id	sid	tid	token	lemma	pos
ajst-30179	1	1	academic	academic	ADJ
ajst-30179	1	2	journal	journal	NOUN
ajst-30179	1	3	of	of	ADP
ajst-30179	1	4	science	science	NOUN
ajst-30179	1	5	and	and	CCONJ
ajst-30179	1	6	technology	technology	NOUN
ajst-30179	1	7	issn	issn	NOUN
ajst-30179	1	8	:	:	PUNCT
ajst-30179	1	9	2771	2771	NUM
ajst-30179	1	10	-	-	SYM
ajst-30179	1	11	3032	3032	NUM
ajst-30179	1	12	|	|	NOUN
ajst-30179	1	13	vol	vol	NOUN
ajst-30179	1	14	.	.	PUNCT
ajst-30179	2	1	14	14	NUM
ajst-30179	2	2	,	,	PUNCT
ajst-30179	2	3	no	no	INTJ
ajst-30179	2	4	.	.	NOUN
ajst-30179	2	5	3	3	NUM
ajst-30179	2	6	,	,	PUNCT
ajst-30179	2	7	2025	2025	NUM
ajst-30179	2	8	61	61	NUM
ajst-30179	2	9	research	research	NOUN
ajst-30179	2	10	on	on	ADP
ajst-30179	2	11	semantic	semantic	ADJ
ajst-30179	2	12	segmentation	segmentation	NOUN
ajst-30179	2	13	algorithms	algorithm	NOUN
ajst-30179	2	14	for	for	ADP
ajst-30179	2	15	street	street	NOUN
ajst-30179	2	16	scenes	scene	NOUN
ajst-30179	2	17	linlin	linlin	PROPN
ajst-30179	2	18	liu	liu	PROPN
ajst-30179	2	19	*	*	PROPN
ajst-30179	2	20	school	school	NOUN
ajst-30179	2	21	of	of	ADP
ajst-30179	2	22	computer	computer	NOUN
ajst-30179	2	23	science	science	NOUN
ajst-30179	2	24	and	and	CCONJ
ajst-30179	2	25	technology	technology	NOUN
ajst-30179	2	26	,	,	PUNCT
ajst-30179	2	27	henan	henan	PROPN
ajst-30179	2	28	polytechnic	polytechnic	PROPN
ajst-30179	2	29	university	university	PROPN
ajst-30179	2	30	,	,	PUNCT
ajst-30179	2	31	jiaozuo	jiaozuo	PROPN
ajst-30179	2	32	,	,	PUNCT
ajst-30179	2	33	henan	henan	PROPN
ajst-30179	2	34	45400	45400	NUM
ajst-30179	2	35	,	,	PUNCT
ajst-30179	2	36	china	china	PROPN
ajst-30179	2	37	*	*	PUNCT
ajst-30179	2	38	corresponding	correspond	VERB
ajst-30179	2	39	author	author	NOUN
ajst-30179	2	40	:	:	PUNCT
ajst-30179	2	41	linlin	linlin	PROPN
ajst-30179	2	42	liu	liu	PROPN
ajst-30179	2	43	abstract	abstract	PROPN
ajst-30179	2	44	:	:	PUNCT
ajst-30179	2	45	some	some	DET
ajst-30179	2	46	advanced	advanced	ADJ
ajst-30179	2	47	semantic	semantic	ADJ
ajst-30179	2	48	segmentation	segmentation	NOUN
ajst-30179	2	49	models	model	NOUN
ajst-30179	2	50	often	often	ADV
ajst-30179	2	51	feature	feature	VERB
ajst-30179	2	52	deep	deep	ADJ
ajst-30179	2	53	network	network	NOUN
ajst-30179	2	54	structures	structure	NOUN
ajst-30179	2	55	and	and	CCONJ
ajst-30179	2	56	a	a	DET
ajst-30179	2	57	large	large	ADJ
ajst-30179	2	58	number	number	NOUN
ajst-30179	2	59	of	of	ADP
ajst-30179	2	60	parameters	parameter	NOUN
ajst-30179	2	61	,	,	PUNCT
ajst-30179	2	62	requiring	require	VERB
ajst-30179	2	63	significant	significant	ADJ
ajst-30179	2	64	memory	memory	NOUN
ajst-30179	2	65	and	and	CCONJ
ajst-30179	2	66	computational	computational	ADJ
ajst-30179	2	67	resources	resource	NOUN
ajst-30179	2	68	.	.	PUNCT
ajst-30179	3	1	this	this	PRON
ajst-30179	3	2	makes	make	VERB
ajst-30179	3	3	them	they	PRON
ajst-30179	3	4	difficult	difficult	ADJ
ajst-30179	3	5	to	to	PART
ajst-30179	3	6	run	run	VERB
ajst-30179	3	7	in	in	ADP
ajst-30179	3	8	real	real	ADJ
ajst-30179	3	9	-	-	PUNCT
ajst-30179	3	10	time	time	NOUN
ajst-30179	3	11	on	on	ADP
ajst-30179	3	12	devices	device	NOUN
ajst-30179	3	13	with	with	ADP
ajst-30179	3	14	limited	limited	ADJ
ajst-30179	3	15	computational	computational	ADJ
ajst-30179	3	16	capacity	capacity	NOUN
ajst-30179	3	17	.	.	PUNCT
ajst-30179	4	1	the	the	DET
ajst-30179	4	2	model	model	NOUN
ajst-30179	4	3	may	may	AUX
ajst-30179	4	4	fail	fail	VERB
ajst-30179	4	5	to	to	PART
ajst-30179	4	6	complete	complete	VERB
ajst-30179	4	7	the	the	DET
ajst-30179	4	8	semantic	semantic	ADJ
ajst-30179	4	9	segmentation	segmentation	NOUN
ajst-30179	4	10	task	task	NOUN
ajst-30179	4	11	within	within	ADP
ajst-30179	4	12	the	the	DET
ajst-30179	4	13	required	required	ADJ
ajst-30179	4	14	timeframe	timeframe	NOUN
ajst-30179	4	15	,	,	PUNCT
ajst-30179	4	16	while	while	SCONJ
ajst-30179	4	17	the	the	DET
ajst-30179	4	18	complex	complex	ADJ
ajst-30179	4	19	feature	feature	NOUN
ajst-30179	4	20	extraction	extraction	NOUN
ajst-30179	4	21	process	process	NOUN
ajst-30179	4	22	further	far	ADV
ajst-30179	4	23	increases	increase	VERB
ajst-30179	4	24	computational	computational	ADJ
ajst-30179	4	25	demands	demand	NOUN
ajst-30179	4	26	and	and	CCONJ
ajst-30179	4	27	processing	processing	NOUN
ajst-30179	4	28	time	time	NOUN
ajst-30179	4	29	,	,	PUNCT
ajst-30179	4	30	reducing	reduce	VERB
ajst-30179	4	31	real	real	ADJ
ajst-30179	4	32	-	-	PUNCT
ajst-30179	4	33	time	time	NOUN
ajst-30179	4	34	performance	performance	NOUN
ajst-30179	4	35	.	.	PUNCT
ajst-30179	5	1	this	this	PRON
ajst-30179	5	2	,	,	PUNCT
ajst-30179	5	3	in	in	ADP
ajst-30179	5	4	turn	turn	NOUN
ajst-30179	5	5	,	,	PUNCT
ajst-30179	5	6	slows	slow	VERB
ajst-30179	5	7	system	system	NOUN
ajst-30179	5	8	response	response	NOUN
ajst-30179	5	9	speed	speed	NOUN
ajst-30179	5	10	and	and	CCONJ
ajst-30179	5	11	negatively	negatively	ADV
ajst-30179	5	12	impacts	impact	VERB
ajst-30179	5	13	practical	practical	ADJ
ajst-30179	5	14	applications	application	NOUN
ajst-30179	5	15	.	.	PUNCT
ajst-30179	6	1	to	to	PART
ajst-30179	6	2	address	address	VERB
ajst-30179	6	3	the	the	DET
ajst-30179	6	4	trade	trade	NOUN
ajst-30179	6	5	-	-	PUNCT
ajst-30179	6	6	off	off	NOUN
ajst-30179	6	7	between	between	ADP
ajst-30179	6	8	segmentation	segmentation	NOUN
ajst-30179	6	9	accuracy	accuracy	NOUN
ajst-30179	6	10	and	and	CCONJ
ajst-30179	6	11	real	real	ADJ
ajst-30179	6	12	-	-	PUNCT
ajst-30179	6	13	time	time	NOUN
ajst-30179	6	14	performance	performance	NOUN
ajst-30179	6	15	,	,	PUNCT
ajst-30179	6	16	this	this	DET
ajst-30179	6	17	paper	paper	NOUN
ajst-30179	6	18	proposes	propose	VERB
ajst-30179	6	19	an	an	DET
ajst-30179	6	20	up	up	ADV
ajst-30179	6	21	-	-	PUNCT
ajst-30179	6	22	sampling	sample	VERB
ajst-30179	6	23	module	module	NOUN
ajst-30179	6	24	-	-	PUNCT
ajst-30179	6	25	the	the	DET
ajst-30179	6	26	scaleaware	scaleaware	NOUN
ajst-30179	6	27	depth	depth	NOUN
ajst-30179	6	28	wise	wise	ADJ
ajst-30179	6	29	separable	separable	ADJ
ajst-30179	6	30	convolution	convolution	NOUN
ajst-30179	6	31	attention	attention	NOUN
ajst-30179	6	32	module	module	NOUN
ajst-30179	6	33	(	(	PUNCT
ajst-30179	6	34	sadam	sadam	PROPN
ajst-30179	6	35	)	)	PUNCT
ajst-30179	6	36	.	.	PUNCT
ajst-30179	7	1	this	this	DET
ajst-30179	7	2	module	module	NOUN
ajst-30179	7	3	enhances	enhance	VERB
ajst-30179	7	4	the	the	DET
ajst-30179	7	5	model	model	NOUN
ajst-30179	7	6	’s	’s	PART
ajst-30179	7	7	ability	ability	NOUN
ajst-30179	7	8	to	to	PART
ajst-30179	7	9	focus	focus	VERB
ajst-30179	7	10	on	on	ADP
ajst-30179	7	11	key	key	ADJ
ajst-30179	7	12	regions	region	NOUN
ajst-30179	7	13	,	,	PUNCT
ajst-30179	7	14	improving	improve	VERB
ajst-30179	7	15	feature	feature	NOUN
ajst-30179	7	16	extraction	extraction	NOUN
ajst-30179	7	17	efficiency	efficiency	NOUN
ajst-30179	7	18	while	while	SCONJ
ajst-30179	7	19	reducing	reduce	VERB
ajst-30179	7	20	model	model	NOUN
ajst-30179	7	21	complexity	complexity	NOUN
ajst-30179	7	22	and	and	CCONJ
ajst-30179	7	23	boosting	boost	VERB
ajst-30179	7	24	inference	inference	NOUN
ajst-30179	7	25	speed	speed	NOUN
ajst-30179	7	26	without	without	ADP
ajst-30179	7	27	compromising	compromise	VERB
ajst-30179	7	28	segmentation	segmentation	NOUN
ajst-30179	7	29	accuracy	accuracy	NOUN
ajst-30179	7	30	.	.	PUNCT
ajst-30179	8	1	additionally	additionally	ADV
ajst-30179	8	2	,	,	PUNCT
ajst-30179	8	3	a	a	DET
ajst-30179	8	4	semantic	semantic	ADJ
ajst-30179	8	5	-	-	PUNCT
ajst-30179	8	6	assisted	assist	VERB
ajst-30179	8	7	optimization	optimization	NOUN
ajst-30179	8	8	branch	branch	NOUN
ajst-30179	8	9	is	be	AUX
ajst-30179	8	10	introduced	introduce	VERB
ajst-30179	8	11	to	to	PART
ajst-30179	8	12	incorporate	incorporate	VERB
ajst-30179	8	13	more	more	ADJ
ajst-30179	8	14	feature	feature	NOUN
ajst-30179	8	15	information	information	NOUN
ajst-30179	8	16	,	,	PUNCT
ajst-30179	8	17	enhancing	enhance	VERB
ajst-30179	8	18	the	the	DET
ajst-30179	8	19	model	model	NOUN
ajst-30179	8	20	’s	’s	PART
ajst-30179	8	21	representation	representation	NOUN
ajst-30179	8	22	capacity	capacity	NOUN
ajst-30179	8	23	and	and	CCONJ
ajst-30179	8	24	adaptability	adaptability	NOUN
ajst-30179	8	25	.	.	PUNCT
ajst-30179	9	1	furthermore	furthermore	ADV
ajst-30179	9	2	,	,	PUNCT
ajst-30179	9	3	the	the	DET
ajst-30179	9	4	loss	loss	NOUN
ajst-30179	9	5	function	function	NOUN
ajst-30179	9	6	is	be	AUX
ajst-30179	9	7	optimized	optimize	VERB
ajst-30179	9	8	to	to	PART
ajst-30179	9	9	improve	improve	VERB
ajst-30179	9	10	segmentation	segmentation	NOUN
ajst-30179	9	11	accuracy	accuracy	NOUN
ajst-30179	9	12	and	and	CCONJ
ajst-30179	9	13	completeness	completeness	NOUN
ajst-30179	9	14	.	.	PUNCT
ajst-30179	10	1	keywords	keyword	NOUN
ajst-30179	10	2	:	:	PUNCT
ajst-30179	10	3	deep	deep	ADJ
ajst-30179	10	4	learning	learning	NOUN
ajst-30179	10	5	;	;	PUNCT
ajst-30179	10	6	semantic	semantic	ADJ
ajst-30179	10	7	segmentation	segmentation	NOUN
ajst-30179	10	8	;	;	PUNCT
ajst-30179	10	9	upsampling	upsample	VERB
ajst-30179	10	10	module	module	NOUN
ajst-30179	10	11	.	.	PUNCT
ajst-30179	11	1	1	1	X
ajst-30179	11	2	.	.	X
ajst-30179	11	3	introduce	introduce	VERB
ajst-30179	11	4	semantic	semantic	ADJ
ajst-30179	11	5	segmentation	segmentation	NOUN
ajst-30179	11	6	is	be	AUX
ajst-30179	11	7	a	a	DET
ajst-30179	11	8	computer	computer	NOUN
ajst-30179	11	9	vision	vision	NOUN
ajst-30179	11	10	technique	technique	NOUN
ajst-30179	11	11	for	for	ADP
ajst-30179	11	12	pixel	pixel	ADJ
ajst-30179	11	13	-	-	ADJ
ajst-30179	11	14	wise	wise	ADJ
ajst-30179	11	15	classification	classification	NOUN
ajst-30179	11	16	,	,	PUNCT
ajst-30179	11	17	aiming	aim	VERB
ajst-30179	11	18	to	to	PART
ajst-30179	11	19	achieve	achieve	VERB
ajst-30179	11	20	fine	fine	ADV
ajst-30179	11	21	-	-	PUNCT
ajst-30179	11	22	grained	grain	VERB
ajst-30179	11	23	scene	scene	NOUN
ajst-30179	11	24	analysis	analysis	NOUN
ajst-30179	11	25	and	and	CCONJ
ajst-30179	11	26	structured	structured	ADJ
ajst-30179	11	27	understanding	understanding	NOUN
ajst-30179	11	28	by	by	ADP
ajst-30179	11	29	assigning	assign	VERB
ajst-30179	11	30	each	each	DET
ajst-30179	11	31	pixel	pixel	NOUN
ajst-30179	11	32	in	in	ADP
ajst-30179	11	33	an	an	DET
ajst-30179	11	34	image	image	NOUN
ajst-30179	11	35	to	to	ADP
ajst-30179	11	36	a	a	DET
ajst-30179	11	37	specific	specific	ADJ
ajst-30179	11	38	semantic	semantic	ADJ
ajst-30179	11	39	category	category	NOUN
ajst-30179	11	40	(	(	PUNCT
ajst-30179	11	41	e.g.	e.g.	ADV
ajst-30179	11	42	,	,	PUNCT
ajst-30179	11	43	"	"	PUNCT
ajst-30179	11	44	vehicle	vehicle	NOUN
ajst-30179	11	45	,	,	PUNCT
ajst-30179	11	46	"	"	PUNCT
ajst-30179	11	47	"	"	PUNCT
ajst-30179	11	48	pedestrian	pedestrian	NOUN
ajst-30179	11	49	,	,	PUNCT
ajst-30179	11	50	"	"	PUNCT
ajst-30179	11	51	"	"	PUNCT
ajst-30179	11	52	road	road	NOUN
ajst-30179	11	53	"	"	PUNCT
ajst-30179	11	54	)	)	PUNCT
ajst-30179	11	55	.	.	PUNCT
ajst-30179	12	1	unlike	unlike	ADP
ajst-30179	12	2	object	object	NOUN
ajst-30179	12	3	detection	detection	NOUN
ajst-30179	12	4	,	,	PUNCT
ajst-30179	12	5	which	which	PRON
ajst-30179	12	6	primarily	primarily	ADV
ajst-30179	12	7	focuses	focus	VERB
ajst-30179	12	8	on	on	ADP
ajst-30179	12	9	localizing	localize	VERB
ajst-30179	12	10	objects	object	NOUN
ajst-30179	12	11	,	,	PUNCT
ajst-30179	12	12	semantic	semantic	ADJ
ajst-30179	12	13	segmentation	segmentation	NOUN
ajst-30179	12	14	requires	require	VERB
ajst-30179	12	15	algorithms	algorithm	NOUN
ajst-30179	12	16	to	to	PART
ajst-30179	12	17	differentiate	differentiate	VERB
ajst-30179	12	18	semantic	semantic	ADJ
ajst-30179	12	19	regions	region	NOUN
ajst-30179	12	20	at	at	ADP
ajst-30179	12	21	the	the	DET
ajst-30179	12	22	pixel	pixel	PROPN
ajst-30179	12	23	level	level	NOUN
ajst-30179	12	24	while	while	SCONJ
ajst-30179	12	25	ensuring	ensure	VERB
ajst-30179	12	26	spatial	spatial	ADJ
ajst-30179	12	27	consistency	consistency	NOUN
ajst-30179	12	28	within	within	ADP
ajst-30179	12	29	the	the	DET
ajst-30179	12	30	same	same	ADJ
ajst-30179	12	31	category	category	NOUN
ajst-30179	12	32	.	.	PUNCT
ajst-30179	13	1	deep	deep	ADJ
ajst-30179	13	2	learning	learning	NOUN
ajst-30179	13	3	-	-	PUNCT
ajst-30179	13	4	based	base	VERB
ajst-30179	13	5	semantic	semantic	ADJ
ajst-30179	13	6	segmentation	segmentation	NOUN
ajst-30179	13	7	methods	method	NOUN
ajst-30179	13	8	are	be	AUX
ajst-30179	13	9	typically	typically	ADV
ajst-30179	13	10	built	build	VERB
ajst-30179	13	11	upon	upon	SCONJ
ajst-30179	13	12	convolutional	convolutional	ADJ
ajst-30179	13	13	neural	neural	ADJ
ajst-30179	13	14	networks	network	NOUN
ajst-30179	13	15	(	(	PUNCT
ajst-30179	13	16	cnns)[1	cnns)[1	NOUN
ajst-30179	13	17	]	]	PUNCT
ajst-30179	13	18	.	.	PUNCT
ajst-30179	14	1	compared	compare	VERB
ajst-30179	14	2	to	to	ADP
ajst-30179	14	3	traditional	traditional	ADJ
ajst-30179	14	4	classification	classification	NOUN
ajst-30179	14	5	networks	network	NOUN
ajst-30179	14	6	,	,	PUNCT
ajst-30179	14	7	their	their	PRON
ajst-30179	14	8	key	key	ADJ
ajst-30179	14	9	innovation	innovation	NOUN
ajst-30179	14	10	lies	lie	VERB
ajst-30179	14	11	in	in	ADP
ajst-30179	14	12	adopting	adopt	VERB
ajst-30179	14	13	a	a	DET
ajst-30179	14	14	fully	fully	ADV
ajst-30179	14	15	convolutional	convolutional	ADJ
ajst-30179	14	16	design	design	NOUN
ajst-30179	14	17	,	,	PUNCT
ajst-30179	14	18	where	where	SCONJ
ajst-30179	14	19	convolutional	convolutional	ADJ
ajst-30179	14	20	layers	layer	NOUN
ajst-30179	14	21	replace	replace	VERB
ajst-30179	14	22	fully	fully	ADV
ajst-30179	14	23	connected	connect	VERB
ajst-30179	14	24	layers	layer	NOUN
ajst-30179	14	25	as	as	ADP
ajst-30179	14	26	the	the	DET
ajst-30179	14	27	classification	classification	NOUN
ajst-30179	14	28	output	output	NOUN
ajst-30179	14	29	,	,	PUNCT
ajst-30179	14	30	preserving	preserve	VERB
ajst-30179	14	31	the	the	DET
ajst-30179	14	32	spatial	spatial	ADJ
ajst-30179	14	33	dimension	dimension	NOUN
ajst-30179	14	34	of	of	ADP
ajst-30179	14	35	feature	feature	NOUN
ajst-30179	14	36	maps	map	NOUN
ajst-30179	14	37	.	.	PUNCT
ajst-30179	15	1	modern	modern	ADJ
ajst-30179	15	2	segmentation	segmentation	NOUN
ajst-30179	15	3	models	model	NOUN
ajst-30179	15	4	commonly	commonly	ADV
ajst-30179	15	5	employ	employ	VERB
ajst-30179	15	6	an	an	DET
ajst-30179	15	7	encoder	encoder	NOUN
ajst-30179	15	8	-	-	PUNCT
ajst-30179	15	9	decoder	decoder	NOUN
ajst-30179	15	10	structure[2].the	structure[2].the	PRON
ajst-30179	15	11	encoder	encoder	NOUN
ajst-30179	15	12	progressively	progressively	ADV
ajst-30179	15	13	reduces	reduce	VERB
ajst-30179	15	14	the	the	DET
ajst-30179	15	15	feature	feature	NOUN
ajst-30179	15	16	map	map	NOUN
ajst-30179	15	17	resolution	resolution	NOUN
ajst-30179	15	18	through	through	ADP
ajst-30179	15	19	multiple	multiple	ADJ
