id	sid	tid	token	lemma	pos
ajst-27738	1	1	academic	academic	ADJ
ajst-27738	1	2	journal	journal	NOUN
ajst-27738	1	3	of	of	ADP
ajst-27738	1	4	science	science	NOUN
ajst-27738	1	5	and	and	CCONJ
ajst-27738	1	6	technology	technology	NOUN
ajst-27738	1	7	issn	issn	NOUN
ajst-27738	1	8	:	:	PUNCT
ajst-27738	1	9	2771	2771	NUM
ajst-27738	1	10	-	-	SYM
ajst-27738	1	11	3032	3032	NUM
ajst-27738	1	12	|	|	NOUN
ajst-27738	1	13	vol	vol	NOUN
ajst-27738	1	14	.	.	PROPN
ajst-27738	1	15	13	13	NUM
ajst-27738	1	16	,	,	PUNCT
ajst-27738	1	17	no	no	INTJ
ajst-27738	1	18	.	.	NOUN
ajst-27738	1	19	2	2	NUM
ajst-27738	1	20	,	,	PUNCT
ajst-27738	1	21	2024	2024	NUM
ajst-27738	1	22	266	266	NUM
ajst-27738	1	23	attention‐refined	attention‐refine	VERB
ajst-27738	1	24	two‐branch	two‐branch	VERB
ajst-27738	1	25	networks	network	NOUN
ajst-27738	1	26	for	for	ADP
ajst-27738	1	27	real‐time	real‐time	NOUN
ajst-27738	1	28	semantic	semantic	ADJ
ajst-27738	1	29	segmentation	segmentation	NOUN
ajst-27738	1	30	shize	shize	NOUN
ajst-27738	1	31	xu	xu	PROPN
ajst-27738	1	32	,	,	PUNCT
ajst-27738	1	33	yongsheng	yongsheng	PROPN
ajst-27738	1	34	dong	dong	PROPN
ajst-27738	1	35	school	school	PROPN
ajst-27738	1	36	of	of	ADP
ajst-27738	1	37	information	information	NOUN
ajst-27738	1	38	engineering	engineering	PROPN
ajst-27738	1	39	,	,	PUNCT
ajst-27738	1	40	henan	henan	PROPN
ajst-27738	1	41	university	university	PROPN
ajst-27738	1	42	of	of	ADP
ajst-27738	1	43	science	science	NOUN
ajst-27738	1	44	and	and	CCONJ
ajst-27738	1	45	technology	technology	NOUN
ajst-27738	1	46	,	,	PUNCT
ajst-27738	1	47	luoyang	luoyang	PROPN
ajst-27738	1	48	471023	471023	NUM
ajst-27738	1	49	,	,	PUNCT
ajst-27738	1	50	china	china	PROPN
ajst-27738	1	51	abstract	abstract	NOUN
ajst-27738	1	52	:	:	PUNCT
ajst-27738	1	53	in	in	ADP
ajst-27738	1	54	real	real	ADJ
ajst-27738	1	55	-	-	PUNCT
ajst-27738	1	56	time	time	NOUN
ajst-27738	1	57	demanding	demand	VERB
ajst-27738	1	58	scenarios	scenario	NOUN
ajst-27738	1	59	as	as	ADP
ajst-27738	1	60	autonomous	autonomous	ADJ
ajst-27738	1	61	driving	driving	NOUN
ajst-27738	1	62	,	,	PUNCT
ajst-27738	1	63	real	real	ADJ
ajst-27738	1	64	-	-	PUNCT
ajst-27738	1	65	time	time	NOUN
ajst-27738	1	66	semantic	semantic	ADJ
ajst-27738	1	67	segmentation	segmentation	NOUN
ajst-27738	1	68	is	be	AUX
ajst-27738	1	69	becoming	become	VERB
ajst-27738	1	70	more	more	ADV
ajst-27738	1	71	and	and	CCONJ
ajst-27738	1	72	more	more	ADV
ajst-27738	1	73	crucial	crucial	ADJ
ajst-27738	1	74	.	.	PUNCT
ajst-27738	2	1	bisenetv2	bisenetv2	PROPN
ajst-27738	2	2	has	have	AUX
ajst-27738	2	3	been	be	AUX
ajst-27738	2	4	shown	show	VERB
ajst-27738	2	5	to	to	PART
ajst-27738	2	6	be	be	AUX
ajst-27738	2	7	an	an	DET
ajst-27738	2	8	effective	effective	ADJ
ajst-27738	2	9	model	model	NOUN
ajst-27738	2	10	,	,	PUNCT
ajst-27738	2	11	but	but	CCONJ
ajst-27738	2	12	its	its	PRON
ajst-27738	2	13	performance	performance	NOUN
ajst-27738	2	14	in	in	ADP
ajst-27738	2	15	improving	improve	VERB
ajst-27738	2	16	speed	speed	NOUN
ajst-27738	2	17	is	be	AUX
ajst-27738	2	18	limited	limit	VERB
ajst-27738	2	19	,	,	PUNCT
ajst-27738	2	20	especially	especially	ADV
ajst-27738	2	21	while	while	SCONJ
ajst-27738	2	22	maintaining	maintain	VERB
ajst-27738	2	23	high	high	ADJ
ajst-27738	2	24	accuracy	accuracy	NOUN
ajst-27738	2	25	.	.	PUNCT
ajst-27738	3	1	furthermore	furthermore	ADV
ajst-27738	3	2	,	,	PUNCT
ajst-27738	3	3	feature	feature	NOUN
ajst-27738	3	4	map	map	NOUN
ajst-27738	3	5	detail	detail	NOUN
ajst-27738	3	6	loss	loss	NOUN
ajst-27738	3	7	results	result	NOUN
ajst-27738	3	8	from	from	ADP
ajst-27738	3	9	combining	combine	VERB
ajst-27738	3	10	high	high	ADJ
ajst-27738	3	11	-	-	PUNCT
ajst-27738	3	12	level	level	NOUN
ajst-27738	3	13	semantic	semantic	ADJ
ajst-27738	3	14	and	and	CCONJ
ajst-27738	3	15	detail	detail	NOUN
ajst-27738	3	16	information	information	NOUN
ajst-27738	3	17	,	,	PUNCT
ajst-27738	3	18	which	which	PRON
ajst-27738	3	19	is	be	AUX
ajst-27738	3	20	especially	especially	ADV
ajst-27738	3	21	crucial	crucial	ADJ
ajst-27738	3	22	for	for	ADP
ajst-27738	3	23	real	real	ADJ
ajst-27738	3	24	-	-	PUNCT
ajst-27738	3	25	time	time	NOUN
ajst-27738	3	26	semantic	semantic	ADJ
ajst-27738	3	27	segmentation	segmentation	NOUN
ajst-27738	3	28	tasks	task	NOUN
ajst-27738	3	29	.	.	PUNCT
ajst-27738	4	1	in	in	ADP
ajst-27738	4	2	this	this	DET
ajst-27738	4	3	paper	paper	NOUN
ajst-27738	4	4	,	,	PUNCT
ajst-27738	4	5	an	an	DET
ajst-27738	4	6	efficient	efficient	ADJ
ajst-27738	4	7	attention	attention	NOUN
ajst-27738	4	8	refined	refine	VERB
ajst-27738	4	9	two	two	NUM
ajst-27738	4	10	-	-	PUNCT
ajst-27738	4	11	branch	branch	NOUN
ajst-27738	4	12	real	real	ADJ
ajst-27738	4	13	-	-	PUNCT
ajst-27738	4	14	time	time	NOUN
ajst-27738	4	15	semantic	semantic	ADJ
ajst-27738	4	16	segmentation	segmentation	NOUN
ajst-27738	4	17	network	network	NOUN
ajst-27738	4	18	(	(	PUNCT
ajst-27738	4	19	artrnet	artrnet	PROPN
ajst-27738	4	20	)	)	PUNCT
ajst-27738	4	21	is	be	AUX
ajst-27738	4	22	designed	design	VERB
ajst-27738	4	23	to	to	PART
ajst-27738	4	24	alleviate	alleviate	VERB
ajst-27738	4	25	the	the	DET
ajst-27738	4	26	above	above	ADJ
ajst-27738	4	27	challenges	challenge	NOUN
ajst-27738	4	28	.	.	PUNCT
ajst-27738	5	1	specifically	specifically	ADV
ajst-27738	5	2	,	,	PUNCT
ajst-27738	5	3	the	the	DET
ajst-27738	5	4	whole	whole	ADJ
ajst-27738	5	5	network	network	NOUN
ajst-27738	5	6	adopts	adopt	VERB
ajst-27738	5	7	a	a	DET
ajst-27738	5	8	two	two	NUM
ajst-27738	5	9	-	-	PUNCT
ajst-27738	5	10	branch	branch	NOUN
ajst-27738	5	11	structure	structure	NOUN
ajst-27738	5	12	:	:	PUNCT
ajst-27738	5	13	a	a	DET
ajst-27738	5	14	spatial	spatial	ADJ
ajst-27738	5	15	detail	detail	NOUN
ajst-27738	5	16	branch	branch	NOUN
ajst-27738	5	17	and	and	CCONJ
ajst-27738	5	18	a	a	DET
ajst-27738	5	19	lightweight	lightweight	ADJ
ajst-27738	5	20	dense	dense	ADJ
ajst-27738	5	21	connectivity	connectivity	NOUN
ajst-27738	5	22	context	context	NOUN
ajst-27738	5	23	refinement	refinement	NOUN
ajst-27738	5	24	branch	branch	NOUN
ajst-27738	5	25	,	,	PUNCT
ajst-27738	5	26	and	and	CCONJ
ajst-27738	5	27	the	the	DET
ajst-27738	5	28	lightweight	lightweight	ADJ
ajst-27738	5	29	dense	dense	ADJ
ajst-27738	5	30	connectivity	connectivity	NOUN
ajst-27738	5	31	context	context	NOUN
ajst-27738	5	32	refinement	refinement	NOUN
ajst-27738	5	33	branch	branch	NOUN
ajst-27738	5	34	is	be	AUX
ajst-27738	5	35	composed	compose	VERB
ajst-27738	5	36	of	of	ADP
ajst-27738	5	37	a	a	DET
ajst-27738	5	38	novel	novel	ADJ
ajst-27738	5	39	downsampling	downsample	VERB
ajst-27738	5	40	module	module	NOUN
ajst-27738	5	41	(	(	PUNCT
ajst-27738	5	42	dsm	dsm	PROPN
ajst-27738	5	43	)	)	PUNCT
ajst-27738	5	44	and	and	CCONJ
ajst-27738	5	45	a	a	DET
ajst-27738	5	46	lightweight	lightweight	ADJ
ajst-27738	5	47	dense	dense	ADJ
ajst-27738	5	48	feature	feature	NOUN
ajst-27738	5	49	module	module	NOUN
ajst-27738	5	50	,	,	PUNCT
ajst-27738	5	51	which	which	PRON
ajst-27738	5	52	achieves	achieve	VERB
ajst-27738	5	53	high	high	ADJ
ajst-27738	5	54	efficiency	efficiency	NOUN
ajst-27738	5	55	in	in	ADP
ajst-27738	5	56	terms	term	NOUN
ajst-27738	5	57	of	of	ADP
ajst-27738	5	58	reduced	reduced	ADJ
ajst-27738	5	59	computational	computational	ADJ
ajst-27738	5	60	cost	cost	NOUN
ajst-27738	5	61	and	and	CCONJ
ajst-27738	5	62	model	model	NOUN
ajst-27738	5	63	size	size	NOUN
ajst-27738	5	64	.	.	PUNCT
ajst-27738	6	1	in	in	ADP
ajst-27738	6	2	addition	addition	NOUN
ajst-27738	6	3	,	,	PUNCT
ajst-27738	6	4	the	the	DET
ajst-27738	6	5	attention	attention	NOUN
ajst-27738	6	6	vector	vector	NOUN
ajst-27738	6	7	of	of	ADP
ajst-27738	6	8	each	each	DET
ajst-27738	6	9	feature	feature	NOUN
ajst-27738	6	10	map	map	NOUN
ajst-27738	6	11	is	be	AUX
ajst-27738	6	12	computed	compute	VERB
ajst-27738	6	13	by	by	ADP
ajst-27738	6	14	residual	residual	ADJ
ajst-27738	6	15	linking	linking	NOUN
ajst-27738	6	16	of	of	ADP
ajst-27738	6	17	the	the	DET
ajst-27738	6	18	attention	attention	NOUN
ajst-27738	6	19	refinement	refinement	NOUN
ajst-27738	6	20	module	module	NOUN
ajst-27738	6	21	(	(	PUNCT
ajst-27738	6	22	arm	arm	NOUN
ajst-27738	6	23	)	)	PUNCT
ajst-27738	6	24	to	to	PART
ajst-27738	6	25	highlight	highlight	VERB
ajst-27738	6	26	the	the	DET
ajst-27738	6	27	features	feature	NOUN
ajst-27738	6	28	.	.	PUNCT
ajst-27738	7	1	a	a	DET
ajst-27738	7	2	low	low	ADJ
ajst-27738	7	3	-	-	PUNCT
ajst-27738	7	4	resolution	resolution	NOUN
ajst-27738	7	5	context	context	NOUN
ajst-27738	7	6	aggregation	aggregation	NOUN
ajst-27738	7	7	module	module	NOUN
ajst-27738	7	8	(	(	PUNCT
ajst-27738	7	9	lrcam	lrcam	NOUN
ajst-27738	7	10	)	)	PUNCT
ajst-27738	7	11	consisting	consist	VERB
ajst-27738	7	12	of	of	ADP
ajst-27738	7	13	lightweight	lightweight	ADJ
ajst-27738	7	14	ghost	ghost	NOUN
ajst-27738	7	15	modules	module	NOUN
ajst-27738	7	16	is	be	AUX
ajst-27738	7	17	also	also	ADV
ajst-27738	7	18	proposed	propose	VERB
ajst-27738	7	19	to	to	PART
ajst-27738	7	20	enhance	enhance	VERB
ajst-27738	7	21	the	the	DET
ajst-27738	7	22	spatial	spatial	ADJ
ajst-27738	7	23	information	information	NOUN
ajst-27738	7	24	processing	processing	NOUN
ajst-27738	7	25	capability	capability	NOUN
ajst-27738	7	26	of	of	ADP
ajst-27738	7	27	the	the	DET
ajst-27738	7	28	lightweight	lightweight	ADJ
ajst-27738	7	29	densely	densely	ADV
ajst-27738	7	30	connected	connected	ADJ
ajst-27738	7	31	context	context	NOUN
ajst-27738	7	32	refinement	refinement	NOUN
ajst-27738	7	33	branch	branch	NOUN
ajst-27738	7	34	.	.	PUNCT
ajst-27738	8	1	in	in	ADP
ajst-27738	8	2	the	the	DET
ajst-27738	8	3	final	final	ADJ
ajst-27738	8	4	fusion	fusion	NOUN
ajst-27738	8	5	stage	stage	NOUN
ajst-27738	8	6	,	,	PUNCT
ajst-27738	8	7	the	the	DET
ajst-27738	8	8	deformed	deform	VERB
ajst-27738	8	9	convolutional	convolutional	ADJ
ajst-27738	8	10	attention	attention	NOUN
ajst-27738	8	11	refinement	refinement	NOUN
ajst-27738	8	12	fusion	fusion	NOUN
ajst-27738	8	13	module	module	NOUN
ajst-27738	8	14	(	(	PUNCT
ajst-27738	8	15	dcarfm	dcarfm	NOUN
ajst-27738	8	16	)	)	PUNCT
ajst-27738	8	17	is	be	AUX
ajst-27738	8	18	proposed	propose	VERB
ajst-27738	8	19	,	,	PUNCT
ajst-27738	8	20	which	which	PRON
ajst-27738	8	21	can	can	AUX
ajst-27738	8	22	enhance	enhance	VERB
ajst-27738	8	23	the	the	DET
ajst-27738	8	24	feature	feature	NOUN
ajst-27738	8	25	expression	expression	NOUN
ajst-27738	8	26	of	of	ADP
ajst-27738	8	27	the	the	DET
ajst-27738	8	28	branch	branch	NOUN
ajst-27738	8	29	and	and	CCONJ
ajst-27738	8	30	improve	improve	VERB
ajst-27738	8	31	the	the	DET
ajst-27738	8	32	final	final	ADJ
ajst-27738	8	33	segmentation	segmentation	NOUN
ajst-27738	8	34	results	result	NOUN
ajst-27738	8	35	by	by	ADP
ajst-27738	8	36	performing	perform	VERB
ajst-27738	8	37	the	the	DET
ajst-27738	8	38	attention	attention	NOUN
ajst-27738	8	39	refinement	refinement	NOUN
ajst-27738	8	40	operation	operation	NOUN
ajst-27738	8	41	on	on	ADP
ajst-27738	8	42	the	the	DET
ajst-27738	8	43	dual	dual	ADJ
ajst-27738	8	44	branches	branch	NOUN
ajst-27738	8	45	separately	separately	ADV
ajst-27738	8	46	.	.	PUNCT
ajst-27738	9	1	finally	finally	ADV
ajst-27738	9	2	,	,	PUNCT
ajst-27738	9	3	experiments	experiment	NOUN
ajst-27738	9	4	on	on	ADP
ajst-27738	9	5	cityscape	cityscape	NOUN
ajst-27738	9	6	and	and	CCONJ
ajst-27738	9	7	camvid	camvid	NOUN
ajst-27738	9	8	datasets	dataset	NOUN
ajst-27738	9	9	show	show	VERB
ajst-27738	9	10	that	that	SCONJ
ajst-27738	9	11	artrnet	artrnet	NOUN
ajst-27738	9	12	achieves	achieve	VERB
ajst-27738	9	13	a	a	DET
ajst-27738	9	14	good	good	ADJ
ajst-27738	9	15	balance	balance	NOUN
ajst-27738	9	16	between	between	ADP
ajst-27738	9	17	segmentation	segmentation	NOUN
ajst-27738	9	18	accuracy	accuracy	NOUN
ajst-27738	9	19	and	and	CCONJ
ajst-27738	9	20	inference	inference	NOUN
ajst-27738	9	21	speed	speed	NOUN
ajst-27738	9	22	.	.	PUNCT
ajst-27738	10	1	on	on	ADP
ajst-27738	10	2	the	the	DET
ajst-27738	10	3	cityscapes	cityscape	NOUN
ajst-27738	10	4	dataset	dataset	VERB
ajst-27738	10	5	,	,	PUNCT
ajst-27738	10	6	we	we	PRON
ajst-27738	10	7	achieved	achieve	VERB
ajst-27738	10	8	75.7	75.7	NUM
ajst-27738	10	9	%	%	NOUN
ajst-27738	10	10	miou	miou	NOUN
ajst-27738	10	11	at	at	ADP
ajst-27738	10	12	132	132	NUM
ajst-27738	10	13	fps	fps	NOUN
ajst-27738	10	14	and	and	CCONJ
ajst-27738	10	15	76.9	76.9	NUM
ajst-27738	10	16	%	%	NOUN
ajst-27738	10	17	miou	miou	NOUN
ajst-27738	10	18	at	at	ADP
ajst-27738	10	19	96	96	NUM
ajst-27738	10	20	fps	fps	NOUN
ajst-27738	10	21	on	on	ADP
ajst-27738	10	22	higher	high	ADJ
ajst-27738	10	23	resolution	resolution	NOUN
ajst-27738	10	24	images	image	NOUN
ajst-27738	10	25	.	.	PUNCT
ajst-27738	11	1	keywords	keyword	NOUN
ajst-27738	11	2	:	:	PUNCT
ajst-27738	11	3	real	real	ADJ
ajst-27738	11	4	-	-	PUNCT
ajst-27738	11	5	time	time	NOUN
ajst-27738	11	6	semantic	semantic	ADJ
ajst-27738	11	7	segmentation	segmentation	NOUN
ajst-27738	11	8	,	,	PUNCT
ajst-27738	11	9	dual	dual	ADJ
ajst-27738	11	10	attention	attention	NOUN
ajst-27738	11	11	,	,	PUNCT
ajst-27738	11	12	two	two	NUM
ajst-27738	11	13	-	-	PUNCT
ajst-27738	11	14	branch	branch	NOUN
ajst-27738	11	15	.	.	PUNCT
ajst-27738	12	1	1	1	X
ajst-27738	12	2	.	.	X
ajst-27738	12	3	introduction	introduction	NOUN
ajst-27738	12	4	semantic	semantic	ADJ
ajst-27738	12	5	segmentation	segmentation	NOUN
ajst-27738	12	6	techniques	technique	NOUN
ajst-27738	12	7	offer	offer	VERB
ajst-27738	12	8	significant	significant	ADJ
ajst-27738	12	9	potential	potential	NOUN
ajst-27738	12	10	and	and	CCONJ
ajst-27738	12	11	opportunities	opportunity	NOUN
ajst-27738	12	12	for	for	ADP
ajst-27738	12	13	several	several	ADJ
ajst-27738	12	14	key	key	ADJ
ajst-27738	12	15	application	application	NOUN
ajst-27738	12	16	areas	area	NOUN
ajst-27738	12	17	.	.	PUNCT
ajst-27738	13	1	it	it	PRON
ajst-27738	13	2	aims	aim	VERB
ajst-27738	13	3	to	to	PART
ajst-27738	13	4	achieve	achieve	VERB
ajst-27738	13	5	accurate	accurate	ADJ
ajst-27738	13	6	classification	classification	NOUN
ajst-27738	13	7	and	and	CCONJ
ajst-27738	13	8	segmentation	segmentation	NOUN
ajst-27738	13	9	of	of	ADP
ajst-27738	13	10	images	image	NOUN
ajst-27738	13	11	by	by	ADP
ajst-27738	13	12	dividing	divide	VERB
ajst-27738	13	13	and	and	CCONJ
ajst-27738	13	14	labelling	labelling	NOUN
ajst-27738	13	15	pixels	pixel	NOUN
ajst-27738	13	16	within	within	ADP
ajst-27738	13	17	an	an	DET
ajst-27738	13	18	image	image	NOUN
ajst-27738	13	19	by	by	ADP
ajst-27738	13	20	setting	set	VERB
ajst-27738	13	21	rules	rule	NOUN
ajst-27738	13	22	.	.	PUNCT
ajst-27738	14	1	it	it	PRON
ajst-27738	14	2	has	have	AUX
ajst-27738	14	3	been	be	AUX
ajst-27738	14	4	widely	widely	ADV
ajst-27738	14	5	used	use	VERB
ajst-27738	14	6	in	in	ADP
ajst-27738	14	7	augmented	augment	VERB
ajst-27738	14	8	reality	reality	NOUN
ajst-27738	15	1	[	[	X
ajst-27738	15	2	1	1	NUM
ajst-27738	15	3	]	]	PUNCT
ajst-27738	15	4	,	,	PUNCT
ajst-27738	15	5	self	self	NOUN
ajst-27738	15	6	-	-	PUNCT
ajst-27738	15	7	driving	drive	VERB
ajst-27738	15	8	cars[2	cars[2	PROPN
ajst-27738	15	9	]	]	PUNCT
ajst-27738	15	10	,	,	PUNCT
ajst-27738	15	11	medical	medical	ADJ
ajst-27738	15	12	image	image	NOUN
ajst-27738	15	13	analysis[3	analysis[3	PROPN
ajst-27738	15	14	]	]	PUNCT
ajst-27738	15	15	,	,	PUNCT
ajst-27738	15	16	remote	remote	ADJ
ajst-27738	15	17	sensing	sense	VERB
ajst-27738	15	18	image	image	NOUN
ajst-27738	15	19	interpretation[4	interpretation[4	NOUN
ajst-27738	15	20	]	]	PUNCT
ajst-27738	15	21	,	,	PUNCT
ajst-27738	15	22	and	and	CCONJ
ajst-27738	15	23	security	security	NOUN
ajst-27738	15	24	surveillance[5	surveillance[5	PROPN
ajst-27738	15	25	]	]	PUNCT
ajst-27738	15	26	.	.	PUNCT
ajst-27738	16	1	deep	deep	ADJ
ajst-27738	16	2	convolutional	convolutional	ADJ
ajst-27738	16	3	neural	neural	ADJ
ajst-27738	16	4	networks	network	NOUN
ajst-27738	16	5	have	have	AUX
ajst-27738	16	6	advanced	advance	VERB
ajst-27738	16	7	significantly	significantly	ADV
ajst-27738	16	8	in	in	ADP
ajst-27738	16	9	semantic	semantic	ADJ
ajst-27738	16	10	segmentation	segmentation	NOUN
ajst-27738	16	11	tasks	task	NOUN
ajst-27738	16	12	in	in	ADP
ajst-27738	16	13	recent	recent	ADJ
ajst-27738	16	14	years	year	NOUN
ajst-27738	16	15	,	,	PUNCT
ajst-27738	16	16	progressively	progressively	ADV
ajst-27738	16	17	taking	take	VERB
ajst-27738	16	18	the	the	DET
ajst-27738	16	19	lead	lead	NOUN
ajst-27738	16	20	as	as	ADP
ajst-27738	16	21	the	the	DET
ajst-27738	16	22	industry	industry	NOUN
ajst-27738	16	23	standard	standard	ADJ
ajst-27738	16	24	technology	technology	NOUN
ajst-27738	16	25	.	.	PUNCT
ajst-27738	17	1	the	the	DET
ajst-27738	17	2	development	development	NOUN
ajst-27738	17	3	of	of	ADP
ajst-27738	17	4	semantic	semantic	ADJ
ajst-27738	17	5	segmentation	segmentation	NOUN
ajst-27738	17	6	algorithms[6	algorithms[6	ADV
ajst-27738	17	7	-	-	SYM
ajst-27738	17	8	8	8	NUM
ajst-27738	17	9	]	]	PUNCT
ajst-27738	17	10	has	have	AUX
ajst-27738	17	11	been	be	AUX
ajst-27738	17	12	facilitated	facilitate	VERB
ajst-27738	17	13	since	since	SCONJ
ajst-27738	17	14	fully	fully	ADV
ajst-27738	17	15	convolutional	convolutional	ADJ
ajst-27738	17	16	networks	network	NOUN
ajst-27738	17	17	(	(	PUNCT
ajst-27738	17	18	fcn)[9	fcn)[9	PROPN
ajst-27738	17	19	]	]	PUNCT
ajst-27738	17	20	was	be	AUX
ajst-27738	17	21	proposed	propose	VERB
ajst-27738	17	22	.	.	PUNCT
ajst-27738	18	1	these	these	DET
ajst-27738	18	2	algorithms	algorithm	NOUN
ajst-27738	18	3	not	not	PART
ajst-27738	18	4	only	only	ADV
ajst-27738	18	5	improve	improve	VERB
ajst-27738	18	6	the	the	DET
ajst-27738	18	7	accuracy	accuracy	NOUN
ajst-27738	18	8	of	of	ADP
ajst-27738	18	9	segmentation	segmentation	NOUN
ajst-27738	18	10	,	,	PUNCT
ajst-27738	18	11	but	but	CCONJ
ajst-27738	18	12	also	also	ADV
ajst-27738	18	13	preserve	preserve	VERB
ajst-27738	18	14	important	important	ADJ
ajst-27738	18	15	details	detail	NOUN
ajst-27738	18	16	of	of	ADP
ajst-27738	18	17	the	the	DET
ajst-27738	18	18	image	image	NOUN
ajst-27738	18	19	.	.	PUNCT
ajst-27738	19	1	with	with	ADP
ajst-27738	19	2	the	the	DET
ajst-27738	19	3	continuous	continuous	ADJ
ajst-27738	19	4	development	development	NOUN
ajst-27738	19	5	of	of	ADP
ajst-27738	19	6	the	the	DET
ajst-27738	19	7	mobile	mobile	ADJ
ajst-27738	19	8	terminal	terminal	PROPN
ajst-27738	19	9	industry	industry	NOUN
ajst-27738	19	10	,	,	PUNCT
ajst-27738	19	11	many	many	ADJ
ajst-27738	19	12	real	real	ADJ
ajst-27738	19	13	-	-	PUNCT
ajst-27738	19	14	time	time	NOUN
ajst-27738	19	15	semantic	semantic	ADJ
ajst-27738	19	16	segmentation	segmentation	NOUN
ajst-27738	19	17	models	model	NOUN
ajst-27738	19	18	[	[	X
ajst-27738	19	19	10	10	NUM
ajst-27738	19	20	-	-	SYM
ajst-27738	19	21	14	14	NUM
ajst-27738	19	22	]	]	PUNCT
ajst-27738	19	23	have	have	AUX
ajst-27738	19	24	emerged	emerge	VERB
ajst-27738	19	25	to	to	PART
ajst-27738	19	26	satisfy	satisfy	VERB
ajst-27738	19	27	the	the	DET
ajst-27738	19	28	needs	need	NOUN
ajst-27738	19	29	of	of	ADP
ajst-27738	19	30	the	the	DET
ajst-27738	19	31	industry	industry	NOUN
ajst-27738	19	32	.	.	PUNCT
ajst-27738	20	1	despite	despite	SCONJ
ajst-27738	20	2	the	the	DET
ajst-27738	20	3	success	success	NOUN
ajst-27738	20	4	of	of	ADP
ajst-27738	20	5	these	these	DET
ajst-27738	20	6	state	state	NOUN
ajst-27738	20	7	-	-	PUNCT
ajst-27738	20	8	of	of	ADP
ajst-27738	20	9	-	-	PUNCT
ajst-27738	20	10	the	the	DET
ajst-27738	20	11	-	-	PUNCT
ajst-27738	20	12	art	art	NOUN
ajst-27738	20	13	models	model	NOUN
ajst-27738	20	14	in	in	ADP
ajst-27738	20	15	improving	improve	VERB
ajst-27738	20	16	segmentation	segmentation	NOUN
ajst-27738	20	17	quality	quality	NOUN
ajst-27738	20	18	,	,	PUNCT
ajst-27738	20	19	they	they	PRON
ajst-27738	20	20	also	also	ADV
ajst-27738	20	21	bring	bring	VERB
ajst-27738	20	22	higher	high	ADJ
ajst-27738	20	23	computational	computational	ADJ
ajst-27738	20	24	demands	demand	NOUN
ajst-27738	20	25	,	,	PUNCT
ajst-27738	20	26	which	which	PRON
ajst-27738	20	27	is	be	AUX
ajst-27738	20	28	a	a	DET
ajst-27738	20	29	major	major	ADJ
ajst-27738	20	30	challenge	challenge	NOUN
ajst-27738	20	31	for	for	ADP
ajst-27738	20	32	real	real	ADJ
ajst-27738	20	33	-	-	PUNCT
ajst-27738	20	34	time	time	NOUN
ajst-27738	20	35	application	application	NOUN
ajst-27738	20	36	scenarios	scenario	NOUN
ajst-27738	20	37	,	,	PUNCT
ajst-27738	20	38	such	such	ADJ
ajst-27738	20	39	as	as	ADP
ajst-27738	20	40	autonomous	autonomous	ADJ
ajst-27738	20	41	driving[2	driving[2	NOUN
ajst-27738	20	42	]	]	PUNCT
ajst-27738	20	43	and	and	CCONJ
ajst-27738	20	44	mechanically	mechanically	ADV
ajst-27738	20	45	assisted	assist	VERB
ajst-27738	20	46	surgery[15	surgery[15	NOUN
ajst-27738	20	47	]	]	PUNCT
ajst-27738	20	48	,	,	PUNCT
ajst-27738	20	49	as	as	SCONJ
ajst-27738	20	50	these	these	DET
ajst-27738	20	51	scenarios	scenario	NOUN
ajst-27738	20	52	require	require	VERB
ajst-27738	20	53	models	model	NOUN
ajst-27738	20	54	that	that	PRON
ajst-27738	20	55	are	be	AUX
ajst-27738	20	56	both	both	ADV
ajst-27738	20	57	highly	highly	ADV
ajst-27738	20	58	accurate	accurate	ADJ
ajst-27738	20	59	and	and	CCONJ
ajst-27738	20	60	have	have	VERB
ajst-27738	20	61	to	to	PART
ajst-27738	20	62	satisfy	satisfy	VERB
ajst-27738	20	63	the	the	DET
ajst-27738	20	64	speed	speed	NOUN
ajst-27738	20	65	requirements	requirement	NOUN
ajst-27738	20	66	of	of	ADP
ajst-27738	20	67	real	real	ADJ
ajst-27738	20	68	-	-	PUNCT
ajst-27738	20	69	time	time	NOUN
ajst-27738	20	70	processing	processing	NOUN
ajst-27738	20	71	.	.	PUNCT
ajst-27738	21	1	in	in	ADP
ajst-27738	21	2	order	order	NOUN
ajst-27738	21	3	to	to	PART
ajst-27738	21	4	adapt	adapt	VERB
ajst-27738	21	5	to	to	ADP
ajst-27738	21	6	the	the	DET
ajst-27738	21	7	demand	demand	NOUN
ajst-27738	21	8	for	for	ADP
ajst-27738	21	9	real	real	ADJ
ajst-27738	21	10	-	-	PUNCT
ajst-27738	21	11	time	time	NOUN
ajst-27738	21	12	interactive	interactive	ADJ
ajst-27738	21	13	performance	performance	NOUN
ajst-27738	21	14	in	in	ADP
ajst-27738	21	15	these	these	DET
ajst-27738	21	16	domains	domain	NOUN
ajst-27738	21	17	,	,	PUNCT
ajst-27738	21	18	a	a	DET
ajst-27738	21	19	large	large	ADJ
ajst-27738	21	20	number	number	NOUN
ajst-27738	21	21	of	of	ADP
ajst-27738	21	22	researchers	researcher	NOUN
ajst-27738	21	23	have	have	AUX
ajst-27738	21	24	developed	develop	VERB
ajst-27738	21	25	semantic	semantic	ADJ
ajst-27738	21	26	segmentation	segmentation	NOUN
ajst-27738	21	27	models	model	NOUN
ajst-27738	21	28	featuring	feature	VERB
ajst-27738	21	29	fewer	few	ADJ
ajst-27738	21	30	parameters	parameter	NOUN
ajst-27738	21	31	and	and	CCONJ
ajst-27738	21	32	rapid	rapid	ADJ
ajst-27738	21	33	reasoning	reasoning	NOUN
ajst-27738	21	34	capabilities[16	capabilities[16	PROPN
ajst-27738	21	35	-	-	PUNCT
ajst-27738	21	36	18	18	NUM
ajst-27738	21	37	]	]	PUNCT
ajst-27738	21	38	.	.	PUNCT
ajst-27738	22	1	these	these	DET
ajst-27738	22	2	models	model	NOUN
ajst-27738	22	3	fall	fall	VERB
ajst-27738	22	4	into	into	ADP
ajst-27738	22	5	two	two	NUM
ajst-27738	22	6	main	main	ADJ
ajst-27738	22	7	categories	category	NOUN
ajst-27738	22	8	:	:	PUNCT
ajst-27738	22	9	one	one	NUM
ajst-27738	22	10	is	be	AUX
ajst-27738	22	11	the	the	DET
ajst-27738	22	12	singlebranch	singlebranch	ADJ
ajst-27738	22	13	encoder	encoder	NOUN
ajst-27738	22	14	-	-	PUNCT
ajst-27738	22	15	decoder	decoder	NOUN
ajst-27738	22	16	architecture	architecture	NOUN
ajst-27738	22	17	,	,	PUNCT
ajst-27738	22	18	whose	whose	DET
ajst-27738	22	19	representative	representative	ADJ
ajst-27738	22	20	studies	study	NOUN
ajst-27738	22	21	[	[	X
ajst-27738	22	22	19	19	NUM
ajst-27738	22	23	-	-	SYM
ajst-27738	22	24	20	20	NUM
ajst-27738	22	25	]	]	PUNCT
ajst-27738	22	26	follow	follow	VERB
ajst-27738	22	27	the	the	DET
ajst-27738	22	28	line	line	NOUN
ajst-27738	22	29	of	of	ADP
ajst-27738	22	30	development	development	NOUN
ajst-27738	22	31	since	since	SCONJ
ajst-27738	22	32	fcn	fcn	PROPN
ajst-27738	22	33	.	.	PUNCT
ajst-27738	23	1	the	the	DET
ajst-27738	23	2	alternative	alternative	ADJ
ajst-27738	23	3	category	category	NOUN
ajst-27738	23	4	encompasses	encompass	VERB
ajst-27738	23	5	multi	multi	ADJ
ajst-27738	23	6	-	-	ADJ
ajst-27738	23	7	branch	branch	ADJ
ajst-27738	23	8	architectures	architecture	NOUN
ajst-27738	23	9	[	[	X
ajst-27738	23	10	16	16	NUM
ajst-27738	23	11	-	-	SYM
ajst-27738	23	12	17	17	NUM
ajst-27738	23	13	]	]	PUNCT
ajst-27738	23	14	that	that	PRON
ajst-27738	23	15	are	be	AUX
ajst-27738	23	16	precisely	precisely	ADV
ajst-27738	23	17	tailored	tailor	VERB
ajst-27738	23	18	to	to	PART
ajst-27738	23	19	address	address	VERB
ajst-27738	23	20	the	the	DET
ajst-27738	23	21	specific	specific	ADJ
ajst-27738	23	22	requirements	requirement	NOUN
ajst-27738	23	23	of	of	ADP
ajst-27738	23	24	real	real	ADJ
ajst-27738	23	25	-	-	PUNCT
ajst-27738	23	26	time	time	NOUN
ajst-27738	23	27	semantic	semantic	ADJ
ajst-27738	23	28	segmentation	segmentation	NOUN
ajst-27738	23	29	.	.	PUNCT
ajst-27738	24	1	the	the	DET
ajst-27738	24	2	main	main	ADJ
ajst-27738	24	3	difference	difference	NOUN
ajst-27738	24	4	between	between	ADP
ajst-27738	24	5	the	the	DET
ajst-27738	24	6	two	two	NUM
ajst-27738	24	7	categories	category	NOUN
ajst-27738	24	8	is	be	AUX
ajst-27738	24	9	reflected	reflect	VERB
ajst-27738	24	10	in	in	ADP
ajst-27738	24	11	their	their	PRON
ajst-27738	24	12	approach	approach	NOUN
ajst-27738	24	13	to	to	ADP
ajst-27738	24	14	multiscale	multiscale	ADJ
ajst-27738	24	15	semantic	semantic	ADJ
ajst-27738	24	16	features	feature	NOUN
ajst-27738	24	17	.	.	PUNCT
ajst-27738	25	1	encoderdecoder	encoderdecoder	PROPN
ajst-27738	25	2	architectures	architecture	NOUN
ajst-27738	25	3	typically	typically	ADV
ajst-27738	25	4	capture	capture	VERB
ajst-27738	25	5	the	the	DET
ajst-27738	25	6	semantic	semantic	ADJ
ajst-27738	25	7	information	information	NOUN
ajst-27738	25	8	of	of	ADP
ajst-27738	25	9	an	an	DET
ajst-27738	25	10	image	image	NOUN
ajst-27738	25	11	through	through	ADP
ajst-27738	25	12	layer	layer	NOUN
ajst-27738	25	13	-	-	PUNCT
ajst-27738	25	14	by	by	ADP
ajst-27738	25	15	-	-	PUNCT
ajst-27738	25	16	layer	layer	NOUN
ajst-27738	25	17	downsampling	downsampling	NOUN
ajst-27738	25	18	and	and	CCONJ
ajst-27738	25	19	feature	feature	NOUN
ajst-27738	25	20	fusion	fusion	NOUN
ajst-27738	25	21	techniques	technique	NOUN
ajst-27738	25	22	,	,	PUNCT
ajst-27738	25	23	and	and	CCONJ
ajst-27738	25	24	this	this	DET
ajst-27738	25	25	process	process	NOUN
ajst-27738	25	26	is	be	AUX
ajst-27738	25	27	usually	usually	ADV
ajst-27738	25	28	done	do	VERB
ajst-27738	25	29	in	in	ADP
ajst-27738	25	30	a	a	DET
ajst-27738	25	31	single	single	ADJ
ajst-27738	25	32	processing	processing	NOUN
ajst-27738	25	33	path	path	NOUN
ajst-27738	25	34	.	.	PUNCT
ajst-27738	26	1	in	in	ADP
ajst-27738	26	2	contrast	contrast	NOUN
ajst-27738	26	3	,	,	PUNCT
ajst-27738	26	4	multibranch	multibranch	ADJ
ajst-27738	26	5	architectures	architecture	NOUN
ajst-27738	26	6	offer	offer	VERB
ajst-27738	26	7	a	a	DET
ajst-27738	26	8	distinct	distinct	ADJ
ajst-27738	26	9	viewpoint	viewpoint	NOUN
ajst-27738	26	10	,	,	PUNCT
ajst-27738	26	11	advocating	advocate	VERB
ajst-27738	26	12	that	that	SCONJ
ajst-27738	26	13	spatial	spatial	ADJ
ajst-27738	26	14	detail	detail	NOUN
ajst-27738	26	15	information	information	NOUN
ajst-27738	26	16	and	and	CCONJ
ajst-27738	26	17	high	high	ADJ
ajst-27738	26	18	-	-	PUNCT
ajst-27738	26	19	level	level	NOUN
ajst-27738	26	20	semantic	semantic	ADJ
ajst-27738	26	21	information	information	NOUN
ajst-27738	26	22	can	can	AUX
ajst-27738	26	23	be	be	AUX
ajst-27738	26	24	independently	independently	ADV
ajst-27738	26	25	extracted	extract	VERB
ajst-27738	26	26	to	to	PART
ajst-27738	26	27	capture	capture	VERB
ajst-27738	26	28	the	the	DET
ajst-27738	26	29	multi	multi	ADJ
ajst-27738	26	30	-	-	ADJ
ajst-27738	26	31	scale	scale	ADJ
ajst-27738	26	32	features	feature	NOUN
ajst-27738	26	33	of	of	ADP
ajst-27738	26	34	an	an	DET
ajst-27738	26	35	image	image	NOUN
ajst-27738	26	36	more	more	ADV
ajst-27738	26	37	effectively	effectively	ADV
ajst-27738	26	38	.	.	PUNCT
ajst-27738	27	1	bisenetv2	bisenetv2	ADJ
ajst-27738	28	1	[	[	X
ajst-27738	28	2	18	18	NUM
ajst-27738	28	3	]	]	PUNCT
ajst-27738	28	4	,	,	PUNCT
ajst-27738	28	5	a	a	DET
ajst-27738	28	6	two	two	NUM
ajst-27738	28	7	-	-	PUNCT
ajst-27738	28	8	branch	branch	NOUN
ajst-27738	28	9	network	network	NOUN
ajst-27738	28	10	,	,	PUNCT
ajst-27738	28	11	has	have	AUX
ajst-27738	28	12	become	become	VERB
ajst-27738	28	13	a	a	DET
ajst-27738	28	14	prime	prime	ADJ
ajst-27738	28	15	example	example	NOUN
ajst-27738	28	16	in	in	ADP
ajst-27738	28	17	the	the	DET
ajst-27738	28	18	field	field	NOUN
ajst-27738	28	19	of	of	ADP
ajst-27738	28	20	real	real	ADJ
ajst-27738	28	21	-	-	PUNCT
ajst-27738	28	22	time	time	NOUN
ajst-27738	28	23	semantic	semantic	ADJ
ajst-27738	28	24	segmentation	segmentation	NOUN
ajst-27738	28	25	due	due	ADP
ajst-27738	28	26	to	to	ADP
ajst-27738	28	27	its	its	PRON
ajst-27738	28	28	excellent	excellent	ADJ
ajst-27738	28	29	performance	performance	NOUN
ajst-27738	28	30	.	.	PUNCT
ajst-27738	29	1	compared	compare	VERB
ajst-27738	29	2	with	with	ADP
ajst-27738	29	3	the	the	DET
ajst-27738	29	4	traditional	traditional	ADJ
ajst-27738	29	5	singlebranch	singlebranch	NOUN
ajst-27738	29	6	structure	structure	NOUN
ajst-27738	29	7	,	,	PUNCT
ajst-27738	29	8	the	the	DET
ajst-27738	29	9	two	two	NUM
ajst-27738	29	10	-	-	PUNCT
ajst-27738	29	11	branch	branch	NOUN
ajst-27738	29	12	structure	structure	NOUN
ajst-27738	29	13	not	not	PART
ajst-27738	29	14	only	only	ADV
ajst-27738	29	15	performs	perform	VERB
ajst-27738	29	16	better	well	ADV
ajst-27738	29	17	in	in	ADP
ajst-27738	29	18	boundary	boundary	ADJ
ajst-27738	29	19	and	and	CCONJ
ajst-27738	29	20	small	small	ADJ
ajst-27738	29	21	target	target	NOUN
ajst-27738	29	22	segmentation	segmentation	NOUN
ajst-27738	29	23	,	,	PUNCT
ajst-27738	29	24	but	but	CCONJ
ajst-27738	29	25	also	also	ADV
ajst-27738	29	26	achieves	achieve	VERB
ajst-27738	29	27	a	a	DET
ajst-27738	29	28	significant	significant	ADJ
ajst-27738	29	29	improvement	improvement	NOUN
ajst-27738	29	30	in	in	ADP
ajst-27738	29	31	inference	inference	NOUN
ajst-27738	29	32	speed	speed	NOUN
ajst-27738	29	33	.	.	PUNCT
ajst-27738	30	1	in	in	ADP
ajst-27738	30	2	most	most	ADJ
ajst-27738	30	3	two	two	NUM
ajst-27738	30	4	-	-	PUNCT
ajst-27738	30	5	branch	branch	NOUN
ajst-27738	30	6	networks	network	NOUN
ajst-27738	30	7	,	,	PUNCT
ajst-27738	30	8	features	feature	NOUN
ajst-27738	30	9	are	be	AUX
ajst-27738	30	10	extracted	extract	VERB
ajst-27738	30	11	independently	independently	ADV
ajst-27738	30	12	on	on	ADP
ajst-27738	30	13	paths	path	NOUN
ajst-27738	30	14	with	with	ADP
ajst-27738	30	15	different	different	ADJ
ajst-27738	30	16	resolutions	resolution	NOUN
ajst-27738	30	17	in	in	ADP
ajst-27738	30	18	order	order	NOUN
ajst-27738	30	19	to	to	PART
ajst-27738	30	20	speed	speed	VERB
ajst-27738	30	21	up	up	ADP
ajst-27738	30	22	downsampling	downsample	VERB
ajst-27738	30	23	and	and	CCONJ
ajst-27738	30	24	reduce	reduce	VERB
ajst-27738	30	25	the	the	DET
ajst-27738	30	26	cost	cost	NOUN
ajst-27738	30	27	of	of	ADP
ajst-27738	30	28	memory	memory	NOUN
ajst-27738	30	29	access	access	NOUN
ajst-27738	30	30	,	,	PUNCT
ajst-27738	30	31	which	which	PRON
ajst-27738	30	32	usually	usually	ADV
ajst-27738	30	33	requires	require	VERB
ajst-27738	30	34	the	the	DET
ajst-27738	30	35	network	network	NOUN
ajst-27738	30	36	to	to	PART
ajst-27738	30	37	perform	perform	VERB
ajst-27738	30	38	complex	complex	ADJ
ajst-27738	30	39	feature	feature	NOUN
ajst-27738	30	40	fusion	fusion	NOUN
ajst-27738	30	41	operations	operation	NOUN
ajst-27738	30	42	at	at	ADP
ajst-27738	30	43	a	a	DET
ajst-27738	30	44	later	later	ADJ
ajst-27738	30	45	stage	stage	NOUN
ajst-27738	30	46	.	.	PUNCT
ajst-27738	31	1	in	in	ADP
ajst-27738	31	2	addition	addition	NOUN
ajst-27738	31	3	,	,	PUNCT
ajst-27738	31	4	some	some	DET
ajst-27738	31	5	networks	network	NOUN
ajst-27738	31	6	,	,	PUNCT
ajst-27738	31	7	including	include	VERB
ajst-27738	31	8	bisenetv2	bisenetv2	NOUN
ajst-27738	31	9	,	,	PUNCT
ajst-27738	31	10	still	still	ADV
ajst-27738	31	11	rely	rely	VERB
ajst-27738	31	12	on	on	ADP
ajst-27738	31	13	handdesigned	handdesigned	ADJ
ajst-27738	31	14	lightweight	lightweight	ADJ
ajst-27738	31	15	backbones	backbone	NOUN
ajst-27738	31	16	,	,	PUNCT
ajst-27738	31	17	which	which	PRON
ajst-27738	31	18	limits	limit	VERB
ajst-27738	31	19	their	their	PRON
ajst-27738	31	20	performance	performance	NOUN
ajst-27738	31	21	upper	upper	ADV
ajst-27738	31	22	bound	bind	VERB
ajst-27738	31	23	to	to	ADP
ajst-27738	31	24	some	some	DET
ajst-27738	31	25	extent	extent	NOUN
ajst-27738	31	26	.	.	PUNCT
ajst-27738	32	1	the	the	DET
ajst-27738	32	2	study	study	NOUN
ajst-27738	32	3	introduces	introduce	VERB
ajst-27738	32	4	a	a	DET
ajst-27738	32	5	novel	novel	NOUN
ajst-27738	32	6	,	,	PUNCT
ajst-27738	32	7	dual	dual	ADJ
ajst-27738	32	8	-	-	PUNCT
ajst-27738	32	9	branch	branch	NOUN
ajst-27738	32	10	architecture	architecture	NOUN
ajst-27738	32	11	for	for	ADP
ajst-27738	32	12	real	real	ADJ
ajst-27738	32	13	-	-	PUNCT
ajst-27738	32	14	time	time	NOUN
ajst-27738	32	15	processing	processing	NOUN
ajst-27738	32	16	,	,	PUNCT
ajst-27738	32	17	designated	designate	VERB
ajst-27738	32	18	as	as	ADP
ajst-27738	32	19	the	the	DET
ajst-27738	32	20	artrnet	artrnet	NOUN
ajst-27738	32	21	.	.	PUNCT
ajst-27738	33	1	the	the	DET
ajst-27738	33	2	aim	aim	NOUN
ajst-27738	33	3	is	be	AUX
ajst-27738	33	4	to	to	PART
ajst-27738	33	5	improve	improve	VERB
ajst-27738	33	6	segmentation	segmentation	NOUN
ajst-27738	33	7	accuracy	accuracy	NOUN
ajst-27738	33	8	,	,	PUNCT
ajst-27738	33	9	structure	structure	NOUN
ajst-27738	33	10	interpretability	interpretability	NOUN
ajst-27738	33	11	,	,	PUNCT
ajst-27738	33	12	and	and	CCONJ
ajst-27738	33	13	performance	performance	NOUN
ajst-27738	33	14	that	that	PRON
ajst-27738	33	15	can	can	AUX
ajst-27738	33	16	compete	compete	VERB
ajst-27738	33	17	with	with	ADP
ajst-27738	33	18	existing	exist	VERB
ajst-27738	33	19	methods	method	NOUN
ajst-27738	33	20	.	.	PUNCT
ajst-27738	34	1	the	the	DET
