id	sid	tid	token	lemma	pos
cana-4791	1	1	communications	communication	NOUN
cana-4791	1	2	on	on	ADP
cana-4791	1	3	applied	apply	VERB
cana-4791	1	4	nonlinear	nonlinear	ADJ
cana-4791	1	5	analysis	analysis	NOUN
cana-4791	1	6	issn	issn	NOUN
cana-4791	1	7	:	:	PUNCT
cana-4791	1	8	1074	1074	NUM
cana-4791	1	9	-	-	PUNCT
cana-4791	1	10	133x	133x	NUM
cana-4791	1	11	vol	vol	NOUN
cana-4791	1	12	31	31	NUM
cana-4791	1	13	no	no	NOUN
cana-4791	1	14	.	.	PUNCT
cana-4791	2	1	1s	1s	NUM
cana-4791	2	2	(	(	PUNCT
cana-4791	2	3	2024	2024	NUM
cana-4791	2	4	)	)	PUNCT
cana-4791	2	5	215	215	NUM
cana-4791	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	2	7	compressgan	compressgan	PROPN
cana-4791	2	8	:	:	PUNCT
cana-4791	2	9	a	a	DET
cana-4791	2	10	generative	generative	ADJ
cana-4791	2	11	adversarial	adversarial	ADJ
cana-4791	2	12	network	network	NOUN
cana-4791	2	13	-	-	PUNCT
cana-4791	2	14	based	base	VERB
cana-4791	2	15	framework	framework	NOUN
cana-4791	2	16	for	for	ADP
cana-4791	2	17	learned	learn	VERB
cana-4791	2	18	image	image	NOUN
cana-4791	2	19	compression	compression	NOUN
cana-4791	2	20	dharmesh	dharmesh	ADJ
cana-4791	2	21	dhabliya	dhabliya	PROPN
cana-4791	2	22	,	,	PUNCT
cana-4791	2	23	dr	dr	PROPN
cana-4791	2	24	.	.	PROPN
cana-4791	2	25	priya	priya	PROPN
cana-4791	2	26	vij	vij	PROPN
cana-4791	2	27	research	research	PROPN
cana-4791	2	28	scholar	scholar	NOUN
cana-4791	2	29	,	,	PUNCT
cana-4791	2	30	department	department	NOUN
cana-4791	2	31	of	of	ADP
cana-4791	2	32	computer	computer	NOUN
cana-4791	2	33	science	science	NOUN
cana-4791	2	34	and	and	CCONJ
cana-4791	2	35	engineering	engineering	NOUN
cana-4791	2	36	kalinga	kalinga	PROPN
cana-4791	2	37	university	university	PROPN
cana-4791	2	38	raipur	raipur	PROPN
cana-4791	2	39	department	department	PROPN
cana-4791	2	40	of	of	ADP
cana-4791	2	41	computer	computer	NOUN
cana-4791	2	42	science	science	NOUN
cana-4791	2	43	and	and	CCONJ
cana-4791	2	44	engineering	engineering	NOUN
cana-4791	2	45	kalinga	kalinga	PROPN
cana-4791	2	46	university	university	PROPN
cana-4791	2	47	raipur	raipur	PROPN
cana-4791	2	48	article	article	NOUN
cana-4791	2	49	history	history	NOUN
cana-4791	2	50	:	:	PUNCT
cana-4791	2	51	received	receive	VERB
cana-4791	2	52	:	:	PUNCT
cana-4791	2	53	12	12	NUM
cana-4791	2	54	-	-	PUNCT
cana-4791	2	55	02	02	NUM
cana-4791	2	56	-	-	PUNCT
cana-4791	2	57	2024	2024	NUM
cana-4791	2	58	revised	revise	VERB
cana-4791	2	59	:	:	PUNCT
cana-4791	2	60	10	10	NUM
cana-4791	2	61	-	-	PUNCT
cana-4791	2	62	04	04	NUM
cana-4791	2	63	-	-	PUNCT
cana-4791	2	64	2024	2024	NUM
cana-4791	2	65	accepted	accept	VERB
cana-4791	2	66	:	:	PUNCT
cana-4791	2	67	24	24	NUM
cana-4791	2	68	-	-	PUNCT
cana-4791	2	69	04	04	NUM
cana-4791	2	70	-	-	PUNCT
cana-4791	2	71	2024	2024	NUM
cana-4791	2	72	abstract	abstract	NOUN
cana-4791	2	73	:	:	PUNCT
cana-4791	2	74	with	with	ADP
cana-4791	2	75	the	the	DET
cana-4791	2	76	rise	rise	NOUN
cana-4791	2	77	of	of	ADP
cana-4791	2	78	high	high	ADJ
cana-4791	2	79	-	-	PUNCT
cana-4791	2	80	resolution	resolution	NOUN
cana-4791	2	81	digital	digital	ADJ
cana-4791	2	82	material	material	NOUN
cana-4791	2	83	,	,	PUNCT
cana-4791	2	84	there	there	PRON
cana-4791	2	85	is	be	VERB
cana-4791	2	86	a	a	DET
cana-4791	2	87	much	much	ADV
cana-4791	2	88	greater	great	ADJ
cana-4791	2	89	need	need	NOUN
cana-4791	2	90	for	for	ADP
cana-4791	2	91	effective	effective	ADJ
cana-4791	2	92	picture	picture	NOUN
cana-4791	2	93	compression	compression	NOUN
cana-4791	2	94	methods	method	NOUN
cana-4791	2	95	.	.	PUNCT
cana-4791	3	1	traditional	traditional	ADJ
cana-4791	3	2	image	image	NOUN
cana-4791	3	3	compression	compression	NOUN
cana-4791	3	4	methods	method	NOUN
cana-4791	3	5	,	,	PUNCT
cana-4791	3	6	like	like	ADP
cana-4791	3	7	jpeg	jpeg	NOUN
cana-4791	3	8	and	and	CCONJ
cana-4791	3	9	png	png	PROPN
cana-4791	3	10	,	,	PUNCT
cana-4791	3	11	have	have	VERB
cana-4791	3	12	a	a	DET
cana-4791	3	13	hard	hard	ADJ
cana-4791	3	14	time	time	NOUN
cana-4791	3	15	keeping	keep	VERB
cana-4791	3	16	the	the	DET
cana-4791	3	17	compression	compression	NOUN
cana-4791	3	18	rate	rate	NOUN
cana-4791	3	19	and	and	CCONJ
cana-4791	3	20	quality	quality	NOUN
cana-4791	3	21	of	of	ADP
cana-4791	3	22	the	the	DET
cana-4791	3	23	picture	picture	NOUN
cana-4791	3	24	in	in	ADP
cana-4791	3	25	balance	balance	NOUN
cana-4791	3	26	,	,	PUNCT
cana-4791	3	27	especially	especially	ADV
cana-4791	3	28	when	when	SCONJ
cana-4791	3	29	the	the	DET
cana-4791	3	30	bitrate	bitrate	NOUN
cana-4791	3	31	is	be	AUX
cana-4791	3	32	low	low	ADJ
cana-4791	3	33	.	.	PUNCT
cana-4791	4	1	we	we	PRON
cana-4791	4	2	present	present	VERB
cana-4791	4	3	compressgan	compressgan	PROPN
cana-4791	4	4	,	,	PUNCT
cana-4791	4	5	a	a	DET
cana-4791	4	6	new	new	ADJ
cana-4791	4	7	method	method	NOUN
cana-4791	4	8	for	for	ADP
cana-4791	4	9	learning	learn	VERB
cana-4791	4	10	to	to	PART
cana-4791	4	11	compress	compress	VERB
cana-4791	4	12	images	image	NOUN
cana-4791	4	13	that	that	PRON
cana-4791	4	14	is	be	AUX
cana-4791	4	15	based	base	VERB
cana-4791	4	16	on	on	ADP
cana-4791	4	17	generative	generative	ADJ
cana-4791	4	18	adversarial	adversarial	ADJ
cana-4791	4	19	networks	network	NOUN
cana-4791	4	20	(	(	PUNCT
cana-4791	4	21	gans	gan	NOUN
cana-4791	4	22	)	)	PUNCT
cana-4791	4	23	.	.	PUNCT
cana-4791	5	1	an	an	DET
cana-4791	5	2	encoder	encoder	NOUN
cana-4791	5	3	-	-	PUNCT
cana-4791	5	4	decoder	decoder	NOUN
cana-4791	5	5	network	network	NOUN
cana-4791	5	6	and	and	CCONJ
cana-4791	5	7	a	a	DET
cana-4791	5	8	discriminator	discriminator	NOUN
cana-4791	5	9	are	be	AUX
cana-4791	5	10	paired	pair	VERB
cana-4791	5	11	in	in	ADP
cana-4791	5	12	the	the	DET
cana-4791	5	13	suggested	suggest	VERB
cana-4791	5	14	design	design	NOUN
cana-4791	5	15	so	so	SCONJ
cana-4791	5	16	that	that	SCONJ
cana-4791	5	17	it	it	PRON
cana-4791	5	18	can	can	AUX
cana-4791	5	19	learn	learn	VERB
cana-4791	5	20	small	small	ADJ
cana-4791	5	21	latent	latent	NOUN
cana-4791	5	22	representations	representation	NOUN
cana-4791	5	23	while	while	SCONJ
cana-4791	5	24	keeping	keep	VERB
cana-4791	5	25	the	the	DET
cana-4791	5	26	quality	quality	NOUN
cana-4791	5	27	of	of	ADP
cana-4791	5	28	the	the	DET
cana-4791	5	29	images	image	NOUN
cana-4791	5	30	.	.	PUNCT
cana-4791	6	1	compressgan	compressgan	PROPN
cana-4791	6	2	is	be	AUX
cana-4791	6	3	different	different	ADJ
cana-4791	6	4	from	from	ADP
cana-4791	6	5	other	other	ADJ
cana-4791	6	6	methods	method	NOUN
cana-4791	6	7	because	because	SCONJ
cana-4791	6	8	it	it	PRON
cana-4791	6	9	uses	use	VERB
cana-4791	6	10	hostile	hostile	ADJ
cana-4791	6	11	training	training	NOUN
cana-4791	6	12	to	to	PART
cana-4791	6	13	find	find	VERB
cana-4791	6	14	features	feature	NOUN
cana-4791	6	15	that	that	PRON
cana-4791	6	16	are	be	AUX
cana-4791	6	17	important	important	ADJ
cana-4791	6	18	to	to	ADP
cana-4791	6	19	perception	perception	NOUN
cana-4791	6	20	.	.	PUNCT
cana-4791	7	1	this	this	PRON
cana-4791	7	2	makes	make	VERB
cana-4791	7	3	reconstructions	reconstruction	NOUN
cana-4791	7	4	that	that	PRON
cana-4791	7	5	look	look	VERB
cana-4791	7	6	good	good	ADJ
cana-4791	7	7	even	even	ADV
cana-4791	7	8	at	at	ADP
cana-4791	7	9	high	high	ADJ
cana-4791	7	10	compression	compression	NOUN
cana-4791	7	11	levels	level	NOUN
cana-4791	7	12	.	.	PUNCT
cana-4791	8	1	the	the	DET
cana-4791	8	2	decoder	decoder	NOUN
cana-4791	8	3	shrinks	shrink	VERB
cana-4791	8	4	the	the	DET
cana-4791	8	5	picture	picture	NOUN
cana-4791	8	6	data	datum	NOUN
cana-4791	8	7	into	into	ADP
cana-4791	8	8	a	a	DET
cana-4791	8	9	small	small	ADJ
cana-4791	8	10	hidden	hide	VERB
cana-4791	8	11	code	code	NOUN
cana-4791	8	12	.	.	PUNCT
cana-4791	9	1	this	this	DET
cana-4791	9	2	code	code	NOUN
cana-4791	9	3	is	be	AUX
cana-4791	9	4	then	then	ADV
cana-4791	9	5	quantised	quantise	VERB
cana-4791	9	6	and	and	CCONJ
cana-4791	9	7	entropy	entropy	ADV
cana-4791	9	8	-	-	PUNCT
cana-4791	9	9	coded	code	VERB
cana-4791	9	10	to	to	PART
cana-4791	9	11	make	make	VERB
cana-4791	9	12	it	it	PRON
cana-4791	9	13	easier	easy	ADJ
cana-4791	9	14	to	to	PART
cana-4791	9	15	store	store	VERB
cana-4791	9	16	.	.	PUNCT
cana-4791	10	1	the	the	DET
cana-4791	10	2	decoder	decoder	NOUN
cana-4791	10	3	builds	build	VERB
cana-4791	10	4	the	the	DET
cana-4791	10	5	picture	picture	NOUN
cana-4791	10	6	back	back	ADV
cana-4791	10	7	up	up	ADP
cana-4791	10	8	from	from	ADP
cana-4791	10	9	the	the	DET
cana-4791	10	10	compressed	compress	VERB
cana-4791	10	11	version	version	NOUN
cana-4791	10	12	using	use	VERB
cana-4791	10	13	both	both	CCONJ
cana-4791	10	14	pixel	pixel	ADJ
cana-4791	10	15	-	-	ADJ
cana-4791	10	16	wise	wise	ADJ
cana-4791	10	17	reconstruction	reconstruction	NOUN
cana-4791	10	18	loss	loss	NOUN
cana-4791	10	19	and	and	CCONJ
cana-4791	10	20	hostile	hostile	ADJ
cana-4791	10	21	loss	loss	NOUN
cana-4791	10	22	from	from	ADP
cana-4791	10	23	the	the	DET
cana-4791	10	24	discriminator	discriminator	NOUN
cana-4791	10	25	as	as	ADP
cana-4791	10	26	guides	guide	NOUN
cana-4791	10	27	.	.	PUNCT
cana-4791	11	1	we	we	PRON
cana-4791	11	2	add	add	VERB
cana-4791	11	3	a	a	DET
cana-4791	11	4	perceived	perceive	VERB
cana-4791	11	5	loss	loss	NOUN
cana-4791	11	6	calculated	calculate	VERB
cana-4791	11	7	from	from	ADP
cana-4791	11	8	a	a	DET
cana-4791	11	9	feature	feature	NOUN
cana-4791	11	10	extractor	extractor	NOUN
cana-4791	11	11	network	network	NOUN
cana-4791	11	12	that	that	PRON
cana-4791	11	13	has	have	AUX
cana-4791	11	14	already	already	ADV
cana-4791	11	15	been	be	AUX
cana-4791	11	16	trained	train	VERB
cana-4791	11	17	to	to	PART
cana-4791	11	18	improve	improve	VERB
cana-4791	11	19	realism	realism	NOUN
cana-4791	11	20	and	and	CCONJ
cana-4791	11	21	lower	low	ADJ
cana-4791	11	22	artefacts	artefact	NOUN
cana-4791	11	23	.	.	PUNCT
cana-4791	12	1	compressgan	compressgan	PROPN
cana-4791	12	2	does	do	VERB
cana-4791	12	3	better	well	ADV
cana-4791	12	4	than	than	ADP
cana-4791	12	5	traditional	traditional	ADJ
cana-4791	12	6	codecs	codec	NOUN
cana-4791	12	7	and	and	CCONJ
cana-4791	12	8	a	a	DET
cana-4791	12	9	few	few	ADJ
cana-4791	12	10	new	new	ADJ
cana-4791	12	11	learnt	learnt	NOUN
cana-4791	12	12	compression	compression	NOUN
cana-4791	12	13	models	model	NOUN
cana-4791	12	14	in	in	ADP
cana-4791	12	15	terms	term	NOUN
cana-4791	12	16	of	of	ADP
cana-4791	12	17	psnr	psnr	NOUN
cana-4791	12	18	,	,	PUNCT
cana-4791	12	19	ssim	ssim	NOUN
cana-4791	12	20	,	,	PUNCT
cana-4791	12	21	and	and	CCONJ
cana-4791	12	22	perceived	perceive	VERB
cana-4791	12	23	quality	quality	NOUN
cana-4791	12	24	measures	measure	NOUN
cana-4791	12	25	,	,	PUNCT
cana-4791	12	26	as	as	SCONJ
cana-4791	12	27	shown	show	VERB
cana-4791	12	28	by	by	ADP
cana-4791	12	29	experiments	experiment	NOUN
cana-4791	12	30	done	do	VERB
cana-4791	12	31	on	on	ADP
cana-4791	12	32	standard	standard	ADJ
cana-4791	12	33	picture	picture	NOUN
cana-4791	12	34	datasets	dataset	NOUN
cana-4791	12	35	.	.	PUNCT
cana-4791	13	1	furthermore	furthermore	ADV
cana-4791	13	2	,	,	PUNCT
cana-4791	13	3	our	our	PRON
cana-4791	13	4	approach	approach	NOUN
cana-4791	13	5	keeps	keep	VERB
cana-4791	13	6	conceptual	conceptual	ADJ
cana-4791	13	7	continuity	continuity	NOUN
cana-4791	13	8	and	and	CCONJ
cana-4791	13	9	visual	visual	ADJ
cana-4791	13	10	features	feature	NOUN
cana-4791	13	11	better	well	ADV
cana-4791	13	12	than	than	ADP
cana-4791	13	13	baselines	baseline	NOUN
cana-4791	13	14	,	,	PUNCT
cana-4791	13	15	especially	especially	ADV
cana-4791	13	16	when	when	SCONJ
cana-4791	13	17	bit	bit	NOUN
cana-4791	13	18	rates	rate	NOUN
cana-4791	13	19	are	be	AUX
cana-4791	13	20	low	low	ADJ
cana-4791	13	21	.	.	PUNCT
cana-4791	14	1	compressgan	compressgan	PROPN
cana-4791	14	2	can	can	AUX
cana-4791	14	3	be	be	AUX
cana-4791	14	4	trained	train	VERB
cana-4791	14	5	from	from	ADP
cana-4791	14	6	start	start	NOUN
cana-4791	14	7	to	to	ADP
cana-4791	14	8	finish	finish	NOUN
cana-4791	14	9	and	and	CCONJ
cana-4791	14	10	can	can	AUX
cana-4791	14	11	be	be	AUX
cana-4791	14	12	changed	change	VERB
cana-4791	14	13	to	to	PART
cana-4791	14	14	work	work	VERB
cana-4791	14	15	with	with	ADP
cana-4791	14	16	different	different	ADJ
cana-4791	14	17	compression	compression	NOUN
cana-4791	14	18	rates	rate	NOUN
cana-4791	14	19	by	by	ADP
cana-4791	14	20	changing	change	VERB
cana-4791	14	21	the	the	DET
cana-4791	14	22	quantisation	quantisation	NOUN
cana-4791	14	23	levels	level	NOUN
cana-4791	14	24	or	or	CCONJ
cana-4791	14	25	latent	latent	ADJ
cana-4791	14	26	space	space	NOUN
cana-4791	14	27	density	density	NOUN
cana-4791	14	28	.	.	PUNCT
cana-4791	15	1	this	this	DET
cana-4791	15	2	framework	framework	NOUN
cana-4791	15	3	looks	look	VERB
cana-4791	15	4	like	like	ADP
cana-4791	15	5	a	a	DET
cana-4791	15	6	good	good	ADJ
cana-4791	15	7	way	way	NOUN
cana-4791	15	8	to	to	PART
cana-4791	15	9	handle	handle	VERB
cana-4791	15	10	apps	app	NOUN
cana-4791	15	11	with	with	ADP
cana-4791	15	12	limited	limited	ADJ
cana-4791	15	13	storage	storage	NOUN
cana-4791	15	14	space	space	NOUN
cana-4791	15	15	and	and	CCONJ
cana-4791	15	16	bandwidth	bandwidth	ADJ
cana-4791	15	17	,	,	PUNCT
cana-4791	15	18	like	like	ADP
cana-4791	15	19	mobile	mobile	ADJ
cana-4791	15	20	images	image	NOUN
cana-4791	15	21	,	,	PUNCT
cana-4791	15	22	monitoring	monitoring	NOUN
cana-4791	15	23	systems	system	NOUN
cana-4791	15	24	,	,	PUNCT
cana-4791	15	25	and	and	CCONJ
cana-4791	15	26	online	online	ADJ
cana-4791	15	27	content	content	NOUN
cana-4791	15	28	delivery	delivery	NOUN
cana-4791	15	29	.	.	PUNCT
cana-4791	16	1	keywords	keyword	NOUN
cana-4791	16	2	:	:	PUNCT
cana-4791	16	3	image	image	NOUN
cana-4791	16	4	compression	compression	NOUN
cana-4791	16	5	,	,	PUNCT
cana-4791	16	6	generative	generative	ADJ
cana-4791	16	7	adversarial	adversarial	ADJ
cana-4791	16	8	network	network	NOUN
cana-4791	16	9	,	,	PUNCT
cana-4791	16	10	deep	deep	ADJ
cana-4791	16	11	learning	learning	NOUN
cana-4791	16	12	,	,	PUNCT
cana-4791	16	13	perceptual	perceptual	ADJ
cana-4791	16	14	quality	quality	NOUN
cana-4791	16	15	,	,	PUNCT
cana-4791	16	16	learned	learn	VERB
cana-4791	16	17	representations	representation	NOUN
cana-4791	16	18	,	,	PUNCT
cana-4791	16	19	neural	neural	ADJ
cana-4791	16	20	codec	codec	NOUN
cana-4791	16	21	1	1	NUM
cana-4791	16	22	.	.	PUNCT
cana-4791	16	23	introduction	introduction	NOUN
cana-4791	16	24	due	due	ADP
cana-4791	16	25	to	to	ADP
cana-4791	16	26	the	the	DET
cana-4791	16	27	widespread	widespread	ADJ
cana-4791	16	28	use	use	NOUN
cana-4791	16	29	of	of	ADP
cana-4791	16	30	high	high	ADJ
cana-4791	16	31	-	-	PUNCT
cana-4791	16	32	resolution	resolution	NOUN
cana-4791	16	33	imaging	imaging	NOUN
cana-4791	16	34	devices	device	NOUN
cana-4791	16	35	and	and	CCONJ
cana-4791	16	36	the	the	DET
cana-4791	16	37	fast	fast	ADJ
cana-4791	16	38	growth	growth	NOUN
cana-4791	16	39	of	of	ADP
cana-4791	16	40	online	online	ADJ
cana-4791	16	41	content	content	NOUN
cana-4791	16	42	sites	site	NOUN
cana-4791	16	43	,	,	PUNCT
cana-4791	16	44	digital	digital	ADJ
cana-4791	16	45	media	medium	NOUN
cana-4791	16	46	has	have	AUX
cana-4791	16	47	grown	grow	VERB
cana-4791	16	48	very	very	ADV
cana-4791	16	49	quickly	quickly	ADV
cana-4791	16	50	.	.	PUNCT
cana-4791	17	1	this	this	PRON
cana-4791	17	2	has	have	AUX
cana-4791	17	3	increased	increase	VERB
cana-4791	17	4	the	the	DET
cana-4791	17	5	need	need	NOUN
cana-4791	17	6	for	for	ADP
cana-4791	17	7	effective	effective	ADJ
cana-4791	17	8	and	and	CCONJ
cana-4791	17	9	high	high	ADJ
cana-4791	17	10	-	-	PUNCT
cana-4791	17	11	quality	quality	NOUN
cana-4791	17	12	picture	picture	NOUN
cana-4791	17	13	compression	compression	NOUN
cana-4791	17	14	methods	method	NOUN
cana-4791	17	15	.	.	PUNCT
cana-4791	18	1	image	image	NOUN
cana-4791	18	2	compression	compression	NOUN
cana-4791	18	3	standards	standard	NOUN
cana-4791	18	4	like	like	ADP
cana-4791	18	5	jpeg	jpeg	NOUN
cana-4791	18	6	,	,	PUNCT
cana-4791	18	7	png	png	PROPN
cana-4791	18	8	,	,	PUNCT
cana-4791	18	9	and	and	CCONJ
cana-4791	18	10	webp	webp	PROPN
cana-4791	18	11	have	have	AUX
cana-4791	18	12	been	be	AUX
cana-4791	18	13	useful	useful	ADJ
cana-4791	18	14	to	to	ADP
cana-4791	18	15	the	the	DET
cana-4791	18	16	digital	digital	ADJ
cana-4791	18	17	world	world	NOUN
cana-4791	18	18	for	for	ADP
cana-4791	18	19	decades	decade	NOUN
cana-4791	18	20	by	by	ADP
cana-4791	18	21	making	make	VERB
cana-4791	18	22	files	file	NOUN
cana-4791	18	23	smaller	small	ADJ
cana-4791	18	24	so	so	SCONJ
cana-4791	18	25	they	they	PRON
cana-4791	18	26	can	can	AUX
cana-4791	18	27	be	be	AUX
cana-4791	18	28	sent	send	VERB
cana-4791	18	29	more	more	ADV
cana-4791	18	30	quickly	quickly	ADV
cana-4791	18	31	and	and	CCONJ
cana-4791	18	32	take	take	VERB
cana-4791	18	33	up	up	ADP
cana-4791	18	34	less	less	ADJ
cana-4791	18	35	space	space	NOUN
cana-4791	18	36	.	.	PUNCT
cana-4791	19	1	but	but	CCONJ
cana-4791	19	2	these	these	DET
cana-4791	19	3	old	old	ADJ
cana-4791	19	4	codecs	codec	NOUN
cana-4791	19	5	depend	depend	VERB
cana-4791	19	6	on	on	ADP
cana-4791	19	7	changes	change	NOUN
cana-4791	19	8	and	and	CCONJ
cana-4791	19	9	quantisation	quantisation	NOUN
cana-4791	19	10	methods	method	NOUN
cana-4791	19	11	that	that	PRON
cana-4791	19	12	are	be	AUX
cana-4791	19	13	carefully	carefully	ADV
cana-4791	19	14	made	make	VERB
cana-4791	19	15	by	by	ADP
cana-4791	19	16	hand	hand	NOUN
cana-4791	19	17	,	,	PUNCT
cana-4791	19	18	and	and	CCONJ
cana-4791	19	19	they	they	PRON
cana-4791	19	20	do	do	AUX
cana-4791	19	21	n't	not	PART
cana-4791	19	22	always	always	ADV
cana-4791	19	23	work	work	VERB
cana-4791	19	24	well	well	ADV
cana-4791	19	25	at	at	ADP
cana-4791	19	26	lower	low	ADJ
cana-4791	19	27	bit	bit	NOUN
cana-4791	19	28	rates	rate	NOUN
cana-4791	19	29	to	to	PART
cana-4791	19	30	keep	keep	VERB
cana-4791	19	31	the	the	DET
cana-4791	19	32	quality	quality	NOUN
cana-4791	19	33	of	of	ADP
cana-4791	19	34	the	the	DET
cana-4791	19	35	sound	sound	NOUN
cana-4791	19	36	.	.	PUNCT
cana-4791	20	1	the	the	DET
cana-4791	20	2	problems	problem	NOUN
cana-4791	20	3	with	with	ADP
cana-4791	20	4	old	old	ADJ
cana-4791	20	5	ways	way	NOUN
cana-4791	20	6	of	of	ADP
cana-4791	20	7	doing	do	VERB
cana-4791	20	8	things	thing	NOUN
cana-4791	20	9	become	become	VERB
cana-4791	20	10	clearer	clear	ADJ
cana-4791	20	11	as	as	SCONJ
cana-4791	20	12	digital	digital	ADJ
cana-4791	20	13	photos	photo	NOUN
cana-4791	20	14	get	get	VERB
cana-4791	20	15	bigger	big	ADJ
cana-4791	20	16	and	and	CCONJ
cana-4791	20	17	more	more	ADV
cana-4791	20	18	complicated	complicated	ADJ
cana-4791	20	19	,	,	PUNCT
cana-4791	20	20	and	and	CCONJ
cana-4791	20	21	as	as	SCONJ
cana-4791	20	22	they	they	PRON
cana-4791	20	23	are	be	AUX
cana-4791	20	24	used	use	VERB
cana-4791	20	25	for	for	ADP
cana-4791	20	26	things	thing	NOUN
cana-4791	20	27	like	like	ADP
cana-4791	20	28	real	real	ADJ
cana-4791	20	29	-	-	PUNCT
cana-4791	20	30	time	time	NOUN
cana-4791	20	31	monitoring	monitoring	NOUN
cana-4791	20	32	,	,	PUNCT
cana-4791	20	33	social	social	ADJ
cana-4791	20	34	media	medium	NOUN
cana-4791	20	35	,	,	PUNCT
cana-4791	20	36	and	and	CCONJ
cana-4791	20	37	taking	take	VERB
cana-4791	20	38	pictures	picture	NOUN
cana-4791	20	39	on	on	ADP
cana-4791	20	40	the	the	DET
cana-4791	20	41	go	go	NOUN
cana-4791	20	42	that	that	PRON
cana-4791	20	43	need	need	VERB
cana-4791	20	44	to	to	PART
cana-4791	20	45	be	be	AUX
cana-4791	20	46	fast	fast	ADJ
cana-4791	20	47	and	and	CCONJ
cana-4791	20	48	accurate	accurate	ADJ
cana-4791	20	49	.	.	PUNCT
cana-4791	21	1	neural	neural	ADJ
cana-4791	21	2	network	network	NOUN
cana-4791	21	3	-	-	PUNCT
cana-4791	21	4	based	base	VERB
cana-4791	21	5	picture	picture	NOUN
cana-4791	21	6	compression	compression	NOUN
cana-4791	21	7	models	model	NOUN
cana-4791	21	8	were	be	AUX
cana-4791	21	9	created	create	VERB
cana-4791	21	10	because	because	SCONJ
cana-4791	21	11	of	of	ADP
cana-4791	21	12	the	the	DET
cana-4791	21	13	need	need	NOUN
cana-4791	21	14	for	for	ADP
cana-4791	21	15	smart	smart	ADJ
cana-4791	21	16	,	,	PUNCT
cana-4791	21	17	data	data	NOUN
cana-4791	21	18	-	-	PUNCT
cana-4791	21	19	driven	drive	VERB
cana-4791	21	20	solutions	solution	NOUN
cana-4791	21	21	that	that	PRON
cana-4791	21	22	can	can	AUX
cana-4791	21	23	learn	learn	VERB
cana-4791	21	24	the	the	DET
cana-4791	21	25	best	good	ADJ
cana-4791	21	26	ways	way	NOUN
cana-4791	21	27	to	to	PART
cana-4791	21	28	reduce	reduce	VERB
cana-4791	21	29	data	datum	NOUN
cana-4791	21	30	from	from	ADP
cana-4791	21	31	it	it	PRON
cana-4791	21	32	[	[	X
cana-4791	21	33	1	1	NUM
cana-4791	21	34	]	]	PUNCT
cana-4791	21	35	.	.	PUNCT
cana-4791	22	1	communications	communication	NOUN
cana-4791	22	2	on	on	ADP
cana-4791	22	3	applied	apply	VERB
cana-4791	22	4	nonlinear	nonlinear	ADJ
cana-4791	22	5	analysis	analysis	NOUN
cana-4791	22	6	issn	issn	NOUN
cana-4791	22	7	:	:	PUNCT
cana-4791	22	8	1074	1074	NUM
cana-4791	22	9	-	-	PUNCT
cana-4791	22	10	133x	133x	NUM
cana-4791	22	11	vol	vol	NOUN
cana-4791	22	12	31	31	NUM
cana-4791	22	13	no	no	NOUN
cana-4791	22	14	.	.	PUNCT
cana-4791	23	1	1s	1s	NUM
cana-4791	23	2	(	(	PUNCT
cana-4791	23	3	2024	2024	NUM
cana-4791	23	4	)	)	PUNCT
cana-4791	23	5	216	216	NUM
cana-4791	23	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	23	7	with	with	ADP
cana-4791	23	8	the	the	DET
cana-4791	23	9	help	help	NOUN
cana-4791	23	10	of	of	ADP
cana-4791	23	11	autoencoders	autoencoder	NOUN
cana-4791	23	12	,	,	PUNCT
cana-4791	23	13	variational	variational	ADJ
cana-4791	23	14	autoencoders	autoencoder	NOUN
cana-4791	23	15	(	(	PUNCT
cana-4791	23	16	vaes	vaes	ADJ
cana-4791	23	17	)	)	PUNCT
cana-4791	23	18	,	,	PUNCT
cana-4791	23	19	and	and	CCONJ
cana-4791	23	20	convolutional	convolutional	ADJ
cana-4791	23	21	neural	neural	ADJ
cana-4791	23	22	networks	network	NOUN
cana-4791	23	23	(	(	PUNCT
cana-4791	23	24	cnns	cnns	PROPN
cana-4791	23	25	)	)	PUNCT
cana-4791	23	26	,	,	PUNCT
cana-4791	23	27	recent	recent	ADJ
cana-4791	23	28	advances	advance	NOUN
cana-4791	23	29	in	in	ADP
cana-4791	23	30	deep	deep	ADJ
cana-4791	23	31	learning	learning	NOUN
cana-4791	23	32	have	have	AUX
cana-4791	23	33	made	make	VERB
cana-4791	23	34	strong	strong	ADJ
cana-4791	23	35	replacements	replacement	NOUN
cana-4791	23	36	to	to	ADP
cana-4791	23	37	old	old	ADJ
cana-4791	23	38	compression	compression	NOUN
cana-4791	23	39	methods	method	NOUN
cana-4791	23	40	.	.	PUNCT
cana-4791	24	1	in	in	ADP
cana-4791	24	2	terms	term	NOUN
cana-4791	24	3	of	of	ADP
cana-4791	24	4	ratedistortion	ratedistortion	NOUN
cana-4791	24	5	trade	trade	NOUN
cana-4791	24	6	-	-	PUNCT
cana-4791	24	7	offs	off	NOUN
cana-4791	24	8	,	,	PUNCT
cana-4791	24	9	these	these	DET
cana-4791	24	10	models	model	NOUN
cana-4791	24	11	learn	learn	VERB
cana-4791	24	12	to	to	PART
cana-4791	24	13	pack	pack	VERB
cana-4791	24	14	pictures	picture	NOUN
cana-4791	24	15	into	into	ADP
cana-4791	24	16	small	small	ADJ
cana-4791	24	17	latent	latent	NOUN
cana-4791	24	18	representations	representation	NOUN
cana-4791	24	19	and	and	CCONJ
cana-4791	24	20	restore	restore	VERB
cana-4791	24	21	them	they	PRON
cana-4791	24	22	with	with	ADP
cana-4791	24	23	little	little	ADJ
cana-4791	24	24	loss	loss	NOUN
cana-4791	24	25	.	.	PUNCT
cana-4791	25	1	they	they	PRON
cana-4791	25	2	often	often	ADV
cana-4791	25	3	do	do	VERB
cana-4791	25	4	a	a	DET
cana-4791	25	5	better	well	ADJ
cana-4791	25	6	job	job	NOUN
cana-4791	25	7	than	than	ADP
cana-4791	25	8	standard	standard	ADJ
cana-4791	25	9	codecs	codec	NOUN
cana-4791	25	10	.	.	PUNCT
cana-4791	26	1	even	even	ADV
cana-4791	26	2	with	with	ADP
cana-4791	26	3	these	these	DET
cana-4791	26	4	changes	change	NOUN
cana-4791	26	5	,	,	PUNCT
cana-4791	26	6	one	one	NUM
cana-4791	26	7	problem	problem	NOUN
cana-4791	26	8	that	that	PRON
cana-4791	26	9	learnt	learn	VERB
cana-4791	26	10	compression	compression	NOUN
cana-4791	26	11	systems	system	NOUN
cana-4791	26	12	often	often	ADV
cana-4791	26	13	have	have	AUX
cana-4791	26	14	is	be	AUX
cana-4791	26	15	that	that	SCONJ
cana-4791	26	16	it	it	PRON
cana-4791	26	17	's	be	AUX
cana-4791	26	18	hard	hard	ADJ
cana-4791	26	19	to	to	PART
cana-4791	26	20	keep	keep	VERB
cana-4791	26	21	the	the	DET
cana-4791	26	22	sound	sound	NOUN
cana-4791	26	23	of	of	ADP
cana-4791	26	24	what	what	PRON
cana-4791	26	25	you	you	PRON
cana-4791	26	26	hear	hear	VERB
cana-4791	26	27	,	,	PUNCT
cana-4791	26	28	especially	especially	ADV
cana-4791	26	29	when	when	SCONJ
cana-4791	26	30	compressing	compress	VERB
cana-4791	26	31	at	at	ADP
cana-4791	26	32	very	very	ADV
cana-4791	26	33	low	low	ADJ
cana-4791	26	34	bitrates	bitrate	NOUN
cana-4791	26	35	[	[	X
cana-4791	26	36	2	2	NUM
cana-4791	26	37	]	]	PUNCT
cana-4791	26	38	.	.	PUNCT
cana-4791	27	1	one	one	NUM
cana-4791	27	2	way	way	NOUN
cana-4791	27	3	to	to	PART
cana-4791	27	4	use	use	VERB
cana-4791	27	5	the	the	DET
cana-4791	27	6	power	power	NOUN
cana-4791	27	7	of	of	ADP
cana-4791	27	8	generative	generative	ADJ
cana-4791	27	9	adversarial	adversarial	ADJ
cana-4791	27	10	networks	network	NOUN
cana-4791	27	11	(	(	PUNCT
cana-4791	27	12	gans	gan	NOUN
cana-4791	27	13	)	)	PUNCT
cana-4791	27	14	is	be	AUX
cana-4791	27	15	in	in	ADP
cana-4791	27	16	this	this	DET
cana-4791	27	17	way	way	NOUN
cana-4791	27	18	.	.	PUNCT
cana-4791	28	1	because	because	SCONJ
cana-4791	28	2	they	they	PRON
cana-4791	28	3	can	can	AUX
cana-4791	28	4	model	model	VERB
cana-4791	28	5	complex	complex	ADJ
cana-4791	28	6	data	datum	NOUN
cana-4791	28	7	patterns	pattern	NOUN
cana-4791	28	8	and	and	CCONJ
cana-4791	28	9	make	make	VERB
cana-4791	28	10	lifelike	lifelike	ADJ
cana-4791	28	11	effects	effect	NOUN
cana-4791	28	12	,	,	PUNCT
cana-4791	28	13	gans	gan	NOUN
cana-4791	28	14	have	have	AUX
cana-4791	28	15	done	do	VERB
cana-4791	28	16	amazingly	amazingly	ADV
cana-4791	28	17	well	well	ADV
cana-4791	28	18	in	in	ADP
cana-4791	28	19	high	high	ADJ
cana-4791	28	20	-	-	PUNCT
cana-4791	28	21	fidelity	fidelity	NOUN
cana-4791	28	22	picture	picture	NOUN
cana-4791	28	23	creation	creation	NOUN
cana-4791	28	24	and	and	CCONJ
cana-4791	28	25	super	super	ADJ
cana-4791	28	26	-	-	ADJ
cana-4791	28	27	resolution	resolution	ADJ
cana-4791	28	28	jobs	job	NOUN
cana-4791	28	29	.	.	PUNCT
cana-4791	29	1	their	their	PRON
cana-4791	29	2	antagonistic	antagonistic	ADJ
cana-4791	29	3	training	training	NOUN
cana-4791	29	4	system	system	NOUN
cana-4791	29	5	pushes	push	VERB
cana-4791	29	6	the	the	DET
cana-4791	29	7	generator	generator	NOUN
cana-4791	29	8	to	to	PART
cana-4791	29	9	make	make	VERB
cana-4791	29	10	outputs	output	NOUN
cana-4791	29	11	that	that	PRON
cana-4791	29	12	ca	can	AUX
cana-4791	29	13	n't	not	PART
cana-4791	29	14	be	be	AUX
cana-4791	29	15	told	tell	VERB
cana-4791	29	16	apart	apart	ADV
cana-4791	29	17	from	from	ADP
cana-4791	29	18	real	real	ADJ
cana-4791	29	19	images	image	NOUN
cana-4791	29	20	.	.	PUNCT
cana-4791	30	1	this	this	PRON
cana-4791	30	2	builds	build	VERB
cana-4791	30	3	a	a	DET
cana-4791	30	4	strong	strong	ADJ
cana-4791	30	5	base	base	NOUN
cana-4791	30	6	for	for	ADP
cana-4791	30	7	reconstructing	reconstruct	VERB
cana-4791	30	8	pictures	picture	NOUN
cana-4791	30	9	in	in	ADP
cana-4791	30	10	a	a	DET
cana-4791	30	11	way	way	NOUN
cana-4791	30	12	that	that	PRON
cana-4791	30	13	is	be	AUX
cana-4791	30	14	aware	aware	ADJ
cana-4791	30	15	of	of	ADP
cana-4791	30	16	how	how	SCONJ
cana-4791	30	17	people	people	NOUN
cana-4791	30	18	see	see	VERB
cana-4791	30	19	them	they	PRON
cana-4791	30	20	.	.	PUNCT
cana-4791	31	1	we	we	PRON
cana-4791	31	2	present	present	VERB
cana-4791	31	3	compressgan	compressgan	PROPN
cana-4791	31	4	,	,	PUNCT
cana-4791	31	5	a	a	DET
cana-4791	31	6	new	new	ADJ
cana-4791	31	7	gan	gan	NOUN
cana-4791	31	8	-	-	PUNCT
cana-4791	31	9	based	base	VERB
cana-4791	31	10	system	system	NOUN
cana-4791	31	11	for	for	ADP
cana-4791	31	12	learnt	learnt	ADJ
cana-4791	31	13	picture	picture	NOUN
cana-4791	31	14	compression	compression	NOUN
cana-4791	31	15	that	that	PRON
cana-4791	31	16	fills	fill	VERB
cana-4791	31	17	the	the	DET
cana-4791	31	18	gap	gap	NOUN
cana-4791	31	19	between	between	ADP
cana-4791	31	20	small	small	ADJ
cana-4791	31	21	representation	representation	NOUN
cana-4791	31	22	and	and	CCONJ
cana-4791	31	23	high	high	ADJ
cana-4791	31	24	quality	quality	NOUN
cana-4791	31	25	perception	perception	NOUN
cana-4791	31	26	.	.	PUNCT
cana-4791	32	1	compressgan	compressgan	PROPN
cana-4791	32	2	takes	take	VERB
cana-4791	32	3	the	the	DET
cana-4791	32	4	best	good	ADJ
cana-4791	32	5	parts	part	NOUN
cana-4791	32	6	of	of	ADP
cana-4791	32	7	an	an	DET
cana-4791	32	8	encoder	encoder	NOUN
cana-4791	32	9	-	-	PUNCT
cana-4791	32	10	decoder	decoder	NOUN
cana-4791	32	11	design	design	NOUN
cana-4791	32	12	and	and	CCONJ
cana-4791	32	13	the	the	DET
cana-4791	32	14	competitive	competitive	ADJ
cana-4791	32	15	nature	nature	NOUN
cana-4791	32	16	of	of	ADP
cana-4791	32	17	gans	gan	NOUN
cana-4791	32	18	to	to	PART
cana-4791	32	19	learn	learn	VERB
cana-4791	32	20	end	end	NOUN
cana-4791	32	21	-	-	PUNCT
cana-4791	32	22	to	to	ADP
cana-4791	32	23	-	-	PUNCT
cana-4791	32	24	end	end	NOUN
cana-4791	32	25	picture	picture	NOUN
cana-4791	32	26	compression	compression	NOUN
cana-4791	32	27	models	model	NOUN
cana-4791	32	28	that	that	PRON
cana-4791	32	29	can	can	AUX
cana-4791	32	30	make	make	VERB
cana-4791	32	31	reconstructions	reconstruction	NOUN
cana-4791	32	32	that	that	PRON
cana-4791	32	33	look	look	VERB
cana-4791	32	34	good	good	ADJ
cana-4791	32	35	.	.	PUNCT
cana-4791	33	1	the	the	DET
cana-4791	33	2	encoder	encoder	NOUN
cana-4791	33	3	turns	turn	VERB
cana-4791	33	4	a	a	DET
cana-4791	33	5	picture	picture	NOUN
cana-4791	33	6	input	input	NOUN
cana-4791	33	7	into	into	ADP
cana-4791	33	8	a	a	DET
cana-4791	33	9	latent	latent	ADJ
cana-4791	33	10	space	space	NOUN
cana-4791	33	11	with	with	ADP
cana-4791	33	12	few	few	ADJ
cana-4791	33	13	dimensions	dimension	NOUN
cana-4791	33	14	.	.	PUNCT
cana-4791	34	1	the	the	DET
