id	sid	tid	token	lemma	pos
fcis-12803	1	1	frontiers	frontier	NOUN
fcis-12803	1	2	in	in	ADP
fcis-12803	1	3	computing	computing	NOUN
fcis-12803	1	4	and	and	CCONJ
fcis-12803	1	5	intelligent	intelligent	ADJ
fcis-12803	1	6	systems	system	NOUN
fcis-12803	1	7	issn	issn	VERB
fcis-12803	1	8	:	:	PUNCT
fcis-12803	1	9	2832	2832	NUM
fcis-12803	1	10	-	-	SYM
fcis-12803	1	11	6024	6024	NUM
fcis-12803	1	12	|	|	NOUN
fcis-12803	1	13	vol	vol	NOUN
fcis-12803	1	14	.	.	PROPN
fcis-12803	2	1	5	5	NUM
fcis-12803	2	2	,	,	PUNCT
fcis-12803	2	3	no	no	INTJ
fcis-12803	2	4	.	.	NOUN
fcis-12803	2	5	2	2	NUM
fcis-12803	2	6	,	,	PUNCT
fcis-12803	2	7	2023	2023	NUM
fcis-12803	2	8	72	72	NUM
fcis-12803	2	9	uav	uav	PROPN
fcis-12803	2	10	target	target	NOUN
fcis-12803	2	11	detection	detection	NOUN
fcis-12803	2	12	algorithm	algorithm	NOUN
fcis-12803	2	13	with	with	ADP
fcis-12803	2	14	improved	improved	ADJ
fcis-12803	2	15	yolov7	yolov7	NOUN
fcis-12803	2	16	fanrun	fanrun	PROPN
fcis-12803	2	17	meng	meng	PROPN
fcis-12803	2	18	,	,	PUNCT
fcis-12803	2	19	chen	chen	PROPN
fcis-12803	2	20	liu	liu	PROPN
fcis-12803	2	21	,	,	PUNCT
fcis-12803	2	22	zhiren	zhiren	PROPN
fcis-12803	2	23	zhu	zhu	PROPN
fcis-12803	2	24	,	,	PUNCT
fcis-12803	2	25	liming	lime	VERB
fcis-12803	2	26	zhou	zhou	PROPN
fcis-12803	2	27	college	college	PROPN
fcis-12803	2	28	of	of	ADP
fcis-12803	2	29	electronic	electronic	ADJ
fcis-12803	2	30	engineering	engineering	NOUN
fcis-12803	2	31	,	,	PUNCT
fcis-12803	2	32	tianjin	tianjin	PROPN
fcis-12803	2	33	university	university	PROPN
fcis-12803	2	34	of	of	ADP
fcis-12803	2	35	technology	technology	NOUN
fcis-12803	2	36	and	and	CCONJ
fcis-12803	2	37	education	education	NOUN
fcis-12803	2	38	,	,	PUNCT
fcis-12803	2	39	tianjin	tianjin	PROPN
fcis-12803	2	40	300222	300222	NUM
fcis-12803	2	41	,	,	PUNCT
fcis-12803	2	42	china	china	PROPN
fcis-12803	2	43	abstract	abstract	NOUN
fcis-12803	2	44	:	:	PUNCT
fcis-12803	2	45	the	the	DET
fcis-12803	2	46	wide	wide	ADJ
fcis-12803	2	47	application	application	NOUN
fcis-12803	2	48	of	of	ADP
fcis-12803	2	49	uav	uav	PROPN
fcis-12803	2	50	technology	technology	PROPN
fcis-12803	2	51	in	in	ADP
fcis-12803	2	52	various	various	ADJ
fcis-12803	2	53	fields	field	NOUN
fcis-12803	2	54	makes	make	VERB
fcis-12803	2	55	uav	uav	PROPN
fcis-12803	2	56	target	target	NOUN
fcis-12803	2	57	detection	detection	NOUN
fcis-12803	2	58	crucial	crucial	ADJ
fcis-12803	2	59	.	.	PUNCT
fcis-12803	3	1	in	in	ADP
fcis-12803	3	2	this	this	DET
fcis-12803	3	3	study	study	NOUN
fcis-12803	3	4	,	,	PUNCT
fcis-12803	3	5	we	we	PRON
fcis-12803	3	6	propose	propose	VERB
fcis-12803	3	7	an	an	DET
fcis-12803	3	8	improved	improved	ADJ
fcis-12803	3	9	algorithm	algorithm	NOUN
fcis-12803	3	10	based	base	VERB
fcis-12803	3	11	on	on	ADP
fcis-12803	3	12	yolov7	yolov7	NOUN
fcis-12803	3	13	to	to	PART
fcis-12803	3	14	enhance	enhance	VERB
fcis-12803	3	15	the	the	DET
fcis-12803	3	16	performance	performance	NOUN
fcis-12803	3	17	and	and	CCONJ
fcis-12803	3	18	robustness	robustness	NOUN
fcis-12803	3	19	of	of	ADP
fcis-12803	3	20	uav	uav	PROPN
fcis-12803	3	21	target	target	PROPN
fcis-12803	3	22	detection	detection	NOUN
fcis-12803	3	23	.	.	PUNCT
fcis-12803	4	1	we	we	PRON
fcis-12803	4	2	utilize	utilize	VERB
fcis-12803	4	3	yolov7	yolov7	NOUN
fcis-12803	4	4	as	as	ADP
fcis-12803	4	5	the	the	DET
fcis-12803	4	6	infrastructure	infrastructure	NOUN
fcis-12803	4	7	and	and	CCONJ
fcis-12803	4	8	introduce	introduce	VERB
fcis-12803	4	9	bifpn	bifpn	PROPN
fcis-12803	4	10	(	(	PUNCT
fcis-12803	4	11	bi	bi	ADJ
fcis-12803	4	12	-	-	ADJ
fcis-12803	4	13	directional	directional	ADJ
fcis-12803	4	14	feature	feature	NOUN
fcis-12803	4	15	pyramid	pyramid	NOUN
fcis-12803	4	16	network	network	NOUN
fcis-12803	4	17	)	)	PUNCT
fcis-12803	4	18	to	to	PART
fcis-12803	4	19	enhance	enhance	VERB
fcis-12803	4	20	the	the	DET
fcis-12803	4	21	feature	feature	NOUN
fcis-12803	4	22	fusion	fusion	NOUN
fcis-12803	4	23	,	,	PUNCT
fcis-12803	4	24	while	while	SCONJ
fcis-12803	4	25	adding	add	VERB
fcis-12803	4	26	the	the	DET
fcis-12803	4	27	gam	gam	NOUN
fcis-12803	4	28	attention	attention	NOUN
fcis-12803	4	29	mechanism	mechanism	NOUN
fcis-12803	4	30	to	to	ADP
fcis-12803	4	31	the	the	DET
fcis-12803	4	32	model	model	NOUN
fcis-12803	4	33	,	,	PUNCT
fcis-12803	4	34	which	which	PRON
fcis-12803	4	35	is	be	AUX
fcis-12803	4	36	trained	train	VERB
fcis-12803	4	37	and	and	CCONJ
fcis-12803	4	38	evaluated	evaluate	VERB
fcis-12803	4	39	using	use	VERB
fcis-12803	4	40	the	the	DET
fcis-12803	4	41	visdrone2019	visdrone2019	PROPN
fcis-12803	4	42	dataset	dataset	NOUN
fcis-12803	4	43	.	.	PUNCT
fcis-12803	5	1	the	the	DET
fcis-12803	5	2	experimental	experimental	ADJ
fcis-12803	5	3	results	result	NOUN
fcis-12803	5	4	of	of	ADP
fcis-12803	5	5	this	this	DET
fcis-12803	5	6	study	study	NOUN
fcis-12803	5	7	show	show	VERB
fcis-12803	5	8	that	that	SCONJ
fcis-12803	5	9	the	the	DET
fcis-12803	5	10	improved	improved	ADJ
fcis-12803	5	11	model	model	NOUN
fcis-12803	5	12	achieves	achieve	VERB
fcis-12803	5	13	an	an	DET
fcis-12803	5	14	average	average	ADJ
fcis-12803	5	15	accuracy	accuracy	NOUN
fcis-12803	5	16	map	map	NOUN
fcis-12803	5	17	value	value	NOUN
fcis-12803	5	18	of	of	ADP
fcis-12803	5	19	45.6	45.6	NUM
fcis-12803	5	20	%	%	NOUN
fcis-12803	5	21	,	,	PUNCT
fcis-12803	5	22	which	which	PRON
fcis-12803	5	23	is	be	AUX
fcis-12803	5	24	2.7	2.7	NUM
fcis-12803	5	25	%	%	NOUN
fcis-12803	5	26	higher	high	ADJ
fcis-12803	5	27	than	than	ADP
fcis-12803	5	28	the	the	DET
fcis-12803	5	29	traditional	traditional	ADJ
fcis-12803	5	30	model	model	NOUN
fcis-12803	5	31	,	,	PUNCT
fcis-12803	5	32	and	and	CCONJ
fcis-12803	5	33	is	be	AUX
fcis-12803	5	34	able	able	ADJ
fcis-12803	5	35	to	to	PART
fcis-12803	5	36	detect	detect	VERB
fcis-12803	5	37	and	and	CCONJ
fcis-12803	5	38	localize	localize	VERB
fcis-12803	5	39	uav	uav	PROPN
fcis-12803	5	40	targets	target	VERB
fcis-12803	5	41	more	more	ADV
fcis-12803	5	42	accurately	accurately	ADV
fcis-12803	5	43	.	.	PUNCT
fcis-12803	6	1	keywords	keyword	NOUN
fcis-12803	6	2	:	:	PUNCT
fcis-12803	6	3	unmanned	unmanned	ADJ
fcis-12803	6	4	aerial	aerial	ADJ
fcis-12803	6	5	vehicle	vehicle	NOUN
fcis-12803	6	6	(	(	PUNCT
fcis-12803	6	7	uav	uav	PROPN
fcis-12803	6	8	)	)	PUNCT
fcis-12803	6	9	;	;	PUNCT
fcis-12803	6	10	yolov7	yolov7	NOUN
fcis-12803	6	11	;	;	PUNCT
fcis-12803	6	12	bifpn	bifpn	PROPN
fcis-12803	6	13	;	;	PUNCT
fcis-12803	6	14	gam	gam	X
fcis-12803	6	15	.	.	NOUN
fcis-12803	7	1	1	1	NUM
fcis-12803	7	2	.	.	X
fcis-12803	7	3	introduction	introduction	NOUN
fcis-12803	7	4	uav	uav	PROPN
fcis-12803	7	5	technology	technology	PROPN
fcis-12803	7	6	has	have	AUX
fcis-12803	7	7	been	be	AUX
fcis-12803	7	8	widely	widely	ADV
fcis-12803	7	9	used	use	VERB
fcis-12803	7	10	in	in	ADP
fcis-12803	7	11	various	various	ADJ
fcis-12803	7	12	fields	field	NOUN
fcis-12803	7	13	such	such	ADJ
fcis-12803	7	14	as	as	ADP
fcis-12803	7	15	military	military	ADJ
fcis-12803	7	16	,	,	PUNCT
fcis-12803	7	17	civil	civil	ADJ
fcis-12803	7	18	and	and	CCONJ
fcis-12803	7	19	scientific	scientific	ADJ
fcis-12803	7	20	research	research	NOUN
fcis-12803	7	21	.	.	PUNCT
fcis-12803	8	1	uav	uav	PROPN
fcis-12803	8	2	target	target	PROPN
fcis-12803	8	3	detection	detection	NOUN
fcis-12803	8	4	has	have	VERB
fcis-12803	8	5	important	important	ADJ
fcis-12803	8	6	practical	practical	ADJ
fcis-12803	8	7	significance	significance	NOUN
fcis-12803	8	8	as	as	ADP
fcis-12803	8	9	one	one	NUM
fcis-12803	8	10	of	of	ADP
fcis-12803	8	11	the	the	DET
fcis-12803	8	12	cores	core	NOUN
fcis-12803	8	13	of	of	ADP
fcis-12803	8	14	uav	uav	PROPN
fcis-12803	8	15	applications	application	NOUN
fcis-12803	8	16	.	.	PUNCT
fcis-12803	9	1	accurately	accurately	ADV
fcis-12803	9	2	detecting	detect	VERB
fcis-12803	9	3	and	and	CCONJ
fcis-12803	9	4	localizing	localize	VERB
fcis-12803	9	5	uav	uav	PROPN
fcis-12803	9	6	targets	target	NOUN
fcis-12803	9	7	can	can	AUX
fcis-12803	9	8	be	be	AUX
fcis-12803	9	9	used	use	VERB
fcis-12803	9	10	in	in	ADP
fcis-12803	9	11	application	application	NOUN
fcis-12803	9	12	scenarios	scenario	NOUN
fcis-12803	9	13	such	such	ADJ
fcis-12803	9	14	as	as	ADP
fcis-12803	9	15	surveillance	surveillance	NOUN
fcis-12803	9	16	,	,	PUNCT
fcis-12803	9	17	security	security	NOUN
fcis-12803	9	18	,	,	PUNCT
fcis-12803	9	19	and	and	CCONJ
fcis-12803	9	20	rescue	rescue	NOUN
fcis-12803	9	21	.	.	PUNCT
fcis-12803	10	1	however	however	ADV
fcis-12803	10	2	,	,	PUNCT
fcis-12803	10	3	uav	uav	PROPN
fcis-12803	10	4	target	target	NOUN
fcis-12803	10	5	detection	detection	NOUN
fcis-12803	10	6	tasks	task	NOUN
fcis-12803	10	7	face	face	VERB
fcis-12803	10	8	many	many	ADJ
fcis-12803	10	9	challenges	challenge	NOUN
fcis-12803	10	10	,	,	PUNCT
fcis-12803	10	11	including	include	VERB
fcis-12803	10	12	complex	complex	ADJ
fcis-12803	10	13	backgrounds	background	NOUN
fcis-12803	10	14	,	,	PUNCT
fcis-12803	10	15	multi	multi	ADJ
fcis-12803	10	16	-	-	ADJ
fcis-12803	10	17	scale	scale	ADJ
fcis-12803	10	18	targets	target	NOUN
fcis-12803	10	19	,	,	PUNCT
fcis-12803	10	20	and	and	CCONJ
fcis-12803	10	21	occlusion	occlusion	NOUN
fcis-12803	10	22	.	.	PUNCT
fcis-12803	11	1	therefore	therefore	ADV
fcis-12803	11	2	,	,	PUNCT
fcis-12803	11	3	it	it	PRON
fcis-12803	11	4	is	be	AUX
fcis-12803	11	5	crucial	crucial	ADJ
fcis-12803	11	6	to	to	PART
fcis-12803	11	7	develop	develop	VERB
fcis-12803	11	8	an	an	DET
fcis-12803	11	9	efficient	efficient	ADJ
fcis-12803	11	10	and	and	CCONJ
fcis-12803	11	11	accurate	accurate	ADJ
fcis-12803	11	12	uav	uav	PROPN
fcis-12803	11	13	target	target	NOUN
fcis-12803	11	14	detection	detection	NOUN
fcis-12803	11	15	algorithm	algorithm	NOUN
fcis-12803	11	16	.	.	PUNCT
fcis-12803	12	1	2	2	X
fcis-12803	12	2	.	.	X
fcis-12803	12	3	overview	overview	NOUN
fcis-12803	12	4	of	of	ADP
fcis-12803	12	5	target	target	NOUN
fcis-12803	12	6	detection	detection	NOUN
fcis-12803	12	7	algorithm	algorithm	NOUN
fcis-12803	12	8	2.1	2.1	NUM
fcis-12803	12	9	.	.	PUNCT
fcis-12803	13	1	traditional	traditional	ADJ
fcis-12803	13	2	target	target	NOUN
fcis-12803	13	3	detection	detection	NOUN
fcis-12803	13	4	algorithm	algorithm	NOUN
fcis-12803	13	5	traditional	traditional	ADJ
fcis-12803	13	6	target	target	NOUN
fcis-12803	13	7	detection	detection	NOUN
fcis-12803	13	8	algorithms	algorithm	NOUN
fcis-12803	13	9	use	use	VERB
fcis-12803	13	10	a	a	DET
fcis-12803	13	11	sliding	slide	VERB
fcis-12803	13	12	window	window	NOUN
fcis-12803	13	13	strategy	strategy	NOUN
fcis-12803	13	14	to	to	PART
fcis-12803	13	15	select	select	VERB
fcis-12803	13	16	candidate	candidate	NOUN
fcis-12803	13	17	regions	region	NOUN
fcis-12803	13	18	on	on	ADP
fcis-12803	13	19	a	a	DET
fcis-12803	13	20	given	give	VERB
fcis-12803	13	21	image	image	NOUN
fcis-12803	13	22	,	,	PUNCT
fcis-12803	13	23	and	and	CCONJ
fcis-12803	13	24	then	then	ADV
fcis-12803	13	25	extract	extract	VERB
fcis-12803	13	26	features	feature	NOUN
fcis-12803	13	27	(	(	PUNCT
fcis-12803	13	28	e.g.	e.g.	ADV
fcis-12803	13	29	,	,	PUNCT
fcis-12803	13	30	sift[1],hog[2	sift[1],hog[2	NOUN
fcis-12803	13	31	]	]	PUNCT
fcis-12803	13	32	)	)	PUNCT
fcis-12803	13	33	for	for	ADP
fcis-12803	13	34	these	these	DET
fcis-12803	13	35	regions	region	NOUN
fcis-12803	13	36	,	,	PUNCT
fcis-12803	13	37	and	and	CCONJ
fcis-12803	13	38	finally	finally	ADV
fcis-12803	13	39	use	use	VERB
fcis-12803	13	40	a	a	DET
fcis-12803	13	41	trained	train	VERB
fcis-12803	13	42	classifier	classifier	NOUN
fcis-12803	13	43	(	(	PUNCT
fcis-12803	13	44	e.g.	e.g.	ADV
fcis-12803	13	45	,	,	PUNCT
fcis-12803	13	46	svm[3	svm[3	NOUN
fcis-12803	13	47	]	]	PUNCT
fcis-12803	13	48	,	,	PUNCT
fcis-12803	13	49	adaboost[4	adaboost[4	PROPN
fcis-12803	13	50	]	]	PUNCT
fcis-12803	13	51	)	)	PUNCT