ajst-27738	34	2	specific	specific	ADJ
ajst-27738	34	3	structure	structure	NOUN
ajst-27738	34	4	is	be	AUX
ajst-27738	34	5	shown	show	VERB
ajst-27738	34	6	in	in	ADP
ajst-27738	34	7	figure	figure	NOUN
ajst-27738	34	8	1	1	NUM
ajst-27738	34	9	,	,	PUNCT
ajst-27738	34	10	artrnet	artrnet	NOUN
ajst-27738	34	11	adopts	adopt	VERB
ajst-27738	34	12	a	a	DET
ajst-27738	34	13	267	267	NUM
ajst-27738	34	14	coder	coder	NOUN
ajst-27738	34	15	-	-	PUNCT
ajst-27738	34	16	decoder	decoder	NOUN
ajst-27738	34	17	architecture	architecture	NOUN
ajst-27738	34	18	.	.	PUNCT
ajst-27738	35	1	the	the	DET
ajst-27738	35	2	entire	entire	ADJ
ajst-27738	35	3	network	network	NOUN
ajst-27738	35	4	uses	use	VERB
ajst-27738	35	5	a	a	DET
ajst-27738	35	6	dual	dual	ADJ
ajst-27738	35	7	branching	branch	VERB
ajst-27738	35	8	structure	structure	NOUN
ajst-27738	35	9	:	:	PUNCT
ajst-27738	35	10	a	a	DET
ajst-27738	35	11	spatial	spatial	ADJ
ajst-27738	35	12	detail	detail	NOUN
ajst-27738	35	13	branch	branch	NOUN
ajst-27738	35	14	and	and	CCONJ
ajst-27738	35	15	a	a	DET
ajst-27738	35	16	lightweight	lightweight	ADJ
ajst-27738	35	17	densely	densely	ADV
ajst-27738	35	18	connected	connect	VERB
ajst-27738	35	19	contextual	contextual	ADJ
ajst-27738	35	20	refinement	refinement	NOUN
ajst-27738	35	21	branch	branch	NOUN
ajst-27738	35	22	,	,	PUNCT
ajst-27738	35	23	which	which	PRON
ajst-27738	35	24	achieves	achieve	VERB
ajst-27738	35	25	high	high	ADJ
ajst-27738	35	26	efficiency	efficiency	NOUN
ajst-27738	35	27	with	with	ADP
ajst-27738	35	28	reduced	reduced	ADJ
ajst-27738	35	29	computational	computational	ADJ
ajst-27738	35	30	cost	cost	NOUN
ajst-27738	35	31	and	and	CCONJ
ajst-27738	35	32	model	model	NOUN
ajst-27738	35	33	size	size	NOUN
ajst-27738	35	34	.	.	PUNCT
ajst-27738	36	1	during	during	ADP
ajst-27738	36	2	the	the	DET
ajst-27738	36	3	final	final	ADJ
ajst-27738	36	4	fusion	fusion	NOUN
ajst-27738	36	5	stage	stage	NOUN
ajst-27738	36	6	,	,	PUNCT
ajst-27738	36	7	the	the	DET
ajst-27738	36	8	feature	feature	NOUN
ajst-27738	36	9	representation	representation	NOUN
ajst-27738	36	10	of	of	ADP
ajst-27738	36	11	each	each	DET
ajst-27738	36	12	branch	branch	NOUN
ajst-27738	36	13	can	can	AUX
ajst-27738	36	14	be	be	AUX
ajst-27738	36	15	enhanced	enhance	VERB
ajst-27738	36	16	by	by	ADP
ajst-27738	36	17	independently	independently	ADV
ajst-27738	36	18	applying	apply	VERB
ajst-27738	36	19	the	the	DET
ajst-27738	36	20	attention	attention	NOUN
ajst-27738	36	21	refinement	refinement	NOUN
ajst-27738	36	22	operation	operation	NOUN
ajst-27738	36	23	to	to	ADP
ajst-27738	36	24	the	the	DET
ajst-27738	36	25	dual	dual	ADJ
ajst-27738	36	26	branches	branch	NOUN
ajst-27738	36	27	,	,	PUNCT
ajst-27738	36	28	and	and	CCONJ
ajst-27738	36	29	at	at	ADP
ajst-27738	36	30	the	the	DET
ajst-27738	36	31	same	same	ADJ
ajst-27738	36	32	time	time	NOUN
ajst-27738	36	33	,	,	PUNCT
ajst-27738	36	34	it	it	PRON
ajst-27738	36	35	can	can	AUX
ajst-27738	36	36	replace	replace	VERB
ajst-27738	36	37	some	some	DET
ajst-27738	36	38	complex	complex	ADJ
ajst-27738	36	39	attention	attention	NOUN
ajst-27738	36	40	computations	computation	NOUN
ajst-27738	36	41	.	.	PUNCT
ajst-27738	37	1	our	our	PRON
ajst-27738	37	2	main	main	ADJ
ajst-27738	37	3	contributions	contribution	NOUN
ajst-27738	37	4	can	can	AUX
ajst-27738	37	5	be	be	AUX
ajst-27738	37	6	outlined	outline	VERB
ajst-27738	37	7	as	as	SCONJ
ajst-27738	37	8	follows	follow	VERB
ajst-27738	37	9	:	:	PUNCT
ajst-27738	37	10	(	(	PUNCT
ajst-27738	37	11	1	1	X
ajst-27738	37	12	)	)	PUNCT
ajst-27738	37	13	we	we	PRON
ajst-27738	37	14	propose	propose	VERB
ajst-27738	37	15	a	a	DET
ajst-27738	37	16	lightweight	lightweight	ADJ
ajst-27738	37	17	dense	dense	ADJ
ajst-27738	37	18	connectivity	connectivity	NOUN
ajst-27738	37	19	context	context	NOUN
ajst-27738	37	20	refinement	refinement	NOUN
ajst-27738	37	21	branch	branch	NOUN
ajst-27738	37	22	consisting	consist	VERB
ajst-27738	37	23	of	of	ADP
ajst-27738	37	24	a	a	DET
ajst-27738	37	25	novel	novel	ADJ
ajst-27738	37	26	downsampling	downsample	VERB
ajst-27738	37	27	module	module	NOUN
ajst-27738	37	28	(	(	PUNCT
ajst-27738	37	29	dsm	dsm	PROPN
ajst-27738	37	30	)	)	PUNCT
ajst-27738	37	31	and	and	CCONJ
ajst-27738	37	32	a	a	DET
ajst-27738	37	33	lightweight	lightweight	ADJ
ajst-27738	37	34	dense	dense	ADJ
ajst-27738	37	35	feature	feature	NOUN
ajst-27738	37	36	module	module	NOUN
ajst-27738	37	37	,	,	PUNCT
ajst-27738	37	38	which	which	PRON
ajst-27738	37	39	achieves	achieve	VERB
ajst-27738	37	40	high	high	ADJ
ajst-27738	37	41	efficiency	efficiency	NOUN
ajst-27738	37	42	with	with	ADP
ajst-27738	37	43	reduced	reduced	ADJ
ajst-27738	37	44	computational	computational	ADJ
ajst-27738	37	45	cost	cost	NOUN
ajst-27738	37	46	and	and	CCONJ
ajst-27738	37	47	model	model	NOUN
ajst-27738	37	48	size	size	NOUN
ajst-27738	37	49	.	.	PUNCT
ajst-27738	38	1	(	(	PUNCT
ajst-27738	38	2	2	2	X
ajst-27738	38	3	)	)	PUNCT
ajst-27738	38	4	we	we	PRON
ajst-27738	38	5	propose	propose	VERB
ajst-27738	38	6	an	an	DET
ajst-27738	38	7	attention	attention	NOUN
ajst-27738	38	8	refinement	refinement	NOUN
ajst-27738	38	9	module	module	NOUN
ajst-27738	38	10	(	(	PUNCT
ajst-27738	38	11	arm	arm	NOUN
ajst-27738	38	12	)	)	PUNCT
ajst-27738	38	13	.	.	PUNCT
ajst-27738	39	1	to	to	PART
ajst-27738	39	2	compute	compute	VERB
ajst-27738	39	3	the	the	DET
ajst-27738	39	4	attention	attention	NOUN
ajst-27738	39	5	vector	vector	NOUN
ajst-27738	39	6	of	of	ADP
ajst-27738	39	7	each	each	DET
ajst-27738	39	8	feature	feature	NOUN
ajst-27738	39	9	map	map	NOUN
ajst-27738	39	10	as	as	ADP
ajst-27738	39	11	a	a	DET
ajst-27738	39	12	way	way	NOUN
ajst-27738	39	13	to	to	PART
ajst-27738	39	14	highlight	highlight	VERB
ajst-27738	39	15	features	feature	NOUN
ajst-27738	39	16	.	.	PUNCT
ajst-27738	40	1	we	we	PRON
ajst-27738	40	2	also	also	ADV
ajst-27738	40	3	propose	propose	VERB
ajst-27738	40	4	a	a	DET
ajst-27738	40	5	low	low	ADJ
ajst-27738	40	6	resolution	resolution	NOUN
ajst-27738	40	7	context	context	NOUN
ajst-27738	40	8	aggregation	aggregation	NOUN
ajst-27738	40	9	module	module	NOUN
ajst-27738	40	10	(	(	PUNCT
ajst-27738	40	11	lrcam	lrcam	NOUN
ajst-27738	40	12	)	)	PUNCT
ajst-27738	40	13	consisting	consist	VERB
ajst-27738	40	14	of	of	ADP
ajst-27738	40	15	lightweight	lightweight	ADJ
ajst-27738	40	16	ghost	ghost	NOUN
ajst-27738	40	17	modules	module	NOUN
ajst-27738	40	18	to	to	PART
ajst-27738	40	19	enhance	enhance	VERB
ajst-27738	40	20	the	the	DET
ajst-27738	40	21	spatial	spatial	ADJ
ajst-27738	40	22	information	information	NOUN
ajst-27738	40	23	processing	processing	NOUN
ajst-27738	40	24	capability	capability	NOUN
ajst-27738	40	25	of	of	ADP
ajst-27738	40	26	lightweight	lightweight	ADJ
ajst-27738	40	27	densely	densely	ADV
ajst-27738	40	28	connected	connect	VERB
ajst-27738	40	29	context	context	NOUN
ajst-27738	40	30	refinement	refinement	NOUN
ajst-27738	40	31	branches	branch	NOUN
ajst-27738	40	32	.	.	PUNCT
ajst-27738	41	1	(	(	PUNCT
ajst-27738	41	2	3	3	X
ajst-27738	41	3	)	)	PUNCT
ajst-27738	41	4	we	we	PRON
ajst-27738	41	5	propose	propose	VERB
ajst-27738	41	6	a	a	DET
ajst-27738	41	7	deformed	deform	VERB
ajst-27738	41	8	convolutional	convolutional	ADJ
ajst-27738	41	9	attention	attention	NOUN
ajst-27738	41	10	refinement	refinement	NOUN
ajst-27738	41	11	fusion	fusion	NOUN
ajst-27738	41	12	module	module	NOUN
ajst-27738	41	13	(	(	PUNCT
ajst-27738	41	14	dcarfm	dcarfm	NOUN
ajst-27738	41	15	)	)	PUNCT
ajst-27738	41	16	,	,	PUNCT
ajst-27738	41	17	which	which	PRON
ajst-27738	41	18	is	be	AUX
ajst-27738	41	19	able	able	ADJ
ajst-27738	41	20	to	to	PART
ajst-27738	41	21	enhance	enhance	VERB
ajst-27738	41	22	the	the	DET
ajst-27738	41	23	feature	feature	NOUN
ajst-27738	41	24	expression	expression	NOUN
ajst-27738	41	25	of	of	ADP
ajst-27738	41	26	the	the	DET
ajst-27738	41	27	branch	branch	NOUN
ajst-27738	41	28	by	by	ADP
ajst-27738	41	29	performing	perform	VERB
ajst-27738	41	30	separate	separate	ADJ
ajst-27738	41	31	attention	attention	NOUN
ajst-27738	41	32	refinement	refinement	NOUN
ajst-27738	41	33	operations	operation	NOUN
ajst-27738	41	34	on	on	ADP
ajst-27738	41	35	the	the	DET
ajst-27738	41	36	dual	dual	ADJ
ajst-27738	41	37	branches	branch	NOUN
ajst-27738	41	38	in	in	ADP
ajst-27738	41	39	the	the	DET
ajst-27738	41	40	final	final	ADJ
ajst-27738	41	41	fusion	fusion	NOUN
ajst-27738	41	42	stage	stage	NOUN
ajst-27738	41	43	.	.	PUNCT
ajst-27738	42	1	(	(	PUNCT
ajst-27738	42	2	4	4	X
ajst-27738	42	3	)	)	PUNCT
ajst-27738	42	4	based	base	VERB
ajst-27738	42	5	on	on	ADP
ajst-27738	42	6	the	the	DET
ajst-27738	42	7	above	above	ADJ
ajst-27738	42	8	efforts	effort	NOUN
ajst-27738	42	9	,	,	PUNCT
ajst-27738	42	10	we	we	PRON
ajst-27738	42	11	construct	construct	VERB
ajst-27738	42	12	a	a	DET
ajst-27738	42	13	real	real	ADJ
ajst-27738	42	14	-	-	PUNCT
ajst-27738	42	15	time	time	NOUN
ajst-27738	42	16	two	two	NUM
ajst-27738	42	17	-	-	PUNCT
ajst-27738	42	18	branch	branch	NOUN
ajst-27738	42	19	segmentation	segmentation	NOUN
ajst-27738	42	20	network	network	NOUN
ajst-27738	42	21	architecture	architecture	NOUN
ajst-27738	42	22	called	call	VERB
ajst-27738	42	23	artrnet	artrnet	NOUN
ajst-27738	42	24	and	and	CCONJ
ajst-27738	42	25	achieved	achieve	VERB
ajst-27738	42	26	competitive	competitive	ADJ
ajst-27738	42	27	results	result	NOUN
ajst-27738	42	28	on	on	ADP
ajst-27738	42	29	standard	standard	ADJ
ajst-27738	42	30	benchmark	benchmark	NOUN
ajst-27738	42	31	tests	test	NOUN
ajst-27738	42	32	.	.	PUNCT
ajst-27738	43	1	2	2	X
ajst-27738	43	2	.	.	X
ajst-27738	43	3	related	relate	VERB
ajst-27738	43	4	work	work	NOUN
ajst-27738	43	5	2.1	2.1	NUM
ajst-27738	43	6	.	.	PUNCT
ajst-27738	44	1	single	single	ADJ
ajst-27738	44	2	-	-	PUNCT
ajst-27738	44	3	branch	branch	NOUN
ajst-27738	44	4	real	real	ADJ
ajst-27738	44	5	-	-	PUNCT
ajst-27738	44	6	time	time	NOUN
ajst-27738	44	7	semantic	semantic	ADJ
ajst-27738	44	8	segmentation	segmentation	NOUN
ajst-27738	44	9	conventional	conventional	ADJ
ajst-27738	44	10	semantic	semantic	ADJ
ajst-27738	44	11	segmentation	segmentation	NOUN
ajst-27738	44	12	approaches	approach	NOUN
ajst-27738	44	13	primarily	primarily	ADV
ajst-27738	44	14	rely	rely	VERB
ajst-27738	44	15	on	on	ADP
ajst-27738	44	16	established	establish	VERB
ajst-27738	44	17	techniques	technique	NOUN
ajst-27738	44	18	and	and	CCONJ
ajst-27738	44	19	methods	method	NOUN
ajst-27738	44	20	in	in	ADP
ajst-27738	44	21	computer	computer	NOUN
ajst-27738	44	22	vision	vision	NOUN
ajst-27738	44	23	and	and	CCONJ
ajst-27738	44	24	image	image	NOUN
ajst-27738	44	25	processing	processing	NOUN
ajst-27738	44	26	,	,	PUNCT
ajst-27738	44	27	and	and	CCONJ
ajst-27738	44	28	usually	usually	ADV
ajst-27738	44	29	use	use	VERB
ajst-27738	44	30	techniques	technique	NOUN
ajst-27738	44	31	of	of	ADP
ajst-27738	44	32	threshold	threshold	NOUN
ajst-27738	44	33	segmentation[21	segmentation[21	PROPN
ajst-27738	44	34	]	]	PUNCT
ajst-27738	44	35	,	,	PUNCT
ajst-27738	44	36	region	region	NOUN
ajst-27738	44	37	segmentation[22	segmentation[22	PROPN
ajst-27738	44	38	]	]	X
ajst-27738	44	39	,	,	PUNCT
ajst-27738	44	40	image	image	NOUN
ajst-27738	44	41	features[23	features[23	NOUN
ajst-27738	44	42	]	]	PUNCT
ajst-27738	44	43	or	or	CCONJ
ajst-27738	44	44	graph	graph	NOUN
ajst-27738	44	45	models[24	models[24	NOUN
ajst-27738	44	46	]	]	PUNCT
ajst-27738	44	47	for	for	ADP
ajst-27738	44	48	pixel	pixel	ADJ
ajst-27738	44	49	-	-	PUNCT
ajst-27738	44	50	level	level	NOUN
ajst-27738	44	51	classification	classification	NOUN
ajst-27738	44	52	to	to	PART
ajst-27738	44	53	achieve	achieve	VERB
ajst-27738	44	54	semantic	semantic	ADJ
ajst-27738	44	55	segmentation	segmentation	NOUN
ajst-27738	44	56	.	.	PUNCT
ajst-27738	45	1	in	in	ADP
ajst-27738	45	2	recent	recent	ADJ
ajst-27738	45	3	years	year	NOUN
ajst-27738	45	4	,	,	PUNCT
ajst-27738	45	5	within	within	ADP
ajst-27738	45	6	the	the	DET
ajst-27738	45	7	field	field	NOUN
ajst-27738	45	8	of	of	ADP
ajst-27738	45	9	real	real	ADJ
ajst-27738	45	10	-	-	PUNCT
ajst-27738	45	11	time	time	NOUN
ajst-27738	45	12	semantic	semantic	ADJ
ajst-27738	45	13	segmentation	segmentation	NOUN
ajst-27738	45	14	research	research	NOUN
ajst-27738	45	15	,	,	PUNCT
ajst-27738	45	16	some	some	DET
ajst-27738	45	17	approaches	approach	NOUN
ajst-27738	45	18	have	have	AUX
ajst-27738	45	19	adopted	adopt	VERB
ajst-27738	45	20	the	the	DET
ajst-27738	45	21	single	single	ADJ
ajst-27738	45	22	-	-	PUNCT
ajst-27738	45	23	branch	branch	NOUN
ajst-27738	45	24	encoder	encoder	NOUN
ajst-27738	45	25	-	-	PUNCT
ajst-27738	45	26	decoder	decoder	NOUN
ajst-27738	45	27	architecture[9	architecture[9	NOUN
ajst-27738	45	28	,	,	PUNCT
ajst-27738	45	29	25	25	NUM
ajst-27738	45	30	-	-	SYM
ajst-27738	45	31	26	26	NUM
ajst-27738	45	32	]	]	PUNCT
ajst-27738	45	33	as	as	ADP
ajst-27738	45	34	their	their	PRON
ajst-27738	45	35	core	core	NOUN
ajst-27738	45	36	framework	framework	NOUN
ajst-27738	45	37	.	.	PUNCT
ajst-27738	46	1	these	these	DET
ajst-27738	46	2	methods	method	NOUN
ajst-27738	46	3	capture	capture	VERB
ajst-27738	46	4	the	the	DET
ajst-27738	46	5	semantic	semantic	ADJ
ajst-27738	46	6	features	feature	NOUN
ajst-27738	46	7	of	of	ADP
ajst-27738	46	8	an	an	DET
ajst-27738	46	9	image	image	NOUN
ajst-27738	46	10	through	through	ADP
ajst-27738	46	11	layer	layer	NOUN
ajst-27738	46	12	-	-	PUNCT
ajst-27738	46	13	by	by	ADP
ajst-27738	46	14	-	-	PUNCT
ajst-27738	46	15	layer	layer	NOUN
ajst-27738	46	16	downsampling	downsampling	NOUN
ajst-27738	46	17	and	and	CCONJ
ajst-27738	46	18	feature	feature	NOUN
ajst-27738	46	19	fusion	fusion	NOUN
ajst-27738	46	20	techniques	technique	NOUN
ajst-27738	46	21	,	,	PUNCT
ajst-27738	46	22	while	while	SCONJ
ajst-27738	46	23	capturing	capture	VERB
ajst-27738	46	24	both	both	CCONJ
ajst-27738	46	25	low	low	ADJ
ajst-27738	46	26	-	-	PUNCT
ajst-27738	46	27	level	level	NOUN
ajst-27738	46	28	detail	detail	NOUN
ajst-27738	46	29	information	information	NOUN
ajst-27738	46	30	and	and	CCONJ
ajst-27738	46	31	highlevel	highlevel	ADJ
ajst-27738	46	32	semantic	semantic	ADJ
ajst-27738	46	33	information	information	NOUN
ajst-27738	46	34	.	.	PUNCT
ajst-27738	47	1	espnet[19	espnet[19	NOUN
ajst-27738	47	2	]	]	PUNCT
ajst-27738	47	3	enhances	enhance	VERB
ajst-27738	47	4	segmentation	segmentation	NOUN
ajst-27738	47	5	performance	performance	NOUN
ajst-27738	47	6	by	by	ADP
ajst-27738	47	7	capturing	capture	VERB
ajst-27738	47	8	multi	multi	ADJ
ajst-27738	47	9	-	-	ADJ
ajst-27738	47	10	scale	scale	ADJ
ajst-27738	47	11	feature	feature	NOUN
ajst-27738	47	12	information	information	NOUN
ajst-27738	47	13	using	use	VERB
ajst-27738	47	14	dilated	dilated	ADJ
ajst-27738	47	15	convolution	convolution	NOUN
ajst-27738	47	16	at	at	ADP
ajst-27738	47	17	various	various	ADJ
ajst-27738	47	18	scales	scale	NOUN
ajst-27738	47	19	.	.	PUNCT
ajst-27738	48	1	dilated	dilate	VERB
ajst-27738	48	2	convolution	convolution	NOUN
ajst-27738	48	3	enables	enable	VERB
ajst-27738	48	4	the	the	DET
ajst-27738	48	5	network	network	NOUN
ajst-27738	48	6	to	to	PART
ajst-27738	48	7	cover	cover	VERB
ajst-27738	48	8	a	a	DET
ajst-27738	48	9	larger	large	ADJ
ajst-27738	48	10	receptive	receptive	ADJ
ajst-27738	48	11	field	field	NOUN
ajst-27738	48	12	with	with	ADP
ajst-27738	48	13	fewer	few	ADJ
ajst-27738	48	14	parameters	parameter	NOUN
ajst-27738	48	15	and	and	CCONJ
ajst-27738	48	16	less	less	ADJ
ajst-27738	48	17	computation	computation	NOUN
ajst-27738	48	18	,	,	PUNCT
ajst-27738	48	19	which	which	PRON
ajst-27738	48	20	is	be	AUX
ajst-27738	48	21	very	very	ADV
ajst-27738	48	22	efficient	efficient	ADJ
ajst-27738	48	23	when	when	SCONJ
ajst-27738	48	24	processing	process	VERB
ajst-27738	48	25	high	high	ADJ
ajst-27738	48	26	-	-	PUNCT
ajst-27738	48	27	resolution	resolution	NOUN
ajst-27738	48	28	images	image	NOUN
ajst-27738	48	29	.	.	PUNCT
ajst-27738	49	1	edanet[20	edanet[20	NOUN
ajst-27738	49	2	]	]	PUNCT
ajst-27738	49	3	employs	employ	VERB
ajst-27738	49	4	asymmetric	asymmetric	ADJ
ajst-27738	49	5	convolution	convolution	NOUN
ajst-27738	49	6	,	,	PUNCT
ajst-27738	49	7	dilated	dilated	ADJ
ajst-27738	49	8	convolution	convolution	NOUN
ajst-27738	49	9	,	,	PUNCT
ajst-27738	49	10	and	and	CCONJ
ajst-27738	49	11	dense	dense	ADJ
ajst-27738	49	12	concatenation	concatenation	NOUN
ajst-27738	49	13	to	to	PART
ajst-27738	49	14	reduce	reduce	VERB
ajst-27738	49	15	parameters	parameter	NOUN
ajst-27738	49	16	and	and	CCONJ
ajst-27738	49	17	computation	computation	NOUN
ajst-27738	49	18	,	,	PUNCT
ajst-27738	49	19	maintaining	maintain	VERB
ajst-27738	49	20	high	high	ADJ
ajst-27738	49	21	efficiency	efficiency	NOUN
ajst-27738	49	22	and	and	CCONJ
ajst-27738	49	23	accuracy	accuracy	NOUN
ajst-27738	49	24	.	.	PUNCT
ajst-27738	50	1	this	this	DET
ajst-27738	50	2	network	network	NOUN
ajst-27738	50	3	is	be	AUX
ajst-27738	50	4	ideal	ideal	ADJ
ajst-27738	50	5	for	for	ADP
ajst-27738	50	6	high	high	ADJ
ajst-27738	50	7	-	-	PUNCT
ajst-27738	50	8	speed	speed	NOUN
ajst-27738	50	9	processing	processing	NOUN
ajst-27738	50	10	applications	application	NOUN
ajst-27738	50	11	,	,	PUNCT
ajst-27738	50	12	such	such	ADJ
ajst-27738	50	13	as	as	ADP
ajst-27738	50	14	autonomous	autonomous	ADJ
ajst-27738	50	15	driving	driving	NOUN
ajst-27738	50	16	,	,	PUNCT
ajst-27738	50	17	and	and	CCONJ
ajst-27738	50	18	is	be	AUX
ajst-27738	50	19	able	able	ADJ
ajst-27738	50	20	to	to	PART
ajst-27738	50	21	achieve	achieve	VERB
ajst-27738	50	22	fast	fast	ADJ
ajst-27738	50	23	segmentation	segmentation	NOUN
ajst-27738	50	24	performance	performance	NOUN
ajst-27738	50	25	while	while	SCONJ
ajst-27738	50	26	maintaining	maintain	VERB
ajst-27738	50	27	high	high	ADJ
ajst-27738	50	28	-	-	PUNCT
ajst-27738	50	29	resolution	resolution	NOUN
ajst-27738	50	30	inputs	input	NOUN
ajst-27738	50	31	.	.	PUNCT
ajst-27738	51	1	dfanet[27	dfanet[27	PROPN
ajst-27738	51	2	]	]	PUNCT
ajst-27738	51	3	efficiently	efficiently	ADV
ajst-27738	51	4	combines	combine	VERB
ajst-27738	51	5	feature	feature	NOUN
ajst-27738	51	6	information	information	NOUN
ajst-27738	51	7	from	from	ADP
ajst-27738	51	8	different	different	ADJ
ajst-27738	51	9	layers	layer	NOUN
ajst-27738	51	10	through	through	ADP
ajst-27738	51	11	deep	deep	ADJ
ajst-27738	51	12	feature	feature	NOUN
ajst-27738	51	13	aggregation	aggregation	NOUN
ajst-27738	51	14	techniques	technique	NOUN
ajst-27738	51	15	to	to	PART
ajst-27738	51	16	improve	improve	VERB
ajst-27738	51	17	segmentation	segmentation	NOUN
ajst-27738	51	18	accuracy	accuracy	NOUN
ajst-27738	51	19	.	.	PUNCT
ajst-27738	52	1	the	the	DET
ajst-27738	52	2	lightweight	lightweight	ADJ
ajst-27738	52	3	architecture	architecture	NOUN
ajst-27738	52	4	design	design	NOUN
ajst-27738	52	5	of	of	ADP
ajst-27738	52	6	the	the	DET
ajst-27738	52	7	network	network	NOUN
ajst-27738	52	8	allows	allow	VERB
ajst-27738	52	9	it	it	PRON
ajst-27738	52	10	to	to	PART
ajst-27738	52	11	handle	handle	VERB
ajst-27738	52	12	high	high	ADJ
ajst-27738	52	13	-	-	PUNCT
ajst-27738	52	14	resolution	resolution	NOUN
ajst-27738	52	15	images	image	NOUN
ajst-27738	52	16	swiftly	swiftly	ADV
ajst-27738	52	17	,	,	PUNCT
ajst-27738	52	18	meeting	meet	VERB
ajst-27738	52	19	real	real	ADJ
ajst-27738	52	20	-	-	PUNCT
ajst-27738	52	21	time	time	NOUN
ajst-27738	52	22	application	application	NOUN
ajst-27738	52	23	demands	demand	NOUN
ajst-27738	52	24	effectively	effectively	ADV
ajst-27738	52	25	.	.	PUNCT
ajst-27738	53	1	2.2	2.2	NUM
ajst-27738	53	2	.	.	X
ajst-27738	53	3	two	two	NUM
ajst-27738	53	4	-	-	PUNCT
ajst-27738	53	5	branch	branch	NOUN
ajst-27738	53	6	real	real	ADJ
ajst-27738	53	7	-	-	PUNCT
ajst-27738	53	8	time	time	NOUN
ajst-27738	53	9	semantic	semantic	ADJ
ajst-27738	53	10	segmentation	segmentation	NOUN
ajst-27738	53	11	the	the	DET
ajst-27738	53	12	two	two	NUM
ajst-27738	53	13	-	-	PUNCT
ajst-27738	53	14	branch	branch	NOUN
ajst-27738	53	15	architecture	architecture	NOUN
ajst-27738	53	16	effectively	effectively	ADV
ajst-27738	53	17	preserves	preserve	VERB
ajst-27738	53	18	the	the	DET
ajst-27738	53	19	highresolution	highresolution	NOUN
ajst-27738	53	20	details	detail	NOUN
ajst-27738	53	21	of	of	ADP
ajst-27738	53	22	an	an	DET
ajst-27738	53	23	image	image	NOUN
ajst-27738	53	24	by	by	ADP
ajst-27738	53	25	processing	process	VERB
ajst-27738	53	26	features	feature	NOUN
ajst-27738	53	27	at	at	ADP
ajst-27738	53	28	different	different	ADJ
ajst-27738	53	29	scales	scale	NOUN
ajst-27738	53	30	independently	independently	ADV
ajst-27738	53	31	compared	compare	VERB
ajst-27738	53	32	to	to	ADP
ajst-27738	53	33	the	the	DET
ajst-27738	53	34	single	single	ADJ
ajst-27738	53	35	-	-	PUNCT
ajst-27738	53	36	branch	branch	NOUN
ajst-27738	53	37	architecture	architecture	NOUN
ajst-27738	53	38	.	.	PUNCT
ajst-27738	54	1	the	the	DET
ajst-27738	54	2	bisenet	bisenet	NOUN
ajst-27738	54	3	series[17	series[17	PROPN
ajst-27738	54	4	-	-	SYM
ajst-27738	54	5	18	18	NUM
ajst-27738	54	6	]	]	PUNCT
ajst-27738	54	7	is	be	AUX
ajst-27738	54	8	a	a	DET
ajst-27738	54	9	good	good	ADJ
ajst-27738	54	10	example	example	NOUN
ajst-27738	54	11	in	in	ADP
ajst-27738	54	12	this	this	DET
ajst-27738	54	13	regard	regard	NOUN
ajst-27738	54	14	.	.	PUNCT
ajst-27738	55	1	bisenet[17	bisenet[17	PROPN
ajst-27738	55	2	]	]	PUNCT
ajst-27738	55	3	introduces	introduce	NOUN
ajst-27738	55	4	parallel	parallel	ADJ
ajst-27738	55	5	spatial	spatial	ADJ
ajst-27738	55	6	and	and	CCONJ
ajst-27738	55	7	contextual	contextual	ADJ
ajst-27738	55	8	paths	path	NOUN
ajst-27738	55	9	as	as	ADV
ajst-27738	55	10	well	well	ADV
ajst-27738	55	11	as	as	ADP
ajst-27738	55	12	feature	feature	NOUN
ajst-27738	55	13	fusion	fusion	NOUN
ajst-27738	55	14	techniques	technique	NOUN
ajst-27738	55	15	,	,	PUNCT
ajst-27738	55	16	which	which	PRON
ajst-27738	55	17	achieves	achieve	VERB
ajst-27738	55	18	the	the	DET
ajst-27738	55	19	fast	fast	ADJ
ajst-27738	55	20	acquisition	acquisition	NOUN
ajst-27738	55	21	of	of	ADP
ajst-27738	55	22	deep	deep	ADJ
ajst-27738	55	23	semantic	semantic	ADJ
ajst-27738	55	24	information	information	NOUN
ajst-27738	55	25	while	while	SCONJ
ajst-27738	55	26	preserving	preserve	VERB
ajst-27738	55	27	the	the	DET
ajst-27738	55	28	image	image	NOUN
ajst-27738	55	29	details	detail	NOUN
ajst-27738	55	30	.	.	PUNCT
ajst-27738	56	1	it	it	PRON
ajst-27738	56	2	significantly	significantly	ADV
ajst-27738	56	3	improves	improve	VERB
ajst-27738	56	4	the	the	DET
ajst-27738	56	5	performance	performance	NOUN
ajst-27738	56	6	of	of	ADP
ajst-27738	56	7	real	real	ADJ
ajst-27738	56	8	-	-	PUNCT
ajst-27738	56	9	time	time	NOUN
ajst-27738	56	10	semantic	semantic	ADJ
ajst-27738	56	11	segmentation	segmentation	NOUN
ajst-27738	56	12	.	.	PUNCT
ajst-27738	57	1	bisenetv2[18	bisenetv2[18	NOUN
ajst-27738	57	2	]	]	PUNCT
ajst-27738	57	3	simplifies	simplifie	NOUN
ajst-27738	57	4	and	and	CCONJ
ajst-27738	57	5	deepens	deepen	VERB
ajst-27738	57	6	the	the	DET
ajst-27738	57	7	network	network	NOUN
ajst-27738	57	8	structure	structure	NOUN
ajst-27738	57	9	,	,	PUNCT
ajst-27738	57	10	improves	improve	VERB
ajst-27738	57	11	the	the	DET
ajst-27738	57	12	operation	operation	NOUN
ajst-27738	57	13	efficiency	efficiency	NOUN
ajst-27738	57	14	,	,	PUNCT
ajst-27738	57	15	introduces	introduce	VERB
ajst-27738	57	16	a	a	DET
ajst-27738	57	17	bilateral	bilateral	ADJ
ajst-27738	57	18	bootstrap	bootstrap	NOUN
ajst-27738	57	19	aggregation	aggregation	NOUN
ajst-27738	57	20	layer	layer	NOUN
ajst-27738	57	21	,	,	PUNCT
ajst-27738	57	22	and	and	CCONJ
ajst-27738	57	23	combines	combine	VERB
ajst-27738	57	24	details	detail	NOUN
ajst-27738	57	25	and	and	CCONJ
ajst-27738	57	26	semantic	semantic	ADJ
ajst-27738	57	27	features	feature	NOUN
ajst-27738	57	28	more	more	ADV
ajst-27738	57	29	effectively	effectively	ADV
ajst-27738	57	30	.	.	PUNCT
ajst-27738	58	1	however	however	ADV
ajst-27738	58	2	,	,	PUNCT
ajst-27738	58	3	since	since	SCONJ
ajst-27738	58	4	bisenetv2	bisenetv2	NOUN
ajst-27738	58	5	adopts	adopt	VERB
ajst-27738	58	6	a	a	DET
ajst-27738	58	7	fast	fast	ADJ
ajst-27738	58	8	downsampling	downsample	VERB
ajst-27738	58	9	strategy	strategy	NOUN
ajst-27738	58	10	,	,	PUNCT
ajst-27738	58	11	some	some	DET
ajst-27738	58	12	important	important	ADJ
ajst-27738	58	13	detail	detail	NOUN
ajst-27738	58	14	information	information	NOUN
ajst-27738	58	15	may	may	AUX
ajst-27738	58	16	be	be	AUX
ajst-27738	58	17	lost	lose	VERB
ajst-27738	58	18	to	to	ADP
ajst-27738	58	19	some	some	DET
ajst-27738	58	20	extent	extent	NOUN
ajst-27738	58	21	,	,	PUNCT
ajst-27738	58	22	which	which	PRON
ajst-27738	58	23	may	may	AUX
ajst-27738	58	24	affect	affect	VERB
ajst-27738	58	25	the	the	DET
ajst-27738	58	26	accuracy	accuracy	NOUN
ajst-27738	58	27	of	of	ADP
ajst-27738	58	28	segmentation	segmentation	NOUN
ajst-27738	58	29	.	.	PUNCT
ajst-27738	59	1	to	to	PART
ajst-27738	59	2	solve	solve	VERB
ajst-27738	59	3	this	this	DET
ajst-27738	59	4	problem	problem	NOUN
ajst-27738	59	5	,	,	PUNCT
ajst-27738	59	6	fast	fast	ADJ
ajst-27738	59	7	-	-	PUNCT
ajst-27738	59	8	scnn[13	scnn[13	NOUN
ajst-27738	59	9	]	]	PUNCT
ajst-27738	59	10	and	and	CCONJ
ajst-27738	59	11	ddrnet[28	ddrnet[28	PROPN
ajst-27738	59	12	]	]	PUNCT
ajst-27738	59	13	adopt	adopt	VERB
ajst-27738	59	14	a	a	DET
ajst-27738	59	15	singlebranch	singlebranch	ADJ
ajst-27738	59	16	architecture	architecture	NOUN
ajst-27738	59	17	with	with	ADP
ajst-27738	59	18	a	a	DET
ajst-27738	59	19	shared	share	VERB
ajst-27738	59	20	backbone	backbone	NOUN
ajst-27738	59	21	to	to	PART
ajst-27738	59	22	increase	increase	VERB
ajst-27738	59	23	multiple	multiple	ADJ
ajst-27738	59	24	interactions	interaction	NOUN
ajst-27738	59	25	by	by	ADP
ajst-27738	59	26	sharing	share	VERB
ajst-27738	59	27	parameters	parameter	NOUN
ajst-27738	59	28	early	early	ADV
ajst-27738	59	29	in	in	ADP
ajst-27738	59	30	the	the	DET
ajst-27738	59	31	network	network	NOUN
ajst-27738	59	32	.	.	PUNCT
ajst-27738	60	1	2.3	2.3	NUM
ajst-27738	60	2	.	.	PUNCT
ajst-27738	60	3	feature	feature	NOUN
ajst-27738	60	4	fusion	fusion	NOUN
ajst-27738	60	5	module	module	NOUN
ajst-27738	60	6	in	in	ADP
ajst-27738	60	7	semantic	semantic	ADJ
ajst-27738	60	8	segmentation	segmentation	NOUN
ajst-27738	60	9	network	network	NOUN
ajst-27738	60	10	architecture	architecture	NOUN
ajst-27738	60	11	,	,	PUNCT
ajst-27738	60	12	the	the	DET
ajst-27738	60	13	feature	feature	NOUN
ajst-27738	60	14	fusion	fusion	NOUN
ajst-27738	60	15	module	module	NOUN
ajst-27738	60	16	plays	play	VERB
ajst-27738	60	17	a	a	DET
ajst-27738	60	18	critical	critical	ADJ
ajst-27738	60	19	role	role	NOUN
ajst-27738	60	20	in	in	ADP
ajst-27738	60	21	integrating	integrate	VERB
ajst-27738	60	22	features	feature	NOUN
ajst-27738	60	23	from	from	ADP
ajst-27738	60	24	multiple	multiple	ADJ
ajst-27738	60	25	levels	level	NOUN
ajst-27738	60	26	to	to	PART
ajst-27738	60	27	enhance	enhance	VERB
ajst-27738	60	28	the	the	DET
ajst-27738	60	29	model	model	NOUN
ajst-27738	60	30	's	's	PART
ajst-27738	60	31	capability	capability	NOUN
ajst-27738	60	32	to	to	PART
ajst-27738	60	33	understand	understand	VERB
ajst-27738	60	34	both	both	DET
ajst-27738	60	35	global	global	ADJ
ajst-27738	60	36	context	context	NOUN
ajst-27738	60	37	and	and	CCONJ
ajst-27738	60	38	local	local	ADJ
ajst-27738	60	39	details	detail	NOUN
ajst-27738	60	40	of	of	ADP
ajst-27738	60	41	scenes	scene	NOUN
ajst-27738	60	42	.	.	PUNCT
ajst-27738	61	1	this	this	DET
ajst-27738	61	2	integration	integration	NOUN
ajst-27738	61	3	boosts	boost	VERB
ajst-27738	61	4	accuracy	accuracy	NOUN
ajst-27738	61	5	and	and	CCONJ
ajst-27738	61	6	segmentation	segmentation	NOUN
ajst-27738	61	7	effectiveness	effectiveness	NOUN
ajst-27738	61	8	.	.	PUNCT
ajst-27738	62	1	in	in	ADP
ajst-27738	62	2	addition	addition	NOUN
ajst-27738	62	3	to	to	ADP
ajst-27738	62	4	the	the	DET
ajst-27738	62	5	basic	basic	ADJ
ajst-27738	62	6	element	element	NOUN
ajst-27738	62	7	-	-	PUNCT
ajst-27738	62	8	by	by	ADP
ajst-27738	62	9	-	-	PUNCT
ajst-27738	62	10	element	element	NOUN
ajst-27738	62	11	addition	addition	NOUN
ajst-27738	62	12	or	or	CCONJ
ajst-27738	62	13	feature	feature	VERB
ajst-27738	62	14	splicing	splicing	NOUN
ajst-27738	62	15	operations	operation	NOUN
ajst-27738	62	16	,	,	PUNCT
ajst-27738	62	17	current	current	ADJ
ajst-27738	62	18	feature	feature	NOUN
ajst-27738	62	19	fusion	fusion	NOUN
ajst-27738	62	20	techniques	technique	NOUN
ajst-27738	62	21	are	be	AUX
ajst-27738	62	22	increasingly	increasingly	ADV
ajst-27738	62	23	implemented	implement	VERB
ajst-27738	62	24	using	use	VERB
ajst-27738	62	25	the	the	DET
ajst-27738	62	26	attention	attention	NOUN
ajst-27738	62	27	mechanism	mechanism	NOUN
ajst-27738	62	28	.	.	PUNCT
ajst-27738	63	1	the	the	DET
ajst-27738	63	2	attention	attention	NOUN
ajst-27738	63	3	mechanism	mechanism	NOUN
ajst-27738	63	4	is	be	AUX
ajst-27738	63	5	equivalent	equivalent	ADJ
ajst-27738	63	6	to	to	ADP
ajst-27738	63	7	an	an	DET
ajst-27738	63	8	intelligent	intelligent	ADJ
ajst-27738	63	9	information	information	NOUN
ajst-27738	63	10	filtering	filtering	NOUN
ajst-27738	63	11	process	process	NOUN
ajst-27738	63	12	,	,	PUNCT
ajst-27738	63	13	which	which	PRON
ajst-27738	63	14	can	can	AUX
ajst-27738	63	15	dynamically	dynamically	ADV
ajst-27738	63	16	focus	focus	VERB
ajst-27738	63	17	on	on	ADP
ajst-27738	63	18	the	the	DET
ajst-27738	63	19	key	key	ADJ
ajst-27738	63	20	information	information	NOUN
ajst-27738	63	21	in	in	ADP
ajst-27738	63	22	the	the	DET
ajst-27738	63	23	image	image	NOUN
ajst-27738	63	24	according	accord	VERB
ajst-27738	63	25	to	to	ADP
ajst-27738	63	26	the	the	DET
ajst-27738	63	27	task	task	NOUN
ajst-27738	63	28	requirements	requirement	NOUN
ajst-27738	63	29	to	to	PART
ajst-27738	63	30	optimise	optimise	VERB
ajst-27738	63	31	the	the	DET
ajst-27738	63	32	feature	feature	NOUN
ajst-27738	63	33	representation	representation	NOUN
ajst-27738	63	34	.	.	PUNCT
ajst-27738	64	1	danet[29	danet[29	NOUN
ajst-27738	64	2	]	]	PUNCT
ajst-27738	64	3	employs	employ	VERB
ajst-27738	64	4	a	a	DET
ajst-27738	64	5	dual	dual	ADJ
ajst-27738	64	6	attention	attention	NOUN
ajst-27738	64	7	mechanism	mechanism	NOUN
ajst-27738	64	8	to	to	PART
ajst-27738	64	9	enhance	enhance	VERB
ajst-27738	64	10	feature	feature	NOUN
ajst-27738	64	11	identification	identification	NOUN
ajst-27738	64	12	by	by	ADP
ajst-27738	64	13	guiding	guide	VERB
ajst-27738	64	14	attention	attention	NOUN
ajst-27738	64	15	across	across	ADP
ajst-27738	64	16	spatial	spatial	ADJ
ajst-27738	64	17	and	and	CCONJ
ajst-27738	64	18	channel	channel	NOUN
ajst-27738	64	19	dimensions	dimension	NOUN
ajst-27738	64	20	,	,	PUNCT
ajst-27738	64	21	thereby	thereby	ADV
ajst-27738	64	22	boosting	boost	VERB
ajst-27738	64	23	segmentation	segmentation	NOUN
ajst-27738	64	24	accuracy	accuracy	NOUN
ajst-27738	64	25	.	.	PUNCT
ajst-27738	65	1	ccnet[30	ccnet[30	PROPN
ajst-27738	65	2	]	]	PUNCT
ajst-27738	65	3	enhances	enhance	VERB
ajst-27738	65	4	the	the	DET
ajst-27738	65	5	feature	feature	NOUN
ajst-27738	65	6	representation	representation	NOUN
ajst-27738	65	7	through	through	ADP
ajst-27738	65	8	a	a	DET
ajst-27738	65	9	contrast	contrast	NOUN
ajst-27738	65	10	compression	compression	NOUN
ajst-27738	65	11	module	module	NOUN
ajst-27738	65	12	to	to	PART
ajst-27738	65	13	enhance	enhance	VERB
ajst-27738	65	14	feature	feature	NOUN
ajst-27738	65	15	representation	representation	NOUN
ajst-27738	65	16	,	,	PUNCT
ajst-27738	65	17	utilising	utilise	VERB
ajst-27738	65	18	contrast	contrast	NOUN
ajst-27738	65	19	learning	learn	VERB
ajst-27738	65	20	to	to	PART
ajst-27738	65	21	improve	improve	VERB
ajst-27738	65	22	feature	feature	NOUN
ajst-27738	65	23	discrimination	discrimination	NOUN
ajst-27738	65	24	and	and	CCONJ
ajst-27738	65	25	reducing	reduce	VERB
ajst-27738	65	26	computation	computation	NOUN
ajst-27738	65	27	through	through	ADP
ajst-27738	65	28	compression	compression	NOUN
ajst-27738	65	29	operations	operation	NOUN
ajst-27738	65	30	to	to	PART
ajst-27738	65	31	achieve	achieve	VERB
ajst-27738	65	32	more	more	ADV
ajst-27738	65	33	efficient	efficient	ADJ
ajst-27738	65	34	real	real	ADJ
ajst-27738	65	35	-	-	PUNCT
ajst-27738	65	36	time	time	NOUN
ajst-27738	65	37	semantic	semantic	ADJ
ajst-27738	65	38	segmentation	segmentation	NOUN
ajst-27738	65	39	performance	performance	NOUN
ajst-27738	65	40	.	.	PUNCT
ajst-27738	66	1	3	3	X
ajst-27738	66	2	.	.	X
ajst-27738	66	3	our	our	PRON
ajst-27738	66	4	proposed	propose	VERB
ajst-27738	66	5	method	method	NOUN
ajst-27738	66	6	in	in	ADP
ajst-27738	66	7	this	this	DET
ajst-27738	66	8	section	section	NOUN
ajst-27738	66	9	,	,	PUNCT
ajst-27738	66	10	we	we	PRON
ajst-27738	66	11	begin	begin	VERB
ajst-27738	66	12	by	by	ADP
ajst-27738	66	13	describing	describe	VERB
ajst-27738	66	14	the	the	DET
ajst-27738	66	15	architecture	architecture	NOUN
ajst-27738	66	16	of	of	ADP
ajst-27738	66	17	the	the	DET
ajst-27738	66	18	proposed	propose	VERB
ajst-27738	66	19	attention	attention	NOUN
ajst-27738	66	20	refined	refine	VERB
ajst-27738	66	21	two	two	NUM
ajst-27738	66	22	-	-	PUNCT
ajst-27738	66	23	branch	branch	NOUN
ajst-27738	66	24	real	real	ADJ
ajst-27738	66	25	-	-	PUNCT
ajst-27738	66	26	time	time	NOUN
ajst-27738	66	27	semantic	semantic	ADJ
ajst-27738	66	28	segmentation	segmentation	NOUN
ajst-27738	66	29	network	network	NOUN
ajst-27738	66	30	(	(	PUNCT
ajst-27738	66	31	artrnet	artrnet	PROPN
ajst-27738	66	32	)	)	PUNCT
ajst-27738	66	33	.	.	PUNCT
ajst-27738	67	1	subsequently	subsequently	ADV
ajst-27738	67	2	,	,	PUNCT
ajst-27738	67	3	we	we	PRON
ajst-27738	67	4	elaborate	elaborate	VERB
ajst-27738	67	5	on	on	ADP
ajst-27738	67	6	the	the	DET
ajst-27738	67	7	design	design	NOUN
ajst-27738	67	8	specifics	specific	NOUN
ajst-27738	67	9	of	of	ADP
ajst-27738	67	10	its	its	PRON
ajst-27738	67	11	key	key	ADJ
ajst-27738	67	12	components	component	NOUN
ajst-27738	67	13	:	:	PUNCT
ajst-27738	67	14	the	the	DET
ajst-27738	67	15	lightweight	lightweight	ADJ
ajst-27738	67	16	densely	densely	ADV
ajst-27738	67	17	-	-	PUNCT
ajst-27738	67	18	connected	connect	VERB
ajst-27738	67	19	context	context	NOUN