cana-4791	34	2	latent	latent	NOUN
cana-4791	34	3	space	space	NOUN
cana-4791	34	4	is	be	AUX
cana-4791	34	5	then	then	ADV
cana-4791	34	6	quantised	quantise	VERB
cana-4791	34	7	and	and	CCONJ
cana-4791	34	8	encoded	encode	VERB
cana-4791	34	9	with	with	ADP
cana-4791	34	10	entropy	entropy	NOUN
cana-4791	34	11	to	to	PART
cana-4791	34	12	make	make	VERB
cana-4791	34	13	it	it	PRON
cana-4791	34	14	easier	easy	ADJ
cana-4791	34	15	to	to	PART
cana-4791	34	16	store	store	VERB
cana-4791	34	17	or	or	CCONJ
cana-4791	34	18	send	send	VERB
cana-4791	34	19	.	.	PUNCT
cana-4791	35	1	to	to	PART
cana-4791	35	2	make	make	VERB
cana-4791	35	3	sure	sure	ADJ
cana-4791	35	4	the	the	DET
cana-4791	35	5	picture	picture	NOUN
cana-4791	35	6	is	be	AUX
cana-4791	35	7	accurate	accurate	ADJ
cana-4791	35	8	,	,	PUNCT
cana-4791	35	9	the	the	DET
cana-4791	35	10	encoder	encoder	NOUN
cana-4791	35	11	rebuilds	rebuild	VERB
cana-4791	35	12	it	it	PRON
cana-4791	35	13	from	from	ADP
cana-4791	35	14	the	the	DET
cana-4791	35	15	hidden	hide	VERB
cana-4791	35	16	representation	representation	NOUN
cana-4791	35	17	using	use	VERB
cana-4791	35	18	both	both	CCONJ
cana-4791	35	19	reconstruction	reconstruction	NOUN
cana-4791	35	20	and	and	CCONJ
cana-4791	35	21	visual	visual	ADJ
cana-4791	35	22	losses	loss	NOUN
cana-4791	35	23	[	[	X
cana-4791	35	24	3	3	NUM
cana-4791	35	25	]	]	PUNCT
cana-4791	35	26	.	.	PUNCT
cana-4791	36	1	a	a	DET
cana-4791	36	2	discriminator	discriminator	NOUN
cana-4791	36	3	network	network	NOUN
cana-4791	36	4	is	be	AUX
cana-4791	36	5	taught	teach	VERB
cana-4791	36	6	to	to	PART
cana-4791	36	7	tell	tell	VERB
cana-4791	36	8	the	the	DET
cana-4791	36	9	difference	difference	NOUN
cana-4791	36	10	between	between	ADP
cana-4791	36	11	real	real	ADJ
cana-4791	36	12	and	and	CCONJ
cana-4791	36	13	rebuilt	rebuild	VERB
cana-4791	36	14	pictures	picture	NOUN
cana-4791	36	15	in	in	ADP
cana-4791	36	16	a	a	DET
cana-4791	36	17	hostile	hostile	ADJ
cana-4791	36	18	way	way	NOUN
cana-4791	36	19	to	to	PART
cana-4791	36	20	improve	improve	VERB
cana-4791	36	21	the	the	DET
cana-4791	36	22	output	output	NOUN
cana-4791	36	23	even	even	ADV
cana-4791	36	24	more	more	ADV
cana-4791	36	25	.	.	PUNCT
cana-4791	37	1	this	this	DET
cana-4791	37	2	forces	force	VERB
cana-4791	37	3	the	the	DET
cana-4791	37	4	generator	generator	NOUN
cana-4791	37	5	to	to	PART
cana-4791	37	6	produce	produce	VERB
cana-4791	37	7	more	more	ADV
cana-4791	37	8	realistic	realistic	ADJ
cana-4791	37	9	results	result	NOUN
cana-4791	37	10	.	.	PUNCT
cana-4791	38	1	compressgan	compressgan	PROPN
cana-4791	38	2	adds	add	VERB
cana-4791	38	3	a	a	DET
cana-4791	38	4	multi	multi	ADJ
cana-4791	38	5	-	-	ADJ
cana-4791	38	6	loss	loss	ADJ
cana-4791	38	7	objective	objective	ADJ
cana-4791	38	8	function	function	NOUN
cana-4791	38	9	that	that	PRON
cana-4791	38	10	mixes	mix	VERB
cana-4791	38	11	hostile	hostile	ADJ
cana-4791	38	12	loss	loss	NOUN
cana-4791	38	13	,	,	PUNCT
cana-4791	38	14	visual	visual	ADJ
cana-4791	38	15	loss	loss	NOUN
cana-4791	38	16	(	(	PUNCT
cana-4791	38	17	based	base	VERB
cana-4791	38	18	on	on	ADP
cana-4791	38	19	features	feature	NOUN
cana-4791	38	20	taken	take	VERB
cana-4791	38	21	from	from	ADP
cana-4791	38	22	a	a	DET
cana-4791	38	23	deep	deep	ADJ
cana-4791	38	24	network	network	NOUN
cana-4791	38	25	that	that	PRON
cana-4791	38	26	has	have	AUX
cana-4791	38	27	already	already	ADV
cana-4791	38	28	been	be	AUX
cana-4791	38	29	trained	train	VERB
cana-4791	38	30	,	,	PUNCT
cana-4791	38	31	like	like	ADP
cana-4791	38	32	vgg	vgg	NOUN
cana-4791	38	33	)	)	PUNCT
cana-4791	38	34	,	,	PUNCT
cana-4791	38	35	and	and	CCONJ
cana-4791	38	36	pixel	pixel	ADJ
cana-4791	38	37	-	-	ADJ
cana-4791	38	38	wise	wise	ADJ
cana-4791	38	39	l1	l1	PROPN
cana-4791	38	40	loss	loss	NOUN
cana-4791	38	41	to	to	PART
cana-4791	38	42	help	help	VERB
cana-4791	38	43	with	with	ADP
cana-4791	38	44	the	the	DET
cana-4791	38	45	rebuilding	rebuilding	NOUN
cana-4791	38	46	process	process	NOUN
cana-4791	38	47	.	.	PUNCT
cana-4791	39	1	this	this	DET
cana-4791	39	2	well	well	ADV
cana-4791	39	3	-	-	PUNCT
cana-4791	39	4	balanced	balance	VERB
cana-4791	39	5	training	training	NOUN
cana-4791	39	6	method	method	NOUN
cana-4791	39	7	not	not	PART
cana-4791	39	8	only	only	ADV
cana-4791	39	9	keeps	keep	VERB
cana-4791	39	10	structure	structure	NOUN
cana-4791	39	11	features	feature	NOUN
cana-4791	39	12	but	but	CCONJ
cana-4791	39	13	also	also	ADV
cana-4791	39	14	makes	make	VERB
cana-4791	39	15	the	the	DET
cana-4791	39	16	rebuilt	rebuild	VERB
cana-4791	39	17	pictures	picture	NOUN
cana-4791	39	18	look	look	VERB
cana-4791	39	19	more	more	ADV
cana-4791	39	20	real	real	ADJ
cana-4791	39	21	.	.	PUNCT
cana-4791	40	1	we	we	PRON
cana-4791	40	2	test	test	VERB
cana-4791	40	3	compressgan	compressgan	VERB
cana-4791	40	4	on	on	ADP
cana-4791	40	5	a	a	DET
cana-4791	40	6	number	number	NOUN
cana-4791	40	7	of	of	ADP
cana-4791	40	8	standard	standard	ADJ
cana-4791	40	9	datasets	dataset	NOUN
cana-4791	40	10	and	and	CCONJ
cana-4791	40	11	see	see	VERB
cana-4791	40	12	how	how	SCONJ
cana-4791	40	13	it	it	PRON
cana-4791	40	14	stacks	stack	VERB
cana-4791	40	15	up	up	ADP
cana-4791	40	16	against	against	ADP
cana-4791	40	17	both	both	CCONJ
cana-4791	40	18	traditional	traditional	ADJ
cana-4791	40	19	and	and	CCONJ
cana-4791	40	20	learnt	learn	VERB
cana-4791	40	21	picture	picture	NOUN
cana-4791	40	22	compression	compression	NOUN
cana-4791	40	23	methods	method	NOUN
cana-4791	40	24	.	.	PUNCT
cana-4791	41	1	peak	peak	NOUN
cana-4791	41	2	signal	signal	NOUN
cana-4791	41	3	-	-	PUNCT
cana-4791	41	4	to	to	ADP
cana-4791	41	5	-	-	PUNCT
cana-4791	41	6	noise	noise	NOUN
cana-4791	41	7	ratio	ratio	NOUN
cana-4791	41	8	(	(	PUNCT
cana-4791	41	9	psnr	psnr	NOUN
cana-4791	41	10	)	)	PUNCT
cana-4791	41	11	,	,	PUNCT
cana-4791	41	12	structural	structural	ADJ
cana-4791	41	13	similarity	similarity	NOUN
cana-4791	41	14	index	index	NOUN
cana-4791	41	15	(	(	PUNCT
cana-4791	41	16	ssim	ssim	NOUN
cana-4791	41	17	)	)	PUNCT
cana-4791	41	18	,	,	PUNCT
cana-4791	41	19	and	and	CCONJ
cana-4791	41	20	perceived	perceive	VERB
cana-4791	41	21	quality	quality	NOUN
cana-4791	41	22	measures	measure	NOUN
cana-4791	41	23	like	like	ADP
cana-4791	41	24	lpips	lpip	NOUN
cana-4791	41	25	(	(	PUNCT
cana-4791	41	26	learnt	learn	VERB
cana-4791	41	27	perceived	perceive	VERB
cana-4791	41	28	image	image	NOUN
cana-4791	41	29	patch	patch	NOUN
cana-4791	41	30	similarity	similarity	NOUN
cana-4791	41	31	)	)	PUNCT
cana-4791	41	32	show	show	VERB
cana-4791	41	33	that	that	SCONJ
cana-4791	41	34	our	our	PRON
cana-4791	41	35	studies	study	NOUN
cana-4791	41	36	are	be	AUX
cana-4791	41	37	better	well	ADJ
cana-4791	41	38	.	.	PUNCT
cana-4791	42	1	compressgan	compressgan	PROPN
cana-4791	42	2	also	also	ADV
cana-4791	42	3	works	work	VERB
cana-4791	42	4	well	well	ADV
cana-4791	42	5	across	across	ADP
cana-4791	42	6	a	a	DET
cana-4791	42	7	wide	wide	ADJ
cana-4791	42	8	range	range	NOUN
cana-4791	42	9	of	of	ADP
cana-4791	42	10	picture	picture	NOUN
cana-4791	42	11	domains	domain	NOUN
cana-4791	42	12	and	and	CCONJ
cana-4791	42	13	is	be	AUX
cana-4791	42	14	still	still	ADV
cana-4791	42	15	useful	useful	ADJ
cana-4791	42	16	at	at	ADP
cana-4791	42	17	low	low	ADJ
cana-4791	42	18	bitrates	bitrate	NOUN
cana-4791	42	19	,	,	PUNCT
cana-4791	42	20	where	where	SCONJ
cana-4791	42	21	other	other	ADJ
cana-4791	42	22	methods	method	NOUN
cana-4791	42	23	fail	fail	VERB
cana-4791	42	24	.	.	PUNCT
cana-4791	43	1	this	this	DET
cana-4791	43	2	paper	paper	NOUN
cana-4791	43	3	makes	make	VERB
cana-4791	43	4	three	three	NUM
cana-4791	43	5	main	main	ADJ
cana-4791	43	6	contributions	contribution	NOUN
cana-4791	43	7	:	:	PUNCT
cana-4791	43	8	(	(	PUNCT
cana-4791	43	9	1	1	X
cana-4791	43	10	)	)	PUNCT
cana-4791	43	11	it	it	PRON
cana-4791	43	12	suggests	suggest	VERB
cana-4791	43	13	a	a	DET
cana-4791	43	14	gan	gan	NOUN
cana-4791	43	15	-	-	PUNCT
cana-4791	43	16	based	base	VERB
cana-4791	43	17	framework	framework	NOUN
cana-4791	43	18	for	for	ADP
cana-4791	43	19	learnt	learnt	ADJ
cana-4791	43	20	image	image	NOUN
cana-4791	43	21	compression	compression	NOUN
cana-4791	43	22	that	that	PRON
cana-4791	43	23	performs	perform	VERB
cana-4791	43	24	well	well	ADV
cana-4791	43	25	across	across	ADP
cana-4791	43	26	a	a	DET
cana-4791	43	27	number	number	NOUN
cana-4791	43	28	of	of	ADP
cana-4791	43	29	evaluation	evaluation	NOUN
cana-4791	43	30	metrics	metric	NOUN
cana-4791	43	31	;	;	PUNCT
cana-4791	43	32	(	(	PUNCT
cana-4791	43	33	2	2	X
cana-4791	43	34	)	)	PUNCT
cana-4791	43	35	it	it	PRON
cana-4791	43	36	describes	describe	VERB
cana-4791	43	37	a	a	DET
cana-4791	43	38	multi	multi	ADJ
cana-4791	43	39	-	-	ADJ
cana-4791	43	40	objective	objective	ADJ
cana-4791	43	41	training	training	NOUN
cana-4791	43	42	strategy	strategy	NOUN
cana-4791	43	43	that	that	PRON
cana-4791	43	44	uses	use	VERB
cana-4791	43	45	adversarial	adversarial	ADJ
cana-4791	43	46	and	and	CCONJ
cana-4791	43	47	perceptual	perceptual	ADJ
cana-4791	43	48	cues	cue	NOUN
cana-4791	43	49	to	to	PART
cana-4791	43	50	improve	improve	VERB
cana-4791	43	51	image	image	NOUN
cana-4791	43	52	quality	quality	NOUN
cana-4791	43	53	;	;	PUNCT
cana-4791	43	54	and	and	CCONJ
cana-4791	43	55	(	(	PUNCT
cana-4791	43	56	3	3	X
cana-4791	43	57	)	)	PUNCT
cana-4791	43	58	it	it	PRON
cana-4791	43	59	does	do	VERB
cana-4791	43	60	a	a	DET
cana-4791	43	61	lot	lot	NOUN
cana-4791	43	62	of	of	ADP
cana-4791	43	63	experiments	experiment	NOUN
cana-4791	43	64	to	to	PART
cana-4791	43	65	show	show	VERB
cana-4791	43	66	that	that	SCONJ
cana-4791	43	67	compressgan	compressgan	PROPN
cana-4791	43	68	works	work	VERB
cana-4791	43	69	well	well	ADV
cana-4791	43	70	and	and	CCONJ
cana-4791	43	71	is	be	AUX
cana-4791	43	72	flexible	flexible	ADJ
cana-4791	43	73	enough	enough	ADV
cana-4791	43	74	for	for	ADP
cana-4791	43	75	modern	modern	ADJ
cana-4791	43	76	image	image	NOUN
cana-4791	43	77	compression	compression	NOUN
cana-4791	43	78	needs	need	NOUN
cana-4791	43	79	.	.	PUNCT
cana-4791	44	1	2	2	X
cana-4791	44	2	.	.	X
cana-4791	44	3	related	relate	VERB
cana-4791	44	4	work	work	NOUN
cana-4791	44	5	a	a	DET
cana-4791	44	6	lot	lot	NOUN
cana-4791	44	7	of	of	ADP
cana-4791	44	8	old	old	ADJ
cana-4791	44	9	picture	picture	NOUN
cana-4791	44	10	compression	compression	NOUN
cana-4791	44	11	methods	method	NOUN
cana-4791	44	12	,	,	PUNCT
cana-4791	44	13	like	like	ADP
cana-4791	44	14	jpeg	jpeg	NOUN
cana-4791	44	15	,	,	PUNCT
cana-4791	44	16	jpeg2000	jpeg2000	PROPN
cana-4791	44	17	,	,	PUNCT
cana-4791	44	18	and	and	CCONJ
cana-4791	44	19	webp	webp	PROPN
cana-4791	44	20	,	,	PUNCT
cana-4791	44	21	use	use	VERB
cana-4791	44	22	discrete	discrete	ADJ
cana-4791	44	23	cosine	cosine	NOUN
cana-4791	44	24	transforms	transform	VERB
cana-4791	44	25	(	(	PUNCT
cana-4791	44	26	dct	dct	PROPN
cana-4791	44	27	)	)	PUNCT
cana-4791	44	28	,	,	PUNCT
cana-4791	44	29	quantisation	quantisation	NOUN
cana-4791	44	30	,	,	PUNCT
cana-4791	44	31	and	and	CCONJ
cana-4791	44	32	huffman	huffman	PROPN
cana-4791	44	33	coding	coding	PROPN
cana-4791	44	34	,	,	PUNCT
cana-4791	44	35	along	along	ADP
cana-4791	44	36	with	with	ADP
cana-4791	44	37	statistical	statistical	ADJ
cana-4791	44	38	entropy	entropy	NOUN
cana-4791	44	39	modelling	modelling	NOUN
cana-4791	44	40	and	and	CCONJ
cana-4791	44	41	block	block	NOUN
cana-4791	44	42	-	-	PUNCT
cana-4791	44	43	based	base	VERB
cana-4791	44	44	transform	transform	NOUN
cana-4791	44	45	coding	code	VERB
cana-4791	44	46	.	.	PUNCT
cana-4791	45	1	the	the	DET
cana-4791	45	2	computations	computation	NOUN
cana-4791	45	3	for	for	ADP
cana-4791	45	4	these	these	DET
cana-4791	45	5	methods	method	NOUN
cana-4791	45	6	are	be	AUX
cana-4791	45	7	easy	easy	ADJ
cana-4791	45	8	and	and	CCONJ
cana-4791	45	9	they	they	PRON
cana-4791	45	10	work	work	VERB
cana-4791	45	11	with	with	ADP
cana-4791	45	12	many	many	ADJ
cana-4791	45	13	systems	system	NOUN
cana-4791	45	14	.	.	PUNCT
cana-4791	46	1	however	however	ADV
cana-4791	46	2	,	,	PUNCT
cana-4791	46	3	they	they	PRON
cana-4791	46	4	do	do	AUX
cana-4791	46	5	n't	not	PART
cana-4791	46	6	work	work	VERB
cana-4791	46	7	as	as	ADV
cana-4791	46	8	well	well	ADV
cana-4791	46	9	at	at	ADP
cana-4791	46	10	low	low	ADJ
cana-4791	46	11	bitrates	bitrate	NOUN
cana-4791	46	12	,	,	PUNCT
cana-4791	46	13	where	where	SCONJ
cana-4791	46	14	they	they	PRON
cana-4791	46	15	cause	cause	VERB
cana-4791	46	16	blocking	block	VERB
cana-4791	46	17	artefacts	artefact	NOUN
cana-4791	46	18	,	,	PUNCT
cana-4791	46	19	blurring	blurring	NOUN
cana-4791	46	20	,	,	PUNCT
cana-4791	46	21	and	and	CCONJ
cana-4791	46	22	the	the	DET
cana-4791	46	23	loss	loss	NOUN
cana-4791	46	24	of	of	ADP
cana-4791	46	25	high	high	ADJ
cana-4791	46	26	-	-	PUNCT
cana-4791	46	27	frequency	frequency	NOUN
cana-4791	46	28	features	feature	NOUN
cana-4791	46	29	[	[	X
cana-4791	46	30	4	4	NUM
cana-4791	46	31	]	]	PUNCT
cana-4791	46	32	.	.	PUNCT
cana-4791	47	1	in	in	ADP
cana-4791	47	2	recent	recent	ADJ
cana-4791	47	3	years	year	NOUN
cana-4791	47	4	,	,	PUNCT
cana-4791	47	5	learnt	learn	VERB
cana-4791	47	6	image	image	NOUN
cana-4791	47	7	compression	compression	NOUN
cana-4791	47	8	methods	method	NOUN
cana-4791	47	9	have	have	AUX
cana-4791	47	10	become	become	VERB
cana-4791	47	11	a	a	DET
cana-4791	47	12	potential	potential	ADJ
cana-4791	47	13	option	option	NOUN
cana-4791	47	14	.	.	PUNCT
cana-4791	48	1	they	they	PRON
cana-4791	48	2	use	use	VERB
cana-4791	48	3	neural	neural	ADJ
cana-4791	48	4	networks	network	NOUN
cana-4791	48	5	to	to	PART
cana-4791	48	6	try	try	VERB
cana-4791	48	7	to	to	PART
cana-4791	48	8	make	make	VERB
cana-4791	48	9	the	the	DET
cana-4791	48	10	whole	whole	ADJ
cana-4791	48	11	compression	compression	NOUN
cana-4791	48	12	process	process	NOUN
cana-4791	48	13	better	well	ADV
cana-4791	48	14	.	.	PUNCT
cana-4791	49	1	most	most	ADJ
cana-4791	49	2	of	of	ADP
cana-4791	49	3	the	the	DET
cana-4791	49	4	time	time	NOUN
cana-4791	49	5	,	,	PUNCT
cana-4791	49	6	these	these	DET
cana-4791	49	7	models	model	NOUN
cana-4791	49	8	use	use	VERB
cana-4791	49	9	autoencoder	autoencoder	NOUN
cana-4791	49	10	-	-	PUNCT
cana-4791	49	11	based	base	VERB
cana-4791	49	12	designs	design	NOUN
cana-4791	49	13	,	,	PUNCT
cana-4791	49	14	in	in	ADP
cana-4791	49	15	which	which	PRON
cana-4791	49	16	an	an	DET
cana-4791	49	17	encoder	encoder	NOUN
cana-4791	49	18	network	network	NOUN
cana-4791	49	19	shrinks	shrink	VERB
cana-4791	49	20	the	the	DET
cana-4791	49	21	input	input	NOUN
cana-4791	49	22	picture	picture	NOUN
cana-4791	49	23	into	into	ADP
cana-4791	49	24	a	a	DET
cana-4791	49	25	hidden	hide	VERB
cana-4791	49	26	representation	representation	NOUN
cana-4791	49	27	and	and	CCONJ
cana-4791	49	28	a	a	DET
cana-4791	49	29	decoder	decoder	NOUN
cana-4791	49	30	uses	use	VERB
cana-4791	49	31	this	this	DET
cana-4791	49	32	representation	representation	NOUN
cana-4791	49	33	to	to	PART
cana-4791	49	34	build	build	VERB
cana-4791	49	35	the	the	DET
cana-4791	49	36	image	image	NOUN
cana-4791	49	37	back	back	ADV
cana-4791	49	38	up	up	ADP
cana-4791	49	39	[	[	X
cana-4791	49	40	5	5	NUM
cana-4791	49	41	,	,	PUNCT
cana-4791	49	42	6	6	NUM
cana-4791	49	43	]	]	PUNCT
cana-4791	49	44	.	.	PUNCT
cana-4791	50	1	a	a	DET
cana-4791	50	2	variational	variational	ADJ
cana-4791	50	3	autoencoder	autoencoder	NOUN
cana-4791	50	4	(	(	PUNCT
cana-4791	50	5	vae)-based	vae)-base	VERB
cana-4791	50	6	system	system	NOUN
cana-4791	50	7	was	be	AUX
cana-4791	50	8	one	one	NUM
cana-4791	50	9	of	of	ADP
cana-4791	50	10	the	the	DET
cana-4791	50	11	first	first	ADJ
cana-4791	50	12	methods	method	NOUN
cana-4791	50	13	in	in	ADP
cana-4791	50	14	this	this	DET
cana-4791	50	15	field	field	NOUN
cana-4791	50	16	.	.	PUNCT
cana-4791	51	1	it	it	PRON
cana-4791	51	2	made	make	VERB
cana-4791	51	3	it	it	PRON
cana-4791	51	4	possible	possible	ADJ
cana-4791	51	5	to	to	PART
cana-4791	51	6	model	model	VERB
cana-4791	51	7	uncertainty	uncertainty	NOUN
cana-4791	51	8	in	in	ADP
cana-4791	51	9	the	the	DET
cana-4791	51	10	latent	latent	NOUN
cana-4791	51	11	space	space	NOUN
cana-4791	51	12	and	and	CCONJ
cana-4791	51	13	made	make	VERB
cana-4791	51	14	the	the	DET
cana-4791	51	15	generalisation	generalisation	NOUN
cana-4791	51	16	better	well	ADV
cana-4791	51	17	across	across	ADP
cana-4791	51	18	picture	picture	NOUN
cana-4791	51	19	distributions	distribution	NOUN
cana-4791	51	20	[	[	X
cana-4791	51	21	7	7	NUM
cana-4791	51	22	]	]	PUNCT
cana-4791	51	23	.	.	PUNCT
cana-4791	52	1	later	later	ADJ
cana-4791	52	2	research	research	PROPN
cana-4791	52	3	tried	try	VERB
cana-4791	52	4	to	to	PART
cana-4791	52	5	improve	improve	VERB
cana-4791	52	6	the	the	DET
cana-4791	52	7	rate	rate	NOUN
cana-4791	52	8	-	-	PUNCT
cana-4791	52	9	distortion	distortion	NOUN
cana-4791	52	10	trade	trade	NOUN
cana-4791	52	11	-	-	PUNCT
cana-4791	52	12	off	off	NOUN
cana-4791	52	13	by	by	ADP
cana-4791	52	14	using	use	VERB
cana-4791	52	15	learnt	learnt	PROPN
cana-4791	52	16	entropy	entropy	NOUN
cana-4791	52	17	models	model	NOUN
cana-4791	52	18	,	,	PUNCT
cana-4791	52	19	like	like	ADP
cana-4791	52	20	hyperpriors	hyperprior	NOUN
cana-4791	52	21	and	and	CCONJ
cana-4791	52	22	autoregressive	autoregressive	ADJ
cana-4791	52	23	components	component	NOUN
cana-4791	52	24	,	,	PUNCT
cana-4791	52	25	to	to	PART
cana-4791	52	26	better	well	ADV
cana-4791	52	27	understand	understand	VERB
cana-4791	52	28	how	how	SCONJ
cana-4791	52	29	hidden	hidden	ADJ
cana-4791	52	30	codes	code	NOUN
cana-4791	52	31	are	be	AUX
cana-4791	52	32	distributed	distribute	VERB
cana-4791	52	33	[	[	X
cana-4791	52	34	8	8	NUM
cana-4791	52	35	,	,	PUNCT
cana-4791	52	36	9	9	NUM
cana-4791	52	37	]	]	PUNCT
cana-4791	52	38	.	.	PUNCT
cana-4791	53	1	even	even	ADV
cana-4791	53	2	though	though	SCONJ
cana-4791	53	3	they	they	PRON
cana-4791	53	4	've	have	AUX
cana-4791	53	5	come	come	VERB
cana-4791	53	6	a	a	DET
cana-4791	53	7	long	long	ADJ
cana-4791	53	8	way	way	NOUN
cana-4791	53	9	,	,	PUNCT
cana-4791	53	10	these	these	DET
cana-4791	53	11	autoencoder	autoencoder	NOUN
cana-4791	53	12	-	-	PUNCT
cana-4791	53	13	based	base	VERB
cana-4791	53	14	methods	method	NOUN
cana-4791	53	15	still	still	ADV
cana-4791	53	16	have	have	VERB
cana-4791	53	17	trouble	trouble	NOUN
cana-4791	53	18	keeping	keep	VERB
cana-4791	53	19	quality	quality	NOUN
cana-4791	53	20	,	,	PUNCT
cana-4791	53	21	especially	especially	ADV
cana-4791	53	22	in	in	ADP
cana-4791	53	23	low	low	ADJ
cana-4791	53	24	-	-	PUNCT
cana-4791	53	25	bitrate	bitrate	NOUN
cana-4791	53	26	settings	setting	NOUN
cana-4791	53	27	.	.	PUNCT
cana-4791	54	1	people	people	NOUN
cana-4791	54	2	started	start	VERB
cana-4791	54	3	to	to	PART
cana-4791	54	4	study	study	VERB
cana-4791	54	5	how	how	SCONJ
cana-4791	54	6	to	to	PART
cana-4791	54	7	improve	improve	VERB
cana-4791	54	8	the	the	DET
cana-4791	54	9	quality	quality	NOUN
cana-4791	54	10	of	of	ADP
cana-4791	54	11	reconstructions	reconstruction	NOUN
cana-4791	54	12	by	by	ADP
cana-4791	54	13	adding	add	VERB
cana-4791	54	14	perceptual	perceptual	ADJ
cana-4791	54	15	losses	loss	NOUN
cana-4791	54	16	,	,	PUNCT
cana-4791	54	17	like	like	ADP
cana-4791	54	18	those	those	PRON
cana-4791	54	19	that	that	PRON
cana-4791	54	20	come	come	VERB
cana-4791	54	21	from	from	ADP
cana-4791	54	22	deep	deep	ADJ
cana-4791	54	23	convolutional	convolutional	ADJ
cana-4791	54	24	features	feature	NOUN
cana-4791	54	25	(	(	PUNCT
cana-4791	54	26	for	for	ADP
cana-4791	54	27	example	example	NOUN
cana-4791	54	28	,	,	PUNCT
cana-4791	54	29	vgg	vgg	NOUN
cana-4791	54	30	-	-	PUNCT
cana-4791	54	31	based	base	VERB
cana-4791	54	32	perceptual	perceptual	ADJ
cana-4791	54	33	loss	loss	NOUN
cana-4791	54	34	)	)	PUNCT
cana-4791	54	35	,	,	PUNCT
cana-4791	54	36	to	to	ADP
cana-4791	54	37	the	the	DET
cana-4791	54	38	training	training	NOUN
cana-4791	54	39	process	process	NOUN
cana-4791	54	40	[	[	X
cana-4791	54	41	10	10	NUM
cana-4791	54	42	]	]	PUNCT
cana-4791	54	43	.	.	PUNCT
cana-4791	55	1	traditional	traditional	ADJ
cana-4791	55	2	pixel	pixel	ADJ
cana-4791	55	3	-	-	ADJ
cana-4791	55	4	wise	wise	ADJ
cana-4791	55	5	measures	measure	NOUN
cana-4791	55	6	,	,	PUNCT
cana-4791	55	7	such	such	ADJ
cana-4791	55	8	as	as	ADP
cana-4791	55	9	mean	mean	NOUN
cana-4791	55	10	squared	square	VERB
cana-4791	55	11	error	error	NOUN
cana-4791	55	12	(	(	PUNCT
cana-4791	55	13	mse	mse	NOUN
cana-4791	55	14	)	)	PUNCT
cana-4791	55	15	,	,	PUNCT
cana-4791	55	16	tend	tend	VERB
cana-4791	55	17	to	to	PART
cana-4791	55	18	miss	miss	VERB
cana-4791	55	19	structure	structure	NOUN
cana-4791	55	20	and	and	CCONJ
cana-4791	55	21	contextual	contextual	ADJ
cana-4791	55	22	information	information	NOUN
cana-4791	55	23	that	that	PRON
cana-4791	55	24	these	these	DET
cana-4791	55	25	losses	loss	NOUN
cana-4791	55	26	help	help	VERB
cana-4791	55	27	keep	keep	VERB
cana-4791	55	28	.	.	PUNCT
cana-4791	56	1	another	another	DET
cana-4791	56	2	big	big	ADJ
cana-4791	56	3	step	step	NOUN
cana-4791	56	4	forward	forward	ADV
cana-4791	56	5	was	be	AUX
cana-4791	56	6	the	the	DET
cana-4791	56	7	addition	addition	NOUN
cana-4791	56	8	of	of	ADP
cana-4791	56	9	hostile	hostile	ADJ
cana-4791	56	10	losses	loss	NOUN
cana-4791	56	11	through	through	ADP
cana-4791	56	12	the	the	DET
cana-4791	56	13	use	use	NOUN
cana-4791	56	14	of	of	ADP
cana-4791	56	15	generative	generative	ADJ
cana-4791	56	16	hostile	hostile	ADJ
cana-4791	56	17	networks	network	NOUN
cana-4791	56	18	(	(	PUNCT
cana-4791	56	19	gans	gan	NOUN
cana-4791	56	20	)	)	PUNCT
cana-4791	56	21	.	.	PUNCT
cana-4791	57	1	image	image	NOUN
cana-4791	57	2	creation	creation	NOUN
cana-4791	57	3	and	and	CCONJ
cana-4791	57	4	super	super	ADJ
cana-4791	57	5	-	-	ADJ
cana-4791	57	6	resolution	resolution	ADJ
cana-4791	57	7	methods	method	NOUN
cana-4791	57	8	based	base	VERB
cana-4791	57	9	on	on	ADP
cana-4791	57	10	gans	gan	NOUN
cana-4791	57	11	were	be	AUX
cana-4791	57	12	shown	show	VERB
cana-4791	57	13	to	to	PART
cana-4791	57	14	be	be	AUX
cana-4791	57	15	able	able	ADJ
cana-4791	57	16	to	to	PART
cana-4791	57	17	create	create	VERB
cana-4791	57	18	high	high	ADJ
cana-4791	57	19	-	-	PUNCT
cana-4791	57	20	fidelity	fidelity	NOUN
cana-4791	57	21	patterns	pattern	NOUN
cana-4791	57	22	and	and	CCONJ
cana-4791	57	23	features	feature	NOUN
cana-4791	57	24	that	that	PRON
cana-4791	57	25	look	look	VERB
cana-4791	57	26	real	real	ADJ
cana-4791	57	27	[	[	X
cana-4791	57	28	11	11	NUM
cana-4791	57	29	,	,	PUNCT
cana-4791	57	30	12	12	NUM
cana-4791	57	31	]	]	PUNCT
cana-4791	57	32	.	.	PUNCT
cana-4791	58	1	when	when	SCONJ
cana-4791	58	2	this	this	DET
cana-4791	58	3	idea	idea	NOUN
cana-4791	58	4	was	be	AUX
cana-4791	58	5	applied	apply	VERB
cana-4791	58	6	to	to	ADP
cana-4791	58	7	image	image	NOUN
cana-4791	58	8	compression	compression	NOUN
cana-4791	58	9	,	,	PUNCT
cana-4791	58	10	it	it	PRON
cana-4791	58	11	led	lead	VERB
cana-4791	58	12	to	to	PART
cana-4791	58	13	gan	gan	VERB
cana-4791	58	14	-	-	PUNCT
cana-4791	58	15	based	base	VERB
cana-4791	58	16	models	model	NOUN
cana-4791	58	17	where	where	SCONJ
cana-4791	58	18	a	a	DET
cana-4791	58	19	discriminator	discriminator	NOUN
cana-4791	58	20	network	network	NOUN
cana-4791	58	21	leads	lead	VERB
cana-4791	58	22	the	the	DET
cana-4791	58	23	rebuilding	rebuilding	NOUN
cana-4791	58	24	process	process	NOUN
cana-4791	58	25	by	by	ADP
cana-4791	58	26	checking	check	VERB
cana-4791	58	27	how	how	SCONJ
cana-4791	58	28	realistic	realistic	ADJ
cana-4791	58	29	the	the	DET
cana-4791	58	30	pictures	picture	NOUN
cana-4791	58	31	are	be	AUX
cana-4791	58	32	to	to	ADP
cana-4791	58	33	the	the	DET
cana-4791	58	34	human	human	ADJ
cana-4791	58	35	eye	eye	NOUN
cana-4791	58	36	.	.	PUNCT
cana-4791	59	1	one	one	NUM
cana-4791	59	2	important	important	ADJ
cana-4791	59	3	area	area	NOUN
cana-4791	59	4	of	of	ADP
cana-4791	59	5	research	research	NOUN
cana-4791	59	6	used	use	VERB
cana-4791	59	7	gans	gan	NOUN
cana-4791	59	8	and	and	CCONJ
cana-4791	59	9	autoencoders	autoencoder	NOUN
cana-4791	59	10	together	together	ADV
cana-4791	59	11	to	to	PART
cana-4791	59	12	create	create	VERB
cana-4791	59	13	a	a	DET
cana-4791	59	14	single	single	ADJ
cana-4791	59	15	model	model	NOUN
cana-4791	59	16	that	that	PRON
cana-4791	59	17	could	could	AUX
cana-4791	59	18	both	both	DET
cana-4791	59	19	communications	communication	NOUN
cana-4791	59	20	on	on	ADP
cana-4791	59	21	applied	apply	VERB
cana-4791	59	22	nonlinear	nonlinear	ADJ
cana-4791	59	23	analysis	analysis	NOUN
cana-4791	59	24	issn	issn	NOUN
cana-4791	59	25	:	:	PUNCT
cana-4791	59	26	1074	1074	NUM
cana-4791	59	27	-	-	PUNCT
cana-4791	59	28	133x	133x	NUM
cana-4791	59	29	vol	vol	NOUN
cana-4791	59	30	31	31	NUM
cana-4791	59	31	no	no	NOUN
cana-4791	59	32	.	.	PUNCT
cana-4791	60	1	1s	1s	NUM
cana-4791	60	2	(	(	PUNCT
cana-4791	60	3	2024	2024	NUM
cana-4791	60	4	)	)	PUNCT
cana-4791	60	5	217	217	NUM
cana-4791	60	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	60	7	reduce	reduce	VERB
cana-4791	60	8	picture	picture	NOUN
cana-4791	60	9	size	size	NOUN
cana-4791	60	10	and	and	CCONJ
cana-4791	60	11	improve	improve	VERB
cana-4791	60	12	its	its	PRON
cana-4791	60	13	quality	quality	NOUN
cana-4791	60	14	[	[	X
cana-4791	60	15	13	13	NUM
cana-4791	60	16	]	]	PUNCT
cana-4791	60	17	.	.	PUNCT
cana-4791	61	1	these	these	DET
cana-4791	61	2	models	model	NOUN
cana-4791	61	3	used	use	VERB
cana-4791	61	4	competing	compete	VERB
cana-4791	61	5	goals	goal	NOUN
cana-4791	61	6	to	to	PART
cana-4791	61	7	improve	improve	VERB
cana-4791	61	8	small	small	ADJ
cana-4791	61	9	texture	texture	ADJ
cana-4791	61	10	details	detail	NOUN
cana-4791	61	11	while	while	SCONJ
cana-4791	61	12	keeping	keep	VERB
cana-4791	61	13	the	the	DET
cana-4791	61	14	general	general	ADJ
cana-4791	61	15	meaning	meaning	NOUN
cana-4791	61	16	of	of	ADP
cana-4791	61	17	the	the	DET
cana-4791	61	18	data	datum	NOUN
cana-4791	61	19	.	.	PUNCT
cana-4791	62	1	to	to	PART
cana-4791	62	2	get	get	VERB
cana-4791	62	3	a	a	DET
cana-4791	62	4	more	more	ADV
cana-4791	62	5	balanced	balanced	ADJ
cana-4791	62	6	compression	compression	NOUN
cana-4791	62	7	model	model	NOUN
cana-4791	62	8	[	[	X
cana-4791	62	9	14	14	NUM
cana-4791	62	10	,	,	PUNCT
cana-4791	62	11	15	15	NUM
cana-4791	62	12	]	]	PUNCT
cana-4791	62	13	,	,	PUNCT
cana-4791	62	14	newer	new	ADJ
cana-4791	62	15	methods	method	NOUN
cana-4791	62	16	have	have	AUX
cana-4791	62	17	looked	look	VERB
cana-4791	62	18	into	into	ADP
cana-4791	62	19	mixed	mixed	ADJ
cana-4791	62	20	training	training	NOUN
cana-4791	62	21	goals	goal	NOUN
cana-4791	62	22	that	that	PRON
cana-4791	62	23	mix	mix	VERB
cana-4791	62	24	hostile	hostile	ADJ
cana-4791	62	25	,	,	PUNCT
cana-4791	62	26	perceptual	perceptual	ADJ
cana-4791	62	27	,	,	PUNCT
cana-4791	62	28	and	and	CCONJ
cana-4791	62	29	distorting	distort	VERB
cana-4791	62	30	losses	loss	NOUN
cana-4791	62	31	.	.	PUNCT
cana-4791	63	1	a	a	DET
cana-4791	63	2	multicomponent	multicomponent	NOUN
cana-4791	63	3	loss	loss	NOUN
cana-4791	63	4	function	function	NOUN
cana-4791	63	5	is	be	AUX
cana-4791	63	6	often	often	ADV
cana-4791	63	7	used	use	VERB
cana-4791	63	8	in	in	ADP
cana-4791	63	9	these	these	DET
cana-4791	63	10	kinds	kind	NOUN
cana-4791	63	11	of	of	ADP
cana-4791	63	12	systems	system	NOUN
cana-4791	63	13	.	.	PUNCT
cana-4791	64	1	each	each	DET
cana-4791	64	2	component	component	NOUN
cana-4791	64	3	is	be	AUX
cana-4791	64	4	in	in	ADP
cana-4791	64	5	charge	charge	NOUN
cana-4791	64	6	of	of	ADP
cana-4791	64	7	improving	improve	VERB
cana-4791	64	8	a	a	DET
cana-4791	64	9	different	different	ADJ
cana-4791	64	10	part	part	NOUN
cana-4791	64	11	of	of	ADP
cana-4791	64	12	the	the	DET
cana-4791	64	13	rebuilt	rebuilt	ADJ
cana-4791	64	14	picture	picture	NOUN
cana-4791	64	15	.	.	PUNCT
cana-4791	65	1	some	some	DET
cana-4791	65	2	researchers	researcher	NOUN
cana-4791	65	3	used	use	VERB
cana-4791	65	4	attention	attention	NOUN
cana-4791	65	5	mechanisms	mechanism	NOUN
cana-4791	65	6	and	and	CCONJ
cana-4791	65	7	hierarchical	hierarchical	ADJ
cana-4791	65	8	latent	latent	NOUN
cana-4791	65	9	structures	structure	NOUN
cana-4791	65	10	to	to	PART
cana-4791	65	11	improve	improve	VERB
cana-4791	65	12	the	the	DET
cana-4791	65	13	representation	representation	NOUN
cana-4791	65	14	and	and	CCONJ
cana-4791	65	15	draw	draw	VERB
cana-4791	65	16	attention	attention	NOUN
cana-4791	65	17	to	to	ADP
cana-4791	65	18	key	key	ADJ
cana-4791	65	19	parts	part	NOUN
cana-4791	65	20	of	of	ADP
cana-4791	65	21	the	the	DET
cana-4791	65	22	picture	picture	NOUN
cana-4791	65	23	while	while	SCONJ
cana-4791	65	24	it	it	PRON
cana-4791	65	25	was	be	AUX
cana-4791	65	26	being	be	AUX
cana-4791	65	27	compressed	compress	VERB
cana-4791	65	28	and	and	CCONJ
cana-4791	65	29	reconstructed	reconstruct	VERB
cana-4791	65	30	[	[	X
cana-4791	65	31	16	16	NUM
cana-4791	65	32	]	]	PUNCT
cana-4791	65	33	.	.	PUNCT
cana-4791	66	1	other	other	ADJ
cana-4791	66	2	research	research	NOUN
cana-4791	66	3	has	have	AUX
cana-4791	66	4	used	use	VERB
cana-4791	66	5	recurrent	recurrent	ADJ
cana-4791	66	6	neural	neural	ADJ
cana-4791	66	7	networks	network	NOUN
cana-4791	66	8	(	(	PUNCT
cana-4791	66	9	rnns	rnns	PROPN
cana-4791	66	10	)	)	PUNCT
cana-4791	66	11	and	and	CCONJ
cana-4791	66	12	progressive	progressive	ADJ
cana-4791	66	13	improvement	improvement	NOUN
cana-4791	66	14	methods	method	NOUN
cana-4791	66	15	to	to	PART
cana-4791	66	16	make	make	VERB
cana-4791	66	17	variable	variable	ADJ
cana-4791	66	18	-	-	PUNCT
cana-4791	66	19	rate	rate	NOUN
cana-4791	66	20	compression	compression	NOUN
cana-4791	66	21	possible	possible	ADJ
cana-4791	66	22	.	.	PUNCT
cana-4791	67	1	this	this	PRON
cana-4791	67	2	gives	give	VERB
cana-4791	67	3	real	real	ADJ
cana-4791	67	4	-	-	PUNCT
cana-4791	67	5	world	world	NOUN
cana-4791	67	6	apps	app	NOUN
cana-4791	67	7	like	like	ADP
cana-4791	67	8	video	video	NOUN
cana-4791	67	9	streaming	streaming	NOUN
