id	sid	tid	token	lemma	pos
ajst-1433	1	1	academic	academic	ADJ
ajst-1433	1	2	journal	journal	NOUN
ajst-1433	1	3	of	of	ADP
ajst-1433	1	4	science	science	NOUN
ajst-1433	1	5	and	and	CCONJ
ajst-1433	1	6	technology	technology	NOUN
ajst-1433	1	7	issn	issn	NOUN
ajst-1433	1	8	:	:	PUNCT
ajst-1433	1	9	2771	2771	NUM
ajst-1433	1	10	-	-	SYM
ajst-1433	1	11	3032	3032	NUM
ajst-1433	1	12	|	|	NOUN
ajst-1433	1	13	vol	vol	NOUN
ajst-1433	1	14	.	.	PROPN
ajst-1433	2	1	2	2	NUM
ajst-1433	2	2	,	,	PUNCT
ajst-1433	2	3	no	no	INTJ
ajst-1433	2	4	.	.	NOUN
ajst-1433	2	5	3	3	NUM
ajst-1433	2	6	,	,	PUNCT
ajst-1433	2	7	2022	2022	NUM
ajst-1433	2	8	1	1	NUM
ajst-1433	2	9	semantic	semantic	ADJ
ajst-1433	2	10	segmentation	segmentation	NOUN
ajst-1433	2	11	based	base	VERB
ajst-1433	2	12	on	on	ADP
ajst-1433	2	13	improved	improved	ADJ
ajst-1433	2	14	robinson	robinson	PROPN
ajst-1433	2	15	operator	operator	NOUN
ajst-1433	2	16	xiaoshuo	xiaoshuo	PROPN
ajst-1433	2	17	jia	jia	PROPN
ajst-1433	2	18	*	*	PROPN
ajst-1433	2	19	,	,	PUNCT
ajst-1433	2	20	zhihui	zhihui	PROPN
ajst-1433	2	21	li	li	PROPN
ajst-1433	2	22	school	school	PROPN
ajst-1433	2	23	of	of	ADP
ajst-1433	2	24	computer	computer	NOUN
ajst-1433	2	25	science	science	NOUN
ajst-1433	2	26	,	,	PUNCT
ajst-1433	2	27	guangdong	guangdong	PROPN
ajst-1433	2	28	university	university	PROPN
ajst-1433	2	29	of	of	ADP
ajst-1433	2	30	science	science	NOUN
ajst-1433	2	31	and	and	CCONJ
ajst-1433	2	32	technology	technology	NOUN
ajst-1433	2	33	,	,	PUNCT
ajst-1433	2	34	dongguan	dongguan	PROPN
ajst-1433	2	35	523079	523079	NUM
ajst-1433	2	36	,	,	PUNCT
ajst-1433	2	37	guangdong	guangdong	PROPN
ajst-1433	2	38	,	,	PUNCT
ajst-1433	2	39	china	china	PROPN
ajst-1433	2	40	abstract	abstract	PROPN
ajst-1433	2	41	:	:	PUNCT
ajst-1433	3	1	classical	classical	ADJ
ajst-1433	3	2	pixel	pixel	ADJ
ajst-1433	3	3	-	-	PUNCT
ajst-1433	3	4	level	level	NOUN
ajst-1433	3	5	semantic	semantic	ADJ
ajst-1433	3	6	segmentation	segmentation	NOUN
ajst-1433	3	7	methods	method	NOUN
ajst-1433	3	8	are	be	AUX
ajst-1433	3	9	easily	easily	ADV
ajst-1433	3	10	affected	affect	VERB
ajst-1433	3	11	by	by	ADP
ajst-1433	3	12	factors	factor	NOUN
ajst-1433	3	13	such	such	ADJ
ajst-1433	3	14	as	as	ADP
ajst-1433	3	15	environment	environment	NOUN
ajst-1433	3	16	and	and	CCONJ
ajst-1433	3	17	pixel	pixel	ADJ
ajst-1433	3	18	values	value	NOUN
ajst-1433	3	19	,	,	PUNCT
ajst-1433	3	20	resulting	result	VERB
ajst-1433	3	21	in	in	ADP
ajst-1433	3	22	low	low	ADJ
ajst-1433	3	23	accuracy	accuracy	NOUN
ajst-1433	3	24	of	of	ADP
ajst-1433	3	25	their	their	PRON
ajst-1433	3	26	methods	method	NOUN
ajst-1433	3	27	.	.	PUNCT
ajst-1433	4	1	therefore	therefore	ADV
ajst-1433	4	2	,	,	PUNCT
ajst-1433	4	3	in	in	ADP
ajst-1433	4	4	order	order	NOUN
ajst-1433	4	5	to	to	PART
ajst-1433	4	6	improve	improve	VERB
ajst-1433	4	7	the	the	DET
ajst-1433	4	8	accuracy	accuracy	NOUN
ajst-1433	4	9	of	of	ADP
ajst-1433	4	10	pixel	pixel	ADJ
ajst-1433	4	11	-	-	PUNCT
ajst-1433	4	12	level	level	NOUN
ajst-1433	4	13	semantic	semantic	ADJ
ajst-1433	4	14	segmentation	segmentation	NOUN
ajst-1433	4	15	under	under	ADP
ajst-1433	4	16	practical	practical	ADJ
ajst-1433	4	17	conditions	condition	NOUN
ajst-1433	4	18	,	,	PUNCT
ajst-1433	4	19	this	this	DET
ajst-1433	4	20	paper	paper	NOUN
ajst-1433	4	21	designs	design	VERB
ajst-1433	4	22	a	a	DET
ajst-1433	4	23	lightweight	lightweight	ADJ
ajst-1433	4	24	network	network	NOUN
ajst-1433	4	25	based	base	VERB
ajst-1433	4	26	on	on	ADP
ajst-1433	4	27	the	the	DET
ajst-1433	4	28	nonlinear	nonlinear	ADJ
ajst-1433	4	29	characteristics	characteristic	NOUN
ajst-1433	4	30	of	of	ADP
ajst-1433	4	31	residual	residual	ADJ
ajst-1433	4	32	structure	structure	NOUN
ajst-1433	4	33	and	and	CCONJ
ajst-1433	4	34	the	the	DET
ajst-1433	4	35	characteristics	characteristic	NOUN
ajst-1433	4	36	of	of	ADP
ajst-1433	4	37	optimized	optimize	VERB
ajst-1433	4	38	edge	edge	NOUN
ajst-1433	4	39	operators	operator	NOUN
ajst-1433	4	40	.	.	PUNCT
ajst-1433	5	1	the	the	DET
ajst-1433	5	2	experimental	experimental	ADJ
ajst-1433	5	3	results	result	NOUN
ajst-1433	5	4	show	show	VERB
ajst-1433	5	5	that	that	SCONJ
ajst-1433	5	6	the	the	DET
ajst-1433	5	7	designed	design	VERB
ajst-1433	5	8	lightweight	lightweight	ADJ
ajst-1433	5	9	residual	residual	ADJ
ajst-1433	5	10	network	network	NOUN
ajst-1433	5	11	can	can	AUX
ajst-1433	5	12	effectively	effectively	ADV
ajst-1433	5	13	improve	improve	VERB
ajst-1433	5	14	the	the	DET
ajst-1433	5	15	accuracy	accuracy	NOUN
ajst-1433	5	16	by	by	ADP
ajst-1433	5	17	about	about	ADV
ajst-1433	5	18	2	2	NUM
ajst-1433	5	19	%	%	NOUN
ajst-1433	5	20	compared	compare	VERB
ajst-1433	5	21	with	with	ADP
ajst-1433	5	22	the	the	DET
ajst-1433	5	23	traditional	traditional	ADJ
ajst-1433	5	24	residual	residual	ADJ
ajst-1433	5	25	network	network	NOUN
ajst-1433	5	26	,	,	PUNCT
ajst-1433	5	27	and	and	CCONJ
ajst-1433	5	28	the	the	DET
ajst-1433	5	29	model	model	NOUN
ajst-1433	5	30	size	size	NOUN
ajst-1433	5	31	is	be	AUX
ajst-1433	5	32	reduced	reduce	VERB
ajst-1433	5	33	from	from	ADP
ajst-1433	5	34	the	the	DET
ajst-1433	5	35	original	original	ADJ
ajst-1433	5	36	40.2	40.2	NUM
ajst-1433	5	37	mb	mb	NOUN
ajst-1433	5	38	to	to	ADP
ajst-1433	5	39	18.9	18.9	NUM
ajst-1433	5	40	mb	mb	NOUN
ajst-1433	5	41	.	.	PUNCT
ajst-1433	6	1	keywords	keyword	NOUN
ajst-1433	6	2	:	:	PUNCT
ajst-1433	6	3	semantic	semantic	ADJ
ajst-1433	6	4	segmentation	segmentation	NOUN
ajst-1433	6	5	,	,	PUNCT
ajst-1433	6	6	residual	residual	ADJ
ajst-1433	6	7	structure	structure	NOUN
ajst-1433	6	8	,	,	PUNCT
ajst-1433	6	9	pooling	pool	VERB
ajst-1433	6	10	layer	layer	NOUN
ajst-1433	6	11	,	,	PUNCT
ajst-1433	6	12	lightweigth	lightweigth	NOUN
ajst-1433	6	13	model	model	NOUN
ajst-1433	6	14	,	,	PUNCT
ajst-1433	6	15	robinson	robinson	PROPN
ajst-1433	6	16	operator	operator	NOUN
ajst-1433	6	17	.	.	PUNCT
ajst-1433	7	1	1	1	X
ajst-1433	7	2	.	.	X
ajst-1433	7	3	introduction	introduction	NOUN
ajst-1433	7	4	in	in	ADP
ajst-1433	7	5	image	image	NOUN
ajst-1433	7	6	processing	processing	NOUN
ajst-1433	7	7	,	,	PUNCT
ajst-1433	7	8	pixel	pixel	PROPN
ajst-1433	7	9	level	level	NOUN
ajst-1433	7	10	semantic	semantic	ADJ
ajst-1433	7	11	segmentation	segmentation	NOUN
ajst-1433	7	12	[	[	X
ajst-1433	7	13	13	13	NUM
ajst-1433	7	14	]	]	PUNCT
ajst-1433	7	15	is	be	AUX
ajst-1433	7	16	an	an	DET
ajst-1433	7	17	extremely	extremely	ADV
ajst-1433	7	18	important	important	ADJ
ajst-1433	7	19	and	and	CCONJ
ajst-1433	7	20	complex	complex	ADJ
ajst-1433	7	21	task	task	NOUN
ajst-1433	7	22	.	.	PUNCT
ajst-1433	8	1	cnn	cnn	PROPN
ajst-1433	8	2	algorithm	algorithm	PROPN
ajst-1433	9	1	[	[	X
ajst-1433	9	2	4	4	NUM
ajst-1433	9	3	-	-	SYM
ajst-1433	9	4	7	7	NUM
ajst-1433	9	5	]	]	PUNCT
ajst-1433	9	6	has	have	AUX
ajst-1433	9	7	made	make	VERB
ajst-1433	9	8	excellent	excellent	ADJ
ajst-1433	9	9	achievements	achievement	NOUN
ajst-1433	9	10	in	in	ADP
ajst-1433	9	11	image	image	NOUN
ajst-1433	9	12	classification	classification	NOUN
ajst-1433	9	13	,	,	PUNCT
ajst-1433	9	14	segmentation	segmentation	NOUN
ajst-1433	9	15	and	and	CCONJ
ajst-1433	9	16	tracking	tracking	NOUN
ajst-1433	9	17	of	of	ADP
ajst-1433	9	18	kaggle	kaggle	NOUN
ajst-1433	9	19	and	and	CCONJ
ajst-1433	9	20	ai	ai	VERB
ajst-1433	9	21	challenger	challenger	NOUN
ajst-1433	9	22	competitions	competition	NOUN
ajst-1433	9	23	by	by	ADP
ajst-1433	9	24	taking	take	VERB
ajst-1433	9	25	advantage	advantage	NOUN
ajst-1433	9	26	of	of	ADP
ajst-1433	9	27	the	the	DET
ajst-1433	9	28	characteristics	characteristic	NOUN
ajst-1433	9	29	of	of	ADP
ajst-1433	9	30	multi	multi	ADJ
ajst-1433	9	31	parameters	parameter	NOUN
ajst-1433	9	32	.	.	PUNCT
ajst-1433	10	1	fcn	fcn	PROPN
ajst-1433	10	2	uses	use	VERB
ajst-1433	10	3	deconvolution	deconvolution	NOUN
ajst-1433	10	4	for	for	ADP
ajst-1433	10	5	up	up	ADP
ajst-1433	10	6	sampling	sample	VERB
ajst-1433	10	7	to	to	PART
ajst-1433	10	8	make	make	VERB
ajst-1433	10	9	the	the	DET
ajst-1433	10	10	extracted	extract	VERB
ajst-1433	10	11	features	feature	NOUN
ajst-1433	10	12	more	more	ADV
ajst-1433	10	13	detailed	detailed	ADJ
ajst-1433	10	14	.	.	PUNCT
ajst-1433	11	1	u	u	ADJ
ajst-1433	11	2	-	-	ADJ
ajst-1433	11	3	net	net	ADJ
