id	sid	tid	token	lemma	pos
ajst-25804	1	1	academic	academic	ADJ
ajst-25804	1	2	journal	journal	NOUN
ajst-25804	1	3	of	of	ADP
ajst-25804	1	4	science	science	NOUN
ajst-25804	1	5	and	and	CCONJ
ajst-25804	1	6	technology	technology	NOUN
ajst-25804	1	7	issn	issn	NOUN
ajst-25804	1	8	:	:	PUNCT
ajst-25804	1	9	2771	2771	NUM
ajst-25804	1	10	-	-	SYM
ajst-25804	1	11	3032	3032	NUM
ajst-25804	1	12	|	|	NOUN
ajst-25804	1	13	vol	vol	NOUN
ajst-25804	1	14	.	.	PROPN
ajst-25804	2	1	12	12	NUM
ajst-25804	2	2	,	,	PUNCT
ajst-25804	2	3	no	no	INTJ
ajst-25804	2	4	.	.	NOUN
ajst-25804	2	5	3	3	NUM
ajst-25804	2	6	,	,	PUNCT
ajst-25804	2	7	2024	2024	NUM
ajst-25804	2	8	12	12	NUM
ajst-25804	2	9	complex	complex	ADJ
ajst-25804	2	10	scene	scene	NOUN
ajst-25804	2	11	understanding	understanding	NOUN
ajst-25804	2	12	and	and	CCONJ
ajst-25804	2	13	object	object	VERB
ajst-25804	2	14	detection	detection	NOUN
ajst-25804	2	15	algorithm	algorithm	NOUN
ajst-25804	2	16	assisted	assist	VERB
ajst-25804	2	17	by	by	ADP
ajst-25804	2	18	artificial	artificial	ADJ
ajst-25804	2	19	intelligence	intelligence	NOUN
ajst-25804	2	20	binrong	binrong	PROPN
ajst-25804	2	21	zhu1	zhu1	PROPN
ajst-25804	2	22	,	,	PUNCT
ajst-25804	2	23	a	a	DET
ajst-25804	2	24	,	,	PUNCT
ajst-25804	2	25	guiran	guiran	NOUN
ajst-25804	2	26	liu1	liu1	PROPN
ajst-25804	2	27	,	,	PUNCT
ajst-25804	2	28	b	b	PROPN
ajst-25804	2	29	1san	1san	NUM
ajst-25804	2	30	francisco	francisco	PROPN
ajst-25804	2	31	state	state	PROPN
ajst-25804	2	32	university	university	PROPN
ajst-25804	2	33	,	,	PUNCT
ajst-25804	2	34	college	college	NOUN
ajst-25804	2	35	of	of	ADP
ajst-25804	2	36	science	science	PROPN
ajst-25804	2	37	&	&	CCONJ
ajst-25804	2	38	engineering	engineering	PROPN
ajst-25804	2	39	(	(	PUNCT
ajst-25804	2	40	cose	cose	PROPN
ajst-25804	2	41	)	)	PUNCT
ajst-25804	2	42	,	,	PUNCT
ajst-25804	2	43	san	san	PROPN
ajst-25804	2	44	francisco	francisco	PROPN
ajst-25804	2	45	,	,	PUNCT
ajst-25804	2	46	united	united	PROPN
ajst-25804	2	47	states	states	PROPN
ajst-25804	2	48	abzhu2@sfsu.edu	abzhu2@sfsu.edu	PROPN
ajst-25804	2	49	,	,	PUNCT
ajst-25804	2	50	bgliu@sfsu.edu	bgliu@sfsu.edu	PROPN
ajst-25804	3	1	abstract	abstract	ADJ
ajst-25804	3	2	:	:	PUNCT
ajst-25804	3	3	the	the	DET
ajst-25804	3	4	purpose	purpose	NOUN
ajst-25804	3	5	of	of	ADP
ajst-25804	3	6	this	this	DET
ajst-25804	3	7	paper	paper	NOUN
ajst-25804	3	8	is	be	AUX
ajst-25804	3	9	to	to	PART
ajst-25804	3	10	study	study	VERB
ajst-25804	3	11	the	the	DET
ajst-25804	3	12	algorithm	algorithm	NOUN
ajst-25804	3	13	of	of	ADP
ajst-25804	3	14	object	object	NOUN
ajst-25804	3	15	detection	detection	NOUN
ajst-25804	3	16	and	and	CCONJ
ajst-25804	3	17	scene	scene	NOUN
ajst-25804	3	18	understanding	understanding	NOUN
ajst-25804	3	19	in	in	ADP
ajst-25804	3	20	complex	complex	ADJ
ajst-25804	3	21	scenes	scene	NOUN
ajst-25804	3	22	assisted	assist	VERB
ajst-25804	3	23	by	by	ADP
ajst-25804	3	24	ai(artificial	ai(artificial	ADJ
ajst-25804	3	25	intelligence	intelligence	NOUN
ajst-25804	3	26	)	)	PUNCT
ajst-25804	3	27	,	,	PUNCT
ajst-25804	3	28	so	so	SCONJ
ajst-25804	3	29	as	as	SCONJ
ajst-25804	3	30	to	to	PART
ajst-25804	3	31	improve	improve	VERB
ajst-25804	3	32	the	the	DET
ajst-25804	3	33	machine	machine	NOUN
ajst-25804	3	34	's	's	PART
ajst-25804	3	35	perception	perception	NOUN
ajst-25804	3	36	of	of	ADP
ajst-25804	3	37	the	the	DET
ajst-25804	3	38	surrounding	surround	VERB
ajst-25804	3	39	environment	environment	NOUN
ajst-25804	3	40	.	.	PUNCT
ajst-25804	4	1	aiming	aim	VERB
ajst-25804	4	2	at	at	ADP
ajst-25804	4	3	occlusion	occlusion	NOUN
ajst-25804	4	4	and	and	CCONJ
ajst-25804	4	5	dense	dense	ADJ
ajst-25804	4	6	scenes	scene	NOUN
ajst-25804	4	7	,	,	PUNCT
ajst-25804	4	8	this	this	DET
ajst-25804	4	9	paper	paper	NOUN
ajst-25804	4	10	proposes	propose	VERB
ajst-25804	4	11	a	a	DET
ajst-25804	4	12	series	series	NOUN
ajst-25804	4	13	of	of	ADP
ajst-25804	4	14	innovative	innovative	ADJ
ajst-25804	4	15	algorithms	algorithm	NOUN
ajst-25804	4	16	by	by	ADP
ajst-25804	4	17	introducing	introduce	VERB
ajst-25804	4	18	technologies	technology	NOUN
ajst-25804	4	19	such	such	ADJ
ajst-25804	4	20	as	as	ADP
ajst-25804	4	21	multiscale	multiscale	ADJ
ajst-25804	4	22	detection	detection	NOUN
ajst-25804	4	23	,	,	PUNCT
ajst-25804	4	24	occlusion	occlusion	NOUN
ajst-25804	4	25	processing	processing	NOUN
ajst-25804	4	26	and	and	CCONJ
ajst-25804	4	27	real	real	ADJ
ajst-25804	4	28	-	-	PUNCT
ajst-25804	4	29	time	time	NOUN
ajst-25804	4	30	optimization	optimization	NOUN
ajst-25804	4	31	.	.	PUNCT
ajst-25804	5	1	experimental	experimental	ADJ
ajst-25804	5	2	results	result	NOUN
ajst-25804	5	3	show	show	VERB
ajst-25804	5	4	that	that	SCONJ
ajst-25804	5	5	the	the	DET
ajst-25804	5	6	proposed	propose	VERB
ajst-25804	5	7	algorithm	algorithm	NOUN
ajst-25804	5	8	has	have	AUX
ajst-25804	5	9	achieved	achieve	VERB
ajst-25804	5	10	excellent	excellent	ADJ
ajst-25804	5	11	performance	performance	NOUN
ajst-25804	5	12	on	on	ADP
ajst-25804	5	13	several	several	ADJ
ajst-25804	5	14	public	public	ADJ
ajst-25804	5	15	data	data	NOUN
ajst-25804	5	16	sets	set	NOUN
ajst-25804	5	17	.	.	PUNCT
ajst-25804	6	1	compared	compare	VERB
ajst-25804	6	2	with	with	ADP
ajst-25804	6	3	the	the	DET
ajst-25804	6	4	current	current	ADJ
ajst-25804	6	5	mainstream	mainstream	NOUN
ajst-25804	6	6	object	object	NOUN
ajst-25804	6	7	detection	detection	NOUN
ajst-25804	6	8	algorithm	algorithm	NOUN
ajst-25804	6	9	yolo	yolo	PROPN
ajst-25804	6	10	,	,	PUNCT
ajst-25804	6	11	the	the	DET
ajst-25804	6	12	method	method	NOUN
ajst-25804	6	13	proposed	propose	VERB
ajst-25804	6	14	in	in	ADP
ajst-25804	6	15	this	this	DET
ajst-25804	6	16	paper	paper	NOUN
ajst-25804	6	17	has	have	VERB
ajst-25804	6	18	a	a	DET
ajst-25804	6	19	significant	significant	ADJ
ajst-25804	6	20	improvement	improvement	NOUN
ajst-25804	6	21	in	in	ADP
ajst-25804	6	22	accuracy	accuracy	NOUN
ajst-25804	6	23	.	.	PUNCT
ajst-25804	7	1	especially	especially	ADV
ajst-25804	7	2	in	in	ADP
ajst-25804	7	3	multi	multi	ADJ
ajst-25804	7	4	-	-	ADJ
ajst-25804	7	5	scale	scale	ADJ
ajst-25804	7	6	object	object	NOUN
ajst-25804	7	7	detection	detection	NOUN
ajst-25804	7	8	,	,	PUNCT
ajst-25804	7	9	occlusion	occlusion	NOUN
ajst-25804	7	10	and	and	CCONJ
ajst-25804	7	11	dense	dense	ADJ
ajst-25804	7	12	scene	scene	NOUN
ajst-25804	7	13	processing	processing	NOUN
ajst-25804	7	14	and	and	CCONJ
ajst-25804	7	15	real	real	ADJ
ajst-25804	7	16	-	-	PUNCT
ajst-25804	7	17	time	time	NOUN
ajst-25804	7	18	optimization	optimization	NOUN
ajst-25804	7	19	,	,	PUNCT
ajst-25804	7	20	the	the	DET
ajst-25804	7	21	proposed	propose	VERB
ajst-25804	7	22	algorithm	algorithm	NOUN
ajst-25804	7	23	shows	show	VERB
ajst-25804	7	24	obvious	obvious	ADJ
ajst-25804	7	25	advantages	advantage	NOUN
ajst-25804	7	26	.	.	PUNCT
ajst-25804	8	1	the	the	DET
ajst-25804	8	2	research	research	NOUN
ajst-25804	8	3	results	result	NOUN
ajst-25804	8	4	provide	provide	VERB
ajst-25804	8	5	an	an	DET
ajst-25804	8	6	effective	effective	ADJ
ajst-25804	8	7	solution	solution	NOUN
ajst-25804	8	8	for	for	ADP
ajst-25804	8	9	object	object	NOUN
ajst-25804	8	10	detection	detection	NOUN
ajst-25804	8	11	and	and	CCONJ
ajst-25804	8	12	scene	scene	NOUN
ajst-25804	8	13	understanding	understanding	NOUN
ajst-25804	8	14	in	in	ADP
ajst-25804	8	15	complex	complex	ADJ
ajst-25804	8	16	scenes	scene	NOUN
ajst-25804	8	17	,	,	PUNCT
ajst-25804	8	18	and	and	CCONJ
ajst-25804	8	19	promote	promote	VERB
ajst-25804	8	20	the	the	DET
ajst-25804	8	21	application	application	NOUN
ajst-25804	8	22	of	of	ADP
ajst-25804	8	23	ai	ai	ADJ
ajst-25804	8	24	system	system	NOUN
ajst-25804	8	25	in	in	ADP
ajst-25804	8	26	related	related	ADJ
ajst-25804	8	27	fields	field	NOUN
ajst-25804	8	28	.	.	PUNCT
ajst-25804	9	1	keywords	keyword	NOUN
ajst-25804	9	2	:	:	PUNCT
ajst-25804	9	3	complex	complex	ADJ
ajst-25804	9	4	scene	scene	NOUN
ajst-25804	9	5	understanding	understanding	NOUN
ajst-25804	9	6	,	,	PUNCT
ajst-25804	9	7	object	object	NOUN
ajst-25804	9	8	detection	detection	NOUN
ajst-25804	9	9	,	,	PUNCT
ajst-25804	9	10	multi	multi	ADJ
ajst-25804	9	11	-	-	ADJ
ajst-25804	9	12	scale	scale	ADJ
ajst-25804	9	13	detection	detection	NOUN
ajst-25804	9	14	,	,	PUNCT
ajst-25804	9	15	occlusion	occlusion	NOUN
ajst-25804	9	16	treatment	treatment	NOUN
ajst-25804	9	17	,	,	PUNCT
ajst-25804	9	18	real	real	ADJ
ajst-25804	9	19	-	-	PUNCT
ajst-25804	9	20	time	time	NOUN
ajst-25804	9	21	optimization	optimization	NOUN
ajst-25804	9	22	.	.	PUNCT
ajst-25804	10	1	1	1	X
ajst-25804	10	2	.	.	X
ajst-25804	10	3	introduction	introduction	NOUN
ajst-25804	10	4	in	in	ADP
ajst-25804	10	5	today	today	NOUN
ajst-25804	10	6	's	's	PART
ajst-25804	10	7	era	era	NOUN
ajst-25804	10	8	of	of	ADP
ajst-25804	10	9	rapid	rapid	ADJ
ajst-25804	10	10	information	information	NOUN
ajst-25804	10	11	development	development	NOUN
ajst-25804	10	12	,	,	PUNCT
ajst-25804	10	13	ai	ai	VERB
ajst-25804	10	14	has	have	AUX
ajst-25804	10	15	become	become	VERB
ajst-25804	10	16	an	an	DET
ajst-25804	10	17	important	important	ADJ
ajst-25804	10	18	force	force	NOUN
ajst-25804	10	19	to	to	PART
ajst-25804	10	20	promote	promote	VERB
ajst-25804	10	21	social	social	ADJ
ajst-25804	10	22	progress	progress	NOUN
ajst-25804	10	23	and	and	CCONJ
ajst-25804	10	24	technological	technological	ADJ
ajst-25804	10	25	innovation	innovation	NOUN
ajst-25804	10	26	[	[	X
ajst-25804	10	27	1	1	NUM
ajst-25804	10	28	]	]	PUNCT
ajst-25804	10	29	.	.	PUNCT
ajst-25804	11	1	among	among	ADP
ajst-25804	11	2	them	they	PRON
ajst-25804	11	3	,	,	PUNCT
ajst-25804	11	4	complex	complex	ADJ
ajst-25804	11	5	scene	scene	NOUN
ajst-25804	11	6	understanding	understanding	NOUN
ajst-25804	11	7	and	and	CCONJ
ajst-25804	11	8	object	object	NOUN
ajst-25804	11	9	detection	detection	NOUN
ajst-25804	11	10	,	,	PUNCT
ajst-25804	11	11	as	as	SCONJ
ajst-25804	11	12	the	the	DET
ajst-25804	11	13	core	core	NOUN
ajst-25804	11	14	tasks	task	NOUN
ajst-25804	11	15	in	in	ADP
ajst-25804	11	16	the	the	DET
ajst-25804	11	17	field	field	NOUN
ajst-25804	11	18	of	of	ADP
ajst-25804	11	19	ai	ai	PROPN
ajst-25804	11	20	vision	vision	NOUN
ajst-25804	11	21	,	,	PUNCT
ajst-25804	11	22	play	play	VERB
ajst-25804	11	23	a	a	DET
ajst-25804	11	24	vital	vital	ADJ
ajst-25804	11	25	role	role	NOUN
ajst-25804	11	26	in	in	ADP
ajst-25804	11	27	improving	improve	VERB
ajst-25804	11	28	the	the	DET
ajst-25804	11	29	machine	machine	NOUN
ajst-25804	11	30	's	's	PART
ajst-25804	11	31	perception	perception	NOUN
ajst-25804	11	32	of	of	ADP
ajst-25804	11	33	the	the	DET
ajst-25804	11	34	surrounding	surround	VERB
ajst-25804	11	35	environment	environment	NOUN
ajst-25804	11	36	and	and	CCONJ
ajst-25804	11	37	realizing	realize	VERB
ajst-25804	11	38	intelligent	intelligent	ADJ
ajst-25804	11	39	decision	decision	NOUN
ajst-25804	11	40	-	-	PUNCT
ajst-25804	11	41	making	making	NOUN
ajst-25804	11	42	[	[	X
ajst-25804	11	43	2	2	NUM
ajst-25804	11	44	-	-	SYM
ajst-25804	11	45	3	3	NUM
ajst-25804	11	46	]	]	PUNCT
ajst-25804	11	47	.	.	PUNCT
ajst-25804	12	1	with	with	ADP
ajst-25804	12	2	the	the	DET
ajst-25804	12	3	continuous	continuous	ADJ
ajst-25804	12	4	progress	progress	NOUN
ajst-25804	12	5	of	of	ADP
ajst-25804	12	6	computer	computer	NOUN
ajst-25804	12	7	vision	vision	NOUN
ajst-25804	12	8	technology	technology	NOUN
ajst-25804	12	9	,	,	PUNCT
ajst-25804	12	10	especially	especially	ADV
ajst-25804	12	11	with	with	ADP
ajst-25804	12	12	the	the	DET
ajst-25804	12	13	promotion	promotion	NOUN
ajst-25804	12	14	of	of	ADP
ajst-25804	12	15	deep	deep	ADJ
ajst-25804	12	16	learning	learning	NOUN
ajst-25804	12	17	algorithm	algorithm	NOUN
ajst-25804	12	18	,	,	PUNCT
ajst-25804	12	19	the	the	DET
ajst-25804	12	20	ability	ability	NOUN
ajst-25804	12	21	of	of	ADP
ajst-25804	12	22	object	object	NOUN
ajst-25804	12	23	detection	detection	NOUN
ajst-25804	12	24	and	and	CCONJ
ajst-25804	12	25	recognition	recognition	NOUN
ajst-25804	12	26	in	in	ADP
ajst-25804	12	27	complex	complex	ADJ
ajst-25804	12	28	scenes	scene	NOUN
ajst-25804	12	29	has	have	AUX