fcis-12803	13	52	for	for	ADP
fcis-12803	13	53	classification	classification	NOUN
fcis-12803	13	54	.	.	PUNCT
fcis-12803	14	1	this	this	DET
fcis-12803	14	2	method	method	NOUN
fcis-12803	14	3	has	have	VERB
fcis-12803	14	4	the	the	DET
fcis-12803	14	5	disadvantages	disadvantage	NOUN
fcis-12803	14	6	of	of	ADP
fcis-12803	14	7	poorly	poorly	ADV
fcis-12803	14	8	targeted	target	VERB
fcis-12803	14	9	region	region	NOUN
fcis-12803	14	10	selection	selection	NOUN
fcis-12803	14	11	strategy	strategy	NOUN
fcis-12803	14	12	,	,	PUNCT
fcis-12803	14	13	high	high	ADJ
fcis-12803	14	14	time	time	NOUN
fcis-12803	14	15	complexity	complexity	NOUN
fcis-12803	14	16	,	,	PUNCT
fcis-12803	14	17	and	and	CCONJ
fcis-12803	14	18	poor	poor	ADJ
fcis-12803	14	19	robustness	robustness	NOUN
fcis-12803	14	20	.	.	PUNCT
fcis-12803	15	1	with	with	ADP
fcis-12803	15	2	the	the	DET
fcis-12803	15	3	rapid	rapid	ADJ
fcis-12803	15	4	development	development	NOUN
fcis-12803	15	5	of	of	ADP
fcis-12803	15	6	artificial	artificial	ADJ
fcis-12803	15	7	intelligence	intelligence	NOUN
fcis-12803	15	8	technology	technology	NOUN
fcis-12803	15	9	,	,	PUNCT
fcis-12803	15	10	it	it	PRON
fcis-12803	15	11	has	have	AUX
fcis-12803	15	12	been	be	AUX
fcis-12803	15	13	gradually	gradually	ADV
fcis-12803	15	14	replaced	replace	VERB
fcis-12803	15	15	by	by	ADP
fcis-12803	15	16	deep	deep	ADJ
fcis-12803	15	17	learning	learning	NOUN
fcis-12803	15	18	methods	method	NOUN
fcis-12803	15	19	of	of	ADP
fcis-12803	15	20	features	feature	NOUN
fcis-12803	15	21	.	.	PUNCT
fcis-12803	16	1	2.2	2.2	NUM
fcis-12803	16	2	.	.	PUNCT
fcis-12803	16	3	yolo	yolo	PROPN
fcis-12803	16	4	series	series	PROPN
fcis-12803	16	5	target	target	NOUN
fcis-12803	16	6	detection	detection	NOUN
fcis-12803	16	7	algorithm	algorithm	NOUN
fcis-12803	16	8	after	after	ADP
fcis-12803	16	9	entering	enter	VERB
fcis-12803	16	10	the	the	DET
fcis-12803	16	11	era	era	NOUN
fcis-12803	16	12	of	of	ADP
fcis-12803	16	13	deep	deep	ADJ
fcis-12803	16	14	learning	learning	NOUN
fcis-12803	16	15	,	,	PUNCT
fcis-12803	16	16	target	target	NOUN
fcis-12803	16	17	detection	detection	NOUN
fcis-12803	16	18	algorithms	algorithm	NOUN
fcis-12803	16	19	keep	keep	VERB
fcis-12803	16	20	emerging	emerge	VERB
fcis-12803	16	21	like	like	ADP
fcis-12803	16	22	a	a	DET
fcis-12803	16	23	spring	spring	NOUN
fcis-12803	16	24	,	,	PUNCT
fcis-12803	16	25	which	which	PRON
fcis-12803	16	26	can	can	AUX
fcis-12803	16	27	be	be	AUX
fcis-12803	16	28	roughly	roughly	ADV
fcis-12803	16	29	divided	divide	VERB
fcis-12803	16	30	into	into	ADP
fcis-12803	16	31	two	two	NUM
fcis-12803	16	32	-	-	PUNCT
fcis-12803	16	33	stage	stage	NOUN
fcis-12803	16	34	algorithms	algorithm	NOUN
fcis-12803	16	35	represented	represent	VERB
fcis-12803	16	36	by	by	ADP
fcis-12803	16	37	the	the	DET
fcis-12803	16	38	rcnn[5][6][7][8	rcnn[5][6][7][8	NOUN
fcis-12803	16	39	]	]	PUNCT
fcis-12803	16	40	series	series	NOUN
fcis-12803	16	41	of	of	ADP
fcis-12803	16	42	algorithms	algorithm	NOUN
fcis-12803	16	43	and	and	CCONJ
fcis-12803	16	44	one	one	NUM
fcis-12803	16	45	-	-	PUNCT
fcis-12803	16	46	stage	stage	NOUN
fcis-12803	16	47	algorithms	algorithm	NOUN
fcis-12803	16	48	represented	represent	VERB
fcis-12803	16	49	by	by	ADP
fcis-12803	16	50	the	the	DET
fcis-12803	16	51	yolo[9	yolo[9	PROPN
fcis-12803	16	52	]	]	PUNCT
fcis-12803	16	53	series	series	NOUN
fcis-12803	16	54	of	of	ADP
fcis-12803	16	55	algorithms	algorithms	PROPN
fcis-12803	16	56	.	.	PUNCT
fcis-12803	17	1	the	the	DET
fcis-12803	17	2	method	method	NOUN
fcis-12803	17	3	is	be	AUX
fcis-12803	17	4	divided	divide	VERB
fcis-12803	17	5	into	into	ADP
fcis-12803	17	6	two	two	NUM
fcis-12803	17	7	steps	step	NOUN
fcis-12803	17	8	,	,	PUNCT
fcis-12803	17	9	the	the	DET
fcis-12803	17	10	first	first	ADJ
fcis-12803	17	11	step	step	NOUN
fcis-12803	17	12	is	be	AUX
fcis-12803	17	13	to	to	PART
fcis-12803	17	14	generate	generate	VERB
fcis-12803	17	15	a	a	DET
fcis-12803	17	16	candidate	candidate	NOUN
fcis-12803	17	17	area	area	NOUN
fcis-12803	17	18	,	,	PUNCT
fcis-12803	17	19	and	and	CCONJ
fcis-12803	17	20	the	the	DET
fcis-12803	17	21	second	second	ADJ
fcis-12803	17	22	step	step	NOUN
fcis-12803	17	23	is	be	AUX
fcis-12803	17	24	to	to	PART
fcis-12803	17	25	divide	divide	VERB
fcis-12803	17	26	the	the	DET
fcis-12803	17	27	candidate	candidate	NOUN
fcis-12803	17	28	area	area	NOUN
fcis-12803	17	29	into	into	ADP
fcis-12803	17	30	a	a	DET
fcis-12803	17	31	number	number	NOUN
fcis-12803	17	32	of	of	ADP
fcis-12803	17	33	candidate	candidate	NOUN
fcis-12803	17	34	areas	area	NOUN
fcis-12803	17	35	,	,	PUNCT
fcis-12803	17	36	and	and	CCONJ
fcis-12803	17	37	then	then	ADV
fcis-12803	17	38	divide	divide	VERB
fcis-12803	17	39	the	the	DET
fcis-12803	17	40	candidate	candidate	NOUN
fcis-12803	17	41	area	area	NOUN
fcis-12803	17	42	into	into	ADP
fcis-12803	17	43	a	a	DET
fcis-12803	17	44	number	number	NOUN
fcis-12803	17	45	of	of	ADP
fcis-12803	17	46	candidate	candidate	NOUN
fcis-12803	17	47	areas	area	NOUN
fcis-12803	17	48	and	and	CCONJ
fcis-12803	17	49	correct	correct	VERB
fcis-12803	17	50	the	the	DET
fcis-12803	17	51	position	position	NOUN
fcis-12803	17	52	of	of	ADP
fcis-12803	17	53	the	the	DET
fcis-12803	17	54	candidate	candidate	NOUN
fcis-12803	17	55	areas	area	NOUN
fcis-12803	17	56	.	.	PUNCT
fcis-12803	18	1	the	the	DET
fcis-12803	18	2	method	method	NOUN
fcis-12803	18	3	has	have	VERB
fcis-12803	18	4	high	high	ADJ
fcis-12803	18	5	accuracy	accuracy	NOUN
fcis-12803	18	6	and	and	CCONJ
fcis-12803	18	7	small	small	ADJ
fcis-12803	18	8	probability	probability	NOUN
fcis-12803	18	9	of	of	ADP
fcis-12803	18	10	missed	miss	VERB
fcis-12803	18	11	detection	detection	NOUN
fcis-12803	18	12	,	,	PUNCT
fcis-12803	18	13	but	but	CCONJ
fcis-12803	18	14	its	its	PRON
fcis-12803	18	15	calculation	calculation	NOUN
fcis-12803	18	16	speed	speed	NOUN
fcis-12803	18	17	is	be	AUX
fcis-12803	18	18	slow	slow	ADJ
fcis-12803	18	19	and	and	CCONJ
fcis-12803	18	20	can	can	AUX
fcis-12803	18	21	not	not	PART
fcis-12803	18	22	meet	meet	VERB
fcis-12803	18	23	the	the	DET
fcis-12803	18	24	real	real	ADJ
fcis-12803	18	25	-	-	PUNCT
fcis-12803	18	26	time	time	NOUN
fcis-12803	18	27	requirements	requirement	NOUN
fcis-12803	18	28	.	.	PUNCT
fcis-12803	19	1	the	the	DET
fcis-12803	19	2	yolo	yolo	ADJ
fcis-12803	19	3	family	family	NOUN
fcis-12803	19	4	of	of	ADP
fcis-12803	19	5	algorithms	algorithm	NOUN
fcis-12803	19	6	was	be	AUX
fcis-12803	19	7	developed	develop	VERB
fcis-12803	19	8	to	to	PART
fcis-12803	19	9	solve	solve	VERB
fcis-12803	19	10	the	the	DET
fcis-12803	19	11	above	above	ADJ
fcis-12803	19	12	problems	problem	NOUN
fcis-12803	19	13	.	.	PUNCT
fcis-12803	20	1	the	the	DET
fcis-12803	20	2	one	one	NUM
fcis-12803	20	3	-	-	PUNCT
fcis-12803	20	4	stage	stage	NOUN
fcis-12803	20	5	target	target	NOUN
fcis-12803	20	6	detection	detection	NOUN
fcis-12803	20	7	approach	approach	NOUN
fcis-12803	20	8	,	,	PUNCT
fcis-12803	20	9	which	which	PRON
fcis-12803	20	10	treats	treat	VERB
fcis-12803	20	11	the	the	DET
fcis-12803	20	12	target	target	NOUN
fcis-12803	20	13	detection	detection	NOUN
fcis-12803	20	14	problem	problem	NOUN
fcis-12803	20	15	as	as	ADP
fcis-12803	20	16	a	a	DET
fcis-12803	20	17	regression	regression	NOUN
fcis-12803	20	18	problem	problem	NOUN
fcis-12803	20	19	,	,	PUNCT
fcis-12803	20	20	simultaneously	simultaneously	ADV
fcis-12803	20	21	predicts	predict	VERB
fcis-12803	20	22	the	the	DET
fcis-12803	20	23	location	location	NOUN
fcis-12803	20	24	and	and	CCONJ
fcis-12803	20	25	class	class	NOUN
fcis-12803	20	26	of	of	ADP
fcis-12803	20	27	targets	target	NOUN
fcis-12803	20	28	through	through	ADP
fcis-12803	20	29	a	a	DET
fcis-12803	20	30	single	single	ADJ
fcis-12803	20	31	neural	neural	ADJ
fcis-12803	20	32	network	network	NOUN
fcis-12803	20	33	model	model	NOUN
fcis-12803	20	34	instead	instead	ADV
fcis-12803	20	35	of	of	ADP
fcis-12803	20	36	selecting	select	VERB
fcis-12803	20	37	candidate	candidate	NOUN
fcis-12803	20	38	regions	region	NOUN
fcis-12803	20	39	one	one	NUM
fcis-12803	20	40	by	by	ADP
fcis-12803	20	41	one	one	NUM
fcis-12803	20	42	.	.	PUNCT
fcis-12803	21	1	this	this	PRON
fcis-12803	21	2	gives	give	VERB
fcis-12803	21	3	yolo	yolo	ADP
fcis-12803	21	4	a	a	DET
fcis-12803	21	5	good	good	ADJ
fcis-12803	21	6	balance	balance	NOUN
fcis-12803	21	7	between	between	ADP
fcis-12803	21	8	speed	speed	NOUN
fcis-12803	21	9	and	and	CCONJ
fcis-12803	21	10	accuracy	accuracy	NOUN
fcis-12803	21	11	.	.	PUNCT
fcis-12803	22	1	r	r	X
fcis-12803	22	2	-	-	PUNCT
fcis-12803	22	3	cnn	cnn	PROPN
fcis-12803	22	4	is	be	AUX
fcis-12803	22	5	the	the	DET
fcis-12803	22	6	first	first	ADJ
fcis-12803	22	7	algorithm	algorithm	NOUN
fcis-12803	22	8	that	that	PRON
fcis-12803	22	9	utilizes	utilize	VERB
fcis-12803	22	10	cnn	cnn	PROPN
fcis-12803	22	11	for	for	ADP
fcis-12803	22	12	target	target	NOUN
fcis-12803	22	13	detection	detection	NOUN
fcis-12803	22	14	,	,	PUNCT
fcis-12803	22	15	which	which	PRON
fcis-12803	22	16	opens	open	VERB
fcis-12803	22	17	the	the	DET
fcis-12803	22	18	era	era	NOUN
fcis-12803	22	19	of	of	ADP
fcis-12803	22	20	target	target	NOUN
fcis-12803	22	21	detection	detection	NOUN
fcis-12803	22	22	based	base	VERB
fcis-12803	22	23	on	on	ADP
fcis-12803	22	24	deep	deep	ADJ
fcis-12803	22	25	learning	learning	NOUN
fcis-12803	22	26	.	.	PUNCT
fcis-12803	23	1	yolo	yolo	PROPN
fcis-12803	23	2	is	be	AUX
fcis-12803	23	3	the	the	DET
fcis-12803	23	4	first	first	ADJ
fcis-12803	23	5	target	target	NOUN
fcis-12803	23	6	detection	detection	NOUN
fcis-12803	23	7	algorithm	algorithm	NOUN
fcis-12803	23	8	,	,	PUNCT
fcis-12803	23	9	and	and	CCONJ
fcis-12803	23	10	many	many	ADJ
fcis-12803	23	11	researchers	researcher	NOUN
fcis-12803	23	12	have	have	AUX
fcis-12803	23	13	proposed	propose	VERB
fcis-12803	23	14	a	a	DET
fcis-12803	23	15	series	series	NOUN
fcis-12803	23	16	of	of	ADP
fcis-12803	23	17	highperformance	highperformance	NOUN
fcis-12803	23	18	target	target	NOUN
fcis-12803	23	19	detection	detection	NOUN
fcis-12803	23	20	algorithms	algorithm	NOUN
fcis-12803	23	21	under	under	ADP
fcis-12803	23	22	the	the	DET
fcis-12803	23	23	influence	influence	NOUN
fcis-12803	23	24	of	of	ADP
fcis-12803	23	25	yolo	yolo	PROPN
fcis-12803	23	26	,	,	PUNCT
fcis-12803	23	27	and	and	CCONJ
fcis-12803	23	28	the	the	DET
fcis-12803	23	29	r	r	NOUN
fcis-12803	23	30	-	-	PUNCT
fcis-12803	23	31	cnn	cnn	PROPN
fcis-12803	23	32	and	and	CCONJ
fcis-12803	23	33	yolo	yolo	ADJ
fcis-12803	23	34	algorithms	algorithm	NOUN
fcis-12803	23	35	have	have	AUX
fcis-12803	23	36	greatly	greatly	ADV
fcis-12803	23	37	promoted	promote	VERB
fcis-12803	23	38	the	the	DET
fcis-12803	23	39	development	development	NOUN
fcis-12803	23	40	of	of	ADP
fcis-12803	23	41	target	target	NOUN
fcis-12803	23	42	detection	detection	NOUN
fcis-12803	23	43	technology	technology	NOUN
fcis-12803	23	44	.	.	PUNCT
fcis-12803	24	1	2.3	2.3	NUM
fcis-12803	24	2	.	.	PUNCT
fcis-12803	24	3	theory	theory	NOUN
fcis-12803	24	4	related	relate	VERB
fcis-12803	24	5	to	to	ADP
fcis-12803	24	6	yolov7	yolov7	NOUN
fcis-12803	24	7	yolov7	yolov7	NOUN
fcis-12803	24	8	(	(	PUNCT
fcis-12803	24	9	you	you	PRON
fcis-12803	24	10	only	only	ADV
fcis-12803	24	11	look	look	VERB
fcis-12803	24	12	once	once	ADV
fcis-12803	24	13	version	version	NOUN
fcis-12803	24	14	7)[10	7)[10	NUM
fcis-12803	24	15	]	]	PUNCT
fcis-12803	24	16	is	be	AUX
fcis-12803	24	17	a	a	DET
fcis-12803	24	18	deep	deep	ADJ
fcis-12803	24	19	learning	learning	NOUN
fcis-12803	24	20	model	model	NOUN
fcis-12803	24	21	in	in	ADP
fcis-12803	24	22	the	the	DET
fcis-12803	24	23	field	field	NOUN
fcis-12803	24	24	of	of	ADP
fcis-12803	24	25	target	target	NOUN
fcis-12803	24	26	detection	detection	NOUN
fcis-12803	24	27	,	,	PUNCT