ajst-1433	11	4	uses	use	VERB
ajst-1433	11	5	network	network	NOUN
ajst-1433	11	6	symmetric	symmetric	ADJ
ajst-1433	11	7	structure	structure	NOUN
ajst-1433	11	8	to	to	PART
ajst-1433	11	9	fuse	fuse	VERB
ajst-1433	11	10	highdimensional	highdimensional	NOUN
ajst-1433	11	11	features	feature	NOUN
ajst-1433	11	12	and	and	CCONJ
ajst-1433	11	13	low	low	ADJ
ajst-1433	11	14	-	-	PUNCT
ajst-1433	11	15	dimensional	dimensional	ADJ
ajst-1433	11	16	features	feature	NOUN
ajst-1433	11	17	to	to	ADP
ajst-1433	11	18	weight	weight	NOUN
ajst-1433	11	19	edge	edge	NOUN
ajst-1433	11	20	features	feature	NOUN
ajst-1433	11	21	.	.	PUNCT
ajst-1433	12	1	in	in	ADP
ajst-1433	12	2	cpfnet	cpfnet	NOUN
ajst-1433	12	3	,	,	PUNCT
ajst-1433	12	4	the	the	DET
ajst-1433	12	5	concept	concept	NOUN
ajst-1433	12	6	of	of	ADP
ajst-1433	12	7	dilated	dilated	ADJ
ajst-1433	12	8	convolution	convolution	NOUN
ajst-1433	12	9	is	be	AUX
ajst-1433	12	10	proposed	propose	VERB
ajst-1433	12	11	,	,	PUNCT
ajst-1433	12	12	which	which	PRON
ajst-1433	12	13	can	can	AUX
ajst-1433	12	14	expand	expand	VERB
ajst-1433	12	15	the	the	DET
ajst-1433	12	16	field	field	NOUN
ajst-1433	12	17	of	of	ADP
ajst-1433	12	18	view	view	NOUN
ajst-1433	12	19	of	of	ADP
ajst-1433	12	20	convolution	convolution	NOUN
ajst-1433	12	21	layer	layer	NOUN
ajst-1433	12	22	to	to	PART
ajst-1433	12	23	extract	extract	VERB
ajst-1433	12	24	more	more	ADJ
ajst-1433	12	25	feature	feature	NOUN
ajst-1433	12	26	information	information	NOUN
ajst-1433	12	27	.	.	PUNCT
ajst-1433	13	1	then	then	ADV
ajst-1433	13	2	,	,	PUNCT
ajst-1433	13	3	the	the	DET
ajst-1433	13	4	context	context	NOUN
ajst-1433	13	5	based	base	VERB
ajst-1433	13	6	feature	feature	NOUN
ajst-1433	13	7	fusion	fusion	NOUN
ajst-1433	13	8	is	be	AUX
ajst-1433	13	9	realized	realize	VERB
ajst-1433	13	10	in	in	ADP
ajst-1433	13	11	combination	combination	NOUN
ajst-1433	13	12	with	with	ADP
ajst-1433	13	13	the	the	DET
ajst-1433	13	14	inception	inception	NOUN
ajst-1433	13	15	module	module	NOUN
ajst-1433	13	16	,	,	PUNCT
ajst-1433	13	17	which	which	PRON
ajst-1433	13	18	has	have	AUX
ajst-1433	13	19	achieved	achieve	VERB
ajst-1433	13	20	excellent	excellent	ADJ
ajst-1433	13	21	results	result	NOUN
ajst-1433	13	22	in	in	ADP
ajst-1433	13	23	medical	medical	ADJ
ajst-1433	13	24	data	data	NOUN
ajst-1433	13	25	sets	set	NOUN
ajst-1433	13	26	.	.	PUNCT
ajst-1433	14	1	stdc	stdc	PROPN
ajst-1433	14	2	is	be	AUX
ajst-1433	14	3	based	base	VERB
ajst-1433	14	4	on	on	ADP
ajst-1433	14	5	fpn	fpn	VERB
ajst-1433	14	6	for	for	ADP
ajst-1433	14	7	multi	multi	ADJ
ajst-1433	14	8	-	-	ADJ
ajst-1433	14	9	scale	scale	ADJ
ajst-1433	14	10	fusion	fusion	NOUN
ajst-1433	14	11	,	,	PUNCT
ajst-1433	14	12	so	so	CCONJ
ajst-1433	14	13	its	its	PRON
ajst-1433	14	14	performance	performance	NOUN
ajst-1433	14	15	is	be	AUX
ajst-1433	14	16	better	well	ADJ
ajst-1433	14	17	than	than	ADP
ajst-1433	14	18	cpfnet	cpfnet	NOUN
ajst-1433	14	19	algorithm	algorithm	NOUN
ajst-1433	14	20	.	.	PUNCT
ajst-1433	15	1	although	although	SCONJ
ajst-1433	15	2	the	the	DET
ajst-1433	15	3	algorithm	algorithm	NOUN
ajst-1433	15	4	based	base	VERB
ajst-1433	15	5	on	on	ADP
ajst-1433	15	6	cnn	cnn	PROPN
ajst-1433	15	7	has	have	VERB
ajst-1433	15	8	high	high	ADJ
ajst-1433	15	9	accuracy	accuracy	NOUN
ajst-1433	15	10	,	,	PUNCT
ajst-1433	15	11	the	the	DET
ajst-1433	15	12	extracted	extract	VERB
ajst-1433	15	13	features	feature	NOUN
ajst-1433	15	14	usually	usually	ADV
ajst-1433	15	15	lose	lose	VERB
ajst-1433	15	16	a	a	DET
ajst-1433	15	17	lot	lot	NOUN
ajst-1433	15	18	of	of	ADP
ajst-1433	15	19	spatial	spatial	ADJ
ajst-1433	15	20	information	information	NOUN
ajst-1433	15	21	due	due	ADP
ajst-1433	15	22	to	to	ADP
ajst-1433	15	23	the	the	DET
ajst-1433	15	24	pool	pool	NOUN
ajst-1433	15	25	layer	layer	NOUN
ajst-1433	15	26	.	.	PUNCT
ajst-1433	16	1	finally	finally	ADV
ajst-1433	16	2	,	,	PUNCT
ajst-1433	16	3	problems	problem	NOUN
ajst-1433	16	4	such	such	ADJ
ajst-1433	16	5	as	as	ADP
ajst-1433	16	6	redundancy	redundancy	NOUN
ajst-1433	16	7	of	of	ADP
ajst-1433	16	8	semantic	semantic	ADJ
ajst-1433	16	9	segmentation	segmentation	NOUN
ajst-1433	16	10	network	network	NOUN
ajst-1433	16	11	structure	structure	NOUN
ajst-1433	16	12	,	,	PUNCT
ajst-1433	16	13	large	large	ADJ
ajst-1433	16	14	amount	amount	NOUN
ajst-1433	16	15	of	of	ADP
ajst-1433	16	16	calculation	calculation	NOUN
ajst-1433	16	17	and	and	CCONJ
ajst-1433	16	18	segmentation	segmentation	NOUN
ajst-1433	16	19	errors	error	NOUN
ajst-1433	16	20	appear	appear	VERB
ajst-1433	16	21	.	.	PUNCT
ajst-1433	17	1	here	here	ADV
ajst-1433	17	2	,	,	PUNCT
ajst-1433	17	3	we	we	PRON
ajst-1433	17	4	analyze	analyze	VERB
ajst-1433	17	5	the	the	DET
ajst-1433	17	6	statistical	statistical	ADJ
ajst-1433	17	7	properties	property	NOUN
ajst-1433	17	8	and	and	CCONJ
ajst-1433	17	9	distribution	distribution	NOUN
ajst-1433	17	10	properties	property	NOUN
ajst-1433	17	11	of	of	ADP
ajst-1433	17	12	the	the	DET
ajst-1433	17	13	data	datum	NOUN
ajst-1433	17	14	on	on	ADP
ajst-1433	17	15	the	the	DET
ajst-1433	17	16	data	data	NOUN
ajst-1433	17	17	distribution	distribution	NOUN
ajst-1433	17	18	of	of	ADP
ajst-1433	17	19	the	the	DET
ajst-1433	17	20	image	image	NOUN
ajst-1433	17	21	edge	edge	NOUN
ajst-1433	17	22	features	feature	NOUN
ajst-1433	17	23	,	,	PUNCT
ajst-1433	17	24	and	and	CCONJ
ajst-1433	17	25	design	design	VERB
ajst-1433	17	26	a	a	DET
ajst-1433	17	27	correlation	correlation	NOUN
ajst-1433	17	28	pooling	pool	VERB
ajst-1433	17	29	layer	layer	NOUN
ajst-1433	17	30	rel	rel	NOUN
ajst-1433	17	31	layer	layer	NOUN
ajst-1433	17	32	.	.	PUNCT
ajst-1433	18	1	then	then	ADV
ajst-1433	18	2	the	the	DET
ajst-1433	18	3	nr	nr	PROPN
ajst-1433	18	4	layer	layer	NOUN
ajst-1433	18	5	is	be	AUX
ajst-1433	18	6	designed	design	VERB
ajst-1433	18	7	on	on	ADP
ajst-1433	18	8	the	the	DET
ajst-1433	18	9	basis	basis	NOUN
ajst-1433	18	10	of	of	ADP
ajst-1433	18	11	robinson	robinson	PROPN
ajst-1433	18	12	operator	operator	NOUN
ajst-1433	18	13	to	to	PART
ajst-1433	18	14	extract	extract	VERB
ajst-1433	18	15	the	the	DET
ajst-1433	18	16	edge	edge	NOUN
ajst-1433	18	17	contour	contour	NOUN
ajst-1433	18	18	features	feature	NOUN
ajst-1433	18	19	.	.	PUNCT
ajst-1433	19	1	finally	finally	ADV
ajst-1433	19	2	,	,	PUNCT
ajst-1433	19	3	renrnet	renrnet	NOUN
ajst-1433	19	4	is	be	AUX
ajst-1433	19	5	designed	design	VERB
ajst-1433	19	6	by	by	ADP
ajst-1433	19	7	combining	combine	VERB
ajst-1433	19	8	nr	nr	PRON
ajst-1433	19	9	layer	layer	NOUN
ajst-1433	19	10	and	and	CCONJ
ajst-1433	19	11	rel	rel	NOUN
ajst-1433	19	12	layer	layer	NOUN
ajst-1433	19	13	in	in	ADP
ajst-1433	19	14	residual	residual	ADJ
ajst-1433	19	15	structure	structure	NOUN
ajst-1433	19	16	.	.	PUNCT
ajst-1433	20	1	renrnet	renrnet	NOUN
ajst-1433	20	2	and	and	CCONJ
ajst-1433	20	3	sota	sota	NOUN
ajst-1433	20	4	algorithms	algorithm	NOUN
ajst-1433	20	5	were	be	AUX
ajst-1433	20	6	compared	compare	VERB
ajst-1433	20	7	under	under	ADP
ajst-1433	20	8	the	the	DET
ajst-1433	20	9	sbd	sbd	NOUN
ajst-1433	20	10	dataset	dataset	NOUN
ajst-1433	20	11	.	.	PUNCT
ajst-1433	21	1	the	the	DET
ajst-1433	21	2	experimental	experimental	ADJ
ajst-1433	21	3	results	result	NOUN
ajst-1433	21	4	show	show	VERB
ajst-1433	21	5	that	that	SCONJ
ajst-1433	21	6	renrnet	renrnet	NOUN
ajst-1433	21	7	has	have	VERB
ajst-1433	21	8	certain	certain	ADJ
ajst-1433	21	9	advantages	advantage	NOUN
ajst-1433	21	10	in	in	ADP
ajst-1433	21	11	accuracy	accuracy	NOUN
ajst-1433	21	12	and	and	CCONJ
ajst-1433	21	13	speed	speed	NOUN
ajst-1433	21	14	.	.	PUNCT
ajst-1433	22	1	2	2	X
ajst-1433	22	2	.	.	X
ajst-1433	22	3	method	method	PROPN
ajst-1433	22	4	2.1	2.1	NUM
ajst-1433	22	5	.	.	PUNCT
ajst-1433	22	6	optimized	optimize	VERB
ajst-1433	22	7	edge	edge	NOUN
ajst-1433	22	8	operator	operator	NOUN
ajst-1433	22	9	nr	nr	PROPN
ajst-1433	22	10	on	on	ADP
ajst-1433	22	11	the	the	DET
ajst-1433	22	12	basis	basis	NOUN
ajst-1433	22	13	of	of	ADP
ajst-1433	22	14	the	the	DET
ajst-1433	22	15	robinson	robinson	PROPN
ajst-1433	22	16	operator	operator	NOUN
ajst-1433	22	17	,	,	PUNCT
ajst-1433	22	18	an	an	DET
ajst-1433	22	19	optimized	optimize	VERB
ajst-1433	22	20	edge	edge	NOUN
ajst-1433	22	21	operator	operator	NOUN
