id	sid	tid	token	lemma	pos
ajst-26756	1	1	academic	academic	ADJ
ajst-26756	1	2	journal	journal	NOUN
ajst-26756	1	3	of	of	ADP
ajst-26756	1	4	science	science	NOUN
ajst-26756	1	5	and	and	CCONJ
ajst-26756	1	6	technology	technology	NOUN
ajst-26756	1	7	issn	issn	NOUN
ajst-26756	1	8	:	:	PUNCT
ajst-26756	1	9	2771	2771	NUM
ajst-26756	1	10	-	-	SYM
ajst-26756	1	11	3032	3032	NUM
ajst-26756	1	12	|	|	NOUN
ajst-26756	1	13	vol	vol	NOUN
ajst-26756	1	14	.	.	PROPN
ajst-26756	1	15	13	13	NUM
ajst-26756	1	16	,	,	PUNCT
ajst-26756	1	17	no	no	INTJ
ajst-26756	1	18	.	.	NOUN
ajst-26756	1	19	1	1	NUM
ajst-26756	1	20	,	,	PUNCT
ajst-26756	1	21	2024	2024	NUM
ajst-26756	1	22	89	89	NUM
ajst-26756	1	23	research	research	NOUN
ajst-26756	1	24	on	on	ADP
ajst-26756	1	25	pavement	pavement	NOUN
ajst-26756	1	26	defect	defect	NOUN
ajst-26756	1	27	detection	detection	NOUN
ajst-26756	1	28	algorithm	algorithm	NOUN
ajst-26756	1	29	based	base	VERB
ajst-26756	1	30	on	on	ADP
ajst-26756	1	31	sem‐yolov8n	sem‐yolov8n	PROPN
ajst-26756	1	32	jingwei	jingwei	NOUN
ajst-26756	1	33	deng1	deng1	NOUN
ajst-26756	1	34	,	,	PUNCT
ajst-26756	1	35	li	li	PROPN
ajst-26756	1	36	yang1	yang1	PROPN
ajst-26756	1	37	,	,	PUNCT
ajst-26756	1	38	2	2	NUM
ajst-26756	1	39	1school	1school	NUM
ajst-26756	1	40	of	of	ADP
ajst-26756	1	41	automation	automation	NOUN
ajst-26756	1	42	and	and	CCONJ
ajst-26756	1	43	electrical	electrical	ADJ
ajst-26756	1	44	engineering	engineering	NOUN
ajst-26756	1	45	,	,	PUNCT
ajst-26756	1	46	tianjin	tianjin	PROPN
ajst-26756	1	47	university	university	PROPN
ajst-26756	1	48	of	of	ADP
ajst-26756	1	49	technology	technology	NOUN
ajst-26756	1	50	and	and	CCONJ
ajst-26756	1	51	education	education	NOUN
ajst-26756	1	52	,	,	PUNCT
ajst-26756	1	53	tianjin	tianjin	PROPN
ajst-26756	1	54	300222	300222	NUM
ajst-26756	1	55	,	,	PUNCT
ajst-26756	1	56	china	china	PROPN
ajst-26756	1	57	2tianjin	2tianjin	NUM
ajst-26756	1	58	key	key	ADJ
ajst-26756	1	59	laboratory	laboratory	NOUN
ajst-26756	1	60	of	of	ADP
ajst-26756	1	61	information	information	NOUN
ajst-26756	1	62	sensing	sense	VERB
ajst-26756	1	63	and	and	CCONJ
ajst-26756	1	64	intelligent	intelligent	ADJ
ajst-26756	1	65	control	control	NOUN
ajst-26756	1	66	,	,	PUNCT
ajst-26756	1	67	tianjin	tianjin	PROPN
ajst-26756	1	68	university	university	PROPN
ajst-26756	1	69	of	of	ADP
ajst-26756	1	70	technology	technology	NOUN
ajst-26756	1	71	and	and	CCONJ
ajst-26756	1	72	education	education	NOUN
ajst-26756	1	73	,	,	PUNCT
ajst-26756	1	74	tianjin	tianjin	PROPN
ajst-26756	1	75	300222	300222	NUM
ajst-26756	1	76	,	,	PUNCT
ajst-26756	1	77	china	china	PROPN
ajst-26756	1	78	abstract	abstract	NOUN
ajst-26756	1	79	:	:	PUNCT
ajst-26756	1	80	automated	automate	VERB
ajst-26756	1	81	detection	detection	NOUN
ajst-26756	1	82	and	and	CCONJ
ajst-26756	1	83	identification	identification	NOUN
ajst-26756	1	84	of	of	ADP
ajst-26756	1	85	pavement	pavement	NOUN
ajst-26756	1	86	distresses	distress	NOUN
ajst-26756	1	87	is	be	AUX
ajst-26756	1	88	essential	essential	ADJ
ajst-26756	1	89	for	for	ADP
ajst-26756	1	90	timely	timely	ADJ
ajst-26756	1	91	pavement	pavement	NOUN
ajst-26756	1	92	repair	repair	NOUN
ajst-26756	1	93	.	.	PUNCT
ajst-26756	2	1	subtle	subtle	ADJ
ajst-26756	2	2	pavement	pavement	NOUN
ajst-26756	2	3	defects	defect	NOUN
ajst-26756	2	4	and	and	CCONJ
ajst-26756	2	5	multiple	multiple	ADJ
ajst-26756	2	6	defects	defect	NOUN
ajst-26756	2	7	detection	detection	NOUN
ajst-26756	2	8	is	be	AUX
ajst-26756	2	9	a	a	DET
ajst-26756	2	10	challenging	challenging	ADJ
ajst-26756	2	11	task	task	NOUN
ajst-26756	2	12	under	under	ADP
ajst-26756	2	13	complex	complex	ADJ
ajst-26756	2	14	background	background	NOUN
ajst-26756	2	15	.	.	PUNCT
ajst-26756	3	1	with	with	ADP
ajst-26756	3	2	the	the	DET
ajst-26756	3	3	deepening	deepening	NOUN
ajst-26756	3	4	of	of	ADP
ajst-26756	3	5	the	the	DET
ajst-26756	3	6	deep	deep	ADJ
ajst-26756	3	7	learning	learning	NOUN
ajst-26756	3	8	network	network	NOUN
ajst-26756	3	9	,	,	PUNCT
ajst-26756	3	10	some	some	DET
ajst-26756	3	11	subtle	subtle	ADJ
ajst-26756	3	12	features	feature	NOUN
ajst-26756	3	13	tend	tend	VERB
ajst-26756	3	14	to	to	PART
ajst-26756	3	15	disappear	disappear	VERB
ajst-26756	3	16	and	and	CCONJ
ajst-26756	3	17	are	be	AUX
ajst-26756	3	18	more	more	ADV
ajst-26756	3	19	difficult	difficult	ADJ
ajst-26756	3	20	to	to	PART
ajst-26756	3	21	detect	detect	VERB
ajst-26756	3	22	under	under	ADP
ajst-26756	3	23	the	the	DET
ajst-26756	3	24	influence	influence	NOUN
ajst-26756	3	25	of	of	ADP
ajst-26756	3	26	the	the	DET
ajst-26756	3	27	complex	complex	ADJ
ajst-26756	3	28	background	background	NOUN
ajst-26756	3	29	.	.	PUNCT
ajst-26756	4	1	to	to	PART
ajst-26756	4	2	solve	solve	VERB
ajst-26756	4	3	the	the	DET
ajst-26756	4	4	above	above	ADJ
ajst-26756	4	5	problems	problem	NOUN
ajst-26756	4	6	,	,	PUNCT
ajst-26756	4	7	this	this	DET
ajst-26756	4	8	paper	paper	NOUN
ajst-26756	4	9	proposes	propose	VERB
ajst-26756	4	10	the	the	DET
ajst-26756	4	11	sem	sem	PROPN
ajst-26756	4	12	-	-	PUNCT
ajst-26756	4	13	yolov8n	yolov8n	NOUN
ajst-26756	4	14	pavement	pavement	NOUN
ajst-26756	4	15	defect	defect	NOUN
ajst-26756	4	16	detection	detection	NOUN
ajst-26756	4	17	algorithm	algorithm	NOUN
ajst-26756	4	18	.	.	PUNCT
ajst-26756	5	1	firstly	firstly	ADV
ajst-26756	5	2	,	,	PUNCT
ajst-26756	5	3	spd	spd	ADJ
ajst-26756	5	4	-	-	PUNCT
ajst-26756	5	5	conv	conv	ADJ
ajst-26756	5	6	is	be	AUX
ajst-26756	5	7	used	use	VERB
ajst-26756	5	8	to	to	PART
ajst-26756	5	9	replace	replace	VERB
ajst-26756	5	10	the	the	DET
ajst-26756	5	11	traditional	traditional	ADJ
ajst-26756	5	12	convolution	convolution	NOUN
ajst-26756	5	13	,	,	PUNCT
ajst-26756	5	14	which	which	PRON
ajst-26756	5	15	is	be	AUX
ajst-26756	5	16	conducive	conducive	ADJ
ajst-26756	5	17	to	to	ADP
ajst-26756	5	18	retaining	retain	VERB
ajst-26756	5	19	more	more	ADJ
ajst-26756	5	20	defect	defect	ADJ
ajst-26756	5	21	detail	detail	NOUN
ajst-26756	5	22	information	information	NOUN
ajst-26756	5	23	in	in	ADP
ajst-26756	5	24	the	the	DET
ajst-26756	5	25	image	image	NOUN
ajst-26756	5	26	and	and	CCONJ
ajst-26756	5	27	improving	improve	VERB
ajst-26756	5	28	the	the	DET
ajst-26756	5	29	detection	detection	NOUN
ajst-26756	5	30	ability	ability	NOUN
ajst-26756	5	31	of	of	ADP
ajst-26756	5	32	subtle	subtle	ADJ
ajst-26756	5	33	defects	defect	NOUN
ajst-26756	5	34	;	;	PUNCT
ajst-26756	5	35	then	then	ADV
ajst-26756	5	36	an	an	DET
ajst-26756	5	37	efficient	efficient	ADJ
ajst-26756	5	38	multi	multi	ADJ
ajst-26756	5	39	-	-	ADJ
ajst-26756	5	40	scale	scale	ADJ
ajst-26756	5	41	attention	attention	NOUN
ajst-26756	5	42	mechanism	mechanism	NOUN
ajst-26756	5	43	is	be	AUX
ajst-26756	5	44	added	add	VERB
ajst-26756	5	45	to	to	ADP
ajst-26756	5	46	the	the	DET
ajst-26756	5	47	fusion	fusion	NOUN
ajst-26756	5	48	network	network	NOUN
ajst-26756	5	49	,	,	PUNCT
ajst-26756	5	50	so	so	SCONJ
ajst-26756	5	51	that	that	SCONJ
ajst-26756	5	52	the	the	DET
ajst-26756	5	53	network	network	NOUN
ajst-26756	5	54	suppresses	suppress	VERB
ajst-26756	5	55	the	the	DET
ajst-26756	5	56	background	background	NOUN
ajst-26756	5	57	information	information	NOUN
ajst-26756	5	58	and	and	CCONJ
ajst-26756	5	59	focuses	focus	VERB
ajst-26756	5	60	more	more	ADJ
ajst-26756	5	61	on	on	ADP
ajst-26756	5	62	the	the	DET
ajst-26756	5	63	defect	defect	NOUN
ajst-26756	5	64	information	information	NOUN
ajst-26756	5	65	.	.	PUNCT
ajst-26756	6	1	finally	finally	ADV
ajst-26756	6	2	,	,	PUNCT
ajst-26756	6	3	mpdiou	mpdiou	NOUN
ajst-26756	6	4	is	be	AUX
ajst-26756	6	5	introduced	introduce	VERB
ajst-26756	6	6	as	as	ADP
ajst-26756	6	7	a	a	DET
ajst-26756	6	8	loss	loss	NOUN
ajst-26756	6	9	function	function	NOUN
ajst-26756	6	10	,	,	PUNCT
ajst-26756	6	11	which	which	PRON
ajst-26756	6	12	optimizes	optimize	VERB
ajst-26756	6	13	the	the	DET
ajst-26756	6	14	minimum	minimum	ADJ
ajst-26756	6	15	perpendicular	perpendicular	ADJ
ajst-26756	6	16	distance	distance	NOUN
ajst-26756	6	17	between	between	ADP
ajst-26756	6	18	the	the	DET
ajst-26756	6	19	predicted	predict	VERB
ajst-26756	6	20	bounding	bounding	NOUN
ajst-26756	6	21	box	box	NOUN
ajst-26756	6	22	and	and	CCONJ
ajst-26756	6	23	the	the	DET
ajst-26756	6	24	real	real	ADJ
ajst-26756	6	25	bounding	bounding	NOUN
ajst-26756	6	26	box	box	NOUN
ajst-26756	6	27	and	and	CCONJ
ajst-26756	6	28	improves	improve	VERB
ajst-26756	6	29	the	the	DET
ajst-26756	6	30	localization	localization	NOUN
ajst-26756	6	31	ability	ability	NOUN
ajst-26756	6	32	,	,	PUNCT
ajst-26756	6	33	thus	thus	ADV
ajst-26756	6	34	improving	improve	VERB
ajst-26756	6	35	the	the	DET
ajst-26756	6	36	accuracy	accuracy	NOUN
ajst-26756	6	37	of	of	ADP
ajst-26756	6	38	the	the	DET
ajst-26756	6	39	network	network	NOUN
ajst-26756	6	40	.	.	PUNCT
ajst-26756	7	1	finally	finally	ADV
ajst-26756	7	2	,	,	PUNCT
ajst-26756	7	3	the	the	DET
ajst-26756	7	4	effectiveness	effectiveness	NOUN
ajst-26756	7	5	of	of	ADP
ajst-26756	7	6	the	the	DET
ajst-26756	7	7	proposed	propose	VERB
ajst-26756	7	8	network	network	NOUN
ajst-26756	7	9	is	be	AUX
ajst-26756	7	10	verified	verify	VERB
ajst-26756	7	11	on	on	ADP
ajst-26756	7	12	the	the	DET
ajst-26756	7	13	irrdd	irrdd	ADJ
ajst-26756	7	14	dataset	dataset	NOUN
ajst-26756	7	15	,	,	PUNCT
ajst-26756	7	16	and	and	CCONJ
ajst-26756	7	17	the	the	DET
ajst-26756	7	18	results	result	NOUN
ajst-26756	7	19	show	show	VERB
ajst-26756	7	20	that	that	SCONJ
ajst-26756	7	21	the	the	DET
ajst-26756	7	22	method	method	NOUN
ajst-26756	7	23	achieves	achieve	VERB
ajst-26756	7	24	91.9	91.9	NUM
ajst-26756	7	25	%	%	NOUN
ajst-26756	7	26	(	(	PUNCT
ajst-26756	7	27	precision	precision	NOUN
ajst-26756	7	28	)	)	PUNCT
ajst-26756	7	29	,	,	PUNCT
ajst-26756	7	30	91.3	91.3	NUM
ajst-26756	7	31	%	%	NOUN
ajst-26756	7	32	(	(	PUNCT
ajst-26756	7	33	recall	recall	NOUN
ajst-26756	7	34	)	)	PUNCT
ajst-26756	7	35	,	,	PUNCT
ajst-26756	7	36	and	and	CCONJ
ajst-26756	7	37	71.3	71.3	NUM
ajst-26756	7	38	%	%	NOUN
ajst-26756	7	39	(	(	PUNCT
ajst-26756	7	40	map	map	NOUN
ajst-26756	7	41	)	)	PUNCT
ajst-26756	7	42	for	for	ADP
ajst-26756	7	43	the	the	DET
ajst-26756	7	44	classification	classification	NOUN
ajst-26756	7	45	and	and	CCONJ
ajst-26756	7	46	detection	detection	NOUN
ajst-26756	7	47	of	of	ADP
ajst-26756	7	48	road	road	NOUN
ajst-26756	7	49	multi	multi	ADJ
ajst-26756	7	50	-	-	ADJ
ajst-26756	7	51	scale	scale	ADJ
ajst-26756	7	52	minor	minor	ADJ
ajst-26756	7	53	defects	defect	NOUN
ajst-26756	7	54	,	,	PUNCT
ajst-26756	7	55	which	which	PRON
ajst-26756	7	56	meets	meet	VERB
ajst-26756	7	57	the	the	DET
ajst-26756	7	58	demand	demand	NOUN
ajst-26756	7	59	of	of	ADP
ajst-26756	7	60	real	real	ADJ
ajst-26756	7	61	-	-	PUNCT
ajst-26756	7	62	time	time	NOUN
ajst-26756	7	63	road	road	NOUN
ajst-26756	7	64	defect	defect	NOUN
ajst-26756	7	65	detection	detection	NOUN
ajst-26756	7	66	.	.	PUNCT
ajst-26756	8	1	keywords	keyword	NOUN
ajst-26756	8	2	:	:	PUNCT
ajst-26756	8	3	road	road	NOUN
ajst-26756	8	4	defect	defect	NOUN
ajst-26756	8	5	;	;	PUNCT
ajst-26756	8	6	deep	deep	ADJ
ajst-26756	8	7	learning	learning	NOUN
ajst-26756	8	8	;	;	PUNCT
ajst-26756	9	1	yolov8	yolov8	PROPN
ajst-26756	9	2	.	.	PUNCT
ajst-26756	10	1	1	1	X
ajst-26756	10	2	.	.	X
ajst-26756	10	3	introduction	introduction	NOUN
ajst-26756	10	4	defects	defect	NOUN
ajst-26756	10	5	in	in	ADP
ajst-26756	10	6	pavement	pavement	NOUN
ajst-26756	10	7	directly	directly	ADV
ajst-26756	10	8	affect	affect	VERB
ajst-26756	10	9	the	the	DET
ajst-26756	10	10	quality	quality	NOUN
ajst-26756	10	11	of	of	ADP
ajst-26756	10	12	the	the	DET
ajst-26756	10	13	pavement	pavement	NOUN
ajst-26756	10	14	.	.	PUNCT
ajst-26756	11	1	cracks	crack	NOUN
ajst-26756	11	2	and	and	CCONJ
ajst-26756	11	3	potholes	pothole	NOUN
ajst-26756	11	4	are	be	AUX
ajst-26756	11	5	the	the	DET
ajst-26756	11	6	most	most	ADV
ajst-26756	11	7	common	common	ADJ
ajst-26756	11	8	causes	cause	NOUN
ajst-26756	11	9	of	of	ADP
ajst-26756	11	10	damage	damage	NOUN
ajst-26756	11	11	to	to	ADP
ajst-26756	11	12	pavements	pavement	NOUN
ajst-26756	11	13	,	,	PUNCT
ajst-26756	11	14	which	which	PRON
ajst-26756	11	15	are	be	AUX
ajst-26756	11	16	usually	usually	ADV
ajst-26756	11	17	caused	cause	VERB
ajst-26756	11	18	by	by	ADP
ajst-26756	11	19	improper	improper	ADJ
ajst-26756	11	20	operation	operation	NOUN
ajst-26756	11	21	or	or	CCONJ
ajst-26756	11	22	inferior	inferior	ADJ
ajst-26756	11	23	materials	material	NOUN
ajst-26756	11	24	during	during	ADP
ajst-26756	11	25	construction	construction	NOUN
ajst-26756	11	26	,	,	PUNCT
ajst-26756	11	27	excessive	excessive	ADJ
ajst-26756	11	28	pressure	pressure	NOUN
ajst-26756	11	29	on	on	ADP
ajst-26756	11	30	the	the	DET
ajst-26756	11	31	pavement	pavement	NOUN
ajst-26756	11	32	during	during	ADP
ajst-26756	11	33	long	long	ADJ
ajst-26756	11	34	periods	period	NOUN
ajst-26756	11	35	of	of	ADP
ajst-26756	11	36	heavy	heavy	ADJ
ajst-26756	11	37	traffic	traffic	NOUN
ajst-26756	11	38	,	,	PUNCT
ajst-26756	11	39	or	or	CCONJ
ajst-26756	11	40	the	the	DET
ajst-26756	11	41	influence	influence	NOUN
ajst-26756	11	42	of	of	ADP
ajst-26756	11	43	specific	specific	ADJ
ajst-26756	11	44	climatic	climatic	ADJ
ajst-26756	11	45	and	and	CCONJ
ajst-26756	11	46	environmental	environmental	ADJ
ajst-26756	11	47	factors	factor	NOUN
ajst-26756	11	48	in	in	ADP
ajst-26756	11	49	certain	certain	ADJ
ajst-26756	11	50	areas	area	NOUN
ajst-26756	11	51	.	.	PUNCT
ajst-26756	12	1	specifically	specifically	ADV
ajst-26756	12	2	,	,	PUNCT
ajst-26756	12	3	poor	poor	ADJ
ajst-26756	12	4	pavement	pavement	NOUN
ajst-26756	12	5	condition	condition	NOUN
ajst-26756	12	6	,	,	PUNCT
ajst-26756	12	7	abnormal	abnormal	ADJ
ajst-26756	12	8	pavement	pavement	NOUN
ajst-26756	12	9	or	or	CCONJ
ajst-26756	12	10	severe	severe	ADJ
ajst-26756	12	11	damage	damage	NOUN
ajst-26756	12	12	may	may	AUX
ajst-26756	12	13	hinder	hinder	VERB
ajst-26756	12	14	traffic	traffic	NOUN
ajst-26756	12	15	,	,	PUNCT
ajst-26756	12	16	guide	guide	VERB
ajst-26756	12	17	incorrect	incorrect	ADJ
ajst-26756	12	18	driving	driving	NOUN
ajst-26756	12	19	behavior	behavior	NOUN
ajst-26756	12	20	,	,	PUNCT
ajst-26756	12	21	or	or	CCONJ
ajst-26756	12	22	even	even	ADV
ajst-26756	12	23	cause	cause	VERB
ajst-26756	12	24	traffic	traffic	NOUN
ajst-26756	12	25	accidents	accident	NOUN
ajst-26756	12	26	and	and	CCONJ
ajst-26756	12	27	casualties	casualty	NOUN
ajst-26756	12	28	.	.	PUNCT
ajst-26756	13	1	therefore	therefore	ADV
ajst-26756	13	2	,	,	PUNCT
ajst-26756	13	3	regular	regular	ADJ
ajst-26756	13	4	comprehensive	comprehensive	ADJ
ajst-26756	13	5	pavement	pavement	NOUN
ajst-26756	13	6	inspections	inspection	NOUN
ajst-26756	13	7	to	to	PART
ajst-26756	13	8	detect	detect	VERB
ajst-26756	13	9	pavement	pavement	NOUN
ajst-26756	13	10	anomalies	anomaly	NOUN
ajst-26756	13	11	and	and	CCONJ
ajst-26756	13	12	damage	damage	NOUN
ajst-26756	13	13	in	in	ADP
ajst-26756	13	14	a	a	DET
ajst-26756	13	15	timely	timely	ADJ
ajst-26756	13	16	manner	manner	NOUN
ajst-26756	13	17	are	be	AUX
ajst-26756	13	18	essential	essential	ADJ
ajst-26756	13	19	to	to	PART
ajst-26756	13	20	ensure	ensure	VERB
ajst-26756	13	21	the	the	DET
ajst-26756	13	22	convenience	convenience	NOUN
ajst-26756	13	23	,	,	PUNCT
ajst-26756	13	24	correctness	correctness	NOUN
ajst-26756	13	25	and	and	CCONJ
ajst-26756	13	26	safety	safety	NOUN
ajst-26756	13	27	of	of	ADP
ajst-26756	13	28	the	the	DET
ajst-26756	13	29	associated	associated	ADJ
ajst-26756	13	30	traffic	traffic	NOUN
ajst-26756	13	31	or	or	CCONJ
ajst-26756	13	32	driving	driving	NOUN
ajst-26756	13	33	behavior	behavior	NOUN
ajst-26756	13	34	.	.	PUNCT
ajst-26756	14	1	in	in	ADP
ajst-26756	14	2	the	the	DET
ajst-26756	14	3	early	early	ADJ
ajst-26756	14	4	days	day	NOUN
ajst-26756	14	5	,	,	PUNCT
ajst-26756	14	6	pavement	pavement	NOUN
ajst-26756	14	7	crack	crack	NOUN
ajst-26756	14	8	inspection	inspection	NOUN
ajst-26756	14	9	was	be	AUX
ajst-26756	14	10	mainly	mainly	ADV
ajst-26756	14	11	carried	carry	VERB
ajst-26756	14	12	out	out	ADP
ajst-26756	14	13	by	by	ADP
ajst-26756	14	14	trained	train	VERB
ajst-26756	14	15	workers	worker	NOUN
ajst-26756	14	16	through	through	ADP
ajst-26756	14	17	on	on	ADP
ajst-26756	14	18	-	-	PUNCT
ajst-26756	14	19	site	site	NOUN
ajst-26756	14	20	field	field	NOUN
ajst-26756	14	21	investigations	investigation	NOUN
ajst-26756	14	22	.	.	PUNCT
ajst-26756	15	1	however	however	ADV
ajst-26756	15	2	,	,	PUNCT
ajst-26756	15	3	this	this	DET
ajst-26756	15	4	solution	solution	NOUN
ajst-26756	15	5	was	be	AUX
ajst-26756	15	6	inefficient	inefficient	ADJ
ajst-26756	15	7	,	,	PUNCT
ajst-26756	15	8	labor	labor	NOUN
ajst-26756	15	9	-	-	PUNCT
ajst-26756	15	10	intensive	intensive	ADJ
ajst-26756	15	11	,	,	PUNCT
