id	sid	tid	token	lemma	pos
fcis-9900	1	1	frontiers	frontier	NOUN
fcis-9900	1	2	in	in	ADP
fcis-9900	1	3	computing	computing	NOUN
fcis-9900	1	4	and	and	CCONJ
fcis-9900	1	5	intelligent	intelligent	ADJ
fcis-9900	1	6	systems	system	NOUN
fcis-9900	1	7	issn	issn	VERB
fcis-9900	1	8	:	:	PUNCT
fcis-9900	1	9	2832	2832	NUM
fcis-9900	1	10	-	-	SYM
fcis-9900	1	11	6024	6024	NUM
fcis-9900	1	12	|	|	NOUN
fcis-9900	1	13	vol	vol	NOUN
fcis-9900	1	14	.	.	PROPN
fcis-9900	2	1	4	4	NUM
fcis-9900	2	2	,	,	PUNCT
fcis-9900	2	3	no	no	INTJ
fcis-9900	2	4	.	.	NOUN
fcis-9900	2	5	2	2	NUM
fcis-9900	2	6	,	,	PUNCT
fcis-9900	2	7	2023	2023	NUM
fcis-9900	2	8	40	40	NUM
fcis-9900	2	9	review	review	NOUN
fcis-9900	2	10	of	of	ADP
fcis-9900	2	11	small	small	ADJ
fcis-9900	2	12	target	target	NOUN
fcis-9900	2	13	detection	detection	NOUN
fcis-9900	2	14	based	base	VERB
fcis-9900	2	15	on	on	ADP
fcis-9900	2	16	deep	deep	ADJ
fcis-9900	2	17	learning	learn	VERB
fcis-9900	2	18	heng	heng	PROPN
fcis-9900	2	19	zhang	zhang	PROPN
fcis-9900	2	20	1	1	PROPN
fcis-9900	2	21	,	,	PUNCT
fcis-9900	2	22	*	*	PROPN
fcis-9900	2	23	,	,	PUNCT
fcis-9900	2	24	wei	wei	PROPN
fcis-9900	2	25	fu	fu	PROPN
fcis-9900	2	26	2	2	NUM
fcis-9900	2	27	,	,	PUNCT
fcis-9900	2	28	ke	ke	PROPN
fcis-9900	2	29	wu	wu	PROPN
fcis-9900	2	30	3	3	NUM
fcis-9900	2	31	1	1	NUM
fcis-9900	2	32	school	school	NOUN
fcis-9900	2	33	of	of	ADP
fcis-9900	2	34	computer	computer	NOUN
fcis-9900	2	35	and	and	CCONJ
fcis-9900	2	36	software	software	NOUN
fcis-9900	2	37	engineering	engineering	NOUN
fcis-9900	2	38	,	,	PUNCT
fcis-9900	2	39	xihua	xihua	PROPN
fcis-9900	2	40	university	university	PROPN
fcis-9900	2	41	,	,	PUNCT
fcis-9900	2	42	chengdu	chengdu	PROPN
fcis-9900	2	43	,	,	PUNCT
fcis-9900	2	44	sichuan	sichuan	PROPN
fcis-9900	2	45	,	,	PUNCT
fcis-9900	2	46	610039	610039	NUM
fcis-9900	2	47	,	,	PUNCT
fcis-9900	2	48	china	china	PROPN
fcis-9900	2	49	2	2	NUM
fcis-9900	2	50	college	college	NOUN
fcis-9900	2	51	of	of	ADP
fcis-9900	2	52	chinese	chinese	PROPN
fcis-9900	2	53	&	&	CCONJ
fcis-9900	2	54	asean	asean	PROPN
fcis-9900	2	55	arts	arts	PROPN
fcis-9900	2	56	,	,	PUNCT
fcis-9900	2	57	chengdu	chengdu	PROPN
fcis-9900	2	58	university	university	PROPN
fcis-9900	2	59	,	,	PUNCT
fcis-9900	2	60	chengdu	chengdu	PROPN
fcis-9900	2	61	,	,	PUNCT
fcis-9900	2	62	sichuan	sichuan	PROPN
fcis-9900	2	63	,	,	PUNCT
fcis-9900	2	64	610106	610106	NUM
fcis-9900	2	65	,	,	PUNCT
fcis-9900	2	66	china	china	PROPN
fcis-9900	2	67	3	3	NUM
fcis-9900	2	68	harbin	harbin	PROPN
fcis-9900	2	69	college	college	PROPN
fcis-9900	2	70	teacher	teacher	PROPN
fcis-9900	2	71	education	education	PROPN
fcis-9900	2	72	college	college	PROPN
fcis-9900	2	73	,	,	PUNCT
fcis-9900	2	74	harbin	harbin	PROPN
fcis-9900	2	75	university	university	PROPN
fcis-9900	2	76	,	,	PUNCT
fcis-9900	2	77	harbin	harbin	PROPN
fcis-9900	2	78	,	,	PUNCT
fcis-9900	2	79	heilongjiang	heilongjiang	PROPN
fcis-9900	2	80	,	,	PUNCT
fcis-9900	2	81	150080	150080	NUM
fcis-9900	2	82	,	,	PUNCT
fcis-9900	2	83	china	china	PROPN
fcis-9900	2	84	*	*	PUNCT
fcis-9900	2	85	corresponding	correspond	VERB
fcis-9900	2	86	author	author	NOUN
fcis-9900	2	87	:	:	PUNCT
fcis-9900	2	88	heng	heng	PROPN
fcis-9900	2	89	zhang	zhang	PROPN
fcis-9900	2	90	(	(	PUNCT
fcis-9900	2	91	email	email	NOUN
fcis-9900	2	92	:	:	PUNCT
fcis-9900	2	93	hengzhang_xhu@163.com	hengzhang_xhu@163.com	X
fcis-9900	2	94	)	)	PUNCT
fcis-9900	2	95	abstract	abstract	NOUN
fcis-9900	2	96	:	:	PUNCT
fcis-9900	2	97	with	with	ADP
fcis-9900	2	98	a	a	DET
fcis-9900	2	99	large	large	ADJ
fcis-9900	2	100	number	number	NOUN
fcis-9900	2	101	of	of	ADP
fcis-9900	2	102	applications	application	NOUN
fcis-9900	2	103	of	of	ADP
fcis-9900	2	104	target	target	NOUN
fcis-9900	2	105	detection	detection	NOUN
fcis-9900	2	106	in	in	ADP
fcis-9900	2	107	daily	daily	ADJ
fcis-9900	2	108	life	life	NOUN
fcis-9900	2	109	,	,	PUNCT
fcis-9900	2	110	the	the	DET
fcis-9900	2	111	performance	performance	NOUN
fcis-9900	2	112	requirements	requirement	NOUN
fcis-9900	2	113	of	of	ADP
fcis-9900	2	114	target	target	NOUN
fcis-9900	2	115	detection	detection	NOUN
fcis-9900	2	116	are	be	AUX
fcis-9900	2	117	constantly	constantly	ADV
fcis-9900	2	118	improving	improve	VERB
fcis-9900	2	119	.	.	PUNCT
fcis-9900	3	1	many	many	ADJ
fcis-9900	3	2	challenges	challenge	NOUN
fcis-9900	3	3	about	about	ADP
fcis-9900	3	4	target	target	NOUN
fcis-9900	3	5	detection	detection	NOUN
fcis-9900	3	6	have	have	AUX
fcis-9900	3	7	been	be	AUX
fcis-9900	3	8	put	put	VERB
fcis-9900	3	9	forward	forward	ADV
fcis-9900	3	10	constantly	constantly	ADV
fcis-9900	3	11	,	,	PUNCT
fcis-9900	3	12	such	such	ADJ
fcis-9900	3	13	as	as	ADP
fcis-9900	3	14	imbalanced	imbalanced	ADJ
fcis-9900	3	15	samples	sample	NOUN
fcis-9900	3	16	,	,	PUNCT
fcis-9900	3	17	fewer	few	ADJ
fcis-9900	3	18	pixels	pixel	NOUN
fcis-9900	3	19	,	,	PUNCT
fcis-9900	3	20	and	and	CCONJ
fcis-9900	3	21	occlusion	occlusion	NOUN
fcis-9900	3	22	of	of	ADP
fcis-9900	3	23	the	the	DET
fcis-9900	3	24	detected	detect	VERB
fcis-9900	3	25	target	target	NOUN
fcis-9900	3	26	,	,	PUNCT
fcis-9900	3	27	all	all	PRON
fcis-9900	3	28	of	of	ADP
fcis-9900	3	29	which	which	PRON
fcis-9900	3	30	bring	bring	VERB
fcis-9900	3	31	difficulties	difficulty	NOUN
fcis-9900	3	32	for	for	ADP
fcis-9900	3	33	the	the	DET
fcis-9900	3	34	model	model	NOUN
fcis-9900	3	35	to	to	PART
fcis-9900	3	36	correctly	correctly	ADV
fcis-9900	3	37	identify	identify	VERB
fcis-9900	3	38	the	the	DET
fcis-9900	3	39	target	target	NOUN
fcis-9900	3	40	.	.	PUNCT
fcis-9900	4	1	small	small	ADJ
fcis-9900	4	2	target	target	NOUN
fcis-9900	4	3	detection	detection	NOUN
fcis-9900	4	4	has	have	AUX
fcis-9900	4	5	always	always	ADV
fcis-9900	4	6	been	be	AUX
fcis-9900	4	7	a	a	DET
fcis-9900	4	8	difficult	difficult	ADJ
fcis-9900	4	9	point	point	NOUN
fcis-9900	4	10	and	and	CCONJ
fcis-9900	4	11	research	research	NOUN
fcis-9900	4	12	hotspot	hotspot	NOUN
fcis-9900	4	13	.	.	PUNCT
fcis-9900	5	1	in	in	ADP
fcis-9900	5	2	recent	recent	ADJ
fcis-9900	5	3	years	year	NOUN
fcis-9900	5	4	,	,	PUNCT
fcis-9900	5	5	many	many	ADJ
fcis-9900	5	6	algorithms	algorithm	NOUN
fcis-9900	5	7	for	for	ADP
fcis-9900	5	8	small	small	ADJ
fcis-9900	5	9	target	target	NOUN
fcis-9900	5	10	detection	detection	NOUN
fcis-9900	5	11	have	have	AUX
fcis-9900	5	12	been	be	AUX
fcis-9900	5	13	proposed	propose	VERB
fcis-9900	5	14	,	,	PUNCT
fcis-9900	5	15	such	such	ADJ
fcis-9900	5	16	as	as	ADP
fcis-9900	5	17	data	data	NOUN
fcis-9900	5	18	enhancement	enhancement	NOUN
fcis-9900	5	19	,	,	PUNCT
fcis-9900	5	20	feature	feature	NOUN
fcis-9900	5	21	fusion	fusion	NOUN
fcis-9900	5	22	,	,	PUNCT
fcis-9900	5	23	attention	attention	NOUN
fcis-9900	5	24	mechanism	mechanism	NOUN
fcis-9900	5	25	,	,	PUNCT
fcis-9900	5	26	and	and	CCONJ
fcis-9900	5	27	super	super	ADJ
fcis-9900	5	28	-	-	ADJ
fcis-9900	5	29	resolution	resolution	ADJ
fcis-9900	5	30	network	network	NOUN
fcis-9900	5	31	structure	structure	NOUN
fcis-9900	5	32	.	.	PUNCT
fcis-9900	6	1	according	accord	VERB
fcis-9900	6	2	to	to	ADP
fcis-9900	6	3	the	the	DET
fcis-9900	6	4	characteristics	characteristic	NOUN
fcis-9900	6	5	of	of	ADP
fcis-9900	6	6	different	different	ADJ
fcis-9900	6	7	network	network	NOUN
fcis-9900	6	8	structures	structure	NOUN
fcis-9900	6	9	,	,	PUNCT
fcis-9900	6	10	the	the	DET
fcis-9900	6	11	training	training	NOUN
fcis-9900	6	12	strategy	strategy	NOUN
fcis-9900	6	13	can	can	AUX
fcis-9900	6	14	be	be	AUX
fcis-9900	6	15	appropriately	appropriately	ADV
fcis-9900	6	16	adjusted	adjust	VERB
fcis-9900	6	17	and	and	CCONJ
fcis-9900	6	18	then	then	ADV
fcis-9900	6	19	applied	apply	VERB
fcis-9900	6	20	to	to	ADP
fcis-9900	6	21	different	different	ADJ
fcis-9900	6	22	environments	environment	NOUN
fcis-9900	6	23	,	,	PUNCT
fcis-9900	6	24	which	which	PRON
fcis-9900	6	25	can	can	AUX
fcis-9900	6	26	greatly	greatly	ADV
fcis-9900	6	27	improve	improve	VERB
fcis-9900	6	28	the	the	DET
fcis-9900	6	29	detection	detection	NOUN
fcis-9900	6	30	accuracy	accuracy	NOUN
fcis-9900	6	31	of	of	ADP
fcis-9900	6	32	small	small	ADJ
fcis-9900	6	33	targets	target	NOUN
fcis-9900	6	34	.	.	PUNCT
fcis-9900	7	1	this	this	DET
fcis-9900	7	2	paper	paper	NOUN
fcis-9900	7	3	will	will	AUX
fcis-9900	7	4	introduce	introduce	VERB
fcis-9900	7	5	the	the	DET
fcis-9900	7	6	data	data	NOUN
fcis-9900	7	7	sets	set	NOUN
fcis-9900	7	8	and	and	CCONJ
fcis-9900	7	9	related	relate	VERB
fcis-9900	7	10	small	small	ADJ
fcis-9900	7	11	target	target	NOUN
fcis-9900	7	12	detection	detection	NOUN
fcis-9900	7	13	algorithms	algorithm	NOUN
fcis-9900	7	14	proposed	propose	VERB
fcis-9900	7	15	in	in	ADP
fcis-9900	7	16	recent	recent	ADJ
fcis-9900	7	17	years	year	NOUN
fcis-9900	7	18	,	,	PUNCT
fcis-9900	7	19	and	and	CCONJ
fcis-9900	7	20	classify	classify	VERB
fcis-9900	7	21	,	,	PUNCT
fcis-9900	7	22	analyze	analyze	VERB
fcis-9900	7	23	,	,	PUNCT
fcis-9900	7	24	and	and	CCONJ
fcis-9900	7	25	compare	compare	VERB
fcis-9900	7	26	the	the	DET
fcis-9900	7	27	corresponding	corresponding	ADJ
fcis-9900	7	28	training	training	NOUN
fcis-9900	7	29	strategies	strategy	NOUN
fcis-9900	7	30	.	.	PUNCT
fcis-9900	8	1	keywords	keyword	NOUN
fcis-9900	8	2	:	:	PUNCT
fcis-9900	8	3	convolutional	convolutional	ADJ
fcis-9900	8	4	neural	neural	ADJ
fcis-9900	8	5	network	network	NOUN
fcis-9900	8	6	;	;	PUNCT
fcis-9900	8	7	residual	residual	ADJ
fcis-9900	8	8	network	network	NOUN
fcis-9900	8	9	;	;	PUNCT
fcis-9900	8	10	image	image	NOUN
fcis-9900	8	11	classification	classification	NOUN
fcis-9900	8	12	.	.	PUNCT
fcis-9900	9	1	1	1	X
fcis-9900	9	2	.	.	X
fcis-9900	9	3	introduction	introduction	NOUN
fcis-9900	9	4	target	target	NOUN
fcis-9900	9	5	detection	detection	NOUN
fcis-9900	9	6	,	,	PUNCT
fcis-9900	9	7	which	which	PRON
fcis-9900	9	8	has	have	AUX
fcis-9900	9	9	been	be	AUX
fcis-9900	9	10	developed	develop	VERB
fcis-9900	9	11	for	for	ADP
fcis-9900	9	12	about	about	ADV
fcis-9900	9	13	two	two	NUM
fcis-9900	9	14	decades	decade	NOUN
fcis-9900	9	15	,	,	PUNCT
fcis-9900	9	16	is	be	AUX
fcis-9900	9	17	a	a	DET
fcis-9900	9	18	very	very	ADV
fcis-9900	9	19	important	important	ADJ
fcis-9900	9	20	core	core	NOUN
fcis-9900	9	21	direction	direction	NOUN
fcis-9900	9	22	of	of	ADP
fcis-9900	9	23	computer	computer	NOUN
fcis-9900	9	24	vision	vision	NOUN
fcis-9900	9	25	and	and	CCONJ
fcis-9900	9	26	has	have	AUX
fcis-9900	9	27	made	make	VERB
fcis-9900	9	28	significant	significant	ADJ
fcis-9900	9	29	progress	progress	NOUN
fcis-9900	9	30	in	in	ADP
fcis-9900	9	31	recent	recent	ADJ
fcis-9900	9	32	years	year	NOUN
fcis-9900	9	33	.	.	PUNCT
fcis-9900	10	1	the	the	DET
fcis-9900	10	2	main	main	ADJ
fcis-9900	10	3	task	task	NOUN
fcis-9900	10	4	of	of	ADP
fcis-9900	10	5	target	target	NOUN
fcis-9900	10	6	detection	detection	NOUN
fcis-9900	10	7	consists	consist	VERB
fcis-9900	10	8	of	of	ADP
fcis-9900	10	9	two	two	NUM
fcis-9900	10	10	main	main	ADJ
fcis-9900	10	11	tasks	task	NOUN
fcis-9900	10	12	,	,	PUNCT
fcis-9900	10	13	i.e.	i.e.	X
fcis-9900	10	14	,	,	PUNCT
fcis-9900	10	15	target	target	VERB
fcis-9900	10	16	classification	classification	NOUN
fcis-9900	10	17	and	and	CCONJ
fcis-9900	10	18	target	target	NOUN
fcis-9900	10	19	localization	localization	NOUN
fcis-9900	10	20	,	,	PUNCT
fcis-9900	10	21	i.e.	i.e.	X
fcis-9900	10	22	,	,	PUNCT
fcis-9900	10	23	identifying	identify	VERB
fcis-9900	10	24	the	the	DET
fcis-9900	10	25	target	target	NOUN
fcis-9900	10	26	in	in	ADP
fcis-9900	10	27	the	the	DET
fcis-9900	10	28	image	image	NOUN
fcis-9900	10	29	and	and	CCONJ
fcis-9900	10	30	labeling	label	VERB
fcis-9900	10	31	the	the	DET
fcis-9900	10	32	location	location	NOUN
fcis-9900	10	33	information	information	NOUN
fcis-9900	10	34	of	of	ADP
fcis-9900	10	35	the	the	DET
fcis-9900	10	36	target	target	NOUN
fcis-9900	10	37	in	in	ADP
fcis-9900	10	38	the	the	DET
fcis-9900	10	39	image	image	NOUN
fcis-9900	10	40	,	,	PUNCT
fcis-9900	10	41	and	and	CCONJ
fcis-9900	10	42	the	the	DET
fcis-9900	10	43	detection	detection	NOUN
fcis-9900	10	44	task	task	NOUN
fcis-9900	10	45	is	be	AUX
fcis-9900	10	46	completed	complete	VERB
fcis-9900	10	47	.	.	PUNCT
fcis-9900	11	1	the	the	DET
fcis-9900	11	2	traditional	traditional	ADJ
fcis-9900	11	3	steps	step	NOUN
fcis-9900	11	4	of	of	ADP
fcis-9900	11	5	target	target	NOUN
fcis-9900	11	6	detection	detection	NOUN
fcis-9900	11	7	are	be	AUX
fcis-9900	11	8	region	region	NOUN
fcis-9900	11	9	selection	selection	NOUN
fcis-9900	11	10	,	,	PUNCT
fcis-9900	11	11	manual	manual	ADJ
fcis-9900	11	12	feature	feature	NOUN
fcis-9900	11	13	extraction	extraction	NOUN
fcis-9900	11	14	,	,	PUNCT
fcis-9900	11	15	and	and	CCONJ
fcis-9900	11	16	classifier	classifier	ADJ
fcis-9900	11	17	classification	classification	NOUN
fcis-9900	11	18	.	.	PUNCT
fcis-9900	12	1	the	the	DET
fcis-9900	12	2	common	common	ADJ
fcis-9900	12	3	traditional	traditional	ADJ
fcis-9900	12	4	methods	method	NOUN
fcis-9900	12	5	are	be	AUX
fcis-9900	12	6	vj	vj	PRON
fcis-9900	12	7	detector	detector	NOUN
fcis-9900	12	8	,	,	PUNCT
fcis-9900	12	9	hog	hog	NOUN
fcis-9900	12	10	features	feature	NOUN
fcis-9900	12	11	,	,	PUNCT
fcis-9900	12	12	variable	variable	ADJ
fcis-9900	12	13	part	part	NOUN
fcis-9900	12	14	model	model	NOUN
fcis-9900	12	15	(	(	PUNCT
fcis-9900	12	16	dpm	dpm	PROPN
fcis-9900	12	17	)	)	PUNCT
fcis-9900	12	18	,	,	PUNCT
fcis-9900	12	19	etc	etc	X
fcis-9900	12	20	.	.	X
fcis-9900	13	1	the	the	DET
fcis-9900	13	2	usual	usual	ADJ
fcis-9900	13	3	method	method	NOUN
fcis-9900	13	4	of	of	ADP
fcis-9900	13	5	manual	manual	ADJ
fcis-9900	13	6	feature	feature	NOUN
fcis-9900	13	7	extraction	extraction	NOUN
fcis-9900	13	8	is	be	AUX
fcis-9900	13	9	difficult	difficult	ADJ
fcis-9900	13	10	to	to	PART
fcis-9900	13	11	meet	meet	VERB
fcis-9900	13	12	the	the	DET
fcis-9900	13	13	demand	demand	NOUN
fcis-9900	13	14	of	of	ADP
fcis-9900	13	15	diverse	diverse	ADJ
fcis-9900	13	16	features	feature	NOUN
fcis-9900	13	17	of	of	ADP
fcis-9900	13	18	the	the	DET
fcis-9900	13	19	target	target	NOUN
fcis-9900	13	20	,	,	PUNCT
fcis-9900	13	21	which	which	PRON
fcis-9900	13	22	needs	need	VERB
fcis-9900	13	23	to	to	PART
fcis-9900	13	24	rely	rely	VERB
fcis-9900	13	25	on	on	ADP
fcis-9900	13	26	a	a	DET
fcis-9900	13	27	lot	lot	NOUN
fcis-9900	13	28	of	of	ADP
fcis-9900	13	29	experience	experience	NOUN
fcis-9900	13	30	and	and	CCONJ
fcis-9900	13	31	expertise	expertise	NOUN
fcis-9900	13	32	,	,	PUNCT
fcis-9900	13	33	and	and	CCONJ
fcis-9900	13	34	requires	require	VERB
fcis-9900	13	35	manual	manual	ADJ
fcis-9900	13	36	resetting	resetting	NOUN
fcis-9900	13	37	of	of	ADP
fcis-9900	13	38	features	feature	NOUN
fcis-9900	13	39	if	if	SCONJ
fcis-9900	13	40	a	a	DET
fcis-9900	13	41	change	change	NOUN
fcis-9900	13	42	of	of	ADP
fcis-9900	13	43	application	application	NOUN
fcis-9900	13	44	scenario	scenario	NOUN
fcis-9900	13	45	,	,	PUNCT
fcis-9900	13	46	with	with	ADP
fcis-9900	13	47	poor	poor	ADJ
fcis-9900	13	48	generalization	generalization	NOUN
fcis-9900	13	49	performance	performance	NOUN
fcis-9900	13	50	.	.	PUNCT
fcis-9900	14	1	therefore	therefore	ADV
fcis-9900	14	2	,	,	PUNCT
fcis-9900	14	3	this	this	DET
fcis-9900	14	4	solution	solution	NOUN
fcis-9900	14	5	has	have	AUX
fcis-9900	14	6	not	not	PART
fcis-9900	14	7	been	be	AUX
fcis-9900	14	8	a	a	DET
fcis-9900	14	9	good	good	ADJ
fcis-9900	14	10	solution	solution	NOUN
fcis-9900	14	11	to	to	ADP
fcis-9900	14	12	the	the	DET
fcis-9900	14	13	problem	problem	NOUN
fcis-9900	14	14	of	of	ADP
fcis-9900	14	15	target	target	NOUN
fcis-9900	14	16	detection	detection	NOUN
fcis-9900	14	17	feature	feature	NOUN
fcis-9900	14	18	extraction	extraction	NOUN
fcis-9900	14	19	.	.	PUNCT
fcis-9900	15	1	with	with	ADP
fcis-9900	15	2	the	the	DET
fcis-9900	15	3	rise	rise	NOUN
fcis-9900	15	4	of	of	ADP
fcis-9900	15	5	deep	deep	ADJ
fcis-9900	15	6	learning	learning	NOUN
fcis-9900	15	7	,	,	PUNCT
fcis-9900	15	8	cnns	cnn	NOUN
fcis-9900	15	9	have	have	AUX
fcis-9900	15	10	been	be	AUX
fcis-9900	15	11	widely	widely	ADV
fcis-9900	15	12	used	use	VERB
fcis-9900	15	13	in	in	ADP
fcis-9900	15	14	target	target	NOUN
fcis-9900	15	15	detection	detection	NOUN
fcis-9900	15	16	tasks	task	NOUN
fcis-9900	15	17	due	due	ADP
fcis-9900	15	18	to	to	ADP
fcis-9900	15	19	their	their	PRON
fcis-9900	15	20	powerful	powerful	ADJ
fcis-9900	15	21	feature	feature	NOUN
fcis-9900	15	22	extraction	extraction	NOUN
fcis-9900	15	23	and	and	CCONJ
fcis-9900	15	24	fitting	fitting	ADJ
fcis-9900	15	25	capabilities	capability	NOUN
fcis-9900	15	26	.	.	PUNCT
fcis-9900	16	1	2012	2012	NUM
fcis-9900	16	2	alex	alex	PROPN
fcis-9900	16	3	krizhevsky	krizhevsky	PROPN
fcis-9900	16	4	proposed	propose	VERB
fcis-9900	16	5	the	the	DET
fcis-9900	16	6	cnn	cnn	PROPN
fcis-9900	16	7	(	(	PUNCT
fcis-9900	16	8	convolutional	convolutional	ADJ
fcis-9900	16	9	neural	neural	ADJ
fcis-9900	16	10	networks	network	NOUN
fcis-9900	16	11	)	)	PUNCT
fcis-9900	16	12	model	model	NOUN
fcis-9900	16	13	at	at	ADP
fcis-9900	16	14	the	the	DET
fcis-9900	16	15	ilsvrc	ilsvrc	PROPN
fcis-9900	16	16	competition	competition	NOUN
fcis-9900	16	17	,	,	PUNCT
fcis-9900	16	18	which	which	PRON
fcis-9900	16	19	has	have	AUX
fcis-9900	16	20	achieved	achieve	VERB
fcis-9900	16	21	historic	historic	ADJ
fcis-9900	16	22	success	success	NOUN
fcis-9900	16	23	in	in	ADP
fcis-9900	16	24	the	the	DET
fcis-9900	16	25	field	field	NOUN
fcis-9900	16	26	of	of	ADP
fcis-9900	16	27	image	image	NOUN
fcis-9900	16	28	classification	classification	NOUN
fcis-9900	16	29	.	.	PUNCT
fcis-9900	17	1	this	this	DET
fcis-9900	17	2	model	model	NOUN
fcis-9900	17	3	has	have	AUX
fcis-9900	17	4	made	make	VERB
fcis-9900	17	5	a	a	DET
fcis-9900	17	6	historic	historic	ADJ
fcis-9900	17	7	breakthrough	breakthrough	NOUN
fcis-9900	17	8	in	in	ADP
fcis-9900	17	9	the	the	DET
fcis-9900	17	10	field	field	NOUN
fcis-9900	17	11	and	and	CCONJ
fcis-9900	17	12	has	have	VERB
fcis-9900	17	13	significant	significant	ADJ
fcis-9900	17	14	advantages	advantage	NOUN
fcis-9900	17	15	over	over	ADP
fcis-9900	17	16	traditional	traditional	ADJ
fcis-9900	17	17	methods	method	NOUN
fcis-9900	17	18	.	.	PUNCT
fcis-9900	18	1	in	in	ADP
fcis-9900	18	2	2014	2014	NUM
fcis-9900	18	3	,	,	PUNCT
fcis-9900	18	4	the	the	DET
fcis-9900	18	5	vgg	vgg	PROPN
fcis-9900	18	6	model	model	NOUN
fcis-9900	18	7	was	be	AUX
fcis-9900	18	8	proposed	propose	VERB
fcis-9900	18	9	by	by	ADP
fcis-9900	18	10	the	the	DET
fcis-9900	18	11	vgg	vgg	PROPN
fcis-9900	18	12	(	(	PUNCT
fcis-9900	18	13	visual	visual	ADJ
fcis-9900	18	14	geometry	geometry	NOUN
fcis-9900	18	15	group	group	NOUN
fcis-9900	18	16	)	)	PUNCT
fcis-9900	18	17	group	group	NOUN
fcis-9900	18	18	at	at	ADP
fcis-9900	18	19	the	the	DET
fcis-9900	18	20	university	university	NOUN
fcis-9900	18	21	of	of	ADP
fcis-9900	18	22	oxford	oxford	PROPN
fcis-9900	18	23	at	at	ADP
fcis-9900	18	24	the	the	DET
fcis-9900	18	25	ilsvrc	ilsvrc	PROPN
fcis-9900	18	26	competition	competition	NOUN
fcis-9900	18	27	.	.	PUNCT
fcis-9900	19	1	2014	2014	NUM
fcis-9900	19	2	,	,	PUNCT
fcis-9900	19	3	googlenet	googlenet	NOUN
fcis-9900	19	4	won	win	VERB
fcis-9900	19	5	the	the	DET
fcis-9900	19	6	ilsvrc	ilsvrc	ADJ
fcis-9900	19	7	competition	competition	NOUN
fcis-9900	19	8	,	,	PUNCT
fcis-9900	19	9	and	and	CCONJ
fcis-9900	19	10	the	the	DET
fcis-9900	19	11	googlenet	googlenet	NOUN
fcis-9900	19	12	model	model	NOUN
fcis-9900	19	13	consists	consist	VERB
fcis-9900	19	14	of	of	ADP
fcis-9900	19	15	multiple	multiple	ADJ
fcis-9900	19	16	groups	group	NOUN
fcis-9900	19	17	of	of	ADP
fcis-9900	19	18	inception	inception	ADJ
fcis-9900	19	19	modules	module	NOUN
fcis-9900	19	20	.	.	PUNCT
fcis-9900	20	1	in	in	ADP
fcis-9900	20	2	2015	2015	NUM
fcis-9900	20	3	,	,	PUNCT
fcis-9900	20	4	kai	kai	PROPN
fcis-9900	20	5	-	-	PUNCT
fcis-9900	20	6	ming	ming	PROPN
fcis-9900	20	7	he	he	PROPN
fcis-9900	20	8	,	,	PUNCT
fcis-9900	20	9	xiang	xiang	PROPN
fcis-9900	20	10	-	-	PUNCT
fcis-9900	20	11	yu	yu	PROPN
fcis-9900	20	12	zhang	zhang	PROPN
fcis-9900	20	13	,	,	PUNCT
fcis-9900	20	14	shao	shao	PROPN
fcis-9900	20	15	-	-	PUNCT
fcis-9900	20	16	qing	qe	VERB
fcis-9900	20	17	ren	ren	PROPN
fcis-9900	20	18	,	,	PUNCT
fcis-9900	20	19	and	and	CCONJ
fcis-9900	20	20	jian	jian	PROPN
fcis-9900	20	21	sun	sun	PROPN
fcis-9900	20	22	of	of	ADP
fcis-9900	20	23	microsoft	microsoft	PROPN
fcis-9900	20	24	research	research	PROPN
fcis-9900	20	25	proposed	propose	VERB
fcis-9900	20	26	the	the	DET
fcis-9900	20	27	resnet	resnet	NOUN
fcis-9900	20	28	(	(	PUNCT
fcis-9900	20	29	residual	residual	ADJ
fcis-9900	20	30	network	network	NOUN
fcis-9900	20	31	,	,	PUNCT
fcis-9900	20	32	or	or	CCONJ
fcis-9900	20	33	resnet	resnet	NOUN
fcis-9900	20	34	)	)	PUNCT
fcis-9900	20	35	model	model	NOUN
fcis-9900	20	36	.	.	PUNCT
fcis-9900	21	1	the	the	DET
fcis-9900	21	2	model	model	NOUN
fcis-9900	21	3	won	win	VERB
fcis-9900	21	4	the	the	DET
fcis-9900	21	5	championship	championship	NOUN
fcis-9900	21	6	in	in	ADP
fcis-9900	21	7	imagenet	imagenet	ADJ
fcis-9900	21	8	image	image	NOUN
fcis-9900	21	9	classification	classification	NOUN
fcis-9900	21	10	,	,	PUNCT
fcis-9900	21	11	image	image	NOUN
fcis-9900	21	12	object	object	NOUN
fcis-9900	21	13	localization	localization	NOUN
fcis-9900	21	14	,	,	PUNCT
fcis-9900	21	15	and	and	CCONJ
fcis-9900	21	16	image	image	NOUN
fcis-9900	21	17	object	object	NOUN
fcis-9900	21	18	detection	detection	NOUN
fcis-9900	21	19	competitions	competition	NOUN
fcis-9900	21	20	.	.	PUNCT
fcis-9900	22	1	therefore	therefore	ADV
fcis-9900	22	2	,	,	PUNCT
fcis-9900	22	3	the	the	DET
fcis-9900	22	4	development	development	NOUN
fcis-9900	22	5	of	of	ADP
fcis-9900	22	6	target	target	NOUN
fcis-9900	22	7	detection	detection	NOUN
fcis-9900	22	8	technology	technology	NOUN
fcis-9900	22	9	has	have	AUX
fcis-9900	22	10	been	be	AUX
fcis-9900	22	11	relatively	relatively	ADV
fcis-9900	22	12	mature	mature	ADJ
fcis-9900	22	13	,	,	PUNCT
fcis-9900	22	14	during	during	ADP
fcis-9900	22	15	which	which	PRON
fcis-9900	22	16	a	a	DET
fcis-9900	22	17	large	large	ADJ
fcis-9900	22	18	number	number	NOUN
fcis-9900	22	19	of	of	ADP
fcis-9900	22	20	classical	classical	ADJ
fcis-9900	22	21	target	target	NOUN
fcis-9900	22	22	detection	detection	NOUN
fcis-9900	22	23	algorithms	algorithm	NOUN
fcis-9900	22	24	emerged	emerge	VERB
fcis-9900	22	25	.	.	PUNCT
fcis-9900	23	1	currently	currently	ADV
fcis-9900	23	2	,	,	PUNCT
fcis-9900	23	3	target	target	NOUN
fcis-9900	23	4	detection	detection	NOUN
fcis-9900	23	5	algorithms	algorithm	NOUN
fcis-9900	23	6	can	can	AUX
fcis-9900	23	7	be	be	AUX
fcis-9900	23	8	mainly	mainly	ADV
fcis-9900	23	9	divided	divide	VERB
fcis-9900	23	10	into	into	ADP
fcis-9900	23	11	two	two	NUM
fcis-9900	23	12	categories	category	NOUN
fcis-9900	23	13	:	:	PUNCT
fcis-9900	23	14	single	single	ADJ
fcis-9900	23	15	-	-	PUNCT
fcis-9900	23	16	stage	stage	NOUN
fcis-9900	23	17	and	and	CCONJ
fcis-9900	23	18	two	two	NUM
fcis-9900	23	19	-	-	PUNCT
fcis-9900	23	20	stage	stage	NOUN
fcis-9900	23	21	.	.	PUNCT
fcis-9900	24	1	the	the	DET
fcis-9900	24	2	singlestage	singlestage	NOUN
fcis-9900	24	3	detection	detection	NOUN
fcis-9900	24	4	algorithms	algorithm	NOUN
fcis-9900	24	5	include	include	VERB
fcis-9900	24	6	yolo	yolo	ADJ
fcis-9900	24	7	series	series	NOUN
fcis-9900	24	8	,	,	PUNCT
