id	sid	tid	token	lemma	pos
fcis-28514	1	1	frontiers	frontier	NOUN
fcis-28514	1	2	in	in	ADP
fcis-28514	1	3	computing	computing	NOUN
fcis-28514	1	4	and	and	CCONJ
fcis-28514	1	5	intelligent	intelligent	ADJ
fcis-28514	1	6	systems	system	NOUN
fcis-28514	1	7	issn	issn	VERB
fcis-28514	1	8	:	:	PUNCT
fcis-28514	1	9	2832	2832	NUM
fcis-28514	1	10	-	-	SYM
fcis-28514	1	11	6024	6024	NUM
fcis-28514	1	12	|	|	NOUN
fcis-28514	1	13	vol	vol	NOUN
fcis-28514	1	14	.	.	PROPN
fcis-28514	2	1	10	10	NUM
fcis-28514	2	2	,	,	PUNCT
fcis-28514	2	3	no	no	INTJ
fcis-28514	2	4	.	.	NOUN
fcis-28514	2	5	3	3	NUM
fcis-28514	2	6	,	,	PUNCT
fcis-28514	2	7	2024	2024	NUM
fcis-28514	2	8	79	79	NUM
fcis-28514	2	9	detection	detection	NOUN
fcis-28514	2	10	of	of	ADP
fcis-28514	2	11	small	small	ADJ
fcis-28514	2	12	object	object	NOUN
fcis-28514	2	13	based	base	VERB
fcis-28514	2	14	on	on	ADP
fcis-28514	2	15	improved‐yolov8	improved‐yolov8	PROPN
fcis-28514	2	16	yingying	yingye	VERB
fcis-28514	2	17	tan	tan	PROPN
fcis-28514	2	18	*	*	PROPN
fcis-28514	2	19	,	,	PUNCT
fcis-28514	2	20	jinpeng	jinpeng	PROPN
fcis-28514	2	21	song	song	PROPN
fcis-28514	2	22	,	,	PUNCT
fcis-28514	2	23	chen	chen	PROPN
fcis-28514	2	24	chu	chu	PROPN
fcis-28514	2	25	department	department	PROPN
fcis-28514	2	26	of	of	ADP
fcis-28514	2	27	computer	computer	NOUN
fcis-28514	2	28	,	,	PUNCT
fcis-28514	2	29	north	north	PROPN
fcis-28514	2	30	china	china	PROPN
fcis-28514	2	31	electric	electric	PROPN
fcis-28514	2	32	power	power	PROPN
fcis-28514	2	33	university	university	PROPN
fcis-28514	2	34	,	,	PUNCT
fcis-28514	2	35	baoding	baoding	PROPN
fcis-28514	2	36	,	,	PUNCT
fcis-28514	2	37	hebei	hebei	PROPN
fcis-28514	2	38	,	,	PUNCT
fcis-28514	2	39	china	china	PROPN
fcis-28514	2	40	*	*	PUNCT
fcis-28514	2	41	corresponding	correspond	VERB
fcis-28514	2	42	author	author	NOUN
fcis-28514	2	43	:	:	PUNCT
fcis-28514	2	44	yingying	yingying	PROPN
fcis-28514	2	45	tan	tan	PROPN
fcis-28514	2	46	(	(	PUNCT
fcis-28514	2	47	email	email	NOUN
fcis-28514	2	48	:	:	PUNCT
fcis-28514	2	49	15073395727@163.com	15073395727@163.com	NUM
fcis-28514	2	50	)	)	PUNCT
fcis-28514	2	51	abstract	abstract	NOUN
fcis-28514	2	52	:	:	PUNCT
fcis-28514	2	53	an	an	DET
fcis-28514	2	54	improved	improved	ADJ
fcis-28514	2	55	yolov8	yolov8	NOUN
fcis-28514	2	56	model	model	NOUN
fcis-28514	2	57	is	be	AUX
fcis-28514	2	58	proposed	propose	VERB
fcis-28514	2	59	to	to	PART
fcis-28514	2	60	address	address	VERB
fcis-28514	2	61	the	the	DET
fcis-28514	2	62	issue	issue	NOUN
fcis-28514	2	63	of	of	ADP
fcis-28514	2	64	poor	poor	ADJ
fcis-28514	2	65	recognition	recognition	NOUN
fcis-28514	2	66	performance	performance	NOUN
fcis-28514	2	67	caused	cause	VERB
fcis-28514	2	68	by	by	ADP
fcis-28514	2	69	their	their	PRON
fcis-28514	2	70	low	low	ADJ
fcis-28514	2	71	resolution	resolution	NOUN
fcis-28514	2	72	and	and	CCONJ
fcis-28514	2	73	weak	weak	ADJ
fcis-28514	2	74	feature	feature	NOUN
fcis-28514	2	75	representation	representation	NOUN
fcis-28514	2	76	in	in	ADP
fcis-28514	2	77	small	small	ADJ
fcis-28514	2	78	object	object	NOUN
fcis-28514	2	79	detection	detection	NOUN
fcis-28514	2	80	task	task	NOUN
fcis-28514	2	81	.	.	PUNCT
fcis-28514	3	1	firstly	firstly	ADV
fcis-28514	3	2	,	,	PUNCT
fcis-28514	3	3	to	to	PART
fcis-28514	3	4	extract	extract	VERB
fcis-28514	3	5	a	a	DET
fcis-28514	3	6	richer	rich	ADJ
fcis-28514	3	7	set	set	NOUN
fcis-28514	3	8	of	of	ADP
fcis-28514	3	9	low	low	ADJ
fcis-28514	3	10	-	-	PUNCT
fcis-28514	3	11	level	level	NOUN
fcis-28514	3	12	features	feature	NOUN
fcis-28514	3	13	from	from	ADP
fcis-28514	3	14	images	image	NOUN
fcis-28514	3	15	,	,	PUNCT
fcis-28514	3	16	a	a	DET
fcis-28514	3	17	wt_conv	wt_conv	NOUN
fcis-28514	3	18	module	module	NOUN
fcis-28514	3	19	is	be	AUX
fcis-28514	3	20	designed	design	VERB
fcis-28514	3	21	to	to	PART
fcis-28514	3	22	fuse	fuse	VERB
fcis-28514	3	23	the	the	DET
fcis-28514	3	24	feature	feature	NOUN
fcis-28514	3	25	components	component	NOUN
fcis-28514	3	26	extracted	extract	VERB
fcis-28514	3	27	by	by	ADP
fcis-28514	3	28	wt	wt	PROPN
fcis-28514	3	29	(	(	PUNCT
fcis-28514	3	30	wavelet	wavelet	NOUN
fcis-28514	3	31	transform	transform	NOUN
fcis-28514	3	32	)	)	PUNCT
fcis-28514	3	33	with	with	ADP
fcis-28514	3	34	those	those	PRON
fcis-28514	3	35	extracted	extract	VERB
fcis-28514	3	36	by	by	ADP
fcis-28514	3	37	convolutional	convolutional	ADJ
fcis-28514	3	38	layer	layer	NOUN
fcis-28514	3	39	.	.	PUNCT
fcis-28514	4	1	secondly	secondly	ADV
fcis-28514	4	2	,	,	PUNCT
fcis-28514	4	3	based	base	VERB
fcis-28514	4	4	on	on	ADP
fcis-28514	4	5	the	the	DET
fcis-28514	4	6	idea	idea	NOUN
fcis-28514	4	7	that	that	PRON
fcis-28514	4	8	shallow	shallow	ADJ
fcis-28514	4	9	and	and	CCONJ
fcis-28514	4	10	deep	deep	ADJ
fcis-28514	4	11	feature	feature	NOUN
fcis-28514	4	12	maps	map	NOUN
fcis-28514	4	13	contain	contain	VERB
fcis-28514	4	14	information	information	NOUN
fcis-28514	4	15	at	at	ADP
fcis-28514	4	16	different	different	ADJ
fcis-28514	4	17	scales	scale	NOUN
fcis-28514	4	18	,	,	PUNCT
fcis-28514	4	19	a	a	DET
fcis-28514	4	20	ms	ms	PROPN
fcis-28514	4	21	(	(	PUNCT
fcis-28514	4	22	multiscale	multiscale	NOUN
fcis-28514	4	23	separation	separation	NOUN
fcis-28514	4	24	)	)	PUNCT
fcis-28514	4	25	module	module	NOUN
fcis-28514	4	26	is	be	AUX
fcis-28514	4	27	designed	design	VERB
fcis-28514	4	28	to	to	PART
fcis-28514	4	29	preserve	preserve	VERB
fcis-28514	4	30	the	the	DET
fcis-28514	4	31	features	feature	NOUN
fcis-28514	4	32	of	of	ADP
fcis-28514	4	33	small	small	ADJ
fcis-28514	4	34	objects	object	NOUN
fcis-28514	4	35	separated	separate	VERB
fcis-28514	4	36	from	from	ADP
fcis-28514	4	37	shallow	shallow	ADJ
fcis-28514	4	38	layer	layer	NOUN
fcis-28514	4	39	and	and	CCONJ
fcis-28514	4	40	transfer	transfer	VERB
fcis-28514	4	41	the	the	DET
fcis-28514	4	42	salient	salient	NOUN
fcis-28514	4	43	features	feature	NOUN
fcis-28514	4	44	of	of	ADP
fcis-28514	4	45	large	large	ADJ
fcis-28514	4	46	objects	object	NOUN
fcis-28514	4	47	to	to	ADP
fcis-28514	4	48	the	the	DET
fcis-28514	4	49	deeper	deep	ADJ
fcis-28514	4	50	layers	layer	NOUN
fcis-28514	4	51	,	,	PUNCT
fcis-28514	4	52	effectively	effectively	ADV
fcis-28514	4	53	solving	solve	VERB
fcis-28514	4	54	the	the	DET
fcis-28514	4	55	problem	problem	NOUN
fcis-28514	4	56	of	of	ADP
fcis-28514	4	57	inconsistent	inconsistent	ADJ
fcis-28514	4	58	feature	feature	NOUN
fcis-28514	4	59	expression	expression	NOUN
fcis-28514	4	60	caused	cause	VERB
fcis-28514	4	61	by	by	ADP
fcis-28514	4	62	the	the	DET
fcis-28514	4	63	direct	direct	ADJ
fcis-28514	4	64	fusion	fusion	NOUN
fcis-28514	4	65	of	of	ADP
fcis-28514	4	66	shallow	shallow	ADJ
fcis-28514	4	67	and	and	CCONJ
fcis-28514	4	68	deep	deep	ADJ
fcis-28514	4	69	feature	feature	NOUN
fcis-28514	4	70	maps	map	NOUN
fcis-28514	4	71	.	.	PUNCT
fcis-28514	5	1	finally	finally	ADV
fcis-28514	5	2	,	,	PUNCT
fcis-28514	5	3	we	we	PRON
fcis-28514	5	4	introduce	introduce	VERB
fcis-28514	5	5	the	the	DET
fcis-28514	5	6	de	de	X
fcis-28514	5	7	(	(	PUNCT
fcis-28514	5	8	detail	detail	NOUN
fcis-28514	5	9	enhancement	enhancement	NOUN
fcis-28514	5	10	)	)	PUNCT
fcis-28514	5	11	module	module	NOUN
fcis-28514	5	12	capable	capable	ADJ
fcis-28514	5	13	of	of	ADP
fcis-28514	5	14	fusing	fuse	VERB
fcis-28514	5	15	adjacent	adjacent	ADJ
fcis-28514	5	16	feature	feature	NOUN
fcis-28514	5	17	maps	map	NOUN
fcis-28514	5	18	to	to	PART
fcis-28514	5	19	process	process	VERB
fcis-28514	5	20	the	the	DET
fcis-28514	5	21	small	small	ADJ
fcis-28514	5	22	-	-	PUNCT
fcis-28514	5	23	objects	object	NOUN
fcis-28514	5	24	features	feature	NOUN
fcis-28514	5	25	separated	separate	VERB
fcis-28514	5	26	by	by	ADP
fcis-28514	5	27	the	the	DET
fcis-28514	5	28	ms	ms	PROPN
fcis-28514	5	29	module	module	NOUN
fcis-28514	5	30	,	,	PUNCT
fcis-28514	5	31	enhancing	enhance	VERB
fcis-28514	5	32	feature	feature	NOUN
fcis-28514	5	33	representation	representation	NOUN
fcis-28514	5	34	for	for	ADP
fcis-28514	5	35	small	small	ADJ
fcis-28514	5	36	objects	object	NOUN
fcis-28514	5	37	.	.	PUNCT
fcis-28514	6	1	experiment	experiment	NOUN
fcis-28514	6	2	results	result	NOUN
fcis-28514	6	3	on	on	ADP
fcis-28514	6	4	uavod-10	uavod-10	ADJ
fcis-28514	6	5	and	and	CCONJ
fcis-28514	6	6	small	small	ADJ
fcis-28514	6	7	object	object	NOUN
fcis-28514	6	8	datasets	dataset	NOUN
fcis-28514	6	9	show	show	VERB
fcis-28514	6	10	that	that	SCONJ
fcis-28514	6	11	our	our	PRON
fcis-28514	6	12	model	model	NOUN
fcis-28514	6	13	achieves	achieve	VERB
fcis-28514	6	14	a	a	DET
fcis-28514	6	15	map	map	NOUN
fcis-28514	6	16	improvement	improvement	NOUN
fcis-28514	6	17	of	of	ADP
fcis-28514	6	18	9.5	9.5	NUM
fcis-28514	6	19	%	%	NOUN
fcis-28514	6	20	and	and	CCONJ
fcis-28514	6	21	2.3	2.3	NUM
fcis-28514	6	22	%	%	NOUN
fcis-28514	6	23	respectively	respectively	ADV
fcis-28514	6	24	over	over	ADP
fcis-28514	6	25	the	the	DET
fcis-28514	6	26	baseline	baseline	NOUN
fcis-28514	6	27	,	,	PUNCT
fcis-28514	6	28	and	and	CCONJ
fcis-28514	6	29	it	it	PRON
fcis-28514	6	30	also	also	ADV
fcis-28514	6	31	shows	show	VERB
fcis-28514	6	32	a	a	DET
fcis-28514	6	33	significant	significant	ADJ
fcis-28514	6	34	advantage	advantage	NOUN
fcis-28514	6	35	over	over	ADP
fcis-28514	6	36	other	other	ADJ
fcis-28514	6	37	comparative	comparative	ADJ
fcis-28514	6	38	models	model	NOUN
fcis-28514	6	39	,	,	PUNCT
fcis-28514	6	40	affirming	affirm	VERB
fcis-28514	6	41	the	the	DET
fcis-28514	6	42	effectiveness	effectiveness	NOUN
fcis-28514	6	43	of	of	ADP
fcis-28514	6	44	the	the	DET
fcis-28514	6	45	proposed	propose	VERB
fcis-28514	6	46	model	model	NOUN
fcis-28514	6	47	for	for	ADP
fcis-28514	6	48	small	small	ADJ
fcis-28514	6	49	object	object	NOUN
fcis-28514	6	50	detection	detection	NOUN
fcis-28514	6	51	tasks	task	NOUN
fcis-28514	6	52	.	.	PUNCT
fcis-28514	7	1	keywords	keyword	NOUN
fcis-28514	7	2	:	:	PUNCT
fcis-28514	7	3	small	small	ADJ
fcis-28514	7	4	object	object	NOUN
fcis-28514	7	5	detection	detection	NOUN
fcis-28514	7	6	;	;	PUNCT
fcis-28514	7	7	yolov8	yolov8	NOUN
fcis-28514	7	8	;	;	PUNCT
fcis-28514	7	9	wavelet	wavelet	NOUN
fcis-28514	7	10	transform	transform	NOUN
fcis-28514	7	11	;	;	PUNCT
fcis-28514	7	12	multiscale	multiscale	ADJ
fcis-28514	7	13	separation	separation	NOUN
fcis-28514	7	14	;	;	PUNCT
fcis-28514	7	15	feature	feature	NOUN
fcis-28514	7	16	fusion	fusion	NOUN
fcis-28514	7	17	.	.	PUNCT
fcis-28514	8	1	1	1	X
fcis-28514	8	2	.	.	X
fcis-28514	8	3	introduction	introduction	NOUN
fcis-28514	8	4	object	object	NOUN
fcis-28514	8	5	detection	detection	NOUN
fcis-28514	8	6	has	have	AUX
fcis-28514	8	7	made	make	VERB
fcis-28514	8	8	remarkable	remarkable	ADJ
fcis-28514	8	9	achievements	achievement	NOUN
fcis-28514	8	10	in	in	ADP
fcis-28514	8	11	many	many	ADJ
fcis-28514	8	12	fields	field	NOUN
fcis-28514	8	13	,	,	PUNCT
fcis-28514	8	14	but	but	CCONJ
fcis-28514	8	15	small	small	ADJ
fcis-28514	8	16	object	object	NOUN
fcis-28514	8	17	detection	detection	NOUN
fcis-28514	8	18	is	be	AUX
fcis-28514	8	19	still	still	ADV
fcis-28514	8	20	a	a	DET
fcis-28514	8	21	very	very	ADV
fcis-28514	8	22	difficult	difficult	ADJ
fcis-28514	8	23	task	task	NOUN
fcis-28514	8	24	.	.	PUNCT
fcis-28514	9	1	in	in	ADP
fcis-28514	9	2	the	the	DET
fcis-28514	9	3	image	image	NOUN
fcis-28514	9	4	,	,	PUNCT
fcis-28514	9	5	small	small	ADJ
fcis-28514	9	6	objects	object	NOUN
fcis-28514	9	7	generally	generally	ADV
fcis-28514	9	8	have	have	VERB
fcis-28514	9	9	small	small	ADJ
fcis-28514	9	10	coverage	coverage	NOUN
fcis-28514	9	11	areas	area	NOUN
fcis-28514	9	12	and	and	CCONJ
fcis-28514	9	13	low	low	ADJ
fcis-28514	9	14	resolution	resolution	NOUN
fcis-28514	9	15	,	,	PUNCT
fcis-28514	9	16	making	make	VERB
fcis-28514	9	17	them	they	PRON
fcis-28514	9	18	easy	easy	ADJ
fcis-28514	9	19	to	to	PART
fcis-28514	9	20	be	be	AUX
fcis-28514	9	21	affected	affect	VERB
fcis-28514	9	22	by	by	ADP
fcis-28514	9	23	environmental	environmental	ADJ
fcis-28514	9	24	factors	factor	NOUN
fcis-28514	9	25	like	like	ADP
fcis-28514	9	26	occlusion	occlusion	NOUN
fcis-28514	9	27	and	and	CCONJ
fcis-28514	9	28	illumination	illumination	NOUN
fcis-28514	9	29	changes	change	NOUN
fcis-28514	9	30	.	.	PUNCT
fcis-28514	10	1	this	this	DET
fcis-28514	10	2	results	result	NOUN
fcis-28514	10	3	in	in	ADP
fcis-28514	10	4	their	their	PRON
fcis-28514	10	5	detection	detection	NOUN
fcis-28514	10	6	performance	performance	NOUN
fcis-28514	10	7	being	be	AUX
fcis-28514	10	8	far	far	ADV
fcis-28514	10	9	worse	bad	ADJ
fcis-28514	10	10	compared	compare	VERB
fcis-28514	10	11	to	to	ADP
fcis-28514	10	12	that	that	PRON
fcis-28514	10	13	of	of	ADP
fcis-28514	10	14	large	large	ADJ
fcis-28514	10	15	and	and	CCONJ
fcis-28514	10	16	medium	medium	ADJ
fcis-28514	10	17	objects	object	NOUN
fcis-28514	10	18	.	.	PUNCT
fcis-28514	11	1	however	however	ADV
fcis-28514	11	2	,	,	PUNCT
fcis-28514	11	3	there	there	PRON
fcis-28514	11	4	is	be	VERB
fcis-28514	11	5	a	a	DET
fcis-28514	11	6	great	great	ADJ
fcis-28514	11	7	demand	demand	NOUN
fcis-28514	11	8	for	for	ADP
fcis-28514	11	9	small	small	ADJ
fcis-28514	11	10	target	target	NOUN
fcis-28514	11	11	detection	detection	NOUN
fcis-28514	11	12	in	in	ADP
fcis-28514	11	13	modern	modern	ADJ
fcis-28514	11	14	society	society	NOUN
fcis-28514	11	15	.	.	PUNCT
fcis-28514	12	1	for	for	ADP
fcis-28514	12	2	example	example	NOUN
fcis-28514	12	3	,	,	PUNCT
fcis-28514	12	4	in	in	ADP
fcis-28514	12	5	the	the	DET
fcis-28514	12	6	industrial	industrial	ADJ
fcis-28514	12	7	field	field	NOUN
fcis-28514	12	8	,	,	PUNCT
fcis-28514	12	9	small	small	ADJ
fcis-28514	12	10	object	object	NOUN
fcis-28514	12	11	detection	detection	NOUN
fcis-28514	12	12	algorithms	algorithm	NOUN
fcis-28514	12	13	are	be	AUX
fcis-28514	12	14	used	use	VERB
fcis-28514	12	15	to	to	PART
fcis-28514	12	16	accurately	accurately	ADV
fcis-28514	12	17	locate	locate	VERB
fcis-28514	12	18	tiny	tiny	ADJ
fcis-28514	12	19	defects	defect	NOUN
fcis-28514	12	20	on	on	ADP
fcis-28514	12	21	material	material	NOUN
fcis-28514	12	22	surfaces	surface	NOUN
fcis-28514	12	23	;	;	PUNCT
fcis-28514	12	24	in	in	ADP
fcis-28514	12	25	agriculture	agriculture	NOUN
fcis-28514	12	26	,	,	PUNCT
fcis-28514	12	27	they	they	PRON
fcis-28514	12	28	are	be	AUX
fcis-28514	12	29	used	use	VERB
fcis-28514	12	30	to	to	PART
fcis-28514	12	31	detect	detect	VERB
fcis-28514	12	32	small	small	ADJ
fcis-28514	12	33	crops	crop	NOUN
fcis-28514	12	34	and	and	CCONJ
fcis-28514	12	35	pests	pest	NOUN
fcis-28514	12	36	in	in	ADP
fcis-28514	12	37	the	the	DET
fcis-28514	12	38	field	field	NOUN
fcis-28514	12	39	for	for	ADP
fcis-28514	12	40	effective	effective	ADJ
fcis-28514	12	41	field	field	NOUN
fcis-28514	12	42	management	management	NOUN
fcis-28514	12	43	;	;	PUNCT
fcis-28514	12	44	in	in	ADP
fcis-28514	12	45	the	the	DET
fcis-28514	12	46	field	field	NOUN
fcis-28514	12	47	of	of	ADP
fcis-28514	12	48	aerial	aerial	ADJ
fcis-28514	12	49	remote	remote	ADJ
fcis-28514	12	50	sensing	sensing	NOUN
fcis-28514	12	51	,	,	PUNCT
fcis-28514	12	52	it	it	PRON
fcis-28514	12	53	is	be	AUX
fcis-28514	12	54	required	require	VERB
fcis-28514	12	55	to	to	PART
fcis-28514	12	56	be	be	AUX
fcis-28514	12	57	able	able	ADJ
fcis-28514	12	58	to	to	PART
fcis-28514	12	59	accurately	accurately	ADV
fcis-28514	12	60	identify	identify	VERB
fcis-28514	12	61	the	the	DET
fcis-28514	12	62	object	object	NOUN
fcis-28514	12	63	with	with	ADP
fcis-28514	12	64	the	the	DET
fcis-28514	12	65	size	size	NOUN
fcis-28514	12	66	of	of	ADP
fcis-28514	12	67	only	only	ADV
fcis-28514	12	68	dozens	dozen	NOUN
fcis-28514	12	69	of	of	ADP
fcis-28514	12	70	pixels	pixel	NOUN
fcis-28514	12	71	from	from	ADP
fcis-28514	12	72	satellite	satellite	NOUN
fcis-28514	12	73	images	image	NOUN
fcis-28514	12	74	.	.	PUNCT
fcis-28514	13	1	therefore	therefore	ADV
fcis-28514	13	2	,	,	PUNCT
fcis-28514	13	3	small	small	ADJ
fcis-28514	13	4	object	object	NOUN
fcis-28514	13	5	detection	detection	NOUN
fcis-28514	13	6	has	have	VERB
fcis-28514	13	7	important	important	ADJ
fcis-28514	13	8	practical	practical	ADJ
fcis-28514	13	9	significance	significance	NOUN
fcis-28514	13	10	.	.	PUNCT
fcis-28514	14	1	in	in	ADP
fcis-28514	14	2	recent	recent	ADJ
fcis-28514	14	3	years	year	NOUN
fcis-28514	14	4	,	,	PUNCT
fcis-28514	14	5	many	many	ADJ
fcis-28514	14	6	new	new	ADJ
fcis-28514	14	7	algorithms	algorithm	NOUN
fcis-28514	14	8	for	for	ADP
fcis-28514	14	9	small	small	ADJ
fcis-28514	14	10	object	object	NOUN
fcis-28514	14	11	recognition	recognition	NOUN
fcis-28514	14	12	have	have	AUX
fcis-28514	14	13	been	be	AUX
fcis-28514	14	14	proposed	propose	VERB
fcis-28514	14	15	.	.	PUNCT
fcis-28514	15	1	for	for	ADP
fcis-28514	15	2	example	example	NOUN
fcis-28514	15	3	,	,	PUNCT
fcis-28514	15	4	in	in	ADP
fcis-28514	15	5	terms	term	NOUN
fcis-28514	15	6	of	of	ADP
fcis-28514	15	7	data	datum	NOUN
fcis-28514	15	8	preprocessing	preprocesse	VERB
fcis-28514	15	9	technology	technology	NOUN
fcis-28514	15	10	,	,	PUNCT
fcis-28514	15	11	data	data	NOUN
fcis-28514	15	12	enhancement	enhancement	NOUN
fcis-28514	15	13	strategies	strategy	NOUN
fcis-28514	15	14	such	such	ADJ
fcis-28514	15	15	as	as	ADP
fcis-28514	15	16	mosaic	mosaic	ADJ
fcis-28514	15	17	[	[	X
fcis-28514	15	18	1	1	NUM
fcis-28514	15	19	]	]	PUNCT
fcis-28514	15	20	and	and	CCONJ
fcis-28514	15	21	copy	copy	NOUN
fcis-28514	15	22	-	-	PUNCT
fcis-28514	15	23	pasting	pasting	NOUN
fcis-28514	15	24	[	[	NOUN
fcis-28514	15	25	2	2	NUM
fcis-28514	15	26	]	]	PUNCT
fcis-28514	15	27	are	be	AUX
fcis-28514	15	28	applied	apply	VERB
fcis-28514	15	29	to	to	PART
fcis-28514	15	30	dataset	dataset	VERB
fcis-28514	15	31	to	to	PART
fcis-28514	15	32	improve	improve	VERB
fcis-28514	15	33	the	the	DET
fcis-28514	15	34	proportion	proportion	NOUN
fcis-28514	15	35	of	of	ADP
fcis-28514	15	36	small	small	ADJ
fcis-28514	15	37	objects	object	NOUN
fcis-28514	15	38	in	in	ADP
fcis-28514	15	39	the	the	DET
fcis-28514	15	40	image	image	NOUN
fcis-28514	15	41	,	,	PUNCT
fcis-28514	15	42	so	so	SCONJ
fcis-28514	15	43	as	as	SCONJ
fcis-28514	15	44	to	to	PART
fcis-28514	15	45	enhance	enhance	VERB
fcis-28514	15	46	the	the	DET
fcis-28514	15	47	learning	learning	NOUN
fcis-28514	15	48	ability	ability	NOUN
fcis-28514	15	49	of	of	ADP
fcis-28514	15	50	the	the	DET
fcis-28514	15	51	algorithm	algorithm	NOUN
fcis-28514	15	52	model	model	NOUN
fcis-28514	15	53	for	for	ADP
fcis-28514	15	54	small	small	ADJ
fcis-28514	15	55	object	object	NOUN
fcis-28514	15	56	features	feature	NOUN
fcis-28514	15	57	.	.	PUNCT
fcis-28514	16	1	in	in	ADP
fcis-28514	16	2	the	the	DET
fcis-28514	16	3	optimization	optimization	NOUN
fcis-28514	16	4	technology	technology	NOUN
fcis-28514	16	5	of	of	ADP
fcis-28514	16	6	neural	neural	ADJ
fcis-28514	16	7	network	network	NOUN
fcis-28514	16	8	structure	structure	NOUN
fcis-28514	16	9	,	,	PUNCT
fcis-28514	16	10	attention	attention	NOUN
fcis-28514	16	11	mechanism	mechanism	NOUN
fcis-28514	16	12	[	[	X
fcis-28514	16	13	3	3	NUM
fcis-28514	16	14	-	-	SYM
fcis-28514	16	15	4	4	NUM
fcis-28514	16	16	]	]	PUNCT
fcis-28514	16	17	is	be	AUX
fcis-28514	16	18	introduced	introduce	VERB
fcis-28514	16	19	into	into	ADP
fcis-28514	16	20	the	the	DET
fcis-28514	16	21	network	network	NOUN
fcis-28514	16	22	to	to	PART
fcis-28514	16	23	enhance	enhance	VERB
fcis-28514	16	24	the	the	DET
fcis-28514	16	25	model	model	NOUN
fcis-28514	16	26	's	's	PART
fcis-28514	16	27	attention	attention	NOUN
fcis-28514	16	28	to	to	ADP
fcis-28514	16	29	local	local	ADJ
fcis-28514	16	30	information	information	NOUN
fcis-28514	16	31	.	.	PUNCT
fcis-28514	17	1	in	in	ADP
fcis-28514	17	2	terms	term	NOUN
fcis-28514	17	3	of	of	ADP
fcis-28514	17	4	positive	positive	ADJ
fcis-28514	17	5	and	and	CCONJ
fcis-28514	17	6	negative	negative	ADJ
fcis-28514	17	7	sample	sample	NOUN
fcis-28514	17	8	matching	matching	NOUN
fcis-28514	17	9	technology	technology	NOUN
fcis-28514	17	10	,	,	PUNCT
fcis-28514	17	11	the	the	DET
fcis-28514	17	12	positive	positive	ADJ
fcis-28514	17	13	sample	sample	NOUN
fcis-28514	17	14	region	region	NOUN
fcis-28514	17	15	is	be	AUX
fcis-28514	17	16	redefined	redefine	VERB
fcis-28514	17	17	by	by	ADP
fcis-28514	17	18	rotating	rotate	VERB
fcis-28514	17	19	the	the	DET
fcis-28514	17	20	box	box	NOUN
fcis-28514	17	21	[	[	X
fcis-28514	17	22	5	5	NUM
fcis-28514	17	23	]	]	PUNCT
fcis-28514	17	24	to	to	PART
fcis-28514	17	25	improve	improve	VERB
fcis-28514	17	26	the	the	DET
fcis-28514	17	27	detection	detection	NOUN
fcis-28514	17	28	accuracy	accuracy	NOUN
fcis-28514	17	29	of	of	ADP
fcis-28514	17	30	dense	dense	ADJ
fcis-28514	17	31	small	small	ADJ
fcis-28514	17	32	objects	object	NOUN
fcis-28514	17	33	.	.	PUNCT
fcis-28514	18	1	in	in	ADP
fcis-28514	18	2	terms	term	NOUN
fcis-28514	18	3	of	of	ADP
fcis-28514	18	4	feature	feature	NOUN
fcis-28514	18	5	fusion	fusion	NOUN
fcis-28514	18	6	,	,	PUNCT
fcis-28514	18	7	there	there	PRON
fcis-28514	18	8	are	be	VERB
fcis-28514	18	9	net	net	ADJ
fcis-28514	18	10	mechanism	mechanism	NOUN
fcis-28514	18	11	[	[	X
fcis-28514	18	12	6	6	NUM
fcis-28514	18	13	]	]	PUNCT
fcis-28514	18	14	for	for	ADP
fcis-28514	18	15	reconfiguring	reconfigure	VERB
fcis-28514	18	16	features	feature	NOUN
fcis-28514	18	17	to	to	PART
fcis-28514	18	18	eliminate	eliminate	VERB