ajst-27738	67	20	refined	refined	ADJ
ajst-27738	67	21	branch	branch	NOUN
ajst-27738	67	22	and	and	CCONJ
ajst-27738	67	23	the	the	DET
ajst-27738	67	24	deformed	deform	VERB
ajst-27738	67	25	convolutional	convolutional	ADJ
ajst-27738	67	26	attention	attention	NOUN
ajst-27738	67	27	refined	refine	VERB
ajst-27738	67	28	fusion	fusion	NOUN
ajst-27738	67	29	module	module	NOUN
ajst-27738	67	30	(	(	PUNCT
ajst-27738	67	31	dcarfm	dcarfm	NOUN
ajst-27738	67	32	)	)	PUNCT
ajst-27738	67	33	.	.	PUNCT
ajst-27738	68	1	3.1	3.1	NUM
ajst-27738	68	2	.	.	PUNCT
ajst-27738	68	3	attention	attention	NOUN
ajst-27738	68	4	-	-	PUNCT
ajst-27738	68	5	refined	refine	VERB
ajst-27738	68	6	two	two	NUM
ajst-27738	68	7	-	-	PUNCT
ajst-27738	68	8	branch	branch	NOUN
ajst-27738	68	9	real	real	ADJ
ajst-27738	68	10	-	-	PUNCT
ajst-27738	68	11	time	time	NOUN
ajst-27738	68	12	semantic	semantic	ADJ
ajst-27738	68	13	segmentation	segmentation	NOUN
ajst-27738	68	14	networks(artrnet	networks(artrnet	PROPN
ajst-27738	68	15	)	)	PUNCT
ajst-27738	68	16	in	in	ADP
ajst-27738	68	17	this	this	DET
ajst-27738	68	18	section	section	NOUN
ajst-27738	68	19	,	,	PUNCT
ajst-27738	68	20	the	the	DET
ajst-27738	68	21	artrnet	artrnet	NOUN
ajst-27738	68	22	network	network	NOUN
ajst-27738	68	23	architecture	architecture	NOUN
ajst-27738	68	24	is	be	AUX
ajst-27738	68	25	described	describe	VERB
ajst-27738	68	26	in	in	ADP
ajst-27738	68	27	detail	detail	NOUN
ajst-27738	68	28	.	.	PUNCT
ajst-27738	69	1	the	the	DET
ajst-27738	69	2	overall	overall	ADJ
ajst-27738	69	3	network	network	NOUN
ajst-27738	69	4	architecture	architecture	NOUN
ajst-27738	69	5	is	be	AUX
ajst-27738	69	6	shown	show	VERB
ajst-27738	69	7	268	268	NUM
ajst-27738	69	8	in	in	ADP
ajst-27738	69	9	figure	figure	NOUN
ajst-27738	69	10	1	1	NUM
ajst-27738	69	11	.	.	PUNCT
ajst-27738	70	1	the	the	DET
ajst-27738	70	2	network	network	NOUN
ajst-27738	70	3	architecture	architecture	NOUN
ajst-27738	70	4	comprises	comprise	VERB
ajst-27738	70	5	two	two	NUM
ajst-27738	70	6	branches	branch	NOUN
ajst-27738	70	7	:	:	PUNCT
ajst-27738	70	8	the	the	DET
ajst-27738	70	9	spatial	spatial	ADJ
ajst-27738	70	10	detail	detail	NOUN
ajst-27738	70	11	branch	branch	NOUN
ajst-27738	70	12	and	and	CCONJ
ajst-27738	70	13	the	the	DET
ajst-27738	70	14	lightweight	lightweight	ADJ
ajst-27738	70	15	denselyconnected	denselyconnecte	VERB
ajst-27738	70	16	context	context	NOUN
ajst-27738	70	17	refinement	refinement	NOUN
ajst-27738	70	18	branch	branch	NOUN
ajst-27738	70	19	.	.	PUNCT
ajst-27738	71	1	these	these	DET
ajst-27738	71	2	branches	branch	NOUN
ajst-27738	71	3	are	be	AUX
ajst-27738	71	4	responsible	responsible	ADJ
ajst-27738	71	5	for	for	ADP
ajst-27738	71	6	extracting	extract	VERB
ajst-27738	71	7	low	low	ADJ
ajst-27738	71	8	-	-	PUNCT
ajst-27738	71	9	level	level	NOUN
ajst-27738	71	10	fine	fine	ADV
ajst-27738	71	11	-	-	PUNCT
ajst-27738	71	12	grained	grain	VERB
ajst-27738	71	13	information	information	NOUN
ajst-27738	71	14	and	and	CCONJ
ajst-27738	71	15	deep	deep	ADJ
ajst-27738	71	16	semantic	semantic	ADJ
ajst-27738	71	17	information	information	NOUN
ajst-27738	71	18	,	,	PUNCT
ajst-27738	71	19	respectively	respectively	ADV
ajst-27738	71	20	.	.	PUNCT
ajst-27738	72	1	the	the	DET
ajst-27738	72	2	spatial	spatial	ADJ
ajst-27738	72	3	detail	detail	NOUN
ajst-27738	72	4	branch	branch	NOUN
ajst-27738	72	5	,	,	PUNCT
ajst-27738	72	6	characterized	characterize	VERB
ajst-27738	72	7	by	by	ADP
ajst-27738	72	8	wide	wide	ADJ
ajst-27738	72	9	channels	channel	NOUN
ajst-27738	72	10	and	and	CCONJ
ajst-27738	72	11	shallow	shallow	ADJ
ajst-27738	72	12	layers	layer	NOUN
ajst-27738	72	13	,	,	PUNCT
ajst-27738	72	14	sufficiently	sufficiently	ADV
ajst-27738	72	15	captures	capture	VERB
ajst-27738	72	16	spatial	spatial	ADJ
ajst-27738	72	17	information	information	NOUN
ajst-27738	72	18	.	.	PUNCT
ajst-27738	73	1	inspired	inspire	VERB
ajst-27738	73	2	by	by	ADP
ajst-27738	73	3	the	the	DET
ajst-27738	73	4	detail	detail	NOUN
ajst-27738	73	5	branch	branch	NOUN
ajst-27738	73	6	of	of	ADP
ajst-27738	73	7	bisenetv2	bisenetv2	PROPN
ajst-27738	74	1	[	[	X
ajst-27738	74	2	18	18	NUM
ajst-27738	74	3	]	]	PUNCT
ajst-27738	74	4	,	,	PUNCT
ajst-27738	74	5	our	our	PRON
ajst-27738	74	6	own	own	ADJ
ajst-27738	74	7	high	high	ADJ
ajst-27738	74	8	-	-	PUNCT
ajst-27738	74	9	resolution	resolution	NOUN
ajst-27738	74	10	branch	branch	NOUN
ajst-27738	74	11	is	be	AUX
ajst-27738	74	12	designed	design	VERB
ajst-27738	74	13	.	.	PUNCT
ajst-27738	75	1	it	it	PRON
ajst-27738	75	2	uses	use	VERB
ajst-27738	75	3	three	three	NUM
ajst-27738	75	4	convolutional	convolutional	ADJ
ajst-27738	75	5	layers	layer	NOUN
ajst-27738	75	6	consisting	consist	VERB
ajst-27738	75	7	of	of	ADP
ajst-27738	75	8	3×3	3×3	NUM
ajst-27738	75	9	convolutions	convolution	NOUN
ajst-27738	75	10	for	for	ADP
ajst-27738	75	11	channel	channel	NOUN
ajst-27738	75	12	expansion	expansion	NOUN
ajst-27738	75	13	,	,	PUNCT
ajst-27738	75	14	each	each	DET
ajst-27738	75	15	consisting	consist	VERB
ajst-27738	75	16	of	of	ADP
ajst-27738	75	17	an	an	DET
ajst-27738	75	18	integrated	integrate	VERB
ajst-27738	75	19	module	module	NOUN
ajst-27738	75	20	of	of	ADP
ajst-27738	75	21	3×3	3×3	NUM
ajst-27738	75	22	convolutions	convolution	NOUN
ajst-27738	75	23	,	,	PUNCT
ajst-27738	75	24	batch	batch	VERB
ajst-27738	75	25	normalisation	normalisation	NOUN
ajst-27738	75	26	and	and	CCONJ
ajst-27738	75	27	activation	activation	NOUN
ajst-27738	75	28	functions	function	NOUN
ajst-27738	75	29	,	,	PUNCT
ajst-27738	75	30	and	and	CCONJ
ajst-27738	75	31	maximum	maximum	ADJ
ajst-27738	75	32	pooling	pooling	NOUN
ajst-27738	75	33	after	after	SCONJ
ajst-27738	75	34	each	each	DET
ajst-27738	75	35	layer	layer	NOUN
ajst-27738	75	36	to	to	PART
ajst-27738	75	37	quickly	quickly	ADV
ajst-27738	75	38	downsample	downsample	VERB
ajst-27738	75	39	the	the	DET
ajst-27738	75	40	input	input	NOUN
ajst-27738	75	41	image	image	NOUN
ajst-27738	75	42	to	to	ADP
ajst-27738	75	43	a	a	DET
ajst-27738	75	44	scale	scale	NOUN
ajst-27738	75	45	of	of	ADP
ajst-27738	75	46	1/8	1/8	NUM
ajst-27738	75	47	.	.	PUNCT
ajst-27738	76	1	the	the	DET
ajst-27738	76	2	spatial	spatial	ADJ
ajst-27738	76	3	detail	detail	NOUN
ajst-27738	76	4	branch	branch	NOUN
ajst-27738	76	5	is	be	AUX
ajst-27738	76	6	only	only	ADV
ajst-27738	76	7	the	the	DET
ajst-27738	76	8	processing	processing	NOUN
ajst-27738	76	9	of	of	ADP
ajst-27738	76	10	local	local	ADJ
ajst-27738	76	11	image	image	NOUN
ajst-27738	76	12	details	detail	NOUN
ajst-27738	76	13	,	,	PUNCT
ajst-27738	76	14	which	which	PRON
ajst-27738	76	15	can	can	AUX
ajst-27738	76	16	not	not	PART
ajst-27738	76	17	take	take	VERB
ajst-27738	76	18	up	up	ADP
ajst-27738	76	19	too	too	ADV
ajst-27738	76	20	much	much	ADJ
ajst-27738	76	21	computational	computational	ADJ
ajst-27738	76	22	resources	resource	NOUN
ajst-27738	76	23	,	,	PUNCT
ajst-27738	76	24	so	so	SCONJ
ajst-27738	76	25	only	only	ADV
ajst-27738	76	26	the	the	DET
ajst-27738	76	27	resolution	resolution	NOUN
ajst-27738	76	28	reduction	reduction	NOUN
ajst-27738	76	29	operation	operation	NOUN
ajst-27738	76	30	is	be	AUX
ajst-27738	76	31	performed	perform	VERB
ajst-27738	76	32	in	in	ADP
ajst-27738	76	33	this	this	DET
ajst-27738	76	34	process	process	NOUN
ajst-27738	76	35	,	,	PUNCT
ajst-27738	76	36	while	while	SCONJ
ajst-27738	76	37	preserving	preserve	VERB
ajst-27738	76	38	detailed	detailed	ADJ
ajst-27738	76	39	object	object	NOUN
ajst-27738	76	40	edge	edge	NOUN
ajst-27738	76	41	information	information	NOUN
ajst-27738	76	42	,	,	PUNCT
ajst-27738	76	43	focusing	focus	VERB
ajst-27738	76	44	the	the	DET
ajst-27738	76	45	main	main	ADJ
ajst-27738	76	46	feature	feature	NOUN
ajst-27738	76	47	extraction	extraction	NOUN
ajst-27738	76	48	capability	capability	NOUN
ajst-27738	76	49	on	on	ADP
ajst-27738	76	50	the	the	DET
ajst-27738	76	51	lightweight	lightweight	ADJ
ajst-27738	76	52	densely	densely	ADV
ajst-27738	76	53	connected	connect	VERB
ajst-27738	76	54	contextual	contextual	ADJ
ajst-27738	76	55	refinement	refinement	NOUN
ajst-27738	76	56	branch	branch	NOUN
ajst-27738	76	57	.	.	PUNCT
ajst-27738	77	1	细节分支	细节分支	NOUN
ajst-27738	77	2	1/2	1/2	NUM
ajst-27738	77	3	1/4	1/4	NUM
ajst-27738	77	4	1/8	1/8	NUM
ajst-27738	77	5	1/2	1/2	NUM
ajst-27738	77	6	1/4	1/4	NUM
ajst-27738	77	7	1/8	1/8	NUM
ajst-27738	77	8	1/16	1/16	NUM
ajst-27738	77	9	context	context	NOUN
ajst-27738	77	10	embedding	embed	VERB
ajst-27738	77	11	轻量级密集连接上下文细化分支	轻量级密集连接上下文细化分支	NOUN
ajst-27738	77	12	dsm-1	dsm-1	CCONJ
ajst-27738	77	13	dsm-2	dsm-2	NUM
ajst-27738	77	14	dsm-3	dsm-3	NUM
ajst-27738	77	15	1/8	1/8	NUM
ajst-27738	77	16	密集特征模块-1	密集特征模块-1	ADV
ajst-27738	77	17	dsm-4	dsm-4	X
ajst-27738	77	18	密集特征模块-2	密集特征模块-2	NUM
ajst-27738	77	19	1/16	1/16	NUM
ajst-27738	77	20	+	+	CCONJ
ajst-27738	77	21	c	c	NOUN
ajst-27738	77	22	c	c	NOUN
ajst-27738	77	23	dcarm	dcarm	NOUN
ajst-27738	77	24	dcarm	dcarm	NOUN
ajst-27738	78	1	+	+	CCONJ
ajst-27738	79	1	+	+	CCONJ
ajst-27738	79	2	2×up	2×up	NUM
ajst-27738	79	3	lrcam	lrcam	NOUN
ajst-27738	79	4	arm	arm	NOUN
ajst-27738	79	5	head	head	NOUN
ajst-27738	79	6	1/16	1/16	NUM
ajst-27738	79	7	1/16	1/16	NUM
ajst-27738	79	8	seg	seg	PROPN
ajst-27738	79	9	head	head	PROPN
ajst-27738	79	10	seg	seg	PROPN
ajst-27738	79	11	head	head	PROPN
ajst-27738	79	12	seg	seg	PROPN
ajst-27738	79	13	head	head	PROPN
ajst-27738	79	14	loss	loss	NOUN
ajst-27738	79	15	booster	booster	NOUN
ajst-27738	79	16	低分辨率上下文聚	低分辨率上下文聚	PROPN
ajst-27738	79	17	合模块	合模块	PROPN
ajst-27738	79	18	注意力细化模块	注意力细化模块	PROPN
ajst-27738	79	19	细节分支	细节分支	PROPN
ajst-27738	79	20	轻量级密集连接	轻量级密集连接	PROPN
ajst-27738	79	21	上下文细化分支	上下文细化分支	NOUN
ajst-27738	79	22	变形卷积注意力细	变形卷积注意力细	NOUN
ajst-27738	79	23	化模块	化模块	NOUN
ajst-27738	79	24	1/16	1/16	NUM
ajst-27738	79	25	1/16	1/16	NUM
ajst-27738	79	26	输入图像	输入图像	NOUN
ajst-27738	79	27	输出分割图像	输出分割图像	NOUN
ajst-27738	79	28	figure	figure	NOUN
ajst-27738	79	29	1	1	NUM
ajst-27738	79	30	.	.	PUNCT
ajst-27738	80	1	the	the	DET
ajst-27738	80	2	structural	structural	ADJ
ajst-27738	80	3	diagram	diagram	NOUN
ajst-27738	80	4	of	of	ADP
ajst-27738	80	5	attention	attention	NOUN
ajst-27738	80	6	-	-	PUNCT
ajst-27738	80	7	refined	refine	VERB
ajst-27738	80	8	two	two	NUM
ajst-27738	80	9	-	-	PUNCT
ajst-27738	80	10	branch	branch	NOUN
ajst-27738	80	11	real	real	ADJ
ajst-27738	80	12	-	-	PUNCT
ajst-27738	80	13	time	time	NOUN
ajst-27738	80	14	semantic	semantic	ADJ
ajst-27738	80	15	segmentation	segmentation	NOUN
ajst-27738	80	16	networks	network	NOUN
ajst-27738	80	17	(	(	PUNCT
ajst-27738	80	18	artrnet	artrnet	PROPN
ajst-27738	80	19	)	)	PUNCT
ajst-27738	80	20	.	.	PUNCT
ajst-27738	81	1	the	the	DET
ajst-27738	81	2	basic	basic	ADJ
ajst-27738	81	3	construction	construction	NOUN
ajst-27738	81	4	of	of	ADP
ajst-27738	81	5	the	the	DET
ajst-27738	81	6	lightweight	lightweight	ADJ
ajst-27738	81	7	dense	dense	ADJ
ajst-27738	81	8	connection	connection	NOUN
ajst-27738	81	9	context	context	NOUN
ajst-27738	81	10	refinement	refinement	NOUN
ajst-27738	81	11	branch	branch	NOUN
ajst-27738	81	12	mainly	mainly	ADV
ajst-27738	81	13	consists	consist	VERB
ajst-27738	81	14	of	of	ADP
ajst-27738	81	15	a	a	DET
ajst-27738	81	16	lightweight	lightweight	ADJ
ajst-27738	81	17	dense	dense	ADJ
ajst-27738	81	18	feature	feature	NOUN
ajst-27738	81	19	module	module	NOUN
ajst-27738	81	20	consisting	consist	VERB
ajst-27738	81	21	of	of	ADP
ajst-27738	81	22	a	a	DET
ajst-27738	81	23	downsampling	downsample	VERB
ajst-27738	81	24	module	module	NOUN
ajst-27738	81	25	(	(	PUNCT
ajst-27738	81	26	dsm	dsm	PROPN
ajst-27738	81	27	)	)	PUNCT
ajst-27738	81	28	and	and	CCONJ
ajst-27738	81	29	a	a	DET
ajst-27738	81	30	lightweight	lightweight	ADJ
ajst-27738	81	31	ghost	ghost	NOUN
ajst-27738	81	32	module[31	module[31	X
ajst-27738	81	33	]	]	PUNCT
ajst-27738	81	34	,	,	PUNCT
ajst-27738	81	35	and	and	CCONJ
ajst-27738	81	36	the	the	DET
ajst-27738	81	37	specific	specific	ADJ
ajst-27738	81	38	structure	structure	NOUN
ajst-27738	81	39	of	of	ADP
ajst-27738	81	40	the	the	DET
ajst-27738	81	41	dsm	dsm	PROPN
ajst-27738	81	42	module	module	NOUN
ajst-27738	81	43	and	and	CCONJ
ajst-27738	81	44	the	the	DET
ajst-27738	81	45	ghost	ghost	NOUN
ajst-27738	81	46	module	module	NOUN
ajst-27738	81	47	is	be	AUX
ajst-27738	81	48	shown	show	VERB
ajst-27738	81	49	in	in	ADP
ajst-27738	81	50	figure	figure	NOUN
ajst-27738	81	51	2	2	NUM
ajst-27738	81	52	.	.	PUNCT
ajst-27738	81	53	specifically	specifically	ADV
ajst-27738	81	54	,	,	PUNCT
ajst-27738	81	55	on	on	ADP
ajst-27738	81	56	the	the	DET
ajst-27738	81	57	lightweight	lightweight	ADJ
ajst-27738	81	58	dense	dense	ADJ
ajst-27738	81	59	connectivity	connectivity	NOUN
ajst-27738	81	60	context	context	NOUN
ajst-27738	81	61	refinement	refinement	NOUN
ajst-27738	81	62	branch	branch	NOUN
ajst-27738	81	63	firstly	firstly	ADV
ajst-27738	81	64	goes	go	VERB
ajst-27738	81	65	through	through	ADP
ajst-27738	81	66	three	three	NUM
ajst-27738	81	67	stages	stage	NOUN
ajst-27738	81	68	,	,	PUNCT
ajst-27738	81	69	dsm-1	dsm-1	NOUN
ajst-27738	81	70	,	,	PUNCT
ajst-27738	81	71	dsm-2	dsm-2	NUM
ajst-27738	81	72	and	and	CCONJ
ajst-27738	81	73	dsm-3	dsm-3	NUM
ajst-27738	81	74	,	,	PUNCT
ajst-27738	81	75	which	which	PRON
ajst-27738	81	76	rapidly	rapidly	ADV
ajst-27738	81	77	downsample	downsample	VERB
ajst-27738	81	78	the	the	DET
ajst-27738	81	79	feature	feature	NOUN
ajst-27738	81	80	map	map	NOUN
ajst-27738	81	81	to	to	ADP
ajst-27738	81	82	1/8	1/8	NUM
ajst-27738	81	83	of	of	ADP
ajst-27738	81	84	the	the	DET
ajst-27738	81	85	original	original	ADJ
ajst-27738	81	86	map	map	NOUN
ajst-27738	81	87	while	while	SCONJ
ajst-27738	81	88	widening	widen	VERB
ajst-27738	81	89	the	the	DET
ajst-27738	81	90	number	number	NOUN
ajst-27738	81	91	of	of	ADP
ajst-27738	81	92	channels	channel	NOUN
ajst-27738	81	93	,	,	PUNCT
ajst-27738	81	94	and	and	CCONJ
ajst-27738	81	95	after	after	ADP
ajst-27738	81	96	that	that	PRON
ajst-27738	81	97	,	,	PUNCT
ajst-27738	81	98	it	it	PRON
ajst-27738	81	99	will	will	AUX
ajst-27738	81	100	enter	enter	VERB
ajst-27738	81	101	into	into	ADP
ajst-27738	81	102	the	the	DET
ajst-27738	81	103	dense	dense	ADJ
ajst-27738	81	104	feature	feature	NOUN
ajst-27738	81	105	module-1	module-1	NOUN
ajst-27738	81	106	consisting	consist	VERB
ajst-27738	81	107	of	of	ADP
ajst-27738	81	108	5	5	NUM
ajst-27738	81	109	ghost	ghost	NOUN
ajst-27738	81	110	modules	module	NOUN
ajst-27738	81	111	,	,	PUNCT
ajst-27738	81	112	and	and	CCONJ
ajst-27738	81	113	after	after	ADP
ajst-27738	81	114	that	that	PRON
ajst-27738	81	115	,	,	PUNCT
ajst-27738	81	116	after	after	ADP
ajst-27738	81	117	going	go	VERB
ajst-27738	81	118	through	through	ADP
ajst-27738	81	119	one	one	NUM
ajst-27738	81	120	dsm-4	dsm-4	PUNCT
ajst-27738	81	121	module	module	NOUN
ajst-27738	81	122	for	for	ADP
ajst-27738	81	123	downsampling	downsampling	NOUN
ajst-27738	81	124	,	,	PUNCT
ajst-27738	81	125	it	it	PRON
ajst-27738	81	126	enters	enter	VERB
ajst-27738	81	127	into	into	ADP
ajst-27738	81	128	the	the	DET
ajst-27738	81	129	dense	dense	ADJ
ajst-27738	81	130	feature	feature	NOUN
ajst-27738	81	131	module-2	module-2	NUM
ajst-27738	81	132	consisting	consist	VERB
ajst-27738	81	133	of	of	ADP
ajst-27738	81	134	7	7	NUM
ajst-27738	81	135	ghost	ghost	NOUN
ajst-27738	81	136	modules	module	NOUN
ajst-27738	81	137	,	,	PUNCT
ajst-27738	81	138	and	and	CCONJ
ajst-27738	81	139	finally	finally	ADV
ajst-27738	81	140	the	the	DET
ajst-27738	81	141	sense	sense	NOUN
ajst-27738	81	142	field	field	NOUN
ajst-27738	81	143	is	be	AUX
ajst-27738	81	144	expanded	expand	VERB
ajst-27738	81	145	by	by	ADP
ajst-27738	81	146	a	a	DET
ajst-27738	81	147	context	context	NOUN
ajst-27738	81	148	embedding	embed	VERB
ajst-27738	81	149	block	block	NOUN
ajst-27738	81	150	to	to	PART
ajst-27738	81	151	capture	capture	VERB
ajst-27738	81	152	the	the	DET
ajst-27738	81	153	high	high	ADJ
ajst-27738	81	154	-	-	PUNCT
ajst-27738	81	155	level	level	NOUN
ajst-27738	81	156	semantics	semantic	NOUN
ajst-27738	81	157	,	,	PUNCT
ajst-27738	81	158	and	and	CCONJ
ajst-27738	81	159	the	the	DET
ajst-27738	81	160	feature	feature	NOUN
ajst-27738	81	161	map	map	NOUN
ajst-27738	81	162	is	be	AUX
ajst-27738	81	163	downsampled	downsample	VERB
ajst-27738	81	164	to	to	ADP
ajst-27738	81	165	1/32	1/32	NUM
ajst-27738	81	166	.	.	PUNCT
ajst-27738	82	1	the	the	DET
ajst-27738	82	2	features	feature	NOUN
ajst-27738	82	3	of	of	ADP
ajst-27738	82	4	dense	dense	ADJ
ajst-27738	82	5	feature	feature	NOUN
ajst-27738	82	6	module1	module1	NOUN
ajst-27738	82	7	are	be	AUX
ajst-27738	82	8	selected	select	VERB
ajst-27738	82	9	to	to	PART
ajst-27738	82	10	be	be	AUX
ajst-27738	82	11	output	output	NOUN
ajst-27738	82	12	to	to	ADP
ajst-27738	82	13	the	the	DET
ajst-27738	82	14	attention	attention	NOUN
ajst-27738	82	15	refinement	refinement	NOUN
ajst-27738	82	16	module	module	NOUN
ajst-27738	82	17	(	(	PUNCT
ajst-27738	82	18	arm	arm	NOUN
ajst-27738	82	19	)	)	PUNCT
ajst-27738	82	20	after	after	ADP
ajst-27738	82	21	downsampling	downsample	VERB
ajst-27738	82	22	the	the	DET
ajst-27738	82	23	feature	feature	NOUN
ajst-27738	82	24	map	map	NOUN
ajst-27738	82	25	to	to	ADP
ajst-27738	82	26	1/16	1/16	NUM
ajst-27738	82	27	.	.	PUNCT
ajst-27738	83	1	the	the	DET
ajst-27738	83	2	arm	arm	NOUN
ajst-27738	83	3	module	module	NOUN
ajst-27738	83	4	calculates	calculate	VERB
ajst-27738	83	5	feature	feature	NOUN
ajst-27738	83	6	map	map	NOUN
ajst-27738	83	7	weights	weight	NOUN
ajst-27738	83	8	using	use	VERB
ajst-27738	83	9	pooling	pooling	NOUN
ajst-27738	83	10	and	and	CCONJ
ajst-27738	83	11	1×1	1×1	NUM
ajst-27738	83	12	convolution	convolution	NOUN
ajst-27738	83	13	,	,	PUNCT
ajst-27738	83	14	which	which	PRON
ajst-27738	83	15	are	be	AUX
ajst-27738	83	16	then	then	ADV
ajst-27738	83	17	multiplied	multiply	VERB
ajst-27738	83	18	with	with	ADP
ajst-27738	83	19	the	the	DET
ajst-27738	83	20	input	input	NOUN
ajst-27738	83	21	feature	feature	NOUN
ajst-27738	83	22	maps	map	NOUN
ajst-27738	83	23	to	to	PART
ajst-27738	83	24	compute	compute	VERB
ajst-27738	83	25	channel	channel	NOUN
ajst-27738	83	26	attention	attention	NOUN
ajst-27738	83	27	.	.	PUNCT
ajst-27738	84	1	the	the	DET
ajst-27738	84	2	specific	specific	ADJ
ajst-27738	84	3	structure	structure	NOUN
ajst-27738	84	4	is	be	AUX
ajst-27738	84	5	shown	show	VERB
ajst-27738	84	6	in	in	ADP
ajst-27738	84	7	figure	figure	NOUN
ajst-27738	84	8	2	2	NUM
ajst-27738	84	9	.	.	PUNCT
ajst-27738	85	1	the	the	DET
ajst-27738	85	2	1/32	1/32	NUM
ajst-27738	85	3	feature	feature	NOUN
ajst-27738	85	4	maps	map	NOUN
ajst-27738	85	5	from	from	ADP
ajst-27738	85	6	the	the	DET
ajst-27738	85	7	context	context	NOUN
ajst-27738	85	8	embedding	embed	VERB
ajst-27738	85	9	block	block	NOUN
ajst-27738	85	10	are	be	AUX
ajst-27738	85	11	up	up	ADV
ajst-27738	85	12	-	-	PUNCT
ajst-27738	85	13	sampled	sample	VERB
ajst-27738	85	14	and	and	CCONJ
ajst-27738	85	15	operated	operate	VERB
ajst-27738	85	16	and	and	CCONJ
ajst-27738	85	17	then	then	ADV
ajst-27738	85	18	summed	sum	VERB
ajst-27738	85	19	with	with	ADP
ajst-27738	85	20	the	the	DET
ajst-27738	85	21	feature	feature	NOUN
ajst-27738	85	22	maps	map	NOUN
ajst-27738	85	23	passing	pass	VERB
ajst-27738	85	24	through	through	ADP
ajst-27738	85	25	the	the	DET
ajst-27738	85	26	arm	arm	NOUN
ajst-27738	85	27	and	and	CCONJ
ajst-27738	85	28	passed	pass	VERB
ajst-27738	85	29	into	into	ADP
ajst-27738	85	30	the	the	DET
ajst-27738	85	31	low	low	ADJ
ajst-27738	85	32	resolution	resolution	NOUN
ajst-27738	85	33	context	context	NOUN
ajst-27738	85	34	aggregation	aggregation	NOUN
ajst-27738	85	35	module	module	NOUN
ajst-27738	85	36	(	(	PUNCT
ajst-27738	85	37	lrcam	lrcam	NOUN
ajst-27738	85	38	)	)	PUNCT
ajst-27738	85	39	consisting	consist	VERB
ajst-27738	85	40	of	of	ADP
ajst-27738	85	41	the	the	DET
ajst-27738	85	42	lightweight	lightweight	ADJ
ajst-27738	85	43	ghost	ghost	NOUN
ajst-27738	85	44	module	module	NOUN
ajst-27738	85	45	,	,	PUNCT
ajst-27738	85	46	and	and	CCONJ
ajst-27738	85	47	outputs	output	VERB
ajst-27738	85	48	the	the	DET
ajst-27738	85	49	final	final	ADJ
ajst-27738	85	50	result	result	NOUN
ajst-27738	85	51	of	of	ADP
ajst-27738	85	52	the	the	DET
ajst-27738	85	53	semantic	semantic	ADJ
ajst-27738	85	54	segmentation	segmentation	NOUN
ajst-27738	85	55	.	.	PUNCT
ajst-27738	86	1	in	in	ADP
ajst-27738	86	2	the	the	DET
ajst-27738	86	3	final	final	ADJ
ajst-27738	86	4	fusion	fusion	NOUN
ajst-27738	86	5	stage	stage	NOUN
ajst-27738	86	6	,	,	PUNCT
ajst-27738	86	7	deformed	deform	VERB
ajst-27738	86	8	convolutional	convolutional	ADJ
ajst-27738	86	9	attention	attention	NOUN
ajst-27738	86	10	refinement	refinement	NOUN
ajst-27738	86	11	fusion	fusion	NOUN
ajst-27738	86	12	module	module	NOUN
ajst-27738	86	13	(	(	PUNCT
ajst-27738	86	14	dcarfm	dcarfm	NOUN
ajst-27738	86	15	)	)	PUNCT
ajst-27738	86	16	is	be	AUX
ajst-27738	86	17	proposed	propose	VERB
ajst-27738	86	18	,	,	PUNCT
ajst-27738	86	19	which	which	PRON
ajst-27738	86	20	can	can	AUX
ajst-27738	86	21	enhance	enhance	VERB
ajst-27738	86	22	the	the	DET
ajst-27738	86	23	feature	feature	NOUN
ajst-27738	86	24	expression	expression	NOUN
ajst-27738	86	25	of	of	ADP
ajst-27738	86	26	the	the	DET
ajst-27738	86	27	branch	branch	NOUN
ajst-27738	86	28	by	by	ADP
ajst-27738	86	29	cross	cross	NOUN
ajst-27738	86	30	-	-	ADJ
ajst-27738	86	31	fertilising	fertilise	VERB
ajst-27738	86	32	the	the	DET
ajst-27738	86	33	dual	dual	ADJ
ajst-27738	86	34	branches	branch	NOUN
ajst-27738	86	35	with	with	ADP
ajst-27738	86	36	the	the	DET
ajst-27738	86	37	attention	attention	NOUN
ajst-27738	86	38	refinement	refinement	NOUN
ajst-27738	86	39	operation	operation	NOUN
ajst-27738	86	40	respectively	respectively	ADV
ajst-27738	86	41	,	,	PUNCT
ajst-27738	86	42	and	and	CCONJ
ajst-27738	86	43	at	at	ADP
ajst-27738	86	44	the	the	DET
ajst-27738	86	45	same	same	ADJ
ajst-27738	86	46	time	time	NOUN
ajst-27738	86	47	,	,	PUNCT
ajst-27738	86	48	it	it	PRON
ajst-27738	86	49	can	can	AUX
ajst-27738	86	50	replace	replace	VERB
ajst-27738	86	51	some	some	DET
ajst-27738	86	52	complex	complex	ADJ
ajst-27738	86	53	attention	attention	NOUN
ajst-27738	86	54	computations	computation	NOUN
ajst-27738	86	55	to	to	PART
ajst-27738	86	56	reduce	reduce	VERB
ajst-27738	86	57	the	the	DET
ajst-27738	86	58	contextual	contextual	ADJ
ajst-27738	86	59	differences	difference	NOUN
ajst-27738	86	60	between	between	ADP
ajst-27738	86	61	the	the	DET
ajst-27738	86	62	high	high	ADJ
ajst-27738	86	63	-	-	PUNCT
ajst-27738	86	64	level	level	NOUN
ajst-27738	86	65	semantic	semantic	ADJ
ajst-27738	86	66	information	information	NOUN
ajst-27738	86	67	and	and	CCONJ
ajst-27738	86	68	the	the	DET
ajst-27738	86	69	underlying	underlying	ADJ
ajst-27738	86	70	spatial	spatial	ADJ
ajst-27738	86	71	detail	detail	NOUN
ajst-27738	86	72	information	information	NOUN
ajst-27738	86	73	.	.	PUNCT
ajst-27738	87	1	3.2	3.2	NUM
ajst-27738	87	2	.	.	PUNCT
ajst-27738	88	1	lightweight	lightweight	ADJ
ajst-27738	88	2	dense	dense	ADJ
ajst-27738	88	3	connection	connection	NOUN
ajst-27738	88	4	context	context	NOUN
ajst-27738	88	5	refinement	refinement	NOUN
ajst-27738	88	6	branch	branch	PROPN
ajst-27738	88	7	the	the	DET
ajst-27738	88	8	spatial	spatial	ADJ
ajst-27738	88	9	detail	detail	NOUN
ajst-27738	88	10	branch	branch	NOUN
ajst-27738	88	11	combines	combine	VERB
ajst-27738	88	12	convolutional	convolutional	ADJ
ajst-27738	88	13	and	and	CCONJ
ajst-27738	88	14	nonlinear	nonlinear	ADJ
ajst-27738	88	15	mapping	mapping	NOUN
ajst-27738	88	16	layers	layer	NOUN
ajst-27738	88	17	to	to	PART
ajst-27738	88	18	capture	capture	VERB
ajst-27738	88	19	detailed	detailed	ADJ
ajst-27738	88	20	information	information	NOUN
ajst-27738	88	21	from	from	ADP
ajst-27738	88	22	local	local	ADJ
ajst-27738	88	23	regions	region	NOUN
ajst-27738	88	24	.	.	PUNCT
ajst-27738	89	1	typical	typical	ADJ
ajst-27738	89	2	semantic	semantic	ADJ
ajst-27738	89	3	branching	branching	NOUN
ajst-27738	89	4	focuses	focus	VERB
ajst-27738	89	5	on	on	ADP
ajst-27738	89	6	delivering	deliver	VERB
ajst-27738	89	7	deep	deep	ADJ
ajst-27738	89	8	semantic	semantic	ADJ
ajst-27738	89	9	information	information	NOUN
ajst-27738	89	10	to	to	PART
ajst-27738	89	11	distinguish	distinguish	VERB
ajst-27738	89	12	between	between	ADP
ajst-27738	89	13	various	various	ADJ
ajst-27738	89	14	object	object	NOUN
ajst-27738	89	15	types	type	NOUN
ajst-27738	89	16	.	.	PUNCT
ajst-27738	90	1	this	this	DET
ajst-27738	90	2	process	process	NOUN
ajst-27738	90	3	involves	involve	VERB
ajst-27738	90	4	a	a	DET
ajst-27738	90	5	more	more	ADV
ajst-27738	90	6	intricate	intricate	ADJ
ajst-27738	90	7	branch	branch	NOUN
ajst-27738	90	8	and	and	CCONJ
ajst-27738	90	9	is	be	AUX
ajst-27738	90	10	also	also	ADV
ajst-27738	90	11	more	more	ADJ
ajst-27738	90	12	time	time	NOUN
ajst-27738	90	13	-	-	PUNCT
ajst-27738	90	14	intensive	intensive	ADJ
ajst-27738	90	15	.	.	PUNCT
ajst-27738	91	1	to	to	PART
ajst-27738	91	2	accelerate	accelerate	VERB
ajst-27738	91	3	segmentation	segmentation	NOUN
ajst-27738	91	4	,	,	PUNCT
ajst-27738	91	5	a	a	DET
ajst-27738	91	6	lightweight	lightweight	ADJ
ajst-27738	91	7	densely	densely	ADV
ajst-27738	91	8	connected	connect	VERB
ajst-27738	91	9	contextual	contextual	ADJ
ajst-27738	91	10	refinement	refinement	NOUN
ajst-27738	91	11	branch	branch	NOUN
ajst-27738	91	12	is	be	AUX
ajst-27738	91	13	employed	employ	VERB
ajst-27738	91	14	to	to	PART
ajst-27738	91	15	lower	lower	VERB
ajst-27738	91	16	the	the	DET
ajst-27738	91	17	computational	computational	ADJ
ajst-27738	91	18	cost	cost	NOUN
ajst-27738	91	19	of	of	ADP
ajst-27738	91	20	semantic	semantic	ADJ
ajst-27738	91	21	branching	branching	NOUN
ajst-27738	91	22	.	.	PUNCT
ajst-27738	92	1	this	this	DET
ajst-27738	92	2	chapter	chapter	NOUN
ajst-27738	92	3	adopts	adopt	VERB
ajst-27738	92	4	a	a	DET
ajst-27738	92	5	similar	similar	ADJ
ajst-27738	92	6	connectivity	connectivity	NOUN
ajst-27738	92	7	strategy	strategy	NOUN
ajst-27738	92	8	as	as	ADP
ajst-27738	92	9	edanet[20	edanet[20	NOUN
ajst-27738	92	10	]	]	PUNCT
ajst-27738	92	11	,	,	PUNCT
ajst-27738	92	12	incorporating	incorporate	VERB
ajst-27738	92	13	a	a	DET
ajst-27738	92	14	new	new	ADJ
ajst-27738	92	15	dsm	dsm	NOUN
ajst-27738	92	16	module	module	NOUN
ajst-27738	92	17	and	and	CCONJ
ajst-27738	92	18	a	a	DET
ajst-27738	92	19	dense	dense	ADJ
ajst-27738	92	20	connection	connection	NOUN
ajst-27738	92	21	block	block	NOUN
ajst-27738	92	22	using	use	VERB
ajst-27738	92	23	the	the	DET
ajst-27738	92	24	lightweight	lightweight	ADJ
ajst-27738	92	25	ghost	ghost	NOUN
ajst-27738	92	26	module	module	NOUN
ajst-27738	92	27	within	within	ADP
ajst-27738	92	28	the	the	DET
ajst-27738	92	29	context	context	NOUN
ajst-27738	92	30	branch	branch	NOUN
ajst-27738	92	31	.	.	PUNCT
ajst-27738	93	1	firstly	firstly	ADV
ajst-27738	93	2	three	three	NUM
ajst-27738	93	3	dsm	dsm	PROPN
ajst-27738	93	4	modules	module	NOUN
ajst-27738	93	5	perform	perform	VERB
ajst-27738	93	6	continuous	continuous	ADJ
ajst-27738	93	7	downsampling	downsampling	NOUN
ajst-27738	93	8	to	to	ADP
ajst-27738	93	9	1/8	1/8	NUM
ajst-27738	93	10	of	of	ADP
ajst-27738	93	11	the	the	DET
ajst-27738	93	12	original	original	ADJ
ajst-27738	93	13	image	image	NOUN
ajst-27738	93	14	,	,	PUNCT
ajst-27738	93	15	three	three	NUM
ajst-27738	93	16	paths	path	NOUN
ajst-27738	93	17	will	will	AUX
ajst-27738	93	18	be	be	AUX
ajst-27738	93	19	divided	divide	VERB
ajst-27738	93	20	in	in	ADP
ajst-27738	93	21	each	each	DET
ajst-27738	93	22	dsm	dsm	NOUN
ajst-27738	93	23	module	module	NOUN
ajst-27738	93	24	,	,	PUNCT
ajst-27738	93	25	two	two	NUM
ajst-27738	93	26	paths	path	NOUN
ajst-27738	93	27	first	first	ADV
ajst-27738	93	28	go	go	VERB
ajst-27738	93	29	through	through	ADP
ajst-27738	93	30	a	a	DET
ajst-27738	93	31	3×3	3×3	NUM
ajst-27738	93	32	convolution	convolution	NOUN
ajst-27738	93	33	for	for	ADP
ajst-27738	93	34	2fold	2fold	NUM
ajst-27738	93	35	downsampling	downsampling	NOUN
ajst-27738	93	36	,	,	PUNCT
ajst-27738	93	37	and	and	CCONJ
ajst-27738	93	38	the	the	DET
ajst-27738	93	39	other	other	ADJ
ajst-27738	93	40	path	path	NOUN
ajst-27738	93	41	undergoes	undergo	VERB
ajst-27738	93	42	maximum	maximum	ADJ
ajst-27738	93	43	pooling	pooling	NOUN
ajst-27738	93	44	for	for	ADP
ajst-27738	93	45	downsampling	downsampling	NOUN
ajst-27738	93	46	,	,	PUNCT
ajst-27738	93	47	and	and	CCONJ
ajst-27738	93	48	after	after	ADP
ajst-27738	93	49	that	that	PRON
ajst-27738	93	50	the	the	DET
ajst-27738	93	51	three	three	NUM
ajst-27738	93	52	paths	path	NOUN
ajst-27738	93	53	are	be	AUX
ajst-27738	93	54	channel	channel	NOUN
ajst-27738	93	55	-	-	PUNCT
ajst-27738	93	56	level	level	NOUN
ajst-27738	93	57	summed	sum	VERB
ajst-27738	93	58	up	up	ADP
ajst-27738	93	59	and	and	CCONJ
ajst-27738	93	60	then	then	ADV
ajst-27738	93	61	go	go	VERB
ajst-27738	93	62	through	through	ADP
ajst-27738	93	63	the	the	DET
ajst-27738	93	64	bn	bn	NOUN
ajst-27738	93	65	and	and	CCONJ
ajst-27738	93	66	relu	relu	NOUN
ajst-27738	93	67	activation	activation	NOUN
ajst-27738	93	68	functions	function	NOUN
ajst-27738	93	69	,	,	PUNCT
ajst-27738	93	70	and	and	CCONJ
ajst-27738	93	71	maximum	maximum	ADJ
ajst-27738	93	72	pooling	pooling	NOUN
ajst-27738	93	73	is	be	AUX
ajst-27738	93	74	used	use	VERB
ajst-27738	93	75	instead	instead	ADV
ajst-27738	93	76	of	of	ADP
ajst-27738	93	77	part	part	NOUN
ajst-27738	93	78	of	of	ADP
ajst-27738	93	79	the	the	DET
ajst-27738	93	80	convolution	convolution	NOUN
ajst-27738	93	81	,	,	PUNCT
ajst-27738	93	82	which	which	PRON
ajst-27738	93	83	reduces	reduce	VERB
ajst-27738	93	84	the	the	DET
ajst-27738	93	85	cost	cost	NOUN
ajst-27738	93	86	of	of	ADP
ajst-27738	93	87	computation	computation	NOUN
ajst-27738	93	88	.	.	PUNCT
ajst-27738	94	1	the	the	DET
ajst-27738	94	2	specific	specific	ADJ
ajst-27738	94	3	structure	structure	NOUN
ajst-27738	94	4	is	be	AUX
ajst-27738	94	5	shown	show	VERB
ajst-27738	94	6	in	in	ADP
ajst-27738	94	7	figure	figure	NOUN
ajst-27738	94	8	2	2	NUM
ajst-27738	94	9	.	.	PUNCT
ajst-27738	95	1	after	after	ADP
ajst-27738	95	2	that	that	PRON
ajst-27738	95	3	,	,	PUNCT
ajst-27738	95	4	it	it	PRON
ajst-27738	95	5	will	will	AUX
ajst-27738	95	6	pass	pass	VERB
ajst-27738	95	7	through	through	ADP
ajst-27738	95	8	a	a	DET
ajst-27738	95	9	dense	dense	ADJ
ajst-27738	95	10	link	link	NOUN
ajst-27738	95	11	block-1	block-1	NUM
ajst-27738	95	12	consisting	consist	VERB
ajst-27738	95	13	of	of	ADP
ajst-27738	95	14	five	five	NUM
ajst-27738	95	15	lightweight	lightweight	ADJ
ajst-27738	95	16	ghost	ghost	NOUN
ajst-27738	95	17	modules	module	NOUN
ajst-27738	95	18	,	,	PUNCT
ajst-27738	95	19	inspired	inspire	VERB
ajst-27738	95	20	by	by	ADP
ajst-27738	95	21	densenet[32	densenet[32	PROPN
ajst-27738	95	22	]	]	PUNCT
ajst-27738	95	23	,	,	PUNCT
ajst-27738	95	24	which	which	PRON
ajst-27738	95	25	replaces	replace	VERB
ajst-27738	95	26	the	the	DET
ajst-27738	95	27	convolutional	convolutional	ADJ
ajst-27738	95	28	blocks	block	NOUN
ajst-27738	95	29	in	in	ADP
ajst-27738	95	30	the	the	DET
ajst-27738	95	31	dense	dense	ADJ
ajst-27738	95	32	link	link	NOUN
ajst-27738	95	33	with	with	ADP
ajst-27738	95	34	lightweight	lightweight	ADJ
ajst-27738	95	35	ghost	ghost	NOUN
ajst-27738	95	36	modules	module	NOUN
ajst-27738	95	37	with	with	ADP
ajst-27738	95	38	smaller	small	ADJ
ajst-27738	95	39	parameter	parameter	NOUN
ajst-27738	95	40	counts	count	NOUN
ajst-27738	95	41	and	and	CCONJ
ajst-27738	95	42	faster	fast	ADJ
ajst-27738	95	43	computation	computation	NOUN
ajst-27738	95	44	speed	speed	NOUN
ajst-27738	95	45	.	.	PUNCT
ajst-27738	96	1	each	each	DET
ajst-27738	96	2	ghost	ghost	NOUN
ajst-27738	96	3	module	module	NOUN
ajst-27738	96	4	first	first	ADV
ajst-27738	96	5	undergoes	undergo	VERB
ajst-27738	96	6	a	a	DET
ajst-27738	96	7	1×1	1×1	NUM
ajst-27738	96	8	convolution	convolution	NOUN
ajst-27738	96	9	,	,	PUNCT
ajst-27738	96	10	bn	bn	ADP
ajst-27738	96	11	and	and	CCONJ
ajst-27738	96	12	rulu	rulu	ADJ
ajst-27738	96	13	activation	activation	NOUN
ajst-27738	96	14	functions	function	NOUN
ajst-27738	96	15	,	,	PUNCT
ajst-27738	96	16	and	and	CCONJ
ajst-27738	96	17	after	after	ADP
ajst-27738	96	18	that	that	PRON
ajst-27738	96	19	,	,	PUNCT
ajst-27738	96	20	after	after	ADP
ajst-27738	96	21	a	a	DET
ajst-27738	96	22	3×3	3×3	NUM
ajst-27738	96	23	group	group	NOUN
ajst-27738	96	24	convolution	convolution	NOUN
ajst-27738	96	25	,	,	PUNCT
ajst-27738	96	26	bn	bn	ADV
ajst-27738	96	27	and	and	CCONJ
ajst-27738	96	28	rulu	rulu	VERB
ajst-27738	96	29	269	269	NUM
ajst-27738	96	30	activation	activation	NOUN
ajst-27738	96	31	functions	function	NOUN
ajst-27738	96	32	,	,	PUNCT
ajst-27738	96	33	it	it	PRON
ajst-27738	96	34	outputs	output	VERB
ajst-27738	96	35	the	the	DET
ajst-27738	96	36	result	result	NOUN
ajst-27738	96	37	after	after	ADP
ajst-27738	96	38	channel	channel	NOUN
ajst-27738	96	39	-	-	PUNCT
ajst-27738	96	40	level	level	NOUN
ajst-27738	96	41	summation	summation	NOUN
ajst-27738	96	42	with	with	ADP
ajst-27738	96	43	the	the	DET
ajst-27738	96	44	residual	residual	ADJ
ajst-27738	96	45	link	link	NOUN
ajst-27738	96	46	.	.	PUNCT
ajst-27738	97	1	the	the	DET
ajst-27738	97	2	specific	specific	ADJ
ajst-27738	97	3	structure	structure	NOUN
ajst-27738	97	4	is	be	AUX
ajst-27738	97	5	shown	show	VERB
ajst-27738	97	6	in	in	ADP
ajst-27738	97	7	figure	figure	NOUN
ajst-27738	97	8	2	2	NUM
ajst-27738	97	9	.	.	PUNCT
ajst-27738	98	1	max	max	PROPN
ajst-27738	98	2	pooling	pool	VERB
ajst-27738	98	3	3	3	NUM
ajst-27738	98	4	*	*	SYM
ajst-27738	98	5	3	3	NUM
ajst-27738	98	6	conv	conv	ADJ
ajst-27738	98	7	（	（	PUNCT
ajst-27738	98	8	stride=2	stride=2	NOUN
ajst-27738	98	9	）	）	PUNCT
ajst-27738	98	10	bn	bn	ADP
ajst-27738	98	11	rulu	rulu	VERB
ajst-27738	98	12	c	c	PROPN
ajst-27738	98	13	下采样模块	下采样模块	ADJ
ajst-27738	98	14	dsm	dsm	PROPN
ajst-27738	98	15	1	1	NUM
ajst-27738	98	16	*	*	SYM
ajst-27738	98	17	1	1	NUM
ajst-27738	98	18	conv	conv	ADJ
ajst-27738	98	19	3	3	NUM
ajst-27738	98	20	*	*	SYM
ajst-27738	98	21	3	3	NUM
ajst-27738	98	22	gconv	gconv	NOUN
