id	sid	tid	token	lemma	pos
ajst-322	1	1	academic	academic	ADJ
ajst-322	1	2	journal	journal	NOUN
ajst-322	1	3	of	of	ADP
ajst-322	1	4	science	science	NOUN
ajst-322	1	5	and	and	CCONJ
ajst-322	1	6	technology	technology	NOUN
ajst-322	1	7	issn	issn	NOUN
ajst-322	1	8	:	:	PUNCT
ajst-322	1	9	2771	2771	NUM
ajst-322	1	10	-	-	SYM
ajst-322	1	11	3032	3032	NUM
ajst-322	1	12	|	|	NOUN
ajst-322	1	13	vol	vol	NOUN
ajst-322	1	14	.	.	PROPN
ajst-322	2	1	1	1	NUM
ajst-322	2	2	,	,	PUNCT
ajst-322	2	3	no	no	INTJ
ajst-322	2	4	.	.	NOUN
ajst-322	2	5	2	2	NUM
ajst-322	2	6	,	,	PUNCT
ajst-322	2	7	2022	2022	NUM
ajst-322	2	8	60	60	NUM
ajst-322	2	9	object	object	NOUN
ajst-322	2	10	detection	detection	NOUN
ajst-322	2	11	method	method	NOUN
ajst-322	2	12	of	of	ADP
ajst-322	2	13	power	power	NOUN
ajst-322	2	14	equipment	equipment	NOUN
ajst-322	2	15	based	base	VERB
ajst-322	2	16	on	on	ADP
ajst-322	2	17	mask	mask	PROPN
ajst-322	3	1	r‐cnn	r‐cnn	PROPN
ajst-322	3	2	chen	chen	PROPN
ajst-322	3	3	wang	wang	PROPN
ajst-322	3	4	,	,	PUNCT
ajst-322	3	5	chunjiang	chunjiang	PROPN
ajst-322	3	6	pang	pang	PROPN
ajst-322	3	7	school	school	NOUN
ajst-322	3	8	of	of	ADP
ajst-322	3	9	control	control	NOUN
ajst-322	3	10	and	and	CCONJ
ajst-322	3	11	computer	computer	NOUN
ajst-322	3	12	engineering	engineering	NOUN
ajst-322	3	13	,	,	PUNCT
ajst-322	3	14	north	north	PROPN
ajst-322	3	15	china	china	PROPN
ajst-322	3	16	electric	electric	PROPN
ajst-322	3	17	power	power	PROPN
ajst-322	3	18	university	university	PROPN
ajst-322	3	19	,	,	PUNCT
ajst-322	3	20	hebei	hebei	PROPN
ajst-322	3	21	,	,	PUNCT
ajst-322	3	22	071000	071000	NUM
ajst-322	3	23	,	,	PUNCT
ajst-322	3	24	china	china	PROPN
ajst-322	3	25	abstract	abstract	PROPN
ajst-322	3	26	:	:	PUNCT
ajst-322	3	27	with	with	ADP
ajst-322	3	28	the	the	DET
ajst-322	3	29	rapid	rapid	ADJ
ajst-322	3	30	development	development	NOUN
ajst-322	3	31	of	of	ADP
ajst-322	3	32	deep	deep	ADJ
ajst-322	3	33	learning	learning	NOUN
ajst-322	3	34	technology	technology	NOUN
ajst-322	3	35	and	and	CCONJ
ajst-322	3	36	its	its	PRON
ajst-322	3	37	outstanding	outstanding	ADJ
ajst-322	3	38	performance	performance	NOUN
ajst-322	3	39	in	in	ADP
ajst-322	3	40	the	the	DET
ajst-322	3	41	field	field	NOUN
ajst-322	3	42	of	of	ADP
ajst-322	3	43	image	image	NOUN
ajst-322	3	44	,	,	PUNCT
ajst-322	3	45	more	more	ADJ
ajst-322	3	46	and	and	CCONJ
ajst-322	3	47	more	more	ADJ
ajst-322	3	48	researchers	researcher	NOUN
ajst-322	3	49	begin	begin	VERB
ajst-322	3	50	to	to	PART
ajst-322	3	51	pay	pay	VERB
ajst-322	3	52	attention	attention	NOUN
ajst-322	3	53	to	to	ADP
ajst-322	3	54	the	the	DET
ajst-322	3	55	application	application	NOUN
ajst-322	3	56	of	of	ADP
ajst-322	3	57	deep	deep	ADJ
ajst-322	3	58	learning	learning	NOUN
ajst-322	3	59	in	in	ADP
ajst-322	3	60	the	the	DET
ajst-322	3	61	field	field	NOUN
ajst-322	3	62	of	of	ADP
ajst-322	3	63	power	power	NOUN
ajst-322	3	64	industry	industry	NOUN
ajst-322	3	65	.	.	PUNCT
ajst-322	4	1	after	after	ADP
ajst-322	4	2	analyzing	analyze	VERB
ajst-322	4	3	the	the	DET
ajst-322	4	4	structure	structure	NOUN
ajst-322	4	5	of	of	ADP
ajst-322	4	6	mask	mask	NOUN
ajst-322	4	7	r	r	PROPN
ajst-322	4	8	-	-	PUNCT
ajst-322	4	9	cnn	cnn	PROPN
ajst-322	4	10	and	and	CCONJ
ajst-322	4	11	considering	consider	VERB
ajst-322	4	12	the	the	DET
ajst-322	4	13	particularity	particularity	NOUN
ajst-322	4	14	of	of	ADP
ajst-322	4	15	infrared	infrared	ADJ
ajst-322	4	16	image	image	NOUN
ajst-322	4	17	data	datum	NOUN
ajst-322	4	18	set	set	VERB
ajst-322	4	19	,	,	PUNCT
ajst-322	4	20	a	a	DET
ajst-322	4	21	new	new	ADJ
ajst-322	4	22	mask	mask	NOUN
ajst-322	4	23	r	r	NOUN
ajst-322	4	24	-	-	PUNCT
ajst-322	4	25	cnn	cnn	PROPN
ajst-322	4	26	model	model	NOUN
ajst-322	4	27	is	be	AUX
ajst-322	4	28	proposed	propose	VERB
ajst-322	4	29	.	.	PUNCT
ajst-322	5	1	channel	channel	NOUN
ajst-322	5	2	attention	attention	NOUN
ajst-322	5	3	mechanism	mechanism	NOUN
ajst-322	5	4	is	be	AUX
ajst-322	5	5	introduced	introduce	VERB
ajst-322	5	6	to	to	PART
ajst-322	5	7	make	make	VERB
ajst-322	5	8	the	the	DET
ajst-322	5	9	network	network	NOUN
ajst-322	5	10	learn	learn	VERB
ajst-322	5	11	the	the	DET
ajst-322	5	12	weight	weight	NOUN
ajst-322	5	13	coefficient	coefficient	NOUN
ajst-322	5	14	of	of	ADP
ajst-322	5	15	each	each	DET
ajst-322	5	16	channel	channel	NOUN
ajst-322	5	17	,	,	PUNCT
ajst-322	5	18	so	so	SCONJ
ajst-322	5	19	that	that	SCONJ
ajst-322	5	20	the	the	DET
ajst-322	5	21	network	network	NOUN
ajst-322	5	22	can	can	AUX
ajst-322	5	23	filter	filter	VERB
ajst-322	5	24	noise	noise	VERB
ajst-322	5	25	more	more	ADV
ajst-322	5	26	effectively	effectively	ADV
ajst-322	5	27	and	and	CCONJ
ajst-322	5	28	extract	extract	VERB
ajst-322	5	29	more	more	ADJ
ajst-322	5	30	information	information	NOUN
ajst-322	5	31	related	relate	VERB
ajst-322	5	32	to	to	ADP
ajst-322	5	33	the	the	DET
ajst-322	5	34	object	object	NOUN
ajst-322	5	35	.	.	PUNCT
ajst-322	6	1	experimental	experimental	ADJ
ajst-322	6	2	results	result	NOUN
ajst-322	6	3	show	show	VERB
ajst-322	6	4	that	that	SCONJ
ajst-322	6	5	the	the	DET
ajst-322	6	6	accuracy	accuracy	NOUN
ajst-322	6	7	of	of	ADP
ajst-322	6	8	the	the	DET
ajst-322	6	9	improved	improved	ADJ
ajst-322	6	10	model	model	NOUN
ajst-322	6	11	is	be	AUX
ajst-322	6	12	better	well	ADJ
ajst-322	6	13	than	than	ADP
ajst-322	6	14	that	that	PRON
ajst-322	6	15	of	of	ADP
ajst-322	6	16	the	the	DET
ajst-322	6	17	original	original	ADJ
ajst-322	6	18	model	model	NOUN
ajst-322	6	19	,	,	PUNCT
ajst-322	6	20	and	and	CCONJ
ajst-322	6	21	the	the	DET
ajst-322	6	22	effectiveness	effectiveness	NOUN
ajst-322	6	23	of	of	ADP
ajst-322	6	24	the	the	DET
ajst-322	6	25	improved	improve	VERB
ajst-322	6	26	method	method	NOUN
ajst-322	6	27	is	be	AUX
ajst-322	6	28	verified	verify	VERB
ajst-322	6	29	.	.	PUNCT
ajst-322	7	1	keywords	keyword	NOUN
ajst-322	7	2	:	:	PUNCT
ajst-322	7	3	power	power	NOUN
ajst-322	7	4	equipment	equipment	NOUN
ajst-322	7	5	,	,	PUNCT
ajst-322	7	6	object	object	NOUN
ajst-322	7	7	detection	detection	NOUN
ajst-322	7	8	,	,	PUNCT
ajst-322	7	9	mask	mask	NOUN
ajst-322	7	10	r	r	NOUN
ajst-322	7	11	-	-	PUNCT
ajst-322	7	12	cnn	cnn	NOUN
ajst-322	7	13	.	.	PUNCT
ajst-322	8	1	1	1	NUM
ajst-322	8	2	.	.	X
ajst-322	8	3	introduction	introduction	NOUN
ajst-322	8	4	in	in	ADP
ajst-322	8	5	recent	recent	ADJ
ajst-322	8	6	years	year	NOUN
ajst-322	8	7	,	,	PUNCT
ajst-322	8	8	with	with	ADP
ajst-322	8	9	the	the	DET
ajst-322	8	10	proposal	proposal	NOUN
ajst-322	8	11	and	and	CCONJ
ajst-322	8	12	development	development	NOUN
ajst-322	8	13	of	of	ADP
ajst-322	8	14	the	the	DET
ajst-322	8	15	concept	concept	NOUN
ajst-322	8	16	of	of	ADP
ajst-322	8	17	"	"	PUNCT
ajst-322	8	18	smart	smart	ADJ
ajst-322	8	19	grid	grid	NOUN
ajst-322	8	20	"	"	PUNCT
ajst-322	8	21	.	.	PUNCT
ajst-322	9	1	image	image	NOUN
ajst-322	9	2	processing	processing	NOUN
ajst-322	9	3	technology	technology	NOUN
ajst-322	9	4	has	have	AUX
ajst-322	9	5	been	be	AUX
ajst-322	9	6	more	more	ADV
ajst-322	9	7	and	and	CCONJ
ajst-322	9	8	more	more	ADV
ajst-322	9	9	widely	widely	ADV
ajst-322	9	10	used	use	VERB
ajst-322	9	11	in	in	ADP
ajst-322	9	12	power	power	NOUN
ajst-322	9	13	equipment	equipment	NOUN
ajst-322	9	14	fault	fault	NOUN
ajst-322	9	15	diagnosis	diagnosis	NOUN
ajst-322	9	16	.	.	PUNCT
ajst-322	10	1	it	it	PRON
ajst-322	10	2	is	be	AUX
ajst-322	10	3	the	the	DET
ajst-322	10	4	first	first	ADJ
ajst-322	10	5	step	step	NOUN
ajst-322	10	6	to	to	PART
ajst-322	10	7	realize	realize	VERB
ajst-322	10	8	intelligent	intelligent	ADJ
ajst-322	10	9	fault	fault	NOUN
ajst-322	10	10	detection	detection	NOUN
ajst-322	10	11	to	to	PART
ajst-322	10	12	identify	identify	VERB
ajst-322	10	13	,	,	PUNCT
ajst-322	10	14	locate	locate	VERB
ajst-322	10	15	and	and	CCONJ
ajst-322	10	16	classify	classify	VERB
ajst-322	10	17	power	power	NOUN
ajst-322	10	18	equipment	equipment	NOUN
ajst-322	10	19	accurately	accurately	ADV
ajst-322	10	20	.	.	PUNCT
ajst-322	11	1	this	this	DET
ajst-322	11	2	task	task	NOUN
ajst-322	11	3	can	can	AUX
ajst-322	11	4	be	be	AUX
ajst-322	11	5	accomplished	accomplish	VERB
ajst-322	11	6	by	by	ADP
ajst-322	11	7	extracting	extract	VERB
ajst-322	11	8	image	image	NOUN
ajst-322	11	9	features	feature	NOUN
ajst-322	11	10	.	.	PUNCT
ajst-322	12	1	in	in	ADP
ajst-322	12	2	chronological	chronological	ADJ
ajst-322	12	3	order	order	NOUN
ajst-322	12	4	,	,	PUNCT
ajst-322	12	5	it	it	PRON
ajst-322	12	6	can	can	AUX
ajst-322	12	7	be	be	AUX
ajst-322	12	8	divided	divide	VERB
ajst-322	12	9	into	into	ADP
ajst-322	12	10	traditional	traditional	ADJ
ajst-322	12	11	image	image	NOUN
ajst-322	12	12	processing	processing	NOUN
ajst-322	12	13	technology	technology	NOUN
ajst-322	12	14	of	of	ADP
ajst-322	12	15	artificial	artificial	ADJ
ajst-322	12	16	design	design	NOUN
ajst-322	12	17	features	feature	NOUN
ajst-322	12	18	and	and	CCONJ
ajst-322	12	19	feature	feature	NOUN
ajst-322	12	20	extraction	extraction	NOUN
ajst-322	12	21	technology	technology	NOUN
ajst-322	12	22	based	base	VERB
ajst-322	12	23	on	on	ADP
ajst-322	12	24	deep	deep	ADJ
ajst-322	12	25	learning	learning	NOUN
ajst-322	12	26	.	.	PUNCT
ajst-322	13	1	at	at	ADP
ajst-322	13	2	present	present	ADJ
ajst-322	13	3	,	,	PUNCT
ajst-322	13	4	object	object	NOUN
ajst-322	13	5	detection	detection	NOUN
ajst-322	13	6	technology	technology	NOUN
ajst-322	13	7	has	have	VERB
ajst-322	13	8	two	two	NUM
ajst-322	13	9	main	main	ADJ
ajst-322	13	10	development	development	NOUN
ajst-322	13	11	directions	direction	NOUN
ajst-322	13	12	:	:	PUNCT
ajst-322	13	13	object	object	VERB
ajst-322	13	14	detection	detection	NOUN
ajst-322	13	15	algorithm	algorithm	NOUN
ajst-322	13	16	based	base	VERB
ajst-322	13	17	on	on	ADP
ajst-322	13	18	candidate	candidate	NOUN
ajst-322	13	19	region	region	NOUN
ajst-322	13	20	and	and	CCONJ
ajst-322	13	21	object	object	VERB
ajst-322	13	22	detection	detection	NOUN
ajst-322	13	23	algorithm	algorithm	NOUN
ajst-322	13	24	based	base	VERB
ajst-322	13	25	on	on	ADP
ajst-322	13	26	regression	regression	NOUN
ajst-322	13	27	,	,	PUNCT
ajst-322	13	28	also	also	ADV
ajst-322	13	29	known	know	VERB
ajst-322	13	30	as	as	ADP
ajst-322	13	31	two	two	NUM
ajst-322	13	32	-	-	PUNCT
ajst-322	13	33	stage	stage	NOUN
ajst-322	13	34	and	and	CCONJ
ajst-322	13	35	one	one	NUM
ajst-322	13	36	-	-	PUNCT
ajst-322	13	37	stage	stage	NOUN
ajst-322	13	38	object	object	NOUN
ajst-322	13	39	detection	detection	NOUN
ajst-322	13	40	algorithm	algorithm	NOUN
ajst-322	13	41	respectively	respectively	ADV
ajst-322	13	42	.	.	PUNCT
ajst-322	14	1	the	the	DET
ajst-322	14	2	two	two	NUM
ajst-322	14	3	-	-	PUNCT
ajst-322	14	4	stage	stage	NOUN
ajst-322	14	5	object	object	NOUN
ajst-322	14	6	detection	detection	NOUN
ajst-322	14	7	algorithm	algorithm	NOUN
ajst-322	14	8	has	have	VERB
ajst-322	14	9	obvious	obvious	ADJ
