id	sid	tid	token	lemma	pos
easat-3732	1	1	edelweiss	edelweiss	PROPN
easat-3732	1	2	applied	apply	VERB
easat-3732	1	3	science	science	NOUN
easat-3732	1	4	and	and	CCONJ
easat-3732	1	5	technology	technology	NOUN
easat-3732	1	6	issn	issn	PROPN
easat-3732	1	7	:	:	PUNCT
easat-3732	1	8	2576	2576	NUM
easat-3732	1	9	-	-	SYM
easat-3732	1	10	8484	8484	NUM
easat-3732	1	11	vol	vol	NOUN
easat-3732	1	12	.	.	PROPN
easat-3732	1	13	8	8	NUM
easat-3732	1	14	,	,	PUNCT
easat-3732	1	15	no	no	INTJ
easat-3732	1	16	.	.	NOUN
easat-3732	1	17	6	6	NUM
easat-3732	1	18	,	,	PUNCT
easat-3732	1	19	7951	7951	NUM
easat-3732	1	20	-	-	SYM
easat-3732	1	21	7970	7970	NUM
easat-3732	1	22	2024	2024	NUM
easat-3732	1	23	publisher	publisher	NOUN
easat-3732	1	24	:	:	PUNCT
easat-3732	1	25	learning	learn	VERB
easat-3732	1	26	gate	gate	NOUN
easat-3732	1	27	doi	doi	PROPN
easat-3732	1	28	:	:	PUNCT
easat-3732	1	29	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	1	30	©	©	ADP
easat-3732	1	31	2024	2024	NUM
easat-3732	1	32	by	by	ADP
easat-3732	1	33	the	the	DET
easat-3732	1	34	authors	author	NOUN
easat-3732	1	35	;	;	PUNCT
easat-3732	1	36	licensee	licensee	PROPN
easat-3732	1	37	learning	learning	NOUN
easat-3732	1	38	gate	gate	NOUN
easat-3732	1	39	©	©	PROPN
easat-3732	1	40	2024	2024	NUM
easat-3732	1	41	by	by	ADP
easat-3732	1	42	the	the	DET
easat-3732	1	43	authors	author	NOUN
easat-3732	1	44	;	;	PUNCT
easat-3732	1	45	licensee	licensee	PROPN
easat-3732	1	46	learning	learn	VERB
easat-3732	1	47	gate	gate	NOUN
easat-3732	1	48	*	*	PUNCT
easat-3732	1	49	correspondence	correspondence	NOUN
easat-3732	1	50	:	:	PUNCT
easat-3732	1	51	ashishgor.ce@ddu.ac.in	ashishgor.ce@ddu.ac.in	NUM
easat-3732	1	52	two	two	NUM
easat-3732	1	53	self	self	NOUN
easat-3732	1	54	-	-	PUNCT
easat-3732	1	55	supervised	supervise	VERB
easat-3732	1	56	image	image	NOUN
easat-3732	1	57	denoiser	denoiser	NOUN
easat-3732	1	58	designs	design	NOUN
easat-3732	1	59	with	with	ADP
easat-3732	1	60	discrete	discrete	ADJ
easat-3732	1	61	wavelet	wavelet	NOUN
easat-3732	1	62	transform	transform	NOUN
easat-3732	1	63	and	and	CCONJ
easat-3732	1	64	non	non	ADJ
easat-3732	1	65	-	-	ADJ
easat-3732	1	66	local	local	ADJ
easat-3732	1	67	means	mean	NOUN
easat-3732	1	68	-	-	PUNCT
easat-3732	1	69	based	base	VERB
easat-3732	1	70	algorithms	algorithm	NOUN
easat-3732	1	71	ashishkumar	ashishkumar	PROPN
easat-3732	1	72	gor1	gor1	PROPN
easat-3732	1	73	*	*	PROPN
easat-3732	1	74	,	,	PUNCT
easat-3732	1	75	c.k	c.k	PROPN
easat-3732	1	76	.	.	PUNCT
easat-3732	2	1	bhensdadia2	bhensdadia2	PROPN
easat-3732	2	2	1,2computer	1,2computer	NUM
easat-3732	2	3	engineering	engineering	NOUN
easat-3732	2	4	,	,	PUNCT
easat-3732	2	5	dharmsinh	dharmsinh	PROPN
easat-3732	2	6	desai	desai	PROPN
easat-3732	2	7	university	university	PROPN
easat-3732	2	8	,	,	PUNCT
easat-3732	2	9	nadiad	nadiad	NOUN
easat-3732	2	10	,	,	PUNCT
easat-3732	2	11	387001	387001	NUM
easat-3732	2	12	,	,	PUNCT
easat-3732	2	13	gujarat	gujarat	PROPN
easat-3732	2	14	,	,	PUNCT
easat-3732	2	15	india	india	PROPN
easat-3732	2	16	;	;	PUNCT
easat-3732	2	17	ashishgor.ce@ddu.ac.in	ashishgor.ce@ddu.ac.in	NUM
easat-3732	3	1	(	(	PUNCT
easat-3732	3	2	a.g	a.g	PROPN
easat-3732	3	3	.	.	PROPN
easat-3732	3	4	)	)	PUNCT
easat-3732	3	5	ckbhensdadia@ddu.ac.in	ckbhensdadia@ddu.ac.in	NOUN
easat-3732	3	6	(	(	PUNCT
easat-3732	3	7	c.k.b	c.k.b	NOUN
easat-3732	3	8	.	.	PUNCT
easat-3732	3	9	)	)	PUNCT
easat-3732	3	10	.	.	PUNCT
easat-3732	4	1	abstract	abstract	ADJ
