id	sid	tid	token	lemma	pos
app01-10442	1	1	acta	acta	PROPN
app01-10442	1	2	polytechnica	polytechnica	PROPN
app01-10442	1	3	ctu	ctu	NOUN
app01-10442	1	4	proceedings	proceeding	NOUN
app01-10442	1	5	https://doi.org/10.14311/app.2024.51.0075	https://doi.org/10.14311/app.2024.51.0075	VERB
app01-10442	1	6	acta	acta	PROPN
app01-10442	1	7	polytechnica	polytechnica	PROPN
app01-10442	1	8	ctu	ctu	PROPN
app01-10442	1	9	proceedings	proceeding	NOUN
app01-10442	1	10	51:75–80	51:75–80	NUM
app01-10442	1	11	,	,	PUNCT
app01-10442	1	12	2024	2024	NUM
app01-10442	1	13	©	©	ADP
app01-10442	1	14	2024	2024	NUM
app01-10442	1	15	the	the	DET
app01-10442	1	16	author(s	author(s	NOUN
app01-10442	1	17	)	)	PUNCT
app01-10442	1	18	.	.	PUNCT
app01-10442	2	1	licensed	license	VERB
app01-10442	2	2	under	under	ADP
app01-10442	2	3	a	a	DET
app01-10442	2	4	cc	cc	NOUN
app01-10442	2	5	-	-	PUNCT
app01-10442	2	6	by	by	ADP
app01-10442	2	7	4.0	4.0	NUM
app01-10442	2	8	licence	licence	NOUN
app01-10442	2	9	published	publish	VERB
app01-10442	2	10	by	by	ADP
app01-10442	2	11	the	the	DET
app01-10442	2	12	czech	czech	PROPN
app01-10442	2	13	technical	technical	PROPN
app01-10442	2	14	university	university	PROPN
app01-10442	2	15	in	in	ADP
app01-10442	2	16	prague	prague	PROPN
app01-10442	2	17	automatic	automatic	ADJ
app01-10442	2	18	detection	detection	NOUN
app01-10442	2	19	of	of	ADP
app01-10442	2	20	sleep	sleep	NOUN
app01-10442	2	21	spindles	spindle	NOUN
app01-10442	2	22	by	by	ADP
app01-10442	2	23	neural	neural	ADJ
app01-10442	2	24	networks	network	NOUN
app01-10442	2	25	algorithms	algorithms	PROPN
app01-10442	2	26	jan	jan	PROPN
app01-10442	2	27	rychlík∗	rychlík∗	PROPN
app01-10442	2	28	,	,	PUNCT
app01-10442	2	29	roman	roman	PROPN
app01-10442	2	30	mouček	mouček	PROPN
app01-10442	2	31	university	university	PROPN
app01-10442	2	32	of	of	ADP
app01-10442	2	33	west	west	PROPN
app01-10442	2	34	bohemia	bohemia	PROPN
app01-10442	2	35	,	,	PUNCT
app01-10442	2	36	faculty	faculty	NOUN
app01-10442	2	37	of	of	ADP
app01-10442	2	38	applied	apply	VERB
app01-10442	2	39	sciences	science	NOUN
app01-10442	2	40	,	,	PUNCT
app01-10442	2	41	department	department	NOUN
app01-10442	2	42	of	of	ADP
app01-10442	2	43	computer	computer	NOUN
app01-10442	2	44	science	science	NOUN
app01-10442	2	45	,	,	PUNCT
app01-10442	2	46	univerzitní	univerzitní	NOUN
app01-10442	2	47	8	8	NUM
app01-10442	2	48	,	,	PUNCT
app01-10442	2	49	301	301	NUM
app01-10442	2	50	00	00	NUM
app01-10442	2	51	plzeň	plzeň	ADJ
app01-10442	2	52	,	,	PUNCT
app01-10442	2	53	czech	czech	PROPN
app01-10442	2	54	republic	republic	NOUN
app01-10442	2	55	∗	∗	NOUN
app01-10442	2	56	corresponding	correspond	VERB
app01-10442	2	57	author	author	NOUN
app01-10442	2	58	:	:	PUNCT
app01-10442	2	59	rychlikj@kiv.zcu.cz	rychlikj@kiv.zcu.cz	NOUN
app01-10442	2	60	abstract	abstract	NOUN
app01-10442	2	61	.	.	PUNCT
app01-10442	3	1	sleep	sleep	NOUN
app01-10442	3	2	constitutes	constitute	VERB
app01-10442	3	3	an	an	DET
app01-10442	3	4	essential	essential	ADJ
app01-10442	3	5	aspect	aspect	NOUN
app01-10442	3	6	of	of	ADP
app01-10442	3	7	human	human	ADJ
app01-10442	3	8	existence	existence	NOUN
app01-10442	3	9	,	,	PUNCT
app01-10442	3	10	with	with	ADP
app01-10442	3	11	the	the	DET
app01-10442	3	12	average	average	ADJ
app01-10442	3	13	individual	individual	NOUN
app01-10442	3	14	dedicating	dedicate	VERB
app01-10442	3	15	approximately	approximately	ADV
app01-10442	3	16	one	one	NUM
app01-10442	3	17	-	-	PUNCT
app01-10442	3	18	third	third	NOUN
app01-10442	3	19	of	of	ADP
app01-10442	3	20	their	their	PRON
app01-10442	3	21	life	life	NOUN
app01-10442	3	22	to	to	ADP
app01-10442	3	23	this	this	DET
app01-10442	3	24	physiological	physiological	ADJ
app01-10442	3	25	activity	activity	NOUN
app01-10442	3	26	.	.	PUNCT
app01-10442	4	1	consequently	consequently	ADV
app01-10442	4	2	,	,	PUNCT
app01-10442	4	3	comprehending	comprehending	ADJ
app01-10442	4	4	and	and	CCONJ
app01-10442	4	5	accurately	accurately	ADV
app01-10442	4	6	analyzing	analyze	VERB
app01-10442	4	7	sleep	sleep	NOUN
app01-10442	4	8	patterns	pattern	NOUN
app01-10442	4	9	is	be	AUX
app01-10442	4	10	of	of	ADP
app01-10442	4	11	paramount	paramount	ADJ
app01-10442	4	12	importance	importance	NOUN
app01-10442	4	13	.	.	PUNCT
app01-10442	5	1	this	this	DET
app01-10442	5	2	research	research	NOUN
app01-10442	5	3	aims	aim	VERB
app01-10442	5	4	to	to	PART
app01-10442	5	5	introduce	introduce	VERB
app01-10442	5	6	,	,	PUNCT
app01-10442	5	7	formulate	formulate	ADJ
app01-10442	5	8	,	,	PUNCT
app01-10442	5	9	execute	execute	NOUN
app01-10442	5	10	,	,	PUNCT
app01-10442	5	11	and	and	CCONJ
app01-10442	5	12	assess	assess	VERB
app01-10442	5	13	diverse	diverse	ADJ
app01-10442	5	14	machine	machine	NOUN
app01-10442	5	15	/	/	SYM
app01-10442	5	16	deep	deep	ADJ
app01-10442	5	17	learning	learning	NOUN
app01-10442	5	18	methodologies	methodology	NOUN
app01-10442	5	19	tailored	tailor	VERB
app01-10442	5	20	for	for	ADP
app01-10442	5	21	the	the	DET
app01-10442	5	22	processing	processing	NOUN
app01-10442	5	23	of	of	ADP
app01-10442	5	24	eeg	eeg	NOUN
app01-10442	5	25	signals	signal	NOUN
app01-10442	5	26	geared	gear	VERB
app01-10442	5	27	explicitly	explicitly	ADV
app01-10442	5	28	towards	towards	ADP
app01-10442	5	29	identifying	identify	VERB
app01-10442	5	30	sleep	sleep	NOUN
app01-10442	5	31	spindles	spindle	NOUN
app01-10442	5	32	.	.	PUNCT
app01-10442	6	1	the	the	DET
app01-10442	6	2	learning	learn	VERB
app01-10442	6	3	algorithms	algorithm	NOUN
app01-10442	6	4	underwent	undergo	VERB
app01-10442	6	5	training	training	NOUN
app01-10442	6	6	using	use	VERB
app01-10442	6	7	meticulously	meticulously	ADV
app01-10442	6	8	annotated	annotate	VERB
app01-10442	6	9	data	datum	NOUN
app01-10442	6	10	from	from	ADP
app01-10442	6	11	the	the	DET
app01-10442	6	12	montreal	montreal	PROPN
app01-10442	6	13	archive	archive	NOUN
app01-10442	6	14	of	of	ADP
app01-10442	6	15	sleep	sleep	NOUN
app01-10442	6	16	studies	study	NOUN
app01-10442	6	17	(	(	PUNCT
app01-10442	6	18	mass	mass	NOUN
app01-10442	6	19	)	)	PUNCT
app01-10442	6	20	data	datum	NOUN
app01-10442	6	21	center	center	NOUN
app01-10442	6	22	.	.	PUNCT
app01-10442	7	1	the	the	DET
app01-10442	7	2	convolutional	convolutional	ADJ
app01-10442	7	3	neural	neural	ADJ
app01-10442	7	4	network	network	NOUN
app01-10442	7	5	emerged	emerge	VERB
app01-10442	7	6	as	as	ADP
app01-10442	7	7	the	the	DET
app01-10442	7	8	most	most	ADV
app01-10442	7	9	effective	effective	ADJ
app01-10442	7	10	classification	classification	NOUN
app01-10442	7	11	model	model	NOUN
app01-10442	7	12	,	,	PUNCT
app01-10442	7	13	achieving	achieve	VERB
app01-10442	7	14	an	an	DET
app01-10442	7	15	accuracy	accuracy	NOUN
app01-10442	7	16	surpassing	surpass	VERB
app01-10442	7	17	67	67	NUM
app01-10442	7	18	%	%	NOUN
app01-10442	7	19	.	.	PUNCT
app01-10442	8	1	keywords	keyword	NOUN
app01-10442	8	2	:	:	PUNCT
app01-10442	8	3	deep	deep	ADJ
app01-10442	8	4	learning	learning	NOUN
app01-10442	8	5	,	,	PUNCT
app01-10442	8	6	eeg	eeg	PROPN
app01-10442	8	7	data	datum	NOUN
app01-10442	8	8	standards	standard	NOUN
app01-10442	8	9	,	,	PUNCT
app01-10442	8	10	eeg	eeg	PROPN
app01-10442	8	11	workflows	workflow	NOUN
app01-10442	8	12	,	,	PUNCT
app01-10442	8	13	eeg	eeg	NOUN
app01-10442	8	14	pipelines	pipeline	NOUN
app01-10442	8	15	,	,	PUNCT
app01-10442	8	16	electroencephalography	electroencephalography	NOUN
app01-10442	8	17	,	,	PUNCT
app01-10442	8	18	event	event	NOUN
app01-10442	8	19	-	-	PUNCT
app01-10442	8	20	related	relate	VERB
app01-10442	8	21	potentials	potential	NOUN
app01-10442	8	22	,	,	PUNCT
app01-10442	8	23	human	human	ADJ
app01-10442	8	24	brain	brain	NOUN
app01-10442	8	25	,	,	PUNCT
app01-10442	8	26	machine	machine	NOUN
app01-10442	8	27	learning	learning	NOUN
app01-10442	8	28	.	.	PUNCT
app01-10442	9	1	1	1	X
app01-10442	9	2	.	.	X
app01-10442	9	3	introduction	introduction	NOUN
app01-10442	9	4	sleep	sleep	NOUN
app01-10442	9	5	,	,	PUNCT
app01-10442	9	6	comprising	comprise	VERB
app01-10442	9	7	approximately	approximately	ADV
app01-10442	9	8	one	one	NUM
app01-10442	9	9	-	-	PUNCT
app01-10442	9	10	third	third	NOUN
app01-10442	9	11	of	of	ADP
app01-10442	9	12	human	human	ADJ
app01-10442	9	13	life	life	NOUN
app01-10442	9	14	,	,	PUNCT
app01-10442	9	15	is	be	AUX
app01-10442	9	16	crucial	crucial	ADJ
app01-10442	9	17	for	for	ADP
app01-10442	9	18	bodily	bodily	ADJ
app01-10442	9	19	rejuvenation	rejuvenation	NOUN
app01-10442	9	20	and	and	CCONJ
app01-10442	9	21	mental	mental	ADJ
app01-10442	9	22	relaxation	relaxation	NOUN
app01-10442	9	23	.	.	PUNCT
app01-10442	10	1	however	however	ADV
app01-10442	10	2	,	,	PUNCT
app01-10442	10	3	the	the	DET
app01-10442	10	4	prevalence	prevalence	NOUN
app01-10442	10	5	of	of	ADP
app01-10442	10	6	sleeping	sleep	VERB
app01-10442	10	7	disorders	disorder	NOUN
app01-10442	10	8	in	in	ADP
app01-10442	10	9	modern	modern	ADJ
app01-10442	10	10	society	society	NOUN
app01-10442	10	11	underscores	underscore	VERB
app01-10442	10	12	the	the	DET
app01-10442	10	13	significance	significance	NOUN
app01-10442	10	14	of	of	ADP
app01-10442	10	15	research	research	NOUN
app01-10442	10	16	in	in	ADP
app01-10442	10	17	this	this	DET
app01-10442	10	18	domain	domain	NOUN
app01-10442	10	19	to	to	PART
app01-10442	10	20	enhance	enhance	VERB
app01-10442	10	21	sleep	sleep	NOUN
app01-10442	10	22	quality	quality	NOUN
app01-10442	10	23	.	.	PUNCT
app01-10442	11	1	the	the	DET
app01-10442	11	2	brain	brain	NOUN
app01-10442	11	3	’s	’s	PART
app01-10442	11	4	activity	activity	NOUN
app01-10442	11	5	undergoes	undergo	VERB
app01-10442	11	6	distinct	distinct	ADJ
app01-10442	11	7	changes	change	NOUN
app01-10442	11	8	during	during	ADP
app01-10442	11	9	sleep	sleep	NOUN
app01-10442	11	10	,	,	PUNCT
app01-10442	11	11	categorized	categorize	VERB
app01-10442	11	12	into	into	ADP
app01-10442	11	13	rem	rem	NOUN
app01-10442	11	14	and	and	CCONJ
app01-10442	11	15	non	non	ADJ
app01-10442	11	16	-	-	ADJ
app01-10442	11	17	rem	rem	ADJ
app01-10442	11	18	phases	phase	NOUN
app01-10442	11	19	;	;	PUNCT
app01-10442	11	20	a	a	DET
app01-10442	11	21	specific	specific	ADJ
app01-10442	11	22	phenomenon	phenomenon	NOUN
app01-10442	11	23	within	within	ADP
app01-10442	11	24	the	the	DET
app01-10442	11	25	non	non	ADJ
app01-10442	11	26	-	-	ADJ
app01-10442	11	27	rem	rem	ADJ
app01-10442	11	28	phase	phase	NOUN
app01-10442	11	29	is	be	AUX
app01-10442	11	30	known	know	VERB
app01-10442	11	31	as	as	ADP
app01-10442	11	32	a	a	DET
app01-10442	11	33	sleep	sleep	NOUN
app01-10442	11	34	spindle	spindle	NOUN
app01-10442	11	35	.	.	PUNCT
app01-10442	12	1	sleep	sleep	NOUN
app01-10442	12	2	spindles	spindle	NOUN
app01-10442	12	3	are	be	AUX
app01-10442	12	4	brief	brief	ADJ
app01-10442	12	5	bursts	burst	NOUN
app01-10442	12	6	of	of	ADP
app01-10442	12	7	neural	neural	ADJ
app01-10442	12	8	oscillatory	oscillatory	ADJ
app01-10442	12	9	activity	activity	NOUN
app01-10442	12	10	during	during	ADP
app01-10442	12	11	non	non	ADJ
app01-10442	12	12	-	-	ADJ
app01-10442	12	13	rem	rem	ADJ
app01-10442	12	14	sleep	sleep	NOUN
app01-10442	12	15	and	and	CCONJ
app01-10442	12	16	play	play	VERB
app01-10442	12	17	a	a	DET
app01-10442	12	18	crucial	crucial	ADJ
app01-10442	12	19	role	role	NOUN
app01-10442	12	20	in	in	ADP
app01-10442	12	21	memory	memory	NOUN
app01-10442	12	22	consolidation	consolidation	NOUN
app01-10442	12	23	.	.	PUNCT
app01-10442	13	1	these	these	DET
app01-10442	13	2	spindle	spindle	NOUN
app01-10442	13	3	events	event	NOUN
app01-10442	13	4	are	be	AUX
app01-10442	13	5	essential	essential	ADJ
app01-10442	13	6	indicators	indicator	NOUN
app01-10442	13	7	of	of	ADP
app01-10442	13	8	sleep	sleep	NOUN
app01-10442	13	9	quality	quality	NOUN
app01-10442	13	10	and	and	CCONJ
app01-10442	13	11	cognitive	cognitive	ADJ
app01-10442	13	12	functions	function	NOUN
app01-10442	13	13	.	.	PUNCT
app01-10442	14	1	electroencephalography	electroencephalography	NOUN
app01-10442	14	2	(	(	PUNCT
app01-10442	14	3	eeg	eeg	PROPN
app01-10442	14	4	)	)	PUNCT
app01-10442	14	5	,	,	PUNCT
app01-10442	14	6	the	the	DET
app01-10442	14	7	fundamental	fundamental	ADJ
app01-10442	14	8	method	method	NOUN
app01-10442	14	9	and	and	CCONJ
app01-10442	14	10	technique	technique	NOUN
app01-10442	14	11	for	for	ADP
app01-10442	14	12	measuring	measure	VERB
app01-10442	14	13	and	and	CCONJ
app01-10442	14	14	collecting	collect	VERB
app01-10442	14	15	electrical	electrical	ADJ
app01-10442	14	16	activity	activity	NOUN
app01-10442	14	17	of	of	ADP
app01-10442	14	18	the	the	DET
app01-10442	14	19	human	human	ADJ
app01-10442	14	20	brain	brain	NOUN
app01-10442	14	21	,	,	PUNCT
app01-10442	14	22	is	be	AUX
app01-10442	14	23	also	also	ADV
app01-10442	14	24	used	use	VERB
app01-10442	14	25	in	in	ADP
app01-10442	14	26	sleep	sleep	NOUN
app01-10442	14	27	data	datum	NOUN
app01-10442	14	28	collection	collection	NOUN
app01-10442	14	29	;	;	PUNCT
app01-10442	14	30	their	their	PRON
app01-10442	14	31	abundance	abundance	NOUN
app01-10442	14	32	and	and	CCONJ
app01-10442	14	33	complexity	complexity	NOUN
app01-10442	14	34	necessitate	necessitate	ADJ
app01-10442	14	35	further	further	ADJ
app01-10442	14	36	computer	computer	NOUN
app01-10442	14	37	processing	processing	NOUN
app01-10442	14	38	.	.	PUNCT
app01-10442	15	1	this	this	PRON
app01-10442	15	2	mitigates	mitigate	VERB
app01-10442	15	3	human	human	ADJ
app01-10442	15	4	error	error	NOUN
app01-10442	15	5	and	and	CCONJ
app01-10442	15	6	promotes	promote	VERB
app01-10442	15	7	more	more	ADV
app01-10442	15	8	efficient	efficient	ADJ
app01-10442	15	9	and	and	CCONJ
app01-10442	15	10	accurate	accurate	ADJ
app01-10442	15	11	data	datum	NOUN
app01-10442	15	12	analysis	analysis	NOUN
app01-10442	15	13	.	.	PUNCT
app01-10442	16	1	machine	machine	NOUN
app01-10442	16	2	and	and	CCONJ
app01-10442	16	3	deep	deep	ADJ
app01-10442	16	4	learning	learning	NOUN
app01-10442	16	5	,	,	PUNCT
app01-10442	16	6	particularly	particularly	ADV
app01-10442	16	7	neural	neural	ADJ
app01-10442	16	8	networks	network	NOUN
app01-10442	16	9	such	such	ADJ
app01-10442	16	10	as	as	ADP
app01-10442	16	11	convolutional	convolutional	ADJ
app01-10442	16	12	neural	neural	ADJ
app01-10442	16	13	networks	network	NOUN
app01-10442	16	14	(	(	PUNCT
app01-10442	16	15	cnn	cnn	PROPN
app01-10442	16	16	)	)	PUNCT
app01-10442	16	17	,	,	PUNCT
app01-10442	16	18	long	long	ADJ
app01-10442	16	19	short	short	ADJ
app01-10442	16	20	-	-	PUNCT
app01-10442	16	21	term	term	NOUN
app01-10442	16	22	memory	memory	NOUN
app01-10442	16	23	networks	network	NOUN
app01-10442	16	24	(	(	PUNCT
app01-10442	16	25	lstm	lstm	NOUN
app01-10442	16	26	)	)	PUNCT
app01-10442	16	27	,	,	PUNCT
app01-10442	16	28	and	and	CCONJ
app01-10442	16	29	dense	dense	ADJ
app01-10442	16	30	networks	network	NOUN
app01-10442	16	31	,	,	PUNCT
app01-10442	16	32	offer	offer	VERB
app01-10442	16	33	a	a	DET
app01-10442	16	34	promising	promising	ADJ
app01-10442	16	35	approach	approach	NOUN
app01-10442	16	36	to	to	ADP
app01-10442	16	37	eeg	eeg	PROPN
app01-10442	16	38	signal	signal	NOUN
app01-10442	16	39	and	and	CCONJ
app01-10442	16	40	sleep	sleep	VERB
app01-10442	16	41	data	datum	NOUN
app01-10442	16	42	processing	processing	NOUN
app01-10442	16	43	.	.	PUNCT
app01-10442	17	1	this	this	DET
app01-10442	17	2	paper	paper	NOUN
app01-10442	17	3	focuses	focus	VERB
app01-10442	17	4	on	on	ADP
