana-2747	138	14	short	short	ADJ
cana-2747	138	15	eeg	eeg	NOUN
cana-2747	138	16	segments	segment	NOUN
cana-2747	138	17	,	,	PUNCT
cana-2747	138	18	each	each	PRON
cana-2747	138	19	lasting	last	VERB
cana-2747	138	20	10	10	NUM
cana-2747	138	21	seconds	second	NOUN
cana-2747	138	22	.	.	PUNCT
cana-2747	139	1	•	•	NOUN
cana-2747	139	2	the	the	DET
cana-2747	139	3	labels	label	NOUN
cana-2747	139	4	used	use	VERB
cana-2747	139	5	for	for	ADP
cana-2747	139	6	this	this	DET
cana-2747	139	7	identification	identification	NOUN
cana-2747	139	8	are	be	AUX
cana-2747	139	9	the	the	DET
cana-2747	139	10	participant	participant	NOUN
cana-2747	139	11	's	's	PART
cana-2747	139	12	i	i	PROPN
cana-2747	139	13	d	d	PROPN
cana-2747	139	14	,	,	PUNCT
cana-2747	139	15	which	which	PRON
cana-2747	139	16	is	be	AUX
cana-2747	139	17	a	a	DET
cana-2747	139	18	unique	unique	ADJ
cana-2747	139	19	identifier	identifier	NOUN
cana-2747	139	20	for	for	ADP
cana-2747	139	21	each	each	DET
cana-2747	139	22	participant	participant	NOUN
cana-2747	139	23	.	.	PUNCT
cana-2747	140	1	in	in	ADP
cana-2747	140	2	summary	summary	NOUN
cana-2747	140	3	,	,	PUNCT
cana-2747	140	4	the	the	DET
cana-2747	140	5	data	datum	NOUN
cana-2747	140	6	is	be	AUX
cana-2747	140	7	transformed	transform	VERB
cana-2747	140	8	into	into	ADP
cana-2747	140	9	a	a	DET
cana-2747	140	10	format	format	NOUN
cana-2747	140	11	suitable	suitable	ADJ
cana-2747	140	12	for	for	ADP
cana-2747	140	13	person	person	NOUN
cana-2747	140	14	identification	identification	NOUN
cana-2747	140	15	using	use	VERB
cana-2747	140	16	short	short	ADJ
cana-2747	140	17	-	-	PUNCT
cana-2747	140	18	length	length	NOUN
cana-2747	140	19	eeg	eeg	NOUN
cana-2747	140	20	segments	segment	NOUN
cana-2747	140	21	.	.	PUNCT
cana-2747	141	1	each	each	DET
cana-2747	141	2	60	60	NUM
cana-2747	141	3	-	-	PUNCT
cana-2747	141	4	second	second	NOUN
cana-2747	141	5	trial	trial	NOUN
cana-2747	141	6	is	be	AUX
cana-2747	141	7	divided	divide	VERB
cana-2747	141	8	into	into	ADP
cana-2747	141	9	6	6	NUM
cana-2747	141	10	equal	equal	ADJ
cana-2747	141	11	10	10	NUM
cana-2747	141	12	-	-	PUNCT
cana-2747	141	13	second	second	ADJ
cana-2747	141	14	subsamples	subsample	NOUN
cana-2747	141	15	,	,	PUNCT
cana-2747	141	16	which	which	PRON
cana-2747	141	17	are	be	AUX
cana-2747	141	18	then	then	ADV
cana-2747	141	19	mapped	map	VERB
cana-2747	141	20	to	to	ADP
cana-2747	141	21	a	a	DET
cana-2747	141	22	9x9	9x9	NUM
cana-2747	141	23	image	image	NOUN
cana-2747	141	24	plane	plane	NOUN
cana-2747	141	25	.	.	PUNCT
cana-2747	142	1	the	the	DET
cana-2747	142	2	image	image	NOUN
cana-2747	142	3	plane	plane	NOUN
cana-2747	142	4	representation	representation	NOUN
cana-2747	142	5	allows	allow	VERB
cana-2747	142	6	for	for	ADP
cana-2747	142	7	the	the	DET
cana-2747	142	8	application	application	NOUN
cana-2747	142	9	of	of	ADP
cana-2747	142	10	various	various	ADJ
cana-2747	142	11	image	image	NOUN
cana-2747	142	12	-	-	PUNCT
cana-2747	142	13	based	base	VERB
cana-2747	142	14	machine	machine	NOUN
cana-2747	142	15	learning	learning	NOUN
cana-2747	142	16	or	or	CCONJ
cana-2747	142	17	pattern	pattern	NOUN
cana-2747	142	18	recognition	recognition	NOUN
cana-2747	142	19	techniques	technique	NOUN
cana-2747	142	20	for	for	ADP
cana-2747	142	21	person	person	NOUN
cana-2747	142	22	identification	identification	NOUN
cana-2747	142	23	based	base	VERB
cana-2747	142	24	on	on	ADP
cana-2747	142	25	eeg	eeg	PROPN
cana-2747	142	26	data	datum	NOUN
cana-2747	142	27	.	.	PUNCT
cana-2747	143	1	the	the	DET
cana-2747	143	2	labels	label	NOUN
cana-2747	143	3	used	use	VERB
cana-2747	143	4	for	for	ADP
cana-2747	143	5	identification	identification	NOUN
cana-2747	143	6	are	be	AUX
cana-2747	143	7	the	the	DET
cana-2747	143	8	participant	participant	NOUN
cana-2747	143	9	's	's	PART
cana-2747	143	10	i	i	PROPN
cana-2747	143	11	d	d	PROPN
cana-2747	143	12	,	,	PUNCT
cana-2747	143	13	and	and	CCONJ
cana-2747	143	14	the	the	DET
cana-2747	143	15	goal	goal	NOUN
cana-2747	143	16	is	be	AUX
cana-2747	143	17	to	to	PART
cana-2747	143	18	classify	classify	VERB
cana-2747	143	19	individuals	individual	NOUN
cana-2747	143	20	based	base	VERB
cana-2747	143	21	on	on	ADP
cana-2747	143	22	their	their	PRON
cana-2747	143	23	eeg	eeg	NOUN
cana-2747	143	24	responses	response	NOUN
cana-2747	143	25	during	during	ADP
cana-2747	143	26	the	the	DET
cana-2747	143	27	10	10	NUM
cana-2747	143	28	-	-	PUNCT
cana-2747	143	29	second	second	NOUN
cana-2747	143	30	subsamples	subsample	NOUN
cana-2747	143	31	.	.	PUNCT
cana-2747	144	1	communications	communication	NOUN
cana-2747	144	2	on	on	ADP
cana-2747	144	3	applied	apply	VERB
cana-2747	144	4	nonlinear	nonlinear	ADJ
cana-2747	144	5	analysis	analysis	NOUN
cana-2747	144	6	issn	issn	NOUN
cana-2747	144	7	:	:	PUNCT
cana-2747	144	8	1074	1074	NUM
cana-2747	144	9	-	-	PUNCT
cana-2747	144	10	133x	133x	NUM
cana-2747	144	11	vol	vol	NOUN
cana-2747	144	12	32	32	NUM
cana-2747	144	13	no	no	NOUN
cana-2747	144	14	.	.	PUNCT
cana-2747	145	1	4s	4s	NUM
cana-2747	145	2	(	(	PUNCT
cana-2747	145	3	2025	2025	NUM
cana-2747	145	4	)	)	PUNCT
cana-2747	145	5	176	176	NUM
cana-2747	145	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	145	7	fig.4	fig.4	PROPN
cana-2747	145	8	.	.	PUNCT
cana-2747	145	9	multichannel	multichannel	PROPN
cana-2747	145	10	eeg	eeg	PROPN
cana-2747	145	11	signals	signal	NOUN
cana-2747	145	12	are	be	AUX
cana-2747	145	13	transformed	transform	VERB
cana-2747	145	14	into	into	ADP
cana-2747	145	15	sequences	sequence	NOUN
cana-2747	145	16	of	of	ADP
cana-2747	145	17	2	2	NUM
cana-2747	145	18	-	-	PUNCT
cana-2747	145	19	d	d	NOUN
cana-2747	145	20	images	image	NOUN
cana-2747	145	21	.	.	PUNCT
cana-2747	146	1	4	4	X
cana-2747	146	2	.	.	NUM
cana-2747	146	3	proposed	propose	VERB
cana-2747	146	4	approach	approach	NOUN
cana-2747	146	5	the	the	DET
cana-2747	146	6	lstm	lstm	PROPN
cana-2747	146	7	-	-	PUNCT
cana-2747	146	8	cnn	cnn	PROPN
cana-2747	146	9	model	model	NOUN
cana-2747	146	10	integrates	integrate	VERB
cana-2747	146	11	long	long	ADJ
cana-2747	146	12	short	short	ADJ
cana-2747	146	13	-	-	PUNCT
cana-2747	146	14	term	term	NOUN
cana-2747	146	15	memory	memory	NOUN
cana-2747	146	16	(	(	PUNCT
cana-2747	146	17	lstm	lstm	NOUN
cana-2747	146	18	)	)	PUNCT
cana-2747	146	19	and	and	CCONJ
cana-2747	146	20	convolutional	convolutional	ADJ
cana-2747	146	21	neural	neural	ADJ
cana-2747	146	22	network	network	NOUN
cana-2747	146	23	(	(	PUNCT
cana-2747	146	24	cnn	cnn	PROPN
cana-2747	146	25	)	)	PUNCT
cana-2747	146	26	architectures	architecture	VERB
cana-2747	146	27	for	for	ADP
cana-2747	146	28	sequence	sequence	NOUN
cana-2747	146	29	modeling	modeling	NOUN
cana-2747	146	30	.	.	PUNCT
cana-2747	147	1	the	the	DET
cana-2747	147	2	lstm	lstm	PROPN
cana-2747	147	3	part	part	NOUN
cana-2747	147	4	handles	handle	VERB
cana-2747	147	5	temporal	temporal	ADJ
cana-2747	147	6	features	feature	NOUN
cana-2747	147	7	and	and	CCONJ
cana-2747	147	8	long	long	ADJ
cana-2747	147	9	-	-	PUNCT
cana-2747	147	10	range	range	NOUN
cana-2747	147	11	dependencies	dependency	NOUN
cana-2747	147	12	,	,	PUNCT
cana-2747	147	13	while	while	SCONJ
cana-2747	147	14	the	the	DET
cana-2747	147	15	cnn	cnn	PROPN
cana-2747	147	16	part	part	NOUN
cana-2747	147	17	learns	learn	VERB
cana-2747	147	18	local	local	ADJ
cana-2747	147	19	patterns	pattern	NOUN
cana-2747	147	20	or	or	CCONJ
cana-2747	147	21	spatial	spatial	ADJ
cana-2747	147	22	features	feature	NOUN
cana-2747	147	23	from	from	ADP
cana-2747	147	24	the	the	DET
cana-2747	147	25	data	datum	NOUN
cana-2747	147	26	.	.	PUNCT
cana-2747	148	1	whereas	whereas	SCONJ
cana-2747	148	2	mobilenet	mobilenet	NOUN
cana-2747	148	3	that	that	PRON
cana-2747	148	4	are	be	AUX
cana-2747	148	5	trained	train	VERB
cana-2747	148	6	on	on	ADP
cana-2747	148	7	the	the	DET
cana-2747	148	8	deep	deep	ADJ
cana-2747	148	9	dataset	dataset	NOUN
cana-2747	148	10	video	video	NOUN
cana-2747	148	11	frames	frame	NOUN
cana-2747	148	12	for	for	ADP
cana-2747	148	13	facial	facial	ADJ
cana-2747	148	14	recognition	recognition	NOUN
cana-2747	148	15	.	.	PUNCT
cana-2747	149	1	4.1	4.1	NUM
cana-2747	149	2	cnn	cnn	NOUN
cana-2747	149	3	(	(	PUNCT
cana-2747	149	4	convolutional	convolutional	ADJ
cana-2747	149	5	neural	neural	ADJ
cana-2747	149	6	network	network	NOUN
cana-2747	149	7	):	):	PUNCT
cana-2747	149	8	the	the	DET
cana-2747	149	9	cnn	cnn	PROPN
cana-2747	149	10	architecture	architecture	NOUN
cana-2747	149	11	employs	employ	VERB
cana-2747	149	12	a	a	DET
cana-2747	149	13	2d	2d	NUM
cana-2747	149	14	convolutional	convolutional	ADJ
cana-2747	149	15	layer	layer	NOUN
cana-2747	149	16	,	,	PUNCT
cana-2747	149	17	where	where	SCONJ
cana-2747	149	18	the	the	DET
cana-2747	149	19	initial	initial	ADJ
cana-2747	149	20	layer	layer	NOUN
cana-2747	149	21	extracts	extract	VERB
cana-2747	149	22	low	low	ADJ
cana-2747	149	23	-	-	PUNCT
cana-2747	149	24	level	level	NOUN
cana-2747	149	25	features	feature	NOUN
cana-2747	149	26	using	use	VERB
cana-2747	149	27	128	128	NUM
cana-2747	149	28	filters	filter	NOUN
cana-2747	149	29	with	with	ADP
cana-2747	149	30	a	a	DET
cana-2747	149	31	3x3	3x3	NUM
cana-2747	149	32	kernel	kernel	NOUN
cana-2747	149	33	size	size	NOUN
cana-2747	149	34	,	,	PUNCT
cana-2747	149	35	followed	follow	VERB
cana-2747	149	36	by	by	ADP
cana-2747	149	37	batch	batch	NOUN
cana-2747	149	38	normalization	normalization	NOUN
cana-2747	149	39	and	and	CCONJ
cana-2747	149	40	a	a	DET
cana-2747	149	41	relu	relu	NOUN
cana-2747	149	42	activation	activation	NOUN
cana-2747	149	43	function	function	NOUN
cana-2747	149	44	.	.	PUNCT
cana-2747	150	1	batch	batch	NOUN
cana-2747	150	2	normalization	normalization	NOUN
cana-2747	150	3	standardizes	standardize	VERB
cana-2747	150	4	the	the	DET
cana-2747	150	5	outputs	output	NOUN
cana-2747	150	6	of	of	ADP
cana-2747	150	7	the	the	DET
cana-2747	150	8	convolutional	convolutional	ADJ
cana-2747	150	9	layer	layer	NOUN
cana-2747	150	10	,	,	PUNCT
cana-2747	150	11	accelerating	accelerate	VERB
cana-2747	150	12	the	the	DET
cana-2747	150	13	training	training	NOUN
cana-2747	150	14	process	process	NOUN
cana-2747	150	15	and	and	CCONJ
cana-2747	150	16	enhancing	enhance	VERB
cana-2747	150	17	model	model	NOUN
cana-2747	150	18	stability	stability	NOUN
cana-2747	150	19	.	.	PUNCT
cana-2747	151	1	the	the	DET
cana-2747	151	2	relu	relu	NOUN
cana-2747	151	3	activation	activation	NOUN
cana-2747	151	4	introduces	introduce	VERB
cana-2747	151	5	nonlinearity	nonlinearity	NOUN
cana-2747	151	6	,	,	PUNCT
cana-2747	151	7	allowing	allow	VERB
cana-2747	151	8	the	the	DET
cana-2747	151	9	network	network	NOUN
cana-2747	151	10	to	to	PART
cana-2747	151	11	capture	capture	VERB
cana-2747	151	12	more	more	ADV
cana-2747	151	13	complex	complex	ADJ
cana-2747	151	14	patterns	pattern	NOUN
cana-2747	151	15	.	.	PUNCT
cana-2747	152	1	the	the	DET
cana-2747	152	2	second	second	ADJ
cana-2747	152	3	convolutional	convolutional	ADJ
cana-2747	152	4	layer	layer	NOUN
cana-2747	152	5	further	far	ADV
cana-2747	152	6	enhances	enhance	VERB
cana-2747	152	7	feature	feature	NOUN
cana-2747	152	8	extraction	extraction	NOUN
cana-2747	152	9	with	with	ADP
cana-2747	152	10	64	64	NUM
cana-2747	152	11	filters	filter	NOUN
cana-2747	152	12	,	,	PUNCT
cana-2747	152	13	refining	refine	VERB
cana-2747	152	14	the	the	DET
cana-2747	152	15	low	low	ADJ
cana-2747	152	16	-	-	PUNCT
cana-2747	152	17	level	level	NOUN
cana-2747	152	18	features	feature	NOUN
cana-2747	152	19	identified	identify	VERB
cana-2747	152	20	by	by	ADP
cana-2747	152	21	the	the	DET
cana-2747	152	22	first	first	ADJ
cana-2747	152	23	layer	layer	NOUN
cana-2747	152	24	.	.	PUNCT
cana-2747	153	1	this	this	DET
cana-2747	153	2	layer	layer	NOUN
cana-2747	153	3	also	also	ADV
cana-2747	153	4	includes	include	VERB
cana-2747	153	5	batch	batch	NOUN
cana-2747	153	6	normalization	normalization	NOUN
cana-2747	153	7	and	and	CCONJ
cana-2747	153	8	a	a	DET
cana-2747	153	9	relu	relu	NOUN
cana-2747	153	10	activation	activation	NOUN
cana-2747	153	11	function	function	NOUN
cana-2747	153	12	,	,	PUNCT
cana-2747	153	13	ensuring	ensure	VERB
cana-2747	153	14	consistency	consistency	NOUN
cana-2747	153	15	in	in	ADP
cana-2747	153	16	activation	activation	NOUN
cana-2747	153	17	and	and	CCONJ
cana-2747	153	18	normalization	normalization	NOUN
cana-2747	153	19	throughout	throughout	ADP
cana-2747	153	20	the	the	DET
cana-2747	153	21	network.the	network.the	DET
cana-2747	153	22	third	third	ADJ
cana-2747	153	23	convolution	convolution	NOUN
cana-2747	153	24	layer	layer	NOUN
cana-2747	153	25	extracts	extract	VERB
cana-2747	153	26	higher	high	ADJ
cana-2747	153	27	-	-	PUNCT
cana-2747	153	28	level	level	NOUN
cana-2747	153	29	features	feature	NOUN
cana-2747	153	30	with	with	ADP
cana-2747	153	31	32	32	NUM
cana-2747	153	32	filters	filter	NOUN
cana-2747	153	33	.	.	PUNCT
cana-2747	154	1	by	by	ADP
cana-2747	154	2	progressively	progressively	ADV
cana-2747	154	3	reducing	reduce	VERB
cana-2747	154	4	the	the	DET
cana-2747	154	5	number	number	NOUN
cana-2747	154	6	of	of	ADP
cana-2747	154	7	filters	filter	NOUN
cana-2747	154	8	,	,	PUNCT
cana-2747	154	9	the	the	DET
cana-2747	154	10	network	network	NOUN
cana-2747	154	11	hones	hone	NOUN
cana-2747	154	12	in	in	ADV
cana-2747	154	13	on	on	ADP
cana-2747	154	14	more	more	ADV
cana-2747	154	15	specific	specific	ADJ
cana-2747	154	16	features	feature	NOUN
cana-2747	154	17	.	.	PUNCT
cana-2747	155	1	similar	similar	ADJ
cana-2747	155	2	to	to	ADP
cana-2747	155	3	the	the	DET
cana-2747	155	4	previous	previous	ADJ
cana-2747	155	5	layers	layer	NOUN
cana-2747	155	6	,	,	PUNCT
cana-2747	155	7	batch	batch	VERB
cana-2747	155	8	normalization	normalization	NOUN
cana-2747	155	9	and	and	CCONJ
cana-2747	155	10	relu	relu	NOUN
cana-2747	155	11	activation	activation	NOUN
cana-2747	155	12	are	be	AUX
cana-2747	155	13	applied	apply	VERB
cana-2747	155	14	.	.	PUNCT
cana-2747	156	1	the	the	DET
cana-2747	156	2	subsequent	subsequent	ADJ
cana-2747	156	3	layer	layer	NOUN
cana-2747	156	4	,	,	PUNCT
cana-2747	156	5	known	know	VERB
cana-2747	156	6	as	as	ADP
cana-2747	156	7	the	the	DET
cana-2747	156	8	flatten	flatten	ADJ
cana-2747	156	9	layer	layer	NOUN
cana-2747	156	10	,	,	PUNCT
cana-2747	156	11	converts	convert	VERB
cana-2747	156	12	the	the	DET
cana-2747	156	13	2d	2d	NUM
cana-2747	156	14	matrix	matrix	NOUN
cana-2747	156	15	outputs	output	NOUN
cana-2747	156	16	from	from	ADP
cana-2747	156	17	the	the	DET
cana-2747	156	18	convolutional	convolutional	ADJ
cana-2747	156	19	layers	layer	NOUN
cana-2747	156	20	into	into	ADP
cana-2747	156	21	1d	1d	NUM
cana-2747	156	22	vectors	vector	NOUN
cana-2747	156	23	,	,	PUNCT
cana-2747	156	24	preparing	prepare	VERB
cana-2747	156	25	them	they	PRON
cana-2747	156	26	for	for	ADP
cana-2747	156	27	input	input	NOUN
cana-2747	156	28	into	into	ADP
cana-2747	156	29	the	the	DET
cana-2747	156	30	dense	dense	ADJ
cana-2747	156	31	layer	layer	NOUN
cana-2747	156	32	.	.	PUNCT
cana-2747	157	1	the	the	DET
cana-2747	157	2	dense	dense	ADJ
cana-2747	157	3	layer	layer	NOUN
cana-2747	157	4	,	,	PUNCT
cana-2747	157	5	consisting	consist	VERB
cana-2747	157	6	of	of	ADP
cana-2747	157	7	1024	1024	NUM
cana-2747	157	8	units	unit	NOUN
cana-2747	157	9	,	,	PUNCT
cana-2747	157	10	then	then	ADV
cana-2747	157	11	processes	process	VERB
cana-2747	157	12	these	these	DET
cana-2747	157	13	flattened	flatten	VERB
cana-2747	157	14	vectors	vector	NOUN
cana-2747	157	15	,	,	PUNCT
cana-2747	157	16	enabling	enable	VERB
cana-2747	157	17	the	the	DET
cana-2747	157	18	network	network	NOUN
cana-2747	157	19	to	to	PART
cana-2747	157	20	learn	learn	VERB
cana-2747	157	21	high	high	ADJ
cana-2747	157	22	-	-	PUNCT
cana-2747	157	23	level	level	NOUN
cana-2747	157	24	representations	representation	NOUN
cana-2747	157	25	of	of	ADP
cana-2747	157	26	the	the	DET
cana-2747	157	27	image	image	NOUN
cana-2747	157	28	data	datum	NOUN
cana-2747	157	29	.	.	PUNCT
cana-2747	158	1	4.2	4.2	NUM
cana-2747	158	2	lstm	lstm	NOUN
cana-2747	158	3	(	(	PUNCT
cana-2747	158	4	long	long	ADJ
cana-2747	158	5	short	short	ADJ
cana-2747	158	6	-	-	PUNCT
cana-2747	158	7	term	term	NOUN
cana-2747	158	8	memory	memory	NOUN
cana-2747	158	9	):	):	PUNCT
cana-2747	158	10	lstm	lstm	PROPN
cana-2747	158	11	,	,	PUNCT
cana-2747	158	12	a	a	DET
cana-2747	158	13	variant	variant	NOUN
cana-2747	158	14	of	of	ADP
cana-2747	158	15	recurrent	recurrent	ADJ
cana-2747	158	16	neural	neural	ADJ
cana-2747	158	17	network	network	NOUN
cana-2747	158	18	(	(	PUNCT
cana-2747	158	19	rnn	rnn	PROPN
cana-2747	158	20	)	)	PUNCT
cana-2747	158	21	,	,	PUNCT
cana-2747	158	22	is	be	AUX
cana-2747	158	23	specifically	specifically	ADV
cana-2747	158	24	designed	design	VERB
cana-2747	158	25	to	to	PART
cana-2747	158	26	effectively	effectively	ADV
cana-2747	158	27	process	process	VERB