easat-3732	4	2	:	:	PUNCT
easat-3732	4	3	image	image	NOUN
easat-3732	4	4	denoising	denoising	NOUN
easat-3732	4	5	is	be	AUX
easat-3732	4	6	crucial	crucial	ADJ
easat-3732	4	7	in	in	ADP
easat-3732	4	8	applications	application	NOUN
easat-3732	4	9	like	like	ADP
easat-3732	4	10	medical	medical	ADJ
easat-3732	4	11	imaging	imaging	NOUN
easat-3732	4	12	and	and	CCONJ
easat-3732	4	13	photography	photography	NOUN
easat-3732	4	14	,	,	PUNCT
easat-3732	4	15	where	where	SCONJ
easat-3732	4	16	restoring	restore	VERB
easat-3732	4	17	high	high	ADJ
easat-3732	4	18	-	-	PUNCT
easat-3732	4	19	quality	quality	NOUN
easat-3732	4	20	images	image	NOUN
easat-3732	4	21	from	from	ADP
easat-3732	4	22	noisy	noisy	ADJ
easat-3732	4	23	data	datum	NOUN
easat-3732	4	24	is	be	AUX
easat-3732	4	25	essential	essential	ADJ
easat-3732	4	26	.	.	PUNCT
easat-3732	5	1	traditional	traditional	ADJ
easat-3732	5	2	techniques	technique	NOUN
easat-3732	5	3	often	often	ADV
easat-3732	5	4	struggle	struggle	VERB
easat-3732	5	5	with	with	ADP
easat-3732	5	6	complex	complex	ADJ
easat-3732	5	7	noise	noise	NOUN
easat-3732	5	8	patterns	pattern	NOUN
easat-3732	5	9	,	,	PUNCT
easat-3732	5	10	while	while	SCONJ
easat-3732	5	11	deep	deep	ADJ
easat-3732	5	12	learning	learning	NOUN
easat-3732	5	13	-	-	PUNCT
easat-3732	5	14	based	base	VERB
easat-3732	5	15	methods	method	NOUN
easat-3732	5	16	typically	typically	ADV
easat-3732	5	17	rely	rely	VERB
easat-3732	5	18	on	on	ADP
easat-3732	5	19	clean	clean	ADJ
easat-3732	5	20	-	-	PUNCT
easat-3732	5	21	noisy	noisy	ADJ
easat-3732	5	22	image	image	NOUN
easat-3732	5	23	pairs	pair	NOUN
easat-3732	5	24	for	for	ADP
easat-3732	5	25	training	training	NOUN
easat-3732	5	26	,	,	PUNCT
easat-3732	5	27	limiting	limit	VERB
easat-3732	5	28	their	their	PRON
easat-3732	5	29	practicality	practicality	NOUN
easat-3732	5	30	.	.	PUNCT
easat-3732	6	1	additionally	additionally	ADV
easat-3732	6	2	,	,	PUNCT
easat-3732	6	3	deep	deep	ADJ
easat-3732	6	4	learning	learning	NOUN
easat-3732	6	5	approaches	approach	NOUN
easat-3732	6	6	face	face	VERB
easat-3732	6	7	challenges	challenge	NOUN
easat-3732	6	8	such	such	ADJ
easat-3732	6	9	as	as	ADP
easat-3732	6	10	the	the	DET
easat-3732	6	11	lack	lack	NOUN
easat-3732	6	12	of	of	ADP
easat-3732	6	13	ground	ground	NOUN
easat-3732	6	14	truth	truth	NOUN
easat-3732	6	15	clean	clean	ADJ
easat-3732	6	16	images	image	NOUN
easat-3732	6	17	,	,	PUNCT
easat-3732	6	18	sensitivity	sensitivity	NOUN
easat-3732	6	19	to	to	ADP
easat-3732	6	20	specific	specific	ADJ
easat-3732	6	21	noise	noise	NOUN
easat-3732	6	22	types	type	NOUN
easat-3732	6	23	,	,	PUNCT
easat-3732	6	24	and	and	CCONJ
easat-3732	6	25	the	the	DET
easat-3732	6	26	introduction	introduction	NOUN
easat-3732	6	27	of	of	ADP
easat-3732	6	28	artifacts	artifact	NOUN
easat-3732	6	29	during	during	ADP
easat-3732	6	30	processing	processing	NOUN
easat-3732	6	31	.	.	PUNCT
easat-3732	7	1	in	in	ADP
easat-3732	7	2	this	this	DET
easat-3732	7	3	work	work	NOUN
easat-3732	7	4	,	,	PUNCT
easat-3732	7	5	we	we	PRON
easat-3732	7	6	propose	propose	VERB
easat-3732	7	7	two	two	NUM
easat-3732	7	8	novel	novel	NOUN
easat-3732	7	9	self	self	NOUN
easat-3732	7	10	-	-	PUNCT
easat-3732	7	11	supervised	supervise	VERB
easat-3732	7	12	denoising	denoising	NOUN
easat-3732	7	13	approaches	approach	NOUN
easat-3732	7	14	:	:	PUNCT
easat-3732	7	15	a	a	DET
easat-3732	7	16	discrete	discrete	ADJ
easat-3732	7	17	wavelet	wavelet	NOUN
easat-3732	7	18	transform	transform	NOUN
