id	sid	tid	token	lemma	pos
fcis-13142	1	1	frontiers	frontier	NOUN
fcis-13142	1	2	in	in	ADP
fcis-13142	1	3	computing	computing	NOUN
fcis-13142	1	4	and	and	CCONJ
fcis-13142	1	5	intelligent	intelligent	ADJ
fcis-13142	1	6	systems	system	NOUN
fcis-13142	1	7	issn	issn	VERB
fcis-13142	1	8	:	:	PUNCT
fcis-13142	1	9	2832	2832	NUM
fcis-13142	1	10	-	-	SYM
fcis-13142	1	11	6024	6024	NUM
fcis-13142	1	12	|	|	NOUN
fcis-13142	1	13	vol	vol	NOUN
fcis-13142	1	14	.	.	PROPN
fcis-13142	2	1	5	5	NUM
fcis-13142	2	2	,	,	PUNCT
fcis-13142	2	3	no	no	INTJ
fcis-13142	2	4	.	.	NOUN
fcis-13142	2	5	2	2	NUM
fcis-13142	2	6	,	,	PUNCT
fcis-13142	2	7	2023	2023	NUM
fcis-13142	2	8	131	131	NUM
fcis-13142	2	9	research	research	NOUN
fcis-13142	2	10	on	on	ADP
fcis-13142	2	11	image	image	NOUN
fcis-13142	2	12	super‐resolution	super‐resolution	NOUN
fcis-13142	2	13	using	use	VERB
fcis-13142	2	14	attention	attention	NOUN
fcis-13142	2	15	mechanisms	mechanism	NOUN
fcis-13142	2	16	based	base	VERB
fcis-13142	2	17	on	on	ADP
fcis-13142	2	18	super‐resolution	super‐resolution	NOUN
fcis-13142	2	19	generative	generative	VERB
fcis-13142	2	20	adversarial	adversarial	ADJ
fcis-13142	2	21	network	network	NOUN
fcis-13142	2	22	zhouli	zhouli	PROPN
fcis-13142	2	23	wu	wu	PROPN
fcis-13142	2	24	*	*	PUNCT
fcis-13142	2	25	software	software	PROPN
fcis-13142	2	26	engineering	engineering	NOUN
fcis-13142	2	27	,	,	PUNCT
fcis-13142	2	28	zhejiang	zhejiang	PROPN
fcis-13142	2	29	university	university	PROPN
fcis-13142	2	30	of	of	ADP
fcis-13142	2	31	technology	technology	PROPN
fcis-13142	2	32	,	,	PUNCT
fcis-13142	2	33	hangzhou	hangzhou	PROPN
fcis-13142	2	34	,	,	PUNCT
fcis-13142	2	35	zhejiang	zhejiang	PROPN
fcis-13142	2	36	,	,	PUNCT
fcis-13142	2	37	310023	310023	NUM
fcis-13142	2	38	,	,	PUNCT
fcis-13142	2	39	china	china	PROPN
fcis-13142	2	40	*	*	PUNCT
fcis-13142	2	41	corresponding	correspond	VERB
fcis-13142	2	42	author	author	NOUN
fcis-13142	2	43	email	email	NOUN
fcis-13142	2	44	:	:	PUNCT
fcis-13142	3	1	luckywzli@163.com	luckywzli@163.com	PROPN
fcis-13142	3	2	abstract	abstract	ADJ
fcis-13142	3	3	:	:	PUNCT
fcis-13142	3	4	with	with	ADP
fcis-13142	3	5	the	the	DET
fcis-13142	3	6	continuous	continuous	ADJ
fcis-13142	3	7	advancement	advancement	NOUN
fcis-13142	3	8	of	of	ADP
fcis-13142	3	9	technology	technology	NOUN
fcis-13142	3	10	,	,	PUNCT
fcis-13142	3	11	super	super	ADJ
fcis-13142	3	12	-	-	ADJ
fcis-13142	3	13	resolution	resolution	ADJ
fcis-13142	3	14	generative	generative	ADJ
fcis-13142	3	15	adversarial	adversarial	ADJ
fcis-13142	3	16	networks	network	NOUN
fcis-13142	3	17	(	(	PUNCT
fcis-13142	3	18	srgan	srgan	NOUN
fcis-13142	3	19	)	)	PUNCT
fcis-13142	3	20	have	have	AUX
fcis-13142	3	21	played	play	VERB
fcis-13142	3	22	a	a	DET
fcis-13142	3	23	significant	significant	ADJ
fcis-13142	3	24	role	role	NOUN
fcis-13142	3	25	in	in	ADP
fcis-13142	3	26	the	the	DET
fcis-13142	3	27	field	field	NOUN
fcis-13142	3	28	of	of	ADP
fcis-13142	3	29	image	image	NOUN
fcis-13142	3	30	super	super	NOUN
fcis-13142	3	31	-	-	NOUN
fcis-13142	3	32	resolution	resolution	NOUN
fcis-13142	3	33	,	,	PUNCT
fcis-13142	3	34	significantly	significantly	ADV
fcis-13142	3	35	enhancing	enhance	VERB
fcis-13142	3	36	the	the	DET
fcis-13142	3	37	resolution	resolution	NOUN
fcis-13142	3	38	of	of	ADP
fcis-13142	3	39	images	image	NOUN
fcis-13142	3	40	.	.	PUNCT
fcis-13142	4	1	however	however	ADV
fcis-13142	4	2	,	,	PUNCT
fcis-13142	4	3	while	while	SCONJ
fcis-13142	4	4	srgan	srgan	VERB
fcis-13142	4	5	excels	excel	NOUN
fcis-13142	4	6	in	in	ADP
fcis-13142	4	7	generating	generate	VERB
fcis-13142	4	8	details	detail	NOUN
fcis-13142	4	9	,	,	PUNCT
fcis-13142	4	10	sometimes	sometimes	ADV
fcis-13142	4	11	the	the	DET
fcis-13142	4	12	restored	restore	VERB
fcis-13142	4	13	details	detail	NOUN
fcis-13142	4	14	do	do	AUX
fcis-13142	4	15	not	not	PART
fcis-13142	4	16	always	always	ADV
fcis-13142	4	17	meet	meet	VERB
fcis-13142	4	18	people	people	NOUN
fcis-13142	4	19	's	's	PART
fcis-13142	4	20	expectations	expectation	NOUN
fcis-13142	4	21	.	.	PUNCT
fcis-13142	5	1	to	to	PART
fcis-13142	5	2	further	far	ADV
fcis-13142	5	3	enhance	enhance	VERB
fcis-13142	5	4	the	the	DET
fcis-13142	5	5	quality	quality	NOUN
fcis-13142	5	6	of	of	ADP
fcis-13142	5	7	images	image	NOUN
fcis-13142	5	8	and	and	CCONJ
fcis-13142	5	9	make	make	VERB
fcis-13142	5	10	image	image	NOUN
fcis-13142	5	11	details	detail	NOUN
fcis-13142	5	12	clearer	clear	ADJ
fcis-13142	5	13	,	,	PUNCT
fcis-13142	5	14	this	this	DET
fcis-13142	5	15	paper	paper	NOUN
fcis-13142	5	16	introduces	introduce	VERB
fcis-13142	5	17	improvements	improvement	NOUN
fcis-13142	5	18	to	to	ADP
fcis-13142	5	19	the	the	DET
fcis-13142	5	20	architecture	architecture	NOUN
fcis-13142	5	21	and	and	CCONJ
fcis-13142	5	22	loss	loss	NOUN
fcis-13142	5	23	functions	function	NOUN
fcis-13142	5	24	of	of	ADP
fcis-13142	5	25	the	the	DET
fcis-13142	5	26	srgan	srgan	NOUN
fcis-13142	5	27	network	network	NOUN
fcis-13142	5	28	.	.	PUNCT
fcis-13142	6	1	specifically	specifically	ADV
fcis-13142	6	2	,	,	PUNCT
fcis-13142	6	3	this	this	DET
fcis-13142	6	4	research	research	NOUN
fcis-13142	6	5	draws	draw	VERB
fcis-13142	6	6	inspiration	inspiration	NOUN
fcis-13142	6	7	from	from	ADP
fcis-13142	6	8	the	the	DET
fcis-13142	6	9	architecture	architecture	NOUN
fcis-13142	6	10	of	of	ADP
fcis-13142	6	11	esrgan	esrgan	NOUN
fcis-13142	6	12	,	,	PUNCT
fcis-13142	6	13	removing	remove	VERB
fcis-13142	6	14	the	the	DET
fcis-13142	6	15	original	original	ADJ
fcis-13142	6	16	batch	batch	NOUN
fcis-13142	6	17	normalization	normalization	NOUN
fcis-13142	6	18	layers	layer	NOUN
fcis-13142	6	19	and	and	CCONJ
fcis-13142	6	20	introducing	introduce	VERB
fcis-13142	6	21	a	a	DET
fcis-13142	6	22	newly	newly	ADV
fcis-13142	6	23	designed	design	VERB
fcis-13142	6	24	residual	residual	ADJ
fcis-13142	6	25	block	block	NOUN
fcis-13142	6	26	.	.	PUNCT
fcis-13142	7	1	leveraging	leverage	VERB
fcis-13142	7	2	insights	insight	NOUN
fcis-13142	7	3	from	from	ADP
fcis-13142	7	4	attention	attention	NOUN
fcis-13142	7	5	mechanisms	mechanism	NOUN
fcis-13142	7	6	,	,	PUNCT
fcis-13142	7	7	we	we	PRON
fcis-13142	7	8	incorporate	incorporate	VERB
fcis-13142	7	9	three	three	NUM
fcis-13142	7	10	layers	layer	NOUN
fcis-13142	7	11	of	of	ADP
fcis-13142	7	12	convolutional	convolutional	ADJ
fcis-13142	7	13	operations	operation	NOUN
fcis-13142	7	14	and	and	CCONJ
fcis-13142	7	15	introduce	introduce	VERB
fcis-13142	7	16	attention	attention	NOUN
fcis-13142	7	17	mechanisms	mechanism	NOUN
fcis-13142	7	18	into	into	ADP
fcis-13142	7	19	these	these	DET
fcis-13142	7	20	new	new	ADJ
fcis-13142	7	21	residual	residual	ADJ
fcis-13142	7	22	blocks	block	NOUN
fcis-13142	7	23	.	.	PUNCT
fcis-13142	8	1	furthermore	furthermore	ADV
fcis-13142	8	2	,	,	PUNCT
fcis-13142	8	3	to	to	PART
fcis-13142	8	4	simplify	simplify	VERB
fcis-13142	8	5	the	the	DET
fcis-13142	8	6	computational	computational	ADJ
fcis-13142	8	7	complexity	complexity	NOUN
fcis-13142	8	8	of	of	ADP
fcis-13142	8	9	the	the	DET
fcis-13142	8	10	model	model	NOUN
fcis-13142	8	11	,	,	PUNCT
fcis-13142	8	12	this	this	DET
fcis-13142	8	13	paper	paper	NOUN
fcis-13142	8	14	simplifies	simplify	VERB
fcis-13142	8	15	the	the	DET
fcis-13142	8	16	original	original	ADJ
fcis-13142	8	17	loss	loss	NOUN
fcis-13142	8	18	functions	function	NOUN
fcis-13142	8	19	,	,	PUNCT
fcis-13142	8	20	consolidating	consolidate	VERB
fcis-13142	8	21	the	the	DET
fcis-13142	8	22	previous	previous	ADJ
fcis-13142	8	23	four	four	NUM
fcis-13142	8	24	losses	loss	NOUN
fcis-13142	8	25	into	into	ADP
fcis-13142	8	26	two	two	NUM
fcis-13142	8	27	.	.	PUNCT
fcis-13142	9	1	these	these	DET
fcis-13142	9	2	enhancements	enhancement	NOUN
fcis-13142	9	3	result	result	VERB
fcis-13142	9	4	in	in	ADP
fcis-13142	9	5	a	a	DET
fcis-13142	9	6	significantly	significantly	ADV
fcis-13142	9	7	improved	improve	VERB
fcis-13142	9	8	model	model	NOUN
fcis-13142	9	9	in	in	ADP
fcis-13142	9	10	capturing	capture	VERB
fcis-13142	9	11	visual	visual	ADJ
fcis-13142	9	12	elements	element	NOUN
fcis-13142	9	13	,	,	PUNCT
fcis-13142	9	14	making	make	VERB
fcis-13142	9	15	key	key	ADJ
fcis-13142	9	16	objects	object	NOUN
fcis-13142	9	17	in	in	ADP
fcis-13142	9	18	the	the	DET
fcis-13142	9	19	images	image	NOUN
fcis-13142	9	20	more	more	ADV
fcis-13142	9	21	prominent	prominent	ADJ
fcis-13142	9	22	compared	compare	VERB
fcis-13142	9	23	to	to	PART
fcis-13142	9	24	srgan	srgan	VERB
fcis-13142	9	25	.	.	PUNCT
fcis-13142	10	1	detailed	detailed	ADJ
fcis-13142	10	2	experimental	experimental	ADJ
fcis-13142	10	3	results	result	NOUN
fcis-13142	10	4	demonstrate	demonstrate	VERB
fcis-13142	10	5	that	that	SCONJ
fcis-13142	10	6	this	this	DET
fcis-13142	10	7	model	model	NOUN
fcis-13142	10	8	,	,	PUNCT
fcis-13142	10	9	while	while	SCONJ
fcis-13142	10	10	maintaining	maintain	VERB
fcis-13142	10	11	the	the	DET
fcis-13142	10	12	clarity	clarity	NOUN
fcis-13142	10	13	of	of	ADP
fcis-13142	10	14	details	detail	NOUN
fcis-13142	10	15	,	,	PUNCT
fcis-13142	10	16	provides	provide	VERB
fcis-13142	10	17	higher	high	ADJ
fcis-13142	10	18	visual	visual	ADJ
fcis-13142	10	19	quality	quality	NOUN
fcis-13142	10	20	.	.	PUNCT
fcis-13142	11	1	these	these	DET
fcis-13142	11	2	achievements	achievement	NOUN
fcis-13142	11	3	provide	provide	VERB
fcis-13142	11	4	valuable	valuable	ADJ
fcis-13142	11	5	insights	insight	NOUN
fcis-13142	11	6	and	and	CCONJ
fcis-13142	11	7	inspiration	inspiration	NOUN
fcis-13142	11	8	for	for	ADP
fcis-13142	11	9	further	further	ADJ
fcis-13142	11	10	research	research	NOUN
fcis-13142	11	11	and	and	CCONJ
fcis-13142	11	12	applications	application	NOUN
fcis-13142	11	13	in	in	ADP
fcis-13142	11	14	the	the	DET
fcis-13142	11	15	field	field	NOUN
fcis-13142	11	16	of	of	ADP
fcis-13142	11	17	image	image	NOUN
fcis-13142	11	18	super	super	NOUN
fcis-13142	11	19	-	-	NOUN
fcis-13142	11	20	resolution	resolution	NOUN
fcis-13142	11	21	.	.	PUNCT
fcis-13142	12	1	keywords	keyword	NOUN
fcis-13142	12	2	:	:	PUNCT
fcis-13142	12	3	srgan	srgan	VERB
fcis-13142	12	4	;	;	PUNCT
fcis-13142	12	5	attention	attention	NOUN
fcis-13142	12	6	mechanism	mechanism	NOUN
fcis-13142	12	7	;	;	PUNCT
fcis-13142	12	8	residual	residual	ADJ
fcis-13142	12	9	blocks	block	NOUN
fcis-13142	12	10	.	.	PUNCT
fcis-13142	13	1	1	1	X
fcis-13142	13	2	.	.	X
fcis-13142	13	3	introduction	introduction	NOUN
fcis-13142	13	4	super	super	ADJ
fcis-13142	13	5	-	-	ADJ
fcis-13142	13	6	resolution	resolution	ADJ
fcis-13142	13	7	reconstruction	reconstruction	NOUN
fcis-13142	13	8	technology	technology	NOUN
fcis-13142	13	9	(	(	PUNCT
fcis-13142	13	10	superresolution	superresolution	NOUN
fcis-13142	13	11	,	,	PUNCT
fcis-13142	13	12	sr	sr	PROPN
fcis-13142	13	13	)	)	PUNCT
fcis-13142	13	14	refers	refer	VERB
fcis-13142	13	15	to	to	ADP
fcis-13142	13	16	the	the	DET
fcis-13142	13	17	technique	technique	NOUN
fcis-13142	13	18	of	of	ADP
fcis-13142	13	19	increasing	increase	VERB
fcis-13142	13	20	the	the	DET
fcis-13142	13	21	resolution	resolution	NOUN
fcis-13142	13	22	of	of	ADP
fcis-13142	13	23	an	an	DET
fcis-13142	13	24	original	original	ADJ
fcis-13142	13	25	image	image	NOUN
fcis-13142	13	26	through	through	ADP
fcis-13142	13	27	hardware	hardware	NOUN
fcis-13142	13	28	upgrades	upgrade	NOUN
fcis-13142	13	29	or	or	CCONJ
fcis-13142	13	30	improvements	improvement	NOUN
fcis-13142	13	31	in	in	ADP
fcis-13142	13	32	software	software	NOUN
fcis-13142	13	33	.	.	PUNCT
fcis-13142	14	1	it	it	PRON
fcis-13142	14	2	involves	involve	VERB
fcis-13142	14	3	processing	process	VERB
fcis-13142	14	4	one	one	NUM
fcis-13142	14	5	or	or	CCONJ
fcis-13142	14	6	multiple	multiple	ADJ
fcis-13142	14	7	blurred	blurred	ADJ
fcis-13142	14	8	but	but	CCONJ
fcis-13142	14	9	similar	similar	ADJ
fcis-13142	14	10	low	low	ADJ
fcis-13142	14	11	-	-	PUNCT
fcis-13142	14	12	resolution	resolution	NOUN
fcis-13142	14	13	images	image	NOUN
fcis-13142	14	14	(	(	PUNCT
fcis-13142	14	15	lr	lr	NOUN
fcis-13142	14	16	)	)	PUNCT
fcis-13142	14	17	using	use	VERB
fcis-13142	14	18	corresponding	correspond	VERB
fcis-13142	14	19	algorithms	algorithm	NOUN
fcis-13142	14	20	to	to	PART
fcis-13142	14	21	reconstruct	reconstruct	VERB
fcis-13142	14	22	one	one	NUM
fcis-13142	14	23	or	or	CCONJ
fcis-13142	14	24	multiple	multiple	ADJ
fcis-13142	14	25	clear	clear	ADJ
fcis-13142	14	26	high	high	ADJ
fcis-13142	14	27	-	-	PUNCT
fcis-13142	14	28	resolution	resolution	NOUN
fcis-13142	14	29	images	image	NOUN
fcis-13142	14	30	(	(	PUNCT
fcis-13142	14	31	hr	hr	NOUN
fcis-13142	14	32	)	)	PUNCT
fcis-13142	15	1	[	[	X
fcis-13142	15	2	1	1	NUM
fcis-13142	15	3	]	]	PUNCT
fcis-13142	15	4	.	.	PUNCT
fcis-13142	16	1	single	single	ADJ
fcis-13142	16	2	image	image	NOUN
fcis-13142	16	3	superresolution	superresolution	NOUN
fcis-13142	16	4	(	(	PUNCT
fcis-13142	16	5	sisr	sisr	NOUN
fcis-13142	16	6	)	)	PUNCT
fcis-13142	16	7	is	be	AUX
fcis-13142	16	8	an	an	DET
fcis-13142	16	9	important	important	ADJ
fcis-13142	16	10	application	application	NOUN
fcis-13142	16	11	area	area	NOUN
fcis-13142	16	12	for	for	ADP
fcis-13142	16	13	this	this	DET
fcis-13142	16	14	technology	technology	NOUN
fcis-13142	16	15	,	,	PUNCT
fcis-13142	16	16	and	and	CCONJ
fcis-13142	16	17	it	it	PRON
fcis-13142	16	18	has	have	AUX
fcis-13142	16	19	garnered	garner	VERB
fcis-13142	16	20	significant	significant	ADJ
fcis-13142	16	21	attention	attention	NOUN
fcis-13142	16	22	from	from	ADP
fcis-13142	16	23	the	the	DET
fcis-13142	16	24	research	research	NOUN
fcis-13142	16	25	community	community	NOUN
fcis-13142	16	26	and	and	CCONJ
fcis-13142	16	27	artificial	artificial	ADJ
fcis-13142	16	28	intelligence	intelligence	NOUN
fcis-13142	16	29	companies	company	NOUN
fcis-13142	16	30	,	,	PUNCT
fcis-13142	16	31	especially	especially	ADV
fcis-13142	16	32	in	in	ADP
fcis-13142	16	33	the	the	DET
fcis-13142	16	34	past	past	ADJ
fcis-13142	16	35	decade	decade	NOUN
fcis-13142	16	36	with	with	ADP
fcis-13142	16	37	advancements	advancement	NOUN
fcis-13142	16	38	in	in	ADP
fcis-13142	16	39	machine	machine	NOUN
fcis-13142	16	40	learning	learning	NOUN
fcis-13142	16	41	and	and	CCONJ
fcis-13142	16	42	deep	deep	ADJ
fcis-13142	16	43	learning	learning	NOUN
fcis-13142	16	44	.	.	PUNCT
fcis-13142	17	1	srgan	srgan	PROPN
fcis-13142	17	2	is	be	AUX
fcis-13142	17	3	a	a	DET
fcis-13142	17	4	deep	deep	ADJ
fcis-13142	17	5	learning	learning	NOUN
fcis-13142	17	6	model	model	NOUN
