id	sid	tid	token	lemma	pos
ajst-16785	1	1	academic	academic	ADJ
ajst-16785	1	2	journal	journal	NOUN
ajst-16785	1	3	of	of	ADP
ajst-16785	1	4	science	science	NOUN
ajst-16785	1	5	and	and	CCONJ
ajst-16785	1	6	technology	technology	NOUN
ajst-16785	1	7	issn	issn	NOUN
ajst-16785	1	8	:	:	PUNCT
ajst-16785	1	9	2771	2771	NUM
ajst-16785	1	10	-	-	SYM
ajst-16785	1	11	3032	3032	NUM
ajst-16785	1	12	|	|	NOUN
ajst-16785	1	13	vol	vol	NOUN
ajst-16785	1	14	.	.	PROPN
ajst-16785	2	1	9	9	NUM
ajst-16785	2	2	,	,	PUNCT
ajst-16785	2	3	no	no	INTJ
ajst-16785	2	4	.	.	NOUN
ajst-16785	2	5	1	1	NUM
ajst-16785	2	6	,	,	PUNCT
ajst-16785	2	7	2024	2024	NUM
ajst-16785	2	8	176	176	NUM
ajst-16785	2	9	inception	inception	NOUN
ajst-16785	2	10	meets	meet	VERB
ajst-16785	2	11	swin	swin	PROPN
ajst-16785	2	12	transformer	transformer	PROPN
ajst-16785	2	13	:	:	PUNCT
ajst-16785	2	14	a	a	DET
ajst-16785	2	15	novel	novel	ADJ
ajst-16785	2	16	approach	approach	NOUN
ajst-16785	2	17	for	for	ADP
ajst-16785	2	18	metal	metal	NOUN
ajst-16785	2	19	defect	defect	NOUN
ajst-16785	2	20	recognition	recognition	NOUN
ajst-16785	2	21	donglin	donglin	PROPN
ajst-16785	2	22	tang	tang	PROPN
ajst-16785	2	23	*	*	PROPN
ajst-16785	2	24	,	,	PUNCT
ajst-16785	2	25	yunliang	yunliang	PROPN
ajst-16785	2	26	zhao	zhao	PROPN
ajst-16785	2	27	school	school	NOUN
ajst-16785	2	28	of	of	ADP
ajst-16785	2	29	electrical	electrical	ADJ
ajst-16785	2	30	and	and	CCONJ
ajst-16785	2	31	mechanical	mechanical	ADJ
ajst-16785	2	32	engineering	engineering	NOUN
ajst-16785	2	33	,	,	PUNCT
ajst-16785	2	34	southwest	southwest	ADJ
ajst-16785	2	35	petroleum	petroleum	PROPN
ajst-16785	2	36	university	university	PROPN
ajst-16785	2	37	,	,	PUNCT
ajst-16785	2	38	chengdu	chengdu	PROPN
ajst-16785	2	39	610500	610500	NUM
ajst-16785	2	40	,	,	PUNCT
ajst-16785	2	41	china	china	PROPN
ajst-16785	2	42	*	*	PUNCT
ajst-16785	2	43	corresponding	correspond	VERB
ajst-16785	2	44	author	author	NOUN
ajst-16785	2	45	abstract	abstract	NOUN
ajst-16785	2	46	:	:	PUNCT
ajst-16785	2	47	the	the	DET
ajst-16785	2	48	detection	detection	NOUN
ajst-16785	2	49	of	of	ADP
ajst-16785	2	50	metal	metal	NOUN
ajst-16785	2	51	defects	defect	NOUN
ajst-16785	2	52	with	with	ADP
ajst-16785	2	53	high	high	ADJ
ajst-16785	2	54	precision	precision	NOUN
ajst-16785	2	55	and	and	CCONJ
ajst-16785	2	56	efficiency	efficiency	NOUN
ajst-16785	2	57	is	be	AUX
ajst-16785	2	58	a	a	DET
ajst-16785	2	59	significant	significant	ADJ
ajst-16785	2	60	challenge	challenge	NOUN
ajst-16785	2	61	in	in	ADP
ajst-16785	2	62	modern	modern	ADJ
ajst-16785	2	63	industry	industry	NOUN
ajst-16785	2	64	.	.	PUNCT
ajst-16785	3	1	existing	exist	VERB
ajst-16785	3	2	machine	machine	NOUN
ajst-16785	3	3	learning	learn	VERB
ajst-16785	3	4	methods	method	NOUN
ajst-16785	3	5	for	for	ADP
ajst-16785	3	6	recognizing	recognize	VERB
ajst-16785	3	7	common	common	ADJ
ajst-16785	3	8	metal	metal	NOUN
ajst-16785	3	9	surface	surface	NOUN
ajst-16785	3	10	defects	defect	NOUN
ajst-16785	3	11	heavily	heavily	ADV
ajst-16785	3	12	rely	rely	VERB
ajst-16785	3	13	on	on	ADP
ajst-16785	3	14	expert	expert	ADJ
ajst-16785	3	15	knowledge	knowledge	NOUN
ajst-16785	3	16	for	for	ADP
ajst-16785	3	17	manual	manual	ADJ
ajst-16785	3	18	feature	feature	NOUN
ajst-16785	3	19	extraction	extraction	NOUN
ajst-16785	3	20	.	.	PUNCT
ajst-16785	4	1	conventional	conventional	ADJ
ajst-16785	4	2	deep	deep	ADJ
ajst-16785	4	3	learning	learning	NOUN
ajst-16785	4	4	methods	method	NOUN
ajst-16785	4	5	face	face	VERB
ajst-16785	4	6	challenges	challenge	NOUN
ajst-16785	4	7	in	in	ADP
ajst-16785	4	8	capturing	capture	VERB
ajst-16785	4	9	global	global	ADJ
ajst-16785	4	10	feature	feature	NOUN
ajst-16785	4	11	information	information	NOUN
ajst-16785	4	12	from	from	ADP
ajst-16785	4	13	defect	defect	NOUN
ajst-16785	4	14	images	image	NOUN
ajst-16785	4	15	or	or	CCONJ
ajst-16785	4	16	defect	defect	VERB
ajst-16785	4	17	detection	detection	NOUN
ajst-16785	4	18	signals.to	signals.to	PRON
ajst-16785	4	19	address	address	VERB
ajst-16785	4	20	this	this	DET
ajst-16785	4	21	issue	issue	NOUN
ajst-16785	4	22	,	,	PUNCT
ajst-16785	4	23	we	we	PRON
ajst-16785	4	24	proposed	propose	VERB
ajst-16785	4	25	a	a	DET
ajst-16785	4	26	metal	metal	NOUN
ajst-16785	4	27	defect	defect	NOUN
ajst-16785	4	28	recognition	recognition	NOUN
ajst-16785	4	29	method	method	NOUN
ajst-16785	4	30	based	base	VERB
ajst-16785	4	31	on	on	ADP
ajst-16785	4	32	an	an	DET
ajst-16785	4	33	inceptionfused	inceptionfused	ADJ
ajst-16785	4	34	swin	swin	PROPN
ajst-16785	4	35	transformer	transformer	PROPN
ajst-16785	4	36	model	model	NOUN
ajst-16785	4	37	.	.	PUNCT
ajst-16785	5	1	the	the	DET
ajst-16785	5	2	method	method	NOUN
ajst-16785	5	3	combines	combine	VERB
ajst-16785	5	4	the	the	DET
ajst-16785	5	5	adaptive	adaptive	ADJ
ajst-16785	5	6	local	local	ADJ
ajst-16785	5	7	feature	feature	NOUN
ajst-16785	5	8	extraction	extraction	NOUN
ajst-16785	5	9	capability	capability	NOUN
ajst-16785	5	10	of	of	ADP
ajst-16785	5	11	the	the	DET
ajst-16785	5	12	inception	inception	ADJ
ajst-16785	5	13	structure	structure	NOUN
ajst-16785	5	14	with	with	ADP
ajst-16785	5	15	the	the	DET
ajst-16785	5	16	advantage	advantage	NOUN
ajst-16785	5	17	of	of	ADP
ajst-16785	5	18	the	the	DET
ajst-16785	5	19	swin	swin	PROPN
ajst-16785	5	20	transformer	transformer	NOUN
ajst-16785	5	21	in	in	ADP
ajst-16785	5	22	capturing	capture	VERB
ajst-16785	5	23	global	global	ADJ
ajst-16785	5	24	feature	feature	NOUN
ajst-16785	5	25	information	information	NOUN
ajst-16785	5	26	from	from	ADP
ajst-16785	5	27	defect	defect	ADJ
ajst-16785	5	28	signals	signal	NOUN
ajst-16785	5	29	.	.	PUNCT
ajst-16785	6	1	additionally	additionally	ADV
ajst-16785	6	2	,	,	PUNCT
ajst-16785	6	3	it	it	PRON
ajst-16785	6	4	utilizes	utilize	VERB
ajst-16785	6	5	the	the	DET
ajst-16785	6	6	channel	channel	NOUN
ajst-16785	6	7	-	-	PUNCT
ajst-16785	6	8	coordinate	coordinate	NOUN
ajst-16785	6	9	attention	attention	NOUN
ajst-16785	6	10	module	module	NOUN
ajst-16785	6	11	(	(	PUNCT
ajst-16785	6	12	coordattention	coordattention	NOUN
ajst-16785	6	13	)	)	PUNCT
ajst-16785	6	14	to	to	PART
ajst-16785	6	15	highlight	highlight	VERB
ajst-16785	6	16	important	important	ADJ
ajst-16785	6	17	feature	feature	NOUN
ajst-16785	6	18	channels	channel	NOUN
ajst-16785	6	19	.	.	PUNCT
ajst-16785	7	1	experimental	experimental	ADJ
ajst-16785	7	2	results	result	NOUN
ajst-16785	7	3	demonstrate	demonstrate	VERB
ajst-16785	7	4	the	the	DET
ajst-16785	7	5	effectiveness	effectiveness	NOUN
ajst-16785	7	6	of	of	ADP
ajst-16785	7	7	the	the	DET
ajst-16785	7	8	proposed	propose	VERB
ajst-16785	7	9	method	method	NOUN
ajst-16785	7	10	on	on	ADP
ajst-16785	7	11	the	the	DET
ajst-16785	7	12	ultrasonic	ultrasonic	ADJ
ajst-16785	7	13	defect	defect	NOUN
ajst-16785	7	14	grayscale	grayscale	NOUN
ajst-16785	7	15	image	image	NOUN
ajst-16785	7	16	dataset	dataset	NOUN
ajst-16785	7	17	(	(	PUNCT
ajst-16785	7	18	ulfsl	ulfsl	NOUN
ajst-16785	7	19	-	-	PUNCT
ajst-16785	7	20	det	det	NOUN
ajst-16785	7	21	)	)	PUNCT
ajst-16785	7	22	and	and	CCONJ
ajst-16785	7	23	the	the	DET
ajst-16785	7	24	publicly	publicly	ADV
ajst-16785	7	25	available	available	ADJ
ajst-16785	7	26	image	image	NOUN
ajst-16785	7	27	-	-	PUNCT
ajst-16785	7	28	based	base	VERB
ajst-16785	7	29	metal	metal	NOUN
ajst-16785	7	30	defect	defect	NOUN
ajst-16785	7	31	dataset	dataset	NOUN
ajst-16785	7	32	(	(	PUNCT
ajst-16785	7	33	neu	neu	NOUN
ajst-16785	7	34	-	-	PUNCT
ajst-16785	7	35	cls	cls	NOUN
ajst-16785	7	36	)	)	PUNCT
ajst-16785	7	37	,	,	PUNCT
ajst-16785	7	38	achieving	achieve	VERB
ajst-16785	7	39	recognition	recognition	NOUN
ajst-16785	7	40	accuracies	accuracy	NOUN
ajst-16785	7	41	of	of	ADP
ajst-16785	7	42	98.1	98.1	NUM
ajst-16785	7	43	%	%	NOUN
ajst-16785	7	44	and	and	CCONJ
ajst-16785	7	45	99.8	99.8	NUM
ajst-16785	7	46	%	%	NOUN
ajst-16785	7	47	,	,	PUNCT
ajst-16785	7	48	respectively	respectively	ADV
ajst-16785	7	49	.	.	PUNCT
ajst-16785	8	1	the	the	DET
ajst-16785	8	2	method	method	NOUN
ajst-16785	8	3	exhibits	exhibit	VERB
ajst-16785	8	4	high	high	ADJ
ajst-16785	8	5	effectiveness	effectiveness	NOUN
ajst-16785	8	6	in	in	ADP
ajst-16785	8	7	recognizing	recognize	VERB
ajst-16785	8	8	metal	metal	NOUN
ajst-16785	8	9	defect	defect	NOUN
ajst-16785	8	10	signals	signal	NOUN
ajst-16785	8	11	in	in	ADP
ajst-16785	8	12	grayscale	grayscale	NOUN
ajst-16785	8	13	images	image	NOUN
ajst-16785	8	14	,	,	PUNCT
ajst-16785	8	15	and	and	CCONJ
ajst-16785	8	16	it	it	PRON
ajst-16785	8	17	demonstrates	demonstrate	VERB
ajst-16785	8	18	strong	strong	ADJ
ajst-16785	8	19	generality	generality	NOUN
ajst-16785	8	20	for	for	ADP
ajst-16785	8	21	image	image	NOUN
ajst-16785	8	22	-	-	PUNCT
ajst-16785	8	23	based	base	VERB
ajst-16785	8	24	metal	metal	NOUN
ajst-16785	8	25	defect	defect	NOUN
ajst-16785	8	26	recognition	recognition	NOUN
ajst-16785	8	27	.	.	PUNCT
ajst-16785	9	1	keywords	keyword	NOUN
ajst-16785	9	2	:	:	PUNCT
ajst-16785	9	3	metal	metal	NOUN
ajst-16785	9	4	defect	defect	NOUN
ajst-16785	9	5	,	,	PUNCT
ajst-16785	9	6	inception	inception	NOUN
ajst-16785	9	7	,	,	PUNCT
ajst-16785	9	8	swin	swin	PROPN
ajst-16785	9	9	transformer	transformer	PROPN
ajst-16785	9	10	,	,	PUNCT
ajst-16785	9	11	signals	signal	NOUN
ajst-16785	9	12	in	in	ADP
ajst-16785	9	13	grayscale	grayscale	NOUN
ajst-16785	9	14	images	image	NOUN
ajst-16785	9	15	.	.	PUNCT
ajst-16785	10	1	1	1	X
ajst-16785	10	2	.	.	X
ajst-16785	10	3	introduction	introduction	NOUN
ajst-16785	10	4	surface	surface	NOUN
ajst-16785	10	5	defects	defect	NOUN
ajst-16785	10	6	of	of	ADP
ajst-16785	10	7	industrial	industrial	ADJ
ajst-16785	10	8	products	product	NOUN
ajst-16785	10	9	,	,	PUNCT
ajst-16785	10	10	such	such	ADJ
ajst-16785	10	11	as	as	ADP
ajst-16785	10	12	those	those	PRON
ajst-16785	10	13	found	find	VERB
ajst-16785	10	14	in	in	ADP
ajst-16785	10	15	machinery	machinery	NOUN
ajst-16785	10	16	,	,	PUNCT
ajst-16785	10	17	chemical	chemical	NOUN
ajst-16785	10	18	,	,	PUNCT
ajst-16785	10	19	and	and	CCONJ
ajst-16785	10	20	petroleum	petroleum	NOUN
ajst-16785	10	21	fields	field	NOUN
ajst-16785	10	22	,	,	PUNCT
ajst-16785	10	23	can	can	AUX
ajst-16785	10	24	significantly	significantly	ADV
ajst-16785	10	25	impact	impact	VERB
ajst-16785	10	26	the	the	DET
ajst-16785	10	27	quality	quality	NOUN
ajst-16785	10	28	,	,	PUNCT
ajst-16785	10	29	safety	safety	NOUN
ajst-16785	10	30	,	,	PUNCT
ajst-16785	10	31	and	and	CCONJ
ajst-16785	10	32	availability	availability	NOUN
ajst-16785	10	33	of	of	ADP
ajst-16785	10	34	products	product	NOUN
ajst-16785	10	35	.	.	PUNCT
ajst-16785	11	1	therefore	therefore	ADV
ajst-16785	11	2	,	,	PUNCT
ajst-16785	11	3	the	the	DET
ajst-16785	11	4	detection	detection	NOUN
ajst-16785	11	5	and	and	CCONJ
ajst-16785	11	6	identification	identification	NOUN
ajst-16785	11	7	of	of	ADP
ajst-16785	11	8	metal	metal	NOUN
ajst-16785	11	9	surface	surface	NOUN
ajst-16785	11	10	defects	defect	NOUN
ajst-16785	11	11	have	have	AUX
ajst-16785	11	12	become	become	VERB
ajst-16785	11	13	a	a	DET
ajst-16785	11	14	prominent	prominent	ADJ
ajst-16785	11	15	research	research	NOUN
ajst-16785	11	16	area	area	NOUN
ajst-16785	11	17	in	in	ADP
ajst-16785	11	18	modern	modern	ADJ
ajst-16785	11	19	industry[1	industry[1	NOUN
ajst-16785	11	20	,	,	PUNCT
ajst-16785	11	21	2	2	NUM
ajst-16785	11	22	]	]	PUNCT
ajst-16785	11	23	.	.	PUNCT
ajst-16785	12	1	traditional	traditional	ADJ
ajst-16785	12	2	non	non	ADJ
ajst-16785	12	3	-	-	ADJ
ajst-16785	12	4	destructive	destructive	ADJ
ajst-16785	12	5	testing	testing	NOUN
ajst-16785	12	6	(	(	PUNCT
ajst-16785	12	7	ndt	ndt	NOUN
ajst-16785	12	8	)	)	PUNCT
ajst-16785	12	9	methods	method	NOUN
ajst-16785	12	10	,	,	PUNCT
ajst-16785	12	11	including	include	VERB
ajst-16785	12	12	ultrasonic	ultrasonic	NOUN
ajst-16785	12	13	,	,	PUNCT
ajst-16785	12	14	eddy	eddy	PROPN
ajst-16785	12	15	current	current	PROPN
ajst-16785	12	16	,	,	PUNCT
ajst-16785	12	17	and	and	CCONJ
ajst-16785	12	18	magnetic	magnetic	ADJ
ajst-16785	12	19	particle	particle	NOUN
ajst-16785	12	20	testing	testing	NOUN
ajst-16785	12	21	,	,	PUNCT
ajst-16785	12	22	have	have	AUX
ajst-16785	12	23	been	be	AUX
ajst-16785	12	24	widely	widely	ADV
ajst-16785	12	25	employed	employ	VERB
ajst-16785	12	26	in	in	ADP
ajst-16785	12	27	metal	metal	NOUN
ajst-16785	12	28	defect	defect	NOUN
ajst-16785	12	29	detection[3	detection[3	ADP
ajst-16785	12	30	]	]	PUNCT
ajst-16785	12	31	.	.	PUNCT
ajst-16785	13	1	however	however	ADV
ajst-16785	13	2	,	,	PUNCT
ajst-16785	13	3	these	these	DET
ajst-16785	13	4	methods	method	NOUN
ajst-16785	13	5	are	be	AUX
ajst-16785	13	6	often	often	ADV
ajst-16785	13	7	limited	limit	VERB
ajst-16785	13	8	by	by	ADP
ajst-16785	13	9	slow	slow	ADJ
ajst-16785	13	10	detection	detection	NOUN
ajst-16785	13	11	speeds	speed	NOUN
ajst-16785	13	12	and	and	CCONJ
ajst-16785	13	13	high	high	ADJ
ajst-16785	13	14	dependence	dependence	NOUN
ajst-16785	13	15	on	on	ADP
ajst-16785	13	16	expert	expert	ADJ
ajst-16785	13	17	knowledge	knowledge	NOUN
ajst-16785	13	18	,	,	PUNCT
ajst-16785	13	19	which	which	PRON
ajst-16785	13	20	no	no	ADV
ajst-16785	13	21	longer	long	ADV
ajst-16785	13	22	meet	meet	VERB
ajst-16785	13	23	the	the	DET
ajst-16785	13	24	requirements	requirement	NOUN
ajst-16785	13	25	of	of	ADP
ajst-16785	13	26	modern	modern	ADJ
ajst-16785	13	27	industry	industry	NOUN
ajst-16785	13	28	.	.	PUNCT
ajst-16785	14	1	with	with	ADP
ajst-16785	14	2	the	the	DET
ajst-16785	14	3	advancement	advancement	NOUN
ajst-16785	14	4	of	of	ADP
ajst-16785	14	5	pattern	pattern	NOUN
ajst-16785	14	6	recognition	recognition	NOUN
ajst-16785	14	7	technology	technology	NOUN
ajst-16785	14	8	(	(	PUNCT
ajst-16785	14	9	prt	prt	PROPN
ajst-16785	14	10	)	)	PUNCT
ajst-16785	14	11	,	,	PUNCT
ajst-16785	14	12	the	the	DET
ajst-16785	14	13	combination	combination	NOUN
ajst-16785	14	14	of	of	ADP
ajst-16785	14	15	ndt	ndt	PROPN
ajst-16785	14	16	and	and	CCONJ
ajst-16785	14	17	prt	prt	PROPN
ajst-16785	14	18	has	have	AUX
ajst-16785	14	19	led	lead	VERB
ajst-16785	14	20	to	to	ADP
ajst-16785	14	21	significant	significant	ADJ
ajst-16785	14	22	improvements	improvement	NOUN
ajst-16785	14	23	in	in	ADP
ajst-16785	14	24	defect	defect	NOUN
ajst-16785	14	25	detection	detection	NOUN
ajst-16785	14	26	efficiency	efficiency	NOUN
ajst-16785	14	27	,	,	PUNCT
ajst-16785	14	28	enabling	enable	VERB
ajst-16785	14	29	automatic	automatic	ADJ
ajst-16785	14	30	defect	defect	NOUN
ajst-16785	14	31	detection	detection	NOUN
ajst-16785	14	32	and	and	CCONJ
ajst-16785	14	33	evaluation	evaluation	NOUN
ajst-16785	14	34	.	.	PUNCT
ajst-16785	15	1	current	current	ADJ
ajst-16785	15	2	methods	method	NOUN
ajst-16785	15	3	for	for	ADP
ajst-16785	15	4	metal	metal	NOUN
ajst-16785	15	5	defect	defect	NOUN
ajst-16785	15	6	detection	detection	NOUN
ajst-16785	15	7	and	and	CCONJ
ajst-16785	15	8	classification	classification	NOUN
ajst-16785	15	9	based	base	VERB
ajst-16785	15	10	on	on	ADP
ajst-16785	15	11	pattern	pattern	NOUN
ajst-16785	15	12	recognition	recognition	NOUN
ajst-16785	15	13	technology	technology	NOUN
ajst-16785	15	14	(	(	PUNCT
ajst-16785	15	15	prt	prt	PROPN
ajst-16785	15	16	)	)	PUNCT
ajst-16785	15	17	can	can	AUX
ajst-16785	15	18	be	be	AUX
ajst-16785	15	19	divided	divide	VERB
ajst-16785	15	20	into	into	ADP
ajst-16785	15	21	two	two	NUM
ajst-16785	15	22	categories	category	NOUN
ajst-16785	15	23	:	:	PUNCT
ajst-16785	15	24	machine	machine	NOUN
ajst-16785	15	25	learning	learning	NOUN
ajst-16785	15	26	(	(	PUNCT
ajst-16785	15	27	ml	ml	NOUN
ajst-16785	15	28	)	)	PUNCT
ajst-16785	15	29	and	and	CCONJ
ajst-16785	15	30	deep	deep	ADJ
ajst-16785	15	31	learning	learning	NOUN
ajst-16785	15	32	(	(	PUNCT
ajst-16785	15	33	dl	dl	NOUN
ajst-16785	15	34	)	)	PUNCT
ajst-16785	15	35	methods	method	NOUN
ajst-16785	15	36	.	.	PUNCT
ajst-16785	16	1	ml	ml	NOUN
ajst-16785	16	2	methods	method	NOUN
ajst-16785	16	3	are	be	AUX
ajst-16785	16	4	effective	effective	ADJ
ajst-16785	16	5	in	in	ADP
ajst-16785	16	6	identifying	identify	VERB
ajst-16785	16	7	and	and	CCONJ
ajst-16785	16	8	classifying	classify	VERB
ajst-16785	16	9	complex	complex	ADJ
ajst-16785	16	10	data	datum	NOUN
ajst-16785	16	11	,	,	PUNCT
ajst-16785	16	12	but	but	CCONJ
ajst-16785	16	13	they	they	PRON
ajst-16785	16	14	require	require	VERB
ajst-16785	16	15	expert	expert	ADJ
ajst-16785	16	16	knowledge	knowledge	NOUN
ajst-16785	16	17	to	to	PART
ajst-16785	16	18	manually	manually	ADV
ajst-16785	16	19	design	design	VERB
ajst-16785	16	20	and	and	CCONJ
ajst-16785	16	21	extract	extract	VERB
ajst-16785	16	22	input	input	NOUN
ajst-16785	16	23	features	feature	NOUN
ajst-16785	16	24	.	.	PUNCT
ajst-16785	17	1	additionally	additionally	ADV
ajst-16785	17	2	,	,	PUNCT
ajst-16785	17	3	they	they	PRON
ajst-16785	17	4	are	be	AUX
ajst-16785	17	5	only	only	ADV
ajst-16785	17	6	useful	useful	ADJ
ajst-16785	17	7	for	for	ADP
ajst-16785	17	8	a	a	DET
ajst-16785	17	9	single	single	ADJ
ajst-16785	17	10	class	class	NOUN
ajst-16785	17	11	of	of	ADP
ajst-16785	17	12	objects	object	NOUN
ajst-16785	17	13	.	.	PUNCT
ajst-16785	18	1	for	for	ADP
ajst-16785	18	2	example	example	NOUN
ajst-16785	18	3	,	,	PUNCT
ajst-16785	18	4	mensah	mensah	PROPN
ajst-16785	18	5	et	et	PROPN
ajst-16785	18	6	al	al	PROPN
ajst-16785	18	7	.	.	PROPN
ajst-16785	18	8	used	use	VERB
ajst-16785	18	9	artificial	artificial	ADJ
ajst-16785	18	10	neural	neural	ADJ
ajst-16785	18	11	networks	network	NOUN
ajst-16785	18	12	(	(	PUNCT
ajst-16785	18	13	ann	ann	PROPN
ajst-16785	18	14	)	)	PUNCT
ajst-16785	18	15	and	and	CCONJ
ajst-16785	18	16	nonlinear	nonlinear	ADJ
ajst-16785	18	17	regression	regression	NOUN
ajst-16785	18	18	models	model	NOUN
ajst-16785	18	19	to	to	PART
ajst-16785	18	20	predict	predict	VERB
ajst-16785	18	21	pipeline	pipeline	NOUN
ajst-16785	18	22	failure	failure	NOUN
ajst-16785	18	23	pressure	pressure	NOUN
ajst-16785	18	24	by	by	ADP
ajst-16785	18	25	evaluating	evaluate	VERB
ajst-16785	18	26	corrosion	corrosion	NOUN
ajst-16785	18	27	clusters	cluster	NOUN
ajst-16785	18	28	in	in	ADP
ajst-16785	18	29	pipelines[4	pipelines[4	NOUN
ajst-16785	18	30	]	]	PUNCT
ajst-16785	18	31	.	.	PUNCT
ajst-16785	19	1	lin	lin	PROPN
ajst-16785	19	2	et	et	PROPN
ajst-16785	19	3	al	al	PROPN
ajst-16785	19	4	.	.	PROPN
ajst-16785	19	5	achieved	achieve	VERB
ajst-16785	19	6	real	real	ADJ
ajst-16785	19	7	-	-	PUNCT
ajst-16785	19	8	time	time	NOUN
ajst-16785	19	9	defect	defect	NOUN
ajst-16785	19	10	detection	detection	NOUN
ajst-16785	19	11	for	for	ADP
ajst-16785	19	12	metal	metal	NOUN
ajst-16785	19	13	additive	additive	ADJ
ajst-16785	19	14	manufacturing	manufacturing	NOUN
ajst-16785	19	15	parts	part	NOUN
ajst-16785	19	16	using	use	VERB
ajst-16785	19	17	laserinduced	laserinduced	ADJ
ajst-16785	19	18	breakdown	breakdown	NOUN
ajst-16785	19	19	spectroscopy	spectroscopy	NOUN
ajst-16785	19	20	(	(	PUNCT
ajst-16785	19	21	libs	libs	PROPN
ajst-16785	19	22	)	)	PUNCT
ajst-16785	19	23	combined	combine	VERB
ajst-16785	19	24	with	with	ADP
ajst-16785	19	25	plain	plain	ADJ
ajst-16785	19	26	bayesian	bayesian	NOUN
ajst-16785	19	27	,	,	PUNCT
ajst-16785	19	28	k	k	X
ajst-16785	19	29	-	-	PUNCT
ajst-16785	19	30	nearest	near	ADJ
ajst-16785	19	31	neighbor	neighbor	NOUN
ajst-16785	19	32	,	,	PUNCT
ajst-16785	19	33	decision	decision	NOUN
ajst-16785	19	34	trees	tree	NOUN
ajst-16785	19	35	,	,	PUNCT
ajst-16785	19	36	and	and	CCONJ
ajst-16785	19	37	random	random	ADJ
ajst-16785	19	38	forests[5	forests[5	NOUN
ajst-16785	19	39	]	]	PUNCT
ajst-16785	19	40	.	.	PUNCT
ajst-16785	20	1	gaja	gaja	PROPN
ajst-16785	20	2	et	et	PROPN
ajst-16785	20	3	al	al	PROPN
ajst-16785	20	4	.	.	PROPN
ajst-16785	20	5	reduced	reduce	VERB
ajst-16785	20	6	the	the	DET
ajst-16785	20	7	risk	risk	NOUN
ajst-16785	20	8	of	of	ADP
ajst-16785	20	9	deposited	deposit	VERB
ajst-16785	20	10	material	material	NOUN
ajst-16785	20	11	failure	failure	NOUN
ajst-16785	20	12	by	by	ADP
ajst-16785	20	13	identifying	identify	VERB
ajst-16785	20	14	laser	laser	NOUN
ajst-16785	20	15	metal	metal	NOUN
ajst-16785	20	16	deposition	deposition	NOUN
ajst-16785	20	17	defects	defect	NOUN
ajst-16785	20	18	using	use	VERB
ajst-16785	20	19	logistic	logistic	ADJ
ajst-16785	20	20	regression	regression	NOUN
ajst-16785	20	21	models	model	NOUN
ajst-16785	20	22	and	and	CCONJ
ajst-16785	20	23	ann[6	ann[6	NUM
ajst-16785	20	24	]	]	PUNCT
ajst-16785	20	25	.	.	PUNCT
ajst-16785	21	1	however	however	ADV
ajst-16785	21	2	,	,	PUNCT
ajst-16785	21	3	these	these	DET
ajst-16785	21	4	methods	method	NOUN
ajst-16785	21	5	all	all	PRON
ajst-16785	21	6	require	require	VERB
ajst-16785	21	7	manual	manual	ADJ
ajst-16785	21	8	feature	feature	NOUN
ajst-16785	21	9	extraction	extraction	NOUN
ajst-16785	21	10	,	,	PUNCT
ajst-16785	21	11	which	which	PRON
ajst-16785	21	12	is	be	AUX
ajst-16785	21	13	timeconsuming	timeconsuming	ADJ
ajst-16785	21	14	,	,	PUNCT
ajst-16785	21	15	labor	labor	NOUN
ajst-16785	21	16	-	-	PUNCT
ajst-16785	21	17	intensive	intensive	ADJ
ajst-16785	21	18	,	,	PUNCT
ajst-16785	21	19	and	and	CCONJ
ajst-16785	21	20	lacks	lack	VERB
ajst-16785	21	21	accuracy	accuracy	NOUN
ajst-16785	21	22	and	and	CCONJ
ajst-16785	21	23	versatility	versatility	NOUN
ajst-16785	21	24	.	.	PUNCT
ajst-16785	22	1	convolutional	convolutional	ADJ
ajst-16785	22	2	neural	neural	ADJ
ajst-16785	22	3	network	network	NOUN
ajst-16785	22	4	(	(	PUNCT
ajst-16785	22	5	cnn	cnn	PROPN
ajst-16785	22	6	)	)	PUNCT
ajst-16785	22	7	has	have	AUX
ajst-16785	22	8	been	be	AUX
ajst-16785	22	9	widely	widely	ADV
ajst-16785	22	10	used	use	VERB
ajst-16785	22	11	in	in	ADP
ajst-16785	22	12	deep	deep	ADJ
ajst-16785	22	13	learning	learning	NOUN
ajst-16785	22	14	due	due	ADP
ajst-16785	22	15	to	to	ADP
ajst-16785	22	16	its	its	PRON
ajst-16785	22	17	ability	ability	NOUN
ajst-16785	22	18	for	for	ADP
ajst-16785	22	19	automatic	automatic	ADJ
ajst-16785	22	20	feature	feature	NOUN
ajst-16785	22	21	extraction	extraction	NOUN
ajst-16785	22	22	and	and	CCONJ
ajst-16785	22	23	end	end	NOUN
ajst-16785	22	24	-	-	PUNCT
ajst-16785	22	25	to	to	ADP
ajst-16785	22	26	-	-	PUNCT
ajst-16785	22	27	end	end	NOUN
ajst-16785	22	28	learning	learning	NOUN
ajst-16785	22	29	.	.	PUNCT
ajst-16785	23	1	however	however	ADV
ajst-16785	23	2	,	,	PUNCT
ajst-16785	23	3	cnn	cnn	PROPN
ajst-16785	23	4	methods	method	NOUN
ajst-16785	23	5	such	such	ADJ
ajst-16785	23	6	as	as	ADP
ajst-16785	23	7	vgg16[7	vgg16[7	NOUN
ajst-16785	23	8	]	]	PUNCT
ajst-16785	23	9	,	,	PUNCT
ajst-16785	23	10	googlenet[8	googlenet[8	PROPN
ajst-16785	23	11	]	]	PUNCT
ajst-16785	23	12	and	and	CCONJ
ajst-16785	23	13	resnet34[9	resnet34[9	PROPN
ajst-16785	23	14	]	]	PUNCT
ajst-16785	23	15	have	have	VERB
ajst-16785	23	16	significant	significant	ADJ
ajst-16785	23	17	drawbacks	drawback	NOUN
ajst-16785	23	18	,	,	PUNCT
ajst-16785	23	19	including	include	VERB
ajst-16785	23	20	large	large	ADJ
ajst-16785	23	21	and	and	CCONJ
ajst-16785	23	22	complex	complex	ADJ
ajst-16785	23	23	parameters	parameter	NOUN
ajst-16785	23	24	,	,	PUNCT
ajst-16785	23	25	high	high	ADJ
ajst-16785	23	26	computational	computational	ADJ
ajst-16785	23	27	complexity	complexity	NOUN
ajst-16785	23	28	,	,	PUNCT
ajst-16785	23	29	high	high	ADJ
ajst-16785	23	30	training	training	NOUN
ajst-16785	23	31	cost	cost	NOUN
ajst-16785	23	32	,	,	PUNCT
ajst-16785	23	33	and	and	CCONJ
ajst-16785	23	34	inability	inability	NOUN
ajst-16785	23	35	to	to	PART
ajst-16785	23	36	capture	capture	VERB
ajst-16785	23	37	global	global	ADJ
ajst-16785	23	38	feature	feature	NOUN
ajst-16785	23	39	information	information	NOUN
ajst-16785	23	40	.	.	PUNCT
ajst-16785	24	1	for	for	ADP
ajst-16785	24	2	instance	instance	NOUN
ajst-16785	24	3	,	,	PUNCT
ajst-16785	24	4	balcioglu	balcioglu	PROPN
ajst-16785	24	5	et	et	PROPN
ajst-16785	24	6	al	al	PROPN
ajst-16785	24	7	.	.	PUNCT
ajst-16785	25	1	[	[	X
ajst-16785	25	2	10	10	NUM
ajst-16785	25	3	]	]	PUNCT
ajst-16785	25	4	utilized	utilize	VERB
ajst-16785	25	5	a	a	DET
ajst-16785	25	6	deep	deep	ADJ
ajst-16785	25	7	convolutional	convolutional	ADJ
ajst-16785	25	8	neural	neural	ADJ
ajst-16785	25	9	network	network	NOUN
ajst-16785	25	10	(	(	PUNCT
ajst-16785	25	11	dcnn	dcnn	PROPN
ajst-16785	25	12	)	)	PUNCT
ajst-16785	25	13	to	to	PART
ajst-16785	25	14	detect	detect	VERB
ajst-16785	25	15	and	and	CCONJ
ajst-16785	25	16	recognize	recognize	VERB
ajst-16785	25	17	surface	surface	NOUN
ajst-16785	25	18	defects	defect	NOUN
ajst-16785	25	19	in	in	ADP
ajst-16785	25	20	metal	metal	NOUN
ajst-16785	25	21	gears	gear	NOUN
ajst-16785	25	22	,	,	PUNCT
ajst-16785	25	23	meng	meng	PROPN
ajst-16785	25	24	tian	tian	PROPN
ajst-16785	25	25	et	et	PROPN
ajst-16785	25	26	al	al	PROPN
ajst-16785	25	27	.	.	PUNCT
ajst-16785	26	1	[	[	X
ajst-16785	26	2	11	11	NUM
ajst-16785	26	3	]	]	PUNCT
ajst-16785	26	4	combined	combine	VERB
ajst-16785	26	5	resnet	resnet	NOUN
ajst-16785	26	6	with	with	ADP
ajst-16785	26	7	an	an	DET
ajst-16785	26	8	eddy	eddy	PROPN
ajst-16785	26	9	current	current	ADJ
ajst-16785	26	10	testing	testing	NOUN
ajst-16785	26	11	technique	technique	NOUN
ajst-16785	26	12	to	to	PART
ajst-16785	26	13	evaluate	evaluate	VERB
ajst-16785	26	14	the	the	DET
ajst-16785	26	15	depth	depth	NOUN
ajst-16785	26	16	of	of	ADP
ajst-16785	26	17	metal	metal	NOUN
ajst-16785	26	18	surface	surface	NOUN
ajst-16785	26	19	defects	defect	NOUN
ajst-16785	26	20	effectively	effectively	ADV
ajst-16785	26	21	,	,	PUNCT
ajst-16785	26	22	and	and	CCONJ
ajst-16785	26	23	he	he	PRON
ajst-16785	26	24	et	et	PROPN
ajst-16785	26	25	al	al	PROPN
ajst-16785	26	26	.	.	PUNCT
ajst-16785	27	1	[	[	X
ajst-16785	27	2	12	12	NUM
ajst-16785	27	3	]	]	PUNCT
ajst-16785	27	4	employed	employ	VERB
ajst-16785	27	5	a	a	DET
ajst-16785	27	6	multi	multi	ADJ
ajst-16785	27	7	-	-	ADJ
ajst-16785	27	8	scale	scale	ADJ
ajst-16785	27	9	convolutional	convolutional	ADJ
ajst-16785	27	10	neural	neural	ADJ
ajst-16785	27	11	network	network	NOUN
ajst-16785	27	12	to	to	PART
ajst-16785	27	13	classify	classify	VERB
ajst-16785	27	14	hot	hot	ADJ
ajst-16785	27	15	rolled	roll	VERB
ajst-16785	27	16	steel	steel	NOUN
ajst-16785	27	17	defects	defect	NOUN
ajst-16785	27	18	.	.	PUNCT
ajst-16785	28	1	these	these	DET
ajst-16785	28	2	studies	study	NOUN
ajst-16785	28	3	chose	choose	VERB
ajst-16785	28	4	deeper	deep	ADJ
ajst-16785	28	5	convolutional	convolutional	ADJ
ajst-16785	28	6	neural	neural	ADJ
ajst-16785	28	7	networks	network	NOUN
ajst-16785	28	8	to	to	PART
ajst-16785	28	9	accomplish	accomplish	VERB
ajst-16785	28	10	the	the	DET
ajst-16785	28	11	defect	defect	NOUN
ajst-16785	28	12	recognition	recognition	NOUN
ajst-16785	28	13	task	task	NOUN
ajst-16785	28	14	.	.	PUNCT
ajst-16785	29	1	however	however	ADV
ajst-16785	29	2	,	,	PUNCT
ajst-16785	29	3	the	the	DET
ajst-16785	29	4	networks	network	NOUN
ajst-16785	29	5	require	require	VERB
ajst-16785	29	6	too	too	ADV
ajst-16785	29	7	many	many	ADJ
ajst-16785	29	8	samples	sample	NOUN
ajst-16785	29	9	for	for	ADP
ajst-16785	29	10	model	model	NOUN
ajst-16785	29	11	parameter	parameter	NOUN
ajst-16785	29	12	training	training	NOUN
ajst-16785	29	13	due	due	ADP
ajst-16785	29	14	to	to	ADP
ajst-16785	29	15	the	the	DET
ajst-16785	29	16	excessive	excessive	ADJ
ajst-16785	29	17	number	number	NOUN
ajst-16785	29	18	of	of	ADP
ajst-16785	29	19	parameters	parameter	NOUN
ajst-16785	29	20	and	and	CCONJ
ajst-16785	29	21	computation	computation	NOUN
ajst-16785	29	22	.	.	PUNCT
ajst-16785	30	1	moreover	moreover	ADV
ajst-16785	30	2	,	,	PUNCT
ajst-16785	30	3	the	the	DET
ajst-16785	30	4	complexity	complexity	NOUN
ajst-16785	30	5	of	of	ADP
ajst-16785	30	6	these	these	DET
ajst-16785	30	7	methods	method	NOUN
ajst-16785	30	8	causes	cause	VERB
ajst-16785	30	9	overfitting	overfitte	VERB
ajst-16785	30	10	phenomena	phenomenon	NOUN
ajst-16785	30	11	.	.	PUNCT
ajst-16785	31	1	the	the	DET
ajst-16785	31	2	transformer	transformer	ADJ
ajst-16785	31	3	algorithm	algorithm	NOUN
ajst-16785	31	4	has	have	AUX
ajst-16785	31	5	emerged	emerge	VERB
ajst-16785	31	6	as	as	ADP
ajst-16785	31	7	a	a	DET
ajst-16785	31	8	powerful	powerful	ADJ
ajst-16785	31	9	tool	tool	NOUN
ajst-16785	31	10	in	in	ADP
ajst-16785	31	11	natural	natural	ADJ
ajst-16785	31	12	language	language	NOUN
ajst-16785	31	13	processing	processing	NOUN
ajst-16785	31	14	(	(	PUNCT
ajst-16785	31	15	nlp	nlp	NOUN
ajst-16785	31	16	)	)	PUNCT
ajst-16785	31	17	and	and	CCONJ
ajst-16785	31	18	has	have	AUX
ajst-16785	31	19	recently	recently	ADV
ajst-16785	31	20	garnered	garner	VERB
ajst-16785	31	21	significant	significant	ADJ
ajst-16785	31	22	attention	attention	NOUN
ajst-16785	31	23	in	in	ADP
ajst-16785	31	24	image	image	NOUN
ajst-16785	31	25	recognition[13	recognition[13	NOUN
ajst-16785	31	26	]	]	X
ajst-16785	31	27	.	.	PUNCT
ajst-16785	32	1	unlike	unlike	ADP
ajst-16785	32	2	cnn	cnn	PROPN
ajst-16785	32	3	,	,	PUNCT
ajst-16785	32	4	which	which	PRON
ajst-16785	32	5	can	can	AUX
ajst-16785	32	6	struggle	struggle	VERB
ajst-16785	32	7	to	to	PART
ajst-16785	32	8	capture	capture	VERB
ajst-16785	32	9	global	global	ADJ
ajst-16785	32	10	feature	feature	NOUN
ajst-16785	32	11	information	information	NOUN
ajst-16785	32	12	,	,	PUNCT
ajst-16785	32	13	the	the	DET
ajst-16785	32	14	transformer	transformer	NOUN
ajst-16785	32	15	algorithm	algorithm	NOUN
ajst-16785	32	16	excels	excel	VERB
ajst-16785	32	17	at	at	ADP
ajst-16785	32	18	this	this	DET
ajst-16785	32	19	task	task	NOUN
ajst-16785	32	20	.	.	PUNCT
ajst-16785	33	1	for	for	ADP
ajst-16785	33	2	example	example	NOUN
ajst-16785	33	3	,	,	PUNCT
ajst-16785	33	4	dosovitskiy	dosovitskiy	PROPN
ajst-16785	33	5	et	et	PROPN
ajst-16785	33	6	al	al	PROPN
ajst-16785	33	7	.	.	PROPN
ajst-16785	33	8	applied	apply	VERB
ajst-16785	33	9	vision	vision	NOUN
ajst-16785	33	10	transformer	transformer	NOUN
ajst-16785	33	11	to	to	ADP
ajst-16785	33	12	image	image	NOUN
ajst-16785	33	13	recognition	recognition	NOUN
ajst-16785	33	14	tasks	task	NOUN
ajst-16785	33	15	and	and	CCONJ
ajst-16785	33	16	outperformed	outperform	VERB
ajst-16785	33	17	cnn	cnn	PROPN
ajst-16785	33	18	in	in	ADP
ajst-16785	33	19	accuracy	accuracy	NOUN
ajst-16785	33	20	on	on	ADP
ajst-16785	33	21	massive	massive	ADJ
ajst-16785	33	22	datasets[14	datasets[14	PROPN
ajst-16785	33	23	]	]	PUNCT
ajst-16785	33	24	.	.	PUNCT
ajst-16785	34	1	zhou[15	zhou[15	NOUN
ajst-16785	34	2	]	]	X
ajst-16785	34	3	and	and	CCONJ
ajst-16785	34	4	touvron	touvron	NOUN
ajst-16785	34	5	et	et	PROPN
ajst-16785	34	6	al	al	PROPN
ajst-16785	34	7	.	.	PROPN
ajst-16785	34	8	continued	continue	VERB
ajst-16785	34	9	to	to	PART
ajst-16785	34	10	improve	improve	VERB
ajst-16785	34	11	the	the	DET
ajst-16785	34	12	accuracy	accuracy	NOUN
ajst-16785	34	13	of	of	ADP
ajst-16785	34	14	the	the	DET
ajst-16785	34	15	vision	vision	NOUN
ajst-16785	34	16	transformer	transformer	NOUN
ajst-16785	34	17	model	model	NOUN
ajst-16785	34	18	in	in	ADP
ajst-16785	34	19	image	image	NOUN
ajst-16785	34	20	classification	classification	NOUN
ajst-16785	34	21	by	by	ADP
ajst-16785	34	22	deepening	deepen	VERB
ajst-16785	34	23	the	the	DET
ajst-16785	34	24	network	network	NOUN
ajst-16785	34	25	depth[16	depth[16	PROPN
ajst-16785	34	26	]	]	PUNCT
ajst-16785	34	27	.	.	PUNCT
ajst-16785	35	1	to	to	PART
ajst-16785	35	2	reduce	reduce	VERB
ajst-16785	35	3	the	the	DET
ajst-16785	35	4	number	number	NOUN
ajst-16785	35	5	of	of	ADP
ajst-16785	35	6	parameters	parameter	NOUN
ajst-16785	35	7	in	in	ADP
ajst-16785	35	8	the	the	DET
ajst-16785	35	9	vision	vision	NOUN
ajst-16785	35	10	transformer	transformer	NOUN
ajst-16785	35	11	model	model	NOUN
ajst-16785	35	12	,	,	PUNCT
ajst-16785	35	13	wang	wang	PROPN
ajst-16785	35	14	et	et	PROPN
ajst-16785	35	15	al	al	PROPN
ajst-16785	35	16	.	.	PROPN
ajst-16785	36	1	reduced	reduce	VERB
ajst-16785	36	2	computational	computational	ADJ
ajst-16785	36	3	complexity	complexity	NOUN
ajst-16785	36	4	by	by	ADP
ajst-16785	36	5	improving	improve	VERB
ajst-16785	36	6	the	the	DET
ajst-16785	36	7	original	original	ADJ
ajst-16785	36	8	pyramidal	pyramidal	ADJ
ajst-16785	36	9	vision	vision	NOUN
ajst-16785	36	10	transformer[17	transformer[17	PROPN
ajst-16785	36	11	]	]	PUNCT
ajst-16785	36	12	.	.	PUNCT
ajst-16785	37	1	liu	liu	PROPN
ajst-16785	37	2	et	et	PROPN
ajst-16785	37	3	al	al	PROPN
ajst-16785	37	4	.	.	PROPN
ajst-16785	37	5	proposed	propose	VERB
ajst-16785	37	6	swin	swin	PROPN
ajst-16785	37	7	transformer	transformer	PROPN
ajst-16785	37	8	based	base	VERB
ajst-16785	37	9	on	on	ADP
ajst-16785	37	10	the	the	DET