app01-10442	17	5	identifying	identify	VERB
app01-10442	17	6	sleep	sleep	NOUN
app01-10442	17	7	spindles	spindle	NOUN
app01-10442	17	8	.	.	PUNCT
app01-10442	18	1	this	this	PRON
app01-10442	18	2	is	be	AUX
app01-10442	18	3	accomplished	accomplish	VERB
app01-10442	18	4	by	by	ADP
app01-10442	18	5	designing	design	VERB
app01-10442	18	6	,	,	PUNCT
app01-10442	18	7	implementing	implement	VERB
app01-10442	18	8	,	,	PUNCT
app01-10442	18	9	and	and	CCONJ
app01-10442	18	10	assessing	assess	VERB
app01-10442	18	11	deep	deep	ADJ
app01-10442	18	12	learning	learning	NOUN
app01-10442	18	13	methods	method	NOUN
app01-10442	18	14	(	(	PUNCT
app01-10442	18	15	neural	neural	ADJ
app01-10442	18	16	networks	network	NOUN
app01-10442	18	17	)	)	PUNCT
app01-10442	18	18	.	.	PUNCT
app01-10442	19	1	the	the	DET
app01-10442	19	2	general	general	ADJ
app01-10442	19	3	aim	aim	NOUN
app01-10442	19	4	is	be	AUX
app01-10442	19	5	to	to	PART
app01-10442	19	6	improve	improve	VERB
app01-10442	19	7	understanding	understanding	NOUN
app01-10442	19	8	and	and	CCONJ
app01-10442	19	9	interpretation	interpretation	NOUN
app01-10442	19	10	of	of	ADP
app01-10442	19	11	eeg	eeg	PROPN
app01-10442	19	12	data	datum	NOUN
app01-10442	19	13	,	,	PUNCT
app01-10442	19	14	contribute	contribute	VERB
app01-10442	19	15	to	to	ADP
app01-10442	19	16	advancements	advancement	NOUN
app01-10442	19	17	in	in	ADP
app01-10442	19	18	automated	automate	VERB
app01-10442	19	19	sleep	sleep	NOUN
app01-10442	19	20	analysis	analysis	NOUN
app01-10442	19	21	,	,	PUNCT
app01-10442	19	22	and	and	CCONJ
app01-10442	19	23	enhance	enhance	VERB
app01-10442	19	24	our	our	PRON
app01-10442	19	25	knowledge	knowledge	NOUN
app01-10442	19	26	of	of	ADP
app01-10442	19	27	sleep	sleep	NOUN
app01-10442	19	28	-	-	PUNCT
app01-10442	19	29	related	relate	VERB
app01-10442	19	30	phenomena	phenomenon	NOUN
app01-10442	19	31	.	.	PUNCT
app01-10442	20	1	the	the	DET
app01-10442	20	2	paper	paper	NOUN
app01-10442	20	3	is	be	AUX
app01-10442	20	4	organized	organize	VERB
app01-10442	20	5	in	in	ADP
app01-10442	20	6	the	the	DET
app01-10442	20	7	following	following	ADJ
app01-10442	20	8	way	way	NOUN
app01-10442	20	9	.	.	PUNCT
app01-10442	21	1	the	the	DET
app01-10442	21	2	state	state	NOUN
app01-10442	21	3	-	-	PUNCT
app01-10442	21	4	of	of	ADP
app01-10442	21	5	-	-	PUNCT
app01-10442	21	6	the	the	DET
app01-10442	21	7	-	-	PUNCT
app01-10442	21	8	art	art	NOUN
app01-10442	21	9	section	section	NOUN
app01-10442	21	10	provides	provide	VERB
app01-10442	21	11	insight	insight	NOUN
app01-10442	21	12	into	into	ADP
app01-10442	21	13	eeg	eeg	NOUN
app01-10442	21	14	and	and	CCONJ
app01-10442	21	15	sleep	sleep	VERB
app01-10442	21	16	stages	stage	NOUN
app01-10442	21	17	classification	classification	NOUN
app01-10442	21	18	,	,	PUNCT
app01-10442	21	19	sleep	sleep	NOUN
app01-10442	21	20	spindle	spindle	NOUN
app01-10442	21	21	characteristics	characteristic	NOUN
app01-10442	21	22	,	,	PUNCT
app01-10442	21	23	and	and	CCONJ
app01-10442	21	24	sleep	sleep	VERB
app01-10442	21	25	data	datum	NOUN
app01-10442	21	26	platforms	platform	NOUN
app01-10442	21	27	and	and	CCONJ
app01-10442	21	28	archives	archive	NOUN
app01-10442	21	29	.	.	PUNCT
app01-10442	22	1	it	it	PRON
app01-10442	22	2	is	be	AUX
app01-10442	22	3	followed	follow	VERB
app01-10442	22	4	by	by	ADP
app01-10442	22	5	the	the	DET
app01-10442	22	6	sections	section	NOUN
app01-10442	22	7	describing	describe	VERB
app01-10442	22	8	the	the	DET
app01-10442	22	9	dataset	dataset	NOUN
app01-10442	22	10	and	and	CCONJ
app01-10442	22	11	neural	neural	ADJ
app01-10442	22	12	network	network	NOUN
app01-10442	22	13	architectures	architecture	NOUN
app01-10442	22	14	used	use	VERB
app01-10442	22	15	.	.	PUNCT
app01-10442	23	1	then	then	ADV
app01-10442	23	2	,	,	PUNCT
app01-10442	23	3	the	the	DET
app01-10442	23	4	dataset	dataset	NOUN
app01-10442	23	5	processing	processing	NOUN
app01-10442	23	6	is	be	AUX
app01-10442	23	7	presented	present	VERB
app01-10442	23	8	,	,	PUNCT
app01-10442	23	9	and	and	CCONJ
app01-10442	23	10	the	the	DET
app01-10442	23	11	results	result	NOUN
app01-10442	23	12	are	be	AUX
app01-10442	23	13	provided	provide	VERB
app01-10442	23	14	.	.	PUNCT
app01-10442	24	1	the	the	DET
app01-10442	24	2	outcomes	outcome	NOUN
app01-10442	24	3	and	and	CCONJ
app01-10442	24	4	future	future	ADJ
app01-10442	24	5	perspectives	perspective	NOUN
app01-10442	24	6	are	be	AUX
app01-10442	24	7	summarized	summarize	VERB
app01-10442	24	8	in	in	ADP
app01-10442	24	9	the	the	DET
app01-10442	24	10	conclusion	conclusion	NOUN
app01-10442	24	11	section	section	NOUN
app01-10442	24	12	.	.	PUNCT
app01-10442	25	1	2	2	X
app01-10442	25	2	.	.	X
app01-10442	25	3	state	state	NOUN
app01-10442	25	4	of	of	ADP
app01-10442	25	5	the	the	DET
app01-10442	25	6	art	art	NOUN
app01-10442	25	7	the	the	DET
app01-10442	25	8	typical	typical	ADJ
app01-10442	25	9	use	use	NOUN
app01-10442	25	10	case	case	NOUN
app01-10442	25	11	in	in	ADP
app01-10442	25	12	eeg	eeg	PROPN
app01-10442	25	13	signal	signal	NOUN
app01-10442	25	14	classification	classification	NOUN
app01-10442	25	15	is	be	AUX
app01-10442	25	16	to	to	PART
app01-10442	25	17	compare	compare	VERB
app01-10442	25	18	methods	method	NOUN
app01-10442	25	19	for	for	ADP
app01-10442	25	20	categorizing	categorize	VERB
app01-10442	25	21	preictal	preictal	ADJ
app01-10442	25	22	,	,	PUNCT
app01-10442	25	23	postictal	postictal	NOUN
app01-10442	25	24	,	,	PUNCT
app01-10442	25	25	and	and	CCONJ
app01-10442	25	26	interictal	interictal	ADJ
app01-10442	25	27	classes	class	NOUN
app01-10442	25	28	when	when	SCONJ
app01-10442	25	29	epileptic	epileptic	ADJ
app01-10442	25	30	seizures	seizure	NOUN
app01-10442	25	31	are	be	AUX
app01-10442	25	32	detected	detect	VERB
app01-10442	25	33	.	.	PUNCT
app01-10442	26	1	the	the	DET
app01-10442	26	2	model	model	NOUN
app01-10442	26	3	proposed	propose	VERB
app01-10442	26	4	in	in	ADP
app01-10442	26	5	[	[	X
app01-10442	26	6	1	1	NUM
app01-10442	26	7	]	]	PUNCT
app01-10442	26	8	integrated	integrate	VERB
app01-10442	26	9	a	a	DET
app01-10442	26	10	twolayer	twolayer	NOUN
app01-10442	26	11	lstm	lstm	NOUN
app01-10442	26	12	and	and	CCONJ
app01-10442	26	13	a	a	DET
app01-10442	26	14	four	four	NUM
app01-10442	26	15	-	-	PUNCT
app01-10442	26	16	layer	layer	NOUN
app01-10442	26	17	enhanced	enhance	VERB
app01-10442	26	18	neural	neural	ADJ
app01-10442	26	19	network	network	NOUN
app01-10442	26	20	(	(	PUNCT
app01-10442	26	21	nn	nn	NOUN
app01-10442	26	22	)	)	PUNCT
app01-10442	26	23	deep	deep	ADJ
app01-10442	26	24	learning	learning	NOUN
app01-10442	26	25	architecture	architecture	NOUN
app01-10442	26	26	using	use	VERB
app01-10442	26	27	improved	improve	VERB
app01-10442	26	28	one	one	NUM
app01-10442	26	29	-	-	PUNCT
app01-10442	26	30	dimensional	dimensional	ADJ
app01-10442	26	31	gradient	gradient	ADJ
app01-10442	26	32	descent	descent	NOUN
app01-10442	26	33	activation	activation	NOUN
app01-10442	26	34	functions	function	NOUN
app01-10442	26	35	.	.	PUNCT
app01-10442	27	1	the	the	DET
app01-10442	27	2	study	study	NOUN
app01-10442	27	3	used	use	VERB
app01-10442	27	4	the	the	DET
app01-10442	27	5	pre	pre	ADJ
app01-10442	27	6	-	-	ADJ
app01-10442	27	7	processed	process	VERB
app01-10442	27	8	bonn	bonn	PROPN
app01-10442	27	9	university	university	NOUN
app01-10442	27	10	database	database	NOUN
app01-10442	27	11	;	;	PUNCT
app01-10442	27	12	statistical	statistical	ADJ
app01-10442	27	13	features	feature	NOUN
app01-10442	27	14	were	be	AUX
app01-10442	27	15	extracted	extract	VERB
app01-10442	27	16	.	.	PUNCT
app01-10442	28	1	conventional	conventional	ADJ
app01-10442	28	2	methods	method	NOUN
app01-10442	28	3	used	use	VERB
app01-10442	28	4	for	for	ADP
app01-10442	28	5	the	the	DET
app01-10442	28	6	classification	classification	NOUN
app01-10442	28	7	included	include	VERB
app01-10442	28	8	support	support	NOUN
app01-10442	28	9	vector	vector	NOUN
app01-10442	28	10	machines	machine	NOUN
app01-10442	28	11	(	(	PUNCT
app01-10442	28	12	svm	svm	PROPN
app01-10442	28	13	)	)	PUNCT
app01-10442	28	14	with	with	ADP
app01-10442	28	15	different	different	ADJ
app01-10442	28	16	kernels	kernel	NOUN
app01-10442	28	17	,	,	PUNCT
app01-10442	28	18	logistic	logistic	ADJ
app01-10442	28	19	regression	regression	NOUN
app01-10442	28	20	,	,	PUNCT
app01-10442	28	21	and	and	CCONJ
app01-10442	28	22	nns	nn	NOUN
app01-10442	28	23	.	.	PUNCT
app01-10442	29	1	the	the	DET
app01-10442	29	2	results	result	NOUN
app01-10442	29	3	showed	show	VERB
app01-10442	29	4	that	that	SCONJ
app01-10442	29	5	the	the	DET
app01-10442	29	6	improved	improved	ADJ
app01-10442	29	7	nn	nn	PROPN
app01-10442	29	8	algorithm	algorithm	NOUN
app01-10442	29	9	achieved	achieve	VERB
app01-10442	29	10	the	the	DET
app01-10442	29	11	highest	high	ADJ
app01-10442	29	12	accuracy	accuracy	NOUN
app01-10442	29	13	(	(	PUNCT
app01-10442	29	14	nearly	nearly	ADV
app01-10442	29	15	79	79	NUM
app01-10442	29	16	%	%	NOUN
app01-10442	29	17	)	)	PUNCT
app01-10442	29	18	,	,	PUNCT
app01-10442	29	19	surpassing	surpass	VERB
app01-10442	29	20	lstm	lstm	NOUN
app01-10442	29	21	(	(	PUNCT
app01-10442	29	22	71	71	NUM
app01-10442	29	23	%	%	NOUN
app01-10442	29	24	)	)	PUNCT
app01-10442	29	25	,	,	PUNCT
app01-10442	29	26	nn	nn	X
app01-10442	29	27	neural	neural	ADJ
app01-10442	29	28	network	network	NOUN
app01-10442	29	29	(	(	PUNCT
app01-10442	29	30	61	61	NUM
app01-10442	29	31	%	%	NOUN
app01-10442	29	32	)	)	PUNCT
app01-10442	29	33	,	,	PUNCT
app01-10442	29	34	and	and	CCONJ
app01-10442	29	35	svm	svm	ADJ
app01-10442	29	36	(	(	PUNCT
app01-10442	29	37	70	70	NUM
app01-10442	29	38	%	%	NOUN
app01-10442	29	39	)	)	PUNCT
app01-10442	29	40	,	,	PUNCT
app01-10442	29	41	while	while	SCONJ
app01-10442	29	42	logistic	logistic	ADJ
app01-10442	29	43	regression	regression	NOUN
app01-10442	29	44	had	have	VERB
app01-10442	29	45	the	the	DET
app01-10442	29	46	lowest	low	ADJ
app01-10442	29	47	accuracy	accuracy	NOUN
app01-10442	29	48	(	(	PUNCT
app01-10442	29	49	about	about	ADV
app01-10442	29	50	53	53	NUM
app01-10442	29	51	%	%	NOUN
app01-10442	29	52	)	)	PUNCT
app01-10442	30	1	[	[	X
app01-10442	30	2	1	1	NUM
app01-10442	30	3	]	]	PUNCT
app01-10442	30	4	.	.	PUNCT
app01-10442	31	1	in	in	ADP
app01-10442	31	2	collaboration	collaboration	NOUN
app01-10442	31	3	with	with	ADP
app01-10442	31	4	the	the	DET
app01-10442	31	5	department	department	NOUN
app01-10442	31	6	of	of	ADP
app01-10442	31	7	medical	medical	ADJ
app01-10442	31	8	engineering	engineering	NOUN
app01-10442	31	9	and	and	CCONJ
app01-10442	31	10	technomathematics	technomathematic	NOUN
app01-10442	31	11	in	in	ADP
app01-10442	31	12	germany	germany	PROPN
app01-10442	31	13	,	,	PUNCT
app01-10442	31	14	aachen	aachen	PROPN
app01-10442	31	15	university	university	PROPN
app01-10442	31	16	of	of	ADP
app01-10442	31	17	applied	apply	VERB
app01-10442	31	18	sciences	science	NOUN
app01-10442	31	19	used	use	VERB
app01-10442	31	20	a	a	DET
app01-10442	31	21	machine	machine	NOUN
app01-10442	31	22	learning	learn	VERB
app01-10442	31	23	approach	approach	NOUN
app01-10442	31	24	[	[	X
app01-10442	31	25	2	2	X
app01-10442	31	26	]	]	PUNCT
app01-10442	31	27	to	to	PART
app01-10442	31	28	score	score	VERB
app01-10442	31	29	pre	pre	ADJ
app01-10442	31	30	-	-	ADJ
app01-10442	31	31	rem	rem	VERB
app01-10442	31	32	sleep	sleep	NOUN
app01-10442	31	33	stages	stage	NOUN
app01-10442	31	34	in	in	ADP
app01-10442	31	35	mice	mouse	NOUN
app01-10442	31	36	automatically	automatically	ADV
app01-10442	31	37	.	.	PUNCT
app01-10442	32	1	using	use	VERB
app01-10442	32	2	a	a	DET
app01-10442	32	3	dataset	dataset	NOUN
app01-10442	32	4	of	of	ADP
app01-10442	32	5	polysomnographic	polysomnographic	ADJ
app01-10442	32	6	recordings	recording	NOUN
app01-10442	32	7	from	from	ADP
app01-10442	32	8	18	18	NUM
app01-10442	32	9	mice	mouse	NOUN
app01-10442	32	10	over	over	ADP
app01-10442	32	11	52	52	NUM
app01-10442	32	12	days	day	NOUN
app01-10442	32	13	,	,	PUNCT
app01-10442	32	14	the	the	DET
app01-10442	32	15	study	study	NOUN
app01-10442	32	16	investigated	investigate	VERB
app01-10442	32	17	the	the	DET
app01-10442	32	18	impact	impact	NOUN
app01-10442	32	19	of	of	ADP
app01-10442	32	20	dietary	dietary	ADJ
app01-10442	32	21	variation	variation	NOUN
app01-10442	32	22	on	on	ADP
app01-10442	32	23	sleep	sleep	NOUN
app01-10442	32	24	.	.	PUNCT
app01-10442	33	1	the	the	DET
app01-10442	33	2	mice	mouse	NOUN
app01-10442	33	3	,	,	PUNCT
app01-10442	33	4	chronically	chronically	ADV
app01-10442	33	5	implanted	implant	VERB
app01-10442	33	6	with	with	ADP
app01-10442	33	7	eeg	eeg	PROPN
app01-10442	33	8	and	and	CCONJ
app01-10442	33	9	emg	emg	NOUN
app01-10442	33	10	electrodes	electrode	NOUN
app01-10442	33	11	,	,	PUNCT
app01-10442	33	12	underwent	underwent	ADJ
app01-10442	33	13	data	datum	NOUN
app01-10442	33	14	pre	pre	NOUN
app01-10442	33	15	-	-	NOUN
app01-10442	33	16	processing	processing	ADJ
app01-10442	33	17	,	,	PUNCT
app01-10442	33	18	75	75	NUM
app01-10442	33	19	https://doi.org/10.14311/app.2024.51.0075	https://doi.org/10.14311/app.2024.51.0075	PROPN
app01-10442	33	20	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
app01-10442	33	21	https://www.cvut.cz/en	https://www.cvut.cz/en	PROPN
app01-10442	33	22	jan	jan	PROPN
app01-10442	33	23	rychlík	rychlík	PROPN
app01-10442	33	24	,	,	PUNCT
app01-10442	33	25	roman	roman	ADJ
app01-10442	33	26	mouček	mouček	PROPN
app01-10442	33	27	acta	acta	PROPN
app01-10442	33	28	polytechnica	polytechnica	PROPN
app01-10442	33	29	ctu	ctu	NOUN
app01-10442	33	30	proceedings	proceeding	NOUN
app01-10442	33	31	including	include	VERB
app01-10442	33	32	low	low	ADJ
app01-10442	33	33	-	-	PUNCT
app01-10442	33	34	pass	pass	NOUN
app01-10442	33	35	filtering	filtering	NOUN
app01-10442	33	36	and	and	CCONJ
app01-10442	33	37	synthetic	synthetic	ADJ
app01-10442	33	38	data	datum	NOUN
app01-10442	33	39	augmentation	augmentation	NOUN
app01-10442	33	40	for	for	ADP
app01-10442	33	41	a	a	DET
app01-10442	33	42	balanced	balanced	ADJ
app01-10442	33	43	training	training	NOUN
app01-10442	33	44	set	set	NOUN
app01-10442	33	45	.	.	PUNCT
app01-10442	34	1	the	the	DET
app01-10442	34	2	neural	neural	ADJ
app01-10442	34	3	network	network	NOUN
app01-10442	34	4	architecture	architecture	NOUN
app01-10442	34	5	,	,	PUNCT
app01-10442	34	6	consisting	consist	VERB
app01-10442	34	7	of	of	ADP
app01-10442	34	8	eight	eight	NUM
app01-10442	34	9	convolutional	convolutional	ADJ
app01-10442	34	10	layers	layer	NOUN
app01-10442	34	11	and	and	CCONJ
app01-10442	34	12	a	a	DET
app01-10442	34	13	classifier	classifier	NOUN
app01-10442	34	14	with	with	ADP
app01-10442	34	15	two	two	NUM
app01-10442	34	16	fully	fully	ADV
app01-10442	34	17	connected	connected	ADJ
app01-10442	34	18	layers	layer	NOUN
app01-10442	34	19	,	,	PUNCT
app01-10442	34	20	demonstrated	demonstrate	VERB
app01-10442	34	21	high	high	ADJ
app01-10442	34	22	accuracy	accuracy	NOUN
app01-10442	34	23	in	in	ADP
app01-10442	34	24	classifying	classify	VERB
app01-10442	34	25	wake	wake	NOUN
app01-10442	34	26	,	,	PUNCT
app01-10442	34	27	rem	rem	X
app01-10442	34	28	,	,	PUNCT
app01-10442	34	29	and	and	CCONJ
app01-10442	34	30	nrem	nrem	PROPN
app01-10442	34	31	segments	segment	NOUN
app01-10442	34	32	,	,	PUNCT
app01-10442	34	33	achieving	achieve	VERB
app01-10442	34	34	over	over	ADP
app01-10442	34	35	98	98	NUM
app01-10442	34	36	%	%	NOUN