fcis-9900	24	9	retinanet	retinanet	NOUN
fcis-9900	24	10	,	,	PUNCT
fcis-9900	24	11	ssd	ssd	NOUN
fcis-9900	24	12	algorithm	algorithm	NOUN
fcis-9900	24	13	,	,	PUNCT
fcis-9900	24	14	etc	etc	X
fcis-9900	24	15	.	.	X
fcis-9900	24	16	;	;	PUNCT
fcis-9900	24	17	while	while	SCONJ
fcis-9900	24	18	the	the	DET
fcis-9900	24	19	two	two	NUM
fcis-9900	24	20	-	-	PUNCT
fcis-9900	24	21	stage	stage	NOUN
fcis-9900	24	22	detection	detection	NOUN
fcis-9900	24	23	algorithms	algorithm	NOUN
fcis-9900	24	24	include	include	VERB
fcis-9900	24	25	rcnn	rcnn	PROPN
fcis-9900	24	26	,	,	PUNCT
fcis-9900	24	27	spp	spp	NOUN
fcis-9900	24	28	-	-	PUNCT
fcis-9900	24	29	net	net	NOUN
fcis-9900	24	30	,	,	PUNCT
fcis-9900	24	31	fast	fast	ADJ
fcis-9900	24	32	r	r	NOUN
fcis-9900	24	33	-	-	PUNCT
fcis-9900	24	34	cnn	cnn	PROPN
fcis-9900	24	35	,	,	PUNCT
fcis-9900	24	36	faster	fast	ADJ
fcis-9900	24	37	r	r	NOUN
fcis-9900	24	38	-	-	PUNCT
fcis-9900	24	39	cnn	cnn	PROPN
fcis-9900	24	40	,	,	PUNCT
fcis-9900	24	41	maskrcnn	maskrcnn	PROPN
fcis-9900	24	42	algorithm	algorithm	PROPN
fcis-9900	24	43	,	,	PUNCT
fcis-9900	24	44	etc	etc	X
fcis-9900	24	45	.	.	X
fcis-9900	24	46	among	among	ADP
fcis-9900	24	47	them	they	PRON
fcis-9900	24	48	,	,	PUNCT
fcis-9900	24	49	yolo	yolo	ADJ
fcis-9900	24	50	series	series	PROPN
fcis-9900	24	51	algorithms	algorithm	NOUN
fcis-9900	24	52	and	and	CCONJ
fcis-9900	24	53	faster	fast	ADJ
fcis-9900	24	54	r	r	NOUN
fcis-9900	24	55	-	-	PUNCT
fcis-9900	24	56	cnn	cnn	PROPN
fcis-9900	24	57	algorithms	algorithm	NOUN
fcis-9900	24	58	are	be	AUX
fcis-9900	24	59	practical	practical	ADJ
fcis-9900	24	60	target	target	NOUN
fcis-9900	24	61	detection	detection	NOUN
fcis-9900	24	62	methods	method	NOUN
fcis-9900	24	63	in	in	ADP
fcis-9900	24	64	the	the	DET
fcis-9900	24	65	industry	industry	NOUN
fcis-9900	24	66	,	,	PUNCT
fcis-9900	24	67	although	although	SCONJ
fcis-9900	24	68	some	some	DET
fcis-9900	24	69	algorithms	algorithm	NOUN
fcis-9900	24	70	have	have	AUX
fcis-9900	24	71	been	be	AUX
fcis-9900	24	72	particularly	particularly	ADV
fcis-9900	24	73	good	good	ADJ
fcis-9900	24	74	for	for	ADP
fcis-9900	24	75	normal	normal	ADJ
fcis-9900	24	76	targets	target	NOUN
fcis-9900	24	77	and	and	CCONJ
fcis-9900	24	78	have	have	AUX
fcis-9900	24	79	made	make	VERB
fcis-9900	24	80	substantial	substantial	ADJ
fcis-9900	24	81	progress	progress	NOUN
fcis-9900	24	82	in	in	ADP
fcis-9900	24	83	general	general	ADJ
fcis-9900	24	84	-	-	PUNCT
fcis-9900	24	85	purpose	purpose	NOUN
fcis-9900	24	86	target	target	NOUN
fcis-9900	24	87	detection	detection	NOUN
fcis-9900	24	88	.	.	PUNCT
fcis-9900	25	1	the	the	DET
fcis-9900	25	2	ways	way	NOUN
fcis-9900	25	3	of	of	ADP
fcis-9900	25	4	defining	define	VERB
fcis-9900	25	5	small	small	ADJ
fcis-9900	25	6	targets	target	NOUN
fcis-9900	25	7	can	can	AUX
fcis-9900	25	8	be	be	AUX
fcis-9900	25	9	mainly	mainly	ADV
fcis-9900	25	10	divided	divide	VERB
fcis-9900	25	11	into	into	ADP
fcis-9900	25	12	two	two	NUM
fcis-9900	25	13	categories	category	NOUN
fcis-9900	25	14	based	base	VERB
fcis-9900	25	15	on	on	ADP
fcis-9900	25	16	a	a	DET
fcis-9900	25	17	relative	relative	ADJ
fcis-9900	25	18	scale	scale	NOUN
fcis-9900	25	19	and	and	CCONJ
fcis-9900	25	20	an	an	DET
fcis-9900	25	21	absolute	absolute	ADJ
fcis-9900	25	22	scale	scale	NOUN
fcis-9900	25	23	.	.	PUNCT
fcis-9900	26	1	for	for	ADP
fcis-9900	26	2	the	the	DET
fcis-9900	26	3	definition	definition	NOUN
fcis-9900	26	4	based	base	VERB
fcis-9900	26	5	on	on	ADP
fcis-9900	26	6	a	a	DET
fcis-9900	26	7	relative	relative	ADJ
fcis-9900	26	8	scale	scale	NOUN
fcis-9900	26	9	,	,	PUNCT
fcis-9900	26	10	chen	chen	PROPN
fcis-9900	26	11	et	et	PROPN
fcis-9900	26	12	al	al	PROPN
fcis-9900	27	1	[	[	X
fcis-9900	27	2	1	1	NUM
fcis-9900	27	3	]	]	PUNCT
fcis-9900	27	4	defined	define	VERB
fcis-9900	27	5	small	small	ADJ
fcis-9900	27	6	targets	target	NOUN
fcis-9900	27	7	as	as	ADP
fcis-9900	27	8	those	those	PRON
fcis-9900	27	9	with	with	ADP
fcis-9900	27	10	a	a	DET
fcis-9900	27	11	median	median	ADJ
fcis-9900	27	12	relative	relative	ADJ
fcis-9900	27	13	area	area	NOUN
fcis-9900	27	14	,	,	PUNCT
fcis-9900	27	15	the	the	DET
fcis-9900	27	16	ratio	ratio	NOUN
fcis-9900	27	17	of	of	ADP
fcis-9900	27	18	bounding	bound	VERB
fcis-9900	27	19	box	box	NOUN
fcis-9900	27	20	area	area	NOUN
fcis-9900	27	21	to	to	ADP
fcis-9900	27	22	image	image	NOUN
fcis-9900	27	23	area	area	NOUN
fcis-9900	27	24	,	,	PUNCT
fcis-9900	27	25	of	of	ADP
fcis-9900	27	26	all	all	DET
fcis-9900	27	27	target	target	NOUN
fcis-9900	27	28	instances	instance	NOUN
fcis-9900	27	29	in	in	ADP
fcis-9900	27	30	the	the	DET
fcis-9900	27	31	same	same	ADJ
fcis-9900	27	32	class	class	NOUN
fcis-9900	27	33	between	between	ADP
fcis-9900	27	34	0.08	0.08	NUM
fcis-9900	27	35	%	%	NOUN
fcis-9900	27	36	and	and	CCONJ
fcis-9900	27	37	0.58	0.58	NUM
fcis-9900	27	38	%	%	NOUN
fcis-9900	27	39	.	.	PUNCT
fcis-9900	28	1	for	for	ADP
fcis-9900	28	2	the	the	DET
fcis-9900	28	3	definition	definition	NOUN
fcis-9900	28	4	of	of	ADP
fcis-9900	28	5	absolute	absolute	ADJ
fcis-9900	28	6	scale	scale	NOUN
fcis-9900	28	7	:	:	PUNCT
fcis-9900	28	8	in	in	ADP
fcis-9900	28	9	the	the	DET
fcis-9900	28	10	ms	ms	PROPN
fcis-9900	28	11	coco	coco	PROPN
fcis-9900	28	12	dataset	dataset	VERB
fcis-9900	29	1	[	[	X
fcis-9900	29	2	2	2	NUM
fcis-9900	29	3	]	]	PUNCT
fcis-9900	29	4	,	,	PUNCT
fcis-9900	29	5	a	a	DET
fcis-9900	29	6	small	small	ADJ
fcis-9900	29	7	target	target	NOUN
fcis-9900	29	8	is	be	AUX
fcis-9900	29	9	defined	define	VERB
fcis-9900	29	10	as	as	ADP
fcis-9900	29	11	a	a	DET
fcis-9900	29	12	target	target	NOUN
fcis-9900	29	13	with	with	ADP
fcis-9900	29	14	a	a	DET
fcis-9900	29	15	resolution	resolution	NOUN
fcis-9900	29	16	of	of	ADP
fcis-9900	29	17	less	less	ADJ
fcis-9900	29	18	than	than	ADP
fcis-9900	29	19	32	32	NUM
fcis-9900	29	20	×	×	NOUN
fcis-9900	29	21	32	32	NUM
fcis-9900	29	22	pixels	pixel	NOUN
fcis-9900	29	23	.	.	PUNCT
fcis-9900	30	1	according	accord	VERB
fcis-9900	30	2	to	to	ADP
fcis-9900	30	3	the	the	DET
fcis-9900	30	4	results	result	NOUN
fcis-9900	30	5	of	of	ADP
fcis-9900	30	6	ms	ms	PROPN
fcis-9900	30	7	coco	coco	PROPN
fcis-9900	30	8	,	,	PUNCT
fcis-9900	30	9	a	a	DET
fcis-9900	30	10	public	public	ADJ
fcis-9900	30	11	dataset	dataset	NOUN
fcis-9900	30	12	for	for	ADP
fcis-9900	30	13	target	target	NOUN
fcis-9900	30	14	detection	detection	NOUN
fcis-9900	30	15	,	,	PUNCT
fcis-9900	30	16	there	there	PRON
fcis-9900	30	17	is	be	VERB
fcis-9900	30	18	a	a	DET
fcis-9900	30	19	significant	significant	ADJ
fcis-9900	30	20	difference	difference	NOUN
fcis-9900	30	21	between	between	ADP
fcis-9900	30	22	large	large	ADJ
fcis-9900	30	23	and	and	CCONJ
fcis-9900	30	24	small	small	ADJ
fcis-9900	30	25	target	target	NOUN
fcis-9900	30	26	detection	detection	NOUN
fcis-9900	30	27	in	in	ADP
fcis-9900	30	28	terms	term	NOUN
fcis-9900	30	29	of	of	ADP
fcis-9900	30	30	detection	detection	NOUN
fcis-9900	30	31	accuracy	accuracy	NOUN
fcis-9900	30	32	,	,	PUNCT
fcis-9900	30	33	and	and	CCONJ
fcis-9900	30	34	the	the	DET
fcis-9900	30	35	detection	detection	NOUN
fcis-9900	30	36	accuracy	accuracy	NOUN
fcis-9900	30	37	of	of	ADP
fcis-9900	30	38	small	small	ADJ
fcis-9900	30	39	targets	target	NOUN
fcis-9900	30	40	is	be	AUX
fcis-9900	30	41	only	only	ADV
fcis-9900	30	42	half	half	NOUN
fcis-9900	30	43	of	of	ADP
fcis-9900	30	44	that	that	PRON
fcis-9900	30	45	of	of	ADP
fcis-9900	30	46	large	large	ADJ
fcis-9900	30	47	target	target	NOUN
fcis-9900	30	48	detection	detection	NOUN
fcis-9900	30	49	.	.	PUNCT
fcis-9900	31	1	the	the	DET
fcis-9900	31	2	detection	detection	NOUN
fcis-9900	31	3	of	of	ADP
fcis-9900	31	4	small	small	ADJ
fcis-9900	31	5	targets	target	NOUN
fcis-9900	31	6	mainly	mainly	ADV
fcis-9900	31	7	faces	face	VERB
fcis-9900	31	8	the	the	DET
fcis-9900	31	9	following	follow	VERB
fcis-9900	31	10	challenges	challenge	NOUN
fcis-9900	31	11	:	:	PUNCT
fcis-9900	31	12	firstly	firstly	ADV
fcis-9900	31	13	,	,	PUNCT
fcis-9900	31	14	the	the	DET
fcis-9900	31	15	problem	problem	NOUN
fcis-9900	31	16	of	of	ADP
fcis-9900	31	17	poor	poor	ADJ
fcis-9900	31	18	performance	performance	NOUN
fcis-9900	31	19	of	of	ADP
fcis-9900	31	20	small	small	ADJ
fcis-9900	31	21	target	target	NOUN
fcis-9900	31	22	detection	detection	NOUN
fcis-9900	31	23	has	have	AUX
fcis-9900	31	24	not	not	PART
fcis-9900	31	25	been	be	AUX
fcis-9900	31	26	completely	completely	ADV
fcis-9900	31	27	solved	solve	VERB
fcis-9900	31	28	due	due	ADJ
fcis-9900	31	29	to	to	ADP
fcis-9900	31	30	poor	poor	ADJ
fcis-9900	31	31	visual	visual	ADJ
fcis-9900	31	32	features	feature	NOUN
fcis-9900	31	33	,	,	PUNCT
fcis-9900	31	34	lack	lack	NOUN
fcis-9900	31	35	of	of	ADP
fcis-9900	31	36	sufficient	sufficient	ADJ
fcis-9900	31	37	appearance	appearance	NOUN
fcis-9900	31	38	information	information	NOUN
fcis-9900	31	39	,	,	PUNCT
fcis-9900	31	40	and	and	CCONJ
fcis-9900	31	41	fewer	few	ADJ
fcis-9900	31	42	useful	useful	ADJ
fcis-9900	31	43	pixel	pixel	NOUN
fcis-9900	31	44	points	point	NOUN
fcis-9900	31	45	corresponding	correspond	VERB
fcis-9900	31	46	to	to	ADP
fcis-9900	31	47	them	they	PRON
fcis-9900	31	48	,	,	PUNCT
fcis-9900	31	49	fewer	few	ADJ
fcis-9900	31	50	feature	feature	NOUN
fcis-9900	31	51	points	point	NOUN
fcis-9900	31	52	that	that	PRON
fcis-9900	31	53	can	can	AUX
fcis-9900	31	54	be	be	AUX
fcis-9900	31	55	extracted	extract	VERB
fcis-9900	31	56	,	,	PUNCT
fcis-9900	31	57	and	and	CCONJ
fcis-9900	31	58	more	more	ADJ
fcis-9900	31	59	noise	noise	NOUN
fcis-9900	31	60	.	.	PUNCT
fcis-9900	32	1	the	the	DET
fcis-9900	32	2	research	research	NOUN
fcis-9900	32	3	progress	progress	NOUN
fcis-9900	32	4	for	for	ADP
fcis-9900	32	5	small	small	ADJ
fcis-9900	32	6	target	target	NOUN
fcis-9900	32	7	detection	detection	NOUN
fcis-9900	32	8	is	be	AUX
fcis-9900	32	9	also	also	ADV
fcis-9900	32	10	relatively	relatively	ADV
fcis-9900	32	11	slow	slow	ADJ
fcis-9900	32	12	;	;	PUNCT
fcis-9900	32	13	secondly	secondly	ADV
fcis-9900	32	14	,	,	PUNCT
fcis-9900	32	15	the	the	DET
fcis-9900	32	16	large	large	ADJ
fcis-9900	32	17	-	-	PUNCT
fcis-9900	32	18	scale	scale	NOUN
fcis-9900	32	19	benchmark	benchmark	NOUN
fcis-9900	32	20	test	test	NOUN
fcis-9900	32	21	datasets	dataset	NOUN
fcis-9900	32	22	for	for	ADP
fcis-9900	32	23	small	small	ADJ
fcis-9900	32	24	-	-	PUNCT
fcis-9900	32	25	size	size	NOUN
fcis-9900	32	26	target	target	NOUN
fcis-9900	32	27	detection	detection	NOUN
fcis-9900	32	28	are	be	AUX
fcis-9900	32	29	still	still	ADV
fcis-9900	32	30	not	not	PART
fcis-9900	32	31	comprehensive	comprehensive	ADJ
fcis-9900	32	32	enough	enough	ADV
fcis-9900	32	33	,	,	PUNCT
fcis-9900	32	34	and	and	CCONJ
fcis-9900	32	35	the	the	DET
fcis-9900	32	36	available	available	ADJ
fcis-9900	32	37	datasets	dataset	NOUN
fcis-9900	32	38	can	can	AUX
fcis-9900	32	39	not	not	PART
fcis-9900	32	40	support	support	VERB
fcis-9900	32	41	model	model	NOUN
fcis-9900	32	42	training	training	NOUN
fcis-9900	32	43	for	for	ADP
fcis-9900	32	44	small	small	ADJ
fcis-9900	32	45	target	target	NOUN
fcis-9900	32	46	detection	detection	NOUN
fcis-9900	32	47	,	,	PUNCT
fcis-9900	32	48	nor	nor	CCONJ
fcis-9900	32	49	can	can	AUX
fcis-9900	32	50	they	they	PRON
fcis-9900	32	51	be	be	AUX
fcis-9900	32	52	used	use	VERB
fcis-9900	32	53	as	as	ADP
fcis-9900	32	54	an	an	DET
fcis-9900	32	55	unbiased	unbiased	ADJ
fcis-9900	32	56	benchmark	benchmark	NOUN
fcis-9900	32	57	for	for	ADP
fcis-9900	32	58	evaluating	evaluate	VERB
fcis-9900	32	59	algorithms	algorithm	NOUN
fcis-9900	32	60	,	,	PUNCT
fcis-9900	32	61	and	and	CCONJ
fcis-9900	32	62	there	there	PRON
fcis-9900	32	63	is	be	VERB
fcis-9900	32	64	a	a	DET
fcis-9900	32	65	lack	lack	NOUN
fcis-9900	32	66	of	of	ADP
fcis-9900	32	67	41	41	NUM
fcis-9900	32	68	large	large	ADJ
fcis-9900	32	69	-	-	PUNCT
fcis-9900	32	70	scale	scale	NOUN
fcis-9900	32	71	datasets	dataset	NOUN
fcis-9900	32	72	for	for	ADP
fcis-9900	32	73	small	small	ADJ
fcis-9900	32	74	target	target	NOUN
fcis-9900	32	75	detection	detection	NOUN
fcis-9900	32	76	;	;	PUNCT
fcis-9900	32	77	then	then	ADV
fcis-9900	32	78	,	,	PUNCT
fcis-9900	32	79	because	because	SCONJ
fcis-9900	32	80	the	the	DET
fcis-9900	32	81	general	general	ADJ
fcis-9900	32	82	target	target	NOUN
fcis-9900	32	83	detection	detection	NOUN
fcis-9900	32	84	network	network	NOUN
fcis-9900	32	85	structure	structure	NOUN
fcis-9900	32	86	is	be	AUX
fcis-9900	32	87	not	not	PART
fcis-9900	32	88	applicable	applicable	ADJ
fcis-9900	32	89	to	to	PART
fcis-9900	32	90	detect	detect	VERB
fcis-9900	32	91	small	small	ADJ
fcis-9900	32	92	targets	target	NOUN
fcis-9900	32	93	.	.	PUNCT
fcis-9900	33	1	because	because	SCONJ
fcis-9900	33	2	the	the	DET
fcis-9900	33	3	pooling	pooling	NOUN
fcis-9900	33	4	and	and	CCONJ
fcis-9900	33	5	convolution	convolution	NOUN
fcis-9900	33	6	operations	operation	NOUN
fcis-9900	33	7	make	make	VERB
fcis-9900	33	8	the	the	DET
fcis-9900	33	9	features	feature	NOUN
fcis-9900	33	10	of	of	ADP
fcis-9900	33	11	small	small	ADJ
fcis-9900	33	12	targets	target	NOUN
fcis-9900	33	13	disappear	disappear	VERB
fcis-9900	33	14	gradually	gradually	ADV
fcis-9900	33	15	as	as	SCONJ
fcis-9900	33	16	the	the	DET
fcis-9900	33	17	network	network	NOUN
fcis-9900	33	18	structure	structure	NOUN
fcis-9900	33	19	deepens	deepen	VERB
fcis-9900	33	20	,	,	PUNCT
fcis-9900	33	21	the	the	DET
fcis-9900	33	22	information	information	NOUN
fcis-9900	33	23	on	on	ADP
fcis-9900	33	24	small	small	ADJ
fcis-9900	33	25	targets	target	NOUN
fcis-9900	33	26	will	will	AUX
fcis-9900	33	27	be	be	AUX
fcis-9900	33	28	particularly	particularly	ADV
fcis-9900	33	29	small	small	ADJ
fcis-9900	33	30	or	or	CCONJ
fcis-9900	33	31	even	even	ADV
fcis-9900	33	32	disappear	disappear	VERB
fcis-9900	33	33	by	by	ADP
fcis-9900	33	34	the	the	DET
fcis-9900	33	35	end	end	NOUN
fcis-9900	33	36	of	of	ADP
fcis-9900	33	37	the	the	DET
fcis-9900	33	38	classification	classification	NOUN
fcis-9900	33	39	layer	layer	NOUN
fcis-9900	33	40	.	.	PUNCT
fcis-9900	34	1	finally	finally	ADV
fcis-9900	34	2	,	,	PUNCT
fcis-9900	34	3	in	in	ADP
fcis-9900	34	4	the	the	DET
fcis-9900	34	5	case	case	NOUN
fcis-9900	34	6	of	of	ADP
fcis-9900	34	7	small	small	ADJ
fcis-9900	34	8	target	target	NOUN
fcis-9900	34	9	aggregation	aggregation	NOUN
fcis-9900	34	10	,	,	PUNCT
fcis-9900	34	11	such	such	ADJ
fcis-9900	34	12	as	as	ADP
fcis-9900	34	13	the	the	DET
fcis-9900	34	14	remote	remote	ADJ
fcis-9900	34	15	sensing	sense	VERB
fcis-9900	34	16	image	image	NOUN
fcis-9900	34	17	of	of	ADP
fcis-9900	34	18	a	a	DET
fcis-9900	34	19	crowd	crowd	NOUN
fcis-9900	34	20	taken	take	VERB
fcis-9900	34	21	by	by	ADP
fcis-9900	34	22	uav	uav	PROPN
fcis-9900	34	23	,	,	PUNCT
fcis-9900	34	24	the	the	DET
fcis-9900	34	25	crowd	crowd	NOUN
fcis-9900	34	26	is	be	AUX
fcis-9900	34	27	densely	densely	ADV
fcis-9900	34	28	piled	pile	VERB
fcis-9900	34	29	up	up	ADP
fcis-9900	34	30	together	together	ADV
fcis-9900	34	31	at	at	ADP
fcis-9900	34	32	the	the	DET
fcis-9900	34	33	edge	edge	NOUN
fcis-9900	34	34	of	of	ADP
fcis-9900	34	35	the	the	DET
fcis-9900	34	36	image	image	NOUN
fcis-9900	34	37	,	,	PUNCT
fcis-9900	34	38	and	and	CCONJ
fcis-9900	34	39	it	it	PRON
fcis-9900	34	40	is	be	AUX
fcis-9900	34	41	very	very	ADV
fcis-9900	34	42	difficult	difficult	ADJ
fcis-9900	34	43	to	to	PART
fcis-9900	34	44	accurately	accurately	ADV
fcis-9900	34	45	locate	locate	VERB
fcis-9900	34	46	and	and	CCONJ
fcis-9900	34	47	identify	identify	VERB
fcis-9900	34	48	each	each	DET
fcis-9900	34	49	individual	individual	NOUN
fcis-9900	34	50	,	,	PUNCT
fcis-9900	34	51	and	and	CCONJ
fcis-9900	34	52	there	there	PRON
fcis-9900	34	53	is	be	VERB
fcis-9900	34	54	only	only	ADV
fcis-9900	34	55	one	one	NUM
fcis-9900	34	56	point	point	NOUN
fcis-9900	34	57	reflected	reflect	VERB
fcis-9900	34	58	on	on	ADP
fcis-9900	34	59	the	the	DET
fcis-9900	34	60	deep	deep	ADJ
fcis-9900	34	61	feature	feature	NOUN
fcis-9900	34	62	map	map	NOUN
fcis-9900	34	63	after	after	ADP
fcis-9900	34	64	multiple	multiple	ADJ
fcis-9900	34	65	downsampling	downsampling	NOUN
fcis-9900	34	66	,	,	PUNCT
fcis-9900	34	67	which	which	PRON
fcis-9900	34	68	leads	lead	VERB
fcis-9900	34	69	to	to	ADP
fcis-9900	34	70	the	the	DET
fcis-9900	34	71	inability	inability	NOUN
fcis-9900	34	72	of	of	ADP
fcis-9900	34	73	the	the	DET
fcis-9900	34	74	model	model	NOUN
fcis-9900	34	75	to	to	PART
fcis-9900	34	76	distinguish	distinguish	VERB
fcis-9900	34	77	the	the	DET
fcis-9900	34	78	targets	target	NOUN
fcis-9900	34	79	.	.	PUNCT
fcis-9900	35	1	small	small	ADJ
fcis-9900	35	2	target	target	NOUN
fcis-9900	35	3	detection	detection	NOUN
fcis-9900	35	4	has	have	AUX
fcis-9900	35	5	become	become	VERB
fcis-9900	35	6	one	one	NUM
fcis-9900	35	7	of	of	ADP
fcis-9900	35	8	the	the	DET
fcis-9900	35	9	most	most	ADV
fcis-9900	35	10	challenging	challenging	ADJ
fcis-9900	35	11	tasks	task	NOUN
fcis-9900	35	12	in	in	ADP
fcis-9900	35	13	computer	computer	NOUN
fcis-9900	35	14	vision	vision	NOUN
fcis-9900	35	15	.	.	PUNCT
fcis-9900	36	1	small	small	ADJ
fcis-9900	36	2	target	target	NOUN
fcis-9900	36	3	detection	detection	NOUN
fcis-9900	36	4	has	have	VERB
fcis-9900	36	5	a	a	DET
fcis-9900	36	6	very	very	ADV
fcis-9900	36	7	important	important	ADJ
fcis-9900	36	8	practical	practical	ADJ
fcis-9900	36	9	value	value	NOUN
fcis-9900	36	10	in	in	ADP
fcis-9900	36	11	a	a	DET
fcis-9900	36	12	variety	variety	NOUN
fcis-9900	36	13	of	of	ADP
fcis-9900	36	14	scenarios	scenario	NOUN
fcis-9900	36	15	such	such	ADJ
fcis-9900	36	16	as	as	ADP
fcis-9900	36	17	surveillance	surveillance	NOUN
fcis-9900	36	18	anti	anti	ADJ
fcis-9900	36	19	-	-	NOUN
fcis-9900	36	20	theft	theft	ADJ
fcis-9900	36	21	,	,	PUNCT
fcis-9900	36	22	uav	uav	PROPN
fcis-9900	36	23	scene	scene	PROPN
fcis-9900	36	24	analysis	analysis	NOUN
fcis-9900	36	25	,	,	PUNCT
fcis-9900	36	26	infrared	infrare	VERB
fcis-9900	36	27	weak	weak	ADJ
fcis-9900	36	28	target	target	NOUN
fcis-9900	36	29	detection	detection	NOUN
fcis-9900	36	30	,	,	PUNCT
fcis-9900	36	31	pedestrian	pedestrian	NOUN
fcis-9900	36	32	detection	detection	NOUN
fcis-9900	36	33	,	,	PUNCT
fcis-9900	36	34	and	and	CCONJ
fcis-9900	36	35	selfdriving	selfdrive	VERB
fcis-9900	36	36	traffic	traffic	NOUN
fcis-9900	36	37	sign	sign	NOUN
fcis-9900	36	38	detection	detection	NOUN
fcis-9900	36	39	.	.	PUNCT
fcis-9900	37	1	it	it	PRON
fcis-9900	37	2	can	can	AUX
fcis-9900	37	3	help	help	VERB
fcis-9900	37	4	people	people	NOUN
fcis-9900	37	5	to	to	PART
fcis-9900	37	6	better	well	ADV
fcis-9900	37	7	protect	protect	VERB
fcis-9900	37	8	property	property	NOUN
fcis-9900	37	9	security	security	NOUN
fcis-9900	37	10	,	,	PUNCT
fcis-9900	37	11	perform	perform	VERB
fcis-9900	37	12	scene	scene	NOUN
fcis-9900	37	13	analysis	analysis	NOUN
fcis-9900	37	14	,	,	PUNCT
fcis-9900	37	15	detect	detect	VERB
fcis-9900	37	16	infrared	infrare	VERB
fcis-9900	37	17	weak	weak	ADJ
fcis-9900	37	18	targets	target	NOUN
fcis-9900	37	19	,	,	PUNCT
fcis-9900	37	20	improve	improve	VERB
fcis-9900	37	21	traffic	traffic	NOUN
fcis-9900	37	22	safety	safety	NOUN
fcis-9900	37	23	,	,	PUNCT
fcis-9900	37	24	etc	etc	X
fcis-9900	37	25	.	.	X
fcis-9900	38	1	in	in	ADP
fcis-9900	38	2	recent	recent	ADJ
fcis-9900	38	3	years	year	NOUN
fcis-9900	38	4	,	,	PUNCT
fcis-9900	38	5	many	many	ADJ
fcis-9900	38	6	researchers	researcher	NOUN
fcis-9900	38	7	have	have	AUX
fcis-9900	38	8	proposed	propose	VERB
fcis-9900	38	9	many	many	ADJ
fcis-9900	38	10	excellent	excellent	ADJ
fcis-9900	38	11	small	small	ADJ
fcis-9900	38	12	target	target	NOUN
fcis-9900	38	13	detection	detection	NOUN
fcis-9900	38	14	algorithms	algorithm	NOUN
fcis-9900	38	15	concerning	concern	VERB
fcis-9900	38	16	network	network	NOUN
fcis-9900	38	17	structure	structure	NOUN
fcis-9900	38	18	,	,	PUNCT
fcis-9900	38	19	training	training	NOUN
fcis-9900	38	20	strategy	strategy	NOUN
fcis-9900	38	21	,	,	PUNCT
fcis-9900	38	22	data	datum	NOUN
fcis-9900	38	23	processing	processing	NOUN
fcis-9900	38	24	,	,	PUNCT
fcis-9900	38	25	etc	etc	X
fcis-9900	38	26	.	.	X
fcis-9900	39	1	some	some	DET
fcis-9900	39	2	processing	processing	NOUN
fcis-9900	39	3	based	base	VERB
fcis-9900	39	4	on	on	ADP
fcis-9900	39	5	the	the	DET
fcis-9900	39	6	generic	generic	ADJ
fcis-9900	39	7	target	target	NOUN
fcis-9900	39	8	detection	detection	NOUN
fcis-9900	39	9	algorithms	algorithm	NOUN
fcis-9900	39	10	is	be	AUX
fcis-9900	39	11	performed	perform	VERB
fcis-9900	39	12	to	to	PART
fcis-9900	39	13	adapt	adapt	VERB
fcis-9900	39	14	to	to	ADP
fcis-9900	39	15	specific	specific	ADJ
fcis-9900	39	16	small	small	ADJ
fcis-9900	39	17	target	target	NOUN
fcis-9900	39	18	detection	detection	NOUN
fcis-9900	39	19	applications	application	NOUN
fcis-9900	39	20	.	.	PUNCT
fcis-9900	40	1	for	for	ADP
fcis-9900	40	2	example	example	NOUN
fcis-9900	40	3	,	,	PUNCT
fcis-9900	40	4	yaeger	yaeger	PROPN
fcis-9900	40	5	et	et	PROPN
fcis-9900	40	6	al	al	PROPN
fcis-9900	40	7	[	[	X
fcis-9900	40	8	3	3	NUM
fcis-9900	40	9	]	]	PUNCT
fcis-9900	40	10	used	use	VERB
fcis-9900	40	11	data	data	NOUN
fcis-9900	40	12	augmentation	augmentation	NOUN
fcis-9900	40	13	methods	method	NOUN
fcis-9900	40	14	,	,	PUNCT
fcis-9900	40	15	including	include	VERB
fcis-9900	40	16	distortion	distortion	NOUN
fcis-9900	40	17	and	and	CCONJ
fcis-9900	40	18	deformation	deformation	NOUN
fcis-9900	40	19	,	,	PUNCT
fcis-9900	40	20	rotation	rotation	NOUN
fcis-9900	40	21	,	,	PUNCT
fcis-9900	40	22	and	and	CCONJ
fcis-9900	40	23	scaling	scaling	NOUN
fcis-9900	40	24	,	,	PUNCT
fcis-9900	40	25	to	to	PART
fcis-9900	40	26	enhance	enhance	VERB
fcis-9900	40	27	handwriting	handwriting	NOUN
fcis-9900	40	28	recognition	recognition	NOUN
fcis-9900	40	29	,	,	PUNCT
fcis-9900	40	30	thus	thus	ADV
fcis-9900	40	31	significantly	significantly	ADV
fcis-9900	40	32	improving	improve	VERB
fcis-9900	40	33	its	its	PRON
fcis-9900	40	34	recognition	recognition	NOUN
fcis-9900	40	35	accuracy	accuracy	NOUN
fcis-9900	40	36	;	;	PUNCT
fcis-9900	40	37	wei	wei	PROPN
fcis-9900	40	38	wei	wei	PROPN
fcis-9900	40	39	et	et	PROPN
fcis-9900	40	40	al	al	PROPN
fcis-9900	41	1	[	[	X
fcis-9900	41	2	4	4	X
fcis-9900	41	3	]	]	PUNCT
fcis-9900	41	4	improved	improve	VERB
fcis-9900	41	5	yolov3	yolov3	NOUN
fcis-9900	41	6	in	in	ADP
fcis-9900	41	7	aerial	aerial	ADJ
fcis-9900	41	8	target	target	NOUN
fcis-9900	41	9	detection	detection	NOUN
fcis-9900	41	10	by	by	ADP
fcis-9900	41	11	reducing	reduce	VERB
fcis-9900	41	12	some	some	DET
fcis-9900	41	13	convolution	convolution	NOUN
fcis-9900	41	14	operations	operation	NOUN
fcis-9900	41	15	and	and	CCONJ
fcis-9900	41	16	introducing	introduce	VERB
fcis-9900	41	17	jump	jump	NOUN
fcis-9900	41	18	layer	layer	NOUN
fcis-9900	41	19	connections	connection	NOUN
fcis-9900	41	20	on	on	ADP
fcis-9900	41	21	the	the	DET
fcis-9900	41	22	basis	basis	NOUN
fcis-9900	41	23	of	of	ADP
fcis-9900	41	24	yolov3	yolov3	PROPN
fcis-9900	41	25	model	model	PROPN
fcis-9900	41	26	,	,	PUNCT
fcis-9900	41	27	which	which	PRON
fcis-9900	41	28	then	then	ADV
fcis-9900	41	29	ensured	ensure	VERB
fcis-9900	41	30	the	the	DET
fcis-9900	41	31	real	real	ADJ
fcis-9900	41	32	-	-	PUNCT
fcis-9900	41	33	time	time	NOUN
fcis-9900	41	34	improves	improve	VERB
fcis-9900	41	35	the	the	DET
fcis-9900	41	36	detection	detection	NOUN