fcis-13142	17	7	that	that	PRON
fcis-13142	17	8	aims	aim	VERB
fcis-13142	17	9	to	to	PART
fcis-13142	17	10	convert	convert	VERB
fcis-13142	17	11	lowresolution	lowresolution	NOUN
fcis-13142	17	12	images	image	NOUN
fcis-13142	17	13	into	into	ADP
fcis-13142	17	14	high	high	ADJ
fcis-13142	17	15	-	-	PUNCT
fcis-13142	17	16	resolution	resolution	NOUN
fcis-13142	17	17	ones	one	NOUN
fcis-13142	17	18	through	through	ADP
fcis-13142	17	19	adversarial	adversarial	ADJ
fcis-13142	17	20	training	training	NOUN
fcis-13142	17	21	.	.	PUNCT
fcis-13142	18	1	it	it	PRON
fcis-13142	18	2	consists	consist	VERB
fcis-13142	18	3	of	of	ADP
fcis-13142	18	4	two	two	NUM
fcis-13142	18	5	components	component	NOUN
fcis-13142	18	6	:	:	PUNCT
fcis-13142	18	7	a	a	DET
fcis-13142	18	8	generator	generator	NOUN
fcis-13142	18	9	that	that	PRON
fcis-13142	18	10	maps	map	VERB
fcis-13142	18	11	low	low	ADJ
fcis-13142	18	12	-	-	PUNCT
fcis-13142	18	13	resolution	resolution	NOUN
fcis-13142	18	14	images	image	NOUN
fcis-13142	18	15	to	to	ADP
fcis-13142	18	16	high	high	ADJ
fcis-13142	18	17	-	-	PUNCT
fcis-13142	18	18	resolution	resolution	NOUN
fcis-13142	18	19	ones	one	NOUN
fcis-13142	18	20	and	and	CCONJ
fcis-13142	18	21	a	a	DET
fcis-13142	18	22	discriminator	discriminator	NOUN
fcis-13142	18	23	that	that	PRON
fcis-13142	18	24	evaluates	evaluate	VERB
fcis-13142	18	25	the	the	DET
fcis-13142	18	26	authenticity	authenticity	NOUN
fcis-13142	18	27	of	of	ADP
fcis-13142	18	28	generated	generate	VERB
fcis-13142	18	29	images	image	NOUN
fcis-13142	18	30	,	,	PUNCT
fcis-13142	18	31	both	both	PRON
fcis-13142	18	32	engaged	engage	VERB
fcis-13142	18	33	in	in	ADP
fcis-13142	18	34	a	a	DET
fcis-13142	18	35	competitive	competitive	ADJ
fcis-13142	18	36	training	training	NOUN
fcis-13142	18	37	process	process	NOUN
fcis-13142	18	38	.	.	PUNCT
fcis-13142	19	1	however	however	ADV
fcis-13142	19	2	,	,	PUNCT
fcis-13142	19	3	srgan	srgan	PROPN
fcis-13142	19	4	has	have	VERB
fcis-13142	19	5	drawbacks	drawback	NOUN
fcis-13142	19	6	,	,	PUNCT
fcis-13142	19	7	including	include	VERB
fcis-13142	19	8	complex	complex	ADJ
fcis-13142	19	9	training	training	NOUN
fcis-13142	19	10	,	,	PUNCT
fcis-13142	19	11	a	a	DET
fcis-13142	19	12	need	need	NOUN
fcis-13142	19	13	for	for	ADP
fcis-13142	19	14	extensive	extensive	ADJ
fcis-13142	19	15	data	datum	NOUN
fcis-13142	19	16	,	,	PUNCT
fcis-13142	19	17	susceptibility	susceptibility	NOUN
fcis-13142	19	18	to	to	ADP
fcis-13142	19	19	artifacts	artifact	NOUN
fcis-13142	19	20	,	,	PUNCT
fcis-13142	19	21	and	and	CCONJ
fcis-13142	19	22	image	image	NOUN
fcis-13142	19	23	degradation	degradation	NOUN
fcis-13142	19	24	,	,	PUNCT
fcis-13142	19	25	which	which	PRON
fcis-13142	19	26	require	require	VERB
fcis-13142	19	27	further	further	ADJ
fcis-13142	19	28	refinement	refinement	NOUN
fcis-13142	19	29	.	.	PUNCT
fcis-13142	20	1	enhanced	enhance	VERB
fcis-13142	20	2	super	super	ADJ
fcis-13142	20	3	-	-	ADJ
fcis-13142	20	4	resolution	resolution	ADJ
fcis-13142	20	5	generative	generative	ADJ
fcis-13142	20	6	adversarial	adversarial	ADJ
fcis-13142	20	7	network	network	NOUN
fcis-13142	20	8	(	(	PUNCT
fcis-13142	20	9	esrgan	esrgan	PROPN
fcis-13142	20	10	)	)	PUNCT
fcis-13142	20	11	,	,	PUNCT
fcis-13142	20	12	is	be	AUX
fcis-13142	20	13	a	a	DET
fcis-13142	20	14	deep	deep	ADJ
fcis-13142	20	15	learning	learning	NOUN
fcis-13142	20	16	model	model	NOUN
fcis-13142	20	17	aimed	aim	VERB
fcis-13142	20	18	at	at	ADP
fcis-13142	20	19	enhancing	enhance	VERB
fcis-13142	20	20	the	the	DET
fcis-13142	20	21	quality	quality	NOUN
fcis-13142	20	22	of	of	ADP
fcis-13142	20	23	high	high	ADJ
fcis-13142	20	24	-	-	PUNCT
fcis-13142	20	25	resolution	resolution	NOUN
fcis-13142	20	26	image	image	NOUN
fcis-13142	20	27	generation	generation	NOUN
fcis-13142	20	28	from	from	ADP
fcis-13142	20	29	low	low	ADJ
fcis-13142	20	30	-	-	PUNCT
fcis-13142	20	31	resolution	resolution	NOUN
fcis-13142	20	32	inputs	input	NOUN
fcis-13142	20	33	.	.	PUNCT
fcis-13142	21	1	it	it	PRON
fcis-13142	21	2	utilizes	utilize	VERB
fcis-13142	21	3	a	a	DET
fcis-13142	21	4	generator	generator	NOUN
fcis-13142	21	5	and	and	CCONJ
fcis-13142	21	6	discriminator	discriminator	NOUN
fcis-13142	21	7	network	network	NOUN
fcis-13142	21	8	in	in	ADP
fcis-13142	21	9	adversarial	adversarial	ADJ
fcis-13142	21	10	training	training	NOUN
fcis-13142	21	11	,	,	PUNCT
fcis-13142	21	12	striving	strive	VERB
fcis-13142	21	13	to	to	PART
fcis-13142	21	14	produce	produce	VERB
fcis-13142	21	15	high	high	ADJ
fcis-13142	21	16	-	-	PUNCT
fcis-13142	21	17	quality	quality	NOUN
fcis-13142	21	18	,	,	PUNCT
fcis-13142	21	19	realistic	realistic	ADJ
fcis-13142	21	20	high	high	ADJ
fcis-13142	21	21	-	-	PUNCT
fcis-13142	21	22	resolution	resolution	NOUN
fcis-13142	21	23	images	image	NOUN
fcis-13142	21	24	.	.	PUNCT
fcis-13142	22	1	however	however	ADV
fcis-13142	22	2	,	,	PUNCT
fcis-13142	22	3	like	like	INTJ
fcis-13142	22	4	srgan	srgan	NOUN
fcis-13142	22	5	,	,	PUNCT
fcis-13142	22	6	it	it	PRON
fcis-13142	22	7	encounters	encounter	VERB
fcis-13142	22	8	challenges	challenge	NOUN
fcis-13142	22	9	such	such	ADJ
fcis-13142	22	10	as	as	ADP
fcis-13142	22	11	complex	complex	ADJ
fcis-13142	22	12	training	training	NOUN
fcis-13142	22	13	,	,	PUNCT
fcis-13142	22	14	data	datum	NOUN
fcis-13142	22	15	requirements	requirement	NOUN
fcis-13142	22	16	,	,	PUNCT
fcis-13142	22	17	and	and	CCONJ
fcis-13142	22	18	potential	potential	ADJ
fcis-13142	22	19	image	image	NOUN
fcis-13142	22	20	artifacts	artifact	NOUN
fcis-13142	22	21	that	that	PRON
fcis-13142	22	22	require	require	VERB
fcis-13142	22	23	ongoing	ongoing	ADJ
fcis-13142	22	24	improvement	improvement	NOUN
fcis-13142	22	25	.	.	PUNCT
fcis-13142	23	1	the	the	DET
fcis-13142	23	2	attention	attention	NOUN
fcis-13142	23	3	mechanism	mechanism	NOUN
fcis-13142	23	4	dynamically	dynamically	ADV
fcis-13142	23	5	computes	compute	VERB
fcis-13142	23	6	the	the	DET
fcis-13142	23	7	importance	importance	NOUN
fcis-13142	23	8	of	of	ADP
fcis-13142	23	9	different	different	ADJ
fcis-13142	23	10	regions	region	NOUN
fcis-13142	23	11	within	within	ADP
fcis-13142	23	12	an	an	DET
fcis-13142	23	13	image	image	NOUN
fcis-13142	23	14	,	,	PUNCT
fcis-13142	23	15	enabling	enable	VERB
fcis-13142	23	16	deep	deep	ADJ
fcis-13142	23	17	learning	learning	NOUN
fcis-13142	23	18	models	model	NOUN
fcis-13142	23	19	to	to	PART
fcis-13142	23	20	focus	focus	VERB
fcis-13142	23	21	more	more	ADV
fcis-13142	23	22	on	on	ADP
fcis-13142	23	23	crucial	crucial	ADJ
fcis-13142	23	24	areas	area	NOUN
fcis-13142	23	25	to	to	PART
fcis-13142	23	26	enhance	enhance	VERB
fcis-13142	23	27	task	task	NOUN
fcis-13142	23	28	performance	performance	NOUN
fcis-13142	23	29	.	.	PUNCT
fcis-13142	24	1	its	its	PRON
fcis-13142	24	2	typical	typical	ADJ
fcis-13142	24	3	process	process	NOUN
fcis-13142	24	4	involves	involve	VERB
fcis-13142	24	5	extracting	extract	VERB
fcis-13142	24	6	features	feature	NOUN
fcis-13142	24	7	from	from	ADP
fcis-13142	24	8	the	the	DET
fcis-13142	24	9	input	input	NOUN
fcis-13142	24	10	image	image	NOUN
fcis-13142	24	11	,	,	PUNCT
fcis-13142	24	12	then	then	ADV
fcis-13142	24	13	calculating	calculate	VERB
fcis-13142	24	14	attention	attention	NOUN
fcis-13142	24	15	weights	weight	NOUN
fcis-13142	24	16	for	for	ADP
fcis-13142	24	17	each	each	DET
fcis-13142	24	18	feature	feature	NOUN
fcis-13142	24	19	location	location	NOUN
fcis-13142	24	20	,	,	PUNCT
fcis-13142	24	21	and	and	CCONJ
fcis-13142	24	22	ultimately	ultimately	ADV
fcis-13142	24	23	synthesizing	synthesize	VERB
fcis-13142	24	24	weighted	weighted	ADJ
fcis-13142	24	25	features	feature	NOUN
fcis-13142	24	26	to	to	PART
fcis-13142	24	27	generate	generate	VERB
fcis-13142	24	28	the	the	DET
fcis-13142	24	29	output	output	NOUN
fcis-13142	24	30	.	.	PUNCT
fcis-13142	25	1	however	however	ADV
fcis-13142	25	2	,	,	PUNCT
fcis-13142	25	3	the	the	DET
fcis-13142	25	4	limited	limited	ADJ
fcis-13142	25	5	interpretability	interpretability	NOUN
fcis-13142	25	6	of	of	ADP
fcis-13142	25	7	why	why	SCONJ
fcis-13142	25	8	the	the	DET
fcis-13142	25	9	model	model	NOUN
fcis-13142	25	10	selects	select	VERB
fcis-13142	25	11	certain	certain	ADJ
fcis-13142	25	12	regions	region	NOUN
fcis-13142	25	13	is	be	AUX
fcis-13142	25	14	a	a	DET
fcis-13142	25	15	challenge	challenge	NOUN
fcis-13142	25	16	.	.	PUNCT
fcis-13142	26	1	considering	consider	VERB
fcis-13142	26	2	the	the	DET
fcis-13142	26	3	aforementioned	aforementioned	ADJ
fcis-13142	26	4	issues	issue	NOUN
fcis-13142	26	5	,	,	PUNCT
fcis-13142	26	6	the	the	DET
fcis-13142	26	7	new	new	ADJ
fcis-13142	26	8	model	model	NOUN
fcis-13142	26	9	builds	build	VERB
fcis-13142	26	10	upon	upon	SCONJ
fcis-13142	26	11	srgan	srgan	NOUN
fcis-13142	26	12	with	with	ADP
fcis-13142	26	13	several	several	ADJ
fcis-13142	26	14	improvements	improvement	NOUN
fcis-13142	26	15	.	.	PUNCT
fcis-13142	27	1	in	in	ADP
fcis-13142	27	2	terms	term	NOUN
fcis-13142	27	3	of	of	ADP
fcis-13142	27	4	loss	loss	NOUN
fcis-13142	27	5	functions	function	NOUN
fcis-13142	27	6	,	,	PUNCT
fcis-13142	27	7	complexity	complexity	NOUN
fcis-13142	27	8	is	be	AUX
fcis-13142	27	9	reduced	reduce	VERB
fcis-13142	27	10	by	by	ADP
fcis-13142	27	11	simplifying	simplify	VERB
fcis-13142	27	12	the	the	DET
fcis-13142	27	13	original	original	ADJ
fcis-13142	27	14	four	four	NUM
fcis-13142	27	15	loss	loss	NOUN
fcis-13142	27	16	functions	function	NOUN
fcis-13142	27	17	into	into	ADP
fcis-13142	27	18	two	two	NUM
fcis-13142	27	19	.	.	PUNCT
fcis-13142	28	1	regarding	regard	VERB
fcis-13142	28	2	network	network	NOUN
fcis-13142	28	3	architecture	architecture	NOUN
fcis-13142	28	4	,	,	PUNCT
fcis-13142	28	5	this	this	DET
fcis-13142	28	6	study	study	NOUN
fcis-13142	28	7	draws	draw	VERB
fcis-13142	28	8	inspiration	inspiration	NOUN
fcis-13142	28	9	from	from	ADP
fcis-13142	28	10	esrgan	esrgan	NOUN
fcis-13142	28	11	,	,	PUNCT
fcis-13142	28	12	eliminating	eliminate	VERB
fcis-13142	28	13	the	the	DET
fcis-13142	28	14	use	use	NOUN
fcis-13142	28	15	of	of	ADP
fcis-13142	28	16	batch	batch	NOUN
fcis-13142	28	17	normalization	normalization	NOUN
fcis-13142	28	18	layers	layer	NOUN
fcis-13142	28	19	and	and	CCONJ
fcis-13142	28	20	introducing	introduce	VERB
fcis-13142	28	21	a	a	DET
fcis-13142	28	22	completely	completely	ADV
fcis-13142	28	23	redesigned	redesign	VERB
fcis-13142	28	24	residual	residual	ADJ
fcis-13142	28	25	block	block	NOUN
fcis-13142	28	26	to	to	PART
fcis-13142	28	27	replace	replace	VERB
fcis-13142	28	28	the	the	DET
fcis-13142	28	29	previous	previous	ADJ
fcis-13142	28	30	one	one	NUM
fcis-13142	28	31	.	.	PUNCT
fcis-13142	29	1	additionally	additionally	ADV
fcis-13142	29	2	,	,	PUNCT
fcis-13142	29	3	the	the	DET
fcis-13142	29	4	new	new	ADJ
fcis-13142	29	5	residual	residual	ADJ
fcis-13142	29	6	block	block	NOUN
fcis-13142	29	7	incorporates	incorporate	VERB
fcis-13142	29	8	an	an	DET
fcis-13142	29	9	attention	attention	NOUN
fcis-13142	29	10	mechanism	mechanism	NOUN
fcis-13142	29	11	[	[	X
fcis-13142	29	12	2	2	NUM
fcis-13142	29	13	]	]	PUNCT
fcis-13142	29	14	,	,	PUNCT
fcis-13142	29	15	which	which	PRON
fcis-13142	29	16	is	be	AUX
fcis-13142	29	17	integrated	integrate	VERB
fcis-13142	29	18	on	on	ADP
fcis-13142	29	19	top	top	NOUN
fcis-13142	29	20	of	of	ADP
fcis-13142	29	21	the	the	DET
fcis-13142	29	22	three	three	NUM
fcis-13142	29	23	convolutional	convolutional	ADJ
fcis-13142	29	24	layers	layer	NOUN
fcis-13142	29	25	.	.	PUNCT
fcis-13142	30	1	through	through	ADP
fcis-13142	30	2	these	these	DET
fcis-13142	30	3	improvements	improvement	NOUN
fcis-13142	30	4	,	,	PUNCT
fcis-13142	30	5	our	our	PRON
fcis-13142	30	6	enhanced	enhanced	ADJ
fcis-13142	30	7	model	model	NOUN
fcis-13142	30	8	has	have	AUX
fcis-13142	30	9	shown	show	VERB
fcis-13142	30	10	significant	significant	ADJ
fcis-13142	30	11	improvements	improvement	NOUN
fcis-13142	30	12	in	in	ADP
fcis-13142	30	13	capturing	capture	VERB
fcis-13142	30	14	visual	visual	ADJ
fcis-13142	30	15	elements	element	NOUN
fcis-13142	30	16	compared	compare	VERB
fcis-13142	30	17	to	to	PART
fcis-13142	30	18	srgan	srgan	VERB
fcis-13142	30	19	,	,	PUNCT
fcis-13142	30	20	making	make	VERB
fcis-13142	30	21	key	key	ADJ
fcis-13142	30	22	objects	object	NOUN
fcis-13142	30	23	in	in	ADP
fcis-13142	30	24	images	image	NOUN
fcis-13142	30	25	stand	stand	VERB
fcis-13142	30	26	out	out	ADP
fcis-13142	30	27	.	.	PUNCT
fcis-13142	31	1	experimental	experimental	ADJ
fcis-13142	31	2	results	result	NOUN
fcis-13142	31	3	indicate	indicate	VERB
fcis-13142	31	4	that	that	SCONJ
fcis-13142	31	5	our	our	PRON
fcis-13142	31	6	model	model	NOUN
fcis-13142	31	7	provides	provide	VERB
fcis-13142	31	8	higher	high	ADJ
fcis-13142	31	9	visual	visual	ADJ
fcis-13142	31	10	quality	quality	NOUN
fcis-13142	31	11	while	while	SCONJ
fcis-13142	31	12	maintaining	maintain	VERB
fcis-13142	31	13	detail	detail	NOUN
fcis-13142	31	14	clarity	clarity	NOUN
fcis-13142	31	15	in	in	ADP
fcis-13142	31	16	image	image	NOUN
fcis-13142	31	17	superresolution	superresolution	NOUN
fcis-13142	31	18	tasks	task	NOUN
fcis-13142	31	19	.	.	PUNCT
fcis-13142	32	1	these	these	DET
fcis-13142	32	2	achievements	achievement	NOUN
fcis-13142	32	3	serve	serve	VERB
fcis-13142	32	4	as	as	ADP
fcis-13142	32	5	important	important	ADJ
fcis-13142	32	6	references	reference	NOUN
fcis-13142	32	7	and	and	CCONJ
fcis-13142	32	8	inspirations	inspiration	NOUN
fcis-13142	32	9	for	for	ADP
fcis-13142	32	10	further	further	ADJ
fcis-13142	32	11	research	research	NOUN
fcis-13142	32	12	and	and	CCONJ
fcis-13142	32	13	applications	application	NOUN
fcis-13142	32	14	in	in	ADP
fcis-13142	32	15	the	the	DET
fcis-13142	32	16	field	field	NOUN
fcis-13142	32	17	of	of	ADP
fcis-13142	32	18	image	image	NOUN
fcis-13142	32	19	super	super	NOUN
fcis-13142	32	20	-	-	NOUN
fcis-13142	32	21	resolution	resolution	NOUN
fcis-13142	32	22	.	.	PUNCT
fcis-13142	33	1	2	2	X
fcis-13142	33	2	.	.	X
fcis-13142	33	3	related	relate	VERB
fcis-13142	33	4	work	work	NOUN
fcis-13142	33	5	in	in	ADP
fcis-13142	33	6	2014	2014	NUM
fcis-13142	33	7	,	,	PUNCT
fcis-13142	33	8	chao	chao	PROPN
fcis-13142	33	9	dong	dong	PROPN
fcis-13142	33	10	,	,	PUNCT
fcis-13142	33	11	chen	chen	PROPN
fcis-13142	33	12	change	change	PROPN
fcis-13142	33	13	loy	loy	PROPN
fcis-13142	33	14	,	,	PUNCT
fcis-13142	33	15	and	and	CCONJ
fcis-13142	33	16	xiaoou	xiaoou	PROPN
fcis-13142	33	17	tang	tang	PROPN