fcis-28514	18	19	scale	scale	NOUN
fcis-28514	18	20	confusion	confusion	NOUN
fcis-28514	18	21	,	,	PUNCT
fcis-28514	18	22	and	and	CCONJ
fcis-28514	18	23	rilfe	rilfe	PROPN
fcis-28514	18	24	module	module	NOUN
fcis-28514	18	25	[	[	X
fcis-28514	18	26	7	7	NUM
fcis-28514	18	27	]	]	PUNCT
fcis-28514	18	28	for	for	ADP
fcis-28514	18	29	fusing	fuse	VERB
fcis-28514	18	30	multiple	multiple	ADJ
fcis-28514	18	31	feature	feature	NOUN
fcis-28514	18	32	maps	map	NOUN
fcis-28514	18	33	to	to	PART
fcis-28514	18	34	enrich	enrich	VERB
fcis-28514	18	35	the	the	DET
fcis-28514	18	36	feature	feature	NOUN
fcis-28514	18	37	information	information	NOUN
fcis-28514	18	38	of	of	ADP
fcis-28514	18	39	small	small	ADJ
fcis-28514	18	40	objects	object	NOUN
fcis-28514	18	41	.	.	PUNCT
fcis-28514	19	1	various	various	ADJ
fcis-28514	19	2	feature	feature	NOUN
fcis-28514	19	3	pyramid	pyramid	NOUN
fcis-28514	19	4	methods	method	NOUN
fcis-28514	19	5	have	have	AUX
fcis-28514	19	6	also	also	ADV
fcis-28514	19	7	been	be	AUX
fcis-28514	19	8	applied	apply	VERB
fcis-28514	19	9	,	,	PUNCT
fcis-28514	19	10	such	such	ADJ
fcis-28514	19	11	as	as	ADP
fcis-28514	19	12	pafpn	pafpn	PROPN
fcis-28514	19	13	[	[	X
fcis-28514	19	14	8	8	NUM
fcis-28514	19	15	]	]	PUNCT
fcis-28514	19	16	,	,	PUNCT
fcis-28514	19	17	bifpn	bifpn	X
fcis-28514	20	1	[	[	X
fcis-28514	20	2	9	9	NUM
fcis-28514	20	3	]	]	PUNCT
fcis-28514	20	4	,	,	PUNCT
fcis-28514	20	5	nas	nas	PROPN
fcis-28514	20	6	-	-	PUNCT
fcis-28514	20	7	fpn	fpn	NOUN
fcis-28514	20	8	[	[	X
fcis-28514	20	9	10	10	NUM
fcis-28514	20	10	]	]	PUNCT
fcis-28514	20	11	,	,	PUNCT
fcis-28514	20	12	etc	etc	X
fcis-28514	20	13	.	.	X
fcis-28514	20	14	the	the	DET
fcis-28514	20	15	common	common	ADJ
fcis-28514	20	16	purpose	purpose	NOUN
fcis-28514	20	17	of	of	ADP
fcis-28514	20	18	these	these	DET
fcis-28514	20	19	feature	feature	NOUN
fcis-28514	20	20	pyramid	pyramid	NOUN
fcis-28514	20	21	methods	method	NOUN
fcis-28514	20	22	is	be	AUX
fcis-28514	20	23	to	to	PART
fcis-28514	20	24	fully	fully	ADV
fcis-28514	20	25	integrate	integrate	VERB
fcis-28514	20	26	the	the	DET
fcis-28514	20	27	feature	feature	NOUN
fcis-28514	20	28	maps	map	NOUN
fcis-28514	20	29	of	of	ADP
fcis-28514	20	30	different	different	ADJ
fcis-28514	20	31	scales	scale	NOUN
fcis-28514	20	32	,	,	PUNCT
fcis-28514	20	33	so	so	SCONJ
fcis-28514	20	34	as	as	SCONJ
fcis-28514	20	35	to	to	PART
fcis-28514	20	36	generate	generate	VERB
fcis-28514	20	37	more	more	ADJ
fcis-28514	20	38	expressive	expressive	ADJ
fcis-28514	20	39	feature	feature	NOUN
fcis-28514	20	40	maps	map	NOUN
fcis-28514	20	41	.	.	PUNCT
fcis-28514	21	1	object	object	NOUN
fcis-28514	21	2	detection	detection	NOUN
fcis-28514	21	3	algorithms	algorithm	NOUN
fcis-28514	21	4	can	can	AUX
fcis-28514	21	5	be	be	AUX
fcis-28514	21	6	classified	classify	VERB
fcis-28514	21	7	into	into	ADP
fcis-28514	21	8	twostage	twostage	NOUN
fcis-28514	21	9	algorithms	algorithm	NOUN
fcis-28514	21	10	and	and	CCONJ
fcis-28514	21	11	one	one	NUM
fcis-28514	21	12	-	-	PUNCT
fcis-28514	21	13	stage	stage	NOUN
fcis-28514	21	14	algorithms	algorithm	NOUN
fcis-28514	21	15	.	.	PUNCT
fcis-28514	22	1	yolo	yolo	PROPN
fcis-28514	23	1	[	[	X
fcis-28514	23	2	11	11	NUM
fcis-28514	23	3	]	]	PUNCT
fcis-28514	23	4	is	be	AUX
fcis-28514	23	5	one	one	NUM
fcis-28514	23	6	of	of	ADP
fcis-28514	23	7	the	the	DET
fcis-28514	23	8	classical	classical	ADJ
fcis-28514	23	9	single	single	ADJ
fcis-28514	23	10	-	-	PUNCT
fcis-28514	23	11	stage	stage	NOUN
fcis-28514	23	12	algorithms	algorithm	NOUN
fcis-28514	23	13	.	.	PUNCT
fcis-28514	24	1	among	among	ADP
fcis-28514	24	2	them	they	PRON
fcis-28514	24	3	,	,	PUNCT
fcis-28514	24	4	yolov8	yolov8	NOUN
fcis-28514	24	5	model	model	NOUN
fcis-28514	24	6	not	not	PART
fcis-28514	24	7	only	only	ADV
fcis-28514	24	8	has	have	VERB
fcis-28514	24	9	the	the	DET
fcis-28514	24	10	advantage	advantage	NOUN
fcis-28514	24	11	of	of	ADP
fcis-28514	24	12	fast	fast	ADJ
fcis-28514	24	13	detection	detection	NOUN
fcis-28514	24	14	speed	speed	NOUN
fcis-28514	24	15	,	,	PUNCT
fcis-28514	24	16	but	but	CCONJ
fcis-28514	24	17	also	also	ADV
fcis-28514	24	18	has	have	VERB
fcis-28514	24	19	better	well	ADJ
fcis-28514	24	20	detection	detection	NOUN
fcis-28514	24	21	performance	performance	NOUN
fcis-28514	24	22	for	for	ADP
fcis-28514	24	23	large	large	ADJ
fcis-28514	24	24	and	and	CCONJ
fcis-28514	24	25	medium	medium	ADJ
fcis-28514	24	26	-	-	PUNCT
fcis-28514	24	27	sized	sized	ADJ
fcis-28514	24	28	objects	object	NOUN
fcis-28514	24	29	than	than	ADP
fcis-28514	24	30	mainstream	mainstream	VERB
fcis-28514	24	31	two	two	NUM
fcis-28514	24	32	-	-	PUNCT
fcis-28514	24	33	stage	stage	NOUN
fcis-28514	24	34	object	object	NOUN
fcis-28514	24	35	detection	detection	NOUN
fcis-28514	24	36	algorithms	algorithm	NOUN
fcis-28514	24	37	.	.	PUNCT
fcis-28514	25	1	the	the	DET
fcis-28514	25	2	pafpn	pafpn	NOUN
fcis-28514	25	3	structure	structure	NOUN
fcis-28514	25	4	in	in	ADP
fcis-28514	25	5	yolov8	yolov8	NOUN
fcis-28514	25	6	directly	directly	ADV
fcis-28514	25	7	connects	connect	VERB
fcis-28514	25	8	the	the	DET
fcis-28514	25	9	shallow	shallow	ADJ
fcis-28514	25	10	feature	feature	NOUN
fcis-28514	25	11	map	map	NOUN
fcis-28514	25	12	of	of	ADP
fcis-28514	25	13	the	the	DET
fcis-28514	25	14	feature	feature	NOUN
fcis-28514	25	15	extraction	extraction	NOUN
fcis-28514	25	16	network	network	NOUN
fcis-28514	25	17	and	and	CCONJ
fcis-28514	25	18	the	the	DET
fcis-28514	25	19	deep	deep	ADJ
fcis-28514	25	20	feature	feature	NOUN
fcis-28514	25	21	map	map	NOUN
fcis-28514	25	22	of	of	ADP
fcis-28514	25	23	the	the	DET
fcis-28514	25	24	fusion	fusion	NOUN
fcis-28514	25	25	network	network	NOUN
fcis-28514	25	26	horizontally	horizontally	ADV
fcis-28514	25	27	to	to	PART
fcis-28514	25	28	enrich	enrich	VERB
fcis-28514	25	29	the	the	DET
fcis-28514	25	30	details	detail	NOUN
fcis-28514	25	31	of	of	ADP
fcis-28514	25	32	the	the	DET
fcis-28514	25	33	features	feature	NOUN
fcis-28514	25	34	of	of	ADP
fcis-28514	25	35	the	the	DET
fcis-28514	25	36	detection	detection	NOUN
fcis-28514	25	37	layer	layer	NOUN
fcis-28514	25	38	.	.	PUNCT
fcis-28514	26	1	however	however	ADV
fcis-28514	26	2	,	,	PUNCT
fcis-28514	26	3	there	there	PRON
fcis-28514	26	4	is	be	VERB
fcis-28514	26	5	a	a	DET
fcis-28514	26	6	significant	significant	ADJ
fcis-28514	26	7	difference	difference	NOUN
fcis-28514	26	8	in	in	ADP
fcis-28514	26	9	information	information	NOUN
fcis-28514	26	10	between	between	ADP
fcis-28514	26	11	the	the	DET
fcis-28514	26	12	feature	feature	NOUN
fcis-28514	26	13	maps	map	NOUN
fcis-28514	26	14	with	with	ADP
fcis-28514	26	15	large	large	ADJ
fcis-28514	26	16	scale	scale	NOUN
fcis-28514	26	17	variations	variation	NOUN
fcis-28514	26	18	.	.	PUNCT
fcis-28514	27	1	in	in	ADP
fcis-28514	27	2	shallow	shallow	ADJ
fcis-28514	27	3	layers	layer	NOUN
fcis-28514	27	4	,	,	PUNCT
fcis-28514	27	5	feature	feature	NOUN
fcis-28514	27	6	maps	map	NOUN
fcis-28514	27	7	contain	contain	VERB
fcis-28514	27	8	various	various	ADJ
fcis-28514	27	9	scale	scale	NOUN
fcis-28514	27	10	target	target	NOUN
fcis-28514	27	11	information	information	NOUN
fcis-28514	27	12	,	,	PUNCT
fcis-28514	27	13	while	while	SCONJ
fcis-28514	27	14	feature	feature	NOUN
fcis-28514	27	15	maps	map	NOUN
fcis-28514	27	16	loses	lose	VERB
fcis-28514	27	17	a	a	DET
fcis-28514	27	18	lot	lot	NOUN
fcis-28514	27	19	of	of	ADP
fcis-28514	27	20	small	small	ADJ
fcis-28514	27	21	object	object	NOUN
fcis-28514	27	22	feature	feature	NOUN
fcis-28514	27	23	in	in	ADP
fcis-28514	27	24	deep	deep	ADJ
fcis-28514	27	25	layers	layer	NOUN
fcis-28514	27	26	.	.	PUNCT
fcis-28514	28	1	if	if	SCONJ
fcis-28514	28	2	the	the	DET
fcis-28514	28	3	two	two	NUM
fcis-28514	28	4	layers	layer	NOUN
fcis-28514	28	5	are	be	AUX
fcis-28514	28	6	directly	directly	ADV
fcis-28514	28	7	sampled	sample	VERB
fcis-28514	28	8	to	to	ADP
fcis-28514	28	9	the	the	DET
fcis-28514	28	10	same	same	ADJ
fcis-28514	28	11	scale	scale	NOUN
fcis-28514	28	12	and	and	CCONJ
fcis-28514	28	13	then	then	ADV
fcis-28514	28	14	fused	fuse	VERB
fcis-28514	28	15	,	,	PUNCT
fcis-28514	28	16	the	the	DET
fcis-28514	28	17	differences	difference	NOUN
fcis-28514	28	18	will	will	AUX
fcis-28514	28	19	be	be	AUX
fcis-28514	28	20	ignored	ignore	VERB
fcis-28514	28	21	,	,	PUNCT
fcis-28514	28	22	resulting	result	VERB
fcis-28514	28	23	in	in	ADP
fcis-28514	28	24	inconsistent	inconsistent	ADJ
fcis-28514	28	25	representations	representation	NOUN
fcis-28514	28	26	,	,	PUNCT
fcis-28514	28	27	and	and	CCONJ
fcis-28514	28	28	information	information	NOUN
fcis-28514	28	29	of	of	ADP
fcis-28514	28	30	large	large	ADJ
fcis-28514	28	31	objects	object	NOUN
fcis-28514	28	32	will	will	AUX
fcis-28514	28	33	weakening	weaken	VERB
fcis-28514	28	34	the	the	DET
fcis-28514	28	35	small	small	ADJ
fcis-28514	28	36	-	-	PUNCT
fcis-28514	28	37	object	object	NOUN
fcis-28514	28	38	features	feature	NOUN
fcis-28514	28	39	thus	thus	ADV
fcis-28514	28	40	interfere	interfere	VERB
fcis-28514	28	41	the	the	DET
fcis-28514	28	42	detection	detection	NOUN
fcis-28514	28	43	of	of	ADP
fcis-28514	28	44	small	small	ADJ
fcis-28514	28	45	objects	object	NOUN
fcis-28514	28	46	.	.	PUNCT
fcis-28514	29	1	as	as	ADP
fcis-28514	29	2	a	a	DET
fcis-28514	29	3	conventional	conventional	ADJ
fcis-28514	29	4	algorithm	algorithm	NOUN
fcis-28514	29	5	,	,	PUNCT
fcis-28514	29	6	wavelet	wavelet	NOUN
fcis-28514	29	7	transform	transform	NOUN
fcis-28514	29	8	transforms	transform	VERB
fcis-28514	29	9	the	the	DET
fcis-28514	29	10	image	image	NOUN
fcis-28514	29	11	from	from	ADP
fcis-28514	29	12	the	the	DET
fcis-28514	29	13	spatial	spatial	ADJ
fcis-28514	29	14	domain	domain	NOUN
fcis-28514	29	15	to	to	ADP
fcis-28514	29	16	the	the	DET
fcis-28514	29	17	wavelet	wavelet	NOUN
fcis-28514	29	18	domain	domain	NOUN
fcis-28514	29	19	.	.	PUNCT
fcis-28514	30	1	there	there	PRON
fcis-28514	30	2	are	be	VERB
fcis-28514	30	3	many	many	ADJ
fcis-28514	30	4	researches	research	NOUN
fcis-28514	30	5	that	that	PRON
fcis-28514	30	6	combine	combine	VERB
fcis-28514	30	7	wavelet	wavelet	NOUN
fcis-28514	30	8	transform	transform	NOUN
fcis-28514	30	9	and	and	CCONJ
fcis-28514	30	10	convolutional	convolutional	ADJ
fcis-28514	30	11	neural	neural	ADJ
fcis-28514	30	12	network	network	NOUN
fcis-28514	30	13	in	in	ADP
fcis-28514	30	14	image	image	NOUN
fcis-28514	30	15	denoising	denoising	NOUN
fcis-28514	30	16	,	,	PUNCT
fcis-28514	30	17	image	image	NOUN
fcis-28514	30	18	reconstruction	reconstruction	NOUN
fcis-28514	30	19	,	,	PUNCT
fcis-28514	30	20	object	object	VERB
fcis-28514	30	21	detection	detection	NOUN
fcis-28514	30	22	and	and	CCONJ
fcis-28514	30	23	other	other	ADJ
fcis-28514	30	24	tasks	task	NOUN
fcis-28514	30	25	.	.	PUNCT
fcis-28514	31	1	for	for	ADP
fcis-28514	31	2	example	example	NOUN
fcis-28514	31	3	,	,	PUNCT
fcis-28514	31	4	in	in	ADP
fcis-28514	31	5	literature	literature	NOUN
fcis-28514	31	6	[	[	X
fcis-28514	31	7	12	12	NUM
fcis-28514	31	8	]	]	PUNCT
fcis-28514	31	9	,	,	PUNCT
fcis-28514	31	10	wavelet	wavelet	NOUN
fcis-28514	31	11	transform	transform	NOUN
fcis-28514	31	12	is	be	AUX
fcis-28514	31	13	used	use	VERB
fcis-28514	31	14	to	to	PART
fcis-28514	31	15	obtain	obtain	VERB
fcis-28514	31	16	wavelet	wavelet	NOUN
fcis-28514	31	17	residual	residual	ADJ
fcis-28514	31	18	images	image	NOUN
fcis-28514	31	19	to	to	PART
fcis-28514	31	20	guide	guide	VERB
fcis-28514	31	21	network	network	NOUN
fcis-28514	31	22	training	training	NOUN
fcis-28514	31	23	,	,	PUNCT
fcis-28514	31	24	which	which	PRON
fcis-28514	31	25	significantly	significantly	ADV
fcis-28514	31	26	improves	improve	VERB
fcis-28514	31	27	the	the	DET
fcis-28514	31	28	de	de	ADJ
fcis-28514	31	29	-	-	ADJ
fcis-28514	31	30	noising	noising	ADJ
fcis-28514	31	31	effect	effect	NOUN
fcis-28514	31	32	.	.	PUNCT
fcis-28514	32	1	in	in	ADP
fcis-28514	32	2	literature	literature	NOUN
fcis-28514	32	3	[	[	X
fcis-28514	32	4	13	13	NUM
fcis-28514	32	5	]	]	PUNCT
fcis-28514	32	6	,	,	PUNCT
fcis-28514	32	7	the	the	DET
fcis-28514	32	8	neural	neural	ADJ
fcis-28514	32	9	network	network	NOUN
fcis-28514	32	10	reconstructs	reconstruct	VERB
fcis-28514	32	11	highresolution	highresolution	NOUN
fcis-28514	32	12	images	image	NOUN
fcis-28514	32	13	by	by	ADP
fcis-28514	32	14	learning	learn	VERB
fcis-28514	32	15	the	the	DET
fcis-28514	32	16	wavelet	wavelet	NOUN
fcis-28514	32	17	transform	transform	NOUN
fcis-28514	32	18	coefficients	coefficient	NOUN
fcis-28514	32	19	of	of	ADP
fcis-28514	32	20	low	low	ADJ
fcis-28514	32	21	-	-	PUNCT
fcis-28514	32	22	resolution	resolution	NOUN
fcis-28514	32	23	face	face	NOUN
fcis-28514	32	24	images	image	NOUN
fcis-28514	32	25	,	,	PUNCT
fcis-28514	32	26	effectively	effectively	ADV
fcis-28514	32	27	enhancing	enhance	VERB
fcis-28514	32	28	the	the	DET
fcis-28514	32	29	clarity	clarity	NOUN
fcis-28514	32	30	of	of	ADP
fcis-28514	32	31	face	face	NOUN
fcis-28514	32	32	images	image	NOUN
fcis-28514	32	33	.	.	PUNCT
fcis-28514	33	1	[	[	X
fcis-28514	33	2	14	14	NUM
fcis-28514	33	3	]	]	PUNCT
fcis-28514	33	4	enhances	enhance	VERB
fcis-28514	33	5	object	object	NOUN
fcis-28514	33	6	detection	detection	NOUN
fcis-28514	33	7	performance	performance	NOUN
fcis-28514	33	8	by	by	ADP
fcis-28514	33	9	introducing	introduce	VERB
fcis-28514	33	10	a	a	DET
fcis-28514	33	11	haar	haar	NOUN
fcis-28514	33	12	wavelet	wavelet	NOUN
fcis-28514	33	13	-	-	PUNCT
fcis-28514	33	14	based	base	VERB
fcis-28514	33	15	lossless	lossless	NOUN
fcis-28514	33	16	feature	feature	NOUN
fcis-28514	33	17	encoding	encode	VERB
fcis-28514	33	18	block	block	NOUN
fcis-28514	33	19	into	into	ADP
fcis-28514	33	20	the	the	DET
fcis-28514	33	21	downsampling	downsample	VERB
fcis-28514	33	22	operation	operation	NOUN
fcis-28514	33	23	of	of	ADP
fcis-28514	33	24	the	the	DET
fcis-28514	33	25	network	network	NOUN
fcis-28514	33	26	.	.	PUNCT
fcis-28514	34	1	[	[	X
fcis-28514	34	2	15	15	NUM
fcis-28514	34	3	]	]	PUNCT
fcis-28514	34	4	extract	extract	VERB
fcis-28514	34	5	the	the	DET
fcis-28514	34	6	defect	defect	NOUN
fcis-28514	34	7	images	image	NOUN
fcis-28514	34	8	component	component	NOUN
fcis-28514	34	9	by	by	ADP
fcis-28514	34	10	wavelet	wavelet	NOUN
fcis-28514	34	11	transform	transform	NOUN
fcis-28514	34	12	to	to	PART
fcis-28514	34	13	achieve	achieve	VERB
fcis-28514	34	14	better	well	ADJ
fcis-28514	34	15	segmentation	segmentation	NOUN
fcis-28514	34	16	effect	effect	NOUN
fcis-28514	34	17	.	.	PUNCT
fcis-28514	35	1	small	small	ADJ
fcis-28514	35	2	object	object	NOUN
fcis-28514	35	3	image	image	NOUN
fcis-28514	35	4	usually	usually	ADV
fcis-28514	35	5	has	have	VERB
fcis-28514	35	6	the	the	DET
fcis-28514	35	7	problem	problem	NOUN
fcis-28514	35	8	of	of	ADP
fcis-28514	35	9	blurred	blurred	ADJ
fcis-28514	35	10	edge	edge	NOUN
fcis-28514	35	11	and	and	CCONJ
fcis-28514	35	12	low	low	ADJ
fcis-28514	35	13	distinction	distinction	NOUN
fcis-28514	35	14	from	from	ADP
fcis-28514	35	15	foreground	foreground	ADV
fcis-28514	35	16	.	.	PUNCT
fcis-28514	36	1	80	80	NUM
fcis-28514	36	2	a	a	DET
fcis-28514	36	3	richer	rich	ADJ
fcis-28514	36	4	and	and	CCONJ
fcis-28514	36	5	more	more	ADV
fcis-28514	36	6	comprehensive	comprehensive	ADJ
fcis-28514	36	7	feature	feature	NOUN
fcis-28514	36	8	representation	representation	NOUN
fcis-28514	36	9	can	can	AUX
fcis-28514	36	10	be	be	AUX
fcis-28514	36	11	constructed	construct	VERB
fcis-28514	36	12	by	by	ADP
fcis-28514	36	13	combining	combine	VERB
fcis-28514	36	14	the	the	DET
fcis-28514	36	15	edge	edge	NOUN
fcis-28514	36	16	and	and	CCONJ
fcis-28514	36	17	texture	texture	NOUN
fcis-28514	36	18	extracted	extract	VERB
fcis-28514	36	19	by	by	ADP
fcis-28514	36	20	wavelet	wavelet	NOUN
fcis-28514	36	21	transform	transform	NOUN
fcis-28514	36	22	with	with	ADP
fcis-28514	36	23	the	the	DET
fcis-28514	36	24	features	feature	NOUN
fcis-28514	36	25	extracted	extract	VERB
fcis-28514	36	26	by	by	ADP
fcis-28514	36	27	convolution	convolution	NOUN
fcis-28514	36	28	.	.	PUNCT
fcis-28514	37	1	based	base	VERB
fcis-28514	37	2	on	on	ADP
fcis-28514	37	3	the	the	DET
fcis-28514	37	4	above	above	ADJ
fcis-28514	37	5	analysis	analysis	NOUN
fcis-28514	37	6	,	,	PUNCT
fcis-28514	37	7	this	this	DET
fcis-28514	37	8	paper	paper	NOUN
fcis-28514	37	9	designs	design	VERB
fcis-28514	37	10	an	an	DET
fcis-28514	37	11	improved	improved	ADJ
fcis-28514	37	12	algorithm	algorithm	NOUN
fcis-28514	37	13	for	for	ADP
fcis-28514	37	14	small	small	ADJ
fcis-28514	37	15	target	target	NOUN
fcis-28514	37	16	detection	detection	NOUN
fcis-28514	37	17	.	.	PUNCT
fcis-28514	38	1	the	the	DET
fcis-28514	38	2	main	main	ADJ
fcis-28514	38	3	contributions	contribution	NOUN
fcis-28514	38	4	are	be	AUX
fcis-28514	38	5	as	as	SCONJ
fcis-28514	38	6	follows	follow	VERB
fcis-28514	38	7	:	:	PUNCT
fcis-28514	38	8	(	(	PUNCT
fcis-28514	38	9	1	1	X
fcis-28514	38	10	)	)	PUNCT
fcis-28514	38	11	wavelet	wavelet	NOUN
fcis-28514	38	12	-	-	PUNCT
fcis-28514	38	13	transform	transform	NOUN
fcis-28514	38	14	convolution	convolution	NOUN
fcis-28514	38	15	(	(	PUNCT
fcis-28514	38	16	wt	wt	NOUN
fcis-28514	38	17	-	-	PUNCT
fcis-28514	38	18	conv	conv	NOUN
fcis-28514	38	19	)	)	PUNCT
fcis-28514	38	20	module	module	NOUN
fcis-28514	38	21	is	be	AUX
fcis-28514	38	22	designed	design	VERB
fcis-28514	38	23	,	,	PUNCT
fcis-28514	38	24	and	and	CCONJ
fcis-28514	38	25	wavelet	wavelet	NOUN
fcis-28514	38	26	transform	transform	NOUN
fcis-28514	38	27	technology	technology	NOUN
fcis-28514	38	28	is	be	AUX
fcis-28514	38	29	introduced	introduce	VERB
fcis-28514	38	30	into	into	ADP
fcis-28514	38	31	feature	feature	NOUN
fcis-28514	38	32	extraction	extraction	NOUN
fcis-28514	38	33	network	network	NOUN
fcis-28514	38	34	to	to	PART
fcis-28514	38	35	extract	extract	VERB
fcis-28514	38	36	high	high	ADJ
fcis-28514	38	37	-	-	PUNCT
fcis-28514	38	38	frequency	frequency	NOUN
fcis-28514	38	39	and	and	CCONJ
fcis-28514	38	40	low	low	ADJ
fcis-28514	38	41	-	-	PUNCT
fcis-28514	38	42	frequency	frequency	NOUN
fcis-28514	38	43	components	component	NOUN
fcis-28514	38	44	in	in	ADP
fcis-28514	38	45	images	image	NOUN
fcis-28514	38	46	and	and	CCONJ
fcis-28514	38	47	enrich	enrich	VERB
fcis-28514	38	48	low	low	ADJ
fcis-28514	38	49	-	-	PUNCT
fcis-28514	38	50	level	level	NOUN
fcis-28514	38	51	features	feature	NOUN
fcis-28514	38	52	.	.	PUNCT
fcis-28514	39	1	(	(	PUNCT
fcis-28514	39	2	2	2	X
fcis-28514	39	3	)	)	PUNCT
fcis-28514	39	4	multiscale	multiscale	ADJ
fcis-28514	39	5	separation	separation	NOUN
fcis-28514	39	6	(	(	PUNCT
fcis-28514	39	7	ms	ms	NOUN
fcis-28514	39	8	)	)	PUNCT
fcis-28514	39	9	module	module	NOUN
fcis-28514	39	10	is	be	AUX
fcis-28514	39	11	designed	design	VERB
fcis-28514	39	12	to	to	PART
fcis-28514	39	13	achieve	achieve	VERB
fcis-28514	39	14	information	information	NOUN
fcis-28514	39	15	stripping	stripping	NOUN
fcis-28514	39	16	of	of	ADP
fcis-28514	39	17	objects	object	NOUN
fcis-28514	39	18	of	of	ADP
fcis-28514	39	19	different	different	ADJ
fcis-28514	39	20	scales	scale	NOUN
fcis-28514	39	21	.	.	PUNCT
fcis-28514	40	1	(	(	PUNCT
fcis-28514	40	2	3	3	X
fcis-28514	40	3	)	)	PUNCT
fcis-28514	40	4	a	a	DET
fcis-28514	40	5	detail	detail	NOUN
fcis-28514	40	6	enhancement	enhancement	NOUN
fcis-28514	40	7	(	(	PUNCT
fcis-28514	40	8	de	de	NOUN
fcis-28514	40	9	)	)	PUNCT
fcis-28514	40	10	module	module	NOUN
fcis-28514	40	11	is	be	AUX
fcis-28514	40	12	designed	design	VERB
fcis-28514	40	13	to	to	PART
fcis-28514	40	14	fuse	fuse	VERB
fcis-28514	40	15	small	small	ADJ
fcis-28514	40	16	object	object	NOUN
fcis-28514	40	17	features	feature	NOUN
fcis-28514	40	18	from	from	ADP
fcis-28514	40	19	adjacent	adjacent	ADJ
fcis-28514	40	20	feature	feature	NOUN
fcis-28514	40	21	maps	map	NOUN
fcis-28514	40	22	,	,	PUNCT
fcis-28514	40	23	thereby	thereby	ADV
fcis-28514	40	24	increasing	increase	VERB
fcis-28514	40	25	the	the	DET
fcis-28514	40	26	semantic	semantic	ADJ
fcis-28514	40	27	information	information	NOUN
fcis-28514	40	28	of	of	ADP
fcis-28514	40	29	channels	channel	NOUN
fcis-28514	40	30	and	and	CCONJ
fcis-28514	40	31	enhancing	enhance	VERB
fcis-28514	40	32	the	the	DET
fcis-28514	40	33	communication	communication	NOUN
fcis-28514	40	34	between	between	ADP
fcis-28514	40	35	channels	channel	NOUN
fcis-28514	40	36	to	to	PART
fcis-28514	40	37	enhance	enhance	VERB
fcis-28514	40	38	the	the	DET
fcis-28514	40	39	feature	feature	NOUN
fcis-28514	40	40	expression	expression	NOUN
fcis-28514	40	41	of	of	ADP
fcis-28514	40	42	small	small	ADJ
fcis-28514	40	43	objects	object	NOUN
fcis-28514	40	44	.	.	PUNCT
fcis-28514	41	1	2	2	X
fcis-28514	41	2	.	.	X
fcis-28514	41	3	methodology	methodology	NOUN
fcis-28514	41	4	the	the	DET
fcis-28514	41	5	yolov8	yolov8	PROPN
fcis-28514	41	6	network	network	PROPN
fcis-28514	41	7	model	model	NOUN
fcis-28514	41	8	consists	consist	VERB
fcis-28514	41	9	of	of	ADP
fcis-28514	41	10	three	three	NUM
fcis-28514	41	11	components	component	NOUN
fcis-28514	41	12	:	:	PUNCT
fcis-28514	41	13	the	the	DET
fcis-28514	41	14	backbone	backbone	NOUN
fcis-28514	41	15	for	for	ADP
fcis-28514	41	16	feature	feature	NOUN
fcis-28514	41	17	extraction	extraction	NOUN
fcis-28514	41	18	,	,	PUNCT
fcis-28514	41	19	the	the	DET