easat-3732	7	19	(	(	PUNCT
easat-3732	7	20	dwt)-based	dwt)-base	VERB
easat-3732	7	21	model	model	NOUN
easat-3732	7	22	and	and	CCONJ
easat-3732	7	23	a	a	DET
easat-3732	7	24	non	non	ADJ
easat-3732	7	25	-	-	ADJ
easat-3732	7	26	local	local	ADJ
easat-3732	7	27	means	mean	NOUN
easat-3732	7	28	(	(	PUNCT
easat-3732	7	29	nlm)-based	nlm)-base	VERB
easat-3732	7	30	model	model	NOUN
easat-3732	7	31	.	.	PUNCT
easat-3732	8	1	the	the	DET
easat-3732	8	2	dwtbased	dwtbase	VERB
easat-3732	8	3	approach	approach	NOUN
easat-3732	8	4	employs	employ	VERB
easat-3732	8	5	wavelet	wavelet	NOUN
easat-3732	8	6	decomposition	decomposition	NOUN
easat-3732	8	7	to	to	PART
easat-3732	8	8	separate	separate	VERB
easat-3732	8	9	image	image	NOUN
easat-3732	8	10	details	detail	NOUN
easat-3732	8	11	across	across	ADP
easat-3732	8	12	multiple	multiple	ADJ
easat-3732	8	13	frequency	frequency	NOUN
easat-3732	8	14	scales	scale	NOUN
easat-3732	8	15	,	,	PUNCT
easat-3732	8	16	selectively	selectively	ADV
easat-3732	8	17	suppressing	suppress	VERB
easat-3732	8	18	high	high	ADJ
easat-3732	8	19	-	-	PUNCT
easat-3732	8	20	frequency	frequency	NOUN
easat-3732	8	21	noise	noise	NOUN
easat-3732	8	22	via	via	ADP
easat-3732	8	23	soft	soft	ADJ
easat-3732	8	24	thresholding	thresholding	NOUN
easat-3732	8	25	while	while	SCONJ
easat-3732	8	26	preserving	preserve	VERB
easat-3732	8	27	lowfrequency	lowfrequency	NOUN
easat-3732	8	28	components	component	NOUN
easat-3732	8	29	.	.	PUNCT
easat-3732	9	1	the	the	DET
easat-3732	9	2	resulting	result	VERB
easat-3732	9	3	wavelet	wavelet	NOUN
easat-3732	9	4	coefficients	coefficient	NOUN
easat-3732	9	5	are	be	AUX
easat-3732	9	6	used	use	VERB
easat-3732	9	7	to	to	PART
easat-3732	9	8	create	create	VERB
easat-3732	9	9	pseudo	pseudo	NOUN
easat-3732	9	10	-	-	ADJ
easat-3732	9	11	clean	clean	ADJ
easat-3732	9	12	targets	target	NOUN
easat-3732	9	13	for	for	ADP
easat-3732	9	14	training	train	VERB
easat-3732	9	15	a	a	DET
easat-3732	9	16	u	u	ADJ
easat-3732	9	17	-	-	ADJ
easat-3732	9	18	net	net	ADJ
easat-3732	9	19	architecture	architecture	NOUN
easat-3732	9	20	,	,	PUNCT
easat-3732	9	21	ensuring	ensure	VERB
easat-3732	9	22	effective	effective	ADJ
easat-3732	9	23	denoising	denoising	NOUN
easat-3732	9	24	while	while	SCONJ
easat-3732	9	25	maintaining	maintain	VERB
easat-3732	9	26	structural	structural	ADJ
easat-3732	9	27	integrity	integrity	NOUN
easat-3732	9	28	.	.	PUNCT
easat-3732	10	1	the	the	DET
easat-3732	10	2	nlm	nlm	NOUN
easat-3732	10	3	-	-	PUNCT
easat-3732	10	4	based	base	VERB
easat-3732	10	5	approach	approach	NOUN
easat-3732	10	6	leverages	leverage	VERB
easat-3732	10	7	redundancy	redundancy	NOUN
easat-3732	10	8	in	in	ADP
easat-3732	10	9	image	image	NOUN
easat-3732	10	10	patches	patch	NOUN
easat-3732	10	11	by	by	ADP
easat-3732	10	12	applying	apply	VERB
easat-3732	10	13	the	the	DET
easat-3732	10	14	nlm	nlm	PROPN
easat-3732	10	15	algorithm	algorithm	NOUN
easat-3732	10	16	to	to	PART
easat-3732	10	17	generate	generate	VERB
easat-3732	10	18	pseudo	pseudo	NOUN
easat-3732	10	19	-	-	ADJ
easat-3732	10	20	clean	clean	ADJ
easat-3732	10	21	targets	target	NOUN
easat-3732	10	22	through	through	ADP
easat-3732	10	23	patch	patch	ADJ
easat-3732	10	24	similarity	similarity	NOUN
easat-3732	10	25	-	-	PUNCT
easat-3732	10	26	based	base	VERB
easat-3732	10	27	averaging	averaging	NOUN
easat-3732	10	28	.	.	PUNCT
easat-3732	11	1	these	these	DET
easat-3732	11	2	targets	target	NOUN
easat-3732	11	3	train	train	VERB