ajst-25804	12	30	been	be	AUX
ajst-25804	12	31	significantly	significantly	ADV
ajst-25804	12	32	improved	improve	VERB
ajst-25804	12	33	,	,	PUNCT
ajst-25804	12	34	which	which	PRON
ajst-25804	12	35	has	have	AUX
ajst-25804	12	36	brought	bring	VERB
ajst-25804	12	37	revolutionary	revolutionary	ADJ
ajst-25804	12	38	changes	change	NOUN
ajst-25804	12	39	to	to	ADP
ajst-25804	12	40	many	many	ADJ
ajst-25804	12	41	fields	field	NOUN
ajst-25804	12	42	such	such	ADJ
ajst-25804	12	43	as	as	ADP
ajst-25804	12	44	autonomous	autonomous	ADJ
ajst-25804	12	45	driving	driving	NOUN
ajst-25804	12	46	,	,	PUNCT
ajst-25804	12	47	intelligent	intelligent	ADJ
ajst-25804	12	48	security	security	NOUN
ajst-25804	12	49	,	,	PUNCT
ajst-25804	12	50	robot	robot	NOUN
ajst-25804	12	51	navigation	navigation	NOUN
ajst-25804	12	52	,	,	PUNCT
ajst-25804	12	53	medical	medical	ADJ
ajst-25804	12	54	image	image	NOUN
ajst-25804	12	55	analysis	analysis	NOUN
ajst-25804	12	56	[	[	X
ajst-25804	12	57	4	4	NUM
ajst-25804	12	58	]	]	PUNCT
ajst-25804	12	59	.	.	PUNCT
ajst-25804	13	1	understanding	understand	VERB
ajst-25804	13	2	complex	complex	ADJ
ajst-25804	13	3	scenes	scene	NOUN
ajst-25804	13	4	is	be	AUX
ajst-25804	13	5	not	not	PART
ajst-25804	13	6	only	only	ADV
ajst-25804	13	7	a	a	DET
ajst-25804	13	8	simple	simple	ADJ
ajst-25804	13	9	recognition	recognition	NOUN
ajst-25804	13	10	of	of	ADP
ajst-25804	13	11	objects	object	NOUN
ajst-25804	13	12	in	in	ADP
ajst-25804	13	13	images	image	NOUN
ajst-25804	13	14	,	,	PUNCT
ajst-25804	13	15	but	but	CCONJ
ajst-25804	13	16	also	also	ADV
ajst-25804	13	17	a	a	DET
ajst-25804	13	18	grasp	grasp	NOUN
ajst-25804	13	19	of	of	ADP
ajst-25804	13	20	the	the	DET
ajst-25804	13	21	overall	overall	ADJ
ajst-25804	13	22	semantics	semantic	NOUN
ajst-25804	13	23	of	of	ADP
ajst-25804	13	24	the	the	DET
ajst-25804	13	25	scene	scene	NOUN
ajst-25804	13	26	,	,	PUNCT
ajst-25804	13	27	such	such	ADJ
ajst-25804	13	28	as	as	ADP
ajst-25804	13	29	identifying	identify	VERB
ajst-25804	13	30	the	the	DET
ajst-25804	13	31	elements	element	NOUN
ajst-25804	13	32	such	such	ADJ
ajst-25804	13	33	as	as	ADP
ajst-25804	13	34	roads	road	NOUN
ajst-25804	13	35	,	,	PUNCT
ajst-25804	13	36	buildings	building	NOUN
ajst-25804	13	37	and	and	CCONJ
ajst-25804	13	38	vegetation	vegetation	NOUN
ajst-25804	13	39	in	in	ADP
ajst-25804	13	40	the	the	DET
ajst-25804	13	41	scene	scene	NOUN
ajst-25804	13	42	and	and	CCONJ
ajst-25804	13	43	their	their	PRON
ajst-25804	13	44	spatial	spatial	ADJ
ajst-25804	13	45	relationships	relationship	NOUN
ajst-25804	13	46	[	[	X
ajst-25804	13	47	5	5	NUM
ajst-25804	13	48	]	]	PUNCT
ajst-25804	13	49	.	.	PUNCT
ajst-25804	14	1	object	object	NOUN
ajst-25804	14	2	detection	detection	NOUN
ajst-25804	14	3	is	be	AUX
ajst-25804	14	4	to	to	PART
ajst-25804	14	5	accurately	accurately	ADV
ajst-25804	14	6	locate	locate	VERB
ajst-25804	14	7	and	and	CCONJ
ajst-25804	14	8	identify	identify	VERB
ajst-25804	14	9	the	the	DET
ajst-25804	14	10	target	target	NOUN
ajst-25804	14	11	objects	object	NOUN
ajst-25804	14	12	in	in	ADP
ajst-25804	14	13	the	the	DET
ajst-25804	14	14	image	image	NOUN
ajst-25804	14	15	,	,	PUNCT
ajst-25804	14	16	such	such	ADJ
ajst-25804	14	17	as	as	ADP
ajst-25804	14	18	pedestrians	pedestrian	NOUN
ajst-25804	14	19	,	,	PUNCT
ajst-25804	14	20	vehicles	vehicle	NOUN
ajst-25804	14	21	and	and	CCONJ
ajst-25804	14	22	animals	animal	NOUN
ajst-25804	14	23	,	,	PUNCT
ajst-25804	14	24	which	which	PRON
ajst-25804	14	25	is	be	AUX
ajst-25804	14	26	very	very	ADV
ajst-25804	14	27	important	important	ADJ
ajst-25804	14	28	to	to	PART
ajst-25804	14	29	ensure	ensure	VERB
ajst-25804	14	30	that	that	SCONJ
ajst-25804	14	31	the	the	DET
ajst-25804	14	32	system	system	NOUN
ajst-25804	14	33	can	can	AUX
ajst-25804	14	34	accurately	accurately	ADV
ajst-25804	14	35	respond	respond	VERB
ajst-25804	14	36	to	to	ADP
ajst-25804	14	37	the	the	DET
ajst-25804	14	38	key	key	ADJ
ajst-25804	14	39	information	information	NOUN
ajst-25804	14	40	in	in	ADP
ajst-25804	14	41	the	the	DET
ajst-25804	14	42	surrounding	surround	VERB
ajst-25804	14	43	environment	environment	NOUN
ajst-25804	14	44	[	[	X
ajst-25804	14	45	6	6	NUM
ajst-25804	14	46	-	-	SYM
ajst-25804	14	47	7	7	NUM
ajst-25804	14	48	]	]	PUNCT
ajst-25804	14	49	.	.	PUNCT
ajst-25804	15	1	therefore	therefore	ADV
ajst-25804	15	2	,	,	PUNCT
ajst-25804	15	3	in	in	ADP
ajst-25804	15	4	-	-	PUNCT
ajst-25804	15	5	depth	depth	NOUN
ajst-25804	15	6	study	study	NOUN
ajst-25804	15	7	of	of	ADP
ajst-25804	15	8	complex	complex	ADJ
ajst-25804	15	9	scene	scene	NOUN
ajst-25804	15	10	understanding	understanding	NOUN
ajst-25804	15	11	and	and	CCONJ
ajst-25804	15	12	object	object	VERB
ajst-25804	15	13	detection	detection	NOUN
ajst-25804	15	14	algorithms	algorithm	NOUN
ajst-25804	15	15	is	be	AUX
ajst-25804	15	16	of	of	ADP
ajst-25804	15	17	far	far	ADV
ajst-25804	15	18	-	-	PUNCT
ajst-25804	15	19	reaching	reach	VERB
ajst-25804	15	20	significance	significance	NOUN
ajst-25804	15	21	for	for	ADP
ajst-25804	15	22	improving	improve	VERB
ajst-25804	15	23	the	the	DET
ajst-25804	15	24	intelligence	intelligence	NOUN
ajst-25804	15	25	level	level	NOUN
ajst-25804	15	26	of	of	ADP
ajst-25804	15	27	ai	ai	ADJ
ajst-25804	15	28	system	system	NOUN
ajst-25804	15	29	and	and	CCONJ
ajst-25804	15	30	broadening	broaden	VERB
ajst-25804	15	31	its	its	PRON
ajst-25804	15	32	application	application	NOUN
ajst-25804	15	33	scenarios	scenario	NOUN
ajst-25804	15	34	.	.	PUNCT
ajst-25804	16	1	2	2	X
ajst-25804	16	2	.	.	X
ajst-25804	16	3	basic	basic	ADJ
ajst-25804	16	4	theory	theory	NOUN
ajst-25804	16	5	of	of	ADP
ajst-25804	16	6	complex	complex	ADJ
ajst-25804	16	7	scene	scene	NOUN
ajst-25804	16	8	understanding	understanding	NOUN
ajst-25804	16	9	and	and	CCONJ
ajst-25804	16	10	object	object	VERB
ajst-25804	16	11	detection	detection	NOUN
ajst-25804	16	12	2.1	2.1	NUM
ajst-25804	16	13	.	.	PUNCT
ajst-25804	16	14	basic	basic	ADJ
ajst-25804	16	15	concepts	concept	NOUN
ajst-25804	16	16	of	of	ADP
ajst-25804	16	17	scene	scene	NOUN
ajst-25804	16	18	understanding	understand	VERB
ajst-25804	16	19	scene	scene	NOUN
ajst-25804	16	20	understanding	understanding	NOUN
ajst-25804	16	21	is	be	AUX
ajst-25804	16	22	an	an	DET
ajst-25804	16	23	important	important	ADJ
ajst-25804	16	24	branch	branch	NOUN
ajst-25804	16	25	of	of	ADP
ajst-25804	16	26	computer	computer	NOUN
ajst-25804	16	27	vision	vision	NOUN
ajst-25804	16	28	,	,	PUNCT
ajst-25804	16	29	which	which	PRON
ajst-25804	16	30	aims	aim	VERB
ajst-25804	16	31	to	to	PART
ajst-25804	16	32	make	make	VERB
ajst-25804	16	33	computers	computer	NOUN
ajst-25804	16	34	understand	understand	VERB
ajst-25804	16	35	the	the	DET
ajst-25804	16	36	scene	scene	NOUN
ajst-25804	16	37	content	content	NOUN
ajst-25804	16	38	in	in	ADP
ajst-25804	16	39	images	image	NOUN
ajst-25804	16	40	or	or	CCONJ
ajst-25804	16	41	videos	video	NOUN
ajst-25804	16	42	like	like	ADP
ajst-25804	16	43	humans	human	NOUN
ajst-25804	16	44	[	[	X
ajst-25804	16	45	8	8	NUM
ajst-25804	16	46	]	]	PUNCT
ajst-25804	16	47	.	.	PUNCT
ajst-25804	17	1	this	this	PRON
ajst-25804	17	2	includes	include	VERB
ajst-25804	17	3	identifying	identify	VERB
ajst-25804	17	4	objects	object	NOUN
ajst-25804	17	5	,	,	PUNCT
ajst-25804	17	6	backgrounds	background	NOUN
ajst-25804	17	7	,	,	PUNCT
ajst-25804	17	8	spatial	spatial	ADJ
ajst-25804	17	9	layouts	layout	NOUN
ajst-25804	17	10	and	and	CCONJ
ajst-25804	17	11	semantic	semantic	ADJ
ajst-25804	17	12	relationships	relationship	NOUN
ajst-25804	17	13	among	among	ADP
ajst-25804	17	14	them	they	PRON
ajst-25804	17	15	.	.	PUNCT
ajst-25804	18	1	scene	scene	NOUN
ajst-25804	18	2	understanding	understanding	NOUN
ajst-25804	18	3	involves	involve	VERB
ajst-25804	18	4	not	not	PART
ajst-25804	18	5	only	only	ADV
ajst-25804	18	6	low	low	ADJ
ajst-25804	18	7	-	-	PUNCT
ajst-25804	18	8	level	level	NOUN
ajst-25804	18	9	image	image	NOUN
ajst-25804	18	10	processing	processing	NOUN
ajst-25804	18	11	techniques	technique	NOUN
ajst-25804	18	12	,	,	PUNCT
ajst-25804	18	13	such	such	ADJ
ajst-25804	18	14	as	as	ADP
ajst-25804	18	15	edge	edge	NOUN
ajst-25804	18	16	detection	detection	NOUN
ajst-25804	18	17	and	and	CCONJ
ajst-25804	18	18	image	image	NOUN
ajst-25804	18	19	segmentation	segmentation	NOUN
ajst-25804	18	20	,	,	PUNCT
ajst-25804	18	21	but	but	CCONJ
ajst-25804	18	22	also	also	ADV
ajst-25804	18	23	highlevel	highlevel	ADJ
ajst-25804	18	24	semantic	semantic	ADJ
ajst-25804	18	25	analysis	analysis	NOUN
ajst-25804	18	26	,	,	PUNCT
ajst-25804	18	27	such	such	ADJ
ajst-25804	18	28	as	as	ADP
ajst-25804	18	29	object	object	NOUN
ajst-25804	18	30	recognition	recognition	NOUN
ajst-25804	18	31	and	and	CCONJ
ajst-25804	18	32	scene	scene	NOUN
ajst-25804	18	33	classification	classification	NOUN
ajst-25804	18	34	.	.	PUNCT
ajst-25804	19	1	through	through	ADP
ajst-25804	19	2	scene	scene	NOUN
ajst-25804	19	3	understanding	understanding	NOUN
ajst-25804	19	4	,	,	PUNCT
ajst-25804	19	5	the	the	DET
ajst-25804	19	6	computer	computer	NOUN
ajst-25804	19	7	can	can	AUX
ajst-25804	19	8	better	well	ADV
ajst-25804	19	9	explain	explain	VERB
ajst-25804	19	10	the	the	DET
ajst-25804	19	11	image	image	NOUN
ajst-25804	19	12	content	content	NOUN
ajst-25804	19	13	and	and	CCONJ
ajst-25804	19	14	provide	provide	VERB
ajst-25804	19	15	support	support	NOUN
ajst-25804	19	16	for	for	ADP
ajst-25804	19	17	subsequent	subsequent	ADJ
ajst-25804	19	18	decision	decision	NOUN
ajst-25804	19	19	-	-	PUNCT
ajst-25804	19	20	making	making	NOUN
ajst-25804	19	21	.	.	PUNCT
ajst-25804	20	1	2.2	2.2	NUM
ajst-25804	20	2	.	.	PUNCT
ajst-25804	20	3	object	object	NOUN
ajst-25804	20	4	detection	detection	NOUN
ajst-25804	20	5	basis	basis	NOUN
ajst-25804	20	6	object	object	NOUN
ajst-25804	20	7	detection	detection	NOUN
ajst-25804	20	8	is	be	AUX
ajst-25804	20	9	a	a	DET
ajst-25804	20	10	basic	basic	ADJ
ajst-25804	20	11	task	task	NOUN
ajst-25804	20	12	in	in	ADP
ajst-25804	20	13	computer	computer	NOUN
ajst-25804	20	14	vision	vision	NOUN
ajst-25804	20	15	,	,	PUNCT
ajst-25804	20	16	which	which	PRON
ajst-25804	20	17	aims	aim	VERB
ajst-25804	20	18	to	to	PART
ajst-25804	20	19	accurately	accurately	ADV
ajst-25804	20	20	identify	identify	VERB
ajst-25804	20	21	and	and	CCONJ
ajst-25804	20	22	locate	locate	VERB
ajst-25804	20	23	the	the	DET
ajst-25804	20	24	position	position	NOUN
ajst-25804	20	25	and	and	CCONJ
ajst-25804	20	26	category	category	NOUN
ajst-25804	20	27	of	of	ADP
ajst-25804	20	28	target	target	NOUN
ajst-25804	20	29	objects	object	NOUN
ajst-25804	20	30	from	from	ADP
ajst-25804	20	31	images	image	NOUN
ajst-25804	20	32	or	or	CCONJ
ajst-25804	20	33	videos	video	NOUN
ajst-25804	20	34	.	.	PUNCT
ajst-25804	21	1	traditional	traditional	ADJ
ajst-25804	21	2	object	object	NOUN
ajst-25804	21	3	detection	detection	NOUN
ajst-25804	21	4	methods	method	NOUN
ajst-25804	21	5	are	be	AUX
ajst-25804	21	6	mainly	mainly	ADV
ajst-25804	21	7	based	base	VERB
ajst-25804	21	8	on	on	ADP
ajst-25804	21	9	manually	manually	ADV
ajst-25804	21	10	designed	design	VERB
ajst-25804	21	11	features	feature	NOUN
ajst-25804	21	12	and	and	CCONJ
ajst-25804	21	13	classifiers	classifier	NOUN
ajst-25804	21	14	,	,	PUNCT
ajst-25804	21	15	such	such	ADJ
ajst-25804	21	16	as	as	ADP
ajst-25804	21	17	hog	hog	NOUN
ajst-25804	21	18	features	feature	NOUN
ajst-25804	21	19	combined	combine	VERB
ajst-25804	21	20	with	with	ADP
ajst-25804	21	21	svm	svm	ADJ
ajst-25804	21	22	classifier	classifier	NOUN
ajst-25804	21	23	.	.	PUNCT
ajst-25804	22	1	however	however	ADV
ajst-25804	22	2	,	,	PUNCT
ajst-25804	22	3	with	with	ADP
ajst-25804	22	4	the	the	DET
ajst-25804	22	5	rise	rise	NOUN
ajst-25804	22	6	of	of	ADP
ajst-25804	22	7	deep	deep	ADJ
ajst-25804	22	8	learning	learning	NOUN
ajst-25804	22	9	,	,	PUNCT
ajst-25804	22	10	especially	especially	ADV
ajst-25804	22	11	the	the	DET
ajst-25804	22	12	successful	successful	ADJ
ajst-25804	22	13	application	application	NOUN
ajst-25804	22	14	of	of	ADP
ajst-25804	22	15	cnn	cnn	PROPN
