id	sid	tid	token	lemma	pos
ajst-11366	1	1	academic	academic	ADJ
ajst-11366	1	2	journal	journal	NOUN
ajst-11366	1	3	of	of	ADP
ajst-11366	1	4	science	science	NOUN
ajst-11366	1	5	and	and	CCONJ
ajst-11366	1	6	technology	technology	NOUN
ajst-11366	1	7	issn	issn	NOUN
ajst-11366	1	8	:	:	PUNCT
ajst-11366	1	9	2771	2771	NUM
ajst-11366	1	10	-	-	SYM
ajst-11366	1	11	3032	3032	NUM
ajst-11366	1	12	|	|	NOUN
ajst-11366	1	13	vol	vol	NOUN
ajst-11366	1	14	.	.	PROPN
ajst-11366	2	1	7	7	NUM
ajst-11366	2	2	,	,	PUNCT
ajst-11366	2	3	no	no	INTJ
ajst-11366	2	4	.	.	NOUN
ajst-11366	2	5	1	1	NUM
ajst-11366	2	6	,	,	PUNCT
ajst-11366	2	7	2023	2023	NUM
ajst-11366	2	8	184	184	NUM
ajst-11366	2	9	tile	tile	NOUN
ajst-11366	2	10	surface	surface	NOUN
ajst-11366	2	11	defect	defect	NOUN
ajst-11366	2	12	detection	detection	NOUN
ajst-11366	2	13	based	base	VERB
ajst-11366	2	14	on	on	ADP
ajst-11366	2	15	improved	improved	ADJ
ajst-11366	2	16	faster	fast	ADV
ajst-11366	2	17	r‐cnn	r‐cnn	PROPN
ajst-11366	2	18	xuan	xuan	PROPN
ajst-11366	2	19	che	che	PROPN
ajst-11366	2	20	,	,	PUNCT
ajst-11366	2	21	wenzhong	wenzhong	PROPN
ajst-11366	2	22	zhu	zhu	PROPN
ajst-11366	2	23	college	college	PROPN
ajst-11366	2	24	of	of	ADP
ajst-11366	2	25	computer	computer	NOUN
ajst-11366	2	26	science	science	NOUN
ajst-11366	2	27	and	and	CCONJ
ajst-11366	2	28	engineering	engineering	NOUN
ajst-11366	2	29	,	,	PUNCT
ajst-11366	2	30	sichuan	sichuan	PROPN
ajst-11366	2	31	university	university	PROPN
ajst-11366	2	32	of	of	ADP
ajst-11366	2	33	science	science	NOUN
ajst-11366	2	34	and	and	CCONJ
ajst-11366	2	35	engineering	engineering	NOUN
ajst-11366	2	36	,	,	PUNCT
ajst-11366	2	37	sichuan	sichuan	PROPN
ajst-11366	2	38	64400	64400	NUM
ajst-11366	2	39	,	,	PUNCT
ajst-11366	2	40	china	china	PROPN
ajst-11366	2	41	abstract	abstract	PROPN
ajst-11366	2	42	:	:	PUNCT
ajst-11366	2	43	with	with	ADP
ajst-11366	2	44	the	the	DET
ajst-11366	2	45	increasing	increase	VERB
ajst-11366	2	46	population	population	NOUN
ajst-11366	2	47	,	,	PUNCT
ajst-11366	2	48	there	there	PRON
ajst-11366	2	49	is	be	VERB
ajst-11366	2	50	a	a	DET
ajst-11366	2	51	high	high	ADJ
ajst-11366	2	52	demand	demand	NOUN
ajst-11366	2	53	for	for	ADP
ajst-11366	2	54	housing	housing	NOUN
ajst-11366	2	55	,	,	PUNCT
ajst-11366	2	56	commercial	commercial	ADJ
ajst-11366	2	57	buildings	building	NOUN
ajst-11366	2	58	,	,	PUNCT
ajst-11366	2	59	and	and	CCONJ
ajst-11366	2	60	lifestyle	lifestyle	NOUN
ajst-11366	2	61	facilities	facility	NOUN
ajst-11366	2	62	.	.	PUNCT
ajst-11366	3	1	the	the	DET
ajst-11366	3	2	development	development	NOUN
ajst-11366	3	3	of	of	ADP
ajst-11366	3	4	modern	modern	ADJ
ajst-11366	3	5	manufacturing	manufacturing	NOUN
ajst-11366	3	6	technology	technology	NOUN
ajst-11366	3	7	has	have	AUX
ajst-11366	3	8	led	lead	VERB
ajst-11366	3	9	to	to	ADP
ajst-11366	3	10	higher	high	ADJ
ajst-11366	3	11	quality	quality	NOUN
ajst-11366	3	12	control	control	NOUN
ajst-11366	3	13	requirements	requirement	NOUN
ajst-11366	3	14	for	for	ADP
ajst-11366	3	15	tiles	tile	NOUN
ajst-11366	3	16	.	.	PUNCT
ajst-11366	4	1	this	this	DET
ajst-11366	4	2	article	article	NOUN
ajst-11366	4	3	presents	present	VERB
ajst-11366	4	4	a	a	DET
ajst-11366	4	5	ceramic	ceramic	ADJ
ajst-11366	4	6	tile	tile	NOUN
ajst-11366	4	7	defect	defect	NOUN
ajst-11366	4	8	detection	detection	NOUN
ajst-11366	4	9	method	method	NOUN
ajst-11366	4	10	based	base	VERB
ajst-11366	4	11	on	on	ADP
ajst-11366	4	12	faster	fast	ADJ
ajst-11366	4	13	r	r	NOUN
ajst-11366	4	14	-	-	PUNCT
ajst-11366	4	15	cnn	cnn	PROPN
ajst-11366	4	16	,	,	PUNCT
ajst-11366	4	17	primarily	primarily	ADV
ajst-11366	4	18	focused	focus	VERB
ajst-11366	4	19	on	on	ADP
ajst-11366	4	20	detecting	detect	VERB
ajst-11366	4	21	surface	surface	NOUN
ajst-11366	4	22	defects	defect	NOUN
ajst-11366	4	23	or	or	CCONJ
ajst-11366	4	24	cracks	crack	NOUN
ajst-11366	4	25	on	on	ADP
ajst-11366	4	26	tiles	tile	NOUN
ajst-11366	4	27	.	.	PUNCT
ajst-11366	5	1	the	the	DET
ajst-11366	5	2	method	method	NOUN
ajst-11366	5	3	replaces	replace	VERB
ajst-11366	5	4	vgg16	vgg16	NOUN
ajst-11366	5	5	with	with	ADP
ajst-11366	5	6	the	the	DET
ajst-11366	5	7	resnet-101	resnet-101	NOUN
ajst-11366	5	8	network	network	NOUN
ajst-11366	5	9	as	as	ADP
ajst-11366	5	10	a	a	DET
ajst-11366	5	11	new	new	ADJ
ajst-11366	5	12	backbone	backbone	NOUN
ajst-11366	5	13	and	and	CCONJ
ajst-11366	5	14	utilizes	utilize	VERB
ajst-11366	5	15	depth	depth	NOUN
ajst-11366	5	16	-	-	PUNCT
ajst-11366	5	17	wise	wise	ADJ
ajst-11366	5	18	separable	separable	ADJ
ajst-11366	5	19	convolution	convolution	NOUN
ajst-11366	5	20	to	to	PART
ajst-11366	5	21	address	address	VERB
ajst-11366	5	22	efficiency	efficiency	NOUN
ajst-11366	5	23	issues	issue	NOUN
ajst-11366	5	24	resulting	result	VERB
ajst-11366	5	25	from	from	ADP
ajst-11366	5	26	the	the	DET
ajst-11366	5	27	backbone	backbone	NOUN
ajst-11366	5	28	replacement	replacement	NOUN
ajst-11366	5	29	.	.	PUNCT
ajst-11366	6	1	finally	finally	ADV
ajst-11366	6	2	,	,	PUNCT
ajst-11366	6	3	soft	soft	ADJ
ajst-11366	6	4	-	-	PUNCT
ajst-11366	6	5	nms	nms	NOUN
ajst-11366	6	6	is	be	AUX
ajst-11366	6	7	employed	employ	VERB
ajst-11366	6	8	to	to	PART
ajst-11366	6	9	optimize	optimize	VERB
ajst-11366	6	10	regression	regression	NOUN
ajst-11366	6	11	boxes	box	NOUN
ajst-11366	6	12	and	and	CCONJ
ajst-11366	6	13	prevent	prevent	VERB
ajst-11366	6	14	missed	miss	VERB
ajst-11366	6	15	detections	detection	NOUN
ajst-11366	6	16	.	.	PUNCT
ajst-11366	7	1	experimental	experimental	ADJ
ajst-11366	7	2	results	result	NOUN
ajst-11366	7	3	demonstrate	demonstrate	VERB
ajst-11366	7	4	that	that	SCONJ
ajst-11366	7	5	the	the	DET
ajst-11366	7	6	improved	improved	ADJ
ajst-11366	7	7	algorithm	algorithm	NOUN
ajst-11366	7	8	achieves	achieve	VERB
ajst-11366	7	9	a	a	DET
ajst-11366	7	10	map	map	NOUN
ajst-11366	7	11	of	of	ADP
ajst-11366	7	12	70.4	70.4	NUM
ajst-11366	7	13	%	%	NOUN
ajst-11366	7	14	,	,	PUNCT
ajst-11366	7	15	a	a	DET
ajst-11366	7	16	13.2	13.2	NUM
ajst-11366	7	17	%	%	NOUN
ajst-11366	7	18	enhancement	enhancement	NOUN
ajst-11366	7	19	over	over	ADP
ajst-11366	7	20	the	the	DET
ajst-11366	7	21	original	original	ADJ
ajst-11366	7	22	algorithm	algorithm	NOUN
ajst-11366	7	23	,	,	PUNCT
ajst-11366	7	24	highlighting	highlight	VERB
ajst-11366	7	25	the	the	DET
ajst-11366	7	26	effectiveness	effectiveness	NOUN
ajst-11366	7	27	and	and	CCONJ
ajst-11366	7	28	feasibility	feasibility	NOUN
ajst-11366	7	29	of	of	ADP
ajst-11366	7	30	the	the	DET
ajst-11366	7	31	proposed	propose	VERB
ajst-11366	7	32	approach	approach	NOUN
ajst-11366	7	33	.	.	PUNCT
ajst-11366	8	1	keywords	keyword	NOUN
ajst-11366	8	2	:	:	PUNCT
ajst-11366	8	3	defect	defect	VERB
ajst-11366	8	4	detection	detection	NOUN
ajst-11366	8	5	,	,	PUNCT
ajst-11366	8	6	tile	tile	NOUN
ajst-11366	8	7	defects	defect	NOUN
ajst-11366	8	8	,	,	PUNCT
ajst-11366	8	9	faster	fast	ADV
ajst-11366	8	10	-	-	PUNCT
ajst-11366	8	11	rcnn	rcnn	NOUN
ajst-11366	8	12	,	,	PUNCT
ajst-11366	8	13	bifpn	bifpn	PROPN
ajst-11366	8	14	.	.	PUNCT
ajst-11366	9	1	1	1	X
ajst-11366	9	2	.	.	X
ajst-11366	9	3	introduction	introduction	NOUN
ajst-11366	9	4	china	china	PROPN
ajst-11366	9	5	,	,	PUNCT
ajst-11366	9	6	as	as	SCONJ
ajst-11366	9	7	the	the	DET
ajst-11366	9	8	world	world	NOUN
ajst-11366	9	9	's	's	PART
ajst-11366	9	10	leading	lead	VERB
ajst-11366	9	11	producer	producer	NOUN
ajst-11366	9	12	of	of	ADP
ajst-11366	9	13	ceramic	ceramic	ADJ
ajst-11366	9	14	tiles[1	tiles[1	PROPN
ajst-11366	9	15	]	]	PUNCT
ajst-11366	9	16	,	,	PUNCT
ajst-11366	9	17	not	not	PART
ajst-11366	9	18	only	only	ADV
ajst-11366	9	19	fulfills	fulfill	VERB
ajst-11366	9	20	the	the	DET
ajst-11366	9	21	substantial	substantial	ADJ
ajst-11366	9	22	domestic	domestic	ADJ
ajst-11366	9	23	construction	construction	NOUN
ajst-11366	9	24	demand	demand	NOUN
ajst-11366	9	25	but	but	CCONJ
ajst-11366	9	26	also	also	ADV
ajst-11366	9	27	exports	export	VERB
ajst-11366	9	28	its	its	PRON
ajst-11366	9	29	products	product	NOUN
ajst-11366	9	30	abroad	abroad	ADV
ajst-11366	9	31	with	with	ADP
ajst-11366	9	32	a	a	DET
ajst-11366	9	33	strong	strong	ADJ
ajst-11366	9	34	reputation	reputation	NOUN
ajst-11366	9	35	and	and	CCONJ
ajst-11366	9	36	capability	capability	NOUN
ajst-11366	9	37	.	.	PUNCT
ajst-11366	10	1	due	due	ADP
ajst-11366	10	2	to	to	ADP
ajst-11366	10	3	the	the	DET
ajst-11366	10	4	unique	unique	ADJ
ajst-11366	10	5	properties	property	NOUN
ajst-11366	10	6	of	of	ADP
ajst-11366	10	7	construction	construction	NOUN
ajst-11366	10	8	materials	material	NOUN
ajst-11366	10	9	,	,	PUNCT
ajst-11366	10	10	ceramic	ceramic	ADJ
ajst-11366	10	11	tiles	tile	NOUN
ajst-11366	10	12	are	be	AUX
ajst-11366	10	13	susceptible	susceptible	ADJ
ajst-11366	10	14	to	to	ADP
ajst-11366	10	15	breakage	breakage	NOUN
ajst-11366	10	16	,	,	PUNCT
ajst-11366	10	17	which	which	PRON
ajst-11366	10	18	can	can	AUX
ajst-11366	10	19	occur	occur	VERB
ajst-11366	10	20	during	during	ADP
ajst-11366	10	21	production	production	NOUN
ajst-11366	10	22	,	,	PUNCT
ajst-11366	10	23	packaging	packaging	NOUN
ajst-11366	10	24	,	,	PUNCT
ajst-11366	10	25	and	and	CCONJ
ajst-11366	10	26	transportation	transportation	NOUN
ajst-11366	10	27	due	due	ADJ
ajst-11366	10	28	to	to	ADP
ajst-11366	10	29	mishandling	mishandle	VERB
ajst-11366	10	30	.	.	PUNCT
ajst-11366	11	1	surface	surface	NOUN
ajst-11366	11	2	defects	defect	NOUN
ajst-11366	11	3	such	such	ADJ
ajst-11366	11	4	as	as	ADP
ajst-11366	11	5	cracks	crack	NOUN
ajst-11366	11	6	,	,	PUNCT
ajst-11366	11	7	scratches	scratch	NOUN
ajst-11366	11	8	,	,	PUNCT
ajst-11366	11	9	and	and	CCONJ
ajst-11366	11	10	indentations	indentation	NOUN
ajst-11366	11	11	on	on	ADP
ajst-11366	11	12	ceramic	ceramic	ADJ
ajst-11366	11	13	tiles	tile	NOUN
ajst-11366	11	14	can	can	AUX
ajst-11366	11	15	mar	mar	VERB
ajst-11366	11	16	their	their	PRON
ajst-11366	11	17	aesthetic	aesthetic	ADJ
ajst-11366	11	18	appearance	appearance	NOUN
ajst-11366	11	19	and	and	CCONJ
ajst-11366	11	20	diminish	diminish	VERB
ajst-11366	11	21	their	their	PRON
ajst-11366	11	22	decorative	decorative	ADJ
ajst-11366	11	23	impact	impact	NOUN
ajst-11366	11	24	.	.	PUNCT
ajst-11366	12	1	furthermore	furthermore	ADV
ajst-11366	12	2	,	,	PUNCT
ajst-11366	12	3	these	these	DET
ajst-11366	12	4	flaws	flaw	NOUN
ajst-11366	12	5	can	can	AUX
ajst-11366	12	6	lead	lead	VERB
ajst-11366	12	7	to	to	ADP
ajst-11366	12	8	dirt	dirt	NOUN
ajst-11366	12	9	accumulation	accumulation	NOUN
ajst-11366	12	10	and	and	CCONJ
ajst-11366	12	11	water	water	NOUN
ajst-11366	12	12	infiltration	infiltration	NOUN
ajst-11366	12	13	,	,	PUNCT
ajst-11366	12	14	further	far	ADV
ajst-11366	12	15	compromising	compromise	VERB
ajst-11366	12	16	the	the	DET
ajst-11366	12	17	quality	quality	NOUN
ajst-11366	12	18	of	of	ADP
ajst-11366	12	19	the	the	DET
ajst-11366	12	20	tiles	tile	NOUN
ajst-11366	12	21	.	.	PUNCT
ajst-11366	13	1	cracks	crack	NOUN
ajst-11366	13	2	on	on	ADP
ajst-11366	13	3	the	the	DET
ajst-11366	13	4	surface	surface	NOUN
ajst-11366	13	5	or	or	CCONJ
ajst-11366	13	6	within	within	ADP
ajst-11366	13	7	the	the	DET
ajst-11366	13	8	interior	interior	NOUN
ajst-11366	13	9	of	of	ADP
ajst-11366	13	10	ceramic	ceramic	ADJ
ajst-11366	13	11	tiles	tile	NOUN
ajst-11366	13	12	might	might	AUX
ajst-11366	13	13	compromise	compromise	VERB
ajst-11366	13	14	their	their	PRON
ajst-11366	13	15	structural	structural	ADJ
ajst-11366	13	16	integrity	integrity	NOUN
ajst-11366	13	17	,	,	PUNCT
ajst-11366	13	18	reducing	reduce	VERB
ajst-11366	13	19	their	their	PRON
ajst-11366	13	20	strength	strength	NOUN
ajst-11366	13	21	and	and	CCONJ
ajst-11366	13	22	durability	durability	NOUN
ajst-11366	13	23	.	.	PUNCT
ajst-11366	14	1	these	these	DET
ajst-11366	14	2	cracks	crack	NOUN
ajst-11366	14	3	can	can	AUX
ajst-11366	14	4	also	also	ADV
ajst-11366	14	5	serve	serve	VERB
ajst-11366	14	6	as	as	ADP
ajst-11366	14	7	pathways	pathway	NOUN
ajst-11366	14	8	for	for	ADP
ajst-11366	14	9	dirt	dirt	NOUN
ajst-11366	14	10	and	and	CCONJ
ajst-11366	14	11	moisture	moisture	NOUN
ajst-11366	14	12	,	,	PUNCT
ajst-11366	14	13	causing	cause	VERB
ajst-11366	14	14	further	further	ADJ
ajst-11366	14	15	deterioration	deterioration	NOUN
ajst-11366	14	16	.	.	PUNCT
ajst-11366	15	1	defects	defect	NOUN
ajst-11366	15	2	in	in	ADP
ajst-11366	15	3	ceramic	ceramic	ADJ
ajst-11366	15	4	tiles	tile	NOUN
ajst-11366	15	5	can	can	AUX
ajst-11366	15	6	have	have	VERB
ajst-11366	15	7	adverse	adverse	ADJ
ajst-11366	15	8	effects	effect	NOUN
ajst-11366	15	9	on	on	ADP
ajst-11366	15	10	their	their	PRON
ajst-11366	15	11	appearance	appearance	NOUN
ajst-11366	15	12	,	,	PUNCT
ajst-11366	15	13	performance	performance	NOUN
ajst-11366	15	14	,	,	PUNCT
ajst-11366	15	15	and	and	CCONJ
ajst-11366	15	16	lifespan.traditional	lifespan.traditional	ADJ
ajst-11366	15	17	manual	manual	ADJ
ajst-11366	15	18	inspection	inspection	NOUN
ajst-11366	15	19	methods	method	NOUN
ajst-11366	15	20	[	[	X
ajst-11366	15	21	2	2	X
ajst-11366	15	22	]	]	PUNCT
ajst-11366	15	23	rely	rely	NOUN
ajst-11366	15	24	on	on	ADP
ajst-11366	15	25	the	the	DET
ajst-11366	15	26	subjective	subjective	ADJ
ajst-11366	15	27	expertise	expertise	NOUN
ajst-11366	15	28	of	of	ADP
ajst-11366	15	29	inspectors	inspector	NOUN
ajst-11366	15	30	to	to	PART
ajst-11366	15	31	identify	identify	VERB
ajst-11366	15	32	flaws	flaw	NOUN
ajst-11366	15	33	and	and	CCONJ
ajst-11366	15	34	defects	defect	NOUN
ajst-11366	15	35	.	.	PUNCT
ajst-11366	16	1	this	this	DET
ajst-11366	16	2	approach	approach	NOUN
ajst-11366	16	3	is	be	AUX
ajst-11366	16	4	inefficient	inefficient	ADJ
ajst-11366	16	5	,	,	PUNCT
ajst-11366	16	6	resource	resource	NOUN
ajst-11366	16	7	-	-	PUNCT
ajst-11366	16	8	intensive	intensive	ADJ
ajst-11366	16	9	,	,	PUNCT
ajst-11366	16	10	heavily	heavily	ADV
ajst-11366	16	11	reliant	reliant	ADJ
ajst-11366	16	12	on	on	ADP
ajst-11366	16	13	human	human	ADJ
ajst-11366	16	14	labor	labor	NOUN
ajst-11366	16	15	,	,	PUNCT
ajst-11366	16	16	and	and	CCONJ
ajst-11366	16	17	prone	prone	ADJ
ajst-11366	16	18	to	to	ADP
ajst-11366	16	19	errors	error	NOUN
ajst-11366	16	20	in	in	ADP
ajst-11366	16	21	detection	detection	NOUN
ajst-11366	16	22	and	and	CCONJ
ajst-11366	16	23	classification	classification	NOUN
ajst-11366	16	24	.	.	PUNCT
ajst-11366	17	1	therefore	therefore	ADV
ajst-11366	17	2	,	,	PUNCT
ajst-11366	17	3	replacing	replace	VERB
ajst-11366	17	4	manual	manual	ADJ
ajst-11366	17	5	inspection	inspection	NOUN
ajst-11366	17	6	with	with	ADP
ajst-11366	17	7	deep	deep	ADJ
ajst-11366	17	8	learning	learning	NOUN
ajst-11366	17	9	object	object	NOUN
ajst-11366	17	10	detection	detection	NOUN
ajst-11366	17	11	algorithms	algorithm	NOUN
ajst-11366	17	12	holds	hold	VERB
ajst-11366	17	13	significant	significant	ADJ
ajst-11366	17	14	importance	importance	NOUN
ajst-11366	17	15	.	.	PUNCT
ajst-11366	18	1	at	at	ADP
ajst-11366	18	2	present	present	ADJ
ajst-11366	18	3	,	,	PUNCT
ajst-11366	18	4	there	there	PRON
ajst-11366	18	5	have	have	AUX
ajst-11366	18	6	been	be	AUX
ajst-11366	18	7	numerous	numerous	ADJ
ajst-11366	18	8	experiments	experiment	NOUN
ajst-11366	18	9	on	on	ADP
ajst-11366	18	10	machine	machine	NOUN
ajst-11366	18	11	vision	vision	NOUN
ajst-11366	18	12	methods	method	NOUN
ajst-11366	18	13	for	for	ADP
ajst-11366	18	14	object	object	NOUN
ajst-11366	18	15	surface	surface	NOUN
ajst-11366	18	16	defect	defect	NOUN
ajst-11366	18	17	detection	detection	NOUN
ajst-11366	18	18	.	.	PUNCT
ajst-11366	19	1	for	for	ADP
ajst-11366	19	2	instance	instance	NOUN
ajst-11366	19	3	,	,	PUNCT
ajst-11366	19	4	pu	pu	PROPN
ajst-11366	19	5	yuxiang[3	yuxiang[3	PROPN
ajst-11366	19	6	]	]	X
ajst-11366	19	7	employed	employ	VERB
ajst-11366	19	8	image	image	NOUN
ajst-11366	19	9	edge	edge	NOUN
ajst-11366	19	10	detection	detection	NOUN
ajst-11366	19	11	to	to	PART
ajst-11366	19	12	determine	determine	VERB
ajst-11366	19	13	the	the	DET
ajst-11366	19	14	presence	presence	NOUN
ajst-11366	19	15	of	of	ADP
ajst-11366	19	16	defects	defect	NOUN
ajst-11366	19	17	on	on	ADP
ajst-11366	19	18	object	object	NOUN
ajst-11366	19	19	surfaces	surface	NOUN
ajst-11366	19	20	based	base	VERB
ajst-11366	19	21	on	on	ADP
ajst-11366	19	22	contours	contours	PROPN
ajst-11366	19	23	.	.	PUNCT
ajst-11366	20	1	through	through	ADP
ajst-11366	20	2	the	the	DET
ajst-11366	20	3	utilization	utilization	NOUN
ajst-11366	20	4	of	of	ADP
ajst-11366	20	5	the	the	DET
ajst-11366	20	6	canny	canny	ADJ
ajst-11366	20	7	algorithm	algorithm	NOUN
ajst-11366	20	8	for	for	ADP
ajst-11366	20	9	image	image	NOUN
ajst-11366	20	10	binarization	binarization	NOUN
ajst-11366	20	11	and	and	CCONJ
ajst-11366	20	12	overlaying	overlay	VERB
ajst-11366	20	13	the	the	DET
ajst-11366	20	14	resulting	result	VERB
ajst-11366	20	15	binary	binary	ADJ
ajst-11366	20	16	image	image	NOUN
ajst-11366	20	17	with	with	ADP
ajst-11366	20	18	the	the	DET
ajst-11366	20	19	original	original	ADJ
ajst-11366	20	20	,	,	PUNCT
ajst-11366	20	21	the	the	DET
ajst-11366	20	22	defect	defect	NOUN
ajst-11366	20	23	positions	position	NOUN
ajst-11366	20	24	could	could	AUX
ajst-11366	20	25	be	be	AUX
ajst-11366	20	26	intuitively	intuitively	ADV
ajst-11366	20	27	displayed	display	VERB
ajst-11366	20	28	.	.	PUNCT
ajst-11366	21	1	with	with	ADP
ajst-11366	21	2	the	the	DET
ajst-11366	21	3	advancement	advancement	NOUN
ajst-11366	21	4	of	of	ADP
ajst-11366	21	5	deep	deep	ADJ
ajst-11366	21	6	learning	learning	NOUN
ajst-11366	21	7	in	in	ADP
ajst-11366	21	8	the	the	DET
ajst-11366	21	9	field	field	NOUN
ajst-11366	21	10	of	of	ADP
ajst-11366	21	11	computer	computer	NOUN
ajst-11366	21	12	vision	vision	NOUN
ajst-11366	21	13	,	,	PUNCT
ajst-11366	21	14	visual	visual	ADJ
ajst-11366	21	15	tasks	task	NOUN
ajst-11366	21	16	similar	similar	ADJ
ajst-11366	21	17	to	to	PART
ajst-11366	21	18	object	object	VERB
ajst-11366	21	19	detection	detection	NOUN
ajst-11366	21	20	have	have	AUX
ajst-11366	21	21	achieved	achieve	VERB
ajst-11366	21	22	breakthroughs	breakthrough	NOUN
ajst-11366	21	23	using	use	VERB
ajst-11366	21	24	neural	neural	ADJ
ajst-11366	21	25	networks	network	NOUN
ajst-11366	21	26	on	on	ADP
ajst-11366	21	27	various	various	ADJ
ajst-11366	21	28	authoritative	authoritative	ADJ
ajst-11366	21	29	datasets	dataset	NOUN
ajst-11366	21	30	.	.	PUNCT
ajst-11366	22	1	yang	yang	PROPN
ajst-11366	22	2	cui[4]proposed	cui[4]propose	VERB
ajst-11366	22	3	a	a	DET
ajst-11366	22	4	machine	machine	NOUN
ajst-11366	22	5	vision	vision	NOUN
ajst-11366	22	6	-	-	PUNCT
ajst-11366	22	7	based	base	VERB
ajst-11366	22	8	method	method	NOUN
ajst-11366	22	9	for	for	ADP
ajst-11366	22	10	detecting	detect	VERB
ajst-11366	22	11	subtle	subtle	ADJ
ajst-11366	22	12	defects	defect	NOUN
ajst-11366	22	13	in	in	ADP
ajst-11366	22	14	images	image	NOUN
ajst-11366	22	15	,	,	PUNCT
ajst-11366	22	16	with	with	ADP
ajst-11366	22	17	the	the	DET
ajst-11366	22	18	main	main	ADJ
ajst-11366	22	19	idea	idea	NOUN
ajst-11366	22	20	of	of	ADP
ajst-11366	22	21	constructing	construct	VERB
ajst-11366	22	22	a	a	DET
ajst-11366	22	23	lightweight	lightweight	ADJ
