id	sid	tid	token	lemma	pos
fcis-12818	1	1	frontiers	frontier	NOUN
fcis-12818	1	2	in	in	ADP
fcis-12818	1	3	computing	computing	NOUN
fcis-12818	1	4	and	and	CCONJ
fcis-12818	1	5	intelligent	intelligent	ADJ
fcis-12818	1	6	systems	system	NOUN
fcis-12818	1	7	issn	issn	VERB
fcis-12818	1	8	:	:	PUNCT
fcis-12818	1	9	2832	2832	NUM
fcis-12818	1	10	-	-	SYM
fcis-12818	1	11	6024	6024	NUM
fcis-12818	1	12	|	|	NOUN
fcis-12818	1	13	vol	vol	NOUN
fcis-12818	1	14	.	.	PROPN
fcis-12818	2	1	5	5	NUM
fcis-12818	2	2	,	,	PUNCT
fcis-12818	2	3	no	no	INTJ
fcis-12818	2	4	.	.	NOUN
fcis-12818	2	5	2	2	NUM
fcis-12818	2	6	,	,	PUNCT
fcis-12818	2	7	2023	2023	NUM
fcis-12818	2	8	81	81	NUM
fcis-12818	2	9	research	research	NOUN
fcis-12818	2	10	on	on	ADP
fcis-12818	2	11	improved	improved	ADJ
fcis-12818	2	12	method	method	NOUN
fcis-12818	2	13	based	base	VERB
fcis-12818	2	14	on	on	ADP
fcis-12818	2	15	yolov5s	yolov5s	PROPN
fcis-12818	2	16	target	target	NOUN
fcis-12818	2	17	detection	detection	NOUN
fcis-12818	2	18	model	model	NOUN
fcis-12818	2	19	xiuhuan	xiuhuan	PROPN
fcis-12818	2	20	dong	dong	PROPN
fcis-12818	2	21	*	*	PROPN
fcis-12818	2	22	,	,	PUNCT
fcis-12818	2	23	shixin	shixin	PROPN
fcis-12818	2	24	li	li	PROPN
fcis-12818	2	25	,	,	PUNCT
fcis-12818	2	26	liming	lime	VERB
fcis-12818	2	27	zhou	zhou	PROPN
fcis-12818	2	28	college	college	PROPN
fcis-12818	2	29	of	of	ADP
fcis-12818	2	30	electronic	electronic	ADJ
fcis-12818	2	31	engineering	engineering	NOUN
fcis-12818	2	32	,	,	PUNCT
fcis-12818	2	33	tianjin	tianjin	PROPN
fcis-12818	2	34	university	university	PROPN
fcis-12818	2	35	of	of	ADP
fcis-12818	2	36	technology	technology	NOUN
fcis-12818	2	37	and	and	CCONJ
fcis-12818	2	38	education	education	NOUN
fcis-12818	2	39	,	,	PUNCT
fcis-12818	2	40	tianjin	tianjin	PROPN
fcis-12818	2	41	300222	300222	NUM
fcis-12818	2	42	,	,	PUNCT
fcis-12818	2	43	china	china	PROPN
fcis-12818	2	44	*	*	PUNCT
fcis-12818	2	45	corresponding	correspond	VERB
fcis-12818	2	46	author	author	NOUN
fcis-12818	2	47	:	:	PUNCT
fcis-12818	2	48	xiuhuan	xiuhuan	PROPN
fcis-12818	2	49	dong	dong	PROPN
fcis-12818	2	50	(	(	PUNCT
fcis-12818	2	51	email	email	NOUN
fcis-12818	2	52	:	:	PUNCT
fcis-12818	2	53	0422211032@tute.edu.cn	0422211032@tute.edu.cn	NUM
fcis-12818	2	54	)	)	PUNCT
fcis-12818	2	55	abstract	abstract	NOUN
fcis-12818	2	56	:	:	PUNCT
fcis-12818	2	57	aiming	aim	VERB
fcis-12818	2	58	at	at	ADP
fcis-12818	2	59	the	the	DET
fcis-12818	2	60	problem	problem	NOUN
fcis-12818	2	61	of	of	ADP
fcis-12818	2	62	low	low	ADJ
fcis-12818	2	63	detection	detection	NOUN
fcis-12818	2	64	accuracy	accuracy	NOUN
fcis-12818	2	65	of	of	ADP
fcis-12818	2	66	small	small	ADJ
fcis-12818	2	67	targets	target	NOUN
fcis-12818	2	68	,	,	PUNCT
fcis-12818	2	69	an	an	DET
fcis-12818	2	70	object	object	NOUN
fcis-12818	2	71	detection	detection	NOUN
fcis-12818	2	72	method	method	NOUN
fcis-12818	2	73	based	base	VERB
fcis-12818	2	74	on	on	ADP
fcis-12818	2	75	average	average	ADJ
fcis-12818	2	76	pooling	pooling	NOUN
fcis-12818	2	77	improved	improve	VERB
fcis-12818	2	78	yolov5s	yolov5s	PROPN
fcis-12818	2	79	model	model	NOUN
fcis-12818	2	80	is	be	AUX
fcis-12818	2	81	proposed	propose	VERB
fcis-12818	2	82	.	.	PUNCT
fcis-12818	3	1	the	the	DET
fcis-12818	3	2	algorithm	algorithm	NOUN
fcis-12818	3	3	introduces	introduce	VERB
fcis-12818	3	4	the	the	DET
fcis-12818	3	5	squeeze	squeeze	NOUN
fcis-12818	3	6	excitation	excitation	NOUN
fcis-12818	3	7	attention	attention	NOUN
fcis-12818	3	8	module	module	NOUN
fcis-12818	3	9	and	and	CCONJ
fcis-12818	3	10	the	the	DET
fcis-12818	3	11	efficient	efficient	ADJ
fcis-12818	3	12	intersection	intersection	NOUN
fcis-12818	3	13	over	over	ADP
fcis-12818	3	14	union	union	NOUN
fcis-12818	3	15	loss	loss	NOUN
fcis-12818	3	16	function	function	NOUN
fcis-12818	3	17	to	to	PART
fcis-12818	3	18	comprehensively	comprehensively	ADV
fcis-12818	3	19	improve	improve	VERB
fcis-12818	3	20	the	the	DET
fcis-12818	3	21	detection	detection	NOUN
fcis-12818	3	22	calculation	calculation	NOUN
fcis-12818	3	23	efficiency	efficiency	NOUN
fcis-12818	3	24	and	and	CCONJ
fcis-12818	3	25	accurate	accurate	ADJ
fcis-12818	3	26	deployment	deployment	NOUN
fcis-12818	3	27	ability	ability	NOUN
fcis-12818	3	28	.	.	PUNCT
fcis-12818	4	1	with	with	ADP
fcis-12818	4	2	the	the	DET
fcis-12818	4	3	development	development	NOUN
fcis-12818	4	4	of	of	ADP
fcis-12818	4	5	deep	deep	ADJ
fcis-12818	4	6	learning	learning	NOUN
fcis-12818	4	7	technology	technology	NOUN
fcis-12818	4	8	,	,	PUNCT
fcis-12818	4	9	which	which	PRON
fcis-12818	4	10	is	be	AUX
fcis-12818	4	11	of	of	ADP
fcis-12818	4	12	great	great	ADJ
fcis-12818	4	13	significance	significance	NOUN
fcis-12818	4	14	to	to	PART
fcis-12818	4	15	improve	improve	VERB
fcis-12818	4	16	the	the	DET
fcis-12818	4	17	detection	detection	NOUN
fcis-12818	4	18	accuracy	accuracy	NOUN
fcis-12818	4	19	and	and	CCONJ
fcis-12818	4	20	detection	detection	NOUN
fcis-12818	4	21	rate	rate	NOUN
fcis-12818	4	22	.	.	PUNCT
fcis-12818	5	1	yolo	yolo	PROPN
fcis-12818	5	2	greatly	greatly	ADV
fcis-12818	5	3	improves	improve	VERB
fcis-12818	5	4	detection	detection	NOUN
fcis-12818	5	5	performance	performance	NOUN
fcis-12818	5	6	,	,	PUNCT
fcis-12818	5	7	three	three	NUM
fcis-12818	5	8	times	time	NOUN
fcis-12818	5	9	faster	fast	ADJ
fcis-12818	5	10	than	than	ADP
fcis-12818	5	11	retinanet	retinanet	NOUN
fcis-12818	5	12	and	and	CCONJ
fcis-12818	5	13	2	2	NUM
fcis-12818	5	14	times	time	NOUN
fcis-12818	5	15	faster	fast	ADV
fcis-12818	5	16	than	than	ADP
fcis-12818	5	17	faster	fast	ADJ
fcis-12818	5	18	-	-	PUNCT
fcis-12818	5	19	rcnn	rcnn	NOUN
fcis-12818	5	20	.	.	PUNCT
fcis-12818	6	1	yolo	yolo	PROPN
fcis-12818	6	2	has	have	VERB
fcis-12818	6	3	strong	strong	ADJ
fcis-12818	6	4	generalization	generalization	NOUN
fcis-12818	6	5	ability	ability	NOUN
fcis-12818	6	6	,	,	PUNCT
fcis-12818	6	7	can	can	AUX
fcis-12818	6	8	be	be	AUX
fcis-12818	6	9	applied	apply	VERB
fcis-12818	6	10	to	to	ADP
fcis-12818	6	11	different	different	ADJ
fcis-12818	6	12	application	application	NOUN
fcis-12818	6	13	scenarios	scenario	NOUN
fcis-12818	6	14	,	,	PUNCT
fcis-12818	6	15	and	and	CCONJ
fcis-12818	6	16	is	be	AUX
fcis-12818	6	17	also	also	ADV
fcis-12818	6	18	easy	easy	ADJ
fcis-12818	6	19	to	to	PART
fcis-12818	6	20	deploy	deploy	VERB
fcis-12818	6	21	.	.	PUNCT
fcis-12818	7	1	the	the	DET
fcis-12818	7	2	steel	steel	NOUN
fcis-12818	7	3	surface	surface	NOUN
fcis-12818	7	4	defect	defect	VERB
fcis-12818	7	5	public	public	ADJ
fcis-12818	7	6	dataset	dataset	NOUN
fcis-12818	7	7	was	be	AUX
fcis-12818	7	8	selected	select	VERB
fcis-12818	7	9	for	for	ADP
fcis-12818	7	10	verification	verification	NOUN
fcis-12818	7	11	.	.	PUNCT
fcis-12818	8	1	the	the	DET
fcis-12818	8	2	results	result	NOUN
fcis-12818	8	3	show	show	VERB
fcis-12818	8	4	that	that	SCONJ
fcis-12818	8	5	the	the	DET
fcis-12818	8	6	improved	improved	ADJ
fcis-12818	8	7	yolov5s	yolov5s	PROPN
fcis-12818	8	8	model	model	NOUN
fcis-12818	8	9	is	be	AUX
fcis-12818	8	10	better	well	ADJ
fcis-12818	8	11	than	than	ADP
fcis-12818	8	12	the	the	DET
fcis-12818	8	13	original	original	ADJ
fcis-12818	8	14	yolov5s	yolov5s	PROPN
fcis-12818	8	15	model	model	NOUN
fcis-12818	8	16	,	,	PUNCT
fcis-12818	8	17	the	the	DET
fcis-12818	8	18	test	test	NOUN
fcis-12818	8	19	average	average	ADJ
fcis-12818	8	20	accuracy	accuracy	NOUN
fcis-12818	8	21	map	map	NOUN
fcis-12818	8	22	can	can	AUX
fcis-12818	8	23	reach	reach	VERB
fcis-12818	8	24	81.8	81.8	NUM
fcis-12818	8	25	%	%	NOUN
fcis-12818	8	26	,	,	PUNCT
fcis-12818	8	27	the	the	DET
fcis-12818	8	28	average	average	ADJ
fcis-12818	8	29	accuracy	accuracy	NOUN
fcis-12818	8	30	map	map	NOUN
fcis-12818	8	31	of	of	ADP
fcis-12818	8	32	the	the	DET
fcis-12818	8	33	model	model	NOUN
fcis-12818	8	34	is	be	AUX
fcis-12818	8	35	increased	increase	VERB
fcis-12818	8	36	by	by	ADP
fcis-12818	8	37	7.4	7.4	NUM
fcis-12818	8	38	%	%	NOUN
fcis-12818	8	39	,	,	PUNCT
fcis-12818	8	40	and	and	CCONJ
fcis-12818	8	41	the	the	DET
fcis-12818	8	42	overall	overall	ADJ
fcis-12818	8	43	performance	performance	NOUN
fcis-12818	8	44	of	of	ADP
fcis-12818	8	45	the	the	DET
fcis-12818	8	46	improved	improved	ADJ
fcis-12818	8	47	model	model	NOUN
fcis-12818	8	48	is	be	AUX
fcis-12818	8	49	better	well	ADJ
fcis-12818	8	50	than	than	ADP
fcis-12818	8	51	other	other	ADJ
fcis-12818	8	52	conventional	conventional	ADJ
fcis-12818	8	53	models	model	NOUN
fcis-12818	8	54	.	.	PUNCT
fcis-12818	9	1	keywords	keyword	NOUN
fcis-12818	9	2	:	:	PUNCT
fcis-12818	9	3	small	small	ADJ
fcis-12818	9	4	targets	target	NOUN
fcis-12818	9	5	;	;	PUNCT
fcis-12818	9	6	squeeze	squeeze	VERB
fcis-12818	9	7	excitation	excitation	NOUN
fcis-12818	9	8	attention	attention	NOUN
fcis-12818	9	9	module	module	NOUN
fcis-12818	9	10	;	;	PUNCT
fcis-12818	9	11	defect	defect	ADJ
fcis-12818	9	12	detection	detection	NOUN
fcis-12818	9	13	.	.	PUNCT
fcis-12818	10	1	1	1	X
fcis-12818	10	2	.	.	X
fcis-12818	10	3	introduction	introduction	NOUN
fcis-12818	10	4	one	one	NUM
fcis-12818	10	5	-	-	PUNCT
fcis-12818	10	6	stage	stage	NOUN
fcis-12818	10	7	object	object	NOUN
fcis-12818	10	8	detection	detection	NOUN
fcis-12818	10	9	algorithms	algorithm	NOUN
fcis-12818	10	10	,	,	PUNCT
fcis-12818	10	11	mainly	mainly	ADV
fcis-12818	10	12	yolo	yolo	ADJ
fcis-12818	10	13	series	series	PROPN
fcis-12818	10	14	,	,	PUNCT
fcis-12818	10	15	ssd	ssd	PROPN
fcis-12818	10	16	,	,	PUNCT
fcis-12818	10	17	etc	etc	X
fcis-12818	10	18	.	.	X
fcis-12818	11	1	its	its	PRON
fcis-12818	11	2	core	core	NOUN
fcis-12818	11	3	goal	goal	NOUN
fcis-12818	11	4	is	be	AUX
fcis-12818	11	5	to	to	PART
fcis-12818	11	6	return	return	VERB
fcis-12818	11	7	the	the	DET
fcis-12818	11	8	category	category	NOUN
fcis-12818	11	9	and	and	CCONJ
fcis-12818	11	10	location	location	NOUN
fcis-12818	11	11	of	of	ADP
fcis-12818	11	12	the	the	DET
fcis-12818	11	13	target	target	NOUN
fcis-12818	11	14	through	through	ADP
fcis-12818	11	15	a	a	DET
fcis-12818	11	16	network	network	NOUN
fcis-12818	11	17	.	.	PUNCT
fcis-12818	12	1	yolo	yolo	INTJ
fcis-12818	12	2	(	(	PUNCT
fcis-12818	12	3	you	you	PRON
fcis-12818	12	4	only	only	ADV
fcis-12818	12	5	look	look	VERB
fcis-12818	12	6	once	once	ADV
fcis-12818	12	7	,	,	PUNCT
fcis-12818	12	8	yolo	yolo	ADJ
fcis-12818	12	9	)	)	PUNCT
fcis-12818	12	10	series	series	PROPN
fcis-12818	12	11	algorithms	algorithm	NOUN
fcis-12818	12	12	have	have	VERB
fcis-12818	12	13	good	good	ADJ
fcis-12818	12	14	comprehensive	comprehensive	ADJ
fcis-12818	12	15	performance	performance	NOUN
fcis-12818	12	16	[	[	X
fcis-12818	12	17	1	1	X
fcis-12818	12	18	]	]	X
fcis-12818	12	19	[	[	X
fcis-12818	12	20	2	2	NUM
fcis-12818	12	21	]	]	PUNCT
fcis-12818	12	22	.	.	PUNCT
fcis-12818	13	1	yolo	yolo	PROPN
fcis-12818	13	2	uses	use	VERB
fcis-12818	13	3	a	a	DET
fcis-12818	13	4	convolutional	convolutional	ADJ
fcis-12818	13	5	network	network	NOUN
fcis-12818	13	6	to	to	PART
fcis-12818	13	7	extract	extract	VERB
fcis-12818	13	8	features	feature	NOUN
fcis-12818	13	9	,	,	PUNCT
fcis-12818	13	10	and	and	CCONJ
fcis-12818	13	11	then	then	ADV
fcis-12818	13	12	uses	use	VERB
fcis-12818	13	13	a	a	DET
fcis-12818	13	14	fully	fully	ADV
fcis-12818	13	15	connected	connect	VERB
fcis-12818	13	16	layer	layer	NOUN
fcis-12818	13	17	to	to	PART
fcis-12818	13	18	obtain	obtain	VERB
fcis-12818	13	19	predicted	predict	VERB
fcis-12818	13	20	values	value	NOUN
fcis-12818	13	21	.	.	PUNCT
fcis-12818	14	1	the	the	DET
fcis-12818	14	2	network	network	NOUN
fcis-12818	14	3	structure	structure	NOUN
fcis-12818	14	4	refers	refer	VERB
fcis-12818	14	5	to	to	ADP
fcis-12818	14	6	the	the	DET
fcis-12818	14	7	goolenet	goolenet	NOUN
fcis-12818	14	8	model	model	NOUN