ajst-16785	37	11	vision	vision	NOUN
ajst-16785	37	12	transformer	transformer	NOUN
ajst-16785	37	13	for	for	ADP
ajst-16785	37	14	self	self	NOUN
ajst-16785	37	15	-	-	PUNCT
ajst-16785	37	16	attentive	attentive	ADJ
ajst-16785	37	17	computation	computation	NOUN
ajst-16785	37	18	with	with	ADP
ajst-16785	37	19	moving	move	VERB
ajst-16785	37	20	windows	window	NOUN
ajst-16785	37	21	.	.	PUNCT
ajst-16785	38	1	the	the	DET
ajst-16785	38	2	swin	swin	PROPN
ajst-16785	38	3	transformer	transformer	PROPN
ajst-16785	38	4	achieves	achieve	VERB
ajst-16785	38	5	global	global	ADJ
ajst-16785	38	6	self	self	NOUN
ajst-16785	38	7	-	-	PUNCT
ajst-16785	38	8	attentive	attentive	ADJ
ajst-16785	38	9	computation	computation	NOUN
ajst-16785	38	10	by	by	ADP
ajst-16785	38	11	computing	compute	VERB
ajst-16785	38	12	local	local	ADJ
ajst-16785	38	13	windows	window	NOUN
ajst-16785	38	14	and	and	CCONJ
ajst-16785	38	15	cross	cross	ADJ
ajst-16785	38	16	-	-	ADJ
ajst-16785	38	17	window	window	NOUN
ajst-16785	38	18	connections	connection	NOUN
ajst-16785	38	19	,	,	PUNCT
ajst-16785	38	20	while	while	SCONJ
ajst-16785	38	21	making	make	VERB
ajst-16785	38	22	the	the	DET
ajst-16785	38	23	model	model	NOUN
ajst-16785	38	24	177	177	NUM
ajst-16785	38	25	complexity	complexity	NOUN
ajst-16785	38	26	linear	linear	NOUN
ajst-16785	38	27	to	to	ADP
ajst-16785	38	28	the	the	DET
ajst-16785	38	29	image	image	NOUN
ajst-16785	38	30	size[18	size[18	ADV
ajst-16785	38	31	]	]	PUNCT
ajst-16785	38	32	.	.	PUNCT
ajst-16785	39	1	despite	despite	SCONJ
ajst-16785	39	2	its	its	PRON
ajst-16785	39	3	advantages	advantage	NOUN
ajst-16785	39	4	,	,	PUNCT
ajst-16785	39	5	the	the	DET
ajst-16785	39	6	transformer	transformer	NOUN
ajst-16785	39	7	model	model	NOUN
ajst-16785	39	8	still	still	ADV
ajst-16785	39	9	suffers	suffer	VERB
ajst-16785	39	10	from	from	ADP
ajst-16785	39	11	several	several	ADJ
ajst-16785	39	12	limitations	limitation	NOUN
ajst-16785	39	13	,	,	PUNCT
ajst-16785	39	14	such	such	ADJ
ajst-16785	39	15	as	as	ADP
ajst-16785	39	16	vast	vast	ADJ
ajst-16785	39	17	and	and	CCONJ
ajst-16785	39	18	complex	complex	ADJ
ajst-16785	39	19	parameters	parameter	NOUN
ajst-16785	39	20	,	,	PUNCT
ajst-16785	39	21	training	training	NOUN
ajst-16785	39	22	difficulties	difficulty	NOUN
ajst-16785	39	23	,	,	PUNCT
ajst-16785	39	24	an	an	DET
ajst-16785	39	25	excessive	excessive	ADJ
ajst-16785	39	26	amount	amount	NOUN
ajst-16785	39	27	of	of	ADP
ajst-16785	39	28	data	datum	NOUN
ajst-16785	39	29	required	require	VERB
ajst-16785	39	30	,	,	PUNCT
ajst-16785	39	31	and	and	CCONJ
ajst-16785	39	32	an	an	DET
ajst-16785	39	33	inability	inability	NOUN
ajst-16785	39	34	to	to	PART
ajst-16785	39	35	capture	capture	VERB
ajst-16785	39	36	local	local	ADJ
ajst-16785	39	37	information	information	NOUN
ajst-16785	39	38	.	.	PUNCT
ajst-16785	40	1	in	in	ADP
ajst-16785	40	2	addressing	address	VERB
ajst-16785	40	3	the	the	DET
ajst-16785	40	4	challenges	challenge	NOUN
ajst-16785	40	5	of	of	ADP
ajst-16785	40	6	heavy	heavy	ADJ
ajst-16785	40	7	dependence	dependence	NOUN
ajst-16785	40	8	on	on	ADP
ajst-16785	40	9	expert	expert	ADJ
ajst-16785	40	10	feature	feature	NOUN
ajst-16785	40	11	extraction	extraction	NOUN
ajst-16785	40	12	,	,	PUNCT
ajst-16785	40	13	low	low	ADJ
ajst-16785	40	14	intelligence	intelligence	NOUN
ajst-16785	40	15	in	in	ADP
ajst-16785	40	16	defect	defect	NOUN
ajst-16785	40	17	detection	detection	NOUN
ajst-16785	40	18	,	,	PUNCT
ajst-16785	40	19	low	low	ADJ
ajst-16785	40	20	accuracy	accuracy	NOUN
ajst-16785	40	21	,	,	PUNCT
ajst-16785	40	22	and	and	CCONJ
ajst-16785	40	23	the	the	DET
ajst-16785	40	24	lack	lack	NOUN
ajst-16785	40	25	of	of	ADP
ajst-16785	40	26	global	global	ADJ
ajst-16785	40	27	attention	attention	NOUN
ajst-16785	40	28	capabilities	capability	NOUN
ajst-16785	40	29	in	in	ADP
ajst-16785	40	30	traditional	traditional	ADJ
ajst-16785	40	31	convolutional	convolutional	ADJ
ajst-16785	40	32	neural	neural	ADJ
ajst-16785	40	33	networks	network	NOUN
ajst-16785	40	34	for	for	ADP
ajst-16785	40	35	image	image	NOUN
ajst-16785	40	36	-	-	PUNCT
ajst-16785	40	37	based	base	VERB
ajst-16785	40	38	metal	metal	NOUN
ajst-16785	40	39	defect	defect	NOUN
ajst-16785	40	40	recognition	recognition	NOUN
ajst-16785	40	41	,	,	PUNCT
ajst-16785	40	42	this	this	DET
ajst-16785	40	43	paper	paper	NOUN
ajst-16785	40	44	proposes	propose	VERB
ajst-16785	40	45	a	a	DET
ajst-16785	40	46	metal	metal	NOUN
ajst-16785	40	47	defect	defect	NOUN
ajst-16785	40	48	recognition	recognition	NOUN
ajst-16785	40	49	method	method	NOUN
ajst-16785	40	50	based	base	VERB
ajst-16785	40	51	on	on	ADP
ajst-16785	40	52	an	an	DET
ajst-16785	40	53	inception	inception	NOUN
ajst-16785	40	54	-	-	PUNCT
ajst-16785	40	55	fused	fuse	VERB
ajst-16785	40	56	swin	swin	PROPN
ajst-16785	40	57	transformer	transformer	PROPN
ajst-16785	40	58	model	model	NOUN
ajst-16785	40	59	.	.	PUNCT
ajst-16785	41	1	focusing	focus	VERB
ajst-16785	41	2	on	on	ADP
ajst-16785	41	3	defects	defect	NOUN
ajst-16785	41	4	on	on	ADP
ajst-16785	41	5	steel	steel	NOUN
ajst-16785	41	6	surfaces	surface	NOUN
ajst-16785	41	7	in	in	ADP
ajst-16785	41	8	industrial	industrial	ADJ
ajst-16785	41	9	components	component	NOUN
ajst-16785	41	10	,	,	PUNCT
ajst-16785	41	11	we	we	PRON
ajst-16785	41	12	employ	employ	VERB
ajst-16785	41	13	wavelet	wavelet	NOUN
ajst-16785	41	14	transform	transform	NOUN
ajst-16785	41	15	to	to	ADP
ajst-16785	41	16	denoise	denoise	VERB
ajst-16785	41	17	ultrasonic	ultrasonic	ADJ
ajst-16785	41	18	echo	echo	NOUN
ajst-16785	41	19	signals	signal	NOUN
ajst-16785	41	20	from	from	ADP
ajst-16785	41	21	steel	steel	NOUN
ajst-16785	41	22	surface	surface	NOUN
ajst-16785	41	23	defects	defect	NOUN
ajst-16785	41	24	.	.	PUNCT
ajst-16785	42	1	after	after	ADP
ajst-16785	42	2	transforming	transform	VERB
ajst-16785	42	3	the	the	DET
ajst-16785	42	4	signals	signal	NOUN
ajst-16785	42	5	into	into	ADP
ajst-16785	42	6	grayscale	grayscale	NOUN
ajst-16785	42	7	images	image	NOUN
ajst-16785	42	8	,	,	PUNCT
ajst-16785	42	9	the	the	DET
ajst-16785	42	10	inception	inception	NOUN
ajst-16785	42	11	model	model	NOUN
ajst-16785	42	12	automatically	automatically	ADV
ajst-16785	42	13	captures	capture	VERB
ajst-16785	42	14	the	the	DET
ajst-16785	42	15	necessary	necessary	ADJ
ajst-16785	42	16	feature	feature	NOUN
ajst-16785	42	17	information	information	NOUN
ajst-16785	42	18	for	for	ADP
ajst-16785	42	19	defect	defect	NOUN
ajst-16785	42	20	recognition	recognition	NOUN
ajst-16785	42	21	.	.	PUNCT
ajst-16785	43	1	the	the	DET
ajst-16785	43	2	swin	swin	PROPN
ajst-16785	43	3	transformer	transformer	PROPN
ajst-16785	43	4	,	,	PUNCT
ajst-16785	43	5	with	with	ADP
ajst-16785	43	6	lower	low	ADJ
ajst-16785	43	7	model	model	NOUN
ajst-16785	43	8	complexity	complexity	NOUN
ajst-16785	43	9	compared	compare	VERB
ajst-16785	43	10	to	to	ADP
ajst-16785	43	11	transformer	transformer	NOUN
ajst-16785	43	12	models	model	NOUN
ajst-16785	43	13	,	,	PUNCT
ajst-16785	43	14	captures	capture	VERB
ajst-16785	43	15	global	global	ADJ
ajst-16785	43	16	feature	feature	NOUN
ajst-16785	43	17	information	information	NOUN
ajst-16785	43	18	.	.	PUNCT
ajst-16785	44	1	simultaneously	simultaneously	ADV
ajst-16785	44	2	,	,	PUNCT
ajst-16785	44	3	the	the	DET
ajst-16785	44	4	introduced	introduce	VERB
ajst-16785	44	5	channel	channel	NOUN
ajst-16785	44	6	-	-	PUNCT
ajst-16785	44	7	coordinate	coordinate	NOUN
ajst-16785	44	8	attention	attention	NOUN
ajst-16785	44	9	module	module	NOUN
ajst-16785	44	10	(	(	PUNCT
ajst-16785	44	11	coordattention	coordattention	NOUN
ajst-16785	44	12	)	)	PUNCT
ajst-16785	44	13	emphasizes	emphasize	VERB
ajst-16785	44	14	crucial	crucial	ADJ
ajst-16785	44	15	feature	feature	NOUN
ajst-16785	44	16	channels[19	channels[19	NOUN
ajst-16785	44	17	]	]	PUNCT
ajst-16785	44	18	,	,	PUNCT
ajst-16785	44	19	achieving	achieve	VERB
ajst-16785	44	20	effective	effective	ADJ
ajst-16785	44	21	identification	identification	NOUN
ajst-16785	44	22	and	and	CCONJ
ajst-16785	44	23	classification	classification	NOUN
ajst-16785	44	24	of	of	ADP
ajst-16785	44	25	metal	metal	NOUN
ajst-16785	44	26	defects	defect	NOUN
ajst-16785	44	27	.	.	PUNCT
ajst-16785	45	1	the	the	DET
ajst-16785	45	2	remainder	remainder	NOUN
ajst-16785	45	3	of	of	ADP
ajst-16785	45	4	this	this	DET
ajst-16785	45	5	paper	paper	NOUN
ajst-16785	45	6	is	be	AUX
ajst-16785	45	7	organized	organize	VERB
ajst-16785	45	8	as	as	SCONJ
ajst-16785	45	9	follows	follow	VERB
ajst-16785	45	10	.	.	PUNCT
ajst-16785	46	1	in	in	ADP
ajst-16785	46	2	the	the	DET
ajst-16785	46	3	next	next	ADJ
ajst-16785	46	4	section	section	NOUN
ajst-16785	46	5	,	,	PUNCT
ajst-16785	46	6	we	we	PRON
ajst-16785	46	7	introduce	introduce	VERB
ajst-16785	46	8	the	the	DET
ajst-16785	46	9	theoretical	theoretical	ADJ
ajst-16785	46	10	knowledge	knowledge	NOUN
ajst-16785	46	11	related	relate	VERB
ajst-16785	46	12	to	to	ADP
ajst-16785	46	13	the	the	DET
ajst-16785	46	14	proposed	propose	VERB
ajst-16785	46	15	method	method	NOUN
ajst-16785	46	16	,	,	PUNCT
ajst-16785	46	17	including	include	VERB
ajst-16785	46	18	convolutional	convolutional	ADJ
ajst-16785	46	19	neural	neural	ADJ
ajst-16785	46	20	network	network	NOUN
ajst-16785	46	21	(	(	PUNCT
ajst-16785	46	22	cnn	cnn	PROPN
ajst-16785	46	23	)	)	PUNCT
ajst-16785	46	24	,	,	PUNCT
ajst-16785	46	25	swin	swin	PROPN
ajst-16785	46	26	transformer	transformer	PROPN
ajst-16785	46	27	,	,	PUNCT
ajst-16785	46	28	and	and	CCONJ
ajst-16785	46	29	channel	channel	NOUN
ajst-16785	46	30	attention	attention	NOUN
ajst-16785	46	31	mechanism	mechanism	NOUN
ajst-16785	46	32	.	.	PUNCT
ajst-16785	47	1	the	the	DET
ajst-16785	47	2	third	third	ADJ
ajst-16785	47	3	section	section	NOUN
ajst-16785	47	4	presents	present	VERB
ajst-16785	47	5	the	the	DET
ajst-16785	47	6	structure	structure	NOUN
ajst-16785	47	7	,	,	PUNCT
ajst-16785	47	8	parameters	parameter	NOUN
ajst-16785	47	9	,	,	PUNCT
ajst-16785	47	10	and	and	CCONJ
ajst-16785	47	11	innovations	innovation	NOUN
ajst-16785	47	12	of	of	ADP
ajst-16785	47	13	the	the	DET
ajst-16785	47	14	proposed	propose	VERB
ajst-16785	47	15	model	model	NOUN
ajst-16785	47	16	.	.	PUNCT
ajst-16785	48	1	in	in	ADP
ajst-16785	48	2	the	the	DET
ajst-16785	48	3	fourth	fourth	ADJ
ajst-16785	48	4	section	section	NOUN
ajst-16785	48	5	,	,	PUNCT
ajst-16785	48	6	we	we	PRON
ajst-16785	48	7	present	present	VERB
ajst-16785	48	8	the	the	DET
ajst-16785	48	9	datasets	dataset	NOUN
ajst-16785	48	10	,	,	PUNCT
ajst-16785	48	11	data	datum	NOUN
ajst-16785	48	12	preprocessing	preprocessing	NOUN
ajst-16785	48	13	process	process	NOUN
ajst-16785	48	14	,	,	PUNCT
ajst-16785	48	15	experimental	experimental	ADJ
ajst-16785	48	16	parameters	parameter	NOUN
ajst-16785	48	17	,	,	PUNCT
ajst-16785	48	18	and	and	CCONJ
ajst-16785	48	19	platform	platform	NOUN
ajst-16785	48	20	configuration	configuration	NOUN
ajst-16785	48	21	.	.	PUNCT
ajst-16785	49	1	the	the	DET
ajst-16785	49	2	fifth	fifth	ADJ
ajst-16785	49	3	section	section	NOUN
ajst-16785	49	4	exhibits	exhibit	VERB
ajst-16785	49	5	the	the	DET
ajst-16785	49	6	experimental	experimental	ADJ
ajst-16785	49	7	evaluation	evaluation	NOUN
ajst-16785	49	8	and	and	CCONJ
ajst-16785	49	9	analysis	analysis	NOUN
ajst-16785	49	10	of	of	ADP
ajst-16785	49	11	the	the	DET
ajst-16785	49	12	proposed	propose	VERB
ajst-16785	49	13	method	method	NOUN
ajst-16785	49	14	on	on	ADP
ajst-16785	49	15	two	two	NUM
ajst-16785	49	16	datasets	dataset	NOUN
ajst-16785	49	17	.	.	PUNCT
ajst-16785	50	1	finally	finally	ADV
ajst-16785	50	2	,	,	PUNCT
ajst-16785	50	3	we	we	PRON
ajst-16785	50	4	summarize	summarize	VERB
ajst-16785	50	5	the	the	DET
ajst-16785	50	6	analysis	analysis	NOUN
ajst-16785	50	7	and	and	CCONJ
ajst-16785	50	8	experiments	experiment	NOUN
ajst-16785	50	9	in	in	ADP
ajst-16785	50	10	the	the	DET
ajst-16785	50	11	last	last	ADJ
ajst-16785	50	12	section	section	NOUN
ajst-16785	50	13	.	.	PUNCT
ajst-16785	51	1	2	2	X
ajst-16785	51	2	.	.	X
ajst-16785	51	3	background	background	NOUN
ajst-16785	51	4	theory	theory	NOUN
ajst-16785	51	5	2.1	2.1	NUM
ajst-16785	51	6	.	.	PUNCT
ajst-16785	52	1	googlenet	googlenet	PROPN
ajst-16785	52	2	cnns	cnn	NOUN
ajst-16785	52	3	have	have	AUX
ajst-16785	52	4	seen	see	VERB
ajst-16785	52	5	significant	significant	ADJ
ajst-16785	52	6	development	development	NOUN
ajst-16785	52	7	in	in	ADP
ajst-16785	52	8	recent	recent	ADJ
ajst-16785	52	9	years	year	NOUN
ajst-16785	52	10	,	,	PUNCT
ajst-16785	52	11	with	with	ADP
ajst-16785	52	12	variants	variant	NOUN
ajst-16785	52	13	such	such	ADJ
ajst-16785	52	14	as	as	ADP
ajst-16785	52	15	lenet	lenet	NOUN
ajst-16785	52	16	,	,	PUNCT
ajst-16785	52	17	alexnet	alexnet	ADJ
ajst-16785	52	18	,	,	PUNCT
ajst-16785	52	19	vgg	vgg	NOUN
ajst-16785	52	20	,	,	PUNCT
ajst-16785	52	21	and	and	CCONJ
ajst-16785	52	22	other	other	ADJ
ajst-16785	52	23	classical	classical	ADJ
ajst-16785	52	24	neural	neural	ADJ
ajst-16785	52	25	networks	network	NOUN
ajst-16785	52	26	achieving	achieve	VERB
ajst-16785	52	27	high	high	ADJ
ajst-16785	52	28	accuracy	accuracy	NOUN
ajst-16785	52	29	in	in	ADP
ajst-16785	52	30	image	image	NOUN
ajst-16785	52	31	classification	classification	NOUN
ajst-16785	52	32	tasks	task	NOUN
ajst-16785	52	33	.	.	PUNCT
ajst-16785	53	1	these	these	DET
ajst-16785	53	2	networks	network	NOUN
ajst-16785	53	3	deepen	deepen	VERB
ajst-16785	53	4	the	the	DET
ajst-16785	53	5	network	network	NOUN
ajst-16785	53	6	depth	depth	NOUN
ajst-16785	53	7	to	to	PART
ajst-16785	53	8	improve	improve	VERB
ajst-16785	53	9	non	non	ADJ
ajst-16785	53	10	-	-	ADJ
ajst-16785	53	11	linear	linear	ADJ
ajst-16785	53	12	expression	expression	NOUN
ajst-16785	53	13	ability	ability	NOUN
ajst-16785	53	14	and	and	CCONJ
ajst-16785	53	15	better	well	ADJ
ajst-16785	53	16	fit	fit	ADJ
ajst-16785	53	17	features	feature	NOUN
ajst-16785	53	18	.	.	PUNCT
ajst-16785	54	1	however	however	ADV
ajst-16785	54	2	,	,	PUNCT
ajst-16785	54	3	as	as	SCONJ
ajst-16785	54	4	the	the	DET
ajst-16785	54	5	number	number	NOUN
ajst-16785	54	6	of	of	ADP
ajst-16785	54	7	network	network	NOUN
ajst-16785	54	8	layers	layer	NOUN
ajst-16785	54	9	increases	increase	VERB
ajst-16785	54	10	,	,	PUNCT
ajst-16785	54	11	the	the	DET
ajst-16785	54	12	model	model	NOUN
ajst-16785	54	13	parameters	parameter	NOUN
ajst-16785	54	14	become	become	VERB
ajst-16785	54	15	large	large	ADJ
ajst-16785	54	16	and	and	CCONJ
ajst-16785	54	17	may	may	AUX
ajst-16785	54	18	lead	lead	VERB
ajst-16785	54	19	to	to	ADP
ajst-16785	54	20	overfitting	overfitte	VERB
ajst-16785	54	21	.	.	PUNCT
ajst-16785	55	1	to	to	PART
ajst-16785	55	2	address	address	VERB
ajst-16785	55	3	this	this	DET
ajst-16785	55	4	issue	issue	NOUN
ajst-16785	55	5	,	,	PUNCT
ajst-16785	55	6	the	the	DET
ajst-16785	55	7	inception	inception	NOUN
ajst-16785	55	8	structure	structure	NOUN
ajst-16785	55	9	is	be	AUX
ajst-16785	55	10	used	use	VERB
ajst-16785	55	11	in	in	ADP
ajst-16785	55	12	googlenet	googlenet	NOUN
ajst-16785	55	13	to	to	PART
ajst-16785	55	14	fuse	fuse	VERB
ajst-16785	55	15	feature	feature	NOUN
ajst-16785	55	16	information	information	NOUN
ajst-16785	55	17	of	of	ADP
ajst-16785	55	18	different	different	ADJ
ajst-16785	55	19	scales	scale	NOUN
ajst-16785	55	20	.	.	PUNCT
ajst-16785	56	1	a	a	DET
ajst-16785	56	2	1x1	1x1	NUM
ajst-16785	56	3	convolution	convolution	NOUN
ajst-16785	56	4	kernel	kernel	NOUN
ajst-16785	56	5	is	be	AUX
ajst-16785	56	6	applied	apply	VERB
ajst-16785	56	7	to	to	PART
ajst-16785	56	8	reduce	reduce	VERB
ajst-16785	56	9	the	the	DET
ajst-16785	56	10	dimensionality	dimensionality	NOUN
ajst-16785	56	11	.	.	PUNCT
ajst-16785	57	1	these	these	DET
ajst-16785	57	2	approaches	approach	NOUN
ajst-16785	57	3	significantly	significantly	ADV
ajst-16785	57	4	reduce	reduce	VERB
ajst-16785	57	5	the	the	DET
ajst-16785	57	6	model	model	NOUN
ajst-16785	57	7	parameters	parameter	NOUN
ajst-16785	57	8	and	and	CCONJ
ajst-16785	57	9	make	make	VERB
ajst-16785	57	10	the	the	DET
ajst-16785	57	11	network	network	NOUN
ajst-16785	57	12	deeper	deep	ADJ
ajst-16785	57	13	and	and	CCONJ
ajst-16785	57	14	wider	wide	ADJ
ajst-16785	57	15	.	.	PUNCT
ajst-16785	58	1	the	the	DET
ajst-16785	58	2	inception	inception	ADJ
ajst-16785	58	3	model	model	NOUN
ajst-16785	58	4	comprises	comprise	VERB
ajst-16785	58	5	three	three	NUM
ajst-16785	58	6	convolutional	convolutional	ADJ
ajst-16785	58	7	kernels	kernel	NOUN
ajst-16785	58	8	of	of	ADP
ajst-16785	58	9	different	different	ADJ
ajst-16785	58	10	sizes	size	NOUN
ajst-16785	58	11	and	and	CCONJ
ajst-16785	58	12	a	a	DET
ajst-16785	58	13	pooling	pool	VERB
ajst-16785	58	14	operation	operation	NOUN
ajst-16785	58	15	,	,	PUNCT
ajst-16785	58	16	and	and	CCONJ
ajst-16785	58	17	the	the	DET
ajst-16785	58	18	results	result	NOUN
ajst-16785	58	19	of	of	ADP
ajst-16785	58	20	the	the	DET
ajst-16785	58	21	four	four	NUM
ajst-16785	58	22	parts	part	NOUN
ajst-16785	58	23	are	be	AUX
ajst-16785	58	24	merged	merge	VERB
ajst-16785	58	25	into	into	ADP
ajst-16785	58	26	a	a	DET
ajst-16785	58	27	channel	channel	NOUN
ajst-16785	58	28	.	.	PUNCT
ajst-16785	59	1	multiple	multiple	ADJ
ajst-16785	59	2	inception	inception	NOUN
ajst-16785	59	3	models	model	NOUN
ajst-16785	59	4	are	be	AUX
ajst-16785	59	5	cascaded	cascade	VERB
ajst-16785	59	6	in	in	ADP
ajst-16785	59	7	series	series	NOUN
ajst-16785	59	8	to	to	PART
ajst-16785	59	9	form	form	VERB
ajst-16785	59	10	googlenet	googlenet	NOUN
ajst-16785	59	11	.	.	PUNCT
ajst-16785	60	1	2.2	2.2	NUM
ajst-16785	60	2	.	.	PUNCT
ajst-16785	61	1	swin	swin	PROPN
ajst-16785	61	2	transformer	transformer	PROPN
ajst-16785	61	3	model	model	NOUN
ajst-16785	61	4	with	with	ADP
ajst-16785	61	5	the	the	DET
ajst-16785	61	6	success	success	NOUN
ajst-16785	61	7	of	of	ADP
ajst-16785	61	8	the	the	DET
ajst-16785	61	9	vision	vision	NOUN
ajst-16785	61	10	transformer	transformer	NOUN
ajst-16785	61	11	(	(	PUNCT
ajst-16785	61	12	vit	vit	NOUN
ajst-16785	61	13	)	)	PUNCT
ajst-16785	61	14	model	model	NOUN
ajst-16785	61	15	in	in	ADP
ajst-16785	61	16	vision	vision	NOUN
ajst-16785	61	17	tasks	task	NOUN
ajst-16785	61	18	that	that	PRON
ajst-16785	61	19	can	can	AUX
ajst-16785	61	20	compete	compete	VERB
ajst-16785	61	21	with	with	ADP
ajst-16785	61	22	cnn	cnn	PROPN
ajst-16785	61	23	,	,	PUNCT
ajst-16785	61	24	the	the	DET
ajst-16785	61	25	transformer	transformer	NOUN
ajst-16785	61	26	has	have	AUX
ajst-16785	61	27	become	become	VERB
ajst-16785	61	28	a	a	DET
ajst-16785	61	29	promising	promising	ADJ
ajst-16785	61	30	research	research	NOUN
ajst-16785	61	31	direction	direction	NOUN
ajst-16785	61	32	in	in	ADP
ajst-16785	61	33	the	the	DET
ajst-16785	61	34	field	field	NOUN
ajst-16785	61	35	of	of	ADP
ajst-16785	61	36	image	image	NOUN
ajst-16785	61	37	processing	processing	NOUN
ajst-16785	61	38	.	.	PUNCT
ajst-16785	62	1	among	among	ADP
ajst-16785	62	2	various	various	ADJ
ajst-16785	62	3	transformer	transformer	NOUN
ajst-16785	62	4	-	-	PUNCT
ajst-16785	62	5	based	base	VERB
ajst-16785	62	6	models	model	NOUN
ajst-16785	62	7	,	,	PUNCT
ajst-16785	62	8	swin	swin	PROPN
ajst-16785	62	9	transformer	transformer	PROPN
ajst-16785	62	10	has	have	AUX
ajst-16785	62	11	drawn	draw	VERB
ajst-16785	62	12	considerable	considerable	ADJ
ajst-16785	62	13	attention	attention	NOUN
ajst-16785	62	14	by	by	ADP
ajst-16785	62	15	keeping	keep	VERB
ajst-16785	62	16	the	the	DET
ajst-16785	62	17	advantages	advantage	NOUN
ajst-16785	62	18	of	of	ADP
ajst-16785	62	19	vit	vit	NOUN
ajst-16785	62	20	while	while	SCONJ
ajst-16785	62	21	reducing	reduce	VERB
ajst-16785	62	22	model	model	NOUN
ajst-16785	62	23	complexity	complexity	NOUN
ajst-16785	62	24	.	.	PUNCT
ajst-16785	63	1	this	this	DET
ajst-16785	63	2	reduction	reduction	NOUN
ajst-16785	63	3	is	be	AUX
ajst-16785	63	4	mainly	mainly	ADV
ajst-16785	63	5	achieved	achieve	VERB
ajst-16785	63	6	by	by	ADP
ajst-16785	63	7	utilizing	utilize	VERB
ajst-16785	63	8	the	the	DET
ajst-16785	63	9	swin	swin	PROPN
ajst-16785	63	10	transformer	transformer	PROPN
ajst-16785	63	11	block	block	NOUN
ajst-16785	63	12	,	,	PUNCT
ajst-16785	63	13	which	which	PRON
ajst-16785	63	14	consists	consist	VERB
ajst-16785	63	15	of	of	ADP
ajst-16785	63	16	two	two	NUM
ajst-16785	63	17	subunits	subunit	NOUN
ajst-16785	63	18	.	.	PUNCT
ajst-16785	64	1	firstly	firstly	ADV
ajst-16785	64	2	,	,	PUNCT
ajst-16785	64	3	layer	layer	NOUN
ajst-16785	64	4	normalization	normalization	NOUN
ajst-16785	64	5	(	(	PUNCT
ajst-16785	64	6	ln	ln	X
ajst-16785	64	7	)	)	PUNCT
ajst-16785	64	8	is	be	AUX
ajst-16785	64	9	applied	apply	VERB
ajst-16785	64	10	to	to	ADP
ajst-16785	64	11	input	input	NOUN
ajst-16785	64	12	feature	feature	NOUN
ajst-16785	64	13	layers	layer	NOUN
ajst-16785	64	14	to	to	PART
ajst-16785	64	15	coordinate	coordinate	VERB
ajst-16785	64	16	the	the	DET
ajst-16785	64	17	feature	feature	NOUN
ajst-16785	64	18	data	datum	NOUN
ajst-16785	64	19	distribution	distribution	NOUN
ajst-16785	64	20	.	.	PUNCT
ajst-16785	65	1	then	then	ADV
ajst-16785	65	2	,	,	PUNCT
ajst-16785	65	3	it	it	PRON
ajst-16785	65	4	passes	pass	VERB
ajst-16785	65	5	to	to	ADP
ajst-16785	65	6	the	the	DET
ajst-16785	65	7	self	self	NOUN
ajst-16785	65	8	-	-	PUNCT
ajst-16785	65	9	attentive	attentive	ADJ
ajst-16785	65	10	mechanism	mechanism	NOUN
ajst-16785	65	11	module	module	NOUN
ajst-16785	65	12	.	.	PUNCT
ajst-16785	66	1	finally	finally	ADV
ajst-16785	66	2	,	,	PUNCT
ajst-16785	66	3	ln	ln	ADJ
ajst-16785	66	4	and	and	CCONJ
ajst-16785	66	5	two	two	NUM
ajst-16785	66	6	relu	relu	NOUN
ajst-16785	66	7	nonlinear	nonlinear	ADJ
ajst-16785	66	8	mapping	mapping	NOUN
ajst-16785	66	9	(	(	PUNCT
ajst-16785	66	10	mlp	mlp	NOUN
ajst-16785	66	11	)	)	PUNCT
ajst-16785	66	12	operations	operation	NOUN
ajst-16785	66	13	are	be	AUX
ajst-16785	66	14	performed	perform	VERB
ajst-16785	66	15	.	.	PUNCT
ajst-16785	67	1	the	the	DET
ajst-16785	67	2	two	two	NUM
ajst-16785	67	3	subunit	subunit	NOUN
ajst-16785	67	4	self	self	NOUN
ajst-16785	67	5	-	-	PUNCT
ajst-16785	67	6	attentive	attentive	ADJ
ajst-16785	67	7	mechanisms	mechanism	NOUN
ajst-16785	67	8	use	use	VERB
ajst-16785	67	9	window	window	NOUN
ajst-16785	67	10	msa	msa	PROPN
ajst-16785	67	11	(	(	PUNCT
ajst-16785	67	12	w	w	PROPN
ajst-16785	67	13	-	-	PUNCT
ajst-16785	67	14	msa	msa	NOUN
ajst-16785	67	15	)	)	PUNCT
ajst-16785	67	16	and	and	CCONJ
ajst-16785	67	17	shifted	shift	VERB
ajst-16785	67	18	window	window	NOUN
ajst-16785	67	19	msa	msa	PROPN
ajst-16785	67	20	(	(	PUNCT
ajst-16785	67	21	swmsa	swmsa	NOUN
ajst-16785	67	22	)	)	PUNCT
ajst-16785	67	23	modules	module	NOUN
ajst-16785	67	24	,	,	PUNCT
ajst-16785	67	25	respectively	respectively	ADV
ajst-16785	67	26	.	.	PUNCT
ajst-16785	68	1			PROPN
ajst-16785	68	2	window	window	NOUN
ajst-16785	68	3	msa	msa	PROPN
ajst-16785	68	4	the	the	DET
ajst-16785	68	5	window	window	NOUN
ajst-16785	68	6	multi	multi	ADJ
ajst-16785	68	7	-	-	ADJ
ajst-16785	68	8	head	head	ADJ
ajst-16785	68	9	self	self	NOUN
ajst-16785	68	10	-	-	PUNCT
ajst-16785	68	11	attention	attention	NOUN
ajst-16785	68	12	mechanism	mechanism	NOUN
ajst-16785	68	13	(	(	PUNCT
ajst-16785	68	14	wmsa	wmsa	NOUN
ajst-16785	68	15	)	)	PUNCT
ajst-16785	68	16	used	use	VERB
ajst-16785	68	17	in	in	ADP
ajst-16785	68	18	swin	swin	PROPN
ajst-16785	68	19	transformer	transformer	PROPN
ajst-16785	68	20	divides	divide	VERB
ajst-16785	68	21	the	the	DET
ajst-16785	68	22	input	input	NOUN
ajst-16785	68	23	feature	feature	NOUN
ajst-16785	68	24	layers	layer	NOUN
ajst-16785	68	25	into	into	ADP
ajst-16785	68	26	windows	window	NOUN
ajst-16785	68	27	of	of	ADP
ajst-16785	68	28	fixed	fix	VERB
ajst-16785	68	29	size	size	NOUN
ajst-16785	68	30	to	to	PART
ajst-16785	68	31	reduce	reduce	VERB
ajst-16785	68	32	the	the	DET
ajst-16785	68	33	computational	computational	ADJ
ajst-16785	68	34	complexity	complexity	NOUN
ajst-16785	68	35	while	while	SCONJ
ajst-16785	68	36	achieving	achieve	VERB
ajst-16785	68	37	the	the	DET
ajst-16785	68	38	same	same	ADJ
ajst-16785	68	39	effect	effect	NOUN
ajst-16785	68	40	as	as	ADP
ajst-16785	68	41	the	the	DET
ajst-16785	68	42	original	original	ADJ
ajst-16785	68	43	multi	multi	ADJ
ajst-16785	68	44	-	-	ADJ
ajst-16785	68	45	head	head	ADJ
ajst-16785	68	46	self	self	NOUN
ajst-16785	68	47	-	-	PUNCT
ajst-16785	68	48	attention	attention	NOUN
ajst-16785	68	49	mechanism	mechanism	NOUN
ajst-16785	68	50	in	in	ADP
ajst-16785	68	51	vision	vision	NOUN
ajst-16785	68	52	transformer	transformer	NOUN
ajst-16785	68	53	.	.	PUNCT
ajst-16785	69	1	the	the	DET
ajst-16785	69	2	attention	attention	NOUN
ajst-16785	69	3	calculation	calculation	NOUN
ajst-16785	69	4	is	be	AUX
ajst-16785	69	5	performed	perform	VERB
ajst-16785	69	6	within	within	ADP
ajst-16785	69	7	each	each	DET
ajst-16785	69	8	window	window	NOUN
ajst-16785	69	9	separately	separately	ADV
ajst-16785	69	10	,	,	PUNCT
ajst-16785	69	11	and	and	CCONJ
ajst-16785	69	12	the	the	DET
ajst-16785	69	13	results	result	NOUN
ajst-16785	69	14	are	be	AUX
ajst-16785	69	15	merged	merge	VERB
ajst-16785	69	16	to	to	PART
ajst-16785	69	17	obtain	obtain	VERB
ajst-16785	69	18	the	the	DET
ajst-16785	69	19	final	final	ADJ
ajst-16785	69	20	output	output	NOUN
ajst-16785	69	21	.	.	PUNCT
ajst-16785	70	1	the	the	DET
ajst-16785	70	2	attention	attention	NOUN
ajst-16785	70	3	computation	computation	NOUN
ajst-16785	70	4	process	process	NOUN
ajst-16785	70	5	could	could	AUX
ajst-16785	70	6	be	be	AUX
ajst-16785	70	7	described	describe	VERB
ajst-16785	70	8	as	as	SCONJ
ajst-16785	70	9	follows	follow	VERB
ajst-16785	70	10	.	.	PUNCT
ajst-16785	71	1	q	q	PUNCT
ajst-16785	72	1	k	k	PROPN
ajst-16785	72	2	vq	vq	PROPN
ajst-16785	72	3	xw	xw	PROPN
ajst-16785	72	4	k	k	PROPN
ajst-16785	72	5	xw	xw	PROPN
ajst-16785	72	6	v	v	NUM
ajst-16785	72	7	xw	xw	PROPN
ajst-16785	73	1			PROPN
ajst-16785	74	1			NOUN
ajst-16785	74	2	(	(	PUNCT
ajst-16785	74	3	1	1	NUM
ajst-16785	74	4	)	)	PUNCT
ajst-16785	74	5	(	(	PUNCT
ajst-16785	74	6	,	,	PUNCT
ajst-16785	74	7	,	,	PUNCT
ajst-16785	74	8	)	)	PUNCT
ajst-16785	74	9	(	(	PUNCT
ajst-16785	74	10	)	)	PUNCT
ajst-16785	74	11	tqk	tqk	PROPN
ajst-16785	74	12	self	self	NOUN
ajst-16785	74	13	attention	attention	NOUN
ajst-16785	74	14	q	q	PROPN
ajst-16785	75	1	k	k	PROPN
ajst-16785	75	2	v	v	X
ajst-16785	75	3	softmax	softmax	NOUN
ajst-16785	75	4	v	v	NOUN
ajst-16785	75	5	d	d	X
ajst-16785	75	6			PROPN
ajst-16785	75	7	(	(	PUNCT
ajst-16785	75	8	2	2	NUM
ajst-16785	75	9	)	)	PUNCT
ajst-16785	75	10	where	where	SCONJ
ajst-16785	75	11	is	be	AUX
ajst-16785	75	12	the	the	DET
ajst-16785	75	13	input	input	NOUN
ajst-16785	75	14	feature	feature	NOUN
ajst-16785	75	15	with	with	ADP
ajst-16785	75	16	the	the	DET
ajst-16785	75	17	fixed	fix	VERB
ajst-16785	75	18	window	window	NOUN
ajst-16785	75	19	size	size	NOUN
ajst-16785	75	20	,	,	PUNCT
ajst-16785	75	21	q	q	X
ajst-16785	75	22	,	,	PUNCT
ajst-16785	75	23	k	k	PROPN
ajst-16785	75	24	,	,	PUNCT
ajst-16785	75	25	v	v	X
ajst-16785	75	26	are	be	AUX
ajst-16785	75	27	the	the	DET
ajst-16785	75	28	query	query	NOUN
ajst-16785	75	29	matrix	matrix	NOUN
ajst-16785	75	30	,	,	PUNCT
ajst-16785	75	31	matching	matching	NOUN
ajst-16785	75	32	matrix	matrix	NOUN
ajst-16785	75	33	,	,	PUNCT
ajst-16785	75	34	and	and	CCONJ
ajst-16785	75	35	value	value	NOUN
ajst-16785	75	36	matrix	matrix	NOUN
ajst-16785	75	37	obtained	obtain	VERB
ajst-16785	75	38	by	by	ADP
ajst-16785	75	39	multiplying	multiply	VERB
ajst-16785	75	40	the	the	DET
ajst-16785	75	41	trainable	trainable	ADJ
ajst-16785	75	42	weight	weight	NOUN
ajst-16785	75	43	matrices	matrix	NOUN
ajst-16785	75	44	qw	qw	INTJ
ajst-16785	75	45	,	,	PUNCT
ajst-16785	75	46	kw	kw	PROPN
ajst-16785	75	47	and	and	CCONJ
ajst-16785	75	48	vw	vw	PRON
ajst-16785	75	49	with	with	ADP
ajst-16785	75	50	the	the	DET
ajst-16785	75	51	input	input	NOUN
ajst-16785	75	52	x	x	X
ajst-16785	75	53	,	,	PUNCT
ajst-16785	75	54	respectively	respectively	ADV
ajst-16785	75	55	,	,	PUNCT
ajst-16785	75	56	softmax	softmax	PROPN
ajst-16785	75	57	is	be	AUX
ajst-16785	75	58	the	the	DET
ajst-16785	75	59	normalized	normalize	VERB
ajst-16785	75	60	exponential	exponential	ADJ
ajst-16785	75	61	activation	activation	NOUN
ajst-16785	75	62	function	function	NOUN
ajst-16785	75	63	,	,	PUNCT
ajst-16785	75	64	and	and	CCONJ
ajst-16785	75	65	d	d	PRON
ajst-16785	75	66	value	value	NOUN
ajst-16785	75	67	is	be	AUX
ajst-16785	75	68	the	the	DET
ajst-16785	75	69	query	query	NOUN
ajst-16785	75	70	matrix	matrix	NOUN
ajst-16785	75	71	dimension	dimension	NOUN
ajst-16785	75	72	.	.	PUNCT
ajst-16785	76	1	the	the	DET
ajst-16785	76	2	workflow	workflow	NOUN
ajst-16785	76	3	of	of	ADP
ajst-16785	76	4	the	the	DET
ajst-16785	76	5	multi	multi	ADJ
ajst-16785	76	6	-	-	ADJ
ajst-16785	76	7	head	head	ADJ
ajst-16785	76	8	attention	attention	NOUN
ajst-16785	76	9	mechanism	mechanism	NOUN
ajst-16785	76	10	is	be	AUX
ajst-16785	76	11	shown	show	VERB
ajst-16785	76	12	in	in	ADP
ajst-16785	76	13	figure	figure	NOUN
ajst-16785	76	14	1(a	1(a	NUM
ajst-16785	76	15	)	)	PUNCT
ajst-16785	76	16	.	.	PUNCT
ajst-16785	77	1	firstly	firstly	ADV
ajst-16785	77	2	,	,	PUNCT
ajst-16785	77	3	the	the	DET
ajst-16785	77	4	input	input	NOUN
ajst-16785	77	5	image	image	NOUN
ajst-16785	77	6	x	x	PUNCT
ajst-16785	77	7	is	be	AUX
ajst-16785	77	8	mapped	map	VERB
ajst-16785	77	9	to	to	ADP
ajst-16785	77	10	groups	group	NOUN
ajst-16785	77	11	of	of	ADP
ajst-16785	77	12	q	q	PROPN
ajst-16785	77	13	,	,	PUNCT
ajst-16785	77	14	k	k	PROPN
ajst-16785	77	15	,	,	PUNCT
ajst-16785	77	16	and	and	CCONJ
ajst-16785	77	17	v	v	X
ajst-16785	77	18	by	by	ADP
ajst-16785	77	19	a	a	DET
ajst-16785	77	20	linear	linear	ADJ
ajst-16785	77	21	transformation	transformation	NOUN
ajst-16785	77	22	of	of	ADP
ajst-16785	77	23	n	n	CCONJ
ajst-16785	77	24	different	different	ADJ
ajst-16785	77	25	trainable	trainable	ADJ
ajst-16785	77	26	weights	weight	NOUN
ajst-16785	77	27	qw	qw	INTJ
ajst-16785	77	28	,	,	PUNCT
ajst-16785	77	29	kw	kw	INTJ
ajst-16785	77	30	,	,	PUNCT
ajst-16785	77	31	vw	vw	PROPN
ajst-16785	77	32	matrices	matrix	NOUN
ajst-16785	77	33	.	.	PUNCT
ajst-16785	78	1	then	then	ADV
ajst-16785	78	2	the	the	DET
ajst-16785	78	3	n	n	CCONJ
ajst-16785	78	4	different	different	ADJ
ajst-16785	78	5	z	z	NOUN
ajst-16785	78	6	matrices	matrix	NOUN
ajst-16785	78	7	obtained	obtain	VERB
ajst-16785	78	8	after	after	ADP
ajst-16785	78	9	self	self	NOUN
ajst-16785	78	10	attention	attention	NOUN
ajst-16785	78	11	calculation	calculation	NOUN
ajst-16785	78	12	for	for	ADP
ajst-16785	78	13	each	each	DET
ajst-16785	78	14	group	group	NOUN
ajst-16785	78	15	of	of	ADP
ajst-16785	78	16	q	q	PROPN
ajst-16785	78	17	,	,	PUNCT
ajst-16785	78	18	k	k	PROPN
ajst-16785	78	19	,	,	PUNCT
ajst-16785	78	20	and	and	CCONJ
ajst-16785	78	21	v	v	NOUN
ajst-16785	78	22	matrices	matrix	NOUN
ajst-16785	78	23	are	be	AUX
ajst-16785	78	24	concatenated	concatenate	VERB
ajst-16785	78	25	together	together	ADV
ajst-16785	78	26	.	.	PUNCT
ajst-16785	79	1	finally	finally	ADV
ajst-16785	79	2	,	,	PUNCT
ajst-16785	79	3	the	the	DET
ajst-16785	79	4	concatenated	concatenate	VERB
ajst-16785	79	5	z	z	NOUN
ajst-16785	79	6	matrix	matrix	NOUN
ajst-16785	79	7	is	be	AUX
ajst-16785	79	8	multiplied	multiply	VERB
ajst-16785	79	9	by	by	ADP
ajst-16785	79	10	the	the	DET
ajst-16785	79	11	weight	weight	NOUN
ajst-16785	79	12	matrix	matrix	NOUN
ajst-16785	79	13	ow	ow	INTJ
ajst-16785	79	14	to	to	PART
ajst-16785	79	15	get	get	VERB
ajst-16785	79	16	the	the	DET
ajst-16785	79	17	final	final	ADJ
ajst-16785	79	18	matrix	matrix	NOUN
ajst-16785	79	19	z	z	NOUN
ajst-16785	79	20	containing	contain	VERB
ajst-16785	79	21	all	all	DET
ajst-16785	79	22	the	the	DET
ajst-16785	79	23	attention	attention	NOUN
ajst-16785	79	24	heads	head	NOUN
ajst-16785	79	25	so	so	SCONJ
ajst-16785	79	26	that	that	SCONJ
ajst-16785	79	27	the	the	DET
ajst-16785	79	28	model	model	NOUN
ajst-16785	79	29	can	can	AUX
ajst-16785	79	30	focus	focus	VERB
ajst-16785	79	31	on	on	ADP
ajst-16785	79	32	different	different	ADJ
ajst-16785	79	33	positions	position	NOUN
ajst-16785	79	34	in	in	ADP
ajst-16785	79	35	different	different	ADJ
ajst-16785	79	36	subspaces	subspace	NOUN
ajst-16785	79	37	.	.	PUNCT
ajst-16785	80	1			PRON
ajst-16785	80	2	shifted	shift	VERB
ajst-16785	80	3	window	window	NOUN
ajst-16785	80	4	msa	msa	PROPN
ajst-16785	80	5	shifted	shift	VERB
ajst-16785	80	6	window	window	NOUN
ajst-16785	80	7	msa	msa	PROPN
ajst-16785	80	8	achieves	achieve	VERB
ajst-16785	80	9	global	global	ADJ