ajst-26756	15	12	and	and	CCONJ
ajst-26756	15	13	even	even	ADV
ajst-26756	15	14	hindered	hinder	VERB
ajst-26756	15	15	traffic	traffic	NOUN
ajst-26756	15	16	,	,	PUNCT
ajst-26756	15	17	resulting	result	VERB
ajst-26756	15	18	in	in	ADP
ajst-26756	15	19	missed	miss	VERB
ajst-26756	15	20	inspections	inspection	NOUN
ajst-26756	15	21	.	.	PUNCT
ajst-26756	16	1	later	later	ADV
ajst-26756	16	2	,	,	PUNCT
ajst-26756	16	3	with	with	ADP
ajst-26756	16	4	the	the	DET
ajst-26756	16	5	development	development	NOUN
ajst-26756	16	6	of	of	ADP
ajst-26756	16	7	science	science	NOUN
ajst-26756	16	8	and	and	CCONJ
ajst-26756	16	9	technology	technology	NOUN
ajst-26756	16	10	,	,	PUNCT
ajst-26756	16	11	such	such	ADJ
ajst-26756	16	12	as	as	ADP
ajst-26756	16	13	the	the	DET
ajst-26756	16	14	use	use	NOUN
ajst-26756	16	15	of	of	ADP
ajst-26756	16	16	ground	ground	NOUN
ajst-26756	16	17	-	-	PUNCT
ajst-26756	16	18	penetrating	penetrate	VERB
ajst-26756	16	19	radar	radar	NOUN
ajst-26756	16	20	for	for	ADP
ajst-26756	16	21	pavement	pavement	NOUN
ajst-26756	16	22	defect	defect	NOUN
ajst-26756	16	23	detection	detection	NOUN
ajst-26756	16	24	[	[	X
ajst-26756	16	25	1	1	NUM
ajst-26756	16	26	]	]	PUNCT
ajst-26756	16	27	,	,	PUNCT
ajst-26756	16	28	this	this	DET
ajst-26756	16	29	method	method	NOUN
ajst-26756	16	30	,	,	PUNCT
ajst-26756	16	31	although	although	SCONJ
ajst-26756	16	32	the	the	DET
ajst-26756	16	33	accuracy	accuracy	NOUN
ajst-26756	16	34	has	have	AUX
ajst-26756	16	35	been	be	AUX
ajst-26756	16	36	improved	improve	VERB
ajst-26756	16	37	to	to	ADP
ajst-26756	16	38	some	some	DET
ajst-26756	16	39	extent	extent	NOUN
ajst-26756	16	40	,	,	PUNCT
ajst-26756	16	41	is	be	AUX
ajst-26756	16	42	costly	costly	ADJ
ajst-26756	16	43	and	and	CCONJ
ajst-26756	16	44	slow	slow	ADJ
ajst-26756	16	45	,	,	PUNCT
ajst-26756	16	46	and	and	CCONJ
ajst-26756	16	47	can	can	AUX
ajst-26756	16	48	not	not	PART
ajst-26756	16	49	meet	meet	VERB
ajst-26756	16	50	the	the	DET
ajst-26756	16	51	huge	huge	ADJ
ajst-26756	16	52	number	number	NOUN
ajst-26756	16	53	of	of	ADP
ajst-26756	16	54	pavement	pavement	NOUN
ajst-26756	16	55	inspections	inspection	NOUN
ajst-26756	16	56	in	in	ADP
ajst-26756	16	57	today	today	NOUN
ajst-26756	16	58	's	's	PART
ajst-26756	16	59	society	society	NOUN
ajst-26756	16	60	.	.	PUNCT
ajst-26756	17	1	several	several	ADJ
ajst-26756	17	2	image	image	NOUN
ajst-26756	17	3	processing	processing	NOUN
ajst-26756	17	4	techniques	technique	NOUN
ajst-26756	17	5	,	,	PUNCT
ajst-26756	17	6	such	such	ADJ
ajst-26756	17	7	as	as	ADP
ajst-26756	17	8	edge	edge	NOUN
ajst-26756	17	9	detection	detection	NOUN
ajst-26756	17	10	[	[	X
ajst-26756	17	11	2	2	NUM
ajst-26756	17	12	]	]	PUNCT
ajst-26756	17	13	,	,	PUNCT
ajst-26756	17	14	threshold	threshold	NOUN
ajst-26756	17	15	segmentation	segmentation	NOUN
ajst-26756	17	16	[	[	X
ajst-26756	17	17	3	3	NUM
ajst-26756	17	18	]	]	PUNCT
ajst-26756	17	19	,	,	PUNCT
ajst-26756	17	20	and	and	CCONJ
ajst-26756	17	21	mathematical	mathematical	ADJ
ajst-26756	17	22	morphology	morphology	NOUN
ajst-26756	17	23	[	[	X
ajst-26756	17	24	4	4	NUM
ajst-26756	17	25	]	]	PUNCT
ajst-26756	17	26	,	,	PUNCT
ajst-26756	17	27	have	have	AUX
ajst-26756	17	28	been	be	AUX
ajst-26756	17	29	used	use	VERB
ajst-26756	17	30	to	to	PART
ajst-26756	17	31	detect	detect	VERB
ajst-26756	17	32	pavement	pavement	NOUN
ajst-26756	17	33	defects	defect	NOUN
ajst-26756	17	34	in	in	ADP
ajst-26756	17	35	the	the	DET
ajst-26756	17	36	past	past	ADJ
ajst-26756	17	37	decades	decade	NOUN
ajst-26756	17	38	.	.	PUNCT
ajst-26756	18	1	due	due	ADP
ajst-26756	18	2	to	to	ADP
ajst-26756	18	3	the	the	DET
ajst-26756	18	4	complex	complex	ADJ
ajst-26756	18	5	background	background	NOUN
ajst-26756	18	6	interference	interference	NOUN
ajst-26756	18	7	such	such	ADJ
ajst-26756	18	8	as	as	ADP
ajst-26756	18	9	multi	multi	ADJ
ajst-26756	18	10	-	-	ADJ
ajst-26756	18	11	texture	texture	ADJ
ajst-26756	18	12	,	,	PUNCT
ajst-26756	18	13	multi	multi	ADJ
ajst-26756	18	14	-	-	NOUN
ajst-26756	18	15	targets	target	NOUN
ajst-26756	18	16	,	,	PUNCT
ajst-26756	18	17	and	and	CCONJ
ajst-26756	18	18	variable	variable	ADJ
ajst-26756	18	19	background	background	NOUN
ajst-26756	18	20	illumination	illumination	NOUN
ajst-26756	18	21	,	,	PUNCT
ajst-26756	18	22	which	which	PRON
ajst-26756	18	23	make	make	VERB
ajst-26756	18	24	pavement	pavement	NOUN
ajst-26756	18	25	images	image	NOUN
ajst-26756	18	26	the	the	DET
ajst-26756	18	27	most	most	ADV
ajst-26756	18	28	difficult	difficult	ADJ
ajst-26756	18	29	targets	target	NOUN
ajst-26756	18	30	to	to	PART
ajst-26756	18	31	recognize	recognize	VERB
ajst-26756	18	32	,	,	PUNCT
ajst-26756	18	33	traditional	traditional	ADJ
ajst-26756	18	34	detection	detection	NOUN
ajst-26756	18	35	methods	method	NOUN
ajst-26756	18	36	can	can	AUX
ajst-26756	18	37	no	no	ADV
ajst-26756	18	38	longer	long	ADV
ajst-26756	18	39	satisfy	satisfy	VERB
ajst-26756	18	40	the	the	DET
ajst-26756	18	41	need	need	NOUN
ajst-26756	18	42	for	for	ADP
ajst-26756	18	43	fast	fast	ADJ
ajst-26756	18	44	and	and	CCONJ
ajst-26756	18	45	accurate	accurate	ADJ
ajst-26756	18	46	detection	detection	NOUN
ajst-26756	18	47	of	of	ADP
ajst-26756	18	48	pavement	pavement	NOUN
ajst-26756	18	49	defects	defect	NOUN
ajst-26756	18	50	.	.	PUNCT
ajst-26756	19	1	with	with	ADP
ajst-26756	19	2	the	the	DET
ajst-26756	19	3	rapid	rapid	ADJ
ajst-26756	19	4	development	development	NOUN
ajst-26756	19	5	of	of	ADP
ajst-26756	19	6	deep	deep	ADJ
ajst-26756	19	7	learning	learning	NOUN
ajst-26756	19	8	,	,	PUNCT
ajst-26756	19	9	computer	computer	NOUN
ajst-26756	19	10	vision	vision	NOUN
ajst-26756	19	11	-	-	PUNCT
ajst-26756	19	12	based	base	VERB
ajst-26756	19	13	defect	defect	NOUN
ajst-26756	19	14	detection	detection	NOUN
ajst-26756	19	15	methods	method	NOUN
ajst-26756	19	16	have	have	AUX
ajst-26756	19	17	attracted	attract	VERB
ajst-26756	19	18	great	great	ADJ
ajst-26756	19	19	interest	interest	NOUN
ajst-26756	19	20	from	from	ADP
ajst-26756	19	21	academia	academia	NOUN
ajst-26756	19	22	and	and	CCONJ
ajst-26756	19	23	industry	industry	NOUN
ajst-26756	19	24	due	due	ADP
ajst-26756	19	25	to	to	ADP
ajst-26756	19	26	their	their	PRON
ajst-26756	19	27	advantages	advantage	NOUN
ajst-26756	19	28	of	of	ADP
ajst-26756	19	29	safety	safety	NOUN
ajst-26756	19	30	,	,	PUNCT
ajst-26756	19	31	cost	cost	NOUN
ajst-26756	19	32	,	,	PUNCT
ajst-26756	19	33	efficiency	efficiency	NOUN
ajst-26756	19	34	and	and	CCONJ
ajst-26756	19	35	objectivity	objectivity	NOUN
ajst-26756	19	36	.	.	PUNCT
ajst-26756	20	1	deep	deep	ADJ
ajst-26756	20	2	learning	learning	NOUN
ajst-26756	20	3	techniques	technique	NOUN
ajst-26756	20	4	have	have	AUX
ajst-26756	20	5	been	be	AUX
ajst-26756	20	6	successfully	successfully	ADV
ajst-26756	20	7	applied	apply	VERB
ajst-26756	20	8	to	to	PART
ajst-26756	20	9	target	target	VERB
ajst-26756	20	10	detection	detection	NOUN
ajst-26756	20	11	[	[	X
ajst-26756	20	12	5	5	NUM
ajst-26756	20	13	]	]	PUNCT
ajst-26756	20	14	and	and	CCONJ
ajst-26756	20	15	image	image	NOUN
ajst-26756	20	16	classification	classification	NOUN
ajst-26756	20	17	tasks	task	NOUN
ajst-26756	20	18	with	with	ADP
ajst-26756	20	19	good	good	ADJ
ajst-26756	20	20	experimental	experimental	ADJ
ajst-26756	20	21	results	result	NOUN
ajst-26756	20	22	.	.	PUNCT
ajst-26756	21	1	deng	deng	PROPN
ajst-26756	21	2	et	et	PROPN
ajst-26756	21	3	al	al	PROPN
ajst-26756	22	1	[	[	X
ajst-26756	22	2	6	6	NUM
ajst-26756	22	3	]	]	PUNCT
ajst-26756	22	4	applied	apply	VERB
ajst-26756	22	5	a	a	DET
ajst-26756	22	6	faster	fast	ADJ
ajst-26756	22	7	region	region	NOUN
ajst-26756	22	8	-	-	PUNCT
ajst-26756	22	9	based	base	VERB
ajst-26756	22	10	convolutional	convolutional	ADJ
ajst-26756	22	11	neural	neural	ADJ
ajst-26756	22	12	network	network	NOUN
ajst-26756	22	13	to	to	ADP
ajst-26756	22	14	real	real	ADJ
ajst-26756	22	15	-	-	PUNCT
ajst-26756	22	16	world	world	NOUN
ajst-26756	22	17	images	image	NOUN
ajst-26756	22	18	taken	take	VERB
ajst-26756	22	19	from	from	ADP
ajst-26756	22	20	concrete	concrete	ADJ
ajst-26756	22	21	bridges	bridge	NOUN
ajst-26756	22	22	with	with	ADP
ajst-26756	22	23	complex	complex	ADJ
ajst-26756	22	24	backgrounds	background	NOUN
ajst-26756	22	25	,	,	PUNCT
ajst-26756	22	26	and	and	CCONJ
ajst-26756	22	27	experimentally	experimentally	ADV
ajst-26756	22	28	proved	prove	VERB
ajst-26756	22	29	that	that	SCONJ
ajst-26756	22	30	the	the	DET
ajst-26756	22	31	network	network	NOUN
ajst-26756	22	32	meets	meet	VERB
ajst-26756	22	33	the	the	DET
ajst-26756	22	34	detection	detection	NOUN
ajst-26756	22	35	requirements	requirement	NOUN
ajst-26756	22	36	.	.	PUNCT
ajst-26756	23	1	wang	wang	PROPN
ajst-26756	23	2	et	et	PROPN
ajst-26756	23	3	al	al	PROPN
ajst-26756	24	1	[	[	X
ajst-26756	24	2	7	7	NUM
ajst-26756	24	3	]	]	PUNCT
ajst-26756	24	4	proposed	propose	VERB
ajst-26756	24	5	and	and	CCONJ
ajst-26756	24	6	validated	validate	VERB
ajst-26756	24	7	an	an	DET
ajst-26756	24	8	effective	effective	ADJ
ajst-26756	24	9	crack	crack	NOUN
ajst-26756	24	10	length	length	NOUN
ajst-26756	24	11	measurement	measurement	NOUN
ajst-26756	24	12	method	method	NOUN
ajst-26756	24	13	.	.	PUNCT
ajst-26756	25	1	the	the	DET
ajst-26756	25	2	method	method	NOUN
ajst-26756	25	3	consists	consist	VERB
ajst-26756	25	4	of	of	ADP
ajst-26756	25	5	a	a	DET
ajst-26756	25	6	detection	detection	NOUN
ajst-26756	25	7	module	module	NOUN
ajst-26756	25	8	based	base	VERB
ajst-26756	25	9	on	on	ADP
ajst-26756	25	10	the	the	DET
ajst-26756	25	11	target	target	NOUN
ajst-26756	25	12	detection	detection	NOUN
ajst-26756	25	13	algorithm	algorithm	NOUN
ajst-26756	25	14	and	and	CCONJ
ajst-26756	25	15	a	a	DET
ajst-26756	25	16	length	length	NOUN
ajst-26756	25	17	calculation	calculation	NOUN
ajst-26756	25	18	module	module	NOUN
ajst-26756	25	19	,	,	PUNCT
ajst-26756	25	20	and	and	CCONJ
ajst-26756	25	21	the	the	DET
ajst-26756	25	22	experiment	experiment	NOUN
ajst-26756	25	23	proves	prove	VERB
ajst-26756	25	24	the	the	DET
ajst-26756	25	25	effectiveness	effectiveness	NOUN
ajst-26756	25	26	of	of	ADP
ajst-26756	25	27	the	the	DET
ajst-26756	25	28	methods	method	NOUN
ajst-26756	25	29	.	.	PUNCT
ajst-26756	26	1	zheng	zheng	PROPN
ajst-26756	26	2	et	et	PROPN
ajst-26756	26	3	al[8	al[8	PROPN
ajst-26756	26	4	]	]	PUNCT
ajst-26756	26	5	proposed	propose	VERB
ajst-26756	26	6	a	a	DET
ajst-26756	26	7	new	new	ADJ
ajst-26756	26	8	automatic	automatic	ADJ
ajst-26756	26	9	road	road	NOUN
ajst-26756	26	10	crack	crack	NOUN
ajst-26756	26	11	detection	detection	NOUN
ajst-26756	26	12	algorithm	algorithm	NOUN
ajst-26756	26	13	for	for	ADP
ajst-26756	26	14	the	the	DET
ajst-26756	26	15	problems	problem	NOUN
ajst-26756	26	16	of	of	ADP
ajst-26756	26	17	low	low	ADJ
ajst-26756	26	18	efficiency	efficiency	NOUN
ajst-26756	26	19	of	of	ADP
ajst-26756	26	20	the	the	DET
ajst-26756	26	21	current	current	ADJ
ajst-26756	26	22	real	real	ADJ
ajst-26756	26	23	-	-	PUNCT
ajst-26756	26	24	time	time	NOUN
ajst-26756	26	25	road	road	NOUN
ajst-26756	26	26	crack	crack	NOUN
ajst-26756	26	27	detection	detection	NOUN
ajst-26756	26	28	research	research	NOUN
ajst-26756	26	29	results	result	NOUN
ajst-26756	26	30	,	,	PUNCT
ajst-26756	26	31	and	and	CCONJ
ajst-26756	26	32	low	low	ADJ
ajst-26756	26	33	storage	storage	NOUN
ajst-26756	26	34	and	and	CCONJ
ajst-26756	26	35	computation	computation	NOUN
ajst-26756	26	36	capacity	capacity	NOUN
ajst-26756	26	37	of	of	ADP
ajst-26756	26	38	the	the	DET
ajst-26756	26	39	edge	edge	NOUN
ajst-26756	26	40	devices	device	NOUN
ajst-26756	26	41	,	,	PUNCT
ajst-26756	26	42	and	and	CCONJ
ajst-26756	26	43	the	the	DET
ajst-26756	26	44	experiment	experiment	NOUN
ajst-26756	26	45	proves	prove	VERB
ajst-26756	26	46	that	that	SCONJ
ajst-26756	26	47	the	the	DET
ajst-26756	26	48	method	method	NOUN
ajst-26756	26	49	effectively	effectively	ADV
ajst-26756	26	50	solves	solve	VERB
ajst-26756	26	51	these	these	DET
ajst-26756	26	52	problems	problem	NOUN
ajst-26756	26	53	.	.	PUNCT
ajst-26756	27	1	luo	luo	PROPN
ajst-26756	27	2	et	et	PROPN
ajst-26756	27	3	al[9	al[9	PROPN
ajst-26756	27	4	]	]	PUNCT
ajst-26756	27	5	proposed	propose	VERB
ajst-26756	27	6	a	a	DET
ajst-26756	27	7	road	road	NOUN
ajst-26756	27	8	crack	crack	VERB
ajst-26756	27	9	automatic	automatic	ADJ
ajst-26756	27	10	detection	detection	NOUN
ajst-26756	27	11	architecture	architecture	NOUN
ajst-26756	27	12	strans	stran	NOUN
ajst-26756	27	13	-	-	PUNCT
ajst-26756	27	14	yolox	yolox	NOUN
ajst-26756	27	15	,	,	PUNCT
ajst-26756	27	16	which	which	PRON
ajst-26756	27	17	solves	solve	VERB
ajst-26756	27	18	the	the	DET
ajst-26756	27	19	problems	problem	NOUN
ajst-26756	27	20	that	that	PRON
ajst-26756	27	21	convolutional	convolutional	ADJ
ajst-26756	27	22	neural	neural	ADJ
ajst-26756	27	23	network	network	NOUN
ajst-26756	27	24	can	can	AUX
ajst-26756	27	25	not	not	PART
ajst-26756	27	26	adequately	adequately	ADV
ajst-26756	27	27	simulate	simulate	VERB
ajst-26756	27	28	the	the	DET
ajst-26756	27	29	long	long	ADJ
ajst-26756	27	30	-	-	PUNCT
ajst-26756	27	31	term	term	NOUN
ajst-26756	27	32	dependency	dependency	NOUN
ajst-26756	27	33	between	between	ADP
ajst-26756	27	34	pixels	pixel	NOUN
ajst-26756	27	35	in	in	ADP
ajst-26756	27	36	complex	complex	ADJ
ajst-26756	27	37	scenes	scene	NOUN
ajst-26756	27	38	,	,	PUNCT
ajst-26756	27	39	and	and	CCONJ
ajst-26756	27	40	is	be	AUX
ajst-26756	27	41	prone	prone	ADJ
ajst-26756	27	42	to	to	PART
ajst-26756	27	43	lose	lose	VERB
ajst-26756	27	44	the	the	DET
ajst-26756	27	45	edge	edge	NOUN
ajst-26756	27	46	detail	detail	NOUN
ajst-26756	27	47	information	information	NOUN
ajst-26756	27	48	.	.	PUNCT
ajst-26756	28	1	although	although	SCONJ
ajst-26756	28	2	all	all	DET
ajst-26756	28	3	the	the	DET
ajst-26756	28	4	above	above	ADJ
ajst-26756	28	5	methods	method	NOUN
ajst-26756	28	6	target	target	VERB
ajst-26756	28	7	specific	specific	ADJ
ajst-26756	28	8	datasets	dataset	NOUN
ajst-26756	28	9	and	and	CCONJ
ajst-26756	28	10	improve	improve	VERB
ajst-26756	28	11	the	the	DET
ajst-26756	28	12	accuracy	accuracy	NOUN
ajst-26756	28	13	of	of	ADP
ajst-26756	28	14	pavement	pavement	NOUN
ajst-26756	28	15	defect	defect	NOUN
ajst-26756	28	16	detection	detection	NOUN
ajst-26756	28	17	,	,	PUNCT
ajst-26756	28	18	the	the	DET
ajst-26756	28	19	computational	computational	ADJ
ajst-26756	28	20	volume	volume	NOUN
ajst-26756	28	21	is	be	AUX
ajst-26756	28	22	still	still	ADV
ajst-26756	28	23	large	large	ADJ
ajst-26756	28	24	and	and	CCONJ
ajst-26756	28	25	the	the	DET
ajst-26756	28	26	accuracy	accuracy	NOUN
ajst-26756	28	27	of	of	ADP
ajst-26756	28	28	detecting	detect	VERB
ajst-26756	28	29	subtle	subtle	ADJ
ajst-26756	28	30	pavement	pavement	NOUN
ajst-26756	28	31	defects	defect	NOUN
ajst-26756	28	32	is	be	AUX
ajst-26756	28	33	low	low	ADJ
ajst-26756	28	34	.	.	PUNCT
ajst-26756	29	1	for	for	ADP
ajst-26756	29	2	subtle	subtle	ADJ
ajst-26756	29	3	defects	defect	NOUN
ajst-26756	29	4	with	with	ADP
ajst-26756	29	5	small	small	ADJ
ajst-26756	29	6	size	size	NOUN
ajst-26756	29	7	and	and	CCONJ
ajst-26756	29	8	low	low	ADJ
ajst-26756	29	9	resolution	resolution	NOUN
ajst-26756	29	10	,	,	PUNCT
ajst-26756	29	11	the	the	DET
ajst-26756	29	12	role	role	NOUN
ajst-26756	29	13	of	of	ADP
ajst-26756	29	14	space	space	NOUN
ajst-26756	29	15	-	-	PUNCT
ajst-26756	29	16	to	to	ADP
ajst-26756	29	17	-	-	PUNCT
ajst-26756	29	18	depth	depth	NOUN
ajst-26756	29	19	(	(	PUNCT
ajst-26756	29	20	spd	spd	NOUN
ajst-26756	29	21	)	)	PUNCT
ajst-26756	29	22	[	[	X
ajst-26756	29	23	10	10	NUM
ajst-26756	29	24	]	]	PUNCT
ajst-26756	29	25	in	in	ADP
ajst-26756	29	26	convolutional	convolutional	ADJ
ajst-26756	29	27	neural	neural	ADJ
ajst-26756	29	28	networks	network	NOUN
ajst-26756	29	29	is	be	AUX
ajst-26756	29	30	to	to	PART
ajst-26756	29	31	split	split	VERB
ajst-26756	29	32	the	the	DET
ajst-26756	29	33	incoming	incoming	ADJ
ajst-26756	29	34	feature	feature	NOUN
ajst-26756	29	35	maps	map	NOUN
ajst-26756	29	36	into	into	ADP
ajst-26756	29	37	multiple	multiple	ADJ
ajst-26756	29	38	bands	band	NOUN
ajst-26756	29	39	,	,	PUNCT
ajst-26756	29	40	each	each	DET
ajst-26756	29	41	band	band	NOUN
ajst-26756	29	42	is	be	AUX
ajst-26756	29	43	convolved	convolve	VERB
ajst-26756	29	44	using	use	VERB
ajst-26756	29	45	a	a	DET
ajst-26756	29	46	different	different	ADJ
ajst-26756	29	47	convolution	convolution	NOUN
ajst-26756	29	48	kernel	kernel	NOUN
ajst-26756	29	49	,	,	PUNCT
ajst-26756	29	50	and	and	CCONJ
ajst-26756	29	51	the	the	DET
ajst-26756	29	52	results	result	NOUN
ajst-26756	29	53	are	be	AUX
ajst-26756	29	54	weighted	weight	VERB
ajst-26756	29	55	and	and	CCONJ
ajst-26756	29	56	summed	sum	VERB
ajst-26756	29	57	up	up	ADP
ajst-26756	29	58	according	accord	VERB