ajst-11366	22	24	network	network	NOUN
ajst-11366	22	25	model	model	NOUN
ajst-11366	22	26	based	base	VERB
ajst-11366	22	27	on	on	ADP
ajst-11366	22	28	the	the	DET
ajst-11366	22	29	faster	fast	ADJ
ajst-11366	22	30	-	-	PUNCT
ajst-11366	22	31	rcnn	rcnn	NOUN
ajst-11366	22	32	framework	framework	NOUN
ajst-11366	22	33	.	.	PUNCT
ajst-11366	23	1	this	this	DET
ajst-11366	23	2	method	method	NOUN
ajst-11366	23	3	utilizes	utilize	VERB
ajst-11366	23	4	sample	sample	NOUN
ajst-11366	23	5	gradient	gradient	NOUN
ajst-11366	23	6	feature	feature	NOUN
ajst-11366	23	7	information	information	NOUN
ajst-11366	23	8	for	for	ADP
ajst-11366	23	9	nonend	nonend	NOUN
ajst-11366	23	10	-	-	PUNCT
ajst-11366	23	11	to	to	ADP
ajst-11366	23	12	-	-	PUNCT
ajst-11366	23	13	end	end	NOUN
ajst-11366	23	14	network	network	NOUN
ajst-11366	23	15	training	training	NOUN
ajst-11366	23	16	,	,	PUNCT
ajst-11366	23	17	effectively	effectively	ADV
ajst-11366	23	18	enhancing	enhance	VERB
ajst-11366	23	19	the	the	DET
ajst-11366	23	20	model	model	NOUN
ajst-11366	23	21	's	's	PART
ajst-11366	23	22	inference	inference	NOUN
ajst-11366	23	23	capability	capability	NOUN
ajst-11366	23	24	.	.	PUNCT
ajst-11366	24	1	maheshwari	maheshwari	PROPN
ajst-11366	24	2	s.	s.	PROPN
ajst-11366	24	3	biradar[5	biradar[5	PROPN
ajst-11366	24	4	]	]	PUNCT
ajst-11366	24	5	utilized	utilize	VERB
ajst-11366	24	6	a	a	DET
ajst-11366	24	7	supervised	supervised	ADJ
ajst-11366	24	8	three	three	NUM
ajst-11366	24	9	-	-	PUNCT
ajst-11366	24	10	layer	layer	NOUN
ajst-11366	24	11	deep	deep	ADJ
ajst-11366	24	12	convolutional	convolutional	ADJ
ajst-11366	24	13	neural	neural	ADJ
ajst-11366	24	14	network	network	NOUN
ajst-11366	24	15	(	(	PUNCT
ajst-11366	24	16	dcnn	dcnn	PROPN
ajst-11366	24	17	)	)	PUNCT
ajst-11366	24	18	,	,	PUNCT
ajst-11366	24	19	with	with	ADP
ajst-11366	24	20	each	each	DET
ajst-11366	24	21	convolutional	convolutional	ADJ
ajst-11366	24	22	layer	layer	NOUN
ajst-11366	24	23	containing	contain	VERB
ajst-11366	24	24	a	a	DET
ajst-11366	24	25	support	support	NOUN
ajst-11366	24	26	vector	vector	NOUN
ajst-11366	24	27	machine	machine	NOUN
ajst-11366	24	28	(	(	PUNCT
ajst-11366	24	29	svm	svm	PROPN
ajst-11366	24	30	)	)	PUNCT
ajst-11366	24	31	as	as	ADP
ajst-11366	24	32	a	a	DET
ajst-11366	24	33	classifier	classifier	NOUN
ajst-11366	24	34	.	.	PUNCT
ajst-11366	25	1	this	this	DET
ajst-11366	25	2	network	network	NOUN
ajst-11366	25	3	detected	detect	VERB
ajst-11366	25	4	local	local	ADJ
ajst-11366	25	5	connectivity	connectivity	NOUN
ajst-11366	25	6	between	between	ADP
ajst-11366	25	7	each	each	DET
ajst-11366	25	8	pixel	pixel	NOUN
ajst-11366	25	9	,	,	PUNCT
ajst-11366	25	10	aiding	aid	VERB
ajst-11366	25	11	in	in	ADP
ajst-11366	25	12	learning	learn	VERB
ajst-11366	25	13	object	object	NOUN
ajst-11366	25	14	structures	structure	NOUN
ajst-11366	25	15	and	and	CCONJ
ajst-11366	25	16	discerning	discern	VERB
ajst-11366	25	17	defects	defect	NOUN
ajst-11366	25	18	.	.	PUNCT
ajst-11366	26	1	based	base	VERB
ajst-11366	26	2	on	on	ADP
ajst-11366	26	3	deep	deep	ADJ
ajst-11366	26	4	learning	learning	NOUN
ajst-11366	26	5	,	,	PUNCT
ajst-11366	26	6	object	object	VERB
ajst-11366	26	7	detection	detection	NOUN
ajst-11366	26	8	algorithms	algorithm	NOUN
ajst-11366	26	9	are	be	AUX
ajst-11366	26	10	currently	currently	ADV
ajst-11366	26	11	divided	divide	VERB
ajst-11366	26	12	into	into	ADP
ajst-11366	26	13	two	two	NUM
ajst-11366	26	14	main	main	ADJ
ajst-11366	26	15	categories	category	NOUN
ajst-11366	26	16	:	:	PUNCT
ajst-11366	26	17	two	two	NUM
ajst-11366	26	18	-	-	PUNCT
ajst-11366	26	19	stage	stage	NOUN
ajst-11366	26	20	algorithms	algorithm	NOUN
ajst-11366	26	21	represented	represent	VERB
ajst-11366	26	22	by	by	ADP
ajst-11366	26	23	rcnn[6	rcnn[6	PROPN
ajst-11366	26	24	]	]	PUNCT
ajst-11366	26	25	and	and	CCONJ
ajst-11366	26	26	faster	fast	ADJ
ajst-11366	26	27	r	r	VERB
ajst-11366	26	28	-	-	PUNCT
ajst-11366	26	29	cnn[7	cnn[7	NOUN
ajst-11366	26	30	]	]	PUNCT
ajst-11366	26	31	,	,	PUNCT
ajst-11366	26	32	and	and	CCONJ
ajst-11366	26	33	one	one	NUM
ajst-11366	26	34	-	-	PUNCT
ajst-11366	26	35	stage	stage	NOUN
ajst-11366	26	36	algorithms	algorithm	NOUN
ajst-11366	26	37	represented	represent	VERB
ajst-11366	26	38	by	by	ADP
ajst-11366	26	39	yolo[8]、retinanet[9	yolo[8]、retinanet[9	PROPN
ajst-11366	26	40	]	]	PUNCT
ajst-11366	26	41	.	.	PUNCT
ajst-11366	27	1	two	two	NUM
ajst-11366	27	2	-	-	PUNCT
ajst-11366	27	3	stage	stage	NOUN
ajst-11366	27	4	algorithms	algorithm	NOUN
ajst-11366	27	5	extract	extract	VERB
ajst-11366	27	6	region	region	NOUN
ajst-11366	27	7	proposals	proposal	NOUN
ajst-11366	27	8	through	through	ADP
ajst-11366	27	9	feature	feature	NOUN
ajst-11366	27	10	extraction	extraction	NOUN
ajst-11366	27	11	and	and	CCONJ
ajst-11366	27	12	then	then	ADV
ajst-11366	27	13	employ	employ	VERB
ajst-11366	27	14	convolutional	convolutional	ADJ
ajst-11366	27	15	neural	neural	ADJ
ajst-11366	27	16	networks	network	NOUN
ajst-11366	27	17	for	for	ADP
ajst-11366	27	18	regression	regression	NOUN
ajst-11366	27	19	and	and	CCONJ
ajst-11366	27	20	classification	classification	NOUN
ajst-11366	27	21	.	.	PUNCT
ajst-11366	28	1	they	they	PRON
ajst-11366	28	2	exhibit	exhibit	VERB
ajst-11366	28	3	high	high	ADJ
ajst-11366	28	4	accuracy	accuracy	NOUN
ajst-11366	28	5	but	but	CCONJ
ajst-11366	28	6	are	be	AUX
ajst-11366	28	7	slower	slow	ADJ
ajst-11366	28	8	.	.	PUNCT
ajst-11366	29	1	on	on	ADP
ajst-11366	29	2	the	the	DET
ajst-11366	29	3	other	other	ADJ
ajst-11366	29	4	hand	hand	NOUN
ajst-11366	29	5	,	,	PUNCT
ajst-11366	29	6	the	the	DET
ajst-11366	29	7	speed	speed	NOUN
ajst-11366	29	8	-	-	PUNCT
ajst-11366	29	9	focused	focus	VERB
ajst-11366	29	10	improvements	improvement	NOUN
ajst-11366	29	11	in	in	ADP
ajst-11366	29	12	one	one	NUM
ajst-11366	29	13	-	-	PUNCT
ajst-11366	29	14	stage	stage	NOUN
ajst-11366	29	15	detection	detection	NOUN
ajst-11366	29	16	algorithms	algorithm	NOUN
ajst-11366	29	17	,	,	PUNCT
ajst-11366	29	18	while	while	SCONJ
ajst-11366	29	19	addressing	address	VERB
ajst-11366	29	20	speed	speed	NOUN
ajst-11366	29	21	concerns	concern	NOUN
ajst-11366	29	22	,	,	PUNCT
ajst-11366	29	23	tend	tend	VERB
ajst-11366	29	24	to	to	PART
ajst-11366	29	25	sacrifice	sacrifice	VERB
ajst-11366	29	26	a	a	DET
ajst-11366	29	27	certain	certain	ADJ
ajst-11366	29	28	level	level	NOUN
ajst-11366	29	29	of	of	ADP
ajst-11366	29	30	accuracy	accuracy	NOUN
ajst-11366	29	31	.	.	PUNCT
ajst-11366	30	1	the	the	DET
ajst-11366	30	2	faster	fast	ADJ
ajst-11366	30	3	r	r	NOUN
ajst-11366	30	4	-	-	PUNCT
ajst-11366	30	5	cnn	cnn	PROPN
ajst-11366	30	6	network	network	NOUN
ajst-11366	30	7	used	use	VERB
ajst-11366	30	8	in	in	ADP
ajst-11366	30	9	this	this	DET
ajst-11366	30	10	study	study	NOUN
ajst-11366	30	11	,	,	PUNCT
ajst-11366	30	12	which	which	PRON
ajst-11366	30	13	was	be	AUX
ajst-11366	30	14	once	once	ADV
ajst-11366	30	15	considered	consider	VERB
ajst-11366	30	16	a	a	DET
ajst-11366	30	17	twostage	twostage	NOUN
ajst-11366	30	18	network	network	NOUN
ajst-11366	30	19	,	,	PUNCT
ajst-11366	30	20	boasts	boast	VERB
ajst-11366	30	21	a	a	DET
ajst-11366	30	22	favorable	favorable	ADJ
ajst-11366	30	23	balance	balance	NOUN
ajst-11366	30	24	between	between	ADP
ajst-11366	30	25	accuracy	accuracy	NOUN
ajst-11366	30	26	and	and	CCONJ
ajst-11366	30	27	speed	speed	NOUN
ajst-11366	30	28	.	.	PUNCT
ajst-11366	31	1	given	give	VERB
ajst-11366	31	2	the	the	DET
ajst-11366	31	3	characteristics	characteristic	NOUN
ajst-11366	31	4	and	and	CCONJ
ajst-11366	31	5	detection	detection	NOUN
ajst-11366	31	6	requirements	requirement	NOUN
ajst-11366	31	7	of	of	ADP
ajst-11366	31	8	ceramic	ceramic	ADJ
ajst-11366	31	9	tile	tile	NOUN
ajst-11366	31	10	defects	defect	NOUN
ajst-11366	31	11	,	,	PUNCT
ajst-11366	31	12	this	this	DET
ajst-11366	31	13	experiment	experiment	NOUN
ajst-11366	31	14	primarily	primarily	ADV
ajst-11366	31	15	made	make	VERB
ajst-11366	31	16	the	the	DET
ajst-11366	31	17	following	follow	VERB
ajst-11366	31	18	improvements	improvement	NOUN
ajst-11366	31	19	to	to	ADP
ajst-11366	31	20	the	the	DET
ajst-11366	31	21	faster	fast	ADJ
ajst-11366	31	22	r	r	NOUN
ajst-11366	31	23	-	-	PUNCT
ajst-11366	31	24	cnn	cnn	NOUN
ajst-11366	31	25	.	.	PUNCT
ajst-11366	32	1	in	in	ADP
ajst-11366	32	2	order	order	NOUN
ajst-11366	32	3	to	to	PART
ajst-11366	32	4	enhance	enhance	VERB
ajst-11366	32	5	the	the	DET
ajst-11366	32	6	network	network	NOUN
ajst-11366	32	7	's	's	PART
ajst-11366	32	8	detection	detection	NOUN
ajst-11366	32	9	capability	capability	NOUN
ajst-11366	32	10	,	,	PUNCT
ajst-11366	32	11	the	the	DET
ajst-11366	32	12	original	original	ADJ
ajst-11366	32	13	vgg16	vgg16	NOUN
ajst-11366	32	14	backbone	backbone	NOUN
ajst-11366	32	15	was	be	AUX
ajst-11366	32	16	replaced	replace	VERB
ajst-11366	32	17	with	with	ADP
ajst-11366	32	18	resnet101[10	resnet101[10	NOUN
ajst-11366	32	19	]	]	PUNCT
ajst-11366	32	20	.	.	PUNCT
ajst-11366	33	1	the	the	DET
ajst-11366	33	2	bifpn[11	bifpn[11	NOUN
ajst-11366	33	3	]	]	X
ajst-11366	33	4	(	(	PUNCT
ajst-11366	33	5	bidirectional	bidirectional	ADJ
ajst-11366	33	6	feature	feature	NOUN
ajst-11366	33	7	pyramid	pyramid	NOUN
ajst-11366	33	8	network	network	NOUN
ajst-11366	33	9	)	)	PUNCT
ajst-11366	33	10	was	be	AUX
ajst-11366	33	11	introduced	introduce	VERB
ajst-11366	33	12	to	to	PART
ajst-11366	33	13	enhance	enhance	VERB
ajst-11366	33	14	feature	feature	NOUN
ajst-11366	33	15	fusion	fusion	NOUN
ajst-11366	33	16	,	,	PUNCT
ajst-11366	33	17	offering	offer	VERB
ajst-11366	33	18	a	a	DET
ajst-11366	33	19	more	more	ADV
ajst-11366	33	20	accurate	accurate	ADJ
ajst-11366	33	21	response	response	NOUN
ajst-11366	33	22	to	to	ADP
ajst-11366	33	23	the	the	DET
ajst-11366	33	24	diverse	diverse	ADJ
ajst-11366	33	25	sizes	size	NOUN
ajst-11366	33	26	and	and	CCONJ
ajst-11366	33	27	shapes	shape	NOUN
ajst-11366	33	28	of	of	ADP
ajst-11366	33	29	ceramic	ceramic	ADJ
ajst-11366	33	30	tile	tile	NOUN
ajst-11366	33	31	defects	defect	NOUN
ajst-11366	33	32	.	.	PUNCT
ajst-11366	34	1	simultaneously	simultaneously	ADV
ajst-11366	34	2	,	,	PUNCT
ajst-11366	34	3	to	to	PART
ajst-11366	34	4	mitigate	mitigate	VERB
ajst-11366	34	5	the	the	DET
ajst-11366	34	6	parameter	parameter	NOUN
ajst-11366	34	7	increase	increase	NOUN
ajst-11366	34	8	resulting	result	VERB
ajst-11366	34	9	from	from	ADP
ajst-11366	34	10	the	the	DET
ajst-11366	34	11	aforementioned	aforementioned	ADJ
ajst-11366	34	12	changes	change	NOUN
ajst-11366	34	13	,	,	PUNCT
ajst-11366	34	14	depth	depth	NOUN
ajst-11366	34	15	-	-	PUNCT
ajst-11366	34	16	wise	wise	ADJ
ajst-11366	34	17	separable	separable	ADJ
ajst-11366	34	18	convolutions[12	convolutions[12	NOUN
ajst-11366	34	19	]	]	PUNCT
ajst-11366	34	20	were	be	AUX
ajst-11366	34	21	employed	employ	VERB
ajst-11366	34	22	to	to	PART
ajst-11366	34	23	reduce	reduce	VERB
ajst-11366	34	24	detection	detection	NOUN
ajst-11366	34	25	time	time	NOUN
ajst-11366	34	26	.	.	PUNCT
ajst-11366	35	1	finally	finally	ADV
ajst-11366	35	2	,	,	PUNCT
ajst-11366	35	3	to	to	PART
ajst-11366	35	4	prevent	prevent	VERB
ajst-11366	35	5	the	the	DET
ajst-11366	35	6	removal	removal	NOUN
ajst-11366	35	7	of	of	ADP
ajst-11366	35	8	regression	regression	NOUN
ajst-11366	35	9	boxes	box	NOUN
ajst-11366	35	10	with	with	ADP
ajst-11366	35	11	large	large	ADJ
ajst-11366	35	12	overlapping	overlap	VERB
ajst-11366	35	13	areas	area	NOUN
ajst-11366	35	14	,	,	PUNCT
ajst-11366	35	15	the	the	DET
ajst-11366	35	16	soft	soft	ADJ
ajst-11366	35	17	-	-	PUNCT
ajst-11366	35	18	nms[13	nms[13	NOUN
ajst-11366	35	19	]	]	PUNCT
ajst-11366	35	20	technique	technique	NOUN
ajst-11366	35	21	was	be	AUX
ajst-11366	35	22	utilized	utilize	VERB
ajst-11366	35	23	to	to	PART
ajst-11366	35	24	suppress	suppress	VERB
ajst-11366	35	25	the	the	DET
ajst-11366	35	26	scores	score	NOUN
ajst-11366	35	27	of	of	ADP
ajst-11366	35	28	regression	regression	NOUN
ajst-11366	35	29	boxes	box	NOUN
ajst-11366	35	30	,	,	PUNCT
ajst-11366	35	31	thus	thus	ADV
ajst-11366	35	32	increasing	increase	VERB
ajst-11366	35	33	the	the	DET
ajst-11366	35	34	detection	detection	NOUN
ajst-11366	35	35	rate	rate	NOUN
ajst-11366	35	36	.	.	PUNCT
ajst-11366	36	1	185	185	NUM
ajst-11366	36	2	2	2	NUM
ajst-11366	36	3	.	.	PUNCT
ajst-11366	36	4	faster	fast	ADJ
ajst-11366	36	5	r	r	NOUN
ajst-11366	36	6	-	-	PUNCT
ajst-11366	36	7	cnn	cnn	NOUN
ajst-11366	36	8	algorithm	algorithm	NOUN
ajst-11366	36	9	and	and	CCONJ
ajst-11366	36	10	improvements	improvement	NOUN
ajst-11366	36	11	2.1	2.1	NUM
ajst-11366	36	12	.	.	PUNCT
ajst-11366	37	1	faster	fast	ADJ
ajst-11366	37	2	r	r	NOUN
ajst-11366	37	3	-	-	PUNCT
ajst-11366	37	4	cnn	cnn	PROPN
ajst-11366	37	5	and	and	CCONJ
ajst-11366	37	6	the	the	DET
ajst-11366	37	7	network	network	NOUN
ajst-11366	37	8	improved	improve	VERB
ajst-11366	37	9	in	in	ADP
ajst-11366	37	10	this	this	DET
ajst-11366	37	11	article	article	NOUN
ajst-11366	37	12	cnn	cnn	PROPN
ajst-11366	37	13	is	be	AUX
ajst-11366	37	14	an	an	DET
ajst-11366	37	15	object	object	NOUN
ajst-11366	37	16	detection	detection	NOUN
ajst-11366	37	17	network	network	NOUN
ajst-11366	37	18	in	in	ADP
ajst-11366	37	19	the	the	DET
ajst-11366	37	20	field	field	NOUN
ajst-11366	37	21	of	of	ADP
ajst-11366	37	22	deep	deep	ADJ
ajst-11366	37	23	learning	learning	NOUN
ajst-11366	37	24	.	.	PUNCT
ajst-11366	38	1	it	it	PRON
ajst-11366	38	2	was	be	AUX
ajst-11366	38	3	proposed	propose	VERB
ajst-11366	38	4	in	in	ADP
ajst-11366	38	5	2015	2015	NUM
ajst-11366	38	6	by	by	ADP
ajst-11366	38	7	shaoqing	shaoqe	VERB
ajst-11366	38	8	ren	ren	PROPN
ajst-11366	38	9	,	,	PUNCT
ajst-11366	38	10	kaiming	kaime	VERB
ajst-11366	38	11	he	he	PRON
ajst-11366	38	12	,	,	PUNCT
ajst-11366	38	13	ross	ross	PROPN
ajst-11366	38	14	girshick	girshick	PROPN
ajst-11366	38	15	,	,	PUNCT
ajst-11366	38	16	and	and	CCONJ
ajst-11366	38	17	jian	jian	PROPN
ajst-11366	38	18	sun	sun	PROPN
ajst-11366	38	19	.	.	PUNCT
ajst-11366	39	1	it	it	PRON
ajst-11366	39	2	represents	represent	VERB
ajst-11366	39	3	a	a	DET
ajst-11366	39	4	significant	significant	ADJ
ajst-11366	39	5	advancement	advancement	NOUN
ajst-11366	39	6	in	in	ADP
ajst-11366	39	7	detection	detection	NOUN
ajst-11366	39	8	algorithms	algorithm	NOUN
ajst-11366	39	9	,	,	PUNCT
ajst-11366	39	10	addressing	address	VERB
ajst-11366	39	11	a	a	DET
ajst-11366	39	12	series	series	NOUN
ajst-11366	39	13	of	of	ADP
ajst-11366	39	14	issues	issue	NOUN
ajst-11366	39	15	present	present	ADJ
ajst-11366	39	16	in	in	ADP
ajst-11366	39	17	previous	previous	ADJ
ajst-11366	39	18	approaches	approach	NOUN
ajst-11366	39	19	.	.	PUNCT
ajst-11366	40	1	this	this	DET
ajst-11366	40	2	innovation	innovation	NOUN
ajst-11366	40	3	has	have	AUX
ajst-11366	40	4	led	lead	VERB
ajst-11366	40	5	to	to	ADP
ajst-11366	40	6	improvements	improvement	NOUN
ajst-11366	40	7	in	in	ADP
ajst-11366	40	8	detection	detection	NOUN
ajst-11366	40	9	speed	speed	NOUN
ajst-11366	40	10	and	and	CCONJ
ajst-11366	40	11	major	major	ADJ
ajst-11366	40	12	breakthroughs	breakthrough	NOUN
ajst-11366	40	13	in	in	ADP
ajst-11366	40	14	detection	detection	NOUN
ajst-11366	40	15	accuracy	accuracy	NOUN
ajst-11366	40	16	.	.	PUNCT
ajst-11366	41	1	additionally	additionally	ADV
ajst-11366	41	2	,	,	PUNCT
ajst-11366	41	3	it	it	PRON
ajst-11366	41	4	has	have	AUX
ajst-11366	41	5	streamlined	streamline	VERB
ajst-11366	41	6	the	the	DET
ajst-11366	41	7	previously	previously	ADV
ajst-11366	41	8	complex	complex	ADJ
ajst-11366	41	9	multi	multi	ADJ
ajst-11366	41	10	-	-	ADJ
ajst-11366	41	11	stage	stage	NOUN
ajst-11366	41	12	processes	process	NOUN
ajst-11366	41	13	.	.	PUNCT
ajst-11366	42	1	one	one	NUM
ajst-11366	42	2	key	key	ADJ
ajst-11366	42	3	addition	addition	NOUN
ajst-11366	42	4	introduced	introduce	VERB
ajst-11366	42	5	by	by	ADP
ajst-11366	42	6	faster	fast	ADJ
ajst-11366	42	7	r	r	NOUN
ajst-11366	42	8	-	-	PUNCT
ajst-11366	42	9	cnn	cnn	PROPN
ajst-11366	42	10	is	be	AUX
ajst-11366	42	11	the	the	DET
ajst-11366	42	12	region	region	NOUN
ajst-11366	42	13	proposal	proposal	NOUN
ajst-11366	42	14	network	network	NOUN
ajst-11366	42	15	(	(	PUNCT
ajst-11366	42	16	rpn	rpn	PROPN
ajst-11366	42	17	)	)	PUNCT
ajst-11366	42	18	,	,	PUNCT
ajst-11366	42	19	which	which	PRON
ajst-11366	42	20	enhances	enhance	VERB
ajst-11366	42	21	the	the	DET
ajst-11366	42	22	efficiency	efficiency	NOUN
ajst-11366	42	23	of	of	ADP
ajst-11366	42	24	object	object	NOUN
ajst-11366	42	25	detection	detection	NOUN
ajst-11366	42	26	.	.	PUNCT
ajst-11366	43	1	the	the	DET
ajst-11366	43	2	diagram	diagram	NOUN
ajst-11366	43	3	below	below	ADV
ajst-11366	43	4	depicts	depict	VERB
ajst-11366	43	5	the	the	DET
ajst-11366	43	6	network	network	NOUN
ajst-11366	43	7	architecture	architecture	NOUN
ajst-11366	43	8	.	.	PUNCT
ajst-11366	44	1	figure	figure	NOUN
ajst-11366	44	2	1	1	NUM
ajst-11366	44	3	.	.	PUNCT
ajst-11366	44	4	faster	fast	ADJ
ajst-11366	44	5	-	-	PUNCT
ajst-11366	44	6	rcnn	rcnn	NOUN
ajst-11366	44	7	structure	structure	NOUN
ajst-11366	44	8	the	the	DET
ajst-11366	44	9	main	main	ADJ
ajst-11366	44	10	architecture	architecture	NOUN
ajst-11366	44	11	of	of	ADP
ajst-11366	44	12	faster	fast	ADJ
ajst-11366	44	13	r	r	NOUN
ajst-11366	44	14	-	-	PUNCT
ajst-11366	44	15	cnn	cnn	PROPN
ajst-11366	44	16	is	be	AUX
ajst-11366	44	17	shown	show	VERB
ajst-11366	44	18	in	in	ADP
ajst-11366	44	19	the	the	DET
ajst-11366	44	20	diagram	diagram	NOUN
ajst-11366	44	21	.	.	PUNCT
ajst-11366	45	1	initially	initially	ADV
ajst-11366	45	2	,	,	PUNCT
ajst-11366	45	3	the	the	DET
ajst-11366	45	4	image	image	NOUN
ajst-11366	45	5	size	size	NOUN
ajst-11366	45	6	is	be	AUX
ajst-11366	45	7	resized	resize	VERB
ajst-11366	45	8	to	to	PART
ajst-11366	45	9	fit	fit	VERB
ajst-11366	45	10	the	the	DET
ajst-11366	45	11	network	network	NOUN
ajst-11366	45	12	.	.	PUNCT
ajst-11366	46	1	after	after	ADP
ajst-11366	46	2	passing	pass	VERB
ajst-11366	46	3	through	through	ADP
ajst-11366	46	4	the	the	DET
ajst-11366	46	5	convolutional	convolutional	ADJ
ajst-11366	46	6	feature	feature	NOUN
ajst-11366	46	7	extractor	extractor	NOUN
ajst-11366	46	8	,	,	PUNCT
ajst-11366	46	9	faster	fast	ADV
ajst-11366	46	10	r	r	NOUN
ajst-11366	46	11	-	-	PUNCT
ajst-11366	46	12	cnn	cnn	PROPN
ajst-11366	46	13	employs	employ	VERB
ajst-11366	46	14	a	a	DET
ajst-11366	46	15	pretrained	pretraine	VERB
ajst-11366	46	16	convolutional	convolutional	ADJ
ajst-11366	46	17	neural	neural	ADJ
ajst-11366	46	18	network	network	NOUN
ajst-11366	46	19	(	(	PUNCT
ajst-11366	46	20	such	such	ADJ
ajst-11366	46	21	as	as	ADP
ajst-11366	46	22	vgg16	vgg16	PROPN
ajst-11366	46	23	,	,	PUNCT
ajst-11366	46	24	resnet	resnet	NOUN
ajst-11366	46	25	,	,	PUNCT
ajst-11366	46	26	etc	etc	X
ajst-11366	46	27	.	.	X
ajst-11366	46	28	)	)	PUNCT
ajst-11366	46	29	to	to	PART
ajst-11366	46	30	extract	extract	VERB
ajst-11366	46	31	features	feature	NOUN
ajst-11366	46	32	from	from	ADP
ajst-11366	46	33	the	the	DET
ajst-11366	46	34	input	input	NOUN
ajst-11366	46	35	image	image	NOUN
ajst-11366	46	36	.	.	PUNCT
ajst-11366	47	1	these	these	DET