easat-3732	11	4	a	a	DET
easat-3732	11	5	u	u	ADJ
easat-3732	11	6	-	-	ADJ
easat-3732	11	7	net	net	ADJ
easat-3732	11	8	model	model	NOUN
easat-3732	11	9	with	with	ADP
easat-3732	11	10	a	a	DET
easat-3732	11	11	custom	custom	NOUN
easat-3732	11	12	loss	loss	NOUN
easat-3732	11	13	function	function	NOUN
easat-3732	11	14	that	that	SCONJ
easat-3732	11	15	balances	balance	NOUN
easat-3732	11	16	mean	mean	VERB
easat-3732	11	17	squared	square	VERB
easat-3732	11	18	error	error	NOUN
easat-3732	11	19	(	(	PUNCT
easat-3732	11	20	mse	mse	NOUN
easat-3732	11	21	)	)	PUNCT
easat-3732	11	22	,	,	PUNCT
easat-3732	11	23	peak	peak	NOUN
easat-3732	11	24	signal	signal	NOUN
easat-3732	11	25	-	-	PUNCT
easat-3732	11	26	to	to	ADP
easat-3732	11	27	-	-	PUNCT
easat-3732	11	28	noise	noise	NOUN
easat-3732	11	29	ratio	ratio	NOUN
easat-3732	11	30	(	(	PUNCT
easat-3732	11	31	psnr	psnr	NOUN
easat-3732	11	32	)	)	PUNCT
easat-3732	11	33	,	,	PUNCT
easat-3732	11	34	and	and	CCONJ
easat-3732	11	35	structural	structural	ADJ
easat-3732	11	36	similarity	similarity	NOUN
easat-3732	11	37	index	index	NOUN
easat-3732	11	38	(	(	PUNCT
easat-3732	11	39	ssim	ssim	NOUN
easat-3732	11	40	)	)	PUNCT
easat-3732	11	41	,	,	PUNCT
easat-3732	11	42	optimizing	optimize	VERB
easat-3732	11	43	perceptual	perceptual	ADJ
easat-3732	11	44	quality	quality	NOUN
easat-3732	11	45	.	.	PUNCT
easat-3732	12	1	both	both	DET
easat-3732	12	2	models	model	NOUN
easat-3732	12	3	are	be	AUX
easat-3732	12	4	trained	train	VERB
easat-3732	12	5	on	on	ADP
easat-3732	12	6	5,000	5,000	NUM
easat-3732	12	7	noisy	noisy	ADJ
easat-3732	12	8	images	image	NOUN
easat-3732	12	9	from	from	ADP
easat-3732	12	10	the	the	DET
easat-3732	12	11	imagenet	imagenet	NOUN
easat-3732	12	12	validation	validation	NOUN
easat-3732	12	13	set	set	VERB
easat-3732	12	14	without	without	ADP
easat-3732	12	15	relying	rely	VERB
easat-3732	12	16	on	on	ADP
easat-3732	12	17	clean	clean	ADJ
easat-3732	12	18	references	reference	NOUN
easat-3732	12	19	.	.	PUNCT
easat-3732	13	1	validated	validate	VERB
easat-3732	13	2	on	on	ADP
easat-3732	13	3	synthetic	synthetic	ADJ
easat-3732	13	4	gaussian	gaussian	NOUN
easat-3732	13	5	and	and	CCONJ
easat-3732	13	6	poisson	poisson	NOUN
easat-3732	13	7	noise	noise	NOUN
easat-3732	13	8	at	at	ADP
easat-3732	13	9	varying	vary	VERB
easat-3732	13	10	magnitudes	magnitude	NOUN
easat-3732	13	11	,	,	PUNCT
easat-3732	13	12	the	the	DET
easat-3732	13	13	dwt	dwt	NOUN
easat-3732	13	14	-	-	PUNCT
easat-3732	13	15	based	base	VERB
easat-3732	13	16	model	model	NOUN
easat-3732	13	17	achieved	achieve	VERB
easat-3732	13	18	mean	mean	PROPN
easat-3732	13	19	psnr	psnr	NOUN
easat-3732	13	20	and	and	CCONJ
easat-3732	13	21	ssim	ssim	NOUN
easat-3732	13	22	values	value	NOUN
easat-3732	13	23	of	of	ADP
easat-3732	13	24	31.07	31.07	NUM
easat-3732	13	25	and	and	CCONJ
easat-3732	13	26	0.9279	0.9279	NUM
easat-3732	13	27	,	,	PUNCT
easat-3732	13	28	respectively	respectively	ADV
easat-3732	13	29	,	,	PUNCT
easat-3732	13	30	while	while	SCONJ
easat-3732	13	31	the	the	DET
easat-3732	13	32	nlm	nlm	NOUN
easat-3732	13	33	-	-	PUNCT
easat-3732	13	34	based	base	VERB
easat-3732	13	35	model	model	NOUN
easat-3732	13	36	attained	attain	VERB
easat-3732	13	37	30.17	30.17	NUM
easat-3732	13	38	and	and	CCONJ
easat-3732	13	39	0.9303	0.9303	NUM
easat-3732	13	40	.	.	PUNCT
easat-3732	14	1	these	these	DET
easat-3732	14	2	results	result	NOUN
easat-3732	14	3	demonstrate	demonstrate	VERB
easat-3732	14	4	the	the	DET