ajst-26756	29	59	to	to	ADP
ajst-26756	29	60	the	the	DET
ajst-26756	29	61	band	band	NOUN
ajst-26756	29	62	they	they	PRON
ajst-26756	29	63	belong	belong	VERB
ajst-26756	29	64	to	to	ADP
ajst-26756	29	65	,	,	PUNCT
ajst-26756	29	66	which	which	PRON
ajst-26756	29	67	can	can	AUX
ajst-26756	29	68	better	well	ADV
ajst-26756	29	69	retain	retain	VERB
ajst-26756	29	70	the	the	DET
ajst-26756	29	71	detailed	detailed	ADJ
ajst-26756	29	72	information	information	NOUN
ajst-26756	29	73	in	in	ADP
ajst-26756	29	74	complex	complex	ADJ
ajst-26756	29	75	background	background	NOUN
ajst-26756	29	76	images	image	NOUN
ajst-26756	29	77	and	and	CCONJ
ajst-26756	29	78	small	small	ADJ
ajst-26756	29	79	objects	object	NOUN
ajst-26756	29	80	,	,	PUNCT
ajst-26756	29	81	90	90	NUM
ajst-26756	29	82	to	to	PART
ajst-26756	29	83	improve	improve	VERB
ajst-26756	29	84	the	the	DET
ajst-26756	29	85	detection	detection	NOUN
ajst-26756	29	86	accuracy	accuracy	NOUN
ajst-26756	29	87	.	.	PUNCT
ajst-26756	30	1	at	at	ADP
ajst-26756	30	2	the	the	DET
ajst-26756	30	3	same	same	ADJ
ajst-26756	30	4	time	time	NOUN
ajst-26756	30	5	,	,	PUNCT
ajst-26756	30	6	due	due	ADP
ajst-26756	30	7	to	to	ADP
ajst-26756	30	8	the	the	DET
ajst-26756	30	9	complex	complex	ADJ
ajst-26756	30	10	background	background	NOUN
ajst-26756	30	11	of	of	ADP
ajst-26756	30	12	the	the	DET
ajst-26756	30	13	pavement	pavement	NOUN
ajst-26756	30	14	,	,	PUNCT
ajst-26756	30	15	the	the	DET
ajst-26756	30	16	attention	attention	NOUN
ajst-26756	30	17	mechanism	mechanism	NOUN
ajst-26756	30	18	can	can	AUX
ajst-26756	30	19	be	be	AUX
ajst-26756	30	20	considered	consider	VERB
ajst-26756	30	21	to	to	PART
ajst-26756	30	22	properly	properly	ADV
ajst-26756	30	23	suppress	suppress	VERB
ajst-26756	30	24	the	the	DET
ajst-26756	30	25	interference	interference	NOUN
ajst-26756	30	26	of	of	ADP
ajst-26756	30	27	the	the	DET
ajst-26756	30	28	background	background	NOUN
ajst-26756	30	29	,	,	PUNCT
ajst-26756	30	30	so	so	SCONJ
ajst-26756	30	31	that	that	SCONJ
ajst-26756	30	32	the	the	DET
ajst-26756	30	33	network	network	NOUN
ajst-26756	30	34	is	be	AUX
ajst-26756	30	35	more	more	ADV
ajst-26756	30	36	focused	focused	ADJ
ajst-26756	30	37	on	on	ADP
ajst-26756	30	38	the	the	DET
ajst-26756	30	39	detection	detection	NOUN
ajst-26756	30	40	of	of	ADP
ajst-26756	30	41	minor	minor	ADJ
ajst-26756	30	42	defects	defect	NOUN
ajst-26756	30	43	on	on	ADP
ajst-26756	30	44	the	the	DET
ajst-26756	30	45	pavement	pavement	NOUN
ajst-26756	30	46	,	,	PUNCT
ajst-26756	30	47	in	in	ADP
ajst-26756	30	48	view	view	NOUN
ajst-26756	30	49	of	of	ADP
ajst-26756	30	50	this	this	PRON
ajst-26756	30	51	,	,	PUNCT
ajst-26756	30	52	this	this	DET
ajst-26756	30	53	paper	paper	NOUN
ajst-26756	30	54	uses	use	VERB
ajst-26756	30	55	the	the	DET
ajst-26756	30	56	efficient	efficient	ADJ
ajst-26756	30	57	multi	multi	ADJ
ajst-26756	30	58	-	-	ADJ
ajst-26756	30	59	scale	scale	ADJ
ajst-26756	30	60	attention	attention	NOUN
ajst-26756	30	61	(	(	PUNCT
ajst-26756	30	62	ema	ema	PROPN
ajst-26756	30	63	)	)	PUNCT
ajst-26756	31	1	[	[	X
ajst-26756	31	2	11	11	NUM
ajst-26756	31	3	]	]	PUNCT
ajst-26756	31	4	as	as	ADP
ajst-26756	31	5	the	the	DET
ajst-26756	31	6	attention	attention	NOUN
ajst-26756	31	7	mechanism	mechanism	NOUN
ajst-26756	31	8	in	in	ADP
ajst-26756	31	9	this	this	DET
ajst-26756	31	10	paper	paper	NOUN
ajst-26756	31	11	.	.	PUNCT
ajst-26756	32	1	the	the	DET
ajst-26756	32	2	main	main	ADJ
ajst-26756	32	3	contributions	contribution	NOUN
ajst-26756	32	4	of	of	ADP
ajst-26756	32	5	this	this	DET
ajst-26756	32	6	paper	paper	NOUN
ajst-26756	32	7	are	be	AUX
ajst-26756	32	8	as	as	SCONJ
ajst-26756	32	9	follows	follow	VERB
ajst-26756	32	10	:	:	PUNCT
ajst-26756	32	11	(	(	PUNCT
ajst-26756	32	12	1	1	X
ajst-26756	32	13	)	)	PUNCT
ajst-26756	32	14	in	in	ADP
ajst-26756	32	15	the	the	DET
ajst-26756	32	16	backbone	backbone	NOUN
ajst-26756	32	17	network	network	NOUN
ajst-26756	32	18	of	of	ADP
ajst-26756	32	19	yolov8n	yolov8n	PROPN
ajst-26756	32	20	,	,	PUNCT
ajst-26756	32	21	the	the	DET
ajst-26756	32	22	original	original	ADJ
ajst-26756	32	23	conventional	conventional	ADJ
ajst-26756	32	24	convolutional	convolutional	ADJ
ajst-26756	32	25	layer	layer	NOUN
ajst-26756	32	26	with	with	ADP
ajst-26756	32	27	a	a	DET
ajst-26756	32	28	step	step	NOUN
ajst-26756	32	29	size	size	NOUN
ajst-26756	32	30	of	of	ADP
ajst-26756	32	31	2	2	NUM
ajst-26756	32	32	is	be	AUX
ajst-26756	32	33	replaced	replace	VERB
ajst-26756	32	34	with	with	ADP
ajst-26756	32	35	an	an	DET
ajst-26756	32	36	spd	spd	NOUN
ajst-26756	32	37	layer	layer	NOUN
ajst-26756	32	38	,	,	PUNCT
ajst-26756	32	39	followed	follow	VERB
ajst-26756	32	40	by	by	ADP
ajst-26756	32	41	a	a	DET
ajst-26756	32	42	stepless	stepless	NOUN
ajst-26756	32	43	convolutional	convolutional	ADJ
ajst-26756	32	44	layer	layer	NOUN
ajst-26756	32	45	,	,	PUNCT
ajst-26756	32	46	and	and	CCONJ
ajst-26756	32	47	finally	finally	ADV
ajst-26756	32	48	an	an	DET
ajst-26756	32	49	spd	spd	ADJ
ajst-26756	32	50	-	-	PUNCT
ajst-26756	32	51	conv	conv	ADJ
ajst-26756	32	52	is	be	AUX
ajst-26756	32	53	formed	form	VERB
ajst-26756	32	54	,	,	PUNCT
ajst-26756	32	55	which	which	PRON
ajst-26756	32	56	can	can	AUX
ajst-26756	32	57	better	well	ADV
ajst-26756	32	58	retain	retain	VERB
ajst-26756	32	59	the	the	DET
ajst-26756	32	60	detail	detail	NOUN
ajst-26756	32	61	information	information	NOUN
ajst-26756	32	62	in	in	ADP
ajst-26756	32	63	the	the	DET
ajst-26756	32	64	complex	complex	ADJ
ajst-26756	32	65	background	background	NOUN
ajst-26756	32	66	image	image	NOUN
ajst-26756	32	67	,	,	PUNCT
ajst-26756	32	68	and	and	CCONJ
ajst-26756	32	69	thus	thus	ADV
ajst-26756	32	70	efficiently	efficiently	ADV
ajst-26756	32	71	extract	extract	VERB
ajst-26756	32	72	the	the	DET
ajst-26756	32	73	feature	feature	NOUN
ajst-26756	32	74	information	information	NOUN
ajst-26756	32	75	of	of	ADP
ajst-26756	32	76	the	the	DET
ajst-26756	32	77	fine	fine	ADJ
ajst-26756	32	78	defects	defect	NOUN
ajst-26756	32	79	at	at	ADP
ajst-26756	32	80	multiple	multiple	ADJ
ajst-26756	32	81	scales	scale	NOUN
ajst-26756	32	82	.	.	PUNCT
ajst-26756	33	1	(	(	PUNCT
ajst-26756	33	2	2	2	X
ajst-26756	33	3	)	)	PUNCT
ajst-26756	33	4	the	the	DET
ajst-26756	33	5	ema	ema	PROPN
ajst-26756	33	6	attention	attention	NOUN
ajst-26756	33	7	module	module	NOUN
ajst-26756	33	8	was	be	AUX
ajst-26756	33	9	introduced	introduce	VERB
ajst-26756	33	10	to	to	PART
ajst-26756	33	11	enhance	enhance	VERB
ajst-26756	33	12	the	the	DET
ajst-26756	33	13	model	model	NOUN
ajst-26756	33	14	's	's	PART
ajst-26756	33	15	feature	feature	NOUN
ajst-26756	33	16	extraction	extraction	NOUN
ajst-26756	33	17	capability	capability	NOUN
ajst-26756	33	18	for	for	ADP
ajst-26756	33	19	pavement	pavement	NOUN
ajst-26756	33	20	defects	defect	NOUN
ajst-26756	33	21	in	in	ADP
ajst-26756	33	22	complex	complex	ADJ
ajst-26756	33	23	environments	environment	NOUN
ajst-26756	33	24	,	,	PUNCT
ajst-26756	33	25	allowing	allow	VERB
ajst-26756	33	26	the	the	DET
ajst-26756	33	27	network	network	NOUN
ajst-26756	33	28	to	to	PART
ajst-26756	33	29	focus	focus	VERB
ajst-26756	33	30	on	on	ADP
ajst-26756	33	31	the	the	DET
ajst-26756	33	32	pavement	pavement	NOUN
ajst-26756	33	33	defects	defect	NOUN
ajst-26756	33	34	,	,	PUNCT
ajst-26756	33	35	thus	thus	ADV
ajst-26756	33	36	reducing	reduce	VERB
ajst-26756	33	37	the	the	DET
ajst-26756	33	38	influence	influence	NOUN
ajst-26756	33	39	of	of	ADP
ajst-26756	33	40	the	the	DET
ajst-26756	33	41	background	background	NOUN
ajst-26756	33	42	,	,	PUNCT
ajst-26756	33	43	such	such	ADJ
ajst-26756	33	44	as	as	ADP
ajst-26756	33	45	the	the	DET
ajst-26756	33	46	shadows	shadow	NOUN
ajst-26756	33	47	of	of	ADP
ajst-26756	33	48	the	the	DET
ajst-26756	33	49	trees	tree	NOUN
ajst-26756	33	50	resembling	resemble	VERB
ajst-26756	33	51	the	the	DET
ajst-26756	33	52	shape	shape	NOUN
ajst-26756	33	53	of	of	ADP
ajst-26756	33	54	the	the	DET
ajst-26756	33	55	cracks	crack	NOUN
ajst-26756	33	56	.	.	PUNCT
ajst-26756	34	1	(	(	PUNCT
ajst-26756	34	2	3	3	X
ajst-26756	34	3	)	)	PUNCT
ajst-26756	34	4	mpdiou	mpdiou	NOUN
ajst-26756	34	5	is	be	AUX
ajst-26756	34	6	introduced	introduce	VERB
ajst-26756	34	7	as	as	ADP
ajst-26756	34	8	the	the	DET
ajst-26756	34	9	loss	loss	NOUN
ajst-26756	34	10	function	function	NOUN
ajst-26756	34	11	of	of	ADP
ajst-26756	34	12	the	the	DET
ajst-26756	34	13	network	network	NOUN
ajst-26756	34	14	to	to	PART
ajst-26756	34	15	improve	improve	VERB
ajst-26756	34	16	the	the	DET
ajst-26756	34	17	localization	localization	NOUN
ajst-26756	34	18	ability	ability	NOUN
ajst-26756	34	19	of	of	ADP
ajst-26756	34	20	the	the	DET
ajst-26756	34	21	model	model	NOUN
ajst-26756	34	22	by	by	ADP
ajst-26756	34	23	considering	consider	VERB
ajst-26756	34	24	the	the	DET
ajst-26756	34	25	minimum	minimum	ADJ
ajst-26756	34	26	vertical	vertical	ADJ
ajst-26756	34	27	distance	distance	NOUN
ajst-26756	34	28	between	between	ADP
ajst-26756	34	29	the	the	DET
ajst-26756	34	30	predicted	predict	VERB
ajst-26756	34	31	bounding	bounding	NOUN
ajst-26756	34	32	box	box	NOUN
ajst-26756	34	33	and	and	CCONJ
ajst-26756	34	34	the	the	DET
ajst-26756	34	35	real	real	ADJ
ajst-26756	34	36	bounding	bounding	NOUN
ajst-26756	34	37	box	box	NOUN
ajst-26756	34	38	,	,	PUNCT
ajst-26756	34	39	thus	thus	ADV
ajst-26756	34	40	improving	improve	VERB
ajst-26756	34	41	the	the	DET
ajst-26756	34	42	convergence	convergence	NOUN
ajst-26756	34	43	speed	speed	NOUN
ajst-26756	34	44	and	and	CCONJ
ajst-26756	34	45	accuracy	accuracy	NOUN
ajst-26756	34	46	of	of	ADP
ajst-26756	34	47	the	the	DET
ajst-26756	34	48	model	model	NOUN
ajst-26756	34	49	.	.	PUNCT
ajst-26756	35	1	2	2	X
ajst-26756	35	2	.	.	X
ajst-26756	35	3	method	method	NOUN
ajst-26756	35	4	in	in	ADP
ajst-26756	35	5	this	this	DET
ajst-26756	35	6	section	section	NOUN
ajst-26756	35	7	,	,	PUNCT
ajst-26756	35	8	the	the	DET
ajst-26756	35	9	overall	overall	ADJ
ajst-26756	35	10	network	network	NOUN
ajst-26756	35	11	structure	structure	NOUN
ajst-26756	35	12	of	of	ADP
ajst-26756	35	13	semyolov8n	semyolov8n	PROPN
ajst-26756	35	14	is	be	AUX
ajst-26756	35	15	first	first	ADV
ajst-26756	35	16	introduced	introduce	VERB
ajst-26756	35	17	,	,	PUNCT
ajst-26756	35	18	followed	follow	VERB
ajst-26756	35	19	by	by	ADP
ajst-26756	35	20	the	the	DET
ajst-26756	35	21	spd	spd	ADJ
ajst-26756	35	22	-	-	PUNCT
ajst-26756	35	23	conv	conv	NOUN
ajst-26756	35	24	module	module	NOUN
ajst-26756	35	25	,	,	PUNCT
ajst-26756	35	26	the	the	DET
ajst-26756	35	27	ema	ema	PROPN
ajst-26756	35	28	attention	attention	NOUN
ajst-26756	35	29	module	module	NOUN
ajst-26756	35	30	,	,	PUNCT
ajst-26756	35	31	and	and	CCONJ
ajst-26756	35	32	the	the	DET
ajst-26756	35	33	mpdiou	mpdiou	NOUN
ajst-26756	35	34	loss	loss	NOUN
ajst-26756	35	35	function	function	NOUN
ajst-26756	35	36	,	,	PUNCT
ajst-26756	35	37	respectively	respectively	ADV
ajst-26756	35	38	.	.	PUNCT
ajst-26756	36	1	2.1	2.1	NUM
ajst-26756	36	2	.	.	PUNCT
ajst-26756	36	3	structure	structure	NOUN
ajst-26756	36	4	of	of	ADP
ajst-26756	36	5	network	network	NOUN
ajst-26756	36	6	the	the	DET
ajst-26756	36	7	network	network	NOUN
ajst-26756	36	8	structure	structure	NOUN
ajst-26756	36	9	consists	consist	VERB
ajst-26756	36	10	of	of	ADP
ajst-26756	36	11	four	four	NUM
ajst-26756	36	12	basic	basic	ADJ
ajst-26756	36	13	components	component	NOUN
ajst-26756	36	14	:	:	PUNCT
ajst-26756	36	15	the	the	DET
ajst-26756	36	16	input	input	NOUN
ajst-26756	36	17	,	,	PUNCT
ajst-26756	36	18	the	the	DET
ajst-26756	36	19	backbone	backbone	NOUN
ajst-26756	36	20	network	network	NOUN
ajst-26756	36	21	,	,	PUNCT
ajst-26756	36	22	the	the	DET
ajst-26756	36	23	neck	neck	NOUN
ajst-26756	36	24	network	network	NOUN
ajst-26756	36	25	,	,	PUNCT
ajst-26756	36	26	and	and	CCONJ
ajst-26756	36	27	the	the	DET
ajst-26756	36	28	detection	detection	NOUN
ajst-26756	36	29	head	head	NOUN
ajst-26756	36	30	,	,	PUNCT
ajst-26756	36	31	as	as	SCONJ
ajst-26756	36	32	shown	show	VERB
ajst-26756	36	33	in	in	ADP
ajst-26756	36	34	figure	figure	NOUN
ajst-26756	36	35	1	1	NUM
ajst-26756	36	36	.	.	PUNCT
ajst-26756	37	1	the	the	DET
ajst-26756	37	2	inputs	input	NOUN
ajst-26756	37	3	are	be	AUX
ajst-26756	37	4	640×640×3	640×640×3	NUM
ajst-26756	37	5	sized	size	VERB
ajst-26756	37	6	images	image	NOUN
ajst-26756	37	7	which	which	PRON
ajst-26756	37	8	are	be	AUX
ajst-26756	37	9	preprocessed	preprocesse	VERB
ajst-26756	37	10	and	and	CCONJ
ajst-26756	37	11	fed	feed	VERB
ajst-26756	37	12	into	into	ADP
ajst-26756	37	13	the	the	DET
ajst-26756	37	14	backbone	backbone	NOUN
ajst-26756	37	15	network	network	NOUN
ajst-26756	37	16	.	.	PUNCT
ajst-26756	38	1	the	the	DET
ajst-26756	38	2	backbone	backbone	NOUN
ajst-26756	38	3	network	network	NOUN
ajst-26756	38	4	is	be	AUX
ajst-26756	38	5	similar	similar	ADJ
ajst-26756	38	6	to	to	ADP
ajst-26756	38	7	yolov8n	yolov8n	NOUN
ajst-26756	38	8	and	and	CCONJ
ajst-26756	38	9	utilizes	utilize	VERB
ajst-26756	38	10	spd	spd	ADJ
ajst-26756	38	11	-	-	PUNCT
ajst-26756	38	12	conv	conv	ADJ
ajst-26756	38	13	instead	instead	ADV
ajst-26756	38	14	of	of	ADP
ajst-26756	38	15	traditional	traditional	ADJ
ajst-26756	38	16	convolution	convolution	NOUN
ajst-26756	38	17	,	,	PUNCT
ajst-26756	38	18	which	which	PRON
ajst-26756	38	19	allows	allow	VERB
ajst-26756	38	20	for	for	ADP
ajst-26756	38	21	the	the	DET
ajst-26756	38	22	extraction	extraction	NOUN
ajst-26756	38	23	of	of	ADP
ajst-26756	38	24	more	more	ADV
ajst-26756	38	25	detailed	detailed	ADJ
ajst-26756	38	26	pavement	pavement	NOUN
ajst-26756	38	27	defect	defect	NOUN
ajst-26756	38	28	feature	feature	NOUN
ajst-26756	38	29	information	information	NOUN
ajst-26756	38	30	while	while	SCONJ
ajst-26756	38	31	reducing	reduce	VERB
ajst-26756	38	32	the	the	DET
ajst-26756	38	33	loss	loss	NOUN
ajst-26756	38	34	of	of	ADP
ajst-26756	38	35	subtle	subtle	ADJ
ajst-26756	38	36	pavement	pavement	NOUN
ajst-26756	38	37	defect	defect	NOUN
ajst-26756	38	38	features	feature	NOUN
ajst-26756	38	39	.	.	PUNCT
ajst-26756	39	1	the	the	DET
ajst-26756	39	2	fusion	fusion	NOUN
ajst-26756	39	3	network	network	NOUN
ajst-26756	39	4	retains	retain	VERB
ajst-26756	39	5	the	the	DET
ajst-26756	39	6	original	original	ADJ
ajst-26756	39	7	structure	structure	NOUN
ajst-26756	39	8	of	of	ADP
ajst-26756	39	9	yolov8n	yolov8n	NOUN
ajst-26756	39	10	,	,	PUNCT
ajst-26756	39	11	fuses	fuse	VERB
ajst-26756	39	12	the	the	DET
ajst-26756	39	13	shallow	shallow	ADJ
ajst-26756	39	14	,	,	PUNCT
ajst-26756	39	15	medium	medium	ADJ
ajst-26756	39	16	and	and	CCONJ
ajst-26756	39	17	deep	deep	ADJ
ajst-26756	39	18	pavement	pavement	NOUN
ajst-26756	39	19	defect	defect	NOUN
ajst-26756	39	20	feature	feature	NOUN
ajst-26756	39	21	information	information	NOUN
ajst-26756	39	22	extracted	extract	VERB
ajst-26756	39	23	from	from	ADP
ajst-26756	39	24	the	the	DET
ajst-26756	39	25	backbone	backbone	NOUN
ajst-26756	39	26	network	network	NOUN
ajst-26756	39	27	,	,	PUNCT
ajst-26756	39	28	and	and	CCONJ
ajst-26756	39	29	adds	add	VERB
ajst-26756	39	30	the	the	DET
ajst-26756	39	31	ema	ema	PROPN
ajst-26756	39	32	attention	attention	NOUN
ajst-26756	39	33	mechanism	mechanism	NOUN
ajst-26756	39	34	in	in	ADP
ajst-26756	39	35	the	the	DET
ajst-26756	39	36	small	small	ADJ
ajst-26756	39	37	target	target	NOUN
ajst-26756	39	38	branch	branch	NOUN
ajst-26756	39	39	to	to	PART
ajst-26756	39	40	make	make	VERB
ajst-26756	39	41	the	the	DET
ajst-26756	39	42	network	network	NOUN
ajst-26756	39	43	more	more	ADV
ajst-26756	39	44	focused	focused	ADJ
ajst-26756	39	45	on	on	ADP
ajst-26756	39	46	subtle	subtle	ADJ
ajst-26756	39	47	defects	defect	NOUN
ajst-26756	39	48	.	.	PUNCT
ajst-26756	40	1	finally	finally	ADV
ajst-26756	40	2	,	,	PUNCT
ajst-26756	40	3	the	the	DET
ajst-26756	40	4	three	three	NUM
ajst-26756	40	5	feature	feature	NOUN
ajst-26756	40	6	layers	layer	NOUN
ajst-26756	40	7	output	output	VERB
ajst-26756	40	8	from	from	ADP
ajst-26756	40	9	the	the	DET
ajst-26756	40	10	fusion	fusion	NOUN
ajst-26756	40	11	network	network	NOUN
ajst-26756	40	12	are	be	AUX
ajst-26756	40	13	further	far	ADV
ajst-26756	40	14	trained	train	VERB
ajst-26756	40	15	in	in	ADP
ajst-26756	40	16	the	the	DET
ajst-26756	40	17	detection	detection	NOUN
ajst-26756	40	18	head	head	NOUN
ajst-26756	40	19	network	network	NOUN
ajst-26756	40	20	,	,	PUNCT
ajst-26756	40	21	and	and	CCONJ
ajst-26756	40	22	these	these	DET
ajst-26756	40	23	outputs	output	NOUN
ajst-26756	40	24	are	be	AUX
ajst-26756	40	25	integrated	integrate	VERB
ajst-26756	40	26	to	to	PART
ajst-26756	40	27	achieve	achieve	VERB
ajst-26756	40	28	multi	multi	ADJ
ajst-26756	40	29	-	-	ADJ
ajst-26756	40	30	scale	scale	ADJ
ajst-26756	40	31	detection	detection	NOUN