ajst-27738	98	23	bn	bn	NUM
ajst-27738	98	24	relu	relu	NOUN
ajst-27738	98	25	c	c	PROPN
ajst-27738	98	26	bn	bn	PROPN
ajst-27738	98	27	relu	relu	NOUN
ajst-27738	98	28	ghost模块	ghost模块	PROPN
ajst-27738	98	29	gm	gm	PROPN
ajst-27738	98	30	cbr	cbr	PROPN
ajst-27738	98	31	avg	avg	PROPN
ajst-27738	98	32	pooling	pool	VERB
ajst-27738	98	33	1	1	NUM
ajst-27738	98	34	*	*	SYM
ajst-27738	98	35	1	1	NUM
ajst-27738	98	36	conv	conv	ADJ
ajst-27738	98	37	bn	bn	PROPN
ajst-27738	98	38	sigmoid	sigmoid	NOUN
ajst-27738	98	39	注意力细化模块	注意力细化模块	NOUN
ajst-27738	98	40	arm	arm	NOUN
ajst-27738	98	41	3	3	NUM
ajst-27738	98	42	*	*	SYM
ajst-27738	98	43	3	3	NUM
ajst-27738	98	44	conv	conv	ADJ
ajst-27738	98	45	（	（	PUNCT
ajst-27738	98	46	stride=2	stride=2	PROPN
ajst-27738	98	47	）	）	SYM
ajst-27738	98	48	max	max	PROPN
ajst-27738	98	49	pooling	pool	VERB
ajst-27738	98	50	c	c	PROPN
ajst-27738	98	51	figure	figure	NOUN
ajst-27738	98	52	2	2	NUM
ajst-27738	98	53	.	.	PUNCT
ajst-27738	99	1	architectural	architectural	ADJ
ajst-27738	99	2	details	detail	NOUN
ajst-27738	99	3	of	of	ADP
ajst-27738	99	4	the	the	DET
ajst-27738	99	5	dsm	dsm	PROPN
ajst-27738	99	6	,	,	PUNCT
ajst-27738	99	7	gm	gm	PROPN
ajst-27738	99	8	and	and	CCONJ
ajst-27738	99	9	arm	arm	NOUN
ajst-27738	99	10	.	.	PUNCT
ajst-27738	100	1	after	after	ADP
ajst-27738	100	2	that	that	PRON
ajst-27738	100	3	,	,	PUNCT
ajst-27738	100	4	it	it	PRON
ajst-27738	100	5	passes	pass	VERB
ajst-27738	100	6	through	through	ADP
ajst-27738	100	7	a	a	DET
ajst-27738	100	8	dsm	dsm	NOUN
ajst-27738	100	9	module	module	NOUN
ajst-27738	100	10	to	to	PART
ajst-27738	100	11	downsample	downsample	VERB
ajst-27738	100	12	the	the	DET
ajst-27738	100	13	feature	feature	NOUN
ajst-27738	100	14	map	map	NOUN
ajst-27738	100	15	to	to	ADP
ajst-27738	100	16	1/16	1/16	NUM
ajst-27738	100	17	,	,	PUNCT
ajst-27738	100	18	and	and	CCONJ
ajst-27738	100	19	then	then	ADV
ajst-27738	100	20	passes	pass	VERB
ajst-27738	100	21	through	through	ADP
ajst-27738	100	22	a	a	DET
ajst-27738	100	23	dense	dense	ADJ
ajst-27738	100	24	connection	connection	NOUN
ajst-27738	100	25	block-2	block-2	NOUN
ajst-27738	100	26	composed	compose	VERB
ajst-27738	100	27	of	of	ADP
ajst-27738	100	28	seven	seven	NUM
ajst-27738	100	29	lightweight	lightweight	ADJ
ajst-27738	100	30	ghost	ghost	NOUN
ajst-27738	100	31	modules	module	NOUN
ajst-27738	100	32	and	and	CCONJ
ajst-27738	100	33	then	then	ADV
ajst-27738	100	34	passes	pass	VERB
ajst-27738	100	35	into	into	ADP
ajst-27738	100	36	the	the	DET
ajst-27738	100	37	context	context	NOUN
ajst-27738	100	38	embedding	embed	VERB
ajst-27738	100	39	block	block	NOUN
ajst-27738	100	40	to	to	PART
ajst-27738	100	41	get	get	VERB
ajst-27738	100	42	1/32	1/32	NUM
ajst-27738	100	43	feature	feature	NOUN
ajst-27738	100	44	map	map	NOUN
ajst-27738	100	45	,	,	PUNCT
ajst-27738	100	46	and	and	CCONJ
ajst-27738	100	47	the	the	DET
ajst-27738	100	48	feature	feature	NOUN
ajst-27738	100	49	map	map	NOUN
ajst-27738	100	50	from	from	ADP
ajst-27738	100	51	the	the	DET
ajst-27738	100	52	dense	dense	ADJ
ajst-27738	100	53	connection	connection	NOUN
ajst-27738	100	54	block-1	block-1	NUM
ajst-27738	100	55	passes	pass	VERB
ajst-27738	100	56	through	through	ADP
ajst-27738	100	57	the	the	DET
ajst-27738	100	58	arm	arm	NOUN
ajst-27738	100	59	module	module	NOUN
ajst-27738	100	60	for	for	ADP
ajst-27738	100	61	attention	attention	NOUN
ajst-27738	100	62	refinement	refinement	NOUN
ajst-27738	100	63	operation	operation	NOUN
ajst-27738	100	64	,	,	PUNCT
ajst-27738	100	65	and	and	CCONJ
ajst-27738	100	66	the	the	DET
ajst-27738	100	67	arm	arm	NOUN
ajst-27738	100	68	module	module	NOUN
ajst-27738	100	69	first	first	ADV
ajst-27738	100	70	passes	pass	VERB
ajst-27738	100	71	through	through	ADP
ajst-27738	100	72	a	a	DET
ajst-27738	100	73	convolution	convolution	NOUN
ajst-27738	100	74	block	block	NOUN
ajst-27738	100	75	composed	compose	VERB
ajst-27738	100	76	of	of	ADP
ajst-27738	100	77	convolution	convolution	NOUN
ajst-27738	100	78	,	,	PUNCT
ajst-27738	100	79	bn	bn	ADP
ajst-27738	100	80	and	and	CCONJ
ajst-27738	100	81	rulu	rulu	ADJ
ajst-27738	100	82	activation	activation	NOUN
ajst-27738	100	83	function	function	NOUN
ajst-27738	100	84	,	,	PUNCT
ajst-27738	100	85	and	and	CCONJ
ajst-27738	100	86	then	then	ADV
ajst-27738	100	87	passes	pass	VERB
ajst-27738	100	88	through	through	ADP
ajst-27738	100	89	a	a	DET
ajst-27738	100	90	convolution	convolution	NOUN
ajst-27738	100	91	block	block	NOUN
ajst-27738	100	92	composed	compose	VERB
ajst-27738	100	93	of	of	ADP
ajst-27738	100	94	3×3	3×3	NUM
ajst-27738	100	95	group	group	NOUN
ajst-27738	100	96	convolution	convolution	NOUN
ajst-27738	100	97	,	,	PUNCT
ajst-27738	100	98	bn	bn	ADP
ajst-27738	100	99	and	and	CCONJ
ajst-27738	100	100	rulu	rulu	ADJ
ajst-27738	100	101	activation	activation	NOUN
ajst-27738	100	102	function	function	NOUN
ajst-27738	100	103	,	,	PUNCT
ajst-27738	100	104	and	and	CCONJ
ajst-27738	100	105	then	then	ADV
ajst-27738	100	106	passes	pass	VERB
ajst-27738	100	107	through	through	ADP
ajst-27738	100	108	the	the	DET
ajst-27738	100	109	residual	residual	ADJ
ajst-27738	100	110	link	link	NOUN
ajst-27738	100	111	to	to	PART
ajst-27738	100	112	output	output	VERB
ajst-27738	100	113	the	the	DET
ajst-27738	100	114	result	result	NOUN
ajst-27738	100	115	after	after	ADP
ajst-27738	100	116	channel	channel	NOUN
ajst-27738	100	117	-	-	PUNCT
ajst-27738	100	118	level	level	NOUN
ajst-27738	100	119	summation	summation	NOUN
ajst-27738	100	120	.	.	PUNCT
ajst-27738	101	1	the	the	DET
ajst-27738	101	2	arm	arm	NOUN
ajst-27738	101	3	module	module	NOUN
ajst-27738	101	4	first	first	ADV
ajst-27738	101	5	passes	pass	VERB
ajst-27738	101	6	through	through	ADP
ajst-27738	101	7	a	a	DET
ajst-27738	101	8	convolution	convolution	NOUN
ajst-27738	101	9	block	block	NOUN
ajst-27738	101	10	consisting	consist	VERB
ajst-27738	101	11	of	of	ADP
ajst-27738	101	12	convolution	convolution	NOUN
ajst-27738	101	13	,	,	PUNCT
ajst-27738	101	14	bn	bn	ADV
ajst-27738	101	15	and	and	CCONJ
ajst-27738	101	16	rulu	rulu	ADJ
ajst-27738	101	17	activation	activation	NOUN
ajst-27738	101	18	functions	function	NOUN
ajst-27738	101	19	,	,	PUNCT
ajst-27738	101	20	after	after	ADP
ajst-27738	101	21	which	which	PRON
ajst-27738	101	22	it	it	PRON
ajst-27738	101	23	performs	perform	VERB
ajst-27738	101	24	average	average	ADJ
ajst-27738	101	25	pooling	pooling	NOUN
ajst-27738	101	26	and	and	CCONJ
ajst-27738	101	27	maximum	maximum	ADJ
ajst-27738	101	28	pooling	pool	VERB
ajst-27738	101	29	operations	operation	NOUN
ajst-27738	101	30	for	for	ADP
ajst-27738	101	31	pixel	pixel	ADJ
ajst-27738	101	32	-	-	PUNCT
ajst-27738	101	33	level	level	NOUN
ajst-27738	101	34	summation	summation	NOUN
ajst-27738	101	35	,	,	PUNCT
ajst-27738	101	36	and	and	CCONJ
ajst-27738	101	37	then	then	ADV
ajst-27738	101	38	passes	pass	VERB
ajst-27738	101	39	through	through	ADP
ajst-27738	101	40	a	a	DET
ajst-27738	101	41	1×1	1×1	NUM
ajst-27738	101	42	convolution	convolution	NOUN
ajst-27738	101	43	,	,	PUNCT
ajst-27738	101	44	bn	bn	NOUN
ajst-27738	101	45	and	and	CCONJ
ajst-27738	101	46	sigmiod	sigmiod	NOUN
ajst-27738	101	47	activation	activation	NOUN
ajst-27738	101	48	functions	function	NOUN
ajst-27738	101	49	,	,	PUNCT
ajst-27738	101	50	and	and	CCONJ
ajst-27738	101	51	then	then	ADV
ajst-27738	101	52	performs	perform	VERB
ajst-27738	101	53	pixel	pixel	ADJ
ajst-27738	101	54	-	-	PUNCT
ajst-27738	101	55	level	level	NOUN
ajst-27738	101	56	multiplication	multiplication	NOUN
ajst-27738	101	57	with	with	ADP
ajst-27738	101	58	residual	residual	ADJ
ajst-27738	101	59	connections	connection	NOUN
ajst-27738	101	60	after	after	SCONJ
ajst-27738	101	61	the	the	DET
ajst-27738	101	62	convolution	convolution	NOUN
ajst-27738	101	63	block	block	NOUN
ajst-27738	101	64	to	to	PART
ajst-27738	101	65	output	output	VERB
ajst-27738	101	66	the	the	DET
ajst-27738	101	67	result.following	result.followe	VERB
ajst-27738	101	68	the	the	DET
ajst-27738	101	69	arm	arm	NOUN
ajst-27738	101	70	module	module	NOUN
ajst-27738	101	71	immediately	immediately	ADV
ajst-27738	101	72	after	after	ADP
ajst-27738	101	73	upsampling	upsample	VERB
ajst-27738	101	74	to	to	ADP
ajst-27738	101	75	1/16	1/16	NUM
ajst-27738	101	76	of	of	ADP
ajst-27738	101	77	the	the	DET
ajst-27738	101	78	original	original	ADJ
ajst-27738	101	79	image	image	NOUN
ajst-27738	101	80	,	,	PUNCT
ajst-27738	101	81	and	and	CCONJ
ajst-27738	101	82	after	after	ADP
ajst-27738	101	83	the	the	DET
ajst-27738	101	84	context	context	NOUN
ajst-27738	101	85	embedding	embed	VERB
ajst-27738	101	86	block	block	NOUN
ajst-27738	101	87	after	after	ADP
ajst-27738	101	88	the	the	DET
ajst-27738	101	89	up	up	NOUN
ajst-27738	101	90	-	-	PUNCT
ajst-27738	101	91	sampling	sampling	NOUN
ajst-27738	101	92	of	of	ADP
ajst-27738	101	93	the	the	DET
ajst-27738	101	94	feature	feature	NOUN
ajst-27738	101	95	map	map	NOUN
ajst-27738	101	96	for	for	ADP
ajst-27738	101	97	pixel	pixel	ADJ
ajst-27738	101	98	-	-	PUNCT
ajst-27738	101	99	level	level	NOUN
ajst-27738	101	100	summation	summation	NOUN
ajst-27738	101	101	and	and	CCONJ
ajst-27738	101	102	input	input	NOUN
ajst-27738	101	103	to	to	ADP
ajst-27738	101	104	the	the	DET
ajst-27738	101	105	low	low	ADJ
ajst-27738	101	106	-	-	PUNCT
ajst-27738	101	107	resolution	resolution	NOUN
ajst-27738	101	108	context	context	NOUN
ajst-27738	101	109	aggregation	aggregation	NOUN
ajst-27738	101	110	module	module	NOUN
ajst-27738	101	111	,	,	PUNCT
ajst-27738	101	112	the	the	DET
ajst-27738	101	113	addition	addition	NOUN
ajst-27738	101	114	of	of	ADP
ajst-27738	101	115	the	the	DET
ajst-27738	101	116	low	low	ADJ
ajst-27738	101	117	-	-	PUNCT
ajst-27738	101	118	resolution	resolution	NOUN
ajst-27738	101	119	context	context	NOUN
ajst-27738	101	120	aggregation	aggregation	NOUN
ajst-27738	101	121	module	module	NOUN
ajst-27738	101	122	at	at	ADP
ajst-27738	101	123	the	the	DET
ajst-27738	101	124	end	end	NOUN
ajst-27738	101	125	of	of	ADP
ajst-27738	101	126	the	the	DET
ajst-27738	101	127	feature	feature	NOUN
ajst-27738	101	128	extractor	extractor	NOUN
ajst-27738	101	129	is	be	AUX
ajst-27738	101	130	mainly	mainly	ADV
ajst-27738	101	131	to	to	PART
ajst-27738	101	132	enhance	enhance	VERB
ajst-27738	101	133	the	the	DET
ajst-27738	101	134	spatial	spatial	ADJ
ajst-27738	101	135	information	information	NOUN
ajst-27738	101	136	processing	processing	NOUN
ajst-27738	101	137	ability	ability	NOUN
ajst-27738	101	138	of	of	ADP
ajst-27738	101	139	lightweight	lightweight	ADJ
ajst-27738	101	140	dense	dense	ADJ
ajst-27738	101	141	connection	connection	NOUN
ajst-27738	101	142	context	context	NOUN
ajst-27738	101	143	refinement	refinement	NOUN
ajst-27738	101	144	branch	branch	NOUN
ajst-27738	101	145	anywhere	anywhere	ADV
ajst-27738	101	146	.	.	PUNCT
ajst-27738	102	1	in	in	ADP
ajst-27738	102	2	this	this	DET
ajst-27738	102	3	way	way	NOUN
ajst-27738	102	4	,	,	PUNCT
ajst-27738	102	5	the	the	DET
ajst-27738	102	6	network	network	NOUN
ajst-27738	102	7	is	be	AUX
ajst-27738	102	8	able	able	ADJ
ajst-27738	102	9	to	to	PART
ajst-27738	102	10	process	process	VERB
ajst-27738	102	11	images	image	NOUN
ajst-27738	102	12	with	with	ADP
ajst-27738	102	13	complex	complex	ADJ
ajst-27738	102	14	spatial	spatial	ADJ
ajst-27738	102	15	structures	structure	NOUN
ajst-27738	102	16	more	more	ADV
ajst-27738	102	17	efficiently	efficiently	ADV
ajst-27738	102	18	,	,	PUNCT
ajst-27738	102	19	while	while	SCONJ
ajst-27738	102	20	allowing	allow	VERB
ajst-27738	102	21	better	well	ADJ
ajst-27738	102	22	articulation	articulation	NOUN
ajst-27738	102	23	with	with	ADP
ajst-27738	102	24	spatial	spatial	ADJ
ajst-27738	102	25	detail	detail	NOUN
ajst-27738	102	26	branches	branch	NOUN
ajst-27738	102	27	.	.	PUNCT
ajst-27738	103	1	mimicking	mimic	VERB
ajst-27738	103	2	pyramid	pyramid	NOUN
ajst-27738	103	3	pooling	pool	VERB
ajst-27738	103	4	without	without	ADP
ajst-27738	103	5	adding	add	VERB
ajst-27738	103	6	parameters	parameter	NOUN
ajst-27738	103	7	,	,	PUNCT
ajst-27738	103	8	the	the	DET
ajst-27738	103	9	convolution	convolution	NOUN
ajst-27738	103	10	is	be	AUX
ajst-27738	103	11	substituted	substitute	VERB
ajst-27738	103	12	with	with	ADP
ajst-27738	103	13	a	a	DET
ajst-27738	103	14	lightweight	lightweight	ADJ
ajst-27738	103	15	ghost	ghost	NOUN
ajst-27738	103	16	module	module	NOUN
ajst-27738	103	17	,	,	PUNCT
ajst-27738	103	18	and	and	CCONJ
ajst-27738	103	19	the	the	DET
ajst-27738	103	20	whole	whole	ADJ
ajst-27738	103	21	module	module	NOUN
ajst-27738	103	22	is	be	AUX
ajst-27738	103	23	divided	divide	VERB
ajst-27738	103	24	into	into	ADP
ajst-27738	103	25	five	five	NUM
ajst-27738	103	26	layers	layer	NOUN
ajst-27738	103	27	,	,	PUNCT
ajst-27738	103	28	with	with	ADP
ajst-27738	103	29	only	only	ADV
ajst-27738	103	30	one	one	NUM
ajst-27738	103	31	ghost	ghost	NOUN
ajst-27738	103	32	module	module	NOUN
ajst-27738	103	33	in	in	ADP
ajst-27738	103	34	the	the	DET
ajst-27738	103	35	first	first	ADJ
ajst-27738	103	36	layer	layer	NOUN
ajst-27738	103	37	to	to	PART
ajst-27738	103	38	get	get	VERB
ajst-27738	103	39	the	the	DET
ajst-27738	103	40	feature	feature	NOUN
ajst-27738	103	41	map	map	NOUN
ajst-27738	103	42	f1	f1	NOUN
ajst-27738	103	43	,	,	PUNCT
ajst-27738	103	44	two	two	NUM
ajst-27738	103	45	consecutive	consecutive	ADJ
ajst-27738	103	46	ghost	ghost	NOUN
ajst-27738	103	47	modules	module	NOUN
ajst-27738	103	48	in	in	ADP
ajst-27738	103	49	the	the	DET
ajst-27738	103	50	second	second	ADJ
ajst-27738	103	51	,	,	PUNCT
ajst-27738	103	52	third	third	ADJ
ajst-27738	103	53	,	,	PUNCT
ajst-27738	103	54	and	and	CCONJ
ajst-27738	103	55	fourth	fourth	ADJ
ajst-27738	103	56	layers	layer	NOUN
ajst-27738	103	57	to	to	PART
ajst-27738	103	58	get	get	VERB
ajst-27738	103	59	the	the	DET
ajst-27738	103	60	feature	feature	NOUN
ajst-27738	103	61	maps	map	NOUN
ajst-27738	103	62	f2	f2	PROPN
ajst-27738	103	63	,	,	PUNCT
ajst-27738	103	64	f3	f3	ADJ
ajst-27738	103	65	,	,	PUNCT
ajst-27738	103	66	and	and	CCONJ
ajst-27738	103	67	f4	f4	NOUN
ajst-27738	103	68	,	,	PUNCT
ajst-27738	103	69	and	and	CCONJ
ajst-27738	103	70	the	the	DET
ajst-27738	103	71	fifth	fifth	ADJ
ajst-27738	103	72	layer	layer	NOUN
ajst-27738	103	73	to	to	PART
ajst-27738	103	74	first	first	ADV
ajst-27738	103	75	perform	perform	VERB
ajst-27738	103	76	an	an	DET
ajst-27738	103	77	average	average	ADJ
ajst-27738	103	78	pooling	pooling	NOUN
ajst-27738	103	79	operation	operation	NOUN
ajst-27738	103	80	and	and	CCONJ
ajst-27738	103	81	then	then	ADV
ajst-27738	103	82	enter	enter	VERB
ajst-27738	103	83	a	a	DET
ajst-27738	103	84	ghost	ghost	NOUN
ajst-27738	103	85	module	module	NOUN
ajst-27738	103	86	to	to	PART
ajst-27738	103	87	obtain	obtain	VERB
ajst-27738	103	88	the	the	DET
ajst-27738	103	89	feature	feature	NOUN
ajst-27738	103	90	map	map	NOUN
ajst-27738	103	91	f5	f5	NOUN
ajst-27738	103	92	.	.	PUNCT
ajst-27738	104	1	after	after	ADP
ajst-27738	104	2	that	that	PRON
ajst-27738	104	3	,	,	PUNCT
ajst-27738	104	4	f5	f5	NOUN
ajst-27738	104	5	and	and	CCONJ
ajst-27738	104	6	f4	f4	NOUN
ajst-27738	104	7	are	be	AUX
ajst-27738	104	8	pixel	pixel	ADJ
ajst-27738	104	9	-	-	PUNCT
ajst-27738	104	10	level	level	NOUN
ajst-27738	104	11	summed	sum	VERB
ajst-27738	104	12	to	to	PART
ajst-27738	104	13	obtain	obtain	VERB
ajst-27738	104	14	f44	f44	NOUN
ajst-27738	104	15	,	,	PUNCT
ajst-27738	104	16	and	and	CCONJ
ajst-27738	104	17	so	so	ADV
ajst-27738	104	18	on	on	ADV
ajst-27738	104	19	,	,	PUNCT
ajst-27738	104	20	to	to	PART
ajst-27738	104	21	obtain	obtain	VERB
ajst-27738	104	22	the	the	DET
ajst-27738	104	23	feature	feature	NOUN
ajst-27738	104	24	maps	map	NOUN
ajst-27738	104	25	f33	f33	PROPN
ajst-27738	104	26	,	,	PUNCT
ajst-27738	104	27	f22	f22	NOUN
ajst-27738	104	28	,	,	PUNCT
ajst-27738	104	29	and	and	CCONJ
ajst-27738	104	30	f11	f11	NOUN
ajst-27738	104	31	,	,	PUNCT
ajst-27738	104	32	and	and	CCONJ
ajst-27738	104	33	finally	finally	ADV
ajst-27738	104	34	the	the	DET
ajst-27738	104	35	results	result	NOUN
ajst-27738	104	36	are	be	AUX
ajst-27738	104	37	output	output	VERB
ajst-27738	104	38	by	by	ADP
ajst-27738	104	39	channel	channel	NOUN
ajst-27738	104	40	-	-	PUNCT
ajst-27738	104	41	level	level	NOUN
ajst-27738	104	42	summing	summing	NOUN
ajst-27738	104	43	of	of	ADP
ajst-27738	104	44	f11	f11	NOUN
ajst-27738	104	45	,	,	PUNCT
ajst-27738	104	46	f22	f22	NOUN
ajst-27738	104	47	,	,	PUNCT
ajst-27738	104	48	f33	f33	PROPN
ajst-27738	104	49	,	,	PUNCT
ajst-27738	104	50	f44	f44	NOUN
ajst-27738	104	51	,	,	PUNCT
ajst-27738	104	52	and	and	CCONJ
ajst-27738	104	53	f5	f5	NOUN
ajst-27738	104	54	,	,	PUNCT
ajst-27738	104	55	and	and	CCONJ
ajst-27738	104	56	residual	residual	ADJ
ajst-27738	104	57	connections	connection	NOUN
ajst-27738	104	58	from	from	ADP
ajst-27738	104	59	the	the	DET
ajst-27738	104	60	input	input	NOUN
ajst-27738	104	61	image	image	NOUN
ajst-27738	104	62	.	.	PUNCT
ajst-27738	105	1	the	the	DET
ajst-27738	105	2	detailed	detailed	ADJ
ajst-27738	105	3	structure	structure	NOUN
ajst-27738	105	4	is	be	AUX
ajst-27738	105	5	illustrated	illustrate	VERB
ajst-27738	105	6	in	in	ADP
ajst-27738	105	7	figure	figure	NOUN
ajst-27738	105	8	3	3	NUM
ajst-27738	105	9	.	.	PUNCT
ajst-27738	106	1	gm	gm	PROPN
ajst-27738	106	2	gm	gm	PROPN
ajst-27738	106	3	gm	gm	PROPN
ajst-27738	106	4	gm	gm	PROPN
ajst-27738	106	5	average	average	ADJ
ajst-27738	106	6	pooling	pool	VERB
ajst-27738	106	7	gm	gm	PROPN
ajst-27738	106	8	gmgm	gmgm	NOUN
ajst-27738	107	1	c	c	PROPN
ajst-27738	108	1	gm	gm	PROPN
ajst-27738	108	2	gm	gm	PROPN
ajst-27738	109	1	+	+	CCONJ
ajst-27738	110	1	+	+	PUNCT
ajst-27738	110	2	+	+	CCONJ
ajst-27738	110	3	+	+	NUM
ajst-27738	110	4	1f	1f	NUM
ajst-27738	110	5	2f	2f	NUM
ajst-27738	110	6	3f	3f	PROPN
ajst-27738	110	7	4f	4f	PROPN
ajst-27738	110	8	44f	44f	PROPN
ajst-27738	110	9	33f	33f	PROPN
ajst-27738	110	10	22f	22f	NOUN
ajst-27738	110	11	11f	11f	NUM
ajst-27738	110	12	5f	5f	NOUN
ajst-27738	110	13	input	input	NOUN
ajst-27738	110	14	output	output	NOUN
ajst-27738	110	15	figure	figure	NOUN
ajst-27738	110	16	3	3	NUM
ajst-27738	110	17	.	.	PUNCT
ajst-27738	111	1	architectural	architectural	ADJ
ajst-27738	111	2	details	detail	NOUN
ajst-27738	111	3	of	of	ADP
ajst-27738	111	4	the	the	DET
ajst-27738	111	5	lrcam	lrcam	NOUN
ajst-27738	111	6	.	.	PUNCT
ajst-27738	112	1	270	270	NUM
ajst-27738	112	2	3.3	3.3	NUM
ajst-27738	112	3	.	.	PUNCT
ajst-27738	113	1	deformed	deform	VERB
ajst-27738	113	2	convolutional	convolutional	ADJ
ajst-27738	113	3	attention	attention	NOUN
ajst-27738	113	4	refinement	refinement	NOUN
ajst-27738	113	5	fusion	fusion	NOUN
ajst-27738	113	6	module(dcarfm	module(dcarfm	NOUN
ajst-27738	113	7	)	)	PUNCT
ajst-27738	113	8	low	low	ADJ
ajst-27738	113	9	-	-	PUNCT
ajst-27738	113	10	resolution	resolution	NOUN
ajst-27738	113	11	features	feature	NOUN
ajst-27738	113	12	contain	contain	VERB
ajst-27738	113	13	rich	rich	ADJ
ajst-27738	113	14	semantic	semantic	ADJ
ajst-27738	113	15	information	information	NOUN
ajst-27738	113	16	,	,	PUNCT
ajst-27738	113	17	while	while	SCONJ
ajst-27738	113	18	high	high	ADJ
ajst-27738	113	19	-	-	PUNCT
ajst-27738	113	20	resolution	resolution	NOUN
ajst-27738	113	21	features	feature	VERB
ajst-27738	113	22	better	well	ADV
ajst-27738	113	23	preserve	preserve	VERB
ajst-27738	113	24	spatial	spatial	ADJ
ajst-27738	113	25	details	detail	NOUN
ajst-27738	113	26	.	.	PUNCT
ajst-27738	114	1	to	to	PART
ajst-27738	114	2	effectively	effectively	ADV
ajst-27738	114	3	integrate	integrate	VERB
ajst-27738	114	4	the	the	DET
ajst-27738	114	5	deep	deep	ADJ
ajst-27738	114	6	semantic	semantic	ADJ
ajst-27738	114	7	information	information	NOUN
ajst-27738	114	8	from	from	ADP
ajst-27738	114	9	the	the	DET
ajst-27738	114	10	lightweight	lightweight	ADJ
ajst-27738	114	11	densely	densely	ADV
ajst-27738	114	12	connected	connect	VERB
ajst-27738	114	13	contextual	contextual	ADJ
ajst-27738	114	14	refinement	refinement	NOUN
ajst-27738	114	15	branch	branch	NOUN
ajst-27738	114	16	with	with	ADP
ajst-27738	114	17	the	the	DET
ajst-27738	114	18	spatial	spatial	ADJ
ajst-27738	114	19	detail	detail	NOUN
ajst-27738	114	20	information	information	NOUN
ajst-27738	114	21	from	from	ADP
ajst-27738	114	22	the	the	DET
ajst-27738	114	23	spatial	spatial	ADJ
ajst-27738	114	24	detail	detail	NOUN
ajst-27738	114	25	branch	branch	NOUN
ajst-27738	114	26	,	,	PUNCT
ajst-27738	114	27	we	we	PRON
ajst-27738	114	28	draw	draw	VERB
ajst-27738	114	29	inspiration	inspiration	NOUN
ajst-27738	114	30	from	from	ADP
ajst-27738	114	31	d	d	NOUN
ajst-27738	114	32	-	-	PUNCT
ajst-27738	114	33	lka	lka	NOUN
ajst-27738	114	34	attention[33	attention[33	NOUN
ajst-27738	114	35	]	]	PUNCT
ajst-27738	114	36	to	to	PART
ajst-27738	114	37	propose	propose	VERB
ajst-27738	114	38	a	a	DET
ajst-27738	114	39	deformed	deform	VERB
ajst-27738	114	40	convolutional	convolutional	ADJ
ajst-27738	114	41	attention	attention	NOUN
ajst-27738	114	42	refinement	refinement	NOUN
ajst-27738	114	43	fusion	fusion	NOUN
ajst-27738	114	44	module	module	NOUN
ajst-27738	114	45	.	.	PUNCT
ajst-27738	115	1	this	this	DET
ajst-27738	115	2	module	module	NOUN
ajst-27738	115	3	primarily	primarily	ADV
ajst-27738	115	4	consists	consist	VERB
ajst-27738	115	5	of	of	ADP
ajst-27738	115	6	a	a	DET
ajst-27738	115	7	deformed	deform	VERB
ajst-27738	115	8	convolutional	convolutional	ADJ
ajst-27738	115	9	attention	attention	NOUN
ajst-27738	115	10	refinement	refinement	NOUN
ajst-27738	115	11	module	module	NOUN
ajst-27738	115	12	.	.	PUNCT
ajst-27738	116	1	the	the	DET
ajst-27738	116	2	detailed	detailed	ADJ
ajst-27738	116	3	structure	structure	NOUN
ajst-27738	116	4	is	be	AUX
ajst-27738	116	5	depicted	depict	VERB
ajst-27738	116	6	in	in	ADP
ajst-27738	116	7	figure	figure	NOUN
ajst-27738	116	8	\ref{fig4	\ref{fig4	NOUN
ajst-27738	116	9	_	_	NOUN
ajst-27738	116	10	}	}	PUNCT
ajst-27738	116	11	.	.	PUNCT
ajst-27738	117	1	firstly	firstly	ADV
ajst-27738	117	2	,	,	PUNCT
ajst-27738	117	3	in	in	ADP
ajst-27738	117	4	the	the	DET
ajst-27738	117	5	fusion	fusion	NOUN
ajst-27738	117	6	stage	stage	NOUN
ajst-27738	117	7	,	,	PUNCT
ajst-27738	117	8	a	a	DET
ajst-27738	117	9	cross	cross	ADJ
ajst-27738	117	10	-	-	ADJ
ajst-27738	117	11	fertilisation	fertilisation	ADJ
ajst-27738	117	12	approach	approach	NOUN
ajst-27738	117	13	is	be	AUX
ajst-27738	117	14	adopted	adopt	VERB
ajst-27738	117	15	,	,	PUNCT
ajst-27738	117	16	specifically	specifically	ADV
ajst-27738	117	17	,	,	PUNCT
ajst-27738	117	18	the	the	DET
ajst-27738	117	19	output	output	NOUN
ajst-27738	117	20	results	result	NOUN
ajst-27738	117	21	of	of	ADP
ajst-27738	117	22	the	the	DET
ajst-27738	117	23	lightweight	lightweight	ADJ
ajst-27738	117	24	dense	dense	ADJ
ajst-27738	117	25	connectivity	connectivity	NOUN
ajst-27738	117	26	context	context	NOUN
ajst-27738	117	27	refinement	refinement	NOUN
ajst-27738	117	28	branch	branch	NOUN
ajst-27738	117	29	are	be	AUX
ajst-27738	117	30	first	first	ADV
ajst-27738	117	31	up	up	ADV
ajst-27738	117	32	-	-	PUNCT
ajst-27738	117	33	sampled	sample	VERB
ajst-27738	117	34	and	and	CCONJ
ajst-27738	117	35	the	the	DET
ajst-27738	117	36	results	result	NOUN
ajst-27738	117	37	of	of	ADP
ajst-27738	117	38	the	the	DET
ajst-27738	117	39	spatial	spatial	ADJ
ajst-27738	117	40	detail	detail	NOUN
ajst-27738	117	41	branch	branch	NOUN
ajst-27738	117	42	are	be	AUX
ajst-27738	117	43	channel	channel	NOUN
ajst-27738	117	44	-	-	PUNCT
ajst-27738	117	45	level	level	NOUN
ajst-27738	117	46	summed	sum	VERB
ajst-27738	117	47	and	and	CCONJ
ajst-27738	117	48	then	then	ADV
ajst-27738	117	49	passed	pass	VERB
ajst-27738	117	50	into	into	ADP
ajst-27738	117	51	the	the	DET
ajst-27738	117	52	deformed	deform	VERB
ajst-27738	117	53	convolutional	convolutional	ADJ
ajst-27738	117	54	attention	attention	NOUN
ajst-27738	117	55	refinement	refinement	NOUN
ajst-27738	117	56	module	module	NOUN
ajst-27738	117	57	(	(	PUNCT
ajst-27738	117	58	dcarm	dcarm	NOUN
ajst-27738	117	59	)	)	PUNCT
ajst-27738	117	60	to	to	PART
ajst-27738	117	61	carry	carry	VERB
ajst-27738	117	62	out	out	ADP
ajst-27738	117	63	the	the	DET
ajst-27738	117	64	process	process	NOUN
ajst-27738	117	65	.	.	PUNCT
ajst-27738	118	1	dcarm	dcarm	NOUN
ajst-27738	118	2	is	be	AUX
ajst-27738	118	3	used	use	VERB
ajst-27738	118	4	for	for	ADP
ajst-27738	118	5	refinement	refinement	NOUN
ajst-27738	118	6	processing	processing	NOUN
ajst-27738	118	7	,	,	PUNCT
ajst-27738	118	8	primarily	primarily	ADV
ajst-27738	118	9	filtering	filter	VERB
ajst-27738	118	10	the	the	DET
ajst-27738	118	11	features	feature	NOUN
ajst-27738	118	12	from	from	ADP
ajst-27738	118	13	the	the	DET
ajst-27738	118	14	spatial	spatial	ADJ
ajst-27738	118	15	detail	detail	NOUN
ajst-27738	118	16	branch	branch	NOUN
ajst-27738	118	17	after	after	ADP
ajst-27738	118	18	summation	summation	NOUN
ajst-27738	118	19	to	to	PART
ajst-27738	118	20	emphasize	emphasize	VERB
ajst-27738	118	21	its	its	PRON
ajst-27738	118	22	feature	feature	NOUN
ajst-27738	118	23	representation	representation	NOUN
ajst-27738	118	24	.	.	PUNCT
ajst-27738	119	1	after	after	ADP
ajst-27738	119	2	that	that	PRON
ajst-27738	119	3	,	,	PUNCT
ajst-27738	119	4	the	the	DET
ajst-27738	119	5	spatial	spatial	ADJ
ajst-27738	119	6	detail	detail	NOUN
ajst-27738	119	7	branch	branch	NOUN
ajst-27738	119	8	is	be	AUX
ajst-27738	119	9	downsampled	downsample	VERB
ajst-27738	119	10	and	and	CCONJ
ajst-27738	119	11	channellevel	channellevel	VERB
ajst-27738	119	12	summed	sum	VERB
ajst-27738	119	13	with	with	ADP
ajst-27738	119	14	the	the	DET
ajst-27738	119	15	lightweight	lightweight	ADJ
ajst-27738	119	16	dense	dense	ADJ
ajst-27738	119	17	connection	connection	NOUN
ajst-27738	119	18	context	context	PROPN
ajst-27738	119	19	refinement	refinement	NOUN
ajst-27738	119	20	branch	branch	NOUN
ajst-27738	119	21	,	,	PUNCT
ajst-27738	119	22	and	and	CCONJ
ajst-27738	119	23	then	then	ADV
ajst-27738	119	24	passed	pass	VERB
ajst-27738	119	25	into	into	ADP
ajst-27738	119	26	the	the	DET
ajst-27738	119	27	deformed	deform	VERB
ajst-27738	119	28	convolutional	convolutional	ADJ
ajst-27738	119	29	attention	attention	NOUN
ajst-27738	119	30	refinement	refinement	NOUN
ajst-27738	119	31	module	module	NOUN
ajst-27738	119	32	,	,	PUNCT
ajst-27738	119	33	where	where	SCONJ
ajst-27738	119	34	the	the	DET
ajst-27738	119	35	refinement	refinement	NOUN
ajst-27738	119	36	process	process	NOUN
ajst-27738	119	37	is	be	AUX
ajst-27738	119	38	mainly	mainly	ADV
ajst-27738	119	39	to	to	PART
ajst-27738	119	40	filter	filter	VERB
ajst-27738	119	41	the	the	DET
ajst-27738	119	42	features	feature	NOUN
ajst-27738	119	43	of	of	ADP
ajst-27738	119	44	the	the	DET
ajst-27738	119	45	lightweight	lightweight	ADJ
ajst-27738	119	46	dense	dense	ADJ
ajst-27738	119	47	connection	connection	NOUN
ajst-27738	119	48	context	context	NOUN
ajst-27738	119	49	refinement	refinement	NOUN
ajst-27738	119	50	branch	branch	NOUN
ajst-27738	119	51	after	after	ADP
ajst-27738	119	52	summing	sum	VERB
ajst-27738	119	53	,	,	PUNCT
ajst-27738	119	54	and	and	CCONJ
ajst-27738	119	55	highlight	highlight	VERB
ajst-27738	119	56	the	the	DET
ajst-27738	119	57	feature	feature	NOUN
ajst-27738	119	58	representation	representation	NOUN
ajst-27738	119	59	of	of	ADP
ajst-27738	119	60	the	the	DET
ajst-27738	119	61	lightweight	lightweight	ADJ
ajst-27738	119	62	dense	dense	ADJ
ajst-27738	119	63	connection	connection	NOUN
ajst-27738	119	64	context	context	NOUN
ajst-27738	119	65	refinement	refinement	NOUN
ajst-27738	119	66	branch	branch	NOUN
ajst-27738	119	67	.	.	PUNCT
ajst-27738	120	1	the	the	DET
ajst-27738	120	2	results	result	NOUN
ajst-27738	120	3	from	from	ADP
ajst-27738	120	4	these	these	DET
ajst-27738	120	5	two	two	NUM
ajst-27738	120	6	refinements	refinement	NOUN
ajst-27738	120	7	are	be	AUX
ajst-27738	120	8	fed	feed	VERB
ajst-27738	120	9	into	into	ADP
ajst-27738	120	10	the	the	DET
ajst-27738	120	11	feature	feature	NOUN
ajst-27738	120	12	fusion	fusion	NOUN
ajst-27738	120	13	module	module	NOUN
ajst-27738	120	14	,	,	PUNCT
ajst-27738	120	15	which	which	PRON
ajst-27738	120	16	then	then	ADV
ajst-27738	120	17	produces	produce	VERB
ajst-27738	120	18	the	the	DET
ajst-27738	120	19	final	final	ADJ
ajst-27738	120	20	output	output	NOUN
ajst-27738	120	21	.	.	PUNCT
ajst-27738	121	1	1	1	NUM
ajst-27738	121	2	*	*	SYM
ajst-27738	121	3	1	1	NUM
ajst-27738	121	4	conv	conv	ADJ
ajst-27738	121	5	gelu	gelu	PROPN
ajst-27738	121	6	dca	dca	PROPN
ajst-27738	121	7	dca	dca	PROPN
ajst-27738	121	8	1	1	NUM
ajst-27738	121	9	*	*	SYM
ajst-27738	121	10	1	1	NUM
ajst-27738	121	11	conv	conv	ADJ
ajst-27738	121	12	1	1	NUM
ajst-27738	121	13	*	*	SYM
ajst-27738	121	14	1	1	NUM
ajst-27738	121	15	conv	conv	NOUN
ajst-27738	121	16	c	c	NOUN
ajst-27738	121	17	+	+	NOUN
ajst-27738	121	18	1	1	NUM
ajst-27738	121	19	*	*	SYM
ajst-27738	121	20	1	1	NUM
ajst-27738	121	21	conv	conv	ADJ
ajst-27738	121	22	1	1	NUM
ajst-27738	121	23	*	*	SYM
ajst-27738	121	24	1	1	NUM
ajst-27738	121	25	conv	conv	ADJ
ajst-27738	121	26	3	3	NUM
ajst-27738	121	27	*	*	SYM
ajst-27738	121	28	3	3	NUM
ajst-27738	121	29	conv	conv	ADJ
ajst-27738	121	30	offsets	offset	NOUN
ajst-27738	121	31	add	add	VERB
ajst-27738	121	32	figure	figure	NOUN
ajst-27738	121	33	4	4	NUM
ajst-27738	121	34	.	.	PUNCT
ajst-27738	122	1	architectural	architectural	ADJ
ajst-27738	122	2	details	detail	NOUN
ajst-27738	122	3	of	of	ADP
ajst-27738	122	4	the	the	DET
ajst-27738	122	5	dcarfm	dcarfm	NOUN
ajst-27738	122	6	.	.	PUNCT
ajst-27738	123	1	4	4	X
ajst-27738	123	2	.	.	X
ajst-27738	123	3	experiments	experiment	NOUN
ajst-27738	123	4	in	in	ADP
ajst-27738	123	5	this	this	DET
ajst-27738	123	6	section	section	NOUN
ajst-27738	123	7	,	,	PUNCT
ajst-27738	123	8	we	we	PRON
ajst-27738	123	9	will	will	AUX
ajst-27738	123	10	evaluate	evaluate	VERB
ajst-27738	123	11	the	the	DET
ajst-27738	123	12	proposed	propose	VERB
ajst-27738	123	13	artrnet	artrnet	NOUN
ajst-27738	123	14	on	on	ADP
ajst-27738	123	15	two	two	NUM
ajst-27738	123	16	datasets	dataset	NOUN
ajst-27738	123	17	:	:	PUNCT
ajst-27738	123	18	cityscapes[34	cityscapes[34	ADJ
ajst-27738	123	19	]	]	PUNCT
ajst-27738	123	20	and	and	CCONJ
ajst-27738	123	21	camvid[35	camvid[35	PROPN
ajst-27738	123	22	]	]	PUNCT
ajst-27738	123	23	.	.	PUNCT
ajst-27738	124	1	we	we	PRON
ajst-27738	124	2	will	will	AUX
ajst-27738	124	3	compare	compare	VERB
ajst-27738	124	4	its	its	PRON
ajst-27738	124	5	performance	performance	NOUN
ajst-27738	124	6	with	with	ADP
ajst-27738	124	7	other	other	ADJ
ajst-27738	124	8	notable	notable	ADJ
ajst-27738	124	9	real	real	ADJ
ajst-27738	124	10	-	-	PUNCT
ajst-27738	124	11	time	time	NOUN
ajst-27738	124	12	semantic	semantic	ADJ
ajst-27738	124	13	segmentation	segmentation	NOUN
ajst-27738	124	14	methods	method	NOUN
ajst-27738	124	15	to	to	PART
ajst-27738	124	16	demonstrate	demonstrate	VERB
ajst-27738	124	17	its	its	PRON
ajst-27738	124	18	advantages	advantage	NOUN
ajst-27738	124	19	.	.	PUNCT
ajst-27738	125	1	in	in	ADP
ajst-27738	125	2	the	the	DET
ajst-27738	125	3	following	follow	VERB
ajst-27738	125	4	subsections	subsection	NOUN
ajst-27738	125	5	,	,	PUNCT
ajst-27738	125	6	we	we	PRON
ajst-27738	125	7	will	will	AUX
ajst-27738	125	8	outline	outline	VERB
ajst-27738	125	9	the	the	DET
ajst-27738	125	10	implementation	implementation	NOUN
ajst-27738	125	11	details	detail	NOUN
ajst-27738	125	12	of	of	ADP
ajst-27738	125	13	the	the	DET
ajst-27738	125	14	datasets	dataset	NOUN
ajst-27738	125	15	and	and	CCONJ
ajst-27738	125	16	training	training	NOUN
ajst-27738	125	17	parameters	parameter	NOUN
ajst-27738	125	18	.	.	PUNCT
ajst-27738	126	1	next	next	ADV
ajst-27738	126	2	,	,	PUNCT
ajst-27738	126	3	we	we	PRON
ajst-27738	126	4	analyze	analyze	VERB
ajst-27738	126	5	the	the	DET
ajst-27738	126	6	effectiveness	effectiveness	NOUN
ajst-27738	126	7	of	of	ADP
ajst-27738	126	8	the	the	DET
ajst-27738	126	9	attention	attention	NOUN
ajst-27738	126	10	refined	refine	VERB
ajst-27738	126	11	two	two	NUM
ajst-27738	126	12	-	-	PUNCT
ajst-27738	126	13	branch	branch	NOUN
ajst-27738	126	14	real	real	ADJ
ajst-27738	126	15	-	-	PUNCT
ajst-27738	126	16	time	time	NOUN
ajst-27738	126	17	semantic	semantic	ADJ
ajst-27738	126	18	segmentation	segmentation	NOUN
ajst-27738	126	19	network	network	NOUN
ajst-27738	126	20	structure	structure	NOUN
ajst-27738	126	21	and	and	CCONJ
ajst-27738	126	22	conduct	conduct	VERB
ajst-27738	126	23	thorough	thorough	ADJ
ajst-27738	126	24	ablation	ablation	NOUN
ajst-27738	126	25	experiments	experiment	NOUN
ajst-27738	126	26	on	on	ADP
ajst-27738	126	27	the	the	DET
ajst-27738	126	28	cityscapes	cityscape	NOUN
ajst-27738	126	29	dataset	dataset	VERB
ajst-27738	126	30	to	to	PART
ajst-27738	126	31	validate	validate	VERB
ajst-27738	126	32	each	each	DET
ajst-27738	126	33	module	module	NOUN
ajst-27738	126	34	's	's	PART
ajst-27738	126	35	efficacy	efficacy	NOUN
ajst-27738	126	36	in	in	ADP
ajst-27738	126	37	our	our	PRON
ajst-27738	126	38	method	method	NOUN
ajst-27738	126	39	.	.	PUNCT
ajst-27738	127	1	finally	finally	ADV
ajst-27738	127	2	,	,	PUNCT
ajst-27738	127	3	we	we	PRON
ajst-27738	127	4	compare	compare	VERB
ajst-27738	127	5	our	our	PRON
ajst-27738	127	6	final	final	ADJ
ajst-27738	127	7	accuracy	accuracy	NOUN
ajst-27738	127	8	and	and	CCONJ
ajst-27738	127	9	speed	speed	NOUN
ajst-27738	127	10	(	(	PUNCT
ajst-27738	127	11	fps	fps	NOUN
ajst-27738	127	12	)	)	PUNCT
ajst-27738	127	13	results	result	NOUN
ajst-27738	127	14	with	with	ADP
ajst-27738	127	15	other	other	ADJ
ajst-27738	127	16	algorithms	algorithm	NOUN
ajst-27738	127	17	across	across	ADP
ajst-27738	127	18	various	various	ADJ
ajst-27738	127	19	benchmarks	benchmark	NOUN
ajst-27738	127	20	.	.	PUNCT
ajst-27738	128	1	4.1	4.1	NUM
ajst-27738	128	2	.	.	PUNCT
ajst-27738	128	3	datasets	dataset	NOUN
ajst-27738	128	4	and	and	CCONJ
ajst-27738	128	5	evaluation	evaluation	NOUN
ajst-27738	128	6	metrics	metric	NOUN
ajst-27738	128	7	cityscapes	cityscape	NOUN
ajst-27738	128	8	:	:	PUNCT
ajst-27738	128	9	the	the	DET
ajst-27738	128	10	cityscapes	cityscape	NOUN