easat-3732	14	5	robustness	robustness	NOUN
easat-3732	14	6	and	and	CCONJ
easat-3732	14	7	effectiveness	effectiveness	NOUN
easat-3732	14	8	of	of	ADP
easat-3732	14	9	the	the	DET
easat-3732	14	10	proposed	propose	VERB
easat-3732	14	11	methods	method	NOUN
easat-3732	14	12	,	,	PUNCT
easat-3732	14	13	making	make	VERB
easat-3732	14	14	them	they	PRON
easat-3732	14	15	suitable	suitable	ADJ
easat-3732	14	16	for	for	ADP
easat-3732	14	17	real	real	ADJ
easat-3732	14	18	-	-	PUNCT
easat-3732	14	19	world	world	NOUN
easat-3732	14	20	applications	application	NOUN
easat-3732	14	21	such	such	ADJ
easat-3732	14	22	as	as	ADP
easat-3732	14	23	medical	medical	ADJ
easat-3732	14	24	diagnostics	diagnostic	NOUN
easat-3732	14	25	and	and	CCONJ
easat-3732	14	26	low	low	ADJ
easat-3732	14	27	-	-	PUNCT
easat-3732	14	28	light	light	NOUN
easat-3732	14	29	photography	photography	NOUN
easat-3732	14	30	.	.	PUNCT
easat-3732	15	1	keywords	keyword	NOUN
easat-3732	15	2	:	:	PUNCT
easat-3732	15	3	discrete	discrete	ADJ
easat-3732	15	4	wavelet	wavelet	NOUN
easat-3732	15	5	transforms	transform	VERB
easat-3732	15	6	(	(	PUNCT
easat-3732	15	7	dwt	dwt	NOUN
easat-3732	15	8	)	)	PUNCT
easat-3732	15	9	,	,	PUNCT
easat-3732	15	10	gaussian	gaussian	NOUN
easat-3732	15	11	noise	noise	NOUN
easat-3732	15	12	,	,	PUNCT
easat-3732	15	13	poisson	poisson	NOUN
easat-3732	15	14	noise	noise	NOUN
easat-3732	15	15	,	,	PUNCT
easat-3732	15	16	haar	haar	PROPN
easat-3732	15	17	wavelet	wavelet	PROPN
easat-3732	15	18	,	,	PUNCT
easat-3732	15	19	debauchies	debauchie	NOUN
easat-3732	15	20	wavelet	wavelet	NOUN
easat-3732	15	21	,	,	PUNCT
easat-3732	15	22	image	image	NOUN
easat-3732	15	23	denoising	denoising	NOUN
easat-3732	15	24	,	,	PUNCT
easat-3732	15	25	non	non	ADJ
easat-3732	15	26	-	-	ADJ
easat-3732	15	27	local	local	ADJ
easat-3732	15	28	means	mean	NOUN
easat-3732	15	29	(	(	PUNCT
easat-3732	15	30	nlm	nlm	PROPN
easat-3732	15	31	)	)	PUNCT
easat-3732	15	32	,	,	PUNCT
easat-3732	15	33	psnr	psnr	NOUN
easat-3732	15	34	(	(	PUNCT
easat-3732	15	35	peak	peak	NOUN
easat-3732	15	36	signal	signal	NOUN
easat-3732	15	37	-	-	PUNCT
easat-3732	15	38	to	to	ADP
easat-3732	15	39	-	-	PUNCT
easat-3732	15	40	noise	noise	NOUN
easat-3732	15	41	ratio	ratio	NOUN
easat-3732	15	42	)	)	PUNCT
easat-3732	15	43	,	,	PUNCT
easat-3732	15	44	self	self	NOUN
easat-3732	15	45	-	-	PUNCT
easat-3732	15	46	supervised	supervise	VERB
easat-3732	15	47	learning	learning	NOUN
easat-3732	15	48	,	,	PUNCT
easat-3732	15	49	ssim	ssim	NOUN
easat-3732	15	50	(	(	PUNCT
easat-3732	15	51	structural	structural	ADJ
easat-3732	15	52	similarity	similarity	NOUN
easat-3732	15	53	index	index	NOUN
easat-3732	15	54	)	)	PUNCT
easat-3732	15	55	,	,	PUNCT
easat-3732	15	56	thresholding	thresholde	VERB
easat-3732	15	57	.	.	PUNCT
easat-3732	16	1	1	1	X
easat-3732	16	2	.	.	X
easat-3732	16	3	introduction	introduction	NOUN
easat-3732	16	4	image	image	NOUN
easat-3732	16	5	denoising	denoising	NOUN
easat-3732	16	6	is	be	AUX
easat-3732	16	7	a	a	DET
easat-3732	16	8	fundamental	fundamental	ADJ
easat-3732	16	9	task	task	NOUN
easat-3732	16	10	in	in	ADP
easat-3732	16	11	computer	computer	NOUN
easat-3732	16	12	vision	vision	NOUN
easat-3732	16	13	,	,	PUNCT
easat-3732	16	14	critical	critical	ADJ
easat-3732	16	15	for	for	ADP
easat-3732	16	16	applications	application	NOUN
easat-3732	16	17	such	such	ADJ
easat-3732	16	18	as	as	ADP
easat-3732	16	19	medical	medical	ADJ
easat-3732	16	20	imaging	imaging	NOUN