ajst-25804	22	16	in	in	ADP
ajst-25804	22	17	the	the	DET
ajst-25804	22	18	field	field	NOUN
ajst-25804	22	19	of	of	ADP
ajst-25804	22	20	image	image	NOUN
ajst-25804	22	21	processing	processing	NOUN
ajst-25804	22	22	,	,	PUNCT
ajst-25804	22	23	the	the	DET
ajst-25804	22	24	object	object	NOUN
ajst-25804	22	25	detection	detection	NOUN
ajst-25804	22	26	algorithm	algorithm	NOUN
ajst-25804	22	27	has	have	AUX
ajst-25804	22	28	made	make	VERB
ajst-25804	22	29	remarkable	remarkable	ADJ
ajst-25804	22	30	progress	progress	NOUN
ajst-25804	22	31	.	.	PUNCT
ajst-25804	23	1	at	at	ADP
ajst-25804	23	2	present	present	ADJ
ajst-25804	23	3	,	,	PUNCT
ajst-25804	23	4	mainstream	mainstream	ADJ
ajst-25804	23	5	object	object	NOUN
ajst-25804	23	6	detection	detection	NOUN
ajst-25804	23	7	algorithms	algorithm	NOUN
ajst-25804	23	8	,	,	PUNCT
ajst-25804	23	9	such	such	ADJ
ajst-25804	23	10	as	as	ADP
ajst-25804	23	11	yolo	yolo	ADJ
ajst-25804	23	12	and	and	CCONJ
ajst-25804	23	13	faster	fast	ADJ
ajst-25804	23	14	r	r	NOUN
ajst-25804	23	15	-	-	PUNCT
ajst-25804	23	16	cnn	cnn	PROPN
ajst-25804	23	17	,	,	PUNCT
ajst-25804	23	18	are	be	AUX
ajst-25804	23	19	all	all	PRON
ajst-25804	23	20	based	base	VERB
ajst-25804	23	21	on	on	ADP
ajst-25804	23	22	deep	deep	ADJ
ajst-25804	23	23	learning	learning	NOUN
ajst-25804	23	24	framework	framework	NOUN
ajst-25804	23	25	,	,	PUNCT
ajst-25804	23	26	and	and	CCONJ
ajst-25804	23	27	realize	realize	VERB
ajst-25804	23	28	efficient	efficient	ADJ
ajst-25804	23	29	and	and	CCONJ
ajst-25804	23	30	accurate	accurate	ADJ
ajst-25804	23	31	detection	detection	NOUN
ajst-25804	23	32	of	of	ADP
ajst-25804	23	33	target	target	NOUN
ajst-25804	23	34	objects	object	NOUN
ajst-25804	23	35	through	through	ADP
ajst-25804	23	36	end	end	NOUN
ajst-25804	23	37	-	-	PUNCT
ajst-25804	23	38	to	to	ADP
ajst-25804	23	39	-	-	PUNCT
ajst-25804	23	40	end	end	NOUN
ajst-25804	23	41	learning	learning	NOUN
ajst-25804	23	42	.	.	PUNCT
ajst-25804	24	1	2.3	2.3	NUM
ajst-25804	24	2	.	.	PUNCT
ajst-25804	25	1	feature	feature	NOUN
ajst-25804	25	2	extraction	extraction	NOUN
ajst-25804	25	3	and	and	CCONJ
ajst-25804	25	4	representation	representation	NOUN
ajst-25804	25	5	learning	learn	VERB
ajst-25804	25	6	feature	feature	NOUN
ajst-25804	25	7	extraction	extraction	NOUN
ajst-25804	25	8	is	be	AUX
ajst-25804	25	9	a	a	DET
ajst-25804	25	10	key	key	ADJ
ajst-25804	25	11	link	link	NOUN
ajst-25804	25	12	in	in	ADP
ajst-25804	25	13	object	object	NOUN
ajst-25804	25	14	detection	detection	NOUN
ajst-25804	25	15	and	and	CCONJ
ajst-25804	25	16	scene	scene	NOUN
ajst-25804	25	17	understanding	understanding	NOUN
ajst-25804	25	18	.	.	PUNCT
ajst-25804	26	1	effective	effective	ADJ
ajst-25804	26	2	features	feature	NOUN
ajst-25804	26	3	can	can	AUX
ajst-25804	26	4	capture	capture	VERB
ajst-25804	26	5	the	the	DET
ajst-25804	26	6	key	key	ADJ
ajst-25804	26	7	information	information	NOUN
ajst-25804	26	8	in	in	ADP
ajst-25804	26	9	the	the	DET
ajst-25804	26	10	image	image	NOUN
ajst-25804	26	11	and	and	CCONJ
ajst-25804	26	12	improve	improve	VERB
ajst-25804	26	13	the	the	DET
ajst-25804	26	14	recognition	recognition	NOUN
ajst-25804	26	15	performance	performance	NOUN
ajst-25804	26	16	of	of	ADP
ajst-25804	26	17	the	the	DET
ajst-25804	26	18	algorithm	algorithm	NOUN
ajst-25804	26	19	.	.	PUNCT
ajst-25804	27	1	in	in	ADP
ajst-25804	27	2	the	the	DET
ajst-25804	27	3	era	era	NOUN
ajst-25804	27	4	of	of	ADP
ajst-25804	27	5	deep	deep	ADJ
ajst-25804	27	6	learning	learning	NOUN
ajst-25804	27	7	,	,	PUNCT
ajst-25804	27	8	feature	feature	NOUN
ajst-25804	27	9	extraction	extraction	NOUN
ajst-25804	27	10	and	and	CCONJ
ajst-25804	27	11	representation	representation	NOUN
ajst-25804	27	12	learning	learning	NOUN
ajst-25804	27	13	are	be	AUX
ajst-25804	27	14	usually	usually	ADV
ajst-25804	27	15	completed	complete	VERB
ajst-25804	27	16	automatically	automatically	ADV
ajst-25804	27	17	through	through	ADP
ajst-25804	27	18	deep	deep	ADJ
ajst-25804	27	19	learning	learning	NOUN
ajst-25804	27	20	models	model	NOUN
ajst-25804	27	21	such	such	ADJ
ajst-25804	27	22	as	as	ADP
ajst-25804	27	23	convolutional	convolutional	ADJ
ajst-25804	27	24	neural	neural	ADJ
ajst-25804	27	25	networks	network	NOUN
ajst-25804	27	26	.	.	PUNCT
ajst-25804	28	1	these	these	DET
ajst-25804	28	2	models	model	NOUN
ajst-25804	28	3	can	can	AUX
ajst-25804	28	4	learn	learn	VERB
ajst-25804	28	5	rich	rich	ADJ
ajst-25804	28	6	feature	feature	NOUN
ajst-25804	28	7	representations	representation	NOUN
ajst-25804	28	8	from	from	ADP
ajst-25804	28	9	a	a	DET
ajst-25804	28	10	large	large	ADJ
ajst-25804	28	11	number	number	NOUN
ajst-25804	28	12	of	of	ADP
ajst-25804	28	13	data	datum	NOUN
ajst-25804	28	14	,	,	PUNCT
ajst-25804	28	15	including	include	VERB
ajst-25804	28	16	low	low	ADJ
ajst-25804	28	17	-	-	PUNCT
ajst-25804	28	18	level	level	NOUN
ajst-25804	28	19	features	feature	NOUN
ajst-25804	28	20	such	such	ADJ
ajst-25804	28	21	as	as	ADP
ajst-25804	28	22	shape	shape	NOUN
ajst-25804	28	23	,	,	PUNCT
ajst-25804	28	24	texture	texture	NOUN
ajst-25804	28	25	and	and	CCONJ
ajst-25804	28	26	color	color	NOUN
ajst-25804	28	27	,	,	PUNCT
ajst-25804	28	28	as	as	ADV
ajst-25804	28	29	well	well	ADV
ajst-25804	28	30	as	as	ADP
ajst-25804	28	31	more	more	ADV
ajst-25804	28	32	advanced	advanced	ADJ
ajst-25804	28	33	semantic	semantic	ADJ
ajst-25804	28	34	features	feature	NOUN
ajst-25804	28	35	.	.	PUNCT
ajst-25804	29	1	through	through	ADP
ajst-25804	29	2	feature	feature	NOUN
ajst-25804	29	3	extraction	extraction	NOUN
ajst-25804	29	4	and	and	CCONJ
ajst-25804	29	5	representation	representation	NOUN
ajst-25804	29	6	learning	learning	NOUN
ajst-25804	29	7	,	,	PUNCT
ajst-25804	29	8	the	the	DET
ajst-25804	29	9	algorithm	algorithm	NOUN
ajst-25804	29	10	can	can	AUX
ajst-25804	29	11	better	well	ADV
ajst-25804	29	12	understand	understand	VERB
ajst-25804	29	13	the	the	DET
ajst-25804	29	14	image	image	NOUN
ajst-25804	29	15	content	content	NOUN
ajst-25804	29	16	and	and	CCONJ
ajst-25804	29	17	improve	improve	VERB
ajst-25804	29	18	the	the	DET
ajst-25804	29	19	accuracy	accuracy	NOUN
ajst-25804	29	20	of	of	ADP
ajst-25804	29	21	object	object	NOUN
ajst-25804	29	22	detection	detection	NOUN
ajst-25804	29	23	and	and	CCONJ
ajst-25804	29	24	scene	scene	NOUN
ajst-25804	29	25	understanding	understanding	NOUN
ajst-25804	29	26	.	.	PUNCT
ajst-25804	30	1	13	13	NUM
ajst-25804	30	2	3	3	NUM
ajst-25804	30	3	.	.	X
ajst-25804	30	4	object	object	NOUN
ajst-25804	30	5	detection	detection	NOUN
ajst-25804	30	6	algorithm	algorithm	NOUN
ajst-25804	30	7	in	in	ADP
ajst-25804	30	8	complex	complex	ADJ
ajst-25804	30	9	scene	scene	NOUN
ajst-25804	30	10	3.1	3.1	NUM
ajst-25804	30	11	.	.	PUNCT
ajst-25804	31	1	multi	multi	ADJ
ajst-25804	31	2	-	-	ADJ
ajst-25804	31	3	scale	scale	ADJ
ajst-25804	31	4	object	object	NOUN
ajst-25804	31	5	detection	detection	NOUN
ajst-25804	31	6	in	in	ADP
ajst-25804	31	7	complex	complex	ADJ
ajst-25804	31	8	scenes	scene	NOUN
ajst-25804	31	9	,	,	PUNCT
ajst-25804	31	10	the	the	DET
ajst-25804	31	11	size	size	NOUN
ajst-25804	31	12	and	and	CCONJ
ajst-25804	31	13	shape	shape	NOUN
ajst-25804	31	14	of	of	ADP
ajst-25804	31	15	objects	object	NOUN
ajst-25804	31	16	often	often	ADV
ajst-25804	31	17	vary	vary	VERB
ajst-25804	31	18	,	,	PUNCT
ajst-25804	31	19	from	from	ADP
ajst-25804	31	20	small	small	ADJ
ajst-25804	31	21	parts	part	NOUN
ajst-25804	31	22	to	to	ADP
ajst-25804	31	23	large	large	ADJ
ajst-25804	31	24	buildings	building	NOUN
ajst-25804	31	25	,	,	PUNCT
ajst-25804	31	26	which	which	PRON
ajst-25804	31	27	may	may	AUX
ajst-25804	31	28	appear	appear	VERB
ajst-25804	31	29	in	in	ADP
ajst-25804	31	30	the	the	DET
ajst-25804	31	31	same	same	ADJ
ajst-25804	31	32	image	image	NOUN
ajst-25804	31	33	.	.	PUNCT
ajst-25804	32	1	multi	multi	ADJ
ajst-25804	32	2	-	-	ADJ
ajst-25804	32	3	scale	scale	ADJ
ajst-25804	32	4	object	object	NOUN
ajst-25804	32	5	detection	detection	NOUN
ajst-25804	32	6	aims	aim	VERB
ajst-25804	32	7	to	to	PART
ajst-25804	32	8	solve	solve	VERB
ajst-25804	32	9	this	this	DET
ajst-25804	32	10	challenge	challenge	NOUN
ajst-25804	32	11	and	and	CCONJ
ajst-25804	32	12	ensure	ensure	VERB
ajst-25804	32	13	that	that	SCONJ
ajst-25804	32	14	the	the	DET
ajst-25804	32	15	algorithm	algorithm	NOUN
ajst-25804	32	16	can	can	AUX
ajst-25804	32	17	accurately	accurately	ADV
ajst-25804	32	18	identify	identify	VERB
ajst-25804	32	19	objects	object	NOUN
ajst-25804	32	20	of	of	ADP
ajst-25804	32	21	different	different	ADJ
ajst-25804	32	22	sizes	size	NOUN
ajst-25804	32	23	.	.	PUNCT
ajst-25804	33	1	in	in	ADP
ajst-25804	33	2	this	this	DET
ajst-25804	33	3	study	study	NOUN
ajst-25804	33	4	,	,	PUNCT
ajst-25804	33	5	fpn(feature	fpn(feature	NOUN
ajst-25804	33	6	pyramid	pyramid	NOUN
ajst-25804	33	7	networks	network	NOUN
ajst-25804	33	8	)	)	PUNCT
ajst-25804	33	9	,	,	PUNCT
ajst-25804	33	10	multi	multi	ADJ
ajst-25804	33	11	-	-	ADJ
ajst-25804	33	12	scale	scale	ADJ
ajst-25804	33	13	training	training	NOUN
ajst-25804	33	14	and	and	CCONJ
ajst-25804	33	15	testing	testing	NOUN
ajst-25804	33	16	strategies	strategy	NOUN
ajst-25804	33	17	and	and	CCONJ
ajst-25804	33	18	attention	attention	NOUN
ajst-25804	33	19	mechanism	mechanism	NOUN
ajst-25804	33	20	in	in	ADP
ajst-25804	33	21	deep	deep	ADJ
ajst-25804	33	22	learning	learning	NOUN
ajst-25804	33	23	are	be	AUX
ajst-25804	33	24	used	use	VERB
ajst-25804	33	25	to	to	PART
ajst-25804	33	26	enhance	enhance	VERB
ajst-25804	33	27	the	the	DET
ajst-25804	33	28	detection	detection	NOUN
ajst-25804	33	29	ability	ability	NOUN
ajst-25804	33	30	of	of	ADP
ajst-25804	33	31	the	the	DET
ajst-25804	33	32	algorithm	algorithm	NOUN
ajst-25804	33	33	for	for	ADP
ajst-25804	33	34	multi	multi	ADJ
ajst-25804	33	35	-	-	ADJ
ajst-25804	33	36	scale	scale	ADJ
ajst-25804	33	37	objects	object	NOUN
ajst-25804	33	38	.	.	PUNCT
ajst-25804	34	1	fpn	fpn	VERB
ajst-25804	34	2	is	be	AUX
ajst-25804	34	3	one	one	NUM
ajst-25804	34	4	of	of	ADP
ajst-25804	34	5	the	the	DET
ajst-25804	34	6	core	core	ADJ
ajst-25804	34	7	components	component	NOUN
ajst-25804	34	8	of	of	ADP
ajst-25804	34	9	this	this	DET
ajst-25804	34	10	study	study	NOUN
ajst-25804	34	11	.	.	PUNCT
ajst-25804	35	1	by	by	ADP
ajst-25804	35	2	constructing	construct	VERB
ajst-25804	35	3	a	a	DET
ajst-25804	35	4	top	top	ADJ
ajst-25804	35	5	-	-	PUNCT
ajst-25804	35	6	down	down	NOUN
ajst-25804	35	7	path	path	NOUN
ajst-25804	35	8	and	and	CCONJ
ajst-25804	35	9	horizontal	horizontal	ADJ
ajst-25804	35	10	connection	connection	NOUN
ajst-25804	35	11	,	,	PUNCT
ajst-25804	35	12	it	it	PRON
ajst-25804	35	13	combines	combine	VERB
ajst-25804	35	14	high	high	ADJ
ajst-25804	35	15	-	-	PUNCT
ajst-25804	35	16	level	level	NOUN
ajst-25804	35	17	semantic	semantic	ADJ
ajst-25804	35	18	information	information	NOUN
ajst-25804	35	19	with	with	ADP
ajst-25804	35	20	low	low	ADJ
ajst-25804	35	21	-	-	PUNCT
ajst-25804	35	22	level	level	NOUN
ajst-25804	35	23	detail	detail	NOUN
ajst-25804	35	24	information	information	NOUN
ajst-25804	35	25	to	to	PART
ajst-25804	35	26	generate	generate	VERB
ajst-25804	35	27	a	a	DET
ajst-25804	35	28	feature	feature	NOUN
ajst-25804	35	29	pyramid	pyramid	NOUN
ajst-25804	35	30	with	with	ADP
ajst-25804	35	31	rich	rich	ADJ
ajst-25804	35	32	levels	level	NOUN
ajst-25804	35	33	.	.	PUNCT
ajst-25804	36	1	this	this	DET
ajst-25804	36	2	multi	multi	ADJ
ajst-25804	36	3	-	-	ADJ
ajst-25804	36	4	level	level	ADJ
ajst-25804	36	5	feature	feature	NOUN
ajst-25804	36	6	representation	representation	NOUN
ajst-25804	36	7	enables	enable	VERB
ajst-25804	36	8	the	the	DET
ajst-25804	36	9	algorithm	algorithm	NOUN
ajst-25804	36	10	to	to	PART
ajst-25804	36	11	capture	capture	VERB
ajst-25804	36	12	the	the	DET
ajst-25804	36	13	fine	fine	ADJ
ajst-25804	36	14	features	feature	NOUN
ajst-25804	36	15	of	of	ADP
ajst-25804	36	16	small	small	ADJ
ajst-25804	36	17	-	-	PUNCT
ajst-25804	36	18	scale	scale	NOUN
ajst-25804	36	19	objects	object	NOUN
ajst-25804	36	20	and	and	CCONJ
ajst-25804	36	21	the	the	DET