cana-2747	158	28	sequences	sequence	NOUN
cana-2747	158	29	and	and	CCONJ
cana-2747	158	30	time	time	NOUN
cana-2747	158	31	-	-	PUNCT
cana-2747	158	32	series	series	NOUN
cana-2747	158	33	data	datum	NOUN
cana-2747	158	34	.	.	PUNCT
cana-2747	159	1	it	it	PRON
cana-2747	159	2	excels	excel	VERB
cana-2747	159	3	at	at	ADP
cana-2747	159	4	capturing	capture	VERB
cana-2747	159	5	long	long	ADJ
cana-2747	159	6	-	-	PUNCT
cana-2747	159	7	range	range	NOUN
cana-2747	159	8	dependencies	dependency	NOUN
cana-2747	159	9	in	in	ADP
cana-2747	159	10	sequential	sequential	ADJ
cana-2747	159	11	data	datum	NOUN
cana-2747	159	12	and	and	CCONJ
cana-2747	159	13	is	be	AUX
cana-2747	159	14	capable	capable	ADJ
cana-2747	159	15	of	of	ADP
cana-2747	159	16	retaining	retain	VERB
cana-2747	159	17	pertinent	pertinent	ADJ
cana-2747	159	18	information	information	NOUN
cana-2747	159	19	across	across	ADP
cana-2747	159	20	extended	extended	ADJ
cana-2747	159	21	time	time	NOUN
cana-2747	159	22	steps.in	steps.in	ADP
cana-2747	159	23	the	the	DET
cana-2747	159	24	context	context	NOUN
cana-2747	159	25	of	of	ADP
cana-2747	159	26	sequence	sequence	NOUN
cana-2747	159	27	modeling	modeling	NOUN
cana-2747	159	28	,	,	PUNCT
cana-2747	159	29	lstm	lstm	NOUN
cana-2747	159	30	is	be	AUX
cana-2747	159	31	frequently	frequently	ADV
cana-2747	159	32	employed	employ	VERB
cana-2747	159	33	to	to	PART
cana-2747	159	34	capture	capture	VERB
cana-2747	159	35	and	and	CCONJ
cana-2747	159	36	process	process	VERB
cana-2747	159	37	the	the	DET
cana-2747	159	38	temporal	temporal	ADJ
cana-2747	159	39	features	feature	NOUN
cana-2747	159	40	of	of	ADP
cana-2747	159	41	data	datum	NOUN
cana-2747	159	42	.	.	PUNCT
cana-2747	160	1	in	in	ADP
cana-2747	160	2	this	this	DET
cana-2747	160	3	work	work	NOUN
cana-2747	160	4	output	output	NOUN
cana-2747	160	5	from	from	ADP
cana-2747	160	6	the	the	DET
cana-2747	160	7	cnn	cnn	PROPN
cana-2747	160	8	is	be	AUX
cana-2747	160	9	passed	pass	VERB
cana-2747	160	10	to	to	ADP
cana-2747	160	11	first	first	ADV
cana-2747	160	12	lstm	lstm	ADJ
cana-2747	160	13	layers	layer	NOUN
cana-2747	160	14	to	to	PART
cana-2747	160	15	capture	capture	VERB
cana-2747	160	16	temporal	temporal	ADJ
cana-2747	160	17	dependencies	dependency	NOUN
cana-2747	160	18	.	.	PUNCT
cana-2747	161	1	its	its	PRON
cana-2747	161	2	purpose	purpose	NOUN
cana-2747	161	3	captures	capture	VERB
cana-2747	161	4	long	long	ADJ
cana-2747	161	5	-	-	PUNCT
cana-2747	161	6	range	range	NOUN
cana-2747	161	7	dependencies	dependency	NOUN
cana-2747	161	8	in	in	ADP
cana-2747	161	9	the	the	DET
cana-2747	161	10	sequence	sequence	NOUN
cana-2747	161	11	data	datum	NOUN
cana-2747	161	12	,	,	PUNCT
cana-2747	161	13	with	with	ADP
cana-2747	161	14	512	512	NUM
cana-2747	161	15	units	unit	NOUN
cana-2747	161	16	.	.	PUNCT
cana-2747	162	1	the	the	DET
cana-2747	162	2	second	second	ADJ
cana-2747	162	3	lstm	lstm	NOUN
cana-2747	162	4	layer	layer	NOUN
cana-2747	162	5	processes	process	VERB
cana-2747	162	6	the	the	DET
cana-2747	162	7	sequential	sequential	ADJ
cana-2747	162	8	data	datum	NOUN
cana-2747	162	9	,	,	PUNCT
cana-2747	162	10	with	with	ADP
cana-2747	162	11	256	256	NUM
cana-2747	162	12	units	unit	NOUN
cana-2747	162	13	.	.	PUNCT
cana-2747	163	1	communications	communication	NOUN
cana-2747	163	2	on	on	ADP
cana-2747	163	3	applied	apply	VERB
cana-2747	163	4	nonlinear	nonlinear	ADJ
cana-2747	163	5	analysis	analysis	NOUN
cana-2747	163	6	issn	issn	NOUN
cana-2747	163	7	:	:	PUNCT
cana-2747	163	8	1074	1074	NUM
cana-2747	163	9	-	-	PUNCT
cana-2747	163	10	133x	133x	NUM
cana-2747	163	11	vol	vol	NOUN
cana-2747	163	12	32	32	NUM
cana-2747	163	13	no	no	NOUN
cana-2747	163	14	.	.	PUNCT
cana-2747	164	1	4s	4s	NUM
cana-2747	164	2	(	(	PUNCT
cana-2747	164	3	2025	2025	NUM
cana-2747	164	4	)	)	PUNCT
cana-2747	164	5	177	177	NUM
cana-2747	164	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	164	7	4.3	4.3	NUM
cana-2747	164	8	integration	integration	NOUN
cana-2747	164	9	of	of	ADP
cana-2747	164	10	lstm	lstm	PROPN
cana-2747	164	11	and	and	CCONJ
cana-2747	164	12	cnn	cnn	PROPN
cana-2747	164	13	in	in	ADP
cana-2747	164	14	the	the	DET
cana-2747	164	15	lstm	lstm	PROPN
cana-2747	164	16	-	-	PUNCT
cana-2747	164	17	cnn	cnn	PROPN
cana-2747	164	18	model	model	NOUN
cana-2747	164	19	:	:	PUNCT
cana-2747	164	20	the	the	DET
cana-2747	164	21	final	final	ADJ
cana-2747	164	22	model	model	NOUN
cana-2747	164	23	combines	combine	VERB
cana-2747	164	24	both	both	CCONJ
cana-2747	164	25	the	the	DET
cana-2747	164	26	cnn	cnn	PROPN
cana-2747	164	27	and	and	CCONJ
cana-2747	164	28	lstm	lstm	ADJ
cana-2747	164	29	components	component	NOUN
cana-2747	164	30	to	to	PART
cana-2747	164	31	leverage	leverage	VERB
cana-2747	164	32	the	the	DET
cana-2747	164	33	strengths	strength	NOUN
cana-2747	164	34	of	of	ADP
cana-2747	164	35	both	both	DET
cana-2747	164	36	architectures	architecture	NOUN
cana-2747	164	37	.	.	PUNCT
cana-2747	165	1	the	the	DET
cana-2747	165	2	cnn	cnn	PROPN
cana-2747	165	3	layers	layer	NOUN
cana-2747	165	4	effectively	effectively	ADV
cana-2747	165	5	capture	capture	VERB
cana-2747	165	6	spatial	spatial	ADJ
cana-2747	165	7	features	feature	NOUN
cana-2747	165	8	from	from	ADP
cana-2747	165	9	each	each	DET
cana-2747	165	10	frame	frame	NOUN
cana-2747	165	11	,	,	PUNCT
cana-2747	165	12	while	while	SCONJ
cana-2747	165	13	the	the	DET
cana-2747	165	14	lstm	lstm	NOUN
cana-2747	165	15	layers	layer	NOUN
cana-2747	165	16	model	model	VERB
cana-2747	165	17	the	the	DET
cana-2747	165	18	temporal	temporal	ADJ
cana-2747	165	19	dynamics	dynamic	NOUN
cana-2747	165	20	across	across	ADP
cana-2747	165	21	frames	frame	NOUN
cana-2747	165	22	.	.	PUNCT
cana-2747	166	1	this	this	DET
cana-2747	166	2	hybrid	hybrid	ADJ
cana-2747	166	3	approach	approach	NOUN
cana-2747	166	4	is	be	AUX
cana-2747	166	5	powerful	powerful	ADJ
cana-2747	166	6	for	for	ADP
cana-2747	166	7	applications	application	NOUN
cana-2747	166	8	like	like	ADP
cana-2747	166	9	video	video	NOUN
cana-2747	166	10	classification	classification	NOUN
cana-2747	166	11	,	,	PUNCT
cana-2747	166	12	where	where	SCONJ
cana-2747	166	13	understanding	understand	VERB
cana-2747	166	14	both	both	CCONJ
cana-2747	166	15	spatial	spatial	ADJ
cana-2747	166	16	and	and	CCONJ
cana-2747	166	17	temporal	temporal	ADJ
cana-2747	166	18	patterns	pattern	NOUN
cana-2747	166	19	is	be	AUX
cana-2747	166	20	essential	essential	ADJ
cana-2747	166	21	.	.	PUNCT
cana-2747	167	1	the	the	DET
cana-2747	167	2	concatenated	concatenate	VERB
cana-2747	167	3	features	feature	NOUN
cana-2747	167	4	from	from	ADP
cana-2747	167	5	both	both	DET
cana-2747	167	6	models	model	NOUN
cana-2747	167	7	are	be	AUX
cana-2747	167	8	processed	process	VERB
cana-2747	167	9	through	through	ADP
cana-2747	167	10	additional	additional	ADJ
cana-2747	167	11	dense	dense	ADJ
cana-2747	167	12	layers	layer	NOUN
cana-2747	167	13	,	,	PUNCT
cana-2747	167	14	resulting	result	VERB
cana-2747	167	15	in	in	ADP
cana-2747	167	16	a	a	DET
cana-2747	167	17	comprehensive	comprehensive	ADJ
cana-2747	167	18	and	and	CCONJ
cana-2747	167	19	robust	robust	ADJ
cana-2747	167	20	model	model	NOUN
cana-2747	167	21	for	for	ADP
cana-2747	167	22	sequence	sequence	NOUN
cana-2747	167	23	-	-	PUNCT
cana-2747	167	24	based	base	VERB
cana-2747	167	25	image	image	NOUN
cana-2747	167	26	classification	classification	NOUN
cana-2747	167	27	tasks.by	tasks.by	X
cana-2747	167	28	freezing	freeze	VERB
cana-2747	167	29	the	the	DET
cana-2747	167	30	layers	layer	NOUN
cana-2747	167	31	of	of	ADP
cana-2747	167	32	the	the	DET
cana-2747	167	33	feature	feature	NOUN
cana-2747	167	34	extractor	extractor	NOUN
cana-2747	167	35	and	and	CCONJ
cana-2747	167	36	focusing	focus	VERB
cana-2747	167	37	on	on	ADP
cana-2747	167	38	training	training	NOUN
cana-2747	167	39	only	only	ADV
cana-2747	167	40	the	the	DET
cana-2747	167	41	top	top	ADJ
cana-2747	167	42	dense	dense	ADJ
cana-2747	167	43	layers	layer	NOUN
cana-2747	167	44	,	,	PUNCT
cana-2747	167	45	the	the	DET
cana-2747	167	46	model	model	NOUN
cana-2747	167	47	leverages	leverage	NOUN
cana-2747	167	48	pretrained	pretraine	VERB
cana-2747	167	49	knowledge	knowledge	NOUN
cana-2747	167	50	while	while	SCONJ
cana-2747	167	51	fine	fine	ADV
cana-2747	167	52	-	-	PUNCT
cana-2747	167	53	tuning	tune	VERB
cana-2747	167	54	the	the	DET
cana-2747	167	55	classification	classification	NOUN
cana-2747	167	56	layers	layer	NOUN
cana-2747	167	57	for	for	ADP
cana-2747	167	58	the	the	DET
cana-2747	167	59	specific	specific	ADJ
cana-2747	167	60	task	task	NOUN
cana-2747	167	61	.	.	PUNCT
cana-2747	168	1	this	this	DET
cana-2747	168	2	approach	approach	NOUN
cana-2747	168	3	balances	balance	VERB
cana-2747	168	4	the	the	DET
cana-2747	168	5	need	need	NOUN
cana-2747	168	6	for	for	ADP
cana-2747	168	7	robust	robust	ADJ
cana-2747	168	8	feature	feature	NOUN
cana-2747	168	9	extraction	extraction	NOUN
cana-2747	168	10	with	with	ADP
cana-2747	168	11	the	the	DET
cana-2747	168	12	flexibility	flexibility	NOUN
cana-2747	168	13	to	to	PART
cana-2747	168	14	adapt	adapt	VERB
cana-2747	168	15	to	to	ADP
cana-2747	168	16	new	new	ADJ
cana-2747	168	17	data	datum	NOUN
cana-2747	168	18	,	,	PUNCT
cana-2747	168	19	making	make	VERB
cana-2747	168	20	it	it	PRON
cana-2747	168	21	a	a	DET
cana-2747	168	22	versatile	versatile	ADJ
cana-2747	168	23	solution	solution	NOUN
cana-2747	168	24	for	for	ADP
cana-2747	168	25	various	various	ADJ
cana-2747	168	26	sequence	sequence	NOUN
cana-2747	168	27	classification	classification	NOUN
cana-2747	168	28	problems	problem	NOUN
cana-2747	168	29	.	.	PUNCT
cana-2747	169	1	lstm	lstm	PROPN
cana-2747	169	2	-	-	PUNCT
cana-2747	169	3	cnn	cnn	PROPN
cana-2747	169	4	will	will	AUX
cana-2747	169	5	get	get	AUX
cana-2747	169	6	trained	train	VERB
cana-2747	169	7	from	from	ADP
cana-2747	169	8	scratch	scratch	NOUN
cana-2747	169	9	since	since	SCONJ
cana-2747	169	10	there	there	PRON
cana-2747	169	11	are	be	VERB
cana-2747	169	12	no	no	DET
cana-2747	169	13	pre	pre	ADJ
cana-2747	169	14	-	-	ADJ
cana-2747	169	15	trained	train	VERB
cana-2747	169	16	weights	weight	NOUN
cana-2747	169	17	.	.	PUNCT
cana-2747	170	1	take	take	VERB
cana-2747	170	2	person	person	NOUN
cana-2747	170	3	i	i	PROPN
cana-2747	170	4	d	d	PROPN
cana-2747	170	5	,	,	PUNCT
cana-2747	170	6	form	form	VERB
cana-2747	170	7	an	an	DET
cana-2747	170	8	array	array	NOUN
cana-2747	170	9	with	with	ADP
cana-2747	170	10	relative	relative	ADJ
cana-2747	170	11	indices	index	NOUN
cana-2747	170	12	,	,	PUNCT
cana-2747	170	13	and	and	CCONJ
cana-2747	170	14	extrapolate	extrapolate	VERB
cana-2747	170	15	those	those	DET
cana-2747	170	16	22	22	NUM
cana-2747	170	17	into	into	ADP
cana-2747	170	18	22x6x40	22x6x40	NUM
cana-2747	170	19	samples	sample	NOUN
cana-2747	170	20	according	accord	VERB
cana-2747	170	21	to	to	ADP
cana-2747	170	22	our	our	PRON
cana-2747	170	23	input	input	NOUN
cana-2747	170	24	data	datum	NOUN
cana-2747	170	25	.	.	PUNCT
cana-2747	171	1	4.4	4.4	NUM
cana-2747	171	2	mobilenet	mobilenet	NOUN
cana-2747	171	3	in	in	ADP
cana-2747	171	4	this	this	DET
cana-2747	171	5	work	work	NOUN
cana-2747	171	6	,	,	PUNCT
cana-2747	171	7	we	we	PRON
cana-2747	171	8	are	be	AUX
cana-2747	171	9	using	use	VERB
cana-2747	171	10	the	the	DET
cana-2747	171	11	networks	network	NOUN
cana-2747	171	12	of	of	ADP
cana-2747	171	13	mobilenet	mobilenet	NOUN
cana-2747	171	14	that	that	PRON
cana-2747	171	15	are	be	AUX
cana-2747	171	16	trained	train	VERB
cana-2747	171	17	on	on	ADP
cana-2747	171	18	the	the	DET
cana-2747	171	19	deep	deep	ADJ
cana-2747	171	20	dataset	dataset	NOUN
cana-2747	171	21	video	video	NOUN
cana-2747	171	22	frames	frame	NOUN
cana-2747	171	23	.	.	PUNCT
cana-2747	172	1	mobilenet	mobilenet	NOUN
cana-2747	172	2	is	be	AUX
cana-2747	172	3	often	often	ADV
cana-2747	172	4	referred	refer	VERB
cana-2747	172	5	to	to	ADP
cana-2747	172	6	as	as	ADP
cana-2747	172	7	a	a	DET
cana-2747	172	8	lightweight	lightweight	ADJ
cana-2747	172	9	convolutional	convolutional	ADJ
cana-2747	172	10	neural	neural	ADJ
cana-2747	172	11	network	network	NOUN
cana-2747	172	12	,	,	PUNCT
cana-2747	172	13	making	make	VERB
cana-2747	172	14	it	it	PRON
cana-2747	172	15	an	an	DET
cana-2747	172	16	efficient	efficient	ADJ
cana-2747	172	17	architecture	architecture	NOUN
cana-2747	172	18	for	for	ADP
cana-2747	172	19	mobile	mobile	ADJ
cana-2747	172	20	applications	application	NOUN
cana-2747	172	21	.	.	PUNCT
cana-2747	173	1	one	one	NUM
cana-2747	173	2	of	of	ADP
cana-2747	173	3	the	the	DET
cana-2747	173	4	key	key	ADJ
cana-2747	173	5	advantages	advantage	NOUN
cana-2747	173	6	of	of	ADP
cana-2747	173	7	mobilenet	mobilenet	NOUN
cana-2747	173	8	is	be	AUX
cana-2747	173	9	its	its	PRON
cana-2747	173	10	minimal	minimal	ADJ
cana-2747	173	11	computational	computational	ADJ
cana-2747	173	12	requirements	requirement	NOUN
cana-2747	173	13	.	.	PUNCT
cana-2747	174	1	unlike	unlike	ADP
cana-2747	174	2	standard	standard	ADJ
cana-2747	174	3	convolutions	convolution	NOUN
cana-2747	174	4	,	,	PUNCT
cana-2747	174	5	mobilenet	mobilenet	NOUN
cana-2747	174	6	employs	employ	VERB
cana-2747	174	7	depth	depth	NOUN
cana-2747	174	8	-	-	PUNCT
cana-2747	174	9	wise	wise	ADJ
cana-2747	174	10	separable	separable	ADJ
cana-2747	174	11	convolutions	convolution	NOUN
cana-2747	174	12	,	,	PUNCT
cana-2747	174	13	which	which	PRON
cana-2747	174	14	result	result	VERB
cana-2747	174	15	in	in	ADP
cana-2747	174	16	a	a	DET
cana-2747	174	17	lower	low	ADJ
cana-2747	174	18	number	number	NOUN
cana-2747	174	19	of	of	ADP
cana-2747	174	20	multiplications	multiplication	NOUN
cana-2747	174	21	compared	compare	VERB
cana-2747	174	22	to	to	ADP
cana-2747	174	23	traditional	traditional	ADJ
cana-2747	174	24	convolutions	convolution	NOUN
cana-2747	174	25	.	.	PUNCT
cana-2747	175	1	this	this	DET
cana-2747	175	2	reduction	reduction	NOUN
cana-2747	175	3	in	in	ADP
cana-2747	175	4	computational	computational	ADJ
cana-2747	175	5	complexity	complexity	NOUN
cana-2747	175	6	contributes	contribute	VERB
cana-2747	175	7	to	to	ADP
cana-2747	175	8	the	the	DET
cana-2747	175	9	overall	overall	ADJ
cana-2747	175	10	efficiency	efficiency	NOUN
cana-2747	175	11	of	of	ADP
cana-2747	175	12	mobilenet	mobilenet	NOUN
cana-2747	175	13	.	.	PUNCT
cana-2747	176	1	depthwise	depthwise	NOUN
cana-2747	176	2	separable	separable	ADJ
cana-2747	176	3	convolution	convolution	NOUN
cana-2747	176	4	comprises	comprise	VERB
cana-2747	176	5	both	both	DET
cana-2747	176	6	depth	depth	NOUN
cana-2747	176	7	-	-	PUNCT
cana-2747	176	8	wise	wise	ADJ
cana-2747	176	9	convolutions	convolution	NOUN
cana-2747	176	10	and	and	CCONJ
cana-2747	176	11	point	point	NOUN
cana-2747	176	12	-	-	PUNCT
cana-2747	176	13	wise	wise	ADJ
cana-2747	176	14	convolutions	convolution	NOUN
cana-2747	176	15	.	.	PUNCT
cana-2747	177	1	unlike	unlike	ADP
cana-2747	177	2	standard	standard	ADJ
cana-2747	177	3	cnns	cnn	NOUN
cana-2747	177	4	where	where	SCONJ
cana-2747	177	5	convolution	convolution	NOUN
cana-2747	177	6	is	be	AUX
cana-2747	177	7	applied	apply	VERB
cana-2747	177	8	to	to	ADP
cana-2747	177	9	all	all	DET
cana-2747	177	10	channels	channel	NOUN
cana-2747	177	11	simultaneously	simultaneously	ADV
cana-2747	177	12	,	,	PUNCT
cana-2747	177	13	depth	depth	NOUN
cana-2747	177	14	-	-	PUNCT
cana-2747	177	15	wise	wise	ADJ
cana-2747	177	16	convolution	convolution	NOUN
cana-2747	177	17	involves	involve	VERB
cana-2747	177	18	applying	apply	VERB
cana-2747	177	19	convolution	convolution	NOUN
cana-2747	177	20	to	to	ADP
cana-2747	177	21	one	one	NUM
cana-2747	177	22	channel	channel	NOUN
cana-2747	177	23	at	at	ADP
cana-2747	177	24	a	a	DET
cana-2747	177	25	time	time	NOUN
cana-2747	177	26	.	.	PUNCT
cana-2747	178	1	a	a	DET
cana-2747	178	2	5d	5d	NUM
cana-2747	178	3	numpy	numpy	NOUN
cana-2747	178	4	array	array	NOUN
cana-2747	178	5	is	be	AUX
cana-2747	178	6	initialized	initialize	VERB
cana-2747	178	7	to	to	PART
cana-2747	178	8	hold	hold	VERB
cana-2747	178	9	facial	facial	ADJ
cana-2747	178	10	images	image	NOUN
cana-2747	178	11	with	with	ADP
cana-2747	178	12	dimensions	dimension	NOUN
cana-2747	178	13	set	set	VERB
cana-2747	178	14	as	as	ADP
cana-2747	178	15	(	(	PUNCT
cana-2747	178	16	number	number	NOUN
cana-2747	178	17	of	of	ADP
cana-2747	178	18	persons	person	NOUN
cana-2747	178	19	,	,	PUNCT
cana-2747	178	20	240	240	NUM
cana-2747	178	21	,	,	PUNCT
cana-2747	178	22	224	224	NUM
cana-2747	178	23	,	,	PUNCT
cana-2747	178	24	224	224	NUM
cana-2747	178	25	,	,	PUNCT
cana-2747	178	26	3	3	NUM
cana-2747	178	27	)	)	PUNCT
cana-2747	178	28	.	.	PUNCT
cana-2747	179	1	the	the	DET
cana-2747	179	2	pixel	pixel	PROPN
cana-2747	179	3	values	value	NOUN
cana-2747	179	4	of	of	ADP
cana-2747	179	5	these	these	DET
cana-2747	179	6	images	image	NOUN