fcis-12803	24	28	which	which	PRON
fcis-12803	24	29	is	be	AUX
fcis-12803	24	30	the	the	DET
fcis-12803	24	31	latest	late	ADJ
fcis-12803	24	32	version	version	NOUN
fcis-12803	24	33	of	of	ADP
fcis-12803	24	34	the	the	DET
fcis-12803	24	35	yolo	yolo	ADJ
fcis-12803	24	36	series	series	NOUN
fcis-12803	24	37	.	.	PUNCT
fcis-12803	25	1	the	the	DET
fcis-12803	25	2	main	main	ADJ
fcis-12803	25	3	feature	feature	NOUN
fcis-12803	25	4	of	of	ADP
fcis-12803	25	5	the	the	DET
fcis-12803	25	6	yolo	yolo	ADJ
fcis-12803	25	7	series	series	NOUN
fcis-12803	25	8	of	of	ADP
fcis-12803	25	9	models	model	NOUN
fcis-12803	25	10	is	be	AUX
fcis-12803	25	11	the	the	DET
fcis-12803	25	12	ability	ability	NOUN
fcis-12803	25	13	to	to	PART
fcis-12803	25	14	perform	perform	VERB
fcis-12803	25	15	target	target	NOUN
fcis-12803	25	16	detection	detection	NOUN
fcis-12803	25	17	in	in	ADP
fcis-12803	25	18	real	real	ADJ
fcis-12803	25	19	time	time	NOUN
fcis-12803	25	20	while	while	SCONJ
fcis-12803	25	21	maintaining	maintain	VERB
fcis-12803	25	22	high	high	ADJ
fcis-12803	25	23	accuracy.yolov7	accuracy.yolov7	ADV
fcis-12803	25	24	improves	improve	VERB
fcis-12803	25	25	and	and	CCONJ
fcis-12803	25	26	optimizes	optimize	VERB
fcis-12803	25	27	on	on	ADP
fcis-12803	25	28	yolov5	yolov5	NOUN
fcis-12803	25	29	,	,	PUNCT
fcis-12803	25	30	aiming	aim	VERB
fcis-12803	25	31	to	to	PART
fcis-12803	25	32	improve	improve	VERB
fcis-12803	25	33	the	the	DET
fcis-12803	25	34	detection	detection	NOUN
fcis-12803	25	35	performance	performance	NOUN
fcis-12803	25	36	and	and	CCONJ
fcis-12803	25	37	speed	speed	NOUN
fcis-12803	25	38	.	.	PUNCT
fcis-12803	26	1	yolov7	yolov7	PROPN
fcis-12803	26	2	is	be	AUX
fcis-12803	26	3	based	base	VERB
fcis-12803	26	4	on	on	ADP
fcis-12803	26	5	yolov5	yolov5	NOUN
fcis-12803	26	6	and	and	CCONJ
fcis-12803	26	7	has	have	AUX
fcis-12803	26	8	been	be	AUX
fcis-12803	26	9	improved	improve	VERB
fcis-12803	26	10	and	and	CCONJ
fcis-12803	26	11	optimized	optimize	VERB
fcis-12803	26	12	with	with	ADP
fcis-12803	26	13	the	the	DET
fcis-12803	26	14	aim	aim	NOUN
fcis-12803	26	15	of	of	ADP
fcis-12803	26	16	increasing	increase	VERB
fcis-12803	26	17	detection	detection	NOUN
fcis-12803	26	18	performance	performance	NOUN
fcis-12803	26	19	and	and	CCONJ
fcis-12803	26	20	speed	speed	NOUN
fcis-12803	26	21	.	.	PUNCT
fcis-12803	27	1	the	the	DET
fcis-12803	27	2	model	model	NOUN
fcis-12803	27	3	structure	structure	NOUN
fcis-12803	27	4	includes	include	VERB
fcis-12803	27	5	four	four	NUM
fcis-12803	27	6	parts	part	NOUN
fcis-12803	27	7	:	:	PUNCT
fcis-12803	27	8	input	input	NOUN
fcis-12803	27	9	,	,	PUNCT
fcis-12803	27	10	backbone	backbone	NOUN
fcis-12803	27	11	,	,	PUNCT
fcis-12803	27	12	head	head	NOUN
fcis-12803	27	13	,	,	PUNCT
fcis-12803	27	14	and	and	CCONJ
fcis-12803	27	15	neck	neck	NOUN
fcis-12803	27	16	.	.	PUNCT
fcis-12803	28	1	input	input	NOUN
fcis-12803	28	2	:	:	PUNCT
fcis-12803	28	3	the	the	DET
fcis-12803	28	4	main	main	ADJ
fcis-12803	28	5	role	role	NOUN
fcis-12803	28	6	is	be	AUX
fcis-12803	28	7	to	to	PART
fcis-12803	28	8	perform	perform	VERB
fcis-12803	28	9	a	a	DET
fcis-12803	28	10	series	series	NOUN
fcis-12803	28	11	of	of	ADP
fcis-12803	28	12	preprocessing	preprocesse	VERB
fcis-12803	28	13	operations	operation	NOUN
fcis-12803	28	14	on	on	ADP
fcis-12803	28	15	the	the	DET
fcis-12803	28	16	input	input	NOUN
fcis-12803	28	17	image	image	NOUN
fcis-12803	28	18	,	,	PUNCT
fcis-12803	28	19	including	include	VERB
fcis-12803	28	20	mosaic	mosaic	ADJ
fcis-12803	28	21	data	data	NOUN
fcis-12803	28	22	enhancement	enhancement	NOUN
fcis-12803	28	23	,	,	PUNCT
fcis-12803	28	24	adaptive	adaptive	ADJ
fcis-12803	28	25	anchor	anchor	NOUN
fcis-12803	28	26	frame	frame	NOUN
fcis-12803	28	27	calculation	calculation	NOUN
fcis-12803	28	28	,	,	PUNCT
fcis-12803	28	29	and	and	CCONJ
fcis-12803	28	30	image	image	NOUN
fcis-12803	28	31	scaling	scaling	NOUN
fcis-12803	28	32	.	.	PUNCT
fcis-12803	29	1	backbone	backbone	NOUN
fcis-12803	29	2	:	:	PUNCT
fcis-12803	29	3	the	the	DET
fcis-12803	29	4	consists	consist	NOUN
fcis-12803	29	5	of	of	ADP
fcis-12803	29	6	several	several	ADJ
fcis-12803	29	7	cbs	cbs	PROPN
fcis-12803	29	8	convolutional	convolutional	ADJ
fcis-12803	29	9	modules	module	NOUN
fcis-12803	29	10	,	,	PUNCT
fcis-12803	29	11	elan	elan	PROPN
fcis-12803	29	12	modules	module	NOUN
fcis-12803	29	13	and	and	CCONJ
fcis-12803	29	14	mp-1	mp-1	NOUN
fcis-12803	29	15	modules	module	NOUN
fcis-12803	29	16	.	.	PUNCT
fcis-12803	30	1	the	the	DET
fcis-12803	30	2	cbs	cbs	PROPN
fcis-12803	30	3	module	module	NOUN
fcis-12803	30	4	consists	consist	VERB
fcis-12803	30	5	of	of	ADP
fcis-12803	30	6	a	a	DET
fcis-12803	30	7	convolutional	convolutional	ADJ
fcis-12803	30	8	layer	layer	NOUN
fcis-12803	30	9	,	,	PUNCT
fcis-12803	30	10	a	a	DET
fcis-12803	30	11	bulk	bulk	NOUN
fcis-12803	30	12	-	-	PUNCT
fcis-12803	30	13	normalized	normalize	VERB
fcis-12803	30	14	bn	bn	NOUN
fcis-12803	30	15	layer	layer	NOUN
fcis-12803	30	16	and	and	CCONJ
fcis-12803	30	17	a	a	DET
fcis-12803	30	18	silu	silu	ADJ
fcis-12803	30	19	activation	activation	NOUN
fcis-12803	30	20	function	function	NOUN
fcis-12803	30	21	.	.	PUNCT
fcis-12803	31	1	the	the	DET
fcis-12803	31	2	elan	elan	PROPN
fcis-12803	31	3	module	module	NOUN
fcis-12803	31	4	consists	consist	VERB
fcis-12803	31	5	of	of	ADP
fcis-12803	31	6	a	a	DET
fcis-12803	31	7	number	number	NOUN
fcis-12803	31	8	of	of	ADP
fcis-12803	31	9	convolutional	convolutional	ADJ
fcis-12803	31	10	modules	module	NOUN
fcis-12803	31	11	,	,	PUNCT
fcis-12803	31	12	which	which	PRON
fcis-12803	31	13	are	be	AUX
fcis-12803	31	14	used	use	VERB
fcis-12803	31	15	to	to	PART
fcis-12803	31	16	learn	learn	VERB
fcis-12803	31	17	and	and	CCONJ
fcis-12803	31	18	converge	converge	VERB
fcis-12803	31	19	more	more	ADV
fcis-12803	31	20	efficiently	efficiently	ADV
fcis-12803	31	21	by	by	ADP
fcis-12803	31	22	controlling	control	VERB
fcis-12803	31	23	the	the	DET
fcis-12803	31	24	shortest	short	ADJ
fcis-12803	31	25	and	and	CCONJ
fcis-12803	31	26	longest	long	ADJ
fcis-12803	31	27	gradient	gradient	ADJ
fcis-12803	31	28	paths	path	NOUN
fcis-12803	31	29	.	.	PUNCT
fcis-12803	32	1	head	head	NOUN
fcis-12803	32	2	:	:	PUNCT
fcis-12803	32	3	it	it	PRON
fcis-12803	32	4	mainly	mainly	ADV
fcis-12803	32	5	includes	include	VERB
fcis-12803	32	6	sppcspc	sppcspc	NOUN
fcis-12803	32	7	,	,	PUNCT
fcis-12803	32	8	elan	elan	PROPN
fcis-12803	32	9	-	-	PUNCT
fcis-12803	32	10	w	w	PROPN
fcis-12803	32	11	,	,	PUNCT
fcis-12803	32	12	upsmaple	upsmaple	ADJ
fcis-12803	32	13	and	and	CCONJ
fcis-12803	32	14	mp-2	mp-2	ADJ
fcis-12803	32	15	.	.	PUNCT
fcis-12803	33	1	it	it	PRON
fcis-12803	33	2	performs	perform	VERB
fcis-12803	33	3	feature	feature	NOUN
fcis-12803	33	4	processing	processing	NOUN
fcis-12803	33	5	on	on	ADP
fcis-12803	33	6	the	the	DET
fcis-12803	33	7	output	output	NOUN
fcis-12803	33	8	image	image	NOUN
fcis-12803	33	9	of	of	ADP
fcis-12803	33	10	the	the	DET
fcis-12803	33	11	backbone	backbone	NOUN
fcis-12803	33	12	network	network	NOUN
fcis-12803	33	13	,	,	PUNCT
fcis-12803	33	14	and	and	CCONJ
fcis-12803	33	15	adopts	adopt	VERB
fcis-12803	33	16	the	the	DET
fcis-12803	33	17	path	path	NOUN
fcis-12803	33	18	aggregation	aggregation	NOUN
fcis-12803	33	19	feature	feature	NOUN
fcis-12803	33	20	pyramid	pyramid	NOUN
fcis-12803	33	21	network	network	NOUN
fcis-12803	33	22	(	(	PUNCT
fcis-12803	33	23	pafpn	pafpn	PROPN
fcis-12803	33	24	)	)	PUNCT
fcis-12803	33	25	structure	structure	NOUN
fcis-12803	33	26	for	for	ADP
fcis-12803	33	27	multi	multi	ADJ
fcis-12803	33	28	-	-	ADJ
fcis-12803	33	29	scale	scale	ADJ
fcis-12803	33	30	feature	feature	NOUN
fcis-12803	33	31	fusion	fusion	NOUN
fcis-12803	33	32	.	.	PUNCT
fcis-12803	34	1	the	the	DET
fcis-12803	34	2	top	top	ADJ
fcis-12803	34	3	-	-	PUNCT
fcis-12803	34	4	down	down	ADP
fcis-12803	34	5	structure	structure	NOUN
fcis-12803	34	6	is	be	AUX
fcis-12803	34	7	used	use	VERB
fcis-12803	34	8	to	to	PART
fcis-12803	34	9	pass	pass	VERB
fcis-12803	34	10	down	down	ADP
fcis-12803	34	11	the	the	DET
fcis-12803	34	12	deep	deep	ADJ
fcis-12803	34	13	strong	strong	ADJ
fcis-12803	34	14	semantic	semantic	ADJ
fcis-12803	34	15	features	feature	NOUN
fcis-12803	34	16	to	to	PART
fcis-12803	34	17	enhance	enhance	VERB
fcis-12803	34	18	the	the	DET
fcis-12803	34	19	features	feature	NOUN
fcis-12803	34	20	of	of	ADP
fcis-12803	34	21	the	the	DET
fcis-12803	34	22	whole	whole	ADJ
fcis-12803	34	23	pyramid	pyramid	NOUN
fcis-12803	34	24	;	;	PUNCT
fcis-12803	34	25	finally	finally	ADV
fcis-12803	34	26	,	,	PUNCT
fcis-12803	34	27	the	the	DET
fcis-12803	34	28	bottom	bottom	ADJ
fcis-12803	34	29	-	-	PUNCT
fcis-12803	34	30	up	up	ADP
fcis-12803	34	31	structure	structure	NOUN
fcis-12803	34	32	is	be	AUX
fcis-12803	34	33	used	use	VERB
fcis-12803	34	34	to	to	PART
fcis-12803	34	35	pass	pass	VERB
fcis-12803	34	36	up	up	ADP
fcis-12803	34	37	the	the	DET
fcis-12803	34	38	shallow	shallow	ADJ
fcis-12803	34	39	image	image	NOUN
fcis-12803	34	40	structure	structure	NOUN
fcis-12803	34	41	,	,	PUNCT
fcis-12803	34	42	color	color	NOUN
fcis-12803	34	43	,	,	PUNCT
fcis-12803	34	44	edge	edge	NOUN
fcis-12803	34	45	,	,	PUNCT
fcis-12803	34	46	position	position	NOUN
fcis-12803	34	47	and	and	CCONJ
fcis-12803	34	48	other	other	ADJ
fcis-12803	34	49	feature	feature	NOUN
fcis-12803	34	50	information	information	NOUN
fcis-12803	34	51	,	,	PUNCT
fcis-12803	34	52	thus	thus	ADV
fcis-12803	34	53	realizing	realize	VERB
fcis-12803	34	54	the	the	DET
fcis-12803	34	55	efficient	efficient	ADJ
fcis-12803	34	56	fusion	fusion	NOUN
fcis-12803	34	57	of	of	ADP
fcis-12803	34	58	features	feature	NOUN
fcis-12803	34	59	at	at	ADP
fcis-12803	34	60	different	different	ADJ
fcis-12803	34	61	levels	level	NOUN
fcis-12803	34	62	.	.	PUNCT
fcis-12803	35	1	neck	neck	NOUN
fcis-12803	35	2	:	:	PUNCT
fcis-12803	35	3	it	it	PRON
fcis-12803	35	4	uses	use	VERB
fcis-12803	35	5	the	the	DET
fcis-12803	35	6	rep	rep	NOUN
fcis-12803	35	7	structure	structure	NOUN
fcis-12803	35	8	to	to	PART
fcis-12803	35	9	adjust	adjust	VERB
fcis-12803	35	10	the	the	DET
fcis-12803	35	11	number	number	NOUN
fcis-12803	35	12	of	of	ADP
fcis-12803	35	13	73	73	NUM
fcis-12803	35	14	channels	channel	NOUN
fcis-12803	35	15	to	to	ADP
fcis-12803	35	16	the	the	DET
fcis-12803	35	17	p3	p3	PROPN
fcis-12803	35	18	,	,	PUNCT
fcis-12803	35	19	p4	p4	ADJ
fcis-12803	35	20	,	,	PUNCT
fcis-12803	35	21	and	and	CCONJ
fcis-12803	35	22	p5	p5	ADJ
fcis-12803	35	23	features	feature	NOUN
fcis-12803	35	24	output	output	NOUN
fcis-12803	35	25	from	from	ADP
fcis-12803	35	26	the	the	DET
fcis-12803	35	27	pafpn	pafpn	NOUN
fcis-12803	35	28	structure	structure	NOUN
fcis-12803	35	29	.	.	PUNCT
fcis-12803	36	1	finally	finally	ADV
fcis-12803	36	2	,	,	PUNCT
fcis-12803	36	3	these	these	DET
fcis-12803	36	4	features	feature	NOUN
fcis-12803	36	5	are	be	AUX
fcis-12803	36	6	fed	feed	VERB
fcis-12803	36	7	into	into	ADP
fcis-12803	36	8	a	a	DET
fcis-12803	36	9	1×1	1×1	ADJ
fcis-12803	36	10	convolutional	convolutional	ADJ
fcis-12803	36	11	module	module	NOUN
fcis-12803	36	12	for	for	ADP
fcis-12803	36	13	predicting	predict	VERB
fcis-12803	36	14	the	the	DET
fcis-12803	36	15	confidence	confidence	NOUN
fcis-12803	36	16	,	,	PUNCT
fcis-12803	36	17	category	category	NOUN
fcis-12803	36	18	and	and	CCONJ
fcis-12803	36	19	anchor	anchor	NOUN
fcis-12803	36	20	frame	frame	NOUN
fcis-12803	36	21	information	information	NOUN
fcis-12803	36	22	of	of	ADP
fcis-12803	36	23	the	the	DET
fcis-12803	36	24	image	image	NOUN
fcis-12803	36	25	and	and	CCONJ
fcis-12803	36	26	generating	generate	VERB
fcis-12803	36	27	the	the	DET
fcis-12803	36	28	final	final	ADJ
fcis-12803	36	29	detection	detection	NOUN
fcis-12803	36	30	results	result	NOUN