ajst-30179	15	20	convolutional	convolutional	ADJ
ajst-30179	15	21	and	and	CCONJ
ajst-30179	15	22	pooling	pool	VERB
ajst-30179	15	23	layers	layer	NOUN
ajst-30179	15	24	,	,	PUNCT
ajst-30179	15	25	extracting	extract	VERB
ajst-30179	15	26	high	high	ADJ
ajst-30179	15	27	-	-	PUNCT
ajst-30179	15	28	dimensional	dimensional	ADJ
ajst-30179	15	29	semantic	semantic	ADJ
ajst-30179	15	30	representations	representation	NOUN
ajst-30179	15	31	.	.	PUNCT
ajst-30179	16	1	the	the	DET
ajst-30179	16	2	decoder	decoder	NOUN
ajst-30179	16	3	restores	restore	VERB
ajst-30179	16	4	the	the	DET
ajst-30179	16	5	feature	feature	NOUN
ajst-30179	16	6	map	map	NOUN
ajst-30179	16	7	resolution	resolution	NOUN
ajst-30179	16	8	using	use	VERB
ajst-30179	16	9	transposed	transpose	VERB
ajst-30179	16	10	convolutions	convolution	NOUN
ajst-30179	16	11	(	(	PUNCT
ajst-30179	16	12	deconvolutions	deconvolution	NOUN
ajst-30179	16	13	)	)	PUNCT
ajst-30179	16	14	or	or	CCONJ
ajst-30179	16	15	upsampling	upsample	VERB
ajst-30179	16	16	techniques	technique	NOUN
ajst-30179	16	17	,	,	PUNCT
ajst-30179	16	18	ultimately	ultimately	ADV
ajst-30179	16	19	producing	produce	VERB
ajst-30179	16	20	a	a	DET
ajst-30179	16	21	pixel	pixel	ADJ
ajst-30179	16	22	-	-	ADJ
ajst-30179	16	23	wise	wise	ADJ
ajst-30179	16	24	classification	classification	NOUN
ajst-30179	16	25	output	output	NOUN
ajst-30179	16	26	that	that	PRON
ajst-30179	16	27	matches	match	VERB
ajst-30179	16	28	the	the	DET
ajst-30179	16	29	input	input	NOUN
ajst-30179	16	30	image	image	NOUN
ajst-30179	16	31	dimensions	dimension	NOUN
ajst-30179	16	32	.	.	PUNCT
ajst-30179	17	1	to	to	PART
ajst-30179	17	2	mitigate	mitigate	VERB
ajst-30179	17	3	detail	detail	NOUN
ajst-30179	17	4	loss	loss	NOUN
ajst-30179	17	5	during	during	ADP
ajst-30179	17	6	downsampling	downsampling	NOUN
ajst-30179	17	7	,	,	PUNCT
ajst-30179	17	8	classic	classic	ADJ
ajst-30179	17	9	models	model	NOUN
ajst-30179	17	10	like	like	ADP
ajst-30179	17	11	u	u	NOUN
ajst-30179	17	12	-	-	ADJ
ajst-30179	17	13	net	net	ADJ
ajst-30179	17	14	introduce	introduce	NOUN
ajst-30179	17	15	skip	skip	ADJ
ajst-30179	17	16	connections	connection	NOUN
ajst-30179	17	17	,	,	PUNCT
ajst-30179	17	18	fusing	fuse	VERB
ajst-30179	17	19	shallow	shallow	ADJ
ajst-30179	17	20	encoder	encoder	NOUN
ajst-30179	17	21	features	feature	VERB
ajst-30179	17	22	with	with	ADP
ajst-30179	17	23	deep	deep	ADJ
ajst-30179	17	24	decoder	decoder	NOUN
ajst-30179	17	25	features	feature	NOUN
ajst-30179	17	26	to	to	PART
ajst-30179	17	27	enhance	enhance	VERB
ajst-30179	17	28	edge	edge	NOUN
ajst-30179	17	29	segmentation	segmentation	NOUN
ajst-30179	17	30	accuracy	accuracy	NOUN
ajst-30179	17	31	.	.	PUNCT
ajst-30179	18	1	it	it	PRON
ajst-30179	18	2	is	be	AUX
ajst-30179	18	3	essential	essential	ADJ
ajst-30179	18	4	to	to	PART
ajst-30179	18	5	distinguish	distinguish	VERB
ajst-30179	18	6	semantic	semantic	ADJ
ajst-30179	18	7	segmentation	segmentation	NOUN
ajst-30179	18	8	from	from	ADP
ajst-30179	18	9	instance	instance	NOUN
ajst-30179	18	10	segmentation[3	segmentation[3	PROPN
ajst-30179	18	11	]	]	PUNCT
ajst-30179	18	12	.	.	PUNCT
ajst-30179	19	1	while	while	SCONJ
ajst-30179	19	2	semantic	semantic	ADJ
ajst-30179	19	3	segmentation	segmentation	NOUN
ajst-30179	19	4	focuses	focus	VERB
ajst-30179	19	5	solely	solely	ADV
ajst-30179	19	6	on	on	ADP
ajst-30179	19	7	categorizing	categorize	VERB
ajst-30179	19	8	pixels	pixel	NOUN
ajst-30179	19	9	into	into	ADP
ajst-30179	19	10	general	general	ADJ
ajst-30179	19	11	classes	class	NOUN
ajst-30179	19	12	(	(	PUNCT
ajst-30179	19	13	e.g.	e.g.	ADV
ajst-30179	19	14	,	,	PUNCT
ajst-30179	19	15	all	all	DET
ajst-30179	19	16	"	"	PUNCT
ajst-30179	19	17	pedestrian	pedestrian	NOUN
ajst-30179	19	18	"	"	PUNCT
ajst-30179	19	19	pixels	pixel	NOUN
ajst-30179	19	20	belong	belong	VERB
ajst-30179	19	21	to	to	ADP
ajst-30179	19	22	the	the	DET
ajst-30179	19	23	same	same	ADJ
ajst-30179	19	24	category	category	NOUN
ajst-30179	19	25	)	)	PUNCT
ajst-30179	19	26	,	,	PUNCT
ajst-30179	19	27	instance	instance	NOUN
ajst-30179	19	28	segmentation	segmentation	NOUN
ajst-30179	19	29	further	far	ADV
ajst-30179	19	30	differentiates	differentiate	VERB
ajst-30179	19	31	individual	individual	ADJ
ajst-30179	19	32	objects	object	NOUN
ajst-30179	19	33	within	within	ADP
ajst-30179	19	34	the	the	DET
ajst-30179	19	35	same	same	ADJ
ajst-30179	19	36	category	category	NOUN
ajst-30179	19	37	(	(	PUNCT
ajst-30179	19	38	e.g.	e.g.	ADV
ajst-30179	19	39	,	,	PUNCT
ajst-30179	19	40	assigning	assign	VERB
ajst-30179	19	41	distinct	distinct	ADJ
ajst-30179	19	42	labels	label	NOUN
ajst-30179	19	43	to	to	ADP
ajst-30179	19	44	each	each	DET
ajst-30179	19	45	pedestrian	pedestrian	NOUN
ajst-30179	19	46	)	)	PUNCT
ajst-30179	19	47	.	.	PUNCT
ajst-30179	20	1	this	this	DET
ajst-30179	20	2	distinction	distinction	NOUN
ajst-30179	20	3	determines	determine	VERB
ajst-30179	20	4	their	their	PRON
ajst-30179	20	5	respective	respective	ADJ
ajst-30179	20	6	applications	application	NOUN
ajst-30179	20	7	.	.	PUNCT
ajst-30179	21	1	instance	instance	NOUN
ajst-30179	21	2	segmentation	segmentation	NOUN
ajst-30179	21	3	is	be	AUX
ajst-30179	21	4	crucial	crucial	ADJ
ajst-30179	21	5	for	for	ADP
ajst-30179	21	6	scenarios	scenario	NOUN
ajst-30179	21	7	requiring	require	VERB
ajst-30179	21	8	precise	precise	ADJ
ajst-30179	21	9	object	object	NOUN
ajst-30179	21	10	counting	counting	NOUN
ajst-30179	21	11	,	,	PUNCT
ajst-30179	21	12	such	such	ADJ
ajst-30179	21	13	as	as	ADP
ajst-30179	21	14	retail	retail	ADJ
ajst-30179	21	15	foot	foot	NOUN
ajst-30179	21	16	traffic	traffic	NOUN
ajst-30179	21	17	analysis	analysis	NOUN
ajst-30179	21	18	.	.	PUNCT
ajst-30179	22	1	semantic	semantic	ADJ
ajst-30179	22	2	segmentation	segmentation	NOUN
ajst-30179	22	3	is	be	AUX
ajst-30179	22	4	better	well	ADV
ajst-30179	22	5	suited	suited	ADJ
ajst-30179	22	6	for	for	ADP
ajst-30179	22	7	global	global	ADJ
ajst-30179	22	8	environmental	environmental	ADJ
ajst-30179	22	9	understanding	understanding	NOUN
ajst-30179	22	10	,	,	PUNCT
ajst-30179	22	11	such	such	ADJ
ajst-30179	22	12	as	as	ADP
ajst-30179	22	13	autonomous	autonomous	ADJ
ajst-30179	22	14	driving	driving	NOUN
ajst-30179	22	15	(	(	PUNCT
ajst-30179	22	16	for	for	ADP
ajst-30179	22	17	drivable	drivable	ADJ
ajst-30179	22	18	area	area	NOUN
ajst-30179	22	19	segmentation	segmentation	NOUN
ajst-30179	22	20	)	)	PUNCT
ajst-30179	22	21	or	or	CCONJ
ajst-30179	22	22	medical	medical	ADJ
ajst-30179	22	23	imaging	imaging	NOUN
ajst-30179	22	24	(	(	PUNCT
ajst-30179	22	25	for	for	ADP
ajst-30179	22	26	organ	organ	NOUN
ajst-30179	22	27	and	and	CCONJ
ajst-30179	22	28	lesion	lesion	NOUN
ajst-30179	22	29	localization).today	localization).today	NOUN
ajst-30179	22	30	,	,	PUNCT
ajst-30179	22	31	semantic	semantic	ADJ
ajst-30179	22	32	segmentation	segmentation	NOUN
ajst-30179	22	33	has	have	AUX
ajst-30179	22	34	been	be	AUX
ajst-30179	22	35	widely	widely	ADV
ajst-30179	22	36	deployed	deploy	VERB
ajst-30179	22	37	across	across	ADP
ajst-30179	22	38	multiple	multiple	ADJ
ajst-30179	22	39	domains	domain	NOUN
ajst-30179	22	40	.	.	PUNCT
ajst-30179	23	1	autonomous	autonomous	ADJ
ajst-30179	23	2	driving	driving	NOUN
ajst-30179	23	3	:	:	PUNCT
ajst-30179	23	4	enables	enable	VERB
ajst-30179	23	5	real	real	ADJ
ajst-30179	23	6	-	-	PUNCT
ajst-30179	23	7	time	time	NOUN
ajst-30179	23	8	analysis	analysis	NOUN
ajst-30179	23	9	of	of	ADP
ajst-30179	23	10	roads	road	NOUN
ajst-30179	23	11	,	,	PUNCT
ajst-30179	23	12	obstacles	obstacle	NOUN
ajst-30179	23	13	,	,	PUNCT
ajst-30179	23	14	and	and	CCONJ
ajst-30179	23	15	traffic	traffic	NOUN
ajst-30179	23	16	signs	sign	NOUN
ajst-30179	23	17	for	for	ADP
ajst-30179	23	18	environmental	environmental	ADJ
ajst-30179	23	19	perception	perception	NOUN
ajst-30179	23	20	.	.	PUNCT
ajst-30179	24	1	medical	medical	ADJ
ajst-30179	24	2	diagnostics	diagnostic	NOUN
ajst-30179	24	3	:	:	PUNCT
ajst-30179	24	4	accurately	accurately	ADV
ajst-30179	24	5	segments	segment	VERB
ajst-30179	24	6	tumor	tumor	NOUN
ajst-30179	24	7	regions	region	NOUN
ajst-30179	24	8	in	in	ADP
ajst-30179	24	9	ct	ct	PROPN
ajst-30179	24	10	/	/	SYM
ajst-30179	24	11	mri	mri	NOUN
ajst-30179	24	12	scans	scan	NOUN
ajst-30179	24	13	,	,	PUNCT
ajst-30179	24	14	assisting	assist	VERB
ajst-30179	24	15	in	in	ADP
ajst-30179	24	16	pathological	pathological	ADJ
ajst-30179	24	17	analysis	analysis	NOUN
ajst-30179	24	18	.	.	PUNCT
ajst-30179	25	1	remote	remote	ADJ
ajst-30179	25	2	sensing	sensing	NOUN
ajst-30179	25	3	:	:	PUNCT
ajst-30179	25	4	facilitates	facilitate	VERB
ajst-30179	25	5	land	land	NOUN
ajst-30179	25	6	cover	cover	NOUN
ajst-30179	25	7	classification	classification	NOUN
ajst-30179	25	8	and	and	CCONJ
ajst-30179	25	9	disaster	disaster	NOUN
ajst-30179	25	10	assessment	assessment	NOUN
ajst-30179	25	11	using	use	VERB
ajst-30179	25	12	aerial	aerial	ADJ
ajst-30179	25	13	and	and	CCONJ
ajst-30179	25	14	satellite	satellite	NOUN
ajst-30179	25	15	imagery	imagery	NOUN
ajst-30179	25	16	.	.	PUNCT
ajst-30179	26	1	2	2	X
ajst-30179	26	2	.	.	X
ajst-30179	26	3	current	current	ADJ
ajst-30179	26	4	research	research	NOUN
ajst-30179	26	5	status	status	NOUN
ajst-30179	26	6	at	at	ADP
ajst-30179	26	7	home	home	ADV
ajst-30179	26	8	and	and	CCONJ
ajst-30179	26	9	abroad	abroad	ADV
ajst-30179	26	10	2.1	2.1	NUM
ajst-30179	26	11	.	.	PUNCT
ajst-30179	27	1	methods	method	NOUN
ajst-30179	27	2	of	of	ADP
ajst-30179	27	3	semantic	semantic	ADJ
ajst-30179	27	4	segmentation	segmentation	NOUN
ajst-30179	27	5	2.1.1	2.1.1	NUM
ajst-30179	27	6	.	.	PUNCT
ajst-30179	28	1	convolutional	convolutional	ADJ
ajst-30179	28	2	neural	neural	ADJ
ajst-30179	28	3	networks	network	NOUN
ajst-30179	28	4	(	(	PUNCT
ajst-30179	28	5	cnns	cnns	ADJ
ajst-30179	28	6	)	)	PUNCT
ajst-30179	28	7	convolutional	convolutional	ADJ
ajst-30179	28	8	neural	neural	ADJ
ajst-30179	28	9	networks	network	NOUN
ajst-30179	28	10	(	(	PUNCT
ajst-30179	28	11	cnns	cnns	PROPN
ajst-30179	28	12	)	)	PUNCT
ajst-30179	28	13	are	be	AUX
ajst-30179	28	14	a	a	DET
ajst-30179	28	15	type	type	NOUN
ajst-30179	28	16	of	of	ADP
ajst-30179	28	17	deep	deep	ADJ
ajst-30179	28	18	learning	learning	NOUN
ajst-30179	28	19	model	model	NOUN
ajst-30179	28	20	widely	widely	ADV
ajst-30179	28	21	used	use	VERB
ajst-30179	28	22	in	in	ADP
ajst-30179	28	23	fields	field	NOUN
ajst-30179	28	24	such	such	ADJ
ajst-30179	28	25	as	as	ADP
ajst-30179	28	26	image	image	NOUN
ajst-30179	28	27	recognition	recognition	NOUN
ajst-30179	28	28	and	and	CCONJ
ajst-30179	28	29	speech	speech	NOUN
ajst-30179	28	30	recognition	recognition	NOUN
ajst-30179	28	31	.	.	PUNCT
ajst-30179	29	1	the	the	DET
ajst-30179	29	2	core	core	ADJ
ajst-30179	29	3	idea	idea	NOUN
ajst-30179	29	4	of	of	ADP
ajst-30179	29	5	cnns	cnns	PROPN
ajst-30179	29	6	is	be	AUX
ajst-30179	29	7	to	to	PART
ajst-30179	29	8	extract	extract	VERB
ajst-30179	29	9	features	feature	NOUN
ajst-30179	29	10	from	from	ADP
ajst-30179	29	11	data	datum	NOUN
ajst-30179	29	12	(	(	PUNCT
ajst-30179	29	13	such	such	ADJ
ajst-30179	29	14	as	as	ADP
ajst-30179	29	15	images	image	NOUN
ajst-30179	29	16	)	)	PUNCT
ajst-30179	29	17	through	through	ADP
ajst-30179	29	18	convolution	convolution	NOUN
ajst-30179	29	19	operations	operation	NOUN
ajst-30179	29	20	,	,	PUNCT
ajst-30179	29	21	enabling	enable	VERB
ajst-30179	29	22	tasks	task	NOUN
ajst-30179	29	23	such	such	ADJ
ajst-30179	29	24	as	as	ADP
ajst-30179	29	25	classification	classification	NOUN
ajst-30179	29	26	and	and	CCONJ
ajst-30179	29	27	recognition.the	recognition.the	DET
ajst-30179	29	28	basic	basic	ADJ
ajst-30179	29	29	structure	structure	NOUN
ajst-30179	29	30	of	of	ADP
ajst-30179	29	31	a	a	DET
ajst-30179	29	32	cnn	cnn	PROPN
ajst-30179	29	33	consists	consist	VERB
ajst-30179	29	34	of	of	ADP
ajst-30179	29	35	convolutional	convolutional	ADJ
ajst-30179	29	36	layers	layer	NOUN
ajst-30179	29	37	,	,	PUNCT
ajst-30179	29	38	pooling	pool	VERB
ajst-30179	29	39	layers	layer	NOUN
ajst-30179	29	40	,	,	PUNCT
ajst-30179	29	41	and	and	CCONJ
ajst-30179	29	42	fully	fully	ADV
ajst-30179	29	43	connected	connected	ADJ
ajst-30179	29	44	layers	layer	NOUN
ajst-30179	29	45	:	:	PUNCT
ajst-30179	29	46	the	the	DET
ajst-30179	29	47	convolutional	convolutional	ADJ
ajst-30179	29	48	layer	layer	NOUN
ajst-30179	29	49	is	be	AUX
ajst-30179	29	50	the	the	DET
ajst-30179	29	51	core	core	NOUN
ajst-30179	29	52	component	component	NOUN
ajst-30179	29	53	of	of	ADP
ajst-30179	29	54	cnns	cnn	NOUN
ajst-30179	29	55	.	.	PUNCT
ajst-30179	30	1	it	it	PRON
ajst-30179	30	2	applies	apply	VERB
ajst-30179	30	3	a	a	DET
ajst-30179	30	4	sliding	slide	VERB
ajst-30179	30	5	convolution	convolution	NOUN
ajst-30179	30	6	kernel	kernel	NOUN
ajst-30179	30	7	over	over	ADP
ajst-30179	30	8	the	the	DET
ajst-30179	30	9	input	input	NOUN
ajst-30179	30	10	data	datum	NOUN
ajst-30179	30	11	to	to	PART
ajst-30179	30	12	perform	perform	VERB
ajst-30179	30	13	convolution	convolution	NOUN
ajst-30179	30	14	operations	operation	NOUN
ajst-30179	30	15	,	,	PUNCT
ajst-30179	30	16	extracting	extract	VERB
ajst-30179	30	17	local	local	ADJ
ajst-30179	30	18	features	feature	NOUN
ajst-30179	30	19	.	.	PUNCT
ajst-30179	31	1	the	the	DET
ajst-30179	31	2	convolution	convolution	NOUN
ajst-30179	31	3	operation	operation	NOUN
ajst-30179	31	4	can	can	AUX
ajst-30179	31	5	be	be	AUX
ajst-30179	31	6	seen	see	VERB
ajst-30179	31	7	as	as	ADP
ajst-30179	31	8	a	a	DET
ajst-30179	31	9	special	special	ADJ
ajst-30179	31	10	weighted	weight	VERB
ajst-30179	31	11	summation	summation	NOUN
ajst-30179	31	12	,	,	PUNCT
ajst-30179	31	13	where	where	SCONJ
ajst-30179	31	14	the	the	DET
ajst-30179	31	15	weights	weight	NOUN
ajst-30179	31	16	in	in	ADP
ajst-30179	31	17	the	the	DET
ajst-30179	31	18	convolution	convolution	NOUN
ajst-30179	31	19	kernel	kernel	NOUN
ajst-30179	31	20	are	be	AUX
ajst-30179	31	21	learned	learn	VERB
ajst-30179	31	22	through	through	ADP
ajst-30179	31	23	training.the	training.the	DET
ajst-30179	31	24	pooling	pool	VERB
ajst-30179	31	25	layer	layer	NOUN
ajst-30179	31	26	is	be	AUX
ajst-30179	31	27	used	use	VERB
ajst-30179	31	28	to	to	PART
ajst-30179	31	29	downsample	downsample	VERB
ajst-30179	31	30	the	the	DET
ajst-30179	31	31	feature	feature	NOUN
ajst-30179	31	32	maps	map	NOUN
ajst-30179	31	33	produced	produce	VERB
ajst-30179	31	34	by	by	ADP
ajst-30179	31	35	the	the	DET
ajst-30179	31	36	convolutional	convolutional	ADJ
ajst-30179	31	37	layer	layer	NOUN
ajst-30179	31	38	,	,	PUNCT
ajst-30179	31	39	reducing	reduce	VERB
ajst-30179	31	40	the	the	DET
ajst-30179	31	41	number	number	NOUN
ajst-30179	31	42	of	of	ADP
ajst-30179	31	43	model	model	NOUN
ajst-30179	31	44	parameters	parameter	NOUN
ajst-30179	31	45	and	and	CCONJ
ajst-30179	31	46	computational	computational	ADJ
