id	sid	tid	token	lemma	pos
fcis-1074	1	1	frontiers	frontier	NOUN
fcis-1074	1	2	in	in	ADP
fcis-1074	1	3	computing	computing	NOUN
fcis-1074	1	4	and	and	CCONJ
fcis-1074	1	5	intelligent	intelligent	ADJ
fcis-1074	1	6	systems	system	NOUN
fcis-1074	1	7	issn	issn	VERB
fcis-1074	1	8	:	:	PUNCT
fcis-1074	1	9	2832	2832	NUM
fcis-1074	1	10	-	-	SYM
fcis-1074	1	11	6024	6024	NUM
fcis-1074	1	12	|	|	NOUN
fcis-1074	1	13	vol	vol	NOUN
fcis-1074	1	14	.	.	PROPN
fcis-1074	2	1	1	1	NUM
fcis-1074	2	2	,	,	PUNCT
fcis-1074	2	3	no	no	INTJ
fcis-1074	2	4	.	.	NOUN
fcis-1074	2	5	1	1	NUM
fcis-1074	2	6	,	,	PUNCT
fcis-1074	2	7	2022	2022	NUM
fcis-1074	2	8	4	4	NUM
fcis-1074	2	9	image	image	NOUN
fcis-1074	2	10	defogging	defogge	VERB
fcis-1074	2	11	algorithm	algorithm	NOUN
fcis-1074	2	12	based	base	VERB
fcis-1074	2	13	on	on	ADP
fcis-1074	2	14	deblurgan	deblurgan	PROPN
fcis-1074	2	15	network	network	PROPN
fcis-1074	2	16	yuanyuan	yuanyuan	PROPN
fcis-1074	2	17	cheng	cheng	PROPN
fcis-1074	2	18	*	*	PROPN
fcis-1074	2	19	,	,	PUNCT
fcis-1074	2	20	xiaorong	xiaorong	PROPN
fcis-1074	2	21	cheng	cheng	PROPN
fcis-1074	2	22	north	north	PROPN
fcis-1074	2	23	china	china	PROPN
fcis-1074	2	24	electric	electric	PROPN
fcis-1074	2	25	power	power	PROPN
fcis-1074	2	26	university	university	PROPN
fcis-1074	2	27	(	(	PUNCT
fcis-1074	2	28	baoding	baoding	PROPN
fcis-1074	2	29	)	)	PUNCT
fcis-1074	2	30	,	,	PUNCT
fcis-1074	2	31	hebei,071003	hebei,071003	NOUN
fcis-1074	2	32	,	,	PUNCT
fcis-1074	2	33	china	china	PROPN
fcis-1074	2	34	*	*	PUNCT
fcis-1074	2	35	corresponding	correspond	VERB
fcis-1074	2	36	author	author	NOUN
fcis-1074	2	37	:	:	PUNCT
fcis-1074	2	38	yuanyuan	yuanyuan	PROPN
fcis-1074	2	39	cheng	cheng	PROPN
fcis-1074	2	40	(	(	PUNCT
fcis-1074	2	41	email	email	NOUN
fcis-1074	2	42	:	:	PUNCT
fcis-1074	2	43	fighting_cheng@163.com	fighting_cheng@163.com	X
fcis-1074	2	44	)	)	PUNCT
fcis-1074	2	45	abstract	abstract	NOUN
fcis-1074	2	46	:	:	PUNCT
fcis-1074	2	47	the	the	DET
fcis-1074	2	48	reduced	reduce	VERB
fcis-1074	2	49	visibility	visibility	NOUN
fcis-1074	2	50	in	in	ADP
fcis-1074	2	51	foggy	foggy	ADJ
fcis-1074	2	52	days	day	NOUN
fcis-1074	2	53	impairs	impair	VERB
fcis-1074	2	54	the	the	DET
fcis-1074	2	55	quality	quality	NOUN
fcis-1074	2	56	of	of	ADP
fcis-1074	2	57	captured	capture	VERB
fcis-1074	2	58	images	image	NOUN
fcis-1074	2	59	and	and	CCONJ
fcis-1074	2	60	videos	video	NOUN
fcis-1074	2	61	to	to	ADP
fcis-1074	2	62	varying	vary	VERB
fcis-1074	2	63	degrees	degree	NOUN
fcis-1074	2	64	,	,	PUNCT
fcis-1074	2	65	leading	lead	VERB
fcis-1074	2	66	to	to	ADP
fcis-1074	2	67	limited	limit	VERB
fcis-1074	2	68	applications	application	NOUN
fcis-1074	2	69	of	of	ADP
fcis-1074	2	70	these	these	DET
fcis-1074	2	71	images	image	NOUN
fcis-1074	2	72	in	in	ADP
fcis-1074	2	73	the	the	DET
fcis-1074	2	74	field	field	NOUN
fcis-1074	2	75	of	of	ADP
fcis-1074	2	76	computer	computer	NOUN
fcis-1074	2	77	vision	vision	NOUN
fcis-1074	2	78	.	.	PUNCT
fcis-1074	3	1	to	to	PART
fcis-1074	3	2	solve	solve	VERB
fcis-1074	3	3	this	this	DET
fcis-1074	3	4	problem	problem	NOUN
fcis-1074	3	5	,	,	PUNCT
fcis-1074	3	6	direct	direct	ADJ
fcis-1074	3	7	recovery	recovery	NOUN
fcis-1074	3	8	of	of	ADP
fcis-1074	3	9	fog	fog	NOUN
fcis-1074	3	10	-	-	PUNCT
fcis-1074	3	11	free	free	ADJ
fcis-1074	3	12	images	image	NOUN
fcis-1074	3	13	based	base	VERB
fcis-1074	3	14	on	on	ADP
fcis-1074	3	15	an	an	DET
fcis-1074	3	16	improved	improved	ADJ
fcis-1074	3	17	deblurgan	deblurgan	NOUN
fcis-1074	3	18	network	network	NOUN
fcis-1074	3	19	is	be	AUX
fcis-1074	3	20	proposed	propose	VERB
fcis-1074	3	21	.	.	PUNCT
fcis-1074	4	1	we	we	PRON
fcis-1074	4	2	add	add	VERB
fcis-1074	4	3	the	the	DET
fcis-1074	4	4	expanded	expand	VERB
fcis-1074	4	5	convolution	convolution	NOUN
fcis-1074	4	6	(	(	PUNCT
fcis-1074	4	7	dialted	dialted	ADJ
fcis-1074	4	8	conv	conv	ADJ
fcis-1074	4	9	)	)	PUNCT
fcis-1074	4	10	module	module	NOUN
fcis-1074	4	11	in	in	ADP
fcis-1074	4	12	the	the	DET
fcis-1074	4	13	generator	generator	NOUN
fcis-1074	4	14	to	to	PART
fcis-1074	4	15	expand	expand	VERB
fcis-1074	4	16	the	the	DET
fcis-1074	4	17	perceptual	perceptual	ADJ
fcis-1074	4	18	field	field	NOUN
fcis-1074	4	19	to	to	PART
fcis-1074	4	20	extract	extract	VERB
fcis-1074	4	21	richer	rich	ADJ
fcis-1074	4	22	semantic	semantic	ADJ
fcis-1074	4	23	information	information	NOUN
fcis-1074	4	24	,	,	PUNCT
fcis-1074	4	25	and	and	CCONJ
fcis-1074	4	26	add	add	VERB
fcis-1074	4	27	the	the	DET
fcis-1074	4	28	spatial	spatial	ADJ
fcis-1074	4	29	attention	attention	NOUN
fcis-1074	4	30	mechanism	mechanism	NOUN
fcis-1074	4	31	module	module	NOUN
fcis-1074	4	32	at	at	ADP
fcis-1074	4	33	specified	specify	VERB
fcis-1074	4	34	locations	location	NOUN
fcis-1074	4	35	to	to	PART
fcis-1074	4	36	facilitate	facilitate	VERB
fcis-1074	4	37	the	the	DET
fcis-1074	4	38	elimination	elimination	NOUN
fcis-1074	4	39	of	of	ADP
fcis-1074	4	40	residual	residual	ADJ
fcis-1074	4	41	fog	fog	PROPN
fcis-1074	4	42	;	;	PUNCT
fcis-1074	4	43	the	the	DET
fcis-1074	4	44	discriminator	discriminator	NOUN
fcis-1074	4	45	uses	use	VERB
fcis-1074	4	46	the	the	DET
fcis-1074	4	47	traditional	traditional	ADJ
fcis-1074	4	48	patchgan	patchgan	NOUN
fcis-1074	4	49	for	for	ADP
fcis-1074	4	50	chunk	chunk	ADJ
fcis-1074	4	51	determination	determination	NOUN
fcis-1074	4	52	to	to	PART
fcis-1074	4	53	improve	improve	VERB
fcis-1074	4	54	the	the	DET
fcis-1074	4	55	discriminative	discriminative	NOUN
fcis-1074	4	56	accuracy	accuracy	NOUN
fcis-1074	4	57	;	;	PUNCT
fcis-1074	4	58	the	the	DET
fcis-1074	4	59	loss	loss	NOUN
fcis-1074	4	60	function	function	NOUN
fcis-1074	4	61	adds	add	VERB
fcis-1074	4	62	bce	bce	PROPN
fcis-1074	4	63	loss	loss	NOUN
fcis-1074	4	64	to	to	PART
fcis-1074	4	65	improve	improve	VERB
fcis-1074	4	66	the	the	DET
fcis-1074	4	67	discriminative	discriminative	NOUN
fcis-1074	4	68	accuracy	accuracy	NOUN
fcis-1074	4	69	of	of	ADP
fcis-1074	4	70	the	the	DET
fcis-1074	4	71	discriminator	discriminator	NOUN
fcis-1074	4	72	and	and	CCONJ
fcis-1074	4	73	the	the	DET
fcis-1074	4	74	pixel	pixel	ADJ
fcis-1074	4	75	-	-	PUNCT
fcis-1074	4	76	level	level	NOUN
fcis-1074	4	77	detail	detail	NOUN
fcis-1074	4	78	retention	retention	NOUN
fcis-1074	4	79	of	of	ADP
fcis-1074	4	80	the	the	DET
fcis-1074	4	81	generator	generator	NOUN
fcis-1074	4	82	.	.	PUNCT
fcis-1074	5	1	in	in	ADP
fcis-1074	5	2	the	the	DET
fcis-1074	5	3	synthetic	synthetic	ADJ
fcis-1074	5	4	fogged	fogged	ADJ
fcis-1074	5	5	dataset	dataset	NOUN
fcis-1074	5	6	reside	reside	NOUN
fcis-1074	5	7	,	,	PUNCT
fcis-1074	5	8	the	the	DET
fcis-1074	5	9	subjective	subjective	ADJ
fcis-1074	5	10	visual	visual	ADJ
fcis-1074	5	11	comparison	comparison	NOUN
fcis-1074	5	12	with	with	ADP
fcis-1074	5	13	dark	dark	ADJ
fcis-1074	5	14	channel	channel	NOUN
fcis-1074	5	15	,	,	PUNCT
fcis-1074	5	16	dehazenet	dehazenet	PROPN
fcis-1074	5	17	,	,	PUNCT
fcis-1074	5	18	aod	aod	PROPN
fcis-1074	5	19	-	-	NOUN
fcis-1074	5	20	net	net	NOUN
fcis-1074	5	21	,	,	PUNCT
fcis-1074	5	22	and	and	CCONJ
fcis-1074	5	23	defogging	defogge	VERB
fcis-1074	5	24	effect	effect	NOUN
fcis-1074	5	25	shows	show	VERB
fcis-1074	5	26	that	that	SCONJ
fcis-1074	5	27	the	the	DET
fcis-1074	5	28	defogging	defogge	VERB
fcis-1074	5	29	effect	effect	NOUN
fcis-1074	5	30	of	of	ADP
fcis-1074	5	31	this	this	DET
fcis-1074	5	32	network	network	NOUN
fcis-1074	5	33	model	model	NOUN
fcis-1074	5	34	and	and	CCONJ
fcis-1074	5	35	the	the	DET
fcis-1074	5	36	detail	detail	NOUN
fcis-1074	5	37	information	information	NOUN
fcis-1074	5	38	and	and	CCONJ
fcis-1074	5	39	color	color	NOUN
fcis-1074	5	40	contrast	contrast	NOUN
fcis-1074	5	41	of	of	ADP
fcis-1074	5	42	defogged	defogged	ADJ
fcis-1074	5	43	images	image	NOUN
fcis-1074	5	44	are	be	AUX
fcis-1074	5	45	improved	improve	VERB
fcis-1074	5	46	;	;	PUNCT
fcis-1074	5	47	meanwhile	meanwhile	ADV
fcis-1074	5	48	,	,	PUNCT
fcis-1074	5	49	the	the	DET
fcis-1074	5	50	objective	objective	ADJ
fcis-1074	5	51	evaluation	evaluation	NOUN
fcis-1074	5	52	indexes	index	NOUN
fcis-1074	5	53	peak	peak	NOUN
fcis-1074	5	54	signalto	signalto	PROPN
fcis-1074	5	55	nise	nise	PROPN
fcis-1074	5	56	rtioo	rtioo	VERB
fcis-1074	5	57	a	a	PRON
fcis-1074	5	58	,	,	PUNCT
fcis-1074	5	59	psnr	psnr	NOUN
fcis-1074	5	60	and	and	CCONJ
fcis-1074	5	61	structure	structure	NOUN
fcis-1074	5	62	smilaritiy	smilaritiy	NOUN
fcis-1074	5	63	(	(	PUNCT
fcis-1074	5	64	ssim	ssim	NOUN
fcis-1074	5	65	)	)	PUNCT
fcis-1074	5	66	were	be	AUX
fcis-1074	5	67	also	also	ADV
fcis-1074	5	68	improved	improve	VERB
fcis-1074	5	69	respectively	respectively	ADV
fcis-1074	5	70	.	.	PUNCT
fcis-1074	6	1	keywords	keyword	NOUN
fcis-1074	6	2	:	:	PUNCT
fcis-1074	6	3	single	single	ADJ
fcis-1074	6	4	image	image	NOUN
fcis-1074	6	5	defogging	defogging	NOUN
fcis-1074	6	6	;	;	PUNCT
fcis-1074	6	7	deblurgan	deblurgan	NOUN
fcis-1074	6	8	;	;	PUNCT
fcis-1074	6	9	dilation	dilation	NOUN
fcis-1074	6	10	convolution	convolution	NOUN
fcis-1074	6	11	;	;	PUNCT
fcis-1074	6	12	spatial	spatial	ADJ
fcis-1074	6	13	attention	attention	NOUN
fcis-1074	6	14	mechanism	mechanism	NOUN
fcis-1074	6	15	;	;	PUNCT
fcis-1074	6	16	bce	bce	PROPN
fcis-1074	6	17	loss	loss	NOUN
fcis-1074	6	18	.	.	PUNCT
fcis-1074	7	1	1	1	X
fcis-1074	7	2	.	.	X
fcis-1074	7	3	introduction	introduction	NOUN
fcis-1074	7	4	the	the	DET
fcis-1074	7	5	role	role	NOUN
fcis-1074	7	6	of	of	ADP
fcis-1074	7	7	image	image	NOUN
fcis-1074	7	8	defogging	defogge	VERB
fcis-1074	7	9	algorithms	algorithm	NOUN
fcis-1074	7	10	in	in	ADP
fcis-1074	7	11	computer	computer	NOUN
fcis-1074	7	12	vision	vision	NOUN
fcis-1074	7	13	applications	application	NOUN
fcis-1074	7	14	such	such	ADJ
fcis-1074	7	15	as	as	ADP
fcis-1074	7	16	target	target	NOUN
fcis-1074	7	17	detection	detection	NOUN
fcis-1074	7	18	and	and	CCONJ
fcis-1074	7	19	traffic	traffic	NOUN
fcis-1074	7	20	control	control	NOUN
fcis-1074	7	21	is	be	AUX
fcis-1074	7	22	becoming	become	VERB
fcis-1074	7	23	more	more	ADV
fcis-1074	7	24	and	and	CCONJ
fcis-1074	7	25	more	more	ADV
fcis-1074	7	26	important	important	ADJ
fcis-1074	7	27	.	.	PUNCT
fcis-1074	8	1	in	in	ADP
fcis-1074	8	2	foggy	foggy	ADJ
fcis-1074	8	3	conditions	condition	NOUN
fcis-1074	8	4	,	,	PUNCT
fcis-1074	8	5	the	the	DET
fcis-1074	8	6	quality	quality	NOUN
fcis-1074	8	7	of	of	ADP
fcis-1074	8	8	images	image	NOUN
fcis-1074	8	9	and	and	CCONJ
fcis-1074	8	10	videos	video	NOUN
fcis-1074	8	11	is	be	AUX
fcis-1074	8	12	drastically	drastically	ADV
fcis-1074	8	13	degraded	degrade	VERB
fcis-1074	8	14	by	by	ADP
fcis-1074	8	15	the	the	DET
fcis-1074	8	16	scattering	scattering	NOUN
fcis-1074	8	17	of	of	ADP
fcis-1074	8	18	suspended	suspend	VERB
fcis-1074	8	19	particles	particle	NOUN
fcis-1074	8	20	in	in	ADP
fcis-1074	8	21	the	the	DET
fcis-1074	8	22	air	air	NOUN
fcis-1074	8	23	and	and	CCONJ
fcis-1074	8	24	the	the	DET
fcis-1074	8	25	ambient	ambient	ADJ
fcis-1074	8	26	light	light	NOUN
fcis-1074	8	27	caused	cause	VERB
fcis-1074	8	28	by	by	ADP
fcis-1074	8	29	suspended	suspend	VERB
fcis-1074	8	30	particles	particle	NOUN
fcis-1074	8	31	,	,	PUNCT
fcis-1074	8	32	which	which	PRON
fcis-1074	8	33	causes	cause	VERB
fcis-1074	8	34	great	great	ADJ
fcis-1074	8	35	difficulties	difficulty	NOUN
fcis-1074	8	36	in	in	ADP
fcis-1074	8	37	fields	field	NOUN
fcis-1074	8	38	such	such	ADJ
fcis-1074	8	39	as	as	ADP
fcis-1074	8	40	traffic	traffic	NOUN
fcis-1074	8	41	detection	detection	NOUN
fcis-1074	8	42	.	.	PUNCT
fcis-1074	9	1	therefore	therefore	ADV
fcis-1074	9	2	,	,	PUNCT
fcis-1074	9	3	image	image	NOUN
fcis-1074	9	4	defogging	defogge	VERB
fcis-1074	9	5	algorithms	algorithm	NOUN
fcis-1074	9	6	are	be	AUX
fcis-1074	9	7	of	of	ADP
fcis-1074	9	8	practical	practical	ADJ
fcis-1074	9	9	importance	importance	NOUN
fcis-1074	9	10	and	and	CCONJ
fcis-1074	9	11	have	have	AUX
fcis-1074	9	12	received	receive	VERB
fcis-1074	9	13	a	a	DET
fcis-1074	9	14	lot	lot	NOUN
fcis-1074	9	15	of	of	ADP
fcis-1074	9	16	attention	attention	NOUN
fcis-1074	9	17	from	from	ADP
fcis-1074	9	18	researchers	researcher	NOUN
fcis-1074	9	19	in	in	ADP
fcis-1074	9	20	recent	recent	ADJ
fcis-1074	9	21	years	year	NOUN
fcis-1074	9	22	.	.	PUNCT
fcis-1074	10	1	with	with	ADP
fcis-1074	10	2	the	the	DET
fcis-1074	10	3	proliferation	proliferation	NOUN
fcis-1074	10	4	of	of	ADP
fcis-1074	10	5	image	image	NOUN
fcis-1074	10	6	defogging	defogge	VERB
fcis-1074	10	7	algorithms	algorithm	NOUN
fcis-1074	10	8	and	and	CCONJ
fcis-1074	10	9	the	the	DET
fcis-1074	10	10	rapid	rapid	ADJ
fcis-1074	10	11	development	development	NOUN
fcis-1074	10	12	of	of	ADP
fcis-1074	10	13	deep	deep	ADJ
fcis-1074	10	14	learning	learning	NOUN
fcis-1074	10	15	,	,	PUNCT
fcis-1074	10	16	defogging	defogge	VERB
fcis-1074	10	17	algorithms	algorithm	NOUN
fcis-1074	10	18	are	be	AUX
fcis-1074	10	19	mainly	mainly	ADV
fcis-1074	10	20	divided	divide	VERB
fcis-1074	10	21	into	into	ADP
fcis-1074	10	22	two	two	NUM
fcis-1074	10	23	categories	category	NOUN
fcis-1074	10	24	:	:	PUNCT
fcis-1074	10	25	traditional	traditional	ADJ
fcis-1074	10	26	defogging	defogging	NOUN
fcis-1074	10	27	methods	method	NOUN
fcis-1074	10	28	,	,	PUNCT
fcis-1074	10	29	and	and	CCONJ
fcis-1074	10	30	neural	neural	ADJ
fcis-1074	10	31	network	network	NOUN
fcis-1074	10	32	-	-	PUNCT
fcis-1074	10	33	based	base	VERB
fcis-1074	10	34	defogging	defogging	NOUN
fcis-1074	10	35	methods	method	NOUN
fcis-1074	10	36	.	.	PUNCT
fcis-1074	11	1	traditional	traditional	ADJ
fcis-1074	11	2	defogging	defogging	NOUN
fcis-1074	11	3	methods	method	NOUN
fcis-1074	11	4	are	be	AUX
fcis-1074	11	5	divided	divide	VERB
fcis-1074	11	6	into	into	ADP
fcis-1074	11	7	image	image	NOUN
fcis-1074	11	8	enhancement	enhancement	NOUN
fcis-1074	11	9	-	-	PUNCT
fcis-1074	11	10	based	base	VERB
fcis-1074	11	11	defogging	defogging	NOUN
fcis-1074	11	12	algorithms	algorithm	NOUN
fcis-1074	11	13	and	and	CCONJ
fcis-1074	11	14	physical	physical	ADJ
fcis-1074	11	15	model	model	NOUN
fcis-1074	11	16	-	-	PUNCT
fcis-1074	11	17	based	base	VERB
fcis-1074	11	18	defogging	defogging	NOUN
fcis-1074	11	19	algorithms	algorithm	NOUN
fcis-1074	11	20	.	.	PUNCT
fcis-1074	12	1	image	image	NOUN
fcis-1074	12	2	enhancementbased	enhancementbase	VERB
fcis-1074	12	3	image	image	NOUN
fcis-1074	12	4	defogging	defogge	VERB
fcis-1074	12	5	algorithms	algorithm	NOUN
fcis-1074	12	6	use	use	VERB
fcis-1074	12	7	contrast	contrast	NOUN
fcis-1074	12	8	enhancement	enhancement	NOUN
fcis-1074	12	9	to	to	PART
fcis-1074	12	10	highlight	highlight	VERB
fcis-1074	12	11	the	the	DET
fcis-1074	12	12	information	information	NOUN
fcis-1074	12	13	of	of	ADP
fcis-1074	12	14	foggy	foggy	ADJ
fcis-1074	12	15	images	image	NOUN
fcis-1074	12	16	,	,	PUNCT
fcis-1074	12	17	such	such	ADJ
fcis-1074	12	18	as	as	ADP
fcis-1074	12	19	the	the	DET
fcis-1074	12	20	subblock	subblock	PROPN
fcis-1074	12	21	histogram	histogram	PROPN
fcis-1074	12	22	equalization	equalization	NOUN
fcis-1074	12	23	algorithm	algorithm	NOUN
fcis-1074	12	24	and	and	CCONJ
fcis-1074	12	25	the	the	DET
fcis-1074	12	26	color	color	NOUN
fcis-1074	12	27	recovery	recovery	NOUN
fcis-1074	12	28	multi	multi	ADJ
fcis-1074	12	29	-	-	ADJ
fcis-1074	12	30	scale	scale	ADJ
fcis-1074	12	31	retinex	retinex	ADJ
fcis-1074	12	32	method	method	NOUN
fcis-1074	12	33	to	to	PART
fcis-1074	12	34	enhance	enhance	VERB
fcis-1074	12	35	the	the	DET
fcis-1074	12	36	contrast	contrast	NOUN
fcis-1074	12	37	of	of	ADP
fcis-1074	12	38	local	local	ADJ
fcis-1074	12	39	information	information	NOUN
fcis-1074	12	40	proposed	propose	VERB
fcis-1074	12	41	by	by	ADP
fcis-1074	12	42	kim	kim	PROPN
fcis-1074	13	1	[	[	X
fcis-1074	13	2	1	1	NUM
fcis-1074	13	3	]	]	PUNCT
fcis-1074	13	4	and	and	CCONJ
fcis-1074	13	5	jobson	jobson	PROPN
fcis-1074	13	6	[	[	X
fcis-1074	13	7	2	2	NUM
fcis-1074	13	8	]	]	PUNCT
fcis-1074	13	9	,	,	PUNCT
fcis-1074	13	10	respectively	respectively	ADV
fcis-1074	13	11	.	.	PUNCT
fcis-1074	14	1	however	however	ADV