fcis-28514	41	20	neck	neck	NOUN
fcis-28514	41	21	for	for	ADP
fcis-28514	41	22	feature	feature	NOUN
fcis-28514	41	23	fusion	fusion	NOUN
fcis-28514	41	24	,	,	PUNCT
fcis-28514	41	25	and	and	CCONJ
fcis-28514	41	26	the	the	DET
fcis-28514	41	27	detect	detect	NOUN
fcis-28514	41	28	head	head	NOUN
fcis-28514	41	29	for	for	ADP
fcis-28514	41	30	object	object	NOUN
fcis-28514	41	31	detection	detection	NOUN
fcis-28514	41	32	.	.	PUNCT
fcis-28514	42	1	the	the	DET
fcis-28514	42	2	network	network	NOUN
fcis-28514	42	3	structure	structure	NOUN
fcis-28514	42	4	of	of	ADP
fcis-28514	42	5	the	the	DET
fcis-28514	42	6	improved	improved	ADJ
fcis-28514	42	7	yolov8	yolov8	NOUN
fcis-28514	42	8	model	model	NOUN
fcis-28514	42	9	proposed	propose	VERB
fcis-28514	42	10	in	in	ADP
fcis-28514	42	11	this	this	DET
fcis-28514	42	12	paper	paper	NOUN
fcis-28514	42	13	is	be	AUX
fcis-28514	42	14	illustrated	illustrate	VERB
fcis-28514	42	15	in	in	ADP
fcis-28514	42	16	fig	fig	NOUN
fcis-28514	42	17	.	.	PUNCT
fcis-28514	43	1	1	1	X
fcis-28514	43	2	.	.	PUNCT
fcis-28514	43	3	firstly	firstly	ADV
fcis-28514	43	4	,	,	PUNCT
fcis-28514	43	5	modifications	modification	NOUN
fcis-28514	43	6	are	be	AUX
fcis-28514	43	7	made	make	VERB
fcis-28514	43	8	to	to	ADP
fcis-28514	43	9	the	the	DET
fcis-28514	43	10	backbone	backbone	NOUN
fcis-28514	43	11	structure	structure	NOUN
fcis-28514	43	12	of	of	ADP
fcis-28514	43	13	the	the	DET
fcis-28514	43	14	meta	meta	NOUN
fcis-28514	43	15	-	-	PUNCT
fcis-28514	43	16	model	model	NOUN
fcis-28514	43	17	by	by	ADP
fcis-28514	43	18	replacing	replace	VERB
fcis-28514	43	19	the	the	DET
fcis-28514	43	20	c	c	NOUN
fcis-28514	43	21	layer	layer	NOUN
fcis-28514	43	22	with	with	ADP
fcis-28514	43	23	a	a	DET
fcis-28514	43	24	wt_conv	wt_conv	NOUN
fcis-28514	43	25	module	module	NOUN
fcis-28514	43	26	,	,	PUNCT
fcis-28514	43	27	which	which	PRON
fcis-28514	43	28	fuses	fuse	VERB
fcis-28514	43	29	wavelettransformed	wavelettransforme	VERB
fcis-28514	43	30	feature	feature	NOUN
fcis-28514	43	31	components	component	NOUN
fcis-28514	43	32	with	with	ADP
fcis-28514	43	33	original	original	ADJ
fcis-28514	43	34	image	image	NOUN
fcis-28514	43	35	features	feature	NOUN
fcis-28514	43	36	.	.	PUNCT
fcis-28514	44	1	secondly	secondly	ADV
fcis-28514	44	2	,	,	PUNCT
fcis-28514	44	3	ms	ms	PROPN
fcis-28514	44	4	modules	module	NOUN
fcis-28514	44	5	and	and	CCONJ
fcis-28514	44	6	de	de	X
fcis-28514	44	7	modules	module	NOUN
fcis-28514	44	8	are	be	AUX
fcis-28514	44	9	introduced	introduce	VERB
fcis-28514	44	10	between	between	ADP
fcis-28514	44	11	the	the	DET
fcis-28514	44	12	original	original	ADJ
fcis-28514	44	13	backbone	backbone	NOUN
fcis-28514	44	14	and	and	CCONJ
fcis-28514	44	15	neck	neck	NOUN
fcis-28514	44	16	.	.	PUNCT
fcis-28514	45	1	two	two	NUM
fcis-28514	45	2	ms	ms	PROPN
fcis-28514	45	3	modules	module	NOUN
fcis-28514	45	4	divide	divide	VERB
fcis-28514	45	5	features	feature	NOUN
fcis-28514	45	6	from	from	ADP
fcis-28514	45	7	shallow	shallow	ADJ
fcis-28514	45	8	layer	layer	NOUN
fcis-28514	45	9	in	in	ADP
fcis-28514	45	10	backbone	backbone	NOUN
fcis-28514	45	11	to	to	PART
fcis-28514	45	12	retain	retain	VERB
fcis-28514	45	13	details	detail	NOUN
fcis-28514	45	14	of	of	ADP
fcis-28514	45	15	small	small	ADJ
fcis-28514	45	16	objects	object	NOUN
fcis-28514	45	17	while	while	SCONJ
fcis-28514	45	18	transferring	transfer	VERB
fcis-28514	45	19	large	large	ADJ
fcis-28514	45	20	-	-	PUNCT
fcis-28514	45	21	objects	object	NOUN
fcis-28514	45	22	feature	feature	NOUN
fcis-28514	45	23	information	information	NOUN
fcis-28514	45	24	to	to	ADP
fcis-28514	45	25	deeper	deep	ADJ
fcis-28514	45	26	layers	layer	NOUN
fcis-28514	45	27	in	in	ADP
fcis-28514	45	28	the	the	DET
fcis-28514	45	29	network	network	NOUN
fcis-28514	45	30	.	.	PUNCT
fcis-28514	46	1	the	the	DET
fcis-28514	46	2	two	two	NUM
fcis-28514	46	3	de	de	NOUN
fcis-28514	46	4	modules	module	NOUN
fcis-28514	46	5	enhance	enhance	VERB
fcis-28514	46	6	small	small	ADJ
fcis-28514	46	7	object	object	NOUN
fcis-28514	46	8	features	feature	NOUN
fcis-28514	46	9	and	and	CCONJ
fcis-28514	46	10	fuse	fuse	VERB
fcis-28514	46	11	them	they	PRON
fcis-28514	46	12	with	with	ADP
fcis-28514	46	13	bottom	bottom	ADJ
fcis-28514	46	14	-	-	PUNCT
fcis-28514	46	15	up	up	ADP
fcis-28514	46	16	information	information	NOUN
fcis-28514	46	17	flow	flow	NOUN
fcis-28514	46	18	in	in	ADP
fcis-28514	46	19	the	the	DET
fcis-28514	46	20	neck	neck	NOUN
fcis-28514	46	21	section	section	NOUN
fcis-28514	46	22	to	to	PART
fcis-28514	46	23	provide	provide	VERB
fcis-28514	46	24	more	more	ADV
fcis-28514	46	25	direct	direct	ADJ
fcis-28514	46	26	small	small	ADJ
fcis-28514	46	27	object	object	NOUN
fcis-28514	46	28	features	feature	VERB
fcis-28514	46	29	for	for	ADP
fcis-28514	46	30	detection	detection	NOUN
fcis-28514	46	31	at	at	ADP
fcis-28514	46	32	d	d	NOUN
fcis-28514	46	33	layer	layer	NOUN
fcis-28514	46	34	.	.	PUNCT
fcis-28514	47	1	additionally	additionally	ADV
fcis-28514	47	2	,	,	PUNCT
fcis-28514	47	3	a	a	DET
fcis-28514	47	4	detect	detect	NOUN
fcis-28514	47	5	layer	layer	NOUN
fcis-28514	47	6	at	at	ADP
fcis-28514	47	7	d	d	PROPN
fcis-28514	47	8	is	be	AUX
fcis-28514	47	9	employed	employ	VERB
fcis-28514	47	10	specifically	specifically	ADV
fcis-28514	47	11	for	for	ADP
fcis-28514	47	12	detecting	detect	VERB
fcis-28514	47	13	large	large	ADJ
fcis-28514	47	14	objects	object	NOUN
fcis-28514	47	15	.	.	PUNCT
fcis-28514	48	1	fig	fig	NOUN
fcis-28514	48	2	1	1	NUM
fcis-28514	48	3	.	.	PUNCT
fcis-28514	49	1	the	the	DET
fcis-28514	49	2	network	network	NOUN
fcis-28514	49	3	structure	structure	NOUN
fcis-28514	49	4	of	of	ADP
fcis-28514	49	5	improved	improve	VERB
fcis-28514	49	6	-	-	PUNCT
fcis-28514	49	7	yolov8	yolov8	NOUN
fcis-28514	49	8	model	model	NOUN
fcis-28514	49	9	2.1	2.1	NUM
fcis-28514	49	10	.	.	PUNCT
fcis-28514	50	1	wt_conv	wt_conv	NOUN
fcis-28514	50	2	module	module	NOUN
fcis-28514	50	3	wavelet	wavelet	NOUN
fcis-28514	50	4	transform	transform	NOUN
fcis-28514	50	5	(	(	PUNCT
fcis-28514	50	6	wt	wt	NOUN
fcis-28514	50	7	)	)	PUNCT
fcis-28514	50	8	is	be	AUX
fcis-28514	50	9	a	a	DET
fcis-28514	50	10	classical	classical	ADJ
fcis-28514	50	11	image	image	NOUN
fcis-28514	50	12	processing	processing	NOUN
fcis-28514	50	13	algorithm	algorithm	NOUN
fcis-28514	50	14	,	,	PUNCT
fcis-28514	50	15	which	which	PRON
fcis-28514	50	16	can	can	AUX
fcis-28514	50	17	transform	transform	VERB
fcis-28514	50	18	an	an	DET
fcis-28514	50	19	image	image	NOUN
fcis-28514	50	20	from	from	ADP
fcis-28514	50	21	the	the	DET
fcis-28514	50	22	spatial	spatial	ADJ
fcis-28514	50	23	domain	domain	NOUN
fcis-28514	50	24	to	to	ADP
fcis-28514	50	25	the	the	DET
fcis-28514	50	26	wavelet	wavelet	NOUN
fcis-28514	50	27	domain	domain	NOUN
fcis-28514	50	28	to	to	PART
fcis-28514	50	29	extract	extract	VERB
fcis-28514	50	30	the	the	DET
fcis-28514	50	31	edge	edge	NOUN
fcis-28514	50	32	,	,	PUNCT
fcis-28514	50	33	texture	texture	NOUN
fcis-28514	50	34	and	and	CCONJ
fcis-28514	50	35	other	other	ADJ
fcis-28514	50	36	features	feature	NOUN
fcis-28514	50	37	of	of	ADP
fcis-28514	50	38	the	the	DET
fcis-28514	50	39	image	image	NOUN
fcis-28514	50	40	.	.	PUNCT
fcis-28514	51	1	small	small	ADJ
fcis-28514	51	2	objects	object	NOUN
fcis-28514	51	3	usually	usually	ADV
fcis-28514	51	4	have	have	AUX
fcis-28514	51	5	blurred	blur	VERB
fcis-28514	51	6	edges	edge	NOUN
fcis-28514	51	7	and	and	CCONJ
fcis-28514	51	8	low	low	ADJ
fcis-28514	51	9	differentiation	differentiation	NOUN
fcis-28514	51	10	from	from	ADP
fcis-28514	51	11	the	the	DET
fcis-28514	51	12	foreground	foreground	NOUN
fcis-28514	51	13	,	,	PUNCT
fcis-28514	51	14	so	so	ADV
fcis-28514	51	15	extracting	extract	VERB
fcis-28514	51	16	these	these	DET
fcis-28514	51	17	fine	fine	ADJ
fcis-28514	51	18	features	feature	NOUN
fcis-28514	51	19	is	be	AUX
fcis-28514	51	20	particularly	particularly	ADV
fcis-28514	51	21	important	important	ADJ
fcis-28514	51	22	for	for	ADP
fcis-28514	51	23	small	small	ADJ
fcis-28514	51	24	object	object	NOUN
fcis-28514	51	25	detection	detection	NOUN
fcis-28514	51	26	.	.	PUNCT
fcis-28514	52	1	by	by	ADP
fcis-28514	52	2	incorporating	incorporate	VERB
fcis-28514	52	3	wavelet	wavelet	NOUN
fcis-28514	52	4	transform	transform	NOUN
fcis-28514	52	5	into	into	ADP
fcis-28514	52	6	the	the	DET
fcis-28514	52	7	convolutional	convolutional	ADJ
fcis-28514	52	8	neural	neural	ADJ
fcis-28514	52	9	network	network	NOUN
fcis-28514	52	10	,	,	PUNCT
fcis-28514	52	11	the	the	DET
fcis-28514	52	12	feature	feature	NOUN
fcis-28514	52	13	richness	richness	NOUN
fcis-28514	52	14	can	can	AUX
fcis-28514	52	15	be	be	AUX
fcis-28514	52	16	improved	improve	VERB
fcis-28514	52	17	without	without	ADP
fcis-28514	52	18	increasing	increase	VERB
fcis-28514	52	19	the	the	DET
fcis-28514	52	20	number	number	NOUN
fcis-28514	52	21	of	of	ADP
fcis-28514	52	22	parameters	parameter	NOUN
fcis-28514	52	23	.	.	PUNCT
fcis-28514	53	1	the	the	DET
fcis-28514	53	2	wt_conv	wt_conv	PROPN
fcis-28514	53	3	module	module	NOUN
fcis-28514	53	4	structure	structure	NOUN
fcis-28514	53	5	is	be	AUX
fcis-28514	53	6	shown	show	VERB
fcis-28514	53	7	in	in	ADP
fcis-28514	53	8	fig	fig	NOUN
fcis-28514	53	9	.	.	PUNCT
fcis-28514	54	1	2	2	X
fcis-28514	54	2	.	.	X
fcis-28514	54	3	it	it	PRON
fcis-28514	54	4	is	be	AUX
fcis-28514	54	5	necessary	necessary	ADJ
fcis-28514	54	6	to	to	PART
fcis-28514	54	7	convert	convert	VERB
fcis-28514	54	8	the	the	DET
fcis-28514	54	9	rgb	rgb	PROPN
fcis-28514	54	10	image	image	NOUN
fcis-28514	54	11	to	to	ADP
fcis-28514	54	12	the	the	DET
fcis-28514	54	13	gray	gray	ADJ
fcis-28514	54	14	image	image	NOUN
fcis-28514	54	15	as	as	ADP
fcis-28514	54	16	the	the	DET
fcis-28514	54	17	input	input	NOUN
fcis-28514	54	18	of	of	ADP
fcis-28514	54	19	the	the	DET
fcis-28514	54	20	wavelet	wavelet	NOUN
fcis-28514	54	21	transform	transform	NOUN
fcis-28514	54	22	,	,	PUNCT
fcis-28514	54	23	and	and	CCONJ
fcis-28514	54	24	finally	finally	ADV
fcis-28514	54	25	obtain	obtain	VERB
fcis-28514	54	26	the	the	DET
fcis-28514	54	27	approximation	approximation	NOUN
fcis-28514	54	28	coefficients	coefficient	NOUN
fcis-28514	54	29	(	(	PUNCT
fcis-28514	54	30	ca	ca	NOUN
fcis-28514	54	31	)	)	PUNCT
fcis-28514	54	32	,	,	PUNCT
fcis-28514	54	33	horizontal	horizontal	ADJ
fcis-28514	54	34	detail	detail	NOUN
fcis-28514	54	35	coefficients	coefficient	NOUN
fcis-28514	54	36	(	(	PUNCT
fcis-28514	54	37	ch	ch	NOUN
fcis-28514	54	38	)	)	PUNCT
fcis-28514	54	39	,	,	PUNCT
fcis-28514	54	40	vertical	vertical	ADJ
fcis-28514	54	41	detail	detail	NOUN
fcis-28514	54	42	coefficients	coefficient	NOUN
fcis-28514	54	43	(	(	PUNCT
fcis-28514	54	44	cv	cv	NOUN
fcis-28514	54	45	)	)	PUNCT
fcis-28514	54	46	and	and	CCONJ
fcis-28514	54	47	diagonal	diagonal	ADJ
fcis-28514	54	48	detail	detail	NOUN
fcis-28514	54	49	coefficients	coefficient	NOUN
fcis-28514	54	50	(	(	PUNCT
fcis-28514	54	51	cd	cd	PROPN
fcis-28514	54	52	)	)	PUNCT
fcis-28514	54	53	.	.	PUNCT
fcis-28514	55	1	the	the	DET
fcis-28514	55	2	process	process	NOUN
fcis-28514	55	3	is	be	AUX
fcis-28514	55	4	expressed	express	VERB
fcis-28514	55	5	by	by	ADP
fcis-28514	55	6	the	the	DET
fcis-28514	55	7	formula	formula	NOUN
fcis-28514	55	8	:	:	PUNCT
fcis-28514	55	9	ca	ca	NOUN
fcis-28514	55	10	,	,	PUNCT
fcis-28514	55	11	ch	ch	NOUN
fcis-28514	55	12	,	,	PUNCT
fcis-28514	55	13	cv	cv	PROPN
fcis-28514	55	14	,	,	PUNCT
fcis-28514	55	15	cd	cd	PROPN
fcis-28514	55	16	=	=	NOUN
fcis-28514	55	17	wt(gray_img	wt(gray_img	PROPN
fcis-28514	55	18	)	)	PUNCT
fcis-28514	55	19	(	(	PUNCT
fcis-28514	55	20	1	1	X
fcis-28514	55	21	)	)	PUNCT
fcis-28514	55	22	fig	fig	NOUN
fcis-28514	55	23	2	2	NUM
fcis-28514	55	24	.	.	PUNCT
fcis-28514	56	1	wt_conv	wt_conv	NOUN
fcis-28514	56	2	module	module	NOUN
fcis-28514	56	3	the	the	DET
fcis-28514	56	4	four	four	NUM
fcis-28514	56	5	coefficients	coefficient	NOUN
fcis-28514	56	6	are	be	AUX
fcis-28514	56	7	of	of	ADP
fcis-28514	56	8	equal	equal	ADJ
fcis-28514	56	9	magnitude	magnitude	NOUN
fcis-28514	56	10	,	,	PUNCT
fcis-28514	56	11	with	with	ADP
fcis-28514	56	12	the	the	DET
fcis-28514	56	13	width	width	ADJ
fcis-28514	56	14	and	and	CCONJ
fcis-28514	56	15	height	height	NOUN
fcis-28514	56	16	dimensions	dimension	NOUN
fcis-28514	56	17	being	be	AUX
fcis-28514	56	18	half	half	DET
fcis-28514	56	19	that	that	PRON
fcis-28514	56	20	of	of	ADP
fcis-28514	56	21	the	the	DET
fcis-28514	56	22	original	original	ADJ
fcis-28514	56	23	81	81	NUM
fcis-28514	56	24	image	image	NOUN
fcis-28514	56	25	.	.	PUNCT
fcis-28514	57	1	they	they	PRON
fcis-28514	57	2	are	be	AUX
fcis-28514	57	3	combined	combine	VERB
fcis-28514	57	4	in	in	ADP
fcis-28514	57	5	the	the	DET
fcis-28514	57	6	channel	channel	NOUN
fcis-28514	57	7	dimension	dimension	NOUN
fcis-28514	57	8	to	to	PART
fcis-28514	57	9	yield	yield	VERB
fcis-28514	57	10	an	an	DET
fcis-28514	57	11	output	output	NOUN
fcis-28514	57	12	with	with	ADP
fcis-28514	57	13	size	size	NOUN
fcis-28514	57	14	[	[	X
fcis-28514	57	15	4	4	NUM
fcis-28514	57	16	,	,	PUNCT
fcis-28514	57	17	320	320	NUM
fcis-28514	57	18	,	,	PUNCT
fcis-28514	57	19	320	320	NUM
fcis-28514	57	20	]	]	PUNCT
fcis-28514	57	21	.	.	PUNCT
fcis-28514	58	1	simultaneously	simultaneously	ADV
fcis-28514	58	2	,	,	PUNCT
fcis-28514	58	3	a	a	DET
fcis-28514	58	4	3×3	3×3	NUM
fcis-28514	58	5	convolution	convolution	NOUN
fcis-28514	58	6	is	be	AUX
fcis-28514	58	7	employed	employ	VERB
fcis-28514	58	8	to	to	PART
fcis-28514	58	9	transform	transform	VERB
fcis-28514	58	10	the	the	DET
fcis-28514	58	11	input	input	NOUN
fcis-28514	58	12	vector	vector	NOUN
fcis-28514	58	13	from	from	ADP
fcis-28514	58	14	[	[	X
fcis-28514	58	15	3	3	NUM
fcis-28514	58	16	,	,	PUNCT
fcis-28514	58	17	640	640	NUM
fcis-28514	58	18	,	,	PUNCT
fcis-28514	58	19	640	640	NUM
fcis-28514	58	20	]	]	PUNCT
fcis-28514	58	21	to	to	ADP
fcis-28514	58	22	[	[	X
fcis-28514	58	23	12	12	NUM
fcis-28514	58	24	,	,	PUNCT
fcis-28514	58	25	320	320	NUM
fcis-28514	58	26	,	,	PUNCT
fcis-28514	58	27	320	320	NUM
fcis-28514	58	28	]	]	PUNCT
fcis-28514	58	29	.	.	PUNCT
fcis-28514	59	1	finally	finally	ADV
fcis-28514	59	2	,	,	PUNCT
fcis-28514	59	3	the	the	DET
fcis-28514	59	4	outputs	output	NOUN
fcis-28514	59	5	after	after	ADP
fcis-28514	59	6	both	both	CCONJ
fcis-28514	59	7	the	the	DET
fcis-28514	59	8	convolution	convolution	NOUN
fcis-28514	59	9	operation	operation	NOUN
fcis-28514	59	10	and	and	CCONJ
fcis-28514	59	11	wavelet	wavelet	NOUN
fcis-28514	59	12	transform	transform	NOUN
fcis-28514	59	13	processing	processing	NOUN
fcis-28514	59	14	are	be	AUX
fcis-28514	59	15	concatenated	concatenate	VERB
fcis-28514	59	16	to	to	PART
fcis-28514	59	17	obtain	obtain	VERB
fcis-28514	59	18	a	a	DET
fcis-28514	59	19	vector	vector	NOUN
fcis-28514	59	20	of	of	ADP
fcis-28514	59	21	size	size	NOUN
fcis-28514	59	22	[	[	X
fcis-28514	59	23	16	16	NUM
fcis-28514	59	24	,	,	PUNCT
fcis-28514	59	25	320	320	NUM
fcis-28514	59	26	,	,	PUNCT
fcis-28514	59	27	320	320	NUM
fcis-28514	59	28	]	]	PUNCT
fcis-28514	59	29	,	,	PUNCT
fcis-28514	59	30	which	which	PRON
fcis-28514	59	31	serves	serve	VERB
fcis-28514	59	32	as	as	ADP
fcis-28514	59	33	input	input	NOUN
fcis-28514	59	34	for	for	ADP
fcis-28514	59	35	the	the	DET
fcis-28514	59	36	subsequent	subsequent	ADJ
fcis-28514	59	37	layer	layer	NOUN
fcis-28514	59	38	.	.	PUNCT
fcis-28514	60	1	2.2	2.2	NUM
fcis-28514	60	2	.	.	PUNCT
fcis-28514	61	1	ms	ms	NOUN
fcis-28514	61	2	module	module	NOUN
fcis-28514	61	3	the	the	DET
fcis-28514	61	4	yolo	yolo	ADJ
fcis-28514	61	5	model	model	NOUN
fcis-28514	61	6	incorporates	incorporate	VERB
fcis-28514	61	7	multiple	multiple	ADJ
fcis-28514	61	8	convolution	convolution	NOUN
fcis-28514	61	9	and	and	CCONJ
fcis-28514	61	10	downsampling	downsample	VERB
fcis-28514	61	11	operations	operation	NOUN
fcis-28514	61	12	,	,	PUNCT
fcis-28514	61	13	resulting	result	VERB
fcis-28514	61	14	in	in	ADP
fcis-28514	61	15	deep	deep	ADJ
fcis-28514	61	16	feature	feature	NOUN
fcis-28514	61	17	maps	map	NOUN
fcis-28514	61	18	that	that	PRON
fcis-28514	61	19	encompass	encompass	VERB
fcis-28514	61	20	rich	rich	ADJ
fcis-28514	61	21	semantic	semantic	ADJ
fcis-28514	61	22	information	information	NOUN
fcis-28514	61	23	but	but	CCONJ
fcis-28514	61	24	lacks	lack	VERB
fcis-28514	61	25	fine	fine	ADV
fcis-28514	61	26	-	-	PUNCT
fcis-28514	61	27	grained	grain	VERB
fcis-28514	61	28	details	detail	NOUN
fcis-28514	61	29	of	of	ADP
fcis-28514	61	30	small	small	ADJ
fcis-28514	61	31	objects	object	NOUN
fcis-28514	61	32	.	.	PUNCT
fcis-28514	62	1	conversely	conversely	ADV
fcis-28514	62	2	,	,	PUNCT
fcis-28514	62	3	the	the	DET
fcis-28514	62	4	shallow	shallow	ADJ
fcis-28514	62	5	feature	feature	NOUN
fcis-28514	62	6	maps	map	NOUN
fcis-28514	62	7	contain	contain	VERB
fcis-28514	62	8	information	information	NOUN
fcis-28514	62	9	about	about	ADP
fcis-28514	62	10	objects	object	NOUN
fcis-28514	62	11	of	of	ADP
fcis-28514	62	12	varying	vary	VERB
fcis-28514	62	13	scales	scale	NOUN
fcis-28514	62	14	.	.	PUNCT
fcis-28514	63	1	to	to	PART
fcis-28514	63	2	address	address	VERB
fcis-28514	63	3	the	the	DET
fcis-28514	63	4	deficiency	deficiency	NOUN
fcis-28514	63	5	in	in	ADP
fcis-28514	63	6	detail	detail	NOUN
fcis-28514	63	7	within	within	ADP
fcis-28514	63	8	the	the	DET
fcis-28514	63	9	deep	deep	ADJ
fcis-28514	63	10	feature	feature	NOUN
fcis-28514	63	11	map	map	NOUN
fcis-28514	63	12	,	,	PUNCT
fcis-28514	63	13	yolov8	yolov8	PROPN
fcis-28514	63	14	employs	employ	VERB
fcis-28514	63	15	the	the	DET
fcis-28514	63	16	neck	neck	NOUN
fcis-28514	63	17	structure	structure	NOUN
fcis-28514	63	18	depicted	depict	VERB
fcis-28514	63	19	in	in	ADP
fcis-28514	63	20	fig	fig	NOUN
fcis-28514	63	21	3	3	NUM
fcis-28514	63	22	.	.	PUNCT
fcis-28514	64	1	however	however	ADV
fcis-28514	64	2	,	,	PUNCT
fcis-28514	64	3	this	this	DET
fcis-28514	64	4	approach	approach	NOUN
fcis-28514	64	5	introduces	introduce	VERB
fcis-28514	64	6	scale	scale	NOUN
fcis-28514	64	7	-	-	PUNCT
fcis-28514	64	8	confusion	confusion	NOUN
fcis-28514	64	9	due	due	ADP
fcis-28514	64	10	to	to	ADP
fcis-28514	64	11	directly	directly	ADV
fcis-28514	64	12	fusing	fuse	VERB
fcis-28514	64	13	the	the	DET
fcis-28514	64	14	feature	feature	NOUN
fcis-28514	64	15	maps	map	NOUN
fcis-28514	64	16	and	and	CCONJ
fcis-28514	64	17	which	which	PRON
fcis-28514	64	18	come	come	VERB
fcis-28514	64	19	from	from	ADP
fcis-28514	64	20	shallow	shallow	ADJ
fcis-28514	64	21	layers	layer	NOUN
fcis-28514	64	22	and	and	CCONJ
fcis-28514	64	23	with	with	ADP
fcis-28514	64	24	and	and	CCONJ
fcis-28514	64	25	,	,	PUNCT
fcis-28514	64	26	respectively	respectively	ADV
fcis-28514	64	27	.	.	PUNCT
fcis-28514	65	1	and	and	CCONJ
fcis-28514	65	2	large	large	ADJ
fcis-28514	65	3	-	-	PUNCT
fcis-28514	65	4	objects	object	NOUN
fcis-28514	65	5	features	feature	NOUN
fcis-28514	65	6	in	in	ADP
fcis-28514	65	7	shallow	shallow	ADJ
fcis-28514	65	8	feature	feature	NOUN
fcis-28514	65	9	maps	map	NOUN
fcis-28514	65	10	will	will	AUX
fcis-28514	65	11	affect	affect	VERB
fcis-28514	65	12	the	the	DET
fcis-28514	65	13	detect	detect	NOUN
fcis-28514	65	14	of	of	ADP
fcis-28514	65	15	small	small	ADJ
fcis-28514	65	16	objects	object	NOUN
fcis-28514	65	17	.	.	PUNCT
fcis-28514	66	1	fig	fig	NOUN
fcis-28514	66	2	3	3	NUM
fcis-28514	66	3	.	.	PUNCT
fcis-28514	67	1	structure	structure	NOUN
fcis-28514	67	2	of	of	ADP
fcis-28514	67	3	yolov8	yolov8	PROPN
fcis-28514	67	4	model	model	NOUN
fcis-28514	67	5	inspired	inspire	VERB
fcis-28514	67	6	by	by	ADP
fcis-28514	67	7	the	the	DET
fcis-28514	67	8	idea	idea	NOUN
fcis-28514	67	9	of	of	ADP
fcis-28514	67	10	separating	separate	VERB
fcis-28514	67	11	large	large	ADJ
fcis-28514	67	12	object	object	NOUN
fcis-28514	67	13	information	information	NOUN
fcis-28514	67	14	from	from	ADP
fcis-28514	67	15	shallow	shallow	ADJ
fcis-28514	67	16	layers	layer	NOUN
fcis-28514	67	17	mentioned	mention	VERB
fcis-28514	67	18	in	in	ADP
fcis-28514	67	19	literature	literature	NOUN
fcis-28514	67	20	[	[	X
fcis-28514	67	21	6	6	NUM
fcis-28514	67	22	]	]	PUNCT
fcis-28514	67	23	to	to	PART
fcis-28514	67	24	reduce	reduce	VERB
fcis-28514	67	25	scale	scale	NOUN
fcis-28514	67	26	confusion	confusion	NOUN
fcis-28514	67	27	,	,	PUNCT
fcis-28514	67	28	the	the	DET
fcis-28514	67	29	ms	ms	PROPN
fcis-28514	67	30	module	module	NOUN
fcis-28514	67	31	is	be	AUX
fcis-28514	67	32	designed	design	VERB
fcis-28514	67	33	,	,	PUNCT
fcis-28514	67	34	as	as	SCONJ
fcis-28514	67	35	shown	show	VERB
fcis-28514	67	36	in	in	ADP
fcis-28514	67	37	fig	fig	NOUN
fcis-28514	67	38	.	.	PUNCT
fcis-28514	68	1	4	4	X
fcis-28514	68	2	.	.	X
fcis-28514	68	3	adjacent	adjacent	ADJ
fcis-28514	68	4	feature	feature	NOUN
fcis-28514	68	5	maps	map	NOUN
fcis-28514	68	6	contain	contain	VERB
fcis-28514	68	7	complementary	complementary	ADJ
fcis-28514	68	8	feature	feature	NOUN
fcis-28514	68	9	information	information	NOUN
fcis-28514	68	10	of	of	ADP
fcis-28514	68	11	the	the	DET
fcis-28514	68	12	same	same	ADJ
fcis-28514	68	13	object	object	NOUN
fcis-28514	68	14	.	.	PUNCT
fcis-28514	69	1	in	in	ADP
fcis-28514	69	2	order	order	NOUN
fcis-28514	69	3	to	to	PART
fcis-28514	69	4	avoid	avoid	VERB
fcis-28514	69	5	the	the	DET
fcis-28514	69	6	feature	feature	NOUN