fcis-13142	33	18	introduced	introduce	VERB
fcis-13142	33	19	the	the	DET
fcis-13142	33	20	super	super	ADJ
fcis-13142	33	21	-	-	ADJ
fcis-13142	33	22	resolution	resolution	ADJ
fcis-13142	33	23	convolutional	convolutional	ADJ
fcis-13142	33	24	neural	neural	ADJ
fcis-13142	33	25	network	network	NOUN
fcis-13142	33	26	(	(	PUNCT
fcis-13142	33	27	srcnn	srcnn	NOUN
fcis-13142	33	28	)	)	PUNCT
fcis-13142	33	29	model	model	NOUN
fcis-13142	34	1	[	[	X
fcis-13142	34	2	3	3	NUM
fcis-13142	34	3	]	]	PUNCT
fcis-13142	34	4	,	,	PUNCT
fcis-13142	34	5	which	which	PRON
fcis-13142	34	6	not	not	PART
fcis-13142	34	7	only	only	ADV
fcis-13142	34	8	improved	improve	VERB
fcis-13142	34	9	image	image	NOUN
fcis-13142	34	10	quality	quality	NOUN
fcis-13142	34	11	but	but	CCONJ
fcis-13142	34	12	also	also	ADV
fcis-13142	34	13	inspired	inspire	VERB
fcis-13142	34	14	subsequent	subsequent	ADJ
fcis-13142	34	15	research	research	NOUN
fcis-13142	34	16	.	.	PUNCT
fcis-13142	35	1	however	however	ADV
fcis-13142	35	2	,	,	PUNCT
fcis-13142	35	3	it	it	PRON
fcis-13142	35	4	still	still	ADV
fcis-13142	35	5	had	have	VERB
fcis-13142	35	6	drawbacks	drawback	NOUN
fcis-13142	35	7	such	such	ADJ
fcis-13142	35	8	as	as	ADP
fcis-13142	35	9	fixed	fix	VERB
fcis-13142	35	10	upscaling	upscale	VERB
fcis-13142	35	11	factors	factor	NOUN
fcis-13142	35	12	and	and	CCONJ
fcis-13142	35	13	high	high	ADJ
fcis-13142	35	14	computational	computational	ADJ
fcis-13142	35	15	complexity	complexity	NOUN
fcis-13142	35	16	.	.	PUNCT
fcis-13142	36	1	132	132	NUM
fcis-13142	36	2	figure	figure	NOUN
fcis-13142	36	3	1	1	NUM
fcis-13142	36	4	.	.	PUNCT
fcis-13142	37	1	the	the	DET
fcis-13142	37	2	super	super	ADJ
fcis-13142	37	3	-	-	ADJ
fcis-13142	37	4	resolution	resolution	ADJ
fcis-13142	37	5	results	result	NOUN
fcis-13142	37	6	of	of	ADP
fcis-13142	37	7	×4	×4	NOUN
fcis-13142	37	8	for	for	ADP
fcis-13142	37	9	srgan	srgan	NOUN
fcis-13142	37	10	,	,	PUNCT
fcis-13142	37	11	the	the	DET
fcis-13142	37	12	proposed	propose	VERB
fcis-13142	37	13	model	model	NOUN
fcis-13142	37	14	.	.	PUNCT
fcis-13142	38	1	this	this	DET
fcis-13142	38	2	new	new	ADJ
fcis-13142	38	3	model	model	NOUN
fcis-13142	38	4	outperforms	outperform	NOUN
fcis-13142	38	5	srgan	srgan	VERB
fcis-13142	38	6	in	in	ADP
fcis-13142	38	7	sharpness	sharpness	NOUN
fcis-13142	38	8	and	and	CCONJ
fcis-13142	38	9	details	detail	NOUN
fcis-13142	38	10	in	in	ADP
fcis-13142	38	11	2016	2016	NUM
fcis-13142	38	12	,	,	PUNCT
fcis-13142	38	13	shi	shi	PROPN
fcis-13142	38	14	et	et	PROPN
fcis-13142	38	15	al	al	PROPN
fcis-13142	38	16	.	.	PROPN
fcis-13142	38	17	proposed	propose	VERB
fcis-13142	38	18	the	the	DET
fcis-13142	38	19	efficient	efficient	ADJ
fcis-13142	38	20	sub	sub	ADJ
fcis-13142	38	21	-	-	ADJ
fcis-13142	38	22	pixel	pixel	ADJ
fcis-13142	38	23	cnn	cnn	PROPN
fcis-13142	38	24	(	(	PUNCT
fcis-13142	38	25	espcn	espcn	NOUN
fcis-13142	38	26	)	)	PUNCT
fcis-13142	38	27	model	model	NOUN
fcis-13142	39	1	[	[	X
fcis-13142	39	2	4	4	NUM
fcis-13142	39	3	]	]	PUNCT
fcis-13142	39	4	,	,	PUNCT
fcis-13142	39	5	which	which	PRON
fcis-13142	39	6	is	be	AUX
fcis-13142	39	7	based	base	VERB
fcis-13142	39	8	on	on	ADP
fcis-13142	39	9	pixel	pixel	PROPN
fcis-13142	39	10	rearrangement	rearrangement	NOUN
fcis-13142	39	11	.	.	PUNCT
fcis-13142	40	1	it	it	PRON
fcis-13142	40	2	extracts	extract	VERB
fcis-13142	40	3	feature	feature	NOUN
fcis-13142	40	4	maps	map	NOUN
fcis-13142	40	5	by	by	ADP
fcis-13142	40	6	performing	perform	VERB
fcis-13142	40	7	convolution	convolution	NOUN
fcis-13142	40	8	operations	operation	NOUN
fcis-13142	40	9	on	on	ADP
fcis-13142	40	10	low	low	ADJ
fcis-13142	40	11	-	-	PUNCT
fcis-13142	40	12	resolution	resolution	NOUN
fcis-13142	40	13	images	image	NOUN
fcis-13142	40	14	and	and	CCONJ
fcis-13142	40	15	then	then	ADV
fcis-13142	40	16	feeds	feed	VERB
fcis-13142	40	17	these	these	DET
fcis-13142	40	18	feature	feature	NOUN
fcis-13142	40	19	maps	map	NOUN
fcis-13142	40	20	into	into	ADP
fcis-13142	40	21	sub	sub	ADJ
fcis-13142	40	22	-	-	ADJ
fcis-13142	40	23	pixel	pixel	ADJ
fcis-13142	40	24	convolutional	convolutional	ADJ
fcis-13142	40	25	layers	layer	NOUN
fcis-13142	40	26	to	to	PART
fcis-13142	40	27	generate	generate	VERB
fcis-13142	40	28	highresolution	highresolution	NOUN
fcis-13142	40	29	images	image	NOUN
fcis-13142	40	30	by	by	ADP
fcis-13142	40	31	rearranging	rearrange	VERB
fcis-13142	40	32	and	and	CCONJ
fcis-13142	40	33	combining	combine	VERB
fcis-13142	40	34	channels	channel	NOUN
fcis-13142	40	35	.	.	PUNCT
fcis-13142	41	1	although	although	SCONJ
fcis-13142	41	2	it	it	PRON
fcis-13142	41	3	reduced	reduce	VERB
fcis-13142	41	4	computational	computational	ADJ
fcis-13142	41	5	complexity	complexity	NOUN
fcis-13142	41	6	,	,	PUNCT
fcis-13142	41	7	it	it	PRON
fcis-13142	41	8	did	do	AUX
fcis-13142	41	9	not	not	PART
fcis-13142	41	10	address	address	VERB
fcis-13142	41	11	the	the	DET
fcis-13142	41	12	fixed	fix	VERB
fcis-13142	41	13	super	super	ADJ
fcis-13142	41	14	-	-	ADJ
fcis-13142	41	15	resolution	resolution	ADJ
fcis-13142	41	16	factor	factor	NOUN
fcis-13142	41	17	problem	problem	NOUN
fcis-13142	41	18	.	.	PUNCT
fcis-13142	42	1	therefore	therefore	ADV
fcis-13142	42	2	,	,	PUNCT
fcis-13142	42	3	in	in	ADP
fcis-13142	42	4	2017	2017	NUM
fcis-13142	42	5	,	,	PUNCT
fcis-13142	42	6	srgan	srgan	NOUN
fcis-13142	42	7	(	(	PUNCT
fcis-13142	42	8	super	super	ADJ
fcis-13142	42	9	-	-	ADJ
fcis-13142	42	10	resolution	resolution	ADJ
fcis-13142	42	11	generative	generative	ADJ
fcis-13142	42	12	adversarial	adversarial	ADJ
fcis-13142	42	13	network	network	NOUN
fcis-13142	42	14	)	)	PUNCT
fcis-13142	42	15	was	be	AUX
fcis-13142	42	16	the	the	DET
fcis-13142	42	17	first	first	ADJ
fcis-13142	42	18	attempt	attempt	NOUN
fcis-13142	42	19	by	by	ADP
fcis-13142	42	20	ledig	ledig	NOUN
fcis-13142	42	21	et	et	NOUN
fcis-13142	42	22	al	al	PROPN
fcis-13142	42	23	.	.	PUNCT
fcis-13142	42	24	to	to	PART
fcis-13142	42	25	use	use	VERB
fcis-13142	42	26	generative	generative	ADJ
fcis-13142	42	27	adversarial	adversarial	ADJ
fcis-13142	42	28	networks	network	NOUN
fcis-13142	42	29	(	(	PUNCT
fcis-13142	42	30	gans	gan	NOUN
fcis-13142	42	31	)	)	PUNCT
fcis-13142	42	32	in	in	ADP
fcis-13142	42	33	the	the	DET
fcis-13142	42	34	field	field	NOUN
fcis-13142	42	35	of	of	ADP
fcis-13142	42	36	image	image	NOUN
fcis-13142	42	37	super	super	NOUN
fcis-13142	42	38	-	-	NOUN
fcis-13142	42	39	resolution	resolution	NOUN
fcis-13142	42	40	[	[	X
fcis-13142	42	41	5	5	NUM
fcis-13142	42	42	]	]	PUNCT
fcis-13142	42	43	.	.	PUNCT
fcis-13142	43	1	this	this	DET
fcis-13142	43	2	model	model	NOUN
fcis-13142	43	3	consists	consist	VERB
fcis-13142	43	4	of	of	ADP
fcis-13142	43	5	two	two	NUM
fcis-13142	43	6	opposing	oppose	VERB
fcis-13142	43	7	modules	module	NOUN
fcis-13142	43	8	:	:	PUNCT
fcis-13142	43	9	a	a	DET
fcis-13142	43	10	generator	generator	NOUN
fcis-13142	43	11	that	that	PRON
fcis-13142	43	12	synthesizes	synthesize	VERB
fcis-13142	43	13	highresolution	highresolution	NOUN
fcis-13142	43	14	images	image	NOUN
fcis-13142	43	15	by	by	ADP
fcis-13142	43	16	adding	add	VERB
fcis-13142	43	17	random	random	ADJ
fcis-13142	43	18	noise	noise	NOUN
fcis-13142	43	19	to	to	ADP
fcis-13142	43	20	the	the	DET
fcis-13142	43	21	original	original	ADJ
fcis-13142	43	22	image	image	NOUN
fcis-13142	43	23	,	,	PUNCT
fcis-13142	43	24	and	and	CCONJ
fcis-13142	43	25	a	a	DET
fcis-13142	43	26	discriminator	discriminator	NOUN
fcis-13142	43	27	that	that	PRON
fcis-13142	43	28	distinguishes	distinguish	VERB
fcis-13142	43	29	whether	whether	SCONJ
fcis-13142	43	30	an	an	DET
fcis-13142	43	31	input	input	NOUN
fcis-13142	43	32	image	image	NOUN
fcis-13142	43	33	is	be	AUX
fcis-13142	43	34	generated	generate	VERB
fcis-13142	43	35	by	by	ADP
fcis-13142	43	36	the	the	DET
fcis-13142	43	37	generator	generator	NOUN
fcis-13142	43	38	or	or	CCONJ
fcis-13142	43	39	a	a	DET
fcis-13142	43	40	real	real	ADJ
fcis-13142	43	41	image	image	NOUN
fcis-13142	43	42	.	.	PUNCT
fcis-13142	44	1	however	however	ADV
fcis-13142	44	2	,	,	PUNCT
fcis-13142	44	3	there	there	PRON
fcis-13142	44	4	were	be	VERB
fcis-13142	44	5	still	still	ADV
fcis-13142	44	6	issues	issue	NOUN
fcis-13142	44	7	with	with	ADP
fcis-13142	44	8	unstable	unstable	ADJ
fcis-13142	44	9	training	training	NOUN
fcis-13142	44	10	and	and	CCONJ
fcis-13142	44	11	difficulty	difficulty	NOUN
fcis-13142	44	12	in	in	ADP
fcis-13142	44	13	preserving	preserve	VERB
fcis-13142	44	14	details	detail	NOUN
fcis-13142	44	15	.	.	PUNCT
fcis-13142	45	1	to	to	PART
fcis-13142	45	2	address	address	VERB
fcis-13142	45	3	these	these	DET
fcis-13142	45	4	issues	issue	NOUN
fcis-13142	45	5	,	,	PUNCT
fcis-13142	45	6	in	in	ADP
fcis-13142	45	7	2018	2018	NUM
fcis-13142	45	8	,	,	PUNCT
fcis-13142	45	9	the	the	DET
fcis-13142	45	10	esrgan	esrgan	NOUN
fcis-13142	45	11	(	(	PUNCT
fcis-13142	45	12	enhanced	enhance	VERB
fcis-13142	45	13	super	super	ADJ
fcis-13142	45	14	-	-	ADJ
fcis-13142	45	15	resolution	resolution	ADJ
fcis-13142	45	16	generative	generative	ADJ
fcis-13142	45	17	adversarial	adversarial	ADJ
fcis-13142	45	18	network	network	NOUN
fcis-13142	45	19	)	)	PUNCT
fcis-13142	45	20	model	model	NOUN
fcis-13142	45	21	made	make	VERB
fcis-13142	45	22	an	an	DET
fcis-13142	45	23	important	important	ADJ
fcis-13142	45	24	attempt	attempt	NOUN
fcis-13142	45	25	to	to	PART
fcis-13142	45	26	introduce	introduce	VERB
fcis-13142	45	27	gans	gan	NOUN
fcis-13142	45	28	into	into	ADP
fcis-13142	45	29	the	the	DET
fcis-13142	45	30	image	image	NOUN
fcis-13142	45	31	super	super	ADJ
fcis-13142	45	32	-	-	ADJ
fcis-13142	45	33	resolution	resolution	ADJ
fcis-13142	45	34	field	field	NOUN
fcis-13142	45	35	[	[	X
fcis-13142	45	36	6	6	NUM
fcis-13142	45	37	]	]	PUNCT
fcis-13142	45	38	.	.	PUNCT
fcis-13142	46	1	this	this	DET
fcis-13142	46	2	model	model	NOUN
fcis-13142	46	3	has	have	VERB
fcis-13142	46	4	a	a	DET
fcis-13142	46	5	similar	similar	ADJ
fcis-13142	46	6	overall	overall	ADJ
fcis-13142	46	7	structure	structure	NOUN
fcis-13142	46	8	to	to	PART
fcis-13142	46	9	srgan	srgan	VERB
fcis-13142	46	10	but	but	CCONJ
fcis-13142	46	11	introduces	introduce	VERB
fcis-13142	46	12	a	a	DET
fcis-13142	46	13	new	new	ADJ
fcis-13142	46	14	residual	residual	ADJ
fcis-13142	46	15	-	-	PUNCT
fcis-13142	46	16	inresidual	inresidual	ADJ
fcis-13142	46	17	dense	dense	ADJ
fcis-13142	46	18	block	block	NOUN
fcis-13142	46	19	(	(	PUNCT
fcis-13142	46	20	rrdb	rrdb	NOUN
fcis-13142	46	21	)	)	PUNCT
fcis-13142	46	22	network	network	NOUN
fcis-13142	46	23	unit	unit	NOUN
fcis-13142	46	24	,	,	PUNCT
fcis-13142	46	25	which	which	PRON
fcis-13142	46	26	removes	remove	VERB
fcis-13142	46	27	the	the	DET
fcis-13142	46	28	batch	batch	NOUN
fcis-13142	46	29	normalization	normalization	NOUN
fcis-13142	46	30	(	(	PUNCT
fcis-13142	46	31	bn	bn	NOUN
fcis-13142	46	32	)	)	PUNCT
fcis-13142	46	33	layer	layer	NOUN
fcis-13142	46	34	and	and	CCONJ
fcis-13142	46	35	uses	use	VERB
fcis-13142	46	36	group	group	NOUN
fcis-13142	46	37	normalization	normalization	NOUN
fcis-13142	46	38	to	to	PART
fcis-13142	46	39	replace	replace	VERB
fcis-13142	46	40	bn	bn	PROPN
fcis-13142	46	41	.	.	PUNCT
fcis-13142	47	1	additionally	additionally	ADV
fcis-13142	47	2	,	,	PUNCT
fcis-13142	47	3	it	it	PRON
fcis-13142	47	4	improves	improve	VERB
fcis-13142	47	5	the	the	DET
fcis-13142	47	6	gan	gan	ADJ
fcis-13142	47	7	network	network	NOUN
fcis-13142	47	8	by	by	ADP
fcis-13142	47	9	using	use	VERB
fcis-13142	47	10	relativistic	relativistic	ADJ
fcis-13142	47	11	average	average	ADJ
fcis-13142	47	12	gan	gan	NOUN
fcis-13142	47	13	(	(	PUNCT
fcis-13142	47	14	ragan	ragan	NOUN
fcis-13142	47	15	)	)	PUNCT
fcis-13142	47	16	.	.	PUNCT
fcis-13142	48	1	these	these	DET
fcis-13142	48	2	enhancements	enhancement	NOUN
fcis-13142	48	3	not	not	PART
fcis-13142	48	4	only	only	ADV
fcis-13142	48	5	improved	improved	ADJ
fcis-13142	48	6	performance	performance	NOUN
fcis-13142	48	7	but	but	CCONJ
fcis-13142	48	8	also	also	ADV
fcis-13142	48	9	increased	increase	VERB
fcis-13142	48	10	the	the	DET
fcis-13142	48	11	model	model	NOUN
fcis-13142	48	12	's	's	PART
fcis-13142	48	13	generalization	generalization	NOUN
fcis-13142	48	14	ability	ability	NOUN
fcis-13142	48	15	,	,	PUNCT
fcis-13142	48	16	achieving	achieve	VERB
fcis-13142	48	17	excellent	excellent	ADJ
fcis-13142	48	18	results	result	NOUN
fcis-13142	48	19	in	in	ADP
fcis-13142	48	20	image	image	NOUN
fcis-13142	48	21	detail	detail	NOUN
fcis-13142	48	22	and	and	CCONJ
fcis-13142	48	23	texture	texture	NOUN
fcis-13142	48	24	.	.	PUNCT
fcis-13142	49	1	however	however	ADV
fcis-13142	49	2	,	,	PUNCT
fcis-13142	49	3	there	there	PRON
fcis-13142	49	4	were	be	VERB
fcis-13142	49	5	still	still	ADV
fcis-13142	49	6	challenges	challenge	NOUN
fcis-13142	49	7	related	relate	VERB
fcis-13142	49	8	to	to	ADP
fcis-13142	49	9	capturing	capture	VERB
fcis-13142	49	10	fine	fine	ADJ
fcis-13142	49	11	details	detail	NOUN
fcis-13142	49	12	and	and	CCONJ
fcis-13142	49	13	slightly	slightly	ADV
fcis-13142	49	14	lower	low	ADJ
fcis-13142	49	15	resolution	resolution	NOUN
fcis-13142	49	16	.	.	PUNCT
fcis-13142	50	1	3	3	X
fcis-13142	50	2	.	.	NUM
fcis-13142	50	3	proposed	propose	VERB
fcis-13142	50	4	methods	method	NOUN
fcis-13142	50	5	the	the	DET
fcis-13142	50	6	main	main	ADJ
fcis-13142	50	7	objective	objective	NOUN
fcis-13142	50	8	of	of	ADP
fcis-13142	50	9	our	our	PRON
fcis-13142	50	10	study	study	NOUN
fcis-13142	50	11	is	be	AUX
fcis-13142	50	12	to	to	PART
fcis-13142	50	13	further	far	ADV
fcis-13142	50	14	enhance	enhance	VERB
fcis-13142	50	15	the	the	DET
fcis-13142	50	16	visual	visual	ADJ
fcis-13142	50	17	quality	quality	NOUN
fcis-13142	50	18	of	of	ADP
fcis-13142	50	19	images	image	NOUN
fcis-13142	50	20	based	base	VERB
fcis-13142	50	21	on	on	ADP
fcis-13142	50	22	srgan	srgan	NOUN
fcis-13142	50	23	.	.	PUNCT
fcis-13142	51	1	in	in	ADP
fcis-13142	51	2	this	this	DET
fcis-13142	51	3	section	section	NOUN
fcis-13142	51	4	,	,	PUNCT
fcis-13142	51	5	we	we	PRON
fcis-13142	51	6	first	first	ADV
fcis-13142	51	7	describe	describe	VERB
fcis-13142	51	8	the	the	DET
fcis-13142	51	9	network	network	NOUN
fcis-13142	51	10	architecture	architecture	NOUN
fcis-13142	51	11	of	of	ADP
fcis-13142	51	12	the	the	DET
fcis-13142	51	13	new	new	ADJ
fcis-13142	51	14	model	model	NOUN
fcis-13142	51	15	and	and	CCONJ
fcis-13142	51	16	then	then	ADV
fcis-13142	51	17	introduce	introduce	VERB