ajst-322	14	10	advantages	advantage	NOUN
ajst-322	14	11	over	over	ADP
ajst-322	14	12	the	the	DET
ajst-322	14	13	first	first	ADJ
ajst-322	14	14	-	-	PUNCT
ajst-322	14	15	stage	stage	NOUN
ajst-322	14	16	algorithm	algorithm	NOUN
ajst-322	14	17	in	in	ADP
ajst-322	14	18	accuracy	accuracy	NOUN
ajst-322	14	19	,	,	PUNCT
ajst-322	14	20	and	and	CCONJ
ajst-322	14	21	among	among	ADP
ajst-322	14	22	the	the	DET
ajst-322	14	23	two	two	NUM
ajst-322	14	24	-	-	PUNCT
ajst-322	14	25	stage	stage	NOUN
ajst-322	14	26	object	object	NOUN
ajst-322	14	27	detection	detection	NOUN
ajst-322	14	28	algorithm	algorithm	NOUN
ajst-322	14	29	,	,	PUNCT
ajst-322	14	30	mask	mask	NOUN
ajst-322	14	31	rcnn[1	rcnn[1	PROPN
ajst-322	14	32	]	]	X
ajst-322	14	33	has	have	VERB
ajst-322	14	34	better	well	ADJ
ajst-322	14	35	object	object	VERB
ajst-322	14	36	detection	detection	NOUN
ajst-322	14	37	accuracy	accuracy	NOUN
ajst-322	14	38	and	and	CCONJ
ajst-322	14	39	good	good	ADJ
ajst-322	14	40	instance	instance	NOUN
ajst-322	14	41	segmentation	segmentation	NOUN
ajst-322	14	42	level	level	NOUN
ajst-322	14	43	.	.	PUNCT
ajst-322	15	1	in	in	ADP
ajst-322	15	2	this	this	DET
ajst-322	15	3	paper	paper	NOUN
ajst-322	15	4	,	,	PUNCT
ajst-322	15	5	mask	mask	NOUN
ajst-322	15	6	r	r	NOUN
ajst-322	15	7	-	-	PUNCT
ajst-322	15	8	cnn	cnn	PROPN
ajst-322	15	9	is	be	AUX
ajst-322	15	10	selected	select	VERB
ajst-322	15	11	as	as	ADP
ajst-322	15	12	the	the	DET
ajst-322	15	13	basic	basic	ADJ
ajst-322	15	14	model	model	NOUN
ajst-322	15	15	of	of	ADP
ajst-322	15	16	the	the	DET
ajst-322	15	17	task	task	NOUN
ajst-322	15	18	to	to	PART
ajst-322	15	19	realize	realize	VERB
ajst-322	15	20	the	the	DET
ajst-322	15	21	recognition	recognition	NOUN
ajst-322	15	22	of	of	ADP
ajst-322	15	23	different	different	ADJ
ajst-322	15	24	kinds	kind	NOUN
ajst-322	15	25	of	of	ADP
ajst-322	15	26	power	power	NOUN
ajst-322	15	27	equipment	equipment	NOUN
ajst-322	15	28	in	in	ADP
ajst-322	15	29	the	the	DET
ajst-322	15	30	infrared	infrared	ADJ
ajst-322	15	31	image	image	NOUN
ajst-322	15	32	.	.	PUNCT
ajst-322	16	1	in	in	ADP
ajst-322	16	2	this	this	DET
ajst-322	16	3	paper	paper	NOUN
ajst-322	16	4	,	,	PUNCT
ajst-322	16	5	the	the	DET
ajst-322	16	6	mask	mask	NOUN
ajst-322	16	7	r	r	NOUN
ajst-322	16	8	-	-	PUNCT
ajst-322	16	9	cnn	cnn	PROPN
ajst-322	16	10	model	model	NOUN
ajst-322	16	11	and	and	CCONJ
ajst-322	16	12	its	its	PRON
ajst-322	16	13	improvement	improvement	NOUN
ajst-322	16	14	during	during	ADP
ajst-322	16	15	the	the	DET
ajst-322	16	16	model	model	NOUN
ajst-322	16	17	construction	construction	NOUN
ajst-322	16	18	will	will	AUX
ajst-322	16	19	be	be	AUX
ajst-322	16	20	introduced	introduce	VERB
ajst-322	16	21	in	in	ADP
ajst-322	16	22	detail	detail	NOUN
ajst-322	16	23	,	,	PUNCT
ajst-322	16	24	so	so	SCONJ
ajst-322	16	25	that	that	SCONJ
ajst-322	16	26	it	it	PRON
ajst-322	16	27	can	can	AUX
ajst-322	16	28	better	well	ADV
ajst-322	16	29	complete	complete	VERB
ajst-322	16	30	the	the	DET
ajst-322	16	31	object	object	NOUN
ajst-322	16	32	detection	detection	NOUN
ajst-322	16	33	task	task	NOUN
ajst-322	16	34	of	of	ADP
ajst-322	16	35	infrared	infrared	ADJ
ajst-322	16	36	images	image	NOUN
ajst-322	16	37	in	in	ADP
ajst-322	16	38	the	the	DET
ajst-322	16	39	electric	electric	ADJ
ajst-322	16	40	power	power	NOUN
ajst-322	16	41	scene	scene	NOUN
ajst-322	16	42	.	.	PUNCT
ajst-322	17	1	firstly	firstly	ADV
ajst-322	17	2	,	,	PUNCT
ajst-322	17	3	the	the	DET
ajst-322	17	4	overall	overall	ADJ
ajst-322	17	5	structure	structure	NOUN
ajst-322	17	6	of	of	ADP
ajst-322	17	7	the	the	DET
ajst-322	17	8	basic	basic	ADJ
ajst-322	17	9	model	model	NOUN
ajst-322	17	10	mask	mask	NOUN
ajst-322	17	11	r	r	NOUN
ajst-322	17	12	-	-	PUNCT
ajst-322	17	13	cnn	cnn	PROPN
ajst-322	17	14	is	be	AUX
ajst-322	17	15	introduced	introduce	VERB
ajst-322	17	16	.	.	PUNCT
ajst-322	18	1	secondly	secondly	ADV
ajst-322	18	2	,	,	PUNCT
ajst-322	18	3	the	the	DET
ajst-322	18	4	design	design	NOUN
ajst-322	18	5	and	and	CCONJ
ajst-322	18	6	implementation	implementation	NOUN
ajst-322	18	7	process	process	NOUN
ajst-322	18	8	of	of	ADP
ajst-322	18	9	object	object	NOUN
ajst-322	18	10	detection	detection	NOUN
ajst-322	18	11	task	task	NOUN
ajst-322	18	12	is	be	AUX
ajst-322	18	13	introduced	introduce	VERB
ajst-322	18	14	,	,	PUNCT
ajst-322	18	15	including	include	VERB
ajst-322	18	16	the	the	DET
ajst-322	18	17	construction	construction	NOUN
ajst-322	18	18	of	of	ADP
ajst-322	18	19	digital	digital	ADJ
ajst-322	18	20	backbone	backbone	NOUN
ajst-322	18	21	network	network	NOUN
ajst-322	18	22	and	and	CCONJ
ajst-322	18	23	the	the	DET
ajst-322	18	24	improvement	improvement	NOUN
ajst-322	18	25	of	of	ADP
ajst-322	18	26	network	network	NOUN
ajst-322	18	27	.	.	PUNCT
ajst-322	19	1	finally	finally	ADV
ajst-322	19	2	,	,	PUNCT
ajst-322	19	3	the	the	DET
ajst-322	19	4	experiment	experiment	NOUN
ajst-322	19	5	proves	prove	VERB
ajst-322	19	6	that	that	SCONJ
ajst-322	19	7	the	the	DET
ajst-322	19	8	improved	improved	ADJ
ajst-322	19	9	module	module	NOUN
ajst-322	19	10	improves	improve	VERB
ajst-322	19	11	the	the	DET
ajst-322	19	12	accuracy	accuracy	NOUN
ajst-322	19	13	.	.	PUNCT
ajst-322	20	1	2	2	X
ajst-322	20	2	.	.	NUM
ajst-322	20	3	related	relate	VERB
ajst-322	20	4	works	work	NOUN
ajst-322	20	5	most	most	ADJ
ajst-322	20	6	of	of	ADP
ajst-322	20	7	the	the	DET
ajst-322	20	8	two	two	NUM
ajst-322	20	9	-	-	PUNCT
ajst-322	20	10	stage	stage	NOUN
ajst-322	20	11	object	object	NOUN
ajst-322	20	12	detection	detection	NOUN
ajst-322	20	13	methods	method	NOUN
ajst-322	20	14	are	be	AUX
ajst-322	20	15	completed	complete	VERB
ajst-322	20	16	by	by	ADP
ajst-322	20	17	the	the	DET
ajst-322	20	18	following	follow	VERB
ajst-322	20	19	steps	step	NOUN
ajst-322	20	20	:	:	PUNCT
ajst-322	20	21	firstly	firstly	ADV
ajst-322	20	22	,	,	PUNCT
ajst-322	20	23	some	some	DET
ajst-322	20	24	possible	possible	ADJ
ajst-322	20	25	regions	region	NOUN
ajst-322	20	26	are	be	AUX
ajst-322	20	27	screened	screen	VERB
ajst-322	20	28	out	out	ADP
ajst-322	20	29	,	,	PUNCT
ajst-322	20	30	which	which	PRON
ajst-322	20	31	are	be	AUX
ajst-322	20	32	enlarged	enlarge	VERB
ajst-322	20	33	or	or	CCONJ
ajst-322	20	34	reduced	reduce	VERB
ajst-322	20	35	to	to	ADP
ajst-322	20	36	a	a	DET
ajst-322	20	37	fixed	fix	VERB
ajst-322	20	38	size	size	NOUN
ajst-322	20	39	.	.	PUNCT
ajst-322	21	1	then	then	ADV
ajst-322	21	2	,	,	PUNCT
ajst-322	21	3	these	these	DET
ajst-322	21	4	regions	region	NOUN
ajst-322	21	5	of	of	ADP
ajst-322	21	6	the	the	DET
ajst-322	21	7	same	same	ADJ
ajst-322	21	8	size	size	NOUN
ajst-322	21	9	are	be	AUX
ajst-322	21	10	divided	divide	VERB
ajst-322	21	11	into	into	ADP
ajst-322	21	12	positive	positive	ADJ
ajst-322	21	13	samples	sample	NOUN
ajst-322	21	14	and	and	CCONJ
ajst-322	21	15	negative	negative	ADJ
ajst-322	21	16	samples	sample	NOUN
ajst-322	21	17	according	accord	VERB
ajst-322	21	18	to	to	ADP
ajst-322	21	19	the	the	DET
ajst-322	21	20	set	set	NOUN
ajst-322	21	21	rules	rule	NOUN
ajst-322	21	22	.	.	PUNCT
ajst-322	22	1	feature	feature	NOUN
ajst-322	22	2	vectors	vector	NOUN
ajst-322	22	3	are	be	AUX
ajst-322	22	4	obtained	obtain	VERB
ajst-322	22	5	by	by	ADP
ajst-322	22	6	training	train	VERB
ajst-322	22	7	cnn	cnn	PROPN
ajst-322	22	8	,	,	PUNCT
ajst-322	22	9	and	and	CCONJ
ajst-322	22	10	then	then	ADV
ajst-322	22	11	they	they	PRON
ajst-322	22	12	are	be	AUX
ajst-322	22	13	put	put	VERB
ajst-322	22	14	into	into	ADP
ajst-322	22	15	the	the	DET
ajst-322	22	16	classifier	classifier	NOUN
ajst-322	22	17	to	to	PART
ajst-322	22	18	realize	realize	VERB
ajst-322	22	19	classification	classification	NOUN
ajst-322	22	20	,	,	PUNCT
ajst-322	22	21	screening	screening	NOUN
ajst-322	22	22	and	and	CCONJ
ajst-322	22	23	correction	correction	NOUN
ajst-322	22	24	of	of	ADP
ajst-322	22	25	generated	generate	VERB
ajst-322	22	26	detection	detection	NOUN
ajst-322	22	27	boxes	box	NOUN
ajst-322	22	28	.	.	PUNCT
ajst-322	23	1	representative	representative	ADJ
ajst-322	23	2	research	research	NOUN
ajst-322	23	3	methods	method	NOUN
ajst-322	23	4	of	of	ADP
ajst-322	23	5	two	two	NUM
ajst-322	23	6	-	-	PUNCT
ajst-322	23	7	stage	stage	NOUN
ajst-322	23	8	object	object	NOUN
ajst-322	23	9	detection	detection	NOUN
ajst-322	23	10	include	include	VERB
ajst-322	23	11	r	r	NOUN
ajst-322	23	12	-	-	PUNCT
ajst-322	23	13	cnn[2	cnn[2	NOUN
ajst-322	23	14	]	]	PUNCT
ajst-322	23	15	,	,	PUNCT
ajst-322	23	16	spp	spp	NOUN
ajst-322	23	17	-	-	PUNCT
ajst-322	23	18	net[3	net[3	NUM
ajst-322	23	19	]	]	PUNCT
ajst-322	23	20	,	,	PUNCT
ajst-322	23	21	fast	fast	ADJ
ajst-322	23	22	r	r	NOUN
ajst-322	23	23	-	-	PUNCT
ajst-322	23	24	cnn[4	cnn[4	NOUN
ajst-322	23	25	]	]	PUNCT
ajst-322	23	26	,	,	PUNCT
ajst-322	23	27	faster	fast	ADJ
ajst-322	23	28	r	r	NOUN
ajst-322	23	29	-	-	PUNCT
ajst-322	23	30	cnn[5	cnn[5	NUM
ajst-322	23	31	]	]	PUNCT
ajst-322	23	32	and	and	CCONJ
ajst-322	23	33	mask	mask	VERB
ajst-322	23	34	r	r	PROPN
ajst-322	23	35	-	-	PUNCT
ajst-322	23	36	cnn	cnn	PROPN
ajst-322	23	37	,	,	PUNCT
ajst-322	23	38	etc	etc	X
ajst-322	23	39	.	.	X
ajst-322	24	1	the	the	DET
ajst-322	24	2	object	object	NOUN
ajst-322	24	3	detection	detection	NOUN
ajst-322	24	4	model	model	NOUN
ajst-322	24	5	adopted	adopt	VERB
ajst-322	24	6	in	in	ADP
ajst-322	24	7	this	this	DET
ajst-322	24	8	paper	paper	NOUN
ajst-322	24	9	is	be	AUX
ajst-322	24	10	mask	mask	NOUN
ajst-322	24	11	r	r	NOUN
ajst-322	24	12	-	-	PUNCT
ajst-322	24	13	cnn	cnn	PROPN
ajst-322	24	14	,	,	PUNCT
ajst-322	24	15	as	as	ADP
ajst-322	24	16	an	an	DET
ajst-322	24	17	extension	extension	NOUN
ajst-322	24	18	of	of	ADP
ajst-322	24	19	faster	fast	ADJ
ajst-322	24	20	rcnn	rcnn	NOUN
ajst-322	24	21	,	,	PUNCT
ajst-322	24	22	and	and	CCONJ
ajst-322	24	23	its	its	PRON
ajst-322	24	24	structure	structure	NOUN
ajst-322	24	25	is	be	AUX
ajst-322	24	26	mainly	mainly	ADV
ajst-322	24	27	divided	divide	VERB
ajst-322	24	28	into	into	ADP
ajst-322	24	29	two	two	NUM
ajst-322	24	30	stages	stage	NOUN
ajst-322	24	31	.	.	PUNCT
ajst-322	25	1	the	the	DET
ajst-322	25	2	task	task	NOUN
ajst-322	25	3	of	of	ADP
ajst-322	25	4	the	the	DET
ajst-322	25	5	first	first	ADJ
ajst-322	25	6	stage	stage	NOUN
ajst-322	25	7	is	be	AUX
ajst-322	25	8	to	to	PART
ajst-322	25	9	generate	generate	VERB
ajst-322	25	10	the	the	DET
ajst-322	25	11	rectangular	rectangular	ADJ
ajst-322	25	12	box	box	NOUN
ajst-322	25	13	with	with	ADP
ajst-322	25	14	a	a	DET
ajst-322	25	15	high	high	ADJ
ajst-322	25	16	probability	probability	NOUN
ajst-322	25	17	of	of	ADP
ajst-322	25	18	detecting	detect	VERB
ajst-322	25	19	objects	object	NOUN
ajst-322	25	20	in	in	ADP
ajst-322	25	21	the	the	DET
ajst-322	25	22	image	image	NOUN
ajst-322	25	23	,	,	PUNCT
ajst-322	25	24	namely	namely	ADV
ajst-322	25	25	the	the	DET
ajst-322	25	26	region	region	NOUN
ajst-322	25	27	proposal	proposal	PROPN