fcis-9900	41	37	accuracy	accuracy	NOUN
fcis-9900	41	38	of	of	ADP
fcis-9900	41	39	yolov3	yolov3	PROPN
fcis-9900	41	40	model	model	PROPN
fcis-9900	41	41	under	under	ADP
fcis-9900	41	42	the	the	DET
fcis-9900	41	43	guarantee	guarantee	NOUN
fcis-9900	41	44	of	of	ADP
fcis-9900	41	45	real	real	ADJ
fcis-9900	41	46	-	-	PUNCT
fcis-9900	41	47	time	time	NOUN
fcis-9900	41	48	;	;	PUNCT
fcis-9900	41	49	wang	wang	PROPN
fcis-9900	41	50	dongli	dongli	PROPN
fcis-9900	41	51	et	et	PROPN
fcis-9900	41	52	al	al	PROPN
fcis-9900	42	1	[	[	X
fcis-9900	42	2	5	5	NUM
fcis-9900	42	3	]	]	PUNCT
fcis-9900	42	4	went	go	VERB
fcis-9900	42	5	for	for	ADP
fcis-9900	42	6	visual	visual	ADJ
fcis-9900	42	7	small	small	ADJ
fcis-9900	42	8	target	target	NOUN
fcis-9900	42	9	detection	detection	NOUN
fcis-9900	42	10	by	by	ADP
fcis-9900	42	11	feature	feature	NOUN
fcis-9900	42	12	fusion	fusion	NOUN
fcis-9900	42	13	on	on	ADP
fcis-9900	42	14	ssd	ssd	NOUN
fcis-9900	42	15	model	model	NOUN
fcis-9900	42	16	to	to	PART
fcis-9900	42	17	fuse	fuse	VERB
fcis-9900	42	18	deep	deep	ADJ
fcis-9900	42	19	feature	feature	NOUN
fcis-9900	42	20	information	information	NOUN
fcis-9900	42	21	with	with	ADP
fcis-9900	42	22	shallow	shallow	ADJ
fcis-9900	42	23	feature	feature	NOUN
fcis-9900	42	24	information	information	NOUN
fcis-9900	42	25	,	,	PUNCT
fcis-9900	42	26	and	and	CCONJ
fcis-9900	42	27	then	then	ADV
fcis-9900	42	28	adjust	adjust	VERB
fcis-9900	42	29	the	the	DET
fcis-9900	42	30	prior	prior	ADJ
fcis-9900	42	31	frame	frame	NOUN
fcis-9900	42	32	according	accord	VERB
fcis-9900	42	33	to	to	ADP
fcis-9900	42	34	the	the	DET
fcis-9900	42	35	small	small	ADJ
fcis-9900	42	36	target	target	NOUN
fcis-9900	42	37	size	size	NOUN
fcis-9900	42	38	so	so	SCONJ
fcis-9900	42	39	that	that	SCONJ
fcis-9900	42	40	the	the	DET
fcis-9900	42	41	model	model	NOUN
fcis-9900	42	42	gets	get	VERB
fcis-9900	42	43	better	well	ADJ
fcis-9900	42	44	small	small	ADJ
fcis-9900	42	45	target	target	NOUN
fcis-9900	42	46	detection	detection	NOUN
fcis-9900	42	47	capability	capability	NOUN
fcis-9900	42	48	;	;	PUNCT
fcis-9900	42	49	xing	xing	PROPN
fcis-9900	42	50	c	c	PROPN
fcis-9900	42	51	et	et	PROPN
fcis-9900	42	52	al	al	PROPN
fcis-9900	43	1	[	[	X
fcis-9900	43	2	6	6	NUM
fcis-9900	43	3	]	]	PUNCT
fcis-9900	43	4	in	in	ADP
fcis-9900	43	5	2019	2019	NUM
fcis-9900	43	6	by	by	ADP
fcis-9900	43	7	segmenting	segment	VERB
fcis-9900	43	8	the	the	DET
fcis-9900	43	9	original	original	ADJ
fcis-9900	43	10	aerial	aerial	ADJ
fcis-9900	43	11	photography	photography	NOUN
fcis-9900	43	12	image	image	NOUN
fcis-9900	43	13	and	and	CCONJ
fcis-9900	43	14	using	use	VERB
fcis-9900	43	15	gan	gan	PROPN
fcis-9900	43	16	network	network	NOUN
fcis-9900	43	17	for	for	ADP
fcis-9900	43	18	super	super	NOUN
fcis-9900	43	19	-	-	NOUN
fcis-9900	43	20	resolution	resolution	NOUN
fcis-9900	43	21	in	in	ADP
fcis-9900	43	22	order	order	NOUN
fcis-9900	43	23	to	to	PART
fcis-9900	43	24	perform	perform	VERB
fcis-9900	43	25	pixel	pixel	ADJ
fcis-9900	43	26	enhancement	enhancement	NOUN
fcis-9900	43	27	of	of	ADP
fcis-9900	43	28	the	the	DET
fcis-9900	43	29	original	original	ADJ
fcis-9900	43	30	image	image	NOUN
fcis-9900	43	31	,	,	PUNCT
fcis-9900	43	32	which	which	PRON
fcis-9900	43	33	in	in	ADP
fcis-9900	43	34	turn	turn	NOUN
fcis-9900	43	35	improves	improve	VERB
fcis-9900	43	36	the	the	DET
fcis-9900	43	37	resolution	resolution	NOUN
fcis-9900	43	38	of	of	ADP
fcis-9900	43	39	small	small	ADJ
fcis-9900	43	40	targets	target	NOUN
fcis-9900	43	41	;	;	PUNCT
fcis-9900	43	42	zhao	zhao	X
fcis-9900	43	43	pengfei	pengfei	NOUN
fcis-9900	43	44	et	et	PROPN
fcis-9900	43	45	al	al	PROPN
fcis-9900	44	1	[	[	X
fcis-9900	44	2	7	7	X
fcis-9900	44	3	]	]	X
fcis-9900	44	4	the	the	DET
fcis-9900	44	5	algorithm	algorithm	NOUN
fcis-9900	44	6	uses	use	VERB
fcis-9900	44	7	multi	multi	ADJ
fcis-9900	44	8	-	-	ADJ
fcis-9900	44	9	scale	scale	ADJ
fcis-9900	44	10	null	null	ADJ
fcis-9900	44	11	convolution	convolution	NOUN
fcis-9900	44	12	cascade	cascade	NOUN
fcis-9900	44	13	to	to	PART
fcis-9900	44	14	expand	expand	VERB
fcis-9900	44	15	the	the	DET
fcis-9900	44	16	perceptual	perceptual	ADJ
fcis-9900	44	17	range	range	NOUN
fcis-9900	44	18	of	of	ADP
fcis-9900	44	19	the	the	DET
fcis-9900	44	20	feature	feature	NOUN
fcis-9900	44	21	map	map	NOUN
fcis-9900	44	22	and	and	CCONJ
fcis-9900	44	23	uses	use	VERB
fcis-9900	44	24	1×1	1×1	NUM
fcis-9900	44	25	convolution	convolution	NOUN
fcis-9900	44	26	for	for	ADP
fcis-9900	44	27	image	image	NOUN
fcis-9900	44	28	feature	feature	NOUN
fcis-9900	44	29	information	information	NOUN
fcis-9900	44	30	fusion	fusion	NOUN
fcis-9900	44	31	on	on	ADP
fcis-9900	44	32	this	this	DET
fcis-9900	44	33	basis	basis	NOUN
fcis-9900	44	34	.	.	PUNCT
fcis-9900	45	1	the	the	DET
fcis-9900	45	2	feature	feature	NOUN
fcis-9900	45	3	maps	map	NOUN
fcis-9900	45	4	of	of	ADP
fcis-9900	45	5	corresponding	correspond	VERB
fcis-9900	45	6	sizes	size	NOUN
fcis-9900	45	7	(	(	PUNCT
fcis-9900	45	8	38	38	NUM
fcis-9900	45	9	×	×	NOUN
fcis-9900	45	10	38	38	NUM
fcis-9900	45	11	,	,	PUNCT
fcis-9900	45	12	10	10	NUM
fcis-9900	45	13	×	×	NOUN
fcis-9900	45	14	10	10	NUM
fcis-9900	45	15	,	,	PUNCT
fcis-9900	45	16	and	and	CCONJ
fcis-9900	45	17	19	19	NUM
fcis-9900	45	18	×	×	NOUN
fcis-9900	45	19	19	19	NUM
fcis-9900	45	20	)	)	PUNCT
fcis-9900	45	21	are	be	AUX
fcis-9900	45	22	then	then	ADV
fcis-9900	45	23	stitched	stitch	VERB
fcis-9900	45	24	together	together	ADV
fcis-9900	45	25	and	and	CCONJ
fcis-9900	45	26	channel	channel	NOUN
fcis-9900	45	27	weighting	weighting	NOUN
fcis-9900	45	28	is	be	AUX
fcis-9900	45	29	implemented	implement	VERB
fcis-9900	45	30	using	use	VERB
fcis-9900	45	31	ecam	ecam	NOUN
fcis-9900	45	32	modules	module	NOUN
fcis-9900	45	33	.	.	PUNCT
fcis-9900	46	1	this	this	DET
fcis-9900	46	2	design	design	NOUN
fcis-9900	46	3	allows	allow	VERB
fcis-9900	46	4	for	for	ADP
fcis-9900	46	5	better	well	ADJ
fcis-9900	46	6	detail	detail	NOUN
fcis-9900	46	7	extraction	extraction	NOUN
fcis-9900	46	8	and	and	CCONJ
fcis-9900	46	9	feature	feature	NOUN
fcis-9900	46	10	fusion	fusion	NOUN
fcis-9900	46	11	of	of	ADP
fcis-9900	46	12	images	image	NOUN
fcis-9900	46	13	and	and	CCONJ
fcis-9900	46	14	improves	improve	VERB
fcis-9900	46	15	the	the	DET
fcis-9900	46	16	detection	detection	NOUN
fcis-9900	46	17	accuracy	accuracy	NOUN
fcis-9900	46	18	of	of	ADP
fcis-9900	46	19	the	the	DET
fcis-9900	46	20	algorithm	algorithm	NOUN
fcis-9900	46	21	.	.	PUNCT
fcis-9900	47	1	woo	woo	VERB
fcis-9900	47	2	et	et	NOUN
fcis-9900	47	3	al	al	PROPN
fcis-9900	48	1	[	[	X
fcis-9900	48	2	8	8	NUM
fcis-9900	48	3	]	]	PUNCT
fcis-9900	48	4	proposed	propose	VERB
fcis-9900	48	5	the	the	DET
fcis-9900	48	6	stairnet	stairnet	NOUN
fcis-9900	48	7	algorithm	algorithm	NOUN
fcis-9900	48	8	in	in	ADP
fcis-9900	48	9	2018	2018	NUM
fcis-9900	48	10	,	,	PUNCT
fcis-9900	48	11	which	which	PRON
fcis-9900	48	12	fuses	fuse	VERB
fcis-9900	48	13	feature	feature	VERB
fcis-9900	48	14	information	information	NOUN
fcis-9900	48	15	through	through	ADP
fcis-9900	48	16	deconvolution	deconvolution	NOUN
fcis-9900	48	17	with	with	ADP
fcis-9900	48	18	a	a	DET
fcis-9900	48	19	shallow	shallow	ADJ
fcis-9900	48	20	layer	layer	NOUN
fcis-9900	48	21	while	while	SCONJ
fcis-9900	48	22	passing	pass	VERB
fcis-9900	48	23	the	the	DET
fcis-9900	48	24	fused	fuse	VERB
fcis-9900	48	25	features	feature	NOUN
fcis-9900	48	26	to	to	ADP
fcis-9900	48	27	the	the	DET
fcis-9900	48	28	next	next	ADJ
fcis-9900	48	29	deconvolution	deconvolution	NOUN
fcis-9900	48	30	layer	layer	NOUN
fcis-9900	48	31	in	in	ADP
fcis-9900	48	32	a	a	DET
fcis-9900	48	33	top	top	ADJ
fcis-9900	48	34	-	-	PUNCT
fcis-9900	48	35	down	down	NOUN
fcis-9900	48	36	manner	manner	NOUN
fcis-9900	48	37	and	and	CCONJ
fcis-9900	48	38	then	then	ADV
fcis-9900	48	39	enhances	enhance	VERB
fcis-9900	48	40	the	the	DET
fcis-9900	48	41	target	target	NOUN
fcis-9900	48	42	semantic	semantic	ADJ
fcis-9900	48	43	information	information	NOUN
fcis-9900	48	44	;	;	PUNCT
fcis-9900	48	45	li	li	PROPN
fcis-9900	48	46	et	et	PROPN
fcis-9900	48	47	al	al	PROPN
fcis-9900	49	1	[	[	X
fcis-9900	49	2	9	9	NUM
fcis-9900	49	3	]	]	PUNCT
fcis-9900	49	4	proposed	propose	VERB
fcis-9900	49	5	an	an	DET
fcis-9900	49	6	attention	attention	NOUN
fcis-9900	49	7	mechanism	mechanism	NOUN
fcis-9900	49	8	,	,	PUNCT
fcis-9900	49	9	which	which	PRON
fcis-9900	49	10	they	they	PRON
fcis-9900	49	11	named	name	VERB
fcis-9900	49	12	knca	knca	ADJ
fcis-9900	49	13	-	-	PUNCT
fcis-9900	49	14	fusion	fusion	NOUN
fcis-9900	49	15	method	method	NOUN
fcis-9900	49	16	tested	test	VERB
fcis-9900	49	17	on	on	ADP
fcis-9900	49	18	public	public	ADJ
fcis-9900	49	19	datasets	dataset	NOUN
fcis-9900	49	20	achieved	achieve	VERB
fcis-9900	49	21	significant	significant	ADJ
fcis-9900	49	22	results	result	NOUN
fcis-9900	49	23	.	.	PUNCT
fcis-9900	50	1	2	2	X
fcis-9900	50	2	.	.	X
fcis-9900	50	3	small	small	ADJ
fcis-9900	50	4	target	target	NOUN
fcis-9900	50	5	dataset	dataset	VERB
fcis-9900	50	6	this	this	DET
fcis-9900	50	7	subsection	subsection	NOUN
fcis-9900	50	8	describes	describe	VERB
fcis-9900	50	9	the	the	DET
fcis-9900	50	10	dataset	dataset	NOUN
fcis-9900	50	11	used	use	VERB
fcis-9900	50	12	for	for	ADP
fcis-9900	50	13	small	small	ADJ
fcis-9900	50	14	target	target	NOUN
fcis-9900	50	15	detection	detection	NOUN
fcis-9900	50	16	.	.	PUNCT
fcis-9900	51	1	since	since	SCONJ
fcis-9900	51	2	deep	deep	ADJ
fcis-9900	51	3	learning	learning	NOUN
fcis-9900	51	4	-	-	PUNCT
fcis-9900	51	5	based	base	VERB
fcis-9900	51	6	target	target	NOUN
fcis-9900	51	7	detection	detection	NOUN
fcis-9900	51	8	algorithms	algorithm	NOUN
fcis-9900	51	9	are	be	AUX
fcis-9900	51	10	all	all	PRON
fcis-9900	51	11	data	data	NOUN
fcis-9900	51	12	-	-	PUNCT
fcis-9900	51	13	driven	drive	VERB
fcis-9900	51	14	,	,	PUNCT
fcis-9900	51	15	however	however	ADV
fcis-9900	51	16	,	,	PUNCT
fcis-9900	51	17	the	the	DET
fcis-9900	51	18	number	number	NOUN
fcis-9900	51	19	of	of	ADP
fcis-9900	51	20	large	large	ADJ
fcis-9900	51	21	targets	target	NOUN
fcis-9900	51	22	in	in	ADP
fcis-9900	51	23	the	the	DET
fcis-9900	51	24	initial	initial	ADJ
fcis-9900	51	25	target	target	NOUN
fcis-9900	51	26	detection	detection	NOUN
fcis-9900	51	27	dataset	dataset	NOUN
fcis-9900	51	28	is	be	AUX
fcis-9900	51	29	much	much	ADV
fcis-9900	51	30	higher	high	ADJ
fcis-9900	51	31	than	than	ADP
fcis-9900	51	32	that	that	PRON
fcis-9900	51	33	of	of	ADP
fcis-9900	51	34	small	small	ADJ
fcis-9900	51	35	targets	target	NOUN
fcis-9900	51	36	,	,	PUNCT
fcis-9900	51	37	which	which	PRON
fcis-9900	51	38	is	be	AUX
fcis-9900	51	39	an	an	DET
fcis-9900	51	40	important	important	ADJ
fcis-9900	51	41	factor	factor	NOUN
fcis-9900	51	42	limiting	limit	VERB
fcis-9900	51	43	the	the	DET
fcis-9900	51	44	development	development	NOUN
fcis-9900	51	45	of	of	ADP
fcis-9900	51	46	small	small	ADJ
fcis-9900	51	47	target	target	NOUN
fcis-9900	51	48	detection	detection	NOUN
fcis-9900	51	49	techniques	technique	NOUN
fcis-9900	51	50	.	.	PUNCT
fcis-9900	52	1	due	due	ADP
fcis-9900	52	2	to	to	ADP
fcis-9900	52	3	the	the	DET
fcis-9900	52	4	relatively	relatively	ADV
fcis-9900	52	5	small	small	ADJ
fcis-9900	52	6	portion	portion	NOUN
fcis-9900	52	7	of	of	ADP
fcis-9900	52	8	small	small	ADJ
fcis-9900	52	9	targets	target	NOUN
fcis-9900	52	10	in	in	ADP
fcis-9900	52	11	the	the	DET
fcis-9900	52	12	image	image	NOUN
fcis-9900	52	13	field	field	NOUN
fcis-9900	52	14	of	of	ADP
fcis-9900	52	15	view	view	NOUN
fcis-9900	52	16	and	and	CCONJ
fcis-9900	52	17	the	the	DET
fcis-9900	52	18	inconspicuous	inconspicuous	ADJ
fcis-9900	52	19	or	or	CCONJ
fcis-9900	52	20	even	even	ADV
fcis-9900	52	21	missing	miss	VERB
fcis-9900	52	22	edge	edge	NOUN
fcis-9900	52	23	features	feature	NOUN
fcis-9900	52	24	,	,	PUNCT
fcis-9900	52	25	deep	deep	ADJ
fcis-9900	52	26	learning	learning	NOUN
fcis-9900	52	27	-	-	PUNCT
fcis-9900	52	28	based	base	VERB
fcis-9900	52	29	small	small	ADJ
fcis-9900	52	30	target	target	NOUN
fcis-9900	52	31	detection	detection	NOUN
fcis-9900	52	32	algorithms	algorithm	NOUN
fcis-9900	52	33	are	be	AUX
fcis-9900	52	34	ineffective	ineffective	ADJ
fcis-9900	52	35	on	on	ADP
fcis-9900	52	36	common	common	ADJ
fcis-9900	52	37	target	target	NOUN
fcis-9900	52	38	detection	detection	NOUN
fcis-9900	52	39	datasets	dataset	NOUN
fcis-9900	52	40	because	because	SCONJ
fcis-9900	52	41	of	of	ADP
fcis-9900	52	42	the	the	DET
fcis-9900	52	43	limited	limited	ADJ
fcis-9900	52	44	resolution	resolution	NOUN
fcis-9900	52	45	and	and	CCONJ
fcis-9900	52	46	amount	amount	NOUN
fcis-9900	52	47	of	of	ADP
fcis-9900	52	48	information	information	NOUN
fcis-9900	52	49	.	.	PUNCT
fcis-9900	53	1	therefore	therefore	ADV
fcis-9900	53	2	,	,	PUNCT
fcis-9900	53	3	training	training	NOUN
fcis-9900	53	4	and	and	CCONJ
fcis-9900	53	5	detection	detection	NOUN
fcis-9900	53	6	tasks	task	NOUN
fcis-9900	53	7	for	for	ADP
fcis-9900	53	8	small	small	ADJ
fcis-9900	53	9	target	target	NOUN
fcis-9900	53	10	feature	feature	NOUN
fcis-9900	53	11	databases	database	NOUN
fcis-9900	53	12	are	be	AUX
fcis-9900	53	13	needed	need	VERB
fcis-9900	53	14	.	.	PUNCT
fcis-9900	54	1	to	to	PART
fcis-9900	54	2	promote	promote	VERB
fcis-9900	54	3	the	the	DET
fcis-9900	54	4	development	development	NOUN
fcis-9900	54	5	of	of	ADP
fcis-9900	54	6	small	small	ADJ
fcis-9900	54	7	target	target	NOUN
fcis-9900	54	8	detection	detection	NOUN
fcis-9900	54	9	techniques	technique	NOUN
fcis-9900	54	10	,	,	PUNCT
fcis-9900	54	11	many	many	ADJ
fcis-9900	54	12	datasets	dataset	NOUN
fcis-9900	54	13	targeting	target	VERB
fcis-9900	54	14	small	small	ADJ
fcis-9900	54	15	target	target	NOUN
fcis-9900	54	16	detection	detection	NOUN
fcis-9900	54	17	have	have	AUX
fcis-9900	54	18	been	be	AUX
fcis-9900	54	19	proposed	propose	VERB
fcis-9900	54	20	and	and	CCONJ
fcis-9900	54	21	published	publish	VERB
fcis-9900	54	22	in	in	ADP
fcis-9900	54	23	recent	recent	ADJ
fcis-9900	54	24	years	year	NOUN
fcis-9900	54	25	.	.	PUNCT
fcis-9900	55	1	2.1	2.1	NUM
fcis-9900	55	2	.	.	PUNCT
fcis-9900	56	1	ms	ms	PROPN
fcis-9900	56	2	coco	coco	PROPN
fcis-9900	56	3	dataset	dataset	VERB
fcis-9900	56	4	the	the	DET
fcis-9900	56	5	coco	coco	PROPN
fcis-9900	57	1	[	[	X
fcis-9900	57	2	10	10	NUM
fcis-9900	57	3	]	]	X
fcis-9900	57	4	dataset	dataset	NOUN
fcis-9900	57	5	is	be	AUX
fcis-9900	57	6	called	call	VERB
fcis-9900	57	7	microsoft	microsoft	PROPN
fcis-9900	57	8	common	common	ADJ
fcis-9900	57	9	objects	object	NOUN
fcis-9900	57	10	in	in	ADP
fcis-9900	57	11	context	context	NOUN
fcis-9900	57	12	(	(	PUNCT
fcis-9900	57	13	ms	ms	PROPN
fcis-9900	57	14	coco	coco	PROPN
fcis-9900	57	15	)	)	PUNCT
fcis-9900	57	16	,	,	PUNCT
fcis-9900	57	17	and	and	CCONJ
fcis-9900	57	18	the	the	DET
fcis-9900	57	19	coco	coco	PROPN
fcis-9900	57	20	dataset	dataset	PROPN
fcis-9900	57	21	is	be	AUX
fcis-9900	57	22	a	a	DET
fcis-9900	57	23	dataset	dataset	NOUN
fcis-9900	57	24	covering	cover	VERB
fcis-9900	57	25	large	large	ADJ
fcis-9900	57	26	-	-	PUNCT
fcis-9900	57	27	scale	scale	NOUN
fcis-9900	57	28	object	object	NOUN
fcis-9900	57	29	detection	detection	NOUN
fcis-9900	57	30	,	,	PUNCT
fcis-9900	57	31	segmentation	segmentation	NOUN
fcis-9900	57	32	,	,	PUNCT
fcis-9900	57	33	key	key	ADJ
fcis-9900	57	34	-	-	PUNCT
fcis-9900	57	35	point	point	NOUN
fcis-9900	57	36	detection	detection	NOUN
fcis-9900	57	37	,	,	PUNCT
fcis-9900	57	38	key	key	ADJ
fcis-9900	57	39	-	-	PUNCT
fcis-9900	57	40	point	point	NOUN
fcis-9900	57	41	detection	detection	NOUN
fcis-9900	57	42	,	,	PUNCT
fcis-9900	57	43	and	and	CCONJ
fcis-9900	57	44	captioning	captioning	NOUN
fcis-9900	57	45	tasks	task	NOUN
fcis-9900	57	46	.	.	PUNCT
fcis-9900	58	1	the	the	DET
fcis-9900	58	2	dataset	dataset	NOUN
fcis-9900	58	3	contains	contain	VERB
fcis-9900	58	4	a	a	DET
fcis-9900	58	5	huge	huge	ADJ
fcis-9900	58	6	number	number	NOUN
fcis-9900	58	7	of	of	ADP
fcis-9900	58	8	328,000	328,000	NUM
fcis-9900	58	9	images	image	NOUN
fcis-9900	58	10	.	.	PUNCT
fcis-9900	59	1	in	in	ADP
fcis-9900	59	2	terms	term	NOUN
fcis-9900	59	3	of	of	ADP
fcis-9900	59	4	target	target	NOUN
fcis-9900	59	5	detection	detection	NOUN
fcis-9900	59	6	,	,	PUNCT
fcis-9900	59	7	a	a	DET
fcis-9900	59	8	large	large	ADJ
fcis-9900	59	9	number	number	NOUN
fcis-9900	59	10	of	of	ADP
fcis-9900	59	11	small	small	ADJ
fcis-9900	59	12	targets	target	NOUN
fcis-9900	59	13	are	be	AUX
fcis-9900	59	14	included	include	VERB
fcis-9900	59	15	.	.	PUNCT
fcis-9900	60	1	a	a	DET
fcis-9900	60	2	total	total	NOUN
fcis-9900	60	3	of	of	ADP
fcis-9900	60	4	91	91	NUM
fcis-9900	60	5	classes	class	NOUN
fcis-9900	60	6	of	of	ADP
fcis-9900	60	7	targets	target	NOUN
fcis-9900	60	8	are	be	AUX
fcis-9900	60	9	included	include	VERB
fcis-9900	60	10	,	,	PUNCT
fcis-9900	60	11	with	with	ADP
fcis-9900	60	12	328,000	328,000	NUM
fcis-9900	60	13	images	image	NOUN
fcis-9900	60	14	and	and	CCONJ
fcis-9900	60	15	2.5	2.5	NUM
fcis-9900	60	16	million	million	NUM
fcis-9900	60	17	annotated	annotate	VERB
fcis-9900	60	18	frames	frame	NOUN
fcis-9900	60	19	.	.	PUNCT
fcis-9900	61	1	an	an	DET
fcis-9900	61	2	example	example	NOUN
fcis-9900	61	3	diagram	diagram	NOUN
fcis-9900	61	4	of	of	ADP
fcis-9900	61	5	the	the	DET
fcis-9900	61	6	coco	coco	PROPN
fcis-9900	61	7	dataset	dataset	PROPN
fcis-9900	61	8	is	be	AUX
fcis-9900	61	9	shown	show	VERB
fcis-9900	61	10	in	in	ADP
fcis-9900	61	11	figure	figure	NOUN
fcis-9900	61	12	1	1	NUM
fcis-9900	61	13	.	.	PUNCT
fcis-9900	61	14	link	link	VERB
fcis-9900	61	15	to	to	ADP
fcis-9900	61	16	the	the	DET
fcis-9900	61	17	coco	coco	PROPN
fcis-9900	61	18	dataset	dataset	PROPN
fcis-9900	61	19	:	:	PUNCT
fcis-9900	62	1	https://cocodataset.org/.	https://cocodataset.org/.	ADJ
fcis-9900	62	2	figure	figure	NOUN
fcis-9900	62	3	1	1	NUM
fcis-9900	62	4	.	.	NOUN
fcis-9900	62	5	example	example	NOUN
fcis-9900	62	6	graph	graph	NOUN
fcis-9900	62	7	of	of	ADP
fcis-9900	62	8	the	the	DET
fcis-9900	62	9	coco	coco	PROPN
fcis-9900	62	10	dataset	dataset	VERB
fcis-9900	62	11	2.2	2.2	NUM
fcis-9900	62	12	.	.	PUNCT
fcis-9900	63	1	eurocity	eurocity	NOUN
fcis-9900	63	2	persons	person	NOUN
fcis-9900	63	3	dataset	dataset	VERB
fcis-9900	63	4	figure	figure	NOUN
fcis-9900	63	5	2	2	NUM
fcis-9900	63	6	.	.	NOUN
fcis-9900	63	7	example	example	NOUN
fcis-9900	63	8	graph	graph	NOUN
fcis-9900	63	9	of	of	ADP
fcis-9900	63	10	eurocity	eurocity	NOUN
fcis-9900	63	11	persons	person	NOUN
fcis-9900	63	12	dataset	dataset	VERB
fcis-9900	63	13	42	42	NUM
fcis-9900	63	14	the	the	DET
fcis-9900	63	15	eurocity	eurocity	NOUN
fcis-9900	63	16	persons	person	NOUN
fcis-9900	63	17	[	[	X
fcis-9900	63	18	11	11	NUM
fcis-9900	63	19	]	]	X
fcis-9900	63	20	dataset	dataset	NOUN
fcis-9900	63	21	focuses	focus	VERB
fcis-9900	63	22	on	on	ADP
fcis-9900	63	23	urban	urban	ADJ
fcis-9900	63	24	traffic	traffic	NOUN
fcis-9900	63	25	scenarios	scenario	NOUN
fcis-9900	63	26	and	and	CCONJ
fcis-9900	63	27	contains	contain	VERB
fcis-9900	63	28	a	a	DET
fcis-9900	63	29	large	large	ADJ
fcis-9900	63	30	variety	variety	NOUN
fcis-9900	63	31	of	of	ADP
fcis-9900	63	32	accurate	accurate	ADJ
fcis-9900	63	33	and	and	CCONJ
fcis-9900	63	34	detailed	detailed	ADJ
fcis-9900	63	35	targets	target	NOUN
fcis-9900	63	36	.	.	PUNCT
fcis-9900	64	1	this	this	DET
fcis-9900	64	2	dataset	dataset	NOUN
fcis-9900	64	3	is	be	AUX
fcis-9900	64	4	almost	almost	ADV
fcis-9900	64	5	an	an	DET
fcis-9900	64	6	order	order	NOUN
fcis-9900	64	7	of	of	ADP
fcis-9900	64	8	magnitude	magnitude	NOUN
fcis-9900	64	9	larger	large	ADJ
fcis-9900	64	10	than	than	ADP
fcis-9900	64	11	the	the	DET
fcis-9900	64	12	previous	previous	ADJ
fcis-9900	64	13	dataset	dataset	NOUN
fcis-9900	64	14	used	use	VERB
fcis-9900	64	15	for	for	ADP
fcis-9900	64	16	benchmarking	benchmarke	VERB
fcis-9900	64	17	.	.	PUNCT
fcis-9900	65	1	the	the	DET
fcis-9900	65	2	dataset	dataset	NOUN
fcis-9900	65	3	covers	cover	VERB
fcis-9900	65	4	a	a	DET
fcis-9900	65	5	large	large	ADJ
fcis-9900	65	6	variety	variety	NOUN
fcis-9900	65	7	of	of	ADP
fcis-9900	65	8	categories	category	NOUN
fcis-9900	65	9	and	and	CCONJ
fcis-9900	65	10	is	be	AUX
fcis-9900	65	11	rich	rich	ADJ
fcis-9900	65	12	in	in	ADP
fcis-9900	65	13	detail	detail	NOUN
fcis-9900	65	14	,	,	PUNCT
fcis-9900	65	15	taking	take	VERB
fcis-9900	65	16	the	the	DET
fcis-9900	65	17	annotation	annotation	NOUN
fcis-9900	65	18	of	of	ADP
fcis-9900	65	19	people	people	NOUN
fcis-9900	65	20	in	in	ADP
fcis-9900	65	21	urban	urban	ADJ
fcis-9900	65	22	traffic	traffic	NOUN
fcis-9900	65	23	to	to	ADP
fcis-9900	65	24	a	a	DET
fcis-9900	65	25	new	new	ADJ
fcis-9900	65	26	level	level	NOUN
fcis-9900	65	27	.	.	PUNCT
fcis-9900	66	1	eurocity	eurocity	NOUN
fcis-9900	66	2	persons	person	VERB
fcis-9900	66	3	an	an	DET
fcis-9900	66	4	example	example	NOUN
fcis-9900	66	5	graph	graph	NOUN
fcis-9900	66	6	of	of	ADP
fcis-9900	66	7	the	the	DET
fcis-9900	66	8	dataset	dataset	NOUN
fcis-9900	66	9	is	be	AUX
fcis-9900	66	10	shown	show	VERB
fcis-9900	66	11	in	in	ADP
fcis-9900	66	12	figure	figure	NOUN
fcis-9900	66	13	2	2	NUM
fcis-9900	66	14	.	.	NOUN
fcis-9900	66	15	2.3	2.3	NUM
fcis-9900	66	16	.	.	PUNCT
fcis-9900	67	1	dota	dota	PROPN
fcis-9900	67	2	dataset	dataset	VERB
fcis-9900	67	3	the	the	DET
fcis-9900	67	4	dota	dota	PROPN
fcis-9900	67	5	dataset	dataset	VERB
fcis-9900	68	1	[	[	X
fcis-9900	68	2	12	12	NUM
fcis-9900	68	3	]	]	PUNCT
fcis-9900	68	4	is	be	AUX
fcis-9900	68	5	a	a	DET
fcis-9900	68	6	large	large	ADJ
fcis-9900	68	7	dataset	dataset	NOUN
fcis-9900	68	8	for	for	ADP
fcis-9900	68	9	target	target	NOUN
fcis-9900	68	10	detection	detection	NOUN
fcis-9900	68	11	in	in	ADP
fcis-9900	68	12	aerial	aerial	ADJ
fcis-9900	68	13	images	image	NOUN
fcis-9900	68	14	and	and	CCONJ
fcis-9900	68	15	contains	contain	VERB
fcis-9900	68	16	objects	object	NOUN
fcis-9900	68	17	of	of	ADP
fcis-9900	68	18	various	various	ADJ
fcis-9900	68	19	scales	scale	NOUN
fcis-9900	68	20	,	,	PUNCT
fcis-9900	68	21	orientations	orientation	NOUN
fcis-9900	68	22	,	,	PUNCT
fcis-9900	68	23	and	and	CCONJ
fcis-9900	68	24	shapes	shape	NOUN
fcis-9900	68	25	.	.	PUNCT
fcis-9900	69	1	the	the	DET
fcis-9900	69	2	annotated	annotate	VERB
fcis-9900	69	3	dota	dota	PROPN
fcis-9900	69	4	dataset	dataset	PROPN
fcis-9900	69	5	contains	contain	VERB
fcis-9900	69	6	188282	188282	NUM
fcis-9900	69	7	samples	sample	NOUN
fcis-9900	69	8	for	for	ADP
fcis-9900	69	9	all	all	DET
fcis-9900	69	10	images	image	NOUN
fcis-9900	69	11	.	.	PUNCT
fcis-9900	70	1	it	it	PRON
fcis-9900	70	2	includes	include	VERB
fcis-9900	70	3	the	the	DET
fcis-9900	70	4	dataset	dataset	NOUN
fcis-9900	70	5	of	of	ADP
fcis-9900	70	6	remote	remote	ADJ
fcis-9900	70	7	sensing	sense	VERB
fcis-9900	70	8	image	image	NOUN
fcis-9900	70	9	target	target	NOUN
fcis-9900	70	10	detection	detection	NOUN
fcis-9900	70	11	area	area	NOUN
fcis-9900	70	12	,	,	PUNCT
fcis-9900	70	13	including	include	VERB
fcis-9900	70	14	15	15	NUM
fcis-9900	70	15	categories	category	NOUN
fcis-9900	70	16	with	with	ADP
fcis-9900	70	17	2806	2806	NUM
fcis-9900	70	18	images	image	NOUN
fcis-9900	70	19	.	.	PUNCT
fcis-9900	71	1	the	the	DET
fcis-9900	71	2	dota	dota	PROPN
fcis-9900	71	3	dataset	dataset	NOUN
fcis-9900	71	4	has	have	AUX
fcis-9900	71	5	been	be	AUX