ajst-30179	31	47	complexity	complexity	NOUN
ajst-30179	31	48	.	.	PUNCT
ajst-30179	32	1	common	common	ADJ
ajst-30179	32	2	pooling	pooling	NOUN
ajst-30179	32	3	methods	method	NOUN
ajst-30179	32	4	include	include	VERB
ajst-30179	32	5	max	max	PROPN
ajst-30179	32	6	pooling	pooling	NOUN
ajst-30179	32	7	and	and	CCONJ
ajst-30179	32	8	average	average	VERB
ajst-30179	32	9	pooling.the	pooling.the	DET
ajst-30179	32	10	fully	fully	ADV
ajst-30179	32	11	connected	connect	VERB
ajst-30179	32	12	layer	layer	NOUN
ajst-30179	32	13	maps	map	VERB
ajst-30179	32	14	the	the	DET
ajst-30179	32	15	output	output	NOUN
ajst-30179	32	16	feature	feature	NOUN
ajst-30179	32	17	vectors	vector	NOUN
ajst-30179	32	18	from	from	ADP
ajst-30179	32	19	the	the	DET
ajst-30179	32	20	pooling	pool	VERB
ajst-30179	32	21	layer	layer	NOUN
ajst-30179	32	22	to	to	ADP
ajst-30179	32	23	the	the	DET
ajst-30179	32	24	final	final	ADJ
ajst-30179	32	25	output	output	NOUN
ajst-30179	32	26	categories	category	NOUN
ajst-30179	32	27	,	,	PUNCT
ajst-30179	32	28	enabling	enable	VERB
ajst-30179	32	29	62	62	NUM
ajst-30179	32	30	classification	classification	NOUN
ajst-30179	32	31	or	or	CCONJ
ajst-30179	32	32	recognition	recognition	NOUN
ajst-30179	32	33	of	of	ADP
ajst-30179	32	34	the	the	DET
ajst-30179	32	35	input	input	NOUN
ajst-30179	32	36	data	datum	NOUN
ajst-30179	32	37	.	.	PUNCT
ajst-30179	33	1	cnns	cnns	PROPN
ajst-30179	33	2	exhibit	exhibit	PROPN
ajst-30179	33	3	translation	translation	NOUN
ajst-30179	33	4	invariance	invariance	NOUN
ajst-30179	33	5	and	and	CCONJ
ajst-30179	33	6	parameter	parameter	NOUN
ajst-30179	33	7	sharing	sharing	NOUN
ajst-30179	33	8	,	,	PUNCT
ajst-30179	33	9	which	which	PRON
ajst-30179	33	10	enhance	enhance	VERB
ajst-30179	33	11	the	the	DET
ajst-30179	33	12	generalization	generalization	NOUN
ajst-30179	33	13	ability	ability	NOUN
ajst-30179	33	14	and	and	CCONJ
ajst-30179	33	15	robustness	robustness	NOUN
ajst-30179	33	16	of	of	ADP
ajst-30179	33	17	the	the	DET
ajst-30179	33	18	model	model	NOUN
ajst-30179	33	19	.	.	PUNCT
ajst-30179	34	1	in	in	ADP
ajst-30179	34	2	summary	summary	NOUN
ajst-30179	34	3	,	,	PUNCT
ajst-30179	34	4	convolutional	convolutional	ADJ
ajst-30179	34	5	neural	neural	ADJ
ajst-30179	34	6	networks	network	NOUN
ajst-30179	34	7	are	be	AUX
ajst-30179	34	8	deep	deep	ADJ
ajst-30179	34	9	learning	learning	NOUN
ajst-30179	34	10	models	model	NOUN
ajst-30179	34	11	based	base	VERB
ajst-30179	34	12	on	on	ADP
ajst-30179	34	13	convolution	convolution	NOUN
ajst-30179	34	14	operations	operation	NOUN
ajst-30179	34	15	,	,	PUNCT
ajst-30179	34	16	which	which	PRON
ajst-30179	34	17	automatically	automatically	ADV
ajst-30179	34	18	learn	learn	VERB
ajst-30179	34	19	and	and	CCONJ
ajst-30179	34	20	extract	extract	VERB
ajst-30179	34	21	features	feature	NOUN
ajst-30179	34	22	from	from	ADP
ajst-30179	34	23	data	datum	NOUN
ajst-30179	34	24	to	to	PART
ajst-30179	34	25	perform	perform	VERB
ajst-30179	34	26	classification	classification	NOUN
ajst-30179	34	27	,	,	PUNCT
ajst-30179	34	28	recognition	recognition	NOUN
ajst-30179	34	29	,	,	PUNCT
ajst-30179	34	30	and	and	CCONJ
ajst-30179	34	31	other	other	ADJ
ajst-30179	34	32	tasks	task	NOUN
ajst-30179	34	33	.	.	PUNCT
ajst-30179	35	1	2.1.2	2.1.2	X
ajst-30179	35	2	.	.	PUNCT
ajst-30179	35	3	fully	fully	ADV
ajst-30179	35	4	convolutional	convolutional	ADJ
ajst-30179	35	5	networks(fcns	networks(fcns	PROPN
ajst-30179	35	6	)	)	PUNCT
ajst-30179	35	7	fully	fully	ADV
ajst-30179	35	8	convolutional	convolutional	ADJ
ajst-30179	35	9	network	network	NOUN
ajst-30179	35	10	(	(	PUNCT
ajst-30179	35	11	fcn	fcn	PROPN
ajst-30179	35	12	)	)	PUNCT
ajst-30179	36	1	[	[	X
ajst-30179	36	2	4	4	X
ajst-30179	36	3	]	]	PUNCT
ajst-30179	36	4	is	be	AUX
ajst-30179	36	5	a	a	DET
ajst-30179	36	6	crucial	crucial	ADJ
ajst-30179	36	7	architecture	architecture	NOUN
ajst-30179	36	8	in	in	ADP
ajst-30179	36	9	deep	deep	ADJ
ajst-30179	36	10	learning	learning	NOUN
ajst-30179	36	11	for	for	ADP
ajst-30179	36	12	image	image	NOUN
ajst-30179	36	13	processing	processing	NOUN
ajst-30179	36	14	tasks	task	NOUN
ajst-30179	36	15	.	.	PUNCT
ajst-30179	37	1	compared	compare	VERB
ajst-30179	37	2	to	to	ADP
ajst-30179	37	3	traditional	traditional	ADJ
ajst-30179	37	4	cnns	cnn	NOUN
ajst-30179	37	5	,	,	PUNCT
ajst-30179	37	6	the	the	DET
ajst-30179	37	7	key	key	ADJ
ajst-30179	37	8	feature	feature	NOUN
ajst-30179	37	9	of	of	ADP
ajst-30179	37	10	fcn	fcn	NOUN
ajst-30179	37	11	is	be	AUX
ajst-30179	37	12	that	that	SCONJ
ajst-30179	37	13	its	its	PRON
ajst-30179	37	14	output	output	NOUN
ajst-30179	37	15	layer	layer	NOUN
ajst-30179	37	16	is	be	AUX
ajst-30179	37	17	a	a	DET
ajst-30179	37	18	dense	dense	ADJ
ajst-30179	37	19	pixel	pixel	ADJ
ajst-30179	37	20	-	-	ADJ
ajst-30179	37	21	wise	wise	ADJ
ajst-30179	37	22	feature	feature	NOUN
ajst-30179	37	23	map	map	NOUN
ajst-30179	37	24	,	,	PUNCT
ajst-30179	37	25	where	where	SCONJ
ajst-30179	37	26	each	each	DET
ajst-30179	37	27	pixel	pixel	NOUN
ajst-30179	37	28	corresponds	correspond	VERB
ajst-30179	37	29	to	to	ADP
ajst-30179	37	30	a	a	DET
ajst-30179	37	31	local	local	ADJ
ajst-30179	37	32	receptive	receptive	ADJ
ajst-30179	37	33	field	field	NOUN
ajst-30179	37	34	in	in	ADP
ajst-30179	37	35	the	the	DET
ajst-30179	37	36	input	input	NOUN
ajst-30179	37	37	image	image	NOUN
ajst-30179	37	38	.	.	PUNCT
ajst-30179	38	1	this	this	PRON
ajst-30179	38	2	enables	enable	VERB
ajst-30179	38	3	fcn	fcn	VERB
ajst-30179	38	4	to	to	PART
ajst-30179	38	5	not	not	PART
ajst-30179	38	6	only	only	ADV
ajst-30179	38	7	identify	identify	VERB
ajst-30179	38	8	objects	object	NOUN
ajst-30179	38	9	in	in	ADP
ajst-30179	38	10	an	an	DET
ajst-30179	38	11	image	image	NOUN
ajst-30179	38	12	but	but	CCONJ
ajst-30179	38	13	also	also	ADV
ajst-30179	38	14	perform	perform	VERB
ajst-30179	38	15	pixel	pixel	ADJ
ajst-30179	38	16	-	-	PUNCT
ajst-30179	38	17	level	level	NOUN
ajst-30179	38	18	predictions	prediction	NOUN
ajst-30179	38	19	,	,	PUNCT
ajst-30179	38	20	such	such	ADJ
ajst-30179	38	21	as	as	ADP
ajst-30179	38	22	image	image	NOUN
ajst-30179	38	23	segmentation	segmentation	NOUN
ajst-30179	38	24	and	and	CCONJ
ajst-30179	38	25	image	image	NOUN
ajst-30179	38	26	generation	generation	NOUN
ajst-30179	38	27	,	,	PUNCT
ajst-30179	38	28	as	as	SCONJ
ajst-30179	38	29	illustrated	illustrate	VERB
ajst-30179	38	30	in	in	ADP
ajst-30179	38	31	figure	figure	NOUN
ajst-30179	38	32	2	2	NUM
ajst-30179	38	33	-	-	SYM
ajst-30179	38	34	1	1	NUM
ajst-30179	38	35	.	.	PUNCT
ajst-30179	38	36	figure	figure	NOUN
ajst-30179	38	37	2	2	NUM
ajst-30179	38	38	-	-	SYM
ajst-30179	38	39	1	1	NUM
ajst-30179	38	40	.	.	PUNCT
ajst-30179	38	41	fcn	fcn	PROPN
ajst-30179	38	42	model	model	PROPN
ajst-30179	38	43	diagram	diagram	PROPN
ajst-30179	38	44	2.2	2.2	NUM
ajst-30179	38	45	.	.	PUNCT
ajst-30179	39	1	deep	deep	ADJ
ajst-30179	39	2	learning	learning	NOUN
ajst-30179	39	3	-	-	PUNCT
ajst-30179	39	4	based	base	VERB
ajst-30179	39	5	semantic	semantic	ADJ
ajst-30179	39	6	segmentation	segmentation	NOUN
ajst-30179	39	7	each	each	DET
ajst-30179	39	8	architecture	architecture	NOUN
ajst-30179	39	9	has	have	VERB
ajst-30179	39	10	subtle	subtle	ADJ
ajst-30179	39	11	differences	difference	NOUN
ajst-30179	39	12	that	that	PRON
ajst-30179	39	13	distinguish	distinguish	VERB
ajst-30179	39	14	it	it	PRON
ajst-30179	39	15	from	from	ADP
ajst-30179	39	16	standard	standard	ADJ
ajst-30179	39	17	models	model	NOUN
ajst-30179	39	18	,	,	PUNCT
ajst-30179	39	19	giving	give	VERB
ajst-30179	39	20	it	it	PRON
ajst-30179	39	21	unique	unique	ADJ
ajst-30179	39	22	advantages	advantage	NOUN
ajst-30179	39	23	when	when	SCONJ
ajst-30179	39	24	applied	apply	VERB
ajst-30179	39	25	to	to	ADP
ajst-30179	39	26	specific	specific	ADJ
ajst-30179	39	27	problems	problem	NOUN
ajst-30179	39	28	.	.	PUNCT
ajst-30179	40	1	these	these	DET
ajst-30179	40	2	architectures	architecture	NOUN
ajst-30179	40	3	fall	fall	VERB
ajst-30179	40	4	under	under	ADP
ajst-30179	40	5	the	the	DET
ajst-30179	40	6	category	category	NOUN
ajst-30179	40	7	of	of	ADP
ajst-30179	40	8	"	"	PUNCT
ajst-30179	40	9	deep	deep	ADJ
ajst-30179	40	10	"	"	PUNCT
ajst-30179	40	11	models	model	NOUN
ajst-30179	40	12	,	,	PUNCT
ajst-30179	40	13	which	which	PRON
ajst-30179	40	14	often	often	ADV
ajst-30179	40	15	outperform	outperform	VERB
ajst-30179	40	16	shallow	shallow	ADJ
ajst-30179	40	17	models	model	NOUN
ajst-30179	40	18	in	in	ADP
ajst-30179	40	19	terms	term	NOUN
ajst-30179	40	20	of	of	ADP
ajst-30179	40	21	performance	performance	NOUN
ajst-30179	40	22	.	.	PUNCT
ajst-30179	41	1	with	with	ADP
ajst-30179	41	2	the	the	DET
ajst-30179	41	3	advancement	advancement	NOUN
ajst-30179	41	4	of	of	ADP
ajst-30179	41	5	machine	machine	NOUN
ajst-30179	41	6	learning	learning	NOUN
ajst-30179	41	7	,	,	PUNCT
ajst-30179	41	8	numerous	numerous	ADJ
ajst-30179	41	9	deep	deep	ADJ
ajst-30179	41	10	learning	learning	NOUN
ajst-30179	41	11	architectures	architecture	NOUN
ajst-30179	41	12	have	have	AUX
ajst-30179	41	13	been	be	AUX
ajst-30179	41	14	proposed	propose	VERB
ajst-30179	41	15	.	.	PUNCT
ajst-30179	42	1	alexnet	alexnet	PROPN
ajst-30179	42	2	,	,	PUNCT
ajst-30179	42	3	introduced	introduce	VERB
ajst-30179	42	4	by	by	ADP
ajst-30179	42	5	geoffrey	geoffrey	PROPN
ajst-30179	42	6	hinton	hinton	PROPN
ajst-30179	42	7	and	and	CCONJ
ajst-30179	42	8	his	his	PRON
ajst-30179	42	9	colleagues[5	colleagues[5	NOUN
ajst-30179	42	10	]	]	PUNCT
ajst-30179	42	11	,	,	PUNCT
ajst-30179	42	12	was	be	AUX
ajst-30179	42	13	the	the	DET
ajst-30179	42	14	first	first	ADJ
ajst-30179	42	15	deep	deep	ADJ
ajst-30179	42	16	architecture	architecture	NOUN
ajst-30179	42	17	.	.	PUNCT
ajst-30179	43	1	it	it	PRON
ajst-30179	43	2	is	be	AUX
ajst-30179	43	3	a	a	DET
ajst-30179	43	4	simple	simple	ADJ
ajst-30179	43	5	yet	yet	CCONJ
ajst-30179	43	6	powerful	powerful	ADJ
ajst-30179	43	7	neural	neural	ADJ
ajst-30179	43	8	network	network	NOUN
ajst-30179	43	9	that	that	PRON
ajst-30179	43	10	laid	lay	VERB
ajst-30179	43	11	the	the	DET
ajst-30179	43	12	foundation	foundation	NOUN
ajst-30179	43	13	for	for	ADP
ajst-30179	43	14	modern	modern	ADJ
ajst-30179	43	15	deep	deep	ADJ
ajst-30179	43	16	learning	learning	NOUN
ajst-30179	43	17	.	.	PUNCT
ajst-30179	44	1	vggnet[6	vggnet[6	NOUN
ajst-30179	44	2	]	]	PUNCT
ajst-30179	44	3	,	,	PUNCT
ajst-30179	44	4	developed	develop	VERB
ajst-30179	44	5	by	by	ADP
ajst-30179	44	6	the	the	DET
ajst-30179	44	7	visual	visual	ADJ
ajst-30179	44	8	geometry	geometry	NOUN
ajst-30179	44	9	group	group	NOUN
ajst-30179	44	10	(	(	PUNCT
ajst-30179	44	11	vgg	vgg	PROPN
ajst-30179	44	12	)	)	PUNCT
ajst-30179	44	13	at	at	ADP
ajst-30179	44	14	the	the	DET
ajst-30179	44	15	university	university	NOUN
ajst-30179	44	16	of	of	ADP
ajst-30179	44	17	oxford	oxford	PROPN
ajst-30179	44	18	,	,	PUNCT
ajst-30179	44	19	is	be	AUX
ajst-30179	44	20	characterized	characterize	VERB
ajst-30179	44	21	by	by	ADP
ajst-30179	44	22	a	a	DET
ajst-30179	44	23	pyramidlike	pyramidlike	ADJ
ajst-30179	44	24	structure	structure	NOUN
ajst-30179	44	25	,	,	PUNCT
ajst-30179	44	26	where	where	SCONJ
ajst-30179	44	27	the	the	DET
ajst-30179	44	28	lower	low	ADJ
ajst-30179	44	29	layers	layer	NOUN
ajst-30179	44	30	are	be	AUX
ajst-30179	44	31	wide	wide	ADJ
ajst-30179	44	32	,	,	PUNCT
ajst-30179	44	33	and	and	CCONJ
ajst-30179	44	34	the	the	DET
ajst-30179	44	35	upper	upper	ADJ
ajst-30179	44	36	layers	layer	NOUN
ajst-30179	44	37	are	be	AUX
ajst-30179	44	38	narrow	narrow	ADJ
ajst-30179	44	39	and	and	CCONJ
ajst-30179	44	40	deep.googlenet	deep.googlenet	NOUN
ajst-30179	44	41	(	(	PUNCT
ajst-30179	44	42	also	also	ADV
ajst-30179	44	43	known	know	VERB
ajst-30179	44	44	as	as	ADP
ajst-30179	44	45	inceptionnet	inceptionnet	NOUN
ajst-30179	44	46	)	)	PUNCT
ajst-30179	44	47	was	be	AUX
ajst-30179	44	48	designed	design	VERB
ajst-30179	44	49	by	by	ADP
ajst-30179	44	50	google	google	PROPN
ajst-30179	44	51	researchers[7	researchers[7	PROPN
ajst-30179	44	52	]	]	X
ajst-30179	44	53	.	.	PUNCT
ajst-30179	45	1	this	this	DET
ajst-30179	45	2	powerful	powerful	ADJ
ajst-30179	45	3	model	model	NOUN
ajst-30179	45	4	not	not	PART
ajst-30179	45	5	only	only	ADV
ajst-30179	45	6	increased	increase	VERB
ajst-30179	45	7	network	network	NOUN
ajst-30179	45	8	depth	depth	NOUN
ajst-30179	45	9	but	but	CCONJ
ajst-30179	45	10	also	also	ADV
ajst-30179	45	11	introduced	introduce	VERB
ajst-30179	45	12	a	a	DET
ajst-30179	45	13	novel	novel	ADJ
ajst-30179	45	14	method	method	NOUN
ajst-30179	45	15	called	call	VERB
ajst-30179	45	16	the	the	DET
ajst-30179	45	17	inception	inception	NOUN
ajst-30179	45	18	module.resnet[8	module.resnet[8	NOUN
ajst-30179	45	19	]	]	X
ajst-30179	45	20	(	(	PUNCT
ajst-30179	45	21	residual	residual	ADJ
ajst-30179	45	22	network	network	NOUN
ajst-30179	45	23	)	)	PUNCT
ajst-30179	45	24	is	be	AUX
ajst-30179	45	25	one	one	NUM
ajst-30179	45	26	of	of	ADP
ajst-30179	45	27	the	the	DET
ajst-30179	45	28	architectures	architecture	NOUN
ajst-30179	45	29	that	that	PRON
ajst-30179	45	30	truly	truly	ADV
ajst-30179	45	31	defined	define	VERB
ajst-30179	45	32	deep	deep	ADJ
ajst-30179	45	33	learning	learning	NOUN
ajst-30179	45	34	models	model	NOUN
ajst-30179	45	35	.	.	PUNCT
ajst-30179	46	1	it	it	PRON
ajst-30179	46	2	consists	consist	VERB
ajst-30179	46	3	of	of	ADP
ajst-30179	46	4	multiple	multiple	ADJ
ajst-30179	46	5	residual	residual	ADJ
ajst-30179	46	6	blocks	block	NOUN
ajst-30179	46	7	,	,	PUNCT
ajst-30179	46	8	which	which	PRON
ajst-30179	46	9	form	form	VERB
ajst-30179	46	10	the	the	DET
ajst-30179	46	11	building	building	NOUN
ajst-30179	46	12	blocks	block	NOUN
ajst-30179	46	13	of	of	ADP
ajst-30179	46	14	resnet	resnet	NOUN
ajst-30179	46	15	architectures	architecture	NOUN
ajst-30179	46	16	and	and	CCONJ
ajst-30179	46	17	help	help	VERB
ajst-30179	46	18	train	train	VERB
ajst-30179	46	19	deeper	deep	ADJ
ajst-30179	46	20	networks	network	NOUN
ajst-30179	46	21	effectively	effectively	ADV
ajst-30179	46	22	.	.	PUNCT
ajst-30179	47	1	yolo	yolo	INTJ
ajst-30179	47	2	(	(	PUNCT
ajst-30179	47	3	you	you	PRON
ajst-30179	47	4	only	only	ADV
ajst-30179	47	5	look	look	VERB
ajst-30179	47	6	once)[9	once)[9	NUM
ajst-30179	47	7	]	]	PUNCT
ajst-30179	47	8	is	be	AUX
ajst-30179	47	9	an	an	DET
ajst-30179	47	10	advanced	advanced	ADJ
ajst-30179	47	11	real	real	ADJ
ajst-30179	47	12	-	-	PUNCT
ajst-30179	47	13	time	time	NOUN
ajst-30179	47	14	system	system	NOUN
ajst-30179	47	15	built	build	VERB
ajst-30179	47	16	on	on	ADP
ajst-30179	47	17	deep	deep	ADJ
ajst-30179	47	18	learning	learning	NOUN
ajst-30179	47	19	principles	principle	NOUN
ajst-30179	47	20	,	,	PUNCT
ajst-30179	47	21	designed	design	VERB
ajst-30179	47	22	specifically	specifically	ADV
ajst-30179	47	23	to	to	PART
ajst-30179	47	24	solve	solve	VERB
ajst-30179	47	25	object	object	NOUN
