id	sid	tid	token	lemma	pos
ajst-18565	1	1	academic	academic	ADJ
ajst-18565	1	2	journal	journal	NOUN
ajst-18565	1	3	of	of	ADP
ajst-18565	1	4	science	science	NOUN
ajst-18565	1	5	and	and	CCONJ
ajst-18565	1	6	technology	technology	NOUN
ajst-18565	1	7	issn	issn	NOUN
ajst-18565	1	8	:	:	PUNCT
ajst-18565	1	9	2771	2771	NUM
ajst-18565	1	10	-	-	SYM
ajst-18565	1	11	3032	3032	NUM
ajst-18565	1	12	|	|	NOUN
ajst-18565	1	13	vol	vol	NOUN
ajst-18565	1	14	.	.	PROPN
ajst-18565	2	1	9	9	NUM
ajst-18565	2	2	,	,	PUNCT
ajst-18565	2	3	no	no	INTJ
ajst-18565	2	4	.	.	NOUN
ajst-18565	2	5	3	3	NUM
ajst-18565	2	6	,	,	PUNCT
ajst-18565	2	7	2024	2024	NUM
ajst-18565	2	8	162	162	NUM
ajst-18565	2	9	research	research	NOUN
ajst-18565	2	10	on	on	ADP
ajst-18565	2	11	road	road	NOUN
ajst-18565	2	12	damage	damage	NOUN
ajst-18565	2	13	detection	detection	NOUN
ajst-18565	2	14	based	base	VERB
ajst-18565	2	15	on	on	ADP
ajst-18565	2	16	improved	improved	ADJ
ajst-18565	2	17	yolov8	yolov8	PROPN
ajst-18565	2	18	jingwei	jingwei	PROPN
ajst-18565	2	19	yang	yang	PROPN
ajst-18565	2	20	,	,	PUNCT
ajst-18565	2	21	yuansong	yuansong	PROPN
ajst-18565	2	22	li	li	PROPN
ajst-18565	2	23	sichuan	sichuan	PROPN
ajst-18565	2	24	university	university	PROPN
ajst-18565	2	25	of	of	ADP
ajst-18565	2	26	science	science	PROPN
ajst-18565	2	27	&	&	CCONJ
ajst-18565	2	28	engineering	engineering	PROPN
ajst-18565	2	29	,	,	PUNCT
ajst-18565	2	30	school	school	NOUN
ajst-18565	2	31	of	of	ADP
ajst-18565	2	32	computer	computer	NOUN
ajst-18565	2	33	science	science	PROPN
ajst-18565	2	34	&	&	CCONJ
ajst-18565	2	35	engineering	engineering	PROPN
ajst-18565	2	36	,	,	PUNCT
ajst-18565	2	37	yibin	yibin	PROPN
ajst-18565	2	38	644000	644000	NUM
ajst-18565	2	39	,	,	PUNCT
ajst-18565	2	40	china	china	PROPN
ajst-18565	2	41	abstract	abstract	NOUN
ajst-18565	2	42	:	:	PUNCT
ajst-18565	2	43	aiming	aim	VERB
ajst-18565	2	44	at	at	ADP
ajst-18565	2	45	the	the	DET
ajst-18565	2	46	low	low	ADJ
ajst-18565	2	47	accuracy	accuracy	NOUN
ajst-18565	2	48	of	of	ADP
ajst-18565	2	49	deep	deep	ADJ
ajst-18565	2	50	learning	learning	NOUN
ajst-18565	2	51	in	in	ADP
ajst-18565	2	52	road	road	NOUN
ajst-18565	2	53	damage	damage	NOUN
ajst-18565	2	54	detection	detection	NOUN
ajst-18565	2	55	,	,	PUNCT
ajst-18565	2	56	a	a	DET
ajst-18565	2	57	road	road	NOUN
ajst-18565	2	58	damage	damage	NOUN
ajst-18565	2	59	detection	detection	NOUN
ajst-18565	2	60	method	method	NOUN
ajst-18565	2	61	based	base	VERB
ajst-18565	2	62	on	on	ADP
ajst-18565	2	63	improved	improved	ADJ
ajst-18565	2	64	yolov8	yolov8	NOUN
ajst-18565	2	65	is	be	AUX
ajst-18565	2	66	proposed	propose	VERB
ajst-18565	2	67	.	.	PUNCT
ajst-18565	3	1	firstly	firstly	ADV
ajst-18565	3	2	,	,	PUNCT
ajst-18565	3	3	senetv2	senetv2	PROPN
ajst-18565	3	4	attention	attention	NOUN
ajst-18565	3	5	module	module	NOUN
ajst-18565	3	6	was	be	AUX
ajst-18565	3	7	added	add	VERB
ajst-18565	3	8	to	to	ADP
ajst-18565	3	9	the	the	DET
ajst-18565	3	10	backbone	backbone	NOUN
ajst-18565	3	11	network	network	NOUN
ajst-18565	3	12	of	of	ADP
ajst-18565	3	13	yolov8	yolov8	NOUN
ajst-18565	3	14	to	to	PART
ajst-18565	3	15	improve	improve	VERB
ajst-18565	3	16	the	the	DET
ajst-18565	3	17	model	model	NOUN
ajst-18565	3	18	's	's	PART
ajst-18565	3	19	feature	feature	NOUN
ajst-18565	3	20	learning	learning	NOUN
ajst-18565	3	21	ability	ability	NOUN
ajst-18565	3	22	.	.	PUNCT
ajst-18565	4	1	secondly	secondly	ADV
ajst-18565	4	2	,	,	PUNCT
ajst-18565	4	3	in	in	ADP
ajst-18565	4	4	the	the	DET
ajst-18565	4	5	neck	neck	NOUN
ajst-18565	4	6	network	network	NOUN
ajst-18565	4	7	,	,	PUNCT
ajst-18565	4	8	gsconv	gsconv	NOUN
ajst-18565	4	9	is	be	AUX
ajst-18565	4	10	used	use	VERB
ajst-18565	4	11	to	to	PART
ajst-18565	4	12	replace	replace	VERB
ajst-18565	4	13	the	the	DET
ajst-18565	4	14	common	common	ADJ
ajst-18565	4	15	convolutional	convolutional	ADJ
ajst-18565	4	16	module	module	NOUN
ajst-18565	4	17	to	to	PART
ajst-18565	4	18	reduce	reduce	VERB
ajst-18565	4	19	the	the	DET
ajst-18565	4	20	complexity	complexity	NOUN
ajst-18565	4	21	of	of	ADP
ajst-18565	4	22	the	the	DET
ajst-18565	4	23	model	model	NOUN
ajst-18565	4	24	and	and	CCONJ
ajst-18565	4	25	improve	improve	VERB
ajst-18565	4	26	the	the	DET
ajst-18565	4	27	accuracy	accuracy	NOUN
ajst-18565	4	28	.	.	PUNCT
ajst-18565	5	1	finally	finally	ADV
ajst-18565	5	2	,	,	PUNCT
ajst-18565	5	3	the	the	DET
ajst-18565	5	4	loss	loss	NOUN
ajst-18565	5	5	function	function	NOUN
ajst-18565	5	6	is	be	AUX
ajst-18565	5	7	changed	change	VERB
ajst-18565	5	8	to	to	ADP
ajst-18565	5	9	wise	wise	ADJ
ajst-18565	5	10	-	-	PUNCT
ajst-18565	5	11	iou	iou	NOUN
ajst-18565	5	12	to	to	PART
ajst-18565	5	13	reduce	reduce	VERB
ajst-18565	5	14	the	the	DET
ajst-18565	5	15	impact	impact	NOUN
ajst-18565	5	16	of	of	ADP
ajst-18565	5	17	detection	detection	NOUN
ajst-18565	5	18	due	due	ADP
ajst-18565	5	19	to	to	ADP
ajst-18565	5	20	a	a	DET
ajst-18565	5	21	small	small	ADJ
ajst-18565	5	22	number	number	NOUN
ajst-18565	5	23	of	of	ADP
ajst-18565	5	24	low	low	ADJ
ajst-18565	5	25	-	-	PUNCT
ajst-18565	5	26	quality	quality	NOUN
ajst-18565	5	27	instances	instance	NOUN
ajst-18565	5	28	.	.	PUNCT
ajst-18565	6	1	the	the	DET
ajst-18565	6	2	experimental	experimental	ADJ
ajst-18565	6	3	results	result	NOUN
ajst-18565	6	4	show	show	VERB
ajst-18565	6	5	that	that	SCONJ
ajst-18565	6	6	compared	compare	VERB
ajst-18565	6	7	with	with	ADP
ajst-18565	6	8	the	the	DET
ajst-18565	6	9	traditional	traditional	ADJ
ajst-18565	6	10	yolov8	yolov8	NOUN
ajst-18565	6	11	,	,	PUNCT
ajst-18565	6	12	the	the	DET
ajst-18565	6	13	map50	map50	NOUN
ajst-18565	6	14	of	of	ADP
ajst-18565	6	15	this	this	DET
ajst-18565	6	16	model	model	NOUN
ajst-18565	6	17	is	be	AUX
ajst-18565	6	18	increased	increase	VERB
ajst-18565	6	19	by	by	ADP
ajst-18565	6	20	2.1	2.1	NUM
ajst-18565	6	21	percentage	percentage	NOUN
ajst-18565	6	22	points	point	NOUN
ajst-18565	6	23	,	,	PUNCT
ajst-18565	6	24	and	and	CCONJ
ajst-18565	6	25	the	the	DET
ajst-18565	6	26	detection	detection	NOUN
ajst-18565	6	27	effect	effect	NOUN
ajst-18565	6	28	is	be	AUX
ajst-18565	6	29	good	good	ADJ
ajst-18565	6	30	,	,	PUNCT
ajst-18565	6	31	which	which	PRON
ajst-18565	6	32	can	can	AUX
ajst-18565	6	33	meet	meet	VERB
ajst-18565	6	34	the	the	DET
ajst-18565	6	35	requirements	requirement	NOUN
ajst-18565	6	36	of	of	ADP
ajst-18565	6	37	accurate	accurate	ADJ
ajst-18565	6	38	detection	detection	NOUN
ajst-18565	6	39	.	.	PUNCT
ajst-18565	7	1	keywords	keyword	NOUN
ajst-18565	7	2	:	:	PUNCT
ajst-18565	7	3	road	road	NOUN
ajst-18565	7	4	detection	detection	NOUN
ajst-18565	7	5	;	;	PUNCT
ajst-18565	7	6	deep	deep	ADJ
ajst-18565	7	7	learning;yolov8	learning;yolov8	ADJ
ajst-18565	7	8	.	.	NOUN
ajst-18565	8	1	1	1	X
ajst-18565	8	2	.	.	X
ajst-18565	8	3	introduction	introduction	NOUN
ajst-18565	8	4	road	road	NOUN
ajst-18565	8	5	damage	damage	NOUN
ajst-18565	8	6	detection	detection	NOUN
ajst-18565	8	7	is	be	AUX
ajst-18565	8	8	of	of	ADP
ajst-18565	8	9	great	great	ADJ
ajst-18565	8	10	significance	significance	NOUN
ajst-18565	8	11	to	to	ADP
ajst-18565	8	12	traffic	traffic	NOUN
ajst-18565	8	13	safety	safety	NOUN
ajst-18565	8	14	,	,	PUNCT
ajst-18565	8	15	road	road	NOUN
ajst-18565	8	16	damage	damage	NOUN
ajst-18565	8	17	maintenance	maintenance	NOUN
ajst-18565	8	18	and	and	CCONJ
ajst-18565	8	19	automobile	automobile	NOUN
ajst-18565	8	20	intelligent	intelligent	ADJ
ajst-18565	8	21	driving	driving	NOUN
ajst-18565	8	22	assistance	assistance	NOUN
ajst-18565	8	23	.	.	PUNCT
ajst-18565	9	1	traditional	traditional	ADJ
ajst-18565	9	2	manual	manual	ADJ
ajst-18565	9	3	detection	detection	NOUN
ajst-18565	9	4	methods	method	NOUN
ajst-18565	9	5	often	often	ADV
ajst-18565	9	6	need	need	VERB
ajst-18565	9	7	to	to	PART
ajst-18565	9	8	close	close	VERB
ajst-18565	9	9	roads	road	NOUN
ajst-18565	9	10	to	to	PART
ajst-18565	9	11	affect	affect	VERB
ajst-18565	9	12	traffic	traffic	NOUN
ajst-18565	9	13	,	,	PUNCT
ajst-18565	9	14	and	and	CCONJ
ajst-18565	9	15	are	be	AUX
ajst-18565	9	16	restricted	restrict	VERB
ajst-18565	9	17	by	by	ADP
ajst-18565	9	18	off	off	ADP
ajst-18565	9	19	-	-	PUNCT
ajst-18565	9	20	site	site	NOUN
ajst-18565	9	21	conditions	condition	NOUN
ajst-18565	9	22	such	such	ADJ
ajst-18565	9	23	as	as	ADP
ajst-18565	9	24	weather	weather	NOUN
ajst-18565	9	25	,	,	PUNCT
ajst-18565	9	26	so	so	CCONJ
ajst-18565	9	27	the	the	DET
ajst-18565	9	28	detection	detection	NOUN
ajst-18565	9	29	cost	cost	NOUN
ajst-18565	9	30	is	be	AUX
ajst-18565	9	31	high	high	ADJ
ajst-18565	9	32	and	and	CCONJ
ajst-18565	9	33	the	the	DET
ajst-18565	9	34	detection	detection	NOUN
ajst-18565	9	35	efficiency	efficiency	NOUN
ajst-18565	9	36	is	be	AUX
ajst-18565	9	37	low	low	ADJ
ajst-18565	9	38	.	.	PUNCT
ajst-18565	10	1	the	the	DET
ajst-18565	10	2	detection	detection	NOUN
ajst-18565	10	3	results	result	NOUN
ajst-18565	10	4	are	be	AUX
ajst-18565	10	5	affected	affect	VERB
ajst-18565	10	6	by	by	ADP
ajst-18565	10	7	subjective	subjective	ADJ
ajst-18565	10	8	factors	factor	NOUN
ajst-18565	10	9	such	such	ADJ
ajst-18565	10	10	as	as	ADP
ajst-18565	10	11	the	the	DET
ajst-18565	10	12	detection	detection	NOUN
ajst-18565	10	13	personnel	personnel	NOUN
ajst-18565	10	14	,	,	PUNCT
ajst-18565	10	15	and	and	CCONJ
ajst-18565	10	16	the	the	DET
ajst-18565	10	17	accuracy	accuracy	NOUN
ajst-18565	10	18	is	be	AUX
ajst-18565	10	19	low	low	ADJ
ajst-18565	10	20	.	.	PUNCT
ajst-18565	11	1	with	with	ADP
ajst-18565	11	2	the	the	DET
ajst-18565	11	3	development	development	NOUN
ajst-18565	11	4	of	of	ADP
ajst-18565	11	5	science	science	NOUN
ajst-18565	11	6	and	and	CCONJ
ajst-18565	11	7	technology	technology	NOUN
ajst-18565	11	8	,	,	PUNCT
ajst-18565	11	9	road	road	NOUN
ajst-18565	11	10	detection	detection	NOUN
ajst-18565	11	11	gradually	gradually	ADV
ajst-18565	11	12	began	begin	VERB
ajst-18565	11	13	to	to	PART
ajst-18565	11	14	use	use	VERB
ajst-18565	11	15	a	a	DET
ajst-18565	11	16	large	large	ADJ
ajst-18565	11	17	number	number	NOUN
ajst-18565	11	18	of	of	ADP
ajst-18565	11	19	fully	fully	ADV
ajst-18565	11	20	automated	automate	VERB
ajst-18565	11	21	detection	detection	NOUN
ajst-18565	11	22	technology	technology	NOUN
ajst-18565	11	23	.	.	PUNCT
ajst-18565	12	1	the	the	DET
ajst-18565	12	2	fully	fully	ADV
ajst-18565	12	3	automated	automate	VERB
ajst-18565	12	4	detection	detection	NOUN
ajst-18565	12	5	technology	technology	NOUN
ajst-18565	12	6	far	far	ADV
ajst-18565	12	7	exceeds	exceed	VERB
ajst-18565	12	8	the	the	DET
ajst-18565	12	9	traditional	traditional	ADJ
ajst-18565	12	10	detection	detection	NOUN
ajst-18565	12	11	technology	technology	NOUN
ajst-18565	12	12	in	in	ADP
ajst-18565	12	13	terms	term	NOUN
ajst-18565	12	14	of	of	ADP
ajst-18565	12	15	speed	speed	NOUN
ajst-18565	12	16	and	and	CCONJ
ajst-18565	12	17	accuracy	accuracy	NOUN
ajst-18565	12	18	,	,	PUNCT
ajst-18565	12	19	and	and	CCONJ
ajst-18565	12	20	the	the	DET
ajst-18565	12	21	detection	detection	NOUN
ajst-18565	12	22	content	content	NOUN
ajst-18565	12	23	is	be	AUX
ajst-18565	12	24	more	more	ADV
ajst-18565	12	25	rich	rich	ADJ
ajst-18565	12	26	and	and	CCONJ
ajst-18565	12	27	detailed	detailed	ADJ
ajst-18565	12	28	.	.	PUNCT
ajst-18565	13	1	with	with	ADP
ajst-18565	13	2	the	the	DET
ajst-18565	13	3	rapid	rapid	ADJ
ajst-18565	13	4	development	development	NOUN
ajst-18565	13	5	of	of	ADP
ajst-18565	13	6	deep	deep	ADJ
ajst-18565	13	7	learning	learning	NOUN
ajst-18565	13	8	,	,	PUNCT
ajst-18565	13	9	scholars	scholar	NOUN
ajst-18565	13	10	in	in	ADP
ajst-18565	13	11	the	the	DET
ajst-18565	13	12	field	field	NOUN
ajst-18565	13	13	of	of	ADP
ajst-18565	13	14	computer	computer	NOUN
ajst-18565	13	15	vision	vision	NOUN
ajst-18565	13	16	have	have	AUX
ajst-18565	13	17	conducted	conduct	VERB
ajst-18565	13	18	research	research	NOUN
ajst-18565	13	19	on	on	ADP
ajst-18565	13	20	pavement	pavement	NOUN
ajst-18565	13	21	disease	disease	NOUN
ajst-18565	13	22	detection	detection	NOUN
ajst-18565	13	23	based	base	VERB
ajst-18565	13	24	on	on	ADP
ajst-18565	13	25	deep	deep	ADJ
ajst-18565	13	26	learning.zhang	learning.zhang	PROPN
ajst-18565	13	27	et	et	PROPN
ajst-18565	13	28	al	al	PROPN
ajst-18565	13	29	.	.	PUNCT
ajst-18565	14	1	[	[	X
ajst-18565	14	2	1	1	X
ajst-18565	14	3	]	]	PUNCT
ajst-18565	14	4	collected	collect	VERB
ajst-18565	14	5	500	500	NUM
ajst-18565	14	6	road	road	NOUN
ajst-18565	14	7	images	image	NOUN
ajst-18565	14	8	of	of	ADP
ajst-18565	14	9	3264×2448	3264×2448	NUM
ajst-18565	14	10	pixels	pixel	NOUN
ajst-18565	14	11	taken	take	VERB
ajst-18565	14	12	by	by	ADP
ajst-18565	14	13	smart	smart	ADJ
ajst-18565	14	14	phones	phone	NOUN
ajst-18565	14	15	,	,	PUNCT
ajst-18565	14	16	divided	divide	VERB
ajst-18565	14	17	them	they	PRON
ajst-18565	14	18	into	into	ADP
ajst-18565	14	19	1	1	NUM
ajst-18565	14	20	million	million	NUM
ajst-18565	14	21	road	road	NOUN
ajst-18565	14	22	image	image	NOUN
ajst-18565	14	23	blocks	block	NOUN
ajst-18565	14	24	of	of	ADP
ajst-18565	14	25	99×99×3	99×99×3	NUM
ajst-18565	14	26	pixels	pixel	NOUN
ajst-18565	14	27	(	(	PUNCT
ajst-18565	14	28	rgb	rgb	PROPN
ajst-18565	14	29	color	color	NOUN
ajst-18565	14	30	images	image	NOUN
ajst-18565	14	31	)	)	PUNCT
ajst-18565	14	32	,	,	PUNCT
ajst-18565	14	33	and	and	CCONJ
ajst-18565	14	34	trained	train	VERB
ajst-18565	14	35	640,000	640,000	NUM
ajst-18565	14	36	images	image	NOUN
ajst-18565	14	37	by	by	ADP
ajst-18565	14	38	using	use	VERB
ajst-18565	14	39	a	a	DET
ajst-18565	14	40	neural	neural	ADJ
ajst-18565	14	41	network	network	NOUN
ajst-18565	14	42	containing	contain	VERB
ajst-18565	14	43	four	four	NUM
ajst-18565	14	44	convolutional	convolutional	ADJ
ajst-18565	14	45	layers	layer	NOUN
ajst-18565	14	46	.	.	PUNCT
ajst-18565	15	1	160,000	160,000	NUM
ajst-18565	15	2	for	for	ADP
ajst-18565	15	3	training	train	VERB
ajst-18565	15	4	validation	validation	NOUN
ajst-18565	15	5	and	and	CCONJ
ajst-18565	15	6	200,000	200,000	NUM
ajst-18565	15	7	for	for	ADP
ajst-18565	15	8	testing	testing	NOUN
ajst-18565	15	9	.	.	PUNCT
ajst-18565	16	1	it	it	PRON
ajst-18565	16	2	is	be	AUX
ajst-18565	16	3	the	the	DET
ajst-18565	16	4	first	first	ADJ
ajst-18565	16	5	time	time	NOUN
ajst-18565	16	6	to	to	PART
ajst-18565	16	7	use	use	VERB
ajst-18565	16	8	deep	deep	ADJ
ajst-18565	16	9	learning	learning	NOUN
ajst-18565	16	10	to	to	PART
ajst-18565	16	11	classify	classify	VERB
ajst-18565	16	12	diseased	diseased	ADJ
ajst-18565	16	13	images	image	NOUN
ajst-18565	16	14	,	,	PUNCT
ajst-18565	16	15	and	and	CCONJ
ajst-18565	16	16	the	the	DET
ajst-18565	16	17	image	image	NOUN
ajst-18565	16	18	blocks	block	NOUN
ajst-18565	16	19	can	can	AUX
ajst-18565	16	20	be	be	AUX
ajst-18565	16	21	quickly	quickly	ADV
ajst-18565	16	22	divided	divide	VERB
ajst-18565	16	23	into	into	ADP
ajst-18565	16	24	two	two	NUM
ajst-18565	16	25	types	type	NOUN
ajst-18565	16	26	with	with	ADP
ajst-18565	16	27	cracks	crack	NOUN
ajst-18565	16	28	and	and	CCONJ
ajst-18565	16	29	without	without	ADP
ajst-18565	16	30	diseases	disease	NOUN
ajst-18565	16	31	.	.	PUNCT
ajst-18565	17	1	the	the	DET
ajst-18565	17	2	recognition	recognition	NOUN
ajst-18565	17	3	accuracy	accuracy	NOUN
ajst-18565	17	4	rate	rate	NOUN
ajst-18565	17	5	is	be	AUX
ajst-18565	17	6	86.96	86.96	NUM
ajst-18565	17	7	%	%	NOUN
ajst-18565	17	8	,	,	PUNCT
ajst-18565	17	9	and	and	CCONJ
ajst-18565	17	10	the	the	DET
ajst-18565	17	11	recall	recall	NOUN
ajst-18565	17	12	rate	rate	NOUN
ajst-18565	17	13	is	be	AUX
ajst-18565	17	14	92.51	92.51	NUM
ajst-18565	17	15	%	%	NOUN
ajst-18565	17	16	.	.	PUNCT
ajst-18565	18	1	the	the	DET
ajst-18565	18	2	classification	classification	NOUN
ajst-18565	18	3	effect	effect	NOUN
ajst-18565	18	4	was	be	AUX
ajst-18565	18	5	significantly	significantly	ADV
ajst-18565	18	6	better	well	ADJ
ajst-18565	18	7	than	than	ADP
ajst-18565	18	8	93	93	NUM
ajst-18565	18	9	-	-	PUNCT
ajst-18565	18	10	dimensional	dimensional	ADJ
ajst-18565	18	11	svm	svm	NOUN
ajst-18565	18	12	and	and	CCONJ
ajst-18565	18	13	boosting	boost	VERB
ajst-18565	18	14	method	method	NOUN
ajst-18565	18	15	in	in	ADP
ajst-18565	18	16	control	control	NOUN
ajst-18565	18	17	group.based	group.base	VERB
ajst-18565	18	18	on	on	ADP
ajst-18565	18	19	yolov3	yolov3	PROPN
ajst-18565	18	20	,	,	PUNCT
ajst-18565	18	21	wang	wang	PROPN
ajst-18565	18	22	et	et	PROPN
ajst-18565	18	23	al.[2	al.[2	PROPN
ajst-18565	18	24	]	]	PUNCT
ajst-18565	18	25	combined	combine	VERB
ajst-18565	18	26	low	low	ADJ
ajst-18565	18	27	-	-	PUNCT
ajst-18565	18	28	level	level	NOUN
ajst-18565	18	29	features	feature	NOUN
ajst-18565	18	30	and	and	CCONJ
ajst-18565	18	31	high	high	ADJ
ajst-18565	18	32	-	-	PUNCT
ajst-18565	18	33	level	level	NOUN
ajst-18565	18	34	features	feature	NOUN
ajst-18565	18	35	to	to	PART
ajst-18565	18	36	enhance	enhance	VERB
ajst-18565	18	37	the	the	DET
ajst-18565	18	38	description	description	NOUN
ajst-18565	18	39	ability	ability	NOUN
ajst-18565	18	40	of	of	ADP
ajst-18565	18	41	the	the	DET
ajst-18565	18	42	network	network	NOUN
ajst-18565	18	43	,	,	PUNCT
ajst-18565	18	44	and	and	CCONJ
ajst-18565	18	45	improved	improve	VERB
ajst-18565	18	46	the	the	DET
ajst-18565	18	47	loss	loss	NOUN
ajst-18565	18	48	function	function	NOUN
ajst-18565	18	49	according	accord	VERB
ajst-18565	18	50	to	to	ADP
ajst-18565	18	51	the	the	DET
ajst-18565	18	52	characteristics	characteristic	NOUN
ajst-18565	18	53	of	of	ADP
ajst-18565	18	54	transverse	transverse	NOUN
ajst-18565	18	55	and	and	CCONJ
ajst-18565	18	56	longitudinal	longitudinal	ADJ
ajst-18565	18	57	crack	crack	NOUN
ajst-18565	18	58	extension	extension	NOUN
ajst-18565	18	59	,	,	PUNCT
ajst-18565	18	60	achieving	achieve	VERB
ajst-18565	18	61	better	well	ADJ
ajst-18565	18	62	results.wan	results.wan	PRON
ajst-18565	18	63	et	et	NOUN
ajst-18565	18	64	al	al	PROPN
ajst-18565	18	65	.	.	PUNCT
ajst-18565	19	1	[	[	X
ajst-18565	19	2	3	3	X
ajst-18565	19	3	]	]	PUNCT
ajst-18565	19	4	proposed	propose	VERB
ajst-18565	19	5	a	a	DET
ajst-18565	19	6	lightweight	lightweight	ADJ
ajst-18565	19	7	road	road	NOUN
ajst-18565	19	8	damage	damage	NOUN
ajst-18565	19	9	recognition	recognition	NOUN
ajst-18565	19	10	model	model	NOUN
ajst-18565	19	11	by	by	ADP
ajst-18565	19	12	enhancing	enhance	VERB
ajst-18565	19	13	the	the	DET
ajst-18565	19	14	yolov5s	yolov5s	PROPN
ajst-18565	19	15	method	method	NOUN
ajst-18565	19	16	.	.	PUNCT
ajst-18565	20	1	their	their	PRON
ajst-18565	20	2	main	main	ADJ
ajst-18565	20	3	work	work	NOUN
ajst-18565	20	4	is	be	AUX
ajst-18565	20	5	to	to	PART
ajst-18565	20	6	add	add	VERB
ajst-18565	20	7	eca	eca	NOUN
ajst-18565	20	8	attention	attention	NOUN
ajst-18565	20	9	module	module	NOUN
ajst-18565	20	10	to	to	ADP
ajst-18565	20	11	the	the	DET
ajst-18565	20	12	lightweight	lightweight	ADJ
ajst-18565	20	13	model	model	NOUN
ajst-18565	20	14	shufflenetv2	shufflenetv2	PROPN
ajst-18565	20	15	,	,	PUNCT
ajst-18565	20	16	improve	improve	VERB
ajst-18565	20	17	the	the	DET
ajst-18565	20	18	detection	detection	NOUN
ajst-18565	20	19	accuracy	accuracy	NOUN
ajst-18565	20	20	while	while	SCONJ
ajst-18565	20	21	lightweight	lightweight	ADJ
ajst-18565	20	22	model	model	NOUN
ajst-18565	20	23	,	,	PUNCT
ajst-18565	20	24	and	and	CCONJ
ajst-18565	20	25	also	also	ADV
ajst-18565	20	26	use	use	VERB
ajst-18565	20	27	bifpn	bifpn	NOUN
ajst-18565	20	28	structure	structure	NOUN
ajst-18565	20	29	instead	instead	ADV
ajst-18565	20	30	of	of	ADP
ajst-18565	20	31	feature	feature	NOUN
ajst-18565	20	32	pyramid	pyramid	NOUN
ajst-18565	20	33	structure	structure	NOUN
ajst-18565	20	34	to	to	PART
ajst-18565	20	35	extract	extract	VERB
ajst-18565	20	36	more	more	ADV
ajst-18565	20	37	rich	rich	ADJ
ajst-18565	20	38	feature	feature	NOUN