fcis-9900	71	6	applied	apply	VERB
fcis-9900	71	7	to	to	ADP
fcis-9900	71	8	cvpr21	cvpr21	NOUN
fcis-9900	71	9	small	small	ADJ
fcis-9900	71	10	target	target	NOUN
fcis-9900	71	11	detection	detection	NOUN
fcis-9900	71	12	.	.	PUNCT
fcis-9900	72	1	the	the	DET
fcis-9900	72	2	example	example	NOUN
fcis-9900	72	3	diagram	diagram	NOUN
fcis-9900	72	4	of	of	ADP
fcis-9900	72	5	the	the	DET
fcis-9900	72	6	dota	dota	PROPN
fcis-9900	72	7	dataset	dataset	NOUN
fcis-9900	72	8	is	be	AUX
fcis-9900	72	9	shown	show	VERB
fcis-9900	72	10	in	in	ADP
fcis-9900	72	11	figure	figure	NOUN
fcis-9900	72	12	3	3	NUM
fcis-9900	72	13	.	.	PUNCT
fcis-9900	72	14	figure	figure	NOUN
fcis-9900	72	15	3	3	NUM
fcis-9900	72	16	.	.	PUNCT
fcis-9900	72	17	schematic	schematic	ADJ
fcis-9900	72	18	diagram	diagram	NOUN
fcis-9900	72	19	of	of	ADP
fcis-9900	72	20	the	the	DET
fcis-9900	72	21	dota	dota	PROPN
fcis-9900	72	22	data	datum	NOUN
fcis-9900	72	23	set	set	VERB
fcis-9900	72	24	.	.	PUNCT
fcis-9900	73	1	2.4	2.4	NUM
fcis-9900	73	2	.	.	PUNCT
fcis-9900	74	1	tinyperson	tinyperson	NOUN
fcis-9900	74	2	dataset	dataset	VERB
fcis-9900	74	3	the	the	DET
fcis-9900	74	4	tinyperson	tinyperson	NOUN
fcis-9900	74	5	dataset	dataset	VERB
fcis-9900	75	1	[	[	X
fcis-9900	75	2	13	13	NUM
fcis-9900	75	3	]	]	PUNCT
fcis-9900	75	4	is	be	AUX
fcis-9900	75	5	a	a	DET
fcis-9900	75	6	benchmark	benchmark	NOUN
fcis-9900	75	7	for	for	ADP
fcis-9900	75	8	tiny	tiny	ADJ
fcis-9900	75	9	object	object	NOUN
fcis-9900	75	10	detection	detection	NOUN
fcis-9900	75	11	at	at	ADP
fcis-9900	75	12	long	long	ADJ
fcis-9900	75	13	distances	distance	NOUN
fcis-9900	75	14	and	and	CCONJ
fcis-9900	75	15	large	large	ADJ
fcis-9900	75	16	-	-	PUNCT
fcis-9900	75	17	scale	scale	NOUN
fcis-9900	75	18	backgrounds	background	NOUN
fcis-9900	75	19	.	.	PUNCT
fcis-9900	76	1	the	the	DET
fcis-9900	76	2	images	image	NOUN
fcis-9900	76	3	in	in	ADP
fcis-9900	76	4	tinyperson	tinyperson	NOUN
fcis-9900	76	5	are	be	AUX
fcis-9900	76	6	collected	collect	VERB
fcis-9900	76	7	from	from	ADP
fcis-9900	76	8	the	the	DET
fcis-9900	76	9	web	web	NOUN
fcis-9900	76	10	.	.	PUNCT
fcis-9900	77	1	first	first	ADV
fcis-9900	77	2	,	,	PUNCT
fcis-9900	77	3	highresolution	highresolution	NOUN
fcis-9900	77	4	videos	video	NOUN
fcis-9900	77	5	are	be	AUX
fcis-9900	77	6	collected	collect	VERB
fcis-9900	77	7	from	from	ADP
fcis-9900	77	8	different	different	ADJ
fcis-9900	77	9	websites	website	NOUN
fcis-9900	77	10	.	.	PUNCT
fcis-9900	78	1	second	second	ADJ
fcis-9900	78	2	,	,	PUNCT
fcis-9900	78	3	the	the	DET
fcis-9900	78	4	images	image	NOUN
fcis-9900	78	5	in	in	ADP
fcis-9900	78	6	the	the	DET
fcis-9900	78	7	videos	video	NOUN
fcis-9900	78	8	are	be	AUX
fcis-9900	78	9	sampled	sample	VERB
fcis-9900	78	10	every	every	DET
fcis-9900	78	11	50	50	NUM
fcis-9900	78	12	frames	frame	NOUN
fcis-9900	78	13	.	.	PUNCT
fcis-9900	79	1	then	then	ADV
fcis-9900	79	2	images	image	VERB
fcis-9900	79	3	with	with	ADP
fcis-9900	79	4	certain	certain	ADJ
fcis-9900	79	5	duplicates	duplicate	NOUN
fcis-9900	79	6	(	(	PUNCT
fcis-9900	79	7	homogeneity	homogeneity	NOUN
fcis-9900	79	8	)	)	PUNCT
fcis-9900	79	9	are	be	AUX
fcis-9900	79	10	removed	remove	VERB
fcis-9900	79	11	and	and	CCONJ
fcis-9900	79	12	72,651	72,651	NUM
fcis-9900	79	13	objects	object	NOUN
fcis-9900	79	14	with	with	ADP
fcis-9900	79	15	bounding	bounding	NOUN
fcis-9900	79	16	boxes	box	NOUN
fcis-9900	79	17	are	be	AUX
fcis-9900	79	18	used	use	VERB
fcis-9900	79	19	to	to	PART
fcis-9900	79	20	manually	manually	ADV
fcis-9900	79	21	annotate	annotate	VERB
fcis-9900	79	22	the	the	DET
fcis-9900	79	23	resulting	result	VERB
fcis-9900	79	24	images	image	NOUN
fcis-9900	79	25	.	.	PUNCT
fcis-9900	80	1	the	the	DET
fcis-9900	80	2	training	training	NOUN
fcis-9900	80	3	set	set	NOUN
fcis-9900	80	4	contains	contain	VERB
fcis-9900	80	5	794	794	NUM
fcis-9900	80	6	images	image	NOUN
fcis-9900	80	7	and	and	CCONJ
fcis-9900	80	8	the	the	DET
fcis-9900	80	9	test	test	NOUN
fcis-9900	80	10	set	set	NOUN
fcis-9900	80	11	contains	contain	VERB
fcis-9900	80	12	816	816	NUM
fcis-9900	80	13	images	image	NOUN
fcis-9900	80	14	.	.	PUNCT
fcis-9900	81	1	an	an	DET
fcis-9900	81	2	example	example	NOUN
fcis-9900	81	3	graph	graph	NOUN
fcis-9900	81	4	of	of	ADP
fcis-9900	81	5	the	the	DET
fcis-9900	81	6	tinyperson	tinyperson	NOUN
fcis-9900	81	7	dataset	dataset	NOUN
fcis-9900	81	8	is	be	AUX
fcis-9900	81	9	shown	show	VERB
fcis-9900	81	10	in	in	ADP
fcis-9900	81	11	figure	figure	NOUN
fcis-9900	81	12	4	4	NUM
fcis-9900	81	13	.	.	PUNCT
fcis-9900	81	14	figure	figure	VERB
fcis-9900	81	15	4	4	NUM
fcis-9900	81	16	.	.	PUNCT
fcis-9900	81	17	schematic	schematic	ADJ
fcis-9900	81	18	diagram	diagram	NOUN
fcis-9900	81	19	of	of	ADP
fcis-9900	81	20	the	the	DET
fcis-9900	81	21	tinyperson	tinyperson	NOUN
fcis-9900	81	22	dataset	dataset	NOUN
fcis-9900	81	23	.	.	PUNCT
fcis-9900	82	1	2.5	2.5	NUM
fcis-9900	82	2	.	.	PUNCT
fcis-9900	82	3	deepscores	deepscore	NOUN
fcis-9900	82	4	dataset	dataset	VERB
fcis-9900	82	5	the	the	DET
fcis-9900	82	6	goal	goal	NOUN
fcis-9900	82	7	of	of	ADP
fcis-9900	82	8	the	the	DET
fcis-9900	82	9	deepscores	deepscore	NOUN
fcis-9900	82	10	[	[	X
fcis-9900	82	11	14	14	NUM
fcis-9900	82	12	]	]	X
fcis-9900	82	13	dataset	dataset	NOUN
fcis-9900	82	14	is	be	AUX
fcis-9900	82	15	to	to	PART
fcis-9900	82	16	advance	advance	VERB
fcis-9900	82	17	the	the	DET
fcis-9900	82	18	state	state	NOUN
fcis-9900	82	19	of	of	ADP
fcis-9900	82	20	the	the	DET
fcis-9900	82	21	art	art	NOUN
fcis-9900	82	22	in	in	ADP
fcis-9900	82	23	small	small	ADJ
fcis-9900	82	24	object	object	NOUN
fcis-9900	82	25	recognition	recognition	NOUN
fcis-9900	82	26	and	and	CCONJ
fcis-9900	82	27	to	to	PART
fcis-9900	82	28	place	place	VERB
fcis-9900	82	29	the	the	DET
fcis-9900	82	30	object	object	NOUN
fcis-9900	82	31	recognition	recognition	NOUN
fcis-9900	82	32	problem	problem	NOUN
fcis-9900	82	33	in	in	ADP
fcis-9900	82	34	the	the	DET
fcis-9900	82	35	context	context	NOUN
fcis-9900	82	36	of	of	ADP
fcis-9900	82	37	scene	scene	NOUN
fcis-9900	82	38	understanding	understanding	NOUN
fcis-9900	82	39	.	.	PUNCT
fcis-9900	83	1	deepscores	deepscore	NOUN
fcis-9900	83	2	contains	contain	VERB
fcis-9900	83	3	high	high	ADJ
fcis-9900	83	4	-	-	PUNCT
fcis-9900	83	5	quality	quality	NOUN
fcis-9900	83	6	sheet	sheet	NOUN
fcis-9900	83	7	music	music	NOUN
fcis-9900	83	8	images	image	NOUN
fcis-9900	83	9	divided	divide	VERB
fcis-9900	83	10	into	into	ADP
fcis-9900	83	11	300,000	300,000	NUM
fcis-9900	83	12	written	write	VERB
fcis-9900	83	13	music	music	NOUN
fcis-9900	83	14	sheets	sheet	NOUN
fcis-9900	83	15	containing	contain	VERB
fcis-9900	83	16	symbols	symbol	NOUN
fcis-9900	83	17	of	of	ADP
fcis-9900	83	18	different	different	ADJ
fcis-9900	83	19	shapes	shape	NOUN
fcis-9900	83	20	and	and	CCONJ
fcis-9900	83	21	sizes	size	NOUN
fcis-9900	83	22	.	.	PUNCT
fcis-9900	84	1	to	to	PART
fcis-9900	84	2	improve	improve	VERB
fcis-9900	84	3	the	the	DET
fcis-9900	84	4	technology	technology	NOUN
fcis-9900	84	5	of	of	ADP
fcis-9900	84	6	small	small	ADJ
fcis-9900	84	7	object	object	NOUN
fcis-9900	84	8	recognition	recognition	NOUN
fcis-9900	84	9	and	and	CCONJ
fcis-9900	84	10	to	to	PART
fcis-9900	84	11	place	place	VERB
fcis-9900	84	12	the	the	DET
fcis-9900	84	13	object	object	NOUN
fcis-9900	84	14	recognition	recognition	NOUN
fcis-9900	84	15	problem	problem	NOUN
fcis-9900	84	16	in	in	ADP
fcis-9900	84	17	the	the	DET
fcis-9900	84	18	context	context	NOUN
fcis-9900	84	19	of	of	ADP
fcis-9900	84	20	scene	scene	NOUN
fcis-9900	84	21	understanding	understanding	NOUN
fcis-9900	84	22	is	be	AUX
fcis-9900	84	23	studied	study	VERB
fcis-9900	84	24	.	.	PUNCT
fcis-9900	85	1	datasets	dataset	NOUN
fcis-9900	85	2	that	that	PRON
fcis-9900	85	3	can	can	AUX
fcis-9900	85	4	be	be	AUX
fcis-9900	85	5	used	use	VERB
fcis-9900	85	6	to	to	PART
fcis-9900	85	7	segment	segment	VERB
fcis-9900	85	8	,	,	PUNCT
fcis-9900	85	9	detect	detect	VERB
fcis-9900	85	10	and	and	CCONJ
fcis-9900	85	11	classify	classify	VERB
fcis-9900	85	12	tiny	tiny	ADJ
fcis-9900	85	13	objects	object	NOUN
fcis-9900	85	14	.	.	PUNCT
fcis-9900	85	15	has	have	AUX
fcis-9900	85	16	been	be	AUX
fcis-9900	85	17	used	use	VERB
fcis-9900	85	18	for	for	ADP
fcis-9900	85	19	road	road	NOUN
fcis-9900	85	20	vehicle	vehicle	NOUN
fcis-9900	85	21	anomaly	anomaly	NOUN
fcis-9900	85	22	detection	detection	NOUN
fcis-9900	85	23	and	and	CCONJ
fcis-9900	85	24	for	for	ADP
fcis-9900	85	25	detecting	detect	VERB
fcis-9900	85	26	anomalies	anomaly	NOUN
fcis-9900	85	27	in	in	ADP
fcis-9900	85	28	video	video	NOUN
fcis-9900	85	29	streams	stream	NOUN
fcis-9900	85	30	.	.	PUNCT
fcis-9900	86	1	an	an	DET
fcis-9900	86	2	example	example	NOUN
fcis-9900	86	3	graph	graph	NOUN
fcis-9900	86	4	of	of	ADP
fcis-9900	86	5	the	the	DET
fcis-9900	86	6	deepscores	deepscore	NOUN
fcis-9900	86	7	dataset	dataset	NOUN
fcis-9900	86	8	is	be	AUX
fcis-9900	86	9	shown	show	VERB
fcis-9900	86	10	in	in	ADP
fcis-9900	86	11	figure	figure	NOUN
fcis-9900	86	12	5	5	NUM
fcis-9900	86	13	.	.	PUNCT
fcis-9900	86	14	figure	figure	NOUN
fcis-9900	86	15	5	5	NUM
fcis-9900	86	16	.	.	PUNCT
fcis-9900	86	17	schematic	schematic	ADJ
fcis-9900	86	18	diagram	diagram	NOUN
fcis-9900	86	19	of	of	ADP
fcis-9900	86	20	the	the	DET
fcis-9900	86	21	deepscores	deepscore	NOUN
fcis-9900	86	22	dataset	dataset	VERB
fcis-9900	86	23	2.6	2.6	NUM
fcis-9900	86	24	.	.	PUNCT
fcis-9900	87	1	other	other	ADJ
fcis-9900	87	2	small	small	ADJ
fcis-9900	87	3	target	target	NOUN
fcis-9900	87	4	datasets	dataset	VERB
fcis-9900	87	5	other	other	ADJ
fcis-9900	87	6	datasets	dataset	NOUN
fcis-9900	87	7	include	include	VERB
fcis-9900	87	8	the	the	DET
fcis-9900	87	9	wider	wide	ADJ
fcis-9900	87	10	face	face	NOUN
fcis-9900	87	11	[	[	X
fcis-9900	87	12	15	15	NUM
fcis-9900	87	13	]	]	X
fcis-9900	87	14	dataset	dataset	NOUN
fcis-9900	87	15	,	,	PUNCT
fcis-9900	87	16	citypersons	cityperson	NOUN
fcis-9900	87	17	[	[	X
fcis-9900	87	18	16	16	NUM
fcis-9900	87	19	]	]	X
fcis-9900	87	20	dataset	dataset	NOUN
fcis-9900	87	21	,	,	PUNCT
fcis-9900	87	22	ai	ai	VERB
fcis-9900	87	23	-	-	PUNCT
fcis-9900	87	24	tod	tod	NOUN
fcis-9900	87	25	[	[	X
fcis-9900	87	26	17	17	NUM
fcis-9900	87	27	]	]	X
fcis-9900	87	28	dataset	dataset	NOUN
fcis-9900	87	29	,	,	PUNCT
fcis-9900	87	30	isaid	isaid	VERB
fcis-9900	87	31	[	[	X
fcis-9900	87	32	18	18	NUM
fcis-9900	87	33	]	]	PUNCT
fcis-9900	87	34	dataset	dataset	NOUN
fcis-9900	87	35	,	,	PUNCT
fcis-9900	87	36	widerperson	widerperson	NOUN
fcis-9900	88	1	[	[	X
fcis-9900	88	2	19	19	NUM
fcis-9900	88	3	]	]	X
fcis-9900	88	4	dataset	dataset	NOUN
fcis-9900	88	5	,	,	PUNCT
fcis-9900	88	6	and	and	CCONJ
fcis-9900	88	7	penn	penn	PROPN
fcis-9900	88	8	-	-	PUNCT
fcis-9900	88	9	fudan	fudan	NOUN
fcis-9900	88	10	pedestrian	pedestrian	NOUN
fcis-9900	88	11	detection	detection	NOUN
fcis-9900	88	12	and	and	CCONJ
fcis-9900	88	13	segmentation	segmentation	NOUN
fcis-9900	88	14	dataset	dataset	VERB
fcis-9900	88	15	.	.	PUNCT
fcis-9900	89	1	3	3	X
fcis-9900	89	2	.	.	X
fcis-9900	89	3	optimization	optimization	NOUN
fcis-9900	89	4	methods	method	NOUN
fcis-9900	89	5	for	for	ADP
fcis-9900	89	6	small	small	ADJ
fcis-9900	89	7	target	target	NOUN
fcis-9900	89	8	detection	detection	NOUN
fcis-9900	89	9	commonly	commonly	ADV
fcis-9900	89	10	used	use	VERB
fcis-9900	89	11	optimization	optimization	NOUN
fcis-9900	89	12	algorithms	algorithm	NOUN
fcis-9900	89	13	to	to	PART
fcis-9900	89	14	improve	improve	VERB
fcis-9900	89	15	the	the	DET
fcis-9900	89	16	accuracy	accuracy	NOUN
fcis-9900	89	17	of	of	ADP
fcis-9900	89	18	small	small	ADJ
fcis-9900	89	19	target	target	NOUN
fcis-9900	89	20	detection	detection	NOUN
fcis-9900	89	21	include	include	VERB
fcis-9900	89	22	multi	multi	ADJ
fcis-9900	89	23	-	-	ADJ
fcis-9900	89	24	scale	scale	ADJ
fcis-9900	89	25	feature	feature	NOUN
fcis-9900	89	26	fusion	fusion	NOUN
fcis-9900	89	27	and	and	CCONJ
fcis-9900	89	28	feature	feature	NOUN
fcis-9900	89	29	enhancement	enhancement	NOUN
fcis-9900	89	30	techniques	technique	NOUN
fcis-9900	89	31	,	,	PUNCT
fcis-9900	89	32	a	a	DET
fcis-9900	89	33	combination	combination	NOUN
fcis-9900	89	34	between	between	ADP
fcis-9900	89	35	networks	network	NOUN
fcis-9900	89	36	,	,	PUNCT
fcis-9900	89	37	data	datum	NOUN
fcis-9900	89	38	enhancement	enhancement	NOUN
fcis-9900	89	39	,	,	PUNCT
fcis-9900	89	40	hyperparameter	hyperparameter	NOUN
fcis-9900	89	41	tuning	tuning	NOUN
fcis-9900	89	42	,	,	PUNCT
fcis-9900	89	43	optimization	optimization	NOUN
fcis-9900	89	44	of	of	ADP
fcis-9900	89	45	backbone	backbone	NOUN
fcis-9900	89	46	networks	network	NOUN
fcis-9900	89	47	,	,	PUNCT
fcis-9900	89	48	the	the	DET
fcis-9900	89	49	introduction	introduction	NOUN
fcis-9900	89	50	of	of	ADP
fcis-9900	89	51	attention	attention	NOUN
fcis-9900	89	52	mechanism	mechanism	NOUN
fcis-9900	89	53	,	,	PUNCT
fcis-9900	89	54	optimization	optimization	NOUN
fcis-9900	89	55	of	of	ADP
fcis-9900	89	56	cross	cross	ADJ
fcis-9900	89	57	-	-	ADJ
fcis-9900	89	58	comparison	comparison	ADJ
fcis-9900	89	59	function	function	NOUN
fcis-9900	89	60	,	,	PUNCT
fcis-9900	89	61	optimization	optimization	NOUN
fcis-9900	89	62	of	of	ADP
fcis-9900	89	63	the	the	DET
fcis-9900	89	64	loss	loss	NOUN
fcis-9900	89	65	function	function	NOUN
fcis-9900	89	66	,	,	PUNCT
fcis-9900	89	67	an	an	DET
fcis-9900	89	68	increase	increase	NOUN
fcis-9900	89	69	of	of	ADP
fcis-9900	89	70	the	the	DET
fcis-9900	89	71	perceptual	perceptual	ADJ
fcis-9900	89	72	field	field	NOUN
fcis-9900	89	73	,	,	PUNCT
fcis-9900	89	74	use	use	NOUN
fcis-9900	89	75	of	of	ADP
fcis-9900	89	76	anchor	anchor	NOUN
fcis-9900	89	77	-	-	PUNCT
fcis-9900	89	78	free	free	ADJ
fcis-9900	89	79	mechanism	mechanism	NOUN
fcis-9900	89	80	,	,	PUNCT
fcis-9900	89	81	contextual	contextual	ADJ
fcis-9900	89	82	learning	learning	NOUN
fcis-9900	89	83	,	,	PUNCT
fcis-9900	89	84	deep	deep	ADJ
fcis-9900	89	85	learning	learning	NOUN
fcis-9900	89	86	combined	combine	VERB
fcis-9900	89	87	with	with	ADP
fcis-9900	89	88	traditional	traditional	ADJ
fcis-9900	89	89	methods	method	NOUN
fcis-9900	89	90	for	for	ADP
fcis-9900	89	91	small	small	ADJ
fcis-9900	89	92	target	target	NOUN
fcis-9900	89	93	detection	detection	NOUN
fcis-9900	89	94	,	,	PUNCT
fcis-9900	89	95	etc	etc	X
fcis-9900	89	96	.	.	X
fcis-9900	90	1	this	this	DET
fcis-9900	90	2	subsection	subsection	NOUN
fcis-9900	90	3	will	will	AUX
fcis-9900	90	4	introduce	introduce	VERB
fcis-9900	90	5	several	several	ADJ
fcis-9900	90	6	common	common	ADJ
fcis-9900	90	7	typical	typical	ADJ
fcis-9900	90	8	optimization	optimization	NOUN
fcis-9900	90	9	methods	method	NOUN
fcis-9900	90	10	related	relate	VERB
fcis-9900	90	11	to	to	ADP
fcis-9900	90	12	improving	improve	VERB
fcis-9900	90	13	the	the	DET
fcis-9900	90	14	accuracy	accuracy	NOUN
fcis-9900	90	15	of	of	ADP
fcis-9900	90	16	small	small	ADJ
fcis-9900	90	17	targets	target	NOUN
fcis-9900	90	18	.	.	PUNCT
fcis-9900	91	1	3.1	3.1	NUM
fcis-9900	91	2	.	.	PUNCT
fcis-9900	91	3	data	datum	NOUN
fcis-9900	91	4	enhancement	enhancement	NOUN
fcis-9900	91	5	data	datum	NOUN
fcis-9900	91	6	enhancement	enhancement	NOUN
fcis-9900	91	7	mainly	mainly	ADV
fcis-9900	91	8	includes	include	VERB
fcis-9900	91	9	distortion	distortion	NOUN
fcis-9900	91	10	,	,	PUNCT
fcis-9900	91	11	rotation	rotation	NOUN
fcis-9900	91	12	and	and	CCONJ
fcis-9900	91	13	scaling	scaling	NOUN
fcis-9900	91	14	,	,	PUNCT
fcis-9900	91	15	elastic	elastic	ADJ
fcis-9900	91	16	distortion	distortion	NOUN
fcis-9900	91	17	[	[	X
fcis-9900	91	18	20	20	NUM
fcis-9900	91	19	]	]	PUNCT
fcis-9900	91	20	,	,	PUNCT
fcis-9900	91	21	random	random	ADJ
fcis-9900	91	22	cropping	cropping	NOUN
fcis-9900	91	23	[	[	X
fcis-9900	91	24	21	21	NUM
fcis-9900	91	25	]	]	PUNCT
fcis-9900	91	26	,	,	PUNCT
fcis-9900	91	27	panning	pan	VERB
fcis-9900	91	28	[	[	X
fcis-9900	91	29	22	22	NUM
fcis-9900	91	30	]	]	PUNCT
fcis-9900	91	31	,	,	PUNCT
fcis-9900	91	32	horizontal	horizontal	ADJ
fcis-9900	91	33	flipping	flipping	NOUN
fcis-9900	91	34	,	,	PUNCT
fcis-9900	91	35	adjusting	adjust	VERB
fcis-9900	91	36	image	image	NOUN
fcis-9900	91	37	exposure	exposure	NOUN
fcis-9900	91	38	and	and	CCONJ
fcis-9900	91	39	saturation	saturation	NOUN
fcis-9900	91	40	,	,	PUNCT
fcis-9900	91	41	cutout	cutout	NOUN
fcis-9900	91	42	[	[	X
fcis-9900	91	43	23	23	NUM
fcis-9900	91	44	]	]	PUNCT
fcis-9900	91	45	,	,	PUNCT
fcis-9900	91	46	mix	mix	VERB
fcis-9900	91	47	up	up	ADP
fcis-9900	91	48	[	[	X
fcis-9900	91	49	24	24	NUM
fcis-9900	91	50	]	]	PUNCT
fcis-9900	91	51	,	,	PUNCT
fcis-9900	91	52	cutmix	cutmix	NOUN
fcis-9900	91	53	[	[	X
fcis-9900	91	54	25	25	NUM
fcis-9900	91	55	]	]	PUNCT
fcis-9900	91	56	,	,	PUNCT
fcis-9900	91	57	mosaic	mosaic	PROPN
fcis-9900	92	1	[	[	X
fcis-9900	92	2	26	26	NUM
fcis-9900	92	3	]	]	PUNCT
fcis-9900	92	4	,	,	PUNCT
fcis-9900	92	5	and	and	CCONJ
fcis-9900	92	6	other	other	ADJ
fcis-9900	92	7	methods	method	NOUN
fcis-9900	92	8	.	.	PUNCT
fcis-9900	93	1	data	datum	NOUN
fcis-9900	93	2	augmentation	augmentation	NOUN
fcis-9900	93	3	is	be	AUX
fcis-9900	93	4	an	an	DET
fcis-9900	93	5	effective	effective	ADJ
fcis-9900	93	6	strategy	strategy	NOUN
fcis-9900	93	7	to	to	PART
fcis-9900	93	8	solve	solve	VERB
fcis-9900	93	9	the	the	DET
fcis-9900	93	10	problems	problem	NOUN
fcis-9900	93	11	of	of	ADP
fcis-9900	93	12	small	small	ADJ
fcis-9900	93	13	targets	target	NOUN
fcis-9900	93	14	with	with	ADP
fcis-9900	93	15	little	little	ADJ
fcis-9900	93	16	information	information	NOUN
fcis-9900	93	17	and	and	CCONJ
fcis-9900	93	18	insufficient	insufficient	ADJ
fcis-9900	93	19	appearance	appearance	NOUN
fcis-9900	93	20	features	feature	NOUN
fcis-9900	93	21	and	and	CCONJ
fcis-9900	93	22	textures	texture	NOUN
fcis-9900	93	23	to	to	ADP
fcis-9900	93	24	some	some	DET
fcis-9900	93	25	extent	extent	NOUN
fcis-9900	93	26	.	.	PUNCT
fcis-9900	94	1	with	with	ADP
fcis-9900	94	2	data	datum	NOUN
fcis-9900	94	3	augmentation	augmentation	NOUN
fcis-9900	94	4	,	,	PUNCT
fcis-9900	94	5	the	the	DET
fcis-9900	94	6	generalization	generalization	NOUN
fcis-9900	94	7	ability	ability	NOUN
fcis-9900	94	8	of	of	ADP
fcis-9900	94	9	the	the	DET
fcis-9900	94	10	network	network	NOUN
fcis-9900	94	11	can	can	AUX
fcis-9900	94	12	be	be	AUX
fcis-9900	94	13	improved	improve	VERB
fcis-9900	94	14	and	and	CCONJ
fcis-9900	94	15	good	good	ADJ
fcis-9900	94	16	results	result	NOUN
fcis-9900	94	17	can	can	AUX
fcis-9900	94	18	be	be	AUX
fcis-9900	94	19	achieved	achieve	VERB
fcis-9900	94	20	in	in	ADP
fcis-9900	94	21	the	the	DET
fcis-9900	94	22	final	final	ADJ
fcis-9900	94	23	detection	detection	NOUN
fcis-9900	94	24	performance	performance	NOUN
fcis-9900	94	25	.	.	PUNCT
fcis-9900	95	1	kisantal	kisantal	PROPN
fcis-9900	95	2	et	et	PROPN
fcis-9900	95	3	al	al	PROPN
fcis-9900	96	1	[	[	X
fcis-9900	96	2	27	27	NUM
fcis-9900	96	3	]	]	PUNCT
fcis-9900	96	4	generated	generate	VERB
fcis-9900	96	5	images	image	NOUN
fcis-9900	96	6	by	by	ADP
fcis-9900	96	7	oversampling	oversample	VERB
fcis-9900	96	8	these	these	DET
fcis-9900	96	9	43	43	NUM
fcis-9900	96	10	images	image	NOUN
fcis-9900	96	11	and	and	CCONJ
fcis-9900	96	12	zooming	zoom	VERB
fcis-9900	96	13	in	in	ADP
fcis-9900	96	14	on	on	ADP
fcis-9900	96	15	each	each	DET
fcis-9900	96	16	small	small	ADJ
fcis-9900	96	17	target	target	NOUN
fcis-9900	96	18	,	,	PUNCT
fcis-9900	96	19	copying	copying	NOUN
fcis-9900	96	20	and	and	CCONJ
fcis-9900	96	21	pasting	paste	VERB
fcis-9900	96	22	small	small	ADJ
fcis-9900	96	23	targets	target	NOUN
fcis-9900	96	24	multiple	multiple	ADJ
fcis-9900	96	25	times	time	NOUN
fcis-9900	96	26	to	to	PART
fcis-9900	96	27	increase	increase	VERB
fcis-9900	96	28	the	the	DET
fcis-9900	96	29	number	number	NOUN
fcis-9900	96	30	of	of	ADP
fcis-9900	96	31	training	training	NOUN
fcis-9900	96	32	samples	sample	NOUN
fcis-9900	96	33	of	of	ADP
fcis-9900	96	34	small	small	ADJ
fcis-9900	96	35	targets	target	NOUN
fcis-9900	96	36	,	,	PUNCT
fcis-9900	96	37	which	which	PRON
fcis-9900	96	38	in	in	ADP
fcis-9900	96	39	turn	turn	NOUN
fcis-9900	96	40	improves	improve	VERB
fcis-9900	96	41	the	the	DET
fcis-9900	96	42	small	small	ADJ
fcis-9900	96	43	target	target	NOUN
fcis-9900	96	44	detection	detection	NOUN
fcis-9900	96	45	performance	performance	NOUN
fcis-9900	96	46	.	.	PUNCT
fcis-9900	97	1	evaluating	evaluate	VERB
fcis-9900	97	2	different	different	ADJ
fcis-9900	97	3	pasting	pasting	NOUN
fcis-9900	97	4	enhancement	enhancement	NOUN
fcis-9900	97	5	strategies	strategy	NOUN
fcis-9900	97	6	achieved	achieve	VERB
fcis-9900	97	7	a	a	DET
fcis-9900	97	8	relative	relative	ADJ
fcis-9900	97	9	improvement	improvement	NOUN
fcis-9900	97	10	of	of	ADP
fcis-9900	97	11	9.7	9.7	NUM
fcis-9900	97	12	%	%	NOUN
fcis-9900	97	13	in	in	ADP
fcis-9900	97	14	object	object	NOUN
fcis-9900	97	15	detection	detection	NOUN
fcis-9900	97	16	of	of	ADP
fcis-9900	97	17	small	small	ADJ
fcis-9900	97	18	objects	object	NOUN
fcis-9900	97	19	on	on	ADP
fcis-9900	97	20	instance	instance	NOUN
fcis-9900	97	21	segmentation	segmentation	NOUN
fcis-9900	97	22	.	.	PUNCT
fcis-9900	98	1	the	the	DET
fcis-9900	98	2	cotout	cotout	NOUN
fcis-9900	98	3	data	data	NOUN
fcis-9900	98	4	enhancement	enhancement	NOUN
fcis-9900	98	5	proposed	propose	VERB
fcis-9900	98	6	by	by	ADP
fcis-9900	98	7	devries	devries	PROPN
fcis-9900	98	8	t	t	PROPN
fcis-9900	98	9	et	et	PROPN
fcis-9900	98	10	al	al	PROPN
fcis-9900	98	11	.	.	PROPN
fcis-9900	98	12	is	be	AUX
fcis-9900	98	13	also	also	ADV
fcis-9900	98	14	similar	similar	ADJ
fcis-9900	98	15	to	to	ADP
fcis-9900	98	16	randomerasing	randomerase	VERB
fcis-9900	98	17	data	datum	NOUN
fcis-9900	98	18	enhancement	enhancement	NOUN
fcis-9900	98	19	by	by	ADP
fcis-9900	98	20	filling	fill	VERB
fcis-9900	98	21	the	the	DET
fcis-9900	98	22	region	region	NOUN
fcis-9900	98	23	,	,	PUNCT
fcis-9900	98	24	thus	thus	ADV
fcis-9900	98	25	masking	mask	VERB
fcis-9900	98	26	the	the	DET
fcis-9900	98	27	image	image	NOUN
fcis-9900	98	28	information	information	NOUN
fcis-9900	98	29	in	in	ADP
fcis-9900	98	30	the	the	DET
fcis-9900	98	31	filled	fill	VERB
fcis-9900	98	32	region	region	NOUN
fcis-9900	98	33	,	,	PUNCT
fcis-9900	98	34	which	which	PRON
fcis-9900	98	35	is	be	AUX
fcis-9900	98	36	beneficial	beneficial	ADJ
fcis-9900	98	37	to	to	PART
fcis-9900	98	38	improve	improve	VERB
fcis-9900	98	39	the	the	DET
fcis-9900	98	40	generalization	generalization	NOUN
fcis-9900	98	41	ability	ability	NOUN
fcis-9900	98	42	of	of	ADP
fcis-9900	98	43	the	the	DET
fcis-9900	98	44	model	model	NOUN
fcis-9900	98	45	.	.	PUNCT
fcis-9900	99	1	unlike	unlike	ADP
fcis-9900	99	2	random	random	ADJ
fcis-9900	99	3	erasing	erasing	NOUN
fcis-9900	99	4	,	,	PUNCT
fcis-9900	99	5	cutout	cutout	NOUN
fcis-9900	99	6	uses	use	VERB
fcis-9900	99	7	a	a	DET
fcis-9900	99	8	fixed	fix	VERB
fcis-9900	99	9	-	-	PUNCT
fcis-9900	99	10	size	size	NOUN
fcis-9900	99	11	square	square	NOUN
fcis-9900	99	12	region	region	NOUN
fcis-9900	99	13	with	with	ADP
fcis-9900	99	14	all-0	all-0	ADJ
fcis-9900	99	15	pixel	pixel	NOUN
fcis-9900	99	16	value	value	NOUN
fcis-9900	99	17	padding	padding	NOUN
fcis-9900	99	18	and	and	CCONJ
fcis-9900	99	19	allows	allow	VERB
fcis-9900	99	20	the	the	DET
fcis-9900	99	21	square	square	ADJ
fcis-9900	99	22	region	region	NOUN