fcis-13142	51	18	some	some	DET
fcis-13142	51	19	modifications	modification	NOUN
fcis-13142	51	20	to	to	ADP
fcis-13142	51	21	the	the	DET
fcis-13142	51	22	loss	loss	NOUN
fcis-13142	51	23	functions	function	NOUN
fcis-13142	51	24	.	.	PUNCT
fcis-13142	52	1	figure	figure	NOUN
fcis-13142	52	2	2	2	NUM
fcis-13142	52	3	.	.	PUNCT
fcis-13142	53	1	this	this	DET
fcis-13142	53	2	study	study	NOUN
fcis-13142	53	3	adopts	adopt	VERB
fcis-13142	53	4	the	the	DET
fcis-13142	53	5	basic	basic	ADJ
fcis-13142	53	6	model	model	NOUN
fcis-13142	53	7	of	of	ADP
fcis-13142	53	8	srgan	srgan	NOUN
fcis-13142	53	9	and	and	CCONJ
fcis-13142	53	10	improves	improve	VERB
fcis-13142	53	11	upon	upon	SCONJ
fcis-13142	53	12	it	it	PRON
fcis-13142	53	13	by	by	ADP
fcis-13142	53	14	modifying	modify	VERB
fcis-13142	53	15	the	the	DET
fcis-13142	53	16	residual	residual	ADJ
fcis-13142	53	17	blocks	block	NOUN
fcis-13142	53	18	,	,	PUNCT
fcis-13142	53	19	thereby	thereby	ADV
fcis-13142	53	20	achieving	achieve	VERB
fcis-13142	53	21	enhanced	enhanced	ADJ
fcis-13142	53	22	performance	performance	NOUN
fcis-13142	53	23	3.1	3.1	NUM
fcis-13142	53	24	.	.	PUNCT
fcis-13142	53	25	network	network	NOUN
fcis-13142	53	26	architecture	architecture	NOUN
fcis-13142	53	27	unlike	unlike	ADP
fcis-13142	53	28	srgan	srgan	NOUN
fcis-13142	53	29	,	,	PUNCT
fcis-13142	53	30	the	the	DET
fcis-13142	53	31	novel	novel	ADJ
fcis-13142	53	32	model	model	NOUN
fcis-13142	53	33	proposed	propose	VERB
fcis-13142	53	34	in	in	ADP
fcis-13142	53	35	this	this	DET
fcis-13142	53	36	study	study	NOUN
fcis-13142	53	37	introduces	introduce	VERB
fcis-13142	53	38	several	several	ADJ
fcis-13142	53	39	improvements	improvement	NOUN
fcis-13142	53	40	to	to	ADP
fcis-13142	53	41	the	the	DET
fcis-13142	53	42	residual	residual	ADJ
fcis-13142	53	43	blocks	block	NOUN
fcis-13142	53	44	.	.	PUNCT
fcis-13142	54	1	it	it	PRON
fcis-13142	54	2	not	not	PART
fcis-13142	54	3	only	only	ADV
fcis-13142	54	4	removes	remove	VERB
fcis-13142	54	5	the	the	DET
fcis-13142	54	6	original	original	ADJ
fcis-13142	54	7	bn	bn	NOUN
fcis-13142	54	8	layers	layer	NOUN
fcis-13142	54	9	but	but	CCONJ
fcis-13142	54	10	also	also	ADV
fcis-13142	54	11	transforms	transform	VERB
fcis-13142	54	12	the	the	DET
fcis-13142	54	13	original	original	ADJ
fcis-13142	54	14	two	two	NUM
fcis-13142	54	15	convolutional	convolutional	ADJ
fcis-13142	54	16	layers	layer	NOUN
fcis-13142	54	17	into	into	ADP
fcis-13142	54	18	three	three	NUM
fcis-13142	54	19	.	.	PUNCT
fcis-13142	55	1	additionally	additionally	ADV
fcis-13142	55	2	,	,	PUNCT
fcis-13142	55	3	it	it	PRON
fcis-13142	55	4	incorporates	incorporate	VERB
fcis-13142	55	5	an	an	DET
fcis-13142	55	6	attention	attention	NOUN
fcis-13142	55	7	mechanism	mechanism	NOUN
fcis-13142	55	8	after	after	ADP
fcis-13142	55	9	the	the	DET
fcis-13142	55	10	convolution	convolution	NOUN
fcis-13142	55	11	,	,	PUNCT
fcis-13142	55	12	replacing	replace	VERB
fcis-13142	55	13	the	the	DET
fcis-13142	55	14	old	old	ADJ
fcis-13142	55	15	residual	residual	ADJ
fcis-13142	55	16	blocks	block	NOUN
fcis-13142	55	17	with	with	ADP
fcis-13142	55	18	these	these	DET
fcis-13142	55	19	new	new	ADJ
fcis-13142	55	20	ones	one	NOUN
fcis-13142	55	21	.	.	PUNCT
fcis-13142	56	1	finally	finally	ADV
fcis-13142	56	2	,	,	PUNCT
fcis-13142	56	3	group	group	NOUN
fcis-13142	56	4	normalization	normalization	NOUN
fcis-13142	56	5	was	be	AUX
fcis-13142	56	6	employed	employ	VERB
fcis-13142	56	7	to	to	PART
fcis-13142	56	8	replace	replace	VERB
fcis-13142	56	9	bn	bn	PROPN
fcis-13142	56	10	.	.	PUNCT
fcis-13142	57	1	the	the	DET
fcis-13142	57	2	specific	specific	ADJ
fcis-13142	57	3	details	detail	NOUN
fcis-13142	57	4	are	be	AUX
fcis-13142	57	5	illustrated	illustrate	VERB
fcis-13142	57	6	in	in	ADP
fcis-13142	57	7	figure	figure	NOUN
fcis-13142	57	8	3	3	NUM
fcis-13142	57	9	.	.	PUNCT
fcis-13142	57	10	figure	figure	NOUN
fcis-13142	57	11	3	3	NUM
fcis-13142	57	12	.	.	PUNCT
fcis-13142	58	1	on	on	ADP
fcis-13142	58	2	the	the	DET
fcis-13142	58	3	left	left	NOUN
fcis-13142	58	4	is	be	AUX
fcis-13142	58	5	the	the	DET
fcis-13142	58	6	original	original	ADJ
fcis-13142	58	7	residual	residual	ADJ
fcis-13142	58	8	block	block	NOUN
fcis-13142	58	9	of	of	ADP
fcis-13142	58	10	srgan	srgan	NOUN
fcis-13142	58	11	,	,	PUNCT
fcis-13142	58	12	while	while	SCONJ
fcis-13142	58	13	on	on	ADP
fcis-13142	58	14	the	the	DET
fcis-13142	58	15	right	right	NOUN
fcis-13142	58	16	is	be	AUX
fcis-13142	58	17	the	the	DET
fcis-13142	58	18	improved	improve	VERB
fcis-13142	58	19	residual	residual	ADJ
fcis-13142	58	20	block	block	NOUN
fcis-13142	58	21	.	.	PUNCT
fcis-13142	59	1	while	while	SCONJ
fcis-13142	59	2	batch	batch	VERB
fcis-13142	59	3	normalization	normalization	NOUN
fcis-13142	59	4	(	(	PUNCT
fcis-13142	59	5	bn	bn	NOUN
fcis-13142	59	6	)	)	PUNCT
fcis-13142	59	7	layers	layer	NOUN
fcis-13142	59	8	offer	offer	VERB
fcis-13142	59	9	several	several	ADJ
fcis-13142	59	10	advantages	advantage	NOUN
fcis-13142	59	11	in	in	ADP
fcis-13142	59	12	deep	deep	ADJ
fcis-13142	59	13	learning	learning	NOUN
fcis-13142	59	14	,	,	PUNCT
fcis-13142	59	15	such	such	ADJ
fcis-13142	59	16	as	as	ADP
fcis-13142	59	17	accelerating	accelerate	VERB
fcis-13142	59	18	training	training	NOUN
fcis-13142	59	19	convergence	convergence	NOUN
fcis-13142	59	20	[	[	X
fcis-13142	59	21	7	7	NUM
fcis-13142	59	22	]	]	PUNCT
fcis-13142	59	23	,	,	PUNCT
fcis-13142	59	24	mitigating	mitigate	VERB
fcis-13142	59	25	gradient	gradient	ADJ
fcis-13142	59	26	vanishing	vanish	VERB
fcis-13142	59	27	issues	issue	NOUN
fcis-13142	59	28	,	,	PUNCT
fcis-13142	59	29	and	and	CCONJ
fcis-13142	59	30	enhancing	enhance	VERB
fcis-13142	59	31	model	model	NOUN
fcis-13142	59	32	generalization	generalization	NOUN
fcis-13142	59	33	,	,	PUNCT
fcis-13142	59	34	recent	recent	ADJ
fcis-13142	59	35	research	research	NOUN
fcis-13142	59	36	has	have	AUX
fcis-13142	59	37	uncovered	uncover	VERB
fcis-13142	59	38	some	some	DET
fcis-13142	59	39	limitations	limitation	NOUN
fcis-13142	59	40	in	in	ADP
fcis-13142	59	41	specific	specific	ADJ
fcis-13142	59	42	scenarios	scenario	NOUN
fcis-13142	59	43	.	.	PUNCT
fcis-13142	60	1	firstly	firstly	ADV
fcis-13142	60	2	,	,	PUNCT
fcis-13142	60	3	bn	bn	PRON
fcis-13142	60	4	layers	layer	NOUN
fcis-13142	60	5	require	require	VERB
fcis-13142	60	6	batch	batch	NOUN
fcis-13142	60	7	data	datum	NOUN
fcis-13142	60	8	mean	mean	VERB
fcis-13142	60	9	and	and	CCONJ
fcis-13142	60	10	variance	variance	NOUN
fcis-13142	60	11	for	for	ADP
fcis-13142	60	12	feature	feature	NOUN
fcis-13142	60	13	normalization	normalization	NOUN
fcis-13142	60	14	during	during	ADP
fcis-13142	60	15	both	both	DET
fcis-13142	60	16	training	training	NOUN
fcis-13142	60	17	and	and	CCONJ
fcis-13142	60	18	inference	inference	NOUN
fcis-13142	60	19	.	.	PUNCT
fcis-13142	61	1	this	this	PRON
fcis-13142	61	2	implies	imply	VERB
fcis-13142	61	3	that	that	SCONJ
fcis-13142	61	4	during	during	ADP
fcis-13142	61	5	the	the	DET
fcis-13142	61	6	testing	testing	NOUN
fcis-13142	61	7	phase	phase	NOUN
fcis-13142	61	8	,	,	PUNCT
fcis-13142	61	9	mean	mean	VERB
fcis-13142	61	10	and	and	CCONJ
fcis-13142	61	11	variance	variance	NOUN
fcis-13142	61	12	calculations	calculation	NOUN
fcis-13142	61	13	need	need	VERB
fcis-13142	61	14	to	to	PART
fcis-13142	61	15	be	be	AUX
fcis-13142	61	16	performed	perform	VERB
fcis-13142	61	17	over	over	ADP
fcis-13142	61	18	the	the	DET
fcis-13142	61	19	entire	entire	ADJ
fcis-13142	61	20	training	training	NOUN
fcis-13142	61	21	dataset	dataset	NOUN
fcis-13142	61	22	.	.	PUNCT
fcis-13142	62	1	moreover	moreover	ADV
fcis-13142	62	2	,	,	PUNCT
fcis-13142	62	3	if	if	SCONJ
fcis-13142	62	4	there	there	PRON
fcis-13142	62	5	is	be	VERB
fcis-13142	62	6	a	a	DET
fcis-13142	62	7	significant	significant	ADJ
fcis-13142	62	8	distribution	distribution	NOUN
fcis-13142	62	9	difference	difference	NOUN
fcis-13142	62	10	between	between	ADP
fcis-13142	62	11	the	the	DET
fcis-13142	62	12	test	test	NOUN
fcis-13142	62	13	data	datum	NOUN
fcis-13142	62	14	and	and	CCONJ
fcis-13142	62	15	the	the	DET
fcis-13142	62	16	training	training	NOUN
fcis-13142	62	17	data	datum	NOUN
fcis-13142	62	18	,	,	PUNCT
fcis-13142	62	19	it	it	PRON
fcis-13142	62	20	can	can	AUX
fcis-13142	62	21	lead	lead	VERB
fcis-13142	62	22	to	to	ADP
fcis-13142	62	23	a	a	DET
fcis-13142	62	24	decrease	decrease	NOUN
fcis-13142	62	25	in	in	ADP
fcis-13142	62	26	performance	performance	NOUN
fcis-13142	62	27	,	,	PUNCT
fcis-13142	62	28	a	a	DET
fcis-13142	62	29	problem	problem	NOUN
fcis-13142	62	30	known	know	VERB
fcis-13142	62	31	as	as	ADP
fcis-13142	62	32	the	the	DET
fcis-13142	62	33	"	"	PUNCT
fcis-13142	62	34	batch	batch	NOUN
fcis-13142	62	35	effect	effect	NOUN
fcis-13142	62	36	.	.	PUNCT
fcis-13142	62	37	"	"	PUNCT
fcis-13142	63	1	secondly	secondly	ADV
fcis-13142	63	2	,	,	PUNCT
fcis-13142	63	3	bn	bn	PRON
fcis-13142	63	4	layers	layer	NOUN
fcis-13142	63	5	introduce	introduce	VERB
fcis-13142	63	6	additional	additional	ADJ
fcis-13142	63	7	learnable	learnable	ADJ
fcis-13142	63	8	parameters	parameter	NOUN
fcis-13142	63	9	(	(	PUNCT
fcis-13142	63	10	estimates	estimate	NOUN
fcis-13142	63	11	of	of	ADP
fcis-13142	63	12	mean	mean	NOUN
fcis-13142	63	13	and	and	CCONJ
fcis-13142	63	14	variance	variance	NOUN
fcis-13142	63	15	)	)	PUNCT
fcis-13142	63	16	,	,	PUNCT
fcis-13142	63	17	increasing	increase	VERB
fcis-13142	63	18	the	the	DET
fcis-13142	63	19	model	model	NOUN
fcis-13142	63	20	's	's	PART
fcis-13142	63	21	storage	storage	NOUN
fcis-13142	63	22	and	and	CCONJ
fcis-13142	63	23	computational	computational	ADJ
fcis-13142	63	24	complexity	complexity	NOUN
fcis-13142	63	25	.	.	PUNCT
fcis-13142	64	1	particularly	particularly	ADV
fcis-13142	64	2	in	in	ADP
fcis-13142	64	3	deep	deep	ADJ
fcis-13142	64	4	networks	network	NOUN
fcis-13142	64	5	,	,	PUNCT
fcis-13142	64	6	this	this	PRON
fcis-13142	64	7	can	can	AUX
fcis-13142	64	8	result	result	VERB
fcis-13142	64	9	in	in	ADP
fcis-13142	64	10	artifacts	artifact	NOUN
fcis-13142	64	11	in	in	ADP
fcis-13142	64	12	the	the	DET
fcis-13142	64	13	generated	generate	VERB
fcis-13142	64	14	images	image	NOUN
fcis-13142	64	15	.	.	PUNCT
fcis-13142	65	1	therefore	therefore	ADV
fcis-13142	65	2	,	,	PUNCT
fcis-13142	65	3	this	this	DET
fcis-13142	65	4	study	study	NOUN
fcis-13142	65	5	replaced	replace	VERB
fcis-13142	65	6	bn	bn	NUM
fcis-13142	65	7	layers	layer	NOUN
fcis-13142	65	8	with	with	ADP
fcis-13142	65	9	group	group	NOUN
fcis-13142	65	10	normalization	normalization	NOUN
fcis-13142	65	11	(	(	PUNCT
fcis-13142	65	12	gn	gn	NOUN
fcis-13142	65	13	)	)	PUNCT
fcis-13142	65	14	layers	layer	NOUN
fcis-13142	65	15	while	while	SCONJ
fcis-13142	65	16	building	build	VERB
fcis-13142	65	17	upon	upon	SCONJ
fcis-13142	65	18	the	the	DET
fcis-13142	65	19	srgan	srgan	NOUN
fcis-13142	65	20	133	133	NUM
fcis-13142	65	21	model	model	NOUN
fcis-13142	65	22	[	[	X
fcis-13142	65	23	8	8	NUM
fcis-13142	65	24	]	]	PUNCT
fcis-13142	65	25	.	.	PUNCT
fcis-13142	66	1	gn	gn	PROPN
fcis-13142	66	2	layers	layers	PROPN
fcis-13142	66	3	partition	partition	PROPN
fcis-13142	66	4	features	feature	VERB
fcis-13142	66	5	into	into	ADP
fcis-13142	66	6	several	several	ADJ
fcis-13142	66	7	groups	group	NOUN
fcis-13142	66	8	and	and	CCONJ
fcis-13142	66	9	normalize	normalize	VERB
fcis-13142	66	10	each	each	DET
fcis-13142	66	11	group	group	NOUN
fcis-13142	66	12	's	's	PART
fcis-13142	66	13	features	feature	NOUN
fcis-13142	66	14	,	,	PUNCT
fcis-13142	66	15	instead	instead	ADV
fcis-13142	66	16	of	of	ADP
fcis-13142	66	17	normalizing	normalize	VERB
fcis-13142	66	18	the	the	DET
fcis-13142	66	19	entire	entire	ADJ
fcis-13142	66	20	batch	batch	NOUN
fcis-13142	66	21	.	.	PUNCT
fcis-13142	67	1	this	this	DET
fcis-13142	67	2	approach	approach	NOUN
fcis-13142	67	3	offers	offer	VERB
fcis-13142	67	4	several	several	ADJ
fcis-13142	67	5	advantages	advantage	NOUN
fcis-13142	67	6	:	:	PUNCT
fcis-13142	67	7	it	it	PRON
fcis-13142	67	8	is	be	AUX
fcis-13142	67	9	more	more	ADV
fcis-13142	67	10	robust	robust	ADJ
fcis-13142	67	11	to	to	ADP
fcis-13142	67	12	small	small	ADJ
fcis-13142	67	13	batch	batch	NOUN
fcis-13142	67	14	data	datum	NOUN
fcis-13142	67	15	with	with	ADP
fcis-13142	67	16	unstable	unstable	ADJ
fcis-13142	67	17	distributions	distribution	NOUN
fcis-13142	67	18	and	and	CCONJ
fcis-13142	67	19	is	be	AUX
fcis-13142	67	20	less	less	ADV
fcis-13142	67	21	susceptible	susceptible	ADJ
fcis-13142	67	22	to	to	ADP
fcis-13142	67	23	batch	batch	NOUN
fcis-13142	67	24	effects	effect	NOUN
fcis-13142	67	25	.	.	PUNCT
fcis-13142	68	1	gn	gn	PROPN
fcis-13142	68	2	layers	layer	NOUN
fcis-13142	68	3	do	do	AUX
fcis-13142	68	4	not	not	PART
fcis-13142	68	5	introduce	introduce	VERB
fcis-13142	68	6	additional	additional	ADJ
fcis-13142	68	7	learnable	learnable	ADJ
fcis-13142	68	8	parameters	parameter	NOUN
fcis-13142	68	9	,	,	PUNCT
fcis-13142	68	10	leading	lead	VERB
fcis-13142	68	11	to	to	ADP
fcis-13142	68	12	smaller	small	ADJ
fcis-13142	68	13	computational	computational	ADJ
fcis-13142	68	14	and	and	CCONJ
fcis-13142	68	15	storage	storage	NOUN
fcis-13142	68	16	overheads	overhead	NOUN
fcis-13142	68	17	,	,	PUNCT
fcis-13142	68	18	making	make	VERB
fcis-13142	68	19	them	they	PRON
fcis-13142	68	20	especially	especially	ADV
fcis-13142	68	21	suitable	suitable	ADJ
fcis-13142	68	22	for	for	ADP
fcis-13142	68	23	deep	deep	ADJ
fcis-13142	68	24	networks	network	NOUN
fcis-13142	68	25	.	.	PUNCT
fcis-13142	69	1	in	in	ADP
fcis-13142	69	2	this	this	DET
fcis-13142	69	3	experiment	experiment	NOUN
fcis-13142	69	4	,	,	PUNCT
fcis-13142	69	5	a	a	DET
fcis-13142	69	6	multi	multi	ADJ
fcis-13142	69	7	-	-	ADJ
fcis-13142	69	8	level	level	ADJ
fcis-13142	69	9	residual	residual	ADJ
fcis-13142	69	10	network	network	NOUN
fcis-13142	69	11	was	be	AUX
fcis-13142	69	12	constructed	construct	VERB
fcis-13142	69	13	by	by	ADP
fcis-13142	69	14	applying	apply	VERB
fcis-13142	69	15	normalization	normalization	NOUN
fcis-13142	69	16	through	through	ADP
fcis-13142	69	17	three	three	NUM
fcis-13142	69	18	layers	layer	NOUN
fcis-13142	69	19	of	of	ADP
fcis-13142	69	20	convolution	convolution	NOUN
fcis-13142	69	21	and	and	CCONJ
fcis-13142	69	22	gn	gn	PROPN
fcis-13142	69	23	layers	layer	NOUN
fcis-13142	69	24	,	,	PUNCT
fcis-13142	69	25	thereby	thereby	ADV
fcis-13142	69	26	improving	improve	VERB
fcis-13142	69	27	image	image	NOUN