ajst-18565	20	39	information	information	NOUN
ajst-18565	20	40	.	.	PUNCT
ajst-18565	21	1	in	in	ADP
ajst-18565	21	2	addition	addition	NOUN
ajst-18565	21	3	,	,	PUNCT
ajst-18565	21	4	in	in	ADP
ajst-18565	21	5	order	order	NOUN
ajst-18565	21	6	to	to	PART
ajst-18565	21	7	correct	correct	VERB
ajst-18565	21	8	the	the	DET
ajst-18565	21	9	imbalance	imbalance	NOUN
ajst-18565	21	10	of	of	ADP
ajst-18565	21	11	samples	sample	NOUN
ajst-18565	21	12	,	,	PUNCT
ajst-18565	21	13	generate	generate	VERB
ajst-18565	21	14	higher	high	ADJ
ajst-18565	21	15	quality	quality	NOUN
ajst-18565	21	16	anchor	anchor	NOUN
ajst-18565	21	17	frame	frame	NOUN
ajst-18565	21	18	.	.	PUNCT
ajst-18565	22	1	they	they	PRON
ajst-18565	22	2	used	use	VERB
ajst-18565	22	3	focal	focal	ADJ
ajst-18565	22	4	-	-	PUNCT
ajst-18565	22	5	eiou	eiou	NOUN
ajst-18565	22	6	as	as	ADP
ajst-18565	22	7	a	a	DET
ajst-18565	22	8	positioning	positioning	NOUN
ajst-18565	22	9	loss	loss	NOUN
ajst-18565	22	10	,	,	PUNCT
ajst-18565	22	11	which	which	PRON
ajst-18565	22	12	provides	provide	VERB
ajst-18565	22	13	superior	superior	ADJ
ajst-18565	22	14	performance	performance	NOUN
ajst-18565	22	15	in	in	ADP
ajst-18565	22	16	both	both	DET
ajst-18565	22	17	accuracy	accuracy	NOUN
ajst-18565	22	18	and	and	CCONJ
ajst-18565	22	19	efficiency.cha	efficiency.cha	PROPN
ajst-18565	22	20	et	et	NOUN
ajst-18565	22	21	al	al	PROPN
ajst-18565	22	22	.	.	PUNCT
ajst-18565	23	1	[	[	X
ajst-18565	23	2	4	4	X
ajst-18565	23	3	]	]	PUNCT
ajst-18565	23	4	proposed	propose	VERB
ajst-18565	23	5	a	a	DET
ajst-18565	23	6	concrete	concrete	ADJ
ajst-18565	23	7	crack	crack	NOUN
ajst-18565	23	8	classifier	classifier	NOUN
ajst-18565	23	9	based	base	VERB
ajst-18565	23	10	on	on	ADP
ajst-18565	23	11	cnn	cnn	PROPN
ajst-18565	23	12	in	in	ADP
ajst-18565	23	13	order	order	NOUN
ajst-18565	23	14	to	to	PART
ajst-18565	23	15	overcome	overcome	VERB
ajst-18565	23	16	the	the	DET
ajst-18565	23	17	influence	influence	NOUN
ajst-18565	23	18	of	of	ADP
ajst-18565	23	19	factors	factor	NOUN
ajst-18565	23	20	such	such	ADJ
ajst-18565	23	21	as	as	ADP
ajst-18565	23	22	light	light	NOUN
ajst-18565	23	23	and	and	CCONJ
ajst-18565	23	24	shadow	shadow	NOUN
ajst-18565	23	25	changes	change	NOUN
ajst-18565	23	26	.	.	PUNCT
ajst-18565	24	1	the	the	DET
ajst-18565	24	2	classifier	classifier	PROPN
ajst-18565	24	3	network	network	NOUN
ajst-18565	24	4	model	model	NOUN
ajst-18565	24	5	has	have	VERB
ajst-18565	24	6	8	8	NUM
ajst-18565	24	7	layers	layer	NOUN
ajst-18565	24	8	(	(	PUNCT
ajst-18565	24	9	4	4	NUM
ajst-18565	24	10	convolutional	convolutional	ADJ
ajst-18565	24	11	layers	layer	NOUN
ajst-18565	24	12	,	,	PUNCT
ajst-18565	24	13	2	2	NUM
ajst-18565	24	14	pooling	pool	VERB
ajst-18565	24	15	layers	layer	NOUN
ajst-18565	24	16	)	)	PUNCT
ajst-18565	24	17	,	,	PUNCT
ajst-18565	24	18	and	and	CCONJ
ajst-18565	24	19	uses	use	VERB
ajst-18565	24	20	sgd	sgd	PROPN
ajst-18565	24	21	algorithm	algorithm	NOUN
ajst-18565	24	22	to	to	PART
ajst-18565	24	23	optimize	optimize	VERB
ajst-18565	24	24	the	the	DET
ajst-18565	24	25	network	network	NOUN
ajst-18565	24	26	.	.	PUNCT
ajst-18565	25	1	the	the	DET
ajst-18565	25	2	output	output	NOUN
ajst-18565	25	3	layer	layer	NOUN
ajst-18565	25	4	uses	use	VERB
ajst-18565	25	5	softmax	softmax	NOUN
ajst-18565	25	6	function	function	NOUN
ajst-18565	25	7	to	to	PART
ajst-18565	25	8	classify	classify	VERB
ajst-18565	25	9	the	the	DET
ajst-18565	25	10	output	output	NOUN
ajst-18565	25	11	detection	detection	NOUN
ajst-18565	25	12	results.nie	results.nie	PUNCT
ajst-18565	25	13	et	et	NOUN
ajst-18565	25	14	al	al	PROPN
ajst-18565	25	15	.	.	PUNCT
ajst-18565	26	1	[	[	X
ajst-18565	26	2	5	5	NUM
ajst-18565	26	3	]	]	PUNCT
ajst-18565	26	4	used	use	VERB
ajst-18565	26	5	the	the	DET
ajst-18565	26	6	faster	fast	ADJ
ajst-18565	26	7	r	r	NOUN
ajst-18565	26	8	-	-	PUNCT
ajst-18565	26	9	cnn	cnn	PROPN
ajst-18565	26	10	target	target	NOUN
ajst-18565	26	11	detection	detection	NOUN
ajst-18565	26	12	model	model	NOUN
ajst-18565	26	13	and	and	CCONJ
ajst-18565	26	14	the	the	DET
ajst-18565	26	15	transfer	transfer	NOUN
ajst-18565	26	16	learning	learning	NOUN
ajst-18565	26	17	method	method	NOUN
ajst-18565	26	18	with	with	ADP
ajst-18565	26	19	parameter	parameter	NOUN
ajst-18565	26	20	finetuning	finetune	VERB
ajst-18565	26	21	to	to	PART
ajst-18565	26	22	complete	complete	VERB
ajst-18565	26	23	the	the	DET
ajst-18565	26	24	task	task	NOUN
ajst-18565	26	25	of	of	ADP
ajst-18565	26	26	road	road	NOUN
ajst-18565	26	27	surface	surface	NOUN
ajst-18565	26	28	damage	damage	NOUN
ajst-18565	26	29	detection.by	detection.by	PRON
ajst-18565	26	30	optimizing	optimize	VERB
ajst-18565	26	31	the	the	DET
ajst-18565	26	32	loss	loss	NOUN
ajst-18565	26	33	function	function	NOUN
ajst-18565	26	34	of	of	ADP
ajst-18565	26	35	the	the	DET
ajst-18565	26	36	ssd	ssd	NOUN
ajst-18565	26	37	algorithm	algorithm	NOUN
ajst-18565	26	38	and	and	CCONJ
ajst-18565	26	39	applying	apply	VERB
ajst-18565	26	40	hierarchical	hierarchical	ADJ
ajst-18565	26	41	convolution	convolution	NOUN
ajst-18565	26	42	to	to	ADP
ajst-18565	26	43	pedestrian	pedestrian	NOUN
ajst-18565	26	44	detection	detection	NOUN
ajst-18565	26	45	,	,	PUNCT
ajst-18565	26	46	yang	yang	PROPN
ajst-18565	26	47	et	et	PROPN
ajst-18565	26	48	al.[6	al.[6	PROPN
ajst-18565	26	49	]	]	PUNCT
ajst-18565	26	50	greatly	greatly	ADV
ajst-18565	26	51	accelerated	accelerate	VERB
ajst-18565	26	52	the	the	DET
ajst-18565	26	53	detection	detection	NOUN
ajst-18565	26	54	speed	speed	NOUN
ajst-18565	26	55	and	and	CCONJ
ajst-18565	26	56	improved	improve	VERB
ajst-18565	26	57	the	the	DET
ajst-18565	26	58	accuracy.by	accuracy.by	PROPN
ajst-18565	26	59	optimizing	optimize	VERB
ajst-18565	26	60	the	the	DET
ajst-18565	26	61	fasterrcnn	fasterrcnn	ADJ
ajst-18565	26	62	model	model	NOUN
ajst-18565	26	63	and	and	CCONJ
ajst-18565	26	64	combining	combine	VERB
ajst-18565	26	65	the	the	DET
ajst-18565	26	66	advantages	advantage	NOUN
ajst-18565	26	67	of	of	ADP
ajst-18565	26	68	vgg16	vgg16	PROPN
ajst-18565	26	69	,	,	PUNCT
ajst-18565	26	70	zfnet	zfnet	PROPN
ajst-18565	26	71	and	and	CCONJ
ajst-18565	26	72	resnet50	resnet50	NOUN
ajst-18565	26	73	networks	network	NOUN
ajst-18565	26	74	,	,	PUNCT
ajst-18565	26	75	sun	sun	PROPN
ajst-18565	26	76	et	et	PROPN
ajst-18565	26	77	al	al	PROPN
ajst-18565	26	78	.	.	PUNCT
ajst-18565	27	1	[	[	X
ajst-18565	27	2	7	7	X
ajst-18565	27	3	]	]	PUNCT
ajst-18565	27	4	proposed	propose	VERB
ajst-18565	27	5	an	an	DET
ajst-18565	27	6	improved	improved	ADJ
ajst-18565	27	7	faster	fast	ADJ
ajst-18565	27	8	-	-	PUNCT
ajst-18565	27	9	rcnn	rcnn	NOUN
ajst-18565	27	10	model	model	NOUN
ajst-18565	27	11	based	base	VERB
ajst-18565	27	12	on	on	ADP
ajst-18565	27	13	pavement	pavement	NOUN
ajst-18565	27	14	potsealing	potsealing	NOUN
ajst-18565	27	15	crack	crack	NOUN
ajst-18565	27	16	detection	detection	NOUN
ajst-18565	27	17	method	method	NOUN
ajst-18565	27	18	,	,	PUNCT
ajst-18565	27	19	thus	thus	ADV
ajst-18565	27	20	significantly	significantly	ADV
ajst-18565	27	21	improving	improve	VERB
ajst-18565	27	22	the	the	DET
ajst-18565	27	23	positioning	positioning	NOUN
ajst-18565	27	24	accuracy	accuracy	NOUN
ajst-18565	27	25	and	and	CCONJ
ajst-18565	27	26	the	the	DET
ajst-18565	27	27	accuracy	accuracy	NOUN
ajst-18565	27	28	of	of	ADP
ajst-18565	27	29	test	test	NOUN
ajst-18565	27	30	results.gu	results.gu	X
ajst-18565	28	1	[	[	X
ajst-18565	28	2	8	8	NUM
ajst-18565	28	3	]	]	PUNCT
ajst-18565	28	4	et	et	PROPN
ajst-18565	28	5	al	al	PROPN
ajst-18565	28	6	.	.	PROPN
ajst-18565	28	7	proposed	propose	VERB
ajst-18565	28	8	an	an	DET
ajst-18565	28	9	automatic	automatic	ADJ
ajst-18565	28	10	crack	crack	NOUN
ajst-18565	28	11	detection	detection	NOUN
ajst-18565	28	12	algorithm	algorithm	NOUN
ajst-18565	28	13	,	,	PUNCT
ajst-18565	28	14	which	which	PRON
ajst-18565	28	15	enhances	enhance	VERB
ajst-18565	28	16	the	the	DET
ajst-18565	28	17	fusion	fusion	NOUN
ajst-18565	28	18	of	of	ADP
ajst-18565	28	19	semantic	semantic	ADJ
ajst-18565	28	20	information	information	NOUN
ajst-18565	28	21	and	and	CCONJ
ajst-18565	28	22	multichannel	multichannel	NOUN
ajst-18565	28	23	features	feature	NOUN
ajst-18565	28	24	,	,	PUNCT
ajst-18565	28	25	and	and	CCONJ
ajst-18565	28	26	introduces	introduce	VERB
ajst-18565	28	27	extended	extend	VERB
ajst-18565	28	28	convolution	convolution	NOUN
ajst-18565	28	29	module	module	NOUN
ajst-18565	28	30	and	and	CCONJ
ajst-18565	28	31	attention	attention	NOUN
ajst-18565	28	32	mechanism	mechanism	NOUN
ajst-18565	28	33	to	to	PART
ajst-18565	28	34	improve	improve	VERB
ajst-18565	28	35	the	the	DET
ajst-18565	28	36	model	model	NOUN
ajst-18565	28	37	's	's	PART
ajst-18565	28	38	ability	ability	NOUN
ajst-18565	28	39	to	to	PART
ajst-18565	28	40	extract	extract	VERB
ajst-18565	28	41	feature	feature	NOUN
ajst-18565	28	42	details.deep	details.deep	NOUN
ajst-18565	28	43	learning	learn	VERB
ajst-18565	28	44	has	have	AUX
ajst-18565	28	45	shown	show	VERB
ajst-18565	28	46	absolute	absolute	ADJ
ajst-18565	28	47	advantages	advantage	NOUN
ajst-18565	28	48	in	in	ADP
ajst-18565	28	49	the	the	DET
ajst-18565	28	50	field	field	NOUN
ajst-18565	28	51	of	of	ADP
ajst-18565	28	52	image	image	NOUN
ajst-18565	28	53	recognition	recognition	NOUN
ajst-18565	28	54	.	.	PUNCT
ajst-18565	29	1	deep	deep	ADJ
ajst-18565	29	2	convolutional	convolutional	ADJ
ajst-18565	29	3	neural	neural	ADJ
ajst-18565	29	4	network	network	NOUN
ajst-18565	29	5	can	can	AUX
ajst-18565	29	6	extract	extract	VERB
ajst-18565	29	7	high	high	ADJ
ajst-18565	29	8	-	-	PUNCT
ajst-18565	29	9	level	level	NOUN
ajst-18565	29	10	semantic	semantic	ADJ
ajst-18565	29	11	features	feature	NOUN
ajst-18565	29	12	of	of	ADP
ajst-18565	29	13	images	image	NOUN
ajst-18565	29	14	and	and	CCONJ
ajst-18565	29	15	realize	realize	VERB
ajst-18565	29	16	automatic	automatic	ADJ
ajst-18565	29	17	recognition	recognition	NOUN
ajst-18565	29	18	of	of	ADP
ajst-18565	29	19	input	input	NOUN
ajst-18565	29	20	images	image	NOUN
ajst-18565	29	21	without	without	ADP
ajst-18565	29	22	preprocessing	preprocesse	VERB
ajst-18565	29	23	input	input	NOUN
ajst-18565	29	24	features	feature	NOUN
ajst-18565	29	25	.	.	PUNCT
ajst-18565	30	1	compared	compare	VERB
ajst-18565	30	2	with	with	ADP
ajst-18565	30	3	traditional	traditional	ADJ
ajst-18565	30	4	image	image	NOUN
ajst-18565	30	5	recognition	recognition	NOUN
ajst-18565	30	6	methods	method	NOUN
ajst-18565	30	7	,	,	PUNCT
ajst-18565	30	8	the	the	DET
ajst-18565	30	9	effect	effect	NOUN
ajst-18565	30	10	is	be	AUX
ajst-18565	30	11	better	well	ADJ
ajst-18565	30	12	.	.	PUNCT
ajst-18565	31	1	this	this	DET
ajst-18565	31	2	paper	paper	NOUN
ajst-18565	31	3	proposes	propose	VERB
ajst-18565	31	4	a	a	DET
ajst-18565	31	5	road	road	NOUN
ajst-18565	31	6	damage	damage	NOUN
ajst-18565	31	7	detection	detection	NOUN
ajst-18565	31	8	method	method	NOUN
ajst-18565	31	9	based	base	VERB
ajst-18565	31	10	on	on	ADP
ajst-18565	31	11	improved	improved	ADJ
ajst-18565	31	12	yolov8n	yolov8n	NOUN
ajst-18565	31	13	:	:	PUNCT
ajst-18565	31	14	(	(	PUNCT
ajst-18565	31	15	1	1	X
ajst-18565	31	16	)	)	PUNCT
ajst-18565	31	17	based	base	VERB
ajst-18565	31	18	on	on	ADP
ajst-18565	31	19	the	the	DET
ajst-18565	31	20	traditional	traditional	ADJ
ajst-18565	31	21	yolov8n	yolov8n	NOUN
ajst-18565	31	22	model	model	NOUN
ajst-18565	31	23	,	,	PUNCT
ajst-18565	31	24	senetv2[9	senetv2[9	PROPN
ajst-18565	31	25	]	]	PUNCT
ajst-18565	31	26	attention	attention	NOUN
ajst-18565	31	27	mechanism	mechanism	NOUN
ajst-18565	31	28	is	be	AUX
ajst-18565	31	29	introduced	introduce	VERB
ajst-18565	31	30	in	in	ADP
ajst-18565	31	31	backbone	backbone	NOUN
ajst-18565	31	32	to	to	PART
ajst-18565	31	33	improve	improve	VERB
ajst-18565	31	34	detection	detection	NOUN
ajst-18565	31	35	accuracy	accuracy	NOUN
ajst-18565	31	36	.	.	PUNCT
ajst-18565	32	1	(	(	PUNCT
ajst-18565	32	2	2	2	X
ajst-18565	32	3	)	)	PUNCT
ajst-18565	32	4	gsconv[10	gsconv[10	NOUN
ajst-18565	32	5	]	]	PUNCT
ajst-18565	32	6	is	be	AUX
ajst-18565	32	7	added	add	VERB
ajst-18565	32	8	to	to	ADP
ajst-18565	32	9	neck	neck	VERB
ajst-18565	32	10	to	to	PART
ajst-18565	32	11	replace	replace	VERB
ajst-18565	32	12	ordinary	ordinary	ADJ
ajst-18565	32	13	convolution	convolution	NOUN
ajst-18565	32	14	,	,	PUNCT
ajst-18565	32	15	reducing	reduce	VERB
ajst-18565	32	16	the	the	DET
ajst-18565	32	17	complexity	complexity	NOUN
ajst-18565	32	18	of	of	ADP
ajst-18565	32	19	the	the	DET
ajst-18565	32	20	model	model	NOUN
ajst-18565	32	21	and	and	CCONJ
ajst-18565	32	22	improving	improve	VERB
ajst-18565	32	23	the	the	DET
ajst-18565	32	24	accuracy	accuracy	NOUN
ajst-18565	32	25	.	.	PUNCT
ajst-18565	33	1	(	(	PUNCT
ajst-18565	33	2	3	3	X
ajst-18565	33	3	)	)	PUNCT
ajst-18565	33	4	use	use	VERB
ajst-18565	33	5	wise	wise	ADJ
ajst-18565	33	6	-	-	PUNCT
ajst-18565	33	7	iou[11	iou[11	NOUN
ajst-18565	33	8	]	]	PUNCT
ajst-18565	33	9	loss	loss	NOUN
ajst-18565	33	10	function	function	NOUN
ajst-18565	33	11	instead	instead	ADV
ajst-18565	33	12	of	of	ADP
ajst-18565	33	13	ciou	ciou	NOUN
ajst-18565	33	14	function	function	NOUN
ajst-18565	33	15	to	to	PART
ajst-18565	33	16	reduce	reduce	VERB
ajst-18565	33	17	the	the	DET
ajst-18565	33	18	impact	impact	NOUN
ajst-18565	33	19	of	of	ADP
ajst-18565	33	20	a	a	DET
ajst-18565	33	21	small	small	ADJ
ajst-18565	33	22	number	number	NOUN
ajst-18565	33	23	of	of	ADP
ajst-18565	33	24	lowquality	lowquality	NOUN
ajst-18565	33	25	data	datum	NOUN
ajst-18565	33	26	instances	instance	NOUN
ajst-18565	33	27	on	on	ADP
ajst-18565	33	28	detection	detection	NOUN
ajst-18565	33	29	.	.	PUNCT
ajst-18565	34	1	163	163	NUM
ajst-18565	34	2	2	2	NUM
ajst-18565	34	3	.	.	PUNCT
ajst-18565	34	4	algorithm	algorithm	NOUN
ajst-18565	34	5	based	base	VERB
ajst-18565	34	6	on	on	ADP
ajst-18565	34	7	yolov8	yolov8	PROPN
ajst-18565	34	8	yolo	yolo	PROPN
ajst-18565	34	9	series	series	PROPN
ajst-18565	34	10	target	target	NOUN
ajst-18565	34	11	detection	detection	NOUN
ajst-18565	34	12	algorithm	algorithm	NOUN
ajst-18565	34	13	has	have	AUX
ajst-18565	34	14	been	be	AUX
ajst-18565	34	15	widely	widely	ADV
ajst-18565	34	16	used	use	VERB
ajst-18565	34	17	in	in	ADP
ajst-18565	34	18	pavement	pavement	NOUN
ajst-18565	34	19	damage	damage	NOUN
ajst-18565	34	20	target	target	NOUN
ajst-18565	34	21	detection	detection	NOUN
ajst-18565	34	22	because	because	SCONJ
ajst-18565	34	23	of	of	ADP
ajst-18565	34	24	its	its	PRON
ajst-18565	34	25	advantages	advantage	NOUN
ajst-18565	34	26	of	of	ADP
ajst-18565	34	27	high	high	ADJ
ajst-18565	34	28	accuracy	accuracy	NOUN
ajst-18565	34	29	and	and	CCONJ
ajst-18565	34	30	fast	fast	ADJ
ajst-18565	34	31	detection	detection	NOUN
ajst-18565	34	32	speed	speed	NOUN
ajst-18565	34	33	.	.	PUNCT
ajst-18565	35	1	at	at	ADP
ajst-18565	35	2	present	present	ADJ
ajst-18565	35	3	,	,	PUNCT
ajst-18565	35	4	yolo	yolo	ADJ
ajst-18565	35	5	algorithm	algorithm	NOUN
ajst-18565	35	6	has	have	AUX
ajst-18565	35	7	been	be	AUX
ajst-18565	35	8	upgraded	upgrade	VERB
ajst-18565	35	9	to	to	ADP
ajst-18565	35	10	yolov8	yolov8	PROPN
ajst-18565	35	11	,	,	PUNCT
ajst-18565	35	12	which	which	PRON
ajst-18565	35	13	further	far	ADV
ajst-18565	35	14	optimizes	optimize	VERB
ajst-18565	35	15	the	the	DET
ajst-18565	35	16	network	network	NOUN
ajst-18565	35	17	structure	structure	NOUN
ajst-18565	35	18	and	and	CCONJ
ajst-18565	35	19	enhances	enhance	VERB
ajst-18565	35	20	the	the	DET
ajst-18565	35	21	performance	performance	NOUN
ajst-18565	35	22	of	of	ADP
ajst-18565	35	23	the	the	DET
ajst-18565	35	24	model	model	NOUN
ajst-18565	35	25	.	.	PUNCT
ajst-18565	36	1	this	this	DET
ajst-18565	36	2	paper	paper	NOUN
ajst-18565	36	3	takes	take	VERB
ajst-18565	36	4	yolov8n	yolov8n	PROPN
ajst-18565	36	5	as	as	ADP
ajst-18565	36	6	the	the	DET
ajst-18565	36	7	base	base	NOUN
ajst-18565	36	8	model	model	NOUN
ajst-18565	36	9	.	.	PUNCT
ajst-18565	37	1	in	in	ADP
ajst-18565	37	2	order	order	NOUN
ajst-18565	37	3	to	to	PART
ajst-18565	37	4	improve	improve	VERB
ajst-18565	37	5	the	the	DET
ajst-18565	37	6	detection	detection	NOUN
ajst-18565	37	7	accuracy	accuracy	NOUN
ajst-18565	37	8	of	of	ADP
ajst-18565	37	9	the	the	DET
ajst-18565	37	10	model	model	NOUN
ajst-18565	37	11	,	,	PUNCT
ajst-18565	37	12	a	a	DET
ajst-18565	37	13	road	road	NOUN
ajst-18565	37	14	surface	surface	NOUN
ajst-18565	37	15	damage	damage	NOUN
ajst-18565	37	16	detection	detection	NOUN
ajst-18565	37	17	algorithm	algorithm	NOUN
ajst-18565	37	18	based	base	VERB
ajst-18565	37	19	on	on	ADP
ajst-18565	37	20	improved	improved	ADJ
ajst-18565	37	21	yolov8	yolov8	NOUN
ajst-18565	37	22	is	be	AUX
ajst-18565	37	23	studied	study	VERB
ajst-18565	37	24	2.1	2.1	NUM
ajst-18565	37	25	.	.	PUNCT
ajst-18565	38	1	yolov8	yolov8	NOUN
ajst-18565	38	2	network	network	NOUN
ajst-18565	38	3	structure	structure	NOUN
ajst-18565	38	4	yolov8	yolov8	PROPN
ajst-18565	38	5	is	be	AUX
ajst-18565	38	6	an	an	DET
ajst-18565	38	7	object	object	NOUN
ajst-18565	38	8	detection	detection	NOUN
ajst-18565	38	9	model	model	NOUN
ajst-18565	38	10	composed	compose	VERB
ajst-18565	38	11	of	of	ADP
ajst-18565	38	12	four	four	NUM
ajst-18565	38	13	main	main	ADJ
ajst-18565	38	14	components	component	NOUN
ajst-18565	38	15	:	:	PUNCT
ajst-18565	38	16	input	input	NOUN
ajst-18565	38	17	,	,	PUNCT
ajst-18565	38	18	backbone	backbone	NOUN
ajst-18565	38	19	,	,	PUNCT
ajst-18565	38	20	neck	neck	NOUN
ajst-18565	38	21	and	and	CCONJ
ajst-18565	38	22	head	head	NOUN
ajst-18565	38	23	.	.	PUNCT
ajst-18565	39	1	yolov8	yolov8	NOUN
ajst-18565	39	2	network	network	NOUN
ajst-18565	39	3	integrates	integrate	VERB
ajst-18565	39	4	many	many	ADJ
ajst-18565	39	5	advantages	advantage	NOUN
ajst-18565	39	6	of	of	ADP
ajst-18565	39	7	target	target	NOUN
ajst-18565	39	8	detection	detection	NOUN
ajst-18565	39	9	models	model	NOUN
ajst-18565	39	10	,	,	PUNCT
ajst-18565	39	11	retains	retain	VERB
ajst-18565	39	12	the	the	DET
ajst-18565	39	13	csp	csp	PROPN
ajst-18565	39	14	idea	idea	NOUN
ajst-18565	39	15	of	of	ADP
ajst-18565	39	16	yolov5	yolov5	NOUN
ajst-18565	39	17	,	,	PUNCT
ajst-18565	39	18	and	and	CCONJ
ajst-18565	39	19	still	still	ADV
ajst-18565	39	20	adopts	adopt	VERB
ajst-18565	39	21	the	the	DET
ajst-18565	39	22	feature	feature	NOUN
ajst-18565	39	23	fusion	fusion	NOUN
ajst-18565	39	24	methods	method	NOUN
ajst-18565	39	25	of	of	ADP
ajst-18565	39	26	fpn	fpn	NOUN
ajst-18565	39	27	-	-	PUNCT
ajst-18565	39	28	pan	pan	NOUN
ajst-18565	39	29	and	and	CCONJ
ajst-18565	39	30	sppf	sppf	ADJ
ajst-18565	39	31	.	.	PUNCT
ajst-18565	40	1	compared	compare	VERB
ajst-18565	40	2	with	with	ADP
ajst-18565	40	3	yolov5	yolov5	NOUN
ajst-18565	40	4	,	,	PUNCT
ajst-18565	40	5	there	there	PRON
ajst-18565	40	6	are	be	VERB
ajst-18565	40	7	mainly	mainly	ADV
ajst-18565	40	8	improvements	improvement	NOUN
ajst-18565	40	9	in	in	ADP
ajst-18565	40	10	the	the	DET
ajst-18565	40	11	following	follow	VERB
ajst-18565	40	12	aspects	aspect	NOUN
ajst-18565	40	13	:	:	PUNCT
ajst-18565	40	14	first	first	ADV
ajst-18565	40	15	,	,	PUNCT
ajst-18565	40	16	in	in	ADP
ajst-18565	40	17	order	order	NOUN
ajst-18565	40	18	to	to	PART
ajst-18565	40	19	meet	meet	VERB
ajst-18565	40	20	the	the	DET
ajst-18565	40	21	needs	need	NOUN
ajst-18565	40	22	of	of	ADP
ajst-18565	40	23	more	more	ADJ
ajst-18565	40	24	scenarios	scenario	NOUN
ajst-18565	40	25	,	,	PUNCT
ajst-18565	40	26	more	more	ADJ
ajst-18565	40	27	size	size	NOUN
ajst-18565	40	28	models	model	NOUN
ajst-18565	40	29	are	be	AUX
ajst-18565	40	30	designed	design	VERB
ajst-18565	40	31	.	.	PUNCT
ajst-18565	41	1	a	a	DET
ajst-18565	41	2	target	target	NOUN
ajst-18565	41	3	detection	detection	NOUN