fcis-9900	99	23	to	to	PART
fcis-9900	99	24	be	be	AUX
fcis-9900	99	25	outside	outside	ADP
fcis-9900	99	26	the	the	DET
fcis-9900	99	27	image	image	NOUN
fcis-9900	99	28	.	.	PUNCT
fcis-9900	100	1	zhang	zhang	PROPN
fcis-9900	100	2	h	h	PROPN
fcis-9900	101	1	[	[	X
fcis-9900	101	2	24	24	NUM
fcis-9900	101	3	]	]	PUNCT
fcis-9900	101	4	proposed	propose	VERB
fcis-9900	101	5	mixup	mixup	PROPN
fcis-9900	101	6	data	datum	NOUN
fcis-9900	101	7	enhancement	enhancement	NOUN
fcis-9900	101	8	,	,	PUNCT
fcis-9900	101	9	a	a	DET
fcis-9900	101	10	data	data	NOUN
fcis-9900	101	11	enhancement	enhancement	NOUN
fcis-9900	101	12	method	method	NOUN
fcis-9900	101	13	published	publish	VERB
fcis-9900	101	14	in	in	ADP
fcis-9900	101	15	iclr	iclr	NOUN
fcis-9900	101	16	in	in	ADP
fcis-9900	101	17	2018	2018	NUM
fcis-9900	101	18	,	,	PUNCT
fcis-9900	101	19	with	with	ADP
fcis-9900	101	20	the	the	DET
fcis-9900	101	21	core	core	ADJ
fcis-9900	101	22	idea	idea	NOUN
fcis-9900	101	23	of	of	ADP
fcis-9900	101	24	randomly	randomly	ADV
fcis-9900	101	25	selecting	select	VERB
fcis-9900	101	26	two	two	NUM
fcis-9900	101	27	images	image	NOUN
fcis-9900	101	28	from	from	ADP
fcis-9900	101	29	each	each	DET
fcis-9900	101	30	batch	batch	NOUN
fcis-9900	101	31	and	and	CCONJ
fcis-9900	101	32	blending	blend	VERB
fcis-9900	101	33	them	they	PRON
fcis-9900	101	34	in	in	ADP
fcis-9900	101	35	a	a	DET
fcis-9900	101	36	certain	certain	ADJ
fcis-9900	101	37	ratio	ratio	NOUN
fcis-9900	101	38	to	to	PART
fcis-9900	101	39	generate	generate	VERB
fcis-9900	101	40	new	new	ADJ
fcis-9900	101	41	images	image	NOUN
fcis-9900	101	42	.	.	PUNCT
fcis-9900	102	1	the	the	DET
fcis-9900	102	2	entire	entire	ADJ
fcis-9900	102	3	training	training	NOUN
fcis-9900	102	4	process	process	NOUN
fcis-9900	102	5	is	be	AUX
fcis-9900	102	6	trained	train	VERB
fcis-9900	102	7	using	use	VERB
fcis-9900	102	8	only	only	ADV
fcis-9900	102	9	the	the	DET
fcis-9900	102	10	blended	blended	ADJ
fcis-9900	102	11	new	new	ADJ
fcis-9900	102	12	images	image	NOUN
fcis-9900	102	13	,	,	PUNCT
fcis-9900	102	14	and	and	CCONJ
fcis-9900	102	15	the	the	DET
fcis-9900	102	16	original	original	ADJ
fcis-9900	102	17	images	image	NOUN
fcis-9900	102	18	are	be	AUX
fcis-9900	102	19	not	not	PART
fcis-9900	102	20	involved	involve	VERB
fcis-9900	102	21	in	in	ADP
fcis-9900	102	22	the	the	DET
fcis-9900	102	23	training	training	NOUN
fcis-9900	102	24	process	process	NOUN
fcis-9900	102	25	.	.	PUNCT
fcis-9900	103	1	cutmix	cutmix	PROPN
fcis-9900	103	2	data	datum	NOUN
fcis-9900	103	3	augmentation	augmentation	NOUN
fcis-9900	103	4	proposed	propose	VERB
fcis-9900	103	5	by	by	ADP
fcis-9900	103	6	yun	yun	PROPN
fcis-9900	103	7	s	s	PART
fcis-9900	103	8	[	[	X
fcis-9900	103	9	28	28	NUM
fcis-9900	103	10	]	]	PUNCT
fcis-9900	103	11	et	et	PROPN
fcis-9900	103	12	al	al	PROPN
fcis-9900	103	13	.	.	PROPN
fcis-9900	103	14	is	be	AUX
fcis-9900	103	15	to	to	PART
fcis-9900	103	16	cut	cut	VERB
fcis-9900	103	17	out	out	ADP
fcis-9900	103	18	a	a	DET
fcis-9900	103	19	part	part	NOUN
fcis-9900	103	20	of	of	ADP
fcis-9900	103	21	the	the	DET
fcis-9900	103	22	region	region	NOUN
fcis-9900	103	23	but	but	CCONJ
fcis-9900	103	24	not	not	PART
fcis-9900	103	25	to	to	PART
fcis-9900	103	26	fill	fill	VERB
fcis-9900	103	27	0	0	NUM
fcis-9900	103	28	pixels	pixel	NOUN
fcis-9900	103	29	but	but	CCONJ
fcis-9900	103	30	to	to	PART
fcis-9900	103	31	randomly	randomly	ADV
fcis-9900	103	32	fill	fill	VERB
fcis-9900	103	33	the	the	DET
fcis-9900	103	34	region	region	NOUN
fcis-9900	103	35	pixel	pixel	NOUN
fcis-9900	103	36	values	value	NOUN
fcis-9900	103	37	of	of	ADP
fcis-9900	103	38	other	other	ADJ
fcis-9900	103	39	data	datum	NOUN
fcis-9900	103	40	in	in	ADP
fcis-9900	103	41	the	the	DET
fcis-9900	103	42	training	training	NOUN
fcis-9900	103	43	set	set	NOUN
fcis-9900	103	44	,	,	PUNCT
fcis-9900	103	45	and	and	CCONJ
fcis-9900	103	46	the	the	DET
fcis-9900	103	47	classification	classification	NOUN
fcis-9900	103	48	results	result	NOUN
fcis-9900	103	49	are	be	AUX
fcis-9900	103	50	assigned	assign	VERB
fcis-9900	103	51	in	in	ADP
fcis-9900	103	52	a	a	DET
fcis-9900	103	53	certain	certain	ADJ
fcis-9900	103	54	proportion	proportion	NOUN
fcis-9900	103	55	.	.	PUNCT
fcis-9900	104	1	cutmix	cutmix	PROPN
fcis-9900	104	2	simply	simply	ADV
fcis-9900	104	3	selects	select	VERB
fcis-9900	104	4	two	two	NUM
fcis-9900	104	5	images	image	NOUN
fcis-9900	104	6	from	from	ADP
fcis-9900	104	7	the	the	DET
fcis-9900	104	8	dataset	dataset	NOUN
fcis-9900	104	9	,	,	PUNCT
fcis-9900	104	10	and	and	CCONJ
fcis-9900	104	11	then	then	ADV
fcis-9900	104	12	a	a	DET
fcis-9900	104	13	part	part	NOUN
fcis-9900	104	14	of	of	ADP
fcis-9900	104	15	one	one	NUM
fcis-9900	104	16	image	image	NOUN
fcis-9900	104	17	is	be	AUX
fcis-9900	104	18	cropped	crop	VERB
fcis-9900	104	19	and	and	CCONJ
fcis-9900	104	20	superimposed	superimpose	VERB
fcis-9900	104	21	on	on	ADP
fcis-9900	104	22	top	top	NOUN
fcis-9900	104	23	of	of	ADP
fcis-9900	104	24	the	the	DET
fcis-9900	104	25	other	other	ADJ
fcis-9900	104	26	image	image	NOUN
fcis-9900	104	27	as	as	ADP
fcis-9900	104	28	a	a	DET
fcis-9900	104	29	new	new	ADJ
fcis-9900	104	30	input	input	NOUN
fcis-9900	104	31	image	image	NOUN
fcis-9900	104	32	into	into	ADP
fcis-9900	104	33	the	the	DET
fcis-9900	104	34	network	network	NOUN
fcis-9900	104	35	for	for	ADP
fcis-9900	104	36	training	training	NOUN
fcis-9900	104	37	.	.	PUNCT
fcis-9900	105	1	bochkovskiy	bochkovskiy	VERB
fcis-9900	105	2	a	a	PRON
fcis-9900	105	3	[	[	X
fcis-9900	105	4	29	29	NUM
fcis-9900	105	5	]	]	PUNCT
fcis-9900	105	6	et	et	PROPN
fcis-9900	105	7	al	al	PROPN
fcis-9900	105	8	.	.	PROPN
fcis-9900	105	9	proposed	propose	VERB
fcis-9900	105	10	a	a	DET
fcis-9900	105	11	data	data	NOUN
fcis-9900	105	12	enhancement	enhancement	NOUN
fcis-9900	105	13	method	method	NOUN
fcis-9900	105	14	called	call	VERB
fcis-9900	105	15	mosaic	mosaic	PROPN
fcis-9900	105	16	in	in	ADP
fcis-9900	105	17	yolov4	yolov4	PROPN
fcis-9900	105	18	.	.	PUNCT
fcis-9900	106	1	the	the	DET
fcis-9900	106	2	main	main	ADJ
fcis-9900	106	3	idea	idea	NOUN
fcis-9900	106	4	of	of	ADP
fcis-9900	106	5	this	this	DET
fcis-9900	106	6	method	method	NOUN
fcis-9900	106	7	is	be	AUX
fcis-9900	106	8	to	to	PART
fcis-9900	106	9	crop	crop	VERB
fcis-9900	106	10	four	four	NUM
fcis-9900	106	11	images	image	NOUN
fcis-9900	106	12	randomly	randomly	ADV
fcis-9900	106	13	and	and	CCONJ
fcis-9900	106	14	then	then	ADV
fcis-9900	106	15	stitch	stitch	VERB
fcis-9900	106	16	them	they	PRON
fcis-9900	106	17	on	on	ADP
fcis-9900	106	18	top	top	NOUN
fcis-9900	106	19	of	of	ADP
fcis-9900	106	20	one	one	NUM
fcis-9900	106	21	image	image	NOUN
fcis-9900	106	22	as	as	ADP
fcis-9900	106	23	training	training	NOUN
fcis-9900	106	24	data	datum	NOUN
fcis-9900	106	25	.	.	PUNCT
fcis-9900	107	1	the	the	DET
fcis-9900	107	2	advantage	advantage	NOUN
fcis-9900	107	3	of	of	ADP
fcis-9900	107	4	mosaic	mosaic	ADJ
fcis-9900	107	5	data	datum	NOUN
fcis-9900	107	6	enhancement	enhancement	NOUN
fcis-9900	107	7	is	be	AUX
fcis-9900	107	8	that	that	SCONJ
fcis-9900	107	9	it	it	PRON
fcis-9900	107	10	not	not	PART
fcis-9900	107	11	only	only	ADV
fcis-9900	107	12	enhances	enhance	VERB
fcis-9900	107	13	the	the	DET
fcis-9900	107	14	diversity	diversity	NOUN
fcis-9900	107	15	of	of	ADP
fcis-9900	107	16	training	training	NOUN
fcis-9900	107	17	data	datum	NOUN
fcis-9900	107	18	but	but	CCONJ
fcis-9900	107	19	also	also	ADV
fcis-9900	107	20	enriches	enrich	VERB
fcis-9900	107	21	the	the	DET
fcis-9900	107	22	background	background	NOUN
fcis-9900	107	23	of	of	ADP
fcis-9900	107	24	the	the	DET
fcis-9900	107	25	images	image	NOUN
fcis-9900	107	26	.	.	PUNCT
fcis-9900	108	1	the	the	DET
fcis-9900	108	2	mosaic	mosaic	ADJ
fcis-9900	108	3	data	datum	NOUN
fcis-9900	108	4	enhancement	enhancement	NOUN
fcis-9900	108	5	method	method	NOUN
fcis-9900	108	6	is	be	AUX
fcis-9900	108	7	an	an	DET
fcis-9900	108	8	improvement	improvement	NOUN
fcis-9900	108	9	on	on	ADP
fcis-9900	108	10	the	the	DET
fcis-9900	108	11	cutmix	cutmix	NOUN
fcis-9900	108	12	data	datum	NOUN
fcis-9900	108	13	enhancement	enhancement	NOUN
fcis-9900	108	14	approach	approach	NOUN
fcis-9900	108	15	and	and	CCONJ
fcis-9900	108	16	its	its	PRON
fcis-9900	108	17	implementation	implementation	NOUN
fcis-9900	108	18	is	be	AUX
fcis-9900	108	19	also	also	ADV
fcis-9900	108	20	inspired	inspire	VERB
fcis-9900	108	21	by	by	ADP
fcis-9900	108	22	the	the	DET
fcis-9900	108	23	cutmix	cutmix	NOUN
fcis-9900	108	24	data	datum	NOUN
fcis-9900	108	25	enhancement	enhancement	NOUN
fcis-9900	108	26	approach	approach	NOUN
fcis-9900	108	27	.	.	PUNCT
fcis-9900	109	1	müller	müller	PROPN
fcis-9900	109	2	s	s	PART
fcis-9900	109	3	g	g	PROPN
fcis-9900	109	4	[	[	X
fcis-9900	109	5	30	30	NUM
fcis-9900	109	6	]	]	X
fcis-9900	109	7	et	et	PROPN
fcis-9900	109	8	al	al	PROPN
fcis-9900	109	9	.	.	PROPN
fcis-9900	109	10	used	use	VERB
fcis-9900	109	11	all	all	DET
fcis-9900	109	12	data	datum	NOUN
fcis-9900	109	13	enhancement	enhancement	NOUN
fcis-9900	109	14	approaches	approach	NOUN
fcis-9900	109	15	to	to	PART
fcis-9900	109	16	enhance	enhance	VERB
fcis-9900	109	17	a	a	DET
fcis-9900	109	18	single	single	ADJ
fcis-9900	109	19	image	image	NOUN
fcis-9900	109	20	and	and	CCONJ
fcis-9900	109	21	then	then	ADV
fcis-9900	109	22	sampled	sample	VERB
fcis-9900	109	23	uniformly	uniformly	ADV
fcis-9900	109	24	from	from	ADP
fcis-9900	109	25	it	it	PRON
fcis-9900	109	26	.	.	PUNCT
fcis-9900	110	1	the	the	DET
fcis-9900	110	2	method	method	NOUN
fcis-9900	110	3	is	be	AUX
fcis-9900	110	4	valid	valid	ADJ
fcis-9900	110	5	for	for	ADP
fcis-9900	110	6	a	a	DET
fcis-9900	110	7	wide	wide	ADJ
fcis-9900	110	8	range	range	NOUN
fcis-9900	110	9	of	of	ADP
fcis-9900	110	10	datasets	dataset	NOUN
fcis-9900	110	11	and	and	CCONJ
fcis-9900	110	12	models	model	NOUN
fcis-9900	110	13	and	and	CCONJ
fcis-9900	110	14	is	be	AUX
fcis-9900	110	15	robust	robust	ADJ
fcis-9900	110	16	,	,	PUNCT
fcis-9900	110	17	and	and	CCONJ
fcis-9900	110	18	has	have	AUX
fcis-9900	110	19	been	be	AUX
fcis-9900	110	20	tested	test	VERB
fcis-9900	110	21	on	on	ADP
fcis-9900	110	22	datasets	dataset	NOUN
fcis-9900	110	23	with	with	ADP
fcis-9900	110	24	good	good	ADJ
fcis-9900	110	25	result	result	NOUN
fcis-9900	110	26	enhancement	enhancement	NOUN
fcis-9900	110	27	.	.	PUNCT
fcis-9900	111	1	3.2	3.2	NUM
fcis-9900	111	2	.	.	PUNCT
fcis-9900	112	1	introducing	introduce	VERB
fcis-9900	112	2	the	the	DET
fcis-9900	112	3	attention	attention	NOUN
fcis-9900	112	4	mechanism	mechanism	NOUN
fcis-9900	112	5	the	the	DET
fcis-9900	112	6	core	core	NOUN
fcis-9900	112	7	idea	idea	NOUN
fcis-9900	112	8	of	of	ADP
fcis-9900	112	9	attention	attention	NOUN
fcis-9900	112	10	mechanism	mechanism	NOUN
fcis-9900	112	11	in	in	ADP
fcis-9900	112	12	computer	computer	NOUN
fcis-9900	112	13	vision	vision	NOUN
fcis-9900	112	14	is	be	AUX
fcis-9900	112	15	to	to	PART
fcis-9900	112	16	find	find	VERB
fcis-9900	112	17	the	the	DET
fcis-9900	112	18	correlation	correlation	NOUN
fcis-9900	112	19	between	between	ADP
fcis-9900	112	20	data	datum	NOUN
fcis-9900	112	21	based	base	VERB
fcis-9900	112	22	on	on	ADP
fcis-9900	112	23	the	the	DET
fcis-9900	112	24	original	original	ADJ
fcis-9900	112	25	data	datum	NOUN
fcis-9900	112	26	and	and	CCONJ
fcis-9900	112	27	highlight	highlight	VERB
fcis-9900	112	28	the	the	DET
fcis-9900	112	29	important	important	ADJ
fcis-9900	112	30	features	feature	NOUN
fcis-9900	112	31	in	in	ADP
fcis-9900	112	32	it	it	PRON
fcis-9900	112	33	.	.	PUNCT
fcis-9900	113	1	the	the	DET
fcis-9900	113	2	attention	attention	NOUN
fcis-9900	113	3	mechanism	mechanism	NOUN
fcis-9900	113	4	includes	include	VERB
fcis-9900	113	5	different	different	ADJ
fcis-9900	113	6	forms	form	NOUN
fcis-9900	113	7	such	such	ADJ
fcis-9900	113	8	as	as	ADP
fcis-9900	113	9	channel	channel	NOUN
fcis-9900	113	10	attention	attention	NOUN
fcis-9900	113	11	,	,	PUNCT
fcis-9900	113	12	pixel	pixel	ADJ
fcis-9900	113	13	attention	attention	NOUN
fcis-9900	113	14	,	,	PUNCT
fcis-9900	113	15	and	and	CCONJ
fcis-9900	113	16	multi	multi	ADJ
fcis-9900	113	17	-	-	ADJ
fcis-9900	113	18	order	order	NOUN
fcis-9900	113	19	attention	attention	NOUN
fcis-9900	113	20	.	.	PUNCT
fcis-9900	114	1	for	for	ADP
fcis-9900	114	2	small	small	ADJ
fcis-9900	114	3	target	target	NOUN
fcis-9900	114	4	detection	detection	NOUN
fcis-9900	114	5	tasks	task	NOUN
fcis-9900	114	6	,	,	PUNCT
fcis-9900	114	7	for	for	ADP
fcis-9900	114	8	convolutional	convolutional	ADJ
fcis-9900	114	9	neural	neural	ADJ
fcis-9900	114	10	networks	network	NOUN
fcis-9900	114	11	to	to	PART
fcis-9900	114	12	learn	learn	VERB
fcis-9900	114	13	more	more	ADJ
fcis-9900	114	14	feature	feature	NOUN
fcis-9900	114	15	information	information	NOUN
fcis-9900	114	16	,	,	PUNCT
fcis-9900	114	17	the	the	DET
fcis-9900	114	18	network	network	NOUN
fcis-9900	114	19	structure	structure	NOUN
fcis-9900	114	20	needs	need	VERB
fcis-9900	114	21	to	to	PART
fcis-9900	114	22	be	be	AUX
fcis-9900	114	23	deepened	deepen	VERB
fcis-9900	114	24	or	or	CCONJ
fcis-9900	114	25	widened	widen	VERB
fcis-9900	114	26	.	.	PUNCT
fcis-9900	115	1	however	however	ADV
fcis-9900	115	2	,	,	PUNCT
fcis-9900	115	3	this	this	PRON
fcis-9900	115	4	would	would	AUX
fcis-9900	115	5	make	make	VERB
fcis-9900	115	6	the	the	DET
fcis-9900	115	7	neural	neural	ADJ
fcis-9900	115	8	network	network	NOUN
fcis-9900	115	9	model	model	NOUN
fcis-9900	115	10	very	very	ADV
fcis-9900	115	11	complex	complex	ADJ
fcis-9900	115	12	.	.	PUNCT
fcis-9900	116	1	meanwhile	meanwhile	ADV
fcis-9900	116	2	,	,	PUNCT
fcis-9900	116	3	the	the	DET
fcis-9900	116	4	feature	feature	NOUN
fcis-9900	116	5	information	information	NOUN
fcis-9900	116	6	of	of	ADP
fcis-9900	116	7	small	small	ADJ
fcis-9900	116	8	targets	target	NOUN
fcis-9900	116	9	is	be	AUX
fcis-9900	116	10	weakly	weakly	ADV
fcis-9900	116	11	expressed	express	VERB
fcis-9900	116	12	because	because	SCONJ
fcis-9900	116	13	the	the	DET
fcis-9900	116	14	small	small	ADJ
fcis-9900	116	15	targets	target	NOUN
fcis-9900	116	16	themselves	themselves	PRON
fcis-9900	116	17	have	have	VERB
fcis-9900	116	18	less	less	ADJ
fcis-9900	116	19	pixel	pixel	ADJ
fcis-9900	116	20	information	information	NOUN
fcis-9900	116	21	.	.	PUNCT
fcis-9900	117	1	therefore	therefore	ADV
fcis-9900	117	2	,	,	PUNCT
fcis-9900	117	3	it	it	PRON
fcis-9900	117	4	is	be	AUX
fcis-9900	117	5	very	very	ADV
fcis-9900	117	6	important	important	ADJ
fcis-9900	117	7	to	to	PART
fcis-9900	117	8	enhance	enhance	VERB
fcis-9900	117	9	the	the	DET
fcis-9900	117	10	small	small	ADJ
fcis-9900	117	11	target	target	NOUN
fcis-9900	117	12	feature	feature	NOUN
fcis-9900	117	13	information	information	NOUN
fcis-9900	117	14	.	.	PUNCT
fcis-9900	118	1	the	the	DET
fcis-9900	118	2	introduction	introduction	NOUN
fcis-9900	118	3	of	of	ADP
fcis-9900	118	4	attention	attention	NOUN
fcis-9900	118	5	mechanisms	mechanism	NOUN
fcis-9900	118	6	that	that	PRON
fcis-9900	118	7	can	can	AUX
fcis-9900	118	8	enhance	enhance	VERB
fcis-9900	118	9	the	the	DET
fcis-9900	118	10	feature	feature	NOUN
fcis-9900	118	11	expression	expression	NOUN
fcis-9900	118	12	ability	ability	NOUN
fcis-9900	118	13	of	of	ADP
fcis-9900	118	14	small	small	ADJ
fcis-9900	118	15	targets	target	NOUN
fcis-9900	118	16	,	,	PUNCT
fcis-9900	118	17	such	such	ADJ
fcis-9900	118	18	as	as	ADP
fcis-9900	118	19	channel	channel	NOUN
fcis-9900	118	20	attention	attention	NOUN
fcis-9900	118	21	mechanisms	mechanism	NOUN
fcis-9900	118	22	and	and	CCONJ
fcis-9900	118	23	spatial	spatial	ADJ
fcis-9900	118	24	attention	attention	NOUN
fcis-9900	118	25	mechanisms	mechanism	NOUN
fcis-9900	118	26	,	,	PUNCT
fcis-9900	118	27	often	often	ADV
fcis-9900	118	28	enables	enable	VERB
fcis-9900	118	29	neural	neural	ADJ
fcis-9900	118	30	networks	network	NOUN
fcis-9900	118	31	to	to	PART
fcis-9900	118	32	enhance	enhance	VERB
fcis-9900	118	33	the	the	DET
fcis-9900	118	34	feature	feature	NOUN
fcis-9900	118	35	expression	expression	NOUN
fcis-9900	118	36	ability	ability	NOUN
fcis-9900	118	37	of	of	ADP
fcis-9900	118	38	small	small	ADJ
fcis-9900	118	39	target	target	NOUN
fcis-9900	118	40	information	information	NOUN
fcis-9900	118	41	in	in	ADP
fcis-9900	118	42	this	this	DET
fcis-9900	118	43	way	way	NOUN
fcis-9900	118	44	,	,	PUNCT
fcis-9900	118	45	which	which	PRON
fcis-9900	118	46	in	in	ADP
fcis-9900	118	47	turn	turn	NOUN
fcis-9900	118	48	improves	improve	VERB
fcis-9900	118	49	the	the	DET
fcis-9900	118	50	detection	detection	NOUN
fcis-9900	118	51	accuracy	accuracy	NOUN
fcis-9900	118	52	of	of	ADP
fcis-9900	118	53	small	small	ADJ
fcis-9900	118	54	targets	target	NOUN
fcis-9900	118	55	.	.	PUNCT
fcis-9900	119	1	the	the	DET
fcis-9900	119	2	senet	senet	NOUN
fcis-9900	119	3	proposed	propose	VERB
fcis-9900	119	4	by	by	ADP
fcis-9900	119	5	jie	jie	PROPN
fcis-9900	119	6	h	h	PROPN
fcis-9900	120	1	[	[	X
fcis-9900	120	2	31	31	NUM
fcis-9900	120	3	]	]	PUNCT
fcis-9900	120	4	considers	consider	VERB
fcis-9900	120	5	the	the	DET
fcis-9900	120	6	relationship	relationship	NOUN
fcis-9900	120	7	between	between	ADP
fcis-9900	120	8	feature	feature	NOUN
fcis-9900	120	9	channels	channel	NOUN
fcis-9900	120	10	and	and	CCONJ
fcis-9900	120	11	incorporates	incorporate	VERB
fcis-9900	120	12	an	an	DET
fcis-9900	120	13	attention	attention	NOUN
fcis-9900	120	14	mechanism	mechanism	NOUN
fcis-9900	120	15	on	on	ADP
fcis-9900	120	16	the	the	DET
fcis-9900	120	17	feature	feature	NOUN
fcis-9900	120	18	channels.senet	channels.senet	NOUN
fcis-9900	120	19	is	be	AUX
fcis-9900	120	20	a	a	DET
fcis-9900	120	21	method	method	NOUN
fcis-9900	120	22	to	to	PART
fcis-9900	120	23	automatically	automatically	ADV
fcis-9900	120	24	obtain	obtain	VERB
fcis-9900	120	25	the	the	DET
fcis-9900	120	26	importance	importance	NOUN
fcis-9900	120	27	of	of	ADP
fcis-9900	120	28	each	each	DET
fcis-9900	120	29	feature	feature	NOUN
fcis-9900	120	30	channel	channel	NOUN
fcis-9900	120	31	employing	employ	VERB
fcis-9900	120	32	learning	learning	NOUN
fcis-9900	120	33	.	.	PUNCT
fcis-9900	121	1	for	for	ADP
fcis-9900	121	2	the	the	DET
fcis-9900	121	3	input	input	NOUN
fcis-9900	121	4	feature	feature	NOUN
fcis-9900	121	5	layer	layer	NOUN
fcis-9900	121	6	,	,	PUNCT
fcis-9900	121	7	senet	senet	NOUN
fcis-9900	121	8	pays	pay	VERB
fcis-9900	121	9	attention	attention	NOUN
fcis-9900	121	10	to	to	ADP
fcis-9900	121	11	the	the	DET
fcis-9900	121	12	weight	weight	NOUN
fcis-9900	121	13	of	of	ADP
fcis-9900	121	14	each	each	DET
fcis-9900	121	15	channel	channel	NOUN
fcis-9900	121	16	,	,	PUNCT
fcis-9900	121	17	and	and	CCONJ
fcis-9900	121	18	its	its	PRON
fcis-9900	121	19	focus	focus	NOUN
fcis-9900	121	20	is	be	AUX
fcis-9900	121	21	on	on	ADP
fcis-9900	121	22	obtaining	obtain	VERB
fcis-9900	121	23	the	the	DET
fcis-9900	121	24	weight	weight	NOUN
fcis-9900	121	25	of	of	ADP
fcis-9900	121	26	each	each	DET
fcis-9900	121	27	channel	channel	NOUN
fcis-9900	121	28	in	in	ADP
fcis-9900	121	29	the	the	DET
fcis-9900	121	30	input	input	NOUN
fcis-9900	121	31	feature	feature	NOUN
fcis-9900	121	32	layer	layer	NOUN
fcis-9900	121	33	.	.	PUNCT
fcis-9900	122	1	by	by	ADP
fcis-9900	122	2	using	use	VERB
fcis-9900	122	3	senet	senet	NOUN
fcis-9900	122	4	to	to	PART
fcis-9900	122	5	obtain	obtain	VERB
fcis-9900	122	6	the	the	DET
fcis-9900	122	7	importance	importance	NOUN
fcis-9900	122	8	level	level	NOUN
fcis-9900	122	9	of	of	ADP
fcis-9900	122	10	each	each	DET
fcis-9900	122	11	channel	channel	NOUN
fcis-9900	122	12	,	,	PUNCT
fcis-9900	122	13	it	it	PRON
fcis-9900	122	14	improves	improve	VERB
fcis-9900	122	15	feature	feature	NOUN
fcis-9900	122	16	representation	representation	NOUN
fcis-9900	122	17	and	and	CCONJ
fcis-9900	122	18	suppresses	suppress	VERB
fcis-9900	122	19	features	feature	NOUN
fcis-9900	122	20	that	that	PRON
fcis-9900	122	21	are	be	AUX
fcis-9900	122	22	not	not	PART
fcis-9900	122	23	important	important	ADJ
fcis-9900	122	24	for	for	ADP
fcis-9900	122	25	the	the	DET
fcis-9900	122	26	task	task	NOUN
fcis-9900	122	27	at	at	ADP
fcis-9900	122	28	hand	hand	NOUN
fcis-9900	122	29	,	,	PUNCT
fcis-9900	122	30	allowing	allow	VERB
fcis-9900	122	31	the	the	DET
fcis-9900	122	32	network	network	NOUN
fcis-9900	122	33	to	to	PART
fcis-9900	122	34	focus	focus	VERB
fcis-9900	122	35	on	on	ADP
fcis-9900	122	36	the	the	DET
fcis-9900	122	37	channels	channel	NOUN
fcis-9900	122	38	it	it	PRON
fcis-9900	122	39	needs	need	VERB
fcis-9900	122	40	to	to	PART
fcis-9900	122	41	focus	focus	VERB
fcis-9900	122	42	on	on	ADP
fcis-9900	122	43	the	the	DET
fcis-9900	122	44	most	most	ADJ
fcis-9900	122	45	.	.	PUNCT
fcis-9900	123	1	li	li	PROPN
fcis-9900	123	2	et	et	PROPN
fcis-9900	123	3	al	al	PROPN
fcis-9900	124	1	[	[	X
fcis-9900	124	2	32	32	NUM
fcis-9900	124	3	]	]	PUNCT
fcis-9900	124	4	proposed	propose	VERB
fcis-9900	124	5	a	a	DET
fcis-9900	124	6	model	model	NOUN
fcis-9900	124	7	called	call	VERB
fcis-9900	124	8	yolo	yolo	PROPN
fcis-9900	124	9	-	-	PUNCT
fcis-9900	124	10	can	can	AUX
fcis-9900	124	11	for	for	ADP
fcis-9900	124	12	small	small	ADJ
fcis-9900	124	13	and	and	CCONJ
fcis-9900	124	14	occluded	occluded	ADJ
fcis-9900	124	15	targets	target	NOUN
fcis-9900	124	16	.	.	PUNCT
fcis-9900	125	1	this	this	DET
fcis-9900	125	2	model	model	NOUN
fcis-9900	125	3	introduces	introduce	VERB
fcis-9900	125	4	an	an	DET
fcis-9900	125	5	attention	attention	NOUN
fcis-9900	125	6	mechanism	mechanism	NOUN
fcis-9900	125	7	in	in	ADP
fcis-9900	125	8	its	its	PRON
fcis-9900	125	9	residual	residual	ADJ
fcis-9900	125	10	structure	structure	NOUN
fcis-9900	125	11	and	and	CCONJ
fcis-9900	125	12	improves	improve	VERB
fcis-9900	125	13	the	the	DET
fcis-9900	125	14	feature	feature	NOUN
fcis-9900	125	15	representation	representation	NOUN
fcis-9900	125	16	of	of	ADP
fcis-9900	125	17	small	small	ADJ
fcis-9900	125	18	target	target	NOUN
fcis-9900	125	19	objects	object	NOUN
fcis-9900	125	20	by	by	ADP
fcis-9900	125	21	up	up	ADV
fcis-9900	125	22	-	-	PUNCT
fcis-9900	125	23	sampling	sample	VERB
fcis-9900	125	24	and	and	CCONJ
fcis-9900	125	25	fusing	fuse	VERB
fcis-9900	125	26	feature	feature	NOUN
fcis-9900	125	27	maps	map	NOUN
fcis-9900	125	28	at	at	ADP
fcis-9900	125	29	different	different	ADJ
fcis-9900	125	30	scales	scale	NOUN
fcis-9900	125	31	.	.	PUNCT
fcis-9900	126	1	the	the	DET
fcis-9900	126	2	detector	detector	NOUN
fcis-9900	126	3	model	model	NOUN
fcis-9900	126	4	is	be	AUX
fcis-9900	126	5	inspired	inspire	VERB
fcis-9900	126	6	by	by	ADP
fcis-9900	126	7	the	the	DET
fcis-9900	126	8	high	high	ADJ
fcis-9900	126	9	detection	detection	NOUN
fcis-9900	126	10	accuracy	accuracy	NOUN
fcis-9900	126	11	and	and	CCONJ
fcis-9900	126	12	speed	speed	NOUN
fcis-9900	126	13	of	of	ADP
fcis-9900	126	14	yolov3	yolov3	PROPN
fcis-9900	126	15	and	and	CCONJ
fcis-9900	126	16	is	be	AUX
fcis-9900	126	17	improved	improve	VERB
fcis-9900	126	18	by	by	ADP
fcis-9900	126	19	adding	add	VERB
fcis-9900	126	20	an	an	DET
fcis-9900	126	21	attention	attention	NOUN
fcis-9900	126	22	mechanism	mechanism	NOUN
fcis-9900	126	23	,	,	PUNCT
fcis-9900	126	24	ciou	ciou	NOUN
fcis-9900	126	25	(	(	PUNCT
fcis-9900	126	26	complete	complete	ADJ
fcis-9900	126	27	intersection	intersection	NOUN