ajst-30179	47	26	detection	detection	NOUN
ajst-30179	47	27	problems.segnet[10	problems.segnet[10	NOUN
ajst-30179	47	28	]	]	PUNCT
ajst-30179	47	29	is	be	AUX
ajst-30179	47	30	a	a	DET
ajst-30179	47	31	deep	deep	ADJ
ajst-30179	47	32	learning	learning	NOUN
ajst-30179	47	33	architecture	architecture	NOUN
ajst-30179	47	34	developed	develop	VERB
ajst-30179	47	35	for	for	ADP
ajst-30179	47	36	image	image	NOUN
ajst-30179	47	37	segmentation	segmentation	NOUN
ajst-30179	47	38	.	.	PUNCT
ajst-30179	48	1	it	it	PRON
ajst-30179	48	2	consists	consist	VERB
ajst-30179	48	3	of	of	ADP
ajst-30179	48	4	a	a	DET
ajst-30179	48	5	series	series	NOUN
ajst-30179	48	6	of	of	ADP
ajst-30179	48	7	encoding	encode	VERB
ajst-30179	48	8	layers	layer	NOUN
ajst-30179	48	9	(	(	PUNCT
ajst-30179	48	10	encoder	encoder	NOUN
ajst-30179	48	11	)	)	PUNCT
ajst-30179	48	12	followed	follow	VERB
ajst-30179	48	13	by	by	ADP
ajst-30179	48	14	corresponding	correspond	VERB
ajst-30179	48	15	decoding	decode	VERB
ajst-30179	48	16	layers	layer	NOUN
ajst-30179	48	17	,	,	PUNCT
ajst-30179	48	18	enabling	enable	VERB
ajst-30179	48	19	pixel	pixel	ADJ
ajst-30179	48	20	-	-	PUNCT
ajst-30179	48	21	level	level	NOUN
ajst-30179	48	22	classification	classification	NOUN
ajst-30179	48	23	.	.	PUNCT
ajst-30179	49	1	the	the	DET
ajst-30179	49	2	continuous	continuous	ADJ
ajst-30179	49	3	development	development	NOUN
ajst-30179	49	4	of	of	ADP
ajst-30179	49	5	neural	neural	ADJ
ajst-30179	49	6	network	network	NOUN
ajst-30179	49	7	architectures	architecture	NOUN
ajst-30179	49	8	has	have	AUX
ajst-30179	49	9	brought	bring	VERB
ajst-30179	49	10	significant	significant	ADJ
ajst-30179	49	11	value	value	NOUN
ajst-30179	49	12	to	to	ADP
ajst-30179	49	13	modern	modern	ADJ
ajst-30179	49	14	information	information	NOUN
ajst-30179	49	15	technology	technology	NOUN
ajst-30179	49	16	and	and	CCONJ
ajst-30179	49	17	communication	communication	NOUN
ajst-30179	49	18	fields	field	NOUN
ajst-30179	49	19	.	.	PUNCT
ajst-30179	50	1	it	it	PRON
ajst-30179	50	2	has	have	AUX
ajst-30179	50	3	not	not	PART
ajst-30179	50	4	only	only	ADV
ajst-30179	50	5	accelerated	accelerate	VERB
ajst-30179	50	6	digital	digital	ADJ
ajst-30179	50	7	transformation	transformation	NOUN
ajst-30179	50	8	in	in	ADP
ajst-30179	50	9	businesses	business	NOUN
ajst-30179	50	10	but	but	CCONJ
ajst-30179	50	11	has	have	AUX
ajst-30179	50	12	also	also	ADV
ajst-30179	50	13	had	have	VERB
ajst-30179	50	14	a	a	DET
ajst-30179	50	15	profound	profound	ADJ
ajst-30179	50	16	impact	impact	NOUN
ajst-30179	50	17	on	on	ADP
ajst-30179	50	18	personal	personal	ADJ
ajst-30179	50	19	life	life	NOUN
ajst-30179	50	20	,	,	PUNCT
ajst-30179	50	21	education	education	NOUN
ajst-30179	50	22	,	,	PUNCT
ajst-30179	50	23	healthcare	healthcare	PROPN
ajst-30179	50	24	,	,	PUNCT
ajst-30179	50	25	and	and	CCONJ
ajst-30179	50	26	various	various	ADJ
ajst-30179	50	27	other	other	ADJ
ajst-30179	50	28	sectors	sector	NOUN
ajst-30179	50	29	.	.	PUNCT
ajst-30179	51	1	3	3	X
ajst-30179	51	2	.	.	X
ajst-30179	51	3	related	relate	VERB
ajst-30179	51	4	work	work	NOUN
ajst-30179	51	5	3.1	3.1	NUM
ajst-30179	51	6	.	.	PUNCT
ajst-30179	51	7	pidnet	pidnet	VERB
ajst-30179	51	8	the	the	DET
ajst-30179	51	9	network	network	NOUN
ajst-30179	51	10	structure	structure	NOUN
ajst-30179	51	11	of	of	ADP
ajst-30179	51	12	pidnet[11	pidnet[11	NOUN
ajst-30179	51	13	]	]	PUNCT
ajst-30179	51	14	is	be	AUX
ajst-30179	51	15	illustrated	illustrate	VERB
ajst-30179	51	16	in	in	ADP
ajst-30179	51	17	figure	figure	NOUN
ajst-30179	51	18	3	3	NUM
ajst-30179	51	19	-	-	SYM
ajst-30179	51	20	1	1	NUM
ajst-30179	51	21	.	.	PUNCT
ajst-30179	52	1	the	the	DET
ajst-30179	52	2	input	input	NOUN
ajst-30179	52	3	image	image	NOUN
ajst-30179	52	4	undergoes	undergo	VERB
ajst-30179	52	5	three	three	NUM
ajst-30179	52	6	convolutional	convolutional	ADJ
ajst-30179	52	7	downsampling	downsample	VERB
ajst-30179	52	8	operations	operation	NOUN
ajst-30179	52	9	,	,	PUNCT
ajst-30179	52	10	producing	produce	VERB
ajst-30179	52	11	a	a	DET
ajst-30179	52	12	feature	feature	NOUN
ajst-30179	52	13	map	map	NOUN
ajst-30179	52	14	at	at	ADP
ajst-30179	52	15	1/8	1/8	NUM
ajst-30179	52	16	of	of	ADP
ajst-30179	52	17	the	the	DET
ajst-30179	52	18	original	original	ADJ
ajst-30179	52	19	image	image	NOUN
ajst-30179	52	20	resolution	resolution	NOUN
ajst-30179	52	21	,	,	PUNCT
ajst-30179	52	22	which	which	PRON
ajst-30179	52	23	serves	serve	VERB
ajst-30179	52	24	as	as	ADP
ajst-30179	52	25	the	the	DET
ajst-30179	52	26	input	input	NOUN
ajst-30179	52	27	for	for	ADP
ajst-30179	52	28	the	the	DET
ajst-30179	52	29	three	three	NUM
ajst-30179	52	30	branches	branch	NOUN
ajst-30179	52	31	of	of	ADP
ajst-30179	52	32	pidnet	pidnet	NOUN
ajst-30179	52	33	.	.	PUNCT
ajst-30179	53	1	proportion	proportion	NOUN
ajst-30179	53	2	(	(	PUNCT
ajst-30179	53	3	p	p	NOUN
ajst-30179	53	4	)	)	PUNCT
ajst-30179	53	5	branch	branch	NOUN
ajst-30179	53	6	:	:	PUNCT
ajst-30179	53	7	this	this	DET
ajst-30179	53	8	branch	branch	NOUN
ajst-30179	53	9	is	be	AUX
ajst-30179	53	10	responsible	responsible	ADJ
ajst-30179	53	11	for	for	ADP
ajst-30179	53	12	analyzing	analyze	VERB
ajst-30179	53	13	and	and	CCONJ
ajst-30179	53	14	preserving	preserve	VERB
ajst-30179	53	15	detailed	detailed	ADJ
ajst-30179	53	16	information	information	NOUN
ajst-30179	53	17	in	in	ADP
ajst-30179	53	18	highresolution	highresolution	NOUN
ajst-30179	53	19	feature	feature	NOUN
ajst-30179	53	20	maps	map	NOUN
ajst-30179	53	21	.	.	PUNCT
ajst-30179	54	1	both	both	CCONJ
ajst-30179	54	2	the	the	DET
ajst-30179	54	3	input	input	NOUN
ajst-30179	54	4	and	and	CCONJ
ajst-30179	54	5	output	output	NOUN
ajst-30179	54	6	feature	feature	NOUN
ajst-30179	54	7	maps	map	NOUN
ajst-30179	54	8	maintain	maintain	VERB
ajst-30179	54	9	a	a	DET
ajst-30179	54	10	1/8	1/8	NUM
ajst-30179	54	11	resolution	resolution	NOUN
ajst-30179	54	12	of	of	ADP
ajst-30179	54	13	the	the	DET
ajst-30179	54	14	original	original	ADJ
ajst-30179	54	15	image	image	NOUN
ajst-30179	54	16	,	,	PUNCT
ajst-30179	54	17	with	with	ADP
ajst-30179	54	18	channel	channel	NOUN
ajst-30179	54	19	dimensions	dimension	NOUN
ajst-30179	54	20	stacked	stack	VERB
ajst-30179	54	21	from	from	ADP
ajst-30179	54	22	64	64	NUM
ajst-30179	54	23	to	to	ADP
ajst-30179	54	24	128	128	NUM
ajst-30179	54	25	.	.	PUNCT
ajst-30179	55	1	the	the	DET
ajst-30179	55	2	pag	pag	PROPN
ajst-30179	55	3	module	module	NOUN
ajst-30179	55	4	enables	enable	VERB
ajst-30179	55	5	interaction	interaction	NOUN
ajst-30179	55	6	between	between	ADP
ajst-30179	55	7	the	the	DET
ajst-30179	55	8	p	p	NOUN
ajst-30179	55	9	branch	branch	NOUN
ajst-30179	55	10	and	and	CCONJ
ajst-30179	55	11	the	the	DET
ajst-30179	55	12	integration	integration	NOUN
ajst-30179	55	13	(	(	PUNCT
ajst-30179	55	14	i	i	NOUN
ajst-30179	55	15	)	)	PUNCT
ajst-30179	55	16	branch	branch	NOUN
ajst-30179	55	17	,	,	PUNCT
ajst-30179	55	18	while	while	SCONJ
ajst-30179	55	19	also	also	ADV
ajst-30179	55	20	passing	pass	VERB
ajst-30179	55	21	output	output	NOUN
ajst-30179	55	22	to	to	ADP
ajst-30179	55	23	the	the	DET
ajst-30179	55	24	s	s	NOUN
ajst-30179	55	25	-	-	NOUN
ajst-30179	55	26	head	head	NOUN
ajst-30179	55	27	for	for	ADP
ajst-30179	55	28	network	network	NOUN
ajst-30179	55	29	loss	loss	NOUN
ajst-30179	55	30	calculation	calculation	NOUN
ajst-30179	55	31	.	.	PUNCT
ajst-30179	56	1	integration	integration	NOUN
ajst-30179	56	2	(	(	PUNCT
ajst-30179	56	3	i	i	NOUN
ajst-30179	56	4	)	)	PUNCT
ajst-30179	56	5	branch	branch	NOUN
ajst-30179	56	6	:	:	PUNCT
ajst-30179	56	7	this	this	DET
ajst-30179	56	8	branch	branch	NOUN
ajst-30179	56	9	is	be	AUX
ajst-30179	56	10	designed	design	VERB
ajst-30179	56	11	to	to	PART
ajst-30179	56	12	aggregate	aggregate	VERB
ajst-30179	56	13	both	both	CCONJ
ajst-30179	56	14	local	local	ADJ
ajst-30179	56	15	and	and	CCONJ
ajst-30179	56	16	global	global	ADJ
ajst-30179	56	17	contextual	contextual	ADJ
ajst-30179	56	18	information	information	NOUN
ajst-30179	56	19	to	to	PART
ajst-30179	56	20	capture	capture	VERB
ajst-30179	56	21	long	long	ADJ
ajst-30179	56	22	-	-	PUNCT
ajst-30179	56	23	range	range	NOUN
ajst-30179	56	24	dependencies	dependency	NOUN
ajst-30179	56	25	.	.	PUNCT
ajst-30179	57	1	it	it	PRON
ajst-30179	57	2	starts	start	VERB
ajst-30179	57	3	with	with	ADP
ajst-30179	57	4	a	a	DET
ajst-30179	57	5	1/8	1/8	NUM
ajst-30179	57	6	resolution	resolution	NOUN
ajst-30179	57	7	feature	feature	NOUN
ajst-30179	57	8	map	map	NOUN
ajst-30179	57	9	and	and	CCONJ
ajst-30179	57	10	undergoes	undergo	VERB
ajst-30179	57	11	three	three	NUM
ajst-30179	57	12	downsampling	downsample	VERB
ajst-30179	57	13	operations	operation	NOUN
ajst-30179	57	14	,	,	PUNCT
ajst-30179	57	15	eventually	eventually	ADV
ajst-30179	57	16	reaching	reach	VERB
ajst-30179	57	17	1/64	1/64	NUM
ajst-30179	57	18	of	of	ADP
ajst-30179	57	19	the	the	DET
ajst-30179	57	20	original	original	ADJ
ajst-30179	57	21	resolution	resolution	NOUN
ajst-30179	57	22	.	.	PUNCT
ajst-30179	58	1	during	during	ADP
ajst-30179	58	2	the	the	DET
ajst-30179	58	3	second	second	ADJ
ajst-30179	58	4	and	and	CCONJ
ajst-30179	58	5	third	third	ADJ
ajst-30179	58	6	downsampling	downsampling	NOUN
ajst-30179	58	7	stages	stage	NOUN
ajst-30179	58	8	,	,	PUNCT
ajst-30179	58	9	interactions	interaction	NOUN
ajst-30179	58	10	with	with	ADP
ajst-30179	58	11	the	the	DET
ajst-30179	58	12	p	p	ADJ
ajst-30179	58	13	branch	branch	NOUN
ajst-30179	58	14	occur	occur	VERB
ajst-30179	58	15	via	via	ADP
ajst-30179	58	16	the	the	DET
ajst-30179	58	17	pag	pag	PROPN
ajst-30179	58	18	module	module	NOUN
ajst-30179	58	19	.	.	PUNCT
ajst-30179	59	1	the	the	DET
ajst-30179	59	2	p	p	NOUN
ajst-30179	59	3	and	and	CCONJ
ajst-30179	59	4	i	i	PRON
ajst-30179	59	5	branch	branch	NOUN
ajst-30179	59	6	inputs	input	NOUN
ajst-30179	59	7	undergo	undergo	VERB
ajst-30179	59	8	elementwise	elementwise	NOUN
ajst-30179	59	9	multiplication	multiplication	NOUN
ajst-30179	59	10	,	,	PUNCT
ajst-30179	59	11	followed	follow	VERB
ajst-30179	59	12	by	by	ADP
ajst-30179	59	13	attention	attention	NOUN
ajst-30179	59	14	-	-	PUNCT
ajst-30179	59	15	based	base	VERB
ajst-30179	59	16	selective	selective	ADJ
ajst-30179	59	17	learning	learning	NOUN
ajst-30179	59	18	,	,	PUNCT
ajst-30179	59	19	constraining	constrain	VERB
ajst-30179	59	20	values	value	NOUN
ajst-30179	59	21	between	between	ADP
ajst-30179	59	22	0	0	NUM
ajst-30179	59	23	and	and	CCONJ
ajst-30179	59	24	1.parallel	1.parallel	NUM
ajst-30179	59	25	aggregation	aggregation	NOUN
ajst-30179	59	26	pyramid	pyramid	NOUN
ajst-30179	59	27	pooling	pool	VERB
ajst-30179	59	28	module	module	NOUN
ajst-30179	59	29	(	(	PUNCT
ajst-30179	59	30	pappm	pappm	ADJ
ajst-30179	59	31	):	):	PUNCT
ajst-30179	59	32	similar	similar	ADJ
ajst-30179	59	33	to	to	PART
ajst-30179	59	34	feature	feature	VERB
ajst-30179	59	35	pyramid	pyramid	NOUN
ajst-30179	59	36	network	network	NOUN
ajst-30179	59	37	(	(	PUNCT
ajst-30179	59	38	fpn	fpn	PROPN
ajst-30179	59	39	)	)	PUNCT
ajst-30179	59	40	,	,	PUNCT
ajst-30179	59	41	pappm	pappm	PROPN
ajst-30179	59	42	fuses	fuse	VERB
ajst-30179	59	43	multi	multi	ADJ
ajst-30179	59	44	-	-	ADJ
ajst-30179	59	45	scale	scale	ADJ
ajst-30179	59	46	features	feature	NOUN
ajst-30179	59	47	through	through	ADP
ajst-30179	59	48	bottom	bottom	ADJ
ajst-30179	59	49	-	-	PUNCT
ajst-30179	59	50	up	up	NOUN
ajst-30179	59	51	and	and	CCONJ
ajst-30179	59	52	lateral	lateral	ADJ
ajst-30179	59	53	connections	connection	NOUN
ajst-30179	59	54	,	,	PUNCT
ajst-30179	59	55	enhancing	enhance	VERB
ajst-30179	59	56	semantic	semantic	ADJ
ajst-30179	59	57	feature	feature	NOUN
ajst-30179	59	58	representation	representation	NOUN
ajst-30179	59	59	.	.	PUNCT
ajst-30179	60	1	differentiation	differentiation	NOUN
ajst-30179	60	2	(	(	PUNCT
ajst-30179	60	3	d	d	NOUN
ajst-30179	60	4	)	)	PUNCT
ajst-30179	60	5	branch	branch	NOUN
ajst-30179	60	6	:	:	PUNCT
ajst-30179	60	7	this	this	DET
ajst-30179	60	8	branch	branch	NOUN
ajst-30179	60	9	extracts	extract	VERB
ajst-30179	60	10	high	high	ADJ
ajst-30179	60	11	-	-	PUNCT
ajst-30179	60	12	frequency	frequency	NOUN
ajst-30179	60	13	features	feature	NOUN
ajst-30179	60	14	to	to	PART
ajst-30179	60	15	predict	predict	VERB
ajst-30179	60	16	boundary	boundary	ADJ
ajst-30179	60	17	regions	region	NOUN
ajst-30179	60	18	.	.	PUNCT
ajst-30179	61	1	information	information	NOUN
ajst-30179	61	2	from	from	ADP
ajst-30179	61	3	the	the	DET
ajst-30179	61	4	d	d	PROPN
ajst-30179	61	5	branch	branch	NOUN
ajst-30179	61	6	is	be	AUX
ajst-30179	61	7	fused	fuse	VERB
ajst-30179	61	8	with	with	ADP
ajst-30179	61	9	the	the	DET
ajst-30179	61	10	i	i	PROPN
ajst-30179	61	11	branch	branch	NOUN
ajst-30179	61	12	through	through	ADP
ajst-30179	61	13	feature	feature	NOUN
ajst-30179	61	14	map	map	NOUN
ajst-30179	61	15	summation	summation	NOUN
ajst-30179	61	16	.	.	PUNCT
ajst-30179	62	1	finally	finally	ADV
ajst-30179	62	2	,	,	PUNCT
ajst-30179	62	3	the	the	DET
ajst-30179	62	4	outputs	output	NOUN
ajst-30179	62	5	from	from	ADP
ajst-30179	62	6	the	the	DET
ajst-30179	62	7	three	three	NUM
ajst-30179	62	8	pid	pid	NOUN
ajst-30179	62	9	branches	branch	NOUN
ajst-30179	62	10	are	be	AUX
ajst-30179	62	11	fused	fuse	VERB
ajst-30179	62	12	using	use	VERB
ajst-30179	62	13	the	the	DET
ajst-30179	62	14	bag	bag	NOUN
ajst-30179	62	15	attention	attention	NOUN
ajst-30179	62	16	-	-	PUNCT
ajst-30179	62	17	guided	guide	VERB
ajst-30179	62	18	module	module	NOUN
ajst-30179	62	19	,	,	PUNCT
ajst-30179	62	20	producing	produce	VERB
ajst-30179	62	21	the	the	DET
ajst-30179	62	22	final	final	ADJ
ajst-30179	62	23	63	63	NUM
ajst-30179	62	24	network	network	NOUN
ajst-30179	62	25	output	output	NOUN
ajst-30179	62	26	with	with	ADP
ajst-30179	62	27	the	the	DET
ajst-30179	62	28	channel	channel	NOUN
ajst-30179	62	29	dimension	dimension	NOUN
ajst-30179	62	30	compressed	compress	VERB
ajst-30179	62	31	to	to	ADP
ajst-30179	62	32	128	128	NUM
ajst-30179	62	33	.	.	PUNCT
ajst-30179	63	1	figure	figure	VERB
ajst-30179	63	2	3	3	NUM
ajst-30179	63	3	-	-	SYM
ajst-30179	63	4	1	1	NUM
ajst-30179	63	5	.	.	PUNCT
ajst-30179	63	6	pidnet	pidnet	NOUN
ajst-30179	63	7	architecture	architecture	NOUN
ajst-30179	63	8	diagram	diagram	NOUN
ajst-30179	63	9	3.2	3.2	NUM
ajst-30179	63	10	.	.	PUNCT
ajst-30179	64	1	efficient	efficient	ADJ
ajst-30179	64	2	upsampling	upsampling	NOUN
ajst-30179	64	3	module	module	NOUN
ajst-30179	64	4	(	(	PUNCT
ajst-30179	64	5	eucb	eucb	ADJ
ajst-30179	64	6	)	)	PUNCT
ajst-30179	64	7	as	as	ADP
ajst-30179	64	8	an	an	DET
ajst-30179	64	9	efficient	efficient	ADJ
ajst-30179	64	10	up	up	ADJ
ajst-30179	64	11	-	-	PUNCT
ajst-30179	64	12	convolution	convolution	NOUN
ajst-30179	64	13	block	block	NOUN
ajst-30179	64	14	(	(	PUNCT
ajst-30179	64	15	eucb)[12	eucb)[12	NOUN
ajst-30179	64	16	]	]	X