ajst-16785	80	10	attention	attention	NOUN
ajst-16785	80	11	capability	capability	NOUN
ajst-16785	80	12	by	by	ADP
ajst-16785	80	13	cross	cros	VERB
ajst-16785	80	14	-	-	ADJ
ajst-16785	80	15	connecting	connect	VERB
ajst-16785	80	16	the	the	DET
ajst-16785	80	17	individual	individual	ADJ
ajst-16785	80	18	windows	window	NOUN
ajst-16785	80	19	.	.	PUNCT
ajst-16785	81	1	the	the	DET
ajst-16785	81	2	procedure	procedure	NOUN
ajst-16785	81	3	is	be	AUX
ajst-16785	81	4	shown	show	VERB
ajst-16785	81	5	in	in	ADP
ajst-16785	81	6	figure	figure	NOUN
ajst-16785	81	7	2(b	2(b	NUM
ajst-16785	81	8	)	)	PUNCT
ajst-16785	81	9	.	.	PUNCT
ajst-16785	82	1	firstly	firstly	ADV
ajst-16785	82	2	,	,	PUNCT
ajst-16785	82	3	the	the	DET
ajst-16785	82	4	window	window	NOUN
ajst-16785	82	5	dividing	dividing	NOUN
ajst-16785	82	6	box	box	PROPN
ajst-16785	82	7	is	be	AUX
ajst-16785	82	8	moved	move	VERB
ajst-16785	82	9	to	to	ADP
ajst-16785	82	10	the	the	DET
ajst-16785	82	11	lower	low	ADJ
ajst-16785	82	12	right	right	ADJ
ajst-16785	82	13	corner	corner	NOUN
ajst-16785	82	14	by	by	ADP
ajst-16785	82	15	the	the	DET
ajst-16785	82	16	distance	distance	NOUN
ajst-16785	82	17	of	of	ADP
ajst-16785	82	18	[	[	X
ajst-16785	82	19	window	window	NOUN
ajst-16785	82	20	size/2	size/2	PROPN
ajst-16785	82	21	]	]	PUNCT
ajst-16785	82	22	to	to	PART
ajst-16785	82	23	connect	connect	VERB
ajst-16785	82	24	different	different	ADJ
ajst-16785	82	25	windows	window	NOUN
ajst-16785	82	26	.	.	PUNCT
ajst-16785	83	1	then	then	ADV
ajst-16785	83	2	,	,	PUNCT
ajst-16785	83	3	the	the	DET
ajst-16785	83	4	isolated	isolated	ADJ
ajst-16785	83	5	patches	patch	NOUN
ajst-16785	83	6	(	(	PUNCT
ajst-16785	83	7	a	a	DET
ajst-16785	83	8	,	,	PUNCT
ajst-16785	83	9	b	b	NOUN
ajst-16785	83	10	,	,	PUNCT
ajst-16785	83	11	c	c	NOUN
ajst-16785	83	12	)	)	PUNCT
ajst-16785	83	13	are	be	AUX
ajst-16785	83	14	moved	move	VERB
ajst-16785	83	15	to	to	ADP
ajst-16785	83	16	windows	window	NOUN
ajst-16785	83	17	1	1	NUM
ajst-16785	83	18	,	,	PUNCT
ajst-16785	83	19	2	2	NUM
ajst-16785	83	20	,	,	PUNCT
ajst-16785	83	21	3	3	NUM
ajst-16785	83	22	with	with	ADP
ajst-16785	83	23	incomplete	incomplete	ADJ
ajst-16785	83	24	patches	patch	NOUN
ajst-16785	83	25	.	.	PUNCT
ajst-16785	84	1	finally	finally	ADV
ajst-16785	84	2	,	,	PUNCT
ajst-16785	84	3	the	the	DET
ajst-16785	84	4	correlation	correlation	NOUN
ajst-16785	84	5	between	between	ADP
ajst-16785	84	6	nonadjacent	nonadjacent	ADJ
ajst-16785	84	7	patches	patch	NOUN
ajst-16785	84	8	in	in	ADP
ajst-16785	84	9	the	the	DET
ajst-16785	84	10	original	original	ADJ
ajst-16785	84	11	feature	feature	NOUN
ajst-16785	84	12	map	map	NOUN
ajst-16785	84	13	is	be	AUX
ajst-16785	84	14	eliminated	eliminate	VERB
ajst-16785	84	15	by	by	ADP
ajst-16785	84	16	masking	mask	VERB
ajst-16785	84	17	operations	operation	NOUN
ajst-16785	84	18	in	in	ADP
ajst-16785	84	19	windows	window	NOUN
ajst-16785	84	20	1	1	NUM
ajst-16785	84	21	,	,	PUNCT
ajst-16785	84	22	2	2	NUM
ajst-16785	84	23	,	,	PUNCT
ajst-16785	84	24	3	3	NUM
ajst-16785	84	25	.	.	PUNCT
ajst-16785	85	1	after	after	ADP
ajst-16785	85	2	completing	complete	VERB
ajst-16785	85	3	the	the	DET
ajst-16785	85	4	window	window	NOUN
ajst-16785	85	5	association	association	NOUN
ajst-16785	85	6	,	,	PUNCT
ajst-16785	85	7	a	a	DET
ajst-16785	85	8	window	window	NOUN
ajst-16785	85	9	msa	msa	PROPN
ajst-16785	85	10	calculation	calculation	NOUN
ajst-16785	85	11	is	be	AUX
ajst-16785	85	12	performed	perform	VERB
ajst-16785	85	13	.	.	PUNCT
ajst-16785	86	1	178	178	NUM
ajst-16785	86	2	figure	figure	NOUN
ajst-16785	86	3	1	1	NUM
ajst-16785	86	4	.	.	PUNCT
ajst-16785	87	1	(	(	PUNCT
ajst-16785	87	2	a	a	X
ajst-16785	87	3	)	)	PUNCT
ajst-16785	87	4	multi	multi	ADJ
ajst-16785	87	5	head	head	NOUN
ajst-16785	87	6	self	self	NOUN
ajst-16785	87	7	attention	attention	NOUN
ajst-16785	87	8	mechanism	mechanism	NOUN
ajst-16785	87	9	.	.	PUNCT
ajst-16785	88	1	(	(	PUNCT
ajst-16785	88	2	b)shifted	b)shifte	VERB
ajst-16785	88	3	window	window	NOUN
ajst-16785	88	4	processing	processing	NOUN
ajst-16785	88	5	method	method	NOUN
ajst-16785	88	6	.	.	PUNCT
ajst-16785	89	1	2.3	2.3	NUM
ajst-16785	89	2	.	.	PUNCT
ajst-16785	90	1	coordattention	coordattention	NOUN
ajst-16785	90	2	model	model	NOUN
ajst-16785	90	3	the	the	DET
ajst-16785	90	4	channel	channel	NOUN
ajst-16785	90	5	attention	attention	NOUN
ajst-16785	90	6	mechanism	mechanism	NOUN
ajst-16785	90	7	is	be	AUX
ajst-16785	90	8	used	use	VERB
ajst-16785	90	9	to	to	PART
ajst-16785	90	10	optimize	optimize	VERB
ajst-16785	90	11	the	the	DET
ajst-16785	90	12	compressed	compress	VERB
ajst-16785	90	13	channel	channel	NOUN
ajst-16785	90	14	weight	weight	NOUN
ajst-16785	90	15	values	value	NOUN
ajst-16785	90	16	with	with	ADP
ajst-16785	90	17	feature	feature	NOUN
ajst-16785	90	18	learning	learn	VERB
ajst-16785	90	19	to	to	PART
ajst-16785	90	20	highlight	highlight	VERB
ajst-16785	90	21	important	important	ADJ
ajst-16785	90	22	feature	feature	NOUN
ajst-16785	90	23	channels	channel	NOUN
ajst-16785	90	24	and	and	CCONJ
ajst-16785	90	25	suppress	suppress	VERB
ajst-16785	90	26	redundant	redundant	ADJ
ajst-16785	90	27	channels	channel	NOUN
ajst-16785	90	28	.	.	PUNCT
ajst-16785	91	1	in	in	ADP
ajst-16785	91	2	this	this	DET
ajst-16785	91	3	paper	paper	NOUN
ajst-16785	91	4	,	,	PUNCT
ajst-16785	91	5	the	the	DET
ajst-16785	91	6	coordattention	coordattention	NOUN
ajst-16785	91	7	module	module	NOUN
ajst-16785	91	8	is	be	AUX
ajst-16785	91	9	used	use	VERB
ajst-16785	91	10	,	,	PUNCT
ajst-16785	91	11	which	which	PRON
ajst-16785	91	12	retains	retain	VERB
ajst-16785	91	13	the	the	DET
ajst-16785	91	14	critical	critical	ADJ
ajst-16785	91	15	channel	channel	NOUN
ajst-16785	91	16	feature	feature	NOUN
ajst-16785	91	17	location	location	NOUN
ajst-16785	91	18	information	information	NOUN
ajst-16785	91	19	.	.	PUNCT
ajst-16785	92	1	unlike	unlike	ADP
ajst-16785	92	2	other	other	ADJ
ajst-16785	92	3	commonly	commonly	ADV
ajst-16785	92	4	used	use	VERB
ajst-16785	92	5	channel	channel	NOUN
ajst-16785	92	6	attention	attention	NOUN
ajst-16785	92	7	mechanisms	mechanism	NOUN
ajst-16785	92	8	such	such	ADJ
ajst-16785	92	9	as	as	ADP
ajst-16785	92	10	se[20	se[20	PROPN
ajst-16785	92	11	]	]	PUNCT
ajst-16785	92	12	and	and	CCONJ
ajst-16785	92	13	cbam[21	cbam[21	PROPN
ajst-16785	92	14	]	]	PUNCT
ajst-16785	92	15	,	,	PUNCT
ajst-16785	92	16	the	the	DET
ajst-16785	92	17	coordattention	coordattention	NOUN
ajst-16785	92	18	module	module	NOUN
ajst-16785	92	19	performs	perform	VERB
ajst-16785	92	20	the	the	DET
ajst-16785	92	21	following	follow	VERB
ajst-16785	92	22	steps	step	NOUN
ajst-16785	92	23	:	:	PUNCT
ajst-16785	92	24	firstly	firstly	ADV
ajst-16785	92	25	,	,	PUNCT
ajst-16785	92	26	the	the	DET
ajst-16785	92	27	global	global	ADJ
ajst-16785	92	28	pooling	pool	VERB
ajst-16785	92	29	kernel	kernel	NOUN
ajst-16785	92	30	is	be	AUX
ajst-16785	92	31	decomposed	decompose	VERB
ajst-16785	92	32	into	into	ADP
ajst-16785	92	33	two	two	NUM
ajst-16785	92	34	individual	individual	ADJ
ajst-16785	92	35	kernels	kernel	NOUN
ajst-16785	92	36	:	:	PUNCT
ajst-16785	92	37	(	(	PUNCT
ajst-16785	92	38	h	h	NOUN
ajst-16785	92	39	,	,	PUNCT
ajst-16785	92	40	1	1	NUM
ajst-16785	92	41	)	)	PUNCT
ajst-16785	92	42	and	and	CCONJ
ajst-16785	92	43	(	(	PUNCT
ajst-16785	92	44	1	1	NUM
ajst-16785	92	45	,	,	PUNCT
ajst-16785	92	46	w	w	NOUN
ajst-16785	92	47	)	)	PUNCT
ajst-16785	92	48	.	.	PUNCT
ajst-16785	93	1	pooling	pool	VERB
ajst-16785	93	2	operation	operation	NOUN
ajst-16785	93	3	is	be	AUX
ajst-16785	93	4	carried	carry	VERB
ajst-16785	93	5	out	out	ADP
ajst-16785	93	6	for	for	ADP
ajst-16785	93	7	every	every	DET
ajst-16785	93	8	feature	feature	NOUN
ajst-16785	93	9	channel	channel	NOUN
ajst-16785	93	10	horizontally	horizontally	ADV
ajst-16785	93	11	and	and	CCONJ
ajst-16785	93	12	vertically	vertically	ADV
ajst-16785	93	13	.	.	PUNCT
ajst-16785	94	1	therefore	therefore	ADV
ajst-16785	94	2	,	,	PUNCT
ajst-16785	94	3	feature	feature	NOUN
ajst-16785	94	4	information	information	NOUN
ajst-16785	94	5	compression	compression	NOUN
ajst-16785	94	6	and	and	CCONJ
ajst-16785	94	7	location	location	NOUN
ajst-16785	94	8	encoding	encoding	NOUN
ajst-16785	94	9	are	be	AUX
ajst-16785	94	10	achieved	achieve	VERB
ajst-16785	94	11	.	.	PUNCT
ajst-16785	94	12	0	0	PUNCT
ajst-16785	95	1	w	w	NOUN
ajst-16785	95	2	1	1	NUM
ajst-16785	95	3	(	(	PUNCT
ajst-16785	95	4	)	)	PUNCT
ajst-16785	95	5	(	(	PUNCT
ajst-16785	95	6	)	)	PUNCT
ajst-16785	95	7	h	h	NOUN
ajst-16785	96	1	c	c	NOUN
ajst-16785	96	2	c	c	NOUN
ajst-16785	97	1	i	i	PRON
ajst-16785	97	2	z	z	NOUN
ajst-16785	97	3	h	h	NOUN
ajst-16785	98	1	x	x	PUNCT
ajst-16785	98	2	h	h	NOUN
ajst-16785	99	1	i	i	NOUN
ajst-16785	99	2	w	w	VERB
ajst-16785	99	3			NOUN
ajst-16785	99	4			PROPN
ajst-16785	100	1			NOUN
ajst-16785	100	2			X
ajst-16785	101	1	，	，	PUNCT
ajst-16785	101	2	(	(	PUNCT
ajst-16785	101	3	3	3	X
ajst-16785	101	4	)	)	PUNCT
ajst-16785	101	5	0	0	NUM
ajst-16785	101	6	1	1	NUM
ajst-16785	101	7	(	(	PUNCT
ajst-16785	101	8	)	)	PUNCT
ajst-16785	101	9	(	(	PUNCT
ajst-16785	101	10	)	)	PUNCT
ajst-16785	101	11	w	w	NOUN
ajst-16785	101	12	c	c	NOUN
ajst-16785	101	13	c	c	PROPN
ajst-16785	101	14	j	j	PROPN
ajst-16785	101	15	h	h	PROPN
ajst-16785	101	16	z	z	PROPN
ajst-16785	101	17	w	w	PROPN
ajst-16785	101	18	x	x	PUNCT
ajst-16785	101	19	j	j	PROPN
ajst-16785	101	20	h	h	NOUN
ajst-16785	101	21			NOUN
ajst-16785	101	22			PROPN
ajst-16785	102	1			NUM
ajst-16785	102	2			X
ajst-16785	103	1	，	，	SCONJ
ajst-16785	103	2	w	w	NOUN
ajst-16785	103	3	(	(	PUNCT
ajst-16785	103	4	4	4	NUM
ajst-16785	103	5	)	)	PUNCT
ajst-16785	103	6	where	where	SCONJ
ajst-16785	103	7	(	(	PUNCT
ajst-16785	103	8	)	)	PUNCT
ajst-16785	103	9	h	h	NOUN
ajst-16785	103	10	cz	cz	NOUN
ajst-16785	103	11	h	h	NOUN
ajst-16785	103	12	,	,	PUNCT
ajst-16785	103	13	(	(	PUNCT
ajst-16785	103	14	)	)	PUNCT
ajst-16785	103	15	w	w	NOUN
ajst-16785	103	16	cz	cz	PROPN
ajst-16785	103	17	w	w	PROPN
ajst-16785	103	18	,	,	PUNCT
ajst-16785	103	19	w	w	PROPN
ajst-16785	103	20	,	,	PUNCT
ajst-16785	103	21	and	and	CCONJ
ajst-16785	103	22	h	h	NOUN
ajst-16785	103	23	denote	denote	VERB
ajst-16785	103	24	the	the	DET
ajst-16785	103	25	output	output	NOUN
ajst-16785	103	26	,	,	PUNCT
ajst-16785	103	27	channel	channel	NOUN
ajst-16785	103	28	width	width	NOUN
ajst-16785	103	29	,	,	PUNCT
ajst-16785	103	30	and	and	CCONJ
ajst-16785	103	31	height	height	NOUN
ajst-16785	103	32	of	of	ADP
ajst-16785	103	33	the	the	DET
ajst-16785	103	34	cth	cth	PROPN
ajst-16785	103	35	channel	channel	PROPN
ajst-16785	103	36	at	at	ADP
ajst-16785	103	37	height	height	NOUN
ajst-16785	103	38	h	h	NOUN
ajst-16785	103	39	and	and	CCONJ
ajst-16785	103	40	width	width	ADJ
ajst-16785	103	41	w	w	NOUN
ajst-16785	103	42	,	,	PUNCT
ajst-16785	103	43	respectively	respectively	ADV
ajst-16785	103	44	.	.	PUNCT
ajst-16785	104	1	then	then	ADV
ajst-16785	104	2	,	,	PUNCT
ajst-16785	104	3	the	the	DET
ajst-16785	104	4	joint	joint	ADJ
ajst-16785	104	5	channel	channel	NOUN
ajst-16785	104	6	feature	feature	NOUN
ajst-16785	104	7	map	map	NOUN
ajst-16785	104	8	formed	form	VERB
ajst-16785	104	9	by	by	ADP
ajst-16785	104	10	joining	join	VERB
ajst-16785	104	11	(	(	PUNCT
ajst-16785	104	12	)	)	PUNCT
ajst-16785	104	13	h	h	NOUN
ajst-16785	104	14	cz	cz	NOUN
ajst-16785	104	15	h	h	NOUN
ajst-16785	104	16	,	,	PUNCT
ajst-16785	104	17	(	(	PUNCT
ajst-16785	104	18	)	)	PUNCT
ajst-16785	104	19	w	w	NOUN
ajst-16785	104	20	cz	cz	NOUN
ajst-16785	104	21	w	w	NOUN
ajst-16785	104	22	is	be	AUX
ajst-16785	104	23	subjected	subject	VERB
ajst-16785	104	24	to	to	ADP
ajst-16785	104	25	a	a	DET
ajst-16785	104	26	1x1	1x1	NUM
ajst-16785	104	27	convolution	convolution	NOUN
ajst-16785	104	28	,	,	PUNCT
ajst-16785	104	29	and	and	CCONJ
ajst-16785	104	30	a	a	DET
ajst-16785	104	31	nonlinear	nonlinear	ADJ
ajst-16785	104	32	activation	activation	NOUN
ajst-16785	104	33	operation	operation	NOUN
ajst-16785	104	34	.	.	PUNCT
ajst-16785	105	1	w	w	ADP
ajst-16785	105	2	1	1	NUM
ajst-16785	105	3	(	(	PUNCT
ajst-16785	105	4	(	(	PUNCT
ajst-16785	105	5	[	[	PUNCT
ajst-16785	105	6	]	]	X
ajst-16785	105	7	)	)	PUNCT
ajst-16785	105	8	)	)	PUNCT
ajst-16785	106	1	hf	hf	ADP
ajst-16785	106	2	f	f	PROPN
ajst-16785	106	3	z	z	NOUN
ajst-16785	106	4	z	z	NOUN
ajst-16785	106	5	，	，	PROPN
ajst-16785	106	6	(	(	PUNCT
ajst-16785	106	7	5	5	X
ajst-16785	106	8	)	)	PUNCT
ajst-16785	106	9	where	where	SCONJ
ajst-16785	106	10	[	[	X
ajst-16785	106	11	*	*	PUNCT
ajst-16785	106	12	*	*	PUNCT
ajst-16785	106	13	]	]	X
ajst-16785	106	14	，	，	PUNCT
ajst-16785	106	15	denotes	denote	VERB
ajst-16785	106	16	the	the	DET
ajst-16785	106	17	spatial	spatial	ADJ
ajst-16785	106	18	feature	feature	NOUN
ajst-16785	106	19	layer	layer	NOUN
ajst-16785	106	20	stacking	stack	VERB
ajst-16785	106	21	operation	operation	NOUN
ajst-16785	106	22	,	,	PUNCT
ajst-16785	106	23	1f	1f	PROPN
ajst-16785	106	24	is	be	AUX
ajst-16785	106	25	the	the	DET
ajst-16785	106	26	convolution	convolution	NOUN
ajst-16785	106	27	operation	operation	NOUN
ajst-16785	106	28	,	,	PUNCT
ajst-16785	106	29			PROPN
ajst-16785	106	30	is	be	AUX
ajst-16785	106	31	the	the	DET
ajst-16785	106	32	nonlinear	nonlinear	ADJ
ajst-16785	106	33	activation	activation	NOUN
ajst-16785	106	34	operation	operation	NOUN
ajst-16785	106	35	,	,	PUNCT
ajst-16785	106	36	/	/	SYM
ajst-16785	106	37	(	(	PUNCT
ajst-16785	106	38	)	)	PUNCT
ajst-16785	106	39	c	c	NOUN
ajst-16785	106	40	r	r	NOUN
ajst-16785	106	41	h	h	NOUN
ajst-16785	106	42	wf	wf	NOUN
ajst-16785	106	43	r	r	NOUN
ajst-16785	106	44			NOUN
ajst-16785	106	45			PROPN
ajst-16785	106	46	is	be	AUX
ajst-16785	106	47	the	the	DET
ajst-16785	106	48	compressed	compress	VERB
ajst-16785	106	49	stacked	stack	VERB
ajst-16785	106	50	feature	feature	NOUN
ajst-16785	106	51	channel	channel	NOUN
ajst-16785	106	52	in	in	ADP
ajst-16785	106	53	the	the	DET
ajst-16785	106	54	horizontal	horizontal	ADJ
ajst-16785	106	55	and	and	CCONJ
ajst-16785	106	56	vertical	vertical	ADJ
ajst-16785	106	57	directions	direction	NOUN
ajst-16785	106	58	,	,	PUNCT
ajst-16785	106	59	and	and	CCONJ
ajst-16785	106	60	r	r	NOUN
ajst-16785	106	61	is	be	AUX
ajst-16785	106	62	the	the	DET
ajst-16785	106	63	1x1	1x1	NUM
ajst-16785	106	64	feature	feature	NOUN
ajst-16785	106	65	convolution	convolution	NOUN
ajst-16785	106	66	layer	layer	NOUN
ajst-16785	106	67	change	change	NOUN
ajst-16785	106	68	ratio	ratio	NOUN
ajst-16785	106	69	.	.	PUNCT
ajst-16785	107	1	finally	finally	ADV
ajst-16785	107	2	,	,	PUNCT
ajst-16785	107	3	f	f	PROPN
ajst-16785	107	4	is	be	AUX
ajst-16785	107	5	divided	divide	VERB
ajst-16785	107	6	into	into	ADP
ajst-16785	107	7	two	two	NUM
ajst-16785	107	8	separate	separate	ADJ
ajst-16785	107	9	feature	feature	NOUN
ajst-16785	107	10	layers	layer	NOUN
ajst-16785	107	11	/h	/h	PUNCT
ajst-16785	107	12	c	c	NOUN
ajst-16785	107	13	r	r	NOUN
ajst-16785	107	14	hf	hf	NOUN
ajst-16785	107	15	r	r	NOUN
ajst-16785	107	16			NOUN
ajst-16785	107	17	and	and	CCONJ
ajst-16785	107	18	/w	/w	NOUN
ajst-16785	107	19	c	c	NOUN
ajst-16785	107	20	r	r	NOUN
ajst-16785	107	21	wf	wf	PROPN
ajst-16785	107	22	r	r	NOUN
ajst-16785	107	23			NOUN
ajst-16785	107	24	,	,	PUNCT
ajst-16785	107	25	then	then	ADV
ajst-16785	107	26	hf	hf	VERB
ajst-16785	107	27	and	and	CCONJ
ajst-16785	107	28	wf	wf	PROPN
ajst-16785	107	29	are	be	AUX
ajst-16785	107	30	transformed	transform	VERB
ajst-16785	107	31	into	into	ADP
ajst-16785	107	32	the	the	DET
ajst-16785	107	33	original	original	ADJ
ajst-16785	107	34	input	input	NOUN
ajst-16785	107	35	feature	feature	NOUN
ajst-16785	107	36	channel	channel	NOUN
ajst-16785	107	37	layers	layer	NOUN
ajst-16785	107	38	using	use	VERB
ajst-16785	107	39	two	two	NUM
ajst-16785	107	40	1x1	1x1	NUM
ajst-16785	107	41	convolutions	convolution	NOUN
ajst-16785	107	42	.	.	PUNCT
ajst-16785	108	1	(	(	PUNCT
ajst-16785	108	2	(	(	PUNCT
ajst-16785	108	3	)	)	PUNCT
ajst-16785	108	4	)	)	PUNCT
ajst-16785	108	5	h	h	NOUN
ajst-16785	108	6	h	h	NOUN
ajst-16785	108	7	hg	hg	PROPN
ajst-16785	108	8	f	f	PROPN
ajst-16785	108	9	f	f	VERB
ajst-16785	108	10	(	(	PUNCT
ajst-16785	108	11	6	6	NUM
ajst-16785	108	12	)	)	PUNCT
ajst-16785	108	13	(	(	PUNCT
ajst-16785	108	14	(	(	PUNCT
ajst-16785	108	15	)	)	PUNCT
ajst-16785	108	16	)	)	PUNCT
ajst-16785	108	17	w	w	PROPN
ajst-16785	108	18	w	w	PROPN
ajst-16785	108	19	wg	wg	PROPN
ajst-16785	108	20	f	f	PROPN
ajst-16785	108	21	f	f	NOUN
ajst-16785	108	22	(	(	PUNCT
ajst-16785	108	23	7	7	NUM
ajst-16785	108	24	)	)	PUNCT
ajst-16785	108	25	where	where	SCONJ
ajst-16785	108	26			PROPN
ajst-16785	108	27	denotes	denote	VERB
ajst-16785	108	28	the	the	DET
ajst-16785	108	29	sigmoid	sigmoid	NOUN
ajst-16785	108	30	activation	activation	NOUN
ajst-16785	108	31	function	function	NOUN
ajst-16785	108	32	,	,	PUNCT
ajst-16785	108	33	hg	hg	NOUN
ajst-16785	108	34	and	and	CCONJ
ajst-16785	108	35	wg	wg	PROPN
ajst-16785	108	36	are	be	AUX
ajst-16785	108	37	the	the	DET
ajst-16785	108	38	attention	attention	NOUN
ajst-16785	108	39	weights	weight	NOUN
ajst-16785	108	40	of	of	ADP
ajst-16785	108	41	the	the	DET
ajst-16785	108	42	feature	feature	NOUN
ajst-16785	108	43	channels	channel	NOUN
ajst-16785	108	44	in	in	ADP
ajst-16785	108	45	the	the	DET
ajst-16785	108	46	horizontal	horizontal	ADJ
ajst-16785	108	47	and	and	CCONJ
ajst-16785	108	48	vertical	vertical	ADJ
ajst-16785	108	49	directions	direction	NOUN
ajst-16785	108	50	,	,	PUNCT
ajst-16785	108	51	respectively	respectively	ADV
ajst-16785	108	52	.	.	PUNCT
ajst-16785	109	1	finally	finally	ADV
ajst-16785	109	2	,	,	PUNCT
ajst-16785	109	3	the	the	DET
ajst-16785	109	4	output	output	NOUN
ajst-16785	109	5	of	of	ADP
ajst-16785	109	6	the	the	DET
ajst-16785	109	7	coordattention	coordattention	NOUN
ajst-16785	109	8	module	module	NOUN
ajst-16785	109	9	can	can	AUX
ajst-16785	109	10	be	be	AUX
ajst-16785	109	11	expressed	express	VERB
ajst-16785	109	12	as	as	ADP
ajst-16785	109	13	:	:	PUNCT
ajst-16785	109	14	(	(	PUNCT
ajst-16785	109	15	,	,	PUNCT
ajst-16785	109	16	)	)	PUNCT
ajst-16785	109	17	(	(	PUNCT
ajst-16785	109	18	,	,	PUNCT
ajst-16785	109	19	)	)	PUNCT
ajst-16785	109	20	(	(	PUNCT
ajst-16785	109	21	)	)	PUNCT
ajst-16785	109	22	(	(	PUNCT
ajst-16785	109	23	)	)	PUNCT
ajst-16785	109	24	h	h	PROPN
ajst-16785	109	25	w	w	NOUN
ajst-16785	109	26	c	c	NOUN
ajst-16785	109	27	c	c	NOUN
ajst-16785	110	1	c	c	NOUN
ajst-16785	110	2	cy	cy	INTJ
ajst-16785	110	3	i	i	PRON
ajst-16785	110	4	j	j	NOUN
ajst-16785	110	5	x	x	VERB
ajst-16785	111	1	i	i	PRON
ajst-16785	111	2	j	j	NOUN
ajst-16785	112	1	g	g	NOUN
ajst-16785	112	2	i	i	PRON
ajst-16785	112	3	g	g	PROPN
ajst-16785	112	4	j	j	PROPN
ajst-16785	112	5			PROPN
ajst-16785	112	6			PROPN
ajst-16785	112	7	(	(	PUNCT
ajst-16785	112	8	8)	8)	PROPN
ajst-16785	112	9	3	3	NUM
ajst-16785	112	10	.	.	PUNCT
ajst-16785	113	1	methods	method	NOUN
ajst-16785	113	2	3.1	3.1	NUM
ajst-16785	113	3	.	.	PUNCT
ajst-16785	114	1	overview	overview	NOUN
ajst-16785	114	2	of	of	ADP
ajst-16785	114	3	icst	icst	ADJ
ajst-16785	114	4	the	the	DET
ajst-16785	114	5	framework	framework	NOUN
ajst-16785	114	6	of	of	ADP
ajst-16785	114	7	icst	icst	PROPN
ajst-16785	114	8	is	be	AUX
ajst-16785	114	9	shown	show	VERB
ajst-16785	114	10	in	in	ADP
ajst-16785	114	11	figure	figure	NOUN
ajst-16785	114	12	2	2	NUM
ajst-16785	114	13	,	,	PUNCT
ajst-16785	114	14	and	and	CCONJ
ajst-16785	114	15	its	its	PRON
ajst-16785	114	16	specific	specific	ADJ
ajst-16785	114	17	steps	step	NOUN
ajst-16785	114	18	are	be	AUX
ajst-16785	114	19	divided	divide	VERB
ajst-16785	114	20	into	into	ADP
ajst-16785	114	21	3	3	NUM
ajst-16785	114	22	stages	stage	NOUN
ajst-16785	114	23	.	.	PUNCT
ajst-16785	115	1	stage	stage	NOUN
ajst-16785	115	2	1	1	NUM
ajst-16785	115	3	:	:	PUNCT
ajst-16785	115	4	the	the	DET
ajst-16785	115	5	input	input	NOUN
ajst-16785	115	6	image	image	NOUN
ajst-16785	115	7	features	feature	NOUN
ajst-16785	115	8	are	be	AUX
ajst-16785	115	9	learned	learn	VERB
ajst-16785	115	10	at	at	ADP
ajst-16785	115	11	different	different	ADJ
ajst-16785	115	12	scales	scale	NOUN
ajst-16785	115	13	using	use	VERB
ajst-16785	115	14	inception1	inception1	NOUN
ajst-16785	115	15	,	,	PUNCT
ajst-16785	115	16	and	and	CCONJ
ajst-16785	115	17	swin	swin	PROPN
ajst-16785	115	18	transformer	transformer	PROPN
ajst-16785	115	19	is	be	AUX
ajst-16785	115	20	applied	apply	VERB
ajst-16785	115	21	to	to	PART
ajst-16785	115	22	capture	capture	VERB
ajst-16785	115	23	the	the	DET
ajst-16785	115	24	global	global	ADJ
ajst-16785	115	25	feature	feature	NOUN
ajst-16785	115	26	correlation	correlation	NOUN
ajst-16785	115	27	of	of	ADP
ajst-16785	115	28	the	the	DET
ajst-16785	115	29	input	input	NOUN
ajst-16785	115	30	image	image	NOUN
ajst-16785	115	31	,	,	PUNCT
ajst-16785	115	32	and	and	CCONJ
ajst-16785	115	33	then	then	ADV
ajst-16785	115	34	the	the	DET
ajst-16785	115	35	global	global	ADJ
ajst-16785	115	36	image	image	NOUN
ajst-16785	115	37	information	information	NOUN
ajst-16785	115	38	is	be	AUX
ajst-16785	115	39	obtained	obtain	VERB
ajst-16785	115	40	.	.	PUNCT
ajst-16785	116	1	stage	stage	NOUN
ajst-16785	116	2	2	2	NUM
ajst-16785	116	3	:	:	PUNCT
ajst-16785	116	4	firstly	firstly	ADV
ajst-16785	116	5	,	,	PUNCT
ajst-16785	116	6	deeper	deep	ADJ
ajst-16785	116	7	feature	feature	NOUN
ajst-16785	116	8	extraction	extraction	NOUN
ajst-16785	116	9	of	of	ADP
ajst-16785	116	10	the	the	DET
ajst-16785	116	11	upper	upper	ADJ
ajst-16785	116	12	layer	layer	NOUN
ajst-16785	116	13	feature	feature	NOUN
ajst-16785	116	14	map	map	NOUN
ajst-16785	116	15	is	be	AUX
ajst-16785	116	16	carried	carry	VERB
ajst-16785	116	17	out	out	ADP
ajst-16785	116	18	by	by	ADP
ajst-16785	116	19	inception2	inception2	NOUN
ajst-16785	116	20	.	.	PUNCT
ajst-16785	117	1	the	the	DET
ajst-16785	117	2	task	task	NOUN
ajst-16785	117	3	of	of	ADP
ajst-16785	117	4	enriching	enrich	VERB
ajst-16785	117	5	the	the	DET
ajst-16785	117	6	number	number	NOUN
ajst-16785	117	7	of	of	ADP
ajst-16785	117	8	feature	feature	NOUN
ajst-16785	117	9	layers	layer	NOUN
ajst-16785	117	10	and	and	CCONJ
ajst-16785	117	11	downsampling	downsampling	NOUN
ajst-16785	117	12	is	be	AUX
ajst-16785	117	13	completed	complete	VERB
ajst-16785	117	14	.	.	PUNCT
ajst-16785	118	1	then	then	ADV
ajst-16785	118	2	,	,	PUNCT
ajst-16785	118	3	the	the	DET
ajst-16785	118	4	coordattention	coordattention	NOUN
ajst-16785	118	5	module	module	NOUN
ajst-16785	118	6	is	be	AUX
ajst-16785	118	7	used	use	VERB
ajst-16785	118	8	to	to	PART
ajst-16785	118	9	highlight	highlight	VERB
ajst-16785	118	10	essential	essential	ADJ
ajst-16785	118	11	feature	feature	NOUN
ajst-16785	118	12	channels	channel	NOUN
ajst-16785	118	13	.	.	PUNCT
ajst-16785	119	1	at	at	ADP
ajst-16785	119	2	the	the	DET
ajst-16785	119	3	same	same	ADJ
ajst-16785	119	4	time	time	NOUN
ajst-16785	119	5	,	,	PUNCT
ajst-16785	119	6	the	the	DET
ajst-16785	119	7	output	output	NOUN
ajst-16785	119	8	feature	feature	NOUN
ajst-16785	119	9	layer	layer	NOUN
ajst-16785	119	10	of	of	ADP
ajst-16785	119	11	the	the	DET
ajst-16785	119	12	coordattention	coordattention	NOUN
ajst-16785	119	13	module	module	NOUN
ajst-16785	119	14	is	be	AUX
ajst-16785	119	15	processed	process	VERB
ajst-16785	119	16	by	by	ADP
ajst-16785	119	17	batch	batch	NOUN
ajst-16785	119	18	normalization	normalization	NOUN
ajst-16785	119	19	(	(	PUNCT
ajst-16785	119	20	bn	bn	NOUN
ajst-16785	119	21	)	)	PUNCT
ajst-16785	119	22	for	for	ADP
ajst-16785	119	23	batch	batch	NOUN
ajst-16785	119	24	normalization	normalization	NOUN
ajst-16785	119	25	to	to	PART
ajst-16785	119	26	ensure	ensure	VERB
ajst-16785	119	27	better	well	ADJ
ajst-16785	119	28	delivery	delivery	NOUN
ajst-16785	119	29	of	of	ADP
ajst-16785	119	30	network	network	NOUN
ajst-16785	119	31	parameter	parameter	PROPN
ajst-16785	119	32	gradient	gradient	PROPN
ajst-16785	119	33	optimization	optimization	NOUN
ajst-16785	119	34	.	.	PUNCT
ajst-16785	120	1	finally	finally	ADV
ajst-16785	120	2	,	,	PUNCT
ajst-16785	120	3	swin	swin	PROPN
ajst-16785	120	4	transformer	transformer	PROPN
ajst-16785	120	5	is	be	AUX
ajst-16785	120	6	used	use	VERB
ajst-16785	120	7	to	to	PART
ajst-16785	120	8	proceed	proceed	VERB
ajst-16785	120	9	learning	learn	VERB
ajst-16785	120	10	global	global	ADJ
ajst-16785	120	11	information	information	NOUN
ajst-16785	120	12	.	.	PUNCT
ajst-16785	121	1	stage	stage	NOUN
ajst-16785	121	2	3	3	NUM
ajst-16785	121	3	:	:	PUNCT
ajst-16785	121	4	after	after	ADP
ajst-16785	121	5	stage	stage	NOUN
ajst-16785	121	6	2	2	NUM
ajst-16785	121	7	is	be	AUX
ajst-16785	121	8	repeated	repeat	VERB
ajst-16785	121	9	three	three	NUM
ajst-16785	121	10	times	time	NOUN
ajst-16785	121	11	,	,	PUNCT
ajst-16785	121	12	defect	defect	ADJ
ajst-16785	121	13	detection	detection	NOUN
ajst-16785	121	14	and	and	CCONJ
ajst-16785	121	15	recognition	recognition	NOUN
ajst-16785	121	16	are	be	AUX
ajst-16785	121	17	achieved	achieve	VERB
ajst-16785	121	18	by	by	ADP
ajst-16785	121	19	applying	apply	VERB
ajst-16785	121	20	a	a	DET
ajst-16785	121	21	fully	fully	ADV
ajst-16785	121	22	connected	connect	VERB
ajst-16785	121	23	layer	layer	NOUN
ajst-16785	121	24	after	after	ADP
ajst-16785	121	25	an	an	DET
ajst-16785	121	26	average	average	ADJ
ajst-16785	121	27	pooling	pool	VERB
ajst-16785	121	28	layer	layer	NOUN
ajst-16785	121	29	.	.	PUNCT
ajst-16785	122	1	179	179	NUM
ajst-16785	122	2	figure	figure	NOUN
ajst-16785	122	3	2	2	NUM
ajst-16785	122	4	.	.	PUNCT
ajst-16785	122	5	icst	icst	PROPN
ajst-16785	122	6	structure	structure	NOUN
ajst-16785	122	7	diagram	diagram	NOUN
ajst-16785	122	8	.	.	PUNCT
ajst-16785	123	1	(	(	PUNCT
ajst-16785	123	2	a)inception	a)inception	NOUN
ajst-16785	123	3	.	.	PUNCT
ajst-16785	124	1	(	(	PUNCT
ajst-16785	124	2	b)coordattention	b)coordattention	PROPN
ajst-16785	124	3	.	.	PUNCT
ajst-16785	125	1	(	(	PUNCT
ajst-16785	125	2	c)swim	c)swim	NUM
ajst-16785	125	3	transformer	transformer	NOUN
ajst-16785	125	4	block	block	NOUN
ajst-16785	125	5	in	in	ADP
ajst-16785	125	6	the	the	DET
ajst-16785	125	7	icst	icst	NOUN
ajst-16785	125	8	,	,	PUNCT
ajst-16785	125	9	four	four	NUM
ajst-16785	125	10	inception	inception	NOUN
ajst-16785	125	11	modules	module	NOUN
ajst-16785	125	12	are	be	AUX
ajst-16785	125	13	distributed	distribute	VERB
ajst-16785	125	14	in	in	ADP
ajst-16785	125	15	three	three	NUM
ajst-16785	125	16	stages	stage	NOUN
ajst-16785	125	17	to	to	PART
ajst-16785	125	18	change	change	VERB
ajst-16785	125	19	the	the	DET
ajst-16785	125	20	feature	feature	NOUN
ajst-16785	125	21	channel	channel	NOUN
ajst-16785	125	22	size	size	NOUN
ajst-16785	125	23	and	and	CCONJ
ajst-16785	125	24	number	number	NOUN
ajst-16785	125	25	,	,	PUNCT
ajst-16785	125	26	while	while	SCONJ
ajst-16785	125	27	other	other	ADJ
ajst-16785	125	28	operations	operation	NOUN
ajst-16785	125	29	do	do	AUX
ajst-16785	125	30	not	not	PART
ajst-16785	125	31	change	change	VERB
ajst-16785	125	32	the	the	DET
ajst-16785	125	33	channel	channel	NOUN
ajst-16785	125	34	size	size	NOUN
ajst-16785	125	35	and	and	CCONJ
ajst-16785	125	36	number	number	NOUN
ajst-16785	125	37	.	.	PUNCT
ajst-16785	126	1	the	the	DET
ajst-16785	126	2	specific	specific	ADJ
ajst-16785	126	3	output	output	NOUN
ajst-16785	126	4	size	size	NOUN
ajst-16785	126	5	of	of	ADP
ajst-16785	126	6	each	each	DET
ajst-16785	126	7	layer	layer	NOUN
ajst-16785	126	8	and	and	CCONJ
ajst-16785	126	9	inception	inception	NOUN
ajst-16785	126	10	module	module	NOUN
ajst-16785	126	11	parameters	parameter	NOUN
ajst-16785	126	12	are	be	AUX
ajst-16785	126	13	shown	show	VERB
ajst-16785	126	14	in	in	ADP
ajst-16785	126	15	table	table	NOUN
ajst-16785	126	16	1	1	NUM
ajst-16785	126	17	.	.	PUNCT
ajst-16785	127	1	in	in	ADP
ajst-16785	127	2	the	the	DET
ajst-16785	127	3	table	table	NOUN
ajst-16785	127	4	,	,	PUNCT
ajst-16785	127	5	h	h	NOUN
ajst-16785	127	6	,	,	PUNCT
ajst-16785	127	7	w	w	PROPN
ajst-16785	127	8	and	and	CCONJ
ajst-16785	127	9	c	c	PROPN
ajst-16785	127	10	indicate	indicate	VERB
ajst-16785	127	11	the	the	DET
ajst-16785	127	12	image	image	NOUN
ajst-16785	127	13	's	's	PART
ajst-16785	127	14	height	height	NOUN
ajst-16785	127	15	,	,	PUNCT
ajst-16785	127	16	width	width	ADJ
ajst-16785	127	17	and	and	CCONJ
ajst-16785	127	18	number	number	NOUN
ajst-16785	127	19	of	of	ADP
ajst-16785	127	20	channels	channel	NOUN
ajst-16785	127	21	,	,	PUNCT
ajst-16785	127	22	respectively	respectively	ADV
ajst-16785	127	23	.	.	PUNCT
ajst-16785	128	1	(	(	PUNCT
ajst-16785	128	2	(	(	PUNCT
ajst-16785	128	3	1	1	NUM
ajst-16785	128	4	1	1	NUM
ajst-16785	128	5	)	)	PUNCT
ajst-16785	128	6	(	(	PUNCT
ajst-16785	128	7	4	4	NUM
ajst-16785	128	8	4),3	4),3	NUM
ajst-16785	128	9	/	/	SYM
ajst-16785	128	10	8)c	8)c	PROPN
ajst-16785	128	11			VERB
ajst-16785	128	12			NOUN
ajst-16785	128	13	in	in	ADP
ajst-16785	128	14	the	the	DET
ajst-16785	128	15	column	column	NOUN
ajst-16785	128	16	of	of	ADP
ajst-16785	128	17	inception	inception	ADJ
ajst-16785	128	18	module	module	NOUN
ajst-16785	128	19	parameters	parameter	NOUN
ajst-16785	128	20	indicates	indicate	VERB
ajst-16785	128	21	that	that	SCONJ
ajst-16785	128	22	the	the	DET
ajst-16785	128	23	1x1	1x1	NUM
ajst-16785	128	24	size	size	NOUN
ajst-16785	128	25	kernel	kernel	NOUN
ajst-16785	128	26	is	be	AUX
ajst-16785	128	27	used	use	VERB
ajst-16785	128	28	for	for	ADP
ajst-16785	128	29	convolution	convolution	NOUN
ajst-16785	128	30	first	first	ADV
ajst-16785	128	31	by	by	ADP
ajst-16785	128	32	step	step	NOUN
ajst-16785	128	33	1	1	NUM
ajst-16785	128	34	,	,	PUNCT
ajst-16785	128	35	and	and	CCONJ
ajst-16785	128	36	then	then	ADV
ajst-16785	128	37	the	the	DET
ajst-16785	128	38	4x4	4x4	NUM
ajst-16785	128	39	size	size	NOUN
ajst-16785	128	40	kernel	kernel	NOUN
ajst-16785	128	41	is	be	AUX
ajst-16785	128	42	used	use	VERB
ajst-16785	128	43	for	for	ADP
ajst-16785	128	44	downsampling	downsample	VERB
ajst-16785	128	45	mapping	mapping	NOUN
ajst-16785	128	46	to	to	PART
ajst-16785	128	47	avoid	avoid	VERB
ajst-16785	128	48	the	the	DET
ajst-16785	128	49	loss	loss	NOUN
ajst-16785	128	50	of	of	ADP
ajst-16785	128	51	image	image	NOUN
ajst-16785	128	52	information	information	NOUN
ajst-16785	128	53	by	by	ADP
ajst-16785	128	54	pooling	pool	VERB
ajst-16785	128	55	.	.	PUNCT
ajst-16785	129	1	3	3	NUM
ajst-16785	129	2	/	/	SYM
ajst-16785	129	3	8c	8c	PROPN
ajst-16785	129	4	is	be	AUX
ajst-16785	129	5	the	the	DET
ajst-16785	129	6	number	number	NOUN
ajst-16785	129	7	of	of	ADP
ajst-16785	129	8	convolutional	convolutional	ADJ
ajst-16785	129	9	kernels	kernel	NOUN
ajst-16785	129	10	,	,	PUNCT
ajst-16785	129	11	and	and	CCONJ
ajst-16785	129	12	the	the	DET
ajst-16785	129	13	value	value	NOUN
ajst-16785	129	14	of	of	ADP
ajst-16785	129	15	c	c	PROPN
ajst-16785	129	16	in	in	ADP
ajst-16785	129	17	this	this	DET
ajst-16785	129	18	paper	paper	NOUN
ajst-16785	129	19	is	be	AUX
ajst-16785	129	20	taken	take	VERB
ajst-16785	129	21	as	as	ADP
ajst-16785	129	22	24	24	NUM
ajst-16785	129	23	.	.	PUNCT
ajst-16785	129	24	table	table	NOUN
ajst-16785	129	25	1	1	NUM
ajst-16785	129	26	.	.	PUNCT
ajst-16785	129	27	specific	specific	ADJ
ajst-16785	129	28	parameters	parameter	NOUN
ajst-16785	129	29	of	of	ADP
ajst-16785	129	30	network	network	NOUN
ajst-16785	129	31	layers	layer	NOUN
ajst-16785	129	32	steps	step	VERB
ajst-16785	129	33	output	output	NOUN
ajst-16785	129	34	size	size	NOUN
ajst-16785	129	35	inception	inception	NOUN
ajst-16785	129	36	module	module	NOUN
ajst-16785	129	37	parameters	parameter	NOUN
ajst-16785	129	38	input	input	VERB
ajst-16785	129	39	1h	1h	NUM
ajst-16785	129	40	w	w	PROPN
ajst-16785	129	41			PROPN
ajst-16785	129	42	—	—	PUNCT
ajst-16785	129	43	stage1	stage1	NOUN
ajst-16785	129	44	4	4	NUM
ajst-16785	129	45	4	4	NUM
ajst-16785	129	46	h	h	NOUN
ajst-16785	129	47	w	w	PROPN
ajst-16785	129	48	c	c	PROPN
ajst-16785	129	49			NOUN
ajst-16785	129	50	3	3	NUM
ajst-16785	129	51	(	(	PUNCT
ajst-16785	129	52	1	1	NUM
ajst-16785	129	53	1	1	NUM
ajst-16785	129	54	)	)	PUNCT
ajst-16785	129	55	(	(	PUNCT
ajst-16785	129	56	4	4	NUM
ajst-16785	129	57	4	4	NUM
ajst-16785	129	58	)	)	PUNCT
ajst-16785	129	59	,	,	PUNCT
ajst-16785	129	60	8	8	NUM
ajst-16785	129	61	2	2	NUM
ajst-16785	129	62	(	(	PUNCT
ajst-16785	129	63	2	2	NUM
ajst-16785	129	64	2	2	NUM
ajst-16785	129	65	)	)	PUNCT
ajst-16785	129	66	(	(	PUNCT
ajst-16785	129	67	2	2	NUM
ajst-16785	129	68	2	2	NUM
ajst-16785	129	69	)	)	PUNCT
ajst-16785	129	70	,	,	PUNCT
ajst-16785	129	71	8	8	NUM
ajst-16785	129	72	2	2	NUM