fcis-12818	14	9	and	and	CCONJ
fcis-12818	14	10	contains	contain	VERB
fcis-12818	14	11	24	24	NUM
fcis-12818	14	12	convolutional	convolutional	ADJ
fcis-12818	14	13	layers	layer	NOUN
fcis-12818	14	14	and	and	CCONJ
fcis-12818	14	15	2	2	NUM
fcis-12818	14	16	fully	fully	ADV
fcis-12818	14	17	connected	connected	ADJ
fcis-12818	14	18	layers	layer	NOUN
fcis-12818	14	19	[	[	X
fcis-12818	14	20	3	3	NUM
fcis-12818	14	21	]	]	PUNCT
fcis-12818	14	22	.	.	PUNCT
fcis-12818	15	1	the	the	DET
fcis-12818	15	2	output	output	NOUN
fcis-12818	15	3	vector	vector	NOUN
fcis-12818	15	4	of	of	ADP
fcis-12818	15	5	yolo	yolo	ADJ
fcis-12818	15	6	includes	include	VERB
fcis-12818	15	7	not	not	PART
fcis-12818	15	8	only	only	ADV
fcis-12818	15	9	the	the	DET
fcis-12818	15	10	category	category	NOUN
fcis-12818	15	11	of	of	ADP
fcis-12818	15	12	the	the	DET
fcis-12818	15	13	target	target	NOUN
fcis-12818	15	14	.	.	PUNCT
fcis-12818	16	1	also	also	ADV
fcis-12818	16	2	include	include	VERB
fcis-12818	16	3	the	the	DET
fcis-12818	16	4	coordinates	coordinate	NOUN
fcis-12818	16	5	of	of	ADP
fcis-12818	16	6	the	the	DET
fcis-12818	16	7	bounding	bounding	NOUN
fcis-12818	16	8	box	box	NOUN
fcis-12818	16	9	and	and	CCONJ
fcis-12818	16	10	the	the	DET
fcis-12818	16	11	confidence	confidence	NOUN
fcis-12818	16	12	level	level	NOUN
fcis-12818	16	13	of	of	ADP
fcis-12818	16	14	the	the	DET
fcis-12818	16	15	prediction	prediction	NOUN
fcis-12818	16	16	.	.	PUNCT
fcis-12818	17	1	then	then	ADV
fcis-12818	17	2	,	,	PUNCT
fcis-12818	17	3	locally	locally	ADV
fcis-12818	17	4	unique	unique	ADJ
fcis-12818	17	5	prediction	prediction	NOUN
fcis-12818	17	6	boxes	box	NOUN
fcis-12818	17	7	are	be	AUX
fcis-12818	17	8	obtained	obtain	VERB
fcis-12818	17	9	by	by	ADP
fcis-12818	17	10	non	non	ADJ
fcis-12818	17	11	-	-	ADJ
fcis-12818	17	12	maximum	maximum	ADJ
fcis-12818	17	13	suppression	suppression	NOUN
fcis-12818	17	14	.	.	PUNCT
fcis-12818	18	1	in	in	ADP
fcis-12818	18	2	the	the	DET
fcis-12818	18	3	field	field	NOUN
fcis-12818	18	4	of	of	ADP
fcis-12818	18	5	deep	deep	ADJ
fcis-12818	18	6	learning	learning	NOUN
fcis-12818	18	7	-	-	PUNCT
fcis-12818	18	8	based	base	VERB
fcis-12818	18	9	object	object	NOUN
fcis-12818	18	10	detection	detection	NOUN
fcis-12818	18	11	,	,	PUNCT
fcis-12818	18	12	rectangles	rectangle	NOUN
fcis-12818	18	13	are	be	AUX
fcis-12818	18	14	used	use	VERB
fcis-12818	18	15	to	to	PART
fcis-12818	18	16	label	label	VERB
fcis-12818	18	17	their	their	PRON
fcis-12818	18	18	position	position	NOUN
fcis-12818	18	19	and	and	CCONJ
fcis-12818	18	20	size	size	NOUN
fcis-12818	18	21	[	[	X
fcis-12818	18	22	4	4	NUM
fcis-12818	18	23	]	]	PUNCT
fcis-12818	18	24	.	.	PUNCT
fcis-12818	19	1	at	at	ADP
fcis-12818	19	2	the	the	DET
fcis-12818	19	3	same	same	ADJ
fcis-12818	19	4	time	time	NOUN
fcis-12818	19	5	,	,	PUNCT
fcis-12818	19	6	convolutional	convolutional	ADJ
fcis-12818	19	7	neural	neural	ADJ
fcis-12818	19	8	networks	network	NOUN
fcis-12818	19	9	are	be	AUX
fcis-12818	19	10	used	use	VERB
fcis-12818	19	11	to	to	PART
fcis-12818	19	12	build	build	VERB
fcis-12818	19	13	machine	machine	NOUN
fcis-12818	19	14	learning	learning	NOUN
fcis-12818	19	15	models	model	NOUN
fcis-12818	19	16	,	,	PUNCT
fcis-12818	19	17	which	which	PRON
fcis-12818	19	18	are	be	AUX
fcis-12818	19	19	driven	drive	VERB
fcis-12818	19	20	by	by	ADP
fcis-12818	19	21	a	a	DET
fcis-12818	19	22	large	large	ADJ
fcis-12818	19	23	amount	amount	NOUN
fcis-12818	19	24	of	of	ADP
fcis-12818	19	25	labeled	label	VERB
fcis-12818	19	26	data	datum	NOUN
fcis-12818	19	27	.	.	PUNCT
fcis-12818	20	1	on	on	ADP
fcis-12818	20	2	top	top	NOUN
fcis-12818	20	3	of	of	ADP
fcis-12818	20	4	the	the	DET
fcis-12818	20	5	20	20	NUM
fcis-12818	20	6	convolutional	convolutional	ADJ
fcis-12818	20	7	layers	layer	NOUN
fcis-12818	20	8	obtained	obtain	VERB
fcis-12818	20	9	by	by	ADP
fcis-12818	20	10	pre	pre	ADJ
fcis-12818	20	11	-	-	NOUN
fcis-12818	20	12	training	training	ADJ
fcis-12818	20	13	,	,	PUNCT
fcis-12818	20	14	4	4	NUM
fcis-12818	20	15	convolutional	convolutional	ADJ
fcis-12818	20	16	layers	layer	NOUN
fcis-12818	20	17	and	and	CCONJ
fcis-12818	20	18	2	2	NUM
fcis-12818	20	19	fully	fully	ADV
fcis-12818	20	20	connected	connected	ADJ
fcis-12818	20	21	layers	layer	NOUN
fcis-12818	20	22	are	be	AUX
fcis-12818	20	23	randomly	randomly	ADV
fcis-12818	20	24	initialized	initialize	VERB
fcis-12818	20	25	[	[	PUNCT
fcis-12818	20	26	5	5	NUM
fcis-12818	20	27	]	]	PUNCT
fcis-12818	20	28	.	.	PUNCT
fcis-12818	21	1	on	on	ADP
fcis-12818	21	2	the	the	DET
fcis-12818	21	3	basis	basis	NOUN
fcis-12818	21	4	of	of	ADP
fcis-12818	21	5	the	the	DET
fcis-12818	21	6	original	original	ADJ
fcis-12818	21	7	yolo	yolo	ADJ
fcis-12818	21	8	backbone	backbone	NOUN
fcis-12818	21	9	model	model	NOUN
fcis-12818	21	10	,	,	PUNCT
fcis-12818	21	11	on	on	ADP
fcis-12818	21	12	the	the	DET
fcis-12818	21	13	one	one	NUM
fcis-12818	21	14	hand	hand	NOUN
fcis-12818	21	15	,	,	PUNCT
fcis-12818	21	16	the	the	DET
fcis-12818	21	17	se	se	PROPN
fcis-12818	21	18	attention	attention	NOUN
fcis-12818	21	19	mechanism	mechanism	NOUN
fcis-12818	21	20	is	be	AUX
fcis-12818	21	21	introduced	introduce	VERB
fcis-12818	21	22	[	[	PUNCT
fcis-12818	21	23	10	10	NUM
fcis-12818	21	24	]	]	PUNCT
fcis-12818	21	25	.	.	PUNCT
fcis-12818	22	1	the	the	DET
fcis-12818	22	2	se	se	PROPN
fcis-12818	22	3	module	module	NOUN
fcis-12818	22	4	was	be	AUX
fcis-12818	22	5	originally	originally	ADV
fcis-12818	22	6	proposed	propose	VERB
fcis-12818	22	7	by	by	ADP
fcis-12818	22	8	jie	jie	PROPN
fcis-12818	22	9	hu	hu	PROPN
fcis-12818	22	10	et	et	PROPN
fcis-12818	22	11	al	al	PROPN
fcis-12818	22	12	.	.	PROPN
fcis-12818	23	1	in	in	ADP
fcis-12818	23	2	2017	2017	NUM
fcis-12818	23	3	with	with	ADP
fcis-12818	23	4	up	up	ADP
fcis-12818	23	5	to	to	PART
fcis-12818	23	6	20,000	20,000	NUM
fcis-12818	23	7	citations	citation	NOUN
fcis-12818	23	8	,	,	PUNCT
fcis-12818	23	9	aiming	aim	VERB
fcis-12818	23	10	to	to	PART
fcis-12818	23	11	improve	improve	VERB
fcis-12818	23	12	the	the	DET
fcis-12818	23	13	efficiency	efficiency	NOUN
fcis-12818	23	14	of	of	ADP
fcis-12818	23	15	channel	channel	NOUN
fcis-12818	23	16	-	-	PUNCT
fcis-12818	23	17	to	to	ADP
fcis-12818	23	18	-	-	PUNCT
fcis-12818	23	19	channel	channel	NOUN
fcis-12818	23	20	information	information	NOUN
fcis-12818	23	21	transmission	transmission	NOUN
fcis-12818	23	22	in	in	ADP
fcis-12818	23	23	convolutional	convolutional	ADJ
fcis-12818	23	24	neural	neural	ADJ
fcis-12818	23	25	networks	network	NOUN
fcis-12818	23	26	(	(	PUNCT
fcis-12818	23	27	cnns	cnns	PROPN
fcis-12818	23	28	)	)	PUNCT
fcis-12818	23	29	.	.	PUNCT
fcis-12818	23	30	se	se	X
fcis-12818	23	31	(	(	PUNCT
fcis-12818	23	32	squeeze	squeeze	NOUN
fcis-12818	23	33	and	and	CCONJ
fcis-12818	23	34	excitation	excitation	NOUN
fcis-12818	23	35	,	,	PUNCT
fcis-12818	23	36	se	se	ADJ
fcis-12818	23	37	)	)	PUNCT
fcis-12818	23	38	attention	attention	NOUN
fcis-12818	23	39	mechanism	mechanism	NOUN
fcis-12818	23	40	learns	learn	VERB
fcis-12818	23	41	an	an	DET
fcis-12818	23	42	adaptive	adaptive	ADJ
fcis-12818	23	43	channel	channel	NOUN
fcis-12818	23	44	weight	weight	NOUN
fcis-12818	23	45	model	model	NOUN
fcis-12818	23	46	[	[	X
fcis-12818	23	47	11	11	NUM
fcis-12818	23	48	]	]	PUNCT
fcis-12818	23	49	.	.	PUNCT
fcis-12818	24	1	it	it	PRON
fcis-12818	24	2	focuses	focus	VERB
fcis-12818	24	3	on	on	ADP
fcis-12818	24	4	more	more	ADV
fcis-12818	24	5	useful	useful	ADJ
fcis-12818	24	6	channel	channel	NOUN
fcis-12818	24	7	information	information	NOUN
fcis-12818	24	8	,	,	PUNCT
fcis-12818	24	9	with	with	ADP
fcis-12818	24	10	high	high	ADJ
fcis-12818	24	11	detection	detection	NOUN
fcis-12818	24	12	efficiency	efficiency	NOUN
fcis-12818	24	13	and	and	CCONJ
fcis-12818	24	14	optimal	optimal	ADJ
fcis-12818	24	15	ablation	ablation	NOUN
fcis-12818	24	16	.	.	PUNCT
fcis-12818	25	1	on	on	ADP
fcis-12818	25	2	the	the	DET
fcis-12818	25	3	other	other	ADJ
fcis-12818	25	4	hand	hand	NOUN
fcis-12818	25	5	[	[	X
fcis-12818	25	6	12	12	NUM
fcis-12818	25	7	]	]	PUNCT
fcis-12818	25	8	,	,	PUNCT
fcis-12818	25	9	eiou	eiou	NOUN
fcis-12818	25	10	is	be	AUX
fcis-12818	25	11	introduced	introduce	VERB
fcis-12818	25	12	,	,	PUNCT
fcis-12818	25	13	and	and	CCONJ
fcis-12818	25	14	the	the	DET
fcis-12818	25	15	aspect	aspect	NOUN
fcis-12818	25	16	ratio	ratio	NOUN
fcis-12818	25	17	is	be	AUX
fcis-12818	25	18	replaced	replace	VERB
fcis-12818	25	19	by	by	ADP
fcis-12818	25	20	the	the	DET
fcis-12818	25	21	width	width	ADJ
fcis-12818	25	22	and	and	CCONJ
fcis-12818	25	23	height	height	NOUN
fcis-12818	25	24	difference	difference	NOUN
fcis-12818	25	25	value	value	NOUN
fcis-12818	25	26	on	on	ADP
fcis-12818	25	27	the	the	DET
fcis-12818	25	28	basis	basis	NOUN
fcis-12818	25	29	of	of	ADP
fcis-12818	25	30	ciou	ciou	NOUN
fcis-12818	25	31	,	,	PUNCT
fcis-12818	25	32	and	and	CCONJ
fcis-12818	25	33	focal	focal	ADJ
fcis-12818	25	34	loss	loss	NOUN
fcis-12818	25	35	solves	solve	VERB
fcis-12818	25	36	the	the	DET
fcis-12818	25	37	problem	problem	NOUN
fcis-12818	25	38	of	of	ADP
fcis-12818	25	39	difficult	difficult	ADJ
fcis-12818	25	40	sample	sample	NOUN
fcis-12818	25	41	imbalance	imbalance	NOUN
fcis-12818	26	1	[	[	X
fcis-12818	26	2	15	15	NUM
fcis-12818	26	3	]	]	PUNCT
fcis-12818	26	4	.	.	PUNCT
fcis-12818	27	1	this	this	DET
fcis-12818	27	2	paper	paper	NOUN
fcis-12818	27	3	finds	find	VERB
fcis-12818	27	4	that	that	SCONJ
fcis-12818	27	5	the	the	DET
fcis-12818	27	6	yolov5s	yolov5s	PROPN
fcis-12818	27	7	framework	framework	NOUN
fcis-12818	27	8	still	still	ADV
fcis-12818	27	9	has	have	VERB
fcis-12818	27	10	room	room	NOUN
fcis-12818	27	11	for	for	ADP
fcis-12818	27	12	improvement	improvement	NOUN
fcis-12818	27	13	in	in	ADP
fcis-12818	27	14	terms	term	NOUN
fcis-12818	27	15	of	of	ADP
fcis-12818	27	16	speed	speed	NOUN
fcis-12818	27	17	and	and	CCONJ
fcis-12818	27	18	accuracy	accuracy	NOUN
fcis-12818	27	19	.	.	PUNCT
fcis-12818	28	1	there	there	PRON
fcis-12818	28	2	is	be	VERB
fcis-12818	28	3	a	a	DET
fcis-12818	28	4	problem	problem	NOUN
fcis-12818	28	5	of	of	ADP
fcis-12818	28	6	low	low	ADJ
fcis-12818	28	7	detection	detection	NOUN
fcis-12818	28	8	accuracy	accuracy	NOUN
fcis-12818	28	9	for	for	ADP
fcis-12818	28	10	object	object	NOUN
fcis-12818	28	11	detection	detection	NOUN
fcis-12818	28	12	methods	method	NOUN
fcis-12818	28	13	.	.	PUNCT
fcis-12818	29	1	an	an	DET
fcis-12818	29	2	improved	improved	ADJ
fcis-12818	29	3	object	object	NOUN
fcis-12818	29	4	detection	detection	NOUN
fcis-12818	29	5	method	method	NOUN
fcis-12818	29	6	based	base	VERB
fcis-12818	29	7	on	on	ADP
fcis-12818	29	8	average	average	ADJ
fcis-12818	29	9	pooling	pooling	NOUN
fcis-12818	29	10	yolov5s	yolov5s	PROPN
fcis-12818	29	11	is	be	AUX
fcis-12818	29	12	proposed	propose	VERB
fcis-12818	29	13	.	.	PUNCT
fcis-12818	30	1	the	the	DET
fcis-12818	30	2	improved	improved	ADJ
fcis-12818	30	3	yolov5s	yolov5s	PROPN
fcis-12818	30	4	model	model	NOUN
fcis-12818	30	5	comprehensively	comprehensively	ADV
fcis-12818	30	6	improves	improve	VERB
fcis-12818	30	7	detection	detection	NOUN
fcis-12818	30	8	performance	performance	NOUN
fcis-12818	30	9	and	and	CCONJ
fcis-12818	30	10	deployment	deployment	NOUN
fcis-12818	30	11	capabilities	capability	NOUN
fcis-12818	30	12	.	.	PUNCT
fcis-12818	31	1	the	the	DET
fcis-12818	31	2	main	main	ADJ
fcis-12818	31	3	improvements	improvement	NOUN
fcis-12818	31	4	are	be	AUX
fcis-12818	31	5	as	as	SCONJ
fcis-12818	31	6	follows	follow	VERB
fcis-12818	31	7	:	:	PUNCT
fcis-12818	31	8	(	(	PUNCT
fcis-12818	31	9	1	1	X
fcis-12818	31	10	)	)	PUNCT
fcis-12818	31	11	the	the	DET
fcis-12818	31	12	se	se	PROPN
fcis-12818	31	13	attention	attention	NOUN