easat-3732	16	21	,	,	PUNCT
easat-3732	16	22	photography	photography	NOUN
easat-3732	16	23	,	,	PUNCT
easat-3732	16	24	and	and	CCONJ
easat-3732	16	25	astronomy	astronomy	NOUN
easat-3732	16	26	,	,	PUNCT
easat-3732	16	27	where	where	SCONJ
easat-3732	16	28	image	image	NOUN
easat-3732	16	29	quality	quality	NOUN
easat-3732	16	30	significantly	significantly	ADV
easat-3732	16	31	impacts	impact	VERB
easat-3732	16	32	downstream	downstream	ADJ
easat-3732	16	33	analysis	analysis	NOUN
easat-3732	16	34	.	.	PUNCT
easat-3732	17	1	the	the	DET
easat-3732	17	2	objective	objective	NOUN
easat-3732	17	3	is	be	AUX
easat-3732	17	4	to	to	PART
easat-3732	17	5	restore	restore	VERB
easat-3732	17	6	images	image	NOUN
easat-3732	17	7	degraded	degrade	VERB
easat-3732	17	8	by	by	ADP
easat-3732	17	9	noise	noise	NOUN
easat-3732	17	10	,	,	PUNCT
easat-3732	17	11	ensuring	ensure	VERB
easat-3732	17	12	the	the	DET
easat-3732	17	13	preservation	preservation	NOUN
easat-3732	17	14	of	of	ADP
easat-3732	17	15	essential	essential	ADJ
easat-3732	17	16	features	feature	NOUN
easat-3732	17	17	.	.	PUNCT
easat-3732	18	1	traditional	traditional	ADJ
easat-3732	18	2	and	and	CCONJ
easat-3732	18	3	deep	deep	ADJ
easat-3732	18	4	learning	learning	NOUN
easat-3732	18	5	-	-	PUNCT
easat-3732	18	6	based	base	VERB
easat-3732	18	7	methods	method	NOUN
easat-3732	18	8	have	have	AUX
easat-3732	18	9	dominated	dominate	VERB
easat-3732	18	10	this	this	DET
easat-3732	18	11	field	field	NOUN
easat-3732	18	12	,	,	PUNCT
easat-3732	18	13	with	with	ADP
easat-3732	18	14	recent	recent	ADJ
easat-3732	18	15	advancements	advancement	NOUN
easat-3732	18	16	in	in	ADP
easat-3732	18	17	self	self	NOUN
easat-3732	18	18	-	-	PUNCT
easat-3732	18	19	supervised	supervise	VERB
easat-3732	18	20	learning	learning	NOUN
easat-3732	18	21	(	(	PUNCT
easat-3732	18	22	ssl	ssl	ADJ
easat-3732	18	23	)	)	PUNCT
easat-3732	18	24	offering	offer	VERB
easat-3732	18	25	robust	robust	ADJ
easat-3732	18	26	solutions	solution	NOUN
easat-3732	18	27	to	to	PART
easat-3732	18	28	address	address	VERB
easat-3732	18	29	the	the	DET
easat-3732	18	30	limitations	limitation	NOUN
easat-3732	18	31	of	of	ADP
easat-3732	18	32	clean	clean	ADJ
easat-3732	18	33	-	-	PUNCT
easat-3732	18	34	noisy	noisy	ADJ
easat-3732	18	35	paired	pair	VERB
easat-3732	18	36	datasets	dataset	NOUN
easat-3732	18	37	.	.	PUNCT
easat-3732	19	1	this	this	DET
easat-3732	19	2	section	section	NOUN
easat-3732	19	3	reviews	review	VERB
easat-3732	19	4	existing	exist	VERB
easat-3732	19	5	approaches	approach	NOUN
easat-3732	19	6	while	while	SCONJ
easat-3732	19	7	contextualizing	contextualize	VERB
easat-3732	19	8	the	the	DET
easat-3732	19	9	proposed	propose	VERB
easat-3732	19	10	methods	method	NOUN
easat-3732	19	11	based	base	VERB
easat-3732	19	12	on	on	ADP
easat-3732	19	13	the	the	DET
easat-3732	19	14	discrete	discrete	ADJ
easat-3732	19	15	wavelet	wavelet	NOUN
easat-3732	19	16	transform	transform	NOUN
easat-3732	19	17	(	(	PUNCT
easat-3732	19	18	dwt	dwt	NOUN
easat-3732	19	19	)	)	PUNCT
easat-3732	19	20	and	and	CCONJ
easat-3732	19	21	non	non	ADJ
easat-3732	19	22	-	-	ADJ
easat-3732	19	23	local	local	ADJ
easat-3732	19	24	means	mean	NOUN
easat-3732	19	25	(	(	PUNCT
easat-3732	19	26	nlm	nlm	PROPN
easat-3732	19	27	)	)	PUNCT
easat-3732	19	28	.	.	PUNCT
easat-3732	20	1	traditional	traditional	ADJ
easat-3732	20	2	denoising	denoising	NOUN
easat-3732	20	3	methods	method	NOUN
easat-3732	20	4	:	:	PUNCT
easat-3732	20	5	traditional	traditional	ADJ