ajst-26756	40	32	of	of	ADP
ajst-26756	40	33	targets	target	NOUN
ajst-26756	40	34	,	,	PUNCT
ajst-26756	40	35	utilizing	utilize	VERB
ajst-26756	40	36	the	the	DET
ajst-26756	40	37	corresponding	correspond	VERB
ajst-26756	40	38	detection	detection	NOUN
ajst-26756	40	39	heads	head	NOUN
ajst-26756	40	40	according	accord	VERB
ajst-26756	40	41	to	to	ADP
ajst-26756	40	42	different	different	ADJ
ajst-26756	40	43	defect	defect	NOUN
ajst-26756	40	44	sizes	size	NOUN
ajst-26756	40	45	.	.	PUNCT
ajst-26756	41	1	figure	figure	NOUN
ajst-26756	41	2	1	1	NUM
ajst-26756	41	3	.	.	PUNCT
ajst-26756	42	1	structure	structure	NOUN
ajst-26756	42	2	of	of	ADP
ajst-26756	42	3	sem	sem	PROPN
ajst-26756	42	4	-	-	PUNCT
ajst-26756	42	5	yolov8n	yolov8n	PROPN
ajst-26756	42	6	2.2	2.2	NUM
ajst-26756	42	7	.	.	PUNCT
ajst-26756	43	1	structure	structure	NOUN
ajst-26756	43	2	of	of	ADP
ajst-26756	43	3	spd	spd	NOUN
ajst-26756	43	4	-	-	PUNCT
ajst-26756	43	5	conv	conv	ADJ
ajst-26756	43	6	in	in	ADP
ajst-26756	43	7	this	this	DET
ajst-26756	43	8	paper	paper	NOUN
ajst-26756	43	9	,	,	PUNCT
ajst-26756	43	10	the	the	DET
ajst-26756	43	11	spd	spd	ADJ
ajst-26756	43	12	-	-	PUNCT
ajst-26756	43	13	conv	conv	ADJ
ajst-26756	43	14	structure	structure	NOUN
ajst-26756	43	15	is	be	AUX
ajst-26756	43	16	used	use	VERB
ajst-26756	43	17	to	to	PART
ajst-26756	43	18	replace	replace	VERB
ajst-26756	43	19	all	all	DET
ajst-26756	43	20	the	the	DET
ajst-26756	43	21	3	3	NUM
ajst-26756	43	22	3	3	NUM
ajst-26756	43	23	convolutional	convolutional	ADJ
ajst-26756	43	24	layers	layer	NOUN
ajst-26756	43	25	in	in	ADP
ajst-26756	43	26	the	the	DET
ajst-26756	43	27	yolov8n	yolov8n	PROPN
ajst-26756	43	28	model	model	NOUN
ajst-26756	43	29	,	,	PUNCT
ajst-26756	43	30	which	which	PRON
ajst-26756	43	31	prevents	prevent	VERB
ajst-26756	43	32	the	the	DET
ajst-26756	43	33	loss	loss	NOUN
ajst-26756	43	34	of	of	ADP
ajst-26756	43	35	fine	fine	ADV
ajst-26756	43	36	-	-	PUNCT
ajst-26756	43	37	grained	grain	VERB
ajst-26756	43	38	information	information	NOUN
ajst-26756	43	39	of	of	ADP
ajst-26756	43	40	the	the	DET
ajst-26756	43	41	91	91	NUM
ajst-26756	43	42	small	small	ADJ
ajst-26756	43	43	targets	target	NOUN
ajst-26756	43	44	in	in	ADP
ajst-26756	43	45	the	the	DET
ajst-26756	43	46	image	image	NOUN
ajst-26756	43	47	processing	processing	NOUN
ajst-26756	43	48	process	process	NOUN
ajst-26756	43	49	,	,	PUNCT
ajst-26756	43	50	especially	especially	ADV
ajst-26756	43	51	in	in	ADP
ajst-26756	43	52	the	the	DET
ajst-26756	43	53	downsampling	downsample	VERB
ajst-26756	43	54	process	process	NOUN
ajst-26756	43	55	.	.	PUNCT
ajst-26756	44	1	the	the	DET
ajst-26756	44	2	spd	spd	ADJ
ajst-26756	44	3	-	-	PUNCT
ajst-26756	44	4	conv	conv	ADJ
ajst-26756	44	5	consists	consist	NOUN
ajst-26756	44	6	of	of	ADP
ajst-26756	44	7	two	two	NUM
ajst-26756	44	8	main	main	ADJ
ajst-26756	44	9	convolutional	convolutional	ADJ
ajst-26756	44	10	operations	operation	NOUN
ajst-26756	44	11	:	:	PUNCT
ajst-26756	44	12	the	the	DET
ajst-26756	44	13	space	space	NOUN
ajst-26756	44	14	-	-	PUNCT
ajst-26756	44	15	to	to	ADP
ajst-26756	44	16	-	-	PUNCT
ajst-26756	44	17	depth	depth	NOUN
ajst-26756	44	18	(	(	PUNCT
ajst-26756	44	19	spd	spd	NOUN
ajst-26756	44	20	)	)	PUNCT
ajst-26756	44	21	and	and	CCONJ
ajst-26756	44	22	the	the	DET
ajst-26756	44	23	non	non	ADJ
ajst-26756	44	24	-	-	ADJ
ajst-26756	44	25	spanned	spanned	ADJ
ajst-26756	44	26	rows	row	NOUN
ajst-26756	44	27	of	of	ADP
ajst-26756	44	28	convolutional	convolutional	ADJ
ajst-26756	44	29	layers	layer	NOUN
ajst-26756	44	30	as	as	SCONJ
ajst-26756	44	31	shown	show	VERB
ajst-26756	44	32	in	in	ADP
ajst-26756	44	33	fig.2	fig.2	PROPN
ajst-26756	44	34	,	,	PUNCT
ajst-26756	44	35	and	and	CCONJ
ajst-26756	44	36	the	the	DET
ajst-26756	44	37	feature	feature	NOUN
ajst-26756	44	38	mapping	mapping	NOUN
ajst-26756	44	39	is	be	AUX
ajst-26756	44	40	processed	process	VERB
ajst-26756	44	41	by	by	ADP
ajst-26756	44	42	the	the	DET
ajst-26756	44	43	spd	spd	ADJ
ajst-26756	44	44	-	-	PUNCT
ajst-26756	44	45	conv	conv	NOUN
ajst-26756	44	46	module	module	NOUN
ajst-26756	44	47	.	.	PUNCT
ajst-26756	45	1	firstly	firstly	ADV
ajst-26756	45	2	,	,	PUNCT
ajst-26756	45	3	the	the	DET
ajst-26756	45	4	input	input	NOUN
ajst-26756	45	5	feature	feature	NOUN
ajst-26756	45	6	maps	map	NOUN
ajst-26756	45	7	are	be	AUX
ajst-26756	45	8	preprocessed	preprocesse	VERB
ajst-26756	45	9	from	from	ADP
ajst-26756	45	10	space	space	NOUN
ajst-26756	45	11	to	to	ADP
ajst-26756	45	12	depth	depth	NOUN
ajst-26756	45	13	,	,	PUNCT
ajst-26756	45	14	and	and	CCONJ
ajst-26756	45	15	the	the	DET
ajst-26756	45	16	input	input	NOUN
ajst-26756	45	17	feature	feature	NOUN
ajst-26756	45	18	maps	map	NOUN
ajst-26756	45	19	are	be	AUX
ajst-26756	45	20	divided	divide	VERB
ajst-26756	45	21	into	into	ADP
ajst-26756	45	22	four	four	NUM
ajst-26756	45	23	classes	class	NOUN
ajst-26756	45	24	in	in	ADP
ajst-26756	45	25	the	the	DET
ajst-26756	45	26	spatial	spatial	ADJ
ajst-26756	45	27	dimension	dimension	NOUN
ajst-26756	45	28	,	,	PUNCT
ajst-26756	45	29	and	and	CCONJ
ajst-26756	45	30	the	the	DET
ajst-26756	45	31	four	four	NUM
ajst-26756	45	32	vectors	vector	NOUN
ajst-26756	45	33	are	be	AUX
ajst-26756	45	34	spliced	splice	VERB
ajst-26756	45	35	in	in	ADP
ajst-26756	45	36	the	the	DET
ajst-26756	45	37	spatial	spatial	ADJ
ajst-26756	45	38	dimension	dimension	NOUN
ajst-26756	45	39	.	.	PUNCT
ajst-26756	46	1	then	then	ADV
ajst-26756	46	2	the	the	DET
ajst-26756	46	3	preprocessed	preprocesse	VERB
ajst-26756	46	4	feature	feature	NOUN
ajst-26756	46	5	maps	map	NOUN
ajst-26756	46	6	are	be	AUX
ajst-26756	46	7	subjected	subject	VERB
ajst-26756	46	8	to	to	ADP
ajst-26756	46	9	standard	standard	ADJ
ajst-26756	46	10	convolution	convolution	NOUN
ajst-26756	46	11	to	to	PART
ajst-26756	46	12	generate	generate	VERB
ajst-26756	46	13	four	four	NUM
ajst-26756	46	14	feature	feature	NOUN
ajst-26756	46	15	maps	map	NOUN
ajst-26756	46	16	of	of	ADP
ajst-26756	46	17	size	size	NOUN
ajst-26756	46	18	12	12	NUM
ajst-26756	46	19	2	2	NUM
ajst-26756	46	20	s	s	NOUN
ajst-26756	46	21	s	s	NOUN
ajst-26756	46	22	c	c	NOUN
ajst-26756	46	23			NOUN
ajst-26756	46	24	,	,	PUNCT
ajst-26756	46	25	which	which	PRON
ajst-26756	46	26	are	be	AUX
ajst-26756	46	27	spliced	splice	VERB
ajst-26756	46	28	along	along	ADP
ajst-26756	46	29	the	the	DET
ajst-26756	46	30	1c	1c	NUM
ajst-26756	46	31	dimension	dimension	NOUN
ajst-26756	46	32	to	to	PART
ajst-26756	46	33	obtain	obtain	VERB
ajst-26756	46	34	a	a	DET
ajst-26756	46	35	feature	feature	NOUN
ajst-26756	46	36	map	map	NOUN
ajst-26756	46	37	of	of	ADP
ajst-26756	46	38	size	size	NOUN
ajst-26756	46	39	14	14	NUM
ajst-26756	46	40	2	2	NUM
ajst-26756	46	41	2	2	NUM
ajst-26756	46	42	s	s	NOUN
ajst-26756	46	43	s	s	NOUN
ajst-26756	46	44	c	c	NOUN
ajst-26756	46	45			NOUN
ajst-26756	46	46	,	,	PUNCT
ajst-26756	46	47	and	and	CCONJ
ajst-26756	46	48	finally	finally	ADV
ajst-26756	46	49	go	go	VERB
ajst-26756	46	50	through	through	ADP
ajst-26756	46	51	a	a	DET
ajst-26756	46	52	non	non	ADJ
ajst-26756	46	53	-	-	ADJ
ajst-26756	46	54	spanning	spanning	ADJ
ajst-26756	46	55	convolutional	convolutional	ADJ
ajst-26756	46	56	layer	layer	NOUN
ajst-26756	46	57	to	to	PART
ajst-26756	46	58	obtain	obtain	VERB
ajst-26756	46	59	22	22	NUM
ajst-26756	46	60	2	2	NUM
ajst-26756	46	61	s	s	NOUN
ajst-26756	46	62	s	s	NOUN
ajst-26756	46	63	c	c	NOUN
ajst-26756	46	64			NOUN
ajst-26756	46	65	.	.	PUNCT
ajst-26756	47	1	spd	spd	ADJ
ajst-26756	47	2	-	-	PUNCT
ajst-26756	47	3	conv	conv	ADJ
ajst-26756	47	4	is	be	AUX
ajst-26756	47	5	utilized	utilize	VERB
ajst-26756	47	6	instead	instead	ADV
ajst-26756	47	7	of	of	ADP
ajst-26756	47	8	traditional	traditional	ADJ
ajst-26756	47	9	step	step	NOUN
ajst-26756	47	10	convolution	convolution	NOUN
ajst-26756	47	11	to	to	PART
ajst-26756	47	12	mitigate	mitigate	VERB
ajst-26756	47	13	the	the	DET
ajst-26756	47	14	loss	loss	NOUN
ajst-26756	47	15	of	of	ADP
ajst-26756	47	16	detailed	detailed	ADJ
ajst-26756	47	17	information	information	NOUN
ajst-26756	47	18	that	that	PRON
ajst-26756	47	19	occurs	occur	VERB
ajst-26756	47	20	when	when	SCONJ
ajst-26756	47	21	only	only	ADV
ajst-26756	47	22	a	a	DET
ajst-26756	47	23	small	small	ADJ
ajst-26756	47	24	fraction	fraction	NOUN
ajst-26756	47	25	of	of	ADP
ajst-26756	47	26	pixels	pixel	NOUN
ajst-26756	47	27	is	be	AUX
ajst-26756	47	28	occupied	occupy	VERB
ajst-26756	47	29	during	during	ADP
ajst-26756	47	30	small	small	ADJ
ajst-26756	47	31	target	target	NOUN
ajst-26756	47	32	detection	detection	NOUN
ajst-26756	47	33	.	.	PUNCT
ajst-26756	48	1	spd	spd	ADJ
ajst-26756	48	2	-	-	PUNCT
ajst-26756	48	3	conv	conv	NOUN
ajst-26756	48	4	enhances	enhance	VERB
ajst-26756	48	5	the	the	DET
ajst-26756	48	6	model	model	NOUN
ajst-26756	48	7	's	's	PART
ajst-26756	48	8	ability	ability	NOUN
ajst-26756	48	9	to	to	PART
ajst-26756	48	10	process	process	VERB
ajst-26756	48	11	spatial	spatial	ADJ
ajst-26756	48	12	information	information	NOUN
ajst-26756	48	13	,	,	PUNCT
ajst-26756	48	14	facilitating	facilitate	VERB
ajst-26756	48	15	the	the	DET
ajst-26756	48	16	differentiation	differentiation	NOUN
ajst-26756	48	17	of	of	ADP
ajst-26756	48	18	individual	individual	ADJ
ajst-26756	48	19	spermatozoa	spermatozoon	NOUN
ajst-26756	48	20	in	in	ADP
ajst-26756	48	21	dense	dense	ADJ
ajst-26756	48	22	clusters	cluster	NOUN
ajst-26756	48	23	while	while	SCONJ
ajst-26756	48	24	it	it	PRON
ajst-26756	48	25	deepens	deepen	VERB
ajst-26756	48	26	the	the	DET
ajst-26756	48	27	feature	feature	NOUN
ajst-26756	48	28	mapping	mapping	NOUN
ajst-26756	48	29	so	so	SCONJ
ajst-26756	48	30	that	that	SCONJ
ajst-26756	48	31	the	the	DET
ajst-26756	48	32	model	model	NOUN
ajst-26756	48	33	is	be	AUX
ajst-26756	48	34	better	well	ADJ
ajst-26756	48	35	able	able	ADJ
ajst-26756	48	36	to	to	PART
ajst-26756	48	37	account	account	VERB
ajst-26756	48	38	for	for	ADP
ajst-26756	48	39	complex	complex	ADJ
ajst-26756	48	40	backgrounds	background	NOUN
ajst-26756	48	41	and	and	CCONJ
ajst-26756	48	42	dense	dense	ADJ
ajst-26756	48	43	objects	object	NOUN
ajst-26756	48	44	.	.	PUNCT
ajst-26756	49	1	thus	thus	ADV
ajst-26756	49	2	utilizing	utilize	VERB
ajst-26756	49	3	spd	spd	ADJ
ajst-26756	49	4	-	-	PUNCT
ajst-26756	49	5	conv	conv	ADJ
ajst-26756	49	6	can	can	AUX
ajst-26756	49	7	significantly	significantly	ADV
ajst-26756	49	8	improve	improve	VERB
ajst-26756	49	9	the	the	DET
ajst-26756	49	10	accuracy	accuracy	NOUN
ajst-26756	49	11	of	of	ADP
ajst-26756	49	12	small	small	ADJ
ajst-26756	49	13	target	target	NOUN
ajst-26756	49	14	detection	detection	NOUN
ajst-26756	49	15	while	while	SCONJ
ajst-26756	49	16	retaining	retain	VERB
ajst-26756	49	17	more	more	ADV
ajst-26756	49	18	detailed	detailed	ADJ
ajst-26756	49	19	information	information	NOUN
ajst-26756	49	20	.	.	PUNCT
ajst-26756	50	1	figure	figure	NOUN
ajst-26756	50	2	2	2	NUM
ajst-26756	50	3	.	.	PUNCT
ajst-26756	51	1	structure	structure	NOUN
ajst-26756	51	2	of	of	ADP
ajst-26756	51	3	spd	spd	ADJ
ajst-26756	51	4	-	-	PUNCT
ajst-26756	51	5	conv	conv	ADJ
ajst-26756	51	6	2.3	2.3	NUM
ajst-26756	51	7	.	.	PUNCT
ajst-26756	52	1	structure	structure	NOUN
ajst-26756	52	2	of	of	ADP
ajst-26756	52	3	attention	attention	NOUN
ajst-26756	52	4	given	give	VERB
ajst-26756	52	5	the	the	DET
ajst-26756	52	6	differences	difference	NOUN
ajst-26756	52	7	in	in	ADP
ajst-26756	52	8	defect	defect	NOUN
ajst-26756	52	9	scales	scale	NOUN
ajst-26756	52	10	and	and	CCONJ
ajst-26756	52	11	shapes	shape	NOUN
ajst-26756	52	12	,	,	PUNCT
ajst-26756	52	13	it	it	PRON
ajst-26756	52	14	is	be	AUX
ajst-26756	52	15	particularly	particularly	ADV
ajst-26756	52	16	important	important	ADJ
ajst-26756	52	17	to	to	PART
ajst-26756	52	18	further	far	ADV
ajst-26756	52	19	improve	improve	VERB
ajst-26756	52	20	the	the	DET
ajst-26756	52	21	multi	multi	ADJ
ajst-26756	52	22	-	-	ADJ
ajst-26756	52	23	scale	scale	ADJ
ajst-26756	52	24	feature	feature	NOUN
ajst-26756	52	25	extraction	extraction	NOUN
ajst-26756	52	26	capability	capability	NOUN
ajst-26756	52	27	of	of	ADP
ajst-26756	52	28	the	the	DET
ajst-26756	52	29	network	network	NOUN
ajst-26756	52	30	.	.	PUNCT
ajst-26756	53	1	meanwhile	meanwhile	ADV
ajst-26756	53	2	,	,	PUNCT
ajst-26756	53	3	the	the	DET
ajst-26756	53	4	complex	complex	ADJ
ajst-26756	53	5	background	background	NOUN
ajst-26756	53	6	of	of	ADP
ajst-26756	53	7	the	the	DET
ajst-26756	53	8	pavement	pavement	NOUN
ajst-26756	53	9	is	be	AUX
ajst-26756	53	10	prone	prone	ADJ
ajst-26756	53	11	to	to	PART
ajst-26756	53	12	have	have	VERB
ajst-26756	53	13	an	an	DET
ajst-26756	53	14	impact	impact	NOUN
ajst-26756	53	15	on	on	ADP
ajst-26756	53	16	the	the	DET
ajst-26756	53	17	defect	defect	NOUN
ajst-26756	53	18	detection	detection	NOUN
ajst-26756	53	19	,	,	PUNCT
ajst-26756	53	20	so	so	SCONJ
ajst-26756	53	21	this	this	DET
ajst-26756	53	22	paper	paper	NOUN
ajst-26756	53	23	introduces	introduce	VERB
ajst-26756	53	24	the	the	DET
ajst-26756	53	25	ema	ema	PROPN
ajst-26756	53	26	attention	attention	NOUN
ajst-26756	53	27	mechanism	mechanism	NOUN
ajst-26756	53	28	to	to	PART
ajst-26756	53	29	make	make	VERB
ajst-26756	53	30	the	the	DET
ajst-26756	53	31	network	network	NOUN
ajst-26756	53	32	more	more	ADV
ajst-26756	53	33	focused	focused	ADJ
ajst-26756	53	34	on	on	ADP
ajst-26756	53	35	the	the	DET
ajst-26756	53	36	fine	fine	ADJ
ajst-26756	53	37	defects	defect	NOUN
ajst-26756	53	38	of	of	ADP
ajst-26756	53	39	the	the	DET
ajst-26756	53	40	pavement	pavement	NOUN
ajst-26756	53	41	.	.	PUNCT
ajst-26756	54	1	the	the	DET
ajst-26756	54	2	ema	ema	PROPN
ajst-26756	54	3	attention	attention	NOUN
ajst-26756	54	4	mechanism	mechanism	NOUN
ajst-26756	54	5	is	be	AUX
ajst-26756	54	6	an	an	DET
ajst-26756	54	7	efficient	efficient	ADJ
ajst-26756	54	8	multiscale	multiscale	ADJ
ajst-26756	54	9	attention	attention	NOUN
ajst-26756	54	10	mechanism	mechanism	NOUN
ajst-26756	54	11	based	base	VERB
ajst-26756	54	12	on	on	ADP
ajst-26756	54	13	cross	cross	ADJ
ajst-26756	54	14	-	-	ADJ
ajst-26756	54	15	space	space	ADJ
ajst-26756	54	16	learning	learning	NOUN
ajst-26756	54	17	proposed	propose	VERB
ajst-26756	54	18	by	by	ADP
ajst-26756	54	19	ouyang	ouyang	PROPN
ajst-26756	54	20	et	et	PROPN
ajst-26756	54	21	al	al	PROPN
ajst-26756	55	1	[	[	X
ajst-26756	55	2	11	11	NUM
ajst-26756	55	3	]	]	PUNCT
ajst-26756	55	4	in	in	ADP
ajst-26756	55	5	2023	2023	NUM
ajst-26756	55	6	,	,	PUNCT
ajst-26756	55	7	which	which	PRON
ajst-26756	55	8	prevents	prevent	VERB
ajst-26756	55	9	the	the	DET
ajst-26756	55	10	loss	loss	NOUN
ajst-26756	55	11	of	of	ADP
ajst-26756	55	12	channel	channel	NOUN
ajst-26756	55	13	feature	feature	NOUN
ajst-26756	55	14	information	information	NOUN
ajst-26756	55	15	and	and	CCONJ
ajst-26756	55	16	reduces	reduce	VERB
ajst-26756	55	17	computational	computational	ADJ
ajst-26756	55	18	overheads	overhead	NOUN
ajst-26756	55	19	by	by	ADP
ajst-26756	55	20	reshaping	reshape	VERB
ajst-26756	55	21	part	part	NOUN
ajst-26756	55	22	of	of	ADP
ajst-26756	55	23	the	the	DET
ajst-26756	55	24	channels	channel	NOUN
ajst-26756	55	25	into	into	ADP
ajst-26756	55	26	bulk	bulk	ADJ
ajst-26756	55	27	dimensions	dimension	NOUN
ajst-26756	55	28	and	and	CCONJ
ajst-26756	55	29	grouping	group	VERB
ajst-26756	55	30	the	the	DET
ajst-26756	55	31	channel	channel	NOUN
ajst-26756	55	32	dimensions	dimension	NOUN
ajst-26756	55	33	without	without	ADP
ajst-26756	55	34	the	the	DET
ajst-26756	55	35	need	need	NOUN
ajst-26756	55	36	of	of	ADP
ajst-26756	55	37	a	a	DET
ajst-26756	55	38	dimensionality	dimensionality	NOUN
ajst-26756	55	39	reduction	reduction	NOUN
ajst-26756	55	40	operation	operation	NOUN
ajst-26756	55	41	,	,	PUNCT
ajst-26756	55	42	which	which	PRON
ajst-26756	55	43	can	can	AUX
ajst-26756	55	44	prevent	prevent	VERB
ajst-26756	55	45	the	the	DET
ajst-26756	55	46	loss	loss	NOUN
ajst-26756	55	47	of	of	ADP
ajst-26756	55	48	channel	channel	NOUN
ajst-26756	55	49	feature	feature	NOUN
ajst-26756	55	50	information	information	NOUN
ajst-26756	55	51	and	and	CCONJ
ajst-26756	55	52	reduce	reduce	VERB
ajst-26756	55	53	the	the	DET
ajst-26756	55	54	computational	computational	ADJ
ajst-26756	55	55	overhead	overhead	NOUN
ajst-26756	55	56	with	with	ADP
ajst-26756	55	57	high	high	ADJ
ajst-26756	55	58	accuracy	accuracy	NOUN
ajst-26756	55	59	and	and	CCONJ
ajst-26756	55	60	small	small	ADJ
ajst-26756	55	61	number	number	NOUN
ajst-26756	55	62	of	of	ADP
ajst-26756	55	63	parameters	parameter	NOUN
ajst-26756	55	64	[	[	X
ajst-26756	55	65	12].the	12].the	NUM
ajst-26756	55	66	structure	structure	NOUN
ajst-26756	55	67	of	of	ADP
ajst-26756	55	68	ema	ema	PROPN
ajst-26756	55	69	attention	attention	NOUN
ajst-26756	55	70	mechanism	mechanism	NOUN