fcis-12818	31	14	mechanism	mechanism	NOUN
fcis-12818	31	15	is	be	AUX
fcis-12818	31	16	introduced	introduce	VERB
fcis-12818	31	17	,	,	PUNCT
fcis-12818	31	18	and	and	CCONJ
fcis-12818	31	19	the	the	DET
fcis-12818	31	20	improved	improved	ADJ
fcis-12818	31	21	yolov5s	yolov5s	PROPN
fcis-12818	31	22	model	model	NOUN
fcis-12818	31	23	effectively	effectively	ADV
fcis-12818	31	24	improves	improve	VERB
fcis-12818	31	25	the	the	DET
fcis-12818	31	26	feature	feature	NOUN
fcis-12818	31	27	extraction	extraction	NOUN
fcis-12818	31	28	ability	ability	NOUN
fcis-12818	31	29	of	of	ADP
fcis-12818	31	30	the	the	DET
fcis-12818	31	31	model	model	NOUN
fcis-12818	31	32	.	.	PUNCT
fcis-12818	32	1	(	(	PUNCT
fcis-12818	32	2	2	2	X
fcis-12818	32	3	)	)	PUNCT
fcis-12818	32	4	eiou	eiou	NOUN
fcis-12818	32	5	loss	loss	NOUN
fcis-12818	32	6	is	be	AUX
fcis-12818	32	7	introduced	introduce	VERB
fcis-12818	32	8	,	,	PUNCT
fcis-12818	32	9	and	and	CCONJ
fcis-12818	32	10	the	the	DET
fcis-12818	32	11	improved	improved	ADJ
fcis-12818	32	12	yolov5s	yolov5s	PROPN
fcis-12818	32	13	model	model	NOUN
fcis-12818	32	14	effectively	effectively	ADV
fcis-12818	32	15	improves	improve	VERB
fcis-12818	32	16	the	the	DET
fcis-12818	32	17	accuracy	accuracy	NOUN
fcis-12818	32	18	of	of	ADP
fcis-12818	32	19	model	model	NOUN
fcis-12818	32	20	object	object	NOUN
fcis-12818	32	21	detection	detection	NOUN
fcis-12818	32	22	,	,	PUNCT
fcis-12818	32	23	accelerates	accelerate	VERB
fcis-12818	32	24	the	the	DET
fcis-12818	32	25	calculation	calculation	NOUN
fcis-12818	32	26	speed	speed	NOUN
fcis-12818	32	27	,	,	PUNCT
fcis-12818	32	28	and	and	CCONJ
fcis-12818	32	29	ensures	ensure	VERB
fcis-12818	32	30	that	that	SCONJ
fcis-12818	32	31	the	the	DET
fcis-12818	32	32	object	object	NOUN
fcis-12818	32	33	detection	detection	NOUN
fcis-12818	32	34	model	model	NOUN
fcis-12818	32	35	obtains	obtain	VERB
fcis-12818	32	36	more	more	ADV
fcis-12818	32	37	important	important	ADJ
fcis-12818	32	38	feature	feature	NOUN
fcis-12818	32	39	information	information	NOUN
fcis-12818	32	40	.	.	PUNCT
fcis-12818	33	1	2	2	X
fcis-12818	33	2	.	.	X
fcis-12818	33	3	method	method	NOUN
fcis-12818	33	4	as	as	SCONJ
fcis-12818	33	5	shown	show	VERB
fcis-12818	33	6	in	in	ADP
fcis-12818	33	7	fig	fig	NOUN
fcis-12818	33	8	.	.	PUNCT
fcis-12818	34	1	1	1	NUM
fcis-12818	34	2	,	,	PUNCT
fcis-12818	34	3	the	the	DET
fcis-12818	34	4	original	original	ADJ
fcis-12818	34	5	yolo	yolo	ADJ
fcis-12818	34	6	model	model	NOUN
fcis-12818	34	7	introduced	introduce	VERB
fcis-12818	34	8	the	the	DET
fcis-12818	34	9	se	se	PROPN
fcis-12818	34	10	attention	attention	NOUN
fcis-12818	34	11	mechanism	mechanism	NOUN
fcis-12818	34	12	.	.	PUNCT
fcis-12818	35	1	se	se	PROPN
fcis-12818	35	2	is	be	AUX
fcis-12818	35	3	a	a	DET
fcis-12818	35	4	mechanism	mechanism	NOUN
fcis-12818	35	5	for	for	ADP
fcis-12818	35	6	assigning	assign	VERB
fcis-12818	35	7	weight	weight	NOUN
fcis-12818	35	8	parameters	parameter	NOUN
fcis-12818	35	9	with	with	ADP
fcis-12818	35	10	the	the	DET
fcis-12818	35	11	goal	goal	NOUN
fcis-12818	35	12	of	of	ADP
fcis-12818	35	13	assisting	assist	VERB
fcis-12818	35	14	the	the	DET
fcis-12818	35	15	model	model	NOUN
fcis-12818	35	16	in	in	ADP
fcis-12818	35	17	capturing	capture	VERB
fcis-12818	35	18	important	important	ADJ
fcis-12818	35	19	information	information	NOUN
fcis-12818	35	20	.	.	PUNCT
fcis-12818	36	1	the	the	DET
fcis-12818	36	2	attention	attention	NOUN
fcis-12818	36	3	mechanism	mechanism	NOUN
fcis-12818	36	4	of	of	ADP
fcis-12818	36	5	mobile	mobile	ADJ
fcis-12818	36	6	network	network	NOUN
fcis-12818	36	7	is	be	AUX
fcis-12818	36	8	introduced	introduce	VERB
fcis-12818	36	9	,	,	PUNCT
fcis-12818	36	10	the	the	DET
fcis-12818	36	11	model	model	NOUN
fcis-12818	36	12	complexity	complexity	NOUN
fcis-12818	36	13	is	be	AUX
fcis-12818	36	14	low	low	ADJ
fcis-12818	36	15	,	,	PUNCT
fcis-12818	36	16	and	and	CCONJ
fcis-12818	36	17	the	the	DET
fcis-12818	36	18	model	model	NOUN
fcis-12818	36	19	detection	detection	NOUN
fcis-12818	36	20	effect	effect	NOUN
fcis-12818	36	21	is	be	AUX
fcis-12818	36	22	greatly	greatly	ADV
fcis-12818	36	23	improved	improve	VERB
fcis-12818	36	24	.	.	PUNCT
fcis-12818	37	1	the	the	DET
fcis-12818	37	2	iou	iou	NOUN
fcis-12818	37	3	(	(	PUNCT
fcis-12818	37	4	intersection	intersection	NOUN
fcis-12818	37	5	over	over	ADP
fcis-12818	37	6	union	union	NOUN
fcis-12818	37	7	loss	loss	NOUN
fcis-12818	37	8	,	,	PUNCT
fcis-12818	37	9	iou	iou	NOUN
fcis-12818	37	10	)	)	PUNCT
fcis-12818	37	11	loss	loss	NOUN
fcis-12818	37	12	of	of	ADP
fcis-12818	37	13	the	the	DET
fcis-12818	37	14	original	original	ADJ
fcis-12818	37	15	yolo	yolo	ADJ
fcis-12818	37	16	model	model	NOUN
fcis-12818	37	17	directly	directly	ADV
fcis-12818	37	18	uses	use	VERB
fcis-12818	37	19	the	the	DET
fcis-12818	37	20	iou	iou	NOUN
fcis-12818	37	21	value	value	NOUN
fcis-12818	37	22	between	between	ADP
fcis-12818	37	23	the	the	DET
fcis-12818	37	24	predicted	predict	VERB
fcis-12818	37	25	bounding	bounding	NOUN
fcis-12818	37	26	box	box	NOUN
fcis-12818	37	27	and	and	CCONJ
fcis-12818	37	28	the	the	DET
fcis-12818	37	29	real	real	ADJ
fcis-12818	37	30	bounding	bounding	NOUN
fcis-12818	37	31	box	box	NOUN
fcis-12818	37	32	as	as	ADP
fcis-12818	37	33	the	the	DET
fcis-12818	37	34	loss	loss	NOUN
fcis-12818	37	35	[	[	X
fcis-12818	37	36	18	18	NUM
fcis-12818	37	37	]	]	PUNCT
fcis-12818	37	38	,	,	PUNCT
fcis-12818	37	39	but	but	CCONJ
fcis-12818	37	40	the	the	DET
fcis-12818	37	41	gradient	gradient	NOUN
fcis-12818	37	42	of	of	ADP
fcis-12818	37	43	the	the	DET
fcis-12818	37	44	loss	loss	NOUN
fcis-12818	37	45	function	function	NOUN
fcis-12818	37	46	is	be	AUX
fcis-12818	37	47	small	small	ADJ
fcis-12818	37	48	and	and	CCONJ
fcis-12818	37	49	can	can	AUX
fcis-12818	37	50	not	not	PART
fcis-12818	37	51	accurately	accurately	ADV
fcis-12818	37	52	reflect	reflect	VERB
fcis-12818	37	53	the	the	DET
fcis-12818	37	54	coincidence	coincidence	NOUN
fcis-12818	37	55	of	of	ADP
fcis-12818	37	56	the	the	DET
fcis-12818	37	57	two	two	NUM
fcis-12818	37	58	boxes	box	NOUN
fcis-12818	37	59	.	.	PUNCT
fcis-12818	38	1	therefore	therefore	ADV
fcis-12818	38	2	,	,	PUNCT
fcis-12818	38	3	it	it	PRON
fcis-12818	38	4	is	be	AUX
fcis-12818	38	5	proposed	propose	VERB
fcis-12818	38	6	to	to	PART
fcis-12818	38	7	introduce	introduce	VERB
fcis-12818	38	8	eiou	eiou	NOUN
fcis-12818	38	9	(	(	PUNCT
fcis-12818	38	10	efficient	efficient	ADJ
fcis-12818	38	11	intersection	intersection	NOUN
fcis-12818	38	12	over	over	ADP
fcis-12818	38	13	union	union	NOUN
fcis-12818	38	14	loss	loss	NOUN
fcis-12818	38	15	,	,	PUNCT
fcis-12818	38	16	eiou	eiou	NOUN
fcis-12818	38	17	)	)	PUNCT
fcis-12818	38	18	,	,	PUNCT
fcis-12818	38	19	replace	replace	VERB
fcis-12818	38	20	the	the	DET
fcis-12818	38	21	aspect	aspect	NOUN
fcis-12818	38	22	ratio	ratio	NOUN
fcis-12818	38	23	with	with	ADP
fcis-12818	38	24	the	the	DET
fcis-12818	38	25	width	width	ADJ
fcis-12818	38	26	and	and	CCONJ
fcis-12818	38	27	height	height	NOUN
fcis-12818	38	28	difference	difference	NOUN
fcis-12818	38	29	value	value	NOUN
fcis-12818	38	30	on	on	ADP
fcis-12818	38	31	the	the	DET
fcis-12818	38	32	basis	basis	NOUN
fcis-12818	38	33	of	of	ADP
fcis-12818	38	34	ciou	ciou	NOUN
fcis-12818	38	35	,	,	PUNCT
fcis-12818	38	36	focal	focal	ADJ
fcis-12818	38	37	loss	loss	NOUN
fcis-12818	38	38	solves	solve	VERB
fcis-12818	38	39	the	the	DET
fcis-12818	38	40	problem	problem	NOUN
fcis-12818	38	41	of	of	ADP
fcis-12818	38	42	unbalanced	unbalanced	ADJ
fcis-12818	38	43	difficult	difficult	ADJ
fcis-12818	38	44	samples	sample	NOUN
fcis-12818	38	45	,	,	PUNCT
fcis-12818	38	46	and	and	CCONJ
fcis-12818	38	47	greatly	greatly	ADV
fcis-12818	38	48	improves	improve	VERB
fcis-12818	38	49	the	the	DET
fcis-12818	38	50	accuracy	accuracy	NOUN
fcis-12818	38	51	of	of	ADP
fcis-12818	38	52	detecting	detect	VERB
fcis-12818	38	53	surface	surface	NOUN
fcis-12818	38	54	defects	defect	NOUN
fcis-12818	38	55	of	of	ADP
fcis-12818	38	56	industrial	industrial	ADJ
fcis-12818	38	57	products	product	NOUN
fcis-12818	38	58	.	.	PUNCT
fcis-12818	39	1	82	82	NUM
fcis-12818	39	2	image	image	NOUN
fcis-12818	39	3	640	640	NUM
fcis-12818	39	4	*	*	SYM
fcis-12818	39	5	640	640	NUM
fcis-12818	39	6	*	*	SYM
fcis-12818	39	7	3	3	NUM
fcis-12818	39	8	backbone	backbone	NOUN
fcis-12818	39	9	neck	neck	NOUN
fcis-12818	39	10	head	head	NOUN
fcis-12818	39	11	0	0	NUM
fcis-12818	39	12	1	1	NUM
fcis-12818	39	13	conv	conv	PROPN
fcis-12818	39	14	k6,s2,p2,c64	k6,s2,p2,c64	PROPN
fcis-12818	39	15	conv	conv	NOUN
fcis-12818	39	16	k3,s2,p1,c128	k3,s2,p1,c128	NOUN
fcis-12818	39	17	2	2	NUM
fcis-12818	39	18	c3	c3	NOUN
fcis-12818	39	19	c128	c128	PROPN
fcis-12818	39	20	3	3	NUM
fcis-12818	39	21	conv	conv	PROPN
fcis-12818	39	22	k3,s2,p1,c256	k3,s2,p1,c256	X
fcis-12818	39	23	c34	c34	NOUN
fcis-12818	39	24	c256	c256	PROPN
fcis-12818	39	25	5	5	NUM
fcis-12818	39	26	conv	conv	NOUN
fcis-12818	39	27	k3,s2,p1,c512	k3,s2,p1,c512	PROPN
fcis-12818	39	28	6	6	NUM
fcis-12818	39	29	c3	c3	NOUN
fcis-12818	39	30	c512	c512	PROPN
fcis-12818	39	31	7	7	NUM
fcis-12818	39	32	conv	conv	NOUN
fcis-12818	39	33	k3,s2,p1,c1024	k3,s2,p1,c1024	PROPN
fcis-12818	39	34	8	8	NUM
fcis-12818	39	35	c3	c3	NOUN
fcis-12818	39	36	c1024	c1024	PROPN
fcis-12818	39	37	9	9	NUM
fcis-12818	39	38	sppf	sppf	NOUN
fcis-12818	39	39	k5,c1024	k5,c1024	NUM
fcis-12818	39	40	10	10	NUM
fcis-12818	39	41	conv	conv	ADJ
fcis-12818	39	42	k3,s2,p1,c512	k3,s2,p1,c512	PROPN
fcis-12818	39	43	11	11	NUM
fcis-12818	39	44	upsample	upsample	NOUN
fcis-12818	39	45	concat	concat	NOUN
fcis-12818	39	46	12	12	NUM
fcis-12818	39	47	c3	c3	NOUN
fcis-12818	39	48	c512	c512	PROPN
fcis-12818	39	49	13	13	NUM
fcis-12818	39	50	conv	conv	NOUN
fcis-12818	39	51	k3,s2,p1,c256	k3,s2,p1,c256	PROPN
fcis-12818	39	52	14	14	NUM
fcis-12818	39	53	15	15	NUM
fcis-12818	39	54	upsample	upsample	NOUN
fcis-12818	39	55	concat	concat	NOUN
fcis-12818	39	56	16	16	NUM
fcis-12818	39	57	c3	c3	PROPN
fcis-12818	39	58	c256	c256	PROPN
fcis-12818	39	59	17	17	NUM
fcis-12818	39	60	conv	conv	PROPN
fcis-12818	39	61	k3,s2,p1,c256	k3,s2,p1,c256	PROPN
fcis-12818	39	62	concat	concat	PROPN
fcis-12818	39	63	19	19	NUM
fcis-12818	39	64	c3	c3	NOUN
fcis-12818	39	65	c512	c512	PROPN
fcis-12818	39	66	20	20	NUM
fcis-12818	39	67	conv	conv	PROPN
fcis-12818	39	68	k3,s2,p1,c512	k3,s2,p1,c512	PROPN
fcis-12818	39	69	concat	concat	PROPN
fcis-12818	39	70	22	22	NUM
fcis-12818	39	71	c3	c3	PROPN
fcis-12818	39	72	c1024	c1024	PROPN
fcis-12818	39	73	23	23	NUM
fcis-12818	39	74	18	18	NUM
fcis-12818	39	75	21	21	NUM
fcis-12818	39	76	c3	c3	PROPN
fcis-12818	39	77	c256	c256	PROPN
fcis-12818	40	1	c3	c3	PROPN
fcis-12818	40	2	c512	c512	PROPN
fcis-12818	41	1	c3	c3	PROPN
fcis-12818	41	2	c512	c512	PROPN
fcis-12818	41	3	c3	c3	PROPN
fcis-12818	41	4	c1024	c1024	PROPN
fcis-12818	41	5	se	se	PROPN
fcis-12818	41	6	fig	fig	NOUN
fcis-12818	41	7	1	1	NUM
fcis-12818	41	8	.	.	PUNCT
fcis-12818	41	9	improved	improve	VERB
fcis-12818	41	10	yolov5s	yolov5s	PROPN
fcis-12818	41	11	network	network	NOUN
fcis-12818	41	12	structure	structure	NOUN
fcis-12818	41	13	2.1	2.1	NUM
fcis-12818	41	14	.	.	PUNCT
fcis-12818	42	1	introduction	introduction	NOUN
fcis-12818	42	2	of	of	ADP
fcis-12818	42	3	the	the	DET
fcis-12818	42	4	se	se	PROPN
fcis-12818	42	5	attention	attention	NOUN
fcis-12818	42	6	mechanism	mechanism	NOUN
fcis-12818	42	7	in	in	ADP
fcis-12818	42	8	traditional	traditional	ADJ
fcis-12818	42	9	cnn	cnn	PROPN
fcis-12818	42	10	architectures	architecture	NOUN
fcis-12818	42	11	,	,	PUNCT
fcis-12818	42	12	convolutional	convolutional	ADJ
fcis-12818	42	13	layers	layer	NOUN