easat-3732	20	6	denoisers	denoiser	NOUN
easat-3732	20	7	rely	rely	VERB
easat-3732	20	8	on	on	ADP
easat-3732	20	9	mathematical	mathematical	ADJ
easat-3732	20	10	models	model	NOUN
easat-3732	20	11	and	and	CCONJ
easat-3732	20	12	handcrafted	handcrafted	ADJ
easat-3732	20	13	priors	prior	NOUN
easat-3732	20	14	.	.	PUNCT
easat-3732	21	1	block	block	NOUN
easat-3732	21	2	matching	matching	NOUN
easat-3732	21	3	and	and	CCONJ
easat-3732	21	4	3d	3d	NUM
easat-3732	21	5	filtering	filtering	NOUN
easat-3732	21	6	(	(	PUNCT
easat-3732	21	7	bm3d	bm3d	PROPN
easat-3732	21	8	)	)	PUNCT
easat-3732	22	1	[	[	X
easat-3732	22	2	1	1	NUM
easat-3732	22	3	]	]	X
easat-3732	22	4	groups	group	NOUN
easat-3732	22	5	similar	similar	ADJ
easat-3732	22	6	patches	patch	NOUN
easat-3732	22	7	through	through	ADP
easat-3732	22	8	block	block	NOUN
easat-3732	22	9	matching	matching	NOUN
easat-3732	22	10	and	and	CCONJ
easat-3732	22	11	applies	apply	VERB
easat-3732	22	12	collaborative	collaborative	ADJ
easat-3732	22	13	filtering	filtering	NOUN
easat-3732	22	14	in	in	ADP
easat-3732	22	15	the	the	DET
easat-3732	22	16	transform	transform	NOUN
easat-3732	22	17	domain	domain	NOUN
easat-3732	22	18	,	,	PUNCT
easat-3732	22	19	effectively	effectively	ADV
easat-3732	22	20	reducing	reduce	VERB
easat-3732	22	21	noise	noise	NOUN
easat-3732	22	22	while	while	SCONJ
easat-3732	22	23	retaining	retain	VERB
easat-3732	22	24	image	image	NOUN
easat-3732	22	25	features	feature	NOUN
easat-3732	22	26	.	.	PUNCT
easat-3732	23	1	non	non	ADJ
easat-3732	23	2	-	-	ADJ
easat-3732	23	3	local	local	ADJ
easat-3732	23	4	means	mean	NOUN
easat-3732	23	5	(	(	PUNCT
easat-3732	23	6	nlm	nlm	PROPN
easat-3732	23	7	)	)	PUNCT
easat-3732	23	8	[	[	X
easat-3732	23	9	2	2	NUM
easat-3732	23	10	-	-	SYM
easat-3732	23	11	4	4	NUM
easat-3732	23	12	]	]	PUNCT
easat-3732	23	13	improves	improve	VERB
easat-3732	23	14	upon	upon	SCONJ
easat-3732	23	15	local	local	ADJ
easat-3732	23	16	smoothing	smooth	VERB
easat-3732	23	17	techniques	technique	NOUN
easat-3732	23	18	by	by	ADP
easat-3732	23	19	averaging	average	VERB
easat-3732	23	20	pixels	pixel	NOUN
easat-3732	23	21	based	base	VERB
easat-3732	23	22	on	on	ADP
easat-3732	23	23	patch	patch	ADJ
easat-3732	23	24	similarity	similarity	NOUN
easat-3732	23	25	across	across	ADP
easat-3732	23	26	the	the	DET
easat-3732	23	27	entire	entire	ADJ
easat-3732	23	28	image	image	NOUN
easat-3732	23	29	,	,	PUNCT
easat-3732	23	30	leveraging	leverage	VERB
easat-3732	23	31	spatial	spatial	ADJ
easat-3732	23	32	redundancy	redundancy	NOUN
easat-3732	23	33	to	to	ADP
easat-3732	23	34	7952	7952	NUM
easat-3732	23	35	edelweiss	edelweiss	PROPN
easat-3732	23	36	applied	apply	VERB
easat-3732	23	37	science	science	NOUN
easat-3732	23	38	and	and	CCONJ
easat-3732	23	39	technology	technology	NOUN
easat-3732	23	40	issn	issn	PROPN
easat-3732	23	41	:	:	PUNCT
easat-3732	23	42	2576	2576	NUM
easat-3732	23	43	-	-	SYM
easat-3732	23	44	8484	8484	NUM
easat-3732	23	45	vol	vol	NOUN
easat-3732	23	46	.	.	PROPN
easat-3732	24	1	8	8	NUM
easat-3732	24	2	,	,	PUNCT
easat-3732	24	3	no	no	INTJ
easat-3732	24	4	.	.	NOUN
easat-3732	25	1	6	6	NUM
easat-3732	25	2	:	:	PUNCT
easat-3732	25	3	7951	7951	NUM
easat-3732	25	4	-	-	SYM
easat-3732	25	5	7970	7970	NUM
easat-3732	25	6	,	,	PUNCT
easat-3732	25	7	2024	2024	NUM
easat-3732	25	8	doi	doi	NOUN
easat-3732	25	9	:	:	PUNCT
easat-3732	25	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	25	11	©	©	ADP
easat-3732	25	12	2024	2024	NUM