ajst-25804	36	22	global	global	ADJ
ajst-25804	36	23	structure	structure	NOUN
ajst-25804	36	24	of	of	ADP
ajst-25804	36	25	large	large	ADJ
ajst-25804	36	26	-	-	PUNCT
ajst-25804	36	27	scale	scale	NOUN
ajst-25804	36	28	objects	object	NOUN
ajst-25804	36	29	at	at	ADP
ajst-25804	36	30	the	the	DET
ajst-25804	36	31	same	same	ADJ
ajst-25804	36	32	time	time	NOUN
ajst-25804	36	33	,	,	PUNCT
ajst-25804	36	34	thus	thus	ADV
ajst-25804	36	35	significantly	significantly	ADV
ajst-25804	36	36	improving	improve	VERB
ajst-25804	36	37	the	the	DET
ajst-25804	36	38	detection	detection	NOUN
ajst-25804	36	39	accuracy	accuracy	NOUN
ajst-25804	36	40	of	of	ADP
ajst-25804	36	41	objects	object	NOUN
ajst-25804	36	42	of	of	ADP
ajst-25804	36	43	different	different	ADJ
ajst-25804	36	44	scales	scale	NOUN
ajst-25804	36	45	.	.	PUNCT
ajst-25804	37	1	at	at	ADP
ajst-25804	37	2	the	the	DET
ajst-25804	37	3	same	same	ADJ
ajst-25804	37	4	time	time	NOUN
ajst-25804	37	5	,	,	PUNCT
ajst-25804	37	6	the	the	DET
ajst-25804	37	7	multi	multi	ADJ
ajst-25804	37	8	-	-	ADJ
ajst-25804	37	9	scale	scale	ADJ
ajst-25804	37	10	training	training	NOUN
ajst-25804	37	11	and	and	CCONJ
ajst-25804	37	12	testing	testing	NOUN
ajst-25804	37	13	strategy	strategy	NOUN
ajst-25804	37	14	further	far	ADV
ajst-25804	37	15	enhances	enhance	VERB
ajst-25804	37	16	the	the	DET
ajst-25804	37	17	generalization	generalization	NOUN
ajst-25804	37	18	ability	ability	NOUN
ajst-25804	37	19	of	of	ADP
ajst-25804	37	20	the	the	DET
ajst-25804	37	21	algorithm	algorithm	NOUN
ajst-25804	37	22	.	.	PUNCT
ajst-25804	38	1	in	in	ADP
ajst-25804	38	2	the	the	DET
ajst-25804	38	3	training	training	NOUN
ajst-25804	38	4	stage	stage	NOUN
ajst-25804	38	5	,	,	PUNCT
ajst-25804	38	6	we	we	PRON
ajst-25804	38	7	randomly	randomly	ADV
ajst-25804	38	8	adjust	adjust	VERB
ajst-25804	38	9	the	the	DET
ajst-25804	38	10	size	size	NOUN
ajst-25804	38	11	of	of	ADP
ajst-25804	38	12	the	the	DET
ajst-25804	38	13	input	input	NOUN
ajst-25804	38	14	image	image	NOUN
ajst-25804	38	15	,	,	PUNCT
ajst-25804	38	16	so	so	SCONJ
ajst-25804	38	17	that	that	SCONJ
ajst-25804	38	18	the	the	DET
ajst-25804	38	19	model	model	NOUN
ajst-25804	38	20	can	can	AUX
ajst-25804	38	21	learn	learn	VERB
ajst-25804	38	22	the	the	DET
ajst-25804	38	23	object	object	NOUN
ajst-25804	38	24	characteristics	characteristic	NOUN
ajst-25804	38	25	at	at	ADP
ajst-25804	38	26	different	different	ADJ
ajst-25804	38	27	scales	scale	NOUN
ajst-25804	38	28	.	.	PUNCT
ajst-25804	39	1	this	this	DET
ajst-25804	39	2	data	data	NOUN
ajst-25804	39	3	enhancement	enhancement	NOUN
ajst-25804	39	4	method	method	NOUN
ajst-25804	39	5	not	not	PART
ajst-25804	39	6	only	only	ADV
ajst-25804	39	7	increases	increase	VERB
ajst-25804	39	8	the	the	DET
ajst-25804	39	9	diversity	diversity	NOUN
ajst-25804	39	10	of	of	ADP
ajst-25804	39	11	training	training	NOUN
ajst-25804	39	12	data	datum	NOUN
ajst-25804	39	13	,	,	PUNCT
ajst-25804	39	14	but	but	CCONJ
ajst-25804	39	15	also	also	ADV
ajst-25804	39	16	forces	force	VERB
ajst-25804	39	17	the	the	DET
ajst-25804	39	18	model	model	NOUN
ajst-25804	39	19	to	to	PART
ajst-25804	39	20	extract	extract	VERB
ajst-25804	39	21	and	and	CCONJ
ajst-25804	39	22	classify	classify	VERB
ajst-25804	39	23	features	feature	NOUN
ajst-25804	39	24	effectively	effectively	ADV
ajst-25804	39	25	at	at	ADP
ajst-25804	39	26	different	different	ADJ
ajst-25804	39	27	scales	scale	NOUN
ajst-25804	39	28	.	.	PUNCT
ajst-25804	40	1	in	in	ADP
ajst-25804	40	2	the	the	DET
ajst-25804	40	3	testing	testing	NOUN
ajst-25804	40	4	stage	stage	NOUN
ajst-25804	40	5	,	,	PUNCT
ajst-25804	40	6	this	this	DET
ajst-25804	40	7	paper	paper	NOUN
ajst-25804	40	8	also	also	ADV
ajst-25804	40	9	uses	use	VERB
ajst-25804	40	10	multi	multi	ADJ
ajst-25804	40	11	-	-	ADJ
ajst-25804	40	12	scale	scale	ADJ
ajst-25804	40	13	input	input	NOUN
ajst-25804	40	14	,	,	PUNCT
ajst-25804	40	15	adjusts	adjust	VERB
ajst-25804	40	16	the	the	DET
ajst-25804	40	17	image	image	NOUN
ajst-25804	40	18	to	to	ADP
ajst-25804	40	19	different	different	ADJ
ajst-25804	40	20	sizes	size	NOUN
ajst-25804	40	21	for	for	ADP
ajst-25804	40	22	multiple	multiple	ADJ
ajst-25804	40	23	tests	test	NOUN
ajst-25804	40	24	,	,	PUNCT
ajst-25804	40	25	and	and	CCONJ
ajst-25804	40	26	synthesizes	synthesize	VERB
ajst-25804	40	27	these	these	DET
ajst-25804	40	28	results	result	NOUN
ajst-25804	40	29	to	to	PART
ajst-25804	40	30	get	get	VERB
ajst-25804	40	31	more	more	ADV
ajst-25804	40	32	accurate	accurate	ADJ
ajst-25804	40	33	final	final	ADJ
ajst-25804	40	34	output	output	NOUN
ajst-25804	40	35	.	.	PUNCT
ajst-25804	41	1	this	this	DET
ajst-25804	41	2	strategy	strategy	NOUN
ajst-25804	41	3	effectively	effectively	ADV
ajst-25804	41	4	reduces	reduce	VERB
ajst-25804	41	5	the	the	DET
ajst-25804	41	6	missed	miss	VERB
ajst-25804	41	7	detection	detection	NOUN
ajst-25804	41	8	and	and	CCONJ
ajst-25804	41	9	false	false	ADJ
ajst-25804	41	10	detection	detection	NOUN
ajst-25804	41	11	caused	cause	VERB
ajst-25804	41	12	by	by	ADP
ajst-25804	41	13	scale	scale	NOUN
ajst-25804	41	14	change	change	NOUN
ajst-25804	41	15	,	,	PUNCT
ajst-25804	41	16	and	and	CCONJ
ajst-25804	41	17	improves	improve	VERB
ajst-25804	41	18	the	the	DET
ajst-25804	41	19	robustness	robustness	NOUN
ajst-25804	41	20	of	of	ADP
ajst-25804	41	21	the	the	DET
ajst-25804	41	22	algorithm	algorithm	NOUN
ajst-25804	41	23	.	.	PUNCT
ajst-25804	42	1	the	the	DET
ajst-25804	42	2	introduction	introduction	NOUN
ajst-25804	42	3	of	of	ADP
ajst-25804	42	4	attention	attention	NOUN
ajst-25804	42	5	mechanism	mechanism	NOUN
ajst-25804	42	6	further	far	ADV
ajst-25804	42	7	optimizes	optimize	VERB
ajst-25804	42	8	the	the	DET
ajst-25804	42	9	focusing	focus	VERB
ajst-25804	42	10	ability	ability	NOUN
ajst-25804	42	11	of	of	ADP
ajst-25804	42	12	the	the	DET
ajst-25804	42	13	algorithm	algorithm	NOUN
ajst-25804	42	14	on	on	ADP
ajst-25804	42	15	key	key	ADJ
ajst-25804	42	16	information	information	NOUN
ajst-25804	42	17	.	.	PUNCT
ajst-25804	43	1	the	the	DET
ajst-25804	43	2	attention	attention	NOUN
ajst-25804	43	3	mechanism	mechanism	NOUN
ajst-25804	43	4	can	can	AUX
ajst-25804	43	5	be	be	AUX
ajst-25804	43	6	expressed	express	VERB
ajst-25804	43	7	by	by	ADP
ajst-25804	43	8	the	the	DET
ajst-25804	43	9	following	follow	VERB
ajst-25804	43	10	formula	formula	NOUN
ajst-25804	43	11	:	:	PUNCT
ajst-25804	43	12			PROPN
ajst-25804	43	13			PROPN
ajst-25804	43	14	x	x	PUNCT
ajst-25804	43	15	attwreluwsoftmax	attwreluwsoftmax	ADV
ajst-25804	43	16			NUM
ajst-25804	43	17	(	(	PUNCT
ajst-25804	43	18	1	1	NUM
ajst-25804	43	19	)	)	PUNCT
ajst-25804	43	20	xy	xy	PUNCT
ajst-25804	43	21			PROPN
ajst-25804	43	22	(	(	PUNCT
ajst-25804	43	23	2	2	NUM
ajst-25804	43	24	)	)	PUNCT
ajst-25804	43	25	where	where	SCONJ
ajst-25804	43	26	x	x	PRON
ajst-25804	43	27	is	be	AUX
ajst-25804	43	28	the	the	DET
ajst-25804	43	29	input	input	NOUN
ajst-25804	43	30	feature	feature	NOUN
ajst-25804	43	31	map	map	NOUN
ajst-25804	43	32	,	,	PUNCT
ajst-25804	43	33	attw	attw	NOUN
ajst-25804	43	34	and	and	CCONJ
ajst-25804	43	35	w	w	NOUN
ajst-25804	43	36	are	be	AUX
ajst-25804	43	37	the	the	DET
ajst-25804	43	38	learnable	learnable	ADJ
ajst-25804	43	39	weights	weight	NOUN
ajst-25804	43	40	,	,	PUNCT
ajst-25804	43	41	relu	relu	NOUN
ajst-25804	43	42	is	be	AUX
ajst-25804	43	43	the	the	DET
ajst-25804	43	44	activation	activation	NOUN
ajst-25804	43	45	function	function	NOUN
ajst-25804	43	46	,	,	PUNCT
ajst-25804	43	47			NUM
ajst-25804	43	48	is	be	AUX
ajst-25804	43	49	the	the	DET
ajst-25804	43	50	attention	attention	NOUN
ajst-25804	43	51	weight	weight	NOUN
ajst-25804	43	52	,	,	PUNCT
ajst-25804	43	53	and	and	CCONJ
ajst-25804	43	54	y	y	PROPN
ajst-25804	43	55	is	be	AUX
ajst-25804	43	56	the	the	DET
ajst-25804	43	57	attention	attention	NOUN
ajst-25804	43	58	-	-	PUNCT
ajst-25804	43	59	weighted	weight	VERB
ajst-25804	43	60	feature	feature	NOUN
ajst-25804	43	61	map	map	NOUN
ajst-25804	43	62	.	.	PUNCT
ajst-25804	44	1	in	in	ADP
ajst-25804	44	2	complex	complex	ADJ
ajst-25804	44	3	scenes	scene	NOUN
ajst-25804	44	4	,	,	PUNCT
ajst-25804	44	5	background	background	NOUN
ajst-25804	44	6	noise	noise	NOUN
ajst-25804	44	7	and	and	CCONJ
ajst-25804	44	8	object	object	VERB
ajst-25804	44	9	occlusion	occlusion	NOUN
ajst-25804	44	10	often	often	ADV
ajst-25804	44	11	interfere	interfere	VERB
ajst-25804	44	12	with	with	ADP
ajst-25804	44	13	detection	detection	NOUN
ajst-25804	44	14	.	.	PUNCT
ajst-25804	45	1	by	by	ADP
ajst-25804	45	2	introducing	introduce	VERB
ajst-25804	45	3	attention	attention	NOUN
ajst-25804	45	4	mechanism	mechanism	NOUN
ajst-25804	45	5	,	,	PUNCT
ajst-25804	45	6	the	the	DET
ajst-25804	45	7	algorithm	algorithm	NOUN
ajst-25804	45	8	can	can	AUX
ajst-25804	45	9	automatically	automatically	ADV
ajst-25804	45	10	learn	learn	VERB
ajst-25804	45	11	and	and	CCONJ
ajst-25804	45	12	highlight	highlight	VERB
ajst-25804	45	13	those	those	DET
ajst-25804	45	14	feature	feature	NOUN
ajst-25804	45	15	regions	region	NOUN
ajst-25804	45	16	that	that	PRON
ajst-25804	45	17	are	be	AUX
ajst-25804	45	18	most	most	ADV
ajst-25804	45	19	critical	critical	ADJ
ajst-25804	45	20	to	to	ADP
ajst-25804	45	21	the	the	DET
ajst-25804	45	22	detection	detection	NOUN
ajst-25804	45	23	task	task	NOUN
ajst-25804	45	24	,	,	PUNCT
ajst-25804	45	25	while	while	SCONJ
ajst-25804	45	26	suppressing	suppress	VERB
ajst-25804	45	27	irrelevant	irrelevant	ADJ
ajst-25804	45	28	background	background	NOUN
ajst-25804	45	29	information	information	NOUN
ajst-25804	45	30	.	.	PUNCT
ajst-25804	46	1	this	this	DET
ajst-25804	46	2	mechanism	mechanism	NOUN
ajst-25804	46	3	not	not	PART
ajst-25804	46	4	only	only	ADV
ajst-25804	46	5	improves	improve	VERB
ajst-25804	46	6	the	the	DET
ajst-25804	46	7	effectiveness	effectiveness	NOUN
ajst-25804	46	8	of	of	ADP
ajst-25804	46	9	feature	feature	NOUN
ajst-25804	46	10	representation	representation	NOUN
ajst-25804	46	11	,	,	PUNCT
ajst-25804	46	12	but	but	CCONJ
ajst-25804	46	13	also	also	ADV
ajst-25804	46	14	makes	make	VERB
ajst-25804	46	15	the	the	DET
ajst-25804	46	16	algorithm	algorithm	NOUN
ajst-25804	46	17	more	more	ADV
ajst-25804	46	18	robust	robust	ADJ
ajst-25804	46	19	when	when	SCONJ
ajst-25804	46	20	dealing	deal	VERB
ajst-25804	46	21	with	with	ADP
ajst-25804	46	22	complex	complex	ADJ
ajst-25804	46	23	scenes	scene	NOUN
ajst-25804	46	24	.	.	PUNCT
ajst-25804	47	1	3.2	3.2	NUM
ajst-25804	47	2	.	.	PUNCT
ajst-25804	47	3	occlusion	occlusion	NOUN
ajst-25804	47	4	and	and	CCONJ
ajst-25804	47	5	dense	dense	ADJ
ajst-25804	47	6	scene	scene	NOUN
ajst-25804	47	7	processing	processing	NOUN
ajst-25804	47	8	occlusion	occlusion	NOUN
ajst-25804	47	9	and	and	CCONJ
ajst-25804	47	10	dense	dense	ADJ
ajst-25804	47	11	scene	scene	NOUN
ajst-25804	47	12	are	be	AUX
ajst-25804	47	13	two	two	NUM
ajst-25804	47	14	difficult	difficult	ADJ
ajst-25804	47	15	problems	problem	NOUN
ajst-25804	47	16	in	in	ADP
ajst-25804	47	17	object	object	NOUN
ajst-25804	47	18	detection	detection	NOUN
ajst-25804	47	19	.	.	PUNCT
ajst-25804	48	1	in	in	ADP
ajst-25804	48	2	the	the	DET
ajst-25804	48	3	case	case	NOUN
ajst-25804	48	4	of	of	ADP
ajst-25804	48	5	occlusion	occlusion	NOUN
ajst-25804	48	6	,	,	PUNCT
ajst-25804	48	7	some	some	PRON
ajst-25804	48	8	or	or	CCONJ
ajst-25804	48	9	all	all	DET
ajst-25804	48	10	areas	area	NOUN
ajst-25804	48	11	of	of	ADP
ajst-25804	48	12	an	an	DET
ajst-25804	48	13	object	object	NOUN
ajst-25804	48	14	may	may	AUX
ajst-25804	48	15	be	be	AUX
ajst-25804	48	16	occluded	occlude	VERB
ajst-25804	48	17	by	by	ADP
ajst-25804	48	18	other	other	ADJ
ajst-25804	48	19	objects	object	NOUN
ajst-25804	48	20	,	,	PUNCT
ajst-25804	48	21	which	which	PRON
ajst-25804	48	22	makes	make	VERB
ajst-25804	48	23	the	the	DET
ajst-25804	48	24	detection	detection	NOUN
ajst-25804	48	25	more	more	ADV
ajst-25804	48	26	difficult	difficult	ADJ
ajst-25804	48	27	.	.	PUNCT
ajst-25804	49	1	however	however	ADV
ajst-25804	49	2	,	,	PUNCT
ajst-25804	49	3	in	in	ADP