ajst-322	25	28	box	box	PROPN
ajst-322	25	29	,	,	PUNCT
ajst-322	25	30	which	which	PRON
ajst-322	25	31	is	be	AUX
ajst-322	25	32	called	call	VERB
ajst-322	25	33	region	region	NOUN
ajst-322	25	34	proposal	proposal	NOUN
ajst-322	25	35	in	in	ADP
ajst-322	25	36	the	the	DET
ajst-322	25	37	original	original	ADJ
ajst-322	25	38	work	work	NOUN
ajst-322	25	39	and	and	CCONJ
ajst-322	25	40	mainly	mainly	ADV
ajst-322	25	41	consists	consist	VERB
ajst-322	25	42	of	of	ADP
ajst-322	25	43	convolutional	convolutional	ADJ
ajst-322	25	44	neural	neural	ADJ
ajst-322	25	45	network	network	NOUN
ajst-322	25	46	and	and	CCONJ
ajst-322	25	47	region	region	NOUN
ajst-322	25	48	proposal	proposal	NOUN
ajst-322	25	49	network	network	NOUN
ajst-322	25	50	(	(	PUNCT
ajst-322	25	51	rpn	rpn	PROPN
ajst-322	25	52	)	)	PUNCT
ajst-322	25	53	.	.	PUNCT
ajst-322	26	1	feature	feature	NOUN
ajst-322	26	2	extraction	extraction	NOUN
ajst-322	26	3	of	of	ADP
ajst-322	26	4	input	input	NOUN
ajst-322	26	5	data	datum	NOUN
ajst-322	26	6	and	and	CCONJ
ajst-322	26	7	suggestion	suggestion	NOUN
ajst-322	26	8	box	box	NOUN
ajst-322	26	9	generation	generation	NOUN
ajst-322	26	10	;	;	PUNCT
ajst-322	26	11	the	the	DET
ajst-322	26	12	task	task	NOUN
ajst-322	26	13	of	of	ADP
ajst-322	26	14	the	the	DET
ajst-322	26	15	second	second	ADJ
ajst-322	26	16	stage	stage	NOUN
ajst-322	26	17	is	be	AUX
ajst-322	26	18	to	to	PART
ajst-322	26	19	output	output	VERB
ajst-322	26	20	the	the	DET
ajst-322	26	21	rectangular	rectangular	ADJ
ajst-322	26	22	box	box	NOUN
ajst-322	26	23	containing	contain	VERB
ajst-322	26	24	the	the	DET
ajst-322	26	25	detection	detection	NOUN
ajst-322	26	26	object	object	NOUN
ajst-322	26	27	,	,	PUNCT
ajst-322	26	28	the	the	DET
ajst-322	26	29	corresponding	corresponding	ADJ
ajst-322	26	30	prediction	prediction	NOUN
ajst-322	26	31	confidence	confidence	NOUN
ajst-322	26	32	and	and	CCONJ
ajst-322	26	33	the	the	DET
ajst-322	26	34	mask	mask	NOUN
ajst-322	26	35	of	of	ADP
ajst-322	26	36	the	the	DET
ajst-322	26	37	generated	generate	VERB
ajst-322	26	38	object	object	NOUN
ajst-322	26	39	,	,	PUNCT
ajst-322	26	40	including	include	VERB
ajst-322	26	41	the	the	DET
ajst-322	26	42	region	region	NOUN
ajst-322	26	43	of	of	ADP
ajst-322	26	44	interest	interest	NOUN
ajst-322	26	45	(	(	PUNCT
ajst-322	26	46	roi	roi	NOUN
ajst-322	26	47	)	)	PUNCT
ajst-322	26	48	corresponding	correspond	VERB
ajst-322	26	49	to	to	ADP
ajst-322	26	50	the	the	DET
ajst-322	26	51	suggestion	suggestion	NOUN
ajst-322	26	52	box	box	NOUN
ajst-322	26	53	,	,	PUNCT
ajst-322	26	54	roi	roi	NOUN
ajst-322	26	55	is	be	AUX
ajst-322	26	56	converted	convert	VERB
ajst-322	26	57	into	into	ADP
ajst-322	26	58	region	region	NOUN
ajst-322	26	59	of	of	ADP
ajst-322	26	60	interest	interest	NOUN
ajst-322	26	61	align	align	NOUN
ajst-322	26	62	(	(	PUNCT
ajst-322	26	63	roialign	roialign	NOUN
ajst-322	26	64	)	)	PUNCT
ajst-322	26	65	layer	layer	NOUN
ajst-322	26	66	of	of	ADP
ajst-322	26	67	fixed	fix	VERB
ajst-322	26	68	-	-	PUNCT
ajst-322	26	69	size	size	NOUN
ajst-322	26	70	feature	feature	NOUN
ajst-322	26	71	map	map	NOUN
ajst-322	26	72	,	,	PUNCT
ajst-322	26	73	and	and	CCONJ
ajst-322	26	74	classification	classification	NOUN
ajst-322	26	75	branch	branch	NOUN
ajst-322	26	76	,	,	PUNCT
ajst-322	26	77	position	position	NOUN
ajst-322	26	78	prediction	prediction	NOUN
ajst-322	26	79	branch	branch	NOUN
ajst-322	26	80	and	and	CCONJ
ajst-322	26	81	mask	mask	NOUN
ajst-322	26	82	generation	generation	NOUN
ajst-322	26	83	branch	branch	NOUN
ajst-322	26	84	for	for	ADP
ajst-322	26	85	classification	classification	NOUN
ajst-322	26	86	and	and	CCONJ
ajst-322	26	87	regression	regression	NOUN
ajst-322	26	88	object	object	NOUN
ajst-322	26	89	detection	detection	NOUN
ajst-322	26	90	frame	frame	NOUN
ajst-322	26	91	.	.	PUNCT
ajst-322	27	1	compared	compare	VERB
ajst-322	27	2	with	with	ADP
ajst-322	27	3	faster	fast	ADJ
ajst-322	27	4	rcnn	rcnn	NOUN
ajst-322	27	5	,	,	PUNCT
ajst-322	27	6	the	the	DET
ajst-322	27	7	improvement	improvement	NOUN
ajst-322	27	8	of	of	ADP
ajst-322	27	9	mask	mask	NOUN
ajst-322	27	10	r	r	NOUN
ajst-322	27	11	-	-	PUNCT
ajst-322	27	12	cnn	cnn	PROPN
ajst-322	27	13	lies	lie	VERB
ajst-322	27	14	in	in	ADP
ajst-322	27	15	the	the	DET
ajst-322	27	16	increase	increase	NOUN
ajst-322	27	17	of	of	ADP
ajst-322	27	18	mask	mask	NOUN
ajst-322	27	19	generation	generation	NOUN
ajst-322	27	20	branch	branch	NOUN
ajst-322	27	21	and	and	CCONJ
ajst-322	27	22	the	the	DET
ajst-322	27	23	replacement	replacement	NOUN
ajst-322	27	24	of	of	ADP
ajst-322	27	25	roialign	roialign	NOUN
ajst-322	27	26	of	of	ADP
ajst-322	27	27	roipool	roipool	NOUN
ajst-322	27	28	.	.	PUNCT
ajst-322	28	1	figure	figure	NOUN
ajst-322	28	2	1	1	NUM
ajst-322	28	3	shows	show	VERB
ajst-322	28	4	the	the	DET
ajst-322	28	5	construction	construction	NOUN
ajst-322	28	6	of	of	ADP
ajst-322	28	7	mask	mask	NOUN
ajst-322	28	8	r	r	PROPN
ajst-322	28	9	-	-	PUNCT
ajst-322	28	10	cnn	cnn	NOUN
ajst-322	28	11	.	.	PUNCT
ajst-322	29	1	2.1	2.1	NUM
ajst-322	29	2	.	.	PUNCT
ajst-322	30	1	rpn	rpn	PROPN
ajst-322	30	2	and	and	CCONJ
ajst-322	30	3	roi	roi	NOUN
ajst-322	30	4	align	align	NOUN
ajst-322	30	5	region	region	NOUN
ajst-322	30	6	proposal	proposal	NOUN
ajst-322	30	7	network	network	NOUN
ajst-322	30	8	(	(	PUNCT
ajst-322	30	9	rpn	rpn	PROPN
ajst-322	30	10	)	)	PUNCT
ajst-322	30	11	is	be	AUX
ajst-322	30	12	a	a	DET
ajst-322	30	13	classless	classless	ADJ
ajst-322	30	14	object	object	NOUN
ajst-322	30	15	detector	detector	NOUN
ajst-322	30	16	based	base	VERB
ajst-322	30	17	on	on	ADP
ajst-322	30	18	sliding	slide	VERB
ajst-322	30	19	window	window	NOUN
ajst-322	30	20	realized	realize	VERB
ajst-322	30	21	by	by	ADP
ajst-322	30	22	convolutional	convolutional	ADJ
ajst-322	30	23	neural	neural	ADJ
ajst-322	30	24	network	network	NOUN
ajst-322	30	25	.	.	PUNCT
ajst-322	31	1	it	it	PRON
ajst-322	31	2	first	first	ADV
ajst-322	31	3	appeared	appear	VERB
ajst-322	31	4	in	in	ADP
ajst-322	31	5	the	the	DET
ajst-322	31	6	faster	fast	ADJ
ajst-322	31	7	rcnn	rcnn	PROPN
ajst-322	31	8	model	model	NOUN
ajst-322	31	9	and	and	CCONJ
ajst-322	31	10	greatly	greatly	ADV
ajst-322	31	11	improved	improve	VERB
ajst-322	31	12	the	the	DET
ajst-322	31	13	generation	generation	NOUN
ajst-322	31	14	speed	speed	NOUN
ajst-322	31	15	of	of	ADP
ajst-322	31	16	candidate	candidate	NOUN
ajst-322	31	17	boxes	box	NOUN
ajst-322	31	18	.	.	PUNCT
ajst-322	32	1	the	the	DET
ajst-322	32	2	input	input	NOUN
ajst-322	32	3	of	of	ADP
ajst-322	32	4	rpn	rpn	PROPN
ajst-322	32	5	is	be	AUX
ajst-322	32	6	the	the	DET
ajst-322	32	7	image	image	NOUN
ajst-322	32	8	of	of	ADP
ajst-322	32	9	any	any	DET
ajst-322	32	10	scale	scale	NOUN
ajst-322	32	11	,	,	PUNCT
ajst-322	32	12	and	and	CCONJ
ajst-322	32	13	the	the	DET
ajst-322	32	14	output	output	NOUN
ajst-322	32	15	is	be	AUX
ajst-322	32	16	a	a	DET
ajst-322	32	17	series	series	NOUN
ajst-322	32	18	of	of	ADP
ajst-322	32	19	rectangular	rectangular	ADJ
ajst-322	32	20	candidate	candidate	NOUN
ajst-322	32	21	boxes	box	NOUN
ajst-322	32	22	(	(	PUNCT
ajst-322	32	23	anchor	anchor	PROPN
ajst-322	32	24	)	)	PUNCT
ajst-322	32	25	.	.	PUNCT
ajst-322	33	1	characteristics	characteristic	NOUN
ajst-322	33	2	of	of	ADP
ajst-322	33	3	each	each	DET
ajst-322	33	4	pixel	pixel	NOUN
ajst-322	33	5	point	point	NOUN
ajst-322	33	6	on	on	ADP
ajst-322	33	7	the	the	DET
ajst-322	33	8	figure	figure	NOUN
ajst-322	33	9	will	will	AUX
ajst-322	33	10	generate	generate	VERB
ajst-322	33	11	a	a	DET
ajst-322	33	12	large	large	ADJ
ajst-322	33	13	number	number	NOUN
ajst-322	33	14	of	of	ADP
ajst-322	33	15	candidates	candidate	NOUN
ajst-322	33	16	for	for	ADP
ajst-322	33	17	the	the	DET
ajst-322	33	18	different	different	ADJ
ajst-322	33	19	size	size	NOUN
ajst-322	33	20	and	and	CCONJ
ajst-322	33	21	different	different	ADJ
ajst-322	33	22	aspect	aspect	NOUN
ajst-322	33	23	ratio	ratio	NOUN
ajst-322	33	24	box	box	PROPN
ajst-322	33	25	,	,	PUNCT
ajst-322	33	26	these	these	DET
ajst-322	33	27	candidate	candidate	NOUN
ajst-322	33	28	box	box	NOUN
ajst-322	33	29	will	will	AUX
ajst-322	33	30	cover	cover	VERB
ajst-322	33	31	more	more	ADJ
ajst-322	33	32	image	image	NOUN
ajst-322	33	33	area	area	NOUN
ajst-322	33	34	,	,	PUNCT
ajst-322	33	35	if	if	SCONJ
ajst-322	33	36	possible	possible	ADJ
ajst-322	33	37	by	by	ADP
ajst-322	33	38	cnn	cnn	PROPN
ajst-322	33	39	to	to	PART
ajst-322	33	40	judge	judge	VERB
ajst-322	33	41	the	the	DET
ajst-322	33	42	candidate	candidate	NOUN
ajst-322	33	43	box	box	NOUN
ajst-322	33	44	which	which	PRON
ajst-322	33	45	is	be	AUX
ajst-322	33	46	a	a	DET
ajst-322	33	47	object	object	NOUN
ajst-322	33	48	is	be	AUX
ajst-322	33	49	sample	sample	NOUN
ajst-322	33	50	box	box	NOUN
ajst-322	33	51	,	,	PUNCT
ajst-322	33	52	which	which	PRON
ajst-322	33	53	is	be	AUX
ajst-322	33	54	not	not	PART
ajst-322	33	55	contain	contain	VERB
ajst-322	33	56	the	the	DET
ajst-322	33	57	object	object	NOUN
ajst-322	33	58	negative	negative	ADJ
ajst-322	33	59	samples	sample	NOUN
ajst-322	33	60	,	,	PUNCT
ajst-322	33	61	and	and	CCONJ
ajst-322	33	62	to	to	PART
ajst-322	33	63	determine	determine	VERB
ajst-322	33	64	the	the	DET
ajst-322	33	65	coordinates	coordinate	NOUN
ajst-322	33	66	correction	correction	PROPN
ajst-322	33	67	sample	sample	PROPN
ajst-322	33	68	box	box	PROPN
ajst-322	33	69	.	.	PUNCT
ajst-322	34	1	61	61	NUM
ajst-322	34	2	figure	figure	NOUN
ajst-322	34	3	1	1	NUM
ajst-322	34	4	.	.	PUNCT
ajst-322	34	5	mask	mask	VERB
ajst-322	34	6	r	r	NOUN
ajst-322	34	7	-	-	PUNCT
ajst-322	34	8	cnn	cnn	PROPN
ajst-322	34	9	in	in	ADP
ajst-322	34	10	faster	fast	ADJ
ajst-322	34	11	r	r	NOUN
ajst-322	34	12	-	-	PUNCT
ajst-322	34	13	cnn	cnn	PROPN
ajst-322	34	14	,	,	PUNCT
ajst-322	34	15	this	this	DET
ajst-322	34	16	step	step	NOUN
ajst-322	34	17	corresponds	correspond	VERB
ajst-322	34	18	to	to	ADP
ajst-322	34	19	roi	roi	NOUN
ajst-322	34	20	pooling	pool	VERB
ajst-322	34	21	layer	layer	NOUN
ajst-322	34	22	,	,	PUNCT
ajst-322	34	23	where	where	SCONJ
ajst-322	34	24	the	the	DET
ajst-322	34	25	operation	operation	NOUN
ajst-322	34	26	is	be	AUX
ajst-322	34	27	:	:	PUNCT
ajst-322	34	28	firstly	firstly	ADV
ajst-322	34	29	,	,	PUNCT
ajst-322	34	30	the	the	DET
ajst-322	34	31	suggestion	suggestion	NOUN
ajst-322	34	32	frames	frame	NOUN
ajst-322	34	33	are	be	AUX
ajst-322	34	34	mapped	map	VERB
ajst-322	34	35	back	back	ADV
ajst-322	34	36	to	to	ADP
ajst-322	34	37	the	the	DET
ajst-322	34	38	scale	scale	NOUN
ajst-322	34	39	of	of	ADP
ajst-322	34	40	feature	feature	NOUN
ajst-322	34	41	maps	map	NOUN
ajst-322	34	42	,	,	PUNCT
ajst-322	34	43	and	and	CCONJ
ajst-322	34	44	then	then	ADV
ajst-322	34	45	the	the	DET
ajst-322	34	46	feature	feature	NOUN
ajst-322	34	47	map	map	NOUN
ajst-322	34	48	region	region	NOUN
ajst-322	34	49	corresponding	correspond	VERB
ajst-322	34	50	to	to	ADP