fcis-12803	36	31	.	.	PUNCT
fcis-12803	37	1	3	3	X
fcis-12803	37	2	.	.	X
fcis-12803	37	3	improvements	improvement	NOUN
fcis-12803	37	4	to	to	ADP
fcis-12803	37	5	the	the	DET
fcis-12803	37	6	yolov7	yolov7	NOUN
fcis-12803	37	7	3.1	3.1	NUM
fcis-12803	37	8	.	.	PUNCT
fcis-12803	37	9	introducing	introduce	VERB
fcis-12803	37	10	bifpn	bifpn	PROPN
fcis-12803	37	11	bifpn	bifpn	PROPN
fcis-12803	37	12	(	(	PUNCT
fcis-12803	37	13	bi	bi	ADJ
fcis-12803	37	14	-	-	ADJ
fcis-12803	37	15	directional	directional	ADJ
fcis-12803	37	16	feature	feature	NOUN
fcis-12803	37	17	pyramid	pyramid	NOUN
fcis-12803	37	18	network)[11	network)[11	NUM
fcis-12803	37	19	]	]	PUNCT
fcis-12803	37	20	is	be	AUX
fcis-12803	37	21	a	a	DET
fcis-12803	37	22	deep	deep	ADJ
fcis-12803	37	23	neural	neural	ADJ
fcis-12803	37	24	network	network	NOUN
fcis-12803	37	25	architecture	architecture	NOUN
fcis-12803	37	26	for	for	ADP
fcis-12803	37	27	target	target	NOUN
fcis-12803	37	28	detection	detection	NOUN
fcis-12803	37	29	and	and	CCONJ
fcis-12803	37	30	semantic	semantic	ADJ
fcis-12803	37	31	segmentation	segmentation	NOUN
fcis-12803	37	32	tasks	task	NOUN
fcis-12803	37	33	,	,	PUNCT
fcis-12803	37	34	which	which	PRON
fcis-12803	37	35	is	be	AUX
fcis-12803	37	36	designed	design	VERB
fcis-12803	37	37	to	to	PART
fcis-12803	37	38	extract	extract	VERB
fcis-12803	37	39	multi	multi	ADJ
fcis-12803	37	40	-	-	ADJ
fcis-12803	37	41	scale	scale	ADJ
fcis-12803	37	42	features	feature	NOUN
fcis-12803	37	43	in	in	ADP
fcis-12803	37	44	images	image	NOUN
fcis-12803	37	45	and	and	CCONJ
fcis-12803	37	46	help	help	VERB
fcis-12803	37	47	the	the	DET
fcis-12803	37	48	model	model	NOUN
fcis-12803	37	49	to	to	PART
fcis-12803	37	50	better	well	ADV
fcis-12803	37	51	understand	understand	VERB
fcis-12803	37	52	and	and	CCONJ
fcis-12803	37	53	process	process	VERB
fcis-12803	37	54	targets	target	NOUN
fcis-12803	37	55	at	at	ADP
fcis-12803	37	56	different	different	ADJ
fcis-12803	37	57	scales	scale	NOUN
fcis-12803	37	58	.	.	PUNCT
fcis-12803	38	1	the	the	DET
fcis-12803	38	2	design	design	NOUN
fcis-12803	38	3	of	of	ADP
fcis-12803	38	4	bifpn	bifpn	PROPN
fcis-12803	38	5	is	be	AUX
fcis-12803	38	6	inspired	inspire	VERB
fcis-12803	38	7	by	by	ADP
fcis-12803	38	8	network	network	NOUN
fcis-12803	38	9	architectures	architecture	NOUN
fcis-12803	38	10	such	such	ADJ
fcis-12803	38	11	as	as	ADP
fcis-12803	38	12	fpn	fpn	NOUN
fcis-12803	38	13	(	(	PUNCT
fcis-12803	38	14	feature	feature	NOUN
fcis-12803	38	15	pyramid	pyramid	NOUN
fcis-12803	38	16	network	network	NOUN
fcis-12803	38	17	)	)	PUNCT
fcis-12803	38	18	and	and	CCONJ
fcis-12803	38	19	network	network	NOUN
fcis-12803	38	20	architectures	architecture	NOUN
fcis-12803	38	21	such	such	ADJ
fcis-12803	38	22	as	as	ADP
fcis-12803	38	23	panet	panet	NOUN
fcis-12803	38	24	,	,	PUNCT
fcis-12803	38	25	which	which	PRON
fcis-12803	38	26	has	have	VERB
fcis-12803	38	27	higher	high	ADJ
fcis-12803	38	28	efficiency	efficiency	NOUN
fcis-12803	38	29	and	and	CCONJ
fcis-12803	38	30	performance	performance	NOUN
fcis-12803	38	31	in	in	ADP
fcis-12803	38	32	processing	process	VERB
fcis-12803	38	33	multi	multi	ADJ
fcis-12803	38	34	-	-	ADJ
fcis-12803	38	35	scale	scale	ADJ
fcis-12803	38	36	features	feature	NOUN
fcis-12803	38	37	.	.	PUNCT
fcis-12803	39	1	as	as	SCONJ
fcis-12803	39	2	shown	show	VERB
fcis-12803	39	3	in	in	ADP
fcis-12803	39	4	figure	figure	NOUN
fcis-12803	39	5	1	1	NUM
fcis-12803	39	6	.	.	PUNCT
fcis-12803	39	7	figure	figure	NOUN
fcis-12803	39	8	1	1	NUM
fcis-12803	39	9	.	.	PUNCT
fcis-12803	40	1	bifpn	bifpn	PROPN
fcis-12803	40	2	structure	structure	PROPN
fcis-12803	40	3	bifpn	bifpn	PROPN
fcis-12803	40	4	consists	consist	VERB
fcis-12803	40	5	of	of	ADP
fcis-12803	40	6	multiple	multiple	ADJ
fcis-12803	40	7	repeating	repeat	VERB
fcis-12803	40	8	modules	module	NOUN
fcis-12803	40	9	,	,	PUNCT
fcis-12803	40	10	each	each	DET
fcis-12803	40	11	consisting	consist	VERB
fcis-12803	40	12	of	of	ADP
fcis-12803	40	13	the	the	DET
fcis-12803	40	14	following	follow	VERB
fcis-12803	40	15	steps	step	NOUN
fcis-12803	40	16	:	:	PUNCT
fcis-12803	40	17	a.	a.	NOUN
fcis-12803	40	18	bottom	bottom	PROPN
fcis-12803	40	19	-	-	PUNCT
fcis-12803	40	20	up	up	ADP
fcis-12803	40	21	connectivity	connectivity	NOUN
fcis-12803	40	22	:	:	PUNCT
fcis-12803	40	23	propagating	propagate	VERB
fcis-12803	40	24	information	information	NOUN
fcis-12803	40	25	from	from	ADP
fcis-12803	40	26	high	high	ADJ
fcis-12803	40	27	-	-	PUNCT
fcis-12803	40	28	resolution	resolution	NOUN
fcis-12803	40	29	bottom	bottom	NOUN
fcis-12803	40	30	features	feature	NOUN
fcis-12803	40	31	to	to	ADP
fcis-12803	40	32	low	low	ADJ
fcis-12803	40	33	-	-	PUNCT
fcis-12803	40	34	resolution	resolution	NOUN
fcis-12803	40	35	top	top	ADJ
fcis-12803	40	36	-	-	PUNCT
fcis-12803	40	37	level	level	NOUN
fcis-12803	40	38	features	feature	NOUN
fcis-12803	40	39	.	.	PUNCT
fcis-12803	41	1	b.	b.	PROPN
fcis-12803	41	2	top	top	VERB
fcis-12803	41	3	-	-	PUNCT
fcis-12803	41	4	down	down	ADP
fcis-12803	41	5	connection	connection	NOUN
fcis-12803	41	6	:	:	PUNCT
fcis-12803	41	7	propagating	propagate	VERB
fcis-12803	41	8	information	information	NOUN
fcis-12803	41	9	from	from	ADP
fcis-12803	41	10	low	low	ADJ
fcis-12803	41	11	-	-	PUNCT
fcis-12803	41	12	resolution	resolution	NOUN
fcis-12803	41	13	high	high	ADJ
fcis-12803	41	14	-	-	PUNCT
fcis-12803	41	15	level	level	NOUN
fcis-12803	41	16	features	feature	NOUN
fcis-12803	41	17	to	to	ADP
fcis-12803	41	18	high	high	ADJ
fcis-12803	41	19	-	-	PUNCT
fcis-12803	41	20	resolution	resolution	NOUN
fcis-12803	41	21	bottom	bottom	ADJ
fcis-12803	41	22	-	-	PUNCT
fcis-12803	41	23	level	level	NOUN
fcis-12803	41	24	features	feature	NOUN
fcis-12803	41	25	.	.	PUNCT
fcis-12803	42	1	c.	c.	PROPN
fcis-12803	42	2	cross	cross	PROPN
fcis-12803	42	3	-	-	NOUN
fcis-12803	42	4	layer	layer	ADJ
fcis-12803	42	5	connectivity	connectivity	NOUN
fcis-12803	42	6	:	:	PUNCT
fcis-12803	42	7	propagate	propagate	VERB
fcis-12803	42	8	information	information	NOUN
fcis-12803	42	9	between	between	ADP
fcis-12803	42	10	different	different	ADJ
fcis-12803	42	11	layers	layer	NOUN
fcis-12803	42	12	to	to	PART
fcis-12803	42	13	make	make	VERB
fcis-12803	42	14	feature	feature	NOUN
fcis-12803	42	15	fusion	fusion	NOUN
fcis-12803	42	16	more	more	ADV
fcis-12803	42	17	complete	complete	ADJ
fcis-12803	42	18	.	.	PUNCT
fcis-12803	43	1	d.	d.	PROPN
fcis-12803	43	2	feature	feature	PROPN
fcis-12803	43	3	fusion	fusion	NOUN
fcis-12803	43	4	:	:	PUNCT
fcis-12803	43	5	fuses	fuse	NOUN
fcis-12803	43	6	feature	feature	VERB
fcis-12803	43	7	from	from	ADP
fcis-12803	43	8	different	different	ADJ
fcis-12803	43	9	connections	connection	NOUN
fcis-12803	43	10	to	to	PART
fcis-12803	43	11	generate	generate	VERB
fcis-12803	43	12	the	the	DET
fcis-12803	43	13	final	final	ADJ
fcis-12803	43	14	multi	multi	ADJ
fcis-12803	43	15	-	-	ADJ
fcis-12803	43	16	scale	scale	ADJ
fcis-12803	43	17	feature	feature	NOUN
fcis-12803	43	18	pyramid	pyramid	NOUN
fcis-12803	43	19	.	.	PUNCT
fcis-12803	44	1	in	in	ADP
fcis-12803	44	2	order	order	NOUN
fcis-12803	44	3	to	to	PART
fcis-12803	44	4	optimize	optimize	VERB
fcis-12803	44	5	the	the	DET
fcis-12803	44	6	detection	detection	NOUN
fcis-12803	44	7	process	process	NOUN
fcis-12803	44	8	,	,	PUNCT
fcis-12803	44	9	we	we	PRON
fcis-12803	44	10	try	try	VERB
fcis-12803	44	11	to	to	PART
fcis-12803	44	12	embed	embed	VERB
fcis-12803	44	13	bifpn	bifpn	PROPN
fcis-12803	44	14	in	in	ADP
fcis-12803	44	15	the	the	DET
fcis-12803	44	16	feature	feature	NOUN
fcis-12803	44	17	extraction	extraction	NOUN
fcis-12803	44	18	network	network	NOUN
fcis-12803	44	19	of	of	ADP
fcis-12803	44	20	yolov7	yolov7	NOUN
fcis-12803	44	21	,	,	PUNCT
fcis-12803	44	22	replacing	replace	VERB
fcis-12803	44	23	the	the	DET
fcis-12803	44	24	original	original	ADJ
fcis-12803	44	25	backbone	backbone	NOUN
fcis-12803	44	26	and	and	CCONJ
fcis-12803	44	27	neck	neck	NOUN
fcis-12803	44	28	networks	network	NOUN
fcis-12803	44	29	to	to	PART
fcis-12803	44	30	enhance	enhance	VERB
fcis-12803	44	31	the	the	DET
fcis-12803	44	32	fusion	fusion	NOUN
fcis-12803	44	33	of	of	ADP
fcis-12803	44	34	multi	multi	ADJ
fcis-12803	44	35	-	-	ADJ
fcis-12803	44	36	scale	scale	ADJ
fcis-12803	44	37	features	feature	NOUN
fcis-12803	44	38	,	,	PUNCT
fcis-12803	44	39	thus	thus	ADV
fcis-12803	44	40	improving	improve	VERB
fcis-12803	44	41	the	the	DET
fcis-12803	44	42	performance	performance	NOUN
fcis-12803	44	43	of	of	ADP
fcis-12803	44	44	target	target	NOUN
fcis-12803	44	45	detection	detection	NOUN
fcis-12803	44	46	.	.	PUNCT
fcis-12803	45	1	3.2	3.2	NUM
fcis-12803	45	2	.	.	PUNCT
fcis-12803	45	3	attention	attention	NOUN
fcis-12803	45	4	in	in	ADP
fcis-12803	45	5	the	the	DET
fcis-12803	45	6	study	study	NOUN
fcis-12803	45	7	of	of	ADP
fcis-12803	45	8	human	human	ADJ
fcis-12803	45	9	vision	vision	NOUN
fcis-12803	45	10	,	,	PUNCT
fcis-12803	45	11	it	it	PRON
fcis-12803	45	12	has	have	AUX
fcis-12803	45	13	been	be	AUX
fcis-12803	45	14	found	find	VERB
fcis-12803	45	15	that	that	SCONJ
fcis-12803	45	16	humans	human	NOUN
fcis-12803	45	17	selectively	selectively	ADV
fcis-12803	45	18	focus	focus	VERB
fcis-12803	45	19	on	on	ADP
fcis-12803	45	20	certain	certain	ADJ
fcis-12803	45	21	visible	visible	ADJ
fcis-12803	45	22	information	information	NOUN
fcis-12803	45	23	and	and	CCONJ
fcis-12803	45	24	ignore	ignore	VERB
fcis-12803	45	25	other	other	ADJ
fcis-12803	45	26	information	information	NOUN
fcis-12803	45	27	to	to	PART
fcis-12803	45	28	rationally	rationally	ADV
fcis-12803	45	29	utilize	utilize	VERB
fcis-12803	45	30	the	the	DET
fcis-12803	45	31	limited	limited	ADJ
fcis-12803	45	32	visual	visual	ADJ
fcis-12803	45	33	processing	processing	NOUN
fcis-12803	45	34	resources	resource	NOUN
fcis-12803	45	35	.	.	PUNCT
fcis-12803	46	1	at	at	ADP
fcis-12803	46	2	the	the	DET
fcis-12803	46	3	same	same	ADJ
fcis-12803	46	4	time	time	NOUN
fcis-12803	46	5	,	,	PUNCT
fcis-12803	46	6	it	it	PRON
fcis-12803	46	7	has	have	AUX
fcis-12803	46	8	been	be	AUX
fcis-12803	46	9	found	find	VERB
fcis-12803	46	10	that	that	SCONJ
fcis-12803	46	11	selective	selective	ADJ
fcis-12803	46	12	encoding	encoding	NOUN
fcis-12803	46	13	of	of	ADP
fcis-12803	46	14	input	input	NOUN
fcis-12803	46	15	data	datum	NOUN
fcis-12803	46	16	can	can	AUX
fcis-12803	46	17	effectively	effectively	ADV
fcis-12803	46	18	improve	improve	VERB
fcis-12803	46	19	the	the	DET
fcis-12803	46	20	expression	expression	NOUN
fcis-12803	46	21	and	and	CCONJ
fcis-12803	46	22	generalization	generalization	NOUN
fcis-12803	46	23	ability	ability	NOUN
fcis-12803	46	24	of	of	ADP
fcis-12803	46	25	neural	neural	ADJ
fcis-12803	46	26	networks	network	NOUN
fcis-12803	46	27	.	.	PUNCT
fcis-12803	47	1	the	the	DET
fcis-12803	47	2	attentional	attentional	ADJ
fcis-12803	47	3	mechanism	mechanism	NOUN
fcis-12803	47	4	simulates	simulate	NOUN
fcis-12803	47	5	that	that	PRON
fcis-12803	47	6	humans	human	NOUN
fcis-12803	47	7	selectively	selectively	ADV
fcis-12803	47	8	focus	focus	VERB
fcis-12803	47	9	on	on	ADP
fcis-12803	47	10	certain	certain	ADJ
fcis-12803	47	11	visible	visible	ADJ
fcis-12803	47	12	information	information	NOUN
fcis-12803	47	13	and	and	CCONJ
fcis-12803	47	14	ignore	ignore	VERB
fcis-12803	47	15	other	other	ADJ
fcis-12803	47	16	information	information	NOUN
fcis-12803	47	17	to	to	PART
fcis-12803	47	18	rationally	rationally	ADV
fcis-12803	47	19	utilize	utilize	VERB
fcis-12803	47	20	limited	limited	ADJ
fcis-12803	47	21	visual	visual	ADJ
fcis-12803	47	22	processing	processing	NOUN
fcis-12803	47	23	resources	resource	NOUN
fcis-12803	47	24	.	.	PUNCT
fcis-12803	48	1	at	at	ADP
fcis-12803	48	2	the	the	DET
fcis-12803	48	3	same	same	ADJ
fcis-12803	48	4	time	time	NOUN