fcis-28514	69	7	information	information	NOUN
fcis-28514	69	8	loss	loss	NOUN
fcis-28514	69	9	of	of	ADP
fcis-28514	69	10	scale	scale	NOUN
fcis-28514	69	11	overlapping	overlap	VERB
fcis-28514	69	12	parts	part	NOUN
fcis-28514	69	13	caused	cause	VERB
fcis-28514	69	14	by	by	ADP
fcis-28514	69	15	subtraction	subtraction	NOUN
fcis-28514	69	16	operation	operation	NOUN
fcis-28514	69	17	,	,	PUNCT
fcis-28514	69	18	the	the	DET
fcis-28514	69	19	input	input	NOUN
fcis-28514	69	20	of	of	ADP
fcis-28514	69	21	ms	ms	NOUN
fcis-28514	69	22	module	module	NOUN
fcis-28514	69	23	is	be	AUX
fcis-28514	69	24	backbone	backbone	NOUN
fcis-28514	69	25	's	's	PART
fcis-28514	69	26	hierarchical	hierarchical	ADJ
fcis-28514	69	27	features	feature	NOUN
fcis-28514	69	28	fi	fi	NOUN
fcis-28514	69	29	and	and	CCONJ
fcis-28514	69	30	fi+2	fi+2	PROPN
fcis-28514	69	31	.	.	PUNCT
fcis-28514	69	32	fi	fi	NOUN
fcis-28514	69	33	represents	represent	VERB
fcis-28514	69	34	feature	feature	NOUN
fcis-28514	69	35	map	map	NOUN
fcis-28514	69	36	from	from	ADP
fcis-28514	69	37	shallow	shallow	ADJ
fcis-28514	69	38	layer	layer	NOUN
fcis-28514	69	39	,	,	PUNCT
fcis-28514	69	40	fi+2	fi+2	PROPN
fcis-28514	69	41	represents	represent	VERB
fcis-28514	69	42	feature	feature	NOUN
fcis-28514	69	43	map	map	NOUN
fcis-28514	69	44	from	from	ADP
fcis-28514	69	45	deep	deep	ADJ
fcis-28514	69	46	layer	layer	NOUN
fcis-28514	69	47	.	.	PUNCT
fcis-28514	70	1	the	the	DET
fcis-28514	70	2	process	process	NOUN
fcis-28514	70	3	of	of	ADP
fcis-28514	70	4	multi	multi	ADJ
fcis-28514	70	5	-	-	ADJ
fcis-28514	70	6	scale	scale	ADJ
fcis-28514	70	7	separation	separation	NOUN
fcis-28514	70	8	is	be	AUX
fcis-28514	70	9	divided	divide	VERB
fcis-28514	70	10	into	into	ADP
fcis-28514	70	11	four	four	NUM
fcis-28514	70	12	steps	step	NOUN
fcis-28514	70	13	,	,	PUNCT
fcis-28514	70	14	of	of	ADP
fcis-28514	70	15	which	which	PRON
fcis-28514	70	16	(	(	PUNCT
fcis-28514	70	17	1	1	X
fcis-28514	70	18	)	)	PUNCT
fcis-28514	70	19	and	and	CCONJ
fcis-28514	70	20	(	(	PUNCT
fcis-28514	70	21	2	2	X
fcis-28514	70	22	)	)	PUNCT
fcis-28514	70	23	are	be	AUX
fcis-28514	70	24	shown	show	VERB
fcis-28514	70	25	in	in	ADP
fcis-28514	70	26	the	the	DET
fcis-28514	70	27	yellow	yellow	PROPN
fcis-28514	70	28	box	box	PROPN
fcis-28514	70	29	in	in	ADP
fcis-28514	70	30	the	the	DET
fcis-28514	70	31	figure	figure	NOUN
fcis-28514	70	32	:	:	PUNCT
fcis-28514	70	33	fig	fig	NOUN
fcis-28514	70	34	4	4	NUM
fcis-28514	70	35	.	.	PUNCT
fcis-28514	71	1	ms	ms	NOUN
fcis-28514	71	2	module	module	NOUN
fcis-28514	71	3	(	(	PUNCT
fcis-28514	71	4	1	1	NUM
fcis-28514	71	5	)	)	PUNCT
fcis-28514	71	6	first	first	ADV
fcis-28514	71	7	,	,	PUNCT
fcis-28514	71	8	is	be	AUX
fcis-28514	71	9	upsampled	upsample	VERB
fcis-28514	71	10	to	to	ADP
fcis-28514	71	11	the	the	DET
fcis-28514	71	12	same	same	ADJ
fcis-28514	71	13	size	size	NOUN
fcis-28514	71	14	as	as	ADP
fcis-28514	71	15	.	.	PUNCT
fcis-28514	72	1	the	the	DET
fcis-28514	72	2	two	two	NUM
fcis-28514	72	3	feature	feature	NOUN
fcis-28514	72	4	maps	map	NOUN
fcis-28514	72	5	are	be	AUX
fcis-28514	72	6	spliced	splice	VERB
fcis-28514	72	7	after	after	ADP
fcis-28514	72	8	maximum	maximum	ADJ
fcis-28514	72	9	pooling	pooling	NOUN
fcis-28514	72	10	and	and	CCONJ
fcis-28514	72	11	average	average	ADJ
fcis-28514	72	12	pooling	pooling	NOUN
fcis-28514	72	13	respectively	respectively	ADV
fcis-28514	72	14	,	,	PUNCT
fcis-28514	72	15	and	and	CCONJ
fcis-28514	72	16	then	then	ADV
fcis-28514	72	17	1×1	1×1	NUM
fcis-28514	72	18	convolution	convolution	NOUN
fcis-28514	72	19	is	be	AUX
fcis-28514	72	20	performed	perform	VERB
fcis-28514	72	21	to	to	PART
fcis-28514	72	22	generate	generate	VERB
fcis-28514	72	23	the	the	DET
fcis-28514	72	24	gate	gate	NOUN
fcis-28514	72	25	of	of	ADP
fcis-28514	72	26	each	each	DET
fcis-28514	72	27	channel	channel	NOUN
fcis-28514	72	28	.	.	PUNCT
fcis-28514	73	1	can	can	AUX
fcis-28514	73	2	adjust	adjust	VERB
fcis-28514	73	3	feature	feature	NOUN
fcis-28514	73	4	activation	activation	NOUN
fcis-28514	73	5	thresholds	threshold	NOUN
fcis-28514	73	6	at	at	ADP
fcis-28514	73	7	different	different	ADJ
fcis-28514	73	8	scales	scale	NOUN
fcis-28514	73	9	in	in	ADP
fcis-28514	73	10	the	the	DET
fcis-28514	73	11	channel	channel	NOUN
fcis-28514	73	12	dimension	dimension	NOUN
fcis-28514	73	13	.	.	PUNCT
fcis-28514	74	1	(	(	PUNCT
fcis-28514	74	2	2	2	X
fcis-28514	74	3	)	)	PUNCT
fcis-28514	74	4	perform	perform	VERB
fcis-28514	74	5	a	a	DET
fcis-28514	74	6	hadamard	hadamard	ADJ
fcis-28514	74	7	product	product	NOUN
fcis-28514	74	8	between	between	ADP
fcis-28514	74	9	the	the	DET
fcis-28514	74	10	variable	variable	NOUN
fcis-28514	74	11	and	and	CCONJ
fcis-28514	74	12	to	to	PART
fcis-28514	74	13	obtain	obtain	VERB
fcis-28514	74	14	the	the	DET
fcis-28514	74	15	feature	feature	NOUN
fcis-28514	74	16	map	map	NOUN
fcis-28514	74	17	.	.	PUNCT
fcis-28514	75	1	in	in	ADP
fcis-28514	75	2	this	this	DET
fcis-28514	75	3	process	process	NOUN
fcis-28514	75	4	,	,	PUNCT
fcis-28514	75	5	based	base	VERB
fcis-28514	75	6	on	on	ADP
fcis-28514	75	7	the	the	DET
fcis-28514	75	8	gating	gate	VERB
fcis-28514	75	9	signal	signal	NOUN
fcis-28514	75	10	generated	generate	VERB
fcis-28514	75	11	by	by	ADP
fcis-28514	75	12	the	the	DET
fcis-28514	75	13	deep	deep	ADJ
fcis-28514	75	14	feature	feature	NOUN
fcis-28514	75	15	information	information	NOUN
fcis-28514	75	16	,	,	PUNCT
fcis-28514	75	17	the	the	DET
fcis-28514	75	18	response	response	NOUN
fcis-28514	75	19	intensity	intensity	NOUN
fcis-28514	75	20	in	in	ADP
fcis-28514	75	21	the	the	DET
fcis-28514	75	22	shallow	shallow	ADJ
fcis-28514	75	23	feature	feature	NOUN
fcis-28514	75	24	map	map	NOUN
fcis-28514	75	25	can	can	AUX
fcis-28514	75	26	be	be	AUX
fcis-28514	75	27	adjusted	adjust	VERB
fcis-28514	75	28	.	.	PUNCT
fcis-28514	76	1	therefore	therefore	ADV
fcis-28514	76	2	,	,	PUNCT
fcis-28514	76	3	it	it	PRON
fcis-28514	76	4	is	be	AUX
fcis-28514	76	5	considered	consider	VERB
fcis-28514	76	6	that	that	SCONJ
fcis-28514	76	7	mainly	mainly	ADV
fcis-28514	76	8	includes	include	VERB
fcis-28514	76	9	large	large	ADJ
fcis-28514	76	10	object	object	NOUN
fcis-28514	76	11	features	feature	NOUN
fcis-28514	76	12	from	from	ADP
fcis-28514	76	13	that	that	DET
fcis-28514	76	14	need	need	NOUN
fcis-28514	76	15	to	to	PART
fcis-28514	76	16	be	be	AUX
fcis-28514	76	17	removed	remove	VERB
fcis-28514	76	18	.	.	PUNCT
fcis-28514	77	1	(	(	PUNCT
fcis-28514	77	2	3	3	X
fcis-28514	77	3	)	)	PUNCT
fcis-28514	77	4	by	by	ADP
fcis-28514	77	5	subtracting	subtract	VERB
fcis-28514	77	6	from	from	ADP
fcis-28514	77	7	,	,	PUNCT
fcis-28514	77	8	it	it	PRON
fcis-28514	77	9	means	mean	VERB
fcis-28514	77	10	that	that	SCONJ
fcis-28514	77	11	the	the	DET
fcis-28514	77	12	big	big	ADJ
fcis-28514	77	13	target	target	NOUN
fcis-28514	77	14	feature	feature	NOUN
fcis-28514	77	15	in	in	ADP
fcis-28514	77	16	is	be	AUX
fcis-28514	77	17	removed	remove	VERB
fcis-28514	77	18	,	,	PUNCT
fcis-28514	77	19	and	and	CCONJ
fcis-28514	77	20	the	the	DET
fcis-28514	77	21	small	small	ADJ
fcis-28514	77	22	target	target	NOUN
fcis-28514	77	23	feature	feature	NOUN
fcis-28514	77	24	map	map	NOUN
fcis-28514	77	25	can	can	AUX
fcis-28514	77	26	be	be	AUX
fcis-28514	77	27	obtained	obtain	VERB
fcis-28514	77	28	.	.	PUNCT
fcis-28514	78	1	(	(	PUNCT
fcis-28514	78	2	4	4	X
fcis-28514	78	3	)	)	PUNCT
fcis-28514	78	4	downsample	downsample	NOUN
fcis-28514	78	5	to	to	ADP
fcis-28514	78	6	a	a	DET
fcis-28514	78	7	size	size	NOUN
fcis-28514	78	8	consistent	consistent	ADJ
fcis-28514	78	9	with	with	ADP
fcis-28514	78	10	.	.	PUNCT
fcis-28514	79	1	the	the	DET
fcis-28514	79	2	two	two	NUM
fcis-28514	79	3	vectors	vector	NOUN
fcis-28514	79	4	are	be	AUX
fcis-28514	79	5	directly	directly	ADV
fcis-28514	79	6	added	add	VERB
fcis-28514	79	7	for	for	ADP
fcis-28514	79	8	fusion	fusion	NOUN
fcis-28514	79	9	,	,	PUNCT
fcis-28514	79	10	and	and	CCONJ
fcis-28514	79	11	then	then	ADV
fcis-28514	79	12	1×1	1×1	NUM
fcis-28514	79	13	convolution	convolution	NOUN
fcis-28514	79	14	is	be	AUX
fcis-28514	79	15	used	use	VERB
fcis-28514	79	16	to	to	PART
fcis-28514	79	17	promote	promote	VERB
fcis-28514	79	18	cross	cross	ADJ
fcis-28514	79	19	-	-	ADJ
fcis-28514	79	20	channel	channel	ADJ
fcis-28514	79	21	information	information	NOUN
fcis-28514	79	22	exchange	exchange	NOUN
fcis-28514	79	23	,	,	PUNCT
fcis-28514	79	24	which	which	PRON
fcis-28514	79	25	transfers	transfer	VERB
fcis-28514	79	26	the	the	DET
fcis-28514	79	27	shallow	shallow	ADJ
fcis-28514	79	28	large	large	ADJ
fcis-28514	79	29	object	object	NOUN
fcis-28514	79	30	feature	feature	NOUN
fcis-28514	79	31	to	to	ADP
fcis-28514	79	32	the	the	DET
fcis-28514	79	33	deep	deep	ADJ
fcis-28514	79	34	neural	neural	ADJ
fcis-28514	79	35	network	network	NOUN
fcis-28514	79	36	,	,	PUNCT
fcis-28514	79	37	and	and	CCONJ
fcis-28514	79	38	finally	finally	ADV
fcis-28514	79	39	outputs	output	VERB
fcis-28514	79	40	the	the	DET
fcis-28514	79	41	large	large	ADJ
fcis-28514	79	42	object	object	NOUN
fcis-28514	79	43	feature	feature	NOUN
fcis-28514	79	44	.	.	PUNCT
fcis-28514	80	1	backbone	backbone	NOUN
fcis-28514	80	2	of	of	ADP
fcis-28514	80	3	yolov8	yolov8	NOUN
fcis-28514	80	4	contains	contain	VERB
fcis-28514	80	5	four	four	NUM
fcis-28514	80	6	layers	layer	NOUN
fcis-28514	80	7	of	of	ADP
fcis-28514	80	8	the	the	DET
fcis-28514	80	9	same	same	ADJ
fcis-28514	80	10	structure	structure	NOUN
fcis-28514	80	11	,	,	PUNCT
fcis-28514	80	12	so	so	SCONJ
fcis-28514	80	13	this	this	DET
fcis-28514	80	14	paper	paper	NOUN
fcis-28514	80	15	sets	set	VERB
fcis-28514	80	16	up	up	ADP
fcis-28514	80	17	two	two	NUM
fcis-28514	80	18	ms	ms	NOUN
fcis-28514	80	19	modules	module	NOUN
fcis-28514	80	20	in	in	ADP
fcis-28514	80	21	the	the	DET
fcis-28514	80	22	improved	improved	ADJ
fcis-28514	80	23	model	model	NOUN
fcis-28514	80	24	,	,	PUNCT
fcis-28514	80	25	named	name	VERB
fcis-28514	80	26	ms-1	ms-1	NOUN
fcis-28514	80	27	and	and	CCONJ
fcis-28514	80	28	ms-2	ms-2	NOUN
fcis-28514	80	29	.	.	PUNCT
fcis-28514	81	1	the	the	DET
fcis-28514	81	2	separated	separate	VERB
fcis-28514	81	3	shallow	shallow	ADJ
fcis-28514	81	4	small	small	ADJ
fcis-28514	81	5	object	object	NOUN
fcis-28514	81	6	features	feature	NOUN
fcis-28514	81	7	and	and	CCONJ
fcis-28514	81	8	are	be	AUX
fcis-28514	81	9	the	the	DET
fcis-28514	81	10	inputs	input	NOUN
fcis-28514	81	11	of	of	ADP
fcis-28514	81	12	the	the	DET
fcis-28514	81	13	two	two	NUM
fcis-28514	81	14	de	de	ADJ
fcis-28514	81	15	modules	module	NOUN
fcis-28514	81	16	respectively	respectively	ADV
fcis-28514	81	17	.	.	PUNCT
fcis-28514	82	1	and	and	CCONJ
fcis-28514	82	2	the	the	DET
fcis-28514	82	3	large	large	ADJ
fcis-28514	82	4	object	object	NOUN
fcis-28514	82	5	feature	feature	NOUN
fcis-28514	82	6	information	information	NOUN
fcis-28514	82	7	output	output	NOUN
fcis-28514	82	8	by	by	ADP
fcis-28514	82	9	ms-2	ms-2	NOUN
fcis-28514	82	10	is	be	AUX
fcis-28514	82	11	transmitted	transmit	VERB
fcis-28514	82	12	to	to	ADP
fcis-28514	82	13	the	the	DET
fcis-28514	82	14	backbone	backbone	NOUN
fcis-28514	82	15	deep	deep	ADJ
fcis-28514	82	16	layer	layer	NOUN
fcis-28514	82	17	as	as	ADP
fcis-28514	82	18	the	the	DET
fcis-28514	82	19	input	input	NOUN
fcis-28514	82	20	of	of	ADP
fcis-28514	82	21	layer	layer	NOUN
fcis-28514	82	22	.	.	PUNCT
fcis-28514	83	1	2.3	2.3	NUM
fcis-28514	83	2	.	.	X
fcis-28514	83	3	de	de	NOUN
fcis-28514	83	4	module	module	NOUN
fcis-28514	83	5	compared	compare	VERB
fcis-28514	83	6	with	with	ADP
fcis-28514	83	7	large	large	ADJ
fcis-28514	83	8	and	and	CCONJ
fcis-28514	83	9	medium	medium	ADJ
fcis-28514	83	10	objects	object	NOUN
fcis-28514	83	11	,	,	PUNCT
fcis-28514	83	12	it	it	PRON
fcis-28514	83	13	is	be	AUX
fcis-28514	83	14	difficult	difficult	ADJ
fcis-28514	83	15	to	to	PART
fcis-28514	83	16	detect	detect	VERB
fcis-28514	83	17	small	small	ADJ
fcis-28514	83	18	objects	object	NOUN
fcis-28514	83	19	in	in	ADP
fcis-28514	83	20	pictures	picture	NOUN
fcis-28514	83	21	with	with	ADP
fcis-28514	83	22	low	low	ADJ
fcis-28514	83	23	resolution	resolution	NOUN
fcis-28514	83	24	and	and	CCONJ
fcis-28514	83	25	fuzzy	fuzzy	ADJ
fcis-28514	83	26	details	detail	NOUN
fcis-28514	83	27	,	,	PUNCT
fcis-28514	83	28	which	which	PRON
fcis-28514	83	29	is	be	AUX
fcis-28514	83	30	more	more	ADV
fcis-28514	83	31	difficult	difficult	ADJ
fcis-28514	83	32	to	to	PART
fcis-28514	83	33	be	be	AUX
fcis-28514	83	34	represented	represent	VERB
fcis-28514	83	35	and	and	CCONJ
fcis-28514	83	36	learned	learn	VERB
fcis-28514	83	37	by	by	ADP
fcis-28514	83	38	neural	neural	ADJ
fcis-28514	83	39	networks	network	NOUN
fcis-28514	83	40	.	.	PUNCT
fcis-28514	84	1	therefore	therefore	ADV
fcis-28514	84	2	,	,	PUNCT
fcis-28514	84	3	a	a	DET
fcis-28514	84	4	module	module	NOUN
fcis-28514	84	5	de	de	ADP
fcis-28514	84	6	designed	design	VERB
fcis-28514	84	7	to	to	PART
fcis-28514	84	8	backbone	backbone	VERB
fcis-28514	84	9	neck	neck	NOUN
fcis-28514	84	10	conv_3	conv_3	AUX
fcis-28514	84	11	c2f	c2f	PROPN
fcis-28514	84	12	sppf	sppf	PROPN
fcis-28514	84	13	conv_3	conv_3	AUX
fcis-28514	84	14	conv_3	conv_3	AUX
fcis-28514	84	15	c2f	c2f	PROPN
fcis-28514	84	16	conv_3	conv_3	VERB
fcis-28514	84	17	c2f	c2f	PROPN
fcis-28514	84	18	conv_3	conv_3	PROPN
fcis-28514	84	19	c2f	c2f	PROPN
fcis-28514	84	20	upsample	upsample	PROPN
fcis-28514	84	21	conv_3	conv_3	AUX
fcis-28514	84	22	conv_3	conv_3	VERB
fcis-28514	84	23	c2f	c2f	PROPN
fcis-28514	84	24	c2f	c2f	PROPN
fcis-28514	84	25	c2f	c2f	PROPN
fcis-28514	84	26	detect	detect	VERB
fcis-28514	84	27	c2f	c2f	NOUN
fcis-28514	84	28	detect	detect	PROPN
fcis-28514	84	29	detect	detect	NOUN
fcis-28514	84	30	upsample	upsample	NOUN
fcis-28514	84	31	'	'	PUNCT
fcis-28514	84	32	2p	2p	NUM
fcis-28514	84	33	'	'	PART
fcis-28514	84	34	3p	3p	NUM
fcis-28514	84	35	1f	1f	PROPN
fcis-28514	84	36	2f	2f	NUM
fcis-28514	84	37	3f	3f	PROPN
fcis-28514	84	38	4f	4f	NUM
fcis-28514	84	39	5f	5f	NOUN
fcis-28514	84	40	4f	4f	NUM
fcis-28514	84	41	3f	3f	PROPN
fcis-28514	84	42	5p	5p	NUM
fcis-28514	84	43	4p	4p	NUM
fcis-28514	84	44	3p	3p	NUM
fcis-28514	84	45	6p	6p	NUM
fcis-28514	84	46	2p	2p	NUM
fcis-28514	84	47	1p	1p	NUM
fcis-28514	84	48	'	'	PUNCT
fcis-28514	84	49	4p	4p	PROPN
fcis-28514	84	50	'	'	PART
fcis-28514	84	51	5p	5p	PROPN
fcis-28514	84	52	'	'	PUNCT
fcis-28514	84	53	6p6p	6p6p	NUM
fcis-28514	84	54	6f	6f	NUM
fcis-28514	84	55	1c	1c	NOUN
fcis-28514	84	56	2c	2c	NUM
fcis-28514	84	57	3c	3c	NUM
fcis-28514	84	58	4c	4c	NOUN
fcis-28514	84	59	5c	5c	PROPN
fcis-28514	84	60	6c	6c	NOUN
fcis-28514	84	61	82	82	NUM
fcis-28514	84	62	enhance	enhance	VERB
fcis-28514	84	63	the	the	DET
fcis-28514	84	64	features	feature	NOUN
fcis-28514	84	65	of	of	ADP
fcis-28514	84	66	small	small	ADJ
fcis-28514	84	67	objects	object	NOUN
fcis-28514	84	68	can	can	AUX
fcis-28514	84	69	fuse	fuse	VERB
fcis-28514	84	70	adjacent	adjacent	ADJ
fcis-28514	84	71	shallow	shallow	ADJ
fcis-28514	84	72	features	feature	NOUN
fcis-28514	84	73	and	and	CCONJ
fcis-28514	84	74	indirectly	indirectly	ADV
fcis-28514	84	75	alleviate	alleviate	VERB
fcis-28514	84	76	the	the	DET
fcis-28514	84	77	problem	problem	NOUN
fcis-28514	84	78	of	of	ADP
fcis-28514	84	79	unbalanced	unbalanced	ADJ
fcis-28514	84	80	feature	feature	NOUN
fcis-28514	84	81	representation	representation	NOUN
fcis-28514	84	82	.	.	PUNCT
fcis-28514	85	1	as	as	SCONJ
fcis-28514	85	2	shown	show	VERB
fcis-28514	85	3	in	in	ADP
fcis-28514	85	4	fig.5	fig.5	PROPN
fcis-28514	85	5	,	,	PUNCT
fcis-28514	85	6	and	and	CCONJ
fcis-28514	85	7	come	come	VERB
fcis-28514	85	8	from	from	ADP
fcis-28514	85	9	two	two	NUM
fcis-28514	85	10	adjacent	adjacent	ADJ
fcis-28514	85	11	shallow	shallow	ADJ
fcis-28514	85	12	layers	layer	NOUN
fcis-28514	85	13	,	,	PUNCT
fcis-28514	85	14	respectively	respectively	ADV
fcis-28514	85	15	,	,	PUNCT
fcis-28514	85	16	which	which	PRON
fcis-28514	85	17	contain	contain	VERB
fcis-28514	85	18	much	much	ADV
fcis-28514	85	19	richer	rich	ADJ
fcis-28514	85	20	information	information	NOUN
fcis-28514	85	21	about	about	ADP
fcis-28514	85	22	small	small	ADJ
fcis-28514	85	23	objects	object	NOUN
fcis-28514	85	24	than	than	ADP
fcis-28514	85	25	the	the	DET
fcis-28514	85	26	deep	deep	ADJ
fcis-28514	85	27	feature	feature	NOUN
fcis-28514	85	28	maps	map	NOUN
fcis-28514	85	29	.	.	PUNCT
fcis-28514	86	1	the	the	DET
fcis-28514	86	2	whole	whole	ADJ
fcis-28514	86	3	process	process	NOUN
fcis-28514	86	4	of	of	ADP
fcis-28514	86	5	detail	detail	NOUN
fcis-28514	86	6	enhancement	enhancement	NOUN
fcis-28514	86	7	is	be	AUX
fcis-28514	86	8	as	as	SCONJ
fcis-28514	86	9	follows	follow	VERB
fcis-28514	86	10	:	:	PUNCT
fcis-28514	86	11	fig	fig	NOUN
fcis-28514	86	12	5	5	NUM
fcis-28514	86	13	.	.	PUNCT
fcis-28514	86	14	de	de	NOUN
fcis-28514	86	15	module	module	NOUN
fcis-28514	86	16	(	(	PUNCT
fcis-28514	86	17	1	1	NUM
fcis-28514	86	18	)	)	PUNCT
fcis-28514	86	19	is	be	AUX
fcis-28514	86	20	up	up	ADV
fcis-28514	86	21	-	-	PUNCT
fcis-28514	86	22	sampled	sample	VERB
fcis-28514	86	23	and	and	CCONJ
fcis-28514	86	24	then	then	ADV
fcis-28514	86	25	concatenated	concatenate	VERB
fcis-28514	86	26	along	along	ADP
fcis-28514	86	27	the	the	DET
fcis-28514	86	28	channel	channel	NOUN
fcis-28514	86	29	dimension	dimension	NOUN
fcis-28514	86	30	to	to	PART
fcis-28514	86	31	obtain	obtain	VERB
fcis-28514	86	32	feature	feature	NOUN
fcis-28514	86	33	.	.	PUNCT
fcis-28514	87	1	is	be	AUX
fcis-28514	87	2	augmented	augment	VERB
fcis-28514	87	3	by	by	ADP
fcis-28514	87	4	adding	add	VERB
fcis-28514	87	5	itself	itself	PRON
fcis-28514	87	6	after	after	ADP
fcis-28514	87	7	global	global	ADJ
fcis-28514	87	8	average	average	ADJ
fcis-28514	87	9	pooling	pooling	NOUN
fcis-28514	87	10	,	,	PUNCT
fcis-28514	87	11	resulting	result	VERB
fcis-28514	87	12	in	in	ADP
fcis-28514	87	13	,	,	PUNCT
fcis-28514	87	14	thus	thus	ADV
fcis-28514	87	15	enhances	enhance	VERB
fcis-28514	87	16	the	the	DET
fcis-28514	87	17	semantic	semantic	ADJ
fcis-28514	87	18	information	information	NOUN
fcis-28514	87	19	of	of	ADP
fcis-28514	87	20	each	each	DET
fcis-28514	87	21	channel	channel	NOUN
fcis-28514	87	22	.	.	PUNCT
fcis-28514	88	1	(	(	PUNCT
fcis-28514	88	2	2	2	X
fcis-28514	88	3	)	)	PUNCT
fcis-28514	88	4	the	the	DET
fcis-28514	88	5	channel	channel	NOUN
fcis-28514	88	6	information	information	NOUN
fcis-28514	88	7	of	of	ADP
fcis-28514	88	8	feature	feature	NOUN
fcis-28514	88	9	graph	graph	NOUN
fcis-28514	88	10	is	be	AUX
fcis-28514	88	11	fully	fully	ADV
fcis-28514	88	12	fused	fuse	VERB
fcis-28514	88	13	using	use	VERB
fcis-28514	88	14	a	a	DET
fcis-28514	88	15	1×1	1×1	NUM
fcis-28514	88	16	convolution	convolution	NOUN
fcis-28514	88	17	,	,	PUNCT
fcis-28514	88	18	and	and	CCONJ
fcis-28514	88	19	then	then	ADV
fcis-28514	88	20	combined	combine	VERB
fcis-28514	88	21	with	with	ADP
fcis-28514	88	22	along	along	ADP
fcis-28514	88	23	the	the	DET
fcis-28514	88	24	channel	channel	NOUN
fcis-28514	88	25	dimension	dimension	NOUN
fcis-28514	88	26	to	to	PART
fcis-28514	88	27	obtain	obtain	VERB
fcis-28514	88	28	.	.	PUNCT
fcis-28514	89	1	considering	consider	VERB
fcis-28514	89	2	that	that	SCONJ
fcis-28514	89	3	feature	feature	NOUN
fcis-28514	89	4	maps	map	NOUN
fcis-28514	89	5	fusion	fusion	NOUN
fcis-28514	89	6	may	may	AUX
fcis-28514	89	7	cause	cause	VERB
fcis-28514	89	8	inconsistent	inconsistent	ADJ
fcis-28514	89	9	expression	expression	NOUN
fcis-28514	89	10	of	of	ADP
fcis-28514	89	11	features	feature	NOUN
fcis-28514	89	12	[	[	X
fcis-28514	89	13	7	7	NUM
fcis-28514	89	14	]	]	PUNCT
fcis-28514	89	15	,	,	PUNCT
fcis-28514	89	16	a	a	DET
fcis-28514	89	17	3×3	3×3	NUM
fcis-28514	89	18	convolution	convolution	NOUN
fcis-28514	89	19	kernel	kernel	NOUN
fcis-28514	89	20	is	be	AUX
fcis-28514	89	21	employed	employ	VERB
fcis-28514	89	22	to	to	PART
fcis-28514	89	23	eliminate	eliminate	VERB
fcis-28514	89	24	noise	noise	NOUN
fcis-28514	89	25	from	from	ADP
fcis-28514	89	26	the	the	DET
fcis-28514	89	27	fused	fuse	VERB
fcis-28514	89	28	feature	feature	NOUN
fcis-28514	89	29	vector	vector	NOUN
fcis-28514	89	30	,	,	PUNCT
fcis-28514	89	31	yielding	yield	VERB
fcis-28514	89	32	the	the	DET
fcis-28514	89	33	final	final	ADJ
fcis-28514	89	34	output	output	NOUN
fcis-28514	89	35	as	as	ADP
fcis-28514	89	36	of	of	ADP
fcis-28514	89	37	the	the	DET
fcis-28514	89	38	de	de	NOUN
fcis-28514	89	39	module	module	NOUN
fcis-28514	89	40	.	.	PUNCT
fcis-28514	90	1	the	the	DET
fcis-28514	90	2	improved	improved	ADJ
fcis-28514	90	3	model	model	NOUN
fcis-28514	90	4	also	also	ADV
fcis-28514	90	5	incorporates	incorporate	VERB
fcis-28514	90	6	two	two	NUM
fcis-28514	90	7	de	de	ADJ
fcis-28514	90	8	modules	module	NOUN
fcis-28514	90	9	,	,	PUNCT
fcis-28514	90	10	named	name	VERB
fcis-28514	90	11	de-1	de-1	ADP
fcis-28514	90	12	and	and	CCONJ
fcis-28514	90	13	de-2	de-2	PRON
fcis-28514	90	14	,	,	PUNCT
fcis-28514	90	15	which	which	PRON
fcis-28514	90	16	enhance	enhance	VERB
fcis-28514	90	17	the	the	DET
fcis-28514	90	18	small	small	ADJ
fcis-28514	90	19	object	object	NOUN
fcis-28514	90	20	features	feature	VERB
fcis-28514	90	21	from	from	ADP
fcis-28514	90	22	the	the	DET
fcis-28514	90	23	two	two	NUM
fcis-28514	90	24	ms	ms	NOUN
fcis-28514	90	25	modules	module	NOUN