fcis-13142	69	28	quality	quality	NOUN
fcis-13142	69	29	.	.	PUNCT
fcis-13142	70	1	specific	specific	ADJ
fcis-13142	70	2	details	detail	NOUN
fcis-13142	70	3	will	will	AUX
fcis-13142	70	4	be	be	AUX
fcis-13142	70	5	discussed	discuss	VERB
fcis-13142	70	6	in	in	ADP
fcis-13142	70	7	section	section	NOUN
fcis-13142	70	8	4	4	NUM
fcis-13142	70	9	.	.	NOUN
fcis-13142	70	10	3.2	3.2	NUM
fcis-13142	70	11	.	.	PUNCT
fcis-13142	71	1	loss	loss	NOUN
fcis-13142	71	2	function	function	NOUN
fcis-13142	71	3	design	design	NOUN
fcis-13142	71	4	in	in	ADP
fcis-13142	71	5	terms	term	NOUN
fcis-13142	71	6	of	of	ADP
fcis-13142	71	7	the	the	DET
fcis-13142	71	8	specific	specific	ADJ
fcis-13142	71	9	structure	structure	NOUN
fcis-13142	71	10	of	of	ADP
fcis-13142	71	11	the	the	DET
fcis-13142	71	12	loss	loss	NOUN
fcis-13142	71	13	function	function	NOUN
fcis-13142	71	14	,	,	PUNCT
fcis-13142	71	15	this	this	DET
fcis-13142	71	16	work	work	NOUN
fcis-13142	71	17	has	have	AUX
fcis-13142	71	18	not	not	PART
fcis-13142	71	19	made	make	VERB
fcis-13142	71	20	significant	significant	ADJ
fcis-13142	71	21	changes	change	NOUN
fcis-13142	71	22	.	.	PUNCT
fcis-13142	72	1	the	the	DET
fcis-13142	72	2	computation	computation	NOUN
fcis-13142	72	3	formula	formula	NOUN
fcis-13142	72	4	for	for	ADP
fcis-13142	72	5	the	the	DET
fcis-13142	72	6	loss	loss	NOUN
fcis-13142	72	7	function	function	NOUN
fcis-13142	72	8	remains	remain	VERB
fcis-13142	72	9	as	as	ADP
fcis-13142	72	10	in	in	ADP
fcis-13142	72	11	g_loss	g_loss	ADJ
fcis-13142	72	12	=	=	SYM
fcis-13142	72	13	l1_loss	l1_loss	NOUN
fcis-13142	72	14	+	+	CCONJ
fcis-13142	72	15	0.001	0.001	NUM
fcis-13142	72	16	*	*	PUNCT
fcis-13142	72	17	adversarial_loss	adversarial_loss	X
fcis-13142	72	18	(	(	PUNCT
fcis-13142	72	19	1	1	NUM
fcis-13142	72	20	)	)	PUNCT
fcis-13142	72	21	however	however	ADV
fcis-13142	72	22	,	,	PUNCT
fcis-13142	72	23	in	in	ADP
fcis-13142	72	24	our	our	PRON
fcis-13142	72	25	new	new	ADJ
fcis-13142	72	26	model	model	NOUN
fcis-13142	72	27	,	,	PUNCT
fcis-13142	72	28	this	this	DET
fcis-13142	72	29	paper	paper	NOUN
fcis-13142	72	30	has	have	AUX
fcis-13142	72	31	adopted	adopt	VERB
fcis-13142	72	32	a	a	DET
fcis-13142	72	33	relatively	relatively	ADV
fcis-13142	72	34	simpler	simple	ADJ
fcis-13142	72	35	calculation	calculation	NOUN
fcis-13142	72	36	approach	approach	NOUN
fcis-13142	72	37	.	.	PUNCT
fcis-13142	73	1	specifically	specifically	ADV
fcis-13142	73	2	,	,	PUNCT
fcis-13142	73	3	the	the	DET
fcis-13142	73	4	loss	loss	NOUN
fcis-13142	73	5	function	function	NOUN
fcis-13142	73	6	consists	consist	VERB
fcis-13142	73	7	of	of	ADP
fcis-13142	73	8	two	two	NUM
fcis-13142	73	9	main	main	ADJ
fcis-13142	73	10	components	component	NOUN
fcis-13142	73	11	:	:	PUNCT
fcis-13142	73	12	adversarial	adversarial	ADJ
fcis-13142	73	13	loss	loss	NOUN
fcis-13142	73	14	and	and	CCONJ
fcis-13142	73	15	l1	l1	PROPN
fcis-13142	73	16	loss	loss	NOUN
fcis-13142	73	17	.	.	PUNCT
fcis-13142	74	1	adversarial	adversarial	ADJ
fcis-13142	74	2	loss	loss	NOUN
fcis-13142	74	3	is	be	AUX
fcis-13142	74	4	computed	compute	VERB
fcis-13142	74	5	as	as	ADP
fcis-13142	74	6	torch.mean(1	torch.mean(1	NOUN
fcis-13142	74	7	out_labels	out_label	NOUN
fcis-13142	74	8	)	)	PUNCT
fcis-13142	74	9	.	.	PUNCT
fcis-13142	75	1	its	its	PRON
fcis-13142	75	2	purpose	purpose	NOUN
fcis-13142	75	3	is	be	AUX
fcis-13142	75	4	to	to	PART
fcis-13142	75	5	encourage	encourage	VERB
fcis-13142	75	6	the	the	DET
fcis-13142	75	7	generated	generate	VERB
fcis-13142	75	8	images	image	NOUN
fcis-13142	75	9	(	(	PUNCT
fcis-13142	75	10	out_images	out_image	NOUN
fcis-13142	75	11	)	)	PUNCT
fcis-13142	75	12	to	to	PART
fcis-13142	75	13	be	be	AUX
fcis-13142	75	14	classified	classify	VERB
fcis-13142	75	15	as	as	ADP
fcis-13142	75	16	real	real	ADJ
fcis-13142	75	17	images	image	NOUN
fcis-13142	75	18	by	by	ADP
fcis-13142	75	19	the	the	DET
fcis-13142	75	20	discriminator	discriminator	NOUN
fcis-13142	75	21	(	(	PUNCT
fcis-13142	75	22	or	or	CCONJ
fcis-13142	75	23	discriminator	discriminator	NOUN
fcis-13142	75	24	)	)	PUNCT
fcis-13142	75	25	,	,	PUNCT
fcis-13142	75	26	meaning	mean	VERB
fcis-13142	75	27	that	that	SCONJ
fcis-13142	75	28	the	the	DET
fcis-13142	75	29	probability	probability	NOUN
fcis-13142	75	30	should	should	AUX
fcis-13142	75	31	be	be	AUX
fcis-13142	75	32	close	close	ADJ
fcis-13142	75	33	to	to	ADP
fcis-13142	75	34	1	1	NUM
fcis-13142	75	35	.	.	PUNCT
fcis-13142	76	1	l1	l1	PROPN
fcis-13142	76	2	loss	loss	NOUN
fcis-13142	76	3	is	be	AUX
fcis-13142	76	4	computed	compute	VERB
fcis-13142	76	5	using	use	VERB
fcis-13142	76	6	nn.l1loss	nn.l1loss	ADV
fcis-13142	76	7	(	(	PUNCT
fcis-13142	76	8	)	)	PUNCT
fcis-13142	76	9	and	and	CCONJ
fcis-13142	76	10	is	be	AUX
fcis-13142	76	11	employed	employ	VERB
fcis-13142	76	12	to	to	PART
fcis-13142	76	13	measure	measure	VERB
fcis-13142	76	14	the	the	DET
fcis-13142	76	15	pixel	pixel	ADJ
fcis-13142	76	16	-	-	PUNCT
fcis-13142	76	17	level	level	NOUN
fcis-13142	76	18	differences	difference	NOUN
fcis-13142	76	19	between	between	ADP
fcis-13142	76	20	the	the	DET
fcis-13142	76	21	generated	generate	VERB
fcis-13142	76	22	images	image	NOUN
fcis-13142	76	23	and	and	CCONJ
fcis-13142	76	24	the	the	DET
fcis-13142	76	25	target	target	NOUN
fcis-13142	76	26	images	image	NOUN
fcis-13142	76	27	.	.	PUNCT
fcis-13142	77	1	the	the	DET
fcis-13142	77	2	initial	initial	ADJ
fcis-13142	77	3	version	version	NOUN
fcis-13142	77	4	of	of	ADP
fcis-13142	77	5	the	the	DET
fcis-13142	77	6	loss	loss	NOUN
fcis-13142	77	7	function	function	NOUN
fcis-13142	77	8	is	be	AUX
fcis-13142	77	9	relatively	relatively	ADV
fcis-13142	77	10	straightforward	straightforward	ADJ
fcis-13142	77	11	,	,	PUNCT
fcis-13142	77	12	including	include	VERB
fcis-13142	77	13	only	only	ADV
fcis-13142	77	14	adversarial	adversarial	ADJ
fcis-13142	77	15	loss	loss	NOUN
fcis-13142	77	16	and	and	CCONJ
fcis-13142	77	17	l1	l1	PROPN
fcis-13142	77	18	loss	loss	NOUN
fcis-13142	77	19	.	.	PUNCT
fcis-13142	78	1	this	this	DET
fcis-13142	78	2	simplicity	simplicity	NOUN
fcis-13142	78	3	enhances	enhance	VERB
fcis-13142	78	4	the	the	DET
fcis-13142	78	5	stability	stability	NOUN
fcis-13142	78	6	and	and	CCONJ
fcis-13142	78	7	efficiency	efficiency	NOUN
fcis-13142	78	8	of	of	ADP
fcis-13142	78	9	the	the	DET
fcis-13142	78	10	training	training	NOUN
fcis-13142	78	11	process	process	NOUN
fcis-13142	78	12	.	.	PUNCT
fcis-13142	79	1	the	the	DET
fcis-13142	79	2	reason	reason	NOUN
fcis-13142	79	3	for	for	ADP
fcis-13142	79	4	opting	opt	VERB
fcis-13142	79	5	for	for	ADP
fcis-13142	79	6	this	this	DET
fcis-13142	79	7	straightforward	straightforward	ADJ
fcis-13142	79	8	structure	structure	NOUN
fcis-13142	79	9	is	be	AUX
fcis-13142	79	10	that	that	SCONJ
fcis-13142	79	11	l1	l1	PROPN
fcis-13142	79	12	loss	loss	NOUN
fcis-13142	79	13	helps	help	VERB
fcis-13142	79	14	generate	generate	VERB
fcis-13142	79	15	images	image	NOUN
fcis-13142	79	16	that	that	PRON
fcis-13142	79	17	closely	closely	ADV
fcis-13142	79	18	resemble	resemble	VERB
fcis-13142	79	19	the	the	DET
fcis-13142	79	20	target	target	NOUN
fcis-13142	79	21	images	image	NOUN
fcis-13142	79	22	at	at	ADP
fcis-13142	79	23	the	the	DET
fcis-13142	79	24	pixel	pixel	PROPN
fcis-13142	79	25	level	level	NOUN
fcis-13142	79	26	.	.	PUNCT
fcis-13142	80	1	furthermore	furthermore	ADV
fcis-13142	80	2	,	,	PUNCT
fcis-13142	80	3	due	due	ADP
fcis-13142	80	4	to	to	ADP
fcis-13142	80	5	the	the	DET
fcis-13142	80	6	modifications	modification	NOUN
fcis-13142	80	7	in	in	ADP
fcis-13142	80	8	the	the	DET
fcis-13142	80	9	architecture	architecture	NOUN
fcis-13142	80	10	of	of	ADP
fcis-13142	80	11	the	the	DET
fcis-13142	80	12	generator	generator	NOUN
fcis-13142	80	13	,	,	PUNCT
fcis-13142	80	14	the	the	DET
fcis-13142	80	15	original	original	ADJ
fcis-13142	80	16	model	model	NOUN
fcis-13142	80	17	has	have	AUX
fcis-13142	80	18	become	become	VERB
fcis-13142	80	19	relatively	relatively	ADV
fcis-13142	80	20	complex	complex	ADJ
fcis-13142	80	21	.	.	PUNCT
fcis-13142	81	1	to	to	PART
fcis-13142	81	2	avoid	avoid	VERB
fcis-13142	81	3	introducing	introduce	VERB
fcis-13142	81	4	training	training	NOUN
fcis-13142	81	5	instability	instability	NOUN
fcis-13142	81	6	and	and	CCONJ
fcis-13142	81	7	to	to	PART
fcis-13142	81	8	make	make	VERB
fcis-13142	81	9	the	the	DET
fcis-13142	81	10	model	model	NOUN
fcis-13142	81	11	more	more	ADV
fcis-13142	81	12	amenable	amenable	ADJ
fcis-13142	81	13	to	to	ADP
fcis-13142	81	14	optimization	optimization	NOUN
fcis-13142	81	15	and	and	CCONJ
fcis-13142	81	16	debugging	debugging	NOUN
fcis-13142	81	17	,	,	PUNCT
fcis-13142	81	18	this	this	DET
fcis-13142	81	19	paper	paper	NOUN
fcis-13142	81	20	has	have	AUX
fcis-13142	81	21	chosen	choose	VERB
fcis-13142	81	22	to	to	PART
fcis-13142	81	23	follow	follow	VERB
fcis-13142	81	24	a	a	DET
fcis-13142	81	25	more	more	ADV
fcis-13142	81	26	classical	classical	ADJ
fcis-13142	81	27	approach	approach	NOUN
fcis-13142	81	28	.	.	PUNCT
fcis-13142	82	1	overall	overall	ADV
fcis-13142	82	2	,	,	PUNCT
fcis-13142	82	3	this	this	DET
fcis-13142	82	4	design	design	NOUN
fcis-13142	82	5	of	of	ADP
fcis-13142	82	6	the	the	DET
fcis-13142	82	7	loss	loss	NOUN
fcis-13142	82	8	function	function	NOUN
fcis-13142	82	9	,	,	PUNCT
fcis-13142	82	10	although	although	SCONJ
fcis-13142	82	11	simple	simple	ADJ
fcis-13142	82	12	,	,	PUNCT
fcis-13142	82	13	serves	serve	VERB
fcis-13142	82	14	the	the	DET
fcis-13142	82	15	purpose	purpose	NOUN
fcis-13142	82	16	of	of	ADP
fcis-13142	82	17	encouraging	encourage	VERB
fcis-13142	82	18	high	high	ADJ
fcis-13142	82	19	-	-	PUNCT
fcis-13142	82	20	quality	quality	NOUN
fcis-13142	82	21	image	image	NOUN
fcis-13142	82	22	generation	generation	NOUN
fcis-13142	82	23	,	,	PUNCT
fcis-13142	82	24	and	and	CCONJ
fcis-13142	82	25	its	its	PRON
fcis-13142	82	26	simplicity	simplicity	NOUN
fcis-13142	82	27	aids	aid	NOUN
fcis-13142	82	28	in	in	ADP
fcis-13142	82	29	training	training	NOUN
fcis-13142	82	30	stability	stability	NOUN
fcis-13142	82	31	,	,	PUNCT
fcis-13142	82	32	optimization	optimization	NOUN
fcis-13142	82	33	,	,	PUNCT
fcis-13142	82	34	and	and	CCONJ
fcis-13142	82	35	debugging	debugging	NOUN
fcis-13142	82	36	.	.	PUNCT
fcis-13142	83	1	4	4	X
fcis-13142	83	2	.	.	NUM
fcis-13142	83	3	experiments	experiment	NOUN
fcis-13142	83	4	4.1	4.1	NUM
fcis-13142	83	5	.	.	PUNCT
fcis-13142	84	1	training	training	NOUN
fcis-13142	84	2	details	detail	NOUN
fcis-13142	84	3	this	this	DET
fcis-13142	84	4	experiment	experiment	NOUN
fcis-13142	84	5	,	,	PUNCT
fcis-13142	84	6	which	which	PRON
fcis-13142	84	7	draws	draw	VERB
fcis-13142	84	8	inspiration	inspiration	NOUN
fcis-13142	84	9	from	from	ADP
fcis-13142	84	10	srgan	srgan	NOUN
fcis-13142	84	11	,	,	PUNCT
fcis-13142	84	12	was	be	AUX
fcis-13142	84	13	configured	configure	VERB
fcis-13142	84	14	with	with	ADP
fcis-13142	84	15	the	the	DET
fcis-13142	84	16	following	follow	VERB
fcis-13142	84	17	specific	specific	ADJ
fcis-13142	84	18	parameters	parameter	NOUN
fcis-13142	84	19	:	:	PUNCT
fcis-13142	84	20	a	a	DET
fcis-13142	84	21	scaling	scale	VERB
fcis-13142	84	22	factor	factor	NOUN
fcis-13142	84	23	of	of	ADP
fcis-13142	84	24	4	4	NUM
fcis-13142	84	25	between	between	ADP
fcis-13142	84	26	lr	lr	PROPN
fcis-13142	84	27	(	(	PUNCT
fcis-13142	84	28	low	low	ADJ
fcis-13142	84	29	-	-	PUNCT
fcis-13142	84	30	resolution	resolution	NOUN
fcis-13142	84	31	)	)	PUNCT
fcis-13142	84	32	and	and	CCONJ
fcis-13142	84	33	hr	hr	NOUN
fcis-13142	84	34	(	(	PUNCT
fcis-13142	84	35	high	high	ADJ
fcis-13142	84	36	-	-	PUNCT
fcis-13142	84	37	resolution	resolution	NOUN
fcis-13142	84	38	)	)	PUNCT
fcis-13142	84	39	images	image	NOUN
fcis-13142	84	40	,	,	PUNCT
fcis-13142	84	41	a	a	DET
fcis-13142	84	42	batch	batch	NOUN
fcis-13142	84	43	size	size	NOUN
fcis-13142	84	44	of	of	ADP
fcis-13142	84	45	16	16	NUM
fcis-13142	84	46	,	,	PUNCT
fcis-13142	84	47	and	and	CCONJ
fcis-13142	84	48	hr	hr	NOUN
fcis-13142	84	49	image	image	NOUN
fcis-13142	84	50	blocks	block	NOUN
fcis-13142	84	51	cropped	crop	VERB
fcis-13142	84	52	to	to	ADP
fcis-13142	84	53	a	a	DET
fcis-13142	84	54	spatial	spatial	ADJ
fcis-13142	84	55	size	size	NOUN
fcis-13142	84	56	of	of	ADP
fcis-13142	84	57	128	128	NUM
fcis-13142	84	58	×	×	NOUN
fcis-13142	84	59	128	128	NUM
fcis-13142	84	60	pixels	pixel	NOUN
fcis-13142	84	61	.	.	PUNCT
fcis-13142	85	1	the	the	DET
fcis-13142	85	2	experiment	experiment	NOUN
fcis-13142	85	3	consisted	consist	VERB
fcis-13142	85	4	of	of	ADP
fcis-13142	85	5	100	100	NUM
fcis-13142	85	6	iterations	iteration	NOUN
fcis-13142	85	7	,	,	PUNCT
fcis-13142	85	8	and	and	CCONJ
fcis-13142	85	9	its	its	PRON
fcis-13142	85	10	overall	overall	ADJ
fcis-13142	85	11	process	process	NOUN
fcis-13142	85	12	can	can	AUX
fcis-13142	85	13	be	be	AUX
fcis-13142	85	14	summarized	summarize	VERB
fcis-13142	85	15	as	as	SCONJ
fcis-13142	85	16	follows	follow	VERB
fcis-13142	85	17	:	:	PUNCT
fcis-13142	85	18	4.1.1	4.1.1	X
fcis-13142	85	19	.	.	PUNCT
fcis-13142	86	1	for	for	ADP
fcis-13142	86	2	initialization	initialization	NOUN
fcis-13142	86	3	:	:	PUNCT
fcis-13142	86	4	initially	initially	ADV
fcis-13142	86	5	,	,	PUNCT
fcis-13142	86	6	instances	instance	NOUN
fcis-13142	86	7	of	of	ADP
fcis-13142	86	8	the	the	DET
fcis-13142	86	9	generator	generator	NOUN
fcis-13142	86	10	(	(	PUNCT
fcis-13142	86	11	netg	netg	PROPN
fcis-13142	86	12	)	)	PUNCT
fcis-13142	86	13	and	and	CCONJ
fcis-13142	86	14	discriminator	discriminator	NOUN
fcis-13142	86	15	(	(	PUNCT
fcis-13142	86	16	netd	netd	NOUN
fcis-13142	86	17	)	)	PUNCT
fcis-13142	86	18	were	be	AUX
fcis-13142	86	19	created	create	VERB
fcis-13142	86	20	.	.	PUNCT
fcis-13142	87	1	4.1.2	4.1.2	X
fcis-13142	87	2	.	.	PUNCT
fcis-13142	87	3	loss	loss	NOUN
fcis-13142	87	4	and	and	CCONJ
fcis-13142	87	5	optimization	optimization	NOUN
fcis-13142	87	6	setup	setup	NOUN
fcis-13142	87	7	:	:	PUNCT
fcis-13142	87	8	the	the	DET
fcis-13142	87	9	generator	generator	NOUN
fcis-13142	87	10	's	's	PART
fcis-13142	87	11	loss	loss	NOUN
fcis-13142	87	12	function	function	NOUN
fcis-13142	87	13	(	(	PUNCT
fcis-13142	87	14	generator_criterion	generator_criterion	NOUN
fcis-13142	87	15	)	)	PUNCT
fcis-13142	87	16	and	and	CCONJ
fcis-13142	87	17	optimizers	optimizer	NOUN
fcis-13142	87	18	(	(	PUNCT
fcis-13142	87	19	optimizerg	optimizerg	PROPN
fcis-13142	87	20	and	and	CCONJ
fcis-13142	87	21	optimizerd	optimizerd	ADJ