fcis-1074	14	2	,	,	PUNCT
fcis-1074	14	3	these	these	DET
fcis-1074	14	4	types	type	NOUN
fcis-1074	14	5	of	of	ADP
fcis-1074	14	6	algorithms	algorithm	NOUN
fcis-1074	14	7	do	do	AUX
fcis-1074	14	8	not	not	PART
fcis-1074	14	9	consider	consider	VERB
fcis-1074	14	10	the	the	DET
fcis-1074	14	11	reason	reason	NOUN
fcis-1074	14	12	of	of	ADP
fcis-1074	14	13	foggy	foggy	ADJ
fcis-1074	14	14	image	image	NOUN
fcis-1074	14	15	degradation	degradation	NOUN
fcis-1074	14	16	,	,	PUNCT
fcis-1074	14	17	which	which	PRON
fcis-1074	14	18	will	will	AUX
fcis-1074	14	19	result	result	VERB
fcis-1074	14	20	in	in	ADP
fcis-1074	14	21	reduced	reduced	ADJ
fcis-1074	14	22	or	or	CCONJ
fcis-1074	14	23	over	over	ADV
fcis-1074	14	24	-	-	PUNCT
fcis-1074	14	25	enhanced	enhance	VERB
fcis-1074	14	26	detail	detail	NOUN
fcis-1074	14	27	information	information	NOUN
fcis-1074	14	28	retention	retention	NOUN
fcis-1074	14	29	.	.	PUNCT
fcis-1074	15	1	the	the	DET
fcis-1074	15	2	image	image	NOUN
fcis-1074	15	3	defogging	defogge	VERB
fcis-1074	15	4	algorithms	algorithm	NOUN
fcis-1074	15	5	based	base	VERB
fcis-1074	15	6	on	on	ADP
fcis-1074	15	7	physical	physical	ADJ
fcis-1074	15	8	models	model	NOUN
fcis-1074	15	9	estimate	estimate	VERB
fcis-1074	15	10	the	the	DET
fcis-1074	15	11	transmittance	transmittance	NOUN
fcis-1074	15	12	values	value	NOUN
fcis-1074	15	13	and	and	CCONJ
fcis-1074	15	14	atmospheric	atmospheric	ADJ
fcis-1074	15	15	illumination	illumination	NOUN
fcis-1074	15	16	values	value	NOUN
fcis-1074	15	17	of	of	ADP
fcis-1074	15	18	foggy	foggy	ADJ
fcis-1074	15	19	images	image	NOUN
fcis-1074	15	20	by	by	ADP
fcis-1074	15	21	a	a	DET
fcis-1074	15	22	priori	priori	ADJ
fcis-1074	15	23	information	information	NOUN
fcis-1074	15	24	,	,	PUNCT
fcis-1074	15	25	and	and	CCONJ
fcis-1074	15	26	then	then	ADV
fcis-1074	15	27	recover	recover	VERB
fcis-1074	15	28	clear	clear	ADJ
fcis-1074	15	29	images	image	NOUN
fcis-1074	15	30	based	base	VERB
fcis-1074	15	31	on	on	ADP
fcis-1074	15	32	atmospheric	atmospheric	ADJ
fcis-1074	15	33	scattering	scattering	NOUN
fcis-1074	15	34	models	model	NOUN
fcis-1074	15	35	,	,	PUNCT
fcis-1074	15	36	such	such	ADJ
fcis-1074	15	37	as	as	ADP
fcis-1074	15	38	the	the	DET
fcis-1074	15	39	dark	dark	ADJ
fcis-1074	15	40	channel	channel	NOUN
fcis-1074	15	41	a	a	DET
fcis-1074	15	42	priori	priori	ADJ
fcis-1074	15	43	defogging	defogge	VERB
fcis-1074	15	44	algorithm	algorithm	NOUN
fcis-1074	15	45	proposed	propose	VERB
fcis-1074	15	46	by	by	ADP
fcis-1074	15	47	he	he	PRON
fcis-1074	15	48	et	et	PROPN
fcis-1074	15	49	al	al	PROPN
fcis-1074	16	1	[	[	X
fcis-1074	16	2	3	3	NUM
fcis-1074	16	3	]	]	PUNCT
fcis-1074	16	4	.	.	PUNCT
fcis-1074	17	1	however	however	ADV
fcis-1074	17	2	,	,	PUNCT
fcis-1074	17	3	there	there	PRON
fcis-1074	17	4	is	be	VERB
fcis-1074	17	5	often	often	ADV
fcis-1074	17	6	a	a	DET
fcis-1074	17	7	large	large	ADJ
fcis-1074	17	8	computational	computational	ADJ
fcis-1074	17	9	effort	effort	NOUN
fcis-1074	17	10	in	in	ADP
fcis-1074	17	11	estimating	estimate	VERB
fcis-1074	17	12	the	the	DET
fcis-1074	17	13	transmittance	transmittance	NOUN
fcis-1074	17	14	value	value	NOUN
fcis-1074	17	15	and	and	CCONJ
fcis-1074	17	16	atmospheric	atmospheric	ADJ
fcis-1074	17	17	illumination	illumination	NOUN
fcis-1074	17	18	value	value	NOUN
fcis-1074	17	19	,	,	PUNCT
fcis-1074	17	20	and	and	CCONJ
fcis-1074	17	21	the	the	DET
fcis-1074	17	22	sky	sky	NOUN
fcis-1074	17	23	area	area	NOUN
fcis-1074	17	24	effect	effect	NOUN
fcis-1074	17	25	is	be	AUX
fcis-1074	17	26	not	not	PART
fcis-1074	17	27	satisfactory	satisfactory	ADJ
fcis-1074	17	28	.	.	PUNCT
fcis-1074	18	1	the	the	DET
fcis-1074	18	2	neural	neural	ADJ
fcis-1074	18	3	network	network	NOUN
fcis-1074	18	4	-	-	PUNCT
fcis-1074	18	5	based	base	VERB
fcis-1074	18	6	defogging	defogging	NOUN
fcis-1074	18	7	algorithm	algorithm	NOUN
fcis-1074	18	8	is	be	AUX
fcis-1074	18	9	divided	divide	VERB
fcis-1074	18	10	into	into	ADP
fcis-1074	18	11	two	two	NUM
fcis-1074	18	12	-	-	PUNCT
fcis-1074	18	13	stage	stage	NOUN
fcis-1074	18	14	defogging	defogge	VERB
fcis-1074	18	15	algorithm	algorithm	NOUN
fcis-1074	18	16	and	and	CCONJ
fcis-1074	18	17	single	single	ADJ
fcis-1074	18	18	-	-	PUNCT
fcis-1074	18	19	stage	stage	NOUN
fcis-1074	18	20	defogging	defogging	NOUN
fcis-1074	18	21	algorithm	algorithm	NOUN
fcis-1074	18	22	.	.	PUNCT
fcis-1074	19	1	the	the	DET
fcis-1074	19	2	basic	basic	ADJ
fcis-1074	19	3	principle	principle	NOUN
fcis-1074	19	4	of	of	ADP
fcis-1074	19	5	the	the	DET
fcis-1074	19	6	two	two	NUM
fcis-1074	19	7	-	-	PUNCT
fcis-1074	19	8	stage	stage	NOUN
fcis-1074	19	9	defogging	defogging	NOUN
fcis-1074	19	10	algorithm	algorithm	NOUN
fcis-1074	19	11	is	be	AUX
fcis-1074	19	12	still	still	ADV
fcis-1074	19	13	to	to	PART
fcis-1074	19	14	use	use	VERB
fcis-1074	19	15	the	the	DET
fcis-1074	19	16	atmospheric	atmospheric	ADJ
fcis-1074	19	17	scattering	scattering	NOUN
fcis-1074	19	18	model	model	NOUN
fcis-1074	19	19	backward	backward	ADJ
fcis-1074	19	20	derivation	derivation	NOUN
fcis-1074	19	21	to	to	PART
fcis-1074	19	22	recover	recover	VERB
fcis-1074	19	23	clear	clear	ADJ
fcis-1074	19	24	images	image	NOUN
fcis-1074	19	25	,	,	PUNCT
fcis-1074	19	26	but	but	CCONJ
fcis-1074	19	27	the	the	DET
fcis-1074	19	28	difference	difference	NOUN
fcis-1074	19	29	from	from	ADP
fcis-1074	19	30	the	the	DET
fcis-1074	19	31	traditional	traditional	ADJ
fcis-1074	19	32	defogging	defogge	VERB
fcis-1074	19	33	algorithm	algorithm	NOUN
fcis-1074	19	34	is	be	AUX
fcis-1074	19	35	to	to	PART
fcis-1074	19	36	use	use	VERB
fcis-1074	19	37	the	the	DET
fcis-1074	19	38	neural	neural	ADJ
fcis-1074	19	39	network	network	NOUN
fcis-1074	19	40	to	to	PART
fcis-1074	19	41	learn	learn	VERB
fcis-1074	19	42	to	to	PART
fcis-1074	19	43	estimate	estimate	VERB
fcis-1074	19	44	the	the	DET
fcis-1074	19	45	transmittance	transmittance	NOUN
fcis-1074	19	46	and	and	CCONJ
fcis-1074	19	47	atmospheric	atmospheric	ADJ
fcis-1074	19	48	light	light	NOUN
fcis-1074	19	49	values	value	NOUN
fcis-1074	19	50	.	.	PUNCT
fcis-1074	20	1	however	however	ADV
fcis-1074	20	2	,	,	PUNCT
fcis-1074	20	3	due	due	ADP
fcis-1074	20	4	to	to	ADP
fcis-1074	20	5	the	the	DET
fcis-1074	20	6	cumulative	cumulative	ADJ
fcis-1074	20	7	effect	effect	NOUN
fcis-1074	20	8	of	of	ADP
fcis-1074	20	9	the	the	DET
fcis-1074	20	10	two	two	NUM
fcis-1074	20	11	stages	stage	NOUN
fcis-1074	20	12	,	,	PUNCT
fcis-1074	20	13	the	the	DET
fcis-1074	20	14	overall	overall	ADJ
fcis-1074	20	15	deviation	deviation	NOUN
fcis-1074	20	16	will	will	AUX
fcis-1074	20	17	be	be	AUX
fcis-1074	20	18	enlarged	enlarge	VERB
fcis-1074	20	19	and	and	CCONJ
fcis-1074	20	20	the	the	DET
fcis-1074	20	21	clear	clear	ADJ
fcis-1074	20	22	image	image	NOUN
fcis-1074	20	23	recovered	recover	VERB
fcis-1074	20	24	by	by	ADP
fcis-1074	20	25	backward	backward	ADJ
fcis-1074	20	26	derivation	derivation	NOUN
fcis-1074	20	27	is	be	AUX
fcis-1074	20	28	prone	prone	ADJ
fcis-1074	20	29	to	to	ADP
fcis-1074	20	30	color	color	NOUN
fcis-1074	20	31	distortion	distortion	NOUN
fcis-1074	20	32	.	.	PUNCT
fcis-1074	21	1	cai	cai	PROPN
fcis-1074	21	2	et	et	PROPN
fcis-1074	21	3	al	al	PROPN
fcis-1074	22	1	[	[	X
fcis-1074	22	2	4	4	X
fcis-1074	22	3	]	]	PUNCT
fcis-1074	22	4	proposed	propose	VERB
fcis-1074	22	5	a	a	DET
fcis-1074	22	6	dehazenet	dehazenet	ADJ
fcis-1074	22	7	defogging	defogge	VERB
fcis-1074	22	8	network	network	NOUN
fcis-1074	22	9	to	to	PART
fcis-1074	22	10	estimate	estimate	VERB
fcis-1074	22	11	the	the	DET
fcis-1074	22	12	transmittance	transmittance	NOUN
fcis-1074	22	13	in	in	ADP
fcis-1074	22	14	the	the	DET
fcis-1074	22	15	atmospheric	atmospheric	ADJ
fcis-1074	22	16	model	model	NOUN
fcis-1074	22	17	,	,	PUNCT
fcis-1074	22	18	pioneering	pioneer	VERB
fcis-1074	22	19	the	the	DET
fcis-1074	22	20	use	use	NOUN
fcis-1074	22	21	of	of	ADP
fcis-1074	22	22	neural	neural	ADJ
fcis-1074	22	23	networks	network	NOUN
fcis-1074	22	24	for	for	ADP
fcis-1074	22	25	image	image	NOUN
fcis-1074	22	26	defogging	defogging	NOUN
fcis-1074	22	27	;	;	PUNCT
fcis-1074	22	28	zhang	zhang	X
fcis-1074	23	1	[	[	X
fcis-1074	23	2	5	5	NUM
fcis-1074	23	3	]	]	PUNCT
fcis-1074	23	4	et	et	PROPN
fcis-1074	23	5	al	al	PROPN
fcis-1074	23	6	proposed	propose	VERB
fcis-1074	23	7	a	a	DET
fcis-1074	23	8	cnn	cnn	PROPN
fcis-1074	23	9	-	-	PUNCT
fcis-1074	23	10	based	base	VERB
fcis-1074	23	11	dcpdn	dcpdn	NOUN
fcis-1074	23	12	defogging	defogge	VERB
fcis-1074	23	13	network	network	NOUN
fcis-1074	23	14	,	,	PUNCT
fcis-1074	23	15	using	use	VERB
fcis-1074	23	16	densely	densely	ADV
fcis-1074	23	17	connected	connect	VERB
fcis-1074	23	18	pyramidal	pyramidal	ADJ
fcis-1074	23	19	modules	module	NOUN
fcis-1074	23	20	to	to	PART
fcis-1074	23	21	estimate	estimate	VERB
fcis-1074	23	22	the	the	DET
fcis-1074	23	23	transmittance	transmittance	NOUN
fcis-1074	23	24	and	and	CCONJ
fcis-1074	23	25	subnetworks	subnetwork	NOUN
fcis-1074	23	26	to	to	PART
fcis-1074	23	27	estimate	estimate	VERB
fcis-1074	23	28	the	the	DET
fcis-1074	23	29	atmospheric	atmospheric	ADJ
fcis-1074	23	30	light	light	NOUN
fcis-1074	23	31	values	value	NOUN
fcis-1074	23	32	.	.	PUNCT
fcis-1074	24	1	a	a	DET
fcis-1074	24	2	singlestage	singlestage	NOUN
fcis-1074	24	3	defogging	defogge	VERB
fcis-1074	24	4	algorithm	algorithm	NOUN
fcis-1074	24	5	,	,	PUNCT
fcis-1074	24	6	which	which	PRON
fcis-1074	24	7	uses	use	VERB
fcis-1074	24	8	a	a	DET
fcis-1074	24	9	neural	neural	ADJ
fcis-1074	24	10	network	network	NOUN
fcis-1074	24	11	to	to	PART
fcis-1074	24	12	directly	directly	ADV
fcis-1074	24	13	restore	restore	VERB
fcis-1074	24	14	fogged	fogged	ADJ
fcis-1074	24	15	images	image	NOUN
fcis-1074	24	16	to	to	ADP
fcis-1074	24	17	clear	clear	ADJ
fcis-1074	24	18	images	image	NOUN
fcis-1074	24	19	,	,	PUNCT
fcis-1074	24	20	i.e.	i.e.	X
fcis-1074	24	21	,	,	PUNCT
fcis-1074	24	22	end	end	ADJ
fcis-1074	24	23	-	-	PUNCT
fcis-1074	24	24	toend	toend	ADJ
fcis-1074	24	25	defogging	defogging	NOUN
fcis-1074	24	26	,	,	PUNCT
fcis-1074	24	27	without	without	ADP
fcis-1074	24	28	a	a	DET
fcis-1074	24	29	priori	priori	ADJ
fcis-1074	24	30	estimation	estimation	NOUN
fcis-1074	24	31	of	of	ADP
fcis-1074	24	32	atmospheric	atmospheric	ADJ
fcis-1074	24	33	light	light	ADJ
fcis-1074	24	34	values	value	NOUN
fcis-1074	24	35	and	and	CCONJ
fcis-1074	24	36	transmittance	transmittance	NOUN
fcis-1074	24	37	,	,	PUNCT
fcis-1074	24	38	achieves	achieve	VERB
fcis-1074	24	39	detachment	detachment	NOUN
fcis-1074	24	40	from	from	ADP
fcis-1074	24	41	the	the	DET
fcis-1074	24	42	atmospheric	atmospheric	ADJ
fcis-1074	24	43	scattering	scattering	NOUN
fcis-1074	24	44	model	model	NOUN
fcis-1074	24	45	.	.	PUNCT
fcis-1074	25	1	li	li	PROPN
fcis-1074	25	2	et	et	PROPN
fcis-1074	25	3	al	al	PROPN
fcis-1074	26	1	[	[	X
fcis-1074	26	2	6	6	NUM
fcis-1074	26	3	]	]	PUNCT
fcis-1074	26	4	proposed	propose	VERB
fcis-1074	26	5	an	an	DET
fcis-1074	26	6	aodnet	aodnet	NOUN
fcis-1074	26	7	defogging	defogge	VERB
fcis-1074	26	8	network	network	NOUN
fcis-1074	26	9	,	,	PUNCT
fcis-1074	26	10	which	which	PRON
fcis-1074	26	11	directly	directly	ADV
fcis-1074	26	12	achieves	achieve	VERB
fcis-1074	26	13	end	end	NOUN
fcis-1074	26	14	-	-	PUNCT
fcis-1074	26	15	to	to	ADP
fcis-1074	26	16	-	-	PUNCT
fcis-1074	26	17	end	end	NOUN
fcis-1074	26	18	defogging	defogging	NOUN
fcis-1074	26	19	by	by	ADP
fcis-1074	26	20	a	a	DET
fcis-1074	26	21	lightweight	lightweight	ADJ
fcis-1074	26	22	cnn	cnn	NOUN
fcis-1074	26	23	and	and	CCONJ
fcis-1074	26	24	can	can	AUX
fcis-1074	26	25	be	be	AUX
fcis-1074	26	26	connected	connect	VERB
fcis-1074	26	27	with	with	ADP
fcis-1074	26	28	a	a	DET
fcis-1074	26	29	faster	fast	ADJ
fcis-1074	26	30	r	r	NOUN
fcis-1074	26	31	-	-	PUNCT
fcis-1074	26	32	cnn	cnn	NOUN
fcis-1074	26	33	to	to	PART
fcis-1074	26	34	improve	improve	VERB
fcis-1074	26	35	performance	performance	NOUN
fcis-1074	26	36	.	.	PUNCT
fcis-1074	27	1	mei	mei	PROPN
fcis-1074	27	2	et	et	PROPN
fcis-1074	27	3	al	al	PROPN
fcis-1074	28	1	[	[	X
fcis-1074	28	2	7	7	NUM
fcis-1074	28	3	]	]	PUNCT
fcis-1074	28	4	proposed	propose	VERB
fcis-1074	28	5	a	a	DET
fcis-1074	28	6	deep	deep	ADJ
fcis-1074	28	7	network	network	NOUN
fcis-1074	28	8	based	base	VERB
fcis-1074	28	9	on	on	ADP
fcis-1074	28	10	feature	feature	NOUN
fcis-1074	28	11	fusion	fusion	NOUN
fcis-1074	28	12	with	with	ADP
fcis-1074	28	13	a	a	DET
fcis-1074	28	14	unet	unet	NOUN
fcis-1074	28	15	-	-	PUNCT
fcis-1074	28	16	like	like	ADJ
fcis-1074	28	17	encoder	encoder	NOUN
fcis-1074	28	18	-	-	PUNCT
fcis-1074	28	19	decoder	decoder	NOUN
fcis-1074	28	20	to	to	PART
fcis-1074	28	21	recover	recover	VERB
fcis-1074	28	22	fog	fog	NOUN
fcis-1074	28	23	-	-	PUNCT
fcis-1074	28	24	free	free	ADJ
fcis-1074	28	25	images	image	NOUN
fcis-1074	28	26	by	by	ADP
fcis-1074	28	27	directly	directly	ADV
fcis-1074	28	28	learning	learn	VERB
fcis-1074	28	29	the	the	DET
fcis-1074	28	30	mapping	mapping	NOUN
fcis-1074	28	31	relationship	relationship	NOUN
fcis-1074	28	32	between	between	ADP
fcis-1074	28	33	fogged	fogged	ADJ
fcis-1074	28	34	and	and	CCONJ
fcis-1074	28	35	clear	clear	ADJ
fcis-1074	28	36	images	image	NOUN
fcis-1074	28	37	.	.	PUNCT
fcis-1074	29	1	with	with	ADP
fcis-1074	29	2	the	the	DET
fcis-1074	29	3	introduction	introduction	NOUN
fcis-1074	29	4	of	of	ADP
fcis-1074	29	5	gan	gan	PROPN
fcis-1074	29	6	networks	network	NOUN
fcis-1074	29	7	into	into	ADP
fcis-1074	29	8	the	the	DET
fcis-1074	29	9	image	image	NOUN
fcis-1074	29	10	domain	domain	NOUN
fcis-1074	29	11	by	by	ADP
fcis-1074	29	12	goodfellow	goodfellow	PROPN
fcis-1074	29	13	et	et	PROPN
fcis-1074	29	14	al	al	PROPN
fcis-1074	30	1	[	[	X
fcis-1074	30	2	8	8	NUM
fcis-1074	30	3	]	]	PUNCT
fcis-1074	30	4	,	,	PUNCT
fcis-1074	30	5	a	a	DET
fcis-1074	30	6	series	series	NOUN
fcis-1074	30	7	of	of	ADP
fcis-1074	30	8	algorithms	algorithm	NOUN
fcis-1074	30	9	for	for	ADP
fcis-1074	30	10	defogging	defogging	NOUN
fcis-1074	30	11	using	use	VERB
fcis-1074	30	12	gan	gan	PROPN
fcis-1074	30	13	networks	network	NOUN
fcis-1074	30	14	have	have	AUX
fcis-1074	30	15	emerged	emerge	VERB
fcis-1074	30	16	[	[	PUNCT
fcis-1074	30	17	9	9	NUM
fcis-1074	30	18	-	-	SYM
fcis-1074	30	19	11	11	NUM
fcis-1074	30	20	]	]	PUNCT
fcis-1074	30	21	.	.	PUNCT
fcis-1074	31	1	the	the	DET
fcis-1074	31	2	deblurgan	deblurgan	NOUN
fcis-1074	31	3	-	-	PUNCT
fcis-1074	31	4	based	base	VERB
fcis-1074	31	5	defogging	defogging	NOUN
fcis-1074	31	6	network	network	NOUN
fcis-1074	31	7	proposed	propose	VERB
fcis-1074	31	8	in	in	ADP
fcis-1074	31	9	this	this	DET
fcis-1074	31	10	paper	paper	NOUN
fcis-1074	31	11	adds	add	VERB
fcis-1074	31	12	the	the	DET
fcis-1074	31	13	dilated	dilated	ADJ
fcis-1074	31	14	convolution	convolution	NOUN
fcis-1074	31	15	(	(	PUNCT
fcis-1074	31	16	dcc	dcc	PROPN
fcis-1074	31	17	)	)	PUNCT
fcis-1074	31	18	module	module	NOUN
fcis-1074	31	19	in	in	ADP
fcis-1074	31	20	the	the	DET
fcis-1074	31	21	generator	generator	NOUN
fcis-1074	31	22	to	to	PART
fcis-1074	31	23	expand	expand	VERB
fcis-1074	31	24	the	the	DET
fcis-1074	31	25	perceptual	perceptual	ADJ
fcis-1074	31	26	field	field	NOUN
fcis-1074	31	27	to	to	PART
fcis-1074	31	28	extract	extract	VERB
fcis-1074	31	29	richer	rich	ADJ
fcis-1074	31	30	semantic	semantic	ADJ
fcis-1074	31	31	information	information	NOUN
fcis-1074	31	32	and	and	CCONJ
fcis-1074	31	33	adds	add	VERB
fcis-1074	31	34	the	the	DET
fcis-1074	31	35	spatial	spatial	ADJ
fcis-1074	31	36	attention	attention	NOUN
fcis-1074	31	37	mechanism	mechanism	NOUN
fcis-1074	31	38	module	module	NOUN
fcis-1074	31	39	at	at	ADP
fcis-1074	31	40	the	the	DET
fcis-1074	31	41	specified	specified	ADJ
fcis-1074	31	42	location	location	NOUN
fcis-1074	31	43	,	,	PUNCT
fcis-1074	31	44	which	which	PRON
fcis-1074	31	45	is	be	AUX
fcis-1074	31	46	beneficial	beneficial	ADJ
fcis-1074	31	47	to	to	PART
fcis-1074	31	48	eliminate	eliminate	VERB
fcis-1074	31	49	fog	fog	PROPN