fcis-9900	126	28	on	on	ADP
fcis-9900	126	29	union	union	NOUN
fcis-9900	126	30	)	)	PUNCT
fcis-9900	126	31	loss	loss	NOUN
fcis-9900	126	32	function	function	NOUN
fcis-9900	126	33	,	,	PUNCT
fcis-9900	126	34	soft	soft	ADJ
fcis-9900	126	35	nms	nms	NOUN
fcis-9900	126	36	(	(	PUNCT
fcis-9900	126	37	non	non	ADJ
fcis-9900	126	38	-	-	ADJ
fcis-9900	126	39	maximum	maximum	ADJ
fcis-9900	126	40	suppression	suppression	NOUN
fcis-9900	126	41	)	)	PUNCT
fcis-9900	126	42	,	,	PUNCT
fcis-9900	126	43	and	and	CCONJ
fcis-9900	126	44	depth	depth	NOUN
fcis-9900	126	45	direction	direction	NOUN
fcis-9900	126	46	separable	separable	ADJ
fcis-9900	126	47	convolution	convolution	NOUN
fcis-9900	126	48	.	.	PUNCT
fcis-9900	127	1	pan	pan	PROPN
fcis-9900	127	2	h	h	PROPN
fcis-9900	127	3	et	et	PROPN
fcis-9900	127	4	al	al	PROPN
fcis-9900	128	1	[	[	X
fcis-9900	128	2	33	33	NUM
fcis-9900	128	3	]	]	PUNCT
fcis-9900	128	4	proposed	propose	VERB
fcis-9900	128	5	a	a	DET
fcis-9900	128	6	new	new	ADJ
fcis-9900	128	7	first	first	ADJ
fcis-9900	128	8	-	-	PUNCT
fcis-9900	128	9	level	level	NOUN
fcis-9900	128	10	target	target	NOUN
fcis-9900	128	11	detection	detection	NOUN
fcis-9900	128	12	network	network	NOUN
fcis-9900	128	13	,	,	PUNCT
fcis-9900	128	14	called	call	VERB
fcis-9900	128	15	adaptive	adaptive	ADJ
fcis-9900	128	16	dense	dense	ADJ
fcis-9900	128	17	feature	feature	NOUN
fcis-9900	128	18	pyramid	pyramid	NOUN
fcis-9900	128	19	network	network	NOUN
fcis-9900	128	20	(	(	PUNCT
fcis-9900	128	21	adfpnet	adfpnet	NOUN
fcis-9900	128	22	)	)	PUNCT
fcis-9900	128	23	,	,	PUNCT
fcis-9900	128	24	for	for	ADP
fcis-9900	128	25	detecting	detect	VERB
fcis-9900	128	26	targets	target	NOUN
fcis-9900	128	27	at	at	ADP
fcis-9900	128	28	different	different	ADJ
fcis-9900	128	29	scales	scale	NOUN
fcis-9900	128	30	.	.	PUNCT
fcis-9900	129	1	the	the	DET
fcis-9900	129	2	network	network	NOUN
fcis-9900	129	3	was	be	AUX
fcis-9900	129	4	developed	develop	VERB
fcis-9900	129	5	on	on	ADP
fcis-9900	129	6	a	a	DET
fcis-9900	129	7	singletrigger	singletrigger	NOUN
fcis-9900	129	8	multi	multi	ADJ
fcis-9900	129	9	-	-	ADJ
fcis-9900	129	10	box	box	NOUN
fcis-9900	129	11	detector	detector	NOUN
fcis-9900	129	12	(	(	PUNCT
fcis-9900	129	13	ssd	ssd	NOUN
fcis-9900	129	14	)	)	PUNCT
fcis-9900	129	15	framework	framework	NOUN
fcis-9900	129	16	with	with	ADP
fcis-9900	129	17	a	a	DET
fcis-9900	129	18	newly	newly	ADV
fcis-9900	129	19	proposed	propose	VERB
fcis-9900	129	20	adfp	adfp	NOUN
fcis-9900	129	21	module	module	NOUN
fcis-9900	129	22	,	,	PUNCT
fcis-9900	129	23	which	which	PRON
fcis-9900	129	24	consists	consist	VERB
fcis-9900	129	25	of	of	ADP
fcis-9900	129	26	two	two	NUM
fcis-9900	129	27	parts	part	NOUN
fcis-9900	129	28	:	:	PUNCT
fcis-9900	129	29	a	a	DET
fcis-9900	129	30	dense	dense	ADJ
fcis-9900	129	31	multiscale	multiscale	NOUN
fcis-9900	129	32	and	and	CCONJ
fcis-9900	129	33	sensory	sensory	ADJ
fcis-9900	129	34	field	field	NOUN
fcis-9900	129	35	block	block	NOUN
fcis-9900	129	36	(	(	PUNCT
fcis-9900	129	37	dmsrb	dmsrb	PROPN
fcis-9900	129	38	)	)	PUNCT
fcis-9900	129	39	and	and	CCONJ
fcis-9900	129	40	an	an	DET
fcis-9900	129	41	adaptive	adaptive	ADJ
fcis-9900	129	42	feature	feature	NOUN
fcis-9900	129	43	calibration	calibration	NOUN
fcis-9900	129	44	block	block	NOUN
fcis-9900	129	45	(	(	PUNCT
fcis-9900	129	46	afcb	afcb	PROPN
fcis-9900	129	47	)	)	PUNCT
fcis-9900	129	48	.	.	PUNCT
fcis-9900	130	1	specifically	specifically	ADV
fcis-9900	130	2	,	,	PUNCT
fcis-9900	130	3	the	the	DET
fcis-9900	130	4	dmsrb	dmsrb	NOUN
fcis-9900	130	5	block	block	NOUN
fcis-9900	130	6	extracts	extract	NOUN
fcis-9900	130	7	rich	rich	ADJ
fcis-9900	130	8	semantic	semantic	ADJ
fcis-9900	130	9	information	information	NOUN
fcis-9900	130	10	in	in	ADP
fcis-9900	130	11	a	a	DET
fcis-9900	130	12	dense	dense	ADJ
fcis-9900	130	13	manner	manner	NOUN
fcis-9900	130	14	by	by	ADP
fcis-9900	130	15	atrous	atrous	ADJ
fcis-9900	130	16	convolution	convolution	NOUN
fcis-9900	130	17	at	at	ADP
fcis-9900	130	18	different	different	ADJ
fcis-9900	130	19	code	code	NOUN
fcis-9900	130	20	rates	rate	NOUN
fcis-9900	130	21	to	to	PART
fcis-9900	130	22	extract	extract	VERB
fcis-9900	130	23	dense	dense	ADJ
fcis-9900	130	24	features	feature	NOUN
fcis-9900	130	25	at	at	ADP
fcis-9900	130	26	multiple	multiple	ADJ
fcis-9900	130	27	scales	scale	NOUN
fcis-9900	130	28	and	and	CCONJ
fcis-9900	130	29	receptive	receptive	ADJ
fcis-9900	130	30	fields	field	NOUN
fcis-9900	130	31	;	;	PUNCT
fcis-9900	130	32	the	the	DET
fcis-9900	130	33	afcb	afcb	NOUN
fcis-9900	130	34	block	block	NOUN
fcis-9900	130	35	calibrates	calibrate	VERB
fcis-9900	130	36	dense	dense	ADJ
fcis-9900	130	37	features	feature	NOUN
fcis-9900	130	38	to	to	PART
fcis-9900	130	39	retain	retain	VERB
fcis-9900	130	40	features	feature	NOUN
fcis-9900	130	41	that	that	PRON
fcis-9900	130	42	contribute	contribute	VERB
fcis-9900	130	43	more	more	ADV
fcis-9900	130	44	and	and	CCONJ
fcis-9900	130	45	suppress	suppress	VERB
fcis-9900	130	46	features	feature	NOUN
fcis-9900	130	47	that	that	PRON
fcis-9900	130	48	contribute	contribute	VERB
fcis-9900	130	49	less	less	ADJ
fcis-9900	130	50	.	.	PUNCT
fcis-9900	131	1	tests	test	NOUN
fcis-9900	131	2	on	on	ADP
fcis-9900	131	3	many	many	ADJ
fcis-9900	131	4	datasets	dataset	NOUN
fcis-9900	131	5	have	have	AUX
fcis-9900	131	6	significantly	significantly	ADV
fcis-9900	131	7	improved	improve	VERB
fcis-9900	131	8	the	the	DET
fcis-9900	131	9	accuracy	accuracy	NOUN
fcis-9900	131	10	and	and	CCONJ
fcis-9900	131	11	met	meet	VERB
fcis-9900	131	12	the	the	DET
fcis-9900	131	13	requirements	requirement	NOUN
fcis-9900	131	14	for	for	ADP
fcis-9900	131	15	real	real	ADJ
fcis-9900	131	16	-	-	PUNCT
fcis-9900	131	17	time	time	NOUN
fcis-9900	131	18	detection	detection	NOUN
fcis-9900	131	19	.	.	PUNCT
fcis-9900	132	1	zhu	zhu	PROPN
fcis-9900	132	2	g	g	PROPN
fcis-9900	133	1	[	[	X
fcis-9900	133	2	34	34	NUM
fcis-9900	133	3	]	]	PUNCT
fcis-9900	133	4	proposed	propose	VERB
fcis-9900	133	5	a	a	DET
fcis-9900	133	6	target	target	NOUN
fcis-9900	133	7	detection	detection	NOUN
fcis-9900	133	8	method	method	NOUN
fcis-9900	133	9	combining	combine	VERB
fcis-9900	133	10	multilevel	multilevel	ADJ
fcis-9900	133	11	feature	feature	NOUN
fcis-9900	133	12	fusion	fusion	NOUN
fcis-9900	133	13	and	and	CCONJ
fcis-9900	133	14	area	area	NOUN
fcis-9900	133	15	channel	channel	NOUN
fcis-9900	133	16	attention	attention	NOUN
fcis-9900	133	17	(	(	PUNCT
fcis-9900	133	18	odmc	odmc	NOUN
fcis-9900	133	19	)	)	PUNCT
fcis-9900	133	20	.	.	PUNCT
fcis-9900	134	1	the	the	DET
fcis-9900	134	2	method	method	NOUN
fcis-9900	134	3	first	first	ADV
fcis-9900	134	4	fuses	fuse	VERB
fcis-9900	134	5	the	the	DET
fcis-9900	134	6	positive	positive	ADJ
fcis-9900	134	7	and	and	CCONJ
fcis-9900	134	8	negative	negative	ADJ
fcis-9900	134	9	phase	phase	NOUN
fcis-9900	134	10	information	information	NOUN
fcis-9900	134	11	of	of	ADP
fcis-9900	134	12	multi	multi	ADJ
fcis-9900	134	13	-	-	ADJ
fcis-9900	134	14	level	level	ADJ
fcis-9900	134	15	features	feature	NOUN
fcis-9900	134	16	based	base	VERB
fcis-9900	134	17	on	on	ADP
fcis-9900	134	18	crelu	crelu	NOUN
fcis-9900	134	19	and	and	CCONJ
fcis-9900	134	20	then	then	ADV
fcis-9900	134	21	uses	use	VERB
fcis-9900	134	22	regional	regional	ADJ
fcis-9900	134	23	channel	channel	NOUN
fcis-9900	134	24	attention	attention	NOUN
fcis-9900	134	25	to	to	AUX
fcis-9900	134	26	further	far	ADV
fcis-9900	134	27	extract	extract	VERB
fcis-9900	134	28	target	target	NOUN
fcis-9900	134	29	features	feature	NOUN
fcis-9900	134	30	.	.	PUNCT
fcis-9900	135	1	the	the	DET
fcis-9900	135	2	semantics	semantic	NOUN
fcis-9900	135	3	of	of	ADP
fcis-9900	135	4	low	low	ADJ
fcis-9900	135	5	-	-	PUNCT
fcis-9900	135	6	level	level	NOUN
fcis-9900	135	7	features	feature	NOUN
fcis-9900	135	8	and	and	CCONJ
fcis-9900	135	9	the	the	DET
fcis-9900	135	10	location	location	NOUN
fcis-9900	135	11	information	information	NOUN
fcis-9900	135	12	of	of	ADP
fcis-9900	135	13	high	high	ADJ
fcis-9900	135	14	-	-	PUNCT
fcis-9900	135	15	level	level	NOUN
fcis-9900	135	16	features	feature	NOUN
fcis-9900	135	17	are	be	AUX
fcis-9900	135	18	enhanced	enhance	VERB
fcis-9900	135	19	.	.	PUNCT
fcis-9900	136	1	secondly	secondly	ADV
fcis-9900	136	2	,	,	PUNCT
fcis-9900	136	3	for	for	ADP
fcis-9900	136	4	the	the	DET
fcis-9900	136	5	channels	channel	NOUN
fcis-9900	136	6	after	after	ADP
fcis-9900	136	7	feature	feature	NOUN
fcis-9900	136	8	fusion	fusion	NOUN
fcis-9900	136	9	,	,	PUNCT
fcis-9900	136	10	the	the	DET
fcis-9900	136	11	region	region	NOUN
fcis-9900	136	12	information	information	NOUN
fcis-9900	136	13	of	of	ADP
fcis-9900	136	14	the	the	DET
fcis-9900	136	15	feature	feature	NOUN
fcis-9900	136	16	map	map	NOUN
fcis-9900	136	17	is	be	AUX
fcis-9900	136	18	used	use	VERB
fcis-9900	136	19	to	to	PART
fcis-9900	136	20	optimize	optimize	VERB
fcis-9900	136	21	the	the	DET
fcis-9900	136	22	weight	weight	NOUN
fcis-9900	136	23	assignment	assignment	NOUN
fcis-9900	136	24	,	,	PUNCT
fcis-9900	136	25	which	which	PRON
fcis-9900	136	26	helps	help	VERB
fcis-9900	136	27	to	to	PART
fcis-9900	136	28	accurately	accurately	ADV
fcis-9900	136	29	focus	focus	VERB
fcis-9900	136	30	on	on	ADP
fcis-9900	136	31	important	important	ADJ
fcis-9900	136	32	channels	channel	NOUN
fcis-9900	136	33	and	and	CCONJ
fcis-9900	136	34	suppress	suppress	VERB
fcis-9900	136	35	irrelevant	irrelevant	ADJ
fcis-9900	136	36	channels	channel	NOUN
fcis-9900	136	37	.	.	PUNCT
fcis-9900	137	1	finally	finally	ADV
fcis-9900	137	2	,	,	PUNCT
fcis-9900	137	3	the	the	DET
fcis-9900	137	4	targets	target	NOUN
fcis-9900	137	5	are	be	AUX
fcis-9900	137	6	classified	classify	VERB
fcis-9900	137	7	and	and	CCONJ
fcis-9900	137	8	localized	localize	VERB
fcis-9900	137	9	based	base	VERB
fcis-9900	137	10	on	on	ADP
fcis-9900	137	11	the	the	DET
fcis-9900	137	12	enhanced	enhanced	ADJ
fcis-9900	137	13	features	feature	NOUN
fcis-9900	137	14	.	.	PUNCT
fcis-9900	138	1	the	the	DET
fcis-9900	138	2	final	final	ADJ
fcis-9900	138	3	experiment	experiment	NOUN
fcis-9900	138	4	verifies	verifie	NOUN
fcis-9900	138	5	that	that	PRON
fcis-9900	138	6	odmc	odmc	PROPN
fcis-9900	138	7	achieves	achieve	VERB
fcis-9900	138	8	significant	significant	ADJ
fcis-9900	138	9	improvements	improvement	NOUN
fcis-9900	138	10	and	and	CCONJ
fcis-9900	138	11	high	high	ADJ
fcis-9900	138	12	efficiency	efficiency	NOUN
fcis-9900	138	13	on	on	ADP
fcis-9900	138	14	comparable	comparable	ADJ
fcis-9900	138	15	state	state	NOUN
fcis-9900	138	16	-	-	PUNCT
fcis-9900	138	17	ofthe	ofthe	NOUN
fcis-9900	138	18	-	-	PUNCT
fcis-9900	138	19	art	art	NOUN
fcis-9900	138	20	detection	detection	NOUN
fcis-9900	138	21	models	model	NOUN
fcis-9900	138	22	.	.	PUNCT
fcis-9900	139	1	3.3	3.3	NUM
fcis-9900	139	2	.	.	PUNCT
fcis-9900	140	1	feature	feature	NOUN
fcis-9900	140	2	fusion	fusion	NOUN
fcis-9900	140	3	the	the	DET
fcis-9900	140	4	fusion	fusion	NOUN
fcis-9900	140	5	of	of	ADP
fcis-9900	140	6	features	feature	NOUN
fcis-9900	140	7	at	at	ADP
fcis-9900	140	8	different	different	ADJ
fcis-9900	140	9	scales	scale	NOUN
fcis-9900	140	10	is	be	AUX
fcis-9900	140	11	one	one	NUM
fcis-9900	140	12	of	of	ADP
fcis-9900	140	13	the	the	DET
fcis-9900	140	14	important	important	ADJ
fcis-9900	140	15	means	mean	NOUN
fcis-9900	140	16	to	to	PART
fcis-9900	140	17	improve	improve	VERB
fcis-9900	140	18	detection	detection	NOUN
fcis-9900	140	19	performance	performance	NOUN
fcis-9900	140	20	.	.	PUNCT
fcis-9900	141	1	lowlevel	lowlevel	VERB
fcis-9900	141	2	features	feature	NOUN
fcis-9900	141	3	have	have	VERB
fcis-9900	141	4	higher	high	ADJ
fcis-9900	141	5	resolution	resolution	NOUN
fcis-9900	141	6	and	and	CCONJ
fcis-9900	141	7	contain	contain	VERB
fcis-9900	141	8	more	more	ADJ
fcis-9900	141	9	location	location	NOUN
fcis-9900	141	10	and	and	CCONJ
fcis-9900	141	11	detail	detail	NOUN
fcis-9900	141	12	information	information	NOUN
fcis-9900	141	13	,	,	PUNCT
fcis-9900	141	14	but	but	CCONJ
fcis-9900	141	15	they	they	PRON
fcis-9900	141	16	are	be	AUX
fcis-9900	141	17	less	less	ADV
fcis-9900	141	18	semantic	semantic	ADJ
fcis-9900	141	19	and	and	CCONJ
fcis-9900	141	20	noisier	noisy	ADJ
fcis-9900	141	21	due	due	ADJ
fcis-9900	141	22	to	to	ADP
fcis-9900	141	23	less	less	ADJ
fcis-9900	141	24	convolution	convolution	NOUN
fcis-9900	141	25	being	be	AUX
fcis-9900	141	26	undergone	undergo	VERB
fcis-9900	141	27	.	.	PUNCT
fcis-9900	142	1	high	high	ADJ
fcis-9900	142	2	-	-	PUNCT
fcis-9900	142	3	level	level	NOUN
fcis-9900	142	4	features	feature	NOUN
fcis-9900	142	5	have	have	VERB
fcis-9900	142	6	stronger	strong	ADJ
fcis-9900	142	7	semantic	semantic	ADJ
fcis-9900	142	8	information	information	NOUN
fcis-9900	142	9	,	,	PUNCT
fcis-9900	142	10	but	but	CCONJ
fcis-9900	142	11	lower	low	ADJ
fcis-9900	142	12	resolution	resolution	NOUN
fcis-9900	142	13	and	and	CCONJ
fcis-9900	142	14	poorer	poor	ADJ
fcis-9900	142	15	perception	perception	NOUN
fcis-9900	142	16	of	of	ADP
fcis-9900	142	17	details	detail	NOUN
fcis-9900	142	18	.	.	PUNCT
fcis-9900	143	1	how	how	SCONJ
fcis-9900	143	2	to	to	PART
fcis-9900	143	3	fuse	fuse	VERB
fcis-9900	143	4	these	these	DET
fcis-9900	143	5	two	two	NUM
fcis-9900	143	6	features	feature	NOUN
fcis-9900	143	7	efficiently	efficiently	ADV
fcis-9900	143	8	to	to	PART
fcis-9900	143	9	fully	fully	ADV
fcis-9900	143	10	utilize	utilize	VERB
fcis-9900	143	11	their	their	PRON
fcis-9900	143	12	advantages	advantage	NOUN
fcis-9900	143	13	and	and	CCONJ
fcis-9900	143	14	avoid	avoid	VERB
fcis-9900	143	15	their	their	PRON
fcis-9900	143	16	disadvantages	disadvantage	NOUN
fcis-9900	143	17	is	be	AUX
fcis-9900	143	18	the	the	DET
fcis-9900	143	19	key	key	NOUN
fcis-9900	143	20	to	to	ADP
fcis-9900	143	21	improving	improve	VERB
fcis-9900	143	22	the	the	DET
fcis-9900	143	23	segmentation	segmentation	NOUN
fcis-9900	143	24	model	model	NOUN
fcis-9900	143	25	.	.	PUNCT
fcis-9900	144	1	there	there	PRON
fcis-9900	144	2	are	be	VERB
fcis-9900	144	3	many	many	ADJ
fcis-9900	144	4	studies	study	NOUN
fcis-9900	144	5	to	to	PART
fcis-9900	144	6	improve	improve	VERB
fcis-9900	144	7	the	the	DET
fcis-9900	144	8	performance	performance	NOUN
fcis-9900	144	9	of	of	ADP
fcis-9900	144	10	detection	detection	NOUN
fcis-9900	144	11	and	and	CCONJ
fcis-9900	144	12	segmentation	segmentation	NOUN
fcis-9900	144	13	by	by	ADP
fcis-9900	144	14	fusing	fuse	VERB
fcis-9900	144	15	features	feature	NOUN
fcis-9900	144	16	from	from	ADP
fcis-9900	144	17	multiple	multiple	ADJ
fcis-9900	144	18	levels	level	NOUN
fcis-9900	144	19	.	.	PUNCT
fcis-9900	145	1	according	accord	VERB
fcis-9900	145	2	to	to	ADP
fcis-9900	145	3	the	the	DET
fcis-9900	145	4	order	order	NOUN
fcis-9900	145	5	of	of	ADP
fcis-9900	145	6	fusion	fusion	NOUN
fcis-9900	145	7	and	and	CCONJ
fcis-9900	145	8	prediction	prediction	NOUN
fcis-9900	145	9	,	,	PUNCT
fcis-9900	145	10	these	these	DET
fcis-9900	145	11	methods	method	NOUN
fcis-9900	145	12	can	can	AUX
fcis-9900	145	13	be	be	AUX
fcis-9900	145	14	classified	classify	VERB
fcis-9900	145	15	as	as	ADP
fcis-9900	145	16	early	early	ADJ
fcis-9900	145	17	fusion	fusion	NOUN
fcis-9900	145	18	and	and	CCONJ
fcis-9900	145	19	late	late	ADJ
fcis-9900	145	20	fusion	fusion	NOUN
fcis-9900	145	21	.	.	PUNCT
fcis-9900	146	1	in	in	ADP
fcis-9900	146	2	complex	complex	ADJ
fcis-9900	146	3	environments	environment	NOUN
fcis-9900	146	4	,	,	PUNCT
fcis-9900	146	5	small	small	ADJ
fcis-9900	146	6	targets	target	NOUN
fcis-9900	146	7	are	be	AUX
fcis-9900	146	8	often	often	ADV
fcis-9900	146	9	44	44	NUM
fcis-9900	146	10	susceptible	susceptible	ADJ
fcis-9900	146	11	to	to	PART
fcis-9900	146	12	interference	interference	VERB
fcis-9900	146	13	from	from	ADP
fcis-9900	146	14	background	background	NOUN
fcis-9900	146	15	information	information	NOUN
fcis-9900	146	16	.	.	PUNCT
fcis-9900	147	1	the	the	DET
fcis-9900	147	2	semantic	semantic	ADJ
fcis-9900	147	3	information	information	NOUN
fcis-9900	147	4	extracted	extract	VERB
fcis-9900	147	5	by	by	ADP
fcis-9900	147	6	the	the	DET
fcis-9900	147	7	feature	feature	NOUN
fcis-9900	147	8	extraction	extraction	NOUN
fcis-9900	147	9	network	network	NOUN
fcis-9900	147	10	is	be	AUX
fcis-9900	147	11	relatively	relatively	ADV
fcis-9900	147	12	limited	limited	ADJ
fcis-9900	147	13	.	.	PUNCT
fcis-9900	148	1	in	in	ADP
fcis-9900	148	2	the	the	DET
fcis-9900	148	3	feature	feature	NOUN
fcis-9900	148	4	extraction	extraction	NOUN
fcis-9900	148	5	process	process	NOUN
fcis-9900	148	6	of	of	ADP
fcis-9900	148	7	target	target	NOUN
fcis-9900	148	8	detection	detection	NOUN
fcis-9900	148	9	,	,	PUNCT
fcis-9900	148	10	the	the	DET
fcis-9900	148	11	shallow	shallow	ADJ
fcis-9900	148	12	feature	feature	NOUN
fcis-9900	148	13	map	map	NOUN
fcis-9900	148	14	contains	contain	VERB
fcis-9900	148	15	resolution	resolution	NOUN
fcis-9900	148	16	information	information	NOUN
fcis-9900	148	17	.	.	PUNCT
fcis-9900	149	1	although	although	SCONJ
fcis-9900	149	2	higher	high	ADJ
fcis-9900	149	3	-	-	PUNCT
fcis-9900	149	4	level	level	NOUN
fcis-9900	149	5	features	feature	NOUN
fcis-9900	149	6	can	can	AUX
fcis-9900	149	7	be	be	AUX
fcis-9900	149	8	used	use	VERB
fcis-9900	149	9	to	to	PART
fcis-9900	149	10	improve	improve	VERB
fcis-9900	149	11	the	the	DET
fcis-9900	149	12	regression	regression	NOUN
fcis-9900	149	13	accuracy	accuracy	NOUN
fcis-9900	149	14	of	of	ADP
fcis-9900	149	15	the	the	DET
fcis-9900	149	16	bounding	bounding	NOUN
fcis-9900	149	17	box	box	NOUN
fcis-9900	149	18	,	,	PUNCT
fcis-9900	149	19	these	these	DET
fcis-9900	149	20	features	feature	NOUN
fcis-9900	149	21	have	have	VERB
fcis-9900	149	22	little	little	ADJ
fcis-9900	149	23	semantic	semantic	ADJ
fcis-9900	149	24	information	information	NOUN
fcis-9900	149	25	and	and	CCONJ
fcis-9900	149	26	are	be	AUX
fcis-9900	149	27	easily	easily	ADV
fcis-9900	149	28	disturbed	disturb	VERB
fcis-9900	149	29	by	by	ADP
fcis-9900	149	30	noise	noise	NOUN
fcis-9900	149	31	points	point	NOUN
fcis-9900	149	32	.	.	PUNCT
fcis-9900	150	1	the	the	DET
fcis-9900	150	2	deep	deep	ADJ
fcis-9900	150	3	-	-	PUNCT
fcis-9900	150	4	level	level	NOUN
fcis-9900	150	5	network	network	NOUN
fcis-9900	150	6	contains	contain	VERB
fcis-9900	150	7	strong	strong	ADJ
fcis-9900	150	8	semantic	semantic	ADJ
fcis-9900	150	9	information	information	NOUN
fcis-9900	150	10	but	but	CCONJ
fcis-9900	150	11	has	have	VERB
fcis-9900	150	12	low	low	ADJ
fcis-9900	150	13	resolution	resolution	NOUN
fcis-9900	150	14	and	and	CCONJ
fcis-9900	150	15	the	the	DET
fcis-9900	150	16	ability	ability	NOUN
fcis-9900	150	17	to	to	PART
fcis-9900	150	18	express	express	VERB
fcis-9900	150	19	details	detail	NOUN
fcis-9900	150	20	.	.	PUNCT
fcis-9900	151	1	the	the	DET
fcis-9900	151	2	introduction	introduction	NOUN
fcis-9900	151	3	of	of	ADP
fcis-9900	151	4	feature	feature	NOUN
fcis-9900	151	5	fusion	fusion	NOUN
fcis-9900	151	6	is	be	AUX
fcis-9900	151	7	effective	effective	ADJ
fcis-9900	151	8	and	and	CCONJ
fcis-9900	151	9	can	can	AUX
fcis-9900	151	10	improve	improve	VERB
fcis-9900	151	11	the	the	DET
fcis-9900	151	12	detection	detection	NOUN
fcis-9900	151	13	of	of	ADP
fcis-9900	151	14	small	small	ADJ
fcis-9900	151	15	targets	target	NOUN
fcis-9900	151	16	.	.	PUNCT
fcis-9900	152	1	shi	shi	PROPN
fcis-9900	152	2	w	w	PROPN
fcis-9900	152	3	et	et	PROPN
fcis-9900	152	4	al	al	PROPN
fcis-9900	153	1	[	[	X
fcis-9900	153	2	35	35	NUM
fcis-9900	153	3	]	]	PUNCT
fcis-9900	153	4	proposed	propose	VERB
fcis-9900	153	5	an	an	DET
fcis-9900	153	6	accurate	accurate	ADJ
fcis-9900	153	7	and	and	CCONJ
fcis-9900	153	8	effective	effective	ADJ
fcis-9900	153	9	target	target	NOUN
fcis-9900	153	10	detection	detection	NOUN
fcis-9900	153	11	method	method	NOUN
fcis-9900	153	12	called	call	VERB
fcis-9900	153	13	feature	feature	NOUN
fcis-9900	153	14	-	-	PUNCT
fcis-9900	153	15	enhanced	enhance	VERB
fcis-9900	153	16	fusion	fusion	NOUN
fcis-9900	153	17	for	for	ADP
fcis-9900	153	18	singleshot	singleshot	NOUN
fcis-9900	153	19	target	target	NOUN
fcis-9900	153	20	detection	detection	NOUN
fcis-9900	153	21	(	(	PUNCT
fcis-9900	153	22	ffessd	ffessd	NOUN
fcis-9900	153	23	)	)	PUNCT
fcis-9900	153	24	,	,	PUNCT
fcis-9900	153	25	which	which	PRON
fcis-9900	153	26	enhances	enhance	VERB
fcis-9900	153	27	and	and	CCONJ
fcis-9900	153	28	utilizes	utilize	VERB
fcis-9900	153	29	shallow	shallow	ADJ
fcis-9900	153	30	and	and	CCONJ
fcis-9900	153	31	deep	deep	ADJ
fcis-9900	153	32	features	feature	NOUN
fcis-9900	153	33	in	in	ADP
fcis-9900	153	34	the	the	DET
fcis-9900	153	35	feature	feature	NOUN
fcis-9900	153	36	pyramid	pyramid	NOUN
fcis-9900	153	37	structure	structure	NOUN
fcis-9900	153	38	of	of	ADP
fcis-9900	153	39	the	the	DET
fcis-9900	153	40	ssd	ssd	NOUN
fcis-9900	153	41	algorithm	algorithm	NOUN
fcis-9900	153	42	.	.	PUNCT
fcis-9900	154	1	a	a	DET
fcis-9900	154	2	feature	feature	NOUN
fcis-9900	154	3	fusion	fusion	NOUN
fcis-9900	154	4	module	module	NOUN
fcis-9900	154	5	and	and	CCONJ
fcis-9900	154	6	two	two	NUM
fcis-9900	154	7	feature	feature	NOUN
fcis-9900	154	8	enhancement	enhancement	NOUN
fcis-9900	154	9	modules	module	NOUN
fcis-9900	154	10	are	be	AUX
fcis-9900	154	11	introduced	introduce	VERB
fcis-9900	154	12	and	and	CCONJ
fcis-9900	154	13	integrated	integrate	VERB
fcis-9900	154	14	into	into	ADP
fcis-9900	154	15	the	the	DET
fcis-9900	154	16	traditional	traditional	ADJ
fcis-9900	154	17	ssd	ssd	NOUN
fcis-9900	154	18	structure	structure	NOUN
fcis-9900	154	19	.	.	PUNCT
fcis-9900	155	1	tests	test	NOUN
fcis-9900	155	2	using	use	VERB
fcis-9900	155	3	the	the	DET
fcis-9900	155	4	proposed	propose	VERB
fcis-9900	155	5	network	network	NOUN
fcis-9900	155	6	on	on	ADP
fcis-9900	155	7	the	the	DET
fcis-9900	155	8	dataset	dataset	NOUN
fcis-9900	155	9	show	show	VERB
fcis-9900	155	10	the	the	DET
fcis-9900	155	11	state	state	NOUN
fcis-9900	155	12	-	-	PUNCT
fcis-9900	155	13	of	of	ADP
fcis-9900	155	14	-	-	PUNCT
fcis-9900	155	15	the	the	DET
fcis-9900	155	16	-	-	PUNCT
fcis-9900	155	17	art	art	NOUN
fcis-9900	155	18	map	map	NOUN
fcis-9900	155	19	,	,	PUNCT
fcis-9900	155	20	which	which	PRON
fcis-9900	155	21	outperforms	outperform	VERB
fcis-9900	155	22	the	the	DET
fcis-9900	155	23	conventional	conventional	ADJ
fcis-9900	155	24	ssd	ssd	NOUN
fcis-9900	155	25	,	,	PUNCT
fcis-9900	155	26	deconvolution	deconvolution	ADJ
fcis-9900	155	27	single	single	ADJ
fcis-9900	155	28	pass	pass	NOUN
fcis-9900	155	29	detector	detector	NOUN
fcis-9900	155	30	(	(	PUNCT
fcis-9900	155	31	dssd	dssd	NOUN
fcis-9900	155	32	)	)	PUNCT
fcis-9900	155	33	,	,	PUNCT
fcis-9900	155	34	feature	feature	NOUN
fcis-9900	155	35	fusion	fusion	NOUN
fcis-9900	155	36	ssd	ssd	NOUN
fcis-9900	155	37	(	(	PUNCT
fcis-9900	155	38	fssd	fssd	NOUN
fcis-9900	155	39	)	)	PUNCT
fcis-9900	155	40	,	,	PUNCT
fcis-9900	155	41	and	and	CCONJ
fcis-9900	155	42	other	other	ADJ
fcis-9900	155	43	advanced	advanced	ADJ
fcis-9900	155	44	detectors	detector	NOUN
fcis-9900	155	45	.	.	PUNCT
fcis-9900	156	1	in	in	ADP
fcis-9900	156	2	extended	extended	ADJ
fcis-9900	156	3	experiments	experiment	NOUN
fcis-9900	156	4	,	,	PUNCT
fcis-9900	156	5	ffessd	ffessd	NOUN
fcis-9900	156	6	outperforms	outperform	VERB