cana-2747	179	7	are	be	AUX
cana-2747	179	8	then	then	ADV
cana-2747	179	9	rescaled	rescale	VERB
cana-2747	179	10	from	from	ADP
cana-2747	179	11	their	their	PRON
cana-2747	179	12	original	original	ADJ
cana-2747	179	13	range	range	NOUN
cana-2747	179	14	of	of	ADP
cana-2747	179	15	[	[	X
cana-2747	179	16	0	0	NUM
cana-2747	179	17	,	,	PUNCT
cana-2747	179	18	255	255	NUM
cana-2747	179	19	]	]	PUNCT
cana-2747	179	20	to	to	ADP
cana-2747	179	21	a	a	DET
cana-2747	179	22	new	new	ADJ
cana-2747	179	23	range	range	NOUN
cana-2747	179	24	of	of	ADP
cana-2747	179	25	[	[	X
cana-2747	179	26	-1	-1	X
cana-2747	179	27	,	,	PUNCT
cana-2747	179	28	1].the	1].the	DET
cana-2747	179	29	division	division	NOUN
cana-2747	179	30	by	by	ADP
cana-2747	179	31	127.5	127.5	NUM
cana-2747	179	32	centres	centre	NOUN
cana-2747	179	33	the	the	DET
cana-2747	179	34	data	datum	NOUN
cana-2747	179	35	around	around	ADP
cana-2747	179	36	0	0	NUM
cana-2747	179	37	,	,	PUNCT
cana-2747	179	38	and	and	CCONJ
cana-2747	179	39	subtracting	subtract	VERB
cana-2747	179	40	1	1	NUM
cana-2747	179	41	scales	scale	VERB
cana-2747	179	42	it	it	PRON
cana-2747	179	43	to	to	ADP
cana-2747	179	44	the	the	DET
cana-2747	179	45	range	range	NOUN
cana-2747	179	46	[	[	X
cana-2747	179	47	-1	-1	X
cana-2747	179	48	,	,	PUNCT
cana-2747	179	49	1	1	NUM
cana-2747	179	50	]	]	PUNCT
cana-2747	179	51	.	.	PUNCT
cana-2747	180	1	scaling	scale	VERB
cana-2747	180	2	pixel	pixel	ADJ
cana-2747	180	3	values	value	NOUN
cana-2747	180	4	to	to	ADP
cana-2747	180	5	a	a	DET
cana-2747	180	6	range	range	NOUN
cana-2747	180	7	of	of	ADP
cana-2747	180	8	[	[	X
cana-2747	180	9	-1	-1	X
cana-2747	180	10	,	,	PUNCT
cana-2747	180	11	1	1	NUM
cana-2747	180	12	]	]	PUNCT
cana-2747	180	13	is	be	AUX
cana-2747	180	14	a	a	DET
cana-2747	180	15	common	common	ADJ
cana-2747	180	16	preprocessing	preprocessing	NOUN
cana-2747	180	17	step	step	NOUN
cana-2747	180	18	in	in	ADP
cana-2747	180	19	machine	machine	NOUN
cana-2747	180	20	learning	learning	NOUN
cana-2747	180	21	,	,	PUNCT
cana-2747	180	22	especially	especially	ADV
cana-2747	180	23	for	for	ADP
cana-2747	180	24	neural	neural	ADJ
cana-2747	180	25	networks	network	NOUN
cana-2747	180	26	.	.	PUNCT
cana-2747	181	1	it	it	PRON
cana-2747	181	2	can	can	AUX
cana-2747	181	3	improve	improve	VERB
cana-2747	181	4	convergence	convergence	NOUN
cana-2747	181	5	during	during	ADP
cana-2747	181	6	training	training	NOUN
cana-2747	181	7	and	and	CCONJ
cana-2747	181	8	help	help	VERB
cana-2747	181	9	the	the	DET
cana-2747	181	10	model	model	NOUN
cana-2747	181	11	better	well	ADV
cana-2747	181	12	handle	handle	VERB
cana-2747	181	13	the	the	DET
cana-2747	181	14	data	datum	NOUN
cana-2747	181	15	.	.	PUNCT
cana-2747	182	1	this	this	PRON
cana-2747	182	2	sets	set	VERB
cana-2747	182	3	up	up	ADP
cana-2747	182	4	a	a	DET
cana-2747	182	5	feature	feature	NOUN
cana-2747	182	6	extractor	extractor	NOUN
cana-2747	182	7	using	use	VERB
cana-2747	182	8	the	the	DET
cana-2747	182	9	mobilenetv3small	mobilenetv3small	NOUN
cana-2747	182	10	model	model	NOUN
cana-2747	182	11	from	from	ADP
cana-2747	182	12	tensor	tensor	NOUN
cana-2747	182	13	flow	flow	NOUN
cana-2747	182	14	's	's	PART
cana-2747	182	15	keras	keras	PROPN
cana-2747	182	16	applications	application	NOUN
cana-2747	182	17	.	.	PUNCT
cana-2747	183	1	this	this	PRON
cana-2747	183	2	sets	set	VERB
cana-2747	183	3	up	up	ADP
cana-2747	183	4	a	a	DET
cana-2747	183	5	pre	pre	ADJ
cana-2747	183	6	-	-	ADJ
cana-2747	183	7	trained	train	VERB
cana-2747	183	8	mobilenetv3small	mobilenetv3small	NOUN
cana-2747	183	9	model	model	NOUN
cana-2747	183	10	for	for	ADP
cana-2747	183	11	feature	feature	NOUN
cana-2747	183	12	extraction	extraction	NOUN
cana-2747	183	13	.	.	PUNCT
cana-2747	184	1	the	the	DET
cana-2747	184	2	model	model	NOUN
cana-2747	184	3	is	be	AUX
cana-2747	184	4	configured	configure	VERB
cana-2747	184	5	to	to	PART
cana-2747	184	6	exclude	exclude	VERB
cana-2747	184	7	the	the	DET
cana-2747	184	8	top	top	ADJ
cana-2747	184	9	layer	layer	NOUN
cana-2747	184	10	,	,	PUNCT
cana-2747	184	11	use	use	VERB
cana-2747	184	12	imagenet	imagenet	NOUN
cana-2747	184	13	pre	pre	ADJ
cana-2747	184	14	-	-	ADJ
cana-2747	184	15	trained	train	VERB
cana-2747	184	16	weights	weight	NOUN
cana-2747	184	17	,	,	PUNCT
cana-2747	184	18	take	take	VERB
cana-2747	184	19	images	image	NOUN
cana-2747	184	20	with	with	ADP
cana-2747	184	21	dimensions	dimension	NOUN
cana-2747	184	22	(	(	PUNCT
cana-2747	184	23	224	224	NUM
cana-2747	184	24	,	,	PUNCT
cana-2747	184	25	224	224	NUM
cana-2747	184	26	,	,	PUNCT
cana-2747	184	27	3	3	NUM
cana-2747	184	28	)	)	PUNCT
cana-2747	184	29	as	as	ADP
cana-2747	184	30	input	input	NOUN
cana-2747	184	31	,	,	PUNCT
cana-2747	184	32	and	and	CCONJ
cana-2747	184	33	use	use	VERB
cana-2747	184	34	global	global	ADJ
cana-2747	184	35	average	average	ADJ
cana-2747	184	36	pooling	pooling	NOUN
cana-2747	184	37	.	.	PUNCT
cana-2747	185	1	all	all	DET
cana-2747	185	2	layers	layer	NOUN
cana-2747	185	3	of	of	ADP
cana-2747	185	4	the	the	DET
cana-2747	185	5	model	model	NOUN
cana-2747	185	6	are	be	AUX
cana-2747	185	7	frozen	freeze	VERB
cana-2747	185	8	,	,	PUNCT
cana-2747	185	9	preventing	prevent	VERB
cana-2747	185	10	them	they	PRON
cana-2747	185	11	from	from	ADP
cana-2747	185	12	being	be	AUX
cana-2747	185	13	updated	update	VERB
cana-2747	185	14	during	during	ADP
cana-2747	185	15	subsequent	subsequent	ADJ
cana-2747	185	16	training	training	NOUN
cana-2747	185	17	.	.	PUNCT
cana-2747	186	1	this	this	DET
cana-2747	186	2	feature	feature	NOUN
cana-2747	186	3	extractor	extractor	NOUN
cana-2747	186	4	can	can	AUX
cana-2747	186	5	then	then	ADV
cana-2747	186	6	be	be	AUX
cana-2747	186	7	used	use	VERB
cana-2747	186	8	as	as	ADP
cana-2747	186	9	part	part	NOUN
cana-2747	186	10	of	of	ADP
cana-2747	186	11	a	a	DET
cana-2747	186	12	larger	large	ADJ
cana-2747	186	13	model	model	NOUN
cana-2747	186	14	for	for	ADP
cana-2747	186	15	tasks	task	NOUN
cana-2747	186	16	such	such	ADJ
cana-2747	186	17	as	as	ADP
cana-2747	186	18	facial	facial	ADJ
cana-2747	186	19	feature	feature	NOUN
cana-2747	186	20	analysis	analysis	NOUN
cana-2747	186	21	or	or	CCONJ
cana-2747	186	22	classification	classification	NOUN
cana-2747	186	23	.	.	PUNCT
cana-2747	187	1	5	5	X
cana-2747	187	2	.	.	X
cana-2747	187	3	hybrid	hybrid	ADJ
cana-2747	187	4	approach	approach	NOUN
cana-2747	187	5	the	the	DET
cana-2747	187	6	proposed	propose	VERB
cana-2747	187	7	model	model	NOUN
cana-2747	187	8	,	,	PUNCT
cana-2747	187	9	illustrated	illustrate	VERB
cana-2747	187	10	in	in	ADP
cana-2747	187	11	figure	figure	NOUN
cana-2747	187	12	3	3	NUM
cana-2747	187	13	consists	consist	NOUN
cana-2747	187	14	of	of	ADP
cana-2747	187	15	extracted	extract	VERB
cana-2747	187	16	feature	feature	NOUN
cana-2747	187	17	result	result	NOUN
cana-2747	187	18	of	of	ADP
cana-2747	187	19	mobile	mobile	ADJ
cana-2747	187	20	net	net	ADJ
cana-2747	187	21	architecture	architecture	NOUN
cana-2747	187	22	and	and	CCONJ
cana-2747	187	23	the	the	DET
cana-2747	187	24	lstm	lstm	PROPN
cana-2747	187	25	-	-	PUNCT
cana-2747	187	26	cnn	cnn	PROPN
cana-2747	187	27	model	model	NOUN
cana-2747	187	28	.	.	PUNCT
cana-2747	188	1	the	the	DET
cana-2747	188	2	proposed	propose	VERB
cana-2747	188	3	model	model	NOUN
cana-2747	188	4	architecture	architecture	NOUN
cana-2747	188	5	consists	consist	VERB
cana-2747	188	6	of	of	ADP
cana-2747	188	7	a	a	DET
cana-2747	188	8	bottleneck	bottleneck	NOUN
cana-2747	188	9	structure	structure	NOUN
cana-2747	188	10	with	with	ADP
cana-2747	188	11	two	two	NUM
cana-2747	188	12	hidden	hidden	ADJ
cana-2747	188	13	layers	layer	NOUN
cana-2747	188	14	having	have	VERB
cana-2747	188	15	256	256	NUM
cana-2747	188	16	and	and	CCONJ
cana-2747	188	17	64	64	NUM
cana-2747	188	18	neurons	neuron	NOUN
cana-2747	188	19	,	,	PUNCT
cana-2747	188	20	with	with	ADP
cana-2747	188	21	alternative	alternative	ADJ
cana-2747	188	22	dropout	dropout	NOUN
cana-2747	188	23	layer	layer	NOUN
cana-2747	188	24	and	and	CCONJ
cana-2747	188	25	an	an	DET
cana-2747	188	26	output	output	NOUN
cana-2747	188	27	layer	layer	NOUN
cana-2747	188	28	with	with	ADP
cana-2747	188	29	22	22	NUM
cana-2747	188	30	neurons	neuron	NOUN
cana-2747	188	31	using	use	VERB
cana-2747	188	32	softmax	softmax	NOUN
cana-2747	188	33	activation	activation	NOUN
cana-2747	188	34	.	.	PUNCT
cana-2747	189	1	the	the	DET
cana-2747	189	2	bottleneck	bottleneck	NOUN
cana-2747	189	3	structure	structure	NOUN
cana-2747	189	4	with	with	ADP
cana-2747	189	5	reduced	reduce	VERB
cana-2747	189	6	dimensions	dimension	NOUN
cana-2747	189	7	(	(	PUNCT
cana-2747	189	8	256	256	NUM
cana-2747	189	9	and	and	CCONJ
cana-2747	189	10	64	64	NUM
cana-2747	189	11	neurons	neuron	NOUN
cana-2747	189	12	)	)	PUNCT
cana-2747	189	13	is	be	AUX
cana-2747	189	14	often	often	ADV
cana-2747	189	15	used	use	VERB
cana-2747	189	16	for	for	ADP
cana-2747	189	17	dimensionality	dimensionality	NOUN
cana-2747	189	18	reduction	reduction	NOUN
cana-2747	189	19	and	and	CCONJ
cana-2747	189	20	feature	feature	NOUN
cana-2747	189	21	abstraction	abstraction	NOUN
cana-2747	189	22	.	.	PUNCT
cana-2747	190	1	it	it	PRON
cana-2747	190	2	communications	communication	VERB
cana-2747	190	3	on	on	ADP
cana-2747	190	4	applied	apply	VERB
cana-2747	190	5	nonlinear	nonlinear	ADJ
cana-2747	190	6	analysis	analysis	NOUN
cana-2747	190	7	issn	issn	NOUN
cana-2747	190	8	:	:	PUNCT
cana-2747	190	9	1074	1074	NUM
cana-2747	190	10	-	-	PUNCT
cana-2747	190	11	133x	133x	NUM
cana-2747	190	12	vol	vol	NOUN
cana-2747	190	13	32	32	NUM
cana-2747	190	14	no	no	NOUN
cana-2747	190	15	.	.	PUNCT
cana-2747	191	1	4s	4s	NUM
cana-2747	191	2	(	(	PUNCT
cana-2747	191	3	2025	2025	NUM
cana-2747	191	4	)	)	PUNCT
cana-2747	191	5	178	178	NUM
cana-2747	191	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	191	7	helps	help	VERB
cana-2747	191	8	in	in	ADP
cana-2747	191	9	learning	learn	VERB
cana-2747	191	10	a	a	DET
cana-2747	191	11	compact	compact	ADJ
cana-2747	191	12	representation	representation	NOUN
cana-2747	191	13	of	of	ADP
cana-2747	191	14	the	the	DET
cana-2747	191	15	input	input	NOUN
cana-2747	191	16	features	feature	NOUN
cana-2747	191	17	.	.	PUNCT
cana-2747	192	1	the	the	DET
cana-2747	192	2	weights	weight	NOUN
cana-2747	192	3	of	of	ADP
cana-2747	192	4	the	the	DET
cana-2747	192	5	lstm	lstm	PROPN
cana-2747	192	6	-	-	PUNCT
cana-2747	192	7	cnn	cnn	PROPN
cana-2747	192	8	layers	layer	NOUN
cana-2747	192	9	and	and	CCONJ
cana-2747	192	10	the	the	DET
cana-2747	192	11	bottleneck	bottleneck	NOUN
cana-2747	192	12	layers	layer	NOUN
cana-2747	192	13	are	be	AUX
cana-2747	192	14	trained	train	VERB
cana-2747	192	15	together	together	ADV
cana-2747	192	16	.	.	PUNCT
cana-2747	193	1	this	this	PRON
cana-2747	193	2	enables	enable	VERB
cana-2747	193	3	the	the	DET
cana-2747	193	4	model	model	NOUN
cana-2747	193	5	to	to	PART
cana-2747	193	6	learn	learn	VERB
cana-2747	193	7	a	a	DET
cana-2747	193	8	task	task	NOUN
cana-2747	193	9	-	-	PUNCT
cana-2747	193	10	specific	specific	ADJ
cana-2747	193	11	representation	representation	NOUN
cana-2747	193	12	while	while	SCONJ
cana-2747	193	13	preserving	preserve	VERB
cana-2747	193	14	the	the	DET
cana-2747	193	15	valuable	valuable	ADJ
cana-2747	193	16	features	feature	NOUN
cana-2747	193	17	learned	learn	VERB
cana-2747	193	18	by	by	ADP
cana-2747	193	19	mobilenet	mobilenet	PROPN
cana-2747	193	20	.	.	PUNCT
cana-2747	194	1	the	the	DET
cana-2747	194	2	output	output	NOUN
cana-2747	194	3	layer	layer	NOUN
cana-2747	194	4	uses	use	VERB
cana-2747	194	5	softmax	softmax	ADJ
cana-2747	194	6	activation	activation	NOUN
cana-2747	194	7	to	to	PART
cana-2747	194	8	transform	transform	VERB
cana-2747	194	9	the	the	DET
cana-2747	194	10	model	model	NOUN
cana-2747	194	11	's	's	PART
cana-2747	194	12	raw	raw	ADJ
cana-2747	194	13	outputs	output	NOUN
cana-2747	194	14	into	into	ADP
cana-2747	194	15	probabilities	probability	NOUN
cana-2747	194	16	,	,	PUNCT
cana-2747	194	17	making	make	VERB
cana-2747	194	18	it	it	PRON
cana-2747	194	19	ideal	ideal	ADJ
cana-2747	194	20	for	for	ADP
cana-2747	194	21	multiclass	multiclass	ADJ
cana-2747	194	22	classification.training	classification.traine	VERB
cana-2747	194	23	the	the	DET
cana-2747	194	24	lstm	lstm	PROPN
cana-2747	194	25	-	-	PUNCT
cana-2747	194	26	cnn	cnn	PROPN
cana-2747	194	27	layers	layer	NOUN
cana-2747	194	28	along	along	ADP
cana-2747	194	29	with	with	ADP
cana-2747	194	30	the	the	DET
cana-2747	194	31	bottleneck	bottleneck	NOUN
cana-2747	194	32	ensures	ensure	VERB
cana-2747	194	33	that	that	SCONJ
cana-2747	194	34	the	the	DET
cana-2747	194	35	model	model	NOUN
cana-2747	194	36	adapts	adapt	VERB
cana-2747	194	37	to	to	ADP
cana-2747	194	38	the	the	DET
cana-2747	194	39	specific	specific	ADJ
cana-2747	194	40	task	task	NOUN
cana-2747	194	41	of	of	ADP
cana-2747	194	42	classifying	classify	VERB
cana-2747	194	43	persons	person	NOUN
cana-2747	194	44	,	,	PUNCT
cana-2747	194	45	taking	take	VERB
cana-2747	194	46	into	into	ADP
cana-2747	194	47	account	account	NOUN
cana-2747	194	48	both	both	CCONJ
cana-2747	194	49	the	the	DET
cana-2747	194	50	facial	facial	ADJ
cana-2747	194	51	features	feature	NOUN
cana-2747	194	52	from	from	ADP
cana-2747	194	53	mobilenet	mobilenet	NOUN
cana-2747	194	54	and	and	CCONJ
cana-2747	194	55	the	the	DET
cana-2747	194	56	temporal	temporal	ADJ
cana-2747	194	57	and	and	CCONJ
cana-2747	194	58	spatial	spatial	ADJ
cana-2747	194	59	features	feature	NOUN
cana-2747	194	60	from	from	ADP
cana-2747	194	61	the	the	DET
cana-2747	194	62	lstm	lstm	PROPN
cana-2747	194	63	-	-	PUNCT
cana-2747	194	64	cnn	cnn	PROPN
cana-2747	194	65	.	.	PUNCT
cana-2747	195	1	in	in	ADP
cana-2747	195	2	deep	deep	ADJ
cana-2747	195	3	learning	learning	NOUN
cana-2747	195	4	training	training	NOUN
cana-2747	195	5	,	,	PUNCT
cana-2747	195	6	the	the	DET
cana-2747	195	7	categorical	categorical	ADJ
cana-2747	195	8	cross	cross	ADJ
cana-2747	195	9	-	-	ADJ
cana-2747	195	10	entropy	entropy	ADJ
cana-2747	195	11	loss	loss	NOUN
cana-2747	195	12	function	function	NOUN
cana-2747	195	13	is	be	AUX
cana-2747	195	14	used	use	VERB
cana-2747	195	15	to	to	PART
cana-2747	195	16	quantify	quantify	VERB
cana-2747	195	17	the	the	DET
cana-2747	195	18	difference	difference	NOUN
cana-2747	195	19	between	between	ADP
cana-2747	195	20	the	the	DET
cana-2747	195	21	predicted	predict	VERB
cana-2747	195	22	class	class	NOUN
cana-2747	195	23	probabilities	probability	NOUN
cana-2747	195	24	and	and	CCONJ
cana-2747	195	25	the	the	DET
cana-2747	195	26	actual	actual	ADJ
cana-2747	195	27	labels	label	NOUN
cana-2747	195	28	.	.	PUNCT
cana-2747	196	1	this	this	DET
cana-2747	196	2	loss	loss	NOUN
cana-2747	196	3	guides	guide	VERB
cana-2747	196	4	the	the	DET
cana-2747	196	5	optimization	optimization	NOUN
cana-2747	196	6	process	process	NOUN
cana-2747	196	7	,	,	PUNCT
cana-2747	196	8	adjusting	adjust	VERB
cana-2747	196	9	the	the	DET
cana-2747	196	10	model	model	NOUN
cana-2747	196	11	parameters	parameter	NOUN
cana-2747	196	12	to	to	PART
cana-2747	196	13	minimize	minimize	VERB
cana-2747	196	14	the	the	DET
cana-2747	196	15	discrepancy	discrepancy	NOUN
cana-2747	196	16	and	and	CCONJ
cana-2747	196	17	improve	improve	VERB
cana-2747	196	18	classification	classification	NOUN
cana-2747	196	19	accuracy	accuracy	NOUN
cana-2747	196	20	.	.	PUNCT
cana-2747	197	1	during	during	ADP
cana-2747	197	2	testing	testing	NOUN
cana-2747	197	3	,	,	PUNCT
cana-2747	197	4	the	the	DET
cana-2747	197	5	categorical	categorical	ADJ
cana-2747	197	6	cross	cross	ADJ
cana-2747	197	7	-	-	ADJ
cana-2747	197	8	entropy	entropy	ADJ
cana-2747	197	9	loss	loss	NOUN
cana-2747	197	10	function	function	NOUN
cana-2747	197	11	is	be	AUX
cana-2747	197	12	also	also	ADV
cana-2747	197	13	applied	apply	VERB
cana-2747	197	14	to	to	PART
cana-2747	197	15	assess	assess	VERB
cana-2747	197	16	the	the	DET
cana-2747	197	17	model	model	NOUN
cana-2747	197	18	's	's	PART
cana-2747	197	19	performance	performance	NOUN
cana-2747	197	20	on	on	ADP
cana-2747	197	21	unseen	unseen	ADJ
cana-2747	197	22	data	datum	NOUN
cana-2747	197	23	.	.	PUNCT
cana-2747	198	1	by	by	ADP
cana-2747	198	2	comparing	compare	VERB
cana-2747	198	3	predicted	predict	VERB
cana-2747	198	4	probabilities	probability	NOUN
cana-2747	198	5	to	to	ADP
cana-2747	198	6	the	the	DET
cana-2747	198	7	actual	actual	ADJ
cana-2747	198	8	labels	label	NOUN
cana-2747	198	9	,	,	PUNCT
cana-2747	198	10	it	it	PRON
cana-2747	198	11	measures	measure	VERB
cana-2747	198	12	the	the	DET
cana-2747	198	13	model	model	NOUN
cana-2747	198	14	's	's	PART
cana-2747	198	15	ability	ability	NOUN
cana-2747	198	16	to	to	PART
cana-2747	198	17	generalize	generalize	VERB
cana-2747	198	18	and	and	CCONJ
cana-2747	198	19	make	make	VERB
cana-2747	198	20	accurate	accurate	ADJ