ajst-16785	129	73	(	(	PUNCT
ajst-16785	129	74	3	3	NUM
ajst-16785	129	75	3	3	NUM
ajst-16785	129	76	)	)	PUNCT
ajst-16785	129	77	(	(	PUNCT
ajst-16785	129	78	4	4	NUM
ajst-16785	129	79	4	4	NUM
ajst-16785	129	80	)	)	PUNCT
ajst-16785	129	81	,	,	PUNCT
ajst-16785	130	1	8	8	NUM
ajst-16785	130	2	1	1	NUM
ajst-16785	130	3	(	(	PUNCT
ajst-16785	130	4	3	3	NUM
ajst-16785	130	5	3max	3max	NUM
ajst-16785	130	6	)	)	PUNCT
ajst-16785	130	7	(	(	PUNCT
ajst-16785	130	8	4	4	NUM
ajst-16785	130	9	4	4	NUM
ajst-16785	130	10	)	)	PUNCT
ajst-16785	130	11	,	,	PUNCT
ajst-16785	130	12	8	8	NUM
ajst-16785	130	13	c	c	NOUN
ajst-16785	130	14	c	c	NOUN
ajst-16785	130	15	c	c	NOUN
ajst-16785	130	16	pool	pool	NOUN
ajst-16785	130	17	c	c	X
ajst-16785	130	18			PROPN
ajst-16785	131	1			PROPN
ajst-16785	131	2			PROPN
ajst-16785	131	3			PROPN
ajst-16785	131	4			NOUN
ajst-16785	131	5			NOUN
ajst-16785	131	6			NOUN
ajst-16785	131	7			NOUN
ajst-16785	131	8			X
ajst-16785	131	9			ADV
ajst-16785	131	10			PROPN
ajst-16785	131	11			NOUN
ajst-16785	131	12			NOUN
ajst-16785	131	13			NOUN
ajst-16785	131	14			NOUN
ajst-16785	131	15			X
ajst-16785	131	16			VERB
ajst-16785	131	17			PROPN
ajst-16785	131	18			PROPN
ajst-16785	131	19			PROPN
ajst-16785	131	20			NOUN
ajst-16785	131	21			NOUN
ajst-16785	131	22			NOUN
ajst-16785	131	23			X
ajst-16785	131	24			VERB
ajst-16785	131	25			PROPN
ajst-16785	131	26			PROPN
ajst-16785	131	27			PROPN
ajst-16785	131	28	stage2	stage2	NOUN
ajst-16785	131	29	2	2	NUM
ajst-16785	131	30	8	8	NUM
ajst-16785	131	31	8	8	NUM
ajst-16785	131	32	h	h	NOUN
ajst-16785	131	33	w	w	PROPN
ajst-16785	131	34	c	c	PROPN
ajst-16785	131	35			NOUN
ajst-16785	131	36	3	3	NUM
ajst-16785	131	37	(	(	PUNCT
ajst-16785	131	38	1	1	NUM
ajst-16785	131	39	1	1	NUM
ajst-16785	131	40	)	)	PUNCT
ajst-16785	131	41	(	(	PUNCT
ajst-16785	131	42	2	2	NUM
ajst-16785	131	43	2	2	NUM
ajst-16785	131	44	)	)	PUNCT
ajst-16785	131	45	,	,	PUNCT
ajst-16785	131	46	2	2	NUM
ajst-16785	131	47	8	8	NUM
ajst-16785	131	48	2	2	NUM
ajst-16785	131	49	(	(	PUNCT
ajst-16785	131	50	2	2	NUM
ajst-16785	131	51	2	2	NUM
ajst-16785	131	52	)	)	PUNCT
ajst-16785	131	53	,	,	PUNCT
ajst-16785	131	54	2	2	NUM
ajst-16785	131	55	8	8	NUM
ajst-16785	131	56	2	2	NUM
ajst-16785	131	57	(	(	PUNCT
ajst-16785	131	58	3	3	NUM
ajst-16785	131	59	3	3	NUM
ajst-16785	131	60	)	)	PUNCT
ajst-16785	131	61	(	(	PUNCT
ajst-16785	131	62	2	2	NUM
ajst-16785	131	63	2	2	NUM
ajst-16785	131	64	)	)	PUNCT
ajst-16785	131	65	,	,	PUNCT
ajst-16785	131	66	2	2	NUM
ajst-16785	131	67	8	8	NUM
ajst-16785	131	68	1	1	NUM
ajst-16785	131	69	(	(	PUNCT
ajst-16785	131	70	3	3	NUM
ajst-16785	131	71	3max	3max	NUM
ajst-16785	131	72	)	)	PUNCT
ajst-16785	131	73	(	(	PUNCT
ajst-16785	131	74	2	2	NUM
ajst-16785	131	75	2	2	NUM
ajst-16785	131	76	)	)	PUNCT
ajst-16785	131	77	,	,	PUNCT
ajst-16785	132	1	2	2	NUM
ajst-16785	132	2	8	8	NUM
ajst-16785	132	3	c	c	NOUN
ajst-16785	132	4	c	c	NOUN
ajst-16785	132	5	c	c	NOUN
ajst-16785	132	6	pool	pool	NOUN
ajst-16785	132	7	c	c	X
ajst-16785	132	8			PROPN
ajst-16785	133	1			PROPN
ajst-16785	133	2			VERB
ajst-16785	133	3			INTJ
ajst-16785	133	4			PROPN
ajst-16785	133	5			PROPN
ajst-16785	133	6			PROPN
ajst-16785	133	7			NOUN
ajst-16785	133	8			NOUN
ajst-16785	133	9			X
ajst-16785	133	10			PROPN
ajst-16785	133	11			NOUN
ajst-16785	133	12			NOUN
ajst-16785	133	13			NOUN
ajst-16785	133	14			NOUN
ajst-16785	133	15			X
ajst-16785	133	16			PROPN
ajst-16785	133	17			PROPN
ajst-16785	133	18			PROPN
ajst-16785	133	19			PROPN
ajst-16785	133	20			PROPN
ajst-16785	133	21			NOUN
ajst-16785	133	22			NOUN
ajst-16785	133	23			NOUN
ajst-16785	133	24			X
ajst-16785	133	25			PROPN
ajst-16785	133	26			PROPN
ajst-16785	133	27			PROPN
ajst-16785	133	28			PROPN
ajst-16785	133	29			PROPN
ajst-16785	133	30	stage3	stage3	NOUN
ajst-16785	133	31	4	4	NUM
ajst-16785	133	32	16	16	NUM
ajst-16785	133	33	16	16	NUM
ajst-16785	133	34	h	h	NOUN
ajst-16785	133	35	w	w	PROPN
ajst-16785	133	36	c	c	PROPN
ajst-16785	133	37			NOUN
ajst-16785	133	38	3	3	NUM
ajst-16785	133	39	(	(	PUNCT
ajst-16785	133	40	1	1	NUM
ajst-16785	133	41	1	1	NUM
ajst-16785	133	42	)	)	PUNCT
ajst-16785	133	43	(	(	PUNCT
ajst-16785	133	44	2	2	NUM
ajst-16785	133	45	2	2	NUM
ajst-16785	133	46	)	)	PUNCT
ajst-16785	133	47	,	,	PUNCT
ajst-16785	133	48	4	4	NUM
ajst-16785	133	49	8	8	NUM
ajst-16785	133	50	2	2	NUM
ajst-16785	133	51	(	(	PUNCT
ajst-16785	133	52	2	2	NUM
ajst-16785	133	53	2	2	NUM
ajst-16785	133	54	)	)	PUNCT
ajst-16785	133	55	,	,	PUNCT
ajst-16785	133	56	4	4	NUM
ajst-16785	133	57	8	8	NUM
ajst-16785	133	58	2	2	NUM
ajst-16785	133	59	(	(	PUNCT
ajst-16785	133	60	3	3	NUM
ajst-16785	133	61	3	3	NUM
ajst-16785	133	62	)	)	PUNCT
ajst-16785	133	63	(	(	PUNCT
ajst-16785	133	64	2	2	NUM
ajst-16785	133	65	2	2	NUM
ajst-16785	133	66	)	)	PUNCT
ajst-16785	133	67	,	,	PUNCT
ajst-16785	133	68	4	4	NUM
ajst-16785	133	69	8	8	NUM
ajst-16785	133	70	1	1	NUM
ajst-16785	133	71	(	(	PUNCT
ajst-16785	133	72	3	3	NUM
ajst-16785	133	73	3max	3max	NUM
ajst-16785	133	74	)	)	PUNCT
ajst-16785	133	75	(	(	PUNCT
ajst-16785	133	76	2	2	NUM
ajst-16785	133	77	2	2	NUM
ajst-16785	133	78	)	)	PUNCT
ajst-16785	133	79	,	,	PUNCT
ajst-16785	133	80	4	4	NUM
ajst-16785	133	81	8	8	NUM
ajst-16785	133	82	c	c	NOUN
ajst-16785	133	83	c	c	NOUN
ajst-16785	133	84	c	c	NOUN
ajst-16785	133	85	pool	pool	NOUN
ajst-16785	133	86	c	c	X
ajst-16785	133	87			PROPN
ajst-16785	133	88			PROPN
ajst-16785	133	89			VERB
ajst-16785	133	90			INTJ
ajst-16785	133	91			PROPN
ajst-16785	133	92			PROPN
ajst-16785	133	93			PROPN
ajst-16785	133	94			NOUN
ajst-16785	133	95			NOUN
ajst-16785	133	96			X
ajst-16785	133	97			PROPN
ajst-16785	133	98			NOUN
ajst-16785	133	99			NOUN
ajst-16785	133	100			NOUN
ajst-16785	133	101			NOUN
ajst-16785	133	102			X
ajst-16785	133	103			PROPN
ajst-16785	133	104			PROPN
ajst-16785	133	105			PROPN
ajst-16785	133	106			PROPN
ajst-16785	133	107			PROPN
ajst-16785	133	108			NOUN
ajst-16785	133	109			NOUN
ajst-16785	133	110			NOUN
ajst-16785	133	111			X
ajst-16785	133	112			PROPN
ajst-16785	133	113			PROPN
ajst-16785	133	114			PROPN
ajst-16785	133	115			PROPN
ajst-16785	133	116			PROPN
ajst-16785	133	117	stage4	stage4	PROPN
ajst-16785	133	118	8	8	NUM
ajst-16785	133	119	32	32	NUM
ajst-16785	133	120	32	32	NUM
ajst-16785	133	121	h	h	NOUN
ajst-16785	133	122	w	w	PROPN
ajst-16785	133	123	c	c	PROPN
ajst-16785	133	124			NOUN
ajst-16785	133	125	3	3	NUM
ajst-16785	133	126	(	(	PUNCT
ajst-16785	133	127	1	1	NUM
ajst-16785	133	128	1	1	NUM
ajst-16785	133	129	)	)	PUNCT
ajst-16785	133	130	(	(	PUNCT
ajst-16785	133	131	2	2	NUM
ajst-16785	133	132	2	2	NUM
ajst-16785	133	133	)	)	PUNCT
ajst-16785	133	134	,	,	PUNCT
ajst-16785	133	135	8	8	NUM
ajst-16785	133	136	8	8	NUM
ajst-16785	133	137	2	2	NUM
ajst-16785	133	138	(	(	PUNCT
ajst-16785	133	139	2	2	NUM
ajst-16785	133	140	2	2	NUM
ajst-16785	133	141	)	)	PUNCT
ajst-16785	133	142	,	,	PUNCT
ajst-16785	133	143	8	8	NUM
ajst-16785	133	144	8	8	NUM
ajst-16785	133	145	2	2	NUM
ajst-16785	133	146	(	(	PUNCT
ajst-16785	133	147	3	3	NUM
ajst-16785	133	148	3	3	NUM
ajst-16785	133	149	)	)	PUNCT
ajst-16785	133	150	(	(	PUNCT
ajst-16785	133	151	2	2	NUM
ajst-16785	133	152	2	2	NUM
ajst-16785	133	153	)	)	PUNCT
ajst-16785	133	154	,	,	PUNCT
ajst-16785	133	155	8	8	NUM
ajst-16785	133	156	8	8	NUM
ajst-16785	133	157	1	1	NUM
ajst-16785	133	158	(	(	PUNCT
ajst-16785	133	159	3	3	NUM
ajst-16785	133	160	3max	3max	NUM
ajst-16785	133	161	)	)	PUNCT
ajst-16785	133	162	(	(	PUNCT
ajst-16785	133	163	2	2	NUM
ajst-16785	133	164	2	2	NUM
ajst-16785	133	165	)	)	PUNCT
ajst-16785	133	166	,	,	PUNCT
ajst-16785	133	167	8	8	NUM
ajst-16785	133	168	8	8	NUM
ajst-16785	133	169	c	c	NOUN
ajst-16785	133	170	c	c	NOUN
ajst-16785	133	171	c	c	NOUN
ajst-16785	133	172	pool	pool	NOUN
ajst-16785	133	173	c	c	X
ajst-16785	133	174			PROPN
ajst-16785	133	175			PROPN
ajst-16785	133	176			VERB
ajst-16785	133	177			INTJ
ajst-16785	133	178			PROPN
ajst-16785	133	179			PROPN
ajst-16785	133	180			PROPN
ajst-16785	133	181			NOUN
ajst-16785	133	182			NOUN
ajst-16785	133	183			X
ajst-16785	133	184			PROPN
ajst-16785	133	185			NOUN
ajst-16785	133	186			NOUN
ajst-16785	133	187			NOUN
ajst-16785	133	188			NOUN
ajst-16785	133	189			X
ajst-16785	133	190			PROPN
ajst-16785	133	191			PROPN
ajst-16785	133	192			PROPN
ajst-16785	133	193			PROPN
ajst-16785	133	194			PROPN
ajst-16785	133	195			NOUN
ajst-16785	133	196			NOUN
ajst-16785	133	197			NOUN
ajst-16785	133	198			X
ajst-16785	133	199			PROPN
ajst-16785	133	200			PROPN
ajst-16785	133	201			PROPN
ajst-16785	133	202			PROPN
ajst-16785	133	203			PROPN
ajst-16785	133	204	avg	avg	NOUN
ajst-16785	133	205	pool	pool	NOUN
ajst-16785	133	206	1	1	NUM
ajst-16785	133	207	8c	8c	NUM
ajst-16785	133	208	—	—	PUNCT
ajst-16785	133	209	fc	fc	PROPN
ajst-16785	133	210	number	number	NOUN
ajst-16785	133	211	classes	class	NOUN
ajst-16785	133	212	—	—	PUNCT
ajst-16785	133	213	180	180	NUM
ajst-16785	133	214	3.2	3.2	NUM
ajst-16785	133	215	.	.	PUNCT
ajst-16785	134	1	network	network	NOUN
ajst-16785	134	2	innovation	innovation	NOUN
ajst-16785	134	3	firstly	firstly	ADV
ajst-16785	134	4	,	,	PUNCT
ajst-16785	134	5	the	the	DET
ajst-16785	134	6	proposed	propose	VERB
ajst-16785	134	7	icst	icst	PROPN
ajst-16785	134	8	model	model	NOUN
ajst-16785	134	9	adopts	adopt	VERB
ajst-16785	134	10	a	a	DET
ajst-16785	134	11	multi	multi	ADJ
ajst-16785	134	12	-	-	ADJ
ajst-16785	134	13	scale	scale	ADJ
ajst-16785	134	14	convolutional	convolutional	ADJ
ajst-16785	134	15	kernel	kernel	NOUN
ajst-16785	134	16	approach	approach	NOUN
ajst-16785	134	17	to	to	PART
ajst-16785	134	18	learn	learn	VERB
ajst-16785	134	19	local	local	ADJ
ajst-16785	134	20	features	feature	NOUN
ajst-16785	134	21	of	of	ADP
ajst-16785	134	22	images	image	NOUN
ajst-16785	134	23	,	,	PUNCT
ajst-16785	134	24	which	which	PRON
ajst-16785	134	25	allows	allow	VERB
ajst-16785	134	26	the	the	DET
ajst-16785	134	27	network	network	NOUN
ajst-16785	134	28	to	to	PART
ajst-16785	134	29	autonomously	autonomously	ADV
ajst-16785	134	30	select	select	VERB
ajst-16785	134	31	the	the	DET
ajst-16785	134	32	required	require	VERB
ajst-16785	134	33	kernel	kernel	NOUN
ajst-16785	134	34	size	size	NOUN
ajst-16785	134	35	and	and	CCONJ
ajst-16785	134	36	complete	complete	VERB
ajst-16785	134	37	the	the	DET
ajst-16785	134	38	task	task	NOUN
ajst-16785	134	39	of	of	ADP
ajst-16785	134	40	down	down	ADV
ajst-16785	134	41	-	-	PUNCT
ajst-16785	134	42	sampling	sampling	NOUN
ajst-16785	134	43	during	during	ADP
ajst-16785	134	44	layer	layer	NOUN
ajst-16785	134	45	-	-	PUNCT
ajst-16785	134	46	by	by	ADP
ajst-16785	134	47	-	-	PUNCT
ajst-16785	134	48	layer	layer	NOUN
ajst-16785	134	49	propagation	propagation	NOUN
ajst-16785	134	50	,	,	PUNCT
ajst-16785	134	51	while	while	SCONJ
ajst-16785	134	52	also	also	ADV
ajst-16785	134	53	reducing	reduce	VERB
ajst-16785	134	54	computational	computational	ADJ
ajst-16785	134	55	complexity	complexity	NOUN
ajst-16785	134	56	.	.	PUNCT
ajst-16785	135	1	in	in	ADP
ajst-16785	135	2	addition	addition	NOUN
ajst-16785	135	3	,	,	PUNCT
ajst-16785	135	4	to	to	PART
ajst-16785	135	5	improve	improve	VERB
ajst-16785	135	6	recognition	recognition	NOUN
ajst-16785	135	7	accuracy	accuracy	NOUN
ajst-16785	135	8	for	for	ADP
ajst-16785	135	9	time	time	NOUN
ajst-16785	135	10	series	series	PROPN
ajst-16785	135	11	signal	signal	PROPN
ajst-16785	135	12	recognition	recognition	PROPN
ajst-16785	135	13	,	,	PUNCT
ajst-16785	135	14	the	the	DET
ajst-16785	135	15	swin	swin	PROPN
ajst-16785	135	16	transformer	transformer	PROPN
ajst-16785	135	17	block	block	NOUN
ajst-16785	135	18	is	be	AUX
ajst-16785	135	19	introduced	introduce	VERB
ajst-16785	135	20	to	to	PART
ajst-16785	135	21	establish	establish	VERB
ajst-16785	135	22	global	global	ADJ
ajst-16785	135	23	feature	feature	NOUN
ajst-16785	135	24	relationships	relationship	NOUN
ajst-16785	135	25	and	and	CCONJ
ajst-16785	135	26	expand	expand	VERB
ajst-16785	135	27	the	the	DET
ajst-16785	135	28	image	image	NOUN
ajst-16785	135	29	perception	perception	NOUN
ajst-16785	135	30	field	field	NOUN
ajst-16785	135	31	.	.	PUNCT
ajst-16785	136	1	finally	finally	ADV
ajst-16785	136	2	,	,	PUNCT
ajst-16785	136	3	to	to	PART
ajst-16785	136	4	address	address	VERB
ajst-16785	136	5	the	the	DET
ajst-16785	136	6	redundant	redundant	ADJ
ajst-16785	136	7	feature	feature	NOUN
ajst-16785	136	8	layers	layer	NOUN
ajst-16785	136	9	introduced	introduce	VERB
ajst-16785	136	10	by	by	ADP
ajst-16785	136	11	the	the	DET
ajst-16785	136	12	inception	inception	NOUN
ajst-16785	136	13	module	module	NOUN
ajst-16785	136	14	,	,	PUNCT
ajst-16785	136	15	the	the	DET
ajst-16785	136	16	coordattention	coordattention	NOUN
ajst-16785	136	17	module	module	NOUN
ajst-16785	136	18	is	be	AUX
ajst-16785	136	19	used	use	VERB
ajst-16785	136	20	to	to	PART
ajst-16785	136	21	highlight	highlight	VERB
ajst-16785	136	22	important	important	ADJ
ajst-16785	136	23	feature	feature	NOUN
ajst-16785	136	24	channels	channel	NOUN
ajst-16785	136	25	while	while	SCONJ
ajst-16785	136	26	retaining	retain	VERB
ajst-16785	136	27	precise	precise	ADJ
ajst-16785	136	28	location	location	NOUN
ajst-16785	136	29	information	information	NOUN
ajst-16785	136	30	to	to	PART
ajst-16785	136	31	preserve	preserve	VERB
ajst-16785	136	32	the	the	DET
ajst-16785	136	33	temporal	temporal	ADJ
ajst-16785	136	34	order	order	NOUN
ajst-16785	136	35	of	of	ADP
ajst-16785	136	36	time	time	NOUN
ajst-16785	136	37	series	series	PROPN
ajst-16785	136	38	defect	defect	VERB
ajst-16785	136	39	sample	sample	NOUN
ajst-16785	136	40	information	information	NOUN
ajst-16785	136	41	.	.	PUNCT
ajst-16785	137	1	these	these	DET
ajst-16785	137	2	design	design	NOUN
ajst-16785	137	3	choices	choice	NOUN
ajst-16785	137	4	enable	enable	VERB
ajst-16785	137	5	the	the	DET
ajst-16785	137	6	model	model	NOUN
ajst-16785	137	7	to	to	PART
ajst-16785	137	8	incorporate	incorporate	VERB
ajst-16785	137	9	a	a	DET
ajst-16785	137	10	priori	priori	ADJ
ajst-16785	137	11	knowledge	knowledge	NOUN
ajst-16785	137	12	of	of	ADP
ajst-16785	137	13	feature	feature	NOUN
ajst-16785	137	14	scale	scale	NOUN
ajst-16785	137	15	,	,	PUNCT
ajst-16785	137	16	translation	translation	NOUN
ajst-16785	137	17	invariance	invariance	NOUN
ajst-16785	137	18	,	,	PUNCT
ajst-16785	137	19	and	and	CCONJ
ajst-16785	137	20	feature	feature	NOUN
ajst-16785	137	21	localization	localization	NOUN
ajst-16785	137	22	,	,	PUNCT
ajst-16785	137	23	and	and	CCONJ
ajst-16785	137	24	reduce	reduce	VERB
ajst-16785	137	25	the	the	DET
ajst-16785	137	26	training	training	NOUN
ajst-16785	137	27	difficulty	difficulty	NOUN
ajst-16785	137	28	and	and	CCONJ
ajst-16785	137	29	overfitting	overfitting	NOUN
ajst-16785	137	30	caused	cause	VERB
ajst-16785	137	31	by	by	ADP
ajst-16785	137	32	a	a	DET
ajst-16785	137	33	large	large	ADJ
ajst-16785	137	34	number	number	NOUN
ajst-16785	137	35	of	of	ADP
ajst-16785	137	36	global	global	ADJ
ajst-16785	137	37	information	information	NOUN
ajst-16785	137	38	parameters	parameter	NOUN
ajst-16785	137	39	,	,	PUNCT
ajst-16785	137	40	resulting	result	VERB
ajst-16785	137	41	in	in	ADP
ajst-16785	137	42	improved	improved	ADJ
ajst-16785	137	43	model	model	NOUN
ajst-16785	137	44	performance	performance	NOUN
ajst-16785	137	45	.	.	PUNCT
ajst-16785	138	1	4	4	X
ajst-16785	138	2	.	.	X
ajst-16785	138	3	datasets	dataset	NOUN
ajst-16785	138	4	description	description	NOUN
ajst-16785	138	5	and	and	CCONJ
ajst-16785	138	6	experimental	experimental	ADJ
ajst-16785	138	7	configuration	configuration	NOUN
ajst-16785	138	8	4.1	4.1	NUM
ajst-16785	138	9	.	.	PUNCT
ajst-16785	139	1	experimental	experimental	ADJ
ajst-16785	139	2	dataset	dataset	NOUN
ajst-16785	139	3	in	in	ADP
ajst-16785	139	4	order	order	NOUN
ajst-16785	139	5	to	to	PART
ajst-16785	139	6	verify	verify	VERB
ajst-16785	139	7	the	the	DET
ajst-16785	139	8	effectiveness	effectiveness	NOUN
ajst-16785	139	9	of	of	ADP
ajst-16785	139	10	icst	icst	NOUN
ajst-16785	139	11	for	for	ADP
ajst-16785	139	12	the	the	DET
ajst-16785	139	13	recognition	recognition	NOUN
ajst-16785	139	14	of	of	ADP
ajst-16785	139	15	metal	metal	NOUN
ajst-16785	139	16	defect	defect	NOUN
ajst-16785	139	17	ultrasonic	ultrasonic	ADJ
ajst-16785	139	18	signal	signal	NOUN
ajst-16785	139	19	grayscale	grayscale	NOUN
ajst-16785	139	20	images	image	NOUN
ajst-16785	139	21	,	,	PUNCT
ajst-16785	139	22	a	a	DET
ajst-16785	139	23	self	self	NOUN
ajst-16785	139	24	-	-	PUNCT
ajst-16785	139	25	built	build	VERB
ajst-16785	139	26	ultrasonic	ultrasonic	ADJ
ajst-16785	139	27	detection	detection	NOUN
ajst-16785	139	28	defect	defect	NOUN
ajst-16785	139	29	dataset	dataset	NOUN
ajst-16785	139	30	(	(	PUNCT
ajst-16785	139	31	ulfsl	ulfsl	NOUN
ajst-16785	139	32	-	-	PUNCT
ajst-16785	139	33	det	det	NOUN
ajst-16785	139	34	)	)	PUNCT
ajst-16785	139	35	was	be	AUX
ajst-16785	139	36	constructed	construct	VERB
ajst-16785	139	37	.	.	PUNCT
ajst-16785	140	1	at	at	ADP
ajst-16785	140	2	the	the	DET
ajst-16785	140	3	same	same	ADJ
ajst-16785	140	4	time	time	NOUN
ajst-16785	140	5	,	,	PUNCT
ajst-16785	140	6	the	the	DET
ajst-16785	140	7	public	public	ADJ
ajst-16785	140	8	defect	defect	NOUN
ajst-16785	140	9	dataset	dataset	NOUN
ajst-16785	140	10	(	(	PUNCT
ajst-16785	140	11	neu	neu	NOUN
ajst-16785	140	12	-	-	PUNCT
ajst-16785	140	13	cls	cls	NOUN
ajst-16785	140	14	)	)	PUNCT
ajst-16785	140	15	on	on	ADP
ajst-16785	140	16	steel	steel	NOUN
ajst-16785	140	17	surface	surface	NOUN
ajst-16785	140	18	was	be	AUX
ajst-16785	140	19	applied	apply	VERB
ajst-16785	140	20	to	to	PART
ajst-16785	140	21	verify	verify	VERB
ajst-16785	140	22	the	the	DET
ajst-16785	140	23	generality	generality	NOUN
ajst-16785	140	24	of	of	ADP
ajst-16785	140	25	the	the	DET
ajst-16785	140	26	recognition	recognition	NOUN
ajst-16785	140	27	of	of	ADP
ajst-16785	140	28	metal	metal	NOUN
ajst-16785	140	29	defects	defect	NOUN
ajst-16785	140	30	.	.	PUNCT
ajst-16785	141	1	ulfsl	ulfsl	NOUN
ajst-16785	141	2	-	-	PUNCT
ajst-16785	141	3	det	det	NOUN
ajst-16785	141	4	contains	contain	VERB
ajst-16785	141	5	2	2	NUM
ajst-16785	141	6	mm	mm	NOUN
ajst-16785	141	7	,	,	PUNCT
ajst-16785	141	8	5	5	NUM
ajst-16785	141	9	mm	mm	NOUN
ajst-16785	141	10	,	,	PUNCT
ajst-16785	141	11	8	8	NUM
ajst-16785	141	12	mm	mm	NOUN
ajst-16785	141	13	of	of	ADP
ajst-16785	141	14	rectangular	rectangular	ADJ
ajst-16785	141	15	,	,	PUNCT
ajst-16785	141	16	circular	circular	ADJ
ajst-16785	141	17	,	,	PUNCT
ajst-16785	141	18	elliptical	elliptical	ADJ
ajst-16785	141	19	and	and	CCONJ
ajst-16785	141	20	irregular	irregular	ADJ
ajst-16785	141	21	shape	shape	NOUN
ajst-16785	141	22	artificial	artificial	ADJ
ajst-16785	141	23	steel	steel	NOUN
ajst-16785	141	24	plate	plate	NOUN
ajst-16785	141	25	ultrasonic	ultrasonic	ADJ
ajst-16785	141	26	echo	echo	NOUN
ajst-16785	141	27	surface	surface	NOUN
ajst-16785	141	28	defect	defect	NOUN
ajst-16785	141	29	signals	signal	NOUN
ajst-16785	141	30	.	.	PUNCT
ajst-16785	142	1	there	there	PRON
ajst-16785	142	2	are	be	VERB
ajst-16785	142	3	200	200	NUM
ajst-16785	142	4	samples	sample	NOUN
ajst-16785	142	5	in	in	ADP
ajst-16785	142	6	each	each	DET
ajst-16785	142	7	type	type	NOUN
ajst-16785	142	8	,	,	PUNCT
ajst-16785	142	9	forming	form	VERB
ajst-16785	142	10	a	a	DET
ajst-16785	142	11	total	total	NOUN
ajst-16785	142	12	of	of	ADP
ajst-16785	142	13	600	600	NUM
ajst-16785	142	14	-	-	PUNCT
ajst-16785	142	15	sample	sample	NOUN
ajst-16785	142	16	dataset	dataset	NOUN
ajst-16785	142	17	.	.	PUNCT
ajst-16785	143	1	in	in	ADP
ajst-16785	143	2	the	the	DET
ajst-16785	143	3	ultrasonic	ultrasonic	ADJ
ajst-16785	143	4	detection	detection	NOUN
ajst-16785	143	5	experiment	experiment	NOUN
ajst-16785	143	6	,	,	PUNCT
ajst-16785	143	7	a	a	DET
ajst-16785	143	8	self	self	NOUN
ajst-16785	143	9	-	-	PUNCT
ajst-16785	143	10	receiving	receive	VERB
ajst-16785	143	11	straight	straight	ADJ
ajst-16785	143	12	probe	probe	NOUN
ajst-16785	143	13	with	with	ADP
ajst-16785	143	14	a	a	DET
ajst-16785	143	15	center	center	ADJ
ajst-16785	143	16	frequency	frequency	NOUN
ajst-16785	143	17	of	of	ADP
ajst-16785	143	18	2.5mhz	2.5mhz	NUM
ajst-16785	143	19	and	and	CCONJ
ajst-16785	143	20	20	20	NUM
ajst-16785	143	21	mm	mm	PROPN
ajst-16785	143	22	diameter	diameter	NOUN
ajst-16785	143	23	was	be	AUX
ajst-16785	143	24	employed	employ	VERB
ajst-16785	143	25	.	.	PUNCT
ajst-16785	144	1	the	the	DET
ajst-16785	144	2	experiment	experiment	NOUN
ajst-16785	144	3	was	be	AUX
ajst-16785	144	4	conducted	conduct	VERB
ajst-16785	144	5	using	use	VERB
ajst-16785	144	6	a	a	DET
ajst-16785	144	7	digital	digital	ADJ
ajst-16785	144	8	ultrasonic	ultrasonic	ADJ
ajst-16785	144	9	flaw	flaw	NOUN
ajst-16785	144	10	detector	detector	NOUN
ajst-16785	144	11	to	to	PART
ajst-16785	144	12	collect	collect	VERB
ajst-16785	144	13	the	the	DET
ajst-16785	144	14	echo	echo	NOUN
ajst-16785	144	15	signals	signal	NOUN
ajst-16785	144	16	reflected	reflect	VERB
ajst-16785	144	17	by	by	ADP
ajst-16785	144	18	the	the	DET
ajst-16785	144	19	defects	defect	NOUN
ajst-16785	144	20	.	.	PUNCT
ajst-16785	145	1	three	three	NUM
ajst-16785	145	2	artificial	artificial	ADJ
ajst-16785	145	3	defect	defect	NOUN
ajst-16785	145	4	plates	plate	NOUN
ajst-16785	145	5	were	be	AUX
ajst-16785	145	6	coated	coat	VERB
ajst-16785	145	7	with	with	ADP
ajst-16785	145	8	ultrasonic	ultrasonic	ADJ
ajst-16785	145	9	coupling	coupling	NOUN
ajst-16785	145	10	agent	agent	NOUN
ajst-16785	145	11	,	,	PUNCT
ajst-16785	145	12	and	and	CCONJ
ajst-16785	145	13	the	the	DET
ajst-16785	145	14	probe	probe	NOUN
ajst-16785	145	15	was	be	AUX
ajst-16785	145	16	moved	move	VERB
ajst-16785	145	17	on	on	ADP
ajst-16785	145	18	them	they	PRON
ajst-16785	145	19	to	to	PART
ajst-16785	145	20	locate	locate	VERB
ajst-16785	145	21	the	the	DET
ajst-16785	145	22	signal	signal	NOUN
ajst-16785	145	23	with	with	ADP
ajst-16785	145	24	the	the	DET
ajst-16785	145	25	largest	large	ADJ
ajst-16785	145	26	echo	echo	NOUN
ajst-16785	145	27	peak	peak	NOUN
ajst-16785	145	28	,	,	PUNCT
ajst-16785	145	29	which	which	PRON
ajst-16785	145	30	was	be	AUX
ajst-16785	145	31	observed	observe	VERB
ajst-16785	145	32	on	on	ADP
ajst-16785	145	33	the	the	DET
ajst-16785	145	34	oscilloscope	oscilloscope	NOUN
ajst-16785	145	35	.	.	PUNCT
ajst-16785	146	1	subsequently	subsequently	ADV
ajst-16785	146	2	,	,	PUNCT
ajst-16785	146	3	the	the	DET
ajst-16785	146	4	echo	echo	NOUN
ajst-16785	146	5	signal	signal	PROPN
ajst-16785	146	6	data	datum	NOUN
ajst-16785	146	7	was	be	AUX
ajst-16785	146	8	saved	save	VERB
ajst-16785	146	9	in	in	ADP
ajst-16785	146	10	the	the	DET
ajst-16785	146	11	ultrasonic	ultrasonic	ADJ
ajst-16785	146	12	detector	detector	NOUN
ajst-16785	146	13	as	as	ADP
ajst-16785	146	14	a	a	DET
ajst-16785	146	15	csv	csv	NOUN
ajst-16785	146	16	file	file	NOUN
ajst-16785	146	17	.	.	PUNCT
ajst-16785	147	1	the	the	DET
ajst-16785	147	2	experimental	experimental	ADJ
ajst-16785	147	3	platform	platform	NOUN
ajst-16785	147	4	and	and	CCONJ
ajst-16785	147	5	defective	defective	ADJ
ajst-16785	147	6	samples	sample	NOUN
ajst-16785	147	7	are	be	AUX
ajst-16785	147	8	illustrated	illustrate	VERB
ajst-16785	147	9	in	in	ADP
ajst-16785	147	10	figure	figure	NOUN
ajst-16785	147	11	3(a	3(a	NUM
ajst-16785	147	12	)	)	PUNCT
ajst-16785	147	13	.	.	PUNCT
ajst-16785	148	1	to	to	PART
ajst-16785	148	2	improve	improve	VERB
ajst-16785	148	3	the	the	DET
ajst-16785	148	4	accuracy	accuracy	NOUN
ajst-16785	148	5	of	of	ADP
ajst-16785	148	6	signal	signal	ADJ
ajst-16785	148	7	recognition	recognition	NOUN
ajst-16785	148	8	,	,	PUNCT
ajst-16785	148	9	preprocessing	preprocessing	NOUN
ajst-16785	148	10	of	of	ADP
ajst-16785	148	11	the	the	DET
ajst-16785	148	12	echo	echo	NOUN
ajst-16785	148	13	signal	signal	NOUN
ajst-16785	148	14	obtained	obtain	VERB
ajst-16785	148	15	from	from	ADP
ajst-16785	148	16	the	the	DET
ajst-16785	148	17	ultrasonic	ultrasonic	ADJ
ajst-16785	148	18	experiment	experiment	NOUN
ajst-16785	148	19	is	be	AUX
ajst-16785	148	20	required	require	VERB
ajst-16785	148	21	due	due	ADP
ajst-16785	148	22	to	to	ADP
ajst-16785	148	23	the	the	DET
ajst-16785	148	24	presence	presence	NOUN
ajst-16785	148	25	of	of	ADP
ajst-16785	148	26	noise	noise	NOUN
ajst-16785	148	27	and	and	CCONJ
ajst-16785	148	28	redundant	redundant	ADJ
ajst-16785	148	29	information	information	NOUN
ajst-16785	148	30	.	.	PUNCT
ajst-16785	149	1	in	in	ADP
ajst-16785	149	2	this	this	DET
ajst-16785	149	3	paper	paper	NOUN
ajst-16785	149	4	,	,	PUNCT
ajst-16785	149	5	the	the	DET
ajst-16785	149	6	pre	pre	ADJ
ajst-16785	149	7	-	-	ADJ
ajst-16785	149	8	processing	processing	ADJ
ajst-16785	149	9	processes	process	NOUN
ajst-16785	149	10	are	be	AUX
ajst-16785	149	11	as	as	SCONJ
ajst-16785	149	12	follows	follow	VERB
ajst-16785	149	13	.	.	PUNCT
ajst-16785	150	1	firstly	firstly	ADV
ajst-16785	150	2	,	,	PUNCT
ajst-16785	150	3	wavelet	wavelet	NOUN
ajst-16785	150	4	packet	packet	NOUN
ajst-16785	150	5	decomposition	decomposition	NOUN
ajst-16785	150	6	is	be	AUX
ajst-16785	150	7	applied	apply	VERB
ajst-16785	150	8	to	to	PART
ajst-16785	150	9	decompose	decompose	VERB
ajst-16785	150	10	the	the	DET
ajst-16785	150	11	signal	signal	NOUN
ajst-16785	150	12	with	with	ADP
ajst-16785	150	13	coif2	coif2	NOUN
ajst-16785	150	14	as	as	ADP
ajst-16785	150	15	the	the	DET
ajst-16785	150	16	decomposition	decomposition	NOUN
ajst-16785	150	17	wavelet	wavelet	NOUN
ajst-16785	150	18	basis	basis	NOUN
ajst-16785	150	19	function	function	NOUN
ajst-16785	150	20	.	.	PUNCT
ajst-16785	151	1	the	the	DET
ajst-16785	151	2	resulting	result	VERB
ajst-16785	151	3	decomposed	decompose	VERB
ajst-16785	151	4	signal	signal	NOUN
ajst-16785	151	5	is	be	AUX
ajst-16785	151	6	then	then	ADV
ajst-16785	151	7	denoised	denoise	VERB
ajst-16785	151	8	using	use	VERB
ajst-16785	151	9	the	the	DET
ajst-16785	151	10	soft	soft	ADJ
ajst-16785	151	11	threshold	threshold	NOUN
ajst-16785	151	12	criterion	criterion	NOUN
ajst-16785	151	13	.	.	PUNCT
ajst-16785	152	1	secondly	secondly	ADV
ajst-16785	152	2	,	,	PUNCT
ajst-16785	152	3	to	to	PART
ajst-16785	152	4	meet	meet	VERB
ajst-16785	152	5	the	the	DET
ajst-16785	152	6	input	input	NOUN
ajst-16785	152	7	requirements	requirement	NOUN
ajst-16785	152	8	of	of	ADP
ajst-16785	152	9	icst	icst	NOUN
ajst-16785	152	10	,	,	PUNCT
ajst-16785	152	11	the	the	DET
ajst-16785	152	12	filtered	filter	VERB
ajst-16785	152	13	ultrasonic	ultrasonic	ADJ
ajst-16785	152	14	defect	defect	NOUN
ajst-16785	152	15	detection	detection	NOUN
ajst-16785	152	16	signal	signal	NOUN
ajst-16785	152	17	needs	need	VERB
ajst-16785	152	18	to	to	PART
ajst-16785	152	19	be	be	AUX
ajst-16785	152	20	converted	convert	VERB
ajst-16785	152	21	into	into	ADP
ajst-16785	152	22	a	a	DET
ajst-16785	152	23	two	two	NUM
ajst-16785	152	24	-	-	PUNCT
ajst-16785	152	25	dimensional	dimensional	ADJ
ajst-16785	152	26	grayscale	grayscale	NOUN
ajst-16785	152	27	image	image	NOUN
ajst-16785	152	28	of	of	ADP
ajst-16785	152	29	128x128	128x128	NUM
ajst-16785	152	30	pixels	pixel	NOUN
ajst-16785	152	31	.	.	PUNCT
ajst-16785	153	1	the	the	DET
ajst-16785	153	2	conversion	conversion	NOUN
ajst-16785	153	3	is	be	AUX
ajst-16785	153	4	processed	process	VERB
ajst-16785	153	5	by	by	ADP
ajst-16785	153	6	normalizing	normalize	VERB
ajst-16785	153	7	the	the	DET
ajst-16785	153	8	voltage	voltage	NOUN
ajst-16785	153	9	value	value	NOUN
ajst-16785	153	10	of	of	ADP
ajst-16785	153	11	the	the	DET
ajst-16785	153	12	ultrasonic	ultrasonic	ADJ
ajst-16785	153	13	echo	echo	NOUN
ajst-16785	153	14	signal	signal	NOUN
ajst-16785	153	15	.	.	PUNCT
ajst-16785	154	1	the	the	DET
ajst-16785	154	2	normalized	normalize	VERB
ajst-16785	154	3	formula	formula	NOUN
ajst-16785	154	4	is	be	AUX
ajst-16785	154	5	as	as	SCONJ
ajst-16785	154	6	follows	follow	VERB
ajst-16785	154	7	.	.	PUNCT
ajst-16785	155	1	due	due	ADP
ajst-16785	155	2	to	to	ADP
ajst-16785	155	3	the	the	DET
ajst-16785	155	4	different	different	ADJ
ajst-16785	155	5	peaks	peak	NOUN
ajst-16785	155	6	of	of	ADP
ajst-16785	155	7	the	the	DET
ajst-16785	155	8	three	three	NUM
ajst-16785	155	9	depth	depth	NOUN
ajst-16785	155	10	defect	defect	NOUN
ajst-16785	155	11	echo	echo	NOUN
ajst-16785	155	12	signals	signal	NOUN
ajst-16785	155	13	,	,	PUNCT
ajst-16785	155	14	maxx	maxx	PROPN
ajst-16785	155	15	and	and	CCONJ
ajst-16785	155	16	minx	minx	NOUN
ajst-16785	155	17	are	be	AUX
ajst-16785	155	18	taken	take	VERB
ajst-16785	155	19	as	as	ADP
ajst-16785	155	20	fixed	fix	VERB
ajst-16785	155	21	values	value	NOUN
ajst-16785	155	22	13	13	NUM
ajst-16785	155	23	and	and	CCONJ
ajst-16785	155	24	-2	-2	INTJ
ajst-16785	155	25	.	.	PUNCT
ajst-16785	156	1	*	*	PUNCT
ajst-16785	156	2	min	min	PROPN
ajst-16785	156	3	max	max	PROPN
ajst-16785	156	4	min	min	PROPN
ajst-16785	156	5	x	x	PUNCT
ajst-16785	156	6	x	x	PUNCT
ajst-16785	156	7	x	x	PUNCT
ajst-16785	156	8	x	x	PUNCT
ajst-16785	156	9	x	x	SYM
ajst-16785	156	10			PROPN
ajst-16785	156	11			NUM
ajst-16785	156	12			NOUN
ajst-16785	156	13	(	(	PUNCT
ajst-16785	156	14	9	9	NUM
ajst-16785	156	15	)	)	PUNCT
ajst-16785	156	16	finally	finally	ADV
ajst-16785	156	17	,	,	PUNCT
ajst-16785	156	18	after	after	SCONJ
ajst-16785	156	19	the	the	DET
ajst-16785	156	20	voltage	voltage	NOUN
ajst-16785	156	21	value	value	NOUN
ajst-16785	156	22	is	be	AUX
ajst-16785	156	23	multiplied	multiply	VERB
ajst-16785	156	24	by	by	ADP
ajst-16785	156	25	255	255	NUM
ajst-16785	156	26	,	,	PUNCT
ajst-16785	156	27	we	we	PRON
ajst-16785	156	28	convert	convert	VERB
ajst-16785	156	29	it	it	PRON
ajst-16785	156	30	into	into	ADP
ajst-16785	156	31	a	a	DET
ajst-16785	156	32	matrix	matrix	NOUN
ajst-16785	156	33	with	with	ADP
ajst-16785	156	34	a	a	DET
ajst-16785	156	35	width	width	NOUN
ajst-16785	156	36	of	of	ADP
ajst-16785	156	37	128	128	NUM
ajst-16785	156	38	.	.	PUNCT
ajst-16785	157	1	part	part	NOUN
ajst-16785	157	2	of	of	ADP
ajst-16785	157	3	the	the	DET
ajst-16785	157	4	experimental	experimental	ADJ
ajst-16785	157	5	echo	echo	NOUN
ajst-16785	157	6	signal	signal	NOUN
ajst-16785	157	7	and	and	CCONJ
ajst-16785	157	8	the	the	DET
ajst-16785	157	9	pre	pre	ADJ
ajst-16785	157	10	-	-	ADJ
ajst-16785	157	11	processing	processing	ADJ
ajst-16785	157	12	process	process	NOUN
ajst-16785	157	13	are	be	AUX
ajst-16785	157	14	shown	show	VERB
ajst-16785	157	15	in	in	ADP
ajst-16785	157	16	figure	figure	NOUN
ajst-16785	157	17	3(b	3(b	NUM
ajst-16785	157	18	)	)	PUNCT
ajst-16785	157	19	.	.	PUNCT
ajst-16785	158	1	the	the	DET
ajst-16785	158	2	neu	neu	PROPN
ajst-16785	158	3	-	-	PUNCT
ajst-16785	158	4	cls	cls	PROPN
ajst-16785	158	5	dataset[22	dataset[22	NOUN
ajst-16785	158	6	]	]	X
ajst-16785	158	7	,	,	PUNCT
ajst-16785	158	8	developed	develop	VERB
ajst-16785	158	9	by	by	ADP
ajst-16785	158	10	northeastern	northeastern	ADJ
ajst-16785	158	11	university	university	NOUN
ajst-16785	158	12	,	,	PUNCT
ajst-16785	158	13	comprises	comprise	NOUN
ajst-16785	158	14	of	of	ADP
ajst-16785	158	15	1800	1800	NUM
ajst-16785	158	16	images	image	NOUN
ajst-16785	158	17	of	of	ADP
ajst-16785	158	18	typical	typical	ADJ
ajst-16785	158	19	surface	surface	NOUN
ajst-16785	158	20	defects	defect	NOUN
ajst-16785	158	21	on	on	ADP
ajst-16785	158	22	hot	hot	ADJ
ajst-16785	158	23	rolled	roll	VERB
ajst-16785	158	24	steel	steel	NOUN
ajst-16785	158	25	strips	strip	NOUN
ajst-16785	158	26	,	,	PUNCT
ajst-16785	158	27	with	with	ADP
ajst-16785	158	28	300	300	NUM
ajst-16785	158	29	images	image	NOUN
ajst-16785	158	30	for	for	ADP
ajst-16785	158	31	each	each	PRON
ajst-16785	158	32	of	of	ADP
ajst-16785	158	33	the	the	DET
ajst-16785	158	34	six	six	NUM
ajst-16785	158	35	defect	defect	ADJ
ajst-16785	158	36	types	type	NOUN
ajst-16785	158	37	:	:	PUNCT
ajst-16785	158	38	cracking	crack	VERB
ajst-16785	158	39	(	(	PUNCT
ajst-16785	158	40	cr	cr	NOUN
ajst-16785	158	41	)	)	PUNCT
ajst-16785	158	42	,	,	PUNCT
ajst-16785	158	43	inclusions	inclusion	NOUN
ajst-16785	158	44	(	(	PUNCT
ajst-16785	158	45	in	in	ADP
ajst-16785	158	46	)	)	PUNCT
ajst-16785	158	47	,	,	PUNCT
ajst-16785	158	48	plaque	plaque	NOUN
ajst-16785	158	49	(	(	PUNCT
ajst-16785	158	50	pa	pa	PROPN
ajst-16785	158	51	)	)	PUNCT
ajst-16785	158	52	,	,	PUNCT
ajst-16785	158	53	pitting	pitting	NOUN
ajst-16785	158	54	(	(	PUNCT
ajst-16785	158	55	ps	ps	NOUN
ajst-16785	158	56	)	)	PUNCT
ajst-16785	158	57	,	,	PUNCT
ajst-16785	158	58	oxide	oxide	NOUN
ajst-16785	158	59	(	(	PUNCT