fcis-12818	42	14	and	and	CCONJ
fcis-12818	42	15	pooling	pool	VERB
fcis-12818	42	16	layers	layer	NOUN
fcis-12818	42	17	are	be	AUX
fcis-12818	42	18	usually	usually	ADV
fcis-12818	42	19	used	use	VERB
fcis-12818	42	20	to	to	PART
fcis-12818	42	21	extract	extract	VERB
fcis-12818	42	22	image	image	NOUN
fcis-12818	42	23	features	feature	NOUN
fcis-12818	42	24	.	.	PUNCT
fcis-12818	43	1	however	however	ADV
fcis-12818	43	2	,	,	PUNCT
fcis-12818	43	3	this	this	DET
fcis-12818	43	4	approach	approach	NOUN
fcis-12818	43	5	does	do	AUX
fcis-12818	43	6	not	not	PART
fcis-12818	43	7	explicitly	explicitly	ADV
fcis-12818	43	8	model	model	VERB
fcis-12818	43	9	the	the	DET
fcis-12818	43	10	relationships	relationship	NOUN
fcis-12818	43	11	between	between	ADP
fcis-12818	43	12	feature	feature	NOUN
fcis-12818	43	13	channels	channel	NOUN
fcis-12818	43	14	,	,	PUNCT
fcis-12818	43	15	resulting	result	VERB
fcis-12818	43	16	in	in	ADP
fcis-12818	43	17	some	some	DET
fcis-12818	43	18	channels	channel	NOUN
fcis-12818	43	19	contributing	contribute	VERB
fcis-12818	43	20	relatively	relatively	ADV
fcis-12818	43	21	little	little	ADJ
fcis-12818	43	22	to	to	ADP
fcis-12818	43	23	a	a	DET
fcis-12818	43	24	particular	particular	ADJ
fcis-12818	43	25	task	task	NOUN
fcis-12818	43	26	,	,	PUNCT
fcis-12818	43	27	while	while	SCONJ
fcis-12818	43	28	others	other	NOUN
fcis-12818	43	29	are	be	AUX
fcis-12818	43	30	more	more	ADV
fcis-12818	43	31	important	important	ADJ
fcis-12818	43	32	.	.	PUNCT
fcis-12818	44	1	the	the	DET
fcis-12818	44	2	se	se	PROPN
fcis-12818	44	3	module	module	NOUN
fcis-12818	44	4	is	be	AUX
fcis-12818	44	5	designed	design	VERB
fcis-12818	44	6	to	to	PART
fcis-12818	44	7	solve	solve	VERB
fcis-12818	44	8	this	this	DET
fcis-12818	44	9	problem	problem	NOUN
fcis-12818	44	10	.	.	PUNCT
fcis-12818	45	1	the	the	DET
fcis-12818	45	2	pooling	pooling	NOUN
fcis-12818	45	3	process	process	NOUN
fcis-12818	45	4	of	of	ADP
fcis-12818	45	5	the	the	DET
fcis-12818	45	6	se	se	PROPN
fcis-12818	45	7	attention	attention	NOUN
fcis-12818	45	8	mechanism	mechanism	NOUN
fcis-12818	45	9	is	be	AUX
fcis-12818	45	10	shown	show	VERB
fcis-12818	45	11	in	in	ADP
fcis-12818	45	12	fig	fig	NOUN
fcis-12818	45	13	.	.	PUNCT
fcis-12818	46	1	2	2	X
fcis-12818	46	2	.	.	X
fcis-12818	46	3	the	the	DET
fcis-12818	46	4	se	se	PROPN
fcis-12818	46	5	module	module	NOUN
fcis-12818	46	6	models	model	NOUN
fcis-12818	46	7	the	the	DET
fcis-12818	46	8	relationship	relationship	NOUN
fcis-12818	46	9	between	between	ADP
fcis-12818	46	10	channels	channel	NOUN
fcis-12818	46	11	by	by	ADP
fcis-12818	46	12	introducing	introduce	VERB
fcis-12818	46	13	a	a	DET
fcis-12818	46	14	squeeze	squeeze	NOUN
fcis-12818	46	15	action	action	NOUN
fcis-12818	46	16	and	and	CCONJ
fcis-12818	46	17	an	an	DET
fcis-12818	46	18	excitation	excitation	NOUN
fcis-12818	46	19	operation	operation	NOUN
fcis-12818	46	20	.	.	PUNCT
fcis-12818	47	1	in	in	ADP
fcis-12818	47	2	the	the	DET
fcis-12818	47	3	squeeze	squeeze	NOUN
fcis-12818	47	4	phase	phase	NOUN
fcis-12818	47	5	,	,	PUNCT
fcis-12818	47	6	it	it	PRON
fcis-12818	47	7	compresses	compress	VERB
fcis-12818	47	8	the	the	DET
fcis-12818	47	9	output	output	NOUN
fcis-12818	47	10	feature	feature	NOUN
fcis-12818	47	11	map	map	NOUN
fcis-12818	47	12	of	of	ADP
fcis-12818	47	13	the	the	DET
fcis-12818	47	14	convolutional	convolutional	ADJ
fcis-12818	47	15	layer	layer	NOUN
fcis-12818	47	16	into	into	ADP
fcis-12818	47	17	a	a	DET
fcis-12818	47	18	feature	feature	NOUN
fcis-12818	47	19	vector	vector	NOUN
fcis-12818	47	20	through	through	ADP
fcis-12818	47	21	the	the	DET
fcis-12818	47	22	global	global	ADJ
fcis-12818	47	23	average	average	ADJ
fcis-12818	47	24	pooling	pool	VERB
fcis-12818	47	25	operation	operation	NOUN
fcis-12818	47	26	.	.	PUNCT
fcis-12818	48	1	then	then	ADV
fcis-12818	48	2	,	,	PUNCT
fcis-12818	48	3	in	in	ADP
fcis-12818	48	4	the	the	DET
fcis-12818	48	5	excitation	excitation	NOUN
fcis-12818	48	6	phase	phase	NOUN
fcis-12818	48	7	,	,	PUNCT
fcis-12818	48	8	by	by	ADP
fcis-12818	48	9	using	use	VERB
fcis-12818	48	10	fully	fully	ADV
fcis-12818	48	11	connected	connected	ADJ
fcis-12818	48	12	layers	layer	NOUN
fcis-12818	48	13	and	and	CCONJ
fcis-12818	48	14	nonlinear	nonlinear	ADJ
fcis-12818	48	15	activation	activation	NOUN
fcis-12818	48	16	functions	function	NOUN
fcis-12818	48	17	,	,	PUNCT
fcis-12818	48	18	learn	learn	VERB
fcis-12818	48	19	to	to	PART
fcis-12818	48	20	generate	generate	VERB
fcis-12818	48	21	a	a	DET
fcis-12818	48	22	weight	weight	NOUN
fcis-12818	48	23	vector	vector	NOUN
fcis-12818	48	24	for	for	ADP
fcis-12818	48	25	a	a	DET
fcis-12818	48	26	channel	channel	NOUN
fcis-12818	48	27	.	.	PUNCT
fcis-12818	49	1	this	this	DET
fcis-12818	49	2	weight	weight	NOUN
fcis-12818	49	3	vector	vector	NOUN
fcis-12818	49	4	is	be	AUX
fcis-12818	49	5	applied	apply	VERB
fcis-12818	49	6	to	to	ADP
fcis-12818	49	7	each	each	DET
fcis-12818	49	8	channel	channel	NOUN
fcis-12818	49	9	on	on	ADP
fcis-12818	49	10	the	the	DET
fcis-12818	49	11	original	original	ADJ
fcis-12818	49	12	feature	feature	NOUN
fcis-12818	49	13	map	map	NOUN
fcis-12818	49	14	to	to	PART
fcis-12818	49	15	weight	weight	VERB
fcis-12818	49	16	the	the	DET
fcis-12818	49	17	features	feature	NOUN
fcis-12818	49	18	of	of	ADP
fcis-12818	49	19	the	the	DET
fcis-12818	49	20	different	different	ADJ
fcis-12818	49	21	channels	channel	NOUN
fcis-12818	49	22	.	.	PUNCT
fcis-12818	50	1	the	the	DET
fcis-12818	50	2	se	se	PROPN
fcis-12818	50	3	attention	attention	NOUN
fcis-12818	50	4	mechanism	mechanism	NOUN
fcis-12818	50	5	helps	help	VERB
fcis-12818	50	6	the	the	DET
fcis-12818	50	7	network	network	NOUN
fcis-12818	50	8	to	to	PART
fcis-12818	50	9	better	well	ADV
fcis-12818	50	10	focus	focus	VERB
fcis-12818	50	11	on	on	ADP
fcis-12818	50	12	important	important	ADJ
fcis-12818	50	13	feature	feature	NOUN
fcis-12818	50	14	channels	channel	NOUN
fcis-12818	50	15	,	,	PUNCT
fcis-12818	50	16	thereby	thereby	ADV
fcis-12818	50	17	improving	improve	VERB
fcis-12818	50	18	model	model	NOUN
fcis-12818	50	19	performance	performance	NOUN
fcis-12818	50	20	.	.	PUNCT
fcis-12818	51	1	squeeze	squeeze	NOUN
fcis-12818	51	2	-	-	PUNCT
fcis-12818	51	3	and	and	CCONJ
fcis-12818	51	4	-	-	PUNCT
fcis-12818	51	5	excitation	excitation	NOUN
fcis-12818	51	6	module	module	NOUN
fcis-12818	51	7	shrinking	shrink	VERB
fcis-12818	51	8	feature	feature	NOUN
fcis-12818	51	9	maps∈	maps∈	ADJ
fcis-12818	51	10	rwxhxc2	rwxhxc2	NOUN
fcis-12818	51	11	through	through	ADP
fcis-12818	51	12	spatial	spatial	ADJ
fcis-12818	51	13	dimensions	dimension	NOUN
fcis-12818	51	14	(	(	PUNCT
fcis-12818	51	15	w	w	NOUN
fcis-12818	51	16	x	x	SYM
fcis-12818	51	17	h	h	NOUN
fcis-12818	51	18	)	)	PUNCT
fcis-12818	51	19	global	global	ADJ
fcis-12818	51	20	distribution	distribution	NOUN
fcis-12818	51	21	of	of	ADP
fcis-12818	51	22	channelwise	channelwise	NOUN
fcis-12818	51	23	responses	response	NOUN
fcis-12818	51	24	squeeze	squeeze	NOUN
fcis-12818	51	25	learning	learn	VERB
fcis-12818	51	26	w	w	PROPN
fcis-12818	51	27	∈rc2xc2	∈rc2xc2	PROPN
fcis-12818	51	28	to	to	PART
fcis-12818	51	29	explicitly	explicitly	ADV
fcis-12818	51	30	model	model	VERB
fcis-12818	51	31	channel	channel	PROPN
fcis-12818	51	32	-	-	PUNCT
fcis-12818	51	33	association	association	NOUN
fcis-12818	51	34	gating	gate	VERB
fcis-12818	51	35	mechanism	mechanism	NOUN
fcis-12818	51	36	to	to	PART
fcis-12818	51	37	produce	produce	VERB
fcis-12818	51	38	channel	channel	NOUN
fcis-12818	51	39	-	-	PUNCT
fcis-12818	51	40	wise	wise	ADJ
fcis-12818	51	41	weights	weight	NOUN
fcis-12818	51	42	reweighting	reweighte	VERB
fcis-12818	51	43	the	the	DET
fcis-12818	51	44	feature	feature	NOUN
fcis-12818	51	45	maps∈rwxhxc2	maps∈rwxhxc2	PROPN
fcis-12818	51	46	excitation	excitation	NOUN
fcis-12818	51	47	scale	scale	NOUN
fcis-12818	51	48	fig	fig	NOUN
fcis-12818	51	49	2	2	NUM
fcis-12818	51	50	.	.	PUNCT
fcis-12818	51	51	se	se	ADJ
fcis-12818	51	52	attention	attention	NOUN
fcis-12818	51	53	mechanism	mechanism	NOUN
fcis-12818	51	54	2.2	2.2	NUM
fcis-12818	51	55	.	.	PUNCT
fcis-12818	51	56	eiou	eiou	NOUN
fcis-12818	51	57	because	because	SCONJ
fcis-12818	51	58	the	the	DET
fcis-12818	51	59	aspect	aspect	NOUN
fcis-12818	51	60	ratio	ratio	NOUN
fcis-12818	51	61	of	of	ADP
fcis-12818	51	62	the	the	DET
fcis-12818	51	63	ciou	ciou	NOUN
fcis-12818	51	64	loss	loss	NOUN
fcis-12818	51	65	prediction	prediction	NOUN
fcis-12818	51	66	box	box	NOUN
fcis-12818	51	67	and	and	CCONJ
fcis-12818	51	68	the	the	DET
fcis-12818	51	69	gt	gt	PROPN
fcis-12818	51	70	box	box	PROPN
fcis-12818	51	71	is	be	AUX
fcis-12818	51	72	linearly	linearly	ADV
fcis-12818	51	73	scaled	scale	VERB
fcis-12818	51	74	,	,	PUNCT
fcis-12818	51	75	it	it	PRON
fcis-12818	51	76	will	will	AUX
fcis-12818	51	77	hinder	hinder	VERB
fcis-12818	51	78	the	the	DET
fcis-12818	51	79	effective	effective	ADJ
fcis-12818	51	80	optimization	optimization	NOUN
fcis-12818	51	81	similarity	similarity	NOUN
fcis-12818	51	82	of	of	ADP
fcis-12818	51	83	the	the	DET
fcis-12818	51	84	model	model	NOUN
fcis-12818	51	85	.	.	PUNCT
fcis-12818	52	1	it	it	PRON
fcis-12818	52	2	is	be	AUX
fcis-12818	52	3	proposed	propose	VERB
fcis-12818	52	4	to	to	PART
fcis-12818	52	5	introduce	introduce	VERB
fcis-12818	52	6	eiou	eiou	NOUN
fcis-12818	52	7	in	in	ADP
fcis-12818	52	8	the	the	DET
fcis-12818	52	9	original	original	ADJ
fcis-12818	52	10	yolov5s	yolov5s	PROPN
fcis-12818	52	11	model	model	NOUN
fcis-12818	52	12	.	.	PUNCT
fcis-12818	53	1	the	the	DET
fcis-12818	53	2	influence	influence	NOUN
fcis-12818	53	3	factor	factor	NOUN
fcis-12818	53	4	of	of	ADP
fcis-12818	53	5	the	the	DET
fcis-12818	53	6	aspect	aspect	NOUN
fcis-12818	53	7	ratio	ratio	NOUN
fcis-12818	53	8	of	of	ADP
fcis-12818	53	9	the	the	DET
fcis-12818	53	10	prediction	prediction	NOUN
fcis-12818	53	11	box	box	NOUN
fcis-12818	53	12	and	and	CCONJ
fcis-12818	53	13	the	the	DET
fcis-12818	53	14	real	real	ADJ
fcis-12818	53	15	box	box	NOUN
fcis-12818	53	16	is	be	AUX
fcis-12818	53	17	separated	separate	VERB
fcis-12818	53	18	,	,	PUNCT
fcis-12818	53	19	and	and	CCONJ
fcis-12818	53	20	the	the	DET
fcis-12818	53	21	length	length	NOUN
fcis-12818	53	22	and	and	CCONJ
fcis-12818	53	23	width	width	ADJ
fcis-12818	53	24	information	information	NOUN
fcis-12818	53	25	of	of	ADP
fcis-12818	53	26	the	the	DET
fcis-12818	53	27	target	target	NOUN
fcis-12818	53	28	box	box	NOUN
fcis-12818	53	29	and	and	CCONJ
fcis-12818	53	30	focal	focal	ADJ
fcis-12818	53	31	focus	focus	NOUN
fcis-12818	53	32	prediction	prediction	NOUN
fcis-12818	53	33	box	box	NOUN
fcis-12818	53	34	are	be	AUX
fcis-12818	53	35	added	add	VERB
fcis-12818	53	36	.	.	PUNCT
fcis-12818	54	1	the	the	DET
fcis-12818	54	2	length	length	NOUN
fcis-12818	54	3	and	and	CCONJ
fcis-12818	54	4	width	width	NOUN
fcis-12818	54	5	of	of	ADP
fcis-12818	54	6	the	the	DET
fcis-12818	54	7	prediction	prediction	NOUN
fcis-12818	54	8	box	box	NOUN
fcis-12818	54	9	and	and	CCONJ
fcis-12818	54	10	the	the	DET
fcis-12818	54	11	real	real	ADJ
fcis-12818	54	12	box	box	NOUN
fcis-12818	54	13	are	be	AUX
fcis-12818	54	14	calculated	calculate	VERB
fcis-12818	54	15	respectively	respectively	ADV
fcis-12818	54	16	to	to	PART
fcis-12818	54	17	solve	solve	VERB
fcis-12818	54	18	the	the	DET
fcis-12818	54	19	problem	problem	NOUN
fcis-12818	54	20	of	of	ADP
fcis-12818	54	21	penalty	penalty	NOUN
fcis-12818	54	22	failure	failure	NOUN
fcis-12818	54	23	in	in	ADP
fcis-12818	54	24	the	the	DET
fcis-12818	54	25	proportional	proportional	ADJ
fcis-12818	54	26	change	change	NOUN
fcis-12818	54	27	of	of	ADP
fcis-12818	54	28	aspect	aspect	NOUN
fcis-12818	54	29	ratio	ratio	NOUN
fcis-12818	54	30	in	in	ADP