ajst-30179	64	17	,	,	PUNCT
ajst-30179	64	18	eucb	eucb	PROPN
ajst-30179	64	19	is	be	AUX
ajst-30179	64	20	designed	design	VERB
ajst-30179	64	21	to	to	PART
ajst-30179	64	22	progressively	progressively	ADV
ajst-30179	64	23	upsample	upsample	VERB
ajst-30179	64	24	feature	feature	NOUN
ajst-30179	64	25	maps	map	NOUN
ajst-30179	64	26	,	,	PUNCT
ajst-30179	64	27	aligning	align	VERB
ajst-30179	64	28	their	their	PRON
ajst-30179	64	29	size	size	NOUN
ajst-30179	64	30	and	and	CCONJ
ajst-30179	64	31	resolution	resolution	NOUN
ajst-30179	64	32	with	with	ADP
ajst-30179	64	33	subsequent	subsequent	ADJ
ajst-30179	64	34	skip	skip	ADJ
ajst-30179	64	35	connections	connection	NOUN
ajst-30179	64	36	.	.	PUNCT
ajst-30179	65	1	this	this	DET
ajst-30179	65	2	alignment	alignment	NOUN
ajst-30179	65	3	enhances	enhance	VERB
ajst-30179	65	4	information	information	NOUN
ajst-30179	65	5	fusion	fusion	NOUN
ajst-30179	65	6	across	across	ADP
ajst-30179	65	7	different	different	ADJ
ajst-30179	65	8	layers	layer	NOUN
ajst-30179	65	9	and	and	CCONJ
ajst-30179	65	10	stages	stage	NOUN
ajst-30179	65	11	,	,	PUNCT
ajst-30179	65	12	making	make	VERB
ajst-30179	65	13	it	it	PRON
ajst-30179	65	14	particularly	particularly	ADV
ajst-30179	65	15	effective	effective	ADJ
ajst-30179	65	16	for	for	ADP
ajst-30179	65	17	segmentation	segmentation	NOUN
ajst-30179	65	18	networks	network	NOUN
ajst-30179	65	19	.	.	PUNCT
ajst-30179	66	1	the	the	DET
ajst-30179	66	2	eucb	eucb	ADJ
ajst-30179	66	3	operates	operate	NOUN
ajst-30179	66	4	as	as	SCONJ
ajst-30179	66	5	follows	follow	VERB
ajst-30179	66	6	:	:	PUNCT
ajst-30179	66	7	upsampling	upsample	VERB
ajst-30179	66	8	operation	operation	NOUN
ajst-30179	66	9	:	:	PUNCT
ajst-30179	66	10	the	the	DET
ajst-30179	66	11	input	input	NOUN
ajst-30179	66	12	feature	feature	NOUN
ajst-30179	66	13	map	map	NOUN
ajst-30179	66	14	is	be	AUX
ajst-30179	66	15	scaled	scale	VERB
ajst-30179	66	16	up	up	ADP
ajst-30179	66	17	by	by	ADP
ajst-30179	66	18	a	a	DET
ajst-30179	66	19	factor	factor	NOUN
ajst-30179	66	20	of	of	ADP
ajst-30179	66	21	2.depthwise	2.depthwise	NUM
ajst-30179	66	22	convolution	convolution	NOUN
ajst-30179	66	23	(	(	PUNCT
ajst-30179	66	24	dwc	dwc	PROPN
ajst-30179	66	25	):	):	PUNCT
ajst-30179	66	26	applied	apply	VERB
ajst-30179	66	27	after	after	ADP
ajst-30179	66	28	upsampling	upsample	VERB
ajst-30179	66	29	to	to	PART
ajst-30179	66	30	extract	extract	VERB
ajst-30179	66	31	spatial	spatial	ADJ
ajst-30179	66	32	features.batch	features.batch	NOUN
ajst-30179	66	33	normalization	normalization	NOUN
ajst-30179	66	34	(	(	PUNCT
ajst-30179	66	35	bn	bn	NOUN
ajst-30179	66	36	)	)	PUNCT
ajst-30179	66	37	&	&	CCONJ
ajst-30179	66	38	relu	relu	NOUN
ajst-30179	66	39	activation	activation	NOUN
ajst-30179	66	40	:	:	PUNCT
ajst-30179	66	41	these	these	DET
ajst-30179	66	42	operations	operation	NOUN
ajst-30179	66	43	efficiently	efficiently	ADV
ajst-30179	66	44	enhance	enhance	VERB
ajst-30179	66	45	the	the	DET
ajst-30179	66	46	feature	feature	NOUN
ajst-30179	66	47	map	map	NOUN
ajst-30179	66	48	without	without	ADP
ajst-30179	66	49	significantly	significantly	ADV
ajst-30179	66	50	increasing	increase	VERB
ajst-30179	66	51	computational	computational	ADJ
ajst-30179	66	52	cost.1×1	cost.1×1	NOUN
ajst-30179	66	53	convolution	convolution	NOUN
ajst-30179	66	54	:	:	PUNCT
ajst-30179	66	55	reduces	reduce	VERB
ajst-30179	66	56	the	the	DET
ajst-30179	66	57	number	number	NOUN
ajst-30179	66	58	of	of	ADP
ajst-30179	66	59	channels	channel	NOUN
ajst-30179	66	60	in	in	ADP
ajst-30179	66	61	the	the	DET
ajst-30179	66	62	upsampled	upsample	VERB
ajst-30179	66	63	feature	feature	NOUN
ajst-30179	66	64	map	map	NOUN
ajst-30179	66	65	to	to	PART
ajst-30179	66	66	match	match	VERB
ajst-30179	66	67	the	the	DET
ajst-30179	66	68	channel	channel	NOUN
ajst-30179	66	69	dimensions	dimension	NOUN
ajst-30179	66	70	of	of	ADP
ajst-30179	66	71	the	the	DET
ajst-30179	66	72	next	next	ADJ
ajst-30179	66	73	stage.this	stage.this	NUM
ajst-30179	66	74	channel	channel	NOUN
ajst-30179	66	75	alignment	alignment	NOUN
ajst-30179	66	76	is	be	AUX
ajst-30179	66	77	crucial	crucial	ADJ
ajst-30179	66	78	for	for	ADP
ajst-30179	66	79	smooth	smooth	ADJ
ajst-30179	66	80	integration	integration	NOUN
ajst-30179	66	81	in	in	ADP
ajst-30179	66	82	the	the	DET
ajst-30179	66	83	decoder	decoder	NOUN
ajst-30179	66	84	path	path	NOUN
ajst-30179	66	85	,	,	PUNCT
ajst-30179	66	86	ensuring	ensure	VERB
ajst-30179	66	87	effective	effective	ADJ
ajst-30179	66	88	feature	feature	NOUN
ajst-30179	66	89	propagation	propagation	NOUN
ajst-30179	66	90	during	during	ADP
ajst-30179	66	91	semantic	semantic	ADJ
ajst-30179	66	92	segmentation	segmentation	NOUN
ajst-30179	66	93	.	.	PUNCT
ajst-30179	67	1	4	4	X
ajst-30179	67	2	.	.	NUM
ajst-30179	67	3	proposed	propose	VERB
ajst-30179	67	4	algorithm	algorithm	NOUN
ajst-30179	67	5	4.1	4.1	NUM
ajst-30179	67	6	.	.	PUNCT
ajst-30179	67	7	semantic	semantic	ADJ
ajst-30179	67	8	-	-	PUNCT
ajst-30179	67	9	assisted	assist	VERB
ajst-30179	67	10	optimization	optimization	NOUN
ajst-30179	67	11	branch	branch	NOUN
ajst-30179	67	12	in	in	ADP
ajst-30179	67	13	the	the	DET
ajst-30179	67	14	pidnet	pidnet	NOUN
ajst-30179	67	15	network	network	NOUN
ajst-30179	67	16	architecture	architecture	NOUN
ajst-30179	67	17	,	,	PUNCT
ajst-30179	67	18	a	a	DET
ajst-30179	67	19	novel	novel	ADJ
ajst-30179	67	20	three	three	NUM
ajst-30179	67	21	-	-	PUNCT
ajst-30179	67	22	branch	branch	NOUN
ajst-30179	67	23	structure	structure	NOUN
ajst-30179	67	24	is	be	AUX
ajst-30179	67	25	employed	employ	VERB
ajst-30179	67	26	,	,	PUNCT
ajst-30179	67	27	consisting	consist	VERB
ajst-30179	67	28	of	of	ADP
ajst-30179	67	29	a	a	DET
ajst-30179	67	30	detail	detail	NOUN
ajst-30179	67	31	branch	branch	NOUN
ajst-30179	67	32	,	,	PUNCT
ajst-30179	67	33	a	a	DET
ajst-30179	67	34	semantic	semantic	ADJ
ajst-30179	67	35	branch	branch	NOUN
ajst-30179	67	36	,	,	PUNCT
ajst-30179	67	37	and	and	CCONJ
ajst-30179	67	38	a	a	DET
ajst-30179	67	39	boundary	boundary	ADJ
ajst-30179	67	40	branch	branch	NOUN
ajst-30179	67	41	.	.	PUNCT
ajst-30179	68	1	the	the	DET
ajst-30179	68	2	boundary	boundary	ADJ
ajst-30179	68	3	branch	branch	NOUN
ajst-30179	68	4	guides	guide	VERB
ajst-30179	68	5	the	the	DET
ajst-30179	68	6	fusion	fusion	NOUN
ajst-30179	68	7	of	of	ADP
ajst-30179	68	8	the	the	DET
ajst-30179	68	9	detail	detail	NOUN
ajst-30179	68	10	and	and	CCONJ
ajst-30179	68	11	semantic	semantic	ADJ
ajst-30179	68	12	branches	branch	NOUN
ajst-30179	68	13	.	.	PUNCT
ajst-30179	69	1	when	when	SCONJ
ajst-30179	69	2	the	the	DET
ajst-30179	69	3	feature	feature	NOUN
ajst-30179	69	4	map	map	NOUN
ajst-30179	69	5	enters	enter	VERB
ajst-30179	69	6	the	the	DET
ajst-30179	69	7	model	model	NOUN
ajst-30179	69	8	,	,	PUNCT
ajst-30179	69	9	it	it	PRON
ajst-30179	69	10	first	first	ADV
ajst-30179	69	11	undergoes	undergo	VERB
ajst-30179	69	12	feature	feature	NOUN
ajst-30179	69	13	extraction	extraction	NOUN
ajst-30179	69	14	through	through	ADP
ajst-30179	69	15	the	the	DET
ajst-30179	69	16	semantic	semantic	ADJ
ajst-30179	69	17	branch	branch	NOUN
ajst-30179	69	18	,	,	PUNCT
ajst-30179	69	19	where	where	SCONJ
ajst-30179	69	20	three	three	NUM
ajst-30179	69	21	downsampling	downsample	VERB
ajst-30179	69	22	operations	operation	NOUN
ajst-30179	69	23	reduce	reduce	VERB
ajst-30179	69	24	the	the	DET
ajst-30179	69	25	feature	feature	NOUN
ajst-30179	69	26	map	map	NOUN
ajst-30179	69	27	to	to	ADP
ajst-30179	69	28	1/8	1/8	NUM
ajst-30179	69	29	of	of	ADP
ajst-30179	69	30	the	the	DET
ajst-30179	69	31	original	original	ADJ
ajst-30179	69	32	image	image	NOUN
ajst-30179	69	33	size	size	NOUN
ajst-30179	69	34	.	.	PUNCT
ajst-30179	70	1	however	however	ADV
ajst-30179	70	2	,	,	PUNCT
ajst-30179	70	3	this	this	DET
ajst-30179	70	4	process	process	NOUN
ajst-30179	70	5	may	may	AUX
ajst-30179	70	6	result	result	VERB
ajst-30179	70	7	in	in	ADP
ajst-30179	70	8	information	information	NOUN
ajst-30179	70	9	loss	loss	NOUN
ajst-30179	70	10	.	.	PUNCT
ajst-30179	71	1	to	to	PART
ajst-30179	71	2	address	address	VERB
ajst-30179	71	3	this	this	DET
ajst-30179	71	4	limitation	limitation	NOUN
ajst-30179	71	5	,	,	PUNCT
ajst-30179	71	6	an	an	DET
ajst-30179	71	7	additional	additional	ADJ
ajst-30179	71	8	semantic	semantic	ADJ
ajst-30179	71	9	-	-	PUNCT
ajst-30179	71	10	assisted	assist	VERB
ajst-30179	71	11	optimization	optimization	NOUN
ajst-30179	71	12	branch	branch	NOUN
ajst-30179	71	13	(	(	PUNCT
ajst-30179	71	14	referred	refer	VERB
ajst-30179	71	15	to	to	ADP
ajst-30179	71	16	as	as	SCONJ
ajst-30179	71	17	the	the	DET
ajst-30179	71	18	"	"	PUNCT
ajst-30179	71	19	fourth	fourth	ADJ
ajst-30179	71	20	branch	branch	NOUN
ajst-30179	71	21	"	"	PUNCT
ajst-30179	71	22	)	)	PUNCT
ajst-30179	71	23	is	be	AUX
ajst-30179	71	24	introduced	introduce	VERB
ajst-30179	71	25	.	.	PUNCT
ajst-30179	72	1	this	this	DET
ajst-30179	72	2	branch	branch	NOUN
ajst-30179	72	3	enhances	enhance	VERB
ajst-30179	72	4	the	the	DET
ajst-30179	72	5	model	model	NOUN
ajst-30179	72	6	’s	’s	PART
ajst-30179	72	7	performance	performance	NOUN
ajst-30179	72	8	as	as	SCONJ
ajst-30179	72	9	follows	follow	VERB
ajst-30179	72	10	:	:	PUNCT
ajst-30179	72	11	when	when	SCONJ
ajst-30179	72	12	the	the	DET
ajst-30179	72	13	feature	feature	NOUN
ajst-30179	72	14	map	map	NOUN
ajst-30179	72	15	is	be	AUX
ajst-30179	72	16	downsampled	downsample	VERB
ajst-30179	72	17	to	to	ADP
ajst-30179	72	18	1/4	1/4	NUM
ajst-30179	72	19	of	of	ADP
ajst-30179	72	20	the	the	DET
ajst-30179	72	21	original	original	ADJ
ajst-30179	72	22	size	size	NOUN
ajst-30179	72	23	,	,	PUNCT
ajst-30179	72	24	it	it	PRON
ajst-30179	72	25	is	be	AUX
ajst-30179	72	26	processed	process	VERB
ajst-30179	72	27	through	through	ADP
ajst-30179	72	28	the	the	DET
ajst-30179	72	29	efficient	efficient	ADJ
ajst-30179	72	30	upconvolution	upconvolution	NOUN
ajst-30179	72	31	block	block	NOUN
ajst-30179	72	32	(	(	PUNCT
ajst-30179	72	33	eucb	eucb	ADJ
ajst-30179	72	34	)	)	PUNCT
ajst-30179	72	35	to	to	PART
ajst-30179	72	36	increase	increase	VERB
ajst-30179	72	37	the	the	DET
ajst-30179	72	38	number	number	NOUN
ajst-30179	72	39	of	of	ADP
ajst-30179	72	40	channels	channel	NOUN
ajst-30179	72	41	.	.	PUNCT
ajst-30179	73	1	more	more	ADJ
ajst-30179	73	2	channels	channel	NOUN
ajst-30179	73	3	allow	allow	VERB
ajst-30179	73	4	the	the	DET
ajst-30179	73	5	model	model	NOUN
ajst-30179	73	6	to	to	PART
ajst-30179	73	7	capture	capture	VERB
ajst-30179	73	8	richer	rich	ADJ
ajst-30179	73	9	feature	feature	NOUN
ajst-30179	73	10	information	information	NOUN
ajst-30179	73	11	,	,	PUNCT
ajst-30179	73	12	improving	improve	VERB
ajst-30179	73	13	representation	representation	NOUN
ajst-30179	73	14	capability	capability	NOUN
ajst-30179	73	15	and	and	CCONJ
ajst-30179	73	16	accuracy	accuracy	NOUN
ajst-30179	73	17	.	.	PUNCT
ajst-30179	74	1	the	the	DET
ajst-30179	74	2	feature	feature	NOUN
ajst-30179	74	3	map	map	NOUN
ajst-30179	74	4	is	be	AUX
ajst-30179	74	5	then	then	ADV
ajst-30179	74	6	downsampled	downsample	VERB
ajst-30179	74	7	to	to	ADP
ajst-30179	74	8	1/8	1/8	NUM
ajst-30179	74	9	using	use	VERB
ajst-30179	74	10	the	the	DET
ajst-30179	74	11	f.interpolate	f.interpolate	ADJ
ajst-30179	74	12	(	(	PUNCT
ajst-30179	74	13	)	)	PUNCT
ajst-30179	74	14	function	function	NOUN
ajst-30179	74	15	and	and	CCONJ
ajst-30179	74	16	element	element	NOUN
ajst-30179	74	17	-	-	ADJ
ajst-30179	74	18	wise	wise	ADJ
ajst-30179	74	19	added	add	VERB
ajst-30179	74	20	to	to	ADP
ajst-30179	74	21	the	the	DET
ajst-30179	74	22	original	original	ADJ
ajst-30179	74	23	1/8	1/8	NUM
ajst-30179	74	24	resolution	resolution	NOUN
ajst-30179	74	25	feature	feature	NOUN
ajst-30179	74	26	map	map	NOUN
ajst-30179	74	27	.	.	PUNCT
ajst-30179	75	1	the	the	DET
ajst-30179	75	2	resulting	result	VERB
ajst-30179	75	3	feature	feature	NOUN
ajst-30179	75	4	map	map	NOUN
ajst-30179	75	5	is	be	AUX
ajst-30179	75	6	further	far	ADV
ajst-30179	75	7	processed	process	VERB
ajst-30179	75	8	through	through	ADP
ajst-30179	75	9	another	another	DET
ajst-30179	75	10	eucb	eucb	ADJ
ajst-30179	75	11	module	module	NOUN
ajst-30179	75	12	to	to	PART
ajst-30179	75	13	increase	increase	VERB
ajst-30179	75	14	the	the	DET
ajst-30179	75	15	number	number	NOUN
ajst-30179	75	16	of	of	ADP
ajst-30179	75	17	channels	channel	NOUN
ajst-30179	75	18	again	again	ADV
ajst-30179	75	19	and	and	CCONJ
ajst-30179	75	20	undergoes	undergo	VERB
ajst-30179	75	21	another	another	DET
ajst-30179	75	22	downsampling	downsampling	NOUN
ajst-30179	75	23	using	use	VERB
ajst-30179	75	24	f.interpolate().when	f.interpolate().when	ADV
ajst-30179	75	25	the	the	DET
ajst-30179	75	26	feature	feature	NOUN
ajst-30179	75	27	map	map	NOUN
ajst-30179	75	28	reaches	reach	VERB
ajst-30179	75	29	1/64	1/64	NUM
ajst-30179	75	30	of	of	ADP
ajst-30179	75	31	the	the	DET
ajst-30179	75	32	original	original	ADJ
ajst-30179	75	33	image	image	NOUN
ajst-30179	75	34	size	size	NOUN
ajst-30179	75	35	,	,	PUNCT
ajst-30179	75	36	it	it	PRON
ajst-30179	75	37	is	be	AUX
ajst-30179	75	38	fed	feed	VERB
ajst-30179	75	39	into	into	ADP
ajst-30179	75	40	the	the	DET
ajst-30179	75	41	boundary	boundary	ADJ
ajst-30179	75	42	-	-	PUNCT
ajst-30179	75	43	attention	attention	NOUN
ajst-30179	75	44	-	-	PUNCT
ajst-30179	75	45	guided	guide	VERB
ajst-30179	75	46	fusion	fusion	NOUN
ajst-30179	75	47	module	module	NOUN
ajst-30179	75	48	(	(	PUNCT
ajst-30179	75	49	bag	bag	NOUN
ajst-30179	75	50	)	)	PUNCT
ajst-30179	75	51	,	,	PUNCT
ajst-30179	75	52	which	which	PRON
ajst-30179	75	53	introduces	introduce	VERB
ajst-30179	75	54	additional	additional	ADJ
ajst-30179	75	55	feature	feature	NOUN
ajst-30179	75	56	information	information	NOUN
ajst-30179	75	57	to	to	PART
ajst-30179	75	58	further	far	ADV
ajst-30179	75	59	enhance	enhance	VERB
ajst-30179	75	60	the	the	DET
ajst-30179	75	61	model	model	NOUN
ajst-30179	75	62	’s	’s	PART
ajst-30179	75	63	representation	representation	NOUN
ajst-30179	75	64	capability	capability	NOUN
ajst-30179	75	65	and	and	CCONJ
ajst-30179	75	66	adaptability	adaptability	NOUN
ajst-30179	75	67	.	.	PUNCT
ajst-30179	76	1	4.2	4.2	NUM
ajst-30179	76	2	.	.	PUNCT
ajst-30179	77	1	sadam	sadam	PROPN
ajst-30179	77	2	in	in	ADP
ajst-30179	77	3	semantic	semantic	ADJ
ajst-30179	77	4	segmentation	segmentation	NOUN
ajst-30179	77	5	,	,	PUNCT
ajst-30179	77	6	an	an	DET
ajst-30179	77	7	upsampling	upsampling	NOUN
ajst-30179	77	8	module	module	NOUN
ajst-30179	77	9	is	be	AUX
ajst-30179	77	10	used	use	VERB
ajst-30179	77	11	to	to	PART
ajst-30179	77	12	restore	restore	VERB
ajst-30179	77	13	low	low	ADJ
ajst-30179	77	14	-	-	PUNCT
ajst-30179	77	15	resolution	resolution	NOUN
ajst-30179	77	16	feature	feature	NOUN
ajst-30179	77	17	maps	map	NOUN
ajst-30179	77	18	back	back	ADV
ajst-30179	77	19	to	to	ADP