cana-4791	67	10	and	and	CCONJ
cana-4791	67	11	mobile	mobile	ADJ
cana-4791	67	12	images	image	NOUN
cana-4791	67	13	more	more	ADJ
cana-4791	67	14	options	option	NOUN
cana-4791	67	15	[	[	X
cana-4791	67	16	17	17	NUM
cana-4791	67	17	]	]	PUNCT
cana-4791	67	18	.	.	PUNCT
cana-4791	68	1	differentiable	differentiable	ADJ
cana-4791	68	2	quantisation	quantisation	NOUN
cana-4791	68	3	and	and	CCONJ
cana-4791	68	4	learnt	learn	VERB
cana-4791	68	5	entropy	entropy	PROPN
cana-4791	68	6	coding	code	VERB
cana-4791	68	7	are	be	AUX
cana-4791	68	8	two	two	NUM
cana-4791	68	9	other	other	ADJ
cana-4791	68	10	ways	way	NOUN
cana-4791	68	11	that	that	PRON
cana-4791	68	12	have	have	AUX
cana-4791	68	13	been	be	AUX
cana-4791	68	14	suggested	suggest	VERB
cana-4791	68	15	to	to	PART
cana-4791	68	16	make	make	VERB
cana-4791	68	17	compression	compression	NOUN
cana-4791	68	18	work	work	NOUN
cana-4791	68	19	better	well	ADV
cana-4791	68	20	while	while	SCONJ
cana-4791	68	21	still	still	ADV
cana-4791	68	22	letting	let	VERB
cana-4791	68	23	you	you	PRON
cana-4791	68	24	train	train	VERB
cana-4791	68	25	the	the	DET
cana-4791	68	26	whole	whole	ADJ
cana-4791	68	27	system	system	NOUN
cana-4791	68	28	[	[	X
cana-4791	68	29	18	18	NUM
cana-4791	68	30	]	]	PUNCT
cana-4791	68	31	.	.	PUNCT
cana-4791	69	1	all	all	PRON
cana-4791	69	2	of	of	ADP
cana-4791	69	3	these	these	DET
cana-4791	69	4	new	new	ADJ
cana-4791	69	5	ideas	idea	NOUN
cana-4791	69	6	push	push	VERB
cana-4791	69	7	the	the	DET
cana-4791	69	8	limits	limit	NOUN
cana-4791	69	9	of	of	ADP
cana-4791	69	10	learnt	learnt	ADJ
cana-4791	69	11	picture	picture	NOUN
cana-4791	69	12	compression	compression	NOUN
cana-4791	69	13	,	,	PUNCT
cana-4791	69	14	but	but	CCONJ
cana-4791	69	15	one	one	NUM
cana-4791	69	16	big	big	ADJ
cana-4791	69	17	problem	problem	NOUN
cana-4791	69	18	is	be	AUX
cana-4791	69	19	that	that	SCONJ
cana-4791	69	20	many	many	ADJ
cana-4791	69	21	models	model	NOUN
cana-4791	69	22	still	still	ADV
cana-4791	69	23	ca	can	AUX
cana-4791	69	24	n't	not	PART
cana-4791	69	25	keep	keep	VERB
cana-4791	69	26	high	high	ADJ
cana-4791	69	27	perceived	perceive	VERB
cana-4791	69	28	quality	quality	NOUN
cana-4791	69	29	in	in	ADP
cana-4791	69	30	very	very	ADV
cana-4791	69	31	low	low	ADJ
cana-4791	69	32	bitrate	bitrate	NOUN
cana-4791	69	33	settings	setting	NOUN
cana-4791	69	34	.	.	PUNCT
cana-4791	70	1	on	on	ADP
cana-4791	70	2	the	the	DET
cana-4791	70	3	other	other	ADJ
cana-4791	70	4	hand	hand	NOUN
cana-4791	70	5	,	,	PUNCT
cana-4791	70	6	our	our	PRON
cana-4791	70	7	work	work	NOUN
cana-4791	70	8	presents	present	VERB
cana-4791	70	9	compressgan	compressgan	PROPN
cana-4791	70	10	,	,	PUNCT
cana-4791	70	11	which	which	PRON
cana-4791	70	12	builds	build	VERB
cana-4791	70	13	on	on	ADP
cana-4791	70	14	these	these	DET
cana-4791	70	15	principles	principle	NOUN
cana-4791	70	16	by	by	ADP
cana-4791	70	17	better	well	ADV
cana-4791	70	18	integrating	integrate	VERB
cana-4791	70	19	adversarial	adversarial	ADJ
cana-4791	70	20	training	training	NOUN
cana-4791	70	21	within	within	ADP
cana-4791	70	22	a	a	DET
cana-4791	70	23	small	small	ADJ
cana-4791	70	24	encoder	encoder	NOUN
cana-4791	70	25	-	-	PUNCT
cana-4791	70	26	decoder	decoder	NOUN
cana-4791	70	27	design	design	NOUN
cana-4791	70	28	.	.	PUNCT
cana-4791	71	1	our	our	PRON
cana-4791	71	2	method	method	NOUN
cana-4791	71	3	is	be	AUX
cana-4791	71	4	designed	design	VERB
cana-4791	71	5	to	to	PART
cana-4791	71	6	work	work	VERB
cana-4791	71	7	in	in	ADP
cana-4791	71	8	situations	situation	NOUN
cana-4791	71	9	where	where	SCONJ
cana-4791	71	10	the	the	DET
cana-4791	71	11	quality	quality	NOUN
cana-4791	71	12	of	of	ADP
cana-4791	71	13	perception	perception	NOUN
cana-4791	71	14	is	be	AUX
cana-4791	71	15	very	very	ADV
cana-4791	71	16	important	important	ADJ
cana-4791	71	17	,	,	PUNCT
cana-4791	71	18	and	and	CCONJ
cana-4791	71	19	where	where	SCONJ
cana-4791	71	20	standard	standard	ADJ
cana-4791	71	21	learnt	learnt	NOUN
cana-4791	71	22	models	model	NOUN
cana-4791	71	23	fail	fail	VERB
cana-4791	71	24	because	because	SCONJ
cana-4791	71	25	they	they	PRON
cana-4791	71	26	rely	rely	VERB
cana-4791	71	27	too	too	ADV
cana-4791	71	28	much	much	ADV
cana-4791	71	29	on	on	ADP
cana-4791	71	30	distortion	distortion	NOUN
cana-4791	71	31	metrics	metric	NOUN
cana-4791	71	32	.	.	PUNCT
cana-4791	72	1	compressgan	compressgan	PROPN
cana-4791	72	2	uses	use	VERB
cana-4791	72	3	the	the	DET
cana-4791	72	4	discriminator	discriminator	NOUN
cana-4791	72	5	as	as	ADP
cana-4791	72	6	a	a	DET
cana-4791	72	7	central	central	ADJ
cana-4791	72	8	part	part	NOUN
cana-4791	72	9	of	of	ADP
cana-4791	72	10	the	the	DET
cana-4791	72	11	training	training	NOUN
cana-4791	72	12	loop	loop	NOUN
cana-4791	72	13	,	,	PUNCT
cana-4791	72	14	unlike	unlike	ADP
cana-4791	72	15	other	other	ADJ
cana-4791	72	16	methods	method	NOUN
cana-4791	72	17	that	that	PRON
cana-4791	72	18	only	only	ADV
cana-4791	72	19	use	use	VERB
cana-4791	72	20	gans	gan	NOUN
cana-4791	72	21	as	as	ADP
cana-4791	72	22	extra	extra	ADJ
cana-4791	72	23	parts	part	NOUN
cana-4791	72	24	.	.	PUNCT
cana-4791	73	1	this	this	PRON
cana-4791	73	2	changes	change	VERB
cana-4791	73	3	both	both	CCONJ
cana-4791	73	4	the	the	DET
cana-4791	73	5	low	low	ADJ
cana-4791	73	6	-	-	PUNCT
cana-4791	73	7	level	level	NOUN
cana-4791	73	8	texture	texture	NOUN
cana-4791	73	9	and	and	CCONJ
cana-4791	73	10	the	the	DET
cana-4791	73	11	high	high	ADJ
cana-4791	73	12	-	-	PUNCT
cana-4791	73	13	level	level	NOUN
cana-4791	73	14	semantic	semantic	ADJ
cana-4791	73	15	consistency	consistency	NOUN
cana-4791	73	16	.	.	PUNCT
cana-4791	74	1	in	in	ADP
cana-4791	74	2	addition	addition	NOUN
cana-4791	74	3	,	,	PUNCT
cana-4791	74	4	we	we	PRON
cana-4791	74	5	add	add	VERB
cana-4791	74	6	a	a	DET
cana-4791	74	7	mixed	mixed	ADJ
cana-4791	74	8	perceptual	perceptual	ADJ
cana-4791	74	9	-	-	PUNCT
cana-4791	74	10	adversarial	adversarial	ADJ
cana-4791	74	11	loss	loss	NOUN
cana-4791	74	12	to	to	PART
cana-4791	74	13	help	help	VERB
cana-4791	74	14	the	the	DET
cana-4791	74	15	generator	generator	NOUN
cana-4791	74	16	make	make	VERB
cana-4791	74	17	reconstructions	reconstruction	NOUN
cana-4791	74	18	that	that	PRON
cana-4791	74	19	are	be	AUX
cana-4791	74	20	both	both	ADV
cana-4791	74	21	correct	correct	ADJ
cana-4791	74	22	and	and	CCONJ
cana-4791	74	23	make	make	VERB
cana-4791	74	24	sense	sense	NOUN
cana-4791	74	25	visually	visually	ADV
cana-4791	74	26	.	.	PUNCT
cana-4791	75	1	we	we	PRON
cana-4791	75	2	use	use	VERB
cana-4791	75	3	training	training	NOUN
cana-4791	75	4	methods	method	NOUN
cana-4791	75	5	and	and	CCONJ
cana-4791	75	6	normalisation	normalisation	NOUN
cana-4791	75	7	techniques	technique	NOUN
cana-4791	75	8	that	that	PRON
cana-4791	75	9	make	make	VERB
cana-4791	75	10	sure	sure	ADJ
cana-4791	75	11	convergence	convergence	NOUN
cana-4791	75	12	and	and	CCONJ
cana-4791	75	13	reliability	reliability	NOUN
cana-4791	75	14	across	across	ADP
cana-4791	75	15	different	different	ADJ
cana-4791	75	16	picture	picture	NOUN
cana-4791	75	17	domains	domain	NOUN
cana-4791	75	18	[	[	X
cana-4791	75	19	19	19	NUM
cana-4791	75	20	]	]	PUNCT
cana-4791	75	21	.	.	PUNCT
cana-4791	76	1	this	this	PRON
cana-4791	76	2	is	be	AUX
cana-4791	76	3	different	different	ADJ
cana-4791	76	4	from	from	ADP
cana-4791	76	5	other	other	ADJ
cana-4791	76	6	gan	gan	PROPN
cana-4791	76	7	-	-	PUNCT
cana-4791	76	8	based	base	VERB
cana-4791	76	9	compression	compression	NOUN
cana-4791	76	10	models	model	NOUN
cana-4791	76	11	that	that	PRON
cana-4791	76	12	may	may	AUX
cana-4791	76	13	be	be	AUX
cana-4791	76	14	prone	prone	ADJ
cana-4791	76	15	to	to	ADP
cana-4791	76	16	instability	instability	NOUN
cana-4791	76	17	and	and	CCONJ
cana-4791	76	18	mode	mode	NOUN
cana-4791	76	19	collapse	collapse	NOUN
cana-4791	76	20	.	.	PUNCT
cana-4791	77	1	our	our	PRON
cana-4791	77	2	new	new	ADJ
cana-4791	77	3	idea	idea	NOUN
cana-4791	77	4	,	,	PUNCT
cana-4791	77	5	compressgan	compressgan	PROPN
cana-4791	77	6	,	,	PUNCT
cana-4791	77	7	fixes	fix	VERB
cana-4791	77	8	some	some	DET
cana-4791	77	9	major	major	ADJ
cana-4791	77	10	problems	problem	NOUN
cana-4791	77	11	with	with	ADP
cana-4791	77	12	the	the	DET
cana-4791	77	13	way	way	NOUN
cana-4791	77	14	perceptual	perceptual	ADJ
cana-4791	77	15	images	image	NOUN
cana-4791	77	16	are	be	AUX
cana-4791	77	17	compressed	compress	VERB
cana-4791	77	18	by	by	ADP
cana-4791	77	19	building	build	VERB
cana-4791	77	20	on	on	ADP
cana-4791	77	21	what	what	PRON
cana-4791	77	22	has	have	AUX
cana-4791	77	23	already	already	ADV
cana-4791	77	24	been	be	AUX
cana-4791	77	25	done	do	VERB
cana-4791	77	26	in	in	ADP
cana-4791	77	27	autoencoder	autoencoder	NOUN
cana-4791	77	28	-	-	PUNCT
cana-4791	77	29	based	base	VERB
cana-4791	77	30	compression	compression	NOUN
cana-4791	77	31	,	,	PUNCT
cana-4791	77	32	perceptual	perceptual	ADJ
cana-4791	77	33	loss	loss	NOUN
cana-4791	77	34	integration	integration	NOUN
cana-4791	77	35	,	,	PUNCT
cana-4791	77	36	entropy	entropy	NOUN
cana-4791	77	37	modelling	modelling	NOUN
cana-4791	77	38	,	,	PUNCT
cana-4791	77	39	and	and	CCONJ
cana-4791	77	40	gan	gin	VERB
cana-4791	77	41	-	-	PUNCT
cana-4791	77	42	based	base	VERB
cana-4791	77	43	image	image	NOUN
cana-4791	77	44	creation	creation	NOUN
cana-4791	77	45	.	.	PUNCT
cana-4791	78	1	our	our	PRON
cana-4791	78	2	system	system	NOUN
cana-4791	78	3	is	be	AUX
cana-4791	78	4	better	well	ADJ
cana-4791	78	5	than	than	ADP
cana-4791	78	6	what	what	PRON
cana-4791	78	7	is	be	AUX
cana-4791	78	8	already	already	ADV
cana-4791	78	9	out	out	ADV
cana-4791	78	10	there	there	ADV
cana-4791	78	11	because	because	SCONJ
cana-4791	78	12	it	it	PRON
cana-4791	78	13	takes	take	VERB
cana-4791	78	14	a	a	DET
cana-4791	78	15	more	more	ADV
cana-4791	78	16	complete	complete	ADJ
cana-4791	78	17	look	look	NOUN
cana-4791	78	18	at	at	ADP
cana-4791	78	19	compression	compression	NOUN
cana-4791	78	20	economy	economy	NOUN
cana-4791	78	21	,	,	PUNCT
cana-4791	78	22	structure	structure	NOUN
cana-4791	78	23	integrity	integrity	NOUN
cana-4791	78	24	,	,	PUNCT
cana-4791	78	25	and	and	CCONJ
cana-4791	78	26	visual	visual	ADJ
cana-4791	78	27	accuracy	accuracy	NOUN
cana-4791	78	28	.	.	PUNCT
cana-4791	79	1	it	it	PRON
cana-4791	79	2	works	work	VERB
cana-4791	79	3	especially	especially	ADV
cana-4791	79	4	well	well	ADV
cana-4791	79	5	for	for	ADP
cana-4791	79	6	medical	medical	ADJ
cana-4791	79	7	imaging	imaging	NOUN
cana-4791	79	8	,	,	PUNCT
cana-4791	79	9	mobile	mobile	ADJ
cana-4791	79	10	photography	photography	NOUN
cana-4791	79	11	,	,	PUNCT
cana-4791	79	12	and	and	CCONJ
cana-4791	79	13	remote	remote	ADJ
cana-4791	79	14	sensing	sensing	NOUN
cana-4791	79	15	,	,	PUNCT
cana-4791	79	16	which	which	PRON
cana-4791	79	17	need	need	VERB
cana-4791	79	18	high	high	ADJ
cana-4791	79	19	-	-	PUNCT
cana-4791	79	20	quality	quality	NOUN
cana-4791	79	21	images	image	NOUN
cana-4791	79	22	but	but	CCONJ
cana-4791	79	23	do	do	AUX
cana-4791	79	24	n't	not	PART
cana-4791	79	25	have	have	VERB
cana-4791	79	26	a	a	DET
cana-4791	79	27	lot	lot	NOUN
cana-4791	79	28	of	of	ADP
cana-4791	79	29	space	space	NOUN
cana-4791	79	30	or	or	CCONJ
cana-4791	79	31	bandwidth	bandwidth	ADJ
cana-4791	79	32	.	.	PUNCT
cana-4791	80	1	table	table	NOUN
cana-4791	80	2	1	1	NUM
cana-4791	80	3	:	:	PUNCT
cana-4791	80	4	related	relate	VERB
cana-4791	80	5	work	work	NOUN
cana-4791	80	6	summary	summary	NOUN
cana-4791	80	7	table	table	NOUN
cana-4791	80	8	for	for	ADP
cana-4791	80	9	compressgan	compressgan	PROPN
cana-4791	80	10	methods	method	NOUN
cana-4791	80	11	finding	find	VERB
cana-4791	80	12	details	detail	NOUN
cana-4791	80	13	limitation	limitation	NOUN
cana-4791	80	14	jpeg	jpeg	NOUN
cana-4791	80	15	simple	simple	ADJ
cana-4791	80	16	and	and	CCONJ
cana-4791	80	17	fast	fast	ADJ
cana-4791	80	18	compression	compression	NOUN
cana-4791	80	19	uses	use	VERB
cana-4791	80	20	dct	dct	PROPN
cana-4791	80	21	and	and	CCONJ
cana-4791	80	22	quantization	quantization	NOUN
cana-4791	80	23	artifacts	artifact	NOUN
cana-4791	80	24	at	at	ADP
cana-4791	80	25	low	low	ADJ
cana-4791	80	26	bitrate	bitrate	NOUN
cana-4791	80	27	jpeg2000	jpeg2000	PROPN
cana-4791	80	28	better	well	ADV
cana-4791	80	29	at	at	ADP
cana-4791	80	30	high	high	ADJ
cana-4791	80	31	compression	compression	NOUN
cana-4791	80	32	uses	use	VERB
cana-4791	80	33	wavelet	wavelet	NOUN
cana-4791	80	34	transform	transform	NOUN
cana-4791	80	35	complex	complex	NOUN
cana-4791	80	36	to	to	PART
cana-4791	80	37	implement	implement	VERB
cana-4791	80	38	webp	webp	PROPN
cana-4791	80	39	improved	improve	VERB
cana-4791	80	40	over	over	ADP
cana-4791	80	41	jpeg	jpeg	NOUN
cana-4791	80	42	block	block	NOUN
cana-4791	80	43	-	-	PUNCT
cana-4791	80	44	based	base	VERB
cana-4791	80	45	lossy	lossy	ADJ
cana-4791	80	46	format	format	NOUN
cana-4791	80	47	blurring	blur	VERB
cana-4791	80	48	at	at	ADP
cana-4791	80	49	high	high	ADJ
cana-4791	80	50	compression	compression	NOUN
cana-4791	80	51	autoencoder	autoencoder	NOUN
cana-4791	80	52	-	-	PUNCT
cana-4791	80	53	based	base	VERB
cana-4791	80	54	compression	compression	NOUN
cana-4791	80	55	learns	learn	VERB
cana-4791	80	56	compact	compact	ADJ
cana-4791	80	57	latent	latent	NOUN
cana-4791	80	58	codes	code	NOUN
cana-4791	80	59	encoder	encoder	NOUN
cana-4791	80	60	-	-	PUNCT
cana-4791	80	61	decoder	decoder	NOUN
cana-4791	80	62	cnn	cnn	PROPN
cana-4791	80	63	limited	limit	VERB
cana-4791	80	64	perceptual	perceptual	ADJ
cana-4791	80	65	quality	quality	NOUN
cana-4791	80	66	3	3	NUM
cana-4791	80	67	.	.	PUNCT
cana-4791	80	68	methodology	methodology	NOUN
cana-4791	80	69	3.1	3.1	NUM
cana-4791	80	70	overview	overview	NOUN
cana-4791	80	71	of	of	ADP
cana-4791	80	72	compressgan	compressgan	ADJ
cana-4791	80	73	architecture	architecture	NOUN
cana-4791	80	74	a.	a.	NOUN
cana-4791	80	75	high	high	ADJ
cana-4791	80	76	-	-	PUNCT
cana-4791	80	77	level	level	NOUN
cana-4791	80	78	pipeline	pipeline	NOUN
cana-4791	80	79	:	:	PUNCT
cana-4791	80	80	from	from	ADP
cana-4791	80	81	start	start	NOUN
cana-4791	80	82	to	to	ADP
cana-4791	80	83	finish	finish	NOUN
cana-4791	80	84	,	,	PUNCT
cana-4791	80	85	compressgan	compressgan	VERB
cana-4791	80	86	rebuilds	rebuild	VERB
cana-4791	80	87	and	and	CCONJ
cana-4791	80	88	reduces	reduce	VERB
cana-4791	80	89	pictures	picture	NOUN
cana-4791	80	90	using	use	VERB
cana-4791	80	91	generative	generative	ADJ
cana-4791	80	92	adversarial	adversarial	ADJ
cana-4791	80	93	learning	learning	NOUN
cana-4791	80	94	.	.	PUNCT
cana-4791	81	1	the	the	DET
cana-4791	81	2	design	design	NOUN
cana-4791	81	3	consists	consist	VERB
cana-4791	81	4	of	of	ADP
cana-4791	81	5	three	three	NUM
cana-4791	81	6	key	key	ADJ
cana-4791	81	7	components	component	NOUN
cana-4791	81	8	:	:	PUNCT
cana-4791	81	9	an	an	DET
cana-4791	81	10	encoder	encoder	NOUN
cana-4791	81	11	,	,	PUNCT
cana-4791	81	12	a	a	DET
cana-4791	81	13	decoder	decoder	NOUN
cana-4791	81	14	,	,	PUNCT
cana-4791	81	15	and	and	CCONJ
cana-4791	81	16	a	a	DET
cana-4791	81	17	discriminator	discriminator	NOUN
cana-4791	81	18	network	network	NOUN
cana-4791	81	19	.	.	PUNCT
cana-4791	82	1	an	an	DET
cana-4791	82	2	uncompressed	uncompressed	ADJ
cana-4791	82	3	image	image	NOUN
cana-4791	82	4	is	be	AUX
cana-4791	82	5	fed	feed	VERB
cana-4791	82	6	to	to	ADP
cana-4791	82	7	the	the	DET
cana-4791	82	8	encoder	encoder	NOUN
cana-4791	82	9	,	,	PUNCT
cana-4791	82	10	which	which	PRON
cana-4791	82	11	compresses	compress	VERB
cana-4791	82	12	it	it	PRON
cana-4791	82	13	into	into	ADP
cana-4791	82	14	a	a	DET
cana-4791	82	15	tiny	tiny	ADJ
cana-4791	82	16	concealed	conceal	VERB
cana-4791	82	17	version	version	NOUN
cana-4791	82	18	.	.	PUNCT
cana-4791	83	1	this	this	DET
cana-4791	83	2	concealed	conceal	VERB
cana-4791	83	3	code	code	NOUN
cana-4791	83	4	is	be	AUX
cana-4791	83	5	then	then	ADV
cana-4791	83	6	communications	communication	NOUN
cana-4791	83	7	on	on	ADP
cana-4791	83	8	applied	apply	VERB
cana-4791	83	9	nonlinear	nonlinear	ADJ
cana-4791	83	10	analysis	analysis	NOUN
cana-4791	83	11	issn	issn	NOUN
cana-4791	83	12	:	:	PUNCT
cana-4791	83	13	1074	1074	NUM
cana-4791	83	14	-	-	PUNCT
cana-4791	83	15	133x	133x	NUM
cana-4791	83	16	vol	vol	NOUN
cana-4791	83	17	31	31	NUM
cana-4791	83	18	no	no	NOUN
cana-4791	83	19	.	.	PUNCT
cana-4791	84	1	1s	1s	NUM
cana-4791	84	2	(	(	PUNCT
cana-4791	84	3	2024	2024	NUM
cana-4791	84	4	)	)	PUNCT
cana-4791	84	5	218	218	NUM
cana-4791	84	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-4791	84	7	quantised	quantise	VERB
cana-4791	84	8	and	and	CCONJ
cana-4791	84	9	entropy	entropy	ADV
cana-4791	84	10	-	-	PUNCT
cana-4791	84	11	coded	code	VERB
cana-4791	84	12	to	to	PART
cana-4791	84	13	simplify	simplify	VERB
cana-4791	84	14	storage	storage	NOUN
cana-4791	84	15	or	or	CCONJ
cana-4791	84	16	transmission	transmission	NOUN
cana-4791	84	17	.	.	PUNCT
cana-4791	85	1	the	the	DET
cana-4791	85	2	decoder	decoder	NOUN
cana-4791	85	3	runs	run	VERB
cana-4791	85	4	the	the	DET
cana-4791	85	5	dequantized	dequantize	VERB
cana-4791	85	6	compressed	compress	VERB
cana-4791	85	7	bitstream	bitstream	NOUN
cana-4791	85	8	first	first	ADV
cana-4791	85	9	and	and	CCONJ
cana-4791	85	10	then	then	ADV
cana-4791	85	11	sends	send	VERB
cana-4791	85	12	it	it	PRON
cana-4791	85	13	through	through	ADP
cana-4791	85	14	to	to	PART
cana-4791	85	15	reassemble	reassemble	VERB
cana-4791	85	16	the	the	DET
cana-4791	85	17	image	image	NOUN
cana-4791	85	18	.	.	PUNCT
cana-4791	86	1	learnt	learn	VERB
cana-4791	86	2	with	with	ADP
cana-4791	86	3	antagonistic	antagonistic	ADJ
cana-4791	86	4	direction	direction	NOUN
cana-4791	86	5	,	,	PUNCT
cana-4791	86	6	compressgan	compressgan	PROPN
cana-4791	86	7	guarantees	guarantee	VERB
cana-4791	86	8	that	that	SCONJ
cana-4791	86	9	the	the	DET
cana-4791	86	10	reconstructed	reconstructed	ADJ
cana-4791	86	11	images	image	NOUN
cana-4791	86	12	retain	retain	VERB
cana-4791	86	13	acceptable	acceptable	ADJ
cana-4791	86	14	perceived	perceive	VERB
cana-4791	86	15	quality	quality	NOUN
cana-4791	86	16	.	.	PUNCT
cana-4791	87	1	unlike	unlike	ADP
cana-4791	87	2	conventional	conventional	ADJ
cana-4791	87	3	picture	picture	NOUN
cana-4791	87	4	compression	compression	NOUN
cana-4791	87	5	techniques	technique	NOUN
cana-4791	87	6	that	that	PRON
cana-4791	87	7	emphasise	emphasise	VERB
cana-4791	87	8	pixel	pixel	ADJ
cana-4791	87	9	-	-	PUNCT
cana-4791	87	10	level	level	NOUN
cana-4791	87	11	fidelity	fidelity	NOUN
cana-4791	87	12	,	,	PUNCT
cana-4791	87	13	this	this	DET
cana-4791	87	14	one	one	NOUN
cana-4791	87	15	using	use	VERB
cana-4791	87	16	a	a	DET
cana-4791	87	17	discriminator	discriminator	NOUN
cana-4791	87	18	network	network	NOUN
cana-4791	87	19	to	to	PART
cana-4791	87	20	evaluate	evaluate	VERB
cana-4791	87	21	the	the	DET
cana-4791	87	22	picture	picture	NOUN
cana-4791	87	23	's	's	PART
cana-4791	87	24	realism	realism	NOUN
cana-4791	87	25	and	and	CCONJ
cana-4791	87	26	provide	provide	VERB
cana-4791	87	27	input	input	NOUN
cana-4791	87	28	to	to	ADP
cana-4791	87	29	the	the	DET
cana-4791	87	30	encoder	encoder	NOUN
cana-4791	87	31	-	-	PUNCT
cana-4791	87	32	decoder	decoder	NOUN
cana-4791	87	33	process	process	NOUN
cana-4791	87	34	is	be	AUX
cana-4791	87	35	one	one	NUM
cana-4791	87	36	method	method	NOUN
cana-4791	87	37	this	this	PRON
cana-4791	87	38	is	be	AUX
cana-4791	87	39	accomplished	accomplish	VERB
cana-4791	87	40	.	.	PUNCT
cana-4791	88	1	deep	deep	ADJ
cana-4791	88	2	feature	feature	NOUN
cana-4791	88	3	-	-	PUNCT
cana-4791	88	4	based	base	VERB
cana-4791	88	5	metrics	metric	NOUN
cana-4791	88	6	are	be	AUX
cana-4791	88	7	also	also	ADV
cana-4791	88	8	used	use	VERB
cana-4791	88	9	to	to	PART
cana-4791	88	10	consider	consider	VERB
cana-4791	88	11	perceptual	perceptual	ADJ
cana-4791	88	12	losses	loss	NOUN
cana-4791	88	13	while	while	SCONJ
cana-4791	88	14	preserving	preserve	VERB
cana-4791	88	15	the	the	DET
cana-4791	88	16	conceptual	conceptual	ADJ
cana-4791	88	17	and	and	CCONJ
cana-4791	88	18	structural	structural	ADJ
cana-4791	88	19	integrity	integrity	NOUN
cana-4791	88	20	of	of	ADP
cana-4791	88	21	the	the	DET
cana-4791	88	22	picture	picture	NOUN
cana-4791	88	23	.	.	PUNCT
cana-4791	89	1	all	all	DET
cana-4791	89	2	things	thing	NOUN
cana-4791	89	3	considered	consider	VERB
cana-4791	89	4	,	,	PUNCT
cana-4791	89	5	the	the	DET
cana-4791	89	6	compressgan	compressgan	NOUN
cana-4791	89	7	approach	approach	NOUN
cana-4791	89	8	not	not	PART
cana-4791	89	9	only	only	ADV
cana-4791	89	10	learns	learn	VERB
cana-4791	89	11	how	how	SCONJ
cana-4791	89	12	to	to	PART
cana-4791	89	13	effectively	effectively	ADV
cana-4791	89	14	remove	remove	VERB
cana-4791	89	15	duplicate	duplicate	ADJ
cana-4791	89	16	data	datum	NOUN
cana-4791	89	17	but	but	CCONJ
cana-4791	89	18	also	also	ADV
cana-4791	89	19	gives	give	VERB
cana-4791	89	20	quality	quality	NOUN
cana-4791	89	21	first	first	ADJ
cana-4791	89	22	priority	priority	NOUN
cana-4791	89	23	,	,	PUNCT
cana-4791	89	24	which	which	PRON
cana-4791	89	25	makes	make	VERB
cana-4791	89	26	it	it	PRON
cana-4791	89	27	ideal	ideal	ADJ
cana-4791	89	28	for	for	ADP
cana-4791	89	29	low	low	ADJ
cana-4791	89	30	-	-	PUNCT
cana-4791	89	31	bitrate	bitrate	NOUN
cana-4791	89	32	environments	environment	NOUN
cana-4791	89	33	.	.	PUNCT
cana-4791	90	1	figure	figure	VERB
cana-4791	90	2	1	1	NUM
cana-4791	90	3	:	:	PUNCT
cana-4791	90	4	systematic	systematic	ADJ
cana-4791	90	5	workflow	workflow	NOUN
cana-4791	90	6	of	of	ADP
cana-4791	90	7	gan	gan	ADJ
cana-4791	90	8	network	network	NOUN
cana-4791	90	9	communications	communication	NOUN
cana-4791	90	10	on	on	ADP
cana-4791	90	11	applied	apply	VERB
cana-4791	90	12	nonlinear	nonlinear	ADJ
cana-4791	90	13	analysis	analysis	NOUN
cana-4791	90	14	issn	issn	NOUN
cana-4791	90	15	:	:	PUNCT
cana-4791	90	16	1074	1074	NUM
cana-4791	90	17	-	-	PUNCT
cana-4791	90	18	133x	133x	NUM
cana-4791	90	19	vol	vol	NOUN
cana-4791	90	20	31	31	NUM
cana-4791	90	21	no	no	NOUN
cana-4791	90	22	.	.	PUNCT
cana-4791	91	1	1s	1s	NUM
cana-4791	91	2	(	(	PUNCT
cana-4791	91	3	2024	2024	NUM
cana-4791	91	4	)	)	PUNCT
cana-4791	91	5	219	219	NUM
cana-4791	91	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	91	7	b.	b.	NOUN
cana-4791	91	8	integration	integration	NOUN
cana-4791	91	9	of	of	ADP
cana-4791	91	10	encoder	encoder	NOUN
cana-4791	91	11	-	-	PUNCT
cana-4791	91	12	decoder	decoder	NOUN
cana-4791	91	13	with	with	ADP
cana-4791	91	14	gan	gan	NOUN
cana-4791	91	15	:	:	PUNCT
cana-4791	91	16	in	in	ADP
cana-4791	91	17	the	the	DET
cana-4791	91	18	adversarial	adversarial	ADJ
cana-4791	91	19	learning	learning	NOUN
cana-4791	91	20	setting	set	VERB
cana-4791	91	21	,	,	PUNCT
cana-4791	91	22	the	the	DET
cana-4791	91	23	pair	pair	NOUN
cana-4791	91	24	of	of	ADP
cana-4791	91	25	encoders	encoder	NOUN
cana-4791	91	26	and	and	CCONJ
cana-4791	91	27	decoders	decoder	NOUN
cana-4791	91	28	in	in	ADP
cana-4791	91	29	compressgan	compressgan	PROPN
cana-4791	91	30	acts	act	NOUN
cana-4791	91	31	as	as	ADP
cana-4791	91	32	the	the	DET
cana-4791	91	33	generator	generator	NOUN
cana-4791	91	34	.	.	PUNCT
cana-4791	92	1	the	the	DET
cana-4791	92	2	encoder	encoder	NOUN
cana-4791	92	3	casts	cast	VERB
cana-4791	92	4	the	the	DET
cana-4791	92	5	three	three	NUM
cana-4791	92	6	-	-	PUNCT
cana-4791	92	7	dimensional	dimensional	ADJ
cana-4791	92	8	picture	picture	NOUN
cana-4791	92	9	into	into	ADP
cana-4791	92	10	a	a	DET
cana-4791	92	11	small	small	ADJ
cana-4791	92	12	hidden	hide	VERB
cana-4791	92	13	area	area	NOUN
cana-4791	92	14	while	while	SCONJ
cana-4791	92	15	keeping	keep	VERB
cana-4791	92	16	important	important	ADJ
cana-4791	92	17	visual	visual	ADJ
cana-4791	92	18	details	detail	NOUN
cana-4791	92	19	.	.	PUNCT
cana-4791	93	1	the	the	DET
cana-4791	93	2	decoder	decoder	NOUN
cana-4791	93	3	uses	use	VERB
cana-4791	93	4	this	this	DET
cana-4791	93	5	hidden	hide	VERB
cana-4791	93	6	code	code	NOUN
cana-4791	93	7	to	to	PART
cana-4791	93	8	put	put	VERB
cana-4791	93	9	the	the	DET
cana-4791	93	10	picture	picture	NOUN
cana-4791	93	11	back	back	ADV
cana-4791	93	12	together	together	ADV
cana-4791	93	13	.	.	PUNCT
cana-4791	94	1	this	this	DET
cana-4791	94	2	generator	generator	NOUN
cana-4791	94	3	is	be	AUX
cana-4791	94	4	taught	teach	VERB
cana-4791	94	5	against	against	ADP
cana-4791	94	6	a	a	DET
cana-4791	94	7	discriminator	discriminator	NOUN
cana-4791	94	8	that	that	PRON
cana-4791	94	9	tells	tell	VERB
cana-4791	94	10	the	the	DET
cana-4791	94	11	difference	difference	NOUN
cana-4791	94	12	between	between	ADP
cana-4791	94	13	real	real	ADJ
cana-4791	94	14	pictures	picture	NOUN
cana-4791	94	15	and	and	CCONJ
cana-4791	94	16	results	result	NOUN
cana-4791	94	17	that	that	PRON
cana-4791	94	18	have	have	AUX
cana-4791	94	19	been	be	AUX
cana-4791	94	20	rebuilt	rebuild	VERB
cana-4791	94	21	.	.	PUNCT
cana-4791	95	1	when	when	SCONJ
cana-4791	95	2	this	this	DET
cana-4791	95	3	hostile	hostile	ADJ
cana-4791	95	4	feedback	feedback	NOUN
cana-4791	95	5	loop	loop	NOUN
cana-4791	95	6	is	be	AUX
cana-4791	95	7	added	add	VERB
cana-4791	95	8	,	,	PUNCT
cana-4791	95	9	the	the	DET
cana-4791	95	10	encoder	encoder	NOUN
cana-4791	95	11	-	-	PUNCT
cana-4791	95	12	decoder	decoder	NOUN
cana-4791	95	13	is	be	AUX
cana-4791	95	14	forced	force	VERB
cana-4791	95	15	to	to	PART
cana-4791	95	16	not	not	PART
cana-4791	95	17	only	only	ADV
cana-4791	95	18	reduce	reduce	VERB
cana-4791	95	19	reconstruction	reconstruction	NOUN
cana-4791	95	20	error	error	NOUN
cana-4791	95	21	but	but	CCONJ
cana-4791	95	22	also	also	ADV
cana-4791	95	23	make	make	VERB
cana-4791	95	24	outputs	output	NOUN
cana-4791	95	25	that	that	PRON
cana-4791	95	26	look	look	VERB
cana-4791	95	27	,	,	PUNCT
cana-4791	95	28	feel	feel	VERB
cana-4791	95	29	,	,	PUNCT
cana-4791	95	30	and	and	CCONJ
cana-4791	95	31	behaving	behave	VERB
cana-4791	95	32	a	a	DET
cana-4791	95	33	lot	lot	NOUN
cana-4791	95	34	like	like	ADP
cana-4791	95	35	natural	natural	ADJ
cana-4791	95	36	pictures	picture	NOUN
cana-4791	95	37	.	.	PUNCT
cana-4791	96	1	this	this	DET
cana-4791	96	2	combination	combination	NOUN
cana-4791	96	3	lets	let	VERB
cana-4791	96	4	the	the	DET
cana-4791	96	5	network	network	NOUN
cana-4791	96	6	do	do	VERB
cana-4791	96	7	more	more	ADJ
cana-4791	96	8	than	than	ADP
cana-4791	96	9	just	just	ADV
cana-4791	96	10	standard	standard	ADJ
cana-4791	96	11	mse	mse	PROPN
cana-4791	96	12	optimisation	optimisation	NOUN
cana-4791	96	13	.	.	PUNCT
cana-4791	97	1	it	it	PRON
cana-4791	97	2	makes	make	VERB
cana-4791	97	3	images	image	NOUN
cana-4791	97	4	that	that	PRON
cana-4791	97	5	are	be	AUX
cana-4791	97	6	more	more	ADV
cana-4791	97	7	visually	visually	ADV
cana-4791	97	8	appealing	appealing	ADJ
cana-4791	97	9	and	and	CCONJ
cana-4791	97	10	ca	can	AUX
cana-4791	97	11	n't	not	PART
cana-4791	97	12	be	be	AUX
cana-4791	97	13	told	tell	VERB
cana-4791	97	14	apart	apart	ADV
cana-4791	97	15	from	from	ADP
cana-4791	97	16	ground	ground	NOUN
cana-4791	97	17	truth	truth	NOUN
cana-4791	97	18	by	by	ADP
cana-4791	97	19	the	the	DET
cana-4791	97	20	discriminator	discriminator	NOUN
cana-4791	97	21	.	.	PUNCT
cana-4791	98	1	3.2	3.2	NUM
cana-4791	98	2	encoder	encoder	NOUN
cana-4791	98	3	and	and	CCONJ
cana-4791	98	4	decoder	decoder	NOUN
cana-4791	98	5	design	design	NOUN
cana-4791	98	6	a.	a.	NOUN
cana-4791	98	7	network	network	NOUN
cana-4791	98	8	architecture	architecture	NOUN
cana-4791	98	9	:	:	PUNCT
cana-4791	98	10	deep	deep	ADJ
cana-4791	98	11	convolutional	convolutional	ADJ
cana-4791	98	12	neural	neural	ADJ
cana-4791	98	13	networks	network	NOUN
cana-4791	98	14	(	(	PUNCT
cana-4791	98	15	cnns	cnns	PROPN
cana-4791	98	16	)	)	PUNCT
cana-4791	98	17	are	be	AUX
cana-4791	98	18	used	use	VERB
cana-4791	98	19	to	to	PART
cana-4791	98	20	build	build	VERB
cana-4791	98	21	compressgan	compressgan	PROPN
cana-4791	98	22	's	's	PART
cana-4791	98	23	encoder	encoder	NOUN
cana-4791	98	24	and	and	CCONJ
cana-4791	98	25	decoder	decoder	NOUN
cana-4791	98	26	networks	network	NOUN
cana-4791	98	27	.	.	PUNCT
cana-4791	99	1	these	these	DET
cana-4791	99	2	networks	network	NOUN
cana-4791	99	3	have	have	VERB
cana-4791	99	4	leftover	leftover	NOUN
cana-4791	99	5	links	link	NOUN
cana-4791	99	6	that	that	PRON
cana-4791	99	7	help	help	VERB
cana-4791	99	8	features	feature	NOUN
cana-4791	99	9	spread	spread	VERB
cana-4791	99	10	and	and	CCONJ
cana-4791	99	11	gradients	gradient	NOUN
cana-4791	99	12	move	move	VERB
cana-4791	99	13	effectively	effectively	ADV
cana-4791	99	14	.	.	PUNCT
cana-4791	100	1	the	the	DET
cana-4791	100	2	encoder	encoder	NOUN
cana-4791	100	3	is	be	AUX
cana-4791	100	4	made	make	VERB
cana-4791	100	5	up	up	ADP
cana-4791	100	6	of	of	ADP
cana-4791	100	7	several	several	ADJ
cana-4791	100	8	convolutional	convolutional	ADJ
cana-4791	100	9	layers	layer	NOUN
cana-4791	100	10	that	that	PRON
cana-4791	100	11	get	get	VERB
cana-4791	100	12	less	less	ADV
cana-4791	100	13	spatially	spatially	ADV
cana-4791	100	14	resolved	resolve	VERB
cana-4791	100	15	and	and	CCONJ
cana-4791	100	16	more	more	ADJ
cana-4791	100	17	feature	feature	NOUN
cana-4791	100	18	channels	channel	NOUN
cana-4791	100	19	as	as	SCONJ
cana-4791	100	20	you	you	PRON
cana-4791	100	21	go	go	VERB
cana-4791	100	22	through	through	ADP
cana-4791	100	23	them	they	PRON
cana-4791	100	24	.	.	PUNCT
cana-4791	101	1	each	each	DET
cana-4791	101	2	layer	layer	NOUN
cana-4791	101	3	uses	use	VERB
cana-4791	101	4	relu	relu	NOUN
cana-4791	101	5	activations	activation	NOUN
cana-4791	101	6	and	and	CCONJ
cana-4791	101	7	downsampling	downsample	VERB
cana-4791	101	8	methods	method	NOUN
cana-4791	101	9	,	,	PUNCT
cana-4791	101	10	like	like	ADP
cana-4791	101	11	strided	strided	ADJ
cana-4791	101	12	convolutions	convolution	NOUN
cana-4791	101	13	,	,	PUNCT
cana-4791	101	14	to	to	PART
cana-4791	101	15	make	make	VERB
cana-4791	101	16	the	the	DET
cana-4791	101	17	data	datum	NOUN
cana-4791	101	18	less	less	ADV