fcis-12818	54	31	ciou	ciou	NOUN
fcis-12818	54	32	.	.	PUNCT
fcis-12818	55	1	the	the	DET
fcis-12818	55	2	regression	regression	NOUN
fcis-12818	55	3	process	process	NOUN
fcis-12818	55	4	focuses	focus	VERB
fcis-12818	55	5	on	on	ADP
fcis-12818	55	6	high	high	ADJ
fcis-12818	55	7	-	-	PUNCT
fcis-12818	55	8	quality	quality	NOUN
fcis-12818	55	9	anchor	anchor	NOUN
fcis-12818	55	10	frames	frame	NOUN
fcis-12818	55	11	,	,	PUNCT
fcis-12818	55	12	which	which	PRON
fcis-12818	55	13	solve	solve	VERB
fcis-12818	55	14	the	the	DET
fcis-12818	55	15	problems	problem	NOUN
fcis-12818	55	16	of	of	ADP
fcis-12818	55	17	sample	sample	NOUN
fcis-12818	55	18	imbalance	imbalance	NOUN
fcis-12818	55	19	,	,	PUNCT
fcis-12818	55	20	slow	slow	ADJ
fcis-12818	55	21	model	model	NOUN
fcis-12818	55	22	convergence	convergence	NOUN
fcis-12818	55	23	,	,	PUNCT
fcis-12818	55	24	and	and	CCONJ
fcis-12818	55	25	imprecision	imprecision	NOUN
fcis-12818	55	26	.	.	PUNCT
fcis-12818	56	1	at	at	ADP
fcis-12818	56	2	the	the	DET
fcis-12818	56	3	same	same	ADJ
fcis-12818	56	4	time	time	NOUN
fcis-12818	56	5	,	,	PUNCT
fcis-12818	56	6	the	the	DET
fcis-12818	56	7	prediction	prediction	NOUN
fcis-12818	56	8	box	box	NOUN
fcis-12818	56	9	regression	regression	NOUN
fcis-12818	56	10	accuracy	accuracy	NOUN
fcis-12818	56	11	is	be	AUX
fcis-12818	56	12	improved	improve	VERB
fcis-12818	56	13	.	.	PUNCT
fcis-12818	57	1	3	3	X
fcis-12818	57	2	.	.	X
fcis-12818	57	3	result	result	VERB
fcis-12818	57	4	3.1	3.1	NUM
fcis-12818	57	5	.	.	PUNCT
fcis-12818	57	6	dataset	dataset	NOUN
fcis-12818	57	7	and	and	CCONJ
fcis-12818	57	8	experiment	experiment	NOUN
fcis-12818	57	9	environment	environment	NOUN
fcis-12818	57	10	configuration	configuration	NOUN
fcis-12818	57	11	the	the	DET
fcis-12818	57	12	dataset	dataset	NOUN
fcis-12818	57	13	discloses	disclose	VERB
fcis-12818	57	14	the	the	DET
fcis-12818	57	15	steel	steel	NOUN
fcis-12818	57	16	surface	surface	NOUN
fcis-12818	57	17	defect	defect	NOUN
fcis-12818	57	18	dataset	dataset	VERB
fcis-12818	57	19	neudet	neudet	NOUN
fcis-12818	57	20	dataset	dataset	NOUN
fcis-12818	57	21	practice	practice	NOUN
fcis-12818	57	22	.	.	PUNCT
fcis-12818	58	1	the	the	DET
fcis-12818	58	2	original	original	ADJ
fcis-12818	58	3	data	datum	NOUN
fcis-12818	58	4	has	have	VERB
fcis-12818	58	5	a	a	DET
fcis-12818	58	6	total	total	NOUN
fcis-12818	58	7	of	of	ADP
fcis-12818	58	8	5404	5404	NUM
fcis-12818	58	9	images	image	NOUN
fcis-12818	58	10	,	,	PUNCT
fcis-12818	58	11	and	and	CCONJ
fcis-12818	58	12	there	there	PRON
fcis-12818	58	13	are	be	VERB
fcis-12818	58	14	only	only	ADV
fcis-12818	58	15	30	30	NUM
fcis-12818	58	16	verification	verification	NOUN
fcis-12818	58	17	images	image	NOUN
fcis-12818	58	18	in	in	ADP
fcis-12818	58	19	the	the	DET
fcis-12818	58	20	original	original	ADJ
fcis-12818	58	21	data	datum	NOUN
fcis-12818	58	22	verification	verification	NOUN
fcis-12818	58	23	set	set	NOUN
fcis-12818	58	24	file	file	NOUN
fcis-12818	58	25	.	.	PUNCT
fcis-12818	59	1	to	to	PART
fcis-12818	59	2	improve	improve	VERB
fcis-12818	59	3	the	the	DET
fcis-12818	59	4	accuracy	accuracy	NOUN
fcis-12818	59	5	of	of	ADP
fcis-12818	59	6	test	test	NOUN
fcis-12818	59	7	recall	recall	NOUN
fcis-12818	59	8	,	,	PUNCT
fcis-12818	59	9	validation	validation	NOUN
fcis-12818	59	10	set	set	NOUN
fcis-12818	59	11	preprocessing	preprocessing	NOUN
fcis-12818	59	12	in	in	ADP
fcis-12818	59	13	the	the	DET
fcis-12818	59	14	original	original	ADJ
fcis-12818	59	15	data	datum	NOUN
fcis-12818	59	16	is	be	AUX
fcis-12818	59	17	performed	perform	VERB
fcis-12818	59	18	first	first	ADV
fcis-12818	59	19	.	.	PUNCT
fcis-12818	60	1	enrich	enrich	VERB
fcis-12818	60	2	the	the	DET
fcis-12818	60	3	validation	validation	NOUN
fcis-12818	60	4	set	set	VERB
fcis-12818	60	5	file	file	NOUN
fcis-12818	60	6	image	image	NOUN
fcis-12818	60	7	and	and	CCONJ
fcis-12818	60	8	tags	tag	NOUN
fcis-12818	60	9	.	.	PUNCT
fcis-12818	61	1	80	80	NUM
fcis-12818	61	2	%	%	NOUN
fcis-12818	61	3	of	of	ADP
fcis-12818	61	4	the	the	DET
fcis-12818	61	5	original	original	ADJ
fcis-12818	61	6	data	datum	NOUN
fcis-12818	61	7	is	be	AUX
fcis-12818	61	8	used	use	VERB
fcis-12818	61	9	for	for	ADP
fcis-12818	61	10	training	training	NOUN
fcis-12818	61	11	,	,	PUNCT
fcis-12818	61	12	10	10	NUM
fcis-12818	61	13	%	%	NOUN
fcis-12818	61	14	for	for	ADP
fcis-12818	61	15	validation	validation	NOUN
fcis-12818	61	16	,	,	PUNCT
fcis-12818	61	17	and	and	CCONJ
fcis-12818	61	18	10	10	NUM
fcis-12818	61	19	%	%	NOUN
fcis-12818	61	20	for	for	ADP
fcis-12818	61	21	testing	testing	NOUN
fcis-12818	61	22	.	.	PUNCT
fcis-12818	62	1	tab	tab	NOUN
fcis-12818	62	2	.	.	PUNCT
fcis-12818	63	1	1	1	NUM
fcis-12818	63	2	describes	describe	VERB
fcis-12818	63	3	the	the	DET
fcis-12818	63	4	configuration	configuration	NOUN
fcis-12818	63	5	of	of	ADP
fcis-12818	63	6	the	the	DET
fcis-12818	63	7	experimental	experimental	ADJ
fcis-12818	63	8	environment	environment	NOUN
fcis-12818	63	9	.	.	PUNCT
fcis-12818	64	1	table	table	NOUN
fcis-12818	64	2	1	1	NUM
fcis-12818	64	3	.	.	PUNCT
fcis-12818	65	1	experimental	experimental	ADJ
fcis-12818	65	2	environment	environment	PROPN
fcis-12818	65	3	configuration	configuration	NOUN
fcis-12818	65	4	environment	environment	NOUN
fcis-12818	65	5	name	name	NOUN
fcis-12818	65	6	operation	operation	NOUN
fcis-12818	65	7	system	system	NOUN
fcis-12818	65	8	windows	window	VERB
fcis-12818	65	9	10	10	NUM
fcis-12818	65	10	cpu	cpu	NOUN
fcis-12818	65	11	lntel	lntel	NOUN
fcis-12818	65	12	(	(	PUNCT
fcis-12818	65	13	r	r	NOUN
fcis-12818	65	14	)	)	PUNCT
fcis-12818	65	15	core	core	NOUN
fcis-12818	65	16	(	(	PUNCT
fcis-12818	65	17	tm	tm	NOUN
fcis-12818	65	18	)	)	PUNCT
fcis-12818	65	19	i7	i7	ADJ
fcis-12818	65	20	-	-	PUNCT
fcis-12818	65	21	10700f	10700f	NOUN
fcis-12818	65	22	cpu	cpu	NOUN
fcis-12818	65	23	@2.90	@2.90	NOUN
fcis-12818	65	24	ghz	ghz	VERB
fcis-12818	65	25	gpu	gpu	PROPN
fcis-12818	65	26	nvidia	nvidia	PROPN
fcis-12818	65	27	geforce	geforce	NOUN
fcis-12818	65	28	rtx	rtx	PROPN
fcis-12818	65	29	2070	2070	NUM
fcis-12818	65	30	super	super	PROPN
fcis-12818	65	31	code	code	NOUN
fcis-12818	65	32	version	version	NOUN
fcis-12818	65	33	yolov5	yolov5	NOUN
fcis-12818	65	34	-	-	PUNCT
fcis-12818	65	35	6.0	6.0	NUM
fcis-12818	65	36	learning	learning	NOUN
fcis-12818	65	37	framework	framework	NOUN
fcis-12818	65	38	pytorch1.8.0	pytorch1.8.0	NOUN
fcis-12818	65	39	3.2	3.2	NUM
fcis-12818	65	40	.	.	PUNCT
fcis-12818	66	1	ablation	ablation	NOUN
fcis-12818	66	2	studies	study	NOUN
fcis-12818	66	3	ablation	ablation	NOUN
fcis-12818	66	4	experiments	experiment	NOUN
fcis-12818	66	5	were	be	AUX
fcis-12818	66	6	carried	carry	VERB
fcis-12818	66	7	out	out	ADP
fcis-12818	66	8	to	to	PART
fcis-12818	66	9	investigate	investigate	VERB
fcis-12818	66	10	the	the	DET
fcis-12818	66	11	feasibility	feasibility	NOUN
fcis-12818	66	12	of	of	ADP
fcis-12818	66	13	improving	improve	VERB
fcis-12818	66	14	the	the	DET
fcis-12818	66	15	model	model	NOUN
fcis-12818	66	16	based	base	VERB
fcis-12818	66	17	on	on	ADP
fcis-12818	66	18	average	average	ADJ
fcis-12818	66	19	pooled	pool	VERB
fcis-12818	66	20	yolov5s	yolov5s	PROPN
fcis-12818	66	21	object	object	NOUN
fcis-12818	66	22	detection	detection	NOUN
fcis-12818	66	23	.	.	PUNCT
fcis-12818	67	1	the	the	DET
fcis-12818	67	2	results	result	NOUN
fcis-12818	67	3	of	of	ADP
fcis-12818	67	4	different	different	ADJ
fcis-12818	67	5	83	83	NUM
fcis-12818	67	6	improvement	improvement	NOUN
fcis-12818	67	7	strategies	strategy	NOUN
fcis-12818	67	8	for	for	ADP
fcis-12818	67	9	ablation	ablation	NOUN
fcis-12818	67	10	experiments	experiment	NOUN
fcis-12818	67	11	are	be	AUX
fcis-12818	67	12	shown	show	VERB
fcis-12818	67	13	in	in	ADP
fcis-12818	67	14	tab	tab	NOUN
fcis-12818	67	15	.	.	PUNCT
fcis-12818	68	1	2	2	X
fcis-12818	68	2	.	.	X
fcis-12818	68	3	observe	observe	VERB
fcis-12818	68	4	the	the	DET
fcis-12818	68	5	experimental	experimental	ADJ
fcis-12818	68	6	data	datum	NOUN
fcis-12818	68	7	to	to	PART
fcis-12818	68	8	find	find	VERB
fcis-12818	68	9	an	an	DET
fcis-12818	68	10	improved	improved	ADJ
fcis-12818	68	11	object	object	NOUN
fcis-12818	68	12	detection	detection	NOUN
fcis-12818	68	13	network	network	NOUN
fcis-12818	68	14	model	model	NOUN
fcis-12818	68	15	through	through	ADP
fcis-12818	68	16	ablation	ablation	NOUN
fcis-12818	68	17	experiments	experiment	NOUN
fcis-12818	68	18	.	.	PUNCT
fcis-12818	69	1	table	table	NOUN
fcis-12818	69	2	2	2	NUM
fcis-12818	69	3	.	.	PUNCT
fcis-12818	69	4	comparison	comparison	NOUN
fcis-12818	69	5	of	of	ADP
fcis-12818	69	6	defect	defect	ADJ
fcis-12818	69	7	detection	detection	NOUN
fcis-12818	69	8	accuracy	accuracy	NOUN
fcis-12818	69	9	of	of	ADP
fcis-12818	69	10	different	different	ADJ
fcis-12818	69	11	improvement	improvement	NOUN
fcis-12818	69	12	strategies	strategy	NOUN
fcis-12818	69	13	model	model	NOUN
fcis-12818	69	14	+	+	PROPN
fcis-12818	69	15	se	se	X
fcis-12818	69	16	+	+	ADJ
fcis-12818	69	17	eiou	eiou	NOUN
fcis-12818	69	18	map@0.5	map@0.5	VERB
fcis-12818	69	19	(	(	PUNCT
fcis-12818	69	20	%	%	INTJ
fcis-12818	69	21	)	)	PUNCT
fcis-12818	69	22	fps	fps	PROPN
fcis-12818	69	23	primeval	primeval	NOUN
fcis-12818	69	24	yolov5s	yolov5s	PROPN
fcis-12818	69	25	74.4	74.4	NUM
fcis-12818	69	26	90	90	NUM
fcis-12818	69	27	yolov5s	yolov5s	NOUN
fcis-12818	69	28	-	-	PUNCT
fcis-12818	69	29	a	a	PRON
fcis-12818	69	30	√	√	NUM
fcis-12818	69	31	81.1（+6.7	81.1（+6.7	NUM
fcis-12818	69	32	）	）	NOUN
fcis-12818	69	33	103（+13	103（+13	NUM
fcis-12818	69	34	）	）	SYM
fcis-12818	69	35	yolov5s	yolov5s	PROPN
fcis-12818	69	36	-	-	PUNCT
fcis-12818	69	37	b	b	NOUN
fcis-12818	69	38	√	√	NUM
fcis-12818	69	39	80.8（+6.4	80.8（+6.4	NUM
fcis-12818	69	40	）	）	SYM
fcis-12818	70	1	101（+11	101（+11	NUM
fcis-12818	70	2	）	）	NOUN
fcis-12818	70	3	yolov5sour	yolov5sour	PRON
fcis-12818	70	4	√	√	ADJ
fcis-12818	70	5	√	√	NUM
fcis-12818	70	6	81.8（+7.4	81.8（+7.4	NUM
fcis-12818	70	7	）	）	NOUN
fcis-12818	70	8	99（+9	99（+9	NUM
fcis-12818	70	9	）	）	NOUN
fcis-12818	70	10	3.3	3.3	NUM
fcis-12818	70	11	.	.	PUNCT
fcis-12818	71	1	experimental	experimental	ADJ
fcis-12818	71	2	comparison	comparison	NOUN
fcis-12818	71	3	firstly	firstly	ADV
fcis-12818	71	4	,	,	PUNCT
fcis-12818	71	5	under	under	ADP
fcis-12818	71	6	the	the	DET
fcis-12818	71	7	condition	condition	NOUN
fcis-12818	71	8	of	of	ADP
fcis-12818	71	9	ensuring	ensure	VERB
fcis-12818	71	10	the	the	DET
fcis-12818	71	11	experimental	experimental	ADJ
fcis-12818	71	12	variables	variable	NOUN
fcis-12818	71	13	,	,	PUNCT
fcis-12818	71	14	a	a	DET
fcis-12818	71	15	comparative	comparative	ADJ
fcis-12818	71	16	experiment	experiment	NOUN
fcis-12818	71	17	of	of	ADP
fcis-12818	71	18	the	the	DET
fcis-12818	71	19	yolov7	yolov7	PROPN
fcis-12818	71	20	network	network	NOUN
fcis-12818	71	21	model	model	NOUN
fcis-12818	71	22	was	be	AUX
fcis-12818	71	23	added	add	VERB
fcis-12818	71	24	.	.	PUNCT
fcis-12818	72	1	the	the	DET
fcis-12818	72	2	average	average	ADJ
fcis-12818	72	3	accuracy	accuracy	NOUN
fcis-12818	72	4	(	(	PUNCT
fcis-12818	72	5	map	map	NOUN
fcis-12818	72	6	)	)	PUNCT
fcis-12818	72	7	of	of	ADP
fcis-12818	72	8	the	the	DET
fcis-12818	72	9	yolov7	yolov7	NOUN
fcis-12818	72	10	object	object	NOUN
fcis-12818	72	11	detection	detection	NOUN
fcis-12818	72	12	network	network	NOUN
fcis-12818	72	13	model	model	NOUN
fcis-12818	72	14	can	can	AUX
fcis-12818	72	15	reach	reach	VERB
fcis-12818	72	16	80.3	80.3	NUM
fcis-12818	72	17	%	%	NOUN
fcis-12818	72	18	,	,	PUNCT
fcis-12818	72	19	which	which	PRON
fcis-12818	72	20	is	be	AUX
fcis-12818	72	21	1.5	1.5	NUM
fcis-12818	72	22	%	%	NOUN
fcis-12818	72	23	lower	low	ADJ
fcis-12818	72	24	than	than	ADP