fcis-9900	156	7	conventional	conventional	ADJ
fcis-9900	156	8	ssd	ssd	NOUN
fcis-9900	156	9	for	for	ADP
fcis-9900	156	10	fuzzy	fuzzy	ADJ
fcis-9900	156	11	target	target	NOUN
fcis-9900	156	12	detection	detection	NOUN
fcis-9900	156	13	.	.	PUNCT
fcis-9900	157	1	woo	woo	VERB
fcis-9900	157	2	s	s	PART
fcis-9900	158	1	[	[	X
fcis-9900	158	2	36	36	NUM
fcis-9900	158	3	]	]	PUNCT
fcis-9900	158	4	et	et	PROPN
fcis-9900	158	5	al	al	PROPN
fcis-9900	158	6	.	.	PROPN
fcis-9900	158	7	started	start	VERB
fcis-9900	158	8	from	from	ADP
fcis-9900	158	9	the	the	DET
fcis-9900	158	10	ssd	ssd	NOUN
fcis-9900	158	11	framework	framework	NOUN
fcis-9900	158	12	,	,	PUNCT
fcis-9900	158	13	where	where	SCONJ
fcis-9900	158	14	the	the	DET
fcis-9900	158	15	lower	low	ADJ
fcis-9900	158	16	layers	layer	NOUN
fcis-9900	158	17	responsible	responsible	ADJ
fcis-9900	158	18	for	for	ADP
fcis-9900	158	19	small	small	ADJ
fcis-9900	158	20	objects	object	NOUN
fcis-9900	158	21	lack	lack	VERB
fcis-9900	158	22	strong	strong	ADJ
fcis-9900	158	23	semantics	semantic	NOUN
fcis-9900	158	24	(	(	PUNCT
fcis-9900	158	25	e.g.	e.g.	ADV
fcis-9900	158	26	,	,	PUNCT
fcis-9900	158	27	contextual	contextual	ADJ
fcis-9900	158	28	information	information	NOUN
fcis-9900	158	29	)	)	PUNCT
fcis-9900	158	30	due	due	ADP
fcis-9900	158	31	to	to	ADP
fcis-9900	158	32	the	the	DET
fcis-9900	158	33	pyramidal	pyramidal	ADJ
fcis-9900	158	34	design	design	NOUN
fcis-9900	158	35	.	.	PUNCT
fcis-9900	159	1	this	this	DET
fcis-9900	159	2	problem	problem	NOUN
fcis-9900	159	3	was	be	AUX
fcis-9900	159	4	addressed	address	VERB
fcis-9900	159	5	by	by	ADP
fcis-9900	159	6	introducing	introduce	VERB
fcis-9900	159	7	a	a	DET
fcis-9900	159	8	feature	feature	NOUN
fcis-9900	159	9	combination	combination	NOUN
fcis-9900	159	10	module	module	NOUN
fcis-9900	159	11	that	that	PRON
fcis-9900	159	12	unfolds	unfold	VERB
fcis-9900	159	13	strong	strong	ADJ
fcis-9900	159	14	semantics	semantic	NOUN
fcis-9900	159	15	in	in	ADP
fcis-9900	159	16	a	a	DET
fcis-9900	159	17	topdown	topdown	ADJ
fcis-9900	159	18	manner	manner	NOUN
fcis-9900	159	19	.	.	PUNCT
fcis-9900	160	1	the	the	DET
fcis-9900	160	2	final	final	ADJ
fcis-9900	160	3	model	model	NOUN
fcis-9900	160	4	stairnet	stairnet	NOUN
fcis-9900	160	5	detector	detector	NOUN
fcis-9900	160	6	effectively	effectively	ADV
fcis-9900	160	7	unifies	unify	VERB
fcis-9900	160	8	the	the	DET
fcis-9900	160	9	multi	multi	ADJ
fcis-9900	160	10	-	-	ADJ
fcis-9900	160	11	scale	scale	ADJ
fcis-9900	160	12	representation	representation	NOUN
fcis-9900	160	13	and	and	CCONJ
fcis-9900	160	14	semantic	semantic	ADJ
fcis-9900	160	15	distribution	distribution	NOUN
fcis-9900	160	16	.	.	PUNCT
fcis-9900	161	1	experiments	experiment	NOUN
fcis-9900	161	2	on	on	ADP
fcis-9900	161	3	many	many	ADJ
fcis-9900	161	4	datasets	dataset	NOUN
fcis-9900	161	5	show	show	VERB
fcis-9900	161	6	that	that	SCONJ
fcis-9900	161	7	stairnet	stairnet	NOUN
fcis-9900	161	8	significantly	significantly	ADV
fcis-9900	161	9	improves	improve	VERB
fcis-9900	161	10	the	the	DET
fcis-9900	161	11	weaknesses	weakness	NOUN
fcis-9900	161	12	of	of	ADP
fcis-9900	161	13	ssd	ssd	NOUN
fcis-9900	161	14	and	and	CCONJ
fcis-9900	161	15	outperforms	outperform	VERB
fcis-9900	161	16	other	other	ADJ
fcis-9900	161	17	state	state	NOUN
fcis-9900	161	18	-	-	PUNCT
fcis-9900	161	19	of	of	ADP
fcis-9900	161	20	-	-	PUNCT
fcis-9900	161	21	the	the	DET
fcis-9900	161	22	-	-	PUNCT
fcis-9900	161	23	art	art	NOUN
fcis-9900	161	24	first	first	ADJ
fcis-9900	161	25	-	-	PUNCT
fcis-9900	161	26	class	class	NOUN
fcis-9900	161	27	detectors	detector	NOUN
fcis-9900	161	28	.	.	PUNCT
fcis-9900	162	1	3.4	3.4	NUM
fcis-9900	162	2	.	.	PUNCT
fcis-9900	162	3	contextual	contextual	ADJ
fcis-9900	162	4	information	information	NOUN
fcis-9900	162	5	contextual	contextual	ADJ
fcis-9900	162	6	information	information	NOUN
fcis-9900	162	7	refers	refer	VERB
fcis-9900	162	8	to	to	ADP
fcis-9900	162	9	the	the	DET
fcis-9900	162	10	fact	fact	NOUN
fcis-9900	162	11	that	that	SCONJ
fcis-9900	162	12	in	in	ADP
fcis-9900	162	13	an	an	DET
fcis-9900	162	14	image	image	NOUN
fcis-9900	162	15	,	,	PUNCT
fcis-9900	162	16	a	a	DET
fcis-9900	162	17	pixel	pixel	NOUN
fcis-9900	162	18	or	or	CCONJ
fcis-9900	162	19	a	a	DET
fcis-9900	162	20	target	target	NOUN
fcis-9900	162	21	does	do	AUX
fcis-9900	162	22	not	not	PART
fcis-9900	162	23	exist	exist	VERB
fcis-9900	162	24	alone	alone	ADV
fcis-9900	162	25	,	,	PUNCT
fcis-9900	162	26	but	but	CCONJ
fcis-9900	162	27	has	have	VERB
fcis-9900	162	28	a	a	DET
fcis-9900	162	29	certain	certain	ADJ
fcis-9900	162	30	dependency	dependency	NOUN
fcis-9900	162	31	relationship	relationship	NOUN
fcis-9900	162	32	with	with	ADP
fcis-9900	162	33	the	the	DET
fcis-9900	162	34	surrounding	surround	VERB
fcis-9900	162	35	pixels	pixel	NOUN
fcis-9900	162	36	and	and	CCONJ
fcis-9900	162	37	targets	target	NOUN
fcis-9900	162	38	.	.	PUNCT
fcis-9900	163	1	reasonably	reasonably	ADV
fcis-9900	163	2	extracting	extract	VERB
fcis-9900	163	3	and	and	CCONJ
fcis-9900	163	4	using	use	VERB
fcis-9900	163	5	the	the	DET
fcis-9900	163	6	relationship	relationship	NOUN
fcis-9900	163	7	between	between	ADP
fcis-9900	163	8	targets	target	NOUN
fcis-9900	163	9	and	and	CCONJ
fcis-9900	163	10	targets	target	NOUN
fcis-9900	163	11	has	have	VERB
fcis-9900	163	12	a	a	DET
fcis-9900	163	13	great	great	ADJ
fcis-9900	163	14	improvement	improvement	NOUN
fcis-9900	163	15	on	on	ADP
fcis-9900	163	16	the	the	DET
fcis-9900	163	17	detection	detection	NOUN
fcis-9900	163	18	accuracy	accuracy	NOUN
fcis-9900	163	19	of	of	ADP
fcis-9900	163	20	small	small	ADJ
fcis-9900	163	21	targets	target	NOUN
fcis-9900	163	22	.	.	PUNCT
fcis-9900	164	1	tang	tang	NOUN
fcis-9900	164	2	x	x	PUNCT
fcis-9900	164	3	et	et	NOUN
fcis-9900	164	4	al	al	PROPN
fcis-9900	165	1	[	[	X
fcis-9900	165	2	37	37	NUM
fcis-9900	165	3	]	]	PUNCT
fcis-9900	165	4	proposed	propose	VERB
fcis-9900	165	5	a	a	DET
fcis-9900	165	6	new	new	ADJ
fcis-9900	165	7	context	context	NOUN
fcis-9900	165	8	-	-	PUNCT
fcis-9900	165	9	assisted	assist	VERB
fcis-9900	165	10	singleshot	singleshot	ADJ
fcis-9900	165	11	face	face	NOUN
fcis-9900	165	12	detector	detector	NOUN
fcis-9900	165	13	,	,	PUNCT
fcis-9900	165	14	called	call	VERB
fcis-9900	165	15	a	a	DET
fcis-9900	165	16	pyramidal	pyramidal	ADJ
fcis-9900	165	17	box	box	NOUN
fcis-9900	165	18	,	,	PUNCT
fcis-9900	165	19	for	for	ADP
fcis-9900	165	20	dealing	deal	VERB
fcis-9900	165	21	with	with	ADP
fcis-9900	165	22	difficult	difficult	ADJ
fcis-9900	165	23	face	face	NOUN
fcis-9900	165	24	detection	detection	NOUN
fcis-9900	165	25	problems	problem	NOUN
fcis-9900	165	26	.	.	PUNCT
fcis-9900	166	1	due	due	ADP
fcis-9900	166	2	to	to	ADP
fcis-9900	166	3	the	the	DET
fcis-9900	166	4	importance	importance	NOUN
fcis-9900	166	5	of	of	ADP
fcis-9900	166	6	context	context	NOUN
fcis-9900	166	7	,	,	PUNCT
fcis-9900	166	8	the	the	DET
fcis-9900	166	9	utilization	utilization	NOUN
fcis-9900	166	10	of	of	ADP
fcis-9900	166	11	contextual	contextual	ADJ
fcis-9900	166	12	information	information	NOUN
fcis-9900	166	13	is	be	AUX
fcis-9900	166	14	increased	increase	VERB
fcis-9900	166	15	at	at	ADP
fcis-9900	166	16	three	three	NUM
fcis-9900	166	17	levels	level	NOUN
fcis-9900	166	18	as	as	SCONJ
fcis-9900	166	19	follows	follow	VERB
fcis-9900	166	20	.	.	PUNCT
fcis-9900	167	1	first	first	ADV
fcis-9900	167	2	,	,	PUNCT
fcis-9900	167	3	we	we	PRON
fcis-9900	167	4	propose	propose	VERB
fcis-9900	167	5	a	a	DET
fcis-9900	167	6	novel	novel	ADJ
fcis-9900	167	7	contextual	contextual	ADJ
fcis-9900	167	8	anchor	anchor	NOUN
fcis-9900	167	9	that	that	PRON
fcis-9900	167	10	employs	employ	VERB
fcis-9900	167	11	a	a	DET
fcis-9900	167	12	zero	zero	NUM
fcis-9900	167	13	-	-	PUNCT
fcis-9900	167	14	point	point	NOUN
fcis-9900	167	15	-	-	PUNCT
fcis-9900	167	16	five	five	NUM
fcis-9900	167	17	supervised	supervised	ADJ
fcis-9900	167	18	approach	approach	NOUN
fcis-9900	167	19	to	to	PART
fcis-9900	167	20	track	track	VERB
fcis-9900	167	21	the	the	DET
fcis-9900	167	22	learning	learning	NOUN
fcis-9900	167	23	of	of	ADP
fcis-9900	167	24	the	the	DET
fcis-9900	167	25	environment	environment	NOUN
fcis-9900	167	26	's	's	PART
fcis-9900	167	27	high	high	ADJ
fcis-9900	167	28	-	-	PUNCT
fcis-9900	167	29	level	level	NOUN
fcis-9900	167	30	context	context	NOUN
fcis-9900	167	31	,	,	PUNCT
fcis-9900	167	32	called	call	VERB
fcis-9900	167	33	the	the	DET
fcis-9900	167	34	pyramid	pyramid	NOUN
fcis-9900	167	35	anchor	anchor	PROPN
fcis-9900	167	36	.	.	PUNCT
fcis-9900	168	1	second	second	ADJ
fcis-9900	168	2	,	,	PUNCT
fcis-9900	168	3	a	a	DET
fcis-9900	168	4	low	low	ADJ
fcis-9900	168	5	-	-	PUNCT
fcis-9900	168	6	level	level	NOUN
fcis-9900	168	7	feature	feature	NOUN
fcis-9900	168	8	pyramid	pyramid	NOUN
fcis-9900	168	9	network	network	NOUN
fcis-9900	168	10	is	be	AUX
fcis-9900	168	11	proposed	propose	VERB
fcis-9900	168	12	to	to	PART
fcis-9900	168	13	combine	combine	VERB
fcis-9900	168	14	sufficient	sufficient	ADJ
fcis-9900	168	15	high	high	ADJ
fcis-9900	168	16	-	-	PUNCT
fcis-9900	168	17	level	level	NOUN
fcis-9900	168	18	contextual	contextual	ADJ
fcis-9900	168	19	semantic	semantic	ADJ
fcis-9900	168	20	features	feature	NOUN
fcis-9900	168	21	with	with	ADP
fcis-9900	168	22	low	low	ADJ
fcis-9900	168	23	-	-	PUNCT
fcis-9900	168	24	level	level	NOUN
fcis-9900	168	25	facial	facial	ADJ
fcis-9900	168	26	features	feature	NOUN
fcis-9900	168	27	,	,	PUNCT
fcis-9900	168	28	which	which	PRON
fcis-9900	168	29	also	also	ADV
fcis-9900	168	30	allows	allow	VERB
fcis-9900	168	31	pyramid	pyramid	NOUN
fcis-9900	168	32	boxes	box	NOUN
fcis-9900	168	33	to	to	PART
fcis-9900	168	34	predict	predict	VERB
fcis-9900	168	35	faces	face	NOUN
fcis-9900	168	36	at	at	ADP
fcis-9900	168	37	all	all	DET
fcis-9900	168	38	scales	scale	NOUN
fcis-9900	168	39	in	in	ADP
fcis-9900	168	40	a	a	DET
fcis-9900	168	41	single	single	ADJ
fcis-9900	168	42	shot	shot	NOUN
fcis-9900	168	43	.	.	PUNCT
fcis-9900	169	1	third	third	ADJ
fcis-9900	169	2	,	,	PUNCT
fcis-9900	169	3	a	a	DET
fcis-9900	169	4	context	context	NOUN
fcis-9900	169	5	-	-	PUNCT
fcis-9900	169	6	sensitive	sensitive	ADJ
fcis-9900	169	7	structure	structure	NOUN
fcis-9900	169	8	is	be	AUX
fcis-9900	169	9	introduced	introduce	VERB
fcis-9900	169	10	to	to	PART
fcis-9900	169	11	increase	increase	VERB
fcis-9900	169	12	the	the	DET
fcis-9900	169	13	capacity	capacity	NOUN
fcis-9900	169	14	of	of	ADP
fcis-9900	169	15	the	the	DET
fcis-9900	169	16	prediction	prediction	NOUN
fcis-9900	169	17	network	network	NOUN
fcis-9900	169	18	to	to	PART
fcis-9900	169	19	improve	improve	VERB
fcis-9900	169	20	the	the	DET
fcis-9900	169	21	accuracy	accuracy	NOUN
fcis-9900	169	22	of	of	ADP
fcis-9900	169	23	the	the	DET
fcis-9900	169	24	final	final	ADJ
fcis-9900	169	25	output	output	NOUN
fcis-9900	169	26	.	.	PUNCT
fcis-9900	170	1	hu	hu	PROPN
fcis-9900	171	1	h	h	PROPN
fcis-9900	171	2	et	et	PROPN
fcis-9900	171	3	al	al	PROPN
fcis-9900	172	1	[	[	X
fcis-9900	172	2	38	38	NUM
fcis-9900	172	3	]	]	PUNCT
fcis-9900	172	4	proposed	propose	VERB
fcis-9900	172	5	an	an	DET
fcis-9900	172	6	object	object	NOUN
fcis-9900	172	7	relationship	relationship	NOUN
fcis-9900	172	8	model	model	NOUN
fcis-9900	172	9	.	.	PUNCT
fcis-9900	173	1	the	the	DET
fcis-9900	173	2	model	model	NOUN
fcis-9900	173	3	takes	take	VERB
fcis-9900	173	4	advantage	advantage	NOUN
fcis-9900	173	5	of	of	ADP
fcis-9900	173	6	the	the	DET
fcis-9900	173	7	appearance	appearance	NOUN
fcis-9900	173	8	properties	property	NOUN
fcis-9900	173	9	of	of	ADP
fcis-9900	173	10	objects	object	NOUN
fcis-9900	173	11	,	,	PUNCT
fcis-9900	173	12	and	and	CCONJ
fcis-9900	173	13	the	the	DET
fcis-9900	173	14	interactions	interaction	NOUN
fcis-9900	173	15	between	between	ADP
fcis-9900	173	16	geometries	geometry	NOUN
fcis-9900	173	17	to	to	PART
fcis-9900	173	18	process	process	VERB
fcis-9900	173	19	each	each	DET
fcis-9900	173	20	object	object	NOUN
fcis-9900	173	21	simultaneously	simultaneously	ADV
fcis-9900	173	22	,	,	PUNCT
fcis-9900	173	23	thus	thus	ADV
fcis-9900	173	24	allowing	allow	VERB
fcis-9900	173	25	the	the	DET
fcis-9900	173	26	modeling	modeling	NOUN
fcis-9900	173	27	of	of	ADP
fcis-9900	173	28	the	the	DET
fcis-9900	173	29	relationships	relationship	NOUN
fcis-9900	173	30	between	between	ADP
fcis-9900	173	31	them	they	PRON
fcis-9900	173	32	.	.	PUNCT
fcis-9900	174	1	it	it	PRON
fcis-9900	174	2	is	be	AUX
fcis-9900	174	3	lightweight	lightweight	ADJ
fcis-9900	174	4	and	and	CCONJ
fcis-9900	174	5	in	in	ADP
fcis-9900	174	6	situ	situ	NOUN
fcis-9900	174	7	.	.	PUNCT
fcis-9900	175	1	the	the	DET
fcis-9900	175	2	model	model	NOUN
fcis-9900	175	3	requires	require	VERB
fcis-9900	175	4	no	no	DET
fcis-9900	175	5	additional	additional	ADJ
fcis-9900	175	6	supervision	supervision	NOUN
fcis-9900	175	7	and	and	CCONJ
fcis-9900	175	8	is	be	AUX
fcis-9900	175	9	easily	easily	ADV
fcis-9900	175	10	embedded	embed	VERB
fcis-9900	175	11	in	in	ADP
fcis-9900	175	12	existing	exist	VERB
fcis-9900	175	13	networks	network	NOUN
fcis-9900	175	14	.	.	PUNCT
fcis-9900	176	1	it	it	PRON
fcis-9900	176	2	proves	prove	VERB
fcis-9900	176	3	to	to	PART
fcis-9900	176	4	be	be	AUX
fcis-9900	176	5	effective	effective	ADJ
fcis-9900	176	6	in	in	ADP
fcis-9900	176	7	improving	improve	VERB
fcis-9900	176	8	object	object	NOUN
fcis-9900	176	9	recognition	recognition	NOUN
fcis-9900	176	10	and	and	CCONJ
fcis-9900	176	11	repetition	repetition	NOUN
fcis-9900	176	12	removal	removal	NOUN
fcis-9900	176	13	steps	step	NOUN
fcis-9900	176	14	in	in	ADP
fcis-9900	176	15	modern	modern	ADJ
fcis-9900	176	16	object	object	NOUN
fcis-9900	176	17	detection	detection	NOUN
fcis-9900	176	18	pipelines	pipeline	NOUN
fcis-9900	176	19	.	.	PUNCT
fcis-9900	177	1	the	the	DET
fcis-9900	177	2	model	model	NOUN
fcis-9900	177	3	validates	validate	VERB
fcis-9900	177	4	the	the	DET
fcis-9900	177	5	effectiveness	effectiveness	NOUN
fcis-9900	177	6	of	of	ADP
fcis-9900	177	7	modeling	model	VERB
fcis-9900	177	8	object	object	NOUN
fcis-9900	177	9	relationships	relationship	NOUN
fcis-9900	177	10	in	in	ADP
fcis-9900	177	11	cnn	cnn	PROPN
fcis-9900	177	12	-	-	PUNCT
fcis-9900	177	13	based	base	VERB
fcis-9900	177	14	detection	detection	NOUN
fcis-9900	177	15	.	.	PUNCT
fcis-9900	178	1	the	the	DET
fcis-9900	178	2	model	model	NOUN
fcis-9900	178	3	yields	yield	VERB
fcis-9900	178	4	the	the	DET
fcis-9900	178	5	first	first	ADJ
fcis-9900	178	6	fully	fully	ADV
fcis-9900	178	7	end	end	NOUN
fcis-9900	178	8	-	-	PUNCT
fcis-9900	178	9	to	to	ADP
fcis-9900	178	10	-	-	PUNCT
fcis-9900	178	11	end	end	NOUN
fcis-9900	178	12	object	object	NOUN
fcis-9900	178	13	detector	detector	NOUN
fcis-9900	178	14	.	.	PUNCT
fcis-9900	179	1	4	4	X
fcis-9900	179	2	.	.	X
fcis-9900	179	3	conclusion	conclusion	VERB
fcis-9900	179	4	many	many	ADJ
fcis-9900	179	5	methods	method	NOUN
fcis-9900	179	6	and	and	CCONJ
fcis-9900	179	7	techniques	technique	NOUN
fcis-9900	179	8	have	have	AUX
fcis-9900	179	9	been	be	AUX
fcis-9900	179	10	proposed	propose	VERB
fcis-9900	179	11	for	for	ADP
fcis-9900	179	12	improving	improve	VERB
fcis-9900	179	13	the	the	DET
fcis-9900	179	14	detection	detection	NOUN
fcis-9900	179	15	accuracy	accuracy	NOUN
fcis-9900	179	16	of	of	ADP
fcis-9900	179	17	small	small	ADJ
fcis-9900	179	18	targets	target	NOUN
fcis-9900	179	19	,	,	PUNCT
fcis-9900	179	20	and	and	CCONJ
fcis-9900	179	21	this	this	DET
fcis-9900	179	22	paper	paper	NOUN
fcis-9900	179	23	has	have	AUX
fcis-9900	179	24	done	do	VERB
fcis-9900	179	25	a	a	DET
fcis-9900	179	26	review	review	NOUN
fcis-9900	179	27	of	of	ADP
fcis-9900	179	28	a	a	DET
fcis-9900	179	29	few	few	ADJ
fcis-9900	179	30	simple	simple	ADJ
fcis-9900	179	31	techniques	technique	NOUN
fcis-9900	179	32	.	.	PUNCT
fcis-9900	180	1	this	this	DET
fcis-9900	180	2	paper	paper	NOUN
fcis-9900	180	3	first	first	ADV
fcis-9900	180	4	starts	start	VERB
fcis-9900	180	5	with	with	ADP
fcis-9900	180	6	the	the	DET
fcis-9900	180	7	development	development	NOUN
fcis-9900	180	8	of	of	ADP
fcis-9900	180	9	target	target	NOUN
fcis-9900	180	10	detection	detection	NOUN
fcis-9900	180	11	briefly	briefly	ADV
fcis-9900	180	12	describes	describe	VERB
fcis-9900	180	13	the	the	DET
fcis-9900	180	14	obstacles	obstacle	NOUN
fcis-9900	180	15	to	to	ADP
fcis-9900	180	16	the	the	DET
fcis-9900	180	17	development	development	NOUN
fcis-9900	180	18	of	of	ADP
fcis-9900	180	19	target	target	NOUN
fcis-9900	180	20	detection	detection	NOUN
fcis-9900	180	21	,	,	PUNCT
fcis-9900	180	22	and	and	CCONJ
fcis-9900	180	23	then	then	ADV
fcis-9900	180	24	transitions	transition	NOUN
fcis-9900	180	25	to	to	ADP
fcis-9900	180	26	small	small	ADJ
fcis-9900	180	27	target	target	NOUN
fcis-9900	180	28	detection	detection	NOUN
fcis-9900	180	29	.	.	PUNCT
fcis-9900	181	1	secondly	secondly	ADV
fcis-9900	181	2	,	,	PUNCT
fcis-9900	181	3	the	the	DET
fcis-9900	181	4	common	common	ADJ
fcis-9900	181	5	datasets	dataset	NOUN
fcis-9900	181	6	for	for	ADP
fcis-9900	181	7	small	small	ADJ
fcis-9900	181	8	target	target	NOUN
fcis-9900	181	9	detection	detection	NOUN
fcis-9900	181	10	are	be	AUX
fcis-9900	181	11	introduced	introduce	VERB
fcis-9900	181	12	.	.	PUNCT
fcis-9900	182	1	finally	finally	ADV
fcis-9900	182	2	,	,	PUNCT
fcis-9900	182	3	optimization	optimization	NOUN
fcis-9900	182	4	methods	method	NOUN
fcis-9900	182	5	for	for	ADP
fcis-9900	182	6	small	small	ADJ
fcis-9900	182	7	target	target	NOUN
fcis-9900	182	8	detection	detection	NOUN
fcis-9900	182	9	are	be	AUX
fcis-9900	182	10	described	describe	VERB
fcis-9900	182	11	,	,	PUNCT
fcis-9900	182	12	and	and	CCONJ
fcis-9900	182	13	several	several	ADJ
fcis-9900	182	14	classical	classical	ADJ
fcis-9900	182	15	optimization	optimization	NOUN
fcis-9900	182	16	methods	method	NOUN
fcis-9900	182	17	for	for	ADP
fcis-9900	182	18	small	small	ADJ
fcis-9900	182	19	target	target	NOUN
fcis-9900	182	20	detection	detection	NOUN
fcis-9900	182	21	are	be	AUX
fcis-9900	182	22	selected	select	VERB
fcis-9900	182	23	and	and	CCONJ
fcis-9900	182	24	elaborated	elaborate	VERB
fcis-9900	182	25	.	.	PUNCT
fcis-9900	183	1	the	the	DET
fcis-9900	183	2	current	current	ADJ
fcis-9900	183	3	network	network	NOUN
fcis-9900	183	4	model	model	NOUN
fcis-9900	183	5	still	still	ADV
fcis-9900	183	6	has	have	VERB
fcis-9900	183	7	a	a	DET
fcis-9900	183	8	complex	complex	ADJ
fcis-9900	183	9	network	network	NOUN
fcis-9900	183	10	structure	structure	NOUN
fcis-9900	183	11	model	model	NOUN
fcis-9900	183	12	and	and	CCONJ
fcis-9900	183	13	too	too	ADV
fcis-9900	183	14	many	many	ADJ
fcis-9900	183	15	parameters	parameter	NOUN
fcis-9900	183	16	of	of	ADP
fcis-9900	183	17	the	the	DET
fcis-9900	183	18	network	network	NOUN
fcis-9900	183	19	model	model	NOUN
fcis-9900	183	20	,	,	PUNCT
fcis-9900	183	21	which	which	PRON
fcis-9900	183	22	are	be	AUX
fcis-9900	183	23	difficult	difficult	ADJ
fcis-9900	183	24	to	to	PART
fcis-9900	183	25	deploy	deploy	VERB
fcis-9900	183	26	.	.	PUNCT
fcis-9900	184	1	the	the	DET
fcis-9900	184	2	detection	detection	NOUN
fcis-9900	184	3	accuracy	accuracy	NOUN
fcis-9900	184	4	for	for	ADP
fcis-9900	184	5	small	small	ADJ
fcis-9900	184	6	targets	target	NOUN
fcis-9900	184	7	is	be	AUX
fcis-9900	184	8	low	low	ADJ
fcis-9900	184	9	,	,	PUNCT
fcis-9900	184	10	so	so	SCONJ
fcis-9900	184	11	it	it	PRON
fcis-9900	184	12	still	still	ADV
fcis-9900	184	13	needs	need	VERB
fcis-9900	184	14	a	a	DET
fcis-9900	184	15	long	long	ADJ
fcis-9900	184	16	time	time	NOUN
fcis-9900	184	17	of	of	ADP
fcis-9900	184	18	development	development	NOUN
fcis-9900	184	19	and	and	CCONJ
fcis-9900	184	20	research	research	NOUN
fcis-9900	184	21	to	to	PART
fcis-9900	184	22	improve	improve	VERB
fcis-9900	184	23	the	the	DET
fcis-9900	184	24	small	small	ADJ
fcis-9900	184	25	target	target	NOUN
fcis-9900	184	26	detection	detection	NOUN
fcis-9900	184	27	technology	technology	NOUN
fcis-9900	184	28	.	.	PUNCT
fcis-9900	185	1	for	for	ADP
fcis-9900	185	2	data	data	NOUN
fcis-9900	185	3	enhancement	enhancement	NOUN
fcis-9900	185	4	methods	method	NOUN
fcis-9900	185	5	,	,	PUNCT
fcis-9900	185	6	first	first	ADV
fcis-9900	185	7	of	of	ADP
fcis-9900	185	8	all	all	PRON
fcis-9900	185	9	,	,	PUNCT
fcis-9900	185	10	when	when	SCONJ
fcis-9900	185	11	data	datum	NOUN
fcis-9900	185	12	enhancement	enhancement	NOUN
fcis-9900	185	13	also	also	ADV
fcis-9900	185	14	has	have	VERB
fcis-9900	185	15	to	to	PART
fcis-9900	185	16	consider	consider	VERB
fcis-9900	185	17	whether	whether	SCONJ
fcis-9900	185	18	the	the	DET
fcis-9900	185	19	problem	problem	NOUN
fcis-9900	185	20	of	of	ADP
fcis-9900	185	21	introduced	introduce	VERB
fcis-9900	185	22	noise	noise	NOUN
fcis-9900	185	23	points	point	NOUN
fcis-9900	185	24	will	will	AUX
fcis-9900	185	25	affect	affect	VERB
fcis-9900	185	26	the	the	DET
fcis-9900	185	27	learning	learning	NOUN
fcis-9900	185	28	of	of	ADP
fcis-9900	185	29	small	small	ADJ
fcis-9900	185	30	target	target	NOUN
fcis-9900	185	31	features	feature	NOUN
fcis-9900	185	32	by	by	ADP
fcis-9900	185	33	neural	neural	ADJ
fcis-9900	185	34	networks	network	NOUN
fcis-9900	185	35	and	and	CCONJ
fcis-9900	185	36	other	other	ADJ
fcis-9900	185	37	issues	issue	NOUN
fcis-9900	185	38	.	.	PUNCT
fcis-9900	186	1	second	second	ADJ
fcis-9900	186	2	is	be	AUX
fcis-9900	186	3	also	also	ADV
fcis-9900	186	4	to	to	PART
fcis-9900	186	5	consider	consider	VERB
fcis-9900	186	6	the	the	DET
fcis-9900	186	7	network	network	NOUN
fcis-9900	186	8	structure	structure	NOUN
fcis-9900	186	9	of	of	ADP
fcis-9900	186	10	different	different	ADJ
fcis-9900	186	11	networks	network	NOUN
fcis-9900	186	12	combined	combine	VERB
fcis-9900	186	13	to	to	PART
fcis-9900	186	14	improve	improve	VERB
fcis-9900	186	15	the	the	DET
fcis-9900	186	16	detection	detection	NOUN
fcis-9900	186	17	accuracy	accuracy	NOUN
fcis-9900	186	18	of	of	ADP
fcis-9900	186	19	small	small	ADJ
fcis-9900	186	20	targets	target	NOUN
fcis-9900	186	21	,	,	PUNCT
fcis-9900	186	22	super	super	ADJ
fcis-9900	186	23	-	-	ADJ
fcis-9900	186	24	resolution	resolution	ADJ
fcis-9900	186	25	reconstruction	reconstruction	NOUN
fcis-9900	186	26	is	be	AUX
fcis-9900	186	27	one	one	NUM
fcis-9900	186	28	of	of	ADP
fcis-9900	186	29	the	the	DET
fcis-9900	186	30	most	most	ADV
fcis-9900	186	31	direct	direct	ADJ
fcis-9900	186	32	and	and	CCONJ
fcis-9900	186	33	interpretable	interpretable	ADJ
fcis-9900	186	34	methods	method	NOUN
fcis-9900	186	35	to	to	PART
fcis-9900	186	36	improve	improve	VERB
fcis-9900	186	37	the	the	DET
fcis-9900	186	38	performance	performance	NOUN
fcis-9900	186	39	of	of	ADP
fcis-9900	186	40	small	small	ADJ
fcis-9900	186	41	target	target	NOUN
fcis-9900	186	42	detection	detection	NOUN
fcis-9900	186	43	.	.	PUNCT
fcis-9900	187	1	a	a	DET
fcis-9900	187	2	feasible	feasible	ADJ
fcis-9900	187	3	future	future	ADJ
fcis-9900	187	4	research	research	NOUN
fcis-9900	187	5	idea	idea	NOUN
fcis-9900	187	6	is	be	AUX
fcis-9900	187	7	to	to	PART
fcis-9900	187	8	deeply	deeply	ADV
fcis-9900	187	9	combine	combine	VERB
fcis-9900	187	10	the	the	DET
fcis-9900	187	11	advanced	advanced	ADJ
fcis-9900	187	12	technology	technology	NOUN
fcis-9900	187	13	of	of	ADP
fcis-9900	187	14	super	super	ADJ
fcis-9900	187	15	-	-	ADJ