fcis-28514	90	26	and	and	CCONJ
fcis-28514	90	27	the	the	DET
fcis-28514	90	28	layer	layer	NOUN
fcis-28514	90	29	output	output	NOUN
fcis-28514	90	30	.	.	PUNCT
fcis-28514	91	1	the	the	DET
fcis-28514	91	2	de	de	PROPN
fcis-28514	91	3	module	module	NOUN
fcis-28514	91	4	receives	receive	VERB
fcis-28514	91	5	and	and	CCONJ
fcis-28514	91	6	enhances	enhance	VERB
fcis-28514	91	7	the	the	DET
fcis-28514	91	8	feature	feature	NOUN
fcis-28514	91	9	information	information	NOUN
fcis-28514	91	10	of	of	ADP
fcis-28514	91	11	small	small	ADJ
fcis-28514	91	12	objects	object	NOUN
fcis-28514	91	13	from	from	ADP
fcis-28514	91	14	,	,	PUNCT
fcis-28514	91	15	and	and	CCONJ
fcis-28514	91	16	layers	layer	NOUN
fcis-28514	91	17	.	.	PUNCT
fcis-28514	92	1	the	the	DET
fcis-28514	92	2	output	output	NOUN
fcis-28514	92	3	of	of	ADP
fcis-28514	92	4	de	de	NOUN
fcis-28514	92	5	module	module	NOUN
fcis-28514	92	6	can	can	AUX
fcis-28514	92	7	provide	provide	VERB
fcis-28514	92	8	rich	rich	ADJ
fcis-28514	92	9	semantic	semantic	ADJ
fcis-28514	92	10	and	and	CCONJ
fcis-28514	92	11	detailed	detailed	ADJ
fcis-28514	92	12	information	information	NOUN
fcis-28514	92	13	of	of	ADP
fcis-28514	92	14	small	small	ADJ
fcis-28514	92	15	objects	object	NOUN
fcis-28514	92	16	to	to	ADP
fcis-28514	92	17	the	the	DET
fcis-28514	92	18	detection	detection	NOUN
fcis-28514	92	19	layer	layer	NOUN
fcis-28514	92	20	,	,	PUNCT
fcis-28514	92	21	thus	thus	ADV
fcis-28514	92	22	improving	improve	VERB
fcis-28514	92	23	the	the	DET
fcis-28514	92	24	small	small	ADJ
fcis-28514	92	25	object	object	NOUN
fcis-28514	92	26	detection	detection	NOUN
fcis-28514	92	27	performance	performance	NOUN
fcis-28514	92	28	of	of	ADP
fcis-28514	92	29	the	the	DET
fcis-28514	92	30	model	model	NOUN
fcis-28514	92	31	.	.	PUNCT
fcis-28514	93	1	3	3	X
fcis-28514	93	2	.	.	X
fcis-28514	93	3	experiment	experiment	NOUN
fcis-28514	93	4	and	and	CCONJ
fcis-28514	93	5	result	result	VERB
fcis-28514	93	6	3.1	3.1	NUM
fcis-28514	93	7	.	.	PUNCT
fcis-28514	94	1	dataset	dataset	VERB
fcis-28514	94	2	introduction	introduction	NOUN
fcis-28514	94	3	and	and	CCONJ
fcis-28514	94	4	processing	process	VERB
fcis-28514	94	5	the	the	DET
fcis-28514	94	6	experimental	experimental	ADJ
fcis-28514	94	7	data	datum	NOUN
fcis-28514	94	8	are	be	AUX
fcis-28514	94	9	obtained	obtain	VERB
fcis-28514	94	10	from	from	ADP
fcis-28514	94	11	the	the	DET
fcis-28514	94	12	open	open	ADJ
fcis-28514	94	13	-	-	PUNCT
fcis-28514	94	14	source	source	NOUN
fcis-28514	94	15	remote	remote	ADJ
fcis-28514	94	16	sensing	sense	VERB
fcis-28514	94	17	dataset	dataset	NOUN
fcis-28514	94	18	called	call	VERB
fcis-28514	94	19	uavod-10	uavod-10	PROPN
fcis-28514	95	1	[	[	X
fcis-28514	95	2	16	16	NUM
fcis-28514	95	3	]	]	PUNCT
fcis-28514	95	4	and	and	CCONJ
fcis-28514	95	5	the	the	DET
fcis-28514	95	6	small	small	ADJ
fcis-28514	95	7	object	object	NOUN
fcis-28514	95	8	dataset	dataset	VERB
fcis-28514	95	9	[	[	X
fcis-28514	95	10	17	17	NUM
fcis-28514	95	11	]	]	PUNCT
fcis-28514	95	12	,	,	PUNCT
fcis-28514	95	13	both	both	PRON
fcis-28514	95	14	are	be	AUX
fcis-28514	95	15	divided	divide	VERB
fcis-28514	95	16	into	into	ADP
fcis-28514	95	17	training	training	NOUN
fcis-28514	95	18	,	,	PUNCT
fcis-28514	95	19	validation	validation	NOUN
fcis-28514	95	20	,	,	PUNCT
fcis-28514	95	21	and	and	CCONJ
fcis-28514	95	22	test	test	NOUN
fcis-28514	95	23	sets	set	NOUN
fcis-28514	95	24	according	accord	VERB
fcis-28514	95	25	to	to	ADP
fcis-28514	95	26	7:2:1	7:2:1	NUM
fcis-28514	95	27	.	.	PUNCT
fcis-28514	96	1	the	the	DET
fcis-28514	96	2	uavod-10	uavod-10	PROPN
fcis-28514	96	3	dataset	dataset	NOUN
fcis-28514	96	4	consists	consist	VERB
fcis-28514	96	5	of	of	ADP
fcis-28514	96	6	a	a	DET
fcis-28514	96	7	total	total	NOUN
fcis-28514	96	8	of	of	ADP
fcis-28514	96	9	844	844	NUM
fcis-28514	96	10	images	image	NOUN
fcis-28514	96	11	labeling	label	VERB
fcis-28514	96	12	10	10	NUM
fcis-28514	96	13	types	type	NOUN
fcis-28514	96	14	of	of	ADP
fcis-28514	96	15	targets	target	NOUN
fcis-28514	96	16	such	such	ADJ
fcis-28514	96	17	as	as	ADP
fcis-28514	96	18	buildings	building	NOUN
fcis-28514	96	19	,	,	PUNCT
fcis-28514	96	20	boats	boat	NOUN
fcis-28514	96	21	,	,	PUNCT
fcis-28514	96	22	vehicles	vehicle	NOUN
fcis-28514	96	23	,	,	PUNCT
fcis-28514	96	24	and	and	CCONJ
fcis-28514	96	25	wells	well	NOUN
fcis-28514	96	26	,	,	PUNCT
fcis-28514	96	27	which	which	PRON
fcis-28514	96	28	are	be	AUX
fcis-28514	96	29	sufficiently	sufficiently	ADV
fcis-28514	96	30	varied	varied	ADJ
fcis-28514	96	31	in	in	ADP
fcis-28514	96	32	size	size	NOUN
fcis-28514	96	33	,	,	PUNCT
fcis-28514	96	34	shape	shape	NOUN
fcis-28514	96	35	,	,	PUNCT
fcis-28514	96	36	and	and	CCONJ
fcis-28514	96	37	texture	texture	NOUN
fcis-28514	96	38	,	,	PUNCT
fcis-28514	96	39	and	and	CCONJ
fcis-28514	96	40	are	be	AUX
fcis-28514	96	41	disturbed	disturb	VERB
fcis-28514	96	42	by	by	ADP
fcis-28514	96	43	imaging	imaging	NOUN
fcis-28514	96	44	conditions	condition	NOUN
fcis-28514	96	45	and	and	CCONJ
fcis-28514	96	46	complex	complex	ADJ
fcis-28514	96	47	environments	environment	NOUN
fcis-28514	96	48	.	.	PUNCT
fcis-28514	97	1	the	the	DET
fcis-28514	97	2	small	small	ADJ
fcis-28514	97	3	target	target	NOUN
fcis-28514	97	4	dataset	dataset	VERB
fcis-28514	97	5	small	small	ADJ
fcis-28514	97	6	object	object	NOUN
fcis-28514	97	7	has	have	VERB
fcis-28514	97	8	three	three	NUM
fcis-28514	97	9	categories	category	NOUN
fcis-28514	97	10	of	of	ADP
fcis-28514	97	11	targets	target	NOUN
fcis-28514	97	12	such	such	ADJ
fcis-28514	97	13	as	as	ADP
fcis-28514	97	14	bees	bee	NOUN
fcis-28514	97	15	,	,	PUNCT
fcis-28514	97	16	flying	fly	VERB
fcis-28514	97	17	insects	insect	NOUN
fcis-28514	97	18	,	,	PUNCT
fcis-28514	97	19	and	and	CCONJ
fcis-28514	97	20	ornamental	ornamental	ADJ
fcis-28514	97	21	fish	fish	NOUN
fcis-28514	97	22	,	,	PUNCT
fcis-28514	97	23	and	and	CCONJ
fcis-28514	97	24	the	the	DET
fcis-28514	97	25	targets	target	NOUN
fcis-28514	97	26	account	account	VERB
fcis-28514	97	27	for	for	ADP
fcis-28514	97	28	fewer	few	ADJ
fcis-28514	97	29	pixels	pixel	NOUN
fcis-28514	97	30	,	,	PUNCT
fcis-28514	97	31	and	and	CCONJ
fcis-28514	97	32	some	some	PRON
fcis-28514	97	33	of	of	ADP
fcis-28514	97	34	them	they	PRON
fcis-28514	97	35	have	have	VERB
fcis-28514	97	36	occlusion	occlusion	NOUN
fcis-28514	97	37	problems	problem	NOUN
fcis-28514	97	38	and	and	CCONJ
fcis-28514	97	39	inconsistent	inconsistent	ADJ
fcis-28514	97	40	densities	density	NOUN
fcis-28514	97	41	.	.	PUNCT
fcis-28514	98	1	due	due	ADP
fcis-28514	98	2	to	to	ADP
fcis-28514	98	3	the	the	DET
fcis-28514	98	4	limited	limited	ADJ
fcis-28514	98	5	number	number	NOUN
fcis-28514	98	6	of	of	ADP
fcis-28514	98	7	images	image	NOUN
fcis-28514	98	8	in	in	ADP
fcis-28514	98	9	the	the	DET
fcis-28514	98	10	original	original	ADJ
fcis-28514	98	11	dataset	dataset	NOUN
fcis-28514	98	12	,	,	PUNCT
fcis-28514	98	13	three	three	NUM
fcis-28514	98	14	enhancement	enhancement	NOUN
fcis-28514	98	15	methods	method	NOUN
fcis-28514	98	16	called	call	VERB
fcis-28514	98	17	flip	flip	NOUN
fcis-28514	98	18	,	,	PUNCT
fcis-28514	98	19	hue	hue	NOUN
fcis-28514	98	20	and	and	CCONJ
fcis-28514	98	21	brightness	brightness	NOUN
fcis-28514	98	22	are	be	AUX
fcis-28514	98	23	used	use	VERB
fcis-28514	98	24	to	to	PART
fcis-28514	98	25	expand	expand	VERB
fcis-28514	98	26	the	the	DET
fcis-28514	98	27	dataset	dataset	NOUN
fcis-28514	98	28	to	to	ADP
fcis-28514	98	29	900	900	NUM
fcis-28514	98	30	images	image	NOUN
fcis-28514	98	31	,	,	PUNCT
fcis-28514	98	32	and	and	CCONJ
fcis-28514	98	33	the	the	DET
fcis-28514	98	34	enhancement	enhancement	NOUN
fcis-28514	98	35	effect	effect	NOUN
fcis-28514	98	36	is	be	AUX
fcis-28514	98	37	shown	show	VERB
fcis-28514	98	38	in	in	ADP
fcis-28514	98	39	fig	fig	NOUN
fcis-28514	98	40	.	.	PUNCT
fcis-28514	99	1	6	6	NUM
fcis-28514	99	2	.	.	X
fcis-28514	99	3	fig	fig	NOUN
fcis-28514	99	4	6	6	NUM
fcis-28514	99	5	.	.	PUNCT
fcis-28514	100	1	examples	example	NOUN
fcis-28514	100	2	of	of	ADP
fcis-28514	100	3	image	image	NOUN
fcis-28514	100	4	enhancement	enhancement	NOUN
fcis-28514	100	5	3.2	3.2	NUM
fcis-28514	100	6	.	.	PUNCT
fcis-28514	101	1	experimental	experimental	ADJ
fcis-28514	101	2	parameter	parameter	NOUN
fcis-28514	101	3	settings	setting	NOUN
fcis-28514	101	4	this	this	DET
fcis-28514	101	5	paper	paper	NOUN
fcis-28514	101	6	builds	build	VERB
fcis-28514	101	7	a	a	DET
fcis-28514	101	8	neural	neural	ADJ
fcis-28514	101	9	network	network	NOUN
fcis-28514	101	10	model	model	NOUN
fcis-28514	101	11	based	base	VERB
fcis-28514	101	12	on	on	ADP
fcis-28514	101	13	the	the	DET
fcis-28514	101	14	pytorch	pytorch	NOUN
fcis-28514	101	15	framework	framework	NOUN
fcis-28514	101	16	,	,	PUNCT
fcis-28514	101	17	using	use	VERB
fcis-28514	101	18	pycharm	pycharm	PROPN
fcis-28514	101	19	2021	2021	NUM
fcis-28514	101	20	professional	professional	NOUN
fcis-28514	101	21	as	as	ADP
fcis-28514	101	22	the	the	DET
fcis-28514	101	23	development	development	NOUN
fcis-28514	101	24	tool	tool	NOUN
fcis-28514	101	25	,	,	PUNCT
fcis-28514	101	26	with	with	ADP
fcis-28514	101	27	an	an	DET
fcis-28514	101	28	nvidia	nvidia	PROPN
fcis-28514	101	29	geforce	geforce	NOUN
fcis-28514	101	30	rtx	rtx	PROPN
fcis-28514	101	31	2060	2060	NUM
fcis-28514	101	32	gpu	gpu	NOUN
fcis-28514	101	33	and	and	CCONJ
fcis-28514	101	34	12	12	NUM
fcis-28514	101	35	gb	gb	NOUN
fcis-28514	101	36	of	of	ADP
fcis-28514	101	37	vram	vram	NOUN
fcis-28514	101	38	.	.	PUNCT
fcis-28514	102	1	the	the	DET
fcis-28514	102	2	python	python	PROPN
fcis-28514	102	3	version	version	NOUN
fcis-28514	102	4	is	be	AUX
fcis-28514	102	5	3.8.18	3.8.18	NUM
fcis-28514	102	6	,	,	PUNCT
fcis-28514	102	7	and	and	CCONJ
fcis-28514	102	8	the	the	DET
fcis-28514	102	9	pytorch	pytorch	NOUN
fcis-28514	102	10	version	version	NOUN
fcis-28514	102	11	is	be	AUX
fcis-28514	102	12	1.12.1	1.12.1	NUM
fcis-28514	102	13	.	.	PUNCT
fcis-28514	103	1	the	the	DET
fcis-28514	103	2	experimental	experimental	ADJ
fcis-28514	103	3	setup	setup	NOUN
fcis-28514	103	4	specifies	specify	VERB
fcis-28514	103	5	a	a	DET
fcis-28514	103	6	batch	batch	NOUN
fcis-28514	103	7	size	size	NOUN
fcis-28514	103	8	of	of	ADP
fcis-28514	103	9	16	16	NUM
fcis-28514	103	10	,	,	PUNCT
fcis-28514	103	11	with	with	ADP
fcis-28514	103	12	an	an	DET
fcis-28514	103	13	initial	initial	ADJ
fcis-28514	103	14	learning	learning	NOUN
fcis-28514	103	15	rate	rate	NOUN
fcis-28514	103	16	of	of	ADP
fcis-28514	103	17	0.01	0.01	NUM
fcis-28514	103	18	and	and	CCONJ
fcis-28514	103	19	a	a	DET
fcis-28514	103	20	final	final	ADJ
fcis-28514	103	21	learning	learning	NOUN
fcis-28514	103	22	rate	rate	NOUN
fcis-28514	103	23	of	of	ADP
fcis-28514	103	24	0.0001	0.0001	NUM
fcis-28514	103	25	.	.	PUNCT
fcis-28514	104	1	observing	observe	VERB
fcis-28514	104	2	the	the	DET
fcis-28514	104	3	loss	loss	NOUN
fcis-28514	104	4	curve	curve	NOUN
fcis-28514	104	5	in	in	ADP
fcis-28514	104	6	fig	fig	NOUN
fcis-28514	104	7	.	.	PUNCT
fcis-28514	105	1	7	7	NUM
fcis-28514	105	2	,	,	PUNCT
fcis-28514	105	3	it	it	PRON
fcis-28514	105	4	's	be	AUX
fcis-28514	105	5	noted	note	VERB
fcis-28514	105	6	that	that	SCONJ
fcis-28514	105	7	the	the	DET
fcis-28514	105	8	validation	validation	NOUN
fcis-28514	105	9	loss	loss	NOUN
fcis-28514	105	10	begins	begin	VERB
fcis-28514	105	11	to	to	PART
fcis-28514	105	12	stabilize	stabilize	VERB
fcis-28514	105	13	within	within	ADP
fcis-28514	105	14	the	the	DET
fcis-28514	105	15	iteration	iteration	NOUN
fcis-28514	105	16	range	range	NOUN
fcis-28514	105	17	of	of	ADP
fcis-28514	105	18	150	150	NUM
fcis-28514	105	19	to	to	ADP
fcis-28514	105	20	200	200	NUM
fcis-28514	105	21	,	,	PUNCT
fcis-28514	105	22	suggesting	suggest	VERB
fcis-28514	105	23	that	that	SCONJ
fcis-28514	105	24	the	the	DET
fcis-28514	105	25	network	network	NOUN
fcis-28514	105	26	training	training	NOUN
fcis-28514	105	27	is	be	AUX
fcis-28514	105	28	sufficiently	sufficiently	ADV
fcis-28514	105	29	thorough	thorough	ADJ
fcis-28514	105	30	.	.	PUNCT
fcis-28514	106	1	consequently	consequently	ADV
fcis-28514	106	2	,	,	PUNCT
fcis-28514	106	3	the	the	DET
fcis-28514	106	4	number	number	NOUN
fcis-28514	106	5	of	of	ADP
fcis-28514	106	6	epochs	epoch	NOUN
fcis-28514	106	7	is	be	AUX
fcis-28514	106	8	set	set	VERB
fcis-28514	106	9	to	to	ADP
fcis-28514	106	10	200	200	NUM
fcis-28514	106	11	.	.	PUNCT
fcis-28514	107	1	fig	fig	PROPN
fcis-28514	107	2	7	7	NUM
fcis-28514	107	3	.	.	PUNCT
fcis-28514	108	1	training	train	VERB
fcis-28514	108	2	loss	loss	NOUN
fcis-28514	108	3	curve	curve	NOUN
fcis-28514	108	4	and	and	CCONJ
fcis-28514	108	5	validation	validation	NOUN
fcis-28514	108	6	loss	loss	NOUN
fcis-28514	108	7	curve	curve	NOUN
fcis-28514	108	8	3.3	3.3	NUM
fcis-28514	108	9	.	.	PUNCT
fcis-28514	109	1	analysis	analysis	NOUN
fcis-28514	109	2	of	of	ADP
fcis-28514	109	3	experimental	experimental	ADJ
fcis-28514	109	4	results	result	NOUN
fcis-28514	109	5	in	in	ADP
fcis-28514	109	6	this	this	DET
fcis-28514	109	7	study	study	NOUN
fcis-28514	109	8	,	,	PUNCT
fcis-28514	109	9	we	we	PRON
fcis-28514	109	10	've	have	AUX
fcis-28514	109	11	selected	select	VERB
fcis-28514	109	12	the	the	DET
fcis-28514	109	13	yolov8n	yolov8n	PROPN
fcis-28514	109	14	model	model	NOUN
fcis-28514	109	15	as	as	ADP
fcis-28514	109	16	our	our	PRON
fcis-28514	109	17	benchmark	benchmark	NOUN
fcis-28514	109	18	and	and	CCONJ
fcis-28514	109	19	compared	compare	VERB
fcis-28514	109	20	it	it	PRON
fcis-28514	109	21	with	with	ADP
fcis-28514	109	22	seven	seven	NUM
fcis-28514	109	23	other	other	ADJ
fcis-28514	109	24	mainstream	mainstream	NOUN
fcis-28514	109	25	algorithms	algorithm	NOUN
fcis-28514	109	26	,	,	PUNCT
fcis-28514	109	27	including	include	VERB
fcis-28514	109	28	the	the	DET
fcis-28514	109	29	two	two	NUM
fcis-28514	109	30	-	-	PUNCT
fcis-28514	109	31	stage	stage	NOUN
fcis-28514	109	32	classic	classic	ADJ
fcis-28514	109	33	model	model	NOUN
fcis-28514	109	34	fasterrcnn	fasterrcnn	PROPN
fcis-28514	109	35	,	,	PUNCT
fcis-28514	109	36	the	the	DET
fcis-28514	109	37	single	single	ADJ
fcis-28514	109	38	-	-	PUNCT
fcis-28514	109	39	stage	stage	NOUN
fcis-28514	109	40	models	model	NOUN
fcis-28514	109	41	from	from	ADP
fcis-28514	109	42	the	the	DET
fcis-28514	109	43	yolov5	yolov5	NOUN
fcis-28514	109	44	to	to	ADP
fcis-28514	109	45	yolov8	yolov8	PROPN
fcis-28514	109	46	series	series	PROPN
fcis-28514	109	47	,	,	PUNCT
fcis-28514	109	48	and	and	CCONJ
fcis-28514	109	49	the	the	DET
fcis-28514	109	50	small	small	ADJ
fcis-28514	109	51	dense	dense	ADJ
fcis-28514	109	52	object	object	NOUN
fcis-28514	109	53	detection	detection	NOUN
fcis-28514	109	54	models	model	NOUN
fcis-28514	109	55	tph	tph	NOUN
fcis-28514	109	56	-	-	PUNCT
fcis-28514	109	57	yolov5	yolov5	NOUN
fcis-28514	110	1	[	[	X
fcis-28514	110	2	18	18	NUM
fcis-28514	110	3	]	]	PUNCT
fcis-28514	110	4	,	,	PUNCT
fcis-28514	110	5	drone	drone	NOUN
fcis-28514	110	6	-	-	PUNCT
fcis-28514	110	7	yolo	yolo	NOUN
fcis-28514	111	1	[	[	X
fcis-28514	111	2	19	19	NUM
fcis-28514	111	3	]	]	PUNCT
fcis-28514	111	4	,	,	PUNCT
fcis-28514	111	5	and	and	CCONJ
fcis-28514	111	6	yolov8bifpn	yolov8bifpn	PROPN
fcis-28514	111	7	.	.	PROPN
fcis-28514	111	8	table	table	NOUN
fcis-28514	111	9	1	1	NUM
fcis-28514	111	10	presents	present	VERB
fcis-28514	111	11	a	a	DET
fcis-28514	111	12	comparison	comparison	NOUN
fcis-28514	111	13	of	of	ADP
fcis-28514	111	14	the	the	DET
fcis-28514	111	15	total	total	ADJ
fcis-28514	111	16	detection	detection	NOUN
fcis-28514	111	17	accuracies	accuracy	NOUN
fcis-28514	111	18	for	for	ADP
fcis-28514	111	19	these	these	DET
fcis-28514	111	20	models	model	NOUN
fcis-28514	111	21	,	,	PUNCT
fcis-28514	111	22	as	as	ADV
fcis-28514	111	23	well	well	ADV
fcis-28514	111	24	as	as	ADP
fcis-28514	111	25	the	the	DET
fcis-28514	111	26	detection	detection	NOUN
fcis-28514	111	27	accuracies	accuracy	NOUN
fcis-28514	111	28	for	for	ADP
fcis-28514	111	29	each	each	DET
fcis-28514	111	30	category	category	NOUN
fcis-28514	111	31	,	,	PUNCT
fcis-28514	111	32	based	base	VERB
fcis-28514	111	33	on	on	ADP
fcis-28514	111	34	the	the	DET
fcis-28514	111	35	uavod-10	uavod-10	PROPN
fcis-28514	111	36	dataset	dataset	NOUN
fcis-28514	111	37	.	.	PUNCT
fcis-28514	112	1	83	83	NUM
fcis-28514	112	2	table	table	NOUN
fcis-28514	112	3	1	1	NUM
fcis-28514	112	4	.	.	PUNCT
fcis-28514	112	5	comparison	comparison	NOUN
fcis-28514	112	6	of	of	ADP
fcis-28514	112	7	the	the	DET
fcis-28514	112	8	accuracy	accuracy	NOUN
fcis-28514	112	9	of	of	ADP
fcis-28514	112	10	each	each	DET
fcis-28514	112	11	model	model	NOUN
fcis-28514	112	12	on	on	ADP
fcis-28514	112	13	the	the	DET
fcis-28514	112	14	uavod-10	uavod-10	PROPN
fcis-28514	112	15	dataset	dataset	NOUN
fcis-28514	112	16	model	model	NOUN
fcis-28514	112	17	map/%	map/%	PROPN
fcis-28514	112	18	building	building	PROPN
fcis-28514	112	19	ship	ship	NOUN
fcis-28514	112	20	vehicle	vehicle	NOUN
fcis-28514	112	21	prefabricated	prefabricate	VERB
fcis-28514	112	22	house	house	NOUN
fcis-28514	112	23	well	well	PROPN
fcis-28514	112	24	cable	cable	NOUN
fcis-28514	112	25	tower	tower	NOUN
fcis-28514	112	26	pool	pool	NOUN
fcis-28514	112	27	cultivation	cultivation	NOUN
fcis-28514	112	28	mesh	mesh	NOUN
fcis-28514	112	29	cage	cage	NOUN
fcis-28514	112	30	quarry	quarry	NOUN
fcis-28514	112	31	fasterrcnn	fasterrcnn	VERB
fcis-28514	113	1	24.3	24.3	NUM
fcis-28514	113	2	32.4	32.4	NUM
fcis-28514	113	3	6.4	6.4	NUM
fcis-28514	113	4	0	0	NUM
fcis-28514	113	5	13.4	13.4	NUM
fcis-28514	113	6	8.2	8.2	NUM
fcis-28514	113	7	25.9	25.9	NUM
fcis-28514	113	8	38.9	38.9	NUM
fcis-28514	113	9	42.7	42.7	NUM
fcis-28514	113	10	50.9	50.9	NUM
fcis-28514	113	11	yolov5n	yolov5n	NOUN
fcis-28514	113	12	27.4	27.4	NUM
fcis-28514	113	13	61.4	61.4	NUM
fcis-28514	113	14	5.4	5.4	NUM
fcis-28514	113	15	0	0	NUM
fcis-28514	113	16	70.4	70.4	NUM
fcis-28514	113	17	4.4	4.4	NUM
fcis-28514	113	18	5.8	5.8	NUM
fcis-28514	113	19	16.6	16.6	NUM
fcis-28514	113	20	41.8	41.8	NUM
fcis-28514	113	21	40.7	40.7	NUM
fcis-28514	113	22	yolov5s	yolov5s	NOUN
fcis-28514	113	23	33.6	33.6	NUM
fcis-28514	113	24	67.9	67.9	NUM
fcis-28514	113	25	6.3	6.3	NUM
fcis-28514	113	26	0.1	0.1	NUM
fcis-28514	113	27	76.9	76.9	NUM
fcis-28514	113	28	5.1	5.1	NUM
fcis-28514	113	29	18.5	18.5	NUM
fcis-28514	113	30	24.9	24.9	NUM
fcis-28514	113	31	55.5	55.5	NUM
fcis-28514	113	32	46.8	46.8	NUM
fcis-28514	113	33	yolov6n	yolov6n	PROPN
fcis-28514	113	34	26.7	26.7	NUM
fcis-28514	113	35	59.4	59.4	NUM
fcis-28514	113	36	9.2	9.2	NUM
fcis-28514	113	37	0	0	NUM
fcis-28514	113	38	74	74	NUM
fcis-28514	113	39	22.3	22.3	NUM
fcis-28514	113	40	2	2	NUM
fcis-28514	113	41	1.4	1.4	NUM
fcis-28514	113	42	30.8	30.8	NUM
fcis-28514	113	43	32.4	32.4	NUM
fcis-28514	113	44	yolov7tiny	yolov7tiny	PROPN
fcis-28514	113	45	37.1	37.1	NUM
fcis-28514	113	46	63.6	63.6	NUM
fcis-28514	113	47	7.1	7.1	NUM
fcis-28514	113	48	0	0	NUM
fcis-28514	114	1	73.5	73.5	NUM
fcis-28514	114	2	13.2	13.2	NUM
fcis-28514	114	3	25.4	25.4	NUM
fcis-28514	114	4	24.8	24.8	NUM
fcis-28514	114	5	54.9	54.9	NUM
fcis-28514	114	6	71.7	71.7	NUM
fcis-28514	114	7	yolov8n	yolov8n	NOUN
fcis-28514	114	8	37.8	37.8	NUM
fcis-28514	114	9	68.1	68.1	NUM
fcis-28514	114	10	18.5	18.5	NUM
fcis-28514	114	11	0.19	0.19	NUM
fcis-28514	114	12	79.4	79.4	NUM
fcis-28514	114	13	38.7	38.7	NUM
fcis-28514	114	14	13.7	13.7	NUM
fcis-28514	114	15	25.0	25.0	NUM
fcis-28514	114	16	59.8	59.8	NUM
fcis-28514	114	17	37.0	37.0	NUM
fcis-28514	114	18	tphyolov5n	tphyolov5n	NOUN
fcis-28514	114	19	22.9	22.9	NUM
fcis-28514	114	20	65.6	65.6	NUM
fcis-28514	114	21	2.91	2.91	NUM
fcis-28514	114	22	0	0	NUM
fcis-28514	114	23	76	76	NUM
fcis-28514	114	24	3.2	3.2	NUM
fcis-28514	114	25	18.9	18.9	NUM
fcis-28514	114	26	0	0	NUM
fcis-28514	114	27	23.7	23.7	NUM
fcis-28514	114	28	15.3	15.3	NUM
fcis-28514	114	29	tphyolov5s	tphyolov5s	PROPN
fcis-28514	114	30	33.6	33.6	NUM
fcis-28514	114	31	72	72	NUM
fcis-28514	114	32	12	12	NUM
fcis-28514	114	33	0.1	0.1	NUM
fcis-28514	114	34	77.4	77.4	NUM
fcis-28514	114	35	24.3	24.3	NUM
fcis-28514	114	36	33.6	33.6	NUM
fcis-28514	114	37	0	0	NUM
fcis-28514	114	38	38.7	38.7	NUM
fcis-28514	114	39	44.1	44.1	NUM
fcis-28514	114	40	droneyolo	droneyolo	NOUN
fcis-28514	114	41	38	38	NUM
fcis-28514	114	42	69.3	69.3	NUM
fcis-28514	114	43	35.1	35.1	NUM
fcis-28514	114	44	0.1	0.1	NUM
fcis-28514	114	45	80.9	80.9	NUM
fcis-28514	114	46	42.1	42.1	NUM
fcis-28514	114	47	28.3	28.3	NUM
fcis-28514	114	48	19.2	19.2	NUM
fcis-28514	114	49	41.8	41.8	NUM
fcis-28514	114	50	25	25	NUM
fcis-28514	114	51	yolov8bifpn	yolov8bifpn	PROPN
fcis-28514	114	52	44.1	44.1	NUM
fcis-28514	114	53	71.8	71.8	NUM
fcis-28514	114	54	22.9	22.9	NUM
fcis-28514	114	55	0.24	0.24	NUM
fcis-28514	114	56	75.1	75.1	NUM
fcis-28514	114	57	32.5	32.5	NUM
fcis-28514	114	58	34.9	34.9	NUM
fcis-28514	114	59	50.1	50.1	NUM
fcis-28514	114	60	66.7	66.7	NUM
fcis-28514	114	61	62.2	62.2	NUM
fcis-28514	114	62	ours	ours	PRON
fcis-28514	114	63	47.3	47.3	NUM
fcis-28514	114	64	71.9	71.9	NUM
fcis-28514	114	65	31.6	31.6	NUM
fcis-28514	114	66	0.21	0.21	NUM
fcis-28514	114	67	78.6	78.6	NUM
fcis-28514	114	68	39.3	39.3	NUM
fcis-28514	114	69	29	29	NUM
fcis-28514	114	70	66.6	66.6	NUM