ajst-27738	128	11	dataset[34	dataset[34	NOUN
ajst-27738	128	12	]	]	PUNCT
ajst-27738	128	13	is	be	AUX
ajst-27738	128	14	a	a	DET
ajst-27738	128	15	widely	widely	ADV
ajst-27738	128	16	utilized	utilize	VERB
ajst-27738	128	17	large	large	ADJ
ajst-27738	128	18	-	-	PUNCT
ajst-27738	128	19	scale	scale	NOUN
ajst-27738	128	20	dataset	dataset	NOUN
ajst-27738	128	21	for	for	ADP
ajst-27738	128	22	semantic	semantic	ADJ
ajst-27738	128	23	segmentation	segmentation	NOUN
ajst-27738	128	24	of	of	ADP
ajst-27738	128	25	urban	urban	ADJ
ajst-27738	128	26	scenes	scene	NOUN
ajst-27738	128	27	,	,	PUNCT
ajst-27738	128	28	serving	serve	VERB
ajst-27738	128	29	as	as	ADP
ajst-27738	128	30	a	a	DET
ajst-27738	128	31	prominent	prominent	ADJ
ajst-27738	128	32	benchmark	benchmark	NOUN
ajst-27738	128	33	in	in	ADP
ajst-27738	128	34	computer	computer	NOUN
ajst-27738	128	35	vision	vision	PROPN
ajst-27738	128	36	research	research	NOUN
ajst-27738	128	37	and	and	CCONJ
ajst-27738	128	38	algorithm	algorithm	NOUN
ajst-27738	128	39	evaluation	evaluation	NOUN
ajst-27738	128	40	.	.	PUNCT
ajst-27738	129	1	the	the	DET
ajst-27738	129	2	dataset	dataset	NOUN
ajst-27738	129	3	consists	consist	VERB
ajst-27738	129	4	of	of	ADP
ajst-27738	129	5	high	high	ADJ
ajst-27738	129	6	-	-	PUNCT
ajst-27738	129	7	resolution	resolution	NOUN
ajst-27738	129	8	images	image	NOUN
ajst-27738	129	9	from	from	ADP
ajst-27738	129	10	50	50	NUM
ajst-27738	129	11	cities	city	NOUN
ajst-27738	129	12	in	in	ADP
ajst-27738	129	13	germany	germany	PROPN
ajst-27738	129	14	,	,	PUNCT
ajst-27738	129	15	covering	cover	VERB
ajst-27738	129	16	different	different	ADJ
ajst-27738	129	17	weather	weather	NOUN
ajst-27738	129	18	conditions	condition	NOUN
ajst-27738	129	19	,	,	PUNCT
ajst-27738	129	20	different	different	ADJ
ajst-27738	129	21	seasons	season	NOUN
ajst-27738	129	22	and	and	CCONJ
ajst-27738	129	23	various	various	ADJ
ajst-27738	129	24	urban	urban	ADJ
ajst-27738	129	25	scenes	scene	NOUN
ajst-27738	129	26	.	.	PUNCT
ajst-27738	130	1	the	the	DET
ajst-27738	130	2	images	image	NOUN
ajst-27738	130	3	contain	contain	VERB
ajst-27738	130	4	rich	rich	ADJ
ajst-27738	130	5	semantic	semantic	ADJ
ajst-27738	130	6	information	information	NOUN
ajst-27738	130	7	such	such	ADJ
ajst-27738	130	8	as	as	ADP
ajst-27738	130	9	roads	road	NOUN
ajst-27738	130	10	,	,	PUNCT
ajst-27738	130	11	pedestrians	pedestrian	NOUN
ajst-27738	130	12	,	,	PUNCT
ajst-27738	130	13	vehicles	vehicle	NOUN
ajst-27738	130	14	,	,	PUNCT
ajst-27738	130	15	buildings	building	NOUN
ajst-27738	130	16	,	,	PUNCT
ajst-27738	130	17	etc	etc	X
ajst-27738	130	18	.	.	X
ajst-27738	130	19	,	,	PUNCT
ajst-27738	130	20	making	make	VERB
ajst-27738	130	21	them	they	PRON
ajst-27738	130	22	ideal	ideal	ADJ
ajst-27738	130	23	for	for	ADP
ajst-27738	130	24	deep	deep	ADJ
ajst-27738	130	25	learning	learning	NOUN
ajst-27738	130	26	models	model	NOUN
ajst-27738	130	27	for	for	ADP
ajst-27738	130	28	semantic	semantic	ADJ
ajst-27738	130	29	segmentation	segmentation	NOUN
ajst-27738	130	30	studies	study	NOUN
ajst-27738	130	31	in	in	ADP
ajst-27738	130	32	urban	urban	ADJ
ajst-27738	130	33	scenes	scene	NOUN
ajst-27738	130	34	.	.	PUNCT
ajst-27738	131	1	the	the	DET
ajst-27738	131	2	cityscapes	cityscape	NOUN
ajst-27738	131	3	dataset	dataset	VERB
ajst-27738	131	4	consists	consist	NOUN
ajst-27738	131	5	of	of	ADP
ajst-27738	131	6	high	high	ADJ
ajst-27738	131	7	-	-	PUNCT
ajst-27738	131	8	resolution	resolution	NOUN
ajst-27738	131	9	images	image	NOUN
ajst-27738	131	10	,	,	PUNCT
ajst-27738	131	11	each	each	PRON
ajst-27738	131	12	meticulously	meticulously	ADV
ajst-27738	131	13	annotated	annotate	VERB
ajst-27738	131	14	at	at	ADP
ajst-27738	131	15	the	the	DET
ajst-27738	131	16	pixel	pixel	PROPN
ajst-27738	131	17	level	level	NOUN
ajst-27738	131	18	with	with	ADP
ajst-27738	131	19	labels	label	NOUN
ajst-27738	131	20	covering	cover	VERB
ajst-27738	131	21	30	30	NUM
ajst-27738	131	22	different	different	ADJ
ajst-27738	131	23	categories	category	NOUN
ajst-27738	131	24	.	.	PUNCT
ajst-27738	132	1	the	the	DET
ajst-27738	132	2	dataset	dataset	NOUN
ajst-27738	132	3	can	can	AUX
ajst-27738	132	4	be	be	AUX
ajst-27738	132	5	divided	divide	VERB
ajst-27738	132	6	into	into	ADP
ajst-27738	132	7	two	two	NUM
ajst-27738	132	8	subsets	subset	NOUN
ajst-27738	132	9	with	with	ADP
ajst-27738	132	10	two	two	NUM
ajst-27738	132	11	levels	level	NOUN
ajst-27738	132	12	of	of	ADP
ajst-27738	132	13	annotation	annotation	NOUN
ajst-27738	132	14	:	:	PUNCT
ajst-27738	132	15	fine	fine	ADJ
ajst-27738	132	16	and	and	CCONJ
ajst-27738	132	17	coarse	coarse	ADJ
ajst-27738	132	18	.	.	PUNCT
ajst-27738	133	1	the	the	DET
ajst-27738	133	2	finely	finely	ADV
ajst-27738	133	3	annotated	annotate	VERB
ajst-27738	133	4	cityscapes	cityscape	NOUN
ajst-27738	133	5	dataset	dataset	VERB
ajst-27738	133	6	includes	include	VERB
ajst-27738	133	7	5000	5000	NUM
ajst-27738	133	8	high	high	ADJ
ajst-27738	133	9	-	-	PUNCT
ajst-27738	133	10	resolution	resolution	NOUN
ajst-27738	133	11	images	image	NOUN
ajst-27738	133	12	,	,	PUNCT
ajst-27738	133	13	with	with	ADP
ajst-27738	133	14	2975	2975	NUM
ajst-27738	133	15	images	image	NOUN
ajst-27738	133	16	allocated	allocate	VERB
ajst-27738	133	17	for	for	ADP
ajst-27738	133	18	training	training	NOUN
ajst-27738	133	19	,	,	PUNCT
ajst-27738	133	20	500	500	NUM
ajst-27738	133	21	for	for	ADP
ajst-27738	133	22	validation	validation	NOUN
ajst-27738	133	23	,	,	PUNCT
ajst-27738	133	24	and	and	CCONJ
ajst-27738	133	25	1525	1525	NUM
ajst-27738	133	26	for	for	ADP
ajst-27738	133	27	testing	testing	NOUN
ajst-27738	133	28	(	(	PUNCT
ajst-27738	133	29	annotations	annotation	NOUN
ajst-27738	133	30	for	for	ADP
ajst-27738	133	31	the	the	DET
ajst-27738	133	32	test	test	NOUN
ajst-27738	133	33	set	set	NOUN
ajst-27738	133	34	are	be	AUX
ajst-27738	133	35	available	available	ADJ
ajst-27738	133	36	on	on	ADP
ajst-27738	133	37	the	the	DET
ajst-27738	133	38	official	official	ADJ
ajst-27738	133	39	website	website	NOUN
ajst-27738	133	40	for	for	ADP
ajst-27738	133	41	evaluation	evaluation	NOUN
ajst-27738	133	42	)	)	PUNCT
ajst-27738	133	43	.	.	PUNCT
ajst-27738	134	1	the	the	DET
ajst-27738	134	2	roughly	roughly	ADV
ajst-27738	134	3	labelled	label	VERB
ajst-27738	134	4	dataset	dataset	NOUN
ajst-27738	134	5	,	,	PUNCT
ajst-27738	134	6	on	on	ADP
ajst-27738	134	7	the	the	DET
ajst-27738	134	8	other	other	ADJ
ajst-27738	134	9	hand	hand	NOUN
ajst-27738	134	10	,	,	PUNCT
ajst-27738	134	11	contains	contain	VERB
ajst-27738	134	12	20,000	20,000	NUM
ajst-27738	134	13	images	image	NOUN
ajst-27738	134	14	.	.	PUNCT
ajst-27738	135	1	we	we	PRON
ajst-27738	135	2	usually	usually	ADV
ajst-27738	135	3	use	use	VERB
ajst-27738	135	4	the	the	DET
ajst-27738	135	5	finely	finely	ADV
ajst-27738	135	6	labelled	label	VERB
ajst-27738	135	7	dataset	dataset	NOUN
ajst-27738	135	8	,	,	PUNCT
ajst-27738	135	9	the	the	DET
ajst-27738	135	10	resolution	resolution	NOUN
ajst-27738	135	11	of	of	ADP
ajst-27738	135	12	these	these	DET
ajst-27738	135	13	images	image	NOUN
ajst-27738	135	14	is	be	AUX
ajst-27738	135	15	up	up	ADP
ajst-27738	135	16	to	to	ADP
ajst-27738	135	17	2048×1024	2048×1024	NUM
ajst-27738	135	18	,	,	PUNCT
ajst-27738	135	19	which	which	PRON
ajst-27738	135	20	provides	provide	VERB
ajst-27738	135	21	detailed	detailed	ADJ
ajst-27738	135	22	and	and	CCONJ
ajst-27738	135	23	rich	rich	ADJ
ajst-27738	135	24	scene	scene	NOUN
ajst-27738	135	25	information	information	NOUN
ajst-27738	135	26	for	for	ADP
ajst-27738	135	27	research	research	NOUN
ajst-27738	135	28	and	and	CCONJ
ajst-27738	135	29	development	development	NOUN
ajst-27738	135	30	.	.	PUNCT
ajst-27738	136	1	camvid	camvid	NOUN
ajst-27738	136	2	:	:	PUNCT
ajst-27738	136	3	the	the	DET
ajst-27738	136	4	camvid	camvid	PROPN
ajst-27738	136	5	dataset[35	dataset[35	PROPN
ajst-27738	136	6	]	]	X
ajst-27738	136	7	is	be	AUX
ajst-27738	136	8	a	a	DET
ajst-27738	136	9	specialized	specialized	ADJ
ajst-27738	136	10	dataset	dataset	NOUN
ajst-27738	136	11	for	for	ADP
ajst-27738	136	12	semantic	semantic	ADJ
ajst-27738	136	13	segmentation	segmentation	NOUN
ajst-27738	136	14	tasks	task	NOUN
ajst-27738	136	15	in	in	ADP
ajst-27738	136	16	road	road	NOUN
ajst-27738	136	17	scenes	scene	NOUN
ajst-27738	136	18	,	,	PUNCT
ajst-27738	136	19	developed	develop	VERB
ajst-27738	136	20	by	by	ADP
ajst-27738	136	21	the	the	DET
ajst-27738	136	22	computer	computer	NOUN
ajst-27738	136	23	vision	vision	NOUN
ajst-27738	136	24	group	group	NOUN
ajst-27738	136	25	at	at	ADP
ajst-27738	136	26	the	the	DET
ajst-27738	136	27	university	university	PROPN
ajst-27738	136	28	of	of	ADP
ajst-27738	136	29	cambridge	cambridge	PROPN
ajst-27738	136	30	.	.	PUNCT
ajst-27738	137	1	it	it	PRON
ajst-27738	137	2	serves	serve	VERB
ajst-27738	137	3	as	as	ADP
ajst-27738	137	4	a	a	DET
ajst-27738	137	5	valuable	valuable	ADJ
ajst-27738	137	6	resource	resource	NOUN
ajst-27738	137	7	for	for	ADP
ajst-27738	137	8	research	research	NOUN
ajst-27738	137	9	in	in	ADP
ajst-27738	137	10	areas	area	NOUN
ajst-27738	137	11	like	like	ADP
ajst-27738	137	12	autonomous	autonomous	ADJ
ajst-27738	137	13	driving	driving	NOUN
ajst-27738	137	14	and	and	CCONJ
ajst-27738	137	15	traffic	traffic	NOUN
ajst-27738	137	16	monitoring	monitoring	NOUN
ajst-27738	137	17	.	.	PUNCT
ajst-27738	138	1	it	it	PRON
ajst-27738	138	2	is	be	AUX
ajst-27738	138	3	the	the	DET
ajst-27738	138	4	first	first	ADJ
ajst-27738	138	5	video	video	NOUN
ajst-27738	138	6	collection	collection	NOUN
ajst-27738	138	7	to	to	PART
ajst-27738	138	8	integrate	integrate	VERB
ajst-27738	138	9	semantic	semantic	ADJ
ajst-27738	138	10	labelling	labelling	NOUN
ajst-27738	138	11	of	of	ADP
ajst-27738	138	12	target	target	NOUN
ajst-27738	138	13	categories	category	NOUN
ajst-27738	138	14	.	.	PUNCT
ajst-27738	139	1	the	the	DET
ajst-27738	139	2	dataset	dataset	NOUN
ajst-27738	139	3	consists	consist	VERB
ajst-27738	139	4	of	of	ADP
ajst-27738	139	5	32	32	NUM
ajst-27738	139	6	semantic	semantic	ADJ
ajst-27738	139	7	labels	label	NOUN
ajst-27738	139	8	and	and	CCONJ
ajst-27738	139	9	was	be	AUX
ajst-27738	139	10	originally	originally	ADV
ajst-27738	139	11	sourced	source	VERB
ajst-27738	139	12	from	from	ADP
ajst-27738	139	13	video	video	NOUN
ajst-27738	139	14	sequences	sequence	NOUN
ajst-27738	139	15	of	of	ADP
ajst-27738	139	16	the	the	DET
ajst-27738	139	17	cambridge	cambridge	PROPN
ajst-27738	139	18	city	city	PROPN
ajst-27738	139	19	area	area	NOUN
ajst-27738	139	20	,	,	PUNCT
ajst-27738	139	21	with	with	ADP
ajst-27738	139	22	a	a	DET
ajst-27738	139	23	total	total	NOUN
ajst-27738	139	24	of	of	ADP
ajst-27738	139	25	701	701	NUM
ajst-27738	139	26	image	image	NOUN
ajst-27738	139	27	sequences	sequence	NOUN
ajst-27738	139	28	containing	contain	VERB
ajst-27738	139	29	hundreds	hundred	NOUN
ajst-27738	139	30	to	to	PART
ajst-27738	139	31	thousands	thousand	NOUN
ajst-27738	139	32	of	of	ADP
ajst-27738	139	33	frames	frame	NOUN
ajst-27738	139	34	each	each	PRON
ajst-27738	139	35	,	,	PUNCT
ajst-27738	139	36	which	which	PRON
ajst-27738	139	37	were	be	AUX
ajst-27738	139	38	subsequently	subsequently	ADV
ajst-27738	139	39	generated	generate	VERB
ajst-27738	139	40	by	by	ADP
ajst-27738	139	41	manually	manually	ADV
ajst-27738	139	42	selecting	select	VERB
ajst-27738	139	43	more	more	ADJ
ajst-27738	139	44	than	than	ADP
ajst-27738	139	45	700	700	NUM
ajst-27738	139	46	images	image	NOUN
ajst-27738	139	47	to	to	PART
ajst-27738	139	48	be	be	AUX
ajst-27738	139	49	annotated	annotate	VERB
ajst-27738	139	50	.	.	PUNCT
ajst-27738	140	1	271	271	NUM
ajst-27738	140	2	the	the	DET
ajst-27738	140	3	camvid	camvid	NOUN
ajst-27738	140	4	dataset	dataset	NOUN
ajst-27738	140	5	comprises	comprise	VERB
ajst-27738	140	6	701	701	NUM
ajst-27738	140	7	images	image	NOUN
ajst-27738	140	8	depicting	depict	VERB
ajst-27738	140	9	urban	urban	ADJ
ajst-27738	140	10	streetscapes	streetscape	NOUN
ajst-27738	140	11	,	,	PUNCT
ajst-27738	140	12	with	with	ADP
ajst-27738	140	13	367	367	NUM
ajst-27738	140	14	images	image	NOUN
ajst-27738	140	15	used	use	VERB
ajst-27738	140	16	for	for	ADP
ajst-27738	140	17	training	training	NOUN
ajst-27738	140	18	,	,	PUNCT
ajst-27738	140	19	101	101	NUM
ajst-27738	140	20	for	for	ADP
ajst-27738	140	21	validation	validation	NOUN
ajst-27738	140	22	,	,	PUNCT
ajst-27738	140	23	and	and	CCONJ
ajst-27738	140	24	the	the	DET
ajst-27738	140	25	remaining	remain	VERB
ajst-27738	140	26	233	233	NUM
ajst-27738	140	27	for	for	ADP
ajst-27738	140	28	testing	testing	NOUN
ajst-27738	140	29	.	.	PUNCT
ajst-27738	141	1	the	the	DET
ajst-27738	141	2	remaining	remain	VERB
ajst-27738	141	3	233	233	NUM
ajst-27738	141	4	images	image	NOUN
ajst-27738	141	5	were	be	AUX
ajst-27738	141	6	used	use	VERB
ajst-27738	141	7	as	as	ADP
ajst-27738	141	8	a	a	DET
ajst-27738	141	9	test	test	NOUN
ajst-27738	141	10	set	set	NOUN
ajst-27738	141	11	.	.	PUNCT
ajst-27738	142	1	this	this	DET
ajst-27738	142	2	division	division	NOUN
ajst-27738	142	3	helps	help	VERB
ajst-27738	142	4	researchers	researcher	NOUN
ajst-27738	142	5	to	to	PART
ajst-27738	142	6	train	train	VERB
ajst-27738	142	7	,	,	PUNCT
ajst-27738	142	8	validate	validate	VERB
ajst-27738	142	9	and	and	CCONJ
ajst-27738	142	10	evaluate	evaluate	VERB
ajst-27738	142	11	the	the	DET
ajst-27738	142	12	algorithm	algorithm	NOUN
ajst-27738	142	13	to	to	PART
ajst-27738	142	14	better	well	ADV
ajst-27738	142	15	understand	understand	VERB
ajst-27738	142	16	its	its	PRON
ajst-27738	142	17	performance	performance	NOUN
ajst-27738	142	18	in	in	ADP
ajst-27738	142	19	different	different	ADJ
ajst-27738	142	20	scenarios	scenario	NOUN
ajst-27738	142	21	.	.	PUNCT
ajst-27738	143	1	the	the	DET
ajst-27738	143	2	images	image	NOUN
ajst-27738	143	3	have	have	VERB
ajst-27738	143	4	a	a	DET
ajst-27738	143	5	resolution	resolution	NOUN
ajst-27738	143	6	of	of	ADP
ajst-27738	143	7	960	960	NUM
ajst-27738	143	8	×	×	NOUN
ajst-27738	143	9	720	720	NUM
ajst-27738	143	10	and	and	CCONJ
ajst-27738	143	11	contain	contain	VERB
ajst-27738	143	12	11	11	NUM
ajst-27738	143	13	commonly	commonly	ADV
ajst-27738	143	14	used	use	VERB
ajst-27738	143	15	semantic	semantic	ADJ
ajst-27738	143	16	labels	label	NOUN
ajst-27738	143	17	.	.	PUNCT
ajst-27738	144	1	4.2	4.2	NUM
ajst-27738	144	2	.	.	PUNCT
ajst-27738	145	1	implementation	implementation	NOUN
ajst-27738	145	2	details	detail	NOUN
ajst-27738	145	3	training	training	NOUN
ajst-27738	145	4	strategy	strategy	NOUN
ajst-27738	145	5	:	:	PUNCT
ajst-27738	145	6	during	during	ADP
ajst-27738	145	7	training	training	NOUN
ajst-27738	145	8	,	,	PUNCT
ajst-27738	145	9	we	we	PRON
ajst-27738	145	10	utilized	utilize	VERB
ajst-27738	145	11	the	the	DET
ajst-27738	145	12	adam	adam	PROPN
ajst-27738	145	13	optimizer	optimizer	NOUN
ajst-27738	145	14	along	along	ADP
ajst-27738	145	15	with	with	ADP
ajst-27738	145	16	a	a	DET
ajst-27738	145	17	polynomial	polynomial	ADJ
ajst-27738	145	18	decay	decay	NOUN
ajst-27738	145	19	learning	learn	VERB
ajst-27738	145	20	rate	rate	NOUN
ajst-27738	145	21	scheduler	scheduler	NOUN
ajst-27738	145	22	and	and	CCONJ
ajst-27738	145	23	a	a	DET
ajst-27738	145	24	warm	warm	ADJ
ajst-27738	145	25	-	-	PUNCT
ajst-27738	145	26	up	up	ADP
ajst-27738	145	27	strategy	strategy	NOUN
ajst-27738	145	28	.	.	PUNCT
ajst-27738	146	1	for	for	ADP
ajst-27738	146	2	training	training	NOUN
ajst-27738	146	3	,	,	PUNCT
ajst-27738	146	4	a	a	DET
ajst-27738	146	5	single	single	ADJ
ajst-27738	146	6	rtx	rtx	NOUN
ajst-27738	146	7	3090	3090	NUM
ajst-27738	146	8	gpu	gpu	NOUN
ajst-27738	146	9	is	be	AUX
ajst-27738	146	10	utilised.considering	utilised.considere	VERB
ajst-27738	146	11	the	the	DET
ajst-27738	146	12	need	need	NOUN
ajst-27738	146	13	to	to	PART
ajst-27738	146	14	process	process	VERB
ajst-27738	146	15	images	image	NOUN
ajst-27738	146	16	with	with	ADP
ajst-27738	146	17	different	different	ADJ
ajst-27738	146	18	resolutions	resolution	NOUN
ajst-27738	146	19	,	,	PUNCT
ajst-27738	146	20	the	the	DET
ajst-27738	146	21	input	input	NOUN
ajst-27738	146	22	resolutions	resolution	NOUN
ajst-27738	146	23	are	be	AUX
ajst-27738	146	24	adjusted	adjust	VERB
ajst-27738	146	25	to	to	ADP
ajst-27738	146	26	512×1024	512×1024	NUM
ajst-27738	146	27	and	and	CCONJ
ajst-27738	146	28	768×1536	768×1536	NUM
ajst-27738	146	29	,	,	PUNCT
ajst-27738	146	30	the	the	DET
ajst-27738	146	31	batchsize	batchsize	NOUN
ajst-27738	146	32	is	be	AUX
ajst-27738	146	33	adjusted	adjust	VERB
ajst-27738	146	34	to	to	ADP
ajst-27738	146	35	20	20	NUM
ajst-27738	146	36	and	and	CCONJ
ajst-27738	146	37	10	10	NUM
ajst-27738	146	38	,	,	PUNCT
ajst-27738	146	39	the	the	DET
ajst-27738	146	40	maximum	maximum	ADJ
ajst-27738	146	41	number	number	NOUN
ajst-27738	146	42	of	of	ADP
ajst-27738	146	43	loops	loop	NOUN
ajst-27738	146	44	are	be	AUX
ajst-27738	146	45	both	both	PRON
ajst-27738	146	46	set	set	VERB
ajst-27738	146	47	to	to	ADP
ajst-27738	146	48	140k	140k	NUM
ajst-27738	146	49	,	,	PUNCT
ajst-27738	146	50	and	and	CCONJ
ajst-27738	146	51	the	the	DET
ajst-27738	146	52	initial	initial	ADJ
ajst-27738	146	53	learning	learning	NOUN
ajst-27738	146	54	rate	rate	NOUN
ajst-27738	146	55	is	be	AUX
ajst-27738	146	56	set	set	VERB
ajst-27738	146	57	to	to	ADP
ajst-27738	146	58	1e-3	1e-3	PROPN
ajst-27738	146	59	on	on	ADP
ajst-27738	146	60	cityscapes	cityscape	NOUN
ajst-27738	146	61	dataset.for	dataset.for	ADP
ajst-27738	146	62	data	datum	NOUN
ajst-27738	146	63	enhancement	enhancement	NOUN
ajst-27738	146	64	aspect	aspect	NOUN
ajst-27738	146	65	,	,	PUNCT
ajst-27738	146	66	random	random	ADJ
ajst-27738	146	67	scaling	scaling	NOUN
ajst-27738	146	68	,	,	PUNCT
ajst-27738	146	69	random	random	ADJ
ajst-27738	146	70	fill	fill	NOUN
ajst-27738	146	71	cropping	cropping	NOUN
ajst-27738	146	72	,	,	PUNCT
ajst-27738	146	73	and	and	CCONJ
ajst-27738	146	74	random	random	ADJ
ajst-27738	146	75	horizontal	horizontal	ADJ
ajst-27738	146	76	flipping	flipping	NOUN
ajst-27738	146	77	techniques	technique	NOUN
ajst-27738	146	78	are	be	AUX
ajst-27738	146	79	used	use	VERB
ajst-27738	146	80	.	.	PUNCT
ajst-27738	147	1	on	on	ADP
ajst-27738	147	2	the	the	DET
ajst-27738	147	3	camvid	camvid	NOUN
ajst-27738	147	4	dataset	dataset	NOUN
ajst-27738	147	5	,	,	PUNCT
ajst-27738	147	6	the	the	DET
ajst-27738	147	7	input	input	NOUN
ajst-27738	147	8	resolution	resolution	NOUN
ajst-27738	147	9	is	be	AUX
ajst-27738	147	10	adjusted	adjust	VERB
ajst-27738	147	11	to	to	ADP
ajst-27738	147	12	720	720	NUM
ajst-27738	147	13	×	×	NOUN
ajst-27738	147	14	960	960	NUM
ajst-27738	147	15	,	,	PUNCT
ajst-27738	147	16	the	the	DET
ajst-27738	147	17	batchsize	batchsize	NOUN
ajst-27738	147	18	is	be	AUX
ajst-27738	147	19	adjusted	adjust	VERB
ajst-27738	147	20	to	to	ADP
ajst-27738	147	21	16	16	NUM
ajst-27738	147	22	,	,	PUNCT
ajst-27738	147	23	and	and	CCONJ
ajst-27738	147	24	the	the	DET
ajst-27738	147	25	maximum	maximum	ADJ
ajst-27738	147	26	number	number	NOUN
ajst-27738	147	27	of	of	ADP
ajst-27738	147	28	loops	loop	NOUN
ajst-27738	147	29	is	be	AUX
ajst-27738	147	30	80k	80k	NUM
ajst-27738	147	31	.	.	PUNCT
ajst-27738	148	1	for	for	ADP
ajst-27738	148	2	data	data	NOUN
ajst-27738	148	3	enhancement	enhancement	NOUN
ajst-27738	148	4	,	,	PUNCT
ajst-27738	148	5	only	only	ADV
ajst-27738	148	6	random	random	ADJ
ajst-27738	148	7	cropping	cropping	NOUN
ajst-27738	148	8	is	be	AUX
ajst-27738	148	9	used	use	VERB
ajst-27738	148	10	.	.	PUNCT
ajst-27738	149	1	in	in	ADP
ajst-27738	149	2	addition	addition	NOUN
ajst-27738	149	3	,	,	PUNCT
ajst-27738	149	4	when	when	SCONJ
ajst-27738	149	5	training	train	VERB
ajst-27738	149	6	on	on	ADP
ajst-27738	149	7	the	the	DET
ajst-27738	149	8	camvid	camvid	NOUN
ajst-27738	149	9	dataset	dataset	NOUN
ajst-27738	149	10	,	,	PUNCT
ajst-27738	149	11	the	the	DET
ajst-27738	149	12	trained	train	VERB
ajst-27738	149	13	pre	pre	NOUN
ajst-27738	149	14	-	-	ADJ
ajst-27738	149	15	training	training	ADJ
ajst-27738	149	16	weights	weight	NOUN
ajst-27738	149	17	on	on	ADP
ajst-27738	149	18	the	the	DET
ajst-27738	149	19	cityscapes	cityscape	NOUN
ajst-27738	149	20	dataset	dataset	VERB
ajst-27738	149	21	are	be	AUX
ajst-27738	149	22	added	add	VERB
ajst-27738	149	23	.	.	PUNCT
ajst-27738	150	1	in	in	ADP
ajst-27738	150	2	the	the	DET
ajst-27738	150	3	inference	inference	NOUN
ajst-27738	150	4	phase	phase	NOUN
ajst-27738	150	5	,	,	PUNCT
ajst-27738	150	6	this	this	DET
ajst-27738	150	7	experiment	experiment	NOUN
ajst-27738	150	8	does	do	AUX
ajst-27738	150	9	not	not	PART
ajst-27738	150	10	use	use	VERB
ajst-27738	150	11	any	any	DET
ajst-27738	150	12	acceleration	acceleration	NOUN
ajst-27738	150	13	trick	trick	NOUN
ajst-27738	150	14	over	over	ADP
ajst-27738	150	15	strategy	strategy	NOUN
ajst-27738	150	16	and	and	CCONJ
ajst-27738	150	17	uses	use	VERB
ajst-27738	150	18	the	the	DET
ajst-27738	150	19	test	test	NOUN
ajst-27738	150	20	code	code	NOUN
ajst-27738	150	21	provided	provide	VERB
ajst-27738	150	22	by	by	ADP
ajst-27738	150	23	the	the	DET
ajst-27738	150	24	paddlepaddle	paddlepaddle	NOUN
ajst-27738	150	25	deep	deep	ADJ
ajst-27738	150	26	learning	learning	NOUN
ajst-27738	150	27	framework	framework	NOUN
ajst-27738	150	28	for	for	ADP
ajst-27738	150	29	speedup	speedup	NOUN
ajst-27738	150	30	.	.	PUNCT
ajst-27738	151	1	in	in	ADP
ajst-27738	151	2	order	order	NOUN
ajst-27738	151	3	to	to	PART
ajst-27738	151	4	ensure	ensure	VERB
ajst-27738	151	5	the	the	DET
ajst-27738	151	6	effectiveness	effectiveness	NOUN
ajst-27738	151	7	of	of	ADP
ajst-27738	151	8	the	the	DET
ajst-27738	151	9	model	model	NOUN
ajst-27738	151	10	in	in	ADP
ajst-27738	151	11	practical	practical	ADJ
ajst-27738	151	12	applications	application	NOUN
ajst-27738	151	13	,	,	PUNCT
ajst-27738	151	14	images	image	NOUN
ajst-27738	151	15	with	with	ADP
ajst-27738	151	16	different	different	ADJ
ajst-27738	151	17	resolutions	resolution	NOUN
ajst-27738	151	18	were	be	AUX
ajst-27738	151	19	used	use	VERB
ajst-27738	151	20	for	for	ADP
ajst-27738	151	21	inference	inference	NOUN
ajst-27738	151	22	,	,	PUNCT
ajst-27738	151	23	and	and	CCONJ
ajst-27738	151	24	the	the	DET
ajst-27738	151	25	processing	processing	NOUN
ajst-27738	151	26	speed	speed	NOUN
ajst-27738	151	27	and	and	CCONJ
ajst-27738	151	28	segmentation	segmentation	NOUN
ajst-27738	151	29	accuracy	accuracy	NOUN
ajst-27738	151	30	were	be	AUX
ajst-27738	151	31	comprehensively	comprehensively	ADV
ajst-27738	151	32	evaluated	evaluate	VERB
ajst-27738	151	33	.	.	PUNCT
ajst-27738	152	1	ultimately	ultimately	ADV
ajst-27738	152	2	,	,	PUNCT
ajst-27738	152	3	the	the	DET
ajst-27738	152	4	standard	standard	ADJ
ajst-27738	152	5	metric	metric	NOUN
ajst-27738	152	6	of	of	ADP
ajst-27738	152	7	concurrent	concurrent	ADJ
ajst-27738	152	8	average	average	ADJ
ajst-27738	152	9	intersection	intersection	NOUN
ajst-27738	152	10	and	and	CCONJ
ajst-27738	152	11	frames	frame	NOUN
ajst-27738	152	12	per	per	ADP
ajst-27738	152	13	second	second	ADJ
ajst-27738	152	14	were	be	AUX
ajst-27738	152	15	used	use	VERB
ajst-27738	152	16	to	to	PART
ajst-27738	152	17	compare	compare	VERB
ajst-27738	152	18	the	the	DET
ajst-27738	152	19	performance	performance	NOUN
ajst-27738	152	20	of	of	ADP
ajst-27738	152	21	different	different	ADJ
ajst-27738	152	22	models	model	NOUN
ajst-27738	152	23	.	.	PUNCT
ajst-27738	153	1	inference	inference	NOUN
ajst-27738	153	2	settings	setting	NOUN
ajst-27738	153	3	:	:	PUNCT
ajst-27738	153	4	during	during	ADP
ajst-27738	153	5	inference	inference	NOUN
ajst-27738	153	6	,	,	PUNCT
ajst-27738	153	7	without	without	ADP
ajst-27738	153	8	employing	employ	VERB
ajst-27738	153	9	acceleration	acceleration	NOUN
ajst-27738	153	10	techniques	technique	NOUN
ajst-27738	153	11	such	such	ADJ
ajst-27738	153	12	as	as	ADP
ajst-27738	153	13	sliding	slide	VERB
ajst-27738	153	14	window	window	NOUN
ajst-27738	153	15	evaluation	evaluation	NOUN
ajst-27738	153	16	or	or	CCONJ
ajst-27738	153	17	tension	tension	NOUN
ajst-27738	153	18	acceleration	acceleration	NOUN
ajst-27738	153	19	strategies	strategy	NOUN
ajst-27738	153	20	,	,	PUNCT
ajst-27738	153	21	for	for	ADP
ajst-27738	153	22	the	the	DET
ajst-27738	153	23	cityscapes	cityscape	NOUN
ajst-27738	153	24	dataset	dataset	VERB
ajst-27738	153	25	,	,	PUNCT
ajst-27738	153	26	we	we	PRON
ajst-27738	153	27	use	use	VERB
ajst-27738	153	28	768×1536	768×1536	NUM
ajst-27738	153	29	and	and	CCONJ
ajst-27738	153	30	512×1024	512×1024	NUM
ajst-27738	153	31	resolutions	resolution	NOUN
ajst-27738	153	32	for	for	ADP
ajst-27738	153	33	inference	inference	NOUN
ajst-27738	153	34	.	.	PUNCT
ajst-27738	154	1	for	for	ADP
ajst-27738	154	2	the	the	DET
ajst-27738	154	3	camvid	camvid	PROPN
ajst-27738	154	4	dataset	dataset	NOUN
ajst-27738	154	5	,	,	PUNCT
ajst-27738	154	6	inference	inference	NOUN
ajst-27738	154	7	was	be	AUX
ajst-27738	154	8	performed	perform	VERB
ajst-27738	154	9	using	use	VERB
ajst-27738	154	10	a	a	DET
ajst-27738	154	11	resolution	resolution	NOUN
ajst-27738	154	12	of	of	ADP
ajst-27738	154	13	960×720	960×720	NUM
ajst-27738	154	14	.	.	PUNCT
ajst-27738	155	1	we	we	PRON
ajst-27738	155	2	used	use	VERB
ajst-27738	155	3	nvidia	nvidia	PROPN
ajst-27738	155	4	gtx	gtx	PROPN
ajst-27738	155	5	3090	3090	NUM
ajst-27738	155	6	gpu	gpu	NOUN
ajst-27738	155	7	and	and	CCONJ
ajst-27738	155	8	performed	perform	VERB
ajst-27738	155	9	all	all	DET
ajst-27738	155	10	inference	inference	NOUN
ajst-27738	155	11	experiments	experiment	NOUN
ajst-27738	155	12	on	on	ADP
ajst-27738	155	13	cuda	cuda	PROPN
ajst-27738	155	14	11.2	11.2	NUM
ajst-27738	155	15	and	and	CCONJ
ajst-27738	155	16	cudnn	cudnn	NOUN
ajst-27738	155	17	8.1	8.1	NUM
ajst-27738	155	18	environments	environment	NOUN
ajst-27738	155	19	.	.	PUNCT
ajst-27738	156	1	we	we	PRON
ajst-27738	156	2	employed	employ	VERB
ajst-27738	156	3	the	the	DET
ajst-27738	156	4	standard	standard	ADJ
ajst-27738	156	5	metrics	metric	NOUN
ajst-27738	156	6	of	of	ADP
ajst-27738	156	7	mean	mean	ADJ
ajst-27738	156	8	intersection	intersection	NOUN
ajst-27738	156	9	over	over	ADP
ajst-27738	156	10	union	union	NOUN
ajst-27738	156	11	(	(	PUNCT
ajst-27738	156	12	miou	miou	NOUN
ajst-27738	156	13	)	)	PUNCT
ajst-27738	156	14	for	for	ADP
ajst-27738	156	15	segmentation	segmentation	NOUN
ajst-27738	156	16	accuracy	accuracy	NOUN
ajst-27738	156	17	comparisons	comparison	NOUN
ajst-27738	156	18	and	and	CCONJ
ajst-27738	156	19	frames	frame	NOUN
ajst-27738	156	20	per	per	ADP
ajst-27738	156	21	second	second	ADJ
ajst-27738	156	22	(	(	PUNCT
ajst-27738	156	23	fps	fps	PROPN
ajst-27738	156	24	)	)	PUNCT
ajst-27738	156	25	for	for	ADP
ajst-27738	156	26	inference	inference	NOUN
ajst-27738	156	27	speed	speed	NOUN
ajst-27738	156	28	comparisons	comparison	NOUN
ajst-27738	156	29	.	.	PUNCT
ajst-27738	157	1	4.3	4.3	NUM
ajst-27738	157	2	.	.	PUNCT
ajst-27738	157	3	experiments	experiment	NOUN
ajst-27738	157	4	on	on	ADP
ajst-27738	157	5	cityscapes	cityscape	NOUN
ajst-27738	157	6	4.3.1	4.3.1	NUM
ajst-27738	157	7	.	.	PUNCT
ajst-27738	157	8	ablation	ablation	NOUN
ajst-27738	157	9	study	study	NOUN
ajst-27738	157	10	in	in	ADP
ajst-27738	157	11	this	this	DET
ajst-27738	157	12	section	section	NOUN
ajst-27738	157	13	,	,	PUNCT
ajst-27738	157	14	ablation	ablation	NOUN
ajst-27738	157	15	experiments	experiment	NOUN
ajst-27738	157	16	are	be	AUX
ajst-27738	157	17	carried	carry	VERB
ajst-27738	157	18	out	out	ADP
ajst-27738	157	19	on	on	ADP
ajst-27738	157	20	each	each	DET
ajst-27738	157	21	component	component	NOUN
ajst-27738	157	22	in	in	ADP
ajst-27738	157	23	the	the	DET
ajst-27738	157	24	lightweight	lightweight	ADJ
ajst-27738	157	25	densely	densely	ADV
ajst-27738	157	26	connected	connect	VERB
ajst-27738	157	27	contextual	contextual	ADJ
ajst-27738	157	28	refinement	refinement	NOUN
ajst-27738	157	29	branch	branch	NOUN
ajst-27738	157	30	of	of	ADP
ajst-27738	157	31	artrnet	artrnet	NOUN
ajst-27738	157	32	as	as	ADV
ajst-27738	157	33	well	well	ADV
ajst-27738	157	34	as	as	ADP
ajst-27738	157	35	on	on	ADP
ajst-27738	157	36	the	the	DET
ajst-27738	157	37	deformed	deform	VERB
ajst-27738	157	38	convolutional	convolutional	ADJ
ajst-27738	157	39	attention	attention	NOUN
ajst-27738	157	40	refinement	refinement	NOUN
ajst-27738	157	41	fusion	fusion	NOUN
ajst-27738	157	42	module	module	NOUN
ajst-27738	157	43	.	.	PUNCT
ajst-27738	158	1	the	the	DET
ajst-27738	158	2	method	method	NOUN
ajst-27738	158	3	of	of	ADP
ajst-27738	158	4	control	control	NOUN
ajst-27738	158	5	variables	variable	NOUN
ajst-27738	158	6	in	in	ADP
ajst-27738	158	7	physical	physical	ADJ
ajst-27738	158	8	experiments	experiment	NOUN
ajst-27738	158	9	is	be	AUX
ajst-27738	158	10	taken	take	VERB
ajst-27738	158	11	and	and	CCONJ
ajst-27738	158	12	experiments	experiment	NOUN
ajst-27738	158	13	are	be	AUX
ajst-27738	158	14	conducted	conduct	VERB
ajst-27738	158	15	module	module	NOUN
ajst-27738	158	16	by	by	ADP
ajst-27738	158	17	module	module	NOUN
ajst-27738	158	18	to	to	PART
ajst-27738	158	19	see	see	VERB
ajst-27738	158	20	their	their	PRON
ajst-27738	158	21	effects	effect	NOUN
ajst-27738	158	22	on	on	ADP
ajst-27738	158	23	the	the	DET
ajst-27738	158	24	experimental	experimental	ADJ
ajst-27738	158	25	results	result	NOUN
ajst-27738	158	26	,	,	PUNCT
ajst-27738	158	27	thus	thus	ADV
ajst-27738	158	28	proving	prove	VERB
ajst-27738	158	29	that	that	SCONJ
ajst-27738	158	30	the	the	DET
ajst-27738	158	31	proposed	propose	VERB
ajst-27738	158	32	model	model	NOUN
ajst-27738	158	33	achieves	achieve	VERB
ajst-27738	158	34	significant	significant	ADJ
ajst-27738	158	35	improvements	improvement	NOUN
ajst-27738	158	36	.	.	PUNCT
ajst-27738	159	1	all	all	DET
ajst-27738	159	2	ablation	ablation	NOUN
ajst-27738	159	3	experiments	experiment	NOUN
ajst-27738	159	4	were	be	AUX
ajst-27738	159	5	conducted	conduct	VERB
ajst-27738	159	6	on	on	ADP
ajst-27738	159	7	the	the	DET
ajst-27738	159	8	cityscapes	cityscape	NOUN
ajst-27738	159	9	dataset	dataset	VERB
ajst-27738	159	10	.	.	PUNCT
ajst-27738	160	1	in	in	ADP
ajst-27738	160	2	order	order	NOUN
ajst-27738	160	3	to	to	PART
ajst-27738	160	4	verify	verify	VERB
ajst-27738	160	5	the	the	DET
ajst-27738	160	6	effectiveness	effectiveness	NOUN
ajst-27738	160	7	of	of	ADP
ajst-27738	160	8	the	the	DET
ajst-27738	160	9	downsampling	downsample	VERB
ajst-27738	160	10	module	module	NOUN
ajst-27738	160	11	(	(	PUNCT
ajst-27738	160	12	dsm	dsm	PROPN
ajst-27738	160	13	)	)	PUNCT
ajst-27738	160	14	,	,	PUNCT
ajst-27738	160	15	the	the	DET
ajst-27738	160	16	experiments	experiment	NOUN
ajst-27738	160	17	will	will	AUX
ajst-27738	160	18	be	be	AUX
ajst-27738	160	19	conducted	conduct	VERB
ajst-27738	160	20	on	on	ADP
ajst-27738	160	21	the	the	DET
ajst-27738	160	22	basis	basis	NOUN
ajst-27738	160	23	of	of	ADP
ajst-27738	160	24	input	input	NOUN
ajst-27738	160	25	images	image	NOUN
ajst-27738	160	26	with	with	ADP
ajst-27738	160	27	resolutions	resolution	NOUN
ajst-27738	160	28	of	of	ADP
ajst-27738	160	29	512×1024	512×1024	NUM
ajst-27738	160	30	and	and	CCONJ
ajst-27738	160	31	768	768	NUM
ajst-27738	160	32	×1536	×1536	NOUN
ajst-27738	160	33	,	,	PUNCT
ajst-27738	160	34	respectively	respectively	ADV
ajst-27738	160	35	.	.	PUNCT
ajst-27738	161	1	from	from	ADP
ajst-27738	161	2	table	table	NOUN
ajst-27738	161	3	1(a	1(a	NUM
ajst-27738	161	4	)	)	PUNCT
ajst-27738	161	5	,	,	PUNCT
ajst-27738	161	6	it	it	PRON
ajst-27738	161	7	can	can	AUX
ajst-27738	161	8	be	be	AUX
ajst-27738	161	9	seen	see	VERB
ajst-27738	161	10	that	that	SCONJ
ajst-27738	161	11	when	when	SCONJ
ajst-27738	161	12	the	the	DET
ajst-27738	161	13	attention	attention	NOUN
ajst-27738	161	14	refinement	refinement	NOUN
ajst-27738	161	15	module	module	NOUN
ajst-27738	161	16	is	be	AUX
ajst-27738	161	17	used	use	VERB
ajst-27738	161	18	for	for	ADP
ajst-27738	161	19	both	both	PRON
ajst-27738	161	20	by	by	ADP
ajst-27738	161	21	default	default	NOUN
ajst-27738	161	22	,	,	PUNCT
ajst-27738	161	23	the	the	DET
ajst-27738	161	24	miou	miou	NOUN
ajst-27738	161	25	of	of	ADP
ajst-27738	161	26	the	the	DET
ajst-27738	161	27	model	model	NOUN
ajst-27738	161	28	is	be	AUX
ajst-27738	161	29	not	not	PART
ajst-27738	161	30	too	too	ADV
ajst-27738	161	31	good	good	ADJ
ajst-27738	161	32	at	at	ADP
ajst-27738	161	33	512×1024	512×1024	NUM
ajst-27738	161	34	resolution	resolution	NOUN
ajst-27738	161	35	when	when	SCONJ
ajst-27738	161	36	normal	normal	ADJ
ajst-27738	161	37	convolution	convolution	NOUN
ajst-27738	161	38	is	be	AUX
ajst-27738	161	39	used	use	VERB
ajst-27738	161	40	.	.	PUNCT
ajst-27738	162	1	whereas	whereas	SCONJ
ajst-27738	162	2	when	when	SCONJ
ajst-27738	162	3	the	the	DET
ajst-27738	162	4	dsm	dsm	PROPN
ajst-27738	162	5	module	module	NOUN
ajst-27738	162	6	is	be	AUX
ajst-27738	162	7	used	use	VERB
ajst-27738	162	8	,	,	PUNCT
ajst-27738	162	9	it	it	PRON
ajst-27738	162	10	can	can	AUX
ajst-27738	162	11	be	be	AUX
ajst-27738	162	12	seen	see	VERB
ajst-27738	162	13	that	that	SCONJ
ajst-27738	162	14	the	the	DET
ajst-27738	162	15	models	model	NOUN
ajst-27738	162	16	all	all	PRON
ajst-27738	162	17	have	have	VERB
ajst-27738	162	18	better	well	ADJ
ajst-27738	162	19	predictions	prediction	NOUN
ajst-27738	162	20	with	with	ADP
ajst-27738	162	21	a	a	DET
ajst-27738	162	22	slightly	slightly	ADV
ajst-27738	162	23	improved	improved	ADJ
ajst-27738	162	24	miou	miou	NOUN
ajst-27738	162	25	of	of	ADP
ajst-27738	162	26	73.2	73.2	NUM
ajst-27738	162	27	%	%	NOUN
ajst-27738	162	28	than	than	ADP
ajst-27738	162	29	when	when	SCONJ
ajst-27738	162	30	the	the	DET
ajst-27738	162	31	dsm	dsm	PROPN
ajst-27738	162	32	module	module	NOUN
ajst-27738	162	33	is	be	AUX
ajst-27738	162	34	not	not	PART
ajst-27738	162	35	used	use	VERB
ajst-27738	162	36	.	.	PUNCT
ajst-27738	163	1	this	this	PRON
ajst-27738	163	2	could	could	AUX
ajst-27738	163	3	mean	mean	VERB
ajst-27738	163	4	that	that	SCONJ
ajst-27738	163	5	the	the	DET
ajst-27738	163	6	dsm	dsm	PROPN
ajst-27738	163	7	provides	provide	VERB
ajst-27738	163	8	a	a	DET
ajst-27738	163	9	better	well	ADJ
ajst-27738	163	10	representation	representation	NOUN