cana-2747	198	21	predictions	prediction	NOUN
cana-2747	198	22	beyond	beyond	ADP
cana-2747	198	23	the	the	DET
cana-2747	198	24	training	training	NOUN
cana-2747	198	25	set	set	NOUN
cana-2747	198	26	.	.	PUNCT
cana-2747	199	1	in	in	ADP
cana-2747	199	2	both	both	DET
cana-2747	199	3	training	training	NOUN
cana-2747	199	4	and	and	CCONJ
cana-2747	199	5	testing	testing	NOUN
cana-2747	199	6	,	,	PUNCT
cana-2747	199	7	this	this	DET
cana-2747	199	8	loss	loss	NOUN
cana-2747	199	9	function	function	NOUN
cana-2747	199	10	plays	play	VERB
cana-2747	199	11	a	a	DET
cana-2747	199	12	vital	vital	ADJ
cana-2747	199	13	role	role	NOUN
cana-2747	199	14	in	in	ADP
cana-2747	199	15	evaluating	evaluate	VERB
cana-2747	199	16	the	the	DET
cana-2747	199	17	model	model	NOUN
cana-2747	199	18	's	's	PART
cana-2747	199	19	effectiveness	effectiveness	NOUN
cana-2747	199	20	and	and	CCONJ
cana-2747	199	21	generalization	generalization	NOUN
cana-2747	199	22	capabilities	capability	NOUN
cana-2747	199	23	in	in	ADP
cana-2747	199	24	classification	classification	NOUN
cana-2747	199	25	tasks	task	NOUN
cana-2747	199	26	,	,	PUNCT
cana-2747	199	27	as	as	SCONJ
cana-2747	199	28	illustrated	illustrate	VERB
cana-2747	199	29	in	in	ADP
cana-2747	199	30	figure	figure	NOUN
cana-2747	199	31	5	5	NUM
cana-2747	199	32	.	.	PUNCT
cana-2747	199	33	fig	fig	NOUN
cana-2747	199	34	.	.	PUNCT
cana-2747	200	1	5	5	X
cana-2747	200	2	.	.	X
cana-2747	200	3	training	training	NOUN
cana-2747	200	4	loss	loss	NOUN
cana-2747	200	5	and	and	CCONJ
cana-2747	200	6	testing	testing	NOUN
cana-2747	200	7	loss	loss	NOUN
cana-2747	200	8	against	against	ADP
cana-2747	200	9	the	the	DET
cana-2747	200	10	number	number	NOUN
cana-2747	200	11	of	of	ADP
cana-2747	200	12	epochs	epoch	NOUN
cana-2747	200	13	6	6	NUM
cana-2747	200	14	.	.	PUNCT
cana-2747	201	1	comparative	comparative	ADJ
cana-2747	201	2	performance	performance	NOUN
cana-2747	201	3	analysis	analysis	NOUN
cana-2747	201	4	in	in	ADP
cana-2747	201	5	this	this	DET
cana-2747	201	6	section	section	NOUN
cana-2747	201	7	,	,	PUNCT
cana-2747	201	8	a	a	DET
cana-2747	201	9	comparative	comparative	ADJ
cana-2747	201	10	analysis	analysis	NOUN
cana-2747	201	11	has	have	AUX
cana-2747	201	12	been	be	AUX
cana-2747	201	13	conducted	conduct	VERB
cana-2747	201	14	with	with	ADP
cana-2747	201	15	a	a	DET
cana-2747	201	16	previous	previous	ADJ
cana-2747	201	17	study	study	NOUN
cana-2747	201	18	[	[	X
cana-2747	201	19	14	14	NUM
cana-2747	201	20	]	]	PUNCT
cana-2747	201	21	that	that	SCONJ
cana-2747	201	22	utilized	utilize	VERB
cana-2747	201	23	deep	deep	ADJ
cana-2747	201	24	learning	learning	NOUN
cana-2747	201	25	for	for	ADP
cana-2747	201	26	subject	subject	ADJ
cana-2747	201	27	classification	classification	NOUN
cana-2747	201	28	.	.	PUNCT
cana-2747	202	1	the	the	DET
cana-2747	202	2	prior	prior	ADJ
cana-2747	202	3	method	method	NOUN
cana-2747	202	4	employed	employ	VERB
cana-2747	202	5	two	two	NUM
cana-2747	202	6	deep	deep	ADJ
cana-2747	202	7	learning	learning	NOUN
cana-2747	202	8	models	model	NOUN
cana-2747	202	9	,	,	PUNCT
cana-2747	202	10	cnn	cnn	PROPN
cana-2747	202	11	-	-	PUNCT
cana-2747	202	12	gru	gru	PROPN
cana-2747	202	13	and	and	CCONJ
cana-2747	202	14	cnn	cnn	PROPN
cana-2747	202	15	-	-	PUNCT
cana-2747	202	16	lstm	lstm	PROPN
cana-2747	202	17	,	,	PUNCT
cana-2747	202	18	achieving	achieve	VERB
cana-2747	202	19	an	an	DET
cana-2747	202	20	impressive	impressive	ADJ
cana-2747	202	21	correct	correct	ADJ
cana-2747	202	22	recognition	recognition	NOUN
cana-2747	202	23	rate	rate	NOUN
cana-2747	202	24	of	of	ADP
cana-2747	202	25	99.17	99.17	NUM
cana-2747	202	26	%	%	NOUN
cana-2747	202	27	by	by	ADP
cana-2747	202	28	focusing	focus	VERB
cana-2747	202	29	on	on	ADP
cana-2747	202	30	brain	brain	NOUN
cana-2747	202	31	signals	signal	NOUN
cana-2747	202	32	from	from	ADP
cana-2747	202	33	the	the	DET
cana-2747	202	34	frontal	frontal	ADJ
cana-2747	202	35	region	region	NOUN
cana-2747	202	36	.	.	PUNCT
cana-2747	203	1	even	even	ADV
cana-2747	203	2	with	with	ADP
cana-2747	203	3	a	a	DET
cana-2747	203	4	reduction	reduction	NOUN
cana-2747	203	5	in	in	ADP
cana-2747	203	6	eeg	eeg	NOUN
cana-2747	203	7	sensors	sensor	NOUN
cana-2747	203	8	from	from	ADP
cana-2747	203	9	32	32	NUM
cana-2747	203	10	to	to	PART
cana-2747	203	11	5	5	NUM
cana-2747	203	12	for	for	ADP
cana-2747	203	13	practicality	practicality	NOUN
cana-2747	203	14	,	,	PUNCT
cana-2747	203	15	the	the	DET
cana-2747	203	16	approach	approach	NOUN
cana-2747	203	17	maintained	maintain	VERB
cana-2747	203	18	strong	strong	ADJ
cana-2747	203	19	performance	performance	NOUN
cana-2747	203	20	.	.	PUNCT
cana-2747	204	1	in	in	ADP
cana-2747	204	2	contrast	contrast	NOUN
cana-2747	204	3	,	,	PUNCT
cana-2747	204	4	the	the	DET
cana-2747	204	5	current	current	ADJ
cana-2747	204	6	work	work	NOUN
cana-2747	204	7	achieved	achieve	VERB
cana-2747	204	8	a	a	DET
cana-2747	204	9	maximum	maximum	ADJ
cana-2747	204	10	accuracy	accuracy	NOUN
cana-2747	204	11	of	of	ADP
cana-2747	204	12	99.81	99.81	NUM
cana-2747	204	13	%	%	NOUN
cana-2747	204	14	by	by	ADP
cana-2747	204	15	integrating	integrate	VERB
cana-2747	204	16	eeg	eeg	NOUN
cana-2747	204	17	brain	brain	NOUN
cana-2747	204	18	wave	wave	NOUN
cana-2747	204	19	data	datum	NOUN
cana-2747	204	20	with	with	ADP
cana-2747	204	21	a	a	DET
cana-2747	204	22	facial	facial	ADJ
cana-2747	204	23	multimodal	multimodal	NOUN
cana-2747	204	24	recognition	recognition	NOUN
cana-2747	204	25	system	system	NOUN
cana-2747	204	26	,	,	PUNCT
cana-2747	204	27	further	far	ADV
cana-2747	204	28	enhancing	enhance	VERB
cana-2747	204	29	identification	identification	NOUN
cana-2747	204	30	accuracy	accuracy	NOUN
cana-2747	204	31	.	.	PUNCT
cana-2747	205	1	7	7	X
cana-2747	205	2	.	.	NUM
cana-2747	205	3	results	result	NOUN
cana-2747	205	4	and	and	CCONJ
cana-2747	205	5	discussion	discussion	NOUN
cana-2747	205	6	:	:	PUNCT
cana-2747	205	7	the	the	PRON
cana-2747	205	8	electroencephalogram	electroencephalogram	NOUN
cana-2747	205	9	(	(	PUNCT
cana-2747	205	10	eeg	eeg	NOUN
cana-2747	205	11	)	)	PUNCT
cana-2747	205	12	and	and	CCONJ
cana-2747	205	13	peripheral	peripheral	ADJ
cana-2747	205	14	physiological	physiological	ADJ
cana-2747	205	15	data	datum	NOUN
cana-2747	205	16	of	of	ADP
cana-2747	205	17	32	32	NUM
cana-2747	205	18	participants	participant	NOUN
cana-2747	205	19	were	be	AUX
cana-2747	205	20	captured	capture	VERB
cana-2747	205	21	while	while	SCONJ
cana-2747	205	22	they	they	PRON
cana-2747	205	23	watched	watch	VERB
cana-2747	205	24	40	40	NUM
cana-2747	205	25	one	one	NUM
cana-2747	205	26	-	-	PUNCT
cana-2747	205	27	minute	minute	NOUN
cana-2747	205	28	clips	clip	NOUN
cana-2747	205	29	of	of	ADP
cana-2747	205	30	music	music	NOUN
cana-2747	205	31	videos	video	NOUN
cana-2747	205	32	.	.	PUNCT
cana-2747	206	1	this	this	DET
cana-2747	206	2	dataset	dataset	NOUN
cana-2747	206	3	,	,	PUNCT
cana-2747	206	4	which	which	PRON
cana-2747	206	5	is	be	AUX
cana-2747	206	6	publicly	publicly	ADV
cana-2747	206	7	accessible	accessible	ADJ
cana-2747	206	8	,	,	PUNCT
cana-2747	206	9	is	be	AUX
cana-2747	206	10	communications	communication	NOUN
cana-2747	206	11	on	on	ADP
cana-2747	206	12	applied	apply	VERB
cana-2747	206	13	nonlinear	nonlinear	ADJ
cana-2747	206	14	analysis	analysis	NOUN
cana-2747	206	15	issn	issn	NOUN
cana-2747	206	16	:	:	PUNCT
cana-2747	206	17	1074	1074	NUM
cana-2747	206	18	-	-	PUNCT
cana-2747	206	19	133x	133x	NUM
cana-2747	206	20	vol	vol	NOUN
cana-2747	206	21	32	32	NUM
cana-2747	206	22	no	no	NOUN
cana-2747	206	23	.	.	PUNCT
cana-2747	207	1	4s	4s	NUM
cana-2747	207	2	(	(	PUNCT
cana-2747	207	3	2025	2025	NUM
cana-2747	207	4	)	)	PUNCT
cana-2747	207	5	179	179	NUM
cana-2747	207	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	207	7	encouraged	encourage	VERB
cana-2747	207	8	for	for	ADP
cana-2747	207	9	use	use	NOUN
cana-2747	207	10	by	by	ADP
cana-2747	207	11	other	other	ADJ
cana-2747	207	12	researchers	researcher	NOUN
cana-2747	207	13	to	to	PART
cana-2747	207	14	test	test	VERB
cana-2747	207	15	their	their	PRON
cana-2747	207	16	affective	affective	ADJ
cana-2747	207	17	state	state	NOUN
cana-2747	207	18	estimation	estimation	NOUN
cana-2747	207	19	methods	method	NOUN
cana-2747	207	20	..	..	PUNCT
cana-2747	207	21	for	for	ADP
cana-2747	207	22	each	each	DET
cana-2747	207	23	trial	trial	NOUN
cana-2747	207	24	,	,	PUNCT
cana-2747	207	25	the	the	DET
cana-2747	207	26	duration	duration	NOUN
cana-2747	207	27	is	be	AUX
cana-2747	207	28	63	63	NUM
cana-2747	207	29	seconds	second	NOUN
cana-2747	207	30	(	(	PUNCT
cana-2747	207	31	60	60	NUM
cana-2747	207	32	seconds	second	NOUN
cana-2747	207	33	trial	trial	NOUN
cana-2747	207	34	+	+	CCONJ
cana-2747	207	35	3	3	NUM
cana-2747	207	36	seconds	second	NOUN
cana-2747	207	37	baseline	baseline	NOUN
cana-2747	207	38	)	)	PUNCT
cana-2747	207	39	.	.	PUNCT
cana-2747	208	1	since	since	SCONJ
cana-2747	208	2	the	the	DET
cana-2747	208	3	data	data	NOUN
cana-2747	208	4	is	be	AUX
cana-2747	208	5	recorded	record	VERB
cana-2747	208	6	at	at	ADP
cana-2747	208	7	128hz	128hz	NOUN
cana-2747	208	8	,	,	PUNCT
cana-2747	208	9	there	there	PRON
cana-2747	208	10	are	be	VERB
cana-2747	208	11	128	128	NUM
cana-2747	208	12	data	datum	NOUN
cana-2747	208	13	points	point	NOUN
cana-2747	208	14	(	(	PUNCT
cana-2747	208	15	samples	sample	NOUN
cana-2747	208	16	)	)	PUNCT
cana-2747	208	17	for	for	ADP
cana-2747	208	18	each	each	DET
cana-2747	208	19	second	second	NOUN
cana-2747	208	20	of	of	ADP
cana-2747	208	21	recording	recording	NOUN
cana-2747	208	22	.	.	PUNCT
cana-2747	209	1	therefore	therefore	ADV
cana-2747	209	2	,	,	PUNCT
cana-2747	209	3	for	for	ADP
cana-2747	209	4	each	each	DET
cana-2747	209	5	trial	trial	NOUN
cana-2747	209	6	,	,	PUNCT
cana-2747	209	7	there	there	PRON
cana-2747	209	8	are	be	VERB
cana-2747	209	9	63	63	NUM
cana-2747	209	10	seconds	second	NOUN
cana-2747	209	11	x	x	NOUN
cana-2747	209	12	128hz	128hz	ADJ
cana-2747	209	13	=	=	SYM
cana-2747	209	14	8064	8064	NUM
cana-2747	209	15	samples	sample	NOUN
cana-2747	209	16	.	.	PUNCT
cana-2747	210	1	to	to	PART
cana-2747	210	2	focus	focus	VERB
cana-2747	210	3	on	on	ADP
cana-2747	210	4	identifying	identify	VERB
cana-2747	210	5	individuals	individual	NOUN
cana-2747	210	6	using	use	VERB
cana-2747	210	7	short	short	ADJ
cana-2747	210	8	eeg	eeg	NOUN
cana-2747	210	9	segments	segment	NOUN
cana-2747	210	10	,	,	PUNCT
cana-2747	210	11	we	we	PRON
cana-2747	210	12	used	use	VERB
cana-2747	210	13	10	10	NUM
cana-2747	210	14	-	-	PUNCT
cana-2747	210	15	second	second	NOUN
cana-2747	210	16	subsamples	subsample	NOUN
cana-2747	210	17	.	.	PUNCT
cana-2747	211	1	each	each	DET
cana-2747	211	2	60	60	NUM
cana-2747	211	3	-	-	PUNCT
cana-2747	211	4	second	second	NOUN
cana-2747	211	5	eeg	eeg	NOUN
cana-2747	211	6	trial	trial	NOUN
cana-2747	211	7	in	in	ADP
cana-2747	211	8	the	the	DET
cana-2747	211	9	deap	deap	ADJ
cana-2747	211	10	dataset	dataset	NOUN
cana-2747	211	11	was	be	AUX
cana-2747	211	12	divided	divide	VERB
cana-2747	211	13	into	into	ADP
cana-2747	211	14	six	six	NUM
cana-2747	211	15	subsamples	subsample	NOUN
cana-2747	211	16	,	,	PUNCT
cana-2747	211	17	giving	give	VERB
cana-2747	211	18	us	we	PRON
cana-2747	211	19	30	30	NUM
cana-2747	211	20	subsamples	subsample	NOUN
cana-2747	211	21	(	(	PUNCT
cana-2747	211	22	6	6	NUM
cana-2747	211	23	subsamples	subsample	NOUN
cana-2747	211	24	×	×	NOUN
cana-2747	211	25	5	5	NUM
cana-2747	211	26	trials	trial	NOUN
cana-2747	211	27	)	)	PUNCT
cana-2747	211	28	per	per	ADP
cana-2747	211	29	participant	participant	NOUN
cana-2747	211	30	for	for	ADP
cana-2747	211	31	each	each	DET
cana-2747	211	32	affective	affective	ADJ
cana-2747	211	33	state	state	NOUN
cana-2747	211	34	.	.	PUNCT
cana-2747	212	1	in	in	ADP
cana-2747	212	2	these	these	DET
cana-2747	212	3	experiments	experiment	NOUN
cana-2747	212	4	,	,	PUNCT
cana-2747	212	5	the	the	DET
cana-2747	212	6	labels	label	NOUN
cana-2747	212	7	represent	represent	VERB
cana-2747	212	8	the	the	DET
cana-2747	212	9	participants	participant	NOUN
cana-2747	212	10	'	'	PART
cana-2747	212	11	unique	unique	ADJ
cana-2747	212	12	ids	id	NOUN
cana-2747	212	13	.	.	PUNCT
cana-2747	213	1	the	the	DET
cana-2747	213	2	data	datum	NOUN
cana-2747	213	3	and	and	CCONJ
cana-2747	213	4	labels	label	NOUN
cana-2747	213	5	are	be	AUX
cana-2747	213	6	structured	structure	VERB
cana-2747	213	7	as	as	SCONJ
cana-2747	213	8	follows	follow	VERB
cana-2747	213	9	:	:	PUNCT
cana-2747	213	10	data	datum	NOUN
cana-2747	213	11	:	:	PUNCT
cana-2747	213	12	number	number	NOUN
cana-2747	213	13	of	of	ADP
cana-2747	213	14	participants	participant	NOUN
cana-2747	213	15	×	×	VERB
cana-2747	213	16	30	30	NUM
cana-2747	213	17	subsamples	subsample	NOUN
cana-2747	213	18	×	×	NOUN
cana-2747	213	19	1280	1280	NUM
cana-2747	213	20	eeg	eeg	NOUN
cana-2747	213	21	data	datum	NOUN
cana-2747	213	22	points	point	NOUN
cana-2747	213	23	(	(	PUNCT
cana-2747	213	24	10	10	NUM
cana-2747	213	25	seconds	second	NOUN
cana-2747	213	26	with	with	ADP
cana-2747	213	27	128	128	NUM
cana-2747	213	28	hz	hz	VERB
cana-2747	213	29	sampling	sample	VERB
cana-2747	213	30	rate	rate	NOUN
cana-2747	213	31	)	)	PUNCT
cana-2747	213	32	label	label	NOUN
cana-2747	213	33	:	:	PUNCT
cana-2747	213	34	number	number	NOUN
cana-2747	213	35	of	of	ADP
cana-2747	213	36	participants	participant	NOUN
cana-2747	213	37	×	×	VERB
cana-2747	213	38	30	30	NUM
cana-2747	213	39	subsamples	subsample	NOUN
cana-2747	213	40	×	×	PROPN
cana-2747	213	41	1(id	1(id	NUM
cana-2747	213	42	)	)	PUNCT
cana-2747	213	43	.	.	PUNCT
cana-2747	214	1	the	the	DET
cana-2747	214	2	analysis	analysis	NOUN
cana-2747	214	3	aims	aim	VERB
cana-2747	214	4	to	to	PART
cana-2747	214	5	identify	identify	VERB
cana-2747	214	6	a	a	DET
cana-2747	214	7	person	person	NOUN
cana-2747	214	8	from	from	ADP
cana-2747	214	9	the	the	DET
cana-2747	214	10	short	short	ADJ
cana-2747	214	11	-	-	PUNCT
cana-2747	214	12	length	length	NOUN
cana-2747	214	13	eeg	eeg	NOUN
cana-2747	214	14	segments	segment	NOUN
cana-2747	214	15	(	(	PUNCT
cana-2747	214	16	10	10	NUM
cana-2747	214	17	-	-	PUNCT
cana-2747	214	18	second	second	ADJ
cana-2747	214	19	subsamples	subsample	NOUN
cana-2747	214	20	)	)	PUNCT
cana-2747	214	21	.	.	PUNCT
cana-2747	215	1	the	the	DET
cana-2747	215	2	labels	label	NOUN
cana-2747	215	3	used	use	VERB
cana-2747	215	4	for	for	ADP
cana-2747	215	5	this	this	DET
cana-2747	215	6	identification	identification	NOUN
cana-2747	215	7	are	be	AUX
cana-2747	215	8	the	the	DET
cana-2747	215	9	participant	participant	NOUN
cana-2747	215	10	's	's	PART
cana-2747	215	11	i	i	PROPN
cana-2747	215	12	d	d	PROPN
cana-2747	215	13	,	,	PUNCT
cana-2747	215	14	which	which	PRON
cana-2747	215	15	is	be	AUX
cana-2747	215	16	a	a	DET
cana-2747	215	17	unique	unique	ADJ
cana-2747	215	18	identifier	identifier	NOUN
cana-2747	215	19	for	for	ADP
cana-2747	215	20	each	each	DET
cana-2747	215	21	participant	participant	NOUN
cana-2747	215	22	.	.	PUNCT
cana-2747	216	1	for	for	ADP
cana-2747	216	2	each	each	DET
cana-2747	216	3	10	10	NUM
cana-2747	216	4	-	-	PUNCT
cana-2747	216	5	second	second	ADJ
cana-2747	216	6	segment	segment	NOUN
cana-2747	216	7	(	(	PUNCT
cana-2747	216	8	sample	sample	NOUN
cana-2747	216	9	)	)	PUNCT
cana-2747	216	10	in	in	ADP
cana-2747	216	11	the	the	DET
cana-2747	216	12	5	5	NUM
cana-2747	216	13	-	-	PUNCT
cana-2747	216	14	dimensional	dimensional	ADJ
cana-2747	216	15	array	array	NOUN
cana-2747	216	16	.	.	PUNCT
cana-2747	217	1	for	for	ADP
cana-2747	217	2	each	each	DET
cana-2747	217	3	channel	channel	NOUN
cana-2747	217	4	(	(	PUNCT
cana-2747	217	5	32	32	NUM
cana-2747	217	6	channels	channel	NOUN
cana-2747	217	7	)	)	PUNCT
cana-2747	217	8	,	,	PUNCT
cana-2747	217	9	interpolate	interpolate	VERB
cana-2747	217	10	the	the	DET
cana-2747	217	11	data	data	NOUN
cana-2747	217	12	points	point	NOUN
cana-2747	217	13	onto	onto	ADP
cana-2747	217	14	the	the	DET
cana-2747	217	15	9x9	9x9	NUM
cana-2747	217	16	mesh	mesh	NOUN
cana-2747	217	17	grid	grid	NOUN
cana-2747	217	18	.	.	PUNCT
cana-2747	218	1	this	this	PRON
cana-2747	218	2	can	can	AUX
cana-2747	218	3	be	be	AUX
cana-2747	218	4	done	do	VERB
cana-2747	218	5	using	use	VERB
cana-2747	218	6	various	various	ADJ
cana-2747	218	7	interpolation	interpolation	NOUN
cana-2747	218	8	techniques	technique	NOUN
cana-2747	218	9	such	such	ADJ
cana-2747	218	10	as	as	ADP
cana-2747	218	11	bilinear	bilinear	NOUN
cana-2747	218	12	,	,	PUNCT
cana-2747	218	13	bicubic	bicubic	NOUN
cana-2747	218	14	,	,	PUNCT
cana-2747	218	15	or	or	CCONJ
cana-2747	218	16	spline	spline	NOUN
cana-2747	218	17	interpolation	interpolation	NOUN
cana-2747	218	18	.	.	PUNCT
cana-2747	219	1	the	the	DET
cana-2747	219	2	interpolated	interpolate	VERB
cana-2747	219	3	values	value	NOUN
cana-2747	219	4	for	for	ADP
cana-2747	219	5	each	each	DET