ajst-18565	41	4	network	network	NOUN
ajst-18565	41	5	with	with	ADP
ajst-18565	41	6	a	a	DET
ajst-18565	41	7	resolution	resolution	NOUN
ajst-18565	41	8	of	of	ADP
ajst-18565	41	9	640×640	640×640	NUM
ajst-18565	41	10	p5	p5	ADJ
ajst-18565	41	11	and	and	CCONJ
ajst-18565	41	12	1280×1280	1280×1280	NUM
ajst-18565	41	13	p6	p6	NOUN
ajst-18565	41	14	is	be	AUX
ajst-18565	41	15	provided	provide	VERB
ajst-18565	41	16	.	.	PUNCT
ajst-18565	42	1	secondly	secondly	ADV
ajst-18565	42	2	,	,	PUNCT
ajst-18565	42	3	we	we	PRON
ajst-18565	42	4	design	design	VERB
ajst-18565	42	5	a	a	DET
ajst-18565	42	6	c2f	c2f	NOUN
ajst-18565	42	7	(	(	PUNCT
ajst-18565	42	8	convolution	convolution	NOUN
ajst-18565	42	9	block	block	NOUN
ajst-18565	42	10	)	)	PUNCT
ajst-18565	42	11	module	module	NOUN
ajst-18565	42	12	similar	similar	ADJ
ajst-18565	42	13	to	to	ADP
ajst-18565	42	14	elan	elan	PROPN
ajst-18565	42	15	(	(	PUNCT
ajst-18565	42	16	high	high	ADJ
ajst-18565	42	17	efficiency	efficiency	NOUN
ajst-18565	42	18	layer	layer	NOUN
ajst-18565	42	19	aggregation	aggregation	NOUN
ajst-18565	42	20	network	network	NOUN
ajst-18565	42	21	)	)	PUNCT
ajst-18565	42	22	structure	structure	NOUN
ajst-18565	42	23	,	,	PUNCT
ajst-18565	42	24	and	and	CCONJ
ajst-18565	42	25	replace	replace	VERB
ajst-18565	42	26	all	all	DET
ajst-18565	42	27	c3	c3	NOUN
ajst-18565	42	28	modules	module	NOUN
ajst-18565	42	29	with	with	ADP
ajst-18565	42	30	c2f	c2f	NOUN
ajst-18565	42	31	modules	module	NOUN
ajst-18565	42	32	.	.	PUNCT
ajst-18565	43	1	two	two	NUM
ajst-18565	43	2	convolutional	convolutional	ADJ
ajst-18565	43	3	connection	connection	NOUN
ajst-18565	43	4	layers	layer	NOUN
ajst-18565	43	5	in	in	ADP
ajst-18565	43	6	the	the	DET
ajst-18565	43	7	neck	neck	NOUN
ajst-18565	43	8	module	module	NOUN
ajst-18565	43	9	were	be	AUX
ajst-18565	43	10	removed	remove	VERB
ajst-18565	43	11	.	.	PUNCT
ajst-18565	44	1	the	the	DET
ajst-18565	44	2	head	head	NOUN
ajst-18565	44	3	part	part	NOUN
ajst-18565	44	4	is	be	AUX
ajst-18565	44	5	changed	change	VERB
ajst-18565	44	6	from	from	ADP
ajst-18565	44	7	the	the	DET
ajst-18565	44	8	coupling	coupling	NOUN
ajst-18565	44	9	detection	detection	NOUN
ajst-18565	44	10	head	head	NOUN
ajst-18565	44	11	to	to	ADP
ajst-18565	44	12	the	the	DET
ajst-18565	44	13	structure	structure	NOUN
ajst-18565	44	14	detection	detection	NOUN
ajst-18565	44	15	head	head	NOUN
ajst-18565	44	16	,	,	PUNCT
ajst-18565	44	17	using	use	VERB
ajst-18565	44	18	anchor	anchor	NOUN
ajst-18565	44	19	-	-	PUNCT
ajst-18565	44	20	free	free	ADJ
ajst-18565	44	21	instead	instead	ADV
ajst-18565	44	22	of	of	ADP
ajst-18565	44	23	anchor	anchor	NOUN
ajst-18565	44	24	-	-	PUNCT
ajst-18565	44	25	based	base	VERB
ajst-18565	44	26	.	.	PUNCT
ajst-18565	45	1	the	the	DET
ajst-18565	45	2	yolov8	yolov8	NOUN
ajst-18565	45	3	structure	structure	NOUN
ajst-18565	45	4	is	be	AUX
ajst-18565	45	5	shown	show	VERB
ajst-18565	45	6	in	in	ADP
ajst-18565	45	7	the	the	DET
ajst-18565	45	8	figure	figure	NOUN
ajst-18565	45	9	.	.	PUNCT
ajst-18565	46	1	figure	figure	NOUN
ajst-18565	46	2	1	1	NUM
ajst-18565	46	3	.	.	PUNCT
ajst-18565	47	1	yolov8	yolov8	NOUN
ajst-18565	47	2	structure	structure	PROPN
ajst-18565	47	3	diagram	diagram	PROPN
ajst-18565	47	4	2.2	2.2	NUM
ajst-18565	47	5	.	.	PUNCT
ajst-18565	48	1	improved	improve	VERB
ajst-18565	48	2	algorithm	algorithm	NOUN
ajst-18565	48	3	based	base	VERB
ajst-18565	48	4	on	on	ADP
ajst-18565	48	5	yolov8	yolov8	NOUN
ajst-18565	48	6	2.2.1	2.2.1	NUM
ajst-18565	48	7	.	.	PUNCT
ajst-18565	49	1	attention	attention	NOUN
ajst-18565	49	2	mechanism	mechanism	NOUN
ajst-18565	49	3	attention	attention	NOUN
ajst-18565	49	4	mechanisms	mechanism	NOUN
ajst-18565	49	5	have	have	AUX
ajst-18565	49	6	been	be	AUX
ajst-18565	49	7	widely	widely	ADV
ajst-18565	49	8	used	use	VERB
ajst-18565	49	9	in	in	ADP
ajst-18565	49	10	deep	deep	ADJ
ajst-18565	49	11	learning	learn	VERB
ajst-18565	49	12	convolutional	convolutional	ADJ
ajst-18565	49	13	neural	neural	ADJ
ajst-18565	49	14	networks	network	NOUN
ajst-18565	49	15	.	.	PUNCT
ajst-18565	50	1	by	by	ADP
ajst-18565	50	2	introducing	introduce	VERB
ajst-18565	50	3	the	the	DET
ajst-18565	50	4	attention	attention	NOUN
ajst-18565	50	5	mechanism	mechanism	NOUN
ajst-18565	50	6	,	,	PUNCT
ajst-18565	50	7	the	the	DET
ajst-18565	50	8	network	network	NOUN
ajst-18565	50	9	can	can	AUX
ajst-18565	50	10	obtain	obtain	VERB
ajst-18565	50	11	the	the	DET
ajst-18565	50	12	importance	importance	NOUN
ajst-18565	50	13	of	of	ADP
ajst-18565	50	14	each	each	DET
ajst-18565	50	15	feature	feature	NOUN
ajst-18565	50	16	map	map	NOUN
ajst-18565	50	17	and	and	CCONJ
ajst-18565	50	18	generate	generate	VERB
ajst-18565	50	19	the	the	DET
ajst-18565	50	20	corresponding	corresponding	ADJ
ajst-18565	50	21	weight	weight	NOUN
ajst-18565	50	22	.	.	PUNCT
ajst-18565	51	1	using	use	VERB
ajst-18565	51	2	the	the	DET
ajst-18565	51	3	detection	detection	NOUN
ajst-18565	51	4	results	result	NOUN
ajst-18565	51	5	to	to	PART
ajst-18565	51	6	guide	guide	VERB
ajst-18565	51	7	the	the	DET
ajst-18565	51	8	feature	feature	NOUN
ajst-18565	51	9	map	map	NOUN
ajst-18565	51	10	weights	weight	NOUN
ajst-18565	51	11	in	in	ADP
ajst-18565	51	12	reverse	reverse	NOUN
ajst-18565	51	13	,	,	PUNCT
ajst-18565	51	14	the	the	DET
ajst-18565	51	15	model	model	NOUN
ajst-18565	51	16	can	can	AUX
ajst-18565	51	17	put	put	VERB
ajst-18565	51	18	more	more	ADJ
ajst-18565	51	19	emphasis	emphasis	NOUN
ajst-18565	51	20	on	on	ADP
ajst-18565	51	21	the	the	DET
ajst-18565	51	22	useful	useful	ADJ
ajst-18565	51	23	spaces	space	NOUN
ajst-18565	51	24	in	in	ADP
ajst-18565	51	25	the	the	DET
ajst-18565	51	26	image	image	NOUN
ajst-18565	51	27	and	and	CCONJ
ajst-18565	51	28	focus	focus	VERB
ajst-18565	51	29	attention	attention	NOUN
ajst-18565	51	30	on	on	ADP
ajst-18565	51	31	these	these	DET
ajst-18565	51	32	areas	area	NOUN
ajst-18565	51	33	when	when	SCONJ
ajst-18565	51	34	processing	process	VERB
ajst-18565	51	35	the	the	DET
ajst-18565	51	36	task	task	NOUN
ajst-18565	51	37	.	.	PUNCT
ajst-18565	52	1	at	at	ADP
ajst-18565	52	2	the	the	DET
ajst-18565	52	3	same	same	ADJ
ajst-18565	52	4	time	time	NOUN
ajst-18565	52	5	,	,	PUNCT
ajst-18565	52	6	irrelevant	irrelevant	ADJ
ajst-18565	52	7	features	feature	NOUN
ajst-18565	52	8	are	be	AUX
ajst-18565	52	9	suppressed	suppress	VERB
ajst-18565	52	10	,	,	PUNCT
ajst-18565	52	11	which	which	PRON
ajst-18565	52	12	improves	improve	VERB
ajst-18565	52	13	processing	processing	NOUN
ajst-18565	52	14	efficiency	efficiency	NOUN
ajst-18565	52	15	.	.	PUNCT
ajst-18565	53	1	this	this	DET
ajst-18565	53	2	approach	approach	NOUN
ajst-18565	53	3	allows	allow	VERB
ajst-18565	53	4	the	the	DET
ajst-18565	53	5	network	network	NOUN
ajst-18565	53	6	to	to	PART
ajst-18565	53	7	focus	focus	VERB
ajst-18565	53	8	more	more	ADV
ajst-18565	53	9	on	on	ADP
ajst-18565	53	10	critical	critical	ADJ
ajst-18565	53	11	information	information	NOUN
ajst-18565	53	12	,	,	PUNCT
ajst-18565	53	13	improving	improve	VERB
ajst-18565	53	14	the	the	DET
ajst-18565	53	15	efficiency	efficiency	NOUN
ajst-18565	53	16	and	and	CCONJ
ajst-18565	53	17	accuracy	accuracy	NOUN
ajst-18565	53	18	of	of	ADP
ajst-18565	53	19	task	task	NOUN
ajst-18565	53	20	processing	processing	NOUN
ajst-18565	53	21	.	.	PUNCT
ajst-18565	54	1	senetv2	senetv2	PROPN
ajst-18565	54	2	is	be	AUX
ajst-18565	54	3	an	an	DET
ajst-18565	54	4	improved	improved	ADJ
ajst-18565	54	5	senet	senet	NOUN
ajst-18565	54	6	module	module	NOUN
ajst-18565	54	7	,	,	PUNCT
ajst-18565	54	8	which	which	PRON
ajst-18565	54	9	improves	improve	VERB
ajst-18565	54	10	the	the	DET
ajst-18565	54	11	expression	expression	NOUN
ajst-18565	54	12	capability	capability	NOUN
ajst-18565	54	13	of	of	ADP
ajst-18565	54	14	the	the	DET
ajst-18565	54	15	network	network	NOUN
ajst-18565	54	16	by	by	ADP
ajst-18565	54	17	introducing	introduce	VERB
ajst-18565	54	18	squeeze	squeeze	NOUN
ajst-18565	54	19	aggregated	aggregate	VERB
ajst-18565	54	20	excitation	excitation	NOUN
ajst-18565	54	21	(	(	PUNCT
ajst-18565	54	22	sae	sae	PROPN
ajst-18565	54	23	)	)	PUNCT
ajst-18565	54	24	module	module	NOUN
ajst-18565	54	25	.	.	PUNCT
ajst-18565	55	1	the	the	DET
ajst-18565	55	2	sae	sae	PROPN
ajst-18565	55	3	module	module	NOUN
ajst-18565	55	4	combines	combine	VERB
ajst-18565	55	5	the	the	DET
ajst-18565	55	6	two	two	NUM
ajst-18565	55	7	operations	operation	NOUN
ajst-18565	55	8	of	of	ADP
ajst-18565	55	9	squeezing	squeeze	VERB
ajst-18565	55	10	and	and	CCONJ
ajst-18565	55	11	excitation	excitation	NOUN
ajst-18565	55	12	,	,	PUNCT
ajst-18565	55	13	and	and	CCONJ
ajst-18565	55	14	enhances	enhance	VERB
ajst-18565	55	15	the	the	DET
ajst-18565	55	16	learning	learning	NOUN
ajst-18565	55	17	ability	ability	NOUN
ajst-18565	55	18	of	of	ADP
ajst-18565	55	19	the	the	DET
ajst-18565	55	20	network	network	NOUN
ajst-18565	55	21	through	through	ADP
ajst-18565	55	22	multiple	multiple	ADJ
ajst-18565	55	23	branches	branch	NOUN
ajst-18565	55	24	.	.	PUNCT
ajst-18565	56	1	senetv2	senetv2	PROPN
ajst-18565	56	2	can	can	AUX
ajst-18565	56	3	greatly	greatly	ADV
ajst-18565	56	4	improve	improve	VERB
ajst-18565	56	5	the	the	DET
ajst-18565	56	6	detection	detection	NOUN
ajst-18565	56	7	accuracy	accuracy	NOUN
ajst-18565	56	8	and	and	CCONJ
ajst-18565	56	9	effectively	effectively	ADV
ajst-18565	56	10	improve	improve	VERB
ajst-18565	56	11	the	the	DET
ajst-18565	56	12	performance	performance	NOUN
ajst-18565	56	13	of	of	ADP
ajst-18565	56	14	the	the	DET
ajst-18565	56	15	model	model	NOUN
ajst-18565	56	16	while	while	SCONJ
ajst-18565	56	17	slightly	slightly	ADV
ajst-18565	56	18	increasing	increase	VERB
ajst-18565	56	19	the	the	DET
ajst-18565	56	20	number	number	NOUN
ajst-18565	56	21	of	of	ADP
ajst-18565	56	22	model	model	NOUN
ajst-18565	56	23	parameters	parameter	NOUN
ajst-18565	56	24	.	.	PUNCT
ajst-18565	57	1	the	the	DET
ajst-18565	57	2	fig	fig	NOUN
ajst-18565	57	3	.	.	PUNCT
ajst-18565	57	4	2	2	NUM
ajst-18565	57	5	shows	show	VERB
ajst-18565	57	6	the	the	DET
ajst-18565	57	7	comparison	comparison	NOUN
ajst-18565	57	8	of	of	ADP
ajst-18565	57	9	the	the	DET
ajst-18565	57	10	three	three	NUM
ajst-18565	57	11	network	network	NOUN
ajst-18565	57	12	modules	module	NOUN
ajst-18565	57	13	.	.	PUNCT
ajst-18565	58	1	figure	figure	NOUN
ajst-18565	58	2	2	2	NUM
ajst-18565	58	3	.	.	PUNCT
ajst-18565	58	4	attention	attention	NOUN
ajst-18565	58	5	mechanism	mechanism	NOUN
ajst-18565	58	6	module	module	NOUN
ajst-18565	58	7	164	164	NUM
ajst-18565	58	8	a)resnext	a)resnext	PROPN
ajst-18565	58	9	module	module	NOUN
ajst-18565	58	10	:	:	PUNCT
ajst-18565	58	11	a	a	DET
ajst-18565	58	12	multi	multi	ADJ
ajst-18565	58	13	-	-	ADJ
ajst-18565	58	14	branch	branch	ADJ
ajst-18565	58	15	convolutional	convolutional	ADJ
ajst-18565	58	16	neural	neural	ADJ
ajst-18565	58	17	network	network	NOUN
ajst-18565	58	18	structure	structure	NOUN
ajst-18565	58	19	is	be	AUX
ajst-18565	58	20	adopted	adopt	VERB
ajst-18565	58	21	.	.	PUNCT
ajst-18565	59	1	the	the	DET
ajst-18565	59	2	feature	feature	NOUN
ajst-18565	59	3	graphs	graph	NOUN
ajst-18565	59	4	of	of	ADP
ajst-18565	59	5	several	several	ADJ
ajst-18565	59	6	branches	branch	NOUN
ajst-18565	59	7	are	be	AUX
ajst-18565	59	8	combined	combine	VERB
ajst-18565	59	9	after	after	ADP
ajst-18565	59	10	convolution	convolution	NOUN
ajst-18565	59	11	processing	processing	NOUN
ajst-18565	59	12	,	,	PUNCT
ajst-18565	59	13	and	and	CCONJ
ajst-18565	59	14	finally	finally	ADV
ajst-18565	59	15	the	the	DET
ajst-18565	59	16	combined	combine	VERB
ajst-18565	59	17	results	result	NOUN
ajst-18565	59	18	are	be	AUX
ajst-18565	59	19	convolved	convolve	VERB
ajst-18565	59	20	again	again	ADV
ajst-18565	59	21	.	.	PUNCT
ajst-18565	60	1	b)senet	b)senet	NOUN
ajst-18565	60	2	module	module	NOUN
ajst-18565	60	3	:	:	PUNCT
ajst-18565	60	4	after	after	ADP
ajst-18565	60	5	the	the	DET
ajst-18565	60	6	first	first	ADJ
ajst-18565	60	7	standard	standard	ADJ
ajst-18565	60	8	convolution	convolution	NOUN
ajst-18565	60	9	operation	operation	NOUN
ajst-18565	60	10	,	,	PUNCT
ajst-18565	60	11	the	the	DET
ajst-18565	60	12	feature	feature	NOUN
ajst-18565	60	13	is	be	AUX
ajst-18565	60	14	extruded	extrude	VERB
ajst-18565	60	15	by	by	ADP
ajst-18565	60	16	global	global	ADJ
ajst-18565	60	17	average	average	ADJ
ajst-18565	60	18	pooling	pooling	NOUN
ajst-18565	60	19	,	,	PUNCT
ajst-18565	60	20	then	then	ADV
ajst-18565	60	21	two	two	NUM
ajst-18565	60	22	1×1	1×1	NOUN
ajst-18565	60	23	fully	fully	ADV
ajst-18565	60	24	connected	connected	ADJ
ajst-18565	60	25	layers	layer	NOUN
ajst-18565	60	26	are	be	AUX
ajst-18565	60	27	used	use	VERB
ajst-18565	60	28	to	to	PART
ajst-18565	60	29	get	get	VERB
ajst-18565	60	30	the	the	DET
ajst-18565	60	31	channel	channel	NOUN
ajst-18565	60	32	weight	weight	NOUN
ajst-18565	60	33	,	,	PUNCT
ajst-18565	60	34	and	and	CCONJ
ajst-18565	60	35	finally	finally	ADV
ajst-18565	60	36	the	the	DET
ajst-18565	60	37	feature	feature	NOUN
ajst-18565	60	38	is	be	AUX
ajst-18565	60	39	scaled	scale	VERB
ajst-18565	60	40	.	.	PUNCT
ajst-18565	61	1	c)senetv2	c)senetv2	PROPN
ajst-18565	61	2	module	module	NOUN
ajst-18565	61	3	:	:	PUNCT
ajst-18565	61	4	combine	combine	VERB
ajst-18565	61	5	the	the	DET
ajst-18565	61	6	features	feature	NOUN
ajst-18565	61	7	of	of	ADP
ajst-18565	61	8	resnext	resnext	ADJ
ajst-18565	61	9	module	module	NOUN
ajst-18565	61	10	and	and	CCONJ
ajst-18565	61	11	senet	senet	NOUN
ajst-18565	61	12	module	module	NOUN
ajst-18565	61	13	.	.	PUNCT
ajst-18565	62	1	firstly	firstly	ADV
ajst-18565	62	2	,	,	PUNCT
ajst-18565	62	3	squeeze	squeeze	VERB
ajst-18565	62	4	and	and	CCONJ
ajst-18565	62	5	excite	excite	VERB
ajst-18565	62	6	the	the	DET
ajst-18565	62	7	features	feature	NOUN
ajst-18565	62	8	through	through	ADP
ajst-18565	62	9	the	the	DET
ajst-18565	62	10	multi	multi	ADJ
ajst-18565	62	11	-	-	ADJ
ajst-18565	62	12	branch	branch	ADJ
ajst-18565	62	13	fully	fully	ADV
ajst-18565	62	14	connected	connect	VERB
ajst-18565	62	15	layer	layer	NOUN
ajst-18565	62	16	,	,	PUNCT
ajst-18565	62	17	and	and	CCONJ
ajst-18565	62	18	finally	finally	ADV
ajst-18565	62	19	carry	carry	VERB
ajst-18565	62	20	out	out	ADP
ajst-18565	62	21	a	a	DET
ajst-18565	62	22	feature	feature	NOUN
ajst-18565	62	23	scaling	scale	VERB
ajst-18565	62	24	operation	operation	NOUN
ajst-18565	62	25	.	.	PUNCT
ajst-18565	63	1	senetv2	senetv2	PROPN
ajst-18565	63	2	is	be	AUX
ajst-18565	63	3	designed	design	VERB
ajst-18565	63	4	to	to	PART
ajst-18565	63	5	use	use	VERB
ajst-18565	63	6	a	a	DET
ajst-18565	63	7	multi	multi	ADJ
ajst-18565	63	8	-	-	ADJ
ajst-18565	63	9	branch	branch	ADJ
ajst-18565	63	10	structure	structure	NOUN
ajst-18565	63	11	to	to	PART
ajst-18565	63	12	further	far	ADV
ajst-18565	63	13	enhance	enhance	VERB
ajst-18565	63	14	feature	feature	NOUN
ajst-18565	63	15	representation	representation	NOUN
ajst-18565	63	16	and	and	CCONJ
ajst-18565	63	17	global	global	ADJ
ajst-18565	63	18	information	information	NOUN
ajst-18565	63	19	integration	integration	NOUN
ajst-18565	63	20	.	.	PUNCT
ajst-18565	64	1	after	after	ADP
ajst-18565	64	2	extruding	extrude	VERB
ajst-18565	64	3	the	the	DET
ajst-18565	64	4	output	output	NOUN
ajst-18565	64	5	,	,	PUNCT
ajst-18565	64	6	it	it	PRON
ajst-18565	64	7	is	be	AUX
ajst-18565	64	8	fed	feed	VERB
ajst-18565	64	9	into	into	ADP
ajst-18565	64	10	a	a	DET
ajst-18565	64	11	fully	fully	ADV
ajst-18565	64	12	connected	connect	VERB
ajst-18565	64	13	layer	layer	NOUN
ajst-18565	64	14	with	with	ADP
ajst-18565	64	15	multiple	multiple	ADJ
ajst-18565	64	16	branches	branch	NOUN
ajst-18565	64	17	,	,	PUNCT
ajst-18565	64	18	and	and	CCONJ
ajst-18565	64	19	then	then	ADV
ajst-18565	64	20	stimulated	stimulate	VERB
ajst-18565	64	21	,	,	PUNCT
ajst-18565	64	22	and	and	CCONJ
ajst-18565	64	23	the	the	DET
ajst-18565	64	24	split	split	ADJ
ajst-18565	64	25	input	input	NOUN
ajst-18565	64	26	is	be	AUX
ajst-18565	64	27	finally	finally	ADV
ajst-18565	64	28	passed	pass	VERB
ajst-18565	64	29	back	back	ADV
ajst-18565	64	30	to	to	ADP
ajst-18565	64	31	its	its	PRON
ajst-18565	64	32	original	original	ADJ
ajst-18565	64	33	shape	shape	NOUN
ajst-18565	64	34	.	.	PUNCT
ajst-18565	65	1	sae	sae	PROPN
ajst-18565	65	2	modules	module	NOUN
ajst-18565	65	3	are	be	AUX
ajst-18565	65	4	designed	design	VERB
ajst-18565	65	5	to	to	PART
ajst-18565	65	6	enable	enable	VERB
ajst-18565	65	7	networks	network	NOUN
ajst-18565	65	8	to	to	PART
ajst-18565	65	9	learn	learn	VERB
ajst-18565	65	10	features	feature	NOUN
ajst-18565	65	11	more	more	ADV
ajst-18565	65	12	efficiently	efficiently	ADV
ajst-18565	65	13	and	and	CCONJ
ajst-18565	65	14	take	take	VERB
ajst-18565	65	15	into	into	ADP
ajst-18565	65	16	account	account	NOUN
ajst-18565	65	17	the	the	DET
ajst-18565	65	18	interdependencies	interdependency	NOUN
ajst-18565	65	19	between	between	ADP
ajst-18565	65	20	different	different	ADJ
ajst-18565	65	21	channels	channel	NOUN
ajst-18565	65	22	during	during	ADP
ajst-18565	65	23	feature	feature	NOUN
ajst-18565	65	24	transformation	transformation	NOUN
ajst-18565	65	25	.	.	PUNCT
ajst-18565	66	1	the	the	DET
ajst-18565	66	2	fig	fig	NOUN
ajst-18565	66	3	.3	.3	NUM
ajst-18565	66	4	shows	show	VERB
ajst-18565	66	5	the	the	DET
ajst-18565	66	6	network	network	NOUN
ajst-18565	66	7	structure	structure	NOUN
ajst-18565	66	8	of	of	ADP
ajst-18565	66	9	sae	sae	PROPN
ajst-18565	66	10	.	.	PROPN
ajst-18565	67	1	figure	figure	VERB
ajst-18565	67	2	3	3	NUM
ajst-18565	67	3	.	.	PUNCT
ajst-18565	67	4	sae	sae	PROPN
ajst-18565	67	5	structure	structure	NOUN
ajst-18565	67	6	in	in	ADP
ajst-18565	67	7	this	this	DET
ajst-18565	67	8	paper	paper	NOUN
ajst-18565	67	9	,	,	PUNCT
ajst-18565	67	10	senetv2	senetv2	PROPN
ajst-18565	67	11	is	be	AUX
ajst-18565	67	12	used	use	VERB
ajst-18565	67	13	to	to	PART
ajst-18565	67	14	add	add	VERB
ajst-18565	67	15	an	an	DET
ajst-18565	67	16	attention	attention	NOUN
ajst-18565	67	17	module	module	NOUN
ajst-18565	67	18	on	on	ADP
ajst-18565	67	19	the	the	DET
ajst-18565	67	20	sppf	sppf	ADJ
ajst-18565	67	21	structure	structure	NOUN
ajst-18565	67	22	of	of	ADP
ajst-18565	67	23	yolov8	yolov8	PROPN
ajst-18565	67	24	backbone	backbone	PROPN
ajst-18565	67	25	network	network	NOUN
ajst-18565	67	26	to	to	PART
ajst-18565	67	27	enhance	enhance	VERB
ajst-18565	67	28	the	the	DET
ajst-18565	67	29	feature	feature	NOUN
ajst-18565	67	30	extraction	extraction	NOUN
ajst-18565	67	31	capability	capability	NOUN
ajst-18565	67	32	of	of	ADP
ajst-18565	67	33	the	the	DET
ajst-18565	67	34	backbone	backbone	NOUN
ajst-18565	67	35	network	network	NOUN
ajst-18565	67	36	2.2.2	2.2.2	NUM
ajst-18565	67	37	.	.	PUNCT
ajst-18565	68	1	gsconv	gsconv	VERB
ajst-18565	68	2	a	a	DET
ajst-18565	68	3	common	common	ADJ
ajst-18565	68	4	convolution	convolution	NOUN
ajst-18565	68	5	module	module	NOUN
ajst-18565	68	6	extracts	extract	NOUN
ajst-18565	68	7	features	feature	NOUN
ajst-18565	68	8	by	by	ADP
ajst-18565	68	9	doing	do	VERB
ajst-18565	68	10	a	a	DET
ajst-18565	68	11	dot	dot	NOUN
ajst-18565	68	12	product	product	NOUN
ajst-18565	68	13	mapping	mapping	NOUN
ajst-18565	68	14	of	of	ADP
ajst-18565	68	15	each	each	DET
ajst-18565	68	16	channel	channel	NOUN
ajst-18565	68	17	in	in	ADP
ajst-18565	68	18	the	the	DET
ajst-18565	68	19	input	input	NOUN
ajst-18565	68	20	feature	feature	NOUN
ajst-18565	68	21	graph	graph	NOUN
ajst-18565	68	22	,	,	PUNCT
ajst-18565	68	23	where	where	SCONJ
ajst-18565	68	24	the	the	DET
ajst-18565	68	25	number	number	NOUN
ajst-18565	68	26	of	of	ADP
ajst-18565	68	27	convolution	convolution	NOUN
ajst-18565	68	28	cores	core	NOUN
ajst-18565	68	29	is	be	AUX
ajst-18565	68	30	the	the	DET
ajst-18565	68	31	same	same	ADJ