ajst-30179	77	20	the	the	DET
ajst-30179	77	21	same	same	ADJ
ajst-30179	77	22	size	size	NOUN
ajst-30179	77	23	as	as	ADP
ajst-30179	77	24	the	the	DET
ajst-30179	77	25	original	original	ADJ
ajst-30179	77	26	input	input	NOUN
ajst-30179	77	27	image	image	NOUN
ajst-30179	77	28	.	.	PUNCT
ajst-30179	78	1	this	this	DET
ajst-30179	78	2	process	process	NOUN
ajst-30179	78	3	is	be	AUX
ajst-30179	78	4	primarily	primarily	ADV
ajst-30179	78	5	employed	employ	VERB
ajst-30179	78	6	in	in	ADP
ajst-30179	78	7	the	the	DET
ajst-30179	78	8	decoder	decoder	NOUN
ajst-30179	78	9	stage	stage	NOUN
ajst-30179	78	10	of	of	ADP
ajst-30179	78	11	deep	deep	ADJ
ajst-30179	78	12	learning	learning	NOUN
ajst-30179	78	13	models	model	NOUN
ajst-30179	78	14	,	,	PUNCT
ajst-30179	78	15	particularly	particularly	ADV
ajst-30179	78	16	convolutional	convolutional	ADJ
ajst-30179	78	17	neural	neural	ADJ
ajst-30179	78	18	networks	network	NOUN
ajst-30179	78	19	(	(	PUNCT
ajst-30179	78	20	cnns	cnns	PROPN
ajst-30179	78	21	)	)	PUNCT
ajst-30179	78	22	,	,	PUNCT
ajst-30179	78	23	with	with	ADP
ajst-30179	78	24	the	the	DET
ajst-30179	78	25	goal	goal	NOUN
ajst-30179	78	26	of	of	ADP
ajst-30179	78	27	recovering	recover	VERB
ajst-30179	78	28	spatial	spatial	ADJ
ajst-30179	78	29	resolution	resolution	NOUN
ajst-30179	78	30	to	to	PART
ajst-30179	78	31	enable	enable	VERB
ajst-30179	78	32	pixel	pixel	ADJ
ajst-30179	78	33	-	-	ADJ
ajst-30179	78	34	wise	wise	ADJ
ajst-30179	78	35	classification	classification	NOUN
ajst-30179	78	36	.	.	PUNCT
ajst-30179	79	1	semantic	semantic	ADJ
ajst-30179	79	2	segmentation	segmentation	NOUN
ajst-30179	79	3	requires	require	VERB
ajst-30179	79	4	the	the	DET
ajst-30179	79	5	model	model	NOUN
ajst-30179	79	6	to	to	PART
ajst-30179	79	7	classify	classify	VERB
ajst-30179	79	8	each	each	DET
ajst-30179	79	9	pixel	pixel	NOUN
ajst-30179	79	10	in	in	ADP
ajst-30179	79	11	an	an	DET
ajst-30179	79	12	image	image	NOUN
ajst-30179	79	13	.	.	PUNCT
ajst-30179	80	1	typically	typically	ADV
ajst-30179	80	2	,	,	PUNCT
ajst-30179	80	3	deep	deep	ADJ
ajst-30179	80	4	networks	network	NOUN
ajst-30179	80	5	extract	extract	VERB
ajst-30179	80	6	high	high	ADJ
ajst-30179	80	7	-	-	PUNCT
ajst-30179	80	8	level	level	NOUN
ajst-30179	80	9	features	feature	NOUN
ajst-30179	80	10	through	through	ADP
ajst-30179	80	11	multiple	multiple	ADJ
ajst-30179	80	12	layers	layer	NOUN
ajst-30179	80	13	of	of	ADP
ajst-30179	80	14	convolution	convolution	NOUN
ajst-30179	80	15	and	and	CCONJ
ajst-30179	80	16	pooling	pool	VERB
ajst-30179	80	17	operations	operation	NOUN
ajst-30179	80	18	,	,	PUNCT
ajst-30179	80	19	but	but	CCONJ
ajst-30179	80	20	this	this	PRON
ajst-30179	80	21	also	also	ADV
ajst-30179	80	22	results	result	VERB
ajst-30179	80	23	in	in	ADP
ajst-30179	80	24	a	a	DET
ajst-30179	80	25	loss	loss	NOUN
ajst-30179	80	26	of	of	ADP
ajst-30179	80	27	spatial	spatial	ADJ
ajst-30179	80	28	resolution	resolution	NOUN
ajst-30179	80	29	.	.	PUNCT
ajst-30179	81	1	to	to	PART
ajst-30179	81	2	address	address	VERB
ajst-30179	81	3	this	this	DET
ajst-30179	81	4	issue	issue	NOUN
ajst-30179	81	5	,	,	PUNCT
ajst-30179	81	6	this	this	DET
ajst-30179	81	7	paper	paper	NOUN
ajst-30179	81	8	introduces	introduce	VERB
ajst-30179	81	9	an	an	DET
ajst-30179	81	10	upsampling	upsampling	NOUN
ajst-30179	81	11	module	module	NOUN
ajst-30179	81	12	called	call	VERB
ajst-30179	81	13	the	the	DET
ajst-30179	81	14	scale	scale	NOUN
ajst-30179	81	15	-	-	PUNCT
ajst-30179	81	16	aware	aware	ADJ
ajst-30179	81	17	depthwise	depthwise	NOUN
ajst-30179	81	18	separable	separable	ADJ
ajst-30179	81	19	convolution	convolution	NOUN
ajst-30179	81	20	attention	attention	NOUN
ajst-30179	81	21	module	module	NOUN
ajst-30179	81	22	(	(	PUNCT
ajst-30179	81	23	sadam).the	sadam).the	DET
ajst-30179	81	24	workflow	workflow	NOUN
ajst-30179	81	25	of	of	ADP
ajst-30179	81	26	sadam	sadam	PROPN
ajst-30179	81	27	is	be	AUX
ajst-30179	81	28	as	as	SCONJ
ajst-30179	81	29	follows	follow	VERB
ajst-30179	81	30	:	:	PUNCT
ajst-30179	81	31	feature	feature	NOUN
ajst-30179	81	32	extraction	extraction	NOUN
ajst-30179	81	33	:	:	PUNCT
ajst-30179	81	34	receives	receive	VERB
ajst-30179	81	35	an	an	DET
ajst-30179	81	36	rgb	rgb	PROPN
ajst-30179	81	37	input	input	NOUN
ajst-30179	81	38	image	image	NOUN
ajst-30179	81	39	(	(	PUNCT
ajst-30179	81	40	assumed	assume	VERB
ajst-30179	81	41	to	to	PART
ajst-30179	81	42	have	have	VERB
ajst-30179	81	43	dimensions	dimension	NOUN
ajst-30179	81	44	h×w×3).the	h×w×3).the	DET
ajst-30179	81	45	input	input	NOUN
ajst-30179	81	46	passes	pass	VERB
ajst-30179	81	47	through	through	ADP
ajst-30179	81	48	an	an	DET
ajst-30179	81	49	initial	initial	ADJ
ajst-30179	81	50	convolution	convolution	NOUN
ajst-30179	81	51	layer	layer	NOUN
ajst-30179	81	52	(	(	PUNCT
ajst-30179	81	53	conv	conv	ADJ
ajst-30179	81	54	)	)	PUNCT
ajst-30179	81	55	for	for	ADP
ajst-30179	81	56	feature	feature	NOUN
ajst-30179	81	57	extraction	extraction	NOUN
ajst-30179	81	58	,	,	PUNCT
ajst-30179	81	59	producing	produce	VERB
ajst-30179	81	60	an	an	DET
ajst-30179	81	61	output	output	NOUN
ajst-30179	81	62	feature	feature	NOUN
ajst-30179	81	63	map	map	NOUN
ajst-30179	81	64	of	of	ADP
ajst-30179	81	65	size	size	NOUN
ajst-30179	81	66	h×w×64	h×w×64	VERB
ajst-30179	81	67	with	with	ADP
ajst-30179	81	68	64	64	NUM
ajst-30179	81	69	channels	channel	NOUN
ajst-30179	81	70	.	.	PUNCT
ajst-30179	82	1	core	core	NOUN
ajst-30179	82	2	module	module	NOUN
ajst-30179	82	3	–	–	PUNCT
ajst-30179	82	4	multi	multi	ADJ
ajst-30179	82	5	-	-	ADJ
ajst-30179	82	6	branch	branch	ADJ
ajst-30179	82	7	depthwise	depthwise	NOUN
ajst-30179	82	8	separable	separable	ADJ
ajst-30179	82	9	convolution	convolution	NOUN
ajst-30179	82	10	(	(	PUNCT
ajst-30179	82	11	dwc):the	dwc):the	PRON
ajst-30179	82	12	feature	feature	NOUN
ajst-30179	82	13	map	map	NOUN
ajst-30179	82	14	is	be	AUX
ajst-30179	82	15	split	split	VERB
ajst-30179	82	16	into	into	ADP
ajst-30179	82	17	two	two	NUM
ajst-30179	82	18	branches	branch	NOUN
ajst-30179	82	19	for	for	ADP
ajst-30179	82	20	parallel	parallel	ADJ
ajst-30179	82	21	processing	processing	NOUN
ajst-30179	82	22	:	:	PUNCT
ajst-30179	82	23	left	left	ADJ
ajst-30179	82	24	branch	branch	NOUN
ajst-30179	82	25	:	:	PUNCT
ajst-30179	82	26	depthwise	depthwise	VERB
ajst-30179	82	27	separable	separable	ADJ
ajst-30179	82	28	convolutions	convolution	NOUN
ajst-30179	82	29	(	(	PUNCT
ajst-30179	82	30	dwc	dwc	PROPN
ajst-30179	82	31	)	)	PUNCT
ajst-30179	82	32	with	with	ADP
ajst-30179	82	33	dilation	dilation	NOUN
ajst-30179	82	34	rates	rate	NOUN
ajst-30179	82	35	d	d	NOUN
ajst-30179	82	36	=	=	SYM
ajst-30179	82	37	{	{	PUNCT
ajst-30179	82	38	1	1	NUM
ajst-30179	82	39	,	,	PUNCT
ajst-30179	82	40	2	2	NUM
ajst-30179	82	41	,	,	PUNCT
ajst-30179	82	42	3	3	NUM
ajst-30179	82	43	}	}	PUNCT
ajst-30179	82	44	,	,	PUNCT
ajst-30179	82	45	capturing	capture	VERB
ajst-30179	82	46	multi	multi	ADJ
ajst-30179	82	47	-	-	ADJ
ajst-30179	82	48	scale	scale	ADJ
ajst-30179	82	49	contextual	contextual	ADJ
ajst-30179	82	50	information	information	NOUN
ajst-30179	82	51	.	.	PUNCT
ajst-30179	83	1	a	a	DET
ajst-30179	83	2	1×1	1×1	NUM
ajst-30179	83	3	convolution	convolution	NOUN
ajst-30179	83	4	is	be	AUX
ajst-30179	83	5	applied	apply	VERB
ajst-30179	83	6	to	to	PART
ajst-30179	83	7	adjust	adjust	VERB
ajst-30179	83	8	the	the	DET
ajst-30179	83	9	channel	channel	NOUN
ajst-30179	83	10	dimensions	dimension	NOUN
ajst-30179	83	11	,	,	PUNCT
ajst-30179	83	12	maintaining	maintain	VERB
ajst-30179	83	13	64	64	NUM
ajst-30179	83	14	output	output	NOUN
ajst-30179	83	15	channels	channel	NOUN
ajst-30179	83	16	per	per	ADP
ajst-30179	83	17	branch	branch	NOUN
ajst-30179	83	18	.	.	PUNCT
ajst-30179	84	1	the	the	DET
ajst-30179	84	2	feature	feature	NOUN
ajst-30179	84	3	maps	map	NOUN
ajst-30179	84	4	are	be	AUX
ajst-30179	84	5	bilinearly	bilinearly	ADV
ajst-30179	84	6	upsampled	upsample	VERB
ajst-30179	84	7	to	to	PART
ajst-30179	84	8	restore	restore	VERB
ajst-30179	84	9	their	their	PRON
ajst-30179	84	10	spatial	spatial	ADJ
ajst-30179	84	11	resolution	resolution	NOUN
ajst-30179	84	12	(	(	PUNCT
ajst-30179	84	13	h×w).right	h×w).right	NUM
ajst-30179	84	14	branch	branch	NOUN
ajst-30179	84	15	:	:	PUNCT
ajst-30179	84	16	global	global	ADJ
ajst-30179	84	17	average	average	ADJ
ajst-30179	84	18	pooling	pooling	NOUN
ajst-30179	84	19	(	(	PUNCT
ajst-30179	84	20	gap	gap	NOUN
ajst-30179	84	21	)	)	PUNCT
ajst-30179	84	22	is	be	AUX
ajst-30179	84	23	used	use	VERB
ajst-30179	84	24	to	to	PART
ajst-30179	84	25	compress	compress	VERB
ajst-30179	84	26	spatial	spatial	ADJ
ajst-30179	84	27	information	information	NOUN
ajst-30179	84	28	,	,	PUNCT
ajst-30179	84	29	reducing	reduce	VERB
ajst-30179	84	30	the	the	DET
ajst-30179	84	31	spatial	spatial	ADJ
ajst-30179	84	32	dimensions	dimension	NOUN
ajst-30179	84	33	to	to	ADP
ajst-30179	84	34	1×1×64.a	1×1×64.a	NUM
ajst-30179	84	35	fully	fully	ADV
ajst-30179	84	36	connected	connect	VERB
ajst-30179	84	37	layer	layer	NOUN
ajst-30179	84	38	(	(	PUNCT
ajst-30179	84	39	fc	fc	INTJ
ajst-30179	84	40	)	)	PUNCT
ajst-30179	84	41	followed	follow	VERB
ajst-30179	84	42	by	by	ADP
ajst-30179	84	43	non	non	ADJ
ajst-30179	84	44	-	-	ADJ
ajst-30179	84	45	linear	linear	ADJ
ajst-30179	84	46	activation	activation	NOUN
ajst-30179	84	47	functions	function	NOUN
ajst-30179	84	48	(	(	PUNCT
ajst-30179	84	49	e.g.	e.g.	ADV
ajst-30179	84	50	,	,	PUNCT
ajst-30179	84	51	relu	relu	NOUN
ajst-30179	84	52	/	/	SYM
ajst-30179	84	53	sigmoid	sigmoid	NOUN
ajst-30179	84	54	)	)	PUNCT
ajst-30179	84	55	generates	generate	VERB
ajst-30179	84	56	channel	channel	NOUN
ajst-30179	84	57	attention	attention	NOUN
ajst-30179	84	58	weights	weight	NOUN
ajst-30179	84	59	.	.	PUNCT
ajst-30179	85	1	these	these	DET
ajst-30179	85	2	weights	weight	NOUN
ajst-30179	85	3	are	be	AUX
ajst-30179	85	4	64	64	NUM
ajst-30179	85	5	applied	apply	VERB
ajst-30179	85	6	to	to	ADP
ajst-30179	85	7	channel	channel	NOUN
ajst-30179	85	8	-	-	PUNCT
ajst-30179	85	9	wise	wise	ADJ
ajst-30179	85	10	scale	scale	NOUN
ajst-30179	85	11	the	the	DET
ajst-30179	85	12	left	left	ADJ
ajst-30179	85	13	branch	branch	NOUN
ajst-30179	85	14	features	feature	NOUN
ajst-30179	85	15	.	.	PUNCT
ajst-30179	86	1	feature	feature	NOUN
ajst-30179	86	2	fusion	fusion	NOUN
ajst-30179	86	3	&	&	CCONJ
ajst-30179	86	4	attention	attention	NOUN
ajst-30179	86	5	map	map	NOUN
ajst-30179	86	6	generation	generation	NOUN
ajst-30179	86	7	:	:	PUNCT
ajst-30179	86	8	the	the	DET
ajst-30179	86	9	left	left	ADJ
ajst-30179	86	10	and	and	CCONJ
ajst-30179	86	11	right	right	ADJ
ajst-30179	86	12	branch	branch	NOUN
ajst-30179	86	13	outputs	output	NOUN
ajst-30179	86	14	are	be	AUX
ajst-30179	86	15	element	element	ADJ
ajst-30179	86	16	-	-	ADJ
ajst-30179	86	17	wise	wise	ADJ
ajst-30179	86	18	multiplied	multiply	VERB
ajst-30179	86	19	to	to	PART
ajst-30179	86	20	fuse	fuse	VERB
ajst-30179	86	21	the	the	DET
ajst-30179	86	22	features	feature	NOUN
ajst-30179	86	23	.	.	PUNCT
ajst-30179	87	1	the	the	DET
ajst-30179	87	2	result	result	NOUN
ajst-30179	87	3	is	be	AUX
ajst-30179	87	4	passed	pass	VERB
ajst-30179	87	5	through	through	ADP
ajst-30179	87	6	a	a	DET
ajst-30179	87	7	sigmoid	sigmoid	NOUN
ajst-30179	87	8	activation	activation	NOUN
ajst-30179	87	9	function	function	NOUN
ajst-30179	87	10	,	,	PUNCT
ajst-30179	87	11	producing	produce	VERB
ajst-30179	87	12	the	the	DET
ajst-30179	87	13	final	final	ADJ
ajst-30179	87	14	attention	attention	NOUN
ajst-30179	87	15	heatmap	heatmap	NOUN
ajst-30179	87	16	of	of	ADP
ajst-30179	87	17	size	size	NOUN
ajst-30179	87	18	h×w×1	h×w×1	PROPN
ajst-30179	87	19	,	,	PUNCT
ajst-30179	87	20	with	with	ADP
ajst-30179	87	21	values	value	NOUN
ajst-30179	87	22	normalized	normalize	VERB
ajst-30179	87	23	in	in	ADP
ajst-30179	87	24	the	the	DET
ajst-30179	87	25	range	range	NOUN
ajst-30179	87	26	[	[	X
ajst-30179	87	27	0,1	0,1	NUM
ajst-30179	87	28	]	]	PUNCT
ajst-30179	87	29	.	.	PUNCT
ajst-30179	88	1	this	this	DET
ajst-30179	88	2	entire	entire	ADJ
ajst-30179	88	3	process	process	NOUN
ajst-30179	88	4	emphasizes	emphasize	VERB
ajst-30179	88	5	multi	multi	ADJ
ajst-30179	88	6	-	-	ADJ
ajst-30179	88	7	scale	scale	ADJ
ajst-30179	88	8	feature	feature	NOUN
ajst-30179	88	9	fusion	fusion	NOUN
ajst-30179	88	10	and	and	CCONJ
ajst-30179	88	11	dynamic	dynamic	ADJ
ajst-30179	88	12	channel	channel	NOUN
ajst-30179	88	13	attention	attention	NOUN
ajst-30179	88	14	adjustment	adjustment	NOUN
ajst-30179	88	15	,	,	PUNCT
ajst-30179	88	16	making	make	VERB
ajst-30179	88	17	it	it	PRON
ajst-30179	88	18	highly	highly	ADV
ajst-30179	88	19	suitable	suitable	ADJ
ajst-30179	88	20	for	for	ADP
ajst-30179	88	21	handling	handle	VERB
ajst-30179	88	22	complex	complex	ADJ
ajst-30179	88	23	semantic	semantic	ADJ
ajst-30179	88	24	segmentation	segmentation	NOUN
ajst-30179	88	25	tasks	task	NOUN
ajst-30179	88	26	.	.	PUNCT
ajst-30179	89	1	the	the	DET
ajst-30179	89	2	sadam	sadam	PROPN
ajst-30179	89	3	model	model	NOUN
ajst-30179	89	4	structure	structure	NOUN
ajst-30179	89	5	is	be	AUX
ajst-30179	89	6	illustrated	illustrate	VERB
ajst-30179	89	7	in	in	ADP
ajst-30179	89	8	figure	figure	NOUN
ajst-30179	89	9	4	4	NUM
ajst-30179	89	10	-	-	SYM
ajst-30179	89	11	1	1	NUM
ajst-30179	89	12	.	.	PUNCT
ajst-30179	89	13	figure	figure	VERB
ajst-30179	89	14	4	4	NUM
ajst-30179	89	15	-	-	SYM
ajst-30179	89	16	1	1	NUM
ajst-30179	89	17	.	.	PUNCT
ajst-30179	90	1	sadam	sadam	PROPN
ajst-30179	90	2	model	model	PROPN
ajst-30179	90	3	diagram	diagram	PROPN
ajst-30179	90	4	4.3	4.3	NUM
ajst-30179	90	5	.	.	PUNCT
ajst-30179	91	1	loss	loss	NOUN
ajst-30179	91	2	function	function	NOUN
ajst-30179	91	3	in	in	ADP
ajst-30179	91	4	deep	deep	ADJ
ajst-30179	91	5	learning	learning	NOUN
ajst-30179	91	6	,	,	PUNCT
ajst-30179	91	7	the	the	DET
ajst-30179	91	8	loss	loss	NOUN
ajst-30179	91	9	function	function	NOUN
ajst-30179	91	10	is	be	AUX
ajst-30179	91	11	crucial	crucial	ADJ
ajst-30179	91	12	for	for	ADP
ajst-30179	91	13	model	model	NOUN
ajst-30179	91	14	training	training	NOUN
ajst-30179	91	15	.	.	PUNCT
ajst-30179	92	1	in	in	ADP
ajst-30179	92	2	the	the	DET
ajst-30179	92	3	pidnet	pidnet	NOUN
ajst-30179	92	4	network	network	NOUN
ajst-30179	92	5	,	,	PUNCT
ajst-30179	92	6	ohemcrossentropy	ohemcrossentropy	ADJ
ajst-30179	92	7	or	or	CCONJ
ajst-30179	92	8	crossentropy	crossentropy	NOUN
ajst-30179	92	9	is	be	AUX
ajst-30179	92	10	selected	select	VERB
ajst-30179	92	11	as	as	ADP
ajst-30179	92	12	the	the	DET
ajst-30179	92	13	base	base	NOUN
ajst-30179	92	14	loss	loss	NOUN
ajst-30179	92	15	function	function	NOUN
ajst-30179	92	16	.	.	PUNCT
ajst-30179	93	1	the	the	DET
ajst-30179	93	2	former	former	ADJ
ajst-30179	93	3	accelerates	accelerate	VERB
ajst-30179	93	4	training	training	NOUN
ajst-30179	93	5	by	by	ADP