ajst-11366	47	2	features	feature	NOUN
ajst-11366	47	3	are	be	AUX
ajst-11366	47	4	then	then	ADV
ajst-11366	47	5	used	use	VERB
ajst-11366	47	6	for	for	ADP
ajst-11366	47	7	subsequent	subsequent	ADJ
ajst-11366	47	8	object	object	NOUN
ajst-11366	47	9	detection	detection	NOUN
ajst-11366	47	10	tasks	task	NOUN
ajst-11366	47	11	.	.	PUNCT
ajst-11366	48	1	the	the	DET
ajst-11366	48	2	region	region	NOUN
ajst-11366	48	3	proposal	proposal	NOUN
ajst-11366	48	4	network	network	NOUN
ajst-11366	48	5	(	(	PUNCT
ajst-11366	48	6	rpn	rpn	PROPN
ajst-11366	48	7	)	)	PUNCT
ajst-11366	48	8	stands	stand	VERB
ajst-11366	48	9	as	as	ADP
ajst-11366	48	10	the	the	DET
ajst-11366	48	11	core	core	NOUN
ajst-11366	48	12	innovation	innovation	NOUN
ajst-11366	48	13	of	of	ADP
ajst-11366	48	14	faster	fast	ADJ
ajst-11366	48	15	rcnn	rcnn	NOUN
ajst-11366	48	16	.	.	PUNCT
ajst-11366	49	1	it	it	PRON
ajst-11366	49	2	's	be	AUX
ajst-11366	49	3	a	a	DET
ajst-11366	49	4	neural	neural	ADJ
ajst-11366	49	5	network	network	NOUN
ajst-11366	49	6	responsible	responsible	ADJ
ajst-11366	49	7	for	for	ADP
ajst-11366	49	8	generating	generate	VERB
ajst-11366	49	9	candidate	candidate	NOUN
ajst-11366	49	10	bounding	bounding	NOUN
ajst-11366	49	11	boxes	box	NOUN
ajst-11366	49	12	.	.	PUNCT
ajst-11366	50	1	by	by	ADP
ajst-11366	50	2	sliding	slide	VERB
ajst-11366	50	3	a	a	DET
ajst-11366	50	4	window	window	NOUN
ajst-11366	50	5	across	across	ADP
ajst-11366	50	6	the	the	DET
ajst-11366	50	7	feature	feature	NOUN
ajst-11366	50	8	map	map	NOUN
ajst-11366	50	9	,	,	PUNCT
ajst-11366	50	10	the	the	DET
ajst-11366	50	11	rpn	rpn	PROPN
ajst-11366	50	12	predicts	predict	VERB
ajst-11366	50	13	multiple	multiple	ADJ
ajst-11366	50	14	candidate	candidate	NOUN
ajst-11366	50	15	bounding	bounding	NOUN
ajst-11366	50	16	boxes	box	NOUN
ajst-11366	50	17	and	and	CCONJ
ajst-11366	50	18	their	their	PRON
ajst-11366	50	19	corresponding	corresponding	ADJ
ajst-11366	50	20	confidences	confidence	NOUN
ajst-11366	50	21	for	for	ADP
ajst-11366	50	22	each	each	DET
ajst-11366	50	23	window	window	NOUN
ajst-11366	50	24	position	position	NOUN
ajst-11366	50	25	.	.	PUNCT
ajst-11366	51	1	these	these	DET
ajst-11366	51	2	candidate	candidate	NOUN
ajst-11366	51	3	boxes	box	NOUN
ajst-11366	51	4	serve	serve	VERB
ajst-11366	51	5	as	as	ADP
ajst-11366	51	6	regions	region	NOUN
ajst-11366	51	7	likely	likely	ADJ
ajst-11366	51	8	to	to	PART
ajst-11366	51	9	contain	contain	VERB
ajst-11366	51	10	objects	object	NOUN
ajst-11366	51	11	.	.	PUNCT
ajst-11366	52	1	in	in	ADP
ajst-11366	52	2	previous	previous	ADJ
ajst-11366	52	3	r	r	NOUN
ajst-11366	52	4	-	-	PUNCT
ajst-11366	52	5	cnn	cnn	PROPN
ajst-11366	52	6	models	model	NOUN
ajst-11366	52	7	,	,	PUNCT
ajst-11366	52	8	each	each	DET
ajst-11366	52	9	candidate	candidate	NOUN
ajst-11366	52	10	box	box	PROPN
ajst-11366	52	11	was	be	AUX
ajst-11366	52	12	handled	handle	VERB
ajst-11366	52	13	separately	separately	ADV
ajst-11366	52	14	,	,	PUNCT
ajst-11366	52	15	leading	lead	VERB
ajst-11366	52	16	to	to	PART
ajst-11366	52	17	redundant	redundant	ADJ
ajst-11366	52	18	feature	feature	NOUN
ajst-11366	52	19	computation	computation	NOUN
ajst-11366	52	20	.	.	PUNCT
ajst-11366	53	1	to	to	PART
ajst-11366	53	2	address	address	VERB
ajst-11366	53	3	this	this	PRON
ajst-11366	53	4	,	,	PUNCT
ajst-11366	53	5	faster	fast	ADV
ajst-11366	53	6	r	r	NOUN
ajst-11366	53	7	-	-	PUNCT
ajst-11366	53	8	cnn	cnn	PROPN
ajst-11366	53	9	introduces	introduce	VERB
ajst-11366	53	10	the	the	DET
ajst-11366	53	11	roi	roi	NOUN
ajst-11366	53	12	(	(	PUNCT
ajst-11366	53	13	region	region	NOUN
ajst-11366	53	14	of	of	ADP
ajst-11366	53	15	interest	interest	NOUN
ajst-11366	53	16	)	)	PUNCT
ajst-11366	53	17	pooling	pool	VERB
ajst-11366	53	18	layer	layer	NOUN
ajst-11366	53	19	,	,	PUNCT
ajst-11366	53	20	which	which	PRON
ajst-11366	53	21	maps	map	VERB
ajst-11366	53	22	each	each	DET
ajst-11366	53	23	candidate	candidate	NOUN
ajst-11366	53	24	box	box	NOUN
ajst-11366	53	25	to	to	ADP
ajst-11366	53	26	a	a	DET
ajst-11366	53	27	fixed	fix	VERB
ajst-11366	53	28	-	-	PUNCT
ajst-11366	53	29	size	size	NOUN
ajst-11366	53	30	feature	feature	NOUN
ajst-11366	53	31	map	map	NOUN
ajst-11366	53	32	,	,	PUNCT
ajst-11366	53	33	allowing	allow	VERB
ajst-11366	53	34	for	for	ADP
ajst-11366	53	35	shared	shared	ADJ
ajst-11366	53	36	computation	computation	NOUN
ajst-11366	53	37	.	.	PUNCT
ajst-11366	54	1	after	after	ADP
ajst-11366	54	2	roi	roi	NOUN
ajst-11366	54	3	pooling	pooling	NOUN
ajst-11366	54	4	,	,	PUNCT
ajst-11366	54	5	each	each	DET
ajst-11366	54	6	candidate	candidate	NOUN
ajst-11366	54	7	box	box	PROPN
ajst-11366	54	8	is	be	AUX
ajst-11366	54	9	fed	feed	VERB
ajst-11366	54	10	into	into	ADP
ajst-11366	54	11	two	two	NUM
ajst-11366	54	12	parallel	parallel	ADJ
ajst-11366	54	13	branches	branch	NOUN
ajst-11366	54	14	of	of	ADP
ajst-11366	54	15	fully	fully	ADV
ajst-11366	54	16	connected	connected	ADJ
ajst-11366	54	17	layers	layer	NOUN
ajst-11366	54	18	.	.	PUNCT
ajst-11366	55	1	one	one	NUM
ajst-11366	55	2	branch	branch	NOUN
ajst-11366	55	3	is	be	AUX
ajst-11366	55	4	for	for	ADP
ajst-11366	55	5	classification	classification	NOUN
ajst-11366	55	6	,	,	PUNCT
ajst-11366	55	7	determining	determine	VERB
ajst-11366	55	8	whether	whether	SCONJ
ajst-11366	55	9	the	the	DET
ajst-11366	55	10	candidate	candidate	NOUN
ajst-11366	55	11	box	box	PROPN
ajst-11366	55	12	contains	contain	VERB
ajst-11366	55	13	an	an	DET
ajst-11366	55	14	object	object	NOUN
ajst-11366	55	15	,	,	PUNCT
ajst-11366	55	16	while	while	SCONJ
ajst-11366	55	17	the	the	DET
ajst-11366	55	18	other	other	ADJ
ajst-11366	55	19	is	be	AUX
ajst-11366	55	20	for	for	ADP
ajst-11366	55	21	bounding	bound	VERB
ajst-11366	55	22	box	box	NOUN
ajst-11366	55	23	regression	regression	NOUN
ajst-11366	55	24	,	,	PUNCT
ajst-11366	55	25	refining	refine	VERB
ajst-11366	55	26	the	the	DET
ajst-11366	55	27	position	position	NOUN
ajst-11366	55	28	of	of	ADP
ajst-11366	55	29	the	the	DET
ajst-11366	55	30	candidate	candidate	NOUN
ajst-11366	55	31	box	box	NOUN
ajst-11366	55	32	more	more	ADV
ajst-11366	55	33	accurately	accurately	ADV
ajst-11366	55	34	.	.	PUNCT
ajst-11366	56	1	in	in	ADP
ajst-11366	56	2	this	this	DET
ajst-11366	56	3	article	article	NOUN
ajst-11366	56	4	,	,	PUNCT
ajst-11366	56	5	an	an	DET
ajst-11366	56	6	improved	improved	ADJ
ajst-11366	56	7	network	network	NOUN
ajst-11366	56	8	is	be	AUX
ajst-11366	56	9	built	build	VERB
ajst-11366	56	10	upon	upon	SCONJ
ajst-11366	56	11	the	the	DET
ajst-11366	56	12	original	original	ADJ
ajst-11366	56	13	architecture	architecture	NOUN
ajst-11366	56	14	by	by	ADP
ajst-11366	56	15	utilizing	utilize	VERB
ajst-11366	56	16	resnet	resnet	NOUN
ajst-11366	56	17	as	as	ADP
ajst-11366	56	18	the	the	DET
ajst-11366	56	19	backbone	backbone	NOUN
ajst-11366	56	20	.	.	PUNCT
ajst-11366	57	1	the	the	DET
ajst-11366	57	2	neck	neck	NOUN
ajst-11366	57	3	includes	include	VERB
ajst-11366	57	4	a	a	DET
ajst-11366	57	5	bifpn	bifpn	PROPN
ajst-11366	57	6	(	(	PUNCT
ajst-11366	57	7	bi	bi	ADJ
ajst-11366	57	8	-	-	ADJ
ajst-11366	57	9	directional	directional	ADJ
ajst-11366	57	10	feature	feature	NOUN
ajst-11366	57	11	pyramid	pyramid	NOUN
ajst-11366	57	12	network	network	NOUN
ajst-11366	57	13	)	)	PUNCT
ajst-11366	57	14	that	that	PRON
ajst-11366	57	15	efficiently	efficiently	ADV
ajst-11366	57	16	connects	connect	VERB
ajst-11366	57	17	across	across	ADP
ajst-11366	57	18	scales	scale	NOUN
ajst-11366	57	19	and	and	CCONJ
ajst-11366	57	20	fuses	fuse	NOUN
ajst-11366	57	21	features	feature	NOUN
ajst-11366	57	22	with	with	ADP
ajst-11366	57	23	weights	weight	NOUN
ajst-11366	57	24	.	.	PUNCT
ajst-11366	58	1	this	this	DET
ajst-11366	58	2	results	result	NOUN
ajst-11366	58	3	in	in	ADP
ajst-11366	58	4	better	well	ADJ
ajst-11366	58	5	fused	fuse	VERB
ajst-11366	58	6	features	feature	NOUN
ajst-11366	58	7	for	for	ADP
ajst-11366	58	8	classification	classification	NOUN
ajst-11366	58	9	and	and	CCONJ
ajst-11366	58	10	regression	regression	NOUN
ajst-11366	58	11	tasks	task	NOUN
ajst-11366	58	12	.	.	PUNCT
ajst-11366	59	1	deep	deep	ADJ
ajst-11366	59	2	separable	separable	ADJ
ajst-11366	59	3	convolutions	convolution	NOUN
ajst-11366	59	4	are	be	AUX
ajst-11366	59	5	introduced	introduce	VERB
ajst-11366	59	6	to	to	PART
ajst-11366	59	7	reduce	reduce	VERB
ajst-11366	59	8	redundant	redundant	ADJ
ajst-11366	59	9	parameter	parameter	NOUN
ajst-11366	59	10	volume	volume	NOUN
ajst-11366	59	11	.	.	PUNCT
ajst-11366	60	1	lastly	lastly	ADV
ajst-11366	60	2	,	,	PUNCT
ajst-11366	60	3	soft	soft	ADJ
ajst-11366	60	4	-	-	PUNCT
ajst-11366	60	5	nms	nms	NOUN
ajst-11366	60	6	is	be	AUX
ajst-11366	60	7	incorporated	incorporate	VERB
ajst-11366	60	8	,	,	PUNCT
ajst-11366	60	9	suppressing	suppress	VERB
ajst-11366	60	10	scores	score	NOUN
ajst-11366	60	11	based	base	VERB
ajst-11366	60	12	on	on	ADP
ajst-11366	60	13	intersection	intersection	NOUN
ajst-11366	60	14	over	over	ADP
ajst-11366	60	15	union	union	NOUN
ajst-11366	60	16	(	(	PUNCT
ajst-11366	60	17	iou	iou	NOUN
ajst-11366	60	18	)	)	PUNCT
ajst-11366	60	19	and	and	CCONJ
ajst-11366	60	20	adjusting	adjust	VERB
ajst-11366	60	21	confidences	confidence	NOUN
ajst-11366	60	22	,	,	PUNCT
ajst-11366	60	23	significantly	significantly	ADV
ajst-11366	60	24	preserving	preserve	VERB
ajst-11366	60	25	true	true	ADJ
ajst-11366	60	26	boxes	box	NOUN
ajst-11366	60	27	and	and	CCONJ
ajst-11366	60	28	enhancing	enhance	VERB
ajst-11366	60	29	accuracy	accuracy	NOUN
ajst-11366	60	30	.	.	PUNCT
ajst-11366	61	1	the	the	DET
ajst-11366	61	2	network	network	NOUN
ajst-11366	61	3	structure	structure	NOUN
ajst-11366	61	4	diagram	diagram	NOUN
ajst-11366	61	5	for	for	ADP
ajst-11366	61	6	the	the	DET
ajst-11366	61	7	improved	improved	ADJ
ajst-11366	61	8	version	version	NOUN
ajst-11366	61	9	is	be	AUX
ajst-11366	61	10	as	as	SCONJ
ajst-11366	61	11	follows	follow	VERB
ajst-11366	61	12	:	:	PUNCT
ajst-11366	61	13	figure	figure	NOUN
ajst-11366	61	14	2	2	NUM
ajst-11366	61	15	.	.	PUNCT
ajst-11366	61	16	improved	improved	ADJ
ajst-11366	61	17	network	network	NOUN
ajst-11366	61	18	186	186	NUM
ajst-11366	61	19	2.2	2.2	NUM
ajst-11366	61	20	.	.	PUNCT
ajst-11366	62	1	backbone	backbone	NOUN
ajst-11366	62	2	network	network	NOUN
ajst-11366	62	3	resnet	resnet	NOUN
ajst-11366	62	4	resnet	resnet	NOUN
ajst-11366	62	5	(	(	PUNCT
ajst-11366	62	6	residual	residual	ADJ
ajst-11366	62	7	networks	network	NOUN
ajst-11366	62	8	)	)	PUNCT
ajst-11366	62	9	is	be	AUX
ajst-11366	62	10	a	a	DET
ajst-11366	62	11	convolutional	convolutional	ADJ
ajst-11366	62	12	neural	neural	ADJ
ajst-11366	62	13	network	network	NOUN
ajst-11366	62	14	(	(	PUNCT
ajst-11366	62	15	cnn	cnn	PROPN
ajst-11366	62	16	)	)	PUNCT
ajst-11366	62	17	architecture	architecture	NOUN
ajst-11366	62	18	in	in	ADP
ajst-11366	62	19	the	the	DET
ajst-11366	62	20	field	field	NOUN
ajst-11366	62	21	of	of	ADP
ajst-11366	62	22	deep	deep	ADJ
ajst-11366	62	23	learning	learning	NOUN
ajst-11366	62	24	,	,	PUNCT
ajst-11366	62	25	proposed	propose	VERB
ajst-11366	62	26	by	by	ADP
ajst-11366	62	27	kaiming	kaime	VERB
ajst-11366	62	28	he	he	PRON
ajst-11366	62	29	and	and	CCONJ
ajst-11366	62	30	others	other	NOUN
ajst-11366	62	31	in	in	ADP
ajst-11366	62	32	2015	2015	NUM
ajst-11366	62	33	.	.	PUNCT
ajst-11366	63	1	the	the	DET
ajst-11366	63	2	primary	primary	ADJ
ajst-11366	63	3	contribution	contribution	NOUN
ajst-11366	63	4	of	of	ADP
ajst-11366	63	5	resnet	resnet	NOUN
ajst-11366	63	6	lies	lie	NOUN
ajst-11366	63	7	in	in	ADP
ajst-11366	63	8	its	its	PRON
ajst-11366	63	9	solution	solution	NOUN
ajst-11366	63	10	to	to	ADP
ajst-11366	63	11	the	the	DET
ajst-11366	63	12	issues	issue	NOUN
ajst-11366	63	13	of	of	ADP
ajst-11366	63	14	vanishing	vanish	VERB
ajst-11366	63	15	gradients	gradient	NOUN
ajst-11366	63	16	and	and	CCONJ
ajst-11366	63	17	exploding	explode	VERB
ajst-11366	63	18	gradients	gradient	NOUN
ajst-11366	63	19	during	during	ADP
ajst-11366	63	20	training	training	NOUN
ajst-11366	63	21	of	of	ADP
ajst-11366	63	22	deep	deep	ADJ
ajst-11366	63	23	neural	neural	ADJ
ajst-11366	63	24	networks	network	NOUN
ajst-11366	63	25	,	,	PUNCT
ajst-11366	63	26	enabling	enable	VERB
ajst-11366	63	27	the	the	DET
ajst-11366	63	28	training	training	NOUN
ajst-11366	63	29	of	of	ADP
ajst-11366	63	30	even	even	ADV
ajst-11366	63	31	deeper	deep	ADJ
ajst-11366	63	32	networks	network	NOUN
ajst-11366	63	33	and	and	CCONJ
ajst-11366	63	34	achieving	achieve	VERB
ajst-11366	63	35	improved	improved	ADJ
ajst-11366	63	36	performance	performance	NOUN
ajst-11366	63	37	.	.	PUNCT
ajst-11366	64	1	traditional	traditional	ADJ
ajst-11366	64	2	deep	deep	ADJ
ajst-11366	64	3	neural	neural	ADJ
ajst-11366	64	4	networks	network	NOUN
ajst-11366	64	5	tend	tend	VERB
ajst-11366	64	6	to	to	PART
ajst-11366	64	7	encounter	encounter	VERB
ajst-11366	64	8	the	the	DET
ajst-11366	64	9	vanishing	vanish	VERB
ajst-11366	64	10	gradient	gradient	NOUN
ajst-11366	64	11	problem	problem	NOUN
ajst-11366	64	12	as	as	ADP
ajst-11366	64	13	the	the	DET
ajst-11366	64	14	number	number	NOUN
ajst-11366	64	15	of	of	ADP
ajst-11366	64	16	layers	layer	NOUN
ajst-11366	64	17	increases	increase	NOUN
ajst-11366	64	18	,	,	PUNCT
ajst-11366	64	19	where	where	SCONJ
ajst-11366	64	20	gradients	gradient	NOUN
ajst-11366	64	21	diminish	diminish	VERB
ajst-11366	64	22	during	during	ADP
ajst-11366	64	23	backpropagation	backpropagation	NOUN
ajst-11366	64	24	,	,	PUNCT
ajst-11366	64	25	rendering	render	VERB
ajst-11366	64	26	ineffective	ineffective	ADJ
ajst-11366	64	27	parameter	parameter	NOUN
ajst-11366	64	28	updates	update	NOUN
ajst-11366	64	29	.	.	PUNCT
ajst-11366	65	1	resnet	resnet	ADJ
ajst-11366	65	2	addresses	address	NOUN
ajst-11366	65	3	this	this	PRON
ajst-11366	65	4	by	by	ADP
ajst-11366	65	5	introducing	introduce	VERB
ajst-11366	65	6	"	"	PUNCT
ajst-11366	65	7	residual	residual	ADJ
ajst-11366	65	8	blocks	block	NOUN
ajst-11366	65	9	.	.	PUNCT
ajst-11366	65	10	"	"	PUNCT
ajst-11366	66	1	each	each	DET
ajst-11366	66	2	residual	residual	ADJ
ajst-11366	66	3	block	block	NOUN
ajst-11366	66	4	includes	include	VERB
ajst-11366	66	5	a	a	DET
ajst-11366	66	6	skip	skip	ADJ
ajst-11366	66	7	connection	connection	NOUN
ajst-11366	66	8	(	(	PUNCT
ajst-11366	66	9	also	also	ADV
ajst-11366	66	10	known	know	VERB
ajst-11366	66	11	as	as	ADP
ajst-11366	66	12	a	a	DET
ajst-11366	66	13	"	"	PUNCT
ajst-11366	66	14	shortcut	shortcut	NOUN
ajst-11366	66	15	"	"	PUNCT
ajst-11366	66	16	or	or	CCONJ
ajst-11366	66	17	"	"	PUNCT
ajst-11366	66	18	identity	identity	NOUN
ajst-11366	66	19	"	"	PUNCT
ajst-11366	66	20	connection	connection	NOUN
ajst-11366	66	21	)	)	PUNCT
ajst-11366	66	22	,	,	PUNCT
ajst-11366	66	23	allowing	allow	VERB
ajst-11366	66	24	gradients	gradient	NOUN
ajst-11366	66	25	to	to	PART
ajst-11366	66	26	flow	flow	VERB
ajst-11366	66	27	directly	directly	ADV
ajst-11366	66	28	,	,	PUNCT
ajst-11366	66	29	thereby	thereby	ADV
ajst-11366	66	30	preventing	prevent	VERB
ajst-11366	66	31	gradient	gradient	ADJ
ajst-11366	66	32	vanishing	vanishing	NOUN
ajst-11366	66	33	.	.	PUNCT
ajst-11366	67	1	a	a	DET
ajst-11366	67	2	typical	typical	ADJ
ajst-11366	67	3	residual	residual	ADJ
ajst-11366	67	4	block	block	NOUN
ajst-11366	67	5	consists	consist	VERB
ajst-11366	67	6	of	of	ADP
ajst-11366	67	7	two	two	NUM
ajst-11366	67	8	convolutional	convolutional	ADJ
ajst-11366	67	9	layers	layer	NOUN
ajst-11366	67	10	.	.	PUNCT
ajst-11366	68	1	if	if	SCONJ
ajst-11366	68	2	the	the	DET
ajst-11366	68	3	input	input	NOUN
ajst-11366	68	4	is	be	AUX
ajst-11366	68	5	denoted	denote	VERB
ajst-11366	68	6	as	as	ADP
ajst-11366	68	7	x	x	PROPN
ajst-11366	68	8	and	and	CCONJ
ajst-11366	68	9	the	the	DET
ajst-11366	68	10	output	output	NOUN
ajst-11366	68	11	of	of	ADP
ajst-11366	68	12	the	the	DET
ajst-11366	68	13	residual	residual	ADJ
ajst-11366	68	14	block	block	NOUN
ajst-11366	68	15	is	be	AUX
ajst-11366	68	16	denoted	denote	VERB
ajst-11366	68	17	as	as	ADP
ajst-11366	68	18	f(x	f(x	PROPN
ajst-11366	68	19	)	)	PUNCT
ajst-11366	68	20	,	,	PUNCT
ajst-11366	68	21	the	the	DET
ajst-11366	68	22	computation	computation	NOUN
ajst-11366	68	23	of	of	ADP
ajst-11366	68	24	the	the	DET
ajst-11366	68	25	residual	residual	ADJ
ajst-11366	68	26	block	block	NOUN
ajst-11366	68	27	can	can	AUX
ajst-11366	68	28	be	be	AUX
ajst-11366	68	29	expressed	express	VERB
ajst-11366	68	30	as	as	ADP
ajst-11366	68	31	:	:	PUNCT
ajst-11366	68	32	f(x	f(x	PROPN
ajst-11366	68	33	)	)	PUNCT
ajst-11366	69	1	=	=	PUNCT
ajst-11366	70	1	x	x	PUNCT
ajst-11366	70	2	+	+	NUM
ajst-11366	70	3	h(x	h(x	PROPN
ajst-11366	70	4	)	)	PUNCT
ajst-11366	70	5	,	,	PUNCT
ajst-11366	70	6	where	where	SCONJ
ajst-11366	70	7	h(x	h(x	PROPN
ajst-11366	70	8	)	)	PUNCT
ajst-11366	70	9	represents	represent	VERB
ajst-11366	70	10	the	the	DET
ajst-11366	70	11	result	result	NOUN
ajst-11366	70	12	of	of	ADP
ajst-11366	70	13	the	the	DET
ajst-11366	70	14	convolutional	convolutional	ADJ
ajst-11366	70	15	layers	layer	NOUN
ajst-11366	70	16	within	within	ADP
ajst-11366	70	17	the	the	DET
ajst-11366	70	18	residual	residual	ADJ
ajst-11366	70	19	block	block	NOUN
ajst-11366	70	20	.	.	PUNCT
ajst-11366	71	1	if	if	SCONJ
ajst-11366	71	2	the	the	DET
ajst-11366	71	3	network	network	NOUN
ajst-11366	71	4	considers	consider	VERB
ajst-11366	71	5	the	the	DET
ajst-11366	71	6	identity	identity	NOUN
ajst-11366	71	7	mapping	mapping	NOUN
ajst-11366	71	8	(	(	PUNCT
ajst-11366	71	9	input	input	NOUN
ajst-11366	71	10	and	and	CCONJ
ajst-11366	71	11	output	output	NOUN
ajst-11366	71	12	consistency	consistency	NOUN
ajst-11366	71	13	)	)	PUNCT
ajst-11366	71	14	to	to	PART
ajst-11366	71	15	be	be	AUX
ajst-11366	71	16	optimal	optimal	ADJ
ajst-11366	71	17	,	,	PUNCT
ajst-11366	71	18	h(x	h(x	PROPN
ajst-11366	71	19	)	)	PUNCT
ajst-11366	71	20	can	can	AUX
ajst-11366	71	21	be	be	AUX
ajst-11366	71	22	set	set	VERB
ajst-11366	71	23	to	to	ADP
ajst-11366	71	24	a	a	DET
ajst-11366	71	25	function	function	NOUN
ajst-11366	71	26	close	close	ADV
ajst-11366	71	27	to	to	ADP
ajst-11366	71	28	zero	zero	NUM
ajst-11366	71	29	,	,	PUNCT
ajst-11366	71	30	effectively	effectively	ADV
ajst-11366	71	31	reducing	reduce	VERB
ajst-11366	71	32	the	the	DET
ajst-11366	71	33	residual	residual	ADJ
ajst-11366	71	34	block	block	NOUN
ajst-11366	71	35	to	to	ADP
ajst-11366	71	36	an	an	DET
ajst-11366	71	37	identity	identity	NOUN
ajst-11366	71	38	mapping	mapping	NOUN
ajst-11366	71	39	.	.	PUNCT
ajst-11366	72	1	this	this	DET
ajst-11366	72	2	design	design	NOUN
ajst-11366	72	3	allows	allow	VERB
ajst-11366	72	4	the	the	DET
ajst-11366	72	5	network	network	NOUN
ajst-11366	72	6	to	to	PART
ajst-11366	72	7	selectively	selectively	ADV
ajst-11366	72	8	learn	learn	VERB
ajst-11366	72	9	residuals	residual	NOUN
ajst-11366	72	10	,	,	PUNCT
ajst-11366	72	11	adapting	adapt	VERB
ajst-11366	72	12	to	to	ADP
ajst-11366	72	13	various	various	ADJ
ajst-11366	72	14	feature	feature	NOUN
ajst-11366	72	15	extraction	extraction	NOUN
ajst-11366	72	16	needs	need	NOUN
ajst-11366	72	17	.	.	PUNCT
ajst-11366	73	1	resnet	resnet	NOUN
ajst-11366	73	2	is	be	AUX