cana-2747	219	6	channel	channel	NOUN
cana-2747	219	7	will	will	AUX
cana-2747	219	8	be	be	AUX
cana-2747	219	9	represented	represent	VERB
cana-2747	219	10	on	on	ADP
cana-2747	219	11	the	the	DET
cana-2747	219	12	9x9	9x9	NUM
cana-2747	219	13	grid	grid	NOUN
cana-2747	219	14	.	.	PUNCT
cana-2747	220	1	this	this	DET
cana-2747	220	2	mesh	mesh	NOUN
cana-2747	220	3	representation	representation	NOUN
cana-2747	220	4	allows	allow	VERB
cana-2747	220	5	you	you	PRON
cana-2747	220	6	to	to	PART
cana-2747	220	7	observe	observe	VERB
cana-2747	220	8	and	and	CCONJ
cana-2747	220	9	analyze	analyze	VERB
cana-2747	220	10	the	the	DET
cana-2747	220	11	spatial	spatial	ADJ
cana-2747	220	12	patterns	pattern	NOUN
cana-2747	220	13	of	of	ADP
cana-2747	220	14	eeg	eeg	PROPN
cana-2747	220	15	data	datum	NOUN
cana-2747	220	16	across	across	ADP
cana-2747	220	17	the	the	DET
cana-2747	220	18	9x9	9x9	NUM
cana-2747	220	19	grid	grid	NOUN
cana-2747	220	20	,	,	PUNCT
cana-2747	220	21	which	which	PRON
cana-2747	220	22	could	could	AUX
cana-2747	220	23	be	be	AUX
cana-2747	220	24	helpful	helpful	ADJ
cana-2747	220	25	for	for	ADP
cana-2747	220	26	further	further	ADJ
cana-2747	220	27	analysis	analysis	NOUN
cana-2747	220	28	,	,	PUNCT
cana-2747	220	29	visualization	visualization	NOUN
cana-2747	220	30	,	,	PUNCT
cana-2747	220	31	or	or	CCONJ
cana-2747	220	32	feature	feature	NOUN
cana-2747	220	33	extraction	extraction	NOUN
cana-2747	220	34	.	.	PUNCT
cana-2747	221	1	performance	performance	NOUN
cana-2747	221	2	is	be	AUX
cana-2747	221	3	evaluated	evaluate	VERB
cana-2747	221	4	using	use	VERB
cana-2747	221	5	three	three	NUM
cana-2747	221	6	statistical	statistical	ADJ
cana-2747	221	7	metrics	metric	NOUN
cana-2747	221	8	:	:	PUNCT
cana-2747	221	9	classification	classification	NOUN
cana-2747	221	10	accuracy	accuracy	NOUN
cana-2747	221	11	,	,	PUNCT
cana-2747	221	12	precision	precision	NOUN
cana-2747	221	13	,	,	PUNCT
cana-2747	221	14	and	and	CCONJ
cana-2747	221	15	recall	recall	NOUN
cana-2747	221	16	.	.	PUNCT
cana-2747	222	1	a	a	DET
cana-2747	222	2	confusion	confusion	NOUN
cana-2747	222	3	matrix	matrix	NOUN
cana-2747	222	4	(	(	PUNCT
cana-2747	222	5	shown	show	VERB
cana-2747	222	6	in	in	ADP
cana-2747	222	7	figure	figure	NOUN
cana-2747	222	8	6	6	NUM
cana-2747	222	9	)	)	PUNCT
cana-2747	222	10	is	be	AUX
cana-2747	222	11	used	use	VERB
cana-2747	222	12	to	to	PART
cana-2747	222	13	determine	determine	VERB
cana-2747	222	14	true	true	ADJ
cana-2747	222	15	positives	positive	NOUN
cana-2747	222	16	(	(	PUNCT
cana-2747	222	17	tp	tp	NOUN
cana-2747	222	18	)	)	PUNCT
cana-2747	222	19	,	,	PUNCT
cana-2747	222	20	true	true	ADJ
cana-2747	222	21	negatives	negative	NOUN
cana-2747	222	22	(	(	PUNCT
cana-2747	222	23	tn	tn	NOUN
cana-2747	222	24	)	)	PUNCT
cana-2747	222	25	,	,	PUNCT
cana-2747	222	26	false	false	ADJ
cana-2747	222	27	positives	positive	NOUN
cana-2747	222	28	(	(	PUNCT
cana-2747	222	29	fp	fp	NOUN
cana-2747	222	30	)	)	PUNCT
cana-2747	222	31	,	,	PUNCT
cana-2747	222	32	and	and	CCONJ
cana-2747	222	33	false	false	ADJ
cana-2747	222	34	negatives	negative	NOUN
cana-2747	222	35	(	(	PUNCT
cana-2747	222	36	fn	fn	NOUN
cana-2747	222	37	)	)	PUNCT
cana-2747	222	38	.	.	PUNCT
cana-2747	223	1	additionally	additionally	ADV
cana-2747	223	2	,	,	PUNCT
cana-2747	223	3	categorical	categorical	ADJ
cana-2747	223	4	cross	cross	NOUN
cana-2747	223	5	-	-	NOUN
cana-2747	223	6	entropy	entropy	ADJ
cana-2747	223	7	,	,	PUNCT
cana-2747	223	8	precision	precision	NOUN
cana-2747	223	9	,	,	PUNCT
cana-2747	223	10	and	and	CCONJ
cana-2747	223	11	recall	recall	NOUN
cana-2747	223	12	are	be	AUX
cana-2747	223	13	plotted	plot	VERB
cana-2747	223	14	against	against	ADP
cana-2747	223	15	the	the	DET
cana-2747	223	16	number	number	NOUN
cana-2747	223	17	of	of	ADP
cana-2747	223	18	epochs	epoch	NOUN
cana-2747	223	19	for	for	ADP
cana-2747	223	20	both	both	DET
cana-2747	223	21	training	training	NOUN
cana-2747	223	22	and	and	CCONJ
cana-2747	223	23	testing	testing	NOUN
cana-2747	223	24	loss	loss	NOUN
cana-2747	223	25	(	(	PUNCT
cana-2747	223	26	as	as	SCONJ
cana-2747	223	27	seen	see	VERB
cana-2747	223	28	in	in	ADP
cana-2747	223	29	figure	figure	NOUN
cana-2747	223	30	5	5	NUM
cana-2747	223	31	)	)	PUNCT
cana-2747	223	32	.	.	PUNCT
cana-2747	224	1	table	table	NOUN
cana-2747	224	2	1	1	NUM
cana-2747	224	3	summarizes	summarize	NOUN
cana-2747	224	4	the	the	DET
cana-2747	224	5	classification	classification	NOUN
cana-2747	224	6	results	result	NOUN
cana-2747	224	7	.	.	PUNCT
cana-2747	225	1	the	the	DET
cana-2747	225	2	classification	classification	NOUN
cana-2747	225	3	report	report	NOUN
cana-2747	225	4	provides	provide	VERB
cana-2747	225	5	a	a	DET
cana-2747	225	6	detailed	detailed	ADJ
cana-2747	225	7	summary	summary	NOUN
cana-2747	225	8	of	of	ADP
cana-2747	225	9	precision	precision	NOUN
cana-2747	225	10	,	,	PUNCT
cana-2747	225	11	recall	recall	NOUN
cana-2747	225	12	,	,	PUNCT
cana-2747	225	13	and	and	CCONJ
cana-2747	225	14	f1	f1	NOUN
cana-2747	225	15	score	score	NOUN
cana-2747	225	16	for	for	ADP
cana-2747	225	17	each	each	DET
cana-2747	225	18	class	class	NOUN
cana-2747	225	19	,	,	PUNCT
cana-2747	225	20	while	while	SCONJ
cana-2747	225	21	the	the	DET
cana-2747	225	22	last	last	ADJ
cana-2747	225	23	column	column	NOUN
cana-2747	225	24	,	,	PUNCT
cana-2747	225	25	"	"	PUNCT
cana-2747	225	26	support	support	NOUN
cana-2747	225	27	,	,	PUNCT
cana-2747	225	28	"	"	PUNCT
cana-2747	225	29	indicates	indicate	VERB
cana-2747	225	30	the	the	DET
cana-2747	225	31	number	number	NOUN
cana-2747	225	32	of	of	ADP
cana-2747	225	33	samples	sample	NOUN
cana-2747	225	34	for	for	ADP
cana-2747	225	35	each	each	DET
cana-2747	225	36	class	class	NOUN
cana-2747	225	37	.	.	PUNCT
cana-2747	226	1	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
cana-2747	226	2	=	=	SYM
cana-2747	226	3	𝑇𝑁	𝑇𝑁	PROPN
cana-2747	226	4	+	+	CCONJ
cana-2747	226	5	𝑇𝑃	𝑇𝑃	PROPN
cana-2747	226	6	𝑇𝑁	𝑇𝑁	PROPN
cana-2747	226	7	+	+	CCONJ
cana-2747	226	8	𝑇𝑃	𝑇𝑃	NOUN
cana-2747	226	9	+	+	CCONJ
cana-2747	226	10	𝐹𝑁	𝐹𝑁	PROPN
cana-2747	227	1	+	+	CCONJ
cana-2747	227	2	𝐹𝑃	𝐹𝑃	PROPN
cana-2747	227	3	∗	∗	NOUN
cana-2747	227	4	100	100	NUM
cana-2747	227	5	(	(	PUNCT
cana-2747	227	6	7	7	NUM
cana-2747	227	7	)	)	PUNCT
cana-2747	227	8	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-2747	227	9	=	=	SYM
cana-2747	227	10	𝑇𝑃	𝑇𝑃	PROPN
cana-2747	227	11	𝑇𝑃	𝑇𝑃	PROPN
cana-2747	227	12	+	+	CCONJ
cana-2747	227	13	𝐹𝑃	𝐹𝑃	PROPN
cana-2747	227	14	∗	∗	NOUN
cana-2747	227	15	100	100	NUM
cana-2747	227	16	(	(	PUNCT
cana-2747	227	17	8)	8)	NUM
cana-2747	227	18	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-2747	227	19	=	=	SYM
cana-2747	227	20	𝑇𝑃	𝑇𝑃	PROPN
cana-2747	227	21	𝑇𝑃	𝑇𝑃	PROPN
cana-2747	227	22	+	+	CCONJ
cana-2747	227	23	𝐹𝑁	𝐹𝑁	PROPN
cana-2747	227	24	∗	∗	NOUN
cana-2747	227	25	100	100	NUM
cana-2747	227	26	(	(	PUNCT
cana-2747	227	27	9	9	NUM
cana-2747	227	28	)	)	PUNCT
cana-2747	227	29	communications	communication	NOUN
cana-2747	227	30	on	on	ADP
cana-2747	227	31	applied	apply	VERB
cana-2747	227	32	nonlinear	nonlinear	ADJ
cana-2747	227	33	analysis	analysis	NOUN
cana-2747	227	34	issn	issn	NOUN
cana-2747	227	35	:	:	PUNCT
cana-2747	227	36	1074	1074	NUM
cana-2747	227	37	-	-	PUNCT
cana-2747	227	38	133x	133x	NUM
cana-2747	227	39	vol	vol	NOUN
cana-2747	227	40	32	32	NUM
cana-2747	227	41	no	no	NOUN
cana-2747	227	42	.	.	PUNCT
cana-2747	228	1	4s	4s	NUM
cana-2747	228	2	(	(	PUNCT
cana-2747	228	3	2025	2025	NUM
cana-2747	228	4	)	)	PUNCT
cana-2747	228	5	180	180	NUM
cana-2747	228	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2747	228	7	fig.6	fig.6	PROPN
cana-2747	228	8	.	.	PUNCT
cana-2747	229	1	confusion	confusion	NOUN
cana-2747	229	2	matrices	matrix	NOUN
cana-2747	229	3	of	of	ADP
cana-2747	229	4	the	the	DET
cana-2747	229	5	combined	combined	ADJ
cana-2747	229	6	model	model	NOUN
cana-2747	229	7	with	with	ADP
cana-2747	229	8	predicted	predict	VERB
cana-2747	229	9	label	label	NOUN
cana-2747	229	10	accuracy	accuracy	NOUN
cana-2747	229	11	table	table	NOUN
cana-2747	229	12	1	1	NUM
cana-2747	229	13	:	:	PUNCT
cana-2747	229	14	classification	classification	NOUN
cana-2747	229	15	report	report	NOUN
cana-2747	229	16	for	for	ADP
cana-2747	229	17	the	the	DET
cana-2747	229	18	feature	feature	NOUN
cana-2747	229	19	-	-	PUNCT
cana-2747	229	20	level	level	NOUN
cana-2747	229	21	fusion	fusion	NOUN
cana-2747	229	22	using	use	VERB
cana-2747	229	23	cnn	cnn	PROPN
cana-2747	229	24	-	-	PUNCT
cana-2747	229	25	lstm	lstm	ADJ
cana-2747	229	26	and	and	CCONJ
cana-2747	229	27	mobilenet	mobilenet	NOUN
cana-2747	229	28	architecture	architecture	NOUN
cana-2747	229	29	subjects	subject	NOUN
cana-2747	229	30	precision	precision	NOUN
cana-2747	229	31	recall	recall	VERB
cana-2747	229	32	f1	f1	NOUN
cana-2747	229	33	-	-	PUNCT
cana-2747	229	34	score	score	NOUN
cana-2747	229	35	support	support	NOUN
cana-2747	229	36	s01	s01	NOUN
cana-2747	229	37	0.96	0.96	NUM
cana-2747	229	38	1.00	1.00	NUM
cana-2747	229	39	0.98	0.98	NUM
cana-2747	229	40	48	48	NUM
cana-2747	229	41	s02	s02	PROPN
cana-2747	229	42	1.00	1.00	NUM
cana-2747	229	43	1.00	1.00	NUM
cana-2747	229	44	1.00	1.00	NUM
cana-2747	229	45	48	48	NUM
cana-2747	229	46	s03	s03	NOUN
cana-2747	229	47	1.00	1.00	NUM
cana-2747	229	48	1.00	1.00	NUM
cana-2747	229	49	1.00	1.00	NUM
cana-2747	229	50	48	48	NUM
cana-2747	229	51	s04	s04	NOUN
cana-2747	229	52	1.00	1.00	NUM
cana-2747	229	53	1.00	1.00	NUM
cana-2747	229	54	1.00	1.00	NUM
cana-2747	229	55	48	48	NUM
cana-2747	229	56	s05	s05	NOUN
cana-2747	229	57	1.00	1.00	NUM
cana-2747	229	58	1.00	1.00	NUM
cana-2747	229	59	1.00	1.00	NUM
cana-2747	229	60	48	48	NUM
cana-2747	229	61	s06	s06	NOUN
cana-2747	229	62	1.00	1.00	NUM
cana-2747	229	63	0.98	0.98	NUM
cana-2747	229	64	0.99	0.99	NUM
cana-2747	229	65	48	48	NUM
cana-2747	229	66	s07	s07	NOUN
cana-2747	229	67	1.00	1.00	NUM
cana-2747	229	68	1.00	1.00	NUM
cana-2747	229	69	1.00	1.00	NUM
cana-2747	229	70	48	48	NUM
cana-2747	229	71	s08	s08	NOUN
cana-2747	229	72	1.00	1.00	NUM
cana-2747	229	73	0.98	0.98	NUM
cana-2747	229	74	0.99	0.99	NUM
cana-2747	229	75	48	48	NUM
cana-2747	229	76	s09	s09	NOUN
cana-2747	229	77	1.00	1.00	NUM
cana-2747	229	78	1.00	1.00	NUM
cana-2747	229	79	1.00	1.00	NUM
cana-2747	229	80	48	48	NUM
cana-2747	229	81	s10	s10	NOUN
cana-2747	229	82	1.00	1.00	NUM
cana-2747	229	83	1.00	1.00	NUM
cana-2747	229	84	1.00	1.00	NUM
cana-2747	229	85	48	48	NUM
cana-2747	229	86	s11	s11	NUM
cana-2747	229	87	1.00	1.00	NUM
cana-2747	229	88	1.00	1.00	NUM
cana-2747	229	89	1.00	1.00	NUM
cana-2747	229	90	48	48	NUM
cana-2747	229	91	s12	s12	NOUN
cana-2747	229	92	1.00	1.00	NUM
cana-2747	229	93	1.00	1.00	NUM
cana-2747	229	94	1.00	1.00	NUM
cana-2747	229	95	48	48	NUM
cana-2747	229	96	s13	s13	NOUN
cana-2747	229	97	1.00	1.00	NUM
cana-2747	229	98	1.00	1.00	NUM
cana-2747	229	99	1.00	1.00	NUM
cana-2747	229	100	48	48	NUM
cana-2747	229	101	s14	s14	NOUN
cana-2747	229	102	1.00	1.00	NUM
cana-2747	229	103	1.00	1.00	NUM
cana-2747	229	104	1.00	1.00	NUM
cana-2747	229	105	48	48	NUM
cana-2747	229	106	s15	s15	NOUN
cana-2747	229	107	1.00	1.00	NUM
cana-2747	229	108	1.00	1.00	NUM
cana-2747	229	109	1.00	1.00	NUM
cana-2747	229	110	48	48	NUM
cana-2747	229	111	communications	communication	NOUN
cana-2747	229	112	on	on	ADP
cana-2747	229	113	applied	apply	VERB
cana-2747	229	114	nonlinear	nonlinear	ADJ
cana-2747	229	115	analysis	analysis	NOUN
cana-2747	229	116	issn	issn	NOUN
cana-2747	229	117	:	:	PUNCT
cana-2747	229	118	1074	1074	NUM
cana-2747	229	119	-	-	PUNCT
cana-2747	229	120	133x	133x	NUM
cana-2747	229	121	vol	vol	NOUN
cana-2747	229	122	32	32	NUM
cana-2747	229	123	no	no	NOUN
cana-2747	229	124	.	.	PUNCT
cana-2747	230	1	4s	4s	NUM
cana-2747	230	2	(	(	PUNCT
cana-2747	230	3	2025	2025	NUM
cana-2747	230	4	)	)	PUNCT
cana-2747	230	5	181	181	NUM
cana-2747	230	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	230	7	s16	s16	NOUN
cana-2747	230	8	1.00	1.00	NUM
cana-2747	230	9	1.00	1.00	NUM
cana-2747	230	10	1.00	1.00	NUM
cana-2747	230	11	48	48	NUM
cana-2747	230	12	s17	s17	NOUN
cana-2747	230	13	1.00	1.00	NUM
cana-2747	230	14	1.00	1.00	NUM
cana-2747	230	15	1.00	1.00	NUM
cana-2747	230	16	48	48	NUM
cana-2747	230	17	s18	s18	PROPN
cana-2747	230	18	1.00	1.00	NUM
cana-2747	230	19	1.00	1.00	NUM
cana-2747	230	20	1.00	1.00	NUM
cana-2747	230	21	48	48	NUM
cana-2747	230	22	s19	s19	NOUN
cana-2747	230	23	1.00	1.00	NUM
cana-2747	230	24	1.00	1.00	NUM
cana-2747	230	25	1.00	1.00	NUM
cana-2747	230	26	48	48	NUM
cana-2747	230	27	s20	s20	NOUN
cana-2747	230	28	1.00	1.00	NUM
cana-2747	230	29	1.00	1.00	NUM
cana-2747	230	30	1.00	1.00	NUM
cana-2747	230	31	48	48	NUM
cana-2747	230	32	s21	s21	NOUN
cana-2747	230	33	1.00	1.00	NUM
cana-2747	230	34	1.00	1.00	NUM
cana-2747	230	35	1.00	1.00	NUM
cana-2747	230	36	48	48	NUM
cana-2747	230	37	s22	s22	NOUN
cana-2747	230	38	1.00	1.00	NUM
cana-2747	230	39	1.00	1.00	NUM
cana-2747	230	40	1.00	1.00	NUM
cana-2747	230	41	48	48	NUM
cana-2747	230	42	macro	macro	NOUN
cana-2747	230	43	avg	avg	NOUN
cana-2747	230	44	1.00	1.00	NUM
cana-2747	230	45	1.00	1.00	NUM
cana-2747	230	46	1.00	1.00	NUM
cana-2747	230	47	1056	1056	NUM
cana-2747	230	48	weighted	weight	VERB
cana-2747	230	49	avg	avg	PROPN
cana-2747	230	50	1.00	1.00	NUM
cana-2747	230	51	1.00	1.00	NUM
cana-2747	230	52	1.00	1.00	NUM
cana-2747	230	53	1056	1056	NUM
cana-2747	230	54	8	8	NUM
cana-2747	230	55	.	.	PUNCT
cana-2747	231	1	conclusion	conclusion	NOUN
cana-2747	231	2	this	this	DET
cana-2747	231	3	research	research	NOUN
cana-2747	231	4	presents	present	VERB
cana-2747	231	5	an	an	DET
cana-2747	231	6	innovative	innovative	ADJ
cana-2747	231	7	method	method	NOUN
cana-2747	231	8	for	for	ADP
cana-2747	231	9	person	person	NOUN
cana-2747	231	10	identification	identification	NOUN
cana-2747	231	11	by	by	ADP
cana-2747	231	12	integrating	integrate	VERB
cana-2747	231	13	eeg	eeg	NOUN
cana-2747	231	14	and	and	CCONJ
cana-2747	231	15	facial	facial	ADJ
cana-2747	231	16	data	datum	NOUN
cana-2747	231	17	.	.	PUNCT
cana-2747	232	1	the	the	DET
cana-2747	232	2	study	study	NOUN
cana-2747	232	3	seeks	seek	VERB
cana-2747	232	4	to	to	PART
cana-2747	232	5	enhance	enhance	VERB
cana-2747	232	6	the	the	DET
cana-2747	232	7	effectiveness	effectiveness	NOUN
cana-2747	232	8	of	of	ADP
cana-2747	232	9	eeg	eeg	NOUN
cana-2747	232	10	-	-	PUNCT
cana-2747	232	11	based	base	VERB
cana-2747	232	12	person	person	NOUN
cana-2747	232	13	identification	identification	NOUN
cana-2747	232	14	(	(	PUNCT
cana-2747	232	15	pi	pi	NOUN
cana-2747	232	16	)	)	PUNCT
cana-2747	232	17	through	through	ADP
cana-2747	232	18	the	the	DET
cana-2747	232	19	use	use	NOUN
cana-2747	232	20	of	of	ADP
cana-2747	232	21	an	an	DET
cana-2747	232	22	lstm	lstm	PROPN
cana-2747	232	23	-	-	PUNCT
cana-2747	232	24	cnn	cnn	PROPN
cana-2747	232	25	model	model	NOUN
cana-2747	232	26	,	,	PUNCT
cana-2747	232	27	which	which	PRON
cana-2747	232	28	combines	combine	VERB
cana-2747	232	29	long	long	ADJ
cana-2747	232	30	short	short	ADJ
cana-2747	232	31	-	-	PUNCT
cana-2747	232	32	term	term	NOUN
cana-2747	232	33	memory	memory	NOUN
cana-2747	232	34	(	(	PUNCT
cana-2747	232	35	lstm	lstm	NOUN
cana-2747	232	36	)	)	PUNCT
cana-2747	232	37	and	and	CCONJ
cana-2747	232	38	convolutional	convolutional	ADJ
cana-2747	232	39	neural	neural	ADJ
cana-2747	232	40	network	network	NOUN
cana-2747	232	41	(	(	PUNCT
cana-2747	232	42	cnn	cnn	PROPN
cana-2747	232	43	)	)	PUNCT
cana-2747	232	44	architectures	architecture	VERB
cana-2747	232	45	for	for	ADP
cana-2747	232	46	a	a	DET
cana-2747	232	47	robust	robust	ADJ
cana-2747	232	48	sequence	sequence	NOUN
cana-2747	232	49	modeling	modeling	NOUN
cana-2747	232	50	approach	approach	NOUN
cana-2747	232	51	.	.	PUNCT
cana-2747	233	1	the	the	DET
cana-2747	233	2	lstm	lstm	PROPN
cana-2747	233	3	component	component	NOUN
cana-2747	233	4	is	be	AUX
cana-2747	233	5	responsible	responsible	ADJ
cana-2747	233	6	for	for	ADP
cana-2747	233	7	processing	process	VERB
cana-2747	233	8	temporal	temporal	ADJ
cana-2747	233	9	features	feature	NOUN
cana-2747	233	10	and	and	CCONJ
cana-2747	233	11	capturing	capture	VERB
cana-2747	233	12	long	long	ADJ
cana-2747	233	13	-	-	PUNCT
cana-2747	233	14	range	range	NOUN
cana-2747	233	15	dependencies	dependency	NOUN
cana-2747	233	16	,	,	PUNCT
cana-2747	233	17	while	while	SCONJ
cana-2747	233	18	the	the	DET
cana-2747	233	19	cnn	cnn	PROPN
cana-2747	233	20	component	component	NOUN
cana-2747	233	21	is	be	AUX
cana-2747	233	22	used	use	VERB
cana-2747	233	23	to	to	PART
cana-2747	233	24	learn	learn	VERB
cana-2747	233	25	local	local	ADJ
cana-2747	233	26	patterns	pattern	NOUN
cana-2747	233	27	or	or	CCONJ
cana-2747	233	28	spatial	spatial	ADJ
cana-2747	233	29	features	feature	NOUN
cana-2747	233	30	from	from	ADP