cana-4791	101	19	complex	complex	ADJ
cana-4791	101	20	while	while	SCONJ
cana-4791	101	21	keeping	keep	VERB
cana-4791	101	22	important	important	ADJ
cana-4791	101	23	traits	trait	NOUN
cana-4791	101	24	.	.	PUNCT
cana-4791	102	1	this	this	DET
cana-4791	102	2	design	design	NOUN
cana-4791	102	3	is	be	AUX
cana-4791	102	4	used	use	VERB
cana-4791	102	5	by	by	ADP
cana-4791	102	6	the	the	DET
cana-4791	102	7	decoder	decoder	NOUN
cana-4791	102	8	,	,	PUNCT
cana-4791	102	9	which	which	PRON
cana-4791	102	10	uses	use	VERB
cana-4791	102	11	upsampling	upsample	VERB
cana-4791	102	12	layers	layer	NOUN
cana-4791	102	13	like	like	ADP
cana-4791	102	14	inverted	inverted	ADJ
cana-4791	102	15	convolutions	convolution	NOUN
cana-4791	102	16	or	or	CCONJ
cana-4791	102	17	nearest	nearest	ADJ
cana-4791	102	18	-	-	PUNCT
cana-4791	102	19	neighbor	neighbor	NOUN
cana-4791	102	20	upsampling	upsampling	NOUN
cana-4791	102	21	followed	follow	VERB
cana-4791	102	22	by	by	ADP
cana-4791	102	23	convolutions	convolution	NOUN
cana-4791	102	24	to	to	PART
cana-4791	102	25	copy	copy	VERB
cana-4791	102	26	it	it	PRON
cana-4791	102	27	,	,	PUNCT
cana-4791	102	28	as	as	SCONJ
cana-4791	102	29	shown	show	VERB
cana-4791	102	30	in	in	ADP
cana-4791	102	31	figure	figure	NOUN
cana-4791	102	32	2	2	NUM
cana-4791	102	33	.	.	PUNCT
cana-4791	102	34	when	when	SCONJ
cana-4791	102	35	it	it	PRON
cana-4791	102	36	makes	make	VERB
cana-4791	102	37	sense	sense	NOUN
cana-4791	102	38	,	,	PUNCT
cana-4791	102	39	skip	skip	ADJ
cana-4791	102	40	links	link	NOUN
cana-4791	102	41	are	be	AUX
cana-4791	102	42	used	use	VERB
cana-4791	102	43	to	to	PART
cana-4791	102	44	connect	connect	VERB
cana-4791	102	45	the	the	DET
cana-4791	102	46	encoder	encoder	NOUN
cana-4791	102	47	and	and	CCONJ
cana-4791	102	48	decoder	decoder	NOUN
cana-4791	102	49	layers	layer	NOUN
cana-4791	102	50	.	.	PUNCT
cana-4791	103	1	this	this	PRON
cana-4791	103	2	makes	make	VERB
cana-4791	103	3	it	it	PRON
cana-4791	103	4	easier	easy	ADJ
cana-4791	103	5	to	to	PART
cana-4791	103	6	recover	recover	VERB
cana-4791	103	7	small	small	ADJ
cana-4791	103	8	picture	picture	NOUN
cana-4791	103	9	details	detail	NOUN
cana-4791	103	10	.	.	PUNCT
cana-4791	104	1	batch	batch	NOUN
cana-4791	104	2	normalisation	normalisation	NOUN
cana-4791	104	3	is	be	AUX
cana-4791	104	4	used	use	VERB
cana-4791	104	5	to	to	PART
cana-4791	104	6	make	make	VERB
cana-4791	104	7	the	the	DET
cana-4791	104	8	training	training	NOUN
cana-4791	104	9	more	more	ADV
cana-4791	104	10	stable	stable	ADJ
cana-4791	104	11	,	,	PUNCT
cana-4791	104	12	and	and	CCONJ
cana-4791	104	13	the	the	DET
cana-4791	104	14	last	last	ADJ
cana-4791	104	15	encoder	encoder	NOUN
cana-4791	104	16	layer	layer	NOUN
cana-4791	104	17	sends	send	VERB
cana-4791	104	18	out	out	ADP
cana-4791	104	19	the	the	DET
cana-4791	104	20	rebuilt	rebuilt	ADJ
cana-4791	104	21	picture	picture	NOUN
cana-4791	104	22	with	with	ADP
cana-4791	104	23	a	a	DET
cana-4791	104	24	tanh	tanh	NOUN
cana-4791	104	25	activation	activation	NOUN
cana-4791	104	26	function	function	NOUN
cana-4791	104	27	that	that	PRON
cana-4791	104	28	changes	change	VERB
cana-4791	104	29	the	the	DET
cana-4791	104	30	values	value	NOUN
cana-4791	104	31	of	of	ADP
cana-4791	104	32	the	the	DET
cana-4791	104	33	pixels	pixel	NOUN
cana-4791	104	34	from	from	ADP
cana-4791	104	35	-1	-1	ADJ
cana-4791	104	36	to	to	ADP
cana-4791	104	37	1	1	NUM
cana-4791	104	38	.	.	PUNCT
cana-4791	105	1	figure	figure	NOUN
cana-4791	105	2	2	2	NUM
cana-4791	105	3	:	:	PUNCT
cana-4791	105	4	compressgan	compressgan	VERB
cana-4791	105	5	architecture	architecture	NOUN
cana-4791	105	6	b.	b.	PROPN
cana-4791	105	7	compressgan	compressgan	PROPN
cana-4791	105	8	in	in	ADP
cana-4791	105	9	compressgan	compressgan	PROPN
cana-4791	105	10	,	,	PUNCT
cana-4791	105	11	the	the	DET
cana-4791	105	12	latent	latent	NOUN
cana-4791	105	13	space	space	NOUN
cana-4791	105	14	is	be	AUX
cana-4791	105	15	a	a	DET
cana-4791	105	16	very	very	ADV
cana-4791	105	17	important	important	ADJ
cana-4791	105	18	part	part	NOUN
cana-4791	105	19	of	of	ADP
cana-4791	105	20	finding	find	VERB
cana-4791	105	21	the	the	DET
cana-4791	105	22	right	right	ADJ
cana-4791	105	23	balance	balance	NOUN
cana-4791	105	24	between	between	ADP
cana-4791	105	25	how	how	SCONJ
cana-4791	105	26	well	well	ADV
cana-4791	105	27	the	the	DET
cana-4791	105	28	data	data	NOUN
cana-4791	105	29	is	be	AUX
cana-4791	105	30	compressed	compress	VERB
cana-4791	105	31	and	and	CCONJ
cana-4791	105	32	how	how	SCONJ
cana-4791	105	33	well	well	ADV
cana-4791	105	34	it	it	PRON
cana-4791	105	35	looks	look	VERB
cana-4791	105	36	.	.	PUNCT
cana-4791	106	1	the	the	DET
cana-4791	106	2	encoder	encoder	NOUN
cana-4791	106	3	changes	change	VERB
cana-4791	106	4	the	the	DET
cana-4791	106	5	original	original	ADJ
cana-4791	106	6	picture	picture	NOUN
cana-4791	106	7	into	into	ADP
cana-4791	106	8	a	a	DET
cana-4791	106	9	dense	dense	ADJ
cana-4791	106	10	,	,	PUNCT
cana-4791	106	11	lower	lower	ADV
cana-4791	106	12	-	-	PUNCT
cana-4791	106	13	dimensional	dimensional	ADJ
cana-4791	106	14	model	model	NOUN
cana-4791	106	15	that	that	PRON
cana-4791	106	16	gets	get	AUX
cana-4791	106	17	rid	rid	VERB
cana-4791	106	18	of	of	ADP
cana-4791	106	19	unnecessary	unnecessary	ADJ
cana-4791	106	20	information	information	NOUN
cana-4791	106	21	while	while	SCONJ
cana-4791	106	22	keeping	keep	VERB
cana-4791	106	23	important	important	ADJ
cana-4791	106	24	details	detail	NOUN
cana-4791	106	25	.	.	PUNCT
cana-4791	107	1	this	this	DET
cana-4791	107	2	hidden	hide	VERB
cana-4791	107	3	code	code	NOUN
cana-4791	107	4	is	be	AUX
cana-4791	107	5	meant	mean	VERB
cana-4791	107	6	to	to	PART
cana-4791	107	7	be	be	AUX
cana-4791	107	8	communications	communication	NOUN
cana-4791	107	9	on	on	ADP
cana-4791	107	10	applied	apply	VERB
cana-4791	107	11	nonlinear	nonlinear	ADJ
cana-4791	107	12	analysis	analysis	NOUN
cana-4791	107	13	issn	issn	NOUN
cana-4791	107	14	:	:	PUNCT
cana-4791	107	15	1074	1074	NUM
cana-4791	107	16	-	-	PUNCT
cana-4791	107	17	133x	133x	NUM
cana-4791	107	18	vol	vol	NOUN
cana-4791	107	19	31	31	NUM
cana-4791	107	20	no	no	NOUN
cana-4791	107	21	.	.	PUNCT
cana-4791	108	1	1s	1s	NUM
cana-4791	108	2	(	(	PUNCT
cana-4791	108	3	2024	2024	NUM
cana-4791	108	4	)	)	PUNCT
cana-4791	108	5	220	220	NUM
cana-4791	108	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	108	7	small	small	ADJ
cana-4791	108	8	enough	enough	ADV
cana-4791	108	9	to	to	PART
cana-4791	108	10	store	store	VERB
cana-4791	108	11	efficiently	efficiently	ADV
cana-4791	108	12	while	while	SCONJ
cana-4791	108	13	also	also	ADV
cana-4791	108	14	being	be	AUX
cana-4791	108	15	rich	rich	ADJ
cana-4791	108	16	enough	enough	ADV
cana-4791	108	17	to	to	PART
cana-4791	108	18	allow	allow	VERB
cana-4791	108	19	for	for	ADP
cana-4791	108	20	accurate	accurate	ADJ
cana-4791	108	21	rebuilding	rebuilding	NOUN
cana-4791	108	22	.	.	PUNCT
cana-4791	109	1	in	in	ADP
cana-4791	109	2	order	order	NOUN
cana-4791	109	3	to	to	PART
cana-4791	109	4	do	do	AUX
cana-4791	109	5	this	this	PRON
cana-4791	109	6	,	,	PUNCT
cana-4791	109	7	the	the	DET
cana-4791	109	8	network	network	NOUN
cana-4791	109	9	is	be	AUX
cana-4791	109	10	trained	train	VERB
cana-4791	109	11	with	with	ADP
cana-4791	109	12	bitrate	bitrate	NOUN
cana-4791	109	13	limits	limit	NOUN
cana-4791	109	14	,	,	PUNCT
cana-4791	109	15	which	which	PRON
cana-4791	109	16	are	be	AUX
cana-4791	109	17	usually	usually	ADV
cana-4791	109	18	put	put	VERB
cana-4791	109	19	in	in	ADP
cana-4791	109	20	place	place	NOUN
cana-4791	109	21	through	through	ADP
cana-4791	109	22	bottlenecks	bottleneck	NOUN
cana-4791	109	23	and	and	CCONJ
cana-4791	109	24	slowing	slow	VERB
cana-4791	109	25	down	down	ADP
cana-4791	109	26	the	the	DET
cana-4791	109	27	flow	flow	NOUN
cana-4791	109	28	of	of	ADP
cana-4791	109	29	information	information	NOUN
cana-4791	109	30	.	.	PUNCT
cana-4791	110	1	compressgan	compressgan	PROPN
cana-4791	110	2	lets	let	VERB
cana-4791	110	3	it	it	PRON
cana-4791	110	4	change	change	VERB
cana-4791	110	5	the	the	DET
cana-4791	110	6	compression	compression	NOUN
cana-4791	110	7	options	option	NOUN
cana-4791	110	8	to	to	PART
cana-4791	110	9	fit	fit	VERB
cana-4791	110	10	both	both	CCONJ
cana-4791	110	11	high	high	ADJ
cana-4791	110	12	and	and	CCONJ
cana-4791	110	13	low	low	ADJ
cana-4791	110	14	bitrate	bitrate	NOUN
cana-4791	110	15	goals	goal	NOUN
cana-4791	110	16	by	by	ADP
cana-4791	110	17	changing	change	VERB
cana-4791	110	18	the	the	DET
cana-4791	110	19	number	number	NOUN
cana-4791	110	20	of	of	ADP
cana-4791	110	21	channels	channel	NOUN
cana-4791	110	22	or	or	CCONJ
cana-4791	110	23	the	the	DET
cana-4791	110	24	quantisation	quantisation	NOUN
cana-4791	110	25	depth	depth	NOUN
cana-4791	110	26	in	in	ADP
cana-4791	110	27	the	the	DET
cana-4791	110	28	latent	latent	NOUN
cana-4791	110	29	space	space	NOUN
cana-4791	110	30	.	.	PUNCT
cana-4791	111	1	in	in	ADP
cana-4791	111	2	contrast	contrast	NOUN
cana-4791	111	3	to	to	ADP
cana-4791	111	4	the	the	DET
cana-4791	111	5	fixed	fix	VERB
cana-4791	111	6	transforms	transform	NOUN
cana-4791	111	7	used	use	VERB
cana-4791	111	8	in	in	ADP
cana-4791	111	9	older	old	ADJ
cana-4791	111	10	methods	method	NOUN
cana-4791	111	11	,	,	PUNCT
cana-4791	111	12	this	this	DET
cana-4791	111	13	latent	latent	NOUN
cana-4791	111	14	space	space	NOUN
cana-4791	111	15	can	can	AUX
cana-4791	111	16	also	also	ADV
cana-4791	111	17	be	be	AUX
cana-4791	111	18	seen	see	VERB
cana-4791	111	19	as	as	ADP
cana-4791	111	20	a	a	DET
cana-4791	111	21	learnt	learn	VERB
cana-4791	111	22	feature	feature	NOUN
cana-4791	111	23	representation	representation	NOUN
cana-4791	111	24	that	that	PRON
cana-4791	111	25	is	be	AUX
cana-4791	111	26	best	good	ADJ
cana-4791	111	27	for	for	ADP
cana-4791	111	28	reconstructing	reconstruct	VERB
cana-4791	111	29	visual	visual	ADJ
cana-4791	111	30	images	image	NOUN
cana-4791	111	31	.	.	PUNCT
cana-4791	112	1	compressgan	compressgan	PROPN
cana-4791	112	2	:	:	PUNCT
cana-4791	112	3	step	step	NOUN
cana-4791	112	4	-	-	PUNCT
cana-4791	112	5	wise	wise	ADJ
cana-4791	112	6	algorithm	algorithm	NOUN
cana-4791	112	7	step	step	NOUN
cana-4791	112	8	1	1	NUM
cana-4791	112	9	:	:	PUNCT
cana-4791	112	10	image	image	NOUN
cana-4791	112	11	encoding	encode	VERB
cana-4791	112	12	input	input	NOUN
cana-4791	112	13	raw	raw	ADJ
cana-4791	112	14	image	image	NOUN
cana-4791	112	15	𝐼_𝑖𝑛	𝐼_𝑖𝑛	NOUN
cana-4791	112	16	∈	∈	PROPN
cana-4791	112	17	ℝ^(𝐻	ℝ^(𝐻	X
cana-4791	112	18	×	×	PROPN
cana-4791	112	19	𝑊	𝑊	PROPN
cana-4791	112	20	×	×	PROPN
cana-4791	112	21	𝐶	𝐶	PROPN
cana-4791	112	22	)	)	PUNCT
cana-4791	112	23	encode	encode	VERB
cana-4791	112	24	to	to	ADP
cana-4791	112	25	latent	latent	NOUN
cana-4791	112	26	representation	representation	NOUN
cana-4791	112	27	:	:	PUNCT
cana-4791	112	28	𝑧	𝑧	PROPN
cana-4791	112	29	=	=	PROPN
cana-4791	112	30	𝐸(𝐼_𝑖𝑛	𝐸(𝐼_𝑖𝑛	PROPN
cana-4791	112	31	)	)	PUNCT
cana-4791	112	32	𝑧	𝑧	PROPN
cana-4791	112	33	∈	∈	PROPN
cana-4791	113	1	ℝ^(ℎ	ℝ^(ℎ	ADJ
cana-4791	113	2	×	×	NOUN
cana-4791	113	3	𝑤	𝑤	ADP
cana-4791	113	4	×	×	PROPN
cana-4791	113	5	𝑐	𝑐	NOUN
cana-4791	113	6	)	)	PUNCT
cana-4791	113	7	,	,	PUNCT
cana-4791	113	8	𝑤ℎ𝑒𝑟𝑒	𝑤ℎ𝑒𝑟𝑒	NOUN
cana-4791	113	9	ℎ	ℎ	X
cana-4791	113	10	<	<	X
cana-4791	113	11	𝐻	𝐻	PROPN
cana-4791	113	12	,	,	PUNCT
cana-4791	113	13	𝑤	𝑤	ADP
cana-4791	113	14	<	<	X
cana-4791	113	15	𝑊	𝑊	NOUN
cana-4791	113	16	step	step	NOUN
cana-4791	113	17	2	2	NUM
cana-4791	113	18	:	:	PUNCT
cana-4791	113	19	quantization	quantization	NOUN
cana-4791	113	20	of	of	ADP
cana-4791	113	21	latent	latent	NOUN
cana-4791	113	22	representation	representation	NOUN
cana-4791	113	23	quantize	quantize	VERB
cana-4791	113	24	z	z	NOUN
cana-4791	113	25	to	to	PART
cana-4791	113	26	obtain	obtain	VERB
cana-4791	113	27	discrete	discrete	ADJ
cana-4791	113	28	latent	latent	NOUN
cana-4791	113	29	:	:	PUNCT
cana-4791	113	30	𝑧ℎ𝑎𝑡	𝑧ℎ𝑎𝑡	NOUN
cana-4791	113	31	=	=	PUNCT
cana-4791	113	32	𝑄𝑢𝑎𝑛𝑡𝑖𝑧𝑒(𝑧	𝑄𝑢𝑎𝑛𝑡𝑖𝑧𝑒(𝑧	NOUN
cana-4791	113	33	)	)	PUNCT
cana-4791	114	1	≈	≈	PROPN
cana-4791	114	2	𝑧	𝑧	PROPN
cana-4791	114	3	+	+	X
cana-4791	114	4	𝑈	𝑈	NOUN
cana-4791	114	5	(	(	PUNCT
cana-4791	114	6	−	−	PROPN
cana-4791	114	7	𝛥	𝛥	PROPN
cana-4791	114	8	2	2	NUM
cana-4791	114	9	,	,	PUNCT
cana-4791	114	10	𝛥	𝛥	PROPN
cana-4791	114	11	2	2	NUM
cana-4791	114	12	)	)	PUNCT
cana-4791	114	13	(	(	PUNCT
cana-4791	114	14	δ	δ	PROPN
cana-4791	114	15	is	be	AUX
cana-4791	114	16	the	the	DET
cana-4791	114	17	quantization	quantization	NOUN
cana-4791	114	18	step	step	NOUN
cana-4791	114	19	size	size	NOUN
cana-4791	114	20	)	)	PUNCT
cana-4791	114	21	step	step	NOUN
cana-4791	114	22	3	3	NUM
cana-4791	114	23	:	:	PUNCT
cana-4791	114	24	entropy	entropy	VERB
cana-4791	114	25	modeling	modeling	NOUN
cana-4791	114	26	and	and	CCONJ
cana-4791	114	27	bitstream	bitstream	NOUN
cana-4791	114	28	generation	generation	NOUN
cana-4791	114	29	model	model	NOUN
cana-4791	114	30	probability	probability	NOUN
cana-4791	114	31	and	and	CCONJ
cana-4791	114	32	encode	encode	ADJ
cana-4791	114	33	bits	bit	NOUN
cana-4791	114	34	:	:	PUNCT
cana-4791	114	35	𝐿_𝑟𝑎𝑡𝑒	𝐿_𝑟𝑎𝑡𝑒	NOUN
cana-4791	114	36	=	=	SYM
cana-4791	114	37	−𝑙𝑜𝑔₂	−𝑙𝑜𝑔₂	NOUN
cana-4791	114	38	𝑃(𝑧_ℎ𝑎𝑡	𝑃(𝑧_ℎ𝑎𝑡	ADJ
cana-4791	114	39	)	)	PUNCT
cana-4791	114	40	bitstream	bitstream	NOUN
cana-4791	114	41	=	=	PUNCT
cana-4791	114	42	entropyencode(z_hat	entropyencode(z_hat	NOUN
cana-4791	114	43	)	)	PUNCT
cana-4791	114	44	step	step	NOUN
cana-4791	114	45	4	4	NUM
cana-4791	114	46	:	:	PUNCT
cana-4791	114	47	image	image	NOUN
cana-4791	114	48	reconstruction	reconstruction	NOUN
cana-4791	114	49	via	via	ADP
cana-4791	114	50	decoder	decoder	NOUN
cana-4791	114	51	decode	decode	NOUN
cana-4791	114	52	to	to	PART
cana-4791	114	53	reconstruct	reconstruct	VERB
cana-4791	114	54	the	the	DET
cana-4791	114	55	image	image	NOUN
cana-4791	114	56	:	:	PUNCT
cana-4791	114	57	𝐼ℎ𝑎𝑡	𝐼ℎ𝑎𝑡	PROPN
cana-4791	114	58	=	=	SYM
cana-4791	114	59	𝐷(𝑧ℎ𝑎𝑡	𝐷(𝑧ℎ𝑎𝑡	PROPN
cana-4791	114	60	)	)	PUNCT
cana-4791	115	1	𝐼ℎ𝑎𝑡	𝐼ℎ𝑎𝑡	PROPN
cana-4791	115	2	∈	∈	PROPN
cana-4791	115	3	ℝ𝐻×𝑊×𝐶	ℝ𝐻×𝑊×𝐶	ADJ
cana-4791	115	4	step	step	NOUN
cana-4791	115	5	5	5	NUM
cana-4791	115	6	:	:	PUNCT
cana-4791	115	7	compute	compute	VERB
cana-4791	115	8	multi	multi	ADJ
cana-4791	115	9	-	-	ADJ
cana-4791	115	10	objective	objective	ADJ
cana-4791	115	11	loss	loss	NOUN
cana-4791	115	12	reconstruction	reconstruction	NOUN
cana-4791	115	13	loss	loss	NOUN
cana-4791	115	14	(	(	PUNCT
cana-4791	115	15	l1	l1	PROPN
cana-4791	115	16	norm	norm	NOUN
cana-4791	115	17	):	):	PUNCT
cana-4791	115	18	𝐿_𝑟𝑒𝑐	𝐿_𝑟𝑒𝑐	ADP
cana-4791	115	19	=	=	PUNCT
cana-4791	115	20	||𝐼_𝑖𝑛	||𝐼_𝑖𝑛	PUNCT
cana-4791	115	21	−	−	PROPN
cana-4791	115	22	𝐼_ℎ𝑎𝑡||₁	𝐼_ℎ𝑎𝑡||₁	X
cana-4791	115	23	perceptual	perceptual	ADJ
cana-4791	115	24	loss	loss	NOUN
cana-4791	115	25	using	use	VERB
cana-4791	115	26	vgg12	vgg12	PROPN
cana-4791	115	27	:	:	PUNCT
cana-4791	115	28	𝐿𝑝𝑒𝑟𝑐	𝐿𝑝𝑒𝑟𝑐	PROPN
cana-4791	115	29	=	=	PUNCT
cana-4791	115	30	𝛴ₗ||𝜙ₗ(𝐼𝑖𝑛	𝛴ₗ||𝜙ₗ(𝐼𝑖𝑛	PROPN
cana-4791	115	31	)	)	PUNCT
cana-4791	115	32	−	−	NOUN
cana-4791	115	33	𝜙ₗ(𝐼ℎ𝑎𝑡)||	𝜙ₗ(𝐼ℎ𝑎𝑡)||	NOUN
cana-4791	115	34	22	22	NUM
cana-4791	115	35	step	step	NOUN
cana-4791	115	36	6	6	NUM
cana-4791	115	37	:	:	PUNCT
cana-4791	115	38	adversarial	adversarial	ADJ
cana-4791	115	39	training	training	NOUN
cana-4791	115	40	train	train	NOUN
cana-4791	115	41	discriminator	discriminator	NOUN
cana-4791	115	42	d_adv	d_adv	PROPN
cana-4791	115	43	:	:	PUNCT
cana-4791	115	44	𝐿𝐷	𝐿𝐷	PROPN
cana-4791	115	45	=	=	PUNCT
cana-4791	116	1	−	−	PROPN
cana-4791	116	2	log	log	NOUN
cana-4791	116	3	𝐷𝑎𝑑𝑣(𝐼𝑖𝑛	𝐷𝑎𝑑𝑣(𝐼𝑖𝑛	PROPN
cana-4791	116	4	)	)	PUNCT
cana-4791	117	1	−	−	PROPN
cana-4791	117	2	log(1	log(1	NOUN
cana-4791	117	3	−	−	PROPN
cana-4791	117	4	𝐷𝑎𝑑𝑣(𝐼ℎ𝑎𝑡	𝐷𝑎𝑑𝑣(𝐼ℎ𝑎𝑡	PROPN
cana-4791	117	5	)	)	PUNCT
cana-4791	117	6	)	)	PUNCT
cana-4791	117	7	adversarial	adversarial	ADJ
cana-4791	117	8	loss	loss	NOUN
cana-4791	117	9	for	for	ADP
cana-4791	117	10	generator	generator	NOUN
cana-4791	117	11	:	:	PUNCT
cana-4791	117	12	𝐿𝑎𝑑𝑣	𝐿𝑎𝑑𝑣	NOUN
cana-4791	117	13	=	=	SYM
cana-4791	117	14	−	−	PROPN
cana-4791	117	15	log	log	PROPN
cana-4791	117	16	𝐷𝑎𝑑𝑣(𝐼ℎ𝑎𝑡	𝐷𝑎𝑑𝑣(𝐼ℎ𝑎𝑡	NOUN
cana-4791	117	17	)	)	PUNCT
cana-4791	117	18	step	step	NOUN
cana-4791	117	19	7	7	NUM
cana-4791	117	20	:	:	PUNCT
cana-4791	117	21	optimize	optimize	NOUN
cana-4791	117	22	compressgan	compressgan	VERB
cana-4791	117	23	objective	objective	ADJ
cana-4791	117	24	total	total	ADJ
cana-4791	117	25	loss	loss	NOUN
cana-4791	117	26	function	function	NOUN
cana-4791	117	27	:	:	PUNCT
cana-4791	117	28	communications	communication	NOUN
cana-4791	117	29	on	on	ADP
cana-4791	117	30	applied	apply	VERB
cana-4791	117	31	nonlinear	nonlinear	ADJ
cana-4791	117	32	analysis	analysis	NOUN
cana-4791	117	33	issn	issn	NOUN
cana-4791	117	34	:	:	PUNCT
cana-4791	117	35	1074	1074	NUM
cana-4791	117	36	-	-	PUNCT
cana-4791	117	37	133x	133x	NUM
cana-4791	117	38	vol	vol	NOUN
cana-4791	117	39	31	31	NUM
cana-4791	117	40	no	no	NOUN
cana-4791	117	41	.	.	PUNCT
cana-4791	118	1	1s	1s	NUM
cana-4791	118	2	(	(	PUNCT
cana-4791	118	3	2024	2024	NUM
cana-4791	118	4	)	)	PUNCT
cana-4791	118	5	221	221	NUM
cana-4791	119	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	119	2	𝐿𝑡𝑜𝑡𝑎𝑙	𝐿𝑡𝑜𝑡𝑎𝑙	PROPN
cana-4791	119	3	=	=	PROPN
cana-4791	119	4	𝜆𝑟𝑒𝑐	𝜆𝑟𝑒𝑐	PROPN
cana-4791	119	5	∗	∗	VERB
cana-4791	119	6	𝐿𝑟𝑒𝑐	𝐿𝑟𝑒𝑐	PROPN
cana-4791	120	1	+	+	CCONJ
cana-4791	120	2	𝜆𝑝𝑒𝑟𝑐	𝜆𝑝𝑒𝑟𝑐	ADP
cana-4791	120	3	∗	∗	NOUN
cana-4791	120	4	𝐿𝑝𝑒𝑟𝑐	𝐿𝑝𝑒𝑟𝑐	PROPN
cana-4791	120	5	+	+	NUM
cana-4791	120	6	𝜆𝑎𝑑𝑣	𝜆𝑎𝑑𝑣	NOUN
cana-4791	120	7	∗	∗	NOUN
cana-4791	120	8	𝐿𝑎𝑑𝑣	𝐿𝑎𝑑𝑣	NOUN
cana-4791	120	9	+	+	CCONJ
cana-4791	120	10	𝜆𝑟𝑎𝑡𝑒	𝜆𝑟𝑎𝑡𝑒	NOUN
cana-4791	120	11	∗	∗	NOUN
cana-4791	120	12	𝐿𝑟𝑎𝑡𝑒	𝐿𝑟𝑎𝑡𝑒	PROPN
cana-4791	120	13	update	update	NOUN
cana-4791	120	14	network	network	NOUN
cana-4791	120	15	parameters	parameter	NOUN
cana-4791	120	16	:	:	PUNCT
cana-4791	120	17	𝜃	𝜃	NUM
cana-4791	120	18	∗	∗	NOUN
cana-4791	120	19	=	=	PUNCT
cana-4791	120	20	𝑎𝑟𝑔𝑚𝑖𝑛𝜃𝐿𝑡𝑜𝑡𝑎𝑙	𝑎𝑟𝑔𝑚𝑖𝑛𝜃𝐿𝑡𝑜𝑡𝑎𝑙	PROPN
cana-4791	120	21	c.	c.	NOUN
cana-4791	120	22	quantization	quantization	NOUN
cana-4791	120	23	and	and	CCONJ
cana-4791	120	24	entropy	entropy	NOUN
cana-4791	120	25	coding	code	VERB
cana-4791	120	26	a	a	DET
cana-4791	120	27	quantisation	quantisation	NOUN
cana-4791	120	28	layer	layer	NOUN
cana-4791	120	29	separates	separate	VERB
cana-4791	120	30	the	the	DET
cana-4791	120	31	latent	latent	NOUN
cana-4791	120	32	features	feature	NOUN
cana-4791	120	33	in	in	ADP
cana-4791	120	34	compressgan	compressgan	NOUN
cana-4791	120	35	so	so	SCONJ
cana-4791	120	36	that	that	SCONJ
cana-4791	120	37	the	the	DET
cana-4791	120	38	continuous	continuous	ADJ
cana-4791	120	39	-	-	PUNCT
cana-4791	120	40	valued	value	VERB
cana-4791	120	41	latent	latent	NOUN
cana-4791	120	42	representation	representation	NOUN
cana-4791	120	43	can	can	AUX
cana-4791	120	44	be	be	AUX
cana-4791	120	45	turned	turn	VERB
cana-4791	120	46	into	into	ADP
cana-4791	120	47	a	a	DET
cana-4791	120	48	compressed	compressed	ADJ
cana-4791	120	49	bitstream	bitstream	NOUN
cana-4791	120	50	.	.	PUNCT
cana-4791	121	1	this	this	DET
cana-4791	121	2	quantisation	quantisation	NOUN
cana-4791	121	3	process	process	NOUN
cana-4791	121	4	is	be	AUX
cana-4791	121	5	n't	not	PART
cana-4791	121	6	usually	usually	ADV
cana-4791	121	7	differentiable	differentiable	ADJ
cana-4791	121	8	,	,	PUNCT
cana-4791	121	9	but	but	CCONJ
cana-4791	121	10	it	it	PRON
cana-4791	121	11	can	can	AUX
cana-4791	121	12	be	be	AUX
cana-4791	121	13	made	make	VERB
cana-4791	121	14	more	more	ADJ
cana-4791	121	15	like	like	ADP
cana-4791	121	16	it	it	PRON
cana-4791	121	17	by	by	ADP
cana-4791	121	18	using	use	VERB
cana-4791	121	19	methods	method	NOUN
cana-4791	121	20	like	like	ADP
cana-4791	121	21	uniform	uniform	ADJ
cana-4791	121	22	noise	noise	NOUN
cana-4791	121	23	input	input	NOUN
cana-4791	121	24	during	during	ADP
cana-4791	121	25	training	training	NOUN
cana-4791	121	26	or	or	CCONJ
cana-4791	121	27	soft	soft	ADJ
cana-4791	121	28	quantisation	quantisation	NOUN
cana-4791	121	29	functions	function	NOUN
cana-4791	121	30	to	to	PART
cana-4791	121	31	let	let	VERB
cana-4791	121	32	gradients	gradient	NOUN
cana-4791	121	33	spread	spread	VERB
cana-4791	121	34	.	.	PUNCT
cana-4791	122	1	after	after	SCONJ
cana-4791	122	2	the	the	DET
cana-4791	122	3	hidden	hide	VERB
cana-4791	122	4	codes	code	NOUN
cana-4791	122	5	are	be	AUX
cana-4791	122	6	quantised	quantise	VERB
cana-4791	122	7	,	,	PUNCT
cana-4791	122	8	they	they	PRON
cana-4791	122	9	are	be	AUX
cana-4791	122	10	entropy	entropy	ADV
cana-4791	122	11	-	-	PUNCT
cana-4791	122	12	coded	code	VERB
cana-4791	122	13	using	use	VERB
cana-4791	122	14	methods	method	NOUN
cana-4791	122	15	such	such	ADJ
cana-4791	122	16	as	as	ADP
cana-4791	122	17	huffman	huffman	PROPN
cana-4791	122	18	coding	coding	NOUN
cana-4791	122	19	or	or	CCONJ
cana-4791	122	20	math	math	NOUN
cana-4791	122	21	coding	coding	NOUN
cana-4791	122	22	.	.	PUNCT
cana-4791	123	1	a	a	DET
cana-4791	123	2	learnt	learn	VERB
cana-4791	123	3	entropy	entropy	NOUN
cana-4791	123	4	model	model	NOUN
cana-4791	123	5	is	be	AUX
cana-4791	123	6	used	use	VERB
cana-4791	123	7	to	to	PART
cana-4791	123	8	guess	guess	VERB
cana-4791	123	9	how	how	SCONJ
cana-4791	123	10	the	the	DET
cana-4791	123	11	quantised	quantise	VERB
cana-4791	123	12	symbols	symbol	NOUN
cana-4791	123	13	'	'	PART
cana-4791	123	14	chance	chance	NOUN
cana-4791	123	15	distribution	distribution	NOUN
cana-4791	123	16	will	will	AUX
cana-4791	123	17	be	be	AUX
cana-4791	123	18	spread	spread	VERB
cana-4791	123	19	out	out	ADP
cana-4791	123	20	.	.	PUNCT
cana-4791	124	1	this	this	PRON
cana-4791	124	2	makes	make	VERB
cana-4791	124	3	entropy	entropy	NOUN
cana-4791	124	4	coding	code	VERB
cana-4791	124	5	work	work	NOUN
cana-4791	124	6	well	well	ADV
cana-4791	124	7	and	and	CCONJ
cana-4791	124	8	cut	cut	VERB
cana-4791	124	9	down	down	ADP
cana-4791	124	10	on	on	ADP
cana-4791	124	11	unnecessary	unnecessary	ADJ
cana-4791	124	12	repetition	repetition	NOUN
cana-4791	124	13	.	.	PUNCT
cana-4791	125	1	this	this	DET
cana-4791	125	2	method	method	NOUN
cana-4791	125	3	of	of	ADP
cana-4791	125	4	compression	compression	NOUN
cana-4791	125	5	makes	make	VERB
cana-4791	125	6	sure	sure	ADJ
cana-4791	125	7	that	that	SCONJ
cana-4791	125	8	the	the	DET
cana-4791	125	9	end	end	NOUN
cana-4791	125	10	bitstream	bitstream	NOUN
cana-4791	125	11	is	be	AUX
cana-4791	125	12	small	small	ADJ
cana-4791	125	13	,	,	PUNCT
cana-4791	125	14	but	but	CCONJ
cana-4791	125	15	it	it	PRON
cana-4791	125	16	can	can	AUX
cana-4791	125	17	still	still	ADV
cana-4791	125	18	be	be	AUX
cana-4791	125	19	decoded	decode	VERB
cana-4791	125	20	with	with	ADP
cana-4791	125	21	high	high	ADJ
cana-4791	125	22	quality	quality	NOUN
cana-4791	125	23	during	during	ADP
cana-4791	125	24	rebuilding	rebuild	VERB
cana-4791	125	25	.	.	PUNCT
cana-4791	126	1	quantization	quantization	NOUN
cana-4791	126	2	and	and	CCONJ
cana-4791	126	3	entropy	entropy	NOUN
cana-4791	126	4	coding	code	VERB
cana-4791	126	5	:	:	PUNCT
cana-4791	126	6	mathematical	mathematical	ADJ
cana-4791	126	7	model	model	NOUN
cana-4791	126	8	1	1	NUM
cana-4791	126	9	.	.	PUNCT
cana-4791	126	10	quantization	quantization	NOUN
cana-4791	126	11	input	input	NOUN
cana-4791	126	12	latent	latent	NOUN
cana-4791	126	13	representation	representation	NOUN
cana-4791	126	14	:	:	PUNCT
cana-4791	126	15	𝑧	𝑧	PROPN
cana-4791	126	16	∈	∈	PROPN
cana-4791	126	17	ℝℎ×𝑤×𝑐	ℝℎ×𝑤×𝑐	NOUN
cana-4791	126	18	output	output	NOUN
cana-4791	126	19	discrete	discrete	ADJ
cana-4791	126	20	latent	latent	NOUN
cana-4791	126	21	:	:	PUNCT
cana-4791	126	22	𝑧ℎ𝑎𝑡	𝑧ℎ𝑎𝑡	PROPN
cana-4791	126	23	∈	∈	PROPN
cana-4791	126	24	ℤℎ×𝑤×𝑐	ℤℎ×𝑤×𝑐	PROPN
cana-4791	126	25	uniform	uniform	ADJ
cana-4791	126	26	quantization	quantization	NOUN
cana-4791	126	27	:	:	PUNCT
cana-4791	126	28	𝑧ℎ𝑎𝑡	𝑧ℎ𝑎𝑡	PROPN
cana-4791	126	29	=	=	SYM
cana-4791	126	30	𝑄(𝑧	𝑄(𝑧	PROPN
cana-4791	126	31	)	)	PUNCT
cana-4791	126	32	=	=	NOUN
cana-4791	126	33	𝑟𝑜𝑢𝑛𝑑	𝑟𝑜𝑢𝑛𝑑	NOUN
cana-4791	126	34	(	(	PUNCT
cana-4791	126	35	𝑧	𝑧	PROPN
cana-4791	126	36	𝛥	𝛥	PROPN
cana-4791	126	37	)	)	PUNCT
cana-4791	126	38	∗	∗	NOUN
cana-4791	126	39	𝛥	𝛥	PROPN
cana-4791	126	40	(	(	PUNCT
cana-4791	126	41	δ	δ	PROPN
cana-4791	126	42	is	be	AUX
cana-4791	126	43	the	the	DET
cana-4791	126	44	quantization	quantization	NOUN
cana-4791	126	45	step	step	NOUN
cana-4791	126	46	size	size	NOUN
cana-4791	126	47	)	)	PUNCT
cana-4791	126	48	differentiable	differentiable	ADJ
cana-4791	126	49	approximation	approximation	NOUN
cana-4791	126	50	(	(	PUNCT
cana-4791	126	51	for	for	ADP
cana-4791	126	52	training	training	NOUN
cana-4791	126	53	):	):	PUNCT
cana-4791	126	54	𝑧ℎ𝑎𝑡	𝑧ℎ𝑎𝑡	PROPN
cana-4791	127	1	≈	≈	PROPN
cana-4791	127	2	𝑧	𝑧	PROPN
cana-4791	127	3	+	+	X
cana-4791	127	4	𝑈	𝑈	NOUN
cana-4791	127	5	(	(	PUNCT
cana-4791	127	6	−	−	PROPN
cana-4791	127	7	𝛥	𝛥	PROPN
cana-4791	127	8	2	2	NUM
cana-4791	127	9	,	,	PUNCT
cana-4791	127	10	𝛥	𝛥	PROPN
cana-4791	127	11	2	2	NUM
cana-4791	127	12	)	)	PUNCT
cana-4791	127	13	(	(	PUNCT
cana-4791	127	14	u	u	NOUN
cana-4791	127	15	is	be	AUX
cana-4791	127	16	uniform	uniform	ADJ
cana-4791	127	17	noise	noise	NOUN
cana-4791	127	18	added	add	VERB
cana-4791	127	19	to	to	ADP
cana-4791	127	20	mimic	mimic	ADJ
cana-4791	127	21	quantization	quantization	NOUN
cana-4791	127	22	)	)	PUNCT
cana-4791	127	23	2	2	X
cana-4791	127	24	.	.	X
cana-4791	127	25	entropy	entropy	PROPN
cana-4791	127	26	modeling	modeling	NOUN
cana-4791	127	27	learned	learn	VERB
cana-4791	127	28	probability	probability	NOUN
cana-4791	127	29	distribution	distribution	NOUN
cana-4791	127	30	:	:	PUNCT
cana-4791	127	31	p(z_hat	p(z_hat	X
cana-4791	127	32	)	)	PUNCT
cana-4791	127	33	rate	rate	NOUN
cana-4791	127	34	(	(	PUNCT
cana-4791	127	35	bit	bit	NOUN
cana-4791	127	36	cost	cost	NOUN
cana-4791	127	37	per	per	ADP
cana-4791	127	38	image	image	NOUN
cana-4791	127	39	):	):	PUNCT
cana-4791	127	40	𝐿_𝑟𝑎𝑡𝑒	𝐿_𝑟𝑎𝑡𝑒	NOUN
cana-4791	127	41	=	=	SYM
cana-4791	127	42	−𝛴_𝑖	−𝛴_𝑖	NUM
cana-4791	127	43	𝑙𝑜𝑔₂	𝑙𝑜𝑔₂	PROPN
cana-4791	127	44	𝑃(𝑧_ℎ𝑎𝑡_𝑖	𝑃(𝑧_ℎ𝑎𝑡_𝑖	NUM
cana-4791	127	45	)	)	PUNCT
cana-4791	127	46	𝐿𝑟𝑎𝑡𝑒	𝐿𝑟𝑎𝑡𝑒	NOUN
cana-4791	127	47	=	=	PUNCT
cana-4791	127	48	𝐸{𝑧ℎ𝑎𝑡∼	𝐸{𝑧ℎ𝑎𝑡∼	NOUN
cana-4791	127	49	𝑄	𝑄	PROPN
cana-4791	127	50	}	}	PUNCT
cana-4791	127	51	[	[	PUNCT
cana-4791	127	52	−𝑙𝑜𝑔2𝑃(𝑧ℎ𝑎𝑡	−𝑙𝑜𝑔2𝑃(𝑧ℎ𝑎𝑡	PROPN
cana-4791	127	53	)	)	PUNCT
cana-4791	127	54	]	]	PUNCT
cana-4791	127	55	entropy	entropy	PROPN
cana-4791	127	56	coding	code	VERB
cana-4791	127	57	(	(	PUNCT
cana-4791	127	58	e.g.	e.g.	ADV
cana-4791	127	59	,	,	PUNCT
cana-4791	127	60	arithmetic	arithmetic	ADJ
cana-4791	127	61	coding	coding	NOUN
cana-4791	127	62	)	)	PUNCT
cana-4791	127	63	uses	use	VERB
cana-4791	127	64	p(z_hat	p(z_hat	NOUN
cana-4791	127	65	)	)	PUNCT
cana-4791	127	66	to	to	PART
cana-4791	127	67	encode	encode	VERB
cana-4791	127	68	z_hat	z_hat	PROPN
cana-4791	127	69	into	into	ADP
cana-4791	127	70	a	a	DET
cana-4791	127	71	binary	binary	ADJ
cana-4791	127	72	stream	stream	NOUN
cana-4791	127	73	.	.	PUNCT
cana-4791	128	1	3.3	3.3	NUM
cana-4791	128	2	discriminator	discriminator	NOUN
cana-4791	128	3	design	design	NOUN
cana-4791	128	4	for	for	ADP
cana-4791	128	5	improving	improve	VERB
cana-4791	128	6	the	the	DET
cana-4791	128	7	quality	quality	NOUN
cana-4791	128	8	of	of	ADP
cana-4791	128	9	perception	perception	NOUN
cana-4791	128	10	of	of	ADP
cana-4791	128	11	rebuilt	rebuilt	ADJ
cana-4791	128	12	pictures	picture	NOUN
cana-4791	128	13	,	,	PUNCT
cana-4791	128	14	adversarial	adversarial	ADJ
cana-4791	128	15	training	training	NOUN
cana-4791	128	16	in	in	ADP
cana-4791	128	17	compressgan	compressgan	PROPN
cana-4791	128	18	is	be	AUX
cana-4791	128	19	very	very	ADV
cana-4791	128	20	important	important	ADJ
cana-4791	128	21	.	.	PUNCT
cana-4791	129	1	it	it	PRON
cana-4791	129	2	learns	learn	VERB
cana-4791	129	3	to	to	PART
cana-4791	129	4	tell	tell	VERB
cana-4791	129	5	the	the	DET
cana-4791	129	6	difference	difference	NOUN
cana-4791	129	7	between	between	ADP
cana-4791	129	8	real	real	ADJ
cana-4791	129	9	and	and	CCONJ
cana-4791	129	10	rebuilt	rebuilt	ADJ
cana-4791	129	11	pictures	picture	NOUN
cana-4791	129	12	and	and	CCONJ
cana-4791	129	13	works	work	VERB
cana-4791	129	14	as	as	ADP
cana-4791	129	15	a	a	DET
cana-4791	129	16	binary	binary	ADJ
cana-4791	129	17	classifier	classifier	NOUN
cana-4791	129	18	.	.	PUNCT
cana-4791	130	1	furthermore	furthermore	ADV
cana-4791	130	2	,	,	PUNCT
cana-4791	130	3	it	it	PRON
cana-4791	130	4	tells	tell	VERB
cana-4791	130	5	the	the	DET
cana-4791	130	6	generator	generator	NOUN
cana-4791	130	7	(	(	PUNCT
cana-4791	130	8	the	the	DET
cana-4791	130	9	encoder	encoder	NOUN
cana-4791	130	10	-	-	PUNCT
cana-4791	130	11	decoder	decoder	NOUN
cana-4791	130	12	pair	pair	NOUN
cana-4791	130	13	)	)	PUNCT
cana-4791	130	14	what	what	PRON
cana-4791	130	15	to	to	PART
cana-4791	130	16	do	do	VERB
cana-4791	130	17	to	to	PART
cana-4791	130	18	make	make	VERB
cana-4791	130	19	results	result	NOUN
cana-4791	130	20	that	that	PRON
cana-4791	130	21	are	be	AUX
cana-4791	130	22	not	not	PART
cana-4791	130	23	only	only	ADV
cana-4791	130	24	physically	physically	ADV
cana-4791	130	25	right	right	ADJ
cana-4791	130	26	but	but	CCONJ
cana-4791	130	27	also	also	ADV
cana-4791	130	28	look	look	VERB
cana-4791	130	29	real	real	ADJ
cana-4791	130	30	.	.	PUNCT
cana-4791	131	1	this	this	DET
cana-4791	131	2	antagonistic	antagonistic	ADJ
cana-4791	131	3	loss	loss	NOUN
cana-4791	131	4	focusses	focusse	NOUN
cana-4791	131	5	on	on	ADP
cana-4791	131	6	high	high	ADJ
cana-4791	131	7	-	-	PUNCT
cana-4791	131	8	frequency	frequency	NOUN
cana-4791	131	9	patterns	pattern	NOUN
cana-4791	131	10	and	and	CCONJ
cana-4791	131	11	semantic	semantic	ADJ
cana-4791	131	12	reality	reality	NOUN
cana-4791	131	13	to	to	PART
cana-4791	131	14	go	go	VERB
cana-4791	131	15	along	along	ADV
cana-4791	131	16	with	with	ADP
cana-4791	131	17	standard	standard	ADJ