fcis-1074	31	50	;	;	PUNCT
fcis-1074	31	51	the	the	DET
fcis-1074	31	52	discriminator	discriminator	NOUN
fcis-1074	31	53	uses	use	VERB
fcis-1074	31	54	the	the	DET
fcis-1074	31	55	traditional	traditional	ADJ
fcis-1074	31	56	34	34	NUM
fcis-1074	31	57	×	×	NOUN
fcis-1074	31	58	34	34	NUM
fcis-1074	31	59	patchgan	patchgan	NOUN
fcis-1074	31	60	for	for	ADP
fcis-1074	31	61	chunking	chunk	VERB
fcis-1074	31	62	determination	determination	NOUN
fcis-1074	31	63	to	to	PART
fcis-1074	31	64	improve	improve	VERB
fcis-1074	31	65	the	the	DET
fcis-1074	31	66	resolution	resolution	NOUN
fcis-1074	31	67	of	of	ADP
fcis-1074	31	68	the	the	DET
fcis-1074	31	69	image	image	NOUN
fcis-1074	31	70	the	the	DET
fcis-1074	31	71	loss	loss	NOUN
fcis-1074	31	72	function	function	NOUN
fcis-1074	31	73	adds	add	VERB
fcis-1074	31	74	bce	bce	PROPN
fcis-1074	31	75	loss	loss	NOUN
fcis-1074	31	76	on	on	ADP
fcis-1074	31	77	top	top	NOUN
fcis-1074	31	78	of	of	ADP
fcis-1074	31	79	the	the	DET
fcis-1074	31	80	adversarial	adversarial	ADJ
fcis-1074	31	81	loss	loss	NOUN
fcis-1074	31	82	and	and	CCONJ
fcis-1074	31	83	content	content	NOUN
fcis-1074	31	84	loss	loss	NOUN
fcis-1074	31	85	5	5	NUM
fcis-1074	31	86	function	function	NOUN
fcis-1074	31	87	to	to	PART
fcis-1074	31	88	better	well	ADV
fcis-1074	31	89	solve	solve	VERB
fcis-1074	31	90	the	the	DET
fcis-1074	31	91	problem	problem	NOUN
fcis-1074	31	92	of	of	ADP
fcis-1074	31	93	blurred	blurred	ADJ
fcis-1074	31	94	generated	generate	VERB
fcis-1074	31	95	images	image	NOUN
fcis-1074	31	96	.	.	PUNCT
fcis-1074	32	1	2	2	X
fcis-1074	32	2	.	.	X
fcis-1074	32	3	network	network	NOUN
fcis-1074	32	4	model	model	NOUN
fcis-1074	32	5	in	in	ADP
fcis-1074	32	6	this	this	DET
fcis-1074	32	7	paper	paper	NOUN
fcis-1074	32	8	the	the	DET
fcis-1074	32	9	deblurgan	deblurgan	PROPN
fcis-1074	32	10	network	network	NOUN
fcis-1074	32	11	proposed	propose	VERB
fcis-1074	32	12	by	by	ADP
fcis-1074	32	13	orest	orest	PROPN
fcis-1074	32	14	kupyn	kupyn	PROPN
fcis-1074	32	15	et	et	NOUN
fcis-1074	32	16	al	al	PROPN
fcis-1074	33	1	[	[	X
fcis-1074	33	2	12	12	NUM
fcis-1074	33	3	]	]	PUNCT
fcis-1074	33	4	has	have	VERB
fcis-1074	33	5	a	a	DET
fcis-1074	33	6	simple	simple	ADJ
fcis-1074	33	7	structure	structure	NOUN
fcis-1074	33	8	and	and	CCONJ
fcis-1074	33	9	fast	fast	ADJ
fcis-1074	33	10	processing	processing	NOUN
fcis-1074	33	11	speed	speed	NOUN
fcis-1074	33	12	.	.	PUNCT
fcis-1074	34	1	however	however	ADV
fcis-1074	34	2	,	,	PUNCT
fcis-1074	34	3	the	the	DET
fcis-1074	34	4	traditional	traditional	ADJ
fcis-1074	34	5	deblurgan	deblurgan	NOUN
fcis-1074	34	6	network	network	NOUN
fcis-1074	34	7	has	have	VERB
fcis-1074	34	8	poor	poor	ADJ
fcis-1074	34	9	color	color	NOUN
fcis-1074	34	10	recovery	recovery	NOUN
fcis-1074	34	11	and	and	CCONJ
fcis-1074	34	12	fog	fog	NOUN
fcis-1074	34	13	residue	residue	NOUN
fcis-1074	34	14	when	when	SCONJ
fcis-1074	34	15	performing	perform	VERB
fcis-1074	34	16	defogging	defogging	NOUN
fcis-1074	34	17	.	.	PUNCT
fcis-1074	35	1	the	the	DET
fcis-1074	35	2	improved	improve	VERB
fcis-1074	35	3	deblurgan	deblurgan	NOUN
fcis-1074	35	4	network	network	NOUN
fcis-1074	35	5	proposed	propose	VERB
fcis-1074	35	6	in	in	ADP
fcis-1074	35	7	this	this	DET
fcis-1074	35	8	paper	paper	NOUN
fcis-1074	35	9	solves	solve	VERB
fcis-1074	35	10	the	the	DET
fcis-1074	35	11	above	above	ADJ
fcis-1074	35	12	problems	problem	NOUN
fcis-1074	35	13	better	well	ADV
fcis-1074	35	14	and	and	CCONJ
fcis-1074	35	15	achieves	achieve	VERB
fcis-1074	35	16	direct	direct	ADJ
fcis-1074	35	17	mapping	mapping	NOUN
fcis-1074	35	18	from	from	ADP
fcis-1074	35	19	foggy	foggy	ADJ
fcis-1074	35	20	images	image	NOUN
fcis-1074	35	21	to	to	ADP
fcis-1074	35	22	fog	fog	NOUN
fcis-1074	35	23	-	-	PUNCT
fcis-1074	35	24	free	free	ADJ
fcis-1074	35	25	images	image	NOUN
fcis-1074	35	26	.	.	PUNCT
fcis-1074	36	1	in	in	ADP
fcis-1074	36	2	this	this	DET
fcis-1074	36	3	paper	paper	NOUN
fcis-1074	36	4	,	,	PUNCT
fcis-1074	36	5	the	the	DET
fcis-1074	36	6	network	network	NOUN
fcis-1074	36	7	consists	consist	VERB
fcis-1074	36	8	of	of	ADP
fcis-1074	36	9	generator	generator	NOUN
fcis-1074	36	10	g	g	PROPN
fcis-1074	36	11	and	and	CCONJ
fcis-1074	36	12	discriminator	discriminator	PROPN
fcis-1074	36	13	d.	d.	PROPN
fcis-1074	36	14	the	the	DET
fcis-1074	36	15	generator	generator	PROPN
fcis-1074	36	16	g	g	PROPN
fcis-1074	36	17	generates	generate	VERB
fcis-1074	36	18	sample	sample	NOUN
fcis-1074	36	19	data	datum	NOUN
fcis-1074	36	20	that	that	PRON
fcis-1074	36	21	approximates	approximate	VERB
fcis-1074	36	22	the	the	DET
fcis-1074	36	23	real	real	ADJ
fcis-1074	36	24	data	datum	NOUN
fcis-1074	36	25	by	by	ADP
fcis-1074	36	26	learning	learn	VERB
fcis-1074	36	27	the	the	DET
fcis-1074	36	28	input	input	NOUN
fcis-1074	36	29	data	datum	NOUN
fcis-1074	36	30	,	,	PUNCT
fcis-1074	36	31	and	and	CCONJ
fcis-1074	36	32	the	the	DET
fcis-1074	36	33	input	input	NOUN
fcis-1074	36	34	has	have	VERB
fcis-1074	36	35	fog	fog	NOUN
fcis-1074	36	36	images	image	NOUN
fcis-1074	36	37	and	and	CCONJ
fcis-1074	36	38	directly	directly	ADV
fcis-1074	36	39	outputs	output	VERB
fcis-1074	36	40	fog	fog	ADJ
fcis-1074	36	41	-	-	PUNCT
fcis-1074	36	42	free	free	ADJ
fcis-1074	36	43	images	image	NOUN
fcis-1074	36	44	;	;	PUNCT
fcis-1074	36	45	the	the	DET
fcis-1074	36	46	role	role	NOUN
fcis-1074	36	47	of	of	ADP
fcis-1074	36	48	discriminator	discriminator	NOUN
fcis-1074	36	49	d	d	NOUN
fcis-1074	36	50	is	be	AUX
fcis-1074	36	51	to	to	PART
fcis-1074	36	52	distinguish	distinguish	VERB
fcis-1074	36	53	the	the	DET
fcis-1074	36	54	real	real	ADJ
fcis-1074	36	55	data	datum	NOUN
fcis-1074	36	56	from	from	ADP
fcis-1074	36	57	the	the	DET
fcis-1074	36	58	samples	sample	NOUN
fcis-1074	36	59	generated	generate	VERB
fcis-1074	36	60	by	by	ADP
fcis-1074	36	61	the	the	DET
fcis-1074	36	62	generator	generator	NOUN
fcis-1074	36	63	g.	g.	PROPN
fcis-1074	36	64	the	the	DET
fcis-1074	36	65	input	input	NOUN
fcis-1074	36	66	is	be	AUX
fcis-1074	36	67	a	a	DET
fcis-1074	36	68	combination	combination	NOUN
fcis-1074	36	69	of	of	ADP
fcis-1074	36	70	clear	clear	ADJ
fcis-1074	36	71	image	image	NOUN
fcis-1074	36	72	fog	fog	NOUN
fcis-1074	36	73	image	image	NOUN
fcis-1074	36	74	or	or	CCONJ
fcis-1074	36	75	defog	defog	NOUN
fcis-1074	36	76	image	image	NOUN
fcis-1074	36	77	fog	fog	NOUN
fcis-1074	36	78	image	image	NOUN
fcis-1074	36	79	.	.	PUNCT
fcis-1074	37	1	inspired	inspire	VERB
fcis-1074	37	2	by	by	ADP
fcis-1074	37	3	the	the	DET
fcis-1074	37	4	idea	idea	NOUN
fcis-1074	37	5	of	of	ADP
fcis-1074	37	6	game	game	NOUN
fcis-1074	37	7	theory	theory	NOUN
fcis-1074	37	8	,	,	PUNCT
fcis-1074	37	9	generator	generator	NOUN
fcis-1074	37	10	g	g	PROPN
fcis-1074	37	11	and	and	CCONJ
fcis-1074	37	12	discriminator	discriminator	PROPN
fcis-1074	37	13	d	d	NOUN
fcis-1074	37	14	are	be	AUX
fcis-1074	37	15	trained	train	VERB
fcis-1074	37	16	adversarially	adversarially	ADV
fcis-1074	37	17	and	and	CCONJ
fcis-1074	37	18	progress	progress	VERB
fcis-1074	37	19	together	together	ADV
fcis-1074	37	20	until	until	SCONJ
fcis-1074	37	21	discriminator	discriminator	NOUN
fcis-1074	37	22	d	d	PROPN
fcis-1074	37	23	can	can	AUX
fcis-1074	37	24	not	not	PART
fcis-1074	37	25	distinguish	distinguish	VERB
fcis-1074	37	26	the	the	DET
fcis-1074	37	27	samples	sample	NOUN
fcis-1074	37	28	generated	generate	VERB
fcis-1074	37	29	by	by	ADP
fcis-1074	37	30	generator	generator	NOUN
fcis-1074	37	31	g	g	PROPN
fcis-1074	37	32	from	from	ADP
fcis-1074	37	33	the	the	DET
fcis-1074	37	34	real	real	ADJ
fcis-1074	37	35	data	datum	NOUN
fcis-1074	37	36	samples	sample	NOUN
fcis-1074	37	37	,	,	PUNCT
fcis-1074	37	38	at	at	ADP
fcis-1074	37	39	which	which	DET
fcis-1074	37	40	time	time	NOUN
fcis-1074	37	41	the	the	DET
fcis-1074	37	42	discriminator	discriminator	NOUN
fcis-1074	37	43	d	d	PROPN
fcis-1074	37	44	output	output	NOUN
fcis-1074	37	45	is	be	AUX
fcis-1074	37	46	stabilized	stabilize	VERB
fcis-1074	37	47	at	at	ADP
fcis-1074	37	48	about	about	ADV
fcis-1074	37	49	0.5	0.5	NUM
fcis-1074	37	50	,	,	PUNCT
fcis-1074	37	51	indicating	indicate	VERB
fcis-1074	37	52	that	that	SCONJ
fcis-1074	37	53	the	the	DET
fcis-1074	37	54	model	model	NOUN
fcis-1074	37	55	reaches	reach	VERB
fcis-1074	37	56	the	the	DET
fcis-1074	37	57	optimal	optimal	ADJ
fcis-1074	37	58	state	state	NOUN
fcis-1074	37	59	nash	nash	PROPN
fcis-1074	37	60	equilibrium	equilibrium	NOUN
fcis-1074	37	61	.	.	PUNCT
fcis-1074	38	1	2.1	2.1	NUM
fcis-1074	38	2	.	.	PUNCT
fcis-1074	38	3	generators	generator	NOUN
fcis-1074	38	4	in	in	ADP
fcis-1074	38	5	order	order	NOUN
fcis-1074	38	6	to	to	PART
fcis-1074	38	7	obtain	obtain	VERB
fcis-1074	38	8	deeper	deep	ADJ
fcis-1074	38	9	features	feature	NOUN
fcis-1074	38	10	as	as	ADV
fcis-1074	38	11	well	well	ADV
fcis-1074	38	12	as	as	ADP
fcis-1074	38	13	multi	multi	ADJ
fcis-1074	38	14	-	-	ADJ
fcis-1074	38	15	scale	scale	ADJ
fcis-1074	38	16	information	information	NOUN
fcis-1074	38	17	and	and	CCONJ
fcis-1074	38	18	enhance	enhance	VERB
fcis-1074	38	19	the	the	DET
fcis-1074	38	20	ability	ability	NOUN
fcis-1074	38	21	of	of	ADP
fcis-1074	38	22	the	the	DET
fcis-1074	38	23	generator	generator	NOUN
fcis-1074	38	24	to	to	PART
fcis-1074	38	25	extract	extract	VERB
fcis-1074	38	26	features	feature	NOUN
fcis-1074	38	27	,	,	PUNCT
fcis-1074	38	28	the	the	DET
fcis-1074	38	29	expanded	expand	VERB
fcis-1074	38	30	convolution	convolution	NOUN
fcis-1074	38	31	module	module	NOUN
fcis-1074	38	32	[	[	X
fcis-1074	38	33	13	13	NUM
fcis-1074	38	34	]	]	PUNCT
fcis-1074	38	35	and	and	CCONJ
fcis-1074	38	36	the	the	DET
fcis-1074	38	37	spatial	spatial	ADJ
fcis-1074	38	38	attention	attention	NOUN
fcis-1074	38	39	mechanism	mechanism	NOUN
fcis-1074	38	40	module	module	NOUN
fcis-1074	38	41	[	[	X
fcis-1074	38	42	14	14	NUM
fcis-1074	38	43	]	]	PUNCT
fcis-1074	38	44	are	be	AUX
fcis-1074	38	45	added	add	VERB
fcis-1074	38	46	to	to	ADP
fcis-1074	38	47	the	the	DET
fcis-1074	38	48	generator	generator	NOUN
fcis-1074	38	49	.	.	PUNCT
fcis-1074	39	1	the	the	DET
fcis-1074	39	2	network	network	NOUN
fcis-1074	39	3	structure	structure	NOUN
fcis-1074	39	4	of	of	ADP
fcis-1074	39	5	the	the	DET
fcis-1074	39	6	generator	generator	NOUN
fcis-1074	39	7	is	be	AUX
fcis-1074	39	8	shown	show	VERB
fcis-1074	39	9	in	in	ADP
fcis-1074	39	10	fig	fig	NOUN
fcis-1074	39	11	.	.	PUNCT
fcis-1074	40	1	(	(	PUNCT
fcis-1074	40	2	1	1	X
fcis-1074	40	3	)	)	PUNCT
fcis-1074	40	4	and	and	CCONJ
fcis-1074	40	5	contains	contain	VERB
fcis-1074	40	6	two	two	NUM
fcis-1074	40	7	7	7	NUM
fcis-1074	40	8	×	×	NOUN
fcis-1074	40	9	7	7	NUM
fcis-1074	40	10	normal	normal	ADJ
fcis-1074	40	11	convolution	convolution	NOUN
fcis-1074	40	12	blocks	block	NOUN
fcis-1074	40	13	,	,	PUNCT
fcis-1074	40	14	two	two	NUM
fcis-1074	40	15	stepwise	stepwise	ADJ
fcis-1074	40	16	convolution	convolution	NOUN
fcis-1074	40	17	blocks	block	NOUN
fcis-1074	40	18	with	with	ADP
fcis-1074	40	19	1/2	1/2	NUM
fcis-1074	40	20	step	step	NOUN
fcis-1074	40	21	,	,	PUNCT
fcis-1074	40	22	nine	nine	NUM
fcis-1074	40	23	resblock	resblock	ADJ
fcis-1074	40	24	residual	residual	ADJ
fcis-1074	40	25	blocks	block	NOUN
fcis-1074	40	26	,	,	PUNCT
fcis-1074	40	27	four	four	NUM
fcis-1074	40	28	dialted	dialted	ADJ
fcis-1074	40	29	conv	conv	ADJ
fcis-1074	40	30	expansion	expansion	NOUN
fcis-1074	40	31	convolution	convolution	NOUN
fcis-1074	40	32	blocks	block	NOUN
fcis-1074	40	33	,	,	PUNCT
fcis-1074	40	34	a	a	DET
fcis-1074	40	35	spatial	spatial	ADJ
fcis-1074	40	36	attention	attention	NOUN
fcis-1074	40	37	mechanism	mechanism	NOUN
fcis-1074	40	38	module	module	NOUN
fcis-1074	40	39	and	and	CCONJ
fcis-1074	40	40	two	two	NUM
fcis-1074	40	41	transposed	transpose	VERB
fcis-1074	40	42	convolution	convolution	NOUN
fcis-1074	40	43	blocks	block	NOUN
fcis-1074	40	44	.	.	PUNCT
fcis-1074	41	1	each	each	DET
fcis-1074	41	2	resblock	resblock	NOUN
fcis-1074	41	3	consists	consist	VERB
fcis-1074	41	4	of	of	ADP
fcis-1074	41	5	a	a	DET
fcis-1074	41	6	3	3	NUM
fcis-1074	41	7	*	*	SYM
fcis-1074	41	8	3	3	NUM
fcis-1074	41	9	layer	layer	NOUN
fcis-1074	41	10	of	of	ADP
fcis-1074	41	11	convolution	convolution	NOUN
fcis-1074	41	12	,	,	PUNCT
fcis-1074	41	13	an	an	DET
fcis-1074	41	14	instancenorm	instancenorm	NOUN
fcis-1074	41	15	(	(	PUNCT
fcis-1074	41	16	instance	instance	NOUN
fcis-1074	41	17	normalization	normalization	NOUN
fcis-1074	41	18	layer	layer	NOUN
fcis-1074	41	19	)	)	PUNCT
fcis-1074	41	20	,	,	PUNCT
fcis-1074	41	21	and	and	CCONJ
fcis-1074	41	22	a	a	DET
fcis-1074	41	23	relu	relu	NOUN
fcis-1074	41	24	activation	activation	NOUN
fcis-1074	41	25	function	function	NOUN
fcis-1074	41	26	,	,	PUNCT
fcis-1074	41	27	and	and	CCONJ
fcis-1074	41	28	a	a	DET
fcis-1074	41	29	loss	loss	NOUN
fcis-1074	41	30	regularization	regularization	NOUN
fcis-1074	41	31	with	with	ADP
fcis-1074	41	32	probability	probability	NOUN
fcis-1074	41	33	0.5	0.5	NUM
fcis-1074	41	34	is	be	AUX
fcis-1074	41	35	added	add	VERB
fcis-1074	41	36	after	after	ADP
fcis-1074	41	37	the	the	DET
fcis-1074	41	38	convolution	convolution	NOUN
fcis-1074	41	39	to	to	ADP
fcis-1074	41	40	combat	combat	NOUN
fcis-1074	41	41	overfitting	overfitting	NOUN
fcis-1074	41	42	.	.	PUNCT
fcis-1074	42	1	the	the	DET
fcis-1074	42	2	resnet	resnet	NOUN
fcis-1074	42	3	network	network	NOUN
fcis-1074	42	4	linearly	linearly	ADV
fcis-1074	42	5	superimposes	superimpose	VERB
fcis-1074	42	6	the	the	DET
fcis-1074	42	7	input	input	NOUN
fcis-1074	42	8	and	and	CCONJ
fcis-1074	42	9	output	output	NOUN
fcis-1074	42	10	to	to	PART
fcis-1074	42	11	achieve	achieve	VERB
fcis-1074	42	12	residual	residual	ADJ
fcis-1074	42	13	connectivity	connectivity	NOUN
fcis-1074	42	14	and	and	CCONJ
fcis-1074	42	15	solve	solve	VERB
fcis-1074	42	16	the	the	DET
fcis-1074	42	17	problem	problem	NOUN
fcis-1074	42	18	of	of	ADP
fcis-1074	42	19	gradient	gradient	ADJ
fcis-1074	42	20	dispersion	dispersion	NOUN
fcis-1074	42	21	.	.	PUNCT
fcis-1074	43	1	in	in	ADP
fcis-1074	43	2	this	this	DET
fcis-1074	43	3	paper	paper	NOUN
fcis-1074	43	4	,	,	PUNCT
fcis-1074	43	5	we	we	PRON
fcis-1074	43	6	add	add	VERB
fcis-1074	43	7	four	four	NUM
fcis-1074	43	8	successive	successive	ADJ
fcis-1074	43	9	dilation	dilation	NOUN
fcis-1074	43	10	convolutions	convolution	NOUN
fcis-1074	43	11	to	to	ADP
fcis-1074	43	12	the	the	DET
fcis-1074	43	13	generator	generator	NOUN
fcis-1074	43	14	,	,	PUNCT
fcis-1074	43	15	and	and	CCONJ
fcis-1074	43	16	the	the	DET
fcis-1074	43	17	dilation	dilation	NOUN
fcis-1074	43	18	factors	factor	NOUN
fcis-1074	43	19	of	of	ADP
fcis-1074	43	20	each	each	DET
fcis-1074	43	21	two	two	NUM
fcis-1074	43	22	successive	successive	ADJ
fcis-1074	43	23	dilation	dilation	NOUN
fcis-1074	43	24	convolutions	convolution	NOUN
fcis-1074	43	25	are	be	AUX
fcis-1074	43	26	not	not	PART
fcis-1074	43	27	multiplicative	multiplicative	ADJ
fcis-1074	43	28	between	between	ADP
fcis-1074	43	29	them	they	PRON
fcis-1074	43	30	,	,	PUNCT
fcis-1074	43	31	and	and	CCONJ
fcis-1074	43	32	the	the	DET
fcis-1074	43	33	dilation	dilation	NOUN
fcis-1074	43	34	factors	factor	NOUN
fcis-1074	43	35	are	be	AUX
fcis-1074	43	36	2	2	NUM
fcis-1074	43	37	,	,	PUNCT
fcis-1074	43	38	3	3	NUM
fcis-1074	43	39	,	,	PUNCT
fcis-1074	43	40	4	4	NUM
fcis-1074	43	41	,	,	PUNCT
fcis-1074	43	42	and	and	CCONJ
fcis-1074	43	43	2	2	NUM
fcis-1074	43	44	respectively	respectively	ADV
fcis-1074	43	45	,	,	PUNCT
fcis-1074	43	46	i.e.	i.e.	X
fcis-1074	43	47	,	,	PUNCT
fcis-1074	43	48	zeroes	zero	NOUN
fcis-1074	43	49	are	be	AUX
fcis-1074	43	50	introduced	introduce	VERB
fcis-1074	43	51	between	between	ADP
fcis-1074	43	52	the	the	DET
fcis-1074	43	53	convolution	convolution	NOUN
fcis-1074	43	54	kernel	kernel	PROPN
fcis-1074	43	55	parameters	parameter	NOUN
fcis-1074	43	56	according	accord	VERB
fcis-1074	43	57	to	to	ADP
fcis-1074	43	58	the	the	DET
fcis-1074	43	59	given	give	VERB
fcis-1074	43	60	dilation	dilation	NOUN