ajst-1433	22	22	nr	nr	PRON
ajst-1433	22	23	is	be	AUX
ajst-1433	22	24	designed	design	VERB
ajst-1433	22	25	,	,	PUNCT
ajst-1433	22	26	at	at	ADP
ajst-1433	22	27	the	the	DET
ajst-1433	22	28	orientation	orientation	NOUN
ajst-1433	22	29	of	of	ADP
ajst-1433	22	30	the	the	DET
ajst-1433	22	31	polar	polar	ADJ
ajst-1433	22	32	coordinate	coordinate	NOUN
ajst-1433	22	33	system	system	NOUN
ajst-1433	22	34	of	of	ADP
ajst-1433	22	35	the	the	DET
ajst-1433	22	36	image	image	NOUN
ajst-1433	22	37	,	,	PUNCT
ajst-1433	22	38	and	and	CCONJ
ajst-1433	22	39	8	8	NUM
ajst-1433	22	40	polar	polar	ADJ
ajst-1433	22	41	coordinate	coordinate	NOUN
ajst-1433	22	42	convolution	convolution	NOUN
ajst-1433	22	43	kernels	kernel	NOUN
ajst-1433	22	44	are	be	AUX
ajst-1433	22	45	given	give	VERB
ajst-1433	22	46	.	.	PUNCT
ajst-1433	23	1	the	the	DET
ajst-1433	23	2	picture	picture	NOUN
ajst-1433	23	3	pic	pic	NOUN
ajst-1433	23	4	and	and	CCONJ
ajst-1433	23	5	the	the	DET
ajst-1433	23	6	8	8	NUM
ajst-1433	23	7	azimuth	azimuth	NOUN
ajst-1433	23	8	convolution	convolution	NOUN
ajst-1433	23	9	kernels	kernels	PROPN
ajst-1433	23	10	r1	r1	PROPN
ajst-1433	23	11	...	...	PUNCT
ajst-1433	23	12	r8	r8	PROPN
ajst-1433	23	13	do	do	VERB
ajst-1433	23	14	the	the	DET
ajst-1433	23	15	convolution	convolution	NOUN
ajst-1433	23	16	operation	operation	NOUN
ajst-1433	23	17	and	and	CCONJ
ajst-1433	23	18	then	then	ADV
ajst-1433	23	19	accumulate	accumulate	VERB
ajst-1433	23	20	the	the	DET
ajst-1433	23	21	result	result	NOUN
ajst-1433	23	22	cov	cov	NOUN
ajst-1433	23	23	,	,	PUNCT
ajst-1433	23	24	such	such	ADJ
ajst-1433	23	25	as	as	ADP
ajst-1433	23	26	formula	formula	NOUN
ajst-1433	23	27	(	(	PUNCT
ajst-1433	23	28	1	1	NUM
ajst-1433	23	29	):	):	SYM
ajst-1433	23	30	8	8	NUM
ajst-1433	23	31	1	1	NUM
ajst-1433	23	32	c	c	NOUN
ajst-1433	23	33	o	o	NOUN
ajst-1433	23	34	v	v	NOUN
ajst-1433	23	35	=	=	PUNCT
ajst-1433	24	1	*	*	PUNCT
ajst-1433	24	2	i	i	PRON
ajst-1433	25	1	i	i	VERB
ajst-1433	25	2	r	r	VERB
ajst-1433	26	1	p	p	X
ajst-1433	27	1	i	i	PRON
ajst-1433	27	2	c	c	PROPN
ajst-1433	28	1			VERB
ajst-1433	28	2			X
ajst-1433	28	3	(	(	PUNCT
ajst-1433	29	1	1	1	X
ajst-1433	29	2	)	)	PUNCT
ajst-1433	29	3	obtain	obtain	VERB
ajst-1433	29	4	the	the	DET
ajst-1433	29	5	minimum	minimum	ADJ
ajst-1433	29	6	value	value	NOUN
ajst-1433	29	7	min	min	NOUN
ajst-1433	29	8	and	and	CCONJ
ajst-1433	29	9	maximum	maximum	ADJ
ajst-1433	29	10	value	value	NOUN
ajst-1433	29	11	max	max	PROPN
ajst-1433	29	12	in	in	ADP
ajst-1433	29	13	cov	cov	PROPN
ajst-1433	29	14	,	,	PUNCT
ajst-1433	29	15	and	and	CCONJ
ajst-1433	29	16	then	then	ADV
ajst-1433	29	17	perform	perform	VERB
ajst-1433	29	18	the	the	DET
ajst-1433	29	19	operation	operation	NOUN
ajst-1433	29	20	,	,	PUNCT
ajst-1433	29	21	and	and	CCONJ
ajst-1433	29	22	finally	finally	ADV
ajst-1433	29	23	obtain	obtain	VERB
ajst-1433	29	24	the	the	DET
ajst-1433	29	25	pixel	pixel	PROPN
ajst-1433	29	26	value	value	NOUN
ajst-1433	29	27	pm	pm	NOUN
ajst-1433	29	28	,	,	PUNCT
ajst-1433	29	29	i	i	PRON
ajst-1433	29	30	,	,	PUNCT
ajst-1433	29	31	j	j	PROPN
ajst-1433	29	32	of	of	ADP
ajst-1433	29	33	the	the	DET
ajst-1433	29	34	edge	edge	NOUN
ajst-1433	29	35	feature	feature	NOUN
ajst-1433	29	36	image	image	NOUN
ajst-1433	29	37	p.	p.	NOUN
ajst-1433	29	38	m	m	PROPN
ajst-1433	29	39	,	,	PUNCT
ajst-1433	29	40	i	i	PRON
ajst-1433	29	41	,	,	PUNCT
ajst-1433	29	42	and	and	CCONJ
ajst-1433	29	43	j	j	PROPN
ajst-1433	29	44	represent	represent	VERB
ajst-1433	29	45	the	the	DET
ajst-1433	29	46	width	width	ADJ
ajst-1433	29	47	,	,	PUNCT
ajst-1433	29	48	length	length	NOUN
ajst-1433	29	49	,	,	PUNCT
ajst-1433	29	50	and	and	CCONJ
ajst-1433	29	51	pass	pass	VERB
ajst-1433	29	52	numbers	number	NOUN
ajst-1433	29	53	of	of	ADP
ajst-1433	29	54	the	the	DET
ajst-1433	29	55	image	image	NOUN
ajst-1433	29	56	,	,	PUNCT
ajst-1433	29	57	respectively	respectively	ADV
ajst-1433	29	58	.	.	PUNCT
ajst-1433	30	1	2.2	2.2	NUM
ajst-1433	30	2	.	.	PUNCT
ajst-1433	30	3	renrnet	renrnet	NOUN
ajst-1433	30	4	in	in	ADP
ajst-1433	30	5	feature	feature	NOUN
ajst-1433	30	6	extraction	extraction	NOUN
ajst-1433	30	7	,	,	PUNCT
ajst-1433	30	8	nr	nr	PRON
ajst-1433	30	9	can	can	AUX
ajst-1433	30	10	effectively	effectively	ADV
ajst-1433	30	11	extract	extract	VERB
ajst-1433	30	12	the	the	DET
ajst-1433	30	13	spatial	spatial	ADJ
ajst-1433	30	14	position	position	NOUN
ajst-1433	30	15	of	of	ADP
ajst-1433	30	16	edge	edge	NOUN
ajst-1433	30	17	features	feature	NOUN
ajst-1433	30	18	and	and	CCONJ
ajst-1433	30	19	reduce	reduce	VERB
ajst-1433	30	20	the	the	DET
ajst-1433	30	21	interference	interference	NOUN
ajst-1433	30	22	of	of	ADP
ajst-1433	30	23	unnecessary	unnecessary	ADJ
ajst-1433	30	24	features	feature	NOUN
ajst-1433	30	25	.	.	PUNCT
ajst-1433	31	1	here	here	ADV
ajst-1433	31	2	,	,	PUNCT
ajst-1433	31	3	to	to	PART
ajst-1433	31	4	ensure	ensure	VERB
ajst-1433	31	5	that	that	SCONJ
ajst-1433	31	6	the	the	DET
ajst-1433	31	7	correlation	correlation	NOUN
ajst-1433	31	8	between	between	ADP
ajst-1433	31	9	features	feature	NOUN
ajst-1433	31	10	is	be	AUX
ajst-1433	31	11	not	not	PART
ajst-1433	31	12	lost	lose	VERB
ajst-1433	31	13	during	during	ADP
ajst-1433	31	14	forward	forward	ADJ
ajst-1433	31	15	propagation	propagation	NOUN
ajst-1433	31	16	,	,	PUNCT
ajst-1433	31	17	we	we	PRON
ajst-1433	31	18	propose	propose	VERB
ajst-1433	31	19	a	a	DET
ajst-1433	31	20	rel	rel	NOUN
ajst-1433	31	21	layer	layer	NOUN
ajst-1433	31	22	,	,	PUNCT
ajst-1433	31	23	as	as	ADP
ajst-1433	31	24	formula	formula	NOUN
ajst-1433	31	25	(	(	PUNCT
ajst-1433	31	26	2	2	NUM
ajst-1433	31	27	)	)	PUNCT
ajst-1433	31	28	and	and	CCONJ
ajst-1433	31	29	(	(	PUNCT
ajst-1433	31	30	3	3	NUM
ajst-1433	31	31	)	)	PUNCT
ajst-1433	31	32	.	.	PUNCT
ajst-1433	32	1	,	,	PUNCT
ajst-1433	32	2	,	,	PUNCT
ajst-1433	32	3	,	,	PUNCT
ajst-1433	32	4	,	,	PUNCT
ajst-1433	32	5	,	,	PUNCT
ajst-1433	32	6	,	,	PUNCT
ajst-1433	32	7	,	,	PUNCT
ajst-1433	32	8	,	,	PUNCT
ajst-1433	32	9	(	(	PUNCT
ajst-1433	32	10	*	*	PUNCT
ajst-1433	32	11	)	)	PUNCT
ajst-1433	32	12	*	*	PUNCT
ajst-1433	32	13	)	)	PUNCT
ajst-1433	32	14	/	/	PUNCT
ajst-1433	33	1	*	*	PUNCT
ajst-1433	33	2	m	m	VERB
ajst-1433	33	3	n	n	ADV
ajst-1433	33	4	m	m	NOUN
ajst-1433	33	5	n	n	PRON
ajst-1433	33	6	m	m	VERB
ajst-1433	33	7	n	n	ADJ
ajst-1433	34	1	i	i	PRON
ajst-1433	34	2	j	j	PROPN
ajst-1433	35	1	i	i	PRON
ajst-1433	35	2	j	j	VERB
ajst-1433	36	1	i	i	PRON
ajst-1433	36	2	j	j	VERB
ajst-1433	37	1	i	i	PRON
ajst-1433	37	2	ji	ji	INTJ
ajst-1433	38	1	j	j	NOUN
ajst-1433	39	1	i	i	PRON
ajst-1433	39	2	j	j	VERB
ajst-1433	40	1	i	i	PRON
ajst-1433	40	2	j	j	PROPN
ajst-1433	40	3	s	s	AUX
ajst-1433	40	4	p	p	X
ajst-1433	40	5	p	p	X
ajst-1433	40	6	p	p	X
ajst-1433	40	7	p	p	NOUN
ajst-1433	40	8	h	h	NOUN
ajst-1433	40	9	w	w	VERB
ajst-1433	40	10			PROPN
ajst-1433	40	11			X
ajst-1433	40	12			X
ajst-1433	40	13	（	（	PUNCT
ajst-1433	40	14	(	(	PUNCT
ajst-1433	40	15	2	2	NUM
ajst-1433	40	16	)	)	PUNCT
ajst-1433	40	17	,	,	PUNCT
ajst-1433	40	18	,	,	PUNCT
ajst-1433	40	19	,	,	PUNCT
ajst-1433	40	20	,	,	PUNCT
ajst-1433	40	21	m	m	VERB
ajst-1433	40	22	n	n	VERB
ajst-1433	40	23	m	m	VERB
ajst-1433	40	24	m	m	VERB
ajst-1433	40	25	n	n	ADP
ajst-1433	40	26	n	n	ADV
ajst-1433	40	27	m	m	VERB
ajst-1433	40	28	nr	nr	NOUN
ajst-1433	40	29	s	s	NOUN
ajst-1433	40	30	s	s	X
ajst-1433	40	31	s	s	ADJ
ajst-1433	40	32	(	(	PUNCT
ajst-1433	40	33	3	3	NUM
ajst-1433	40	34	)	)	PUNCT
ajst-1433	40	35	the	the	DET
ajst-1433	40	36	feature	feature	NOUN
ajst-1433	40	37	map	map	NOUN
ajst-1433	40	38	p	p	NOUN
ajst-1433	40	39	obtains	obtain	VERB
ajst-1433	40	40	n	n	PRON
ajst-1433	40	41	special	special	ADJ
ajst-1433	40	42	detection	detection	NOUN
ajst-1433	40	43	maps	map	NOUN
ajst-1433	40	44	p1	p1	PROPN
ajst-1433	40	45	,	,	PUNCT
ajst-1433	40	46	...	...	PUNCT
ajst-1433	40	47	,	,	PUNCT
ajst-1433	40	48	pn	pn	INTJ
ajst-1433	40	49	(	(	PUNCT
ajst-1433	40	50	only	only	ADV
ajst-1433	40	51	five	five	NUM
ajst-1433	40	52	feature	feature	NOUN
ajst-1433	40	53	maps	map	NOUN
ajst-1433	40	54	are	be	AUX
ajst-1433	40	55	illustrated	illustrate	VERB
ajst-1433	40	56	here	here	ADV
ajst-1433	40	57	)	)	PUNCT
ajst-1433	40	58	under	under	ADP
ajst-1433	40	59	the	the	DET