fcis-12818	72	25	that	that	PRON
fcis-12818	72	26	of	of	ADP
fcis-12818	72	27	the	the	DET
fcis-12818	72	28	improved	improved	ADJ
fcis-12818	72	29	model	model	NOUN
fcis-12818	72	30	.	.	PUNCT
fcis-12818	73	1	to	to	PART
fcis-12818	73	2	verify	verify	VERB
fcis-12818	73	3	the	the	DET
fcis-12818	73	4	performance	performance	NOUN
fcis-12818	73	5	of	of	ADP
fcis-12818	73	6	the	the	DET
fcis-12818	73	7	improved	improved	ADJ
fcis-12818	73	8	yolov5s	yolov5s	PROPN
fcis-12818	73	9	object	object	NOUN
fcis-12818	73	10	detection	detection	NOUN
fcis-12818	73	11	method	method	NOUN
fcis-12818	73	12	based	base	VERB
fcis-12818	73	13	on	on	ADP
fcis-12818	73	14	average	average	ADJ
fcis-12818	73	15	pooling	pooling	NOUN
fcis-12818	73	16	.	.	PUNCT
fcis-12818	74	1	compare	compare	VERB
fcis-12818	74	2	experiments	experiment	NOUN
fcis-12818	74	3	under	under	ADP
fcis-12818	74	4	the	the	DET
fcis-12818	74	5	same	same	ADJ
fcis-12818	74	6	data	datum	NOUN
fcis-12818	74	7	set	set	NOUN
fcis-12818	74	8	division	division	NOUN
fcis-12818	74	9	.	.	PUNCT
fcis-12818	75	1	in	in	ADP
fcis-12818	75	2	this	this	DET
fcis-12818	75	3	experiment	experiment	NOUN
fcis-12818	75	4	,	,	PUNCT
fcis-12818	75	5	four	four	NUM
fcis-12818	75	6	target	target	NOUN
fcis-12818	75	7	detection	detection	NOUN
fcis-12818	75	8	networks	network	NOUN
fcis-12818	75	9	were	be	AUX
fcis-12818	75	10	used	use	VERB
fcis-12818	75	11	:	:	PUNCT
fcis-12818	75	12	yolov5s	yolov5s	PROPN
fcis-12818	75	13	,	,	PUNCT
fcis-12818	75	14	yolov5n	yolov5n	PROPN
fcis-12818	75	15	,	,	PUNCT
fcis-12818	75	16	yolov5x	yolov5x	PROPN
fcis-12818	75	17	,	,	PUNCT
fcis-12818	75	18	and	and	CCONJ
fcis-12818	75	19	yolov7	yolov7	NOUN
fcis-12818	75	20	.	.	PUNCT
fcis-12818	76	1	tab	tab	NOUN
fcis-12818	76	2	.	.	PUNCT
fcis-12818	76	3	3	3	NUM
fcis-12818	76	4	shows	show	VERB
fcis-12818	76	5	the	the	DET
fcis-12818	76	6	training	training	NOUN
fcis-12818	76	7	results	result	NOUN
fcis-12818	76	8	of	of	ADP
fcis-12818	76	9	different	different	ADJ
fcis-12818	76	10	yolo	yolo	ADJ
fcis-12818	76	11	series	series	NOUN
fcis-12818	76	12	algorithm	algorithm	NOUN
fcis-12818	76	13	models	model	NOUN
fcis-12818	76	14	.	.	PUNCT
fcis-12818	77	1	the	the	DET
fcis-12818	77	2	data	datum	NOUN
fcis-12818	77	3	in	in	ADP
fcis-12818	77	4	row	row	NOUN
fcis-12818	77	5	1	1	NUM
fcis-12818	77	6	is	be	AUX
fcis-12818	77	7	the	the	DET
fcis-12818	77	8	training	training	NOUN
fcis-12818	77	9	results	result	NOUN
fcis-12818	77	10	of	of	ADP
fcis-12818	77	11	the	the	DET
fcis-12818	77	12	yolov5s	yolov5s	PROPN
fcis-12818	77	13	model	model	NOUN
fcis-12818	77	14	,	,	PUNCT
fcis-12818	77	15	and	and	CCONJ
fcis-12818	77	16	the	the	DET
fcis-12818	77	17	map@0.5	map@0.5	PROPN
fcis-12818	77	18	is	be	AUX
fcis-12818	77	19	74.4	74.4	NUM
fcis-12818	77	20	%	%	NOUN
fcis-12818	77	21	.	.	PUNCT
fcis-12818	78	1	the	the	DET
fcis-12818	78	2	data	datum	NOUN
fcis-12818	78	3	in	in	ADP
fcis-12818	78	4	row	row	NOUN
fcis-12818	78	5	2	2	NUM
fcis-12818	78	6	is	be	AUX
fcis-12818	78	7	the	the	DET
fcis-12818	78	8	training	training	NOUN
fcis-12818	78	9	result	result	NOUN
fcis-12818	78	10	of	of	ADP
fcis-12818	78	11	the	the	DET
fcis-12818	78	12	yolov5n	yolov5n	PROPN
fcis-12818	78	13	model	model	NOUN
fcis-12818	78	14	,	,	PUNCT
fcis-12818	78	15	and	and	CCONJ
fcis-12818	78	16	the	the	DET
fcis-12818	78	17	map@0.5	map@0.5	PROPN
fcis-12818	78	18	is	be	AUX
fcis-12818	78	19	77.6	77.6	NUM
fcis-12818	78	20	%	%	NOUN
fcis-12818	78	21	.	.	PUNCT
fcis-12818	79	1	the	the	DET
fcis-12818	79	2	data	datum	NOUN
fcis-12818	79	3	in	in	ADP
fcis-12818	79	4	row	row	NOUN
fcis-12818	79	5	4	4	NUM
fcis-12818	79	6	is	be	AUX
fcis-12818	79	7	the	the	DET
fcis-12818	79	8	yolo	yolo	ADJ
fcis-12818	79	9	v7	v7	VERB
fcis-12818	79	10	model	model	NOUN
fcis-12818	79	11	training	training	NOUN
fcis-12818	79	12	results	result	NOUN
fcis-12818	79	13	,	,	PUNCT
fcis-12818	79	14	and	and	CCONJ
fcis-12818	79	15	the	the	DET
fcis-12818	79	16	map@0.5	map@0.5	PROPN
fcis-12818	79	17	is	be	AUX
fcis-12818	79	18	80.3	80.3	NUM
fcis-12818	79	19	%	%	NOUN
fcis-12818	79	20	.	.	PUNCT
fcis-12818	80	1	the	the	DET
fcis-12818	80	2	yolov5	yolov5	NOUN
fcis-12818	80	3	series	series	PROPN
fcis-12818	80	4	performs	perform	VERB
fcis-12818	80	5	well	well	ADV
fcis-12818	80	6	in	in	ADP
fcis-12818	80	7	both	both	CCONJ
fcis-12818	80	8	speed	speed	NOUN
fcis-12818	80	9	and	and	CCONJ
fcis-12818	80	10	precision	precision	NOUN
fcis-12818	80	11	.	.	PUNCT
fcis-12818	81	1	the	the	DET
fcis-12818	81	2	average	average	ADJ
fcis-12818	81	3	accuracy	accuracy	NOUN
fcis-12818	81	4	(	(	PUNCT
fcis-12818	81	5	map	map	NOUN
fcis-12818	81	6	)	)	PUNCT
fcis-12818	81	7	of	of	ADP
fcis-12818	81	8	the	the	DET
fcis-12818	81	9	yolov5s	yolov5s	PROPN
fcis-12818	81	10	target	target	NOUN
fcis-12818	81	11	detection	detection	NOUN
fcis-12818	81	12	model	model	NOUN
fcis-12818	81	13	based	base	VERB
fcis-12818	81	14	on	on	ADP
fcis-12818	81	15	average	average	ADJ
fcis-12818	81	16	pooling	pooling	NOUN
fcis-12818	81	17	can	can	AUX
fcis-12818	81	18	reach	reach	VERB
fcis-12818	81	19	81.8	81.8	NUM
fcis-12818	81	20	%	%	NOUN
fcis-12818	81	21	,	,	PUNCT
fcis-12818	81	22	and	and	CCONJ
fcis-12818	81	23	the	the	DET
fcis-12818	81	24	overall	overall	ADJ
fcis-12818	81	25	performance	performance	NOUN
fcis-12818	81	26	is	be	AUX
fcis-12818	81	27	better	well	ADJ
fcis-12818	81	28	than	than	ADP
fcis-12818	81	29	that	that	PRON
fcis-12818	81	30	of	of	ADP
fcis-12818	81	31	other	other	ADJ
fcis-12818	81	32	yolo	yolo	ADJ
fcis-12818	81	33	models	model	NOUN
fcis-12818	81	34	,	,	PUNCT
fcis-12818	81	35	which	which	PRON
fcis-12818	81	36	indicates	indicate	VERB
fcis-12818	81	37	that	that	SCONJ
fcis-12818	81	38	the	the	DET
fcis-12818	81	39	improved	improved	ADJ
fcis-12818	81	40	method	method	NOUN
fcis-12818	81	41	in	in	ADP
fcis-12818	81	42	this	this	DET
fcis-12818	81	43	paper	paper	NOUN
fcis-12818	81	44	can	can	AUX
fcis-12818	81	45	identify	identify	VERB
fcis-12818	81	46	and	and	CCONJ
fcis-12818	81	47	locate	locate	VERB
fcis-12818	81	48	small	small	ADJ
fcis-12818	81	49	targets	target	NOUN
fcis-12818	81	50	more	more	ADV
fcis-12818	81	51	accurately	accurately	ADV
fcis-12818	81	52	.	.	PUNCT
fcis-12818	82	1	table	table	NOUN
fcis-12818	82	2	3	3	NUM
fcis-12818	82	3	.	.	PUNCT
fcis-12818	82	4	data	data	PROPN
fcis-12818	82	5	comparison	comparison	PROPN
fcis-12818	82	6	model	model	PROPN
fcis-12818	82	7	map@0.5(%	map@0.5(%	PROPN
fcis-12818	82	8	)	)	PUNCT
fcis-12818	83	1	p	p	NOUN
fcis-12818	83	2	(	(	PUNCT
fcis-12818	83	3	%	%	INTJ
fcis-12818	83	4	)	)	PUNCT
fcis-12818	83	5	r	r	NOUN
fcis-12818	83	6	(	(	PUNCT
fcis-12818	83	7	%	%	INTJ
fcis-12818	83	8	)	)	PUNCT
fcis-12818	83	9	fps	fps	NOUN
fcis-12818	83	10	1	1	NUM
fcis-12818	83	11	yolov5s	yolov5s	NOUN
fcis-12818	83	12	74.4	74.4	NUM
fcis-12818	83	13	76.7	76.7	NUM
fcis-12818	83	14	67.8	67.8	NUM
fcis-12818	83	15	90	90	NUM
fcis-12818	83	16	2	2	NUM
fcis-12818	83	17	yolov5n	yolov5n	NOUN
fcis-12818	83	18	77.6(+3.2	77.6(+3.2	NUM
fcis-12818	83	19	)	)	PUNCT
fcis-12818	83	20	65.4	65.4	NUM
fcis-12818	83	21	81.4	81.4	NUM
fcis-12818	83	22	108(+18	108(+18	NUM
fcis-12818	83	23	)	)	PUNCT
fcis-12818	83	24	3	3	NUM
fcis-12818	83	25	yolov5x	yolov5x	PROPN
fcis-12818	83	26	82.2(+7.8	82.2(+7.8	NUM
fcis-12818	83	27	)	)	PUNCT
fcis-12818	83	28	76.9	76.9	NUM
fcis-12818	83	29	77.9	77.9	NUM
fcis-12818	83	30	77(-13	77(-13	NUM
fcis-12818	83	31	)	)	PUNCT
fcis-12818	83	32	4	4	NUM
fcis-12818	83	33	yolov7	yolov7	NOUN
fcis-12818	83	34	80.3(+5.9	80.3(+5.9	NUM
fcis-12818	83	35	)	)	PUNCT
fcis-12818	83	36	81.2	81.2	NUM
fcis-12818	83	37	76.2	76.2	NUM
fcis-12818	83	38	61(-29	61(-29	NUM
fcis-12818	83	39	)	)	PUNCT
fcis-12818	83	40	5our	5our	NUM
fcis-12818	83	41	81.8（+7.4	81.8（+7.4	NUM
fcis-12818	83	42	）	）	NOUN
fcis-12818	83	43	86.8	86.8	NUM
fcis-12818	83	44	87.3	87.3	NUM
fcis-12818	83	45	99（+9	99（+9	NUM
fcis-12818	83	46	）	）	NOUN
fcis-12818	83	47	4	4	NUM
fcis-12818	83	48	.	.	X
fcis-12818	83	49	conclusion	conclusion	NOUN
fcis-12818	83	50	fig	fig	NOUN
fcis-12818	83	51	3	3	X
fcis-12818	83	52	.	.	PUNCT
fcis-12818	83	53	original	original	ADJ
fcis-12818	83	54	-yolov5s	-yolov5s	PUNCT
fcis-12818	83	55	fig	fig	NOUN
fcis-12818	83	56	4	4	NUM
fcis-12818	83	57	.	.	PUNCT
fcis-12818	84	1	yolov5s	yolov5s	NOUN
fcis-12818	84	2	-	-	PUNCT
fcis-12818	84	3	our	our	PRON
fcis-12818	84	4	in	in	ADP
fcis-12818	84	5	the	the	DET
fcis-12818	84	6	pr	pr	NOUN
fcis-12818	84	7	image	image	NOUN
fcis-12818	84	8	,	,	PUNCT
fcis-12818	84	9	the	the	PRON
fcis-12818	84	10	closer	close	ADJ
fcis-12818	84	11	the	the	DET
fcis-12818	84	12	polyline	polyline	NOUN
fcis-12818	84	13	to	to	ADP
fcis-12818	84	14	the	the	DET
fcis-12818	84	15	upper	upper	ADJ
fcis-12818	84	16	right	right	NOUN
fcis-12818	84	17	,	,	PUNCT
fcis-12818	84	18	the	the	PRON
fcis-12818	84	19	better	well	ADJ
fcis-12818	84	20	the	the	DET
fcis-12818	84	21	performance	performance	NOUN
fcis-12818	84	22	of	of	ADP
fcis-12818	84	23	the	the	DET
fcis-12818	84	24	object	object	NOUN
fcis-12818	84	25	detection	detection	NOUN
fcis-12818	84	26	network	network	NOUN
fcis-12818	84	27	model	model	NOUN
fcis-12818	84	28	.	.	PUNCT
fcis-12818	85	1	the	the	DET
fcis-12818	85	2	performance	performance	NOUN
fcis-12818	85	3	of	of	ADP
fcis-12818	85	4	the	the	DET
fcis-12818	85	5	original	original	ADJ
fcis-12818	85	6	yolov5s	yolov5s	PROPN
fcis-12818	85	7	model	model	NOUN
fcis-12818	85	8	is	be	AUX
fcis-12818	85	9	shown	show	VERB
fcis-12818	85	10	in	in	ADP
fcis-12818	85	11	fig	fig	NOUN
fcis-12818	85	12	.	.	PUNCT
fcis-12818	86	1	3	3	NUM
fcis-12818	86	2	original	original	ADJ
fcis-12818	86	3	-yolov5s	-yolov5s	NOUN
fcis-12818	86	4	,	,	PUNCT
fcis-12818	86	5	and	and	CCONJ
fcis-12818	86	6	the	the	DET
fcis-12818	86	7	improved	improved	ADJ
fcis-12818	86	8	performance	performance	NOUN
fcis-12818	86	9	of	of	ADP
fcis-12818	86	10	the	the	DET
fcis-12818	86	11	yolov5s	yolov5s	PROPN
fcis-12818	86	12	model	model	NOUN
fcis-12818	86	13	based	base	VERB
fcis-12818	86	14	on	on	ADP
fcis-12818	86	15	average	average	ADJ
fcis-12818	86	16	pooling	pooling	NOUN
fcis-12818	86	17	is	be	AUX
fcis-12818	86	18	shown	show	VERB
fcis-12818	86	19	in	in	ADP
fcis-12818	86	20	fig	fig	NOUN
fcis-12818	86	21	.	.	PUNCT
fcis-12818	87	1	4	4	NUM
fcis-12818	87	2	yolov5s	yolov5s	NOUN
fcis-12818	87	3	-	-	PUNCT
fcis-12818	87	4	our	our	PRON
fcis-12818	87	5	.	.	PUNCT
fcis-12818	88	1	it	it	PRON
fcis-12818	88	2	can	can	AUX
fcis-12818	88	3	be	be	AUX
fcis-12818	88	4	found	find	VERB
fcis-12818	88	5	that	that	SCONJ
fcis-12818	88	6	the	the	DET
fcis-12818	88	7	improved	improved	ADJ
fcis-12818	88	8	performance	performance	NOUN
fcis-12818	88	9	is	be	AUX
fcis-12818	88	10	better	well	ADJ
fcis-12818	88	11	than	than	ADP
fcis-12818	88	12	the	the	DET
fcis-12818	88	13	original	original	ADJ
fcis-12818	88	14	yolov5s	yolov5s	PROPN
fcis-12818	88	15	object	object	NOUN
fcis-12818	88	16	detection	detection	NOUN
fcis-12818	88	17	network	network	NOUN
fcis-12818	88	18	model	model	NOUN
fcis-12818	88	19	.	.	PUNCT
fcis-12818	89	1	eiou	eiou	NOUN
fcis-12818	89	2	bounding	bound	VERB
fcis-12818	89	3	box	box	NOUN
fcis-12818	89	4	regression	regression	NOUN
fcis-12818	89	5	loss	loss	NOUN
fcis-12818	89	6	is	be	AUX
fcis-12818	89	7	introduced	introduce	VERB
fcis-12818	89	8	to	to	PART
fcis-12818	89	9	further	far	ADV
fcis-12818	89	10	improve	improve	VERB
fcis-12818	89	11	the	the	DET
fcis-12818	89	12	detection	detection	NOUN
fcis-12818	89	13	accuracy	accuracy	NOUN
fcis-12818	90	1	[	[	X
fcis-12818	90	2	16	16	NUM
fcis-12818	90	3	]	]	X
fcis-12818	90	4	[	[	X
fcis-12818	90	5	17	17	NUM
fcis-12818	90	6	]	]	PUNCT
fcis-12818	90	7	.	.	PUNCT