ajst-16785	158	60	rs	rs	NOUN
ajst-16785	158	61	)	)	PUNCT
ajst-16785	158	62	,	,	PUNCT
ajst-16785	158	63	and	and	CCONJ
ajst-16785	158	64	scratches	scratch	NOUN
ajst-16785	158	65	(	(	PUNCT
ajst-16785	158	66	sc	sc	PROPN
ajst-16785	158	67	)	)	PUNCT
ajst-16785	158	68	.	.	PUNCT
ajst-16785	159	1	sample	sample	NOUN
ajst-16785	159	2	images	image	NOUN
ajst-16785	159	3	of	of	ADP
ajst-16785	159	4	these	these	DET
ajst-16785	159	5	defects	defect	NOUN
ajst-16785	159	6	are	be	AUX
ajst-16785	159	7	shown	show	VERB
ajst-16785	159	8	in	in	ADP
ajst-16785	159	9	figure	figure	NOUN
ajst-16785	159	10	3(c	3(c	NUM
ajst-16785	159	11	)	)	PUNCT
ajst-16785	159	12	.	.	PUNCT
ajst-16785	160	1	4.2	4.2	NUM
ajst-16785	160	2	.	.	PUNCT
ajst-16785	161	1	experimental	experimental	ADJ
ajst-16785	161	2	data	datum	NOUN
ajst-16785	161	3	configuration	configuration	NOUN
ajst-16785	161	4	and	and	CCONJ
ajst-16785	161	5	parameter	parameter	NOUN
ajst-16785	161	6	settings	setting	NOUN
ajst-16785	161	7	in	in	ADP
ajst-16785	161	8	this	this	DET
ajst-16785	161	9	paper	paper	NOUN
ajst-16785	161	10	,	,	PUNCT
ajst-16785	161	11	the	the	DET
ajst-16785	161	12	experimental	experimental	ADJ
ajst-16785	161	13	platform	platform	NOUN
ajst-16785	161	14	is	be	AUX
ajst-16785	161	15	pycharm	pycharm	NOUN
ajst-16785	161	16	.	.	PUNCT
ajst-16785	162	1	the	the	DET
ajst-16785	162	2	experimental	experimental	ADJ
ajst-16785	162	3	code	code	NOUN
ajst-16785	162	4	is	be	AUX
ajst-16785	162	5	developed	develop	VERB
ajst-16785	162	6	and	and	CCONJ
ajst-16785	162	7	implemented	implement	VERB
ajst-16785	162	8	based	base	VERB
ajst-16785	162	9	on	on	ADP
ajst-16785	162	10	the	the	DET
ajst-16785	162	11	deep	deep	ADJ
ajst-16785	162	12	learning	learning	NOUN
ajst-16785	162	13	framework	framework	NOUN
ajst-16785	162	14	pytorch	pytorch	NOUN
ajst-16785	162	15	.	.	PUNCT
ajst-16785	163	1	the	the	DET
ajst-16785	163	2	hardware	hardware	NOUN
ajst-16785	163	3	devices	device	NOUN
ajst-16785	163	4	are	be	AUX
ajst-16785	163	5	amd	amd	PROPN
ajst-16785	163	6	epyc	epyc	NOUN
ajst-16785	163	7	7r13	7r13	PROPN
ajst-16785	163	8	48	48	NUM
ajst-16785	163	9	-	-	PUNCT
ajst-16785	163	10	core	core	NOUN
ajst-16785	163	11	cpu@2.65ghz	cpu@2.65ghz	NOUN
ajst-16785	163	12	,	,	PUNCT
ajst-16785	163	13	nvidia	nvidia	PROPN
ajst-16785	163	14	geforce	geforce	NOUN
ajst-16785	163	15	rtx	rtx	PROPN
ajst-16785	163	16	3060	3060	NUM
ajst-16785	163	17	(	(	PUNCT
ajst-16785	163	18	12	12	NUM
ajst-16785	163	19	gb	gb	NOUN
ajst-16785	163	20	)	)	PUNCT
ajst-16785	163	21	gpu	gpu	PROPN
ajst-16785	163	22	.	.	PROPN
ajst-16785	164	1	as	as	SCONJ
ajst-16785	164	2	the	the	DET
ajst-16785	164	3	two	two	NUM
ajst-16785	164	4	datasets	dataset	NOUN
ajst-16785	164	5	contain	contain	VERB
ajst-16785	164	6	limited	limited	ADJ
ajst-16785	164	7	data	datum	NOUN
ajst-16785	164	8	,	,	PUNCT
ajst-16785	164	9	the	the	DET
ajst-16785	164	10	crossvalidation	crossvalidation	NOUN
ajst-16785	164	11	method	method	NOUN
ajst-16785	164	12	is	be	AUX
ajst-16785	164	13	employed	employ	VERB
ajst-16785	164	14	in	in	ADP
ajst-16785	164	15	five	five	NUM
ajst-16785	164	16	independent	independent	ADJ
ajst-16785	164	17	experiments	experiment	NOUN
ajst-16785	164	18	to	to	PART
ajst-16785	164	19	obtain	obtain	VERB
ajst-16785	164	20	more	more	ADJ
ajst-16785	164	21	training	training	NOUN
ajst-16785	164	22	samples	sample	NOUN
ajst-16785	164	23	.	.	PUNCT
ajst-16785	165	1	the	the	DET
ajst-16785	165	2	final	final	ADJ
ajst-16785	165	3	experimental	experimental	ADJ
ajst-16785	165	4	results	result	NOUN
ajst-16785	165	5	are	be	AUX
ajst-16785	165	6	averaged	average	VERB
ajst-16785	165	7	across	across	ADP
ajst-16785	165	8	these	these	DET
ajst-16785	165	9	five	five	NUM
ajst-16785	165	10	experiments	experiment	NOUN
ajst-16785	165	11	.	.	PUNCT
ajst-16785	166	1	in	in	ADP
ajst-16785	166	2	the	the	DET
ajst-16785	166	3	ulfsl	ulfsl	NOUN
ajst-16785	166	4	-	-	PUNCT
ajst-16785	166	5	det	det	NOUN
ajst-16785	166	6	dataset	dataset	NOUN
ajst-16785	166	7	,	,	PUNCT
ajst-16785	166	8	80	80	NUM
ajst-16785	166	9	%	%	NOUN
ajst-16785	166	10	of	of	ADP
ajst-16785	166	11	the	the	DET
ajst-16785	166	12	total	total	ADJ
ajst-16785	166	13	samples	sample	NOUN
ajst-16785	166	14	are	be	AUX
ajst-16785	166	15	used	use	VERB
ajst-16785	166	16	as	as	ADP
ajst-16785	166	17	training	training	NOUN
ajst-16785	166	18	data	datum	NOUN
ajst-16785	166	19	,	,	PUNCT
ajst-16785	166	20	with	with	ADP
ajst-16785	166	21	the	the	DET
ajst-16785	166	22	remaining	remain	VERB
ajst-16785	166	23	20	20	NUM
ajst-16785	166	24	%	%	NOUN
ajst-16785	166	25	used	use	VERB
ajst-16785	166	26	as	as	ADP
ajst-16785	166	27	test	test	NOUN
ajst-16785	166	28	data	datum	NOUN
ajst-16785	166	29	.	.	PUNCT
ajst-16785	167	1	similarly	similarly	ADV
ajst-16785	167	2	,	,	PUNCT
ajst-16785	167	3	in	in	ADP
ajst-16785	167	4	the	the	DET
ajst-16785	167	5	neu	neu	PROPN
ajst-16785	167	6	-	-	PUNCT
ajst-16785	167	7	cls	cls	NOUN
ajst-16785	167	8	dataset	dataset	NOUN
ajst-16785	167	9	,	,	PUNCT
ajst-16785	167	10	70	70	NUM
ajst-16785	167	11	%	%	NOUN
ajst-16785	167	12	of	of	ADP
ajst-16785	167	13	the	the	DET
ajst-16785	167	14	total	total	ADJ
ajst-16785	167	15	samples	sample	NOUN
ajst-16785	167	16	are	be	AUX
ajst-16785	167	17	used	use	VERB
ajst-16785	167	18	as	as	ADP
ajst-16785	167	19	training	training	NOUN
ajst-16785	167	20	data	datum	NOUN
ajst-16785	167	21	,	,	PUNCT
ajst-16785	167	22	while	while	SCONJ
ajst-16785	167	23	30	30	NUM
ajst-16785	167	24	%	%	NOUN
ajst-16785	167	25	of	of	ADP
ajst-16785	167	26	the	the	DET
ajst-16785	167	27	total	total	ADJ
ajst-16785	167	28	samples	sample	NOUN
ajst-16785	167	29	are	be	AUX
ajst-16785	167	30	used	use	VERB
ajst-16785	167	31	as	as	ADP
ajst-16785	167	32	test	test	NOUN
ajst-16785	167	33	data	datum	NOUN
ajst-16785	167	34	.	.	PUNCT
ajst-16785	168	1	the	the	DET
ajst-16785	168	2	specific	specific	ADJ
ajst-16785	168	3	parameters	parameter	NOUN
ajst-16785	168	4	of	of	ADP
ajst-16785	168	5	the	the	DET
ajst-16785	168	6	dataset	dataset	NOUN
ajst-16785	168	7	division	division	NOUN
ajst-16785	168	8	and	and	CCONJ
ajst-16785	168	9	the	the	DET
ajst-16785	168	10	model	model	NOUN
ajst-16785	168	11	training	training	NOUN
ajst-16785	168	12	parameters	parameter	NOUN
ajst-16785	168	13	are	be	AUX
ajst-16785	168	14	listed	list	VERB
ajst-16785	168	15	in	in	ADP
ajst-16785	168	16	table	table	NOUN
ajst-16785	168	17	2	2	NUM
ajst-16785	168	18	.	.	PUNCT
ajst-16785	168	19	table	table	NOUN
ajst-16785	168	20	2	2	NUM
ajst-16785	168	21	.	.	PUNCT
ajst-16785	168	22	dataset	dataset	ADJ
ajst-16785	168	23	partition	partition	NOUN
ajst-16785	168	24	parameter	parameter	NOUN
ajst-16785	168	25	and	and	CCONJ
ajst-16785	168	26	model	model	NOUN
ajst-16785	168	27	parameter	parameter	NOUN
ajst-16785	168	28	setting	set	VERB
ajst-16785	168	29	table	table	NOUN
ajst-16785	168	30	category	category	NOUN
ajst-16785	168	31	ulfsl	ulfsl	NOUN
ajst-16785	168	32	-	-	PUNCT
ajst-16785	168	33	det	det	PROPN
ajst-16785	168	34	neu	neu	PROPN
ajst-16785	168	35	-	-	PUNCT
ajst-16785	168	36	cls	cls	NOUN
ajst-16785	168	37	2	2	NUM
ajst-16785	168	38	mm	mm	NOUN
ajst-16785	168	39	5	5	NUM
ajst-16785	168	40	mm	mm	NUM
ajst-16785	168	41	8	8	NUM
ajst-16785	168	42	mm	mm	NOUN
ajst-16785	169	1	total	total	ADJ
ajst-16785	169	2	rs	rs	NOUN
ajst-16785	169	3	pa	pa	PROPN
ajst-16785	169	4	cr	cr	PROPN
ajst-16785	169	5	ps	ps	PROPN
ajst-16785	169	6	in	in	ADP
ajst-16785	169	7	sc	sc	PROPN
ajst-16785	169	8	total	total	ADJ
ajst-16785	169	9	training	training	NOUN
ajst-16785	169	10	set	set	VERB
ajst-16785	169	11	160	160	NUM
ajst-16785	169	12	160	160	NUM
ajst-16785	169	13	160	160	NUM
ajst-16785	169	14	480	480	NUM
ajst-16785	169	15	210	210	NUM
ajst-16785	169	16	210	210	NUM
ajst-16785	169	17	210	210	NUM
ajst-16785	169	18	210	210	NUM
ajst-16785	169	19	210	210	NUM
ajst-16785	169	20	210	210	NUM
ajst-16785	169	21	1260	1260	NUM
ajst-16785	169	22	test	test	NOUN
ajst-16785	169	23	sets	set	VERB
ajst-16785	169	24	40	40	NUM
ajst-16785	169	25	40	40	NUM
ajst-16785	169	26	40	40	NUM
ajst-16785	169	27	120	120	NUM
ajst-16785	169	28	90	90	NUM
ajst-16785	169	29	90	90	NUM
ajst-16785	169	30	90	90	NUM
ajst-16785	169	31	90	90	NUM
ajst-16785	169	32	90	90	NUM
ajst-16785	169	33	90	90	NUM
ajst-16785	169	34	540	540	NUM
ajst-16785	169	35	image	image	NOUN
ajst-16785	169	36	size	size	NOUN
ajst-16785	169	37	1×128×128	1×128×128	NUM
ajst-16785	169	38	1×200×200	1×200×200	NUM
ajst-16785	169	39	learning	learning	NOUN
ajst-16785	169	40	rate	rate	NOUN
ajst-16785	169	41	0.001	0.001	NUM
ajst-16785	169	42	0.001	0.001	NUM
ajst-16785	169	43	number	number	NOUN
ajst-16785	169	44	of	of	ADP
ajst-16785	169	45	iterations	iteration	NOUN
ajst-16785	169	46	150	150	NUM
ajst-16785	169	47	100	100	NUM
ajst-16785	169	48	rate	rate	NOUN
ajst-16785	169	49	adjustment	adjustment	NOUN
ajst-16785	169	50	cosine	cosine	NOUN
ajst-16785	169	51	annealing	annealing	NOUN
ajst-16785	169	52	(	(	PUNCT
ajst-16785	169	53	t	t	NOUN
ajst-16785	169	54	=	=	SYM
ajst-16785	169	55	130	130	NUM
ajst-16785	169	56	)	)	PUNCT
ajst-16785	169	57	cosine	cosine	NOUN
ajst-16785	169	58	annealing	annealing	NOUN
ajst-16785	169	59	(	(	PUNCT
ajst-16785	169	60	t	t	NOUN
ajst-16785	169	61	=	=	SYM
ajst-16785	169	62	80	80	NUM
ajst-16785	169	63	)	)	PUNCT
ajst-16785	169	64	optimization	optimization	NOUN
ajst-16785	169	65	adamw	adamw	NOUN
ajst-16785	169	66	adamw	adamw	PROPN
ajst-16785	169	67	loss	loss	PROPN
ajst-16785	169	68	function	function	NOUN
ajst-16785	169	69	cross	cross	NOUN
ajst-16785	169	70	-	-	ADJ
ajst-16785	169	71	entropy	entropy	ADJ
ajst-16785	169	72	cross	cross	NOUN
ajst-16785	169	73	-	-	ADJ
ajst-16785	169	74	entropy	entropy	ADJ
ajst-16785	169	75	181	181	NUM
ajst-16785	169	76	figure	figure	NOUN
ajst-16785	169	77	3	3	NUM
ajst-16785	169	78	.	.	PUNCT
ajst-16785	170	1	(	(	PUNCT
ajst-16785	170	2	a)experimental	a)experimental	ADJ
ajst-16785	170	3	diagram	diagram	NOUN
ajst-16785	170	4	of	of	ADP
ajst-16785	170	5	ultrasonic	ultrasonic	ADJ
ajst-16785	170	6	testing	testing	NOUN
ajst-16785	170	7	of	of	ADP
ajst-16785	170	8	steel	steel	NOUN
ajst-16785	170	9	plate	plate	NOUN
ajst-16785	170	10	defects	defect	NOUN
ajst-16785	170	11	.	.	PUNCT
ajst-16785	171	1	(	(	PUNCT
ajst-16785	171	2	b	b	X
ajst-16785	171	3	)	)	PUNCT
ajst-16785	171	4	partial	partial	ADJ
ajst-16785	171	5	ultrasonic	ultrasonic	ADJ
ajst-16785	171	6	echo	echo	NOUN
ajst-16785	171	7	signal	signal	NOUN
ajst-16785	171	8	and	and	CCONJ
ajst-16785	171	9	the	the	DET
ajst-16785	171	10	preprocessing	preprocessing	NOUN
ajst-16785	171	11	process	process	NOUN
ajst-16785	171	12	.	.	PUNCT
ajst-16785	172	1	(	(	PUNCT
ajst-16785	172	2	c	c	X
ajst-16785	172	3	)	)	PUNCT
ajst-16785	172	4	partial	partial	ADJ
ajst-16785	172	5	defect	defect	NOUN
ajst-16785	172	6	samples	sample	NOUN
ajst-16785	172	7	of	of	ADP
ajst-16785	172	8	the	the	DET
ajst-16785	172	9	neu	neu	PROPN
ajst-16785	172	10	-	-	PUNCT
ajst-16785	172	11	cls	cls	NOUN
ajst-16785	172	12	dataset	dataset	VERB
ajst-16785	172	13	5	5	NUM
ajst-16785	172	14	.	.	PUNCT
ajst-16785	172	15	experimental	experimental	ADJ
ajst-16785	172	16	results	result	NOUN
ajst-16785	172	17	in	in	ADP
ajst-16785	172	18	this	this	DET
ajst-16785	172	19	study	study	NOUN
ajst-16785	172	20	,	,	PUNCT
ajst-16785	172	21	the	the	DET
ajst-16785	172	22	accuracy	accuracy	NOUN
ajst-16785	172	23	of	of	ADP
ajst-16785	172	24	the	the	DET
ajst-16785	172	25	model	model	NOUN
ajst-16785	172	26	was	be	AUX
ajst-16785	172	27	evaluated	evaluate	VERB
ajst-16785	172	28	using	use	VERB
ajst-16785	172	29	two	two	NUM
ajst-16785	172	30	different	different	ADJ
ajst-16785	172	31	sets	set	NOUN
ajst-16785	172	32	of	of	ADP
ajst-16785	172	33	data	datum	NOUN
ajst-16785	172	34	:	:	PUNCT
ajst-16785	172	35	the	the	DET
ajst-16785	172	36	training	training	NOUN
ajst-16785	172	37	set	set	NOUN
ajst-16785	172	38	and	and	CCONJ
ajst-16785	172	39	the	the	DET
ajst-16785	172	40	test	test	NOUN
ajst-16785	172	41	set	set	NOUN
ajst-16785	172	42	.	.	PUNCT
ajst-16785	173	1	the	the	DET
ajst-16785	173	2	training	training	NOUN
ajst-16785	173	3	set	set	NOUN
ajst-16785	173	4	accuracy	accuracy	NOUN
ajst-16785	173	5	measures	measure	NOUN
ajst-16785	173	6	the	the	DET
ajst-16785	173	7	consistency	consistency	NOUN
ajst-16785	173	8	between	between	ADP
ajst-16785	173	9	the	the	DET
ajst-16785	173	10	predicted	predict	VERB
ajst-16785	173	11	labels	label	NOUN
ajst-16785	173	12	and	and	CCONJ
ajst-16785	173	13	the	the	DET
ajst-16785	173	14	actual	actual	ADJ
ajst-16785	173	15	labels	label	NOUN
ajst-16785	173	16	of	of	ADP
ajst-16785	173	17	the	the	DET
ajst-16785	173	18	samples	sample	NOUN
ajst-16785	173	19	used	use	VERB
ajst-16785	173	20	for	for	ADP
ajst-16785	173	21	parameter	parameter	NOUN
ajst-16785	173	22	learning	learning	NOUN
ajst-16785	173	23	.	.	PUNCT
ajst-16785	174	1	on	on	ADP
ajst-16785	174	2	the	the	DET
ajst-16785	174	3	other	other	ADJ
ajst-16785	174	4	hand	hand	NOUN
ajst-16785	174	5	,	,	PUNCT
ajst-16785	174	6	the	the	DET
ajst-16785	174	7	test	test	NOUN
ajst-16785	174	8	set	set	VERB
ajst-16785	174	9	accuracy	accuracy	NOUN
ajst-16785	174	10	measures	measure	NOUN
ajst-16785	174	11	the	the	DET
ajst-16785	174	12	consistency	consistency	NOUN
ajst-16785	174	13	between	between	ADP
ajst-16785	174	14	the	the	DET
ajst-16785	174	15	predicted	predict	VERB
ajst-16785	174	16	labels	label	NOUN
ajst-16785	174	17	and	and	CCONJ
ajst-16785	174	18	the	the	DET
ajst-16785	174	19	actual	actual	ADJ
ajst-16785	174	20	labels	label	NOUN
ajst-16785	174	21	of	of	ADP
ajst-16785	174	22	the	the	DET
ajst-16785	174	23	samples	sample	NOUN
ajst-16785	174	24	that	that	PRON
ajst-16785	174	25	were	be	AUX
ajst-16785	174	26	not	not	PART
ajst-16785	174	27	used	use	VERB
ajst-16785	174	28	for	for	ADP
ajst-16785	174	29	model	model	NOUN
ajst-16785	174	30	training	training	NOUN
ajst-16785	174	31	or	or	CCONJ
ajst-16785	174	32	parameter	parameter	NOUN
ajst-16785	174	33	learning	learning	NOUN
ajst-16785	174	34	.	.	PUNCT
ajst-16785	175	1	the	the	DET
ajst-16785	175	2	test	test	NOUN
ajst-16785	175	3	set	set	VERB
ajst-16785	175	4	is	be	AUX
ajst-16785	175	5	crucial	crucial	ADJ
ajst-16785	175	6	for	for	ADP
ajst-16785	175	7	evaluating	evaluate	VERB
ajst-16785	175	8	the	the	DET
ajst-16785	175	9	generalization	generalization	NOUN
ajst-16785	175	10	ability	ability	NOUN
ajst-16785	175	11	of	of	ADP
ajst-16785	175	12	the	the	DET
ajst-16785	175	13	model	model	NOUN
ajst-16785	175	14	and	and	CCONJ
ajst-16785	175	15	is	be	AUX
ajst-16785	175	16	used	use	VERB
ajst-16785	175	17	as	as	ADP
ajst-16785	175	18	the	the	DET
ajst-16785	175	19	primary	primary	ADJ
ajst-16785	175	20	basis	basis	NOUN
ajst-16785	175	21	for	for	ADP
ajst-16785	175	22	reporting	report	VERB
ajst-16785	175	23	the	the	DET
ajst-16785	175	24	experimental	experimental	ADJ
ajst-16785	175	25	results	result	NOUN
ajst-16785	175	26	.	.	PUNCT
ajst-16785	176	1	5.1	5.1	NUM
ajst-16785	176	2	.	.	PUNCT
ajst-16785	177	1	defect	defect	VERB
ajst-16785	177	2	classification	classification	NOUN
ajst-16785	177	3	experiment	experiment	NOUN
ajst-16785	177	4	to	to	PART
ajst-16785	177	5	evaluate	evaluate	VERB
ajst-16785	177	6	the	the	DET
ajst-16785	177	7	recognition	recognition	NOUN
ajst-16785	177	8	performance	performance	NOUN
ajst-16785	177	9	of	of	ADP
ajst-16785	177	10	icst	icst	NOUN
ajst-16785	177	11	for	for	ADP
ajst-16785	177	12	metal	metal	NOUN
ajst-16785	177	13	defect	defect	NOUN
ajst-16785	177	14	ultrasonic	ultrasonic	ADJ
ajst-16785	177	15	signal	signal	NOUN
ajst-16785	177	16	grayscale	grayscale	NOUN
ajst-16785	177	17	images	image	NOUN
ajst-16785	177	18	,	,	PUNCT
ajst-16785	177	19	experiments	experiment	NOUN
ajst-16785	177	20	were	be	AUX
ajst-16785	177	21	carried	carry	VERB
ajst-16785	177	22	out	out	ADP
ajst-16785	177	23	using	use	VERB
ajst-16785	177	24	the	the	DET
ajst-16785	177	25	ulfsl	ulfsl	NOUN
ajst-16785	177	26	-	-	PUNCT
ajst-16785	177	27	det	det	NOUN
ajst-16785	177	28	dataset	dataset	NOUN
ajst-16785	177	29	,	,	PUNCT
ajst-16785	177	30	which	which	PRON
ajst-16785	177	31	was	be	AUX
ajst-16785	177	32	preprocessed	preprocesse	VERB
ajst-16785	177	33	by	by	ADP
ajst-16785	177	34	wavelet	wavelet	NOUN
ajst-16785	177	35	transform	transform	NOUN
ajst-16785	177	36	.	.	PUNCT
ajst-16785	178	1	the	the	DET
ajst-16785	178	2	test	test	NOUN
ajst-16785	178	3	set	set	VERB
ajst-16785	178	4	accuracy	accuracy	NOUN
ajst-16785	178	5	and	and	CCONJ
ajst-16785	178	6	loss	loss	NOUN
ajst-16785	178	7	value	value	NOUN
ajst-16785	178	8	obtained	obtain	VERB
ajst-16785	178	9	from	from	ADP
ajst-16785	178	10	the	the	DET
ajst-16785	178	11	experimental	experimental	ADJ
ajst-16785	178	12	results	result	NOUN
ajst-16785	178	13	are	be	AUX
ajst-16785	178	14	presented	present	VERB
ajst-16785	178	15	in	in	ADP
ajst-16785	178	16	figure	figure	NOUN
ajst-16785	178	17	4(a	4(a	NUM
ajst-16785	178	18	)	)	PUNCT
ajst-16785	178	19	.	.	PUNCT
ajst-16785	179	1	since	since	SCONJ
ajst-16785	179	2	the	the	DET
ajst-16785	179	3	ulfsl	ulfsl	NOUN
ajst-16785	179	4	-	-	PUNCT
ajst-16785	179	5	det	det	NOUN
ajst-16785	179	6	dataset	dataset	PROPN
ajst-16785	179	7	has	have	VERB
ajst-16785	179	8	a	a	DET
ajst-16785	179	9	smaller	small	ADJ
ajst-16785	179	10	number	number	NOUN
ajst-16785	179	11	of	of	ADP
ajst-16785	179	12	samples	sample	NOUN
ajst-16785	179	13	and	and	CCONJ
ajst-16785	179	14	a	a	DET
ajst-16785	179	15	larger	large	ADJ
ajst-16785	179	16	learning	learning	NOUN
ajst-16785	179	17	rate	rate	NOUN
ajst-16785	179	18	,	,	PUNCT
ajst-16785	179	19	the	the	DET
ajst-16785	179	20	accuracy	accuracy	NOUN
ajst-16785	179	21	rate	rate	NOUN
ajst-16785	179	22	fluctuates	fluctuate	VERB
ajst-16785	179	23	significantly	significantly	ADV
ajst-16785	179	24	at	at	ADP
ajst-16785	179	25	the	the	DET
ajst-16785	179	26	beginning	beginning	NOUN
ajst-16785	179	27	of	of	ADP
ajst-16785	179	28	the	the	DET
ajst-16785	179	29	iteration	iteration	NOUN
ajst-16785	179	30	,	,	PUNCT
ajst-16785	179	31	but	but	CCONJ
ajst-16785	179	32	it	it	PRON
ajst-16785	179	33	shows	show	VERB
ajst-16785	179	34	an	an	DET
ajst-16785	179	35	upward	upward	ADJ
ajst-16785	179	36	trend	trend	NOUN
ajst-16785	179	37	in	in	ADP
ajst-16785	179	38	general	general	ADJ
ajst-16785	179	39	.	.	PUNCT
ajst-16785	180	1	under	under	ADP
ajst-16785	180	2	the	the	DET
ajst-16785	180	3	adamw	adamw	PROPN
ajst-16785	180	4	gradient	gradient	PROPN
ajst-16785	180	5	optimization	optimization	NOUN
ajst-16785	180	6	strategy	strategy	NOUN
ajst-16785	180	7	,	,	PUNCT
ajst-16785	180	8	the	the	DET
ajst-16785	180	9	accuracy	accuracy	NOUN
ajst-16785	180	10	rate	rate	NOUN
ajst-16785	180	11	steadily	steadily	ADV
ajst-16785	180	12	increases	increase	VERB
ajst-16785	180	13	and	and	CCONJ
ajst-16785	180	14	gradually	gradually	ADV
ajst-16785	180	15	reaches	reach	VERB
ajst-16785	180	16	the	the	DET
ajst-16785	180	17	convergence	convergence	NOUN
ajst-16785	180	18	state	state	NOUN
ajst-16785	180	19	after	after	ADP
ajst-16785	180	20	100	100	NUM
ajst-16785	180	21	iterations	iteration	NOUN
ajst-16785	180	22	.	.	PUNCT
ajst-16785	181	1	the	the	DET
ajst-16785	181	2	experimental	experimental	ADJ
ajst-16785	181	3	results	result	NOUN
ajst-16785	181	4	show	show	VERB
ajst-16785	181	5	that	that	SCONJ
ajst-16785	181	6	the	the	DET
ajst-16785	181	7	proposed	propose	VERB
ajst-16785	181	8	icst	icst	NOUN
ajst-16785	181	9	method	method	NOUN
ajst-16785	181	10	achieves	achieve	VERB
ajst-16785	181	11	a	a	DET
ajst-16785	181	12	high	high	ADJ
ajst-16785	181	13	recognition	recognition	NOUN
ajst-16785	181	14	accuracy	accuracy	NOUN
ajst-16785	181	15	of	of	ADP
ajst-16785	181	16	98.1	98.1	NUM
ajst-16785	181	17	%	%	NOUN
ajst-16785	181	18	in	in	ADP
ajst-16785	181	19	the	the	DET
ajst-16785	181	20	ulfsl	ulfsl	NOUN
ajst-16785	181	21	-	-	PUNCT
ajst-16785	181	22	det	det	NOUN
ajst-16785	181	23	dataset	dataset	NOUN
ajst-16785	181	24	.	.	PUNCT
ajst-16785	182	1	the	the	DET
ajst-16785	182	2	accuracy	accuracy	NOUN
ajst-16785	182	3	rate	rate	NOUN
ajst-16785	182	4	is	be	AUX
ajst-16785	182	5	calculated	calculate	VERB
ajst-16785	182	6	as	as	ADP
ajst-16785	182	7	the	the	DET
ajst-16785	182	8	average	average	NOUN
ajst-16785	182	9	of	of	ADP
ajst-16785	182	10	the	the	DET
ajst-16785	182	11	accuracy	accuracy	NOUN
ajst-16785	182	12	of	of	ADP
ajst-16785	182	13	the	the	DET
ajst-16785	182	14	five	five	NUM
ajst-16785	182	15	test	test	NOUN
ajst-16785	182	16	sets	set	NOUN
ajst-16785	182	17	.	.	PUNCT
ajst-16785	183	1	to	to	PART
ajst-16785	183	2	further	far	ADV
ajst-16785	183	3	investigate	investigate	VERB
ajst-16785	183	4	the	the	DET
ajst-16785	183	5	recognition	recognition	NOUN
ajst-16785	183	6	errors	error	NOUN
ajst-16785	183	7	on	on	ADP
ajst-16785	183	8	the	the	DET
ajst-16785	183	9	ulfsldet	ulfsldet	NOUN
ajst-16785	183	10	dataset	dataset	NOUN
ajst-16785	183	11	,	,	PUNCT
ajst-16785	183	12	a	a	DET
ajst-16785	183	13	confusion	confusion	NOUN
ajst-16785	183	14	matrix	matrix	NOUN
ajst-16785	183	15	was	be	AUX
ajst-16785	183	16	used	use	VERB
ajst-16785	183	17	to	to	PART
ajst-16785	183	18	show	show	VERB
ajst-16785	183	19	the	the	DET
ajst-16785	183	20	correspondence	correspondence	NOUN
ajst-16785	183	21	between	between	ADP
ajst-16785	183	22	the	the	DET
ajst-16785	183	23	predicted	predict	VERB
ajst-16785	183	24	values	value	NOUN
ajst-16785	183	25	and	and	CCONJ
ajst-16785	183	26	the	the	DET
ajst-16785	183	27	actual	actual	ADJ
ajst-16785	183	28	labels	label	NOUN
ajst-16785	183	29	.	.	PUNCT
ajst-16785	184	1	as	as	SCONJ
ajst-16785	184	2	shown	show	VERB
ajst-16785	184	3	in	in	ADP
ajst-16785	184	4	figure	figure	NOUN
ajst-16785	184	5	4(b	4(b	NUM
ajst-16785	184	6	)	)	PUNCT
ajst-16785	184	7	,	,	PUNCT
ajst-16785	184	8	the	the	DET
ajst-16785	184	9	true	true	ADJ
ajst-16785	184	10	labels	label	NOUN
ajst-16785	184	11	are	be	AUX
ajst-16785	184	12	in	in	ADP
ajst-16785	184	13	the	the	DET
ajst-16785	184	14	horizontal	horizontal	ADJ
ajst-16785	184	15	coordinates	coordinate	NOUN
ajst-16785	184	16	and	and	CCONJ
ajst-16785	184	17	the	the	DET
ajst-16785	184	18	predicted	predict	VERB
ajst-16785	184	19	values	value	NOUN
ajst-16785	184	20	are	be	AUX
ajst-16785	184	21	in	in	ADP
ajst-16785	184	22	the	the	DET
ajst-16785	184	23	vertical	vertical	ADJ
ajst-16785	184	24	coordinates	coordinate	NOUN
ajst-16785	184	25	.	.	PUNCT
ajst-16785	185	1	in	in	ADP
ajst-16785	185	2	five	five	NUM
ajst-16785	185	3	independent	independent	ADJ
ajst-16785	185	4	experiments	experiment	NOUN
ajst-16785	185	5	on	on	ADP
ajst-16785	185	6	the	the	DET
ajst-16785	185	7	ulfsl	ulfsl	NOUN
ajst-16785	185	8	-	-	PUNCT
ajst-16785	185	9	det	det	NOUN
ajst-16785	185	10	dataset	dataset	NOUN
ajst-16785	185	11	,	,	PUNCT
ajst-16785	185	12	errors	error	NOUN
ajst-16785	185	13	were	be	AUX
ajst-16785	185	14	observed	observe	VERB
ajst-16785	185	15	in	in	ADP
ajst-16785	185	16	identifying	identify	VERB
ajst-16785	185	17	5	5	NUM
ajst-16785	185	18	mm	mm	NOUN
ajst-16785	185	19	defects	defect	NOUN
ajst-16785	185	20	as	as	ADP
ajst-16785	185	21	2	2	NUM
ajst-16785	185	22	mm	mm	NOUN
ajst-16785	185	23	and	and	CCONJ
ajst-16785	185	24	8	8	NUM
ajst-16785	185	25	mm	mm	NOUN
ajst-16785	185	26	defects	defect	NOUN
ajst-16785	185	27	as	as	ADP
ajst-16785	185	28	5	5	NUM
ajst-16785	185	29	mm	mm	NOUN
ajst-16785	185	30	.	.	PUNCT
ajst-16785	186	1	these	these	DET
ajst-16785	186	2	errors	error	NOUN
ajst-16785	186	3	were	be	AUX
ajst-16785	186	4	mainly	mainly	ADV
ajst-16785	186	5	due	due	ADJ
ajst-16785	186	6	to	to	ADP
ajst-16785	186	7	the	the	DET
ajst-16785	186	8	presence	presence	NOUN
ajst-16785	186	9	of	of	ADP
ajst-16785	186	10	irregularly	irregularly	ADV
ajst-16785	186	11	shaped	shape	VERB
ajst-16785	186	12	defects	defect	NOUN
ajst-16785	186	13	in	in	ADP
ajst-16785	186	14	the	the	DET
ajst-16785	186	15	dataset	dataset	NOUN
ajst-16785	186	16	,	,	PUNCT
ajst-16785	186	17	which	which	PRON
ajst-16785	186	18	affected	affect	VERB
ajst-16785	186	19	the	the	DET
ajst-16785	186	20	depth	depth	NOUN
ajst-16785	186	21	judgment	judgment	NOUN
ajst-16785	186	22	,	,	PUNCT
ajst-16785	186	23	and	and	CCONJ
ajst-16785	186	24	their	their	PRON
ajst-16785	186	25	echo	echo	NOUN
ajst-16785	186	26	signals	signal	NOUN
ajst-16785	186	27	had	have	VERB
ajst-16785	186	28	similar	similar	ADJ
ajst-16785	186	29	characteristics	characteristic	NOUN
ajst-16785	186	30	.	.	PUNCT
ajst-16785	187	1	these	these	DET
ajst-16785	187	2	results	result	NOUN
ajst-16785	187	3	suggest	suggest	VERB
ajst-16785	187	4	that	that	SCONJ
ajst-16785	187	5	the	the	DET
ajst-16785	187	6	accuracy	accuracy	NOUN
ajst-16785	187	7	of	of	ADP
ajst-16785	187	8	defect	defect	ADJ
ajst-16785	187	9	recognition	recognition	NOUN
ajst-16785	187	10	can	can	AUX
ajst-16785	187	11	be	be	AUX
ajst-16785	187	12	further	far	ADV
ajst-16785	187	13	improved	improve	VERB
ajst-16785	187	14	by	by	ADP
ajst-16785	187	15	enhancing	enhance	VERB
ajst-16785	187	16	the	the	DET
ajst-16785	187	17	ability	ability	NOUN
ajst-16785	187	18	of	of	ADP
ajst-16785	187	19	the	the	DET
ajst-16785	187	20	model	model	NOUN
ajst-16785	187	21	to	to	PART
ajst-16785	187	22	distinguish	distinguish	VERB
ajst-16785	187	23	between	between	ADP
ajst-16785	187	24	defects	defect	NOUN
ajst-16785	187	25	with	with	ADP
ajst-16785	187	26	similar	similar	ADJ
ajst-16785	187	27	characteristics	characteristic	NOUN
ajst-16785	187	28	.	.	PUNCT
ajst-16785	188	1	in	in	ADP
ajst-16785	188	2	order	order	NOUN
ajst-16785	188	3	to	to	PART
ajst-16785	188	4	assess	assess	VERB
ajst-16785	188	5	the	the	DET
ajst-16785	188	6	icst	icst	NOUN
ajst-16785	188	7	's	's	PART
ajst-16785	188	8	ability	ability	NOUN
ajst-16785	188	9	to	to	PART
ajst-16785	188	10	recognize	recognize	VERB
ajst-16785	188	11	metal	metal	NOUN
ajst-16785	188	12	surface	surface	NOUN
ajst-16785	188	13	defects	defect	NOUN
ajst-16785	188	14	in	in	ADP
ajst-16785	188	15	image	image	NOUN
ajst-16785	188	16	form	form	NOUN
ajst-16785	188	17	,	,	PUNCT
ajst-16785	188	18	experiments	experiment	NOUN
ajst-16785	188	19	were	be	AUX
ajst-16785	188	20	conducted	conduct	VERB
ajst-16785	188	21	on	on	ADP
ajst-16785	188	22	the	the	DET
ajst-16785	188	23	public	public	PROPN
ajst-16785	188	24	neu	neu	PROPN
ajst-16785	188	25	-	-	PUNCT
ajst-16785	188	26	cls	cls	NOUN
ajst-16785	188	27	dataset	dataset	NOUN
ajst-16785	188	28	.	.	PUNCT
ajst-16785	189	1	the	the	DET
ajst-16785	189	2	experimental	experimental	ADJ
ajst-16785	189	3	results	result	NOUN
ajst-16785	189	4	,	,	PUNCT
ajst-16785	189	5	as	as	SCONJ
ajst-16785	189	6	shown	show	VERB
ajst-16785	189	7	in	in	ADP
ajst-16785	189	8	figure	figure	NOUN
ajst-16785	189	9	4(c	4(c	NUM
ajst-16785	189	10	)	)	PUNCT
ajst-16785	189	11	,	,	PUNCT
ajst-16785	189	12	demonstrate	demonstrate	VERB
ajst-16785	189	13	the	the	DET
ajst-16785	189	14	effectiveness	effectiveness	NOUN
ajst-16785	189	15	of	of	ADP
ajst-16785	189	16	the	the	DET
ajst-16785	189	17	model	model	NOUN
ajst-16785	189	18	in	in	ADP
ajst-16785	189	19	recognizing	recognize	VERB
ajst-16785	189	20	surface	surface	NOUN
ajst-16785	189	21	defects	defect	NOUN
ajst-16785	189	22	in	in	ADP
ajst-16785	189	23	images	image	NOUN
ajst-16785	189	24	.	.	PUNCT
ajst-16785	190	1	the	the	DET
ajst-16785	190	2	larger	large	ADJ
ajst-16785	190	3	sample	sample	NOUN
ajst-16785	190	4	size	size	NOUN
ajst-16785	190	5	of	of	ADP
ajst-16785	190	6	the	the	DET
ajst-16785	190	7	neu	neu	PROPN
ajst-16785	190	8	-	-	PUNCT
ajst-16785	190	9	cls	cls	NOUN
ajst-16785	190	10	dataset	dataset	NOUN
ajst-16785	190	11	allows	allow	VERB
ajst-16785	190	12	for	for	ADP
ajst-16785	190	13	more	more	ADV
ajst-16785	190	14	efficient	efficient	ADJ
ajst-16785	190	15	optimization	optimization	NOUN
ajst-16785	190	16	of	of	ADP
ajst-16785	190	17	model	model	NOUN
ajst-16785	190	18	parameters	parameter	NOUN
ajst-16785	190	19	,	,	PUNCT
ajst-16785	190	20	resulting	result	VERB
ajst-16785	190	21	in	in	ADP
ajst-16785	190	22	a	a	DET
ajst-16785	190	23	quick	quick	ADJ
ajst-16785	190	24	and	and	CCONJ
ajst-16785	190	25	182	182	NUM
ajst-16785	190	26	accurate	accurate	ADJ
ajst-16785	190	27	convergence	convergence	NOUN
ajst-16785	190	28	of	of	ADP
ajst-16785	190	29	the	the	DET
ajst-16785	190	30	test	test	NOUN
ajst-16785	190	31	set	set	VERB
ajst-16785	190	32	accuracy	accuracy	NOUN
ajst-16785	190	33	.	.	PUNCT
ajst-16785	191	1	this	this	PRON
ajst-16785	191	2	suggests	suggest	VERB
ajst-16785	191	3	that	that	SCONJ
ajst-16785	191	4	the	the	DET
ajst-16785	191	5	model	model	NOUN
ajst-16785	191	6	possesses	possess	VERB
ajst-16785	191	7	excellent	excellent	ADJ
ajst-16785	191	8	generalization	generalization	NOUN
ajst-16785	191	9	capabilities	capability	NOUN
ajst-16785	191	10	in	in	ADP
ajst-16785	191	11	the	the	DET
ajst-16785	191	12	domain	domain	NOUN
ajst-16785	191	13	of	of	ADP
ajst-16785	191	14	image	image	NOUN
ajst-16785	191	15	metal	metal	NOUN
ajst-16785	191	16	surface	surface	NOUN
ajst-16785	191	17	defect	defect	NOUN
ajst-16785	191	18	recognition	recognition	NOUN
ajst-16785	191	19	.	.	PUNCT
ajst-16785	192	1	the	the	DET
ajst-16785	192	2	average	average	ADJ
ajst-16785	192	3	test	test	NOUN
ajst-16785	192	4	set	set	VERB
ajst-16785	192	5	accuracy	accuracy	NOUN
ajst-16785	192	6	of	of	ADP
ajst-16785	192	7	five	five	NUM
ajst-16785	192	8	independent	independent	ADJ
ajst-16785	192	9	experiments	experiment	NOUN
ajst-16785	192	10	was	be	AUX
ajst-16785	192	11	taken	take	VERB
ajst-16785	192	12	as	as	ADP
ajst-16785	192	13	the	the	DET
ajst-16785	192	14	experimental	experimental	ADJ
ajst-16785	192	15	result	result	NOUN
ajst-16785	192	16	,	,	PUNCT
ajst-16785	192	17	and	and	CCONJ
ajst-16785	192	18	the	the	DET
ajst-16785	192	19	icst	icst	NOUN
ajst-16785	192	20	achieved	achieve	VERB
ajst-16785	192	21	a	a	DET
ajst-16785	192	22	recognition	recognition	NOUN
ajst-16785	192	23	accuracy	accuracy	NOUN
ajst-16785	192	24	of	of	ADP
ajst-16785	192	25	99.8	99.8	NUM
ajst-16785	192	26	%	%	NOUN
ajst-16785	192	27	on	on	ADP
ajst-16785	192	28	the	the	DET
ajst-16785	192	29	neu	neu	PROPN
ajst-16785	192	30	-	-	PUNCT
ajst-16785	192	31	cls	cls	NOUN
ajst-16785	192	32	dataset	dataset	NOUN
ajst-16785	192	33	.	.	PUNCT
ajst-16785	193	1	the	the	DET
ajst-16785	193	2	neu	neu	PROPN
ajst-16785	193	3	-	-	PUNCT
ajst-16785	193	4	cls	cls	NOUN
ajst-16785	193	5	dataset	dataset	NOUN
ajst-16785	193	6	has	have	AUX
ajst-16785	193	7	demonstrated	demonstrate	VERB
ajst-16785	193	8	high	high	ADJ
ajst-16785	193	9	recognition	recognition	NOUN
ajst-16785	193	10	accuracy	accuracy	NOUN
ajst-16785	193	11	in	in	ADP
ajst-16785	193	12	general	general	ADJ
ajst-16785	193	13	,	,	PUNCT
ajst-16785	193	14	but	but	CCONJ
ajst-16785	193	15	the	the	DET
ajst-16785	193	16	results	result	NOUN
ajst-16785	193	17	also	also	ADV
ajst-16785	193	18	revealed	reveal	VERB
ajst-16785	193	19	some	some	DET
ajst-16785	193	20	errors	error	NOUN
ajst-16785	193	21	in	in	ADP
ajst-16785	193	22	the	the	DET
ajst-16785	193	23	recognition	recognition	NOUN
ajst-16785	193	24	of	of	ADP
ajst-16785	193	25	oxidized	oxidized	ADJ
ajst-16785	193	26	skin	skin	NOUN
ajst-16785	193	27	(	(	PUNCT
ajst-16785	193	28	rs	rs	NOUN
ajst-16785	193	29	)	)	PUNCT
ajst-16785	193	30	and	and	CCONJ
ajst-16785	193	31	plaque	plaque	NOUN
ajst-16785	193	32	(	(	PUNCT
ajst-16785	193	33	pa	pa	NOUN
ajst-16785	193	34	)	)	PUNCT
ajst-16785	193	35	defects	defect	NOUN
ajst-16785	193	36	.	.	PUNCT
ajst-16785	194	1	this	this	PRON
ajst-16785	194	2	may	may	AUX
ajst-16785	194	3	be	be	AUX
ajst-16785	194	4	attributed	attribute	VERB
ajst-16785	194	5	to	to	ADP
ajst-16785	194	6	the	the	DET
ajst-16785	194	7	fact	fact	NOUN
ajst-16785	194	8	that	that	SCONJ
ajst-16785	194	9	these	these	DET
ajst-16785	194	10	defects	defect	NOUN
ajst-16785	194	11	share	share	VERB
ajst-16785	194	12	significant	significant	ADJ
ajst-16785	194	13	similarities	similarity	NOUN
ajst-16785	194	14	in	in	ADP
ajst-16785	194	15	their	their	PRON
ajst-16785	194	16	image	image	NOUN
ajst-16785	194	17	shape	shape	NOUN
ajst-16785	194	18	and	and	CCONJ
ajst-16785	194	19	characteristics	characteristic	NOUN
ajst-16785	194	20	.	.	PUNCT
ajst-16785	195	1	further	further	ADJ
ajst-16785	195	2	research	research	NOUN
ajst-16785	195	3	may	may	AUX
ajst-16785	195	4	be	be	AUX
ajst-16785	195	5	necessary	necessary	ADJ
ajst-16785	195	6	to	to	PART
ajst-16785	195	7	explore	explore	VERB
ajst-16785	195	8	how	how	SCONJ
ajst-16785	195	9	to	to	PART
ajst-16785	195	10	distinguish	distinguish	VERB