fcis-9900	187	16	resolution	resolution	ADJ
fcis-9900	187	17	reconstruction	reconstruction	NOUN
fcis-9900	187	18	with	with	ADP
fcis-9900	187	19	target	target	NOUN
fcis-9900	187	20	detection	detection	NOUN
fcis-9900	187	21	technology	technology	NOUN
fcis-9900	187	22	.	.	PUNCT
fcis-9900	188	1	lastly	lastly	ADV
fcis-9900	188	2	,	,	PUNCT
fcis-9900	188	3	it	it	PRON
fcis-9900	188	4	is	be	AUX
fcis-9900	188	5	important	important	ADJ
fcis-9900	188	6	to	to	PART
fcis-9900	188	7	improve	improve	VERB
fcis-9900	188	8	the	the	DET
fcis-9900	188	9	small	small	ADJ
fcis-9900	188	10	target	target	NOUN
fcis-9900	188	11	data	datum	NOUN
fcis-9900	188	12	set	set	VERB
fcis-9900	188	13	as	as	ADV
fcis-9900	188	14	much	much	ADV
fcis-9900	188	15	as	as	ADP
fcis-9900	188	16	possible	possible	ADJ
fcis-9900	188	17	,	,	PUNCT
fcis-9900	188	18	because	because	SCONJ
fcis-9900	188	19	data	datum	NOUN
fcis-9900	188	20	enhancement	enhancement	NOUN
fcis-9900	188	21	also	also	ADV
fcis-9900	188	22	has	have	VERB
fcis-9900	188	23	certain	certain	ADJ
fcis-9900	188	24	limitations	limitation	NOUN
fcis-9900	188	25	,	,	PUNCT
fcis-9900	188	26	and	and	CCONJ
fcis-9900	188	27	only	only	ADV
fcis-9900	188	28	enough	enough	ADJ
fcis-9900	188	29	data	datum	NOUN
fcis-9900	188	30	is	be	AUX
fcis-9900	188	31	an	an	DET
fcis-9900	188	32	important	important	ADJ
fcis-9900	188	33	cornerstone	cornerstone	NOUN
fcis-9900	188	34	to	to	PART
fcis-9900	188	35	improve	improve	VERB
fcis-9900	188	36	the	the	DET
fcis-9900	188	37	small	small	ADJ
fcis-9900	188	38	target	target	NOUN
fcis-9900	188	39	detection	detection	NOUN
fcis-9900	188	40	accuracy	accuracy	NOUN
fcis-9900	188	41	.	.	PUNCT
fcis-9900	189	1	references	reference	NOUN
fcis-9900	189	2	[	[	X
fcis-9900	189	3	1	1	NUM
fcis-9900	189	4	]	]	PUNCT
fcis-9900	189	5	chen	chen	PROPN
fcis-9900	189	6	c	c	PROPN
fcis-9900	189	7	,	,	PUNCT
fcis-9900	189	8	liu	liu	PROPN
fcis-9900	189	9	m	m	PROPN
fcis-9900	189	10	y	y	PROPN
fcis-9900	189	11	,	,	PUNCT
fcis-9900	189	12	tuzel	tuzel	ADJ
fcis-9900	189	13	o	o	NOUN
fcis-9900	189	14	,	,	PUNCT
fcis-9900	189	15	et	et	PROPN
fcis-9900	189	16	al	al	PROPN
fcis-9900	189	17	.	.	PUNCT
fcis-9900	190	1	r	r	X
fcis-9900	190	2	-	-	PUNCT
fcis-9900	190	3	cnn	cnn	PROPN
fcis-9900	190	4	for	for	ADP
fcis-9900	190	5	small	small	ADJ
fcis-9900	190	6	object	object	NOUN
fcis-9900	190	7	detection[c]//proceeding	detection[c]//proceeding	PROPN
fcis-9900	190	8	of	of	ADP
fcis-9900	190	9	asian	asian	ADJ
fcis-9900	190	10	conference	conference	NOUN
fcis-9900	190	11	on	on	ADP
fcis-9900	190	12	computer	computer	NOUN
fcis-9900	190	13	vision	vision	NOUN
fcis-9900	190	14	.	.	PUNCT
fcis-9900	191	1	cham	cham	PROPN
fcis-9900	191	2	:	:	PUNCT
fcis-9900	191	3	springer	springer	NOUN
fcis-9900	191	4	,	,	PUNCT
fcis-9900	191	5	2016	2016	NUM
fcis-9900	191	6	:	:	PUNCT
fcis-9900	191	7	214	214	NUM
fcis-9900	191	8	-	-	SYM
fcis-9900	191	9	230	230	NUM
fcis-9900	191	10	.	.	PUNCT
fcis-9900	192	1	[	[	X
fcis-9900	192	2	2	2	NUM
fcis-9900	192	3	]	]	PUNCT
fcis-9900	192	4	lin	lin	PROPN
fcis-9900	192	5	t	t	PROPN
fcis-9900	192	6	y	y	PROPN
fcis-9900	192	7	,	,	PUNCT
fcis-9900	192	8	maire	maire	VERB
fcis-9900	192	9	m	m	PROPN
fcis-9900	192	10	,	,	PUNCT
fcis-9900	192	11	belongie	belongie	PROPN
fcis-9900	192	12	s	s	PROPN
fcis-9900	192	13	,	,	PUNCT
fcis-9900	192	14	et	et	PROPN
fcis-9900	192	15	al	al	PROPN
fcis-9900	192	16	.	.	PROPN
fcis-9900	193	1	microsoft	microsoft	PROPN
fcis-9900	193	2	coco	coco	PROPN
fcis-9900	193	3	:	:	PUNCT
fcis-9900	193	4	common	common	ADJ
fcis-9900	193	5	objects	object	NOUN
fcis-9900	193	6	in	in	ADP
fcis-9900	193	7	context[c]//proceedings	context[c]//proceeding	NOUN
fcis-9900	193	8	of	of	ADP
fcis-9900	193	9	european	european	ADJ
fcis-9900	193	10	conference	conference	NOUN
fcis-9900	193	11	on	on	ADP
fcis-9900	193	12	computer	computer	NOUN
fcis-9900	193	13	vision	vision	NOUN
fcis-9900	193	14	.	.	PUNCT
fcis-9900	194	1	cham	cham	PROPN
fcis-9900	194	2	:	:	PUNCT
fcis-9900	194	3	springer	springer	NOUN
fcis-9900	194	4	,	,	PUNCT
fcis-9900	194	5	2014	2014	NUM
fcis-9900	194	6	:	:	PUNCT
fcis-9900	194	7	740	740	NUM
fcis-9900	194	8	-	-	SYM
fcis-9900	194	9	755	755	NUM
fcis-9900	194	10	.	.	PUNCT
fcis-9900	195	1	[	[	X
fcis-9900	195	2	3	3	NUM
fcis-9900	195	3	]	]	X
fcis-9900	195	4	yaeger	yaeger	PROPN
fcis-9900	195	5	l	l	PROPN
fcis-9900	195	6	,	,	PUNCT
fcis-9900	195	7	lyon	lyon	PROPN
fcis-9900	195	8	r	r	PROPN
fcis-9900	195	9	,	,	PUNCT
fcis-9900	195	10	webb	webb	PROPN
fcis-9900	195	11	b.effective	b.effective	ADJ
fcis-9900	195	12	training	training	NOUN
fcis-9900	195	13	of	of	ADP
fcis-9900	195	14	a	a	DET
fcis-9900	195	15	neural	neural	ADJ
fcis-9900	195	16	network	network	NOUN
fcis-9900	195	17	character	character	NOUN
fcis-9900	195	18	classifier	classifier	NOUN
fcis-9900	195	19	for	for	ADP
fcis-9900	195	20	word	word	NOUN
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fcis-9900	195	22	in	in	ADP
fcis-9900	195	23	neural	neural	ADJ
fcis-9900	195	24	information	information	NOUN
fcis-9900	195	25	processing	process	VERB
fcis-9900	195	26	systems,1996,9	systems,1996,9	PROPN
fcis-9900	195	27	:	:	PUNCT
fcis-9900	195	28	807	807	NUM
fcis-9900	195	29	-	-	SYM
fcis-9900	195	30	816	816	NUM
fcis-9900	195	31	.	.	PUNCT
fcis-9900	196	1	[	[	X
fcis-9900	196	2	4	4	NUM
fcis-9900	196	3	]	]	X
fcis-9900	196	4	wei	wei	PROPN
fcis-9900	196	5	wei	wei	PROPN
fcis-9900	196	6	,	,	PUNCT
fcis-9900	196	7	pu	pu	PROPN
fcis-9900	196	8	wei	wei	PROPN
fcis-9900	196	9	,	,	PUNCT
fcis-9900	196	10	liu	liu	PROPN
fcis-9900	196	11	yi	yi	PROPN
fcis-9900	196	12	.	.	PUNCT
fcis-9900	197	1	improvement	improvement	NOUN
fcis-9900	197	2	of	of	ADP
fcis-9900	197	3	yolov3	yolov3	PROPN
fcis-9900	197	4	in	in	ADP
fcis-9900	197	5	aerial	aerial	ADJ
fcis-9900	197	6	target	target	NOUN
fcis-9900	197	7	detection	detection	NOUN
fcis-9900	198	1	[	[	X
fcis-9900	198	2	j	j	X
fcis-9900	198	3	]	]	X
fcis-9900	198	4	.	.	PUNCT
fcis-9900	199	1	computer	computer	NOUN
fcis-9900	199	2	engineering	engineering	NOUN
fcis-9900	199	3	and	and	CCONJ
fcis-9900	199	4	applications	application	NOUN
fcis-9900	199	5	,	,	PUNCT
fcis-9900	199	6	2020	2020	NUM
fcis-9900	199	7	,	,	PUNCT
fcis-9900	199	8	56(7	56(7	NUM
fcis-9900	199	9	):	):	PUNCT
fcis-9900	199	10	17	17	NUM
fcis-9900	199	11	-	-	SYM
fcis-9900	199	12	23	23	NUM
fcis-9900	199	13	.	.	PUNCT
fcis-9900	200	1	[	[	X
fcis-9900	200	2	5	5	NUM
fcis-9900	200	3	]	]	PUNCT
fcis-9900	200	4	wang	wang	PROPN
fcis-9900	200	5	dongli	dongli	PROPN
fcis-9900	200	6	,	,	PUNCT
fcis-9900	200	7	liao	liao	PROPN
fcis-9900	200	8	chunjiang	chunjiang	PROPN
fcis-9900	200	9	,	,	PUNCT
fcis-9900	200	10	mou	mou	PROPN
fcis-9900	200	11	jinzhen	jinzhen	PROPN
fcis-9900	200	12	,	,	PUNCT
fcis-9900	200	13	et	et	PROPN
fcis-9900	200	14	al	al	PROPN
fcis-9900	200	15	.	.	PROPN
fcis-9900	201	1	feature	feature	NOUN
fcis-9900	201	2	fusion	fusion	NOUN
fcis-9900	201	3	-	-	PUNCT
fcis-9900	201	4	based	base	VERB
fcis-9900	201	5	small	small	ADJ
fcis-9900	201	6	target	target	NOUN
fcis-9900	201	7	detection	detection	NOUN
fcis-9900	201	8	for	for	ADP
fcis-9900	201	9	ssd	ssd	NOUN
fcis-9900	201	10	vision	vision	NOUN
fcis-9900	202	1	[	[	X
fcis-9900	202	2	j	j	X
fcis-9900	202	3	]	]	X
fcis-9900	202	4	.	.	PUNCT
fcis-9900	203	1	computer	computer	NOUN
fcis-9900	203	2	engineering	engineering	NOUN
fcis-9900	203	3	and	and	CCONJ
fcis-9900	203	4	applications	application	NOUN
fcis-9900	203	5	,	,	PUNCT
fcis-9900	203	6	2020	2020	NUM
fcis-9900	203	7	,	,	PUNCT
fcis-9900	203	8	56(16	56(16	NUM
fcis-9900	203	9	):	):	PUNCT
fcis-9900	203	10	31	31	NUM
fcis-9900	203	11	-	-	SYM
fcis-9900	203	12	36	36	NUM
fcis-9900	203	13	.	.	PUNCT
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fcis-9900	204	2	6	6	NUM
fcis-9900	204	3	]	]	PUNCT
fcis-9900	204	4	xing	xing	PROPN
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fcis-9900	204	6	,	,	PUNCT
fcis-9900	204	7	liang	liang	PROPN
fcis-9900	204	8	x	x	PROPN
fcis-9900	204	9	,	,	PUNCT
fcis-9900	204	10	bao	bao	PROPN
fcis-9900	204	11	z.a	z.a	PROPN
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fcis-9900	204	13	object	object	NOUN
fcis-9900	204	14	detection	detection	NOUN
fcis-9900	204	15	solution	solution	NOUN
fcis-9900	204	16	by	by	ADP
fcis-9900	204	17	using	use	VERB
fcis-9900	204	18	super	super	NOUN
fcis-9900	204	19	-	-	NOUN
fcis-9900	204	20	resolution	resolution	NOUN
fcis-9900	204	21	recovery[c]//2019	recovery[c]//2019	NUM
fcis-9900	204	22	ieee	ieee	NOUN
fcis-9900	204	23	7th	7th	ADJ
fcis-9900	204	24	international	international	ADJ
fcis-9900	204	25	conference	conference	NOUN
fcis-9900	204	26	on	on	ADP
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fcis-9900	204	28	science	science	NOUN
fcis-9900	204	29	and	and	CCONJ
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fcis-9900	204	31	technology(iccsnt),2019:313	technology(iccsnt),2019:313	PROPN
fcis-9900	204	32	-	-	PUNCT
fcis-9900	204	33	316	316	NUM
fcis-9900	204	34	.	.	PUNCT
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fcis-9900	205	2	7	7	X
fcis-9900	205	3	]	]	X
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fcis-9900	205	6	.	.	PROPN
fcis-9900	205	7	,	,	PUNCT
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fcis-9900	206	3	,	,	PUNCT
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fcis-9900	206	5	l.	l.	PROPN
fcis-9900	206	6	a	a	DET
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fcis-9900	206	12	incorporating	incorporate	VERB
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fcis-9900	207	1	[	[	X
fcis-9900	207	2	j	j	X
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fcis-9900	207	6	.	.	PUNCT
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fcis-9900	208	4	exploration	exploration	NOUN
fcis-9900	208	5	[	[	X
fcis-9900	208	6	2021	2021	NUM
fcis-9900	208	7	-	-	SYM
fcis-9900	208	8	10	10	NUM
fcis-9900	208	9	-	-	NUM
fcis-9900	208	10	18	18	NUM
fcis-9900	208	11	]	]	PUNCT
fcis-9900	208	12	.	.	PUNCT
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fcis-9900	209	2	8	8	NUM
fcis-9900	209	3	]	]	X
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fcis-9900	209	5	s	s	PROPN
fcis-9900	209	6	,	,	PUNCT
fcis-9900	209	7	hwang	hwang	PROPN
fcis-9900	209	8	s	s	PROPN
fcis-9900	209	9	,	,	PUNCT
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fcis-9900	209	11	i	i	PROPN
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fcis-9900	209	16	-	-	PUNCT
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fcis-9900	209	19	aggregation	aggregation	NOUN
fcis-9900	209	20	for	for	ADP
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fcis-9900	209	22	one	one	NUM
fcis-9900	209	23	-	-	PUNCT
fcis-9900	209	24	shot	shot	NOUN
fcis-9900	209	25	detection	detection	NOUN
fcis-9900	209	26	[	[	X
fcis-9900	209	27	c]//	c]//	ADJ
fcis-9900	209	28	proceedings	proceeding	NOUN
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fcis-9900	209	31	2018	2018	NUM
fcis-9900	209	32	ieee	ieee	NOUN
fcis-9900	209	33	winter	winter	NOUN
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fcis-9900	209	36	45	45	NUM
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fcis-9900	209	39	computer	computer	NOUN
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fcis-9900	209	41	,	,	PUNCT
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fcis-9900	209	49	,	,	PUNCT
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fcis-9900	210	4	,	,	PUNCT
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fcis-9900	210	6	-	-	SYM
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fcis-9900	211	7	,	,	PUNCT
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fcis-9900	211	13	algorithm	algorithm	NOUN
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fcis-9900	211	20	]	]	PUNCT
fcis-9900	211	21	.	.	PUNCT
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fcis-9900	212	2	science	science	NOUN
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fcis-9900	212	5	,	,	PUNCT
fcis-9900	212	6	2021	2021	NUM
fcis-9900	212	7	,	,	PUNCT
fcis-9900	212	8	15(12	15(12	NUM
fcis-9900	212	9	):	):	PUNCT
fcis-9900	212	10	2390	2390	NUM
fcis-9900	212	11	-	-	SYM
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fcis-9900	214	9	c]//	c]//	PROPN
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fcis-9900	219	27	//ieee	//ieee	PUNCT
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fcis-9900	220	6	pattern	pattern	NOUN
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fcis-9900	220	8	:	:	PUNCT
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fcis-9900	220	10	,	,	PUNCT
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fcis-9900	220	12	:	:	PUNCT
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fcis-9900	220	14	-	-	SYM
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fcis-9900	220	16	.	.	PUNCT
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fcis-9900	221	30	:	:	PUNCT
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fcis-9900	226	2	.	.	PUNCT
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fcis-9900	228	27	.	.	PUNCT
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fcis-9900	234	2	:	:	PUNCT
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fcis-9900	236	6	:	:	PUNCT
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fcis-9900	269	20	.	.	PUNCT
fcis-9900	270	1	[	[	X
fcis-9900	270	2	31	31	NUM
fcis-9900	270	3	]	]	X
fcis-9900	270	4	jie	jie	PROPN
fcis-9900	270	5	h	h	PROPN
fcis-9900	270	6	,	,	PUNCT
fcis-9900	270	7	li	li	PROPN
fcis-9900	270	8	s	s	PROPN
fcis-9900	270	9	,	,	PUNCT
fcis-9900	270	10	gang	gang	NOUN
fcis-9900	270	11	s	s	PROPN
fcis-9900	270	12	,	,	PUNCT
fcis-9900	270	13	et	et	PROPN
fcis-9900	270	14	al	al	PROPN
fcis-9900	270	15	.	.	PUNCT
fcis-9900	270	16	squeeze	squeeze	NOUN
fcis-9900	270	17	-	-	PUNCT
fcis-9900	270	18	and	and	CCONJ
fcis-9900	270	19	-	-	PUNCT
fcis-9900	270	20	excitation	excitation	NOUN
fcis-9900	270	21	networks[j	networks[j	PROPN
fcis-9900	270	22	]	]	X
fcis-9900	270	23	.	.	PUNCT
fcis-9900	271	1	ieee	ieee	NOUN
fcis-9900	271	2	transactions	transaction	NOUN
fcis-9900	271	3	on	on	ADP
fcis-9900	271	4	pattern	pattern	NOUN
fcis-9900	271	5	analysis	analysis	NOUN
fcis-9900	271	6	and	and	CCONJ
fcis-9900	271	7	machine	machine	NOUN
fcis-9900	271	8	intelligence	intelligence	NOUN
fcis-9900	271	9	,	,	PUNCT
fcis-9900	271	10	2017	2017	NUM
fcis-9900	271	11	,	,	PUNCT
fcis-9900	271	12	pp(99	pp(99	NOUN
fcis-9900	271	13	)	)	PUNCT
fcis-9900	271	14	.	.	PUNCT
fcis-9900	272	1	[	[	X
fcis-9900	272	2	32	32	NUM
fcis-9900	272	3	]	]	X
fcis-9900	272	4	li	li	PROPN
fcis-9900	272	5	y	y	PROPN
fcis-9900	272	6	,	,	PUNCT
fcis-9900	272	7	li	li	PROPN
fcis-9900	272	8	s	s	PROPN
fcis-9900	272	9	,	,	PUNCT
fcis-9900	272	10	du	du	PROPN
fcis-9900	272	11	h	h	PROPN
fcis-9900	272	12	,	,	PUNCT
fcis-9900	272	13	et	et	PROPN
fcis-9900	272	14	al	al	PROPN
fcis-9900	272	15	.	.	PROPN
fcis-9900	272	16	yoloacn	yoloacn	PROPN
fcis-9900	272	17	:	:	PUNCT
fcis-9900	272	18	focusing	focus	VERB
fcis-9900	272	19	on	on	ADP
fcis-9900	272	20	small	small	ADJ
fcis-9900	272	21	target	target	NOUN
fcis-9900	272	22	and	and	CCONJ
fcis-9900	272	23	occluded	occlude	VERB
fcis-9900	272	24	object	object	VERB
fcis-9900	272	25	detection[j	detection[j	PROPN
fcis-9900	272	26	]	]	PUNCT
fcis-9900	272	27	.	.	PUNCT
fcis-9900	273	1	ieee	ieee	NOUN
fcis-9900	273	2	access	access	NOUN
fcis-9900	273	3	,	,	PUNCT
fcis-9900	273	4	2020	2020	NUM
fcis-9900	273	5	,	,	PUNCT
fcis-9900	273	6	8	8	NUM
fcis-9900	273	7	:	:	SYM
fcis-9900	273	8	227288	227288	NUM
fcis-9900	273	9	-	-	SYM
fcis-9900	273	10	227303	227303	NUM
fcis-9900	273	11	.	.	PUNCT
fcis-9900	274	1	[	[	X
fcis-9900	274	2	33	33	NUM
fcis-9900	274	3	]	]	PUNCT
fcis-9900	274	4	pan	pan	PROPN
fcis-9900	274	5	h	h	PROPN
fcis-9900	274	6	,	,	PUNCT
fcis-9900	274	7	chen	chen	PROPN
fcis-9900	274	8	g	g	PROPN
fcis-9900	274	9	,	,	PUNCT
fcis-9900	274	10	jiang	jiang	PROPN
fcis-9900	274	11	j.	j.	PROPN
fcis-9900	274	12	adaptively	adaptively	ADV
fcis-9900	274	13	dense	dense	ADJ
fcis-9900	274	14	feature	feature	NOUN
fcis-9900	274	15	pyramid	pyramid	NOUN
fcis-9900	274	16	network	network	NOUN
fcis-9900	274	17	for	for	ADP
fcis-9900	274	18	object	object	NOUN
fcis-9900	274	19	detection[j	detection[j	PROPN
fcis-9900	274	20	]	]	PUNCT
fcis-9900	274	21	.	.	PUNCT
fcis-9900	275	1	ieee	ieee	NOUN
fcis-9900	275	2	access	access	NOUN
fcis-9900	275	3	,	,	PUNCT
fcis-9900	275	4	2019	2019	NUM
fcis-9900	275	5	,	,	PUNCT
fcis-9900	275	6	7	7	NUM
fcis-9900	275	7	:	:	SYM
fcis-9900	275	8	8113281144	8113281144	NUM
fcis-9900	275	9	.	.	PUNCT
fcis-9900	276	1	[	[	X
fcis-9900	276	2	34	34	NUM
fcis-9900	276	3	]	]	X
fcis-9900	276	4	zhu	zhu	PROPN
fcis-9900	276	5	g	g	PROPN
fcis-9900	276	6	,	,	PUNCT
fcis-9900	276	7	wei	wei	PROPN
fcis-9900	276	8	z	z	PROPN
fcis-9900	276	9	,	,	PUNCT
fcis-9900	276	10	lin	lin	PROPN
fcis-9900	276	11	f.	f.	PROPN
fcis-9900	276	12	an	an	DET
fcis-9900	276	13	object	object	NOUN
fcis-9900	276	14	detection	detection	NOUN
fcis-9900	276	15	method	method	NOUN
fcis-9900	276	16	combining	combine	VERB
fcis-9900	276	17	multi	multi	ADJ
fcis-9900	276	18	-	-	ADJ
fcis-9900	276	19	level	level	ADJ
fcis-9900	276	20	feature	feature	NOUN
fcis-9900	276	21	fusion	fusion	NOUN
fcis-9900	276	22	and	and	CCONJ
fcis-9900	276	23	region	region	NOUN
fcis-9900	276	24	channel	channel	PROPN
fcis-9900	276	25	attention[j	attention[j	PROPN
fcis-9900	276	26	]	]	PUNCT
fcis-9900	276	27	.	.	PUNCT
fcis-9900	277	1	ieee	ieee	NOUN
fcis-9900	277	2	access	access	NOUN
fcis-9900	277	3	,	,	PUNCT
fcis-9900	277	4	2021	2021	NUM
fcis-9900	277	5	,	,	PUNCT
fcis-9900	277	6	9	9	NUM
fcis-9900	277	7	:	:	SYM
fcis-9900	277	8	25101	25101	NUM
fcis-9900	277	9	-	-	SYM
fcis-9900	277	10	25109	25109	NUM
fcis-9900	277	11	.	.	PUNCT
fcis-9900	278	1	[	[	X
fcis-9900	278	2	35	35	NUM
fcis-9900	278	3	]	]	X
fcis-9900	278	4	shi	shi	PROPN
fcis-9900	278	5	w	w	PROPN
fcis-9900	278	6	,	,	PUNCT
fcis-9900	278	7	bao	bao	PROPN
fcis-9900	278	8	s	s	PROPN
fcis-9900	278	9	,	,	PUNCT
fcis-9900	278	10	tan	tan	PROPN
fcis-9900	278	11	d.	d.	PROPN
fcis-9900	278	12	ffessd	ffessd	PROPN
fcis-9900	278	13	:	:	PUNCT
fcis-9900	278	14	an	an	DET
fcis-9900	278	15	accurate	accurate	ADJ
fcis-9900	278	16	and	and	CCONJ
fcis-9900	278	17	efficient	efficient	ADJ
fcis-9900	278	18	single	single	ADJ
fcis-9900	278	19	-	-	PUNCT
fcis-9900	278	20	shot	shot	NOUN
fcis-9900	278	21	detector	detector	NOUN
fcis-9900	278	22	for	for	ADP
fcis-9900	278	23	target	target	NOUN
fcis-9900	278	24	detection[j	detection[j	PROPN
fcis-9900	278	25	]	]	PUNCT
fcis-9900	278	26	.	.	PUNCT
fcis-9900	279	1	applied	apply	VERB
fcis-9900	279	2	sciences	science	NOUN
fcis-9900	279	3	,	,	PUNCT
fcis-9900	279	4	2019	2019	NUM
fcis-9900	279	5	,	,	PUNCT
fcis-9900	279	6	9(20	9(20	NUM
fcis-9900	279	7	):	):	PUNCT
fcis-9900	279	8	4276	4276	NUM
fcis-9900	279	9	.	.	PUNCT
fcis-9900	280	1	[	[	X
fcis-9900	280	2	36	36	NUM
fcis-9900	280	3	]	]	X
fcis-9900	280	4	woo	woo	PROPN
fcis-9900	280	5	s	s	PROPN
fcis-9900	280	6	,	,	PUNCT
fcis-9900	280	7	hwang	hwang	PROPN
fcis-9900	280	8	s	s	PROPN
fcis-9900	280	9	,	,	PUNCT
fcis-9900	280	10	kweon	kweon	PROPN
fcis-9900	280	11	i	i	PROPN
fcis-9900	280	12	s.	s.	PROPN
fcis-9900	280	13	stairnet	stairnet	PROPN
fcis-9900	280	14	:	:	PUNCT
fcis-9900	280	15	top	top	ADJ
fcis-9900	280	16	-	-	PUNCT
fcis-9900	280	17	down	down	ADP
fcis-9900	280	18	segmantic	segmantic	ADJ
fcis-9900	280	19	aggregation	aggregation	NOUN
fcis-9900	280	20	for	for	ADP
fcis-9900	280	21	accurate	accurate	ADJ
fcis-9900	280	22	one	one	NUM
fcis-9900	280	23	-	-	PUNCT
fcis-9900	280	24	shot	shot	NOUN
fcis-9900	280	25	detection[c]//	detection[c]//	PROPN
fcis-9900	280	26	proceedings	proceeding	NOUN
fcis-9900	280	27	of	of	ADP
fcis-9900	280	28	the	the	DET
fcis-9900	280	29	2018	2018	NUM
fcis-9900	280	30	ieee	ieee	NOUN
fcis-9900	280	31	winter	winter	NOUN
fcis-9900	280	32	conference	conference	NOUN
fcis-9900	280	33	on	on	ADP
fcis-9900	280	34	applications	application	NOUN
fcis-9900	280	35	of	of	ADP
fcis-9900	280	36	computer	computer	NOUN
fcis-9900	280	37	vision	vision	NOUN
fcis-9900	280	38	,	,	PUNCT
fcis-9900	280	39	lake	lake	PROPN
fcis-9900	280	40	tahoe	tahoe	PROPN
fcis-9900	280	41	,	,	PUNCT
fcis-9900	280	42	mar	mar	PROPN
fcis-9900	280	43	12	12	NUM
fcis-9900	280	44	-	-	SYM
fcis-9900	280	45	15	15	NUM
fcis-9900	280	46	,	,	PUNCT
fcis-9900	280	47	2018	2018	NUM
fcis-9900	280	48	.	.	PUNCT
fcis-9900	281	1	piscataway	piscataway	NOUN
fcis-9900	281	2	:	:	PUNCT
fcis-9900	281	3	ieee	ieee	NOUN
fcis-9900	281	4	,	,	PUNCT
fcis-9900	281	5	2018:1093	2018:1093	NUM
fcis-9900	281	6	-	-	SYM
fcis-9900	281	7	1102	1102	NUM
fcis-9900	281	8	.	.	PUNCT
fcis-9900	282	1	[	[	X
fcis-9900	282	2	37	37	NUM
fcis-9900	282	3	]	]	X
fcis-9900	282	4	tang	tang	X
fcis-9900	282	5	x	x	X
fcis-9900	282	6	,	,	PUNCT
fcis-9900	282	7	du	du	PROPN
fcis-9900	282	8	d	d	PROPN
fcis-9900	282	9	k	k	PROPN
fcis-9900	282	10	,	,	PUNCT
fcis-9900	282	11	he	he	PRON
fcis-9900	282	12	z	z	X
fcis-9900	282	13	,	,	PUNCT
fcis-9900	282	14	et	et	PROPN
fcis-9900	282	15	al	al	PROPN
fcis-9900	282	16	.	.	PROPN
fcis-9900	282	17	pyramidbox	pyramidbox	PROPN
fcis-9900	282	18	:	:	PUNCT
fcis-9900	282	19	a	a	DET
fcis-9900	282	20	context	context	NOUN
fcis-9900	282	21	assisted	assist	VERB
fcis-9900	282	22	single	single	ADJ
fcis-9900	282	23	shot	shot	NOUN
fcis-9900	282	24	face	face	NOUN
fcis-9900	282	25	detector	detector	NOUN
fcis-9900	282	26	[	[	X
fcis-9900	282	27	c]//	c]//	PROPN
fcis-9900	282	28	european	european	ADJ
fcis-9900	282	29	conference	conference	NOUN
fcis-9900	282	30	on	on	ADP
fcis-9900	282	31	computer	computer	NOUN
fcis-9900	282	32	vision	vision	NOUN
fcis-9900	282	33	.	.	PUNCT
fcis-9900	283	1	zurich	zurich	PROPN
fcis-9900	283	2	:	:	PUNCT
fcis-9900	283	3	ecva,2018	ecva,2018	NOUN
fcis-9900	283	4	:	:	PUNCT
fcis-9900	283	5	812	812	NUM
fcis-9900	283	6	-	-	SYM
fcis-9900	283	7	828	828	NUM
fcis-9900	283	8	.	.	PUNCT
fcis-9900	284	1	[	[	X
fcis-9900	284	2	38	38	NUM
fcis-9900	284	3	]	]	PUNCT
fcis-9900	284	4	hu	hu	PROPN
fcis-9900	284	5	h	h	PROPN
fcis-9900	284	6	,	,	PUNCT
fcis-9900	284	7	gu	gu	PROPN
fcis-9900	284	8	j	j	PROPN
fcis-9900	284	9	,	,	PUNCT
fcis-9900	284	10	zhang	zhang	PROPN
fcis-9900	284	11	z	z	PROPN
fcis-9900	284	12	,	,	PUNCT
fcis-9900	284	13	et	et	NOUN
fcis-9900	284	14	al.relation	al.relation	NOUN
fcis-9900	284	15	networks	network	NOUN
fcis-9900	284	16	for	for	ADP
fcis-9900	284	17	object	object	NOUN
fcis-9900	284	18	detection	detection	NOUN
fcis-9900	284	19	[	[	X
fcis-9900	284	20	c	c	X
fcis-9900	284	21	]	]	X
fcis-9900	284	22	//	//	PUNCT
fcis-9900	284	23	ieee	ieee	PROPN
fcis-9900	284	24	conference	conference	NOUN
fcis-9900	284	25	on	on	ADP
fcis-9900	284	26	computer	computer	NOUN
fcis-9900	284	27	vision	vision	NOUN
fcis-9900	284	28	and	and	CCONJ
fcis-9900	284	29	pattern	pattern	NOUN
fcis-9900	284	30	recognition	recognition	NOUN
fcis-9900	284	31	.	.	PUNCT
fcis-9900	285	1	piscataway	piscataway	PROPN
fcis-9900	285	2	:	:	PUNCT
fcis-9900	286	1	ieee,2018	ieee,2018	NOUN
fcis-9900	286	2	:	:	PUNCT
fcis-9900	286	3	3588	3588	NUM
fcis-9900	286	4	-	-	SYM
fcis-9900	286	5	3597	3597	NUM
fcis-9900	286	6	.	.	PUNCT