fcis-28514	114	71	66.7	66.7	NUM
fcis-28514	114	72	52.7	52.7	NUM
fcis-28514	114	73	the	the	DET
fcis-28514	114	74	improved	improved	ADJ
fcis-28514	114	75	model	model	NOUN
fcis-28514	114	76	achieved	achieve	VERB
fcis-28514	114	77	a	a	DET
fcis-28514	114	78	9.5	9.5	NUM
fcis-28514	114	79	%	%	NOUN
fcis-28514	114	80	increase	increase	NOUN
fcis-28514	114	81	in	in	ADP
fcis-28514	114	82	map	map	NOUN
fcis-28514	114	83	compared	compare	VERB
fcis-28514	114	84	to	to	ADP
fcis-28514	114	85	the	the	DET
fcis-28514	114	86	benchmark	benchmark	ADJ
fcis-28514	114	87	model	model	NOUN
fcis-28514	114	88	yolov8	yolov8	NOUN
fcis-28514	114	89	on	on	ADP
fcis-28514	114	90	the	the	DET
fcis-28514	114	91	uavod10	uavod10	PROPN
fcis-28514	114	92	test	test	NOUN
fcis-28514	114	93	set	set	VERB
fcis-28514	114	94	.	.	PUNCT
fcis-28514	115	1	different	different	ADJ
fcis-28514	115	2	categories	category	NOUN
fcis-28514	115	3	showed	show	VERB
fcis-28514	115	4	varying	vary	VERB
fcis-28514	115	5	degrees	degree	NOUN
fcis-28514	115	6	of	of	ADP
fcis-28514	115	7	improvement	improvement	NOUN
fcis-28514	115	8	in	in	ADP
fcis-28514	115	9	detection	detection	NOUN
fcis-28514	115	10	accuracy	accuracy	NOUN
fcis-28514	115	11	.	.	PUNCT
fcis-28514	116	1	among	among	ADP
fcis-28514	116	2	them	they	PRON
fcis-28514	116	3	,	,	PUNCT
fcis-28514	116	4	the	the	DET
fcis-28514	116	5	categories	category	NOUN
fcis-28514	116	6	"	"	PUNCT
fcis-28514	116	7	pool	pool	NOUN
fcis-28514	116	8	"	"	PUNCT
fcis-28514	116	9	and	and	CCONJ
fcis-28514	116	10	"	"	PUNCT
fcis-28514	116	11	quary	quary	NOUN
fcis-28514	116	12	"	"	PUNCT
fcis-28514	116	13	have	have	VERB
fcis-28514	116	14	the	the	DET
fcis-28514	116	15	largest	large	ADJ
fcis-28514	116	16	pixel	pixel	ADJ
fcis-28514	116	17	area	area	NOUN
fcis-28514	116	18	and	and	CCONJ
fcis-28514	116	19	are	be	AUX
fcis-28514	116	20	easily	easily	ADV
fcis-28514	116	21	have	have	VERB
fcis-28514	116	22	its	its	PRON
fcis-28514	116	23	features	feature	NOUN
fcis-28514	116	24	extracted	extract	VERB
fcis-28514	116	25	by	by	ADP
fcis-28514	116	26	the	the	DET
fcis-28514	116	27	wt_conv	wt_conv	PROPN
fcis-28514	116	28	module	module	NOUN
fcis-28514	116	29	at	at	ADP
fcis-28514	116	30	different	different	ADJ
fcis-28514	116	31	scales	scale	NOUN
fcis-28514	116	32	and	and	CCONJ
fcis-28514	116	33	directions	direction	NOUN
fcis-28514	116	34	,	,	PUNCT
fcis-28514	116	35	so	so	ADV
fcis-28514	116	36	their	their	PRON
fcis-28514	116	37	detection	detection	NOUN
fcis-28514	116	38	accuracies	accuracy	NOUN
fcis-28514	116	39	see	see	VERB
fcis-28514	116	40	the	the	DET
fcis-28514	116	41	most	most	ADJ
fcis-28514	116	42	improvement	improvement	NOUN
fcis-28514	116	43	,	,	PUNCT
fcis-28514	116	44	with	with	ADP
fcis-28514	116	45	increases	increase	NOUN
fcis-28514	116	46	of	of	ADP
fcis-28514	116	47	41.6	41.6	NUM
fcis-28514	116	48	%	%	NOUN
fcis-28514	116	49	and	and	CCONJ
fcis-28514	116	50	15.7	15.7	NUM
fcis-28514	116	51	%	%	NOUN
fcis-28514	116	52	.	.	PUNCT
fcis-28514	117	1	following	follow	VERB
fcis-28514	117	2	are	be	AUX
fcis-28514	117	3	categories	category	NOUN
fcis-28514	117	4	of	of	ADP
fcis-28514	117	5	cable	cable	NOUN
fcis-28514	117	6	-	-	PUNCT
fcis-28514	117	7	tower	tower	NOUN
fcis-28514	117	8	and	and	CCONJ
fcis-28514	117	9	ship	ship	NOUN
fcis-28514	117	10	,	,	PUNCT
fcis-28514	117	11	with	with	ADP
fcis-28514	117	12	an	an	DET
fcis-28514	117	13	average	average	ADJ
fcis-28514	117	14	edge	edge	NOUN
fcis-28514	117	15	length	length	NOUN
fcis-28514	117	16	proportion	proportion	NOUN
fcis-28514	117	17	of	of	ADP
fcis-28514	117	18	only	only	ADV
fcis-28514	117	19	0.02	0.02	NUM
fcis-28514	117	20	to	to	ADP
fcis-28514	117	21	0.03	0.03	NUM
fcis-28514	117	22	,	,	PUNCT
fcis-28514	117	23	whose	whose	DET
fcis-28514	117	24	detection	detection	NOUN
fcis-28514	117	25	accuracy	accuracy	NOUN
fcis-28514	117	26	increases	increase	NOUN
fcis-28514	117	27	of	of	ADP
fcis-28514	117	28	15.3	15.3	NUM
fcis-28514	117	29	%	%	NOUN
fcis-28514	117	30	and	and	CCONJ
fcis-28514	117	31	13.1	13.1	NUM
fcis-28514	117	32	%	%	NOUN
fcis-28514	117	33	.	.	PUNCT
fcis-28514	118	1	this	this	PRON
fcis-28514	118	2	is	be	AUX
fcis-28514	118	3	attributed	attribute	VERB
fcis-28514	118	4	to	to	ADP
fcis-28514	118	5	the	the	DET
fcis-28514	118	6	ms	ms	PROPN
fcis-28514	118	7	module	module	NOUN
fcis-28514	118	8	which	which	PRON
fcis-28514	118	9	prevent	prevent	VERB
fcis-28514	118	10	small	small	ADJ
fcis-28514	118	11	object	object	NOUN
fcis-28514	118	12	from	from	ADP
fcis-28514	118	13	being	be	AUX
fcis-28514	118	14	interfered	interfere	VERB
fcis-28514	118	15	with	with	ADP
fcis-28514	118	16	by	by	ADP
fcis-28514	118	17	other	other	ADJ
fcis-28514	118	18	scales	scale	NOUN
fcis-28514	118	19	object	object	NOUN
fcis-28514	118	20	and	and	CCONJ
fcis-28514	118	21	de	de	ADP
fcis-28514	118	22	module	module	NOUN
fcis-28514	118	23	which	which	PRON
fcis-28514	118	24	enhances	enhance	VERB
fcis-28514	118	25	small	small	ADJ
fcis-28514	118	26	targets	target	NOUN
fcis-28514	118	27	expression	expression	NOUN
fcis-28514	118	28	.	.	PUNCT
fcis-28514	119	1	the	the	DET
fcis-28514	119	2	category	category	NOUN
fcis-28514	119	3	with	with	ADP
fcis-28514	119	4	the	the	DET
fcis-28514	119	5	smallest	small	ADJ
fcis-28514	119	6	pixel	pixel	NOUN
fcis-28514	119	7	area	area	NOUN
fcis-28514	119	8	is	be	AUX
fcis-28514	119	9	vehicle	vehicle	NOUN
fcis-28514	119	10	,	,	PUNCT
fcis-28514	119	11	with	with	ADP
fcis-28514	119	12	an	an	DET
fcis-28514	119	13	average	average	ADJ
fcis-28514	119	14	side	side	NOUN
fcis-28514	119	15	length	length	NOUN
fcis-28514	119	16	ratio	ratio	NOUN
fcis-28514	119	17	of	of	ADP
fcis-28514	119	18	0.01	0.01	NUM
fcis-28514	119	19	,	,	PUNCT
fcis-28514	119	20	which	which	PRON
fcis-28514	119	21	is	be	AUX
fcis-28514	119	22	extremely	extremely	ADV
fcis-28514	119	23	difficult	difficult	ADJ
fcis-28514	119	24	to	to	PART
fcis-28514	119	25	observe	observe	VERB
fcis-28514	119	26	even	even	ADV
fcis-28514	119	27	with	with	SCONJ
fcis-28514	119	28	the	the	DET
fcis-28514	119	29	human	human	ADJ
fcis-28514	119	30	eye	eye	NOUN
fcis-28514	119	31	and	and	CCONJ
fcis-28514	119	32	our	our	PRON
fcis-28514	119	33	model	model	NOUN
fcis-28514	119	34	do	do	AUX
fcis-28514	119	35	not	not	PART
fcis-28514	119	36	perform	perform	VERB
fcis-28514	119	37	well	well	ADV
fcis-28514	119	38	on	on	ADP
fcis-28514	119	39	this	this	DET
fcis-28514	119	40	category	category	NOUN
fcis-28514	119	41	.	.	PUNCT
fcis-28514	120	1	our	our	PRON
fcis-28514	120	2	model	model	NOUN
fcis-28514	120	3	achieves	achieve	VERB
fcis-28514	120	4	the	the	DET
fcis-28514	120	5	highest	high	ADJ
fcis-28514	120	6	map	map	NOUN
fcis-28514	120	7	,	,	PUNCT
fcis-28514	120	8	which	which	PRON
fcis-28514	120	9	is	be	AUX
fcis-28514	120	10	3.2	3.2	NUM
fcis-28514	120	11	%	%	NOUN
fcis-28514	120	12	,	,	PUNCT
fcis-28514	120	13	9.3	9.3	NUM
fcis-28514	120	14	%	%	NOUN
fcis-28514	120	15	,	,	PUNCT
fcis-28514	120	16	24.4	24.4	NUM
fcis-28514	120	17	%	%	NOUN
fcis-28514	120	18	and	and	CCONJ
fcis-28514	120	19	13.7	13.7	NUM
fcis-28514	120	20	%	%	NOUN
fcis-28514	120	21	higher	high	ADJ
fcis-28514	120	22	than	than	ADP
fcis-28514	120	23	other	other	ADJ
fcis-28514	120	24	small	small	ADJ
fcis-28514	120	25	object	object	NOUN
fcis-28514	120	26	detection	detection	NOUN
fcis-28514	120	27	models	model	NOUN
fcis-28514	120	28	like	like	ADP
fcis-28514	120	29	yolov8	yolov8	NOUN
fcis-28514	120	30	-	-	PUNCT
fcis-28514	120	31	bifpn	bifpn	PROPN
fcis-28514	120	32	,	,	PUNCT
fcis-28514	120	33	drone	drone	NOUN
fcis-28514	120	34	-	-	PUNCT
fcis-28514	120	35	yolo	yolo	PROPN
fcis-28514	120	36	,	,	PUNCT
fcis-28514	120	37	tphyolov5n	tphyolov5n	NOUN
fcis-28514	120	38	and	and	CCONJ
fcis-28514	120	39	tph	tph	PROPN
fcis-28514	120	40	-	-	PUNCT
fcis-28514	120	41	yolov5s	yolov5s	PROPN
fcis-28514	120	42	,	,	PUNCT
fcis-28514	120	43	respectively	respectively	ADV
fcis-28514	120	44	and	and	CCONJ
fcis-28514	120	45	achieves	achieve	VERB
fcis-28514	120	46	optimal	optimal	ADJ
fcis-28514	120	47	or	or	CCONJ
fcis-28514	120	48	suboptimal	suboptimal	ADJ
fcis-28514	120	49	detection	detection	NOUN
fcis-28514	120	50	results	result	NOUN
fcis-28514	120	51	in	in	ADP
fcis-28514	120	52	the	the	DET
fcis-28514	120	53	categories	category	NOUN
fcis-28514	120	54	of	of	ADP
fcis-28514	120	55	building	building	NOUN
fcis-28514	120	56	,	,	PUNCT
fcis-28514	120	57	ship	ship	NOUN
fcis-28514	120	58	,	,	PUNCT
fcis-28514	120	59	well	well	INTJ
fcis-28514	120	60	,	,	PUNCT
fcis-28514	120	61	pool	pool	NOUN
fcis-28514	120	62	,	,	PUNCT
fcis-28514	120	63	and	and	CCONJ
fcis-28514	120	64	cultivation	cultivation	NOUN
fcis-28514	120	65	-	-	PUNCT
fcis-28514	120	66	mesh	mesh	NOUN
fcis-28514	120	67	-	-	PUNCT
fcis-28514	120	68	cage	cage	NOUN
fcis-28514	120	69	.	.	PUNCT
fcis-28514	121	1	in	in	ADP
fcis-28514	121	2	order	order	NOUN
fcis-28514	121	3	to	to	PART
fcis-28514	121	4	prove	prove	VERB
fcis-28514	121	5	the	the	DET
fcis-28514	121	6	effectiveness	effectiveness	NOUN
fcis-28514	121	7	of	of	ADP
fcis-28514	121	8	the	the	DET
fcis-28514	121	9	improved	improved	ADJ
fcis-28514	121	10	model	model	NOUN
fcis-28514	121	11	for	for	ADP
fcis-28514	121	12	small	small	ADJ
fcis-28514	121	13	object	object	NOUN
fcis-28514	121	14	detection	detection	NOUN
fcis-28514	121	15	tasks	task	NOUN
fcis-28514	121	16	,	,	PUNCT
fcis-28514	121	17	experiments	experiment	NOUN
fcis-28514	121	18	were	be	AUX
fcis-28514	121	19	conducted	conduct	VERB
fcis-28514	121	20	on	on	ADP
fcis-28514	121	21	a	a	DET
fcis-28514	121	22	small	small	ADJ
fcis-28514	121	23	object	object	NOUN
fcis-28514	121	24	dataset	dataset	NOUN
fcis-28514	121	25	named	name	VERB
fcis-28514	121	26	small	small	ADJ
fcis-28514	121	27	object	object	NOUN
fcis-28514	121	28	,	,	PUNCT
fcis-28514	121	29	and	and	CCONJ
fcis-28514	121	30	the	the	DET
fcis-28514	121	31	results	result	NOUN
fcis-28514	121	32	were	be	AUX
fcis-28514	121	33	shown	show	VERB
fcis-28514	121	34	in	in	ADP
fcis-28514	121	35	table	table	NOUN
fcis-28514	121	36	2	2	NUM
fcis-28514	121	37	.	.	PUNCT
fcis-28514	121	38	table	table	NOUN
fcis-28514	121	39	2	2	NUM
fcis-28514	121	40	.	.	PUNCT
fcis-28514	121	41	comparison	comparison	NOUN
fcis-28514	121	42	of	of	ADP
fcis-28514	121	43	the	the	DET
fcis-28514	121	44	accuracy	accuracy	NOUN
fcis-28514	121	45	of	of	ADP
fcis-28514	121	46	each	each	DET
fcis-28514	121	47	model	model	NOUN
fcis-28514	121	48	on	on	ADP
fcis-28514	121	49	the	the	DET
fcis-28514	121	50	small	small	ADJ
fcis-28514	121	51	object	object	NOUN
fcis-28514	121	52	dataset	dataset	NOUN
fcis-28514	121	53	model	model	NOUN
fcis-28514	121	54	map/%	map/%	PROPN
fcis-28514	121	55	fish	fish	NOUN
fcis-28514	121	56	fly	fly	VERB
fcis-28514	121	57	honeybee	honeybee	ADV
fcis-28514	121	58	faster	fast	ADV
fcis-28514	121	59	-	-	PUNCT
fcis-28514	121	60	rcnn	rcnn	NOUN
fcis-28514	121	61	69.6	69.6	NUM
fcis-28514	121	62	77	77	NUM
fcis-28514	121	63	59	59	NUM
fcis-28514	121	64	72.8	72.8	NUM
fcis-28514	121	65	yolov5n	yolov5n	NOUN
fcis-28514	121	66	88	88	NUM
fcis-28514	121	67	96.6	96.6	NUM
fcis-28514	121	68	71.6	71.6	NUM
fcis-28514	121	69	95.7	95.7	NUM
fcis-28514	121	70	yolov5s	yolov5s	NOUN
fcis-28514	121	71	91.3	91.3	NUM
fcis-28514	121	72	97	97	NUM
fcis-28514	121	73	80.1	80.1	NUM
fcis-28514	121	74	96.9	96.9	NUM
fcis-28514	122	1	yolov6n	yolov6n	PROPN
fcis-28514	122	2	88.5	88.5	NUM
fcis-28514	122	3	94.9	94.9	NUM
fcis-28514	122	4	77.7	77.7	NUM
fcis-28514	122	5	92.9	92.9	NUM
fcis-28514	122	6	yolov7	yolov7	ADV
fcis-28514	122	7	-	-	PUNCT
fcis-28514	122	8	tiny	tiny	ADJ
fcis-28514	122	9	92.6	92.6	NUM
fcis-28514	122	10	97.4	97.4	NUM
fcis-28514	122	11	84	84	NUM
fcis-28514	122	12	96.4	96.4	NUM
fcis-28514	122	13	yolov8n	yolov8n	NOUN
fcis-28514	122	14	92.8	92.8	NUM
fcis-28514	122	15	97.5	97.5	NUM
fcis-28514	122	16	85.3	85.3	NUM
fcis-28514	122	17	95.6	95.6	NUM
fcis-28514	122	18	tph	tph	PROPN
fcis-28514	122	19	-	-	PUNCT
fcis-28514	122	20	yolov5n	yolov5n	PROPN
fcis-28514	122	21	93.3	93.3	NUM
fcis-28514	122	22	96.3	96.3	NUM
fcis-28514	122	23	88.9	88.9	NUM
fcis-28514	122	24	94.8	94.8	NUM
fcis-28514	122	25	drone	drone	NOUN
fcis-28514	122	26	-	-	PUNCT
fcis-28514	122	27	yolo	yolo	ADJ
fcis-28514	122	28	94.7	94.7	NUM
fcis-28514	122	29	97.6	97.6	NUM
fcis-28514	122	30	91.5	91.5	NUM
fcis-28514	122	31	95.1	95.1	NUM
fcis-28514	122	32	yolov8	yolov8	NOUN
fcis-28514	122	33	-	-	PUNCT
fcis-28514	122	34	bifpn	bifpn	PROPN
fcis-28514	122	35	94	94	NUM
fcis-28514	122	36	96	96	NUM
fcis-28514	122	37	90	90	NUM
fcis-28514	122	38	96.2	96.2	NUM
fcis-28514	122	39	ours	ours	PRON
fcis-28514	122	40	95.1	95.1	NUM
fcis-28514	122	41	97.9	97.9	NUM
fcis-28514	122	42	91.5	91.5	NUM
fcis-28514	122	43	95.8	95.8	NUM
fcis-28514	122	44	due	due	ADP
fcis-28514	122	45	to	to	ADP
fcis-28514	122	46	the	the	DET
fcis-28514	122	47	simplicity	simplicity	NOUN
fcis-28514	122	48	of	of	ADP
fcis-28514	122	49	the	the	DET
fcis-28514	122	50	small	small	ADJ
fcis-28514	122	51	object	object	NOUN
fcis-28514	122	52	dataset	dataset	NOUN
fcis-28514	123	1	,	,	PUNCT
fcis-28514	123	2	the	the	DET
fcis-28514	123	3	detection	detection	NOUN
fcis-28514	123	4	accuracy	accuracy	NOUN
fcis-28514	123	5	of	of	ADP
fcis-28514	123	6	the	the	DET
fcis-28514	123	7	benchmark	benchmark	NOUN
fcis-28514	123	8	model	model	NOUN
fcis-28514	123	9	has	have	AUX
fcis-28514	123	10	reached	reach	VERB
fcis-28514	123	11	a	a	DET
fcis-28514	123	12	higher	high	ADJ
fcis-28514	123	13	level	level	NOUN
fcis-28514	123	14	of	of	ADP
fcis-28514	123	15	92.8	92.8	NUM
fcis-28514	123	16	%	%	NOUN
fcis-28514	123	17	,	,	PUNCT
fcis-28514	123	18	so	so	CCONJ
fcis-28514	123	19	the	the	DET
fcis-28514	123	20	improvement	improvement	NOUN
fcis-28514	123	21	is	be	AUX
fcis-28514	123	22	smaller	small	ADJ
fcis-28514	123	23	than	than	ADP
fcis-28514	123	24	that	that	PRON
fcis-28514	123	25	of	of	ADP
fcis-28514	123	26	the	the	DET
fcis-28514	123	27	uavod-10	uavod-10	PROPN
fcis-28514	123	28	dataset	dataset	NOUN
fcis-28514	123	29	,	,	PUNCT
fcis-28514	123	30	and	and	CCONJ
fcis-28514	123	31	the	the	DET
fcis-28514	123	32	overall	overall	ADJ
fcis-28514	123	33	map	map	NOUN
fcis-28514	123	34	improvement	improvement	NOUN
fcis-28514	123	35	is	be	AUX
fcis-28514	123	36	2.3	2.3	NUM
fcis-28514	123	37	%	%	NOUN
fcis-28514	123	38	.	.	PUNCT
fcis-28514	124	1	among	among	ADP
fcis-28514	124	2	them	they	PRON
fcis-28514	124	3	,	,	PUNCT
fcis-28514	124	4	the	the	DET
fcis-28514	124	5	detection	detection	NOUN
fcis-28514	124	6	accuracy	accuracy	NOUN
fcis-28514	124	7	of	of	ADP
fcis-28514	124	8	fish	fish	NOUN
fcis-28514	124	9	,	,	PUNCT
fcis-28514	124	10	fly	fly	VERB
fcis-28514	124	11	and	and	CCONJ
fcis-28514	124	12	honeybee	honeybee	VERB
fcis-28514	124	13	three	three	NUM
fcis-28514	124	14	categories	category	NOUN
fcis-28514	124	15	increased	increase	VERB
fcis-28514	124	16	by	by	ADP
fcis-28514	124	17	2.3	2.3	NUM
fcis-28514	124	18	%	%	NOUN
fcis-28514	124	19	,	,	PUNCT
fcis-28514	124	20	6.2	6.2	NUM
fcis-28514	124	21	%	%	NOUN
fcis-28514	124	22	and	and	CCONJ
fcis-28514	124	23	0.2	0.2	NUM
fcis-28514	124	24	%	%	NOUN
fcis-28514	124	25	respectively	respectively	ADV
fcis-28514	124	26	.	.	PUNCT
fcis-28514	125	1	among	among	ADP
fcis-28514	125	2	all	all	DET
fcis-28514	125	3	the	the	DET
fcis-28514	125	4	models	model	NOUN
fcis-28514	125	5	involved	involve	VERB
fcis-28514	125	6	in	in	ADP
fcis-28514	125	7	the	the	DET
fcis-28514	125	8	comparison	comparison	NOUN
fcis-28514	125	9	,	,	PUNCT
fcis-28514	125	10	the	the	DET
fcis-28514	125	11	overall	overall	ADJ
fcis-28514	125	12	map	map	NOUN
fcis-28514	125	13	value	value	NOUN
fcis-28514	125	14	of	of	ADP
fcis-28514	125	15	the	the	DET
fcis-28514	125	16	model	model	NOUN
fcis-28514	125	17	proposed	propose	VERB
fcis-28514	125	18	in	in	ADP
fcis-28514	125	19	this	this	DET
fcis-28514	125	20	paper	paper	NOUN
fcis-28514	125	21	is	be	AUX
fcis-28514	125	22	the	the	DET
fcis-28514	125	23	highest	high	ADJ
fcis-28514	125	24	,	,	PUNCT
fcis-28514	125	25	which	which	PRON
fcis-28514	125	26	is	be	AUX
fcis-28514	125	27	95.1	95.1	NUM
fcis-28514	125	28	%	%	NOUN
fcis-28514	125	29	,	,	PUNCT
fcis-28514	125	30	and	and	CCONJ
fcis-28514	125	31	it	it	PRON
fcis-28514	125	32	achieves	achieve	VERB
fcis-28514	125	33	the	the	DET
fcis-28514	125	34	best	good	ADJ
fcis-28514	125	35	detection	detection	NOUN
fcis-28514	125	36	performance	performance	NOUN
fcis-28514	125	37	in	in	ADP
fcis-28514	125	38	the	the	DET
fcis-28514	125	39	detection	detection	NOUN
fcis-28514	125	40	tasks	task	NOUN
fcis-28514	125	41	of	of	ADP
fcis-28514	125	42	fish	fish	NOUN
fcis-28514	125	43	and	and	CCONJ
fcis-28514	125	44	fly	fly	VERB
fcis-28514	125	45	,	,	PUNCT
fcis-28514	125	46	and	and	CCONJ
fcis-28514	125	47	also	also	ADV
fcis-28514	125	48	achieves	achieve	VERB
fcis-28514	125	49	good	good	ADJ
fcis-28514	125	50	performance	performance	NOUN
fcis-28514	125	51	in	in	ADP
fcis-28514	125	52	the	the	DET
fcis-28514	125	53	detection	detection	NOUN
fcis-28514	125	54	of	of	ADP
fcis-28514	125	55	honeybee	honeybee	NOUN
fcis-28514	125	56	.	.	PUNCT
fcis-28514	126	1	based	base	VERB
fcis-28514	126	2	on	on	ADP
fcis-28514	126	3	the	the	DET
fcis-28514	126	4	above	above	ADJ
fcis-28514	126	5	analysis	analysis	NOUN
fcis-28514	126	6	,	,	PUNCT
fcis-28514	126	7	the	the	DET
fcis-28514	126	8	improved	improved	ADJ
fcis-28514	126	9	model	model	NOUN
fcis-28514	126	10	presented	present	VERB
fcis-28514	126	11	in	in	ADP
fcis-28514	126	12	this	this	DET
fcis-28514	126	13	paper	paper	NOUN
fcis-28514	126	14	shows	show	VERB
fcis-28514	126	15	excellent	excellent	ADJ
fcis-28514	126	16	ability	ability	NOUN
fcis-28514	126	17	of	of	ADP
fcis-28514	126	18	small	small	ADJ
fcis-28514	126	19	target	target	NOUN
fcis-28514	126	20	detection	detection	NOUN
fcis-28514	126	21	.	.	PUNCT
fcis-28514	127	1	as	as	SCONJ
fcis-28514	127	2	shown	show	VERB
fcis-28514	127	3	in	in	ADP
fcis-28514	127	4	fig	fig	NOUN
fcis-28514	127	5	.	.	PUNCT
fcis-28514	128	1	8	8	NUM
fcis-28514	128	2	,	,	PUNCT
fcis-28514	128	3	the	the	DET
fcis-28514	128	4	results	result	NOUN
fcis-28514	128	5	of	of	ADP
fcis-28514	128	6	small	small	ADJ
fcis-28514	128	7	object	object	NOUN
fcis-28514	128	8	detection	detection	NOUN
fcis-28514	128	9	in	in	ADP
fcis-28514	128	10	part	part	NOUN
fcis-28514	128	11	of	of	ADP
fcis-28514	128	12	the	the	DET
fcis-28514	128	13	dataset	dataset	NOUN
fcis-28514	128	14	were	be	AUX
fcis-28514	128	15	visually	visually	ADV
fcis-28514	128	16	compared	compare	VERB
fcis-28514	128	17	between	between	ADP
fcis-28514	128	18	the	the	DET
fcis-28514	128	19	proposed	propose	VERB
fcis-28514	128	20	improved	improved	ADJ
fcis-28514	128	21	model	model	NOUN
fcis-28514	128	22	and	and	CCONJ
fcis-28514	128	23	the	the	DET
fcis-28514	128	24	baseline	baseline	PROPN
fcis-28514	128	25	model	model	NOUN
fcis-28514	128	26	.	.	PUNCT
fcis-28514	129	1	to	to	PART
fcis-28514	129	2	avoid	avoid	VERB
fcis-28514	129	3	the	the	DET
fcis-28514	129	4	obstruction	obstruction	NOUN
fcis-28514	129	5	caused	cause	VERB
fcis-28514	129	6	by	by	ADP
fcis-28514	129	7	the	the	DET
fcis-28514	129	8	label	label	NOUN
fcis-28514	129	9	text	text	NOUN
fcis-28514	129	10	,	,	PUNCT
fcis-28514	129	11	only	only	ADV
fcis-28514	129	12	the	the	DET
fcis-28514	129	13	detection	detection	NOUN
fcis-28514	129	14	box	box	NOUN
fcis-28514	129	15	is	be	AUX
fcis-28514	129	16	drawn	draw	VERB
fcis-28514	129	17	in	in	ADP
fcis-28514	129	18	the	the	DET
fcis-28514	129	19	figure	figure	NOUN
fcis-28514	129	20	,	,	PUNCT
fcis-28514	129	21	and	and	CCONJ
fcis-28514	129	22	the	the	DET
fcis-28514	129	23	difference	difference	NOUN
fcis-28514	129	24	between	between	ADP
fcis-28514	129	25	the	the	DET
fcis-28514	129	26	two	two	NUM
fcis-28514	129	27	is	be	AUX
fcis-28514	129	28	marked	mark	VERB
fcis-28514	129	29	with	with	ADP
fcis-28514	129	30	a	a	DET
fcis-28514	129	31	white	white	ADJ
fcis-28514	129	32	oval	oval	NOUN
fcis-28514	129	33	box	box	PROPN
fcis-28514	129	34	.	.	PUNCT
fcis-28514	130	1	as	as	SCONJ
fcis-28514	130	2	you	you	PRON
fcis-28514	130	3	can	can	AUX
fcis-28514	130	4	see	see	VERB
fcis-28514	130	5	,	,	PUNCT
fcis-28514	130	6	the	the	DET
fcis-28514	130	7	improved	improved	ADJ
fcis-28514	130	8	model	model	NOUN
fcis-28514	130	9	successfully	successfully	ADV
fcis-28514	130	10	identified	identify	VERB
fcis-28514	130	11	several	several	ADJ
fcis-28514	130	12	small	small	ADJ
fcis-28514	130	13	objects	object	NOUN
fcis-28514	130	14	that	that	SCONJ
fcis-28514	130	15	the	the	DET
fcis-28514	130	16	benchmark	benchmark	NOUN
fcis-28514	130	17	model	model	NOUN
fcis-28514	130	18	had	have	AUX
fcis-28514	130	19	previously	previously	ADV
fcis-28514	130	20	missed	miss	VERB
fcis-28514	130	21	.	.	PUNCT
fcis-28514	131	1	4	4	X
fcis-28514	131	2	.	.	X
fcis-28514	131	3	discussion	discussion	NOUN
fcis-28514	131	4	4.1	4.1	NUM
fcis-28514	131	5	.	.	PUNCT
fcis-28514	131	6	ablation	ablation	NOUN
fcis-28514	131	7	experiment	experiment	NOUN
fcis-28514	131	8	in	in	ADP
fcis-28514	131	9	order	order	NOUN
fcis-28514	131	10	to	to	PART
fcis-28514	131	11	verify	verify	VERB
fcis-28514	131	12	the	the	DET
fcis-28514	131	13	effectiveness	effectiveness	NOUN