fcis-1074	43	61	factors	factor	NOUN
fcis-1074	43	62	to	to	PART
fcis-1074	43	63	expand	expand	VERB
fcis-1074	43	64	the	the	DET
fcis-1074	43	65	perceptual	perceptual	ADJ
fcis-1074	43	66	field	field	NOUN
fcis-1074	43	67	of	of	ADP
fcis-1074	43	68	the	the	DET
fcis-1074	43	69	convolution	convolution	NOUN
fcis-1074	43	70	process	process	NOUN
fcis-1074	43	71	and	and	CCONJ
fcis-1074	43	72	enable	enable	VERB
fcis-1074	43	73	the	the	DET
fcis-1074	43	74	network	network	NOUN
fcis-1074	43	75	to	to	PART
fcis-1074	43	76	extract	extract	VERB
fcis-1074	43	77	multi	multi	ADJ
fcis-1074	43	78	-	-	ADJ
fcis-1074	43	79	scale	scale	ADJ
fcis-1074	43	80	information	information	NOUN
fcis-1074	43	81	and	and	CCONJ
fcis-1074	43	82	learn	learn	VERB
fcis-1074	43	83	more	more	ADJ
fcis-1074	43	84	features	feature	NOUN
fcis-1074	43	85	without	without	ADP
fcis-1074	43	86	reducing	reduce	VERB
fcis-1074	43	87	the	the	DET
fcis-1074	43	88	resolution	resolution	NOUN
fcis-1074	43	89	.	.	PUNCT
fcis-1074	44	1	however	however	ADV
fcis-1074	44	2	,	,	PUNCT
fcis-1074	44	3	the	the	DET
fcis-1074	44	4	null	null	ADJ
fcis-1074	44	5	convolution	convolution	NOUN
fcis-1074	44	6	is	be	AUX
fcis-1074	44	7	computed	compute	VERB
fcis-1074	44	8	in	in	ADP
fcis-1074	44	9	a	a	DET
fcis-1074	44	10	tessellation	tessellation	NOUN
fcis-1074	44	11	-	-	PUNCT
fcis-1074	44	12	like	like	ADJ
fcis-1074	44	13	format	format	NOUN
fcis-1074	44	14	,	,	PUNCT
fcis-1074	44	15	resulting	result	VERB
fcis-1074	44	16	in	in	ADP
fcis-1074	44	17	no	no	DET
fcis-1074	44	18	correlation	correlation	NOUN
fcis-1074	44	19	between	between	ADP
fcis-1074	44	20	the	the	DET
fcis-1074	44	21	pixels	pixel	NOUN
fcis-1074	44	22	obtained	obtain	VERB
fcis-1074	44	23	from	from	ADP
fcis-1074	44	24	the	the	DET
fcis-1074	44	25	convolution	convolution	NOUN
fcis-1074	44	26	calculation	calculation	NOUN
fcis-1074	44	27	and	and	CCONJ
fcis-1074	44	28	loss	loss	NOUN
fcis-1074	44	29	of	of	ADP
fcis-1074	44	30	local	local	ADJ
fcis-1074	44	31	information	information	NOUN
fcis-1074	44	32	.	.	PUNCT
fcis-1074	45	1	the	the	DET
fcis-1074	45	2	problem	problem	NOUN
fcis-1074	45	3	of	of	ADP
fcis-1074	45	4	grid	grid	NOUN
fcis-1074	45	5	artifacts	artifact	NOUN
fcis-1074	45	6	occurs	occur	VERB
fcis-1074	45	7	when	when	SCONJ
fcis-1074	45	8	superimposing	superimpose	VERB
fcis-1074	45	9	two	two	NUM
fcis-1074	45	10	convolutions	convolution	NOUN
fcis-1074	45	11	with	with	ADP
fcis-1074	45	12	a	a	DET
fcis-1074	45	13	dilation	dilation	NOUN
fcis-1074	45	14	factor	factor	NOUN
fcis-1074	45	15	of	of	ADP
fcis-1074	45	16	2	2	NUM
fcis-1074	45	17	,	,	PUNCT
fcis-1074	45	18	as	as	SCONJ
fcis-1074	45	19	shown	show	VERB
fcis-1074	45	20	in	in	ADP
fcis-1074	45	21	the	the	DET
fcis-1074	45	22	figure	figure	NOUN
fcis-1074	45	23	2	2	NUM
fcis-1074	45	24	and	and	CCONJ
fcis-1074	45	25	3	3	NUM
fcis-1074	45	26	.	.	X
fcis-1074	45	27	7ˣ7	7ˣ7	PROPN
fcis-1074	46	1	conv	conv	ADJ
fcis-1074	46	2	instancenorm	instancenorm	PROPN
fcis-1074	46	3	relu	relu	NOUN
fcis-1074	46	4	spatial	spatial	ADJ
fcis-1074	46	5	attention	attention	NOUN
fcis-1074	46	6	m	m	NOUN
fcis-1074	46	7	odule	odule	NOUN
fcis-1074	46	8	3ˣ3	3ˣ3	PRON
fcis-1074	46	9	conv	conv	PROPN
fcis-1074	46	10	instancenorm	instancenorm	NOUN
fcis-1074	46	11	relu	relu	PROPN
fcis-1074	46	12	7ˣ7	7ˣ7	NUM
fcis-1074	46	13	conv	conv	PROPN
fcis-1074	46	14	tanh	tanh	PROPN
fcis-1074	46	15	3ˣ3	3ˣ3	PROPN
fcis-1074	46	16	conv	conv	PROPN
fcis-1074	46	17	instancenorm	instancenorm	PROPN
fcis-1074	46	18	relu	relu	PROPN
fcis-1074	46	19	3ˣ3	3ˣ3	PROPN
fcis-1074	46	20	conv	conv	PROPN
fcis-1074	46	21	instancenorm	instancenorm	PROPN
fcis-1074	46	22	relu	relu	PROPN
fcis-1074	46	23	3ˣ3	3ˣ3	PROPN
fcis-1074	46	24	conv	conv	PROPN
fcis-1074	46	25	instancenorm	instancenorm	NOUN
fcis-1074	46	26	relu	relu	NOUN
fcis-1074	46	27	dialted	dialte	VERB
fcis-1074	46	28	conv	conv	ADJ
fcis-1074	46	29	instancenorm	instancenorm	NOUN
fcis-1074	46	30	relu	relu	NOUN
fcis-1074	46	31	dialted	dialte	VERB
fcis-1074	46	32	conv	conv	ADJ
fcis-1074	46	33	instancenorm	instancenorm	NOUN
fcis-1074	46	34	relu	relu	NOUN
fcis-1074	46	35	9	9	NUM
fcis-1074	46	36	resblocks	resblock	NOUN
fcis-1074	46	37	4	4	NUM
fcis-1074	46	38	dialted	dialted	ADJ
fcis-1074	46	39	conv	conv	ADJ
fcis-1074	46	40	convtranspose	convtranspose	PROPN
fcis-1074	46	41	instancenorm	instancenorm	PROPN
fcis-1074	46	42	relu	relu	PROPN
fcis-1074	46	43	convtranspose	convtranspose	PROPN
fcis-1074	46	44	instancenorm	instancenorm	PROPN
fcis-1074	46	45	relu	relu	NOUN
fcis-1074	46	46	n64	n64	NOUN
fcis-1074	46	47	n128s2	n128s2	PROPN
fcis-1074	46	48	n128s2	n128s2	PROPN
fcis-1074	47	1	n256	n256	PROPN
fcis-1074	47	2	n256	n256	PROPN
fcis-1074	48	1	n256n256n256n128s2n64s2n64	n256n256n256n128s2n64s2n64	ADJ
fcis-1074	48	2	figure	figure	NOUN
fcis-1074	48	3	1	1	NUM
fcis-1074	48	4	.	.	PUNCT
fcis-1074	48	5	generator	generator	NOUN
fcis-1074	48	6	network	network	NOUN
fcis-1074	48	7	structure	structure	NOUN
fcis-1074	48	8	figure	figure	NOUN
fcis-1074	48	9	2	2	NUM
fcis-1074	48	10	.	.	PUNCT
fcis-1074	49	1	the	the	DET
fcis-1074	49	2	expansion	expansion	NOUN
fcis-1074	49	3	factor	factor	NOUN
fcis-1074	49	4	is	be	AUX
fcis-1074	49	5	multiplied	multiply	VERB
fcis-1074	49	6	figure	figure	NOUN
fcis-1074	49	7	3	3	NUM
fcis-1074	49	8	.	.	PUNCT
fcis-1074	49	9	dilation	dilation	NOUN
fcis-1074	49	10	factor	factor	NOUN
fcis-1074	49	11	is	be	AUX
fcis-1074	49	12	not	not	PART
fcis-1074	49	13	multiplied	multiply	VERB
fcis-1074	49	14	6	6	NUM
fcis-1074	49	15	therefore	therefore	ADV
fcis-1074	49	16	,	,	PUNCT
fcis-1074	49	17	the	the	DET
fcis-1074	49	18	above	above	ADJ
fcis-1074	49	19	problem	problem	NOUN
fcis-1074	49	20	is	be	AUX
fcis-1074	49	21	solved	solve	VERB
fcis-1074	49	22	by	by	ADP
fcis-1074	49	23	setting	set	VERB
fcis-1074	49	24	the	the	DET
fcis-1074	49	25	expansion	expansion	NOUN
fcis-1074	49	26	convolution	convolution	NOUN
fcis-1074	49	27	to	to	ADP
fcis-1074	49	28	a	a	DET
fcis-1074	49	29	continuous	continuous	ADJ
fcis-1074	49	30	expansion	expansion	NOUN
fcis-1074	49	31	factor	factor	NOUN
fcis-1074	49	32	that	that	PRON
fcis-1074	49	33	is	be	AUX
fcis-1074	49	34	not	not	PART
fcis-1074	49	35	multiplicative	multiplicative	ADJ
fcis-1074	49	36	,	,	PUNCT
fcis-1074	49	37	as	as	SCONJ
fcis-1074	49	38	shown	show	VERB
fcis-1074	49	39	in	in	ADP
fcis-1074	49	40	the	the	DET
fcis-1074	49	41	figure	figure	NOUN
fcis-1074	49	42	4	4	NUM
fcis-1074	49	43	.	.	PUNCT
fcis-1074	50	1	in	in	ADP
fcis-1074	50	2	this	this	DET
fcis-1074	50	3	paper	paper	NOUN
fcis-1074	50	4	,	,	PUNCT
fcis-1074	50	5	a	a	DET
fcis-1074	50	6	spatial	spatial	ADJ
fcis-1074	50	7	attention	attention	NOUN
fcis-1074	50	8	mechanism	mechanism	NOUN
fcis-1074	50	9	is	be	AUX
fcis-1074	50	10	added	add	VERB
fcis-1074	50	11	to	to	ADP
fcis-1074	50	12	the	the	DET
fcis-1074	50	13	generator	generator	NOUN
fcis-1074	50	14	,	,	PUNCT
fcis-1074	50	15	in	in	ADP
fcis-1074	50	16	which	which	PRON
fcis-1074	50	17	two	two	NUM
fcis-1074	50	18	feature	feature	NOUN
fcis-1074	50	19	maps	map	NOUN
fcis-1074	50	20	representing	represent	VERB
fcis-1074	50	21	different	different	ADJ
fcis-1074	50	22	information	information	NOUN
fcis-1074	50	23	are	be	AUX
fcis-1074	50	24	generated	generate	VERB
fcis-1074	50	25	based	base	VERB
fcis-1074	50	26	on	on	ADP
fcis-1074	50	27	channel	channel	NOUN
fcis-1074	50	28	-	-	PUNCT
fcis-1074	50	29	based	base	VERB
fcis-1074	50	30	global	global	ADJ
fcis-1074	50	31	average	average	ADJ
fcis-1074	50	32	pooling	pooling	NOUN
fcis-1074	50	33	and	and	CCONJ
fcis-1074	50	34	global	global	ADJ
fcis-1074	50	35	maximum	maximum	ADJ
fcis-1074	50	36	pooling	pool	VERB
fcis-1074	50	37	operations	operation	NOUN
fcis-1074	50	38	,	,	PUNCT
fcis-1074	50	39	and	and	CCONJ
fcis-1074	50	40	then	then	ADV
fcis-1074	50	41	combined	combine	VERB
fcis-1074	50	42	and	and	CCONJ
fcis-1074	50	43	downscaled	downscale	VERB
fcis-1074	50	44	to	to	ADP
fcis-1074	50	45	1	1	NUM
fcis-1074	50	46	channel	channel	NOUN
fcis-1074	50	47	number	number	NOUN
fcis-1074	50	48	by	by	ADP
fcis-1074	50	49	a	a	DET
fcis-1074	50	50	convolution	convolution	NOUN
fcis-1074	50	51	operation	operation	NOUN
fcis-1074	50	52	,	,	PUNCT
fcis-1074	50	53	and	and	CCONJ
fcis-1074	50	54	finally	finally	ADV
fcis-1074	50	55	a	a	DET
fcis-1074	50	56	weight	weight	NOUN
fcis-1074	50	57	map	map	NOUN
fcis-1074	50	58	is	be	AUX
fcis-1074	50	59	generated	generate	VERB
fcis-1074	50	60	by	by	ADP
fcis-1074	50	61	a	a	DET
fcis-1074	50	62	sigmoid	sigmoid	NOUN
fcis-1074	50	63	operation	operation	NOUN
fcis-1074	50	64	,	,	PUNCT
fcis-1074	50	65	i.e.	i.e.	X
fcis-1074	50	66	,	,	PUNCT
fcis-1074	50	67	a	a	DET
fcis-1074	50	68	weight	weight	NOUN
fcis-1074	50	69	mask	mask	NOUN
fcis-1074	50	70	is	be	AUX
fcis-1074	50	71	generated	generate	VERB
fcis-1074	50	72	for	for	ADP
fcis-1074	50	73	each	each	DET
fcis-1074	50	74	location	location	NOUN
fcis-1074	50	75	and	and	CCONJ
fcis-1074	50	76	weighted	weight	VERB
fcis-1074	50	77	to	to	PART
fcis-1074	50	78	output	output	NOUN
fcis-1074	50	79	.	.	PUNCT
fcis-1074	51	1	then	then	ADV
fcis-1074	51	2	superimposed	superimpose	VERB
fcis-1074	51	3	back	back	ADV
fcis-1074	51	4	to	to	ADP
fcis-1074	51	5	the	the	DET
fcis-1074	51	6	original	original	ADJ
fcis-1074	51	7	input	input	NOUN
fcis-1074	51	8	feature	feature	NOUN
fcis-1074	51	9	map	map	NOUN
fcis-1074	51	10	,	,	PUNCT
fcis-1074	51	11	thus	thus	ADV
fcis-1074	51	12	making	make	VERB
fcis-1074	51	13	the	the	DET
fcis-1074	51	14	target	target	NOUN
fcis-1074	51	15	region	region	NOUN
fcis-1074	51	16	enhanced	enhance	VERB
fcis-1074	51	17	,	,	PUNCT
fcis-1074	51	18	the	the	DET
fcis-1074	51	19	module	module	NOUN
fcis-1074	51	20	is	be	AUX
fcis-1074	51	21	shown	show	VERB
fcis-1074	51	22	in	in	ADP
fcis-1074	51	23	figure	figure	NOUN
fcis-1074	51	24	(	(	PUNCT
fcis-1074	51	25	4	4	NUM
fcis-1074	51	26	)	)	PUNCT
fcis-1074	51	27	below	below	ADV
fcis-1074	51	28	.	.	PUNCT
fcis-1074	52	1	for	for	ADP
fcis-1074	52	2	the	the	DET
fcis-1074	52	3	generator	generator	NOUN
fcis-1074	52	4	's	's	PART
fcis-1074	52	5	task	task	NOUN
fcis-1074	52	6	of	of	ADP
fcis-1074	52	7	removing	remove	VERB
fcis-1074	52	8	fog	fog	NOUN
fcis-1074	52	9	from	from	ADP
fcis-1074	52	10	the	the	DET
fcis-1074	52	11	image	image	NOUN
fcis-1074	52	12	,	,	PUNCT
fcis-1074	52	13	the	the	DET
fcis-1074	52	14	spatial	spatial	ADJ
fcis-1074	52	15	attention	attention	NOUN
fcis-1074	52	16	mechanism	mechanism	NOUN
fcis-1074	52	17	enables	enable	VERB
fcis-1074	52	18	the	the	DET
fcis-1074	52	19	generator	generator	NOUN
fcis-1074	52	20	to	to	PART
fcis-1074	52	21	spatially	spatially	ADV
fcis-1074	52	22	focus	focus	VERB
fcis-1074	52	23	its	its	PRON
fcis-1074	52	24	attention	attention	NOUN
fcis-1074	52	25	on	on	ADP
fcis-1074	52	26	the	the	DET
fcis-1074	52	27	foggy	foggy	ADJ
fcis-1074	52	28	locations	location	NOUN
fcis-1074	52	29	and	and	CCONJ
fcis-1074	52	30	enhance	enhance	VERB
fcis-1074	52	31	the	the	DET
fcis-1074	52	32	recognition	recognition	NOUN
fcis-1074	52	33	of	of	ADP
fcis-1074	52	34	fog	fog	NOUN
fcis-1074	52	35	with	with	ADP
fcis-1074	52	36	different	different	ADJ
fcis-1074	52	37	concentrations	concentration	NOUN
fcis-1074	52	38	in	in	ADP
fcis-1074	52	39	the	the	DET
fcis-1074	52	40	image	image	NOUN
fcis-1074	52	41	,	,	PUNCT
fcis-1074	52	42	thus	thus	ADV
fcis-1074	52	43	achieving	achieve	VERB
fcis-1074	52	44	better	well	ADJ
fcis-1074	52	45	defogging	defogging	NOUN
fcis-1074	52	46	results	result	NOUN
fcis-1074	52	47	.	.	PUNCT
fcis-1074	53	1	2.2	2.2	NUM
fcis-1074	53	2	.	.	PUNCT
fcis-1074	53	3	discriminator	discriminator	NOUN
fcis-1074	54	1	d	d	PROPN
fcis-1074	54	2	the	the	DET
fcis-1074	54	3	discriminator	discriminator	NOUN
fcis-1074	54	4	is	be	AUX
fcis-1074	54	5	a	a	DET
fcis-1074	54	6	fully	fully	ADV
fcis-1074	54	7	convolutional	convolutional	ADJ
fcis-1074	54	8	network	network	NOUN
fcis-1074	54	9	with	with	ADP
fcis-1074	54	10	the	the	DET
fcis-1074	54	11	network	network	NOUN
fcis-1074	54	12	structure	structure	NOUN
fcis-1074	54	13	shown	show	VERB
fcis-1074	54	14	in	in	ADP
fcis-1074	54	15	fig	fig	NOUN
fcis-1074	54	16	.	.	PUNCT
fcis-1074	55	1	5	5	NUM
fcis-1074	55	2	,	,	PUNCT
fcis-1074	55	3	which	which	PRON
fcis-1074	55	4	uses	use	VERB
fcis-1074	55	5	a	a	DET
fcis-1074	55	6	patchgan	patchgan	NOUN
fcis-1074	55	7	with	with	ADP
fcis-1074	55	8	block	block	NOUN
fcis-1074	55	9	determination	determination	NOUN
fcis-1074	55	10	,	,	PUNCT
fcis-1074	55	11	consisting	consist	VERB
fcis-1074	55	12	of	of	ADP
fcis-1074	55	13	six	six	NUM
fcis-1074	55	14	convolutional	convolutional	ADJ
fcis-1074	55	15	blocks	block	NOUN
fcis-1074	55	16	containing	contain	VERB
fcis-1074	55	17	six	six	NUM
fcis-1074	55	18	4×4	4×4	NUM
fcis-1074	55	19	convolutions	convolution	NOUN
fcis-1074	55	20	,	,	PUNCT
fcis-1074	55	21	four	four	NUM
fcis-1074	55	22	instance	instance	NOUN
fcis-1074	55	23	normalization	normalization	NOUN
fcis-1074	55	24	(	(	PUNCT
fcis-1074	55	25	batchnorm	batchnorm	NOUN
fcis-1074	55	26	)	)	PUNCT
fcis-1074	55	27	layers	layer	NOUN
fcis-1074	55	28	,	,	PUNCT
fcis-1074	55	29	and	and	CCONJ
fcis-1074	55	30	the	the	DET
fcis-1074	55	31	leaky	leaky	ADJ
fcis-1074	55	32	relu	relu	NOUN
fcis-1074	55	33	activation	activation	NOUN
fcis-1074	55	34	function	function	NOUN
fcis-1074	55	35	.	.	PUNCT
fcis-1074	56	1	the	the	DET
fcis-1074	56	2	output	output	NOUN
fcis-1074	56	3	of	of	ADP
fcis-1074	56	4	the	the	DET
fcis-1074	56	5	discriminator	discriminator	NOUN
fcis-1074	56	6	is	be	AUX
fcis-1074	56	7	a	a	DET
fcis-1074	56	8	matrix	matrix	NOUN
fcis-1074	56	9	,	,	PUNCT
fcis-1074	56	10	and	and	CCONJ
fcis-1074	56	11	the	the	DET
fcis-1074	56	12	value	value	NOUN
fcis-1074	56	13	of	of	ADP
fcis-1074	56	14	each	each	DET
fcis-1074	56	15	pixel	pixel	NOUN
fcis-1074	56	16	point	point	NOUN
fcis-1074	56	17	in	in	ADP
fcis-1074	56	18	the	the	DET
fcis-1074	56	19	matrix	matrix	NOUN
fcis-1074	56	20	corresponds	correspond	VERB
fcis-1074	56	21	to	to	ADP
fcis-1074	56	22	a	a	DET
fcis-1074	56	23	34×34	34×34	NUM
fcis-1074	56	24	image	image	NOUN
fcis-1074	56	25	block	block	NOUN
fcis-1074	56	26	(	(	PUNCT
fcis-1074	56	27	patches	patch	NOUN
fcis-1074	56	28	)	)	PUNCT
fcis-1074	56	29	of	of	ADP
fcis-1074	56	30	the	the	DET
fcis-1074	56	31	input	input	NOUN
fcis-1074	56	32	image	image	NOUN
fcis-1074	56	33	,	,	PUNCT
fcis-1074	56	34	which	which	PRON
fcis-1074	56	35	is	be	AUX
fcis-1074	56	36	used	use	VERB
fcis-1074	56	37	to	to	PART
fcis-1074	56	38	determine	determine	VERB
fcis-1074	56	39	the	the	DET
fcis-1074	56	40	true	true	ADJ
fcis-1074	56	41	/	/	SYM
fcis-1074	56	42	false	false	ADJ
fcis-1074	56	43	of	of	ADP
fcis-1074	56	44	each	each	DET
fcis-1074	56	45	patch	patch	NOUN
fcis-1074	56	46	,	,	PUNCT
fcis-1074	56	47	and	and	CCONJ
fcis-1074	56	48	finally	finally	ADV
fcis-1074	56	49	the	the	DET
fcis-1074	56	50	mean	mean	ADJ
fcis-1074	56	51	value	value	NOUN
fcis-1074	56	52	of	of	ADP
fcis-1074	56	53	the	the	DET
fcis-1074	56	54	output	output	NOUN
fcis-1074	56	55	matrix	matrix	NOUN
fcis-1074	56	56	is	be	AUX
fcis-1074	56	57	taken	take	VERB
fcis-1074	56	58	as	as	ADP
fcis-1074	56	59	the	the	DET
fcis-1074	56	60	output	output	NOUN
fcis-1074	56	61	of	of	ADP
fcis-1074	56	62	true	true	ADJ
fcis-1074	56	63	/	/	SYM
fcis-1074	56	64	false	false	ADJ
fcis-1074	56	65	.	.	PUNCT
fcis-1074	57	1	the	the	DET
fcis-1074	57	2	difference	difference	NOUN
fcis-1074	57	3	judgment	judgment	NOUN
fcis-1074	57	4	by	by	ADP
fcis-1074	57	5	each	each	DET
fcis-1074	57	6	patch	patch	NOUN
fcis-1074	57	7	changes	change	VERB
fcis-1074	57	8	the	the	DET
fcis-1074	57	9	traditional	traditional	ADJ
fcis-1074	57	10	discriminator	discriminator	NOUN
fcis-1074	57	11	's	's	PART
fcis-1074	57	12	"	"	PUNCT
fcis-1074	57	13	one	one	NUM
fcis-1074	57	14	-	-	PUNCT
fcis-1074	57	15	word	word	NOUN
fcis-1074	57	16	"	"	PUNCT
fcis-1074	57	17	discriminative	discriminative	NOUN