ajst-11366	73	3	an	an	DET
ajst-11366	73	4	architecture	architecture	NOUN
ajst-11366	73	5	that	that	PRON
ajst-11366	73	6	tackles	tackle	VERB
ajst-11366	73	7	the	the	DET
ajst-11366	73	8	problem	problem	NOUN
ajst-11366	73	9	of	of	ADP
ajst-11366	73	10	vanishing	vanish	VERB
ajst-11366	73	11	gradients	gradient	NOUN
ajst-11366	73	12	in	in	ADP
ajst-11366	73	13	training	train	VERB
ajst-11366	73	14	deep	deep	ADJ
ajst-11366	73	15	neural	neural	ADJ
ajst-11366	73	16	networks	network	NOUN
ajst-11366	73	17	by	by	ADP
ajst-11366	73	18	introducing	introduce	VERB
ajst-11366	73	19	residual	residual	ADJ
ajst-11366	73	20	blocks	block	NOUN
ajst-11366	73	21	and	and	CCONJ
ajst-11366	73	22	skip	skip	ADJ
ajst-11366	73	23	connections	connection	NOUN
ajst-11366	73	24	.	.	PUNCT
ajst-11366	74	1	its	its	PRON
ajst-11366	74	2	innovative	innovative	ADJ
ajst-11366	74	3	design	design	NOUN
ajst-11366	74	4	enables	enable	VERB
ajst-11366	74	5	the	the	DET
ajst-11366	74	6	training	training	NOUN
ajst-11366	74	7	of	of	ADP
ajst-11366	74	8	very	very	ADV
ajst-11366	74	9	deep	deep	ADJ
ajst-11366	74	10	networks	network	NOUN
ajst-11366	74	11	,	,	PUNCT
ajst-11366	74	12	leading	lead	VERB
ajst-11366	74	13	to	to	ADP
ajst-11366	74	14	outstanding	outstanding	ADJ
ajst-11366	74	15	performance	performance	NOUN
ajst-11366	74	16	across	across	ADP
ajst-11366	74	17	a	a	DET
ajst-11366	74	18	variety	variety	NOUN
ajst-11366	74	19	of	of	ADP
ajst-11366	74	20	computer	computer	NOUN
ajst-11366	74	21	vision	vision	NOUN
ajst-11366	74	22	tasks	task	NOUN
ajst-11366	74	23	.	.	PUNCT
ajst-11366	75	1	figure	figure	NOUN
ajst-11366	75	2	3	3	NUM
ajst-11366	75	3	.	.	PUNCT
ajst-11366	75	4	residual	residual	ADJ
ajst-11366	75	5	block	block	NOUN
ajst-11366	75	6	2.3	2.3	NUM
ajst-11366	75	7	.	.	PUNCT
ajst-11366	76	1	bifpn	bifpn	PROPN
ajst-11366	76	2	bifpn	bifpn	PROPN
ajst-11366	76	3	stands	stand	VERB
ajst-11366	76	4	for	for	ADP
ajst-11366	76	5	bidirectional	bidirectional	ADJ
ajst-11366	76	6	feature	feature	NOUN
ajst-11366	76	7	pyramid	pyramid	NOUN
ajst-11366	76	8	network	network	NOUN
ajst-11366	76	9	,	,	PUNCT
ajst-11366	76	10	which	which	PRON
ajst-11366	76	11	is	be	AUX
ajst-11366	76	12	a	a	DET
ajst-11366	76	13	neural	neural	ADJ
ajst-11366	76	14	network	network	NOUN
ajst-11366	76	15	architecture	architecture	NOUN
ajst-11366	76	16	widely	widely	ADV
ajst-11366	76	17	used	use	VERB
ajst-11366	76	18	in	in	ADP
ajst-11366	76	19	tasks	task	NOUN
ajst-11366	76	20	such	such	ADJ
ajst-11366	76	21	as	as	ADP
ajst-11366	76	22	object	object	NOUN
ajst-11366	76	23	detection	detection	NOUN
ajst-11366	76	24	and	and	CCONJ
ajst-11366	76	25	semantic	semantic	ADJ
ajst-11366	76	26	segmentation	segmentation	NOUN
ajst-11366	76	27	.	.	PUNCT
ajst-11366	77	1	it	it	PRON
ajst-11366	77	2	effectively	effectively	ADV
ajst-11366	77	3	integrates	integrate	VERB
ajst-11366	77	4	feature	feature	NOUN
ajst-11366	77	5	information	information	NOUN
ajst-11366	77	6	across	across	ADP
ajst-11366	77	7	multiple	multiple	ADJ
ajst-11366	77	8	scales	scale	NOUN
ajst-11366	77	9	.	.	PUNCT
ajst-11366	78	1	bifpn	bifpn	PROPN
ajst-11366	78	2	draws	draw	VERB
ajst-11366	78	3	inspiration	inspiration	NOUN
ajst-11366	78	4	from	from	ADP
ajst-11366	78	5	feature	feature	NOUN
ajst-11366	78	6	pyramid	pyramid	NOUN
ajst-11366	78	7	networks	network	NOUN
ajst-11366	78	8	(	(	PUNCT
ajst-11366	78	9	fpn	fpn	ADJ
ajst-11366	78	10	)	)	PUNCT
ajst-11366	78	11	and	and	CCONJ
ajst-11366	78	12	aims	aim	VERB
ajst-11366	78	13	to	to	PART
ajst-11366	78	14	address	address	VERB
ajst-11366	78	15	the	the	DET
ajst-11366	78	16	fusion	fusion	NOUN
ajst-11366	78	17	of	of	ADP
ajst-11366	78	18	features	feature	NOUN
ajst-11366	78	19	at	at	ADP
ajst-11366	78	20	different	different	ADJ
ajst-11366	78	21	scales	scale	NOUN
ajst-11366	78	22	,	,	PUNCT
ajst-11366	78	23	allowing	allow	VERB
ajst-11366	78	24	the	the	DET
ajst-11366	78	25	network	network	NOUN
ajst-11366	78	26	to	to	PART
ajst-11366	78	27	capture	capture	VERB
ajst-11366	78	28	multi	multi	ADJ
ajst-11366	78	29	-	-	ADJ
ajst-11366	78	30	scale	scale	ADJ
ajst-11366	78	31	information	information	NOUN
ajst-11366	78	32	of	of	ADP
ajst-11366	78	33	objects	object	NOUN
ajst-11366	78	34	in	in	ADP
ajst-11366	78	35	various	various	ADJ
ajst-11366	78	36	levels	level	NOUN
ajst-11366	78	37	of	of	ADP
ajst-11366	78	38	feature	feature	NOUN
ajst-11366	78	39	representation	representation	NOUN
ajst-11366	78	40	.	.	PUNCT
ajst-11366	79	1	bifpn	bifpn	PROPN
ajst-11366	79	2	improves	improve	VERB
ajst-11366	79	3	upon	upon	SCONJ
ajst-11366	79	4	fpn	fpn	VERB
ajst-11366	79	5	by	by	ADP
ajst-11366	79	6	introducing	introduce	VERB
ajst-11366	79	7	bidirectional	bidirectional	ADJ
ajst-11366	79	8	information	information	NOUN
ajst-11366	79	9	flow	flow	NOUN
ajst-11366	79	10	,	,	PUNCT
ajst-11366	79	11	further	far	ADV
ajst-11366	79	12	enhancing	enhance	VERB
ajst-11366	79	13	feature	feature	NOUN
ajst-11366	79	14	representation.the	representation.the	PRON
ajst-11366	79	15	following	follow	VERB
ajst-11366	79	16	image	image	NOUN
ajst-11366	79	17	illustrates	illustrate	VERB
ajst-11366	79	18	the	the	DET
ajst-11366	79	19	differences	difference	NOUN
ajst-11366	79	20	between	between	ADP
ajst-11366	79	21	fpn	fpn	PROPN
ajst-11366	79	22	and	and	CCONJ
ajst-11366	79	23	bifpn	bifpn	PROPN
ajst-11366	79	24	.	.	PUNCT
ajst-11366	80	1	(	(	PUNCT
ajst-11366	80	2	a	a	X
ajst-11366	80	3	)	)	PUNCT
ajst-11366	80	4	fpn	fpn	NOUN
ajst-11366	80	5	(	(	PUNCT
ajst-11366	80	6	b	b	NOUN
ajst-11366	80	7	)	)	PUNCT
ajst-11366	80	8	bifpn	bifpn	PROPN
ajst-11366	80	9	figure	figure	NOUN
ajst-11366	80	10	4	4	NUM
ajst-11366	80	11	.	.	PUNCT
ajst-11366	80	12	comparison	comparison	NOUN
ajst-11366	80	13	between	between	ADP
ajst-11366	80	14	fpn	fpn	NOUN
ajst-11366	80	15	and	and	CCONJ
ajst-11366	80	16	bifpn	bifpn	VERB
ajst-11366	80	17	the	the	DET
ajst-11366	80	18	key	key	ADJ
ajst-11366	80	19	idea	idea	NOUN
ajst-11366	80	20	behind	behind	ADP
ajst-11366	80	21	bifpn	bifpn	PROPN
ajst-11366	80	22	is	be	AUX
ajst-11366	80	23	to	to	PART
ajst-11366	80	24	perform	perform	VERB
ajst-11366	80	25	not	not	PART
ajst-11366	80	26	only	only	ADV
ajst-11366	80	27	topdown	topdown	ADJ
ajst-11366	80	28	information	information	NOUN
ajst-11366	80	29	fusion	fusion	NOUN
ajst-11366	80	30	among	among	ADP
ajst-11366	80	31	higher	high	ADJ
ajst-11366	80	32	-	-	PUNCT
ajst-11366	80	33	resolution	resolution	NOUN
ajst-11366	80	34	feature	feature	NOUN
ajst-11366	80	35	pyramid	pyramid	NOUN
ajst-11366	80	36	levels	level	NOUN
ajst-11366	80	37	,	,	PUNCT
ajst-11366	80	38	but	but	CCONJ
ajst-11366	80	39	also	also	ADV
ajst-11366	80	40	bottom	bottom	ADJ
ajst-11366	80	41	-	-	PUNCT
ajst-11366	80	42	up	up	ADP
ajst-11366	80	43	information	information	NOUN
ajst-11366	80	44	fusion	fusion	NOUN
ajst-11366	80	45	among	among	ADP
ajst-11366	80	46	lower	low	ADJ
ajst-11366	80	47	-	-	PUNCT
ajst-11366	80	48	resolution	resolution	NOUN
ajst-11366	80	49	layers	layer	NOUN
ajst-11366	80	50	.	.	PUNCT
ajst-11366	81	1	this	this	DET
ajst-11366	81	2	bidirectional	bidirectional	ADJ
ajst-11366	81	3	flow	flow	NOUN
ajst-11366	81	4	structure	structure	NOUN
ajst-11366	81	5	enables	enable	VERB
ajst-11366	81	6	better	well	ADJ
ajst-11366	81	7	propagation	propagation	NOUN
ajst-11366	81	8	of	of	ADP
ajst-11366	81	9	feature	feature	NOUN
ajst-11366	81	10	information	information	NOUN
ajst-11366	81	11	at	at	ADP
ajst-11366	81	12	different	different	ADJ
ajst-11366	81	13	scales	scale	NOUN
ajst-11366	81	14	while	while	SCONJ
ajst-11366	81	15	maintaining	maintain	VERB
ajst-11366	81	16	a	a	DET
ajst-11366	81	17	balance	balance	NOUN
ajst-11366	81	18	between	between	ADP
ajst-11366	81	19	detailed	detailed	ADJ
ajst-11366	81	20	and	and	CCONJ
ajst-11366	81	21	semantic	semantic	ADJ
ajst-11366	81	22	information	information	NOUN
ajst-11366	81	23	.	.	PUNCT
ajst-11366	82	1	the	the	DET
ajst-11366	82	2	architecture	architecture	NOUN
ajst-11366	82	3	of	of	ADP
ajst-11366	82	4	bifpn	bifpn	PROPN
ajst-11366	82	5	involves	involve	VERB
ajst-11366	82	6	the	the	DET
ajst-11366	82	7	following	follow	VERB
ajst-11366	82	8	key	key	ADJ
ajst-11366	82	9	steps	step	NOUN
ajst-11366	82	10	:	:	PUNCT
ajst-11366	82	11	top	top	ADJ
ajst-11366	82	12	-	-	PUNCT
ajst-11366	82	13	down	down	ADP
ajst-11366	82	14	information	information	NOUN
ajst-11366	82	15	flow	flow	NOUN
ajst-11366	82	16	,	,	PUNCT
ajst-11366	82	17	bottom	bottom	ADJ
ajst-11366	82	18	-	-	PUNCT
ajst-11366	82	19	up	up	ADP
ajst-11366	82	20	information	information	NOUN
ajst-11366	82	21	flow	flow	NOUN
ajst-11366	82	22	,	,	PUNCT
ajst-11366	82	23	and	and	CCONJ
ajst-11366	82	24	bidirectional	bidirectional	ADJ
ajst-11366	82	25	information	information	NOUN
ajst-11366	82	26	flow	flow	NOUN
ajst-11366	82	27	balance	balance	NOUN
ajst-11366	82	28	.	.	PUNCT
ajst-11366	83	1	these	these	DET
ajst-11366	83	2	steps	step	NOUN
ajst-11366	83	3	enable	enable	VERB
ajst-11366	83	4	bifpn	bifpn	PROPN
ajst-11366	83	5	to	to	PART
ajst-11366	83	6	capture	capture	VERB
ajst-11366	83	7	rich	rich	ADJ
ajst-11366	83	8	semantic	semantic	ADJ
ajst-11366	83	9	information	information	NOUN
ajst-11366	83	10	,	,	PUNCT
ajst-11366	83	11	convey	convey	VERB
ajst-11366	83	12	detected	detect	VERB
ajst-11366	83	13	details	detail	NOUN
ajst-11366	83	14	and	and	CCONJ
ajst-11366	83	15	local	local	ADJ
ajst-11366	83	16	features	feature	NOUN
ajst-11366	83	17	,	,	PUNCT
ajst-11366	83	18	allowing	allow	VERB
ajst-11366	83	19	the	the	DET
ajst-11366	83	20	network	network	NOUN
ajst-11366	83	21	to	to	PART
ajst-11366	83	22	adapt	adapt	VERB
ajst-11366	83	23	better	well	ADV
ajst-11366	83	24	to	to	ADP
ajst-11366	83	25	targets	target	NOUN
ajst-11366	83	26	of	of	ADP
ajst-11366	83	27	different	different	ADJ
ajst-11366	83	28	scales	scale	NOUN
ajst-11366	83	29	.	.	PUNCT
ajst-11366	84	1	2.4	2.4	NUM
ajst-11366	84	2	.	.	PUNCT
ajst-11366	85	1	depthwise	depthwise	NOUN
ajst-11366	85	2	separable	separable	ADJ
ajst-11366	85	3	convolution	convolution	NOUN
ajst-11366	85	4	depthwise	depthwise	NOUN
ajst-11366	85	5	separable	separable	ADJ
ajst-11366	85	6	convolution	convolution	NOUN
ajst-11366	85	7	is	be	AUX
ajst-11366	85	8	at	at	ADP
ajst-11366	85	9	the	the	DET
ajst-11366	85	10	core	core	NOUN
ajst-11366	85	11	of	of	ADP
ajst-11366	85	12	mobilenet	mobilenet	NOUN
ajst-11366	85	13	,	,	PUNCT
ajst-11366	85	14	an	an	DET
ajst-11366	85	15	architecture	architecture	NOUN
ajst-11366	85	16	that	that	PRON
ajst-11366	85	17	employs	employ	VERB
ajst-11366	85	18	factorized	factorize	VERB
ajst-11366	85	19	convolution	convolution	NOUN
ajst-11366	85	20	.	.	PUNCT
ajst-11366	86	1	its	its	PRON
ajst-11366	86	2	goal	goal	NOUN
ajst-11366	86	3	is	be	AUX
ajst-11366	86	4	to	to	PART
ajst-11366	86	5	reduce	reduce	VERB
ajst-11366	86	6	model	model	NOUN
ajst-11366	86	7	computation	computation	NOUN
ajst-11366	86	8	and	and	CCONJ
ajst-11366	86	9	parameter	parameter	NOUN
ajst-11366	86	10	count	count	NOUN
ajst-11366	86	11	,	,	PUNCT
ajst-11366	86	12	thereby	thereby	ADV
ajst-11366	86	13	enhancing	enhance	VERB
ajst-11366	86	14	computational	computational	ADJ
ajst-11366	86	15	efficiency	efficiency	NOUN
ajst-11366	86	16	while	while	SCONJ
ajst-11366	86	17	maintaining	maintain	VERB
ajst-11366	86	18	a	a	DET
ajst-11366	86	19	certain	certain	ADJ
ajst-11366	86	20	level	level	NOUN
ajst-11366	86	21	of	of	ADP
ajst-11366	86	22	performance	performance	NOUN
ajst-11366	86	23	.	.	PUNCT
ajst-11366	87	1	it	it	PRON
ajst-11366	87	2	proves	prove	VERB
ajst-11366	87	3	especially	especially	ADV
ajst-11366	87	4	valuable	valuable	ADJ
ajst-11366	87	5	in	in	ADP
ajst-11366	87	6	scenarios	scenario	NOUN
ajst-11366	87	7	with	with	ADP
ajst-11366	87	8	limited	limited	ADJ
ajst-11366	87	9	computing	computing	NOUN
ajst-11366	87	10	resources	resource	NOUN
ajst-11366	87	11	,	,	PUNCT
ajst-11366	87	12	such	such	ADJ
ajst-11366	87	13	as	as	ADP
ajst-11366	87	14	mobile	mobile	ADJ
ajst-11366	87	15	devices	device	NOUN
ajst-11366	87	16	.	.	PUNCT
ajst-11366	88	1	traditional	traditional	ADJ
ajst-11366	88	2	convolutional	convolutional	ADJ
ajst-11366	88	3	layers	layer	NOUN
ajst-11366	88	4	consist	consist	VERB
ajst-11366	88	5	of	of	ADP
ajst-11366	88	6	two	two	NUM
ajst-11366	88	7	main	main	ADJ
ajst-11366	88	8	components	component	NOUN
ajst-11366	88	9	:	:	PUNCT
ajst-11366	88	10	spatial	spatial	ADJ
ajst-11366	88	11	convolution	convolution	NOUN
ajst-11366	88	12	and	and	CCONJ
ajst-11366	88	13	cross	cross	ADJ
ajst-11366	88	14	-	-	ADJ
ajst-11366	88	15	channel	channel	ADJ
ajst-11366	88	16	convolution	convolution	NOUN
ajst-11366	88	17	.	.	PUNCT
ajst-11366	89	1	depthwise	depthwise	NOUN
ajst-11366	89	2	separable	separable	ADJ
ajst-11366	89	3	convolution	convolution	NOUN
ajst-11366	89	4	breaks	break	VERB
ajst-11366	89	5	these	these	DET
ajst-11366	89	6	components	component	NOUN
ajst-11366	89	7	apart	apart	ADV
ajst-11366	89	8	into	into	ADP
ajst-11366	89	9	two	two	NUM
ajst-11366	89	10	steps	step	NOUN
ajst-11366	89	11	:	:	PUNCT
ajst-11366	89	12	depthwise	depthwise	NOUN
ajst-11366	89	13	convolution	convolution	NOUN
ajst-11366	89	14	and	and	CCONJ
ajst-11366	89	15	pointwise	pointwise	NOUN
ajst-11366	89	16	convolution	convolution	NOUN
ajst-11366	89	17	.	.	PUNCT
ajst-11366	90	1	by	by	ADP
ajst-11366	90	2	combining	combine	VERB
ajst-11366	90	3	these	these	DET
ajst-11366	90	4	steps	step	NOUN
ajst-11366	90	5	,	,	PUNCT
ajst-11366	90	6	depthwise	depthwise	NOUN
ajst-11366	90	7	separable	separable	ADJ
ajst-11366	90	8	convolution	convolution	NOUN
ajst-11366	90	9	effectively	effectively	ADV
ajst-11366	90	10	reduces	reduce	VERB
ajst-11366	90	11	computation	computation	NOUN
ajst-11366	90	12	and	and	CCONJ
ajst-11366	90	13	parameter	parameter	NOUN
ajst-11366	90	14	requirements	requirement	NOUN
ajst-11366	90	15	.	.	PUNCT
ajst-11366	91	1	the	the	DET
ajst-11366	91	2	depthwise	depthwise	NOUN
ajst-11366	91	3	convolution	convolution	NOUN
ajst-11366	91	4	learns	learn	VERB
ajst-11366	91	5	spatial	spatial	ADJ
ajst-11366	91	6	features	feature	NOUN
ajst-11366	91	7	,	,	PUNCT
ajst-11366	91	8	while	while	SCONJ
ajst-11366	91	9	the	the	DET
ajst-11366	91	10	pointwise	pointwise	PROPN
ajst-11366	91	11	convolution	convolution	NOUN
ajst-11366	91	12	learns	learn	VERB
ajst-11366	91	13	relationships	relationship	NOUN
ajst-11366	91	14	between	between	ADP
ajst-11366	91	15	channels	channel	NOUN
ajst-11366	91	16	.	.	PUNCT
ajst-11366	92	1	this	this	DET
ajst-11366	92	2	separation	separation	NOUN
ajst-11366	92	3	allows	allow	VERB
ajst-11366	92	4	the	the	DET
ajst-11366	92	5	model	model	NOUN
ajst-11366	92	6	to	to	PART
ajst-11366	92	7	learn	learn	VERB
ajst-11366	92	8	and	and	CCONJ
ajst-11366	92	9	represent	represent	VERB
ajst-11366	92	10	features	feature	NOUN
ajst-11366	92	11	more	more	ADV
ajst-11366	92	12	efficiently	efficiently	ADV
ajst-11366	92	13	.	.	PUNCT
ajst-11366	93	1	this	this	DET
ajst-11366	93	2	structure	structure	NOUN
ajst-11366	93	3	is	be	AUX
ajst-11366	93	4	particularly	particularly	ADV
ajst-11366	93	5	suitable	suitable	ADJ
ajst-11366	93	6	for	for	ADP
ajst-11366	93	7	resource	resource	NOUN
ajst-11366	93	8	-	-	PUNCT
ajst-11366	93	9	constrained	constrain	VERB
ajst-11366	93	10	environments	environment	NOUN
ajst-11366	93	11	like	like	ADP
ajst-11366	93	12	mobile	mobile	ADJ
ajst-11366	93	13	devices	device	NOUN
ajst-11366	93	14	,	,	PUNCT
ajst-11366	93	15	as	as	SCONJ
ajst-11366	93	16	it	it	PRON
ajst-11366	93	17	can	can	AUX
ajst-11366	93	18	maintain	maintain	VERB
ajst-11366	93	19	relatively	relatively	ADV
ajst-11366	93	20	high	high	ADJ
ajst-11366	93	21	performance	performance	NOUN
ajst-11366	93	22	while	while	SCONJ
ajst-11366	93	23	reducing	reduce	VERB
ajst-11366	93	24	computational	computational	ADJ
ajst-11366	93	25	demands	demand	NOUN
ajst-11366	93	26	.	.	PUNCT
ajst-11366	94	1	2.5	2.5	NUM
ajst-11366	94	2	.	.	PUNCT
ajst-11366	94	3	soft	soft	ADJ
ajst-11366	94	4	-	-	PUNCT
ajst-11366	94	5	nms	nms	NOUN
ajst-11366	94	6	nms	nms	NOUN
ajst-11366	94	7	(	(	PUNCT
ajst-11366	94	8	non	non	ADJ
ajst-11366	94	9	-	-	ADJ
ajst-11366	94	10	maximum	maximum	ADJ
ajst-11366	94	11	suppression	suppression	NOUN
ajst-11366	94	12	)	)	PUNCT
ajst-11366	94	13	has	have	AUX
ajst-11366	94	14	consistently	consistently	ADV
ajst-11366	94	15	been	be	AUX
ajst-11366	94	16	a	a	DET
ajst-11366	94	17	component	component	NOUN
ajst-11366	94	18	of	of	ADP
ajst-11366	94	19	many	many	ADJ
ajst-11366	94	20	object	object	NOUN
ajst-11366	94	21	detection	detection	NOUN
ajst-11366	94	22	algorithms	algorithm	NOUN
ajst-11366	94	23	.	.	PUNCT
ajst-11366	95	1	the	the	DET
ajst-11366	95	2	algorithm	algorithm	NOUN
ajst-11366	95	3	selects	select	VERB
ajst-11366	95	4	the	the	DET
ajst-11366	95	5	proposal	proposal	NOUN
ajst-11366	95	6	box	box	NOUN
ajst-11366	95	7	with	with	ADP
ajst-11366	95	8	the	the	DET
ajst-11366	95	9	highest	high	ADJ
ajst-11366	95	10	score	score	NOUN
ajst-11366	95	11	among	among	ADP
ajst-11366	95	12	the	the	DET
ajst-11366	95	13	model	model	NOUN
ajst-11366	95	14	's	's	PART
ajst-11366	95	15	predictions	prediction	NOUN
ajst-11366	95	16	and	and	CCONJ
ajst-11366	95	17	discards	discard	VERB
ajst-11366	95	18	other	other	ADJ
ajst-11366	95	19	boxes	box	NOUN
ajst-11366	95	20	that	that	PRON
ajst-11366	95	21	significantly	significantly	ADV
ajst-11366	95	22	overlap	overlap	VERB
ajst-11366	95	23	with	with	ADP
ajst-11366	95	24	the	the	DET
ajst-11366	95	25	chosen	choose	VERB
ajst-11366	95	26	one	one	NUM
ajst-11366	95	27	,	,	PUNCT
ajst-11366	95	28	and	and	CCONJ
ajst-11366	95	29	this	this	DET
ajst-11366	95	30	process	process	NOUN
ajst-11366	95	31	is	be	AUX
ajst-11366	95	32	executed	execute	VERB
ajst-11366	95	33	recursively	recursively	ADV
ajst-11366	95	34	.	.	PUNCT
ajst-11366	96	1	in	in	ADP
ajst-11366	96	2	the	the	DET
ajst-11366	96	3	context	context	NOUN
ajst-11366	96	4	of	of	ADP
ajst-11366	96	5	bottle	bottle	NOUN
ajst-11366	96	6	cap	cap	NOUN
ajst-11366	96	7	detection	detection	NOUN
ajst-11366	96	8	,	,	PUNCT
ajst-11366	96	9	various	various	ADJ
ajst-11366	96	10	categories	category	NOUN
ajst-11366	96	11	of	of	ADP
ajst-11366	96	12	actual	actual	ADJ
ajst-11366	96	13	boxes	box	NOUN
ajst-11366	96	14	exhibit	exhibit	VERB
ajst-11366	96	15	overlapping	overlap	VERB
ajst-11366	96	16	and	and	CCONJ
ajst-11366	96	17	containing	contain	VERB
ajst-11366	96	18	portions	portion	NOUN
ajst-11366	96	19	.	.	PUNCT
ajst-11366	97	1	however	however	ADV
ajst-11366	97	2	,	,	PUNCT
ajst-11366	97	3	in	in	ADP
ajst-11366	97	4	nms	nms	NOUN
ajst-11366	97	5	algorithms	algorithm	NOUN
ajst-11366	97	6	for	for	ADP
ajst-11366	97	7	detecting	detect	VERB
ajst-11366	97	8	overlapping	overlap	VERB
ajst-11366	97	9	objects	object	NOUN
ajst-11366	97	10	,	,	PUNCT
ajst-11366	97	11	only	only	ADV
ajst-11366	97	12	boxes	box	NOUN
ajst-11366	97	13	with	with	ADP
ajst-11366	97	14	higher	high	ADJ
ajst-11366	97	15	scores	score	NOUN
ajst-11366	97	16	are	be	AUX
ajst-11366	97	17	retained	retain	VERB
ajst-11366	97	18	,	,	PUNCT
ajst-11366	97	19	which	which	PRON