ajst-26756	55	71	is	be	AUX
ajst-26756	55	72	shown	show	VERB
ajst-26756	55	73	in	in	ADP
ajst-26756	55	74	fig	fig	NOUN
ajst-26756	55	75	.	.	PUNCT
ajst-26756	56	1	3	3	X
ajst-26756	56	2	.	.	PUNCT
ajst-26756	57	1	the	the	DET
ajst-26756	57	2	workflow	workflow	NOUN
ajst-26756	57	3	is	be	AUX
ajst-26756	57	4	as	as	SCONJ
ajst-26756	57	5	follows	follow	VERB
ajst-26756	57	6	:	:	PUNCT
ajst-26756	57	7	first	first	ADV
ajst-26756	57	8	,	,	PUNCT
ajst-26756	57	9	for	for	ADP
ajst-26756	57	10	any	any	DET
ajst-26756	57	11	input	input	NOUN
ajst-26756	58	1	c	c	NOUN
ajst-26756	58	2	h	h	NOUN
ajst-26756	58	3	wx	wx	NOUN
ajst-26756	58	4	r	r	NOUN
ajst-26756	58	5			NOUN
ajst-26756	58	6			NOUN
ajst-26756	58	7	,	,	PUNCT
ajst-26756	58	8	ema	ema	PROPN
ajst-26756	58	9	slices	slice	VERB
ajst-26756	58	10	it	it	PRON
ajst-26756	58	11	into	into	ADP
ajst-26756	58	12	g	g	PROPN
ajst-26756	58	13	subfeatures	subfeature	NOUN
ajst-26756	58	14	,	,	PUNCT
ajst-26756	58	15	such	such	ADJ
ajst-26756	58	16	as	as	ADP
ajst-26756	58	17	//	//	NUM
ajst-26756	58	18	0	0	NUM
ajst-26756	58	19	1	1	NUM
ajst-26756	58	20	[	[	PUNCT
ajst-26756	58	21	,	,	PUNCT
ajst-26756	58	22	,	,	PUNCT
ajst-26756	58	23	...	...	PUNCT
ajst-26756	58	24	,	,	PUNCT
ajst-26756	58	25	]	]	PUNCT
ajst-26756	58	26	,	,	PUNCT
ajst-26756	58	27	c	c	PROPN
ajst-26756	58	28	g	g	PROPN
ajst-26756	58	29	h	h	PROPN
ajst-26756	59	1	w	w	PROPN
ajst-26756	59	2	i	i	INTJ
ajst-26756	59	3	gx	gx	NOUN
ajst-26756	59	4	x	x	PUNCT
ajst-26756	59	5	x	x	PUNCT
ajst-26756	59	6	x	x	PUNCT
ajst-26756	59	7	x	x	SYM
ajst-26756	59	8	r	r	NOUN
ajst-26756	59	9			NOUN
ajst-26756	59	10			PROPN
ajst-26756	59	11			ADJ
ajst-26756	59	12			PROPN
ajst-26756	59	13	,	,	PUNCT
ajst-26756	59	14	in	in	ADP
ajst-26756	59	15	the	the	DET
ajst-26756	59	16	channel	channel	NOUN
ajst-26756	59	17	dimension	dimension	NOUN
ajst-26756	59	18	to	to	PART
ajst-26756	59	19	obtain	obtain	VERB
ajst-26756	59	20	different	different	ADJ
ajst-26756	59	21	semantics	semantic	NOUN
ajst-26756	59	22	.	.	PUNCT
ajst-26756	60	1	next	next	ADV
ajst-26756	60	2	,	,	PUNCT
ajst-26756	60	3	ema	ema	PROPN
ajst-26756	60	4	uses	use	VERB
ajst-26756	60	5	3	3	NUM
ajst-26756	60	6	routes	route	NOUN
ajst-26756	60	7	to	to	PART
ajst-26756	60	8	extract	extract	VERB
ajst-26756	60	9	the	the	DET
ajst-26756	60	10	attention	attention	NOUN
ajst-26756	60	11	weight	weight	NOUN
ajst-26756	60	12	descriptors	descriptor	NOUN
ajst-26756	60	13	of	of	ADP
ajst-26756	60	14	the	the	DET
ajst-26756	60	15	grouped	group	VERB
ajst-26756	60	16	feature	feature	NOUN
ajst-26756	60	17	graphs	graph	NOUN
ajst-26756	60	18	respectively	respectively	ADV
ajst-26756	60	19	[	[	X
ajst-26756	60	20	13	13	NUM
ajst-26756	60	21	]	]	PUNCT
ajst-26756	60	22	.	.	PUNCT
ajst-26756	61	1	figure	figure	NOUN
ajst-26756	61	2	3	3	NUM
ajst-26756	61	3	.	.	PUNCT
ajst-26756	61	4	structure	structure	NOUN
ajst-26756	61	5	of	of	ADP
ajst-26756	61	6	ema	ema	PROPN
ajst-26756	61	7	92	92	NUM
ajst-26756	61	8	2.4	2.4	NUM
ajst-26756	61	9	.	.	PUNCT
ajst-26756	62	1	loss	loss	NOUN
ajst-26756	62	2	function	function	NOUN
ajst-26756	62	3	while	while	SCONJ
ajst-26756	62	4	the	the	DET
ajst-26756	62	5	complete	complete	ADJ
ajst-26756	62	6	intersection	intersection	NOUN
ajst-26756	62	7	over	over	ADP
ajst-26756	62	8	union	union	NOUN
ajst-26756	62	9	(	(	PUNCT
ajst-26756	62	10	ciou	ciou	NOUN
ajst-26756	62	11	)	)	PUNCT
ajst-26756	62	12	loss	loss	NOUN
ajst-26756	62	13	function	function	NOUN
ajst-26756	62	14	used	use	VERB
ajst-26756	62	15	by	by	ADP
ajst-26756	62	16	yolov8n	yolov8n	PROPN
ajst-26756	62	17	,	,	PUNCT
ajst-26756	62	18	sem	sem	NOUN
ajst-26756	62	19	-	-	PUNCT
ajst-26756	62	20	yolov8n	yolov8n	PROPN
ajst-26756	62	21	uses	use	VERB
ajst-26756	62	22	the	the	DET
ajst-26756	62	23	minimum	minimum	ADJ
ajst-26756	62	24	point	point	NOUN
ajst-26756	62	25	distance	distance	NOUN
ajst-26756	62	26	intersection	intersection	NOUN
ajst-26756	62	27	over	over	ADP
ajst-26756	62	28	union	union	NOUN
ajst-26756	62	29	(	(	PUNCT
ajst-26756	62	30	mpdiou	mpdiou	NOUN
ajst-26756	62	31	)	)	PUNCT
ajst-26756	62	32	loss	loss	NOUN
ajst-26756	62	33	function	function	NOUN
ajst-26756	62	34	.	.	PUNCT
ajst-26756	63	1	it	it	PRON
ajst-26756	63	2	improves	improve	VERB
ajst-26756	63	3	the	the	DET
ajst-26756	63	4	localization	localization	NOUN
ajst-26756	63	5	ability	ability	NOUN
ajst-26756	63	6	of	of	ADP
ajst-26756	63	7	the	the	DET
ajst-26756	63	8	model	model	NOUN
ajst-26756	63	9	by	by	ADP
ajst-26756	63	10	taking	take	VERB
ajst-26756	63	11	into	into	ADP
ajst-26756	63	12	account	account	NOUN
ajst-26756	63	13	the	the	DET
ajst-26756	63	14	minimum	minimum	ADJ
ajst-26756	63	15	vertical	vertical	ADJ
ajst-26756	63	16	distance	distance	NOUN
ajst-26756	63	17	between	between	ADP
ajst-26756	63	18	the	the	DET
ajst-26756	63	19	predicted	predict	VERB
ajst-26756	63	20	bounding	bounding	NOUN
ajst-26756	63	21	box	box	NOUN
ajst-26756	63	22	and	and	CCONJ
ajst-26756	63	23	the	the	DET
ajst-26756	63	24	real	real	ADJ
ajst-26756	63	25	bounding	bounding	NOUN
ajst-26756	63	26	box	box	NOUN
ajst-26756	63	27	,	,	PUNCT
ajst-26756	63	28	especially	especially	ADV
ajst-26756	63	29	when	when	SCONJ
ajst-26756	63	30	the	the	DET
ajst-26756	63	31	bounding	bounding	NOUN
ajst-26756	63	32	boxes	box	NOUN
ajst-26756	63	33	are	be	AUX
ajst-26756	63	34	highly	highly	ADV
ajst-26756	63	35	overlapped	overlapped	ADJ
ajst-26756	63	36	or	or	CCONJ
ajst-26756	63	37	partially	partially	ADV
ajst-26756	63	38	overlapped	overlap	VERB
ajst-26756	63	39	.	.	PUNCT
ajst-26756	64	1	mpdiou	mpdiou	NOUN
ajst-26756	65	1	[	[	X
ajst-26756	65	2	14	14	NUM
ajst-26756	65	3	]	]	PUNCT
ajst-26756	65	4	compensates	compensate	NOUN
ajst-26756	65	5	for	for	ADP
ajst-26756	65	6	this	this	PRON
ajst-26756	65	7	by	by	ADP
ajst-26756	65	8	introducing	introduce	VERB
ajst-26756	65	9	an	an	DET
ajst-26756	65	10	additional	additional	ADJ
ajst-26756	65	11	distance	distance	NOUN
ajst-26756	65	12	metric	metric	ADJ
ajst-26756	65	13	,	,	PUNCT
ajst-26756	65	14	i.e.	i.e.	X
ajst-26756	65	15	,	,	PUNCT
ajst-26756	65	16	the	the	DET
ajst-26756	65	17	minimum	minimum	ADJ
ajst-26756	65	18	vertical	vertical	ADJ
ajst-26756	65	19	distance	distance	NOUN
ajst-26756	65	20	of	of	ADP
ajst-26756	65	21	the	the	DET
ajst-26756	65	22	vertices	vertex	NOUN
ajst-26756	65	23	between	between	ADP
ajst-26756	65	24	the	the	DET
ajst-26756	65	25	predicted	predict	VERB
ajst-26756	65	26	box	box	NOUN
ajst-26756	65	27	and	and	CCONJ
ajst-26756	65	28	the	the	DET
ajst-26756	65	29	real	real	ADJ
ajst-26756	65	30	box	box	NOUN
ajst-26756	65	31	,	,	PUNCT
ajst-26756	65	32	which	which	PRON
ajst-26756	65	33	allows	allow	VERB
ajst-26756	65	34	the	the	DET
ajst-26756	65	35	loss	loss	NOUN
ajst-26756	65	36	function	function	NOUN
ajst-26756	65	37	to	to	PART
ajst-26756	65	38	be	be	AUX
ajst-26756	65	39	more	more	ADV
ajst-26756	65	40	concerned	concerned	ADJ
ajst-26756	65	41	with	with	ADP
ajst-26756	65	42	the	the	DET
ajst-26756	65	43	exact	exact	ADJ
ajst-26756	65	44	alignment	alignment	NOUN
ajst-26756	65	45	of	of	ADP
ajst-26756	65	46	the	the	DET
ajst-26756	65	47	bounding	bounding	NOUN
ajst-26756	65	48	boxes	box	NOUN
ajst-26756	65	49	during	during	ADP
ajst-26756	65	50	the	the	DET
ajst-26756	65	51	optimization	optimization	NOUN
ajst-26756	65	52	.	.	PUNCT
ajst-26756	66	1	alignment	alignment	NOUN
ajst-26756	66	2	,	,	PUNCT
ajst-26756	66	3	which	which	PRON
ajst-26756	66	4	can	can	AUX
ajst-26756	66	5	be	be	AUX
ajst-26756	66	6	mathematically	mathematically	ADV
ajst-26756	66	7	expressed	express	VERB
ajst-26756	66	8	as	as	ADP
ajst-26756	66	9	.	.	PROPN
ajst-26756	66	10	2	2	NUM
ajst-26756	66	11	2	2	NUM
ajst-26756	66	12	1	1	NUM
ajst-26756	66	13	2	2	NUM
ajst-26756	66	14	2	2	NUM
ajst-26756	66	15	2	2	NUM
ajst-26756	66	16	d	d	NOUN
ajst-26756	66	17	d	d	NOUN
ajst-26756	66	18	mpdiou	mpdiou	NOUN
ajst-26756	66	19	iou	iou	PROPN
ajst-26756	66	20	h	h	PROPN
ajst-26756	66	21	w	w	PROPN
ajst-26756	66	22			PROPN
ajst-26756	66	23			PROPN
ajst-26756	66	24			PROPN
ajst-26756	66	25			X
ajst-26756	66	26	(	(	PUNCT
ajst-26756	66	27	1	1	X
ajst-26756	66	28	)	)	PUNCT
ajst-26756	66	29	where	where	SCONJ
ajst-26756	66	30	1d	1d	NUM
ajst-26756	66	31	and	and	CCONJ
ajst-26756	66	32	2d	2d	NOUN
ajst-26756	66	33	represent	represent	VERB
ajst-26756	66	34	the	the	DET
ajst-26756	66	35	euclidean	euclidean	ADJ
ajst-26756	66	36	distances	distance	NOUN
ajst-26756	66	37	between	between	ADP
ajst-26756	66	38	the	the	DET
ajst-26756	66	39	diagonals	diagonal	NOUN
ajst-26756	66	40	of	of	ADP
ajst-26756	66	41	the	the	DET
ajst-26756	66	42	predicted	predict	VERB
ajst-26756	66	43	bounding	bounding	NOUN
ajst-26756	66	44	box	box	NOUN
ajst-26756	66	45	and	and	CCONJ
ajst-26756	66	46	the	the	DET
ajst-26756	66	47	real	real	ADJ
ajst-26756	66	48	bounding	bounding	NOUN
ajst-26756	66	49	box	box	NOUN
ajst-26756	66	50	respectively	respectively	ADV
ajst-26756	66	51	.	.	PUNCT
ajst-26756	67	1	h	h	NOUN
ajst-26756	67	2	and	and	CCONJ
ajst-26756	67	3	w	w	PROPN
ajst-26756	67	4	are	be	AUX
ajst-26756	67	5	the	the	DET
ajst-26756	67	6	height	height	NOUN
ajst-26756	67	7	and	and	CCONJ
ajst-26756	67	8	width	width	NOUN
ajst-26756	67	9	of	of	ADP
ajst-26756	67	10	the	the	DET
ajst-26756	67	11	bounding	bounding	NOUN
ajst-26756	67	12	box	box	NOUN
ajst-26756	67	13	,	,	PUNCT
ajst-26756	67	14	respectively	respectively	ADV
ajst-26756	67	15	,	,	PUNCT
ajst-26756	67	16	and	and	CCONJ
ajst-26756	67	17	iou	iou	NOUN
ajst-26756	67	18	denotes	denote	VERB
ajst-26756	67	19	the	the	DET
ajst-26756	67	20	intersection	intersection	NOUN
ajst-26756	67	21	and	and	CCONJ
ajst-26756	67	22	concurrency	concurrency	NOUN
ajst-26756	67	23	ratio	ratio	NOUN
ajst-26756	67	24	between	between	ADP
ajst-26756	67	25	the	the	DET
ajst-26756	67	26	predicted	predict	VERB
ajst-26756	67	27	bounding	bounding	NOUN
ajst-26756	67	28	box	box	NOUN
ajst-26756	67	29	and	and	CCONJ
ajst-26756	67	30	the	the	DET
ajst-26756	67	31	real	real	ADJ
ajst-26756	67	32	bounding	bounding	NOUN
ajst-26756	67	33	box	box	NOUN
ajst-26756	67	34	.	.	PUNCT
ajst-26756	68	1	3	3	X
ajst-26756	68	2	.	.	X
ajst-26756	68	3	experiment	experiment	NOUN
ajst-26756	68	4	in	in	ADP
ajst-26756	68	5	order	order	NOUN
ajst-26756	68	6	to	to	PART
ajst-26756	68	7	verify	verify	VERB
ajst-26756	68	8	the	the	DET
ajst-26756	68	9	performance	performance	NOUN
ajst-26756	68	10	of	of	ADP
ajst-26756	68	11	sem	sem	PROPN
ajst-26756	68	12	-	-	PUNCT
ajst-26756	68	13	yolov8n	yolov8n	PROPN
ajst-26756	68	14	proposed	propose	VERB
ajst-26756	68	15	in	in	ADP
ajst-26756	68	16	this	this	DET
ajst-26756	68	17	paper	paper	NOUN
ajst-26756	68	18	for	for	ADP
ajst-26756	68	19	road	road	NOUN
ajst-26756	68	20	defect	defect	NOUN
ajst-26756	68	21	detection	detection	NOUN
ajst-26756	68	22	,	,	PUNCT
ajst-26756	68	23	the	the	DET
ajst-26756	68	24	algorithm	algorithm	NOUN
ajst-26756	68	25	was	be	AUX
ajst-26756	68	26	trained	train	VERB
ajst-26756	68	27	and	and	CCONJ
ajst-26756	68	28	tested	test	VERB
ajst-26756	68	29	using	use	VERB
ajst-26756	68	30	iranian	iranian	ADJ
ajst-26756	68	31	road	road	NOUN
ajst-26756	68	32	disease	disease	NOUN
ajst-26756	68	33	dataset	dataset	NOUN
ajst-26756	68	34	and	and	CCONJ
ajst-26756	68	35	sem	sem	PROPN
ajst-26756	68	36	-	-	PUNCT
ajst-26756	68	37	yolov8n	yolov8n	PROPN
ajst-26756	68	38	was	be	AUX
ajst-26756	68	39	compared	compare	VERB
ajst-26756	68	40	with	with	ADP
ajst-26756	68	41	other	other	ADJ
ajst-26756	68	42	mainstream	mainstream	NOUN
ajst-26756	68	43	detection	detection	NOUN
ajst-26756	68	44	algorithms	algorithm	NOUN
ajst-26756	68	45	and	and	CCONJ
ajst-26756	68	46	its	its	PRON
ajst-26756	68	47	actual	actual	ADJ
ajst-26756	68	48	detection	detection	NOUN
ajst-26756	68	49	was	be	AUX
ajst-26756	68	50	visualized	visualize	VERB
ajst-26756	68	51	,	,	PUNCT
ajst-26756	68	52	which	which	PRON
ajst-26756	68	53	verified	verify	VERB
ajst-26756	68	54	that	that	SCONJ
ajst-26756	68	55	the	the	DET
ajst-26756	68	56	algorithm	algorithm	NOUN
ajst-26756	68	57	proposed	propose	VERB
ajst-26756	68	58	in	in	ADP
ajst-26756	68	59	this	this	DET
ajst-26756	68	60	paper	paper	NOUN
ajst-26756	68	61	shows	show	VERB
ajst-26756	68	62	good	good	ADJ
ajst-26756	68	63	detection	detection	NOUN
ajst-26756	68	64	performance	performance	NOUN
ajst-26756	68	65	for	for	ADP
ajst-26756	68	66	subtle	subtle	ADJ
ajst-26756	68	67	road	road	NOUN
ajst-26756	68	68	defects	defect	NOUN
ajst-26756	68	69	with	with	ADP
ajst-26756	68	70	complex	complex	ADJ
ajst-26756	68	71	background	background	NOUN
ajst-26756	68	72	.	.	PUNCT
ajst-26756	69	1	finally	finally	ADV
ajst-26756	69	2	,	,	PUNCT
ajst-26756	69	3	ablation	ablation	NOUN
ajst-26756	69	4	experiments	experiment	NOUN
ajst-26756	69	5	are	be	AUX
ajst-26756	69	6	conducted	conduct	VERB
ajst-26756	69	7	to	to	PART
ajst-26756	69	8	verify	verify	VERB
ajst-26756	69	9	the	the	DET
ajst-26756	69	10	effectiveness	effectiveness	NOUN
ajst-26756	69	11	of	of	ADP
ajst-26756	69	12	each	each	DET
ajst-26756	69	13	improved	improve	VERB
ajst-26756	69	14	module	module	NOUN
ajst-26756	69	15	.	.	PUNCT
ajst-26756	70	1	3.1	3.1	NUM
ajst-26756	70	2	.	.	PUNCT
ajst-26756	70	3	dataset	dataset	VERB
ajst-26756	70	4	the	the	DET
ajst-26756	70	5	experimental	experimental	ADJ
ajst-26756	70	6	results	result	NOUN
ajst-26756	70	7	of	of	ADP
ajst-26756	70	8	the	the	DET
ajst-26756	70	9	proposed	propose	VERB
ajst-26756	70	10	sem	sem	NOUN
ajst-26756	70	11	-	-	PUNCT
ajst-26756	70	12	yolov8n	yolov8n	PROPN
ajst-26756	70	13	were	be	AUX
ajst-26756	70	14	evaluated	evaluate	VERB
ajst-26756	70	15	on	on	ADP
ajst-26756	70	16	the	the	DET
ajst-26756	70	17	iranian	iranian	ADJ
ajst-26756	70	18	road	road	NOUN
ajst-26756	70	19	disease	disease	NOUN
ajst-26756	70	20	dataset	dataset	VERB
ajst-26756	70	21	(	(	PUNCT
ajst-26756	70	22	irrdd	irrdd	ADJ
ajst-26756	70	23	)	)	PUNCT
ajst-26756	70	24	.	.	PUNCT
ajst-26756	71	1	this	this	DET
ajst-26756	71	2	dataset	dataset	NOUN
ajst-26756	71	3	collects	collect	VERB
ajst-26756	71	4	local	local	ADJ
ajst-26756	71	5	iranian	iranian	ADJ
ajst-26756	71	6	road	road	NOUN
ajst-26756	71	7	damage	damage	NOUN
ajst-26756	71	8	dataset	dataset	NOUN
ajst-26756	71	9	including	include	VERB
ajst-26756	71	10	different	different	ADJ
ajst-26756	71	11	environmental	environmental	ADJ
ajst-26756	71	12	conditions	condition	NOUN
ajst-26756	71	13	such	such	ADJ
ajst-26756	71	14	as	as	ADP
ajst-26756	71	15	different	different	ADJ
ajst-26756	71	16	shadows	shadow	NOUN
ajst-26756	71	17	,	,	PUNCT
ajst-26756	71	18	lighting	lighting	NOUN
ajst-26756	71	19	levels	level	NOUN
ajst-26756	71	20	and	and	CCONJ
ajst-26756	71	21	daylight	daylight	NOUN
ajst-26756	71	22	hours	hour	NOUN
ajst-26756	71	23	.	.	PUNCT
ajst-26756	72	1	in	in	ADP
ajst-26756	72	2	this	this	DET
ajst-26756	72	3	dataset	dataset	NOUN
ajst-26756	72	4	,	,	PUNCT
ajst-26756	72	5	there	there	PRON
ajst-26756	72	6	are	be	VERB
ajst-26756	72	7	25,000	25,000	NUM
ajst-26756	72	8	images	image	NOUN
ajst-26756	72	9	of	of	ADP
ajst-26756	72	10	urban	urban	ADJ
ajst-26756	72	11	roads	road	NOUN
ajst-26756	72	12	with	with	ADP
ajst-26756	72	13	a	a	DET
ajst-26756	72	14	resolution	resolution	NOUN
ajst-26756	72	15	of	of	ADP
ajst-26756	72	16	640×640	640×640	NUM
ajst-26756	72	17	,	,	PUNCT
ajst-26756	72	18	and	and	CCONJ
ajst-26756	72	19	it	it	PRON
ajst-26756	72	20	is	be	AUX
ajst-26756	72	21	divided	divide	VERB
ajst-26756	72	22	into	into	ADP
ajst-26756	72	23	training	training	NOUN
ajst-26756	72	24	,	,	PUNCT
ajst-26756	72	25	testing	testing	NOUN
ajst-26756	72	26	and	and	CCONJ
ajst-26756	72	27	validation	validation	NOUN
ajst-26756	72	28	sets	set	NOUN
ajst-26756	72	29	with	with	ADP
ajst-26756	72	30	17,500	17,500	NUM
ajst-26756	72	31	,	,	PUNCT
ajst-26756	72	32	5,000	5,000	NUM
ajst-26756	72	33	and	and	CCONJ
ajst-26756	72	34	2,500	2,500	NUM
ajst-26756	72	35	images	image	NOUN
ajst-26756	72	36	in	in	ADP
ajst-26756	72	37	a	a	DET
ajst-26756	72	38	7:2:1	7:2:1	NUM
ajst-26756	72	39	ratio	ratio	NOUN
ajst-26756	72	40	,	,	PUNCT
ajst-26756	72	41	respectively	respectively	ADV
ajst-26756	72	42	.	.	PUNCT
ajst-26756	73	1	the	the	DET
ajst-26756	73	2	defect	defect	ADJ
ajst-26756	73	3	categories	category	NOUN
ajst-26756	73	4	are	be	AUX
ajst-26756	73	5	categorized	categorize	VERB
ajst-26756	73	6	into	into	ADP
ajst-26756	73	7	four	four	NUM
ajst-26756	73	8	,	,	PUNCT
ajst-26756	73	9	namely	namely	ADV
ajst-26756	73	10	:	:	PUNCT
ajst-26756	73	11	transverse	transverse	NOUN
ajst-26756	73	12	cracks	crack	NOUN
ajst-26756	73	13	,	,	PUNCT
ajst-26756	73	14	longitudinal	longitudinal	ADJ
ajst-26756	73	15	cracks	crack	NOUN
ajst-26756	73	16	,	,	PUNCT
ajst-26756	73	17	mesh	mesh	NOUN
ajst-26756	73	18	cracks	crack	NOUN