ajst-18565	68	32	as	as	ADP
ajst-18565	68	33	the	the	DET
ajst-18565	68	34	number	number	NOUN
ajst-18565	68	35	of	of	ADP
ajst-18565	68	36	input	input	NOUN
ajst-18565	68	37	features	feature	NOUN
ajst-18565	68	38	.	.	PUNCT
ajst-18565	69	1	however	however	ADV
ajst-18565	69	2	,	,	PUNCT
ajst-18565	69	3	when	when	SCONJ
ajst-18565	69	4	a	a	DET
ajst-18565	69	5	large	large	ADJ
ajst-18565	69	6	number	number	NOUN
ajst-18565	69	7	of	of	ADP
ajst-18565	69	8	convolutional	convolutional	ADJ
ajst-18565	69	9	layers	layer	NOUN
ajst-18565	69	10	are	be	AUX
ajst-18565	69	11	stacked	stack	VERB
ajst-18565	69	12	,	,	PUNCT
ajst-18565	69	13	redundant	redundant	ADJ
ajst-18565	69	14	feature	feature	NOUN
ajst-18565	69	15	graphs	graph	NOUN
ajst-18565	69	16	will	will	AUX
ajst-18565	69	17	appear	appear	VERB
ajst-18565	69	18	,	,	PUNCT
ajst-18565	69	19	which	which	PRON
ajst-18565	69	20	consumes	consume	VERB
ajst-18565	69	21	too	too	ADV
ajst-18565	69	22	much	much	ADJ
ajst-18565	69	23	computation	computation	NOUN
ajst-18565	69	24	and	and	CCONJ
ajst-18565	69	25	parameter	parameter	NOUN
ajst-18565	69	26	number	number	NOUN
ajst-18565	69	27	.	.	PUNCT
ajst-18565	70	1	the	the	DET
ajst-18565	70	2	gsconv	gsconv	NOUN
ajst-18565	70	3	can	can	AUX
ajst-18565	70	4	ensure	ensure	VERB
ajst-18565	70	5	the	the	DET
ajst-18565	70	6	detection	detection	NOUN
ajst-18565	70	7	performance	performance	NOUN
ajst-18565	70	8	of	of	ADP
ajst-18565	70	9	the	the	DET
ajst-18565	70	10	model	model	NOUN
ajst-18565	70	11	while	while	SCONJ
ajst-18565	70	12	reducing	reduce	VERB
ajst-18565	70	13	the	the	DET
ajst-18565	70	14	computational	computational	ADJ
ajst-18565	70	15	load	load	NOUN
ajst-18565	70	16	.	.	PUNCT
ajst-18565	71	1	in	in	ADP
ajst-18565	71	2	general	general	ADJ
ajst-18565	71	3	,	,	PUNCT
ajst-18565	71	4	in	in	ADP
ajst-18565	71	5	order	order	NOUN
ajst-18565	71	6	to	to	PART
ajst-18565	71	7	improve	improve	VERB
ajst-18565	71	8	the	the	DET
ajst-18565	71	9	inference	inference	NOUN
ajst-18565	71	10	speed	speed	NOUN
ajst-18565	71	11	,	,	PUNCT
ajst-18565	71	12	the	the	DET
ajst-18565	71	13	images	image	NOUN
ajst-18565	71	14	in	in	ADP
ajst-18565	71	15	the	the	DET
ajst-18565	71	16	convolutional	convolutional	ADJ
ajst-18565	71	17	neural	neural	ADJ
ajst-18565	71	18	network	network	NOUN
ajst-18565	71	19	must	must	AUX
ajst-18565	71	20	transmit	transmit	VERB
ajst-18565	71	21	spatial	spatial	ADJ
ajst-18565	71	22	information	information	NOUN
ajst-18565	71	23	step	step	NOUN
ajst-18565	71	24	by	by	ADP
ajst-18565	71	25	step	step	NOUN
ajst-18565	71	26	to	to	ADP
ajst-18565	71	27	the	the	DET
ajst-18565	71	28	channel	channel	NOUN
ajst-18565	71	29	.	.	PUNCT
ajst-18565	72	1	gsconv	gsconv	PROPN
ajst-18565	72	2	preserves	preserve	VERB
ajst-18565	72	3	the	the	DET
ajst-18565	72	4	connections	connection	NOUN
ajst-18565	72	5	between	between	ADP
ajst-18565	72	6	each	each	DET
ajst-18565	72	7	channel	channel	NOUN
ajst-18565	72	8	as	as	ADV
ajst-18565	72	9	much	much	ADV
ajst-18565	72	10	as	as	ADP
ajst-18565	72	11	possible	possible	ADJ
ajst-18565	72	12	at	at	ADP
ajst-18565	72	13	a	a	DET
ajst-18565	72	14	low	low	ADJ
ajst-18565	72	15	cost	cost	NOUN
ajst-18565	72	16	,	,	PUNCT
ajst-18565	72	17	protecting	protect	VERB
ajst-18565	72	18	the	the	DET
ajst-18565	72	19	semantic	semantic	ADJ
ajst-18565	72	20	information	information	NOUN
ajst-18565	72	21	of	of	ADP
ajst-18565	72	22	the	the	DET
ajst-18565	72	23	feature	feature	NOUN
ajst-18565	72	24	map	map	NOUN
ajst-18565	72	25	.	.	PUNCT
ajst-18565	73	1	using	use	VERB
ajst-18565	73	2	gsconv	gsconv	NOUN
ajst-18565	73	3	instead	instead	ADV
ajst-18565	73	4	of	of	ADP
ajst-18565	73	5	standard	standard	ADJ
ajst-18565	73	6	convolution	convolution	NOUN
ajst-18565	73	7	can	can	AUX
ajst-18565	73	8	effectively	effectively	ADV
ajst-18565	73	9	reduce	reduce	VERB
ajst-18565	73	10	the	the	DET
ajst-18565	73	11	computational	computational	ADJ
ajst-18565	73	12	cost	cost	NOUN
ajst-18565	73	13	and	and	CCONJ
ajst-18565	73	14	maintain	maintain	VERB
ajst-18565	73	15	the	the	DET
ajst-18565	73	16	learning	learning	NOUN
ajst-18565	73	17	ability	ability	NOUN
ajst-18565	73	18	of	of	ADP
ajst-18565	73	19	the	the	DET
ajst-18565	73	20	model	model	NOUN
ajst-18565	73	21	.	.	PUNCT
ajst-18565	74	1	then	then	ADV
ajst-18565	74	2	,	,	PUNCT
ajst-18565	74	3	a	a	DET
ajst-18565	74	4	gsbottleneck	gsbottleneck	NOUN
ajst-18565	74	5	module	module	NOUN
ajst-18565	74	6	is	be	AUX
ajst-18565	74	7	constructed	construct	VERB
ajst-18565	74	8	on	on	ADP
ajst-18565	74	9	the	the	DET
ajst-18565	74	10	basis	basis	NOUN
ajst-18565	74	11	of	of	ADP
ajst-18565	74	12	gsconv	gsconv	NOUN
ajst-18565	74	13	,	,	PUNCT
ajst-18565	74	14	and	and	CCONJ
ajst-18565	74	15	its	its	PRON
ajst-18565	74	16	structure	structure	NOUN
ajst-18565	74	17	is	be	AUX
ajst-18565	74	18	shown	show	VERB
ajst-18565	74	19	in	in	ADP
ajst-18565	74	20	figure	figure	NOUN
ajst-18565	74	21	4	4	NUM
ajst-18565	74	22	.	.	PUNCT
ajst-18565	75	1	gsconv	gsconv	NOUN
ajst-18565	75	2	is	be	AUX
ajst-18565	75	3	first	first	ADV
ajst-18565	75	4	subsampled	subsample	VERB
ajst-18565	75	5	by	by	ADP
ajst-18565	75	6	a	a	DET
ajst-18565	75	7	conventional	conventional	ADJ
ajst-18565	75	8	convolution	convolution	NOUN
ajst-18565	75	9	and	and	CCONJ
ajst-18565	75	10	then	then	ADV
ajst-18565	75	11	deep	deep	ADJ
ajst-18565	75	12	convolution	convolution	NOUN
ajst-18565	75	13	by	by	ADP
ajst-18565	75	14	dwconv	dwconv	ADJ
ajst-18565	75	15	.	.	PUNCT
ajst-18565	76	1	the	the	DET
ajst-18565	76	2	results	result	NOUN
ajst-18565	76	3	processed	process	VERB
ajst-18565	76	4	by	by	ADP
ajst-18565	76	5	the	the	DET
ajst-18565	76	6	two	two	NUM
ajst-18565	76	7	are	be	AUX
ajst-18565	76	8	concatenated	concatenate	VERB
ajst-18565	76	9	.	.	PUNCT
ajst-18565	77	1	finally	finally	ADV
ajst-18565	77	2	,	,	PUNCT
ajst-18565	77	3	the	the	DET
ajst-18565	77	4	corresponding	corresponding	ADJ
ajst-18565	77	5	channels	channel	NOUN
ajst-18565	77	6	of	of	ADP
ajst-18565	77	7	the	the	DET
ajst-18565	77	8	two	two	NUM
ajst-18565	77	9	convolution	convolution	NOUN
ajst-18565	77	10	are	be	AUX
ajst-18565	77	11	adjacent	adjacent	ADJ
ajst-18565	77	12	by	by	ADP
ajst-18565	77	13	shuffle	shuffle	NOUN
ajst-18565	77	14	.	.	PUNCT
ajst-18565	78	1	fig	fig	PROPN
ajst-18565	78	2	.4	.4	NUM
ajst-18565	78	3	shows	show	VERB
ajst-18565	78	4	the	the	DET
ajst-18565	78	5	gsconv	gsconv	NOUN
ajst-18565	78	6	structure	structure	NOUN
ajst-18565	78	7	.	.	PUNCT
ajst-18565	79	1	figure	figure	VERB
ajst-18565	79	2	4	4	NUM
ajst-18565	79	3	.	.	PUNCT
ajst-18565	80	1	gsconv	gsconv	NOUN
ajst-18565	80	2	structure	structure	NOUN
ajst-18565	80	3	assume	assume	VERB
ajst-18565	80	4	that	that	SCONJ
ajst-18565	80	5	the	the	DET
ajst-18565	80	6	input	input	NOUN
ajst-18565	80	7	channel	channel	NOUN
ajst-18565	80	8	of	of	ADP
ajst-18565	80	9	the	the	DET
ajst-18565	80	10	module	module	NOUN
ajst-18565	80	11	is	be	AUX
ajst-18565	80	12	c1	c1	PROPN
ajst-18565	80	13	and	and	CCONJ
ajst-18565	80	14	the	the	DET
ajst-18565	80	15	output	output	NOUN
ajst-18565	80	16	channel	channel	NOUN
ajst-18565	80	17	is	be	AUX
ajst-18565	80	18	c2	c2	PROPN
ajst-18565	80	19	.	.	PUNCT
ajst-18565	81	1	first	first	ADV
ajst-18565	81	2	,	,	PUNCT
ajst-18565	81	3	the	the	DET
ajst-18565	81	4	number	number	NOUN
ajst-18565	81	5	of	of	ADP
ajst-18565	81	6	channels	channel	NOUN
ajst-18565	81	7	is	be	AUX
ajst-18565	81	8	adjusted	adjust	VERB
ajst-18565	81	9	to	to	PART
ajst-18565	81	10	c2/2	c2/2	VERB
ajst-18565	81	11	by	by	ADP
ajst-18565	81	12	standard	standard	ADJ
ajst-18565	81	13	convolution	convolution	NOUN
ajst-18565	81	14	,	,	PUNCT
ajst-18565	81	15	and	and	CCONJ
ajst-18565	81	16	then	then	ADV
ajst-18565	81	17	the	the	DET
ajst-18565	81	18	convolution	convolution	NOUN
ajst-18565	81	19	can	can	AUX
ajst-18565	81	20	be	be	AUX
ajst-18565	81	21	separated	separate	VERB
ajst-18565	81	22	by	by	ADP
ajst-18565	81	23	the	the	DET
ajst-18565	81	24	depth	depth	NOUN
ajst-18565	81	25	of	of	ADP
ajst-18565	81	26	convolution	convolution	NOUN
ajst-18565	81	27	kernel	kernel	NOUN
ajst-18565	81	28	size	size	NOUN
ajst-18565	81	29	of	of	ADP
ajst-18565	81	30	5×5	5×5	NUM
ajst-18565	81	31	and	and	CCONJ
ajst-18565	81	32	the	the	DET
ajst-18565	81	33	number	number	NOUN
ajst-18565	81	34	of	of	ADP
ajst-18565	81	35	channels	channel	NOUN
ajst-18565	81	36	is	be	AUX
ajst-18565	81	37	kept	keep	VERB
ajst-18565	81	38	constant	constant	ADJ
ajst-18565	81	39	.	.	PUNCT
ajst-18565	82	1	finally	finally	ADV
ajst-18565	82	2	,	,	PUNCT
ajst-18565	82	3	the	the	DET
ajst-18565	82	4	feature	feature	NOUN
ajst-18565	82	5	graphs	graph	NOUN
ajst-18565	82	6	obtained	obtain	VERB
ajst-18565	82	7	from	from	ADP
ajst-18565	82	8	the	the	DET
ajst-18565	82	9	two	two	NUM
ajst-18565	82	10	convolution	convolution	NOUN
ajst-18565	82	11	operations	operation	NOUN
ajst-18565	82	12	are	be	AUX
ajst-18565	82	13	splicted	splicte	VERB
ajst-18565	82	14	and	and	CCONJ
ajst-18565	82	15	mixed	mixed	ADJ
ajst-18565	82	16	.	.	PUNCT
ajst-18565	83	1	the	the	DET
ajst-18565	83	2	mixing	mix	VERB
ajst-18565	83	3	operation	operation	NOUN
ajst-18565	83	4	can	can	AUX
ajst-18565	83	5	evenly	evenly	ADV
ajst-18565	83	6	shuffle	shuffle	VERB
ajst-18565	83	7	the	the	DET
ajst-18565	83	8	output	output	NOUN
ajst-18565	83	9	feature	feature	NOUN
ajst-18565	83	10	graphs	graph	NOUN
ajst-18565	83	11	,	,	PUNCT
ajst-18565	83	12	so	so	SCONJ
ajst-18565	83	13	that	that	SCONJ
ajst-18565	83	14	the	the	DET
ajst-18565	83	15	information	information	NOUN
ajst-18565	83	16	generated	generate	VERB
ajst-18565	83	17	by	by	ADP
ajst-18565	83	18	standard	standard	ADJ
ajst-18565	83	19	convolution	convolution	NOUN
ajst-18565	83	20	can	can	AUX
ajst-18565	83	21	penetrate	penetrate	VERB
ajst-18565	83	22	into	into	ADP
ajst-18565	83	23	the	the	DET
ajst-18565	83	24	information	information	NOUN
ajst-18565	83	25	generated	generate	VERB
ajst-18565	83	26	by	by	ADP
ajst-18565	83	27	deep	deep	ADJ
ajst-18565	83	28	separable	separable	ADJ
ajst-18565	83	29	convolution	convolution	NOUN
ajst-18565	83	30	to	to	PART
ajst-18565	83	31	enhance	enhance	VERB
ajst-18565	83	32	the	the	DET
ajst-18565	83	33	channel	channel	NOUN
ajst-18565	83	34	information	information	NOUN
ajst-18565	83	35	fusion	fusion	NOUN
ajst-18565	83	36	and	and	CCONJ
ajst-18565	83	37	improve	improve	VERB
ajst-18565	83	38	the	the	DET
ajst-18565	83	39	representation	representation	NOUN
ajst-18565	83	40	ability	ability	NOUN
ajst-18565	83	41	of	of	ADP
ajst-18565	83	42	the	the	DET
ajst-18565	83	43	network	network	NOUN
ajst-18565	83	44	.	.	PUNCT
ajst-18565	84	1	in	in	ADP
ajst-18565	84	2	this	this	DET
ajst-18565	84	3	paper	paper	NOUN
ajst-18565	84	4	,	,	PUNCT
ajst-18565	84	5	gsconv	gsconv	NOUN
ajst-18565	84	6	is	be	AUX
ajst-18565	84	7	introduced	introduce	VERB
ajst-18565	84	8	into	into	ADP
ajst-18565	84	9	the	the	DET
ajst-18565	84	10	neck	neck	NOUN
ajst-18565	84	11	part	part	NOUN
ajst-18565	84	12	of	of	ADP
ajst-18565	84	13	yolov8n	yolov8n	PROPN
ajst-18565	84	14	to	to	PART
ajst-18565	84	15	replace	replace	VERB
ajst-18565	84	16	two	two	NUM
ajst-18565	84	17	common	common	ADJ
ajst-18565	84	18	convolution	convolution	NOUN
ajst-18565	84	19	modules	module	NOUN
ajst-18565	84	20	.	.	PUNCT
ajst-18565	85	1	after	after	ADP
ajst-18565	85	2	improvement	improvement	NOUN
ajst-18565	85	3	,	,	PUNCT
ajst-18565	85	4	the	the	DET
ajst-18565	85	5	feature	feature	NOUN
ajst-18565	85	6	fusion	fusion	NOUN
ajst-18565	85	7	capability	capability	NOUN
ajst-18565	85	8	of	of	ADP
ajst-18565	85	9	the	the	DET
ajst-18565	85	10	neck	neck	NOUN
ajst-18565	85	11	part	part	NOUN
ajst-18565	85	12	is	be	AUX
ajst-18565	85	13	enhanced	enhance	VERB
ajst-18565	85	14	,	,	PUNCT
ajst-18565	85	15	the	the	DET
ajst-18565	85	16	receptive	receptive	ADJ
ajst-18565	85	17	field	field	NOUN
ajst-18565	85	18	is	be	AUX
ajst-18565	85	19	enlarged	enlarge	VERB
ajst-18565	85	20	,	,	PUNCT
ajst-18565	85	21	the	the	DET
ajst-18565	85	22	parameter	parameter	NOUN
ajst-18565	85	23	number	number	NOUN
ajst-18565	85	24	and	and	CCONJ
ajst-18565	85	25	calculation	calculation	NOUN
ajst-18565	85	26	amount	amount	NOUN
ajst-18565	85	27	are	be	AUX
ajst-18565	85	28	reduced	reduce	VERB
ajst-18565	85	29	,	,	PUNCT
ajst-18565	85	30	and	and	CCONJ
ajst-18565	85	31	the	the	DET
ajst-18565	85	32	calculation	calculation	NOUN
ajst-18565	85	33	speed	speed	NOUN
ajst-18565	85	34	of	of	ADP
ajst-18565	85	35	the	the	DET
ajst-18565	85	36	network	network	NOUN
ajst-18565	85	37	is	be	AUX
ajst-18565	85	38	improved	improve	VERB
ajst-18565	85	39	.	.	PUNCT
ajst-18565	86	1	2.2.3	2.2.3	X
ajst-18565	86	2	.	.	X
ajst-18565	86	3	wise	wise	ADJ
ajst-18565	86	4	-	-	PUNCT
ajst-18565	86	5	iou	iou	NOUN
ajst-18565	86	6	in	in	ADP
ajst-18565	86	7	the	the	DET
ajst-18565	86	8	process	process	NOUN
ajst-18565	86	9	of	of	ADP
ajst-18565	86	10	model	model	NOUN
ajst-18565	86	11	training	training	NOUN
ajst-18565	86	12	,	,	PUNCT
ajst-18565	86	13	each	each	DET
ajst-18565	86	14	data	data	NOUN
ajst-18565	86	15	sample	sample	NOUN
ajst-18565	86	16	will	will	AUX
ajst-18565	86	17	get	get	VERB
ajst-18565	86	18	a	a	DET
ajst-18565	86	19	predicted	predict	VERB
ajst-18565	86	20	value	value	NOUN
ajst-18565	86	21	after	after	ADP
ajst-18565	86	22	passing	pass	VERB
ajst-18565	86	23	through	through	ADP
ajst-18565	86	24	the	the	DET
ajst-18565	86	25	model	model	NOUN
ajst-18565	86	26	,	,	PUNCT
ajst-18565	86	27	and	and	CCONJ
ajst-18565	86	28	the	the	DET
ajst-18565	86	29	gap	gap	NOUN
ajst-18565	86	30	between	between	ADP
ajst-18565	86	31	the	the	DET
ajst-18565	86	32	predicted	predict	VERB
ajst-18565	86	33	value	value	NOUN
ajst-18565	86	34	and	and	CCONJ
ajst-18565	86	35	the	the	DET
ajst-18565	86	36	real	real	ADJ
ajst-18565	86	37	value	value	NOUN
ajst-18565	86	38	is	be	AUX
ajst-18565	86	39	called	call	VERB
ajst-18565	86	40	the	the	DET
ajst-18565	86	41	loss	loss	NOUN
ajst-18565	86	42	value	value	NOUN
ajst-18565	86	43	.	.	PUNCT
ajst-18565	87	1	the	the	DET
ajst-18565	87	2	loss	loss	NOUN
ajst-18565	87	3	function	function	NOUN
ajst-18565	87	4	is	be	AUX
ajst-18565	87	5	the	the	DET
ajst-18565	87	6	function	function	NOUN
ajst-18565	87	7	used	use	VERB
ajst-18565	87	8	to	to	PART
ajst-18565	87	9	calculate	calculate	VERB
ajst-18565	87	10	the	the	DET
ajst-18565	87	11	gap	gap	NOUN
ajst-18565	87	12	between	between	ADP
ajst-18565	87	13	the	the	DET
ajst-18565	87	14	predicted	predict	VERB
ajst-18565	87	15	value	value	NOUN
ajst-18565	87	16	and	and	CCONJ
ajst-18565	87	17	the	the	DET
ajst-18565	87	18	real	real	ADJ
ajst-18565	87	19	value	value	NOUN
ajst-18565	87	20	,	,	PUNCT
ajst-18565	87	21	and	and	CCONJ
ajst-18565	87	22	also	also	ADV
ajst-18565	87	23	serves	serve	VERB
ajst-18565	87	24	as	as	ADP
ajst-18565	87	25	the	the	DET
ajst-18565	87	26	learning	learning	NOUN
ajst-18565	87	27	criterion	criterion	NOUN
ajst-18565	87	28	for	for	ADP
ajst-18565	87	29	optimizing	optimize	VERB
ajst-18565	87	30	the	the	DET
ajst-18565	87	31	model	model	NOUN
ajst-18565	87	32	problem	problem	NOUN
ajst-18565	87	33	.	.	PUNCT
ajst-18565	88	1	the	the	DET
ajst-18565	88	2	loss	loss	NOUN
ajst-18565	88	3	function	function	NOUN
ajst-18565	88	4	plays	play	VERB
ajst-18565	88	5	a	a	DET
ajst-18565	88	6	decisive	decisive	ADJ
ajst-18565	88	7	role	role	NOUN
ajst-18565	88	8	in	in	ADP
ajst-18565	88	9	the	the	DET
ajst-18565	88	10	target	target	NOUN
ajst-18565	88	11	detection	detection	NOUN
ajst-18565	88	12	network	network	NOUN
ajst-18565	88	13	model	model	NOUN
ajst-18565	88	14	.	.	PUNCT
ajst-18565	89	1	as	as	ADP
ajst-18565	89	2	a	a	DET
ajst-18565	89	3	penalty	penalty	NOUN
ajst-18565	89	4	measure	measure	NOUN
ajst-18565	89	5	,	,	PUNCT
ajst-18565	89	6	the	the	DET
ajst-18565	89	7	loss	loss	NOUN
ajst-18565	89	8	function	function	NOUN
ajst-18565	89	9	needs	need	VERB
ajst-18565	89	10	to	to	PART
ajst-18565	89	11	be	be	AUX
ajst-18565	89	12	continuously	continuously	ADV
ajst-18565	89	13	minimized	minimize	VERB
ajst-18565	89	14	during	during	ADP
ajst-18565	89	15	the	the	DET
ajst-18565	89	16	training	training	NOUN
ajst-18565	89	17	process	process	NOUN
ajst-18565	89	18	,	,	PUNCT
ajst-18565	89	19	and	and	CCONJ
ajst-18565	89	20	ideally	ideally	ADV
ajst-18565	89	21	match	match	VERB
ajst-18565	89	22	the	the	DET
ajst-18565	89	23	target	target	NOUN
ajst-18565	89	24	prediction	prediction	NOUN
ajst-18565	89	25	frame	frame	NOUN
ajst-18565	89	26	with	with	ADP
ajst-18565	89	27	the	the	DET
ajst-18565	89	28	real	real	ADJ
ajst-18565	89	29	prediction	prediction	NOUN
ajst-18565	89	30	frame	frame	NOUN
ajst-18565	89	31	.	.	PUNCT
ajst-18565	90	1	intersection	intersection	NOUN
ajst-18565	90	2	over	over	ADP
ajst-18565	90	3	union	union	NOUN
ajst-18565	90	4	(	(	PUNCT
ajst-18565	90	5	iou	iou	NOUN
ajst-18565	90	6	)	)	PUNCT
ajst-18565	90	7	is	be	AUX
ajst-18565	90	8	a	a	DET
ajst-18565	90	9	distance	distance	NOUN
ajst-18565	90	10	measure	measure	NOUN
ajst-18565	90	11	used	use	VERB
ajst-18565	90	12	in	in	ADP
ajst-18565	90	13	object	object	NOUN
ajst-18565	90	14	detection	detection	NOUN
ajst-18565	90	15	tasks	task	NOUN
ajst-18565	90	16	to	to	PART
ajst-18565	90	17	measure	measure	VERB
ajst-18565	90	18	the	the	DET
ajst-18565	90	19	overlap	overlap	NOUN
ajst-18565	90	20	between	between	ADP
ajst-18565	90	21	the	the	DET
ajst-18565	90	22	predicted	predict	VERB
ajst-18565	90	23	bounding	bounding	NOUN
ajst-18565	90	24	box	box	NOUN
ajst-18565	90	25	and	and	CCONJ
ajst-18565	90	26	the	the	DET
ajst-18565	90	27	real	real	ADJ
ajst-18565	90	28	bounding	bounding	NOUN
ajst-18565	90	29	box	box	NOUN
ajst-18565	90	30	.	.	PUNCT
ajst-18565	91	1	the	the	DET
ajst-18565	91	2	calculation	calculation	NOUN
ajst-18565	91	3	formula	formula	NOUN
ajst-18565	91	4	of	of	ADP
ajst-18565	91	5	iou	iou	NOUN
ajst-18565	91	6	is	be	AUX
ajst-18565	91	7	as	as	SCONJ
ajst-18565	91	8	follows	follow	VERB
ajst-18565	91	9	:	:	PUNCT
ajst-18565	91	10	a	a	DET
ajst-18565	91	11	b	b	X
ajst-18565	91	12	iou	iou	VERB
ajst-18565	91	13	a	a	DET
ajst-18565	91	14	b	b	NOUN
ajst-18565	91	15			NOUN
ajst-18565	91	16			ADP
ajst-18565	91	17			PROPN
ajst-18565	91	18	(	(	PUNCT
ajst-18565	91	19	1	1	X
ajst-18565	91	20	)	)	PUNCT
ajst-18565	91	21	a	a	PRON
ajst-18565	91	22	represents	represent	VERB
ajst-18565	91	23	the	the	DET
ajst-18565	91	24	predicted	predict	VERB
ajst-18565	91	25	bounding	bounding	NOUN
ajst-18565	91	26	box	box	NOUN
ajst-18565	91	27	,	,	PUNCT
ajst-18565	91	28	b	b	PROPN
ajst-18565	91	29	represents	represent	VERB
ajst-18565	91	30	the	the	DET
ajst-18565	91	31	true	true	ADJ
ajst-18565	91	32	bounding	bounding	NOUN
ajst-18565	91	33	box	box	NOUN
ajst-18565	91	34	,	,	PUNCT
ajst-18565	91	35	a∩b	a∩b	PROPN
ajst-18565	91	36	represents	represent	VERB
ajst-18565	91	37	the	the	DET
ajst-18565	91	38	intersection	intersection	NOUN
ajst-18565	91	39	between	between	ADP
ajst-18565	91	40	two	two	NUM
ajst-18565	91	41	boxes	box	NOUN
ajst-18565	91	42	,	,	PUNCT
ajst-18565	91	43	and	and	CCONJ
ajst-18565	91	44	a∪b	a∪b	NOUN
ajst-18565	91	45	represents	represent	VERB
ajst-18565	91	46	the	the	DET
ajst-18565	91	47	union	union	NOUN
ajst-18565	91	48	between	between	ADP
ajst-18565	91	49	two	two	NUM
ajst-18565	91	50	boxes	box	NOUN
ajst-18565	91	51	.	.	PUNCT
ajst-18565	92	1	the	the	PRON
ajst-18565	92	2	larger	large	ADJ
ajst-18565	92	3	the	the	DET
ajst-18565	92	4	iou	iou	NOUN
ajst-18565	92	5	value	value	NOUN
ajst-18565	92	6	,	,	PUNCT
ajst-18565	92	7	the	the	PRON
ajst-18565	92	8	closer	close	ADV
ajst-18565	92	9	the	the	DET
ajst-18565	92	10	prediction	prediction	NOUN
ajst-18565	92	11	frame	frame	NOUN
ajst-18565	92	12	is	be	AUX
ajst-18565	92	13	to	to	ADP
ajst-18565	92	14	the	the	DET