cana-2747	233	31	the	the	DET
cana-2747	233	32	data	datum	NOUN
cana-2747	233	33	.	.	PUNCT
cana-2747	234	1	the	the	DET
cana-2747	234	2	proposed	propose	VERB
cana-2747	234	3	method	method	NOUN
cana-2747	234	4	is	be	AUX
cana-2747	234	5	assessed	assess	VERB
cana-2747	234	6	using	use	VERB
cana-2747	234	7	the	the	DET
cana-2747	234	8	deap	deap	ADJ
cana-2747	234	9	dataset	dataset	NOUN
cana-2747	234	10	,	,	PUNCT
cana-2747	234	11	a	a	DET
cana-2747	234	12	state	state	NOUN
cana-2747	234	13	-	-	PUNCT
cana-2747	234	14	of	of	ADP
cana-2747	234	15	-	-	PUNCT
cana-2747	234	16	the	the	DET
cana-2747	234	17	-	-	PUNCT
cana-2747	234	18	art	art	NOUN
cana-2747	234	19	benchmark	benchmark	NOUN
cana-2747	234	20	for	for	ADP
cana-2747	234	21	affective	affective	ADJ
cana-2747	234	22	data	datum	NOUN
cana-2747	234	23	.	.	PUNCT
cana-2747	235	1	the	the	DET
cana-2747	235	2	findings	finding	NOUN
cana-2747	235	3	reveal	reveal	VERB
cana-2747	235	4	that	that	SCONJ
cana-2747	235	5	the	the	DET
cana-2747	235	6	cnn	cnn	PROPN
cana-2747	235	7	-	-	PUNCT
cana-2747	235	8	lstm	lstm	PROPN
cana-2747	235	9	model	model	NOUN
cana-2747	235	10	,	,	PUNCT
cana-2747	235	11	enhanced	enhance	VERB
cana-2747	235	12	with	with	ADP
cana-2747	235	13	mobilenet	mobilenet	NOUN
cana-2747	235	14	,	,	PUNCT
cana-2747	235	15	can	can	AUX
cana-2747	235	16	achieve	achieve	VERB
cana-2747	235	17	a	a	DET
cana-2747	235	18	mean	mean	ADJ
cana-2747	235	19	correct	correct	ADJ
cana-2747	235	20	recognition	recognition	NOUN
cana-2747	235	21	rate	rate	NOUN
cana-2747	235	22	of	of	ADP
cana-2747	235	23	up	up	ADP
cana-2747	235	24	to	to	PART
cana-2747	235	25	99.81	99.81	NUM
cana-2747	235	26	%	%	NOUN
cana-2747	235	27	for	for	ADP
cana-2747	235	28	person	person	NOUN
cana-2747	235	29	identification	identification	NOUN
cana-2747	235	30	(	(	PUNCT
cana-2747	235	31	pi	pi	NOUN
cana-2747	235	32	)	)	PUNCT
cana-2747	235	33	.	.	PUNCT
cana-2747	236	1	this	this	DET
cana-2747	236	2	study	study	NOUN
cana-2747	236	3	employs	employ	VERB
cana-2747	236	4	the	the	DET
cana-2747	236	5	lstm	lstm	PROPN
cana-2747	236	6	-	-	PUNCT
cana-2747	236	7	cnn	cnn	PROPN
cana-2747	236	8	model	model	NOUN
cana-2747	236	9	,	,	PUNCT
cana-2747	236	10	which	which	PRON
cana-2747	236	11	integrates	integrate	VERB
cana-2747	236	12	long	long	ADJ
cana-2747	236	13	short	short	ADJ
cana-2747	236	14	-	-	PUNCT
cana-2747	236	15	term	term	NOUN
cana-2747	236	16	memory	memory	NOUN
cana-2747	236	17	(	(	PUNCT
cana-2747	236	18	lstm	lstm	NOUN
cana-2747	236	19	)	)	PUNCT
cana-2747	236	20	and	and	CCONJ
cana-2747	236	21	convolutional	convolutional	ADJ
cana-2747	236	22	neural	neural	ADJ
cana-2747	236	23	network	network	NOUN
cana-2747	236	24	(	(	PUNCT
cana-2747	236	25	cnn	cnn	PROPN
cana-2747	236	26	)	)	PUNCT
cana-2747	236	27	architectures	architecture	NOUN
cana-2747	236	28	for	for	ADP
cana-2747	236	29	effective	effective	ADJ
cana-2747	236	30	sequence	sequence	NOUN
cana-2747	236	31	modeling.the	modeling.the	DET
cana-2747	236	32	lstm	lstm	PROPN
cana-2747	236	33	component	component	NOUN
cana-2747	236	34	is	be	AUX
cana-2747	236	35	responsible	responsible	ADJ
cana-2747	236	36	for	for	ADP
cana-2747	236	37	processing	process	VERB
cana-2747	236	38	temporal	temporal	ADJ
cana-2747	236	39	features	feature	NOUN
cana-2747	236	40	and	and	CCONJ
cana-2747	236	41	capturing	capture	VERB
cana-2747	236	42	long	long	ADJ
cana-2747	236	43	-	-	PUNCT
cana-2747	236	44	range	range	NOUN
cana-2747	236	45	dependencies	dependency	NOUN
cana-2747	236	46	,	,	PUNCT
cana-2747	236	47	while	while	SCONJ
cana-2747	236	48	the	the	DET
cana-2747	236	49	cnn	cnn	PROPN
cana-2747	236	50	component	component	NOUN
cana-2747	236	51	is	be	AUX
cana-2747	236	52	used	use	VERB
cana-2747	236	53	to	to	PART
cana-2747	236	54	learn	learn	VERB
cana-2747	236	55	local	local	ADJ
cana-2747	236	56	patterns	pattern	NOUN
cana-2747	236	57	or	or	CCONJ
cana-2747	236	58	spatial	spatial	ADJ
cana-2747	236	59	features	feature	NOUN
cana-2747	236	60	from	from	ADP
cana-2747	236	61	the	the	DET
cana-2747	236	62	data	datum	NOUN
cana-2747	236	63	.	.	PUNCT
cana-2747	237	1	the	the	DET
cana-2747	237	2	proposed	propose	VERB
cana-2747	237	3	hybrid	hybrid	NOUN
cana-2747	237	4	model	model	NOUN
cana-2747	237	5	demonstrates	demonstrate	VERB
cana-2747	237	6	promising	promise	VERB
cana-2747	237	7	results	result	NOUN
cana-2747	237	8	,	,	PUNCT
cana-2747	237	9	and	and	CCONJ
cana-2747	237	10	the	the	DET
cana-2747	237	11	findings	finding	NOUN
cana-2747	237	12	contribute	contribute	VERB
cana-2747	237	13	to	to	ADP
cana-2747	237	14	the	the	DET
cana-2747	237	15	evolving	evolve	VERB
cana-2747	237	16	field	field	NOUN
cana-2747	237	17	of	of	ADP
cana-2747	237	18	biometric	biometric	ADJ
cana-2747	237	19	identification	identification	NOUN
cana-2747	237	20	.	.	PUNCT
cana-2747	238	1	future	future	ADJ
cana-2747	238	2	research	research	NOUN
cana-2747	238	3	could	could	AUX
cana-2747	238	4	focus	focus	VERB
cana-2747	238	5	on	on	ADP
cana-2747	238	6	optimizing	optimize	VERB
cana-2747	238	7	the	the	DET
cana-2747	238	8	model	model	NOUN
cana-2747	238	9	architecture	architecture	NOUN
cana-2747	238	10	,	,	PUNCT
cana-2747	238	11	investigating	investigate	VERB
cana-2747	238	12	additional	additional	ADJ
cana-2747	238	13	features	feature	NOUN
cana-2747	238	14	,	,	PUNCT
cana-2747	238	15	and	and	CCONJ
cana-2747	238	16	enlarging	enlarge	VERB
cana-2747	238	17	the	the	DET
cana-2747	238	18	dataset	dataset	NOUN
cana-2747	238	19	to	to	PART
cana-2747	238	20	improve	improve	VERB
cana-2747	238	21	generalization	generalization	NOUN
cana-2747	238	22	capabilities	capability	NOUN
cana-2747	238	23	.	.	PUNCT
cana-2747	239	1	data	datum	NOUN
cana-2747	239	2	availability	availability	NOUN
cana-2747	239	3	the	the	DET
cana-2747	239	4	deap	deap	NOUN
cana-2747	239	5	dataset	dataset	NOUN
cana-2747	239	6	(	(	PUNCT
cana-2747	239	7	database	database	NOUN
cana-2747	239	8	for	for	ADP
cana-2747	239	9	emotion	emotion	NOUN
cana-2747	239	10	analysis	analysis	NOUN
cana-2747	239	11	using	use	VERB
cana-2747	239	12	physiological	physiological	ADJ
cana-2747	239	13	signals	signal	NOUN
cana-2747	239	14	)	)	PUNCT
cana-2747	239	15	is	be	AUX
cana-2747	239	16	publicly	publicly	ADV
cana-2747	239	17	accessible	accessible	ADJ
cana-2747	239	18	online	online	ADV
cana-2747	239	19	via	via	ADP
cana-2747	239	20	the	the	DET
cana-2747	239	21	dataset	dataset	NOUN
cana-2747	239	22	doi	doi	NOUN
cana-2747	239	23	:	:	PUNCT
cana-2747	239	24	10.1109	10.1109	NUM
cana-2747	239	25	/	/	SYM
cana-2747	239	26	taffc.2012.12	taffc.2012.12	NOUN
cana-2747	239	27	.	.	PUNCT
cana-2747	240	1	it	it	PRON
cana-2747	240	2	can	can	AUX
cana-2747	240	3	be	be	AUX
cana-2747	240	4	found	find	VERB
cana-2747	240	5	at	at	ADP
cana-2747	240	6	the	the	DET
cana-2747	240	7	following	follow	VERB
cana-2747	240	8	url	url	NOUN
cana-2747	240	9	:	:	PUNCT
cana-2747	240	10	http://www.eecs.qmul.ac.uk/mmv/datasets/deap/	http://www.eecs.qmul.ac.uk/mmv/datasets/deap/	PROPN
cana-2747	240	11	(	(	PUNCT
cana-2747	240	12	accessed	access	VERB
cana-2747	240	13	on	on	ADP
cana-2747	240	14	may	may	PROPN
cana-2747	240	15	13	13	NUM
cana-2747	240	16	,	,	PUNCT
cana-2747	240	17	2023	2023	NUM
cana-2747	240	18	)	)	PUNCT
cana-2747	240	19	.	.	PUNCT
cana-2747	241	1	declarations	declaration	NOUN
cana-2747	241	2	:	:	PUNCT
cana-2747	241	3	conflict	conflict	NOUN
cana-2747	241	4	of	of	ADP
cana-2747	241	5	interest	interest	NOUN
cana-2747	241	6	:	:	PUNCT
cana-2747	241	7	the	the	DET
cana-2747	241	8	authors	author	NOUN
cana-2747	241	9	declare	declare	VERB
cana-2747	241	10	that	that	SCONJ
cana-2747	241	11	they	they	PRON
cana-2747	241	12	have	have	VERB
cana-2747	241	13	no	no	DET
cana-2747	241	14	conflict	conflict	NOUN
cana-2747	241	15	of	of	ADP
cana-2747	241	16	interest	interest	NOUN
cana-2747	241	17	.	.	PUNCT
cana-2747	242	1	references	reference	NOUN
cana-2747	242	2	[	[	X
cana-2747	242	3	1	1	NUM
cana-2747	242	4	]	]	PUNCT
cana-2747	242	5	w.	w.	PROPN
cana-2747	242	6	li	li	PROPN
cana-2747	242	7	,	,	PUNCT
cana-2747	242	8	y.	y.	PROPN
cana-2747	242	9	yi	yi	PROPN
cana-2747	242	10	,	,	PUNCT
cana-2747	242	11	m.	m.	PROPN
cana-2747	242	12	wang	wang	PROPN
cana-2747	242	13	,	,	PUNCT
cana-2747	242	14	b.	b.	PROPN
cana-2747	242	15	peng	peng	PROPN
cana-2747	242	16	,	,	PUNCT
cana-2747	242	17	j.	j.	PROPN
cana-2747	242	18	zhu	zhu	PROPN
cana-2747	242	19	,	,	PUNCT
cana-2747	242	20	and	and	CCONJ
cana-2747	242	21	a.	a.	NOUN
cana-2747	242	22	song	song	NOUN
cana-2747	242	23	,	,	PUNCT
cana-2747	242	24	“	"	PUNCT
cana-2747	242	25	a	a	DET
cana-2747	242	26	novel	novel	ADJ
cana-2747	242	27	tensorial	tensorial	ADJ
cana-2747	242	28	scheme	scheme	NOUN
cana-2747	242	29	for	for	ADP
cana-2747	242	30	eeg	eeg	NOUN
cana-2747	242	31	-	-	PUNCT
cana-2747	242	32	based	base	VERB
cana-2747	242	33	person	person	NOUN
cana-2747	242	34	identification	identification	NOUN
cana-2747	242	35	,	,	PUNCT
cana-2747	242	36	”	"	PUNCT
cana-2747	242	37	in	in	ADP
cana-2747	242	38	ieee	ieee	NOUN
cana-2747	242	39	transactions	transaction	NOUN
cana-2747	242	40	on	on	ADP
cana-2747	242	41	instrumentation	instrumentation	NOUN
cana-2747	242	42	and	and	CCONJ
cana-2747	242	43	measurement	measurement	NOUN
cana-2747	242	44	,	,	PUNCT
cana-2747	242	45	institute	institute	NOUN
cana-2747	242	46	of	of	ADP
cana-2747	242	47	electrical	electrical	ADJ
cana-2747	242	48	and	and	CCONJ
cana-2747	242	49	electronics	electronics	PROPN
cana-2747	242	50	engineers	engineers	PROPN
cana-2747	242	51	inc	inc	PROPN
cana-2747	242	52	.	.	PROPN
cana-2747	242	53	,	,	PUNCT
cana-2747	242	54	2023	2023	NUM
cana-2747	242	55	.	.	PUNCT
cana-2747	243	1	doi	doi	NOUN
cana-2747	243	2	:	:	PUNCT
cana-2747	243	3	10.1109	10.1109	NUM
cana-2747	243	4	/	/	SYM
cana-2747	243	5	tim.2022.3225016	tim.2022.3225016	PROPN
cana-2747	243	6	.	.	PUNCT
cana-2747	244	1	http://www.eecs.qmul.ac.uk/mmv/datasets/deap/	http://www.eecs.qmul.ac.uk/mmv/datasets/deap/	PROPN
cana-2747	244	2	communications	communication	NOUN
cana-2747	244	3	on	on	ADP
cana-2747	244	4	applied	apply	VERB
cana-2747	244	5	nonlinear	nonlinear	ADJ
cana-2747	244	6	analysis	analysis	NOUN
cana-2747	244	7	issn	issn	NOUN
cana-2747	244	8	:	:	PUNCT
cana-2747	244	9	1074	1074	NUM
cana-2747	244	10	-	-	PUNCT
cana-2747	244	11	133x	133x	NUM
cana-2747	244	12	vol	vol	NOUN
cana-2747	244	13	32	32	NUM
cana-2747	244	14	no	no	NOUN
cana-2747	244	15	.	.	PUNCT
cana-2747	245	1	4s	4s	NUM
cana-2747	245	2	(	(	PUNCT
cana-2747	245	3	2025	2025	NUM
cana-2747	245	4	)	)	PUNCT
cana-2747	245	5	182	182	NUM
cana-2747	245	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2747	246	1	[	[	X
cana-2747	246	2	2	2	X
cana-2747	246	3	]	]	PUNCT
cana-2747	246	4	w.	w.	PROPN
cana-2747	246	5	kudisthalert	kudisthalert	PROPN
cana-2747	246	6	,	,	PUNCT
cana-2747	246	7	k.	k.	PROPN
cana-2747	246	8	pasupa	pasupa	PROPN
cana-2747	246	9	,	,	PUNCT
cana-2747	246	10	a.	a.	NOUN
cana-2747	246	11	morales	morale	NOUN
cana-2747	246	12	,	,	PUNCT
cana-2747	246	13	and	and	CCONJ
cana-2747	246	14	j.	j.	PROPN
cana-2747	246	15	fierrez	fierrez	PROPN
cana-2747	246	16	,	,	PUNCT
cana-2747	246	17	“	"	PUNCT
cana-2747	246	18	selm	selm	ADJ
cana-2747	246	19	:	:	PUNCT
cana-2747	246	20	siamese	siamese	ADJ
cana-2747	246	21	extreme	extreme	ADJ
cana-2747	246	22	learning	learning	NOUN
cana-2747	246	23	machine	machine	NOUN
cana-2747	246	24	with	with	ADP
cana-2747	246	25	application	application	NOUN
cana-2747	246	26	to	to	PART
cana-2747	246	27	face	face	VERB
cana-2747	246	28	biometrics	biometric	NOUN
cana-2747	246	29	,	,	PUNCT
cana-2747	246	30	”	"	PUNCT
cana-2747	246	31	neural	neural	ADJ
cana-2747	246	32	comput	comput	NOUN
cana-2747	246	33	.	.	PUNCT
cana-2747	247	1	appl	appl	PROPN
cana-2747	247	2	.	.	PROPN
cana-2747	247	3	,	,	PUNCT
cana-2747	247	4	vol	vol	NOUN
cana-2747	247	5	.	.	NOUN
cana-2747	247	6	0123456789	0123456789	NUM
cana-2747	247	7	,	,	PUNCT
cana-2747	247	8	2022	2022	NUM
cana-2747	247	9	,	,	PUNCT
cana-2747	247	10	doi	doi	NOUN
cana-2747	247	11	:	:	PUNCT
cana-2747	247	12	10.1007	10.1007	NUM
cana-2747	247	13	/	/	SYM
cana-2747	247	14	s00521	s00521	NOUN
cana-2747	247	15	-	-	PUNCT
cana-2747	247	16	022	022	NUM
cana-2747	247	17	-	-	PUNCT
cana-2747	247	18	07100	07100	NUM
cana-2747	247	19	-	-	PUNCT
cana-2747	247	20	z.	z.	PROPN
cana-2747	248	1	[	[	X
cana-2747	248	2	3	3	X
cana-2747	248	3	]	]	PUNCT
cana-2747	248	4	s.	s.	PROPN
cana-2747	248	5	b.	b.	PROPN
cana-2747	248	6	abdullahi	abdullahi	PROPN
cana-2747	248	7	,	,	PUNCT
cana-2747	248	8	z.	z.	PROPN
cana-2747	248	9	a.	a.	PROPN
cana-2747	248	10	bature	bature	PROPN
cana-2747	248	11	,	,	PUNCT
cana-2747	248	12	p.	p.	NOUN
cana-2747	248	13	chophuk	chophuk	PROPN
cana-2747	248	14	,	,	PUNCT
cana-2747	248	15	and	and	CCONJ
cana-2747	248	16	a.	a.	NOUN
cana-2747	248	17	muhammad	muhammad	PROPN
cana-2747	248	18	,	,	PUNCT
cana-2747	248	19	“	"	PUNCT
cana-2747	248	20	sequence	sequence	NOUN
cana-2747	248	21	-	-	PUNCT
cana-2747	248	22	wise	wise	ADJ
cana-2747	248	23	multimodal	multimodal	ADJ
cana-2747	248	24	biometric	biometric	ADJ
cana-2747	248	25	fingerprint	fingerprint	NOUN
cana-2747	248	26	and	and	CCONJ
cana-2747	248	27	finger	finger	NOUN
cana-2747	248	28	-	-	PUNCT
cana-2747	248	29	vein	vein	ADJ
cana-2747	248	30	recognition	recognition	NOUN
cana-2747	248	31	network	network	NOUN
cana-2747	248	32	(	(	PUNCT
cana-2747	248	33	stmfpfv	stmfpfv	NOUN
cana-2747	248	34	-	-	PUNCT
cana-2747	248	35	net	net	NOUN
cana-2747	248	36	)	)	PUNCT
cana-2747	248	37	,	,	PUNCT
cana-2747	248	38	”	"	PUNCT
cana-2747	248	39	intell	intell	PROPN
cana-2747	248	40	.	.	PUNCT
cana-2747	249	1	syst	syst	PROPN
cana-2747	249	2	.	.	PUNCT
cana-2747	250	1	with	with	ADP
cana-2747	250	2	appl	appl	PROPN
cana-2747	250	3	.	.	PROPN
cana-2747	250	4	,	,	PUNCT
cana-2747	250	5	vol	vol	NOUN
cana-2747	250	6	.	.	PROPN
cana-2747	250	7	19	19	NUM
cana-2747	250	8	,	,	PUNCT
cana-2747	250	9	no	no	INTJ
cana-2747	250	10	.	.	PUNCT
cana-2747	250	11	april	april	PROPN
cana-2747	250	12	,	,	PUNCT
cana-2747	250	13	p.	p.	NOUN
cana-2747	250	14	200256	200256	NUM
cana-2747	250	15	,	,	PUNCT
cana-2747	250	16	2023	2023	NUM
cana-2747	250	17	,	,	PUNCT
cana-2747	250	18	doi	doi	NOUN
cana-2747	250	19	:	:	PUNCT
cana-2747	250	20	10.1016	10.1016	NUM
cana-2747	250	21	/	/	SYM
cana-2747	250	22	j.iswa.2023.200256	j.iswa.2023.200256	PROPN
cana-2747	250	23	.	.	PUNCT
cana-2747	251	1	[	[	X
cana-2747	251	2	4	4	X
cana-2747	251	3	]	]	X
cana-2747	251	4	y.	y.	PROPN
cana-2747	251	5	l.	l.	PROPN
cana-2747	251	6	lai	lai	PROPN
cana-2747	251	7	,	,	PUNCT
cana-2747	251	8	t.-y	t.-y	NOUN
cana-2747	251	9	.	.	PUNCT
cana-2747	252	1	chai	chai	NOUN
cana-2747	252	2	,	,	PUNCT
cana-2747	252	3	m.	m.	PROPN
cana-2747	252	4	lee	lee	PROPN
cana-2747	252	5	,	,	PUNCT
cana-2747	252	6	and	and	CCONJ
cana-2747	252	7	b.-m	b.-m	PROPN
cana-2747	252	8	.	.	PUNCT
cana-2747	253	1	goi	goi	PROPN
cana-2747	253	2	,	,	PUNCT
cana-2747	253	3	“	"	PUNCT
cana-2747	253	4	iriscode	iriscode	ADJ
cana-2747	253	5	matching	matching	NOUN
cana-2747	253	6	comparator	comparator	NOUN
cana-2747	253	7	to	to	PART
cana-2747	253	8	improve	improve	VERB
cana-2747	253	9	decidability	decidability	NOUN
cana-2747	253	10	of	of	ADP
cana-2747	253	11	human	human	ADJ
cana-2747	253	12	iris	iris	NOUN
cana-2747	253	13	recognition	recognition	NOUN
cana-2747	253	14	,	,	PUNCT
cana-2747	253	15	”	"	PUNCT
cana-2747	253	16	in	in	ADP
cana-2747	253	17	proceedings	proceeding	NOUN
cana-2747	253	18	of	of	ADP
cana-2747	253	19	the	the	DET
cana-2747	253	20	6th	6th	ADJ
cana-2747	253	21	international	international	ADJ
cana-2747	253	22	conference	conference	NOUN
cana-2747	253	23	on	on	ADP
cana-2747	253	24	digital	digital	ADJ
cana-2747	253	25	signal	signal	NOUN
cana-2747	253	26	processing	processing	NOUN
cana-2747	253	27	,	,	PUNCT
cana-2747	253	28	in	in	ADP
cana-2747	253	29	icdsp	icdsp	NOUN
cana-2747	253	30	’	'	PUNCT
cana-2747	253	31	22	22	NUM
cana-2747	253	32	.	.	PUNCT
cana-2747	254	1	new	new	PROPN
cana-2747	254	2	york	york	PROPN
cana-2747	254	3	,	,	PUNCT
cana-2747	254	4	ny	ny	PROPN
cana-2747	254	5	,	,	PUNCT
cana-2747	254	6	usa	usa	PROPN
cana-2747	254	7	:	:	PUNCT
cana-2747	254	8	association	association	NOUN
cana-2747	254	9	for	for	ADP
cana-2747	254	10	computing	compute	VERB
cana-2747	254	11	machinery	machinery	NOUN
cana-2747	254	12	,	,	PUNCT
cana-2747	254	13	2022	2022	NUM
cana-2747	254	14	,	,	PUNCT
cana-2747	254	15	pp	pp	ADJ
cana-2747	254	16	.	.	PUNCT
cana-2747	255	1	120–126	120–126	NUM
cana-2747	255	2	.	.	PUNCT
cana-2747	256	1	doi	doi	NOUN
cana-2747	256	2	:	:	PUNCT
cana-2747	256	3	10.1145/3529570.3529591	10.1145/3529570.3529591	NUM
cana-2747	256	4	.	.	PUNCT
cana-2747	257	1	[	[	X
cana-2747	257	2	5	5	NUM
cana-2747	257	3	]	]	PUNCT
cana-2747	257	4	x.	x.	NOUN
cana-2747	257	5	zhang	zhang	PROPN