fcis-1074	57	18	result	result	NOUN
fcis-1074	57	19	,	,	PUNCT
fcis-1074	57	20	realizes	realize	VERB
fcis-1074	57	21	the	the	DET
fcis-1074	57	22	extraction	extraction	NOUN
fcis-1074	57	23	and	and	CCONJ
fcis-1074	57	24	characterization	characterization	NOUN
fcis-1074	57	25	of	of	ADP
fcis-1074	57	26	local	local	ADJ
fcis-1074	57	27	image	image	NOUN
fcis-1074	57	28	features	feature	NOUN
fcis-1074	57	29	,	,	PUNCT
fcis-1074	57	30	and	and	CCONJ
fcis-1074	57	31	helps	help	VERB
fcis-1074	57	32	to	to	PART
fcis-1074	57	33	maintain	maintain	VERB
fcis-1074	57	34	the	the	DET
fcis-1074	57	35	high	high	ADJ
fcis-1074	57	36	resolution	resolution	NOUN
fcis-1074	57	37	and	and	CCONJ
fcis-1074	57	38	detail	detail	NOUN
fcis-1074	57	39	of	of	ADP
fcis-1074	57	40	the	the	DET
fcis-1074	57	41	image	image	NOUN
fcis-1074	57	42	.	.	PUNCT
fcis-1074	58	1	figure	figure	NOUN
fcis-1074	58	2	4	4	NUM
fcis-1074	58	3	.	.	PUNCT
fcis-1074	59	1	network	network	NOUN
fcis-1074	59	2	structure	structure	NOUN
fcis-1074	59	3	of	of	ADP
fcis-1074	59	4	spatial	spatial	ADJ
fcis-1074	59	5	attention	attention	NOUN
fcis-1074	59	6	mechanism	mechanism	NOUN
fcis-1074	59	7	figure	figure	NOUN
fcis-1074	59	8	5	5	NUM
fcis-1074	59	9	.	.	PUNCT
fcis-1074	60	1	discriminator	discriminator	NOUN
fcis-1074	60	2	network	network	NOUN
fcis-1074	60	3	structure	structure	NOUN
fcis-1074	60	4	3	3	NUM
fcis-1074	60	5	.	.	PUNCT
fcis-1074	61	1	loss	loss	NOUN
fcis-1074	61	2	function	function	NOUN
fcis-1074	61	3	3.1	3.1	NUM
fcis-1074	61	4	.	.	PUNCT
fcis-1074	62	1	adversarial	adversarial	ADJ
fcis-1074	62	2	loss	loss	NOUN
fcis-1074	62	3	(	(	PUNCT
fcis-1074	62	4	adversarial	adversarial	ADJ
fcis-1074	62	5	loss	loss	NOUN
fcis-1074	62	6	)	)	PUNCT
fcis-1074	62	7	in	in	ADP
fcis-1074	62	8	order	order	NOUN
fcis-1074	62	9	to	to	PART
fcis-1074	62	10	solve	solve	VERB
fcis-1074	62	11	the	the	DET
fcis-1074	62	12	problem	problem	NOUN
fcis-1074	62	13	of	of	ADP
fcis-1074	62	14	slow	slow	ADJ
fcis-1074	62	15	convergence	convergence	NOUN
fcis-1074	62	16	and	and	CCONJ
fcis-1074	62	17	possible	possible	ADJ
fcis-1074	62	18	training	training	NOUN
fcis-1074	62	19	instability	instability	NOUN
fcis-1074	62	20	during	during	ADP
fcis-1074	62	21	training	training	NOUN
fcis-1074	62	22	,	,	PUNCT
fcis-1074	62	23	the	the	DET
fcis-1074	62	24	adversarial	adversarial	ADJ
fcis-1074	62	25	loss	loss	NOUN
fcis-1074	62	26	function	function	NOUN
fcis-1074	62	27	uses	use	VERB
fcis-1074	62	28	wgan	wgan	ADJ
fcis-1074	62	29	-	-	PUNCT
fcis-1074	62	30	gp	gp	NOUN
fcis-1074	62	31	with	with	ADP
fcis-1074	62	32	gradient	gradient	ADJ
fcis-1074	62	33	penalty	penalty	NOUN
fcis-1074	62	34	[	[	X
fcis-1074	62	35	15	15	NUM
fcis-1074	62	36	]	]	X
fcis-1074	62	37	,	,	PUNCT
fcis-1074	62	38	which	which	PRON
fcis-1074	62	39	is	be	AUX
fcis-1074	62	40	calculated	calculate	VERB
fcis-1074	62	41	as	as	SCONJ
fcis-1074	62	42	follows	follow	VERB
fcis-1074	62	43	.	.	PUNCT
fcis-1074	63	1	~	~	PUNCT
fcis-1074	63	2	~	~	PUNCT
fcis-1074	63	3	~	~	PUNCT
fcis-1074	63	4	[	[	PUNCT
fcis-1074	63	5	(	(	PUNCT
fcis-1074	63	6	)	)	PUNCT
fcis-1074	63	7	]	]	PUNCT
fcis-1074	63	8	[	[	PUNCT
fcis-1074	63	9	(	(	PUNCT
fcis-1074	63	10	)	)	PUNCT
fcis-1074	63	11	]	]	PUNCT
fcis-1074	63	12	[	[	PUNCT
fcis-1074	63	13	1	1	NUM
fcis-1074	63	14	]	]	X
fcis-1074	63	15	(	(	PUNCT
fcis-1074	63	16	)	)	PUNCT
fcis-1074	63	17	g	g	PROPN
fcis-1074	63	18	r	r	NOUN
fcis-1074	63	19	adv	adv	PROPN
fcis-1074	63	20	x	x	X
fcis-1074	63	21	x	x	PUNCT
fcis-1074	63	22	x	x	X
fcis-1074	63	23	p	p	X
fcis-1074	63	24	d	d	X
fcis-1074	63	25	x	x	X
fcis-1074	63	26	d	d	NOUN
fcis-1074	63	27	x	x	X
fcis-1074	63	28	xp	xp	INTJ
fcis-1074	63	29	p	p	PROPN
fcis-1074	63	30	d	d	X
fcis-1074	63	31	xl	xl	PROPN
fcis-1074	63	32	e	e	PROPN
fcis-1074	63	33	e	e	ADP
fcis-1074	63	34	e	e	NOUN
fcis-1074	63	35			AUX
fcis-1074	63	36	=	=	PUNCT
fcis-1074	63	37	−	−	NOUN
fcis-1074	63	38	+	+	CCONJ
fcis-1074	63	39	−	−	PROPN
fcis-1074	63	40	(	(	PUNCT
fcis-1074	63	41	1	1	NUM
fcis-1074	63	42	)	)	PUNCT
fcis-1074	63	43	where	where	SCONJ
fcis-1074	63	44	pr	pr	NOUN
fcis-1074	63	45	denotes	denote	VERB
fcis-1074	63	46	the	the	DET
fcis-1074	63	47	real	real	PROPN
fcis-1074	63	48	fog	fog	PROPN
fcis-1074	63	49	-	-	PUNCT
fcis-1074	63	50	free	free	ADJ
fcis-1074	63	51	image	image	NOUN
fcis-1074	63	52	data	datum	NOUN
fcis-1074	63	53	,	,	PUNCT
fcis-1074	63	54	pg	pg	PROPN
fcis-1074	63	55	denotes	denote	VERB
fcis-1074	63	56	the	the	DET
fcis-1074	63	57	generated	generate	VERB
fcis-1074	63	58	fog	fog	PROPN
fcis-1074	63	59	-	-	PUNCT
fcis-1074	63	60	free	free	ADJ
fcis-1074	63	61	image	image	NOUN
fcis-1074	63	62	data	datum	NOUN
fcis-1074	63	63	,	,	PUNCT
fcis-1074	63	64	xx	xx	NUM
fcis-1074	63	65	gr	gr	NUM
fcis-1074	63	66	)	)	PUNCT
fcis-1074	63	67	1	1	NUM
fcis-1074	63	68	(	(	PUNCT
fcis-1074	63	69			NOUN
fcis-1074	63	70	−+=	−+=	NOUN
fcis-1074	63	71	,	,	PUNCT
fcis-1074	63	72	where	where	SCONJ
fcis-1074	63	73	）	）	PUNCT
fcis-1074	63	74	（	（	PROPN
fcis-1074	63	75	1,0	1,0	NUM
fcis-1074	63	76	denotes	denote	VERB
fcis-1074	63	77	the	the	DET
fcis-1074	63	78	randomly	randomly	ADV
fcis-1074	63	79	selected	select	VERB
fcis-1074	63	80	data	data	NOUN
fcis-1074	63	81	samples	sample	NOUN
fcis-1074	63	82	in	in	ADP
fcis-1074	63	83	pr	pr	NOUN
fcis-1074	63	84	and	and	CCONJ
fcis-1074	63	85	pg	pg	VERB
fcis-1074	63	86	,	,	PUNCT
fcis-1074	64	1	d	d	PROPN
fcis-1074	64	2	denotes	denote	VERB
fcis-1074	64	3	the	the	DET
fcis-1074	64	4	probability	probability	NOUN
fcis-1074	64	5	that	that	SCONJ
fcis-1074	64	6	the	the	DET
fcis-1074	64	7	discriminator	discriminator	NOUN
fcis-1074	64	8	discriminates	discriminate	VERB
fcis-1074	64	9	the	the	DET
fcis-1074	64	10	input	input	NOUN
fcis-1074	64	11	image	image	NOUN
fcis-1074	64	12	as	as	ADP
fcis-1074	64	13	the	the	DET
fcis-1074	64	14	real	real	ADJ
fcis-1074	64	15	fogfree	fogfree	NOUN
fcis-1074	64	16	image	image	NOUN
fcis-1074	64	17	,	,	PUNCT
fcis-1074	64	18	and	and	CCONJ
fcis-1074	64	19	e	e	NOUN
fcis-1074	64	20	denotes	denote	VERB
fcis-1074	64	21	the	the	DET
fcis-1074	64	22	average	average	ADJ
fcis-1074	64	23	statistics	statistic	NOUN
fcis-1074	64	24	of	of	ADP
fcis-1074	64	25	the	the	DET
fcis-1074	64	26	discriminator	discriminator	NOUN
fcis-1074	64	27	on	on	ADP
fcis-1074	64	28	the	the	DET
fcis-1074	64	29	discriminated	discriminate	VERB
fcis-1074	64	30	results	result	NOUN
fcis-1074	64	31	.	.	PUNCT
fcis-1074	65	1	3.2	3.2	NUM
fcis-1074	65	2	.	.	PUNCT
fcis-1074	65	3	content	content	NOUN
fcis-1074	65	4	loss	loss	NOUN
fcis-1074	65	5	in	in	ADP
fcis-1074	65	6	this	this	DET
fcis-1074	65	7	paper	paper	NOUN
fcis-1074	65	8	,	,	PUNCT
fcis-1074	65	9	we	we	PRON
fcis-1074	65	10	adopt	adopt	VERB
fcis-1074	65	11	the	the	DET
fcis-1074	65	12	content	content	NOUN
fcis-1074	65	13	loss	loss	NOUN
fcis-1074	65	14	based	base	VERB
fcis-1074	65	15	on	on	ADP
fcis-1074	65	16	l1	l1	PROPN
fcis-1074	65	17	loss	loss	NOUN
fcis-1074	65	18	,	,	PUNCT
fcis-1074	65	19	which	which	PRON
fcis-1074	65	20	can	can	AUX
fcis-1074	65	21	identify	identify	VERB
fcis-1074	65	22	low	low	ADJ
fcis-1074	65	23	-	-	PUNCT
fcis-1074	65	24	frequency	frequency	NOUN
fcis-1074	65	25	information	information	NOUN
fcis-1074	65	26	more	more	ADV
fcis-1074	65	27	effectively	effectively	ADV
fcis-1074	65	28	,	,	PUNCT
fcis-1074	65	29	reduce	reduce	VERB
fcis-1074	65	30	the	the	DET
fcis-1074	65	31	artifact	artifact	ADJ
fcis-1074	65	32	phenomenon	phenomenon	NOUN
fcis-1074	65	33	when	when	SCONJ
fcis-1074	65	34	the	the	DET
fcis-1074	65	35	generator	generator	NOUN
fcis-1074	65	36	generates	generate	VERB
fcis-1074	65	37	images	image	NOUN
fcis-1074	65	38	,	,	PUNCT
fcis-1074	65	39	and	and	CCONJ
fcis-1074	65	40	make	make	VERB
fcis-1074	65	41	the	the	DET
fcis-1074	65	42	generated	generate	VERB
fcis-1074	65	43	image	image	NOUN
fcis-1074	65	44	content	content	NOUN
fcis-1074	65	45	more	more	ADV
fcis-1074	65	46	realistic	realistic	ADJ
fcis-1074	65	47	,	,	PUNCT
fcis-1074	65	48	and	and	CCONJ
fcis-1074	65	49	its	its	PRON
fcis-1074	65	50	calculation	calculation	NOUN
fcis-1074	65	51	formula	formula	NOUN
fcis-1074	65	52	is	be	AUX
fcis-1074	65	53	as	as	SCONJ
fcis-1074	65	54	follows	follow	VERB
fcis-1074	65	55	.	.	PUNCT
fcis-1074	66	1	,	,	PUNCT
fcis-1074	66	2	,	,	PUNCT
fcis-1074	66	3	2	2	NUM
fcis-1074	66	4	1	1	NUM
fcis-1074	66	5	1	1	NUM
fcis-1074	66	6	,	,	PUNCT
fcis-1074	66	7	,	,	PUNCT
fcis-1074	66	8	1	1	NUM
fcis-1074	66	9	,	,	PUNCT
fcis-1074	66	10	,	,	PUNCT
fcis-1074	66	11	,	,	PUNCT
fcis-1074	66	12	,	,	PUNCT
fcis-1074	66	13	(	(	PUNCT
fcis-1074	66	14	(	(	PUNCT
fcis-1074	66	15	)	)	PUNCT
fcis-1074	66	16	)	)	PUNCT
fcis-1074	66	17	(	(	PUNCT
fcis-1074	66	18	)	)	PUNCT
fcis-1074	66	19	(	(	PUNCT
fcis-1074	66	20	)	)	PUNCT
fcis-1074	67	1	i	i	PRON
fcis-1074	67	2	j	j	VERB
fcis-1074	68	1	i	i	PRON
fcis-1074	68	2	j	j	NOUN
fcis-1074	69	1	x	x	PUNCT
fcis-1074	69	2	x	x	X
fcis-1074	69	3	yi	yi	INTJ
fcis-1074	70	1	ji	ji	PROPN
fcis-1074	71	1	j	j	PROPN
fcis-1074	71	2	w	w	PROPN
fcis-1074	71	3	h	h	NOUN
fcis-1074	72	1	bs	bs	INTJ
fcis-1074	73	1	i	i	PRON
fcis-1074	73	2	j	j	VERB
fcis-1074	74	1	i	i	PRON
fcis-1074	74	2	jx	jx	PROPN
fcis-1074	75	1	y	y	PROPN
fcis-1074	75	2	g	g	PROPN
fcis-1074	75	3	x	x	VERB
fcis-1074	75	4	y	y	PROPN
fcis-1074	75	5	g	g	PROPN
fcis-1074	75	6	iil	iil	PROPN
fcis-1074	75	7	w	w	PROPN
fcis-1074	75	8	h	h	PROPN
fcis-1074	75	9			X
fcis-1074	76	1	=	=	PUNCT
fcis-1074	76	2	=	=	PUNCT
fcis-1074	76	3	=	=	PUNCT
fcis-1074	76	4	−	−	PROPN
fcis-1074	76	5			NUM
fcis-1074	76	6			X
fcis-1074	76	7	(	(	PUNCT
fcis-1074	76	8	2	2	NUM
fcis-1074	76	9	)	)	PUNCT
fcis-1074	76	10	where	where	SCONJ
fcis-1074	76	11	pr	pr	NOUN
fcis-1074	76	12	denotes	denote	VERB
fcis-1074	76	13	the	the	DET
fcis-1074	76	14	real	real	PROPN
fcis-1074	76	15	fog	fog	PROPN
fcis-1074	76	16	-	-	PUNCT
fcis-1074	76	17	free	free	ADJ
fcis-1074	76	18	image	image	NOUN
fcis-1074	76	19	data	datum	NOUN
fcis-1074	76	20	,	,	PUNCT
fcis-1074	76	21	pg	pg	PROPN
fcis-1074	76	22	denotes	denote	VERB
fcis-1074	76	23	the	the	DET
fcis-1074	76	24	generated	generate	VERB
fcis-1074	76	25	fog	fog	PROPN
fcis-1074	76	26	-	-	PUNCT
fcis-1074	76	27	free	free	ADJ
fcis-1074	76	28	image	image	NOUN
fcis-1074	76	29	data	datum	NOUN
fcis-1074	76	30	,	,	PUNCT
fcis-1074	76	31	xx	xx	NUM
fcis-1074	76	32	gr	gr	NUM
fcis-1074	76	33	)	)	PUNCT
fcis-1074	76	34	1	1	NUM
fcis-1074	76	35	(	(	PUNCT
fcis-1074	76	36			NOUN
fcis-1074	76	37	−+=	−+=	NOUN
fcis-1074	76	38	,	,	PUNCT
fcis-1074	76	39	where	where	SCONJ
fcis-1074	76	40	）	）	PUNCT
fcis-1074	76	41	（	（	PROPN
fcis-1074	76	42	1,0	1,0	NUM
fcis-1074	76	43	denotes	denote	VERB
fcis-1074	76	44	the	the	DET
fcis-1074	76	45	randomly	randomly	ADV
fcis-1074	76	46	selected	select	VERB
fcis-1074	76	47	data	data	NOUN
fcis-1074	76	48	samples	sample	NOUN
fcis-1074	76	49	in	in	ADP
fcis-1074	76	50	pr	pr	NOUN
fcis-1074	76	51	and	and	CCONJ
fcis-1074	76	52	pg	pg	VERB
fcis-1074	76	53	,	,	PUNCT
fcis-1074	77	1	d	d	PROPN
fcis-1074	77	2	denotes	denote	VERB
fcis-1074	77	3	the	the	DET
fcis-1074	77	4	probability	probability	NOUN
fcis-1074	77	5	that	that	SCONJ
fcis-1074	77	6	the	the	DET
fcis-1074	77	7	discriminator	discriminator	NOUN
fcis-1074	77	8	discriminates	discriminate	VERB
fcis-1074	77	9	the	the	DET
fcis-1074	77	10	input	input	NOUN
fcis-1074	77	11	image	image	NOUN
fcis-1074	77	12	as	as	ADP
fcis-1074	77	13	the	the	DET
fcis-1074	77	14	real	real	ADJ
fcis-1074	77	15	fogfree	fogfree	NOUN
fcis-1074	77	16	image	image	NOUN
fcis-1074	77	17	,	,	PUNCT
fcis-1074	77	18	and	and	CCONJ
fcis-1074	77	19	e	e	NOUN
fcis-1074	77	20	denotes	denote	VERB
fcis-1074	77	21	the	the	DET
fcis-1074	77	22	average	average	ADJ
fcis-1074	77	23	statistics	statistic	NOUN
fcis-1074	77	24	of	of	ADP
fcis-1074	77	25	the	the	DET
fcis-1074	77	26	discriminator	discriminator	NOUN
fcis-1074	77	27	on	on	ADP
fcis-1074	77	28	the	the	DET
fcis-1074	77	29	discriminated	discriminate	VERB
fcis-1074	77	30	results	result	NOUN
fcis-1074	77	31	.	.	PUNCT
fcis-1074	78	1	3.3	3.3	NUM
fcis-1074	78	2	.	.	PUNCT
fcis-1074	79	1	content	content	NOUN
fcis-1074	79	2	loss	loss	PROPN
fcis-1074	79	3	bce	bce	PROPN
fcis-1074	79	4	loss	loss	NOUN
fcis-1074	79	5	[	[	X
fcis-1074	79	6	16	16	NUM
fcis-1074	79	7	]	]	PUNCT
fcis-1074	79	8	is	be	AUX
fcis-1074	79	9	a	a	DET
fcis-1074	79	10	loss	loss	NOUN
fcis-1074	79	11	function	function	NOUN
fcis-1074	79	12	based	base	VERB
fcis-1074	79	13	on	on	ADP
fcis-1074	79	14	pixel	pixel	PROPN
fcis-1074	79	15	points	point	NOUN
fcis-1074	79	16	,	,	PUNCT
fcis-1074	79	17	which	which	PRON
fcis-1074	79	18	is	be	AUX
fcis-1074	79	19	predicted	predict	VERB
fcis-1074	79	20	for	for	ADP
fcis-1074	79	21	each	each	DET
fcis-1074	79	22	pixel	pixel	NOUN
fcis-1074	79	23	and	and	CCONJ
fcis-1074	79	24	is	be	AUX
fcis-1074	79	25	calculated	calculate	VERB
fcis-1074	79	26	as	as	SCONJ
fcis-1074	79	27	follows	follow	VERB
fcis-1074	79	28	.	.	PUNCT
fcis-1074	80	1			X
fcis-1074	81	1	−−+−=	−−+−=	NOUN
fcis-1074	81	2	i	i	PRON
fcis-1074	81	3	bce	bce	PROPN
fcis-1074	81	4	)	)	PUNCT
fcis-1074	81	5	)	)	PUNCT
fcis-1074	81	6	)	)	PUNCT
fcis-1074	82	1	i(olog())i(t())i(olog()i(t(n	i(olog())i(t())i(olog()i(t(n	PROPN
fcis-1074	82	2	/	/	SYM
fcis-1074	82	3	l	l	PROPN
fcis-1074	82	4	111	111	NUM
fcis-1074	82	5	(	(	PUNCT
fcis-1074	82	6	3	3	NUM
fcis-1074	82	7	)	)	PUNCT
fcis-1074	82	8	where	where	SCONJ
fcis-1074	82	9	,	,	PUNCT
fcis-1074	82	10	denotes	denote	VERB
fcis-1074	82	11	the	the	DET
fcis-1074	82	12	target	target	NOUN
fcis-1074	82	13	value	value	NOUN
fcis-1074	82	14	,	,	PUNCT
fcis-1074	82	15	denotes	denote	VERB
fcis-1074	82	16	the	the	DET
fcis-1074	82	17	predicted	predict	VERB
fcis-1074	82	18	value	value	NOUN
fcis-1074	82	19	,	,	PUNCT
fcis-1074	82	20	and	and	CCONJ
fcis-1074	82	21	is	be	AUX
fcis-1074	82	22	the	the	DET
fcis-1074	82	23	pixel	pixel	PROPN
fcis-1074	82	24	point	point	NOUN
fcis-1074	82	25	.	.	PUNCT
fcis-1074	83	1	for	for	ADP
fcis-1074	83	2	the	the	DET
fcis-1074	83	3	task	task	NOUN
fcis-1074	83	4	of	of	ADP
fcis-1074	83	5	defogging	defogging	NOUN
fcis-1074	83	6	in	in	ADP
fcis-1074	83	7	this	this	DET
fcis-1074	83	8	thesis	thesis	NOUN
fcis-1074	83	9	,	,	PUNCT
fcis-1074	83	10	denotes	denote	VERB
fcis-1074	83	11	the	the	DET
fcis-1074	83	12	pixel	pixel	PROPN
fcis-1074	83	13	point	point	NOUN
fcis-1074	83	14	value	value	NOUN
fcis-1074	83	15	of	of	ADP
fcis-1074	83	16	the	the	DET
fcis-1074	83	17	clear	clear	ADJ
fcis-1074	83	18	and	and	CCONJ
fcis-1074	83	19	fog	fog	NOUN
fcis-1074	83	20	-	-	PUNCT
fcis-1074	83	21	free	free	ADJ
fcis-1074	83	22	image	image	NOUN
fcis-1074	83	23	,	,	PUNCT
fcis-1074	83	24	and	and	CCONJ
fcis-1074	83	25	denotes	denote	VERB
fcis-1074	83	26	the	the	DET
fcis-1074	83	27	pixel	pixel	PROPN
fcis-1074	83	28	point	point	NOUN
fcis-1074	83	29	value	value	NOUN
fcis-1074	83	30	of	of	ADP
fcis-1074	83	31	the	the	DET
fcis-1074	83	32	generated	generate	VERB
fcis-1074	83	33	image	image	NOUN
fcis-1074	83	34	of	of	ADP
fcis-1074	83	35	the	the	DET
fcis-1074	83	36	corresponding	corresponding	ADJ
fcis-1074	83	37	generator	generator	NOUN
fcis-1074	83	38	,	,	PUNCT
fcis-1074	83	39	which	which	PRON
fcis-1074	83	40	can	can	AUX
fcis-1074	83	41	distinguish	distinguish	VERB
fcis-1074	83	42	the	the	DET
fcis-1074	83	43	real	real	ADJ
fcis-1074	83	44	clear	clear	ADJ
fcis-1074	83	45	and	and	CCONJ
fcis-1074	83	46	fog	fog	NOUN
fcis-1074	83	47	-	-	PUNCT
fcis-1074	83	48	free	free	ADJ
fcis-1074	83	49	image	image	NOUN
fcis-1074	83	50	from	from	ADP
fcis-1074	83	51	the	the	DET
fcis-1074	83	52	generated	generate	VERB
fcis-1074	83	53	image	image	NOUN
fcis-1074	83	54	more	more	ADV
fcis-1074	83	55	precisely	precisely	ADV
fcis-1074	83	56	based	base	VERB
fcis-1074	83	57	on	on	ADP
fcis-1074	83	58	pixel	pixel	PROPN
fcis-1074	83	59	points	point	NOUN
fcis-1074	83	60	,	,	PUNCT
fcis-1074	83	61	making	make	VERB
fcis-1074	83	62	the	the	DET
fcis-1074	83	63	generated	generate	VERB