ajst-18565	92	15	real	real	ADJ
ajst-18565	92	16	frame	frame	NOUN
ajst-18565	92	17	,	,	PUNCT
ajst-18565	92	18	the	the	PRON
ajst-18565	92	19	higher	high	ADJ
ajst-18565	92	20	the	the	DET
ajst-18565	92	21	accuracy	accuracy	NOUN
ajst-18565	92	22	of	of	ADP
ajst-18565	92	23	the	the	DET
ajst-18565	92	24	algorithm	algorithm	NOUN
ajst-18565	92	25	,	,	PUNCT
ajst-18565	92	26	and	and	CCONJ
ajst-18565	92	27	the	the	PRON
ajst-18565	92	28	better	well	ADJ
ajst-18565	92	29	the	the	DET
ajst-18565	92	30	performance	performance	NOUN
ajst-18565	92	31	of	of	ADP
ajst-18565	92	32	the	the	DET
ajst-18565	92	33	model	model	NOUN
ajst-18565	92	34	.	.	PUNCT
ajst-18565	93	1	the	the	DET
ajst-18565	93	2	iou	iou	PROPN
ajst-18565	93	3	calculation	calculation	NOUN
ajst-18565	93	4	165	165	NUM
ajst-18565	93	5	diagram	diagram	NOUN
ajst-18565	93	6	is	be	AUX
ajst-18565	93	7	shown	show	VERB
ajst-18565	93	8	in	in	ADP
ajst-18565	93	9	the	the	DET
ajst-18565	93	10	figure	figure	NOUN
ajst-18565	93	11	.	.	PUNCT
ajst-18565	94	1	figure	figure	VERB
ajst-18565	94	2	5	5	NUM
ajst-18565	94	3	.	.	PUNCT
ajst-18565	94	4	iou	iou	NOUN
ajst-18565	94	5	calculation	calculation	NOUN
ajst-18565	94	6	process	process	NOUN
ajst-18565	94	7	when	when	SCONJ
ajst-18565	94	8	iou	iou	NOUN
ajst-18565	94	9	is	be	AUX
ajst-18565	94	10	used	use	VERB
ajst-18565	94	11	as	as	ADP
ajst-18565	94	12	a	a	DET
ajst-18565	94	13	loss	loss	NOUN
ajst-18565	94	14	function	function	NOUN
ajst-18565	94	15	,	,	PUNCT
ajst-18565	94	16	its	its	PRON
ajst-18565	94	17	calculation	calculation	NOUN
ajst-18565	94	18	formula	formula	NOUN
ajst-18565	94	19	is	be	AUX
ajst-18565	94	20	as	as	SCONJ
ajst-18565	94	21	follows	follow	VERB
ajst-18565	94	22	:	:	PUNCT
ajst-18565	95	1	1	1	NUM
ajst-18565	95	2	1iou	1iou	NUM
ajst-18565	95	3	a	a	DET
ajst-18565	95	4	b	b	X
ajst-18565	95	5	l	l	NOUN
ajst-18565	95	6	iou	iou	NOUN
ajst-18565	95	7	a	a	DET
ajst-18565	95	8	b	b	NOUN
ajst-18565	95	9			PROPN
ajst-18565	95	10			PROPN
ajst-18565	95	11			PROPN
ajst-18565	95	12			NOUN
ajst-18565	95	13			ADP
ajst-18565	95	14			ADJ
ajst-18565	95	15	(	(	PUNCT
ajst-18565	95	16	2	2	NUM
ajst-18565	95	17	)	)	PUNCT
ajst-18565	95	18	in	in	ADP
ajst-18565	95	19	the	the	DET
ajst-18565	95	20	process	process	NOUN
ajst-18565	95	21	of	of	ADP
ajst-18565	95	22	road	road	NOUN
ajst-18565	95	23	damage	damage	NOUN
ajst-18565	95	24	model	model	NOUN
ajst-18565	95	25	training	training	NOUN
ajst-18565	95	26	,	,	PUNCT
ajst-18565	95	27	due	due	ADP
ajst-18565	95	28	to	to	ADP
ajst-18565	95	29	the	the	DET
ajst-18565	95	30	large	large	ADJ
ajst-18565	95	31	amount	amount	NOUN
ajst-18565	95	32	of	of	ADP
ajst-18565	95	33	training	training	NOUN
ajst-18565	95	34	data	datum	NOUN
ajst-18565	95	35	,	,	PUNCT
ajst-18565	95	36	complex	complex	ADJ
ajst-18565	95	37	and	and	CCONJ
ajst-18565	95	38	diverse	diverse	ADJ
ajst-18565	95	39	scenes	scene	NOUN
ajst-18565	95	40	,	,	PUNCT
ajst-18565	95	41	and	and	CCONJ
ajst-18565	95	42	because	because	SCONJ
ajst-18565	95	43	of	of	ADP
ajst-18565	95	44	the	the	DET
ajst-18565	95	45	characteristics	characteristic	NOUN
ajst-18565	95	46	of	of	ADP
ajst-18565	95	47	road	road	NOUN
ajst-18565	95	48	cracks	crack	NOUN
ajst-18565	95	49	themselves	themselves	PRON
ajst-18565	95	50	,	,	PUNCT
ajst-18565	95	51	the	the	DET
ajst-18565	95	52	shape	shape	NOUN
ajst-18565	95	53	of	of	ADP
ajst-18565	95	54	target	target	NOUN
ajst-18565	95	55	instances	instance	NOUN
ajst-18565	95	56	is	be	AUX
ajst-18565	95	57	long	long	ADJ
ajst-18565	95	58	and	and	CCONJ
ajst-18565	95	59	varied	varied	ADJ
ajst-18565	95	60	,	,	PUNCT
ajst-18565	95	61	and	and	CCONJ
ajst-18565	95	62	it	it	PRON
ajst-18565	95	63	is	be	AUX
ajst-18565	95	64	inevitable	inevitable	ADJ
ajst-18565	95	65	that	that	SCONJ
ajst-18565	95	66	there	there	PRON
ajst-18565	95	67	will	will	AUX
ajst-18565	95	68	be	be	AUX
ajst-18565	95	69	a	a	DET
ajst-18565	95	70	small	small	ADJ
ajst-18565	95	71	number	number	NOUN
ajst-18565	95	72	of	of	ADP
ajst-18565	95	73	low	low	ADJ
ajst-18565	95	74	-	-	PUNCT
ajst-18565	95	75	quality	quality	NOUN
ajst-18565	95	76	target	target	NOUN
ajst-18565	95	77	instances	instance	NOUN
ajst-18565	95	78	.	.	PUNCT
ajst-18565	96	1	however	however	ADV
ajst-18565	96	2	,	,	PUNCT
ajst-18565	96	3	geometric	geometric	ADJ
ajst-18565	96	4	measures	measure	NOUN
ajst-18565	96	5	such	such	ADJ
ajst-18565	96	6	as	as	ADP
ajst-18565	96	7	distance	distance	NOUN
ajst-18565	96	8	and	and	CCONJ
ajst-18565	96	9	aspect	aspect	NOUN
ajst-18565	96	10	ratio	ratio	NOUN
ajst-18565	96	11	will	will	AUX
ajst-18565	96	12	magnify	magnify	VERB
ajst-18565	96	13	the	the	DET
ajst-18565	96	14	penalty	penalty	NOUN
ajst-18565	96	15	for	for	ADP
ajst-18565	96	16	lowquality	lowquality	NOUN
ajst-18565	96	17	examples	example	NOUN
ajst-18565	96	18	,	,	PUNCT
ajst-18565	96	19	which	which	PRON
ajst-18565	96	20	will	will	AUX
ajst-18565	96	21	reduce	reduce	VERB
ajst-18565	96	22	the	the	DET
ajst-18565	96	23	generalization	generalization	NOUN
ajst-18565	96	24	performance	performance	NOUN
ajst-18565	96	25	of	of	ADP
ajst-18565	96	26	the	the	DET
ajst-18565	96	27	model	model	NOUN
ajst-18565	96	28	.	.	PUNCT
ajst-18565	97	1	the	the	DET
ajst-18565	97	2	high	high	ADJ
ajst-18565	97	3	performance	performance	NOUN
ajst-18565	97	4	loss	loss	NOUN
ajst-18565	97	5	function	function	NOUN
ajst-18565	97	6	should	should	AUX
ajst-18565	97	7	take	take	VERB
ajst-18565	97	8	into	into	ADP
ajst-18565	97	9	account	account	NOUN
ajst-18565	97	10	the	the	DET
ajst-18565	97	11	penalty	penalty	NOUN
ajst-18565	97	12	of	of	ADP
ajst-18565	97	13	weakening	weaken	VERB
ajst-18565	97	14	the	the	DET
ajst-18565	97	15	geometric	geometric	ADJ
ajst-18565	97	16	measure	measure	NOUN
ajst-18565	97	17	when	when	SCONJ
ajst-18565	97	18	the	the	DET
ajst-18565	97	19	anchor	anchor	NOUN
ajst-18565	97	20	frame	frame	NOUN
ajst-18565	97	21	and	and	CCONJ
ajst-18565	97	22	the	the	DET
ajst-18565	97	23	target	target	NOUN
ajst-18565	97	24	frame	frame	NOUN
ajst-18565	97	25	coincide	coincide	NOUN
ajst-18565	97	26	well	well	ADV
ajst-18565	97	27	,	,	PUNCT
ajst-18565	97	28	so	so	SCONJ
ajst-18565	97	29	as	as	SCONJ
ajst-18565	97	30	to	to	PART
ajst-18565	97	31	maintain	maintain	VERB
ajst-18565	97	32	the	the	DET
ajst-18565	97	33	generalization	generalization	NOUN
ajst-18565	97	34	ability	ability	NOUN
ajst-18565	97	35	of	of	ADP
ajst-18565	97	36	the	the	DET
ajst-18565	97	37	model	model	NOUN
ajst-18565	97	38	.	.	PUNCT
ajst-18565	98	1	ciou	ciou	NOUN
ajst-18565	98	2	calculates	calculate	VERB
ajst-18565	98	3	the	the	DET
ajst-18565	98	4	boundary	boundary	ADJ
ajst-18565	98	5	frame	frame	NOUN
ajst-18565	98	6	loss	loss	NOUN
ajst-18565	98	7	and	and	CCONJ
ajst-18565	98	8	adds	add	VERB
ajst-18565	98	9	the	the	DET
ajst-18565	98	10	aspect	aspect	NOUN
ajst-18565	98	11	ratio	ratio	NOUN
ajst-18565	98	12	calculation	calculation	NOUN
ajst-18565	98	13	,	,	PUNCT
ajst-18565	98	14	but	but	CCONJ
ajst-18565	98	15	does	do	AUX
ajst-18565	98	16	not	not	PART
ajst-18565	98	17	consider	consider	VERB
ajst-18565	98	18	the	the	DET
ajst-18565	98	19	balance	balance	NOUN
ajst-18565	98	20	of	of	ADP
ajst-18565	98	21	the	the	DET
ajst-18565	98	22	dataset	dataset	NOUN
ajst-18565	98	23	sample	sample	NOUN
ajst-18565	98	24	itself	itself	PRON
ajst-18565	98	25	.	.	PUNCT
ajst-18565	99	1	therefore	therefore	ADV
ajst-18565	99	2	,	,	PUNCT
ajst-18565	99	3	wise	wise	ADJ
ajst-18565	99	4	-	-	PUNCT
ajst-18565	99	5	iou	iou	NOUN
ajst-18565	99	6	is	be	AUX
ajst-18565	99	7	introduced	introduce	VERB
ajst-18565	99	8	as	as	ADP
ajst-18565	99	9	a	a	DET
ajst-18565	99	10	bounding	bounding	NOUN
ajst-18565	99	11	box	box	NOUN
ajst-18565	99	12	loss	loss	NOUN
ajst-18565	99	13	function	function	NOUN
ajst-18565	99	14	.	.	PUNCT
ajst-18565	100	1	the	the	DET
ajst-18565	100	2	formula	formula	NOUN
ajst-18565	100	3	for	for	ADP
ajst-18565	100	4	wise	wise	ADJ
ajst-18565	100	5	-	-	PUNCT
ajst-18565	100	6	iou	iou	NOUN
ajst-18565	100	7	is	be	AUX
ajst-18565	100	8	as	as	SCONJ
ajst-18565	100	9	follows	follow	VERB
ajst-18565	100	10	:	:	PUNCT
ajst-18565	101	1	wiou	wiou	NOUN
ajst-18565	101	2	wiou	wiou	NOUN
ajst-18565	101	3	ioul	ioul	NOUN
ajst-18565	101	4	r	r	NOUN
ajst-18565	101	5	l	l	PROPN
ajst-18565	102	1			PROPN
ajst-18565	102	2			PROPN
ajst-18565	102	3			PROPN
ajst-18565	102	4			PROPN
ajst-18565	102	5	(	(	PUNCT
ajst-18565	102	6	3	3	NUM
ajst-18565	102	7	)	)	SYM
ajst-18565	102	8	2	2	NUM
ajst-18565	102	9	2	2	NUM
ajst-18565	102	10	2	2	NUM
ajst-18565	102	11	2	2	NUM
ajst-18565	102	12	*	*	PUNCT
ajst-18565	102	13	(	(	PUNCT
ajst-18565	102	14	)	)	PUNCT
ajst-18565	102	15	(	(	PUNCT
ajst-18565	102	16	)	)	PUNCT
ajst-18565	102	17	exp	exp	NOUN
ajst-18565	102	18	(	(	PUNCT
ajst-18565	102	19	)	)	PUNCT
ajst-18565	102	20	(	(	PUNCT
ajst-18565	102	21	)	)	PUNCT
ajst-18565	102	22	gt	gt	PROPN
ajst-18565	102	23	gt	gt	PROPN
ajst-18565	102	24	wiou	wiou	NOUN
ajst-18565	102	25	g	g	PROPN
ajst-18565	102	26	g	g	NOUN
ajst-18565	102	27	x	x	PUNCT
ajst-18565	102	28	x	x	VERB
ajst-18565	102	29	y	y	NOUN
ajst-18565	102	30	y	y	NOUN
ajst-18565	102	31	r	r	PROPN
ajst-18565	102	32	w	w	PROPN
ajst-18565	102	33	h	h	PROPN
ajst-18565	102	34			PROPN
ajst-18565	102	35			VERB
ajst-18565	102	36			PROPN
ajst-18565	102	37			PRON
ajst-18565	102	38			PUNCT
ajst-18565	102	39	(	(	PUNCT
ajst-18565	102	40	4	4	NUM
ajst-18565	102	41	)	)	PUNCT
ajst-18565	102	42	in	in	ADP
ajst-18565	102	43	the	the	DET
ajst-18565	102	44	formula,	formula,	PROPN
ajst-18565	102	45	and	and	CCONJ
ajst-18565	102	46			PROPN
ajst-18565	102	47	are	be	AUX
ajst-18565	102	48	used	use	VERB
ajst-18565	102	49	as	as	ADP
ajst-18565	102	50	hyperparameters	hyperparameter	NOUN
ajst-18565	102	51	,	,	PUNCT
ajst-18565	102	52	which	which	PRON
ajst-18565	102	53	are	be	AUX
ajst-18565	102	54	generally	generally	ADV
ajst-18565	102	55	set	set	VERB
ajst-18565	102	56	to	to	ADP
ajst-18565	102	57	1.9	1.9	NUM
ajst-18565	102	58	and	and	CCONJ
ajst-18565	102	59	3.0	3.0	NUM
ajst-18565	102	60	.	.	PUNCT
ajst-18565	103	1	gw	gw	PROPN
ajst-18565	103	2	and	and	CCONJ
ajst-18565	103	3	gh	gh	PROPN
ajst-18565	103	4	are	be	AUX
ajst-18565	103	5	the	the	DET
ajst-18565	103	6	size	size	NOUN
ajst-18565	103	7	of	of	ADP
ajst-18565	103	8	the	the	DET
ajst-18565	103	9	minimum	minimum	NOUN
ajst-18565	103	10	surrounding	surround	VERB
ajst-18565	103	11	box	box	NOUN
ajst-18565	103	12	,	,	PUNCT
ajst-18565	103	13	(	(	PUNCT
ajst-18565	103	14	,	,	PUNCT
ajst-18565	103	15	)	)	PUNCT
ajst-18565	103	16	x	x	SYM
ajst-18565	103	17	y	y	PROPN
ajst-18565	103	18	and	and	CCONJ
ajst-18565	103	19	(	(	PUNCT
ajst-18565	103	20	,	,	PUNCT
ajst-18565	103	21	)	)	PUNCT
ajst-18565	103	22	gt	gt	PROPN
ajst-18565	104	1	gtx	gtx	PROPN
ajst-18565	104	2	y	y	PROPN
ajst-18565	104	3	are	be	AUX
ajst-18565	104	4	the	the	DET
ajst-18565	104	5	coordinates	coordinate	NOUN
ajst-18565	104	6	of	of	ADP
ajst-18565	104	7	the	the	DET
ajst-18565	104	8	center	center	ADJ
ajst-18565	104	9	point	point	NOUN
ajst-18565	104	10	of	of	ADP
ajst-18565	104	11	the	the	DET
ajst-18565	104	12	anchor	anchor	NOUN
ajst-18565	104	13	box	box	NOUN
ajst-18565	104	14	and	and	CCONJ
ajst-18565	104	15	the	the	DET
ajst-18565	104	16	target	target	NOUN
ajst-18565	104	17	box	box	NOUN
ajst-18565	104	18	,	,	PUNCT
ajst-18565	104	19	respectively	respectively	ADV
ajst-18565	104	20	.	.	PUNCT
ajst-18565	105	1			NOUN
ajst-18565	105	2	is	be	AUX
ajst-18565	105	3	defined	define	VERB
ajst-18565	105	4	as	as	ADP
ajst-18565	105	5	the	the	DET
ajst-18565	105	6	outlier	outlier	NOUN
ajst-18565	105	7	,	,	PUNCT
ajst-18565	105	8	used	use	VERB
ajst-18565	105	9	to	to	PART
ajst-18565	105	10	describe	describe	VERB
ajst-18565	105	11	the	the	DET
ajst-18565	105	12	mass	mass	NOUN
ajst-18565	105	13	of	of	ADP
ajst-18565	105	14	the	the	DET
ajst-18565	105	15	anchor	anchor	NOUN
ajst-18565	105	16	frame	frame	NOUN
ajst-18565	105	17	,	,	PUNCT
ajst-18565	105	18	expressed	express	VERB
ajst-18565	105	19	as	as	ADP
ajst-18565	105	20	:	:	PUNCT
ajst-18565	105	21			ADJ
ajst-18565	105	22			PROPN
ajst-18565	105	23	*	*	PUNCT
ajst-18565	105	24	0,iou	0,iou	NUM
ajst-18565	105	25	iou	iou	PROPN
ajst-18565	105	26	l	l	NOUN
ajst-18565	105	27	l	l	NOUN
ajst-18565	105	28			PROPN
ajst-18565	105	29			PROPN
ajst-18565	105	30			NOUN
ajst-18565	105	31			ADJ
ajst-18565	105	32	(	(	PUNCT
ajst-18565	105	33	5	5	NUM
ajst-18565	105	34	)	)	PUNCT
ajst-18565	105	35	in	in	ADP
ajst-18565	105	36	the	the	DET
ajst-18565	105	37	formula	formula	NOUN
ajst-18565	105	38	,	,	PUNCT
ajst-18565	105	39	*	*	PUNCT
ajst-18565	105	40	ioul	ioul	NOUN
ajst-18565	105	41	is	be	AUX
ajst-18565	105	42	the	the	DET
ajst-18565	105	43	gradient	gradient	ADJ
ajst-18565	105	44	gain	gain	NOUN
ajst-18565	105	45	of	of	ADP
ajst-18565	105	46	the	the	DET
ajst-18565	105	47	monotone	monotone	ADJ
ajst-18565	105	48	focusing	focus	VERB
ajst-18565	105	49	coefficient	coefficient	NOUN
ajst-18565	105	50	,	,	PUNCT
ajst-18565	105	51	where	where	SCONJ
ajst-18565	105	52	*	*	PUNCT
ajst-18565	105	53	represents	represent	VERB
ajst-18565	105	54	the	the	DET
ajst-18565	105	55	dynamic	dynamic	ADJ
ajst-18565	105	56	change	change	NOUN
ajst-18565	105	57	in	in	ADP
ajst-18565	105	58	the	the	DET
ajst-18565	105	59	training	training	NOUN
ajst-18565	105	60	process	process	NOUN
ajst-18565	105	61	according	accord	VERB
ajst-18565	105	62	to	to	ADP
ajst-18565	105	63	the	the	DET
ajst-18565	105	64	specific	specific	ADJ
ajst-18565	105	65	situation	situation	NOUN
ajst-18565	105	66	,	,	PUNCT
ajst-18565	105	67	ioul	ioul	NOUN
ajst-18565	105	68	is	be	AUX
ajst-18565	105	69	the	the	DET
ajst-18565	105	70	moving	move	VERB
ajst-18565	105	71	average	average	NOUN
ajst-18565	105	72	of	of	ADP
ajst-18565	105	73	the	the	DET
ajst-18565	105	74	momentum	momentum	NOUN
ajst-18565	105	75	m	m	NOUN
ajst-18565	105	76	,	,	PUNCT
ajst-18565	105	77	and	and	CCONJ
ajst-18565	105	78	the	the	DET
ajst-18565	105	79	dynamic	dynamic	ADJ
ajst-18565	105	80	updating	updating	NOUN
ajst-18565	105	81	of	of	ADP
ajst-18565	105	82	the	the	DET
ajst-18565	105	83	normalization	normalization	NOUN
ajst-18565	105	84	factor	factor	NOUN
ajst-18565	105	85	can	can	AUX
ajst-18565	105	86	keep	keep	VERB
ajst-18565	105	87	the	the	DET
ajst-18565	105	88	gradient	gradient	ADJ
ajst-18565	105	89	gain	gain	NOUN
ajst-18565	105	90	at	at	ADP
ajst-18565	105	91	a	a	DET
ajst-18565	105	92	higher	high	ADJ
ajst-18565	105	93	level	level	NOUN
ajst-18565	105	94	as	as	ADP
ajst-18565	105	95	a	a	DET
ajst-18565	105	96	whole	whole	NOUN
ajst-18565	105	97	,	,	PUNCT
ajst-18565	105	98	solving	solve	VERB
ajst-18565	105	99	the	the	DET
ajst-18565	105	100	problem	problem	NOUN
ajst-18565	105	101	of	of	ADP
ajst-18565	105	102	slow	slow	ADJ
ajst-18565	105	103	convergence	convergence	NOUN
ajst-18565	105	104	in	in	ADP
ajst-18565	105	105	the	the	DET
ajst-18565	105	106	late	late	ADJ
ajst-18565	105	107	training	training	NOUN
ajst-18565	105	108	period	period	NOUN
ajst-18565	105	109	.	.	PUNCT
ajst-18565	106	1	the	the	DET
ajst-18565	106	2	formula	formula	NOUN
ajst-18565	106	3	for	for	ADP
ajst-18565	106	4	calculating	calculate	VERB
ajst-18565	106	5	momentum	momentum	NOUN
ajst-18565	106	6	m	m	VERB
ajst-18565	106	7	is	be	AUX
ajst-18565	106	8	as	as	SCONJ
ajst-18565	106	9	follows	follow	VERB
ajst-18565	106	10	:	:	PUNCT
ajst-18565	106	11	1	1	NUM
ajst-18565	106	12	0.05tnm	0.05tnm	NUM
ajst-18565	106	13			NUM
ajst-18565	106	14			NOUN
ajst-18565	106	15	(	(	PUNCT
ajst-18565	106	16	6	6	NUM
ajst-18565	106	17	)	)	PUNCT
ajst-18565	106	18	in	in	ADP
ajst-18565	106	19	the	the	DET
ajst-18565	106	20	formula	formula	NOUN
ajst-18565	106	21	,	,	PUNCT
ajst-18565	106	22	t	t	PROPN
ajst-18565	106	23	represents	represent	VERB
ajst-18565	106	24	the	the	DET
ajst-18565	106	25	value	value	NOUN
ajst-18565	106	26	of	of	ADP
ajst-18565	106	27	the	the	DET
ajst-18565	106	28	training	training	NOUN
ajst-18565	106	29	rounds	round	VERB
ajst-18565	106	30	epoch	epoch	NOUN
ajst-18565	106	31	,	,	PUNCT
ajst-18565	106	32	and	and	CCONJ
ajst-18565	106	33	n	n	CCONJ
ajst-18565	106	34	represents	represent	VERB
ajst-18565	106	35	the	the	DET
ajst-18565	106	36	value	value	NOUN
ajst-18565	106	37	of	of	ADP
ajst-18565	106	38	batchsize	batchsize	NOUN
ajst-18565	106	39	during	during	ADP
ajst-18565	106	40	the	the	DET
ajst-18565	106	41	training	training	NOUN
ajst-18565	106	42	process	process	NOUN
ajst-18565	106	43	.	.	PUNCT
ajst-18565	107	1	after	after	ADP
ajst-18565	107	2	t	t	PROPN
ajst-18565	107	3	-	-	PUNCT
ajst-18565	107	4	wheel	wheel	NOUN
ajst-18565	107	5	training	training	NOUN
ajst-18565	107	6	,	,	PUNCT
ajst-18565	107	7	wiou	wiou	NOUN
ajst-18565	107	8	assigns	assign	VERB
ajst-18565	107	9	small	small	ADJ
ajst-18565	107	10	gradient	gradient	NOUN
ajst-18565	107	11	gains	gain	NOUN
ajst-18565	107	12	to	to	ADP
ajst-18565	107	13	low	low	ADJ
ajst-18565	107	14	-	-	PUNCT
ajst-18565	107	15	quality	quality	NOUN
ajst-18565	107	16	frames	frame	NOUN
ajst-18565	107	17	to	to	PART
ajst-18565	107	18	reduce	reduce	VERB
ajst-18565	107	19	harmful	harmful	ADJ
ajst-18565	107	20	gradients	gradient	NOUN
ajst-18565	107	21	,	,	PUNCT
ajst-18565	107	22	while	while	SCONJ
ajst-18565	107	23	focusing	focus	VERB
ajst-18565	107	24	on	on	ADP
ajst-18565	107	25	average	average	ADJ
ajst-18565	107	26	-	-	PUNCT
ajst-18565	107	27	quality	quality	NOUN
ajst-18565	107	28	frames	frame	NOUN
ajst-18565	107	29	to	to	PART
ajst-18565	107	30	improve	improve	VERB
ajst-18565	107	31	the	the	DET
ajst-18565	107	32	positioning	positioning	NOUN
ajst-18565	107	33	performance	performance	NOUN
ajst-18565	107	34	of	of	ADP
ajst-18565	107	35	the	the	DET
ajst-18565	107	36	model	model	NOUN
ajst-18565	107	37	.	.	PUNCT
ajst-18565	108	1	3	3	X
ajst-18565	108	2	.	.	X
ajst-18565	108	3	experiments	experiment	NOUN
ajst-18565	108	4	and	and	CCONJ
ajst-18565	108	5	analysis	analysis	NOUN
ajst-18565	108	6	3.1	3.1	NUM
ajst-18565	108	7	.	.	PUNCT
ajst-18565	109	1	experimental	experimental	ADJ
ajst-18565	109	2	environment	environment	NOUN
ajst-18565	109	3	configuration	configuration	NOUN
ajst-18565	109	4	in	in	ADP
ajst-18565	109	5	this	this	DET
ajst-18565	109	6	paper	paper	NOUN
ajst-18565	109	7	,	,	PUNCT
ajst-18565	109	8	the	the	DET
ajst-18565	109	9	experimental	experimental	ADJ
ajst-18565	109	10	operating	operating	NOUN
ajst-18565	109	11	system	system	NOUN
ajst-18565	109	12	is	be	AUX
ajst-18565	109	13	windows10	windows10	ADJ
ajst-18565	109	14	,	,	PUNCT
ajst-18565	109	15	the	the	DET
ajst-18565	109	16	graphics	graphic	NOUN
ajst-18565	109	17	card	card	NOUN
ajst-18565	109	18	is	be	AUX
ajst-18565	109	19	rtx	rtx	NOUN
ajst-18565	109	20	2080ti	2080ti	NOUN
ajst-18565	109	21	,	,	PUNCT
ajst-18565	109	22	and	and	CCONJ
ajst-18565	109	23	the	the	DET
ajst-18565	109	24	cpu	cpu	NOUN
ajst-18565	109	25	is	be	AUX
ajst-18565	109	26	intel	intel	PROPN
ajst-18565	109	27	xeon	xeon	PROPN
ajst-18565	109	28	platinum	platinum	NOUN
ajst-18565	109	29	8255c	8255c	NUM
ajst-18565	109	30	cpu@2.50ghz	cpu@2.50ghz	PROPN
ajst-18565	109	31	.	.	PUNCT
ajst-18565	110	1	pycharm	pycharm	PROPN
ajst-18565	110	2	is	be	AUX
ajst-18565	110	3	used	use	VERB
ajst-18565	110	4	as	as	ADP
ajst-18565	110	5	the	the	DET
ajst-18565	110	6	ide	ide	NOUN
ajst-18565	110	7	and	and	CCONJ
ajst-18565	110	8	pytorch	pytorch	NOUN
ajst-18565	110	9	is	be	AUX
ajst-18565	110	10	used	use	VERB
ajst-18565	110	11	as	as	ADP
ajst-18565	110	12	the	the	DET
ajst-18565	110	13	deep	deep	ADJ
ajst-18565	110	14	learning	learning	NOUN
ajst-18565	110	15	framework	framework	NOUN
ajst-18565	110	16	in	in	ADP
ajst-18565	110	17	the	the	DET
ajst-18565	110	18	experimental	experimental	ADJ
ajst-18565	110	19	environment	environment	NOUN