cana-2747	257	6	,	,	PUNCT
cana-2747	257	7	l.	l.	PROPN
cana-2747	257	8	yao	yao	PROPN
cana-2747	257	9	,	,	PUNCT
cana-2747	257	10	c.	c.	PROPN
cana-2747	257	11	huang	huang	PROPN
cana-2747	257	12	,	,	PUNCT
cana-2747	257	13	t.	t.	PROPN
cana-2747	257	14	a.	a.	PROPN
cana-2747	257	15	o.	o.	PROPN
cana-2747	257	16	gu	gu	PROPN
cana-2747	257	17	,	,	PUNCT
cana-2747	257	18	z.	z.	PROPN
cana-2747	257	19	yang	yang	PROPN
cana-2747	257	20	,	,	PUNCT
cana-2747	257	21	and	and	CCONJ
cana-2747	257	22	y.	y.	PROPN
cana-2747	257	23	liu	liu	PROPN
cana-2747	257	24	,	,	PUNCT
cana-2747	257	25	“	"	PUNCT
cana-2747	257	26	deepkey	deepkey	NOUN
cana-2747	257	27	:	:	PUNCT
cana-2747	257	28	a	a	DET
cana-2747	257	29	multimodal	multimodal	ADJ
cana-2747	257	30	biometric	biometric	ADJ
cana-2747	257	31	authentication	authentication	NOUN
cana-2747	257	32	system	system	NOUN
cana-2747	257	33	via	via	ADP
cana-2747	257	34	deep	deep	ADJ
cana-2747	257	35	decoding	decode	VERB
cana-2747	257	36	gaits	gait	NOUN
cana-2747	257	37	and	and	CCONJ
cana-2747	257	38	brainwaves	brainwave	NOUN
cana-2747	257	39	,	,	PUNCT
cana-2747	257	40	”	"	PUNCT
cana-2747	257	41	in	in	ADP
cana-2747	257	42	acm	acm	NOUN
cana-2747	257	43	transactions	transaction	NOUN
cana-2747	257	44	on	on	ADP
cana-2747	257	45	intelligent	intelligent	ADJ
cana-2747	257	46	systems	system	NOUN
cana-2747	257	47	and	and	CCONJ
cana-2747	257	48	technology	technology	NOUN
cana-2747	257	49	,	,	PUNCT
cana-2747	257	50	2020	2020	NUM
cana-2747	257	51	.	.	PUNCT
cana-2747	257	52	doi	doi	NOUN
cana-2747	257	53	:	:	PUNCT
cana-2747	257	54	10.1145/3393619	10.1145/3393619	NUM
cana-2747	257	55	.	.	PUNCT
cana-2747	258	1	[	[	X
cana-2747	258	2	6	6	NUM
cana-2747	258	3	]	]	X
cana-2747	258	4	d.	d.	PROPN
cana-2747	258	5	das	das	PROPN
cana-2747	258	6	chakladar	chakladar	PROPN
cana-2747	258	7	et	et	PROPN
cana-2747	258	8	al	al	PROPN
cana-2747	258	9	.	.	PROPN
cana-2747	258	10	,	,	PUNCT
cana-2747	258	11	“	"	PUNCT
cana-2747	258	12	a	a	DET
cana-2747	258	13	multimodal	multimodal	NOUN
cana-2747	258	14	-	-	PUNCT
cana-2747	258	15	siamese	siamese	ADJ
cana-2747	258	16	neural	neural	ADJ
cana-2747	258	17	network	network	NOUN
cana-2747	258	18	(	(	PUNCT
cana-2747	258	19	msnn	msnn	NOUN
cana-2747	258	20	)	)	PUNCT
cana-2747	258	21	for	for	ADP
cana-2747	258	22	person	person	NOUN
cana-2747	258	23	verification	verification	NOUN
cana-2747	258	24	using	use	VERB
cana-2747	258	25	signatures	signature	NOUN
cana-2747	258	26	and	and	CCONJ
cana-2747	258	27	eeg	eeg	NOUN
cana-2747	258	28	,	,	PUNCT
cana-2747	258	29	”	"	PUNCT
cana-2747	258	30	in	in	ADP
cana-2747	258	31	information	information	NOUN
cana-2747	258	32	fusion	fusion	NOUN
cana-2747	258	33	,	,	PUNCT
cana-2747	258	34	elsevier	elsevier	PROPN
cana-2747	258	35	b.v	b.v	PROPN
cana-2747	258	36	.	.	PROPN
cana-2747	258	37	,	,	PUNCT
cana-2747	258	38	2021	2021	NUM
cana-2747	258	39	,	,	PUNCT
cana-2747	258	40	pp	pp	ADJ
cana-2747	258	41	.	.	PUNCT
cana-2747	258	42	17–27	17–27	NUM
cana-2747	258	43	.	.	PUNCT
cana-2747	259	1	doi	doi	NOUN
cana-2747	259	2	:	:	PUNCT
cana-2747	259	3	10.1016	10.1016	NUM
cana-2747	259	4	/	/	SYM
cana-2747	259	5	j.inffus.2021.01.004	j.inffus.2021.01.004	NOUN
cana-2747	259	6	.	.	PUNCT
cana-2747	260	1	[	[	X
cana-2747	260	2	7	7	X
cana-2747	260	3	]	]	X
cana-2747	260	4	c.	c.	NOUN
cana-2747	260	5	ding	ding	PROPN
cana-2747	260	6	and	and	CCONJ
cana-2747	260	7	d.	d.	PROPN
cana-2747	260	8	tao	tao	PROPN
cana-2747	260	9	,	,	PUNCT
cana-2747	260	10	“	"	PUNCT
cana-2747	260	11	trunk	trunk	NOUN
cana-2747	260	12	-	-	PUNCT
cana-2747	260	13	branch	branch	NOUN
cana-2747	260	14	ensemble	ensemble	ADJ
cana-2747	260	15	convolutional	convolutional	ADJ
cana-2747	260	16	neural	neural	ADJ
cana-2747	260	17	networks	network	NOUN
cana-2747	260	18	for	for	ADP
cana-2747	260	19	video	video	NOUN
cana-2747	260	20	-	-	PUNCT
cana-2747	260	21	based	base	VERB
cana-2747	260	22	face	face	NOUN
cana-2747	260	23	recognition	recognition	NOUN
cana-2747	260	24	,	,	PUNCT
cana-2747	260	25	”	"	PUNCT
cana-2747	260	26	ieee	ieee	NOUN
cana-2747	260	27	trans	tran	NOUN
cana-2747	260	28	.	.	PUNCT
cana-2747	261	1	pattern	pattern	PROPN
cana-2747	261	2	anal	anal	PROPN
cana-2747	261	3	.	.	PUNCT
cana-2747	262	1	mach	mach	PROPN
cana-2747	262	2	.	.	PUNCT
cana-2747	263	1	intell	intell	PROPN
cana-2747	263	2	.	.	PUNCT
cana-2747	264	1	,	,	PUNCT
cana-2747	264	2	vol	vol	NOUN
cana-2747	264	3	.	.	PROPN
cana-2747	265	1	40	40	NUM
cana-2747	265	2	,	,	PUNCT
cana-2747	265	3	no	no	INTJ
cana-2747	265	4	.	.	NOUN
cana-2747	265	5	4	4	NUM
cana-2747	265	6	,	,	PUNCT
cana-2747	265	7	pp	pp	ADJ
cana-2747	265	8	.	.	PUNCT
cana-2747	266	1	1002–1014	1002–1014	NUM
cana-2747	266	2	,	,	PUNCT
cana-2747	266	3	2018	2018	NUM
cana-2747	266	4	,	,	PUNCT
cana-2747	266	5	doi	doi	NOUN
cana-2747	266	6	:	:	PUNCT
cana-2747	266	7	10.1109	10.1109	NUM
cana-2747	266	8	/	/	SYM
cana-2747	266	9	tpami.2017.2700390	tpami.2017.2700390	NOUN
cana-2747	266	10	.	.	PUNCT
cana-2747	267	1	[	[	X
cana-2747	267	2	8	8	X
cana-2747	267	3	]	]	PUNCT
cana-2747	267	4	k.	k.	PROPN
cana-2747	267	5	patel	patel	PROPN
cana-2747	267	6	,	,	PUNCT
cana-2747	267	7	h.	h.	PROPN
cana-2747	267	8	han	han	PROPN
cana-2747	267	9	,	,	PUNCT
cana-2747	267	10	and	and	CCONJ
cana-2747	267	11	a.	a.	PROPN
cana-2747	267	12	k.	k.	PROPN
cana-2747	267	13	jain	jain	PROPN
cana-2747	267	14	,	,	PUNCT
cana-2747	267	15	“	"	PUNCT
cana-2747	267	16	secure	secure	ADJ
cana-2747	267	17	face	face	NOUN
cana-2747	267	18	unlock	unlock	NOUN
cana-2747	267	19	:	:	PUNCT
cana-2747	267	20	spoof	spoof	ADJ
cana-2747	267	21	detection	detection	NOUN
cana-2747	267	22	on	on	ADP
cana-2747	267	23	smartphones	smartphone	NOUN
cana-2747	267	24	,	,	PUNCT
cana-2747	267	25	”	"	PUNCT
cana-2747	267	26	ieee	ieee	NOUN
cana-2747	267	27	trans	trans	PROPN
cana-2747	267	28	.	.	PROPN
cana-2747	267	29	inf	inf	PROPN
cana-2747	267	30	.	.	PUNCT
cana-2747	267	31	forensics	forensic	NOUN
cana-2747	267	32	secur	secur	PROPN
cana-2747	267	33	.	.	PUNCT
cana-2747	267	34	,	,	PUNCT
cana-2747	267	35	vol	vol	NOUN
cana-2747	267	36	.	.	PROPN
cana-2747	268	1	11	11	NUM
cana-2747	268	2	,	,	PUNCT
cana-2747	268	3	no	no	INTJ
cana-2747	268	4	.	.	NOUN
cana-2747	268	5	10	10	NUM
cana-2747	268	6	,	,	PUNCT
cana-2747	268	7	pp	pp	ADJ
cana-2747	268	8	.	.	PUNCT
cana-2747	269	1	2268–2283	2268–2283	NUM
cana-2747	269	2	,	,	PUNCT
cana-2747	269	3	2016	2016	NUM
cana-2747	269	4	,	,	PUNCT
cana-2747	269	5	doi	doi	NOUN
cana-2747	269	6	:	:	PUNCT
cana-2747	269	7	10.1109	10.1109	NUM
cana-2747	269	8	/	/	SYM
cana-2747	269	9	tifs.2016.2578288	tifs.2016.2578288	NUM
cana-2747	269	10	.	.	PUNCT
cana-2747	270	1	[	[	X
cana-2747	270	2	9	9	NUM
cana-2747	270	3	]	]	X
cana-2747	270	4	n.	n.	PROPN
cana-2747	270	5	bala	bala	PROPN
cana-2747	270	6	,	,	PUNCT
cana-2747	270	7	r.	r.	PROPN
cana-2747	270	8	gupta	gupta	PROPN
cana-2747	270	9	,	,	PUNCT
cana-2747	270	10	and	and	CCONJ
cana-2747	270	11	a.	a.	PROPN
cana-2747	270	12	kumar	kumar	PROPN
cana-2747	270	13	,	,	PUNCT
cana-2747	270	14	“	"	PUNCT
cana-2747	270	15	multimodal	multimodal	ADJ
cana-2747	270	16	biometric	biometric	ADJ
cana-2747	270	17	system	system	NOUN
cana-2747	270	18	based	base	VERB
cana-2747	270	19	on	on	ADP
cana-2747	270	20	fusion	fusion	NOUN
cana-2747	270	21	techniques	technique	NOUN
cana-2747	270	22	:	:	PUNCT
cana-2747	270	23	a	a	DET
cana-2747	270	24	review	review	NOUN
cana-2747	270	25	,	,	PUNCT
cana-2747	270	26	”	"	PUNCT
cana-2747	270	27	inf	inf	PROPN
cana-2747	270	28	.	.	PROPN
cana-2747	270	29	secur	secur	PROPN
cana-2747	270	30	.	.	PUNCT
cana-2747	271	1	j.	j.	PROPN
cana-2747	271	2	,	,	PUNCT
cana-2747	271	3	vol	vol	NOUN
cana-2747	271	4	.	.	PROPN
cana-2747	271	5	31	31	NUM
cana-2747	271	6	,	,	PUNCT
cana-2747	271	7	no	no	INTJ
cana-2747	271	8	.	.	NOUN
cana-2747	271	9	3	3	NUM
cana-2747	271	10	,	,	PUNCT
cana-2747	271	11	pp	pp	ADJ
cana-2747	271	12	.	.	PUNCT
cana-2747	272	1	289–337	289–337	NUM
cana-2747	272	2	,	,	PUNCT
cana-2747	272	3	2022	2022	NUM
cana-2747	272	4	,	,	PUNCT
cana-2747	272	5	doi	doi	NOUN
cana-2747	272	6	:	:	PUNCT
cana-2747	272	7	10.1080/19393555.2021.1974130	10.1080/19393555.2021.1974130	NUM
cana-2747	272	8	.	.	PUNCT
cana-2747	273	1	[	[	X
cana-2747	273	2	10	10	NUM
cana-2747	273	3	]	]	PUNCT
cana-2747	273	4	a.	a.	NOUN
cana-2747	273	5	al	al	PROPN
cana-2747	273	6	abdulwahid	abdulwahid	PROPN
cana-2747	273	7	,	,	PUNCT
cana-2747	273	8	n.	n.	PROPN
cana-2747	273	9	clarke	clarke	PROPN
cana-2747	273	10	,	,	PUNCT
cana-2747	273	11	i.	i.	PROPN
cana-2747	273	12	stengel	stengel	PROPN
cana-2747	273	13	,	,	PUNCT
cana-2747	273	14	s.	s.	PROPN
cana-2747	273	15	furnell	furnell	PROPN
cana-2747	273	16	,	,	PUNCT
cana-2747	273	17	and	and	CCONJ
cana-2747	273	18	c.	c.	PROPN
cana-2747	273	19	reich	reich	PROPN
cana-2747	273	20	,	,	PUNCT
cana-2747	273	21	“	"	PUNCT
cana-2747	273	22	continuous	continuous	ADJ
cana-2747	273	23	and	and	CCONJ
cana-2747	273	24	transparent	transparent	ADJ
cana-2747	273	25	multimodal	multimodal	NOUN
cana-2747	273	26	authentication	authentication	NOUN
cana-2747	273	27	:	:	PUNCT
cana-2747	273	28	reviewing	review	VERB
cana-2747	273	29	the	the	DET
cana-2747	273	30	state	state	NOUN
cana-2747	273	31	of	of	ADP
cana-2747	273	32	the	the	DET
cana-2747	273	33	art	art	NOUN
cana-2747	273	34	,	,	PUNCT
cana-2747	273	35	”	"	PUNCT
cana-2747	273	36	cluster	cluster	NOUN
cana-2747	273	37	comput	comput	NOUN
cana-2747	273	38	.	.	PUNCT
cana-2747	273	39	,	,	PUNCT
cana-2747	273	40	vol	vol	NOUN
cana-2747	273	41	.	.	PROPN
cana-2747	273	42	19	19	NUM
cana-2747	273	43	,	,	PUNCT
cana-2747	273	44	no	no	INTJ
cana-2747	273	45	.	.	NOUN
cana-2747	273	46	1	1	NUM
cana-2747	273	47	,	,	PUNCT
cana-2747	273	48	pp	pp	ADJ
cana-2747	273	49	.	.	PUNCT
cana-2747	274	1	455–474	455–474	NUM
cana-2747	274	2	,	,	PUNCT
cana-2747	274	3	2016	2016	NUM
cana-2747	274	4	,	,	PUNCT
cana-2747	274	5	doi	doi	NOUN
cana-2747	274	6	:	:	PUNCT
cana-2747	274	7	10.1007	10.1007	NUM
cana-2747	274	8	/	/	SYM
cana-2747	274	9	s10586	s10586	PROPN
cana-2747	274	10	-	-	PUNCT
cana-2747	274	11	015	015	NUM
cana-2747	274	12	-	-	PUNCT
cana-2747	274	13	0510	0510	NUM
cana-2747	274	14	-	-	PUNCT
cana-2747	274	15	4	4	NUM
cana-2747	274	16	.	.	PUNCT
cana-2747	275	1	[	[	X
cana-2747	275	2	11	11	NUM
cana-2747	275	3	]	]	PUNCT
cana-2747	275	4	t.	t.	PROPN
cana-2747	275	5	fukami	fukami	PROPN
cana-2747	275	6	,	,	PUNCT
cana-2747	275	7	y.	y.	PROPN
cana-2747	275	8	abe	abe	PROPN
cana-2747	275	9	,	,	PUNCT
cana-2747	275	10	t.	t.	PROPN
cana-2747	275	11	shimada	shimada	PROPN
cana-2747	275	12	,	,	PUNCT
cana-2747	275	13	and	and	CCONJ
cana-2747	275	14	b.	b.	PROPN
cana-2747	275	15	ishikawa	ishikawa	PROPN
cana-2747	275	16	,	,	PUNCT
cana-2747	275	17	“	"	PUNCT
cana-2747	275	18	authentication	authentication	NOUN
cana-2747	275	19	system	system	NOUN
cana-2747	275	20	preventing	prevent	VERB
cana-2747	275	21	unauthorized	unauthorized	ADJ
cana-2747	275	22	access	access	NOUN
cana-2747	275	23	of	of	ADP
cana-2747	275	24	a	a	DET
cana-2747	275	25	third	third	ADJ
cana-2747	275	26	person	person	NOUN
cana-2747	275	27	based	base	VERB
cana-2747	275	28	on	on	ADP
cana-2747	275	29	steady	steady	ADJ
cana-2747	275	30	state	state	NOUN
cana-2747	275	31	visual	visual	ADJ
cana-2747	275	32	evoked	evoke	VERB
cana-2747	275	33	potentials	potential	NOUN
cana-2747	275	34	,	,	PUNCT
cana-2747	275	35	”	"	PUNCT
cana-2747	275	36	in	in	ADP
cana-2747	275	37	international	international	ADJ
cana-2747	275	38	journal	journal	NOUN
cana-2747	275	39	of	of	ADP
cana-2747	275	40	innovative	innovative	ADJ
cana-2747	275	41	computing	computing	NOUN
cana-2747	275	42	,	,	PUNCT
cana-2747	275	43	information	information	NOUN
cana-2747	275	44	and	and	CCONJ
cana-2747	275	45	control	control	NOUN
cana-2747	275	46	,	,	PUNCT
cana-2747	275	47	icic	icic	PROPN
cana-2747	275	48	international	international	PROPN
cana-2747	275	49	,	,	PUNCT
cana-2747	275	50	2018	2018	NUM
cana-2747	275	51	,	,	PUNCT
cana-2747	275	52	pp	pp	ADJ
cana-2747	275	53	.	.	PUNCT
cana-2747	276	1	2091–2100	2091–2100	NUM
cana-2747	276	2	.	.	PUNCT
cana-2747	277	1	doi	doi	NOUN
cana-2747	277	2	:	:	PUNCT
cana-2747	277	3	10.24507	10.24507	NUM
cana-2747	277	4	/	/	SYM
cana-2747	277	5	ijicic.14.06.2091	ijicic.14.06.2091	ADJ
cana-2747	277	6	.	.	PUNCT
cana-2747	278	1	[	[	X
cana-2747	278	2	12	12	NUM
cana-2747	278	3	]	]	X
cana-2747	278	4	w.	w.	PROPN
cana-2747	278	5	deng	deng	PROPN
cana-2747	278	6	,	,	PUNCT
cana-2747	278	7	t.	t.	PROPN
cana-2747	278	8	hassner	hassner	PROPN
cana-2747	278	9	,	,	PUNCT
cana-2747	278	10	x.	x.	PROPN
cana-2747	278	11	liu	liu	PROPN
cana-2747	278	12	,	,	PUNCT
cana-2747	278	13	and	and	CCONJ
cana-2747	278	14	m.	m.	NOUN
cana-2747	278	15	pantic	pantic	PROPN
cana-2747	278	16	,	,	PUNCT
cana-2747	278	17	“	"	PUNCT
cana-2747	278	18	tbiom	tbiom	ADV
cana-2747	278	19	special	special	ADJ
cana-2747	278	20	issue	issue	NOUN
cana-2747	278	21	on	on	ADP
cana-2747	278	22	trustworthy	trustworthy	ADJ
cana-2747	278	23	biometrics	biometric	NOUN
cana-2747	278	24	-	-	PUNCT
cana-2747	278	25	editorial	editorial	NOUN
cana-2747	278	26	,	,	PUNCT
cana-2747	278	27	”	"	PUNCT
cana-2747	278	28	ieee	ieee	NOUN
cana-2747	278	29	trans	tran	NOUN
cana-2747	278	30	.	.	PUNCT
cana-2747	279	1	biometrics	biometric	NOUN
cana-2747	279	2	,	,	PUNCT
cana-2747	279	3	behav	behav	NOUN
cana-2747	279	4	.	.	PUNCT
cana-2747	280	1	identity	identity	PROPN
cana-2747	280	2	sci	sci	PROPN
cana-2747	280	3	.	.	PROPN
cana-2747	280	4	,	,	PUNCT
cana-2747	280	5	vol	vol	NOUN
cana-2747	280	6	.	.	PROPN
cana-2747	280	7	4	4	NUM
cana-2747	280	8	,	,	PUNCT
cana-2747	280	9	no	no	INTJ
cana-2747	280	10	.	.	NOUN
cana-2747	280	11	3	3	NUM
cana-2747	280	12	,	,	PUNCT
cana-2747	280	13	pp	pp	ADJ
cana-2747	280	14	.	.	PUNCT
cana-2747	281	1	301–302	301–302	NUM
cana-2747	281	2	,	,	PUNCT
cana-2747	281	3	2022	2022	NUM
cana-2747	281	4	,	,	PUNCT
cana-2747	281	5	doi	doi	NOUN
cana-2747	281	6	:	:	PUNCT
cana-2747	281	7	10.1109	10.1109	NUM
cana-2747	281	8	/	/	SYM
cana-2747	281	9	tbiom.2022.3185447	tbiom.2022.3185447	NOUN
cana-2747	281	10	.	.	PUNCT
cana-2747	282	1	[	[	X
cana-2747	282	2	13	13	NUM
cana-2747	282	3	]	]	PUNCT
cana-2747	282	4	a.	a.	NOUN
cana-2747	282	5	dediu	dediu	PROPN
cana-2747	282	6	,	,	PUNCT
cana-2747	282	7	c.	c.	PROPN
cana-2747	282	8	martín	martín	PROPN
cana-2747	282	9	-	-	PUNCT
cana-2747	282	10	vide	vide	NOUN
cana-2747	282	11	,	,	PUNCT
cana-2747	282	12	and	and	CCONJ
cana-2747	282	13	r.	r.	PROPN
cana-2747	282	14	goebel	goebel	PROPN
cana-2747	282	15	,	,	PUNCT
cana-2747	282	16	lnai	lnai	ADJ
cana-2747	282	17	7978	7978	NUM
cana-2747	282	18	statistical	statistical	ADJ
cana-2747	282	19	language	language	NOUN
cana-2747	282	20	and	and	CCONJ
cana-2747	282	21	speech	speech	NOUN
cana-2747	282	22	processing	processing	NOUN
cana-2747	282	23	,	,	PUNCT
cana-2747	282	24	no	no	INTJ
cana-2747	282	25	.	.	PUNCT
cana-2747	282	26	july	july	PROPN
cana-2747	282	27	.	.	PUNCT
cana-2747	283	1	2013	2013	NUM
cana-2747	283	2	.	.	PUNCT
cana-2747	284	1	[	[	X
cana-2747	284	2	14	14	NUM
cana-2747	284	3	]	]	X
cana-2747	284	4	t.	t.	NOUN
cana-2747	284	5	wilaiprasitporn	wilaiprasitporn	NOUN
cana-2747	284	6	,	,	PUNCT
cana-2747	284	7	a.	a.	NOUN
cana-2747	284	8	ditthapron	ditthapron	PROPN
cana-2747	284	9	,	,	PUNCT
cana-2747	284	10	k.	k.	PROPN
cana-2747	284	11	matchaparn	matchaparn	PROPN
cana-2747	284	12	,	,	PUNCT
cana-2747	284	13	t.	t.	PROPN
cana-2747	284	14	tongbuasirilai	tongbuasirilai	PROPN
cana-2747	284	15	,	,	PUNCT
cana-2747	284	16	n.	n.	PROPN
cana-2747	284	17	banluesombatkul	banluesombatkul	PROPN
cana-2747	284	18	,	,	PUNCT
cana-2747	284	19	and	and	CCONJ
cana-2747	284	20	e.	e.	PROPN
cana-2747	284	21	chuangsuwanich	chuangsuwanich	PROPN
cana-2747	284	22	,	,	PUNCT
cana-2747	284	23	“	"	PUNCT
cana-2747	284	24	affective	affective	ADJ
cana-2747	284	25	eeg	eeg	NOUN
cana-2747	284	26	-	-	PUNCT
cana-2747	284	27	based	base	VERB
cana-2747	284	28	person	person	NOUN
cana-2747	284	29	identification	identification	NOUN
cana-2747	284	30	using	use	VERB
cana-2747	284	31	the	the	DET
cana-2747	284	32	deep	deep	ADJ
cana-2747	284	33	learning	learning	NOUN
cana-2747	284	34	approach	approach	NOUN
cana-2747	284	35	,	,	PUNCT
cana-2747	284	36	”	"	PUNCT
cana-2747	284	37	ieee	ieee	NOUN
cana-2747	284	38	trans	trans	PROPN
cana-2747	284	39	.	.	PROPN
cana-2747	284	40	cogn	cogn	PROPN
cana-2747	284	41	.	.	PUNCT
cana-2747	285	1	dev	dev	PROPN
cana-2747	285	2	.	.	PUNCT
cana-2747	286	1	syst	syst	PROPN
cana-2747	286	2	.	.	PUNCT
cana-2747	286	3	,	,	PUNCT
cana-2747	286	4	vol	vol	NOUN
cana-2747	286	5	.	.	PROPN
cana-2747	286	6	12	12	NUM
cana-2747	286	7	,	,	PUNCT
cana-2747	286	8	no	no	INTJ
cana-2747	286	9	.	.	NOUN
cana-2747	286	10	3	3	NUM
cana-2747	286	11	,	,	PUNCT
cana-2747	286	12	pp	pp	ADJ
cana-2747	286	13	.	.	PUNCT