ajst-322	34	51	each	each	DET
ajst-322	34	52	suggestion	suggestion	NOUN
ajst-322	34	53	frame	frame	NOUN
ajst-322	34	54	is	be	AUX
ajst-322	34	55	horizontally	horizontally	ADV
ajst-322	34	56	divided	divide	VERB
ajst-322	34	57	into	into	ADP
ajst-322	34	58	fixed	fix	VERB
ajst-322	34	59	-	-	PUNCT
ajst-322	34	60	size	size	NOUN
ajst-322	34	61	grids	grid	NOUN
ajst-322	34	62	(	(	PUNCT
ajst-322	34	63	bin	bin	NOUN
ajst-322	34	64	)	)	PUNCT
ajst-322	34	65	,	,	PUNCT
ajst-322	34	66	and	and	CCONJ
ajst-322	34	67	each	each	DET
ajst-322	34	68	piece	piece	NOUN
ajst-322	34	69	of	of	ADP
ajst-322	34	70	the	the	DET
ajst-322	34	71	grid	grid	NOUN
ajst-322	34	72	is	be	AUX
ajst-322	34	73	maximized	maximize	VERB
ajst-322	34	74	to	to	PART
ajst-322	34	75	make	make	VERB
ajst-322	34	76	the	the	DET
ajst-322	34	77	corresponding	corresponding	ADJ
ajst-322	34	78	regions	region	NOUN
ajst-322	34	79	of	of	ADP
ajst-322	34	80	suggestion	suggestion	NOUN
ajst-322	34	81	frames	frame	NOUN
ajst-322	34	82	of	of	ADP
ajst-322	34	83	different	different	ADJ
ajst-322	34	84	scales	scale	NOUN
ajst-322	34	85	have	have	VERB
ajst-322	34	86	the	the	DET
ajst-322	34	87	same	same	ADJ
ajst-322	34	88	resolution	resolution	NOUN
ajst-322	34	89	.	.	PUNCT
ajst-322	35	1	in	in	ADP
ajst-322	35	2	this	this	DET
ajst-322	35	3	process	process	NOUN
ajst-322	35	4	,	,	PUNCT
ajst-322	35	5	both	both	CCONJ
ajst-322	35	6	the	the	DET
ajst-322	35	7	mapping	mapping	NOUN
ajst-322	35	8	operation	operation	NOUN
ajst-322	35	9	and	and	CCONJ
ajst-322	35	10	the	the	DET
ajst-322	35	11	meshing	meshing	NOUN
ajst-322	35	12	operation	operation	NOUN
ajst-322	35	13	are	be	AUX
ajst-322	35	14	likely	likely	ADJ
ajst-322	35	15	to	to	PART
ajst-322	35	16	generate	generate	VERB
ajst-322	35	17	floating	float	VERB
ajst-322	35	18	point	point	NOUN
ajst-322	35	19	numbers	number	NOUN
ajst-322	35	20	,	,	PUNCT
ajst-322	35	21	and	and	CCONJ
ajst-322	35	22	the	the	DET
ajst-322	35	23	roi	roi	NOUN
ajst-322	35	24	pooling	pool	VERB
ajst-322	35	25	layer	layer	NOUN
ajst-322	35	26	quantifies	quantifie	NOUN
ajst-322	35	27	these	these	DET
ajst-322	35	28	two	two	NUM
ajst-322	35	29	steps	step	NOUN
ajst-322	35	30	,	,	PUNCT
ajst-322	35	31	i.e.	i.e.	X
ajst-322	35	32	,	,	PUNCT
ajst-322	35	33	rounding	round	VERB
ajst-322	35	34	.	.	PUNCT
ajst-322	36	1	the	the	DET
ajst-322	36	2	roialign	roialign	NOUN
ajst-322	36	3	layer	layer	NOUN
ajst-322	36	4	is	be	AUX
ajst-322	36	5	used	use	VERB
ajst-322	36	6	in	in	ADP
ajst-322	36	7	mask	mask	NOUN
ajst-322	36	8	r	r	PROPN
ajst-322	36	9	-	-	PUNCT
ajst-322	36	10	cnn	cnn	PROPN
ajst-322	36	11	,	,	PUNCT
ajst-322	36	12	and	and	CCONJ
ajst-322	36	13	the	the	DET
ajst-322	36	14	steps	step	NOUN
ajst-322	36	15	of	of	ADP
ajst-322	36	16	mapping	mapping	NOUN
ajst-322	36	17	and	and	CCONJ
ajst-322	36	18	grid	grid	NOUN
ajst-322	36	19	partitioning	partitioning	NOUN
ajst-322	36	20	are	be	AUX
ajst-322	36	21	no	no	ADV
ajst-322	36	22	longer	long	ADV
ajst-322	36	23	quantified	quantify	VERB
ajst-322	36	24	.	.	PUNCT
ajst-322	37	1	floating	float	VERB
ajst-322	37	2	point	point	NOUN
ajst-322	37	3	numbers	number	NOUN
ajst-322	37	4	are	be	AUX
ajst-322	37	5	retained	retain	VERB
ajst-322	37	6	directly	directly	ADV
ajst-322	37	7	.	.	PUNCT
ajst-322	38	1	bilinear	bilinear	NOUN
ajst-322	38	2	interpolation	interpolation	NOUN
ajst-322	38	3	method	method	NOUN
ajst-322	38	4	is	be	AUX
ajst-322	38	5	adopted	adopt	VERB
ajst-322	38	6	to	to	PART
ajst-322	38	7	obtain	obtain	VERB
ajst-322	38	8	the	the	DET
ajst-322	38	9	coordinate	coordinate	NOUN
ajst-322	38	10	positions	position	NOUN
ajst-322	38	11	of	of	ADP
ajst-322	38	12	a	a	DET
ajst-322	38	13	fixed	fix	VERB
ajst-322	38	14	number	number	NOUN
ajst-322	38	15	of	of	ADP
ajst-322	38	16	sampling	sample	VERB
ajst-322	38	17	points	point	NOUN
ajst-322	38	18	in	in	ADP
ajst-322	38	19	each	each	DET
ajst-322	38	20	bin	bin	NOUN
ajst-322	38	21	,	,	PUNCT
ajst-322	38	22	and	and	CCONJ
ajst-322	38	23	then	then	ADV
ajst-322	38	24	the	the	DET
ajst-322	38	25	maximum	maximum	ADJ
ajst-322	38	26	pooling	pool	VERB
ajst-322	38	27	operation	operation	NOUN
ajst-322	38	28	is	be	AUX
ajst-322	38	29	carried	carry	VERB
ajst-322	38	30	out	out	ADP
ajst-322	38	31	to	to	PART
ajst-322	38	32	obtain	obtain	VERB
ajst-322	38	33	more	more	ADV
ajst-322	38	34	accurate	accurate	ADJ
ajst-322	38	35	features	feature	NOUN
ajst-322	38	36	.	.	PUNCT
ajst-322	39	1	2.2	2.2	NUM
ajst-322	39	2	.	.	PUNCT
ajst-322	39	3	senet	senet	NOUN
ajst-322	39	4	in	in	ADP
ajst-322	39	5	recent	recent	ADJ
ajst-322	39	6	years	year	NOUN
ajst-322	39	7	,	,	PUNCT
ajst-322	39	8	attention	attention	NOUN
ajst-322	39	9	models	model	NOUN
ajst-322	39	10	in	in	ADP
ajst-322	39	11	different	different	ADJ
ajst-322	39	12	fields	field	NOUN
ajst-322	39	13	have	have	AUX
ajst-322	39	14	been	be	AUX
ajst-322	39	15	proposed	propose	VERB
ajst-322	39	16	,	,	PUNCT
ajst-322	39	17	which	which	PRON
ajst-322	39	18	are	be	AUX
ajst-322	39	19	widely	widely	ADV
ajst-322	39	20	used	use	VERB
ajst-322	39	21	in	in	ADP
ajst-322	39	22	deep	deep	ADJ
ajst-322	39	23	learning	learning	NOUN
ajst-322	39	24	tasks	task	NOUN
ajst-322	39	25	such	such	ADJ
ajst-322	39	26	as	as	ADP
ajst-322	39	27	natural	natural	ADJ
ajst-322	39	28	language	language	NOUN
ajst-322	39	29	processing	processing	NOUN
ajst-322	39	30	,	,	PUNCT
ajst-322	39	31	speech	speech	NOUN
ajst-322	39	32	recognition	recognition	NOUN
ajst-322	39	33	,	,	PUNCT
ajst-322	39	34	object	object	VERB
ajst-322	39	35	detection	detection	NOUN
ajst-322	39	36	and	and	CCONJ
ajst-322	39	37	image	image	NOUN
ajst-322	39	38	segmentation	segmentation	NOUN
ajst-322	39	39	.	.	PUNCT
ajst-322	40	1	it	it	PRON
ajst-322	40	2	can	can	AUX
ajst-322	40	3	be	be	AUX
ajst-322	40	4	easily	easily	ADV
ajst-322	40	5	embedded	embed	VERB
ajst-322	40	6	into	into	ADP
ajst-322	40	7	existing	exist	VERB
ajst-322	40	8	networks	network	NOUN
ajst-322	40	9	to	to	PART
ajst-322	40	10	improve	improve	VERB
ajst-322	40	11	the	the	DET
ajst-322	40	12	representation	representation	NOUN
ajst-322	40	13	of	of	ADP
ajst-322	40	14	models	model	NOUN
ajst-322	40	15	in	in	ADP
ajst-322	40	16	a	a	DET
ajst-322	40	17	plug	plug	VERB
ajst-322	40	18	-	-	PUNCT
ajst-322	40	19	and	and	CCONJ
ajst-322	40	20	-	-	PUNCT
ajst-322	40	21	play	play	NOUN
ajst-322	40	22	manner	manner	NOUN
ajst-322	40	23	.	.	PUNCT
ajst-322	41	1	the	the	DET
ajst-322	41	2	attention	attention	NOUN
ajst-322	41	3	mechanism	mechanism	NOUN
ajst-322	41	4	for	for	ADP
ajst-322	41	5	senet[6	senet[6	NOUN
ajst-322	41	6	]	]	PUNCT
ajst-322	41	7	is	be	AUX
ajst-322	41	8	composed	compose	VERB
ajst-322	41	9	of	of	ADP
ajst-322	41	10	two	two	NUM
ajst-322	41	11	operations	operation	NOUN
ajst-322	41	12	squeeze	squeeze	NOUN
ajst-322	41	13	and	and	CCONJ
ajst-322	41	14	excitation	excitation	NOUN
ajst-322	41	15	.	.	PUNCT
ajst-322	42	1	firstly	firstly	ADV
ajst-322	42	2	,	,	PUNCT
ajst-322	42	3	squeeze	squeeze	NOUN
ajst-322	42	4	is	be	AUX
ajst-322	42	5	used	use	VERB
ajst-322	42	6	to	to	PART
ajst-322	42	7	compress	compress	VERB
ajst-322	42	8	from	from	ADP
ajst-322	42	9	the	the	DET
ajst-322	42	10	spatial	spatial	ADJ
ajst-322	42	11	dimension	dimension	NOUN
ajst-322	42	12	.	.	PUNCT
ajst-322	43	1	since	since	SCONJ
ajst-322	43	2	the	the	DET
ajst-322	43	3	convolution	convolution	NOUN
ajst-322	43	4	operation	operation	NOUN
ajst-322	43	5	is	be	AUX
ajst-322	43	6	carried	carry	VERB
ajst-322	43	7	out	out	ADP
ajst-322	43	8	in	in	ADP
ajst-322	43	9	the	the	DET
ajst-322	43	10	local	local	ADJ
ajst-322	43	11	area	area	NOUN
ajst-322	43	12	,	,	PUNCT
ajst-322	43	13	the	the	DET
ajst-322	43	14	output	output	NOUN
ajst-322	43	15	features	feature	NOUN
ajst-322	43	16	can	can	AUX
ajst-322	43	17	not	not	PART
ajst-322	43	18	use	use	VERB
ajst-322	43	19	the	the	DET
ajst-322	43	20	information	information	NOUN
ajst-322	43	21	outside	outside	ADP
ajst-322	43	22	the	the	DET
ajst-322	43	23	local	local	ADJ
ajst-322	43	24	area	area	NOUN
ajst-322	43	25	.	.	PUNCT
ajst-322	44	1	this	this	DET
ajst-322	44	2	problem	problem	NOUN
ajst-322	44	3	is	be	AUX
ajst-322	44	4	more	more	ADV
ajst-322	44	5	serious	serious	ADJ
ajst-322	44	6	for	for	ADP
ajst-322	44	7	the	the	DET
ajst-322	44	8	underlying	underlie	VERB
ajst-322	44	9	network	network	NOUN
ajst-322	44	10	.	.	PUNCT
ajst-322	45	1	so	so	ADV
ajst-322	45	2	the	the	DET
ajst-322	45	3	squeeze	squeeze	NOUN
ajst-322	45	4	operation	operation	NOUN
ajst-322	45	5	compresses	compress	VERB
ajst-322	45	6	the	the	DET
ajst-322	45	7	global	global	ADJ
ajst-322	45	8	spatial	spatial	ADJ
ajst-322	45	9	feature	feature	NOUN
ajst-322	45	10	on	on	ADP
ajst-322	45	11	a	a	DET
ajst-322	45	12	channel	channel	NOUN
ajst-322	45	13	into	into	ADP
ajst-322	45	14	a	a	DET
ajst-322	45	15	global	global	ADJ
ajst-322	45	16	feature	feature	NOUN
ajst-322	45	17	descriptor	descriptor	NOUN
ajst-322	45	18	,	,	PUNCT
ajst-322	45	19	that	that	ADV
ajst-322	45	20	is	is	ADV
ajst-322	45	21	,	,	PUNCT
ajst-322	45	22	the	the	DET
ajst-322	45	23	h	h	NOUN
ajst-322	45	24	*	*	PROPN
ajst-322	45	25	w	w	PROPN
ajst-322	45	26	*	*	PUNCT
ajst-322	45	27	c	c	NOUN
ajst-322	45	28	feature	feature	NOUN
ajst-322	45	29	into	into	ADP
ajst-322	45	30	a	a	DET
ajst-322	45	31	1	1	NUM
ajst-322	45	32	*	*	SYM
ajst-322	45	33	1	1	NUM
ajst-322	45	34	*	*	NOUN
ajst-322	45	35	c	c	NOUN
ajst-322	45	36	feature	feature	NOUN
ajst-322	45	37	,	,	PUNCT
ajst-322	45	38	using	use	VERB
ajst-322	45	39	the	the	DET
ajst-322	45	40	statistics	statistic	NOUN
ajst-322	45	41	generated	generate	VERB
ajst-322	45	42	by	by	ADP
ajst-322	45	43	the	the	DET
ajst-322	45	44	global	global	ADJ
ajst-322	45	45	average	average	ADJ
ajst-322	45	46	pooling	pool	VERB
ajst-322	45	47	operation	operation	NOUN
ajst-322	45	48	.	.	PUNCT
ajst-322	46	1	to	to	PART
ajst-322	46	2	take	take	VERB
ajst-322	46	3	advantage	advantage	NOUN
ajst-322	46	4	of	of	ADP
ajst-322	46	5	the	the	DET
ajst-322	46	6	global	global	ADJ
ajst-322	46	7	description	description	NOUN
ajst-322	46	8	characteristics	characteristic	NOUN
ajst-322	46	9	obtained	obtain	VERB
ajst-322	46	10	by	by	ADP
ajst-322	46	11	the	the	DET
ajst-322	46	12	squeeze	squeeze	NOUN
ajst-322	46	13	operation	operation	NOUN
ajst-322	46	14	,	,	PUNCT
ajst-322	46	15	the	the	DET
ajst-322	46	16	nonlinear	nonlinear	ADJ
ajst-322	46	17	relationship	relationship	NOUN
ajst-322	46	18	between	between	ADP
ajst-322	46	19	the	the	DET
ajst-322	46	20	different	different	ADJ
ajst-322	46	21	channels	channel	NOUN
ajst-322	46	22	is	be	AUX
ajst-322	46	23	used	use	VERB
ajst-322	46	24	and	and	CCONJ
ajst-322	46	25	the	the	DET
ajst-322	46	26	weighting	weighting	NOUN
ajst-322	46	27	is	be	AUX
ajst-322	46	28	generated	generate	VERB
ajst-322	46	29	for	for	ADP
ajst-322	46	30	each	each	DET
ajst-322	46	31	channel	channel	NOUN
ajst-322	46	32	.	.	PUNCT
ajst-322	47	1	in	in	ADP