ajst-30179	93	6	selecting	select	VERB
ajst-30179	93	7	difficult	difficult	ADJ
ajst-30179	93	8	samples	sample	NOUN
ajst-30179	93	9	during	during	ADP
ajst-30179	93	10	the	the	DET
ajst-30179	93	11	training	training	NOUN
ajst-30179	93	12	process	process	NOUN
ajst-30179	93	13	,	,	PUNCT
ajst-30179	93	14	while	while	SCONJ
ajst-30179	93	15	the	the	DET
ajst-30179	93	16	latter	latter	ADJ
ajst-30179	93	17	calculates	calculate	VERB
ajst-30179	93	18	cross	cross	ADJ
ajst-30179	93	19	-	-	ADJ
ajst-30179	93	20	entropy	entropy	ADJ
ajst-30179	93	21	loss	loss	NOUN
ajst-30179	93	22	for	for	ADP
ajst-30179	93	23	all	all	DET
ajst-30179	93	24	samples	sample	NOUN
ajst-30179	93	25	without	without	ADP
ajst-30179	93	26	distinguishing	distinguish	VERB
ajst-30179	93	27	between	between	ADP
ajst-30179	93	28	difficult	difficult	ADJ
ajst-30179	93	29	and	and	CCONJ
ajst-30179	93	30	simple	simple	ADJ
ajst-30179	93	31	samples	sample	NOUN
ajst-30179	93	32	.	.	PUNCT
ajst-30179	94	1	this	this	DET
ajst-30179	94	2	paper	paper	NOUN
ajst-30179	94	3	designs	design	VERB
ajst-30179	94	4	a	a	DET
ajst-30179	94	5	combined	combine	VERB
ajst-30179	94	6	loss	loss	NOUN
ajst-30179	94	7	function	function	NOUN
ajst-30179	94	8	,	,	PUNCT
ajst-30179	94	9	combinedloss	combinedloss	PROPN
ajst-30179	94	10	,	,	PUNCT
ajst-30179	94	11	which	which	PRON
ajst-30179	94	12	combines	combine	VERB
ajst-30179	94	13	multiple	multiple	ADJ
ajst-30179	94	14	loss	loss	NOUN
ajst-30179	94	15	functions	function	NOUN
ajst-30179	94	16	and	and	CCONJ
ajst-30179	94	17	controls	control	VERB
ajst-30179	94	18	the	the	DET
ajst-30179	94	19	weight	weight	NOUN
ajst-30179	94	20	of	of	ADP
ajst-30179	94	21	each	each	DET
ajst-30179	94	22	loss	loss	NOUN
ajst-30179	94	23	function	function	NOUN
ajst-30179	94	24	in	in	ADP
ajst-30179	94	25	the	the	DET
ajst-30179	94	26	final	final	ADJ
ajst-30179	94	27	loss	loss	NOUN
ajst-30179	94	28	calculation	calculation	NOUN
ajst-30179	94	29	.	.	PUNCT
ajst-30179	95	1	with	with	ADP
ajst-30179	95	2	alpha	alpha	NOUN
ajst-30179	95	3	set	set	VERB
ajst-30179	95	4	to	to	ADP
ajst-30179	95	5	0.7	0.7	NUM
ajst-30179	95	6	,	,	PUNCT
ajst-30179	95	7	ohemcrossentropy	ohemcrossentropy	ADJ
ajst-30179	95	8	contributes	contribute	VERB
ajst-30179	95	9	70	70	NUM
ajst-30179	95	10	%	%	NOUN
ajst-30179	95	11	to	to	ADP
ajst-30179	95	12	the	the	DET
ajst-30179	95	13	loss	loss	NOUN
ajst-30179	95	14	.	.	PUNCT
ajst-30179	96	1	the	the	DET
ajst-30179	96	2	goal	goal	NOUN
ajst-30179	96	3	is	be	AUX
ajst-30179	96	4	to	to	PART
ajst-30179	96	5	leverage	leverage	VERB
ajst-30179	96	6	different	different	ADJ
ajst-30179	96	7	loss	loss	NOUN
ajst-30179	96	8	information	information	NOUN
ajst-30179	96	9	to	to	PART
ajst-30179	96	10	enhance	enhance	VERB
ajst-30179	96	11	the	the	DET
ajst-30179	96	12	model	model	NOUN
ajst-30179	96	13	's	's	PART
ajst-30179	96	14	training	training	NOUN
ajst-30179	96	15	performance	performance	NOUN
ajst-30179	96	16	while	while	SCONJ
ajst-30179	96	17	optimizing	optimize	VERB
ajst-30179	96	18	pixel	pixel	ADJ
ajst-30179	96	19	-	-	PUNCT
ajst-30179	96	20	level	level	NOUN
ajst-30179	96	21	accuracy	accuracy	NOUN
ajst-30179	96	22	and	and	CCONJ
ajst-30179	96	23	shape	shape	NOUN
ajst-30179	96	24	similarity	similarity	NOUN
ajst-30179	96	25	.	.	PUNCT
ajst-30179	97	1	5	5	X
ajst-30179	97	2	.	.	X
ajst-30179	97	3	conclusion	conclusion	NOUN
ajst-30179	97	4	this	this	DET
ajst-30179	97	5	paper	paper	NOUN
ajst-30179	97	6	focuses	focus	VERB
ajst-30179	97	7	on	on	ADP
ajst-30179	97	8	the	the	DET
ajst-30179	97	9	optimization	optimization	NOUN
ajst-30179	97	10	and	and	CCONJ
ajst-30179	97	11	improvement	improvement	NOUN
ajst-30179	97	12	of	of	ADP
ajst-30179	97	13	pidnet	pidnet	NOUN
ajst-30179	97	14	.	.	PUNCT
ajst-30179	98	1	first	first	ADV
ajst-30179	98	2	,	,	PUNCT
ajst-30179	98	3	a	a	DET
ajst-30179	98	4	scale	scale	NOUN
ajst-30179	98	5	-	-	PUNCT
ajst-30179	98	6	aware	aware	ADJ
ajst-30179	98	7	depth	depth	NOUN
ajst-30179	98	8	-	-	PUNCT
ajst-30179	98	9	separable	separable	NOUN
ajst-30179	98	10	convolution	convolution	NOUN
ajst-30179	98	11	attention	attention	NOUN
ajst-30179	98	12	module	module	NOUN
ajst-30179	98	13	(	(	PUNCT
ajst-30179	98	14	sadam	sadam	PROPN
ajst-30179	98	15	)	)	PUNCT
ajst-30179	98	16	is	be	AUX
ajst-30179	98	17	designed	design	VERB
ajst-30179	98	18	as	as	ADP
ajst-30179	98	19	an	an	DET
ajst-30179	98	20	upsampling	upsampling	NOUN
ajst-30179	98	21	module	module	NOUN
ajst-30179	98	22	.	.	PUNCT
ajst-30179	99	1	through	through	ADP
ajst-30179	99	2	three	three	NUM
ajst-30179	99	3	parallel	parallel	ADJ
ajst-30179	99	4	depth	depth	NOUN
ajst-30179	99	5	-	-	PUNCT
ajst-30179	99	6	separable	separable	NOUN
ajst-30179	99	7	convolution	convolution	NOUN
ajst-30179	99	8	branches	branch	NOUN
ajst-30179	99	9	(	(	PUNCT
ajst-30179	99	10	with	with	ADP
ajst-30179	99	11	dilation	dilation	NOUN
ajst-30179	99	12	rates	rate	NOUN
ajst-30179	99	13	d=1	d=1	NOUN
ajst-30179	99	14	,	,	PUNCT
ajst-30179	99	15	2	2	NUM
ajst-30179	99	16	,	,	PUNCT
ajst-30179	99	17	and	and	CCONJ
ajst-30179	99	18	3	3	NUM
ajst-30179	99	19	)	)	PUNCT
ajst-30179	99	20	,	,	PUNCT
ajst-30179	99	21	the	the	DET
ajst-30179	99	22	module	module	NOUN
ajst-30179	99	23	captures	capture	VERB
ajst-30179	99	24	features	feature	NOUN
ajst-30179	99	25	of	of	ADP
ajst-30179	99	26	local	local	ADJ
ajst-30179	99	27	details	detail	NOUN
ajst-30179	99	28	(	(	PUNCT
ajst-30179	99	29	d=1	d=1	NOUN
ajst-30179	99	30	)	)	PUNCT
ajst-30179	99	31	,	,	PUNCT
ajst-30179	99	32	medium	medium	ADJ
ajst-30179	99	33	-	-	PUNCT
ajst-30179	99	34	range	range	NOUN
ajst-30179	99	35	(	(	PUNCT
ajst-30179	99	36	d=2	d=2	NOUN
ajst-30179	99	37	)	)	PUNCT
ajst-30179	99	38	,	,	PUNCT
ajst-30179	99	39	and	and	CCONJ
ajst-30179	99	40	global	global	ADJ
ajst-30179	99	41	context	context	NOUN
ajst-30179	99	42	(	(	PUNCT
ajst-30179	99	43	d=3	d=3	PROPN
ajst-30179	99	44	)	)	PUNCT
ajst-30179	99	45	.	.	PUNCT
ajst-30179	100	1	after	after	ADP
ajst-30179	100	2	adding	add	VERB
ajst-30179	100	3	the	the	DET
ajst-30179	100	4	features	feature	NOUN
ajst-30179	100	5	from	from	ADP
ajst-30179	100	6	each	each	DET
ajst-30179	100	7	branch	branch	NOUN
ajst-30179	100	8	,	,	PUNCT
ajst-30179	100	9	a	a	DET
ajst-30179	100	10	1×1	1×1	NUM
ajst-30179	100	11	convolution	convolution	NOUN
ajst-30179	100	12	is	be	AUX
ajst-30179	100	13	applied	apply	VERB
ajst-30179	100	14	to	to	PART
ajst-30179	100	15	adjust	adjust	VERB
ajst-30179	100	16	the	the	DET
ajst-30179	100	17	channel	channel	NOUN
ajst-30179	100	18	number	number	NOUN
ajst-30179	100	19	,	,	PUNCT
ajst-30179	100	20	ensuring	ensure	VERB
ajst-30179	100	21	effective	effective	ADJ
ajst-30179	100	22	integration	integration	NOUN
ajst-30179	100	23	of	of	ADP
ajst-30179	100	24	multi	multi	ADJ
ajst-30179	100	25	-	-	ADJ
ajst-30179	100	26	scale	scale	ADJ
ajst-30179	100	27	information	information	NOUN
ajst-30179	100	28	and	and	CCONJ
ajst-30179	100	29	maintaining	maintain	VERB
ajst-30179	100	30	consistency	consistency	NOUN
ajst-30179	100	31	with	with	ADP
ajst-30179	100	32	the	the	DET
ajst-30179	100	33	original	original	ADJ
ajst-30179	100	34	input	input	NOUN
ajst-30179	100	35	size	size	NOUN
ajst-30179	100	36	to	to	PART
ajst-30179	100	37	avoid	avoid	VERB
ajst-30179	100	38	information	information	NOUN
ajst-30179	100	39	loss	loss	NOUN
ajst-30179	100	40	.	.	PUNCT
ajst-30179	101	1	the	the	DET
ajst-30179	101	2	internal	internal	ADJ
ajst-30179	101	3	branches	branch	NOUN
ajst-30179	101	4	extract	extract	VERB
ajst-30179	101	5	channel	channel	NOUN
ajst-30179	101	6	-	-	PUNCT
ajst-30179	101	7	level	level	NOUN
ajst-30179	101	8	information	information	NOUN
ajst-30179	101	9	through	through	ADP
ajst-30179	101	10	global	global	ADJ
ajst-30179	101	11	average	average	ADJ
ajst-30179	101	12	pooling	pooling	NOUN
ajst-30179	101	13	(	(	PUNCT
ajst-30179	101	14	gap	gap	NOUN
ajst-30179	101	15	)	)	PUNCT
ajst-30179	101	16	and	and	CCONJ
ajst-30179	101	17	use	use	VERB
ajst-30179	101	18	a	a	DET
ajst-30179	101	19	compression	compression	NOUN
ajst-30179	101	20	-	-	PUNCT
ajst-30179	101	21	expansion	expansion	NOUN
ajst-30179	101	22	structure	structure	NOUN
ajst-30179	101	23	in	in	ADP
ajst-30179	101	24	the	the	DET
ajst-30179	101	25	fully	fully	ADV
ajst-30179	101	26	connected	connected	ADJ
ajst-30179	101	27	layer	layer	NOUN
ajst-30179	101	28	to	to	PART
ajst-30179	101	29	generate	generate	VERB
ajst-30179	101	30	channel	channel	NOUN
ajst-30179	101	31	attention	attention	NOUN
ajst-30179	101	32	weights	weight	NOUN
ajst-30179	101	33	.	.	PUNCT
ajst-30179	102	1	sigmoid	sigmoid	NOUN
ajst-30179	102	2	outputs	output	VERB
ajst-30179	102	3	the	the	DET
ajst-30179	102	4	activation	activation	NOUN
ajst-30179	102	5	strength	strength	NOUN
ajst-30179	102	6	of	of	ADP
ajst-30179	102	7	each	each	DET
ajst-30179	102	8	channel	channel	NOUN
ajst-30179	102	9	,	,	PUNCT
ajst-30179	102	10	suppressing	suppress	VERB
ajst-30179	102	11	redundant	redundant	ADJ
ajst-30179	102	12	features	feature	NOUN
ajst-30179	102	13	and	and	CCONJ
ajst-30179	102	14	enhancing	enhance	VERB
ajst-30179	102	15	key	key	ADJ
ajst-30179	102	16	channels	channel	NOUN
ajst-30179	102	17	.	.	PUNCT
ajst-30179	103	1	the	the	DET
ajst-30179	103	2	separation	separation	NOUN
ajst-30179	103	3	of	of	ADP
ajst-30179	103	4	spatial	spatial	ADJ
ajst-30179	103	5	convolution	convolution	NOUN
ajst-30179	103	6	and	and	CCONJ
ajst-30179	103	7	channel	channel	NOUN
ajst-30179	103	8	projection	projection	NOUN
ajst-30179	103	9	reduces	reduce	VERB
ajst-30179	103	10	about	about	ADV
ajst-30179	103	11	90	90	NUM
ajst-30179	103	12	%	%	NOUN
ajst-30179	103	13	of	of	ADP
ajst-30179	103	14	the	the	DET
ajst-30179	103	15	computational	computational	ADJ
ajst-30179	103	16	cost	cost	NOUN
ajst-30179	103	17	compared	compare	VERB
ajst-30179	103	18	to	to	ADP
ajst-30179	103	19	standard	standard	ADJ
ajst-30179	103	20	convolution	convolution	NOUN
ajst-30179	103	21	,	,	PUNCT
ajst-30179	103	22	maintaining	maintain	VERB
ajst-30179	103	23	the	the	DET
ajst-30179	103	24	lightweight	lightweight	ADJ
ajst-30179	103	25	characteristics	characteristic	NOUN
ajst-30179	103	26	of	of	ADP
ajst-30179	103	27	the	the	DET
ajst-30179	103	28	overall	overall	ADJ
ajst-30179	103	29	module	module	NOUN
ajst-30179	103	30	.	.	PUNCT
ajst-30179	104	1	then	then	ADV
ajst-30179	104	2	,	,	PUNCT
ajst-30179	104	3	a	a	DET
ajst-30179	104	4	"	"	PUNCT
ajst-30179	104	5	fourth	fourth	ADJ
ajst-30179	104	6	branch	branch	NOUN
ajst-30179	104	7	"	"	PUNCT
ajst-30179	104	8	(	(	PUNCT
ajst-30179	104	9	semantic	semantic	ADJ
ajst-30179	104	10	-	-	PUNCT
ajst-30179	104	11	assisted	assist	VERB
ajst-30179	104	12	optimization	optimization	NOUN
ajst-30179	104	13	branch	branch	NOUN
ajst-30179	104	14	)	)	PUNCT
ajst-30179	104	15	is	be	AUX
ajst-30179	104	16	proposed	propose	VERB
ajst-30179	104	17	to	to	PART
ajst-30179	104	18	solve	solve	VERB
ajst-30179	104	19	the	the	DET
ajst-30179	104	20	problem	problem	NOUN
ajst-30179	104	21	of	of	ADP
ajst-30179	104	22	feature	feature	NOUN
ajst-30179	104	23	loss	loss	NOUN
ajst-30179	104	24	during	during	ADP
ajst-30179	104	25	the	the	DET
ajst-30179	104	26	downsampling	downsample	VERB
ajst-30179	104	27	process	process	NOUN
ajst-30179	104	28	in	in	ADP
ajst-30179	104	29	the	the	DET
ajst-30179	104	30	original	original	ADJ
ajst-30179	104	31	pidnet	pidnet	NOUN
ajst-30179	104	32	.	.	PUNCT
ajst-30179	105	1	finally	finally	ADV
ajst-30179	105	2	,	,	PUNCT
ajst-30179	105	3	a	a	DET
ajst-30179	105	4	combined	combine	VERB
ajst-30179	105	5	loss	loss	NOUN
ajst-30179	105	6	function	function	NOUN
ajst-30179	105	7	,	,	PUNCT
ajst-30179	105	8	combinedloss	combinedloss	PROPN
ajst-30179	105	9	,	,	PUNCT
ajst-30179	105	10	is	be	AUX
ajst-30179	105	11	designed	design	VERB
ajst-30179	105	12	,	,	PUNCT
ajst-30179	105	13	combining	combine	VERB
ajst-30179	105	14	ohemcrossentropy	ohemcrossentropy	NOUN
ajst-30179	105	15	(	(	PUNCT
ajst-30179	105	16	70	70	NUM
ajst-30179	105	17	%	%	NOUN
ajst-30179	105	18	)	)	PUNCT
ajst-30179	105	19	and	and	CCONJ
ajst-30179	105	20	crossentropy	crossentropy	NOUN
ajst-30179	105	21	(	(	PUNCT
ajst-30179	105	22	30	30	NUM
ajst-30179	105	23	%	%	NOUN
ajst-30179	105	24	)	)	PUNCT
ajst-30179	105	25	to	to	PART
ajst-30179	105	26	enhance	enhance	VERB
ajst-30179	105	27	the	the	DET
ajst-30179	105	28	learning	learning	NOUN
ajst-30179	105	29	ability	ability	NOUN
ajst-30179	105	30	of	of	ADP
ajst-30179	105	31	difficult	difficult	ADJ
ajst-30179	105	32	samples	sample	NOUN
ajst-30179	105	33	,	,	PUNCT
ajst-30179	105	34	optimizing	optimize	VERB
ajst-30179	105	35	pixel	pixel	ADJ
ajst-30179	105	36	-	-	PUNCT
ajst-30179	105	37	level	level	NOUN
ajst-30179	105	38	accuracy	accuracy	NOUN
ajst-30179	105	39	and	and	CCONJ
ajst-30179	105	40	shape	shape	NOUN
ajst-30179	105	41	similarity	similarity	NOUN
ajst-30179	105	42	.	.	PUNCT
ajst-30179	106	1	in	in	ADP
ajst-30179	106	2	conclusion	conclusion	NOUN
ajst-30179	106	3	,	,	PUNCT
ajst-30179	106	4	through	through	ADP
ajst-30179	106	5	the	the	DET
ajst-30179	106	6	proposal	proposal	NOUN
ajst-30179	106	7	of	of	ADP
ajst-30179	106	8	a	a	DET
ajst-30179	106	9	novel	novel	ADJ
ajst-30179	106	10	upsampling	upsampling	NOUN
ajst-30179	106	11	module	module	NOUN
ajst-30179	106	12	,	,	PUNCT
ajst-30179	106	13	optimization	optimization	NOUN
ajst-30179	106	14	of	of	ADP
ajst-30179	106	15	pidnet	pidnet	PROPN
ajst-30179	106	16	’s	’s	PART
ajst-30179	106	17	network	network	NOUN
ajst-30179	106	18	structure	structure	NOUN
ajst-30179	106	19	,	,	PUNCT
ajst-30179	106	20	design	design	NOUN
ajst-30179	106	21	of	of	ADP
ajst-30179	106	22	a	a	DET
ajst-30179	106	23	combined	combine	VERB
ajst-30179	106	24	loss	loss	NOUN
ajst-30179	106	25	function	function	NOUN
ajst-30179	106	26	,	,	PUNCT
ajst-30179	106	27	and	and	CCONJ
ajst-30179	106	28	thorough	thorough	ADJ
ajst-30179	106	29	experimental	experimental	ADJ
ajst-30179	106	30	validation	validation	NOUN
ajst-30179	106	31	,	,	PUNCT
ajst-30179	106	32	a	a	DET
ajst-30179	106	33	high	high	ADJ
ajst-30179	106	34	-	-	PUNCT
ajst-30179	106	35	precision	precision	NOUN
ajst-30179	106	36	,	,	PUNCT
ajst-30179	106	37	low	low	ADJ
ajst-30179	106	38	computational	computational	ADJ
ajst-30179	106	39	cost	cost	NOUN
ajst-30179	106	40	,	,	PUNCT
ajst-30179	106	41	and	and	CCONJ
ajst-30179	106	42	strong	strong	ADJ
ajst-30179	106	43	generalization	generalization	NOUN
ajst-30179	106	44	ability	ability	NOUN
ajst-30179	106	45	semantic	semantic	ADJ
ajst-30179	106	46	segmentation	segmentation	NOUN
ajst-30179	106	47	model	model	NOUN
ajst-30179	106	48	is	be	AUX
ajst-30179	106	49	achieved	achieve	VERB
ajst-30179	106	50	.	.	PUNCT
ajst-30179	107	1	these	these	DET
ajst-30179	107	2	improvements	improvement	NOUN
ajst-30179	107	3	not	not	PART
ajst-30179	107	4	only	only	ADV