fcis-12818	91	1	the	the	DET
fcis-12818	91	2	se	se	PROPN
fcis-12818	91	3	attention	attention	NOUN
fcis-12818	91	4	mechanism	mechanism	NOUN
fcis-12818	91	5	object	object	NOUN
fcis-12818	91	6	detection	detection	NOUN
fcis-12818	91	7	network	network	NOUN
fcis-12818	91	8	model	model	NOUN
fcis-12818	91	9	is	be	AUX
fcis-12818	91	10	selected	select	VERB
fcis-12818	91	11	to	to	PART
fcis-12818	91	12	effectively	effectively	ADV
fcis-12818	91	13	reduce	reduce	VERB
fcis-12818	91	14	the	the	DET
fcis-12818	91	15	loss	loss	NOUN
fcis-12818	91	16	of	of	ADP
fcis-12818	91	17	feature	feature	NOUN
fcis-12818	91	18	map	map	NOUN
fcis-12818	91	19	information	information	NOUN
fcis-12818	91	20	and	and	CCONJ
fcis-12818	91	21	improve	improve	VERB
fcis-12818	91	22	the	the	DET
fcis-12818	91	23	recognition	recognition	NOUN
fcis-12818	91	24	accuracy	accuracy	NOUN
fcis-12818	91	25	.	.	PUNCT
fcis-12818	92	1	the	the	DET
fcis-12818	92	2	yolov5s	yolov5s	PROPN
fcis-12818	92	3	network	network	NOUN
fcis-12818	92	4	structure	structure	NOUN
fcis-12818	92	5	with	with	ADP
fcis-12818	92	6	fast	fast	ADJ
fcis-12818	92	7	detection	detection	NOUN
fcis-12818	92	8	speed	speed	NOUN
fcis-12818	92	9	and	and	CCONJ
fcis-12818	92	10	excellent	excellent	ADJ
fcis-12818	92	11	accuracy	accuracy	NOUN
fcis-12818	92	12	value	value	NOUN
fcis-12818	92	13	is	be	AUX
fcis-12818	92	14	obtained	obtain	VERB
fcis-12818	92	15	.	.	PUNCT
fcis-12818	93	1	a	a	DET
fcis-12818	93	2	detection	detection	NOUN
fcis-12818	93	3	classification	classification	NOUN
fcis-12818	93	4	method	method	NOUN
fcis-12818	93	5	based	base	VERB
fcis-12818	93	6	on	on	ADP
fcis-12818	93	7	improved	improved	ADJ
fcis-12818	93	8	yolov5s	yolov5s	PROPN
fcis-12818	93	9	is	be	AUX
fcis-12818	93	10	proposed	propose	VERB
fcis-12818	93	11	.	.	PUNCT
fcis-12818	94	1	the	the	DET
fcis-12818	94	2	se	se	PROPN
fcis-12818	94	3	module	module	NOUN
fcis-12818	94	4	is	be	AUX
fcis-12818	94	5	integrated	integrate	VERB
fcis-12818	94	6	in	in	ADP
fcis-12818	94	7	the	the	DET
fcis-12818	94	8	backbone	backbone	NOUN
fcis-12818	94	9	feature	feature	NOUN
fcis-12818	94	10	extraction	extraction	NOUN
fcis-12818	94	11	network	network	NOUN
fcis-12818	94	12	stage	stage	NOUN
fcis-12818	94	13	,	,	PUNCT
fcis-12818	94	14	so	so	SCONJ
fcis-12818	94	15	that	that	SCONJ
fcis-12818	94	16	the	the	DET
fcis-12818	94	17	backbone	backbone	NOUN
fcis-12818	94	18	network	network	NOUN
fcis-12818	94	19	highlights	highlight	NOUN
fcis-12818	94	20	useful	useful	ADJ
fcis-12818	94	21	features	feature	NOUN
fcis-12818	94	22	and	and	CCONJ
fcis-12818	94	23	pays	pay	VERB
fcis-12818	94	24	more	more	ADJ
fcis-12818	94	25	attention	attention	NOUN
fcis-12818	94	26	to	to	ADP
fcis-12818	94	27	small	small	ADJ
fcis-12818	94	28	target	target	NOUN
fcis-12818	94	29	features	feature	NOUN
fcis-12818	94	30	.	.	PUNCT
fcis-12818	95	1	in	in	ADP
fcis-12818	95	2	addition	addition	NOUN
fcis-12818	95	3	,	,	PUNCT
fcis-12818	95	4	the	the	DET
fcis-12818	95	5	eiou	eiou	NOUN
fcis-12818	95	6	module	module	NOUN
fcis-12818	95	7	is	be	AUX
fcis-12818	95	8	introduced	introduce	VERB
fcis-12818	95	9	to	to	PART
fcis-12818	95	10	better	well	ADV
fcis-12818	95	11	integrate	integrate	VERB
fcis-12818	95	12	the	the	DET
fcis-12818	95	13	characteristics	characteristic	NOUN
fcis-12818	95	14	of	of	ADP
fcis-12818	95	15	each	each	DET
fcis-12818	95	16	scale	scale	NOUN
fcis-12818	95	17	.	.	PUNCT
fcis-12818	96	1	the	the	DET
fcis-12818	96	2	test	test	NOUN
fcis-12818	96	3	results	result	NOUN
fcis-12818	96	4	of	of	ADP
fcis-12818	96	5	the	the	DET
fcis-12818	96	6	proposed	propose	VERB
fcis-12818	96	7	method	method	NOUN
fcis-12818	96	8	are	be	AUX
fcis-12818	96	9	compared	compare	VERB
fcis-12818	96	10	with	with	ADP
fcis-12818	96	11	the	the	DET
fcis-12818	96	12	yolov5n	yolov5n	PROPN
fcis-12818	96	13	,	,	PUNCT
fcis-12818	96	14	yolov5x	yolov5x	PROPN
fcis-12818	96	15	,	,	PUNCT
fcis-12818	96	16	and	and	CCONJ
fcis-12818	96	17	yolov7	yolov7	NOUN
fcis-12818	96	18	calculations	calculation	NOUN
fcis-12818	96	19	.	.	PUNCT
fcis-12818	97	1	the	the	DET
fcis-12818	97	2	experimental	experimental	ADJ
fcis-12818	97	3	results	result	NOUN
fcis-12818	97	4	show	show	VERB
fcis-12818	97	5	that	that	SCONJ
fcis-12818	97	6	compared	compare	VERB
fcis-12818	97	7	with	with	ADP
fcis-12818	97	8	the	the	DET
fcis-12818	97	9	original	original	ADJ
fcis-12818	97	10	yolov5s	yolov5s	PROPN
fcis-12818	97	11	algorithm	algorithm	NOUN
fcis-12818	97	12	,	,	PUNCT
fcis-12818	97	13	the	the	DET
fcis-12818	97	14	improved	improved	ADJ
fcis-12818	97	15	network	network	NOUN
fcis-12818	97	16	has	have	VERB
fcis-12818	97	17	a	a	DET
fcis-12818	97	18	great	great	ADJ
fcis-12818	97	19	improvement	improvement	NOUN
fcis-12818	97	20	in	in	ADP
fcis-12818	97	21	the	the	DET
fcis-12818	97	22	false	false	ADJ
fcis-12818	97	23	and	and	CCONJ
fcis-12818	97	24	missed	miss	VERB
fcis-12818	97	25	detection	detection	NOUN
fcis-12818	97	26	situation	situation	NOUN
fcis-12818	97	27	,	,	PUNCT
fcis-12818	97	28	and	and	CCONJ
fcis-12818	97	29	can	can	AUX
fcis-12818	97	30	accurately	accurately	ADV
fcis-12818	97	31	and	and	CCONJ
fcis-12818	97	32	quickly	quickly	ADV
fcis-12818	97	33	detect	detect	VERB
fcis-12818	97	34	the	the	DET
fcis-12818	97	35	target	target	NOUN
fcis-12818	97	36	.	.	PUNCT
fcis-12818	98	1	references	reference	NOUN
fcis-12818	98	2	[	[	X
fcis-12818	98	3	1	1	NUM
fcis-12818	98	4	]	]	X
fcis-12818	98	5	ying	ying	PROPN
fcis-12818	98	6	z	z	PROPN
fcis-12818	98	7	,	,	PUNCT
fcis-12818	98	8	lin	lin	PROPN
fcis-12818	98	9	z	z	PROPN
fcis-12818	98	10	,	,	PUNCT
fcis-12818	98	11	wu	wu	PROPN
fcis-12818	98	12	z.a	z.a	PROPN
fcis-12818	98	13	modified	modify	VERB
fcis-12818	98	14	-	-	PUNCT
fcis-12818	98	15	yolov5s	yolov5s	NOUN
fcis-12818	98	16	model	model	NOUN
fcis-12818	98	17	for	for	ADP
fcis-12818	98	18	detection	detection	NOUN
fcis-12818	98	19	of	of	ADP
fcis-12818	98	20	wire	wire	NOUN
fcis-12818	98	21	braided	braid	VERB
fcis-12818	98	22	hose	hose	PROPN
fcis-12818	98	23	defects[j].measurement	defects[j].measurement	NOUN
fcis-12818	98	24	,	,	PUNCT
fcis-12818	98	25	2022(190-):190.doi:10.1016	2022(190-):190.doi:10.1016	NUM
fcis-12818	98	26	/	/	SYM
fcis-12818	98	27	j.measurement.2021.110683	j.measurement.2021.110683	NOUN
fcis-12818	98	28	.	.	PUNCT
fcis-12818	99	1	[	[	X
fcis-12818	99	2	2	2	X
fcis-12818	99	3	]	]	PUNCT
fcis-12818	99	4	abdulghani	abdulghani	VERB
fcis-12818	99	5	a	a	DET
fcis-12818	99	6	m	m	NOUN
fcis-12818	99	7	,	,	PUNCT
fcis-12818	99	8	abdulghani	abdulghani	ADJ
fcis-12818	99	9	m	m	VERB
fcis-12818	99	10	m	m	PROPN
fcis-12818	99	11	,	,	PUNCT
fcis-12818	99	12	walters	walters	PROPN
fcis-12818	99	13	w	w	PROPN
fcis-12818	99	14	l.	l.	PROPN
fcis-12818	99	15	multiple	multiple	ADJ
fcis-12818	99	16	data	datum	NOUN
fcis-12818	99	17	augmentation	augmentation	NOUN
fcis-12818	99	18	strategy	strategy	NOUN
fcis-12818	99	19	for	for	ADP
fcis-12818	99	20	enhancing	enhance	VERB
fcis-12818	99	21	the	the	DET
fcis-12818	99	22	performance	performance	NOUN
fcis-12818	99	23	of	of	ADP
fcis-12818	99	24	yolov7	yolov7	NOUN
fcis-12818	99	25	object	object	VERB
fcis-12818	99	26	detection	detection	NOUN
fcis-12818	99	27	algorithm[j].tech	algorithm[j].tech	PROPN
fcis-12818	99	28	science	science	NOUN
fcis-12818	99	29	press	press	NOUN
fcis-12818	99	30	,	,	PUNCT
fcis-12818	99	31	2023.doi:10.32604	2023.doi:10.32604	NUM
fcis-12818	99	32	/	/	SYM
fcis-12818	99	33	jai.2023.041341	jai.2023.041341	NOUN
fcis-12818	99	34	.	.	PUNCT
fcis-12818	100	1	[	[	X
fcis-12818	100	2	3	3	X
fcis-12818	100	3	]	]	X
fcis-12818	100	4	mao	mao	NOUN
fcis-12818	101	1	q	q	NOUN
fcis-12818	101	2	,	,	PUNCT
fcis-12818	101	3	wang	wang	PROPN
fcis-12818	101	4	m	m	PROPN
fcis-12818	101	5	,	,	PUNCT
fcis-12818	101	6	hu	hu	PROPN
fcis-12818	101	7	x	x	INTJ
fcis-12818	101	8	.	.	PUNCT
fcis-12818	102	1	intelligent	intelligent	ADJ
fcis-12818	102	2	identification	identification	NOUN
fcis-12818	102	3	method	method	NOUN
fcis-12818	102	4	of	of	ADP
fcis-12818	102	5	shearer	shearer	PROPN
fcis-12818	102	6	drums	drum	NOUN
fcis-12818	102	7	based	base	VERB
fcis-12818	102	8	on	on	ADP
fcis-12818	102	9	improved	improved	ADJ
fcis-12818	102	10	yolov5s	yolov5s	PROPN
fcis-12818	102	11	with	with	ADP
fcis-12818	102	12	dark	dark	ADJ
fcis-12818	102	13	channel	channel	NOUN
fcis-12818	102	14	-	-	PUNCT
fcis-12818	102	15	guided	guide	VERB
fcis-12818	102	16	filtering	filtering	NOUN
fcis-12818	102	17	defogging[j	defogging[j	NOUN
fcis-12818	102	18	]	]	PUNCT
fcis-12818	102	19	.	.	PUNCT
fcis-12818	103	1	2023	2023	NUM
fcis-12818	103	2	.	.	PUNCT
fcis-12818	104	1	[	[	X
fcis-12818	104	2	4	4	NUM
fcis-12818	104	3	]	]	PUNCT
fcis-12818	104	4	xi	xi	X
fcis-12818	104	5	d	d	PROPN
fcis-12818	104	6	,	,	PUNCT
fcis-12818	104	7	qin	qin	PROPN
fcis-12818	104	8	y	y	PROPN
fcis-12818	104	9	,	,	PUNCT
fcis-12818	104	10	wang	wang	PROPN
fcis-12818	104	11	s	s	PART
fcis-12818	104	12	.ydrsnet	.ydrsnet	NOUN
fcis-12818	104	13	:	:	PUNCT
fcis-12818	104	14	an	an	DET
fcis-12818	104	15	integrated	integrate	VERB
fcis-12818	104	16	yolov5deeplabv3+real	yolov5deeplabv3+real	PROPN
fcis-12818	104	17	-	-	PUNCT
fcis-12818	104	18	time	time	NOUN
fcis-12818	104	19	segmentation	segmentation	NOUN
fcis-12818	104	20	network	network	NOUN
fcis-12818	104	21	for	for	ADP
fcis-12818	104	22	gear	gear	NOUN
fcis-12818	104	23	pitting	pitting	NOUN
fcis-12818	104	24	measurement[j].journal	measurement[j].journal	PROPN
fcis-12818	104	25	of	of	ADP
fcis-12818	104	26	intelligent	intelligent	ADJ
fcis-12818	104	27	manufacturing	manufacturing	NOUN
fcis-12818	104	28	,	,	PUNCT
fcis-12818	104	29	2023	2023	NUM
fcis-12818	104	30	.	.	PUNCT
fcis-12818	105	1	[	[	X
fcis-12818	105	2	5	5	NUM
fcis-12818	105	3	]	]	X
fcis-12818	105	4	shaikh	shaikh	PROPN
fcis-12818	105	5	s	s	X
fcis-12818	105	6	a	a	DET
fcis-12818	105	7	,	,	PUNCT
fcis-12818	105	8	chopade	chopade	NOUN
fcis-12818	105	9	j	j	PROPN
fcis-12818	105	10	j	j	PROPN
fcis-12818	105	11	,	,	PUNCT
fcis-12818	105	12	sardey	sardey	PROPN
fcis-12818	105	13	m	m	VERB
fcis-12818	105	14	p	p	NOUN
fcis-12818	105	15	.real	.real	ADJ
fcis-12818	105	16	-	-	PUNCT
fcis-12818	105	17	time	time	NOUN
fcis-12818	105	18	multi	multi	ADJ
fcis-12818	105	19	-	-	ADJ
fcis-12818	105	20	object	object	ADJ
fcis-12818	105	21	detection	detection	NOUN
fcis-12818	105	22	using	use	VERB
fcis-12818	105	23	enhanced	enhanced	ADJ
fcis-12818	105	24	yolov5	yolov5	NOUN
fcis-12818	105	25	-	-	PUNCT
fcis-12818	105	26	7s	7	NOUN
fcis-12818	105	27	on	on	ADP
fcis-12818	105	28	multi	multi	ADJ
fcis-12818	105	29	-	-	NOUN
fcis-12818	105	30	gpu	gpu	NOUN
fcis-12818	105	31	for	for	ADP
fcis-12818	105	32	highresolution	highresolution	NOUN
fcis-12818	105	33	video[j].international	video[j].international	ADJ
fcis-12818	105	34	journal	journal	NOUN
fcis-12818	105	35	of	of	ADP
fcis-12818	105	36	image	image	NOUN
fcis-12818	105	37	and	and	CCONJ
fcis-12818	105	38	graphics	graphic	NOUN
fcis-12818	105	39	,	,	PUNCT
fcis-12818	105	40	2023.doi:10.1142	2023.doi:10.1142	NUM
fcis-12818	105	41	/	/	SYM
fcis-12818	105	42	s0219467824500190	s0219467824500190	NOUN
fcis-12818	105	43	.	.	PUNCT
fcis-12818	106	1	[	[	X
fcis-12818	106	2	6	6	NUM
fcis-12818	106	3	]	]	X
fcis-12818	106	4	panigrahi	panigrahi	NOUN
fcis-12818	106	5	s	s	PART
fcis-12818	106	6	,	,	PUNCT
fcis-12818	106	7	raju	raju	PROPN
fcis-12818	106	8	u	u	PROPN
fcis-12818	106	9	s	s	PART
fcis-12818	106	10	n	n	PRON
fcis-12818	106	11	.ms	.ms	PUNCT
fcis-12818	106	12	-	-	PUNCT
fcis-12818	106	13	ml	ml	ADP
fcis-12818	106	14	-	-	PUNCT
fcis-12818	106	15	snyolov(3	snyolov(3	NOUN
fcis-12818	106	16	):	):	PUNCT
fcis-12818	106	17	a	a	DET