fcis-12803	48	5	,	,	PUNCT
fcis-12803	48	6	it	it	PRON
fcis-12803	48	7	also	also	ADV
fcis-12803	48	8	helps	help	VERB
fcis-12803	48	9	to	to	PART
fcis-12803	48	10	solve	solve	VERB
fcis-12803	48	11	the	the	DET
fcis-12803	48	12	problem	problem	NOUN
fcis-12803	48	13	of	of	ADP
fcis-12803	48	14	the	the	DET
fcis-12803	48	15	existence	existence	NOUN
fcis-12803	48	16	of	of	ADP
fcis-12803	48	17	a	a	DET
fcis-12803	48	18	large	large	ADJ
fcis-12803	48	19	amount	amount	NOUN
fcis-12803	48	20	of	of	ADP
fcis-12803	48	21	redundant	redundant	ADJ
fcis-12803	48	22	information	information	NOUN
fcis-12803	48	23	in	in	ADP
fcis-12803	48	24	the	the	DET
fcis-12803	48	25	image	image	NOUN
fcis-12803	48	26	or	or	CCONJ
fcis-12803	48	27	video	video	NOUN
fcis-12803	48	28	,	,	PUNCT
fcis-12803	48	29	thus	thus	ADV
fcis-12803	48	30	improving	improve	VERB
fcis-12803	48	31	the	the	DET
fcis-12803	48	32	neural	neural	ADJ
fcis-12803	48	33	network	network	NOUN
fcis-12803	48	34	expressive	expressive	ADJ
fcis-12803	48	35	ability	ability	NOUN
fcis-12803	48	36	and	and	CCONJ
fcis-12803	48	37	generalization	generalization	NOUN
fcis-12803	48	38	ability.[12	ability.[12	PROPN
fcis-12803	48	39	]	]	PUNCT
fcis-12803	48	40	in	in	ADP
fcis-12803	48	41	order	order	NOUN
fcis-12803	48	42	to	to	PART
fcis-12803	48	43	better	well	ADV
fcis-12803	48	44	balance	balance	VERB
fcis-12803	48	45	the	the	DET
fcis-12803	48	46	model	model	NOUN
fcis-12803	48	47	's	's	PART
fcis-12803	48	48	lightweight	lightweight	ADJ
fcis-12803	48	49	and	and	CCONJ
fcis-12803	48	50	detection	detection	NOUN
fcis-12803	48	51	accuracy	accuracy	NOUN
fcis-12803	48	52	,	,	PUNCT
fcis-12803	48	53	this	this	DET
fcis-12803	48	54	paper	paper	NOUN
fcis-12803	48	55	proposes	propose	VERB
fcis-12803	48	56	to	to	PART
fcis-12803	48	57	add	add	VERB
fcis-12803	48	58	the	the	DET
fcis-12803	48	59	gam	gam	NOUN
fcis-12803	48	60	(	(	PUNCT
fcis-12803	48	61	global	global	ADJ
fcis-12803	48	62	attention	attention	NOUN
fcis-12803	48	63	mechanism	mechanism	NOUN
fcis-12803	48	64	)	)	PUNCT
fcis-12803	48	65	attention	attention	NOUN
fcis-12803	48	66	mechanism	mechanism	NOUN
fcis-12803	48	67	to	to	ADP
fcis-12803	48	68	the	the	DET
fcis-12803	48	69	yolov7.gam	yolov7.gam	PROPN
fcis-12803	48	70	redesigns	redesign	NOUN
fcis-12803	48	71	the	the	DET
fcis-12803	48	72	sub	sub	NOUN
fcis-12803	48	73	-	-	NOUN
fcis-12803	48	74	module	module	NOUN
fcis-12803	48	75	of	of	ADP
fcis-12803	48	76	cbam	cbam	NOUN
fcis-12803	48	77	,	,	PUNCT
fcis-12803	48	78	as	as	SCONJ
fcis-12803	48	79	shown	show	VERB
fcis-12803	48	80	in	in	ADP
fcis-12803	48	81	figure	figure	NOUN
fcis-12803	48	82	2	2	NUM
fcis-12803	48	83	,	,	PUNCT
fcis-12803	48	84	with	with	ADP
fcis-12803	48	85	two	two	NUM
fcis-12803	48	86	modules	module	NOUN
fcis-12803	48	87	,	,	PUNCT
fcis-12803	48	88	the	the	DET
fcis-12803	48	89	channel	channel	NOUN
fcis-12803	48	90	attention	attention	NOUN
fcis-12803	48	91	mechanism	mechanism	NOUN
fcis-12803	48	92	module	module	NOUN
fcis-12803	48	93	and	and	CCONJ
fcis-12803	48	94	the	the	DET
fcis-12803	48	95	spatial	spatial	ADJ
fcis-12803	48	96	attention	attention	NOUN
fcis-12803	48	97	mechanism	mechanism	NOUN
fcis-12803	48	98	.	.	PUNCT
fcis-12803	49	1	the	the	DET
fcis-12803	49	2	relevant	relevant	ADJ
fcis-12803	49	3	information	information	NOUN
fcis-12803	49	4	is	be	AUX
fcis-12803	49	5	extracted	extract	VERB
fcis-12803	49	6	by	by	ADP
fcis-12803	49	7	selectively	selectively	ADV
fcis-12803	49	8	focusing	focus	VERB
fcis-12803	49	9	on	on	ADP
fcis-12803	49	10	the	the	DET
fcis-12803	49	11	desired	desire	VERB
fcis-12803	49	12	parts	part	NOUN
fcis-12803	49	13	of	of	ADP
fcis-12803	49	14	the	the	DET
fcis-12803	49	15	channel	channel	NOUN
fcis-12803	49	16	and	and	CCONJ
fcis-12803	49	17	space	space	NOUN
fcis-12803	49	18	,	,	PUNCT
fcis-12803	49	19	and	and	CCONJ
fcis-12803	49	20	important	important	ADJ
fcis-12803	49	21	features	feature	NOUN
fcis-12803	49	22	are	be	AUX
fcis-12803	49	23	captured	capture	VERB
fcis-12803	49	24	in	in	ADP
fcis-12803	49	25	the	the	DET
fcis-12803	49	26	3d	3d	PROPN
fcis-12803	49	27	channel	channel	NOUN
fcis-12803	49	28	,	,	PUNCT
fcis-12803	49	29	spatial	spatial	ADJ
fcis-12803	49	30	width	width	NOUN
fcis-12803	49	31	and	and	CCONJ
fcis-12803	49	32	spatial	spatial	ADJ
fcis-12803	49	33	height	height	NOUN
fcis-12803	49	34	to	to	PART
fcis-12803	49	35	improve	improve	VERB
fcis-12803	49	36	the	the	DET
fcis-12803	49	37	recognition	recognition	NOUN
fcis-12803	49	38	accuracy	accuracy	NOUN
fcis-12803	49	39	of	of	ADP
fcis-12803	49	40	the	the	DET
fcis-12803	49	41	model	model	NOUN
fcis-12803	49	42	.	.	PUNCT
fcis-12803	50	1	figure	figure	NOUN
fcis-12803	50	2	2	2	NUM
fcis-12803	50	3	.	.	X
fcis-12803	50	4	gam	gam	NOUN
fcis-12803	50	5	structure	structure	NOUN
fcis-12803	50	6	4	4	NUM
fcis-12803	50	7	.	.	PUNCT
fcis-12803	50	8	experimental	experimental	ADJ
fcis-12803	50	9	design	design	NOUN
fcis-12803	50	10	and	and	CCONJ
fcis-12803	50	11	analysis	analysis	NOUN
fcis-12803	50	12	of	of	ADP
fcis-12803	50	13	results	result	NOUN
fcis-12803	50	14	4.1	4.1	NUM
fcis-12803	50	15	.	.	PUNCT
fcis-12803	51	1	dataset	dataset	VERB
fcis-12803	51	2	the	the	DET
fcis-12803	51	3	visdrone2019	visdrone2019	PROPN
fcis-12803	51	4	dataset	dataset	NOUN
fcis-12803	51	5	was	be	AUX
fcis-12803	51	6	collected	collect	VERB
fcis-12803	51	7	by	by	ADP
fcis-12803	51	8	the	the	DET
fcis-12803	51	9	aiskyeye	aiskyeye	NOUN
fcis-12803	51	10	team	team	NOUN
fcis-12803	51	11	at	at	ADP
fcis-12803	51	12	the	the	DET
fcis-12803	51	13	machine	machine	NOUN
fcis-12803	51	14	learning	learning	NOUN
fcis-12803	51	15	and	and	CCONJ
fcis-12803	51	16	data	datum	NOUN
fcis-12803	51	17	mining	mining	NOUN
fcis-12803	51	18	laboratory	laboratory	NOUN
fcis-12803	51	19	of	of	ADP
fcis-12803	51	20	tianjin	tianjin	PROPN
fcis-12803	51	21	university	university	PROPN
fcis-12803	51	22	.	.	PUNCT
fcis-12803	52	1	the	the	DET
fcis-12803	52	2	benchmark	benchmark	NOUN
fcis-12803	52	3	dataset	dataset	NOUN
fcis-12803	52	4	consists	consist	VERB
fcis-12803	52	5	of	of	ADP
fcis-12803	52	6	288	288	NUM
fcis-12803	52	7	video	video	NOUN
fcis-12803	52	8	clips	clip	NOUN
fcis-12803	52	9	consisting	consist	VERB
fcis-12803	52	10	of	of	ADP
fcis-12803	52	11	261,908	261,908	NUM
fcis-12803	52	12	frames	frame	NOUN
fcis-12803	52	13	and	and	CCONJ
fcis-12803	52	14	10,209	10,209	NUM
fcis-12803	52	15	still	still	ADV
fcis-12803	52	16	images	image	NOUN
fcis-12803	52	17	captured	capture	VERB
fcis-12803	52	18	by	by	ADP
fcis-12803	52	19	a	a	DET
fcis-12803	52	20	variety	variety	NOUN
fcis-12803	52	21	of	of	ADP
fcis-12803	52	22	uav	uav	PROPN
fcis-12803	52	23	cameras	camera	NOUN
fcis-12803	52	24	covering	cover	VERB
fcis-12803	52	25	a	a	DET
fcis-12803	52	26	wide	wide	ADJ
fcis-12803	52	27	range	range	NOUN
fcis-12803	52	28	of	of	ADP
fcis-12803	52	29	locations	location	NOUN
fcis-12803	52	30	,	,	PUNCT
fcis-12803	52	31	environments	environment	NOUN
fcis-12803	52	32	(	(	PUNCT
fcis-12803	52	33	urban	urban	ADJ
fcis-12803	52	34	and	and	CCONJ
fcis-12803	52	35	rural	rural	ADJ
fcis-12803	52	36	)	)	PUNCT
fcis-12803	52	37	,	,	PUNCT
fcis-12803	52	38	objects	object	NOUN
fcis-12803	52	39	(	(	PUNCT
fcis-12803	52	40	pedestrians	pedestrian	NOUN
fcis-12803	52	41	,	,	PUNCT
fcis-12803	52	42	vehicles	vehicle	NOUN
fcis-12803	52	43	,	,	PUNCT
fcis-12803	52	44	bicycles	bicycle	NOUN
fcis-12803	52	45	,	,	PUNCT
fcis-12803	52	46	etc	etc	X
fcis-12803	52	47	.	.	X
fcis-12803	52	48	)	)	PUNCT
fcis-12803	52	49	,	,	PUNCT
fcis-12803	52	50	and	and	CCONJ
fcis-12803	52	51	densities	density	NOUN
fcis-12803	52	52	(	(	PUNCT
fcis-12803	52	53	sparse	sparse	ADJ
fcis-12803	52	54	and	and	CCONJ
fcis-12803	52	55	crowded	crowded	ADJ
fcis-12803	52	56	scenes	scene	NOUN
fcis-12803	52	57	)	)	PUNCT
fcis-12803	52	58	.	.	PUNCT
fcis-12803	53	1	some	some	DET
fcis-12803	53	2	important	important	ADJ
fcis-12803	53	3	attributes	attribute	NOUN
fcis-12803	53	4	,	,	PUNCT
fcis-12803	53	5	including	include	VERB
fcis-12803	53	6	scene	scene	NOUN
fcis-12803	53	7	visibility	visibility	NOUN
fcis-12803	53	8	,	,	PUNCT
fcis-12803	53	9	object	object	VERB
fcis-12803	53	10	class	class	NOUN
fcis-12803	53	11	and	and	CCONJ
fcis-12803	53	12	occlusion	occlusion	NOUN
fcis-12803	53	13	,	,	PUNCT
fcis-12803	53	14	also	also	ADV
fcis-12803	53	15	provide	provide	VERB
fcis-12803	53	16	better	well	ADJ
fcis-12803	53	17	data	datum	NOUN
fcis-12803	53	18	utilization	utilization	NOUN
fcis-12803	53	19	.	.	PUNCT
fcis-12803	54	1	this	this	DET
fcis-12803	54	2	dataset	dataset	NOUN
fcis-12803	54	3	is	be	AUX
fcis-12803	54	4	valuable	valuable	ADJ
fcis-12803	54	5	to	to	PART
fcis-12803	54	6	study	study	VERB
fcis-12803	54	7	for	for	ADP
fcis-12803	54	8	ships	ship	NOUN
fcis-12803	54	9	with	with	ADP
fcis-12803	54	10	small	small	ADJ
fcis-12803	54	11	targets	target	NOUN
fcis-12803	54	12	,	,	PUNCT
fcis-12803	54	13	overlapping	overlap	VERB
fcis-12803	54	14	targets	target	NOUN
fcis-12803	54	15	,	,	PUNCT
fcis-12803	54	16	and	and	CCONJ
fcis-12803	54	17	complex	complex	ADJ
fcis-12803	54	18	backgrounds	background	NOUN
fcis-12803	54	19	as	as	ADP
fcis-12803	54	20	a	a	DET
fcis-12803	54	21	difficulty	difficulty	NOUN
fcis-12803	54	22	,	,	PUNCT
fcis-12803	54	23	resulting	result	VERB
fcis-12803	54	24	in	in	ADP
fcis-12803	54	25	a	a	DET
fcis-12803	54	26	low	low	ADJ
fcis-12803	54	27	map	map	NOUN
fcis-12803	54	28	for	for	ADP
fcis-12803	54	29	detection	detection	NOUN
fcis-12803	54	30	.	.	PUNCT
fcis-12803	55	1	in	in	ADP
fcis-12803	55	2	this	this	DET
fcis-12803	55	3	experiment	experiment	NOUN
fcis-12803	55	4	,	,	PUNCT
fcis-12803	55	5	1,550	1,550	NUM
fcis-12803	55	6	randomly	randomly	ADV
fcis-12803	55	7	selected	select	VERB
fcis-12803	55	8	from	from	ADP
fcis-12803	55	9	the	the	DET
fcis-12803	55	10	dataset	dataset	NOUN
fcis-12803	55	11	and	and	CCONJ
fcis-12803	55	12	464	464	NUM
fcis-12803	55	13	images	image	NOUN
fcis-12803	55	14	were	be	AUX
fcis-12803	55	15	selected	select	VERB
fcis-12803	55	16	to	to	PART
fcis-12803	55	17	form	form	VERB
fcis-12803	55	18	the	the	DET
fcis-12803	55	19	training	training	NOUN
fcis-12803	55	20	and	and	CCONJ
fcis-12803	55	21	validation	validation	NOUN
fcis-12803	55	22	set	set	NOUN
fcis-12803	55	23	for	for	ADP
fcis-12803	55	24	this	this	DET
fcis-12803	55	25	experiment	experiment	NOUN
fcis-12803	55	26	respectively	respectively	ADV
fcis-12803	55	27	.	.	PUNCT
fcis-12803	56	1	4.2	4.2	NUM
fcis-12803	56	2	.	.	PUNCT
fcis-12803	57	1	experimental	experimental	ADJ
fcis-12803	57	2	configuration	configuration	NOUN
fcis-12803	57	3	table	table	NOUN
fcis-12803	57	4	1	1	NUM
fcis-12803	57	5	.	.	PUNCT
fcis-12803	57	6	experimental	experimental	ADJ
fcis-12803	57	7	configuration	configuration	NOUN
fcis-12803	57	8	table	table	NOUN
fcis-12803	57	9	name	name	NOUN
fcis-12803	57	10	version&model	version&model	PROPN
fcis-12803	57	11	cpu	cpu	VERB
fcis-12803	57	12	inter	inter	NOUN
fcis-12803	57	13	i7	i7	PROPN
fcis-12803	57	14	-	-	PUNCT
fcis-12803	57	15	11700	11700	NUM
fcis-12803	57	16	gpu	gpu	NOUN
fcis-12803	57	17	nvidia	nvidia	PROPN
fcis-12803	57	18	rtx	rtx	PROPN
fcis-12803	57	19	a4000	a4000	NUM
fcis-12803	57	20	stystem	stystem	NOUN
fcis-12803	57	21	windows10	windows10	NOUN
fcis-12803	57	22	64	64	NUM
fcis-12803	57	23	-	-	PUNCT
fcis-12803	57	24	bit	bit	NOUN
fcis-12803	57	25	cuda	cuda	PROPN
fcis-12803	57	26	11.7.1	11.7.1	PROPN
fcis-12803	57	27	python	python	PROPN
fcis-12803	57	28	3.8	3.8	NUM
fcis-12803	57	29	pytorch	pytorch	NOUN
fcis-12803	57	30	1.13.1	1.13.1	NUM
fcis-12803	57	31	all	all	DET
fcis-12803	57	32	the	the	DET
fcis-12803	57	33	experiments	experiment	NOUN
fcis-12803	57	34	were	be	AUX
fcis-12803	57	35	conducted	conduct	VERB
fcis-12803	57	36	in	in	ADP