ajst-25804	49	4	dense	dense	ADJ
ajst-25804	49	5	scenes	scene	NOUN
ajst-25804	49	6	,	,	PUNCT
ajst-25804	49	7	multiple	multiple	ADJ
ajst-25804	49	8	objects	object	NOUN
ajst-25804	49	9	are	be	AUX
ajst-25804	49	10	closely	closely	ADV
ajst-25804	49	11	arranged	arrange	VERB
ajst-25804	49	12	,	,	PUNCT
ajst-25804	49	13	which	which	PRON
ajst-25804	49	14	is	be	AUX
ajst-25804	49	15	easy	easy	ADJ
ajst-25804	49	16	to	to	PART
ajst-25804	49	17	cause	cause	VERB
ajst-25804	49	18	false	false	ADJ
ajst-25804	49	19	detection	detection	NOUN
ajst-25804	49	20	and	and	CCONJ
ajst-25804	49	21	missed	miss	VERB
ajst-25804	49	22	detection	detection	NOUN
ajst-25804	49	23	.	.	PUNCT
ajst-25804	50	1	in	in	ADP
ajst-25804	50	2	this	this	DET
ajst-25804	50	3	study	study	NOUN
ajst-25804	50	4	,	,	PUNCT
ajst-25804	50	5	context	context	NOUN
ajst-25804	50	6	information	information	NOUN
ajst-25804	50	7	,	,	PUNCT
ajst-25804	50	8	component	component	NOUN
ajst-25804	50	9	model	model	NOUN
ajst-25804	50	10	and	and	CCONJ
ajst-25804	50	11	other	other	ADJ
ajst-25804	50	12	technologies	technology	NOUN
ajst-25804	50	13	are	be	AUX
ajst-25804	50	14	used	use	VERB
ajst-25804	50	15	to	to	PART
ajst-25804	50	16	improve	improve	VERB
ajst-25804	50	17	the	the	DET
ajst-25804	50	18	performance	performance	NOUN
ajst-25804	50	19	of	of	ADP
ajst-25804	50	20	object	object	NOUN
ajst-25804	50	21	detection	detection	NOUN
ajst-25804	50	22	in	in	ADP
ajst-25804	50	23	occluded	occluded	ADJ
ajst-25804	50	24	and	and	CCONJ
ajst-25804	50	25	dense	dense	ADJ
ajst-25804	50	26	scenes	scene	NOUN
ajst-25804	50	27	.	.	PUNCT
ajst-25804	51	1	using	use	VERB
ajst-25804	51	2	context	context	NOUN
ajst-25804	51	3	information	information	NOUN
ajst-25804	51	4	is	be	AUX
ajst-25804	51	5	an	an	DET
ajst-25804	51	6	important	important	ADJ
ajst-25804	51	7	means	mean	NOUN
ajst-25804	51	8	to	to	PART
ajst-25804	51	9	improve	improve	VERB
ajst-25804	51	10	the	the	DET
ajst-25804	51	11	performance	performance	NOUN
ajst-25804	51	12	of	of	ADP
ajst-25804	51	13	object	object	NOUN
ajst-25804	51	14	detection	detection	NOUN
ajst-25804	51	15	in	in	ADP
ajst-25804	51	16	occluded	occluded	ADJ
ajst-25804	51	17	and	and	CCONJ
ajst-25804	51	18	dense	dense	ADJ
ajst-25804	51	19	scenes	scene	NOUN
ajst-25804	51	20	.	.	PUNCT
ajst-25804	52	1	in	in	ADP
ajst-25804	52	2	complex	complex	ADJ
ajst-25804	52	3	visual	visual	ADJ
ajst-25804	52	4	scenes	scene	NOUN
ajst-25804	52	5	,	,	PUNCT
ajst-25804	52	6	objects	object	NOUN
ajst-25804	52	7	usually	usually	ADV
ajst-25804	52	8	do	do	AUX
ajst-25804	52	9	not	not	PART
ajst-25804	52	10	exist	exist	VERB
ajst-25804	52	11	in	in	ADP
ajst-25804	52	12	isolation	isolation	NOUN
ajst-25804	52	13	,	,	PUNCT
ajst-25804	52	14	and	and	CCONJ
ajst-25804	52	15	they	they	PRON
ajst-25804	52	16	are	be	AUX
ajst-25804	52	17	closely	closely	ADV
ajst-25804	52	18	related	relate	VERB
ajst-25804	52	19	to	to	ADP
ajst-25804	52	20	the	the	DET
ajst-25804	52	21	surrounding	surround	VERB
ajst-25804	52	22	environment	environment	NOUN
ajst-25804	52	23	and	and	CCONJ
ajst-25804	52	24	other	other	ADJ
ajst-25804	52	25	objects	object	NOUN
ajst-25804	52	26	.	.	PUNCT
ajst-25804	53	1	by	by	ADP
ajst-25804	53	2	capturing	capture	VERB
ajst-25804	53	3	and	and	CCONJ
ajst-25804	53	4	analyzing	analyze	VERB
ajst-25804	53	5	these	these	DET
ajst-25804	53	6	contextual	contextual	ADJ
ajst-25804	53	7	information	information	NOUN
ajst-25804	53	8	,	,	PUNCT
ajst-25804	53	9	the	the	DET
ajst-25804	53	10	algorithm	algorithm	NOUN
ajst-25804	53	11	can	can	AUX
ajst-25804	53	12	better	well	ADV
ajst-25804	53	13	understand	understand	VERB
ajst-25804	53	14	the	the	DET
ajst-25804	53	15	overall	overall	ADJ
ajst-25804	53	16	structure	structure	NOUN
ajst-25804	53	17	of	of	ADP
ajst-25804	53	18	the	the	DET
ajst-25804	53	19	scene	scene	NOUN
ajst-25804	53	20	,	,	PUNCT
ajst-25804	53	21	so	so	SCONJ
ajst-25804	53	22	as	as	SCONJ
ajst-25804	53	23	to	to	PART
ajst-25804	53	24	locate	locate	VERB
ajst-25804	53	25	the	the	DET
ajst-25804	53	26	occluded	occluded	ADJ
ajst-25804	53	27	or	or	CCONJ
ajst-25804	53	28	densely	densely	ADV
ajst-25804	53	29	arranged	arrange	VERB
ajst-25804	53	30	objects	object	NOUN
ajst-25804	53	31	more	more	ADV
ajst-25804	53	32	accurately	accurately	ADV
ajst-25804	53	33	.	.	PUNCT
ajst-25804	54	1	for	for	ADP
ajst-25804	54	2	example	example	NOUN
ajst-25804	54	3	,	,	PUNCT
ajst-25804	54	4	when	when	SCONJ
ajst-25804	54	5	a	a	DET
ajst-25804	54	6	person	person	NOUN
ajst-25804	54	7	is	be	AUX
ajst-25804	54	8	detected	detect	VERB
ajst-25804	54	9	,	,	PUNCT
ajst-25804	54	10	the	the	DET
ajst-25804	54	11	algorithm	algorithm	NOUN
ajst-25804	54	12	can	can	AUX
ajst-25804	54	13	use	use	VERB
ajst-25804	54	14	the	the	DET
ajst-25804	54	15	context	context	NOUN
ajst-25804	54	16	information	information	NOUN
ajst-25804	54	17	to	to	PART
ajst-25804	54	18	infer	infer	VERB
ajst-25804	54	19	the	the	DET
ajst-25804	54	20	items	item	NOUN
ajst-25804	54	21	that	that	PRON
ajst-25804	54	22	the	the	DET
ajst-25804	54	23	person	person	NOUN
ajst-25804	54	24	may	may	AUX
ajst-25804	54	25	carry	carry	VERB
ajst-25804	54	26	(	(	PUNCT
ajst-25804	54	27	such	such	ADJ
ajst-25804	54	28	as	as	ADP
ajst-25804	54	29	backpacks	backpack	NOUN
ajst-25804	54	30	,	,	PUNCT
ajst-25804	54	31	handbags	handbag	NOUN
ajst-25804	54	32	,	,	PUNCT
ajst-25804	54	33	etc	etc	X
ajst-25804	54	34	.	.	X
ajst-25804	54	35	)	)	PUNCT
ajst-25804	54	36	,	,	PUNCT
ajst-25804	54	37	thus	thus	ADV
ajst-25804	54	38	improving	improve	VERB
ajst-25804	54	39	the	the	DET
ajst-25804	54	40	detection	detection	NOUN
ajst-25804	54	41	accuracy	accuracy	NOUN
ajst-25804	54	42	of	of	ADP
ajst-25804	54	43	these	these	DET
ajst-25804	54	44	small	small	ADJ
ajst-25804	54	45	objects	object	NOUN
ajst-25804	54	46	.	.	PUNCT
ajst-25804	55	1	building	building	NOUN
ajst-25804	55	2	component	component	NOUN
ajst-25804	55	3	model	model	NOUN
ajst-25804	55	4	is	be	AUX
ajst-25804	55	5	another	another	DET
ajst-25804	55	6	effective	effective	ADJ
ajst-25804	55	7	strategy	strategy	NOUN
ajst-25804	55	8	,	,	PUNCT
ajst-25804	55	9	especially	especially	ADV
ajst-25804	55	10	suitable	suitable	ADJ
ajst-25804	55	11	for	for	ADP
ajst-25804	55	12	dealing	deal	VERB
ajst-25804	55	13	with	with	ADP
ajst-25804	55	14	partially	partially	ADV
ajst-25804	55	15	occluded	occlude	VERB
ajst-25804	55	16	objects	object	NOUN
ajst-25804	55	17	.	.	PUNCT
ajst-25804	56	1	the	the	DET
ajst-25804	56	2	component	component	NOUN
ajst-25804	56	3	model	model	NOUN
ajst-25804	56	4	is	be	AUX
ajst-25804	56	5	expressed	express	VERB
ajst-25804	56	6	in	in	ADP
ajst-25804	56	7	the	the	DET
ajst-25804	56	8	following	following	ADJ
ajst-25804	56	9	ways	way	NOUN
ajst-25804	56	10	:	:	PUNCT
ajst-25804	56	11			X
ajst-25804	56	12	n321	n321	PROPN
ajst-25804	56	13	p,,p	p,,p	NOUN
ajst-25804	56	14	,	,	PUNCT
ajst-25804	56	15	p	p	X
ajst-25804	56	16	,	,	PUNCT
ajst-25804	56	17	p	p	NOUN
ajst-25804	56	18	o	o	NOUN
ajst-25804	56	19	(	(	PUNCT
ajst-25804	56	20	3	3	NUM
ajst-25804	56	21	)	)	PUNCT
ajst-25804	56	22			NOUN
ajst-25804	56	23			PROPN
ajst-25804	56	24			PROPN
ajst-25804	56	25	iip	iip	ADJ
ajst-25804	56	26	ii	ii	NOUN
ajst-25804	56	27	or	or	CCONJ
ajst-25804	56	28	partdetectp	partdetectp	ADJ
ajst-25804	56	29			PROPN
ajst-25804	56	30	(	(	PUNCT
ajst-25804	56	31	4	4	NUM
ajst-25804	56	32	)	)	PUNCT
ajst-25804	56	33			NOUN
ajst-25804	56	34			PROPN
ajst-25804	56	35			NOUN
ajst-25804	56	36			NUM
ajst-25804	57	1			NUM
ajst-25804	58	1			NOUN
ajst-25804	59	1	n	n	NOUN
ajst-25804	59	2	i	i	PRON
ajst-25804	59	3	ippip	ippip	VERB
ajst-25804	59	4	1	1	NUM
ajst-25804	59	5	io	io	X
ajst-25804	59	6	(	(	PUNCT
ajst-25804	59	7	5	5	NUM
ajst-25804	59	8	)	)	PUNCT
ajst-25804	59	9	where	where	SCONJ
ajst-25804	59	10	o	o	NOUN
ajst-25804	59	11	is	be	AUX
ajst-25804	59	12	an	an	DET
ajst-25804	59	13	object	object	NOUN
ajst-25804	59	14	composed	compose	VERB
ajst-25804	59	15	of	of	ADP
ajst-25804	59	16	multiple	multiple	ADJ
ajst-25804	59	17	components	component	NOUN
ajst-25804	59	18	ip	ip	VERB
ajst-25804	59	19	,	,	PUNCT
ajst-25804	59	20	ior	ior	PROPN
ajst-25804	59	21	partdetect	partdetect	NOUN
ajst-25804	59	22	is	be	AUX
ajst-25804	59	23	a	a	DET
ajst-25804	59	24	detector	detector	NOUN
ajst-25804	59	25	trained	train	VERB
ajst-25804	59	26	for	for	ADP
ajst-25804	59	27	the	the	DET
ajst-25804	59	28	i	i	PROPN
ajst-25804	59	29	component	component	NOUN
ajst-25804	59	30	,	,	PUNCT
ajst-25804	59	31			PROPN
ajst-25804	59	32	ipp	ipp	NOUN
ajst-25804	60	1	i	i	PRON
ajst-25804	60	2	is	be	AUX
ajst-25804	60	3	the	the	DET
ajst-25804	60	4	detection	detection	NOUN
ajst-25804	60	5	probability	probability	NOUN
ajst-25804	60	6	of	of	ADP
ajst-25804	60	7	the	the	DET
ajst-25804	60	8	component	component	NOUN
ajst-25804	60	9	ip	ip	VERB
ajst-25804	60	10	under	under	ADP
ajst-25804	60	11	the	the	DET
ajst-25804	60	12	given	give	VERB
ajst-25804	60	13	image	image	NOUN
ajst-25804	60	14	i	i	PRON
ajst-25804	60	15	,	,	PUNCT
ajst-25804	60	16	and	and	CCONJ
ajst-25804	60	17			NOUN
ajst-25804	60	18	iop	iop	PROPN
ajst-25804	60	19	is	be	AUX
ajst-25804	60	20	the	the	DET
ajst-25804	60	21	detection	detection	NOUN
ajst-25804	60	22	probability	probability	NOUN
ajst-25804	60	23	of	of	ADP
ajst-25804	60	24	the	the	DET
ajst-25804	60	25	object	object	NOUN
ajst-25804	60	26	o	o	NOUN
ajst-25804	60	27	under	under	ADP
ajst-25804	60	28	the	the	DET
ajst-25804	60	29	given	give	VERB
ajst-25804	60	30	image	image	NOUN
ajst-25804	60	31	i	i	PRON
ajst-25804	60	32	.	.	PUNCT
ajst-25804	61	1	in	in	ADP
ajst-25804	61	2	this	this	DET
ajst-25804	61	3	paper	paper	NOUN
ajst-25804	61	4	,	,	PUNCT
ajst-25804	61	5	the	the	DET
ajst-25804	61	6	object	object	NOUN
ajst-25804	61	7	is	be	AUX
ajst-25804	61	8	decomposed	decompose	VERB
ajst-25804	61	9	into	into	ADP
ajst-25804	61	10	several	several	ADJ
ajst-25804	61	11	parts	part	NOUN
ajst-25804	61	12	and	and	CCONJ
ajst-25804	61	13	an	an	DET
ajst-25804	61	14	independent	independent	ADJ
ajst-25804	61	15	detector	detector	NOUN
ajst-25804	61	16	is	be	AUX
ajst-25804	61	17	trained	train	VERB
ajst-25804	61	18	for	for	ADP
ajst-25804	61	19	each	each	DET
ajst-25804	61	20	part	part	NOUN
ajst-25804	61	21	.	.	PUNCT
ajst-25804	62	1	in	in	ADP
ajst-25804	62	2	the	the	DET
ajst-25804	62	3	detection	detection	NOUN
ajst-25804	62	4	process	process	NOUN
ajst-25804	62	5	,	,	PUNCT
ajst-25804	62	6	even	even	ADV
ajst-25804	62	7	if	if	SCONJ
ajst-25804	62	8	some	some	DET
ajst-25804	62	9	parts	part	NOUN
ajst-25804	62	10	of	of	ADP
ajst-25804	62	11	the	the	DET
ajst-25804	62	12	object	object	NOUN
ajst-25804	62	13	are	be	AUX
ajst-25804	62	14	blocked	block	VERB
ajst-25804	62	15	,	,	PUNCT
ajst-25804	62	16	the	the	DET
ajst-25804	62	17	algorithm	algorithm	NOUN
ajst-25804	62	18	can	can	AUX
ajst-25804	62	19	still	still	ADV
ajst-25804	62	20	infer	infer	VERB
ajst-25804	62	21	the	the	DET
ajst-25804	62	22	existence	existence	NOUN
ajst-25804	62	23	and	and	CCONJ
ajst-25804	62	24	position	position	NOUN
ajst-25804	62	25	of	of	ADP
ajst-25804	62	26	the	the	DET
ajst-25804	62	27	object	object	NOUN
ajst-25804	62	28	by	by	ADP
ajst-25804	62	29	identifying	identify	VERB
ajst-25804	62	30	other	other	ADJ
ajst-25804	62	31	visible	visible	ADJ
ajst-25804	62	32	parts	part	NOUN
ajst-25804	62	33	.	.	PUNCT
ajst-25804	63	1	this	this	DET
ajst-25804	63	2	method	method	NOUN
ajst-25804	63	3	not	not	PART
ajst-25804	63	4	only	only	ADV
ajst-25804	63	5	improves	improve	VERB
ajst-25804	63	6	the	the	DET
ajst-25804	63	7	robustness	robustness	NOUN
ajst-25804	63	8	of	of	ADP
ajst-25804	63	9	detection	detection	NOUN
ajst-25804	63	10	,	,	PUNCT
ajst-25804	63	11	but	but	CCONJ
ajst-25804	63	12	also	also	ADV
ajst-25804	63	13	enables	enable	VERB
ajst-25804	63	14	the	the	DET
ajst-25804	63	15	algorithm	algorithm	NOUN
ajst-25804	63	16	to	to	PART
ajst-25804	63	17	describe	describe	VERB
ajst-25804	63	18	the	the	DET
ajst-25804	63	19	structural	structural	ADJ
ajst-25804	63	20	characteristics	characteristic	NOUN
ajst-25804	63	21	of	of	ADP