fcis-13142	87	22	)	)	PUNCT
fcis-13142	87	23	were	be	AUX
fcis-13142	87	24	defined	define	VERB
fcis-13142	87	25	.	.	PUNCT
fcis-13142	88	1	these	these	DET
fcis-13142	88	2	components	component	NOUN
fcis-13142	88	3	were	be	AUX
fcis-13142	88	4	used	use	VERB
fcis-13142	88	5	for	for	ADP
fcis-13142	88	6	training	train	VERB
fcis-13142	88	7	the	the	DET
fcis-13142	88	8	generator	generator	NOUN
fcis-13142	88	9	and	and	CCONJ
fcis-13142	88	10	discriminator	discriminator	NOUN
fcis-13142	88	11	.	.	PUNCT
fcis-13142	89	1	4.1.3	4.1.3	NUM
fcis-13142	89	2	.	.	PUNCT
fcis-13142	89	3	data	datum	NOUN
fcis-13142	89	4	storage	storage	NOUN
fcis-13142	89	5	:	:	PUNCT
fcis-13142	89	6	an	an	DET
fcis-13142	89	7	empty	empty	ADJ
fcis-13142	89	8	dictionary	dictionary	NOUN
fcis-13142	89	9	named	name	VERB
fcis-13142	89	10	"	"	PUNCT
fcis-13142	89	11	results	result	NOUN
fcis-13142	89	12	"	"	PUNCT
fcis-13142	89	13	was	be	AUX
fcis-13142	89	14	established	establish	VERB
fcis-13142	89	15	.	.	PUNCT
fcis-13142	90	1	this	this	DET
fcis-13142	90	2	dictionary	dictionary	NOUN
fcis-13142	90	3	was	be	AUX
fcis-13142	90	4	employed	employ	VERB
fcis-13142	90	5	to	to	PART
fcis-13142	90	6	store	store	VERB
fcis-13142	90	7	various	various	ADJ
fcis-13142	90	8	metrics	metric	NOUN
fcis-13142	90	9	during	during	ADP
fcis-13142	90	10	the	the	DET
fcis-13142	90	11	training	training	NOUN
fcis-13142	90	12	process	process	NOUN
fcis-13142	90	13	,	,	PUNCT
fcis-13142	90	14	including	include	VERB
fcis-13142	90	15	losses	loss	NOUN
fcis-13142	90	16	,	,	PUNCT
fcis-13142	90	17	scores	score	NOUN
fcis-13142	90	18	,	,	PUNCT
fcis-13142	90	19	psnr	psnr	NOUN
fcis-13142	90	20	,	,	PUNCT
fcis-13142	90	21	ssim	ssim	NOUN
fcis-13142	90	22	.	.	PUNCT
fcis-13142	91	1	4.1.4	4.1.4	X
fcis-13142	91	2	.	.	PUNCT
fcis-13142	92	1	training	training	NOUN
fcis-13142	92	2	loop	loop	NOUN
fcis-13142	92	3	:	:	PUNCT
fcis-13142	92	4	the	the	DET
fcis-13142	92	5	main	main	ADJ
fcis-13142	92	6	training	training	NOUN
fcis-13142	92	7	loop	loop	NOUN
fcis-13142	92	8	began	begin	VERB
fcis-13142	92	9	.	.	PUNCT
fcis-13142	93	1	in	in	ADP
fcis-13142	93	2	each	each	DET
fcis-13142	93	3	iteration	iteration	NOUN
fcis-13142	93	4	,	,	PUNCT
fcis-13142	93	5	the	the	DET
fcis-13142	93	6	following	follow	VERB
fcis-13142	93	7	steps	step	NOUN
fcis-13142	93	8	were	be	AUX
fcis-13142	93	9	executed	execute	VERB
fcis-13142	93	10	:	:	PUNCT
fcis-13142	93	11	training	training	NOUN
fcis-13142	93	12	mode	mode	NOUN
fcis-13142	93	13	:	:	PUNCT
fcis-13142	93	14	the	the	DET
fcis-13142	93	15	generator	generator	NOUN
fcis-13142	93	16	and	and	CCONJ
fcis-13142	93	17	discriminator	discriminator	NOUN
fcis-13142	93	18	were	be	AUX
fcis-13142	93	19	set	set	VERB
fcis-13142	93	20	to	to	ADP
fcis-13142	93	21	training	training	NOUN
fcis-13142	93	22	mode	mode	NOUN
fcis-13142	93	23	.	.	PUNCT
fcis-13142	94	1	data	datum	NOUN
fcis-13142	94	2	loading	loading	NOUN
fcis-13142	94	3	:	:	PUNCT
fcis-13142	94	4	the	the	DET
fcis-13142	94	5	code	code	NOUN
fcis-13142	94	6	iterated	iterate	VERB
fcis-13142	94	7	through	through	ADP
fcis-13142	94	8	the	the	DET
fcis-13142	94	9	training	training	NOUN
fcis-13142	94	10	dataset	dataset	NOUN
fcis-13142	94	11	,	,	PUNCT
fcis-13142	94	12	loading	load	VERB
fcis-13142	94	13	batches	batch	NOUN
fcis-13142	94	14	of	of	ADP
fcis-13142	94	15	image	image	NOUN
fcis-13142	94	16	data	datum	NOUN
fcis-13142	94	17	.	.	PUNCT
fcis-13142	95	1	discriminator	discriminator	NOUN
fcis-13142	95	2	update	update	NOUN
fcis-13142	95	3	:	:	PUNCT
fcis-13142	95	4	for	for	ADP
fcis-13142	95	5	each	each	DET
fcis-13142	95	6	batch	batch	NOUN
fcis-13142	95	7	,	,	PUNCT
fcis-13142	95	8	the	the	DET
fcis-13142	95	9	discriminator	discriminator	NOUN
fcis-13142	95	10	(	(	PUNCT
fcis-13142	95	11	d	d	NOUN
fcis-13142	95	12	)	)	PUNCT
fcis-13142	95	13	network	network	NOUN
fcis-13142	95	14	was	be	AUX
fcis-13142	95	15	updated	update	VERB
fcis-13142	95	16	.	.	PUNCT
fcis-13142	96	1	this	this	DET
fcis-13142	96	2	process	process	NOUN
fcis-13142	96	3	involved	involve	VERB
fcis-13142	96	4	computing	compute	VERB
fcis-13142	96	5	the	the	DET
fcis-13142	96	6	discriminator	discriminator	NOUN
fcis-13142	96	7	outputs	output	NOUN
fcis-13142	96	8	for	for	ADP
fcis-13142	96	9	both	both	CCONJ
fcis-13142	96	10	real	real	ADJ
fcis-13142	96	11	and	and	CCONJ
fcis-13142	96	12	generated	generate	VERB
fcis-13142	96	13	images	image	NOUN
fcis-13142	96	14	and	and	CCONJ
fcis-13142	96	15	calculating	calculate	VERB
fcis-13142	96	16	the	the	DET
fcis-13142	96	17	discriminator	discriminator	NOUN
fcis-13142	96	18	loss	loss	NOUN
fcis-13142	96	19	.	.	PUNCT
fcis-13142	97	1	subsequently	subsequently	ADV
fcis-13142	97	2	,	,	PUNCT
fcis-13142	97	3	backpropagation	backpropagation	NOUN
fcis-13142	97	4	and	and	CCONJ
fcis-13142	97	5	optimization	optimization	NOUN
fcis-13142	97	6	were	be	AUX
fcis-13142	97	7	performed	perform	VERB
fcis-13142	97	8	.	.	PUNCT
fcis-13142	98	1	generator	generator	NOUN
fcis-13142	98	2	update	update	NOUN
fcis-13142	98	3	:	:	PUNCT
fcis-13142	98	4	the	the	DET
fcis-13142	98	5	generator	generator	NOUN
fcis-13142	98	6	(	(	PUNCT
fcis-13142	98	7	g	g	NOUN
fcis-13142	98	8	)	)	PUNCT
fcis-13142	98	9	network	network	NOUN
fcis-13142	98	10	was	be	AUX
fcis-13142	98	11	then	then	ADV
fcis-13142	98	12	updated	update	VERB
fcis-13142	98	13	.	.	PUNCT
fcis-13142	99	1	this	this	DET
fcis-13142	99	2	step	step	NOUN
fcis-13142	99	3	included	include	VERB
fcis-13142	99	4	computing	compute	VERB
fcis-13142	99	5	the	the	DET
fcis-13142	99	6	discriminator	discriminator	NOUN
fcis-13142	99	7	output	output	NOUN
fcis-13142	99	8	for	for	ADP
fcis-13142	99	9	the	the	DET
fcis-13142	99	10	generated	generate	VERB
fcis-13142	99	11	images	image	NOUN
fcis-13142	99	12	and	and	CCONJ
fcis-13142	99	13	calculating	calculate	VERB
fcis-13142	99	14	the	the	DET
fcis-13142	99	15	generator	generator	NOUN
fcis-13142	99	16	loss	loss	NOUN
fcis-13142	99	17	.	.	PUNCT
fcis-13142	100	1	again	again	ADV
fcis-13142	100	2	,	,	PUNCT
fcis-13142	100	3	backpropagation	backpropagation	NOUN
fcis-13142	100	4	and	and	CCONJ
fcis-13142	100	5	optimization	optimization	NOUN
fcis-13142	100	6	were	be	AUX
fcis-13142	100	7	carried	carry	VERB
fcis-13142	100	8	out	out	ADP
fcis-13142	100	9	.	.	PUNCT
fcis-13142	101	1	loss	loss	NOUN
fcis-13142	101	2	and	and	CCONJ
fcis-13142	101	3	score	score	NOUN
fcis-13142	101	4	updates	update	NOUN
fcis-13142	101	5	:	:	PUNCT
fcis-13142	101	6	the	the	DET
fcis-13142	101	7	losses	loss	NOUN
fcis-13142	101	8	and	and	CCONJ
fcis-13142	101	9	scores	score	NOUN
fcis-13142	101	10	for	for	ADP
fcis-13142	101	11	the	the	DET
fcis-13142	101	12	current	current	ADJ
fcis-13142	101	13	batch	batch	NOUN
fcis-13142	101	14	were	be	AUX
fcis-13142	101	15	computed	compute	VERB
fcis-13142	101	16	and	and	CCONJ
fcis-13142	101	17	updated	update	VERB
fcis-13142	101	18	.	.	PUNCT
fcis-13142	102	1	4.1.5	4.1.5	X
fcis-13142	102	2	.	.	PUNCT
fcis-13142	102	3	evaluation	evaluation	NOUN
fcis-13142	102	4	mode	mode	NOUN
fcis-13142	102	5	:	:	PUNCT
fcis-13142	102	6	after	after	ADP
fcis-13142	102	7	each	each	DET
fcis-13142	102	8	iteration	iteration	NOUN
fcis-13142	102	9	,	,	PUNCT
fcis-13142	102	10	the	the	DET
fcis-13142	102	11	generator	generator	NOUN
fcis-13142	102	12	was	be	AUX
fcis-13142	102	13	set	set	VERB
fcis-13142	102	14	to	to	ADP
fcis-13142	102	15	evaluation	evaluation	NOUN
fcis-13142	102	16	mode	mode	NOUN
fcis-13142	102	17	,	,	PUNCT
fcis-13142	102	18	and	and	CCONJ
fcis-13142	102	19	the	the	DET
fcis-13142	102	20	model	model	NOUN
fcis-13142	102	21	's	's	PART
fcis-13142	102	22	performance	performance	NOUN
fcis-13142	102	23	was	be	AUX
fcis-13142	102	24	assessed	assess	VERB
fcis-13142	102	25	using	use	VERB
fcis-13142	102	26	a	a	DET
fcis-13142	102	27	validation	validation	NOUN
fcis-13142	102	28	dataset	dataset	NOUN
fcis-13142	102	29	.	.	PUNCT
fcis-13142	103	1	metrics	metric	NOUN
fcis-13142	103	2	such	such	ADJ
fcis-13142	103	3	as	as	ADP
fcis-13142	103	4	psnr	psnr	NOUN
fcis-13142	103	5	and	and	CCONJ
fcis-13142	103	6	ssim	ssim	NOUN
fcis-13142	103	7	were	be	AUX
fcis-13142	103	8	computed	compute	VERB
fcis-13142	103	9	to	to	PART
fcis-13142	103	10	evaluate	evaluate	VERB
fcis-13142	103	11	the	the	DET
fcis-13142	103	12	model	model	NOUN
fcis-13142	103	13	's	's	PART
fcis-13142	103	14	quality	quality	NOUN
fcis-13142	103	15	.	.	PUNCT
fcis-13142	104	1	4.1.6	4.1.6	X
fcis-13142	104	2	.	.	PROPN
fcis-13142	104	3	results	result	NOUN
fcis-13142	104	4	and	and	CCONJ
fcis-13142	104	5	model	model	NOUN
fcis-13142	104	6	saving	saving	PROPN
fcis-13142	104	7	:	:	PUNCT
fcis-13142	104	8	the	the	DET
fcis-13142	104	9	model	model	NOUN
fcis-13142	104	10	parameters	parameter	NOUN
fcis-13142	104	11	,	,	PUNCT
fcis-13142	104	12	training	training	NOUN
fcis-13142	104	13	results	result	NOUN
fcis-13142	104	14	,	,	PUNCT
fcis-13142	104	15	and	and	CCONJ
fcis-13142	104	16	evaluation	evaluation	NOUN
fcis-13142	104	17	metrics	metric	NOUN
fcis-13142	104	18	were	be	AUX
fcis-13142	104	19	saved	save	VERB
fcis-13142	104	20	.	.	PUNCT
fcis-13142	105	1	4.1.7	4.1.7	NUM
fcis-13142	105	2	.	.	PUNCT
fcis-13142	106	1	periodic	periodic	ADJ
fcis-13142	106	2	metric	metric	ADJ
fcis-13142	106	3	recording	recording	NOUN
fcis-13142	106	4	:	:	PUNCT
fcis-13142	106	5	at	at	ADP
fcis-13142	106	6	regular	regular	ADJ
fcis-13142	106	7	intervals	interval	NOUN
fcis-13142	106	8	during	during	ADP
fcis-13142	106	9	training	training	NOUN
fcis-13142	106	10	,	,	PUNCT
fcis-13142	106	11	the	the	DET
fcis-13142	106	12	experiment	experiment	NOUN
fcis-13142	106	13	recorded	record	VERB
fcis-13142	106	14	metrics	metric	NOUN
fcis-13142	106	15	such	such	ADJ
fcis-13142	106	16	as	as	ADP
fcis-13142	106	17	losses	loss	NOUN
fcis-13142	106	18	,	,	PUNCT
fcis-13142	106	19	scores	score	NOUN
fcis-13142	106	20	,	,	PUNCT
fcis-13142	106	21	psnr	psnr	NOUN
fcis-13142	106	22	,	,	PUNCT
fcis-13142	106	23	and	and	CCONJ
fcis-13142	106	24	ssim	ssim	VERB
fcis-13142	106	25	into	into	ADP
fcis-13142	106	26	a	a	DET
fcis-13142	106	27	csv	csv	NOUN
fcis-13142	106	28	file	file	NOUN
fcis-13142	106	29	.	.	PUNCT
fcis-13142	107	1	this	this	DET
fcis-13142	107	2	data	datum	NOUN
fcis-13142	107	3	was	be	AUX
fcis-13142	107	4	intended	intend	VERB
fcis-13142	107	5	for	for	ADP
fcis-13142	107	6	subsequent	subsequent	ADJ
fcis-13142	107	7	analysis	analysis	NOUN
fcis-13142	107	8	and	and	CCONJ
fcis-13142	107	9	visualization	visualization	NOUN
fcis-13142	107	10	4.2	4.2	NUM
fcis-13142	107	11	.	.	PUNCT
fcis-13142	108	1	data	datum	NOUN
fcis-13142	108	2	in	in	ADP
fcis-13142	108	3	the	the	DET
fcis-13142	108	4	training	training	NOUN
fcis-13142	108	5	phase	phase	NOUN
fcis-13142	108	6	,	,	PUNCT
fcis-13142	108	7	the	the	DET
fcis-13142	108	8	dataset	dataset	NOUN
fcis-13142	108	9	used	use	VERB
fcis-13142	108	10	is	be	AUX
fcis-13142	108	11	the	the	DET
fcis-13142	108	12	div2k	div2k	PROPN
fcis-13142	108	13	dataset	dataset	NOUN
fcis-13142	109	1	[	[	PUNCT
fcis-13142	109	2	9	9	NUM
fcis-13142	109	3	]	]	PUNCT
fcis-13142	109	4	.	.	PUNCT
fcis-13142	110	1	div2k	div2k	PROPN
fcis-13142	111	1	(	(	PUNCT
fcis-13142	111	2	diverse	diverse	ADJ
fcis-13142	111	3	2k	2k	NUM
fcis-13142	111	4	resolution	resolution	NOUN
fcis-13142	111	5	high	high	ADJ
fcis-13142	111	6	-	-	PUNCT
fcis-13142	111	7	quality	quality	NOUN
fcis-13142	111	8	images	image	NOUN
fcis-13142	111	9	)	)	PUNCT
fcis-13142	111	10	is	be	AUX
fcis-13142	111	11	a	a	DET
fcis-13142	111	12	commonly	commonly	ADV
fcis-13142	111	13	used	use	VERB
fcis-13142	111	14	dataset	dataset	NOUN
fcis-13142	111	15	for	for	ADP
fcis-13142	111	16	super	super	ADJ
fcis-13142	111	17	-	-	ADJ
fcis-13142	111	18	resolution	resolution	ADJ
fcis-13142	111	19	image	image	NOUN
fcis-13142	111	20	processing	processing	NOUN
fcis-13142	111	21	tasks	task	NOUN
fcis-13142	111	22	.	.	PUNCT
fcis-13142	112	1	it	it	PRON
fcis-13142	112	2	consists	consist	VERB
fcis-13142	112	3	of	of	ADP
fcis-13142	112	4	800	800	NUM
fcis-13142	112	5	diverse	diverse	ADJ
fcis-13142	112	6	high	high	ADJ
fcis-13142	112	7	-	-	PUNCT
fcis-13142	112	8	quality	quality	NOUN
fcis-13142	112	9	images	image	NOUN
fcis-13142	112	10	,	,	PUNCT
fcis-13142	112	11	typically	typically	ADV
fcis-13142	112	12	at	at	ADP
fcis-13142	112	13	a	a	DET
fcis-13142	112	14	resolution	resolution	NOUN
fcis-13142	112	15	of	of	ADP
fcis-13142	112	16	2k	2k	NOUN
fcis-13142	112	17	(	(	PUNCT
fcis-13142	112	18	usually	usually	ADV
fcis-13142	112	19	referring	refer	VERB
fcis-13142	112	20	to	to	ADP
fcis-13142	112	21	2048x1080	2048x1080	NOUN
fcis-13142	112	22	pixels	pixel	NOUN
fcis-13142	112	23	)	)	PUNCT
fcis-13142	112	24	,	,	PUNCT
fcis-13142	112	25	and	and	CCONJ
fcis-13142	112	26	is	be	AUX
fcis-13142	112	27	used	use	VERB
fcis-13142	112	28	for	for	ADP
fcis-13142	112	29	training	training	NOUN
fcis-13142	112	30	and	and	CCONJ
fcis-13142	112	31	evaluation	evaluation	NOUN
fcis-13142	112	32	of	of	ADP
fcis-13142	112	33	super	super	NOUN
fcis-13142	112	34	-	-	NOUN
fcis-13142	112	35	resolution	resolution	NOUN
fcis-13142	112	36	,	,	PUNCT
fcis-13142	112	37	image	image	NOUN
fcis-13142	112	38	restoration	restoration	NOUN
fcis-13142	112	39	,	,	PUNCT
fcis-13142	112	40	and	and	CCONJ
fcis-13142	112	41	other	other	ADJ
fcis-13142	112	42	computer	computer	NOUN
fcis-13142	112	43	vision	vision	NOUN
fcis-13142	112	44	tasks	task	NOUN
fcis-13142	112	45	.	.	PUNCT
fcis-13142	113	1	in	in	ADP
fcis-13142	113	2	the	the	DET
fcis-13142	113	3	testing	testing	NOUN
fcis-13142	113	4	phase	phase	NOUN
fcis-13142	113	5	,	,	PUNCT
fcis-13142	113	6	this	this	DET
fcis-13142	113	7	experiment	experiment	NOUN
fcis-13142	113	8	employed	employ	VERB
fcis-13142	113	9	several	several	ADJ
fcis-13142	113	10	datasets	dataset	NOUN
fcis-13142	113	11	,	,	PUNCT
fcis-13142	113	12	including	include	VERB
fcis-13142	113	13	set5	set5	PROPN
fcis-13142	113	14	,	,	PUNCT
fcis-13142	113	15	set14	set14	NOUN
fcis-13142	113	16	,	,	PUNCT
fcis-13142	113	17	bsd100[10	bsd100[10	PROPN
fcis-13142	113	18	]	]	PUNCT
fcis-13142	113	19	,	,	PUNCT
fcis-13142	113	20	and	and	CCONJ
fcis-13142	113	21	urban100	urban100	PROPN
fcis-13142	113	22	,	,	PUNCT
fcis-13142	113	23	for	for	ADP
fcis-13142	113	24	evaluation	evaluation	NOUN
fcis-13142	113	25	.	.	PUNCT
fcis-13142	114	1	4.3	4.3	NUM
fcis-13142	114	2	.	.	PUNCT
fcis-13142	114	3	results	result	VERB