fcis-1074	83	64	image	image	NOUN
fcis-1074	83	65	of	of	ADP
fcis-1074	83	66	the	the	DET
fcis-1074	83	67	generator	generator	NOUN
fcis-1074	83	68	more	more	ADV
fcis-1074	83	69	detailed	detailed	ADJ
fcis-1074	83	70	and	and	CCONJ
fcis-1074	83	71	clearer	clear	ADJ
fcis-1074	83	72	,	,	PUNCT
fcis-1074	83	73	and	and	CCONJ
fcis-1074	83	74	the	the	DET
fcis-1074	83	75	discriminator	discriminator	NOUN
fcis-1074	83	76	more	more	ADV
fcis-1074	83	77	precise	precise	ADJ
fcis-1074	83	78	based	base	VERB
fcis-1074	83	79	on	on	ADP
fcis-1074	83	80	pixel	pixel	PROPN
fcis-1074	83	81	discrimination	discrimination	NOUN
fcis-1074	83	82	.	.	PUNCT
fcis-1074	84	1	in	in	ADP
fcis-1074	84	2	this	this	DET
fcis-1074	84	3	paper	paper	NOUN
fcis-1074	84	4	,	,	PUNCT
fcis-1074	84	5	the	the	DET
fcis-1074	84	6	content	content	NOUN
fcis-1074	84	7	loss	loss	NOUN
fcis-1074	84	8	and	and	CCONJ
fcis-1074	84	9	bce	bce	PROPN
fcis-1074	84	10	loss	loss	NOUN
fcis-1074	84	11	are	be	AUX
fcis-1074	84	12	used	use	VERB
fcis-1074	84	13	in	in	ADP
fcis-1074	84	14	the	the	DET
fcis-1074	84	15	generator	generator	NOUN
fcis-1074	84	16	and	and	CCONJ
fcis-1074	84	17	the	the	DET
fcis-1074	84	18	bce	bce	PROPN
fcis-1074	84	19	loss	loss	NOUN
fcis-1074	84	20	is	be	AUX
fcis-1074	84	21	used	use	VERB
fcis-1074	84	22	in	in	ADP
fcis-1074	84	23	the	the	DET
fcis-1074	84	24	discriminator	discriminator	NOUN
fcis-1074	84	25	,	,	PUNCT
fcis-1074	84	26	and	and	CCONJ
fcis-1074	84	27	the	the	DET
fcis-1074	84	28	total	total	ADJ
fcis-1074	84	29	loss	loss	NOUN
fcis-1074	84	30	function	function	NOUN
fcis-1074	84	31	expression	expression	NOUN
fcis-1074	84	32	is	be	AUX
fcis-1074	84	33	as	as	SCONJ
fcis-1074	84	34	follows	follow	VERB
fcis-1074	84	35	.	.	PUNCT
fcis-1074	85	1	llll	llll	PROPN
fcis-1074	85	2	x	x	PUNCT
fcis-1074	85	3	++=	++=	VERB
fcis-1074	85	4	bceadvtotal	bceadvtotal	ADJ
fcis-1074	85	5	(	(	PUNCT
fcis-1074	85	6	4	4	NUM
fcis-1074	85	7	)	)	PUNCT
fcis-1074	85	8	4×4	4×4	NUM
fcis-1074	85	9	conv	conv	ADJ
fcis-1074	85	10	leaky	leaky	ADJ
fcis-1074	85	11	relu	relu	NOUN
fcis-1074	85	12	4×4	4×4	NUM
fcis-1074	86	1	conv	conv	ADJ
fcis-1074	86	2	leaky	leaky	ADJ
fcis-1074	86	3	relu	relu	NOUN
fcis-1074	86	4	batchnorm	batchnorm	PROPN
fcis-1074	86	5	4×4	4×4	NUM
fcis-1074	86	6	conv	conv	ADJ
fcis-1074	86	7	leaky	leaky	ADJ
fcis-1074	86	8	relu	relu	NOUN
fcis-1074	86	9	batchnorm	batchnorm	PROPN
fcis-1074	86	10	4×4	4×4	NUM
fcis-1074	86	11	conv	conv	ADJ
fcis-1074	86	12	leaky	leaky	ADJ
fcis-1074	86	13	relu	relu	NOUN
fcis-1074	86	14	batchnorm	batchnorm	PROPN
fcis-1074	86	15	4×4	4×4	NUM
fcis-1074	86	16	conv	conv	ADJ
fcis-1074	86	17	leaky	leaky	ADJ
fcis-1074	86	18	relu	relu	NOUN
fcis-1074	86	19	batchnorm	batchnorm	PROPN
fcis-1074	86	20	4×4	4×4	NUM
fcis-1074	86	21	conv	conv	ADJ
fcis-1074	86	22	leaky	leaky	ADJ
fcis-1074	86	23	relu	relu	NOUN
fcis-1074	86	24	output	output	NOUN
fcis-1074	87	1	t	t	X
fcis-1074	87	2	o	o	INTJ
fcis-1074	87	3	i	i	INTJ
fcis-1074	87	4	)	)	PUNCT
fcis-1074	87	5	(	(	PUNCT
fcis-1074	87	6	it	it	PRON
fcis-1074	87	7	)	)	PUNCT
fcis-1074	87	8	(	(	PUNCT
fcis-1074	87	9	io	io	X
fcis-1074	87	10	7	7	NUM
fcis-1074	87	11	4	4	NUM
fcis-1074	87	12	.	.	PUNCT
fcis-1074	88	1	experiments	experiment	NOUN
fcis-1074	88	2	and	and	CCONJ
fcis-1074	88	3	analysis	analysis	NOUN
fcis-1074	88	4	of	of	ADP
fcis-1074	88	5	results	result	NOUN
fcis-1074	88	6	4.1	4.1	NUM
fcis-1074	88	7	.	.	PUNCT
fcis-1074	88	8	dataset	dataset	VERB
fcis-1074	88	9	the	the	DET
fcis-1074	88	10	dataset	dataset	NOUN
fcis-1074	88	11	used	use	VERB
fcis-1074	88	12	in	in	ADP
fcis-1074	88	13	this	this	DET
fcis-1074	88	14	paper	paper	NOUN
fcis-1074	88	15	is	be	AUX
fcis-1074	88	16	from	from	ADP
fcis-1074	88	17	the	the	DET
fcis-1074	88	18	outdoor	outdoor	ADJ
fcis-1074	88	19	dataset	dataset	NOUN
fcis-1074	88	20	ots	ots	PROPN
fcis-1074	88	21	(	(	PUNCT
fcis-1074	88	22	outdoor	outdoor	ADJ
fcis-1074	88	23	training	training	NOUN
fcis-1074	88	24	set	set	NOUN
fcis-1074	88	25	)	)	PUNCT
fcis-1074	88	26	added	add	VERB
fcis-1074	88	27	to	to	ADP
fcis-1074	88	28	the	the	DET
fcis-1074	88	29	reside	reside	NOUN
fcis-1074	88	30	dataset	dataset	NOUN
fcis-1074	88	31	.	.	PUNCT
fcis-1074	89	1	this	this	DET
fcis-1074	89	2	dataset	dataset	NOUN
fcis-1074	89	3	uses	use	VERB
fcis-1074	89	4	2061	2061	NUM
fcis-1074	89	5	real	real	ADJ
fcis-1074	89	6	outdoor	outdoor	ADJ
fcis-1074	89	7	maps	map	NOUN
fcis-1074	89	8	of	of	ADP
fcis-1074	89	9	beijing	beijing	PROPN
fcis-1074	89	10	real	real	ADJ
fcis-1074	89	11	-	-	PUNCT
fcis-1074	89	12	time	time	NOUN
fcis-1074	89	13	weather	weather	NOUN
fcis-1074	89	14	,	,	PUNCT
fcis-1074	89	15	and	and	CCONJ
fcis-1074	89	16	uses	use	VERB
fcis-1074	89	17	the	the	DET
fcis-1074	89	18	algorithm	algorithm	NOUN
fcis-1074	89	19	proposed	propose	VERB
fcis-1074	89	20	by	by	ADP
fcis-1074	89	21	liu	liu	PROPN
fcis-1074	89	22	et	et	PROPN
fcis-1074	89	23	al	al	PROPN
fcis-1074	90	1	[	[	X
fcis-1074	90	2	17	17	NUM
fcis-1074	90	3	]	]	PUNCT
fcis-1074	90	4	to	to	PART
fcis-1074	90	5	reduce	reduce	VERB
fcis-1074	90	6	the	the	DET
fcis-1074	90	7	error	error	NOUN
fcis-1074	90	8	of	of	ADP
fcis-1074	90	9	depth	depth	NOUN
fcis-1074	90	10	and	and	CCONJ
fcis-1074	90	11	the	the	DET
fcis-1074	90	12	visual	visual	ADJ
fcis-1074	90	13	artifacts	artifact	NOUN
fcis-1074	90	14	that	that	PRON
fcis-1074	90	15	may	may	AUX
fcis-1074	90	16	be	be	AUX
fcis-1074	90	17	generated	generate	VERB
fcis-1074	90	18	.	.	PUNCT
fcis-1074	91	1	the	the	DET
fcis-1074	91	2	parameter	parameter	NOUN
fcis-1074	91	3	settings	setting	NOUN
fcis-1074	91	4	of	of	ADP
fcis-1074	91	5	beta	beta	NOUN
fcis-1074	91	6	are	be	AUX
fcis-1074	91	7	[	[	X
fcis-1074	91	8	0.04	0.04	NUM
fcis-1074	91	9	,	,	PUNCT
fcis-1074	91	10	0.06	0.06	NUM
fcis-1074	91	11	,	,	PUNCT
fcis-1074	91	12	0.08	0.08	NUM
fcis-1074	91	13	,	,	PUNCT
fcis-1074	91	14	0.1	0.1	NUM
fcis-1074	91	15	,	,	PUNCT
fcis-1074	91	16	0.12	0.12	NUM
fcis-1074	91	17	,	,	PUNCT
fcis-1074	91	18	0.16	0.16	NUM
fcis-1074	91	19	,	,	PUNCT
fcis-1074	91	20	0.2	0.2	NUM
fcis-1074	91	21	]	]	PUNCT
fcis-1074	91	22	and	and	CCONJ
fcis-1074	91	23	the	the	DET
fcis-1074	91	24	parameter	parameter	NOUN
fcis-1074	91	25	settings	setting	NOUN
fcis-1074	91	26	of	of	ADP
fcis-1074	91	27	atmospheric	atmospheric	ADJ
fcis-1074	91	28	light	light	NOUN
fcis-1074	91	29	value	value	NOUN
fcis-1074	91	30	a	a	DET
fcis-1074	91	31	are	be	AUX
fcis-1074	91	32	[	[	X
fcis-1074	91	33	0.8	0.8	NUM
fcis-1074	91	34	,	,	PUNCT
fcis-1074	91	35	0.85	0.85	NUM
fcis-1074	91	36	,	,	PUNCT
fcis-1074	91	37	0.9	0.9	NUM
fcis-1074	91	38	,	,	PUNCT
fcis-1074	91	39	0.95	0.95	NUM
fcis-1074	91	40	,	,	PUNCT
fcis-1074	91	41	1	1	NUM
fcis-1074	91	42	]	]	PUNCT
fcis-1074	91	43	,	,	PUNCT
fcis-1074	91	44	so	so	SCONJ
fcis-1074	91	45	that	that	SCONJ
fcis-1074	91	46	35	35	NUM
fcis-1074	91	47	fog	fog	NOUN
fcis-1074	91	48	maps	map	NOUN
fcis-1074	91	49	of	of	ADP
fcis-1074	91	50	different	different	ADJ
fcis-1074	91	51	degrees	degree	NOUN
fcis-1074	91	52	are	be	AUX
fcis-1074	91	53	generated	generate	VERB
fcis-1074	91	54	for	for	ADP
fcis-1074	91	55	each	each	DET
fcis-1074	91	56	clear	clear	ADJ
fcis-1074	91	57	image	image	NOUN
fcis-1074	91	58	,	,	PUNCT
fcis-1074	91	59	and	and	CCONJ
fcis-1074	91	60	a	a	DET
fcis-1074	91	61	total	total	NOUN
fcis-1074	91	62	of	of	ADP
fcis-1074	91	63	72135	72135	NUM
fcis-1074	91	64	maps	map	NOUN
fcis-1074	91	65	are	be	AUX
fcis-1074	91	66	generated	generate	VERB
fcis-1074	91	67	.	.	PUNCT
fcis-1074	92	1	before	before	ADP
fcis-1074	92	2	training	training	NOUN
fcis-1074	92	3	,	,	PUNCT
fcis-1074	92	4	the	the	DET
fcis-1074	92	5	dataset	dataset	NOUN
fcis-1074	92	6	is	be	AUX
fcis-1074	92	7	preprocessed	preprocesse	VERB
fcis-1074	92	8	to	to	PART
fcis-1074	92	9	get	get	VERB
fcis-1074	92	10	10,000	10,000	NUM
fcis-1074	92	11	pairs	pair	NOUN
fcis-1074	92	12	of	of	ADP
fcis-1074	92	13	datasets	dataset	NOUN
fcis-1074	92	14	with	with	ADP
fcis-1074	92	15	consistent	consistent	ADJ
fcis-1074	92	16	names	name	NOUN
fcis-1074	92	17	,	,	PUNCT
fcis-1074	92	18	and	and	CCONJ
fcis-1074	92	19	1000	1000	NUM
fcis-1074	92	20	sheets	sheet	NOUN
fcis-1074	92	21	are	be	AUX
fcis-1074	92	22	tested	test	VERB
fcis-1074	92	23	.	.	PUNCT
fcis-1074	93	1	this	this	DET
fcis-1074	93	2	experiment	experiment	NOUN
fcis-1074	93	3	is	be	AUX
fcis-1074	93	4	trained	train	VERB
fcis-1074	93	5	under	under	ADP
fcis-1074	93	6	ubuntu	ubuntu	ADJ
fcis-1074	93	7	system	system	NOUN
fcis-1074	93	8	with	with	ADP
fcis-1074	93	9	gpu	gpu	PROPN
fcis-1074	93	10	of	of	ADP
fcis-1074	93	11	nvidia	nvidia	PROPN
fcis-1074	93	12	1080ti	1080ti	PROPN
fcis-1074	93	13	.	.	PUNCT
fcis-1074	94	1	optimizer	optimizer	NOUN
fcis-1074	94	2	is	be	AUX
fcis-1074	94	3	adam	adam	PROPN
fcis-1074	94	4	,	,	PUNCT
fcis-1074	94	5	learning	learn	VERB
fcis-1074	94	6	rate	rate	NOUN
fcis-1074	94	7	is	be	AUX
fcis-1074	94	8	0.0001	0.0001	NUM
fcis-1074	94	9	,	,	PUNCT
fcis-1074	94	10	batchsize	batchsize	NOUN
fcis-1074	94	11	is	be	AUX
fcis-1074	94	12	2	2	NUM
fcis-1074	94	13	,	,	PUNCT
fcis-1074	94	14	epoch	epoch	PROPN
fcis-1074	94	15	is	be	AUX
fcis-1074	94	16	100	100	NUM
fcis-1074	94	17	.	.	PUNCT
fcis-1074	95	1	4.2	4.2	NUM
fcis-1074	95	2	.	.	PUNCT
fcis-1074	96	1	experimental	experimental	ADJ
fcis-1074	96	2	results	result	NOUN
fcis-1074	96	3	in	in	ADP
fcis-1074	96	4	this	this	DET
fcis-1074	96	5	experiment	experiment	NOUN
fcis-1074	96	6	,	,	PUNCT
fcis-1074	96	7	1000	1000	NUM
fcis-1074	96	8	images	image	NOUN
fcis-1074	96	9	are	be	AUX
fcis-1074	96	10	selected	select	VERB
fcis-1074	96	11	and	and	CCONJ
fcis-1074	96	12	compared	compare	VERB
fcis-1074	96	13	with	with	ADP
fcis-1074	96	14	three	three	NUM
fcis-1074	96	15	algorithms	algorithm	NOUN
fcis-1074	96	16	with	with	ADP
fcis-1074	96	17	better	well	ADJ
fcis-1074	96	18	defogging	defogge	VERB
fcis-1074	96	19	effect	effect	NOUN
fcis-1074	96	20	,	,	PUNCT
fcis-1074	96	21	which	which	PRON
fcis-1074	96	22	are	be	AUX
fcis-1074	96	23	dark	dark	ADJ
fcis-1074	96	24	channel	channel	NOUN
fcis-1074	96	25	a	a	DET
fcis-1074	96	26	priori	priori	ADJ
fcis-1074	96	27	algorithm	algorithm	NOUN
fcis-1074	96	28	,	,	PUNCT
fcis-1074	96	29	aod	aod	PROPN
fcis-1074	96	30	-	-	ADJ
fcis-1074	96	31	net	net	ADJ
fcis-1074	96	32	algorithm	algorithm	NOUN
fcis-1074	96	33	and	and	CCONJ
fcis-1074	96	34	dehaznet	dehaznet	PROPN
fcis-1074	96	35	algorithm	algorithm	NOUN
fcis-1074	96	36	,	,	PUNCT
fcis-1074	96	37	for	for	ADP
fcis-1074	96	38	defogging	defogge	VERB
fcis-1074	96	39	effect	effect	NOUN
fcis-1074	96	40	,	,	PUNCT
fcis-1074	96	41	as	as	SCONJ
fcis-1074	96	42	shown	show	VERB
fcis-1074	96	43	in	in	ADP
fcis-1074	96	44	the	the	DET
fcis-1074	96	45	figure	figure	NOUN
fcis-1074	96	46	6	6	NUM
fcis-1074	96	47	.	.	PUNCT
fcis-1074	97	1	(	(	PUNCT
fcis-1074	97	2	a)fog	a)fog	NOUN
fcis-1074	97	3	map	map	NOUN
fcis-1074	97	4	(	(	PUNCT
fcis-1074	97	5	b)dark	b)dark	PROPN
fcis-1074	97	6	channel	channel	NOUN
fcis-1074	97	7	algorithm	algorithm	NOUN
fcis-1074	97	8	(	(	PUNCT
fcis-1074	97	9	c)aod	c)aod	PROPN
fcis-1074	97	10	-	-	NOUN
fcis-1074	97	11	net	net	NOUN
fcis-1074	97	12	(	(	PUNCT
fcis-1074	97	13	d)dehaznet	d)dehaznet	PROPN
fcis-1074	97	14	(	(	PUNCT
fcis-1074	97	15	e)algorithm	e)algorithm	NOUN
fcis-1074	97	16	of	of	ADP
fcis-1074	97	17	this	this	DET
fcis-1074	97	18	paper	paper	NOUN
fcis-1074	97	19	figure	figure	NOUN
fcis-1074	97	20	6	6	NUM
fcis-1074	97	21	.	.	PUNCT
fcis-1074	98	1	fog	fog	NOUN
fcis-1074	98	2	removal	removal	PROPN
fcis-1074	98	3	effect	effect	NOUN
fcis-1074	98	4	of	of	ADP
fcis-1074	98	5	different	different	ADJ
fcis-1074	98	6	algorithms	algorithm	NOUN
fcis-1074	98	7	through	through	ADP
fcis-1074	98	8	the	the	DET
fcis-1074	98	9	subjective	subjective	ADJ
fcis-1074	98	10	comparison	comparison	NOUN
fcis-1074	98	11	figure	figure	NOUN
fcis-1074	98	12	fig	fig	NOUN
fcis-1074	98	13	.	.	PUNCT
fcis-1074	99	1	6	6	NUM
fcis-1074	99	2	can	can	AUX
fcis-1074	99	3	be	be	AUX
fcis-1074	99	4	seen	see	VERB
fcis-1074	99	5	,	,	PUNCT
fcis-1074	99	6	the	the	DET
fcis-1074	99	7	dark	dark	ADJ
fcis-1074	99	8	channel	channel	NOUN
fcis-1074	99	9	defogging	defogge	VERB
fcis-1074	99	10	algorithm	algorithm	NOUN
fcis-1074	99	11	for	for	ADP
fcis-1074	99	12	the	the	DET
fcis-1074	99	13	bright	bright	ADJ
fcis-1074	99	14	region	region	NOUN
fcis-1074	99	15	of	of	ADP
fcis-1074	99	16	the	the	DET
fcis-1074	99	17	transmittance	transmittance	NOUN
fcis-1074	99	18	and	and	CCONJ
fcis-1074	99	19	atmospheric	atmospheric	ADJ
fcis-1074	99	20	light	light	NOUN
fcis-1074	99	21	value	value	NOUN
fcis-1074	99	22	estimation	estimation	NOUN
fcis-1074	99	23	inaccurate	inaccurate	ADJ
fcis-1074	99	24	make	make	VERB
fcis-1074	99	25	the	the	DET
fcis-1074	99	26	sky	sky	NOUN
fcis-1074	99	27	region	region	NOUN
fcis-1074	99	28	overexposure	overexposure	NOUN
fcis-1074	99	29	phenomenon	phenomenon	NOUN
fcis-1074	99	30	,	,	PUNCT
fcis-1074	99	31	and	and	CCONJ
fcis-1074	99	32	the	the	DET
fcis-1074	99	33	defogging	defogge	VERB
fcis-1074	99	34	image	image	NOUN
fcis-1074	99	35	color	color	NOUN
fcis-1074	99	36	darkened	darken	VERB
fcis-1074	99	37	,	,	PUNCT
fcis-1074	99	38	there	there	PRON
fcis-1074	99	39	are	be	VERB
fcis-1074	99	40	fog	fog	NOUN
fcis-1074	99	41	residue	residue	NOUN
fcis-1074	99	42	;	;	PUNCT
fcis-1074	99	43	aod	aod	ADJ
fcis-1074	99	44	-	-	ADJ
fcis-1074	99	45	net	net	ADJ
fcis-1074	99	46	algorithm	algorithm	NOUN
fcis-1074	99	47	can	can	AUX
fcis-1074	99	48	obviously	obviously	ADV
fcis-1074	99	49	see	see	VERB
fcis-1074	99	50	the	the	DET
fcis-1074	99	51	defogging	defogging	NOUN
fcis-1074	99	52	effect	effect	NOUN
fcis-1074	99	53	is	be	AUX
fcis-1074	99	54	not	not	PART
fcis-1074	99	55	ideal	ideal	ADJ
fcis-1074	99	56	,	,	PUNCT
fcis-1074	99	57	the	the	DET
fcis-1074	99	58	fog	fog	NOUN
fcis-1074	99	59	residue	residue	NOUN
fcis-1074	99	60	most	most	ADV
fcis-1074	99	61	;	;	PUNCT
fcis-1074	99	62	dehaznet	dehaznet	ADJ
fcis-1074	99	63	algorithm	algorithm	NOUN
fcis-1074	99	64	compared	compare	VERB
fcis-1074	99	65	to	to	ADP
fcis-1074	99	66	the	the	DET
fcis-1074	99	67	aod	aod	PROPN
fcis-1074	99	68	-	-	ADJ
fcis-1074	99	69	net	net	ADJ
fcis-1074	99	70	algorithm	algorithm	NOUN
fcis-1074	99	71	fog	fog	NOUN
fcis-1074	99	72	residue	residue	NOUN
fcis-1074	99	73	less	less	ADV
fcis-1074	99	74	,	,	PUNCT
fcis-1074	99	75	but	but	CCONJ
fcis-1074	99	76	will	will	AUX
fcis-1074	99	77	the	the	DET
fcis-1074	99	78	fog	fog	NOUN
fcis-1074	99	79	residue	residue	NOUN
fcis-1074	99	80	of	of	ADP
fcis-1074	99	81	dehaznet	dehaznet	ADJ
fcis-1074	99	82	algorithm	algorithm	NOUN
fcis-1074	99	83	is	be	AUX
fcis-1074	99	84	less	less	ADJ
fcis-1074	99	85	than	than	ADP
fcis-1074	99	86	that	that	PRON
fcis-1074	99	87	of	of	ADP
fcis-1074	99	88	aod	aod	PROPN
fcis-1074	99	89	-	-	ADJ
fcis-1074	99	90	net	net	ADJ
fcis-1074	99	91	algorithm	algorithm	NOUN
fcis-1074	99	92	,	,	PUNCT
fcis-1074	99	93	but	but	CCONJ
fcis-1074	99	94	there	there	PRON
fcis-1074	99	95	are	be	VERB
fcis-1074	99	96	small	small	ADJ
fcis-1074	99	97	areas	area	NOUN
fcis-1074	99	98	of	of	ADP
fcis-1074	99	99	distortion	distortion	NOUN
fcis-1074	99	100	,	,	PUNCT
fcis-1074	99	101	such	such	ADJ
fcis-1074	99	102	as	as	ADP
fcis-1074	99	103	the	the	DET
fcis-1074	99	104	lower	low	ADJ
fcis-1074	99	105	right	right	ADJ
fcis-1074	99	106	part	part	NOUN
fcis-1074	99	107	of	of	ADP
fcis-1074	99	108	the	the	DET
fcis-1074	99	109	defogged	defogged	ADJ
fcis-1074	99	110	image	image	NOUN
fcis-1074	99	111	in	in	ADP
fcis-1074	99	112	the	the	DET
fcis-1074	99	113	first	first	ADJ
fcis-1074	99	114	row	row	NOUN
fcis-1074	99	115	of	of	ADP
fcis-1074	99	116	fig	fig	NOUN
fcis-1074	99	117	.	.	PUNCT
fcis-1074	100	1	6	6	NUM
fcis-1074	100	2	.	.	X
fcis-1074	100	3	in	in	ADP
fcis-1074	100	4	this	this	DET
fcis-1074	100	5	paper	paper	NOUN
fcis-1074	100	6	,	,	PUNCT
fcis-1074	100	7	two	two	NUM
fcis-1074	100	8	image	image	NOUN
fcis-1074	100	9	quality	quality	NOUN