ajst-1433	40	60	sliding	slide	VERB
ajst-1433	40	61	window	window	NOUN
ajst-1433	40	62	movement	movement	NOUN
ajst-1433	40	63	with	with	ADP
ajst-1433	40	64	the	the	DET
ajst-1433	40	65	step	step	NOUN
ajst-1433	40	66	size	size	NOUN
ajst-1433	40	67	s	s	PROPN
ajst-1433	40	68	of	of	ADP
ajst-1433	40	69	1	1	NUM
ajst-1433	40	70	.	.	PUNCT
ajst-1433	41	1	p2	p2	PROPN
ajst-1433	41	2	,	,	PUNCT
ajst-1433	41	3	...	...	PUNCT
ajst-1433	41	4	,	,	PUNCT
ajst-1433	41	5	pn	pn	PROPN
ajst-1433	41	6	all	all	PRON
ajst-1433	41	7	intersect	intersect	ADJ
ajst-1433	41	8	with	with	ADP
ajst-1433	41	9	p1	p1	PROPN
ajst-1433	41	10	.	.	PUNCT
ajst-1433	42	1	p1	p1	PROPN
ajst-1433	42	2	,	,	PUNCT
ajst-1433	42	3	p2	p2	NOUN
ajst-1433	42	4	,	,	PUNCT
ajst-1433	42	5	...	...	PUNCT
ajst-1433	42	6	,	,	PUNCT
ajst-1433	42	7	p5	p5	PROPN
ajst-1433	42	8	get	get	VERB
ajst-1433	42	9	the	the	DET
ajst-1433	42	10	corresponding	correspond	VERB
ajst-1433	42	11	correlation	correlation	NOUN
ajst-1433	42	12	features	feature	VERB
ajst-1433	42	13	r1	r1	PROPN
ajst-1433	42	14	,	,	PUNCT
ajst-1433	42	15	2	2	NUM
ajst-1433	42	16	,	,	PUNCT
ajst-1433	42	17	...	...	PUNCT
ajst-1433	42	18	,	,	PUNCT
ajst-1433	42	19	r1	r1	PROPN
ajst-1433	42	20	,	,	PUNCT
ajst-1433	42	21	5	5	NUM
ajst-1433	42	22	under	under	ADP
ajst-1433	42	23	formula	formula	NOUN
ajst-1433	42	24	2	2	NUM
ajst-1433	42	25	and	and	CCONJ
ajst-1433	42	26	formula	formula	NOUN
ajst-1433	42	27	3	3	NUM
ajst-1433	42	28	,	,	PUNCT
ajst-1433	42	29	and	and	CCONJ
ajst-1433	42	30	then	then	ADV
ajst-1433	42	31	regression	regression	VERB
ajst-1433	42	32	the	the	DET
ajst-1433	42	33	correlation	correlation	NOUN
ajst-1433	42	34	features	feature	VERB
ajst-1433	42	35	r1	r1	PROPN
ajst-1433	42	36	,	,	PUNCT
ajst-1433	42	37	2	2	NUM
ajst-1433	42	38	,	,	PUNCT
ajst-1433	42	39	...	...	PUNCT
ajst-1433	42	40	,	,	PUNCT
ajst-1433	42	41	r1	r1	PROPN
ajst-1433	42	42	,	,	PUNCT
ajst-1433	42	43	5	5	NUM
ajst-1433	42	44	to	to	ADP
ajst-1433	42	45	the	the	DET
ajst-1433	42	46	positions	position	NOUN
ajst-1433	42	47	where	where	SCONJ
ajst-1433	42	48	p1	p1	NOUN
ajst-1433	42	49	,	,	PUNCT
ajst-1433	42	50	p2	p2	NOUN
ajst-1433	42	51	,	,	PUNCT
ajst-1433	42	52	...	...	PUNCT
ajst-1433	42	53	,	,	PUNCT
ajst-1433	42	54	p5	p5	ADJ
ajst-1433	42	55	interact	interact	NOUN
ajst-1433	42	56	with	with	ADP
ajst-1433	42	57	each	each	DET
ajst-1433	42	58	other	other	ADJ
ajst-1433	42	59	,	,	PUNCT
ajst-1433	42	60	and	and	CCONJ
ajst-1433	42	61	finally	finally	ADV
ajst-1433	42	62	get	get	VERB
ajst-1433	42	63	the	the	DET
ajst-1433	42	64	correlation	correlation	NOUN
ajst-1433	42	65	feature	feature	NOUN
ajst-1433	42	66	map	map	NOUN
ajst-1433	42	67	rel1	rel1	PROPN
ajst-1433	42	68	,	,	PUNCT
ajst-1433	42	69	2	2	NUM
ajst-1433	42	70	,	,	PUNCT
ajst-1433	42	71	...	...	PUNCT
ajst-1433	42	72	,	,	PUNCT
ajst-1433	42	73	rel1	rel1	PROPN
ajst-1433	42	74	,	,	PUNCT
ajst-1433	43	1	5	5	NUM
ajst-1433	43	2	.	.	X
ajst-1433	43	3	p1	p1	NOUN
ajst-1433	43	4	and	and	CCONJ
ajst-1433	43	5	the	the	DET
ajst-1433	43	6	surrounding	surround	VERB
ajst-1433	43	7	characteristic	characteristic	ADJ
ajst-1433	43	8	map	map	NOUN
ajst-1433	43	9	p2	p2	NOUN
ajst-1433	43	10	,	,	PUNCT
ajst-1433	43	11	...	...	PUNCT
ajst-1433	43	12	,	,	PUNCT
ajst-1433	43	13	p5	p5	PROPN
ajst-1433	43	14	are	be	AUX
ajst-1433	43	15	calculated	calculate	VERB
ajst-1433	43	16	by	by	ADP
ajst-1433	43	17	algorithm2	algorithm2	NOUN
ajst-1433	43	18	to	to	PART
ajst-1433	43	19	obtain	obtain	VERB
ajst-1433	43	20	the	the	DET
ajst-1433	43	21	correlation	correlation	NOUN
ajst-1433	43	22	coefficient	coefficient	NOUN
ajst-1433	43	23	characteristic	characteristic	ADJ
ajst-1433	43	24	map	map	NOUN
ajst-1433	43	25	relp1	relp1	NOUN
ajst-1433	43	26	of	of	ADP
ajst-1433	43	27	p1	p1	PROPN
ajst-1433	43	28	.	.	PUNCT
ajst-1433	44	1	the	the	DET
ajst-1433	44	2	eigenvalue	eigenvalue	PROPN
ajst-1433	44	3	of	of	ADP
ajst-1433	44	4	relp1	relp1	PROPN
ajst-1433	44	5	indicates	indicate	VERB
ajst-1433	44	6	the	the	DET
ajst-1433	44	7	degree	degree	NOUN
ajst-1433	44	8	of	of	ADP
ajst-1433	44	9	correlation	correlation	NOUN
ajst-1433	44	10	between	between	ADP
ajst-1433	44	11	p1	p1	PROPN
ajst-1433	44	12	and	and	CCONJ
ajst-1433	44	13	the	the	DET
ajst-1433	44	14	surrounding	surround	VERB
ajst-1433	44	15	feature	feature	NOUN
ajst-1433	44	16	maps	map	NOUN
ajst-1433	44	17	p2	p2	NOUN
ajst-1433	44	18	,	,	PUNCT
ajst-1433	44	19	...	...	PUNCT
ajst-1433	44	20	,	,	PUNCT
ajst-1433	44	21	p5	p5	PROPN
ajst-1433	44	22	.	.	PUNCT
ajst-1433	45	1	finally	finally	ADV
ajst-1433	45	2	,	,	PUNCT
ajst-1433	45	3	the	the	DET
ajst-1433	45	4	result	result	NOUN
ajst-1433	45	5	of	of	ADP
ajst-1433	45	6	point	point	NOUN
ajst-1433	45	7	multiplication	multiplication	NOUN
ajst-1433	45	8	is	be	AUX
ajst-1433	45	9	regressed	regress	VERB
ajst-1433	45	10	to	to	ADP
ajst-1433	45	11	the	the	DET
ajst-1433	45	12	spatial	spatial	ADJ
ajst-1433	45	13	position	position	NOUN
ajst-1433	45	14	corresponding	correspond	VERB
ajst-1433	45	15	to	to	ADP
ajst-1433	45	16	p1	p1	PROPN
ajst-1433	45	17	.	.	PROPN
ajst-1433	46	1	2	2	NUM
ajst-1433	46	2	table	table	NOUN
ajst-1433	46	3	1	1	NUM
ajst-1433	46	4	.	.	PUNCT
ajst-1433	47	1	the	the	DET
ajst-1433	47	2	network	network	NOUN
ajst-1433	47	3	structure	structure	NOUN
ajst-1433	47	4	parameters	parameter	NOUN
ajst-1433	47	5	are	be	AUX
ajst-1433	47	6	shown	show	VERB
ajst-1433	47	7	in	in	ADP
ajst-1433	47	8	the	the	DET
ajst-1433	47	9	following	follow	VERB
ajst-1433	47	10	table	table	NOUN
ajst-1433	47	11	layer	layer	NOUN
ajst-1433	47	12	kernel	kernel	NOUN
ajst-1433	47	13	/	/	SYM
ajst-1433	47	14	stride	stride	NOUN
ajst-1433	47	15	conv1	conv1	NOUN
ajst-1433	47	16	128	128	NUM
ajst-1433	47	17	*	*	SYM
ajst-1433	47	18	11	11	NUM
ajst-1433	47	19	*	*	SYM
ajst-1433	47	20	11/4	11/4	NUM
ajst-1433	47	21	nr	nr	PRON
ajst-1433	47	22	5	5	NUM
ajst-1433	47	23	*	*	SYM
ajst-1433	47	24	3/15	3/15	NUM
ajst-1433	47	25	conv3/5/7/9/11/13	conv3/5/7/9/11/13	PROPN
ajst-1433	47	26	16	16	NUM
ajst-1433	47	27	*	*	SYM
ajst-1433	47	28	1	1	NUM
ajst-1433	47	29	*	*	SYM
ajst-1433	47	30	3/2	3/2	NUM
ajst-1433	47	31	16	16	NUM
ajst-1433	47	32	*	*	SYM
ajst-1433	47	33	3	3	NUM
ajst-1433	47	34	*	*	NUM
ajst-1433	47	35	1/2	1/2	NUM
ajst-1433	47	36	rel	rel	NOUN
ajst-1433	47	37	pool	pool	NOUN
ajst-1433	47	38	3	3	NUM
ajst-1433	47	39	*	*	SYM
ajst-1433	47	40	3/2	3/2	NUM
ajst-1433	47	41	conv2/4/6/8/10/12	conv2/4/6/8/10/12	PROPN
ajst-1433	47	42	8	8	NUM
ajst-1433	47	43	*	*	SYM
ajst-1433	47	44	3	3	NUM
ajst-1433	47	45	*	*	SYM
ajst-1433	47	46	3/2	3/2	NUM
ajst-1433	47	47	it	it	PRON
ajst-1433	47	48	can	can	AUX
ajst-1433	47	49	be	be	AUX
ajst-1433	47	50	seen	see	VERB
ajst-1433	47	51	from	from	ADP
ajst-1433	47	52	the	the	DET
ajst-1433	47	53	principle	principle	NOUN
ajst-1433	47	54	that	that	SCONJ
ajst-1433	47	55	the	the	DET
ajst-1433	47	56	rel	rel	NOUN
ajst-1433	47	57	layer	layer	NOUN
ajst-1433	47	58	can	can	AUX
ajst-1433	47	59	not	not	PART
ajst-1433	47	60	only	only	ADV
ajst-1433	47	61	effectively	effectively	ADV
ajst-1433	47	62	filter	filter	VERB
ajst-1433	47	63	the	the	DET
ajst-1433	47	64	interference	interference	NOUN
ajst-1433	47	65	of	of	ADP
ajst-1433	47	66	non	non	ADJ
ajst-1433	47	67	-	-	ADJ
ajst-1433	47	68	related	related	ADJ
ajst-1433	47	69	features	feature	NOUN
ajst-1433	47	70	and	and	CCONJ
ajst-1433	47	71	improve	improve	VERB
ajst-1433	47	72	the	the	DET
ajst-1433	47	73	accurate	accurate	ADJ
ajst-1433	47	74	removal	removal	NOUN
ajst-1433	47	75	rate	rate	NOUN
ajst-1433	47	76	,	,	PUNCT
ajst-1433	47	77	but	but	CCONJ
ajst-1433	47	78	also	also	ADV
ajst-1433	47	79	strengthen	strengthen	VERB
ajst-1433	47	80	the	the	DET
ajst-1433	47	81	features	feature	NOUN
ajst-1433	47	82	according	accord	VERB
ajst-1433	47	83	to	to	ADP
ajst-1433	47	84	a	a	DET
ajst-1433	47	85	certain	certain	ADJ
ajst-1433	47	86	proportion	proportion	NOUN
ajst-1433	47	87	,	,	PUNCT
ajst-1433	47	88	thus	thus	ADV
ajst-1433	47	89	helping	help	VERB
ajst-1433	47	90	nr	nr	PRON
ajst-1433	47	91	improve	improve	VERB
ajst-1433	47	92	the	the	DET
ajst-1433	47	93	efficient	efficient	ADJ
ajst-1433	47	94	positioning	positioning	NOUN
ajst-1433	47	95	of	of	ADP
ajst-1433	47	96	edge	edge	NOUN