ajst-16785	195	11	and	and	CCONJ
ajst-16785	195	12	classify	classify	VERB
ajst-16785	195	13	these	these	DET
ajst-16785	195	14	types	type	NOUN
ajst-16785	195	15	of	of	ADP
ajst-16785	195	16	defects	defect	NOUN
ajst-16785	195	17	more	more	ADV
ajst-16785	195	18	accurately	accurately	ADV
ajst-16785	195	19	.	.	PUNCT
ajst-16785	196	1	figure	figure	VERB
ajst-16785	196	2	4	4	NUM
ajst-16785	196	3	.	.	PUNCT
ajst-16785	196	4	defect	defect	VERB
ajst-16785	196	5	identification	identification	NOUN
ajst-16785	196	6	performance	performance	NOUN
ajst-16785	196	7	curve	curve	NOUN
ajst-16785	196	8	and	and	CCONJ
ajst-16785	196	9	identification	identification	NOUN
ajst-16785	196	10	confusion	confusion	NOUN
ajst-16785	196	11	.	.	PUNCT
ajst-16785	197	1	(	(	PUNCT
ajst-16785	197	2	a)(b	a)(b	ADJ
ajst-16785	197	3	)	)	PUNCT
ajst-16785	197	4	ulfsl	ulfsl	NOUN
ajst-16785	197	5	-	-	PUNCT
ajst-16785	197	6	det	det	PROPN
ajst-16785	197	7	;	;	PUNCT
ajst-16785	197	8	(	(	PUNCT
ajst-16785	197	9	c)(d	c)(d	NOUN
ajst-16785	197	10	)	)	PUNCT
ajst-16785	197	11	neu	neu	NOUN
ajst-16785	197	12	-	-	PUNCT
ajst-16785	197	13	cls	cls	NOUN
ajst-16785	197	14	.	.	PUNCT
ajst-16785	198	1	5.2	5.2	NUM
ajst-16785	198	2	.	.	PUNCT
ajst-16785	199	1	ablation	ablation	NOUN
ajst-16785	199	2	experiments	experiment	NOUN
ajst-16785	199	3	in	in	ADP
ajst-16785	199	4	order	order	NOUN
ajst-16785	199	5	to	to	PART
ajst-16785	199	6	investigate	investigate	VERB
ajst-16785	199	7	the	the	DET
ajst-16785	199	8	effects	effect	NOUN
ajst-16785	199	9	of	of	ADP
ajst-16785	199	10	the	the	DET
ajst-16785	199	11	swin	swin	PROPN
ajst-16785	199	12	transformer	transformer	PROPN
ajst-16785	199	13	block	block	NOUN
ajst-16785	199	14	and	and	CCONJ
ajst-16785	199	15	coordattention	coordattention	NOUN
ajst-16785	199	16	modules	module	NOUN
ajst-16785	199	17	,	,	PUNCT
ajst-16785	199	18	we	we	PRON
ajst-16785	199	19	compared	compare	VERB
ajst-16785	199	20	the	the	DET
ajst-16785	199	21	performance	performance	NOUN
ajst-16785	199	22	of	of	ADP
ajst-16785	199	23	different	different	ADJ
ajst-16785	199	24	networks	network	NOUN
ajst-16785	199	25	including	include	VERB
ajst-16785	199	26	the	the	DET
ajst-16785	199	27	inception	inception	ADJ
ajst-16785	199	28	network	network	NOUN
ajst-16785	199	29	,	,	PUNCT
ajst-16785	199	30	inception_coordattention	inception_coordattention	NOUN
ajst-16785	199	31	network	network	NOUN
ajst-16785	199	32	,	,	PUNCT
ajst-16785	199	33	inception_swin	inception_swin	PROPN
ajst-16785	199	34	transformer	transformer	NOUN
ajst-16785	199	35	block	block	NOUN
ajst-16785	199	36	network	network	NOUN
ajst-16785	199	37	,	,	PUNCT
ajst-16785	199	38	and	and	CCONJ
ajst-16785	199	39	icst	icst	PROPN
ajst-16785	199	40	.	.	PUNCT
ajst-16785	200	1	the	the	DET
ajst-16785	200	2	evaluation	evaluation	NOUN
ajst-16785	200	3	metrics	metric	NOUN
ajst-16785	200	4	included	include	VERB
ajst-16785	200	5	accuracy	accuracy	NOUN
ajst-16785	200	6	(	(	PUNCT
ajst-16785	200	7	acc	acc	PROPN
ajst-16785	200	8	)	)	PUNCT
ajst-16785	200	9	,	,	PUNCT
ajst-16785	200	10	floating	float	VERB
ajst-16785	200	11	point	point	NOUN
ajst-16785	200	12	computations	computation	NOUN
ajst-16785	200	13	(	(	PUNCT
ajst-16785	200	14	flops	flop	NOUN
ajst-16785	200	15	)	)	PUNCT
ajst-16785	200	16	,	,	PUNCT
ajst-16785	200	17	and	and	CCONJ
ajst-16785	200	18	the	the	DET
ajst-16785	200	19	number	number	NOUN
ajst-16785	200	20	of	of	ADP
ajst-16785	200	21	parameters	parameter	NOUN
ajst-16785	200	22	(	(	PUNCT
ajst-16785	200	23	params	param	NOUN
ajst-16785	200	24	)	)	PUNCT
ajst-16785	200	25	.	.	PUNCT
ajst-16785	201	1	the	the	DET
ajst-16785	201	2	results	result	NOUN
ajst-16785	201	3	are	be	AUX
ajst-16785	201	4	presented	present	VERB
ajst-16785	201	5	in	in	ADP
ajst-16785	201	6	table	table	NOUN
ajst-16785	201	7	3	3	NUM
ajst-16785	201	8	.	.	PUNCT
ajst-16785	201	9	figure	figure	NOUN
ajst-16785	201	10	5	5	NUM
ajst-16785	201	11	.	.	PUNCT
ajst-16785	201	12	defect	defect	VERB
ajst-16785	201	13	identification	identification	NOUN
ajst-16785	201	14	performance	performance	NOUN
ajst-16785	201	15	curve	curve	NOUN
ajst-16785	201	16	of	of	ADP
ajst-16785	201	17	ablation	ablation	NOUN
ajst-16785	201	18	experiment	experiment	NOUN
ajst-16785	201	19	.	.	PUNCT
ajst-16785	202	1	(	(	PUNCT
ajst-16785	202	2	a	a	X
ajst-16785	202	3	)	)	PUNCT
ajst-16785	202	4	ulfsl	ulfsl	NOUN
ajst-16785	202	5	-	-	PUNCT
ajst-16785	202	6	det	det	PROPN
ajst-16785	202	7	;	;	PUNCT
ajst-16785	202	8	(	(	PUNCT
ajst-16785	202	9	b	b	X
ajst-16785	202	10	)	)	PUNCT
ajst-16785	202	11	neu	neu	NOUN
ajst-16785	202	12	-	-	PUNCT
ajst-16785	202	13	cls	cls	NOUN
ajst-16785	202	14	.	.	PUNCT
ajst-16785	202	15	0	0	NUM
ajst-16785	203	1	30	30	NUM
ajst-16785	203	2	60	60	NUM
ajst-16785	203	3	90	90	NUM
ajst-16785	203	4	120	120	NUM
ajst-16785	203	5	150	150	NUM
ajst-16785	203	6	40	40	NUM
ajst-16785	203	7	50	50	NUM
ajst-16785	203	8	60	60	NUM
ajst-16785	203	9	70	70	NUM
ajst-16785	203	10	80	80	NUM
ajst-16785	203	11	90	90	NUM
ajst-16785	203	12	100	100	NUM
ajst-16785	203	13	test	test	NOUN
ajst-16785	203	14	set	set	VERB
ajst-16785	203	15	loss	loss	NOUN
ajst-16785	203	16	curve	curve	NOUN
ajst-16785	203	17	number	number	NOUN
ajst-16785	203	18	of	of	ADP
ajst-16785	203	19	iterations(n	iterations(n	NOUN
ajst-16785	203	20	)	)	PUNCT
ajst-16785	203	21	a	a	DET
ajst-16785	203	22	cc	cc	NOUN
ajst-16785	203	23	ur	ur	INTJ
ajst-16785	203	24	ac	ac	PROPN
ajst-16785	203	25	y	y	PROPN
ajst-16785	203	26	(	(	PUNCT
ajst-16785	203	27	δ/	δ/	NUM
ajst-16785	203	28	%	%	NOUN
ajst-16785	203	29	)	)	PUNCT
ajst-16785	203	30	0.0	0.0	NUM
ajst-16785	203	31	0.2	0.2	NUM
ajst-16785	203	32	0.4	0.4	NUM
ajst-16785	203	33	0.6	0.6	NUM
ajst-16785	203	34	0.8	0.8	NUM
ajst-16785	203	35	1.0	1.0	NUM
ajst-16785	203	36	1.2	1.2	NUM
ajst-16785	203	37	l	l	NOUN
ajst-16785	203	38	os	os	NOUN
ajst-16785	203	39	s	s	PROPN
ajst-16785	203	40	(	(	PUNCT
ajst-16785	203	41	δ	δ	PROPN
ajst-16785	203	42	)	)	PUNCT
ajst-16785	203	43	0	0	NUM
ajst-16785	203	44	0	0	NUM
ajst-16785	203	45	39	39	NUM
ajst-16785	203	46	0	0	NUM
ajst-16785	203	47	39	39	NUM
ajst-16785	203	48	1	1	NUM
ajst-16785	203	49	40	40	NUM
ajst-16785	203	50	1	1	NUM
ajst-16785	203	51	0	0	NUM
ajst-16785	203	52	2	2	NUM
ajst-16785	203	53	mm	mm	NUM
ajst-16785	203	54	5	5	NUM
ajst-16785	203	55	mm	mm	NOUN
ajst-16785	203	56	8	8	NUM
ajst-16785	203	57	mm	mm	NUM
ajst-16785	203	58	8	8	NUM
ajst-16785	203	59	mm	mm	NUM
ajst-16785	203	60	5	5	NUM
ajst-16785	203	61	mm	mm	NOUN
ajst-16785	203	62	2	2	NUM
ajst-16785	203	63	mm	mm	NOUN
ajst-16785	203	64	0	0	NUM
ajst-16785	203	65	8	8	NUM
ajst-16785	203	66	16	16	NUM
ajst-16785	203	67	24	24	NUM
ajst-16785	203	68	32	32	NUM
ajst-16785	203	69	40	40	NUM
ajst-16785	203	70	0	0	NUM
ajst-16785	203	71	20	20	NUM
ajst-16785	203	72	40	40	NUM
ajst-16785	203	73	60	60	NUM
ajst-16785	203	74	80	80	NUM
ajst-16785	203	75	100	100	NUM
ajst-16785	203	76	40	40	NUM
ajst-16785	203	77	50	50	NUM
ajst-16785	203	78	60	60	NUM
ajst-16785	203	79	70	70	NUM
ajst-16785	203	80	80	80	NUM
ajst-16785	203	81	90	90	NUM
ajst-16785	203	82	100	100	NUM
ajst-16785	203	83	test	test	NOUN
ajst-16785	203	84	set	set	VERB
ajst-16785	203	85	loss	loss	NOUN
ajst-16785	203	86	curve	curve	NOUN
ajst-16785	203	87	number	number	NOUN
ajst-16785	203	88	of	of	ADP
ajst-16785	203	89	iterations(n	iterations(n	NOUN
ajst-16785	203	90	)	)	PUNCT
ajst-16785	203	91	a	a	PRON
ajst-16785	203	92	cc	cc	NOUN
ajst-16785	203	93	ur	ur	INTJ
ajst-16785	203	94	ac	ac	PROPN
ajst-16785	203	95	y	y	PROPN
ajst-16785	203	96	(	(	PUNCT
ajst-16785	203	97	δ/	δ/	NUM
ajst-16785	203	98	%	%	NOUN
ajst-16785	203	99	)	)	PUNCT
ajst-16785	203	100	0.0	0.0	NUM
ajst-16785	203	101	0.2	0.2	NUM
ajst-16785	203	102	0.4	0.4	NUM
ajst-16785	203	103	0.6	0.6	NUM
ajst-16785	203	104	0.8	0.8	NUM
ajst-16785	203	105	1.0	1.0	NUM
ajst-16785	203	106	1.2	1.2	NUM
ajst-16785	203	107	lo	lo	PROPN
ajst-16785	203	108	s	s	PART
ajst-16785	203	109	s	s	X
ajst-16785	203	110	(	(	PUNCT
ajst-16785	203	111	δ	δ	PROPN
ajst-16785	203	112	)	)	PUNCT
ajst-16785	203	113	0	0	NUM
ajst-16785	204	1	0	0	NUM
ajst-16785	204	2	0	0	NUM
ajst-16785	204	3	0	0	NUM
ajst-16785	204	4	0	0	NUM
ajst-16785	204	5	89	89	NUM
ajst-16785	204	6	1	1	NUM
ajst-16785	204	7	0	0	NUM
ajst-16785	204	8	0	0	NUM
ajst-16785	204	9	0	0	NUM
ajst-16785	204	10	86	86	NUM
ajst-16785	204	11	1	1	NUM
ajst-16785	204	12	0	0	NUM
ajst-16785	204	13	0	0	NUM
ajst-16785	204	14	0	0	NUM
ajst-16785	205	1	90	90	NUM
ajst-16785	205	2	0	0	NUM
ajst-16785	205	3	0	0	NUM
ajst-16785	205	4	0	0	NUM
ajst-16785	205	5	0	0	NUM
ajst-16785	206	1	90	90	NUM
ajst-16785	206	2	0	0	NUM
ajst-16785	206	3	3	3	NUM
ajst-16785	206	4	0	0	NUM
ajst-16785	206	5	0	0	NUM
ajst-16785	206	6	90	90	NUM
ajst-16785	206	7	0	0	NUM
ajst-16785	206	8	0	0	NUM
ajst-16785	206	9	0	0	NUM
ajst-16785	206	10	0	0	NUM
ajst-16785	206	11	89	89	NUM
ajst-16785	206	12	0	0	NUM
ajst-16785	206	13	0	0	NUM
ajst-16785	206	14	0	0	NUM
ajst-16785	206	15	1	1	NUM
ajst-16785	206	16	0	0	NUM
ajst-16785	206	17	cr	cr	PROPN
ajst-16785	206	18	in	in	ADP
ajst-16785	206	19	pa	pa	PROPN
ajst-16785	206	20	ps	ps	PROPN
ajst-16785	206	21	rs	rs	PROPN
ajst-16785	206	22	sc	sc	PROPN
ajst-16785	206	23	sc	sc	PROPN
ajst-16785	206	24	rs	rs	NOUN
ajst-16785	206	25	ps	ps	PROPN
ajst-16785	206	26	pa	pa	PROPN
ajst-16785	206	27	in	in	ADP
ajst-16785	206	28	cr	cr	PROPN
ajst-16785	206	29	0	0	NUM
ajst-16785	206	30	10	10	NUM
ajst-16785	206	31	20	20	NUM
ajst-16785	206	32	30	30	NUM
ajst-16785	206	33	40	40	NUM
ajst-16785	206	34	50	50	NUM
ajst-16785	206	35	60	60	NUM
ajst-16785	206	36	70	70	NUM
ajst-16785	206	37	80	80	NUM
ajst-16785	206	38	90	90	NUM
ajst-16785	206	39	(	(	PUNCT
ajst-16785	206	40	a	a	NOUN
ajst-16785	206	41	)	)	PUNCT
ajst-16785	206	42	(	(	PUNCT
ajst-16785	206	43	c	c	X
ajst-16785	206	44	)	)	PUNCT
ajst-16785	206	45	(	(	PUNCT
ajst-16785	206	46	b	b	X
ajst-16785	206	47	)	)	PUNCT
ajst-16785	206	48	(	(	PUNCT
ajst-16785	206	49	d	d	NOUN
ajst-16785	206	50	)	)	PUNCT
ajst-16785	206	51	0	0	NUM
ajst-16785	206	52	30	30	NUM
ajst-16785	206	53	60	60	NUM
ajst-16785	206	54	90	90	NUM
ajst-16785	206	55	120	120	NUM
ajst-16785	206	56	150	150	NUM
ajst-16785	206	57	40	40	NUM
ajst-16785	206	58	50	50	NUM
ajst-16785	206	59	60	60	NUM
ajst-16785	206	60	70	70	NUM
ajst-16785	206	61	80	80	NUM
ajst-16785	206	62	90	90	NUM
ajst-16785	206	63	100	100	NUM
ajst-16785	206	64	a	a	DET
ajst-16785	206	65	cc	cc	ADP
ajst-16785	206	66	ur	ur	INTJ
ajst-16785	206	67	ac	ac	PROPN
ajst-16785	206	68	y	y	PROPN
ajst-16785	206	69	(	(	PUNCT
ajst-16785	206	70	δ/	δ/	NUM
ajst-16785	206	71	%	%	NOUN
ajst-16785	206	72	)	)	PUNCT
ajst-16785	206	73	number	number	NOUN
ajst-16785	206	74	of	of	ADP
ajst-16785	206	75	iterations(n	iterations(n	NOUN
ajst-16785	206	76	)	)	PUNCT
ajst-16785	206	77	proposed	propose	VERB
ajst-16785	206	78	method	method	NOUN
ajst-16785	206	79	inception_swin	inception_swin	PROPN
ajst-16785	206	80	transformer	transformer	NOUN
ajst-16785	206	81	inception_coordattention	inception_coordattention	PROPN
ajst-16785	206	82	inception	inception	NOUN
ajst-16785	206	83	0	0	NUM
ajst-16785	206	84	20	20	NUM
ajst-16785	206	85	40	40	NUM
ajst-16785	206	86	60	60	NUM
ajst-16785	206	87	80	80	NUM
ajst-16785	206	88	100	100	NUM
ajst-16785	206	89	40	40	NUM
ajst-16785	206	90	50	50	NUM
ajst-16785	206	91	60	60	NUM
ajst-16785	206	92	70	70	NUM
ajst-16785	206	93	80	80	NUM
ajst-16785	206	94	90	90	NUM
ajst-16785	206	95	100	100	NUM
ajst-16785	206	96	a	a	DET
ajst-16785	206	97	cc	cc	ADP
ajst-16785	206	98	ur	ur	INTJ
ajst-16785	206	99	ac	ac	PROPN
ajst-16785	206	100	y	y	PROPN
ajst-16785	206	101	(	(	PUNCT
ajst-16785	206	102	δ/	δ/	NUM
ajst-16785	206	103	%	%	NOUN
ajst-16785	206	104	)	)	PUNCT
ajst-16785	206	105	number	number	NOUN
ajst-16785	206	106	of	of	ADP
ajst-16785	206	107	iterations(n	iterations(n	NOUN
ajst-16785	206	108	)	)	PUNCT
ajst-16785	206	109	proposed	propose	VERB
ajst-16785	206	110	method	method	NOUN
ajst-16785	206	111	inception_swin	inception_swin	PROPN
ajst-16785	206	112	transformer	transformer	NOUN
ajst-16785	206	113	inception_coordattention	inception_coordattention	PROPN
ajst-16785	206	114	inception	inception	NOUN
ajst-16785	206	115	(	(	PUNCT
ajst-16785	206	116	a	a	NOUN
ajst-16785	206	117	)	)	PUNCT
ajst-16785	206	118	(	(	PUNCT
ajst-16785	206	119	b	b	X
ajst-16785	206	120	)	)	PUNCT
ajst-16785	206	121	183	183	NUM
ajst-16785	206	122	the	the	DET
ajst-16785	206	123	results	result	NOUN
ajst-16785	206	124	of	of	ADP
ajst-16785	206	125	the	the	DET
ajst-16785	206	126	experiments	experiment	NOUN
ajst-16785	206	127	on	on	ADP
ajst-16785	206	128	the	the	DET
ajst-16785	206	129	ulfsl	ulfsl	NOUN
ajst-16785	206	130	-	-	PUNCT
ajst-16785	206	131	det	det	PROPN
ajst-16785	206	132	and	and	CCONJ
ajst-16785	206	133	neu	neu	PROPN
ajst-16785	206	134	-	-	PUNCT
ajst-16785	206	135	cls	cls	NOUN
ajst-16785	206	136	datasets	dataset	NOUN
ajst-16785	206	137	are	be	AUX
ajst-16785	206	138	presented	present	VERB
ajst-16785	206	139	in	in	ADP
ajst-16785	206	140	figure	figure	NOUN
ajst-16785	206	141	5	5	NUM
ajst-16785	206	142	,	,	PUNCT
ajst-16785	206	143	respectively	respectively	ADV
ajst-16785	206	144	,	,	PUNCT
ajst-16785	206	145	which	which	PRON
ajst-16785	206	146	demonstrate	demonstrate	VERB
ajst-16785	206	147	the	the	DET
ajst-16785	206	148	performance	performance	NOUN
ajst-16785	206	149	enhancement	enhancement	NOUN
ajst-16785	206	150	achieved	achieve	VERB
ajst-16785	206	151	by	by	ADP
ajst-16785	206	152	the	the	DET
ajst-16785	206	153	swin	swin	PROPN
ajst-16785	206	154	transformer	transformer	PROPN
ajst-16785	206	155	block	block	NOUN
ajst-16785	206	156	and	and	CCONJ
ajst-16785	206	157	coordattention	coordattention	NOUN
ajst-16785	206	158	modules	module	NOUN
ajst-16785	206	159	.	.	PUNCT
ajst-16785	207	1	the	the	DET
ajst-16785	207	2	swin	swin	PROPN
ajst-16785	207	3	transformer	transformer	PROPN
ajst-16785	207	4	block	block	NOUN
ajst-16785	207	5	has	have	VERB
ajst-16785	207	6	a	a	DET
ajst-16785	207	7	more	more	ADV
ajst-16785	207	8	significant	significant	ADJ
ajst-16785	207	9	impact	impact	NOUN
ajst-16785	207	10	on	on	ADP
ajst-16785	207	11	the	the	DET
ajst-16785	207	12	recognition	recognition	NOUN
ajst-16785	207	13	performance	performance	NOUN
ajst-16785	207	14	of	of	ADP
ajst-16785	207	15	time	time	NOUN
ajst-16785	207	16	series	series	PROPN
ajst-16785	207	17	metal	metal	NOUN
ajst-16785	207	18	defect	defect	NOUN
ajst-16785	207	19	signal	signal	NOUN
ajst-16785	207	20	recognition	recognition	NOUN
ajst-16785	207	21	than	than	ADP
ajst-16785	207	22	that	that	PRON
ajst-16785	207	23	of	of	ADP
ajst-16785	207	24	the	the	DET
ajst-16785	207	25	neu	neu	PROPN
ajst-16785	207	26	-	-	PUNCT
ajst-16785	207	27	cls	cls	NOUN
ajst-16785	207	28	dataset	dataset	NOUN
ajst-16785	207	29	,	,	PUNCT
ajst-16785	207	30	indicating	indicate	VERB
ajst-16785	207	31	its	its	PRON
ajst-16785	207	32	effectiveness	effectiveness	NOUN
ajst-16785	207	33	in	in	ADP
ajst-16785	207	34	improving	improve	VERB
ajst-16785	207	35	the	the	DET
ajst-16785	207	36	model	model	NOUN
ajst-16785	207	37	performance	performance	NOUN
ajst-16785	207	38	in	in	ADP
ajst-16785	207	39	such	such	ADJ
ajst-16785	207	40	tasks	task	NOUN
ajst-16785	207	41	.	.	PUNCT
ajst-16785	208	1	on	on	ADP
ajst-16785	208	2	the	the	DET
ajst-16785	208	3	other	other	ADJ
ajst-16785	208	4	hand	hand	NOUN
ajst-16785	208	5	,	,	PUNCT
ajst-16785	208	6	the	the	DET
ajst-16785	208	7	coordattention	coordattention	NOUN
ajst-16785	208	8	module	module	NOUN
ajst-16785	208	9	enhances	enhance	VERB
ajst-16785	208	10	the	the	DET
ajst-16785	208	11	model	model	NOUN
ajst-16785	208	12	's	's	PART
ajst-16785	208	13	ability	ability	NOUN
ajst-16785	208	14	to	to	PART
ajst-16785	208	15	focus	focus	VERB
ajst-16785	208	16	on	on	ADP
ajst-16785	208	17	essential	essential	ADJ
ajst-16785	208	18	feature	feature	NOUN
ajst-16785	208	19	channels	channel	NOUN
ajst-16785	208	20	and	and	CCONJ
ajst-16785	208	21	suppress	suppress	VERB
ajst-16785	208	22	redundant	redundant	ADJ
ajst-16785	208	23	feature	feature	NOUN
ajst-16785	208	24	channel	channel	NOUN
ajst-16785	208	25	weights	weight	NOUN
ajst-16785	208	26	,	,	PUNCT
ajst-16785	208	27	leading	lead	VERB
ajst-16785	208	28	to	to	ADP
ajst-16785	208	29	overall	overall	ADJ
ajst-16785	208	30	performance	performance	NOUN
ajst-16785	208	31	improvement	improvement	NOUN
ajst-16785	208	32	.	.	PUNCT
ajst-16785	209	1	furthermore	furthermore	ADV
ajst-16785	209	2	,	,	PUNCT
ajst-16785	209	3	the	the	DET
ajst-16785	209	4	coordattention	coordattention	NOUN
ajst-16785	209	5	module	module	NOUN
ajst-16785	209	6	achieves	achieve	VERB
ajst-16785	209	7	performance	performance	NOUN
ajst-16785	209	8	improvement	improvement	NOUN
ajst-16785	209	9	with	with	ADP
ajst-16785	209	10	a	a	DET
ajst-16785	209	11	smaller	small	ADJ
ajst-16785	209	12	number	number	NOUN
ajst-16785	209	13	of	of	ADP
ajst-16785	209	14	parameters	parameter	NOUN
ajst-16785	209	15	and	and	CCONJ
ajst-16785	209	16	computation	computation	NOUN
ajst-16785	209	17	cost	cost	NOUN
ajst-16785	209	18	than	than	ADP
ajst-16785	209	19	the	the	DET
ajst-16785	209	20	swin	swin	PROPN
ajst-16785	209	21	transformer	transformer	PROPN
ajst-16785	209	22	block	block	NOUN
ajst-16785	209	23	.	.	PUNCT
ajst-16785	210	1	therefore	therefore	ADV
ajst-16785	210	2	,	,	PUNCT
ajst-16785	210	3	the	the	DET
ajst-16785	210	4	coordattention	coordattention	NOUN
ajst-16785	210	5	module	module	NOUN
ajst-16785	210	6	is	be	AUX
ajst-16785	210	7	more	more	ADV
ajst-16785	210	8	suitable	suitable	ADJ
ajst-16785	210	9	when	when	SCONJ
ajst-16785	210	10	there	there	PRON
ajst-16785	210	11	is	be	VERB
ajst-16785	210	12	a	a	DET
ajst-16785	210	13	need	need	NOUN
ajst-16785	210	14	to	to	PART
ajst-16785	210	15	reduce	reduce	VERB
ajst-16785	210	16	the	the	DET
ajst-16785	210	17	number	number	NOUN
ajst-16785	210	18	of	of	ADP
ajst-16785	210	19	model	model	NOUN
ajst-16785	210	20	parameters	parameter	NOUN
ajst-16785	210	21	and	and	CCONJ
ajst-16785	210	22	computations	computation	NOUN
ajst-16785	210	23	while	while	SCONJ
ajst-16785	210	24	sacrificing	sacrifice	VERB
ajst-16785	210	25	less	less	ADJ
ajst-16785	210	26	accuracy	accuracy	NOUN
ajst-16785	210	27	.	.	PUNCT
ajst-16785	211	1	table	table	NOUN
ajst-16785	211	2	3	3	NUM
ajst-16785	211	3	.	.	PUNCT
ajst-16785	211	4	ablation	ablation	NOUN
ajst-16785	211	5	experiment	experiment	NOUN
ajst-16785	211	6	inceptio	inceptio	NOUN
ajst-16785	211	7	n	n	PRON
ajst-16785	211	8	coordat	coordat	PROPN
ajst-16785	211	9	t	t	PROPN
ajst-16785	211	10	swin	swin	PROPN
ajst-16785	211	11	transforme	transforme	PROPN
ajst-16785	211	12	r	r	PROPN
ajst-16785	211	13	ulfsl	ulfsl	NOUN
ajst-16785	211	14	-	-	PUNCT
ajst-16785	211	15	det	det	PROPN
ajst-16785	211	16	neu	neu	PROPN
ajst-16785	211	17	-	-	PUNCT
ajst-16785	211	18	cls	cls	NOUN
ajst-16785	211	19	acc(%	acc(%	NOUN
ajst-16785	211	20	)	)	PUNCT
ajst-16785	211	21	flops(g	flops(g	PROPN
ajst-16785	211	22	)	)	PUNCT
ajst-16785	211	23	params(m	params(m	PROPN
ajst-16785	211	24	)	)	PUNCT
ajst-16785	211	25	acc(%	acc(%	NOUN
ajst-16785	211	26	)	)	PUNCT
ajst-16785	211	27	flops	flop	NOUN
ajst-16785	211	28	(	(	PUNCT
ajst-16785	211	29	g	g	NOUN
ajst-16785	211	30	)	)	PUNCT
ajst-16785	211	31	params(m	params(m	NOUN
ajst-16785	211	32	)	)	PUNCT
ajst-16785	211	33	√	√	PROPN
ajst-16785	211	34	94.1	94.1	NUM
ajst-16785	211	35	0.0172	0.0172	NUM
ajst-16785	211	36	0.140	0.140	NUM
ajst-16785	211	37	98.5	98.5	NUM
ajst-16785	211	38	0.0453	0.0453	NUM
ajst-16785	211	39	0.140	0.140	NUM
ajst-16785	211	40	√	√	NOUN
ajst-16785	211	41	√	√	ADP
ajst-16785	211	42	95.8	95.8	NUM
ajst-16785	211	43	0.0173	0.0173	NUM
ajst-16785	211	44	0.149	0.149	NUM
ajst-16785	211	45	98.9	98.9	NUM
ajst-16785	211	46	0.0455	0.0455	NUM
ajst-16785	211	47	0.149	0.149	NUM
ajst-16785	211	48	√	√	NUM
ajst-16785	211	49	√	√	ADP
ajst-16785	211	50	97.8	97.8	NUM
ajst-16785	211	51	0.0980	0.0980	NUM
ajst-16785	211	52	1.340	1.340	NUM
ajst-16785	211	53	99.4	99.4	NUM
ajst-16785	211	54	0.2039	0.2039	NUM
ajst-16785	211	55	1.340	1.340	NUM
ajst-16785	211	56	√	√	NUM
ajst-16785	211	57	√	√	NUM
ajst-16785	211	58	√	√	NUM
ajst-16785	211	59	98.1	98.1	NUM
ajst-16785	211	60	0.0981	0.0981	NUM
ajst-16785	211	61	1.350	1.350	NUM
ajst-16785	211	62	99.8	99.8	NUM
ajst-16785	211	63	0.2042	0.2042	NUM
ajst-16785	211	64	1.350	1.350	NUM
ajst-16785	211	65	5.3	5.3	NUM
ajst-16785	211	66	.	.	PUNCT
ajst-16785	212	1	comparison	comparison	NOUN
ajst-16785	212	2	experiments	experiment	NOUN
ajst-16785	212	3	of	of	ADP
ajst-16785	212	4	different	different	ADJ
ajst-16785	212	5	classifiers	classifier	NOUN
ajst-16785	212	6	to	to	PART
ajst-16785	212	7	comprehensively	comprehensively	ADV
ajst-16785	212	8	evaluate	evaluate	VERB
ajst-16785	212	9	the	the	DET
ajst-16785	212	10	performance	performance	NOUN
ajst-16785	212	11	of	of	ADP
ajst-16785	212	12	icst	icst	NOUN
ajst-16785	212	13	,	,	PUNCT
ajst-16785	212	14	we	we	PRON
ajst-16785	212	15	compared	compare	VERB
ajst-16785	212	16	it	it	PRON
ajst-16785	212	17	with	with	ADP
ajst-16785	212	18	traditional	traditional	ADJ
ajst-16785	212	19	machine	machine	NOUN
ajst-16785	212	20	learning	learning	NOUN
ajst-16785	212	21	methods	method	NOUN
ajst-16785	212	22	,	,	PUNCT
ajst-16785	212	23	including	include	VERB
ajst-16785	212	24	decision	decision	NOUN
ajst-16785	212	25	trees	tree	NOUN
ajst-16785	212	26	and	and	CCONJ
ajst-16785	212	27	svms	svms	NOUN
ajst-16785	212	28	,	,	PUNCT
ajst-16785	212	29	as	as	ADV
ajst-16785	212	30	well	well	ADV
ajst-16785	212	31	as	as	ADP
ajst-16785	212	32	classical	classical	ADJ
ajst-16785	212	33	convolutional	convolutional	ADJ
ajst-16785	212	34	neural	neural	ADJ
ajst-16785	212	35	network	network	NOUN
ajst-16785	212	36	models	model	NOUN
ajst-16785	212	37	such	such	ADJ
ajst-16785	212	38	as	as	ADP
ajst-16785	212	39	vgg16[7	vgg16[7	NOUN
ajst-16785	212	40	]	]	PUNCT
ajst-16785	212	41	,	,	PUNCT
ajst-16785	212	42	googlenet[8	googlenet[8	PROPN
ajst-16785	212	43	]	]	PUNCT
ajst-16785	212	44	,	,	PUNCT
ajst-16785	212	45	resnet34[9	resnet34[9	X
ajst-16785	212	46	]	]	PUNCT
ajst-16785	212	47	,	,	PUNCT
ajst-16785	212	48	and	and	CCONJ
ajst-16785	212	49	transformer	transformer	NOUN
ajst-16785	212	50	model	model	NOUN
ajst-16785	212	51	vit	vit	NOUN
ajst-16785	212	52	.	.	PUNCT
ajst-16785	213	1	we	we	PRON
ajst-16785	213	2	employed	employ	VERB
ajst-16785	213	3	accuracy	accuracy	NOUN
ajst-16785	213	4	(	(	PUNCT
ajst-16785	213	5	acc	acc	PROPN
ajst-16785	213	6	)	)	PUNCT
ajst-16785	213	7	,	,	PUNCT
ajst-16785	213	8	floating	float	VERB
ajst-16785	213	9	point	point	NOUN
ajst-16785	213	10	computations	computation	NOUN
ajst-16785	213	11	(	(	PUNCT
ajst-16785	213	12	flops	flop	NOUN
ajst-16785	213	13	)	)	PUNCT
ajst-16785	213	14	,	,	PUNCT
ajst-16785	213	15	and	and	CCONJ
ajst-16785	213	16	the	the	DET
ajst-16785	213	17	number	number	NOUN
ajst-16785	213	18	of	of	ADP
ajst-16785	213	19	parameters	parameter	NOUN
ajst-16785	213	20	(	(	PUNCT
ajst-16785	213	21	params	param	NOUN
ajst-16785	213	22	)	)	PUNCT
ajst-16785	213	23	as	as	ADP
ajst-16785	213	24	evaluation	evaluation	NOUN
ajst-16785	213	25	metrics	metric	NOUN
ajst-16785	213	26	.	.	PUNCT
ajst-16785	214	1	in	in	ADP
ajst-16785	214	2	the	the	DET
ajst-16785	214	3	ulfsl	ulfsl	NOUN
ajst-16785	214	4	-	-	PUNCT
ajst-16785	214	5	det	det	NOUN
ajst-16785	214	6	dataset	dataset	PROPN
ajst-16785	214	7	,	,	PUNCT
ajst-16785	214	8	conventional	conventional	ADJ
ajst-16785	214	9	machine	machine	NOUN
ajst-16785	214	10	learning	learning	NOUN
ajst-16785	214	11	methods	method	NOUN
ajst-16785	214	12	require	require	VERB
ajst-16785	214	13	manual	manual	ADJ
ajst-16785	214	14	extraction	extraction	NOUN
ajst-16785	214	15	of	of	ADP
ajst-16785	214	16	ultrasound	ultrasound	ADJ
ajst-16785	214	17	detection	detection	NOUN
ajst-16785	214	18	echo	echo	NOUN
ajst-16785	214	19	signal	signal	PROPN
ajst-16785	214	20	features	feature	NOUN
ajst-16785	214	21	.	.	PUNCT
ajst-16785	215	1	to	to	PART
ajst-16785	215	2	extract	extract	VERB
ajst-16785	215	3	data	datum	NOUN
ajst-16785	215	4	features	feature	NOUN
ajst-16785	215	5	with	with	ADP
ajst-16785	215	6	higher	high	ADJ
ajst-16785	215	7	accuracy	accuracy	NOUN
ajst-16785	215	8	and	and	CCONJ
ajst-16785	215	9	less	less	ADJ
ajst-16785	215	10	noise	noise	NOUN
ajst-16785	215	11	,	,	PUNCT
ajst-16785	215	12	we	we	PRON
ajst-16785	215	13	applied	apply	VERB
ajst-16785	215	14	the	the	DET
ajst-16785	215	15	variational	variational	ADJ
ajst-16785	215	16	mode	mode	NOUN
ajst-16785	215	17	decomposition[23	decomposition[23	PROPN
ajst-16785	215	18	]	]	X
ajst-16785	215	19	(	(	PUNCT
ajst-16785	215	20	vmd	vmd	NOUN
ajst-16785	215	21	)	)	PUNCT
ajst-16785	215	22	method	method	NOUN
ajst-16785	215	23	to	to	PART
ajst-16785	215	24	perform	perform	VERB
ajst-16785	215	25	the	the	DET
ajst-16785	215	26	eigenmode	eigenmode	ADJ
ajst-16785	215	27	decomposition	decomposition	NOUN
ajst-16785	215	28	of	of	ADP
ajst-16785	215	29	the	the	DET
ajst-16785	215	30	ultrasound	ultrasound	NOUN
ajst-16785	215	31	signals	signal	NOUN
ajst-16785	215	32	after	after	ADP
ajst-16785	215	33	the	the	DET
ajst-16785	215	34	filtering	filtering	NOUN
ajst-16785	215	35	operation	operation	NOUN
ajst-16785	215	36	.	.	PUNCT
ajst-16785	216	1	figure	figure	NOUN
ajst-16785	216	2	6	6	NUM
ajst-16785	216	3	illustrates	illustrate	VERB
ajst-16785	216	4	that	that	SCONJ
ajst-16785	216	5	each	each	DET
ajst-16785	216	6	ultrasound	ultrasound	NOUN
ajst-16785	216	7	signal	signal	NOUN
ajst-16785	216	8	is	be	AUX
ajst-16785	216	9	decomposed	decompose	VERB
ajst-16785	216	10	to	to	PART
ajst-16785	216	11	obtain	obtain	VERB
ajst-16785	216	12	seven	seven	NUM
ajst-16785	216	13	eigenmode	eigenmode	ADJ
ajst-16785	216	14	components	component	NOUN
ajst-16785	216	15	imf	imf	PROPN
ajst-16785	216	16	and	and	CCONJ
ajst-16785	216	17	one	one	NUM
ajst-16785	216	18	residual	residual	ADJ
ajst-16785	216	19	res	re	NOUN
ajst-16785	216	20	.	.	PUNCT
ajst-16785	217	1	we	we	PRON
ajst-16785	217	2	extracted	extract	VERB
ajst-16785	217	3	nine	nine	NUM
ajst-16785	217	4	defective	defective	ADJ
ajst-16785	217	5	features	feature	NOUN
ajst-16785	217	6	from	from	ADP
ajst-16785	217	7	each	each	DET
ajst-16785	217	8	eigenmode	eigenmode	ADJ
ajst-16785	217	9	component	component	NOUN
ajst-16785	217	10	under	under	ADP
ajst-16785	217	11	the	the	DET
ajst-16785	217	12	time	time	NOUN
ajst-16785	217	13	domain	domain	PROPN
ajst-16785	217	14	indicator	indicator	NOUN
ajst-16785	217	15	parameter	parameter	NOUN
ajst-16785	217	16	,	,	PUNCT
ajst-16785	217	17	totaling	total	VERB
ajst-16785	217	18	63	63	NUM
ajst-16785	217	19	features	feature	NOUN
ajst-16785	217	20	for	for	ADP
ajst-16785	217	21	one	one	NUM
ajst-16785	217	22	sample	sample	NOUN
ajst-16785	217	23	signal	signal	NOUN
ajst-16785	217	24	.	.	PUNCT
ajst-16785	218	1	each	each	DET
ajst-16785	218	2	eigenmode	eigenmode	PROPN
ajst-16785	218	3	component	component	NOUN
ajst-16785	218	4	was	be	AUX
ajst-16785	218	5	manually	manually	ADV
ajst-16785	218	6	extracted	extract	VERB
ajst-16785	218	7	and	and	CCONJ
ajst-16785	218	8	divided	divide	VERB
ajst-16785	218	9	into	into	ADP
ajst-16785	218	10	two	two	NUM
ajst-16785	218	11	categories	category	NOUN
ajst-16785	218	12	:	:	PUNCT
ajst-16785	218	13	dimensionless	dimensionless	NOUN
ajst-16785	218	14	parameters	parameter	NOUN
ajst-16785	218	15	and	and	CCONJ
ajst-16785	218	16	dimensioned	dimension	VERB
ajst-16785	218	17	parameters	parameter	NOUN
ajst-16785	218	18	.	.	PUNCT
ajst-16785	219	1	the	the	DET
ajst-16785	219	2	dimensionless	dimensionless	NOUN
ajst-16785	219	3	parameters	parameter	NOUN
ajst-16785	219	4	included	include	VERB
ajst-16785	219	5	skewness	skewness	NOUN
ajst-16785	219	6	,	,	PUNCT
ajst-16785	219	7	kurtosis	kurtosis	NOUN
ajst-16785	219	8	,	,	PUNCT
ajst-16785	219	9	and	and	CCONJ
ajst-16785	219	10	peak	peak	NOUN
ajst-16785	219	11	,	,	PUNCT
ajst-16785	219	12	while	while	SCONJ
ajst-16785	219	13	the	the	DET
ajst-16785	219	14	dimensioned	dimension	VERB
ajst-16785	219	15	parameters	parameter	NOUN
ajst-16785	219	16	included	include	VERB
ajst-16785	219	17	variance	variance	NOUN
ajst-16785	219	18	,	,	PUNCT
ajst-16785	219	19	mean	mean	VERB
ajst-16785	219	20	,	,	PUNCT
ajst-16785	219	21	maximum	maximum	ADJ
ajst-16785	219	22	,	,	PUNCT
ajst-16785	219	23	minimum	minimum	ADJ
ajst-16785	219	24	,	,	PUNCT
ajst-16785	219	25	amplitude	amplitude	NOUN
ajst-16785	219	26	,	,	PUNCT
ajst-16785	219	27	and	and	CCONJ
ajst-16785	219	28	standard	standard	ADJ
ajst-16785	219	29	deviation	deviation	NOUN
ajst-16785	219	30	.	.	PUNCT
ajst-16785	220	1	the	the	DET
ajst-16785	220	2	test	test	NOUN
ajst-16785	220	3	results	result	NOUN
ajst-16785	220	4	of	of	ADP
ajst-16785	220	5	each	each	DET
ajst-16785	220	6	model	model	NOUN
ajst-16785	220	7	on	on	ADP
ajst-16785	220	8	the	the	DET
ajst-16785	220	9	ulfsl	ulfsl	NOUN
ajst-16785	220	10	-	-	PUNCT
ajst-16785	220	11	det	det	PROPN
ajst-16785	220	12	and	and	CCONJ
ajst-16785	220	13	neu	neu	PROPN
ajst-16785	220	14	-	-	PUNCT
ajst-16785	220	15	cls	cls	NOUN
ajst-16785	220	16	dataset	dataset	NOUN
ajst-16785	220	17	are	be	AUX
ajst-16785	220	18	shown	show	VERB
ajst-16785	220	19	in	in	ADP
ajst-16785	220	20	table	table	NOUN
ajst-16785	220	21	4	4	NUM
ajst-16785	220	22	.	.	PUNCT
ajst-16785	220	23	compared	compare	VERB
ajst-16785	220	24	with	with	ADP
ajst-16785	220	25	icst	icst	PROPN
ajst-16785	220	26	,	,	PUNCT
ajst-16785	220	27	the	the	DET
ajst-16785	220	28	advantage	advantage	NOUN
ajst-16785	220	29	of	of	ADP
ajst-16785	220	30	machine	machine	NOUN
ajst-16785	220	31	learning	learning	NOUN
ajst-16785	220	32	method	method	NOUN
ajst-16785	220	33	is	be	AUX
ajst-16785	220	34	that	that	SCONJ
ajst-16785	220	35	the	the	DET
ajst-16785	220	36	model	model	NOUN
ajst-16785	220	37	computation	computation	NOUN
ajst-16785	220	38	and	and	CCONJ
ajst-16785	220	39	the	the	DET
ajst-16785	220	40	number	number	NOUN
ajst-16785	220	41	of	of	ADP
ajst-16785	220	42	parameters	parameter	NOUN
ajst-16785	220	43	are	be	AUX
ajst-16785	220	44	negligible	negligible	ADJ
ajst-16785	220	45	.	.	PUNCT
ajst-16785	221	1	however	however	ADV
ajst-16785	221	2	,	,	PUNCT
ajst-16785	221	3	their	their	PRON
ajst-16785	221	4	recognition	recognition	NOUN
ajst-16785	221	5	accuracy	accuracy	NOUN
ajst-16785	221	6	of	of	ADP
ajst-16785	221	7	metal	metal	NOUN
ajst-16785	221	8	defect	defect	NOUN
ajst-16785	221	9	ultrasonic	ultrasonic	ADJ
ajst-16785	221	10	signal	signal	NOUN
ajst-16785	221	11	grayscale	grayscale	NOUN
ajst-16785	221	12	images	image	NOUN
ajst-16785	221	13	is	be	AUX
ajst-16785	221	14	much	much	ADV
ajst-16785	221	15	lower	low	ADJ
ajst-16785	221	16	than	than	ADP
ajst-16785	221	17	the	the	DET
ajst-16785	221	18	icst	icst	NOUN
ajst-16785	221	19	.	.	PUNCT
ajst-16785	222	1	still	still	ADV
ajst-16785	222	2	,	,	PUNCT
ajst-16785	222	3	the	the	DET
ajst-16785	222	4	machine	machine	NOUN
ajst-16785	222	5	learning	learning	NOUN
ajst-16785	222	6	method	method	NOUN
ajst-16785	222	7	is	be	AUX
ajst-16785	222	8	also	also	ADV
ajst-16785	222	9	highly	highly	ADV
ajst-16785	222	10	dependent	dependent	ADJ
ajst-16785	222	11	on	on	ADP
ajst-16785	222	12	expert	expert	NOUN
ajst-16785	222	13	opinions	opinion	NOUN
ajst-16785	222	14	and	and	CCONJ
ajst-16785	222	15	a	a	DET
ajst-16785	222	16	cumbersome	cumbersome	ADJ
ajst-16785	222	17	work	work	NOUN
ajst-16785	222	18	process	process	NOUN
ajst-16785	222	19	in	in	ADP
ajst-16785	222	20	the	the	DET
ajst-16785	222	21	feature	feature	NOUN
ajst-16785	222	22	extraction	extraction	NOUN
ajst-16785	222	23	work	work	NOUN
ajst-16785	222	24	.	.	PUNCT
ajst-16785	223	1	it	it	PRON
ajst-16785	223	2	shows	show	VERB
ajst-16785	223	3	that	that	SCONJ
ajst-16785	223	4	icst	icst	PROPN
ajst-16785	223	5	can	can	AUX
ajst-16785	223	6	be	be	AUX
ajst-16785	223	7	primarily	primarily	ADV
ajst-16785	223	8	referred	refer	VERB
ajst-16785	223	9	to	to	ADP
ajst-16785	223	10	other	other	ADJ
ajst-16785	223	11	tasks	task	NOUN
ajst-16785	223	12	that	that	SCONJ
ajst-16785	223	13	machine	machine	NOUN
ajst-16785	223	14	learning	learning	NOUN
ajst-16785	223	15	method	method	NOUN
ajst-16785	223	16	is	be	AUX
ajst-16785	223	17	applied	apply	VERB
ajst-16785	223	18	for	for	ADP
ajst-16785	223	19	time	time	NOUN
ajst-16785	223	20	series	series	PROPN
ajst-16785	223	21	defect	defect	PROPN
ajst-16785	223	22	signal	signal	NOUN
ajst-16785	223	23	recognition	recognition	NOUN