ajst-11366	97	20	can	can	AUX
ajst-11366	97	21	often	often	ADV
ajst-11366	97	22	result	result	VERB
ajst-11366	97	23	in	in	ADP
ajst-11366	97	24	mistakenly	mistakenly	ADV
ajst-11366	97	25	discarding	discard	VERB
ajst-11366	97	26	187	187	NUM
ajst-11366	97	27	target	target	NOUN
ajst-11366	97	28	boxes	box	NOUN
ajst-11366	97	29	.	.	PUNCT
ajst-11366	98	1	to	to	PART
ajst-11366	98	2	prevent	prevent	VERB
ajst-11366	98	3	the	the	DET
ajst-11366	98	4	omission	omission	NOUN
ajst-11366	98	5	of	of	ADP
ajst-11366	98	6	actual	actual	ADJ
ajst-11366	98	7	detected	detect	VERB
ajst-11366	98	8	objects	object	NOUN
ajst-11366	98	9	,	,	PUNCT
ajst-11366	98	10	the	the	DET
ajst-11366	98	11	present	present	ADJ
ajst-11366	98	12	algorithm	algorithm	NOUN
ajst-11366	98	13	employs	employ	VERB
ajst-11366	98	14	soft	soft	ADJ
ajst-11366	98	15	-	-	PUNCT
ajst-11366	98	16	nms	nms	NOUN
ajst-11366	98	17	for	for	ADP
ajst-11366	98	18	suppressing	suppress	VERB
ajst-11366	98	19	predicted	predict	VERB
ajst-11366	98	20	boxes	box	NOUN
ajst-11366	98	21	.	.	PUNCT
ajst-11366	99	1	soft	soft	ADJ
ajst-11366	99	2	-	-	PUNCT
ajst-11366	99	3	nms	nms	NOUN
ajst-11366	99	4	does	do	AUX
ajst-11366	99	5	n't	not	PART
ajst-11366	99	6	directly	directly	ADV
ajst-11366	99	7	discard	discard	VERB
ajst-11366	99	8	boxes	box	NOUN
ajst-11366	99	9	with	with	ADP
ajst-11366	99	10	iou	iou	NOUN
ajst-11366	99	11	above	above	ADP
ajst-11366	99	12	the	the	DET
ajst-11366	99	13	threshold	threshold	NOUN
ajst-11366	99	14	;	;	PUNCT
ajst-11366	99	15	rather	rather	ADV
ajst-11366	99	16	,	,	PUNCT
ajst-11366	99	17	it	it	PRON
ajst-11366	99	18	reduces	reduce	VERB
ajst-11366	99	19	confidence	confidence	NOUN
ajst-11366	99	20	scores	score	NOUN
ajst-11366	99	21	for	for	ADP
ajst-11366	99	22	suppression	suppression	NOUN
ajst-11366	99	23	.	.	PUNCT
ajst-11366	100	1	building	build	VERB
ajst-11366	100	2	upon	upon	SCONJ
ajst-11366	100	3	nms	nms	NOUN
ajst-11366	100	4	,	,	PUNCT
ajst-11366	100	5	the	the	DET
ajst-11366	100	6	algorithm	algorithm	NOUN
ajst-11366	100	7	designates	designate	VERB
ajst-11366	100	8	m	m	PRON
ajst-11366	100	9	as	as	ADP
ajst-11366	100	10	the	the	DET
ajst-11366	100	11	box	box	NOUN
ajst-11366	100	12	with	with	ADP
ajst-11366	100	13	the	the	DET
ajst-11366	100	14	highest	high	ADJ
ajst-11366	100	15	score	score	NOUN
ajst-11366	100	16	and	and	CCONJ
ajst-11366	100	17	bi	bi	NOUN
ajst-11366	100	18	as	as	SCONJ
ajst-11366	100	19	the	the	DET
ajst-11366	100	20	box	box	NOUN
ajst-11366	100	21	to	to	PART
ajst-11366	100	22	be	be	AUX
ajst-11366	100	23	processed	process	VERB
ajst-11366	100	24	.	.	PUNCT
ajst-11366	101	1	after	after	ADP
ajst-11366	101	2	calculating	calculate	VERB
ajst-11366	101	3	their	their	PRON
ajst-11366	101	4	iou	iou	NOUN
ajst-11366	101	5	,	,	PUNCT
ajst-11366	101	6	a	a	DET
ajst-11366	101	7	weight	weight	NOUN
ajst-11366	101	8	function	function	NOUN
ajst-11366	101	9	is	be	AUX
ajst-11366	101	10	applied	apply	VERB
ajst-11366	101	11	.	.	PUNCT
ajst-11366	102	1	boxes	box	NOUN
ajst-11366	102	2	with	with	ADP
ajst-11366	102	3	higher	high	ADJ
ajst-11366	102	4	overlap	overlap	NOUN
ajst-11366	102	5	with	with	ADP
ajst-11366	102	6	m	m	PROPN
ajst-11366	102	7	experience	experience	VERB
ajst-11366	102	8	more	more	ADV
ajst-11366	102	9	significant	significant	ADJ
ajst-11366	102	10	score	score	NOUN
ajst-11366	102	11	attenuation	attenuation	NOUN
ajst-11366	102	12	.	.	PUNCT
ajst-11366	103	1	based	base	VERB
ajst-11366	103	2	on	on	ADP
ajst-11366	103	3	this	this	DET
ajst-11366	103	4	attenuation	attenuation	NOUN
ajst-11366	103	5	,	,	PUNCT
ajst-11366	103	6	scores	score	NOUN
ajst-11366	103	7	are	be	AUX
ajst-11366	103	8	determined	determine	VERB
ajst-11366	103	9	,	,	PUNCT
ajst-11366	103	10	and	and	CCONJ
ajst-11366	103	11	boxes	box	NOUN
ajst-11366	103	12	falling	fall	VERB
ajst-11366	103	13	below	below	ADP
ajst-11366	103	14	the	the	DET
ajst-11366	103	15	threshold	threshold	NOUN
ajst-11366	103	16	are	be	AUX
ajst-11366	103	17	discarded	discard	VERB
ajst-11366	103	18	.	.	PUNCT
ajst-11366	104	1	by	by	ADP
ajst-11366	104	2	scoring	score	VERB
ajst-11366	104	3	based	base	VERB
ajst-11366	104	4	on	on	ADP
ajst-11366	104	5	overlap	overlap	NOUN
ajst-11366	104	6	instead	instead	ADV
ajst-11366	104	7	of	of	ADP
ajst-11366	104	8	a	a	DET
ajst-11366	104	9	uniform	uniform	ADJ
ajst-11366	104	10	zeroing	zeroing	NOUN
ajst-11366	104	11	,	,	PUNCT
ajst-11366	104	12	soft	soft	ADJ
ajst-11366	104	13	-	-	PUNCT
ajst-11366	104	14	nms	nms	NOUN
ajst-11366	104	15	not	not	PART
ajst-11366	104	16	only	only	ADV
ajst-11366	104	17	eliminates	eliminate	VERB
ajst-11366	104	18	surplus	surplus	ADJ
ajst-11366	104	19	boxes	box	NOUN
ajst-11366	104	20	but	but	CCONJ
ajst-11366	104	21	also	also	ADV
ajst-11366	104	22	retains	retain	VERB
ajst-11366	104	23	object	object	NOUN
ajst-11366	104	24	boxes	box	NOUN
ajst-11366	104	25	,	,	PUNCT
ajst-11366	104	26	effectively	effectively	ADV
ajst-11366	104	27	enhancing	enhance	VERB
ajst-11366	104	28	detection	detection	NOUN
ajst-11366	104	29	accuracy	accuracy	NOUN
ajst-11366	104	30	.	.	PUNCT
ajst-11366	105	1	due	due	ADP
ajst-11366	105	2	to	to	ADP
ajst-11366	105	3	the	the	DET
ajst-11366	105	4	possibility	possibility	NOUN
ajst-11366	105	5	of	of	ADP
ajst-11366	105	6	discontinuity	discontinuity	NOUN
ajst-11366	105	7	in	in	ADP
ajst-11366	105	8	linear	linear	ADJ
ajst-11366	105	9	weighting	weighting	NOUN
ajst-11366	105	10	,	,	PUNCT
ajst-11366	105	11	soft	soft	ADJ
ajst-11366	105	12	-	-	PUNCT
ajst-11366	105	13	nms	nms	NOUN
ajst-11366	105	14	can	can	AUX
ajst-11366	105	15	also	also	ADV
ajst-11366	105	16	be	be	AUX
ajst-11366	105	17	modified	modify	VERB
ajst-11366	105	18	to	to	PART
ajst-11366	105	19	use	use	VERB
ajst-11366	105	20	gaussian	gaussian	ADJ
ajst-11366	105	21	weighting	weighting	NOUN
ajst-11366	105	22	.	.	PUNCT
ajst-11366	106	1	the	the	DET
ajst-11366	106	2	specific	specific	ADJ
ajst-11366	106	3	formula	formula	NOUN
ajst-11366	106	4	is	be	AUX
ajst-11366	106	5	as	as	SCONJ
ajst-11366	106	6	follows	follow	VERB
ajst-11366	106	7	:	:	PUNCT
ajst-11366	106	8	,	,	PUNCT
ajst-11366	106	9	n)(),,(1	n)(),,(1	NOUN
ajst-11366	106	10	(	(	PUNCT
ajst-11366	106	11	n	n	CCONJ
ajst-11366	106	12	)	)	PUNCT
ajst-11366	106	13	(	(	PUNCT
ajst-11366	106	14	,	,	PUNCT
ajst-11366	106	15	t	t	PROPN
ajst-11366	106	16	t	t	PROPN
ajst-11366	106	17			PROPN
ajst-11366	106	18			NUM
ajst-11366	106	19			ADP
ajst-11366	106	20			NOUN
ajst-11366	107	1			PROPN
ajst-11366	107	2			PROPN
ajst-11366	107	3	iii	iii	X
ajst-11366	107	4	ii	ii	NOUN
ajst-11366	107	5	i	i	PRON
ajst-11366	107	6	m	m	VERB
ajst-11366	107	7	,	,	PUNCT
ajst-11366	107	8	biou	biou	VERB
ajst-11366	107	9	bmious	bmious	ADJ
ajst-11366	107	10	m	m	NOUN
ajst-11366	107	11	,	,	PUNCT
ajst-11366	107	12	biou	biou	NOUN
ajst-11366	107	13	s	s	PART
ajst-11366	107	14	s	s	X
ajst-11366	107	15	i	i	PROPN
ajst-11366	107	16	bmiou	bmiou	PROPN
ajst-11366	107	17	ii	ii	PROPN
ajst-11366	107	18	bess	bess	PROPN
ajst-11366	107	19	i	i	PRON
ajst-11366	107	20			PUNCT
ajst-11366	107	21			VERB
ajst-11366	107	22	,	,	PUNCT
ajst-11366	107	23	2	2	NUM
ajst-11366	107	24	)	)	PUNCT
ajst-11366	107	25	,	,	PUNCT
ajst-11366	107	26	(	(	PUNCT
ajst-11366	107	27			PROPN
ajst-11366	107	28	3	3	NUM
ajst-11366	107	29	.	.	NOUN
ajst-11366	107	30	analysis	analysis	NOUN
ajst-11366	107	31	and	and	CCONJ
ajst-11366	107	32	discussion	discussion	NOUN
ajst-11366	107	33	3.1	3.1	NUM
ajst-11366	107	34	.	.	PUNCT
ajst-11366	108	1	dataset	dataset	NOUN
ajst-11366	108	2	preprocessing	preprocesse	VERB
ajst-11366	108	3	the	the	DET
ajst-11366	108	4	data	datum	NOUN
ajst-11366	108	5	is	be	AUX
ajst-11366	108	6	sourced	source	VERB
ajst-11366	108	7	from	from	ADP
ajst-11366	108	8	a	a	DET
ajst-11366	108	9	well	well	ADV
ajst-11366	108	10	-	-	PUNCT
ajst-11366	108	11	known	know	VERB
ajst-11366	108	12	tile	tile	NOUN
ajst-11366	108	13	enterprise	enterprise	NOUN
ajst-11366	108	14	in	in	ADP
ajst-11366	108	15	foshan	foshan	PROPN
ajst-11366	108	16	,	,	PUNCT
ajst-11366	108	17	guangdong	guangdong	PROPN
ajst-11366	108	18	province	province	PROPN
ajst-11366	108	19	.	.	PUNCT
ajst-11366	109	1	data	datum	NOUN
ajst-11366	109	2	collection	collection	NOUN
ajst-11366	109	3	was	be	AUX
ajst-11366	109	4	conducted	conduct	VERB
ajst-11366	109	5	by	by	ADP
ajst-11366	109	6	setting	set	VERB
ajst-11366	109	7	up	up	ADP
ajst-11366	109	8	specialized	specialized	ADJ
ajst-11366	109	9	photography	photography	NOUN
ajst-11366	109	10	equipment	equipment	NOUN
ajst-11366	109	11	on	on	ADP
ajst-11366	109	12	the	the	DET
ajst-11366	109	13	production	production	NOUN
ajst-11366	109	14	line	line	NOUN
ajst-11366	109	15	to	to	PART
ajst-11366	109	16	gather	gather	VERB
ajst-11366	109	17	real	real	ADJ
ajst-11366	109	18	-	-	PUNCT
ajst-11366	109	19	time	time	NOUN
ajst-11366	109	20	production	production	NOUN
ajst-11366	109	21	process	process	NOUN
ajst-11366	109	22	data	datum	NOUN
ajst-11366	109	23	.	.	PUNCT
ajst-11366	110	1	it	it	PRON
ajst-11366	110	2	covers	cover	VERB
ajst-11366	110	3	a	a	DET
ajst-11366	110	4	wide	wide	ADJ
ajst-11366	110	5	range	range	NOUN
ajst-11366	110	6	of	of	ADP
ajst-11366	110	7	common	common	ADJ
ajst-11366	110	8	defects	defect	NOUN
ajst-11366	110	9	in	in	ADP
ajst-11366	110	10	the	the	DET
ajst-11366	110	11	tile	tile	NOUN
ajst-11366	110	12	production	production	NOUN
ajst-11366	110	13	line	line	NOUN
ajst-11366	110	14	,	,	PUNCT
ajst-11366	110	15	including	include	VERB
ajst-11366	110	16	powder	powder	NOUN
ajst-11366	110	17	spots	spot	NOUN
ajst-11366	110	18	,	,	PUNCT
ajst-11366	110	19	corner	corner	NOUN
ajst-11366	110	20	cracks	crack	NOUN
ajst-11366	110	21	,	,	PUNCT
ajst-11366	110	22	glaze	glaze	NOUN
ajst-11366	110	23	drips	drip	NOUN
ajst-11366	110	24	,	,	PUNCT
ajst-11366	110	25	ink	ink	NOUN
ajst-11366	110	26	breaks	break	NOUN
ajst-11366	110	27	,	,	PUNCT
ajst-11366	110	28	ink	ink	NOUN
ajst-11366	110	29	drips	drip	NOUN
ajst-11366	110	30	,	,	PUNCT
ajst-11366	110	31	b	b	NOUN
ajst-11366	110	32	holes	hole	NOUN
ajst-11366	110	33	,	,	PUNCT
ajst-11366	110	34	soiling	soiling	NOUN
ajst-11366	110	35	,	,	PUNCT
ajst-11366	110	36	edge	edge	NOUN
ajst-11366	110	37	cracks	crack	NOUN
ajst-11366	110	38	,	,	PUNCT
ajst-11366	110	39	chipping	chipping	NOUN
ajst-11366	110	40	,	,	PUNCT
ajst-11366	110	41	tile	tile	NOUN
ajst-11366	110	42	residue	residue	NOUN
ajst-11366	110	43	,	,	PUNCT
ajst-11366	110	44	white	white	ADJ
ajst-11366	110	45	edges	edge	NOUN
ajst-11366	110	46	,	,	PUNCT
ajst-11366	110	47	etc	etc	X
ajst-11366	110	48	.	.	X
ajst-11366	111	1	the	the	DET
ajst-11366	111	2	dataset	dataset	NOUN
ajst-11366	111	3	has	have	AUX
ajst-11366	111	4	been	be	AUX
ajst-11366	111	5	publicly	publicly	ADV
ajst-11366	111	6	released	release	VERB
ajst-11366	111	7	on	on	ADP
ajst-11366	111	8	the	the	DET
ajst-11366	111	9	tianchi	tianchi	ADJ
ajst-11366	111	10	data	datum	NOUN
ajst-11366	111	11	website	website	NOUN
ajst-11366	111	12	.	.	PUNCT
ajst-11366	112	1	(	(	PUNCT
ajst-11366	112	2	1	1	X
ajst-11366	112	3	)	)	PUNCT
ajst-11366	112	4	data	datum	NOUN
ajst-11366	112	5	details	detail	NOUN
ajst-11366	112	6	and	and	CCONJ
ajst-11366	112	7	labeling	labeling	NOUN
ajst-11366	112	8	process	process	NOUN
ajst-11366	112	9	during	during	ADP
ajst-11366	112	10	the	the	DET
ajst-11366	112	11	data	data	NOUN
ajst-11366	112	12	collection	collection	NOUN
ajst-11366	112	13	process	process	NOUN
ajst-11366	112	14	,	,	PUNCT
ajst-11366	112	15	certain	certain	ADJ
ajst-11366	112	16	defects	defect	NOUN
ajst-11366	112	17	could	could	AUX
ajst-11366	112	18	only	only	ADV
ajst-11366	112	19	be	be	AUX
ajst-11366	112	20	captured	capture	VERB
ajst-11366	112	21	from	from	ADP
ajst-11366	112	22	specific	specific	ADJ
ajst-11366	112	23	angles	angle	NOUN
ajst-11366	112	24	.	.	PUNCT
ajst-11366	113	1	three	three	NUM
ajst-11366	113	2	images	image	NOUN
ajst-11366	113	3	were	be	AUX
ajst-11366	113	4	taken	take	VERB
ajst-11366	113	5	for	for	ADP
ajst-11366	113	6	each	each	DET
ajst-11366	113	7	tile	tile	NOUN
ajst-11366	113	8	,	,	PUNCT
ajst-11366	113	9	including	include	VERB
ajst-11366	113	10	low	low	ADJ
ajst-11366	113	11	-	-	PUNCT
ajst-11366	113	12	angle	angle	NOUN
ajst-11366	113	13	monochromatic	monochromatic	ADJ
ajst-11366	113	14	images	image	NOUN
ajst-11366	113	15	,	,	PUNCT
ajst-11366	113	16	high	high	ADJ
ajst-11366	113	17	-	-	PUNCT
ajst-11366	113	18	angle	angle	NOUN
ajst-11366	113	19	monochromatic	monochromatic	ADJ
ajst-11366	113	20	images	image	NOUN
ajst-11366	113	21	,	,	PUNCT
ajst-11366	113	22	and	and	CCONJ
ajst-11366	113	23	color	color	NOUN
ajst-11366	113	24	images	image	NOUN
ajst-11366	113	25	.	.	PUNCT
ajst-11366	114	1	figure	figure	NOUN
ajst-11366	114	2	5	5	NUM
ajst-11366	114	3	.	.	NOUN
ajst-11366	114	4	example	example	NOUN
ajst-11366	114	5	fig	fig	NOUN
ajst-11366	114	6	the	the	DET
ajst-11366	114	7	data	data	NOUN
ajst-11366	114	8	is	be	AUX
ajst-11366	114	9	annotated	annotate	VERB
ajst-11366	114	10	using	use	VERB
ajst-11366	114	11	the	the	DET
ajst-11366	114	12	voc	voc	NOUN
ajst-11366	114	13	format	format	NOUN
ajst-11366	114	14	for	for	ADP
ajst-11366	114	15	detection	detection	NOUN
ajst-11366	114	16	.	.	PUNCT
ajst-11366	115	1	the	the	DET
ajst-11366	115	2	images	image	NOUN
ajst-11366	115	3	were	be	AUX
ajst-11366	115	4	processed	process	VERB
ajst-11366	115	5	into	into	ADP
ajst-11366	115	6	a	a	DET
ajst-11366	115	7	standard	standard	ADJ
ajst-11366	115	8	voc	voc	NOUN
ajst-11366	115	9	dataset	dataset	NOUN
ajst-11366	115	10	format	format	NOUN
ajst-11366	115	11	using	use	VERB
ajst-11366	115	12	the	the	DET
ajst-11366	115	13	object	object	NOUN
ajst-11366	115	14	detection	detection	NOUN
ajst-11366	115	15	annotation	annotation	NOUN
ajst-11366	115	16	tool	tool	NOUN
ajst-11366	115	17	,	,	PUNCT
ajst-11366	115	18	labelimg	labelimg	NOUN
ajst-11366	115	19	.	.	PUNCT
ajst-11366	116	1	based	base	VERB
ajst-11366	116	2	on	on	ADP
ajst-11366	116	3	the	the	DET
ajst-11366	116	4	annotated	annotate	VERB
ajst-11366	116	5	bounding	bounding	NOUN
ajst-11366	116	6	box	box	NOUN
ajst-11366	116	7	positions	position	NOUN
ajst-11366	116	8	,	,	PUNCT
ajst-11366	116	9	new	new	ADJ
ajst-11366	116	10	xml	xml	NOUN
ajst-11366	116	11	files	file	NOUN
ajst-11366	116	12	were	be	AUX
ajst-11366	116	13	generated	generate	VERB
ajst-11366	116	14	containing	contain	VERB
ajst-11366	116	15	the	the	DET
ajst-11366	116	16	file	file	NOUN
ajst-11366	116	17	name	name	NOUN
ajst-11366	116	18	,	,	PUNCT
ajst-11366	116	19	category	category	NOUN
ajst-11366	116	20	number	number	NOUN
ajst-11366	116	21	,	,	PUNCT
ajst-11366	116	22	image	image	NOUN
ajst-11366	116	23	width	width	NOUN
ajst-11366	116	24	and	and	CCONJ
ajst-11366	116	25	height	height	NOUN
ajst-11366	116	26	,	,	PUNCT
ajst-11366	116	27	as	as	ADV
ajst-11366	116	28	well	well	ADV
ajst-11366	116	29	as	as	ADP
ajst-11366	116	30	the	the	DET
ajst-11366	116	31	bounding	bounding	NOUN
ajst-11366	116	32	box	box	NOUN
ajst-11366	116	33	(	(	PUNCT
ajst-11366	116	34	bbox	bbox	NOUN
ajst-11366	116	35	)	)	PUNCT
ajst-11366	116	36	coordinates	coordinate	VERB
ajst-11366	116	37	information	information	NOUN
ajst-11366	116	38	.	.	PUNCT
ajst-11366	117	1	the	the	DET
ajst-11366	117	2	bbox	bbox	NOUN
ajst-11366	117	3	includes	include	VERB
ajst-11366	117	4	four	four	NUM
ajst-11366	117	5	points	point	NOUN
ajst-11366	117	6	(	(	PUNCT
ajst-11366	117	7	xmin	xmin	NOUN
ajst-11366	117	8	,	,	PUNCT
ajst-11366	117	9	ymin	ymin	NOUN
ajst-11366	117	10	,	,	PUNCT
ajst-11366	117	11	xmax	xmax	PROPN
ajst-11366	117	12	,	,	PUNCT
ajst-11366	117	13	ymax	ymax	NUM
ajst-11366	117	14	)	)	PUNCT
ajst-11366	117	15	that	that	PRON
ajst-11366	117	16	determine	determine	VERB
ajst-11366	117	17	the	the	DET
ajst-11366	117	18	position	position	NOUN
ajst-11366	117	19	of	of	ADP
ajst-11366	117	20	the	the	DET
ajst-11366	117	21	detected	detect	VERB
ajst-11366	117	22	tile	tile	NOUN
ajst-11366	117	23	defects	defect	NOUN
ajst-11366	117	24	.	.	PUNCT
ajst-11366	118	1	the	the	DET
ajst-11366	118	2	annotation	annotation	NOUN
ajst-11366	118	3	process	process	NOUN
ajst-11366	118	4	is	be	AUX
ajst-11366	118	5	illustrated	illustrate	VERB
ajst-11366	118	6	in	in	ADP
ajst-11366	118	7	the	the	DET
ajst-11366	118	8	figure	figure	NOUN
ajst-11366	118	9	.	.	PUNCT
ajst-11366	119	1	(	(	PUNCT
ajst-11366	119	2	a	a	X
ajst-11366	119	3	)	)	PUNCT
ajst-11366	119	4	labelimg	labelimg	NOUN
ajst-11366	119	5	(	(	PUNCT
ajst-11366	119	6	b	b	NOUN
ajst-11366	119	7	)	)	PUNCT
ajst-11366	119	8	xml	xml	NOUN
ajst-11366	119	9	document	document	NOUN
ajst-11366	119	10	figure	figure	NOUN
ajst-11366	119	11	6	6	NUM
ajst-11366	119	12	.	.	PUNCT
ajst-11366	120	1	dataset	dataset	ADJ
ajst-11366	120	2	creation	creation	NOUN
ajst-11366	120	3	(	(	PUNCT
ajst-11366	120	4	2	2	X
ajst-11366	120	5	)	)	PUNCT
ajst-11366	120	6	tile	tile	NOUN
ajst-11366	120	7	defect	defect	NOUN
ajst-11366	120	8	classification	classification	NOUN
ajst-11366	120	9	during	during	ADP
ajst-11366	120	10	the	the	DET
ajst-11366	120	11	production	production	NOUN
ajst-11366	120	12	process	process	NOUN
ajst-11366	120	13	,	,	PUNCT
ajst-11366	120	14	based	base	VERB
ajst-11366	120	15	on	on	ADP
ajst-11366	120	16	the	the	DET
ajst-11366	120	17	characteristics	characteristic	NOUN
ajst-11366	120	18	,	,	PUNCT
ajst-11366	120	19	sizes	size	NOUN
ajst-11366	120	20	,	,	PUNCT
ajst-11366	120	21	and	and	CCONJ
ajst-11366	120	22	positions	position	NOUN
ajst-11366	120	23	of	of	ADP
ajst-11366	120	24	tile	tile	NOUN
ajst-11366	120	25	defects	defect	NOUN
ajst-11366	120	26	,	,	PUNCT
ajst-11366	120	27	the	the	DET
ajst-11366	120	28	defects	defect	NOUN
ajst-11366	120	29	other	other	ADJ
ajst-11366	120	30	than	than	ADP
ajst-11366	120	31	the	the	DET
ajst-11366	120	32	background	background	NOUN
ajst-11366	120	33	were	be	AUX
ajst-11366	120	34	categorized	categorize	VERB
ajst-11366	120	35	into	into	ADP
ajst-11366	120	36	six	six	NUM
ajst-11366	120	37	classes	class	NOUN
ajst-11366	120	38	:	:	PUNCT
ajst-11366	120	39	edge	edge	NOUN
ajst-11366	120	40	anomalies	anomaly	NOUN
ajst-11366	120	41	,	,	PUNCT
ajst-11366	120	42	angular	angular	ADJ
ajst-11366	120	43	anomalies	anomaly	NOUN
ajst-11366	120	44	,	,	PUNCT
ajst-11366	120	45	white	white	ADJ
ajst-11366	120	46	blemish	blemish	NOUN
ajst-11366	120	47	,	,	PUNCT
ajst-11366	120	48	dark	dark	ADJ
ajst-11366	120	49	blemish	blemish	NOUN
ajst-11366	120	50	,	,	PUNCT
ajst-11366	120	51	light	light	ADJ
ajst-11366	120	52	blemish	blemish	ADJ
ajst-11366	120	53	and	and	CCONJ
ajst-11366	120	54	aperture	aperture	ADJ
ajst-11366	120	55	defects	defect	NOUN
ajst-11366	120	56	.	.	PUNCT
ajst-11366	121	1	188	188	NUM
ajst-11366	121	2	(	(	PUNCT
ajst-11366	121	3	a	a	NOUN
ajst-11366	121	4	)	)	PUNCT
ajst-11366	121	5	edge	edge	NOUN
ajst-11366	121	6	anomaly	anomaly	NOUN
ajst-11366	121	7	(	(	PUNCT
ajst-11366	121	8	b	b	NOUN
ajst-11366	121	9	)	)	PUNCT
ajst-11366	121	10	angular	angular	ADJ
ajst-11366	121	11	anomaly	anomaly	NOUN
ajst-11366	121	12	(	(	PUNCT
ajst-11366	121	13	c	c	NOUN
ajst-11366	121	14	)	)	PUNCT