ajst-1433	47	97	features	feature	NOUN
ajst-1433	47	98	.	.	PUNCT
ajst-1433	48	1	finally	finally	ADV
ajst-1433	48	2	,	,	PUNCT
ajst-1433	48	3	renrnet	renrnet	NOUN
ajst-1433	48	4	achieves	achieve	VERB
ajst-1433	48	5	efficient	efficient	ADJ
ajst-1433	48	6	semantic	semantic	ADJ
ajst-1433	48	7	segmentation	segmentation	NOUN
ajst-1433	48	8	effect	effect	NOUN
ajst-1433	48	9	.	.	PUNCT
ajst-1433	49	1	3	3	X
ajst-1433	49	2	.	.	X
ajst-1433	49	3	experiments	experiment	NOUN
ajst-1433	49	4	3.1	3.1	NUM
ajst-1433	49	5	.	.	PUNCT
ajst-1433	49	6	dataset	dataset	VERB
ajst-1433	49	7	the	the	DET
ajst-1433	49	8	pacal	pacal	ADJ
ajst-1433	49	9	voc	voc	NOUN
ajst-1433	49	10	(	(	PUNCT
ajst-1433	49	11	07	07	NUM
ajst-1433	49	12	+	+	NUM
ajst-1433	49	13	12	12	NUM
ajst-1433	49	14	)	)	PUNCT
ajst-1433	49	15	dataset	dataset	NOUN
ajst-1433	49	16	is	be	AUX
ajst-1433	49	17	divided	divide	VERB
ajst-1433	49	18	into	into	ADP
ajst-1433	49	19	4	4	NUM
ajst-1433	49	20	categories	category	NOUN
ajst-1433	49	21	and	and	CCONJ
ajst-1433	49	22	20	20	NUM
ajst-1433	49	23	subcategories	subcategorie	NOUN
ajst-1433	49	24	.	.	PUNCT
ajst-1433	50	1	there	there	PRON
ajst-1433	50	2	are	be	VERB
ajst-1433	50	3	33k	33k	NOUN
ajst-1433	50	4	photos	photo	NOUN
ajst-1433	50	5	in	in	ADP
ajst-1433	50	6	total	total	NOUN
ajst-1433	50	7	,	,	PUNCT
ajst-1433	50	8	including	include	VERB
ajst-1433	50	9	16k	16k	NUM
ajst-1433	50	10	train	train	NOUN
ajst-1433	50	11	-	-	PUNCT
ajst-1433	50	12	val	val	NOUN
ajst-1433	50	13	data	datum	NOUN
ajst-1433	50	14	set	set	VERB
ajst-1433	50	15	and	and	CCONJ
ajst-1433	50	16	16k	16k	NUM
ajst-1433	50	17	test	test	NOUN
ajst-1433	50	18	data	datum	NOUN
ajst-1433	50	19	set	set	VERB
ajst-1433	50	20	.	.	PUNCT
ajst-1433	51	1	sbd	sbd	PROPN
ajst-1433	51	2	belongs	belong	VERB
ajst-1433	51	3	to	to	ADP
ajst-1433	51	4	the	the	DET
ajst-1433	51	5	enhanced	enhanced	ADJ
ajst-1433	51	6	dataset	dataset	NOUN
ajst-1433	51	7	of	of	ADP
ajst-1433	51	8	voc	voc	NOUN
ajst-1433	51	9	dataset	dataset	PROPN
ajst-1433	51	10	.	.	PUNCT
ajst-1433	52	1	it	it	PRON
ajst-1433	52	2	contains	contain	VERB
ajst-1433	52	3	11355	11355	NUM
ajst-1433	52	4	marker	marker	NOUN
ajst-1433	52	5	images	image	NOUN
ajst-1433	52	6	in	in	ADP
ajst-1433	52	7	the	the	DET
ajst-1433	52	8	voc	voc	NOUN
ajst-1433	52	9	.	.	PUNCT
ajst-1433	53	1	we	we	PRON
ajst-1433	53	2	used	use	VERB
ajst-1433	53	3	segmentation	segmentation	NOUN
ajst-1433	53	4	of	of	ADP
ajst-1433	53	5	voc	voc	NOUN
ajst-1433	53	6	datasets	dataset	NOUN
ajst-1433	53	7	as	as	ADP
ajst-1433	53	8	annotations	annotation	NOUN
ajst-1433	53	9	to	to	PART
ajst-1433	53	10	train	train	VERB
ajst-1433	53	11	the	the	DET
ajst-1433	53	12	network	network	NOUN
ajst-1433	53	13	.	.	PUNCT
ajst-1433	54	1	sbd	sbd	PROPN
ajst-1433	54	2	divided	divide	VERB
ajst-1433	54	3	the	the	DET
ajst-1433	54	4	whole	whole	ADJ
ajst-1433	54	5	data	datum	NOUN
ajst-1433	54	6	set	set	VERB
ajst-1433	54	7	into	into	ADP
ajst-1433	54	8	two	two	NUM
ajst-1433	54	9	parts	part	NOUN
ajst-1433	54	10	,	,	PUNCT
ajst-1433	54	11	8498	8498	NUM
ajst-1433	54	12	training	training	NOUN
ajst-1433	54	13	images	image	NOUN
ajst-1433	54	14	and	and	CCONJ
ajst-1433	54	15	2857	2857	NUM
ajst-1433	54	16	test	test	NOUN
ajst-1433	54	17	images	image	NOUN
ajst-1433	54	18	.	.	PUNCT
ajst-1433	55	1	3.2	3.2	NUM
ajst-1433	55	2	.	.	PUNCT
ajst-1433	55	3	comparison	comparison	NOUN
ajst-1433	55	4	with	with	ADP
ajst-1433	55	5	sota	sota	NOUN
ajst-1433	55	6	the	the	DET
ajst-1433	55	7	training	training	NOUN
ajst-1433	55	8	platforms	platform	NOUN
ajst-1433	55	9	are	be	AUX
ajst-1433	55	10	rtx	rtx	PROPN
ajst-1433	55	11	3060	3060	NUM
ajst-1433	55	12	.	.	PUNCT
ajst-1433	56	1	the	the	DET
ajst-1433	56	2	optimization	optimization	NOUN
ajst-1433	56	3	function	function	NOUN
ajst-1433	56	4	is	be	AUX
ajst-1433	56	5	adam	adam	PROPN
ajst-1433	56	6	optimizer	optimizer	NOUN
ajst-1433	56	7	.	.	PUNCT
ajst-1433	57	1	the	the	DET
ajst-1433	57	2	loss	loss	NOUN
ajst-1433	57	3	function	function	NOUN
ajst-1433	57	4	uses	use	VERB
ajst-1433	57	5	formula	formula	NOUN
ajst-1433	57	6	4	4	NUM
ajst-1433	57	7	to	to	PART
ajst-1433	57	8	calculate	calculate	VERB
ajst-1433	57	9	the	the	DET
ajst-1433	57	10	error	error	NOUN
ajst-1433	57	11	between	between	ADP
ajst-1433	57	12	the	the	DET
ajst-1433	57	13	true	true	ADJ
ajst-1433	57	14	value	value	NOUN
ajst-1433	57	15	and	and	CCONJ
ajst-1433	57	16	the	the	DET
ajst-1433	57	17	predicted	predict	VERB
ajst-1433	57	18	value	value	NOUN
ajst-1433	57	19	,	,	PUNCT
ajst-1433	57	20	and	and	CCONJ
ajst-1433	57	21	uses	use	VERB
ajst-1433	57	22	iou	iou	VERB
ajst-1433	57	23	to	to	PART
ajst-1433	57	24	evaluate	evaluate	VERB
ajst-1433	57	25	the	the	DET
ajst-1433	57	26	test	test	NOUN
ajst-1433	57	27	results	result	NOUN
ajst-1433	57	28	.	.	PUNCT
ajst-1433	58	1	yp	yp	PROPN
ajst-1433	58	2	and	and	CCONJ
ajst-1433	58	3	yt	yt	PROPN
ajst-1433	58	4	represent	represent	VERB
ajst-1433	58	5	the	the	DET
ajst-1433	58	6	predicted	predict	VERB
ajst-1433	58	7	values	value	NOUN
ajst-1433	58	8	and	and	CCONJ
ajst-1433	58	9	actual	actual	ADJ
ajst-1433	58	10	values	value	NOUN
ajst-1433	58	11	respectively	respectively	ADV
ajst-1433	58	12	.	.	PUNCT
ajst-1433	59	1	dice	dice	PROPN
ajst-1433	59	2	p	p	NOUN
ajst-1433	59	3	,	,	PUNCT
ajst-1433	59	4	t	t	PROPN
ajst-1433	59	5	2	2	NUM
ajst-1433	59	6	∗	∗	NOUN
ajst-1433	59	7	|𝑦	|𝑦	PROPN
ajst-1433	59	8	∩	∩	PROPN
ajst-1433	59	9	𝑦	𝑦	PROPN
ajst-1433	59	10	|	|	ADV
ajst-1433	59	11	𝑦	𝑦	PROPN
ajst-1433	59	12	|𝑦	|𝑦	X
ajst-1433	59	13	|⁄	|⁄	X
ajst-1433	59	14	(	(	PUNCT
ajst-1433	59	15	4	4	NUM
ajst-1433	59	16	)	)	PUNCT
ajst-1433	59	17	here	here	ADV
ajst-1433	59	18	we	we	PRON
ajst-1433	59	19	compare	compare	VERB
ajst-1433	59	20	resnet	resnet	NOUN
ajst-1433	59	21	with	with	ADP
ajst-1433	59	22	some	some	DET
ajst-1433	59	23	sota	sota	ADJ
ajst-1433	59	24	algorithms	algorithm	NOUN
ajst-1433	59	25	,	,	PUNCT
ajst-1433	59	26	such	such	ADJ
ajst-1433	59	27	as	as	ADP
ajst-1433	59	28	deep	deep	ADJ
ajst-1433	59	29	snake[8	snake[8	NOUN
ajst-1433	59	30	]	]	NOUN
ajst-1433	59	31	,	,	PUNCT
ajst-1433	59	32	unet[9	unet[9	PROPN
ajst-1433	59	33	]	]	X
ajst-1433	59	34	,	,	PUNCT
ajst-1433	59	35	panet[10	panet[10	PROPN
ajst-1433	59	36	]	]	PUNCT
ajst-1433	59	37	,	,	PUNCT
ajst-1433	59	38	fcis[11	fcis[11	PROPN
ajst-1433	59	39	]	]	PUNCT
ajst-1433	59	40	,	,	PUNCT
ajst-1433	59	41	ese[12	ese[12	PROPN
ajst-1433	59	42	-	-	PUNCT
ajst-1433	59	43	13	13	NUM
ajst-1433	59	44	]	]	PUNCT
ajst-1433	59	45	,	,	PUNCT
ajst-1433	59	46	etc	etc	X
ajst-1433	59	47	.	.	X
ajst-1433	60	1	the	the	DET
ajst-1433	60	2	results	result	NOUN
ajst-1433	60	3	for	for	ADP
ajst-1433	60	4	the	the	DET
ajst-1433	60	5	sbd	sbd	NOUN
ajst-1433	60	6	datasets	dataset	NOUN
ajst-1433	60	7	are	be	AUX
ajst-1433	60	8	shown	show	VERB
ajst-1433	60	9	in	in	ADP
ajst-1433	60	10	table	table	NOUN
ajst-1433	60	11	2	2	NUM
ajst-1433	60	12	below	below	ADV
ajst-1433	60	13	.	.	PUNCT
ajst-1433	61	1	table	table	NOUN
ajst-1433	61	2	2	2	NUM
ajst-1433	61	3	.	.	PUNCT
ajst-1433	61	4	comparison	comparison	NOUN
ajst-1433	61	5	results	result	NOUN
ajst-1433	61	6	of	of	ADP
ajst-1433	61	7	sbd	sbd	NOUN
ajst-1433	61	8	datasets	dataset	NOUN
ajst-1433	61	9	.	.	PUNCT
ajst-1433	62	1	network	network	NOUN
ajst-1433	62	2	discnet	discnet	PROPN
ajst-1433	62	3	deep	deep	ADJ
ajst-1433	62	4	unet	unet	NOUN
ajst-1433	62	5	panet	panet	PROPN
ajst-1433	62	6	fcis	fcis	PROPN
ajst-1433	62	7	ese	ese	PROPN
ajst-1433	62	8	segnet	segnet	PROPN
ajst-1433	62	9	auc(%	auc(%	PROPN
ajst-1433	62	10	)	)	PUNCT
ajst-1433	62	11	42.6	42.6	NUM
ajst-1433	62	12	40.7	40.7	NUM
ajst-1433	62	13	34.4	34.4	NUM
ajst-1433	62	14	40.1	40.1	NUM
ajst-1433	62	15	36.4	36.4	NUM
ajst-1433	62	16	28.2	28.2	NUM
ajst-1433	62	17	33.6	33.6	NUM
ajst-1433	62	18	fps	fps	PROPN
ajst-1433	62	19	28.6	28.6	NUM
ajst-1433	62	20	20.1	20.1	NUM
ajst-1433	62	21	19.6	19.6	NUM
ajst-1433	62	22	23.1	23.1	NUM
ajst-1433	62	23	17.4	17.4	NUM
ajst-1433	62	24	15.9	15.9	NUM
ajst-1433	62	25	20.3	20.3	NUM
ajst-1433	62	26	the	the	DET
ajst-1433	62	27	sbd	sbd	NOUN
ajst-1433	62	28	dataset	dataset	NOUN
ajst-1433	62	29	is	be	AUX
ajst-1433	62	30	an	an	DET
ajst-1433	62	31	enhanced	enhance	VERB