ajst-27738	163	11	of	of	ADP
ajst-27738	163	12	the	the	DET
ajst-27738	163	13	features	feature	NOUN
ajst-27738	163	14	during	during	ADP
ajst-27738	163	15	the	the	DET
ajst-27738	163	16	downsampling	downsample	VERB
ajst-27738	163	17	process	process	NOUN
ajst-27738	163	18	.	.	PUNCT
ajst-27738	164	1	a	a	DET
ajst-27738	164	2	similar	similar	ADJ
ajst-27738	164	3	trend	trend	NOUN
ajst-27738	164	4	is	be	AUX
ajst-27738	164	5	observed	observe	VERB
ajst-27738	164	6	at	at	ADP
ajst-27738	164	7	a	a	DET
ajst-27738	164	8	higher	high	ADJ
ajst-27738	164	9	resolution	resolution	NOUN
ajst-27738	164	10	of	of	ADP
ajst-27738	164	11	768×1536	768×1536	NUM
ajst-27738	164	12	.	.	PUNCT
ajst-27738	165	1	with	with	ADP
ajst-27738	165	2	arm	arm	NOUN
ajst-27738	165	3	,	,	PUNCT
ajst-27738	165	4	the	the	DET
ajst-27738	165	5	miou	miou	NOUN
ajst-27738	165	6	of	of	ADP
ajst-27738	165	7	artrnet	artrnet	NOUN
ajst-27738	165	8	with	with	ADP
ajst-27738	165	9	dsm	dsm	PROPN
ajst-27738	165	10	only	only	ADV
ajst-27738	165	11	is	be	AUX
ajst-27738	165	12	73.2	73.2	NUM
ajst-27738	165	13	%	%	NOUN
ajst-27738	165	14	at	at	ADP
ajst-27738	165	15	512×1024	512×1024	NUM
ajst-27738	165	16	resolution	resolution	NOUN
ajst-27738	165	17	,	,	PUNCT
ajst-27738	165	18	while	while	SCONJ
ajst-27738	165	19	at	at	ADP
ajst-27738	165	20	768×1536	768×1536	NUM
ajst-27738	165	21	resolution	resolution	NOUN
ajst-27738	165	22	,	,	PUNCT
ajst-27738	165	23	the	the	DET
ajst-27738	165	24	miou	miou	NOUN
ajst-27738	165	25	improves	improve	VERB
ajst-27738	165	26	to	to	ADP
ajst-27738	165	27	74.2	74.2	NUM
ajst-27738	165	28	%	%	NOUN
ajst-27738	165	29	.	.	PUNCT
ajst-27738	166	1	this	this	PRON
ajst-27738	166	2	further	far	ADV
ajst-27738	166	3	confirms	confirm	VERB
ajst-27738	166	4	the	the	DET
ajst-27738	166	5	effectiveness	effectiveness	NOUN
ajst-27738	166	6	of	of	ADP
ajst-27738	166	7	dsm	dsm	PROPN
ajst-27738	166	8	in	in	ADP
ajst-27738	166	9	processing	process	VERB
ajst-27738	166	10	higher	high	ADJ
ajst-27738	166	11	resolution	resolution	NOUN
ajst-27738	166	12	images	image	NOUN
ajst-27738	166	13	.	.	PUNCT
ajst-27738	167	1	next	next	ADV
ajst-27738	167	2	,	,	PUNCT
ajst-27738	167	3	in	in	ADP
ajst-27738	167	4	table	table	NOUN
ajst-27738	167	5	1(b	1(b	NUM
ajst-27738	167	6	)	)	PUNCT
ajst-27738	167	7	,	,	PUNCT
ajst-27738	167	8	the	the	DET
ajst-27738	167	9	effect	effect	NOUN
ajst-27738	167	10	of	of	ADP
ajst-27738	167	11	arm	arm	NOUN
ajst-27738	167	12	on	on	ADP
ajst-27738	167	13	artrnet	artrnet	NOUN
ajst-27738	167	14	performance	performance	NOUN
ajst-27738	167	15	at	at	ADP
ajst-27738	167	16	different	different	ADJ
ajst-27738	167	17	resolutions	resolution	NOUN
ajst-27738	167	18	is	be	AUX
ajst-27738	167	19	explored	explore	VERB
ajst-27738	167	20	.	.	PUNCT
ajst-27738	168	1	using	use	VERB
ajst-27738	168	2	dsm	dsm	NOUN
ajst-27738	168	3	by	by	ADP
ajst-27738	168	4	default	default	NOUN
ajst-27738	168	5	for	for	ADP
ajst-27738	168	6	all	all	PRON
ajst-27738	168	7	,	,	PUNCT
ajst-27738	168	8	the	the	DET
ajst-27738	168	9	miou	miou	NOUN
ajst-27738	168	10	of	of	ADP
ajst-27738	168	11	artrnet	artrnet	NOUN
ajst-27738	168	12	with	with	ADP
ajst-27738	168	13	arm	arm	NOUN
ajst-27738	168	14	is	be	AUX
ajst-27738	168	15	73.2	73.2	NUM
ajst-27738	168	16	%	%	NOUN
ajst-27738	168	17	at	at	ADP
ajst-27738	168	18	512×1024	512×1024	NUM
ajst-27738	168	19	resolution	resolution	NOUN
ajst-27738	168	20	.	.	PUNCT
ajst-27738	169	1	however	however	ADV
ajst-27738	169	2	,	,	PUNCT
ajst-27738	169	3	at	at	ADP
ajst-27738	169	4	768×1536	768×1536	NUM
ajst-27738	169	5	resolution	resolution	NOUN
ajst-27738	169	6	,	,	PUNCT
ajst-27738	169	7	the	the	DET
ajst-27738	169	8	miou	miou	NOUN
ajst-27738	169	9	of	of	ADP
ajst-27738	169	10	artrnet	artrnet	NOUN
ajst-27738	169	11	using	use	VERB
ajst-27738	169	12	arm	arm	NOUN
ajst-27738	169	13	reaches	reach	VERB
ajst-27738	169	14	74.2	74.2	NUM
ajst-27738	169	15	%	%	NOUN
ajst-27738	169	16	.	.	PUNCT
ajst-27738	170	1	this	this	PRON
ajst-27738	170	2	shows	show	VERB
ajst-27738	170	3	that	that	SCONJ
ajst-27738	170	4	arm	arm	NOUN
ajst-27738	170	5	plays	play	VERB
ajst-27738	170	6	an	an	DET
ajst-27738	170	7	equally	equally	ADV
ajst-27738	170	8	important	important	ADJ
ajst-27738	170	9	role	role	NOUN
ajst-27738	170	10	in	in	ADP
ajst-27738	170	11	attention	attention	NOUN
ajst-27738	170	12	refinement	refinement	NOUN
ajst-27738	170	13	,	,	PUNCT
ajst-27738	170	14	especially	especially	ADV
ajst-27738	170	15	when	when	SCONJ
ajst-27738	170	16	dealing	deal	VERB
ajst-27738	170	17	with	with	ADP
ajst-27738	170	18	higher	high	ADJ
ajst-27738	170	19	resolution	resolution	NOUN
ajst-27738	170	20	images	image	NOUN
ajst-27738	170	21	.	.	PUNCT
ajst-27738	171	1	the	the	DET
ajst-27738	171	2	experimental	experimental	ADJ
ajst-27738	171	3	results	result	NOUN
ajst-27738	171	4	in	in	ADP
ajst-27738	171	5	this	this	DET
ajst-27738	171	6	section	section	NOUN
ajst-27738	171	7	highlight	highlight	VERB
ajst-27738	171	8	the	the	DET
ajst-27738	171	9	effectiveness	effectiveness	NOUN
ajst-27738	171	10	of	of	ADP
ajst-27738	171	11	dsm	dsm	PROPN
ajst-27738	171	12	and	and	CCONJ
ajst-27738	171	13	arm	arm	NOUN
ajst-27738	171	14	in	in	ADP
ajst-27738	171	15	artrnet	artrnet	NOUN
ajst-27738	171	16	.	.	PUNCT
ajst-27738	172	1	table	table	NOUN
ajst-27738	172	2	1	1	NUM
ajst-27738	172	3	.	.	PUNCT
ajst-27738	172	4	comparison	comparison	NOUN
ajst-27738	172	5	of	of	ADP
ajst-27738	172	6	dam	dam	NOUN
ajst-27738	172	7	and	and	CCONJ
ajst-27738	172	8	arm	arm	NOUN
ajst-27738	172	9	in	in	ADP
ajst-27738	172	10	artrnet	artrnet	NOUN
ajst-27738	172	11	on	on	ADP
ajst-27738	172	12	the	the	DET
ajst-27738	172	13	cityscapes	cityscape	NOUN
ajst-27738	172	14	validation	validation	NOUN
ajst-27738	172	15	set	set	NOUN
ajst-27738	172	16	.	.	PUNCT
ajst-27738	173	1	model	model	NOUN
ajst-27738	173	2	resolution	resolution	NOUN
ajst-27738	173	3	none	none	NOUN
ajst-27738	173	4	dsm	dsm	ADJ
ajst-27738	173	5	none	none	NOUN
ajst-27738	173	6	arm	arm	NOUN
ajst-27738	173	7	miou	miou	NOUN
ajst-27738	173	8	(	(	PUNCT
ajst-27738	173	9	a	a	NOUN
ajst-27738	173	10	)	)	PUNCT
ajst-27738	173	11	dsm	dsm	ADJ
ajst-27738	173	12	artrnet	artrnet	NOUN
ajst-27738	173	13	512×1024	512×1024	NUM
ajst-27738	173	14	√	√	NUM
ajst-27738	173	15	√	√	ADP
ajst-27738	173	16	72.3	72.3	NUM
ajst-27738	173	17	artrnet	artrnet	NOUN
ajst-27738	173	18	512×1024	512×1024	NUM
ajst-27738	173	19	√	√	NUM
ajst-27738	173	20	√	√	ADP
ajst-27738	173	21	73.2	73.2	NUM
ajst-27738	173	22	artrnet	artrnet	NOUN
ajst-27738	173	23	768×1536	768×1536	NUM
ajst-27738	173	24	√	√	NOUN
ajst-27738	173	25	√	√	ADP
ajst-27738	173	26	72.8	72.8	NUM
ajst-27738	173	27	artrnet	artrnet	NOUN
ajst-27738	173	28	768×1536	768×1536	NUM
ajst-27738	173	29	√	√	NOUN
ajst-27738	173	30	√	√	ADP
ajst-27738	173	31	74.2	74.2	NUM
ajst-27738	173	32	(	(	PUNCT
ajst-27738	173	33	b	b	NOUN
ajst-27738	173	34	)	)	PUNCT
ajst-27738	173	35	arm	arm	NOUN
ajst-27738	173	36	artrnet	artrnet	VERB
ajst-27738	173	37	512×1024	512×1024	NUM
ajst-27738	173	38	√	√	NUM
ajst-27738	173	39	√	√	ADP
ajst-27738	173	40	72.6	72.6	NUM
ajst-27738	173	41	artrnet	artrnet	NOUN
ajst-27738	173	42	512×1024	512×1024	NUM
ajst-27738	173	43	√	√	NUM
ajst-27738	173	44	√	√	ADP
ajst-27738	173	45	73.2	73.2	NUM
ajst-27738	173	46	artrnet	artrnet	NOUN
ajst-27738	173	47	768×1536	768×1536	NUM
ajst-27738	173	48	√	√	NUM
ajst-27738	173	49	√	√	ADP
ajst-27738	173	50	72.9	72.9	NUM
ajst-27738	173	51	artrnet	artrnet	NOUN
ajst-27738	173	52	768×1536	768×1536	NUM
ajst-27738	173	53	√	√	NUM
ajst-27738	173	54	√	√	ADP
ajst-27738	173	55	74.2	74.2	NUM
ajst-27738	173	56	to	to	PART
ajst-27738	173	57	assess	assess	VERB
ajst-27738	173	58	the	the	DET
ajst-27738	173	59	impact	impact	NOUN
ajst-27738	173	60	of	of	ADP
ajst-27738	173	61	the	the	DET
ajst-27738	173	62	low	low	ADJ
ajst-27738	173	63	resolution	resolution	NOUN
ajst-27738	173	64	context	context	NOUN
ajst-27738	173	65	aggregation	aggregation	NOUN
ajst-27738	173	66	module	module	NOUN
ajst-27738	173	67	(	(	PUNCT
ajst-27738	173	68	lrcam	lrcam	PROPN
ajst-27738	173	69	)	)	PUNCT
ajst-27738	173	70	and	and	CCONJ
ajst-27738	173	71	deformed	deform	VERB
ajst-27738	173	72	convolutional	convolutional	ADJ
ajst-27738	173	73	attention	attention	NOUN
ajst-27738	173	74	refinement	refinement	NOUN
ajst-27738	173	75	fusion	fusion	NOUN
ajst-27738	173	76	module	module	NOUN
ajst-27738	173	77	(	(	PUNCT
ajst-27738	173	78	dcarfm	dcarfm	NOUN
ajst-27738	173	79	)	)	PUNCT
ajst-27738	173	80	on	on	ADP
ajst-27738	173	81	semantic	semantic	ADJ
ajst-27738	173	82	segmentation	segmentation	NOUN
ajst-27738	173	83	performance	performance	NOUN
ajst-27738	173	84	across	across	ADP
ajst-27738	173	85	various	various	ADJ
ajst-27738	173	86	resolutions	resolution	NOUN
ajst-27738	173	87	.	.	PUNCT
ajst-27738	174	1	in	in	ADP
ajst-27738	174	2	this	this	DET
ajst-27738	174	3	subsection	subsection	NOUN
ajst-27738	174	4	,	,	PUNCT
ajst-27738	174	5	ablation	ablation	NOUN
ajst-27738	174	6	experiments	experiment	NOUN
ajst-27738	174	7	are	be	AUX
ajst-27738	174	8	performed	perform	VERB
ajst-27738	174	9	on	on	ADP
ajst-27738	174	10	the	the	DET
ajst-27738	174	11	low	low	ADJ
ajst-27738	174	12	resolution	resolution	NOUN
ajst-27738	174	13	context	context	NOUN
ajst-27738	174	14	aggregation	aggregation	NOUN
ajst-27738	174	15	module	module	NOUN
ajst-27738	174	16	(	(	PUNCT
ajst-27738	174	17	lrcam	lrcam	PROPN
ajst-27738	174	18	)	)	PUNCT
ajst-27738	174	19	and	and	CCONJ
ajst-27738	174	20	deformed	deform	VERB
ajst-27738	174	21	convolutional	convolutional	ADJ
ajst-27738	174	22	attention	attention	NOUN
ajst-27738	174	23	refinement	refinement	NOUN
ajst-27738	174	24	fusion	fusion	NOUN
ajst-27738	174	25	module	module	NOUN
ajst-27738	174	26	(	(	PUNCT
ajst-27738	174	27	dcarfm	dcarfm	NOUN
ajst-27738	174	28	)	)	PUNCT
ajst-27738	174	29	.	.	PUNCT
ajst-27738	175	1	using	use	VERB
ajst-27738	175	2	the	the	DET
ajst-27738	175	3	dsm	dsm	PROPN
ajst-27738	175	4	module	module	NOUN
ajst-27738	175	5	and	and	CCONJ
ajst-27738	175	6	arm	arm	NOUN
ajst-27738	175	7	module	module	NOUN
ajst-27738	175	8	by	by	ADP
ajst-27738	175	9	default	default	NOUN
ajst-27738	175	10	,	,	PUNCT
ajst-27738	175	11	table	table	NOUN
ajst-27738	175	12	2(c	2(c	NUM
ajst-27738	175	13	)	)	PUNCT
ajst-27738	175	14	demonstrates	demonstrate	VERB
ajst-27738	175	15	the	the	DET
ajst-27738	175	16	experimental	experimental	ADJ
ajst-27738	175	17	results	result	NOUN
ajst-27738	175	18	of	of	ADP
ajst-27738	175	19	the	the	DET
ajst-27738	175	20	low	low	ADJ
ajst-27738	175	21	-	-	PUNCT
ajst-27738	175	22	resolution	resolution	NOUN
ajst-27738	175	23	context	context	NOUN
ajst-27738	175	24	aggregation	aggregation	NOUN
ajst-27738	175	25	module	module	NOUN
ajst-27738	175	26	(	(	PUNCT
ajst-27738	175	27	lrcam	lrcam	PROPN
ajst-27738	175	28	)	)	PUNCT
ajst-27738	175	29	,	,	PUNCT
ajst-27738	175	30	from	from	ADP
ajst-27738	175	31	which	which	PRON
ajst-27738	175	32	it	it	PRON
ajst-27738	175	33	can	can	AUX
ajst-27738	175	34	be	be	AUX
ajst-27738	175	35	seen	see	VERB
ajst-27738	175	36	that	that	SCONJ
ajst-27738	175	37	the	the	DET
ajst-27738	175	38	model	model	NOUN
ajst-27738	175	39	with	with	ADP
ajst-27738	175	40	the	the	DET
ajst-27738	175	41	introduction	introduction	NOUN
ajst-27738	175	42	of	of	ADP
ajst-27738	175	43	the	the	DET
ajst-27738	175	44	lrcam	lrcam	NOUN
ajst-27738	175	45	improves	improve	VERB
ajst-27738	175	46	the	the	DET
ajst-27738	175	47	272	272	NUM
ajst-27738	175	48	miou	miou	NOUN
ajst-27738	175	49	from	from	ADP
ajst-27738	175	50	74.5	74.5	NUM
ajst-27738	175	51	%	%	NOUN
ajst-27738	175	52	to	to	PART
ajst-27738	175	53	75.7	75.7	NUM
ajst-27738	175	54	%	%	NOUN
ajst-27738	175	55	compared	compare	VERB
ajst-27738	175	56	to	to	ADP
ajst-27738	175	57	the	the	DET
ajst-27738	175	58	model	model	NOUN
ajst-27738	175	59	without	without	ADP
ajst-27738	175	60	the	the	DET
ajst-27738	175	61	lrcam	lrcam	NOUN
ajst-27738	175	62	at	at	ADP
ajst-27738	175	63	a	a	DET
ajst-27738	175	64	resolution	resolution	NOUN
ajst-27738	175	65	of	of	ADP
ajst-27738	175	66	512	512	NUM
ajst-27738	175	67	×	×	NOUN
ajst-27738	175	68	1024	1024	NUM
ajst-27738	175	69	.	.	PUNCT
ajst-27738	176	1	this	this	DET
ajst-27738	176	2	result	result	NOUN
ajst-27738	176	3	indicates	indicate	VERB
ajst-27738	176	4	that	that	SCONJ
ajst-27738	176	5	at	at	ADP
ajst-27738	176	6	lower	low	ADJ
ajst-27738	176	7	resolutions	resolution	NOUN
ajst-27738	176	8	,	,	PUNCT
ajst-27738	176	9	lrcam	lrcam	PROPN
ajst-27738	176	10	can	can	AUX
ajst-27738	176	11	effectively	effectively	ADV
ajst-27738	176	12	aggregate	aggregate	VERB
ajst-27738	176	13	contextual	contextual	ADJ
ajst-27738	176	14	information	information	NOUN
ajst-27738	176	15	,	,	PUNCT
ajst-27738	176	16	thus	thus	ADV
ajst-27738	176	17	improving	improve	VERB
ajst-27738	176	18	segmentation	segmentation	NOUN
ajst-27738	176	19	accuracy	accuracy	NOUN
ajst-27738	176	20	.	.	PUNCT
ajst-27738	177	1	at	at	ADP
ajst-27738	177	2	a	a	DET
ajst-27738	177	3	higher	high	ADJ
ajst-27738	177	4	resolution	resolution	NOUN
ajst-27738	177	5	of	of	ADP
ajst-27738	177	6	768×1536	768×1536	NUM
ajst-27738	177	7	,	,	PUNCT
ajst-27738	177	8	lrcam	lrcam	PROPN
ajst-27738	177	9	also	also	ADV
ajst-27738	177	10	demonstrates	demonstrate	VERB
ajst-27738	177	11	its	its	PRON
ajst-27738	177	12	advantages	advantage	NOUN
ajst-27738	177	13	,	,	PUNCT
ajst-27738	177	14	resulting	result	VERB
ajst-27738	177	15	in	in	ADP
ajst-27738	177	16	an	an	DET
ajst-27738	177	17	increase	increase	NOUN
ajst-27738	177	18	in	in	ADP
ajst-27738	177	19	miou	miou	NOUN
ajst-27738	177	20	from	from	ADP
ajst-27738	177	21	75.3	75.3	NUM
ajst-27738	177	22	%	%	NOUN
ajst-27738	177	23	to	to	ADP
ajst-27738	177	24	76.9	76.9	NUM
ajst-27738	177	25	%	%	NOUN
ajst-27738	177	26	.	.	PUNCT
ajst-27738	178	1	this	this	PRON
ajst-27738	178	2	further	far	ADV
ajst-27738	178	3	confirms	confirm	VERB
ajst-27738	178	4	the	the	DET
ajst-27738	178	5	effectiveness	effectiveness	NOUN
ajst-27738	178	6	of	of	ADP
ajst-27738	178	7	lrcam	lrcam	NOUN
ajst-27738	178	8	in	in	ADP
ajst-27738	178	9	capturing	capture	VERB
ajst-27738	178	10	richer	rich	ADJ
ajst-27738	178	11	contextual	contextual	ADJ
ajst-27738	178	12	information	information	NOUN
ajst-27738	178	13	.	.	PUNCT
ajst-27738	179	1	table	table	NOUN
ajst-27738	179	2	2(d	2(d	NUM
ajst-27738	179	3	)	)	PUNCT
ajst-27738	179	4	demonstrates	demonstrate	VERB
ajst-27738	179	5	the	the	DET
ajst-27738	179	6	experimental	experimental	ADJ
ajst-27738	179	7	results	result	NOUN
ajst-27738	179	8	of	of	ADP
ajst-27738	179	9	the	the	DET
ajst-27738	179	10	deformed	deform	VERB
ajst-27738	179	11	convolutional	convolutional	ADJ
ajst-27738	179	12	attention	attention	NOUN
ajst-27738	179	13	refinement	refinement	NOUN
ajst-27738	179	14	fusion	fusion	NOUN
ajst-27738	179	15	module	module	NOUN
ajst-27738	179	16	(	(	PUNCT
ajst-27738	179	17	dcarfm	dcarfm	NOUN
ajst-27738	179	18	)	)	PUNCT
ajst-27738	179	19	,	,	PUNCT
ajst-27738	179	20	from	from	ADP
ajst-27738	179	21	which	which	PRON
ajst-27738	179	22	it	it	PRON
ajst-27738	179	23	can	can	AUX
ajst-27738	179	24	be	be	AUX
ajst-27738	179	25	seen	see	VERB
ajst-27738	179	26	that	that	SCONJ
ajst-27738	179	27	the	the	DET
ajst-27738	179	28	introduction	introduction	NOUN
ajst-27738	179	29	of	of	ADP
ajst-27738	179	30	the	the	DET
ajst-27738	179	31	dcarfm	dcarfm	NOUN
ajst-27738	179	32	improves	improve	VERB
ajst-27738	179	33	the	the	DET
ajst-27738	179	34	miou	miou	NOUN
ajst-27738	179	35	of	of	ADP
ajst-27738	179	36	the	the	DET
ajst-27738	179	37	model	model	NOUN
ajst-27738	179	38	from	from	ADP
ajst-27738	179	39	74.4	74.4	NUM
ajst-27738	179	40	%	%	NOUN
ajst-27738	179	41	to	to	ADP
ajst-27738	179	42	75.7	75.7	NUM
ajst-27738	179	43	%	%	NOUN
ajst-27738	179	44	at	at	ADP
ajst-27738	179	45	512	512	NUM
ajst-27738	179	46	×	×	NOUN
ajst-27738	179	47	1024	1024	NUM
ajst-27738	179	48	resolution	resolution	NOUN
ajst-27738	179	49	.	.	PUNCT
ajst-27738	180	1	however	however	ADV
ajst-27738	180	2	,	,	PUNCT
ajst-27738	180	3	at	at	ADP
ajst-27738	180	4	768×1536	768×1536	NUM
ajst-27738	180	5	resolution	resolution	NOUN
ajst-27738	180	6	,	,	PUNCT
ajst-27738	180	7	the	the	DET
ajst-27738	180	8	model	model	NOUN
ajst-27738	180	9	with	with	ADP
ajst-27738	180	10	dcarfm	dcarfm	NOUN
ajst-27738	180	11	outperforms	outperform	VERB
ajst-27738	180	12	the	the	DET
ajst-27738	180	13	model	model	NOUN
ajst-27738	180	14	without	without	ADP
ajst-27738	180	15	dcarfm	dcarfm	NOUN
ajst-27738	180	16	by	by	ADP
ajst-27738	180	17	76.9	76.9	NUM
ajst-27738	180	18	%	%	NOUN
ajst-27738	180	19	miou	miou	NOUN
ajst-27738	180	20	.	.	PUNCT
ajst-27738	181	1	the	the	DET
ajst-27738	181	2	experimental	experimental	ADJ
ajst-27738	181	3	results	result	NOUN
ajst-27738	181	4	confirm	confirm	VERB
ajst-27738	181	5	the	the	DET
ajst-27738	181	6	effectiveness	effectiveness	NOUN
ajst-27738	181	7	of	of	ADP
ajst-27738	181	8	lrcam	lrcam	NOUN
ajst-27738	181	9	and	and	CCONJ
ajst-27738	181	10	dcarfm	dcarfm	NOUN
ajst-27738	181	11	in	in	ADP
ajst-27738	181	12	artrnet	artrnet	PROPN
ajst-27738	181	13	.	.	PUNCT
ajst-27738	182	1	table	table	NOUN
ajst-27738	182	2	2	2	NUM
ajst-27738	182	3	.	.	PUNCT
ajst-27738	182	4	comparison	comparison	NOUN
ajst-27738	182	5	of	of	ADP
ajst-27738	182	6	ablation	ablation	NOUN
ajst-27738	182	7	experiments	experiment	NOUN
ajst-27738	182	8	of	of	ADP
ajst-27738	182	9	lrcam	lrcam	NOUN
ajst-27738	182	10	and	and	CCONJ
ajst-27738	182	11	dcarfm	dcarfm	NOUN
ajst-27738	182	12	in	in	ADP
ajst-27738	182	13	artrnet	artrnet	NOUN
ajst-27738	182	14	on	on	ADP
ajst-27738	182	15	cityscapes	cityscape	NOUN
ajst-27738	182	16	validation	validation	NOUN
ajst-27738	182	17	set	set	NOUN
ajst-27738	182	18	.	.	PUNCT
ajst-27738	183	1	model	model	NOUN
ajst-27738	183	2	resolution	resolution	NOUN
ajst-27738	183	3	none	none	NOUN
ajst-27738	183	4	lrcam	lrcam	VERB
ajst-27738	183	5	none	none	NOUN
ajst-27738	183	6	dcarfm	dcarfm	NOUN
ajst-27738	183	7	miou	miou	NOUN
ajst-27738	183	8	(	(	PUNCT
ajst-27738	183	9	a	a	NOUN
ajst-27738	183	10	)	)	PUNCT
ajst-27738	183	11	lrcam	lrcam	NOUN
ajst-27738	183	12	artrnet	artrnet	NOUN
ajst-27738	183	13	512×1024	512×1024	NUM
ajst-27738	183	14	√	√	NUM
ajst-27738	183	15	√	√	ADP
ajst-27738	183	16	74.5	74.5	NUM
ajst-27738	183	17	artrnet	artrnet	NOUN
ajst-27738	183	18	512×1024	512×1024	NUM
ajst-27738	183	19	√	√	NUM
ajst-27738	183	20	√	√	ADP
ajst-27738	183	21	75.7	75.7	NUM
ajst-27738	183	22	artrnet	artrnet	NOUN
ajst-27738	183	23	768×1536	768×1536	NUM
ajst-27738	183	24	√	√	NOUN
ajst-27738	183	25	√	√	ADP
ajst-27738	183	26	75.3	75.3	NUM
ajst-27738	183	27	artrnet	artrnet	NOUN
ajst-27738	183	28	768×1536	768×1536	NUM
ajst-27738	183	29	√	√	NOUN
ajst-27738	183	30	√	√	ADP
ajst-27738	183	31	76.9	76.9	NUM
ajst-27738	183	32	(	(	PUNCT
ajst-27738	183	33	b	b	NOUN
ajst-27738	183	34	)	)	PUNCT
ajst-27738	183	35	dcarfm	dcarfm	NOUN
ajst-27738	183	36	artrnet	artrnet	NOUN
ajst-27738	183	37	512×1024	512×1024	NUM
ajst-27738	183	38	√	√	NUM
ajst-27738	183	39	√	√	ADP
ajst-27738	183	40	74.4	74.4	NUM
ajst-27738	183	41	artrnet	artrnet	NOUN
ajst-27738	183	42	512×1024	512×1024	NUM
ajst-27738	183	43	√	√	NUM
ajst-27738	183	44	√	√	ADP
ajst-27738	183	45	75.7	75.7	NUM
ajst-27738	183	46	artrnet	artrnet	NOUN
ajst-27738	183	47	768×1536	768×1536	NUM
ajst-27738	183	48	√	√	NOUN
ajst-27738	183	49	√	√	ADP
ajst-27738	183	50	75.4	75.4	NUM
ajst-27738	183	51	artrnet	artrnet	NOUN
ajst-27738	183	52	768×1536	768×1536	NUM
ajst-27738	183	53	√	√	NOUN
ajst-27738	183	54	√	√	ADP
ajst-27738	183	55	76.9	76.9	NUM
ajst-27738	183	56	4.3.2	4.3.2	NOUN
ajst-27738	183	57	.	.	PUNCT
ajst-27738	184	1	comparison	comparison	NOUN
ajst-27738	184	2	with	with	ADP
ajst-27738	184	3	sota	sota	ADJ
ajst-27738	184	4	methods	method	NOUN
ajst-27738	184	5	in	in	ADP
ajst-27738	184	6	this	this	DET
ajst-27738	184	7	subsection	subsection	NOUN
ajst-27738	184	8	,	,	PUNCT
ajst-27738	184	9	we	we	PRON
ajst-27738	184	10	present	present	VERB
ajst-27738	184	11	performance	performance	NOUN
ajst-27738	184	12	results	result	NOUN
ajst-27738	184	13	of	of	ADP
ajst-27738	184	14	artrnet	artrnet	NOUN
ajst-27738	184	15	on	on	ADP
ajst-27738	184	16	the	the	DET
ajst-27738	184	17	cityscapes	cityscape	NOUN
ajst-27738	184	18	and	and	CCONJ
ajst-27738	184	19	camvid	camvid	NOUN
ajst-27738	184	20	datasets	dataset	NOUN
ajst-27738	184	21	,	,	PUNCT
ajst-27738	184	22	followed	follow	VERB
ajst-27738	184	23	by	by	ADP
ajst-27738	184	24	comparisons	comparison	NOUN
ajst-27738	184	25	with	with	ADP
ajst-27738	184	26	other	other	ADJ
ajst-27738	184	27	state	state	NOUN
ajst-27738	184	28	-	-	PUNCT
ajst-27738	184	29	of	of	ADP
ajst-27738	184	30	-	-	PUNCT
ajst-27738	184	31	the	the	DET
ajst-27738	184	32	-	-	PUNCT
ajst-27738	184	33	art	art	NOUN
ajst-27738	184	34	real	real	ADJ
ajst-27738	184	35	-	-	PUNCT
ajst-27738	184	36	time	time	NOUN
ajst-27738	184	37	semantic	semantic	ADJ
ajst-27738	184	38	segmentation	segmentation	NOUN
ajst-27738	184	39	methods	method	NOUN
ajst-27738	184	40	to	to	PART
ajst-27738	184	41	validate	validate	VERB
ajst-27738	184	42	its	its	PRON
ajst-27738	184	43	effectiveness	effectiveness	NOUN
ajst-27738	184	44	.	.	PUNCT
ajst-27738	185	1	the	the	DET
ajst-27738	185	2	evaluation	evaluation	NOUN
ajst-27738	185	3	is	be	AUX
ajst-27738	185	4	conducted	conduct	VERB
ajst-27738	185	5	using	use	VERB
ajst-27738	185	6	a	a	DET
ajst-27738	185	7	resolution	resolution	NOUN
ajst-27738	185	8	of	of	ADP
ajst-27738	185	9	768×1536	768×1536	NUM
ajst-27738	185	10	for	for	ADP
ajst-27738	185	11	cityscapes	cityscape	NOUN
ajst-27738	185	12	and	and	CCONJ
ajst-27738	185	13	720	720	NUM
ajst-27738	185	14	×	×	NOUN
ajst-27738	185	15	960	960	NUM
ajst-27738	185	16	for	for	ADP
ajst-27738	185	17	camvid	camvid	NOUN
ajst-27738	185	18	.	.	PUNCT
ajst-27738	186	1	the	the	DET
ajst-27738	186	2	models	model	NOUN
ajst-27738	186	3	are	be	AUX
ajst-27738	186	4	assessed	assess	VERB
ajst-27738	186	5	based	base	VERB
ajst-27738	186	6	on	on	ADP
ajst-27738	186	7	four	four	NUM
ajst-27738	186	8	key	key	ADJ
ajst-27738	186	9	metrics	metric	NOUN
ajst-27738	186	10	:	:	PUNCT
ajst-27738	186	11	floating	float	VERB
ajst-27738	186	12	-	-	PUNCT
ajst-27738	186	13	point	point	NOUN
ajst-27738	186	14	operations	operation	NOUN
ajst-27738	186	15	per	per	ADP
ajst-27738	186	16	second	second	ADJ
ajst-27738	186	17	(	(	PUNCT
ajst-27738	186	18	flops	flop	NOUN
ajst-27738	186	19	)	)	PUNCT
ajst-27738	186	20	,	,	PUNCT
ajst-27738	186	21	number	number	NOUN
ajst-27738	186	22	of	of	ADP
ajst-27738	186	23	parameters	parameter	NOUN
ajst-27738	186	24	,	,	PUNCT
ajst-27738	186	25	mean	mean	ADJ
ajst-27738	186	26	intersection	intersection	NOUN
ajst-27738	186	27	over	over	ADP
ajst-27738	186	28	union	union	NOUN
ajst-27738	186	29	(	(	PUNCT
ajst-27738	186	30	miou	miou	NOUN
ajst-27738	186	31	)	)	PUNCT
ajst-27738	186	32	,	,	PUNCT
ajst-27738	186	33	and	and	CCONJ
ajst-27738	186	34	inference	inference	NOUN
ajst-27738	186	35	speed	speed	NOUN
ajst-27738	186	36	(	(	PUNCT
ajst-27738	186	37	fps	fps	PROPN
ajst-27738	186	38	)	)	PUNCT
ajst-27738	186	39	.	.	PUNCT
ajst-27738	187	1	a	a	DET
ajst-27738	187	2	comprehensive	comprehensive	ADJ
ajst-27738	187	3	analysis	analysis	NOUN
ajst-27738	187	4	of	of	ADP
ajst-27738	187	5	these	these	DET
ajst-27738	187	6	metrics	metric	NOUN
ajst-27738	187	7	is	be	AUX
ajst-27738	187	8	provided	provide	VERB
ajst-27738	187	9	below	below	ADP
ajst-27738	187	10	.	.	PUNCT
ajst-27738	188	1	table	table	NOUN
ajst-27738	188	2	3	3	NUM
ajst-27738	188	3	compares	compare	VERB
ajst-27738	188	4	artrnet	artrnet	NOUN
ajst-27738	188	5	with	with	ADP
ajst-27738	188	6	nine	nine	NUM
ajst-27738	188	7	other	other	ADJ
ajst-27738	188	8	models	model	NOUN
ajst-27738	188	9	on	on	ADP
ajst-27738	188	10	the	the	DET
ajst-27738	188	11	cityscapes	cityscape	NOUN
ajst-27738	188	12	dataset	dataset	VERB
ajst-27738	188	13	.	.	PUNCT
ajst-27738	189	1	special	special	ADJ
ajst-27738	189	2	attention	attention	NOUN
ajst-27738	189	3	is	be	AUX
ajst-27738	189	4	given	give	VERB
ajst-27738	189	5	to	to	ADP
ajst-27738	189	6	the	the	DET
ajst-27738	189	7	performance	performance	NOUN
ajst-27738	189	8	comparison	comparison	NOUN
ajst-27738	189	9	between	between	ADP
ajst-27738	189	10	artrnet	artrnet	NOUN
ajst-27738	189	11	and	and	CCONJ
ajst-27738	189	12	bisenetv2	bisenetv2	NOUN
ajst-27738	189	13	.	.	PUNCT
ajst-27738	190	1	bisenetv2	bisenetv2	PROPN
ajst-27738	190	2	,	,	PUNCT
ajst-27738	190	3	a	a	DET
ajst-27738	190	4	lightweight	lightweight	ADJ
ajst-27738	190	5	network	network	NOUN
ajst-27738	190	6	,	,	PUNCT
ajst-27738	190	7	is	be	AUX
ajst-27738	190	8	designed	design	VERB
ajst-27738	190	9	to	to	PART
ajst-27738	190	10	prioritize	prioritize	VERB
ajst-27738	190	11	fast	fast	ADJ
ajst-27738	190	12	inference	inference	NOUN
ajst-27738	190	13	speed	speed	NOUN
ajst-27738	190	14	without	without	ADP
ajst-27738	190	15	compromising	compromise	VERB
ajst-27738	190	16	on	on	ADP
ajst-27738	190	17	accuracy	accuracy	NOUN
ajst-27738	190	18	.	.	PUNCT
ajst-27738	191	1	without	without	ADP
ajst-27738	191	2	the	the	DET
ajst-27738	191	3	use	use	NOUN
ajst-27738	191	4	of	of	ADP
ajst-27738	191	5	a	a	DET
ajst-27738	191	6	pre	pre	ADJ
ajst-27738	191	7	-	-	ADJ
ajst-27738	191	8	trained	train	VERB
ajst-27738	191	9	backbone	backbone	NOUN
ajst-27738	191	10	network	network	NOUN
ajst-27738	191	11	,	,	PUNCT
ajst-27738	191	12	bisenetv2	bisenetv2	NOUN
ajst-27738	191	13	achieves	achieve	VERB
ajst-27738	191	14	73.4	73.4	NUM
ajst-27738	191	15	%	%	NOUN
ajst-27738	191	16	miou	miou	NOUN
ajst-27738	191	17	and	and	CCONJ
ajst-27738	191	18	156	156	NUM
ajst-27738	191	19	fps	fps	NOUN
ajst-27738	191	20	at	at	ADP
ajst-27738	191	21	512×1024	512×1024	NUM
ajst-27738	191	22	resolution	resolution	NOUN
ajst-27738	191	23	without	without	ADP
ajst-27738	191	24	using	use	VERB
ajst-27738	191	25	accelerated	accelerate	VERB
ajst-27738	191	26	processing	processing	NOUN
ajst-27738	191	27	,	,	PUNCT
ajst-27738	191	28	which	which	PRON
ajst-27738	191	29	shows	show	VERB
ajst-27738	191	30	that	that	SCONJ
ajst-27738	191	31	it	it	PRON
ajst-27738	191	32	is	be	AUX
ajst-27738	191	33	competitive	competitive	ADJ
ajst-27738	191	34	in	in	ADP
ajst-27738	191	35	real	real	ADJ
ajst-27738	191	36	-	-	PUNCT
ajst-27738	191	37	time	time	NOUN
ajst-27738	191	38	applications	application	NOUN
ajst-27738	191	39	.	.	PUNCT
ajst-27738	192	1	in	in	ADP
ajst-27738	192	2	comparison	comparison	NOUN
ajst-27738	192	3	,	,	PUNCT
ajst-27738	192	4	artrnet	artrnet	PROPN
ajst-27738	192	5	achieved	achieve	VERB
ajst-27738	192	6	76.9	76.9	NUM
ajst-27738	192	7	%	%	NOUN
ajst-27738	192	8	miou	miou	NOUN
ajst-27738	192	9	and	and	CCONJ
ajst-27738	192	10	96	96	NUM
ajst-27738	192	11	fps	fps	NOUN
ajst-27738	192	12	at	at	ADP
ajst-27738	192	13	a	a	DET
ajst-27738	192	14	higher	high	ADJ
ajst-27738	192	15	resolution	resolution	NOUN
ajst-27738	192	16	of	of	ADP
ajst-27738	192	17	768×1536	768×1536	NUM
ajst-27738	192	18	.	.	PUNCT
ajst-27738	193	1	this	this	DET
ajst-27738	193	2	result	result	NOUN
ajst-27738	193	3	suggests	suggest	VERB
ajst-27738	193	4	that	that	SCONJ
ajst-27738	193	5	artrnet	artrnet	NOUN
ajst-27738	193	6	has	have	AUX
ajst-27738	193	7	improved	improve	VERB
ajst-27738	193	8	in	in	ADP
ajst-27738	193	9	accuracy	accuracy	NOUN
ajst-27738	193	10	despite	despite	SCONJ
ajst-27738	193	11	being	be	AUX
ajst-27738	193	12	slightly	slightly	ADV
ajst-27738	193	13	slower	slow	ADJ
ajst-27738	193	14	than	than	ADP
ajst-27738	193	15	bisenetv2	bisenetv2	PROPN
ajst-27738	193	16	.	.	PUNCT
ajst-27738	194	1	this	this	DET
ajst-27738	194	2	enhancement	enhancement	NOUN
ajst-27738	194	3	may	may	AUX
ajst-27738	194	4	be	be	AUX
ajst-27738	194	5	attributed	attribute	VERB
ajst-27738	194	6	to	to	ADP
ajst-27738	194	7	the	the	DET
ajst-27738	194	8	specific	specific	ADJ
ajst-27738	194	9	structure	structure	NOUN
ajst-27738	194	10	and	and	CCONJ
ajst-27738	194	11	optimisation	optimisation	NOUN
ajst-27738	194	12	strategies	strategy	NOUN
ajst-27738	194	13	that	that	PRON
ajst-27738	194	14	artrnet	artrnet	VERB
ajst-27738	194	15	employs	employ	VERB
ajst-27738	194	16	in	in	ADP
ajst-27738	194	17	its	its	PRON
ajst-27738	194	18	network	network	NOUN
ajst-27738	194	19	design	design	NOUN
ajst-27738	194	20	,	,	PUNCT
ajst-27738	194	21	which	which	PRON
ajst-27738	194	22	help	help	VERB
ajst-27738	194	23	to	to	PART
ajst-27738	194	24	capture	capture	VERB
ajst-27738	194	25	finer	fine	ADJ
ajst-27738	194	26	image	image	NOUN
ajst-27738	194	27	details	detail	NOUN
ajst-27738	194	28	and	and	CCONJ
ajst-27738	194	29	thus	thus	ADV
ajst-27738	194	30	improve	improve	VERB
ajst-27738	194	31	the	the	DET
ajst-27738	194	32	accuracy	accuracy	NOUN
ajst-27738	194	33	of	of	ADP
ajst-27738	194	34	segmentation	segmentation	NOUN
ajst-27738	194	35	.	.	PUNCT
ajst-27738	195	1	table	table	NOUN
ajst-27738	195	2	3	3	NUM
ajst-27738	195	3	shows	show	VERB
ajst-27738	195	4	that	that	SCONJ
ajst-27738	195	5	most	most	ADJ
ajst-27738	195	6	of	of	ADP
ajst-27738	195	7	the	the	DET
ajst-27738	195	8	models	model	NOUN
ajst-27738	195	9	are	be	AUX
ajst-27738	195	10	pre	pre	ADJ
ajst-27738	195	11	-	-	VERB
ajst-27738	195	12	trained	train	VERB
ajst-27738	195	13	on	on	ADP
ajst-27738	195	14	imagenet	imagenet	NOUN
ajst-27738	195	15	,	,	PUNCT
ajst-27738	195	16	which	which	PRON
ajst-27738	195	17	is	be	AUX
ajst-27738	195	18	a	a	DET
ajst-27738	195	19	time	time	NOUN
ajst-27738	195	20	-	-	PUNCT
ajst-27738	195	21	consuming	consume	VERB
ajst-27738	195	22	process	process	NOUN
ajst-27738	195	23	but	but	CCONJ
ajst-27738	195	24	can	can	AUX
ajst-27738	195	25	be	be	AUX
ajst-27738	195	26	traded	trade	VERB
ajst-27738	195	27	off	off	ADP
ajst-27738	195	28	for	for	ADP
ajst-27738	195	29	a	a	DET
ajst-27738	195	30	relatively	relatively	ADV
ajst-27738	195	31	high	high	ADJ
ajst-27738	195	32	segmentation	segmentation	NOUN
ajst-27738	195	33	accuracy	accuracy	NOUN
ajst-27738	195	34	.	.	PUNCT
ajst-27738	196	1	in	in	ADP
ajst-27738	196	2	contrast	contrast	NOUN
ajst-27738	196	3	,	,	PUNCT
ajst-27738	196	4	the	the	DET
ajst-27738	196	5	training	training	NOUN
ajst-27738	196	6	of	of	ADP
ajst-27738	196	7	the	the	DET
ajst-27738	196	8	models	model	NOUN
ajst-27738	196	9	in	in	ADP
ajst-27738	196	10	this	this	DET
ajst-27738	196	11	chapter	chapter	NOUN
ajst-27738	196	12	chooses	choose	VERB
ajst-27738	196	13	to	to	PART
ajst-27738	196	14	start	start	VERB
ajst-27738	196	15	from	from	ADP
ajst-27738	196	16	zero	zero	NUM
ajst-27738	196	17	.	.	PUNCT
ajst-27738	197	1	in	in	ADP
ajst-27738	197	2	addition	addition	NOUN
ajst-27738	197	3	,	,	PUNCT
ajst-27738	197	4	due	due	ADP
ajst-27738	197	5	to	to	ADP
ajst-27738	197	6	the	the	DET
ajst-27738	197	7	limitation	limitation	NOUN
ajst-27738	197	8	of	of	ADP
ajst-27738	197	9	gpu	gpu	NOUN
ajst-27738	197	10	memory	memory	NOUN
ajst-27738	197	11	,	,	PUNCT
ajst-27738	197	12	in	in	ADP
ajst-27738	197	13	order	order	NOUN
ajst-27738	197	14	to	to	PART
ajst-27738	197	15	be	be	AUX
ajst-27738	197	16	able	able	ADJ
ajst-27738	197	17	to	to	PART
ajst-27738	197	18	make	make	VERB
ajst-27738	197	19	the	the	DET
ajst-27738	197	20	training	training	NOUN
ajst-27738	197	21	gradient	gradient	NOUN
ajst-27738	197	22	more	more	ADV
ajst-27738	197	23	accurate	accurate	ADJ
ajst-27738	197	24	,	,	PUNCT
ajst-27738	197	25	the	the	DET
ajst-27738	197	26	artrnet	artrnet	NOUN
ajst-27738	197	27	model	model	NOUN
ajst-27738	197	28	in	in	ADP
ajst-27738	197	29	this	this	DET
ajst-27738	197	30	section	section	NOUN
ajst-27738	197	31	is	be	AUX
ajst-27738	197	32	loaded	load	VERB
ajst-27738	197	33	with	with	ADP
ajst-27738	197	34	the	the	DET
ajst-27738	197	35	pre	pre	NOUN
ajst-27738	197	36	-	-	NOUN
ajst-27738	197	37	training	training	ADJ
ajst-27738	197	38	weights	weight	NOUN
ajst-27738	197	39	of	of	ADP
ajst-27738	197	40	artrnet	artrnet	NOUN
ajst-27738	197	41	with	with	ADP
ajst-27738	197	42	a	a	DET
ajst-27738	197	43	resolution	resolution	NOUN
ajst-27738	197	44	of	of	ADP
ajst-27738	197	45	512×1024	512×1024	NUM
ajst-27738	197	46	size	size	NOUN
ajst-27738	197	47	on	on	ADP
ajst-27738	197	48	top	top	NOUN
ajst-27738	197	49	of	of	ADP
ajst-27738	197	50	the	the	DET
ajst-27738	197	51	resolution	resolution	NOUN
ajst-27738	197	52	of	of	ADP
ajst-27738	197	53	768×1536	768×1536	NUM
ajst-27738	197	54	size	size	NOUN
ajst-27738	197	55	.	.	PUNCT
ajst-27738	198	1	as	as	SCONJ
ajst-27738	198	2	can	can	AUX
ajst-27738	198	3	be	be	AUX
ajst-27738	198	4	seen	see	VERB
ajst-27738	198	5	from	from	ADP
ajst-27738	198	6	table	table	NOUN
ajst-27738	198	7	3	3	NUM
ajst-27738	198	8	,	,	PUNCT
ajst-27738	198	9	the	the	DET
ajst-27738	198	10	artrnet	artrnet	NOUN
ajst-27738	198	11	in	in	ADP
ajst-27738	198	12	this	this	DET
ajst-27738	198	13	section	section	NOUN
ajst-27738	198	14	achieves	achieve	VERB
ajst-27738	198	15	a	a	DET
ajst-27738	198	16	balance	balance	NOUN
ajst-27738	198	17	between	between	ADP
ajst-27738	198	18	accuracy	accuracy	NOUN
ajst-27738	198	19	and	and	CCONJ
ajst-27738	198	20	speed	speed	NOUN
ajst-27738	198	21	.	.	PUNCT
ajst-27738	199	1	in	in	ADP
ajst-27738	199	2	terms	term	NOUN
ajst-27738	199	3	of	of	ADP
ajst-27738	199	4	miou	miou	NOUN
ajst-27738	199	5	,	,	PUNCT
ajst-27738	199	6	the	the	DET
ajst-27738	199	7	method	method	NOUN
ajst-27738	199	8	in	in	ADP
ajst-27738	199	9	this	this	DET
ajst-27738	199	10	section	section	NOUN
ajst-27738	199	11	is	be	AUX
ajst-27738	199	12	significantly	significantly	ADV
ajst-27738	199	13	better	well	ADJ
ajst-27738	199	14	than	than	ADP
ajst-27738	199	15	other	other	ADJ
ajst-27738	199	16	more	more	ADV
ajst-27738	199	17	advanced	advanced	ADJ
ajst-27738	199	18	methods	method	NOUN
ajst-27738	199	19	such	such	ADJ
ajst-27738	199	20	as	as	ADP
ajst-27738	199	21	bisenetv2[18	bisenetv2[18	PROPN
ajst-27738	199	22	]	]	PUNCT
ajst-27738	199	23	.	.	PUNCT
ajst-27738	200	1	in	in	ADP
ajst-27738	200	2	table	table	NOUN
ajst-27738	200	3	3	3	NUM
ajst-27738	200	4	,	,	PUNCT
ajst-27738	200	5	this	this	DET
ajst-27738	200	6	paper	paper	NOUN
ajst-27738	200	7	uses	use	VERB