fcis-12803	57	37	the	the	DET
fcis-12803	57	38	same	same	ADJ
fcis-12803	57	39	hardware	hardware	NOUN
fcis-12803	57	40	environment	environment	NOUN
fcis-12803	57	41	,	,	PUNCT
fcis-12803	57	42	and	and	CCONJ
fcis-12803	57	43	the	the	DET
fcis-12803	57	44	relevant	relevant	ADJ
fcis-12803	57	45	environment	environment	NOUN
fcis-12803	57	46	configurations	configuration	NOUN
fcis-12803	57	47	are	be	AUX
fcis-12803	57	48	74	74	NUM
fcis-12803	57	49	shown	show	VERB
fcis-12803	57	50	in	in	ADP
fcis-12803	57	51	table	table	NOUN
fcis-12803	57	52	1	1	NUM
fcis-12803	57	53	.	.	X
fcis-12803	57	54	4.3	4.3	NUM
fcis-12803	57	55	.	.	PUNCT
fcis-12803	58	1	performance	performance	NOUN
fcis-12803	58	2	indicators	indicator	NOUN
fcis-12803	58	3	precision	precision	VERB
fcis-12803	58	4	:	:	PUNCT
fcis-12803	58	5	the	the	DET
fcis-12803	58	6	percentage	percentage	NOUN
fcis-12803	58	7	of	of	ADP
fcis-12803	58	8	samples	sample	NOUN
fcis-12803	58	9	with	with	ADP
fcis-12803	58	10	true	true	ADJ
fcis-12803	58	11	predictions	prediction	NOUN
fcis-12803	58	12	that	that	PRON
fcis-12803	58	13	are	be	AUX
fcis-12803	58	14	correct.tp	correct.tp	X
fcis-12803	58	15	(	(	PUNCT
fcis-12803	58	16	true	true	ADJ
fcis-12803	58	17	positive	positive	ADJ
fcis-12803	58	18	)	)	PUNCT
fcis-12803	58	19	indicates	indicate	VERB
fcis-12803	58	20	the	the	DET
fcis-12803	58	21	number	number	NOUN
fcis-12803	58	22	of	of	ADP
fcis-12803	58	23	samples	sample	NOUN
fcis-12803	58	24	with	with	ADP
fcis-12803	58	25	correct	correct	ADJ
fcis-12803	58	26	predictions	prediction	NOUN
fcis-12803	58	27	.	.	PUNCT
fcis-12803	59	1	fp	fp	INTJ
fcis-12803	59	2	(	(	PUNCT
fcis-12803	59	3	false	false	ADJ
fcis-12803	59	4	positive	positive	ADJ
fcis-12803	59	5	)	)	PUNCT
fcis-12803	59	6	is	be	AUX
fcis-12803	59	7	the	the	DET
fcis-12803	59	8	number	number	NOUN
fcis-12803	59	9	of	of	ADP
fcis-12803	59	10	samples	sample	NOUN
fcis-12803	59	11	with	with	ADP
fcis-12803	59	12	incorrect	incorrect	ADJ
fcis-12803	59	13	predictions	prediction	NOUN
fcis-12803	59	14	.	.	PUNCT
fcis-12803	60	1	this	this	PRON
fcis-12803	60	2	is	be	AUX
fcis-12803	60	3	shown	show	VERB
fcis-12803	60	4	in	in	ADP
fcis-12803	60	5	equation	equation	NOUN
fcis-12803	60	6	(	(	PUNCT
fcis-12803	60	7	1	1	NUM
fcis-12803	60	8	):	):	PUNCT
fcis-12803	60	9	(	(	PUNCT
fcis-12803	60	10	1	1	X
fcis-12803	60	11	)	)	PUNCT
fcis-12803	60	12	recall	recall	NOUN
fcis-12803	60	13	:	:	PUNCT
fcis-12803	60	14	recall	recall	NOUN
fcis-12803	60	15	,	,	PUNCT
fcis-12803	60	16	also	also	ADV
fcis-12803	60	17	known	know	VERB
fcis-12803	60	18	as	as	ADP
fcis-12803	60	19	the	the	DET
fcis-12803	60	20	check	check	NOUN
fcis-12803	60	21	rate	rate	NOUN
fcis-12803	60	22	,	,	PUNCT
fcis-12803	60	23	indicates	indicate	VERB
fcis-12803	60	24	the	the	DET
fcis-12803	60	25	proportion	proportion	NOUN
fcis-12803	60	26	of	of	ADP
fcis-12803	60	27	predicted	predict	VERB
fcis-12803	60	28	true	true	ADJ
fcis-12803	60	29	positive	positive	ADJ
fcis-12803	60	30	samples	sample	NOUN
fcis-12803	60	31	to	to	ADP
fcis-12803	60	32	the	the	DET
fcis-12803	60	33	total	total	ADJ
fcis-12803	60	34	number	number	NOUN
fcis-12803	60	35	of	of	ADP
fcis-12803	60	36	actual	actual	ADJ
fcis-12803	60	37	positive	positive	ADJ
fcis-12803	60	38	samples	sample	NOUN
fcis-12803	60	39	,	,	PUNCT
fcis-12803	60	40	which	which	PRON
fcis-12803	60	41	is	be	AUX
fcis-12803	60	42	used	use	VERB
fcis-12803	60	43	to	to	PART
fcis-12803	60	44	reflect	reflect	VERB
fcis-12803	60	45	the	the	DET
fcis-12803	60	46	leakage	leakage	NOUN
fcis-12803	60	47	situation	situation	NOUN
fcis-12803	60	48	.	.	PUNCT
fcis-12803	61	1	fn	fn	INTJ
fcis-12803	61	2	(	(	PUNCT
fcis-12803	61	3	false	false	ADJ
fcis-12803	61	4	negative	negative	NOUN
fcis-12803	61	5	)	)	PUNCT
fcis-12803	61	6	denotesd	denotesd	VERB
fcis-12803	61	7	the	the	DET
fcis-12803	61	8	number	number	NOUN
fcis-12803	61	9	of	of	ADP
fcis-12803	61	10	sample	sample	NOUN
fcis-12803	61	11	misses	miss	NOUN
fcis-12803	61	12	.	.	PUNCT
fcis-12803	62	1	calculated	calculate	VERB
fcis-12803	62	2	as	as	SCONJ
fcis-12803	62	3	shown	show	VERB
fcis-12803	62	4	in	in	ADP
fcis-12803	62	5	equation	equation	NOUN
fcis-12803	62	6	(	(	PUNCT
fcis-12803	62	7	2	2	NUM
fcis-12803	62	8	):	):	PUNCT
fcis-12803	62	9	(	(	PUNCT
fcis-12803	62	10	2	2	X
fcis-12803	62	11	)	)	PUNCT
fcis-12803	62	12	mean	mean	ADJ
fcis-12803	62	13	average	average	ADJ
fcis-12803	62	14	precision	precision	NOUN
fcis-12803	62	15	(	(	PUNCT
fcis-12803	62	16	map	map	NOUN
fcis-12803	62	17	):	):	PUNCT
fcis-12803	62	18	precision	precision	NOUN
fcis-12803	62	19	and	and	CCONJ
fcis-12803	62	20	recall	recall	NOUN
fcis-12803	62	21	are	be	AUX
fcis-12803	62	22	a	a	DET
fcis-12803	62	23	pair	pair	NOUN
fcis-12803	62	24	of	of	ADP
fcis-12803	62	25	mutually	mutually	ADV
fcis-12803	62	26	constrained	constrain	VERB
fcis-12803	62	27	performance	performance	NOUN
fcis-12803	62	28	indicators	indicator	NOUN
fcis-12803	62	29	,	,	PUNCT
fcis-12803	62	30	which	which	PRON
fcis-12803	62	31	have	have	VERB
fcis-12803	62	32	the	the	DET
fcis-12803	62	33	limitation	limitation	NOUN
fcis-12803	62	34	of	of	ADP
fcis-12803	62	35	single	single	ADJ
fcis-12803	62	36	-	-	PUNCT
fcis-12803	62	37	point	point	NOUN
fcis-12803	62	38	value	value	NOUN
fcis-12803	62	39	and	and	CCONJ
fcis-12803	62	40	can	can	AUX
fcis-12803	62	41	not	not	PART
fcis-12803	62	42	fully	fully	ADV
fcis-12803	62	43	evaluate	evaluate	VERB
fcis-12803	62	44	the	the	DET
fcis-12803	62	45	model	model	NOUN
fcis-12803	62	46	performance	performance	NOUN
fcis-12803	62	47	,	,	PUNCT
fcis-12803	62	48	so	so	ADV
fcis-12803	62	49	map	map	NOUN
fcis-12803	62	50	is	be	AUX
fcis-12803	62	51	introduced	introduce	VERB
fcis-12803	62	52	to	to	PART
fcis-12803	62	53	equalize	equalize	VERB
fcis-12803	62	54	the	the	DET
fcis-12803	62	55	results	result	NOUN
fcis-12803	62	56	of	of	ADP
fcis-12803	62	57	the	the	DET
fcis-12803	62	58	two	two	NUM
fcis-12803	62	59	calculations	calculation	NOUN
fcis-12803	62	60	.	.	PUNCT
fcis-12803	63	1	taking	take	VERB
fcis-12803	63	2	precision	precision	NOUN
fcis-12803	63	3	as	as	ADP
fcis-12803	63	4	the	the	DET
fcis-12803	63	5	vertical	vertical	ADJ
fcis-12803	63	6	coordinate	coordinate	NOUN
fcis-12803	63	7	and	and	CCONJ
fcis-12803	63	8	recall	recall	NOUN
fcis-12803	63	9	as	as	ADP
fcis-12803	63	10	the	the	DET
fcis-12803	63	11	horizontal	horizontal	ADJ
fcis-12803	63	12	coordinate	coordinate	NOUN
fcis-12803	63	13	,	,	PUNCT
fcis-12803	63	14	the	the	DET
fcis-12803	63	15	p	p	NOUN
fcis-12803	63	16	-	-	PUNCT
fcis-12803	63	17	r	r	NOUN
fcis-12803	63	18	curve	curve	NOUN
fcis-12803	63	19	can	can	AUX
fcis-12803	63	20	be	be	AUX
fcis-12803	63	21	obtained	obtain	VERB
fcis-12803	63	22	,	,	PUNCT
fcis-12803	63	23	and	and	CCONJ
fcis-12803	63	24	the	the	DET
fcis-12803	63	25	area	area	NOUN
fcis-12803	63	26	enclosed	enclose	VERB
fcis-12803	63	27	by	by	ADP
fcis-12803	63	28	the	the	DET
fcis-12803	63	29	p	p	PROPN
fcis-12803	63	30	-	-	PUNCT
fcis-12803	63	31	r	r	NOUN
fcis-12803	63	32	curve	curve	NOUN
fcis-12803	63	33	and	and	CCONJ
fcis-12803	63	34	the	the	DET
fcis-12803	63	35	coordinate	coordinate	NOUN
fcis-12803	63	36	axis	axis	NOUN
fcis-12803	63	37	is	be	AUX
fcis-12803	63	38	the	the	DET
fcis-12803	63	39	value	value	NOUN
fcis-12803	63	40	of	of	ADP
fcis-12803	63	41	ap	ap	PROPN
fcis-12803	63	42	,	,	PUNCT
fcis-12803	63	43	and	and	CCONJ
fcis-12803	63	44	map	map	NOUN
fcis-12803	63	45	represents	represent	VERB
fcis-12803	63	46	the	the	DET
fcis-12803	63	47	average	average	ADJ
fcis-12803	63	48	value	value	NOUN
fcis-12803	63	49	of	of	ADP
fcis-12803	63	50	all	all	DET
fcis-12803	63	51	the	the	DET
fcis-12803	63	52	aps	ap	NOUN
fcis-12803	63	53	in	in	ADP
fcis-12803	63	54	the	the	DET
fcis-12803	63	55	whole	whole	ADJ
fcis-12803	63	56	dataset	dataset	NOUN
fcis-12803	63	57	,	,	PUNCT
fcis-12803	63	58	which	which	PRON
fcis-12803	63	59	is	be	AUX
fcis-12803	63	60	calculated	calculate	VERB
fcis-12803	63	61	as	as	SCONJ
fcis-12803	63	62	shown	show	VERB
fcis-12803	63	63	in	in	ADP
fcis-12803	63	64	equation	equation	NOUN
fcis-12803	63	65	.	.	PUNCT
fcis-12803	64	1	(	(	PUNCT
fcis-12803	64	2	3	3	X
fcis-12803	64	3	)	)	PUNCT
fcis-12803	64	4	and	and	CCONJ
fcis-12803	64	5	(	(	PUNCT
fcis-12803	64	6	4	4	NUM
fcis-12803	64	7	)	)	PUNCT
fcis-12803	64	8	.	.	PUNCT
fcis-12803	65	1	(	(	PUNCT
fcis-12803	65	2	3	3	X
fcis-12803	65	3	)	)	PUNCT
fcis-12803	65	4	∑	∑	PUNCT
fcis-12803	65	5	(	(	PUNCT
fcis-12803	65	6	4	4	NUM
fcis-12803	65	7	)	)	PUNCT
fcis-12803	65	8	4.4	4.4	NUM
fcis-12803	65	9	.	.	PUNCT
fcis-12803	66	1	analysis	analysis	NOUN
fcis-12803	66	2	of	of	ADP
fcis-12803	66	3	experimental	experimental	ADJ
fcis-12803	66	4	results	result	NOUN
fcis-12803	66	5	in	in	ADP
fcis-12803	66	6	order	order	NOUN
fcis-12803	66	7	to	to	PART
fcis-12803	66	8	verify	verify	VERB
fcis-12803	66	9	the	the	DET
fcis-12803	66	10	efficiency	efficiency	NOUN
fcis-12803	66	11	and	and	CCONJ
fcis-12803	66	12	adaptability	adaptability	NOUN
fcis-12803	66	13	of	of	ADP
fcis-12803	66	14	the	the	DET
fcis-12803	66	15	improved	improved	ADJ
fcis-12803	66	16	model	model	NOUN
fcis-12803	66	17	,	,	PUNCT
fcis-12803	66	18	this	this	DET
fcis-12803	66	19	paper	paper	NOUN
fcis-12803	66	20	uses	use	VERB
fcis-12803	66	21	the	the	DET
fcis-12803	66	22	original	original	ADJ
fcis-12803	66	23	yolov7	yolov7	NOUN
fcis-12803	66	24	model	model	NOUN
fcis-12803	66	25	to	to	PART
fcis-12803	66	26	train	train	VERB
fcis-12803	66	27	and	and	CCONJ
fcis-12803	66	28	validate	validate	VERB
fcis-12803	66	29	this	this	DET
fcis-12803	66	30	dataset	dataset	NOUN
fcis-12803	66	31	with	with	ADP
fcis-12803	66	32	300	300	NUM
fcis-12803	66	33	iterations	iteration	NOUN
fcis-12803	66	34	.	.	PUNCT
fcis-12803	67	1	a	a	DET
fcis-12803	67	2	total	total	NOUN
fcis-12803	67	3	of	of	ADP
fcis-12803	67	4	five	five	NUM
fcis-12803	67	5	performance	performance	NOUN
fcis-12803	67	6	metrics	metric	NOUN
fcis-12803	67	7	with	with	ADP
fcis-12803	67	8	parameters	parameter	NOUN
fcis-12803	67	9	precision	precision	PROPN
fcis-12803	67	10	,	,	PUNCT
fcis-12803	67	11	recall	recall	PROPN
fcis-12803	67	12	,	,	PUNCT
fcis-12803	67	13	ap	ap	PROPN
fcis-12803	67	14	,	,	PUNCT
fcis-12803	67	15	map	map	NOUN
fcis-12803	67	16	,	,	PUNCT
fcis-12803	67	17	etc	etc	X
fcis-12803	67	18	.	.	X
fcis-12803	67	19	are	be	AUX
fcis-12803	67	20	selected	select	VERB
fcis-12803	67	21	for	for	ADP
fcis-12803	67	22	side	side	NOUN
fcis-12803	67	23	-	-	PUNCT
fcis-12803	67	24	by	by	ADP
fcis-12803	67	25	-	-	PUNCT
fcis-12803	67	26	side	side	NOUN
fcis-12803	67	27	comparison	comparison	NOUN
fcis-12803	67	28	.	.	PUNCT
fcis-12803	68	1	compared	compare	VERB
fcis-12803	68	2	with	with	ADP
fcis-12803	68	3	the	the	DET
fcis-12803	68	4	original	original	ADJ
fcis-12803	68	5	model	model	NOUN
fcis-12803	68	6	,	,	PUNCT
fcis-12803	68	7	the	the	DET
fcis-12803	68	8	improved	improved	ADJ
fcis-12803	68	9	model	model	NOUN
fcis-12803	68	10	has	have	VERB
fcis-12803	68	11	some	some	DET
fcis-12803	68	12	improvement	improvement	NOUN
fcis-12803	68	13	in	in	ADP
fcis-12803	68	14	terms	term	NOUN
fcis-12803	68	15	of	of	ADP
fcis-12803	68	16	recall	recall	NOUN
fcis-12803	68	17	,	,	PUNCT
fcis-12803	68	18	accuracy	accuracy	NOUN
fcis-12803	68	19	and	and	CCONJ
fcis-12803	68	20	precision	precision	NOUN
fcis-12803	68	21	,	,	PUNCT
fcis-12803	68	22	and	and	CCONJ
fcis-12803	68	23	the	the	DET
fcis-12803	68	24	effect	effect	NOUN
fcis-12803	68	25	of	of	ADP
fcis-12803	68	26	improvement	improvement	NOUN
fcis-12803	68	27	is	be	AUX
fcis-12803	68	28	obvious	obvious	ADJ
fcis-12803	68	29	for	for	ADP
fcis-12803	68	30	the	the	DET
fcis-12803	68	31	whole	whole	ADJ
fcis-12803	68	32	category	category	NOUN
fcis-12803	68	33	of	of	ADP