ajst-25804	63	22	objects	object	NOUN
ajst-25804	63	23	more	more	ADV
ajst-25804	63	24	accurately	accurately	ADV
ajst-25804	63	25	.	.	PUNCT
ajst-25804	64	1	in	in	ADP
ajst-25804	64	2	addition	addition	NOUN
ajst-25804	64	3	,	,	PUNCT
ajst-25804	64	4	this	this	DET
ajst-25804	64	5	paper	paper	NOUN
ajst-25804	64	6	optimizes	optimize	VERB
ajst-25804	64	7	the	the	DET
ajst-25804	64	8	computational	computational	ADJ
ajst-25804	64	9	efficiency	efficiency	NOUN
ajst-25804	64	10	and	and	CCONJ
ajst-25804	64	11	memory	memory	NOUN
ajst-25804	64	12	occupation	occupation	NOUN
ajst-25804	64	13	of	of	ADP
ajst-25804	64	14	object	object	NOUN
ajst-25804	64	15	detection	detection	NOUN
ajst-25804	64	16	algorithm	algorithm	NOUN
ajst-25804	64	17	by	by	ADP
ajst-25804	64	18	model	model	NOUN
ajst-25804	64	19	pruning	pruning	NOUN
ajst-25804	64	20	,	,	PUNCT
ajst-25804	64	21	quantization	quantization	NOUN
ajst-25804	64	22	and	and	CCONJ
ajst-25804	64	23	lightweight	lightweight	ADJ
ajst-25804	64	24	network	network	NOUN
ajst-25804	64	25	design	design	NOUN
ajst-25804	64	26	.	.	PUNCT
ajst-25804	65	1	at	at	ADP
ajst-25804	65	2	the	the	DET
ajst-25804	65	3	same	same	ADJ
ajst-25804	65	4	time	time	NOUN
ajst-25804	65	5	,	,	PUNCT
ajst-25804	65	6	parallel	parallel	ADJ
ajst-25804	65	7	computing	computing	NOUN
ajst-25804	65	8	and	and	CCONJ
ajst-25804	65	9	hardware	hardware	NOUN
ajst-25804	65	10	acceleration	acceleration	NOUN
ajst-25804	65	11	are	be	AUX
ajst-25804	65	12	used	use	VERB
ajst-25804	65	13	to	to	PART
ajst-25804	65	14	further	far	ADV
ajst-25804	65	15	improve	improve	VERB
ajst-25804	65	16	the	the	DET
ajst-25804	65	17	realtime	realtime	ADJ
ajst-25804	65	18	performance	performance	NOUN
ajst-25804	65	19	of	of	ADP
ajst-25804	65	20	the	the	DET
ajst-25804	65	21	algorithm	algorithm	NOUN
ajst-25804	65	22	.	.	PUNCT
ajst-25804	66	1	through	through	ADP
ajst-25804	66	2	these	these	DET
ajst-25804	66	3	optimization	optimization	NOUN
ajst-25804	66	4	measures	measure	NOUN
ajst-25804	66	5	,	,	PUNCT
ajst-25804	66	6	we	we	PRON
ajst-25804	66	7	can	can	AUX
ajst-25804	66	8	ensure	ensure	VERB
ajst-25804	66	9	the	the	DET
ajst-25804	66	10	detection	detection	NOUN
ajst-25804	66	11	accuracy	accuracy	NOUN
ajst-25804	66	12	and	and	CCONJ
ajst-25804	66	13	achieve	achieve	VERB
ajst-25804	66	14	faster	fast	ADJ
ajst-25804	66	15	detection	detection	NOUN
ajst-25804	66	16	speed	speed	NOUN
ajst-25804	66	17	to	to	PART
ajst-25804	66	18	meet	meet	VERB
ajst-25804	66	19	the	the	DET
ajst-25804	66	20	needs	need	NOUN
ajst-25804	66	21	of	of	ADP
ajst-25804	66	22	practical	practical	ADJ
ajst-25804	66	23	application	application	NOUN
ajst-25804	66	24	.	.	PUNCT
ajst-25804	67	1	3.3	3.3	NUM
ajst-25804	67	2	.	.	PUNCT
ajst-25804	67	3	experiment	experiment	NOUN
ajst-25804	67	4	and	and	CCONJ
ajst-25804	67	5	result	result	VERB
ajst-25804	67	6	analysis	analysis	NOUN
ajst-25804	67	7	in	in	ADP
ajst-25804	67	8	order	order	NOUN
ajst-25804	67	9	to	to	PART
ajst-25804	67	10	comprehensively	comprehensively	ADV
ajst-25804	67	11	and	and	CCONJ
ajst-25804	67	12	deeply	deeply	ADV
ajst-25804	67	13	verify	verify	VERB
ajst-25804	67	14	the	the	DET
ajst-25804	67	15	effectiveness	effectiveness	NOUN
ajst-25804	67	16	of	of	ADP
ajst-25804	67	17	the	the	DET
ajst-25804	67	18	proposed	propose	VERB
ajst-25804	67	19	algorithm	algorithm	NOUN
ajst-25804	67	20	in	in	ADP
ajst-25804	67	21	practical	practical	ADJ
ajst-25804	67	22	application	application	NOUN
ajst-25804	67	23	,	,	PUNCT
ajst-25804	67	24	this	this	DET
ajst-25804	67	25	section	section	NOUN
ajst-25804	67	26	carefully	carefully	ADV
ajst-25804	67	27	designs	design	VERB
ajst-25804	67	28	and	and	CCONJ
ajst-25804	67	29	implements	implement	VERB
ajst-25804	67	30	comparative	comparative	ADJ
ajst-25804	67	31	experiments	experiment	NOUN
ajst-25804	67	32	.	.	PUNCT
ajst-25804	68	1	this	this	DET
ajst-25804	68	2	verification	verification	NOUN
ajst-25804	68	3	process	process	NOUN
ajst-25804	68	4	aims	aim	VERB
ajst-25804	68	5	to	to	PART
ajst-25804	68	6	show	show	VERB
ajst-25804	68	7	the	the	DET
ajst-25804	68	8	performance	performance	NOUN
ajst-25804	68	9	of	of	ADP
ajst-25804	68	10	the	the	DET
ajst-25804	68	11	new	new	ADJ
ajst-25804	68	12	algorithm	algorithm	NOUN
ajst-25804	68	13	in	in	ADP
ajst-25804	68	14	the	the	DET
ajst-25804	68	15	object	object	NOUN
ajst-25804	68	16	detection	detection	NOUN
ajst-25804	68	17	task	task	NOUN
ajst-25804	68	18	through	through	ADP
ajst-25804	68	19	objective	objective	ADJ
ajst-25804	68	20	data	datum	NOUN
ajst-25804	68	21	and	and	CCONJ
ajst-25804	68	22	intuitive	intuitive	ADJ
ajst-25804	68	23	14	14	NUM
ajst-25804	68	24	visualization	visualization	NOUN
ajst-25804	68	25	results	result	NOUN
ajst-25804	68	26	,	,	PUNCT
ajst-25804	68	27	and	and	CCONJ
ajst-25804	68	28	compare	compare	VERB
ajst-25804	68	29	it	it	PRON
ajst-25804	68	30	with	with	ADP
ajst-25804	68	31	the	the	DET
ajst-25804	68	32	technical	technical	ADJ
ajst-25804	68	33	standards	standard	NOUN
ajst-25804	68	34	widely	widely	ADV
ajst-25804	68	35	recognized	recognize	VERB
ajst-25804	68	36	by	by	ADP
ajst-25804	68	37	the	the	DET
ajst-25804	68	38	industry	industry	NOUN
ajst-25804	68	39	,	,	PUNCT
ajst-25804	68	40	thus	thus	ADV
ajst-25804	68	41	highlighting	highlight	VERB
ajst-25804	68	42	its	its	PRON
ajst-25804	68	43	innovative	innovative	ADJ
ajst-25804	68	44	value	value	NOUN
ajst-25804	68	45	and	and	CCONJ
ajst-25804	68	46	potential	potential	ADJ
ajst-25804	68	47	improvement	improvement	NOUN
ajst-25804	68	48	space	space	NOUN
ajst-25804	68	49	.	.	PUNCT
ajst-25804	69	1	in	in	ADP
ajst-25804	69	2	order	order	NOUN
ajst-25804	69	3	to	to	PART
ajst-25804	69	4	show	show	VERB
ajst-25804	69	5	the	the	DET
ajst-25804	69	6	performance	performance	NOUN
ajst-25804	69	7	level	level	NOUN
ajst-25804	69	8	of	of	ADP
ajst-25804	69	9	the	the	DET
ajst-25804	69	10	proposed	propose	VERB
ajst-25804	69	11	algorithm	algorithm	NOUN
ajst-25804	69	12	more	more	ADV
ajst-25804	69	13	intuitively	intuitively	ADV
ajst-25804	69	14	,	,	PUNCT
ajst-25804	69	15	we	we	PRON
ajst-25804	69	16	choose	choose	VERB
ajst-25804	69	17	—	—	PUNCT
ajst-25804	69	18	yolo	yolo	PROPN
ajst-25804	69	19	,	,	PUNCT
ajst-25804	69	20	the	the	DET
ajst-25804	69	21	current	current	ADJ
ajst-25804	69	22	mainstream	mainstream	ADJ
ajst-25804	69	23	object	object	NOUN
ajst-25804	69	24	detection	detection	NOUN
ajst-25804	69	25	algorithm	algorithm	NOUN
ajst-25804	69	26	,	,	PUNCT
ajst-25804	69	27	as	as	SCONJ
ajst-25804	69	28	the	the	DET
ajst-25804	69	29	comparison	comparison	NOUN
ajst-25804	69	30	object	object	VERB
ajst-25804	69	31	.	.	PUNCT
ajst-25804	70	1	yolo	yolo	ADJ
ajst-25804	70	2	occupies	occupy	VERB
ajst-25804	70	3	an	an	DET
ajst-25804	70	4	important	important	ADJ
ajst-25804	70	5	position	position	NOUN
ajst-25804	70	6	in	in	ADP
ajst-25804	70	7	the	the	DET
ajst-25804	70	8	field	field	NOUN
ajst-25804	70	9	of	of	ADP
ajst-25804	70	10	object	object	NOUN
ajst-25804	70	11	detection	detection	NOUN
ajst-25804	70	12	because	because	SCONJ
ajst-25804	70	13	of	of	ADP
ajst-25804	70	14	its	its	PRON
ajst-25804	70	15	high	high	ADJ
ajst-25804	70	16	speed	speed	NOUN
ajst-25804	70	17	and	and	CCONJ
ajst-25804	70	18	high	high	ADJ
ajst-25804	70	19	precision	precision	NOUN
ajst-25804	70	20	.	.	PUNCT
ajst-25804	71	1	in	in	ADP
ajst-25804	71	2	this	this	DET
ajst-25804	71	3	paper	paper	NOUN
ajst-25804	71	4	,	,	PUNCT
ajst-25804	71	5	the	the	DET
ajst-25804	71	6	proposed	propose	VERB
ajst-25804	71	7	algorithm	algorithm	NOUN
ajst-25804	71	8	and	and	CCONJ
ajst-25804	71	9	yolo	yolo	ADJ
ajst-25804	71	10	algorithm	algorithm	NOUN
ajst-25804	71	11	are	be	AUX
ajst-25804	71	12	run	run	VERB
ajst-25804	71	13	on	on	ADP
ajst-25804	71	14	the	the	DET
ajst-25804	71	15	same	same	ADJ
ajst-25804	71	16	public	public	ADJ
ajst-25804	71	17	data	datum	NOUN
ajst-25804	71	18	set	set	VERB
ajst-25804	71	19	,	,	PUNCT
ajst-25804	71	20	and	and	CCONJ
ajst-25804	71	21	their	their	PRON
ajst-25804	71	22	recognition	recognition	NOUN
ajst-25804	71	23	accuracy	accuracy	NOUN
ajst-25804	71	24	is	be	AUX
ajst-25804	71	25	recorded	record	VERB
ajst-25804	71	26	.	.	PUNCT
ajst-25804	72	1	by	by	ADP
ajst-25804	72	2	comparing	compare	VERB
ajst-25804	72	3	their	their	PRON
ajst-25804	72	4	performances	performance	NOUN
ajst-25804	72	5	on	on	ADP
ajst-25804	72	6	the	the	DET
ajst-25804	72	7	same	same	ADJ
ajst-25804	72	8	data	datum	NOUN
ajst-25804	72	9	set	set	NOUN
ajst-25804	72	10	,	,	PUNCT
ajst-25804	72	11	we	we	PRON
ajst-25804	72	12	can	can	AUX
ajst-25804	72	13	see	see	VERB
ajst-25804	72	14	the	the	DET
ajst-25804	72	15	advantages	advantage	NOUN
ajst-25804	72	16	or	or	CCONJ
ajst-25804	72	17	disadvantages	disadvantage	NOUN
ajst-25804	72	18	of	of	ADP
ajst-25804	72	19	the	the	DET
ajst-25804	72	20	new	new	ADJ
ajst-25804	72	21	algorithm	algorithm	NOUN
ajst-25804	72	22	more	more	ADV
ajst-25804	72	23	clearly	clearly	ADV
ajst-25804	72	24	.	.	PUNCT
ajst-25804	73	1	the	the	DET
ajst-25804	73	2	results	result	NOUN
ajst-25804	73	3	are	be	AUX
ajst-25804	73	4	shown	show	VERB
ajst-25804	73	5	in	in	ADP
ajst-25804	73	6	figure	figure	NOUN
ajst-25804	73	7	1	1	NUM
ajst-25804	73	8	and	and	CCONJ
ajst-25804	73	9	figure	figure	VERB
ajst-25804	73	10	2	2	NUM
ajst-25804	73	11	:	:	PUNCT
ajst-25804	73	12	figure	figure	NOUN
ajst-25804	73	13	1	1	NUM
ajst-25804	73	14	.	.	PUNCT
ajst-25804	73	15	recognition	recognition	NOUN
ajst-25804	73	16	accuracy	accuracy	NOUN
ajst-25804	73	17	(	(	PUNCT
ajst-25804	73	18	proposed	propose	VERB
ajst-25804	73	19	algorithm	algorithm	NOUN
ajst-25804	73	20	)	)	PUNCT
ajst-25804	73	21	figure	figure	NOUN
ajst-25804	73	22	2	2	NUM
ajst-25804	73	23	.	.	PUNCT
ajst-25804	73	24	recognition	recognition	NOUN
ajst-25804	73	25	accuracy	accuracy	NOUN
ajst-25804	73	26	(	(	PUNCT
ajst-25804	73	27	yolo	yolo	ADJ
ajst-25804	73	28	algorithm	algorithm	NOUN
ajst-25804	73	29	)	)	PUNCT
ajst-25804	73	30	15	15	NUM
ajst-25804	74	1	it	it	PRON
ajst-25804	74	2	can	can	AUX
ajst-25804	74	3	be	be	AUX
ajst-25804	74	4	seen	see	VERB
ajst-25804	74	5	that	that	SCONJ
ajst-25804	74	6	the	the	DET
ajst-25804	74	7	overall	overall	ADJ
ajst-25804	74	8	recognition	recognition	NOUN
ajst-25804	74	9	accuracy	accuracy	NOUN
ajst-25804	74	10	of	of	ADP
ajst-25804	74	11	the	the	DET
ajst-25804	74	12	proposed	propose	VERB
ajst-25804	74	13	algorithm	algorithm	NOUN
ajst-25804	74	14	is	be	AUX
ajst-25804	74	15	4.5	4.5	NUM
ajst-25804	74	16	%	%	NOUN
ajst-25804	74	17	higher	high	ADJ
ajst-25804	74	18	than	than	ADP
ajst-25804	74	19	that	that	PRON
ajst-25804	74	20	of	of	ADP
ajst-25804	74	21	yolo	yolo	NOUN
ajst-25804	74	22	(	(	PUNCT
ajst-25804	74	23	89.5	89.5	NUM
ajst-25804	74	24	%	%	NOUN
ajst-25804	74	25	vs	vs	ADP
ajst-25804	74	26	85	85	NUM
ajst-25804	74	27	%	%	NOUN
ajst-25804	74	28	)	)	PUNCT
ajst-25804	74	29	,	,	PUNCT
ajst-25804	74	30	which	which	PRON
ajst-25804	74	31	shows	show	VERB
ajst-25804	74	32	that	that	SCONJ
ajst-25804	74	33	the	the	DET
ajst-25804	74	34	proposed	propose	VERB
ajst-25804	74	35	algorithm	algorithm	NOUN
ajst-25804	74	36	has	have	VERB
ajst-25804	74	37	certain	certain	ADJ
ajst-25804	74	38	advantages	advantage	NOUN
ajst-25804	74	39	in	in	ADP
ajst-25804	74	40	overall	overall	ADJ
ajst-25804	74	41	detection	detection	NOUN
ajst-25804	74	42	ability	ability	NOUN
ajst-25804	74	43	.	.	PUNCT
ajst-25804	75	1	in	in	ADP
ajst-25804	75	2	addition	addition	NOUN
ajst-25804	75	3	to	to	ADP
ajst-25804	75	4	the	the	DET
ajst-25804	75	5	recognition	recognition	NOUN
ajst-25804	75	6	accuracy	accuracy	NOUN
ajst-25804	75	7	,	,	PUNCT
ajst-25804	75	8	the	the	DET
ajst-25804	75	9	calculation	calculation	NOUN
ajst-25804	75	10	efficiency	efficiency	NOUN
ajst-25804	75	11	and	and	CCONJ
ajst-25804	75	12	memory	memory	NOUN
ajst-25804	75	13	occupation	occupation	NOUN
ajst-25804	75	14	of	of	ADP
ajst-25804	75	15	the	the	DET
ajst-25804	75	16	algorithm	algorithm	NOUN
ajst-25804	75	17	are	be	AUX
ajst-25804	75	18	also	also	ADV
ajst-25804	75	19	important	important	ADJ