ajst-322	47	2	order	order	NOUN
ajst-322	47	3	to	to	PART
ajst-322	47	4	limit	limit	VERB
ajst-322	47	5	the	the	DET
ajst-322	47	6	complexity	complexity	NOUN
ajst-322	47	7	of	of	ADP
ajst-322	47	8	the	the	DET
ajst-322	47	9	model	model	NOUN
ajst-322	47	10	and	and	CCONJ
ajst-322	47	11	improve	improve	VERB
ajst-322	47	12	the	the	DET
ajst-322	47	13	generalization	generalization	NOUN
ajst-322	47	14	ability	ability	NOUN
ajst-322	47	15	,	,	PUNCT
ajst-322	47	16	a	a	DET
ajst-322	47	17	bottleneck	bottleneck	NOUN
ajst-322	47	18	structure	structure	NOUN
ajst-322	47	19	composed	compose	VERB
ajst-322	47	20	of	of	ADP
ajst-322	47	21	two	two	NUM
ajst-322	47	22	fully	fully	ADV
ajst-322	47	23	connected	connected	ADJ
ajst-322	47	24	layers	layer	NOUN
ajst-322	47	25	was	be	AUX
ajst-322	47	26	adopted	adopt	VERB
ajst-322	47	27	.	.	PUNCT
ajst-322	48	1	the	the	DET
ajst-322	48	2	first	first	ADJ
ajst-322	48	3	fully	fully	ADV
ajst-322	48	4	connected	connect	VERB
ajst-322	48	5	layer	layer	NOUN
ajst-322	48	6	was	be	AUX
ajst-322	48	7	used	use	VERB
ajst-322	48	8	for	for	ADP
ajst-322	48	9	dimensionality	dimensionality	NOUN
ajst-322	48	10	reduction	reduction	NOUN
ajst-322	48	11	and	and	CCONJ
ajst-322	48	12	relu	relu	NOUN
ajst-322	48	13	activation	activation	NOUN
ajst-322	48	14	,	,	PUNCT
ajst-322	48	15	and	and	CCONJ
ajst-322	48	16	then	then	ADV
ajst-322	48	17	the	the	DET
ajst-322	48	18	second	second	ADJ
ajst-322	48	19	fully	fully	ADV
ajst-322	48	20	connected	connect	VERB
ajst-322	48	21	layer	layer	NOUN
ajst-322	48	22	was	be	AUX
ajst-322	48	23	used	use	VERB
ajst-322	48	24	to	to	PART
ajst-322	48	25	restore	restore	VERB
ajst-322	48	26	the	the	DET
ajst-322	48	27	original	original	ADJ
ajst-322	48	28	dimension	dimension	NOUN
ajst-322	48	29	.	.	PUNCT
ajst-322	49	1	finally	finally	ADV
ajst-322	49	2	,	,	PUNCT
ajst-322	49	3	the	the	DET
ajst-322	49	4	sigmoid	sigmoid	NOUN
ajst-322	49	5	function	function	NOUN
ajst-322	49	6	is	be	AUX
ajst-322	49	7	used	use	VERB
ajst-322	49	8	to	to	PART
ajst-322	49	9	obtain	obtain	VERB
ajst-322	49	10	the	the	DET
ajst-322	49	11	normalized	normalize	VERB
ajst-322	49	12	weight	weight	NOUN
ajst-322	49	13	,	,	PUNCT
ajst-322	49	14	and	and	CCONJ
ajst-322	49	15	the	the	DET
ajst-322	49	16	final	final	ADJ
ajst-322	49	17	feature	feature	NOUN
ajst-322	49	18	is	be	AUX
ajst-322	49	19	obtained	obtain	VERB
ajst-322	49	20	by	by	ADP
ajst-322	49	21	multiplying	multiply	VERB
ajst-322	49	22	the	the	DET
ajst-322	49	23	weight	weight	NOUN
ajst-322	49	24	by	by	ADP
ajst-322	49	25	the	the	DET
ajst-322	49	26	original	original	ADJ
ajst-322	49	27	feature	feature	NOUN
ajst-322	49	28	.	.	PUNCT
ajst-322	50	1	3	3	X
ajst-322	50	2	.	.	NUM
ajst-322	50	3	improved	improve	VERB
ajst-322	50	4	mask	mask	NOUN
ajst-322	50	5	r	r	NOUN
ajst-322	50	6	-	-	PUNCT
ajst-322	50	7	cnn	cnn	PROPN
ajst-322	50	8	3.1	3.1	NUM
ajst-322	50	9	.	.	PUNCT
ajst-322	51	1	put	put	VERB
ajst-322	51	2	se	se	ADV
ajst-322	51	3	into	into	ADP
ajst-322	51	4	mask	mask	NOUN
ajst-322	51	5	r	r	PROPN
ajst-322	51	6	-	-	PUNCT
ajst-322	51	7	cnn	cnn	PROPN
ajst-322	51	8	senet	senet	NOUN
ajst-322	51	9	construction	construction	NOUN
ajst-322	51	10	is	be	AUX
ajst-322	51	11	very	very	ADV
ajst-322	51	12	simple	simple	ADJ
ajst-322	51	13	,	,	PUNCT
ajst-322	51	14	does	do	AUX
ajst-322	51	15	not	not	PART
ajst-322	51	16	need	need	VERB
ajst-322	51	17	to	to	PART
ajst-322	51	18	introduce	introduce	VERB
ajst-322	51	19	additional	additional	ADJ
ajst-322	51	20	new	new	ADJ
ajst-322	51	21	functions	function	NOUN
ajst-322	51	22	or	or	CCONJ
ajst-322	51	23	convolution	convolution	NOUN
ajst-322	51	24	layer	layer	NOUN
ajst-322	51	25	,	,	PUNCT
ajst-322	51	26	and	and	CCONJ
ajst-322	51	27	has	have	VERB
ajst-322	51	28	good	good	ADJ
ajst-322	51	29	characteristics	characteristic	NOUN
ajst-322	51	30	in	in	ADP
ajst-322	51	31	increasing	increase	VERB
ajst-322	51	32	the	the	DET
ajst-322	51	33	computational	computational	ADJ
ajst-322	51	34	complexity	complexity	NOUN
ajst-322	51	35	.	.	PUNCT
ajst-322	52	1	theoretically	theoretically	ADV
ajst-322	52	2	,	,	PUNCT
ajst-322	52	3	the	the	DET
ajst-322	52	4	additional	additional	ADJ
ajst-322	52	5	computation	computation	NOUN
ajst-322	52	6	amount	amount	NOUN
ajst-322	52	7	increased	increase	VERB
ajst-322	52	8	by	by	ADP
ajst-322	52	9	senet	senet	NOUN
ajst-322	52	10	is	be	AUX
ajst-322	52	11	less	less	ADJ
ajst-322	52	12	than	than	ADP
ajst-322	52	13	1	1	NUM
ajst-322	52	14	%	%	NOUN
ajst-322	52	15	.	.	PUNCT
ajst-322	53	1	therefore	therefore	ADV
ajst-322	53	2	,	,	PUNCT
ajst-322	53	3	the	the	DET
ajst-322	53	4	introduction	introduction	NOUN
ajst-322	53	5	of	of	ADP
ajst-322	53	6	this	this	DET
ajst-322	53	7	structure	structure	NOUN
ajst-322	53	8	into	into	ADP
ajst-322	53	9	the	the	DET
ajst-322	53	10	existing	exist	VERB
ajst-322	53	11	network	network	NOUN
ajst-322	53	12	structure	structure	NOUN
ajst-322	53	13	is	be	AUX
ajst-322	53	14	very	very	ADV
ajst-322	53	15	friendly	friendly	ADJ
ajst-322	53	16	to	to	ADP
ajst-322	53	17	the	the	DET
ajst-322	53	18	increase	increase	NOUN
ajst-322	53	19	of	of	ADP
ajst-322	53	20	parameters	parameter	NOUN
ajst-322	53	21	and	and	CCONJ
ajst-322	53	22	computation	computation	NOUN
ajst-322	53	23	.	.	PUNCT
ajst-322	54	1	therefore	therefore	ADV
ajst-322	54	2	,	,	PUNCT
ajst-322	54	3	the	the	DET
ajst-322	54	4	channel	channel	NOUN
ajst-322	54	5	attention	attention	NOUN
ajst-322	54	6	mechanism	mechanism	NOUN
ajst-322	54	7	is	be	AUX
ajst-322	54	8	added	add	VERB
ajst-322	54	9	to	to	ADP
ajst-322	54	10	the	the	DET
ajst-322	54	11	trunk	trunk	NOUN
ajst-322	54	12	network	network	NOUN
ajst-322	54	13	in	in	ADP
ajst-322	54	14	this	this	DET
ajst-322	54	15	task	task	NOUN
ajst-322	54	16	,	,	PUNCT
ajst-322	54	17	combined	combine	VERB
ajst-322	54	18	with	with	ADP
ajst-322	54	19	the	the	DET
ajst-322	54	20	resnet	resnet	NOUN
ajst-322	54	21	module	module	NOUN
ajst-322	54	22	structure	structure	NOUN
ajst-322	54	23	of	of	ADP
ajst-322	54	24	se	se	PROPN
ajst-322	54	25	.	.	PROPN
ajst-322	54	26	3.2	3.2	NUM
ajst-322	54	27	.	.	PUNCT
ajst-322	55	1	rpn	rpn	PROPN
ajst-322	55	2	adjustment	adjustment	NOUN
ajst-322	55	3	rpn	rpn	PROPN
ajst-322	55	4	generates	generate	VERB
ajst-322	55	5	candidate	candidate	NOUN
ajst-322	55	6	boxes	box	NOUN
ajst-322	55	7	of	of	ADP
ajst-322	55	8	9	9	NUM
ajst-322	55	9	specifications	specification	NOUN
ajst-322	55	10	for	for	ADP
ajst-322	55	11	each	each	DET
ajst-322	55	12	position	position	NOUN
ajst-322	55	13	on	on	ADP
ajst-322	55	14	the	the	DET
ajst-322	55	15	shared	share	VERB
ajst-322	55	16	feature	feature	NOUN
ajst-322	55	17	map	map	NOUN
ajst-322	55	18	.	.	PUNCT
ajst-322	56	1	the	the	DET
ajst-322	56	2	length	length	NOUN
ajst-322	56	3	to	to	PART
ajst-322	56	4	width	width	VERB
ajst-322	56	5	ratio	ratio	NOUN
ajst-322	56	6	is	be	AUX
ajst-322	56	7	1:1	1:1	NUM
ajst-322	56	8	,	,	PUNCT
ajst-322	56	9	1:2	1:2	NUM
ajst-322	56	10	,	,	PUNCT
ajst-322	56	11	2:1	2:1	NUM
ajst-322	56	12	,	,	PUNCT
ajst-322	56	13	and	and	CCONJ
ajst-322	56	14	the	the	DET
ajst-322	56	15	area	area	NOUN
ajst-322	56	16	is	be	AUX
ajst-322	56	17	128×128	128×128	NUM
ajst-322	56	18	,	,	PUNCT
ajst-322	56	19	256×256	256×256	NUM
ajst-322	56	20	,	,	PUNCT
ajst-322	56	21	and	and	CCONJ
ajst-322	56	22	512×512	512×512	NUM
ajst-322	56	23	.	.	PUNCT
ajst-322	57	1	a	a	DET
ajst-322	57	2	total	total	NOUN
ajst-322	57	3	of	of	ADP
ajst-322	57	4	9	9	NUM
ajst-322	57	5	types	type	NOUN
ajst-322	57	6	of	of	ADP
ajst-322	57	7	candidate	candidate	NOUN
ajst-322	57	8	boxes	box	NOUN
ajst-322	57	9	are	be	AUX
ajst-322	57	10	generated	generate	VERB
ajst-322	57	11	by	by	ADP
ajst-322	57	12	the	the	DET
ajst-322	57	13	combination	combination	NOUN
ajst-322	57	14	of	of	ADP
ajst-322	57	15	length	length	NOUN
ajst-322	57	16	to	to	PART
ajst-322	57	17	width	width	VERB
ajst-322	57	18	ratio	ratio	NOUN
ajst-322	57	19	and	and	CCONJ
ajst-322	57	20	area	area	NOUN
ajst-322	57	21	.	.	PUNCT
ajst-322	58	1	considering	consider	VERB
ajst-322	58	2	the	the	DET
ajst-322	58	3	size	size	NOUN
ajst-322	58	4	and	and	CCONJ
ajst-322	58	5	proportion	proportion	NOUN
ajst-322	58	6	of	of	ADP
ajst-322	58	7	power	power	NOUN
ajst-322	58	8	equipment	equipment	NOUN
ajst-322	58	9	objects	object	NOUN
ajst-322	58	10	in	in	ADP
ajst-322	58	11	this	this	DET
ajst-322	58	12	task	task	NOUN
ajst-322	58	13	,	,	PUNCT
ajst-322	58	14	the	the	DET
ajst-322	58	15	original	original	ADJ
ajst-322	58	16	aspect	aspect	NOUN
ajst-322	58	17	ratio	ratio	NOUN
ajst-322	58	18	was	be	AUX
ajst-322	58	19	adjusted	adjust	VERB
ajst-322	58	20	to	to	ADP
ajst-322	58	21	1:1	1:1	NUM
ajst-322	58	22	,	,	PUNCT
ajst-322	58	23	1:3	1:3	NUM
ajst-322	58	24	and	and	CCONJ
ajst-322	58	25	3:1	3:1	NUM
ajst-322	58	26	to	to	PART
ajst-322	58	27	achieve	achieve	VERB
ajst-322	58	28	a	a	DET
ajst-322	58	29	more	more	ADV
ajst-322	58	30	accurate	accurate	ADJ
ajst-322	58	31	distinction	distinction	NOUN
ajst-322	58	32	between	between	ADP
ajst-322	58	33	foreground	foreground	NOUN
ajst-322	58	34	and	and	CCONJ
ajst-322	58	35	background	background	NOUN
ajst-322	58	36	.	.	PUNCT
ajst-322	59	1	4	4	X
ajst-322	59	2	.	.	X
ajst-322	59	3	experiments	experiment	NOUN
ajst-322	59	4	4.1	4.1	NUM
ajst-322	59	5	.	.	PUNCT
ajst-322	60	1	experiment	experiment	NOUN
ajst-322	60	2	platform	platform	NOUN
ajst-322	60	3	the	the	DET
ajst-322	60	4	following	following	NOUN
ajst-322	60	5	describes	describe	VERB
ajst-322	60	6	the	the	DET
ajst-322	60	7	construction	construction	NOUN
ajst-322	60	8	of	of	ADP
ajst-322	60	9	the	the	DET
ajst-322	60	10	experimental	experimental	ADJ
ajst-322	60	11	environment	environment	NOUN
ajst-322	60	12	,	,	PUNCT
ajst-322	60	13	including	include	VERB
ajst-322	60	14	the	the	DET
ajst-322	60	15	development	development	NOUN
ajst-322	60	16	language	language	NOUN
ajst-322	60	17	,	,	PUNCT
ajst-322	60	18	development	development	NOUN
ajst-322	60	19	environment	environment	NOUN
ajst-322	60	20	and	and	CCONJ
ajst-322	60	21	deep	deep	ADJ
ajst-322	60	22	learning	learning	NOUN
ajst-322	60	23	framework	framework	NOUN
ajst-322	60	24	.	.	PUNCT
ajst-322	61	1	in	in	ADP
ajst-322	61	2	this	this	DET
ajst-322	61	3	experiment	experiment	NOUN
ajst-322	61	4	,	,	PUNCT
ajst-322	61	5	python3.7	python3.7	NOUN
ajst-322	61	6	was	be	AUX
ajst-322	61	7	used	use	VERB
ajst-322	61	8	as	as	ADP
ajst-322	61	9	the	the	DET
ajst-322	61	10	development	development	NOUN
ajst-322	61	11	language	language	NOUN
ajst-322	61	12	,	,	PUNCT
ajst-322	61	13	python	python	NOUN
ajst-322	61	14	numpy	numpy	NOUN
ajst-322	61	15	,	,	PUNCT
ajst-322	61	16	opencv	opencv	PROPN
ajst-322	61	17	,	,	PUNCT
ajst-322	61	18	matplotlib	matplotlib	PROPN
ajst-322	61	19	and	and	CCONJ
ajst-322	61	20	other	other	ADJ
ajst-322	61	21	third	third	ADJ
ajst-322	61	22	-	-	PUNCT
ajst-322	61	23	party	party	NOUN