ajst-30179	107	5	enhance	enhance	VERB
ajst-30179	107	6	the	the	DET
ajst-30179	107	7	overall	overall	ADJ
ajst-30179	107	8	performance	performance	NOUN
ajst-30179	107	9	of	of	ADP
ajst-30179	107	10	pidnet	pidnet	NOUN
ajst-30179	107	11	but	but	CCONJ
ajst-30179	107	12	also	also	ADV
ajst-30179	107	13	provide	provide	VERB
ajst-30179	107	14	a	a	DET
ajst-30179	107	15	reference	reference	NOUN
ajst-30179	107	16	for	for	ADP
ajst-30179	107	17	future	future	ADJ
ajst-30179	107	18	lightweight	lightweight	ADJ
ajst-30179	107	19	and	and	CCONJ
ajst-30179	107	20	efficient	efficient	ADJ
ajst-30179	107	21	segmentation	segmentation	NOUN
ajst-30179	107	22	networks	network	NOUN
ajst-30179	107	23	.	.	PUNCT
ajst-30179	108	1	references	reference	NOUN
ajst-30179	108	2	[	[	X
ajst-30179	108	3	1	1	NUM
ajst-30179	108	4	]	]	X
ajst-30179	108	5	li	li	PROPN
ajst-30179	108	6	z	z	PROPN
ajst-30179	108	7	,	,	PUNCT
ajst-30179	108	8	liu	liu	PROPN
ajst-30179	108	9	f	f	PROPN
ajst-30179	108	10	,	,	PUNCT
ajst-30179	108	11	yang	yang	PROPN
ajst-30179	108	12	w	w	PROPN
ajst-30179	108	13	,	,	PUNCT
ajst-30179	108	14	et	et	PROPN
ajst-30179	108	15	al	al	PROPN
ajst-30179	108	16	.	.	PUNCT
ajst-30179	109	1	a	a	DET
ajst-30179	109	2	survey	survey	NOUN
ajst-30179	109	3	of	of	ADP
ajst-30179	109	4	convolutional	convolutional	ADJ
ajst-30179	109	5	neural	neural	ADJ
ajst-30179	109	6	networks	network	NOUN
ajst-30179	109	7	:	:	PUNCT
ajst-30179	109	8	analysis	analysis	NOUN
ajst-30179	109	9	,	,	PUNCT
ajst-30179	109	10	applications	application	NOUN
ajst-30179	109	11	,	,	PUNCT
ajst-30179	109	12	and	and	CCONJ
ajst-30179	109	13	prospects[j	prospects[j	PROPN
ajst-30179	109	14	]	]	PUNCT
ajst-30179	109	15	.	.	PUNCT
ajst-30179	110	1	ieee	ieee	NOUN
ajst-30179	110	2	transactions	transaction	NOUN
ajst-30179	110	3	on	on	ADP
ajst-30179	110	4	neural	neural	ADJ
ajst-30179	110	5	networks	network	NOUN
ajst-30179	110	6	and	and	CCONJ
ajst-30179	110	7	learning	learning	NOUN
ajst-30179	110	8	systems	system	NOUN
ajst-30179	110	9	,	,	PUNCT
ajst-30179	110	10	2021	2021	NUM
ajst-30179	110	11	,	,	PUNCT
ajst-30179	110	12	33(12	33(12	NUM
ajst-30179	110	13	):	):	PUNCT
ajst-30179	110	14	6999	6999	NUM
ajst-30179	110	15	-	-	SYM
ajst-30179	110	16	7019	7019	NUM
ajst-30179	110	17	.	.	PUNCT
ajst-30179	111	1	[	[	X
ajst-30179	111	2	2	2	NUM
ajst-30179	111	3	]	]	PUNCT
ajst-30179	111	4	badrinarayanan	badrinarayanan	NOUN
ajst-30179	111	5	v	v	PROPN
ajst-30179	111	6	,	,	PUNCT
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ajst-30179	111	8	a	a	PROPN
ajst-30179	111	9	,	,	PUNCT
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ajst-30179	111	11	r.	r.	PROPN
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ajst-30179	111	13	:	:	PUNCT
ajst-30179	111	14	a	a	DET
ajst-30179	111	15	deep	deep	ADJ
ajst-30179	111	16	convolutional	convolutional	ADJ
ajst-30179	111	17	encoder	encoder	NOUN
ajst-30179	111	18	-	-	PUNCT
ajst-30179	111	19	decoder	decoder	NOUN
ajst-30179	111	20	architecture	architecture	NOUN
ajst-30179	111	21	for	for	ADP
ajst-30179	111	22	image	image	NOUN
ajst-30179	111	23	segmentation[j	segmentation[j	PROPN
ajst-30179	111	24	]	]	PUNCT
ajst-30179	111	25	.	.	PUNCT
ajst-30179	112	1	ieee	ieee	NOUN
ajst-30179	112	2	transactions	transaction	NOUN
ajst-30179	112	3	on	on	ADP
ajst-30179	112	4	pattern	pattern	NOUN
ajst-30179	112	5	analysis	analysis	NOUN
ajst-30179	112	6	and	and	CCONJ
ajst-30179	112	7	machine	machine	NOUN
ajst-30179	112	8	intelligence	intelligence	NOUN
ajst-30179	112	9	,	,	PUNCT
ajst-30179	112	10	2017	2017	NUM
ajst-30179	112	11	,	,	PUNCT
ajst-30179	112	12	39(12	39(12	NUM
ajst-30179	112	13	):	):	PUNCT
ajst-30179	112	14	2481	2481	NUM
ajst-30179	112	15	-	-	SYM
ajst-30179	112	16	2495	2495	NUM
ajst-30179	112	17	.	.	PUNCT
ajst-30179	113	1	[	[	X
ajst-30179	113	2	3	3	NUM
ajst-30179	113	3	]	]	X
ajst-30179	113	4	guo	guo	PROPN
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ajst-30179	113	9	,	,	PUNCT
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ajst-30179	113	12	,	,	PUNCT
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ajst-30179	113	15	.	.	PUNCT
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ajst-30179	114	2	review	review	NOUN
ajst-30179	114	3	of	of	ADP
ajst-30179	114	4	semantic	semantic	ADJ
ajst-30179	114	5	segmentation	segmentation	NOUN
ajst-30179	114	6	using	use	VERB
ajst-30179	114	7	deep	deep	ADJ
ajst-30179	114	8	neural	neural	ADJ
ajst-30179	114	9	networks[j	networks[j	PROPN
ajst-30179	114	10	]	]	X
ajst-30179	114	11	.	.	PUNCT
ajst-30179	115	1	international	international	ADJ
ajst-30179	115	2	journal	journal	PROPN
ajst-30179	115	3	of	of	ADP
ajst-30179	115	4	multimedia	multimedia	PROPN
ajst-30179	115	5	information	information	NOUN
ajst-30179	115	6	retrieval	retrieval	NOUN
ajst-30179	115	7	,	,	PUNCT
ajst-30179	115	8	2018	2018	NUM
ajst-30179	115	9	,	,	PUNCT
ajst-30179	115	10	7	7	NUM
ajst-30179	115	11	:	:	SYM
ajst-30179	115	12	87	87	NUM
ajst-30179	115	13	-	-	SYM
ajst-30179	115	14	93	93	NUM
ajst-30179	115	15	.	.	PUNCT
ajst-30179	116	1	[	[	X
ajst-30179	116	2	4	4	NUM
ajst-30179	116	3	]	]	X
ajst-30179	116	4	long	long	PROPN
ajst-30179	116	5	j	j	PROPN
ajst-30179	116	6	,	,	PUNCT
ajst-30179	116	7	shelhamer	shelhamer	NOUN
ajst-30179	116	8	e	e	NOUN
ajst-30179	116	9	,	,	PUNCT
ajst-30179	116	10	darrell	darrell	PROPN
ajst-30179	116	11	t.	t.	PROPN
ajst-30179	116	12	fully	fully	ADV
ajst-30179	116	13	convolutional	convolutional	ADJ
ajst-30179	116	14	networks	network	NOUN
ajst-30179	116	15	for	for	ADP
ajst-30179	116	16	semantic	semantic	ADJ
ajst-30179	116	17	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-30179	116	18	of	of	ADP
ajst-30179	116	19	the	the	DET
ajst-30179	116	20	ieee	ieee	NOUN
ajst-30179	116	21	conference	conference	NOUN
ajst-30179	116	22	on	on	ADP
ajst-30179	116	23	computer	computer	NOUN
ajst-30179	116	24	vision	vision	NOUN
ajst-30179	116	25	and	and	CCONJ
ajst-30179	116	26	pattern	pattern	NOUN
ajst-30179	116	27	recognition	recognition	NOUN
ajst-30179	116	28	.	.	PUNCT
ajst-30179	117	1	2015	2015	NUM
ajst-30179	117	2	:	:	PUNCT
ajst-30179	117	3	3431	3431	NUM
ajst-30179	117	4	-	-	SYM
ajst-30179	117	5	3440	3440	NUM
ajst-30179	117	6	.	.	PUNCT
ajst-30179	118	1	[	[	X
ajst-30179	118	2	5	5	NUM
ajst-30179	118	3	]	]	PUNCT
ajst-30179	118	4	krizhevsky	krizhevsky	NOUN
ajst-30179	118	5	a	a	PROPN
ajst-30179	118	6	,	,	PUNCT
ajst-30179	118	7	sutskever	sutskever	VERB
ajst-30179	118	8	i	i	PRON
ajst-30179	118	9	,	,	PUNCT
ajst-30179	118	10	hinton	hinton	PROPN
ajst-30179	118	11	g	g	PROPN
ajst-30179	118	12	e.	e.	PROPN
ajst-30179	118	13	imagenet	imagenet	PROPN
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ajst-30179	118	15	with	with	ADP
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ajst-30179	118	17	convolutional	convolutional	ADJ
ajst-30179	118	18	neural	neural	ADJ
ajst-30179	118	19	networks[j	networks[j	NOUN
ajst-30179	118	20	]	]	X
ajst-30179	118	21	.	.	PUNCT
ajst-30179	119	1	advances	advance	NOUN
ajst-30179	119	2	in	in	ADP
ajst-30179	119	3	neural	neural	ADJ
ajst-30179	119	4	information	information	NOUN
ajst-30179	119	5	processing	processing	NOUN
ajst-30179	119	6	systems	system	NOUN
ajst-30179	119	7	,	,	PUNCT
ajst-30179	119	8	2012	2012	NUM
ajst-30179	119	9	,	,	PUNCT
ajst-30179	119	10	25	25	NUM
ajst-30179	119	11	.	.	PUNCT
ajst-30179	120	1	[	[	X
ajst-30179	120	2	6	6	NUM
ajst-30179	120	3	]	]	SYM
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ajst-30179	120	5	k	k	NOUN
ajst-30179	120	6	,	,	PUNCT
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ajst-30179	120	8	a.	a.	NOUN
ajst-30179	120	9	very	very	ADV
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ajst-30179	120	11	convolutional	convolutional	ADJ
ajst-30179	120	12	networks	network	NOUN
ajst-30179	120	13	for	for	ADP
ajst-30179	120	14	large	large	ADJ
ajst-30179	120	15	-	-	PUNCT
ajst-30179	120	16	scale	scale	NOUN
ajst-30179	120	17	image	image	NOUN
ajst-30179	120	18	recognition[j	recognition[j	NOUN
ajst-30179	120	19	]	]	PUNCT
ajst-30179	120	20	.	.	PUNCT
ajst-30179	121	1	arxiv	arxiv	PROPN
ajst-30179	121	2	preprint	preprint	PROPN
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ajst-30179	121	4	,	,	PUNCT
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ajst-30179	121	6	.	.	PUNCT
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ajst-30179	122	2	7	7	X
ajst-30179	122	3	]	]	X
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ajst-30179	122	5	c	c	PROPN
ajst-30179	122	6	,	,	PUNCT
ajst-30179	122	7	liu	liu	PROPN
ajst-30179	122	8	w	w	PROPN
ajst-30179	122	9	,	,	PUNCT
ajst-30179	122	10	jia	jia	PROPN
ajst-30179	122	11	y	y	PROPN
ajst-30179	122	12	,	,	PUNCT
ajst-30179	122	13	et	et	PROPN
ajst-30179	122	14	al	al	PROPN
ajst-30179	122	15	.	.	PUNCT
ajst-30179	123	1	going	go	VERB
ajst-30179	123	2	deeper	deeply	ADV
ajst-30179	123	3	with	with	ADP
ajst-30179	123	4	convolutions[c]//proceedings	convolutions[c]//proceeding	NOUN
ajst-30179	123	5	of	of	ADP
ajst-30179	123	6	the	the	DET
ajst-30179	123	7	ieee	ieee	NOUN
ajst-30179	123	8	conference	conference	NOUN
ajst-30179	123	9	on	on	ADP
ajst-30179	123	10	computer	computer	NOUN
ajst-30179	123	11	vision	vision	NOUN
ajst-30179	123	12	and	and	CCONJ
ajst-30179	123	13	pattern	pattern	NOUN
ajst-30179	123	14	recognition	recognition	NOUN
ajst-30179	123	15	.	.	PUNCT
ajst-30179	124	1	2015	2015	NUM
ajst-30179	124	2	:	:	PUNCT
ajst-30179	124	3	1	1	NUM
ajst-30179	124	4	-	-	SYM
ajst-30179	124	5	9	9	NUM
ajst-30179	124	6	.	.	PUNCT
ajst-30179	125	1	[	[	X
ajst-30179	125	2	8	8	NUM
ajst-30179	125	3	]	]	PUNCT
ajst-30179	125	4	he	he	PRON
ajst-30179	125	5	k	k	PROPN
ajst-30179	125	6	,	,	PUNCT
ajst-30179	125	7	zhang	zhang	PROPN
ajst-30179	125	8	x	x	PROPN
ajst-30179	125	9	,	,	PUNCT
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ajst-30179	125	11	s	s	PROPN
ajst-30179	125	12	,	,	PUNCT
ajst-30179	125	13	et	et	PROPN
ajst-30179	125	14	al	al	PROPN
ajst-30179	125	15	.	.	PUNCT
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ajst-30179	126	2	residual	residual	ADJ
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ajst-30179	126	5	image	image	NOUN
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ajst-30179	126	7	of	of	ADP
ajst-30179	126	8	the	the	DET
ajst-30179	126	9	ieee	ieee	NOUN
ajst-30179	126	10	conference	conference	NOUN
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ajst-30179	126	12	computer	computer	NOUN
ajst-30179	126	13	vision	vision	NOUN
ajst-30179	126	14	and	and	CCONJ
ajst-30179	126	15	pattern	pattern	NOUN
ajst-30179	126	16	recognition	recognition	NOUN
ajst-30179	126	17	.	.	PUNCT
ajst-30179	127	1	2016	2016	NUM
ajst-30179	127	2	:	:	PUNCT
ajst-30179	128	1	770	770	NUM
ajst-30179	128	2	-	-	SYM
ajst-30179	128	3	778	778	NUM
ajst-30179	128	4	.	.	PUNCT
ajst-30179	129	1	[	[	X
ajst-30179	129	2	9	9	NUM
ajst-30179	129	3	]	]	X
ajst-30179	129	4	redmon	redmon	PROPN
ajst-30179	129	5	j	j	PROPN
ajst-30179	129	6	,	,	PUNCT
ajst-30179	129	7	divvala	divvala	PROPN
ajst-30179	129	8	s	s	PROPN
ajst-30179	129	9	,	,	PUNCT
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ajst-30179	129	12	,	,	PUNCT
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ajst-30179	129	14	al	al	PROPN
ajst-30179	129	15	.	.	PUNCT
ajst-30179	130	1	you	you	PRON
ajst-30179	130	2	only	only	ADV
ajst-30179	130	3	look	look	VERB
ajst-30179	130	4	once	once	ADV
ajst-30179	130	5	:	:	PUNCT
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ajst-30179	130	7	,	,	PUNCT
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ajst-30179	130	9	-	-	PUNCT
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ajst-30179	130	14	the	the	DET
ajst-30179	130	15	65	65	NUM
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ajst-30179	130	17	conference	conference	NOUN
ajst-30179	130	18	on	on	ADP
ajst-30179	130	19	computer	computer	NOUN
ajst-30179	130	20	vision	vision	NOUN
ajst-30179	130	21	and	and	CCONJ
ajst-30179	130	22	pattern	pattern	NOUN
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ajst-30179	130	24	.	.	PUNCT
ajst-30179	131	1	2016	2016	NUM
ajst-30179	131	2	:	:	PUNCT
ajst-30179	131	3	779	779	NUM
ajst-30179	131	4	-	-	SYM
ajst-30179	131	5	788	788	NUM
ajst-30179	131	6	.	.	PUNCT
ajst-30179	132	1	[	[	X
ajst-30179	132	2	10	10	NUM
ajst-30179	132	3	]	]	X
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ajst-30179	132	5	v	v	PROPN
ajst-30179	132	6	,	,	PUNCT
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ajst-30179	132	13	:	:	PUNCT
ajst-30179	132	14	a	a	DET
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ajst-30179	132	18	-	-	PUNCT
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ajst-30179	132	20	architecture	architecture	NOUN
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ajst-30179	132	24	]	]	PUNCT
ajst-30179	132	25	.	.	PUNCT
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ajst-30179	133	4	pattern	pattern	NOUN
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ajst-30179	133	8	intelligence	intelligence	NOUN
ajst-30179	133	9	,	,	PUNCT
ajst-30179	133	10	2017	2017	NUM
ajst-30179	133	11	,	,	PUNCT
ajst-30179	133	12	39(12	39(12	NUM
ajst-30179	133	13	):	):	PUNCT
ajst-30179	133	14	2481	2481	NUM
ajst-30179	133	15	-	-	SYM
ajst-30179	133	16	2495	2495	NUM
ajst-30179	133	17	.	.	PUNCT
ajst-30179	134	1	[	[	X
ajst-30179	134	2	11	11	NUM
ajst-30179	134	3	]	]	PUNCT
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ajst-30179	134	5	j	j	PROPN
ajst-30179	134	6	,	,	PUNCT
ajst-30179	134	7	xiong	xiong	PROPN
ajst-30179	134	8	z	z	PROPN
ajst-30179	134	9	,	,	PUNCT
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ajst-30179	134	14	:	:	PUNCT
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ajst-30179	134	17	-	-	PUNCT
ajst-30179	134	18	time	time	NOUN
ajst-30179	134	19	semantic	semantic	ADJ
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ajst-30179	134	33	computer	computer	NOUN
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ajst-30179	135	1	2023	2023	NUM
ajst-30179	135	2	:	:	PUNCT
ajst-30179	135	3	19529	19529	NUM
ajst-30179	135	4	-	-	SYM
ajst-30179	135	5	19539	19539	NUM
ajst-30179	135	6	.	.	PUNCT
ajst-30179	136	1	[	[	X
ajst-30179	136	2	12	12	NUM
ajst-30179	136	3	]	]	X
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ajst-30179	136	26	of	of	ADP
ajst-30179	136	27	the	the	DET
ajst-30179	136	28	ieee	ieee	NOUN
ajst-30179	136	29	/	/	SYM
ajst-30179	136	30	cvf	cvf	NOUN
ajst-30179	136	31	conference	conference	NOUN
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ajst-30179	136	33	computer	computer	NOUN
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ajst-30179	136	38	.	.	PUNCT
ajst-30179	137	1	2024	2024	NUM
ajst-30179	137	2	:	:	PUNCT
ajst-30179	137	3	1176911779	1176911779	NUM
ajst-30179	137	4	.	.	PUNCT