app01-10442	34	37	,	,	PUNCT
app01-10442	34	38	more	more	ADJ
app01-10442	34	39	than	than	ADP
app01-10442	34	40	94	94	NUM
app01-10442	34	41	%	%	NOUN
app01-10442	34	42	,	,	PUNCT
app01-10442	34	43	and	and	CCONJ
app01-10442	34	44	close	close	ADJ
app01-10442	34	45	to	to	ADP
app01-10442	34	46	92	92	NUM
app01-10442	34	47	%	%	NOUN
app01-10442	34	48	accuracy	accuracy	NOUN
app01-10442	34	49	,	,	PUNCT
app01-10442	34	50	respectively	respectively	ADV
app01-10442	34	51	.	.	PUNCT
app01-10442	35	1	the	the	DET
app01-10442	35	2	pre	pre	ADJ
app01-10442	35	3	-	-	ADJ
app01-10442	35	4	rem	rem	ADJ
app01-10442	35	5	stage	stage	NOUN
app01-10442	35	6	was	be	AUX
app01-10442	35	7	correctly	correctly	ADV
app01-10442	35	8	classified	classify	VERB
app01-10442	35	9	in	in	ADP
app01-10442	35	10	58	58	NUM
app01-10442	35	11	%	%	NOUN
app01-10442	35	12	of	of	ADP
app01-10442	35	13	the	the	DET
app01-10442	35	14	segments	segment	NOUN
app01-10442	35	15	.	.	PUNCT
app01-10442	36	1	the	the	DET
app01-10442	36	2	classifier	classifier	NOUN
app01-10442	36	3	showed	show	VERB
app01-10442	36	4	robust	robust	ADJ
app01-10442	36	5	performance	performance	NOUN
app01-10442	36	6	,	,	PUNCT
app01-10442	36	7	correctly	correctly	ADV
app01-10442	36	8	predicting	predict	VERB
app01-10442	36	9	human	human	ADJ
app01-10442	36	10	-	-	PUNCT
app01-10442	36	11	expert	expert	NOUN
app01-10442	36	12	assigned	assign	VERB
app01-10442	36	13	stages	stage	NOUN
app01-10442	36	14	for	for	ADP
app01-10442	36	15	segments	segment	NOUN
app01-10442	36	16	predicted	predict	VERB
app01-10442	36	17	to	to	PART
app01-10442	36	18	be	be	AUX
app01-10442	36	19	wake	wake	VERB
app01-10442	36	20	,	,	PUNCT
app01-10442	36	21	rem	rem	X
app01-10442	36	22	,	,	PUNCT
app01-10442	36	23	and	and	CCONJ
app01-10442	36	24	nrem	nrem	PROPN
app01-10442	36	25	,	,	PUNCT
app01-10442	36	26	demonstrating	demonstrate	VERB
app01-10442	36	27	the	the	DET
app01-10442	36	28	effectiveness	effectiveness	NOUN
app01-10442	36	29	of	of	ADP
app01-10442	36	30	the	the	DET
app01-10442	36	31	network	network	NOUN
app01-10442	36	32	in	in	ADP
app01-10442	36	33	the	the	DET
app01-10442	36	34	automated	automate	VERB
app01-10442	36	35	classification	classification	NOUN
app01-10442	36	36	of	of	ADP
app01-10442	36	37	sleep	sleep	NOUN
app01-10442	36	38	stages	stage	NOUN
app01-10442	36	39	in	in	ADP
app01-10442	36	40	mice	mouse	NOUN
app01-10442	36	41	[	[	X
app01-10442	36	42	2	2	NUM
app01-10442	36	43	]	]	PUNCT
app01-10442	36	44	.	.	PUNCT
app01-10442	37	1	a	a	DET
app01-10442	37	2	1d	1d	NUM
app01-10442	37	3	cnn	cnn	PROPN
app01-10442	37	4	-	-	PUNCT
app01-10442	37	5	lstm	lstm	ADJ
app01-10442	37	6	algorithm	algorithm	NOUN
app01-10442	37	7	for	for	ADP
app01-10442	37	8	automatic	automatic	ADJ
app01-10442	37	9	sleep	sleep	NOUN
app01-10442	37	10	staging	stage	VERB
app01-10442	37	11	(	(	PUNCT
app01-10442	37	12	wake	wake	VERB
app01-10442	37	13	,	,	PUNCT
app01-10442	37	14	rem	rem	NOUN
app01-10442	37	15	,	,	PUNCT
app01-10442	37	16	non	non	ADJ
app01-10442	37	17	-	-	ADJ
app01-10442	37	18	rem	rem	ADJ
app01-10442	37	19	)	)	PUNCT
app01-10442	37	20	on	on	ADP
app01-10442	37	21	the	the	DET
app01-10442	37	22	sleep	sleep	NOUN
app01-10442	37	23	-	-	PUNCT
app01-10442	37	24	edf	edf	PROPN
app01-10442	37	25	dataset	dataset	NOUN
app01-10442	37	26	,	,	PUNCT
app01-10442	37	27	achieving	achieve	VERB
app01-10442	37	28	93.47	93.47	NUM
app01-10442	37	29	%	%	NOUN
app01-10442	37	30	accuracy	accuracy	NOUN
app01-10442	37	31	with	with	ADP
app01-10442	37	32	the	the	DET
app01-10442	37	33	fpz	fpz	NOUN
app01-10442	37	34	-	-	PUNCT
app01-10442	37	35	cz	cz	NOUN
app01-10442	37	36	eeg	eeg	PROPN
app01-10442	37	37	channel	channel	NOUN
app01-10442	37	38	,	,	PUNCT
app01-10442	37	39	is	be	AUX
app01-10442	37	40	described	describe	VERB
app01-10442	37	41	in	in	ADP
app01-10442	37	42	[	[	X
app01-10442	37	43	3	3	NUM
app01-10442	37	44	]	]	PUNCT
app01-10442	37	45	.	.	PUNCT
app01-10442	38	1	the	the	DET
app01-10442	38	2	dataset	dataset	NOUN
app01-10442	38	3	comprises	comprise	VERB
app01-10442	38	4	197	197	NUM
app01-10442	38	5	polysomnographic	polysomnographic	ADJ
app01-10442	38	6	sleep	sleep	NOUN
app01-10442	38	7	recordings	recording	NOUN
app01-10442	38	8	with	with	ADP
app01-10442	38	9	manually	manually	ADV
app01-10442	38	10	scored	score	VERB
app01-10442	38	11	hypnograms	hypnogram	NOUN
app01-10442	38	12	.	.	PUNCT
app01-10442	39	1	with	with	ADP
app01-10442	39	2	seven	seven	NUM
app01-10442	39	3	layers	layer	NOUN
app01-10442	39	4	(	(	PUNCT
app01-10442	39	5	four	four	NUM
app01-10442	39	6	1d	1d	NUM
app01-10442	39	7	cnn	cnn	NOUN
app01-10442	39	8	and	and	CCONJ
app01-10442	39	9	three	three	NUM
app01-10442	39	10	lstm	lstm	ADJ
app01-10442	39	11	layers	layer	NOUN
app01-10442	39	12	)	)	PUNCT
app01-10442	39	13	,	,	PUNCT
app01-10442	39	14	the	the	DET
app01-10442	39	15	algorithm	algorithm	NOUN
app01-10442	39	16	exhibited	exhibit	VERB
app01-10442	39	17	robust	robust	ADJ
app01-10442	39	18	performance	performance	NOUN
app01-10442	39	19	across	across	ADP
app01-10442	39	20	various	various	ADJ
app01-10442	39	21	physiological	physiological	ADJ
app01-10442	39	22	signals	signal	NOUN
app01-10442	39	23	.	.	PUNCT
app01-10442	40	1	evaluations	evaluation	NOUN
app01-10442	40	2	on	on	ADP
app01-10442	40	3	single	single	ADJ
app01-10442	40	4	-	-	PUNCT
app01-10442	40	5	channel	channel	NOUN
app01-10442	40	6	eeg	eeg	NOUN
app01-10442	40	7	and	and	CCONJ
app01-10442	40	8	eog	eog	PROPN
app01-10442	40	9	classifications	classification	NOUN
app01-10442	40	10	,	,	PUNCT
app01-10442	40	11	using	use	VERB
app01-10442	40	12	five	five	NUM
app01-10442	40	13	test	test	NOUN
app01-10442	40	14	sets	set	NOUN
app01-10442	40	15	for	for	ADP
app01-10442	40	16	each	each	DET
app01-10442	40	17	group	group	NOUN
app01-10442	40	18	,	,	PUNCT
app01-10442	40	19	confirmed	confirm	VERB
app01-10442	40	20	the	the	DET
app01-10442	40	21	model	model	NOUN
app01-10442	40	22	’s	’s	PART
app01-10442	40	23	reliability	reliability	NOUN
app01-10442	40	24	.	.	PUNCT
app01-10442	41	1	achieving	achieve	VERB
app01-10442	41	2	94.15	94.15	NUM
app01-10442	41	3	%	%	NOUN
app01-10442	41	4	accuracy	accuracy	NOUN
app01-10442	41	5	when	when	SCONJ
app01-10442	41	6	incorporating	incorporate	VERB
app01-10442	41	7	fpz	fpz	NOUN
app01-10442	41	8	-	-	PUNCT
app01-10442	41	9	cz	cz	NOUN
app01-10442	41	10	eeg	eeg	NOUN
app01-10442	41	11	and	and	CCONJ
app01-10442	41	12	eog	eog	PROPN
app01-10442	41	13	signals	signal	NOUN
app01-10442	41	14	,	,	PUNCT
app01-10442	41	15	the	the	DET
app01-10442	41	16	algorithm	algorithm	NOUN
app01-10442	41	17	demonstrates	demonstrate	VERB
app01-10442	41	18	promise	promise	NOUN
app01-10442	41	19	for	for	ADP
app01-10442	41	20	automated	automate	VERB
app01-10442	41	21	sleep	sleep	NOUN
app01-10442	41	22	staging	stage	VERB
app01-10442	41	23	in	in	ADP
app01-10442	41	24	future	future	ADJ
app01-10442	41	25	sleep	sleep	NOUN
app01-10442	41	26	-	-	PUNCT
app01-10442	41	27	related	relate	VERB
app01-10442	41	28	research	research	NOUN
app01-10442	41	29	.	.	PUNCT
app01-10442	42	1	it	it	PRON
app01-10442	42	2	offers	offer	VERB
app01-10442	42	3	an	an	DET
app01-10442	42	4	efficient	efficient	ADJ
app01-10442	42	5	alternative	alternative	NOUN
app01-10442	42	6	to	to	ADP
app01-10442	42	7	manual	manual	ADJ
app01-10442	42	8	expert	expert	NOUN
app01-10442	42	9	inspection	inspection	NOUN
app01-10442	42	10	in	in	ADP
app01-10442	42	11	large	large	ADJ
app01-10442	42	12	-	-	PUNCT
app01-10442	42	13	scale	scale	NOUN
app01-10442	42	14	polysomnography	polysomnography	NOUN
app01-10442	42	15	(	(	PUNCT
app01-10442	42	16	psg	psg	PROPN
app01-10442	42	17	)	)	PUNCT
app01-10442	42	18	signal	signal	NOUN
app01-10442	42	19	analysis	analysis	NOUN
app01-10442	42	20	,	,	PUNCT
app01-10442	42	21	showcasing	showcase	VERB
app01-10442	42	22	the	the	DET
app01-10442	42	23	effectiveness	effectiveness	NOUN
app01-10442	42	24	of	of	ADP
app01-10442	42	25	deep	deep	ADJ
app01-10442	42	26	learning	learning	NOUN
app01-10442	42	27	in	in	ADP
app01-10442	42	28	discerning	discern	VERB
app01-10442	42	29	similar	similar	ADJ
app01-10442	42	30	sleep	sleep	NOUN
app01-10442	42	31	periods	period	NOUN
app01-10442	42	32	[	[	X
app01-10442	42	33	3	3	NUM
app01-10442	42	34	]	]	PUNCT
app01-10442	42	35	.	.	PUNCT
app01-10442	43	1	figure	figure	NOUN
app01-10442	43	2	1	1	NUM
app01-10442	43	3	displays	display	VERB
app01-10442	43	4	a	a	DET
app01-10442	43	5	characteristic	characteristic	ADJ
app01-10442	43	6	sleep	sleep	NOUN
app01-10442	43	7	spindle	spindle	NOUN
app01-10442	43	8	evident	evident	ADJ
app01-10442	43	9	in	in	ADP
app01-10442	43	10	the	the	DET
app01-10442	43	11	eeg	eeg	NOUN
app01-10442	43	12	waveform	waveform	NOUN
app01-10442	43	13	during	during	ADP
app01-10442	43	14	non	non	ADJ
app01-10442	43	15	-	-	ADJ
app01-10442	43	16	rapid	rapid	ADJ
app01-10442	43	17	eye	eye	NOUN
app01-10442	43	18	movement	movement	NOUN
app01-10442	43	19	(	(	PUNCT
app01-10442	43	20	non	non	ADJ
app01-10442	43	21	-	-	ADJ
app01-10442	43	22	rem	rem	ADJ
app01-10442	43	23	)	)	PUNCT
app01-10442	43	24	sleep	sleep	NOUN
app01-10442	43	25	.	.	PUNCT
app01-10442	44	1	this	this	DET
app01-10442	44	2	spindle	spindle	NOUN
app01-10442	44	3	,	,	PUNCT
app01-10442	44	4	observed	observe	VERB
app01-10442	44	5	in	in	ADP
app01-10442	44	6	frontal	frontal	ADJ
app01-10442	44	7	and	and	CCONJ
app01-10442	44	8	central	central	ADJ
app01-10442	44	9	brain	brain	NOUN
app01-10442	44	10	regions	region	NOUN
app01-10442	44	11	,	,	PUNCT
app01-10442	44	12	manifests	manifest	NOUN
app01-10442	44	13	as	as	ADP
app01-10442	44	14	a	a	DET
app01-10442	44	15	brief	brief	ADJ
app01-10442	44	16	burst	burst	NOUN
app01-10442	44	17	of	of	ADP
app01-10442	44	18	rhythmic	rhythmic	ADJ
app01-10442	44	19	oscillations	oscillation	NOUN
app01-10442	44	20	lasting	last	VERB
app01-10442	44	21	0.5	0.5	NUM
app01-10442	44	22	to	to	PART
app01-10442	44	23	2	2	NUM
app01-10442	44	24	seconds	second	NOUN
app01-10442	44	25	,	,	PUNCT
app01-10442	44	26	with	with	ADP
app01-10442	44	27	frequencies	frequency	NOUN
app01-10442	44	28	ranging	range	VERB
app01-10442	44	29	from	from	ADP
app01-10442	44	30	11	11	NUM
app01-10442	44	31	to	to	ADP
app01-10442	44	32	16hz	16hz	ADJ
app01-10442	44	33	.	.	PUNCT
app01-10442	45	1	the	the	DET
app01-10442	45	2	figure	figure	NOUN
app01-10442	45	3	provides	provide	VERB
app01-10442	45	4	a	a	DET
app01-10442	45	5	visual	visual	ADJ
app01-10442	45	6	representation	representation	NOUN
app01-10442	45	7	of	of	ADP
app01-10442	45	8	the	the	DET
app01-10442	45	9	spatial	spatial	ADJ
app01-10442	45	10	and	and	CCONJ
app01-10442	45	11	temporal	temporal	ADJ
app01-10442	45	12	dynamics	dynamic	NOUN
app01-10442	45	13	of	of	ADP
app01-10442	45	14	the	the	DET
app01-10442	45	15	sleep	sleep	NOUN
app01-10442	45	16	spindle	spindle	NOUN
app01-10442	45	17	,	,	PUNCT
app01-10442	45	18	contributing	contribute	VERB
app01-10442	45	19	to	to	ADP
app01-10442	45	20	the	the	DET
app01-10442	45	21	understanding	understanding	NOUN
app01-10442	45	22	of	of	ADP
app01-10442	45	23	its	its	PRON
app01-10442	45	24	electrographic	electrographic	ADJ
app01-10442	45	25	features	feature	NOUN
app01-10442	45	26	.	.	PUNCT
app01-10442	46	1	recognized	recognize	VERB
app01-10442	46	2	for	for	ADP
app01-10442	46	3	its	its	PRON
app01-10442	46	4	role	role	NOUN
app01-10442	46	5	in	in	ADP
app01-10442	46	6	memory	memory	NOUN
app01-10442	46	7	consolidation	consolidation	NOUN
app01-10442	46	8	,	,	PUNCT
app01-10442	46	9	the	the	DET
app01-10442	46	10	accurate	accurate	ADJ
app01-10442	46	11	identification	identification	NOUN
app01-10442	46	12	and	and	CCONJ
app01-10442	46	13	analysis	analysis	NOUN
app01-10442	46	14	of	of	ADP
app01-10442	46	15	sleep	sleep	NOUN
app01-10442	46	16	spindles	spindle	NOUN
app01-10442	46	17	,	,	PUNCT
app01-10442	46	18	as	as	SCONJ
app01-10442	46	19	illustrated	illustrate	VERB
app01-10442	46	20	in	in	ADP
app01-10442	46	21	figure	figure	NOUN
app01-10442	46	22	1	1	NUM
app01-10442	46	23	,	,	PUNCT
app01-10442	46	24	are	be	AUX
app01-10442	46	25	crucial	crucial	ADJ
app01-10442	46	26	for	for	ADP
app01-10442	46	27	investigating	investigate	VERB
app01-10442	46	28	sleep	sleep	NOUN
app01-10442	46	29	disorders	disorder	NOUN
app01-10442	46	30	and	and	CCONJ
app01-10442	46	31	neurological	neurological	ADJ
app01-10442	46	32	conditions	condition	NOUN
app01-10442	46	33	,	,	PUNCT
app01-10442	46	34	enhancing	enhance	VERB
app01-10442	46	35	comprehension	comprehension	NOUN
app01-10442	46	36	of	of	ADP
app01-10442	46	37	neural	neural	ADJ
app01-10442	46	38	activities	activity	NOUN
app01-10442	46	39	during	during	ADP
app01-10442	46	40	sleep	sleep	NOUN
app01-10442	46	41	.	.	PUNCT
app01-10442	47	1	due	due	ADP
app01-10442	47	2	to	to	ADP
app01-10442	47	3	its	its	PRON
app01-10442	47	4	characteristic	characteristic	ADJ
app01-10442	47	5	properties	property	NOUN
app01-10442	47	6	,	,	PUNCT
app01-10442	47	7	it	it	PRON
app01-10442	47	8	is	be	AUX
app01-10442	47	9	suitable	suitable	ADJ
app01-10442	47	10	for	for	ADP
app01-10442	47	11	testing	testing	NOUN
app01-10442	47	12	processing	processing	NOUN
app01-10442	47	13	techniques	technique	NOUN
app01-10442	47	14	like	like	ADP
app01-10442	47	15	machine	machine	NOUN
app01-10442	47	16	learning	learning	NOUN
app01-10442	47	17	and	and	CCONJ
app01-10442	47	18	neural	neural	ADJ
app01-10442	47	19	networks	network	NOUN
app01-10442	47	20	further	far	ADV
app01-10442	47	21	to	to	PART
app01-10442	47	22	refine	refine	VERB
app01-10442	47	23	the	the	DET
app01-10442	47	24	detection	detection	NOUN
app01-10442	47	25	and	and	CCONJ
app01-10442	47	26	interpretation	interpretation	NOUN
app01-10442	47	27	of	of	ADP
app01-10442	47	28	sleep	sleep	NOUN
app01-10442	47	29	spindles	spindle	NOUN
app01-10442	47	30	.	.	PUNCT
app01-10442	48	1	the	the	DET
app01-10442	48	2	massive	massive	ADJ
app01-10442	48	3	online	online	ADJ
app01-10442	48	4	data	data	NOUN
app01-10442	48	5	annotation	annotation	NOUN
app01-10442	48	6	(	(	PUNCT
app01-10442	48	7	moda	moda	NOUN
app01-10442	48	8	)	)	PUNCT
app01-10442	48	9	platform	platform	NOUN
app01-10442	48	10	is	be	AUX
app01-10442	48	11	pivotal	pivotal	ADJ
app01-10442	48	12	in	in	ADP
app01-10442	48	13	generating	generate	VERB
app01-10442	48	14	standardized	standardized	ADJ
app01-10442	48	15	datasets	dataset	NOUN
app01-10442	48	16	for	for	ADP
app01-10442	48	17	training	training	NOUN
app01-10442	48	18	and	and	CCONJ
app01-10442	48	19	validating	validate	VERB
app01-10442	48	20	automated	automate	VERB
app01-10442	48	21	detectors	detector	NOUN
app01-10442	48	22	of	of	ADP
app01-10442	48	23	biological	biological	ADJ
app01-10442	48	24	signals	signal	NOUN
app01-10442	48	25	,	,	PUNCT
app01-10442	48	26	including	include	VERB
app01-10442	48	27	eeg	eeg	PROPN
app01-10442	48	28	[	[	X
app01-10442	48	29	5	5	NUM
app01-10442	48	30	]	]	PUNCT
app01-10442	48	31	.	.	PUNCT
app01-10442	49	1	a	a	DET
app01-10442	49	2	canadian	canadian	ADJ
app01-10442	49	3	study	study	NOUN
app01-10442	49	4	using	use	VERB
app01-10442	49	5	moda	moda	PROPN
app01-10442	49	6	compared	compare	VERB
app01-10442	49	7	the	the	DET
app01-10442	49	8	results	result	NOUN
app01-10442	49	9	of	of	ADP
app01-10442	49	10	expert	expert	NOUN
app01-10442	49	11	,	,	PUNCT
app01-10442	49	12	researcher	researcher	NOUN
app01-10442	49	13	,	,	PUNCT