cana-2747	287	1	486–496	486–496	NUM
cana-2747	287	2	,	,	PUNCT
cana-2747	287	3	2020	2020	NUM
cana-2747	287	4	,	,	PUNCT
cana-2747	287	5	doi	doi	NOUN
cana-2747	287	6	:	:	PUNCT
cana-2747	287	7	10.1109	10.1109	NUM
cana-2747	287	8	/	/	SYM
cana-2747	287	9	tcds.2019.2924648	tcds.2019.2924648	NOUN
cana-2747	287	10	.	.	PUNCT
cana-2747	288	1	[	[	X
cana-2747	288	2	15	15	NUM
cana-2747	288	3	]	]	X
cana-2747	288	4	m.	m.	NOUN
cana-2747	288	5	wang	wang	PROPN
cana-2747	288	6	,	,	PUNCT
cana-2747	288	7	j.	j.	PROPN
cana-2747	288	8	hu	hu	PROPN
cana-2747	288	9	,	,	PUNCT
cana-2747	288	10	and	and	CCONJ
cana-2747	288	11	h.	h.	PROPN
cana-2747	288	12	a.	a.	NOUN
cana-2747	288	13	abbass	abbass	PROPN
cana-2747	288	14	,	,	PUNCT
cana-2747	288	15	“	"	PUNCT
cana-2747	288	16	brainprint	brainprint	NOUN
cana-2747	288	17	:	:	PUNCT
cana-2747	288	18	eeg	eeg	NOUN
cana-2747	288	19	biometric	biometric	ADJ
cana-2747	288	20	identification	identification	NOUN
cana-2747	288	21	based	base	VERB
cana-2747	288	22	on	on	ADP
cana-2747	288	23	analyzing	analyze	VERB
cana-2747	288	24	brain	brain	NOUN
cana-2747	288	25	connectivity	connectivity	NOUN
cana-2747	288	26	graphs	graph	NOUN
cana-2747	288	27	,	,	PUNCT
cana-2747	288	28	”	"	PUNCT
cana-2747	288	29	in	in	ADP
cana-2747	288	30	pattern	pattern	NOUN
cana-2747	288	31	recognition	recognition	NOUN
cana-2747	288	32	,	,	PUNCT
cana-2747	288	33	elsevier	elsevier	PROPN
cana-2747	288	34	ltd	ltd	PROPN
cana-2747	288	35	,	,	PUNCT
cana-2747	288	36	2020	2020	NUM
cana-2747	288	37	,	,	PUNCT
cana-2747	288	38	p.	p.	NOUN
cana-2747	288	39	107381	107381	NUM
cana-2747	288	40	.	.	PUNCT
cana-2747	289	1	doi	doi	NOUN
cana-2747	289	2	:	:	PUNCT
cana-2747	289	3	https://doi.org/10.1016/j.patcog.2020.107381	https://doi.org/10.1016/j.patcog.2020.107381	NOUN
cana-2747	289	4	.	.	PUNCT
cana-2747	290	1	[	[	X
cana-2747	290	2	16	16	NUM
cana-2747	290	3	]	]	X
cana-2747	290	4	b.	b.	PROPN
cana-2747	290	5	b.	b.	PROPN
cana-2747	290	6	das	das	PROPN
cana-2747	290	7	,	,	PUNCT
cana-2747	290	8	p.	p.	PROPN
cana-2747	290	9	kumar	kumar	PROPN
cana-2747	290	10	,	,	PUNCT
cana-2747	290	11	d.	d.	PROPN
cana-2747	290	12	kar	kar	PROPN
cana-2747	290	13	,	,	PUNCT
cana-2747	290	14	s.	s.	PROPN
cana-2747	290	15	k.	k.	PROPN
cana-2747	290	16	ram	ram	PROPN
cana-2747	290	17	,	,	PUNCT
cana-2747	290	18	k.	k.	PROPN
cana-2747	290	19	s.	s.	PROPN
cana-2747	290	20	babu	babu	PROPN
cana-2747	290	21	,	,	PUNCT
cana-2747	290	22	and	and	CCONJ
cana-2747	290	23	r.	r.	PROPN
cana-2747	290	24	k.	k.	PROPN
cana-2747	290	25	mohapatra	mohapatra	PROPN
cana-2747	290	26	,	,	PUNCT
cana-2747	290	27	“	"	PUNCT
cana-2747	290	28	a	a	DET
cana-2747	290	29	spatio	spatio	PROPN
cana-2747	290	30	-	-	PUNCT
cana-2747	290	31	temporal	temporal	ADJ
cana-2747	290	32	model	model	NOUN
cana-2747	290	33	for	for	ADP
cana-2747	290	34	eeg	eeg	NOUN
cana-2747	290	35	-	-	PUNCT
cana-2747	290	36	based	base	VERB
cana-2747	290	37	person	person	NOUN
cana-2747	290	38	identification	identification	NOUN
cana-2747	290	39	,	,	PUNCT
cana-2747	290	40	”	"	PUNCT
cana-2747	290	41	multimed	multime	VERB
cana-2747	290	42	.	.	PUNCT
cana-2747	291	1	tools	tool	NOUN
cana-2747	291	2	appl	appl	PROPN
cana-2747	291	3	.	.	PUNCT
cana-2747	291	4	,	,	PUNCT
cana-2747	291	5	vol	vol	NOUN
cana-2747	291	6	.	.	PROPN
cana-2747	292	1	78	78	NUM
cana-2747	292	2	,	,	PUNCT
cana-2747	292	3	no	no	INTJ
cana-2747	292	4	.	.	NOUN
cana-2747	292	5	19	19	NUM
cana-2747	292	6	,	,	PUNCT
cana-2747	292	7	pp	pp	ADJ
cana-2747	292	8	.	.	PUNCT
cana-2747	293	1	28157–28177	28157–28177	NUM
cana-2747	293	2	,	,	PUNCT
cana-2747	293	3	2019	2019	NUM
cana-2747	293	4	,	,	PUNCT
cana-2747	293	5	doi	doi	NOUN
cana-2747	293	6	:	:	PUNCT
cana-2747	293	7	10.1007	10.1007	NUM
cana-2747	293	8	/	/	SYM
cana-2747	293	9	s11042	s11042	PROPN
cana-2747	293	10	-	-	PUNCT
cana-2747	293	11	01907905	01907905	NUM
cana-2747	293	12	-	-	PUNCT
cana-2747	293	13	6	6	NUM
cana-2747	293	14	.	.	PUNCT
cana-2747	294	1	[	[	X
cana-2747	294	2	17	17	NUM
cana-2747	294	3	]	]	X
cana-2747	294	4	y.	y.	PROPN
cana-2747	294	5	sun	sun	PROPN
cana-2747	294	6	,	,	PUNCT
cana-2747	294	7	f.	f.	PROPN
cana-2747	294	8	p.-w	p.-w	PROPN
cana-2747	294	9	.	.	PUNCT
cana-2747	295	1	lo	lo	PROPN
cana-2747	295	2	,	,	PUNCT
cana-2747	295	3	and	and	CCONJ
cana-2747	295	4	b.	b.	PROPN
cana-2747	295	5	lo	lo	PROPN
cana-2747	295	6	,	,	PUNCT
cana-2747	295	7	“	"	PUNCT
cana-2747	295	8	eeg	eeg	NOUN
cana-2747	295	9	-	-	PUNCT
cana-2747	295	10	based	base	VERB
cana-2747	295	11	user	user	NOUN
cana-2747	295	12	identification	identification	NOUN
cana-2747	295	13	system	system	NOUN
cana-2747	295	14	using	use	VERB
cana-2747	295	15	1d	1d	NUM
cana-2747	295	16	-	-	PUNCT
cana-2747	295	17	convolutional	convolutional	ADJ
cana-2747	295	18	long	long	ADJ
cana-2747	295	19	short	short	ADJ
cana-2747	295	20	-	-	PUNCT
cana-2747	295	21	term	term	NOUN
cana-2747	295	22	memory	memory	NOUN
cana-2747	295	23	neural	neural	ADJ
cana-2747	295	24	networks	network	NOUN
cana-2747	295	25	,	,	PUNCT
cana-2747	295	26	”	"	PUNCT
cana-2747	295	27	in	in	ADP
cana-2747	295	28	expert	expert	NOUN
cana-2747	295	29	systems	system	NOUN
cana-2747	295	30	with	with	ADP
cana-2747	295	31	applications	application	NOUN
cana-2747	295	32	,	,	PUNCT
cana-2747	295	33	2019	2019	NUM
cana-2747	295	34	,	,	PUNCT
cana-2747	295	35	pp	pp	ADJ
cana-2747	295	36	.	.	PUNCT
cana-2747	296	1	259–267	259–267	NUM
cana-2747	296	2	.	.	PUNCT
cana-2747	296	3	doi	doi	NOUN
cana-2747	296	4	:	:	PUNCT
cana-2747	296	5	https://doi.org/10.1016/j.eswa.2019.01.080	https://doi.org/10.1016/j.eswa.2019.01.080	NOUN
cana-2747	296	6	.	.	PUNCT
cana-2747	297	1	[	[	X
cana-2747	297	2	18	18	NUM
cana-2747	297	3	]	]	X
cana-2747	297	4	e.	e.	PROPN
cana-2747	297	5	maiorana	maiorana	PROPN
cana-2747	297	6	,	,	PUNCT
cana-2747	297	7	“	"	PUNCT
cana-2747	297	8	learning	learn	VERB
cana-2747	297	9	deep	deep	ADJ
cana-2747	297	10	features	feature	NOUN
cana-2747	297	11	for	for	ADP
cana-2747	297	12	task	task	NOUN
cana-2747	297	13	-	-	PUNCT
cana-2747	297	14	independent	independent	ADJ
cana-2747	297	15	eeg	eeg	NOUN
cana-2747	297	16	-	-	PUNCT
cana-2747	297	17	based	base	VERB
cana-2747	297	18	biometric	biometric	ADJ
cana-2747	297	19	verification	verification	NOUN
cana-2747	297	20	,	,	PUNCT
cana-2747	297	21	”	"	PUNCT
cana-2747	297	22	pattern	pattern	NOUN
cana-2747	297	23	recognit	recognit	VERB
cana-2747	297	24	.	.	PUNCT
cana-2747	298	1	lett	lett	PROPN
cana-2747	298	2	.	.	PROPN
cana-2747	298	3	,	,	PUNCT
cana-2747	298	4	vol	vol	NOUN
cana-2747	298	5	.	.	PUNCT
cana-2747	299	1	143	143	NUM
cana-2747	299	2	,	,	PUNCT
cana-2747	299	3	pp	pp	ADJ
cana-2747	299	4	.	.	PUNCT
cana-2747	300	1	122–129	122–129	NUM
cana-2747	300	2	,	,	PUNCT
cana-2747	300	3	2021	2021	NUM
cana-2747	300	4	,	,	PUNCT
cana-2747	300	5	doi	doi	NOUN
cana-2747	300	6	:	:	PUNCT
cana-2747	300	7	10.1016	10.1016	NUM
cana-2747	300	8	/	/	SYM
cana-2747	300	9	j.patrec.2021.01.004	j.patrec.2021.01.004	PROPN
cana-2747	300	10	.	.	PUNCT
cana-2747	301	1	[	[	X
cana-2747	301	2	19	19	NUM
cana-2747	301	3	]	]	PUNCT
cana-2747	301	4	z.	z.	PROPN
cana-2747	301	5	abdi	abdi	PROPN
cana-2747	301	6	et	et	PROPN
cana-2747	301	7	al	al	PROPN
cana-2747	301	8	.	.	PROPN
cana-2747	301	9	,	,	PUNCT
cana-2747	301	10	“	"	PUNCT
cana-2747	301	11	eeg	eeg	NOUN
cana-2747	301	12	channel	channel	NOUN
cana-2747	301	13	selection	selection	NOUN
cana-2747	301	14	for	for	ADP
cana-2747	301	15	person	person	NOUN
cana-2747	301	16	identification	identification	NOUN
cana-2747	301	17	using	use	VERB
cana-2747	301	18	binary	binary	ADJ
cana-2747	301	19	grey	grey	PROPN
cana-2747	301	20	wolf	wolf	PROPN
cana-2747	301	21	optimizer	optimizer	NOUN
cana-2747	301	22	,	,	PUNCT
cana-2747	301	23	”	"	PUNCT
cana-2747	301	24	vol	vol	NOUN
cana-2747	301	25	.	.	PROPN
cana-2747	301	26	10	10	NUM
cana-2747	301	27	,	,	PUNCT
cana-2747	301	28	2022	2022	NUM
cana-2747	301	29	,	,	PUNCT
cana-2747	301	30	doi	doi	NOUN
cana-2747	301	31	:	:	PUNCT
cana-2747	301	32	10.1109	10.1109	NUM
cana-2747	301	33	/	/	SYM
cana-2747	301	34	access.2021.3135805	access.2021.3135805	PROPN
cana-2747	301	35	.	.	PUNCT
cana-2747	302	1	[	[	X
cana-2747	302	2	20	20	NUM
cana-2747	302	3	]	]	X
cana-2747	302	4	t.	t.	NOUN
cana-2747	302	5	wilaiprasitporn	wilaiprasitporn	NOUN
cana-2747	302	6	,	,	PUNCT
cana-2747	302	7	a.	a.	NOUN
cana-2747	302	8	ditthapron	ditthapron	PROPN
cana-2747	302	9	,	,	PUNCT
cana-2747	302	10	k.	k.	PROPN
cana-2747	302	11	matchaparn	matchaparn	PROPN
cana-2747	302	12	,	,	PUNCT
cana-2747	302	13	t.	t.	PROPN
cana-2747	302	14	tongbuasirilai	tongbuasirilai	PROPN
cana-2747	302	15	,	,	PUNCT
cana-2747	302	16	n.	n.	PROPN
cana-2747	302	17	banluesombatkul	banluesombatkul	PROPN
cana-2747	302	18	,	,	PUNCT
cana-2747	302	19	and	and	CCONJ
cana-2747	302	20	e.	e.	PROPN
cana-2747	302	21	chuangsuwanich	chuangsuwanich	PROPN
cana-2747	302	22	,	,	PUNCT
cana-2747	302	23	“	"	PUNCT
cana-2747	302	24	affective	affective	ADJ
cana-2747	302	25	eeg	eeg	NOUN
cana-2747	302	26	-	-	PUNCT
cana-2747	302	27	based	base	VERB
cana-2747	302	28	person	person	NOUN
cana-2747	302	29	identification	identification	NOUN
cana-2747	302	30	using	use	VERB
cana-2747	302	31	the	the	DET
cana-2747	302	32	deep	deep	ADJ
cana-2747	302	33	learning	learning	NOUN
cana-2747	302	34	approach	approach	NOUN
cana-2747	302	35	,	,	PUNCT
cana-2747	302	36	”	"	PUNCT
cana-2747	302	37	in	in	ADP
cana-2747	302	38	ieee	ieee	NOUN
cana-2747	302	39	transactions	transaction	NOUN
cana-2747	302	40	on	on	ADP
cana-2747	302	41	cognitive	cognitive	ADJ
cana-2747	302	42	and	and	CCONJ
cana-2747	302	43	developmental	developmental	ADJ
cana-2747	302	44	systems	system	NOUN
cana-2747	302	45	,	,	PUNCT
cana-2747	302	46	ieee	ieee	NOUN
cana-2747	302	47	,	,	PUNCT
cana-2747	302	48	2020	2020	NUM
cana-2747	302	49	,	,	PUNCT
cana-2747	302	50	pp	pp	ADV
cana-2747	302	51	.	.	PUNCT
cana-2747	303	1	486–496	486–496	NUM
cana-2747	303	2	.	.	PUNCT
cana-2747	304	1	doi	doi	NOUN
cana-2747	304	2	:	:	PUNCT
cana-2747	304	3	10.1109	10.1109	NUM
cana-2747	304	4	/	/	SYM
cana-2747	304	5	tcds.2019.2924648	tcds.2019.2924648	NOUN
cana-2747	304	6	.	.	PUNCT
cana-2747	305	1	[	[	X
cana-2747	305	2	21	21	NUM
cana-2747	305	3	]	]	X
cana-2747	305	4	w.	w.	NOUN
cana-2747	305	5	alsumari	alsumari	PROPN
cana-2747	305	6	,	,	PUNCT
cana-2747	305	7	m.	m.	NOUN
cana-2747	305	8	hussain	hussain	PROPN
cana-2747	305	9	,	,	PUNCT
cana-2747	305	10	l.	l.	PROPN
cana-2747	305	11	alshehri	alshehri	PROPN
cana-2747	305	12	,	,	PUNCT
cana-2747	305	13	and	and	CCONJ
cana-2747	305	14	h.	h.	PROPN
cana-2747	305	15	a.	a.	PROPN
cana-2747	305	16	aboalsamh	aboalsamh	PROPN
cana-2747	305	17	,	,	PUNCT
cana-2747	305	18	“	"	PUNCT
cana-2747	305	19	eeg	eeg	NOUN
cana-2747	305	20	-	-	PUNCT
cana-2747	305	21	based	base	VERB
cana-2747	305	22	person	person	NOUN
cana-2747	305	23	identification	identification	NOUN
cana-2747	305	24	and	and	CCONJ
cana-2747	305	25	authentication	authentication	NOUN
cana-2747	305	26	using	use	VERB
cana-2747	305	27	deep	deep	ADJ
cana-2747	305	28	convolutional	convolutional	ADJ
cana-2747	305	29	neural	neural	ADJ
cana-2747	305	30	network	network	NOUN
cana-2747	305	31	,	,	PUNCT
cana-2747	305	32	”	"	PUNCT
cana-2747	305	33	axioms	axiom	NOUN
cana-2747	305	34	,	,	PUNCT
cana-2747	305	35	vol	vol	NOUN
cana-2747	305	36	.	.	PROPN
cana-2747	305	37	12	12	NUM
cana-2747	305	38	,	,	PUNCT
cana-2747	305	39	no	no	INTJ
cana-2747	305	40	.	.	NOUN
cana-2747	305	41	1	1	NUM
cana-2747	305	42	,	,	PUNCT
cana-2747	305	43	2023	2023	NUM
cana-2747	305	44	,	,	PUNCT
cana-2747	305	45	doi	doi	NOUN
cana-2747	305	46	:	:	PUNCT
cana-2747	305	47	10.3390	10.3390	NUM
cana-2747	305	48	/	/	SYM
cana-2747	305	49	axioms12010074	axioms12010074	PROPN
cana-2747	305	50	.	.	PUNCT
cana-2747	306	1	[	[	X
cana-2747	306	2	22	22	NUM
cana-2747	306	3	]	]	X
cana-2747	306	4	d.	d.	PROPN
cana-2747	306	5	zhang	zhang	PROPN
cana-2747	306	6	,	,	PUNCT
cana-2747	306	7	l.	l.	PROPN
cana-2747	306	8	yao	yao	PROPN
cana-2747	306	9	,	,	PUNCT
cana-2747	306	10	x.	x.	PROPN
cana-2747	306	11	zhang	zhang	PROPN
cana-2747	306	12	,	,	PUNCT
cana-2747	306	13	s.	s.	PROPN
cana-2747	306	14	wang	wang	PROPN
cana-2747	306	15	,	,	PUNCT
cana-2747	306	16	w.	w.	PROPN
cana-2747	306	17	chen	chen	PROPN
cana-2747	306	18	,	,	PUNCT
cana-2747	306	19	and	and	CCONJ
cana-2747	306	20	r.	r.	NOUN
cana-2747	306	21	boots	boot	NOUN
cana-2747	306	22	,	,	PUNCT
cana-2747	306	23	“	"	PUNCT
cana-2747	306	24	cascade	cascade	NOUN
cana-2747	306	25	and	and	CCONJ
cana-2747	306	26	parallel	parallel	ADJ
cana-2747	306	27	convolutional	convolutional	ADJ
cana-2747	306	28	recurrent	recurrent	ADJ
cana-2747	306	29	neural	neural	ADJ
cana-2747	306	30	networks	network	NOUN
cana-2747	306	31	on	on	ADP
cana-2747	306	32	eeg	eeg	NOUN
cana-2747	306	33	-	-	PUNCT
cana-2747	306	34	based	base	VERB
cana-2747	306	35	intention	intention	NOUN
cana-2747	306	36	recognition	recognition	NOUN
cana-2747	306	37	for	for	ADP
cana-2747	306	38	brain	brain	NOUN
cana-2747	306	39	computer	computer	NOUN
cana-2747	306	40	interface	interface	NOUN
cana-2747	306	41	,	,	PUNCT
cana-2747	306	42	”	"	PUNCT
cana-2747	306	43	32nd	32nd	ADJ
cana-2747	306	44	aaai	aaai	PROPN
cana-2747	306	45	conf	conf	NOUN
cana-2747	306	46	.	.	PUNCT
cana-2747	307	1	artif	artif	PROPN
cana-2747	307	2	.	.	PUNCT
cana-2747	308	1	intell	intell	PROPN
cana-2747	308	2	.	.	PUNCT
cana-2747	309	1	aaai	aaai	PROPN
cana-2747	309	2	2018	2018	NUM
cana-2747	309	3	,	,	PUNCT
cana-2747	309	4	no	no	INTJ
cana-2747	309	5	.	.	PUNCT
cana-2747	310	1	august	august	PROPN
cana-2747	310	2	,	,	PUNCT
cana-2747	310	3	pp	pp	ADP
cana-2747	310	4	.	.	PUNCT
cana-2747	311	1	1703–1710	1703–1710	NUM
cana-2747	311	2	,	,	PUNCT
cana-2747	311	3	2018	2018	NUM
cana-2747	311	4	,	,	PUNCT
cana-2747	311	5	doi	doi	NOUN
cana-2747	311	6	:	:	PUNCT
cana-2747	311	7	10.1609	10.1609	NUM
cana-2747	311	8	/	/	SYM
cana-2747	311	9	aaai.v32i1.11496	aaai.v32i1.11496	NOUN
cana-2747	311	10	.	.	PUNCT
cana-2747	312	1	[	[	X
cana-2747	312	2	23	23	NUM
cana-2747	312	3	]	]	X
cana-2747	312	4	i.	i.	PROPN
cana-2747	312	5	sander	sander	PROPN
cana-2747	312	6	koelstra	koelstra	PROPN
cana-2747	312	7	,	,	PUNCT
cana-2747	312	8	student	student	NOUN
cana-2747	312	9	member	member	NOUN
cana-2747	312	10	,	,	PUNCT
cana-2747	312	11	ieee	ieee	PROPN
cana-2747	312	12	,	,	PUNCT
cana-2747	312	13	christian	christian	PROPN
cana-2747	312	14	m¨uhl	m¨uhl	PROPN
cana-2747	312	15	,	,	PUNCT
cana-2747	312	16	mohammad	mohammad	PROPN
cana-2747	312	17	soleymani	soleymani	PROPN
cana-2747	312	18	,	,	PUNCT
cana-2747	312	19	student	student	NOUN
cana-2747	312	20	member	member	NOUN
cana-2747	312	21	,	,	PUNCT
cana-2747	312	22	ieee	ieee	PROPN
cana-2747	312	23	,	,	PUNCT
cana-2747	312	24	jongseok	jongseok	PROPN
cana-2747	312	25	lee	lee	PROPN
cana-2747	312	26	,	,	PUNCT
cana-2747	312	27	member	member	NOUN
cana-2747	312	28	,	,	PUNCT
cana-2747	312	29	ieee	ieee	PROPN
cana-2747	312	30	,	,	PUNCT
cana-2747	312	31	ashkan	ashkan	PROPN
cana-2747	312	32	yazdani	yazdani	PROPN
cana-2747	312	33	,	,	PUNCT
cana-2747	312	34	touradj	touradj	PROPN
cana-2747	312	35	ebrahimi	ebrahimi	PROPN
cana-2747	312	36	,	,	PUNCT
cana-2747	312	37	member	member	NOUN
cana-2747	312	38	,	,	PUNCT
cana-2747	312	39	ieee	ieee	PROPN
cana-2747	312	40	,	,	PUNCT
cana-2747	312	41	thierry	thierry	NOUN
cana-2747	312	42	pun	pun	NOUN
cana-2747	312	43	,	,	PUNCT
cana-2747	312	44	member	member	NOUN
cana-2747	312	45	,	,	PUNCT
cana-2747	312	46	ieee	ieee	PROPN
cana-2747	312	47	,	,	PUNCT
cana-2747	312	48	anton	anton	PROPN
cana-2747	312	49	nijholt	nijholt	PROPN
cana-2747	312	50	,	,	PUNCT
cana-2747	312	51	member	member	NOUN
cana-2747	312	52	,	,	PUNCT
cana-2747	312	53	ieee	ieee	PROPN
cana-2747	312	54	,	,	PUNCT
cana-2747	312	55	ioannis	ioannis	PROPN
cana-2747	312	56	patras	patras	PROPN
cana-2747	312	57	,	,	PUNCT
cana-2747	312	58	member	member	NOUN
cana-2747	312	59	and	and	CCONJ
cana-2747	312	60	abstract	abstract	ADJ
cana-2747	312	61	—	—	PUNCT
cana-2747	312	62	we	we	PRON
cana-2747	312	63	,	,	PUNCT
cana-2747	312	64	“	"	PUNCT
cana-2747	312	65	deap	deap	ADJ
cana-2747	312	66	:	:	PUNCT
cana-2747	312	67	a	a	DET
cana-2747	312	68	database	database	NOUN
cana-2747	312	69	for	for	ADP
cana-2747	312	70	emotion	emotion	NOUN
cana-2747	312	71	analysis	analysis	NOUN
cana-2747	312	72	using	use	VERB
cana-2747	312	73	physiological	physiological	ADJ
cana-2747	312	74	signals	signal	NOUN
cana-2747	312	75	,	,	PUNCT
cana-2747	312	76	”	"	PUNCT
cana-2747	312	77	ieee	ieee	NOUN
cana-2747	312	78	trans	tran	NOUN
cana-2747	312	79	.	.	PROPN
cana-2747	312	80	affect	affect	VERB
cana-2747	312	81	.	.	PUNCT
cana-2747	313	1	comput	comput	NOUN
cana-2747	313	2	.	.	PUNCT
cana-2747	313	3	,	,	PUNCT
cana-2747	313	4	2011	2011	NUM
cana-2747	313	5	.	.	PUNCT