cana-4791	131	18	pixel	pixel	NOUN
cana-4791	131	19	-	-	PUNCT
cana-4791	131	20	based	base	VERB
cana-4791	131	21	losses	loss	NOUN
cana-4791	131	22	.	.	PUNCT
cana-4791	132	1	as	as	SCONJ
cana-4791	132	2	training	training	NOUN
cana-4791	132	3	goes	go	VERB
cana-4791	132	4	on	on	ADP
cana-4791	132	5	,	,	PUNCT
cana-4791	132	6	the	the	DET
cana-4791	132	7	generator	generator	NOUN
cana-4791	132	8	gets	get	VERB
cana-4791	132	9	better	well	ADJ
cana-4791	132	10	at	at	ADP
cana-4791	132	11	making	make	VERB
cana-4791	132	12	reconstructions	reconstruction	NOUN
cana-4791	132	13	that	that	PRON
cana-4791	132	14	are	be	AUX
cana-4791	132	15	hard	hard	ADJ
cana-4791	132	16	for	for	SCONJ
cana-4791	132	17	the	the	DET
cana-4791	132	18	discriminator	discriminator	NOUN
cana-4791	132	19	to	to	PART
cana-4791	132	20	tell	tell	VERB
cana-4791	132	21	apart	apart	ADV
cana-4791	132	22	from	from	ADP
cana-4791	132	23	real	real	ADJ
cana-4791	132	24	pictures	picture	NOUN
cana-4791	132	25	.	.	PUNCT
cana-4791	133	1	this	this	PRON
cana-4791	133	2	raises	raise	VERB
cana-4791	133	3	the	the	DET
cana-4791	133	4	quality	quality	NOUN
cana-4791	133	5	of	of	ADP
cana-4791	133	6	the	the	DET
cana-4791	133	7	output	output	NOUN
cana-4791	133	8	to	to	ADP
cana-4791	133	9	a	a	DET
cana-4791	133	10	higher	high	ADJ
cana-4791	133	11	level	level	NOUN
cana-4791	133	12	of	of	ADP
cana-4791	133	13	perceived	perceive	VERB
cana-4791	133	14	quality	quality	NOUN
cana-4791	133	15	.	.	PUNCT
cana-4791	134	1	in	in	ADP
cana-4791	134	2	compressgan	compressgan	PROPN
cana-4791	134	3	,	,	PUNCT
cana-4791	134	4	the	the	DET
cana-4791	134	5	discriminator	discriminator	NOUN
cana-4791	134	6	is	be	AUX
cana-4791	134	7	made	make	VERB
cana-4791	134	8	up	up	ADP
cana-4791	134	9	of	of	ADP
cana-4791	134	10	multiple	multiple	ADJ
cana-4791	134	11	layers	layer	NOUN
cana-4791	134	12	of	of	ADP
cana-4791	134	13	a	a	DET
cana-4791	134	14	convolutional	convolutional	ADJ
cana-4791	134	15	network	network	NOUN
cana-4791	134	16	that	that	PRON
cana-4791	134	17	works	work	VERB
cana-4791	134	18	at	at	ADP
cana-4791	134	19	both	both	CCONJ
cana-4791	134	20	the	the	DET
cana-4791	134	21	global	global	ADJ
cana-4791	134	22	and	and	CCONJ
cana-4791	134	23	local	local	ADJ
cana-4791	134	24	picture	picture	NOUN
cana-4791	134	25	sizes	size	NOUN
cana-4791	134	26	.	.	PUNCT
cana-4791	135	1	it	it	PRON
cana-4791	135	2	is	be	AUX
cana-4791	135	3	made	make	VERB
cana-4791	135	4	up	up	ADP
cana-4791	135	5	of	of	ADP
cana-4791	135	6	several	several	ADJ
cana-4791	135	7	convolutional	convolutional	ADJ
cana-4791	135	8	layers	layer	NOUN
cana-4791	135	9	that	that	PRON
cana-4791	135	10	use	use	VERB
cana-4791	135	11	leaky	leaky	ADJ
cana-4791	135	12	relu	relu	NOUN
cana-4791	135	13	activations	activation	NOUN
cana-4791	135	14	and	and	CCONJ
cana-4791	135	15	then	then	ADV
cana-4791	135	16	downsampling	downsample	VERB
cana-4791	135	17	layers	layer	NOUN
cana-4791	135	18	that	that	PRON
cana-4791	135	19	make	make	VERB
cana-4791	135	20	the	the	DET
cana-4791	135	21	spatial	spatial	ADJ
cana-4791	135	22	precision	precision	NOUN
cana-4791	135	23	smaller	small	ADJ
cana-4791	135	24	and	and	CCONJ
cana-4791	135	25	smaller	small	ADJ
cana-4791	135	26	.	.	PUNCT
cana-4791	136	1	spectral	spectral	ADJ
cana-4791	136	2	normalisation	normalisation	NOUN
cana-4791	136	3	keeps	keep	VERB
cana-4791	136	4	communications	communication	NOUN
cana-4791	136	5	on	on	ADP
cana-4791	136	6	applied	apply	VERB
cana-4791	136	7	nonlinear	nonlinear	ADJ
cana-4791	136	8	analysis	analysis	NOUN
cana-4791	136	9	issn	issn	NOUN
cana-4791	136	10	:	:	PUNCT
cana-4791	136	11	1074	1074	NUM
cana-4791	136	12	-	-	PUNCT
cana-4791	136	13	133x	133x	NUM
cana-4791	136	14	vol	vol	NOUN
cana-4791	136	15	31	31	NUM
cana-4791	136	16	no	no	NOUN
cana-4791	136	17	.	.	PUNCT
cana-4791	137	1	1s	1s	NUM
cana-4791	137	2	(	(	PUNCT
cana-4791	137	3	2024	2024	NUM
cana-4791	137	4	)	)	PUNCT
cana-4791	137	5	222	222	NUM
cana-4791	137	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	137	7	the	the	DET
cana-4791	137	8	training	training	NOUN
cana-4791	137	9	dynamics	dynamic	NOUN
cana-4791	137	10	stable	stable	ADJ
cana-4791	138	1	and	and	CCONJ
cana-4791	138	2	stops	stop	VERB
cana-4791	138	3	the	the	DET
cana-4791	138	4	discriminator	discriminator	NOUN
cana-4791	138	5	from	from	ADP
cana-4791	138	6	getting	get	VERB
cana-4791	138	7	too	too	ADV
cana-4791	138	8	strong	strong	ADJ
cana-4791	138	9	compared	compare	VERB
cana-4791	138	10	to	to	ADP
cana-4791	138	11	the	the	DET
cana-4791	138	12	generator	generator	NOUN
cana-4791	138	13	.	.	PUNCT
cana-4791	139	1	the	the	DET
cana-4791	139	2	last	last	ADJ
cana-4791	139	3	layer	layer	NOUN
cana-4791	139	4	sends	send	VERB
cana-4791	139	5	a	a	DET
cana-4791	139	6	numeric	numeric	ADJ
cana-4791	139	7	chance	chance	NOUN
cana-4791	139	8	that	that	PRON
cana-4791	139	9	tells	tell	VERB
cana-4791	139	10	us	we	PRON
cana-4791	139	11	if	if	SCONJ
cana-4791	139	12	the	the	DET
cana-4791	139	13	information	information	NOUN
cana-4791	139	14	is	be	AUX
cana-4791	139	15	real	real	ADJ
cana-4791	139	16	or	or	CCONJ
cana-4791	139	17	not	not	PART
cana-4791	139	18	.	.	PUNCT
cana-4791	140	1	3.4	3.4	NUM
cana-4791	140	2	loss	loss	NOUN
cana-4791	140	3	functions	function	NOUN
cana-4791	140	4	to	to	PART
cana-4791	140	5	guarantee	guarantee	VERB
cana-4791	140	6	that	that	SCONJ
cana-4791	140	7	the	the	DET
cana-4791	140	8	pixel	pixel	ADJ
cana-4791	140	9	-	-	ADJ
cana-4791	140	10	wise	wise	ADJ
cana-4791	140	11	disparity	disparity	NOUN
cana-4791	140	12	between	between	ADP
cana-4791	140	13	the	the	DET
cana-4791	140	14	original	original	ADJ
cana-4791	140	15	and	and	CCONJ
cana-4791	140	16	rebuilt	rebuild	VERB
cana-4791	140	17	pictures	picture	NOUN
cana-4791	140	18	is	be	AUX
cana-4791	140	19	minimised	minimise	VERB
cana-4791	140	20	,	,	PUNCT
cana-4791	140	21	compressgan	compressgan	PROPN
cana-4791	140	22	employs	employ	VERB
cana-4791	140	23	reconstruction	reconstruction	NOUN
cana-4791	140	24	losses	loss	NOUN
cana-4791	140	25	like	like	ADP
cana-4791	140	26	l1	l1	PROPN
cana-4791	140	27	or	or	CCONJ
cana-4791	140	28	l2	l2	NOUN
cana-4791	140	29	loss	loss	NOUN
cana-4791	140	30	.	.	PUNCT
cana-4791	141	1	while	while	SCONJ
cana-4791	141	2	l2	l2	NOUN
cana-4791	141	3	loss	loss	NOUN
cana-4791	141	4	(	(	PUNCT
cana-4791	141	5	mean	mean	INTJ
cana-4791	141	6	squared	square	VERB
cana-4791	141	7	error	error	NOUN
cana-4791	141	8	)	)	PUNCT
cana-4791	141	9	penalises	penalise	VERB
cana-4791	141	10	big	big	ADJ
cana-4791	141	11	deviations	deviation	NOUN
cana-4791	141	12	more	more	ADV
cana-4791	141	13	strongly	strongly	ADV
cana-4791	141	14	and	and	CCONJ
cana-4791	141	15	may	may	AUX
cana-4791	141	16	provide	provide	VERB
cana-4791	141	17	smoother	smooth	ADJ
cana-4791	141	18	pictures	picture	NOUN
cana-4791	141	19	,	,	PUNCT
cana-4791	141	20	the	the	DET
cana-4791	141	21	l1	l1	PROPN
cana-4791	141	22	loss	loss	NOUN
cana-4791	141	23	(	(	PUNCT
cana-4791	141	24	mean	mean	ADJ
cana-4791	141	25	absolute	absolute	ADJ
cana-4791	141	26	error	error	NOUN
cana-4791	141	27	)	)	PUNCT
cana-4791	141	28	is	be	AUX
cana-4791	141	29	usually	usually	ADV
cana-4791	141	30	favoured	favour	VERB
cana-4791	141	31	for	for	ADP
cana-4791	141	32	its	its	PRON
cana-4791	141	33	capacity	capacity	NOUN
cana-4791	141	34	to	to	PART
cana-4791	141	35	maintain	maintain	VERB
cana-4791	141	36	sharper	sharp	ADJ
cana-4791	141	37	edges	edge	NOUN
cana-4791	141	38	and	and	CCONJ
cana-4791	141	39	lower	low	ADJ
cana-4791	141	40	blurring	blurring	NOUN
cana-4791	141	41	.	.	PUNCT
cana-4791	142	1	these	these	DET
cana-4791	142	2	losses	loss	NOUN
cana-4791	142	3	guarantee	guarantee	VERB
cana-4791	142	4	that	that	SCONJ
cana-4791	142	5	the	the	DET
cana-4791	142	6	reconstructed	reconstructed	ADJ
cana-4791	142	7	pictures	picture	NOUN
cana-4791	142	8	are	be	AUX
cana-4791	142	9	structurally	structurally	ADV
cana-4791	142	10	true	true	ADJ
cana-4791	142	11	to	to	ADP
cana-4791	142	12	the	the	DET
cana-4791	142	13	input	input	NOUN
cana-4791	142	14	and	and	CCONJ
cana-4791	142	15	provide	provide	VERB
cana-4791	142	16	a	a	DET
cana-4791	142	17	basic	basic	ADJ
cana-4791	142	18	baseline	baseline	NOUN
cana-4791	142	19	for	for	ADP
cana-4791	142	20	training	training	NOUN
cana-4791	142	21	.	.	PUNCT
cana-4791	143	1	but	but	CCONJ
cana-4791	143	2	,	,	PUNCT
cana-4791	143	3	maintaining	maintain	VERB
cana-4791	143	4	perceived	perceive	VERB
cana-4791	143	5	quality	quality	NOUN
cana-4791	143	6	alone	alone	ADV
cana-4791	143	7	using	use	VERB
cana-4791	143	8	pixel	pixel	ADJ
cana-4791	143	9	-	-	ADJ
cana-4791	143	10	wise	wise	ADJ
cana-4791	143	11	losses	loss	NOUN
cana-4791	143	12	is	be	AUX
cana-4791	143	13	not	not	PART
cana-4791	143	14	enough	enough	ADJ
cana-4791	143	15	;	;	PUNCT
cana-4791	143	16	this	this	PRON
cana-4791	143	17	motivates	motivate	VERB
cana-4791	143	18	the	the	DET
cana-4791	143	19	use	use	NOUN
cana-4791	143	20	of	of	ADP
cana-4791	143	21	more	more	ADV
cana-4791	143	22	sophisticated	sophisticated	ADJ
cana-4791	143	23	loss	loss	NOUN
cana-4791	143	24	algorithms	algorithm	NOUN
cana-4791	143	25	.	.	PUNCT
cana-4791	144	1	the	the	DET
cana-4791	144	2	adversarial	adversarial	ADJ
cana-4791	144	3	loss	loss	NOUN
cana-4791	144	4	comes	come	VERB
cana-4791	144	5	from	from	ADP
cana-4791	144	6	the	the	DET
cana-4791	144	7	categorisation	categorisation	NOUN
cana-4791	144	8	output	output	NOUN
cana-4791	144	9	of	of	ADP
cana-4791	144	10	the	the	DET
cana-4791	144	11	discriminator	discriminator	NOUN
cana-4791	144	12	.	.	PUNCT
cana-4791	145	1	it	it	PRON
cana-4791	145	2	punishes	punish	VERB
cana-4791	145	3	the	the	DET
cana-4791	145	4	generator	generator	NOUN
cana-4791	145	5	if	if	SCONJ
cana-4791	145	6	the	the	DET
cana-4791	145	7	discriminator	discriminator	NOUN
cana-4791	145	8	effectively	effectively	ADV
cana-4791	145	9	separates	separate	VERB
cana-4791	145	10	reconstructed	reconstructed	ADJ
cana-4791	145	11	pictures	picture	NOUN
cana-4791	145	12	from	from	ADP
cana-4791	145	13	actual	actual	ADJ
cana-4791	145	14	ones	one	NOUN
cana-4791	145	15	.	.	PUNCT
cana-4791	146	1	usually	usually	ADV
cana-4791	146	2	,	,	PUNCT
cana-4791	146	3	a	a	DET
cana-4791	146	4	binary	binary	ADJ
cana-4791	146	5	cross	cross	NOUN
cana-4791	146	6	-	-	NOUN
cana-4791	146	7	entropy	entropy	ADJ
cana-4791	146	8	or	or	CCONJ
cana-4791	146	9	least	least	ADJ
cana-4791	146	10	squares	square	NOUN
cana-4791	146	11	gan	gan	PROPN
cana-4791	146	12	(	(	PUNCT
cana-4791	146	13	lsgan	lsgan	NOUN
cana-4791	146	14	)	)	PUNCT
cana-4791	146	15	formulation	formulation	NOUN
cana-4791	146	16	is	be	AUX
cana-4791	146	17	employed	employ	VERB
cana-4791	146	18	to	to	PART
cana-4791	146	19	stabilise	stabilise	VERB
cana-4791	146	20	the	the	DET
cana-4791	146	21	training	training	NOUN
cana-4791	146	22	.	.	PUNCT
cana-4791	147	1	this	this	DET
cana-4791	147	2	loss	loss	NOUN
cana-4791	147	3	increases	increase	VERB
cana-4791	147	4	the	the	DET
cana-4791	147	5	perceived	perceive	VERB
cana-4791	147	6	believability	believability	NOUN
cana-4791	147	7	of	of	ADP
cana-4791	147	8	the	the	DET
cana-4791	147	9	produced	produce	VERB
cana-4791	147	10	pictures	picture	NOUN
cana-4791	147	11	by	by	ADP
cana-4791	147	12	encouraging	encourage	VERB
cana-4791	147	13	the	the	DET
cana-4791	147	14	generator	generator	NOUN
cana-4791	147	15	to	to	PART
cana-4791	147	16	concentrate	concentrate	VERB
cana-4791	147	17	on	on	ADP
cana-4791	147	18	high	high	ADJ
cana-4791	147	19	-	-	PUNCT
cana-4791	147	20	frequency	frequency	NOUN
cana-4791	147	21	information	information	NOUN
cana-4791	147	22	and	and	CCONJ
cana-4791	147	23	lifelike	lifelike	ADJ
cana-4791	147	24	textures	texture	NOUN
cana-4791	147	25	.	.	PUNCT
cana-4791	148	1	the	the	DET
cana-4791	148	2	adversarial	adversarial	ADJ
cana-4791	148	3	loss	loss	NOUN
cana-4791	148	4	offers	offer	VERB
cana-4791	148	5	an	an	DET
cana-4791	148	6	additional	additional	ADJ
cana-4791	148	7	gradient	gradient	NOUN
cana-4791	148	8	directing	direct	VERB
cana-4791	148	9	the	the	DET
cana-4791	148	10	generator	generator	NOUN
cana-4791	148	11	towards	towards	ADP
cana-4791	148	12	generating	generate	VERB
cana-4791	148	13	visually	visually	ADV
cana-4791	148	14	consistent	consistent	ADJ
cana-4791	148	15	and	and	CCONJ
cana-4791	148	16	natural	natural	ADJ
cana-4791	148	17	outputs	output	NOUN
cana-4791	148	18	when	when	SCONJ
cana-4791	148	19	paired	pair	VERB
cana-4791	148	20	with	with	ADP
cana-4791	148	21	pixel	pixel	NOUN
cana-4791	148	22	-	-	PUNCT
cana-4791	148	23	based	base	VERB
cana-4791	148	24	losses	loss	NOUN
cana-4791	148	25	.	.	PUNCT
cana-4791	149	1	vgg12	vgg12	PROPN
cana-4791	149	2	:	:	PUNCT
cana-4791	149	3	perceptual	perceptual	ADJ
cana-4791	149	4	loss	loss	NOUN
cana-4791	149	5	in	in	ADP
cana-4791	149	6	compressgan	compressgan	NOUN
cana-4791	149	7	in	in	ADP
cana-4791	149	8	contemporary	contemporary	ADJ
cana-4791	149	9	deep	deep	ADJ
cana-4791	149	10	learning	learning	NOUN
cana-4791	149	11	-	-	PUNCT
cana-4791	149	12	based	base	VERB
cana-4791	149	13	image	image	NOUN
cana-4791	149	14	compression	compression	NOUN
cana-4791	149	15	systems	system	NOUN
cana-4791	149	16	like	like	ADP
cana-4791	149	17	compressgan	compressgan	PROPN
cana-4791	149	18	,	,	PUNCT
cana-4791	149	19	conventional	conventional	ADJ
cana-4791	149	20	pixel	pixel	ADJ
cana-4791	149	21	-	-	ADJ
cana-4791	149	22	wise	wise	ADJ
cana-4791	149	23	losses	loss	NOUN
cana-4791	149	24	such	such	ADJ
cana-4791	149	25	as	as	ADP
cana-4791	149	26	l1	l1	PROPN
cana-4791	149	27	and	and	CCONJ
cana-4791	149	28	l2	l2	NOUN
cana-4791	149	29	are	be	AUX
cana-4791	149	30	often	often	ADV
cana-4791	149	31	inadequate	inadequate	ADJ
cana-4791	149	32	to	to	PART
cana-4791	149	33	capture	capture	VERB
cana-4791	149	34	perceptual	perceptual	ADJ
cana-4791	149	35	subtleties	subtlety	NOUN
cana-4791	149	36	vital	vital	ADJ
cana-4791	149	37	for	for	ADP
cana-4791	149	38	human	human	ADJ
cana-4791	149	39	visual	visual	ADJ
cana-4791	149	40	experience	experience	NOUN
cana-4791	149	41	.	.	PUNCT
cana-4791	150	1	operating	operate	VERB
cana-4791	150	2	just	just	ADV
cana-4791	150	3	in	in	ADP
cana-4791	150	4	the	the	DET
cana-4791	150	5	spatial	spatial	ADJ
cana-4791	150	6	domain	domain	NOUN
cana-4791	150	7	,	,	PUNCT
cana-4791	150	8	these	these	DET
cana-4791	150	9	pixel	pixel	NOUN
cana-4791	150	10	-	-	PUNCT
cana-4791	150	11	based	base	VERB
cana-4791	150	12	losses	loss	NOUN
cana-4791	150	13	are	be	AUX
cana-4791	150	14	sensitive	sensitive	ADJ
cana-4791	150	15	to	to	ADP
cana-4791	150	16	pixel	pixel	ADJ
cana-4791	150	17	-	-	PUNCT
cana-4791	150	18	level	level	NOUN
cana-4791	150	19	misalignments	misalignment	NOUN
cana-4791	150	20	that	that	PRON
cana-4791	150	21	may	may	AUX
cana-4791	150	22	not	not	PART
cana-4791	150	23	directly	directly	ADV
cana-4791	150	24	relate	relate	VERB
cana-4791	150	25	to	to	ADP
cana-4791	150	26	notable	notable	ADJ
cana-4791	150	27	perceptual	perceptual	ADJ
cana-4791	150	28	deterioration	deterioration	NOUN
cana-4791	150	29	.	.	PUNCT
cana-4791	151	1	for	for	ADP
cana-4791	151	2	instance	instance	NOUN
cana-4791	151	3	,	,	PUNCT
cana-4791	151	4	a	a	DET
cana-4791	151	5	picture	picture	NOUN
cana-4791	151	6	that	that	PRON
cana-4791	151	7	is	be	AUX
cana-4791	151	8	structurally	structurally	ADV
cana-4791	151	9	accurate	accurate	ADJ
cana-4791	151	10	but	but	CCONJ
cana-4791	151	11	displaced	displace	VERB
cana-4791	151	12	by	by	ADP
cana-4791	151	13	one	one	NUM
cana-4791	151	14	pixel	pixel	NOUN
cana-4791	151	15	may	may	AUX
cana-4791	151	16	show	show	VERB
cana-4791	151	17	significant	significant	ADJ
cana-4791	151	18	l2	l2	NOUN
cana-4791	151	19	error	error	NOUN
cana-4791	151	20	but	but	CCONJ
cana-4791	151	21	still	still	ADV
cana-4791	151	22	seem	seem	VERB
cana-4791	151	23	visually	visually	ADV
cana-4791	151	24	acceptable	acceptable	ADJ
cana-4791	151	25	.	.	PUNCT
cana-4791	152	1	perceptual	perceptual	ADJ
cana-4791	152	2	loss	loss	NOUN
cana-4791	152	3	functions	function	NOUN
cana-4791	152	4	have	have	AUX
cana-4791	152	5	been	be	AUX
cana-4791	152	6	developed	develop	VERB
cana-4791	152	7	to	to	AUX
cana-4791	152	8	more	more	ADV
cana-4791	152	9	closely	closely	ADV
cana-4791	152	10	match	match	VERB
cana-4791	152	11	the	the	DET
cana-4791	152	12	training	training	NOUN
cana-4791	152	13	goal	goal	NOUN
cana-4791	152	14	with	with	ADP
cana-4791	152	15	human	human	ADJ
cana-4791	152	16	perception	perception	NOUN
cana-4791	152	17	in	in	ADP
cana-4791	152	18	order	order	NOUN
cana-4791	152	19	to	to	PART
cana-4791	152	20	overcome	overcome	VERB
cana-4791	152	21	these	these	DET
cana-4791	152	22	constraints	constraint	NOUN
cana-4791	152	23	.	.	PUNCT
cana-4791	153	1	deep	deep	ADJ
cana-4791	153	2	features	feature	NOUN
cana-4791	153	3	taken	take	VERB
cana-4791	153	4	from	from	ADP
cana-4791	153	5	a	a	DET
cana-4791	153	6	pre	pre	ADJ
cana-4791	153	7	-	-	ADJ
cana-4791	153	8	trained	train	VERB
cana-4791	153	9	convolutional	convolutional	ADJ
cana-4791	153	10	neural	neural	ADJ
cana-4791	153	11	network	network	NOUN
cana-4791	153	12	are	be	AUX
cana-4791	153	13	among	among	ADP
cana-4791	153	14	the	the	DET
cana-4791	153	15	most	most	ADV
cana-4791	153	16	often	often	ADV
cana-4791	153	17	used	use	VERB
cana-4791	153	18	methods	method	NOUN
cana-4791	153	19	for	for	ADP
cana-4791	153	20	calculating	calculate	VERB
cana-4791	153	21	perceptual	perceptual	ADJ
cana-4791	153	22	loss	loss	NOUN
cana-4791	153	23	.	.	PUNCT
cana-4791	154	1	compressgan	compressgan	PROPN
cana-4791	154	2	uses	use	VERB
cana-4791	154	3	the	the	DET
cana-4791	154	4	vgg12	vgg12	PROPN
cana-4791	154	5	network	network	NOUN
cana-4791	154	6	for	for	ADP
cana-4791	154	7	this	this	DET
cana-4791	154	8	goal	goal	NOUN
cana-4791	154	9	.	.	PUNCT
cana-4791	155	1	vgg12	vgg12	PROPN
cana-4791	155	2	:	:	PUNCT
cana-4791	155	3	model	model	NOUN
cana-4791	155	4	for	for	ADP
cana-4791	155	5	perceptual	perceptual	ADJ
cana-4791	155	6	loss	loss	NOUN
cana-4791	155	7	step	step	NOUN
cana-4791	155	8	1	1	NUM
cana-4791	155	9	:	:	PUNCT
cana-4791	155	10	input	input	NOUN
cana-4791	155	11	images	image	NOUN
cana-4791	155	12	−	−	ADP
cana-4791	155	13	𝑂𝑟𝑖𝑔𝑖𝑛𝑎𝑙	𝑂𝑟𝑖𝑔𝑖𝑛𝑎𝑙	PROPN
cana-4791	155	14	𝑖𝑚𝑎𝑔𝑒	𝑖𝑚𝑎𝑔𝑒	NOUN
cana-4791	155	15	:	:	PUNCT
cana-4791	155	16	𝐼𝑖𝑛	𝐼𝑖𝑛	PROPN
cana-4791	155	17	∈	∈	PROPN
cana-4791	155	18	ℝ𝐻×𝑊×3	ℝ𝐻×𝑊×3	NOUN
cana-4791	155	19	−	−	ADP
cana-4791	155	20	𝑅𝑒𝑐𝑜𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑒𝑑	𝑅𝑒𝑐𝑜𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑒𝑑	PROPN
cana-4791	155	21	𝑖𝑚𝑎𝑔𝑒	𝑖𝑚𝑎𝑔𝑒	NOUN
cana-4791	155	22	:	:	PUNCT
cana-4791	155	23	𝐼ℎ𝑎𝑡	𝐼ℎ𝑎𝑡	PROPN
cana-4791	155	24	∈	∈	PROPN
cana-4791	155	25	ℝ𝐻×𝑊×3	ℝ𝐻×𝑊×3	NOUN
cana-4791	155	26	step	step	NOUN
cana-4791	155	27	2	2	NUM
cana-4791	155	28	:	:	PUNCT
cana-4791	155	29	preprocessing	preprocesse	VERB
cana-4791	155	30	normalize	normalize	VERB
cana-4791	155	31	images	image	NOUN
cana-4791	155	32	using	use	VERB
cana-4791	155	33	vgg	vgg	PROPN
cana-4791	155	34	mean	mean	NOUN
cana-4791	155	35	&	&	CCONJ
cana-4791	155	36	std	std	PROPN
cana-4791	155	37	:	:	PUNCT
cana-4791	155	38	𝐼	𝐼	PROPN
cana-4791	155	39	=	=	PUNCT
cana-4791	155	40	𝐼	𝐼	PROPN
cana-4791	155	41	−	−	PROPN
cana-4791	155	42	𝜇	𝜇	ADP
cana-4791	155	43	𝜎	𝜎	PROPN
cana-4791	155	44	𝑤ℎ𝑒𝑟𝑒𝜇	𝑤ℎ𝑒𝑟𝑒𝜇	NOUN
cana-4791	155	45	=	=	PUNCT
cana-4791	156	1	[	[	X
cana-4791	156	2	0.485,0.456,0.406	0.485,0.456,0.406	ADJ
cana-4791	156	3	]	]	X
cana-4791	156	4	,	,	PUNCT
cana-4791	156	5	𝜎	𝜎	NOUN
cana-4791	157	1	=	=	PUNCT
cana-4791	158	1	[	[	X
cana-4791	158	2	0.229,0.224,0.225	0.229,0.224,0.225	X
cana-4791	158	3	]	]	X
cana-4791	158	4	step	step	NOUN
cana-4791	158	5	3	3	NUM
cana-4791	158	6	:	:	PUNCT
cana-4791	158	7	feature	feature	NOUN
cana-4791	158	8	extraction	extraction	NOUN
cana-4791	158	9	pass	pass	VERB
cana-4791	158	10	both	both	DET
cana-4791	158	11	images	image	NOUN
cana-4791	158	12	through	through	ADP
cana-4791	158	13	pre	pre	ADJ
cana-4791	158	14	-	-	ADJ
cana-4791	158	15	trained	trained	ADJ
cana-4791	158	16	vgg12	vgg12	PROPN
cana-4791	158	17	extract	extract	VERB
cana-4791	158	18	intermediate	intermediate	ADJ
cana-4791	158	19	layer	layer	NOUN
cana-4791	158	20	features	feature	NOUN
cana-4791	158	21	:	:	PUNCT
cana-4791	158	22	𝐹_𝑙(𝐼_𝑖𝑛	𝐹_𝑙(𝐼_𝑖𝑛	ADJ
cana-4791	158	23	)	)	PUNCT
cana-4791	158	24	=	=	SYM
cana-4791	158	25	𝑉𝐺𝐺12_𝑙(𝐼_𝑖𝑛	𝑉𝐺𝐺12_𝑙(𝐼_𝑖𝑛	PROPN
cana-4791	158	26	)	)	PUNCT
cana-4791	158	27	𝐹_𝑙(𝐼_ℎ𝑎𝑡	𝐹_𝑙(𝐼_ℎ𝑎𝑡	PROPN
cana-4791	158	28	)	)	PUNCT
cana-4791	159	1	=	=	SYM
cana-4791	159	2	𝑉𝐺𝐺12_𝑙(𝐼_ℎ𝑎𝑡	𝑉𝐺𝐺12_𝑙(𝐼_ℎ𝑎𝑡	ADJ
cana-4791	159	3	)	)	PUNCT
cana-4791	159	4	step	step	NOUN
cana-4791	159	5	4	4	NUM
cana-4791	159	6	:	:	PUNCT
cana-4791	159	7	compute	compute	NOUN
cana-4791	159	8	feature	feature	NOUN
cana-4791	159	9	difference	difference	NOUN
cana-4791	159	10	use	use	NOUN
cana-4791	159	11	l2	l2	NOUN
cana-4791	159	12	norm	norm	NOUN
cana-4791	159	13	between	between	ADP
cana-4791	159	14	feature	feature	NOUN
cana-4791	159	15	maps	map	NOUN
cana-4791	159	16	:	:	PUNCT
cana-4791	159	17	𝛥_𝑙	𝛥_𝑙	NOUN
cana-4791	159	18	=	=	SYM
cana-4791	159	19	||𝐹_𝑙(𝐼_𝑖𝑛	||𝐹_𝑙(𝐼_𝑖𝑛	PROPN
cana-4791	159	20	)	)	PUNCT
cana-4791	159	21	−	−	NOUN
cana-4791	160	1	𝐹_𝑙(𝐼_ℎ𝑎𝑡)||₂²	𝐹_𝑙(𝐼_ℎ𝑎𝑡)||₂²	NUM
cana-4791	160	2	step	step	NOUN
cana-4791	160	3	5	5	NUM
cana-4791	160	4	:	:	PUNCT
cana-4791	160	5	aggregate	aggregate	ADJ
cana-4791	160	6	perceptual	perceptual	ADJ
cana-4791	160	7	loss	loss	NOUN
cana-4791	160	8	communications	communication	NOUN
cana-4791	160	9	on	on	ADP
cana-4791	160	10	applied	apply	VERB
cana-4791	160	11	nonlinear	nonlinear	ADJ
cana-4791	160	12	analysis	analysis	NOUN
cana-4791	160	13	issn	issn	NOUN
cana-4791	160	14	:	:	PUNCT
cana-4791	160	15	1074	1074	NUM
cana-4791	160	16	-	-	PUNCT
cana-4791	160	17	133x	133x	NUM
cana-4791	160	18	vol	vol	NOUN
cana-4791	160	19	31	31	NUM
cana-4791	160	20	no	no	NOUN
cana-4791	160	21	.	.	PUNCT
cana-4791	161	1	1s	1s	NUM
cana-4791	161	2	(	(	PUNCT
cana-4791	161	3	2024	2024	NUM
cana-4791	161	4	)	)	PUNCT
cana-4791	161	5	223	223	NUM
cana-4791	161	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	161	7	sum	sum	NOUN
cana-4791	161	8	over	over	ADP
cana-4791	161	9	selected	select	VERB
cana-4791	161	10	layers	layer	NOUN
cana-4791	161	11	(	(	PUNCT
cana-4791	161	12	e.g.	e.g.	ADV
cana-4791	161	13	,	,	PUNCT
cana-4791	161	14	l	l	PROPN
cana-4791	161	15	∈	∈	PROPN
cana-4791	161	16	{	{	PUNCT
cana-4791	161	17	conv1_2	conv1_2	NOUN
cana-4791	161	18	,	,	PUNCT
cana-4791	161	19	conv2_2	conv2_2	PROPN
cana-4791	161	20	,	,	PUNCT
cana-4791	161	21	conv3_3	conv3_3	PROPN
cana-4791	161	22	}	}	PUNCT
cana-4791	161	23	):	):	PUNCT
cana-4791	162	1	𝐿𝑝𝑒𝑟𝑐	𝐿𝑝𝑒𝑟𝑐	PROPN
cana-4791	162	2	=	=	SYM
cana-4791	162	3	𝛴𝑙𝑤𝑙	𝛴𝑙𝑤𝑙	NOUN
cana-4791	162	4	∗	∗	VERB
cana-4791	162	5	𝛥𝑙	𝛥𝑙	ADV
cana-4791	162	6	where	where	SCONJ
cana-4791	162	7	w_l	w_l	PROPN
cana-4791	162	8	is	be	AUX
cana-4791	162	9	a	a	DET
cana-4791	162	10	weight	weight	NOUN
cana-4791	162	11	assigned	assign	VERB
cana-4791	162	12	to	to	ADP
cana-4791	162	13	each	each	DET
cana-4791	162	14	layer	layer	NOUN
cana-4791	162	15	step	step	VERB
cana-4791	162	16	6	6	NUM
cana-4791	162	17	:	:	PUNCT
cana-4791	162	18	backpropagation	backpropagation	NOUN
cana-4791	162	19	treat	treat	VERB
cana-4791	162	20	l_perc	l_perc	NOUN
cana-4791	162	21	as	as	ADP
cana-4791	162	22	part	part	NOUN
cana-4791	162	23	of	of	ADP
cana-4791	162	24	total	total	ADJ
cana-4791	162	25	loss	loss	NOUN
cana-4791	162	26	:	:	PUNCT
cana-4791	162	27	𝐿_𝑡𝑜𝑡𝑎𝑙	𝐿_𝑡𝑜𝑡𝑎𝑙	PROPN
cana-4791	162	28	=	=	PRON
cana-4791	162	29	.	.	PUNCT
cana-4791	162	30	.	.	PUNCT
cana-4791	162	31	.	.	PUNCT
cana-4791	163	1	+	+	CCONJ
cana-4791	163	2	𝜆_𝑝𝑒𝑟𝑐	𝜆_𝑝𝑒𝑟𝑐	NOUN
cana-4791	163	3	∗	∗	NOUN
cana-4791	163	4	𝐿_𝑝𝑒𝑟𝑐	𝐿_𝑝𝑒𝑟𝑐	X
cana-4791	163	5	+	+	X
cana-4791	163	6	.	.	PUNCT
cana-4791	163	7	..	..	PUNCT
cana-4791	164	1	use	use	VERB
cana-4791	164	2	∇l_total	∇l_total	ADJ
cana-4791	164	3	to	to	PART
cana-4791	164	4	update	update	VERB
cana-4791	164	5	generator	generator	NOUN
cana-4791	164	6	parameters	parameter	NOUN
cana-4791	164	7	in	in	ADP
cana-4791	164	8	compressgan	compressgan	PROPN
cana-4791	164	9	,	,	PUNCT
cana-4791	164	10	the	the	DET
cana-4791	164	11	vgg12	vgg12	PROPN
cana-4791	164	12	network	network	NOUN
cana-4791	164	13	is	be	AUX
cana-4791	164	14	used	use	VERB
cana-4791	164	15	not	not	PART
cana-4791	164	16	for	for	ADP
cana-4791	164	17	classification	classification	NOUN
cana-4791	164	18	but	but	CCONJ
cana-4791	164	19	as	as	ADP
cana-4791	164	20	a	a	DET
cana-4791	164	21	fixed	fix	VERB
cana-4791	164	22	feature	feature	NOUN
cana-4791	164	23	extractor	extractor	NOUN
cana-4791	164	24	.	.	PUNCT
cana-4791	165	1	it	it	PRON
cana-4791	165	2	is	be	AUX
cana-4791	165	3	pretrained	pretraine	VERB
cana-4791	165	4	on	on	ADP
cana-4791	165	5	a	a	DET
cana-4791	165	6	large	large	ADJ
cana-4791	165	7	-	-	PUNCT
cana-4791	165	8	scale	scale	NOUN
cana-4791	165	9	dataset	dataset	NOUN
cana-4791	165	10	like	like	ADP
cana-4791	165	11	imagenet	imagenet	NOUN
cana-4791	165	12	and	and	CCONJ
cana-4791	165	13	remains	remain	VERB
cana-4791	165	14	frozen	frozen	ADJ
cana-4791	165	15	during	during	ADP
cana-4791	165	16	training	training	NOUN
cana-4791	165	17	to	to	PART
cana-4791	165	18	ensure	ensure	VERB
cana-4791	165	19	consistent	consistent	ADJ
cana-4791	165	20	gradient	gradient	ADJ
cana-4791	165	21	feedback	feedback	NOUN
cana-4791	165	22	.	.	PUNCT
cana-4791	166	1	the	the	DET
cana-4791	166	2	perceptual	perceptual	ADJ
cana-4791	166	3	loss	loss	NOUN
cana-4791	166	4	is	be	AUX
cana-4791	166	5	computed	compute	VERB
cana-4791	166	6	by	by	ADP
cana-4791	166	7	feeding	feed	VERB
cana-4791	166	8	both	both	CCONJ
cana-4791	166	9	the	the	DET
cana-4791	166	10	original	original	ADJ
cana-4791	166	11	and	and	CCONJ
cana-4791	166	12	reconstructed	reconstructed	ADJ
cana-4791	166	13	images	image	NOUN
cana-4791	166	14	through	through	ADP
cana-4791	166	15	the	the	DET
cana-4791	166	16	vgg12	vgg12	PROPN
cana-4791	166	17	network	network	NOUN
cana-4791	166	18	and	and	CCONJ
cana-4791	166	19	measuring	measure	VERB
cana-4791	166	20	the	the	DET
cana-4791	166	21	l1	l1	PROPN
cana-4791	166	22	or	or	CCONJ
cana-4791	166	23	l2	l2	NOUN
cana-4791	166	24	distance	distance	NOUN
cana-4791	166	25	between	between	ADP
cana-4791	166	26	the	the	DET
cana-4791	166	27	resulting	result	VERB
cana-4791	166	28	feature	feature	NOUN
cana-4791	166	29	maps	map	NOUN
cana-4791	166	30	at	at	ADP
cana-4791	166	31	one	one	NUM
cana-4791	166	32	or	or	CCONJ
cana-4791	166	33	more	more	ADJ
cana-4791	166	34	intermediate	intermediate	ADJ
cana-4791	166	35	layers	layer	NOUN
cana-4791	166	36	.	.	PUNCT
cana-4791	167	1	typically	typically	ADV
cana-4791	167	2	,	,	PUNCT
cana-4791	167	3	feature	feature	NOUN
cana-4791	167	4	maps	map	NOUN
cana-4791	167	5	from	from	ADP
cana-4791	167	6	the	the	DET
cana-4791	167	7	earlier	early	ADJ
cana-4791	167	8	layers	layer	NOUN
cana-4791	167	9	(	(	PUNCT
cana-4791	167	10	e.g.	e.g.	ADV
cana-4791	167	11	,	,	PUNCT
cana-4791	167	12	conv1_2	conv1_2	NOUN
cana-4791	167	13	or	or	CCONJ
cana-4791	167	14	conv2_2	conv2_2	PROPN
cana-4791	167	15	)	)	PUNCT
cana-4791	167	16	are	be	AUX
cana-4791	167	17	sensitive	sensitive	ADJ
cana-4791	167	18	to	to	ADP
cana-4791	167	19	textures	texture	NOUN
cana-4791	167	20	and	and	CCONJ
cana-4791	167	21	edges	edge	NOUN
cana-4791	167	22	,	,	PUNCT
cana-4791	167	23	while	while	SCONJ
cana-4791	167	24	deeper	deep	ADJ
cana-4791	167	25	layers	layer	NOUN
cana-4791	167	26	(	(	PUNCT
cana-4791	167	27	e.g.	e.g.	ADV
cana-4791	167	28	,	,	PUNCT
cana-4791	167	29	conv4_3	conv4_3	NOUN
cana-4791	167	30	or	or	CCONJ
cana-4791	167	31	conv5_3	conv5_3	NOUN
cana-4791	167	32	)	)	PUNCT
cana-4791	167	33	capture	capture	VERB
cana-4791	167	34	semantic	semantic	ADJ
cana-4791	167	35	structures	structure	NOUN
cana-4791	167	36	and	and	CCONJ
cana-4791	167	37	object	object	NOUN
cana-4791	167	38	-	-	PUNCT
cana-4791	167	39	level	level	NOUN
cana-4791	167	40	information	information	NOUN
cana-4791	167	41	.	.	PUNCT
cana-4791	168	1	by	by	ADP
cana-4791	168	2	combining	combine	VERB
cana-4791	168	3	losses	loss	NOUN
cana-4791	168	4	from	from	ADP
cana-4791	168	5	multiple	multiple	ADJ
cana-4791	168	6	layers	layer	NOUN
cana-4791	168	7	,	,	PUNCT
cana-4791	168	8	compressgan	compressgan	PROPN
cana-4791	168	9	can	can	AUX
cana-4791	168	10	enforce	enforce	VERB
cana-4791	168	11	both	both	PRON
cana-4791	168	12	low	low	ADJ
cana-4791	168	13	-	-	PUNCT
cana-4791	168	14	level	level	NOUN
cana-4791	168	15	fidelity	fidelity	NOUN
cana-4791	168	16	and	and	CCONJ
cana-4791	168	17	high	high	ADJ
cana-4791	168	18	-	-	PUNCT
cana-4791	168	19	level	level	NOUN
cana-4791	168	20	content	content	NOUN
cana-4791	168	21	preservation	preservation	NOUN
cana-4791	168	22	in	in	ADP
cana-4791	168	23	the	the	DET
cana-4791	168	24	reconstructed	reconstruct	VERB
cana-4791	168	25	images	image	NOUN
cana-4791	168	26	.	.	PUNCT
cana-4791	169	1	one	one	NUM
cana-4791	169	2	of	of	ADP
cana-4791	169	3	the	the	DET
cana-4791	169	4	advantages	advantage	NOUN
cana-4791	169	5	of	of	ADP
cana-4791	169	6	using	use	VERB
cana-4791	169	7	vgg12	vgg12	PROPN
cana-4791	169	8	over	over	ADP
cana-4791	169	9	its	its	PRON
cana-4791	169	10	deeper	deep	ADJ
cana-4791	169	11	variants	variant	NOUN
cana-4791	169	12	like	like	ADP
cana-4791	169	13	vgg16	vgg16	PROPN
cana-4791	169	14	or	or	CCONJ
cana-4791	169	15	vgg19	vgg19	PROPN
cana-4791	169	16	is	be	AUX
cana-4791	169	17	computational	computational	ADJ
cana-4791	169	18	efficiency	efficiency	NOUN
cana-4791	169	19	.	.	PUNCT
cana-4791	170	1	vgg12	vgg12	PROPN
cana-4791	170	2	retains	retain	VERB
cana-4791	170	3	much	much	ADJ
cana-4791	170	4	of	of	ADP
cana-4791	170	5	the	the	DET
cana-4791	170	6	representational	representational	ADJ
cana-4791	170	7	power	power	NOUN
cana-4791	170	8	required	require	VERB
cana-4791	170	9	for	for	ADP
cana-4791	170	10	perceptual	perceptual	ADJ
cana-4791	170	11	similarity	similarity	NOUN