fcis-28514	131	14	of	of	ADP
fcis-28514	131	15	the	the	DET
fcis-28514	131	16	improved	improve	VERB
fcis-28514	131	17	algorithm	algorithm	NOUN
fcis-28514	131	18	model	model	NOUN
fcis-28514	131	19	in	in	ADP
fcis-28514	131	20	this	this	DET
fcis-28514	131	21	paper	paper	NOUN
fcis-28514	131	22	,	,	PUNCT
fcis-28514	131	23	ablation	ablation	NOUN
fcis-28514	131	24	experiments	experiment	NOUN
fcis-28514	131	25	were	be	AUX
fcis-28514	131	26	designed	design	VERB
fcis-28514	131	27	on	on	ADP
fcis-28514	131	28	the	the	DET
fcis-28514	131	29	uavod-10	uavod-10	PROPN
fcis-28514	131	30	dataset	dataset	NOUN
fcis-28514	131	31	for	for	ADP
fcis-28514	131	32	the	the	DET
fcis-28514	131	33	proposed	propose	VERB
fcis-28514	131	34	wt_conv	wt_conv	NOUN
fcis-28514	131	35	module	module	NOUN
fcis-28514	131	36	,	,	PUNCT
fcis-28514	131	37	ms	ms	NOUN
fcis-28514	131	38	module	module	NOUN
fcis-28514	131	39	and	and	CCONJ
fcis-28514	131	40	de	de	NOUN
fcis-28514	131	41	module	module	NOUN
fcis-28514	131	42	,	,	PUNCT
fcis-28514	131	43	and	and	CCONJ
fcis-28514	131	44	the	the	DET
fcis-28514	131	45	84	84	NUM
fcis-28514	131	46	results	result	NOUN
fcis-28514	131	47	are	be	AUX
fcis-28514	131	48	shown	show	VERB
fcis-28514	131	49	in	in	ADP
fcis-28514	131	50	table	table	NOUN
fcis-28514	131	51	3	3	NUM
fcis-28514	131	52	.	.	PUNCT
fcis-28514	131	53	fig	fig	NOUN
fcis-28514	131	54	8	8	NUM
fcis-28514	131	55	.	.	PUNCT
fcis-28514	132	1	comparison	comparison	NOUN
fcis-28514	132	2	of	of	ADP
fcis-28514	132	3	detection	detection	NOUN
fcis-28514	132	4	results	result	NOUN
fcis-28514	132	5	between	between	ADP
fcis-28514	132	6	improved	improved	ADJ
fcis-28514	132	7	model	model	NOUN
fcis-28514	132	8	and	and	CCONJ
fcis-28514	132	9	baseline	baseline	NOUN
fcis-28514	132	10	on	on	ADP
fcis-28514	132	11	the	the	DET
fcis-28514	132	12	basis	basis	NOUN
fcis-28514	132	13	of	of	ADP
fcis-28514	132	14	the	the	DET
fcis-28514	132	15	baseline	baseline	PROPN
fcis-28514	132	16	model	model	NOUN
fcis-28514	132	17	,	,	PUNCT
fcis-28514	132	18	three	three	NUM
fcis-28514	132	19	models	model	NOUN
fcis-28514	132	20	a	a	DET
fcis-28514	132	21	,	,	PUNCT
fcis-28514	132	22	b	b	NOUN
fcis-28514	133	1	and	and	CCONJ
fcis-28514	133	2	c	c	PROPN
fcis-28514	133	3	were	be	AUX
fcis-28514	133	4	designed	design	VERB
fcis-28514	133	5	to	to	PART
fcis-28514	133	6	constitute	constitute	VERB
fcis-28514	133	7	the	the	DET
fcis-28514	133	8	ablation	ablation	NOUN
fcis-28514	133	9	experiment	experiment	NOUN
fcis-28514	133	10	.	.	PUNCT
fcis-28514	134	1	model	model	PROPN
fcis-28514	134	2	a	a	DET
fcis-28514	134	3	adds	add	NOUN
fcis-28514	134	4	wt_conv	wt_conv	NOUN
fcis-28514	134	5	module	module	NOUN
fcis-28514	134	6	to	to	ADP
fcis-28514	134	7	the	the	DET
fcis-28514	134	8	layer	layer	NOUN
fcis-28514	134	9	of	of	ADP
fcis-28514	134	10	the	the	DET
fcis-28514	134	11	baseline	baseline	NOUN
fcis-28514	134	12	model	model	NOUN
fcis-28514	134	13	,	,	PUNCT
fcis-28514	134	14	which	which	PRON
fcis-28514	134	15	can	can	AUX
fcis-28514	134	16	extract	extract	VERB
fcis-28514	134	17	more	more	ADJ
fcis-28514	134	18	low	low	ADJ
fcis-28514	134	19	-	-	PUNCT
fcis-28514	134	20	level	level	NOUN
fcis-28514	134	21	features	feature	NOUN
fcis-28514	134	22	from	from	ADP
fcis-28514	134	23	different	different	ADJ
fcis-28514	134	24	scales	scale	NOUN
fcis-28514	134	25	,	,	PUNCT
fcis-28514	134	26	enrich	enrich	VERB
fcis-28514	134	27	the	the	DET
fcis-28514	134	28	representation	representation	NOUN
fcis-28514	134	29	of	of	ADP
fcis-28514	134	30	features	feature	NOUN
fcis-28514	134	31	,	,	PUNCT
fcis-28514	134	32	and	and	CCONJ
fcis-28514	134	33	its	its	PRON
fcis-28514	134	34	map	map	NOUN
fcis-28514	134	35	is	be	AUX
fcis-28514	134	36	increased	increase	VERB
fcis-28514	134	37	by	by	ADP
fcis-28514	134	38	1.7	1.7	NUM
fcis-28514	134	39	%	%	NOUN
fcis-28514	134	40	.	.	PUNCT
fcis-28514	135	1	model	model	PROPN
fcis-28514	135	2	b	b	PROPN
fcis-28514	135	3	adds	add	VERB
fcis-28514	135	4	ms-1	ms-1	NUM
fcis-28514	135	5	and	and	CCONJ
fcis-28514	135	6	ms-2	ms-2	NOUN
fcis-28514	135	7	modules	module	NOUN
fcis-28514	135	8	based	base	VERB
fcis-28514	135	9	on	on	ADP
fcis-28514	135	10	a	a	PRON
fcis-28514	135	11	,	,	PUNCT
fcis-28514	135	12	and	and	CCONJ
fcis-28514	135	13	fuses	fuse	NOUN
fcis-28514	135	14	and	and	CCONJ
fcis-28514	135	15	by	by	ADP
fcis-28514	135	16	downsampling	downsample	VERB
fcis-28514	135	17	the	the	DET
fcis-28514	135	18	separated	separate	VERB
fcis-28514	135	19	small	small	ADJ
fcis-28514	135	20	target	target	NOUN
fcis-28514	135	21	feature	feature	NOUN
fcis-28514	135	22	graph	graph	NOUN
fcis-28514	135	23	twice	twice	ADV
fcis-28514	135	24	,	,	PUNCT
fcis-28514	135	25	and	and	CCONJ
fcis-28514	135	26	transfers	transfer	NOUN
fcis-28514	135	27	the	the	DET
fcis-28514	135	28	separated	separate	VERB
fcis-28514	135	29	large	large	ADJ
fcis-28514	135	30	object	object	NOUN
fcis-28514	135	31	features	feature	NOUN
fcis-28514	135	32	to	to	ADP
fcis-28514	135	33	the	the	DET
fcis-28514	135	34	deep	deep	ADJ
fcis-28514	135	35	layer	layer	NOUN
fcis-28514	135	36	of	of	ADP
fcis-28514	135	37	the	the	DET
fcis-28514	135	38	network	network	NOUN
fcis-28514	135	39	to	to	PART
fcis-28514	135	40	reduce	reduce	VERB
fcis-28514	135	41	the	the	DET
fcis-28514	135	42	interference	interference	NOUN
fcis-28514	135	43	to	to	ADP
fcis-28514	135	44	the	the	DET
fcis-28514	135	45	small	small	ADJ
fcis-28514	135	46	object	object	NOUN
fcis-28514	135	47	feature	feature	NOUN
fcis-28514	135	48	information	information	NOUN
fcis-28514	135	49	,	,	PUNCT
fcis-28514	135	50	and	and	CCONJ
fcis-28514	135	51	its	its	PRON
fcis-28514	135	52	map	map	NOUN
fcis-28514	135	53	increases	increase	NOUN
fcis-28514	135	54	by	by	ADP
fcis-28514	135	55	4.1	4.1	NUM
fcis-28514	135	56	%	%	NOUN
fcis-28514	135	57	.	.	PUNCT
fcis-28514	136	1	the	the	DET
fcis-28514	136	2	final	final	ADJ
fcis-28514	136	3	model	model	NOUN
fcis-28514	136	4	c	c	PROPN
fcis-28514	136	5	is	be	AUX
fcis-28514	136	6	based	base	VERB
fcis-28514	136	7	on	on	ADP
fcis-28514	136	8	b	b	PROPN
fcis-28514	136	9	,	,	PUNCT
fcis-28514	136	10	which	which	PRON
fcis-28514	136	11	adds	add	VERB
fcis-28514	136	12	de-1	de-1	ADP
fcis-28514	136	13	and	and	CCONJ
fcis-28514	136	14	de-2	de-2	ADV
fcis-28514	136	15	modules	module	NOUN
fcis-28514	136	16	to	to	PART
fcis-28514	136	17	strengthen	strengthen	VERB
fcis-28514	136	18	the	the	DET
fcis-28514	136	19	feature	feature	NOUN
fcis-28514	136	20	representation	representation	NOUN
fcis-28514	136	21	of	of	ADP
fcis-28514	136	22	small	small	ADJ
fcis-28514	136	23	objects	object	NOUN
fcis-28514	136	24	,	,	PUNCT
fcis-28514	136	25	and	and	CCONJ
fcis-28514	136	26	the	the	DET
fcis-28514	136	27	map	map	NOUN
fcis-28514	136	28	of	of	ADP
fcis-28514	136	29	the	the	DET
fcis-28514	136	30	model	model	NOUN
fcis-28514	136	31	is	be	AUX
fcis-28514	136	32	improved	improve	VERB
fcis-28514	136	33	by	by	ADP
fcis-28514	136	34	3.7	3.7	NUM
fcis-28514	136	35	%	%	NOUN
fcis-28514	136	36	.	.	PUNCT
fcis-28514	137	1	as	as	SCONJ
fcis-28514	137	2	can	can	AUX
fcis-28514	137	3	be	be	AUX
fcis-28514	137	4	seen	see	VERB
fcis-28514	137	5	from	from	ADP
fcis-28514	137	6	table	table	NOUN
fcis-28514	137	7	3	3	NUM
fcis-28514	137	8	,	,	PUNCT
fcis-28514	137	9	the	the	DET
fcis-28514	137	10	detection	detection	NOUN
fcis-28514	137	11	accuracy	accuracy	NOUN
fcis-28514	137	12	of	of	ADP
fcis-28514	137	13	the	the	DET
fcis-28514	137	14	proposed	propose	VERB
fcis-28514	137	15	improved	improve	VERB
fcis-28514	137	16	method	method	NOUN
fcis-28514	137	17	has	have	AUX
fcis-28514	137	18	achieved	achieve	VERB
fcis-28514	137	19	the	the	DET
fcis-28514	137	20	highest	high	ADJ
fcis-28514	137	21	degree	degree	NOUN
fcis-28514	137	22	of	of	ADP
fcis-28514	137	23	improvement	improvement	NOUN
fcis-28514	137	24	,	,	PUNCT
fcis-28514	137	25	and	and	CCONJ
fcis-28514	137	26	its	its	PRON
fcis-28514	137	27	effectiveness	effectiveness	NOUN
fcis-28514	137	28	has	have	AUX
fcis-28514	137	29	been	be	AUX
fcis-28514	137	30	proved	prove	VERB
fcis-28514	137	31	.	.	PUNCT
fcis-28514	138	1	table	table	NOUN
fcis-28514	138	2	3	3	NUM
fcis-28514	138	3	.	.	PUNCT
fcis-28514	139	1	the	the	DET
fcis-28514	139	2	results	result	NOUN
fcis-28514	139	3	of	of	ADP
fcis-28514	139	4	the	the	DET
fcis-28514	139	5	ablation	ablation	NOUN
fcis-28514	139	6	experiment	experiment	NOUN
fcis-28514	139	7	model	model	NOUN
fcis-28514	139	8	wt_conv	wt_conv	PROPN
fcis-28514	139	9	ms	ms	PROPN
fcis-28514	139	10	de	de	PROPN
fcis-28514	139	11	map/%	map/%	PROPN
fcis-28514	139	12	baseline	baseline	PROPN
fcis-28514	139	13	37.8	37.8	NUM
fcis-28514	139	14	a	a	PRON
fcis-28514	139	15	√	√	NUM
fcis-28514	139	16	39.5	39.5	NUM
fcis-28514	139	17	b	b	NOUN
fcis-28514	139	18	√	√	NUM
fcis-28514	139	19	√	√	ADP
fcis-28514	139	20	43.6	43.6	NUM
fcis-28514	139	21	c(ours	c(our	NOUN
fcis-28514	139	22	)	)	PUNCT
fcis-28514	139	23	√	√	ADP
fcis-28514	140	1	√	√	NUM
fcis-28514	141	1	√	√	ADP
fcis-28514	141	2	47.3	47.3	NUM
fcis-28514	141	3	4.2	4.2	NUM
fcis-28514	141	4	.	.	PUNCT
fcis-28514	142	1	algorithm	algorithm	PROPN
fcis-28514	142	2	complexity	complexity	NOUN
fcis-28514	142	3	analysis	analysis	NOUN
fcis-28514	142	4	the	the	DET
fcis-28514	142	5	complexity	complexity	NOUN
fcis-28514	142	6	of	of	ADP
fcis-28514	142	7	the	the	DET
fcis-28514	142	8	algorithm	algorithm	NOUN
fcis-28514	142	9	is	be	AUX
fcis-28514	142	10	also	also	ADV
fcis-28514	142	11	an	an	DET
fcis-28514	142	12	important	important	ADJ
fcis-28514	142	13	factor	factor	NOUN
fcis-28514	142	14	to	to	PART
fcis-28514	142	15	consider	consider	VERB
fcis-28514	142	16	when	when	SCONJ
fcis-28514	142	17	evaluating	evaluate	VERB
fcis-28514	142	18	the	the	DET
fcis-28514	142	19	performance	performance	NOUN
fcis-28514	142	20	of	of	ADP
fcis-28514	142	21	the	the	DET
fcis-28514	142	22	model	model	NOUN
fcis-28514	142	23	,	,	PUNCT
fcis-28514	142	24	which	which	PRON
fcis-28514	142	25	represents	represent	VERB
fcis-28514	142	26	the	the	DET
fcis-28514	142	27	operational	operational	ADJ
fcis-28514	142	28	efficiency	efficiency	NOUN
fcis-28514	142	29	and	and	CCONJ
fcis-28514	142	30	resource	resource	NOUN
fcis-28514	142	31	consumption	consumption	NOUN
fcis-28514	142	32	of	of	ADP
fcis-28514	142	33	the	the	DET
fcis-28514	142	34	algorithm	algorithm	NOUN
fcis-28514	142	35	.	.	PUNCT
fcis-28514	143	1	in	in	ADP
fcis-28514	143	2	order	order	NOUN
fcis-28514	143	3	to	to	PART
fcis-28514	143	4	evaluate	evaluate	VERB
fcis-28514	143	5	the	the	DET
fcis-28514	143	6	complexity	complexity	NOUN
fcis-28514	143	7	of	of	ADP
fcis-28514	143	8	the	the	DET
fcis-28514	143	9	improved	improved	ADJ
fcis-28514	143	10	model	model	NOUN
fcis-28514	143	11	more	more	ADV
fcis-28514	143	12	comprehensively	comprehensively	ADV
fcis-28514	143	13	,	,	PUNCT
fcis-28514	143	14	the	the	DET
fcis-28514	143	15	number	number	NOUN
fcis-28514	143	16	of	of	ADP
fcis-28514	143	17	model	model	NOUN
fcis-28514	143	18	parameters	parameter	NOUN
fcis-28514	143	19	and	and	CCONJ
fcis-28514	143	20	the	the	DET
fcis-28514	143	21	amount	amount	NOUN
fcis-28514	143	22	of	of	ADP
fcis-28514	143	23	computation	computation	NOUN
fcis-28514	143	24	are	be	AUX
fcis-28514	143	25	taken	take	VERB
fcis-28514	143	26	as	as	ADP
fcis-28514	143	27	evaluation	evaluation	NOUN
fcis-28514	143	28	indicators	indicator	NOUN
fcis-28514	143	29	,	,	PUNCT
fcis-28514	143	30	and	and	CCONJ
fcis-28514	143	31	the	the	DET
fcis-28514	143	32	improved	improved	ADJ
fcis-28514	143	33	model	model	NOUN
fcis-28514	143	34	is	be	AUX
fcis-28514	143	35	compared	compare	VERB
fcis-28514	143	36	with	with	ADP
fcis-28514	143	37	a	a	DET
fcis-28514	143	38	series	series	NOUN
fcis-28514	143	39	of	of	ADP
fcis-28514	143	40	models	model	NOUN
fcis-28514	143	41	mentioned	mention	VERB
fcis-28514	143	42	in	in	ADP
fcis-28514	143	43	the	the	DET
fcis-28514	143	44	comparison	comparison	NOUN
fcis-28514	143	45	experiment	experiment	NOUN
fcis-28514	143	46	above	above	ADV
fcis-28514	143	47	.	.	PUNCT
fcis-28514	144	1	the	the	DET
fcis-28514	144	2	results	result	NOUN
fcis-28514	144	3	are	be	AUX
fcis-28514	144	4	shown	show	VERB
fcis-28514	144	5	in	in	ADP
fcis-28514	144	6	table	table	NOUN
fcis-28514	144	7	4	4	NUM
fcis-28514	144	8	.	.	PUNCT
fcis-28514	145	1	the	the	DET
fcis-28514	145	2	results	result	NOUN
fcis-28514	145	3	show	show	VERB
fcis-28514	145	4	that	that	SCONJ
fcis-28514	145	5	the	the	DET
fcis-28514	145	6	parameters	parameter	NOUN
fcis-28514	145	7	of	of	ADP
fcis-28514	145	8	the	the	DET
fcis-28514	145	9	improved	improved	ADJ
fcis-28514	145	10	model	model	NOUN
fcis-28514	145	11	are	be	AUX
fcis-28514	145	12	4.4	4.4	NUM
fcis-28514	145	13	m	m	NOUN
fcis-28514	145	14	and	and	CCONJ
fcis-28514	145	15	the	the	DET
fcis-28514	145	16	calculation	calculation	NOUN
fcis-28514	145	17	consumption	consumption	NOUN
fcis-28514	145	18	reaches	reach	VERB
fcis-28514	145	19	19.3	19.3	NUM
fcis-28514	145	20	g	g	NOUN
fcis-28514	145	21	,	,	PUNCT
fcis-28514	145	22	which	which	PRON
fcis-28514	145	23	is	be	AUX
fcis-28514	145	24	higher	high	ADJ
fcis-28514	145	25	than	than	ADP
fcis-28514	145	26	that	that	PRON
fcis-28514	145	27	of	of	ADP
fcis-28514	145	28	the	the	DET
fcis-28514	145	29	baseline	baseline	NOUN
fcis-28514	145	30	model	model	NOUN
fcis-28514	145	31	yolov8n	yolov8n	PROPN
fcis-28514	145	32	,	,	PUNCT
fcis-28514	145	33	but	but	CCONJ
fcis-28514	145	34	the	the	DET
fcis-28514	145	35	map	map	NOUN
fcis-28514	145	36	is	be	AUX
fcis-28514	145	37	significantly	significantly	ADV
fcis-28514	145	38	improved	improve	VERB
fcis-28514	145	39	.	.	PUNCT
fcis-28514	146	1	compared	compare	VERB
fcis-28514	146	2	with	with	ADP
fcis-28514	146	3	other	other	ADJ
fcis-28514	146	4	models	model	NOUN
fcis-28514	146	5	,	,	PUNCT
fcis-28514	146	6	the	the	DET
fcis-28514	146	7	parameters	parameter	NOUN
fcis-28514	146	8	of	of	ADP
fcis-28514	146	9	the	the	DET
fcis-28514	146	10	improved	improved	ADJ
fcis-28514	146	11	model	model	NOUN
fcis-28514	146	12	are	be	AUX
fcis-28514	146	13	at	at	ADP
fcis-28514	146	14	a	a	DET
fcis-28514	146	15	moderate	moderate	ADJ
fcis-28514	146	16	level	level	NOUN
fcis-28514	146	17	,	,	PUNCT
fcis-28514	146	18	but	but	CCONJ
fcis-28514	146	19	the	the	DET
fcis-28514	146	20	calculation	calculation	NOUN
fcis-28514	146	21	cost	cost	NOUN
fcis-28514	146	22	is	be	AUX
fcis-28514	146	23	a	a	DET
fcis-28514	146	24	little	little	ADJ
fcis-28514	146	25	larger	large	ADJ
fcis-28514	146	26	,	,	PUNCT
fcis-28514	146	27	but	but	CCONJ
fcis-28514	146	28	the	the	DET
fcis-28514	146	29	accuracy	accuracy	NOUN
fcis-28514	146	30	of	of	ADP
fcis-28514	146	31	the	the	DET
fcis-28514	146	32	improved	improved	ADJ
fcis-28514	146	33	model	model	NOUN
fcis-28514	146	34	is	be	AUX
fcis-28514	146	35	obviously	obviously	ADV
fcis-28514	146	36	higher	high	ADJ
fcis-28514	146	37	than	than	ADP
fcis-28514	146	38	other	other	ADJ
fcis-28514	146	39	models	model	NOUN
fcis-28514	146	40	.	.	PUNCT
fcis-28514	147	1	in	in	ADP
fcis-28514	147	2	summary	summary	NOUN
fcis-28514	147	3	,	,	PUNCT
fcis-28514	147	4	the	the	DET
fcis-28514	147	5	improved	improved	ADJ
fcis-28514	147	6	model	model	NOUN
fcis-28514	147	7	can	can	AUX
fcis-28514	147	8	greatly	greatly	ADV
fcis-28514	147	9	improve	improve	VERB
fcis-28514	147	10	the	the	DET
fcis-28514	147	11	detection	detection	NOUN
fcis-28514	147	12	accuracy	accuracy	NOUN
fcis-28514	147	13	of	of	ADP
fcis-28514	147	14	small	small	ADJ
fcis-28514	147	15	objects	object	NOUN
fcis-28514	147	16	with	with	ADP
fcis-28514	147	17	acceptable	acceptable	ADJ
fcis-28514	147	18	increase	increase	NOUN
fcis-28514	147	19	of	of	ADP
fcis-28514	147	20	parameters	parameter	NOUN
fcis-28514	147	21	and	and	CCONJ
fcis-28514	147	22	calculation	calculation	NOUN
fcis-28514	147	23	cost	cost	NOUN
fcis-28514	147	24	.	.	PUNCT
fcis-28514	148	1	table	table	NOUN
fcis-28514	148	2	4	4	NUM
fcis-28514	148	3	.	.	PUNCT
fcis-28514	148	4	comparison	comparison	NOUN
fcis-28514	148	5	of	of	ADP
fcis-28514	148	6	model	model	NOUN
fcis-28514	148	7	complexity	complexity	NOUN
fcis-28514	148	8	model	model	NOUN
fcis-28514	148	9	magnitude	magnitude	NOUN
fcis-28514	148	10	of	of	ADP
fcis-28514	148	11	parameters	parameter	NOUN
fcis-28514	148	12	/	/	SYM
fcis-28514	148	13	m	m	NOUN
fcis-28514	148	14	flops	flop	NOUN
fcis-28514	148	15	/	/	SYM
fcis-28514	148	16	g	g	PROPN
fcis-28514	148	17	map/%	map/%	PROPN
fcis-28514	148	18	faster	fast	ADV
fcis-28514	148	19	-	-	PUNCT
fcis-28514	148	20	rcnn	rcnn	NOUN
fcis-28514	148	21	137	137	NUM
fcis-28514	148	22	370	370	NUM
fcis-28514	148	23	24.3	24.3	NUM
fcis-28514	148	24	yolov5n	yolov5n	NOUN
fcis-28514	148	25	1.78	1.78	NUM
fcis-28514	148	26	4.2	4.2	NUM
fcis-28514	148	27	27.4	27.4	NUM
fcis-28514	148	28	yolov5s	yolov5s	NOUN
fcis-28514	148	29	7.05	7.05	NUM
fcis-28514	148	30	15.8	15.8	NUM
fcis-28514	148	31	33.6	33.6	NUM
fcis-28514	148	32	yolov6n	yolov6n	PROPN
fcis-28514	148	33	4.92	4.92	NUM
fcis-28514	148	34	11.4	11.4	NUM
fcis-28514	148	35	26.7	26.7	NUM
fcis-28514	148	36	yolov7	yolov7	ADV
fcis-28514	148	37	-	-	PUNCT
fcis-28514	148	38	tiny	tiny	ADJ
fcis-28514	148	39	6.03	6.03	NUM
fcis-28514	148	40	13.1	13.1	NUM
fcis-28514	148	41	37.1	37.1	NUM
fcis-28514	148	42	yolov8n	yolov8n	NOUN
fcis-28514	148	43	3.16	3.16	NUM
fcis-28514	148	44	8.9	8.9	NUM
fcis-28514	148	45	37.8	37.8	NUM
fcis-28514	148	46	yolov8bifpn	yolov8bifpn	PROPN
fcis-28514	148	47	3.17	3.17	NUM
fcis-28514	148	48	8.9	8.9	NUM
fcis-28514	148	49	44.1	44.1	NUM
fcis-28514	148	50	drone	drone	NOUN
fcis-28514	148	51	-	-	PUNCT
fcis-28514	148	52	yolo	yolo	ADJ
fcis-28514	148	53	3.4	3.4	NUM
fcis-28514	148	54	17.6	17.6	NUM
fcis-28514	148	55	38	38	NUM
fcis-28514	148	56	tphyolov5n	tphyolov5n	NOUN
fcis-28514	148	57	2.32	2.32	NUM
fcis-28514	148	58	6.2	6.2	NUM
fcis-28514	148	59	22.9	22.9	NUM
fcis-28514	148	60	tphyolov5s	tphyolov5s	NOUN
fcis-28514	148	61	9.2	9.2	NUM
fcis-28514	148	62	23.3	23.3	NUM
fcis-28514	148	63	33.6	33.6	NUM
fcis-28514	148	64	ours	ours	PRON
fcis-28514	148	65	4.4	4.4	NUM
fcis-28514	148	66	19.3	19.3	NUM
fcis-28514	148	67	47.3	47.3	NUM
fcis-28514	148	68	5	5	NUM
fcis-28514	148	69	.	.	PUNCT
fcis-28514	149	1	conclusion	conclusion	NOUN
fcis-28514	149	2	in	in	ADP
fcis-28514	149	3	order	order	NOUN
fcis-28514	149	4	to	to	PART
fcis-28514	149	5	solve	solve	VERB
fcis-28514	149	6	the	the	DET
fcis-28514	149	7	problem	problem	NOUN
fcis-28514	149	8	of	of	ADP
fcis-28514	149	9	poor	poor	ADJ
fcis-28514	149	10	recognition	recognition	NOUN
fcis-28514	149	11	of	of	ADP
fcis-28514	149	12	small	small	ADJ
fcis-28514	149	13	objects	object	NOUN
fcis-28514	149	14	caused	cause	VERB
fcis-28514	149	15	by	by	ADP
fcis-28514	149	16	scale	scale	NOUN
fcis-28514	149	17	confusion	confusion	NOUN
fcis-28514	149	18	,	,	PUNCT
fcis-28514	149	19	an	an	DET
fcis-28514	149	20	improved	improved	ADJ
fcis-28514	149	21	yolov8	yolov8	NOUN
fcis-28514	149	22	model	model	NOUN
fcis-28514	149	23	is	be	AUX
fcis-28514	149	24	proposed	propose	VERB
fcis-28514	149	25	in	in	ADP
fcis-28514	149	26	this	this	DET
fcis-28514	149	27	paper	paper	NOUN
fcis-28514	149	28	.	.	PUNCT
fcis-28514	150	1	firstly	firstly	ADV
fcis-28514	150	2	,	,	PUNCT
fcis-28514	150	3	the	the	DET
fcis-28514	150	4	wt_conv	wt_conv	NOUN
fcis-28514	150	5	module	module	NOUN
fcis-28514	150	6	is	be	AUX
fcis-28514	150	7	designed	design	VERB
fcis-28514	150	8	in	in	ADP
fcis-28514	150	9	the	the	DET
fcis-28514	150	10	model	model	NOUN
fcis-28514	150	11	,	,	PUNCT
fcis-28514	150	12	which	which	PRON
fcis-28514	150	13	uses	use	VERB
fcis-28514	150	14	wavelet	wavelet	NOUN
fcis-28514	150	15	transform	transform	NOUN
fcis-28514	150	16	to	to	PART
fcis-28514	150	17	extract	extract	VERB
fcis-28514	150	18	low	low	ADJ
fcis-28514	150	19	-	-	PUNCT
fcis-28514	150	20	level	level	NOUN
fcis-28514	150	21	features	feature	NOUN
fcis-28514	150	22	and	and	CCONJ
fcis-28514	150	23	increase	increase	VERB
fcis-28514	150	24	the	the	DET
fcis-28514	150	25	feature	feature	NOUN
fcis-28514	150	26	information	information	NOUN
fcis-28514	150	27	.	.	PUNCT
fcis-28514	151	1	secondly	secondly	ADV
fcis-28514	151	2	,	,	PUNCT
fcis-28514	151	3	the	the	DET
fcis-28514	151	4	ms	ms	PROPN
fcis-28514	151	5	module	module	NOUN
fcis-28514	151	6	is	be	AUX
fcis-28514	151	7	designed	design	VERB
fcis-28514	151	8	to	to	PART
fcis-28514	151	9	separate	separate	VERB
fcis-28514	151	10	the	the	DET
fcis-28514	151	11	features	feature	NOUN
fcis-28514	151	12	of	of	ADP
fcis-28514	151	13	objects	object	NOUN
fcis-28514	151	14	at	at	ADP
fcis-28514	151	15	different	different	ADJ
fcis-28514	151	16	scales	scale	NOUN
fcis-28514	151	17	,	,	PUNCT
fcis-28514	151	18	so	so	SCONJ
fcis-28514	151	19	as	as	SCONJ
fcis-28514	151	20	to	to	PART
fcis-28514	151	21	effectively	effectively	ADV
fcis-28514	151	22	deal	deal	VERB
fcis-28514	151	23	with	with	ADP
fcis-28514	151	24	the	the	DET
fcis-28514	151	25	problem	problem	NOUN
fcis-28514	151	26	of	of	ADP
fcis-28514	151	27	inconsistent	inconsistent	ADJ
fcis-28514	151	28	feature	feature	NOUN
fcis-28514	151	29	expression	expression	NOUN
fcis-28514	151	30	caused	cause	VERB
fcis-28514	151	31	by	by	ADP
fcis-28514	151	32	the	the	DET
fcis-28514	151	33	direct	direct	ADJ