app01-10442	49	14	and	and	CCONJ
app01-10442	49	15	non	non	ADJ
app01-10442	49	16	-	-	ADJ
app01-10442	49	17	expert	expert	ADJ
app01-10442	49	18	scorers	scorer	NOUN
app01-10442	49	19	with	with	ADP
app01-10442	49	20	seven	seven	NUM
app01-10442	49	21	spindle	spindle	NOUN
app01-10442	49	22	detection	detection	NOUN
app01-10442	49	23	algorithms	algorithm	NOUN
app01-10442	49	24	,	,	PUNCT
app01-10442	49	25	revealing	reveal	VERB
app01-10442	49	26	that	that	SCONJ
app01-10442	49	27	only	only	ADV
app01-10442	49	28	two	two	NUM
app01-10442	49	29	algorithms	algorithm	NOUN
app01-10442	49	30	performed	perform	VERB
app01-10442	49	31	comparably	comparably	ADV
app01-10442	49	32	to	to	ADP
app01-10442	49	33	human	human	ADJ
app01-10442	49	34	experts	expert	NOUN
app01-10442	49	35	,	,	PUNCT
app01-10442	49	36	showcasing	showcase	VERB
app01-10442	49	37	moda	moda	PROPN
app01-10442	49	38	’s	’s	PART
app01-10442	49	39	significance	significance	NOUN
app01-10442	49	40	in	in	ADP
app01-10442	49	41	benchmarking	benchmarke	VERB
app01-10442	49	42	automated	automate	VERB
app01-10442	49	43	sleep	sleep	NOUN
app01-10442	49	44	analysis	analysis	NOUN
app01-10442	49	45	methods	method	NOUN
app01-10442	49	46	.	.	PUNCT
app01-10442	50	1	figure	figure	NOUN
app01-10442	50	2	1	1	NUM
app01-10442	50	3	.	.	PUNCT
app01-10442	50	4	example	example	NOUN
app01-10442	50	5	of	of	ADP
app01-10442	50	6	eeg	eeg	PROPN
app01-10442	50	7	sleep	sleep	NOUN
app01-10442	50	8	spindles	spindle	NOUN
app01-10442	50	9	;	;	PUNCT
app01-10442	50	10	adopted	adopt	VERB
app01-10442	50	11	from	from	ADP
app01-10442	50	12	[	[	X
app01-10442	50	13	4	4	NUM
app01-10442	50	14	]	]	PUNCT
app01-10442	50	15	.	.	PUNCT
app01-10442	51	1	the	the	DET
app01-10442	51	2	montreal	montreal	PROPN
app01-10442	51	3	archive	archive	NOUN
app01-10442	51	4	of	of	ADP
app01-10442	51	5	sleep	sleep	NOUN
app01-10442	51	6	studies	study	NOUN
app01-10442	51	7	(	(	PUNCT
app01-10442	51	8	mass	mass	PROPN
app01-10442	51	9	)	)	PUNCT
app01-10442	51	10	also	also	ADV
app01-10442	51	11	serves	serve	VERB
app01-10442	51	12	as	as	ADP
app01-10442	51	13	an	an	DET
app01-10442	51	14	open	open	ADJ
app01-10442	51	15	-	-	PUNCT
app01-10442	51	16	access	access	NOUN
app01-10442	51	17	repository	repository	NOUN
app01-10442	51	18	,	,	PUNCT
app01-10442	51	19	providing	provide	VERB
app01-10442	51	20	psg	psg	NOUN
app01-10442	51	21	data	datum	NOUN
app01-10442	51	22	for	for	ADP
app01-10442	51	23	benchmarking	benchmarke	VERB
app01-10442	51	24	automated	automate	VERB
app01-10442	51	25	sleep	sleep	NOUN
app01-10442	51	26	analysis	analysis	NOUN
app01-10442	51	27	systems	system	NOUN
app01-10442	51	28	[	[	X
app01-10442	51	29	6	6	NUM
app01-10442	51	30	]	]	PUNCT
app01-10442	51	31	.	.	PUNCT
app01-10442	52	1	established	establish	VERB
app01-10442	52	2	as	as	ADP
app01-10442	52	3	part	part	NOUN
app01-10442	52	4	of	of	ADP
app01-10442	52	5	the	the	DET
app01-10442	52	6	moda	moda	NOUN
app01-10442	52	7	project	project	NOUN
app01-10442	52	8	[	[	X
app01-10442	52	9	5	5	NUM
app01-10442	52	10	]	]	PUNCT
app01-10442	52	11	,	,	PUNCT
app01-10442	52	12	mass	mass	PROPN
app01-10442	52	13	is	be	AUX
app01-10442	52	14	a	a	DET
app01-10442	52	15	comprehensive	comprehensive	ADJ
app01-10442	52	16	and	and	CCONJ
app01-10442	52	17	openly	openly	ADV
app01-10442	52	18	accessible	accessible	ADJ
app01-10442	52	19	repository	repository	NOUN
app01-10442	52	20	of	of	ADP
app01-10442	52	21	psg	psg	NOUN
app01-10442	52	22	recordings	recording	NOUN
app01-10442	52	23	with	with	ADP
app01-10442	52	24	annotated	annotate	VERB
app01-10442	52	25	eeg	eeg	NOUN
app01-10442	52	26	signals	signal	NOUN
app01-10442	52	27	,	,	PUNCT
app01-10442	52	28	supporting	support	VERB
app01-10442	52	29	large	large	ADJ
app01-10442	52	30	-	-	PUNCT
app01-10442	52	31	scale	scale	NOUN
app01-10442	52	32	collaborations	collaboration	NOUN
app01-10442	52	33	in	in	ADP
app01-10442	52	34	sleep	sleep	NOUN
app01-10442	52	35	studies	study	NOUN
app01-10442	52	36	[	[	X
app01-10442	52	37	6	6	NUM
app01-10442	52	38	]	]	PUNCT
app01-10442	52	39	.	.	PUNCT
app01-10442	53	1	the	the	DET
app01-10442	53	2	maas	maas	PROPN
app01-10442	53	3	database	database	NOUN
app01-10442	53	4	is	be	AUX
app01-10442	53	5	structured	structure	VERB
app01-10442	53	6	into	into	ADP
app01-10442	53	7	cohorts	cohort	NOUN
app01-10442	53	8	,	,	PUNCT
app01-10442	53	9	with	with	ADP
app01-10442	53	10	subsets	subset	NOUN
app01-10442	53	11	categorizing	categorize	VERB
app01-10442	53	12	recordings	recording	NOUN
app01-10442	53	13	based	base	VERB
app01-10442	53	14	on	on	ADP
app01-10442	53	15	specific	specific	ADJ
app01-10442	53	16	characteristics	characteristic	NOUN
app01-10442	53	17	[	[	X
app01-10442	53	18	6	6	NUM
app01-10442	53	19	]	]	PUNCT
app01-10442	53	20	.	.	PUNCT
app01-10442	54	1	3	3	X
app01-10442	54	2	.	.	X
app01-10442	54	3	sleep	sleep	NOUN
app01-10442	54	4	spindles	spindle	NOUN
app01-10442	54	5	dataset	dataset	VERB
app01-10442	54	6	this	this	DET
app01-10442	54	7	study	study	NOUN
app01-10442	54	8	used	use	VERB
app01-10442	54	9	eeg	eeg	PROPN
app01-10442	54	10	data	datum	NOUN
app01-10442	54	11	from	from	ADP
app01-10442	54	12	the	the	DET
app01-10442	54	13	mass	mass	NOUN
app01-10442	54	14	archive	archive	NOUN
app01-10442	54	15	’s	’s	PART
app01-10442	54	16	stage	stage	NOUN
app01-10442	54	17	ss2	ss2	PROPN
app01-10442	54	18	(	(	PUNCT
app01-10442	54	19	described	describe	VERB
app01-10442	54	20	in	in	ADP
app01-10442	54	21	table	table	NOUN
app01-10442	54	22	1	1	NUM
app01-10442	54	23	)	)	PUNCT
app01-10442	54	24	.	.	PUNCT
app01-10442	55	1	the	the	DET
app01-10442	55	2	data	data	NOUN
app01-10442	55	3	preparation	preparation	NOUN
app01-10442	55	4	of	of	ADP
app01-10442	55	5	eeg	eeg	NOUN
app01-10442	55	6	recordings	recording	NOUN
app01-10442	55	7	involves	involve	VERB
app01-10442	55	8	addressing	address	VERB
app01-10442	55	9	challenges	challenge	NOUN
app01-10442	55	10	such	such	ADJ
app01-10442	55	11	as	as	ADP
app01-10442	55	12	the	the	DET
app01-10442	55	13	unique	unique	ADJ
app01-10442	55	14	occurrence	occurrence	NOUN
app01-10442	55	15	of	of	ADP
app01-10442	55	16	sleep	sleep	NOUN
app01-10442	55	17	spindles	spindle	NOUN
app01-10442	55	18	in	in	ADP
app01-10442	55	19	specific	specific	ADJ
app01-10442	55	20	sleep	sleep	NOUN
app01-10442	55	21	segments	segment	NOUN
app01-10442	55	22	,	,	PUNCT
app01-10442	55	23	constituting	constitute	VERB
app01-10442	55	24	about	about	ADV
app01-10442	55	25	two	two	NUM
app01-10442	55	26	percent	percent	NOUN
app01-10442	55	27	of	of	ADP
app01-10442	55	28	the	the	DET
app01-10442	55	29	overall	overall	ADJ
app01-10442	55	30	recording	recording	NOUN
app01-10442	55	31	.	.	PUNCT
app01-10442	56	1	given	give	VERB
app01-10442	56	2	this	this	DET
app01-10442	56	3	imbalance	imbalance	NOUN
app01-10442	56	4	,	,	PUNCT
app01-10442	56	5	set	set	VERB
app01-10442	56	6	balancing	balancing	NOUN
app01-10442	56	7	is	be	AUX
app01-10442	56	8	crucial	crucial	ADJ
app01-10442	56	9	for	for	ADP
app01-10442	56	10	effective	effective	ADJ
app01-10442	56	11	neural	neural	ADJ
app01-10442	56	12	network	network	NOUN
app01-10442	56	13	training	training	NOUN
app01-10442	56	14	.	.	PUNCT
app01-10442	57	1	the	the	DET
app01-10442	57	2	measured	measure	VERB
app01-10442	57	3	voltage	voltage	NOUN
app01-10442	57	4	values	value	NOUN
app01-10442	57	5	in	in	ADP
app01-10442	57	6	the	the	DET
app01-10442	57	7	eeg	eeg	PROPN
app01-10442	57	8	signal	signal	NOUN
app01-10442	57	9	range	range	NOUN
app01-10442	57	10	from	from	ADP
app01-10442	57	11	10−4	10−4	NUM
app01-10442	57	12	to	to	ADP
app01-10442	57	13	10−6	10−6	NUM
app01-10442	57	14	volts	volt	NOUN
app01-10442	57	15	,	,	PUNCT
app01-10442	57	16	necessitating	necessitate	VERB
app01-10442	57	17	normalization	normalization	NOUN
app01-10442	57	18	.	.	PUNCT
app01-10442	58	1	the	the	DET
app01-10442	58	2	eeg	eeg	NOUN
app01-10442	58	3	records	record	VERB
app01-10442	58	4	from	from	ADP
app01-10442	58	5	only	only	ADV
app01-10442	58	6	the	the	DET
app01-10442	58	7	pz	pz	ADJ
app01-10442	58	8	-	-	ADJ
app01-10442	58	9	cle	cle	ADJ
app01-10442	58	10	channel	channel	NOUN
app01-10442	58	11	were	be	AUX
app01-10442	58	12	further	far	ADV
app01-10442	58	13	processed	process	VERB
app01-10442	58	14	,	,	PUNCT
app01-10442	58	15	as	as	SCONJ
app01-10442	58	16	this	this	DET
app01-10442	58	17	channel	channel	NOUN
app01-10442	58	18	provides	provide	VERB
app01-10442	58	19	optimal	optimal	ADJ
app01-10442	58	20	visibility	visibility	NOUN
app01-10442	58	21	for	for	ADP
app01-10442	58	22	sleep	sleep	NOUN
app01-10442	58	23	spindles	spindle	NOUN
app01-10442	58	24	.	.	PUNCT
app01-10442	59	1	the	the	DET
app01-10442	59	2	eeg	eeg	PROPN
app01-10442	59	3	records	record	NOUN
app01-10442	59	4	were	be	AUX
app01-10442	59	5	subdivided	subdivide	VERB
app01-10442	59	6	into	into	ADP
app01-10442	59	7	smaller	small	ADJ
app01-10442	59	8	segments	segment	NOUN
app01-10442	59	9	for	for	ADP
app01-10442	59	10	neural	neural	ADJ
app01-10442	59	11	network	network	NOUN
app01-10442	59	12	processing	processing	NOUN
app01-10442	59	13	;	;	PUNCT
app01-10442	59	14	each	each	DET
app01-10442	59	15	segment	segment	NOUN
app01-10442	59	16	was	be	AUX
app01-10442	59	17	further	far	ADV
app01-10442	59	18	divided	divide	VERB
app01-10442	59	19	into	into	ADP
app01-10442	59	20	sets	set	NOUN
app01-10442	59	21	using	use	VERB
app01-10442	59	22	annotations	annotation	NOUN
app01-10442	59	23	.	.	PUNCT
app01-10442	60	1	the	the	DET
app01-10442	60	2	dataset	dataset	NOUN
app01-10442	60	3	’s	’s	PART
app01-10442	60	4	imbalance	imbalance	NOUN
app01-10442	60	5	,	,	PUNCT
app01-10442	60	6	where	where	SCONJ
app01-10442	60	7	segments	segment	NOUN
app01-10442	60	8	without	without	ADP
app01-10442	60	9	spindles	spindle	NOUN
app01-10442	60	10	make	make	VERB
app01-10442	60	11	up	up	ADP
app01-10442	60	12	about	about	ADP
app01-10442	60	13	ninety	ninety	NUM
app01-10442	60	14	-	-	PUNCT
app01-10442	60	15	eight	eight	NUM
app01-10442	60	16	percent	percent	NOUN
app01-10442	60	17	of	of	ADP
app01-10442	60	18	the	the	DET
app01-10442	60	19	dataset	dataset	NOUN
app01-10442	60	20	,	,	PUNCT
app01-10442	60	21	is	be	AUX
app01-10442	60	22	reduced	reduce	VERB
app01-10442	60	23	using	use	VERB
app01-10442	60	24	a	a	DET
app01-10442	60	25	python	python	NOUN
app01-10442	60	26	random	random	ADJ
app01-10442	60	27	number	number	NOUN
app01-10442	60	28	generator	generator	NOUN
app01-10442	60	29	for	for	ADP
app01-10442	60	30	unbiased	unbiased	ADJ
app01-10442	60	31	set	set	NOUN
app01-10442	60	32	balancing	balancing	NOUN
app01-10442	60	33	,	,	PUNCT
app01-10442	60	34	avoiding	avoid	VERB
app01-10442	60	35	pattern	pattern	NOUN
app01-10442	60	36	-	-	PUNCT
app01-10442	60	37	based	base	VERB
app01-10442	60	38	distortions	distortion	NOUN
app01-10442	60	39	during	during	ADP
app01-10442	60	40	training	training	NOUN
app01-10442	60	41	.	.	PUNCT
app01-10442	61	1	4	4	X
app01-10442	61	2	.	.	X
app01-10442	61	3	neural	neural	ADJ
app01-10442	61	4	network	network	NOUN
app01-10442	61	5	architectures	architecture	NOUN
app01-10442	61	6	this	this	DET
app01-10442	61	7	section	section	NOUN
app01-10442	61	8	briefly	briefly	NOUN
app01-10442	61	9	overviews	overview	VERB
app01-10442	61	10	the	the	DET
app01-10442	61	11	methods	method	NOUN
app01-10442	61	12	(	(	PUNCT
app01-10442	61	13	neural	neural	ADJ
app01-10442	61	14	network	network	NOUN
app01-10442	61	15	architectures	architecture	NOUN
app01-10442	61	16	)	)	PUNCT
app01-10442	61	17	employed	employ	VERB
app01-10442	61	18	for	for	ADP
app01-10442	61	19	the	the	DET
app01-10442	61	20	automated	automate	VERB
app01-10442	61	21	detection	detection	NOUN
app01-10442	61	22	of	of	ADP
app01-10442	61	23	sleep	sleep	NOUN
app01-10442	61	24	spindles	spindle	NOUN
app01-10442	61	25	in	in	ADP
app01-10442	61	26	the	the	DET
app01-10442	61	27	dataset	dataset	NOUN
app01-10442	61	28	described	describe	VERB
app01-10442	61	29	above	above	ADV
app01-10442	61	30	.	.	PUNCT
app01-10442	62	1	furthermore	furthermore	ADV
app01-10442	62	2	,	,	PUNCT
app01-10442	62	3	these	these	DET
app01-10442	62	4	architectures	architecture	NOUN
app01-10442	62	5	were	be	AUX
app01-10442	62	6	complemented	complement	VERB
app01-10442	62	7	by	by	ADP
app01-10442	62	8	their	their	PRON
app01-10442	62	9	combinations	combination	NOUN
app01-10442	62	10	,	,	PUNCT
app01-10442	62	11	with	with	ADP
app01-10442	62	12	the	the	DET
app01-10442	62	13	anticipation	anticipation	NOUN
app01-10442	62	14	of	of	ADP
app01-10442	62	15	preserving	preserve	VERB
app01-10442	62	16	the	the	DET
app01-10442	62	17	advantages	advantage	NOUN
app01-10442	62	18	and	and	CCONJ
app01-10442	62	19	properties	property	NOUN
app01-10442	62	20	inherent	inherent	ADJ
app01-10442	62	21	in	in	ADP
app01-10442	62	22	each	each	DET
app01-10442	62	23	architecture	architecture	NOUN
app01-10442	62	24	.	.	PUNCT
app01-10442	63	1	4.1	4.1	NUM
app01-10442	63	2	.	.	PUNCT
app01-10442	64	1	dense	dense	ADJ
app01-10442	64	2	neural	neural	ADJ
app01-10442	64	3	network	network	NOUN
app01-10442	64	4	the	the	DET
app01-10442	64	5	dense	dense	ADJ
app01-10442	64	6	neural	neural	ADJ
app01-10442	64	7	network	network	NOUN
app01-10442	64	8	(	(	PUNCT
app01-10442	64	9	dnn	dnn	PROPN
app01-10442	64	10	)	)	PUNCT
app01-10442	64	11	depicted	depict	VERB
app01-10442	64	12	in	in	ADP
app01-10442	64	13	figure	figure	NOUN
app01-10442	64	14	2	2	NUM
app01-10442	64	15	,	,	PUNCT
app01-10442	64	16	also	also	ADV
app01-10442	64	17	known	know	VERB
app01-10442	64	18	as	as	ADP
app01-10442	64	19	a	a	DET
app01-10442	64	20	fully	fully	ADV
app01-10442	64	21	connected	connected	ADJ
app01-10442	64	22	neural	neural	ADJ
app01-10442	64	23	network	network	NOUN
app01-10442	64	24	,	,	PUNCT
app01-10442	64	25	exhibits	exhibit	VERB
app01-10442	64	26	a	a	DET
app01-10442	64	27	structure	structure	NOUN
app01-10442	64	28	where	where	SCONJ
app01-10442	64	29	each	each	DET
app01-10442	64	30	node	node	NOUN
app01-10442	64	31	in	in	ADP
app01-10442	64	32	one	one	NUM
app01-10442	64	33	layer	layer	NOUN
app01-10442	64	34	connects	connect	VERB
app01-10442	64	35	to	to	ADP
app01-10442	64	36	every	every	DET
app01-10442	64	37	node	node	NOUN
app01-10442	64	38	in	in	ADP
app01-10442	64	39	the	the	DET
app01-10442	64	40	next	next	ADJ
app01-10442	64	41	.	.	PUNCT
app01-10442	65	1	this	this	DET
app01-10442	65	2	dense	dense	ADJ
app01-10442	65	3	connectivity	connectivity	NOUN
app01-10442	65	4	allows	allow	VERB
app01-10442	65	5	comprehensive	comprehensive	ADJ
app01-10442	65	6	eeg	eeg	PROPN
app01-10442	65	7	signal	signal	NOUN
app01-10442	65	8	processing	processing	NOUN
app01-10442	65	9	76	76	NUM
app01-10442	65	10	vol	vol	NOUN
app01-10442	65	11	.	.	PUNCT
app01-10442	66	1	51/2024	51/2024	NUM
app01-10442	66	2	sleep	sleep	NOUN
app01-10442	66	3	spindle	spindle	NOUN
app01-10442	66	4	detection	detection	NOUN
app01-10442	66	5	stage	stage	NOUN
app01-10442	66	6	2	2	NUM
app01-10442	66	7	(	(	PUNCT
app01-10442	66	8	ss2	ss2	NOUN
app01-10442	66	9	)	)	PUNCT
app01-10442	66	10	memory	memory	NOUN
app01-10442	66	11	size	size	NOUN
app01-10442	66	12	7.26	7.26	NUM
app01-10442	66	13	gb	gb	NOUN
app01-10442	66	14	total	total	ADJ
app01-10442	66	15	number	number	NOUN
app01-10442	66	16	of	of	ADP
app01-10442	66	17	measurements	measurement	NOUN
app01-10442	66	18	19	19	NUM
app01-10442	66	19	total	total	ADJ