cana-4791	170	12	assessment	assessment	NOUN
cana-4791	170	13	while	while	SCONJ
cana-4791	170	14	reducing	reduce	VERB
cana-4791	170	15	the	the	DET
cana-4791	170	16	computational	computational	ADJ
cana-4791	170	17	overhead	overhead	NOUN
cana-4791	170	18	,	,	PUNCT
cana-4791	170	19	which	which	PRON
cana-4791	170	20	is	be	AUX
cana-4791	170	21	crucial	crucial	ADJ
cana-4791	170	22	for	for	ADP
cana-4791	170	23	real	real	ADJ
cana-4791	170	24	-	-	PUNCT
cana-4791	170	25	time	time	NOUN
cana-4791	170	26	or	or	CCONJ
cana-4791	170	27	resource	resource	NOUN
cana-4791	170	28	-	-	PUNCT
cana-4791	170	29	constrained	constrain	VERB
cana-4791	170	30	applications	application	NOUN
cana-4791	170	31	.	.	PUNCT
cana-4791	171	1	moreover	moreover	ADV
cana-4791	171	2	,	,	PUNCT
cana-4791	171	3	the	the	DET
cana-4791	171	4	selection	selection	NOUN
cana-4791	171	5	of	of	ADP
cana-4791	171	6	specific	specific	ADJ
cana-4791	171	7	layers	layer	NOUN
cana-4791	171	8	for	for	ADP
cana-4791	171	9	loss	loss	NOUN
cana-4791	171	10	computation	computation	NOUN
cana-4791	171	11	is	be	AUX
cana-4791	171	12	informed	inform	VERB
cana-4791	171	13	by	by	ADP
cana-4791	171	14	empirical	empirical	ADJ
cana-4791	171	15	studies	study	NOUN
cana-4791	171	16	showing	show	VERB
cana-4791	171	17	which	which	PRON
cana-4791	171	18	features	feature	VERB
cana-4791	171	19	align	align	VERB
cana-4791	171	20	best	well	ADV
cana-4791	171	21	with	with	ADP
cana-4791	171	22	human	human	ADJ
cana-4791	171	23	visual	visual	ADJ
cana-4791	171	24	preferences	preference	NOUN
cana-4791	171	25	.	.	PUNCT
cana-4791	172	1	for	for	ADP
cana-4791	172	2	instance	instance	NOUN
cana-4791	172	3	,	,	PUNCT
cana-4791	172	4	layers	layer	NOUN
cana-4791	172	5	with	with	ADP
cana-4791	172	6	a	a	DET
cana-4791	172	7	larger	large	ADJ
cana-4791	172	8	receptive	receptive	ADJ
cana-4791	172	9	field	field	NOUN
cana-4791	172	10	tend	tend	VERB
cana-4791	172	11	to	to	PART
cana-4791	172	12	be	be	AUX
cana-4791	172	13	better	well	ADJ
cana-4791	172	14	at	at	ADP
cana-4791	172	15	enforcing	enforce	VERB
cana-4791	172	16	global	global	ADJ
cana-4791	172	17	consistency	consistency	NOUN
cana-4791	172	18	,	,	PUNCT
cana-4791	172	19	while	while	SCONJ
cana-4791	172	20	shallow	shallow	ADJ
cana-4791	172	21	layers	layer	NOUN
cana-4791	172	22	are	be	AUX
cana-4791	172	23	more	more	ADV
cana-4791	172	24	effective	effective	ADJ
cana-4791	172	25	at	at	ADP
cana-4791	172	26	preserving	preserve	VERB
cana-4791	172	27	fine	fine	ADJ
cana-4791	172	28	details	detail	NOUN
cana-4791	172	29	such	such	ADJ
cana-4791	172	30	as	as	ADP
cana-4791	172	31	edges	edge	NOUN
cana-4791	172	32	and	and	CCONJ
cana-4791	172	33	textures	texture	NOUN
cana-4791	172	34	.	.	PUNCT
cana-4791	173	1	by	by	ADP
cana-4791	173	2	carefully	carefully	ADV
cana-4791	173	3	balancing	balance	VERB
cana-4791	173	4	these	these	DET
cana-4791	173	5	layers	layer	NOUN
cana-4791	173	6	,	,	PUNCT
cana-4791	173	7	the	the	DET
cana-4791	173	8	vgg12	vgg12	PROPN
cana-4791	173	9	-	-	PUNCT
cana-4791	173	10	based	base	VERB
cana-4791	173	11	perceptual	perceptual	ADJ
cana-4791	173	12	loss	loss	NOUN
cana-4791	173	13	enables	enable	VERB
cana-4791	173	14	compressgan	compressgan	VERB
cana-4791	173	15	to	to	PART
cana-4791	173	16	generate	generate	VERB
cana-4791	173	17	images	image	NOUN
cana-4791	173	18	that	that	PRON
cana-4791	173	19	are	be	AUX
cana-4791	173	20	not	not	PART
cana-4791	173	21	only	only	ADV
cana-4791	173	22	numerically	numerically	ADV
cana-4791	173	23	accurate	accurate	ADJ
cana-4791	173	24	but	but	CCONJ
cana-4791	173	25	also	also	ADV
cana-4791	173	26	visually	visually	ADV
cana-4791	173	27	pleasing	pleasing	ADJ
cana-4791	173	28	.	.	PUNCT
cana-4791	174	1	5	5	X
cana-4791	174	2	.	.	X
cana-4791	174	3	result	result	NOUN
cana-4791	174	4	and	and	CCONJ
cana-4791	174	5	discussion	discussion	NOUN
cana-4791	174	6	in	in	ADP
cana-4791	174	7	table	table	NOUN
cana-4791	174	8	2	2	NUM
cana-4791	174	9	,	,	PUNCT
cana-4791	174	10	demonstrate	demonstrate	VERB
cana-4791	174	11	how	how	SCONJ
cana-4791	174	12	well	well	ADV
cana-4791	174	13	compressgan	compressgan	PROPN
cana-4791	174	14	compares	compare	VERB
cana-4791	174	15	to	to	ADP
cana-4791	174	16	a	a	DET
cana-4791	174	17	number	number	NOUN
cana-4791	174	18	of	of	ADP
cana-4791	174	19	other	other	ADJ
cana-4791	174	20	image	image	NOUN
cana-4791	174	21	compression	compression	NOUN
cana-4791	174	22	methods	method	NOUN
cana-4791	174	23	using	use	VERB
cana-4791	174	24	three	three	NUM
cana-4791	174	25	well	well	ADV
cana-4791	174	26	-	-	PUNCT
cana-4791	174	27	known	know	VERB
cana-4791	174	28	metrics	metric	NOUN
cana-4791	174	29	:	:	PUNCT
cana-4791	174	30	psnr	psnr	NOUN
cana-4791	174	31	(	(	PUNCT
cana-4791	174	32	peak	peak	NOUN
cana-4791	174	33	signal	signal	NOUN
cana-4791	174	34	-	-	PUNCT
cana-4791	174	35	to	to	ADP
cana-4791	174	36	-	-	PUNCT
cana-4791	174	37	noise	noise	NOUN
cana-4791	174	38	ratio	ratio	NOUN
cana-4791	174	39	)	)	PUNCT
cana-4791	174	40	,	,	PUNCT
cana-4791	174	41	ssim	ssim	NOUN
cana-4791	174	42	(	(	PUNCT
cana-4791	174	43	structural	structural	ADJ
cana-4791	174	44	similarity	similarity	NOUN
cana-4791	174	45	index	index	NOUN
cana-4791	174	46	)	)	PUNCT
cana-4791	174	47	,	,	PUNCT
cana-4791	174	48	and	and	CCONJ
cana-4791	174	49	lpips	lpip	NOUN
cana-4791	174	50	(	(	PUNCT
cana-4791	174	51	learnt	learn	VERB
cana-4791	174	52	perceptual	perceptual	ADJ
cana-4791	174	53	image	image	NOUN
cana-4791	174	54	patch	patch	NOUN
cana-4791	174	55	similarity	similarity	NOUN
cana-4791	174	56	)	)	PUNCT
cana-4791	174	57	.	.	PUNCT
cana-4791	175	1	together	together	ADV
cana-4791	175	2	,	,	PUNCT
cana-4791	175	3	these	these	DET
cana-4791	175	4	measures	measure	NOUN
cana-4791	175	5	rate	rate	VERB
cana-4791	175	6	both	both	CCONJ
cana-4791	175	7	the	the	DET
cana-4791	175	8	accuracy	accuracy	NOUN
cana-4791	175	9	and	and	CCONJ
cana-4791	175	10	the	the	DET
cana-4791	175	11	quality	quality	NOUN
cana-4791	175	12	of	of	ADP
cana-4791	175	13	how	how	SCONJ
cana-4791	175	14	the	the	DET
cana-4791	175	15	rebuilt	rebuilt	ADJ
cana-4791	175	16	pictures	picture	NOUN
cana-4791	175	17	are	be	AUX
cana-4791	175	18	perceived	perceive	VERB
cana-4791	175	19	.	.	PUNCT
cana-4791	176	1	starting	start	VERB
cana-4791	176	2	with	with	ADP
cana-4791	176	3	psnr	psnr	NOUN
cana-4791	176	4	,	,	PUNCT
cana-4791	176	5	which	which	PRON
cana-4791	176	6	measures	measure	VERB
cana-4791	176	7	how	how	SCONJ
cana-4791	176	8	accurate	accurate	ADJ
cana-4791	176	9	the	the	DET
cana-4791	176	10	original	original	ADJ
cana-4791	176	11	and	and	CCONJ
cana-4791	176	12	rebuilt	rebuild	VERB
cana-4791	176	13	images	image	NOUN
cana-4791	176	14	are	be	AUX
cana-4791	176	15	down	down	ADP
cana-4791	176	16	to	to	ADP
cana-4791	176	17	the	the	DET
cana-4791	176	18	pixel	pixel	PROPN
cana-4791	176	19	level	level	NOUN
cana-4791	176	20	,	,	PUNCT
cana-4791	176	21	compressgan	compressgan	PROPN
cana-4791	176	22	gets	get	VERB
cana-4791	176	23	the	the	DET
cana-4791	176	24	best	good	ADJ
cana-4791	176	25	score	score	NOUN
cana-4791	176	26	of	of	ADP
cana-4791	176	27	36.7	36.7	NUM
cana-4791	176	28	db	db	NOUN
cana-4791	176	29	,	,	PUNCT
cana-4791	176	30	which	which	PRON
cana-4791	176	31	means	mean	VERB
cana-4791	176	32	that	that	SCONJ
cana-4791	176	33	the	the	DET
cana-4791	176	34	reconstruction	reconstruction	NOUN
cana-4791	176	35	is	be	AUX
cana-4791	176	36	more	more	ADV
cana-4791	176	37	accurate	accurate	ADJ
cana-4791	176	38	.	.	PUNCT
cana-4791	177	1	on	on	ADP
cana-4791	177	2	the	the	DET
cana-4791	177	3	other	other	ADJ
cana-4791	177	4	hand	hand	NOUN
cana-4791	177	5	,	,	PUNCT
cana-4791	177	6	standard	standard	ADJ
cana-4791	177	7	codecs	codec	NOUN
cana-4791	177	8	like	like	ADP
cana-4791	177	9	jpeg	jpeg	NOUN
cana-4791	177	10	and	and	CCONJ
cana-4791	177	11	jpeg2000	jpeg2000	PROPN
cana-4791	177	12	only	only	ADV
cana-4791	177	13	reach	reach	VERB
cana-4791	177	14	29.1	29.1	NUM
cana-4791	177	15	db	db	NOUN
cana-4791	177	16	and	and	CCONJ
cana-4791	177	17	31.5	31.5	NUM
cana-4791	177	18	db	db	NOUN
cana-4791	177	19	,	,	PUNCT
cana-4791	177	20	which	which	PRON
cana-4791	177	21	shows	show	VERB
cana-4791	177	22	that	that	SCONJ
cana-4791	177	23	they	they	PRON
cana-4791	177	24	ca	can	AUX
cana-4791	177	25	n't	not	PART
cana-4791	177	26	keep	keep	VERB
cana-4791	177	27	small	small	ADJ
cana-4791	177	28	features	feature	NOUN
cana-4791	177	29	,	,	PUNCT
cana-4791	177	30	especially	especially	ADV
cana-4791	177	31	at	at	ADP
cana-4791	177	32	lower	low	ADJ
cana-4791	177	33	bitrates	bitrate	NOUN
cana-4791	177	34	.	.	PUNCT
cana-4791	178	1	with	with	ADP
cana-4791	178	2	33.2	33.2	NUM
cana-4791	178	3	db	db	PROPN
cana-4791	178	4	,	,	PUNCT
cana-4791	178	5	the	the	DET
cana-4791	178	6	current	current	ADJ
cana-4791	178	7	compression	compression	NOUN
cana-4791	178	8	standard	standard	NOUN
cana-4791	178	9	bpg	bpg	PROPN
cana-4791	178	10	does	do	VERB
cana-4791	178	11	better	well	ADV
cana-4791	178	12	,	,	PUNCT
cana-4791	178	13	but	but	CCONJ
cana-4791	178	14	it	it	PRON
cana-4791	178	15	's	be	AUX
cana-4791	178	16	still	still	ADV
cana-4791	178	17	not	not	PART
cana-4791	178	18	as	as	ADV
cana-4791	178	19	good	good	ADJ
cana-4791	178	20	as	as	ADP
cana-4791	178	21	learning	learning	NOUN
cana-4791	178	22	-	-	PUNCT
cana-4791	178	23	based	base	VERB
cana-4791	178	24	models	model	NOUN
cana-4791	178	25	.	.	PUNCT
cana-4791	179	1	the	the	DET
cana-4791	179	2	autoencoder	autoencoder	NOUN
cana-4791	179	3	and	and	CCONJ
cana-4791	179	4	vae	vae	PROPN
cana-4791	179	5	-	-	PUNCT
cana-4791	179	6	based	base	VERB
cana-4791	179	7	methods	method	NOUN
cana-4791	179	8	work	work	VERB
cana-4791	179	9	well	well	ADV
cana-4791	179	10	,	,	PUNCT
cana-4791	179	11	with	with	ADP
cana-4791	179	12	34.8	34.8	NUM
cana-4791	179	13	db	db	NOUN
cana-4791	179	14	and	and	CCONJ
cana-4791	179	15	35.2	35.2	NUM
cana-4791	179	16	db	db	PROPN
cana-4791	179	17	of	of	ADP
cana-4791	179	18	performance	performance	NOUN
cana-4791	179	19	,	,	PUNCT
cana-4791	179	20	respectively	respectively	ADV
cana-4791	179	21	.	.	PUNCT
cana-4791	180	1	this	this	PRON
cana-4791	180	2	shows	show	VERB
cana-4791	180	3	the	the	DET
cana-4791	180	4	benefit	benefit	NOUN
cana-4791	180	5	of	of	ADP
cana-4791	180	6	data	data	NOUN
cana-4791	180	7	-	-	PUNCT
cana-4791	180	8	driven	drive	VERB
cana-4791	180	9	latent	latent	NOUN
cana-4791	180	10	models	model	NOUN
cana-4791	180	11	.	.	PUNCT
cana-4791	181	1	but	but	CCONJ
cana-4791	181	2	compressgan	compressgan	PROPN
cana-4791	181	3	does	do	VERB
cana-4791	181	4	better	well	ADV
cana-4791	181	5	than	than	ADP
cana-4791	181	6	all	all	PRON
cana-4791	181	7	of	of	ADP
cana-4791	181	8	them	they	PRON
cana-4791	181	9	because	because	SCONJ
cana-4791	181	10	it	it	PRON
cana-4791	181	11	combines	combine	VERB
cana-4791	181	12	hostile	hostile	ADJ
cana-4791	181	13	and	and	CCONJ
cana-4791	181	14	visual	visual	ADJ
cana-4791	181	15	parts	part	NOUN
cana-4791	181	16	.	.	PUNCT
cana-4791	182	1	table	table	NOUN
cana-4791	182	2	2	2	NUM
cana-4791	182	3	:	:	PUNCT
cana-4791	182	4	quantitative	quantitative	ADJ
cana-4791	182	5	evaluation	evaluation	NOUN
cana-4791	182	6	table	table	NOUN
cana-4791	182	7	model	model	NOUN
cana-4791	182	8	psnr	psnr	NOUN
cana-4791	182	9	(	(	PUNCT
cana-4791	182	10	db	db	NOUN
cana-4791	182	11	)	)	PUNCT
cana-4791	182	12	ssim	ssim	NOUN
cana-4791	182	13	lpips	lpip	NOUN
cana-4791	182	14	(	(	PUNCT
cana-4791	182	15	↓	↓	NOUN
cana-4791	182	16	)	)	PUNCT
cana-4791	182	17	jpeg	jpeg	NOUN
cana-4791	182	18	29.1	29.1	NUM
cana-4791	182	19	0.842	0.842	NUM
cana-4791	182	20	0.31	0.31	NUM
cana-4791	182	21	jpeg2000	jpeg2000	PROPN
cana-4791	182	22	31.5	31.5	NUM
cana-4791	182	23	0.891	0.891	NUM
cana-4791	182	24	0.256	0.256	NUM
cana-4791	182	25	bpg	bpg	PROPN
cana-4791	182	26	33.2	33.2	NUM
cana-4791	182	27	0.903	0.903	NUM
cana-4791	182	28	0.204	0.204	NUM
cana-4791	182	29	communications	communication	NOUN
cana-4791	182	30	on	on	ADP
cana-4791	182	31	applied	apply	VERB
cana-4791	182	32	nonlinear	nonlinear	ADJ
cana-4791	182	33	analysis	analysis	NOUN
cana-4791	182	34	issn	issn	NOUN
cana-4791	182	35	:	:	PUNCT
cana-4791	182	36	1074	1074	NUM
cana-4791	182	37	-	-	PUNCT
cana-4791	182	38	133x	133x	NUM
cana-4791	182	39	vol	vol	NOUN
cana-4791	182	40	31	31	NUM
cana-4791	182	41	no	no	NOUN
cana-4791	182	42	.	.	PUNCT
cana-4791	183	1	1s	1s	NUM
cana-4791	183	2	(	(	PUNCT
cana-4791	183	3	2024	2024	NUM
cana-4791	183	4	)	)	PUNCT
cana-4791	183	5	224	224	NUM
cana-4791	183	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	183	7	autoencoder	autoencoder	NOUN
cana-4791	183	8	34.8	34.8	NUM
cana-4791	183	9	0.917	0.917	NUM
cana-4791	183	10	0.182	0.182	NUM
cana-4791	183	11	vae	vae	PROPN
cana-4791	183	12	35.2	35.2	NUM
cana-4791	183	13	0.921	0.921	NUM
cana-4791	183	14	0.175	0.175	NUM
cana-4791	183	15	compressgan	compressgan	VERB
cana-4791	183	16	36.7	36.7	NUM
cana-4791	183	17	0.942	0.942	NUM
cana-4791	183	18	0.128	0.128	NUM
cana-4791	183	19	with	with	ADP
cana-4791	183	20	a	a	DET
cana-4791	183	21	score	score	NOUN
cana-4791	183	22	of	of	ADP
cana-4791	183	23	0.942	0.942	NUM
cana-4791	183	24	,	,	PUNCT
cana-4791	183	25	compressgan	compressgan	VERB
cana-4791	183	26	again	again	ADV
cana-4791	183	27	comes	come	VERB
cana-4791	183	28	out	out	ADP
cana-4791	183	29	on	on	ADP
cana-4791	183	30	top	top	NOUN
cana-4791	183	31	for	for	ADP
cana-4791	183	32	ssim	ssim	NOUN
cana-4791	183	33	,	,	PUNCT
cana-4791	183	34	which	which	PRON
cana-4791	183	35	measures	measure	VERB
cana-4791	183	36	structural	structural	ADJ
cana-4791	183	37	resemblance	resemblance	NOUN
cana-4791	183	38	and	and	CCONJ
cana-4791	183	39	visual	visual	ADJ
cana-4791	183	40	consistency	consistency	NOUN
cana-4791	183	41	.	.	PUNCT
cana-4791	184	1	this	this	PRON
cana-4791	184	2	shows	show	VERB
cana-4791	184	3	that	that	SCONJ
cana-4791	184	4	it	it	PRON
cana-4791	184	5	can	can	AUX
cana-4791	184	6	keep	keep	VERB
cana-4791	184	7	edges	edge	NOUN
cana-4791	184	8	sharp	sharp	ADJ
cana-4791	184	9	and	and	CCONJ
cana-4791	184	10	picture	picture	NOUN
cana-4791	184	11	structure	structure	NOUN
cana-4791	184	12	.	.	PUNCT
cana-4791	185	1	the	the	DET
cana-4791	185	2	ssim	ssim	NOUN
cana-4791	185	3	numbers	number	NOUN
cana-4791	185	4	for	for	ADP
cana-4791	185	5	jpeg	jpeg	NOUN
cana-4791	185	6	and	and	CCONJ
cana-4791	185	7	jpeg2000	jpeg2000	PROPN
cana-4791	185	8	are	be	AUX
cana-4791	185	9	much	much	ADV
cana-4791	185	10	lower	low	ADJ
cana-4791	185	11	(	(	PUNCT
cana-4791	185	12	0.842	0.842	NUM
cana-4791	185	13	and	and	CCONJ
cana-4791	185	14	0.891	0.891	NUM
cana-4791	185	15	)	)	PUNCT
cana-4791	185	16	,	,	PUNCT
cana-4791	185	17	which	which	PRON
cana-4791	185	18	means	mean	VERB
cana-4791	185	19	that	that	SCONJ
cana-4791	185	20	flaws	flaw	NOUN
cana-4791	185	21	and	and	CCONJ
cana-4791	185	22	artefacts	artefact	NOUN
cana-4791	185	23	can	can	AUX
cana-4791	185	24	be	be	AUX
cana-4791	185	25	seen	see	VERB
cana-4791	185	26	.	.	PUNCT
cana-4791	186	1	the	the	DET
cana-4791	186	2	steady	steady	ADJ
cana-4791	186	3	improvement	improvement	NOUN
cana-4791	186	4	from	from	ADP
cana-4791	186	5	autoencoder	autoencoder	NOUN
cana-4791	186	6	(	(	PUNCT
cana-4791	186	7	0.917	0.917	NUM
cana-4791	186	8	)	)	PUNCT
cana-4791	186	9	to	to	ADP
cana-4791	186	10	vae	vae	PROPN
cana-4791	186	11	(	(	PUNCT
cana-4791	186	12	0.921	0.921	NUM
cana-4791	186	13	)	)	PUNCT
cana-4791	186	14	and	and	CCONJ
cana-4791	186	15	finally	finally	ADV
cana-4791	186	16	to	to	PART
cana-4791	186	17	compressgan	compressgan	VERB
cana-4791	186	18	shows	show	VERB
cana-4791	186	19	that	that	SCONJ
cana-4791	186	20	advanced	advanced	ADJ
cana-4791	186	21	loss	loss	NOUN
cana-4791	186	22	formulas	formula	NOUN
cana-4791	186	23	are	be	AUX
cana-4791	186	24	good	good	ADJ
cana-4791	186	25	at	at	ADP
cana-4791	186	26	keeping	keep	VERB
cana-4791	186	27	structure	structure	NOUN
cana-4791	186	28	content	content	NOUN
cana-4791	186	29	.	.	PUNCT
cana-4791	187	1	figure	figure	VERB
cana-4791	187	2	3	3	NUM
cana-4791	187	3	:	:	PUNCT
cana-4791	187	4	comparison	comparison	NOUN
cana-4791	187	5	of	of	ADP
cana-4791	187	6	image	image	NOUN
cana-4791	187	7	compression	compression	NOUN
cana-4791	187	8	models	model	NOUN
cana-4791	187	9	with	with	ADP
cana-4791	187	10	a	a	DET
cana-4791	187	11	value	value	NOUN
cana-4791	187	12	of	of	ADP
cana-4791	187	13	0.128	0.128	NUM
cana-4791	187	14	,	,	PUNCT
cana-4791	187	15	lpips	lpip	NOUN
cana-4791	187	16	,	,	PUNCT
cana-4791	187	17	a	a	DET
cana-4791	187	18	perceived	perceive	VERB
cana-4791	187	19	quality	quality	NOUN
cana-4791	187	20	measure	measure	NOUN
cana-4791	187	21	that	that	PRON
cana-4791	187	22	shows	show	VERB
cana-4791	187	23	better	well	ADJ
cana-4791	187	24	performance	performance	NOUN
cana-4791	187	25	as	as	ADP
cana-4791	187	26	smaller	small	ADJ
cana-4791	187	27	values	value	NOUN
cana-4791	187	28	,	,	PUNCT
cana-4791	187	29	compressgan	compressgan	PROPN
cana-4791	187	30	is	be	AUX
cana-4791	187	31	even	even	ADV
cana-4791	187	32	more	more	ADV
cana-4791	187	33	clearly	clearly	ADV
cana-4791	187	34	better	well	ADJ
cana-4791	187	35	.	.	PUNCT
cana-4791	188	1	lpips	lpip	NOUN
cana-4791	188	2	for	for	ADP
cana-4791	188	3	traditional	traditional	ADJ
cana-4791	188	4	ways	way	NOUN
cana-4791	188	5	are	be	AUX
cana-4791	188	6	pretty	pretty	ADV
cana-4791	188	7	high	high	ADJ
cana-4791	188	8	(	(	PUNCT
cana-4791	188	9	jpeg	jpeg	NOUN
cana-4791	188	10	is	be	AUX
cana-4791	188	11	0.31	0.31	NUM
cana-4791	188	12	)	)	PUNCT
cana-4791	188	13	,	,	PUNCT
cana-4791	188	14	which	which	PRON
cana-4791	188	15	shows	show	VERB
cana-4791	188	16	that	that	SCONJ
cana-4791	188	17	the	the	DET
cana-4791	188	18	quality	quality	NOUN
cana-4791	188	19	of	of	ADP
cana-4791	188	20	the	the	DET
cana-4791	188	21	image	image	NOUN
cana-4791	188	22	is	be	AUX
cana-4791	188	23	n't	not	PART
cana-4791	188	24	very	very	ADV
cana-4791	188	25	good	good	ADJ
cana-4791	188	26	.	.	PUNCT
cana-4791	189	1	compressgan	compressgan	PROPN
cana-4791	189	2	's	's	PART
cana-4791	189	3	lower	low	ADJ
cana-4791	189	4	lpips	lpip	NOUN
cana-4791	189	5	shows	show	VERB
cana-4791	189	6	that	that	SCONJ
cana-4791	189	7	it	it	PRON
cana-4791	189	8	can	can	AUX
cana-4791	189	9	make	make	VERB
cana-4791	189	10	models	model	NOUN
cana-4791	189	11	that	that	PRON
cana-4791	189	12	are	be	AUX
cana-4791	189	13	not	not	PART
cana-4791	189	14	only	only	ADV
cana-4791	189	15	accurate	accurate	ADJ
cana-4791	189	16	but	but	CCONJ
cana-4791	189	17	also	also	ADV
cana-4791	189	18	believable	believable	ADJ
cana-4791	189	19	to	to	ADP
cana-4791	189	20	the	the	DET
cana-4791	189	21	human	human	ADJ
cana-4791	189	22	eye	eye	NOUN
cana-4791	189	23	.	.	PUNCT
cana-4791	190	1	this	this	PRON
cana-4791	190	2	makes	make	VERB
cana-4791	190	3	it	it	PRON
cana-4791	190	4	a	a	DET
cana-4791	190	5	great	great	ADJ
cana-4791	190	6	choice	choice	NOUN
cana-4791	190	7	for	for	ADP
cana-4791	190	8	real	real	ADJ
cana-4791	190	9	-	-	PUNCT
cana-4791	190	10	world	world	NOUN
cana-4791	190	11	picture	picture	NOUN
cana-4791	190	12	compression	compression	NOUN
cana-4791	190	13	tasks	task	NOUN
cana-4791	190	14	.	.	PUNCT
cana-4791	191	1	compressgan	compressgan	PROPN
cana-4791	191	2	always	always	ADV
cana-4791	191	3	does	do	VERB
cana-4791	191	4	better	well	ADV
cana-4791	191	5	than	than	ADP
cana-4791	191	6	the	the	DET
cana-4791	191	7	other	other	ADJ
cana-4791	191	8	models	model	NOUN
cana-4791	191	9	that	that	PRON
cana-4791	191	10	were	be	AUX
cana-4791	191	11	tested	test	VERB
cana-4791	191	12	in	in	ADP
cana-4791	191	13	all	all	DET
cana-4791	191	14	three	three	NUM
cana-4791	191	15	quality	quality	NOUN
cana-4791	191	16	areas	area	NOUN
cana-4791	191	17	.	.	PUNCT
cana-4791	192	1	it	it	PRON
cana-4791	192	2	gets	get	VERB
cana-4791	192	3	an	an	DET
cana-4791	192	4	edge	edge	NOUN
cana-4791	192	5	preservation	preservation	NOUN
cana-4791	192	6	score	score	NOUN
cana-4791	192	7	of	of	ADP
cana-4791	192	8	84.7	84.7	NUM
cana-4791	192	9	,	,	PUNCT
cana-4791	192	10	which	which	PRON
cana-4791	192	11	is	be	AUX
cana-4791	192	12	much	much	ADV
cana-4791	192	13	better	well	ADJ
cana-4791	192	14	than	than	ADP
cana-4791	192	15	jpeg	jpeg	NOUN
cana-4791	192	16	(	(	PUNCT
cana-4791	192	17	62.3	62.3	NUM
cana-4791	192	18	)	)	PUNCT
cana-4791	192	19	and	and	CCONJ
cana-4791	192	20	jpeg2000	jpeg2000	PROPN
cana-4791	192	21	(	(	PUNCT
cana-4791	192	22	69.4	69.4	NUM
cana-4791	192	23	)	)	PUNCT
cana-4791	192	24	.	.	PUNCT
cana-4791	193	1	this	this	PRON
cana-4791	193	2	means	mean	VERB
cana-4791	193	3	that	that	SCONJ
cana-4791	193	4	even	even	ADV
cana-4791	193	5	when	when	SCONJ
cana-4791	193	6	compressed	compress	VERB
cana-4791	193	7	,	,	PUNCT
cana-4791	193	8	it	it	PRON
cana-4791	193	9	can	can	AUX
cana-4791	193	10	keep	keep	VERB
cana-4791	193	11	lines	line	NOUN
cana-4791	193	12	that	that	PRON
cana-4791	193	13	are	be	AUX
cana-4791	193	14	sharp	sharp	ADJ
cana-4791	193	15	and	and	CCONJ
cana-4791	193	16	well	well	ADV
cana-4791	193	17	-	-	PUNCT
cana-4791	193	18	defined	define	VERB
cana-4791	193	19	.	.	PUNCT
cana-4791	194	1	if	if	SCONJ
cana-4791	194	2	you	you	PRON
cana-4791	194	3	want	want	VERB
cana-4791	194	4	to	to	PART
cana-4791	194	5	keep	keep	VERB
cana-4791	194	6	details	detail	NOUN
cana-4791	194	7	in	in	ADP
cana-4791	194	8	high	high	ADJ
cana-4791	194	9	-	-	PUNCT
cana-4791	194	10	frequency	frequency	NOUN
cana-4791	194	11	areas	area	NOUN
cana-4791	194	12	like	like	ADP
cana-4791	194	13	writing	writing	NOUN
cana-4791	194	14	,	,	PUNCT
cana-4791	194	15	face	face	NOUN
cana-4791	194	16	features	feature	NOUN
cana-4791	194	17	,	,	PUNCT
cana-4791	194	18	or	or	CCONJ
cana-4791	194	19	building	building	NOUN
cana-4791	194	20	lines	line	NOUN
cana-4791	194	21	,	,	PUNCT
cana-4791	194	22	this	this	PRON
cana-4791	194	23	is	be	AUX
cana-4791	194	24	especially	especially	ADV
cana-4791	194	25	important	important	ADJ
cana-4791	194	26	.	.	PUNCT
cana-4791	195	1	communications	communication	NOUN
cana-4791	195	2	on	on	ADP
cana-4791	195	3	applied	apply	VERB
cana-4791	195	4	nonlinear	nonlinear	ADJ
cana-4791	195	5	analysis	analysis	NOUN
cana-4791	195	6	issn	issn	NOUN
cana-4791	195	7	:	:	PUNCT
cana-4791	195	8	1074	1074	NUM
cana-4791	195	9	-	-	PUNCT
cana-4791	195	10	133x	133x	NUM
cana-4791	195	11	vol	vol	NOUN
cana-4791	195	12	31	31	NUM
cana-4791	195	13	no	no	NOUN
cana-4791	195	14	.	.	PUNCT
cana-4791	196	1	1s	1s	NUM
cana-4791	196	2	(	(	PUNCT
cana-4791	196	3	2024	2024	NUM
cana-4791	196	4	)	)	PUNCT
cana-4791	196	5	225	225	NUM
cana-4791	196	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	196	7	figure	figure	NOUN
cana-4791	196	8	4	4	NUM
cana-4791	196	9	:	:	PUNCT
cana-4791	196	10	qualitative	qualitative	ADJ
cana-4791	196	11	comparison	comparison	NOUN
cana-4791	196	12	of	of	ADP
cana-4791	196	13	image	image	NOUN
cana-4791	196	14	compression	compression	NOUN
cana-4791	196	15	models	model	NOUN
cana-4791	196	16	in	in	ADP
cana-4791	196	17	the	the	DET
cana-4791	196	18	same	same	ADJ
cana-4791	196	19	way	way	NOUN
cana-4791	196	20	,	,	PUNCT
cana-4791	196	21	compressgan	compressgan	PROPN
cana-4791	196	22	does	do	VERB
cana-4791	196	23	a	a	DET
cana-4791	196	24	great	great	ADJ
cana-4791	196	25	job	job	NOUN
cana-4791	196	26	with	with	ADP
cana-4791	196	27	colour	colour	NOUN
cana-4791	196	28	accuracy	accuracy	NOUN
cana-4791	196	29	,	,	PUNCT
cana-4791	196	30	scoring	score	VERB
cana-4791	196	31	89.6	89.6	NUM
cana-4791	196	32	%	%	NOUN
cana-4791	196	33	,	,	PUNCT
cana-4791	196	34	which	which	PRON
cana-4791	196	35	means	mean	VERB
cana-4791	196	36	it	it	PRON
cana-4791	196	37	comes	come	VERB
cana-4791	196	38	very	very	ADV
cana-4791	196	39	close	close	ADV
cana-4791	196	40	to	to	ADP
cana-4791	196	41	the	the	DET
cana-4791	196	42	original	original	ADJ
cana-4791	196	43	colours	colour	NOUN
cana-4791	196	44	.	.	PUNCT
cana-4791	197	1	traditional	traditional	ADJ
cana-4791	197	2	ways	way	NOUN
cana-4791	197	3	,	,	PUNCT
cana-4791	197	4	like	like	ADP
cana-4791	197	5	jpeg	jpeg	NOUN
cana-4791	197	6	and	and	CCONJ
cana-4791	197	7	jpeg2000	jpeg2000	PROPN
cana-4791	197	8	,	,	PUNCT
cana-4791	197	9	give	give	VERB
cana-4791	197	10	much	much	ADV
cana-4791	197	11	lower	low	ADJ
cana-4791	197	12	scores	score	NOUN
cana-4791	197	13	(	(	PUNCT
cana-4791	197	14	71.8	71.8	NUM
cana-4791	197	15	%	%	NOUN
cana-4791	197	16	and	and	CCONJ
cana-4791	197	17	76.0	76.0	NUM
cana-4791	197	18	%	%	NOUN
cana-4791	197	19	,	,	PUNCT
cana-4791	197	20	respectively	respectively	ADV
cana-4791	197	21	)	)	PUNCT
cana-4791	197	22	,	,	PUNCT
cana-4791	197	23	and	and	CCONJ
cana-4791	197	24	they	they	PRON
cana-4791	197	25	often	often	ADV
cana-4791	197	26	add	add	VERB
cana-4791	197	27	hue	hue	ADJ
cana-4791	197	28	changes	change	NOUN
cana-4791	197	29	or	or	CCONJ
cana-4791	197	30	colour	colour	NOUN
cana-4791	197	31	banding	banding	NOUN
cana-4791	197	32	.	.	PUNCT
cana-4791	198	1	table	table	NOUN
cana-4791	198	2	3	3	NUM
cana-4791	198	3	:	:	PUNCT
cana-4791	198	4	qualitative	qualitative	ADJ
cana-4791	198	5	analysis	analysis	NOUN
cana-4791	198	6	model	model	NOUN
cana-4791	198	7	edge	edge	NOUN
cana-4791	198	8	preservation	preservation	NOUN
cana-4791	198	9	score	score	NOUN
cana-4791	198	10	color	color	NOUN
cana-4791	198	11	accuracy	accuracy	NOUN
cana-4791	198	12	(	(	PUNCT
cana-4791	198	13	%	%	INTJ
cana-4791	198	14	)	)	PUNCT
cana-4791	198	15	texture	texture	ADJ
cana-4791	198	16	realism	realism	NOUN
cana-4791	198	17	(	(	PUNCT
cana-4791	198	18	1	1	NUM
cana-4791	198	19	-	-	SYM
cana-4791	198	20	100	100	NUM
cana-4791	198	21	)	)	PUNCT
cana-4791	198	22	jpeg	jpeg	NOUN
cana-4791	198	23	62.3	62.3	NUM
cana-4791	198	24	71.8	71.8	NUM
cana-4791	198	25	58	58	NUM
cana-4791	198	26	jpeg2000	jpeg2000	PROPN
cana-4791	198	27	69.4	69.4	NUM
cana-4791	198	28	76.0	76.0	NUM
cana-4791	198	29	65	65	NUM
cana-4791	198	30	autoencoder	autoencoder	NOUN
cana-4791	198	31	75.1	75.1	NUM
cana-4791	198	32	82.5	82.5	NUM
cana-4791	198	33	72	72	NUM
cana-4791	198	34	compressgan	compressgan	VERB
cana-4791	198	35	84.7	84.7	NUM
cana-4791	198	36	89.6	89.6	NUM
cana-4791	198	37	91	91	NUM
cana-4791	198	38	the	the	DET
cana-4791	198	39	best	good	ADJ
cana-4791	198	40	thing	thing	NOUN
cana-4791	198	41	about	about	ADP
cana-4791	198	42	compressgan	compressgan	PROPN
cana-4791	198	43	is	be	AUX
cana-4791	198	44	that	that	SCONJ
cana-4791	198	45	it	it	PRON
cana-4791	198	46	gets	get	VERB
cana-4791	198	47	a	a	DET
cana-4791	198	48	texture	texture	ADJ
cana-4791	198	49	realism	realism	NOUN
cana-4791	198	50	score	score	NOUN
cana-4791	198	51	of	of	ADP
cana-4791	198	52	91	91	NUM
cana-4791	198	53	out	out	ADP
cana-4791	198	54	of	of	ADP
cana-4791	198	55	100	100	NUM
cana-4791	198	56	,	,	PUNCT
cana-4791	198	57	which	which	PRON
cana-4791	198	58	shows	show	VERB
cana-4791	198	59	in	in	ADP
cana-4791	198	60	figure	figure	NOUN
cana-4791	198	61	3	3	NUM
cana-4791	198	62	that	that	SCONJ
cana-4791	198	63	it	it	PRON
cana-4791	198	64	can	can	AUX
cana-4791	198	65	accurately	accurately	ADV
cana-4791	198	66	recreate	recreate	VERB
cana-4791	198	67	complex	complex	ADJ
cana-4791	198	68	textures	texture	NOUN
cana-4791	198	69	like	like	ADP
cana-4791	198	70	skin	skin	NOUN
cana-4791	198	71	tones	tone	NOUN
cana-4791	198	72	,	,	PUNCT
cana-4791	198	73	grass	grass	NOUN
cana-4791	198	74	,	,	PUNCT
cana-4791	198	75	and	and	CCONJ
cana-4791	198	76	fabrics	fabric	NOUN
cana-4791	198	77	.	.	PUNCT
cana-4791	199	1	the	the	DET
cana-4791	199	2	antagonistic	antagonistic	ADJ
cana-4791	199	3	and	and	CCONJ
cana-4791	199	4	perception	perception	NOUN
cana-4791	199	5	loss	loss	NOUN
cana-4791	199	6	components	component	NOUN
cana-4791	199	7	give	give	VERB
cana-4791	199	8	compressgan	compressgan	VERB
cana-4791	199	9	better	well	ADJ
cana-4791	199	10	texture	texture	NOUN
cana-4791	199	11	handling	handling	NOUN
cana-4791	199	12	compared	compare	VERB
cana-4791	199	13	to	to	ADP
cana-4791	199	14	jpeg	jpeg	PROPN
cana-4791	199	15	's	's	PART
cana-4791	199	16	58	58	NUM
cana-4791	199	17	or	or	CCONJ
cana-4791	199	18	even	even	ADV
cana-4791	199	19	the	the	DET
cana-4791	199	20	autoencoder	autoencoder	NOUN
cana-4791	199	21	's	's	PART
cana-4791	199	22	72	72	NUM
cana-4791	199	23	.	.	PUNCT
cana-4791	200	1	this	this	PRON
cana-4791	200	2	makes	make	VERB
cana-4791	200	3	it	it	PRON
cana-4791	200	4	better	well	ADJ
cana-4791	200	5	for	for	ADP
cana-4791	200	6	real	real	ADJ
cana-4791	200	7	-	-	PUNCT
cana-4791	200	8	world	world	NOUN
cana-4791	200	9	watching	watch	VERB
cana-4791	200	10	apps	app	NOUN
cana-4791	200	11	.	.	PUNCT
cana-4791	200	12	table	table	NOUN
cana-4791	200	13	4	4	NUM
cana-4791	200	14	:	:	PUNCT
cana-4791	200	15	low	low	ADJ
cana-4791	200	16	bitrate	bitrate	NOUN
cana-4791	200	17	evaluation	evaluation	NOUN
cana-4791	200	18	table	table	NOUN
cana-4791	200	19	model	model	NOUN
cana-4791	200	20	bitrate	bitrate	NOUN
cana-4791	200	21	(	(	PUNCT
cana-4791	200	22	bpp	bpp	NOUN
cana-4791	200	23	)	)	PUNCT
cana-4791	200	24	psnr	psnr	NOUN
cana-4791	200	25	(	(	PUNCT
cana-4791	200	26	db	db	NOUN
cana-4791	200	27	)	)	PUNCT
cana-4791	200	28	ssim	ssim	NOUN
cana-4791	200	29	jpeg	jpeg	NOUN
cana-4791	200	30	0.25	0.25	NUM
cana-4791	200	31	25.3	25.3	NUM
cana-4791	200	32	0.751	0.751	NUM
cana-4791	200	33	jpeg2000	jpeg2000	PROPN
cana-4791	200	34	0.25	0.25	NUM
cana-4791	200	35	27.1	27.1	NUM
cana-4791	200	36	0.804	0.804	NUM
cana-4791	200	37	bpg	bpg	VERB
cana-4791	200	38	0.25	0.25	NUM
cana-4791	200	39	28.6	28.6	NUM
cana-4791	200	40	0.826	0.826	NUM
cana-4791	200	41	communications	communication	NOUN
cana-4791	200	42	on	on	ADP
cana-4791	200	43	applied	apply	VERB
cana-4791	200	44	nonlinear	nonlinear	ADJ
cana-4791	200	45	analysis	analysis	NOUN
cana-4791	200	46	issn	issn	NOUN
cana-4791	200	47	:	:	PUNCT
cana-4791	200	48	1074	1074	NUM
cana-4791	200	49	-	-	PUNCT
cana-4791	200	50	133x	133x	NUM
cana-4791	200	51	vol	vol	NOUN
cana-4791	200	52	31	31	NUM
cana-4791	200	53	no	no	NOUN
cana-4791	200	54	.	.	PUNCT