fcis-12803	68	34	the	the	DET
fcis-12803	68	35	dataset	dataset	NOUN
fcis-12803	68	36	,	,	PUNCT
fcis-12803	68	37	and	and	CCONJ
fcis-12803	68	38	the	the	DET
fcis-12803	68	39	comparison	comparison	NOUN
fcis-12803	68	40	of	of	ADP
fcis-12803	68	41	the	the	DET
fcis-12803	68	42	training	training	NOUN
fcis-12803	68	43	results	result	NOUN
fcis-12803	68	44	of	of	ADP
fcis-12803	68	45	the	the	DET
fcis-12803	68	46	improved	improved	ADJ
fcis-12803	68	47	model	model	NOUN
fcis-12803	68	48	and	and	CCONJ
fcis-12803	68	49	the	the	DET
fcis-12803	68	50	traditional	traditional	ADJ
fcis-12803	68	51	model	model	NOUN
fcis-12803	68	52	for	for	ADP
fcis-12803	68	53	each	each	DET
fcis-12803	68	54	category	category	NOUN
fcis-12803	68	55	is	be	AUX
fcis-12803	68	56	shown	show	VERB
fcis-12803	68	57	in	in	ADP
fcis-12803	68	58	tables	table	NOUN
fcis-12803	68	59	2	2	NUM
fcis-12803	68	60	and	and	CCONJ
fcis-12803	68	61	3	3	NUM
fcis-12803	68	62	.	.	NOUN
fcis-12803	68	63	table	table	NOUN
fcis-12803	68	64	2	2	NUM
fcis-12803	68	65	.	.	PUNCT
fcis-12803	68	66	compared	compare	VERB
fcis-12803	68	67	yolov7	yolov7	NOUN
fcis-12803	68	68	and	and	CCONJ
fcis-12803	68	69	yolov7	yolov7	NOUN
fcis-12803	68	70	-	-	PUNCT
fcis-12803	68	71	bifpn	bifpn	ADJ
fcis-12803	68	72	yolov7	yolov7	PROPN
fcis-12803	68	73	-	-	PUNCT
fcis-12803	68	74	ap	ap	PROPN
fcis-12803	68	75	yolov7	yolov7	NOUN
fcis-12803	68	76	-	-	PUNCT
fcis-12803	68	77	bifpn	bifpn	PROPN
fcis-12803	68	78	-	-	PUNCT
fcis-12803	68	79	ap	ap	PROPN
fcis-12803	68	80	pedestrian	pedestrian	NOUN
fcis-12803	68	81	0.571	0.571	NUM
fcis-12803	68	82	0.599	0.599	NUM
fcis-12803	68	83	people	people	NOUN
fcis-12803	68	84	0.494	0.494	NUM
fcis-12803	68	85	0.511	0.511	NUM
fcis-12803	68	86	bicycle	bicycle	NOUN
fcis-12803	68	87	0.185	0.185	NUM
fcis-12803	68	88	0.217	0.217	NUM
fcis-12803	68	89	car	car	NOUN
fcis-12803	68	90	0.812	0.812	NUM
fcis-12803	68	91	0.832	0.832	NUM
fcis-12803	68	92	van	van	PROPN
fcis-12803	68	93	0.358	0.358	NUM
fcis-12803	68	94	0.377	0.377	NUM
fcis-12803	68	95	truck	truck	NOUN
fcis-12803	68	96	0.374	0.374	NUM
fcis-12803	68	97	0.403	0.403	NUM
fcis-12803	68	98	tricycle	tricycle	NOUN
fcis-12803	68	99	0.340	0.340	NUM
fcis-12803	68	100	0.379	0.379	NUM
fcis-12803	68	101	awning	awning	NOUN
fcis-12803	68	102	-	-	PUNCT
fcis-12803	68	103	tricycle	tricycle	NOUN
fcis-12803	68	104	0.166	0.166	NUM
fcis-12803	68	105	0.197	0.197	NUM
fcis-12803	68	106	bus	bus	NOUN
fcis-12803	68	107	0.416	0.416	NUM
fcis-12803	68	108	0.445	0.445	NUM
fcis-12803	68	109	motor	motor	NOUN
fcis-12803	68	110	0.572	0.572	NUM
fcis-12803	68	111	0.604	0.604	NUM
fcis-12803	68	112	table	table	NOUN
fcis-12803	68	113	3	3	NUM
fcis-12803	68	114	.	.	PUNCT
fcis-12803	68	115	compared	compare	VERB
fcis-12803	68	116	yolov7	yolov7	NOUN
fcis-12803	68	117	and	and	CCONJ
fcis-12803	68	118	yolov7	yolov7	NOUN
fcis-12803	68	119	-	-	PUNCT
fcis-12803	68	120	bifpn	bifpn	PROPN
fcis-12803	68	121	class	class	NOUN
fcis-12803	68	122	precision	precision	NOUN
fcis-12803	68	123	(	(	PUNCT
fcis-12803	68	124	%	%	INTJ
fcis-12803	68	125	)	)	PUNCT
fcis-12803	68	126	recall	recall	NOUN
fcis-12803	68	127	(	(	PUNCT
fcis-12803	68	128	%	%	INTJ
fcis-12803	68	129	)	)	PUNCT
fcis-12803	68	130	map@0.5	map@0.5	PROPN
fcis-12803	68	131	(	(	PUNCT
fcis-12803	68	132	%	%	INTJ
fcis-12803	68	133	)	)	PUNCT
fcis-12803	68	134	map@0.5:0.95	map@0.5:0.95	NOUN
fcis-12803	68	135	(	(	PUNCT
fcis-12803	68	136	%	%	INTJ
fcis-12803	68	137	)	)	PUNCT
fcis-12803	68	138	yolov7	yolov7	NOUN
fcis-12803	68	139	0.554	0.554	SYM
fcis-12803	68	140	0.441	0.441	NUM
fcis-12803	68	141	0.429	0.429	NUM
fcis-12803	68	142	0.236	0.236	NUM
fcis-12803	68	143	yolov7bifpn	yolov7bifpn	PROPN
fcis-12803	68	144	0.567	0.567	NUM
fcis-12803	68	145	0.454	0.454	NUM
fcis-12803	68	146	0.456	0.456	NUM
fcis-12803	68	147	0.251	0.251	NUM
fcis-12803	68	148	from	from	ADP
fcis-12803	68	149	the	the	DET
fcis-12803	68	150	experimental	experimental	ADJ
fcis-12803	68	151	results	result	NOUN
fcis-12803	68	152	,	,	PUNCT
fcis-12803	68	153	it	it	PRON
fcis-12803	68	154	is	be	AUX
fcis-12803	68	155	easy	easy	ADJ
fcis-12803	68	156	to	to	PART
fcis-12803	68	157	see	see	VERB
fcis-12803	68	158	that	that	SCONJ
fcis-12803	68	159	the	the	DET
fcis-12803	68	160	improved	improved	ADJ
fcis-12803	68	161	yolov7	yolov7	NOUN
fcis-12803	68	162	has	have	VERB
fcis-12803	68	163	an	an	DET
fcis-12803	68	164	increase	increase	NOUN
fcis-12803	68	165	of	of	ADP
fcis-12803	68	166	about	about	ADV
fcis-12803	68	167	3	3	NUM
fcis-12803	68	168	%	%	NOUN
fcis-12803	68	169	in	in	ADP
fcis-12803	68	170	the	the	DET
fcis-12803	68	171	target	target	NOUN
fcis-12803	68	172	ap	ap	NOUN
fcis-12803	68	173	value	value	NOUN
fcis-12803	68	174	of	of	ADP
fcis-12803	68	175	each	each	DET
fcis-12803	68	176	category	category	NOUN
fcis-12803	68	177	,	,	PUNCT
fcis-12803	68	178	and	and	CCONJ
fcis-12803	68	179	the	the	DET
fcis-12803	68	180	map@0.5	map@0.5	NOUN
fcis-12803	68	181	is	be	AUX
fcis-12803	68	182	also	also	ADV
fcis-12803	68	183	improved	improve	VERB
fcis-12803	68	184	by	by	ADP
fcis-12803	68	185	2.7	2.7	NUM
fcis-12803	68	186	%	%	NOUN
fcis-12803	68	187	.	.	PUNCT
fcis-12803	68	188	.	.	PUNCT
fcis-12803	69	1	figure	figure	VERB
fcis-12803	69	2	3	3	NUM
fcis-12803	69	3	.	.	PUNCT
fcis-12803	70	1	the	the	DET
fcis-12803	70	2	experimental	experimental	ADJ
fcis-12803	70	3	process	process	NOUN
fcis-12803	70	4	of	of	ADP
fcis-12803	70	5	yolov7	yolov7	NOUN
fcis-12803	70	6	figure	figure	VERB
fcis-12803	70	7	4	4	NUM
fcis-12803	70	8	.	.	PUNCT
fcis-12803	71	1	the	the	DET
fcis-12803	71	2	experimental	experimental	ADJ
fcis-12803	71	3	process	process	NOUN
fcis-12803	71	4	of	of	ADP
fcis-12803	71	5	yolov7	yolov7	NOUN
fcis-12803	71	6	-	-	PUNCT
fcis-12803	71	7	bifpn	bifpn	ADJ
fcis-12803	71	8	comparison	comparison	NOUN
fcis-12803	71	9	of	of	ADP
fcis-12803	71	10	the	the	DET
fcis-12803	71	11	training	training	NOUN
fcis-12803	71	12	results	result	NOUN
fcis-12803	71	13	figure	figure	VERB
fcis-12803	71	14	3	3	NUM
fcis-12803	71	15	and	and	CCONJ
fcis-12803	71	16	figure	figure	VERB
fcis-12803	71	17	4	4	NUM
fcis-12803	71	18	shows	show	VERB
fcis-12803	71	19	that	that	SCONJ
fcis-12803	71	20	the	the	DET
fcis-12803	71	21	traditional	traditional	ADJ
fcis-12803	71	22	yolov7	yolov7	NOUN
fcis-12803	71	23	model	model	NOUN
fcis-12803	71	24	has	have	VERB
fcis-12803	71	25	the	the	DET
fcis-12803	71	26	problems	problem	NOUN
fcis-12803	71	27	of	of	ADP
fcis-12803	71	28	unstable	unstable	ADJ
fcis-12803	71	29	accuracy	accuracy	NOUN
fcis-12803	71	30	,	,	PUNCT
fcis-12803	71	31	unsatisfactory	unsatisfactory	ADJ
fcis-12803	71	32	recall	recall	NOUN
fcis-12803	71	33	and	and	CCONJ
fcis-12803	71	34	low	low	ADJ
fcis-12803	71	35	map	map	NOUN
fcis-12803	71	36	value	value	NOUN
fcis-12803	71	37	in	in	ADP
fcis-12803	71	38	the	the	DET
fcis-12803	71	39	training	training	NOUN
fcis-12803	71	40	process	process	NOUN
fcis-12803	71	41	.	.	PUNCT
fcis-12803	72	1	the	the	DET
fcis-12803	72	2	improved	improved	ADJ
fcis-12803	72	3	model	model	NOUN
fcis-12803	72	4	is	be	AUX
fcis-12803	72	5	more	more	ADV
fcis-12803	72	6	stable	stable	ADJ
fcis-12803	72	7	in	in	ADP
fcis-12803	72	8	terms	term	NOUN
fcis-12803	72	9	of	of	ADP
fcis-12803	72	10	training	training	NOUN
fcis-12803	72	11	than	than	ADP
fcis-12803	72	12	the	the	DET
fcis-12803	72	13	traditional	traditional	ADJ
fcis-12803	72	14	model	model	NOUN
fcis-12803	72	15	in	in	ADP
fcis-12803	72	16	terms	term	NOUN
fcis-12803	72	17	of	of	ADP
fcis-12803	72	18	accuracy	accuracy	NOUN
fcis-12803	72	19	,	,	PUNCT
fcis-12803	72	20	the	the	DET
fcis-12803	72	21	recall	recall	NOUN
fcis-12803	72	22	curve	curve	NOUN
fcis-12803	72	23	is	be	AUX
fcis-12803	72	24	smoother	smooth	ADJ
fcis-12803	72	25	,	,	PUNCT
fcis-12803	72	26	and	and	CCONJ
fcis-12803	72	27	the	the	DET
fcis-12803	72	28	map	map	NOUN
fcis-12803	72	29	value	value	NOUN
fcis-12803	72	30	is	be	AUX
fcis-12803	72	31	also	also	ADV
fcis-12803	72	32	improved	improve	VERB
fcis-12803	72	33	.	.	PUNCT
fcis-12803	73	1	therefore	therefore	ADV
fcis-12803	73	2	,	,	PUNCT
fcis-12803	73	3	our	our	PRON
fcis-12803	73	4	improved	improved	ADJ
fcis-12803	73	5	yolov7	yolov7	NOUN
fcis-12803	73	6	algorithm	algorithm	NOUN
fcis-12803	73	7	is	be	AUX
fcis-12803	73	8	feasible	feasible	ADJ
fcis-12803	73	9	.	.	PUNCT
fcis-12803	74	1	5	5	X
fcis-12803	74	2	.	.	X
fcis-12803	74	3	conclusion	conclusion	NOUN
fcis-12803	74	4	aiming	aim	VERB
fcis-12803	74	5	at	at	ADP
fcis-12803	74	6	the	the	DET
fcis-12803	74	7	challenges	challenge	NOUN
fcis-12803	74	8	faced	face	VERB
fcis-12803	74	9	by	by	ADP
fcis-12803	74	10	uav	uav	PROPN
fcis-12803	74	11	target	target	NOUN
fcis-12803	74	12	detection	detection	NOUN
fcis-12803	74	13	with	with	ADP
fcis-12803	74	14	yolov7	yolov7	PROPN
fcis-12803	74	15	algorithm	algorithm	PROPN
fcis-12803	74	16	's	's	PART
fcis-12803	74	17	everything	everything	PRON
fcis-12803	74	18	is	be	AUX
fcis-12803	74	19	fine	fine	ADJ
fcis-12803	74	20	except	except	SCONJ
fcis-12803	74	21	for	for	ADP
fcis-12803	74	22	one	one	NUM
fcis-12803	74	23	small	small	ADJ
fcis-12803	74	24	defect	defect	NOUN
fcis-12803	74	25	,	,	PUNCT
fcis-12803	74	26	this	this	DET
fcis-12803	74	27	study	study	NOUN
fcis-12803	74	28	proposes	propose	VERB
fcis-12803	74	29	an	an	DET
fcis-12803	74	30	improved	improved	ADJ
fcis-12803	74	31	algorithm	algorithm	NOUN
fcis-12803	74	32	for	for	ADP
fcis-12803	74	33	uav	uav	PROPN
fcis-12803	74	34	target	target	PROPN
fcis-12803	74	35	detection	detection	NOUN
fcis-12803	74	36	based	base	VERB
fcis-12803	74	37	on	on	ADP
fcis-12803	74	38	yolov7	yolov7	PROPN
fcis-12803	74	39	,	,	PUNCT
fcis-12803	74	40	which	which	PRON
fcis-12803	74	41	improves	improve	VERB
fcis-12803	74	42	the	the	DET
fcis-12803	74	43	75	75	NUM
fcis-12803	74	44	accuracy	accuracy	NOUN
fcis-12803	74	45	of	of	ADP
fcis-12803	74	46	uav	uav	PROPN
fcis-12803	74	47	target	target	NOUN
fcis-12803	74	48	detection	detection	NOUN
fcis-12803	74	49	by	by	ADP
fcis-12803	74	50	introducing	introduce	VERB
fcis-12803	74	51	bifpn	bifpn	PROPN
fcis-12803	74	52	and	and	CCONJ
fcis-12803	74	53	gam	gam	NOUN
fcis-12803	74	54	attention	attention	NOUN
fcis-12803	74	55	mechanism	mechanism	NOUN
fcis-12803	74	56	.	.	PUNCT
fcis-12803	75	1	our	our	PRON
fcis-12803	75	2	algorithm	algorithm	NOUN
fcis-12803	75	3	achieves	achieve	VERB
fcis-12803	75	4	satisfactory	satisfactory	ADJ
fcis-12803	75	5	results	result	NOUN
fcis-12803	75	6	on	on	ADP
fcis-12803	75	7	the	the	DET
fcis-12803	75	8	visdrone2019	visdrone2019	PROPN
fcis-12803	75	9	dataset	dataset	VERB
fcis-12803	75	10	,	,	PUNCT
fcis-12803	75	11	indicating	indicate	VERB
fcis-12803	75	12	its	its	PRON
fcis-12803	75	13	broad	broad	ADJ
fcis-12803	75	14	potential	potential	NOUN
fcis-12803	75	15	for	for	ADP
fcis-12803	75	16	practical	practical	ADJ
fcis-12803	75	17	applications	application	NOUN
fcis-12803	75	18	acknowledgments	acknowledgment	NOUN
fcis-12803	75	19	we	we	PRON
fcis-12803	75	20	would	would	AUX
fcis-12803	75	21	like	like	VERB
fcis-12803	75	22	to	to	PART
fcis-12803	75	23	express	express	VERB
fcis-12803	75	24	our	our	PRON
fcis-12803	75	25	gratitude	gratitude	NOUN
fcis-12803	75	26	to	to	ADP
fcis-12803	75	27	the	the	DET
fcis-12803	75	28	authors	author	NOUN
fcis-12803	75	29	of	of	ADP
fcis-12803	75	30	the	the	DET
fcis-12803	75	31	yolov7	yolov7	NOUN
fcis-12803	75	32	algorithm	algorithm	NOUN
fcis-12803	75	33	and	and	CCONJ
fcis-12803	75	34	the	the	DET
fcis-12803	75	35	benchmark	benchmark	ADJ
fcis-12803	75	36	datasets	dataset	NOUN
fcis-12803	75	37	used	use	VERB
fcis-12803	75	38	in	in	ADP
fcis-12803	75	39	this	this	DET
fcis-12803	75	40	paper	paper	NOUN
fcis-12803	75	41	.	.	PUNCT
fcis-12803	76	1	we	we	PRON