fcis-13142	114	4	this	this	DET
fcis-13142	114	5	experiment	experiment	NOUN
fcis-13142	114	6	compares	compare	VERB
fcis-13142	114	7	the	the	DET
fcis-13142	114	8	new	new	ADJ
fcis-13142	114	9	model	model	NOUN
fcis-13142	114	10	with	with	ADP
fcis-13142	114	11	the	the	DET
fcis-13142	114	12	original	original	ADJ
fcis-13142	114	13	srgan	srgan	NOUN
fcis-13142	114	14	.	.	PUNCT
fcis-13142	115	1	here	here	ADV
fcis-13142	115	2	are	be	AUX
fcis-13142	115	3	the	the	DET
fcis-13142	115	4	relevant	relevant	ADJ
fcis-13142	115	5	data	datum	NOUN
fcis-13142	115	6	and	and	CCONJ
fcis-13142	115	7	performance	performance	NOUN
fcis-13142	115	8	comparisons	comparison	NOUN
fcis-13142	115	9	.	.	PUNCT
fcis-13142	116	1	134	134	NUM
fcis-13142	116	2	table	table	NOUN
fcis-13142	116	3	1	1	NUM
fcis-13142	116	4	.	.	PUNCT
fcis-13142	116	5	relevant	relevant	ADJ
fcis-13142	116	6	data	data	PROPN
fcis-13142	116	7	model	model	NOUN
fcis-13142	116	8	dataset	dataset	NOUN
fcis-13142	116	9	(	(	PUNCT
fcis-13142	116	10	psnr	psnr	NOUN
fcis-13142	116	11	/	/	SYM
fcis-13142	116	12	ssim	ssim	NOUN
fcis-13142	116	13	)	)	PUNCT
fcis-13142	116	14	set5	set5	PROPN
fcis-13142	116	15	set14	set14	PROPN
fcis-13142	116	16	bsd100	bsd100	PROPN
fcis-13142	116	17	urban100	urban100	PROPN
fcis-13142	116	18	srgan	srgan	VERB
fcis-13142	116	19	28.63/	28.63/	NUM
fcis-13142	116	20	0.83	0.83	NUM
fcis-13142	116	21	25.49/	25.49/	NUM
fcis-13142	116	22	0.73	0.73	NUM
fcis-13142	116	23	25.56/	25.56/	NUM
fcis-13142	116	24	0.69	0.69	NUM
fcis-13142	116	25	25.45/	25.45/	NUM
fcis-13142	116	26	0.72	0.72	NUM
fcis-13142	116	27	new	new	ADJ
fcis-13142	116	28	model	model	NOUN
fcis-13142	116	29	26.73/	26.73/	NUM
fcis-13142	116	30	0.84	0.84	NUM
fcis-13142	116	31	23.57/	23.57/	NUM
fcis-13142	116	32	0.73	0.73	NUM
fcis-13142	116	33	23.70/	23.70/	NUM
fcis-13142	116	34	0.69	0.69	NUM
fcis-13142	116	35	21.33/	21.33/	NUM
fcis-13142	116	36	0.72	0.72	NUM
fcis-13142	116	37	from	from	ADP
fcis-13142	116	38	this	this	DET
fcis-13142	116	39	table	table	NOUN
fcis-13142	116	40	,	,	PUNCT
fcis-13142	116	41	it	it	PRON
fcis-13142	116	42	can	can	AUX
fcis-13142	116	43	be	be	AUX
fcis-13142	116	44	observed	observe	VERB
fcis-13142	116	45	that	that	SCONJ
fcis-13142	116	46	the	the	DET
fcis-13142	116	47	new	new	ADJ
fcis-13142	116	48	model	model	NOUN
fcis-13142	116	49	exhibits	exhibit	VERB
fcis-13142	116	50	a	a	DET
fcis-13142	116	51	slight	slight	ADJ
fcis-13142	116	52	decrease	decrease	NOUN
fcis-13142	116	53	in	in	ADP
fcis-13142	116	54	psnr	psnr	NOUN
fcis-13142	116	55	compared	compare	VERB
fcis-13142	116	56	to	to	ADP
fcis-13142	116	57	srgan	srgan	VERB
fcis-13142	116	58	,	,	PUNCT
fcis-13142	116	59	but	but	CCONJ
fcis-13142	116	60	the	the	DET
fcis-13142	116	61	ssim	ssim	NOUN
fcis-13142	116	62	values	value	NOUN
fcis-13142	116	63	are	be	AUX
fcis-13142	116	64	close	close	ADJ
fcis-13142	116	65	to	to	ADP
fcis-13142	116	66	being	be	AUX
fcis-13142	116	67	the	the	DET
fcis-13142	116	68	same	same	ADJ
fcis-13142	116	69	.	.	PUNCT
fcis-13142	117	1	this	this	DET
fcis-13142	117	2	phenomenon	phenomenon	NOUN
fcis-13142	117	3	reflects	reflect	VERB
fcis-13142	117	4	the	the	DET
fcis-13142	117	5	distinct	distinct	ADJ
fcis-13142	117	6	performance	performance	NOUN
fcis-13142	117	7	characteristics	characteristic	NOUN
fcis-13142	117	8	of	of	ADP
fcis-13142	117	9	the	the	DET
fcis-13142	117	10	two	two	NUM
fcis-13142	117	11	models	model	NOUN
fcis-13142	117	12	in	in	ADP
fcis-13142	117	13	image	image	NOUN
fcis-13142	117	14	reconstruction	reconstruction	NOUN
fcis-13142	117	15	tasks	task	NOUN
fcis-13142	117	16	.	.	PUNCT
fcis-13142	118	1	due	due	ADP
fcis-13142	118	2	to	to	ADP
fcis-13142	118	3	the	the	DET
fcis-13142	118	4	introduction	introduction	NOUN
fcis-13142	118	5	of	of	ADP
fcis-13142	118	6	attention	attention	NOUN
fcis-13142	118	7	mechanisms	mechanism	NOUN
fcis-13142	118	8	,	,	PUNCT
fcis-13142	118	9	the	the	DET
fcis-13142	118	10	new	new	ADJ
fcis-13142	118	11	model	model	NOUN
fcis-13142	118	12	may	may	AUX
fcis-13142	118	13	not	not	PART
fcis-13142	118	14	particularly	particularly	ADV
fcis-13142	118	15	emphasize	emphasize	VERB
fcis-13142	118	16	pixel	pixel	ADJ
fcis-13142	118	17	changes	change	NOUN
fcis-13142	118	18	in	in	ADP
fcis-13142	118	19	certain	certain	ADJ
fcis-13142	118	20	areas	area	NOUN
fcis-13142	118	21	of	of	ADP
fcis-13142	118	22	an	an	DET
fcis-13142	118	23	image	image	NOUN
fcis-13142	118	24	.	.	PUNCT
fcis-13142	119	1	however	however	ADV
fcis-13142	119	2	,	,	PUNCT
fcis-13142	119	3	from	from	ADP
fcis-13142	119	4	a	a	DET
fcis-13142	119	5	perceptual	perceptual	ADJ
fcis-13142	119	6	perspective	perspective	NOUN
fcis-13142	119	7	,	,	PUNCT
fcis-13142	119	8	the	the	DET
fcis-13142	119	9	primary	primary	ADJ
fcis-13142	119	10	concern	concern	NOUN
fcis-13142	119	11	is	be	AUX
fcis-13142	119	12	the	the	DET
fcis-13142	119	13	perceived	perceive	VERB
fcis-13142	119	14	image	image	NOUN
fcis-13142	119	15	quality	quality	NOUN
fcis-13142	119	16	.	.	PUNCT
fcis-13142	120	1	therefore	therefore	ADV
fcis-13142	120	2	,	,	PUNCT
fcis-13142	120	3	the	the	DET
fcis-13142	120	4	new	new	ADJ
fcis-13142	120	5	model	model	NOUN
fcis-13142	120	6	aligns	align	VERB
fcis-13142	120	7	more	more	ADV
fcis-13142	120	8	closely	closely	ADV
fcis-13142	120	9	with	with	ADP
fcis-13142	120	10	human	human	ADJ
fcis-13142	120	11	perceptual	perceptual	ADJ
fcis-13142	120	12	standards	standard	NOUN
fcis-13142	120	13	.	.	PUNCT
fcis-13142	121	1	srgan	srgan	NOUN
fcis-13142	121	2	-	-	PUNCT
fcis-13142	121	3	set14	set14	NOUN
fcis-13142	121	4	-	-	PUNCT
fcis-13142	121	5	005	005	NUM
fcis-13142	121	6	new	new	ADJ
fcis-13142	121	7	model	model	NOUN
fcis-13142	121	8	-	-	PUNCT
fcis-13142	121	9	set14	set14	NOUN
fcis-13142	121	10	-	-	PUNCT
fcis-13142	121	11	005	005	NUM
fcis-13142	121	12	srgan	srgan	NOUN
fcis-13142	121	13	-	-	PUNCT
fcis-13142	121	14	bsd100	bsd100	PROPN
fcis-13142	121	15	-	-	PUNCT
fcis-13142	121	16	023	023	NUM
fcis-13142	121	17	new	new	ADJ
fcis-13142	121	18	model	model	NOUN
fcis-13142	121	19	-	-	PUNCT
fcis-13142	121	20	bsd100	bsd100	PROPN
fcis-13142	121	21	-	-	PUNCT
fcis-13142	121	22	023	023	NUM
fcis-13142	121	23	srgan	srgan	VERB
fcis-13142	121	24	new	new	ADJ
fcis-13142	121	25	model	model	NOUN
fcis-13142	121	26	figure	figure	NOUN
fcis-13142	121	27	4	4	NUM
fcis-13142	121	28	.	.	PUNCT
fcis-13142	122	1	the	the	DET
fcis-13142	122	2	comparison	comparison	NOUN
fcis-13142	122	3	between	between	ADP
fcis-13142	122	4	the	the	DET
fcis-13142	122	5	new	new	ADJ
fcis-13142	122	6	model	model	NOUN
fcis-13142	122	7	and	and	CCONJ
fcis-13142	122	8	srgan	srgan	NOUN
fcis-13142	122	9	,	,	PUNCT
fcis-13142	122	10	with	with	ADP
fcis-13142	122	11	srgan	srgan	NOUN
fcis-13142	122	12	-	-	PUNCT
fcis-13142	122	13	restored	restore	VERB
fcis-13142	122	14	images	image	NOUN
fcis-13142	122	15	on	on	ADP
fcis-13142	122	16	the	the	DET
fcis-13142	122	17	left	left	NOUN
fcis-13142	122	18	and	and	CCONJ
fcis-13142	122	19	images	image	NOUN
fcis-13142	122	20	restored	restore	VERB
fcis-13142	122	21	by	by	ADP
fcis-13142	122	22	the	the	DET
fcis-13142	122	23	new	new	ADJ
fcis-13142	122	24	model	model	NOUN
fcis-13142	122	25	on	on	ADP
fcis-13142	122	26	the	the	DET
fcis-13142	122	27	right	right	NOUN
fcis-13142	122	28	from	from	ADP
fcis-13142	122	29	the	the	DET
fcis-13142	122	30	above	above	ADJ
fcis-13142	122	31	images	image	NOUN
fcis-13142	122	32	,	,	PUNCT
fcis-13142	122	33	it	it	PRON
fcis-13142	122	34	can	can	AUX
fcis-13142	122	35	be	be	AUX
fcis-13142	122	36	observed	observe	VERB
fcis-13142	122	37	that	that	SCONJ
fcis-13142	122	38	,	,	PUNCT
fcis-13142	122	39	compared	compare	VERB
fcis-13142	122	40	to	to	PART
fcis-13142	122	41	srgan	srgan	VERB
fcis-13142	122	42	,	,	PUNCT
fcis-13142	122	43	even	even	ADV
fcis-13142	122	44	though	though	SCONJ
fcis-13142	122	45	the	the	DET
fcis-13142	122	46	new	new	ADJ
fcis-13142	122	47	model	model	NOUN
fcis-13142	122	48	has	have	VERB
fcis-13142	122	49	a	a	DET
fcis-13142	122	50	lower	low	ADJ
fcis-13142	122	51	psnr	psnr	NOUN
fcis-13142	122	52	value	value	NOUN
fcis-13142	122	53	than	than	ADP
fcis-13142	122	54	srgan	srgan	NOUN
fcis-13142	122	55	,	,	PUNCT
fcis-13142	122	56	it	it	PRON
fcis-13142	122	57	exhibits	exhibit	VERB
fcis-13142	122	58	improvements	improvement	NOUN
fcis-13142	122	59	in	in	ADP
fcis-13142	122	60	both	both	PRON
fcis-13142	122	61	artifact	artifact	ADJ
fcis-13142	122	62	removal	removal	NOUN
fcis-13142	122	63	and	and	CCONJ
fcis-13142	122	64	facial	facial	ADJ
fcis-13142	122	65	image	image	NOUN
fcis-13142	122	66	quality	quality	NOUN
fcis-13142	122	67	.	.	PUNCT
fcis-13142	123	1	the	the	DET
fcis-13142	123	2	new	new	ADJ
fcis-13142	123	3	model	model	NOUN
fcis-13142	123	4	does	do	AUX
fcis-13142	123	5	n't	not	PART
fcis-13142	123	6	introduce	introduce	VERB
fcis-13142	123	7	unnecessary	unnecessary	ADJ
fcis-13142	123	8	textures	texture	NOUN
fcis-13142	123	9	,	,	PUNCT
fcis-13142	123	10	such	such	ADJ
fcis-13142	123	11	as	as	ADP
fcis-13142	123	12	wrinkles	wrinkle	NOUN
fcis-13142	123	13	on	on	ADP
fcis-13142	123	14	the	the	DET
fcis-13142	123	15	face	face	NOUN
fcis-13142	123	16	.	.	PUNCT
fcis-13142	124	1	5	5	X
fcis-13142	124	2	.	.	X
fcis-13142	124	3	conclusion	conclusion	NOUN
fcis-13142	124	4	comparison	comparison	NOUN
fcis-13142	124	5	between	between	ADP
fcis-13142	124	6	the	the	DET
fcis-13142	124	7	new	new	ADJ
fcis-13142	124	8	model	model	NOUN
fcis-13142	124	9	and	and	CCONJ
fcis-13142	124	10	srgan	srgan	NOUN
fcis-13142	124	11	,	,	PUNCT
fcis-13142	124	12	with	with	ADP
fcis-13142	124	13	srgan	srgan	NOUN
fcis-13142	124	14	-	-	PUNCT
fcis-13142	124	15	restored	restore	VERB
fcis-13142	124	16	images	image	NOUN
fcis-13142	124	17	on	on	ADP
fcis-13142	124	18	the	the	DET
fcis-13142	124	19	left	left	ADJ
fcis-13142	124	20	and	and	CCONJ
fcis-13142	124	21	new	new	ADJ
fcis-13142	124	22	model	model	NOUN
fcis-13142	124	23	-	-	PUNCT
fcis-13142	124	24	restored	restore	VERB
fcis-13142	124	25	images	image	NOUN
fcis-13142	124	26	on	on	ADP
fcis-13142	124	27	the	the	DET
fcis-13142	124	28	right	right	NOUN
fcis-13142	124	29	.	.	PUNCT
fcis-13142	125	1	in	in	ADP
fcis-13142	125	2	summary	summary	NOUN
fcis-13142	125	3	,	,	PUNCT
fcis-13142	125	4	the	the	DET
fcis-13142	125	5	new	new	ADJ
fcis-13142	125	6	model	model	NOUN
fcis-13142	125	7	has	have	AUX
fcis-13142	125	8	made	make	VERB
fcis-13142	125	9	changes	change	NOUN
fcis-13142	125	10	in	in	ADP
fcis-13142	125	11	the	the	DET
fcis-13142	125	12	design	design	NOUN
fcis-13142	125	13	of	of	ADP
fcis-13142	125	14	the	the	DET
fcis-13142	125	15	residual	residual	ADJ
fcis-13142	125	16	blocks	block	NOUN
fcis-13142	125	17	and	and	CCONJ
fcis-13142	125	18	loss	loss	NOUN
fcis-13142	125	19	functions	function	NOUN
fcis-13142	125	20	,	,	PUNCT
fcis-13142	125	21	and	and	CCONJ
fcis-13142	125	22	has	have	AUX
fcis-13142	125	23	additionally	additionally	ADV
fcis-13142	125	24	introduced	introduce	VERB
fcis-13142	125	25	an	an	DET
fcis-13142	125	26	attention	attention	NOUN
fcis-13142	125	27	mechanism	mechanism	NOUN
fcis-13142	125	28	,	,	PUNCT
fcis-13142	125	29	achieving	achieve	VERB
fcis-13142	125	30	certain	certain	ADJ
fcis-13142	125	31	improvements	improvement	NOUN
fcis-13142	125	32	in	in	ADP
fcis-13142	125	33	the	the	DET
fcis-13142	125	34	quality	quality	NOUN
fcis-13142	125	35	of	of	ADP
fcis-13142	125	36	face	face	NOUN
fcis-13142	125	37	restoration	restoration	NOUN
fcis-13142	125	38	and	and	CCONJ
fcis-13142	125	39	artifact	artifact	NOUN
fcis-13142	125	40	removal	removal	NOUN
fcis-13142	125	41	.	.	PUNCT
fcis-13142	126	1	firstly	firstly	ADV
fcis-13142	126	2	,	,	PUNCT
fcis-13142	126	3	by	by	ADP
fcis-13142	126	4	altering	alter	VERB
fcis-13142	126	5	the	the	DET
fcis-13142	126	6	design	design	NOUN
fcis-13142	126	7	of	of	ADP
fcis-13142	126	8	the	the	DET
fcis-13142	126	9	residual	residual	ADJ
fcis-13142	126	10	blocks	block	NOUN
fcis-13142	126	11	,	,	PUNCT
fcis-13142	126	12	the	the	DET
fcis-13142	126	13	new	new	ADJ
fcis-13142	126	14	model	model	NOUN
fcis-13142	126	15	may	may	AUX
fcis-13142	126	16	enhance	enhance	VERB
fcis-13142	126	17	the	the	DET
fcis-13142	126	18	model	model	NOUN
fcis-13142	126	19	's	's	PART
fcis-13142	126	20	feature	feature	NOUN
fcis-13142	126	21	extraction	extraction	NOUN
fcis-13142	126	22	capability	capability	NOUN
fcis-13142	126	23	and	and	CCONJ
fcis-13142	126	24	information	information	NOUN
fcis-13142	126	25	propagation	propagation	NOUN
fcis-13142	126	26	efficiency	efficiency	NOUN
fcis-13142	126	27	.	.	PUNCT
fcis-13142	127	1	these	these	DET
fcis-13142	127	2	changes	change	NOUN
fcis-13142	127	3	likely	likely	ADV
fcis-13142	127	4	contribute	contribute	VERB
fcis-13142	127	5	to	to	ADP
fcis-13142	127	6	capturing	capture	VERB
fcis-13142	127	7	richer	rich	ADJ
fcis-13142	127	8	image	image	NOUN
fcis-13142	127	9	features	feature	NOUN
fcis-13142	127	10	,	,	PUNCT
fcis-13142	127	11	especially	especially	ADV
fcis-13142	127	12	in	in	ADP
fcis-13142	127	13	the	the	DET
fcis-13142	127	14	context	context	NOUN
fcis-13142	127	15	of	of	ADP
fcis-13142	127	16	face	face	NOUN
fcis-13142	127	17	images	image	NOUN
fcis-13142	127	18	,	,	PUNCT
fcis-13142	127	19	potentially	potentially	ADV
fcis-13142	127	20	resulting	result	VERB
fcis-13142	127	21	in	in	ADP
fcis-13142	127	22	better	well	ADJ
fcis-13142	127	23	image	image	NOUN
fcis-13142	127	24	quality	quality	NOUN
fcis-13142	127	25	and	and	CCONJ
fcis-13142	127	26	higher	high	ADJ
fcis-13142	127	27	perceptual	perceptual	ADJ
fcis-13142	127	28	quality	quality	NOUN
fcis-13142	127	29	.	.	PUNCT
fcis-13142	128	1	due	due	ADP
fcis-13142	128	2	to	to	ADP
fcis-13142	128	3	the	the	DET
fcis-13142	128	4	increased	increase	VERB
fcis-13142	128	5	complexity	complexity	NOUN
fcis-13142	128	6	of	of	ADP
fcis-13142	128	7	the	the	DET
fcis-13142	128	8	residual	residual	ADJ
fcis-13142	128	9	blocks	block	NOUN
fcis-13142	128	10	,	,	PUNCT
fcis-13142	128	11	this	this	DET
fcis-13142	128	12	study	study	NOUN
fcis-13142	128	13	decided	decide	VERB
fcis-13142	128	14	to	to	PART
fcis-13142	128	15	simplify	simplify	VERB
fcis-13142	128	16	the	the	DET
fcis-13142	128	17	design	design	NOUN
fcis-13142	128	18	of	of	ADP
fcis-13142	128	19	the	the	DET
fcis-13142	128	20	loss	loss	NOUN
fcis-13142	128	21	functions	function	NOUN
fcis-13142	128	22	to	to	PART
fcis-13142	128	23	reduce	reduce	VERB