app01-10442	66	20	number	number	NOUN
app01-10442	66	21	of	of	ADP
app01-10442	66	22	spindles	spindle	NOUN
app01-10442	66	23	11204	11204	NUM
app01-10442	66	24	average	average	ADJ
app01-10442	66	25	number	number	NOUN
app01-10442	66	26	of	of	ADP
app01-10442	66	27	spindles	spindle	NOUN
app01-10442	66	28	in	in	ADP
app01-10442	66	29	a	a	DET
app01-10442	66	30	measurement	measurement	NOUN
app01-10442	66	31	217	217	NUM
app01-10442	66	32	time	time	NOUN
app01-10442	66	33	length	length	NOUN
app01-10442	66	34	151	151	NUM
app01-10442	66	35	h	h	NOUN
app01-10442	66	36	maximum	maximum	ADJ
app01-10442	66	37	number	number	NOUN
app01-10442	66	38	of	of	ADP
app01-10442	66	39	spindles	spindle	NOUN
app01-10442	66	40	in	in	ADP
app01-10442	66	41	a	a	DET
app01-10442	66	42	measurement	measurement	NOUN
app01-10442	66	43	569	569	NUM
app01-10442	66	44	minimum	minimum	ADJ
app01-10442	66	45	number	number	NOUN
app01-10442	66	46	of	of	ADP
app01-10442	66	47	spindles	spindle	NOUN
app01-10442	66	48	in	in	ADP
app01-10442	66	49	a	a	DET
app01-10442	66	50	measurement	measurement	NOUN
app01-10442	66	51	86	86	NUM
app01-10442	66	52	maximum	maximum	ADJ
app01-10442	66	53	duration	duration	NOUN
app01-10442	66	54	of	of	ADP
app01-10442	66	55	spindle	spindle	NOUN
app01-10442	66	56	2.218605	2.218605	NUM
app01-10442	66	57	s	s	PART
app01-10442	66	58	minimum	minimum	NOUN
app01-10442	66	59	duration	duration	NOUN
app01-10442	66	60	of	of	ADP
app01-10442	66	61	spindle	spindle	NOUN
app01-10442	66	62	0.335915	0.335915	NUM
app01-10442	66	63	s	s	PART
app01-10442	66	64	average	average	ADJ
app01-10442	66	65	length	length	NOUN
app01-10442	66	66	of	of	ADP
app01-10442	66	67	an	an	DET
app01-10442	66	68	eeg	eeg	NOUN
app01-10442	66	69	measurement	measurement	NOUN
app01-10442	66	70	7	7	NUM
app01-10442	66	71	h	h	NOUN
app01-10442	66	72	59min	59min	NOUN
app01-10442	66	73	table	table	NOUN
app01-10442	66	74	1	1	NUM
app01-10442	66	75	.	.	PUNCT
app01-10442	66	76	characteristics	characteristic	NOUN
app01-10442	66	77	of	of	ADP
app01-10442	66	78	stage	stage	NOUN
app01-10442	66	79	ss2	ss2	PROPN
app01-10442	66	80	.	.	PROPN
app01-10442	66	81	figure	figure	NOUN
app01-10442	66	82	2	2	NUM
app01-10442	66	83	.	.	PUNCT
app01-10442	66	84	an	an	DET
app01-10442	66	85	example	example	NOUN
app01-10442	66	86	of	of	ADP
app01-10442	66	87	a	a	DET
app01-10442	66	88	standard	standard	ADJ
app01-10442	66	89	dense	dense	ADJ
app01-10442	66	90	neural	neural	ADJ
app01-10442	66	91	network	network	NOUN
app01-10442	66	92	.	.	PUNCT
app01-10442	67	1	the	the	DET
app01-10442	67	2	network	network	NOUN
app01-10442	67	3	has	have	VERB
app01-10442	67	4	one	one	NUM
app01-10442	67	5	input	input	NOUN
app01-10442	67	6	,	,	PUNCT
app01-10442	67	7	two	two	NUM
app01-10442	67	8	hidden	hide	VERB
app01-10442	67	9	,	,	PUNCT
app01-10442	67	10	and	and	CCONJ
app01-10442	67	11	one	one	NUM
app01-10442	67	12	output	output	NOUN
app01-10442	67	13	layer	layer	NOUN
app01-10442	67	14	,	,	PUNCT
app01-10442	67	15	adopted	adopt	VERB
app01-10442	67	16	from	from	ADP
app01-10442	67	17	[	[	X
app01-10442	67	18	7	7	NUM
app01-10442	67	19	]	]	PUNCT
app01-10442	67	20	.	.	PUNCT
app01-10442	68	1	and	and	CCONJ
app01-10442	68	2	feature	feature	NOUN
app01-10442	68	3	extraction	extraction	NOUN
app01-10442	68	4	,	,	PUNCT
app01-10442	68	5	enabling	enable	VERB
app01-10442	68	6	the	the	DET
app01-10442	68	7	network	network	NOUN
app01-10442	68	8	to	to	PART
app01-10442	68	9	capture	capture	VERB
app01-10442	68	10	intricate	intricate	ADJ
app01-10442	68	11	data	datum	NOUN
app01-10442	68	12	relationships	relationship	NOUN
app01-10442	68	13	.	.	PUNCT
app01-10442	69	1	dnns	dnn	NOUN
app01-10442	69	2	are	be	AUX
app01-10442	69	3	widely	widely	ADV
app01-10442	69	4	applied	apply	VERB
app01-10442	69	5	in	in	ADP
app01-10442	69	6	domains	domain	NOUN
app01-10442	69	7	such	such	ADJ
app01-10442	69	8	as	as	ADP
app01-10442	69	9	image	image	NOUN
app01-10442	69	10	recognition	recognition	NOUN
app01-10442	69	11	,	,	PUNCT
app01-10442	69	12	natural	natural	ADJ
app01-10442	69	13	language	language	NOUN
app01-10442	69	14	processing	processing	NOUN
app01-10442	69	15	,	,	PUNCT
app01-10442	69	16	and	and	CCONJ
app01-10442	69	17	signal	signal	ADJ
app01-10442	69	18	processing	processing	NOUN
app01-10442	69	19	due	due	ADP
app01-10442	69	20	to	to	ADP
app01-10442	69	21	their	their	PRON
app01-10442	69	22	ability	ability	NOUN
app01-10442	69	23	to	to	PART
app01-10442	69	24	learn	learn	VERB
app01-10442	69	25	complex	complex	ADJ
app01-10442	69	26	patterns	pattern	NOUN
app01-10442	69	27	from	from	ADP
app01-10442	69	28	extensive	extensive	ADJ
app01-10442	69	29	datasets	dataset	NOUN
app01-10442	69	30	.	.	PUNCT
app01-10442	70	1	4.2	4.2	NUM
app01-10442	70	2	.	.	PUNCT
app01-10442	71	1	cnn	cnn	PROPN
app01-10442	71	2	the	the	DET
app01-10442	71	3	convolutional	convolutional	ADJ
app01-10442	71	4	neural	neural	ADJ
app01-10442	71	5	network	network	NOUN
app01-10442	71	6	(	(	PUNCT
app01-10442	71	7	cnn	cnn	PROPN
app01-10442	71	8	)	)	PUNCT
app01-10442	71	9	illustrated	illustrate	VERB
app01-10442	71	10	in	in	ADP
app01-10442	71	11	figure	figure	NOUN
app01-10442	71	12	3	3	NUM
app01-10442	71	13	is	be	AUX
app01-10442	71	14	a	a	DET
app01-10442	71	15	specialized	specialized	ADJ
app01-10442	71	16	class	class	NOUN
app01-10442	71	17	of	of	ADP
app01-10442	71	18	artificial	artificial	ADJ
app01-10442	71	19	neural	neural	ADJ
app01-10442	71	20	networks	network	NOUN
app01-10442	71	21	designed	design	VERB
app01-10442	71	22	for	for	ADP
app01-10442	71	23	processing	process	VERB
app01-10442	71	24	structured	structured	ADJ
app01-10442	71	25	grid	grid	NOUN
app01-10442	71	26	data	datum	NOUN
app01-10442	71	27	,	,	PUNCT
app01-10442	71	28	particularly	particularly	ADV
app01-10442	71	29	effective	effective	ADJ
app01-10442	71	30	for	for	ADP
app01-10442	71	31	tasks	task	NOUN
app01-10442	71	32	involving	involve	VERB
app01-10442	71	33	image	image	NOUN
app01-10442	71	34	analysis	analysis	NOUN
app01-10442	71	35	and	and	CCONJ
app01-10442	71	36	recognition	recognition	NOUN
app01-10442	71	37	.	.	PUNCT
app01-10442	72	1	with	with	ADP
app01-10442	72	2	distinctive	distinctive	ADJ
app01-10442	72	3	architectural	architectural	ADJ
app01-10442	72	4	elements	element	NOUN
app01-10442	72	5	,	,	PUNCT
app01-10442	72	6	including	include	VERB
app01-10442	72	7	convolutional	convolutional	ADJ
app01-10442	72	8	layers	layer	NOUN
app01-10442	72	9	,	,	PUNCT
app01-10442	72	10	pooling	pool	VERB
app01-10442	72	11	layers	layer	NOUN
app01-10442	72	12	,	,	PUNCT
app01-10442	72	13	and	and	CCONJ
app01-10442	72	14	fully	fully	ADV
app01-10442	72	15	connected	connected	ADJ
app01-10442	72	16	layers	layer	NOUN
app01-10442	72	17	,	,	PUNCT
app01-10442	72	18	cnns	cnns	PROPN
app01-10442	72	19	excel	excel	VERB
app01-10442	72	20	at	at	ADP
app01-10442	72	21	capturing	capture	VERB
app01-10442	72	22	hierarchical	hierarchical	ADJ
app01-10442	72	23	features	feature	NOUN
app01-10442	72	24	and	and	CCONJ
app01-10442	72	25	spatial	spatial	ADJ
app01-10442	72	26	hierarchies	hierarchy	NOUN
app01-10442	72	27	in	in	ADP
app01-10442	72	28	input	input	NOUN
app01-10442	72	29	data	datum	NOUN
app01-10442	72	30	.	.	PUNCT
app01-10442	73	1	convolutional	convolutional	ADJ
app01-10442	73	2	layers	layer	NOUN
app01-10442	73	3	use	use	VERB
app01-10442	73	4	filters	filter	NOUN
app01-10442	73	5	to	to	PART
app01-10442	73	6	convolve	convolve	VERB
app01-10442	73	7	across	across	ADP
app01-10442	73	8	input	input	NOUN
app01-10442	73	9	data	datum	NOUN
app01-10442	73	10	,	,	PUNCT
app01-10442	73	11	extracting	extract	VERB
app01-10442	73	12	local	local	ADJ
app01-10442	73	13	features	feature	NOUN
app01-10442	73	14	and	and	CCONJ
app01-10442	73	15	patterns	pattern	NOUN
app01-10442	73	16	.	.	PUNCT
app01-10442	74	1	pooling	pool	VERB
app01-10442	74	2	layers	layer	NOUN
app01-10442	74	3	reduce	reduce	VERB
app01-10442	74	4	spatial	spatial	ADJ
app01-10442	74	5	dimensions	dimension	NOUN
app01-10442	74	6	,	,	PUNCT
app01-10442	74	7	preserving	preserve	VERB
app01-10442	74	8	crucial	crucial	ADJ
app01-10442	74	9	information	information	NOUN
app01-10442	74	10	while	while	SCONJ
app01-10442	74	11	minimizing	minimize	VERB
app01-10442	74	12	computational	computational	ADJ
app01-10442	74	13	complexity	complexity	NOUN
app01-10442	74	14	.	.	PUNCT
app01-10442	75	1	fully	fully	ADV
app01-10442	75	2	connected	connected	ADJ
app01-10442	75	3	layers	layer	NOUN
app01-10442	75	4	enable	enable	VERB
app01-10442	75	5	high	high	ADJ
app01-10442	75	6	-	-	PUNCT
app01-10442	75	7	level	level	NOUN
app01-10442	75	8	abstraction	abstraction	NOUN
app01-10442	75	9	and	and	CCONJ
app01-10442	75	10	decision	decision	NOUN
app01-10442	75	11	-	-	PUNCT
app01-10442	75	12	making	making	NOUN
app01-10442	75	13	.	.	PUNCT
app01-10442	76	1	cnns	cnns	PROPN
app01-10442	76	2	demonstrate	demonstrate	VERB
app01-10442	76	3	notable	notable	ADJ
app01-10442	76	4	efficacy	efficacy	NOUN
app01-10442	76	5	in	in	ADP
app01-10442	76	6	applications	application	NOUN
app01-10442	76	7	like	like	ADP
app01-10442	76	8	image	image	NOUN
app01-10442	76	9	classification	classification	NOUN
app01-10442	76	10	,	,	PUNCT
app01-10442	76	11	object	object	NOUN
app01-10442	76	12	detection	detection	NOUN
app01-10442	76	13	,	,	PUNCT
app01-10442	76	14	and	and	CCONJ
app01-10442	76	15	facial	facial	ADJ
app01-10442	76	16	recognition	recognition	NOUN
app01-10442	76	17	,	,	PUNCT
app01-10442	76	18	underscoring	underscore	VERB
app01-10442	76	19	their	their	PRON
app01-10442	76	20	significance	significance	NOUN
app01-10442	76	21	in	in	ADP
app01-10442	76	22	computer	computer	NOUN
app01-10442	76	23	vision	vision	NOUN
app01-10442	76	24	and	and	CCONJ
app01-10442	76	25	pattern	pattern	NOUN
app01-10442	76	26	recognition	recognition	NOUN
app01-10442	76	27	research	research	NOUN
app01-10442	76	28	.	.	PUNCT
app01-10442	77	1	figure	figure	NOUN
app01-10442	77	2	3	3	NUM
app01-10442	77	3	.	.	PUNCT
app01-10442	78	1	an	an	DET
app01-10442	78	2	example	example	NOUN
app01-10442	78	3	of	of	ADP
app01-10442	78	4	an	an	DET
app01-10442	78	5	application	application	NOUN
app01-10442	78	6	of	of	ADP
app01-10442	78	7	filter	filter	NOUN
app01-10442	78	8	on	on	ADP
app01-10442	78	9	an	an	DET
app01-10442	78	10	image	image	NOUN
app01-10442	78	11	inside	inside	ADP
app01-10442	78	12	a	a	DET
app01-10442	78	13	cnn	cnn	PROPN
app01-10442	78	14	network	network	NOUN
app01-10442	78	15	,	,	PUNCT
app01-10442	78	16	adopted	adopt	VERB
app01-10442	78	17	from	from	ADP
app01-10442	78	18	[	[	X
app01-10442	78	19	8	8	NUM
app01-10442	78	20	]	]	PUNCT
app01-10442	78	21	.	.	PUNCT
app01-10442	79	1	4.3	4.3	NUM
app01-10442	79	2	.	.	PUNCT
app01-10442	79	3	lstm	lstm	VERB
app01-10442	79	4	the	the	DET
app01-10442	79	5	long	long	ADJ
app01-10442	79	6	short	short	ADJ
app01-10442	79	7	-	-	PUNCT
app01-10442	79	8	term	term	NOUN
app01-10442	79	9	memory	memory	NOUN
app01-10442	79	10	(	(	PUNCT
app01-10442	79	11	lstm	lstm	ADJ
app01-10442	79	12	)	)	PUNCT
app01-10442	79	13	neural	neural	ADJ
app01-10442	79	14	network	network	NOUN
app01-10442	79	15	,	,	PUNCT
app01-10442	79	16	a	a	DET
app01-10442	79	17	specialized	specialized	ADJ
app01-10442	79	18	recurrent	recurrent	ADJ
app01-10442	79	19	neural	neural	ADJ
app01-10442	79	20	network	network	NOUN
app01-10442	79	21	(	(	PUNCT
app01-10442	79	22	rnn	rnn	PROPN
app01-10442	79	23	)	)	PUNCT
app01-10442	79	24	architecture	architecture	NOUN
app01-10442	79	25	,	,	PUNCT
app01-10442	79	26	addresses	address	VERB
app01-10442	79	27	the	the	DET
app01-10442	79	28	challenge	challenge	NOUN
app01-10442	79	29	of	of	ADP
app01-10442	79	30	capturing	capture	VERB
app01-10442	79	31	longrange	longrange	NOUN
app01-10442	79	32	dependencies	dependency	NOUN
app01-10442	79	33	in	in	ADP
app01-10442	79	34	sequential	sequential	ADJ
app01-10442	79	35	data	datum	NOUN
app01-10442	79	36	by	by	ADP
app01-10442	79	37	incorporating	incorporate	VERB
app01-10442	79	38	memory	memory	NOUN
app01-10442	79	39	cells	cell	NOUN
app01-10442	79	40	with	with	ADP
app01-10442	79	41	input	input	NOUN
app01-10442	79	42	,	,	PUNCT
app01-10442	79	43	forget	forget	VERB
app01-10442	79	44	,	,	PUNCT
app01-10442	79	45	and	and	CCONJ
app01-10442	79	46	output	output	NOUN
app01-10442	79	47	gates	gate	NOUN
app01-10442	79	48	,	,	PUNCT
app01-10442	79	49	making	make	VERB
app01-10442	79	50	these	these	DET
app01-10442	79	51	networks	network	NOUN
app01-10442	79	52	particularly	particularly	ADV
app01-10442	79	53	suitable	suitable	ADJ
app01-10442	79	54	for	for	ADP
app01-10442	79	55	tasks	task	NOUN
app01-10442	79	56	involving	involve	VERB
app01-10442	79	57	memory	memory	NOUN
app01-10442	79	58	and	and	CCONJ
app01-10442	79	59	temporal	temporal	ADJ
app01-10442	79	60	patterns	pattern	NOUN
app01-10442	79	61	.	.	PUNCT
app01-10442	80	1	the	the	DET
app01-10442	80	2	gates	gate	NOUN
app01-10442	80	3	selectively	selectively	ADV
app01-10442	80	4	control	control	VERB
app01-10442	80	5	information	information	NOUN
app01-10442	80	6	flow	flow	NOUN
app01-10442	80	7	,	,	PUNCT
app01-10442	80	8	allowing	allow	VERB
app01-10442	80	9	the	the	DET
app01-10442	80	10	network	network	NOUN
app01-10442	80	11	to	to	PART
app01-10442	80	12	retain	retain	VERB
app01-10442	80	13	relevant	relevant	ADJ
app01-10442	80	14	context	context	NOUN
app01-10442	80	15	over	over	ADP
app01-10442	80	16	extended	extended	ADJ
app01-10442	80	17	sequences	sequence	NOUN
app01-10442	80	18	and	and	CCONJ
app01-10442	80	19	mitigating	mitigate	VERB
app01-10442	80	20	the	the	DET
app01-10442	80	21	vanishing	vanish	VERB
app01-10442	80	22	gradient	gradient	NOUN
app01-10442	80	23	problem	problem	NOUN
app01-10442	80	24	.	.	PUNCT
app01-10442	81	1	lstms	lstms	ADJ
app01-10442	81	2	excel	excel	VERB
app01-10442	81	3	in	in	ADP
app01-10442	81	4	natural	natural	ADJ
app01-10442	81	5	language	language	NOUN
app01-10442	81	6	processing	processing	NOUN
app01-10442	81	7	,	,	PUNCT
app01-10442	81	8	speech	speech	NOUN
app01-10442	81	9	recognition	recognition	NOUN
app01-10442	81	10	,	,	PUNCT
app01-10442	81	11	and	and	CCONJ
app01-10442	81	12	time	time	NOUN
app01-10442	81	13	series	series	PROPN
app01-10442	81	14	analysis	analysis	NOUN
app01-10442	81	15	,	,	PUNCT
app01-10442	81	16	effectively	effectively	ADV
app01-10442	81	17	capturing	capture	VERB
app01-10442	81	18	temporal	temporal	ADJ
app01-10442	81	19	dependencies	dependency	NOUN
app01-10442	81	20	.	.	PUNCT
app01-10442	82	1	their	their	PRON
app01-10442	82	2	role	role	NOUN
app01-10442	82	3	in	in	ADP
app01-10442	82	4	mitigating	mitigate	VERB
app01-10442	82	5	the	the	DET
app01-10442	82	6	vanishing	vanish	VERB
app01-10442	82	7	gradient	gradient	NOUN
app01-10442	82	8	problem	problem	NOUN
app01-10442	82	9	has	have	AUX
app01-10442	82	10	positioned	position	VERB
app01-10442	82	11	lstms	lstms	NOUN
app01-10442	82	12	as	as	ADP
app01-10442	82	13	a	a	DET
app01-10442	82	14	cornerstone	cornerstone	NOUN
app01-10442	82	15	in	in	ADP
app01-10442	82	16	developing	develop	VERB
app01-10442	82	17	advanced	advanced	ADJ
app01-10442	82	18	deep	deep	ADJ
app01-10442	82	19	-	-	PUNCT
app01-10442	82	20	learning	learn	VERB
app01-10442	82	21	models	model	NOUN
app01-10442	82	22	for	for	ADP
app01-10442	82	23	sequential	sequential	ADJ
app01-10442	82	24	data	datum	NOUN
app01-10442	82	25	processing	processing	NOUN