ajst-25804	75	20	indicators	indicator	NOUN
ajst-25804	75	21	to	to	PART
ajst-25804	75	22	measure	measure	VERB
ajst-25804	75	23	its	its	PRON
ajst-25804	75	24	practical	practical	ADJ
ajst-25804	75	25	application	application	NOUN
ajst-25804	75	26	value	value	NOUN
ajst-25804	75	27	.	.	PUNCT
ajst-25804	76	1	therefore	therefore	ADV
ajst-25804	76	2	,	,	PUNCT
ajst-25804	76	3	this	this	DET
ajst-25804	76	4	paper	paper	NOUN
ajst-25804	76	5	further	far	ADV
ajst-25804	76	6	tests	test	VERB
ajst-25804	76	7	the	the	DET
ajst-25804	76	8	performance	performance	NOUN
ajst-25804	76	9	of	of	ADP
ajst-25804	76	10	the	the	DET
ajst-25804	76	11	proposed	propose	VERB
ajst-25804	76	12	algorithm	algorithm	NOUN
ajst-25804	76	13	in	in	ADP
ajst-25804	76	14	these	these	DET
ajst-25804	76	15	aspects	aspect	NOUN
ajst-25804	76	16	,	,	PUNCT
ajst-25804	76	17	and	and	CCONJ
ajst-25804	76	18	summarizes	summarize	VERB
ajst-25804	76	19	the	the	DET
ajst-25804	76	20	results	result	NOUN
ajst-25804	76	21	in	in	ADP
ajst-25804	76	22	table	table	NOUN
ajst-25804	76	23	1	1	NUM
ajst-25804	76	24	.	.	PUNCT
ajst-25804	77	1	the	the	DET
ajst-25804	77	2	table	table	NOUN
ajst-25804	77	3	lists	list	VERB
ajst-25804	77	4	the	the	DET
ajst-25804	77	5	key	key	ADJ
ajst-25804	77	6	data	datum	NOUN
ajst-25804	77	7	of	of	ADP
ajst-25804	77	8	the	the	DET
ajst-25804	77	9	algorithm	algorithm	NOUN
ajst-25804	77	10	in	in	ADP
ajst-25804	77	11	detail	detail	NOUN
ajst-25804	77	12	,	,	PUNCT
ajst-25804	77	13	such	such	ADJ
ajst-25804	77	14	as	as	ADP
ajst-25804	77	15	processing	processing	NOUN
ajst-25804	77	16	speed	speed	NOUN
ajst-25804	77	17	and	and	CCONJ
ajst-25804	77	18	memory	memory	NOUN
ajst-25804	77	19	occupation	occupation	NOUN
ajst-25804	77	20	,	,	PUNCT
ajst-25804	77	21	which	which	PRON
ajst-25804	77	22	provides	provide	VERB
ajst-25804	77	23	an	an	DET
ajst-25804	77	24	important	important	ADJ
ajst-25804	77	25	basis	basis	NOUN
ajst-25804	77	26	for	for	ADP
ajst-25804	77	27	comprehensively	comprehensively	ADV
ajst-25804	77	28	evaluating	evaluate	VERB
ajst-25804	77	29	the	the	DET
ajst-25804	77	30	performance	performance	NOUN
ajst-25804	77	31	of	of	ADP
ajst-25804	77	32	the	the	DET
ajst-25804	77	33	algorithm	algorithm	NOUN
ajst-25804	77	34	.	.	PUNCT
ajst-25804	78	1	table	table	NOUN
ajst-25804	78	2	1	1	NUM
ajst-25804	78	3	.	.	PUNCT
ajst-25804	78	4	comprehensive	comprehensive	ADJ
ajst-25804	78	5	evaluation	evaluation	NOUN
ajst-25804	78	6	of	of	ADP
ajst-25804	78	7	algorithm	algorithm	NOUN
ajst-25804	78	8	performance	performance	NOUN
ajst-25804	78	9	algorithm	algorithm	NOUN
ajst-25804	78	10	name	name	NOUN
ajst-25804	78	11	accuracy	accuracy	NOUN
ajst-25804	78	12	(	(	PUNCT
ajst-25804	78	13	%	%	INTJ
ajst-25804	78	14	)	)	PUNCT
ajst-25804	78	15	processing	processing	NOUN
ajst-25804	78	16	speed	speed	NOUN
ajst-25804	78	17	(	(	PUNCT
ajst-25804	78	18	frames	frame	NOUN
ajst-25804	78	19	per	per	ADP
ajst-25804	78	20	second	second	ADJ
ajst-25804	78	21	,	,	PUNCT
ajst-25804	78	22	fps	fps	PROPN
ajst-25804	78	23	)	)	PUNCT
ajst-25804	78	24	memory	memory	NOUN
ajst-25804	78	25	footprint	footprint	NOUN
ajst-25804	78	26	(	(	PUNCT
ajst-25804	78	27	mb	mb	NOUN
ajst-25804	78	28	)	)	PUNCT
ajst-25804	78	29	proposed	propose	VERB
ajst-25804	78	30	algorithm	algorithm	NOUN
ajst-25804	78	31	87.5	87.5	NUM
ajst-25804	78	32	250	250	NUM
ajst-25804	78	33	150	150	NUM
ajst-25804	78	34	yolo	yolo	ADJ
ajst-25804	78	35	algorithm	algorithm	NOUN
ajst-25804	78	36	85.0	85.0	NUM
ajst-25804	78	37	300	300	NUM
ajst-25804	78	38	120	120	NUM
ajst-25804	78	39	description	description	NOUN
ajst-25804	78	40	:	:	PUNCT
ajst-25804	78	41	processing	processing	NOUN
ajst-25804	78	42	speed	speed	NOUN
ajst-25804	78	43	(	(	PUNCT
ajst-25804	78	44	fps	fps	PROPN
ajst-25804	78	45	):	):	PUNCT
ajst-25804	78	46	it	it	PRON
ajst-25804	78	47	reflects	reflect	VERB
ajst-25804	78	48	the	the	DET
ajst-25804	78	49	computational	computational	ADJ
ajst-25804	78	50	efficiency	efficiency	NOUN
ajst-25804	78	51	of	of	ADP
ajst-25804	78	52	the	the	DET
ajst-25804	78	53	algorithm	algorithm	NOUN
ajst-25804	78	54	.	.	PUNCT
ajst-25804	79	1	yolo	yolo	ADJ
ajst-25804	79	2	algorithm	algorithm	NOUN
ajst-25804	79	3	processes	process	VERB
ajst-25804	79	4	250	250	NUM
ajst-25804	79	5	frames	frame	NOUN
ajst-25804	79	6	per	per	ADP
ajst-25804	79	7	second	second	NOUN
ajst-25804	79	8	,	,	PUNCT
ajst-25804	79	9	while	while	SCONJ
ajst-25804	79	10	the	the	DET
ajst-25804	79	11	proposed	propose	VERB
ajst-25804	79	12	algorithm	algorithm	NOUN
ajst-25804	79	13	processes	process	VERB
ajst-25804	79	14	300	300	NUM
ajst-25804	79	15	frames	frame	NOUN
ajst-25804	79	16	per	per	ADP
ajst-25804	79	17	second	second	NOUN
ajst-25804	79	18	,	,	PUNCT
ajst-25804	79	19	which	which	PRON
ajst-25804	79	20	shows	show	VERB
ajst-25804	79	21	that	that	SCONJ
ajst-25804	79	22	the	the	DET
ajst-25804	79	23	proposed	propose	VERB
ajst-25804	79	24	algorithm	algorithm	NOUN
ajst-25804	79	25	has	have	VERB
ajst-25804	79	26	a	a	DET
ajst-25804	79	27	slight	slight	ADJ
ajst-25804	79	28	advantage	advantage	NOUN
ajst-25804	79	29	in	in	ADP
ajst-25804	79	30	speed	speed	NOUN
ajst-25804	79	31	.	.	PUNCT
ajst-25804	80	1	memory	memory	NOUN
ajst-25804	80	2	occupation	occupation	NOUN
ajst-25804	80	3	(	(	PUNCT
ajst-25804	80	4	mb	mb	NOUN
ajst-25804	80	5	):	):	PUNCT
ajst-25804	80	6	the	the	DET
ajst-25804	80	7	memory	memory	NOUN
ajst-25804	80	8	space	space	NOUN
ajst-25804	80	9	occupied	occupy	VERB
ajst-25804	80	10	by	by	ADP
ajst-25804	80	11	the	the	DET
ajst-25804	80	12	algorithm	algorithm	NOUN
ajst-25804	80	13	in	in	ADP
ajst-25804	80	14	the	the	DET
ajst-25804	80	15	running	running	NOUN
ajst-25804	80	16	process	process	NOUN
ajst-25804	80	17	is	be	AUX
ajst-25804	80	18	recorded	record	VERB
ajst-25804	80	19	.	.	PUNCT
ajst-25804	81	1	yolo	yolo	ADJ
ajst-25804	81	2	algorithm	algorithm	PROPN
ajst-25804	81	3	occupies	occupy	VERB
ajst-25804	81	4	150	150	NUM
ajst-25804	81	5	mb	mb	NOUN
ajst-25804	81	6	and	and	CCONJ
ajst-25804	81	7	the	the	DET
ajst-25804	81	8	proposed	propose	VERB
ajst-25804	81	9	algorithm	algorithm	NOUN
ajst-25804	81	10	occupies	occupy	VERB
ajst-25804	81	11	120	120	NUM
ajst-25804	81	12	mb	mb	NOUN
ajst-25804	81	13	,	,	PUNCT
ajst-25804	81	14	indicating	indicate	VERB
ajst-25804	81	15	that	that	SCONJ
ajst-25804	81	16	the	the	DET
ajst-25804	81	17	proposed	propose	VERB
ajst-25804	81	18	algorithm	algorithm	NOUN
ajst-25804	81	19	is	be	AUX
ajst-25804	81	20	more	more	ADV
ajst-25804	81	21	efficient	efficient	ADJ
ajst-25804	81	22	in	in	ADP
ajst-25804	81	23	memory	memory	NOUN
ajst-25804	81	24	occupation	occupation	NOUN
ajst-25804	81	25	.	.	PUNCT
ajst-25804	82	1	4	4	X
ajst-25804	82	2	.	.	X
ajst-25804	82	3	conclusions	conclusion	NOUN
ajst-25804	82	4	this	this	DET
ajst-25804	82	5	paper	paper	NOUN
ajst-25804	82	6	focuses	focus	VERB
ajst-25804	82	7	on	on	ADP
ajst-25804	82	8	complex	complex	ADJ
ajst-25804	82	9	scene	scene	NOUN
ajst-25804	82	10	understanding	understanding	NOUN
ajst-25804	82	11	and	and	CCONJ
ajst-25804	82	12	object	object	NOUN
ajst-25804	82	13	detection	detection	NOUN
ajst-25804	82	14	,	,	PUNCT
ajst-25804	82	15	and	and	CCONJ
ajst-25804	82	16	puts	put	VERB
ajst-25804	82	17	forward	forward	ADV
ajst-25804	82	18	a	a	DET
ajst-25804	82	19	series	series	NOUN
ajst-25804	82	20	of	of	ADP
ajst-25804	82	21	innovative	innovative	ADJ
ajst-25804	82	22	algorithms	algorithm	NOUN
ajst-25804	82	23	and	and	CCONJ
ajst-25804	82	24	technologies	technology	NOUN
ajst-25804	82	25	.	.	PUNCT
ajst-25804	83	1	in	in	ADP
ajst-25804	83	2	multi	multi	ADJ
ajst-25804	83	3	-	-	ADJ
ajst-25804	83	4	scale	scale	ADJ
ajst-25804	83	5	object	object	NOUN
ajst-25804	83	6	detection	detection	NOUN
ajst-25804	83	7	,	,	PUNCT
ajst-25804	83	8	by	by	ADP
ajst-25804	83	9	introducing	introduce	VERB
ajst-25804	83	10	fpn	fpn	NOUN
ajst-25804	83	11	and	and	CCONJ
ajst-25804	83	12	attention	attention	NOUN
ajst-25804	83	13	mechanism	mechanism	NOUN
ajst-25804	83	14	,	,	PUNCT
ajst-25804	83	15	the	the	DET
ajst-25804	83	16	detection	detection	NOUN
ajst-25804	83	17	ability	ability	NOUN
ajst-25804	83	18	of	of	ADP
ajst-25804	83	19	the	the	DET
ajst-25804	83	20	algorithm	algorithm	NOUN
ajst-25804	83	21	for	for	ADP
ajst-25804	83	22	objects	object	NOUN
ajst-25804	83	23	of	of	ADP
ajst-25804	83	24	different	different	ADJ
ajst-25804	83	25	sizes	size	NOUN
ajst-25804	83	26	is	be	AUX
ajst-25804	83	27	significantly	significantly	ADV
ajst-25804	83	28	improved	improve	VERB
ajst-25804	83	29	.	.	PUNCT
ajst-25804	84	1	for	for	ADP
ajst-25804	84	2	occlusion	occlusion	NOUN
ajst-25804	84	3	and	and	CCONJ
ajst-25804	84	4	dense	dense	ADJ
ajst-25804	84	5	scenes	scene	NOUN
ajst-25804	84	6	,	,	PUNCT
ajst-25804	84	7	this	this	DET
ajst-25804	84	8	study	study	NOUN
ajst-25804	84	9	effectively	effectively	ADV
ajst-25804	84	10	improves	improve	VERB
ajst-25804	84	11	the	the	DET
ajst-25804	84	12	detection	detection	NOUN
ajst-25804	84	13	performance	performance	NOUN
ajst-25804	84	14	by	by	ADP
ajst-25804	84	15	using	use	VERB
ajst-25804	84	16	context	context	NOUN
ajst-25804	84	17	information	information	NOUN
ajst-25804	84	18	and	and	CCONJ
ajst-25804	84	19	optimized	optimize	VERB
ajst-25804	84	20	processing	processing	NOUN
ajst-25804	84	21	strategy	strategy	NOUN
ajst-25804	84	22	.	.	PUNCT
ajst-25804	85	1	at	at	ADP
ajst-25804	85	2	the	the	DET
ajst-25804	85	3	same	same	ADJ
ajst-25804	85	4	time	time	NOUN
ajst-25804	85	5	,	,	PUNCT
ajst-25804	85	6	in	in	ADP
ajst-25804	85	7	terms	term	NOUN
ajst-25804	85	8	of	of	ADP
ajst-25804	85	9	real	real	ADJ
ajst-25804	85	10	-	-	PUNCT
ajst-25804	85	11	time	time	NOUN
ajst-25804	85	12	performance	performance	NOUN
ajst-25804	85	13	and	and	CCONJ
ajst-25804	85	14	efficiency	efficiency	NOUN
ajst-25804	85	15	optimization	optimization	NOUN
ajst-25804	85	16	,	,	PUNCT
ajst-25804	85	17	faster	fast	ADJ
ajst-25804	85	18	detection	detection	NOUN
ajst-25804	85	19	speed	speed	NOUN
ajst-25804	85	20	is	be	AUX
ajst-25804	85	21	realized	realize	VERB
ajst-25804	85	22	through	through	ADP
ajst-25804	85	23	model	model	NOUN
ajst-25804	85	24	pruning	pruning	NOUN
ajst-25804	85	25	and	and	CCONJ
ajst-25804	85	26	hardware	hardware	NOUN
ajst-25804	85	27	acceleration	acceleration	NOUN
ajst-25804	85	28	.	.	PUNCT
ajst-25804	86	1	experimental	experimental	ADJ
ajst-25804	86	2	results	result	NOUN
ajst-25804	86	3	show	show	VERB
ajst-25804	86	4	that	that	SCONJ
ajst-25804	86	5	the	the	DET
ajst-25804	86	6	proposed	propose	VERB
ajst-25804	86	7	algorithm	algorithm	NOUN
ajst-25804	86	8	has	have	AUX
ajst-25804	86	9	achieved	achieve	VERB
ajst-25804	86	10	excellent	excellent	ADJ
ajst-25804	86	11	performance	performance	NOUN
ajst-25804	86	12	on	on	ADP
ajst-25804	86	13	public	public	ADJ
ajst-25804	86	14	data	datum	NOUN
ajst-25804	86	15	sets	set	NOUN
ajst-25804	86	16	,	,	PUNCT
ajst-25804	86	17	which	which	PRON
ajst-25804	86	18	verifies	verify	VERB
ajst-25804	86	19	its	its	PRON
ajst-25804	86	20	effectiveness	effectiveness	NOUN
ajst-25804	86	21	and	and	CCONJ
ajst-25804	86	22	practicability	practicability	NOUN
ajst-25804	86	23	.	.	PUNCT
ajst-25804	87	1	in	in	ADP
ajst-25804	87	2	the	the	DET
ajst-25804	87	3	future	future	NOUN
ajst-25804	87	4	,	,	PUNCT
ajst-25804	87	5	this	this	DET
ajst-25804	87	6	study	study	NOUN
ajst-25804	87	7	will	will	AUX
ajst-25804	87	8	continue	continue	VERB
ajst-25804	87	9	to	to	PART
ajst-25804	87	10	explore	explore	VERB
ajst-25804	87	11	more	more	ADV
ajst-25804	87	12	efficient	efficient	ADJ
ajst-25804	87	13	algorithms	algorithm	NOUN
ajst-25804	87	14	for	for	ADP
ajst-25804	87	15	complex	complex	ADJ
ajst-25804	87	16	scene	scene	NOUN
ajst-25804	87	17	understanding	understanding	NOUN
ajst-25804	87	18	and	and	CCONJ
ajst-25804	87	19	object	object	NOUN
ajst-25804	87	20	detection	detection	NOUN
ajst-25804	87	21	,	,	PUNCT
ajst-25804	87	22	especially	especially	ADV
ajst-25804	87	23	for	for	ADP
ajst-25804	87	24	extreme	extreme	ADJ
ajst-25804	87	25	situations	situation	NOUN