ajst-26756	73	19	and	and	CCONJ
ajst-26756	73	20	potholes	pothole	NOUN
ajst-26756	73	21	.	.	PUNCT
ajst-26756	74	1	3.2	3.2	NUM
ajst-26756	74	2	.	.	PUNCT
ajst-26756	74	3	evaluation	evaluation	NOUN
ajst-26756	74	4	metrics	metric	NOUN
ajst-26756	74	5	the	the	DET
ajst-26756	74	6	classification	classification	NOUN
ajst-26756	74	7	of	of	ADP
ajst-26756	74	8	the	the	DET
ajst-26756	74	9	model	model	NOUN
ajst-26756	74	10	is	be	AUX
ajst-26756	74	11	evaluated	evaluate	VERB
ajst-26756	74	12	by	by	ADP
ajst-26756	74	13	precision	precision	NOUN
ajst-26756	74	14	(	(	PUNCT
ajst-26756	74	15	p	p	NOUN
ajst-26756	74	16	)	)	PUNCT
ajst-26756	74	17	and	and	CCONJ
ajst-26756	74	18	recall	recall	NOUN
ajst-26756	74	19	(	(	PUNCT
ajst-26756	74	20	r	r	NOUN
ajst-26756	74	21	)	)	PUNCT
ajst-26756	74	22	.	.	PUNCT
ajst-26756	75	1	in	in	ADP
ajst-26756	75	2	addition	addition	NOUN
ajst-26756	75	3	,	,	PUNCT
ajst-26756	75	4	mean	mean	ADJ
ajst-26756	75	5	average	average	ADJ
ajst-26756	75	6	precision	precision	NOUN
ajst-26756	75	7	(	(	PUNCT
ajst-26756	75	8	map	map	NOUN
ajst-26756	75	9	)	)	PUNCT
ajst-26756	75	10	is	be	AUX
ajst-26756	75	11	used	use	VERB
ajst-26756	75	12	to	to	PART
ajst-26756	75	13	evaluate	evaluate	VERB
ajst-26756	75	14	the	the	DET
ajst-26756	75	15	defect	defect	NOUN
ajst-26756	75	16	detection	detection	NOUN
ajst-26756	75	17	results	result	NOUN
ajst-26756	75	18	.	.	PUNCT
ajst-26756	76	1	the	the	DET
ajst-26756	76	2	number	number	NOUN
ajst-26756	76	3	of	of	ADP
ajst-26756	76	4	parameters	parameter	NOUN
ajst-26756	76	5	is	be	AUX
ajst-26756	76	6	the	the	DET
ajst-26756	76	7	metric	metric	ADJ
ajst-26756	76	8	used	use	VERB
ajst-26756	76	9	to	to	PART
ajst-26756	76	10	evaluate	evaluate	VERB
ajst-26756	76	11	the	the	DET
ajst-26756	76	12	complexity	complexity	NOUN
ajst-26756	76	13	of	of	ADP
ajst-26756	76	14	the	the	DET
ajst-26756	76	15	model	model	NOUN
ajst-26756	76	16	and	and	CCONJ
ajst-26756	76	17	is	be	AUX
ajst-26756	76	18	defined	define	VERB
ajst-26756	76	19	as	as	SCONJ
ajst-26756	76	20	follows	follow	VERB
ajst-26756	76	21	:	:	PUNCT
ajst-26756	77	1	tp	tp	ADP
ajst-26756	77	2	p	p	PROPN
ajst-26756	77	3	tp	tp	ADP
ajst-26756	77	4	fp	fp	PROPN
ajst-26756	77	5			PROPN
ajst-26756	77	6			X
ajst-26756	77	7	(	(	PUNCT
ajst-26756	77	8	2	2	NUM
ajst-26756	77	9	)	)	PUNCT
ajst-26756	77	10	tp	tp	ADP
ajst-26756	77	11	r	r	NOUN
ajst-26756	77	12	tp	tp	NOUN
ajst-26756	78	1	fn	fn	PROPN
ajst-26756	79	1			PROPN
ajst-26756	79	2			X
ajst-26756	79	3	(	(	PUNCT
ajst-26756	79	4	3	3	NUM
ajst-26756	79	5	)	)	PUNCT
ajst-26756	79	6	1	1	NUM
ajst-26756	79	7	0	0	NUM
ajst-26756	79	8	(	(	PUNCT
ajst-26756	79	9	)	)	PUNCT
ajst-26756	79	10	ap	ap	PROPN
ajst-26756	80	1	p	p	NOUN
ajst-26756	80	2	x	x	X
ajst-26756	80	3	dx	dx	NOUN
ajst-26756	80	4			PUNCT
ajst-26756	80	5	(	(	PUNCT
ajst-26756	80	6	4	4	X
ajst-26756	80	7	)	)	SYM
ajst-26756	81	1	1	1	NUM
ajst-26756	81	2	1	1	NUM
ajst-26756	81	3	n	n	PRON
ajst-26756	81	4	ii	ii	NOUN
ajst-26756	81	5	map	map	NOUN
ajst-26756	81	6	ap	ap	PROPN
ajst-26756	81	7	n	n	ADV
ajst-26756	81	8			NOUN
ajst-26756	81	9			NOUN
ajst-26756	81	10			X
ajst-26756	81	11	(	(	PUNCT
ajst-26756	81	12	5	5	NUM
ajst-26756	81	13	)	)	PUNCT
ajst-26756	81	14	where	where	SCONJ
ajst-26756	81	15	p	p	NOUN
ajst-26756	81	16	is	be	AUX
ajst-26756	81	17	the	the	DET
ajst-26756	81	18	average	average	ADJ
ajst-26756	81	19	precision	precision	NOUN
ajst-26756	81	20	;	;	PUNCT
ajst-26756	81	21	tp	tp	NOUN
ajst-26756	81	22	is	be	AUX
ajst-26756	81	23	the	the	DET
ajst-26756	81	24	count	count	NOUN
ajst-26756	81	25	of	of	ADP
ajst-26756	81	26	“	"	PUNCT
ajst-26756	81	27	cracked	crack	VERB
ajst-26756	81	28	”	"	PUNCT
ajst-26756	81	29	examples	example	NOUN
ajst-26756	81	30	predicted	predict	VERB
ajst-26756	81	31	by	by	ADP
ajst-26756	81	32	the	the	DET
ajst-26756	81	33	model	model	NOUN
ajst-26756	81	34	to	to	PART
ajst-26756	81	35	be	be	AUX
ajst-26756	81	36	“	"	PUNCT
ajst-26756	81	37	cracked	crack	VERB
ajst-26756	81	38	”	"	PUNCT
ajst-26756	81	39	;	;	PUNCT
ajst-26756	81	40	fp	fp	X
ajst-26756	81	41	is	be	AUX
ajst-26756	81	42	the	the	DET
ajst-26756	81	43	count	count	NOUN
ajst-26756	81	44	of	of	ADP
ajst-26756	81	45	“	"	PUNCT
ajst-26756	81	46	background	background	NOUN
ajst-26756	81	47	”	"	PUNCT
ajst-26756	81	48	examples	example	NOUN
ajst-26756	81	49	predicted	predict	VERB
ajst-26756	81	50	by	by	ADP
ajst-26756	81	51	the	the	DET
ajst-26756	81	52	model	model	NOUN
ajst-26756	81	53	to	to	PART
ajst-26756	81	54	be	be	AUX
ajst-26756	81	55	“	"	PUNCT
ajst-26756	81	56	cracked	crack	VERB
ajst-26756	81	57	”	"	PUNCT
ajst-26756	81	58	;	;	PUNCT
ajst-26756	81	59	fn	fn	NOUN
ajst-26756	81	60	represents	represent	VERB
ajst-26756	81	61	the	the	DET
ajst-26756	81	62	number	number	NOUN
ajst-26756	81	63	of	of	ADP
ajst-26756	81	64	“	"	PUNCT
ajst-26756	81	65	cracked	crack	VERB
ajst-26756	81	66	”	"	PUNCT
ajst-26756	81	67	examples	example	NOUN
ajst-26756	81	68	that	that	PRON
ajst-26756	81	69	are	be	AUX
ajst-26756	81	70	predicted	predict	VERB
ajst-26756	81	71	by	by	ADP
ajst-26756	81	72	the	the	DET
ajst-26756	81	73	model	model	NOUN
ajst-26756	81	74	to	to	PART
ajst-26756	81	75	be	be	AUX
ajst-26756	81	76	“	"	PUNCT
ajst-26756	81	77	background	background	NOUN
ajst-26756	81	78	”	"	PUNCT
ajst-26756	81	79	;	;	PUNCT
ajst-26756	81	80	and	and	CCONJ
ajst-26756	81	81	map	map	NOUN
ajst-26756	81	82	represents	represent	VERB
ajst-26756	81	83	the	the	DET
ajst-26756	81	84	average	average	ADJ
ajst-26756	81	85	value	value	NOUN
ajst-26756	81	86	of	of	ADP
ajst-26756	81	87	the	the	DET
ajst-26756	81	88	mean	mean	ADJ
ajst-26756	81	89	precision	precision	NOUN
ajst-26756	81	90	.	.	PUNCT
ajst-26756	82	1	3.3	3.3	NUM
ajst-26756	82	2	.	.	PUNCT
ajst-26756	83	1	implementation	implementation	NOUN
ajst-26756	83	2	details	detail	NOUN
ajst-26756	83	3	the	the	DET
ajst-26756	83	4	experiments	experiment	NOUN
ajst-26756	83	5	are	be	AUX
ajst-26756	83	6	performed	perform	VERB
ajst-26756	83	7	on	on	ADP
ajst-26756	83	8	a	a	DET
ajst-26756	83	9	workstation	workstation	NOUN
ajst-26756	83	10	with	with	ADP
ajst-26756	83	11	a	a	DET
ajst-26756	83	12	cpu	cpu	NOUN
ajst-26756	83	13	model	model	NOUN
ajst-26756	83	14	intel	intel	PROPN
ajst-26756	83	15	core	core	NOUN
ajst-26756	83	16	i9	i9	NOUN
ajst-26756	83	17	-	-	PUNCT
ajst-26756	83	18	12900k@3.40ghz	12900k@3.40ghz	NUM
ajst-26756	83	19	,	,	PUNCT
ajst-26756	83	20	gpu	gpu	PROPN
ajst-26756	83	21	model	model	NOUN
ajst-26756	83	22	nvdia	nvdia	PROPN
ajst-26756	83	23	geforce	geforce	PROPN
ajst-26756	83	24	rtx	rtx	PROPN
ajst-26756	83	25	3090	3090	NUM
ajst-26756	83	26	,	,	PUNCT
ajst-26756	83	27	24	24	NUM
ajst-26756	83	28	g	g	PROPN
ajst-26756	83	29	video	video	NOUN
ajst-26756	83	30	memory	memory	NOUN
ajst-26756	83	31	,	,	PUNCT
ajst-26756	83	32	and	and	CCONJ
ajst-26756	83	33	128	128	NUM
ajst-26756	83	34	g	g	NOUN
ajst-26756	83	35	ram	ram	NOUN
ajst-26756	83	36	.	.	PUNCT
ajst-26756	84	1	the	the	DET
ajst-26756	84	2	experiment	experiment	NOUN
ajst-26756	84	3	does	do	AUX
ajst-26756	84	4	not	not	PART
ajst-26756	84	5	use	use	VERB
ajst-26756	84	6	a	a	DET
ajst-26756	84	7	pre	pre	ADJ
ajst-26756	84	8	-	-	ADJ
ajst-26756	84	9	trained	train	VERB
ajst-26756	84	10	model	model	NOUN
ajst-26756	84	11	so	so	SCONJ
ajst-26756	84	12	that	that	SCONJ
ajst-26756	84	13	the	the	DET
ajst-26756	84	14	model	model	NOUN
ajst-26756	84	15	architecture	architecture	NOUN
ajst-26756	84	16	and	and	CCONJ
ajst-26756	84	17	parameters	parameter	NOUN
ajst-26756	84	18	can	can	AUX
ajst-26756	84	19	be	be	AUX
ajst-26756	84	20	better	well	ADV
ajst-26756	84	21	customized	customize	VERB
ajst-26756	84	22	for	for	ADP
ajst-26756	84	23	this	this	DET
ajst-26756	84	24	experiment	experiment	NOUN
ajst-26756	84	25	;	;	PUNCT
ajst-26756	84	26	this	this	DET
ajst-26756	84	27	customization	customization	NOUN
ajst-26756	84	28	improves	improve	VERB
ajst-26756	84	29	the	the	DET
ajst-26756	84	30	performance	performance	NOUN
ajst-26756	84	31	of	of	ADP
ajst-26756	84	32	the	the	DET
ajst-26756	84	33	model	model	NOUN
ajst-26756	84	34	and	and	CCONJ
ajst-26756	84	35	makes	make	VERB
ajst-26756	84	36	the	the	DET
ajst-26756	84	37	experiment	experiment	NOUN
ajst-26756	84	38	more	more	ADV
ajst-26756	84	39	objective	objective	ADJ
ajst-26756	84	40	.	.	PUNCT
ajst-26756	85	1	the	the	DET
ajst-26756	85	2	learning	learning	NOUN
ajst-26756	85	3	rate	rate	NOUN
ajst-26756	85	4	is	be	AUX
ajst-26756	85	5	set	set	VERB
ajst-26756	85	6	to	to	ADP
ajst-26756	85	7	0.01	0.01	NUM
ajst-26756	85	8	and	and	CCONJ
ajst-26756	85	9	the	the	DET
ajst-26756	85	10	number	number	NOUN
ajst-26756	85	11	of	of	ADP
ajst-26756	85	12	categories	category	NOUN
ajst-26756	85	13	is	be	AUX
ajst-26756	85	14	set	set	VERB
ajst-26756	85	15	to	to	ADP
ajst-26756	85	16	4	4	NUM
ajst-26756	85	17	.	.	PUNCT
ajst-26756	86	1	the	the	DET
ajst-26756	86	2	batch	batch	NOUN
ajst-26756	86	3	size	size	NOUN
ajst-26756	86	4	is	be	AUX
ajst-26756	86	5	set	set	VERB
ajst-26756	86	6	to	to	ADP
ajst-26756	86	7	32	32	NUM
ajst-26756	86	8	due	due	ADP
ajst-26756	86	9	to	to	ADP
ajst-26756	86	10	gpu	gpu	NOUN
ajst-26756	86	11	memory	memory	NOUN
ajst-26756	86	12	constraints	constraint	NOUN
ajst-26756	86	13	.	.	PUNCT
ajst-26756	87	1	the	the	DET
ajst-26756	87	2	maximum	maximum	ADJ
ajst-26756	87	3	iteration	iteration	NOUN
ajst-26756	87	4	is	be	AUX
ajst-26756	87	5	fixed	fix	VERB
ajst-26756	87	6	to	to	ADP
ajst-26756	87	7	100	100	NUM
ajst-26756	87	8	,	,	PUNCT
ajst-26756	87	9	which	which	PRON
ajst-26756	87	10	ensures	ensure	VERB
ajst-26756	87	11	a	a	DET
ajst-26756	87	12	full	full	ADJ
ajst-26756	87	13	loop	loop	NOUN
ajst-26756	87	14	through	through	ADP
ajst-26756	87	15	the	the	DET
ajst-26756	87	16	training	training	NOUN
ajst-26756	87	17	data	datum	NOUN
ajst-26756	87	18	for	for	ADP
ajst-26756	87	19	the	the	DET
ajst-26756	87	20	road	road	NOUN
ajst-26756	87	21	images	image	NOUN
ajst-26756	87	22	.	.	PUNCT
ajst-26756	88	1	the	the	DET
ajst-26756	88	2	detailed	detailed	ADJ
ajst-26756	88	3	information	information	NOUN
ajst-26756	88	4	and	and	CCONJ
ajst-26756	88	5	hyperparameters	hyperparameter	NOUN
ajst-26756	88	6	of	of	ADP
ajst-26756	88	7	the	the	DET
ajst-26756	88	8	experiment	experiment	NOUN
ajst-26756	88	9	are	be	AUX
ajst-26756	88	10	shown	show	VERB
ajst-26756	88	11	in	in	ADP
ajst-26756	88	12	table	table	NOUN
ajst-26756	88	13	1	1	NUM
ajst-26756	88	14	.	.	PUNCT
ajst-26756	88	15	table	table	NOUN
ajst-26756	88	16	1	1	NUM
ajst-26756	88	17	.	.	PUNCT
ajst-26756	89	1	implementation	implementation	NOUN
ajst-26756	89	2	parameters	parameter	NOUN
ajst-26756	89	3	train	train	NOUN
ajst-26756	89	4	batch	batch	NOUN
ajst-26756	89	5	size	size	NOUN
ajst-26756	89	6	epoch	epoch	NOUN
ajst-26756	89	7	64	64	NUM
ajst-26756	89	8	640	640	NUM
ajst-26756	89	9	100	100	NUM
ajst-26756	89	10	momentum	momentum	NOUN
ajst-26756	89	11	learning	learn	VERB
ajst-26756	89	12	rate	rate	NOUN
ajst-26756	89	13	decay	decay	NOUN
ajst-26756	89	14	0.937	0.937	NUM
ajst-26756	89	15	0.01	0.01	NUM
ajst-26756	89	16	0.0005	0.0005	NUM
ajst-26756	89	17	test	test	NOUN
ajst-26756	89	18	iou	iou	PROPN
ajst-26756	89	19	nms	nms	PROPN
ajst-26756	89	20	0.3	0.3	NUM
ajst-26756	89	21	0.5	0.5	NUM
ajst-26756	89	22	3.4	3.4	NUM
ajst-26756	89	23	.	.	PUNCT
ajst-26756	90	1	results	result	VERB
ajst-26756	90	2	3.4.1	3.4.1	NUM
ajst-26756	90	3	.	.	PUNCT
ajst-26756	91	1	evaluation	evaluation	NOUN
ajst-26756	91	2	in	in	ADP
ajst-26756	91	3	order	order	NOUN
ajst-26756	91	4	to	to	PART
ajst-26756	91	5	validate	validate	VERB
ajst-26756	91	6	the	the	DET
ajst-26756	91	7	detection	detection	NOUN
ajst-26756	91	8	performance	performance	NOUN
ajst-26756	91	9	of	of	ADP
ajst-26756	91	10	the	the	DET
ajst-26756	91	11	proposed	propose	VERB
ajst-26756	91	12	model	model	NOUN
ajst-26756	91	13	,	,	PUNCT
ajst-26756	91	14	three	three	NUM
ajst-26756	91	15	sets	set	NOUN
ajst-26756	91	16	of	of	ADP
ajst-26756	91	17	comparison	comparison	NOUN
ajst-26756	91	18	experiments	experiment	NOUN
ajst-26756	91	19	were	be	AUX
ajst-26756	91	20	conducted	conduct	VERB
ajst-26756	91	21	on	on	ADP
ajst-26756	91	22	the	the	DET
ajst-26756	91	23	irrdd	irrdd	ADJ
ajst-26756	91	24	dataset	dataset	NOUN
ajst-26756	91	25	to	to	PART
ajst-26756	91	26	compare	compare	VERB
ajst-26756	91	27	the	the	DET
ajst-26756	91	28	model	model	NOUN
ajst-26756	91	29	with	with	ADP
ajst-26756	91	30	the	the	DET
ajst-26756	91	31	yolov8n	yolov8n	PROPN
ajst-26756	91	32	,	,	PUNCT
ajst-26756	91	33	yolov9n	yolov9n	NOUN
ajst-26756	91	34	,	,	PUNCT
ajst-26756	91	35	and	and	CCONJ
ajst-26756	91	36	yolov10n	yolov10n	NOUN
ajst-26756	91	37	models	model	NOUN
ajst-26756	91	38	.	.	PUNCT
ajst-26756	92	1	table	table	NOUN
ajst-26756	92	2	2	2	NUM
ajst-26756	92	3	shows	show	VERB
ajst-26756	92	4	the	the	DET
ajst-26756	92	5	p	p	X
ajst-26756	92	6	,	,	PUNCT
ajst-26756	92	7	r	r	NOUN
ajst-26756	92	8	,	,	PUNCT
ajst-26756	92	9	map	map	NOUN
ajst-26756	92	10	,	,	PUNCT
ajst-26756	92	11	and	and	CCONJ
ajst-26756	92	12	parametric	parametric	ADJ
ajst-26756	92	13	counts	count	NOUN
ajst-26756	92	14	of	of	ADP
ajst-26756	92	15	semyolov8n	semyolov8n	NOUN
ajst-26756	92	16	and	and	CCONJ
ajst-26756	92	17	yolov8n	yolov8n	NOUN
ajst-26756	92	18	,	,	PUNCT
ajst-26756	92	19	yolov9n	yolov9n	NOUN
ajst-26756	92	20	,	,	PUNCT
ajst-26756	92	21	and	and	CCONJ
ajst-26756	92	22	yolov10n	yolov10n	NOUN
ajst-26756	92	23	models	model	NOUN
ajst-26756	92	24	.	.	PUNCT
ajst-26756	93	1	93	93	NUM
ajst-26756	93	2	table	table	NOUN
ajst-26756	93	3	2	2	NUM
ajst-26756	93	4	.	.	PUNCT
ajst-26756	93	5	comparative	comparative	ADJ
ajst-26756	93	6	results	result	NOUN
ajst-26756	93	7	of	of	ADP
ajst-26756	93	8	the	the	DET
ajst-26756	93	9	detection	detection	NOUN
ajst-26756	93	10	ability	ability	NOUN
ajst-26756	93	11	of	of	ADP
ajst-26756	93	12	different	different	ADJ
ajst-26756	93	13	models	model	NOUN
ajst-26756	93	14	methods	method	NOUN
ajst-26756	93	15	p	p	NOUN
ajst-26756	93	16	(	(	PUNCT
ajst-26756	93	17	%	%	INTJ
ajst-26756	93	18	)	)	PUNCT
ajst-26756	93	19	r	r	NOUN
ajst-26756	93	20	(	(	PUNCT
ajst-26756	93	21	%	%	INTJ
ajst-26756	93	22	)	)	PUNCT
ajst-26756	93	23	map	map	NOUN
ajst-26756	93	24	(	(	PUNCT
ajst-26756	93	25	%	%	INTJ
ajst-26756	93	26	)	)	PUNCT
ajst-26756	93	27	parameter	parameter	NOUN
ajst-26756	93	28	(	(	PUNCT
ajst-26756	93	29	m	m	NOUN
ajst-26756	93	30	)	)	PUNCT
ajst-26756	93	31	yolov8n	yolov8n	NOUN
ajst-26756	93	32	89.1	89.1	NUM
ajst-26756	93	33	91.0	91.0	NUM
ajst-26756	93	34	67.4	67.4	NUM
ajst-26756	93	35	3.01	3.01	NUM
ajst-26756	93	36	yolov9n	yolov9n	NOUN
ajst-26756	93	37	90.5	90.5	NUM
ajst-26756	93	38	93.0	93.0	NUM
ajst-26756	93	39	69.4	69.4	NUM
ajst-26756	93	40	8.18	8.18	NUM
ajst-26756	93	41	yolov10n	yolov10n	NOUN
ajst-26756	93	42	66.1	66.1	NUM
ajst-26756	93	43	57.6	57.6	NUM
ajst-26756	93	44	64.7	64.7	NUM
ajst-26756	93	45	2.70	2.70	NUM
ajst-26756	93	46	sem	sem	NOUN
ajst-26756	93	47	-	-	PUNCT
ajst-26756	93	48	yolov8n	yolov8n	PROPN
ajst-26756	93	49	91.9	91.9	NUM
ajst-26756	93	50	91.3	91.3	NUM
ajst-26756	93	51	71.3	71.3	NUM
ajst-26756	93	52	4.76	4.76	NUM
ajst-26756	93	53	3.4.2	3.4.2	NUM
ajst-26756	93	54	.	.	PUNCT
ajst-26756	94	1	visualization	visualization	NOUN
ajst-26756	94	2	in	in	ADP
ajst-26756	94	3	order	order	NOUN
ajst-26756	94	4	to	to	PART
ajst-26756	94	5	visualize	visualize	VERB
ajst-26756	94	6	the	the	DET
ajst-26756	94	7	detection	detection	NOUN
ajst-26756	94	8	effect	effect	NOUN
ajst-26756	94	9	of	of	ADP
ajst-26756	94	10	the	the	DET
ajst-26756	94	11	improved	improved	ADJ
ajst-26756	94	12	modeling	modeling	NOUN
ajst-26756	94	13	algorithm	algorithm	NOUN
ajst-26756	94	14	,	,	PUNCT
ajst-26756	94	15	an	an	DET
ajst-26756	94	16	actual	actual	ADJ
ajst-26756	94	17	detection	detection	NOUN
ajst-26756	94	18	comparison	comparison	NOUN
ajst-26756	94	19	experiment	experiment	NOUN
ajst-26756	94	20	using	use	VERB
ajst-26756	94	21	yolov8n	yolov8n	PROPN
ajst-26756	94	22	and	and	CCONJ
ajst-26756	94	23	sem	sem	PROPN
ajst-26756	94	24	-	-	PUNCT
ajst-26756	94	25	yolov8n	yolov8n	PROPN
ajst-26756	94	26	proposed	propose	VERB
ajst-26756	94	27	in	in	ADP
ajst-26756	94	28	this	this	DET
ajst-26756	94	29	paper	paper	NOUN
ajst-26756	94	30	is	be	AUX
ajst-26756	94	31	carried	carry	VERB
ajst-26756	94	32	out	out	ADP
ajst-26756	94	33	as	as	SCONJ
ajst-26756	94	34	shown	show	VERB
ajst-26756	94	35	in	in	ADP
ajst-26756	94	36	fig	fig	NOUN
ajst-26756	94	37	.	.	PUNCT
ajst-26756	95	1	as	as	SCONJ
ajst-26756	95	2	can	can	AUX
ajst-26756	95	3	be	be	AUX
ajst-26756	95	4	seen	see	VERB
ajst-26756	95	5	from	from	ADP
ajst-26756	95	6	the	the	DET
ajst-26756	95	7	first	first	ADJ
ajst-26756	95	8	row	row	NOUN
ajst-26756	95	9	,	,	PUNCT
ajst-26756	95	10	yolov8n	yolov8n	PROPN