ajst-322	61	24	libraries	library	NOUN
ajst-322	61	25	were	be	AUX
ajst-322	61	26	installed	instal	VERB
ajst-322	61	27	,	,	PUNCT
ajst-322	61	28	the	the	DET
ajst-322	61	29	operating	operating	NOUN
ajst-322	61	30	system	system	NOUN
ajst-322	61	31	was	be	AUX
ajst-322	61	32	ubuntu18.04	ubuntu18.04	ADJ
ajst-322	61	33	,	,	PUNCT
ajst-322	61	34	and	and	CCONJ
ajst-322	61	35	pytorch	pytorch	NOUN
ajst-322	61	36	was	be	AUX
ajst-322	61	37	used	use	VERB
ajst-322	61	38	as	as	ADP
ajst-322	61	39	the	the	DET
ajst-322	61	40	deep	deep	ADJ
ajst-322	61	41	learning	learning	NOUN
ajst-322	61	42	framework	framework	NOUN
ajst-322	61	43	.	.	PUNCT
ajst-322	62	1	considering	consider	VERB
ajst-322	62	2	that	that	SCONJ
ajst-322	62	3	the	the	DET
ajst-322	62	4	training	training	NOUN
ajst-322	62	5	process	process	NOUN
ajst-322	62	6	of	of	ADP
ajst-322	62	7	deep	deep	ADJ
ajst-322	62	8	learning	learning	NOUN
ajst-322	62	9	requires	require	VERB
ajst-322	62	10	high	high	ADJ
ajst-322	62	11	gpu	gpu	NOUN
ajst-322	62	12	memory	memory	NOUN
ajst-322	62	13	and	and	CCONJ
ajst-322	62	14	computing	computing	NOUN
ajst-322	62	15	speed	speed	NOUN
ajst-322	62	16	,	,	PUNCT
ajst-322	62	17	nvidia	nvidia	PROPN
ajst-322	62	18	professional	professional	PROPN
ajst-322	62	19	computing	computing	NOUN
ajst-322	62	20	graphics	graphic	NOUN
ajst-322	62	21	card	card	NOUN
ajst-322	62	22	configured	configure	VERB
ajst-322	62	23	with	with	ADP
ajst-322	62	24	compute	compute	NOUN
ajst-322	62	25	unified	unify	VERB
ajst-322	62	26	device	device	NOUN
ajst-322	62	27	architecture	architecture	NOUN
ajst-322	62	28	(	(	PUNCT
ajst-322	62	29	cuda	cuda	NOUN
ajst-322	62	30	)	)	PUNCT
ajst-322	62	31	is	be	AUX
ajst-322	62	32	used	use	VERB
ajst-322	62	33	to	to	PART
ajst-322	62	34	accelerate	accelerate	VERB
ajst-322	62	35	the	the	DET
ajst-322	62	36	training	training	NOUN
ajst-322	62	37	of	of	ADP
ajst-322	62	38	the	the	DET
ajst-322	62	39	model	model	NOUN
ajst-322	62	40	.	.	PUNCT
ajst-322	63	1	62	62	NUM
ajst-322	63	2	4.2	4.2	NUM
ajst-322	63	3	.	.	PUNCT
ajst-322	64	1	data	datum	NOUN
ajst-322	64	2	set	set	VERB
ajst-322	64	3	the	the	DET
ajst-322	64	4	first	first	ADJ
ajst-322	64	5	step	step	NOUN
ajst-322	64	6	is	be	AUX
ajst-322	64	7	to	to	PART
ajst-322	64	8	obtain	obtain	VERB
ajst-322	64	9	original	original	ADJ
ajst-322	64	10	data	datum	NOUN
ajst-322	64	11	,	,	PUNCT
ajst-322	64	12	use	use	VERB
ajst-322	64	13	infrared	infrared	ADJ
ajst-322	64	14	thermal	thermal	ADJ
ajst-322	64	15	imager	imager	NOUN
ajst-322	64	16	to	to	PART
ajst-322	64	17	take	take	VERB
ajst-322	64	18	infrared	infrared	ADJ
ajst-322	64	19	photos	photo	NOUN
ajst-322	64	20	of	of	ADP
ajst-322	64	21	power	power	NOUN
ajst-322	64	22	equipment	equipment	NOUN
ajst-322	64	23	,	,	PUNCT
ajst-322	64	24	and	and	CCONJ
ajst-322	64	25	screen	screen	VERB
ajst-322	64	26	out	out	ADP
ajst-322	64	27	clearer	clear	ADJ
ajst-322	64	28	pictures	picture	NOUN
ajst-322	64	29	that	that	PRON
ajst-322	64	30	meet	meet	VERB
ajst-322	64	31	requirements	requirement	NOUN
ajst-322	64	32	.	.	PUNCT
ajst-322	65	1	in	in	ADP
ajst-322	65	2	the	the	DET
ajst-322	65	3	second	second	ADJ
ajst-322	65	4	step	step	NOUN
ajst-322	65	5	,	,	PUNCT
ajst-322	65	6	labelme	labelme	ADJ
ajst-322	65	7	software	software	NOUN
ajst-322	65	8	is	be	AUX
ajst-322	65	9	used	use	VERB
ajst-322	65	10	to	to	PART
ajst-322	65	11	label	label	VERB
ajst-322	65	12	power	power	NOUN
ajst-322	65	13	equipment	equipment	NOUN
ajst-322	65	14	.	.	PUNCT
ajst-322	66	1	the	the	DET
ajst-322	66	2	photos	photo	NOUN
ajst-322	66	3	screened	screen	VERB
ajst-322	66	4	in	in	ADP
ajst-322	66	5	the	the	DET
ajst-322	66	6	first	first	ADJ
ajst-322	66	7	step	step	NOUN
ajst-322	66	8	mainly	mainly	ADV
ajst-322	66	9	include	include	VERB
ajst-322	66	10	circuit	circuit	NOUN
ajst-322	66	11	breakers	breaker	NOUN
ajst-322	66	12	and	and	CCONJ
ajst-322	66	13	disconnecting	disconnect	VERB
ajst-322	66	14	switches	switch	NOUN
ajst-322	66	15	.	.	PUNCT
ajst-322	67	1	after	after	ADP
ajst-322	67	2	labeling	label	VERB
ajst-322	67	3	with	with	ADP
ajst-322	67	4	labelme	labelme	NOUN
ajst-322	67	5	,	,	PUNCT
ajst-322	67	6	a	a	DET
ajst-322	67	7	.json	.json	NOUN
ajst-322	67	8	file	file	NOUN
ajst-322	67	9	corresponding	correspond	VERB
ajst-322	67	10	to	to	ADP
ajst-322	67	11	the	the	DET
ajst-322	67	12	image	image	NOUN
ajst-322	67	13	can	can	AUX
ajst-322	67	14	be	be	AUX
ajst-322	67	15	exported	export	VERB
ajst-322	67	16	.	.	PUNCT
ajst-322	68	1	the	the	DET
ajst-322	68	2	content	content	NOUN
ajst-322	68	3	of	of	ADP
ajst-322	68	4	the	the	DET
ajst-322	68	5	file	file	NOUN
ajst-322	68	6	is	be	AUX
ajst-322	68	7	the	the	DET
ajst-322	68	8	manually	manually	ADV
ajst-322	68	9	labeled	label	VERB
ajst-322	68	10	point	point	NOUN
ajst-322	68	11	coordinates	coordinate	NOUN
ajst-322	68	12	and	and	CCONJ
ajst-322	68	13	the	the	DET
ajst-322	68	14	object	object	NOUN
ajst-322	68	15	category	category	NOUN
ajst-322	68	16	,	,	PUNCT
ajst-322	68	17	which	which	PRON
ajst-322	68	18	will	will	AUX
ajst-322	68	19	be	be	AUX
ajst-322	68	20	used	use	VERB
ajst-322	68	21	for	for	ADP
ajst-322	68	22	the	the	DET
ajst-322	68	23	training	training	NOUN
ajst-322	68	24	of	of	ADP
ajst-322	68	25	model	model	NOUN
ajst-322	68	26	weight	weight	NOUN
ajst-322	68	27	.	.	PUNCT
ajst-322	69	1	in	in	ADP
ajst-322	69	2	the	the	DET
ajst-322	69	3	third	third	ADJ
ajst-322	69	4	step	step	NOUN
ajst-322	69	5	,	,	PUNCT
ajst-322	69	6	use	use	VERB
ajst-322	69	7	the	the	DET
ajst-322	69	8	images	image	NOUN
ajst-322	69	9	and	and	CCONJ
ajst-322	69	10	.json	.json	NOUN
ajst-322	69	11	files	file	NOUN
ajst-322	69	12	obtained	obtain	VERB
ajst-322	69	13	in	in	ADP
ajst-322	69	14	the	the	DET
ajst-322	69	15	second	second	ADJ
ajst-322	69	16	step	step	NOUN
ajst-322	69	17	to	to	PART
ajst-322	69	18	convert	convert	VERB
ajst-322	69	19	a	a	DET
ajst-322	69	20	dataset	dataset	NOUN
ajst-322	69	21	called	call	VERB
ajst-322	69	22	coco	coco	PROPN
ajst-322	69	23	format	format	NOUN
ajst-322	69	24	.	.	PUNCT
ajst-322	70	1	there	there	PRON
ajst-322	70	2	are	be	VERB
ajst-322	70	3	1200	1200	NUM
ajst-322	70	4	data	datum	NOUN
ajst-322	70	5	sets	set	NOUN
ajst-322	70	6	,	,	PUNCT
ajst-322	70	7	and	and	CCONJ
ajst-322	70	8	the	the	DET
ajst-322	70	9	images	image	NOUN
ajst-322	70	10	are	be	AUX
ajst-322	70	11	randomly	randomly	ADV
ajst-322	70	12	divided	divide	VERB
ajst-322	70	13	into	into	ADP
ajst-322	70	14	training	training	NOUN
ajst-322	70	15	set	set	NOUN
ajst-322	70	16	,	,	PUNCT
ajst-322	70	17	verification	verification	NOUN
ajst-322	70	18	set	set	NOUN
ajst-322	70	19	and	and	CCONJ
ajst-322	70	20	test	test	NOUN
ajst-322	70	21	set	set	VERB
ajst-322	70	22	according	accord	VERB
ajst-322	70	23	to	to	ADP
ajst-322	70	24	the	the	DET
ajst-322	70	25	number	number	NOUN
ajst-322	70	26	ratio	ratio	NOUN
ajst-322	70	27	of	of	ADP
ajst-322	70	28	10:1:1	10:1:1	NUM
ajst-322	70	29	.	.	PUNCT
ajst-322	71	1	4.3	4.3	NUM
ajst-322	71	2	.	.	PUNCT
ajst-322	71	3	model	model	NOUN
ajst-322	71	4	training	training	NOUN
ajst-322	71	5	method	method	NOUN
ajst-322	71	6	and	and	CCONJ
ajst-322	71	7	parameter	parameter	NOUN
ajst-322	71	8	setting	setting	NOUN
ajst-322	71	9	in	in	ADP
ajst-322	71	10	the	the	DET
ajst-322	71	11	training	training	NOUN
ajst-322	71	12	process	process	NOUN
ajst-322	71	13	,	,	PUNCT
ajst-322	71	14	the	the	DET
ajst-322	71	15	training	training	NOUN
ajst-322	71	16	set	set	NOUN
ajst-322	71	17	made	make	VERB
ajst-322	71	18	in	in	ADP
ajst-322	71	19	the	the	DET
ajst-322	71	20	previous	previous	ADJ
ajst-322	71	21	section	section	NOUN
ajst-322	71	22	is	be	AUX
ajst-322	71	23	used	use	VERB
ajst-322	71	24	to	to	PART
ajst-322	71	25	train	train	VERB
ajst-322	71	26	network	network	NOUN
ajst-322	71	27	parameters	parameter	NOUN
ajst-322	71	28	,	,	PUNCT
ajst-322	71	29	i.e.	i.e.	X
ajst-322	71	30	,	,	PUNCT
ajst-322	71	31	there	there	PRON
ajst-322	71	32	are	be	VERB
ajst-322	71	33	1000	1000	NUM
ajst-322	71	34	images	image	NOUN
ajst-322	71	35	in	in	ADP
ajst-322	71	36	total	total	NOUN
ajst-322	71	37	.	.	PUNCT
ajst-322	72	1	because	because	SCONJ
ajst-322	72	2	mask	mask	NOUN
ajst-322	72	3	r	r	NOUN
ajst-322	72	4	-	-	PUNCT
ajst-322	72	5	cnn	cnn	PROPN
ajst-322	72	6	requires	require	VERB
ajst-322	72	7	massive	massive	ADJ
ajst-322	72	8	data	datum	NOUN
ajst-322	72	9	for	for	ADP
ajst-322	72	10	training	training	NOUN
ajst-322	72	11	to	to	PART
ajst-322	72	12	achieve	achieve	VERB
ajst-322	72	13	excellent	excellent	ADJ
ajst-322	72	14	performance	performance	NOUN
ajst-322	72	15	,	,	PUNCT
ajst-322	72	16	the	the	DET
ajst-322	72	17	number	number	NOUN
ajst-322	72	18	of	of	ADP
ajst-322	72	19	power	power	NOUN
ajst-322	72	20	equipment	equipment	NOUN
ajst-322	72	21	infrared	infrare	VERB
ajst-322	72	22	image	image	NOUN
ajst-322	72	23	data	datum	NOUN
ajst-322	72	24	sets	set	NOUN
ajst-322	72	25	in	in	ADP
ajst-322	72	26	this	this	DET
ajst-322	72	27	paper	paper	NOUN
ajst-322	72	28	is	be	AUX
ajst-322	72	29	small	small	ADJ
ajst-322	72	30	,	,	PUNCT
ajst-322	72	31	so	so	SCONJ
ajst-322	72	32	the	the	DET
ajst-322	72	33	task	task	NOUN
ajst-322	72	34	of	of	ADP
ajst-322	72	35	this	this	DET
ajst-322	72	36	paper	paper	NOUN
ajst-322	72	37	adopts	adopt	VERB
ajst-322	72	38	the	the	DET
ajst-322	72	39	strategy	strategy	NOUN
ajst-322	72	40	of	of	ADP
ajst-322	72	41	transfer	transfer	NOUN
ajst-322	72	42	learning	learn	VERB
ajst-322	72	43	to	to	PART
ajst-322	72	44	obtain	obtain	VERB
ajst-322	72	45	the	the	DET
ajst-322	72	46	pre	pre	ADJ
ajst-322	72	47	-	-	ADJ
ajst-322	72	48	training	training	ADJ
ajst-322	72	49	model	model	NOUN
ajst-322	72	50	.	.	PUNCT
ajst-322	73	1	an	an	DET
ajst-322	73	2	epoch	epoch	NOUN
ajst-322	73	3	refers	refer	VERB
ajst-322	73	4	to	to	ADP
ajst-322	73	5	the	the	DET
ajst-322	73	6	process	process	NOUN
ajst-322	73	7	of	of	ADP
ajst-322	73	8	feeding	feed	VERB
ajst-322	73	9	all	all	DET
ajst-322	73	10	data	datum	NOUN
ajst-322	73	11	into	into	ADP
ajst-322	73	12	a	a	DET
ajst-322	73	13	model	model	NOUN
ajst-322	73	14	to	to	PART
ajst-322	73	15	complete	complete	VERB
ajst-322	73	16	a	a	DET
ajst-322	73	17	previous	previous	ADJ
ajst-322	73	18	calculation	calculation	NOUN
ajst-322	73	19	and	and	CCONJ
ajst-322	73	20	back	back	ADJ
ajst-322	73	21	propagation	propagation	NOUN
ajst-322	73	22	.	.	PUNCT
ajst-322	74	1	in	in	ADP
ajst-322	74	2	this	this	DET
ajst-322	74	3	task	task	NOUN
ajst-322	74	4	,	,	PUNCT
ajst-322	74	5	each	each	DET
ajst-322	74	6	epoch	epoch	NOUN
ajst-322	74	7	is	be	AUX
ajst-322	74	8	trained	train	VERB
ajst-322	74	9	on	on	ADP
ajst-322	74	10	1000	1000	NUM
ajst-322	74	11	images	image	NOUN
ajst-322	74	12	in	in	ADP
ajst-322	74	13	the	the	DET
ajst-322	74	14	training	training	NOUN
ajst-322	74	15	set	set	NOUN
ajst-322	74	16	.	.	PUNCT
ajst-322	75	1	the	the	DET
ajst-322	75	2	initial	initial	ADJ