ajst-16785	223	24	.	.	PUNCT
ajst-16785	224	1	compared	compare	VERB
ajst-16785	224	2	with	with	ADP
ajst-16785	224	3	the	the	DET
ajst-16785	224	4	classical	classical	ADJ
ajst-16785	224	5	deep	deep	ADJ
ajst-16785	224	6	learning	learning	NOUN
ajst-16785	224	7	methods	method	NOUN
ajst-16785	224	8	,	,	PUNCT
ajst-16785	224	9	the	the	DET
ajst-16785	224	10	difference	difference	NOUN
ajst-16785	224	11	in	in	ADP
ajst-16785	224	12	accuracy	accuracy	NOUN
ajst-16785	224	13	is	be	AUX
ajst-16785	224	14	very	very	ADV
ajst-16785	224	15	small	small	ADJ
ajst-16785	224	16	.	.	PUNCT
ajst-16785	225	1	however	however	ADV
ajst-16785	225	2	,	,	PUNCT
ajst-16785	225	3	in	in	ADP
ajst-16785	225	4	terms	term	NOUN
ajst-16785	225	5	of	of	ADP
ajst-16785	225	6	model	model	NOUN
ajst-16785	225	7	computation	computation	NOUN
ajst-16785	225	8	and	and	CCONJ
ajst-16785	225	9	the	the	DET
ajst-16785	225	10	number	number	NOUN
ajst-16785	225	11	of	of	ADP
ajst-16785	225	12	parameters	parameter	NOUN
ajst-16785	225	13	,	,	PUNCT
ajst-16785	225	14	icst	icst	PROPN
ajst-16785	225	15	is	be	AUX
ajst-16785	225	16	much	much	ADV
ajst-16785	225	17	smaller	small	ADJ
ajst-16785	225	18	than	than	ADP
ajst-16785	225	19	the	the	DET
ajst-16785	225	20	classical	classical	ADJ
ajst-16785	225	21	deep	deep	ADJ
ajst-16785	225	22	learning	learning	NOUN
ajst-16785	225	23	methods	method	NOUN
ajst-16785	225	24	.	.	PUNCT
ajst-16785	226	1	because	because	SCONJ
ajst-16785	226	2	the	the	DET
ajst-16785	226	3	structure	structure	NOUN
ajst-16785	226	4	of	of	ADP
ajst-16785	226	5	icst	icst	PROPN
ajst-16785	226	6	is	be	AUX
ajst-16785	226	7	simple	simple	ADJ
ajst-16785	226	8	and	and	CCONJ
ajst-16785	226	9	the	the	DET
ajst-16785	226	10	number	number	NOUN
ajst-16785	226	11	of	of	ADP
ajst-16785	226	12	parameters	parameter	NOUN
ajst-16785	226	13	is	be	AUX
ajst-16785	226	14	small	small	ADJ
ajst-16785	226	15	,	,	PUNCT
ajst-16785	226	16	icst	icst	PROPN
ajst-16785	226	17	is	be	AUX
ajst-16785	226	18	more	more	ADV
ajst-16785	226	19	advantageous	advantageous	ADJ
ajst-16785	226	20	in	in	ADP
ajst-16785	226	21	small	small	ADJ
ajst-16785	226	22	and	and	CCONJ
ajst-16785	226	23	medium	medium	ADJ
ajst-16785	226	24	-	-	PUNCT
ajst-16785	226	25	sized	sized	ADJ
ajst-16785	226	26	datasets	dataset	NOUN
ajst-16785	226	27	,	,	PUNCT
ajst-16785	226	28	and	and	CCONJ
ajst-16785	226	29	the	the	DET
ajst-16785	226	30	model	model	NOUN
ajst-16785	226	31	parameters	parameter	NOUN
ajst-16785	226	32	are	be	AUX
ajst-16785	226	33	easier	easy	ADJ
ajst-16785	226	34	to	to	PART
ajst-16785	226	35	train	train	VERB
ajst-16785	226	36	.	.	PUNCT
ajst-16785	227	1	figure	figure	NOUN
ajst-16785	227	2	6	6	NUM
ajst-16785	227	3	.	.	PUNCT
ajst-16785	228	1	vmd	vmd	PROPN
ajst-16785	228	2	exploded	explode	VERB
ajst-16785	228	3	view	view	NOUN
ajst-16785	228	4	of	of	ADP
ajst-16785	228	5	ulfsl	ulfsl	NOUN
ajst-16785	228	6	-	-	PUNCT
ajst-16785	228	7	det	det	NOUN
ajst-16785	228	8	dataset	dataset	NOUN
ajst-16785	228	9	sample	sample	NOUN
ajst-16785	228	10	since	since	SCONJ
ajst-16785	228	11	neu	neu	NOUN
ajst-16785	228	12	-	-	PUNCT
ajst-16785	228	13	cls	cls	NOUN
ajst-16785	228	14	is	be	AUX
ajst-16785	228	15	an	an	DET
ajst-16785	228	16	image	image	NOUN
ajst-16785	228	17	-	-	PUNCT
ajst-16785	228	18	based	base	VERB
ajst-16785	228	19	mental	mental	ADJ
ajst-16785	228	20	defect	defect	NOUN
ajst-16785	228	21	dataset	dataset	NOUN
ajst-16785	228	22	and	and	CCONJ
ajst-16785	228	23	does	do	AUX
ajst-16785	228	24	not	not	PART
ajst-16785	228	25	require	require	VERB
ajst-16785	228	26	manual	manual	ADJ
ajst-16785	228	27	feature	feature	NOUN
ajst-16785	228	28	extraction	extraction	NOUN
ajst-16785	228	29	,	,	PUNCT
ajst-16785	228	30	it	it	PRON
ajst-16785	228	31	is	be	AUX
ajst-16785	228	32	only	only	ADV
ajst-16785	228	33	selected	select	VERB
ajst-16785	228	34	for	for	ADP
ajst-16785	228	35	comparison	comparison	NOUN
ajst-16785	228	36	experiments	experiment	NOUN
ajst-16785	228	37	of	of	ADP
ajst-16785	228	38	icst	icst	NOUN
ajst-16785	228	39	versus	versus	ADP
ajst-16785	228	40	with	with	ADP
ajst-16785	228	41	the	the	DET
ajst-16785	228	42	classical	classical	ADJ
ajst-16785	228	43	convolutional	convolutional	ADJ
ajst-16785	228	44	neural	neural	ADJ
ajst-16785	228	45	network	network	NOUN
ajst-16785	228	46	model	model	NOUN
ajst-16785	228	47	and	and	CCONJ
ajst-16785	228	48	transformer	transformer	NOUN
ajst-16785	228	49	model	model	NOUN
ajst-16785	228	50	.	.	PUNCT
ajst-16785	229	1	since	since	SCONJ
ajst-16785	229	2	the	the	DET
ajst-16785	229	3	neu	neu	PROPN
ajst-16785	229	4	-	-	PUNCT
ajst-16785	229	5	cls	cls	NOUN
ajst-16785	229	6	dataset	dataset	NOUN
ajst-16785	229	7	has	have	VERB
ajst-16785	229	8	a	a	DET
ajst-16785	229	9	larger	large	ADJ
ajst-16785	229	10	sample	sample	NOUN
ajst-16785	229	11	size	size	NOUN
ajst-16785	229	12	than	than	ADP
ajst-16785	229	13	the	the	DET
ajst-16785	229	14	ulfsl	ulfsl	NOUN
ajst-16785	229	15	-	-	PUNCT
ajst-16785	229	16	det	det	NOUN
ajst-16785	229	17	dataset	dataset	NOUN
ajst-16785	229	18	,	,	PUNCT
ajst-16785	229	19	each	each	DET
ajst-16785	229	20	model	model	NOUN
ajst-16785	229	21	gets	get	VERB
ajst-16785	229	22	better	well	ADJ
ajst-16785	229	23	parameter	parameter	NOUN
ajst-16785	229	24	optimization	optimization	NOUN
ajst-16785	229	25	.	.	PUNCT
ajst-16785	230	1	so	so	ADV
ajst-16785	230	2	the	the	DET
ajst-16785	230	3	accuracy	accuracy	NOUN
ajst-16785	230	4	of	of	ADP
ajst-16785	230	5	each	each	DET
ajst-16785	230	6	model	model	NOUN
ajst-16785	230	7	0	0	NUM
ajst-16785	230	8	6	6	NUM
ajst-16785	230	9	12	12	NUM
ajst-16785	230	10	-3	-3	SYM
ajst-16785	230	11	0	0	NUM
ajst-16785	230	12	3	3	NUM
ajst-16785	230	13	-5	-5	NOUN
ajst-16785	230	14	0	0	NUM
ajst-16785	230	15	5	5	NUM
ajst-16785	230	16	-4	-4	SYM
ajst-16785	230	17	0	0	NUM
ajst-16785	230	18	4	4	NUM
ajst-16785	230	19	-0.5	-0.5	NUM
ajst-16785	230	20	0.0	0.0	NUM
ajst-16785	230	21	0.5	0.5	NUM
ajst-16785	230	22	-0.5	-0.5	NUM
ajst-16785	230	23	0.0	0.0	NUM
ajst-16785	230	24	0.5	0.5	NUM
ajst-16785	230	25	-0.5	-0.5	NUM
ajst-16785	230	26	0.0	0.0	NUM
ajst-16785	230	27	0.5	0.5	NUM
ajst-16785	230	28	-0.5	-0.5	NUM
ajst-16785	230	29	0.0	0.0	NUM
ajst-16785	230	30	0.5	0.5	NUM
ajst-16785	230	31	0	0	NUM
ajst-16785	230	32	5	5	NUM
ajst-16785	230	33	10	10	NUM
ajst-16785	230	34	15	15	NUM
ajst-16785	230	35	20	20	NUM
ajst-16785	230	36	25	25	NUM
ajst-16785	230	37	0	0	NUM
ajst-16785	230	38	6	6	NUM
ajst-16785	230	39	12	12	NUM
ajst-16785	230	40	time(t	time(t	PROPN
ajst-16785	230	41	/	/	SYM
ajst-16785	230	42	us	we	PRON
ajst-16785	230	43	)	)	PUNCT
ajst-16785	230	44	original	original	ADJ
ajst-16785	230	45	signal	signal	NOUN
ajst-16785	230	46	imf1	imf1	PROPN
ajst-16785	231	1	imf2	imf2	VERB
ajst-16785	231	2	imf3	imf3	PROPN
ajst-16785	231	3	v	v	ADP
ajst-16785	231	4	ol	ol	PROPN
ajst-16785	231	5	ta	ta	PROPN
ajst-16785	231	6	ge	ge	PROPN
ajst-16785	231	7	(	(	PUNCT
ajst-16785	231	8	u	u	PROPN
ajst-16785	231	9	/v	/v	PUNCT
ajst-16785	231	10	)	)	PUNCT
ajst-16785	231	11	imf4	imf4	PROPN
ajst-16785	231	12	imf5	imf5	PROPN
ajst-16785	231	13	imf6	imf6	PROPN
ajst-16785	231	14	imf7	imf7	PROPN
ajst-16785	231	15	res	re	VERB
ajst-16785	231	16	184	184	NUM
ajst-16785	231	17	on	on	ADP
ajst-16785	231	18	the	the	DET
ajst-16785	231	19	neu	neu	PROPN
ajst-16785	231	20	-	-	PUNCT
ajst-16785	231	21	cls	cls	NOUN
ajst-16785	231	22	dataset	dataset	NOUN
ajst-16785	231	23	is	be	AUX
ajst-16785	231	24	slightly	slightly	ADV
ajst-16785	231	25	improved	improve	VERB
ajst-16785	231	26	.	.	PUNCT
ajst-16785	232	1	resnet34	resnet34	NOUN
ajst-16785	232	2	,	,	PUNCT
ajst-16785	232	3	vgg16	vgg16	NOUN
ajst-16785	232	4	and	and	CCONJ
ajst-16785	232	5	icst	icst	NOUN
ajst-16785	232	6	are	be	AUX
ajst-16785	232	7	similar	similar	ADJ
ajst-16785	232	8	in	in	ADP
ajst-16785	232	9	recognition	recognition	NOUN
ajst-16785	232	10	accuracy	accuracy	NOUN
ajst-16785	232	11	,	,	PUNCT
ajst-16785	232	12	but	but	CCONJ
ajst-16785	232	13	conventional	conventional	ADJ
ajst-16785	232	14	methods	method	NOUN
ajst-16785	232	15	’	'	PUNCT
ajst-16785	232	16	network	network	NOUN
ajst-16785	232	17	computation	computation	NOUN
ajst-16785	232	18	and	and	CCONJ
ajst-16785	232	19	the	the	DET
ajst-16785	232	20	number	number	NOUN
ajst-16785	232	21	of	of	ADP
ajst-16785	232	22	parameters	parameter	NOUN
ajst-16785	232	23	are	be	AUX
ajst-16785	232	24	too	too	ADV
ajst-16785	232	25	large	large	ADJ
ajst-16785	232	26	,	,	PUNCT
ajst-16785	232	27	which	which	PRON
ajst-16785	232	28	is	be	AUX
ajst-16785	232	29	not	not	PART
ajst-16785	232	30	conducive	conducive	ADJ
ajst-16785	232	31	to	to	ADP
ajst-16785	232	32	small	small	ADJ
ajst-16785	232	33	and	and	CCONJ
ajst-16785	232	34	medium	medium	ADJ
ajst-16785	232	35	-	-	PUNCT
ajst-16785	232	36	sized	sized	ADJ
ajst-16785	232	37	datasets	dataset	NOUN
ajst-16785	232	38	.	.	PUNCT
ajst-16785	233	1	in	in	ADP
ajst-16785	233	2	contrast	contrast	NOUN
ajst-16785	233	3	,	,	PUNCT
ajst-16785	233	4	icst	icst	PROPN
ajst-16785	233	5	achieves	achieve	VERB
ajst-16785	233	6	the	the	DET
ajst-16785	233	7	detection	detection	NOUN
ajst-16785	233	8	of	of	ADP
ajst-16785	233	9	metal	metal	NOUN
ajst-16785	233	10	defect	defect	NOUN
ajst-16785	233	11	ultrasonic	ultrasonic	ADJ
ajst-16785	233	12	signal	signal	NOUN
ajst-16785	233	13	grayscale	grayscale	NOUN
ajst-16785	233	14	images	image	NOUN
ajst-16785	233	15	and	and	CCONJ
ajst-16785	233	16	image	image	NOUN
ajst-16785	233	17	-	-	PUNCT
ajst-16785	233	18	based	base	VERB
ajst-16785	233	19	mental	mental	ADJ
ajst-16785	233	20	defects	defect	NOUN
ajst-16785	233	21	with	with	ADP
ajst-16785	233	22	lower	low	ADJ
ajst-16785	233	23	computation	computation	NOUN
ajst-16785	233	24	cost	cost	NOUN
ajst-16785	233	25	,	,	PUNCT
ajst-16785	233	26	while	while	SCONJ
ajst-16785	233	27	obtaining	obtain	VERB
ajst-16785	233	28	optimal	optimal	ADJ
ajst-16785	233	29	accuracy	accuracy	NOUN
ajst-16785	233	30	in	in	ADP
ajst-16785	233	31	small	small	ADJ
ajst-16785	233	32	and	and	CCONJ
ajst-16785	233	33	medium	medium	ADJ
ajst-16785	233	34	-	-	PUNCT
ajst-16785	233	35	sized	sized	ADJ
ajst-16785	233	36	datasets	dataset	NOUN
ajst-16785	233	37	.	.	PUNCT
ajst-16785	234	1	table	table	NOUN
ajst-16785	234	2	4	4	NUM
ajst-16785	234	3	.	.	PUNCT
ajst-16785	234	4	test	test	NOUN
ajst-16785	234	5	results	result	NOUN
ajst-16785	234	6	of	of	ADP
ajst-16785	234	7	different	different	ADJ
ajst-16785	234	8	models	model	NOUN
ajst-16785	234	9	dataset	dataset	ADJ
ajst-16785	234	10	indicators	indicator	NOUN
ajst-16785	234	11	machine	machine	NOUN
ajst-16785	234	12	learning	learn	VERB
ajst-16785	234	13	deep	deep	ADV
ajst-16785	234	14	learning	learning	NOUN
ajst-16785	234	15	proposed	propose	VERB
ajst-16785	234	16	method	method	NOUN
ajst-16785	234	17	dt	dt	AUX
ajst-16785	234	18	svm	svm	PROPN
ajst-16785	234	19	resnet34	resnet34	NOUN
ajst-16785	234	20	googlenet	googlenet	PROPN
ajst-16785	234	21	vgg16	vgg16	VERB
ajst-16785	234	22	vit	vit	PROPN
ajst-16785	234	23	icst	icst	PROPN
ajst-16785	234	24	u	u	PROPN
ajst-16785	234	25	l	l	NOUN
ajst-16785	234	26	f	f	PROPN
ajst-16785	234	27	s	s	PROPN
ajst-16785	234	28	l	l	NOUN
ajst-16785	234	29	d	d	X
ajst-16785	234	30	e	e	PROPN
ajst-16785	234	31	t	t	PROPN
ajst-16785	234	32	acc	acc	PROPN
ajst-16785	234	33	74.3	74.3	NUM
ajst-16785	234	34	%	%	NOUN
ajst-16785	234	35	75.8	75.8	NUM
ajst-16785	234	36	%	%	NOUN
ajst-16785	234	37	98.2	98.2	NUM
ajst-16785	234	38	%	%	NOUN
ajst-16785	234	39	96.5	96.5	NUM
ajst-16785	234	40	%	%	NOUN
ajst-16785	234	41	97.9	97.9	NUM
ajst-16785	234	42	%	%	NOUN
ajst-16785	234	43	93.8	93.8	NUM
ajst-16785	234	44	%	%	NOUN
ajst-16785	234	45	98.1	98.1	NUM
ajst-16785	234	46	%	%	NOUN
ajst-16785	234	47	flops	flop	NOUN
ajst-16785	234	48	—	—	PUNCT
ajst-16785	234	49	—	—	PUNCT
ajst-16785	234	50	1.172	1.172	NUM
ajst-16785	234	51	g	g	NOUN
ajst-16785	234	52	0.494	0.494	NUM
ajst-16785	234	53	g	g	ADP
ajst-16785	234	54	5.023	5.023	NUM
ajst-16785	234	55	g	g	ADP
ajst-16785	234	56	5.530	5.530	NUM
ajst-16785	234	57	g	g	NOUN
ajst-16785	234	58	0.0981	0.0981	NUM
ajst-16785	234	59	g	g	NOUN
ajst-16785	234	60	params	param	NOUN
ajst-16785	234	61	—	—	PUNCT
ajst-16785	234	62	—	—	PUNCT
ajst-16785	234	63	21.28	21.28	NUM
ajst-16785	234	64	m	m	NUM
ajst-16785	234	65	5.97	5.97	NUM
ajst-16785	234	66	m	m	NUM
ajst-16785	234	67	65.07	65.07	NUM
ajst-16785	234	68	m	m	NOUN
ajst-16785	234	69	85.22	85.22	NUM
ajst-16785	234	70	m	m	NUM
ajst-16785	234	71	1.35	1.35	NUM
ajst-16785	234	72	m	m	NOUN
ajst-16785	234	73	extraction	extraction	NOUN
ajst-16785	234	74	artificial	artificial	ADJ
ajst-16785	234	75	artificial	artificial	ADJ
ajst-16785	234	76	convolution	convolution	NOUN
ajst-16785	234	77	convolution	convolution	NOUN
ajst-16785	234	78	convolution	convolution	NOUN
ajst-16785	234	79	convolution	convolution	NOUN
ajst-16785	234	80	convolution	convolution	NOUN
ajst-16785	234	81	n	n	PROPN
ajst-16785	234	82	e	e	NOUN
ajst-16785	234	83	u	u	X
ajst-16785	234	84	-c	-c	PROPN
ajst-16785	234	85	l	l	PROPN
ajst-16785	234	86	s	s	PROPN
ajst-16785	234	87	acc	acc	PROPN
ajst-16785	234	88	—	—	PUNCT
ajst-16785	234	89	—	—	PUNCT
ajst-16785	234	90	99.2	99.2	NUM
ajst-16785	234	91	%	%	NOUN
ajst-16785	234	92	97.8	97.8	NUM
ajst-16785	234	93	%	%	NOUN
ajst-16785	234	94	98.3	98.3	NUM
ajst-16785	234	95	%	%	NOUN
ajst-16785	234	96	97.5	97.5	NUM
ajst-16785	234	97	%	%	NOUN
ajst-16785	234	98	99.8	99.8	NUM
ajst-16785	234	99	%	%	NOUN
ajst-16785	234	100	flops	flop	NOUN
ajst-16785	234	101	—	—	PUNCT
ajst-16785	234	102	—	—	PUNCT
ajst-16785	234	103	3.083	3.083	NUM
ajst-16785	234	104	g	g	NOUN
ajst-16785	234	105	1.160	1.160	NUM
ajst-16785	234	106	g	g	NOUN
ajst-16785	234	107	12.15	12.15	NUM
ajst-16785	234	108	g	g	NOUN
ajst-16785	234	109	12.34	12.34	NUM
ajst-16785	234	110	g	g	NOUN
ajst-16785	234	111	0.2042	0.2042	NUM
ajst-16785	234	112	g	g	NOUN
ajst-16785	234	113	params	param	NOUN
ajst-16785	234	114	—	—	PUNCT
ajst-16785	234	115	—	—	PUNCT
ajst-16785	234	116	21.28	21.28	NUM
ajst-16785	234	117	m	m	NUM
ajst-16785	234	118	5.97	5.97	NUM
ajst-16785	234	119	m	m	NUM
ajst-16785	234	120	65.07	65.07	NUM
ajst-16785	234	121	m	m	NOUN
ajst-16785	234	122	85.22	85.22	NUM
ajst-16785	234	123	m	m	NUM
ajst-16785	234	124	1.350	1.350	NUM
ajst-16785	234	125	m	m	NOUN
ajst-16785	234	126	extraction	extraction	NOUN
ajst-16785	234	127	—	—	PUNCT
ajst-16785	234	128	—	—	PUNCT
ajst-16785	234	129	convolution	convolution	NOUN
ajst-16785	234	130	convolution	convolution	NOUN
ajst-16785	234	131	convolution	convolution	NOUN
ajst-16785	234	132	convolution	convolution	NOUN
ajst-16785	234	133	convolution	convolution	NOUN
ajst-16785	234	134	6	6	NUM
ajst-16785	234	135	.	.	PUNCT
ajst-16785	235	1	conclusion	conclusion	NOUN
ajst-16785	235	2	in	in	ADP
ajst-16785	235	3	conclusion	conclusion	NOUN
ajst-16785	235	4	,	,	PUNCT
ajst-16785	235	5	the	the	DET
ajst-16785	235	6	proposed	propose	VERB
ajst-16785	235	7	inception	inception	NOUN
ajst-16785	235	8	fusion	fusion	NOUN
ajst-16785	235	9	swin	swin	PROPN
ajst-16785	235	10	transformer	transformer	NOUN
ajst-16785	235	11	-	-	PUNCT
ajst-16785	235	12	based	base	VERB
ajst-16785	235	13	method	method	NOUN
ajst-16785	235	14	has	have	AUX
ajst-16785	235	15	shown	show	VERB
ajst-16785	235	16	promising	promising	ADJ
ajst-16785	235	17	results	result	NOUN
ajst-16785	235	18	in	in	ADP
ajst-16785	235	19	the	the	DET
ajst-16785	235	20	recognition	recognition	NOUN
ajst-16785	235	21	of	of	ADP
ajst-16785	235	22	metal	metal	NOUN
ajst-16785	235	23	defect	defect	NOUN
ajst-16785	235	24	ultrasonic	ultrasonic	ADJ
ajst-16785	235	25	signal	signal	NOUN
ajst-16785	235	26	grayscale	grayscale	NOUN
ajst-16785	235	27	images	image	NOUN
ajst-16785	235	28	.	.	PUNCT
ajst-16785	236	1	by	by	ADP
ajst-16785	236	2	combining	combine	VERB
ajst-16785	236	3	the	the	DET
ajst-16785	236	4	inception	inception	ADJ
ajst-16785	236	5	structure	structure	NOUN
ajst-16785	236	6	and	and	CCONJ
ajst-16785	236	7	the	the	DET
ajst-16785	236	8	swin	swin	PROPN
ajst-16785	236	9	transformer	transformer	PROPN
ajst-16785	236	10	model	model	PROPN
ajst-16785	236	11	,	,	PUNCT
ajst-16785	236	12	the	the	DET
ajst-16785	236	13	method	method	NOUN
ajst-16785	236	14	can	can	AUX
ajst-16785	236	15	effectively	effectively	ADV
ajst-16785	236	16	extract	extract	VERB
ajst-16785	236	17	both	both	DET
ajst-16785	236	18	local	local	ADJ
ajst-16785	236	19	and	and	CCONJ
ajst-16785	236	20	global	global	ADJ
ajst-16785	236	21	features	feature	NOUN
ajst-16785	236	22	of	of	ADP
ajst-16785	236	23	the	the	DET
ajst-16785	236	24	defect	defect	ADJ
ajst-16785	236	25	echo	echo	NOUN
ajst-16785	236	26	signals	signal	NOUN
ajst-16785	236	27	,	,	PUNCT
ajst-16785	236	28	achieving	achieve	VERB
ajst-16785	236	29	high	high	ADJ
ajst-16785	236	30	recognition	recognition	NOUN
ajst-16785	236	31	accuracy	accuracy	NOUN
ajst-16785	236	32	with	with	ADP
ajst-16785	236	33	fewer	few	ADJ
ajst-16785	236	34	parameters	parameter	NOUN
ajst-16785	236	35	and	and	CCONJ
ajst-16785	236	36	computational	computational	ADJ
ajst-16785	236	37	cost	cost	NOUN
ajst-16785	236	38	compared	compare	VERB
ajst-16785	236	39	to	to	ADP
ajst-16785	236	40	classical	classical	ADJ
ajst-16785	236	41	deep	deep	ADJ
ajst-16785	236	42	learning	learning	NOUN
ajst-16785	236	43	models	model	NOUN
ajst-16785	236	44	.	.	PUNCT
ajst-16785	237	1	the	the	DET
ajst-16785	237	2	experiments	experiment	NOUN
ajst-16785	237	3	on	on	ADP
ajst-16785	237	4	the	the	DET
ajst-16785	237	5	ulfsl	ulfsl	NOUN
ajst-16785	237	6	-	-	PUNCT
ajst-16785	237	7	det	det	NOUN
ajst-16785	237	8	dataset	dataset	NOUN
ajst-16785	237	9	demonstrate	demonstrate	VERB
ajst-16785	237	10	the	the	DET
ajst-16785	237	11	effectiveness	effectiveness	NOUN
ajst-16785	237	12	of	of	ADP
ajst-16785	237	13	the	the	DET
ajst-16785	237	14	proposed	propose	VERB
ajst-16785	237	15	method	method	NOUN
ajst-16785	237	16	in	in	ADP
ajst-16785	237	17	the	the	DET
ajst-16785	237	18	ultrasonic	ultrasonic	ADJ
ajst-16785	237	19	detection	detection	NOUN
ajst-16785	237	20	defect	defect	NOUN
ajst-16785	237	21	task	task	NOUN
ajst-16785	237	22	,	,	PUNCT
ajst-16785	237	23	and	and	CCONJ
ajst-16785	237	24	the	the	DET
ajst-16785	237	25	experiments	experiment	NOUN
ajst-16785	237	26	on	on	ADP
ajst-16785	237	27	the	the	DET
ajst-16785	237	28	neu	neu	PROPN
ajst-16785	237	29	-	-	PUNCT
ajst-16785	237	30	cls	cls	NOUN
ajst-16785	237	31	dataset	dataset	NOUN
ajst-16785	237	32	show	show	VERB
ajst-16785	237	33	its	its	PRON
ajst-16785	237	34	generality	generality	NOUN
ajst-16785	237	35	in	in	ADP
ajst-16785	237	36	image	image	NOUN
ajst-16785	237	37	-	-	PUNCT
ajst-16785	237	38	based	base	VERB
ajst-16785	237	39	metal	metal	NOUN
ajst-16785	237	40	defect	defect	NOUN
ajst-16785	237	41	recognition	recognition	NOUN
ajst-16785	237	42	.	.	PUNCT
ajst-16785	238	1	these	these	DET
ajst-16785	238	2	results	result	NOUN
ajst-16785	238	3	indicate	indicate	VERB
ajst-16785	238	4	the	the	DET
ajst-16785	238	5	great	great	ADJ
ajst-16785	238	6	potential	potential	NOUN
ajst-16785	238	7	of	of	ADP
ajst-16785	238	8	the	the	DET
ajst-16785	238	9	proposed	propose	VERB
ajst-16785	238	10	method	method	NOUN
ajst-16785	238	11	in	in	ADP
ajst-16785	238	12	real	real	ADJ
ajst-16785	238	13	-	-	PUNCT
ajst-16785	238	14	time	time	NOUN
ajst-16785	238	15	detection	detection	NOUN
ajst-16785	238	16	fields	field	NOUN
ajst-16785	238	17	for	for	ADP
ajst-16785	238	18	metal	metal	NOUN
ajst-16785	238	19	defect	defect	NOUN
ajst-16785	238	20	ultrasonic	ultrasonic	ADJ
ajst-16785	238	21	signal	signal	NOUN
ajst-16785	238	22	grayscale	grayscale	NOUN
ajst-16785	238	23	images	image	NOUN
ajst-16785	238	24	and	and	CCONJ
ajst-16785	238	25	image	image	NOUN
ajst-16785	238	26	-	-	PUNCT
ajst-16785	238	27	based	base	VERB
ajst-16785	238	28	metal	metal	NOUN
ajst-16785	238	29	defects	defect	NOUN
ajst-16785	238	30	.	.	PUNCT
ajst-16785	239	1	acknowledgment	acknowledgment	NOUN
ajst-16785	239	2	this	this	DET
ajst-16785	239	3	work	work	NOUN
ajst-16785	239	4	was	be	AUX
ajst-16785	239	5	supported	support	VERB
ajst-16785	239	6	by	by	ADP
ajst-16785	239	7	the	the	DET
ajst-16785	239	8	sichuan	sichuan	PROPN
ajst-16785	239	9	provincial	provincial	ADJ
ajst-16785	239	10	science	science	NOUN
ajst-16785	239	11	and	and	CCONJ
ajst-16785	239	12	technology	technology	NOUN
ajst-16785	239	13	support	support	NOUN
ajst-16785	239	14	plan	plan	NOUN
ajst-16785	239	15	project	project	NOUN
ajst-16785	239	16	(	(	PUNCT
ajst-16785	239	17	2017fz0033	2017fz0033	NUM
ajst-16785	239	18	)	)	PUNCT
ajst-16785	239	19	,	,	PUNCT
ajst-16785	239	20	sichuan	sichuan	PROPN
ajst-16785	239	21	provincial	provincial	ADJ
ajst-16785	239	22	bureau	bureau	NOUN
ajst-16785	239	23	of	of	ADP
ajst-16785	239	24	market	market	NOUN
ajst-16785	239	25	supervision	supervision	NOUN
ajst-16785	239	26	and	and	CCONJ
ajst-16785	239	27	pipeline	pipeline	NOUN
ajst-16785	239	28	science	science	NOUN
ajst-16785	239	29	and	and	CCONJ
ajst-16785	239	30	technology	technology	NOUN
ajst-16785	239	31	plan	plan	NOUN
ajst-16785	239	32	project	project	NOUN
ajst-16785	239	33	(	(	PUNCT
ajst-16785	239	34	cscjz2022007	cscjz2022007	PROPN
ajst-16785	239	35	)	)	PUNCT
ajst-16785	239	36	and	and	CCONJ
ajst-16785	239	37	chengdu	chengdu	PROPN
ajst-16785	239	38	technology	technology	PROPN
ajst-16785	239	39	innovation	innovation	NOUN
ajst-16785	239	40	r&d	r&d	NOUN
ajst-16785	239	41	project	project	NOUN
ajst-16785	239	42	(	(	PUNCT
ajst-16785	239	43	1	1	NUM
ajst-16785	239	44	)	)	PUNCT
ajst-16785	239	45	.	.	PUNCT
ajst-16785	240	1	author	author	NOUN
ajst-16785	240	2	’s	’s	PART
ajst-16785	240	3	contributions	contribution	NOUN
ajst-16785	240	4	donglin	donglin	PROPN
ajst-16785	240	5	tang	tang	PROPN
ajst-16785	240	6	and	and	CCONJ
ajst-16785	240	7	yunliang	yunliang	PROPN
ajst-16785	240	8	zhao	zhao	PROPN
ajst-16785	240	9	completed	complete	VERB
ajst-16785	240	10	the	the	DET
ajst-16785	240	11	research	research	NOUN
ajst-16785	240	12	and	and	CCONJ
ajst-16785	240	13	implemented	implement	VERB
ajst-16785	240	14	the	the	DET
ajst-16785	240	15	network	network	NOUN
ajst-16785	240	16	.	.	PUNCT
ajst-16785	241	1	yuanyuan	yuanyuan	PROPN
ajst-16785	241	2	he	he	PRON
ajst-16785	241	3	,	,	PUNCT
ajst-16785	241	4	henghui	henghui	PROPN
ajst-16785	241	5	li	li	PROPN
ajst-16785	241	6	and	and	CCONJ
ajst-16785	241	7	simeng	simeng	PROPN
ajst-16785	241	8	yi	yi	PROPN
ajst-16785	241	9	contributed	contribute	VERB
ajst-16785	241	10	to	to	ADP
ajst-16785	241	11	the	the	DET
ajst-16785	241	12	ulfsl	ulfsl	NOUN
ajst-16785	241	13	-	-	PUNCT
ajst-16785	241	14	det	det	NOUN
ajst-16785	241	15	dataset	dataset	NOUN
ajst-16785	241	16	and	and	CCONJ
ajst-16785	241	17	provided	provide	VERB
ajst-16785	241	18	meaningful	meaningful	ADJ
ajst-16785	241	19	discussion	discussion	NOUN
ajst-16785	241	20	.	.	PUNCT
ajst-16785	242	1	funding	fund	VERB
ajst-16785	242	2	this	this	DET
ajst-16785	242	3	study	study	NOUN
ajst-16785	242	4	was	be	AUX
ajst-16785	242	5	supported	support	VERB
ajst-16785	242	6	by	by	ADP
ajst-16785	242	7	the	the	DET
ajst-16785	242	8	sichuan	sichuan	PROPN
ajst-16785	242	9	provincial	provincial	ADJ
ajst-16785	242	10	science	science	NOUN
ajst-16785	242	11	and	and	CCONJ
ajst-16785	242	12	technology	technology	NOUN
ajst-16785	242	13	support	support	NOUN
ajst-16785	242	14	plan	plan	NOUN
ajst-16785	242	15	project	project	NOUN
ajst-16785	242	16	(	(	PUNCT
ajst-16785	242	17	2017fz0033	2017fz0033	NUM
ajst-16785	242	18	)	)	PUNCT
ajst-16785	242	19	,	,	PUNCT
ajst-16785	242	20	sichuan	sichuan	PROPN
ajst-16785	242	21	provincial	provincial	ADJ
ajst-16785	242	22	bureau	bureau	NOUN
ajst-16785	242	23	of	of	ADP
ajst-16785	242	24	market	market	NOUN
ajst-16785	242	25	supervision	supervision	NOUN
ajst-16785	242	26	and	and	CCONJ
ajst-16785	242	27	pipeline	pipeline	NOUN
ajst-16785	242	28	science	science	NOUN
ajst-16785	242	29	and	and	CCONJ
ajst-16785	242	30	technology	technology	NOUN
ajst-16785	242	31	plan	plan	NOUN
ajst-16785	242	32	project	project	NOUN
ajst-16785	242	33	(	(	PUNCT
ajst-16785	242	34	cscjz2022007	cscjz2022007	PROPN
ajst-16785	242	35	)	)	PUNCT
ajst-16785	242	36	and	and	CCONJ
ajst-16785	242	37	chengdu	chengdu	PROPN
ajst-16785	242	38	technology	technology	PROPN
ajst-16785	242	39	innovation	innovation	NOUN
ajst-16785	242	40	r&d	r&d	NOUN
ajst-16785	242	41	project	project	NOUN
ajst-16785	242	42	(	(	PUNCT
ajst-16785	242	43	2018	2018	NUM
ajst-16785	242	44	-	-	PUNCT
ajst-16785	242	45	yf05	yf05	PROPN
ajst-16785	242	46	-	-	PUNCT
ajst-16785	242	47	00201	00201	NUM
ajst-16785	242	48	-	-	PUNCT
ajst-16785	242	49	gx	gx	PROPN
ajst-16785	242	50	)	)	PUNCT
ajst-16785	242	51	.	.	PUNCT
ajst-16785	243	1	availability	availability	NOUN
ajst-16785	243	2	of	of	ADP
ajst-16785	243	3	data	datum	NOUN
ajst-16785	243	4	and	and	CCONJ
ajst-16785	243	5	code	code	VERB
ajst-16785	243	6	the	the	DET
ajst-16785	243	7	neu	neu	PROPN
ajst-16785	243	8	-	-	PUNCT
ajst-16785	243	9	cls	cls	NOUN
ajst-16785	243	10	dataset	dataset	NOUN
ajst-16785	243	11	can	can	AUX
ajst-16785	243	12	be	be	AUX
ajst-16785	243	13	as	as	ADP
ajst-16785	243	14	a	a	DET
ajst-16785	243	15	public	public	ADJ
ajst-16785	243	16	dataset	dataset	NOUN
ajst-16785	243	17	downloaded	download	VERB
ajst-16785	243	18	via	via	ADP
ajst-16785	243	19	the	the	DET
ajst-16785	243	20	link	link	NOUN
ajst-16785	243	21	http://faculty.neu.edu.cn/yunhyan/neu_surface_defect_data	http://faculty.neu.edu.cn/yunhyan/neu_surface_defect_data	INTJ
ajst-16785	244	1	base.html	base.html	NOUN
ajst-16785	244	2	.	.	PUNCT
ajst-16785	245	1	the	the	DET
ajst-16785	245	2	ulfsl	ulfsl	NOUN
ajst-16785	245	3	-	-	PUNCT
ajst-16785	245	4	det	det	NOUN
ajst-16785	245	5	dataset	dataset	NOUN
ajst-16785	245	6	can	can	AUX
ajst-16785	245	7	not	not	PART
ajst-16785	245	8	be	be	AUX
ajst-16785	245	9	shared	share	VERB
ajst-16785	245	10	at	at	ADP
ajst-16785	245	11	this	this	DET
ajst-16785	245	12	time	time	NOUN
ajst-16785	245	13	due	due	ADP
ajst-16785	245	14	to	to	ADP
ajst-16785	245	15	the	the	DET
ajst-16785	245	16	need	need	NOUN
ajst-16785	245	17	for	for	ADP
ajst-16785	245	18	other	other	ADJ
ajst-16785	245	19	company	company	NOUN
ajst-16785	245	20	project	project	NOUN
ajst-16785	245	21	.	.	PUNCT
ajst-16785	246	1	the	the	DET
ajst-16785	246	2	code	code	NOUN
ajst-16785	246	3	can	can	AUX
ajst-16785	246	4	be	be	AUX
ajst-16785	246	5	shared	share	VERB
ajst-16785	246	6	by	by	ADP
ajst-16785	246	7	contacting	contact	VERB
ajst-16785	246	8	email	email	NOUN
ajst-16785	246	9	1490608930@qq.com	1490608930@qq.com	NUM
ajst-16785	246	10	.	.	PUNCT
ajst-16785	247	1	declarations	declaration	NOUN
ajst-16785	247	2	ethics	ethic	NOUN
ajst-16785	247	3	approval	approval	VERB
ajst-16785	247	4	the	the	DET
ajst-16785	247	5	authors	author	NOUN
ajst-16785	247	6	declare	declare	VERB
ajst-16785	247	7	that	that	SCONJ
ajst-16785	247	8	this	this	DET
ajst-16785	247	9	manuscript	manuscript	NOUN
ajst-16785	247	10	was	be	AUX
ajst-16785	247	11	not	not	PART
ajst-16785	247	12	submitted	submit	VERB
ajst-16785	247	13	to	to	ADP
ajst-16785	247	14	more	more	ADJ
ajst-16785	247	15	than	than	ADP
ajst-16785	247	16	one	one	NUM
ajst-16785	247	17	journal	journal	NOUN
ajst-16785	247	18	for	for	ADP
ajst-16785	247	19	simultaneous	simultaneous	ADJ
ajst-16785	247	20	consideration	consideration	NOUN
ajst-16785	247	21	.	.	PUNCT
ajst-16785	248	1	the	the	DET
ajst-16785	248	2	submitted	submit	VERB
ajst-16785	248	3	work	work	NOUN
ajst-16785	248	4	is	be	AUX
ajst-16785	248	5	original	original	ADJ
ajst-16785	248	6	and	and	CCONJ
ajst-16785	248	7	not	not	PART
ajst-16785	248	8	has	have	AUX
ajst-16785	248	9	been	be	AUX
ajst-16785	248	10	published	publish	VERB
ajst-16785	248	11	elsewhere	elsewhere	ADV
ajst-16785	248	12	in	in	ADP
ajst-16785	248	13	any	any	DET
ajst-16785	248	14	form	form	NOUN
ajst-16785	248	15	or	or	CCONJ
ajst-16785	248	16	language	language	NOUN
ajst-16785	248	17	competing	compete	VERB
ajst-16785	248	18	interests	interest	NOUN
ajst-16785	249	1	the	the	DET
ajst-16785	249	2	authors	author	NOUN
ajst-16785	249	3	declare	declare	VERB
ajst-16785	249	4	that	that	SCONJ
ajst-16785	249	5	they	they	PRON
ajst-16785	249	6	have	have	VERB
ajst-16785	249	7	no	no	DET
ajst-16785	249	8	conflict	conflict	NOUN
ajst-16785	249	9	of	of	ADP
ajst-16785	249	10	interest	interest	NOUN
ajst-16785	249	11	.	.	PUNCT
ajst-16785	250	1	references	reference	NOUN
ajst-16785	250	2	[	[	X
ajst-16785	250	3	1	1	NUM
ajst-16785	250	4	]	]	PUNCT
ajst-16785	250	5	czimmermann	czimmermann	PROPN
ajst-16785	250	6	t	t	PROPN
ajst-16785	250	7	,	,	PUNCT
ajst-16785	250	8	ciuti	ciuti	PROPN
ajst-16785	250	9	g	g	PROPN
ajst-16785	250	10	,	,	PUNCT
ajst-16785	250	11	milazzo	milazzo	PROPN
ajst-16785	250	12	m	m	PROPN
ajst-16785	250	13	,	,	PUNCT
ajst-16785	250	14	chiurazzi	chiurazzi	PROPN
ajst-16785	250	15	m	m	PROPN
ajst-16785	250	16	,	,	PUNCT
ajst-16785	250	17	roccella	roccella	PROPN
ajst-16785	250	18	s	s	PART
ajst-16785	250	19	,	,	PUNCT
ajst-16785	250	20	oddo	oddo	VERB
ajst-16785	250	21	cm	cm	PROPN
ajst-16785	250	22	,	,	PUNCT
ajst-16785	250	23	dario	dario	NOUN
ajst-16785	250	24	p	p	PROPN
ajst-16785	250	25	(	(	PUNCT
ajst-16785	250	26	2020	2020	NUM
ajst-16785	250	27	)	)	PUNCT
ajst-16785	250	28	visual	visual	ADJ
ajst-16785	250	29	-	-	PUNCT
ajst-16785	250	30	based	base	VERB
ajst-16785	250	31	defect	defect	NOUN
ajst-16785	250	32	detection	detection	NOUN
ajst-16785	250	33	and	and	CCONJ
ajst-16785	250	34	classification	classification	NOUN
ajst-16785	250	35	approaches	approach	NOUN
ajst-16785	250	36	for	for	ADP
ajst-16785	250	37	industrial	industrial	ADJ
ajst-16785	250	38	applications	application	NOUN
ajst-16785	250	39	-	-	PUNCT
ajst-16785	250	40	a	a	DET
ajst-16785	250	41	survey	survey	NOUN
ajst-16785	250	42	.	.	PUNCT
ajst-16785	251	1	sensors	sensor	NOUN
ajst-16785	251	2	20:1459	20:1459	NUM
ajst-16785	251	3	.	.	PUNCT
ajst-16785	252	1	https://doi.org/10.3390/s20051459	https://doi.org/10.3390/s20051459	NUM
ajst-16785	253	1	[	[	X
ajst-16785	253	2	2	2	NUM
ajst-16785	253	3	]	]	X
ajst-16785	253	4	fang	fang	X
ajst-16785	253	5	x	x	X
ajst-16785	253	6	,	,	PUNCT
ajst-16785	253	7	luo	luo	PROPN
ajst-16785	253	8	q	q	PROPN
ajst-16785	253	9	,	,	PUNCT
ajst-16785	253	10	zhou	zhou	PROPN
ajst-16785	253	11	b	b	PROPN
ajst-16785	253	12	,	,	PUNCT
ajst-16785	253	13	li	li	PROPN
ajst-16785	253	14	c	c	PROPN
ajst-16785	253	15	,	,	PUNCT
ajst-16785	253	16	tian	tian	ADJ
ajst-16785	253	17	l	l	NOUN
ajst-16785	253	18	(	(	PUNCT
ajst-16785	253	19	2020	2020	NUM
ajst-16785	253	20	)	)	PUNCT
ajst-16785	253	21	research	research	NOUN
ajst-16785	253	22	progress	progress	NOUN
ajst-16785	253	23	of	of	ADP
ajst-16785	253	24	automated	automate	VERB
ajst-16785	253	25	visual	visual	ADJ
ajst-16785	253	26	surface	surface	NOUN
ajst-16785	253	27	defect	defect	NOUN
ajst-16785	253	28	detection	detection	NOUN
ajst-16785	253	29	for	for	ADP
ajst-16785	253	30	industrial	industrial	ADJ
ajst-16785	253	31	metal	metal	NOUN
ajst-16785	253	32	planar	planar	ADJ
ajst-16785	253	33	materials	material	NOUN
ajst-16785	253	34	.	.	PUNCT
ajst-16785	253	35	sensors	sensor	NOUN
ajst-16785	253	36	20:5136	20:5136	NUM
ajst-16785	253	37	.	.	PUNCT
ajst-16785	254	1	https://doi.org/10.3390/s20185136	https://doi.org/10.3390/s20185136	NUM
ajst-16785	255	1	[	[	X
ajst-16785	255	2	3	3	NUM
ajst-16785	255	3	]	]	X
ajst-16785	255	4	ming	ming	NOUN
ajst-16785	255	5	-	-	PUNCT
ajst-16785	255	6	jian	jian	PROPN
ajst-16785	255	7	s	s	PROPN
ajst-16785	255	8	,	,	PUNCT
ajst-16785	255	9	ting	ting	PROPN
ajst-16785	255	10	l	l	PROPN
ajst-16785	255	11	,	,	PUNCT
ajst-16785	255	12	xing	xing	PROPN
ajst-16785	255	13	-	-	PUNCT
ajst-16785	255	14	zhen	zhen	PROPN
ajst-16785	255	15	c	c	PROPN
ajst-16785	255	16	,	,	PUNCT
ajst-16785	255	17	de	de	PROPN
ajst-16785	255	18	-	-	NOUN
ajst-16785	255	19	ying	ying	ADJ
ajst-16785	255	20	c	c	NOUN
ajst-16785	255	21	,	,	PUNCT
ajst-16785	255	22	feng	feng	PROPN
ajst-16785	255	23	-	-	PUNCT
ajst-16785	255	24	gang	gang	PROPN
ajst-16785	255	25	y	y	PROPN
ajst-16785	255	26	,	,	PUNCT
ajst-16785	255	27	nai	nai	PROPN
ajst-16785	255	28	-	-	PROPN
ajst-16785	255	29	zhang	zhang	PROPN
ajst-16785	255	30	f	f	PROPN
ajst-16785	255	31	(	(	PUNCT
ajst-16785	255	32	2016	2016	NUM
ajst-16785	255	33	)	)	PUNCT
ajst-16785	255	34	nondestructive	nondestructive	ADJ
ajst-16785	255	35	detecting	detecting	NOUN
ajst-16785	255	36	method	method	NOUN
ajst-16785	255	37	for	for	ADP