cana-4791	201	1	1s	1s	NUM
cana-4791	201	2	(	(	PUNCT
cana-4791	201	3	2024	2024	NUM
cana-4791	201	4	)	)	PUNCT
cana-4791	201	5	226	226	NUM
cana-4791	201	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	201	7	compressgan	compressgan	VERB
cana-4791	201	8	0.25	0.25	NUM
cana-4791	201	9	30.9	30.9	NUM
cana-4791	201	10	0.883	0.883	NUM
cana-4791	201	11	table	table	NOUN
cana-4791	201	12	4	4	NUM
cana-4791	201	13	shows	show	VERB
cana-4791	201	14	how	how	SCONJ
cana-4791	201	15	well	well	ADV
cana-4791	201	16	different	different	ADJ
cana-4791	201	17	image	image	NOUN
cana-4791	201	18	compression	compression	NOUN
cana-4791	201	19	models	model	NOUN
cana-4791	201	20	work	work	VERB
cana-4791	201	21	at	at	ADP
cana-4791	201	22	a	a	DET
cana-4791	201	23	set	set	ADJ
cana-4791	201	24	low	low	ADJ
cana-4791	201	25	bitrate	bitrate	NOUN
cana-4791	201	26	of	of	ADP
cana-4791	201	27	0.25	0.25	NUM
cana-4791	201	28	bits	bit	NOUN
cana-4791	201	29	per	per	ADP
cana-4791	201	30	pixel	pixel	NOUN
cana-4791	201	31	(	(	PUNCT
cana-4791	201	32	bpp	bpp	NOUN
cana-4791	201	33	)	)	PUNCT
cana-4791	201	34	,	,	PUNCT
cana-4791	201	35	showing	show	VERB
cana-4791	201	36	how	how	SCONJ
cana-4791	201	37	well	well	ADV
cana-4791	201	38	they	they	PRON
cana-4791	201	39	can	can	AUX
cana-4791	201	40	keep	keep	VERB
cana-4791	201	41	quality	quality	NOUN
cana-4791	201	42	even	even	ADV
cana-4791	201	43	when	when	SCONJ
cana-4791	201	44	compression	compression	NOUN
cana-4791	201	45	limits	limit	NOUN
cana-4791	201	46	are	be	AUX
cana-4791	201	47	tight	tight	ADJ
cana-4791	201	48	.	.	PUNCT
cana-4791	202	1	with	with	ADP
cana-4791	202	2	psnr	psnr	NOUN
cana-4791	202	3	values	value	NOUN
cana-4791	202	4	of	of	ADP
cana-4791	202	5	25.3	25.3	NUM
cana-4791	202	6	db	db	NOUN
cana-4791	202	7	and	and	CCONJ
cana-4791	202	8	27.1	27.1	NUM
cana-4791	202	9	db	db	PROPN
cana-4791	202	10	,	,	PUNCT
cana-4791	202	11	respectively	respectively	ADV
cana-4791	202	12	,	,	PUNCT
cana-4791	202	13	standard	standard	ADJ
cana-4791	202	14	codecs	codec	NOUN
cana-4791	202	15	like	like	ADP
cana-4791	202	16	jpeg	jpeg	NOUN
cana-4791	202	17	and	and	CCONJ
cana-4791	202	18	jpeg2000	jpeg2000	PROPN
cana-4791	202	19	lose	lose	VERB
cana-4791	202	20	a	a	DET
cana-4791	202	21	lot	lot	NOUN
cana-4791	202	22	of	of	ADP
cana-4791	202	23	quality	quality	NOUN
cana-4791	202	24	at	at	ADP
cana-4791	202	25	this	this	DET
cana-4791	202	26	speed	speed	NOUN
cana-4791	202	27	.	.	PUNCT
cana-4791	203	1	their	their	PRON
cana-4791	203	2	ssim	ssim	NOUN
cana-4791	203	3	scores	score	NOUN
cana-4791	203	4	also	also	ADV
cana-4791	203	5	show	show	VERB
cana-4791	203	6	that	that	SCONJ
cana-4791	203	7	they	they	PRON
cana-4791	203	8	have	have	AUX
cana-4791	203	9	lost	lose	VERB
cana-4791	203	10	structure	structure	NOUN
cana-4791	203	11	,	,	PUNCT
cana-4791	203	12	especially	especially	ADV
cana-4791	203	13	when	when	SCONJ
cana-4791	203	14	comparing	compare	VERB
cana-4791	203	15	jpeg	jpeg	NOUN
cana-4791	203	16	(	(	PUNCT
cana-4791	203	17	0.751	0.751	NUM
cana-4791	203	18	)	)	PUNCT
cana-4791	203	19	to	to	ADP
cana-4791	203	20	jpeg2000	jpeg2000	PROPN
cana-4791	203	21	(	(	PUNCT
cana-4791	203	22	0.804	0.804	NUM
cana-4791	203	23	)	)	PUNCT
cana-4791	203	24	.	.	PUNCT
cana-4791	204	1	since	since	SCONJ
cana-4791	204	2	bpg	bpg	PROPN
cana-4791	204	3	is	be	AUX
cana-4791	204	4	a	a	DET
cana-4791	204	5	more	more	ADV
cana-4791	204	6	modern	modern	ADJ
cana-4791	204	7	codec	codec	NOUN
cana-4791	204	8	,	,	PUNCT
cana-4791	204	9	it	it	PRON
cana-4791	204	10	works	work	VERB
cana-4791	204	11	better	well	ADV
cana-4791	204	12	with	with	ADP
cana-4791	204	13	28.6	28.6	NUM
cana-4791	204	14	db	db	PROPN
cana-4791	204	15	psnr	psnr	NOUN
cana-4791	204	16	and	and	CCONJ
cana-4791	204	17	0.826	0.826	NUM
cana-4791	204	18	ssim	ssim	NOUN
cana-4791	204	19	,	,	PUNCT
cana-4791	204	20	showing	show	VERB
cana-4791	204	21	that	that	SCONJ
cana-4791	204	22	it	it	PRON
cana-4791	204	23	compresses	compress	VERB
cana-4791	204	24	data	datum	NOUN
cana-4791	204	25	more	more	ADV
cana-4791	204	26	efficiently	efficiently	ADV
cana-4791	204	27	,	,	PUNCT
cana-4791	204	28	as	as	SCONJ
cana-4791	204	29	shown	show	VERB
cana-4791	204	30	in	in	ADP
cana-4791	204	31	figure	figure	NOUN
cana-4791	204	32	5	5	NUM
cana-4791	204	33	.	.	PUNCT
cana-4791	204	34	figure	figure	VERB
cana-4791	204	35	5	5	NUM
cana-4791	204	36	:	:	PUNCT
cana-4791	204	37	low	low	ADJ
cana-4791	204	38	bitrate	bitrate	NOUN
cana-4791	204	39	performance	performance	NOUN
cana-4791	204	40	comparison	comparison	NOUN
cana-4791	204	41	but	but	CCONJ
cana-4791	204	42	compressgan	compressgan	PROPN
cana-4791	204	43	does	do	VERB
cana-4791	204	44	the	the	DET
cana-4791	204	45	best	good	ADJ
cana-4791	204	46	.	.	PUNCT
cana-4791	205	1	it	it	PRON
cana-4791	205	2	got	get	VERB
cana-4791	205	3	a	a	DET
cana-4791	205	4	psnr	psnr	NOUN
cana-4791	205	5	of	of	ADP
cana-4791	205	6	30.9	30.9	NUM
cana-4791	205	7	db	db	NOUN
cana-4791	205	8	and	and	CCONJ
cana-4791	205	9	an	an	DET
cana-4791	205	10	ssim	ssim	NOUN
cana-4791	205	11	of	of	ADP
cana-4791	205	12	0.883	0.883	NUM
cana-4791	205	13	,	,	PUNCT
cana-4791	205	14	showing	show	VERB
cana-4791	205	15	that	that	SCONJ
cana-4791	205	16	it	it	PRON
cana-4791	205	17	can	can	AUX
cana-4791	205	18	keep	keep	VERB
cana-4791	205	19	both	both	DET
cana-4791	205	20	quality	quality	NOUN
cana-4791	205	21	and	and	CCONJ
cana-4791	205	22	structure	structure	NOUN
cana-4791	205	23	even	even	ADV
cana-4791	205	24	at	at	ADP
cana-4791	205	25	low	low	ADJ
cana-4791	205	26	bitrates	bitrate	NOUN
cana-4791	205	27	.	.	PUNCT
cana-4791	206	1	this	this	PRON
cana-4791	206	2	shows	show	VERB
cana-4791	206	3	how	how	SCONJ
cana-4791	206	4	good	good	ADJ
cana-4791	206	5	compressgan	compressgan	NOUN
cana-4791	206	6	is	be	AUX
cana-4791	206	7	at	at	ADP
cana-4791	206	8	matching	match	VERB
cana-4791	206	9	high	high	ADJ
cana-4791	206	10	graphic	graphic	ADJ
cana-4791	206	11	clarity	clarity	NOUN
cana-4791	206	12	with	with	ADP
cana-4791	206	13	efficient	efficient	ADJ
cana-4791	206	14	compression	compression	NOUN
cana-4791	206	15	,	,	PUNCT
cana-4791	206	16	which	which	PRON
cana-4791	206	17	makes	make	VERB
cana-4791	206	18	it	it	PRON
cana-4791	206	19	perfect	perfect	ADJ
cana-4791	206	20	for	for	ADP
cana-4791	206	21	apps	app	NOUN
cana-4791	206	22	with	with	ADP
cana-4791	206	23	limited	limited	ADJ
cana-4791	206	24	bandwidth	bandwidth	NOUN
cana-4791	206	25	.	.	PUNCT
cana-4791	206	26	table	table	NOUN
cana-4791	206	27	5	5	NUM
cana-4791	206	28	:	:	PUNCT
cana-4791	206	29	cross	cross	ADJ
cana-4791	206	30	-	-	ADJ
cana-4791	206	31	dataset	dataset	ADJ
cana-4791	206	32	performance	performance	NOUN
cana-4791	206	33	table	table	NOUN
cana-4791	206	34	dataset	dataset	VERB
cana-4791	206	35	compressgan	compressgan	PROPN
cana-4791	206	36	psnr	psnr	NOUN
cana-4791	206	37	(	(	PUNCT
cana-4791	206	38	db	db	PROPN
cana-4791	206	39	)	)	PUNCT
cana-4791	206	40	compressgan	compressgan	PROPN
cana-4791	206	41	ssim	ssim	NOUN
cana-4791	206	42	compressgan	compressgan	VERB
cana-4791	206	43	lpips	lpip	NOUN
cana-4791	206	44	(	(	PUNCT
cana-4791	206	45	↓	↓	NOUN
cana-4791	206	46	)	)	PUNCT
cana-4791	206	47	kodak	kodak	PROPN
cana-4791	206	48	36.7	36.7	NUM
cana-4791	206	49	0.942	0.942	NUM
cana-4791	206	50	0.128	0.128	NUM
cana-4791	206	51	clic	clic	NOUN
cana-4791	206	52	35.8	35.8	NUM
cana-4791	206	53	0.935	0.935	NUM
cana-4791	206	54	0.132	0.132	NUM
cana-4791	206	55	div2k	div2k	PROPN
cana-4791	206	56	37.3	37.3	NUM
cana-4791	206	57	0.948	0.948	NUM
cana-4791	206	58	0.119	0.119	NUM
cana-4791	206	59	urban100	urban100	PROPN
cana-4791	206	60	34.9	34.9	NUM
cana-4791	206	61	0.927	0.927	NUM
cana-4791	206	62	0.14	0.14	NUM
cana-4791	206	63	table	table	NOUN
cana-4791	206	64	5	5	NUM
cana-4791	206	65	shows	show	VERB
cana-4791	206	66	that	that	PRON
cana-4791	206	67	compressgan	compressgan	PROPN
cana-4791	206	68	can	can	AUX
cana-4791	206	69	generalise	generalise	VERB
cana-4791	206	70	across	across	ADP
cana-4791	206	71	a	a	DET
cana-4791	206	72	number	number	NOUN
cana-4791	206	73	of	of	ADP
cana-4791	206	74	different	different	ADJ
cana-4791	206	75	standard	standard	ADJ
cana-4791	206	76	datasets	dataset	NOUN
cana-4791	206	77	,	,	PUNCT
cana-4791	206	78	such	such	ADJ
cana-4791	206	79	as	as	ADP
cana-4791	206	80	kodak	kodak	PROPN
cana-4791	206	81	,	,	PUNCT
cana-4791	206	82	clic	clic	PROPN
cana-4791	206	83	,	,	PUNCT
cana-4791	206	84	div2k	div2k	PROPN
cana-4791	206	85	,	,	PUNCT
cana-4791	206	86	and	and	CCONJ
cana-4791	206	87	urban100	urban100	PROPN
cana-4791	206	88	.	.	PUNCT
cana-4791	207	1	the	the	DET
cana-4791	207	2	results	result	NOUN
cana-4791	207	3	show	show	VERB
cana-4791	207	4	that	that	SCONJ
cana-4791	207	5	the	the	DET
cana-4791	207	6	model	model	NOUN
cana-4791	207	7	is	be	AUX
cana-4791	207	8	strong	strong	ADJ
cana-4791	207	9	and	and	CCONJ
cana-4791	207	10	can	can	AUX
cana-4791	207	11	work	work	VERB
cana-4791	207	12	with	with	ADP
cana-4791	207	13	a	a	DET
cana-4791	207	14	wide	wide	ADJ
cana-4791	207	15	range	range	NOUN
cana-4791	207	16	of	of	ADP
cana-4791	207	17	picture	picture	NOUN
cana-4791	207	18	domains	domain	NOUN
cana-4791	207	19	that	that	PRON
cana-4791	207	20	have	have	VERB
cana-4791	207	21	different	different	ADJ
cana-4791	207	22	patterns	pattern	NOUN
cana-4791	207	23	,	,	PUNCT
cana-4791	207	24	sizes	size	NOUN
cana-4791	207	25	,	,	PUNCT
cana-4791	207	26	and	and	CCONJ
cana-4791	207	27	levels	level	NOUN
cana-4791	207	28	of	of	ADP
cana-4791	207	29	complexity	complexity	NOUN
cana-4791	207	30	.	.	PUNCT
cana-4791	208	1	the	the	DET
cana-4791	208	2	fact	fact	NOUN
cana-4791	208	3	that	that	SCONJ
cana-4791	208	4	compressgan	compressgan	PROPN
cana-4791	208	5	always	always	ADV
cana-4791	208	6	has	have	AUX
cana-4791	208	7	high	high	ADJ
cana-4791	208	8	scores	score	NOUN
cana-4791	208	9	for	for	ADP
cana-4791	208	10	psnr	psnr	NOUN
cana-4791	208	11	,	,	PUNCT
cana-4791	208	12	ssim	ssim	NOUN
cana-4791	208	13	,	,	PUNCT
cana-4791	208	14	and	and	CCONJ
cana-4791	208	15	lpips	lpip	NOUN
cana-4791	208	16	shows	show	VERB
cana-4791	208	17	that	that	SCONJ
cana-4791	208	18	the	the	DET
cana-4791	208	19	model	model	NOUN
cana-4791	208	20	works	work	VERB
cana-4791	208	21	well	well	ADV
cana-4791	208	22	with	with	ADP
cana-4791	208	23	a	a	DET
cana-4791	208	24	lot	lot	NOUN
cana-4791	208	25	of	of	ADP
cana-4791	208	26	different	different	ADJ
cana-4791	208	27	datasets	dataset	NOUN
cana-4791	208	28	.	.	PUNCT
cana-4791	209	1	communications	communication	NOUN
cana-4791	209	2	on	on	ADP
cana-4791	209	3	applied	apply	VERB
cana-4791	209	4	nonlinear	nonlinear	ADJ
cana-4791	209	5	analysis	analysis	NOUN
cana-4791	209	6	issn	issn	NOUN
cana-4791	209	7	:	:	PUNCT
cana-4791	209	8	1074	1074	NUM
cana-4791	209	9	-	-	PUNCT
cana-4791	209	10	133x	133x	NUM
cana-4791	209	11	vol	vol	NOUN
cana-4791	209	12	31	31	NUM
cana-4791	209	13	no	no	NOUN
cana-4791	209	14	.	.	PUNCT
cana-4791	210	1	1s	1s	NUM
cana-4791	210	2	(	(	PUNCT
cana-4791	210	3	2024	2024	NUM
cana-4791	210	4	)	)	PUNCT
cana-4791	210	5	227	227	NUM
cana-4791	210	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	210	7	compressgan	compressgan	PROPN
cana-4791	210	8	does	do	VERB
cana-4791	210	9	its	its	PRON
cana-4791	210	10	best	good	ADJ
cana-4791	210	11	on	on	ADP
cana-4791	210	12	the	the	DET
cana-4791	210	13	div2k	div2k	PROPN
cana-4791	210	14	dataset	dataset	NOUN
cana-4791	210	15	,	,	PUNCT
cana-4791	210	16	which	which	PRON
cana-4791	210	17	has	have	VERB
cana-4791	210	18	a	a	DET
cana-4791	210	19	lot	lot	NOUN
cana-4791	210	20	of	of	ADP
cana-4791	210	21	different	different	ADJ
cana-4791	210	22	high	high	ADJ
cana-4791	210	23	-	-	PUNCT
cana-4791	210	24	resolution	resolution	NOUN
cana-4791	210	25	natural	natural	ADJ
cana-4791	210	26	pictures	picture	NOUN
cana-4791	210	27	.	.	PUNCT
cana-4791	211	1	it	it	PRON
cana-4791	211	2	gets	get	VERB
cana-4791	211	3	a	a	DET
cana-4791	211	4	psnr	psnr	NOUN
cana-4791	211	5	of	of	ADP
cana-4791	211	6	37.3	37.3	NUM
cana-4791	211	7	db	db	NOUN
cana-4791	211	8	,	,	PUNCT
cana-4791	211	9	an	an	DET
cana-4791	211	10	ssim	ssim	NOUN
cana-4791	211	11	of	of	ADP
cana-4791	211	12	0.948	0.948	NUM
cana-4791	211	13	,	,	PUNCT
cana-4791	211	14	and	and	CCONJ
cana-4791	211	15	a	a	DET
cana-4791	211	16	low	low	ADJ
cana-4791	211	17	lpips	lpip	NOUN
cana-4791	211	18	of	of	ADP
cana-4791	211	19	0.119	0.119	NUM
cana-4791	211	20	,	,	PUNCT
cana-4791	211	21	which	which	PRON
cana-4791	211	22	means	mean	VERB
cana-4791	211	23	it	it	PRON
cana-4791	211	24	has	have	VERB
cana-4791	211	25	great	great	ADJ
cana-4791	211	26	accuracy	accuracy	NOUN
cana-4791	211	27	and	and	CCONJ
cana-4791	211	28	visual	visual	ADJ
cana-4791	211	29	quality	quality	NOUN
cana-4791	211	30	.	.	PUNCT
cana-4791	212	1	figure	figure	NOUN
cana-4791	212	2	6	6	NUM
cana-4791	212	3	:	:	PUNCT
cana-4791	212	4	compressgan	compressgan	VERB
cana-4791	212	5	cross	cross	ADJ
cana-4791	212	6	-	-	ADJ
cana-4791	212	7	dataset	dataset	ADJ
cana-4791	212	8	performance	performance	NOUN
cana-4791	212	9	the	the	DET
cana-4791	212	10	model	model	NOUN
cana-4791	212	11	almost	almost	ADV
cana-4791	212	12	does	do	VERB
cana-4791	212	13	as	as	ADV
cana-4791	212	14	well	well	ADV
cana-4791	212	15	on	on	ADP
cana-4791	212	16	the	the	DET
cana-4791	212	17	kodak	kodak	PROPN
cana-4791	212	18	dataset	dataset	PROPN
cana-4791	212	19	,	,	PUNCT
cana-4791	212	20	which	which	PRON
cana-4791	212	21	is	be	AUX
cana-4791	212	22	a	a	DET
cana-4791	212	23	common	common	ADJ
cana-4791	212	24	way	way	NOUN
cana-4791	212	25	to	to	PART
cana-4791	212	26	test	test	VERB
cana-4791	212	27	how	how	SCONJ
cana-4791	212	28	well	well	ADV
cana-4791	212	29	image	image	NOUN
cana-4791	212	30	compression	compression	NOUN
cana-4791	212	31	works	work	VERB
cana-4791	212	32	.	.	PUNCT
cana-4791	213	1	it	it	PRON
cana-4791	213	2	gets	get	VERB
cana-4791	213	3	36.7	36.7	NUM
cana-4791	213	4	db	db	PROPN
cana-4791	213	5	psnr	psnr	NOUN
cana-4791	213	6	and	and	CCONJ
cana-4791	213	7	0.942	0.942	NUM
cana-4791	213	8	ssim	ssim	NOUN
cana-4791	213	9	,	,	PUNCT
cana-4791	213	10	which	which	PRON
cana-4791	213	11	means	mean	VERB
cana-4791	213	12	it	it	PRON
cana-4791	213	13	can	can	AUX
cana-4791	213	14	reliably	reliably	ADV
cana-4791	213	15	recreate	recreate	VERB
cana-4791	213	16	images	image	NOUN
cana-4791	213	17	and	and	CCONJ
cana-4791	213	18	keep	keep	VERB
cana-4791	213	19	their	their	PRON
cana-4791	213	20	structure	structure	NOUN
cana-4791	213	21	.	.	PUNCT
cana-4791	214	1	compressgan	compressgan	PROPN
cana-4791	214	2	gets	get	VERB
cana-4791	214	3	35.8	35.8	NUM
cana-4791	214	4	db	db	NOUN
cana-4791	214	5	psnr	psnr	NOUN
cana-4791	214	6	and	and	CCONJ
cana-4791	214	7	0.935	0.935	NUM
cana-4791	214	8	ssim	ssim	NOUN
cana-4791	214	9	on	on	ADP
cana-4791	214	10	clic	clic	NOUN
cana-4791	214	11	,	,	PUNCT
cana-4791	214	12	which	which	PRON
cana-4791	214	13	has	have	VERB
cana-4791	214	14	a	a	DET
cana-4791	214	15	lot	lot	NOUN
cana-4791	214	16	of	of	ADP
cana-4791	214	17	different	different	ADJ
cana-4791	214	18	customer	customer	NOUN
cana-4791	214	19	pictures	picture	NOUN
cana-4791	214	20	.	.	PUNCT
cana-4791	215	1	this	this	PRON
cana-4791	215	2	means	mean	VERB
cana-4791	215	3	that	that	SCONJ
cana-4791	215	4	it	it	PRON
cana-4791	215	5	still	still	ADV
cana-4791	215	6	gives	give	VERB
cana-4791	215	7	good	good	ADJ
cana-4791	215	8	results	result	NOUN
cana-4791	215	9	with	with	ADP
cana-4791	215	10	only	only	ADJ
cana-4791	215	11	small	small	ADJ
cana-4791	215	12	drops	drop	NOUN
cana-4791	215	13	caused	cause	VERB
cana-4791	215	14	by	by	ADP
cana-4791	215	15	more	more	ADJ
cana-4791	215	16	complex	complex	ADJ
cana-4791	215	17	variations	variation	NOUN
cana-4791	215	18	.	.	PUNCT
cana-4791	216	1	for	for	ADP
cana-4791	216	2	urban100	urban100	PROPN
cana-4791	216	3	,	,	PUNCT
cana-4791	216	4	which	which	PRON
cana-4791	216	5	has	have	VERB
cana-4791	216	6	city	city	NOUN
cana-4791	216	7	scenes	scene	NOUN
cana-4791	216	8	with	with	ADP
cana-4791	216	9	lots	lot	NOUN
cana-4791	216	10	of	of	ADP
cana-4791	216	11	features	feature	NOUN
cana-4791	216	12	and	and	CCONJ
cana-4791	216	13	repeating	repeat	VERB
cana-4791	216	14	patterns	pattern	NOUN
cana-4791	216	15	,	,	PUNCT
cana-4791	216	16	the	the	DET
cana-4791	216	17	model	model	NOUN
cana-4791	216	18	's	's	PART
cana-4791	216	19	performance	performance	NOUN
cana-4791	216	20	drops	drop	VERB
cana-4791	216	21	a	a	DET
cana-4791	216	22	little	little	ADJ
cana-4791	216	23	(	(	PUNCT
cana-4791	216	24	34.9	34.9	NUM
cana-4791	216	25	db	db	PROPN
cana-4791	216	26	psnr	psnr	NOUN
cana-4791	216	27	,	,	PUNCT
cana-4791	216	28	0.927	0.927	NUM
cana-4791	216	29	ssim	ssim	NOUN
cana-4791	216	30	)	)	PUNCT
cana-4791	216	31	,	,	PUNCT
cana-4791	216	32	but	but	CCONJ
cana-4791	216	33	it	it	PRON
cana-4791	216	34	still	still	ADV
cana-4791	216	35	has	have	VERB
cana-4791	216	36	a	a	DET
cana-4791	216	37	good	good	ADJ
cana-4791	216	38	lpips	lpip	NOUN
cana-4791	216	39	(	(	PUNCT
cana-4791	216	40	0.140	0.140	NUM
cana-4791	216	41	)	)	PUNCT
cana-4791	216	42	.	.	PUNCT
cana-4791	217	1	these	these	DET
cana-4791	217	2	results	result	NOUN
cana-4791	217	3	show	show	VERB
cana-4791	217	4	that	that	SCONJ
cana-4791	217	5	compressgan	compressgan	PROPN
cana-4791	217	6	can	can	AUX
cana-4791	217	7	be	be	AUX
cana-4791	217	8	used	use	VERB
cana-4791	217	9	across	across	ADP
cana-4791	217	10	domains	domain	NOUN
cana-4791	217	11	and	and	CCONJ
cana-4791	217	12	still	still	ADV
cana-4791	217	13	deliver	deliver	VERB
cana-4791	217	14	high	high	ADJ
cana-4791	217	15	-	-	PUNCT
cana-4791	217	16	quality	quality	NOUN
cana-4791	217	17	images	image	NOUN
cana-4791	217	18	.	.	PUNCT
cana-4791	218	1	6	6	X
cana-4791	218	2	.	.	X
cana-4791	218	3	conclusion	conclusion	NOUN
cana-4791	218	4	compressgan	compressgan	PROPN
cana-4791	218	5	is	be	AUX
cana-4791	218	6	a	a	DET
cana-4791	218	7	new	new	ADJ
cana-4791	218	8	generative	generative	ADJ
cana-4791	218	9	adversarial	adversarial	ADJ
cana-4791	218	10	network	network	NOUN
cana-4791	218	11	-	-	PUNCT
cana-4791	218	12	based	base	VERB
cana-4791	218	13	system	system	NOUN
cana-4791	218	14	for	for	ADP
cana-4791	218	15	learnt	learnt	ADJ
cana-4791	218	16	picture	picture	NOUN
cana-4791	218	17	compression	compression	NOUN
cana-4791	218	18	that	that	PRON
cana-4791	218	19	fixes	fix	VERB
cana-4791	218	20	the	the	DET
cana-4791	218	21	problems	problem	NOUN
cana-4791	218	22	with	with	ADP
cana-4791	218	23	both	both	CCONJ
cana-4791	218	24	old	old	ADJ
cana-4791	218	25	and	and	CCONJ
cana-4791	218	26	new	new	ADJ
cana-4791	218	27	compression	compression	NOUN
cana-4791	218	28	models	model	NOUN
cana-4791	218	29	,	,	PUNCT
cana-4791	218	30	especially	especially	ADV
cana-4791	218	31	when	when	SCONJ
cana-4791	218	32	the	the	DET
cana-4791	218	33	bitrate	bitrate	NOUN
cana-4791	218	34	is	be	AUX
cana-4791	218	35	low	low	ADJ
cana-4791	218	36	.	.	PUNCT
cana-4791	219	1	by	by	ADP
cana-4791	219	2	combining	combine	VERB
cana-4791	219	3	an	an	DET
cana-4791	219	4	encoder	encoder	NOUN
cana-4791	219	5	-	-	PUNCT
cana-4791	219	6	decoder	decoder	NOUN
cana-4791	219	7	structure	structure	NOUN
cana-4791	219	8	with	with	ADP
cana-4791	219	9	hostile	hostile	ADJ
cana-4791	219	10	training	training	NOUN
cana-4791	219	11	and	and	CCONJ
cana-4791	219	12	visual	visual	ADJ
cana-4791	219	13	loss	loss	NOUN
cana-4791	219	14	instruction	instruction	NOUN
cana-4791	219	15	,	,	PUNCT
cana-4791	219	16	compressgan	compressgan	PROPN
cana-4791	219	17	can	can	AUX
cana-4791	219	18	make	make	VERB
cana-4791	219	19	reconstructions	reconstruction	NOUN
cana-4791	219	20	that	that	PRON
cana-4791	219	21	are	be	AUX
cana-4791	219	22	true	true	ADJ
cana-4791	219	23	to	to	ADP
cana-4791	219	24	the	the	DET
cana-4791	219	25	original	original	ADJ
cana-4791	219	26	structure	structure	NOUN
cana-4791	219	27	and	and	CCONJ
cana-4791	219	28	to	to	ADP
cana-4791	219	29	the	the	DET
cana-4791	219	30	user	user	NOUN
cana-4791	219	31	's	's	PART
cana-4791	219	32	experience	experience	NOUN
cana-4791	219	33	.	.	PUNCT
cana-4791	220	1	to	to	PART
cana-4791	220	2	help	help	VERB
cana-4791	220	3	with	with	ADP
cana-4791	220	4	training	training	NOUN
cana-4791	220	5	,	,	PUNCT
cana-4791	220	6	the	the	DET
cana-4791	220	7	system	system	NOUN
cana-4791	220	8	uses	use	VERB
cana-4791	220	9	a	a	DET
cana-4791	220	10	mix	mix	NOUN
cana-4791	220	11	of	of	ADP
cana-4791	220	12	multi	multi	ADJ
cana-4791	220	13	-	-	ADJ
cana-4791	220	14	objective	objective	ADJ
cana-4791	220	15	loss	loss	NOUN
cana-4791	220	16	functions	function	NOUN
cana-4791	220	17	,	,	PUNCT
cana-4791	220	18	including	include	VERB
cana-4791	220	19	pixel	pixel	ADJ
cana-4791	220	20	-	-	ADJ
cana-4791	220	21	wise	wise	ADJ
cana-4791	220	22	reconstruction	reconstruction	NOUN
cana-4791	220	23	loss	loss	NOUN
cana-4791	220	24	,	,	PUNCT
cana-4791	220	25	deep	deep	ADJ
cana-4791	220	26	feature	feature	NOUN
cana-4791	220	27	-	-	PUNCT
cana-4791	220	28	based	base	VERB
cana-4791	220	29	visual	visual	ADJ
cana-4791	220	30	loss	loss	NOUN
cana-4791	220	31	from	from	ADP
cana-4791	220	32	vgg12	vgg12	PROPN
cana-4791	220	33	,	,	PUNCT
cana-4791	220	34	and	and	CCONJ
cana-4791	220	35	hostile	hostile	ADJ
cana-4791	220	36	input	input	NOUN
cana-4791	220	37	from	from	ADP
cana-4791	220	38	a	a	DET
cana-4791	220	39	discriminator	discriminator	NOUN
cana-4791	220	40	network	network	NOUN
cana-4791	220	41	.	.	PUNCT
cana-4791	221	1	many	many	ADJ
cana-4791	221	2	tests	test	NOUN
cana-4791	221	3	showed	show	VERB
cana-4791	221	4	that	that	SCONJ
cana-4791	221	5	compressgan	compressgan	PROPN
cana-4791	221	6	works	work	VERB
cana-4791	221	7	better	well	ADV
cana-4791	221	8	than	than	ADP
cana-4791	221	9	well	well	ADV
cana-4791	221	10	-	-	PUNCT
cana-4791	221	11	known	know	VERB
cana-4791	221	12	codecs	codec	NOUN
cana-4791	221	13	like	like	ADP
cana-4791	221	14	jpeg	jpeg	NOUN
cana-4791	221	15	,	,	PUNCT
cana-4791	221	16	jpeg2000	jpeg2000	PROPN
cana-4791	221	17	,	,	PUNCT
cana-4791	221	18	and	and	CCONJ
cana-4791	221	19	bpg	bpg	PROPN
cana-4791	221	20	,	,	PUNCT
cana-4791	221	21	as	as	ADV
cana-4791	221	22	well	well	ADV
cana-4791	221	23	as	as	ADP
cana-4791	221	24	new	new	ADJ
cana-4791	221	25	deep	deep	ADJ
cana-4791	221	26	learning	learning	NOUN
cana-4791	221	27	models	model	NOUN
cana-4791	221	28	like	like	ADP
cana-4791	221	29	autoencoders	autoencoder	NOUN
cana-4791	221	30	and	and	CCONJ
cana-4791	221	31	vaes	vaes	ADV
cana-4791	221	32	,	,	PUNCT
cana-4791	221	33	using	use	VERB
cana-4791	221	34	a	a	DET
cana-4791	221	35	number	number	NOUN
cana-4791	221	36	of	of	ADP
cana-4791	221	37	common	common	ADJ
cana-4791	221	38	measures	measure	NOUN
cana-4791	221	39	such	such	ADJ
cana-4791	221	40	as	as	ADP
cana-4791	221	41	psnr	psnr	NOUN
cana-4791	221	42	,	,	PUNCT
cana-4791	221	43	ssim	ssim	NOUN
cana-4791	221	44	,	,	PUNCT
cana-4791	221	45	and	and	CCONJ
cana-4791	221	46	lpips	lpip	NOUN
cana-4791	221	47	.	.	PUNCT
cana-4791	222	1	the	the	DET
cana-4791	222	2	model	model	NOUN
cana-4791	222	3	keeps	keep	VERB
cana-4791	222	4	the	the	DET
cana-4791	222	5	quality	quality	NOUN
cana-4791	222	6	of	of	ADP
cana-4791	222	7	the	the	DET
cana-4791	222	8	images	image	NOUN
cana-4791	222	9	even	even	ADV
cana-4791	222	10	when	when	SCONJ
cana-4791	222	11	they	they	PRON
cana-4791	222	12	are	be	AUX
cana-4791	222	13	compressed	compress	VERB
cana-4791	222	14	very	very	ADV
cana-4791	222	15	heavily	heavily	ADV
cana-4791	222	16	,	,	PUNCT
cana-4791	222	17	and	and	CCONJ
cana-4791	222	18	it	it	PRON
cana-4791	222	19	also	also	ADV
cana-4791	222	20	works	work	VERB
cana-4791	222	21	well	well	ADV
cana-4791	222	22	with	with	ADP
cana-4791	222	23	a	a	DET
cana-4791	222	24	wide	wide	ADJ
cana-4791	222	25	range	range	NOUN
cana-4791	222	26	of	of	ADP
cana-4791	222	27	datasets	dataset	NOUN
cana-4791	222	28	,	,	PUNCT
cana-4791	222	29	showing	show	VERB
cana-4791	222	30	that	that	SCONJ
cana-4791	222	31	it	it	PRON
cana-4791	222	32	is	be	AUX
cana-4791	222	33	both	both	CCONJ
cana-4791	222	34	solid	solid	ADJ
cana-4791	222	35	and	and	CCONJ
cana-4791	222	36	generalisable	generalisable	ADJ
cana-4791	222	37	.	.	PUNCT
cana-4791	223	1	even	even	ADV
cana-4791	223	2	at	at	ADP
cana-4791	223	3	low	low	ADJ
cana-4791	223	4	bitrates	bitrate	NOUN
cana-4791	223	5	(	(	PUNCT
cana-4791	223	6	0.25	0.25	NUM
cana-4791	223	7	bpp	bpp	NOUN
cana-4791	223	8	)	)	PUNCT
cana-4791	223	9	,	,	PUNCT
cana-4791	223	10	compressgan	compressgan	PROPN
cana-4791	223	11	keeps	keep	VERB
cana-4791	223	12	more	more	ADJ
cana-4791	223	13	edge	edge	NOUN
cana-4791	223	14	features	feature	NOUN
cana-4791	223	15	,	,	PUNCT
cana-4791	223	16	colour	colour	NOUN
cana-4791	223	17	accuracy	accuracy	NOUN
cana-4791	223	18	,	,	PUNCT
cana-4791	223	19	and	and	CCONJ
cana-4791	223	20	material	material	NOUN
cana-4791	223	21	realism	realism	NOUN
cana-4791	223	22	than	than	ADP
cana-4791	223	23	its	its	PRON
cana-4791	223	24	competitors	competitor	NOUN
cana-4791	223	25	.	.	PUNCT
cana-4791	224	1	it	it	PRON
cana-4791	224	2	can	can	AUX
cana-4791	224	3	be	be	AUX
cana-4791	224	4	trained	train	VERB
cana-4791	224	5	from	from	ADP
cana-4791	224	6	beginning	begin	VERB
cana-4791	224	7	to	to	PART
cana-4791	224	8	end	end	NOUN
cana-4791	224	9	and	and	CCONJ
cana-4791	224	10	can	can	AUX
cana-4791	224	11	adapt	adapt	VERB
cana-4791	224	12	to	to	ADP
cana-4791	224	13	different	different	ADJ
cana-4791	224	14	compression	compression	NOUN
cana-4791	224	15	needs	need	NOUN
cana-4791	224	16	by	by	ADP
cana-4791	224	17	changing	change	VERB
cana-4791	224	18	the	the	DET
cana-4791	224	19	number	number	NOUN
cana-4791	224	20	of	of	ADP
cana-4791	224	21	dimensions	dimension	NOUN
cana-4791	224	22	in	in	ADP
cana-4791	224	23	the	the	DET
cana-4791	224	24	hidden	hide	VERB
cana-4791	224	25	space	space	NOUN
cana-4791	224	26	and	and	CCONJ
cana-4791	224	27	the	the	DET
cana-4791	224	28	depth	depth	NOUN
cana-4791	224	29	of	of	ADP
cana-4791	224	30	quantisation	quantisation	NOUN
cana-4791	224	31	.	.	PUNCT
cana-4791	225	1	compressgan	compressgan	PROPN
cana-4791	225	2	is	be	AUX
cana-4791	225	3	perfect	perfect	ADJ
cana-4791	225	4	for	for	ADP
cana-4791	225	5	real	real	ADJ
cana-4791	225	6	-	-	PUNCT
cana-4791	225	7	life	life	NOUN
cana-4791	225	8	uses	use	VERB
cana-4791	225	9	where	where	SCONJ
cana-4791	225	10	bandwidth	bandwidth	NOUN
cana-4791	225	11	or	or	CCONJ
cana-4791	225	12	storage	storage	NOUN
cana-4791	225	13	space	space	NOUN
cana-4791	225	14	is	be	AUX
cana-4791	225	15	limited	limit	VERB
cana-4791	225	16	,	,	PUNCT
cana-4791	225	17	like	like	ADP
cana-4791	225	18	mobile	mobile	ADJ
cana-4791	225	19	photography	photography	NOUN
cana-4791	225	20	,	,	PUNCT
cana-4791	225	21	remote	remote	ADJ
cana-4791	225	22	sensing	sensing	NOUN
cana-4791	225	23	,	,	PUNCT
cana-4791	225	24	monitoring	monitoring	NOUN
cana-4791	225	25	,	,	PUNCT
cana-4791	225	26	and	and	CCONJ
cana-4791	225	27	delivering	deliver	VERB
cana-4791	225	28	media	medium	NOUN
cana-4791	225	29	over	over	ADP
cana-4791	225	30	the	the	DET
cana-4791	225	31	web	web	NOUN
cana-4791	225	32	.	.	PUNCT
cana-4791	225	33	using	use	VERB
cana-4791	225	34	adversarial	adversarial	ADJ
cana-4791	225	35	learning	learning	NOUN
cana-4791	225	36	that	that	PRON
cana-4791	225	37	is	be	AUX
cana-4791	225	38	aware	aware	ADJ
cana-4791	225	39	of	of	ADP
cana-4791	225	40	perception	perception	NOUN
cana-4791	225	41	is	be	AUX
cana-4791	225	42	a	a	DET
cana-4791	225	43	big	big	ADJ
cana-4791	225	44	step	step	NOUN
cana-4791	225	45	forward	forward	ADV
cana-4791	225	46	in	in	ADP
cana-4791	225	47	the	the	DET
cana-4791	225	48	development	development	NOUN
cana-4791	225	49	of	of	ADP
cana-4791	225	50	neural	neural	ADJ
cana-4791	225	51	codecs	codec	NOUN
cana-4791	225	52	.	.	PUNCT
cana-4791	226	1	attention	attention	NOUN
cana-4791	226	2	processes	process	NOUN
cana-4791	226	3	,	,	PUNCT
cana-4791	226	4	dynamic	dynamic	ADJ
cana-4791	226	5	bitrate	bitrate	NOUN
cana-4791	226	6	change	change	NOUN
cana-4791	226	7	,	,	PUNCT
cana-4791	226	8	and	and	CCONJ
cana-4791	226	9	cross	cross	ADJ
cana-4791	226	10	-	-	ADJ
cana-4791	226	11	domain	domain	ADJ
cana-4791	226	12	perceptual	perceptual	ADJ
cana-4791	226	13	alignment	alignment	NOUN
cana-4791	226	14	will	will	AUX
cana-4791	226	15	be	be	AUX
cana-4791	226	16	looked	look	VERB
cana-4791	226	17	at	at	ADP
cana-4791	226	18	in	in	ADP
cana-4791	226	19	more	more	ADJ
cana-4791	226	20	detail	detail	NOUN
cana-4791	226	21	in	in	ADP
cana-4791	226	22	future	future	ADJ
cana-4791	226	23	research	research	NOUN
cana-4791	226	24	that	that	PRON
cana-4791	226	25	aims	aim	VERB
cana-4791	226	26	to	to	PART
cana-4791	226	27	improve	improve	VERB
cana-4791	226	28	compression	compression	NOUN
cana-4791	226	29	performance	performance	NOUN
cana-4791	226	30	and	and	CCONJ
cana-4791	226	31	model	model	NOUN
cana-4791	226	32	generalisation	generalisation	NOUN
cana-4791	226	33	even	even	ADV
cana-4791	226	34	more	more	ADV
cana-4791	226	35	.	.	PUNCT
cana-4791	227	1	compressgan	compressgan	PROPN
cana-4791	227	2	eventually	eventually	ADV
cana-4791	227	3	makes	make	VERB
cana-4791	227	4	it	it	PRON
cana-4791	227	5	possible	possible	ADJ
cana-4791	227	6	for	for	SCONJ
cana-4791	227	7	picture	picture	NOUN
cana-4791	227	8	compression	compression	NOUN
cana-4791	227	9	systems	system	NOUN
cana-4791	227	10	to	to	PART
cana-4791	227	11	be	be	AUX
cana-4791	227	12	smarter	smart	ADJ
cana-4791	227	13	,	,	PUNCT
cana-4791	227	14	more	more	ADV
cana-4791	227	15	flexible	flexible	ADJ
cana-4791	227	16	,	,	PUNCT
cana-4791	227	17	and	and	CCONJ
cana-4791	227	18	more	more	ADV
cana-4791	227	19	focused	focused	ADJ
cana-4791	227	20	on	on	ADP
cana-4791	227	21	people	people	NOUN
cana-4791	227	22	.	.	PUNCT
cana-4791	228	1	communications	communication	NOUN
cana-4791	228	2	on	on	ADP
cana-4791	228	3	applied	apply	VERB
cana-4791	228	4	nonlinear	nonlinear	ADJ
cana-4791	228	5	analysis	analysis	NOUN