ajst-322	75	3	value	value	NOUN
ajst-322	75	4	of	of	ADP
ajst-322	75	5	the	the	DET
ajst-322	75	6	learning	learning	NOUN
ajst-322	75	7	rate	rate	NOUN
ajst-322	75	8	was	be	AUX
ajst-322	75	9	0.001	0.001	NUM
ajst-322	75	10	,	,	PUNCT
ajst-322	75	11	the	the	DET
ajst-322	75	12	batch	batch	NOUN
ajst-322	75	13	size	size	NOUN
ajst-322	75	14	was	be	AUX
ajst-322	75	15	2	2	NUM
ajst-322	75	16	,	,	PUNCT
ajst-322	75	17	the	the	DET
ajst-322	75	18	step	step	NOUN
ajst-322	75	19	size	size	NOUN
ajst-322	75	20	of	of	ADP
ajst-322	75	21	each	each	DET
ajst-322	75	22	epoch	epoch	NOUN
ajst-322	75	23	was	be	AUX
ajst-322	75	24	1000	1000	NUM
ajst-322	75	25	,	,	PUNCT
ajst-322	75	26	and	and	CCONJ
ajst-322	75	27	the	the	DET
ajst-322	75	28	momentum	momentum	NOUN
ajst-322	75	29	was	be	AUX
ajst-322	75	30	0.9	0.9	NUM
ajst-322	75	31	.	.	PUNCT
ajst-322	76	1	during	during	ADP
ajst-322	76	2	the	the	DET
ajst-322	76	3	training	training	NOUN
ajst-322	76	4	,	,	PUNCT
ajst-322	76	5	adam	adam	PROPN
ajst-322	76	6	optimizer	optimizer	NOUN
ajst-322	76	7	is	be	AUX
ajst-322	76	8	used	use	VERB
ajst-322	76	9	to	to	PART
ajst-322	76	10	update	update	VERB
ajst-322	76	11	the	the	DET
ajst-322	76	12	parameters	parameter	NOUN
ajst-322	76	13	in	in	ADP
ajst-322	76	14	the	the	DET
ajst-322	76	15	model	model	NOUN
ajst-322	76	16	.	.	PUNCT
ajst-322	77	1	this	this	DET
ajst-322	77	2	method	method	NOUN
ajst-322	77	3	updates	update	VERB
ajst-322	77	4	the	the	DET
ajst-322	77	5	network	network	NOUN
ajst-322	77	6	parameters	parameter	NOUN
ajst-322	77	7	by	by	ADP
ajst-322	77	8	randomly	randomly	ADV
ajst-322	77	9	selecting	select	VERB
ajst-322	77	10	the	the	DET
ajst-322	77	11	image	image	NOUN
ajst-322	77	12	gradient	gradient	NOUN
ajst-322	77	13	.	.	PUNCT
ajst-322	78	1	compared	compare	VERB
ajst-322	78	2	with	with	ADP
ajst-322	78	3	the	the	DET
ajst-322	78	4	random	random	ADJ
ajst-322	78	5	gradient	gradient	ADJ
ajst-322	78	6	descent	descent	NOUN
ajst-322	78	7	algorithm	algorithm	NOUN
ajst-322	78	8	(	(	PUNCT
ajst-322	78	9	sgd	sgd	PROPN
ajst-322	78	10	)	)	PUNCT
ajst-322	78	11	,	,	PUNCT
ajst-322	78	12	it	it	PRON
ajst-322	78	13	can	can	AUX
ajst-322	78	14	automatically	automatically	ADV
ajst-322	78	15	adjust	adjust	VERB
ajst-322	78	16	the	the	DET
ajst-322	78	17	learning	learning	NOUN
ajst-322	78	18	rate	rate	NOUN
ajst-322	78	19	and	and	CCONJ
ajst-322	78	20	has	have	VERB
ajst-322	78	21	better	well	ADJ
ajst-322	78	22	performance	performance	NOUN
ajst-322	78	23	.	.	PUNCT
ajst-322	79	1	in	in	ADP
ajst-322	79	2	order	order	NOUN
ajst-322	79	3	to	to	PART
ajst-322	79	4	prevent	prevent	VERB
ajst-322	79	5	parameter	parameter	NOUN
ajst-322	79	6	overfitting	overfitting	NOUN
ajst-322	79	7	,	,	PUNCT
ajst-322	79	8	the	the	DET
ajst-322	79	9	validation	validation	NOUN
ajst-322	79	10	set	set	NOUN
ajst-322	79	11	made	make	VERB
ajst-322	79	12	in	in	ADP
ajst-322	79	13	the	the	DET
ajst-322	79	14	previous	previous	ADJ
ajst-322	79	15	section	section	NOUN
ajst-322	79	16	was	be	AUX
ajst-322	79	17	used	use	VERB
ajst-322	79	18	to	to	PART
ajst-322	79	19	verify	verify	VERB
ajst-322	79	20	the	the	DET
ajst-322	79	21	performance	performance	NOUN
ajst-322	79	22	of	of	ADP
ajst-322	79	23	the	the	DET
ajst-322	79	24	model	model	NOUN
ajst-322	79	25	after	after	ADP
ajst-322	79	26	the	the	DET
ajst-322	79	27	training	training	NOUN
ajst-322	79	28	of	of	ADP
ajst-322	79	29	each	each	DET
ajst-322	79	30	epoch	epoch	NOUN
ajst-322	79	31	.	.	PUNCT
ajst-322	80	1	figure	figure	NOUN
ajst-322	80	2	2	2	NUM
ajst-322	80	3	is	be	AUX
ajst-322	80	4	the	the	DET
ajst-322	80	5	curve	curve	NOUN
ajst-322	80	6	of	of	ADP
ajst-322	80	7	loss	loss	NOUN
ajst-322	80	8	value	value	NOUN
ajst-322	80	9	in	in	ADP
ajst-322	80	10	the	the	DET
ajst-322	80	11	training	training	NOUN
ajst-322	80	12	process	process	NOUN
ajst-322	80	13	.	.	PUNCT
ajst-322	81	1	the	the	DET
ajst-322	81	2	experiment	experiment	NOUN
ajst-322	81	3	stopped	stop	VERB
ajst-322	81	4	training	training	NOUN
ajst-322	81	5	after	after	ADP
ajst-322	81	6	iterating	iterate	VERB
ajst-322	81	7	150	150	NUM
ajst-322	81	8	epochs	epoch	NOUN
ajst-322	81	9	.	.	PUNCT
ajst-322	82	1	the	the	DET
ajst-322	82	2	final	final	ADJ
ajst-322	82	3	test	test	NOUN
ajst-322	82	4	set	set	NOUN
ajst-322	82	5	is	be	AUX
ajst-322	82	6	used	use	VERB
ajst-322	82	7	to	to	PART
ajst-322	82	8	test	test	VERB
ajst-322	82	9	the	the	DET
ajst-322	82	10	final	final	ADJ
ajst-322	82	11	accuracy	accuracy	NOUN
ajst-322	82	12	of	of	ADP
ajst-322	82	13	the	the	DET
ajst-322	82	14	network	network	NOUN
ajst-322	82	15	and	and	CCONJ
ajst-322	82	16	output	output	NOUN
ajst-322	82	17	evaluation	evaluation	NOUN
ajst-322	82	18	results	result	NOUN
ajst-322	82	19	.	.	PUNCT
ajst-322	83	1	figure	figure	NOUN
ajst-322	83	2	2	2	NUM
ajst-322	83	3	.	.	PUNCT
ajst-322	83	4	loss	loss	NOUN
ajst-322	83	5	value	value	NOUN
ajst-322	83	6	during	during	ADP
ajst-322	83	7	training	train	VERB
ajst-322	83	8	4.4	4.4	NUM
ajst-322	83	9	.	.	PUNCT
ajst-322	84	1	experimental	experimental	ADJ
ajst-322	84	2	results	result	NOUN
ajst-322	84	3	and	and	CCONJ
ajst-322	84	4	analysis	analysis	NOUN
ajst-322	84	5	in	in	ADP
ajst-322	84	6	order	order	NOUN
ajst-322	84	7	to	to	PART
ajst-322	84	8	evaluate	evaluate	VERB
ajst-322	84	9	the	the	DET
ajst-322	84	10	effectiveness	effectiveness	NOUN
ajst-322	84	11	of	of	ADP
ajst-322	84	12	the	the	DET
ajst-322	84	13	improved	improved	ADJ
ajst-322	84	14	model	model	NOUN
ajst-322	84	15	in	in	ADP
ajst-322	84	16	detecting	detect	VERB
ajst-322	84	17	objects	object	NOUN
ajst-322	84	18	in	in	ADP
ajst-322	84	19	this	this	DET
ajst-322	84	20	task	task	NOUN
ajst-322	84	21	,	,	PUNCT
ajst-322	84	22	the	the	DET
ajst-322	84	23	standard	standard	PROPN
ajst-322	84	24	coco	coco	PROPN
ajst-322	84	25	index	index	NOUN
ajst-322	84	26	is	be	AUX
ajst-322	84	27	used	use	VERB
ajst-322	84	28	to	to	PART
ajst-322	84	29	measure	measure	VERB
ajst-322	84	30	the	the	DET
ajst-322	84	31	performance	performance	NOUN
ajst-322	84	32	of	of	ADP
ajst-322	84	33	the	the	DET
ajst-322	84	34	model	model	NOUN
ajst-322	84	35	.	.	PUNCT
ajst-322	85	1	as	as	SCONJ
ajst-322	85	2	described	describe	VERB
ajst-322	85	3	in	in	ADP
ajst-322	85	4	the	the	DET
ajst-322	85	5	preceding	precede	VERB
ajst-322	85	6	section	section	NOUN
ajst-322	85	7	,	,	PUNCT
ajst-322	85	8	ap50	ap50	PROPN
ajst-322	85	9	represents	represent	VERB
ajst-322	85	10	an	an	DET
ajst-322	85	11	ap	ap	NOUN
ajst-322	85	12	whose	whose	DET
ajst-322	85	13	iou	iou	NOUN
ajst-322	85	14	threshold	threshold	NOUN
ajst-322	85	15	is	be	AUX
ajst-322	85	16	set	set	VERB
ajst-322	85	17	to	to	ADP
ajst-322	85	18	0.5	0.5	NUM
ajst-322	85	19	.	.	PUNCT
ajst-322	86	1	ap75	ap75	PROPN
ajst-322	86	2	represents	represent	VERB
ajst-322	86	3	an	an	DET
ajst-322	86	4	ap	ap	NOUN
ajst-322	86	5	whose	whose	DET
ajst-322	86	6	iou	iou	NOUN
ajst-322	86	7	threshold	threshold	NOUN
ajst-322	86	8	is	be	AUX
ajst-322	86	9	set	set	VERB
ajst-322	86	10	to	to	ADP
ajst-322	86	11	0.75	0.75	NUM
ajst-322	86	12	.	.	PUNCT
ajst-322	87	1	ap	ap	PROPN
ajst-322	87	2	represents	represent	VERB
ajst-322	87	3	the	the	DET
ajst-322	87	4	average	average	ADJ
ajst-322	87	5	value	value	NOUN
ajst-322	87	6	of	of	ADP
ajst-322	87	7	aps	ap	NOUN
ajst-322	87	8	whose	whose	DET
ajst-322	87	9	iou	iou	NOUN
ajst-322	87	10	threshold	threshold	NOUN
ajst-322	87	11	ranges	range	VERB
ajst-322	87	12	from	from	ADP
ajst-322	87	13	0.5	0.5	NUM
ajst-322	87	14	to	to	PART
ajst-322	87	15	0.95	0.95	NUM
ajst-322	87	16	.	.	PUNCT
ajst-322	88	1	table	table	NOUN
ajst-322	88	2	1	1	NUM
ajst-322	88	3	is	be	AUX
ajst-322	88	4	the	the	DET
ajst-322	88	5	experimental	experimental	ADJ
ajst-322	88	6	results	result	NOUN
ajst-322	88	7	on	on	ADP
ajst-322	88	8	our	our	PRON
ajst-322	88	9	data	datum	NOUN
ajst-322	88	10	set	set	VERB
ajst-322	88	11	.	.	PUNCT
ajst-322	89	1	it	it	PRON
ajst-322	89	2	can	can	AUX
ajst-322	89	3	be	be	AUX
ajst-322	89	4	seen	see	VERB
ajst-322	89	5	that	that	SCONJ
ajst-322	89	6	the	the	DET
ajst-322	89	7	ap	ap	PROPN
ajst-322	89	8	value	value	NOUN
ajst-322	89	9	of	of	ADP
ajst-322	89	10	the	the	DET
ajst-322	89	11	mask	mask	NOUN
ajst-322	89	12	r	r	NOUN
ajst-322	89	13	-	-	PUNCT
ajst-322	89	14	cnn	cnn	PROPN
ajst-322	89	15	model	model	NOUN
ajst-322	89	16	after	after	ADP
ajst-322	89	17	the	the	DET
ajst-322	89	18	introduction	introduction	NOUN
ajst-322	89	19	of	of	ADP
ajst-322	89	20	the	the	DET
ajst-322	89	21	attention	attention	NOUN
ajst-322	89	22	mechanism	mechanism	NOUN
ajst-322	89	23	is	be	AUX
ajst-322	89	24	greatly	greatly	ADV
ajst-322	89	25	improved	improve	VERB
ajst-322	89	26	,	,	PUNCT
ajst-322	89	27	and	and	CCONJ
ajst-322	89	28	the	the	DET
ajst-322	89	29	three	three	NUM
ajst-322	89	30	ap	ap	PROPN
ajst-322	89	31	values	value	NOUN
ajst-322	89	32	are	be	AUX
ajst-322	89	33	increased	increase	VERB
ajst-322	89	34	by	by	ADP
ajst-322	89	35	1.7	1.7	NUM
ajst-322	89	36	%	%	NOUN
ajst-322	89	37	,	,	PUNCT
ajst-322	89	38	2.0	2.0	NUM
ajst-322	89	39	%	%	NOUN
ajst-322	89	40	and	and	CCONJ
ajst-322	89	41	1.8	1.8	NUM
ajst-322	89	42	%	%	NOUN
ajst-322	89	43	respectively	respectively	ADV
ajst-322	89	44	,	,	PUNCT
ajst-322	89	45	which	which	PRON
ajst-322	89	46	indicates	indicate	VERB
ajst-322	89	47	the	the	DET
ajst-322	89	48	effectiveness	effectiveness	NOUN
ajst-322	89	49	of	of	ADP
ajst-322	89	50	the	the	DET
ajst-322	89	51	attention	attention	NOUN
ajst-322	89	52	module	module	NOUN
ajst-322	89	53	introduced	introduce	VERB
ajst-322	89	54	in	in	ADP
ajst-322	89	55	this	this	DET
ajst-322	89	56	model	model	NOUN
ajst-322	89	57	,	,	PUNCT
ajst-322	89	58	with	with	ADP
ajst-322	89	59	a	a	DET
ajst-322	89	60	small	small	ADJ
ajst-322	89	61	increase	increase	NOUN
ajst-322	89	62	in	in	ADP
ajst-322	89	63	calculation	calculation	NOUN
ajst-322	89	64	but	but	CCONJ
ajst-322	89	65	a	a	DET
ajst-322	89	66	large	large	ADJ
ajst-322	89	67	improvement	improvement	NOUN
ajst-322	89	68	in	in	ADP
ajst-322	89	69	performance	performance	NOUN
ajst-322	89	70	.	.	PUNCT
ajst-322	90	1	table	table	NOUN
ajst-322	90	2	1	1	NUM
ajst-322	90	3	.	.	PUNCT
ajst-322	91	1	the	the	DET
ajst-322	91	2	experimental	experimental	ADJ
ajst-322	91	3	results	result	NOUN
ajst-322	91	4	methord	methord	NOUN
ajst-322	91	5	ap	ap	PROPN
ajst-322	92	1	ap50	ap50	PROPN
ajst-322	92	2	ap75	ap75	PROPN
ajst-322	92	3	mask	mask	NOUN
ajst-322	92	4	r	r	PROPN
ajst-322	92	5	-	-	PUNCT
ajst-322	92	6	cnn	cnn	PROPN
ajst-322	92	7	81.1	81.1	NUM
ajst-322	92	8	87.4	87.4	NUM
ajst-322	92	9	76.3	76.3	NUM
ajst-322	92	10	improved	improve	VERB
ajst-322	92	11	mask	mask	NOUN
ajst-322	92	12	r	r	NOUN
ajst-322	92	13	-	-	PUNCT
ajst-322	92	14	cnn	cnn	PROPN
ajst-322	92	15	82.8	82.8	NUM
ajst-322	92	16	89.4	89.4	NUM
ajst-322	92	17	78.1	78.1	NUM
ajst-322	92	18	5	5	NUM
ajst-322	92	19	.	.	PUNCT
ajst-322	92	20	conclusion	conclusion	NOUN