ajst-1433	62	32	dataset	dataset	NOUN
ajst-1433	62	33	for	for	ADP
ajst-1433	62	34	pascal	pascal	ADJ
ajst-1433	62	35	voc	voc	NOUN
ajst-1433	62	36	.	.	PUNCT
ajst-1433	63	1	we	we	PRON
ajst-1433	63	2	used	use	VERB
ajst-1433	63	3	the	the	DET
ajst-1433	63	4	model	model	NOUN
ajst-1433	63	5	trained	train	VERB
ajst-1433	63	6	under	under	ADP
ajst-1433	63	7	pascal	pascal	PROPN
ajst-1433	63	8	voc	voc	NOUN
ajst-1433	63	9	as	as	ADP
ajst-1433	63	10	the	the	DET
ajst-1433	63	11	pre	pre	ADJ
ajst-1433	63	12	training	training	NOUN
ajst-1433	63	13	model	model	NOUN
ajst-1433	63	14	and	and	CCONJ
ajst-1433	63	15	tested	test	VERB
ajst-1433	63	16	it	it	PRON
ajst-1433	63	17	under	under	ADP
ajst-1433	63	18	the	the	DET
ajst-1433	63	19	sbd	sbd	NOUN
ajst-1433	63	20	dataset	dataset	NOUN
ajst-1433	63	21	.	.	PUNCT
ajst-1433	64	1	the	the	DET
ajst-1433	64	2	results	result	NOUN
ajst-1433	64	3	are	be	AUX
ajst-1433	64	4	shown	show	VERB
ajst-1433	64	5	in	in	ADP
ajst-1433	64	6	table	table	NOUN
ajst-1433	64	7	2	2	NUM
ajst-1433	64	8	,	,	PUNCT
ajst-1433	64	9	and	and	CCONJ
ajst-1433	64	10	the	the	DET
ajst-1433	64	11	segmentation	segmentation	NOUN
ajst-1433	64	12	effect	effect	NOUN
ajst-1433	64	13	is	be	AUX
ajst-1433	64	14	shown	show	VERB
ajst-1433	64	15	in	in	ADP
ajst-1433	64	16	figure	figure	NOUN
ajst-1433	64	17	1	1	NUM
ajst-1433	64	18	.	.	PUNCT
ajst-1433	65	1	under	under	ADP
ajst-1433	65	2	the	the	DET
ajst-1433	65	3	sbd	sbd	NOUN
ajst-1433	65	4	dataset	dataset	PROPN
ajst-1433	65	5	,	,	PUNCT
ajst-1433	65	6	the	the	DET
ajst-1433	65	7	model	model	NOUN
ajst-1433	65	8	of	of	ADP
ajst-1433	65	9	ese	ese	NOUN
ajst-1433	65	10	,	,	PUNCT
ajst-1433	65	11	unet	unet	NOUN
ajst-1433	65	12	and	and	CCONJ
ajst-1433	65	13	segnet	segnet	NOUN
ajst-1433	65	14	are	be	AUX
ajst-1433	65	15	relatively	relatively	ADV
ajst-1433	65	16	small	small	ADJ
ajst-1433	65	17	.	.	PUNCT
ajst-1433	66	1	renrnet	renrnet	NOUN
ajst-1433	66	2	adopts	adopt	VERB
ajst-1433	66	3	a	a	DET
ajst-1433	66	4	residual	residual	ADJ
ajst-1433	66	5	structure	structure	NOUN
ajst-1433	66	6	based	base	VERB
ajst-1433	66	7	on	on	ADP
ajst-1433	66	8	correlation	correlation	NOUN
ajst-1433	66	9	features	feature	NOUN
ajst-1433	66	10	,	,	PUNCT
ajst-1433	66	11	which	which	PRON
ajst-1433	66	12	can	can	AUX
ajst-1433	66	13	effectively	effectively	ADV
ajst-1433	66	14	reduce	reduce	VERB
ajst-1433	66	15	the	the	DET
ajst-1433	66	16	weight	weight	NOUN
ajst-1433	66	17	of	of	ADP
ajst-1433	66	18	the	the	DET
ajst-1433	66	19	model	model	NOUN
ajst-1433	66	20	and	and	CCONJ
ajst-1433	66	21	effectively	effectively	ADV
ajst-1433	66	22	improve	improve	VERB
ajst-1433	66	23	the	the	DET
ajst-1433	66	24	calculation	calculation	NOUN
ajst-1433	66	25	speed	speed	NOUN
ajst-1433	66	26	.	.	PUNCT
ajst-1433	67	1	it	it	PRON
ajst-1433	67	2	can	can	AUX
ajst-1433	67	3	be	be	AUX
ajst-1433	67	4	seen	see	VERB
ajst-1433	67	5	from	from	ADP
ajst-1433	67	6	the	the	DET
ajst-1433	67	7	segmentation	segmentation	NOUN
ajst-1433	67	8	effect	effect	NOUN
ajst-1433	67	9	in	in	ADP
ajst-1433	67	10	figure	figure	NOUN
ajst-1433	67	11	1	1	NUM
ajst-1433	67	12	that	that	SCONJ
ajst-1433	67	13	whether	whether	SCONJ
ajst-1433	67	14	it	it	PRON
ajst-1433	67	15	is	be	AUX
ajst-1433	67	16	a	a	DET
ajst-1433	67	17	complex	complex	ADJ
ajst-1433	67	18	background	background	NOUN
ajst-1433	67	19	or	or	CCONJ
ajst-1433	67	20	a	a	DET
ajst-1433	67	21	small	small	ADJ
ajst-1433	67	22	target	target	NOUN
ajst-1433	67	23	,	,	PUNCT
ajst-1433	67	24	renrnet	renrnet	NOUN
ajst-1433	67	25	can	can	AUX
ajst-1433	67	26	extract	extract	VERB
ajst-1433	67	27	the	the	DET
ajst-1433	67	28	related	related	ADJ
ajst-1433	67	29	features	feature	NOUN
ajst-1433	67	30	through	through	ADP
ajst-1433	67	31	the	the	DET
ajst-1433	67	32	nr	nr	NOUN
ajst-1433	67	33	and	and	CCONJ
ajst-1433	67	34	the	the	DET
ajst-1433	67	35	rel	rel	NOUN
ajst-1433	67	36	layer	layer	NOUN
ajst-1433	67	37	under	under	ADP
ajst-1433	67	38	the	the	DET
ajst-1433	67	39	residual	residual	ADJ
ajst-1433	67	40	structure	structure	NOUN
ajst-1433	67	41	,	,	PUNCT
ajst-1433	67	42	thereby	thereby	ADV
ajst-1433	67	43	realizing	realize	VERB
ajst-1433	67	44	the	the	DET
ajst-1433	67	45	lightweight	lightweight	ADJ
ajst-1433	67	46	model	model	NOUN
ajst-1433	67	47	and	and	CCONJ
ajst-1433	67	48	pixel	pixel	ADJ
ajst-1433	67	49	level	level	NOUN
ajst-1433	67	50	segmentation	segmentation	NOUN
ajst-1433	67	51	.	.	PUNCT
ajst-1433	68	1	renrnet	renrnet	NOUN
ajst-1433	68	2	ese	ese	NOUN
ajst-1433	68	3	deepimage	deepimage	NOUN
ajst-1433	68	4	figure	figure	NOUN
ajst-1433	68	5	1	1	NUM
ajst-1433	68	6	.	.	PUNCT
ajst-1433	68	7	image	image	NOUN
ajst-1433	68	8	represent	represent	VERB
ajst-1433	68	9	the	the	DET
ajst-1433	68	10	original	original	ADJ
ajst-1433	68	11	image	image	NOUN
ajst-1433	68	12	.	.	PUNCT
ajst-1433	69	1	and	and	CCONJ
ajst-1433	69	2	renrnet	renrnet	NOUN
ajst-1433	69	3	,	,	PUNCT
ajst-1433	69	4	ese	ese	NOUN
ajst-1433	69	5	,	,	PUNCT
ajst-1433	69	6	deep	deep	ADJ
ajst-1433	69	7	sanke	sanke	NOUN
ajst-1433	69	8	correspond	correspond	NOUN
ajst-1433	69	9	to	to	ADP
ajst-1433	69	10	the	the	DET
ajst-1433	69	11	segmentation	segmentation	NOUN
ajst-1433	69	12	effect	effect	NOUN
ajst-1433	69	13	image	image	NOUN
ajst-1433	69	14	of	of	ADP
ajst-1433	69	15	these	these	DET
ajst-1433	69	16	algorithms	algorithm	NOUN
ajst-1433	69	17	respectively	respectively	ADV
ajst-1433	69	18	.	.	PUNCT
ajst-1433	70	1	3	3	NUM
ajst-1433	70	2	4	4	NUM
ajst-1433	70	3	.	.	PUNCT
ajst-1433	70	4	conclusion	conclusion	NOUN
ajst-1433	70	5	in	in	ADP
ajst-1433	70	6	this	this	DET
ajst-1433	70	7	paper	paper	NOUN
ajst-1433	70	8	,	,	PUNCT
ajst-1433	70	9	the	the	DET
ajst-1433	70	10	statistical	statistical	ADJ
ajst-1433	70	11	features	feature	NOUN
ajst-1433	70	12	of	of	ADP
ajst-1433	70	13	discrete	discrete	ADJ
ajst-1433	70	14	data	datum	NOUN
ajst-1433	70	15	and	and	CCONJ
ajst-1433	70	16	robinson	robinson	PROPN
ajst-1433	70	17	operator	operator	NOUN
ajst-1433	70	18	are	be	AUX
ajst-1433	70	19	analyzed	analyze	VERB
ajst-1433	70	20	to	to	PART
ajst-1433	70	21	extract	extract	VERB
ajst-1433	70	22	the	the	DET
ajst-1433	70	23	correlation	correlation	NOUN
ajst-1433	70	24	features	feature	VERB
ajst-1433	70	25	in	in	ADP
ajst-1433	70	26	the	the	DET
ajst-1433	70	27	image	image	NOUN
ajst-1433	70	28	,	,	PUNCT
ajst-1433	70	29	and	and	CCONJ
ajst-1433	70	30	the	the	DET
ajst-1433	70	31	corresponding	correspond	VERB
ajst-1433	70	32	correlation	correlation	NOUN
ajst-1433	70	33	pooling	pool	VERB
ajst-1433	70	34	layer	layer	NOUN
ajst-1433	70	35	and	and	CCONJ
ajst-1433	70	36	nr	nr	NOUN
ajst-1433	70	37	layer	layer	NOUN
ajst-1433	70	38	are	be	AUX
ajst-1433	70	39	designed	design	VERB
ajst-1433	70	40	.	.	PUNCT
ajst-1433	71	1	then	then	ADV
ajst-1433	71	2	combined	combine	VERB
ajst-1433	71	3	with	with	ADP
ajst-1433	71	4	residual	residual	ADJ
ajst-1433	71	5	structure	structure	NOUN
ajst-1433	71	6	,	,	PUNCT
ajst-1433	71	7	renrnet	renrnet	NOUN
ajst-1433	71	8	is	be	AUX
ajst-1433	71	9	designed	design	VERB
ajst-1433	71	10	.	.	PUNCT
ajst-1433	72	1	then	then	ADV
ajst-1433	72	2	we	we	PRON
ajst-1433	72	3	make	make	VERB
ajst-1433	72	4	a	a	DET
ajst-1433	72	5	comprehensive	comprehensive	ADJ
ajst-1433	72	6	comparison	comparison	NOUN
ajst-1433	72	7	of	of	ADP
ajst-1433	72	8	some	some	DET
ajst-1433	72	9	sota	sota	ADJ
ajst-1433	72	10	algorithms	algorithm	NOUN
ajst-1433	72	11	under	under	ADP
ajst-1433	72	12	the	the	DET
ajst-1433	72	13	sbd	sbd	NOUN
ajst-1433	72	14	dataset	dataset	NOUN
ajst-1433	72	15	,	,	PUNCT
ajst-1433	72	16	and	and	CCONJ
ajst-1433	72	17	prove	prove	VERB
ajst-1433	72	18	that	that	SCONJ
ajst-1433	72	19	renrnet	renrnet	NOUN
ajst-1433	72	20	performs	perform	VERB
ajst-1433	72	21	well	well	ADV
ajst-1433	72	22	in	in	ADP
ajst-1433	72	23	accuracy	accuracy	NOUN
ajst-1433	72	24	and	and	CCONJ
ajst-1433	72	25	speed	speed	NOUN
ajst-1433	72	26	.	.	PUNCT
ajst-1433	73	1	acknowledgment	acknowledgment	NOUN
ajst-1433	73	2	this	this	DET
ajst-1433	73	3	work	work	NOUN
ajst-1433	73	4	is	be	AUX
ajst-1433	73	5	supported	support	VERB
ajst-1433	73	6	by	by	ADP
ajst-1433	73	7	natural	natural	ADJ
ajst-1433	73	8	science	science	NOUN