ajst-27738	200	8	no	no	INTJ
ajst-27738	200	9	to	to	PART
ajst-27738	200	10	denote	denote	VERB
ajst-27738	200	11	that	that	SCONJ
ajst-27738	200	12	the	the	DET
ajst-27738	200	13	method	method	NOUN
ajst-27738	200	14	has	have	VERB
ajst-27738	200	15	no	no	DET
ajst-27738	200	16	backbone	backbone	NOUN
ajst-27738	200	17	.	.	PUNCT
ajst-27738	201	1	backbone	backbone	NOUN
ajst-27738	201	2	denotes	denote	NOUN
ajst-27738	201	3	in	in	ADP
ajst-27738	201	4	the	the	DET
ajst-27738	201	5	backbone	backbone	NOUN
ajst-27738	201	6	model	model	NOUN
ajst-27738	201	7	.	.	PUNCT
ajst-27738	202	1	"	"	PUNCT
ajst-27738	202	2	*	*	PUNCT
ajst-27738	202	3	"	"	PUNCT
ajst-27738	202	4	indicates	indicate	VERB
ajst-27738	202	5	that	that	SCONJ
ajst-27738	202	6	the	the	DET
ajst-27738	202	7	inference	inference	NOUN
ajst-27738	202	8	speed	speed	NOUN
ajst-27738	202	9	,	,	PUNCT
ajst-27738	202	10	gflops	gflop	NOUN
ajst-27738	202	11	and	and	CCONJ
ajst-27738	202	12	parameters	parameter	NOUN
ajst-27738	202	13	of	of	ADP
ajst-27738	202	14	the	the	DET
ajst-27738	202	15	model	model	NOUN
ajst-27738	202	16	are	be	AUX
ajst-27738	202	17	tested	test	VERB
ajst-27738	202	18	and	and	CCONJ
ajst-27738	202	19	provided	provide	VERB
ajst-27738	202	20	on	on	ADP
ajst-27738	202	21	the	the	DET
ajst-27738	202	22	platform	platform	NOUN
ajst-27738	202	23	in	in	ADP
ajst-27738	202	24	this	this	DET
ajst-27738	202	25	section	section	NOUN
ajst-27738	202	26	.	.	PUNCT
ajst-27738	203	1	if	if	SCONJ
ajst-27738	203	2	"	"	PUNCT
ajst-27738	203	3	ɨ	ɨ	X
ajst-27738	203	4	"	"	PUNCT
ajst-27738	203	5	the	the	DET
ajst-27738	203	6	method	method	NOUN
ajst-27738	203	7	is	be	AUX
ajst-27738	203	8	labelled	label	VERB
ajst-27738	203	9	with	with	ADP
ajst-27738	203	10	,	,	PUNCT
ajst-27738	203	11	the	the	DET
ajst-27738	203	12	accelerated	accelerated	ADJ
ajst-27738	203	13	processing	processing	NOUN
ajst-27738	203	14	is	be	AUX
ajst-27738	203	15	performed	perform	VERB
ajst-27738	203	16	using	use	VERB
ajst-27738	203	17	tensorrt	tensorrt	NOUN
ajst-27738	203	18	.	.	PUNCT
ajst-27738	204	1	"	"	PUNCT
ajst-27738	204	2	-	-	PUNCT
ajst-27738	204	3	"	"	PUNCT
ajst-27738	204	4	indicates	indicate	VERB
ajst-27738	204	5	that	that	SCONJ
ajst-27738	204	6	the	the	DET
ajst-27738	204	7	methods	method	NOUN
ajst-27738	204	8	do	do	AUX
ajst-27738	204	9	not	not	PART
ajst-27738	204	10	report	report	VERB
ajst-27738	204	11	the	the	DET
ajst-27738	204	12	corresponding	corresponding	ADJ
ajst-27738	204	13	results	result	NOUN
ajst-27738	204	14	.	.	PUNCT
ajst-27738	205	1	table	table	NOUN
ajst-27738	205	2	3	3	NUM
ajst-27738	205	3	.	.	PUNCT
ajst-27738	205	4	comparison	comparison	NOUN
ajst-27738	205	5	with	with	ADP
ajst-27738	205	6	other	other	ADJ
ajst-27738	205	7	methods	method	NOUN
ajst-27738	205	8	on	on	ADP
ajst-27738	205	9	the	the	DET
ajst-27738	205	10	cityscapes	cityscape	NOUN
ajst-27738	205	11	dataset	dataset	VERB
ajst-27738	205	12	.	.	PUNCT
ajst-27738	206	1	model	model	NOUN
ajst-27738	206	2	backbone	backbone	NOUN
ajst-27738	206	3	resolution	resolution	NOUN
ajst-27738	206	4	gflops	gflop	NOUN
ajst-27738	206	5	params	param	VERB
ajst-27738	206	6	miou	miou	PROPN
ajst-27738	206	7	fps	fps	PROPN
ajst-27738	206	8	dfanet[27	dfanet[27	PROPN
ajst-27738	206	9	]	]	PUNCT
ajst-27738	206	10	43	43	NUM
ajst-27738	206	11	-	-	PUNCT
ajst-27738	206	12	layer	layer	NOUN
ajst-27738	206	13	cnn	cnn	PROPN
ajst-27738	206	14	1024×1024	1024×1024	NUM
ajst-27738	206	15	3.4	3.4	NUM
ajst-27738	206	16	7.8	7.8	NUM
ajst-27738	206	17	m	m	NOUN
ajst-27738	206	18	71.3	71.3	NUM
ajst-27738	206	19	100	100	NUM
ajst-27738	206	20	swiftnet[37	swiftnet[37	NOUN
ajst-27738	206	21	]	]	PUNCT
ajst-27738	206	22	resnet18	resnet18	NOUN
ajst-27738	206	23	1024×2048	1024×2048	NUM
ajst-27738	206	24	104.0	104.0	NUM
ajst-27738	206	25	11.8	11.8	NUM
ajst-27738	206	26	m	m	NOUN
ajst-27738	206	27	75.5	75.5	NUM
ajst-27738	206	28	39.9	39.9	NUM
ajst-27738	206	29	lrnnet[38	lrnnet[38	NOUN
ajst-27738	206	30	]	]	PUNCT
ajst-27738	206	31	55	55	NUM
ajst-27738	206	32	-	-	PUNCT
ajst-27738	206	33	layer	layer	NOUN
ajst-27738	206	34	cnn	cnn	NOUN
ajst-27738	206	35	512×1024	512×1024	NUM
ajst-27738	206	36	8.58	8.58	NUM
ajst-27738	206	37	0.68	0.68	NUM
ajst-27738	206	38	m	m	NOUN
ajst-27738	206	39	72.2	72.2	NUM
ajst-27738	206	40	71	71	NUM
ajst-27738	206	41	rthp[39	rthp[39	NOUN
ajst-27738	206	42	]	]	X
ajst-27738	206	43	mobilenetv2	mobilenetv2	NOUN
ajst-27738	206	44	448×896	448×896	NUM
ajst-27738	207	1	49.5	49.5	NUM
ajst-27738	207	2	6.2	6.2	NUM
ajst-27738	207	3	m	m	NUM
ajst-27738	207	4	73.6	73.6	NUM
ajst-27738	207	5	51	51	NUM
ajst-27738	207	6	pp	pp	ADJ
ajst-27738	207	7	-	-	PUNCT
ajst-27738	207	8	liteseg	liteseg	NOUN
ajst-27738	207	9	-	-	PUNCT
ajst-27738	207	10	t1[40	t1[40	NOUN
ajst-27738	207	11	]	]	PUNCT
ajst-27738	207	12	stdc1	stdc1	X
ajst-27738	208	1	512×1024	512×1024	NUM
ajst-27738	208	2	73.1	73.1	NUM
ajst-27738	208	3	273.6	273.6	NUM
ajst-27738	208	4	pp	pp	ADJ
ajst-27738	208	5	-	-	PUNCT
ajst-27738	208	6	liteseg	liteseg	NOUN
ajst-27738	208	7	-	-	PUNCT
ajst-27738	208	8	t2[40	t2[40	NOUN
ajst-27738	208	9	]	]	PUNCT
ajst-27738	208	10	stdc1	stdc1	X
ajst-27738	209	1	768×1536	768×1536	NUM
ajst-27738	209	2	76.0	76.0	NUM
ajst-27738	209	3	143.6	143.6	NUM
ajst-27738	209	4	bisenetv1[17	bisenetv1[17	PROPN
ajst-27738	209	5	]	]	PUNCT
ajst-27738	209	6	xception	xception	NOUN
ajst-27738	209	7	39	39	NUM
ajst-27738	209	8	768×1536	768×1536	NUM
ajst-27738	209	9	14.8	14.8	NUM
ajst-27738	209	10	5.8	5.8	NUM
ajst-27738	209	11	m	m	PROPN
ajst-27738	209	12	69.0	69.0	NUM
ajst-27738	209	13	105.8	105.8	NUM
ajst-27738	209	14	bisenetv1[17	bisenetv1[17	PROPN
ajst-27738	209	15	]	]	PUNCT
ajst-27738	209	16	resnet18	resnet18	NOUN
ajst-27738	209	17	768×1536	768×1536	NUM
ajst-27738	209	18	55.3	55.3	NUM
ajst-27738	209	19	49	49	NUM
ajst-27738	209	20	m	m	NOUN
ajst-27738	209	21	74.8	74.8	NUM
ajst-27738	209	22	65.5	65.5	NUM
ajst-27738	209	23	stdc1	stdc1	NOUN
ajst-27738	209	24	-	-	PUNCT
ajst-27738	209	25	seg50*†[36	seg50*†[36	NOUN
ajst-27738	209	26	]	]	PUNCT
ajst-27738	209	27	stdc1	stdc1	X
ajst-27738	209	28	512×1024	512×1024	NUM
ajst-27738	209	29	24.8	24.8	NUM
ajst-27738	209	30	8.3	8.3	NUM
ajst-27738	209	31	m	m	NUM
ajst-27738	209	32	72.2	72.2	NUM
ajst-27738	209	33	206.9	206.9	NUM
ajst-27738	209	34	stdc2	stdc2	PROPN
ajst-27738	209	35	-	-	PUNCT
ajst-27738	209	36	seg50*†[36	seg50*†[36	NOUN
ajst-27738	209	37	]	]	PUNCT
ajst-27738	209	38	stdc2	stdc2	NOUN
ajst-27738	210	1	512×1024	512×1024	NUM
ajst-27738	210	2	38.0	38.0	NUM
ajst-27738	210	3	12.3	12.3	NUM
ajst-27738	210	4	m	m	NOUN
ajst-27738	210	5	74.2	74.2	NUM
ajst-27738	210	6	156.6	156.6	NUM
ajst-27738	210	7	stdc1	stdc1	NOUN
ajst-27738	210	8	-	-	PUNCT
ajst-27738	210	9	seg75*†[36	seg75*†[36	X
ajst-27738	210	10	]	]	PUNCT
ajst-27738	210	11	stdc1	stdc1	VERB
ajst-27738	211	1	768×1536	768×1536	NUM
ajst-27738	211	2	55.9	55.9	NUM
ajst-27738	211	3	8.3	8.3	NUM
ajst-27738	211	4	m	m	NUM
ajst-27738	211	5	74.5	74.5	NUM
ajst-27738	211	6	140.7	140.7	NUM
ajst-27738	211	7	stdc2	stdc2	NOUN
ajst-27738	211	8	-	-	PUNCT
ajst-27738	211	9	seg75*†[36	seg75*†[36	PROPN
ajst-27738	211	10	]	]	PUNCT
ajst-27738	211	11	stdc2	stdc2	NOUN
ajst-27738	212	1	768×1536	768×1536	NUM
ajst-27738	212	2	85.6	85.6	NUM
ajst-27738	212	3	12.3	12.3	NUM
ajst-27738	212	4	m	m	NOUN
ajst-27738	212	5	77.0	77.0	NUM
ajst-27738	212	6	106.2	106.2	NUM
ajst-27738	212	7	bisenetv2†[18	bisenetv2†[18	NOUN
ajst-27738	212	8	]	]	X
ajst-27738	212	9	no	no	DET
ajst-27738	212	10	512×1024	512×1024	NUM
ajst-27738	212	11	21.1	21.1	NUM
ajst-27738	212	12	73.4	73.4	NUM
ajst-27738	212	13	156	156	NUM
ajst-27738	212	14	bisenetv2	bisenetv2	NOUN
ajst-27738	212	15	-	-	PUNCT
ajst-27738	212	16	l†[18	l†[18	NOUN
ajst-27738	212	17	]	]	PUNCT
ajst-27738	212	18	no	no	DET
ajst-27738	212	19	512×1024	512×1024	NUM
ajst-27738	212	20	118.5	118.5	NUM
ajst-27738	212	21	75.8	75.8	NUM
ajst-27738	212	22	47.3	47.3	NUM
ajst-27738	212	23	artrnet	artrnet	NOUN
ajst-27738	212	24	no	no	DET
ajst-27738	212	25	512×1024	512×1024	NUM
ajst-27738	212	26	19	19	NUM
ajst-27738	212	27	6.6	6.6	NUM
ajst-27738	212	28	m	m	NOUN
ajst-27738	212	29	75.7	75.7	NUM
ajst-27738	212	30	132	132	NUM
ajst-27738	212	31	artrnet	artrnet	NOUN
ajst-27738	212	32	no	no	DET
ajst-27738	212	33	768×1536	768×1536	NUM
ajst-27738	212	34	38.6	38.6	NUM
ajst-27738	212	35	6.6	6.6	NUM
ajst-27738	212	36	m	m	NUM
ajst-27738	212	37	76.9	76.9	NUM
ajst-27738	212	38	96	96	NUM
ajst-27738	212	39	273	273	NUM
ajst-27738	212	40	4.3.3	4.3.3	NUM
ajst-27738	212	41	.	.	PUNCT
ajst-27738	213	1	experiments	experiment	NOUN
ajst-27738	213	2	on	on	ADP
ajst-27738	213	3	camvid	camvid	NOUN
ajst-27738	213	4	to	to	PART
ajst-27738	213	5	further	far	ADV
ajst-27738	213	6	validate	validate	VERB
ajst-27738	213	7	the	the	DET
ajst-27738	213	8	generalization	generalization	NOUN
ajst-27738	213	9	of	of	ADP
ajst-27738	213	10	artrnet	artrnet	NOUN
ajst-27738	213	11	,	,	PUNCT
ajst-27738	213	12	experiments	experiment	NOUN
ajst-27738	213	13	were	be	AUX
ajst-27738	213	14	also	also	ADV
ajst-27738	213	15	conducted	conduct	VERB
ajst-27738	213	16	on	on	ADP
ajst-27738	213	17	the	the	DET
ajst-27738	213	18	camvid	camvid	NOUN
ajst-27738	213	19	dataset	dataset	VERB
ajst-27738	213	20	with	with	ADP
ajst-27738	213	21	an	an	DET
ajst-27738	213	22	input	input	NOUN
ajst-27738	213	23	resolution	resolution	NOUN
ajst-27738	213	24	of	of	ADP
ajst-27738	213	25	720×960	720×960	NUM
ajst-27738	213	26	using	use	VERB
ajst-27738	213	27	the	the	DET
ajst-27738	213	28	same	same	ADJ
ajst-27738	213	29	configuration	configuration	NOUN
ajst-27738	213	30	.	.	PUNCT
ajst-27738	214	1	the	the	DET
ajst-27738	214	2	specific	specific	ADJ
ajst-27738	214	3	results	result	NOUN
ajst-27738	214	4	are	be	AUX
ajst-27738	214	5	detailed	detail	VERB
ajst-27738	214	6	in	in	ADP
ajst-27738	214	7	table	table	NOUN
ajst-27738	214	8	4	4	NUM
ajst-27738	214	9	.	.	PUNCT
ajst-27738	215	1	artrnet	artrnet	NOUN
ajst-27738	215	2	performs	perform	VERB
ajst-27738	215	3	the	the	DET
ajst-27738	215	4	best	good	ADJ
ajst-27738	215	5	,	,	PUNCT
ajst-27738	215	6	achieving	achieve	VERB
ajst-27738	215	7	76.5	76.5	NUM
ajst-27738	215	8	%	%	NOUN
ajst-27738	215	9	miou	miou	NOUN
ajst-27738	215	10	and	and	CCONJ
ajst-27738	215	11	110.4	110.4	NUM
ajst-27738	215	12	fps	fps	PROPN
ajst-27738	215	13	,	,	PUNCT
ajst-27738	215	14	which	which	PRON
ajst-27738	215	15	is	be	AUX
ajst-27738	215	16	higher	high	ADJ
ajst-27738	215	17	than	than	ADP
ajst-27738	215	18	that	that	PRON
ajst-27738	215	19	of	of	ADP
ajst-27738	215	20	stdc2	stdc2	PROPN
ajst-27738	215	21	-	-	PUNCT
ajst-27738	215	22	seg[36	seg[36	PROPN
ajst-27738	215	23	]	]	PUNCT
ajst-27738	215	24	but	but	CCONJ
ajst-27738	215	25	slightly	slightly	ADV
ajst-27738	215	26	lower	low	ADJ
ajst-27738	215	27	than	than	ADP
ajst-27738	215	28	that	that	PRON
ajst-27738	215	29	of	of	ADP
ajst-27738	215	30	the	the	DET
ajst-27738	215	31	accelerated	accelerated	ADJ
ajst-27738	215	32	bisenetv2[18	bisenetv2[18	PROPN
ajst-27738	215	33	]	]	PUNCT
ajst-27738	215	34	.	.	PUNCT
ajst-27738	216	1	meanwhile	meanwhile	ADV
ajst-27738	216	2	,	,	PUNCT
ajst-27738	216	3	artrnet	artrnet	PROPN
ajst-27738	216	4	achieves	achieve	VERB
ajst-27738	216	5	a	a	DET
ajst-27738	216	6	good	good	ADJ
ajst-27738	216	7	balance	balance	NOUN
ajst-27738	216	8	of	of	ADP
ajst-27738	216	9	speed	speed	NOUN
ajst-27738	216	10	and	and	CCONJ
ajst-27738	216	11	accuracy	accuracy	NOUN
ajst-27738	216	12	,	,	PUNCT
ajst-27738	216	13	which	which	PRON
ajst-27738	216	14	further	far	ADV
ajst-27738	216	15	proves	prove	VERB
ajst-27738	216	16	the	the	DET
ajst-27738	216	17	superior	superior	ADJ
ajst-27738	216	18	performance	performance	NOUN
ajst-27738	216	19	of	of	ADP
ajst-27738	216	20	the	the	DET
ajst-27738	216	21	method	method	NOUN
ajst-27738	216	22	.	.	PUNCT
ajst-27738	217	1	in	in	ADP
ajst-27738	217	2	table	table	NOUN
ajst-27738	217	3	4	4	NUM
ajst-27738	217	4	,	,	PUNCT
ajst-27738	217	5	this	this	DET
ajst-27738	217	6	section	section	NOUN
ajst-27738	217	7	uses	use	VERB
ajst-27738	217	8	"	"	PUNCT
ajst-27738	217	9	*	*	PUNCT
ajst-27738	217	10	"	"	PUNCT
ajst-27738	217	11	to	to	PART
ajst-27738	217	12	denote	denote	VERB
ajst-27738	217	13	the	the	DET
ajst-27738	217	14	pre	pre	NOUN
ajst-27738	217	15	-	-	NOUN
ajst-27738	217	16	training	training	NOUN
ajst-27738	217	17	of	of	ADP
ajst-27738	217	18	the	the	DET
ajst-27738	217	19	model	model	NOUN
ajst-27738	217	20	loaded	load	VERB
ajst-27738	217	21	with	with	ADP
ajst-27738	217	22	artrnet	artrnet	NOUN
ajst-27738	217	23	under	under	ADP
ajst-27738	217	24	3/4	3/4	NUM
ajst-27738	217	25	graph	graph	NOUN
ajst-27738	217	26	.	.	PUNCT
ajst-27738	218	1	if	if	SCONJ
ajst-27738	218	2	the	the	DET
ajst-27738	218	3	method	method	NOUN
ajst-27738	218	4	is	be	AUX
ajst-27738	218	5	labelled	label	VERB
ajst-27738	218	6	with	with	ADP
ajst-27738	218	7	"	"	PUNCT
ajst-27738	218	8	ɨ	ɨ	NOUN
ajst-27738	218	9	"	"	PUNCT
ajst-27738	218	10	,	,	PUNCT
ajst-27738	218	11	the	the	DET
ajst-27738	218	12	accelerated	accelerated	ADJ
ajst-27738	218	13	processing	processing	NOUN
ajst-27738	218	14	was	be	AUX
ajst-27738	218	15	performed	perform	VERB
ajst-27738	218	16	using	use	VERB
ajst-27738	218	17	tensorrt	tensorrt	NOUN
ajst-27738	218	18	.	.	PUNCT
ajst-27738	219	1	table	table	NOUN
ajst-27738	219	2	4	4	NUM
ajst-27738	219	3	.	.	PUNCT
ajst-27738	219	4	comparison	comparison	NOUN
ajst-27738	219	5	with	with	ADP
ajst-27738	219	6	other	other	ADJ
ajst-27738	219	7	methods	method	NOUN
ajst-27738	219	8	on	on	ADP
ajst-27738	219	9	the	the	DET
ajst-27738	219	10	camvid	camvid	NOUN
ajst-27738	219	11	dataset	dataset	PROPN
ajst-27738	219	12	.	.	PUNCT
ajst-27738	220	1	model	model	PROPN
ajst-27738	220	2	backbone	backbone	PROPN
ajst-27738	220	3	gpu	gpu	PROPN
ajst-27738	220	4	miou	miou	NOUN
ajst-27738	220	5	fps	fps	PROPN
ajst-27738	220	6	enet[41	enet[41	X
ajst-27738	220	7	]	]	X
ajst-27738	220	8	43	43	NUM
ajst-27738	220	9	-	-	PUNCT
ajst-27738	220	10	layer	layer	NOUN
ajst-27738	220	11	cnn	cnn	PROPN
ajst-27738	220	12	titanx	titanx	VERB
ajst-27738	220	13	51.3	51.3	NUM
ajst-27738	220	14	61.2	61.2	NUM
ajst-27738	220	15	icnet[16	icnet[16	PROPN
ajst-27738	220	16	]	]	PUNCT
ajst-27738	220	17	pspnet50	pspnet50	NOUN
ajst-27738	220	18	titanx	titanx	VERB
ajst-27738	220	19	67.1	67.1	NUM
ajst-27738	220	20	27.8	27.8	NUM
ajst-27738	220	21	dfanet	dfanet	NOUN
ajst-27738	220	22	a[27	a[27	PROPN
ajst-27738	220	23	]	]	PUNCT
ajst-27738	220	24	xception	xception	NOUN
ajst-27738	220	25	a	a	DET
ajst-27738	220	26	titanx	titanx	NOUN
ajst-27738	220	27	64.7	64.7	NUM
ajst-27738	220	28	120	120	NUM
ajst-27738	220	29	dfanet	dfanet	NOUN
ajst-27738	220	30	b[27	b[27	PROPN
ajst-27738	220	31	]	]	PUNCT
ajst-27738	220	32	xception	xception	PROPN
ajst-27738	220	33	b	b	PROPN
ajst-27738	220	34	titanx	titanx	NOUN
ajst-27738	220	35	59.3	59.3	NUM
ajst-27738	220	36	160	160	NUM
ajst-27738	220	37	swiftnet[37	swiftnet[37	NOUN
ajst-27738	220	38	]	]	PUNCT
ajst-27738	220	39	resnet18	resnet18	NOUN
ajst-27738	220	40	gtx	gtx	PROPN
ajst-27738	220	41	1080ti	1080ti	PROPN
ajst-27738	220	42	72.6	72.6	NUM
ajst-27738	220	43	bisenetv1[17	bisenetv1[17	PROPN
ajst-27738	220	44	]	]	PUNCT
ajst-27738	220	45	xception39	xception39	PROPN
ajst-27738	221	1	gtx	gtx	PROPN
ajst-27738	221	2	1080ti	1080ti	PROPN
ajst-27738	221	3	65.6	65.6	NUM
ajst-27738	221	4	175	175	NUM
ajst-27738	221	5	bisenetv1[17	bisenetv1[17	PROPN
ajst-27738	221	6	]	]	PUNCT
ajst-27738	221	7	resnet18	resnet18	NOUN
ajst-27738	221	8	gtx	gtx	PROPN
ajst-27738	221	9	1080ti	1080ti	PROPN
ajst-27738	221	10	68.7	68.7	NUM
ajst-27738	221	11	116.3	116.3	NUM
ajst-27738	221	12	stdc1†[36	stdc1†[36	NOUN
ajst-27738	221	13	]	]	PUNCT
ajst-27738	221	14	stdc1	stdc1	X
ajst-27738	221	15	gtx	gtx	PROPN
ajst-27738	221	16	1080ti	1080ti	PROPN
ajst-27738	221	17	73.0	73.0	NUM
ajst-27738	221	18	197.6	197.6	NUM
ajst-27738	221	19	stdc2†[36	stdc2†[36	NOUN
ajst-27738	221	20	]	]	PUNCT
ajst-27738	221	21	stdc2	stdc2	PROPN
ajst-27738	222	1	gtx	gtx	PROPN
ajst-27738	222	2	1080ti	1080ti	PROPN
ajst-27738	222	3	73.9	73.9	NUM
ajst-27738	222	4	152.2	152.2	NUM
ajst-27738	222	5	bisenetv2[18	bisenetv2[18	NOUN
ajst-27738	222	6	]	]	PUNCT
ajst-27738	222	7	no	no	DET
ajst-27738	222	8	gtx	gtx	PROPN
ajst-27738	222	9	1080ti	1080ti	PROPN
ajst-27738	222	10	72.4	72.4	NUM
ajst-27738	222	11	124.5	124.5	NUM
ajst-27738	222	12	bisenetv2	bisenetv2	NOUN
ajst-27738	222	13	-	-	PUNCT
ajst-27738	222	14	l[18	l[18	PROPN
ajst-27738	222	15	]	]	X
ajst-27738	222	16	no	no	DET
ajst-27738	222	17	gtx	gtx	PROPN
ajst-27738	222	18	1080ti	1080ti	PROPN
ajst-27738	222	19	73.2	73.2	NUM
ajst-27738	222	20	32.7	32.7	NUM
ajst-27738	222	21	bisenetv2*†[18	bisenetv2*†[18	NOUN
ajst-27738	222	22	]	]	X
ajst-27738	222	23	no	no	DET
ajst-27738	222	24	gtx	gtx	PROPN
ajst-27738	222	25	1080ti	1080ti	PROPN
ajst-27738	222	26	76.7	76.7	NUM
ajst-27738	222	27	124.5	124.5	NUM
ajst-27738	222	28	artrnet	artrnet	NOUN
ajst-27738	222	29	no	no	DET
ajst-27738	222	30	rtx	rtx	NOUN
ajst-27738	222	31	3090	3090	NUM
ajst-27738	222	32	76.5	76.5	NUM
ajst-27738	222	33	110.4	110.4	NUM
ajst-27738	222	34	4.3.4	4.3.4	NOUN
ajst-27738	222	35	.	.	PUNCT
ajst-27738	223	1	visualization	visualization	NOUN
ajst-27738	223	2	experiments	experiment	NOUN
ajst-27738	223	3	on	on	ADP
ajst-27738	223	4	cityscapes	cityscape	NOUN
ajst-27738	223	5	to	to	PART
ajst-27738	223	6	visually	visually	ADV
ajst-27738	223	7	highlight	highlight	VERB
ajst-27738	223	8	the	the	DET
ajst-27738	223	9	significant	significant	ADJ
ajst-27738	223	10	advantages	advantage	NOUN
ajst-27738	223	11	of	of	ADP
ajst-27738	223	12	our	our	PRON
ajst-27738	223	13	proposed	propose	VERB
ajst-27738	223	14	method	method	NOUN
ajst-27738	223	15	,	,	PUNCT
ajst-27738	223	16	figure	figure	NOUN
ajst-27738	223	17	5	5	NUM
ajst-27738	223	18	compares	compare	VERB
ajst-27738	223	19	our	our	PRON
ajst-27738	223	20	approach	approach	NOUN
ajst-27738	223	21	with	with	ADP
ajst-27738	223	22	several	several	ADJ
ajst-27738	223	23	other	other	ADJ
ajst-27738	223	24	methods	method	NOUN
ajst-27738	223	25	on	on	ADP
ajst-27738	223	26	the	the	DET
ajst-27738	223	27	cityscapes	cityscape	NOUN
ajst-27738	223	28	dataset	dataset	VERB
ajst-27738	223	29	.	.	PUNCT
ajst-27738	224	1	through	through	ADP
ajst-27738	224	2	these	these	DET
ajst-27738	224	3	comparison	comparison	NOUN
ajst-27738	224	4	plots	plot	NOUN
ajst-27738	224	5	,	,	PUNCT
ajst-27738	224	6	it	it	PRON
ajst-27738	224	7	can	can	AUX
ajst-27738	224	8	be	be	AUX
ajst-27738	224	9	clearly	clearly	ADV
ajst-27738	224	10	observed	observe	VERB
ajst-27738	224	11	that	that	SCONJ
ajst-27738	224	12	our	our	PRON
ajst-27738	224	13	method	method	NOUN
ajst-27738	224	14	is	be	AUX
ajst-27738	224	15	the	the	DET
ajst-27738	224	16	closest	close	ADJ
ajst-27738	224	17	to	to	ADP
ajst-27738	224	18	the	the	DET
ajst-27738	224	19	real	real	ADJ
ajst-27738	224	20	-	-	PUNCT
ajst-27738	224	21	world	world	NOUN
ajst-27738	224	22	scenarios	scenario	NOUN
ajst-27738	224	23	in	in	ADP
ajst-27738	224	24	terms	term	NOUN
ajst-27738	224	25	of	of	ADP
ajst-27738	224	26	presenting	present	VERB
ajst-27738	224	27	results	result	NOUN
ajst-27738	224	28	,	,	PUNCT
ajst-27738	224	29	i.e.	i.e.	X
ajst-27738	224	30	,	,	PUNCT
ajst-27738	224	31	our	our	PRON
ajst-27738	224	32	method	method	NOUN
ajst-27738	224	33	exhibits	exhibit	VERB
ajst-27738	224	34	a	a	DET
ajst-27738	224	35	superior	superior	ADJ
ajst-27738	224	36	performance	performance	NOUN
ajst-27738	224	37	in	in	ADP
ajst-27738	224	38	comparison	comparison	NOUN
ajst-27738	224	39	with	with	ADP
ajst-27738	224	40	the	the	DET
ajst-27738	224	41	three	three	NUM
ajst-27738	224	42	comparable	comparable	ADJ
ajst-27738	224	43	methods	method	NOUN
ajst-27738	224	44	.	.	PUNCT
ajst-27738	225	1	(	(	PUNCT
ajst-27738	225	2	a	a	X
ajst-27738	225	3	)	)	PUNCT
ajst-27738	225	4	(	(	PUNCT
ajst-27738	225	5	c	c	X
ajst-27738	225	6	)	)	PUNCT
ajst-27738	225	7	(	(	PUNCT
ajst-27738	225	8	d	d	X
ajst-27738	225	9	)	)	PUNCT
ajst-27738	225	10	(	(	PUNCT
ajst-27738	225	11	e	e	NOUN
ajst-27738	225	12	)	)	PUNCT
ajst-27738	225	13	(	(	PUNCT
ajst-27738	225	14	b	b	X
ajst-27738	225	15	)	)	PUNCT
ajst-27738	225	16	figure	figure	NOUN
ajst-27738	225	17	5	5	NUM
ajst-27738	225	18	.	.	PUNCT
ajst-27738	226	1	visualisation	visualisation	NOUN
ajst-27738	226	2	of	of	ADP
ajst-27738	226	3	segmentation	segmentation	NOUN
ajst-27738	226	4	results	result	NOUN
ajst-27738	226	5	of	of	ADP
ajst-27738	226	6	bisenetv1	bisenetv1	PROPN
ajst-27738	226	7	,	,	PUNCT
ajst-27738	226	8	bisenetv2	bisenetv2	NOUN
ajst-27738	226	9	and	and	CCONJ
ajst-27738	226	10	artrnet	artrnet	VERB
ajst-27738	226	11	on	on	ADP
ajst-27738	226	12	cityscape	cityscape	NOUN
ajst-27738	226	13	dataset	dataset	NOUN
ajst-27738	226	14	.	.	PUNCT
ajst-27738	227	1	(	(	PUNCT
ajst-27738	227	2	a	a	X
ajst-27738	227	3	)	)	PUNCT
ajst-27738	227	4	input	input	NOUN
ajst-27738	227	5	image	image	NOUN
ajst-27738	227	6	;	;	PUNCT
ajst-27738	227	7	(	(	PUNCT
ajst-27738	227	8	b	b	X
ajst-27738	227	9	)	)	PUNCT
ajst-27738	227	10	ground	ground	NOUN
ajst-27738	227	11	truth	truth	NOUN
ajst-27738	227	12	;	;	PUNCT
ajst-27738	227	13	(	(	PUNCT
ajst-27738	227	14	c	c	X
ajst-27738	227	15	)	)	PUNCT
ajst-27738	227	16	bisenetv1	bisenetv1	NOUN
ajst-27738	227	17	;	;	PUNCT
ajst-27738	227	18	(	(	PUNCT
ajst-27738	227	19	d	d	X
ajst-27738	227	20	)	)	PUNCT
ajst-27738	227	21	bisenetv2	bisenetv2	NOUN
ajst-27738	227	22	;	;	PUNCT
ajst-27738	227	23	(	(	PUNCT
ajst-27738	227	24	e	e	NOUN
ajst-27738	227	25	)	)	PUNCT
ajst-27738	227	26	artrnet	artrnet	NOUN
ajst-27738	227	27	.	.	PUNCT
ajst-27738	228	1	5	5	X
ajst-27738	228	2	.	.	X
ajst-27738	228	3	conclusion	conclusion	VERB
ajst-27738	228	4	real	real	ADJ
ajst-27738	228	5	-	-	PUNCT
ajst-27738	228	6	time	time	NOUN
ajst-27738	228	7	semantic	semantic	ADJ
ajst-27738	228	8	segmentation	segmentation	NOUN
ajst-27738	228	9	is	be	AUX
ajst-27738	228	10	increasingly	increasingly	ADV
ajst-27738	228	11	crucial	crucial	ADJ
ajst-27738	228	12	in	in	ADP
ajst-27738	228	13	demanding	demand	VERB
ajst-27738	228	14	scenarios	scenario	NOUN
ajst-27738	228	15	like	like	ADP
ajst-27738	228	16	autonomous	autonomous	ADJ
ajst-27738	228	17	driving	driving	NOUN
ajst-27738	228	18	.	.	PUNCT
ajst-27738	229	1	however	however	ADV
ajst-27738	229	2	,	,	PUNCT
ajst-27738	229	3	many	many	ADJ
ajst-27738	229	4	existing	exist	VERB
ajst-27738	229	5	methods	method	NOUN
ajst-27738	229	6	prioritize	prioritize	VERB
ajst-27738	229	7	accuracy	accuracy	NOUN
ajst-27738	229	8	over	over	ADP
ajst-27738	229	9	speed	speed	NOUN
ajst-27738	229	10	.	.	PUNCT
ajst-27738	230	1	although	although	SCONJ
ajst-27738	230	2	bisenetv2	bisenetv2	NOUN
ajst-27738	230	3	is	be	AUX
ajst-27738	230	4	effective	effective	ADJ
ajst-27738	230	5	,	,	PUNCT
ajst-27738	230	6	its	its	PRON
ajst-27738	230	7	speed	speed	NOUN
ajst-27738	230	8	improvement	improvement	NOUN
ajst-27738	230	9	is	be	AUX
ajst-27738	230	10	limited	limit	VERB
ajst-27738	230	11	while	while	SCONJ
ajst-27738	230	12	maintaining	maintain	VERB
ajst-27738	230	13	high	high	ADJ
ajst-27738	230	14	accuracy	accuracy	NOUN
ajst-27738	230	15	.	.	PUNCT
ajst-27738	231	1	therefore	therefore	ADV
ajst-27738	231	2	,	,	PUNCT
ajst-27738	231	3	achieving	achieve	VERB
ajst-27738	231	4	a	a	DET
ajst-27738	231	5	balanced	balanced	ADJ
ajst-27738	231	6	trade	trade	NOUN
ajst-27738	231	7	-	-	PUNCT
ajst-27738	231	8	off	off	NOUN
ajst-27738	231	9	between	between	ADP
ajst-27738	231	10	speed	speed	NOUN
ajst-27738	231	11	and	and	CCONJ
ajst-27738	231	12	accuracy	accuracy	NOUN
ajst-27738	231	13	is	be	AUX
ajst-27738	231	14	274	274	NUM
ajst-27738	231	15	a	a	DET
ajst-27738	231	16	key	key	ADJ
ajst-27738	231	17	focus	focus	NOUN
ajst-27738	231	18	of	of	ADP
ajst-27738	231	19	current	current	ADJ
ajst-27738	231	20	research	research	NOUN
ajst-27738	231	21	.	.	PUNCT
ajst-27738	232	1	in	in	ADP
ajst-27738	232	2	this	this	DET
ajst-27738	232	3	paper	paper	NOUN
ajst-27738	232	4	,	,	PUNCT
ajst-27738	232	5	we	we	PRON
ajst-27738	232	6	introduce	introduce	VERB
ajst-27738	232	7	an	an	DET
ajst-27738	232	8	efficient	efficient	ADJ
ajst-27738	232	9	attention	attention	NOUN
ajst-27738	232	10	refined	refine	VERB
ajst-27738	232	11	two	two	NUM
ajst-27738	232	12	-	-	PUNCT
ajst-27738	232	13	branch	branch	NOUN
ajst-27738	232	14	real	real	ADJ
ajst-27738	232	15	-	-	PUNCT
ajst-27738	232	16	time	time	NOUN
ajst-27738	232	17	semantic	semantic	ADJ
ajst-27738	232	18	segmentation	segmentation	NOUN
ajst-27738	232	19	network	network	NOUN
ajst-27738	232	20	.	.	PUNCT
ajst-27738	233	1	we	we	PRON
ajst-27738	233	2	propose	propose	VERB
ajst-27738	233	3	lightweight	lightweight	ADJ
ajst-27738	233	4	densely	densely	ADV
ajst-27738	233	5	connected	connect	VERB
ajst-27738	233	6	contextual	contextual	ADJ
ajst-27738	233	7	refinement	refinement	NOUN
ajst-27738	233	8	branches	branch	NOUN
ajst-27738	233	9	to	to	PART
ajst-27738	233	10	reduce	reduce	VERB
ajst-27738	233	11	computational	computational	ADJ
ajst-27738	233	12	load	load	NOUN
ajst-27738	233	13	and	and	CCONJ
ajst-27738	233	14	improve	improve	VERB
ajst-27738	233	15	speed	speed	NOUN
ajst-27738	233	16	while	while	SCONJ
ajst-27738	233	17	ensuring	ensure	VERB
ajst-27738	233	18	accuracy	accuracy	NOUN
ajst-27738	233	19	.	.	PUNCT
ajst-27738	234	1	additionally	additionally	ADV
ajst-27738	234	2	,	,	PUNCT
ajst-27738	234	3	to	to	PART
ajst-27738	234	4	address	address	VERB
ajst-27738	234	5	the	the	DET
ajst-27738	234	6	challenge	challenge	NOUN
ajst-27738	234	7	of	of	ADP
ajst-27738	234	8	feature	feature	NOUN
ajst-27738	234	9	map	map	NOUN
ajst-27738	234	10	detail	detail	NOUN
ajst-27738	234	11	loss	loss	NOUN
ajst-27738	234	12	during	during	ADP
ajst-27738	234	13	branch	branch	NOUN
ajst-27738	234	14	fusion	fusion	NOUN
ajst-27738	234	15	,	,	PUNCT
ajst-27738	234	16	we	we	PRON
ajst-27738	234	17	propose	propose	VERB
ajst-27738	234	18	the	the	DET
ajst-27738	234	19	deformed	deform	VERB
ajst-27738	234	20	convolutional	convolutional	ADJ
ajst-27738	234	21	attention	attention	NOUN
ajst-27738	234	22	refinement	refinement	NOUN
ajst-27738	234	23	fusion	fusion	NOUN
ajst-27738	234	24	module	module	NOUN
ajst-27738	234	25	.	.	PUNCT
ajst-27738	235	1	this	this	DET
ajst-27738	235	2	module	module	NOUN
ajst-27738	235	3	refines	refine	VERB
ajst-27738	235	4	feature	feature	NOUN
ajst-27738	235	5	map	map	NOUN
ajst-27738	235	6	details	detail	NOUN
ajst-27738	235	7	through	through	ADP
ajst-27738	235	8	deformed	deform	VERB
ajst-27738	235	9	convolutional	convolutional	ADJ
ajst-27738	235	10	attention	attention	NOUN
ajst-27738	235	11	refinement	refinement	NOUN
ajst-27738	235	12	operations	operation	NOUN
ajst-27738	235	13	,	,	PUNCT
ajst-27738	235	14	enhancing	enhance	VERB
ajst-27738	235	15	the	the	DET
ajst-27738	235	16	segmentation	segmentation	NOUN
ajst-27738	235	17	capability	capability	NOUN
ajst-27738	235	18	of	of	ADP
ajst-27738	235	19	the	the	DET
ajst-27738	235	20	model	model	NOUN
ajst-27738	235	21	.	.	PUNCT
ajst-27738	236	1	experimental	experimental	ADJ
ajst-27738	236	2	results	result	NOUN
ajst-27738	236	3	on	on	ADP
ajst-27738	236	4	cityscapes	cityscape	NOUN
ajst-27738	236	5	and	and	CCONJ
ajst-27738	236	6	camvid	camvid	NOUN
ajst-27738	236	7	datasets	dataset	NOUN
ajst-27738	236	8	demonstrate	demonstrate	VERB
ajst-27738	236	9	that	that	SCONJ
ajst-27738	236	10	our	our	PRON
ajst-27738	236	11	proposed	propose	VERB
ajst-27738	236	12	artrnet	artrnet	NOUN
ajst-27738	236	13	achieves	achieve	VERB
ajst-27738	236	14	a	a	DET
ajst-27738	236	15	favorable	favorable	ADJ
ajst-27738	236	16	balance	balance	NOUN
ajst-27738	236	17	between	between	ADP
ajst-27738	236	18	segmentation	segmentation	NOUN
ajst-27738	236	19	accuracy	accuracy	NOUN
ajst-27738	236	20	and	and	CCONJ
ajst-27738	236	21	inference	inference	NOUN
ajst-27738	236	22	speed	speed	NOUN
ajst-27738	236	23	,	,	PUNCT
ajst-27738	236	24	surpassing	surpass	VERB
ajst-27738	236	25	other	other	ADJ
ajst-27738	236	26	representative	representative	ADJ
ajst-27738	236	27	real	real	ADJ
ajst-27738	236	28	-	-	PUNCT
ajst-27738	236	29	time	time	NOUN
ajst-27738	236	30	semantic	semantic	ADJ
ajst-27738	236	31	segmentation	segmentation	NOUN
ajst-27738	236	32	methods	method	NOUN
ajst-27738	236	33	.	.	PUNCT
ajst-27738	237	1	references	reference	NOUN
ajst-27738	237	2	[	[	X
ajst-27738	237	3	1	1	NUM
ajst-27738	237	4	]	]	X
ajst-27738	237	5	azuma	azuma	NOUN
ajst-27738	237	6	r	r	NOUN
ajst-27738	237	7	t.	t.	NOUN
ajst-27738	237	8	a	a	DET
ajst-27738	237	9	survey	survey	NOUN
ajst-27738	237	10	of	of	ADP
ajst-27738	237	11	augmented	augment	VERB
ajst-27738	237	12	reality	reality	NOUN
ajst-27738	238	1	[	[	X
ajst-27738	238	2	j	j	X
ajst-27738	238	3	]	]	X
ajst-27738	238	4	.	.	PUNCT
ajst-27738	239	1	presence	presence	NOUN
ajst-27738	239	2	:	:	PUNCT
ajst-27738	239	3	teleoperators	teleoperator	NOUN
ajst-27738	239	4	and	and	CCONJ
ajst-27738	239	5	virtual	virtual	ADJ
ajst-27738	239	6	environments	environment	NOUN
ajst-27738	239	7	,	,	PUNCT
ajst-27738	239	8	1997	1997	NUM
ajst-27738	239	9	,	,	PUNCT
ajst-27738	239	10	6(4	6(4	NUM
ajst-27738	239	11	):	):	PUNCT
ajst-27738	239	12	355	355	NUM
ajst-27738	239	13	-	-	SYM
ajst-27738	239	14	385	385	NUM
ajst-27738	239	15	.	.	PUNCT
ajst-27738	240	1	[	[	X
ajst-27738	240	2	2	2	X
ajst-27738	240	3	]	]	X
ajst-27738	240	4	siam	siam	PROPN
ajst-27738	240	5	m	m	PROPN
ajst-27738	240	6	,	,	PUNCT
ajst-27738	240	7	gamal	gamal	PROPN
ajst-27738	240	8	m	m	PROPN
ajst-27738	240	9	,	,	PUNCT
ajst-27738	240	10	abdel	abdel	ADJ
ajst-27738	240	11	-	-	PUNCT
ajst-27738	240	12	razek	razek	NOUN
ajst-27738	240	13	m	m	NOUN
ajst-27738	240	14	,	,	PUNCT
ajst-27738	240	15	et	et	PROPN
ajst-27738	240	16	al	al	PROPN
ajst-27738	240	17	.	.	PUNCT
ajst-27738	241	1	a	a	DET
ajst-27738	241	2	comparative	comparative	ADJ
ajst-27738	241	3	study	study	NOUN
ajst-27738	241	4	of	of	ADP
ajst-27738	241	5	real	real	ADJ
ajst-27738	241	6	-	-	PUNCT
ajst-27738	241	7	time	time	NOUN
ajst-27738	241	8	semantic	semantic	ADJ
ajst-27738	241	9	segmentation	segmentation	NOUN
ajst-27738	241	10	for	for	ADP
ajst-27738	241	11	autonomous	autonomous	ADJ
ajst-27738	241	12	driving[c	driving[c	NOUN
ajst-27738	241	13	]	]	PUNCT
ajst-27738	241	14	.	.	PUNCT
ajst-27738	242	1	ieee	ieee	PROPN
ajst-27738	242	2	conference	conference	PROPN
ajst-27738	242	3	on	on	ADP
ajst-27738	242	4	computer	computer	NOUN
ajst-27738	242	5	vision	vision	NOUN
ajst-27738	242	6	and	and	CCONJ
ajst-27738	242	7	pattern	pattern	NOUN
ajst-27738	242	8	recognition	recognition	NOUN
ajst-27738	242	9	,	,	PUNCT
ajst-27738	242	10	2018	2018	NUM
ajst-27738	242	11	:	:	PUNCT
ajst-27738	242	12	587	587	NUM
ajst-27738	242	13	-	-	SYM
ajst-27738	242	14	597	597	NUM
ajst-27738	242	15	.	.	PUNCT
ajst-27738	243	1	[	[	X
ajst-27738	243	2	3	3	X
ajst-27738	243	3	]	]	PUNCT
ajst-27738	243	4	you	you	PRON
ajst-27738	243	5	h	h	NOUN
ajst-27738	243	6	,	,	PUNCT
ajst-27738	243	7	yu	yu	PROPN
ajst-27738	243	8	l	l	PROPN
ajst-27738	243	9	,	,	PUNCT
ajst-27738	243	10	tian	tian	PROPN
ajst-27738	243	11	s	s	PROPN
ajst-27738	243	12	,	,	PUNCT
ajst-27738	243	13	et	et	PROPN
ajst-27738	243	14	al	al	PROPN
ajst-27738	243	15	.	.	PROPN
ajst-27738	243	16	dr	dr	PROPN
ajst-27738	243	17	-	-	PUNCT
ajst-27738	243	18	net	net	NOUN
ajst-27738	243	19	:	:	PUNCT
ajst-27738	243	20	dual	dual	ADJ
ajst-27738	243	21	-	-	PUNCT
ajst-27738	243	22	rotation	rotation	NOUN
ajst-27738	243	23	network	network	NOUN
ajst-27738	243	24	with	with	ADP
ajst-27738	243	25	feature	feature	NOUN
ajst-27738	243	26	map	map	NOUN
ajst-27738	243	27	enhancement	enhancement	NOUN
ajst-27738	243	28	for	for	ADP
ajst-27738	243	29	medical	medical	ADJ
ajst-27738	243	30	image	image	NOUN
ajst-27738	243	31	segmentation	segmentation	NOUN
ajst-27738	244	1	[	[	X
ajst-27738	244	2	j	j	X
ajst-27738	244	3	]	]	X
ajst-27738	244	4	.	.	PUNCT
ajst-27738	245	1	complex	complex	ADJ
ajst-27738	245	2	and	and	CCONJ
ajst-27738	245	3	intelligent	intelligent	ADJ
ajst-27738	245	4	systems	system	NOUN
ajst-27738	245	5	,	,	PUNCT
ajst-27738	245	6	2021	2021	NUM
ajst-27738	245	7	:	:	PUNCT
ajst-27738	245	8	1	1	NUM
ajst-27738	245	9	-	-	SYM
ajst-27738	245	10	13	13	NUM
ajst-27738	245	11	.	.	PUNCT
ajst-27738	246	1	[	[	X
ajst-27738	246	2	4	4	NUM
ajst-27738	246	3	]	]	X
ajst-27738	246	4	dechesne	dechesne	ADJ
ajst-27738	246	5	c	c	NOUN
ajst-27738	246	6	,	,	PUNCT
ajst-27738	246	7	mallet	mallet	NOUN
ajst-27738	246	8	c	c	NOUN
ajst-27738	246	9	,	,	PUNCT
ajst-27738	246	10	le	le	X
ajst-27738	246	11	bris	bris	VERB
ajst-27738	246	12	a	a	PRON
ajst-27738	246	13	,	,	PUNCT
ajst-27738	246	14	et	et	PROPN
ajst-27738	246	15	al	al	PROPN
ajst-27738	246	16	.	.	PUNCT
ajst-27738	247	1	semantic	semantic	ADJ
ajst-27738	247	2	segmentation	segmentation	NOUN
ajst-27738	247	3	of	of	ADP
ajst-27738	247	4	forest	forest	NOUN
ajst-27738	247	5	stands	stand	VERB
ajst-27738	247	6	of	of	ADP
ajst-27738	247	7	pure	pure	ADJ
ajst-27738	247	8	species	specie	NOUN
ajst-27738	247	9	combining	combine	VERB
ajst-27738	247	10	airborne	airborne	ADJ
ajst-27738	247	11	lidar	lidar	NOUN
ajst-27738	247	12	data	datum	NOUN
ajst-27738	247	13	and	and	CCONJ
ajst-27738	247	14	very	very	ADV
ajst-27738	247	15	high	high	ADJ
ajst-27738	247	16	resolution	resolution	NOUN
ajst-27738	247	17	multispectral	multispectral	ADJ
ajst-27738	247	18	imagery	imagery	NOUN
ajst-27738	248	1	[	[	X
ajst-27738	248	2	j	j	X
ajst-27738	248	3	]	]	X
ajst-27738	248	4	.	.	PUNCT
ajst-27738	249	1	isprs	isprs	PROPN
ajst-27738	249	2	journal	journal	PROPN
ajst-27738	249	3	of	of	ADP
ajst-27738	249	4	photogrammetry	photogrammetry	NOUN
ajst-27738	249	5	and	and	CCONJ
ajst-27738	249	6	remote	remote	ADJ
ajst-27738	249	7	sensing	sensing	NOUN
ajst-27738	249	8	,	,	PUNCT
ajst-27738	249	9	2017	2017	NUM
ajst-27738	249	10	,	,	PUNCT
ajst-27738	249	11	126	126	NUM
ajst-27738	249	12	:	:	SYM
ajst-27738	249	13	129	129	NUM
ajst-27738	249	14	-	-	SYM
ajst-27738	249	15	145	145	NUM
ajst-27738	249	16	.	.	PUNCT
ajst-27738	250	1	[	[	X
ajst-27738	250	2	5	5	X