ajst-11366	121	15	white	white	ADJ
ajst-11366	121	16	blemish	blemish	NOUN
ajst-11366	121	17	(	(	PUNCT
ajst-11366	121	18	d	d	NOUN
ajst-11366	121	19	)	)	PUNCT
ajst-11366	121	20	dark	dark	ADJ
ajst-11366	121	21	blemish	blemish	NOUN
ajst-11366	121	22	(	(	PUNCT
ajst-11366	121	23	e	e	NOUN
ajst-11366	121	24	)	)	PUNCT
ajst-11366	121	25	light	light	ADJ
ajst-11366	121	26	blemish	blemish	NOUN
ajst-11366	121	27	(	(	PUNCT
ajst-11366	121	28	f	f	X
ajst-11366	121	29	)	)	PUNCT
ajst-11366	121	30	aperture	aperture	ADJ
ajst-11366	121	31	defects	defect	NOUN
ajst-11366	121	32	figure	figure	VERB
ajst-11366	121	33	7	7	NUM
ajst-11366	121	34	.	.	PUNCT
ajst-11366	121	35	defect	defect	NOUN
ajst-11366	121	36	category	category	NOUN
ajst-11366	121	37	(	(	PUNCT
ajst-11366	121	38	3	3	X
ajst-11366	121	39	)	)	PUNCT
ajst-11366	121	40	dataset	dataset	NOUN
ajst-11366	121	41	partitioning	partition	VERB
ajst-11366	121	42	reasonable	reasonable	ADJ
ajst-11366	121	43	dataset	dataset	NOUN
ajst-11366	121	44	partitioning	partitioning	NOUN
ajst-11366	121	45	can	can	AUX
ajst-11366	121	46	enhance	enhance	VERB
ajst-11366	121	47	training	training	NOUN
ajst-11366	121	48	efficiency	efficiency	NOUN
ajst-11366	121	49	and	and	CCONJ
ajst-11366	121	50	during	during	ADP
ajst-11366	121	51	the	the	DET
ajst-11366	121	52	model	model	NOUN
ajst-11366	121	53	construction	construction	NOUN
ajst-11366	121	54	process	process	NOUN
ajst-11366	121	55	,	,	PUNCT
ajst-11366	121	56	it	it	PRON
ajst-11366	121	57	is	be	AUX
ajst-11366	121	58	important	important	ADJ
ajst-11366	121	59	to	to	PART
ajst-11366	121	60	assess	assess	VERB
ajst-11366	121	61	the	the	DET
ajst-11366	121	62	model	model	NOUN
ajst-11366	121	63	's	's	PART
ajst-11366	121	64	performance	performance	NOUN
ajst-11366	121	65	status	status	NOUN
ajst-11366	121	66	and	and	CCONJ
ajst-11366	121	67	determine	determine	VERB
ajst-11366	121	68	whether	whether	SCONJ
ajst-11366	121	69	it	it	PRON
ajst-11366	121	70	is	be	AUX
ajst-11366	121	71	overfitting	overfitte	VERB
ajst-11366	121	72	or	or	CCONJ
ajst-11366	121	73	underfitting	underfitting	NOUN
ajst-11366	121	74	.	.	PUNCT
ajst-11366	122	1	therefore	therefore	ADV
ajst-11366	122	2	,	,	PUNCT
ajst-11366	122	3	in	in	ADP
ajst-11366	122	4	this	this	DET
ajst-11366	122	5	experiment	experiment	NOUN
ajst-11366	122	6	,	,	PUNCT
ajst-11366	122	7	the	the	DET
ajst-11366	122	8	dataset	dataset	NOUN
ajst-11366	122	9	was	be	AUX
ajst-11366	122	10	partitioned	partition	VERB
ajst-11366	122	11	into	into	ADP
ajst-11366	122	12	training	training	NOUN
ajst-11366	122	13	,	,	PUNCT
ajst-11366	122	14	validation	validation	NOUN
ajst-11366	122	15	,	,	PUNCT
ajst-11366	122	16	and	and	CCONJ
ajst-11366	122	17	test	test	NOUN
ajst-11366	122	18	sets	set	NOUN
ajst-11366	122	19	in	in	ADP
ajst-11366	122	20	an	an	DET
ajst-11366	122	21	8:1:1	8:1:1	NUM
ajst-11366	122	22	ratio	ratio	NOUN
ajst-11366	122	23	.	.	PUNCT
ajst-11366	123	1	the	the	DET
ajst-11366	123	2	training	training	NOUN
ajst-11366	123	3	set	set	NOUN
ajst-11366	123	4	consists	consist	VERB
ajst-11366	123	5	of	of	ADP
ajst-11366	123	6	12,003	12,003	NUM
ajst-11366	123	7	images	image	NOUN
ajst-11366	123	8	,	,	PUNCT
ajst-11366	123	9	the	the	DET
ajst-11366	123	10	validation	validation	NOUN
ajst-11366	123	11	set	set	NOUN
ajst-11366	123	12	includes	include	VERB
ajst-11366	123	13	1,345	1,345	NUM
ajst-11366	123	14	images	image	NOUN
ajst-11366	123	15	,	,	PUNCT
ajst-11366	123	16	and	and	CCONJ
ajst-11366	123	17	the	the	DET
ajst-11366	123	18	test	test	NOUN
ajst-11366	123	19	set	set	NOUN
ajst-11366	123	20	contains	contain	VERB
ajst-11366	123	21	1,627	1,627	NUM
ajst-11366	123	22	images	image	NOUN
ajst-11366	123	23	.	.	PUNCT
ajst-11366	124	1	the	the	DET
ajst-11366	124	2	specific	specific	ADJ
ajst-11366	124	3	partitioning	partitioning	NOUN
ajst-11366	124	4	is	be	AUX
ajst-11366	124	5	detailed	detail	VERB
ajst-11366	124	6	in	in	ADP
ajst-11366	124	7	the	the	DET
ajst-11366	124	8	table	table	NOUN
ajst-11366	124	9	：	：	PUNCT
ajst-11366	124	10	table	table	NOUN
ajst-11366	124	11	1	1	NUM
ajst-11366	124	12	.	.	PUNCT
ajst-11366	125	1	dataset	dataset	ADJ
ajst-11366	125	2	partitioning	partitioning	NOUN
ajst-11366	125	3	table	table	NOUN
ajst-11366	125	4	category	category	NOUN
ajst-11366	125	5	background	background	NOUN
ajst-11366	125	6	edge	edge	NOUN
ajst-11366	125	7	anomaly	anomaly	VERB
ajst-11366	125	8	angular	angular	PROPN
ajst-11366	125	9	anomaly	anomaly	PROPN
ajst-11366	125	10	white	white	PROPN
ajst-11366	125	11	blemish	blemish	ADJ
ajst-11366	125	12	light	light	NOUN
ajst-11366	125	13	blemish	blemish	ADJ
ajst-11366	125	14	dark	dark	ADJ
ajst-11366	125	15	blemish	blemish	ADJ
ajst-11366	125	16	aperture	aperture	NOUN
ajst-11366	125	17	defects	defect	VERB
ajst-11366	125	18	num	num	ADJ
ajst-11366	125	19	0	0	NUM
ajst-11366	125	20	1	1	NUM
ajst-11366	125	21	2	2	NUM
ajst-11366	125	22	3	3	NUM
ajst-11366	125	23	4	4	NUM
ajst-11366	125	24	5	5	NUM
ajst-11366	125	25	6	6	NUM
ajst-11366	125	26	training	training	NOUN
ajst-11366	125	27	1290	1290	NUM
ajst-11366	125	28	1715	1715	NUM
ajst-11366	125	29	1428	1428	NUM
ajst-11366	125	30	1911	1911	NUM
ajst-11366	125	31	2301	2301	NUM
ajst-11366	125	32	1875	1875	NUM
ajst-11366	125	33	1928	1928	NUM
ajst-11366	125	34	validation	validation	NOUN
ajst-11366	125	35	175	175	NUM
ajst-11366	125	36	215	215	NUM
ajst-11366	125	37	201	201	NUM
ajst-11366	125	38	195	195	NUM
ajst-11366	125	39	242	242	NUM
ajst-11366	125	40	151	151	NUM
ajst-11366	125	41	174	174	NUM
ajst-11366	125	42	test	test	NOUN
ajst-11366	125	43	121	121	NUM
ajst-11366	125	44	231	231	NUM
ajst-11366	125	45	221	221	NUM
ajst-11366	125	46	259	259	NUM
ajst-11366	125	47	287	287	NUM
ajst-11366	125	48	212	212	NUM
ajst-11366	125	49	198	198	NUM
ajst-11366	125	50	3.2	3.2	NUM
ajst-11366	125	51	.	.	PUNCT
ajst-11366	126	1	experimental	experimental	ADJ
ajst-11366	126	2	evaluation	evaluation	NOUN
ajst-11366	126	3	metrics	metric	NOUN
ajst-11366	126	4	iou	iou	NOUN
ajst-11366	126	5	refers	refer	VERB
ajst-11366	126	6	to	to	ADP
ajst-11366	126	7	the	the	DET
ajst-11366	126	8	intersection	intersection	NOUN
ajst-11366	126	9	over	over	ADP
ajst-11366	126	10	union	union	NOUN
ajst-11366	126	11	,	,	PUNCT
ajst-11366	126	12	which	which	PRON
ajst-11366	126	13	is	be	AUX
ajst-11366	126	14	the	the	DET
ajst-11366	126	15	result	result	NOUN
ajst-11366	126	16	of	of	ADP
ajst-11366	126	17	the	the	DET
ajst-11366	126	18	intersection	intersection	NOUN
ajst-11366	126	19	of	of	ADP
ajst-11366	126	20	predicted	predict	VERB
ajst-11366	126	21	box	box	PROPN
ajst-11366	126	22	a	a	DET
ajst-11366	126	23	divided	divide	VERB
ajst-11366	126	24	by	by	ADP
ajst-11366	126	25	the	the	DET
ajst-11366	126	26	union	union	NOUN
ajst-11366	126	27	of	of	ADP
ajst-11366	126	28	true	true	PROPN
ajst-11366	126	29	box	box	PROPN
ajst-11366	126	30	b.	b.	PROPN
ajst-11366	126	31	it	it	PRON
ajst-11366	126	32	measures	measure	VERB
ajst-11366	126	33	the	the	DET
ajst-11366	126	34	overlap	overlap	NOUN
ajst-11366	126	35	between	between	ADP
ajst-11366	126	36	algorithm	algorithm	NOUN
ajst-11366	126	37	-	-	PUNCT
ajst-11366	126	38	predicted	predict	VERB
ajst-11366	126	39	boxes	box	NOUN
ajst-11366	126	40	and	and	CCONJ
ajst-11366	126	41	true	true	ADJ
ajst-11366	126	42	boxes	box	NOUN
ajst-11366	126	43	,	,	PUNCT
ajst-11366	126	44	serving	serve	VERB
ajst-11366	126	45	as	as	ADP
ajst-11366	126	46	a	a	DET
ajst-11366	126	47	measure	measure	NOUN
ajst-11366	126	48	of	of	ADP
ajst-11366	126	49	the	the	DET
ajst-11366	126	50	model	model	NOUN
ajst-11366	126	51	's	's	PART
ajst-11366	126	52	performance	performance	NOUN
ajst-11366	126	53	.	.	PUNCT
ajst-11366	127	1	the	the	DET
ajst-11366	127	2	experiment	experiment	NOUN
ajst-11366	127	3	primarily	primarily	ADV
ajst-11366	127	4	employs	employ	VERB
ajst-11366	127	5	iou	iou	ADJ
ajst-11366	127	6	intersection	intersection	NOUN
ajst-11366	127	7	-	-	PUNCT
ajst-11366	127	8	over	over	ADP
ajst-11366	127	9	-	-	PUNCT
ajst-11366	127	10	union	union	NOUN
ajst-11366	127	11	ratios	ratio	NOUN
ajst-11366	127	12	to	to	PART
ajst-11366	127	13	compute	compute	VERB
ajst-11366	127	14	the	the	DET
ajst-11366	127	15	average	average	ADJ
ajst-11366	127	16	precision	precision	NOUN
ajst-11366	127	17	(	(	PUNCT
ajst-11366	127	18	ap	ap	PROPN
ajst-11366	127	19	)	)	PUNCT
ajst-11366	127	20	and	and	CCONJ
ajst-11366	127	21	mean	mean	VERB
ajst-11366	127	22	average	average	ADJ
ajst-11366	127	23	precision	precision	NOUN
ajst-11366	127	24	(	(	PUNCT
ajst-11366	127	25	map	map	NOUN
ajst-11366	127	26	)	)	PUNCT
ajst-11366	127	27	as	as	ADV
ajst-11366	127	28	well	well	ADV
ajst-11366	127	29	as	as	ADP
ajst-11366	127	30	recall	recall	NOUN
ajst-11366	127	31	rate	rate	NOUN
ajst-11366	127	32	as	as	ADP
ajst-11366	127	33	evaluation	evaluation	NOUN
ajst-11366	127	34	metrics	metric	NOUN
ajst-11366	127	35	.	.	PUNCT
ajst-11366	128	1	the	the	DET
ajst-11366	128	2	calculation	calculation	NOUN
ajst-11366	128	3	formulas	formula	NOUN
ajst-11366	128	4	are	be	AUX
ajst-11366	128	5	as	as	SCONJ
ajst-11366	128	6	follows	follow	VERB
ajst-11366	128	7	,	,	PUNCT
ajst-11366	128	8	where	where	SCONJ
ajst-11366	128	9	tp	tp	PART
ajst-11366	128	10	(	(	PUNCT
ajst-11366	128	11	true	true	ADJ
ajst-11366	128	12	positive	positive	ADJ
ajst-11366	128	13	)	)	PUNCT
ajst-11366	128	14	represents	represent	VERB
ajst-11366	128	15	true	true	ADJ
ajst-11366	128	16	positive	positive	ADJ
ajst-11366	128	17	predictions	prediction	NOUN
ajst-11366	128	18	,	,	PUNCT
ajst-11366	128	19	tn	tn	PROPN
ajst-11366	128	20	(	(	PUNCT
ajst-11366	128	21	true	true	ADJ
ajst-11366	128	22	negative	negative	ADJ
ajst-11366	128	23	)	)	PUNCT
ajst-11366	128	24	signifies	signify	VERB
ajst-11366	128	25	true	true	ADJ
ajst-11366	128	26	negative	negative	ADJ
ajst-11366	128	27	predictions	prediction	NOUN
ajst-11366	128	28	,	,	PUNCT
ajst-11366	128	29	fp	fp	X
ajst-11366	128	30	(	(	PUNCT
ajst-11366	128	31	false	false	ADJ
ajst-11366	128	32	positive	positive	ADJ
ajst-11366	128	33	)	)	PUNCT
ajst-11366	128	34	indicates	indicate	VERB
ajst-11366	128	35	false	false	ADJ
ajst-11366	128	36	positive	positive	ADJ
ajst-11366	128	37	predictions	prediction	NOUN
ajst-11366	128	38	,	,	PUNCT
ajst-11366	128	39	fn	fn	INTJ
ajst-11366	128	40	(	(	PUNCT
ajst-11366	128	41	false	false	ADJ
ajst-11366	128	42	negative	negative	ADJ
ajst-11366	128	43	)	)	PUNCT
ajst-11366	128	44	denotes	denote	VERB
ajst-11366	128	45	false	false	ADJ
ajst-11366	128	46	negative	negative	ADJ
ajst-11366	128	47	predictions	prediction	NOUN
ajst-11366	128	48	,	,	PUNCT
ajst-11366	128	49	and	and	CCONJ
ajst-11366	128	50	n	n	CCONJ
ajst-11366	128	51	represents	represent	VERB
ajst-11366	128	52	the	the	DET
ajst-11366	128	53	number	number	NOUN
ajst-11366	128	54	of	of	ADP
ajst-11366	128	55	detected	detect	VERB
ajst-11366	128	56	sample	sample	NOUN
ajst-11366	128	57	categories	category	NOUN
ajst-11366	128	58	,	,	PUNCT
ajst-11366	128	59	with	with	ADP
ajst-11366	128	60	6	6	NUM
ajst-11366	128	61	categories	category	NOUN
ajst-11366	128	62	in	in	ADP
ajst-11366	128	63	this	this	DET
ajst-11366	128	64	study	study	NOUN
ajst-11366	128	65	.	.	PUNCT
ajst-11366	129	1	ba	ba	PROPN
ajst-11366	129	2	ba	ba	PROPN
ajst-11366	129	3	iou	iou	PROPN
ajst-11366	129	4	∪	∪	ADJ
ajst-11366	129	5	∩	∩	PROPN
ajst-11366	129	6			PROPN
ajst-11366	129	7	fptp	fptp	PROPN
ajst-11366	129	8	tp	tp	PROPN
ajst-11366	129	9	ecision	ecision	PROPN
ajst-11366	129	10			VERB
ajst-11366	129	11	pr	pr	ADJ
ajst-11366	129	12	fntp	fntp	NOUN
ajst-11366	129	13	tp	tp	PART
ajst-11366	129	14	recall	recall	VERB
ajst-11366	129	15			PROPN
ajst-11366	129	16			PROPN
ajst-11366	129	17			NOUN
ajst-11366	129	18	)	)	PUNCT
ajst-11366	129	19	(	(	PUNCT
ajst-11366	129	20	)	)	PUNCT
ajst-11366	129	21	(	(	PUNCT
ajst-11366	129	22	ap	ap	PROPN
ajst-11366	129	23	recalldrecallprecision	recalldrecallprecision	PROPN
ajst-11366	129	24	n	n	PROPN
ajst-11366	129	25	ap	ap	PROPN
ajst-11366	129	26	map	map	VERB
ajst-11366	129	27			ADV
ajst-11366	129	28	3.3	3.3	NUM
ajst-11366	129	29	.	.	PUNCT
ajst-11366	130	1	the	the	DET
ajst-11366	130	2	experimental	experimental	ADJ
ajst-11366	130	3	process	process	NOUN
ajst-11366	130	4	of	of	ADP
ajst-11366	130	5	the	the	DET
ajst-11366	130	6	improved	improved	ADJ
ajst-11366	130	7	network	network	NOUN
ajst-11366	130	8	for	for	ADP
ajst-11366	130	9	tile	tile	NOUN
ajst-11366	130	10	defect	defect	NOUN
ajst-11366	130	11	detection	detection	NOUN
ajst-11366	130	12	in	in	ADP
ajst-11366	130	13	this	this	DET
ajst-11366	130	14	experiment	experiment	NOUN
ajst-11366	130	15	,	,	PUNCT
ajst-11366	130	16	the	the	DET
ajst-11366	130	17	faster	fast	ADJ
ajst-11366	130	18	r	r	NOUN
ajst-11366	130	19	-	-	PUNCT
ajst-11366	130	20	cnn	cnn	PROPN
ajst-11366	130	21	model	model	NOUN
ajst-11366	130	22	was	be	AUX
ajst-11366	130	23	utilized	utilize	VERB
ajst-11366	130	24	with	with	ADP
ajst-11366	130	25	transferred	transfer	VERB
ajst-11366	130	26	learning	learning	NOUN
ajst-11366	130	27	from	from	ADP
ajst-11366	130	28	pre	pre	ADJ
ajst-11366	130	29	-	-	ADJ
ajst-11366	130	30	trained	train	VERB
ajst-11366	130	31	weights	weight	NOUN
ajst-11366	130	32	on	on	ADP
ajst-11366	130	33	the	the	DET
ajst-11366	130	34	pascal	pascal	PROPN
ajst-11366	130	35	voc	voc	NOUN
ajst-11366	130	36	dataset	dataset	PROPN
ajst-11366	130	37	.	.	PUNCT
ajst-11366	131	1	during	during	ADP
ajst-11366	131	2	training	training	NOUN
ajst-11366	131	3	,	,	PUNCT
ajst-11366	131	4	the	the	DET
ajst-11366	131	5	dataset	dataset	NOUN
ajst-11366	131	6	was	be	AUX
ajst-11366	131	7	augmented	augment	VERB
ajst-11366	131	8	with	with	ADP
ajst-11366	131	9	random	random	ADJ
ajst-11366	131	10	flips	flip	NOUN
ajst-11366	131	11	,	,	PUNCT
ajst-11366	131	12	enhanced	enhanced	ADJ
ajst-11366	131	13	brightness	brightness	NOUN
ajst-11366	131	14	,	,	PUNCT
ajst-11366	131	15	and	and	CCONJ
ajst-11366	131	16	other	other	ADJ
ajst-11366	131	17	data	data	NOUN
ajst-11366	131	18	augmentation	augmentation	NOUN
ajst-11366	131	19	strategies	strategy	NOUN
ajst-11366	131	20	.	.	PUNCT
ajst-11366	132	1	the	the	DET
ajst-11366	132	2	input	input	NOUN
ajst-11366	132	3	images	image	NOUN
ajst-11366	132	4	underwent	underwent	ADJ
ajst-11366	132	5	multi	multi	ADJ
ajst-11366	132	6	-	-	ADJ
ajst-11366	132	7	scale	scale	ADJ
ajst-11366	132	8	training	training	NOUN
ajst-11366	132	9	(	(	PUNCT
ajst-11366	132	10	mst	mst	PROPN
ajst-11366	132	11	)	)	PUNCT
ajst-11366	132	12	,	,	PUNCT
ajst-11366	132	13	which	which	PRON
ajst-11366	132	14	involves	involve	VERB
ajst-11366	132	15	training	train	VERB
ajst-11366	132	16	the	the	DET
ajst-11366	132	17	model	model	NOUN
ajst-11366	132	18	with	with	ADP
ajst-11366	132	19	various	various	ADJ
ajst-11366	132	20	input	input	NOUN
ajst-11366	132	21	sizes	size	NOUN
ajst-11366	132	22	to	to	PART
ajst-11366	132	23	effectively	effectively	ADV
ajst-11366	132	24	improve	improve	VERB
ajst-11366	132	25	multiscale	multiscale	ADJ
ajst-11366	132	26	object	object	NOUN
ajst-11366	132	27	detection	detection	NOUN
ajst-11366	132	28	and	and	CCONJ
ajst-11366	132	29	enhance	enhance	VERB
ajst-11366	132	30	the	the	DET
ajst-11366	132	31	network	network	NOUN
ajst-11366	132	32	's	's	PART
ajst-11366	132	33	robustness	robustness	NOUN
ajst-11366	132	34	.	.	PUNCT
ajst-11366	133	1	the	the	DET
ajst-11366	133	2	input	input	NOUN
ajst-11366	133	3	scales	scale	NOUN
ajst-11366	133	4	were	be	AUX
ajst-11366	133	5	set	set	VERB
ajst-11366	133	6	to	to	ADP
ajst-11366	133	7	(	(	PUNCT
ajst-11366	133	8	640	640	NUM
ajst-11366	133	9	,	,	PUNCT
ajst-11366	133	10	640	640	NUM
ajst-11366	133	11	)	)	PUNCT
ajst-11366	133	12	and	and	CCONJ
ajst-11366	133	13	(	(	PUNCT
ajst-11366	133	14	1280	1280	NUM
ajst-11366	133	15	,	,	PUNCT
ajst-11366	133	16	1280	1280	NUM
ajst-11366	133	17	)	)	PUNCT
ajst-11366	133	18	.	.	PUNCT
ajst-11366	134	1	the	the	DET
ajst-11366	134	2	batch	batch	NOUN
ajst-11366	134	3	size	size	NOUN
ajst-11366	134	4	was	be	AUX
ajst-11366	134	5	set	set	VERB
ajst-11366	134	6	to	to	ADP
ajst-11366	134	7	8	8	NUM
ajst-11366	134	8	,	,	PUNCT
ajst-11366	134	9	influenced	influence	VERB
ajst-11366	134	10	by	by	ADP
ajst-11366	134	11	the	the	DET
ajst-11366	134	12	image	image	NOUN
ajst-11366	134	13	size	size	NOUN
ajst-11366	134	14	.	.	PUNCT
ajst-11366	135	1	an	an	DET
ajst-11366	135	2	initial	initial	ADJ
ajst-11366	135	3	learning	learning	NOUN
ajst-11366	135	4	rate	rate	NOUN
ajst-11366	135	5	of	of	ADP
ajst-11366	135	6	0.0001	0.0001	NUM
ajst-11366	135	7	was	be	AUX
ajst-11366	135	8	employed	employ	VERB
ajst-11366	135	9	,	,	PUNCT
ajst-11366	135	10	and	and	CCONJ
ajst-11366	135	11	a	a	DET
ajst-11366	135	12	warmup	warmup	NOUN
ajst-11366	135	13	optimization	optimization	NOUN
ajst-11366	135	14	algorithm	algorithm	NOUN
ajst-11366	135	15	,	,	PUNCT
ajst-11366	135	16	also	also	ADV
ajst-11366	135	17	known	know	VERB
ajst-11366	135	18	as	as	ADP
ajst-11366	135	19	a	a	DET
ajst-11366	135	20	learning	learning	NOUN
ajst-11366	135	21	rate	rate	NOUN
ajst-11366	135	22	warmup	warmup	NOUN
ajst-11366	135	23	method	method	NOUN
ajst-11366	135	24	,	,	PUNCT
ajst-11366	135	25	was	be	AUX
ajst-11366	135	26	used	use	VERB
ajst-11366	135	27	for	for	ADP
ajst-11366	135	28	adjusting	adjust	VERB
ajst-11366	135	29	the	the	DET
ajst-11366	135	30	learning	learning	NOUN
ajst-11366	135	31	rate	rate	NOUN
ajst-11366	135	32	.	.	PUNCT
ajst-11366	136	1	warmup	warmup	NOUN
ajst-11366	136	2	189	189	NUM
ajst-11366	136	3	involves	involve	VERB
ajst-11366	136	4	starting	start	VERB
ajst-11366	136	5	the	the	DET
ajst-11366	136	6	training	training	NOUN
ajst-11366	136	7	process	process	NOUN
ajst-11366	136	8	with	with	ADP
ajst-11366	136	9	a	a	DET
ajst-11366	136	10	smaller	small	ADJ
ajst-11366	136	11	learning	learning	NOUN
ajst-11366	136	12	rate	rate	NOUN
ajst-11366	136	13	,	,	PUNCT
ajst-11366	136	14	gradually	gradually	ADV
ajst-11366	136	15	increasing	increase	VERB
ajst-11366	136	16	it	it	PRON
ajst-11366	136	17	to	to	ADP
ajst-11366	136	18	a	a	DET
ajst-11366	136	19	predefined	predefine	VERB
ajst-11366	136	20	value	value	NOUN
ajst-11366	136	21	after	after	ADP
ajst-11366	136	22	training	training	NOUN
ajst-11366	136	23	for	for	ADP
ajst-11366	136	24	a	a	DET
ajst-11366	136	25	certain	certain	ADJ
ajst-11366	136	26	number	number	NOUN
ajst-11366	136	27	of	of	ADP
ajst-11366	136	28	epochs	epoch	NOUN
ajst-11366	136	29	.	.	PUNCT
ajst-11366	137	1	3.4	3.4	NUM
ajst-11366	137	2	.	.	PUNCT
ajst-11366	137	3	comparison	comparison	NOUN
ajst-11366	137	4	of	of	ADP
ajst-11366	137	5	results	result	NOUN
ajst-11366	137	6	before	before	ADP
ajst-11366	137	7	and	and	CCONJ
ajst-11366	137	8	after	after	ADP
ajst-11366	137	9	network	network	NOUN
ajst-11366	137	10	improvement	improvement	NOUN
ajst-11366	137	11	in	in	ADP
ajst-11366	137	12	order	order	NOUN
ajst-11366	137	13	to	to	PART
ajst-11366	137	14	verify	verify	VERB
ajst-11366	137	15	the	the	DET
ajst-11366	137	16	effectiveness	effectiveness	NOUN
ajst-11366	137	17	of	of	ADP
ajst-11366	137	18	the	the	DET
ajst-11366	137	19	improved	improve	VERB