ajst-26756	95	11	has	have	AUX
ajst-26756	95	12	missed	miss	VERB
ajst-26756	95	13	detection	detection	NOUN
ajst-26756	95	14	due	due	ADP
ajst-26756	95	15	to	to	ADP
ajst-26756	95	16	shadow	shadow	NOUN
ajst-26756	95	17	masking	masking	NOUN
ajst-26756	95	18	,	,	PUNCT
ajst-26756	95	19	while	while	SCONJ
ajst-26756	95	20	sem	sem	NOUN
ajst-26756	95	21	-	-	PUNCT
ajst-26756	95	22	yolov8n	yolov8n	NOUN
ajst-26756	95	23	can	can	AUX
ajst-26756	95	24	detect	detect	VERB
ajst-26756	95	25	the	the	DET
ajst-26756	95	26	defects	defect	NOUN
ajst-26756	95	27	;	;	PUNCT
ajst-26756	95	28	as	as	SCONJ
ajst-26756	95	29	can	can	AUX
ajst-26756	95	30	be	be	AUX
ajst-26756	95	31	seen	see	VERB
ajst-26756	95	32	from	from	ADP
ajst-26756	95	33	the	the	DET
ajst-26756	95	34	second	second	ADJ
ajst-26756	95	35	row	row	NOUN
ajst-26756	95	36	,	,	PUNCT
ajst-26756	95	37	sem	sem	NOUN
ajst-26756	95	38	-	-	PUNCT
ajst-26756	95	39	yolov8n	yolov8n	PROPN
ajst-26756	95	40	has	have	VERB
ajst-26756	95	41	better	well	ADJ
ajst-26756	95	42	boundary	boundary	ADJ
ajst-26756	95	43	detection	detection	NOUN
ajst-26756	95	44	ability	ability	NOUN
ajst-26756	95	45	;	;	PUNCT
ajst-26756	95	46	as	as	SCONJ
ajst-26756	95	47	can	can	AUX
ajst-26756	95	48	be	be	AUX
ajst-26756	95	49	seen	see	VERB
ajst-26756	95	50	from	from	ADP
ajst-26756	95	51	the	the	DET
ajst-26756	95	52	third	third	ADJ
ajst-26756	95	53	row	row	NOUN
ajst-26756	95	54	,	,	PUNCT
ajst-26756	95	55	sem	sem	NOUN
ajst-26756	95	56	-	-	PUNCT
ajst-26756	95	57	yolov8n	yolov8n	PROPN
ajst-26756	95	58	has	have	VERB
ajst-26756	95	59	better	well	ADJ
ajst-26756	95	60	detection	detection	NOUN
ajst-26756	95	61	ability	ability	NOUN
ajst-26756	95	62	of	of	ADP
ajst-26756	95	63	subtle	subtle	ADJ
ajst-26756	95	64	defects	defect	NOUN
ajst-26756	95	65	than	than	ADP
ajst-26756	95	66	yolov8n	yolov8n	NOUN
ajst-26756	95	67	.	.	PUNCT
ajst-26756	96	1	therefore	therefore	ADV
ajst-26756	96	2	,	,	PUNCT
ajst-26756	96	3	the	the	DET
ajst-26756	96	4	semyolov8n	semyolov8n	PROPN
ajst-26756	96	5	algorithm	algorithm	NOUN
ajst-26756	96	6	proposed	propose	VERB
ajst-26756	96	7	in	in	ADP
ajst-26756	96	8	this	this	DET
ajst-26756	96	9	paper	paper	NOUN
ajst-26756	96	10	can	can	AUX
ajst-26756	96	11	over	over	ADP
ajst-26756	96	12	detect	detect	NOUN
ajst-26756	96	13	pavement	pavement	NOUN
ajst-26756	96	14	defects	defect	NOUN
ajst-26756	96	15	more	more	ADV
ajst-26756	96	16	accurately	accurately	ADV
ajst-26756	96	17	.	.	PUNCT
ajst-26756	97	1	raw	raw	ADJ
ajst-26756	97	2	label	label	NOUN
ajst-26756	97	3	yolov8n	yolov8n	PROPN
ajst-26756	97	4	sem	sem	PROPN
ajst-26756	97	5	-	-	PUNCT
ajst-26756	97	6	yolov8n	yolov8n	NOUN
ajst-26756	97	7	figure	figure	NOUN
ajst-26756	97	8	4	4	NUM
ajst-26756	97	9	.	.	NOUN
ajst-26756	97	10	comparison	comparison	NOUN
ajst-26756	97	11	of	of	ADP
ajst-26756	97	12	yolov8n	yolov8n	PROPN
ajst-26756	97	13	and	and	CCONJ
ajst-26756	97	14	sem	sem	PROPN
ajst-26756	97	15	-	-	PUNCT
ajst-26756	97	16	yolov8n	yolov8n	ADJ
ajst-26756	97	17	3.4.3	3.4.3	PROPN
ajst-26756	97	18	.	.	PUNCT
ajst-26756	97	19	ablation	ablation	NOUN
ajst-26756	97	20	ablation	ablation	NOUN
ajst-26756	97	21	were	be	AUX
ajst-26756	97	22	conducted	conduct	VERB
ajst-26756	97	23	on	on	ADP
ajst-26756	97	24	the	the	DET
ajst-26756	97	25	test	test	NOUN
ajst-26756	97	26	set	set	VERB
ajst-26756	97	27	to	to	PART
ajst-26756	97	28	verify	verify	VERB
ajst-26756	97	29	the	the	DET
ajst-26756	97	30	effectiveness	effectiveness	NOUN
ajst-26756	97	31	of	of	ADP
ajst-26756	97	32	adding	add	VERB
ajst-26756	97	33	each	each	DET
ajst-26756	97	34	module	module	NOUN
ajst-26756	97	35	,	,	PUNCT
ajst-26756	97	36	as	as	SCONJ
ajst-26756	97	37	shown	show	VERB
ajst-26756	97	38	in	in	ADP
ajst-26756	97	39	table	table	NOUN
ajst-26756	97	40	3	3	NUM
ajst-26756	97	41	.	.	PUNCT
ajst-26756	98	1	after	after	ADP
ajst-26756	98	2	replacing	replace	VERB
ajst-26756	98	3	the	the	DET
ajst-26756	98	4	ordinary	ordinary	ADJ
ajst-26756	98	5	convolution	convolution	NOUN
ajst-26756	98	6	in	in	ADP
ajst-26756	98	7	yolov8n	yolov8n	PROPN
ajst-26756	98	8	with	with	ADP
ajst-26756	98	9	spd	spd	NOUN
ajst-26756	98	10	-	-	PUNCT
ajst-26756	98	11	conv	conv	ADJ
ajst-26756	98	12	,	,	PUNCT
ajst-26756	98	13	the	the	DET
ajst-26756	98	14	map	map	NOUN
ajst-26756	98	15	is	be	AUX
ajst-26756	98	16	improved	improve	VERB
ajst-26756	98	17	by	by	ADP
ajst-26756	98	18	2.0	2.0	NUM
ajst-26756	98	19	%	%	NOUN
ajst-26756	98	20	;	;	PUNCT
ajst-26756	98	21	then	then	ADV
ajst-26756	98	22	the	the	DET
ajst-26756	98	23	ema	ema	PROPN
ajst-26756	98	24	attention	attention	NOUN
ajst-26756	98	25	mechanism	mechanism	NOUN
ajst-26756	98	26	is	be	AUX
ajst-26756	98	27	added	add	VERB
ajst-26756	98	28	to	to	ADP
ajst-26756	98	29	the	the	DET
ajst-26756	98	30	fusion	fusion	NOUN
ajst-26756	98	31	network	network	NOUN
ajst-26756	98	32	,	,	PUNCT
ajst-26756	98	33	and	and	CCONJ
ajst-26756	98	34	the	the	DET
ajst-26756	98	35	map	map	NOUN
ajst-26756	98	36	is	be	AUX
ajst-26756	98	37	improved	improve	VERB
ajst-26756	98	38	by	by	ADP
ajst-26756	98	39	2.8	2.8	NUM
ajst-26756	98	40	%	%	NOUN
ajst-26756	98	41	;	;	PUNCT
ajst-26756	98	42	finally	finally	ADV
ajst-26756	98	43	,	,	PUNCT
ajst-26756	98	44	applying	apply	VERB
ajst-26756	98	45	the	the	DET
ajst-26756	98	46	mpdiou	mpdiou	NOUN
ajst-26756	98	47	as	as	ADP
ajst-26756	98	48	the	the	DET
ajst-26756	98	49	loss	loss	NOUN
ajst-26756	98	50	function	function	NOUN
ajst-26756	98	51	,	,	PUNCT
ajst-26756	98	52	the	the	DET
ajst-26756	98	53	line	line	NOUN
ajst-26756	98	54	is	be	AUX
ajst-26756	98	55	formed	form	VERB
ajst-26756	98	56	into	into	ADP
ajst-26756	98	57	the	the	DET
ajst-26756	98	58	sem	sem	NOUN
ajst-26756	98	59	-	-	PUNCT
ajst-26756	98	60	yolov8n	yolov8n	PROPN
ajst-26756	98	61	,	,	PUNCT
ajst-26756	98	62	and	and	CCONJ
ajst-26756	98	63	the	the	DET
ajst-26756	98	64	map	map	NOUN
ajst-26756	98	65	is	be	AUX
ajst-26756	98	66	improved	improve	VERB
ajst-26756	98	67	by	by	ADP
ajst-26756	98	68	3.9	3.9	NUM
ajst-26756	98	69	%	%	NOUN
ajst-26756	98	70	,	,	PUNCT
ajst-26756	98	71	and	and	CCONJ
ajst-26756	98	72	the	the	DET
ajst-26756	98	73	experiments	experiment	NOUN
ajst-26756	98	74	proved	prove	VERB
ajst-26756	98	75	the	the	DET
ajst-26756	98	76	validity	validity	NOUN
ajst-26756	98	77	of	of	ADP
ajst-26756	98	78	the	the	DET
ajst-26756	98	79	individual	individual	ADJ
ajst-26756	98	80	modules	module	NOUN
ajst-26756	98	81	.	.	PUNCT
ajst-26756	99	1	table	table	NOUN
ajst-26756	99	2	3	3	NUM
ajst-26756	99	3	.	.	PUNCT
ajst-26756	100	1	results	result	NOUN
ajst-26756	100	2	of	of	ADP
ajst-26756	100	3	ablation	ablation	NOUN
ajst-26756	100	4	spd	spd	ADJ
ajst-26756	100	5	-	-	PUNCT
ajst-26756	100	6	conv	conv	ADJ
ajst-26756	100	7	ema	ema	PROPN
ajst-26756	100	8	mpdiou	mpdiou	NOUN
ajst-26756	100	9	map	map	NOUN
ajst-26756	100	10	(	(	PUNCT
ajst-26756	100	11	%	%	INTJ
ajst-26756	100	12	)	)	PUNCT
ajst-26756	100	13	parameter	parameter	NOUN
ajst-26756	100	14	(	(	PUNCT
ajst-26756	100	15	m	m	NOUN
ajst-26756	100	16	)	)	PUNCT
ajst-26756	100	17	67.4	67.4	NUM
ajst-26756	100	18	3.01	3.01	NUM
ajst-26756	100	19	√	√	NUM
ajst-26756	100	20	69.4	69.4	NUM
ajst-26756	100	21	4.74	4.74	NUM
ajst-26756	100	22	√	√	PROPN
ajst-26756	100	23	√	√	ADP
ajst-26756	100	24	70.2	70.2	NUM
ajst-26756	100	25	4.76	4.76	NUM
ajst-26756	100	26	√	√	PROPN
ajst-26756	100	27	√	√	NUM
ajst-26756	100	28	√	√	PROPN
ajst-26756	100	29	71.3	71.3	NUM
ajst-26756	100	30	4.76	4.76	NUM
ajst-26756	100	31	4	4	NUM
ajst-26756	100	32	.	.	PUNCT
ajst-26756	101	1	conclusion	conclusion	NOUN
ajst-26756	101	2	aiming	aim	VERB
ajst-26756	101	3	at	at	ADP
ajst-26756	101	4	the	the	DET
ajst-26756	101	5	problems	problem	NOUN
ajst-26756	101	6	that	that	PRON
ajst-26756	101	7	the	the	DET
ajst-26756	101	8	pavement	pavement	NOUN
ajst-26756	101	9	defects	defect	VERB
ajst-26756	101	10	account	account	VERB
ajst-26756	101	11	for	for	ADP
ajst-26756	101	12	few	few	ADJ
ajst-26756	101	13	pixels	pixel	NOUN
ajst-26756	101	14	in	in	ADP
ajst-26756	101	15	the	the	DET
ajst-26756	101	16	picture	picture	NOUN
ajst-26756	101	17	,	,	PUNCT
ajst-26756	101	18	small	small	ADJ
ajst-26756	101	19	volume	volume	NOUN
ajst-26756	101	20	,	,	PUNCT
ajst-26756	101	21	complex	complex	ADJ
ajst-26756	101	22	background	background	NOUN
ajst-26756	101	23	and	and	CCONJ
ajst-26756	101	24	multi	multi	NOUN
ajst-26756	101	25	-	-	NOUN
ajst-26756	101	26	target	target	NOUN
ajst-26756	102	1	,	,	PUNCT
ajst-26756	102	2	this	this	DET
ajst-26756	102	3	paper	paper	NOUN
ajst-26756	102	4	proposes	propose	VERB
ajst-26756	102	5	an	an	DET
ajst-26756	102	6	algorithm	algorithm	NOUN
ajst-26756	102	7	sem-yolov8n.firstly	sem-yolov8n.firstly	ADV
ajst-26756	102	8	,	,	PUNCT
ajst-26756	102	9	the	the	DET
ajst-26756	102	10	traditional	traditional	ADJ
ajst-26756	102	11	convolution	convolution	NOUN
ajst-26756	102	12	is	be	AUX
ajst-26756	102	13	replaced	replace	VERB
ajst-26756	102	14	by	by	ADP
ajst-26756	102	15	spd	spd	NOUN
ajst-26756	102	16	-	-	PUNCT
ajst-26756	102	17	conv	conv	ADJ
ajst-26756	102	18	to	to	PART
ajst-26756	102	19	extract	extract	VERB
ajst-26756	102	20	the	the	DET
ajst-26756	102	21	feature	feature	NOUN
ajst-26756	102	22	information	information	NOUN
ajst-26756	102	23	of	of	ADP
ajst-26756	102	24	the	the	DET
ajst-26756	102	25	multi	multi	ADJ
ajst-26756	102	26	-	-	ADJ
ajst-26756	102	27	scale	scale	ADJ
ajst-26756	102	28	fine	fine	ADJ
ajst-26756	102	29	defects	defect	NOUN
ajst-26756	102	30	,	,	PUNCT
ajst-26756	102	31	and	and	CCONJ
ajst-26756	102	32	then	then	ADV
ajst-26756	102	33	the	the	DET
ajst-26756	102	34	ema	ema	PROPN
ajst-26756	102	35	attention	attention	NOUN
ajst-26756	102	36	module	module	NOUN
ajst-26756	102	37	is	be	AUX
ajst-26756	102	38	added	add	VERB
ajst-26756	102	39	to	to	ADP
ajst-26756	102	40	the	the	DET
ajst-26756	102	41	fusion	fusion	NOUN
ajst-26756	102	42	network	network	NOUN
ajst-26756	102	43	to	to	PART
ajst-26756	102	44	improve	improve	VERB
ajst-26756	102	45	the	the	DET
ajst-26756	102	46	model	model	NOUN
ajst-26756	102	47	's	's	PART
ajst-26756	102	48	ability	ability	NOUN
ajst-26756	102	49	of	of	ADP
ajst-26756	102	50	feature	feature	NOUN
ajst-26756	102	51	extraction	extraction	NOUN
ajst-26756	102	52	for	for	ADP
ajst-26756	102	53	the	the	DET
ajst-26756	102	54	pavement	pavement	NOUN
ajst-26756	102	55	defects	defect	NOUN
ajst-26756	102	56	in	in	ADP
ajst-26756	102	57	the	the	DET
ajst-26756	102	58	complex	complex	ADJ
ajst-26756	102	59	environment	environment	NOUN
ajst-26756	102	60	,	,	PUNCT
ajst-26756	102	61	and	and	CCONJ
ajst-26756	102	62	finally	finally	ADV
ajst-26756	102	63	mpdiou	mpdiou	NOUN
ajst-26756	102	64	is	be	AUX
ajst-26756	102	65	chosen	choose	VERB
ajst-26756	102	66	as	as	ADP
ajst-26756	102	67	the	the	DET
ajst-26756	102	68	loss	loss	NOUN
ajst-26756	102	69	function	function	NOUN
ajst-26756	102	70	of	of	ADP
ajst-26756	102	71	the	the	DET
ajst-26756	102	72	network	network	NOUN
ajst-26756	102	73	to	to	PART
ajst-26756	102	74	improve	improve	VERB
ajst-26756	102	75	the	the	DET
ajst-26756	102	76	94	94	NUM
ajst-26756	102	77	convergence	convergence	NOUN
ajst-26756	102	78	speed	speed	NOUN
ajst-26756	102	79	and	and	CCONJ
ajst-26756	102	80	accuracy	accuracy	NOUN
ajst-26756	102	81	of	of	ADP
ajst-26756	102	82	the	the	DET
ajst-26756	102	83	model	model	NOUN
ajst-26756	102	84	.	.	PUNCT
ajst-26756	103	1	the	the	DET
ajst-26756	103	2	experimental	experimental	ADJ
ajst-26756	103	3	results	result	NOUN
ajst-26756	103	4	show	show	VERB
ajst-26756	103	5	that	that	SCONJ
ajst-26756	103	6	the	the	DET
ajst-26756	103	7	proposed	propose	VERB
ajst-26756	103	8	sem	sem	NOUN
ajst-26756	103	9	-	-	PUNCT
ajst-26756	103	10	yolov8n	yolov8n	NOUN
ajst-26756	103	11	outperforms	outperform	VERB
ajst-26756	103	12	other	other	ADJ
ajst-26756	103	13	state	state	NOUN
ajst-26756	103	14	-	-	PUNCT
ajst-26756	103	15	of	of	ADP
ajst-26756	103	16	-	-	PUNCT
ajst-26756	103	17	the	the	DET
ajst-26756	103	18	-	-	PUNCT
ajst-26756	103	19	art	art	NOUN
ajst-26756	103	20	detectors	detector	NOUN
ajst-26756	103	21	in	in	ADP
ajst-26756	103	22	all	all	DET
ajst-26756	103	23	quantitative	quantitative	ADJ
ajst-26756	103	24	indexes	index	NOUN
ajst-26756	103	25	,	,	PUNCT
ajst-26756	103	26	so	so	CCONJ
ajst-26756	103	27	the	the	DET
ajst-26756	103	28	deep	deep	ADJ
ajst-26756	103	29	learning	learning	NOUN
ajst-26756	103	30	model	model	NOUN
ajst-26756	103	31	proposed	propose	VERB
ajst-26756	103	32	in	in	ADP
ajst-26756	103	33	this	this	DET
ajst-26756	103	34	paper	paper	NOUN
ajst-26756	103	35	has	have	VERB
ajst-26756	103	36	certain	certain	ADJ
ajst-26756	103	37	advantages	advantage	NOUN
ajst-26756	103	38	in	in	ADP
ajst-26756	103	39	defect	defect	NOUN
ajst-26756	103	40	detection	detection	NOUN
ajst-26756	103	41	and	and	CCONJ
ajst-26756	103	42	provides	provide	VERB
ajst-26756	103	43	a	a	DET
ajst-26756	103	44	practical	practical	ADJ
ajst-26756	103	45	solution	solution	NOUN
ajst-26756	103	46	for	for	ADP
ajst-26756	103	47	the	the	DET
ajst-26756	103	48	research	research	NOUN
ajst-26756	103	49	and	and	CCONJ
ajst-26756	103	50	application	application	NOUN
ajst-26756	103	51	of	of	ADP
ajst-26756	103	52	road	road	NOUN
ajst-26756	103	53	defect	defect	NOUN
ajst-26756	103	54	detection	detection	NOUN
ajst-26756	103	55	.	.	PUNCT
ajst-26756	104	1	references	reference	NOUN
ajst-26756	104	2	[	[	X
ajst-26756	104	3	1	1	NUM
ajst-26756	104	4	]	]	X
ajst-26756	104	5	n.	n.	PROPN
ajst-26756	104	6	ahmad	ahmad	PROPN
ajst-26756	104	7	,	,	PUNCT
ajst-26756	104	8	m.	m.	NOUN
ajst-26756	104	9	wistuba	wistuba	PROPN
ajst-26756	104	10	and	and	CCONJ
ajst-26756	104	11	h.	h.	PROPN
ajst-26756	104	12	lorenzl	lorenzl	PROPN
ajst-26756	104	13	,	,	PUNCT
ajst-26756	104	14	gpr	gpr	PROPN
ajst-26756	104	15	as	as	ADP
ajst-26756	104	16	a	a	DET
ajst-26756	104	17	crack	crack	NOUN
ajst-26756	104	18	detection	detection	NOUN
ajst-26756	104	19	tool	tool	NOUN
ajst-26756	104	20	for	for	ADP
ajst-26756	104	21	asphalt	asphalt	NOUN
ajst-26756	104	22	pavements	pavement	NOUN
ajst-26756	104	23	:	:	PUNCT
ajst-26756	104	24	possibilities	possibility	NOUN
ajst-26756	104	25	and	and	CCONJ
ajst-26756	104	26	limitations	limitation	NOUN
ajst-26756	104	27	,	,	PUNCT
ajst-26756	104	28	2012	2012	NUM
ajst-26756	104	29	14th	14th	ADJ
ajst-26756	104	30	international	international	ADJ
ajst-26756	104	31	conference	conference	NOUN
ajst-26756	104	32	on	on	ADP
ajst-26756	104	33	ground	ground	NOUN
ajst-26756	104	34	penetrating	penetrate	VERB
ajst-26756	104	35	radar	radar	NOUN
ajst-26756	104	36	(	(	PUNCT
ajst-26756	104	37	gpr	gpr	PROPN
ajst-26756	104	38	)	)	PUNCT
ajst-26756	104	39	,	,	PUNCT
ajst-26756	104	40	shanghai	shanghai	PROPN
ajst-26756	104	41	,	,	PUNCT
ajst-26756	104	42	china	china	PROPN
ajst-26756	104	43	,	,	PUNCT
ajst-26756	104	44	2012	2012	NUM
ajst-26756	104	45	,	,	PUNCT
ajst-26756	104	46	pp	pp	ADJ
ajst-26756	104	47	.	.	PUNCT
ajst-26756	105	1	551	551	NUM
ajst-26756	105	2	-	-	SYM
ajst-26756	105	3	555	555	NUM
ajst-26756	105	4	,	,	PUNCT
ajst-26756	105	5	doi	doi	NOUN
ajst-26756	105	6	:	:	PUNCT
ajst-26756	105	7	10.1109	10.1109	NUM
ajst-26756	105	8	/	/	SYM
ajst-26756	105	9	icgpr.2012.6254925	icgpr.2012.6254925	PROPN
ajst-26756	105	10	.	.	PUNCT
ajst-26756	106	1	[	[	X
ajst-26756	106	2	2	2	NUM
ajst-26756	106	3	]	]	X
ajst-26756	106	4	zhao	zhao	PROPN
ajst-26756	106	5	h	h	NOUN
ajst-26756	106	6	,	,	PUNCT
ajst-26756	106	7	qin	qin	PROPN
ajst-26756	106	8	g	g	PROPN
ajst-26756	106	9	,	,	PUNCT
ajst-26756	106	10	wang	wang	PROPN
ajst-26756	106	11	x.	x.	NOUN
ajst-26756	106	12	improvement	improvement	NOUN
ajst-26756	106	13	of	of	ADP
ajst-26756	106	14	canny	canny	ADJ
ajst-26756	106	15	algorithm	algorithm	NOUN
ajst-26756	106	16	based	base	VERB
ajst-26756	106	17	on	on	ADP
ajst-26756	106	18	pavement	pavement	NOUN
ajst-26756	106	19	edge	edge	NOUN
ajst-26756	106	20	detection[c]//2010	detection[c]//2010	ADP
ajst-26756	106	21	3rd	3rd	PROPN
ajst-26756	106	22	international	international	ADJ
ajst-26756	106	23	congress	congress	PROPN
ajst-26756	106	24	on	on	ADP
ajst-26756	106	25	image	image	NOUN
ajst-26756	106	26	and	and	CCONJ
ajst-26756	106	27	signal	signal	NOUN
ajst-26756	106	28	processing	processing	NOUN
ajst-26756	106	29	.	.	PUNCT
ajst-26756	107	1	ieee	ieee	PROPN
ajst-26756	107	2	,	,	PUNCT
ajst-26756	107	3	2010	2010	NUM
ajst-26756	107	4	,	,	PUNCT
ajst-26756	107	5	2	2	NUM
ajst-26756	107	6	:	:	SYM
ajst-26756	107	7	964967	964967	NUM
ajst-26756	107	8	.	.	PUNCT
ajst-26756	108	1	[	[	X
ajst-26756	108	2	3	3	X
ajst-26756	108	3	]	]	X
ajst-26756	108	4	peng	peng	PROPN
ajst-26756	108	5	c	c	PROPN
ajst-26756	108	6	,	,	PUNCT
ajst-26756	108	7	yang	yang	PROPN
ajst-26756	108	8	m	m	PROPN
ajst-26756	108	9	,	,	PUNCT