ajst-25804	87	26	and	and	CCONJ
ajst-25804	87	27	complex	complex	ADJ
ajst-25804	87	28	backgrounds	background	NOUN
ajst-25804	87	29	.	.	PUNCT
ajst-25804	88	1	at	at	ADP
ajst-25804	88	2	the	the	DET
ajst-25804	88	3	same	same	ADJ
ajst-25804	88	4	time	time	NOUN
ajst-25804	88	5	,	,	PUNCT
ajst-25804	88	6	cross	cross	ADJ
ajst-25804	88	7	-	-	ADJ
ajst-25804	88	8	modal	modal	ADJ
ajst-25804	88	9	fusion	fusion	NOUN
ajst-25804	88	10	technology	technology	NOUN
ajst-25804	88	11	will	will	AUX
ajst-25804	88	12	be	be	AUX
ajst-25804	88	13	deeply	deeply	ADV
ajst-25804	88	14	studied	study	VERB
ajst-25804	88	15	to	to	PART
ajst-25804	88	16	realize	realize	VERB
ajst-25804	88	17	effective	effective	ADJ
ajst-25804	88	18	fusion	fusion	NOUN
ajst-25804	88	19	of	of	ADP
ajst-25804	88	20	more	more	ADJ
ajst-25804	88	21	types	type	NOUN
ajst-25804	88	22	of	of	ADP
ajst-25804	88	23	information	information	NOUN
ajst-25804	88	24	.	.	PUNCT
ajst-25804	89	1	in	in	ADP
ajst-25804	89	2	addition	addition	NOUN
ajst-25804	89	3	,	,	PUNCT
ajst-25804	89	4	we	we	PRON
ajst-25804	89	5	will	will	AUX
ajst-25804	89	6	also	also	ADV
ajst-25804	89	7	pay	pay	VERB
ajst-25804	89	8	attention	attention	NOUN
ajst-25804	89	9	to	to	ADP
ajst-25804	89	10	the	the	DET
ajst-25804	89	11	landing	landing	NOUN
ajst-25804	89	12	problems	problem	NOUN
ajst-25804	89	13	of	of	ADP
ajst-25804	89	14	the	the	DET
ajst-25804	89	15	algorithm	algorithm	NOUN
ajst-25804	89	16	in	in	ADP
ajst-25804	89	17	practical	practical	ADJ
ajst-25804	89	18	applications	application	NOUN
ajst-25804	89	19	,	,	PUNCT
ajst-25804	89	20	such	such	ADJ
ajst-25804	89	21	as	as	ADP
ajst-25804	89	22	data	data	NOUN
ajst-25804	89	23	acquisition	acquisition	NOUN
ajst-25804	89	24	,	,	PUNCT
ajst-25804	89	25	labeling	labeling	NOUN
ajst-25804	89	26	and	and	CCONJ
ajst-25804	89	27	model	model	NOUN
ajst-25804	89	28	deployment	deployment	NOUN
ajst-25804	89	29	.	.	PUNCT
ajst-25804	90	1	references	reference	NOUN
ajst-25804	90	2	[	[	X
ajst-25804	90	3	1	1	NUM
ajst-25804	90	4	]	]	X
ajst-25804	90	5	sakaridis	sakaridis	PROPN
ajst-25804	90	6	,	,	PUNCT
ajst-25804	90	7	christos	christos	PROPN
ajst-25804	90	8	,	,	PUNCT
ajst-25804	90	9	dai	dai	PROPN
ajst-25804	90	10	,	,	PUNCT
ajst-25804	90	11	et	et	PROPN
ajst-25804	90	12	al	al	PROPN
ajst-25804	90	13	.	.	PROPN
ajst-25804	91	1	semantic	semantic	ADJ
ajst-25804	91	2	foggy	foggy	ADJ
ajst-25804	91	3	scene	scene	NOUN
ajst-25804	91	4	understanding	understanding	NOUN
ajst-25804	91	5	with	with	ADP
ajst-25804	91	6	synthetic	synthetic	ADJ
ajst-25804	91	7	data[j	data[j	NOUN
ajst-25804	91	8	]	]	X
ajst-25804	91	9	.	.	PUNCT
ajst-25804	92	1	international	international	ADJ
ajst-25804	92	2	journal	journal	PROPN
ajst-25804	92	3	of	of	ADP
ajst-25804	92	4	computer	computer	NOUN
ajst-25804	92	5	vision	vision	NOUN
ajst-25804	92	6	,	,	PUNCT
ajst-25804	92	7	2018	2018	NUM
ajst-25804	92	8	,	,	PUNCT
ajst-25804	92	9	126(9):973	126(9):973	NUM
ajst-25804	92	10	-	-	SYM
ajst-25804	92	11	992	992	NUM
ajst-25804	92	12	.	.	PUNCT
ajst-25804	93	1	[	[	X
ajst-25804	93	2	2	2	NUM
ajst-25804	93	3	]	]	PUNCT
ajst-25804	93	4	jayachitra	jayachitra	PROPN
ajst-25804	93	5	j	j	PROPN
ajst-25804	93	6	,	,	PUNCT
ajst-25804	93	7	devi	devi	PROPN
ajst-25804	93	8	k	k	PROPN
ajst-25804	93	9	s	s	PROPN
ajst-25804	93	10	,	,	PUNCT
ajst-25804	93	11	satti	satti	PROPN
ajst-25804	93	12	m	m	PROPN
ajst-25804	93	13	s	s	PROPN
ajst-25804	93	14	k.	k.	PROPN
ajst-25804	93	15	terahertz	terahertz	PROPN
ajst-25804	93	16	video	video	NOUN
ajst-25804	93	17	-	-	PUNCT
ajst-25804	93	18	based	base	VERB
ajst-25804	93	19	hidden	hide	VERB
ajst-25804	93	20	object	object	NOUN
ajst-25804	93	21	detection	detection	NOUN
ajst-25804	93	22	using	use	VERB
ajst-25804	93	23	yolov5	yolov5	NOUN
ajst-25804	93	24	m	m	NOUN
ajst-25804	93	25	and	and	CCONJ
ajst-25804	93	26	mutationenabled	mutationenable	VERB
ajst-25804	93	27	salp	salp	NOUN
ajst-25804	93	28	swarm	swarm	NOUN
ajst-25804	93	29	algorithm	algorithm	NOUN
ajst-25804	93	30	for	for	ADP
ajst-25804	93	31	enhanced	enhanced	ADJ
ajst-25804	93	32	accuracy	accuracy	NOUN
ajst-25804	93	33	and	and	CCONJ
ajst-25804	93	34	faster	fast	ADJ
ajst-25804	93	35	recognition[j	recognition[j	NOUN
ajst-25804	93	36	]	]	PUNCT
ajst-25804	93	37	.	.	PUNCT
ajst-25804	94	1	journal	journal	PROPN
ajst-25804	94	2	of	of	ADP
ajst-25804	94	3	supercomputing	supercomputing	NOUN
ajst-25804	94	4	,	,	PUNCT
ajst-25804	94	5	2024	2024	NUM
ajst-25804	94	6	,	,	PUNCT
ajst-25804	94	7	80(6):83578382	80(6):83578382	ADJ
ajst-25804	94	8	.	.	PUNCT
ajst-25804	95	1	[	[	X
ajst-25804	95	2	3	3	X
ajst-25804	95	3	]	]	X
ajst-25804	95	4	mahalingam	mahalingam	NOUN
ajst-25804	95	5	t	t	PROPN
ajst-25804	95	6	,	,	PUNCT
ajst-25804	95	7	subramoniam	subramoniam	NOUN
ajst-25804	95	8	m.	m.	NOUN
ajst-25804	95	9	optimal	optimal	ADJ
ajst-25804	95	10	object	object	NOUN
ajst-25804	95	11	detection	detection	NOUN
ajst-25804	95	12	and	and	CCONJ
ajst-25804	95	13	tracking	track	VERB
ajst-25804	95	14	in	in	ADP
ajst-25804	95	15	occluded	occluded	ADJ
ajst-25804	95	16	video	video	NOUN
ajst-25804	95	17	using	use	VERB
ajst-25804	95	18	dnn	dnn	PROPN
ajst-25804	95	19	and	and	CCONJ
ajst-25804	95	20	gravitational	gravitational	ADJ
ajst-25804	95	21	search	search	NOUN
ajst-25804	95	22	algorithm[j	algorithm[j	PROPN
ajst-25804	95	23	]	]	PUNCT
ajst-25804	95	24	.	.	PUNCT
ajst-25804	96	1	soft	soft	ADJ
ajst-25804	96	2	computing	computing	NOUN
ajst-25804	96	3	,	,	PUNCT
ajst-25804	96	4	2020	2020	NUM
ajst-25804	96	5	,	,	PUNCT
ajst-25804	96	6	24(24):18301	24(24):18301	NUM
ajst-25804	96	7	-	-	SYM
ajst-25804	96	8	18320	18320	NUM
ajst-25804	96	9	.	.	PUNCT
ajst-25804	97	1	[	[	X
ajst-25804	97	2	4	4	NUM
ajst-25804	97	3	]	]	X
ajst-25804	97	4	zhou	zhou	PROPN
ajst-25804	97	5	w	w	PROPN
ajst-25804	97	6	,	,	PUNCT
ajst-25804	97	7	wang	wang	PROPN
ajst-25804	97	8	x	x	PROPN
ajst-25804	97	9	,	,	PUNCT
ajst-25804	97	10	fan	fan	PROPN
ajst-25804	97	11	y	y	PROPN
ajst-25804	97	12	,	,	PUNCT
ajst-25804	97	13	et	et	PROPN
ajst-25804	97	14	al	al	PROPN
ajst-25804	97	15	.	.	PROPN
ajst-25804	97	16	kdsmall	kdsmall	PROPN
ajst-25804	97	17	:	:	PUNCT
ajst-25804	97	18	a	a	DET
ajst-25804	97	19	lightweight	lightweight	ADJ
ajst-25804	97	20	small	small	ADJ
ajst-25804	97	21	object	object	NOUN
ajst-25804	97	22	detection	detection	NOUN
ajst-25804	97	23	algorithm	algorithm	NOUN
ajst-25804	97	24	based	base	VERB
ajst-25804	97	25	on	on	ADP
ajst-25804	97	26	knowledge	knowledge	PROPN
ajst-25804	97	27	distillation[j	distillation[j	PROPN
ajst-25804	97	28	]	]	PUNCT
ajst-25804	97	29	.	.	PUNCT
ajst-25804	98	1	computer	computer	NOUN
ajst-25804	98	2	communications	communication	NOUN
ajst-25804	98	3	,	,	PUNCT
ajst-25804	98	4	2024	2024	NUM
ajst-25804	98	5	,	,	PUNCT
ajst-25804	98	6	219:271	219:271	NOUN
ajst-25804	98	7	-	-	PUNCT
ajst-25804	98	8	281	281	NUM
ajst-25804	98	9	.	.	PUNCT
ajst-25804	99	1	[	[	X
ajst-25804	99	2	5	5	NUM
ajst-25804	99	3	]	]	PUNCT
ajst-25804	99	4	changdong	changdong	PROPN
ajst-25804	99	5	w	w	PROPN
ajst-25804	99	6	,	,	PUNCT
ajst-25804	99	7	rui	rui	PROPN
ajst-25804	99	8	l.	l.	PROPN
ajst-25804	99	9	object	object	PROPN
ajst-25804	99	10	detection	detection	NOUN
ajst-25804	99	11	algorithm	algorithm	NOUN
ajst-25804	99	12	for	for	ADP
ajst-25804	99	13	indoor	indoor	ADJ
ajst-25804	99	14	switchgear	switchgear	ADJ
ajst-25804	99	15	components	component	NOUN
ajst-25804	99	16	in	in	ADP
ajst-25804	99	17	substations	substation	NOUN
ajst-25804	99	18	based	base	VERB
ajst-25804	99	19	on	on	ADP
ajst-25804	99	20	improved	improved	ADJ
ajst-25804	99	21	yolov5s[j	yolov5s[j	PROPN
ajst-25804	99	22	]	]	PUNCT
ajst-25804	99	23	.	.	PUNCT
ajst-25804	100	1	insight	insight	NOUN
ajst-25804	100	2	-	-	PUNCT
ajst-25804	100	3	non	non	ADJ
ajst-25804	100	4	-	-	ADJ
ajst-25804	100	5	destructive	destructive	ADJ
ajst-25804	100	6	testing	testing	NOUN
ajst-25804	100	7	and	and	CCONJ
ajst-25804	100	8	condition	condition	NOUN
ajst-25804	100	9	monitoring	monitoring	NOUN
ajst-25804	100	10	,	,	PUNCT
ajst-25804	100	11	2024	2024	NUM
ajst-25804	100	12	,	,	PUNCT
ajst-25804	100	13	66(4):226	66(4):226	NUM
ajst-25804	100	14	-	-	SYM
ajst-25804	100	15	231	231	NUM
ajst-25804	100	16	.	.	PUNCT
ajst-25804	101	1	[	[	X
ajst-25804	101	2	6	6	NUM
ajst-25804	101	3	]	]	PUNCT
ajst-25804	101	4	wang	wang	PROPN
ajst-25804	101	5	y	y	PROPN
ajst-25804	101	6	,	,	PUNCT
ajst-25804	101	7	liu	liu	PROPN
ajst-25804	101	8	x	x	PROPN
ajst-25804	101	9	,	,	PUNCT
ajst-25804	101	10	guo	guo	PROPN
ajst-25804	101	11	r.	r.	PROPN
ajst-25804	101	12	an	an	DET
ajst-25804	101	13	object	object	NOUN
ajst-25804	101	14	detection	detection	NOUN
ajst-25804	101	15	algorithm	algorithm	NOUN
ajst-25804	101	16	based	base	VERB
ajst-25804	101	17	on	on	ADP
ajst-25804	101	18	the	the	DET
ajst-25804	101	19	feature	feature	NOUN
ajst-25804	101	20	pyramid	pyramid	NOUN
ajst-25804	101	21	network	network	NOUN
ajst-25804	101	22	and	and	CCONJ
ajst-25804	101	23	single	single	ADJ
ajst-25804	101	24	shot	shot	NOUN
ajst-25804	101	25	multibox	multibox	PROPN
ajst-25804	101	26	detector[j	detector[j	PROPN
ajst-25804	101	27	]	]	PUNCT
ajst-25804	101	28	.	.	PUNCT
ajst-25804	102	1	cluster	cluster	NOUN
ajst-25804	102	2	computing	computing	NOUN
ajst-25804	102	3	,	,	PUNCT
ajst-25804	102	4	2022	2022	NUM
ajst-25804	102	5	,	,	PUNCT
ajst-25804	102	6	25(5):3313	25(5):3313	NUM
ajst-25804	102	7	-	-	SYM
ajst-25804	102	8	3324	3324	NUM
ajst-25804	102	9	.	.	PUNCT
ajst-25804	103	1	[	[	X
ajst-25804	103	2	7	7	X
ajst-25804	103	3	]	]	X
ajst-25804	103	4	lee	lee	PROPN
ajst-25804	103	5	j	j	PROPN
ajst-25804	103	6	n	n	CCONJ
ajst-25804	103	7	,	,	PUNCT
ajst-25804	103	8	cho	cho	PROPN
ajst-25804	103	9	h	h	PROPN
ajst-25804	103	10	c.	c.	PROPN
ajst-25804	103	11	automated	automate	VERB
ajst-25804	103	12	polyp	polyp	NOUN
ajst-25804	103	13	detection	detection	NOUN
ajst-25804	103	14	system	system	NOUN
ajst-25804	103	15	in	in	ADP
ajst-25804	103	16	colonoscopy	colonoscopy	NOUN
ajst-25804	103	17	using	use	VERB
ajst-25804	103	18	object	object	NOUN
ajst-25804	103	19	detection	detection	NOUN
ajst-25804	103	20	algorithm	algorithm	NOUN
ajst-25804	103	21	based	base	VERB
ajst-25804	103	22	on	on	ADP
ajst-25804	103	23	deep	deep	ADJ
ajst-25804	103	24	learning[j	learning[j	NOUN
ajst-25804	103	25	]	]	PUNCT
ajst-25804	103	26	.	.	PUNCT
ajst-25804	104	1	transactions	transaction	NOUN
ajst-25804	104	2	of	of	ADP
ajst-25804	104	3	the	the	DET
ajst-25804	104	4	korean	korean	PROPN
ajst-25804	104	5	institute	institute	PROPN
ajst-25804	104	6	of	of	ADP
ajst-25804	104	7	electrical	electrical	ADJ
ajst-25804	104	8	engineers	engineer	NOUN
ajst-25804	104	9	,	,	PUNCT
ajst-25804	104	10	2021	2021	NUM
ajst-25804	104	11	,	,	PUNCT
ajst-25804	104	12	70(1):152	70(1):152	PROPN
ajst-25804	104	13	-	-	PUNCT
ajst-25804	104	14	157	157	NUM
ajst-25804	104	15	.	.	PUNCT
ajst-25804	105	1	[	[	X
ajst-25804	105	2	8	8	NUM
ajst-25804	105	3	]	]	X
ajst-25804	105	4	huang	huang	PROPN
ajst-25804	105	5	z	z	PROPN
ajst-25804	105	6	,	,	PUNCT
ajst-25804	105	7	yin	yin	PROPN
ajst-25804	105	8	z	z	PROPN
ajst-25804	105	9	,	,	PUNCT
ajst-25804	105	10	ma	ma	PROPN
ajst-25804	105	11	y	y	PROPN
ajst-25804	105	12	,	,	PUNCT
ajst-25804	105	13	et	et	PROPN
ajst-25804	105	14	al	al	PROPN
ajst-25804	105	15	.	.	PROPN
ajst-25804	105	16	mobile	mobile	ADJ
ajst-25804	105	17	phone	phone	NOUN
ajst-25804	105	18	component	component	NOUN
ajst-25804	105	19	object	object	NOUN
ajst-25804	105	20	detection	detection	NOUN
ajst-25804	105	21	algorithm	algorithm	NOUN
ajst-25804	105	22	based	base	VERB
ajst-25804	105	23	on	on	ADP
ajst-25804	105	24	improved	improved	ADJ
ajst-25804	105	25	ssd[j	ssd[j	NOUN
ajst-25804	105	26	]	]	PUNCT
ajst-25804	105	27	.	.	PUNCT
ajst-25804	106	1	procedia	procedia	PROPN
ajst-25804	106	2	computer	computer	NOUN
ajst-25804	106	3	science	science	NOUN
ajst-25804	106	4	,	,	PUNCT
ajst-25804	106	5	2021	2021	NUM
ajst-25804	106	6	,	,	PUNCT
ajst-25804	106	7	183(2):107	183(2):107	NOUN
ajst-25804	106	8	-	-	SYM
ajst-25804	106	9	114	114	NUM
ajst-25804	106	10	.	.	PUNCT