ajst-11366	137	20	retinanet	retinanet	NOUN
ajst-11366	137	21	network	network	NOUN
ajst-11366	137	22	for	for	ADP
ajst-11366	137	23	bottle	bottle	NOUN
ajst-11366	137	24	cap	cap	NOUN
ajst-11366	137	25	defect	defect	NOUN
ajst-11366	137	26	detection	detection	NOUN
ajst-11366	137	27	,	,	PUNCT
ajst-11366	137	28	this	this	DET
ajst-11366	137	29	experiment	experiment	NOUN
ajst-11366	137	30	trained	train	VERB
ajst-11366	137	31	the	the	DET
ajst-11366	137	32	original	original	ADJ
ajst-11366	137	33	network	network	NOUN
ajst-11366	137	34	,	,	PUNCT
ajst-11366	137	35	the	the	DET
ajst-11366	137	36	network	network	NOUN
ajst-11366	137	37	with	with	ADP
ajst-11366	137	38	swin	swin	NOUN
ajst-11366	137	39	-	-	PUNCT
ajst-11366	137	40	transformer	transformer	NOUN
ajst-11366	137	41	as	as	ADP
ajst-11366	137	42	the	the	DET
ajst-11366	137	43	backbone	backbone	NOUN
ajst-11366	137	44	,	,	PUNCT
ajst-11366	137	45	the	the	DET
ajst-11366	137	46	network	network	NOUN
ajst-11366	137	47	with	with	ADP
ajst-11366	137	48	the	the	DET
ajst-11366	137	49	neural	neural	ADJ
ajst-11366	137	50	architecture	architecture	NOUN
ajst-11366	137	51	search	search	NOUN
ajst-11366	137	52	fpn	fpn	VERB
ajst-11366	137	53	as	as	ADP
ajst-11366	137	54	the	the	DET
ajst-11366	137	55	neck	neck	NOUN
ajst-11366	137	56	,	,	PUNCT
ajst-11366	137	57	and	and	CCONJ
ajst-11366	137	58	the	the	DET
ajst-11366	137	59	network	network	NOUN
ajst-11366	137	60	with	with	ADP
ajst-11366	137	61	soft	soft	ADJ
ajst-11366	137	62	-	-	PUNCT
ajst-11366	137	63	nms	nms	NOUN
ajst-11366	137	64	for	for	ADP
ajst-11366	137	65	suppressing	suppress	VERB
ajst-11366	137	66	predicted	predict	VERB
ajst-11366	137	67	boxes	box	NOUN
ajst-11366	137	68	.	.	PUNCT
ajst-11366	138	1	these	these	DET
ajst-11366	138	2	networks	network	NOUN
ajst-11366	138	3	were	be	AUX
ajst-11366	138	4	tested	test	VERB
ajst-11366	138	5	on	on	ADP
ajst-11366	138	6	the	the	DET
ajst-11366	138	7	test	test	NOUN
ajst-11366	138	8	set	set	NOUN
ajst-11366	138	9	,	,	PUNCT
ajst-11366	138	10	and	and	CCONJ
ajst-11366	138	11	their	their	PRON
ajst-11366	138	12	performance	performance	NOUN
ajst-11366	138	13	was	be	AUX
ajst-11366	138	14	compared	compare	VERB
ajst-11366	138	15	.	.	PUNCT
ajst-11366	139	1	the	the	DET
ajst-11366	139	2	results	result	NOUN
ajst-11366	139	3	are	be	AUX
ajst-11366	139	4	shown	show	VERB
ajst-11366	139	5	in	in	ADP
ajst-11366	139	6	the	the	DET
ajst-11366	139	7	table	table	NOUN
ajst-11366	139	8	:	:	PUNCT
ajst-11366	139	9	table	table	NOUN
ajst-11366	139	10	2	2	NUM
ajst-11366	139	11	.	.	PUNCT
ajst-11366	139	12	detection	detection	NOUN
ajst-11366	139	13	effect	effect	NOUN
ajst-11366	139	14	table	table	NOUN
ajst-11366	139	15	resnet	resnet	PROPN
ajst-11366	139	16	bifpn	bifpn	PROPN
ajst-11366	139	17	depthwise	depthwise	VERB
ajst-11366	139	18	soft	soft	ADJ
ajst-11366	139	19	-	-	PUNCT
ajst-11366	139	20	nms	nms	NOUN
ajst-11366	139	21	map/%	map/%	PROPN
ajst-11366	139	22	memory	memory	NOUN
ajst-11366	139	23	1	1	NUM
ajst-11366	139	24	57.2	57.2	NUM
ajst-11366	139	25	3598	3598	NUM
ajst-11366	139	26	2	2	NUM
ajst-11366	139	27	√	√	ADP
ajst-11366	139	28	62.3	62.3	NUM
ajst-11366	139	29	3984	3984	NUM
ajst-11366	139	30	3	3	NUM
ajst-11366	139	31	√	√	ADP
ajst-11366	139	32	62.7	62.7	NUM
ajst-11366	139	33	3894	3894	NUM
ajst-11366	139	34	4	4	NUM
ajst-11366	139	35	√	√	ADP
ajst-11366	139	36	60.7	60.7	NUM
ajst-11366	139	37	3137	3137	NUM
ajst-11366	139	38	5	5	NUM
ajst-11366	139	39	√	√	PROPN
ajst-11366	139	40	59.8	59.8	NUM
ajst-11366	139	41	3598	3598	NUM
ajst-11366	139	42	6	6	NUM
ajst-11366	139	43	√	√	NUM
ajst-11366	139	44	√	√	PROPN
ajst-11366	139	45	√	√	PROPN
ajst-11366	139	46	√	√	NUM
ajst-11366	139	47	70.4	70.4	NUM
ajst-11366	139	48	3827	3827	NUM
ajst-11366	139	49	by	by	ADP
ajst-11366	139	50	employing	employ	VERB
ajst-11366	139	51	resnet	resnet	NOUN
ajst-11366	139	52	as	as	ADP
ajst-11366	139	53	the	the	DET
ajst-11366	139	54	backbone	backbone	NOUN
ajst-11366	139	55	in	in	ADP
ajst-11366	139	56	faster	fast	ADJ
ajst-11366	139	57	r	r	NOUN
ajst-11366	139	58	-	-	PUNCT
ajst-11366	139	59	cnn	cnn	PROPN
ajst-11366	139	60	,	,	PUNCT
ajst-11366	139	61	the	the	DET
ajst-11366	139	62	map	map	NOUN
ajst-11366	139	63	improved	improve	VERB
ajst-11366	139	64	by	by	ADP
ajst-11366	139	65	5.1	5.1	NUM
ajst-11366	139	66	%	%	NOUN
ajst-11366	139	67	.	.	PUNCT
ajst-11366	140	1	introducing	introduce	VERB
ajst-11366	140	2	bifpn	bifpn	PROPN
ajst-11366	140	3	resulted	result	VERB
ajst-11366	140	4	in	in	ADP
ajst-11366	140	5	a	a	DET
ajst-11366	140	6	5.5	5.5	NUM
ajst-11366	140	7	%	%	NOUN
ajst-11366	140	8	map	map	NOUN
ajst-11366	140	9	enhancement	enhancement	NOUN
ajst-11366	140	10	.	.	PUNCT
ajst-11366	141	1	finally	finally	ADV
ajst-11366	141	2	,	,	PUNCT
ajst-11366	141	3	incorporating	incorporate	VERB
ajst-11366	141	4	soft	soft	ADJ
ajst-11366	141	5	-	-	PUNCT
ajst-11366	141	6	nms	nms	NOUN
ajst-11366	141	7	achieved	achieve	VERB
ajst-11366	141	8	an	an	DET
ajst-11366	141	9	accuracy	accuracy	NOUN
ajst-11366	141	10	of	of	ADP
ajst-11366	141	11	59.8	59.8	NUM
ajst-11366	141	12	%	%	NOUN
ajst-11366	141	13	,	,	PUNCT
ajst-11366	141	14	yielding	yield	VERB
ajst-11366	141	15	a	a	DET
ajst-11366	141	16	2.6	2.6	NUM
ajst-11366	141	17	%	%	NOUN
ajst-11366	141	18	increase	increase	NOUN
ajst-11366	141	19	and	and	CCONJ
ajst-11366	141	20	an	an	DET
ajst-11366	141	21	overall	overall	ADJ
ajst-11366	141	22	improvement	improvement	NOUN
ajst-11366	141	23	of	of	ADP
ajst-11366	141	24	13.2	13.2	NUM
ajst-11366	141	25	%	%	NOUN
ajst-11366	141	26	in	in	ADP
ajst-11366	141	27	precision	precision	NOUN
ajst-11366	141	28	.	.	PUNCT
ajst-11366	142	1	based	base	VERB
ajst-11366	142	2	on	on	ADP
ajst-11366	142	3	the	the	DET
ajst-11366	142	4	experimental	experimental	ADJ
ajst-11366	142	5	results	result	NOUN
ajst-11366	142	6	,	,	PUNCT
ajst-11366	142	7	it	it	PRON
ajst-11366	142	8	is	be	AUX
ajst-11366	142	9	evident	evident	ADJ
ajst-11366	142	10	that	that	SCONJ
ajst-11366	142	11	each	each	DET
ajst-11366	142	12	module	module	NOUN
ajst-11366	142	13	showed	show	VERB
ajst-11366	142	14	varying	vary	VERB
ajst-11366	142	15	degrees	degree	NOUN
ajst-11366	142	16	of	of	ADP
ajst-11366	142	17	progress	progress	NOUN
ajst-11366	142	18	,	,	PUNCT
ajst-11366	142	19	with	with	ADP
ajst-11366	142	20	the	the	DET
ajst-11366	142	21	backbone	backbone	NOUN
ajst-11366	142	22	showcasing	showcase	VERB
ajst-11366	142	23	the	the	DET
ajst-11366	142	24	most	most	ADV
ajst-11366	142	25	noticeable	noticeable	ADJ
ajst-11366	142	26	improvement	improvement	NOUN
ajst-11366	142	27	.	.	PUNCT
ajst-11366	143	1	the	the	DET
ajst-11366	143	2	precision	precision	NOUN
ajst-11366	143	3	comparison	comparison	NOUN
ajst-11366	143	4	chart	chart	NOUN
ajst-11366	143	5	further	far	ADV
ajst-11366	143	6	underscores	underscore	VERB
ajst-11366	143	7	the	the	DET
ajst-11366	143	8	elevated	elevated	ADJ
ajst-11366	143	9	recognition	recognition	NOUN
ajst-11366	143	10	performance	performance	NOUN
ajst-11366	143	11	of	of	ADP
ajst-11366	143	12	the	the	DET
ajst-11366	143	13	improved	improved	ADJ
ajst-11366	143	14	network	network	NOUN
ajst-11366	143	15	on	on	ADP
ajst-11366	143	16	the	the	DET
ajst-11366	143	17	tile	tile	NOUN
ajst-11366	143	18	defect	defect	NOUN
ajst-11366	143	19	detection	detection	NOUN
ajst-11366	143	20	dataset	dataset	NOUN
ajst-11366	143	21	,	,	PUNCT
ajst-11366	143	22	along	along	ADP
ajst-11366	143	23	with	with	ADP
ajst-11366	143	24	the	the	DET
ajst-11366	143	25	efficacy	efficacy	NOUN
ajst-11366	143	26	of	of	ADP
ajst-11366	143	27	the	the	DET
ajst-11366	143	28	added	add	VERB
ajst-11366	143	29	modules	module	NOUN
ajst-11366	143	30	.	.	PUNCT
ajst-11366	144	1	3.5	3.5	NUM
ajst-11366	144	2	.	.	PUNCT
ajst-11366	145	1	accuracy	accuracy	NOUN
ajst-11366	145	2	and	and	CCONJ
ajst-11366	145	3	training	training	NOUN
ajst-11366	145	4	performance	performance	NOUN
ajst-11366	145	5	for	for	ADP
ajst-11366	145	6	each	each	DET
ajst-11366	145	7	category	category	NOUN
ajst-11366	145	8	from	from	ADP
ajst-11366	145	9	figure	figure	NOUN
ajst-11366	145	10	8	8	NUM
ajst-11366	145	11	,	,	PUNCT
ajst-11366	145	12	it	it	PRON
ajst-11366	145	13	is	be	AUX
ajst-11366	145	14	evident	evident	ADJ
ajst-11366	145	15	that	that	SCONJ
ajst-11366	145	16	the	the	DET
ajst-11366	145	17	accuracy	accuracy	NOUN
ajst-11366	145	18	for	for	ADP
ajst-11366	145	19	'	'	PUNCT
ajst-11366	145	20	edge	edge	NOUN
ajst-11366	145	21	anomaly	anomaly	NOUN
ajst-11366	145	22	'	'	PUNCT
ajst-11366	145	23	reaches	reach	VERB
ajst-11366	145	24	80.3	80.3	NUM
ajst-11366	145	25	%	%	NOUN
ajst-11366	145	26	,	,	PUNCT
ajst-11366	145	27	'	'	PUNCT
ajst-11366	145	28	angular	angular	ADJ
ajst-11366	145	29	anomaly	anomaly	NOUN
ajst-11366	145	30	'	'	PUNCT
ajst-11366	145	31	achieves	achieve	VERB
ajst-11366	145	32	89	89	NUM
ajst-11366	145	33	%	%	NOUN
ajst-11366	145	34	,	,	PUNCT
ajst-11366	145	35	and	and	CCONJ
ajst-11366	145	36	even	even	ADV
ajst-11366	145	37	the	the	DET
ajst-11366	145	38	'	'	PUNCT
ajst-11366	145	39	aperture	aperture	ADJ
ajst-11366	145	40	defects	defect	NOUN
ajst-11366	145	41	'	'	PART
ajst-11366	145	42	,	,	PUNCT
ajst-11366	145	43	which	which	PRON
ajst-11366	145	44	can	can	AUX
ajst-11366	145	45	be	be	AUX
ajst-11366	145	46	somewhat	somewhat	ADV
ajst-11366	145	47	ambiguous	ambiguous	ADJ
ajst-11366	145	48	even	even	ADV
ajst-11366	145	49	to	to	ADP
ajst-11366	145	50	human	human	ADJ
ajst-11366	145	51	observers	observer	NOUN
ajst-11366	145	52	,	,	PUNCT
ajst-11366	145	53	achieve	achieve	VERB
ajst-11366	145	54	an	an	DET
ajst-11366	145	55	accuracy	accuracy	NOUN
ajst-11366	145	56	of	of	ADP
ajst-11366	145	57	82.1	82.1	NUM
ajst-11366	145	58	%	%	NOUN
ajst-11366	145	59	.	.	PUNCT
ajst-11366	146	1	the	the	DET
ajst-11366	146	2	accuracies	accuracy	NOUN
ajst-11366	146	3	for	for	ADP
ajst-11366	146	4	'	'	PUNCT
ajst-11366	146	5	white	white	ADJ
ajst-11366	146	6	blemish	blemish	NOUN
ajst-11366	146	7	'	'	PUNCT
ajst-11366	146	8	,	,	PUNCT
ajst-11366	146	9	'	'	PUNCT
ajst-11366	146	10	light	light	ADJ
ajst-11366	146	11	blemish	blemish	NOUN
ajst-11366	146	12	'	'	PUNCT
ajst-11366	146	13	,	,	PUNCT
ajst-11366	146	14	and	and	CCONJ
ajst-11366	146	15	'	'	PUNCT
ajst-11366	146	16	dark	dark	ADJ
ajst-11366	146	17	blemish	blemish	NOUN
ajst-11366	146	18	'	'	PUNCT
ajst-11366	146	19	have	have	AUX
ajst-11366	146	20	also	also	ADV
ajst-11366	146	21	shown	show	VERB
ajst-11366	146	22	significant	significant	ADJ
ajst-11366	146	23	improvement	improvement	NOUN
ajst-11366	146	24	.	.	PUNCT
ajst-11366	147	1	these	these	DET
ajst-11366	147	2	results	result	NOUN
ajst-11366	147	3	indicate	indicate	VERB
ajst-11366	147	4	that	that	SCONJ
ajst-11366	147	5	the	the	DET
ajst-11366	147	6	improved	improved	ADJ
ajst-11366	147	7	network	network	NOUN
ajst-11366	147	8	in	in	ADP
ajst-11366	147	9	this	this	DET
ajst-11366	147	10	study	study	NOUN
ajst-11366	147	11	performs	perform	VERB
ajst-11366	147	12	well	well	ADV
ajst-11366	147	13	in	in	ADP
ajst-11366	147	14	tile	tile	NOUN
ajst-11366	147	15	defect	defect	NOUN
ajst-11366	147	16	detection	detection	NOUN
ajst-11366	147	17	,	,	PUNCT
ajst-11366	147	18	effectively	effectively	ADV
ajst-11366	147	19	enhancing	enhance	VERB
ajst-11366	147	20	the	the	DET
ajst-11366	147	21	network	network	NOUN
ajst-11366	147	22	's	's	PART
ajst-11366	147	23	capability	capability	NOUN
ajst-11366	147	24	to	to	PART
ajst-11366	147	25	detect	detect	VERB
ajst-11366	147	26	small	small	ADJ
ajst-11366	147	27	target	target	NOUN
ajst-11366	147	28	defects	defect	NOUN
ajst-11366	147	29	.	.	PUNCT
ajst-11366	148	1	figure	figure	NOUN
ajst-11366	148	2	8	8	NUM
ajst-11366	148	3	.	.	PUNCT
ajst-11366	148	4	defect	defect	VERB
ajst-11366	148	5	type	type	NOUN
ajst-11366	148	6	accuracy	accuracy	NOUN
ajst-11366	148	7	to	to	PART
ajst-11366	148	8	provide	provide	VERB
ajst-11366	148	9	a	a	DET
ajst-11366	148	10	clearer	clear	ADJ
ajst-11366	148	11	demonstration	demonstration	NOUN
ajst-11366	148	12	of	of	ADP
ajst-11366	148	13	the	the	DET
ajst-11366	148	14	progress	progress	NOUN
ajst-11366	148	15	achieved	achieve	VERB
ajst-11366	148	16	by	by	ADP
ajst-11366	148	17	the	the	DET
ajst-11366	148	18	improved	improved	ADJ
ajst-11366	148	19	network	network	NOUN
ajst-11366	148	20	,	,	PUNCT
ajst-11366	148	21	the	the	DET
ajst-11366	148	22	following	follow	VERB
ajst-11366	148	23	figure	figure	NOUN
ajst-11366	148	24	presents	present	VERB
ajst-11366	148	25	a	a	DET
ajst-11366	148	26	comparison	comparison	NOUN
ajst-11366	148	27	between	between	ADP
ajst-11366	148	28	the	the	DET
ajst-11366	148	29	original	original	ADJ
ajst-11366	148	30	network	network	NOUN
ajst-11366	148	31	and	and	CCONJ
ajst-11366	148	32	the	the	DET
ajst-11366	148	33	network	network	NOUN
ajst-11366	148	34	presented	present	VERB
ajst-11366	148	35	in	in	ADP
ajst-11366	148	36	this	this	DET
ajst-11366	148	37	study	study	NOUN
ajst-11366	148	38	.	.	PUNCT
ajst-11366	149	1	it	it	PRON
ajst-11366	149	2	is	be	AUX
ajst-11366	149	3	evident	evident	ADJ
ajst-11366	149	4	that	that	SCONJ
ajst-11366	149	5	the	the	DET
ajst-11366	149	6	enhanced	enhanced	ADJ
ajst-11366	149	7	version	version	NOUN
ajst-11366	149	8	of	of	ADP
ajst-11366	149	9	the	the	DET
ajst-11366	149	10	network	network	NOUN
ajst-11366	149	11	in	in	ADP
ajst-11366	149	12	this	this	DET
ajst-11366	149	13	study	study	NOUN
ajst-11366	149	14	achieves	achieve	VERB
ajst-11366	149	15	a	a	DET
ajst-11366	149	16	higher	high	ADJ
ajst-11366	149	17	level	level	NOUN
ajst-11366	149	18	of	of	ADP
ajst-11366	149	19	defect	defect	ADJ
ajst-11366	149	20	detection	detection	NOUN
ajst-11366	149	21	recognition	recognition	NOUN
ajst-11366	149	22	,	,	PUNCT
ajst-11366	149	23	effectively	effectively	ADV
ajst-11366	149	24	preventing	prevent	VERB
ajst-11366	149	25	false	false	ADJ
ajst-11366	149	26	negatives	negative	NOUN
ajst-11366	149	27	,	,	PUNCT
ajst-11366	149	28	and	and	CCONJ
ajst-11366	149	29	meets	meet	VERB
ajst-11366	149	30	the	the	DET
ajst-11366	149	31	factory	factory	NOUN
ajst-11366	149	32	's	's	PART
ajst-11366	149	33	requirements	requirement	NOUN
ajst-11366	149	34	for	for	ADP
ajst-11366	149	35	tile	tile	NOUN
ajst-11366	149	36	defect	defect	NOUN
ajst-11366	149	37	detection	detection	NOUN
ajst-11366	149	38	.	.	PUNCT
ajst-11366	150	1	figure	figure	NOUN
ajst-11366	150	2	9	9	NUM
ajst-11366	150	3	.	.	PUNCT
ajst-11366	150	4	faster	fast	ADJ
ajst-11366	150	5	-	-	PUNCT
ajst-11366	150	6	rcnn	rcnn	NOUN
ajst-11366	150	7	detection	detection	NOUN
ajst-11366	150	8	result	result	NOUN
ajst-11366	150	9	figure	figure	NOUN
ajst-11366	150	10	10	10	NUM
ajst-11366	150	11	.	.	PUNCT
ajst-11366	151	1	improved	improve	VERB
ajst-11366	151	2	network	network	NOUN
ajst-11366	151	3	detection	detection	NOUN
ajst-11366	151	4	result	result	VERB
ajst-11366	151	5	190	190	NUM
ajst-11366	151	6	4	4	NUM
ajst-11366	151	7	.	.	PUNCT
ajst-11366	152	1	summary	summary	VERB
ajst-11366	152	2	the	the	DET
ajst-11366	152	3	tile	tile	NOUN
ajst-11366	152	4	defect	defect	NOUN
ajst-11366	152	5	dataset	dataset	NOUN
ajst-11366	152	6	exhibits	exhibit	VERB
ajst-11366	152	7	a	a	DET
ajst-11366	152	8	wide	wide	ADJ
ajst-11366	152	9	range	range	NOUN
ajst-11366	152	10	of	of	ADP
ajst-11366	152	11	defect	defect	ADJ
ajst-11366	152	12	sizes	size	NOUN
ajst-11366	152	13	and	and	CCONJ
ajst-11366	152	14	significant	significant	ADJ
ajst-11366	152	15	variations	variation	NOUN
ajst-11366	152	16	in	in	ADP
ajst-11366	152	17	their	their	PRON
ajst-11366	152	18	characteristics	characteristic	NOUN
ajst-11366	152	19	.	.	PUNCT
ajst-11366	153	1	the	the	DET
ajst-11366	153	2	distribution	distribution	NOUN
ajst-11366	153	3	of	of	ADP
ajst-11366	153	4	easy	easy	ADJ
ajst-11366	153	5	-	-	PUNCT
ajst-11366	153	6	to	to	ADP
ajst-11366	153	7	-	-	PUNCT
ajst-11366	153	8	detect	detect	VERB
ajst-11366	153	9	and	and	CCONJ
ajst-11366	153	10	hard	hard	ADJ
ajst-11366	153	11	-	-	PUNCT
ajst-11366	153	12	to	to	ADP
ajst-11366	153	13	-	-	PUNCT
ajst-11366	153	14	detect	detect	NOUN
ajst-11366	153	15	categories	category	NOUN
ajst-11366	153	16	is	be	AUX
ajst-11366	153	17	uneven	uneven	ADJ
ajst-11366	153	18	.	.	PUNCT
ajst-11366	154	1	in	in	ADP
ajst-11366	154	2	this	this	DET
ajst-11366	154	3	study	study	NOUN
ajst-11366	154	4	,	,	PUNCT
ajst-11366	154	5	a	a	DET
ajst-11366	154	6	faster	fast	ADJ
ajst-11366	154	7	r	r	NOUN
ajst-11366	154	8	-	-	PUNCT
ajst-11366	154	9	cnn	cnn	PROPN
ajst-11366	154	10	model	model	NOUN
ajst-11366	154	11	with	with	ADP
ajst-11366	154	12	resnet	resnet	NOUN
ajst-11366	154	13	as	as	SCONJ
ajst-11366	154	14	the	the	DET
ajst-11366	154	15	backbone	backbone	NOUN
ajst-11366	154	16	was	be	AUX
ajst-11366	154	17	employed	employ	VERB
ajst-11366	154	18	to	to	PART
ajst-11366	154	19	address	address	VERB
ajst-11366	154	20	these	these	DET
ajst-11366	154	21	challenges	challenge	NOUN
ajst-11366	154	22	.	.	PUNCT
ajst-11366	155	1	this	this	DET
ajst-11366	155	2	approach	approach	NOUN
ajst-11366	155	3	not	not	PART
ajst-11366	155	4	only	only	ADV
ajst-11366	155	5	enables	enable	VERB
ajst-11366	155	6	the	the	DET
ajst-11366	155	7	model	model	NOUN
ajst-11366	155	8	to	to	PART
ajst-11366	155	9	focus	focus	VERB
ajst-11366	155	10	on	on	ADP
ajst-11366	155	11	less	less	ADV
ajst-11366	155	12	readily	readily	ADV
ajst-11366	155	13	detectable	detectable	ADJ
ajst-11366	155	14	features	feature	NOUN
ajst-11366	155	15	,	,	PUNCT
ajst-11366	155	16	resolving	resolve	VERB
ajst-11366	155	17	the	the	DET
ajst-11366	155	18	issue	issue	NOUN
ajst-11366	155	19	of	of	ADP
ajst-11366	155	20	data	datum	NOUN
ajst-11366	155	21	imbalance	imbalance	NOUN
ajst-11366	155	22	,	,	PUNCT
ajst-11366	155	23	but	but	CCONJ
ajst-11366	155	24	also	also	ADV
ajst-11366	155	25	ensures	ensure	VERB
ajst-11366	155	26	stability	stability	NOUN
ajst-11366	155	27	and	and	CCONJ
ajst-11366	155	28	enhancement	enhancement	NOUN
ajst-11366	155	29	through	through	ADP
ajst-11366	155	30	the	the	DET
ajst-11366	155	31	use	use	NOUN
ajst-11366	155	32	of	of	ADP
ajst-11366	155	33	a	a	DET
ajst-11366	155	34	bifpn	bifpn	NOUN
ajst-11366	155	35	-	-	PUNCT
ajst-11366	155	36	based	base	VERB
ajst-11366	155	37	neck	neck	NOUN
ajst-11366	155	38	.	.	PUNCT
ajst-11366	156	1	the	the	DET
ajst-11366	156	2	adoption	adoption	NOUN
ajst-11366	156	3	of	of	ADP
ajst-11366	156	4	the	the	DET
ajst-11366	156	5	pascal	pascal	PROPN
ajst-11366	156	6	voc	voc	NOUN
ajst-11366	156	7	format	format	NOUN
ajst-11366	156	8	for	for	ADP
ajst-11366	156	9	the	the	DET
ajst-11366	156	10	dataset	dataset	NOUN
ajst-11366	156	11	and	and	CCONJ
ajst-11366	156	12	the	the	DET
ajst-11366	156	13	coco	coco	PROPN
ajst-11366	156	14	evaluation	evaluation	NOUN
ajst-11366	156	15	metrics	metric	NOUN
ajst-11366	156	16	adheres	adhere	VERB
ajst-11366	156	17	to	to	ADP
ajst-11366	156	18	the	the	DET
ajst-11366	156	19	common	common	ADJ
ajst-11366	156	20	detection	detection	NOUN
ajst-11366	156	21	methodology	methodology	NOUN
ajst-11366	156	22	in	in	ADP
ajst-11366	156	23	object	object	NOUN
ajst-11366	156	24	detection	detection	NOUN