ajst-1433	73	9	program	program	NOUN
ajst-1433	73	10	of	of	ADP
ajst-1433	73	11	guangdong	guangdong	PROPN
ajst-1433	73	12	university	university	PROPN
ajst-1433	73	13	of	of	ADP
ajst-1433	73	14	science	science	NOUN
ajst-1433	73	15	and	and	CCONJ
ajst-1433	73	16	technology	technology	NOUN
ajst-1433	73	17	under	under	ADP
ajst-1433	73	18	the	the	DET
ajst-1433	73	19	grant	grant	PROPN
ajst-1433	73	20	no.gky-2021kyqnk-2	no.gky-2021kyqnk-2	PROPN
ajst-1433	73	21	.	.	PUNCT
ajst-1433	74	1	references	reference	NOUN
ajst-1433	74	2	[	[	X
ajst-1433	74	3	1	1	NUM
ajst-1433	74	4	]	]	X
ajst-1433	74	5	liu	liu	PROPN
ajst-1433	74	6	s	s	PROPN
ajst-1433	74	7	,	,	PUNCT
ajst-1433	74	8	qi	qi	PROPN
ajst-1433	74	9	l	l	NOUN
ajst-1433	74	10	,	,	PUNCT
ajst-1433	74	11	qin	qin	PROPN
ajst-1433	74	12	h	h	PROPN
ajst-1433	74	13	,	,	PUNCT
ajst-1433	74	14	et	et	PROPN
ajst-1433	74	15	al	al	PROPN
ajst-1433	74	16	.	.	PROPN
ajst-1433	74	17	path	path	PROPN
ajst-1433	74	18	aggregation	aggregation	NOUN
ajst-1433	74	19	network	network	NOUN
ajst-1433	74	20	for	for	ADP
ajst-1433	74	21	instance	instance	NOUN
ajst-1433	74	22	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-1433	74	23	of	of	ADP
ajst-1433	74	24	the	the	DET
ajst-1433	74	25	ieee	ieee	NOUN
ajst-1433	74	26	conference	conference	NOUN
ajst-1433	74	27	on	on	ADP
ajst-1433	74	28	computer	computer	NOUN
ajst-1433	74	29	vision	vision	NOUN
ajst-1433	74	30	and	and	CCONJ
ajst-1433	74	31	pattern	pattern	NOUN
ajst-1433	74	32	recognition	recognition	NOUN
ajst-1433	74	33	.	.	PUNCT
ajst-1433	75	1	2018	2018	NUM
ajst-1433	75	2	:	:	PUNCT
ajst-1433	75	3	8759	8759	NUM
ajst-1433	75	4	-	-	SYM
ajst-1433	75	5	8768	8768	NUM
ajst-1433	75	6	.	.	PUNCT
ajst-1433	76	1	[	[	X
ajst-1433	76	2	2	2	NUM
ajst-1433	76	3	]	]	SYM
ajst-1433	76	4	li	li	PROPN
ajst-1433	76	5	y	y	PROPN
ajst-1433	76	6	,	,	PUNCT
ajst-1433	76	7	qi	qi	PROPN
ajst-1433	76	8	h	h	NOUN
ajst-1433	76	9	,	,	PUNCT
ajst-1433	76	10	dai	dai	PROPN
ajst-1433	76	11	j	j	PROPN
ajst-1433	76	12	,	,	PUNCT
ajst-1433	76	13	et	et	PROPN
ajst-1433	76	14	al	al	PROPN
ajst-1433	76	15	.	.	PUNCT
ajst-1433	76	16	fully	fully	ADV
ajst-1433	76	17	convolutional	convolutional	ADJ
ajst-1433	76	18	instance	instance	NOUN
ajst-1433	76	19	-	-	PUNCT
ajst-1433	76	20	aware	aware	ADJ
ajst-1433	76	21	semantic	semantic	ADJ
ajst-1433	76	22	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-1433	76	23	of	of	ADP
ajst-1433	76	24	the	the	DET
ajst-1433	76	25	ieee	ieee	NOUN
ajst-1433	76	26	conference	conference	NOUN
ajst-1433	76	27	on	on	ADP
ajst-1433	76	28	computer	computer	NOUN
ajst-1433	76	29	vision	vision	NOUN
ajst-1433	76	30	and	and	CCONJ
ajst-1433	76	31	pattern	pattern	NOUN
ajst-1433	76	32	recognition	recognition	NOUN
ajst-1433	76	33	.	.	PUNCT
ajst-1433	77	1	2017	2017	NUM
ajst-1433	77	2	:	:	PUNCT
ajst-1433	77	3	2359	2359	NUM
ajst-1433	77	4	-	-	SYM
ajst-1433	77	5	2367	2367	NUM
ajst-1433	77	6	.	.	PUNCT
ajst-1433	78	1	[	[	X
ajst-1433	78	2	3	3	NUM
ajst-1433	78	3	]	]	PUNCT
ajst-1433	78	4	xu	xu	PROPN
ajst-1433	78	5	w	w	PROPN
ajst-1433	78	6	,	,	PUNCT
ajst-1433	78	7	wang	wang	PROPN
ajst-1433	78	8	h	h	PROPN
ajst-1433	78	9	,	,	PUNCT
ajst-1433	78	10	qi	qi	PROPN
ajst-1433	78	11	f	f	PROPN
ajst-1433	78	12	,	,	PUNCT
ajst-1433	78	13	et	et	PROPN
ajst-1433	78	14	al	al	PROPN
ajst-1433	78	15	.	.	PROPN
ajst-1433	78	16	explicit	explicit	ADJ
ajst-1433	78	17	shape	shape	NOUN
ajst-1433	78	18	encoding	encoding	NOUN
ajst-1433	78	19	for	for	ADP
ajst-1433	78	20	realtime	realtime	ADJ
ajst-1433	78	21	instance	instance	NOUN
ajst-1433	78	22	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-1433	78	23	of	of	ADP
ajst-1433	78	24	the	the	DET
ajst-1433	78	25	ieee	ieee	NOUN
ajst-1433	78	26	/	/	SYM
ajst-1433	78	27	cvf	cvf	NOUN
ajst-1433	78	28	international	international	ADJ
ajst-1433	78	29	conference	conference	NOUN
ajst-1433	78	30	on	on	ADP
ajst-1433	78	31	computer	computer	NOUN
ajst-1433	78	32	vision	vision	NOUN
ajst-1433	78	33	.	.	PUNCT
ajst-1433	79	1	2019	2019	NUM
ajst-1433	79	2	:	:	PUNCT
ajst-1433	79	3	51685177	51685177	NUM
ajst-1433	79	4	.	.	PUNCT
ajst-1433	80	1	[	[	X
ajst-1433	80	2	4	4	NUM
ajst-1433	80	3	]	]	SYM
ajst-1433	80	4	yuan	yuan	NOUN
ajst-1433	80	5	z	z	PROPN
ajst-1433	80	6	w	w	PROPN
ajst-1433	80	7	,	,	PUNCT
ajst-1433	80	8	zhang	zhang	PROPN
ajst-1433	80	9	j.	j.	PROPN
ajst-1433	80	10	feature	feature	PROPN
ajst-1433	80	11	extraction	extraction	NOUN
ajst-1433	80	12	and	and	CCONJ
ajst-1433	80	13	image	image	NOUN
ajst-1433	80	14	retrieval	retrieval	NOUN
ajst-1433	80	15	based	base	VERB
ajst-1433	80	16	on	on	ADP
ajst-1433	80	17	alexnet[c]//eighth	alexnet[c]//eighth	PROPN
ajst-1433	80	18	international	international	ADJ
ajst-1433	80	19	conference	conference	NOUN
ajst-1433	80	20	on	on	ADP
ajst-1433	80	21	digital	digital	ADJ
ajst-1433	80	22	image	image	NOUN
ajst-1433	80	23	processing	processing	NOUN
ajst-1433	80	24	(	(	PUNCT
ajst-1433	80	25	icdip	icdip	NOUN
ajst-1433	80	26	2016	2016	NUM
ajst-1433	80	27	)	)	PUNCT
ajst-1433	80	28	.	.	PUNCT
ajst-1433	81	1	spie	spie	NOUN
ajst-1433	81	2	,	,	PUNCT
ajst-1433	81	3	2016	2016	NUM
ajst-1433	81	4	,	,	PUNCT
ajst-1433	81	5	10033	10033	NUM
ajst-1433	81	6	:	:	PUNCT
ajst-1433	81	7	65	65	NUM
ajst-1433	81	8	-	-	SYM
ajst-1433	81	9	69	69	NUM
ajst-1433	81	10	.	.	PUNCT
ajst-1433	82	1	[	[	X
ajst-1433	82	2	5	5	X
ajst-1433	82	3	]	]	PUNCT
ajst-1433	82	4	iandola	iandola	PROPN
ajst-1433	82	5	f	f	PROPN
ajst-1433	82	6	n	n	PROPN
ajst-1433	82	7	,	,	PUNCT
ajst-1433	82	8	han	han	PROPN
ajst-1433	82	9	s	s	PROPN
ajst-1433	82	10	,	,	PUNCT
ajst-1433	82	11	moskewicz	moskewicz	PROPN
ajst-1433	82	12	m	m	PROPN
ajst-1433	82	13	w	w	PROPN
ajst-1433	82	14	,	,	PUNCT
ajst-1433	82	15	et	et	PROPN
ajst-1433	82	16	al	al	PROPN
ajst-1433	82	17	.	.	PUNCT
ajst-1433	82	18	squeezenet	squeezenet	NOUN
ajst-1433	82	19	:	:	PUNCT
ajst-1433	82	20	alexnet	alexnet	ADJ
ajst-1433	82	21	-	-	PUNCT
ajst-1433	82	22	level	level	NOUN
ajst-1433	82	23	accuracy	accuracy	NOUN
ajst-1433	82	24	with	with	ADP
ajst-1433	82	25	50x	50x	NUM
ajst-1433	82	26	fewer	few	ADJ
ajst-1433	82	27	parameters	parameter	NOUN
ajst-1433	82	28	and	and	CCONJ
ajst-1433	82	29	<	<	X
ajst-1433	82	30	0.5	0.5	NUM
ajst-1433	82	31	mb	mb	PROPN
ajst-1433	82	32	model	model	NOUN
ajst-1433	82	33	size[j	size[j	PROPN
ajst-1433	82	34	]	]	PUNCT
ajst-1433	82	35	.	.	PUNCT
ajst-1433	83	1	arxiv	arxiv	PROPN
ajst-1433	83	2	preprint	preprint	PROPN
ajst-1433	83	3	arxiv:1602.07360	arxiv:1602.07360	NOUN
ajst-1433	83	4	,	,	PUNCT
ajst-1433	83	5	2016	2016	NUM
ajst-1433	83	6	.	.	PUNCT
ajst-1433	84	1	[	[	X
ajst-1433	84	2	6	6	X
ajst-1433	84	3	]	]	PUNCT
ajst-1433	84	4	szegedy	szegedy	NOUN
ajst-1433	84	5	c	c	PROPN
ajst-1433	84	6	,	,	PUNCT
ajst-1433	84	7	vanhoucke	vanhoucke	NOUN
ajst-1433	84	8	v	v	NOUN
ajst-1433	84	9	,	,	PUNCT
ajst-1433	84	10	ioffe	ioffe	PROPN
ajst-1433	84	11	s	s	PART
ajst-1433	84	12	,	,	PUNCT
ajst-1433	84	13	et	et	PROPN
ajst-1433	84	14	al	al	PROPN
ajst-1433	84	15	.	.	PUNCT
ajst-1433	85	1	rethinking	rethink	VERB
ajst-1433	85	2	the	the	DET
ajst-1433	85	3	inception	inception	ADJ
ajst-1433	85	4	architecture	architecture	NOUN
ajst-1433	85	5	for	for	ADP
ajst-1433	85	6	computer	computer	NOUN
ajst-1433	85	7	vision[j	vision[j	PROPN
ajst-1433	85	8	]	]	PUNCT
ajst-1433	85	9	.	.	PUNCT
ajst-1433	86	1	ieee	ieee	PROPN
ajst-1433	86	2	,	,	PUNCT
ajst-1433	86	3	2016:2818	2016:2818	PROPN
ajst-1433	86	4	-	-	SYM
ajst-1433	86	5	2826	2826	NUM
ajst-1433	86	6	.	.	PUNCT
ajst-1433	87	1	[	[	X
ajst-1433	87	2	7	7	X
ajst-1433	87	3	]	]	X
ajst-1433	87	4	howard	howard	PROPN
ajst-1433	87	5	a	a	DET
ajst-1433	87	6	g	g	PROPN
ajst-1433	87	7	,	,	PUNCT
ajst-1433	87	8	zhu	zhu	PROPN
ajst-1433	87	9	m	m	PROPN
ajst-1433	87	10	,	,	PUNCT
ajst-1433	87	11	chen	chen	PROPN
ajst-1433	87	12	b	b	PROPN
ajst-1433	87	13	,	,	PUNCT
ajst-1433	87	14	et	et	PROPN
ajst-1433	87	15	al	al	PROPN
ajst-1433	87	16	.	.	PROPN
ajst-1433	87	17	mobilenets	mobilenet	NOUN
ajst-1433	87	18	:	:	PUNCT
ajst-1433	87	19	efficient	efficient	ADJ
ajst-1433	87	20	convolutional	convolutional	ADJ
ajst-1433	87	21	neural	neural	ADJ
ajst-1433	87	22	networks	network	NOUN
ajst-1433	87	23	for	for	ADP
ajst-1433	87	24	mobile	mobile	ADJ
ajst-1433	87	25	vision	vision	NOUN