app01-10442	82	26	,	,	PUNCT
app01-10442	82	27	contributing	contribute	VERB
app01-10442	82	28	to	to	ADP
app01-10442	82	29	diverse	diverse	ADJ
app01-10442	82	30	areas	area	NOUN
app01-10442	82	31	of	of	ADP
app01-10442	82	32	artificial	artificial	ADJ
app01-10442	82	33	intelligence	intelligence	NOUN
app01-10442	82	34	research	research	NOUN
app01-10442	82	35	.	.	PUNCT
app01-10442	83	1	the	the	DET
app01-10442	83	2	network	network	NOUN
app01-10442	83	3	architecture	architecture	NOUN
app01-10442	83	4	is	be	AUX
app01-10442	83	5	depicted	depict	VERB
app01-10442	83	6	in	in	ADP
app01-10442	83	7	figure	figure	NOUN
app01-10442	83	8	4	4	NUM
app01-10442	83	9	,	,	PUNCT
app01-10442	83	10	showcasing	showcase	VERB
app01-10442	83	11	its	its	PRON
app01-10442	83	12	capability	capability	NOUN
app01-10442	83	13	to	to	PART
app01-10442	83	14	detect	detect	VERB
app01-10442	83	15	specific	specific	ADJ
app01-10442	83	16	eeg	eeg	NOUN
app01-10442	83	17	signals	signal	NOUN
app01-10442	83	18	.	.	PUNCT
app01-10442	84	1	5	5	X
app01-10442	84	2	.	.	X
app01-10442	84	3	dataset	dataset	NOUN
app01-10442	84	4	processing	process	VERB
app01-10442	84	5	the	the	DET
app01-10442	84	6	current	current	ADJ
app01-10442	84	7	research	research	NOUN
app01-10442	84	8	incorporates	incorporate	VERB
app01-10442	84	9	three	three	NUM
app01-10442	84	10	prominent	prominent	ADJ
app01-10442	84	11	neural	neural	ADJ
app01-10442	84	12	network	network	NOUN
app01-10442	84	13	architectures	architecture	NOUN
app01-10442	84	14	discussed	discuss	VERB
app01-10442	84	15	above	above	ADP
app01-10442	84	16	:	:	PUNCT
app01-10442	84	17	dnn	dnn	PROPN
app01-10442	84	18	,	,	PUNCT
app01-10442	84	19	lstm	lstm	ADJ
app01-10442	84	20	,	,	PUNCT
app01-10442	84	21	and	and	CCONJ
app01-10442	84	22	cnn	cnn	PROPN
app01-10442	84	23	.	.	PUNCT
app01-10442	85	1	the	the	DET
app01-10442	85	2	strategic	strategic	ADJ
app01-10442	85	3	use	use	NOUN
app01-10442	85	4	of	of	ADP
app01-10442	85	5	these	these	DET
app01-10442	85	6	architectures	architecture	NOUN
app01-10442	85	7	underscores	underscore	VERB
app01-10442	85	8	a	a	DET
app01-10442	85	9	sophisticated	sophisticated	ADJ
app01-10442	85	10	approach	approach	NOUN
app01-10442	85	11	to	to	ADP
app01-10442	85	12	ad77	ad77	PROPN
app01-10442	85	13	jan	jan	PROPN
app01-10442	85	14	rychlík	rychlík	NOUN
app01-10442	85	15	,	,	PUNCT
app01-10442	85	16	roman	roman	ADJ
app01-10442	85	17	mouček	mouček	PROPN
app01-10442	85	18	acta	acta	PROPN
app01-10442	85	19	polytechnica	polytechnica	PROPN
app01-10442	85	20	ctu	ctu	PROPN
app01-10442	85	21	proceedings	proceeding	NOUN
app01-10442	85	22	figure	figure	VERB
app01-10442	85	23	4	4	NUM
app01-10442	85	24	.	.	PUNCT
app01-10442	86	1	lstm	lstm	PROPN
app01-10442	86	2	neural	neural	ADJ
app01-10442	86	3	network	network	NOUN
app01-10442	86	4	scheme	scheme	NOUN
app01-10442	86	5	,	,	PUNCT
app01-10442	86	6	adopted	adopt	VERB
app01-10442	86	7	from	from	ADP
app01-10442	86	8	[	[	X
app01-10442	86	9	9	9	NUM
app01-10442	86	10	]	]	PUNCT
app01-10442	86	11	.	.	PUNCT
app01-10442	87	1	dressing	dress	VERB
app01-10442	87	2	the	the	DET
app01-10442	87	3	complexities	complexity	NOUN
app01-10442	87	4	associated	associate	VERB
app01-10442	87	5	with	with	ADP
app01-10442	87	6	sleep	sleep	NOUN
app01-10442	87	7	spindle	spindle	NOUN
app01-10442	87	8	detection	detection	NOUN
app01-10442	87	9	in	in	ADP
app01-10442	87	10	research	research	NOUN
app01-10442	87	11	studies	study	NOUN
app01-10442	87	12	.	.	PUNCT
app01-10442	88	1	the	the	DET
app01-10442	88	2	dnn	dnn	PROPN
app01-10442	88	3	architecture	architecture	NOUN
app01-10442	88	4	was	be	AUX
app01-10442	88	5	the	the	DET
app01-10442	88	6	primary	primary	ADJ
app01-10442	88	7	choice	choice	NOUN
app01-10442	88	8	for	for	ADP
app01-10442	88	9	sleep	sleep	NOUN
app01-10442	88	10	spindle	spindle	NOUN
app01-10442	88	11	dataset	dataset	NOUN
app01-10442	88	12	processing	processing	NOUN
app01-10442	88	13	;	;	PUNCT
app01-10442	88	14	it	it	PRON
app01-10442	88	15	provides	provide	VERB
app01-10442	88	16	a	a	DET
app01-10442	88	17	basic	basic	ADJ
app01-10442	88	18	model	model	NOUN
app01-10442	88	19	for	for	ADP
app01-10442	88	20	initial	initial	ADJ
app01-10442	88	21	exploration	exploration	NOUN
app01-10442	88	22	and	and	CCONJ
app01-10442	88	23	understanding	understanding	NOUN
app01-10442	88	24	of	of	ADP
app01-10442	88	25	the	the	DET
app01-10442	88	26	dataset	dataset	NOUN
app01-10442	88	27	.	.	PUNCT
app01-10442	89	1	the	the	DET
app01-10442	89	2	lstm	lstm	ADJ
app01-10442	89	3	architecture	architecture	NOUN
app01-10442	89	4	has	have	AUX
app01-10442	89	5	been	be	AUX
app01-10442	89	6	incorporated	incorporate	VERB
app01-10442	89	7	to	to	PART
app01-10442	89	8	process	process	VERB
app01-10442	89	9	the	the	DET
app01-10442	89	10	data	datum	NOUN
app01-10442	89	11	further	far	ADV
app01-10442	89	12	.	.	PUNCT
app01-10442	90	1	the	the	DET
app01-10442	90	2	inclusion	inclusion	NOUN
app01-10442	90	3	of	of	ADP
app01-10442	90	4	lstms	lstms	NOUN
app01-10442	90	5	is	be	AUX
app01-10442	90	6	motivated	motivate	VERB
app01-10442	90	7	by	by	ADP
app01-10442	90	8	their	their	PRON
app01-10442	90	9	ability	ability	NOUN
app01-10442	90	10	to	to	PART
app01-10442	90	11	detect	detect	VERB
app01-10442	90	12	subtle	subtle	ADJ
app01-10442	90	13	signals	signal	NOUN
app01-10442	90	14	that	that	PRON
app01-10442	90	15	precede	precede	VERB
app01-10442	90	16	the	the	DET
app01-10442	90	17	occurrence	occurrence	NOUN
app01-10442	90	18	of	of	ADP
app01-10442	90	19	sleep	sleep	NOUN
app01-10442	90	20	spindles	spindle	NOUN
app01-10442	90	21	.	.	PUNCT
app01-10442	91	1	to	to	PART
app01-10442	91	2	enhance	enhance	VERB
app01-10442	91	3	the	the	DET
app01-10442	91	4	data	datum	NOUN
app01-10442	91	5	processing	process	VERB
app01-10442	91	6	capabilities	capability	NOUN
app01-10442	91	7	,	,	PUNCT
app01-10442	91	8	the	the	DET
app01-10442	91	9	cnn	cnn	PROPN
app01-10442	91	10	was	be	AUX
app01-10442	91	11	introduced	introduce	VERB
app01-10442	91	12	into	into	ADP
app01-10442	91	13	the	the	DET
app01-10442	91	14	architecture	architecture	NOUN
app01-10442	91	15	.	.	PUNCT
app01-10442	92	1	in	in	ADP
app01-10442	92	2	the	the	DET
app01-10442	92	3	context	context	NOUN
app01-10442	92	4	of	of	ADP
app01-10442	92	5	sleep	sleep	NOUN
app01-10442	92	6	spindle	spindle	NOUN
app01-10442	92	7	detection	detection	NOUN
app01-10442	92	8	,	,	PUNCT
app01-10442	92	9	treating	treat	VERB
app01-10442	92	10	eeg	eeg	NOUN
app01-10442	92	11	data	datum	NOUN
app01-10442	92	12	as	as	ADP
app01-10442	92	13	an	an	DET
app01-10442	92	14	image	image	NOUN
app01-10442	92	15	allows	allow	VERB
app01-10442	92	16	cnns	cnn	NOUN
app01-10442	92	17	to	to	PART
app01-10442	92	18	capture	capture	VERB
app01-10442	92	19	hierarchical	hierarchical	ADJ
app01-10442	92	20	features	feature	NOUN
app01-10442	92	21	and	and	CCONJ
app01-10442	92	22	spatial	spatial	ADJ
app01-10442	92	23	hierarchies	hierarchy	NOUN
app01-10442	92	24	efficiently	efficiently	ADV
app01-10442	92	25	.	.	PUNCT
app01-10442	93	1	the	the	DET
app01-10442	93	2	convolutional	convolutional	ADJ
app01-10442	93	3	layers	layer	NOUN
app01-10442	93	4	in	in	ADP
app01-10442	93	5	cnns	cnns	PROPN
app01-10442	93	6	facilitate	facilitate	NOUN
app01-10442	93	7	extracting	extract	VERB
app01-10442	93	8	local	local	ADJ
app01-10442	93	9	features	feature	NOUN
app01-10442	93	10	and	and	CCONJ
app01-10442	93	11	patterns	pattern	NOUN
app01-10442	93	12	,	,	PUNCT
app01-10442	93	13	contributing	contribute	VERB
app01-10442	93	14	to	to	ADP
app01-10442	93	15	a	a	DET
app01-10442	93	16	comprehensive	comprehensive	ADJ
app01-10442	93	17	understanding	understanding	NOUN
app01-10442	93	18	of	of	ADP
app01-10442	93	19	the	the	DET
app01-10442	93	20	dataset	dataset	NOUN
app01-10442	93	21	.	.	PUNCT
app01-10442	94	1	various	various	ADJ
app01-10442	94	2	combinations	combination	NOUN
app01-10442	94	3	of	of	ADP
app01-10442	94	4	dnn	dnn	PROPN
app01-10442	94	5	,	,	PUNCT
app01-10442	94	6	lstm	lstm	ADJ
app01-10442	94	7	,	,	PUNCT
app01-10442	94	8	and	and	CCONJ
app01-10442	94	9	cnn	cnn	PROPN
app01-10442	94	10	architectures	architecture	NOUN
app01-10442	94	11	provide	provide	VERB
app01-10442	94	12	a	a	DET
app01-10442	94	13	diverse	diverse	ADJ
app01-10442	94	14	and	and	CCONJ
app01-10442	94	15	comprehensive	comprehensive	ADJ
app01-10442	94	16	approach	approach	NOUN
app01-10442	94	17	to	to	ADP
app01-10442	94	18	the	the	DET
app01-10442	94	19	data	datum	NOUN
app01-10442	94	20	processing	processing	NOUN
app01-10442	94	21	to	to	PART
app01-10442	94	22	improve	improve	VERB
app01-10442	94	23	sleep	sleep	NOUN
app01-10442	94	24	spindle	spindle	NOUN
app01-10442	94	25	detection	detection	NOUN
app01-10442	94	26	algorithms	algorithm	NOUN
app01-10442	94	27	;	;	PUNCT
app01-10442	94	28	we	we	PRON
app01-10442	94	29	chose	choose	VERB
app01-10442	94	30	the	the	DET
app01-10442	94	31	following	following	ADJ
app01-10442	94	32	simple	simple	ADJ
app01-10442	94	33	architectures	architecture	NOUN
app01-10442	94	34	:	:	PUNCT
app01-10442	94	35	lstm	lstm	ADJ
app01-10442	94	36	,	,	PUNCT
app01-10442	94	37	dense	dense	ADJ
app01-10442	94	38	,	,	PUNCT
app01-10442	94	39	cnn	cnn	PROPN
app01-10442	94	40	and	and	CCONJ
app01-10442	94	41	cnn	cnn	PROPN
app01-10442	94	42	and	and	CCONJ
app01-10442	94	43	their	their	PRON
app01-10442	94	44	combinations	combination	NOUN
app01-10442	94	45	of	of	ADP
app01-10442	94	46	architecture	architecture	NOUN
app01-10442	94	47	:	:	PUNCT
app01-10442	94	48	cnn	cnn	PROPN
app01-10442	94	49	-	-	PUNCT
app01-10442	94	50	lstm	lstm	PROPN
app01-10442	94	51	implemented	implement	VERB
app01-10442	94	52	in	in	ADP
app01-10442	94	53	keras	keras	PROPN
app01-10442	94	54	python	python	PROPN
app01-10442	94	55	package	package	NOUN
app01-10442	94	56	and	and	CCONJ
app01-10442	94	57	cnn	cnn	PROPN
app01-10442	94	58	-	-	PUNCT
app01-10442	94	59	lstm	lstm	PROPN
app01-10442	94	60	implemented	implement	VERB
app01-10442	94	61	in	in	ADP
app01-10442	94	62	torch	torch	NOUN
app01-10442	94	63	python	python	NOUN
app01-10442	94	64	package	package	NOUN
app01-10442	94	65	.	.	PUNCT
app01-10442	95	1	the	the	DET
app01-10442	95	2	proposed	propose	VERB
app01-10442	95	3	cnn	cnn	PROPN
app01-10442	95	4	-	-	PUNCT
app01-10442	95	5	lstm	lstm	PROPN
app01-10442	95	6	implemented	implement	VERB
app01-10442	95	7	in	in	ADP
app01-10442	95	8	keras	keras	PROPN
app01-10442	95	9	package	package	NOUN
app01-10442	95	10	architecture	architecture	NOUN
app01-10442	95	11	is	be	AUX
app01-10442	95	12	shown	show	VERB
app01-10442	95	13	in	in	ADP
app01-10442	95	14	figure	figure	NOUN
app01-10442	95	15	5	5	NUM
app01-10442	95	16	.	.	PUNCT
app01-10442	96	1	it	it	PRON
app01-10442	96	2	consists	consist	VERB
app01-10442	96	3	of	of	ADP
app01-10442	96	4	seven	seven	NUM
app01-10442	96	5	layers	layer	NOUN
app01-10442	96	6	,	,	PUNCT
app01-10442	96	7	with	with	ADP
app01-10442	96	8	the	the	DET
app01-10442	96	9	initial	initial	ADJ
app01-10442	96	10	four	four	NUM
app01-10442	96	11	layers	layer	NOUN
app01-10442	96	12	characterized	characterize	VERB
app01-10442	96	13	by	by	ADP
app01-10442	96	14	convolutional	convolutional	ADJ
app01-10442	96	15	structures	structure	NOUN
app01-10442	96	16	,	,	PUNCT
app01-10442	96	17	each	each	PRON
app01-10442	96	18	having	have	VERB
app01-10442	96	19	32	32	NUM
app01-10442	96	20	neurons	neuron	NOUN
app01-10442	96	21	.	.	PUNCT
app01-10442	97	1	following	follow	VERB
app01-10442	97	2	the	the	DET
app01-10442	97	3	non	non	ADJ
app01-10442	97	4	-	-	ADJ
app01-10442	97	5	convolutional	convolutional	ADJ
app01-10442	97	6	layer	layer	NOUN
app01-10442	97	7	is	be	AUX
app01-10442	97	8	a	a	DET
app01-10442	97	9	linear	linear	ADJ
app01-10442	97	10	layer	layer	NOUN
app01-10442	97	11	with	with	ADP
app01-10442	97	12	384	384	NUM
app01-10442	97	13	neurons	neuron	NOUN
app01-10442	97	14	,	,	PUNCT
app01-10442	97	15	introducing	introduce	VERB
app01-10442	97	16	a	a	DET
app01-10442	97	17	deeper	deep	ADJ
app01-10442	97	18	level	level	NOUN
app01-10442	97	19	of	of	ADP
app01-10442	97	20	abstraction	abstraction	NOUN
app01-10442	97	21	.	.	PUNCT
app01-10442	98	1	subsequently	subsequently	ADV
app01-10442	98	2	,	,	PUNCT
app01-10442	98	3	the	the	DET
app01-10442	98	4	penultimate	penultimate	NOUN
app01-10442	98	5	layer	layer	NOUN
app01-10442	98	6	is	be	AUX
app01-10442	98	7	also	also	ADV
app01-10442	98	8	linear	linear	ADJ
app01-10442	98	9	,	,	PUNCT
app01-10442	98	10	incorporating	incorporate	VERB
app01-10442	98	11	64	64	NUM
app01-10442	98	12	neurons	neuron	NOUN
app01-10442	98	13	.	.	PUNCT
app01-10442	99	1	ultimately	ultimately	ADV
app01-10442	99	2	,	,	PUNCT
app01-10442	99	3	the	the	DET
app01-10442	99	4	final	final	ADJ
app01-10442	99	5	layer	layer	NOUN
app01-10442	99	6	consists	consist	VERB
app01-10442	99	7	of	of	ADP
app01-10442	99	8	two	two	NUM
app01-10442	99	9	neurons	neuron	NOUN
app01-10442	99	10	.	.	PUNCT
app01-10442	100	1	5.1	5.1	NUM
app01-10442	100	2	.	.	PUNCT
app01-10442	100	3	validation	validation	NOUN
app01-10442	100	4	dataset	dataset	VERB
app01-10442	100	5	the	the	DET
app01-10442	100	6	validation	validation	NOUN
app01-10442	100	7	dataset	dataset	NOUN
app01-10442	100	8	encompasses	encompass	VERB
app01-10442	100	9	nearly	nearly	ADV
app01-10442	100	10	200,000	200,000	NUM
app01-10442	100	11	instances	instance	NOUN
app01-10442	100	12	,	,	PUNCT
app01-10442	100	13	with	with	ADP
app01-10442	100	14	51.2	51.2	NUM
app01-10442	100	15	%	%	NOUN
app01-10442	100	16	attributed	attribute	VERB
app01-10442	100	17	to	to	ADP
app01-10442	100	18	non	non	ADJ
app01-10442	100	19	-	-	ADJ
app01-10442	100	20	sleep	sleep	ADJ
app01-10442	100	21	spindles	spindle	NOUN
app01-10442	100	22	,	,	PUNCT
app01-10442	100	23	and	and	CCONJ
app01-10442	100	24	the	the	DET
app01-10442	100	25	remaining	remain	VERB
app01-10442	100	26	instances	instance	NOUN
app01-10442	100	27	dedicated	dedicate	VERB
app01-10442	100	28	to	to	PART
app01-10442	100	29	sleep	sleep	VERB
app01-10442	100	30	spindles	spindle	NOUN
app01-10442	100	31	.	.	PUNCT
app01-10442	101	1	this	this	DET
app01-10442	101	2	meticulously	meticulously	ADV
app01-10442	101	3	constructed	construct	VERB
app01-10442	101	4	dataset	dataset	NOUN
app01-10442	101	5	is	be	AUX
app01-10442	101	6	a	a	DET
app01-10442	101	7	subset	subset	NOUN
app01-10442	101	8	derived	derive	VERB
app01-10442	101	9	from	from	ADP
app01-10442	101	10	the	the	DET
app01-10442	101	11	extensive	extensive	ADJ
app01-10442	101	12	data	datum	NOUN
app01-10442	101	13	repository	repository	NOUN
app01-10442	101	14	provided	provide	VERB
app01-10442	101	15	by	by	ADP
app01-10442	101	16	the	the	DET
app01-10442	101	17	montreal	montreal	PROPN
app01-10442	101	18	archive	archive	NOUN
app01-10442	101	19	of	of	ADP
app01-10442	101	20	sleep	sleep	NOUN
app01-10442	101	21	studies	study	NOUN
app01-10442	101	22	(	(	PUNCT
app01-10442	101	23	mass	mass	ADJ
app01-10442	101	24	)	)	PUNCT
app01-10442	101	25	center	center	NOUN
app01-10442	101	26	.	.	PUNCT
app01-10442	102	1	the	the	DET
app01-10442	102	2	deliberate	deliberate	ADJ
app01-10442	102	3	balance	balance	NOUN
app01-10442	102	4	between	between	ADP
app01-10442	102	5	the	the	DET
app01-10442	102	6	two	two	NUM
app01-10442	102	7	classes	class	NOUN
app01-10442	102	8	ensures	ensure	VERB
app01-10442	102	9	a	a	DET
app01-10442	102	10	representative	representative	ADJ