ajst-11366	156	25	algorithms	algorithm	NOUN
ajst-11366	156	26	,	,	PUNCT
ajst-11366	156	27	resulting	result	VERB
ajst-11366	156	28	in	in	ADP
ajst-11366	156	29	improved	improved	ADJ
ajst-11366	156	30	accuracy	accuracy	NOUN
ajst-11366	156	31	and	and	CCONJ
ajst-11366	156	32	dataset	dataset	ADJ
ajst-11366	156	33	robustness	robustness	NOUN
ajst-11366	156	34	compared	compare	VERB
ajst-11366	156	35	to	to	ADP
ajst-11366	156	36	the	the	DET
ajst-11366	156	37	original	original	ADJ
ajst-11366	156	38	network	network	NOUN
ajst-11366	156	39	.	.	PUNCT
ajst-11366	157	1	the	the	DET
ajst-11366	157	2	algorithm	algorithm	NOUN
ajst-11366	157	3	's	's	PART
ajst-11366	157	4	feasibility	feasibility	NOUN
ajst-11366	157	5	and	and	CCONJ
ajst-11366	157	6	effectiveness	effectiveness	NOUN
ajst-11366	157	7	are	be	AUX
ajst-11366	157	8	validated	validate	VERB
ajst-11366	157	9	.	.	PUNCT
ajst-11366	158	1	although	although	SCONJ
ajst-11366	158	2	the	the	DET
ajst-11366	158	3	incorporation	incorporation	NOUN
ajst-11366	158	4	of	of	ADP
ajst-11366	158	5	resnet	resnet	NOUN
ajst-11366	158	6	and	and	CCONJ
ajst-11366	158	7	the	the	DET
ajst-11366	158	8	more	more	ADV
ajst-11366	158	9	complex	complex	ADJ
ajst-11366	158	10	fpn	fpn	NOUN
ajst-11366	158	11	increases	increase	VERB
ajst-11366	158	12	the	the	DET
ajst-11366	158	13	number	number	NOUN
ajst-11366	158	14	of	of	ADP
ajst-11366	158	15	parameters	parameter	NOUN
ajst-11366	158	16	,	,	PUNCT
ajst-11366	158	17	the	the	DET
ajst-11366	158	18	use	use	NOUN
ajst-11366	158	19	of	of	ADP
ajst-11366	158	20	depthwise	depthwise	NOUN
ajst-11366	158	21	separable	separable	ADJ
ajst-11366	158	22	convolution	convolution	NOUN
ajst-11366	158	23	reduces	reduce	VERB
ajst-11366	158	24	detection	detection	NOUN
ajst-11366	158	25	time	time	NOUN
ajst-11366	158	26	,	,	PUNCT
ajst-11366	158	27	still	still	ADV
ajst-11366	158	28	meeting	meet	VERB
ajst-11366	158	29	the	the	DET
ajst-11366	158	30	requirements	requirement	NOUN
ajst-11366	158	31	for	for	ADP
ajst-11366	158	32	tile	tile	NOUN
ajst-11366	158	33	defect	defect	NOUN
ajst-11366	158	34	detection	detection	NOUN
ajst-11366	158	35	on	on	ADP
ajst-11366	158	36	factory	factory	NOUN
ajst-11366	158	37	production	production	NOUN
ajst-11366	158	38	lines	line	NOUN
ajst-11366	158	39	.	.	PUNCT
ajst-11366	159	1	this	this	DET
ajst-11366	159	2	improvement	improvement	NOUN
ajst-11366	159	3	offers	offer	VERB
ajst-11366	159	4	significant	significant	ADJ
ajst-11366	159	5	practical	practical	ADJ
ajst-11366	159	6	significance	significance	NOUN
ajst-11366	159	7	for	for	ADP
ajst-11366	159	8	modern	modern	ADJ
ajst-11366	159	9	,	,	PUNCT
ajst-11366	159	10	intelligent	intelligent	ADJ
ajst-11366	159	11	construction	construction	NOUN
ajst-11366	159	12	factories	factory	NOUN
ajst-11366	159	13	.	.	PUNCT
ajst-11366	160	1	the	the	DET
ajst-11366	160	2	current	current	ADJ
ajst-11366	160	3	enhanced	enhanced	ADJ
ajst-11366	160	4	network	network	NOUN
ajst-11366	160	5	focuses	focus	VERB
ajst-11366	160	6	solely	solely	ADV
ajst-11366	160	7	on	on	ADP
ajst-11366	160	8	tile	tile	NOUN
ajst-11366	160	9	defect	defect	NOUN
ajst-11366	160	10	detection	detection	NOUN
ajst-11366	160	11	.	.	PUNCT
ajst-11366	161	1	future	future	ADJ
ajst-11366	161	2	considerations	consideration	NOUN
ajst-11366	161	3	include	include	VERB
ajst-11366	161	4	incorporating	incorporate	VERB
ajst-11366	161	5	various	various	ADJ
ajst-11366	161	6	features	feature	NOUN
ajst-11366	161	7	into	into	ADP
ajst-11366	161	8	detection	detection	NOUN
ajst-11366	161	9	targets	target	NOUN
ajst-11366	161	10	and	and	CCONJ
ajst-11366	161	11	introducing	introduce	VERB
ajst-11366	161	12	suitable	suitable	ADJ
ajst-11366	161	13	attention	attention	NOUN
ajst-11366	161	14	mechanisms	mechanism	NOUN
ajst-11366	161	15	into	into	ADP
ajst-11366	161	16	the	the	DET
ajst-11366	161	17	neck	neck	NOUN
ajst-11366	161	18	component	component	NOUN
ajst-11366	161	19	to	to	PART
ajst-11366	161	20	optimize	optimize	VERB
ajst-11366	161	21	detection	detection	NOUN
ajst-11366	161	22	speed	speed	NOUN
ajst-11366	161	23	,	,	PUNCT
ajst-11366	161	24	aiming	aim	VERB
ajst-11366	161	25	for	for	ADP
ajst-11366	161	26	a	a	DET
ajst-11366	161	27	more	more	ADV
ajst-11366	161	28	broadly	broadly	ADV
ajst-11366	161	29	applicable	applicable	ADJ
ajst-11366	161	30	and	and	CCONJ
ajst-11366	161	31	efficient	efficient	ADJ
ajst-11366	161	32	network	network	NOUN
ajst-11366	161	33	model	model	NOUN
ajst-11366	161	34	.	.	PUNCT
ajst-11366	162	1	references	reference	NOUN
ajst-11366	162	2	[	[	X
ajst-11366	162	3	1	1	NUM
ajst-11366	162	4	]	]	X
ajst-11366	162	5	huang	huang	PROPN
ajst-11366	162	6	huining	huining	PROPN
ajst-11366	162	7	.	.	PUNCT
ajst-11366	163	1	global	global	ADJ
ajst-11366	163	2	ceramic	ceramic	ADJ
ajst-11366	163	3	tile	tile	PROPN
ajst-11366	163	4	development	development	NOUN
ajst-11366	163	5	status	status	NOUN
ajst-11366	163	6	and	and	CCONJ
ajst-11366	163	7	implications[j].foshan	implications[j].foshan	PROPN
ajst-11366	163	8	ceramics.vol	ceramics.vol	PROPN
ajst-11366	163	9	.	.	PUNCT
ajst-11366	164	1	25(2015),p.1	25(2015),p.1	PROPN
ajst-11366	164	2	-	-	PUNCT
ajst-11366	164	3	11	11	NUM
ajst-11366	164	4	.	.	PUNCT
ajst-11366	165	1	[	[	X
ajst-11366	165	2	2	2	NUM
ajst-11366	165	3	]	]	SYM
ajst-11366	165	4	shockletti.review	shockletti.review	NOUN
ajst-11366	165	5	on	on	ADP
ajst-11366	165	6	application	application	NOUN
ajst-11366	165	7	of	of	ADP
ajst-11366	165	8	surface	surface	NOUN
ajst-11366	165	9	defect	defect	NOUN
ajst-11366	165	10	detection[j].electronic	detection[j].electronic	ADJ
ajst-11366	165	11	technology.vol	technology.vol	PROPN
ajst-11366	165	12	.	.	PUNCT
ajst-11366	165	13	49(2020),p.189	49(2020),p.189	NUM
ajst-11366	165	14	-	-	PUNCT
ajst-11366	165	15	191	191	NUM
ajst-11366	165	16	.	.	PUNCT
ajst-11366	166	1	[	[	X
ajst-11366	166	2	3	3	X
ajst-11366	166	3	]	]	X
ajst-11366	166	4	pu	pu	PROPN
ajst-11366	166	5	yuxiang.design	yuxiang.design	PROPN
ajst-11366	166	6	of	of	ADP
ajst-11366	166	7	bottle	bottle	NOUN
ajst-11366	166	8	cap	cap	PROPN
ajst-11366	166	9	visual	visual	ADJ
ajst-11366	166	10	inspection	inspection	NOUN
ajst-11366	166	11	system	system	NOUN
ajst-11366	166	12	based	base	VERB
ajst-11366	166	13	on	on	ADP
ajst-11366	166	14	machine	machine	NOUN
ajst-11366	166	15	vision[j].light	vision[j].light	ADJ
ajst-11366	166	16	textile	textile	NOUN
ajst-11366	166	17	industry	industry	NOUN
ajst-11366	166	18	and	and	CCONJ
ajst-11366	166	19	technology	technology	NOUN
ajst-11366	166	20	.	.	PUNCT
ajst-11366	167	1	vol	vol	NOUN
ajst-11366	167	2	.	.	PUNCT
ajst-11366	168	1	49(2020),p.30	49(2020),p.30	NUM
ajst-11366	168	2	-	-	SYM
ajst-11366	168	3	33	33	NUM
ajst-11366	168	4	.	.	PUNCT
ajst-11366	169	1	[	[	X
ajst-11366	169	2	4	4	X
ajst-11366	169	3	]	]	PUNCT
ajst-11366	169	4	yang	yang	PROPN
ajst-11366	169	5	cui.speckled	cui.speckle	VERB
ajst-11366	169	6	micro	micro	ADJ
ajst-11366	169	7	-	-	ADJ
ajst-11366	169	8	defects	defect	NOUN
ajst-11366	169	9	detection	detection	NOUN
ajst-11366	169	10	based	base	VERB
ajst-11366	169	11	on	on	ADP
ajst-11366	169	12	deep	deep	ADJ
ajst-11366	169	13	neural	neural	ADJ
ajst-11366	169	14	network	network	NOUN
ajst-11366	169	15	learning[j].journal	learning[j].journal	ADJ
ajst-11366	169	16	of	of	ADP
ajst-11366	169	17	anqing	anqe	VERB
ajst-11366	169	18	normal	normal	ADJ
ajst-11366	169	19	university(natural	university(natural	ADJ
ajst-11366	169	20	science	science	NOUN
ajst-11366	169	21	edition).vol.28(2022)no.4,p.5156	edition).vol.28(2022)no.4,p.5156	PROPN
ajst-11366	169	22	.	.	PUNCT
ajst-11366	170	1	[	[	X
ajst-11366	170	2	5	5	X
ajst-11366	170	3	]	]	PUNCT
ajst-11366	170	4	biradara	biradara	PROPN
ajst-11366	170	5	m	m	PROPN
ajst-11366	170	6	,	,	PUNCT
ajst-11366	170	7	shiparamattia	shiparamattia	PROPN
ajst-11366	170	8	b	b	PROPN
ajst-11366	170	9	,	,	PUNCT
ajst-11366	170	10	patilb	patilb	ADJ
ajst-11366	170	11	b	b	NOUN
ajst-11366	170	12	.fabric	.fabric	VERB
ajst-11366	170	13	defect	defect	VERB
ajst-11366	170	14	detection	detection	NOUN
ajst-11366	170	15	using	use	VERB
ajst-11366	170	16	deep	deep	ADJ
ajst-11366	170	17	convol	convol	NOUN
ajst-11366	170	18	-	-	PUNCT
ajst-11366	170	19	utional	utional	ADJ
ajst-11366	170	20	neural	neural	ADJ
ajst-11366	170	21	network[j].optical	network[j].optical	ADJ
ajst-11366	170	22	memory	memory	NOUN
ajst-11366	170	23	and	and	CCONJ
ajst-11366	170	24	neural	neural	ADJ
ajst-11366	170	25	networks.vol	networks.vol	NUM
ajst-11366	170	26	.	.	NOUN
ajst-11366	170	27	30(2021),p.250	30(2021),p.250	NUM
ajst-11366	170	28	-	-	SYM
ajst-11366	170	29	256	256	NUM
ajst-11366	170	30	[	[	SYM
ajst-11366	170	31	6	6	NUM
ajst-11366	170	32	]	]	X
ajst-11366	170	33	girshick	girshick	ADJ
ajst-11366	170	34	r	r	PROPN
ajst-11366	170	35	,	,	PUNCT
ajst-11366	170	36	donahue	donahue	PROPN
ajst-11366	170	37	j	j	PROPN
ajst-11366	170	38	,	,	PUNCT
ajst-11366	170	39	darrell	darrell	PROPN
ajst-11366	170	40	t	t	PROPN
ajst-11366	170	41	,	,	PUNCT
ajst-11366	170	42	et	et	NOUN
ajst-11366	170	43	al.rich	al.rich	ADP
ajst-11366	170	44	feature	feature	NOUN
ajst-11366	170	45	hierarchies	hierarchy	NOUN
ajst-11366	170	46	for	for	ADP
ajst-11366	170	47	accurate	accurate	ADJ
ajst-11366	170	48	object	object	NOUN
ajst-11366	170	49	detection	detection	NOUN
ajst-11366	170	50	and	and	CCONJ
ajst-11366	170	51	semantic	semantic	ADJ
ajst-11366	170	52	segmentation[c	segmentation[c	NOUN
ajst-11366	170	53	]	]	PUNCT
ajst-11366	170	54	.	.	PUNCT
ajst-11366	171	1	proceedings	proceeding	NOUN
ajst-11366	171	2	of	of	ADP
ajst-11366	171	3	the	the	DET
ajst-11366	171	4	ieee	ieee	NOUN
ajst-11366	171	5	conference	conference	NOUN
ajst-11366	171	6	on	on	ADP
ajst-11366	171	7	computer	computer	NOUN
ajst-11366	171	8	vision	vision	NOUN
ajst-11366	171	9	and	and	CCONJ
ajst-11366	171	10	pattern	pattern	NOUN
ajst-11366	171	11	recognition.beijing	recognition.beije	VERB
ajst-11366	171	12	,	,	PUNCT
ajst-11366	171	13	jul	jul	PROPN
ajst-11366	171	14	6,p.580587	6,p.580587	NUM
ajst-11366	171	15	.	.	PUNCT
ajst-11366	172	1	[	[	X
ajst-11366	172	2	7	7	X
ajst-11366	172	3	]	]	X
ajst-11366	172	4	ren	ren	PROPN
ajst-11366	172	5	s	s	PROPN
ajst-11366	172	6	q	q	NOUN
ajst-11366	172	7	,	,	PUNCT
ajst-11366	172	8	he	he	PRON
ajst-11366	172	9	k	k	PROPN
ajst-11366	172	10	m	m	VERB
ajst-11366	172	11	,	,	PUNCT
ajst-11366	172	12	girshick	girshick	ADJ
ajst-11366	172	13	r	r	NOUN
ajst-11366	172	14	,	,	PUNCT
ajst-11366	172	15	et	et	NOUN
ajst-11366	172	16	al.faster	al.faster	ADP
ajst-11366	172	17	r	r	NOUN
ajst-11366	172	18	-	-	PUNCT
ajst-11366	172	19	cnn	cnn	NOUN
ajst-11366	172	20	:	:	PUNCT
ajst-11366	172	21	towards	towards	ADP
ajst-11366	172	22	real	real	ADJ
ajst-11366	172	23	-	-	PUNCT
ajst-11366	172	24	time	time	NOUN
ajst-11366	172	25	object	object	NOUN
ajst-11366	172	26	detection	detection	NOUN
ajst-11366	172	27	with	with	ADP
ajst-11366	172	28	region	region	NOUN
ajst-11366	172	29	proposal	proposal	NOUN
ajst-11366	172	30	networks[j].neural	networks[j].neural	ADJ
ajst-11366	172	31	information	information	NOUN
ajst-11366	172	32	processing	processing	NOUN
ajst-11366	172	33	systems	system	NOUN
ajst-11366	172	34	.	.	PUNCT
ajst-11366	173	1	6(2017	6(2017	NUM
ajst-11366	173	2	)	)	PUNCT
ajst-11366	173	3	,	,	PUNCT
ajst-11366	173	4	p.1137	p.1137	X
ajst-11366	173	5	-	-	PUNCT
ajst-11366	173	6	1149	1149	NUM
ajst-11366	173	7	.	.	PUNCT
ajst-11366	174	1	[	[	X
ajst-11366	174	2	8	8	NUM
ajst-11366	174	3	]	]	X
ajst-11366	174	4	redmon	redmon	PROPN
ajst-11366	174	5	j	j	PROPN
ajst-11366	174	6	,	,	PUNCT
ajst-11366	174	7	divvala	divvala	PROPN
ajst-11366	174	8	s	s	PROPN
ajst-11366	174	9	,	,	PUNCT
ajst-11366	174	10	girshick	girshick	ADJ
ajst-11366	174	11	r	r	NOUN
ajst-11366	174	12	,	,	PUNCT
ajst-11366	174	13	et	et	NOUN
ajst-11366	174	14	al.you	al.you	PRON
ajst-11366	174	15	only	only	ADV
ajst-11366	174	16	look	look	VERB
ajst-11366	174	17	once	once	ADV
ajst-11366	174	18	:	:	PUNCT
ajst-11366	174	19	unified	unified	ADJ
ajst-11366	174	20	,	,	PUNCT
ajst-11366	174	21	real	real	ADJ
ajst-11366	174	22	-	-	PUNCT
ajst-11366	174	23	time	time	NOUN
ajst-11366	174	24	object	object	NOUN
ajst-11366	174	25	detection[c	detection[c	VERB
ajst-11366	174	26	]	]	PUNCT
ajst-11366	174	27	.	.	PUNCT
ajst-11366	175	1	proceedings	proceeding	NOUN
ajst-11366	175	2	of	of	ADP
ajst-11366	175	3	the	the	DET
ajst-11366	175	4	ieee	ieee	NOUN
ajst-11366	175	5	conference	conference	NOUN
ajst-11366	175	6	on	on	ADP
ajst-11366	175	7	computer	computer	NOUN
ajst-11366	175	8	vision	vision	NOUN
ajst-11366	175	9	and	and	CCONJ
ajst-11366	175	10	pattern	pattern	NOUN
ajst-11366	175	11	recognition.santiago	recognition.santiago	PROPN
ajst-11366	175	12	,	,	PUNCT
ajst-11366	175	13	dec	dec	PROPN
ajst-11366	175	14	7	7	NUM
ajst-11366	175	15	-	-	SYM
ajst-11366	175	16	13,p.779	13,p.779	NUM
ajst-11366	175	17	-	-	PUNCT
ajst-11366	175	18	788	788	NUM
ajst-11366	175	19	.	.	PUNCT
ajst-11366	176	1	[	[	X
ajst-11366	176	2	9	9	NUM
ajst-11366	176	3	]	]	X
ajst-11366	176	4	lin	lin	PROPN
ajst-11366	176	5	t	t	PROPN
ajst-11366	176	6	,	,	PUNCT
ajst-11366	176	7	goyal	goyal	PROPN
ajst-11366	176	8	p	p	NOUN
ajst-11366	176	9	,	,	PUNCT
ajst-11366	176	10	girshick	girshick	ADJ
ajst-11366	176	11	r	r	NOUN
ajst-11366	176	12	,	,	PUNCT
ajst-11366	176	13	he	he	PRON
ajst-11366	176	14	k	k	PROPN
ajst-11366	176	15	m	m	PROPN
ajst-11366	176	16	,	,	PUNCT
ajst-11366	176	17	et	et	PROPN
ajst-11366	176	18	al	al	PROPN
ajst-11366	176	19	.	.	PROPN
ajst-11366	176	20	focal	focal	ADJ
ajst-11366	176	21	loss	loss	NOUN
ajst-11366	176	22	for	for	ADP
ajst-11366	176	23	dense	dense	ADJ
ajst-11366	176	24	object	object	NOUN
ajst-11366	176	25	detection[c	detection[c	VERB
ajst-11366	176	26	]	]	PUNCT
ajst-11366	176	27	.	.	PROPN
ajst-11366	177	1	2017	2017	NUM
ajst-11366	177	2	ieee	ieee	PROPN
ajst-11366	177	3	international	international	ADJ
ajst-11366	177	4	conference	conference	NOUN
ajst-11366	177	5	on	on	ADP
ajst-11366	177	6	computer	computer	NOUN
ajst-11366	177	7	vision	vision	NOUN
ajst-11366	177	8	.	.	PUNCT
ajst-11366	178	1	venice.italy	venice.italy	NUM
ajst-11366	178	2	,	,	PUNCT
ajst-11366	178	3	oct	oct	PROPN
ajst-11366	178	4	22	22	NUM
ajst-11366	178	5	-	-	SYM
ajst-11366	178	6	29	29	NUM
ajst-11366	178	7	,	,	PUNCT
ajst-11366	178	8	p.2999	p.2999	NOUN
ajst-11366	178	9	-	-	PUNCT
ajst-11366	178	10	3007	3007	NUM
ajst-11366	178	11	.	.	PUNCT
ajst-11366	179	1	[	[	X
ajst-11366	179	2	10	10	NUM
ajst-11366	179	3	]	]	X
ajst-11366	179	4	zhang	zhang	PROPN
ajst-11366	179	5	zuoren.resnet	zuoren.resnet	PROPN
ajst-11366	179	6	-	-	PUNCT
ajst-11366	179	7	based	base	VERB
ajst-11366	179	8	model	model	NOUN
ajst-11366	179	9	for	for	ADP
ajst-11366	179	10	autonomous	autonomous	ADJ
ajst-11366	179	11	vehicles	vehicle	NOUN
ajst-11366	179	12	trajectory	trajectory	NOUN
ajst-11366	179	13	prediction	prediction	NOUN
ajst-11366	179	14	[	[	X
ajst-11366	179	15	c].2021	c].2021	NOUN
ajst-11366	179	16	ieee	ieee	NOUN
ajst-11366	179	17	international	international	ADJ
ajst-11366	179	18	conference	conference	NOUN
ajst-11366	179	19	on	on	ADP
ajst-11366	179	20	consumer	consumer	NOUN
ajst-11366	179	21	electronics	electronic	NOUN
ajst-11366	179	22	and	and	CCONJ
ajst-11366	179	23	computer	computer	NOUN
ajst-11366	179	24	engineering	engineering	NOUN
ajst-11366	179	25	.	.	PUNCT
ajst-11366	180	1	guangzhou	guangzhou	PROPN
ajst-11366	180	2	,	,	PUNCT
ajst-11366	180	3	oct	oct	PROPN
ajst-11366	180	4	3,p.565	3,p.565	NUM
ajst-11366	180	5	-	-	SYM
ajst-11366	180	6	568	568	NUM
ajst-11366	180	7	.	.	PUNCT
ajst-11366	181	1	[	[	X
ajst-11366	181	2	11	11	NUM
ajst-11366	181	3	]	]	X
ajst-11366	181	4	mingxing	mingxe	VERB
ajst-11366	181	5	tan	tan	PROPN
ajst-11366	181	6	,	,	PUNCT
ajst-11366	181	7	ruoming	ruome	VERB
ajst-11366	181	8	pang	pang	NOUN
ajst-11366	181	9	,	,	PUNCT
ajst-11366	181	10	quoc	quoc	PROPN
ajst-11366	181	11	v.	v.	ADP
ajst-11366	181	12	le.efficientdet	le.efficientdet	NOUN
ajst-11366	181	13	:	:	PUNCT
ajst-11366	181	14	scalable	scalable	ADJ
ajst-11366	181	15	and	and	CCONJ
ajst-11366	181	16	efficient	efficient	ADJ
ajst-11366	181	17	object	object	NOUN
ajst-11366	181	18	detection[c].proceedings	detection[c].proceeding	NOUN
ajst-11366	181	19	of	of	ADP
ajst-11366	181	20	the	the	DET
ajst-11366	181	21	ieee	ieee	NOUN
ajst-11366	181	22	conference	conference	NOUN
ajst-11366	181	23	on	on	ADP
ajst-11366	181	24	computer	computer	NOUN
ajst-11366	181	25	vision	vision	NOUN
ajst-11366	181	26	and	and	CCONJ
ajst-11366	181	27	pattern	pattern	NOUN
ajst-11366	181	28	recognition	recognition	NOUN
ajst-11366	181	29	(	(	PUNCT
ajst-11366	181	30	2020).seattle	2020).seattle	PROPN
ajst-11366	181	31	,	,	PUNCT
ajst-11366	181	32	june	june	PROPN
ajst-11366	181	33	14	14	NUM
ajst-11366	181	34	-	-	PUNCT
ajst-11366	181	35	19,p.10781	19,p.10781	NUM
ajst-11366	181	36	-	-	PUNCT
ajst-11366	181	37	10790	10790	NUM
ajst-11366	181	38	[	[	X
ajst-11366	181	39	12	12	NUM
ajst-11366	181	40	]	]	X
ajst-11366	181	41	andrew	andrew	PROPN
ajst-11366	181	42	g.	g.	PROPN
ajst-11366	181	43	howard	howard	PROPN
ajst-11366	181	44	,	,	PUNCT
ajst-11366	181	45	menglong	menglong	PROPN
ajst-11366	181	46	zhu	zhu	PROPN
ajst-11366	181	47	,	,	PUNCT
ajst-11366	181	48	bo	bo	PROPN
ajst-11366	181	49	chen	chen	PROPN
ajst-11366	181	50	,	,	PUNCT
ajst-11366	181	51	et	et	NOUN
ajst-11366	181	52	al.mobilenets	al.mobilenet	NOUN
ajst-11366	181	53	:	:	PUNCT
ajst-11366	181	54	efficient	efficient	ADJ
ajst-11366	181	55	convolutional	convolutional	ADJ
ajst-11366	181	56	neural	neural	ADJ
ajst-11366	181	57	networks	network	NOUN
ajst-11366	181	58	for	for	ADP
ajst-11366	181	59	mobile	mobile	ADJ
ajst-11366	181	60	vision	vision	NOUN
ajst-11366	181	61	applications.goggle	applications.goggle	PROPN
ajst-11366	181	62	.	.	PUNCT
ajst-11366	182	1	[	[	X
ajst-11366	182	2	13	13	NUM
ajst-11366	182	3	]	]	PUNCT
ajst-11366	182	4	bodla	bodla	NOUN
ajst-11366	182	5	n	n	CCONJ
ajst-11366	182	6	,	,	PUNCT
ajst-11366	182	7	singh	singh	PROPN
ajst-11366	182	8	b	b	NOUN
ajst-11366	182	9	,	,	PUNCT
ajst-11366	182	10	chellappa	chellappa	ADJ
ajst-11366	182	11	r.soft	r.soft	NOUN
ajst-11366	182	12	-	-	PUNCT
ajst-11366	182	13	nms	nms	NOUN
ajst-11366	182	14	im	im	ADV
ajst-11366	182	15	-	-	PUNCT
ajst-11366	182	16	proving	prove	VERB
ajst-11366	182	17	object	object	NOUN
ajst-11366	182	18	detection	detection	NOUN
ajst-11366	182	19	with	with	ADP
ajst-11366	182	20	one	one	NUM
ajst-11366	182	21	line	line	NOUN
ajst-11366	182	22	of	of	ADP
ajst-11366	182	23	code	code	NOUN
ajst-11366	182	24	[	[	X
ajst-11366	182	25	c].2017	c].2017	X
ajst-11366	182	26	ieee	ieee	PROPN
ajst-11366	182	27	international	international	ADJ
ajst-11366	182	28	conference	conference	NOUN
ajst-11366	182	29	on	on	ADP
ajst-11366	182	30	computer	computer	PROPN
ajst-11366	182	31	vision.venice	vision.venice	PROPN
ajst-11366	182	32	,	,	PUNCT
ajst-11366	182	33	aug	aug	PROPN
ajst-11366	182	34	9,p.5562	9,p.5562	NUM
ajst-11366	182	35	-	-	SYM
ajst-11366	182	36	5570	5570	NUM
ajst-11366	182	37	.	.	PUNCT