fcis-1074	100	10	evaluation	evaluation	NOUN
fcis-1074	100	11	indexes	index	NOUN
fcis-1074	100	12	,	,	PUNCT
fcis-1074	100	13	psnr	psnr	NOUN
fcis-1074	100	14	and	and	CCONJ
fcis-1074	100	15	ssim	ssim	NOUN
fcis-1074	100	16	,	,	PUNCT
fcis-1074	100	17	are	be	AUX
fcis-1074	100	18	used	use	VERB
fcis-1074	100	19	to	to	PART
fcis-1074	100	20	demonstrate	demonstrate	VERB
fcis-1074	100	21	the	the	DET
fcis-1074	100	22	superiority	superiority	NOUN
fcis-1074	100	23	of	of	ADP
fcis-1074	100	24	this	this	DET
fcis-1074	100	25	method	method	NOUN
fcis-1074	100	26	from	from	ADP
fcis-1074	100	27	the	the	DET
fcis-1074	100	28	objective	objective	ADJ
fcis-1074	100	29	aspect	aspect	NOUN
fcis-1074	100	30	.	.	PUNCT
fcis-1074	101	1	psnr	psnr	NOUN
fcis-1074	101	2	peak	peak	NOUN
fcis-1074	101	3	signal	signal	NOUN
fcis-1074	101	4	-	-	PUNCT
fcis-1074	101	5	to	to	ADP
fcis-1074	101	6	-	-	PUNCT
fcis-1074	101	7	noise	noise	NOUN
fcis-1074	101	8	ratio	ratio	NOUN
fcis-1074	101	9	,	,	PUNCT
fcis-1074	101	10	which	which	PRON
fcis-1074	101	11	is	be	AUX
fcis-1074	101	12	the	the	DET
fcis-1074	101	13	most	most	ADV
fcis-1074	101	14	common	common	ADJ
fcis-1074	101	15	and	and	CCONJ
fcis-1074	101	16	widely	widely	ADV
fcis-1074	101	17	used	use	VERB
fcis-1074	101	18	image	image	NOUN
fcis-1074	101	19	objective	objective	ADJ
fcis-1074	101	20	evaluation	evaluation	NOUN
fcis-1074	101	21	index	index	NOUN
fcis-1074	101	22	,	,	PUNCT
fcis-1074	101	23	is	be	AUX
fcis-1074	101	24	based	base	VERB
fcis-1074	101	25	on	on	ADP
fcis-1074	101	26	the	the	DET
fcis-1074	101	27	error	error	NOUN
fcis-1074	101	28	between	between	ADP
fcis-1074	101	29	corresponding	correspond	VERB
fcis-1074	101	30	pixel	pixel	PROPN
fcis-1074	101	31	points	point	NOUN
fcis-1074	101	32	in	in	ADP
fcis-1074	101	33	db	db	PROPN
fcis-1074	101	34	,	,	PUNCT
fcis-1074	101	35	and	and	CCONJ
fcis-1074	101	36	the	the	DET
fcis-1074	101	37	larger	large	ADJ
fcis-1074	101	38	value	value	NOUN
fcis-1074	101	39	means	mean	VERB
fcis-1074	101	40	the	the	DET
fcis-1074	101	41	smaller	small	ADJ
fcis-1074	101	42	distortion	distortion	NOUN
fcis-1074	101	43	.	.	PUNCT
fcis-1074	102	1	ssim	ssim	NOUN
fcis-1074	102	2	structural	structural	ADJ
fcis-1074	102	3	similarity	similarity	NOUN
fcis-1074	102	4	,	,	PUNCT
fcis-1074	102	5	which	which	PRON
fcis-1074	102	6	is	be	AUX
fcis-1074	102	7	also	also	ADV
fcis-1074	102	8	a	a	DET
fcis-1074	102	9	full	full	ADJ
fcis-1074	102	10	-	-	PUNCT
fcis-1074	102	11	reference	reference	NOUN
fcis-1074	102	12	image	image	NOUN
fcis-1074	102	13	quality	quality	NOUN
fcis-1074	102	14	ssim	ssim	NOUN
fcis-1074	102	15	structural	structural	ADJ
fcis-1074	102	16	similarity	similarity	NOUN
fcis-1074	102	17	,	,	PUNCT
fcis-1074	102	18	which	which	PRON
fcis-1074	102	19	is	be	AUX
fcis-1074	102	20	also	also	ADV
fcis-1074	102	21	a	a	DET
fcis-1074	102	22	full	full	ADJ
fcis-1074	102	23	-	-	PUNCT
fcis-1074	102	24	reference	reference	NOUN
fcis-1074	102	25	image	image	NOUN
fcis-1074	102	26	quality	quality	NOUN
fcis-1074	102	27	evaluation	evaluation	NOUN
fcis-1074	102	28	index	index	NOUN
fcis-1074	102	29	,	,	PUNCT
fcis-1074	102	30	measures	measure	VERB
fcis-1074	102	31	image	image	NOUN
fcis-1074	102	32	similarity	similarity	NOUN
fcis-1074	102	33	in	in	ADP
fcis-1074	102	34	terms	term	NOUN
fcis-1074	102	35	of	of	ADP
fcis-1074	102	36	brightness	brightness	NOUN
fcis-1074	102	37	,	,	PUNCT
fcis-1074	102	38	contrast	contrast	NOUN
fcis-1074	102	39	,	,	PUNCT
fcis-1074	102	40	and	and	CCONJ
fcis-1074	102	41	structure	structure	NOUN
fcis-1074	102	42	,	,	PUNCT
fcis-1074	102	43	respectively	respectively	ADV
fcis-1074	102	44	,	,	PUNCT
fcis-1074	102	45	and	and	CCONJ
fcis-1074	102	46	ssim	ssim	NOUN
fcis-1074	102	47	takes	take	VERB
fcis-1074	102	48	values	value	NOUN
fcis-1074	102	49	in	in	ADP
fcis-1074	102	50	the	the	DET
fcis-1074	102	51	range	range	NOUN
fcis-1074	103	1	[	[	X
fcis-1074	103	2	0,1	0,1	NUM
fcis-1074	103	3	]	]	PUNCT
fcis-1074	103	4	,	,	PUNCT
fcis-1074	103	5	with	with	ADP
fcis-1074	103	6	larger	large	ADJ
fcis-1074	103	7	values	value	NOUN
fcis-1074	103	8	indicating	indicate	VERB
fcis-1074	103	9	higher	high	ADJ
fcis-1074	103	10	similarity	similarity	NOUN
fcis-1074	103	11	to	to	ADP
fcis-1074	103	12	the	the	DET
fcis-1074	103	13	original	original	ADJ
fcis-1074	103	14	image	image	NOUN
fcis-1074	103	15	.	.	PUNCT
fcis-1074	104	1	the	the	DET
fcis-1074	104	2	following	follow	VERB
fcis-1074	104	3	comparison	comparison	NOUN
fcis-1074	104	4	table	table	NOUN
fcis-1074	104	5	1	1	NUM
fcis-1074	104	6	shows	show	VERB
fcis-1074	104	7	that	that	SCONJ
fcis-1074	104	8	the	the	DET
fcis-1074	104	9	psnr	psnr	NOUN
fcis-1074	104	10	and	and	CCONJ
fcis-1074	104	11	ssim	ssim	NOUN
fcis-1074	104	12	values	value	NOUN
fcis-1074	104	13	of	of	ADP
fcis-1074	104	14	this	this	DET
fcis-1074	104	15	paper	paper	NOUN
fcis-1074	104	16	are	be	AUX
fcis-1074	104	17	not	not	PART
fcis-1074	104	18	only	only	ADV
fcis-1074	104	19	the	the	DET
fcis-1074	104	20	highest	high	ADJ
fcis-1074	104	21	but	but	CCONJ
fcis-1074	104	22	also	also	ADV
fcis-1074	104	23	have	have	AUX
fcis-1074	104	24	been	be	AUX
fcis-1074	104	25	improved	improve	VERB
fcis-1074	104	26	.	.	PUNCT
fcis-1074	105	1	table	table	NOUN
fcis-1074	105	2	1	1	NUM
fcis-1074	105	3	.	.	PUNCT
fcis-1074	105	4	comparison	comparison	NOUN
fcis-1074	105	5	of	of	ADP
fcis-1074	105	6	psnr	psnr	NOUN
fcis-1074	105	7	and	and	CCONJ
fcis-1074	105	8	ssim	ssim	NOUN
fcis-1074	105	9	of	of	ADP
fcis-1074	105	10	different	different	ADJ
fcis-1074	105	11	algorithms	algorithm	NOUN
fcis-1074	105	12	de	de	NOUN
fcis-1074	105	13	-	-	ADJ
fcis-1074	105	14	fogging	fogging	ADJ
fcis-1074	105	15	algorithm	algorithm	NOUN
fcis-1074	105	16	ssim/%	ssim/%	ADP
fcis-1074	105	17	psnr	psnr	NOUN
fcis-1074	105	18	/	/	SYM
fcis-1074	105	19	db	db	PROPN
fcis-1074	105	20	dark	dark	ADJ
fcis-1074	105	21	channel	channel	NOUN
fcis-1074	105	22	0.8833	0.8833	NUM
fcis-1074	105	23	15.5543	15.5543	NUM
fcis-1074	105	24	aod	aod	NOUN
fcis-1074	105	25	-	-	ADJ
fcis-1074	105	26	net	net	ADJ
fcis-1074	105	27	0.8894	0.8894	NUM
fcis-1074	105	28	18.7977	18.7977	NUM
fcis-1074	105	29	dehazenet	dehazenet	NOUN
fcis-1074	105	30	0.8831	0.8831	NUM
fcis-1074	105	31	18.9424	18.9424	NUM
fcis-1074	105	32	my	my	PRON
fcis-1074	105	33	method	method	NOUN
fcis-1074	105	34	0.9505	0.9505	NUM
fcis-1074	105	35	26.8199	26.8199	NUM
fcis-1074	105	36	5	5	NUM
fcis-1074	105	37	.	.	PUNCT
fcis-1074	106	1	conclusion	conclusion	VERB
fcis-1074	106	2	the	the	DET
fcis-1074	106	3	image	image	NOUN
fcis-1074	106	4	defogging	defogge	VERB
fcis-1074	106	5	algorithm	algorithm	NOUN
fcis-1074	106	6	based	base	VERB
fcis-1074	106	7	on	on	ADP
fcis-1074	106	8	deblurgan	deblurgan	ADJ
fcis-1074	106	9	network	network	NOUN
fcis-1074	106	10	proposed	propose	VERB
fcis-1074	106	11	in	in	ADP
fcis-1074	106	12	this	this	DET
fcis-1074	106	13	paper	paper	NOUN
fcis-1074	106	14	adds	add	VERB
fcis-1074	106	15	dilated	dilate	VERB
fcis-1074	106	16	convolution	convolution	NOUN
fcis-1074	106	17	to	to	ADP
fcis-1074	106	18	the	the	DET
fcis-1074	106	19	generator	generator	NOUN
fcis-1074	106	20	to	to	PART
fcis-1074	106	21	expand	expand	VERB
fcis-1074	106	22	the	the	DET
fcis-1074	106	23	perceptual	perceptual	ADJ
fcis-1074	106	24	field	field	NOUN
fcis-1074	106	25	without	without	ADP
fcis-1074	106	26	changing	change	VERB
fcis-1074	106	27	the	the	DET
fcis-1074	106	28	resolution	resolution	NOUN
fcis-1074	106	29	,	,	PUNCT
fcis-1074	106	30	and	and	CCONJ
fcis-1074	106	31	also	also	ADV
fcis-1074	106	32	adds	add	VERB
fcis-1074	106	33	a	a	DET
fcis-1074	106	34	spatial	spatial	ADJ
fcis-1074	106	35	attention	attention	NOUN
fcis-1074	106	36	mechanism	mechanism	NOUN
fcis-1074	106	37	at	at	ADP
fcis-1074	106	38	specified	specify	VERB
fcis-1074	106	39	locations	location	NOUN
fcis-1074	106	40	to	to	PART
fcis-1074	106	41	optimize	optimize	VERB
fcis-1074	106	42	the	the	DET
fcis-1074	106	43	detail	detail	NOUN
fcis-1074	106	44	information	information	NOUN
fcis-1074	106	45	of	of	ADP
fcis-1074	106	46	the	the	DET
fcis-1074	106	47	generated	generate	VERB
fcis-1074	106	48	fog	fog	PROPN
fcis-1074	106	49	-	-	PUNCT
fcis-1074	106	50	free	free	ADJ
fcis-1074	106	51	images	image	NOUN
fcis-1074	106	52	and	and	CCONJ
fcis-1074	106	53	reduce	reduce	VERB
fcis-1074	106	54	the	the	DET
fcis-1074	106	55	fog	fog	NOUN
fcis-1074	106	56	residue	residue	NOUN
fcis-1074	106	57	.	.	PUNCT
fcis-1074	107	1	the	the	DET
fcis-1074	107	2	loss	loss	NOUN
fcis-1074	107	3	function	function	NOUN
fcis-1074	107	4	replaces	replace	VERB
fcis-1074	107	5	the	the	DET
fcis-1074	107	6	traditional	traditional	ADJ
fcis-1074	107	7	adversarial	adversarial	ADJ
fcis-1074	107	8	loss	loss	NOUN
fcis-1074	107	9	with	with	ADP
fcis-1074	107	10	a	a	DET
fcis-1074	107	11	pixel	pixel	NOUN
fcis-1074	107	12	-	-	PUNCT
fcis-1074	107	13	based	base	VERB
fcis-1074	107	14	bce	bce	PROPN
fcis-1074	107	15	loss	loss	NOUN
fcis-1074	107	16	to	to	PART
fcis-1074	107	17	improve	improve	VERB
fcis-1074	107	18	detail	detail	NOUN
fcis-1074	107	19	retention	retention	NOUN
fcis-1074	107	20	.	.	PUNCT
fcis-1074	108	1	by	by	ADP
fcis-1074	108	2	comparing	compare	VERB
fcis-1074	108	3	the	the	DET
fcis-1074	108	4	subjective	subjective	ADJ
fcis-1074	108	5	defogging	defogging	NOUN
fcis-1074	108	6	effect	effect	NOUN
fcis-1074	108	7	graph	graph	NOUN
fcis-1074	108	8	and	and	CCONJ
fcis-1074	108	9	the	the	DET
fcis-1074	108	10	objective	objective	ADJ
fcis-1074	108	11	experimental	experimental	ADJ
fcis-1074	108	12	data	datum	NOUN
fcis-1074	108	13	,	,	PUNCT
fcis-1074	108	14	we	we	PRON
fcis-1074	108	15	can	can	AUX
fcis-1074	108	16	see	see	VERB
fcis-1074	108	17	that	that	SCONJ
fcis-1074	108	18	the	the	DET
fcis-1074	108	19	defogging	defogge	VERB
fcis-1074	108	20	effect	effect	NOUN
fcis-1074	108	21	of	of	ADP
fcis-1074	108	22	this	this	DET
fcis-1074	108	23	algorithm	algorithm	NOUN
fcis-1074	108	24	is	be	AUX
fcis-1074	108	25	obvious	obvious	ADJ
fcis-1074	108	26	.	.	PUNCT
fcis-1074	109	1	references	reference	NOUN
fcis-1074	109	2	[	[	X
fcis-1074	109	3	1	1	X
fcis-1074	109	4	]	]	PUNCT
fcis-1074	109	5	kim	kim	PROPN
fcis-1074	109	6	t	t	PROPN
fcis-1074	109	7	k	k	PROPN
fcis-1074	109	8	,	,	PUNCT
fcis-1074	109	9	paik	paik	PROPN
fcis-1074	109	10	j	j	PROPN
fcis-1074	109	11	k	k	PROPN
fcis-1074	109	12	,	,	PUNCT
fcis-1074	109	13	kang	kang	PROPN
fcis-1074	109	14	b	b	PROPN
fcis-1074	109	15	s.	s.	PROPN
fcis-1074	109	16	contrast	contrast	PROPN
fcis-1074	109	17	enhancement	enhancement	NOUN
fcis-1074	109	18	system	system	NOUN
fcis-1074	109	19	using	use	VERB
fcis-1074	109	20	spatially	spatially	ADV
fcis-1074	109	21	adaptive	adaptive	ADJ
fcis-1074	109	22	histogram	histogram	NOUN
fcis-1074	109	23	equalization	equalization	NOUN
fcis-1074	109	24	with	with	ADP
fcis-1074	109	25	temporal	temporal	ADJ
fcis-1074	109	26	filtering	filtering	NOUN
fcis-1074	110	1	[	[	X
fcis-1074	110	2	j	j	X
fcis-1074	110	3	]	]	X
fcis-1074	110	4	.	.	PUNCT
fcis-1074	111	1	ieee	ieee	NOUN
fcis-1074	111	2	transactions	transaction	NOUN
fcis-1074	111	3	on	on	ADP
fcis-1074	111	4	consumer	consumer	NOUN
fcis-1074	111	5	electronics	electronic	NOUN
fcis-1074	111	6	,	,	PUNCT
fcis-1074	111	7	1998	1998	NUM
fcis-1074	111	8	,	,	PUNCT
fcis-1074	111	9	44(1	44(1	PROPN
fcis-1074	111	10	):	):	PUNCT
fcis-1074	111	11	82	82	NUM
fcis-1074	111	12	-	-	SYM
fcis-1074	111	13	87	87	NUM
fcis-1074	111	14	.	.	PUNCT
fcis-1074	111	15	8	8	NUM
fcis-1074	112	1	[	[	SYM
fcis-1074	112	2	2	2	NUM
fcis-1074	112	3	]	]	X
fcis-1074	112	4	jobson	jobson	PROPN
fcis-1074	112	5	d	d	PROPN
fcis-1074	112	6	j	j	PROPN
fcis-1074	112	7	,	,	PUNCT
fcis-1074	112	8	rahman	rahman	PROPN
fcis-1074	112	9	z	z	PROPN
fcis-1074	112	10	,	,	PUNCT
fcis-1074	112	11	woodell	woodell	VERB
fcis-1074	112	12	g	g	PROPN
fcis-1074	112	13	a.	a.	NOUN
fcis-1074	112	14	a	a	DET
fcis-1074	112	15	multiscale	multiscale	ADJ
fcis-1074	112	16	retinex	retinex	NOUN
fcis-1074	112	17	for	for	ADP
fcis-1074	112	18	bridging	bridge	VERB
fcis-1074	112	19	the	the	DET
fcis-1074	112	20	gap	gap	NOUN
fcis-1074	112	21	between	between	ADP
fcis-1074	112	22	color	color	NOUN
fcis-1074	112	23	images	image	NOUN
fcis-1074	112	24	and	and	CCONJ
fcis-1074	112	25	the	the	DET
fcis-1074	112	26	human	human	ADJ
fcis-1074	112	27	observation	observation	NOUN
fcis-1074	112	28	of	of	ADP
fcis-1074	112	29	scenes[j	scenes[j	NOUN
fcis-1074	112	30	]	]	PUNCT
fcis-1074	112	31	.	.	PUNCT
fcis-1074	113	1	ieee	ieee	NOUN
fcis-1074	113	2	transactions	transaction	NOUN
fcis-1074	113	3	on	on	ADP
fcis-1074	113	4	image	image	NOUN
fcis-1074	113	5	processing	processing	NOUN
fcis-1074	113	6	,	,	PUNCT
fcis-1074	113	7	2002	2002	NUM
fcis-1074	113	8	,	,	PUNCT
fcis-1074	113	9	6(7	6(7	NUM
fcis-1074	113	10	):	):	PUNCT
fcis-1074	113	11	965	965	NUM
fcis-1074	113	12	-	-	SYM
fcis-1074	113	13	976	976	NUM
fcis-1074	113	14	.	.	PUNCT
fcis-1074	114	1	[	[	X
fcis-1074	114	2	3	3	X
fcis-1074	114	3	]	]	PUNCT
fcis-1074	114	4	he	he	PRON
fcis-1074	114	5	k	k	PROPN
fcis-1074	114	6	m	m	PROPN
fcis-1074	114	7	,	,	PUNCT
fcis-1074	114	8	sun	sun	PROPN
fcis-1074	114	9	j	j	PROPN
fcis-1074	114	10	,	,	PUNCT
fcis-1074	114	11	tang	tang	PROPN
fcis-1074	114	12	x	x	SYM
fcis-1074	114	13	o.	o.	PROPN
fcis-1074	114	14	single	single	ADJ
fcis-1074	114	15	image	image	NOUN
fcis-1074	114	16	haze	haze	NOUN
fcis-1074	114	17	removal	removal	NOUN
fcis-1074	114	18	using	use	VERB
fcis-1074	114	19	dark	dark	ADJ
fcis-1074	114	20	channel	channel	NOUN
fcis-1074	114	21	prior[j	prior[j	NOUN
fcis-1074	114	22	]	]	PUNCT
fcis-1074	114	23	.	.	PUNCT
fcis-1074	115	1	ieee	ieee	NOUN
fcis-1074	115	2	transactions	transaction	NOUN
fcis-1074	115	3	on	on	ADP
fcis-1074	115	4	pattern	pattern	NOUN
fcis-1074	115	5	analysis	analysis	NOUN
fcis-1074	115	6	and	and	CCONJ
fcis-1074	115	7	machine	machine	NOUN
fcis-1074	115	8	intelligence	intelligence	NOUN
fcis-1074	115	9	,	,	PUNCT
fcis-1074	115	10	2011	2011	NUM
fcis-1074	115	11	,	,	PUNCT
fcis-1074	115	12	33(12	33(12	NUM
fcis-1074	115	13	):	):	PUNCT
fcis-1074	115	14	2341	2341	NUM
fcis-1074	115	15	-	-	SYM
fcis-1074	115	16	2353	2353	NUM
fcis-1074	115	17	.	.	PUNCT
fcis-1074	116	1	[	[	X
fcis-1074	116	2	4	4	X
fcis-1074	116	3	]	]	X
fcis-1074	116	4	cai	cai	PROPN
fcis-1074	116	5	b	b	PROPN
fcis-1074	116	6	l	l	PROPN
fcis-1074	116	7	,	,	PUNCT
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fcis-1074	116	9	x	x	PROPN
fcis-1074	116	10	m	m	PROPN
fcis-1074	116	11	,	,	PUNCT
fcis-1074	116	12	jia	jia	PROPN
fcis-1074	116	13	k	k	PROPN
fcis-1074	116	14	,	,	PUNCT
fcis-1074	116	15	et	et	PROPN
fcis-1074	116	16	al	al	PROPN
fcis-1074	116	17	.	.	PROPN
fcis-1074	116	18	dehaze	dehaze	PROPN
fcis-1074	116	19	net	net	NOUN
fcis-1074	116	20	:	:	PUNCT
fcis-1074	116	21	an	an	DET
fcis-1074	116	22	end	end	NOUN
fcis-1074	116	23	-	-	PUNCT
fcis-1074	116	24	toendsystem	toendsystem	NOUN
fcis-1074	116	25	for	for	ADP
fcis-1074	116	26	single	single	ADJ
fcis-1074	116	27	image	image	NOUN
fcis-1074	116	28	haze	haze	NOUN
fcis-1074	116	29	removal[j	removal[j	NOUN
fcis-1074	116	30	]	]	PUNCT
fcis-1074	116	31	.	.	PUNCT
fcis-1074	117	1	ieee	ieee	NOUN
fcis-1074	117	2	transactions	transaction	NOUN
fcis-1074	117	3	on	on	ADP
fcis-1074	117	4	image	image	NOUN
fcis-1074	117	5	processing	processing	NOUN
fcis-1074	117	6	,	,	PUNCT
fcis-1074	117	7	2016	2016	NUM
fcis-1074	117	8	,	,	PUNCT
fcis-1074	117	9	25(11	25(11	NUM
fcis-1074	117	10	):	):	PUNCT
fcis-1074	117	11	5187	5187	NUM
fcis-1074	117	12	-	-	SYM
fcis-1074	117	13	5198	5198	NUM
fcis-1074	117	14	.	.	PUNCT
fcis-1074	118	1	[	[	X
fcis-1074	118	2	5	5	X
fcis-1074	118	3	]	]	PUNCT
fcis-1074	118	4	he	he	PROPN
fcis-1074	118	5	zhang	zhang	PROPN
fcis-1074	118	6	,	,	PUNCT
fcis-1074	118	7	vishal	vishal	PROPN
fcis-1074	118	8	m.	m.	PROPN
fcis-1074	118	9	patel	patel	PROPN
fcis-1074	118	10	.	.	PUNCT
fcis-1074	119	1	densely	densely	ADV
fcis-1074	119	2	connected	connected	ADJ