app01-10442	102	11	and	and	CCONJ
app01-10442	102	12	unbiased	unbiased	ADJ
app01-10442	102	13	sample	sample	NOUN
app01-10442	102	14	for	for	ADP
app01-10442	102	15	thorough	thorough	ADJ
app01-10442	102	16	evaluation	evaluation	NOUN
app01-10442	102	17	,	,	PUNCT
app01-10442	102	18	fostering	foster	VERB
app01-10442	102	19	the	the	DET
app01-10442	102	20	reliability	reliability	NOUN
app01-10442	102	21	and	and	CCONJ
app01-10442	102	22	generalizability	generalizability	NOUN
app01-10442	102	23	of	of	ADP
app01-10442	102	24	the	the	DET
app01-10442	102	25	neural	neural	ADJ
app01-10442	102	26	network	network	NOUN
app01-10442	102	27	’s	’s	PART
app01-10442	102	28	performance	performance	NOUN
app01-10442	102	29	assessment	assessment	NOUN
app01-10442	102	30	.	.	PUNCT
app01-10442	103	1	the	the	DET
app01-10442	103	2	training	training	NOUN
app01-10442	103	3	and	and	CCONJ
app01-10442	103	4	testing	testing	NOUN
app01-10442	103	5	of	of	ADP
app01-10442	103	6	the	the	DET
app01-10442	103	7	neural	neural	ADJ
app01-10442	103	8	network	network	NOUN
app01-10442	103	9	architectures	architecture	NOUN
app01-10442	103	10	has	have	AUX
app01-10442	103	11	been	be	AUX
app01-10442	103	12	performed	perform	VERB
app01-10442	103	13	on	on	ADP
app01-10442	103	14	a	a	DET
app01-10442	103	15	normalized	normalize	VERB
app01-10442	103	16	data	datum	NOUN
app01-10442	103	17	set	set	VERB
app01-10442	103	18	.	.	PUNCT
app01-10442	104	1	the	the	DET
app01-10442	104	2	parameters	parameter	NOUN
app01-10442	104	3	for	for	ADP
app01-10442	104	4	the	the	DET
app01-10442	104	5	neural	neural	ADJ
app01-10442	104	6	networks	network	NOUN
app01-10442	104	7	,	,	PUNCT
app01-10442	104	8	such	such	ADJ
app01-10442	104	9	as	as	ADP
app01-10442	104	10	the	the	DET
app01-10442	104	11	size	size	NOUN
app01-10442	104	12	of	of	ADP
app01-10442	104	13	the	the	DET
app01-10442	104	14	input	input	NOUN
app01-10442	104	15	layer	layer	NOUN
app01-10442	104	16	and	and	CCONJ
app01-10442	104	17	the	the	DET
app01-10442	104	18	number	number	NOUN
app01-10442	104	19	of	of	ADP
app01-10442	104	20	epochs	epoch	NOUN
app01-10442	104	21	,	,	PUNCT
app01-10442	104	22	were	be	AUX
app01-10442	104	23	determined	determine	VERB
app01-10442	104	24	using	use	VERB
app01-10442	104	25	genetic	genetic	ADJ
app01-10442	104	26	algorithms	algorithm	NOUN
app01-10442	104	27	.	.	PUNCT
app01-10442	105	1	the	the	DET
app01-10442	105	2	number	number	NOUN
app01-10442	105	3	of	of	ADP
app01-10442	105	4	epochs	epoch	NOUN
app01-10442	105	5	varies	vary	VERB
app01-10442	105	6	for	for	ADP
app01-10442	105	7	each	each	DET
app01-10442	105	8	architecture	architecture	NOUN
app01-10442	105	9	.	.	PUNCT
app01-10442	106	1	the	the	DET
app01-10442	106	2	last	last	ADJ
app01-10442	106	3	method	method	NOUN
app01-10442	106	4	used	use	VERB
app01-10442	106	5	to	to	PART
app01-10442	106	6	process	process	VERB
app01-10442	106	7	the	the	DET
app01-10442	106	8	sleep	sleep	NOUN
app01-10442	106	9	spindle	spindle	NOUN
app01-10442	106	10	dataset	dataset	NOUN
app01-10442	106	11	,	,	PUNCT
app01-10442	106	12	the	the	DET
app01-10442	106	13	value	value	NOUN
app01-10442	106	14	-	-	PUNCT
app01-10442	106	15	based	base	VERB
app01-10442	106	16	method	method	NOUN
app01-10442	106	17	,	,	PUNCT
app01-10442	106	18	is	be	AUX
app01-10442	106	19	a	a	DET
app01-10442	106	20	simple	simple	ADJ
app01-10442	106	21	analytic	analytic	ADJ
app01-10442	106	22	method	method	NOUN
app01-10442	106	23	.	.	PUNCT
app01-10442	107	1	its	its	PRON
app01-10442	107	2	principle	principle	NOUN
app01-10442	107	3	is	be	AUX
app01-10442	107	4	that	that	SCONJ
app01-10442	107	5	it	it	PRON
app01-10442	107	6	sums	sum	VERB
app01-10442	107	7	the	the	DET
app01-10442	107	8	measured	measured	ADJ
app01-10442	107	9	values	value	NOUN
app01-10442	107	10	on	on	ADP
app01-10442	107	11	a	a	DET
app01-10442	107	12	specific	specific	ADJ
app01-10442	107	13	interval	interval	NOUN
app01-10442	107	14	and	and	CCONJ
app01-10442	107	15	compares	compare	VERB
app01-10442	107	16	the	the	DET
app01-10442	107	17	resulting	result	VERB
app01-10442	107	18	values	value	NOUN
app01-10442	107	19	with	with	ADP
app01-10442	107	20	each	each	DET
app01-10442	107	21	other	other	ADJ
app01-10442	107	22	.	.	PUNCT
app01-10442	108	1	for	for	ADP
app01-10442	108	2	this	this	DET
app01-10442	108	3	method	method	NOUN
app01-10442	108	4	,	,	PUNCT
app01-10442	108	5	it	it	PRON
app01-10442	108	6	is	be	AUX
app01-10442	108	7	crucial	crucial	ADJ
app01-10442	108	8	to	to	PART
app01-10442	108	9	set	set	VERB
app01-10442	108	10	the	the	DET
app01-10442	108	11	border	border	NOUN
app01-10442	108	12	correctly	correctly	ADV
app01-10442	108	13	.	.	PUNCT
app01-10442	109	1	at	at	ADP
app01-10442	109	2	the	the	DET
app01-10442	109	3	outset	outset	NOUN
app01-10442	109	4	of	of	ADP
app01-10442	109	5	the	the	DET
app01-10442	109	6	algorithm	algorithm	NOUN
app01-10442	109	7	,	,	PUNCT
app01-10442	109	8	the	the	DET
app01-10442	109	9	border	border	NOUN
app01-10442	109	10	was	be	AUX
app01-10442	109	11	initialized	initialize	VERB
app01-10442	109	12	to	to	ADP
app01-10442	109	13	zero	zero	NUM
app01-10442	109	14	.	.	PUNCT
app01-10442	110	1	subsequently	subsequently	ADV
app01-10442	110	2	,	,	PUNCT
app01-10442	110	3	the	the	DET
app01-10442	110	4	eeg	eeg	NOUN
app01-10442	110	5	signal	signal	NOUN
app01-10442	110	6	underwent	underwent	ADJ
app01-10442	110	7	segmentation	segmentation	NOUN
app01-10442	110	8	,	,	PUNCT
app01-10442	110	9	with	with	ADP
app01-10442	110	10	each	each	DET
app01-10442	110	11	segment	segment	NOUN
app01-10442	110	12	consistently	consistently	ADV
app01-10442	110	13	comprising	comprise	VERB
app01-10442	110	14	64	64	NUM
app01-10442	110	15	measured	measure	VERB
app01-10442	110	16	values	value	NOUN
app01-10442	110	17	.	.	PUNCT
app01-10442	111	1	the	the	DET
app01-10442	111	2	absolute	absolute	ADJ
app01-10442	111	3	sum	sum	NOUN
app01-10442	111	4	of	of	ADP
app01-10442	111	5	all	all	DET
app01-10442	111	6	values	value	NOUN
app01-10442	111	7	within	within	ADP
app01-10442	111	8	the	the	DET
app01-10442	111	9	segment	segment	NOUN
app01-10442	111	10	was	be	AUX
app01-10442	111	11	computed	compute	VERB
app01-10442	111	12	and	and	CCONJ
app01-10442	111	13	compared	compare	VERB
app01-10442	111	14	against	against	ADP
app01-10442	111	15	the	the	DET
app01-10442	111	16	border	border	NOUN
app01-10442	111	17	.	.	PUNCT
app01-10442	112	1	if	if	SCONJ
app01-10442	112	2	the	the	DET
app01-10442	112	3	computed	compute	VERB
app01-10442	112	4	value	value	NOUN
app01-10442	112	5	exceeded	exceed	VERB
app01-10442	112	6	the	the	DET
app01-10442	112	7	border	border	NOUN
app01-10442	112	8	threshold	threshold	NOUN
app01-10442	112	9	,	,	PUNCT
app01-10442	112	10	the	the	DET
app01-10442	112	11	segment	segment	NOUN
app01-10442	112	12	was	be	AUX
app01-10442	112	13	annotated	annotate	VERB
app01-10442	112	14	as	as	ADP
app01-10442	112	15	a	a	DET
app01-10442	112	16	sleep	sleep	NOUN
app01-10442	112	17	spindle	spindle	NOUN
app01-10442	112	18	.	.	PUNCT
app01-10442	113	1	the	the	DET
app01-10442	113	2	algorithm	algorithm	NOUN
app01-10442	113	3	then	then	ADV
app01-10442	113	4	tallied	tally	VERB
app01-10442	113	5	the	the	DET
app01-10442	113	6	number	number	NOUN
app01-10442	113	7	of	of	ADP
app01-10442	113	8	correctly	correctly	ADV
app01-10442	113	9	and	and	CCONJ
app01-10442	113	10	incorrectly	incorrectly	ADV
app01-10442	113	11	classified	classified	ADJ
app01-10442	113	12	segments	segment	NOUN
app01-10442	113	13	,	,	PUNCT
app01-10442	113	14	following	follow	VERB
app01-10442	113	15	which	which	PRON
app01-10442	113	16	the	the	DET
app01-10442	113	17	border	border	NOUN
app01-10442	113	18	was	be	AUX
app01-10442	113	19	incrementally	incrementally	ADV
app01-10442	113	20	adjusted	adjust	VERB
app01-10442	113	21	by	by	ADP
app01-10442	113	22	a	a	DET
app01-10442	113	23	small	small	ADJ
app01-10442	113	24	increment	increment	NOUN
app01-10442	113	25	.	.	PUNCT
app01-10442	114	1	the	the	DET
app01-10442	114	2	optimal	optimal	ADJ
app01-10442	114	3	threshold	threshold	NOUN
app01-10442	114	4	value	value	NOUN
app01-10442	114	5	for	for	ADP
app01-10442	114	6	classification	classification	NOUN
app01-10442	114	7	was	be	AUX
app01-10442	114	8	determined	determine	VERB
app01-10442	114	9	as	as	ADP
app01-10442	114	10	the	the	DET
app01-10442	114	11	one	one	NOUN
app01-10442	114	12	yielding	yield	VERB
app01-10442	114	13	the	the	DET
app01-10442	114	14	highest	high	ADJ
app01-10442	114	15	number	number	NOUN
app01-10442	114	16	of	of	ADP
app01-10442	114	17	correctly	correctly	ADV
app01-10442	114	18	identified	identify	VERB
app01-10442	114	19	spindles	spindle	NOUN
app01-10442	114	20	.	.	PUNCT
app01-10442	115	1	6	6	X
app01-10442	115	2	.	.	X
app01-10442	115	3	results	result	NOUN
app01-10442	115	4	table	table	NOUN
app01-10442	115	5	2	2	NUM
app01-10442	115	6	summarizes	summarize	NOUN
app01-10442	115	7	the	the	DET
app01-10442	115	8	results	result	NOUN
app01-10442	115	9	obtained	obtain	VERB
app01-10442	115	10	from	from	ADP
app01-10442	115	11	testing	test	VERB
app01-10442	115	12	various	various	ADJ
app01-10442	115	13	classifiers	classifier	NOUN
app01-10442	115	14	and	and	CCONJ
app01-10442	115	15	their	their	PRON
app01-10442	115	16	combinations	combination	NOUN
app01-10442	115	17	.	.	PUNCT
app01-10442	116	1	also	also	ADV
app01-10442	116	2	the	the	DET
app01-10442	116	3	figure	figure	NOUN
app01-10442	116	4	6	6	NUM
app01-10442	116	5	shows	show	VERB
app01-10442	116	6	peak	peak	NOUN
app01-10442	116	7	accuracies	accuracy	NOUN
app01-10442	116	8	achieved	achieve	VERB
app01-10442	116	9	by	by	ADP
app01-10442	116	10	the	the	DET
app01-10442	116	11	used	use	VERB
app01-10442	116	12	classifiers	classifier	NOUN
app01-10442	116	13	.	.	PUNCT
app01-10442	117	1	network	network	NOUN
app01-10442	117	2	architecture	architecture	NOUN
app01-10442	117	3	accuracy	accuracy	NOUN
app01-10442	117	4	dense	dense	ADJ
app01-10442	117	5	64.63	64.63	NUM
app01-10442	117	6	%	%	NOUN
app01-10442	117	7	lstm	lstm	NOUN
app01-10442	117	8	52.81	52.81	NUM
app01-10442	117	9	%	%	NOUN
app01-10442	118	1	cnn	cnn	PROPN
app01-10442	118	2	60.87	60.87	NUM
app01-10442	118	3	%	%	NOUN
app01-10442	118	4	cnn	cnn	PROPN
app01-10442	118	5	-	-	NOUN
app01-10442	118	6	lstm	lstm	PROPN
app01-10442	118	7	in	in	ADP
app01-10442	118	8	keras	keras	PROPN
app01-10442	118	9	52.81	52.81	NUM
app01-10442	118	10	%	%	NOUN
app01-10442	118	11	cnn	cnn	PROPN
app01-10442	118	12	-	-	NOUN
app01-10442	118	13	lstm	lstm	PROPN
app01-10442	118	14	in	in	ADP
app01-10442	118	15	torch	torch	NOUN
app01-10442	118	16	67.15	67.15	NUM
app01-10442	118	17	%	%	NOUN
app01-10442	118	18	value	value	NOUN
app01-10442	118	19	-	-	PUNCT
app01-10442	118	20	based	base	VERB
app01-10442	118	21	method	method	NOUN
app01-10442	118	22	64.12	64.12	NUM
app01-10442	118	23	%	%	NOUN
app01-10442	118	24	table	table	NOUN
app01-10442	118	25	2	2	NUM
app01-10442	118	26	.	.	PUNCT
app01-10442	118	27	best	good	ADJ
app01-10442	118	28	results	result	NOUN
app01-10442	118	29	provided	provide	VERB
app01-10442	118	30	by	by	ADP
app01-10442	118	31	the	the	DET
app01-10442	118	32	used	use	VERB
app01-10442	118	33	classifiers	classifier	NOUN
app01-10442	118	34	.	.	PUNCT
app01-10442	119	1	figures	figure	NOUN
app01-10442	119	2	7	7	NUM
app01-10442	119	3	and	and	CCONJ
app01-10442	119	4	8	8	NUM
app01-10442	119	5	present	present	VERB
app01-10442	119	6	the	the	DET
app01-10442	119	7	accuracy	accuracy	NOUN
app01-10442	119	8	and	and	CCONJ
app01-10442	119	9	loss	loss	NOUN
app01-10442	119	10	function	function	NOUN
app01-10442	119	11	values	value	NOUN
app01-10442	119	12	corresponding	correspond	VERB
app01-10442	119	13	to	to	ADP
app01-10442	119	14	the	the	DET
app01-10442	119	15	optimal	optimal	ADJ
app01-10442	119	16	neural	neural	ADJ
app01-10442	119	17	network	network	NOUN
app01-10442	119	18	configuration	configuration	NOUN
app01-10442	119	19	evaluated	evaluate	VERB
app01-10442	119	20	on	on	ADP
app01-10442	119	21	the	the	DET
app01-10442	119	22	validation	validation	NOUN
app01-10442	119	23	dataset	dataset	NOUN
app01-10442	119	24	.	.	PUNCT
app01-10442	120	1	both	both	DET
app01-10442	120	2	figures	figure	NOUN
app01-10442	120	3	are	be	AUX
app01-10442	120	4	structured	structure	VERB
app01-10442	120	5	with	with	ADP
app01-10442	120	6	the	the	DET
app01-10442	120	7	number	number	NOUN
app01-10442	120	8	of	of	ADP
app01-10442	120	9	the	the	DET
app01-10442	120	10	validation	validation	NOUN
app01-10442	120	11	set	set	VERB
app01-10442	120	12	epochs	epoch	NOUN
app01-10442	120	13	delineated	delineated	ADJ
app01-10442	120	14	on	on	ADP
app01-10442	120	15	the	the	DET
app01-10442	120	16	x	x	NOUN
app01-10442	120	17	-	-	NOUN
app01-10442	120	18	axis	axis	ADJ
app01-10442	120	19	,	,	PUNCT
app01-10442	120	20	visually	visually	ADV
app01-10442	120	21	representing	represent	VERB
app01-10442	120	22	the	the	DET
app01-10442	120	23	network	network	NOUN
app01-10442	120	24	’s	’s	PART
app01-10442	120	25	performance	performance	NOUN
app01-10442	120	26	metrics	metric	NOUN
app01-10442	120	27	across	across	ADP
app01-10442	120	28	multiple	multiple	ADJ
app01-10442	120	29	epochs	epoch	NOUN
app01-10442	120	30	.	.	PUNCT
app01-10442	121	1	78	78	NUM
app01-10442	121	2	vol	vol	NOUN
app01-10442	121	3	.	.	PUNCT
app01-10442	122	1	51/2024	51/2024	NUM
app01-10442	122	2	sleep	sleep	NOUN
app01-10442	122	3	spindle	spindle	NOUN
app01-10442	122	4	detection	detection	NOUN
app01-10442	122	5	figure	figure	NOUN
app01-10442	122	6	5	5	NUM
app01-10442	122	7	.	.	PUNCT
app01-10442	123	1	the	the	DET
app01-10442	123	2	cnn	cnn	PROPN
app01-10442	123	3	-	-	PUNCT
app01-10442	123	4	lstm	lstm	ADJ
app01-10442	123	5	architecture	architecture	NOUN
app01-10442	123	6	implemented	implement	VERB
app01-10442	123	7	in	in	ADP
app01-10442	123	8	torch	torch	NOUN
app01-10442	123	9	package	package	NOUN
app01-10442	123	10	.	.	PUNCT
app01-10442	124	1	the	the	DET
app01-10442	124	2	dropout	dropout	NOUN
app01-10442	124	3	layer	layer	NOUN
app01-10442	124	4	prevents	prevent	VERB
app01-10442	124	5	getting	getting	AUX
app01-10442	124	6	stuck	stick	VERB
app01-10442	124	7	in	in	ADP
app01-10442	124	8	the	the	DET
app01-10442	124	9	local	local	ADJ
app01-10442	124	10	minimum	minimum	NOUN
app01-10442	124	11	;	;	PUNCT
app01-10442	124	12	flatten	flatten	VERB
app01-10442	124	13	links	link	NOUN
app01-10442	124	14	cnn	cnn	PROPN
app01-10442	124	15	and	and	CCONJ
app01-10442	124	16	the	the	DET
app01-10442	124	17	linear	linear	ADJ
app01-10442	124	18	layer	layer	NOUN
app01-10442	124	19	.	.	PUNCT
app01-10442	125	1	figure	figure	VERB
app01-10442	125	2	6	6	NUM
app01-10442	125	3	.	.	PUNCT
app01-10442	126	1	the	the	DET
app01-10442	126	2	best	good	ADJ
app01-10442	126	3	classification	classification	NOUN
app01-10442	126	4	results	result	NOUN
app01-10442	126	5	(	(	PUNCT
app01-10442	126	6	peak	peak	NOUN
app01-10442	126	7	accuracies	accuracy	NOUN
app01-10442	126	8	)	)	PUNCT
app01-10442	126	9	achieved	achieve	VERB
app01-10442	126	10	by	by	ADP
app01-10442	126	11	the	the	DET
app01-10442	126	12	used	use	VERB
app01-10442	126	13	classifiers	classifier	NOUN
app01-10442	126	14	.	.	PUNCT
app01-10442	127	1	7	7	X
app01-10442	127	2	.	.	X
app01-10442	127	3	conclusion	conclusion	NOUN
app01-10442	127	4	the	the	DET
app01-10442	127	5	paper	paper	NOUN