ajst-1433	87	26	applications[j	applications[j	PROPN
ajst-1433	87	27	]	]	PUNCT
ajst-1433	87	28	.	.	PUNCT
ajst-1433	88	1	arxiv	arxiv	PROPN
ajst-1433	88	2	preprint	preprint	PROPN
ajst-1433	88	3	arxiv:1704.04861	arxiv:1704.04861	NOUN
ajst-1433	88	4	,	,	PUNCT
ajst-1433	88	5	2017	2017	NUM
ajst-1433	88	6	.	.	PUNCT
ajst-1433	89	1	[	[	X
ajst-1433	89	2	8	8	NUM
ajst-1433	89	3	]	]	X
ajst-1433	89	4	peng	peng	PROPN
ajst-1433	89	5	s	s	PROPN
ajst-1433	89	6	,	,	PUNCT
ajst-1433	89	7	jiang	jiang	PROPN
ajst-1433	89	8	w	w	PROPN
ajst-1433	89	9	,	,	PUNCT
ajst-1433	89	10	pi	pi	PROPN
ajst-1433	89	11	h	h	NOUN
ajst-1433	89	12	,	,	PUNCT
ajst-1433	89	13	et	et	PROPN
ajst-1433	89	14	al	al	PROPN
ajst-1433	89	15	.	.	PUNCT
ajst-1433	90	1	deep	deep	ADJ
ajst-1433	90	2	snake	snake	NOUN
ajst-1433	90	3	for	for	ADP
ajst-1433	90	4	real	real	ADJ
ajst-1433	90	5	-	-	PUNCT
ajst-1433	90	6	time	time	NOUN
ajst-1433	90	7	instance	instance	NOUN
ajst-1433	90	8	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-1433	90	9	of	of	ADP
ajst-1433	90	10	the	the	DET
ajst-1433	90	11	ieee	ieee	NOUN
ajst-1433	90	12	/	/	SYM
ajst-1433	90	13	cvf	cvf	NOUN
ajst-1433	90	14	conference	conference	NOUN
ajst-1433	90	15	on	on	ADP
ajst-1433	90	16	computer	computer	NOUN
ajst-1433	90	17	vision	vision	NOUN
ajst-1433	90	18	and	and	CCONJ
ajst-1433	90	19	pattern	pattern	NOUN
ajst-1433	90	20	recognition	recognition	NOUN
ajst-1433	90	21	.	.	PUNCT
ajst-1433	91	1	2020	2020	NUM
ajst-1433	91	2	:	:	PUNCT
ajst-1433	91	3	8533	8533	NUM
ajst-1433	91	4	-	-	SYM
ajst-1433	91	5	8542	8542	NUM
ajst-1433	91	6	.	.	PUNCT
ajst-1433	92	1	[	[	X
ajst-1433	92	2	9	9	NUM
ajst-1433	92	3	]	]	X
ajst-1433	92	4	zhao	zhao	PROPN
ajst-1433	92	5	x	x	PROPN
ajst-1433	92	6	,	,	PUNCT
ajst-1433	92	7	vemulapalli	vemulapalli	PROPN
ajst-1433	92	8	r	r	PROPN
ajst-1433	92	9	,	,	PUNCT
ajst-1433	92	10	mansfield	mansfield	PROPN
ajst-1433	92	11	p	p	PROPN
ajst-1433	92	12	a	a	PROPN
ajst-1433	92	13	,	,	PUNCT
ajst-1433	92	14	et	et	PROPN
ajst-1433	92	15	al	al	PROPN
ajst-1433	92	16	.	.	PROPN
ajst-1433	92	17	contrastive	contrastive	ADJ
ajst-1433	92	18	learning	learning	NOUN
ajst-1433	92	19	for	for	ADP
ajst-1433	92	20	label	label	NOUN
ajst-1433	92	21	efficient	efficient	ADJ
ajst-1433	92	22	semantic	semantic	ADJ
ajst-1433	92	23	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-1433	92	24	of	of	ADP
ajst-1433	92	25	the	the	DET
ajst-1433	92	26	ieee	ieee	NOUN
ajst-1433	92	27	/	/	SYM
ajst-1433	92	28	cvf	cvf	NOUN
ajst-1433	92	29	international	international	ADJ
ajst-1433	92	30	conference	conference	NOUN
ajst-1433	92	31	on	on	ADP
ajst-1433	92	32	computer	computer	NOUN
ajst-1433	92	33	vision	vision	NOUN
ajst-1433	92	34	.	.	PUNCT
ajst-1433	93	1	2021	2021	NUM
ajst-1433	93	2	:	:	PUNCT
ajst-1433	93	3	10623	10623	NUM
ajst-1433	93	4	-	-	SYM
ajst-1433	93	5	10633	10633	NUM
ajst-1433	93	6	.	.	PUNCT
ajst-1433	94	1	[	[	X
ajst-1433	94	2	10	10	NUM
ajst-1433	94	3	]	]	X
ajst-1433	94	4	armato	armato	PROPN
ajst-1433	94	5	s	s	PART
ajst-1433	94	6	g	g	NOUN
ajst-1433	94	7	,	,	PUNCT
ajst-1433	94	8	roberts	roberts	PROPN
ajst-1433	94	9	r	r	PROPN
ajst-1433	94	10	y	y	PROPN
ajst-1433	94	11	,	,	PUNCT
ajst-1433	94	12	mcnitt	mcnitt	VERB
ajst-1433	94	13	-	-	PUNCT
ajst-1433	94	14	gray	gray	ADJ
ajst-1433	94	15	m	m	NOUN
ajst-1433	94	16	f	f	NOUN
ajst-1433	94	17	,	,	PUNCT
ajst-1433	94	18	et	et	PROPN
ajst-1433	94	19	al	al	PROPN
ajst-1433	94	20	.	.	PUNCT
ajst-1433	95	1	the	the	DET
ajst-1433	95	2	lung	lung	NOUN
ajst-1433	95	3	image	image	NOUN
ajst-1433	95	4	database	database	NOUN
ajst-1433	95	5	consortium	consortium	PROPN
ajst-1433	95	6	(	(	PUNCT
ajst-1433	95	7	lidc	lidc	NOUN
ajst-1433	95	8	)	)	PUNCT
ajst-1433	95	9	and	and	CCONJ
ajst-1433	95	10	image	image	NOUN
ajst-1433	95	11	database	database	NOUN
ajst-1433	95	12	resource	resource	NOUN
ajst-1433	95	13	initiative	initiative	NOUN
ajst-1433	95	14	(	(	PUNCT
ajst-1433	95	15	idri	idri	ADJ
ajst-1433	95	16	):	):	PUNCT
ajst-1433	95	17	a	a	DET
ajst-1433	95	18	completed	complete	VERB
ajst-1433	95	19	reference	reference	NOUN
ajst-1433	95	20	database	database	NOUN
ajst-1433	95	21	of	of	ADP
ajst-1433	95	22	lung	lung	NOUN
ajst-1433	95	23	nodules	nodule	NOUN
ajst-1433	95	24	on	on	ADP
ajst-1433	95	25	ct	ct	PROPN
ajst-1433	95	26	scans.[j	scans.[j	PROPN
ajst-1433	95	27	]	]	PUNCT
ajst-1433	95	28	.	.	PUNCT
ajst-1433	96	1	academic	academic	ADJ
ajst-1433	96	2	radiology	radiology	NOUN
ajst-1433	96	3	,	,	PUNCT
ajst-1433	96	4	2007	2007	NUM
ajst-1433	96	5	,	,	PUNCT
ajst-1433	96	6	14	14	NUM
ajst-1433	96	7	(	(	PUNCT
ajst-1433	96	8	12):1455	12):1455	NUM
ajst-1433	96	9	-	-	SYM
ajst-1433	96	10	1463	1463	NUM
ajst-1433	96	11	.	.	PUNCT
ajst-1433	97	1	[	[	X
ajst-1433	97	2	11	11	NUM
ajst-1433	97	3	]	]	PUNCT
ajst-1433	97	4	jetley	jetley	PROPN
ajst-1433	97	5	s	s	PROPN
ajst-1433	97	6	,	,	PUNCT
ajst-1433	97	7	sapienza	sapienza	PROPN
ajst-1433	97	8	m	m	PROPN
ajst-1433	97	9	,	,	PUNCT
ajst-1433	97	10	golodetz	golodetz	VERB
ajst-1433	97	11	s	s	PROPN
ajst-1433	97	12	,	,	PUNCT
ajst-1433	97	13	et	et	PROPN
ajst-1433	97	14	al	al	PROPN
ajst-1433	97	15	.	.	PUNCT
ajst-1433	98	1	straight	straight	ADJ
ajst-1433	98	2	to	to	ADP
ajst-1433	98	3	shapes	shape	NOUN
ajst-1433	98	4	:	:	PUNCT
ajst-1433	98	5	realtime	realtime	NOUN
ajst-1433	98	6	detection	detection	NOUN
ajst-1433	98	7	of	of	ADP
ajst-1433	98	8	encoded	encode	VERB
ajst-1433	98	9	shapes[c]//proceedings	shapes[c]//proceeding	NOUN
ajst-1433	98	10	of	of	ADP
ajst-1433	98	11	the	the	DET
ajst-1433	98	12	ieee	ieee	NOUN
ajst-1433	98	13	conference	conference	NOUN
ajst-1433	98	14	on	on	ADP
ajst-1433	98	15	computer	computer	NOUN
ajst-1433	98	16	vision	vision	NOUN
ajst-1433	98	17	and	and	CCONJ
ajst-1433	98	18	pattern	pattern	NOUN
ajst-1433	98	19	recognition	recognition	NOUN
ajst-1433	98	20	.	.	PUNCT
ajst-1433	99	1	2017	2017	NUM
ajst-1433	99	2	:	:	PUNCT
ajst-1433	99	3	6550	6550	NUM
ajst-1433	99	4	-	-	SYM
ajst-1433	99	5	6559	6559	NUM
ajst-1433	99	6	.	.	PUNCT
ajst-1433	100	1	[	[	X
ajst-1433	100	2	12	12	NUM
ajst-1433	100	3	]	]	PUNCT
ajst-1433	100	4	ze	ze	PROPN
ajst-1433	100	5	yang	yang	PROPN
ajst-1433	100	6	,	,	PUNCT
ajst-1433	100	7	yinghao	yinghao	PROPN
ajst-1433	100	8	xu	xu	PROPN
ajst-1433	100	9	,	,	PUNCT
ajst-1433	100	10	han	han	PROPN
ajst-1433	100	11	xue	xue	PROPN
ajst-1433	100	12	,	,	PUNCT
ajst-1433	100	13	zheng	zheng	PROPN
ajst-1433	100	14	zhang	zhang	PROPN
ajst-1433	100	15	,	,	PUNCT
ajst-1433	100	16	raquel	raquel	PROPN
ajst-1433	100	17	urtasun	urtasun	PROPN
ajst-1433	100	18	,	,	PUNCT
ajst-1433	100	19	liwei	liwei	PROPN
ajst-1433	100	20	wang	wang	PROPN
ajst-1433	100	21	,	,	PUNCT
ajst-1433	100	22	stephen	stephen	PROPN
ajst-1433	100	23	lin	lin	PROPN
ajst-1433	100	24	,	,	PUNCT
ajst-1433	100	25	and	and	CCONJ
ajst-1433	100	26	han	han	PROPN
ajst-1433	100	27	hu	hu	PROPN
ajst-1433	100	28	.	.	PUNCT
ajst-1433	101	1	dense	dense	ADJ
ajst-1433	101	2	reppoints	reppoint	NOUN
ajst-1433	101	3	:	:	PUNCT
ajst-1433	101	4	representing	represent	VERB
ajst-1433	101	5	visual	visual	ADJ
ajst-1433	101	6	objects	object	NOUN
ajst-1433	101	7	with	with	ADP
ajst-1433	101	8	dense	dense	ADJ
ajst-1433	101	9	point	point	NOUN
ajst-1433	101	10	sets	set	NOUN
ajst-1433	101	11	.	.	PUNCT
ajst-1433	102	1	arxiv	arxiv	PROPN
ajst-1433	102	2	preprint	preprint	NOUN
ajst-1433	102	3	arxiv:1912.11473	arxiv:1912.11473	NOUN
ajst-1433	102	4	,	,	PUNCT
ajst-1433	102	5	2019	2019	NUM
ajst-1433	102	6	.	.	PUNCT
ajst-1433	103	1	[	[	X
ajst-1433	103	2	13	13	NUM
ajst-1433	103	3	]	]	PUNCT
ajst-1433	103	4	xingyi	xingyi	PROPN
ajst-1433	103	5	zhou	zhou	PROPN
ajst-1433	103	6	,	,	PUNCT
ajst-1433	103	7	dequan	dequan	PROPN
ajst-1433	103	8	wang	wang	PROPN
ajst-1433	103	9	,	,	PUNCT
ajst-1433	103	10	and	and	CCONJ
ajst-1433	103	11	philipp	philipp	PROPN
ajst-1433	103	12	kr¨ahenb¨uhl	kr¨ahenb¨uhl	PROPN
ajst-1433	103	13	.	.	PUNCT
ajst-1433	104	1	objects	object	NOUN
ajst-1433	104	2	as	as	ADP
ajst-1433	104	3	points	point	NOUN
ajst-1433	104	4	.	.	PUNCT
ajst-1433	105	1	arxiv	arxiv	PROPN
ajst-1433	105	2	preprint	preprint	NOUN
ajst-1433	105	3	arxiv:1904.07850	arxiv:1904.07850	NOUN
ajst-1433	105	4	,	,	PUNCT
ajst-1433	105	5	2019	2019	NUM
ajst-1433	105	6	.	.	PUNCT