fcis-1074	119	3	pyramid	pyramid	NOUN
fcis-1074	119	4	dehazing	dehaze	VERB
fcis-1074	119	5	network	network	NOUN
fcis-1074	119	6	[	[	X
fcis-1074	119	7	j	j	X
fcis-1074	119	8	]	]	X
fcis-1074	119	9	.	.	PUNCT
fcis-1074	120	1	arxiv	arxiv	NOUN
fcis-1074	120	2	:	:	PUNCT
fcis-1074	121	1	1803.0839	1803.0839	NUM
fcis-1074	121	2	[	[	X
fcis-1074	121	3	cs	cs	PROPN
fcis-1074	121	4	.	.	PROPN
fcis-1074	121	5	cv	cv	PROPN
fcis-1074	121	6	]	]	X
fcis-1074	122	1	https://doi.org/10.48550/arxiv.1803.08396	https://doi.org/10.48550/arxiv.1803.08396	PROPN
fcis-1074	122	2	[	[	X
fcis-1074	122	3	6	6	NUM
fcis-1074	122	4	]	]	SYM
fcis-1074	122	5	li	li	PROPN
fcis-1074	122	6	b	b	PROPN
fcis-1074	122	7	y	y	PROPN
fcis-1074	122	8	,	,	PUNCT
fcis-1074	122	9	peng	peng	PROPN
fcis-1074	122	10	x	x	PROPN
fcis-1074	122	11	l	l	PROPN
fcis-1074	122	12	,	,	PUNCT
fcis-1074	122	13	wang	wang	PROPN
fcis-1074	122	14	z	z	PROPN
fcis-1074	122	15	y	y	PROPN
fcis-1074	122	16	,	,	PUNCT
fcis-1074	122	17	et	et	PROPN
fcis-1074	122	18	al	al	PROPN
fcis-1074	122	19	.	.	PROPN
fcis-1074	122	20	aod	aod	PROPN
fcis-1074	122	21	-	-	NOUN
fcis-1074	122	22	net	net	NOUN
fcis-1074	122	23	:	:	PUNCT
fcis-1074	122	24	all	all	PRON
fcis-1074	122	25	-	-	PUNCT
fcis-1074	122	26	in	in	ADP
fcis-1074	122	27	-	-	PUNCT
fcis-1074	122	28	one	one	NUM
fcis-1074	122	29	dehazing	dehaze	VERB
fcis-1074	122	30	network	network	NOUN
fcis-1074	122	31	[	[	X
fcis-1074	122	32	c	c	X
fcis-1074	122	33	]	]	PUNCT
fcis-1074	122	34	.	.	PUNCT
fcis-1074	123	1	ieee	ieee	PROPN
fcis-1074	123	2	international	international	PROPN
fcis-1074	123	3	conference	conference	NOUN
fcis-1074	123	4	on	on	ADP
fcis-1074	123	5	computer	computer	NOUN
fcis-1074	123	6	vision	vision	NOUN
fcis-1074	123	7	,	,	PUNCT
fcis-1074	123	8	2017	2017	NUM
fcis-1074	123	9	:	:	PUNCT
fcis-1074	123	10	4770	4770	NUM
fcis-1074	123	11	-	-	SYM
fcis-1074	123	12	4778	4778	NUM
fcis-1074	123	13	.	.	PUNCT
fcis-1074	124	1	[	[	X
fcis-1074	124	2	7	7	X
fcis-1074	124	3	]	]	X
fcis-1074	124	4	mei	mei	PROPN
fcis-1074	124	5	k	k	PROPN
fcis-1074	124	6	f	f	PROPN
fcis-1074	124	7	,	,	PUNCT
fcis-1074	124	8	jiang	jiang	PROPN
fcis-1074	124	9	a	a	DET
fcis-1074	124	10	w	w	PROPN
fcis-1074	124	11	,	,	PUNCT
fcis-1074	124	12	li	li	PROPN
fcis-1074	125	1	j	j	PROPN
fcis-1074	125	2	c	c	PROPN
fcis-1074	125	3	,	,	PUNCT
fcis-1074	125	4	et	et	NOUN
fcis-1074	125	5	al.progressive	al.progressive	X
fcis-1074	125	6	feature	feature	NOUN
fcis-1074	125	7	fusion	fusion	NOUN
fcis-1074	125	8	network	network	NOUN
fcis-1074	125	9	for	for	ADP
fcis-1074	125	10	realistic	realistic	ADJ
fcis-1074	125	11	image	image	NOUN
fcis-1074	125	12	dehazing[c	dehazing[c	NOUN
fcis-1074	125	13	]	]	PUNCT
fcis-1074	125	14	.	.	PUNCT
fcis-1074	126	1	asian	asian	ADJ
fcis-1074	126	2	conference	conference	NOUN
fcis-1074	126	3	on	on	ADP
fcis-1074	126	4	computer	computer	NOUN
fcis-1074	126	5	vision	vision	NOUN
fcis-1074	126	6	,	,	PUNCT
fcis-1074	126	7	2018	2018	NUM
fcis-1074	126	8	:	:	PUNCT
fcis-1074	126	9	203	203	NUM
fcis-1074	126	10	-	-	SYM
fcis-1074	126	11	215	215	NUM
fcis-1074	126	12	.	.	PUNCT
fcis-1074	127	1	[	[	X
fcis-1074	127	2	8	8	NUM
fcis-1074	127	3	]	]	X
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fcis-1074	127	5	i	i	PROPN
fcis-1074	127	6	j	j	PROPN
fcis-1074	127	7	,	,	PUNCT
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fcis-1074	127	9	-	-	PUNCT
fcis-1074	127	10	abadie	abadie	NOUN
fcis-1074	127	11	j	j	PROPN
fcis-1074	127	12	,	,	PUNCT
fcis-1074	127	13	mirza	mirza	PROPN
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fcis-1074	127	16	et	et	PROPN
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fcis-1074	127	18	adversarial	adversarial	PROPN
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fcis-1074	127	21	of	of	ADP
fcis-1074	127	22	the	the	DET
fcis-1074	127	23	2014	2014	NUM
fcis-1074	127	24	neural	neural	ADJ
fcis-1074	127	25	information	information	NOUN
fcis-1074	127	26	processing	processing	NOUN
fcis-1074	127	27	systems	system	NOUN
fcis-1074	127	28	.	.	PUNCT
fcis-1074	128	1	cambridge	cambridge	PROPN
fcis-1074	128	2	,	,	PUNCT
fcis-1074	128	3	ma	ma	PROPN
fcis-1074	128	4	:	:	PUNCT
fcis-1074	128	5	mit	mit	PROPN
fcis-1074	128	6	press	press	NOUN
fcis-1074	128	7	,	,	PUNCT
fcis-1074	128	8	2014	2014	NUM
fcis-1074	128	9	:	:	PUNCT
fcis-1074	128	10	2672	2672	NUM
fcis-1074	128	11	-	-	SYM
fcis-1074	128	12	2680	2680	NUM
fcis-1074	128	13	.	.	PUNCT
fcis-1074	129	1	[	[	X
fcis-1074	129	2	9	9	NUM
fcis-1074	129	3	]	]	PUNCT
fcis-1074	129	4	zhu	zhu	PROPN
fcis-1074	129	5	h	h	PROPN
fcis-1074	129	6	y	y	PROPN
fcis-1074	129	7	,	,	PUNCT
fcis-1074	129	8	peng	peng	PROPN
fcis-1074	129	9	x	x	PROPN
fcis-1074	129	10	,	,	PUNCT
fcis-1074	129	11	chandrasekhar	chandrasekhar	PROPN
fcis-1074	129	12	v	v	PROPN
fcis-1074	129	13	,	,	PUNCT
fcis-1074	129	14	et	et	PROPN
fcis-1074	129	15	al	al	PROPN
fcis-1074	129	16	.	.	PROPN
fcis-1074	129	17	dehaze	dehaze	PROPN
fcis-1074	129	18	gan	gan	PROPN
fcis-1074	129	19	:	:	PUNCT
fcis-1074	129	20	when	when	SCONJ
fcis-1074	129	21	image	image	NOUN
fcis-1074	129	22	dehazing	dehazing	NOUN
fcis-1074	129	23	meets	meet	VERB
fcis-1074	129	24	diferential	diferential	ADJ
fcis-1074	129	25	programming	programming	NOUN
fcis-1074	129	26	[	[	X
fcis-1074	129	27	c	c	X
fcis-1074	129	28	]	]	PUNCT
fcis-1074	129	29	.	.	PUNCT
fcis-1074	130	1	the	the	DET
fcis-1074	130	2	twenty	twenty	NUM
fcis-1074	130	3	-	-	PUNCT
fcis-1074	130	4	seventh	seventh	ADJ
fcis-1074	130	5	international	international	ADJ
fcis-1074	130	6	joint	joint	ADJ
fcis-1074	130	7	conference	conference	NOUN
fcis-1074	130	8	on	on	ADP
fcis-1074	130	9	artificial	artificial	ADJ
fcis-1074	130	10	intelligence	intelligence	NOUN
fcis-1074	130	11	,	,	PUNCT
fcis-1074	130	12	2018	2018	NUM
fcis-1074	130	13	:	:	PUNCT
fcis-1074	130	14	1234	1234	NUM
fcis-1074	130	15	-	-	SYM
fcis-1074	130	16	1240	1240	NUM
fcis-1074	130	17	.	.	PUNCT
fcis-1074	131	1	[	[	X
fcis-1074	131	2	10	10	NUM
fcis-1074	131	3	]	]	X
fcis-1074	131	4	zhong	zhong	PROPN
fcis-1074	131	5	w	w	PROPN
fcis-1074	131	6	f	f	PROPN
fcis-1074	131	7	,	,	PUNCT
fcis-1074	131	8	zhao	zhao	PROPN
fcis-1074	131	9	j.	j.	PROPN
fcis-1074	131	10	image	image	PROPN
fcis-1074	131	11	defogging	defogge	VERB
fcis-1074	131	12	algorithm	algorithm	NOUN
fcis-1074	131	13	based	base	VERB
fcis-1074	131	14	on	on	ADP
fcis-1074	131	15	generative	generative	ADJ
fcis-1074	131	16	adversarial	adversarial	ADJ
fcis-1074	131	17	network[j	network[j	NOUN
fcis-1074	131	18	]	]	PUNCT
fcis-1074	131	19	.	.	PUNCT
fcis-1074	132	1	advances	advance	NOUN
fcis-1074	132	2	in	in	ADP
fcis-1074	132	3	laser	laser	NOUN
fcis-1074	132	4	and	and	CCONJ
fcis-1074	132	5	optoelectronics	optoelectronic	NOUN
fcis-1074	132	6	2022,59(4):337	2022,59(4):337	NOUN
fcis-1074	132	7	-	-	PUNCT
fcis-1074	132	8	345	345	NUM
fcis-1074	132	9	.	.	PUNCT
fcis-1074	133	1	[	[	X
fcis-1074	133	2	11	11	NUM
fcis-1074	133	3	]	]	X
fcis-1074	133	4	tu	tu	PROPN
fcis-1074	133	5	,	,	PUNCT
fcis-1074	133	6	h	h	PROPN
fcis-1074	133	7	y	y	PROPN
fcis-1074	133	8	,	,	PUNCT
fcis-1074	133	9	wang	wang	PROPN
fcis-1074	133	10	w	w	PROPN
fcis-1074	133	11	l	l	PROPN
fcis-1074	133	12	,	,	PUNCT
fcis-1074	133	13	chen	chen	PROPN
fcis-1074	133	14	j	j	PROPN
fcis-1074	133	15	c	c	PROPN
fcis-1074	133	16	,	,	PUNCT
fcis-1074	133	17	et	et	PROPN
fcis-1074	133	18	al	al	PROPN
fcis-1074	133	19	.	.	PUNCT
fcis-1074	134	1	a	a	DET
fcis-1074	134	2	generative	generative	ADJ
fcis-1074	134	3	adversarial	adversarial	ADJ
fcis-1074	134	4	network	network	NOUN
fcis-1074	134	5	defogging	defogge	VERB
fcis-1074	134	6	algorithm	algorithm	NOUN
fcis-1074	134	7	combining	combine	VERB
fcis-1074	134	8	atmospheric	atmospheric	ADJ
fcis-1074	134	9	scattering	scattering	NOUN
fcis-1074	134	10	model	model	NOUN
fcis-1074	135	1	[	[	X
fcis-1074	135	2	j	j	X
fcis-1074	135	3	]	]	X
fcis-1074	135	4	.	.	PUNCT
fcis-1074	136	1	journal	journal	PROPN
fcis-1074	136	2	of	of	ADP
fcis-1074	136	3	zhejiang	zhejiang	PROPN
fcis-1074	136	4	university	university	PROPN
fcis-1074	136	5	(	(	PUNCT
fcis-1074	136	6	engineering	engineering	NOUN
fcis-1074	136	7	edition	edition	NOUN
fcis-1074	136	8	)	)	PUNCT
fcis-1074	136	9	,	,	PUNCT
fcis-1074	136	10	2022,56(02),225	2022,56(02),225	X
fcis-1074	136	11	-	-	SYM
fcis-1074	136	12	235	235	NUM
fcis-1074	136	13	.	.	PUNCT
fcis-1074	137	1	[	[	X
fcis-1074	137	2	12	12	NUM
fcis-1074	137	3	]	]	PUNCT
fcis-1074	137	4	orest	or	ADJ
fcis-1074	137	5	kupyn	kupyn	PROPN
fcis-1074	137	6	,	,	PUNCT
fcis-1074	137	7	volodymyr	volodymyr	PROPN
fcis-1074	137	8	budzan	budzan	PROPN
fcis-1074	137	9	,	,	PUNCT
fcis-1074	137	10	mykola	mykola	PROPN
fcis-1074	137	11	mykhailych	mykhailych	PROPN
fcis-1074	137	12	,	,	PUNCT
fcis-1074	137	13	et	et	PROPN
fcis-1074	137	14	al	al	PROPN
fcis-1074	137	15	.	.	PROPN
fcis-1074	137	16	deblurgan	deblurgan	PROPN
fcis-1074	137	17	:	:	PUNCT
fcis-1074	137	18	blind	blind	ADJ
fcis-1074	137	19	motion	motion	NOUN
fcis-1074	137	20	deblurring	deblurre	VERB
fcis-1074	137	21	using	use	VERB
fcis-1074	137	22	conditional	conditional	ADJ
fcis-1074	137	23	adversarial	adversarial	ADJ
fcis-1074	137	24	networks[c	networks[c	PROPN
fcis-1074	137	25	]	]	PUNCT
fcis-1074	137	26	.	.	PUNCT
fcis-1074	138	1	proceedings	proceeding	NOUN
fcis-1074	138	2	of	of	ADP
fcis-1074	138	3	the	the	DET
fcis-1074	138	4	ieee	ieee	NOUN
fcis-1074	138	5	conference	conference	NOUN
fcis-1074	138	6	on	on	ADP
fcis-1074	138	7	computer	computer	NOUN
fcis-1074	138	8	vision	vision	NOUN
fcis-1074	138	9	and	and	CCONJ
fcis-1074	138	10	pattern	pattern	NOUN
fcis-1074	138	11	recognition	recognition	NOUN
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fcis-1074	138	14	:	:	PUNCT
fcis-1074	138	15	8183	8183	NUM
fcis-1074	138	16	-	-	SYM
fcis-1074	138	17	8192	8192	NUM
fcis-1074	138	18	.	.	PUNCT
fcis-1074	139	1	[	[	X
fcis-1074	139	2	13	13	NUM
fcis-1074	139	3	]	]	X
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fcis-1074	139	8	,	,	PUNCT
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fcis-1074	139	11	,	,	PUNCT
fcis-1074	139	12	i.	i.	PROPN
fcis-1074	139	13	kokkinos	kokkinos	PROPN
fcis-1074	139	14	,	,	PUNCT
fcis-1074	139	15	k.	k.	PROPN
fcis-1074	139	16	murphy	murphy	PROPN
fcis-1074	139	17	,	,	PUNCT
fcis-1074	139	18	et	et	PROPN
fcis-1074	139	19	al	al	PROPN
fcis-1074	139	20	.	.	PUNCT
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fcis-1074	139	22	image	image	NOUN
fcis-1074	139	23	segmentation	segmentation	NOUN
fcis-1074	139	24	with	with	ADP
fcis-1074	139	25	deep	deep	ADJ
fcis-1074	139	26	convolutional	convolutional	ADJ
fcis-1074	139	27	nets	net	NOUN
fcis-1074	139	28	and	and	CCONJ
fcis-1074	139	29	fully	fully	ADV
fcis-1074	139	30	connected	connect	VERB
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fcis-1074	139	32	.	.	PUNCT
fcis-1074	140	1	in	in	ADP
fcis-1074	140	2	iclr	iclr	NOUN
fcis-1074	140	3	,	,	PUNCT
fcis-1074	140	4	2015	2015	NUM
fcis-1074	140	5	.	.	PUNCT
fcis-1074	141	1	[	[	X
fcis-1074	141	2	14	14	NUM
fcis-1074	141	3	]	]	X
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fcis-1074	141	5	x	x	SYM
fcis-1074	141	6	y	y	PROPN
fcis-1074	141	7	,	,	PUNCT
fcis-1074	141	8	wang	wang	PROPN
fcis-1074	141	9	y	y	PROPN
fcis-1074	141	10	q	q	PROPN
fcis-1074	141	11	,	,	PUNCT
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fcis-1074	141	13	l	l	PROPN
fcis-1074	141	14	g	g	PROPN
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fcis-1074	141	16	et	et	PROPN
fcis-1074	141	17	al	al	PROPN
fcis-1074	141	18	.	.	PUNCT
fcis-1074	142	1	a	a	DET
fcis-1074	142	2	stereo	stereo	ADJ
fcis-1074	142	3	attention	attention	NOUN
fcis-1074	142	4	module	module	NOUN
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fcis-1074	142	6	stereo	stereo	ADJ
fcis-1074	142	7	image	image	NOUN
fcis-1074	142	8	super	super	NOUN
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fcis-1074	142	10	resolution[j	resolution[j	PROPN
fcis-1074	142	11	]	]	PUNCT
fcis-1074	142	12	.	.	PUNCT
fcis-1074	143	1	ieee	ieee	NOUN
fcis-1074	143	2	signal	signal	NOUN
fcis-1074	143	3	processing	processing	NOUN
fcis-1074	143	4	letters	letter	NOUN
fcis-1074	143	5	,	,	PUNCT
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fcis-1074	143	7	,	,	PUNCT
fcis-1074	143	8	27	27	NUM
fcis-1074	143	9	:	:	PUNCT
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fcis-1074	143	11	-	-	SYM
fcis-1074	143	12	500	500	NUM
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fcis-1074	144	2	15	15	NUM
fcis-1074	144	3	]	]	X
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fcis-1074	144	5	i	i	PROPN
fcis-1074	144	6	,	,	PUNCT
fcis-1074	144	7	ahmed	ahmed	PROPN
fcis-1074	144	8	,	,	PUNCT
fcis-1074	144	9	f	f	PROPN
fcis-1074	144	10	,	,	PUNCT
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fcis-1074	144	14	,	,	PUNCT
fcis-1074	144	15	et	et	PROPN
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fcis-1074	144	17	training	training	NOUN
fcis-1074	144	18	of	of	ADP
fcis-1074	144	19	wasserstein	wasserstein	PROPN
fcis-1074	144	20	gans[j	gans[j	PROPN
fcis-1074	144	21	]	]	PUNCT
fcis-1074	144	22	.	.	PUNCT
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fcis-1074	146	1	[	[	X
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fcis-1074	146	3	]	]	X
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fcis-1074	146	6	p	p	PROPN
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fcis-1074	146	8	,	,	PUNCT
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fcis-1074	146	10	d	d	X
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fcis-1074	146	16	et	et	NOUN
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fcis-1074	146	19	on	on	ADP
fcis-1074	146	20	the	the	DET
fcis-1074	146	21	cross	cross	ADJ
fcis-1074	146	22	-	-	ADJ
fcis-1074	146	23	entropy	entropy	ADJ
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fcis-1074	146	25	[	[	X
fcis-1074	146	26	j	j	X
fcis-1074	146	27	]	]	X
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fcis-1074	147	2	of	of	ADP
fcis-1074	147	3	operations	operation	NOUN
fcis-1074	147	4	reserach	reserach	NOUN
fcis-1074	147	5	,	,	PUNCT
fcis-1074	147	6	2005	2005	NUM
fcis-1074	147	7	,	,	PUNCT
fcis-1074	147	8	134	134	NUM
fcis-1074	147	9	(	(	PUNCT
fcis-1074	147	10	1	1	NUM
fcis-1074	147	11	):	):	PUNCT
fcis-1074	147	12	16	16	NUM
fcis-1074	147	13	-	-	SYM
fcis-1074	147	14	67	67	NUM
fcis-1074	147	15	.	.	PUNCT
fcis-1074	148	1	[	[	X
fcis-1074	148	2	17	17	NUM
fcis-1074	148	3	]	]	X
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fcis-1074	148	17	reid	reid	PROPN
fcis-1074	148	18	l.	l.	PROPN
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fcis-1074	148	21	from	from	ADP
fcis-1074	148	22	single	single	ADJ
fcis-1074	148	23	monocular	monocular	ADJ
fcis-1074	148	24	images	image	NOUN
fcis-1074	148	25	using	use	VERB
fcis-1074	148	26	deep	deep	ADJ
fcis-1074	148	27	convolutional	convolutional	ADJ
fcis-1074	148	28	neural	neural	ADJ
fcis-1074	148	29	fields[j	fields[j	PROPN
fcis-1074	148	30	]	]	PUNCT
fcis-1074	148	31	.	.	PUNCT
fcis-1074	149	1	ieee	ieee	NOUN
fcis-1074	149	2	transactions	transaction	NOUN
fcis-1074	149	3	on	on	ADP
fcis-1074	149	4	pattern	pattern	NOUN
fcis-1074	149	5	analysis	analysis	NOUN
fcis-1074	149	6	and	and	CCONJ
fcis-1074	149	7	machine	machine	NOUN
fcis-1074	149	8	intelligence	intelligence	NOUN
fcis-1074	149	9	,	,	PUNCT
fcis-1074	149	10	vol	vol	NOUN
fcis-1074	149	11	.	.	PROPN
fcis-1074	150	1	38	38	NUM
fcis-1074	150	2	,	,	PUNCT
fcis-1074	150	3	no	no	INTJ
fcis-1074	150	4	.	.	NOUN
fcis-1074	150	5	10	10	NUM
fcis-1074	150	6	,	,	PUNCT
fcis-1074	150	7	2016	2016	NUM
fcis-1074	150	8	.	.	PUNCT
fcis-1074	151	1	https://arxiv.org/search/cs?searchtype=author&query=zhang,+h	https://arxiv.org/search/cs?searchtype=author&query=zhang,+h	PROPN
fcis-1074	151	2	https://arxiv.org/search/cs?searchtype=author&query=patel,+v+m	https://arxiv.org/search/cs?searchtype=author&query=patel,+v+m	PUNCT