fcis-12818	106	18	robust	robust	ADJ
fcis-12818	106	19	lightweight	lightweight	ADJ
fcis-12818	106	20	modification	modification	NOUN
fcis-12818	106	21	of	of	ADP
fcis-12818	106	22	squeezenet	squeezenet	NOUN
fcis-12818	106	23	based	base	VERB
fcis-12818	106	24	yolov(3	yolov(3	NOUN
fcis-12818	106	25	)	)	PUNCT
fcis-12818	106	26	for	for	ADP
fcis-12818	106	27	pedestrian	pedestrian	NOUN
fcis-12818	106	28	detection[j	detection[j	PROPN
fcis-12818	106	29	]	]	PUNCT
fcis-12818	106	30	.	.	PUNCT
fcis-12818	107	1	optik	optik	PROPN
fcis-12818	107	2	:	:	PUNCT
fcis-12818	107	3	zeitschrift	zeitschrift	NOUN
fcis-12818	107	4	fur	fur	NOUN
fcis-12818	107	5	lichtund	lichtund	VERB
fcis-12818	107	6	84	84	NUM
fcis-12818	107	7	elektronenoptik	elektronenoptik	NOUN
fcis-12818	107	8	:	:	PUNCT
fcis-12818	107	9	=	=	SYM
fcis-12818	107	10	journal	journal	NOUN
fcis-12818	107	11	for	for	ADP
fcis-12818	107	12	light	light	ADJ
fcis-12818	107	13	-	-	PUNCT
fcis-12818	107	14	and	and	CCONJ
fcis-12818	107	15	electronoptic	electronoptic	ADJ
fcis-12818	107	16	,	,	PUNCT
fcis-12818	107	17	2022	2022	NUM
fcis-12818	107	18	(	(	PUNCT
fcis-12818	107	19	260-	260-	NUM
fcis-12818	107	20	):	):	PUNCT
fcis-12818	107	21	260	260	NUM
fcis-12818	107	22	.	.	PUNCT
fcis-12818	108	1	[	[	X
fcis-12818	108	2	7	7	X
fcis-12818	108	3	]	]	X
fcis-12818	108	4	iyer	iyer	PROPN
fcis-12818	108	5	r	r	NOUN
fcis-12818	108	6	,	,	PUNCT
fcis-12818	108	7	bhensdadiya	bhensdadiya	PROPN
fcis-12818	108	8	k	k	PROPN
fcis-12818	108	9	p	p	X
fcis-12818	108	10	,	,	PUNCT
fcis-12818	108	11	priyansh_ringe.comparison	priyansh_ringe.comparison	VERB
fcis-12818	108	12	of	of	ADP
fcis-12818	108	13	yolov3	yolov3	PROPN
fcis-12818	108	14	,	,	PUNCT
fcis-12818	108	15	yolov5s	yolov5s	PROPN
fcis-12818	108	16	and	and	CCONJ
fcis-12818	108	17	mobilenet	mobilenet	NOUN
fcis-12818	108	18	-	-	PUNCT
fcis-12818	108	19	ssd	ssd	NOUN
fcis-12818	108	20	v2	v2	NOUN
fcis-12818	108	21	for	for	ADP
fcis-12818	108	22	real	real	ADJ
fcis-12818	108	23	-	-	PUNCT
fcis-12818	108	24	time	time	NOUN
fcis-12818	108	25	mask	mask	NOUN
fcis-12818	108	26	detection[j	detection[j	PROPN
fcis-12818	108	27	]	]	PUNCT
fcis-12818	108	28	.	.	PUNCT
fcis-12818	108	29	2021	2021	NUM
fcis-12818	108	30	.	.	PUNCT
fcis-12818	109	1	[	[	X
fcis-12818	109	2	8	8	NUM
fcis-12818	109	3	]	]	X
fcis-12818	109	4	ying	ying	PROPN
fcis-12818	109	5	z	z	PROPN
fcis-12818	109	6	,	,	PUNCT
fcis-12818	109	7	lin	lin	PROPN
fcis-12818	109	8	z	z	PROPN
fcis-12818	109	9	,	,	PUNCT
fcis-12818	109	10	wu	wu	PROPN
fcis-12818	109	11	z.	z.	PROPN
fcis-12818	110	1	a	a	DET
fcis-12818	110	2	modified	modify	VERB
fcis-12818	110	3	-	-	PUNCT
fcis-12818	110	4	yolov5s	yolov5s	NOUN
fcis-12818	110	5	model	model	NOUN
fcis-12818	110	6	for	for	ADP
fcis-12818	110	7	detection	detection	NOUN
fcis-12818	110	8	of	of	ADP
fcis-12818	110	9	wire	wire	NOUN
fcis-12818	110	10	braided	braid	VERB
fcis-12818	110	11	hose	hose	PROPN
fcis-12818	110	12	defects[j	defects[j	PROPN
fcis-12818	110	13	]	]	PUNCT
fcis-12818	110	14	.	.	PUNCT
fcis-12818	111	1	measurement	measurement	NOUN
fcis-12818	111	2	,	,	PUNCT
fcis-12818	111	3	2022	2022	NUM
fcis-12818	111	4	(	(	PUNCT
fcis-12818	111	5	190-	190-	NUM
fcis-12818	111	6	):	):	PUNCT
fcis-12818	111	7	190.doi:10.1016	190.doi:10.1016	NUM
fcis-12818	111	8	/	/	SYM
fcis-12818	111	9	j.measurement.2021.110683	j.measurement.2021.110683	NOUN
fcis-12818	111	10	.	.	PUNCT
fcis-12818	112	1	[	[	X
fcis-12818	112	2	9	9	NUM
fcis-12818	112	3	]	]	SYM
fcis-12818	112	4	mao	mao	NOUN
fcis-12818	113	1	q	q	NOUN
fcis-12818	113	2	,	,	PUNCT
fcis-12818	113	3	wang	wang	PROPN
fcis-12818	113	4	m	m	PROPN
fcis-12818	113	5	,	,	PUNCT
fcis-12818	113	6	hu	hu	PROPN
fcis-12818	113	7	x	x	INTJ
fcis-12818	113	8	.	.	PUNCT
fcis-12818	114	1	intelligent	intelligent	ADJ
fcis-12818	114	2	identification	identification	NOUN
fcis-12818	114	3	method	method	NOUN
fcis-12818	114	4	of	of	ADP
fcis-12818	114	5	shearer	shearer	PROPN
fcis-12818	114	6	drums	drum	NOUN
fcis-12818	114	7	based	base	VERB
fcis-12818	114	8	on	on	ADP
fcis-12818	114	9	improved	improved	ADJ
fcis-12818	114	10	yolov5s	yolov5s	PROPN
fcis-12818	114	11	with	with	ADP
fcis-12818	114	12	dark	dark	ADJ
fcis-12818	114	13	channel	channel	NOUN
fcis-12818	114	14	-	-	PUNCT
fcis-12818	114	15	guided	guide	VERB
fcis-12818	114	16	filtering	filtering	NOUN
fcis-12818	114	17	defogging[j	defogging[j	NOUN
fcis-12818	114	18	]	]	PUNCT
fcis-12818	114	19	.	.	PUNCT
fcis-12818	115	1	2023	2023	NUM
fcis-12818	115	2	.	.	PUNCT
fcis-12818	116	1	[	[	X
fcis-12818	116	2	10	10	NUM
fcis-12818	116	3	]	]	PUNCT
fcis-12818	116	4	xu	xu	PROPN
fcis-12818	117	1	q	q	X
fcis-12818	117	2	,	,	PUNCT
fcis-12818	117	3	liang	liang	PROPN
fcis-12818	117	4	y	y	PROPN
fcis-12818	117	5	,	,	PUNCT
fcis-12818	118	1	wang	wang	PROPN
fcis-12818	118	2	d	d	PROPN
fcis-12818	118	3	.	.	PUNCT
fcis-12818	119	1	hyperspectral	hyperspectral	ADJ
fcis-12818	119	2	image	image	NOUN
fcis-12818	119	3	classification	classification	NOUN
fcis-12818	119	4	based	base	VERB
fcis-12818	119	5	on	on	ADP
fcis-12818	119	6	se	se	PROPN
fcis-12818	119	7	-	-	NOUN
fcis-12818	119	8	res2net	res2net	NOUN
fcis-12818	119	9	and	and	CCONJ
fcis-12818	119	10	multi	multi	ADJ
fcis-12818	119	11	-	-	ADJ
fcis-12818	119	12	scale	scale	ADJ
fcis-12818	119	13	spatial	spatial	ADJ
fcis-12818	119	14	spectral	spectral	ADJ
fcis-12818	119	15	fusion	fusion	NOUN
fcis-12818	119	16	attention	attention	NOUN
fcis-12818	119	17	mechanism[j].journal	mechanism[j].journal	ADJ
fcis-12818	119	18	of	of	ADP
fcis-12818	119	19	computer	computer	NOUN
fcis-12818	119	20	-	-	PUNCT
fcis-12818	119	21	aided	aid	VERB
fcis-12818	119	22	design	design	NOUN
fcis-12818	119	23	&	&	CCONJ
fcis-12818	119	24	computer	computer	NOUN
fcis-12818	119	25	graphics	graphic	NOUN
fcis-12818	119	26	,	,	PUNCT
fcis-12818	119	27	2021	2021	NUM
fcis-12818	119	28	,	,	PUNCT
fcis-12818	119	29	33(11):1726	33(11):1726	NUM
fcis-12818	119	30	-	-	SYM
fcis-12818	119	31	1734.doi	1734.doi	NUM
fcis-12818	119	32	:	:	PUNCT
fcis-12818	119	33	10.3724/	10.3724/	NUM
fcis-12818	119	34	sp.j.1089	sp.j.1089	NOUN
fcis-12818	119	35	.	.	PUNCT
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fcis-12818	120	2	.	.	PUNCT
fcis-12818	121	1	[	[	X
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fcis-12818	121	3	]	]	SYM
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fcis-12818	121	9	,	,	PUNCT
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fcis-12818	121	13	pyramid	pyramid	NOUN
fcis-12818	121	14	attention	attention	NOUN
fcis-12818	121	15	network	network	NOUN
fcis-12818	121	16	for	for	ADP
fcis-12818	121	17	real	real	ADJ
fcis-12818	121	18	-	-	PUNCT
fcis-12818	121	19	time	time	NOUN
fcis-12818	121	20	semantic	semantic	ADJ
fcis-12818	121	21	segmentation	segmentation	NOUN
fcis-12818	121	22	of	of	ADP
fcis-12818	121	23	urban	urban	ADJ
fcis-12818	121	24	scenes[j].applied	scenes[j].applie	VERB
fcis-12818	121	25	intelligence	intelligence	NOUN
fcis-12818	121	26	:	:	PUNCT
fcis-12818	121	27	the	the	DET
fcis-12818	121	28	international	international	ADJ
fcis-12818	121	29	journal	journal	NOUN
fcis-12818	121	30	of	of	ADP
fcis-12818	121	31	artificial	artificial	ADJ
fcis-12818	121	32	intelligence	intelligence	NOUN
fcis-12818	121	33	,	,	PUNCT
fcis-12818	121	34	neural	neural	ADJ
fcis-12818	121	35	networks	network	NOUN
fcis-12818	121	36	,	,	PUNCT
fcis-12818	121	37	and	and	CCONJ
fcis-12818	121	38	complex	complex	ADJ
fcis-12818	121	39	problem	problem	NOUN
fcis-12818	121	40	-	-	PUNCT
fcis-12818	121	41	solving	solve	VERB
fcis-12818	121	42	technologies	technology	NOUN
fcis-12818	121	43	,	,	PUNCT
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fcis-12818	121	45	.	.	PUNCT
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fcis-12818	122	10	,	,	PUNCT
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fcis-12818	122	12	z.	z.	PROPN
fcis-12818	122	13	focal	focal	ADJ
fcis-12818	122	14	and	and	CCONJ
fcis-12818	122	15	efficient	efficient	ADJ
fcis-12818	122	16	iou	iou	NOUN
fcis-12818	122	17	loss	loss	NOUN
fcis-12818	122	18	for	for	ADP
fcis-12818	122	19	accurate	accurate	ADJ
fcis-12818	122	20	bounding	bounding	NOUN
fcis-12818	122	21	box	box	NOUN
fcis-12818	122	22	regression[j	regression[j	PROPN
fcis-12818	122	23	]	]	PUNCT
fcis-12818	122	24	.	.	PUNCT
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fcis-12818	123	2	:	:	PUNCT
fcis-12818	123	3	10	10	NUM
fcis-12818	123	4	.	.	X
fcis-12818	123	5	48550/	48550/	NUM
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fcis-12818	124	2	13	13	NUM
fcis-12818	124	3	]	]	X
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fcis-12818	124	5	y	y	PROPN
fcis-12818	124	6	,	,	PUNCT
fcis-12818	124	7	zhang	zhang	PROPN
fcis-12818	124	8	f	f	PROPN
fcis-12818	124	9	,	,	PUNCT
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fcis-12818	124	11	d.	d.	PROPN
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fcis-12818	124	13	-	-	PUNCT
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fcis-12818	124	15	iou	iou	NOUN
fcis-12818	124	16	loss	loss	NOUN
fcis-12818	124	17	for	for	ADP
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fcis-12818	124	19	and	and	CCONJ
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fcis-12818	124	22	box	box	NOUN
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fcis-12818	124	24	and	and	CCONJ
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fcis-12818	124	28	.	.	PUNCT
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fcis-12818	125	2	,	,	PUNCT
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fcis-12818	125	4	.	.	PUNCT
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fcis-12818	126	3	]	]	SYM
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fcis-12818	126	9	,	,	PUNCT
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fcis-12818	126	11	d	d	PROPN
fcis-12818	126	12	.	.	PUNCT
fcis-12818	127	1	pcb	pcb	PROPN
fcis-12818	127	2	-	-	PUNCT
fcis-12818	127	3	yolo	yolo	PROPN
fcis-12818	127	4	:	:	PUNCT
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fcis-12818	127	17	.	.	PUNCT
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fcis-12818	129	11	x	x	PROPN
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fcis-12818	130	3	-	-	PUNCT
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fcis-12818	130	5	:	:	PUNCT
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fcis-12818	130	11	combining	combine	VERB
fcis-12818	130	12	mobilenet	mobilenet	NOUN
fcis-12818	130	13	v2	v2	PROPN
fcis-12818	130	14	and	and	CCONJ
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fcis-12818	130	18	.	.	PUNCT
fcis-12818	131	1	journal	journal	PROPN
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fcis-12818	131	5	series	series	NOUN
fcis-12818	131	6	,	,	PUNCT
fcis-12818	131	7	2021	2021	NUM
fcis-12818	131	8	,	,	PUNCT
fcis-12818	131	9	1883(1	1883(1	NUM
fcis-12818	131	10	):	):	PUNCT
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fcis-12818	131	12	.	.	PUNCT
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fcis-12818	133	13	algorithm	algorithm	NOUN
fcis-12818	133	14	based	base	VERB
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fcis-12818	133	16	yolo	yolo	PROPN
fcis-12818	133	17	v4[j].international	v4[j].international	PROPN
fcis-12818	133	18	journal	journal	NOUN
fcis-12818	133	19	of	of	ADP
fcis-12818	133	20	foundations	foundation	NOUN
fcis-12818	133	21	of	of	ADP
fcis-12818	133	22	computer	computer	NOUN
fcis-12818	133	23	science	science	NOUN
fcis-12818	133	24	,	,	PUNCT
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fcis-12818	134	6	,	,	PUNCT
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