ajst-18565	110	20	.	.	PUNCT
ajst-18565	111	1	the	the	DET
ajst-18565	111	2	python	python	PROPN
ajst-18565	111	3	version	version	NOUN
ajst-18565	111	4	is	be	AUX
ajst-18565	111	5	3.8	3.8	NUM
ajst-18565	111	6	.	.	PUNCT
ajst-18565	112	1	in	in	ADP
ajst-18565	112	2	this	this	DET
ajst-18565	112	3	paper	paper	NOUN
ajst-18565	112	4	,	,	PUNCT
ajst-18565	112	5	the	the	DET
ajst-18565	112	6	stochastic	stochastic	ADJ
ajst-18565	112	7	gradient	gradient	ADJ
ajst-18565	112	8	descent	descent	NOUN
ajst-18565	112	9	(	(	PUNCT
ajst-18565	112	10	sgd	sgd	NOUN
ajst-18565	112	11	)	)	PUNCT
ajst-18565	112	12	optimizer	optimizer	NOUN
ajst-18565	112	13	was	be	AUX
ajst-18565	112	14	adopted	adopt	VERB
ajst-18565	112	15	for	for	ADP
ajst-18565	112	16	network	network	NOUN
ajst-18565	112	17	model	model	NOUN
ajst-18565	112	18	training	training	NOUN
ajst-18565	112	19	.	.	PUNCT
ajst-18565	113	1	the	the	DET
ajst-18565	113	2	initial	initial	ADJ
ajst-18565	113	3	learning	learning	NOUN
ajst-18565	113	4	rate	rate	NOUN
ajst-18565	113	5	was	be	AUX
ajst-18565	113	6	set	set	VERB
ajst-18565	113	7	to	to	ADP
ajst-18565	113	8	0.01	0.01	NUM
ajst-18565	113	9	,	,	PUNCT
ajst-18565	113	10	the	the	DET
ajst-18565	113	11	momentum	momentum	NOUN
ajst-18565	113	12	factor	factor	NOUN
ajst-18565	113	13	was	be	AUX
ajst-18565	113	14	set	set	VERB
ajst-18565	113	15	to	to	ADP
ajst-18565	113	16	0.937	0.937	NUM
ajst-18565	113	17	,	,	PUNCT
ajst-18565	113	18	and	and	CCONJ
ajst-18565	113	19	the	the	DET
ajst-18565	113	20	weight	weight	NOUN
ajst-18565	113	21	attenuation	attenuation	NOUN
ajst-18565	113	22	coefficient	coefficient	NOUN
ajst-18565	113	23	was	be	AUX
ajst-18565	113	24	set	set	VERB
ajst-18565	113	25	to	to	ADP
ajst-18565	113	26	0.0005	0.0005	NUM
ajst-18565	113	27	.	.	PUNCT
ajst-18565	114	1	the	the	DET
ajst-18565	114	2	total	total	ADJ
ajst-18565	114	3	number	number	NOUN
ajst-18565	114	4	of	of	ADP
ajst-18565	114	5	training	training	NOUN
ajst-18565	114	6	rounds	round	NOUN
ajst-18565	114	7	was	be	AUX
ajst-18565	114	8	set	set	VERB
ajst-18565	114	9	to	to	ADP
ajst-18565	114	10	300	300	NUM
ajst-18565	114	11	epoch	epoch	NOUN
ajst-18565	114	12	and	and	CCONJ
ajst-18565	114	13	32	32	NUM
ajst-18565	114	14	batchsize	batchsize	NOUN
ajst-18565	114	15	.	.	PUNCT
ajst-18565	115	1	workers	worker	NOUN
ajst-18565	115	2	is	be	AUX
ajst-18565	115	3	set	set	VERB
ajst-18565	115	4	to	to	ADP
ajst-18565	115	5	8	8	NUM
ajst-18565	115	6	.	.	PUNCT
ajst-18565	116	1	during	during	ADP
ajst-18565	116	2	the	the	DET
ajst-18565	116	3	training	training	NOUN
ajst-18565	116	4	of	of	ADP
ajst-18565	116	5	the	the	DET
ajst-18565	116	6	network	network	NOUN
ajst-18565	116	7	model	model	NOUN
ajst-18565	116	8	,	,	PUNCT
ajst-18565	116	9	the	the	DET
ajst-18565	116	10	input	input	NOUN
ajst-18565	116	11	image	image	NOUN
ajst-18565	116	12	size	size	NOUN
ajst-18565	116	13	was	be	AUX
ajst-18565	116	14	set	set	VERB
ajst-18565	116	15	to	to	ADP
ajst-18565	116	16	640×640	640×640	NUM
ajst-18565	116	17	.	.	PUNCT
ajst-18565	117	1	the	the	DET
ajst-18565	117	2	data	datum	NOUN
ajst-18565	117	3	of	of	ADP
ajst-18565	117	4	the	the	DET
ajst-18565	117	5	training	training	NOUN
ajst-18565	117	6	set	set	NOUN
ajst-18565	117	7	was	be	AUX
ajst-18565	117	8	input	input	NOUN
ajst-18565	117	9	to	to	ADP
ajst-18565	117	10	the	the	DET
ajst-18565	117	11	network	network	NOUN
ajst-18565	117	12	after	after	ADP
ajst-18565	117	13	mosaic	mosaic	ADJ
ajst-18565	117	14	data	datum	NOUN
ajst-18565	117	15	enhancement	enhancement	NOUN
ajst-18565	117	16	.	.	PUNCT
ajst-18565	118	1	all	all	DET
ajst-18565	118	2	the	the	DET
ajst-18565	118	3	models	model	NOUN
ajst-18565	118	4	were	be	AUX
ajst-18565	118	5	trained	train	VERB
ajst-18565	118	6	and	and	CCONJ
ajst-18565	118	7	tested	test	VERB
ajst-18565	118	8	on	on	ADP
ajst-18565	118	9	the	the	DET
ajst-18565	118	10	same	same	ADJ
ajst-18565	118	11	equipment	equipment	NOUN
ajst-18565	118	12	.	.	PUNCT
ajst-18565	119	1	3.2	3.2	NUM
ajst-18565	119	2	.	.	PUNCT
ajst-18565	119	3	experimental	experimental	ADJ
ajst-18565	119	4	evaluation	evaluation	NOUN
ajst-18565	119	5	index	index	NOUN
ajst-18565	119	6	in	in	ADP
ajst-18565	119	7	this	this	DET
ajst-18565	119	8	paper	paper	NOUN
ajst-18565	119	9	,	,	PUNCT
ajst-18565	119	10	precision	precision	NOUN
ajst-18565	119	11	,	,	PUNCT
ajst-18565	119	12	recall	recall	NOUN
ajst-18565	119	13	,	,	PUNCT
ajst-18565	119	14	map	map	NOUN
ajst-18565	119	15	,	,	PUNCT
ajst-18565	119	16	parameter	parameter	NOUN
ajst-18565	119	17	number	number	NOUN
ajst-18565	119	18	and	and	CCONJ
ajst-18565	119	19	calculation	calculation	NOUN
ajst-18565	119	20	amount	amount	NOUN
ajst-18565	119	21	are	be	AUX
ajst-18565	119	22	used	use	VERB
ajst-18565	119	23	as	as	ADP
ajst-18565	119	24	evaluation	evaluation	NOUN
ajst-18565	119	25	indexes	index	NOUN
ajst-18565	119	26	of	of	ADP
ajst-18565	119	27	the	the	DET
ajst-18565	119	28	model	model	NOUN
ajst-18565	119	29	.	.	PUNCT
ajst-18565	120	1	accuracy	accuracy	NOUN
ajst-18565	120	2	refers	refer	VERB
ajst-18565	120	3	to	to	ADP
ajst-18565	120	4	the	the	DET
ajst-18565	120	5	correct	correct	ADJ
ajst-18565	120	6	proportion	proportion	NOUN
ajst-18565	120	7	of	of	ADP
ajst-18565	120	8	all	all	DET
ajst-18565	120	9	detected	detect	VERB
ajst-18565	120	10	objects	object	NOUN
ajst-18565	120	11	;	;	PUNCT
ajst-18565	120	12	recall	recall	NOUN
ajst-18565	120	13	rate	rate	NOUN
ajst-18565	120	14	refers	refer	VERB
ajst-18565	120	15	to	to	ADP
ajst-18565	120	16	the	the	DET
ajst-18565	120	17	proportion	proportion	NOUN
ajst-18565	120	18	of	of	ADP
ajst-18565	120	19	targeted	target	VERB
ajst-18565	120	20	cases	case	NOUN
ajst-18565	120	21	correctly	correctly	ADV
ajst-18565	120	22	identified	identify	VERB
ajst-18565	120	23	by	by	ADP
ajst-18565	120	24	the	the	DET
ajst-18565	120	25	model	model	NOUN
ajst-18565	120	26	in	in	ADP
ajst-18565	120	27	all	all	DET
ajst-18565	120	28	correct	correct	ADJ
ajst-18565	120	29	cases	case	NOUN
ajst-18565	120	30	.	.	PUNCT
ajst-18565	121	1	the	the	DET
ajst-18565	121	2	map	map	NOUN
ajst-18565	121	3	is	be	AUX
ajst-18565	121	4	the	the	DET
ajst-18565	121	5	average	average	ADJ
ajst-18565	121	6	accuracy	accuracy	NOUN
ajst-18565	121	7	of	of	ADP
ajst-18565	121	8	multiple	multiple	ADJ
ajst-18565	121	9	categories	category	NOUN
ajst-18565	121	10	and	and	CCONJ
ajst-18565	121	11	is	be	AUX
ajst-18565	121	12	used	use	VERB
ajst-18565	121	13	to	to	PART
ajst-18565	121	14	evaluate	evaluate	VERB
ajst-18565	121	15	how	how	SCONJ
ajst-18565	121	16	good	good	ADJ
ajst-18565	121	17	the	the	DET
ajst-18565	121	18	model	model	NOUN
ajst-18565	121	19	is	be	AUX
ajst-18565	121	20	on	on	ADP
ajst-18565	121	21	all	all	DET
ajst-18565	121	22	categories	category	NOUN
ajst-18565	121	23	.	.	PUNCT
ajst-18565	122	1	the	the	DET
ajst-18565	122	2	calculation	calculation	NOUN
ajst-18565	122	3	formula	formula	NOUN
ajst-18565	122	4	of	of	ADP
ajst-18565	122	5	evaluation	evaluation	NOUN
ajst-18565	122	6	index	index	NOUN
ajst-18565	122	7	is	be	AUX
ajst-18565	122	8	as	as	SCONJ
ajst-18565	122	9	follows	follow	VERB
ajst-18565	122	10	:	:	PUNCT
ajst-18565	122	11	tp	tp	ADP
ajst-18565	122	12	p	p	PROPN
ajst-18565	122	13	tp	tp	ADP
ajst-18565	122	14	fp	fp	PROPN
ajst-18565	122	15			PROPN
ajst-18565	122	16			X
ajst-18565	122	17	(	(	PUNCT
ajst-18565	122	18	7	7	NUM
ajst-18565	122	19	)	)	PUNCT
ajst-18565	122	20	166	166	NUM
ajst-18565	122	21	tp	tp	ADP
ajst-18565	122	22	r	r	NOUN
ajst-18565	122	23	tp	tp	NOUN
ajst-18565	122	24	fn	fn	PROPN
ajst-18565	123	1			PROPN
ajst-18565	123	2			X
ajst-18565	123	3	(	(	PUNCT
ajst-18565	123	4	8)	8)	NUM
ajst-18565	123	5	1	1	NUM
ajst-18565	123	6	0	0	NUM
ajst-18565	123	7	(	(	PUNCT
ajst-18565	123	8	)	)	PUNCT
ajst-18565	123	9	ap	ap	PROPN
ajst-18565	124	1	p	p	PROPN
ajst-18565	124	2	r	r	VERB
ajst-18565	124	3			X
ajst-18565	124	4	(	(	PUNCT
ajst-18565	124	5	9	9	NUM
ajst-18565	124	6	)	)	SYM
ajst-18565	124	7	1	1	NUM
ajst-18565	124	8	1	1	NUM
ajst-18565	124	9	c	c	NOUN
ajst-18565	125	1	i	i	PRON
ajst-18565	125	2	i	i	PRON
ajst-18565	125	3	map	map	VERB
ajst-18565	125	4	ap	ap	INTJ
ajst-18565	125	5	n	n	ADV
ajst-18565	125	6			NOUN
ajst-18565	126	1			NOUN
ajst-18565	126	2			X
ajst-18565	126	3	(	(	PUNCT
ajst-18565	126	4	10	10	NUM
ajst-18565	126	5	)	)	PUNCT
ajst-18565	126	6	in	in	ADP
ajst-18565	126	7	the	the	DET
ajst-18565	126	8	formula	formula	NOUN
ajst-18565	126	9	,	,	PUNCT
ajst-18565	126	10	tp	tp	NOUN
ajst-18565	126	11	represents	represent	VERB
ajst-18565	126	12	the	the	DET
ajst-18565	126	13	correct	correct	ADJ
ajst-18565	126	14	number	number	NOUN
ajst-18565	126	15	of	of	ADP
ajst-18565	126	16	positive	positive	ADJ
ajst-18565	126	17	samples	sample	NOUN
ajst-18565	126	18	detected	detect	VERB
ajst-18565	126	19	;	;	PUNCT
ajst-18565	126	20	fp	fp	X
ajst-18565	126	21	represents	represent	VERB
ajst-18565	126	22	the	the	DET
ajst-18565	126	23	number	number	NOUN
ajst-18565	126	24	of	of	ADP
ajst-18565	126	25	positive	positive	ADJ
ajst-18565	126	26	samples	sample	NOUN
ajst-18565	126	27	for	for	ADP
ajst-18565	126	28	detecting	detect	VERB
ajst-18565	126	29	errors	error	NOUN
ajst-18565	126	30	;	;	PUNCT
ajst-18565	126	31	fn	fn	NOUN
ajst-18565	126	32	represents	represent	VERB
ajst-18565	126	33	the	the	DET
ajst-18565	126	34	negative	negative	ADJ
ajst-18565	126	35	sample	sample	NOUN
ajst-18565	126	36	number	number	NOUN
ajst-18565	126	37	of	of	ADP
ajst-18565	126	38	detection	detection	NOUN
ajst-18565	126	39	errors	error	NOUN
ajst-18565	126	40	;	;	PUNCT
ajst-18565	126	41	n	n	PRON
ajst-18565	126	42	indicates	indicate	VERB
ajst-18565	126	43	the	the	DET
ajst-18565	126	44	number	number	NOUN
ajst-18565	126	45	of	of	ADP
ajst-18565	126	46	categories	category	NOUN
ajst-18565	126	47	.	.	PUNCT
ajst-18565	127	1	3.3	3.3	NUM
ajst-18565	127	2	.	.	PUNCT
ajst-18565	127	3	dataset	dataset	VERB
ajst-18565	127	4	the	the	DET
ajst-18565	127	5	data	datum	NOUN
ajst-18565	127	6	set	set	VERB
ajst-18565	127	7	adopted	adopt	VERB
ajst-18565	127	8	in	in	ADP
ajst-18565	127	9	this	this	DET
ajst-18565	127	10	paper	paper	NOUN
ajst-18565	127	11	is	be	AUX
ajst-18565	127	12	the	the	DET
ajst-18565	127	13	open	open	ADJ
ajst-18565	127	14	data	datum	NOUN
ajst-18565	127	15	set	set	VERB
ajst-18565	127	16	rdd2022(road	rdd2022(road	PART
ajst-18565	127	17	damage	damage	NOUN
ajst-18565	127	18	detection-2022	detection-2022	NOUN
ajst-18565	127	19	)	)	PUNCT
ajst-18565	128	1	[	[	X
ajst-18565	128	2	12	12	NUM
ajst-18565	128	3	]	]	PUNCT
ajst-18565	128	4	.	.	PUNCT
ajst-18565	129	1	it	it	PRON
ajst-18565	129	2	includes	include	VERB
ajst-18565	129	3	47,420	47,420	NUM
ajst-18565	129	4	road	road	NOUN
ajst-18565	129	5	images	image	NOUN
ajst-18565	129	6	from	from	ADP
ajst-18565	129	7	six	six	NUM
ajst-18565	129	8	countries	country	NOUN
ajst-18565	129	9	,	,	PUNCT
ajst-18565	129	10	including	include	VERB
ajst-18565	129	11	china	china	PROPN
ajst-18565	129	12	,	,	PUNCT
ajst-18565	129	13	india	india	PROPN
ajst-18565	129	14	,	,	PUNCT
ajst-18565	129	15	the	the	DET
ajst-18565	129	16	united	united	PROPN
ajst-18565	129	17	states	states	PROPN
ajst-18565	129	18	,	,	PUNCT
ajst-18565	129	19	japan	japan	PROPN
ajst-18565	129	20	,	,	PUNCT
ajst-18565	129	21	the	the	DET
ajst-18565	129	22	czech	czech	PROPN
ajst-18565	129	23	republic	republic	NOUN
ajst-18565	129	24	and	and	CCONJ
ajst-18565	129	25	norway	norway	PROPN
ajst-18565	129	26	,	,	PUNCT
ajst-18565	129	27	and	and	CCONJ
ajst-18565	129	28	contains	contain	VERB
ajst-18565	129	29	more	more	ADJ
ajst-18565	129	30	than	than	ADP
ajst-18565	129	31	50,000	50,000	NUM
ajst-18565	129	32	examples	example	NOUN
ajst-18565	129	33	of	of	ADP
ajst-18565	129	34	road	road	NOUN
ajst-18565	129	35	damage	damage	NOUN
ajst-18565	129	36	.	.	PUNCT
ajst-18565	130	1	the	the	DET
ajst-18565	130	2	data	datum	NOUN
ajst-18565	130	3	set	set	VERB
ajst-18565	130	4	mainly	mainly	ADV
ajst-18565	130	5	divides	divide	VERB
ajst-18565	130	6	road	road	NOUN
ajst-18565	130	7	damage	damage	NOUN
ajst-18565	130	8	into	into	ADP
ajst-18565	130	9	four	four	NUM
ajst-18565	130	10	common	common	ADJ
ajst-18565	130	11	types	type	NOUN
ajst-18565	130	12	of	of	ADP
ajst-18565	130	13	road	road	NOUN
ajst-18565	130	14	damage	damage	NOUN
ajst-18565	130	15	,	,	PUNCT
ajst-18565	130	16	namely	namely	ADV
ajst-18565	130	17	d00(longitudinal	d00(longitudinal	ADJ
ajst-18565	130	18	cracks	crack	NOUN
ajst-18565	130	19	)	)	PUNCT
ajst-18565	130	20	,	,	PUNCT
ajst-18565	130	21	d10(lateral	d10(lateral	ADJ
ajst-18565	130	22	cracks	crack	NOUN
ajst-18565	130	23	)	)	PUNCT
ajst-18565	130	24	,	,	PUNCT
ajst-18565	130	25	d20(mesh	d20(mesh	NOUN
ajst-18565	130	26	cracks	crack	NOUN
ajst-18565	130	27	)	)	PUNCT
ajst-18565	130	28	and	and	CCONJ
ajst-18565	130	29	d40(potholes	d40(pothole	NOUN
ajst-18565	130	30	)	)	PUNCT
ajst-18565	130	31	.	.	PUNCT
ajst-18565	131	1	in	in	ADP
ajst-18565	131	2	addition	addition	NOUN
ajst-18565	131	3	,	,	PUNCT
ajst-18565	131	4	the	the	DET
ajst-18565	131	5	data	datum	NOUN
ajst-18565	131	6	set	set	VERB
ajst-18565	131	7	also	also	ADV
ajst-18565	131	8	includes	include	VERB
ajst-18565	131	9	some	some	DET
ajst-18565	131	10	other	other	ADJ
ajst-18565	131	11	types	type	NOUN
ajst-18565	131	12	of	of	ADP
ajst-18565	131	13	road	road	NOUN
ajst-18565	131	14	damage	damage	NOUN
ajst-18565	131	15	,	,	PUNCT
ajst-18565	131	16	such	such	ADJ
ajst-18565	131	17	as	as	ADP
ajst-18565	131	18	pedestrian	pedestrian	NOUN
ajst-18565	131	19	crossing	crossing	NOUN
ajst-18565	131	20	blur	blur	PROPN
ajst-18565	131	21	d43	d43	PROPN
ajst-18565	131	22	,	,	PUNCT
ajst-18565	131	23	white	white	ADJ
ajst-18565	131	24	line	line	NOUN
ajst-18565	131	25	blur	blur	PROPN
ajst-18565	131	26	d44	d44	PROPN
ajst-18565	131	27	,	,	PUNCT
ajst-18565	131	28	etc	etc	X
ajst-18565	131	29	.	.	X
ajst-18565	131	30	,	,	PUNCT
ajst-18565	131	31	but	but	CCONJ
ajst-18565	131	32	they	they	PRON
ajst-18565	131	33	do	do	AUX
ajst-18565	131	34	not	not	PART
ajst-18565	131	35	belong	belong	VERB
ajst-18565	131	36	to	to	ADP
ajst-18565	131	37	the	the	DET
ajst-18565	131	38	detection	detection	NOUN
ajst-18565	131	39	objects	object	VERB
ajst-18565	131	40	in	in	ADP
ajst-18565	131	41	this	this	DET
ajst-18565	131	42	paper	paper	NOUN
ajst-18565	131	43	,	,	PUNCT
ajst-18565	131	44	so	so	CCONJ
ajst-18565	131	45	after	after	ADP
ajst-18565	131	46	data	datum	NOUN
ajst-18565	131	47	cleaning	clean	VERB
ajst-18565	131	48	,	,	PUNCT
ajst-18565	131	49	redundant	redundant	ADJ
ajst-18565	131	50	data	data	NOUN
ajst-18565	131	51	annotations	annotation	NOUN
ajst-18565	131	52	are	be	AUX
ajst-18565	131	53	removed	remove	VERB
ajst-18565	131	54	.	.	PUNCT
ajst-18565	132	1	in	in	ADP
ajst-18565	132	2	this	this	DET
ajst-18565	132	3	paper	paper	NOUN
ajst-18565	132	4	,	,	PUNCT
ajst-18565	132	5	yolo	yolo	ADJ
ajst-18565	132	6	series	series	PROPN
ajst-18565	132	7	algorithms	algorithm	NOUN
ajst-18565	132	8	are	be	AUX
ajst-18565	132	9	used	use	VERB
ajst-18565	132	10	as	as	ADP
ajst-18565	132	11	the	the	DET
ajst-18565	132	12	benchmark	benchmark	NOUN
ajst-18565	132	13	model	model	NOUN
ajst-18565	132	14	.	.	PUNCT
ajst-18565	133	1	in	in	ADP
ajst-18565	133	2	the	the	DET
ajst-18565	133	3	process	process	NOUN
ajst-18565	133	4	of	of	ADP
ajst-18565	133	5	training	training	NOUN
ajst-18565	133	6	,	,	PUNCT
ajst-18565	133	7	xml	xml	VERB
ajst-18565	133	8	annotation	annotation	NOUN
ajst-18565	133	9	files	file	NOUN
ajst-18565	133	10	in	in	ADP
ajst-18565	133	11	pascal	pascal	PROPN
ajst-18565	133	12	voc	voc	NOUN
ajst-18565	133	13	format	format	NOUN
ajst-18565	133	14	need	need	VERB
ajst-18565	133	15	to	to	PART
ajst-18565	133	16	be	be	AUX
ajst-18565	133	17	converted	convert	VERB
ajst-18565	133	18	to	to	AUX
ajst-18565	133	19	txt	txt	VERB
ajst-18565	133	20	annotation	annotation	NOUN
ajst-18565	133	21	files	file	NOUN
ajst-18565	133	22	in	in	ADP
ajst-18565	133	23	yolo	yolo	ADJ
ajst-18565	133	24	format	format	NOUN
ajst-18565	133	25	first	first	ADV
ajst-18565	133	26	.	.	PUNCT
ajst-18565	134	1	in	in	ADP
ajst-18565	134	2	the	the	DET
ajst-18565	134	3	original	original	ADJ
ajst-18565	134	4	data	datum	NOUN
ajst-18565	134	5	set	set	NOUN
ajst-18565	134	6	,	,	PUNCT
ajst-18565	134	7	there	there	PRON
ajst-18565	134	8	are	be	VERB
ajst-18565	134	9	some	some	DET
ajst-18565	134	10	pictures	picture	NOUN
ajst-18565	134	11	that	that	PRON
ajst-18565	134	12	do	do	AUX
ajst-18565	134	13	not	not	PART
ajst-18565	134	14	meet	meet	VERB
ajst-18565	134	15	the	the	DET
ajst-18565	134	16	requirements	requirement	NOUN
ajst-18565	134	17	,	,	PUNCT
ajst-18565	134	18	so	so	SCONJ
ajst-18565	134	19	it	it	PRON
ajst-18565	134	20	is	be	AUX
ajst-18565	134	21	necessary	necessary	ADJ
ajst-18565	134	22	to	to	PART
ajst-18565	134	23	filter	filter	VERB
ajst-18565	134	24	these	these	DET
ajst-18565	134	25	pictures	picture	NOUN
ajst-18565	134	26	.	.	PUNCT
ajst-18565	135	1	after	after	ADP
ajst-18565	135	2	data	datum	NOUN
ajst-18565	135	3	cleaning	cleaning	NOUN
ajst-18565	135	4	,	,	PUNCT
ajst-18565	135	5	this	this	DET
ajst-18565	135	6	paper	paper	NOUN
ajst-18565	135	7	randomly	randomly	ADV
ajst-18565	135	8	selected	select	VERB
ajst-18565	135	9	11600	11600	NUM
ajst-18565	135	10	pictures	picture	NOUN
ajst-18565	135	11	from	from	ADP
ajst-18565	135	12	the	the	DET
ajst-18565	135	13	rdd2022	rdd2022	NOUN
ajst-18565	135	14	data	datum	NOUN
ajst-18565	135	15	set	set	VERB
ajst-18565	135	16	as	as	ADP
ajst-18565	135	17	the	the	DET
ajst-18565	135	18	data	datum	NOUN
ajst-18565	135	19	set	set	VERB
ajst-18565	135	20	of	of	ADP
ajst-18565	135	21	this	this	DET
ajst-18565	135	22	experiment	experiment	NOUN
ajst-18565	135	23	,	,	PUNCT
ajst-18565	135	24	and	and	CCONJ
ajst-18565	135	25	divided	divide	VERB
ajst-18565	135	26	the	the	DET
ajst-18565	135	27	training	training	NOUN
ajst-18565	135	28	set	set	NOUN
ajst-18565	135	29	,	,	PUNCT
ajst-18565	135	30	verification	verification	NOUN
ajst-18565	135	31	set	set	NOUN
ajst-18565	135	32	and	and	CCONJ
ajst-18565	135	33	test	test	NOUN
ajst-18565	135	34	set	set	VERB
ajst-18565	135	35	according	accord	VERB
ajst-18565	135	36	to	to	ADP
ajst-18565	135	37	the	the	DET
ajst-18565	135	38	ratio	ratio	NOUN
ajst-18565	135	39	of	of	ADP
ajst-18565	135	40	8:1:1	8:1:1	NUM
ajst-18565	135	41	,	,	PUNCT
ajst-18565	135	42	including	include	VERB
ajst-18565	135	43	9280	9280	NUM
ajst-18565	135	44	pictures	picture	NOUN
ajst-18565	135	45	in	in	ADP
ajst-18565	135	46	the	the	DET
ajst-18565	135	47	training	training	NOUN
ajst-18565	135	48	set	set	NOUN
ajst-18565	135	49	,	,	PUNCT
ajst-18565	135	50	1160	1160	NUM
ajst-18565	135	51	pictures	picture	NOUN
ajst-18565	135	52	in	in	ADP
ajst-18565	135	53	the	the	DET
ajst-18565	135	54	verification	verification	NOUN
ajst-18565	135	55	set	set	VERB
ajst-18565	135	56	and	and	CCONJ
ajst-18565	135	57	1160	1160	NUM
ajst-18565	135	58	pictures	picture	NOUN
ajst-18565	135	59	in	in	ADP
ajst-18565	135	60	the	the	DET
ajst-18565	135	61	test	test	NOUN
ajst-18565	135	62	set	set	NOUN
ajst-18565	135	63	.	.	PUNCT
ajst-18565	136	1	in	in	ADP
ajst-18565	136	2	order	order	NOUN
ajst-18565	136	3	to	to	PART
ajst-18565	136	4	more	more	ADV
ajst-18565	136	5	intuitively	intuitively	ADV
ajst-18565	136	6	show	show	VERB
ajst-18565	136	7	the	the	DET
ajst-18565	136	8	different	different	ADJ
ajst-18565	136	9	types	type	NOUN
ajst-18565	136	10	of	of	ADP
ajst-18565	136	11	road	road	NOUN
ajst-18565	136	12	damage	damage	NOUN
ajst-18565	136	13	examples	example	NOUN
ajst-18565	136	14	in	in	ADP
ajst-18565	136	15	the	the	DET
ajst-18565	136	16	dataset	dataset	NOUN
ajst-18565	136	17	,	,	PUNCT
ajst-18565	136	18	four	four	NUM
ajst-18565	136	19	data	datum	NOUN