fcis-12803	76	2	would	would	AUX
fcis-12803	76	3	also	also	ADV
fcis-12803	76	4	like	like	VERB
fcis-12803	76	5	to	to	PART
fcis-12803	76	6	thank	thank	VERB
fcis-12803	76	7	our	our	PRON
fcis-12803	76	8	colleagues	colleague	NOUN
fcis-12803	76	9	for	for	ADP
fcis-12803	76	10	their	their	PRON
fcis-12803	76	11	helpful	helpful	ADJ
fcis-12803	76	12	discussions	discussion	NOUN
fcis-12803	76	13	and	and	CCONJ
fcis-12803	76	14	feedback	feedback	NOUN
fcis-12803	76	15	on	on	ADP
fcis-12803	76	16	this	this	DET
fcis-12803	76	17	research	research	NOUN
fcis-12803	76	18	.	.	PUNCT
fcis-12803	77	1	references	reference	NOUN
fcis-12803	77	2	[	[	X
fcis-12803	77	3	1	1	NUM
fcis-12803	77	4	]	]	X
fcis-12803	77	5	a	a	X
fcis-12803	77	6	,	,	PUNCT
fcis-12803	77	7	huiyu	huiyu	NOUN
fcis-12803	77	8	zhou	zhou	PROPN
fcis-12803	77	9	,	,	PUNCT
fcis-12803	77	10	y.	y.	PROPN
fcis-12803	77	11	y.	y.	PROPN
fcis-12803	77	12	b	b	PROPN
fcis-12803	77	13	,	,	PUNCT
fcis-12803	77	14	and	and	CCONJ
fcis-12803	77	15	c.	c.	PROPN
fcis-12803	77	16	s.	s.	PROPN
fcis-12803	77	17	c	c	PROPN
fcis-12803	77	18	.	.	PUNCT
fcis-12803	78	1	"	"	PUNCT
fcis-12803	78	2	object	object	VERB
fcis-12803	78	3	tracking	tracking	NOUN
fcis-12803	78	4	using	use	VERB
fcis-12803	78	5	sift	sift	ADJ
fcis-12803	78	6	features	feature	NOUN
fcis-12803	78	7	and	and	CCONJ
fcis-12803	78	8	mean	mean	ADJ
fcis-12803	78	9	shift	shift	NOUN
fcis-12803	78	10	.	.	PUNCT
fcis-12803	78	11	"	"	PUNCT
fcis-12803	79	1	computer	computer	NOUN
fcis-12803	79	2	vision	vision	NOUN
fcis-12803	79	3	and	and	CCONJ
fcis-12803	79	4	image	image	NOUN
fcis-12803	79	5	understanding	understand	VERB
fcis-12803	79	6	113	113	NUM
fcis-12803	79	7	.	.	PUNCT
fcis-12803	80	1	3(2009):345	3(2009):345	NUM
fcis-12803	80	2	-	-	PUNCT
fcis-12803	80	3	352	352	NUM
fcis-12803	80	4	.	.	PUNCT
fcis-12803	81	1	[	[	X
fcis-12803	81	2	2	2	NUM
fcis-12803	81	3	]	]	PUNCT
fcis-12803	81	4	yang	yang	PROPN
fcis-12803	81	5	jinkun	jinkun	PROPN
fcis-12803	81	6	,	,	PUNCT
fcis-12803	81	7	et	et	PROPN
fcis-12803	81	8	al	al	PROPN
fcis-12803	81	9	.	.	PUNCT
fcis-12803	81	10	"hog	"hog	PUNCT
fcis-12803	81	11	and	and	CCONJ
fcis-12803	81	12	svm	svm	ADJ
fcis-12803	81	13	algorithm	algorithm	NOUN
fcis-12803	81	14	based	base	VERB
fcis-12803	81	15	on	on	ADP
fcis-12803	81	16	vehicle	vehicle	NOUN
fcis-12803	81	17	model	model	NOUN
fcis-12803	81	18	recognition	recognition	PROPN
fcis-12803	81	19	.	.	PUNCT
fcis-12803	81	20	"	"	PUNCT
fcis-12803	82	1	mippr	mippr	NOUN
fcis-12803	82	2	2019	2019	NUM
fcis-12803	82	3	:	:	PUNCT
fcis-12803	82	4	pattern	pattern	NOUN
fcis-12803	82	5	recognition	recognition	NOUN
fcis-12803	82	6	and	and	CCONJ
fcis-12803	82	7	computer	computer	NOUN
fcis-12803	82	8	vision	vision	NOUN
fcis-12803	82	9	11430.(2020	11430.(2020	NUM
fcis-12803	82	10	)	)	PUNCT
fcis-12803	82	11	.	.	PUNCT
fcis-12803	83	1	[	[	X
fcis-12803	83	2	3	3	NUM
fcis-12803	83	3	]	]	X
fcis-12803	83	4	joachims	joachim	NOUN
fcis-12803	83	5	,	,	PUNCT
fcis-12803	83	6	thorsten	thorsten	INTJ
fcis-12803	83	7	.	.	PUNCT
fcis-12803	84	1	"	"	PUNCT
fcis-12803	84	2	making	make	VERB
fcis-12803	84	3	large	large	ADJ
fcis-12803	84	4	-	-	PUNCT
fcis-12803	84	5	scale	scale	NOUN
fcis-12803	84	6	svm	svm	NOUN
fcis-12803	84	7	learning	learn	VERB
fcis-12803	84	8	practical	practical	ADJ
fcis-12803	84	9	.	.	PUNCT
fcis-12803	84	10	"	"	PUNCT
fcis-12803	85	1	technical	technical	ADJ
fcis-12803	85	2	reports	report	NOUN
fcis-12803	85	3	8.3(1998):499	8.3(1998):499	NUM
fcis-12803	85	4	-	-	SYM
fcis-12803	85	5	526	526	NUM
fcis-12803	85	6	.	.	PUNCT
fcis-12803	86	1	[	[	X
fcis-12803	86	2	4	4	NUM
fcis-12803	86	3	]	]	X
fcis-12803	86	4	viola	viola	PROPN
fcis-12803	86	5	,	,	PUNCT
fcis-12803	86	6	paul	paul	PROPN
fcis-12803	86	7	,	,	PUNCT
fcis-12803	86	8	and	and	CCONJ
fcis-12803	86	9	m.	m.	PROPN
fcis-12803	86	10	j.	j.	PROPN
fcis-12803	86	11	jones	jones	PROPN
fcis-12803	86	12	.	.	PUNCT
fcis-12803	87	1	"	"	PUNCT
fcis-12803	87	2	fast	fast	ADJ
fcis-12803	87	3	and	and	CCONJ
fcis-12803	87	4	robust	robust	ADJ
fcis-12803	87	5	classification	classification	NOUN
fcis-12803	87	6	using	use	VERB
fcis-12803	87	7	asymmetric	asymmetric	ADJ
fcis-12803	87	8	adaboost	adaboost	ADV
fcis-12803	87	9	and	and	CCONJ
fcis-12803	87	10	a	a	DET
fcis-12803	87	11	detector	detector	NOUN
fcis-12803	87	12	cascade	cascade	NOUN
fcis-12803	87	13	.	.	PUNCT
fcis-12803	87	14	"	"	PUNCT
fcis-12803	88	1	nips	nip	NOUN
fcis-12803	88	2	2001	2001	NUM
fcis-12803	88	3	.	.	PUNCT
fcis-12803	89	1	[	[	X
fcis-12803	89	2	5	5	NUM
fcis-12803	89	3	]	]	X
fcis-12803	89	4	chua	chua	PROPN
fcis-12803	89	5	,	,	PUNCT
fcis-12803	89	6	l.	l.	PROPN
fcis-12803	89	7	o.	o.	PROPN
fcis-12803	89	8	,	,	PUNCT
fcis-12803	89	9	and	and	CCONJ
fcis-12803	89	10	t.	t.	NOUN
fcis-12803	89	11	roska	roska	NOUN
fcis-12803	89	12	.	.	PUNCT
fcis-12803	90	1	"	"	PUNCT
fcis-12803	90	2	the	the	DET
fcis-12803	90	3	cnn	cnn	PROPN
fcis-12803	90	4	paradigm	paradigm	NOUN
fcis-12803	90	5	.	.	PUNCT
fcis-12803	90	6	"	"	PUNCT
fcis-12803	91	1	circuits	circuit	NOUN
fcis-12803	91	2	&	&	CCONJ
fcis-12803	91	3	systems	system	NOUN
fcis-12803	91	4	i	i	PRON
fcis-12803	91	5	fundamental	fundamental	ADJ
fcis-12803	91	6	theory	theory	NOUN
fcis-12803	91	7	&	&	CCONJ
fcis-12803	91	8	applications	application	NOUN
fcis-12803	91	9	ieee	ieee	NOUN
fcis-12803	91	10	transactions	transaction	NOUN
fcis-12803	91	11	on	on	ADP
fcis-12803	91	12	40.3(1993):147	40.3(1993):147	NUM
fcis-12803	91	13	-	-	SYM
fcis-12803	91	14	156	156	NUM
fcis-12803	91	15	.	.	PUNCT
fcis-12803	92	1	[	[	X
fcis-12803	92	2	6	6	NUM
fcis-12803	92	3	]	]	PUNCT
fcis-12803	92	4	r.	r.	PROPN
fcis-12803	92	5	girshick	girshick	PROPN
fcis-12803	92	6	,	,	PUNCT
fcis-12803	92	7	"	"	PUNCT
fcis-12803	92	8	fast	fast	ADJ
fcis-12803	92	9	r	r	NOUN
fcis-12803	92	10	-	-	PUNCT
fcis-12803	92	11	cnn	cnn	PROPN
fcis-12803	92	12	,	,	PUNCT
fcis-12803	92	13	"	"	PUNCT
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fcis-12803	92	16	the	the	DET
fcis-12803	92	17	ieee	ieee	NOUN
fcis-12803	92	18	international	international	PROPN
fcis-12803	92	19	conference	conference	NOUN
fcis-12803	92	20	on	on	ADP
fcis-12803	92	21	computer	computer	NOUN
fcis-12803	92	22	vision	vision	NOUN
fcis-12803	92	23	,	,	PUNCT
fcis-12803	92	24	vol	vol	NOUN
fcis-12803	92	25	.	.	PROPN
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fcis-12803	92	27	,	,	PUNCT
fcis-12803	92	28	pp	pp	ADJ
fcis-12803	92	29	.	.	PUNCT
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fcis-12803	92	31	,	,	PUNCT
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fcis-12803	92	33	.	.	PUNCT
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fcis-12803	94	26	,	,	PUNCT
fcis-12803	94	27	"	"	PUNCT
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fcis-12803	94	29	in	in	ADP
fcis-12803	94	30	neural	neural	ADJ
fcis-12803	94	31	information	information	NOUN
fcis-12803	94	32	processing	processing	NOUN
fcis-12803	94	33	systems	system	NOUN
fcis-12803	94	34	,	,	PUNCT
fcis-12803	94	35	vol	vol	NOUN
fcis-12803	94	36	.	.	PROPN
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fcis-12803	94	38	,	,	PUNCT
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fcis-12803	94	40	.	.	PUNCT
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fcis-12803	95	3	]	]	PUNCT
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fcis-12803	96	13	"	"	PUNCT
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fcis-12803	96	19	"	"	PUNCT
fcis-12803	96	20	proceedings	proceeding	NOUN
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fcis-12803	96	22	the	the	DET
fcis-12803	96	23	ieee	ieee	NOUN
fcis-12803	96	24	international	international	PROPN
fcis-12803	96	25	conference	conference	NOUN
fcis-12803	96	26	on	on	ADP
fcis-12803	96	27	computer	computer	NOUN
fcis-12803	96	28	vision	vision	NOUN
fcis-12803	96	29	.	.	PUNCT
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fcis-12803	98	2	,	,	PUNCT
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fcis-12803	98	4	.	.	PUNCT
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fcis-12803	99	2	-	-	SYM
fcis-12803	99	3	2969	2969	NUM
fcis-12803	99	4	,	,	PUNCT
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fcis-12803	100	2	9	9	NUM
fcis-12803	100	3	]	]	X
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fcis-12803	100	5	,	,	PUNCT
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fcis-12803	100	11	.	.	PUNCT
fcis-12803	101	1	"	"	PUNCT
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fcis-12803	101	4	an	an	DET
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fcis-12803	101	7	.	.	PUNCT
fcis-12803	101	8	"	"	PUNCT
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fcis-12803	102	2	e	e	PROPN
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fcis-12803	102	5	(	(	PUNCT
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fcis-12803	103	3	]	]	X
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fcis-12803	103	8	,	,	PUNCT
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fcis-12803	103	11	.	.	PUNCT
fcis-12803	104	1	"	"	PUNCT
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fcis-12803	104	4	and	and	CCONJ
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fcis-12803	104	7	surface	surface	NOUN
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fcis-12803	104	10	in	in	ADP
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fcis-12803	104	14	strips	strip	NOUN
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fcis-12803	104	19	"	"	PUNCT
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fcis-12803	105	4	)	)	PUNCT
fcis-12803	105	5	.	.	PUNCT
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fcis-12803	106	5	,	,	PUNCT
fcis-12803	106	6	lehai	lehai	PROPN
fcis-12803	106	7	,	,	PUNCT
fcis-12803	106	8	et	et	PROPN
fcis-12803	106	9	al	al	PROPN
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fcis-12803	106	11	"	"	PUNCT
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fcis-12803	106	13	between	between	ADP
fcis-12803	106	14	cascade	cascade	NOUN
fcis-12803	106	15	regionbased	regionbase	VERB
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fcis-12803	106	17	neural	neural	ADJ
fcis-12803	106	18	network	network	NOUN
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fcis-12803	106	21	-	-	ADJ
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fcis-12803	106	24	pyramid	pyramid	NOUN
fcis-12803	106	25	network	network	NOUN
fcis-12803	106	26	for	for	ADP
fcis-12803	106	27	live	live	ADJ
fcis-12803	106	28	object	object	NOUN
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fcis-12803	106	30	and	and	CCONJ
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fcis-12803	106	32	.	.	PUNCT
fcis-12803	106	33	"	"	PUNCT
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fcis-12803	107	2	du	du	PROPN
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fcis-12803	107	4	:	:	PUNCT
fcis-12803	107	5	signal	signal	ADJ
fcis-12803	107	6	image	image	NOUN
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fcis-12803	107	10	)	)	PUNCT
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fcis-12803	108	3	]	]	PUNCT
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fcis-12803	109	1	"	"	PUNCT
fcis-12803	109	2	a	a	DET
fcis-12803	109	3	feature	feature	NOUN
fcis-12803	109	4	-	-	PUNCT
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fcis-12803	109	6	theory	theory	NOUN
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fcis-12803	109	9	.	.	PUNCT
fcis-12803	110	1	"	"	PUNCT
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fcis-12803	110	3	psychology	psychology	NOUN
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fcis-12803	111	2	-	-	SYM
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