cana-4791	228	6	issn	issn	NOUN
cana-4791	228	7	:	:	PUNCT
cana-4791	228	8	1074	1074	NUM
cana-4791	228	9	-	-	PUNCT
cana-4791	228	10	133x	133x	NUM
cana-4791	228	11	vol	vol	NOUN
cana-4791	228	12	31	31	NUM
cana-4791	228	13	no	no	NOUN
cana-4791	228	14	.	.	PUNCT
cana-4791	229	1	1s	1s	NUM
cana-4791	229	2	(	(	PUNCT
cana-4791	229	3	2024	2024	NUM
cana-4791	229	4	)	)	PUNCT
cana-4791	229	5	228	228	NUM
cana-4791	229	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4791	229	7	references	reference	NOUN
cana-4791	229	8	[	[	X
cana-4791	229	9	1	1	NUM
cana-4791	229	10	]	]	X
cana-4791	229	11	park	park	NOUN
cana-4791	229	12	,	,	PUNCT
cana-4791	229	13	y.	y.	PROPN
cana-4791	229	14	;	;	PUNCT
cana-4791	229	15	lee	lee	PROPN
cana-4791	229	16	,	,	PUNCT
cana-4791	229	17	s.	s.	PROPN
cana-4791	229	18	;	;	PUNCT
cana-4791	229	19	jeong	jeong	PROPN
cana-4791	229	20	,	,	PUNCT
cana-4791	229	21	b.	b.	PROPN
cana-4791	229	22	;	;	PUNCT
cana-4791	229	23	yoon	yoon	PROPN
cana-4791	229	24	,	,	PUNCT
cana-4791	229	25	j.	j.	PROPN
cana-4791	229	26	joint	joint	PROPN
cana-4791	229	27	demosaicing	demosaicing	NOUN
cana-4791	229	28	and	and	CCONJ
cana-4791	229	29	denoising	denoising	NOUN
cana-4791	229	30	based	base	VERB
cana-4791	229	31	on	on	ADP
cana-4791	229	32	a	a	DET
cana-4791	229	33	variational	variational	ADJ
cana-4791	229	34	deep	deep	ADJ
cana-4791	229	35	image	image	NOUN
cana-4791	229	36	prior	prior	ADP
cana-4791	229	37	neural	neural	ADJ
cana-4791	229	38	network	network	NOUN
cana-4791	229	39	.	.	PUNCT
cana-4791	230	1	sensors	sensor	NOUN
cana-4791	230	2	2020	2020	NUM
cana-4791	230	3	,	,	PUNCT
cana-4791	230	4	20	20	NUM
cana-4791	230	5	,	,	PUNCT
cana-4791	230	6	2970	2970	NUM
cana-4791	230	7	.	.	PUNCT
cana-4791	231	1	[	[	X
cana-4791	231	2	2	2	NUM
cana-4791	231	3	]	]	PUNCT
cana-4791	231	4	khadidos	khadido	NOUN
cana-4791	231	5	,	,	PUNCT
cana-4791	231	6	a.o	a.o	PROPN
cana-4791	231	7	.	.	PROPN
cana-4791	231	8	;	;	PUNCT
cana-4791	231	9	khadidos	khadido	NOUN
cana-4791	231	10	,	,	PUNCT
cana-4791	231	11	a.o	a.o	PROPN
cana-4791	231	12	.	.	PROPN
cana-4791	231	13	;	;	PUNCT
cana-4791	231	14	khan	khan	PROPN
cana-4791	231	15	,	,	PUNCT
cana-4791	231	16	f.q	f.q	PROPN
cana-4791	231	17	.	.	PROPN
cana-4791	231	18	;	;	PUNCT
cana-4791	231	19	tsaramirsis	tsaramirsis	NOUN
cana-4791	231	20	,	,	PUNCT
cana-4791	231	21	g.	g.	PROPN
cana-4791	231	22	;	;	PUNCT
cana-4791	231	23	ahmad	ahmad	PROPN
cana-4791	231	24	,	,	PUNCT
cana-4791	231	25	a.	a.	NOUN
cana-4791	231	26	bayer	bayer	NOUN
cana-4791	231	27	image	image	NOUN
cana-4791	231	28	demosaicking	demosaicking	NOUN
cana-4791	231	29	and	and	CCONJ
cana-4791	231	30	denoising	denoising	NOUN
cana-4791	231	31	based	base	VERB
cana-4791	231	32	on	on	ADP
cana-4791	231	33	specialized	specialized	ADJ
cana-4791	231	34	networks	network	NOUN
cana-4791	231	35	using	use	VERB
cana-4791	231	36	deep	deep	ADJ
cana-4791	231	37	learning	learning	NOUN
cana-4791	231	38	.	.	PUNCT
cana-4791	232	1	multimedia	multimedia	PROPN
cana-4791	232	2	syst	syst	PROPN
cana-4791	232	3	.	.	PUNCT
cana-4791	232	4	2021	2021	NUM
cana-4791	232	5	,	,	PUNCT
cana-4791	232	6	27	27	NUM
cana-4791	232	7	,	,	PUNCT
cana-4791	232	8	807	807	NUM
cana-4791	232	9	–	–	PUNCT
cana-4791	232	10	819	819	NUM
cana-4791	232	11	.	.	PUNCT
cana-4791	233	1	[	[	X
cana-4791	233	2	3	3	NUM
cana-4791	233	3	]	]	X
cana-4791	233	4	liang	liang	PROPN
cana-4791	233	5	,	,	PUNCT
cana-4791	233	6	j.	j.	PROPN
cana-4791	233	7	;	;	PUNCT
cana-4791	233	8	zeng	zeng	PROPN
cana-4791	233	9	,	,	PUNCT
cana-4791	233	10	h.	h.	PROPN
cana-4791	233	11	;	;	PUNCT
cana-4791	233	12	zhang	zhang	PROPN
cana-4791	233	13	,	,	PUNCT
cana-4791	233	14	l.	l.	PROPN
cana-4791	233	15	details	detail	NOUN
cana-4791	233	16	or	or	CCONJ
cana-4791	233	17	artifacts	artifact	NOUN
cana-4791	233	18	:	:	PUNCT
cana-4791	233	19	a	a	DET
cana-4791	233	20	locally	locally	ADV
cana-4791	233	21	discriminative	discriminative	NOUN
cana-4791	233	22	learning	learn	VERB
cana-4791	233	23	approach	approach	NOUN
cana-4791	233	24	to	to	ADP
cana-4791	233	25	realistic	realistic	ADJ
cana-4791	233	26	image	image	NOUN
cana-4791	233	27	super	super	NOUN
cana-4791	233	28	-	-	NOUN
cana-4791	233	29	resolution	resolution	NOUN
cana-4791	233	30	.	.	PUNCT
cana-4791	234	1	in	in	ADP
cana-4791	234	2	proceedings	proceeding	NOUN
cana-4791	234	3	of	of	ADP
cana-4791	234	4	the	the	DET
cana-4791	234	5	2022	2022	NUM
cana-4791	234	6	ieee	ieee	NOUN
cana-4791	234	7	/	/	SYM
cana-4791	234	8	cvf	cvf	NOUN
cana-4791	234	9	conference	conference	NOUN
cana-4791	234	10	on	on	ADP
cana-4791	234	11	computer	computer	NOUN
cana-4791	234	12	vision	vision	NOUN
cana-4791	234	13	and	and	CCONJ
cana-4791	234	14	pattern	pattern	NOUN
cana-4791	234	15	recognition	recognition	NOUN
cana-4791	234	16	(	(	PUNCT
cana-4791	234	17	cvpr	cvpr	NOUN
cana-4791	234	18	)	)	PUNCT
cana-4791	234	19	,	,	PUNCT
cana-4791	234	20	ieee	ieee	NOUN
cana-4791	234	21	,	,	PUNCT
cana-4791	234	22	new	new	PROPN
cana-4791	234	23	orleans	orleans	PROPN
cana-4791	234	24	,	,	PUNCT
cana-4791	234	25	la	la	PROPN
cana-4791	234	26	,	,	PUNCT
cana-4791	234	27	usa	usa	PROPN
cana-4791	234	28	,	,	PUNCT
cana-4791	234	29	18–24	18–24	NUM
cana-4791	234	30	june	june	PROPN
cana-4791	234	31	2022	2022	NUM
cana-4791	234	32	.	.	PUNCT
cana-4791	235	1	[	[	X
cana-4791	235	2	4	4	NUM
cana-4791	235	3	]	]	SYM
cana-4791	235	4	ledig	ledig	NOUN
cana-4791	235	5	,	,	PUNCT
cana-4791	235	6	c.	c.	PROPN
cana-4791	235	7	;	;	PUNCT
cana-4791	235	8	theis	theis	PROPN
cana-4791	235	9	,	,	PUNCT
cana-4791	235	10	l.	l.	PROPN
cana-4791	235	11	;	;	PUNCT
cana-4791	235	12	huszár	huszár	PROPN
cana-4791	235	13	,	,	PUNCT
cana-4791	235	14	f.	f.	PROPN
cana-4791	235	15	;	;	PUNCT
cana-4791	235	16	caballero	caballero	PROPN
cana-4791	235	17	,	,	PUNCT
cana-4791	235	18	j.	j.	PROPN
cana-4791	235	19	;	;	PUNCT
cana-4791	235	20	cunningham	cunningham	PROPN
cana-4791	235	21	,	,	PUNCT
cana-4791	235	22	a.	a.	NOUN
cana-4791	235	23	;	;	PUNCT
cana-4791	235	24	acosta	acosta	PROPN
cana-4791	235	25	,	,	PUNCT
cana-4791	235	26	a.	a.	NOUN
cana-4791	235	27	;	;	PUNCT
cana-4791	235	28	aitken	aitken	PROPN
cana-4791	235	29	,	,	PUNCT
cana-4791	235	30	a.	a.	PROPN
cana-4791	235	31	;	;	PUNCT
cana-4791	235	32	tejani	tejani	NOUN
cana-4791	235	33	,	,	PUNCT
cana-4791	235	34	a.	a.	NOUN
cana-4791	235	35	;	;	PUNCT
cana-4791	235	36	totz	totz	PROPN
cana-4791	235	37	,	,	PUNCT
cana-4791	235	38	j.	j.	PROPN
cana-4791	235	39	;	;	PUNCT
cana-4791	235	40	wang	wang	PROPN
cana-4791	235	41	,	,	PUNCT
cana-4791	235	42	z.	z.	PROPN
cana-4791	235	43	;	;	PUNCT
cana-4791	235	44	et	et	PROPN
cana-4791	235	45	al	al	PROPN
cana-4791	235	46	.	.	PUNCT
cana-4791	235	47	photo	photo	NOUN
cana-4791	235	48	-	-	PUNCT
cana-4791	235	49	realistic	realistic	ADJ
cana-4791	235	50	single	single	ADJ
cana-4791	235	51	image	image	NOUN
cana-4791	235	52	super	super	NOUN
cana-4791	235	53	-	-	NOUN
cana-4791	235	54	resolution	resolution	NOUN
cana-4791	235	55	using	use	VERB
cana-4791	235	56	a	a	DET
cana-4791	235	57	generative	generative	ADJ
cana-4791	235	58	adversarial	adversarial	ADJ
cana-4791	235	59	network	network	NOUN
cana-4791	235	60	.	.	PUNCT
cana-4791	236	1	in	in	ADP
cana-4791	236	2	proceedings	proceeding	NOUN
cana-4791	236	3	of	of	ADP
cana-4791	236	4	the	the	DET
cana-4791	236	5	2017	2017	NUM
cana-4791	236	6	ieee	ieee	NOUN
cana-4791	236	7	conference	conference	NOUN
cana-4791	236	8	on	on	ADP
cana-4791	236	9	computer	computer	NOUN
cana-4791	236	10	vision	vision	NOUN
cana-4791	236	11	and	and	CCONJ
cana-4791	236	12	pattern	pattern	NOUN
cana-4791	236	13	recognition	recognition	NOUN
cana-4791	236	14	(	(	PUNCT
cana-4791	236	15	cvpr	cvpr	NOUN
cana-4791	236	16	)	)	PUNCT
cana-4791	236	17	,	,	PUNCT
cana-4791	236	18	honolulu	honolulu	PROPN
cana-4791	236	19	,	,	PUNCT
cana-4791	236	20	hi	hi	PROPN
cana-4791	236	21	,	,	PUNCT
cana-4791	236	22	usa	usa	PROPN
cana-4791	236	23	,	,	PUNCT
cana-4791	236	24	21–26	21–26	NUM
cana-4791	236	25	july	july	NOUN
cana-4791	236	26	2017	2017	NUM
cana-4791	236	27	;	;	PUNCT
cana-4791	236	28	pp	pp	ADP
cana-4791	236	29	.	.	PUNCT
cana-4791	237	1	105–114	105–114	NUM
cana-4791	237	2	.	.	PUNCT
cana-4791	238	1	[	[	X
cana-4791	238	2	5	5	NUM
cana-4791	238	3	]	]	X
cana-4791	238	4	liu	liu	PROPN
cana-4791	238	5	,	,	PUNCT
cana-4791	238	6	y.	y.	PROPN
cana-4791	238	7	;	;	PUNCT
cana-4791	238	8	shao	shao	PROPN
cana-4791	238	9	,	,	PUNCT
cana-4791	238	10	z.	z.	PROPN
cana-4791	238	11	;	;	PUNCT
cana-4791	238	12	hoffmann	hoffmann	PROPN
cana-4791	238	13	,	,	PUNCT
cana-4791	238	14	n.	n.	PROPN
cana-4791	238	15	global	global	ADJ
cana-4791	238	16	attention	attention	NOUN
cana-4791	238	17	mechanism	mechanism	NOUN
cana-4791	238	18	:	:	PUNCT
cana-4791	238	19	retain	retain	VERB
cana-4791	238	20	information	information	NOUN
cana-4791	238	21	to	to	PART
cana-4791	238	22	enhance	enhance	VERB
cana-4791	238	23	channelspatial	channelspatial	ADJ
cana-4791	238	24	interactions	interaction	NOUN
cana-4791	238	25	.	.	PUNCT
cana-4791	239	1	arxiv	arxiv	PROPN
cana-4791	239	2	2021	2021	NUM
cana-4791	239	3	,	,	PUNCT
cana-4791	239	4	arxiv:2112.05561	arxiv:2112.05561	PROPN
cana-4791	239	5	.	.	PUNCT
cana-4791	240	1	[	[	X
cana-4791	240	2	6	6	NUM
cana-4791	240	3	]	]	X
cana-4791	240	4	zhang	zhang	PROPN
cana-4791	240	5	,	,	PUNCT
cana-4791	240	6	l.	l.	PROPN
cana-4791	240	7	;	;	PUNCT
cana-4791	240	8	wang	wang	PROPN
cana-4791	240	9	,	,	PUNCT
cana-4791	240	10	h.	h.	PROPN
cana-4791	241	1	an	an	DET
cana-4791	241	2	improved	improved	ADJ
cana-4791	241	3	lsb	lsb	NOUN
cana-4791	241	4	-	-	PUNCT
cana-4791	241	5	based	base	VERB
cana-4791	241	6	steganography	steganography	NOUN
cana-4791	241	7	method	method	NOUN
cana-4791	241	8	for	for	ADP
cana-4791	241	9	image	image	NOUN
cana-4791	241	10	security	security	NOUN
cana-4791	241	11	.	.	PUNCT
cana-4791	242	1	int	int	NOUN
cana-4791	242	2	.	.	PUNCT
cana-4791	243	1	j.	j.	PROPN
cana-4791	243	2	image	image	PROPN
cana-4791	243	3	process	process	NOUN
cana-4791	243	4	.	.	PUNCT
cana-4791	244	1	2024	2024	NUM
cana-4791	244	2	,	,	PUNCT
cana-4791	244	3	14	14	NUM
cana-4791	244	4	,	,	PUNCT
cana-4791	244	5	67–80	67–80	NOUN
cana-4791	244	6	.	.	PUNCT
cana-4791	245	1	[	[	X
cana-4791	245	2	7	7	X
cana-4791	245	3	]	]	X
cana-4791	245	4	liu	liu	PROPN
cana-4791	245	5	,	,	PUNCT
cana-4791	245	6	j.	j.	PROPN
cana-4791	245	7	;	;	PUNCT
cana-4791	245	8	chen	chen	PROPN
cana-4791	245	9	,	,	PUNCT
cana-4791	245	10	y.	y.	PROPN
cana-4791	245	11	wavelet	wavelet	PROPN
cana-4791	245	12	transform	transform	NOUN
cana-4791	245	13	-	-	PUNCT
cana-4791	245	14	based	base	VERB
cana-4791	245	15	image	image	NOUN
cana-4791	245	16	steganography	steganography	NOUN
cana-4791	245	17	:	:	PUNCT
cana-4791	245	18	a	a	DET
cana-4791	245	19	new	new	ADJ
cana-4791	245	20	approach	approach	NOUN
cana-4791	245	21	.	.	PUNCT
cana-4791	246	1	j.	j.	PROPN
cana-4791	246	2	signal	signal	PROPN
cana-4791	246	3	process	process	NOUN
cana-4791	246	4	.	.	PUNCT
cana-4791	247	1	syst	syst	PROPN
cana-4791	247	2	.	.	PUNCT
cana-4791	248	1	2023	2023	NUM
cana-4791	248	2	,	,	PUNCT
cana-4791	248	3	95	95	NUM
cana-4791	248	4	,	,	PUNCT
cana-4791	248	5	123–135	123–135	NUM
cana-4791	248	6	.	.	PUNCT
cana-4791	249	1	[	[	X
cana-4791	249	2	8	8	NUM
cana-4791	249	3	]	]	SYM
cana-4791	249	4	yuan	yuan	NOUN
cana-4791	249	5	,	,	PUNCT
cana-4791	249	6	x.	x.	NOUN
cana-4791	249	7	;	;	PUNCT
cana-4791	249	8	song	song	PROPN
cana-4791	249	9	,	,	PUNCT
cana-4791	249	10	w.	w.	PROPN
cana-4791	249	11	;	;	PUNCT
cana-4791	249	12	zhang	zhang	PROPN
cana-4791	249	13	,	,	PUNCT
cana-4791	249	14	c.	c.	PROPN
cana-4791	249	15	;	;	PUNCT
cana-4791	249	16	yuan	yuan	NOUN
cana-4791	249	17	,	,	PUNCT
cana-4791	249	18	y.	y.	PROPN
cana-4791	249	19	understanding	understand	VERB
cana-4791	249	20	the	the	DET
cana-4791	249	21	evolution	evolution	NOUN
cana-4791	249	22	of	of	ADP
cana-4791	249	23	photovoltaic	photovoltaic	NOUN
cana-4791	249	24	value	value	NOUN
cana-4791	249	25	chain	chain	NOUN
cana-4791	249	26	from	from	ADP
cana-4791	249	27	a	a	DET
cana-4791	249	28	global	global	ADJ
cana-4791	249	29	perspective	perspective	NOUN
cana-4791	249	30	:	:	PUNCT
cana-4791	249	31	based	base	VERB
cana-4791	249	32	on	on	ADP
cana-4791	249	33	the	the	DET
cana-4791	249	34	patent	patent	NOUN
cana-4791	249	35	analysis	analysis	NOUN
cana-4791	249	36	.	.	PUNCT
cana-4791	250	1	j.	j.	PROPN
cana-4791	250	2	clean	clean	PROPN
cana-4791	250	3	.	.	PUNCT
cana-4791	251	1	prod	prod	PROPN
cana-4791	251	2	.	.	PUNCT
cana-4791	252	1	2022	2022	NUM
cana-4791	252	2	,	,	PUNCT
cana-4791	252	3	377	377	NUM
cana-4791	252	4	,	,	PUNCT
cana-4791	252	5	134466	134466	NUM
cana-4791	252	6	.	.	PUNCT
cana-4791	253	1	[	[	X
cana-4791	253	2	9	9	NUM
cana-4791	253	3	]	]	X
cana-4791	253	4	jia	jia	PROPN
cana-4791	253	5	,	,	PUNCT
cana-4791	253	6	x.	x.	PROPN
cana-4791	253	7	;	;	PUNCT
cana-4791	253	8	wei	wei	PROPN
cana-4791	253	9	,	,	PUNCT
cana-4791	253	10	x.	x.	PROPN
cana-4791	253	11	;	;	PUNCT
cana-4791	253	12	cao	cao	PROPN
cana-4791	253	13	,	,	PUNCT
cana-4791	253	14	x.	x.	PROPN
cana-4791	253	15	;	;	PUNCT
cana-4791	253	16	han	han	PROPN
cana-4791	253	17	,	,	PUNCT
cana-4791	253	18	x.	x.	NOUN
cana-4791	253	19	adv	adv	PROPN
cana-4791	253	20	-	-	PUNCT
cana-4791	253	21	watermark	watermark	NOUN
cana-4791	253	22	:	:	PUNCT
cana-4791	253	23	a	a	DET
cana-4791	253	24	novel	novel	ADJ
cana-4791	253	25	watermark	watermark	NOUN
cana-4791	253	26	perturbation	perturbation	NOUN
cana-4791	253	27	for	for	ADP
cana-4791	253	28	adversarial	adversarial	ADJ
cana-4791	253	29	examples	example	NOUN
cana-4791	253	30	.	.	PUNCT
cana-4791	254	1	in	in	ADP
cana-4791	254	2	proceedings	proceeding	NOUN
cana-4791	254	3	of	of	ADP
cana-4791	254	4	the	the	DET
cana-4791	254	5	28th	28th	ADJ
cana-4791	254	6	acm	acm	PROPN
cana-4791	254	7	international	international	ADJ
cana-4791	254	8	conference	conference	NOUN
cana-4791	254	9	on	on	ADP
cana-4791	254	10	multimedia	multimedia	PROPN
cana-4791	254	11	,	,	PUNCT
cana-4791	254	12	seattle	seattle	PROPN
cana-4791	254	13	,	,	PUNCT
cana-4791	254	14	wa	wa	PROPN
cana-4791	254	15	,	,	PUNCT
cana-4791	254	16	usa	usa	PROPN
cana-4791	254	17	,	,	PUNCT
cana-4791	254	18	12–16	12–16	NUM
cana-4791	254	19	october	october	NOUN
cana-4791	254	20	2020	2020	NUM
cana-4791	254	21	;	;	PUNCT
cana-4791	254	22	pp	pp	X
cana-4791	254	23	.	.	PUNCT
cana-4791	255	1	1579–1587	1579–1587	NUM
cana-4791	255	2	.	.	PUNCT
cana-4791	256	1	[	[	X
cana-4791	256	2	10	10	NUM
cana-4791	256	3	]	]	X
cana-4791	256	4	goodfellow	goodfellow	PROPN
cana-4791	256	5	,	,	PUNCT
cana-4791	256	6	i.	i.	NOUN
cana-4791	256	7	;	;	PUNCT
cana-4791	256	8	pouget	pouget	NOUN
cana-4791	256	9	-	-	PUNCT
cana-4791	256	10	abadie	abadie	ADJ
cana-4791	256	11	,	,	PUNCT
cana-4791	256	12	j.	j.	PROPN
cana-4791	256	13	;	;	PUNCT
cana-4791	256	14	mirza	mirza	PROPN
cana-4791	256	15	,	,	PUNCT
cana-4791	256	16	m.	m.	NOUN
cana-4791	256	17	;	;	PUNCT
cana-4791	256	18	xu	xu	PROPN
cana-4791	256	19	,	,	PUNCT
cana-4791	256	20	b.	b.	PROPN
cana-4791	256	21	;	;	PUNCT
cana-4791	256	22	warde	warde	PROPN
cana-4791	256	23	-	-	PUNCT
cana-4791	256	24	farley	farley	PROPN
cana-4791	256	25	,	,	PUNCT
cana-4791	256	26	d.	d.	PROPN
cana-4791	256	27	;	;	PUNCT
cana-4791	256	28	ozair	ozair	PROPN
cana-4791	256	29	,	,	PUNCT
cana-4791	256	30	s.	s.	PROPN
cana-4791	256	31	;	;	PUNCT
cana-4791	256	32	bengio	bengio	PROPN
cana-4791	256	33	,	,	PUNCT
cana-4791	256	34	y.	y.	PROPN
cana-4791	256	35	generative	generative	VERB
cana-4791	256	36	adversarial	adversarial	ADJ
cana-4791	256	37	nets	net	NOUN
cana-4791	256	38	.	.	PUNCT
cana-4791	257	1	in	in	ADP
cana-4791	257	2	proceedings	proceeding	NOUN
cana-4791	257	3	of	of	ADP
cana-4791	257	4	the	the	DET
cana-4791	257	5	27th	27th	ADJ
cana-4791	257	6	international	international	ADJ
cana-4791	257	7	conference	conference	NOUN
cana-4791	257	8	on	on	ADP
cana-4791	257	9	neural	neural	ADJ
cana-4791	257	10	information	information	NOUN
cana-4791	257	11	processing	processing	NOUN
cana-4791	257	12	systems	system	NOUN
cana-4791	257	13	(	(	PUNCT
cana-4791	257	14	nips	nip	NOUN
cana-4791	257	15	)	)	PUNCT
cana-4791	257	16	,	,	PUNCT
cana-4791	257	17	montreal	montreal	PROPN
cana-4791	257	18	,	,	PUNCT
cana-4791	257	19	qc	qc	PROPN
cana-4791	257	20	,	,	PUNCT
cana-4791	257	21	canada	canada	PROPN
cana-4791	257	22	,	,	PUNCT
cana-4791	257	23	8–13	8–13	NOUN
cana-4791	257	24	december	december	PROPN
cana-4791	257	25	2014	2014	NUM
cana-4791	257	26	;	;	PUNCT
cana-4791	257	27	volume	volume	NOUN
cana-4791	257	28	2	2	NUM
cana-4791	257	29	,	,	PUNCT
cana-4791	257	30	pp	pp	ADJ
cana-4791	257	31	.	.	PUNCT
cana-4791	258	1	2672–2680	2672–2680	NUM
cana-4791	258	2	.	.	PUNCT
cana-4791	259	1	[	[	X
cana-4791	259	2	11	11	NUM
cana-4791	259	3	]	]	SYM
cana-4791	259	4	yang	yang	PROPN
cana-4791	259	5	,	,	PUNCT
cana-4791	259	6	d.	d.	PROPN
cana-4791	259	7	;	;	PUNCT
cana-4791	259	8	hong	hong	PROPN
cana-4791	259	9	,	,	PUNCT
cana-4791	259	10	s.	s.	PROPN
cana-4791	259	11	;	;	PUNCT
cana-4791	259	12	jang	jang	PROPN
cana-4791	259	13	,	,	PUNCT
cana-4791	259	14	y.	y.	PROPN
cana-4791	259	15	;	;	PUNCT
cana-4791	259	16	zhao	zhao	PROPN
cana-4791	259	17	,	,	PUNCT
cana-4791	259	18	t.	t.	PROPN
cana-4791	259	19	;	;	PUNCT
cana-4791	259	20	lee	lee	PROPN
cana-4791	259	21	,	,	PUNCT
cana-4791	259	22	h.	h.	PROPN
cana-4791	259	23	diversity	diversity	NOUN
cana-4791	259	24	-	-	PUNCT
cana-4791	259	25	sensitive	sensitive	ADJ
cana-4791	259	26	conditional	conditional	ADJ
cana-4791	259	27	generative	generative	ADJ
cana-4791	259	28	adversarial	adversarial	ADJ
cana-4791	259	29	networks	network	NOUN
cana-4791	259	30	.	.	PUNCT
cana-4791	260	1	arxiv	arxiv	PROPN
cana-4791	260	2	2019	2019	NUM
cana-4791	260	3	,	,	PUNCT
cana-4791	260	4	arxiv:1901.09024	arxiv:1901.09024	NUM
cana-4791	260	5	.	.	PUNCT
cana-4791	261	1	[	[	X
cana-4791	261	2	12	12	NUM
cana-4791	261	3	]	]	SYM
cana-4791	261	4	li	li	PROPN
cana-4791	261	5	,	,	PUNCT
cana-4791	261	6	k.	k.	PROPN
cana-4791	261	7	;	;	PUNCT
cana-4791	261	8	dai	dai	PROPN
cana-4791	261	9	,	,	PUNCT
cana-4791	261	10	z.	z.	PROPN
cana-4791	261	11	;	;	PUNCT
cana-4791	261	12	wang	wang	PROPN
cana-4791	261	13	,	,	PUNCT
cana-4791	261	14	x.	x.	PROPN
cana-4791	261	15	;	;	PUNCT
cana-4791	261	16	song	song	NOUN
cana-4791	261	17	,	,	PUNCT
cana-4791	261	18	y.	y.	PROPN
cana-4791	261	19	;	;	PUNCT
cana-4791	261	20	jeon	jeon	PROPN
cana-4791	261	21	,	,	PUNCT
cana-4791	261	22	g.	g.	PROPN
cana-4791	261	23	gan	gan	PROPN
cana-4791	261	24	-	-	PUNCT
cana-4791	261	25	based	base	VERB
cana-4791	261	26	controllable	controllable	ADJ
cana-4791	261	27	image	image	NOUN
cana-4791	261	28	data	datum	NOUN
cana-4791	261	29	augmentation	augmentation	NOUN
cana-4791	261	30	in	in	ADP
cana-4791	261	31	low	low	ADJ
cana-4791	261	32	-	-	PUNCT
cana-4791	261	33	visibility	visibility	NOUN
cana-4791	261	34	conditions	condition	NOUN
cana-4791	261	35	for	for	ADP
cana-4791	261	36	improved	improved	ADJ
cana-4791	261	37	roadside	roadside	NOUN
cana-4791	261	38	traffic	traffic	NOUN
cana-4791	261	39	perception	perception	NOUN
cana-4791	261	40	.	.	PUNCT
cana-4791	262	1	ieee	ieee	PROPN
cana-4791	262	2	trans	trans	PROPN
cana-4791	262	3	.	.	PUNCT
cana-4791	263	1	consum	consum	PROPN
cana-4791	263	2	.	.	PUNCT
cana-4791	263	3	electron	electron	PROPN
cana-4791	263	4	.	.	PUNCT
cana-4791	264	1	2024	2024	NUM
cana-4791	264	2	,	,	PUNCT
cana-4791	264	3	70	70	NUM
cana-4791	264	4	,	,	PUNCT
cana-4791	264	5	6174–6188	6174–6188	NUM
cana-4791	264	6	.	.	PUNCT
cana-4791	265	1	[	[	X
cana-4791	265	2	13	13	NUM
cana-4791	265	3	]	]	X
cana-4791	265	4	chen	chen	PROPN
cana-4791	265	5	,	,	PUNCT
cana-4791	265	6	l.	l.	PROPN
cana-4791	265	7	;	;	PUNCT
cana-4791	265	8	liu	liu	PROPN
cana-4791	265	9	,	,	PUNCT
cana-4791	265	10	s.	s.	PROPN
cana-4791	265	11	enhanced	enhance	VERB
cana-4791	265	12	adversarial	adversarial	ADJ
cana-4791	265	13	training	training	NOUN
cana-4791	265	14	using	use	VERB
cana-4791	265	15	generative	generative	ADJ
cana-4791	265	16	adversarial	adversarial	ADJ
cana-4791	265	17	networks	network	NOUN
cana-4791	265	18	.	.	PUNCT
cana-4791	266	1	pattern	pattern	NOUN
cana-4791	266	2	recognit	recognit	VERB
cana-4791	266	3	.	.	PUNCT
cana-4791	267	1	2024	2024	NUM
cana-4791	267	2	,	,	PUNCT
cana-4791	267	3	123	123	NUM
cana-4791	267	4	,	,	PUNCT
cana-4791	267	5	108–120	108–120	NUM
cana-4791	267	6	.	.	PUNCT
cana-4791	268	1	[	[	X
cana-4791	268	2	14	14	NUM
cana-4791	268	3	]	]	X
cana-4791	268	4	kumar	kumar	PROPN
cana-4791	268	5	,	,	PUNCT
cana-4791	268	6	r.	r.	PROPN
cana-4791	268	7	;	;	PUNCT
cana-4791	268	8	patel	patel	PROPN
cana-4791	268	9	,	,	PUNCT
cana-4791	268	10	m.	m.	NOUN
cana-4791	268	11	exploring	explore	VERB
cana-4791	268	12	the	the	DET
cana-4791	268	13	limits	limit	NOUN
cana-4791	268	14	of	of	ADP
cana-4791	268	15	adversarial	adversarial	ADJ
cana-4791	268	16	sample	sample	NOUN
cana-4791	268	17	generation	generation	NOUN
cana-4791	268	18	with	with	ADP
cana-4791	268	19	gans	gan	NOUN
cana-4791	268	20	.	.	PUNCT
cana-4791	269	1	in	in	ADP
cana-4791	269	2	proceedings	proceeding	NOUN
cana-4791	269	3	of	of	ADP
cana-4791	269	4	the	the	DET
cana-4791	269	5	2024	2024	NUM
cana-4791	269	6	international	international	ADJ
cana-4791	269	7	conference	conference	NOUN
cana-4791	269	8	on	on	ADP
cana-4791	269	9	learning	learn	VERB
cana-4791	269	10	representations	representation	NOUN
cana-4791	269	11	(	(	PUNCT
cana-4791	269	12	iclr	iclr	NOUN
cana-4791	269	13	)	)	PUNCT
cana-4791	269	14	,	,	PUNCT
cana-4791	269	15	vienna	vienna	PROPN
cana-4791	269	16	,	,	PUNCT
cana-4791	269	17	austria	austria	PROPN
cana-4791	269	18	,	,	PUNCT
cana-4791	269	19	7–11	7–11	PROPN
cana-4791	269	20	may	may	PROPN
cana-4791	269	21	2024	2024	NUM
cana-4791	269	22	.	.	PUNCT
cana-4791	270	1	[	[	X
cana-4791	270	2	15	15	NUM
cana-4791	270	3	]	]	X
cana-4791	270	4	liu	liu	PROPN
cana-4791	270	5	,	,	PUNCT
cana-4791	270	6	x.	x.	PROPN
cana-4791	270	7	;	;	PUNCT
cana-4791	270	8	wang	wang	PROPN
cana-4791	270	9	,	,	PUNCT
cana-4791	270	10	j.	j.	PROPN
cana-4791	270	11	steganography	steganography	PROPN
cana-4791	270	12	using	use	VERB
cana-4791	270	13	generative	generative	ADJ
cana-4791	270	14	adversarial	adversarial	ADJ
cana-4791	270	15	networks	network	NOUN
cana-4791	270	16	.	.	PUNCT
cana-4791	271	1	in	in	ADP
cana-4791	271	2	proceedings	proceeding	NOUN
cana-4791	271	3	of	of	ADP
cana-4791	271	4	the	the	DET
cana-4791	271	5	2019	2019	NUM
cana-4791	271	6	ieee	ieee	NOUN
cana-4791	271	7	conference	conference	NOUN
cana-4791	271	8	on	on	ADP
cana-4791	271	9	computer	computer	NOUN
cana-4791	271	10	vision	vision	NOUN
cana-4791	271	11	and	and	CCONJ
cana-4791	271	12	pattern	pattern	NOUN
cana-4791	271	13	recognition	recognition	NOUN
cana-4791	271	14	(	(	PUNCT
cana-4791	271	15	cvpr	cvpr	NOUN
cana-4791	271	16	)	)	PUNCT
cana-4791	271	17	,	,	PUNCT
cana-4791	271	18	long	long	ADJ
cana-4791	271	19	beach	beach	NOUN
cana-4791	271	20	,	,	PUNCT
cana-4791	271	21	ca	ca	PROPN
cana-4791	271	22	,	,	PUNCT
cana-4791	271	23	usa	usa	PROPN
cana-4791	271	24	,	,	PUNCT
cana-4791	271	25	15–20	15–20	NUM
cana-4791	271	26	june	june	PROPN
cana-4791	271	27	2019	2019	NUM
cana-4791	271	28	.	.	PUNCT
cana-4791	272	1	[	[	X
cana-4791	272	2	16	16	NUM
cana-4791	272	3	]	]	X
cana-4791	272	4	ghamizi	ghamizi	PROPN
cana-4791	272	5	,	,	PUNCT
cana-4791	272	6	s.	s.	PROPN
cana-4791	272	7	;	;	PUNCT
cana-4791	272	8	cordy	cordy	PROPN
cana-4791	272	9	,	,	PUNCT
cana-4791	272	10	m.	m.	NOUN
cana-4791	272	11	;	;	PUNCT
cana-4791	272	12	papadakis	papadaki	NOUN
cana-4791	272	13	,	,	PUNCT
cana-4791	272	14	m.	m.	NOUN
cana-4791	272	15	;	;	PUNCT
cana-4791	272	16	traon	traon	PROPN
cana-4791	272	17	,	,	PUNCT
cana-4791	273	1	y.l	y.l	PROPN
cana-4791	273	2	.	.	PROPN
cana-4791	273	3	adversarial	adversarial	ADJ
cana-4791	273	4	embedding	embed	VERB
cana-4791	273	5	:	:	PUNCT
cana-4791	273	6	a	a	DET
cana-4791	273	7	robust	robust	ADJ
cana-4791	273	8	and	and	CCONJ
cana-4791	273	9	elusive	elusive	ADJ
cana-4791	273	10	steganography	steganography	NOUN
cana-4791	273	11	and	and	CCONJ
cana-4791	273	12	watermarking	watermarking	NOUN
cana-4791	273	13	technique	technique	NOUN
cana-4791	273	14	.	.	PUNCT
cana-4791	274	1	arxiv	arxiv	PROPN
cana-4791	274	2	2019	2019	NUM
cana-4791	274	3	,	,	PUNCT
cana-4791	274	4	arxiv:1912.01487	arxiv:1912.01487	NUM
cana-4791	274	5	.	.	PUNCT
cana-4791	275	1	[	[	X
cana-4791	275	2	17	17	NUM
cana-4791	275	3	]	]	PUNCT
cana-4791	275	4	yanuar	yanuar	NOUN
cana-4791	275	5	,	,	PUNCT
cana-4791	275	6	m.r	m.r	PROPN
cana-4791	275	7	.	.	PROPN
cana-4791	275	8	;	;	PUNCT
cana-4791	275	9	mt	mt	PROPN
cana-4791	275	10	,	,	PUNCT
cana-4791	275	11	s.	s.	PROPN
cana-4791	275	12	;	;	PUNCT
cana-4791	275	13	apriono	apriono	PROPN
cana-4791	275	14	,	,	PUNCT
cana-4791	275	15	c.	c.	NOUN
cana-4791	275	16	;	;	PUNCT
cana-4791	275	17	syawaludin	syawaludin	PROPN
cana-4791	275	18	,	,	PUNCT
cana-4791	275	19	m.f	m.f	PROPN
cana-4791	275	20	.	.	PUNCT
cana-4791	275	21	image	image	NOUN
cana-4791	275	22	-	-	PUNCT
cana-4791	275	23	to	to	ADP
cana-4791	275	24	-	-	PUNCT
cana-4791	275	25	image	image	NOUN
cana-4791	275	26	steganography	steganography	NOUN
cana-4791	275	27	with	with	ADP
cana-4791	275	28	josephus	josephus	PROPN
cana-4791	275	29	permutation	permutation	NOUN
cana-4791	275	30	and	and	CCONJ
cana-4791	275	31	least	least	ADV
cana-4791	275	32	significant	significant	ADJ
cana-4791	275	33	bit	bit	NOUN
cana-4791	275	34	(	(	PUNCT
cana-4791	275	35	lsb	lsb	PROPN
cana-4791	275	36	)	)	PUNCT
cana-4791	275	37	3	3	NUM
cana-4791	275	38	-	-	SYM
cana-4791	275	39	3	3	NUM
cana-4791	275	40	-	-	SYM
cana-4791	275	41	2	2	NUM
cana-4791	275	42	embedding	embed	VERB
cana-4791	275	43	.	.	PUNCT
cana-4791	276	1	appl	appl	PROPN
cana-4791	276	2	.	.	PUNCT
cana-4791	277	1	sci	sci	PROPN
cana-4791	277	2	.	.	PROPN
cana-4791	277	3	2024	2024	NUM
cana-4791	277	4	,	,	PUNCT
cana-4791	277	5	14	14	NUM
cana-4791	277	6	,	,	PUNCT
cana-4791	277	7	7119	7119	NUM
cana-4791	277	8	.	.	PUNCT
cana-4791	278	1	[	[	X
cana-4791	278	2	18	18	NUM
cana-4791	278	3	]	]	X
cana-4791	278	4	gupta	gupta	PROPN
cana-4791	278	5	banik	banik	X
cana-4791	278	6	,	,	PUNCT
cana-4791	278	7	b.	b.	PROPN
cana-4791	278	8	;	;	PUNCT
cana-4791	278	9	poddar	poddar	PROPN
cana-4791	278	10	,	,	PUNCT
cana-4791	278	11	m.k	m.k	PROPN
cana-4791	278	12	.	.	PUNCT
cana-4791	278	13	;	;	PUNCT
cana-4791	278	14	bandyopadhyay	bandyopadhyay	NOUN
cana-4791	278	15	,	,	PUNCT
cana-4791	278	16	s.k	s.k	PROPN
cana-4791	278	17	.	.	PROPN
cana-4791	278	18	image	image	NOUN
cana-4791	278	19	steganography	steganography	NOUN
cana-4791	278	20	using	use	VERB
cana-4791	278	21	edge	edge	NOUN
cana-4791	278	22	detection	detection	NOUN
cana-4791	278	23	by	by	ADP
cana-4791	278	24	kirsch	kirsch	PROPN
cana-4791	278	25	operator	operator	NOUN
cana-4791	278	26	and	and	CCONJ
cana-4791	278	27	flexible	flexible	ADJ
cana-4791	278	28	replacement	replacement	NOUN
cana-4791	278	29	technique	technique	NOUN
cana-4791	278	30	.	.	PUNCT
cana-4791	279	1	in	in	ADP
cana-4791	279	2	emerging	emerge	VERB
cana-4791	279	3	technologies	technology	NOUN
cana-4791	279	4	in	in	ADP
cana-4791	279	5	data	datum	NOUN
cana-4791	279	6	mining	mining	NOUN
cana-4791	279	7	and	and	CCONJ
cana-4791	279	8	information	information	NOUN
cana-4791	279	9	security	security	NOUN
cana-4791	279	10	:	:	PUNCT
cana-4791	279	11	proceedings	proceeding	NOUN
cana-4791	279	12	of	of	ADP
cana-4791	279	13	iemis	iemis	PROPN
cana-4791	279	14	2018	2018	NUM
cana-4791	279	15	;	;	PUNCT
cana-4791	279	16	springer	springer	NOUN
cana-4791	279	17	:	:	PUNCT
cana-4791	279	18	singapore	singapore	PROPN
cana-4791	279	19	,	,	PUNCT
cana-4791	279	20	2019	2019	NUM
cana-4791	279	21	;	;	PUNCT
cana-4791	279	22	volume	volume	NOUN
cana-4791	279	23	3	3	NUM
cana-4791	279	24	,	,	PUNCT
cana-4791	279	25	pp	pp	ADJ
cana-4791	279	26	.	.	PUNCT
cana-4791	280	1	175–187	175–187	NUM
cana-4791	280	2	.	.	PUNCT
cana-4791	281	1	[	[	X
cana-4791	281	2	19	19	NUM
cana-4791	281	3	]	]	X
cana-4791	281	4	liu	liu	PROPN
cana-4791	281	5	,	,	PUNCT
cana-4791	281	6	x.	x.	PROPN
cana-4791	281	7	;	;	PUNCT
cana-4791	281	8	ma	ma	PROPN
cana-4791	281	9	,	,	PUNCT
cana-4791	281	10	z.	z.	PROPN
cana-4791	281	11	;	;	PUNCT
cana-4791	281	12	ma	ma	PROPN
cana-4791	281	13	,	,	PUNCT
cana-4791	281	14	j.	j.	PROPN
cana-4791	281	15	;	;	PUNCT
cana-4791	281	16	zhang	zhang	PROPN
cana-4791	281	17	,	,	PUNCT
cana-4791	281	18	j.	j.	PROPN
cana-4791	281	19	;	;	PUNCT
cana-4791	281	20	schaefer	schaefer	PROPN
cana-4791	281	21	,	,	PUNCT
cana-4791	281	22	g.	g.	PROPN
cana-4791	281	23	;	;	PUNCT
cana-4791	281	24	fang	fang	X
cana-4791	281	25	,	,	PUNCT
cana-4791	281	26	h.	h.	PROPN
cana-4791	281	27	image	image	PROPN
cana-4791	281	28	disentanglement	disentanglement	NOUN
cana-4791	281	29	autoencoder	autoencoder	NOUN
cana-4791	281	30	for	for	ADP
cana-4791	281	31	steganography	steganography	NOUN
cana-4791	281	32	without	without	ADP
cana-4791	281	33	embedding	embed	VERB
cana-4791	281	34	.	.	PUNCT
cana-4791	282	1	in	in	ADP
cana-4791	282	2	proceedings	proceeding	NOUN
cana-4791	282	3	of	of	ADP
cana-4791	282	4	the	the	DET
cana-4791	282	5	ieee	ieee	NOUN
cana-4791	282	6	/	/	SYM
cana-4791	282	7	cvf	cvf	NOUN
cana-4791	282	8	conference	conference	NOUN
cana-4791	282	9	on	on	ADP
cana-4791	282	10	computer	computer	NOUN
cana-4791	282	11	vision	vision	NOUN
cana-4791	282	12	and	and	CCONJ
cana-4791	282	13	pattern	pattern	NOUN
cana-4791	282	14	recognition	recognition	NOUN
cana-4791	282	15	,	,	PUNCT
cana-4791	282	16	new	new	PROPN
cana-4791	282	17	orleans	orleans	PROPN
cana-4791	282	18	,	,	PUNCT
cana-4791	282	19	la	la	PROPN
cana-4791	282	20	,	,	PUNCT
cana-4791	282	21	usa	usa	PROPN
cana-4791	282	22	,	,	PUNCT
cana-4791	282	23	18–24	18–24	NUM
cana-4791	282	24	june	june	PROPN
cana-4791	282	25	2022	2022	NUM
cana-4791	282	26	;	;	PUNCT
cana-4791	282	27	pp	pp	ADP
cana-4791	282	28	.	.	PUNCT
cana-4791	283	1	2303–2312	2303–2312	NUM
cana-4791	283	2	.	.	PUNCT