ajst-18565	136	20	categories	category	NOUN
ajst-18565	136	21	are	be	AUX
ajst-18565	136	22	shown	show	VERB
ajst-18565	136	23	,	,	PUNCT
ajst-18565	136	24	namely	namely	ADV
ajst-18565	136	25	(	(	PUNCT
ajst-18565	136	26	a	a	X
ajst-18565	136	27	)	)	PUNCT
ajst-18565	136	28	longitudinal	longitudinal	ADJ
ajst-18565	136	29	cracks	crack	NOUN
ajst-18565	136	30	,	,	PUNCT
ajst-18565	136	31	(	(	PUNCT
ajst-18565	136	32	b	b	X
ajst-18565	136	33	)	)	PUNCT
ajst-18565	136	34	transverse	transverse	NOUN
ajst-18565	136	35	cracks	crack	NOUN
ajst-18565	136	36	,	,	PUNCT
ajst-18565	136	37	(	(	PUNCT
ajst-18565	136	38	c	c	X
ajst-18565	136	39	)	)	PUNCT
ajst-18565	136	40	mesh	mesh	NOUN
ajst-18565	136	41	cracks	crack	NOUN
ajst-18565	136	42	,	,	PUNCT
ajst-18565	136	43	and	and	CCONJ
ajst-18565	136	44	(	(	PUNCT
ajst-18565	136	45	d	d	NOUN
ajst-18565	136	46	)	)	PUNCT
ajst-18565	136	47	potholes	pothole	NOUN
ajst-18565	136	48	.	.	PUNCT
ajst-18565	137	1	figure	figure	VERB
ajst-18565	137	2	6	6	NUM
ajst-18565	137	3	.	.	PUNCT
ajst-18565	137	4	road	road	NOUN
ajst-18565	137	5	damage	damage	NOUN
ajst-18565	137	6	examples	example	NOUN
ajst-18565	137	7	in	in	ADP
ajst-18565	137	8	the	the	DET
ajst-18565	137	9	dataset	dataset	NOUN
ajst-18565	137	10	3.4	3.4	NUM
ajst-18565	137	11	.	.	PUNCT
ajst-18565	138	1	experimental	experimental	ADJ
ajst-18565	138	2	result	result	NOUN
ajst-18565	138	3	3.4.1	3.4.1	NUM
ajst-18565	138	4	.	.	PUNCT
ajst-18565	138	5	comparative	comparative	ADJ
ajst-18565	138	6	experiment	experiment	NOUN
ajst-18565	138	7	of	of	ADP
ajst-18565	138	8	attention	attention	NOUN
ajst-18565	138	9	mechanism	mechanism	NOUN
ajst-18565	138	10	the	the	DET
ajst-18565	138	11	experiment	experiment	NOUN
ajst-18565	138	12	also	also	ADV
ajst-18565	138	13	uses	use	VERB
ajst-18565	138	14	several	several	ADJ
ajst-18565	138	15	other	other	ADJ
ajst-18565	138	16	attentional	attentional	ADJ
ajst-18565	138	17	mechanism	mechanism	NOUN
ajst-18565	138	18	modules	module	NOUN
ajst-18565	138	19	,	,	PUNCT
ajst-18565	138	20	such	such	ADJ
ajst-18565	138	21	as	as	ADP
ajst-18565	138	22	se	se	X
ajst-18565	138	23	attention	attention	NOUN
ajst-18565	138	24	module	module	NOUN
ajst-18565	138	25	,	,	PUNCT
ajst-18565	138	26	ca	can	AUX
ajst-18565	138	27	attention	attention	NOUN
ajst-18565	138	28	module	module	NOUN
ajst-18565	138	29	and	and	CCONJ
ajst-18565	138	30	cbam	cbam	NOUN
ajst-18565	138	31	attention	attention	NOUN
ajst-18565	138	32	module	module	NOUN
ajst-18565	138	33	.	.	PUNCT
ajst-18565	139	1	the	the	DET
ajst-18565	139	2	experimental	experimental	ADJ
ajst-18565	139	3	results	result	NOUN
ajst-18565	139	4	are	be	AUX
ajst-18565	139	5	shown	show	VERB
ajst-18565	139	6	in	in	ADP
ajst-18565	139	7	table	table	NOUN
ajst-18565	139	8	1	1	NUM
ajst-18565	139	9	.	.	PUNCT
ajst-18565	139	10	table	table	NOUN
ajst-18565	139	11	1	1	NUM
ajst-18565	139	12	.	.	PUNCT
ajst-18565	139	13	comparison	comparison	NOUN
ajst-18565	139	14	results	result	NOUN
ajst-18565	139	15	of	of	ADP
ajst-18565	139	16	multiple	multiple	ADJ
ajst-18565	139	17	attention	attention	NOUN
ajst-18565	139	18	mechanisms	mechanism	NOUN
ajst-18565	140	1	numble	numble	ADJ
ajst-18565	140	2	attention	attention	NOUN
ajst-18565	140	3	module	module	NOUN
ajst-18565	140	4	map50	map50	PROPN
ajst-18565	140	5	map50	map50	PROPN
ajst-18565	140	6	-	-	PUNCT
ajst-18565	140	7	95	95	NUM
ajst-18565	140	8	params	param	NOUN
ajst-18565	140	9	/	/	SYM
ajst-18565	140	10	m	m	NOUN
ajst-18565	140	11	gflops	gflop	NOUN
ajst-18565	140	12	1	1	NUM
ajst-18565	140	13	yolov8n	yolov8n	NOUN
ajst-18565	140	14	56.4	56.4	NUM
ajst-18565	140	15	27.9	27.9	NUM
ajst-18565	140	16	3.0	3.0	NUM
ajst-18565	140	17	8.1	8.1	NUM
ajst-18565	140	18	2	2	NUM
ajst-18565	140	19	yolov8n+se	yolov8n+se	NOUN
ajst-18565	140	20	56.1	56.1	NUM
ajst-18565	140	21	27.5	27.5	NUM
ajst-18565	140	22	3.0	3.0	NUM
ajst-18565	140	23	8.1	8.1	NUM
ajst-18565	140	24	3	3	NUM
ajst-18565	140	25	yolov8+cbam	yolov8+cbam	NOUN
ajst-18565	140	26	56.7	56.7	NUM
ajst-18565	140	27	28.1	28.1	NUM
ajst-18565	140	28	3.1	3.1	NUM
ajst-18565	140	29	8.1	8.1	NUM
ajst-18565	140	30	4	4	NUM
ajst-18565	140	31	yolov8+ca	yolov8+ca	PROPN
ajst-18565	140	32	56.9	56.9	NUM
ajst-18565	140	33	28.2	28.2	NUM
ajst-18565	140	34	3.0	3.0	NUM
ajst-18565	140	35	8.1	8.1	NUM
ajst-18565	140	36	5	5	NUM
ajst-18565	140	37	yolov8+senetv2	yolov8+senetv2	NOUN
ajst-18565	140	38	57.5	57.5	NUM
ajst-18565	140	39	28.5	28.5	NUM
ajst-18565	140	40	3.0	3.0	NUM
ajst-18565	140	41	8.1	8.1	NUM
ajst-18565	140	42	as	as	SCONJ
ajst-18565	140	43	can	can	AUX
ajst-18565	140	44	be	be	AUX
ajst-18565	140	45	seen	see	VERB
ajst-18565	140	46	from	from	ADP
ajst-18565	140	47	table	table	NOUN
ajst-18565	140	48	1	1	NUM
ajst-18565	140	49	,	,	PUNCT
ajst-18565	140	50	the	the	DET
ajst-18565	140	51	addition	addition	NOUN
ajst-18565	140	52	of	of	ADP
ajst-18565	140	53	senetv2	senetv2	NOUN
ajst-18565	140	54	attention	attention	NOUN
ajst-18565	140	55	mechanism	mechanism	NOUN
ajst-18565	140	56	greatly	greatly	ADV
ajst-18565	140	57	improves	improve	VERB
ajst-18565	140	58	the	the	DET
ajst-18565	140	59	accuracy	accuracy	NOUN
ajst-18565	140	60	compared	compare	VERB
ajst-18565	140	61	with	with	ADP
ajst-18565	140	62	other	other	ADJ
ajst-18565	140	63	attention	attention	NOUN
ajst-18565	140	64	mechanisms	mechanism	NOUN
ajst-18565	140	65	3.4.2	3.4.2	NUM
ajst-18565	140	66	.	.	PUNCT
ajst-18565	141	1	comparison	comparison	NOUN
ajst-18565	141	2	of	of	ADP
ajst-18565	141	3	ablation	ablation	NOUN
ajst-18565	141	4	experiments	experiment	NOUN
ajst-18565	141	5	in	in	ADP
ajst-18565	141	6	order	order	NOUN
ajst-18565	141	7	to	to	PART
ajst-18565	141	8	verify	verify	VERB
ajst-18565	141	9	the	the	DET
ajst-18565	141	10	accuracy	accuracy	NOUN
ajst-18565	141	11	of	of	ADP
ajst-18565	141	12	the	the	DET
ajst-18565	141	13	improved	improved	ADJ
ajst-18565	141	14	algorithm	algorithm	NOUN
ajst-18565	141	15	in	in	ADP
ajst-18565	141	16	this	this	DET
ajst-18565	141	17	paper	paper	NOUN
ajst-18565	141	18	,	,	PUNCT
ajst-18565	141	19	several	several	ADJ
ajst-18565	141	20	models	model	NOUN
ajst-18565	141	21	need	need	VERB
ajst-18565	141	22	to	to	PART
ajst-18565	141	23	be	be	AUX
ajst-18565	141	24	established	establish	VERB
ajst-18565	141	25	to	to	PART
ajst-18565	141	26	conduct	conduct	VERB
ajst-18565	141	27	ablation	ablation	NOUN
ajst-18565	141	28	experiments	experiment	NOUN
ajst-18565	141	29	.	.	PUNCT
ajst-18565	142	1	as	as	SCONJ
ajst-18565	142	2	shown	show	VERB
ajst-18565	142	3	in	in	ADP
ajst-18565	142	4	table	table	NOUN
ajst-18565	142	5	2	2	NUM
ajst-18565	142	6	,	,	PUNCT
ajst-18565	142	7	the	the	DET
ajst-18565	142	8	improved	improved	ADJ
ajst-18565	142	9	algorithm	algorithm	NOUN
ajst-18565	142	10	adopts	adopt	VERB
ajst-18565	142	11	a	a	DET
ajst-18565	142	12	more	more	ADV
ajst-18565	142	13	efficient	efficient	ADJ
ajst-18565	142	14	network	network	NOUN
ajst-18565	142	15	structure	structure	NOUN
ajst-18565	142	16	to	to	PART
ajst-18565	142	17	improve	improve	VERB
ajst-18565	142	18	the	the	DET
ajst-18565	142	19	network	network	NOUN
ajst-18565	142	20	structure	structure	NOUN
ajst-18565	142	21	of	of	ADP
ajst-18565	142	22	yolov8n	yolov8n	PROPN
ajst-18565	142	23	,	,	PUNCT
ajst-18565	142	24	and	and	CCONJ
ajst-18565	142	25	each	each	DET
ajst-18565	142	26	module	module	NOUN
ajst-18565	142	27	plays	play	VERB
ajst-18565	142	28	a	a	DET
ajst-18565	142	29	role	role	NOUN
ajst-18565	142	30	in	in	ADP
ajst-18565	142	31	promoting	promote	VERB
ajst-18565	142	32	the	the	DET
ajst-18565	142	33	model	model	NOUN
ajst-18565	142	34	.	.	PUNCT
ajst-18565	143	1	through	through	ADP
ajst-18565	143	2	the	the	DET
ajst-18565	143	3	final	final	ADJ
ajst-18565	143	4	experiment	experiment	NOUN
ajst-18565	143	5	,	,	PUNCT
ajst-18565	143	6	the	the	DET
ajst-18565	143	7	accuracy	accuracy	NOUN
ajst-18565	143	8	is	be	AUX
ajst-18565	143	9	improved	improve	VERB
ajst-18565	143	10	while	while	SCONJ
ajst-18565	143	11	the	the	DET
ajst-18565	143	12	number	number	NOUN
ajst-18565	143	13	of	of	ADP
ajst-18565	143	14	parameters	parameter	NOUN
ajst-18565	143	15	and	and	CCONJ
ajst-18565	143	16	calculation	calculation	NOUN
ajst-18565	143	17	amount	amount	NOUN
ajst-18565	143	18	of	of	ADP
ajst-18565	143	19	the	the	DET
ajst-18565	143	20	model	model	NOUN
ajst-18565	143	21	are	be	AUX
ajst-18565	143	22	reduced	reduce	VERB
ajst-18565	143	23	slightly	slightly	ADV
ajst-18565	143	24	.	.	PUNCT
ajst-18565	144	1	table	table	NOUN
ajst-18565	144	2	2	2	NUM
ajst-18565	144	3	.	.	PUNCT
ajst-18565	144	4	comparison	comparison	NOUN
ajst-18565	144	5	results	result	NOUN
ajst-18565	144	6	of	of	ADP
ajst-18565	144	7	ablation	ablation	NOUN
ajst-18565	144	8	experiments	experiment	NOUN
ajst-18565	144	9	numble	numble	ADJ
ajst-18565	144	10	senetv2	senetv2	PROPN
ajst-18565	144	11	gsconv	gsconv	NOUN
ajst-18565	144	12	wise	wise	ADJ
ajst-18565	144	13	-	-	PUNCT
ajst-18565	144	14	iou	iou	NOUN
ajst-18565	144	15	map50	map50	PROPN
ajst-18565	144	16	map50	map50	PROPN
ajst-18565	144	17	-	-	PUNCT
ajst-18565	144	18	95	95	NUM
ajst-18565	144	19	params	param	NOUN
ajst-18565	144	20	/	/	SYM
ajst-18565	144	21	m	m	NOUN
ajst-18565	144	22	gflops	gflop	NOUN
ajst-18565	144	23	1	1	NUM
ajst-18565	144	24	56.4	56.4	NUM
ajst-18565	144	25	27.9	27.9	NUM
ajst-18565	144	26	3.0	3.0	NUM
ajst-18565	144	27	8.1	8.1	NUM
ajst-18565	144	28	2	2	NUM
ajst-18565	144	29	√	√	ADP
ajst-18565	144	30	57.5	57.5	NUM
ajst-18565	144	31	28.4	28.4	NUM
ajst-18565	144	32	3.0	3.0	NUM
ajst-18565	144	33	8.1	8.1	NUM
ajst-18565	144	34	3	3	NUM
ajst-18565	144	35	√	√	ADP
ajst-18565	144	36	57.1	57.1	NUM
ajst-18565	144	37	28.2	28.2	NUM
ajst-18565	144	38	2.9	2.9	NUM
ajst-18565	144	39	8.0	8.0	NUM
ajst-18565	144	40	4	4	NUM
ajst-18565	144	41	√	√	PROPN
ajst-18565	144	42	56.9	56.9	NUM
ajst-18565	144	43	28.1	28.1	NUM
ajst-18565	144	44	3.0	3.0	NUM
ajst-18565	144	45	8.1	8.1	NUM
ajst-18565	144	46	5	5	NUM
ajst-18565	144	47	√	√	NUM
ajst-18565	144	48	√	√	ADP
ajst-18565	144	49	58.1	58.1	NUM
ajst-18565	144	50	28.6	28.6	NUM
ajst-18565	144	51	2.9	2.9	NUM
ajst-18565	144	52	8.0	8.0	NUM
ajst-18565	144	53	6	6	NUM
ajst-18565	144	54	√	√	NUM
ajst-18565	144	55	√	√	ADP
ajst-18565	144	56	57.2	57.2	NUM
ajst-18565	144	57	28.5	28.5	NUM
ajst-18565	144	58	3.0	3.0	NUM
ajst-18565	144	59	8.1	8.1	NUM
ajst-18565	144	60	7	7	NUM
ajst-18565	144	61	√	√	NUM
ajst-18565	144	62	√	√	ADP
ajst-18565	145	1	√	√	NUM
ajst-18565	145	2	58.5	58.5	NUM
ajst-18565	145	3	28.9	28.9	NUM
ajst-18565	145	4	2.9	2.9	NUM
ajst-18565	145	5	8.0	8.0	NUM
ajst-18565	145	6	167	167	NUM
ajst-18565	145	7	3.4.3	3.4.3	NUM
ajst-18565	145	8	.	.	PUNCT
ajst-18565	146	1	visualization	visualization	NOUN
ajst-18565	146	2	of	of	ADP
ajst-18565	146	3	experimental	experimental	ADJ
ajst-18565	146	4	results	result	NOUN
ajst-18565	146	5	the	the	DET
ajst-18565	146	6	comparison	comparison	NOUN
ajst-18565	146	7	between	between	ADP
ajst-18565	146	8	the	the	DET
ajst-18565	146	9	improved	improved	ADJ
ajst-18565	146	10	model	model	NOUN
ajst-18565	146	11	in	in	ADP
ajst-18565	146	12	this	this	DET
ajst-18565	146	13	paper	paper	NOUN
ajst-18565	146	14	and	and	CCONJ
ajst-18565	146	15	the	the	DET
ajst-18565	146	16	yolov8n	yolov8n	PROPN
ajst-18565	146	17	model	model	NOUN
ajst-18565	146	18	training	training	NOUN
ajst-18565	146	19	process	process	NOUN
ajst-18565	146	20	map50	map50	PROPN
ajst-18565	146	21	is	be	AUX
ajst-18565	146	22	shown	show	VERB
ajst-18565	146	23	in	in	ADP
ajst-18565	146	24	the	the	DET
ajst-18565	146	25	fig	fig	NOUN
ajst-18565	146	26	.	.	PUNCT
ajst-18565	147	1	7	7	X
ajst-18565	147	2	.	.	X
ajst-18565	147	3	figure	figure	NOUN
ajst-18565	147	4	7	7	NUM
ajst-18565	147	5	.	.	PUNCT
ajst-18565	147	6	training	training	NOUN
ajst-18565	147	7	process	process	NOUN
ajst-18565	147	8	map50	map50	PROPN
ajst-18565	147	9	comparison	comparison	NOUN
ajst-18565	147	10	as	as	SCONJ
ajst-18565	147	11	can	can	AUX
ajst-18565	147	12	be	be	AUX
ajst-18565	147	13	seen	see	VERB
ajst-18565	147	14	from	from	ADP
ajst-18565	147	15	the	the	DET
ajst-18565	147	16	figure	figure	NOUN
ajst-18565	147	17	,	,	PUNCT
ajst-18565	147	18	map50	map50	PROPN
ajst-18565	147	19	of	of	ADP
ajst-18565	147	20	the	the	DET
ajst-18565	147	21	two	two	NUM
ajst-18565	147	22	algorithms	algorithm	NOUN
ajst-18565	147	23	grows	grow	VERB
ajst-18565	147	24	faster	fast	ADV
ajst-18565	147	25	in	in	ADP
ajst-18565	147	26	the	the	DET
ajst-18565	147	27	first	first	ADJ
ajst-18565	147	28	100	100	NUM
ajst-18565	147	29	rounds	round	NOUN
ajst-18565	147	30	;	;	PUNCT
ajst-18565	147	31	between	between	ADP
ajst-18565	147	32	100200	100200	NUM
ajst-18565	147	33	rounds	round	NOUN
ajst-18565	147	34	,	,	PUNCT
ajst-18565	147	35	the	the	DET
ajst-18565	147	36	map50	map50	PROPN
ajst-18565	147	37	's	's	PART
ajst-18565	147	38	growth	growth	NOUN
ajst-18565	147	39	rate	rate	NOUN
ajst-18565	147	40	gradually	gradually	ADV
ajst-18565	147	41	slows	slow	VERB
ajst-18565	147	42	down	down	ADP
ajst-18565	147	43	,	,	PUNCT
ajst-18565	147	44	and	and	CCONJ
ajst-18565	147	45	between	between	ADP
ajst-18565	147	46	200	200	NUM
ajst-18565	147	47	-	-	SYM
ajst-18565	147	48	300	300	NUM
ajst-18565	147	49	rounds	round	NOUN
ajst-18565	147	50	,	,	PUNCT
ajst-18565	147	51	it	it	PRON
ajst-18565	147	52	begins	begin	VERB
ajst-18565	147	53	to	to	PART
ajst-18565	147	54	level	level	VERB
ajst-18565	147	55	off	off	ADP
ajst-18565	147	56	.	.	PUNCT
ajst-18565	148	1	it	it	PRON
ajst-18565	148	2	can	can	AUX
ajst-18565	148	3	also	also	ADV
ajst-18565	148	4	be	be	AUX
ajst-18565	148	5	seen	see	VERB
ajst-18565	148	6	from	from	ADP
ajst-18565	148	7	the	the	DET
ajst-18565	148	8	figure	figure	NOUN
ajst-18565	148	9	that	that	SCONJ
ajst-18565	148	10	the	the	DET
ajst-18565	148	11	map50	map50	PROPN
ajst-18565	148	12	curve	curve	NOUN
ajst-18565	148	13	of	of	ADP
ajst-18565	148	14	the	the	DET
ajst-18565	148	15	improved	improved	ADJ
ajst-18565	148	16	model	model	NOUN
ajst-18565	148	17	in	in	ADP
ajst-18565	148	18	this	this	DET
ajst-18565	148	19	paper	paper	NOUN
ajst-18565	148	20	is	be	AUX
ajst-18565	148	21	basically	basically	ADV
ajst-18565	148	22	above	above	ADP
ajst-18565	148	23	yolov8n	yolov8n	NOUN
ajst-18565	148	24	,	,	PUNCT
ajst-18565	148	25	and	and	CCONJ
ajst-18565	148	26	the	the	DET
ajst-18565	148	27	fluctuation	fluctuation	NOUN
ajst-18565	148	28	is	be	AUX
ajst-18565	148	29	relatively	relatively	ADV
ajst-18565	148	30	gentle	gentle	ADJ
ajst-18565	148	31	,	,	PUNCT
ajst-18565	148	32	indicating	indicate	VERB
ajst-18565	148	33	that	that	SCONJ
ajst-18565	148	34	the	the	DET
ajst-18565	148	35	proposed	propose	VERB
ajst-18565	148	36	algorithm	algorithm	NOUN
ajst-18565	148	37	is	be	AUX
ajst-18565	148	38	superior	superior	ADJ
ajst-18565	148	39	to	to	ADP
ajst-18565	148	40	yolov8n	yolov8n	PROPN
ajst-18565	148	41	in	in	ADP
ajst-18565	148	42	road	road	NOUN
ajst-18565	148	43	damage	damage	NOUN
ajst-18565	148	44	detection	detection	NOUN
ajst-18565	148	45	accuracy	accuracy	NOUN
ajst-18565	148	46	and	and	CCONJ
ajst-18565	148	47	feature	feature	NOUN
ajst-18565	148	48	learning	learn	VERB
ajst-18565	148	49	effect	effect	NOUN
ajst-18565	148	50	.	.	PUNCT
ajst-18565	149	1	in	in	ADP
ajst-18565	149	2	order	order	NOUN
ajst-18565	149	3	to	to	PART
ajst-18565	149	4	more	more	ADV
ajst-18565	149	5	intuitively	intuitively	ADV
ajst-18565	149	6	show	show	VERB
ajst-18565	149	7	the	the	DET
ajst-18565	149	8	effect	effect	NOUN
ajst-18565	149	9	of	of	ADP
ajst-18565	149	10	the	the	DET
ajst-18565	149	11	improved	improved	ADJ
ajst-18565	149	12	model	model	NOUN
ajst-18565	149	13	,	,	PUNCT
ajst-18565	149	14	figure	figure	NOUN
ajst-18565	149	15	8	8	NUM
ajst-18565	149	16	is	be	AUX
ajst-18565	149	17	a	a	DET
ajst-18565	149	18	comparison	comparison	NOUN
ajst-18565	149	19	diagram	diagram	NOUN
ajst-18565	149	20	of	of	ADP
ajst-18565	149	21	the	the	DET
ajst-18565	149	22	two	two	NUM
ajst-18565	149	23	model	model	NOUN
ajst-18565	149	24	detection.it	detection.it	PRON
ajst-18565	149	25	can	can	AUX
ajst-18565	149	26	be	be	AUX
ajst-18565	149	27	seen	see	VERB
ajst-18565	149	28	that	that	SCONJ
ajst-18565	149	29	the	the	DET
ajst-18565	149	30	accuracy	accuracy	NOUN
ajst-18565	149	31	of	of	ADP
ajst-18565	149	32	the	the	DET
ajst-18565	149	33	improved	improved	ADJ
ajst-18565	149	34	model	model	NOUN
ajst-18565	149	35	detection	detection	NOUN
ajst-18565	149	36	has	have	AUX
ajst-18565	149	37	been	be	AUX
ajst-18565	149	38	significantly	significantly	ADV
ajst-18565	149	39	improved	improve	VERB
ajst-18565	149	40	figure	figure	NOUN
ajst-18565	149	41	8	8	NUM
ajst-18565	149	42	.	.	PUNCT
ajst-18565	149	43	comparison	comparison	NOUN
ajst-18565	149	44	figure	figure	NOUN
ajst-18565	149	45	of	of	ADP
ajst-18565	149	46	the	the	DET
ajst-18565	149	47	two	two	NUM
ajst-18565	149	48	model	model	NOUN
ajst-18565	149	49	detection	detection	NOUN
ajst-18565	149	50	4	4	NUM
ajst-18565	149	51	.	.	PUNCT
ajst-18565	150	1	conclusions	conclusion	NOUN
ajst-18565	150	2	in	in	ADP
ajst-18565	150	3	this	this	DET
ajst-18565	150	4	paper	paper	NOUN
ajst-18565	150	5	,	,	PUNCT
ajst-18565	150	6	an	an	DET
ajst-18565	150	7	improved	improved	ADJ
ajst-18565	150	8	yolov8n	yolov8n	NOUN
ajst-18565	150	9	network	network	NOUN
ajst-18565	150	10	model	model	NOUN
ajst-18565	150	11	is	be	AUX
ajst-18565	150	12	proposed	propose	VERB
ajst-18565	150	13	to	to	PART
ajst-18565	150	14	solve	solve	VERB
ajst-18565	150	15	the	the	DET
ajst-18565	150	16	problem	problem	NOUN
ajst-18565	150	17	of	of	ADP
ajst-18565	150	18	low	low	ADJ
ajst-18565	150	19	accuracy	accuracy	NOUN
ajst-18565	150	20	in	in	ADP
ajst-18565	150	21	road	road	NOUN
ajst-18565	150	22	damage	damage	NOUN
ajst-18565	150	23	detection	detection	NOUN
ajst-18565	150	24	.	.	PUNCT
ajst-18565	151	1	the	the	DET
ajst-18565	151	2	network	network	NOUN
ajst-18565	151	3	is	be	AUX
ajst-18565	151	4	optimized	optimize	VERB
ajst-18565	151	5	by	by	ADP
ajst-18565	151	6	introducing	introduce	VERB
ajst-18565	151	7	senetv2	senetv2	NOUN
ajst-18565	151	8	attention	attention	NOUN
ajst-18565	151	9	mechanism	mechanism	NOUN
ajst-18565	151	10	,	,	PUNCT
ajst-18565	151	11	replacing	replace	VERB
ajst-18565	151	12	a	a	DET
ajst-18565	151	13	part	part	NOUN
ajst-18565	151	14	of	of	ADP
ajst-18565	151	15	the	the	DET
ajst-18565	151	16	conv	conv	NOUN
ajst-18565	151	17	in	in	ADP
ajst-18565	151	18	the	the	DET
ajst-18565	151	19	neck	neck	NOUN
ajst-18565	151	20	part	part	NOUN
ajst-18565	151	21	of	of	ADP
ajst-18565	151	22	the	the	DET
ajst-18565	151	23	model	model	NOUN
ajst-18565	151	24	with	with	ADP
ajst-18565	151	25	gsconv	gsconv	NOUN
ajst-18565	151	26	,	,	PUNCT
ajst-18565	151	27	and	and	CCONJ
ajst-18565	151	28	using	use	VERB
ajst-18565	151	29	wiseiou	wiseiou	NOUN
ajst-18565	151	30	loss	loss	NOUN
ajst-18565	151	31	function	function	NOUN
ajst-18565	151	32	instead	instead	ADV
ajst-18565	151	33	of	of	ADP
ajst-18565	151	34	the	the	DET
ajst-18565	151	35	original	original	ADJ
ajst-18565	151	36	ciou	ciou	NOUN
ajst-18565	151	37	loss	loss	NOUN
ajst-18565	151	38	function	function	NOUN
ajst-18565	151	39	.	.	PUNCT
ajst-18565	152	1	the	the	DET
ajst-18565	152	2	experimental	experimental	ADJ
ajst-18565	152	3	results	result	NOUN
ajst-18565	152	4	show	show	VERB
ajst-18565	152	5	that	that	SCONJ
ajst-18565	152	6	on	on	ADP
ajst-18565	152	7	the	the	DET
ajst-18565	152	8	rdd2022	rdd2022	NOUN
ajst-18565	152	9	data	datum	NOUN
ajst-18565	152	10	set	set	PROPN
ajst-18565	152	11	,	,	PUNCT
ajst-18565	152	12	the	the	DET
ajst-18565	152	13	map50	map50	NOUN
ajst-18565	152	14	of	of	ADP
ajst-18565	152	15	the	the	DET
ajst-18565	152	16	improved	improved	ADJ
ajst-18565	152	17	algorithm	algorithm	NOUN