ajst-322	92	21	in	in	ADP
ajst-322	92	22	this	this	DET
ajst-322	92	23	paper	paper	NOUN
ajst-322	92	24	,	,	PUNCT
ajst-322	92	25	the	the	DET
ajst-322	92	26	mask	mask	NOUN
ajst-322	92	27	r	r	NOUN
ajst-322	92	28	-	-	PUNCT
ajst-322	92	29	cnn	cnn	PROPN
ajst-322	92	30	model	model	NOUN
ajst-322	92	31	is	be	AUX
ajst-322	92	32	introduced	introduce	VERB
ajst-322	92	33	,	,	PUNCT
ajst-322	92	34	and	and	CCONJ
ajst-322	92	35	an	an	DET
ajst-322	92	36	improved	improved	ADJ
ajst-322	92	37	method	method	NOUN
ajst-322	92	38	is	be	AUX
ajst-322	92	39	proposed	propose	VERB
ajst-322	92	40	for	for	ADP
ajst-322	92	41	the	the	DET
ajst-322	92	42	infrared	infrared	ADJ
ajst-322	92	43	image	image	NOUN
ajst-322	92	44	data	datum	NOUN
ajst-322	92	45	set	set	VERB
ajst-322	92	46	of	of	ADP
ajst-322	92	47	power	power	NOUN
ajst-322	92	48	equipment	equipment	NOUN
ajst-322	92	49	.	.	PUNCT
ajst-322	93	1	the	the	DET
ajst-322	93	2	specific	specific	ADJ
ajst-322	93	3	links	link	NOUN
ajst-322	93	4	of	of	ADP
ajst-322	93	5	the	the	DET
ajst-322	93	6	experiment	experiment	NOUN
ajst-322	93	7	are	be	AUX
ajst-322	93	8	introduced	introduce	VERB
ajst-322	93	9	,	,	PUNCT
ajst-322	93	10	including	include	VERB
ajst-322	93	11	the	the	DET
ajst-322	93	12	experimental	experimental	ADJ
ajst-322	93	13	environment	environment	NOUN
ajst-322	93	14	,	,	PUNCT
ajst-322	93	15	the	the	DET
ajst-322	93	16	specific	specific	ADJ
ajst-322	93	17	production	production	NOUN
ajst-322	93	18	process	process	NOUN
ajst-322	93	19	of	of	ADP
ajst-322	93	20	the	the	DET
ajst-322	93	21	data	datum	NOUN
ajst-322	93	22	set	set	VERB
ajst-322	93	23	,	,	PUNCT
ajst-322	93	24	the	the	DET
ajst-322	93	25	training	training	NOUN
ajst-322	93	26	method	method	NOUN
ajst-322	93	27	of	of	ADP
ajst-322	93	28	the	the	DET
ajst-322	93	29	model	model	NOUN
ajst-322	93	30	and	and	CCONJ
ajst-322	93	31	parameter	parameter	NOUN
ajst-322	93	32	setting	setting	NOUN
ajst-322	93	33	.	.	PUNCT
ajst-322	94	1	the	the	DET
ajst-322	94	2	effectiveness	effectiveness	NOUN
ajst-322	94	3	of	of	ADP
ajst-322	94	4	the	the	DET
ajst-322	94	5	improved	improved	ADJ
ajst-322	94	6	method	method	NOUN
ajst-322	94	7	on	on	ADP
ajst-322	94	8	the	the	DET
ajst-322	94	9	data	datum	NOUN
ajst-322	94	10	set	set	VERB
ajst-322	94	11	in	in	ADP
ajst-322	94	12	this	this	DET
ajst-322	94	13	paper	paper	NOUN
ajst-322	94	14	is	be	AUX
ajst-322	94	15	proved	prove	VERB
ajst-322	94	16	by	by	ADP
ajst-322	94	17	experiments	experiment	NOUN
ajst-322	94	18	.	.	PUNCT
ajst-322	95	1	references	reference	NOUN
ajst-322	95	2	[	[	X
ajst-322	95	3	1	1	X
ajst-322	95	4	]	]	PUNCT
ajst-322	95	5	he	he	PRON
ajst-322	95	6	k	k	NOUN
ajst-322	95	7	,	,	PUNCT
ajst-322	95	8	gkioxari	gkioxari	NOUN
ajst-322	95	9	g	g	NOUN
ajst-322	95	10	,	,	PUNCT
ajst-322	95	11	dollár	dollár	NOUN
ajst-322	95	12	p	p	NOUN
ajst-322	95	13	,	,	PUNCT
ajst-322	95	14	et	et	PROPN
ajst-322	95	15	al	al	PROPN
ajst-322	95	16	.	.	PROPN
ajst-322	96	1	mask	mask	PROPN
ajst-322	96	2	r	r	PROPN
ajst-322	96	3	-	-	PUNCT
ajst-322	96	4	cnn	cnn	PROPN
ajst-322	96	5	;	;	PUNCT
ajst-322	96	6	proceedings	proceeding	NOUN
ajst-322	96	7	of	of	ADP
ajst-322	96	8	the	the	DET
ajst-322	96	9	2017	2017	NUM
ajst-322	96	10	ieee	ieee	NOUN
ajst-322	96	11	international	international	ADJ
ajst-322	96	12	conference	conference	NOUN
ajst-322	96	13	on	on	ADP
ajst-322	96	14	computer	computer	NOUN
ajst-322	96	15	vision	vision	NOUN
ajst-322	96	16	(	(	PUNCT
ajst-322	96	17	iccv	iccv	PROPN
ajst-322	96	18	)	)	PUNCT
ajst-322	96	19	,	,	PUNCT
ajst-322	96	20	f	f	PROPN
ajst-322	96	21	22	22	NUM
ajst-322	96	22	-	-	SYM
ajst-322	96	23	29	29	NUM
ajst-322	96	24	oct	oct	PROPN
ajst-322	96	25	.	.	PROPN
ajst-322	96	26	2017	2017	NUM
ajst-322	96	27	,	,	PUNCT
ajst-322	96	28	2017	2017	NUM
ajst-322	97	1	[	[	X
ajst-322	97	2	c	c	X
ajst-322	97	3	]	]	PUNCT
ajst-322	97	4	.	.	PUNCT
ajst-322	98	1	[	[	X
ajst-322	98	2	2	2	X
ajst-322	98	3	]	]	X
ajst-322	98	4	girshick	girshick	ADJ
ajst-322	98	5	r	r	PROPN
ajst-322	98	6	,	,	PUNCT
ajst-322	98	7	donahue	donahue	PROPN
ajst-322	98	8	j	j	PROPN
ajst-322	98	9	,	,	PUNCT
ajst-322	98	10	darrell	darrell	PROPN
ajst-322	98	11	t	t	PROPN
ajst-322	98	12	,	,	PUNCT
ajst-322	98	13	et	et	PROPN
ajst-322	98	14	al	al	PROPN
ajst-322	98	15	.	.	PROPN
ajst-322	98	16	rich	rich	ADJ
ajst-322	98	17	feature	feature	NOUN
ajst-322	98	18	hierarchies	hierarchy	NOUN
ajst-322	98	19	for	for	ADP
ajst-322	98	20	accurate	accurate	ADJ
ajst-322	98	21	object	object	NOUN
ajst-322	98	22	detection	detection	NOUN
ajst-322	98	23	and	and	CCONJ
ajst-322	98	24	semantic	semantic	ADJ
ajst-322	98	25	segmentation	segmentation	NOUN
ajst-322	98	26	;	;	PUNCT
ajst-322	98	27	proceedings	proceeding	NOUN
ajst-322	98	28	of	of	ADP
ajst-322	98	29	the	the	DET
ajst-322	98	30	2014	2014	NUM
ajst-322	98	31	ieee	ieee	NOUN
ajst-322	98	32	conference	conference	NOUN
ajst-322	98	33	on	on	ADP
ajst-322	98	34	computer	computer	NOUN
ajst-322	98	35	vision	vision	NOUN
ajst-322	98	36	and	and	CCONJ
ajst-322	98	37	pattern	pattern	NOUN
ajst-322	98	38	recognition	recognition	NOUN
ajst-322	98	39	,	,	PUNCT
ajst-322	98	40	f	f	PROPN
ajst-322	98	41	23	23	NUM
ajst-322	98	42	-	-	SYM
ajst-322	98	43	28	28	NUM
ajst-322	98	44	june	june	PROPN
ajst-322	98	45	2014	2014	NUM
ajst-322	98	46	,	,	PUNCT
ajst-322	98	47	2014	2014	NUM
ajst-322	99	1	[	[	X
ajst-322	99	2	c	c	X
ajst-322	99	3	]	]	PUNCT
ajst-322	99	4	.	.	PUNCT
ajst-322	100	1	[	[	X
ajst-322	100	2	3	3	X
ajst-322	100	3	]	]	PUNCT
ajst-322	100	4	he	he	PRON
ajst-322	100	5	k	k	PROPN
ajst-322	100	6	,	,	PUNCT
ajst-322	100	7	zhang	zhang	PROPN
ajst-322	100	8	x	x	PROPN
ajst-322	100	9	,	,	PUNCT
ajst-322	100	10	ren	ren	PROPN
ajst-322	100	11	s	s	PROPN
ajst-322	100	12	,	,	PUNCT
ajst-322	100	13	et	et	PROPN
ajst-322	100	14	al	al	PROPN
ajst-322	100	15	.	.	PUNCT
ajst-322	101	1	spatial	spatial	ADJ
ajst-322	101	2	pyramid	pyramid	NOUN
ajst-322	101	3	pooling	pool	VERB
ajst-322	101	4	in	in	ADP
ajst-322	101	5	deep	deep	ADJ
ajst-322	101	6	convolutional	convolutional	ADJ
ajst-322	101	7	networks	network	NOUN
ajst-322	101	8	for	for	ADP
ajst-322	101	9	visual	visual	ADJ
ajst-322	101	10	recognition	recognition	NOUN
ajst-322	102	1	[	[	X
ajst-322	102	2	j	j	X
ajst-322	102	3	]	]	X
ajst-322	102	4	.	.	PUNCT
ajst-322	103	1	ieee	ieee	NOUN
ajst-322	103	2	transactions	transaction	NOUN
ajst-322	103	3	on	on	ADP
ajst-322	103	4	pattern	pattern	NOUN
ajst-322	103	5	analysis	analysis	NOUN
ajst-322	103	6	and	and	CCONJ
ajst-322	103	7	machine	machine	NOUN
ajst-322	103	8	intelligence	intelligence	NOUN
ajst-322	103	9	,	,	PUNCT
ajst-322	103	10	2015	2015	NUM
ajst-322	103	11	,	,	PUNCT
ajst-322	103	12	37(9	37(9	NUM
ajst-322	103	13	):	):	PUNCT
ajst-322	103	14	1904	1904	NUM
ajst-322	103	15	-	-	SYM
ajst-322	103	16	16	16	NUM
ajst-322	103	17	.	.	PUNCT
ajst-322	104	1	[	[	X
ajst-322	104	2	4	4	X
ajst-322	104	3	]	]	X
ajst-322	104	4	girshick	girshick	PROPN
ajst-322	104	5	r.	r.	PROPN
ajst-322	104	6	fast	fast	ADV
ajst-322	104	7	r	r	PROPN
ajst-322	104	8	-	-	PUNCT
ajst-322	104	9	cnn	cnn	PROPN
ajst-322	104	10	;	;	PUNCT
ajst-322	104	11	proceedings	proceeding	NOUN
ajst-322	104	12	of	of	ADP
ajst-322	104	13	the	the	DET
ajst-322	104	14	2015	2015	NUM
ajst-322	104	15	ieee	ieee	NOUN
ajst-322	104	16	international	international	ADJ
ajst-322	104	17	conference	conference	NOUN
ajst-322	104	18	on	on	ADP
ajst-322	104	19	computer	computer	NOUN
ajst-322	104	20	vision	vision	NOUN
ajst-322	104	21	(	(	PUNCT
ajst-322	104	22	iccv	iccv	PROPN
ajst-322	104	23	)	)	PUNCT
ajst-322	104	24	,	,	PUNCT
ajst-322	104	25	f	f	PROPN
ajst-322	104	26	7	7	NUM
ajst-322	104	27	-	-	SYM
ajst-322	104	28	13	13	NUM
ajst-322	104	29	dec	dec	PROPN
ajst-322	104	30	.	.	PROPN
ajst-322	104	31	2015	2015	NUM
ajst-322	104	32	,	,	PUNCT
ajst-322	104	33	2015	2015	NUM
ajst-322	105	1	[	[	X
ajst-322	105	2	c	c	X
ajst-322	105	3	]	]	PUNCT
ajst-322	105	4	.	.	PUNCT
ajst-322	106	1	[	[	X
ajst-322	106	2	5	5	X
ajst-322	106	3	]	]	X
ajst-322	106	4	ren	ren	PROPN
ajst-322	106	5	s	s	PROPN
ajst-322	106	6	,	,	PUNCT
ajst-322	106	7	he	he	PRON
ajst-322	106	8	k	k	NOUN
ajst-322	106	9	,	,	PUNCT
ajst-322	106	10	girshick	girshick	ADJ
ajst-322	106	11	r	r	NOUN
ajst-322	106	12	,	,	PUNCT
ajst-322	106	13	et	et	PROPN
ajst-322	106	14	al	al	PROPN
ajst-322	106	15	.	.	PUNCT
ajst-322	107	1	faster	fast	ADJ
ajst-322	107	2	r	r	NOUN
ajst-322	107	3	-	-	PUNCT
ajst-322	107	4	cnn	cnn	NOUN
ajst-322	107	5	:	:	PUNCT
ajst-322	107	6	towards	towards	ADP
ajst-322	107	7	real	real	ADJ
ajst-322	107	8	-	-	PUNCT
ajst-322	107	9	time	time	NOUN
ajst-322	107	10	object	object	NOUN
ajst-322	107	11	detection	detection	NOUN
ajst-322	107	12	with	with	ADP
ajst-322	107	13	region	region	NOUN
ajst-322	107	14	proposal	proposal	NOUN
ajst-322	107	15	networks	network	NOUN
ajst-322	108	1	[	[	X
ajst-322	108	2	j	j	X
ajst-322	108	3	]	]	X
ajst-322	108	4	.	.	PUNCT
ajst-322	109	1	ieee	ieee	NOUN
ajst-322	109	2	transactions	transaction	NOUN
ajst-322	109	3	on	on	ADP
ajst-322	109	4	pattern	pattern	NOUN
ajst-322	109	5	analysis	analysis	NOUN
ajst-322	109	6	and	and	CCONJ
ajst-322	109	7	machine	machine	NOUN
ajst-322	109	8	intelligence	intelligence	NOUN
ajst-322	109	9	,	,	PUNCT
ajst-322	109	10	2017	2017	NUM
ajst-322	109	11	,	,	PUNCT
ajst-322	109	12	39(6	39(6	NUM
ajst-322	109	13	):	):	PUNCT
ajst-322	109	14	1137	1137	NUM
ajst-322	109	15	-	-	SYM
ajst-322	109	16	49	49	NUM
ajst-322	109	17	.	.	PUNCT
ajst-322	110	1	[	[	X
ajst-322	110	2	6	6	NUM
ajst-322	110	3	]	]	SYM
ajst-322	110	4	li	li	PROPN
ajst-322	110	5	x	x	PROPN
ajst-322	110	6	,	,	PUNCT
ajst-322	110	7	wang	wang	PROPN
ajst-322	110	8	w	w	PROPN
ajst-322	110	9	,	,	PUNCT
ajst-322	110	10	hu	hu	PROPN
ajst-322	110	11	x	x	PROPN
ajst-322	110	12	,	,	PUNCT
ajst-322	110	13	et	et	PROPN
ajst-322	110	14	al	al	PROPN
ajst-322	110	15	.	.	PROPN
ajst-322	110	16	selective	selective	ADJ
ajst-322	110	17	kernel	kernel	PROPN
ajst-322	110	18	networks	network	NOUN
ajst-322	110	19	;	;	PUNCT
ajst-322	110	20	proceedings	proceeding	NOUN
ajst-322	110	21	of	of	ADP
ajst-322	110	22	the	the	DET
ajst-322	110	23	2019	2019	NUM
ajst-322	110	24	ieee	ieee	NOUN
ajst-322	110	25	/	/	SYM
ajst-322	110	26	cvf	cvf	NOUN
ajst-322	110	27	conference	conference	NOUN
ajst-322	110	28	on	on	ADP
ajst-322	110	29	computer	computer	NOUN
ajst-322	110	30	vision	vision	NOUN
ajst-322	110	31	and	and	CCONJ
ajst-322	110	32	pattern	pattern	NOUN
ajst-322	110	33	recognition	recognition	NOUN
ajst-322	110	34	(	(	PUNCT
ajst-322	110	35	cvpr	cvpr	NOUN
ajst-322	110	36	)	)	PUNCT
ajst-322	110	37	,	,	PUNCT
ajst-322	110	38	f	f	PROPN
ajst-322	110	39	15	15	NUM
ajst-322	110	40	-	-	SYM
ajst-322	110	41	20	20	NUM
ajst-322	110	42	june	june	PROPN
ajst-322	110	43	2019	2019	NUM
ajst-322	110	44	,	,	PUNCT
ajst-322	110	45	2019	2019	NUM
ajst-322	111	1	[	[	X
ajst-322	111	2	c	c	X
ajst-322	111	3	]	]	PUNCT
ajst-322	111	4	.	.	PUNCT