ajst-16785	255	38	metal	metal	NOUN
ajst-16785	255	39	material	material	NOUN
ajst-16785	255	40	defects	defect	NOUN
ajst-16785	255	41	based	base	VERB
ajst-16785	255	42	on	on	ADP
ajst-16785	255	43	multimodal	multimodal	NOUN
ajst-16785	255	44	signals	signal	NOUN
ajst-16785	255	45	.	.	PUNCT
ajst-16785	256	1	acta	acta	PROPN
ajst-16785	256	2	phys	phys	PROPN
ajst-16785	256	3	sin	sin	VERB
ajst-16785	256	4	65:167802	65:167802	ADJ
ajst-16785	256	5	.	.	PUNCT
ajst-16785	257	1	https://doi.org/10.7498/aps.65.167802	https://doi.org/10.7498/aps.65.167802	NOUN
ajst-16785	258	1	[	[	X
ajst-16785	258	2	4	4	NUM
ajst-16785	258	3	]	]	X
ajst-16785	258	4	mensah	mensah	PROPN
ajst-16785	258	5	a	a	PRON
ajst-16785	258	6	,	,	PUNCT
ajst-16785	258	7	sriramula	sriramula	NOUN
ajst-16785	258	8	s	s	NOUN
ajst-16785	258	9	(	(	PUNCT
ajst-16785	258	10	2022	2022	NUM
ajst-16785	258	11	)	)	PUNCT
ajst-16785	258	12	machine	machine	NOUN
ajst-16785	258	13	learning	learning	NOUN
ajst-16785	258	14	based	base	VERB
ajst-16785	258	15	integrity	integrity	NOUN
ajst-16785	258	16	decision	decision	NOUN
ajst-16785	258	17	management	management	NOUN
ajst-16785	258	18	of	of	ADP
ajst-16785	258	19	pipeline	pipeline	NOUN
ajst-16785	258	20	corrosion	corrosion	NOUN
ajst-16785	258	21	clusters	cluster	NOUN
ajst-16785	258	22	.	.	PUNCT
ajst-16785	259	1	in	in	ADP
ajst-16785	259	2	:	:	PUNCT
ajst-16785	259	3	2022	2022	NUM
ajst-16785	259	4	international	international	ADJ
ajst-16785	259	5	conference	conference	NOUN
ajst-16785	259	6	on	on	ADP
ajst-16785	259	7	decision	decision	NOUN
ajst-16785	259	8	aid	aid	NOUN
ajst-16785	259	9	sciences	science	NOUN
ajst-16785	259	10	and	and	CCONJ
ajst-16785	259	11	applications	application	NOUN
ajst-16785	259	12	(	(	PUNCT
ajst-16785	259	13	dasa	dasa	PROPN
ajst-16785	259	14	)	)	PUNCT
ajst-16785	259	15	.	.	PUNCT
ajst-16785	260	1	ieee	ieee	PROPN
ajst-16785	260	2	,	,	PUNCT
ajst-16785	260	3	new	new	PROPN
ajst-16785	260	4	york	york	PROPN
ajst-16785	260	5	,	,	PUNCT
ajst-16785	260	6	pp	pp	PROPN
ajst-16785	260	7	795–799	795–799	NUM
ajst-16785	261	1	[	[	X
ajst-16785	261	2	5	5	NUM
ajst-16785	261	3	]	]	PUNCT
ajst-16785	261	4	lin	lin	PROPN
ajst-16785	261	5	j	j	PROPN
ajst-16785	261	6	,	,	PUNCT
ajst-16785	261	7	yang	yang	PROPN
ajst-16785	261	8	j	j	PROPN
ajst-16785	261	9	,	,	PUNCT
ajst-16785	261	10	huang	huang	PROPN
ajst-16785	261	11	y	y	PROPN
ajst-16785	261	12	,	,	PUNCT
ajst-16785	261	13	lin	lin	PROPN
ajst-16785	261	14	x	x	X
ajst-16785	261	15	(	(	PUNCT
ajst-16785	261	16	2021	2021	NUM
ajst-16785	261	17	)	)	PUNCT
ajst-16785	261	18	defect	defect	VERB
ajst-16785	261	19	identification	identification	NOUN
ajst-16785	261	20	of	of	ADP
ajst-16785	261	21	metal	metal	NOUN
ajst-16785	261	22	additive	additive	ADJ
ajst-16785	261	23	manufacturing	manufacturing	NOUN
ajst-16785	261	24	parts	part	NOUN
ajst-16785	261	25	based	base	VERB
ajst-16785	261	26	on	on	ADP
ajst-16785	261	27	laser	laser	NOUN
ajst-16785	261	28	-	-	PUNCT
ajst-16785	261	29	induced	induce	VERB
ajst-16785	261	30	breakdown	breakdown	NOUN
ajst-16785	261	31	spectroscopy	spectroscopy	NOUN
ajst-16785	261	32	and	and	CCONJ
ajst-16785	261	33	machine	machine	NOUN
ajst-16785	261	34	learning	learning	NOUN
ajst-16785	261	35	.	.	PUNCT
ajst-16785	262	1	appl	appl	PROPN
ajst-16785	262	2	phys	phy	NOUN
ajst-16785	262	3	blasers	blaser	NOUN
ajst-16785	262	4	opt	opt	VERB
ajst-16785	262	5	127:173	127:173	PROPN
ajst-16785	262	6	.	.	PUNCT
ajst-16785	263	1	https://doi.org/10.1007/s00340-02107725-3	https://doi.org/10.1007/s00340-02107725-3	PROPN
ajst-16785	264	1	[	[	X
ajst-16785	264	2	6	6	NUM
ajst-16785	264	3	]	]	PUNCT
ajst-16785	264	4	gaja	gaja	PROPN
ajst-16785	264	5	h	h	PROPN
ajst-16785	264	6	,	,	PUNCT
ajst-16785	264	7	liou	liou	ADJ
ajst-16785	264	8	f	f	PROPN
ajst-16785	264	9	(	(	PUNCT
ajst-16785	264	10	2018	2018	NUM
ajst-16785	264	11	)	)	PUNCT
ajst-16785	264	12	defect	defect	VERB
ajst-16785	264	13	classification	classification	NOUN
ajst-16785	264	14	of	of	ADP
ajst-16785	264	15	laser	laser	NOUN
ajst-16785	264	16	metal	metal	NOUN
ajst-16785	264	17	deposition	deposition	NOUN
ajst-16785	264	18	using	use	VERB
ajst-16785	264	19	logistic	logistic	ADJ
ajst-16785	264	20	regression	regression	NOUN
ajst-16785	264	21	and	and	CCONJ
ajst-16785	264	22	artificial	artificial	ADJ
ajst-16785	264	23	neural	neural	ADJ
ajst-16785	264	24	networks	network	NOUN
ajst-16785	264	25	for	for	ADP
ajst-16785	264	26	pattern	pattern	NOUN
ajst-16785	264	27	recognition	recognition	NOUN
ajst-16785	264	28	.	.	PUNCT
ajst-16785	265	1	int	int	PROPN
ajst-16785	265	2	j	j	PROPN
ajst-16785	265	3	adv	adv	PROPN
ajst-16785	265	4	manuf	manuf	PROPN
ajst-16785	265	5	technol	technol	PROPN
ajst-16785	265	6	94:315–326	94:315–326	PROPN
ajst-16785	265	7	.	.	PUNCT
ajst-16785	266	1	https://doi.org/10.1007/s00170-017-0878-9	https://doi.org/10.1007/s00170-017-0878-9	X
ajst-16785	267	1	[	[	X
ajst-16785	267	2	7	7	X
ajst-16785	267	3	]	]	X
ajst-16785	267	4	zhang	zhang	PROPN
ajst-16785	267	5	y	y	PROPN
ajst-16785	267	6	,	,	PUNCT
ajst-16785	267	7	chan	chan	PROPN
ajst-16785	267	8	w	w	PROPN
ajst-16785	267	9	,	,	PUNCT
ajst-16785	267	10	jaitly	jaitly	ADV
ajst-16785	267	11	n	n	CCONJ
ajst-16785	267	12	(	(	PUNCT
ajst-16785	267	13	2017	2017	NUM
ajst-16785	267	14	)	)	PUNCT
ajst-16785	267	15	very	very	ADV
ajst-16785	267	16	deep	deep	ADJ
ajst-16785	267	17	convolutional	convolutional	ADJ
ajst-16785	267	18	networks	network	NOUN
ajst-16785	267	19	for	for	ADP
ajst-16785	267	20	end	end	NOUN
ajst-16785	267	21	-	-	PUNCT
ajst-16785	267	22	to	to	ADP
ajst-16785	267	23	-	-	PUNCT
ajst-16785	267	24	end	end	NOUN
ajst-16785	267	25	speech	speech	NOUN
ajst-16785	267	26	recognition	recognition	NOUN
ajst-16785	267	27	.	.	PUNCT
ajst-16785	268	1	in	in	ADP
ajst-16785	268	2	:	:	PUNCT
ajst-16785	268	3	2017	2017	NUM
ajst-16785	268	4	ieee	ieee	NOUN
ajst-16785	268	5	international	international	ADJ
ajst-16785	268	6	conference	conference	NOUN
ajst-16785	268	7	on	on	ADP
ajst-16785	268	8	acoustics	acoustic	NOUN
ajst-16785	268	9	,	,	PUNCT
ajst-16785	268	10	speech	speech	NOUN
ajst-16785	268	11	and	and	CCONJ
ajst-16785	268	12	signal	signal	NOUN
ajst-16785	268	13	processing	processing	NOUN
ajst-16785	268	14	(	(	PUNCT
ajst-16785	268	15	icassp	icassp	PROPN
ajst-16785	268	16	)	)	PUNCT
ajst-16785	268	17	.	.	PUNCT
ajst-16785	269	1	ieee	ieee	PROPN
ajst-16785	269	2	,	,	PUNCT
ajst-16785	269	3	new	new	PROPN
ajst-16785	269	4	york	york	PROPN
ajst-16785	269	5	,	,	PUNCT
ajst-16785	269	6	pp	pp	PROPN
ajst-16785	269	7	4845–4849	4845–4849	NUM
ajst-16785	269	8	[	[	SYM
ajst-16785	269	9	8	8	NUM
ajst-16785	269	10	]	]	PUNCT
ajst-16785	269	11	szegedy	szegedy	VERB
ajst-16785	269	12	c	c	PROPN
ajst-16785	269	13	,	,	PUNCT
ajst-16785	269	14	liu	liu	PROPN
ajst-16785	269	15	w	w	PROPN
ajst-16785	269	16	,	,	PUNCT
ajst-16785	269	17	jia	jia	PROPN
ajst-16785	269	18	y	y	PROPN
ajst-16785	269	19	,	,	PUNCT
ajst-16785	269	20	sermanet	sermanet	NOUN
ajst-16785	269	21	p	p	NOUN
ajst-16785	269	22	,	,	PUNCT
ajst-16785	269	23	reed	reed	PROPN
ajst-16785	269	24	s	s	PROPN
ajst-16785	269	25	,	,	PUNCT
ajst-16785	269	26	anguelov	anguelov	NOUN
ajst-16785	269	27	d	d	NOUN
ajst-16785	269	28	,	,	PUNCT
ajst-16785	269	29	erhan	erhan	ADP
ajst-16785	269	30	d	d	PROPN
ajst-16785	269	31	,	,	PUNCT
ajst-16785	269	32	vanhoucke	vanhoucke	NOUN
ajst-16785	269	33	v	v	NOUN
ajst-16785	269	34	,	,	PUNCT
ajst-16785	269	35	rabinovich	rabinovich	VERB
ajst-16785	269	36	a	a	DET
ajst-16785	269	37	(	(	PUNCT
ajst-16785	269	38	2015	2015	NUM
ajst-16785	269	39	)	)	PUNCT
ajst-16785	269	40	going	go	VERB
ajst-16785	269	41	deeper	deeply	ADV
ajst-16785	269	42	with	with	ADP
ajst-16785	269	43	convolutions	convolution	NOUN
ajst-16785	269	44	.	.	PUNCT
ajst-16785	270	1	in	in	ADP
ajst-16785	270	2	:	:	PUNCT
ajst-16785	270	3	2015	2015	NUM
ajst-16785	270	4	ieee	ieee	NOUN
ajst-16785	270	5	conference	conference	NOUN
ajst-16785	270	6	on	on	ADP
ajst-16785	270	7	computer	computer	NOUN
ajst-16785	270	8	vision	vision	NOUN
ajst-16785	270	9	and	and	CCONJ
ajst-16785	270	10	pattern	pattern	NOUN
ajst-16785	270	11	recognition	recognition	NOUN
ajst-16785	270	12	(	(	PUNCT
ajst-16785	270	13	cvpr	cvpr	NOUN
ajst-16785	270	14	)	)	PUNCT
ajst-16785	270	15	.	.	PUNCT
ajst-16785	271	1	ieee	ieee	PROPN
ajst-16785	271	2	,	,	PUNCT
ajst-16785	271	3	new	new	PROPN
ajst-16785	271	4	york	york	PROPN
ajst-16785	271	5	,	,	PUNCT
ajst-16785	271	6	pp	pp	ADP
ajst-16785	271	7	1	1	NUM
ajst-16785	271	8	–	–	PUNCT
ajst-16785	271	9	9	9	NUM
ajst-16785	271	10	[	[	SYM
ajst-16785	271	11	9	9	NUM
ajst-16785	271	12	]	]	PUNCT
ajst-16785	271	13	he	he	PRON
ajst-16785	271	14	k	k	PROPN
ajst-16785	271	15	,	,	PUNCT
ajst-16785	271	16	zhang	zhang	PROPN
ajst-16785	271	17	x	x	PROPN
ajst-16785	271	18	,	,	PUNCT
ajst-16785	271	19	ren	ren	PROPN
ajst-16785	271	20	s	s	PROPN
ajst-16785	271	21	,	,	PUNCT
ajst-16785	271	22	sun	sun	PROPN
ajst-16785	271	23	j	j	PROPN
ajst-16785	271	24	(	(	PUNCT
ajst-16785	271	25	2016	2016	NUM
ajst-16785	271	26	)	)	PUNCT
ajst-16785	271	27	deep	deep	ADJ
ajst-16785	271	28	residual	residual	ADJ
ajst-16785	271	29	learning	learning	NOUN
ajst-16785	271	30	for	for	ADP
ajst-16785	271	31	image	image	NOUN
ajst-16785	271	32	recognition	recognition	NOUN
ajst-16785	271	33	.	.	PUNCT
ajst-16785	272	1	in	in	ADP
ajst-16785	272	2	:	:	PUNCT
ajst-16785	272	3	2016	2016	NUM
ajst-16785	272	4	ieee	ieee	NOUN
ajst-16785	272	5	conference	conference	NOUN
ajst-16785	272	6	on	on	ADP
ajst-16785	272	7	185	185	NUM
ajst-16785	272	8	computer	computer	NOUN
ajst-16785	272	9	vision	vision	NOUN
ajst-16785	272	10	and	and	CCONJ
ajst-16785	272	11	pattern	pattern	NOUN
ajst-16785	272	12	recognition	recognition	NOUN
ajst-16785	272	13	(	(	PUNCT
ajst-16785	272	14	cvpr	cvpr	NOUN
ajst-16785	272	15	)	)	PUNCT
ajst-16785	272	16	.	.	PUNCT
ajst-16785	273	1	pp	pp	ADP
ajst-16785	273	2	770	770	NUM
ajst-16785	273	3	–	–	PUNCT
ajst-16785	273	4	778	778	NUM
ajst-16785	274	1	[	[	SYM
ajst-16785	274	2	10	10	NUM
ajst-16785	274	3	]	]	PUNCT
ajst-16785	274	4	balcioglu	balcioglu	PROPN
ajst-16785	274	5	ys	ys	PROPN
ajst-16785	274	6	,	,	PUNCT
ajst-16785	274	7	sezen	sezen	PROPN
ajst-16785	274	8	b	b	PROPN
ajst-16785	274	9	,	,	PUNCT
ajst-16785	274	10	gok	gok	PROPN
ajst-16785	274	11	ms	ms	PROPN
ajst-16785	274	12	,	,	PUNCT
ajst-16785	274	13	tunca	tunca	PROPN
ajst-16785	274	14	s	s	X
ajst-16785	274	15	(	(	PUNCT
ajst-16785	274	16	2022	2022	NUM
ajst-16785	274	17	)	)	PUNCT
ajst-16785	274	18	image	image	NOUN
ajst-16785	274	19	processing	processing	NOUN
ajst-16785	274	20	with	with	ADP
ajst-16785	274	21	deep	deep	ADJ
ajst-16785	274	22	learning	learning	NOUN
ajst-16785	274	23	:	:	PUNCT
ajst-16785	274	24	surface	surface	NOUN
ajst-16785	274	25	defect	defect	NOUN
ajst-16785	274	26	detection	detection	NOUN
ajst-16785	274	27	of	of	ADP
ajst-16785	274	28	metal	metal	NOUN
ajst-16785	274	29	gears	gear	NOUN
ajst-16785	274	30	through	through	ADP
ajst-16785	274	31	deep	deep	ADJ
ajst-16785	274	32	learning	learning	NOUN
ajst-16785	274	33	.	.	PUNCT
ajst-16785	275	1	mater	mater	PROPN
ajst-16785	275	2	eval	eval	PROPN
ajst-16785	275	3	80:44–53	80:44–53	PROPN
ajst-16785	275	4	.	.	PUNCT
ajst-16785	276	1	https://doi.org/10.32548/2022.me-04230	https://doi.org/10.32548/2022.me-04230	PROPN
ajst-16785	276	2	[	[	X
ajst-16785	276	3	11	11	NUM
ajst-16785	276	4	]	]	X
ajst-16785	276	5	meng	meng	PROPN
ajst-16785	276	6	t	t	PROPN
ajst-16785	276	7	,	,	PUNCT
ajst-16785	276	8	tao	tao	PROPN
ajst-16785	276	9	y	y	PROPN
ajst-16785	276	10	,	,	PUNCT
ajst-16785	276	11	chen	chen	PROPN
ajst-16785	276	12	z	z	PROPN
ajst-16785	276	13	,	,	PUNCT
ajst-16785	276	14	avila	avila	PROPN
ajst-16785	276	15	jrs	jrs	PROPN
ajst-16785	276	16	,	,	PUNCT
ajst-16785	276	17	ran	run	VERB
ajst-16785	276	18	q	q	PROPN
ajst-16785	276	19	,	,	PUNCT
ajst-16785	276	20	shao	shao	PROPN
ajst-16785	276	21	y	y	PROPN
ajst-16785	276	22	,	,	PUNCT
ajst-16785	276	23	huang	huang	PROPN
ajst-16785	276	24	r	r	PROPN
ajst-16785	276	25	,	,	PUNCT
ajst-16785	276	26	xie	xie	PROPN
ajst-16785	276	27	y	y	PROPN
ajst-16785	276	28	,	,	PUNCT
ajst-16785	276	29	zhao	zhao	PROPN
ajst-16785	276	30	q	q	PROPN
ajst-16785	276	31	,	,	PUNCT
ajst-16785	276	32	zhang	zhang	PROPN
ajst-16785	276	33	z	z	PROPN
ajst-16785	276	34	,	,	PUNCT
ajst-16785	276	35	yin	yin	PROPN
ajst-16785	276	36	h	h	PROPN
ajst-16785	276	37	,	,	PUNCT
ajst-16785	276	38	peyton	peyton	PROPN
ajst-16785	276	39	aj	aj	PROPN
ajst-16785	276	40	,	,	PUNCT
ajst-16785	276	41	yin	yin	PROPN
ajst-16785	276	42	w	w	PROPN
ajst-16785	276	43	(	(	PUNCT
ajst-16785	276	44	2021	2021	NUM
ajst-16785	276	45	)	)	PUNCT
ajst-16785	276	46	depth	depth	NOUN
ajst-16785	276	47	evaluation	evaluation	NOUN
ajst-16785	276	48	for	for	ADP
ajst-16785	276	49	metal	metal	NOUN
ajst-16785	276	50	surface	surface	NOUN
ajst-16785	276	51	defects	defect	NOUN
ajst-16785	276	52	by	by	ADP
ajst-16785	276	53	eddy	eddy	PROPN
ajst-16785	276	54	current	current	ADJ
ajst-16785	276	55	testing	testing	NOUN
ajst-16785	276	56	using	use	VERB
ajst-16785	276	57	deep	deep	ADJ
ajst-16785	276	58	residual	residual	ADJ
ajst-16785	276	59	convolutional	convolutional	ADJ
ajst-16785	276	60	neural	neural	ADJ
ajst-16785	276	61	networks	network	NOUN
ajst-16785	276	62	.	.	PUNCT
ajst-16785	277	1	ieee	ieee	PROPN
ajst-16785	277	2	trans	trans	PROPN
ajst-16785	277	3	instrum	instrum	PROPN
ajst-16785	277	4	meas	meas	PROPN
ajst-16785	277	5	70:2515413	70:2515413	NUM
ajst-16785	277	6	.	.	PUNCT
ajst-16785	278	1	https://doi.org/10.1109/tim.2021.3117367	https://doi.org/10.1109/tim.2021.3117367	PROPN
ajst-16785	279	1	[	[	X
ajst-16785	279	2	12	12	NUM
ajst-16785	279	3	]	]	PUNCT
ajst-16785	279	4	he	he	PRON
ajst-16785	279	5	d	d	PROPN
ajst-16785	279	6	,	,	PUNCT
ajst-16785	279	7	xu	xu	PROPN
ajst-16785	280	1	k	k	PROPN
ajst-16785	280	2	,	,	PUNCT
ajst-16785	280	3	wang	wang	PROPN
ajst-16785	280	4	d	d	PROPN
ajst-16785	280	5	(	(	PUNCT
ajst-16785	280	6	2019	2019	NUM
ajst-16785	280	7	)	)	PUNCT
ajst-16785	280	8	design	design	NOUN
ajst-16785	280	9	of	of	ADP
ajst-16785	280	10	multi	multi	ADJ
ajst-16785	280	11	-	-	ADJ
ajst-16785	280	12	scale	scale	ADJ
ajst-16785	280	13	receptive	receptive	ADJ
ajst-16785	280	14	field	field	NOUN
ajst-16785	280	15	convolutional	convolutional	ADJ
ajst-16785	280	16	neural	neural	ADJ
ajst-16785	280	17	network	network	NOUN
ajst-16785	280	18	for	for	ADP
ajst-16785	280	19	surface	surface	NOUN
ajst-16785	280	20	inspection	inspection	NOUN
ajst-16785	280	21	of	of	ADP
ajst-16785	280	22	hot	hot	ADJ
ajst-16785	280	23	rolled	roll	VERB
ajst-16785	280	24	steels	steel	NOUN
ajst-16785	280	25	.	.	PUNCT
ajst-16785	281	1	image	image	NOUN
ajst-16785	281	2	vis	vis	X
ajst-16785	281	3	comput	comput	NOUN
ajst-16785	281	4	89:12–20	89:12–20	NUM
ajst-16785	281	5	.	.	PUNCT
ajst-16785	282	1	https://doi.org/10.1016/j.imavis.2019.06.008	https://doi.org/10.1016/j.imavis.2019.06.008	PROPN
ajst-16785	282	2	[	[	X
ajst-16785	282	3	13	13	NUM
ajst-16785	282	4	]	]	PUNCT
ajst-16785	282	5	vaswani	vaswani	NOUN
ajst-16785	282	6	a	a	PRON
ajst-16785	282	7	,	,	PUNCT
ajst-16785	282	8	shazeer	shazeer	NOUN
ajst-16785	282	9	n	n	SYM
ajst-16785	282	10	,	,	PUNCT
ajst-16785	282	11	parmar	parmar	PROPN
ajst-16785	282	12	n	n	CCONJ
ajst-16785	282	13	,	,	PUNCT
ajst-16785	282	14	uszkoreit	uszkoreit	PROPN
ajst-16785	282	15	j	j	PROPN
ajst-16785	282	16	,	,	PUNCT
ajst-16785	282	17	jones	jones	PROPN
ajst-16785	282	18	l	l	PROPN
ajst-16785	282	19	,	,	PUNCT
ajst-16785	282	20	gomez	gomez	PROPN
ajst-16785	282	21	an	an	PROPN
ajst-16785	282	22	,	,	PUNCT
ajst-16785	282	23	kaiser	kaiser	PROPN
ajst-16785	282	24	l	l	PROPN
ajst-16785	282	25	,	,	PUNCT
ajst-16785	282	26	polosukhin	polosukhin	ADJ
ajst-16785	282	27	i	i	PRON
ajst-16785	282	28	(	(	PUNCT
ajst-16785	282	29	2017	2017	NUM
ajst-16785	282	30	)	)	PUNCT
ajst-16785	282	31	attention	attention	NOUN
ajst-16785	282	32	is	be	AUX
ajst-16785	282	33	all	all	PRON
ajst-16785	282	34	you	you	PRON
ajst-16785	282	35	need	need	VERB
ajst-16785	282	36	.	.	PUNCT
ajst-16785	283	1	in	in	ADP
ajst-16785	283	2	:	:	PUNCT
ajst-16785	283	3	guyon	guyon	PROPN
ajst-16785	283	4	i	i	PROPN
ajst-16785	283	5	,	,	PUNCT
ajst-16785	283	6	luxburg	luxburg	PROPN
ajst-16785	283	7	uv	uv	PROPN
ajst-16785	283	8	,	,	PUNCT
ajst-16785	283	9	bengio	bengio	PROPN
ajst-16785	283	10	s	s	PROPN
ajst-16785	283	11	,	,	PUNCT
ajst-16785	283	12	wallach	wallach	PROPN
ajst-16785	283	13	h	h	PROPN
ajst-16785	283	14	,	,	PUNCT
ajst-16785	283	15	fergus	fergus	PROPN
ajst-16785	283	16	r	r	PROPN
ajst-16785	283	17	,	,	PUNCT
ajst-16785	283	18	vishwanathan	vishwanathan	PROPN
ajst-16785	283	19	s	s	PROPN
ajst-16785	283	20	,	,	PUNCT
ajst-16785	283	21	garnett	garnett	PROPN
ajst-16785	283	22	r	r	PROPN
ajst-16785	283	23	(	(	PUNCT
ajst-16785	283	24	eds	ed	NOUN
ajst-16785	283	25	)	)	PUNCT
ajst-16785	283	26	advances	advance	NOUN
ajst-16785	283	27	in	in	ADP
ajst-16785	283	28	neural	neural	ADJ
ajst-16785	283	29	information	information	NOUN
ajst-16785	283	30	processing	processing	NOUN
ajst-16785	283	31	systems	system	NOUN
ajst-16785	283	32	30	30	NUM
ajst-16785	283	33	(	(	PUNCT
ajst-16785	283	34	nips	nip	NOUN
ajst-16785	283	35	2017	2017	NUM
ajst-16785	283	36	)	)	PUNCT
ajst-16785	283	37	.	.	PUNCT
ajst-16785	284	1	neural	neural	ADJ
ajst-16785	284	2	information	information	NOUN
ajst-16785	284	3	processing	processing	NOUN
ajst-16785	284	4	systems	system	NOUN
ajst-16785	284	5	(	(	PUNCT
ajst-16785	284	6	nips	nip	NOUN
ajst-16785	284	7	)	)	PUNCT
ajst-16785	284	8	,	,	PUNCT
ajst-16785	284	9	la	la	PROPN
ajst-16785	284	10	jolla	jolla	PROPN
ajst-16785	285	1	[	[	X
ajst-16785	285	2	14	14	NUM
ajst-16785	285	3	]	]	X
ajst-16785	285	4	dosovitskiy	dosovitskiy	NOUN
ajst-16785	285	5	a	a	PRON
ajst-16785	285	6	,	,	PUNCT
ajst-16785	285	7	beyer	beyer	PROPN
ajst-16785	285	8	l	l	PROPN
ajst-16785	285	9	,	,	PUNCT
ajst-16785	285	10	kolesnikov	kolesnikov	PROPN
ajst-16785	285	11	a	a	X
ajst-16785	285	12	,	,	PUNCT
ajst-16785	285	13	weissenborn	weissenborn	ADJ
ajst-16785	285	14	d	d	PROPN
ajst-16785	285	15	,	,	PUNCT
ajst-16785	285	16	zhai	zhai	PROPN
ajst-16785	285	17	x	x	PROPN
ajst-16785	285	18	,	,	PUNCT
ajst-16785	285	19	unterthiner	unterthiner	PROPN
ajst-16785	285	20	t	t	PROPN
ajst-16785	285	21	,	,	PUNCT
ajst-16785	285	22	dehghani	dehghani	PROPN
ajst-16785	285	23	m	m	PROPN
ajst-16785	285	24	,	,	PUNCT
ajst-16785	285	25	minderer	minderer	PROPN
ajst-16785	285	26	m	m	PROPN
ajst-16785	285	27	,	,	PUNCT
ajst-16785	285	28	heigold	heigold	VERB
ajst-16785	285	29	g	g	PROPN
ajst-16785	285	30	,	,	PUNCT
ajst-16785	285	31	gelly	gelly	NOUN
ajst-16785	285	32	s	s	NOUN
ajst-16785	285	33	,	,	PUNCT
ajst-16785	285	34	uszkoreit	uszkoreit	PROPN
ajst-16785	285	35	j	j	PROPN
ajst-16785	285	36	,	,	PUNCT
ajst-16785	285	37	houlsby	houlsby	ADJ
ajst-16785	285	38	n	n	PROPN
ajst-16785	285	39	(	(	PUNCT
ajst-16785	285	40	2021	2021	NUM
ajst-16785	285	41	)	)	PUNCT
ajst-16785	285	42	an	an	DET
ajst-16785	285	43	image	image	NOUN
ajst-16785	285	44	is	be	AUX
ajst-16785	285	45	worth	worth	ADJ
ajst-16785	285	46	16x16	16x16	NUM
ajst-16785	285	47	words	word	NOUN
ajst-16785	285	48	:	:	PUNCT
ajst-16785	285	49	transformers	transformer	NOUN
ajst-16785	285	50	for	for	ADP
ajst-16785	285	51	image	image	NOUN
ajst-16785	285	52	recognition	recognition	NOUN
ajst-16785	285	53	at	at	ADP
ajst-16785	285	54	scale	scale	NOUN
ajst-16785	285	55	[	[	X
ajst-16785	285	56	15	15	NUM
ajst-16785	285	57	]	]	X
ajst-16785	285	58	zhou	zhou	PROPN
ajst-16785	286	1	d	d	PROPN
ajst-16785	286	2	,	,	PUNCT
ajst-16785	286	3	kang	kang	PROPN
ajst-16785	286	4	b	b	PROPN
ajst-16785	286	5	,	,	PUNCT
ajst-16785	286	6	jin	jin	NOUN
ajst-16785	286	7	x	x	PROPN
ajst-16785	286	8	,	,	PUNCT
ajst-16785	286	9	yang	yang	PROPN
ajst-16785	286	10	l	l	PROPN
ajst-16785	286	11	,	,	PUNCT
ajst-16785	286	12	lian	lian	PROPN
ajst-16785	286	13	x	x	NOUN
ajst-16785	286	14	,	,	PUNCT
ajst-16785	286	15	jiang	jiang	PROPN
ajst-16785	286	16	z	z	PROPN
ajst-16785	286	17	,	,	PUNCT
ajst-16785	286	18	hou	hou	PROPN
ajst-16785	286	19	q	q	PROPN
ajst-16785	286	20	,	,	PUNCT
ajst-16785	286	21	feng	feng	PROPN
ajst-16785	286	22	j	j	PROPN
ajst-16785	286	23	(	(	PUNCT
ajst-16785	286	24	2021	2021	NUM
ajst-16785	286	25	)	)	PUNCT
ajst-16785	286	26	deepvit	deepvit	NOUN
ajst-16785	286	27	:	:	PUNCT
ajst-16785	286	28	towards	towards	ADP
ajst-16785	286	29	deeper	deep	ADJ
ajst-16785	286	30	vision	vision	NOUN
ajst-16785	286	31	transformer	transformer	NOUN
ajst-16785	286	32	[	[	X
ajst-16785	286	33	16	16	NUM
ajst-16785	286	34	]	]	PUNCT
ajst-16785	286	35	touvron	touvron	PROPN
ajst-16785	286	36	h	h	NOUN
ajst-16785	286	37	,	,	PUNCT
ajst-16785	286	38	cord	cord	PROPN
ajst-16785	286	39	m	m	PROPN
ajst-16785	286	40	,	,	PUNCT
ajst-16785	286	41	sablayrolles	sablayrolle	VERB
ajst-16785	286	42	a	a	PRON
ajst-16785	286	43	,	,	PUNCT
ajst-16785	286	44	synnaeve	synnaeve	VERB
ajst-16785	286	45	g	g	PROPN
ajst-16785	286	46	,	,	PUNCT
ajst-16785	286	47	jégou	jégou	PROPN
ajst-16785	286	48	h	h	NOUN
ajst-16785	286	49	(	(	PUNCT
ajst-16785	286	50	2021	2021	NUM
ajst-16785	286	51	)	)	PUNCT
ajst-16785	286	52	going	go	VERB
ajst-16785	286	53	deeper	deeply	ADV
ajst-16785	286	54	with	with	ADP
ajst-16785	286	55	image	image	NOUN
ajst-16785	286	56	transformers	transformer	NOUN
ajst-16785	286	57	.	.	PUNCT
ajst-16785	287	1	pp	pp	X
ajst-16785	288	1	32–42	32–42	NUM
ajst-16785	289	1	[	[	X
ajst-16785	289	2	17	17	NUM
ajst-16785	289	3	]	]	X
ajst-16785	289	4	wang	wang	PROPN
ajst-16785	289	5	w	w	PROPN
ajst-16785	289	6	,	,	PUNCT
ajst-16785	289	7	xie	xie	PROPN
ajst-16785	289	8	e	e	PROPN
ajst-16785	289	9	,	,	PUNCT
ajst-16785	289	10	li	li	PROPN
ajst-16785	289	11	x	x	PROPN
ajst-16785	289	12	,	,	PUNCT
ajst-16785	289	13	fan	fan	PROPN
ajst-16785	289	14	d	d	PROPN
ajst-16785	289	15	-	-	PUNCT
ajst-16785	289	16	p	p	NOUN
ajst-16785	289	17	,	,	PUNCT
ajst-16785	289	18	song	song	NOUN
ajst-16785	289	19	k	k	PROPN
ajst-16785	289	20	,	,	PUNCT
ajst-16785	289	21	liang	liang	PROPN
ajst-16785	289	22	d	d	PROPN
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ajst-16785	289	24	lu	lu	PROPN
ajst-16785	289	25	t	t	PROPN
ajst-16785	289	26	,	,	PUNCT
ajst-16785	289	27	luo	luo	PROPN
ajst-16785	289	28	p	p	PROPN
ajst-16785	289	29	,	,	PUNCT
ajst-16785	289	30	shao	shao	PROPN
ajst-16785	289	31	l	l	PROPN
ajst-16785	289	32	(	(	PUNCT
ajst-16785	289	33	2022	2022	NUM
ajst-16785	289	34	)	)	PUNCT
ajst-16785	290	1	pvt	pvt	PROPN
ajst-16785	290	2	v2	v2	PROPN
ajst-16785	290	3	:	:	PUNCT
ajst-16785	290	4	improved	improve	VERB
ajst-16785	290	5	baselines	baseline	NOUN
ajst-16785	290	6	with	with	ADP
ajst-16785	290	7	pyramid	pyramid	PROPN
ajst-16785	290	8	vision	vision	PROPN
ajst-16785	290	9	transformer	transformer	NOUN
ajst-16785	290	10	.	.	PUNCT
ajst-16785	291	1	comput	comput	NOUN
ajst-16785	291	2	vis	vis	ADP
ajst-16785	291	3	media	medium	NOUN
ajst-16785	291	4	8:415–424	8:415–424	NUM
ajst-16785	291	5	.	.	PUNCT
ajst-16785	291	6	https://doi.org/10.1007/s41095-022-0274-8	https://doi.org/10.1007/s41095-022-0274-8	PUNCT
ajst-16785	292	1	[	[	X
ajst-16785	292	2	18	18	NUM
ajst-16785	292	3	]	]	X
ajst-16785	292	4	liu	liu	PROPN
ajst-16785	292	5	z	z	PROPN
ajst-16785	292	6	,	,	PUNCT
ajst-16785	292	7	lin	lin	PROPN
ajst-16785	292	8	y	y	PROPN
ajst-16785	292	9	,	,	PUNCT
ajst-16785	292	10	cao	cao	PROPN
ajst-16785	292	11	y	y	PROPN
ajst-16785	292	12	,	,	PUNCT
ajst-16785	292	13	hu	hu	PROPN
ajst-16785	292	14	h	h	PROPN
ajst-16785	292	15	,	,	PUNCT
ajst-16785	292	16	wei	wei	PROPN
ajst-16785	292	17	y	y	PROPN
ajst-16785	292	18	,	,	PUNCT
ajst-16785	292	19	zhang	zhang	PROPN
ajst-16785	292	20	z	z	PROPN
ajst-16785	292	21	,	,	PUNCT
ajst-16785	292	22	lin	lin	PROPN
ajst-16785	292	23	s	s	PROPN
ajst-16785	292	24	,	,	PUNCT
ajst-16785	292	25	guo	guo	PROPN
ajst-16785	292	26	b	b	PROPN
ajst-16785	292	27	(	(	PUNCT
ajst-16785	292	28	2021	2021	NUM
ajst-16785	292	29	)	)	PUNCT
ajst-16785	292	30	swin	swin	PROPN
ajst-16785	292	31	transformer	transformer	PROPN
ajst-16785	292	32	:	:	PUNCT
ajst-16785	292	33	hierarchical	hierarchical	ADJ
ajst-16785	292	34	vision	vision	NOUN
ajst-16785	292	35	transformer	transformer	NOUN
ajst-16785	292	36	using	use	VERB
ajst-16785	292	37	shifted	shift	VERB
ajst-16785	292	38	windows	window	NOUN
ajst-16785	292	39	.	.	PUNCT
ajst-16785	293	1	in	in	ADP
ajst-16785	293	2	:	:	PUNCT
ajst-16785	293	3	2021	2021	NUM
ajst-16785	293	4	ieee	ieee	NOUN
ajst-16785	293	5	/	/	SYM
ajst-16785	293	6	cvf	cvf	NOUN
ajst-16785	293	7	international	international	ADJ
ajst-16785	293	8	conference	conference	NOUN
ajst-16785	293	9	on	on	ADP
ajst-16785	293	10	computer	computer	NOUN
ajst-16785	293	11	vision	vision	NOUN
ajst-16785	293	12	(	(	PUNCT
ajst-16785	293	13	iccv	iccv	NOUN
ajst-16785	293	14	2021	2021	NUM
ajst-16785	293	15	)	)	PUNCT
ajst-16785	293	16	.	.	PUNCT
ajst-16785	294	1	ieee	ieee	PROPN
ajst-16785	294	2	,	,	PUNCT
ajst-16785	294	3	new	new	PROPN
ajst-16785	294	4	york	york	PROPN
ajst-16785	294	5	,	,	PUNCT
ajst-16785	294	6	pp	pp	ADP
ajst-16785	294	7	9992–10002	9992–10002	NUM
ajst-16785	294	8	[	[	X
ajst-16785	294	9	19	19	NUM
ajst-16785	294	10	]	]	X
ajst-16785	294	11	hou	hou	PROPN
ajst-16785	294	12	q	q	NOUN
ajst-16785	294	13	,	,	PUNCT
ajst-16785	294	14	zhou	zhou	PROPN
ajst-16785	294	15	d	d	PROPN
ajst-16785	294	16	,	,	PUNCT
ajst-16785	294	17	feng	feng	PROPN
ajst-16785	294	18	j	j	PROPN
ajst-16785	294	19	(	(	PUNCT
ajst-16785	294	20	2021	2021	NUM
ajst-16785	294	21	)	)	PUNCT
ajst-16785	294	22	coordinate	coordinate	VERB
ajst-16785	294	23	attention	attention	NOUN
ajst-16785	294	24	for	for	ADP
ajst-16785	294	25	efficient	efficient	ADJ
ajst-16785	294	26	mobile	mobile	ADJ
ajst-16785	294	27	network	network	NOUN
ajst-16785	294	28	design	design	NOUN
ajst-16785	294	29	.	.	PUNCT
ajst-16785	295	1	in	in	ADP
ajst-16785	295	2	:	:	PUNCT
ajst-16785	295	3	2021	2021	NUM
ajst-16785	295	4	ieee	ieee	NOUN
ajst-16785	295	5	/	/	SYM
ajst-16785	295	6	cvf	cvf	NOUN
ajst-16785	295	7	conference	conference	NOUN
ajst-16785	295	8	on	on	ADP
ajst-16785	295	9	computer	computer	NOUN
ajst-16785	295	10	vision	vision	NOUN
ajst-16785	295	11	and	and	CCONJ
ajst-16785	295	12	pattern	pattern	NOUN
ajst-16785	295	13	recognition	recognition	NOUN
ajst-16785	295	14	,	,	PUNCT
ajst-16785	295	15	cvpr	cvpr	NOUN
ajst-16785	295	16	2021	2021	NUM
ajst-16785	295	17	.	.	PUNCT
ajst-16785	296	1	ieee	ieee	NOUN
ajst-16785	296	2	computer	computer	NOUN
ajst-16785	296	3	soc	soc	NOUN
ajst-16785	296	4	,	,	PUNCT
ajst-16785	296	5	los	los	PROPN
ajst-16785	296	6	alamitos	alamitos	PROPN
ajst-16785	296	7	,	,	PUNCT
ajst-16785	296	8	pp	pp	ADP
ajst-16785	296	9	13708–13717	13708–13717	PRON
ajst-16785	296	10	[	[	X
ajst-16785	296	11	20	20	NUM
ajst-16785	296	12	]	]	SYM
ajst-16785	296	13	hu	hu	PROPN
ajst-16785	297	1	j	j	PROPN
ajst-16785	297	2	,	,	PUNCT
ajst-16785	297	3	shen	shen	PROPN
ajst-16785	297	4	l	l	PROPN
ajst-16785	297	5	,	,	PUNCT
ajst-16785	297	6	sun	sun	PROPN
ajst-16785	297	7	g	g	PROPN
ajst-16785	297	8	(	(	PUNCT
ajst-16785	297	9	2018	2018	NUM
ajst-16785	297	10	)	)	PUNCT
ajst-16785	297	11	squeeze	squeeze	NOUN
ajst-16785	297	12	-	-	PUNCT
ajst-16785	297	13	and	and	CCONJ
ajst-16785	297	14	-	-	PUNCT
ajst-16785	297	15	excitation	excitation	NOUN
ajst-16785	297	16	networks	network	NOUN
ajst-16785	297	17	.	.	PUNCT
ajst-16785	298	1	in	in	ADP
ajst-16785	298	2	:	:	PUNCT
ajst-16785	298	3	2018	2018	NUM
ajst-16785	298	4	ieee	ieee	NOUN
ajst-16785	298	5	/	/	SYM
ajst-16785	298	6	cvf	cvf	NOUN
ajst-16785	298	7	conference	conference	NOUN
ajst-16785	298	8	on	on	ADP
ajst-16785	298	9	computer	computer	NOUN
ajst-16785	298	10	vision	vision	NOUN
ajst-16785	298	11	and	and	CCONJ
ajst-16785	298	12	pattern	pattern	NOUN
ajst-16785	298	13	recognition	recognition	NOUN
ajst-16785	298	14	(	(	PUNCT
ajst-16785	298	15	cvpr	cvpr	NOUN
ajst-16785	298	16	)	)	PUNCT
ajst-16785	298	17	.	.	PUNCT
ajst-16785	299	1	ieee	ieee	PROPN
ajst-16785	299	2	,	,	PUNCT
ajst-16785	299	3	new	new	PROPN
ajst-16785	299	4	york	york	PROPN
ajst-16785	299	5	,	,	PUNCT
ajst-16785	299	6	pp	pp	ADP
ajst-16785	299	7	7132–7141	7132–7141	NUM
ajst-16785	299	8	[	[	X
ajst-16785	299	9	21	21	NUM
ajst-16785	299	10	]	]	X
ajst-16785	299	11	woo	woo	NOUN
ajst-16785	299	12	s	s	PROPN
ajst-16785	299	13	,	,	PUNCT
ajst-16785	299	14	park	park	PROPN
ajst-16785	299	15	j	j	PROPN
ajst-16785	299	16	,	,	PUNCT
ajst-16785	299	17	lee	lee	PROPN
ajst-16785	299	18	j	j	PROPN
ajst-16785	299	19	-	-	PROPN
ajst-16785	299	20	y	y	PROPN
ajst-16785	299	21	,	,	PUNCT
ajst-16785	299	22	kweon	kweon	PROPN
ajst-16785	299	23	is	be	AUX
ajst-16785	299	24	(	(	PUNCT
ajst-16785	299	25	2018	2018	NUM
ajst-16785	299	26	)	)	PUNCT
ajst-16785	299	27	cbam	cbam	NOUN
ajst-16785	299	28	:	:	PUNCT
ajst-16785	299	29	convolutional	convolutional	ADJ
ajst-16785	299	30	block	block	NOUN
ajst-16785	299	31	attention	attention	NOUN
ajst-16785	299	32	module	module	NOUN
ajst-16785	299	33	.	.	PUNCT
ajst-16785	300	1	in	in	ADP
ajst-16785	300	2	:	:	PUNCT
ajst-16785	300	3	ferrari	ferrari	PROPN
ajst-16785	300	4	v	v	NOUN
ajst-16785	300	5	,	,	PUNCT
ajst-16785	300	6	hebert	hebert	PROPN
ajst-16785	300	7	m	m	PROPN
ajst-16785	300	8	,	,	PUNCT
ajst-16785	300	9	sminchisescu	sminchisescu	PROPN
ajst-16785	300	10	c	c	PROPN
ajst-16785	300	11	,	,	PUNCT
ajst-16785	300	12	weiss	weiss	PROPN
ajst-16785	300	13	y	y	PROPN
ajst-16785	300	14	(	(	PUNCT
ajst-16785	300	15	eds	eds	PROPN
ajst-16785	300	16	)	)	PUNCT
ajst-16785	300	17	computer	computer	NOUN
ajst-16785	300	18	vision	vision	NOUN
ajst-16785	300	19	eccv	eccv	ADV
ajst-16785	300	20	2018	2018	NUM
ajst-16785	300	21	,	,	PUNCT
ajst-16785	300	22	pt	pt	PROPN
ajst-16785	300	23	vii	vii	PROPN
ajst-16785	300	24	.	.	PROPN
ajst-16785	300	25	springer	springer	PROPN
ajst-16785	300	26	international	international	PROPN
ajst-16785	300	27	publishing	publishing	PROPN
ajst-16785	300	28	ag	ag	PROPN
ajst-16785	300	29	,	,	PUNCT
ajst-16785	300	30	cham	cham	PROPN
ajst-16785	300	31	,	,	PUNCT
ajst-16785	300	32	pp	pp	ADP
ajst-16785	300	33	3–19	3–19	PROPN
ajst-16785	300	34	[	[	PUNCT
ajst-16785	300	35	22	22	NUM
ajst-16785	300	36	]	]	PUNCT
ajst-16785	300	37	he	he	PRON
ajst-16785	300	38	y	y	PROPN
ajst-16785	300	39	,	,	PUNCT
ajst-16785	300	40	song	song	NOUN
ajst-16785	300	41	k	k	PROPN
ajst-16785	300	42	,	,	PUNCT
ajst-16785	300	43	meng	meng	PROPN
ajst-16785	300	44	q	q	PROPN
ajst-16785	300	45	,	,	PUNCT
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ajst-16785	300	47	y	y	PROPN
ajst-16785	300	48	(	(	PUNCT
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ajst-16785	300	50	)	)	PUNCT
ajst-16785	300	51	an	an	DET
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ajst-16785	300	53	-	-	PUNCT
ajst-16785	300	54	to	to	ADP
ajst-16785	300	55	-	-	PUNCT
ajst-16785	300	56	end	end	NOUN
ajst-16785	300	57	steel	steel	NOUN
ajst-16785	300	58	surface	surface	NOUN
ajst-16785	300	59	defect	defect	NOUN
ajst-16785	300	60	detection	detection	NOUN
ajst-16785	300	61	approach	approach	NOUN
ajst-16785	300	62	via	via	ADP
ajst-16785	300	63	fusing	fuse	VERB
ajst-16785	300	64	multiple	multiple	ADJ
ajst-16785	300	65	hierarchical	hierarchical	ADJ
ajst-16785	300	66	features	feature	NOUN
ajst-16785	300	67	.	.	PUNCT
ajst-16785	301	1	ieee	ieee	NOUN
ajst-16785	301	2	trans	trans	PROPN
ajst-16785	301	3	instrum	instrum	PROPN
ajst-16785	301	4	meas	mea	NOUN
ajst-16785	301	5	69:1493	69:1493	NUM
ajst-16785	301	6	–	–	PUNCT
ajst-16785	301	7	1504	1504	NUM
ajst-16785	301	8	.	.	PUNCT
ajst-16785	302	1	https://doi.org/10.1109/tim.2019.2915404	https://doi.org/10.1109/tim.2019.2915404	NOUN
ajst-16785	302	2	[	[	X
ajst-16785	302	3	23	23	NUM
ajst-16785	302	4	]	]	PUNCT
ajst-16785	302	5	dragomiretskiy	dragomiretskiy	NOUN
ajst-16785	302	6	k	k	PROPN
ajst-16785	302	7	,	,	PUNCT
ajst-16785	302	8	zosso	zosso	PROPN
ajst-16785	302	9	d	d	PROPN
ajst-16785	302	10	(	(	PUNCT
ajst-16785	302	11	2014	2014	NUM
ajst-16785	302	12	)	)	PUNCT
ajst-16785	302	13	variational	variational	ADJ
ajst-16785	302	14	mode	mode	NOUN
ajst-16785	302	15	decomposition	decomposition	NOUN
ajst-16785	302	16	.	.	PUNCT
ajst-16785	303	1	ieee	ieee	PROPN
ajst-16785	303	2	trans	trans	PROPN
ajst-16785	303	3	signal	signal	PROPN
ajst-16785	303	4	process	process	NOUN
ajst-16785	303	5	62:531–544	62:531–544	PROPN
ajst-16785	303	6	.	.	PUNCT
ajst-16785	304	1	https://doi.org/10.1109/tsp.2013.2288675	https://doi.org/10.1109/tsp.2013.2288675	PROPN