ajst-18565	152	18	in	in	ADP
ajst-18565	152	19	this	this	DET
ajst-18565	152	20	paper	paper	NOUN
ajst-18565	152	21	reaches	reach	VERB
ajst-18565	152	22	58.5	58.5	NUM
ajst-18565	152	23	%	%	NOUN
ajst-18565	152	24	,	,	PUNCT
ajst-18565	152	25	which	which	PRON
ajst-18565	152	26	is	be	AUX
ajst-18565	152	27	2.1	2.1	NUM
ajst-18565	152	28	%	%	NOUN
ajst-18565	152	29	higher	high	ADJ
ajst-18565	152	30	than	than	ADP
ajst-18565	152	31	the	the	DET
ajst-18565	152	32	original	original	ADJ
ajst-18565	152	33	yolov8n	yolov8n	NOUN
ajst-18565	152	34	model	model	NOUN
ajst-18565	152	35	.	.	PUNCT
ajst-18565	153	1	the	the	DET
ajst-18565	153	2	performance	performance	NOUN
ajst-18565	153	3	is	be	AUX
ajst-18565	153	4	better	well	ADJ
ajst-18565	153	5	than	than	ADP
ajst-18565	153	6	the	the	DET
ajst-18565	153	7	original	original	ADJ
ajst-18565	153	8	yolov8n	yolov8n	NOUN
ajst-18565	153	9	model	model	NOUN
ajst-18565	153	10	,	,	PUNCT
ajst-18565	153	11	which	which	PRON
ajst-18565	153	12	can	can	AUX
ajst-18565	153	13	effectively	effectively	ADV
ajst-18565	153	14	extract	extract	VERB
ajst-18565	153	15	feature	feature	NOUN
ajst-18565	153	16	information	information	NOUN
ajst-18565	153	17	and	and	CCONJ
ajst-18565	153	18	meet	meet	VERB
ajst-18565	153	19	the	the	DET
ajst-18565	153	20	requirements	requirement	NOUN
ajst-18565	153	21	for	for	ADP
ajst-18565	153	22	accurate	accurate	ADJ
ajst-18565	153	23	detection	detection	NOUN
ajst-18565	153	24	of	of	ADP
ajst-18565	153	25	road	road	NOUN
ajst-18565	153	26	damage	damage	NOUN
ajst-18565	153	27	targets	target	NOUN
ajst-18565	153	28	.	.	PUNCT
ajst-18565	154	1	references	reference	NOUN
ajst-18565	154	2	[	[	X
ajst-18565	154	3	1	1	NUM
ajst-18565	154	4	]	]	X
ajst-18565	154	5	zhang	zhang	PROPN
ajst-18565	154	6	,	,	PUNCT
ajst-18565	154	7	l.	l.	PROPN
ajst-18565	154	8	,	,	PUNCT
ajst-18565	154	9	yang	yang	PROPN
ajst-18565	154	10	,	,	PUNCT
ajst-18565	154	11	f.	f.	PROPN
ajst-18565	154	12	,	,	PUNCT
ajst-18565	154	13	zhang	zhang	PROPN
ajst-18565	154	14	,	,	PUNCT
ajst-18565	154	15	y.	y.	PROPN
ajst-18565	154	16	d.	d.	PROPN
ajst-18565	154	17	,	,	PUNCT
ajst-18565	154	18	et	et	PROPN
ajst-18565	154	19	al	al	PROPN
ajst-18565	154	20	.	.	PUNCT
ajst-18565	155	1	(	(	PUNCT
ajst-18565	155	2	2016	2016	NUM
ajst-18565	155	3	)	)	PUNCT
ajst-18565	155	4	.	.	PUNCT
ajst-18565	156	1	road	road	NOUN
ajst-18565	156	2	crack	crack	NOUN
ajst-18565	156	3	detection	detection	NOUN
ajst-18565	156	4	using	use	VERB
ajst-18565	156	5	deep	deep	ADJ
ajst-18565	156	6	convolutional	convolutional	ADJ
ajst-18565	156	7	neural	neural	ADJ
ajst-18565	156	8	network	network	NOUN
ajst-18565	156	9	.	.	PUNCT
ajst-18565	157	1	in	in	ADP
ajst-18565	157	2	2016	2016	NUM
ajst-18565	157	3	ieee	ieee	NOUN
ajst-18565	157	4	international	international	ADJ
ajst-18565	157	5	conference	conference	NOUN
ajst-18565	157	6	on	on	ADP
ajst-18565	157	7	image	image	NOUN
ajst-18565	157	8	processing	processing	NOUN
ajst-18565	157	9	(	(	PUNCT
ajst-18565	157	10	icip	icip	PROPN
ajst-18565	157	11	)	)	PUNCT
ajst-18565	157	12	(	(	PUNCT
ajst-18565	157	13	pp	pp	ADP
ajst-18565	157	14	.	.	PUNCT
ajst-18565	158	1	3708	3708	NUM
ajst-18565	158	2	-	-	PUNCT
ajst-18565	158	3	3712	3712	NUM
ajst-18565	158	4	)	)	PUNCT
ajst-18565	158	5	.	.	PUNCT
ajst-18565	159	1	ieee	ieee	NOUN
ajst-18565	159	2	.	.	PUNCT
ajst-18565	160	1	[	[	X
ajst-18565	160	2	2	2	NUM
ajst-18565	160	3	]	]	X
ajst-18565	160	4	wang	wang	PROPN
ajst-18565	160	5	,	,	PUNCT
ajst-18565	160	6	q.	q.	PROPN
ajst-18565	160	7	,	,	PUNCT
ajst-18565	160	8	mao	mao	PROPN
ajst-18565	160	9	,	,	PUNCT
ajst-18565	160	10	j.	j.	PROPN
ajst-18565	160	11	,	,	PUNCT
ajst-18565	160	12	zhai	zhai	PROPN
ajst-18565	160	13	,	,	PUNCT
ajst-18565	160	14	x.	x.	PROPN
ajst-18565	160	15	,	,	PUNCT
ajst-18565	160	16	et	et	PROPN
ajst-18565	160	17	al	al	PROPN
ajst-18565	160	18	.	.	PROPN
ajst-18565	160	19	(	(	PUNCT
ajst-18565	160	20	2021	2021	NUM
ajst-18565	160	21	)	)	PUNCT
ajst-18565	160	22	.	.	PUNCT
ajst-18565	161	1	improvements	improvement	NOUN
ajst-18565	161	2	of	of	ADP
ajst-18565	161	3	yolov3	yolov3	PROPN
ajst-18565	161	4	for	for	ADP
ajst-18565	161	5	road	road	NOUN
ajst-18565	161	6	damage	damage	NOUN
ajst-18565	161	7	detection	detection	NOUN
ajst-18565	161	8	.	.	PUNCT
ajst-18565	162	1	in	in	ADP
ajst-18565	162	2	journal	journal	PROPN
ajst-18565	162	3	of	of	ADP
ajst-18565	162	4	physics	physics	PROPN
ajst-18565	162	5	:	:	PUNCT
ajst-18565	162	6	conference	conference	NOUN
ajst-18565	162	7	series	series	NOUN
ajst-18565	162	8	(	(	PUNCT
ajst-18565	162	9	vol	vol	NOUN
ajst-18565	162	10	.	.	PUNCT
ajst-18565	162	11	1903	1903	NUM
ajst-18565	162	12	,	,	PUNCT
ajst-18565	162	13	no	no	INTJ
ajst-18565	162	14	.	.	NOUN
ajst-18565	162	15	1	1	NUM
ajst-18565	162	16	,	,	PUNCT
ajst-18565	162	17	p.	p.	NOUN
ajst-18565	162	18	012008	012008	NUM
ajst-18565	162	19	)	)	PUNCT
ajst-18565	162	20	.	.	PUNCT
ajst-18565	163	1	iop	iop	NOUN
ajst-18565	163	2	publishing	publishing	NOUN
ajst-18565	163	3	.	.	PUNCT
ajst-18565	164	1	[	[	X
ajst-18565	164	2	3	3	X
ajst-18565	164	3	]	]	X
ajst-18565	164	4	wan	wan	PROPN
ajst-18565	164	5	,	,	PUNCT
ajst-18565	164	6	f.	f.	PROPN
ajst-18565	164	7	,	,	PUNCT
ajst-18565	164	8	sun	sun	PROPN
ajst-18565	164	9	,	,	PUNCT
ajst-18565	164	10	c.	c.	PROPN
ajst-18565	164	11	,	,	PUNCT
ajst-18565	164	12	he	he	PRON
ajst-18565	164	13	,	,	PUNCT
ajst-18565	164	14	h.	h.	PROPN
ajst-18565	164	15	,	,	PUNCT
ajst-18565	164	16	et	et	PROPN
ajst-18565	164	17	al	al	PROPN
ajst-18565	164	18	.	.	PROPN
ajst-18565	164	19	(	(	PUNCT
ajst-18565	164	20	2022	2022	NUM
ajst-18565	164	21	)	)	PUNCT
ajst-18565	164	22	.	.	PUNCT
ajst-18565	165	1	yolo	yolo	PROPN
ajst-18565	165	2	-	-	PUNCT
ajst-18565	165	3	lrdd	lrdd	PROPN
ajst-18565	165	4	:	:	PUNCT
ajst-18565	165	5	a	a	DET
ajst-18565	165	6	lightweight	lightweight	ADJ
ajst-18565	165	7	method	method	NOUN
ajst-18565	165	8	for	for	ADP
ajst-18565	165	9	road	road	NOUN
ajst-18565	165	10	damage	damage	NOUN
ajst-18565	165	11	detection	detection	NOUN
ajst-18565	165	12	based	base	VERB
ajst-18565	165	13	on	on	ADP
ajst-18565	165	14	improved	improve	VERB
ajst-18565	165	15	yolov5s	yolov5s	PROPN
ajst-18565	165	16	.	.	PUNCT
ajst-18565	166	1	eurasip	eurasip	PROPN
ajst-18565	166	2	journal	journal	PROPN
ajst-18565	166	3	on	on	ADP
ajst-18565	166	4	advances	advance	NOUN
ajst-18565	166	5	in	in	ADP
ajst-18565	166	6	signal	signal	ADJ
ajst-18565	166	7	processing	processing	NOUN
ajst-18565	166	8	,	,	PUNCT
ajst-18565	166	9	2022(1	2022(1	NUM
ajst-18565	166	10	)	)	PUNCT
ajst-18565	166	11	,	,	PUNCT
ajst-18565	166	12	98	98	NUM
ajst-18565	166	13	.	.	PUNCT
ajst-18565	167	1	[	[	X
ajst-18565	167	2	4	4	NUM
ajst-18565	167	3	]	]	X
ajst-18565	167	4	cha	cha	X
ajst-18565	167	5	,	,	PUNCT
ajst-18565	167	6	y.	y.	PROPN
ajst-18565	167	7	j.	j.	PROPN
ajst-18565	167	8	,	,	PUNCT
ajst-18565	167	9	choi	choi	PROPN
ajst-18565	167	10	,	,	PUNCT
ajst-18565	167	11	w.	w.	PROPN
ajst-18565	167	12	,	,	PUNCT
ajst-18565	167	13	&	&	CCONJ
ajst-18565	167	14	büyüköztürk	büyüköztürk	PROPN
ajst-18565	167	15	,	,	PUNCT
ajst-18565	167	16	o.	o.	PROPN
ajst-18565	167	17	(	(	PUNCT
ajst-18565	167	18	2017	2017	NUM
ajst-18565	167	19	)	)	PUNCT
ajst-18565	167	20	.	.	PUNCT
ajst-18565	168	1	deep	deep	ADJ
ajst-18565	168	2	learning	learning	NOUN
ajst-18565	168	3	-	-	PUNCT
ajst-18565	168	4	based	base	VERB
ajst-18565	168	5	crack	crack	NOUN
ajst-18565	168	6	damage	damage	NOUN
ajst-18565	168	7	detection	detection	NOUN
ajst-18565	168	8	using	use	VERB
ajst-18565	168	9	convolutional	convolutional	ADJ
ajst-18565	168	10	neural	neural	ADJ
ajst-18565	168	11	networks	network	NOUN
ajst-18565	168	12	.	.	PUNCT
ajst-18565	169	1	computer	computer	NOUN
ajst-18565	169	2	-	-	PUNCT
ajst-18565	169	3	aided	aid	VERB
ajst-18565	169	4	civil	civil	ADJ
ajst-18565	169	5	and	and	CCONJ
ajst-18565	169	6	infrastructure	infrastructure	NOUN
ajst-18565	169	7	engineering	engineering	NOUN
ajst-18565	169	8	,	,	PUNCT
ajst-18565	169	9	32(5	32(5	NOUN
ajst-18565	169	10	)	)	PUNCT
ajst-18565	169	11	,	,	PUNCT
ajst-18565	169	12	361	361	NUM
ajst-18565	169	13	-	-	SYM
ajst-18565	169	14	378	378	NUM
ajst-18565	169	15	.	.	PUNCT
ajst-18565	170	1	[	[	X
ajst-18565	170	2	5	5	NUM
ajst-18565	170	3	]	]	SYM
ajst-18565	170	4	nie	nie	PROPN
ajst-18565	170	5	,	,	PUNCT
ajst-18565	170	6	m.	m.	NOUN
ajst-18565	170	7	,	,	PUNCT
ajst-18565	170	8	&	&	CCONJ
ajst-18565	170	9	wang	wang	PROPN
ajst-18565	170	10	,	,	PUNCT
ajst-18565	170	11	k.	k.	PROPN
ajst-18565	170	12	(	(	PUNCT
ajst-18565	170	13	2018	2018	NUM
ajst-18565	170	14	)	)	PUNCT
ajst-18565	170	15	.	.	PUNCT
ajst-18565	171	1	pavement	pavement	NOUN
ajst-18565	171	2	distress	distress	NOUN
ajst-18565	171	3	detection	detection	NOUN
ajst-18565	171	4	based	base	VERB
ajst-18565	171	5	on	on	ADP
ajst-18565	171	6	transfer	transfer	NOUN
ajst-18565	171	7	learning	learning	NOUN
ajst-18565	171	8	.	.	PUNCT
ajst-18565	172	1	in	in	ADP
ajst-18565	172	2	2018	2018	NUM
ajst-18565	172	3	5th	5th	ADJ
ajst-18565	172	4	international	international	ADJ
ajst-18565	172	5	conference	conference	NOUN
ajst-18565	172	6	on	on	ADP
ajst-18565	172	7	systems	system	NOUN
ajst-18565	172	8	and	and	CCONJ
ajst-18565	172	9	informatics	informatic	NOUN
ajst-18565	172	10	(	(	PUNCT
ajst-18565	172	11	icsai	icsai	PROPN
ajst-18565	172	12	)	)	PUNCT
ajst-18565	172	13	(	(	PUNCT
ajst-18565	172	14	pp	pp	ADV
ajst-18565	172	15	.	.	PUNCT
ajst-18565	173	1	435	435	NUM
ajst-18565	173	2	-	-	SYM
ajst-18565	173	3	439	439	NUM
ajst-18565	173	4	)	)	PUNCT
ajst-18565	173	5	.	.	PUNCT
ajst-18565	174	1	ieee	ieee	NOUN
ajst-18565	174	2	.	.	PUNCT
ajst-18565	175	1	[	[	X
ajst-18565	175	2	6	6	NUM
ajst-18565	175	3	]	]	SYM
ajst-18565	175	4	yang	yang	PROPN
ajst-18565	175	5	,	,	PUNCT
ajst-18565	175	6	d.	d.	PROPN
ajst-18565	175	7	m.	m.	PROPN
ajst-18565	175	8	,	,	PUNCT
ajst-18565	175	9	zhang	zhang	PROPN
ajst-18565	175	10	,	,	PUNCT
ajst-18565	175	11	j.	j.	PROPN
ajst-18565	175	12	g.	g.	PROPN
ajst-18565	175	13	,	,	PUNCT
ajst-18565	175	14	xu	xu	PROPN
ajst-18565	175	15	,	,	PUNCT
ajst-18565	175	16	s.	s.	PROPN
ajst-18565	175	17	b.	b.	PROPN
ajst-18565	175	18	,	,	PUNCT
ajst-18565	175	19	et	et	PROPN
ajst-18565	175	20	al	al	PROPN
ajst-18565	175	21	.	.	PUNCT
ajst-18565	176	1	(	(	PUNCT
ajst-18565	176	2	2018	2018	NUM
ajst-18565	176	3	)	)	PUNCT
ajst-18565	176	4	.	.	PUNCT
ajst-18565	177	1	real	real	ADJ
ajst-18565	177	2	-	-	PUNCT
ajst-18565	177	3	time	time	NOUN
ajst-18565	177	4	pedestrian	pedestrian	NOUN
ajst-18565	177	5	detection	detection	NOUN
ajst-18565	177	6	via	via	ADP
ajst-18565	177	7	hierarchical	hierarchical	ADJ
ajst-18565	177	8	convolutional	convolutional	ADJ
ajst-18565	177	9	feature	feature	NOUN
ajst-18565	177	10	.	.	PUNCT
ajst-18565	178	1	multimedia	multimedia	NOUN
ajst-18565	178	2	tools	tool	NOUN
ajst-18565	178	3	and	and	CCONJ
ajst-18565	178	4	applications	application	NOUN
ajst-18565	178	5	,	,	PUNCT
ajst-18565	178	6	77(19	77(19	NUM
ajst-18565	178	7	)	)	PUNCT
ajst-18565	178	8	,	,	PUNCT
ajst-18565	178	9	25841	25841	NUM
ajst-18565	178	10	-	-	SYM
ajst-18565	178	11	25860	25860	NUM
ajst-18565	178	12	.	.	PUNCT
ajst-18565	179	1	[	[	X
ajst-18565	179	2	7	7	X
ajst-18565	179	3	]	]	X
ajst-18565	179	4	sun	sun	NOUN
ajst-18565	179	5	,	,	PUNCT
ajst-18565	179	6	z.	z.	PROPN
ajst-18565	179	7	,	,	PUNCT
ajst-18565	179	8	pei	pei	PROPN
ajst-18565	179	9	,	,	PUNCT
ajst-18565	179	10	l.	l.	PROPN
ajst-18565	179	11	,	,	PUNCT
ajst-18565	179	12	li	li	PROPN
ajst-18565	179	13	,	,	PUNCT
ajst-18565	179	14	w.	w.	PROPN
ajst-18565	179	15	,	,	PUNCT
ajst-18565	179	16	et	et	PROPN
ajst-18565	179	17	al	al	PROPN
ajst-18565	179	18	.	.	PROPN
ajst-18565	179	19	(	(	PUNCT
ajst-18565	179	20	2020	2020	NUM
ajst-18565	179	21	)	)	PUNCT
ajst-18565	179	22	.	.	PUNCT
ajst-18565	180	1	pavement	pavement	NOUN
ajst-18565	180	2	sealed	seal	VERB
ajst-18565	180	3	crack	crack	NOUN
ajst-18565	180	4	detection	detection	NOUN
ajst-18565	180	5	method	method	NOUN
ajst-18565	180	6	based	base	VERB
ajst-18565	180	7	on	on	ADP
ajst-18565	180	8	improved	improved	ADJ
ajst-18565	180	9	faster	fast	ADV
ajst-18565	180	10	r	r	NOUN
ajst-18565	180	11	-	-	PUNCT
ajst-18565	180	12	cnn	cnn	PROPN
ajst-18565	180	13	.	.	PUNCT
ajst-18565	181	1	journal	journal	PROPN
ajst-18565	181	2	of	of	ADP
ajst-18565	181	3	south	south	PROPN
ajst-18565	181	4	china	china	PROPN
ajst-18565	181	5	university	university	PROPN
ajst-18565	181	6	of	of	ADP
ajst-18565	181	7	technology	technology	NOUN
ajst-18565	181	8	(	(	PUNCT
ajst-18565	181	9	natural	natural	ADJ
ajst-18565	181	10	science	science	NOUN
ajst-18565	181	11	edition	edition	NOUN
ajst-18565	181	12	)	)	PUNCT
ajst-18565	181	13	,	,	PUNCT
ajst-18565	181	14	48(02	48(02	NOUN
ajst-18565	181	15	)	)	PUNCT
ajst-18565	181	16	,	,	PUNCT
ajst-18565	181	17	84	84	NUM
ajst-18565	181	18	-	-	SYM
ajst-18565	181	19	93	93	NUM
ajst-18565	181	20	.	.	PUNCT
ajst-18565	182	1	[	[	X
ajst-18565	182	2	8	8	NUM
ajst-18565	182	3	]	]	SYM
ajst-18565	182	4	gu	gu	NOUN
ajst-18565	182	5	,	,	PUNCT
ajst-18565	182	6	s.	s.	PROPN
ajst-18565	182	7	,	,	PUNCT
ajst-18565	182	8	li	li	PROPN
ajst-18565	182	9	,	,	PUNCT
ajst-18565	182	10	x.	x.	PROPN
ajst-18565	182	11	,	,	PUNCT
ajst-18565	182	12	wang	wang	PROPN
ajst-18565	182	13	,	,	PUNCT
ajst-18565	182	14	x.	x.	PROPN
ajst-18565	182	15	,	,	PUNCT
ajst-18565	182	16	et	et	PROPN
ajst-18565	182	17	al	al	PROPN
ajst-18565	182	18	.	.	PROPN
ajst-18565	183	1	(	(	PUNCT
ajst-18565	183	2	2021	2021	NUM
ajst-18565	183	3	)	)	PUNCT
ajst-18565	183	4	.	.	PUNCT
ajst-18565	184	1	crack	crack	VERB
ajst-18565	184	2	detection	detection	NOUN
ajst-18565	184	3	based	base	VERB
ajst-18565	184	4	on	on	ADP
ajst-18565	184	5	enhanced	enhanced	ADJ
ajst-18565	184	6	semantic	semantic	ADJ
ajst-18565	184	7	information	information	NOUN
ajst-18565	184	8	and	and	CCONJ
ajst-18565	184	9	multi	multi	ADJ
ajst-18565	184	10	-	-	ADJ
ajst-18565	184	11	channel	channel	ADJ
ajst-18565	184	12	feature	feature	NOUN
ajst-18565	184	13	fusion	fusion	NOUN
ajst-18565	184	14	.	.	PUNCT
ajst-18565	185	1	computer	computer	NOUN
ajst-18565	185	2	engineering	engineering	NOUN
ajst-18565	185	3	and	and	CCONJ
ajst-18565	185	4	applications	application	NOUN
ajst-18565	185	5	,	,	PUNCT
ajst-18565	185	6	57(10	57(10	NUM
ajst-18565	185	7	)	)	PUNCT
ajst-18565	185	8	,	,	PUNCT
ajst-18565	185	9	204210	204210	NUM
ajst-18565	185	10	.	.	PUNCT
ajst-18565	186	1	[	[	X
ajst-18565	186	2	9	9	NUM
ajst-18565	186	3	]	]	X
ajst-18565	186	4	narayanan	narayanan	PROPN
ajst-18565	186	5	,	,	PUNCT
ajst-18565	186	6	m.	m.	NOUN
ajst-18565	186	7	(	(	PUNCT
ajst-18565	186	8	2023	2023	NUM
ajst-18565	186	9	)	)	PUNCT
ajst-18565	186	10	.	.	PUNCT
ajst-18565	187	1	senetv2	senetv2	PROPN
ajst-18565	187	2	:	:	PUNCT
ajst-18565	187	3	aggregated	aggregate	VERB
ajst-18565	187	4	dense	dense	ADJ
ajst-18565	187	5	layer	layer	NOUN
ajst-18565	187	6	for	for	ADP
ajst-18565	187	7	channelwise	channelwise	NOUN
ajst-18565	187	8	and	and	CCONJ
ajst-18565	187	9	global	global	ADJ
ajst-18565	187	10	representations	representation	NOUN
ajst-18565	187	11	.	.	PUNCT
ajst-18565	188	1	arxiv	arxiv	PROPN
ajst-18565	188	2	preprint	preprint	NOUN
ajst-18565	188	3	arxiv:2311.10807	arxiv:2311.10807	VERB
ajst-18565	188	4	.	.	PUNCT
ajst-18565	189	1	[	[	X
ajst-18565	189	2	10	10	NUM
ajst-18565	189	3	]	]	SYM
ajst-18565	189	4	li	li	PROPN
ajst-18565	189	5	,	,	PUNCT
ajst-18565	189	6	h.	h.	PROPN
ajst-18565	189	7	,	,	PUNCT
ajst-18565	189	8	li	li	PROPN
ajst-18565	189	9	,	,	PUNCT
ajst-18565	189	10	j.	j.	PROPN
ajst-18565	189	11	,	,	PUNCT
ajst-18565	189	12	wei	wei	PROPN
ajst-18565	189	13	,	,	PUNCT
ajst-18565	189	14	h.	h.	PROPN
ajst-18565	189	15	,	,	PUNCT
ajst-18565	189	16	et	et	PROPN
ajst-18565	189	17	al	al	PROPN
ajst-18565	189	18	.	.	PROPN
ajst-18565	189	19	(	(	PUNCT
ajst-18565	189	20	2022	2022	NUM
ajst-18565	189	21	)	)	PUNCT
ajst-18565	189	22	.	.	PUNCT
ajst-18565	189	23	slim	slim	ADJ
ajst-18565	189	24	-	-	PUNCT
ajst-18565	189	25	neck	neck	NOUN
ajst-18565	189	26	by	by	ADP
ajst-18565	189	27	gsconv	gsconv	NOUN
ajst-18565	189	28	:	:	PUNCT
ajst-18565	189	29	a	a	DET
ajst-18565	189	30	better	well	ADJ
ajst-18565	189	31	design	design	NOUN
ajst-18565	189	32	paradigm	paradigm	NOUN
ajst-18565	189	33	of	of	ADP
ajst-18565	189	34	detector	detector	NOUN
ajst-18565	189	35	architectures	architecture	NOUN
ajst-18565	189	36	for	for	ADP
ajst-18565	189	37	autonomous	autonomous	ADJ
ajst-18565	189	38	vehicles	vehicle	NOUN
ajst-18565	189	39	.	.	PUNCT
ajst-18565	190	1	arxiv	arxiv	PROPN
ajst-18565	190	2	preprint	preprint	PROPN
ajst-18565	190	3	arxiv:2206.02424	arxiv:2206.02424	NOUN
ajst-18565	190	4	.	.	PUNCT
ajst-18565	191	1	[	[	X
ajst-18565	191	2	11	11	NUM
ajst-18565	191	3	]	]	X
ajst-18565	191	4	tong	tong	PROPN
ajst-18565	191	5	,	,	PUNCT
ajst-18565	191	6	z.	z.	PROPN
ajst-18565	191	7	,	,	PUNCT
ajst-18565	191	8	chen	chen	PROPN
ajst-18565	191	9	,	,	PUNCT
ajst-18565	191	10	y.	y.	PROPN
ajst-18565	191	11	,	,	PUNCT
ajst-18565	191	12	xu	xu	PROPN
ajst-18565	191	13	,	,	PUNCT
ajst-18565	191	14	z.	z.	PROPN
ajst-18565	191	15	,	,	PUNCT
ajst-18565	191	16	et	et	PROPN
ajst-18565	191	17	al	al	PROPN
ajst-18565	191	18	.	.	PROPN
ajst-18565	191	19	(	(	PUNCT
ajst-18565	191	20	2023	2023	NUM
ajst-18565	191	21	)	)	PUNCT
ajst-18565	191	22	.	.	PUNCT
ajst-18565	191	23	wise	wise	ADJ
ajst-18565	191	24	-	-	PUNCT
ajst-18565	191	25	iou	iou	NOUN
ajst-18565	191	26	:	:	PUNCT
ajst-18565	191	27	bounding	bound	VERB
ajst-18565	191	28	box	box	NOUN
ajst-18565	191	29	regression	regression	NOUN
ajst-18565	191	30	loss	loss	NOUN
ajst-18565	191	31	with	with	ADP
ajst-18565	191	32	dynamic	dynamic	ADJ
ajst-18565	191	33	focusing	focus	VERB
ajst-18565	191	34	mechanism	mechanism	NOUN
ajst-18565	191	35	.	.	PUNCT
ajst-18565	192	1	arxiv	arxiv	PROPN
ajst-18565	192	2	preprint	preprint	PROPN
ajst-18565	192	3	arxiv:2301.10051	arxiv:2301.10051	PROPN
ajst-18565	192	4	.	.	PUNCT
ajst-18565	193	1	[	[	X
ajst-18565	193	2	12	12	NUM
ajst-18565	193	3	]	]	PUNCT
ajst-18565	193	4	arya	arya	NOUN
ajst-18565	193	5	,	,	PUNCT
ajst-18565	193	6	d.	d.	PROPN
ajst-18565	193	7	,	,	PUNCT
ajst-18565	193	8	maeda	maeda	PROPN
ajst-18565	193	9	,	,	PUNCT
ajst-18565	193	10	h.	h.	PROPN
ajst-18565	193	11	,	,	PUNCT
ajst-18565	193	12	ghosh	ghosh	PROPN
ajst-18565	193	13	,	,	PUNCT
ajst-18565	193	14	s.	s.	PROPN
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ajst-18565	193	16	,	,	PUNCT
ajst-18565	193	17	et	et	PROPN
ajst-18565	193	18	al	al	PROPN
ajst-18565	193	19	.	.	PROPN
ajst-18565	193	20	(	(	PUNCT
ajst-18565	193	21	2022	2022	NUM
ajst-18565	193	22	)	)	PUNCT
ajst-18565	193	23	.	.	PUNCT
ajst-18565	194	1	crowdsensing	crowdsensing	ADJ
ajst-18565	194	2	-	-	PUNCT
ajst-18565	194	3	based	base	VERB
ajst-18565	194	4	road	road	NOUN
ajst-18565	194	5	damage	damage	NOUN
ajst-18565	194	6	detection	detection	NOUN
ajst-18565	194	7	challenge	challenge	NOUN
ajst-18565	194	8	(	(	PUNCT
ajst-18565	194	9	crddc’2022	crddc’2022	NOUN
ajst-18565	194	10	)	)	PUNCT
ajst-18565	194	11	.	.	PUNCT
ajst-18565	195	1	in	in	ADP
ajst-18565	195	2	2022	2022	NUM
ajst-18565	195	3	ieee	ieee	NOUN
ajst-18565	195	4	international	international	ADJ
ajst-18565	195	5	conference	conference	NOUN
ajst-18565	195	6	on	on	ADP
ajst-18565	195	7	big	big	ADJ
ajst-18565	195	8	data	datum	NOUN
ajst-18565	195	9	(	(	PUNCT
ajst-18565	195	10	big	big	ADJ
ajst-18565	195	11	data	datum	NOUN
ajst-18565	195	12	)	)	PUNCT
ajst-18565	195	13	(	(	PUNCT
ajst-18565	195	14	pp	pp	ADJ
ajst-18565	195	15	.	.	PUNCT
ajst-18565	195	16	6378	6378	NUM
ajst-18565	195	17	-	-	SYM
ajst-18565	195	18	6386	6386	NUM
ajst-18565	195	19	)	)	PUNCT
ajst-18565	195	20	.	.	PUNCT
ajst-18565	196	1	ieee	ieee	PROPN
ajst-18565	196	2	.	.	PUNCT