fcis-28514	151	34	fusion	fusion	NOUN
fcis-28514	151	35	of	of	ADP
fcis-28514	151	36	deep	deep	ADJ
fcis-28514	151	37	and	and	CCONJ
fcis-28514	151	38	shallow	shallow	ADJ
fcis-28514	151	39	feature	feature	NOUN
fcis-28514	151	40	maps	map	NOUN
fcis-28514	151	41	.	.	PUNCT
fcis-28514	152	1	at	at	ADP
fcis-28514	152	2	the	the	DET
fcis-28514	152	3	same	same	ADJ
fcis-28514	152	4	time	time	NOUN
fcis-28514	152	5	,	,	PUNCT
fcis-28514	152	6	a	a	DET
fcis-28514	152	7	de	de	NOUN
fcis-28514	152	8	module	module	NOUN
fcis-28514	152	9	is	be	AUX
fcis-28514	152	10	designed	design	VERB
fcis-28514	152	11	to	to	PART
fcis-28514	152	12	fuse	fuse	VERB
fcis-28514	152	13	the	the	DET
fcis-28514	152	14	separated	separate	VERB
fcis-28514	152	15	shallow	shallow	ADJ
fcis-28514	152	16	feature	feature	NOUN
fcis-28514	152	17	maps	map	NOUN
fcis-28514	152	18	to	to	PART
fcis-28514	152	19	enhance	enhance	VERB
fcis-28514	152	20	the	the	DET
fcis-28514	152	21	expression	expression	NOUN
fcis-28514	152	22	of	of	ADP
fcis-28514	152	23	small	small	ADJ
fcis-28514	152	24	object	object	NOUN
fcis-28514	152	25	features	feature	NOUN
fcis-28514	152	26	.	.	PUNCT
fcis-28514	153	1	experimental	experimental	ADJ
fcis-28514	153	2	results	result	NOUN
fcis-28514	153	3	on	on	ADP
fcis-28514	153	4	uavod-10	uavod-10	ADJ
fcis-28514	153	5	and	and	CCONJ
fcis-28514	153	6	small	small	ADJ
fcis-28514	153	7	object	object	NOUN
fcis-28514	153	8	datasets	dataset	NOUN
fcis-28514	153	9	show	show	VERB
fcis-28514	153	10	that	that	SCONJ
fcis-28514	153	11	the	the	DET
fcis-28514	153	12	detection	detection	NOUN
fcis-28514	153	13	performance	performance	NOUN
fcis-28514	153	14	of	of	ADP
fcis-28514	153	15	this	this	DET
fcis-28514	153	16	model	model	NOUN
fcis-28514	153	17	is	be	AUX
fcis-28514	153	18	significantly	significantly	ADV
fcis-28514	153	19	improved	improve	VERB
fcis-28514	153	20	compared	compare	VERB
fcis-28514	153	21	with	with	ADP
fcis-28514	153	22	the	the	DET
fcis-28514	153	23	baseline	baseline	NOUN
fcis-28514	153	24	model	model	NOUN
fcis-28514	153	25	,	,	PUNCT
fcis-28514	153	26	and	and	CCONJ
fcis-28514	153	27	it	it	PRON
fcis-28514	153	28	also	also	ADV
fcis-28514	153	29	has	have	VERB
fcis-28514	153	30	greater	great	ADJ
fcis-28514	153	31	advantages	advantage	NOUN
fcis-28514	153	32	compared	compare	VERB
fcis-28514	153	33	with	with	ADP
fcis-28514	153	34	other	other	ADJ
fcis-28514	153	35	comparative	comparative	ADJ
fcis-28514	153	36	network	network	NOUN
fcis-28514	153	37	models	model	NOUN
fcis-28514	153	38	.	.	PUNCT
fcis-28514	154	1	however	however	ADV
fcis-28514	154	2	,	,	PUNCT
fcis-28514	154	3	the	the	DET
fcis-28514	154	4	ms	ms	PROPN
fcis-28514	154	5	module	module	NOUN
fcis-28514	154	6	proposed	propose	VERB
fcis-28514	154	7	in	in	ADP
fcis-28514	154	8	this	this	DET
fcis-28514	154	9	paper	paper	NOUN
fcis-28514	154	10	simply	simply	ADV
fcis-28514	154	11	85	85	NUM
fcis-28514	154	12	classifies	classify	VERB
fcis-28514	154	13	the	the	DET
fcis-28514	154	14	detected	detect	VERB
fcis-28514	154	15	objects	object	NOUN
fcis-28514	154	16	according	accord	VERB
fcis-28514	154	17	to	to	ADP
fcis-28514	154	18	their	their	PRON
fcis-28514	154	19	sizes	size	NOUN
fcis-28514	154	20	,	,	PUNCT
fcis-28514	154	21	while	while	SCONJ
fcis-28514	154	22	the	the	DET
fcis-28514	154	23	scale	scale	NOUN
fcis-28514	154	24	range	range	NOUN
fcis-28514	154	25	of	of	ADP
fcis-28514	154	26	various	various	ADJ
fcis-28514	154	27	target	target	NOUN
fcis-28514	154	28	objects	object	NOUN
fcis-28514	154	29	in	in	ADP
fcis-28514	154	30	the	the	DET
fcis-28514	154	31	real	real	ADJ
fcis-28514	154	32	scene	scene	NOUN
fcis-28514	154	33	is	be	AUX
fcis-28514	154	34	varied	varied	ADJ
fcis-28514	154	35	.	.	PUNCT
fcis-28514	155	1	in	in	ADP
fcis-28514	155	2	the	the	DET
fcis-28514	155	3	future	future	NOUN
fcis-28514	155	4	,	,	PUNCT
fcis-28514	155	5	we	we	PRON
fcis-28514	155	6	can	can	AUX
fcis-28514	155	7	try	try	VERB
fcis-28514	155	8	to	to	PART
fcis-28514	155	9	design	design	VERB
fcis-28514	155	10	lighter	light	ADJ
fcis-28514	155	11	model	model	NOUN
fcis-28514	155	12	structures	structure	NOUN
fcis-28514	155	13	in	in	ADP
fcis-28514	155	14	the	the	DET
fcis-28514	155	15	case	case	NOUN
fcis-28514	155	16	of	of	ADP
fcis-28514	155	17	finer	fine	ADJ
fcis-28514	155	18	scale	scale	NOUN
fcis-28514	155	19	division	division	NOUN
fcis-28514	155	20	.	.	PUNCT
fcis-28514	156	1	acknowledgments	acknowledgment	NOUN
fcis-28514	156	2	i	i	PRON
fcis-28514	156	3	am	be	AUX
fcis-28514	156	4	deeply	deeply	ADV
fcis-28514	156	5	grateful	grateful	ADJ
fcis-28514	156	6	for	for	ADP
fcis-28514	156	7	the	the	DET
fcis-28514	156	8	support	support	NOUN
fcis-28514	156	9	of	of	ADP
fcis-28514	156	10	my	my	PRON
fcis-28514	156	11	friends	friend	NOUN
fcis-28514	156	12	and	and	CCONJ
fcis-28514	156	13	colleagues	colleague	NOUN
fcis-28514	156	14	during	during	ADP
fcis-28514	156	15	the	the	DET
fcis-28514	156	16	writing	writing	NOUN
fcis-28514	156	17	of	of	ADP
fcis-28514	156	18	this	this	DET
fcis-28514	156	19	thesis	thesis	NOUN
fcis-28514	156	20	.	.	PUNCT
fcis-28514	157	1	their	their	PRON
fcis-28514	157	2	encouragement	encouragement	NOUN
fcis-28514	157	3	and	and	CCONJ
fcis-28514	157	4	feedback	feedback	NOUN
fcis-28514	157	5	were	be	AUX
fcis-28514	157	6	crucial	crucial	ADJ
fcis-28514	157	7	.	.	PUNCT
fcis-28514	158	1	i	i	PRON
fcis-28514	158	2	also	also	ADV
fcis-28514	158	3	extend	extend	VERB
fcis-28514	158	4	my	my	PRON
fcis-28514	158	5	thanks	thank	NOUN
fcis-28514	158	6	to	to	ADP
fcis-28514	158	7	the	the	DET
fcis-28514	158	8	providers	provider	NOUN
fcis-28514	158	9	of	of	ADP
fcis-28514	158	10	the	the	DET
fcis-28514	158	11	small	small	ADJ
fcis-28514	158	12	object	object	NOUN
fcis-28514	158	13	and	and	CCONJ
fcis-28514	158	14	uavod	uavod	ADJ
fcis-28514	158	15	datasets	dataset	NOUN
fcis-28514	158	16	for	for	ADP
fcis-28514	158	17	their	their	PRON
fcis-28514	158	18	invaluable	invaluable	ADJ
fcis-28514	158	19	contributions	contribution	NOUN
fcis-28514	158	20	to	to	ADP
fcis-28514	158	21	my	my	PRON
fcis-28514	158	22	research	research	NOUN
fcis-28514	158	23	.	.	PUNCT
fcis-28514	159	1	additionally	additionally	ADV
fcis-28514	159	2	,	,	PUNCT
fcis-28514	159	3	i	i	PRON
fcis-28514	159	4	appreciate	appreciate	VERB
fcis-28514	159	5	the	the	DET
fcis-28514	159	6	ideas	idea	NOUN
fcis-28514	159	7	and	and	CCONJ
fcis-28514	159	8	insights	insight	NOUN
fcis-28514	159	9	from	from	ADP
fcis-28514	159	10	all	all	DET
fcis-28514	159	11	authors	author	NOUN
fcis-28514	159	12	whose	whose	DET
fcis-28514	159	13	works	work	NOUN
fcis-28514	159	14	i	i	PRON
fcis-28514	159	15	have	have	AUX
fcis-28514	159	16	cited	cite	VERB
fcis-28514	159	17	,	,	PUNCT
fcis-28514	159	18	whose	whose	DET
fcis-28514	159	19	scholarship	scholarship	NOUN
fcis-28514	159	20	has	have	AUX
fcis-28514	159	21	significantly	significantly	ADV
fcis-28514	159	22	influenced	influence	VERB
fcis-28514	159	23	my	my	PRON
fcis-28514	159	24	own	own	ADJ
fcis-28514	159	25	.	.	PUNCT
fcis-28514	160	1	references	reference	NOUN
fcis-28514	160	2	[	[	X
fcis-28514	160	3	1	1	NUM
fcis-28514	160	4	]	]	PUNCT
fcis-28514	160	5	bochkovskiy	bochkovskiy	X
fcis-28514	160	6	a	a	PRON
fcis-28514	160	7	,	,	PUNCT
fcis-28514	160	8	wang	wang	PROPN
fcis-28514	160	9	c	c	PROPN
fcis-28514	160	10	y	y	PROPN
fcis-28514	160	11	,	,	PUNCT
fcis-28514	160	12	liao	liao	PROPN
fcis-28514	160	13	h	h	PROPN
fcis-28514	160	14	y	y	PROPN
fcis-28514	160	15	m.yolov4	m.yolov4	PROPN
fcis-28514	160	16	:	:	PUNCT
fcis-28514	160	17	optimal	optimal	ADJ
fcis-28514	160	18	speed	speed	NOUN
fcis-28514	160	19	and	and	CCONJ
fcis-28514	160	20	accuracy	accuracy	NOUN
fcis-28514	160	21	of	of	ADP
fcis-28514	160	22	object	object	NOUN
fcis-28514	160	23	detection	detection	NOUN
fcis-28514	161	1	[	[	X
fcis-28514	161	2	eb	eb	PROPN
fcis-28514	161	3	/	/	SYM
fcis-28514	161	4	ol	ol	PROPN
fcis-28514	161	5	]	]	PUNCT
fcis-28514	161	6	.	.	PUNCT
fcis-28514	162	1	2020	2020	NUM
fcis-28514	162	2	.	.	PUNCT
fcis-28514	163	1	https://arxiv.org/	https://arxiv.org/	PRON
fcis-28514	163	2	abs/2004.10934	abs/2004.10934	VERB
fcis-28514	163	3	.	.	PUNCT
fcis-28514	164	1	[	[	X
fcis-28514	164	2	2	2	NUM
fcis-28514	164	3	]	]	X
fcis-28514	164	4	kisantal	kisantal	PROPN
fcis-28514	164	5	m	m	PROPN
fcis-28514	164	6	,	,	PUNCT
fcis-28514	164	7	wojna	wojna	PROPN
fcis-28514	164	8	z	z	NOUN
fcis-28514	164	9	,	,	PUNCT
fcis-28514	164	10	murawski	murawski	PROPN
fcis-28514	164	11	j	j	PROPN
fcis-28514	164	12	,	,	PUNCT
fcis-28514	164	13	et	et	PROPN
fcis-28514	164	14	al	al	PROPN
fcis-28514	164	15	.	.	PUNCT
fcis-28514	164	16	augmentation	augmentation	NOUN
fcis-28514	164	17	for	for	ADP
fcis-28514	164	18	small	small	ADJ
fcis-28514	164	19	object	object	NOUN
fcis-28514	164	20	detection	detection	NOUN
fcis-28514	164	21	[	[	X
fcis-28514	164	22	eb	eb	PROPN
fcis-28514	164	23	/	/	SYM
fcis-28514	164	24	ol	ol	PROPN
fcis-28514	164	25	]	]	X
fcis-28514	164	26	.	.	PUNCT
fcis-28514	165	1	2019	2019	NUM
fcis-28514	165	2	.	.	PUNCT
fcis-28514	166	1	https	https	NOUN
fcis-28514	166	2	:	:	PUNCT
fcis-28514	166	3	//	//	PUNCT
fcis-28514	166	4	arxiv.org/abs/1902.07296	arxiv.org/abs/1902.07296	NOUN
fcis-28514	166	5	.	.	PUNCT
fcis-28514	167	1	[	[	X
fcis-28514	167	2	3	3	X
fcis-28514	167	3	]	]	X
fcis-28514	167	4	li	li	PROPN
fcis-28514	167	5	li	li	PROPN
fcis-28514	167	6	-	-	PROPN
fcis-28514	167	7	xia	xia	PROPN
fcis-28514	167	8	,	,	PUNCT
fcis-28514	167	9	wang	wang	PROPN
fcis-28514	167	10	xin	xin	PROPN
fcis-28514	167	11	,	,	PUNCT
fcis-28514	167	12	wang	wang	PROPN
fcis-28514	167	13	jun	jun	PROPN
fcis-28514	167	14	,	,	PUNCT
fcis-28514	167	15	et	et	PROPN
fcis-28514	167	16	al	al	PROPN
fcis-28514	167	17	.	.	PUNCT
fcis-28514	167	18	small	small	ADJ
fcis-28514	167	19	object	object	NOUN
fcis-28514	167	20	detection	detection	NOUN
fcis-28514	167	21	algorithm	algorithm	NOUN
fcis-28514	167	22	in	in	ADP
fcis-28514	167	23	uav	uav	PROPN
fcis-28514	167	24	image	image	NOUN
fcis-28514	167	25	based	base	VERB
fcis-28514	167	26	on	on	ADP
fcis-28514	167	27	feature	feature	NOUN
fcis-28514	167	28	fusion	fusion	NOUN
fcis-28514	167	29	and	and	CCONJ
fcis-28514	167	30	attention	attention	NOUN
fcis-28514	167	31	mechanism[j	mechanism[j	PROPN
fcis-28514	167	32	]	]	PUNCT
fcis-28514	167	33	.	.	PUNCT
fcis-28514	168	1	journal	journal	PROPN
fcis-28514	168	2	of	of	ADP
fcis-28514	168	3	graphics	graphic	NOUN
fcis-28514	168	4	,	,	PUNCT
fcis-28514	168	5	2023,44(04):658666	2023,44(04):658666	NUM
fcis-28514	168	6	.	.	PUNCT
fcis-28514	169	1	[	[	X
fcis-28514	169	2	4	4	NUM
fcis-28514	169	3	]	]	X
fcis-28514	169	4	li	li	PROPN
fcis-28514	169	5	qingyuan	qingyuan	PROPN
fcis-28514	169	6	,	,	PUNCT
fcis-28514	169	7	deng	deng	PROPN
fcis-28514	169	8	zhaohong	zhaohong	PROPN
fcis-28514	169	9	,	,	PUNCT
fcis-28514	169	10	luo	luo	PROPN
fcis-28514	169	11	xiaoqing	xiaoqing	PROPN
fcis-28514	169	12	,	,	PUNCT
fcis-28514	169	13	et	et	PROPN
fcis-28514	169	14	al	al	PROPN
fcis-28514	169	15	.	.	PROPN
fcis-28514	169	16	ssd	ssd	PROPN
fcis-28514	169	17	object	object	NOUN
fcis-28514	169	18	detection	detection	NOUN
fcis-28514	169	19	algorithm	algorithm	NOUN
fcis-28514	169	20	with	with	ADP
fcis-28514	169	21	attention	attention	NOUN
fcis-28514	169	22	and	and	CCONJ
fcis-28514	169	23	cross	cross	ADJ
fcis-28514	169	24	-	-	NOUN
fcis-28514	169	25	scale	scale	ADJ
fcis-28514	169	26	fusion[j	fusion[j	NOUN
fcis-28514	169	27	]	]	PUNCT
fcis-28514	169	28	.	.	PUNCT
fcis-28514	170	1	journal	journal	PROPN
fcis-28514	170	2	of	of	ADP
fcis-28514	170	3	frontiers	frontier	NOUN
fcis-28514	170	4	of	of	ADP
fcis-28514	170	5	computer	computer	NOUN
fcis-28514	170	6	science	science	NOUN
fcis-28514	170	7	and	and	CCONJ
fcis-28514	170	8	technology	technology	NOUN
fcis-28514	170	9	,	,	PUNCT
fcis-28514	170	10	2022,16(11	2022,16(11	NUM
fcis-28514	170	11	):	):	PUNCT
fcis-28514	170	12	2575	2575	NUM
fcis-28514	170	13	-	-	SYM
fcis-28514	170	14	2586	2586	NUM
fcis-28514	170	15	.	.	PUNCT
fcis-28514	171	1	[	[	X
fcis-28514	171	2	5	5	NUM
fcis-28514	171	3	]	]	PUNCT
fcis-28514	171	4	ma	ma	PROPN
fcis-28514	171	5	j	j	PROPN
fcis-28514	171	6	,	,	PUNCT
fcis-28514	171	7	shao	shao	PROPN
fcis-28514	171	8	w	w	PROPN
fcis-28514	171	9	,	,	PUNCT
fcis-28514	171	10	ye	ye	PRON
fcis-28514	171	11	h	h	NOUN
fcis-28514	171	12	,	,	PUNCT
fcis-28514	171	13	et	et	PROPN
fcis-28514	171	14	al	al	PROPN
fcis-28514	171	15	.	.	PUNCT
fcis-28514	172	1	arbitrary	arbitrary	ADJ
fcis-28514	172	2	-	-	PUNCT
fcis-28514	172	3	oriented	orient	VERB
fcis-28514	172	4	scene	scene	NOUN
fcis-28514	172	5	text	text	NOUN
fcis-28514	172	6	detection	detection	NOUN
fcis-28514	172	7	via	via	ADP
fcis-28514	172	8	rotation	rotation	PROPN
fcis-28514	172	9	proposals[j	proposals[j	PROPN
fcis-28514	172	10	]	]	PUNCT
fcis-28514	172	11	.	.	PUNCT
fcis-28514	173	1	ieee	ieee	NOUN
fcis-28514	173	2	transactions	transaction	NOUN
fcis-28514	173	3	on	on	ADP
fcis-28514	173	4	multimedia	multimedia	NOUN
fcis-28514	173	5	,	,	PUNCT
fcis-28514	173	6	2017,99	2017,99	NUM
fcis-28514	173	7	:	:	PUNCT
fcis-28514	173	8	1	1	NUM
fcis-28514	173	9	-	-	SYM
fcis-28514	173	10	1	1	NUM
fcis-28514	173	11	.	.	PUNCT
fcis-28514	174	1	[	[	X
fcis-28514	174	2	6	6	NUM
fcis-28514	174	3	]	]	SYM
fcis-28514	174	4	li	li	PROPN
fcis-28514	174	5	y	y	PROPN
fcis-28514	174	6	,	,	PUNCT
fcis-28514	174	7	pang	pang	NOUN
fcis-28514	174	8	y	y	PROPN
fcis-28514	174	9	,	,	PUNCT
fcis-28514	174	10	shen	shen	PROPN
fcis-28514	174	11	j	j	PROPN
fcis-28514	174	12	,	,	PUNCT
fcis-28514	174	13	et	et	PROPN
fcis-28514	174	14	al	al	PROPN
fcis-28514	174	15	.	.	PROPN
fcis-28514	174	16	netnet	netnet	PROPN
fcis-28514	174	17	:	:	PUNCT
fcis-28514	174	18	neighbor	neighbor	NOUN
fcis-28514	174	19	erasing	erase	VERB
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fcis-28514	174	21	transferring	transfer	VERB
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fcis-28514	174	25	single	single	ADJ
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fcis-28514	177	12	for	for	ADP
fcis-28514	177	13	small	small	ADJ
fcis-28514	177	14	object	object	NOUN
fcis-28514	177	15	detection	detection	NOUN
fcis-28514	177	16	with	with	ADP
fcis-28514	177	17	dense	dense	ADJ
fcis-28514	177	18	detector[j	detector[j	NOUN
fcis-28514	177	19	]	]	PUNCT
fcis-28514	177	20	.	.	PUNCT
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fcis-28514	178	4	,	,	PUNCT
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fcis-28514	179	33	.	.	PUNCT
fcis-28514	180	1	2018	2018	NUM
fcis-28514	180	2	:	:	PUNCT
fcis-28514	180	3	8759	8759	NUM
fcis-28514	180	4	-	-	SYM
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fcis-28514	180	6	.	.	PUNCT
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fcis-28514	181	20	of	of	ADP
fcis-28514	181	21	the	the	DET
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fcis-28514	181	23	/	/	SYM
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fcis-28514	181	25	conference	conference	NOUN
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fcis-28514	181	27	computer	computer	NOUN
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fcis-28514	181	29	and	and	CCONJ
fcis-28514	181	30	pattern	pattern	NOUN
fcis-28514	181	31	recognition	recognition	NOUN
fcis-28514	181	32	.	.	PUNCT
fcis-28514	182	1	2020	2020	NUM
fcis-28514	182	2	:	:	PUNCT
fcis-28514	182	3	10781	10781	NUM
fcis-28514	182	4	-	-	SYM
fcis-28514	182	5	10790	10790	NUM
fcis-28514	182	6	.	.	PUNCT
fcis-28514	183	1	[	[	X
fcis-28514	183	2	10	10	NUM
fcis-28514	183	3	]	]	PUNCT
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fcis-28514	183	7	lin	lin	PROPN
fcis-28514	183	8	t	t	PROPN
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fcis-28514	183	21	pyramid	pyramid	NOUN
fcis-28514	183	22	architecture	architecture	NOUN
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fcis-28514	183	27	of	of	ADP
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fcis-28514	183	32	conference	conference	NOUN
fcis-28514	183	33	on	on	ADP
fcis-28514	183	34	computer	computer	NOUN
fcis-28514	183	35	vision	vision	NOUN
fcis-28514	183	36	and	and	CCONJ
fcis-28514	183	37	pattern	pattern	NOUN
fcis-28514	183	38	recognition	recognition	NOUN
fcis-28514	183	39	.	.	PUNCT
fcis-28514	184	1	2019	2019	NUM
fcis-28514	184	2	:	:	PUNCT
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fcis-28514	186	8	,	,	PUNCT
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fcis-28514	186	10	:	:	PUNCT
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fcis-28514	186	15	:	:	PUNCT
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fcis-28514	186	17	-	-	SYM
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fcis-28514	188	2	:	:	PUNCT
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fcis-28514	189	19	:	:	PUNCT
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fcis-28514	189	36	(	(	PUNCT
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fcis-28514	197	23	images[j	images[j	PROPN
fcis-28514	197	24	]	]	PUNCT
fcis-28514	197	25	.	.	PUNCT
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fcis-28514	198	11	,	,	PUNCT
fcis-28514	198	12	112:102966	112:102966	NUM
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fcis-28514	199	1	[	[	X
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fcis-28514	199	6	,	,	PUNCT
fcis-28514	199	7	lei	lei	PROPN
fcis-28514	199	8	y	y	PROPN
fcis-28514	199	9	,	,	PUNCT
fcis-28514	199	10	chan	chan	PROPN
fcis-28514	199	11	a	a	DET
fcis-28514	199	12	b.	b.	PROPN
fcis-28514	199	13	small	small	PROPN
fcis-28514	199	14	instance	instance	NOUN
fcis-28514	199	15	detection	detection	NOUN
fcis-28514	199	16	by	by	ADP
fcis-28514	199	17	integer	integer	NOUN
fcis-28514	199	18	programming	programming	NOUN
fcis-28514	199	19	on	on	ADP
fcis-28514	199	20	object	object	NOUN
fcis-28514	199	21	density	density	NOUN
fcis-28514	199	22	maps[c]//	maps[c]//	ADJ
fcis-28514	199	23	proceedings	proceeding	NOUN
fcis-28514	199	24	of	of	ADP
fcis-28514	199	25	the	the	DET
fcis-28514	199	26	ieee	ieee	NOUN
fcis-28514	199	27	conference	conference	NOUN
fcis-28514	199	28	on	on	ADP
fcis-28514	199	29	computer	computer	NOUN
fcis-28514	199	30	vision	vision	NOUN
fcis-28514	199	31	and	and	CCONJ
fcis-28514	199	32	pattern	pattern	NOUN
fcis-28514	199	33	recognition	recognition	NOUN
fcis-28514	199	34	.	.	PUNCT
fcis-28514	200	1	2015	2015	NUM
fcis-28514	200	2	:	:	PUNCT
fcis-28514	200	3	3689	3689	NUM
fcis-28514	200	4	-	-	SYM
fcis-28514	200	5	3697	3697	NUM
fcis-28514	200	6	.	.	PUNCT
fcis-28514	201	1	[	[	X
fcis-28514	201	2	18	18	NUM
fcis-28514	201	3	]	]	X
fcis-28514	201	4	zhu	zhu	PROPN
fcis-28514	201	5	x	x	SYM
fcis-28514	201	6	,	,	PUNCT
fcis-28514	201	7	lyu	lyu	X
fcis-28514	201	8	s	s	X
fcis-28514	201	9	,	,	PUNCT
fcis-28514	201	10	wang	wang	PROPN
fcis-28514	201	11	x	x	PROPN
fcis-28514	201	12	,	,	PUNCT
fcis-28514	201	13	et	et	PROPN
fcis-28514	201	14	al	al	PROPN
fcis-28514	201	15	.	.	PUNCT
fcis-28514	202	1	tph	tph	PROPN
fcis-28514	202	2	-	-	PUNCT
fcis-28514	202	3	yolov5	yolov5	PROPN
fcis-28514	202	4	:	:	PUNCT
fcis-28514	202	5	improved	improved	ADJ
fcis-28514	202	6	yolov5	yolov5	NOUN
fcis-28514	202	7	based	base	VERB
fcis-28514	202	8	on	on	ADP
fcis-28514	202	9	transformer	transformer	NOUN
fcis-28514	202	10	prediction	prediction	NOUN
fcis-28514	202	11	head	head	NOUN
fcis-28514	202	12	for	for	ADP
fcis-28514	202	13	object	object	NOUN
fcis-28514	202	14	detection	detection	NOUN
fcis-28514	202	15	on	on	ADP
fcis-28514	202	16	drone	drone	NOUN
fcis-28514	202	17	-	-	PUNCT
fcis-28514	202	18	captured	capture	VERB
fcis-28514	202	19	scenarios[c]//proceedings	scenarios[c]//proceeding	NOUN
fcis-28514	202	20	of	of	ADP
fcis-28514	202	21	the	the	DET
fcis-28514	202	22	ieee	ieee	NOUN
fcis-28514	202	23	/	/	SYM
fcis-28514	202	24	cvf	cvf	NOUN
fcis-28514	202	25	international	international	ADJ
fcis-28514	202	26	conference	conference	NOUN
fcis-28514	202	27	on	on	ADP
fcis-28514	202	28	computer	computer	NOUN
fcis-28514	202	29	vision	vision	NOUN
fcis-28514	202	30	.	.	PUNCT
fcis-28514	203	1	2021	2021	NUM
fcis-28514	203	2	:	:	PUNCT
fcis-28514	203	3	2778	2778	NUM
fcis-28514	203	4	-	-	SYM
fcis-28514	203	5	2788	2788	NUM
fcis-28514	203	6	.	.	PUNCT
fcis-28514	204	1	[	[	X
fcis-28514	204	2	19	19	NUM
fcis-28514	204	3	]	]	X
fcis-28514	204	4	zhang	zhang	PROPN
fcis-28514	204	5	z.	z.	PROPN
fcis-28514	204	6	drone	drone	PROPN
fcis-28514	204	7	-	-	PUNCT
fcis-28514	204	8	yolo	yolo	PROPN
fcis-28514	204	9	:	:	PUNCT
fcis-28514	204	10	an	an	DET
fcis-28514	204	11	efficient	efficient	ADJ
fcis-28514	204	12	neural	neural	ADJ
fcis-28514	204	13	network	network	NOUN
fcis-28514	204	14	method	method	NOUN
fcis-28514	204	15	for	for	ADP
fcis-28514	204	16	target	target	NOUN
fcis-28514	204	17	detection	detection	NOUN
fcis-28514	204	18	in	in	ADP
fcis-28514	204	19	drone	drone	NOUN
fcis-28514	204	20	images[j	images[j	PROPN
fcis-28514	204	21	]	]	PUNCT
fcis-28514	204	22	.	.	PUNCT
fcis-28514	205	1	drones	drone	NOUN
fcis-28514	205	2	,	,	PUNCT
fcis-28514	205	3	2023	2023	NUM
fcis-28514	205	4	,	,	PUNCT
fcis-28514	205	5	7(8	7(8	NUM
fcis-28514	205	6	):	):	PUNCT
fcis-28514	205	7	526	526	NUM
fcis-28514	205	8	.	.	PUNCT