fcis-13142	128	24	model	model	NOUN
fcis-13142	128	25	complexity	complexity	NOUN
fcis-13142	128	26	.	.	PUNCT
fcis-13142	129	1	this	this	DET
fcis-13142	129	2	decision	decision	NOUN
fcis-13142	129	3	helps	help	VERB
fcis-13142	129	4	balance	balance	VERB
fcis-13142	129	5	model	model	NOUN
fcis-13142	129	6	performance	performance	NOUN
fcis-13142	129	7	and	and	CCONJ
fcis-13142	129	8	computational	computational	ADJ
fcis-13142	129	9	cost	cost	NOUN
fcis-13142	129	10	,	,	PUNCT
fcis-13142	129	11	ensuring	ensure	VERB
fcis-13142	129	12	efficiency	efficiency	NOUN
fcis-13142	129	13	during	during	ADP
fcis-13142	129	14	both	both	DET
fcis-13142	129	15	training	training	NOUN
fcis-13142	129	16	and	and	CCONJ
fcis-13142	129	17	inference	inference	NOUN
fcis-13142	129	18	.	.	PUNCT
fcis-13142	130	1	references	reference	NOUN
fcis-13142	130	2	[	[	X
fcis-13142	130	3	1	1	NUM
fcis-13142	130	4	]	]	X
fcis-13142	130	5	han	han	PROPN
fcis-13142	130	6	,	,	PUNCT
fcis-13142	130	7	w.	w.	PROPN
fcis-13142	130	8	,	,	PUNCT
fcis-13142	130	9	dong	dong	PROPN
fcis-13142	130	10	,	,	PUNCT
fcis-13142	130	11	x.	x.	PROPN
fcis-13142	130	12	,	,	PUNCT
fcis-13142	130	13	dong	dong	PROPN
fcis-13142	130	14	,	,	PUNCT
fcis-13142	130	15	w.	w.	NOUN
fcis-13142	130	16	(	(	PUNCT
fcis-13142	130	17	2021	2021	NUM
fcis-13142	130	18	)	)	PUNCT
fcis-13142	130	19	.	.	PUNCT
fcis-13142	131	1	application	application	NOUN
fcis-13142	131	2	research	research	NOUN
fcis-13142	131	3	of	of	ADP
fcis-13142	131	4	neural	neural	ADJ
fcis-13142	131	5	network	network	NOUN
fcis-13142	131	6	models	model	NOUN
fcis-13142	131	7	in	in	ADP
fcis-13142	131	8	the	the	DET
fcis-13142	131	9	field	field	NOUN
fcis-13142	131	10	of	of	ADP
fcis-13142	131	11	image	image	NOUN
fcis-13142	131	12	super	super	NOUN
fcis-13142	131	13	-	-	NOUN
fcis-13142	131	14	resolution	resolution	NOUN
fcis-13142	131	15	.	.	PUNCT
fcis-13142	132	1	journal	journal	PROPN
fcis-13142	132	2	of	of	ADP
fcis-13142	132	3	information	information	NOUN
fcis-13142	132	4	engineering	engineering	PROPN
fcis-13142	132	5	university	university	NOUN
fcis-13142	132	6	,	,	PUNCT
fcis-13142	132	7	22(02	22(02	NUM
fcis-13142	132	8	)	)	PUNCT
fcis-13142	132	9	,	,	PUNCT
fcis-13142	132	10	159163	159163	NUM
fcis-13142	132	11	.	.	PUNCT
fcis-13142	133	1	[	[	X
fcis-13142	133	2	2	2	NUM
fcis-13142	133	3	]	]	X
fcis-13142	133	4	zhang	zhang	PROPN
fcis-13142	133	5	,	,	PUNCT
fcis-13142	133	6	y.	y.	PROPN
fcis-13142	133	7	,	,	PUNCT
fcis-13142	133	8	li	li	PROPN
fcis-13142	133	9	,	,	PUNCT
fcis-13142	133	10	k.	k.	PROPN
fcis-13142	133	11	,	,	PUNCT
fcis-13142	133	12	li	li	PROPN
fcis-13142	133	13	,	,	PUNCT
fcis-13142	133	14	k.	k.	PROPN
fcis-13142	133	15	,	,	PUNCT
fcis-13142	133	16	et	et	PROPN
fcis-13142	133	17	al	al	PROPN
fcis-13142	133	18	.	.	PUNCT
fcis-13142	134	1	(	(	PUNCT
fcis-13142	134	2	2018	2018	NUM
fcis-13142	134	3	)	)	PUNCT
fcis-13142	134	4	.	.	PUNCT
fcis-13142	135	1	image	image	NOUN
fcis-13142	135	2	super	super	ADJ
fcis-13142	135	3	-	-	NOUN
fcis-13142	135	4	resolution	resolution	NOUN
fcis-13142	135	5	using	use	VERB
fcis-13142	135	6	very	very	ADV
fcis-13142	135	7	deep	deep	ADJ
fcis-13142	135	8	residual	residual	ADJ
fcis-13142	135	9	channel	channel	NOUN
fcis-13142	135	10	attention	attention	NOUN
fcis-13142	135	11	networks	network	NOUN
fcis-13142	135	12	.	.	PUNCT
fcis-13142	136	1	https://	https://	PROPN
fcis-13142	136	2	arxiv.org/abs/1807.02758	arxiv.org/abs/1807.02758	ADV
fcis-13142	136	3	.	.	PUNCT
fcis-13142	137	1	[	[	X
fcis-13142	137	2	3	3	NUM
fcis-13142	137	3	]	]	X
fcis-13142	137	4	dong	dong	PROPN
fcis-13142	137	5	,	,	PUNCT
fcis-13142	137	6	c.	c.	PROPN
fcis-13142	137	7	,	,	PUNCT
fcis-13142	137	8	loy	loy	PROPN
fcis-13142	137	9	,	,	PUNCT
fcis-13142	137	10	c.	c.	PROPN
fcis-13142	137	11	c.	c.	PROPN
fcis-13142	137	12	,	,	PUNCT
fcis-13142	137	13	he	he	PRON
fcis-13142	137	14	,	,	PUNCT
fcis-13142	137	15	k.	k.	PROPN
fcis-13142	137	16	,	,	PUNCT
fcis-13142	137	17	et	et	PROPN
fcis-13142	137	18	al	al	PROPN
fcis-13142	137	19	.	.	PUNCT
fcis-13142	138	1	(	(	PUNCT
fcis-13142	138	2	2015	2015	NUM
fcis-13142	138	3	)	)	PUNCT
fcis-13142	138	4	.	.	PUNCT
fcis-13142	139	1	image	image	NOUN
fcis-13142	139	2	superresolution	superresolution	NOUN
fcis-13142	139	3	using	use	VERB
fcis-13142	139	4	deep	deep	ADJ
fcis-13142	139	5	convolutional	convolutional	ADJ
fcis-13142	139	6	networks	network	NOUN
fcis-13142	139	7	.	.	PUNCT
fcis-13142	140	1	https://arxiv	https://arxiv	X
fcis-13142	140	2	.	.	PUNCT
fcis-13142	140	3	org/	org/	PROPN
fcis-13142	140	4	abs/1501.00092	abs/1501.00092	NOUN
fcis-13142	140	5	.	.	PUNCT
fcis-13142	141	1	[	[	X
fcis-13142	141	2	4	4	NUM
fcis-13142	141	3	]	]	X
fcis-13142	141	4	shi	shi	PROPN
fcis-13142	141	5	,	,	PUNCT
fcis-13142	141	6	w.	w.	PROPN
fcis-13142	141	7	,	,	PUNCT
fcis-13142	141	8	caballero	caballero	PROPN
fcis-13142	141	9	,	,	PUNCT
fcis-13142	141	10	j.	j.	PROPN
fcis-13142	141	11	,	,	PUNCT
fcis-13142	141	12	huszár	huszár	PROPN
fcis-13142	141	13	,	,	PUNCT
fcis-13142	141	14	f.	f.	PROPN
fcis-13142	141	15	,	,	PUNCT
fcis-13142	141	16	et	et	PROPN
fcis-13142	141	17	al	al	PROPN
fcis-13142	141	18	.	.	PUNCT
fcis-13142	141	19	(	(	PUNCT
fcis-13142	141	20	2016	2016	NUM
fcis-13142	141	21	)	)	PUNCT
fcis-13142	141	22	.	.	PUNCT
fcis-13142	142	1	real	real	ADJ
fcis-13142	142	2	-	-	PUNCT
fcis-13142	142	3	time	time	NOUN
fcis-13142	142	4	single	single	ADJ
fcis-13142	142	5	image	image	NOUN
fcis-13142	142	6	and	and	CCONJ
fcis-13142	142	7	video	video	NOUN
fcis-13142	142	8	super	super	NOUN
fcis-13142	142	9	-	-	NOUN
fcis-13142	142	10	resolution	resolution	NOUN
fcis-13142	142	11	using	use	VERB
fcis-13142	142	12	an	an	DET
fcis-13142	142	13	efficient	efficient	ADJ
fcis-13142	142	14	sub	sub	ADJ
fcis-13142	142	15	-	-	ADJ
fcis-13142	142	16	pixel	pixel	ADJ
fcis-13142	142	17	convolutional	convolutional	ADJ
fcis-13142	142	18	neural	neural	ADJ
fcis-13142	142	19	network	network	NOUN
fcis-13142	142	20	.	.	PUNCT
fcis-13142	143	1	https://arxiv	https://arxiv	X
fcis-13142	143	2	.	.	PUNCT
fcis-13142	143	3	org	org	PROPN
fcis-13142	143	4	/	/	SYM
fcis-13142	143	5	abs/	abs/	ADJ
fcis-13142	143	6	1609	1609	NUM
fcis-13142	143	7	.	.	PUNCT
fcis-13142	144	1	05158	05158	NUM
fcis-13142	144	2	.	.	PUNCT
fcis-13142	145	1	[	[	X
fcis-13142	145	2	5	5	NUM
fcis-13142	145	3	]	]	SYM
fcis-13142	145	4	ledig	ledig	NOUN
fcis-13142	145	5	,	,	PUNCT
fcis-13142	145	6	c.	c.	PROPN
fcis-13142	145	7	,	,	PUNCT
fcis-13142	145	8	theis	theis	PROPN
fcis-13142	145	9	,	,	PUNCT
fcis-13142	145	10	l.	l.	PROPN
fcis-13142	145	11	,	,	PUNCT
fcis-13142	145	12	huszar	huszar	PROPN
fcis-13142	145	13	,	,	PUNCT
fcis-13142	145	14	f.	f.	PROPN
fcis-13142	145	15	,	,	PUNCT
fcis-13142	145	16	et	et	PROPN
fcis-13142	145	17	al	al	PROPN
fcis-13142	145	18	.	.	PUNCT
fcis-13142	145	19	(	(	PUNCT
fcis-13142	145	20	2017	2017	NUM
fcis-13142	145	21	)	)	PUNCT
fcis-13142	145	22	.	.	PUNCT
fcis-13142	146	1	photo	photo	NOUN
fcis-13142	146	2	-	-	PUNCT
fcis-13142	146	3	realistic	realistic	ADJ
fcis-13142	146	4	single	single	ADJ
fcis-13142	146	5	image	image	NOUN
fcis-13142	146	6	super	super	NOUN
fcis-13142	146	7	-	-	NOUN
fcis-13142	146	8	resolution	resolution	NOUN
fcis-13142	146	9	using	use	VERB
fcis-13142	146	10	a	a	DET
fcis-13142	146	11	generative	generative	ADJ
fcis-13142	146	12	adversarial	adversarial	ADJ
fcis-13142	146	13	network	network	NOUN
fcis-13142	146	14	.	.	PUNCT
fcis-13142	147	1	https://arxiv.org/abs/1609.04802	https://arxiv.org/abs/1609.04802	NOUN
fcis-13142	147	2	.	.	PUNCT
fcis-13142	148	1	[	[	X
fcis-13142	148	2	6	6	NUM
fcis-13142	148	3	]	]	X
fcis-13142	148	4	wang	wang	PROPN
fcis-13142	148	5	,	,	PUNCT
fcis-13142	148	6	x.	x.	PROPN
fcis-13142	148	7	,	,	PUNCT
fcis-13142	148	8	yu	yu	PROPN
fcis-13142	148	9	,	,	PUNCT
fcis-13142	148	10	k.	k.	PROPN
fcis-13142	148	11	,	,	PUNCT
fcis-13142	148	12	wu	wu	PROPN
fcis-13142	148	13	,	,	PUNCT
fcis-13142	148	14	s.	s.	PROPN
fcis-13142	148	15	,	,	PUNCT
fcis-13142	148	16	et	et	PROPN
fcis-13142	148	17	al	al	PROPN
fcis-13142	148	18	.	.	PUNCT
fcis-13142	148	19	(	(	PUNCT
fcis-13142	148	20	2018	2018	NUM
fcis-13142	148	21	)	)	PUNCT
fcis-13142	148	22	.	.	PUNCT
fcis-13142	149	1	esrgan	esrgan	PROPN
fcis-13142	149	2	:	:	PUNCT
fcis-13142	149	3	enhanced	enhance	VERB
fcis-13142	149	4	super	super	ADJ
fcis-13142	149	5	-	-	ADJ
fcis-13142	149	6	resolution	resolution	ADJ
fcis-13142	149	7	generative	generative	ADJ
fcis-13142	149	8	adversarial	adversarial	ADJ
fcis-13142	149	9	networks	network	NOUN
fcis-13142	149	10	.	.	PUNCT
fcis-13142	150	1	https://arxiv	https://arxiv	X
fcis-13142	150	2	.	.	PUNCT
fcis-13142	150	3	org	org	ADJ
fcis-13142	150	4	/	/	SYM
fcis-13142	150	5	abs/	abs/	ADJ
fcis-13142	150	6	1809.00219	1809.00219	NOUN
fcis-13142	150	7	.	.	PUNCT
fcis-13142	151	1	[	[	X
fcis-13142	151	2	7	7	NUM
fcis-13142	151	3	]	]	X
fcis-13142	151	4	ioffe	ioffe	NOUN
fcis-13142	151	5	,	,	PUNCT
fcis-13142	151	6	s.	s.	PROPN
fcis-13142	151	7	,	,	PUNCT
fcis-13142	151	8	szegedy	szegedy	PROPN
fcis-13142	151	9	,	,	PUNCT
fcis-13142	151	10	c.	c.	NOUN
fcis-13142	151	11	(	(	PUNCT
fcis-13142	151	12	2015	2015	NUM
fcis-13142	151	13	)	)	PUNCT
fcis-13142	151	14	.	.	PUNCT
fcis-13142	152	1	batch	batch	NOUN
fcis-13142	152	2	normalization	normalization	NOUN
fcis-13142	152	3	:	:	PUNCT
fcis-13142	152	4	accelerating	accelerate	VERB
fcis-13142	152	5	deep	deep	ADJ
fcis-13142	152	6	network	network	NOUN
fcis-13142	152	7	training	training	NOUN
fcis-13142	152	8	by	by	ADP
fcis-13142	152	9	reducing	reduce	VERB
fcis-13142	152	10	internal	internal	ADJ
fcis-13142	152	11	covariate	covariate	ADJ
fcis-13142	152	12	shift	shift	NOUN
fcis-13142	152	13	.	.	PUNCT
fcis-13142	153	1	https://arxiv.org/abs/1502.03167	https://arxiv.org/abs/1502.03167	ADJ
fcis-13142	153	2	.	.	PUNCT
fcis-13142	154	1	[	[	X
fcis-13142	154	2	8	8	NUM
fcis-13142	154	3	]	]	SYM
fcis-13142	154	4	wu	wu	PROPN
fcis-13142	154	5	,	,	PUNCT
fcis-13142	154	6	y.	y.	PROPN
fcis-13142	154	7	,	,	PUNCT
fcis-13142	154	8	he	he	PRON
fcis-13142	154	9	,	,	PUNCT
fcis-13142	154	10	k.	k.	PROPN
fcis-13142	154	11	(	(	PUNCT
fcis-13142	154	12	2018	2018	NUM
fcis-13142	154	13	)	)	PUNCT
fcis-13142	154	14	.	.	PUNCT
fcis-13142	155	1	group	group	NOUN
fcis-13142	155	2	normalization	normalization	NOUN
fcis-13142	155	3	.	.	PUNCT
fcis-13142	156	1	https://arxiv	https://arxiv	X
fcis-13142	156	2	.	.	PUNCT
fcis-13142	156	3	org/	org/	PRON
fcis-13142	156	4	abs/	abs/	ADJ
fcis-13142	156	5	1803.08494	1803.08494	NUM
fcis-13142	156	6	.	.	PUNCT
fcis-13142	157	1	[	[	X
fcis-13142	157	2	9	9	NUM
fcis-13142	157	3	]	]	PUNCT
fcis-13142	157	4	timofte	timofte	NOUN
fcis-13142	157	5	,	,	PUNCT
fcis-13142	157	6	r.	r.	PROPN
fcis-13142	157	7	,	,	PUNCT
fcis-13142	157	8	agustsson	agustsson	NOUN
fcis-13142	157	9	,	,	PUNCT
fcis-13142	157	10	e.	e.	PROPN
fcis-13142	157	11	,	,	PUNCT
fcis-13142	157	12	gool	gool	PROPN
fcis-13142	157	13	,	,	PUNCT
fcis-13142	157	14	l.v	l.v	PROPN
fcis-13142	157	15	.	.	PROPN
fcis-13142	157	16	,	,	PUNCT
fcis-13142	157	17	et	et	PROPN
fcis-13142	157	18	al	al	PROPN
fcis-13142	157	19	..	..	PUNCT
fcis-13142	157	20	(	(	PUNCT
fcis-13142	157	21	2017	2017	NUM
fcis-13142	157	22	)	)	PUNCT
fcis-13142	157	23	.	.	PUNCT
fcis-13142	157	24	ntire	ntire	NOUN
fcis-13142	157	25	2017	2017	NUM
fcis-13142	157	26	challenge	challenge	NOUN
fcis-13142	157	27	on	on	ADP
fcis-13142	157	28	single	single	ADJ
fcis-13142	157	29	image	image	NOUN
fcis-13142	157	30	super	super	NOUN
fcis-13142	157	31	-	-	NOUN
fcis-13142	157	32	resolution	resolution	NOUN
fcis-13142	157	33	:	:	PUNCT
fcis-13142	157	34	methods	method	NOUN
fcis-13142	157	35	and	and	CCONJ
fcis-13142	157	36	results	result	NOUN
fcis-13142	157	37	.	.	PUNCT
fcis-13142	158	1	2017	2017	NUM
fcis-13142	158	2	ieee	ieee	NOUN
fcis-13142	158	3	conference	conference	NOUN
fcis-13142	158	4	on	on	ADP
fcis-13142	158	5	computer	computer	NOUN
fcis-13142	158	6	vision	vision	NOUN
fcis-13142	158	7	and	and	CCONJ
fcis-13142	158	8	pattern	pattern	NOUN
fcis-13142	158	9	recognition	recognition	NOUN
fcis-13142	158	10	workshops	workshop	NOUN
fcis-13142	158	11	(	(	PUNCT
fcis-13142	158	12	cvprw	cvprw	PROPN
fcis-13142	158	13	)	)	PUNCT
fcis-13142	158	14	,	,	PUNCT
fcis-13142	158	15	1110	1110	NUM
fcis-13142	158	16	-	-	SYM
fcis-13142	158	17	1121	1121	NUM
fcis-13142	158	18	.	.	PUNCT
fcis-13142	159	1	[	[	X
fcis-13142	159	2	10	10	NUM
fcis-13142	159	3	]	]	X
fcis-13142	159	4	d.	d.	PROPN
fcis-13142	159	5	martin	martin	PROPN
fcis-13142	159	6	,	,	PUNCT
fcis-13142	159	7	c.	c.	PROPN
fcis-13142	159	8	fowlkes	fowlkes	PROPN
fcis-13142	159	9	,	,	PUNCT
fcis-13142	159	10	d.	d.	PROPN
fcis-13142	159	11	tal	tal	PROPN
fcis-13142	159	12	,	,	PUNCT
fcis-13142	159	13	et	et	PROPN
fcis-13142	159	14	al	al	PROPN
fcis-13142	159	15	..	..	PUNCT
fcis-13142	159	16	(	(	PUNCT
fcis-13142	159	17	2002	2002	NUM
fcis-13142	159	18	)	)	PUNCT
fcis-13142	159	19	.	.	PUNCT
fcis-13142	160	1	a	a	DET
fcis-13142	160	2	database	database	NOUN
fcis-13142	160	3	of	of	ADP
fcis-13142	160	4	human	human	ADJ
fcis-13142	160	5	segmented	segment	VERB
fcis-13142	160	6	natural	natural	ADJ
fcis-13142	160	7	images	image	NOUN
fcis-13142	160	8	and	and	CCONJ
fcis-13142	160	9	its	its	PRON
fcis-13142	160	10	application	application	NOUN
fcis-13142	160	11	to	to	ADP
fcis-13142	160	12	evaluating	evaluate	VERB
fcis-13142	160	13	segmentation	segmentation	NOUN
fcis-13142	160	14	algorithms	algorithm	NOUN
fcis-13142	160	15	and	and	CCONJ
fcis-13142	160	16	measuring	measure	VERB
fcis-13142	160	17	ecological	ecological	ADJ
fcis-13142	160	18	statistics	statistic	NOUN
fcis-13142	160	19	.	.	PUNCT
fcis-13142	161	1	proceedings	proceeding	NOUN
fcis-13142	161	2	eighth	eighth	ADJ
fcis-13142	161	3	ieee	ieee	PROPN
fcis-13142	161	4	international	international	ADJ
fcis-13142	161	5	conference	conference	NOUN
fcis-13142	161	6	on	on	ADP
fcis-13142	161	7	computer	computer	NOUN
fcis-13142	161	8	vision	vision	NOUN
fcis-13142	161	9	(	(	PUNCT
fcis-13142	161	10	iccv	iccv	NOUN
fcis-13142	161	11	2001	2001	NUM
fcis-13142	161	12	)	)	PUNCT
fcis-13142	161	13	,	,	PUNCT
fcis-13142	161	14	vancouver	vancouver	PROPN
fcis-13142	161	15	,	,	PUNCT
fcis-13142	161	16	canada	canada	PROPN
fcis-13142	161	17	,	,	PUNCT
fcis-13142	161	18	pp	pp	PROPN
fcis-13142	161	19	.	.	PUNCT
fcis-13142	162	1	416	416	NUM
fcis-13142	162	2	-	-	SYM
fcis-13142	162	3	423	423	NUM
fcis-13142	162	4	.	.	PUNCT