ajst-27738	250	3	]	]	PUNCT
ajst-27738	250	4	zhuang	zhuang	PROPN
ajst-27738	250	5	j	j	PROPN
ajst-27738	250	6	,	,	PUNCT
ajst-27738	250	7	wang	wang	PROPN
ajst-27738	250	8	z	z	PROPN
ajst-27738	250	9	,	,	PUNCT
ajst-27738	250	10	wang	wang	PROPN
ajst-27738	250	11	b.	b.	PROPN
ajst-27738	250	12	video	video	PROPN
ajst-27738	250	13	semantic	semantic	ADJ
ajst-27738	250	14	segmentation	segmentation	NOUN
ajst-27738	250	15	with	with	ADP
ajst-27738	250	16	distortion	distortion	NOUN
ajst-27738	250	17	-	-	PUNCT
ajst-27738	250	18	aware	aware	ADJ
ajst-27738	250	19	feature	feature	NOUN
ajst-27738	250	20	correction	correction	NOUN
ajst-27738	250	21	[	[	X
ajst-27738	250	22	j	j	X
ajst-27738	250	23	]	]	X
ajst-27738	250	24	.	.	PUNCT
ajst-27738	251	1	ieee	ieee	NOUN
ajst-27738	251	2	transactions	transaction	NOUN
ajst-27738	251	3	on	on	ADP
ajst-27738	251	4	circuits	circuit	NOUN
ajst-27738	251	5	and	and	CCONJ
ajst-27738	251	6	systems	system	NOUN
ajst-27738	251	7	for	for	ADP
ajst-27738	251	8	video	video	NOUN
ajst-27738	251	9	technology	technology	NOUN
ajst-27738	251	10	,	,	PUNCT
ajst-27738	251	11	2020	2020	NUM
ajst-27738	251	12	,	,	PUNCT
ajst-27738	251	13	31(8	31(8	NUM
ajst-27738	251	14	):	):	PUNCT
ajst-27738	251	15	3128	3128	NUM
ajst-27738	251	16	-	-	SYM
ajst-27738	251	17	3139	3139	NUM
ajst-27738	251	18	.	.	PUNCT
ajst-27738	252	1	[	[	X
ajst-27738	252	2	6	6	NUM
ajst-27738	252	3	]	]	PUNCT
ajst-27738	252	4	chen	chen	PROPN
ajst-27738	252	5	l	l	PROPN
ajst-27738	252	6	c	c	PROPN
ajst-27738	252	7	,	,	PUNCT
ajst-27738	252	8	zhu	zhu	PROPN
ajst-27738	252	9	y	y	PROPN
ajst-27738	252	10	,	,	PUNCT
ajst-27738	252	11	papandreou	papandreou	PROPN
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ajst-27738	252	13	,	,	PUNCT
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ajst-27738	252	20	with	with	ADP
ajst-27738	252	21	atrous	atrous	ADJ
ajst-27738	252	22	separable	separable	ADJ
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ajst-27738	252	25	semantic	semantic	ADJ
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ajst-27738	253	1	[	[	X
ajst-27738	253	2	c	c	X
ajst-27738	253	3	]	]	PUNCT
ajst-27738	253	4	.	.	PUNCT
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ajst-27738	254	2	conference	conference	PROPN
ajst-27738	254	3	on	on	ADP
ajst-27738	254	4	computer	computer	NOUN
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ajst-27738	254	6	,	,	PUNCT
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ajst-27738	254	8	:	:	PUNCT
ajst-27738	254	9	801	801	NUM
ajst-27738	254	10	-	-	SYM
ajst-27738	254	11	818	818	NUM
ajst-27738	254	12	.	.	PUNCT
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ajst-27738	255	3	]	]	PUNCT
ajst-27738	255	4	nirkin	nirkin	PROPN
ajst-27738	255	5	y	y	PROPN
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ajst-27738	255	16	wise	wise	ADJ
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ajst-27738	255	18	for	for	ADP
ajst-27738	255	19	real	real	ADJ
ajst-27738	255	20	-	-	PUNCT
ajst-27738	255	21	time	time	NOUN
ajst-27738	255	22	semantic	semantic	ADJ
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ajst-27738	256	1	[	[	X
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ajst-27738	256	3	]	]	PUNCT
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ajst-27738	257	4	computer	computer	NOUN
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ajst-27738	257	13	-	-	SYM
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ajst-27738	258	3	]	]	SYM
ajst-27738	258	4	yuan	yuan	NOUN
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ajst-27738	258	6	,	,	PUNCT
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ajst-27738	258	9	,	,	PUNCT
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ajst-27738	259	1	[	[	X
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ajst-27738	259	4	.	.	PUNCT
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ajst-27738	260	2	journal	journal	PROPN
ajst-27738	260	3	of	of	ADP
ajst-27738	260	4	computer	computer	NOUN
ajst-27738	260	5	vision	vision	NOUN
ajst-27738	260	6	,	,	PUNCT
ajst-27738	260	7	2021	2021	NUM
ajst-27738	260	8	,	,	PUNCT
ajst-27738	260	9	129(8	129(8	NUM
ajst-27738	260	10	):	):	PUNCT
ajst-27738	260	11	2375	2375	NUM
ajst-27738	260	12	-	-	SYM
ajst-27738	260	13	2398	2398	NUM
ajst-27738	260	14	.	.	PUNCT
ajst-27738	261	1	[	[	X
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ajst-27738	261	9	,	,	PUNCT
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ajst-27738	262	3	]	]	PUNCT
ajst-27738	262	4	.	.	PUNCT
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ajst-27738	263	4	computer	computer	NOUN
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ajst-27738	263	9	,	,	PUNCT
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ajst-27738	263	13	-	-	SYM
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ajst-27738	264	3	]	]	X
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ajst-27738	264	17	,	,	PUNCT
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ajst-27738	264	23	a	a	DET
ajst-27738	264	24	fusion	fusion	NOUN
ajst-27738	264	25	-	-	PUNCT
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ajst-27738	264	27	network	network	NOUN
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ajst-27738	264	30	segmentation	segmentation	NOUN
ajst-27738	265	1	[	[	X
ajst-27738	265	2	c	c	X
ajst-27738	265	3	]	]	PUNCT
ajst-27738	265	4	.	.	PUNCT
ajst-27738	266	1	ieee	ieee	PROPN
ajst-27738	266	2	international	international	PROPN
ajst-27738	266	3	conference	conference	NOUN
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ajst-27738	266	6	processing	processing	NOUN
ajst-27738	266	7	,	,	PUNCT
ajst-27738	266	8	2019	2019	NUM
ajst-27738	266	9	:	:	PUNCT
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ajst-27738	266	11	-	-	SYM
ajst-27738	266	12	2378	2378	NUM
ajst-27738	266	13	.	.	PUNCT
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ajst-27738	267	3	]	]	PUNCT
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ajst-27738	267	6	,	,	PUNCT
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ajst-27738	267	13	m	m	PROPN
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ajst-27738	267	21	residual	residual	ADJ
ajst-27738	267	22	factorized	factorize	VERB
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ajst-27738	267	25	real	real	ADJ
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ajst-27738	267	28	semantic	semantic	ADJ
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ajst-27738	267	30	[	[	X
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ajst-27738	267	33	.	.	PUNCT
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ajst-27738	268	2	transactions	transaction	NOUN
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ajst-27738	268	9	,	,	PUNCT
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ajst-27738	268	11	):	):	PUNCT
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ajst-27738	268	13	-	-	SYM
ajst-27738	268	14	272	272	NUM
ajst-27738	268	15	.	.	PUNCT
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ajst-27738	270	10	-	-	SYM
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ajst-27738	273	12	,	,	PUNCT
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ajst-27738	274	1	[	[	X
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ajst-27738	275	4	,	,	PUNCT
ajst-27738	275	5	2023	2023	NUM
ajst-27738	275	6	,	,	PUNCT
ajst-27738	275	7	17(6	17(6	NUM
ajst-27738	275	8	):	):	PUNCT
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ajst-27738	275	10	-	-	SYM
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ajst-27738	275	12	.	.	PUNCT
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ajst-27738	276	20	segmentation	segmentation	NOUN
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ajst-27738	276	22	robot	robot	NOUN
ajst-27738	276	23	-	-	PUNCT
ajst-27738	276	24	assisted	assist	VERB
ajst-27738	276	25	surgery	surgery	NOUN
ajst-27738	276	26	using	use	VERB
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ajst-27738	277	3	]	]	PUNCT
ajst-27738	277	4	.	.	PUNCT
ajst-27738	278	1	ieee	ieee	PROPN
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ajst-27738	278	3	conference	conference	PROPN
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ajst-27738	278	11	:	:	PUNCT
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ajst-27738	280	4	computer	computer	NOUN
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ajst-27738	280	7	2018	2018	NUM
ajst-27738	280	8	:	:	PUNCT
ajst-27738	280	9	405	405	NUM
ajst-27738	280	10	-	-	SYM
ajst-27738	280	11	420	420	NUM
ajst-27738	280	12	.	.	PUNCT
ajst-27738	281	1	[	[	X
ajst-27738	281	2	17	17	NUM
ajst-27738	281	3	]	]	PUNCT
ajst-27738	281	4	yu	yu	PROPN
ajst-27738	281	5	c	c	PROPN
ajst-27738	281	6	,	,	PUNCT
ajst-27738	281	7	wang	wang	PROPN
ajst-27738	281	8	j	j	PROPN
ajst-27738	281	9	,	,	PUNCT
ajst-27738	281	10	peng	peng	PROPN
ajst-27738	281	11	c	c	PROPN
ajst-27738	281	12	,	,	PUNCT
ajst-27738	281	13	et	et	PROPN
ajst-27738	281	14	al	al	PROPN
ajst-27738	281	15	.	.	PUNCT
ajst-27738	281	16	bisenet	bisenet	PROPN
ajst-27738	281	17	:	:	PUNCT
ajst-27738	281	18	bilateral	bilateral	ADJ
ajst-27738	281	19	segmentation	segmentation	NOUN
ajst-27738	281	20	network	network	NOUN
ajst-27738	281	21	for	for	ADP
ajst-27738	281	22	real	real	ADJ
ajst-27738	281	23	-	-	PUNCT
ajst-27738	281	24	time	time	NOUN
ajst-27738	281	25	semantic	semantic	ADJ
ajst-27738	281	26	segmentation	segmentation	NOUN
ajst-27738	281	27	[	[	X
ajst-27738	281	28	c	c	X
ajst-27738	281	29	]	]	PUNCT
ajst-27738	281	30	.	.	PUNCT
ajst-27738	282	1	european	european	ADJ
ajst-27738	282	2	conference	conference	PROPN
ajst-27738	282	3	on	on	ADP
ajst-27738	282	4	computer	computer	NOUN
ajst-27738	282	5	vision	vision	NOUN
ajst-27738	282	6	,	,	PUNCT
ajst-27738	282	7	2018	2018	NUM
ajst-27738	282	8	:	:	PUNCT
ajst-27738	282	9	325	325	NUM
ajst-27738	282	10	-	-	SYM
ajst-27738	282	11	341	341	NUM
ajst-27738	282	12	.	.	PUNCT
ajst-27738	283	1	[	[	X
ajst-27738	283	2	18	18	NUM
ajst-27738	283	3	]	]	PUNCT
ajst-27738	283	4	yu	yu	PROPN
ajst-27738	283	5	c	c	PROPN
ajst-27738	283	6	,	,	PUNCT
ajst-27738	283	7	gao	gao	PROPN
ajst-27738	283	8	c	c	PROPN
ajst-27738	283	9	,	,	PUNCT
ajst-27738	283	10	wang	wang	PROPN
ajst-27738	283	11	j	j	PROPN
ajst-27738	283	12	,	,	PUNCT
ajst-27738	283	13	et	et	PROPN
ajst-27738	283	14	al	al	PROPN
ajst-27738	283	15	.	.	PUNCT
ajst-27738	283	16	bisenet	bisenet	PROPN
ajst-27738	283	17	v2	v2	PROPN
ajst-27738	283	18	:	:	PUNCT
ajst-27738	283	19	bilateral	bilateral	ADJ
ajst-27738	283	20	network	network	NOUN
ajst-27738	283	21	with	with	ADP
ajst-27738	283	22	guided	guide	VERB
ajst-27738	283	23	aggregation	aggregation	NOUN
ajst-27738	283	24	for	for	ADP
ajst-27738	283	25	real	real	ADJ
ajst-27738	283	26	-	-	PUNCT
ajst-27738	283	27	time	time	NOUN
ajst-27738	283	28	semantic	semantic	ADJ
ajst-27738	283	29	segmentation	segmentation	NOUN
ajst-27738	283	30	[	[	X
ajst-27738	283	31	j	j	X
ajst-27738	283	32	]	]	X
ajst-27738	283	33	.	.	PUNCT
ajst-27738	284	1	international	international	ADJ
ajst-27738	284	2	journal	journal	PROPN
ajst-27738	284	3	of	of	ADP
ajst-27738	284	4	computer	computer	NOUN
ajst-27738	284	5	vision	vision	NOUN
ajst-27738	284	6	,	,	PUNCT
ajst-27738	284	7	2021	2021	NUM
ajst-27738	284	8	,	,	PUNCT
ajst-27738	284	9	129	129	NUM
ajst-27738	284	10	:	:	SYM
ajst-27738	284	11	30513068	30513068	NUM
ajst-27738	284	12	.	.	PUNCT
ajst-27738	285	1	[	[	X
ajst-27738	285	2	19	19	NUM
ajst-27738	285	3	]	]	X
ajst-27738	285	4	mehta	mehta	PROPN
ajst-27738	285	5	s	s	PROPN
ajst-27738	285	6	,	,	PUNCT
ajst-27738	285	7	rastegari	rastegari	NOUN
ajst-27738	285	8	m	m	PROPN
ajst-27738	285	9	,	,	PUNCT
ajst-27738	285	10	caspi	caspi	PROPN
ajst-27738	285	11	a	a	X
ajst-27738	285	12	,	,	PUNCT
ajst-27738	285	13	et	et	PROPN
ajst-27738	285	14	al	al	PROPN
ajst-27738	285	15	.	.	PROPN
ajst-27738	285	16	espnet	espnet	PROPN
ajst-27738	285	17	:	:	PUNCT
ajst-27738	285	18	efficient	efficient	ADJ
ajst-27738	285	19	spatial	spatial	ADJ
ajst-27738	285	20	pyramid	pyramid	NOUN
ajst-27738	285	21	of	of	ADP
ajst-27738	285	22	dilated	dilated	ADJ
ajst-27738	285	23	convolutions	convolution	NOUN
ajst-27738	285	24	for	for	ADP
ajst-27738	285	25	semantic	semantic	ADJ
ajst-27738	285	26	segmentation	segmentation	NOUN
ajst-27738	285	27	[	[	X
ajst-27738	285	28	c	c	X
ajst-27738	285	29	]	]	PUNCT
ajst-27738	285	30	.	.	PUNCT
ajst-27738	286	1	european	european	ADJ
ajst-27738	286	2	conference	conference	PROPN
ajst-27738	286	3	on	on	ADP
ajst-27738	286	4	computer	computer	NOUN
ajst-27738	286	5	vision	vision	NOUN
ajst-27738	286	6	,	,	PUNCT
ajst-27738	286	7	2018	2018	NUM
ajst-27738	286	8	:	:	PUNCT
ajst-27738	286	9	552	552	NUM
ajst-27738	286	10	-	-	SYM
ajst-27738	286	11	568	568	NUM
ajst-27738	286	12	.	.	PUNCT
ajst-27738	287	1	[	[	X
ajst-27738	287	2	20	20	NUM
ajst-27738	287	3	]	]	X
ajst-27738	287	4	lo	lo	PROPN
ajst-27738	287	5	s	s	PROPN
ajst-27738	287	6	y	y	PROPN
ajst-27738	287	7	,	,	PUNCT
ajst-27738	287	8	hang	hang	VERB
ajst-27738	287	9	h	h	NOUN
ajst-27738	287	10	m	m	PROPN
ajst-27738	287	11	,	,	PUNCT
ajst-27738	287	12	chan	chan	PROPN
ajst-27738	287	13	s	s	PROPN
ajst-27738	287	14	w	w	PROPN
ajst-27738	287	15	,	,	PUNCT
ajst-27738	287	16	et	et	PROPN
ajst-27738	287	17	al	al	PROPN
ajst-27738	287	18	.	.	PROPN
ajst-27738	288	1	efficient	efficient	ADJ
ajst-27738	288	2	dense	dense	ADJ
ajst-27738	288	3	modules	module	NOUN
ajst-27738	288	4	of	of	ADP
ajst-27738	288	5	asymmetric	asymmetric	ADJ
ajst-27738	288	6	convolution	convolution	NOUN
ajst-27738	288	7	for	for	ADP
ajst-27738	288	8	real	real	ADJ
ajst-27738	288	9	-	-	PUNCT
ajst-27738	288	10	time	time	NOUN
ajst-27738	288	11	semantic	semantic	ADJ
ajst-27738	288	12	segmentation	segmentation	NOUN
ajst-27738	288	13	[	[	X
ajst-27738	288	14	c	c	X
ajst-27738	288	15	]	]	PUNCT
ajst-27738	288	16	.	.	PUNCT
ajst-27738	288	17	acm	acm	PROPN
ajst-27738	288	18	international	international	ADJ
ajst-27738	288	19	conference	conference	NOUN
ajst-27738	288	20	on	on	ADP
ajst-27738	288	21	multimedia	multimedia	NOUN
ajst-27738	288	22	in	in	ADP
ajst-27738	288	23	asia	asia	PROPN
ajst-27738	288	24	,	,	PUNCT
ajst-27738	288	25	2019	2019	NUM
ajst-27738	288	26	:	:	PUNCT
ajst-27738	288	27	1	1	NUM
ajst-27738	288	28	-	-	SYM
ajst-27738	288	29	6	6	NUM
ajst-27738	288	30	.	.	PUNCT
ajst-27738	289	1	[	[	X
ajst-27738	289	2	21	21	NUM
ajst-27738	289	3	]	]	X
ajst-27738	289	4	otsu	otsu	NOUN
ajst-27738	289	5	n.	n.	NOUN
ajst-27738	289	6	a	a	DET
ajst-27738	289	7	threshold	threshold	NOUN
ajst-27738	289	8	selection	selection	NOUN
ajst-27738	289	9	method	method	NOUN
ajst-27738	289	10	from	from	ADP
ajst-27738	289	11	gray	gray	ADJ
ajst-27738	289	12	-	-	PUNCT
ajst-27738	289	13	level	level	NOUN
ajst-27738	289	14	histograms	histogram	NOUN
ajst-27738	290	1	[	[	X
ajst-27738	290	2	j	j	X
ajst-27738	290	3	]	]	X
ajst-27738	290	4	.	.	PUNCT
ajst-27738	291	1	automatica	automatica	PROPN
ajst-27738	291	2	,	,	PUNCT
ajst-27738	291	3	1975	1975	NUM
ajst-27738	291	4	,	,	PUNCT
ajst-27738	291	5	11(285	11(285	NOUN
ajst-27738	291	6	-	-	SYM
ajst-27738	291	7	296	296	NUM
ajst-27738	291	8	):	):	PUNCT
ajst-27738	291	9	23	23	NUM
ajst-27738	291	10	-	-	SYM
ajst-27738	291	11	27	27	NUM
ajst-27738	291	12	.	.	PUNCT
ajst-27738	292	1	[	[	X
ajst-27738	292	2	22	22	NUM
ajst-27738	292	3	]	]	X
ajst-27738	292	4	vincent	vincent	PROPN
ajst-27738	292	5	l	l	PROPN
ajst-27738	292	6	,	,	PUNCT
ajst-27738	292	7	soille	soille	NOUN
ajst-27738	292	8	p.	p.	NOUN
ajst-27738	292	9	watersheds	watershed	NOUN
ajst-27738	292	10	in	in	ADP
ajst-27738	292	11	digital	digital	ADJ
ajst-27738	292	12	spaces	space	NOUN
ajst-27738	292	13	:	:	PUNCT
ajst-27738	292	14	an	an	DET
ajst-27738	292	15	efficient	efficient	ADJ
ajst-27738	292	16	algorithm	algorithm	NOUN
ajst-27738	292	17	based	base	VERB
ajst-27738	292	18	on	on	ADP
ajst-27738	292	19	immersion	immersion	NOUN
ajst-27738	292	20	simulations	simulation	NOUN
ajst-27738	293	1	[	[	X
ajst-27738	293	2	j	j	X
ajst-27738	293	3	]	]	X
ajst-27738	293	4	.	.	PUNCT
ajst-27738	294	1	ieee	ieee	NOUN
ajst-27738	294	2	transactions	transaction	NOUN
ajst-27738	294	3	on	on	ADP
ajst-27738	294	4	pattern	pattern	NOUN
ajst-27738	294	5	analysis	analysis	NOUN
ajst-27738	294	6	and	and	CCONJ
ajst-27738	294	7	machine	machine	NOUN
ajst-27738	294	8	intelligence	intelligence	NOUN
ajst-27738	294	9	,	,	PUNCT
ajst-27738	294	10	1991	1991	NUM
ajst-27738	294	11	,	,	PUNCT
ajst-27738	294	12	13(06	13(06	NUM
ajst-27738	294	13	):	):	PUNCT
ajst-27738	294	14	583	583	NUM
ajst-27738	294	15	-	-	SYM
ajst-27738	294	16	598	598	NUM
ajst-27738	294	17	.	.	PUNCT
ajst-27738	295	1	[	[	X
ajst-27738	295	2	23	23	NUM
ajst-27738	295	3	]	]	X
ajst-27738	295	4	ren	ren	PROPN
ajst-27738	295	5	,	,	PUNCT
ajst-27738	295	6	malik	malik	PROPN
ajst-27738	295	7	.	.	PUNCT
ajst-27738	296	1	learning	learn	VERB
ajst-27738	296	2	a	a	DET
ajst-27738	296	3	classification	classification	NOUN
ajst-27738	296	4	model	model	NOUN
ajst-27738	296	5	for	for	ADP
ajst-27738	296	6	segmentation	segmentation	NOUN
ajst-27738	296	7	[	[	X
ajst-27738	296	8	c	c	X
ajst-27738	296	9	]	]	PUNCT
ajst-27738	296	10	.	.	PUNCT
ajst-27738	297	1	ieee	ieee	PROPN
ajst-27738	297	2	international	international	PROPN
ajst-27738	297	3	conference	conference	NOUN
ajst-27738	297	4	on	on	ADP
ajst-27738	297	5	computer	computer	NOUN
ajst-27738	297	6	vision	vision	NOUN
ajst-27738	297	7	,	,	PUNCT
ajst-27738	297	8	2003	2003	NUM
ajst-27738	297	9	:	:	PUNCT
ajst-27738	297	10	10	10	NUM
ajst-27738	297	11	-	-	SYM
ajst-27738	297	12	17	17	NUM
ajst-27738	297	13	vol	vol	NOUN
ajst-27738	297	14	.	.	PUNCT
ajst-27738	298	1	1	1	NUM
ajst-27738	298	2	.	.	PUNCT
ajst-27738	299	1	[	[	X
ajst-27738	299	2	24	24	NUM
ajst-27738	299	3	]	]	PUNCT
ajst-27738	299	4	barbu	barbu	PROPN
ajst-27738	299	5	a.	a.	NOUN
ajst-27738	299	6	training	training	NOUN
ajst-27738	299	7	an	an	DET
ajst-27738	299	8	active	active	ADJ
ajst-27738	299	9	random	random	ADJ
ajst-27738	299	10	field	field	NOUN
ajst-27738	299	11	for	for	ADP
ajst-27738	299	12	real	real	ADJ
ajst-27738	299	13	-	-	PUNCT
ajst-27738	299	14	time	time	NOUN
ajst-27738	299	15	image	image	NOUN
ajst-27738	299	16	denoising	denoise	VERB
ajst-27738	299	17	[	[	X
ajst-27738	299	18	j	j	X
ajst-27738	299	19	]	]	X
ajst-27738	299	20	.	.	PUNCT
ajst-27738	300	1	ieee	ieee	NOUN
ajst-27738	300	2	transactions	transaction	NOUN
ajst-27738	300	3	on	on	ADP
ajst-27738	300	4	image	image	NOUN
ajst-27738	300	5	processing	processing	NOUN
ajst-27738	300	6	,	,	PUNCT
ajst-27738	300	7	2009	2009	NUM
ajst-27738	300	8	,	,	PUNCT
ajst-27738	300	9	18(11	18(11	NUM
ajst-27738	300	10	):	):	PUNCT
ajst-27738	300	11	2451	2451	NUM
ajst-27738	300	12	-	-	SYM
ajst-27738	300	13	2462	2462	NUM
ajst-27738	300	14	.	.	PUNCT
ajst-27738	301	1	[	[	X
ajst-27738	301	2	25	25	NUM
ajst-27738	301	3	]	]	PUNCT
ajst-27738	301	4	badrinarayanan	badrinarayanan	NOUN
ajst-27738	301	5	v	v	PROPN
ajst-27738	301	6	,	,	PUNCT
ajst-27738	301	7	kendall	kendall	PROPN
ajst-27738	301	8	a	a	PROPN
ajst-27738	301	9	,	,	PUNCT
ajst-27738	301	10	cipolla	cipolla	PROPN
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ajst-27738	301	16	convolutional	convolutional	ADJ
ajst-27738	301	17	encoder	encoder	NOUN
ajst-27738	301	18	-	-	PUNCT
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ajst-27738	301	20	architecture	architecture	NOUN
ajst-27738	301	21	for	for	ADP
ajst-27738	301	22	image	image	NOUN
ajst-27738	301	23	segmentation	segmentation	NOUN
ajst-27738	302	1	[	[	X
ajst-27738	302	2	j	j	X
ajst-27738	302	3	]	]	X
ajst-27738	302	4	.	.	PUNCT
ajst-27738	303	1	ieee	ieee	NOUN
ajst-27738	303	2	transactions	transaction	NOUN
ajst-27738	303	3	on	on	ADP
ajst-27738	303	4	pattern	pattern	NOUN
ajst-27738	303	5	analysis	analysis	NOUN
ajst-27738	303	6	and	and	CCONJ
ajst-27738	303	7	machine	machine	NOUN
ajst-27738	303	8	intelligence	intelligence	NOUN
ajst-27738	303	9	,	,	PUNCT
ajst-27738	303	10	2017	2017	NUM
ajst-27738	303	11	,	,	PUNCT
ajst-27738	303	12	39(12	39(12	NUM
ajst-27738	303	13	):	):	PUNCT
ajst-27738	303	14	2481	2481	NUM
ajst-27738	303	15	-	-	SYM
ajst-27738	303	16	2495	2495	NUM
ajst-27738	303	17	.	.	PUNCT
ajst-27738	304	1	[	[	X
ajst-27738	304	2	26	26	NUM
ajst-27738	304	3	]	]	PUNCT
ajst-27738	304	4	ronneberger	ronneberger	NOUN
ajst-27738	304	5	o	o	NOUN
ajst-27738	304	6	,	,	PUNCT
ajst-27738	304	7	fischer	fischer	PROPN
ajst-27738	304	8	p	p	PROPN
ajst-27738	304	9	,	,	PUNCT
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ajst-27738	304	11	t.	t.	PROPN
ajst-27738	304	12	u	u	PROPN
ajst-27738	304	13	-	-	NOUN
ajst-27738	304	14	net	net	ADJ
ajst-27738	304	15	:	:	PUNCT
ajst-27738	304	16	convolutional	convolutional	ADJ
ajst-27738	304	17	networks	network	NOUN
ajst-27738	304	18	for	for	ADP
ajst-27738	304	19	biomedical	biomedical	ADJ
ajst-27738	304	20	image	image	NOUN
ajst-27738	304	21	segmentation	segmentation	NOUN
ajst-27738	305	1	[	[	X
ajst-27738	305	2	c	c	X
ajst-27738	305	3	]	]	PUNCT
ajst-27738	305	4	.	.	PUNCT
ajst-27738	306	1	medical	medical	ADJ
ajst-27738	306	2	image	image	NOUN
ajst-27738	306	3	computing	computing	NOUN
ajst-27738	306	4	and	and	CCONJ
ajst-27738	306	5	computer	computer	NOUN
ajst-27738	306	6	-	-	PUNCT
ajst-27738	306	7	assisted	assist	VERB
ajst-27738	306	8	intervention	intervention	NOUN
ajst-27738	306	9	,	,	PUNCT
ajst-27738	306	10	2015	2015	NUM
ajst-27738	306	11	:	:	PUNCT
ajst-27738	306	12	234	234	NUM
ajst-27738	306	13	-	-	SYM
ajst-27738	306	14	241	241	NUM
ajst-27738	306	15	.	.	PUNCT
ajst-27738	307	1	[	[	X
ajst-27738	307	2	27	27	NUM
ajst-27738	307	3	]	]	X
ajst-27738	307	4	li	li	PROPN
ajst-27738	307	5	h	h	PROPN
ajst-27738	307	6	,	,	PUNCT
ajst-27738	307	7	xiong	xiong	PROPN
ajst-27738	307	8	p	p	PROPN
ajst-27738	307	9	,	,	PUNCT
ajst-27738	307	10	fan	fan	PROPN
ajst-27738	307	11	h	h	PROPN
ajst-27738	307	12	,	,	PUNCT
ajst-27738	307	13	et	et	PROPN
ajst-27738	307	14	al	al	PROPN
ajst-27738	307	15	.	.	PUNCT
ajst-27738	307	16	dfanet	dfanet	PROPN
ajst-27738	307	17	:	:	PUNCT
ajst-27738	307	18	deep	deep	ADJ
ajst-27738	307	19	feature	feature	NOUN
ajst-27738	307	20	aggregation	aggregation	NOUN
ajst-27738	307	21	for	for	ADP
ajst-27738	307	22	real	real	ADJ
ajst-27738	307	23	-	-	PUNCT
ajst-27738	307	24	time	time	NOUN
ajst-27738	307	25	semantic	semantic	ADJ
ajst-27738	307	26	segmentation	segmentation	NOUN
ajst-27738	308	1	[	[	X
ajst-27738	308	2	c	c	X
ajst-27738	308	3	]	]	PUNCT
ajst-27738	308	4	.	.	PUNCT
ajst-27738	309	1	ieee	ieee	PROPN
ajst-27738	309	2	conference	conference	PROPN
ajst-27738	309	3	on	on	ADP
ajst-27738	309	4	computer	computer	NOUN
ajst-27738	309	5	vision	vision	NOUN
ajst-27738	309	6	and	and	CCONJ
ajst-27738	309	7	pattern	pattern	NOUN
ajst-27738	309	8	recognition	recognition	NOUN
ajst-27738	309	9	,	,	PUNCT
ajst-27738	309	10	2019	2019	NUM
ajst-27738	309	11	:	:	PUNCT
ajst-27738	309	12	9522	9522	NUM
ajst-27738	309	13	-	-	SYM
ajst-27738	309	14	9531	9531	NUM
ajst-27738	309	15	.	.	PUNCT
ajst-27738	310	1	[	[	X
ajst-27738	310	2	28	28	NUM
ajst-27738	310	3	]	]	X
ajst-27738	310	4	hong	hong	PROPN
ajst-27738	310	5	y	y	PROPN
ajst-27738	310	6	,	,	PUNCT
ajst-27738	310	7	pan	pan	NOUN
ajst-27738	310	8	h	h	PROPN
ajst-27738	310	9	,	,	PUNCT
ajst-27738	310	10	sun	sun	PROPN
ajst-27738	310	11	w	w	PROPN
ajst-27738	310	12	,	,	PUNCT
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ajst-27738	310	14	al	al	PROPN
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ajst-27738	311	2	dual	dual	ADJ
ajst-27738	311	3	-	-	PUNCT
ajst-27738	311	4	resolution	resolution	NOUN
ajst-27738	311	5	networks	network	NOUN
ajst-27738	311	6	for	for	ADP
ajst-27738	311	7	real	real	ADJ
ajst-27738	311	8	-	-	PUNCT
ajst-27738	311	9	time	time	NOUN
ajst-27738	311	10	and	and	CCONJ
ajst-27738	311	11	accurate	accurate	ADJ
ajst-27738	311	12	semantic	semantic	ADJ
ajst-27738	311	13	segmentation	segmentation	NOUN
ajst-27738	311	14	of	of	ADP
ajst-27738	311	15	road	road	NOUN
ajst-27738	311	16	scenes	scene	NOUN
ajst-27738	312	1	[	[	X
ajst-27738	312	2	j	j	X
ajst-27738	312	3	]	]	X
ajst-27738	312	4	.	.	PUNCT
ajst-27738	313	1	arxiv	arxiv	PROPN
ajst-27738	313	2	preprint	preprint	PROPN
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ajst-27738	313	4	,	,	PUNCT
ajst-27738	313	5	2021	2021	NUM
ajst-27738	313	6	.	.	PUNCT
ajst-27738	314	1	[	[	X
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ajst-27738	314	5	j	j	PROPN
ajst-27738	314	6	,	,	PUNCT
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ajst-27738	314	8	j	j	PROPN
ajst-27738	314	9	,	,	PUNCT
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ajst-27738	314	11	h	h	NOUN
ajst-27738	314	12	,	,	PUNCT
ajst-27738	314	13	et	et	PROPN
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ajst-27738	314	15	.	.	PUNCT
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ajst-27738	315	4	for	for	ADP
ajst-27738	315	5	scene	scene	NOUN
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ajst-27738	316	1	[	[	X
ajst-27738	316	2	c	c	X
ajst-27738	316	3	]	]	PUNCT
ajst-27738	316	4	.	.	PUNCT
ajst-27738	317	1	ieee	ieee	PROPN
ajst-27738	317	2	conference	conference	PROPN
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ajst-27738	317	4	computer	computer	NOUN
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ajst-27738	317	8	recognition	recognition	NOUN
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ajst-27738	317	11	:	:	PUNCT
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ajst-27738	317	13	-	-	SYM
ajst-27738	317	14	3154	3154	NUM
ajst-27738	317	15	.	.	PUNCT
ajst-27738	318	1	[	[	X
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ajst-27738	318	9	,	,	PUNCT
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ajst-27738	318	11	l	l	PROPN
ajst-27738	318	12	,	,	PUNCT
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ajst-27738	318	14	al	al	PROPN
ajst-27738	318	15	.	.	PROPN
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ajst-27738	318	17	:	:	PUNCT
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ajst-27738	318	19	-	-	PUNCT
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ajst-27738	318	25	[	[	X
ajst-27738	318	26	c	c	X
ajst-27738	318	27	]	]	PUNCT
ajst-27738	318	28	.	.	PUNCT
ajst-27738	319	1	ieee	ieee	PROPN
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ajst-27738	319	9	:	:	PUNCT
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ajst-27738	319	11	-	-	SYM
ajst-27738	319	12	612	612	NUM
ajst-27738	319	13	.	.	PUNCT
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ajst-27738	321	2	c	c	X
ajst-27738	321	3	]	]	PUNCT
ajst-27738	321	4	.	.	PUNCT
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ajst-27738	322	13	-	-	SYM
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ajst-27738	322	15	.	.	PUNCT
ajst-27738	323	1	[	[	X
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ajst-27738	323	3	]	]	PUNCT
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ajst-27738	325	1	[	[	X
ajst-27738	325	2	c	c	X
ajst-27738	325	3	]	]	PUNCT
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ajst-27738	326	11	:	:	SYM
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ajst-27738	326	13	-	-	SYM
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ajst-27738	326	15	.	.	PUNCT
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ajst-27738	328	3	]	]	X
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ajst-27738	330	1	[	[	X
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ajst-27738	330	3	]	]	PUNCT
ajst-27738	330	4	.	.	PUNCT
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ajst-27738	331	13	-	-	SYM
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ajst-27738	331	15	.	.	PUNCT
ajst-27738	332	1	[	[	X
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ajst-27738	333	10	c	c	X
ajst-27738	333	11	]	]	PUNCT
ajst-27738	333	12	.	.	PUNCT
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ajst-27738	334	11	:	:	PUNCT
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ajst-27738	334	13	-	-	SYM
ajst-27738	334	14	3223	3223	NUM
ajst-27738	334	15	.	.	PUNCT
ajst-27738	335	1	[	[	X
ajst-27738	335	2	35	35	NUM
ajst-27738	335	3	]	]	X
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ajst-27738	335	24	point	point	NOUN
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ajst-27738	336	2	c	c	X
ajst-27738	336	3	]	]	PUNCT
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ajst-27738	338	3	]	]	X
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ajst-27738	340	3	]	]	PUNCT
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ajst-27738	342	1	[	[	X
ajst-27738	342	2	37	37	NUM
ajst-27738	342	3	]	]	PUNCT
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ajst-27738	343	3	]	]	PUNCT
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ajst-27738	345	14	al	al	PROPN
ajst-27738	345	15	.	.	PUNCT
ajst-27738	345	16	lrnnet	lrnnet	PROPN
ajst-27738	345	17	:	:	PUNCT
ajst-27738	345	18	a	a	DET
ajst-27738	345	19	light	light	ADJ
ajst-27738	345	20	-	-	PUNCT
ajst-27738	345	21	weighted	weight	VERB
ajst-27738	345	22	network	network	NOUN
ajst-27738	345	23	with	with	ADP
ajst-27738	345	24	efficient	efficient	ADJ
ajst-27738	345	25	reduced	reduce	VERB
ajst-27738	345	26	non	non	ADJ
ajst-27738	345	27	-	-	ADJ
ajst-27738	345	28	local	local	ADJ
ajst-27738	345	29	operation	operation	NOUN
ajst-27738	345	30	for	for	ADP
ajst-27738	345	31	real	real	ADJ
ajst-27738	345	32	-	-	PUNCT
ajst-27738	345	33	time	time	NOUN
ajst-27738	345	34	semantic	semantic	ADJ
ajst-27738	345	35	segmentation	segmentation	NOUN
ajst-27738	345	36	[	[	X
ajst-27738	345	37	c	c	X
ajst-27738	345	38	]	]	PUNCT
ajst-27738	345	39	.	.	PUNCT
ajst-27738	346	1	ieee	ieee	PROPN
ajst-27738	346	2	international	international	PROPN
ajst-27738	346	3	conference	conference	NOUN
ajst-27738	346	4	on	on	ADP
ajst-27738	346	5	multimedia	multimedia	NOUN
ajst-27738	346	6	and	and	CCONJ
ajst-27738	346	7	expo	expo	NOUN
ajst-27738	346	8	workshops	workshop	NOUN
ajst-27738	346	9	,	,	PUNCT
ajst-27738	346	10	2020	2020	NUM
ajst-27738	346	11	:	:	PUNCT
ajst-27738	346	12	1	1	NUM
ajst-27738	346	13	-	-	SYM
ajst-27738	346	14	6	6	NUM
ajst-27738	346	15	.	.	PUNCT
ajst-27738	347	1	[	[	X
ajst-27738	347	2	39	39	NUM
ajst-27738	347	3	]	]	PUNCT
ajst-27738	347	4	dong	dong	NOUN
ajst-27738	347	5	g	g	PROPN
ajst-27738	347	6	,	,	PUNCT
ajst-27738	347	7	yan	yan	PROPN
ajst-27738	347	8	y	y	PROPN
ajst-27738	347	9	,	,	PUNCT
ajst-27738	347	10	shen	shen	PROPN
ajst-27738	348	1	c	c	X
ajst-27738	348	2	,	,	PUNCT
ajst-27738	348	3	et	et	PROPN
ajst-27738	348	4	al	al	PROPN
ajst-27738	348	5	.	.	PUNCT
ajst-27738	349	1	real	real	ADJ
ajst-27738	349	2	-	-	PUNCT
ajst-27738	349	3	time	time	NOUN
ajst-27738	349	4	high	high	ADJ
ajst-27738	349	5	-	-	PUNCT
ajst-27738	349	6	performance	performance	NOUN
ajst-27738	349	7	semantic	semantic	ADJ
ajst-27738	349	8	image	image	NOUN
ajst-27738	349	9	segmentation	segmentation	NOUN
ajst-27738	349	10	of	of	ADP
ajst-27738	349	11	urban	urban	PROPN
ajst-27738	349	12	street	street	NOUN
ajst-27738	349	13	scenes	scene	NOUN
ajst-27738	350	1	[	[	X
ajst-27738	350	2	j	j	X
ajst-27738	350	3	]	]	X
ajst-27738	350	4	.	.	PUNCT
ajst-27738	351	1	ieee	ieee	NOUN
ajst-27738	351	2	transactions	transaction	NOUN
ajst-27738	351	3	on	on	ADP
ajst-27738	351	4	intelligent	intelligent	ADJ
ajst-27738	351	5	transportation	transportation	NOUN
ajst-27738	351	6	systems	system	NOUN
ajst-27738	351	7	,	,	PUNCT
ajst-27738	351	8	2020	2020	NUM
ajst-27738	351	9	,	,	PUNCT
ajst-27738	351	10	22(6	22(6	NUM
ajst-27738	351	11	):	):	PUNCT
ajst-27738	351	12	3258	3258	NUM
ajst-27738	351	13	-	-	SYM
ajst-27738	351	14	3274	3274	NUM
ajst-27738	351	15	.	.	PUNCT
ajst-27738	352	1	[	[	X
ajst-27738	352	2	40	40	NUM
ajst-27738	352	3	]	]	X
ajst-27738	352	4	peng	peng	PROPN
ajst-27738	352	5	j	j	PROPN
ajst-27738	352	6	,	,	PUNCT
ajst-27738	352	7	liu	liu	PROPN
ajst-27738	352	8	y	y	PROPN
ajst-27738	352	9	,	,	PUNCT
ajst-27738	352	10	tang	tang	PROPN
ajst-27738	352	11	s	s	PROPN
ajst-27738	352	12	,	,	PUNCT
ajst-27738	352	13	et	et	PROPN
ajst-27738	352	14	al	al	PROPN
ajst-27738	352	15	.	.	PROPN
ajst-27738	353	1	pp	pp	PROPN
ajst-27738	353	2	-	-	PUNCT
ajst-27738	353	3	liteseg	liteseg	NOUN
ajst-27738	353	4	:	:	PUNCT
ajst-27738	353	5	a	a	DET
ajst-27738	353	6	superior	superior	ADJ
ajst-27738	353	7	real	real	ADJ
ajst-27738	353	8	-	-	PUNCT
ajst-27738	353	9	time	time	NOUN
ajst-27738	353	10	semantic	semantic	ADJ
ajst-27738	353	11	segmentation	segmentation	NOUN
ajst-27738	353	12	model	model	NOUN
ajst-27738	353	13	.	.	PUNCT
ajst-27738	354	1	arxiv	arxiv	PROPN
ajst-27738	354	2	2022[j	2022[j	NUM
ajst-27738	354	3	]	]	PUNCT
ajst-27738	354	4	.	.	PUNCT
ajst-27738	355	1	arxiv	arxiv	PROPN
ajst-27738	355	2	preprint	preprint	NOUN
ajst-27738	355	3	arxiv:2204.02681	arxiv:2204.02681	NOUN
ajst-27738	355	4	.	.	PUNCT
ajst-27738	356	1	[	[	X
ajst-27738	356	2	41	41	NUM
ajst-27738	356	3	]	]	PUNCT
ajst-27738	356	4	paszke	paszke	NOUN
ajst-27738	356	5	a	a	PRON
ajst-27738	356	6	,	,	PUNCT
ajst-27738	356	7	chaurasia	chaurasia	PROPN
ajst-27738	356	8	a	a	PROPN
ajst-27738	356	9	,	,	PUNCT
ajst-27738	356	10	kim	kim	PROPN
ajst-27738	356	11	s	s	PROPN
ajst-27738	356	12	,	,	PUNCT
ajst-27738	356	13	et	et	PROPN
ajst-27738	356	14	al	al	PROPN
ajst-27738	356	15	.	.	PUNCT
ajst-27738	357	1	enet	enet	PROPN
ajst-27738	357	2	:	:	PUNCT
ajst-27738	357	3	a	a	DET
ajst-27738	357	4	deep	deep	ADJ
ajst-27738	357	5	neural	neural	ADJ
ajst-27738	357	6	network	network	NOUN
ajst-27738	357	7	architecture	architecture	NOUN
ajst-27738	357	8	for	for	ADP
ajst-27738	357	9	real	real	ADJ
ajst-27738	357	10	-	-	PUNCT
ajst-27738	357	11	time	time	NOUN
ajst-27738	357	12	semantic	semantic	ADJ
ajst-27738	357	13	segmentation	segmentation	NOUN
ajst-27738	358	1	[	[	X
ajst-27738	358	2	j	j	X
ajst-27738	358	3	]	]	X
ajst-27738	358	4	.	.	PUNCT
ajst-27738	359	1	arxiv	arxiv	PROPN
ajst-27738	359	2	preprint	preprint	NOUN
ajst-27738	359	3	arxiv:1606.02147	arxiv:1606.02147	NOUN
ajst-27738	359	4	,	,	PUNCT
ajst-27738	359	5	2016	2016	NUM
ajst-27738	359	6	.	.	PUNCT