ajst-26756	108	10	zheng	zheng	PROPN
ajst-26756	108	11	q	q	PROPN
ajst-26756	108	12	,	,	PUNCT
ajst-26756	108	13	et	et	PROPN
ajst-26756	108	14	al	al	PROPN
ajst-26756	108	15	.	.	PUNCT
ajst-26756	109	1	a	a	DET
ajst-26756	109	2	triple	triple	ADJ
ajst-26756	109	3	-	-	PUNCT
ajst-26756	109	4	thresholds	thresholds	NOUN
ajst-26756	109	5	pavement	pavement	NOUN
ajst-26756	109	6	crack	crack	NOUN
ajst-26756	109	7	detection	detection	NOUN
ajst-26756	109	8	method	method	NOUN
ajst-26756	109	9	leveraging	leverage	VERB
ajst-26756	109	10	random	random	ADJ
ajst-26756	109	11	structured	structured	ADJ
ajst-26756	109	12	forest[j	forest[j	NOUN
ajst-26756	109	13	]	]	PUNCT
ajst-26756	109	14	.	.	PUNCT
ajst-26756	110	1	construction	construction	NOUN
ajst-26756	110	2	and	and	CCONJ
ajst-26756	110	3	building	building	NOUN
ajst-26756	110	4	materials	material	NOUN
ajst-26756	110	5	,	,	PUNCT
ajst-26756	110	6	2020	2020	NUM
ajst-26756	110	7	,	,	PUNCT
ajst-26756	110	8	263	263	NUM
ajst-26756	110	9	:	:	SYM
ajst-26756	110	10	120080	120080	NUM
ajst-26756	110	11	.	.	PUNCT
ajst-26756	111	1	[	[	X
ajst-26756	111	2	4	4	X
ajst-26756	111	3	]	]	PUNCT
ajst-26756	111	4	landstrom	landstrom	ADP
ajst-26756	111	5	a	a	DET
ajst-26756	111	6	,	,	PUNCT
ajst-26756	111	7	thurley	thurley	PROPN
ajst-26756	111	8	m	m	VERB
ajst-26756	111	9	j.	j.	PROPN
ajst-26756	111	10	morphology	morphology	PROPN
ajst-26756	111	11	-	-	PUNCT
ajst-26756	111	12	based	base	VERB
ajst-26756	111	13	crack	crack	NOUN
ajst-26756	111	14	detection	detection	NOUN
ajst-26756	111	15	for	for	ADP
ajst-26756	111	16	steel	steel	NOUN
ajst-26756	111	17	slabs[j	slabs[j	PROPN
ajst-26756	111	18	]	]	PUNCT
ajst-26756	111	19	.	.	PUNCT
ajst-26756	112	1	ieee	ieee	PROPN
ajst-26756	112	2	journal	journal	PROPN
ajst-26756	112	3	of	of	ADP
ajst-26756	112	4	selected	select	VERB
ajst-26756	112	5	topics	topic	NOUN
ajst-26756	112	6	in	in	ADP
ajst-26756	112	7	signal	signal	ADJ
ajst-26756	112	8	processing	processing	NOUN
ajst-26756	112	9	,	,	PUNCT
ajst-26756	112	10	2012	2012	NUM
ajst-26756	112	11	,	,	PUNCT
ajst-26756	112	12	6(7	6(7	NUM
ajst-26756	112	13	):	):	PUNCT
ajst-26756	112	14	866	866	NUM
ajst-26756	112	15	-	-	SYM
ajst-26756	112	16	875	875	NUM
ajst-26756	112	17	.	.	PUNCT
ajst-26756	113	1	[	[	X
ajst-26756	113	2	5	5	X
ajst-26756	113	3	]	]	PUNCT
ajst-26756	113	4	yang	yang	PROPN
ajst-26756	113	5	l	l	PROPN
ajst-26756	113	6	,	,	PUNCT
ajst-26756	113	7	deng	deng	PROPN
ajst-26756	113	8	j	j	PROPN
ajst-26756	113	9	,	,	PUNCT
ajst-26756	113	10	duan	duan	PROPN
ajst-26756	113	11	h	h	PROPN
ajst-26756	113	12	,	,	PUNCT
ajst-26756	113	13	et	et	PROPN
ajst-26756	113	14	al	al	PROPN
ajst-26756	113	15	.	.	PROPN
ajst-26756	113	16	tunnel	tunnel	PROPN
ajst-26756	113	17	water	water	NOUN
ajst-26756	113	18	leakage	leakage	NOUN
ajst-26756	113	19	detection	detection	NOUN
ajst-26756	113	20	method	method	NOUN
ajst-26756	113	21	based	base	VERB
ajst-26756	113	22	on	on	ADP
ajst-26756	113	23	eca	eca	NOUN
ajst-26756	113	24	and	and	CCONJ
ajst-26756	113	25	yolov5	yolov5	NOUN
ajst-26756	114	1	[	[	X
ajst-26756	114	2	j	j	X
ajst-26756	114	3	]	]	X
ajst-26756	114	4	.	.	PUNCT
ajst-26756	115	1	journal	journal	PROPN
ajst-26756	115	2	of	of	ADP
ajst-26756	115	3	tianjin	tianjin	PROPN
ajst-26756	115	4	university	university	PROPN
ajst-26756	115	5	of	of	ADP
ajst-26756	115	6	technology	technology	NOUN
ajst-26756	115	7	and	and	CCONJ
ajst-26756	115	8	education	education	NOUN
ajst-26756	115	9	,	,	PUNCT
ajst-26756	115	10	2024,34(02):19	2024,34(02):19	NUM
ajst-26756	115	11	-	-	SYM
ajst-26756	115	12	24	24	NUM
ajst-26756	115	13	.	.	PUNCT
ajst-26756	116	1	doi:10.19573	doi:10.19573	PROPN
ajst-26756	116	2	/	/	SYM
ajst-26756	116	3	j.issn20950926.202402003	j.issn20950926.202402003	PROPN
ajst-26756	116	4	.	.	PUNCT
ajst-26756	117	1	[	[	X
ajst-26756	117	2	6	6	NUM
ajst-26756	117	3	]	]	X
ajst-26756	117	4	deng	deng	PROPN
ajst-26756	117	5	j	j	PROPN
ajst-26756	117	6	,	,	PUNCT
ajst-26756	117	7	lu	lu	PROPN
ajst-26756	117	8	y	y	PROPN
ajst-26756	117	9	,	,	PUNCT
ajst-26756	117	10	lee	lee	PROPN
ajst-26756	117	11	v	v	PROPN
ajst-26756	117	12	c	c	PROPN
ajst-26756	117	13	s.	s.	PROPN
ajst-26756	117	14	concrete	concrete	PROPN
ajst-26756	117	15	crack	crack	NOUN
ajst-26756	117	16	detection	detection	NOUN
ajst-26756	117	17	with	with	ADP
ajst-26756	117	18	handwriting	handwriting	NOUN
ajst-26756	117	19	script	script	NOUN
ajst-26756	117	20	interferences	interference	NOUN
ajst-26756	117	21	using	use	VERB
ajst-26756	117	22	faster	fast	ADV
ajst-26756	117	23	region‐based	region‐base	VERB
ajst-26756	117	24	convolutional	convolutional	ADJ
ajst-26756	117	25	neural	neural	ADJ
ajst-26756	117	26	network[j	network[j	NOUN
ajst-26756	117	27	]	]	PUNCT
ajst-26756	117	28	.	.	PUNCT
ajst-26756	118	1	computer‐aided	computer‐aide	VERB
ajst-26756	118	2	civil	civil	ADJ
ajst-26756	118	3	and	and	CCONJ
ajst-26756	118	4	infrastructure	infrastructure	NOUN
ajst-26756	118	5	engineering	engineering	NOUN
ajst-26756	118	6	,	,	PUNCT
ajst-26756	118	7	2020	2020	NUM
ajst-26756	118	8	,	,	PUNCT
ajst-26756	118	9	35(4	35(4	NUM
ajst-26756	118	10	):	):	PUNCT
ajst-26756	118	11	373	373	NUM
ajst-26756	118	12	-	-	SYM
ajst-26756	118	13	388	388	NUM
ajst-26756	118	14	.	.	PUNCT
ajst-26756	119	1	[	[	X
ajst-26756	119	2	7	7	X
ajst-26756	119	3	]	]	X
ajst-26756	119	4	wang	wang	PROPN
ajst-26756	119	5	s	s	PROPN
ajst-26756	119	6	,	,	PUNCT
ajst-26756	119	7	dong	dong	PROPN
ajst-26756	119	8	q	q	PROPN
ajst-26756	119	9	,	,	PUNCT
ajst-26756	119	10	chen	chen	PROPN
ajst-26756	119	11	x	x	PROPN
ajst-26756	119	12	,	,	PUNCT
ajst-26756	119	13	et	et	PROPN
ajst-26756	119	14	al	al	PROPN
ajst-26756	119	15	.	.	PROPN
ajst-26756	119	16	measurement	measurement	PROPN
ajst-26756	119	17	of	of	ADP
ajst-26756	119	18	asphalt	asphalt	NOUN
ajst-26756	119	19	pavement	pavement	NOUN
ajst-26756	119	20	crack	crack	NOUN
ajst-26756	119	21	length	length	NOUN
ajst-26756	119	22	using	use	VERB
ajst-26756	119	23	yolo	yolo	ADJ
ajst-26756	119	24	v5	v5	PROPN
ajst-26756	119	25	-	-	PUNCT
ajst-26756	119	26	bifpn[j	bifpn[j	NOUN
ajst-26756	119	27	]	]	PUNCT
ajst-26756	119	28	.	.	PUNCT
ajst-26756	120	1	journal	journal	PROPN
ajst-26756	120	2	of	of	ADP
ajst-26756	120	3	infrastructure	infrastructure	NOUN
ajst-26756	120	4	systems	system	NOUN
ajst-26756	120	5	,	,	PUNCT
ajst-26756	120	6	2024	2024	NUM
ajst-26756	120	7	,	,	PUNCT
ajst-26756	120	8	30(2	30(2	NUM
ajst-26756	120	9	):	):	PUNCT
ajst-26756	120	10	04024005	04024005	NUM
ajst-26756	120	11	.	.	PUNCT
ajst-26756	121	1	[	[	X
ajst-26756	121	2	8	8	NUM
ajst-26756	121	3	]	]	X
ajst-26756	121	4	zheng	zheng	PROPN
ajst-26756	121	5	x	x	PROPN
ajst-26756	121	6	,	,	PUNCT
ajst-26756	121	7	qian	qian	PROPN
ajst-26756	121	8	s	s	PROPN
ajst-26756	121	9	,	,	PUNCT
ajst-26756	121	10	wei	wei	PROPN
ajst-26756	121	11	s	s	PROPN
ajst-26756	121	12	,	,	PUNCT
ajst-26756	121	13	et	et	PROPN
ajst-26756	121	14	al	al	PROPN
ajst-26756	121	15	.	.	PUNCT
ajst-26756	122	1	the	the	DET
ajst-26756	122	2	combination	combination	NOUN
ajst-26756	122	3	of	of	ADP
ajst-26756	122	4	transformer	transformer	NOUN
ajst-26756	122	5	and	and	CCONJ
ajst-26756	122	6	you	you	PRON
ajst-26756	122	7	only	only	ADV
ajst-26756	122	8	look	look	VERB
ajst-26756	122	9	once	once	ADV
ajst-26756	122	10	for	for	ADP
ajst-26756	122	11	automatic	automatic	ADJ
ajst-26756	122	12	concrete	concrete	ADJ
ajst-26756	122	13	pavement	pavement	NOUN
ajst-26756	122	14	crack	crack	VERB
ajst-26756	122	15	detection[j	detection[j	PROPN
ajst-26756	122	16	]	]	PUNCT
ajst-26756	122	17	.	.	PUNCT
ajst-26756	123	1	applied	apply	VERB
ajst-26756	123	2	sciences	science	NOUN
ajst-26756	123	3	,	,	PUNCT
ajst-26756	123	4	2023	2023	NUM
ajst-26756	123	5	,	,	PUNCT
ajst-26756	123	6	13(16	13(16	NUM
ajst-26756	123	7	):	):	PUNCT
ajst-26756	123	8	9211	9211	NUM
ajst-26756	123	9	.	.	PUNCT
ajst-26756	124	1	[	[	X
ajst-26756	124	2	9	9	NUM
ajst-26756	124	3	]	]	X
ajst-26756	124	4	luo	luo	PROPN
ajst-26756	124	5	h	h	PROPN
ajst-26756	124	6	,	,	PUNCT
ajst-26756	124	7	li	li	PROPN
ajst-26756	124	8	j	j	PROPN
ajst-26756	124	9	,	,	PUNCT
ajst-26756	124	10	cai	cai	PROPN
ajst-26756	124	11	l	l	PROPN
ajst-26756	124	12	,	,	PUNCT
ajst-26756	124	13	et	et	PROPN
ajst-26756	124	14	al	al	PROPN
ajst-26756	124	15	.	.	PROPN
ajst-26756	124	16	strans	strans	PROPN
ajst-26756	124	17	-	-	PUNCT
ajst-26756	124	18	yolox	yolox	NOUN
ajst-26756	124	19	:	:	PUNCT
ajst-26756	124	20	fusing	fuse	VERB
ajst-26756	124	21	swin	swin	PROPN
ajst-26756	124	22	transformer	transformer	NOUN
ajst-26756	124	23	and	and	CCONJ
ajst-26756	124	24	yolox	yolox	NOUN
ajst-26756	124	25	for	for	ADP
ajst-26756	124	26	automatic	automatic	ADJ
ajst-26756	124	27	pavement	pavement	NOUN
ajst-26756	124	28	crack	crack	VERB
ajst-26756	124	29	detection[j	detection[j	PROPN
ajst-26756	124	30	]	]	PUNCT
ajst-26756	124	31	.	.	PUNCT
ajst-26756	125	1	applied	apply	VERB
ajst-26756	125	2	sciences	science	NOUN
ajst-26756	125	3	,	,	PUNCT
ajst-26756	125	4	2023	2023	NUM
ajst-26756	125	5	,	,	PUNCT
ajst-26756	125	6	13(3	13(3	NUM
ajst-26756	125	7	):	):	PUNCT
ajst-26756	125	8	1999	1999	NUM
ajst-26756	125	9	.	.	PUNCT
ajst-26756	126	1	[	[	X
ajst-26756	126	2	10	10	NUM
ajst-26756	126	3	]	]	SYM
ajst-26756	126	4	sunkararaja	sunkararaja	NOUN
ajst-26756	126	5	,	,	PUNCT
ajst-26756	126	6	luotie	luotie	PROPN
ajst-26756	126	7	.	.	PUNCT
ajst-26756	127	1	no	no	DET
ajst-26756	127	2	more	more	ADV
ajst-26756	127	3	strided	strided	ADJ
ajst-26756	127	4	convolutions	convolution	NOUN
ajst-26756	127	5	or	or	CCONJ
ajst-26756	127	6	pooling	pooling	NOUN
ajst-26756	127	7	:	:	PUNCT
ajst-26756	127	8	a	a	DET
ajst-26756	127	9	new	new	ADJ
ajst-26756	127	10	cnn	cnn	PROPN
ajst-26756	127	11	building	building	NOUN
ajst-26756	127	12	block	block	NOUN
ajst-26756	127	13	for	for	ADP
ajst-26756	127	14	low	low	ADJ
ajst-26756	127	15	-	-	PUNCT
ajst-26756	127	16	resolution	resolution	NOUN
ajst-26756	127	17	images	image	NOUN
ajst-26756	127	18	and	and	CCONJ
ajst-26756	127	19	small	small	ADJ
ajst-26756	127	20	objects	object	NOUN
ajst-26756	127	21	c.	c.	NOUN
ajst-26756	127	22	machine	machine	NOUN
ajst-26756	127	23	learning	learning	NOUN
ajst-26756	127	24	and	and	CCONJ
ajst-26756	127	25	knowledge	knowledge	NOUN
ajst-26756	127	26	discovery	discovery	NOUN
ajst-26756	127	27	in	in	ADP
ajst-26756	127	28	databases	database	NOUN
ajst-26756	127	29	:	:	PUNCT
ajst-26756	127	30	european	european	ADJ
ajst-26756	127	31	conference	conference	NOUN
ajst-26756	127	32	,	,	PUNCT
ajst-26756	127	33	ecml	ecml	PROPN
ajst-26756	127	34	pkdd	pkdd	NOUN
ajst-26756	127	35	2022	2022	NUM
ajst-26756	127	36	,	,	PUNCT
ajst-26756	127	37	grenoble	grenoble	ADJ
ajst-26756	127	38	,	,	PUNCT
ajst-26756	127	39	f	f	X
ajst-26756	127	40	-	-	PUNCT
ajst-26756	127	41	rance,2022:443	rance,2022:443	NOUN
ajst-26756	127	42	-	-	PUNCT
ajst-26756	127	43	459	459	NUM
ajst-26756	127	44	.	.	PUNCT
ajst-26756	128	1	[	[	X
ajst-26756	128	2	11	11	NUM
ajst-26756	128	3	]	]	X
ajst-26756	128	4	ouyang	ouyang	PROPN
ajst-26756	128	5	d	d	PROPN
ajst-26756	128	6	,	,	PUNCT
ajst-26756	128	7	he	he	PRON
ajst-26756	128	8	s	s	PART
ajst-26756	128	9	,	,	PUNCT
ajst-26756	128	10	zhang	zhang	PROPN
ajst-26756	128	11	g	g	PROPN
ajst-26756	128	12	,	,	PUNCT
ajst-26756	128	13	et	et	PROPN
ajst-26756	128	14	al	al	PROPN
ajst-26756	128	15	.	.	PROPN
ajst-26756	129	1	efficient	efficient	ADJ
ajst-26756	129	2	multi	multi	ADJ
ajst-26756	129	3	-	-	ADJ
ajst-26756	129	4	scale	scale	ADJ
ajst-26756	129	5	attention	attention	NOUN
ajst-26756	129	6	module	module	NOUN
ajst-26756	129	7	with	with	ADP
ajst-26756	129	8	cross	cross	ADJ
ajst-26756	129	9	-	-	ADJ
ajst-26756	129	10	spatial	spatial	ADJ
ajst-26756	129	11	learning[c]//icassp	learning[c]//icassp	PROPN
ajst-26756	129	12	2023	2023	NUM
ajst-26756	129	13	-	-	SYM
ajst-26756	129	14	2023	2023	NUM
ajst-26756	129	15	ieee	ieee	NOUN
ajst-26756	129	16	international	international	ADJ
ajst-26756	129	17	conference	conference	NOUN
ajst-26756	129	18	on	on	ADP
ajst-26756	129	19	acoustics	acoustic	NOUN
ajst-26756	129	20	,	,	PUNCT
ajst-26756	129	21	speech	speech	NOUN
ajst-26756	129	22	and	and	CCONJ
ajst-26756	129	23	signal	signal	NOUN
ajst-26756	129	24	processing	processing	NOUN
ajst-26756	129	25	(	(	PUNCT
ajst-26756	129	26	icassp	icassp	PROPN
ajst-26756	129	27	)	)	PUNCT
ajst-26756	129	28	.	.	PUNCT
ajst-26756	130	1	ieee	ieee	NOUN
ajst-26756	130	2	,	,	PUNCT
ajst-26756	130	3	2023	2023	NUM
ajst-26756	130	4	:	:	PUNCT
ajst-26756	130	5	1	1	NUM
ajst-26756	130	6	-	-	SYM
ajst-26756	130	7	5	5	NUM
ajst-26756	130	8	.	.	PUNCT
ajst-26756	131	1	[	[	X
ajst-26756	131	2	12	12	NUM
ajst-26756	131	3	]	]	X
ajst-26756	131	4	chen	chen	PROPN
ajst-26756	131	5	s	s	PROPN
ajst-26756	131	6	,	,	PUNCT
ajst-26756	131	7	li	li	PROPN
ajst-26756	131	8	y	y	PROPN
ajst-26756	131	9	,	,	PUNCT
ajst-26756	131	10	zhang	zhang	PROPN
ajst-26756	131	11	y	y	PROPN
ajst-26756	131	12	,	,	PUNCT
ajst-26756	131	13	et	et	PROPN
ajst-26756	131	14	al	al	PROPN
ajst-26756	131	15	.	.	PROPN
ajst-26756	131	16	soft	soft	ADJ
ajst-26756	131	17	x	x	ADJ
ajst-26756	131	18	-	-	NOUN
ajst-26756	131	19	ray	ray	NOUN
ajst-26756	131	20	image	image	NOUN
ajst-26756	131	21	recognition	recognition	NOUN
ajst-26756	131	22	and	and	CCONJ
ajst-26756	131	23	classification	classification	NOUN
ajst-26756	131	24	of	of	ADP
ajst-26756	131	25	maize	maize	NOUN
ajst-26756	131	26	seed	seed	NOUN
ajst-26756	131	27	cracks	crack	NOUN
ajst-26756	131	28	based	base	VERB
ajst-26756	131	29	on	on	ADP
ajst-26756	131	30	image	image	NOUN
ajst-26756	131	31	enhancement	enhancement	NOUN
ajst-26756	131	32	and	and	CCONJ
ajst-26756	131	33	optimized	optimize	VERB
ajst-26756	131	34	yolov8	yolov8	NOUN
ajst-26756	131	35	model[j	model[j	PROPN
ajst-26756	131	36	]	]	PUNCT
ajst-26756	131	37	.	.	PUNCT
ajst-26756	132	1	computers	computer	NOUN
ajst-26756	132	2	and	and	CCONJ
ajst-26756	132	3	electronics	electronic	NOUN
ajst-26756	132	4	in	in	ADP
ajst-26756	132	5	agriculture	agriculture	NOUN
ajst-26756	132	6	,	,	PUNCT
ajst-26756	132	7	2024	2024	NUM
ajst-26756	132	8	,	,	PUNCT
ajst-26756	132	9	216	216	NUM
ajst-26756	132	10	:	:	SYM
ajst-26756	132	11	108475	108475	NUM
ajst-26756	132	12	.	.	PUNCT
ajst-26756	133	1	[	[	X
ajst-26756	133	2	13	13	NUM
ajst-26756	133	3	]	]	X
ajst-26756	133	4	liu	liu	PROPN
ajst-26756	133	5	,	,	PUNCT
ajst-26756	133	6	lu	lu	PROPN
ajst-26756	133	7	a	a	X
ajst-26756	133	8	,	,	PUNCT
ajst-26756	133	9	cui	cui	NOUN
ajst-26756	133	10	h	h	NOUN
ajst-26756	133	11	,	,	PUNCT
ajst-26756	133	12	et	et	PROPN
ajst-26756	133	13	al	al	PROPN
ajst-26756	133	14	.	.	PUNCT
ajst-26756	133	15	lightweight	lightweight	ADJ
ajst-26756	133	16	model	model	NOUN
ajst-26756	133	17	for	for	ADP
ajst-26756	133	18	detecting	detect	VERB
ajst-26756	133	19	lotus	lotus	PROPN
ajst-26756	133	20	leaf	leaf	NOUN
ajst-26756	133	21	diseases	disease	NOUN
ajst-26756	133	22	and	and	CCONJ
ajst-26756	133	23	pests	pest	NOUN
ajst-26756	133	24	using	use	VERB
ajst-26756	133	25	improved	improved	ADJ
ajst-26756	133	26	yolov8[j	yolov8[j	NOUN
ajst-26756	133	27	]	]	PUNCT
ajst-26756	133	28	.	.	PUNCT
ajst-26756	134	1	transactions	transaction	NOUN
ajst-26756	134	2	of	of	ADP
ajst-26756	134	3	the	the	DET
ajst-26756	134	4	chinese	chinese	ADJ
ajst-26756	134	5	society	society	NOUN
ajst-26756	134	6	of	of	ADP
ajst-26756	134	7	agricultural	agricultural	ADJ
ajst-26756	134	8	engineering	engineering	NOUN
ajst-26756	134	9	(	(	PUNCT
ajst-26756	134	10	transactions	transaction	NOUN
ajst-26756	134	11	of	of	ADP
ajst-26756	134	12	the	the	DET
ajst-26756	134	13	csae	csae	NOUN
ajst-26756	134	14	)	)	PUNCT
ajst-26756	134	15	,	,	PUNCT
ajst-26756	134	16	2024	2024	NUM
ajst-26756	134	17	,	,	PUNCT
ajst-26756	134	18	40(19	40(19	NUM
ajst-26756	134	19	):	):	PUNCT
ajst-26756	134	20	168176	168176	NUM
ajst-26756	134	21	.	.	PUNCT
ajst-26756	135	1	[	[	X
ajst-26756	135	2	14	14	NUM
ajst-26756	135	3	]	]	X
ajst-26756	135	4	ma	ma	PROPN
ajst-26756	135	5	s	s	PROPN
ajst-26756	135	6	,	,	PUNCT
ajst-26756	135	7	xu	xu	PROPN
ajst-26756	135	8	y.	y.	PROPN
ajst-26756	135	9	mpdiou	mpdiou	PROPN
ajst-26756	135	10	:	:	PUNCT
ajst-26756	135	11	a	a	DET
ajst-26756	135	12	loss	loss	NOUN
ajst-26756	135	13	for	for	ADP
ajst-26756	135	14	efficient	efficient	ADJ
ajst-26756	135	15	and	and	CCONJ
ajst-26756	135	16	accurate	accurate	ADJ
ajst-26756	135	17	bounding	bounding	NOUN
ajst-26756	135	18	box	box	NOUN
ajst-26756	135	19	regression[j	regression[j	PROPN
ajst-26756	135	20	]	]	PUNCT
ajst-26756	135	21	.	.	PUNCT
ajst-26756	136	1	arxiv	arxiv	PROPN
ajst-26756	136	2	preprint	preprint	PROPN
ajst-26756	136	3	arxiv:2307.07662	arxiv:2307.07662	NOUN
ajst-26756	136	4	,	,	PUNCT
ajst-26756	136	5	2023	2023	NUM
ajst-26756	136	6	.	.	PUNCT