app01-10442	127	6	examines	examine	VERB
app01-10442	127	7	the	the	DET
app01-10442	127	8	processing	processing	NOUN
app01-10442	127	9	of	of	ADP
app01-10442	127	10	eeg	eeg	NOUN
app01-10442	127	11	signals	signal	NOUN
app01-10442	127	12	during	during	ADP
app01-10442	127	13	sleep	sleep	NOUN
app01-10442	127	14	to	to	PART
app01-10442	127	15	identify	identify	VERB
app01-10442	127	16	sleep	sleep	NOUN
app01-10442	127	17	spindles	spindle	NOUN
app01-10442	127	18	using	use	VERB
app01-10442	127	19	mostly	mostly	ADV
app01-10442	127	20	various	various	ADJ
app01-10442	127	21	simple	simple	ADJ
app01-10442	127	22	and	and	CCONJ
app01-10442	127	23	hybrid	hybrid	ADJ
app01-10442	127	24	neural	neural	ADJ
app01-10442	127	25	network	network	NOUN
app01-10442	127	26	architectures	architecture	NOUN
app01-10442	127	27	.	.	PUNCT
app01-10442	128	1	the	the	DET
app01-10442	128	2	study	study	NOUN
app01-10442	128	3	used	use	VERB
app01-10442	128	4	data	datum	NOUN
app01-10442	128	5	from	from	ADP
app01-10442	128	6	the	the	DET
app01-10442	128	7	recognized	recognize	VERB
app01-10442	128	8	mass	mass	NOUN
app01-10442	128	9	archive	archive	NOUN
app01-10442	128	10	.	.	PUNCT
app01-10442	129	1	the	the	DET
app01-10442	129	2	used	use	VERB
app01-10442	129	3	dataset	dataset	NOUN
app01-10442	129	4	was	be	AUX
app01-10442	129	5	balanced	balance	VERB
app01-10442	129	6	,	,	PUNCT
app01-10442	129	7	divided	divide	VERB
app01-10442	129	8	into	into	ADP
app01-10442	129	9	training	training	NOUN
app01-10442	129	10	and	and	CCONJ
app01-10442	129	11	testing	testing	NOUN
app01-10442	129	12	sets	set	NOUN
app01-10442	129	13	,	,	PUNCT
app01-10442	129	14	and	and	CCONJ
app01-10442	129	15	used	use	VERB
app01-10442	129	16	to	to	PART
app01-10442	129	17	train	train	VERB
app01-10442	129	18	neural	neural	ADJ
app01-10442	129	19	networks	network	NOUN
app01-10442	129	20	.	.	PUNCT
app01-10442	130	1	the	the	DET
app01-10442	130	2	classification	classification	NOUN
app01-10442	130	3	accuracy	accuracy	NOUN
app01-10442	130	4	of	of	ADP
app01-10442	130	5	lstm	lstm	NOUN
app01-10442	130	6	and	and	CCONJ
app01-10442	130	7	lstm	lstm	PROPN
app01-10442	130	8	-	-	PUNCT
app01-10442	130	9	cnn	cnn	PROPN
app01-10442	130	10	networks	network	NOUN
app01-10442	130	11	was	be	AUX
app01-10442	130	12	the	the	DET
app01-10442	130	13	lowest	low	ADJ
app01-10442	130	14	at	at	ADP
app01-10442	130	15	52.81	52.81	NUM
app01-10442	130	16	%	%	NOUN
app01-10442	130	17	.	.	PUNCT
app01-10442	131	1	keras	keras	PROPN
app01-10442	131	2	’	'	PUNCT
app01-10442	131	3	dense	dense	ADJ
app01-10442	131	4	and	and	CCONJ
app01-10442	131	5	cnn	cnn	PROPN
app01-10442	131	6	networks	network	NOUN
app01-10442	131	7	showed	show	VERB
app01-10442	131	8	slightly	slightly	ADV
app01-10442	131	9	better	well	ADJ
app01-10442	131	10	results	result	NOUN
app01-10442	131	11	with	with	ADP
app01-10442	131	12	an	an	DET
app01-10442	131	13	accuracy	accuracy	NOUN
app01-10442	131	14	of	of	ADP
app01-10442	131	15	60–65	60–65	NUM
app01-10442	131	16	%	%	NOUN
app01-10442	131	17	.	.	PUNCT
app01-10442	132	1	the	the	DET
app01-10442	132	2	most	most	ADV
app01-10442	132	3	successful	successful	ADJ
app01-10442	132	4	network	network	NOUN
app01-10442	132	5	was	be	AUX
app01-10442	132	6	the	the	DET
app01-10442	132	7	cnn	cnn	PROPN
app01-10442	132	8	network	network	NOUN
app01-10442	132	9	implemented	implement	VERB
app01-10442	132	10	in	in	ADP
app01-10442	132	11	the	the	DET
app01-10442	132	12	torch	torch	NOUN
app01-10442	132	13	package	package	NOUN
app01-10442	132	14	,	,	PUNCT
app01-10442	132	15	achieving	achieve	VERB
app01-10442	132	16	accuracy	accuracy	NOUN
app01-10442	132	17	exceeding	exceed	VERB
app01-10442	132	18	67	67	NUM
app01-10442	132	19	%	%	NOUN
app01-10442	132	20	.	.	PUNCT
app01-10442	133	1	figure	figure	NOUN
app01-10442	133	2	7	7	NUM
app01-10442	133	3	.	.	PUNCT
app01-10442	134	1	the	the	DET
app01-10442	134	2	accuracy	accuracy	NOUN
app01-10442	134	3	on	on	ADP
app01-10442	134	4	the	the	DET
app01-10442	134	5	validation	validation	NOUN
app01-10442	134	6	dataset	dataset	NOUN
app01-10442	134	7	;	;	PUNCT
app01-10442	134	8	xaxis	xaxis	PROPN
app01-10442	134	9	=	=	SYM
app01-10442	134	10	number	number	NOUN
app01-10442	134	11	of	of	ADP
app01-10442	134	12	epochs	epoch	NOUN
app01-10442	134	13	over	over	ADP
app01-10442	134	14	the	the	DET
app01-10442	134	15	validation	validation	NOUN
app01-10442	134	16	dataset	dataset	NOUN
app01-10442	134	17	;	;	PUNCT
app01-10442	134	18	y	y	PROPN
app01-10442	134	19	-axis	-axis	PROPN
app01-10442	134	20	=	=	NOUN
app01-10442	134	21	the	the	DET
app01-10442	134	22	accuracy	accuracy	NOUN
app01-10442	134	23	value	value	NOUN
app01-10442	134	24	.	.	PUNCT
app01-10442	135	1	the	the	DET
app01-10442	135	2	achieved	achieve	VERB
app01-10442	135	3	classification	classification	NOUN
app01-10442	135	4	results	result	NOUN
app01-10442	135	5	are	be	AUX
app01-10442	135	6	consistent	consistent	ADJ
app01-10442	135	7	with	with	ADP
app01-10442	135	8	those	those	PRON
app01-10442	135	9	reported	report	VERB
app01-10442	135	10	in	in	ADP
app01-10442	135	11	the	the	DET
app01-10442	135	12	literature	literature	NOUN
app01-10442	135	13	,	,	PUNCT
app01-10442	135	14	where	where	SCONJ
app01-10442	135	15	the	the	DET
app01-10442	135	16	best	good	ADJ
app01-10442	135	17	results	result	NOUN
app01-10442	135	18	for	for	ADP
app01-10442	135	19	eeg	eeg	PROPN
app01-10442	135	20	sleeep	sleeep	PROPN
app01-10442	135	21	artifact	artifact	PROPN
app01-10442	135	22	classification	classification	NOUN
app01-10442	135	23	reached	reach	VERB
app01-10442	135	24	70–75	70–75	NUM
app01-10442	135	25	%	%	NOUN
app01-10442	135	26	.	.	PUNCT
app01-10442	136	1	the	the	DET
app01-10442	136	2	value	value	NOUN
app01-10442	136	3	-	-	PUNCT
app01-10442	136	4	based	base	VERB
app01-10442	136	5	method	method	NOUN
app01-10442	136	6	achieved	achieve	VERB
app01-10442	136	7	an	an	DET
app01-10442	136	8	accuracy	accuracy	NOUN
app01-10442	136	9	of	of	ADP
app01-10442	136	10	64.12	64.12	NUM
app01-10442	136	11	%	%	NOUN
app01-10442	136	12	,	,	PUNCT
app01-10442	136	13	slightly	slightly	ADV
app01-10442	136	14	below	below	ADP
app01-10442	136	15	the	the	DET
app01-10442	136	16	state	state	NOUN
app01-10442	136	17	-	-	PUNCT
app01-10442	136	18	of	of	ADP
app01-10442	136	19	-	-	PUNCT
app01-10442	136	20	the	the	DET
app01-10442	136	21	-	-	PUNCT
app01-10442	136	22	art	art	NOUN
app01-10442	136	23	.	.	PUNCT
app01-10442	137	1	it	it	PRON
app01-10442	137	2	may	may	AUX
app01-10442	137	3	be	be	AUX
app01-10442	137	4	worth	worth	ADJ
app01-10442	137	5	refining	refine	VERB
app01-10442	137	6	the	the	DET
app01-10442	137	7	neural	neural	ADJ
app01-10442	137	8	network	network	NOUN
app01-10442	137	9	parameters	parameter	NOUN
app01-10442	137	10	by	by	ADP
app01-10442	137	11	extending	extend	VERB
app01-10442	137	12	the	the	DET
app01-10442	137	13	state	state	NOUN
app01-10442	137	14	area	area	NOUN
app01-10442	137	15	of	of	ADP
app01-10442	137	16	input	input	NOUN
app01-10442	137	17	parameters	parameter	NOUN
app01-10442	137	18	to	to	PART
app01-10442	137	19	improve	improve	VERB
app01-10442	137	20	performance	performance	NOUN
app01-10442	137	21	.	.	PUNCT
app01-10442	138	1	also	also	ADV
app01-10442	138	2	,	,	PUNCT
app01-10442	138	3	the	the	DET
app01-10442	138	4	potential	potential	ADJ
app01-10442	138	5	benefits	benefit	NOUN
app01-10442	138	6	of	of	ADP
app01-10442	138	7	the	the	DET
app01-10442	138	8	next	next	ADJ
app01-10442	138	9	alternative	alternative	ADJ
app01-10442	138	10	hybrid	hybrid	ADJ
app01-10442	138	11	deep	deep	ADJ
app01-10442	138	12	learning	learning	NOUN
app01-10442	138	13	architectures	architecture	NOUN
app01-10442	138	14	in	in	ADP
app01-10442	138	15	identifying	identify	VERB
app01-10442	138	16	sleep	sleep	NOUN
app01-10442	138	17	spindles	spindle	NOUN
app01-10442	138	18	can	can	AUX
app01-10442	138	19	be	be	AUX
app01-10442	138	20	considered	consider	VERB
app01-10442	138	21	.	.	PUNCT
app01-10442	139	1	acknowledgements	acknowledgement	NOUN
app01-10442	139	2	79	79	NUM
app01-10442	139	3	jan	jan	PROPN
app01-10442	139	4	rychlík	rychlík	NOUN
app01-10442	139	5	,	,	PUNCT
app01-10442	139	6	roman	roman	ADJ
app01-10442	139	7	mouček	mouček	PROPN
app01-10442	139	8	acta	acta	PROPN
app01-10442	139	9	polytechnica	polytechnica	PROPN
app01-10442	139	10	ctu	ctu	PROPN
app01-10442	139	11	proceedings	proceeding	NOUN
app01-10442	139	12	figure	figure	VERB
app01-10442	139	13	8	8	NUM
app01-10442	139	14	.	.	PUNCT
app01-10442	140	1	the	the	DET
app01-10442	140	2	loss	loss	NOUN
app01-10442	140	3	function	function	NOUN
app01-10442	140	4	on	on	ADP
app01-10442	140	5	the	the	DET
app01-10442	140	6	validation	validation	NOUN
app01-10442	140	7	dataset	dataset	NOUN
app01-10442	140	8	;	;	PUNCT
app01-10442	140	9	x	x	X
app01-10442	140	10	-	-	ADJ
app01-10442	140	11	axis	axis	ADJ
app01-10442	140	12	=	=	NOUN
app01-10442	140	13	number	number	NOUN
app01-10442	140	14	of	of	ADP
app01-10442	140	15	epochs	epoch	NOUN
app01-10442	140	16	over	over	ADP
app01-10442	140	17	the	the	DET
app01-10442	140	18	validation	validation	NOUN
app01-10442	140	19	dataset	dataset	NOUN
app01-10442	140	20	;	;	PUNCT
app01-10442	140	21	y	y	PROPN
app01-10442	140	22	-axis	-axis	PROPN
app01-10442	140	23	=	=	NOUN
app01-10442	140	24	the	the	DET
app01-10442	140	25	loss	loss	NOUN
app01-10442	140	26	value	value	NOUN
app01-10442	140	27	.	.	PUNCT
app01-10442	141	1	this	this	DET
app01-10442	141	2	work	work	NOUN
app01-10442	141	3	was	be	AUX
app01-10442	141	4	supported	support	VERB
app01-10442	141	5	by	by	ADP
app01-10442	141	6	the	the	DET
app01-10442	141	7	university	university	NOUN
app01-10442	141	8	-	-	PUNCT
app01-10442	141	9	specific	specific	ADJ
app01-10442	141	10	research	research	NOUN
app01-10442	141	11	project	project	NOUN
app01-10442	141	12	sgs-2022	sgs-2022	NOUN
app01-10442	141	13	-	-	PUNCT
app01-10442	141	14	016	016	NUM
app01-10442	141	15	advanced	advanced	ADJ
app01-10442	141	16	methods	method	NOUN
app01-10442	141	17	of	of	ADP
app01-10442	141	18	data	datum	NOUN
app01-10442	141	19	processing	processing	NOUN
app01-10442	141	20	and	and	CCONJ
app01-10442	141	21	analysis	analysis	NOUN
app01-10442	141	22	(	(	PUNCT
app01-10442	141	23	project	project	NOUN
app01-10442	141	24	sgs-2022	sgs-2022	NOUN
app01-10442	141	25	-	-	PUNCT
app01-10442	141	26	016	016	NUM
app01-10442	141	27	)	)	PUNCT
app01-10442	141	28	.	.	PUNCT
app01-10442	142	1	references	reference	NOUN
app01-10442	142	2	[	[	X
app01-10442	142	3	1	1	NUM
app01-10442	142	4	]	]	PUNCT
app01-10442	142	5	p.	p.	NOUN
app01-10442	142	6	nagabushanam	nagabushanam	PROPN
app01-10442	142	7	,	,	PUNCT
app01-10442	142	8	s.	s.	PROPN
app01-10442	142	9	t.	t.	PROPN
app01-10442	142	10	george	george	PROPN
app01-10442	142	11	,	,	PUNCT
app01-10442	142	12	s.	s.	PROPN
app01-10442	142	13	radha	radha	PROPN
app01-10442	142	14	.	.	PUNCT
app01-10442	143	1	eeg	eeg	PROPN
app01-10442	143	2	signal	signal	NOUN
app01-10442	143	3	classification	classification	NOUN
app01-10442	143	4	using	use	VERB
app01-10442	143	5	lstm	lstm	NOUN
app01-10442	143	6	and	and	CCONJ
app01-10442	143	7	improved	improve	VERB
app01-10442	143	8	neural	neural	ADJ
app01-10442	143	9	network	network	NOUN
app01-10442	143	10	algorithms	algorithm	NOUN
app01-10442	143	11	.	.	PUNCT
app01-10442	144	1	soft	soft	ADJ
app01-10442	144	2	computing	computing	NOUN
app01-10442	144	3	7:9981–10003	7:9981–10003	NUM
app01-10442	144	4	,	,	PUNCT
app01-10442	144	5	2020	2020	NUM
app01-10442	144	6	.	.	PUNCT
app01-10442	145	1	https://doi.org/10.1007/s00500-019-04515-0	https://doi.org/10.1007/s00500-019-04515-0	NUM
app01-10442	146	1	[	[	X
app01-10442	146	2	2	2	NUM
app01-10442	146	3	]	]	X
app01-10442	146	4	n.	n.	NOUN
app01-10442	146	5	grieger	grieger	PROPN
app01-10442	146	6	,	,	PUNCT
app01-10442	146	7	j.	j.	PROPN
app01-10442	146	8	t.	t.	PROPN
app01-10442	146	9	c.	c.	PROPN
app01-10442	146	10	schwabedal	schwabedal	PROPN
app01-10442	146	11	,	,	PUNCT
app01-10442	146	12	s.	s.	PROPN
app01-10442	146	13	wendel	wendel	PROPN
app01-10442	146	14	,	,	PUNCT
app01-10442	146	15	et	et	PROPN
app01-10442	146	16	al	al	PROPN
app01-10442	146	17	.	.	PROPN
app01-10442	146	18	automated	automate	VERB
app01-10442	146	19	scoring	scoring	NOUN
app01-10442	146	20	of	of	ADP
app01-10442	146	21	pre	pre	ADJ
app01-10442	146	22	-	-	ADJ
app01-10442	146	23	rem	rem	ADJ
app01-10442	146	24	sleep	sleep	NOUN
app01-10442	146	25	in	in	ADP
app01-10442	146	26	mice	mouse	NOUN
app01-10442	146	27	with	with	ADP
app01-10442	146	28	deep	deep	ADJ
app01-10442	146	29	learning	learning	NOUN
app01-10442	146	30	.	.	PUNCT
app01-10442	147	1	scientific	scientific	ADJ
app01-10442	147	2	reports	report	NOUN
app01-10442	147	3	11:12245	11:12245	NUM
app01-10442	147	4	,	,	PUNCT
app01-10442	147	5	2021	2021	NUM
app01-10442	147	6	.	.	PUNCT
app01-10442	148	1	https://doi.org/10.1038/s41598-021-91286-0	https://doi.org/10.1038/s41598-021-91286-0	NUM
app01-10442	148	2	[	[	X
app01-10442	148	3	3	3	NUM
app01-10442	148	4	]	]	X
app01-10442	148	5	d.	d.	PROPN
app01-10442	148	6	zhao	zhao	PROPN
app01-10442	148	7	,	,	PUNCT
app01-10442	148	8	r.	r.	PROPN
app01-10442	148	9	jiang	jiang	PROPN
app01-10442	148	10	,	,	PUNCT
app01-10442	148	11	m.	m.	PROPN
app01-10442	148	12	feng	feng	PROPN
app01-10442	148	13	,	,	PUNCT
app01-10442	148	14	et	et	PROPN
app01-10442	148	15	al	al	PROPN
app01-10442	148	16	.	.	PUNCT
app01-10442	149	1	a	a	DET
app01-10442	149	2	deep	deep	ADJ
app01-10442	149	3	learning	learning	NOUN
app01-10442	149	4	algorithm	algorithm	NOUN
app01-10442	149	5	based	base	VERB
app01-10442	149	6	on	on	ADP
app01-10442	149	7	1d	1d	NUM
app01-10442	149	8	cnn	cnn	PROPN
app01-10442	149	9	-	-	PUNCT
app01-10442	149	10	lstm	lstm	PROPN
app01-10442	149	11	for	for	ADP
app01-10442	149	12	automatic	automatic	ADJ
app01-10442	149	13	sleep	sleep	NOUN
app01-10442	149	14	staging	stage	VERB
app01-10442	149	15	.	.	PUNCT
app01-10442	150	1	technology	technology	NOUN
app01-10442	150	2	and	and	CCONJ
app01-10442	150	3	health	health	NOUN
app01-10442	150	4	care	care	NOUN
app01-10442	150	5	30(2):323–336	30(2):323–336	PROPN
app01-10442	150	6	,	,	PUNCT
app01-10442	150	7	2022	2022	NUM
app01-10442	150	8	.	.	PUNCT
app01-10442	150	9	https://doi.org/10.3233/thc-212847	https://doi.org/10.3233/thc-212847	X
app01-10442	151	1	[	[	X
app01-10442	151	2	4	4	NUM
app01-10442	151	3	]	]	X
app01-10442	151	4	i.	i.	PROPN
app01-10442	151	5	b.	b.	PROPN
app01-10442	151	6	iotchev	iotchev	PROPN
app01-10442	151	7	,	,	PUNCT
app01-10442	151	8	e.	e.	PROPN
app01-10442	151	9	kubinyi	kubinyi	PROPN
app01-10442	151	10	.	.	PROPN
app01-10442	151	11	shared	share	VERB
app01-10442	151	12	and	and	CCONJ
app01-10442	151	13	unique	unique	ADJ
app01-10442	151	14	features	feature	NOUN
app01-10442	151	15	of	of	ADP
app01-10442	151	16	mammalian	mammalian	ADJ
app01-10442	151	17	sleep	sleep	NOUN
app01-10442	151	18	spindles	spindle	NOUN
app01-10442	151	19	–	–	PUNCT
app01-10442	151	20	insights	insight	NOUN
app01-10442	151	21	from	from	ADP
app01-10442	151	22	new	new	ADJ
app01-10442	151	23	and	and	CCONJ
app01-10442	151	24	old	old	ADJ
app01-10442	151	25	animal	animal	NOUN
app01-10442	151	26	modelss	modelss	NOUN
app01-10442	151	27	.	.	PUNCT
app01-10442	152	1	biological	biological	ADJ
app01-10442	152	2	reviews	review	NOUN
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