easat-3732	25	13	by	by	ADP
easat-3732	25	14	the	the	DET
easat-3732	25	15	authors	author	NOUN
easat-3732	25	16	;	;	PUNCT
easat-3732	25	17	licensee	licensee	PROPN
easat-3732	25	18	learning	learn	VERB
easat-3732	25	19	gate	gate	NOUN
easat-3732	25	20	enhance	enhance	PROPN
easat-3732	25	21	detail	detail	NOUN
easat-3732	25	22	preservation	preservation	NOUN
easat-3732	25	23	.	.	PUNCT
easat-3732	26	1	weighted	weight	VERB
easat-3732	26	2	nuclear	nuclear	ADJ
easat-3732	26	3	norm	norm	NOUN
easat-3732	26	4	minimization	minimization	NOUN
easat-3732	26	5	(	(	PUNCT
easat-3732	26	6	wnnm	wnnm	NOUN
easat-3732	26	7	)	)	PUNCT
easat-3732	27	1	[	[	X
easat-3732	27	2	5	5	NUM
easat-3732	27	3	]	]	PUNCT
easat-3732	27	4	adopts	adopt	VERB
easat-3732	27	5	low	low	ADJ
easat-3732	27	6	-	-	PUNCT
easat-3732	27	7	rank	rank	NOUN
easat-3732	27	8	matrix	matrix	NOUN
easat-3732	27	9	approximations	approximation	NOUN
easat-3732	27	10	,	,	PUNCT
easat-3732	27	11	preserving	preserve	VERB
easat-3732	27	12	image	image	NOUN
easat-3732	27	13	structures	structure	NOUN
easat-3732	27	14	while	while	SCONJ
easat-3732	27	15	suppressing	suppress	VERB
easat-3732	27	16	noise	noise	NOUN
easat-3732	27	17	.	.	PUNCT
easat-3732	28	1	despite	despite	SCONJ
easat-3732	28	2	their	their	PRON
easat-3732	28	3	effectiveness	effectiveness	NOUN
easat-3732	28	4	,	,	PUNCT
easat-3732	28	5	these	these	DET
easat-3732	28	6	methods	method	NOUN
easat-3732	28	7	struggle	struggle	VERB
easat-3732	28	8	with	with	ADP
easat-3732	28	9	high	high	ADJ
easat-3732	28	10	computational	computational	ADJ
easat-3732	28	11	costs	cost	NOUN
easat-3732	28	12	and	and	CCONJ
easat-3732	28	13	adapting	adapt	VERB
easat-3732	28	14	to	to	ADP
easat-3732	28	15	complex	complex	ADJ
easat-3732	28	16	noise	noise	NOUN
easat-3732	28	17	patterns	pattern	NOUN
easat-3732	28	18	in	in	ADP
easat-3732	28	19	real	real	ADJ
easat-3732	28	20	-	-	PUNCT
easat-3732	28	21	world	world	NOUN
easat-3732	28	22	scenarios	scenario	NOUN
easat-3732	28	23	.	.	PUNCT
easat-3732	29	1	supervised	supervise	VERB
easat-3732	29	2	learning	learn	VERB
easat-3732	29	3	for	for	ADP
easat-3732	29	4	image	image	NOUN
easat-3732	29	5	denoising	denoising	NOUN
easat-3732	29	6	:	:	PUNCT
easat-3732	29	7	the	the	DET
easat-3732	29	8	advent	advent	NOUN
easat-3732	29	9	of	of	ADP
easat-3732	29	10	deep	deep	ADJ
easat-3732	29	11	learning	learning	NOUN
easat-3732	29	12	introduced	introduce	VERB
easat-3732	29	13	supervised	supervised	ADJ
easat-3732	29	14	models	model	NOUN
easat-3732	29	15	like	like	ADP
easat-3732	29	16	dncnn	dncnn	PROPN
easat-3732	29	17	[	[	X
easat-3732	29	18	6	6	NUM
easat-3732	29	19	]	]	PUNCT
easat-3732	29	20	,	,	PUNCT
easat-3732	29	21	which	which	PRON
easat-3732	29	22	combines	combine	VERB
easat-3732	29	23	convolutional	convolutional	ADJ
easat-3732	29	24	networks	network	NOUN
easat-3732	29	25	with	with	ADP
easat-3732	29	26	residual	residual	ADJ
easat-3732	29	27	learning	learning	NOUN
easat-3732	29	28	to	to	PART
easat-3732	29	29	map	map	VERB
easat-3732	29	30	noisy	noisy	ADJ
easat-3732	29	31	images	image	NOUN
easat-3732	29	32	to	to	ADP
easat-3732	29	33	clean	clean	ADJ
easat-3732	29	34	counterparts	counterpart	NOUN
easat-3732	29	35	.	.	PUNCT
easat-3732	30	1	while	while	SCONJ
easat-3732	30	2	these	these	DET
easat-3732	30	3	methods	method	NOUN
easat-3732	30	4	outperform	outperform	VERB
easat-3732	30	5	traditional	traditional	ADJ
easat-3732	30	6	approaches	approach	NOUN
easat-3732	30	7	,	,	PUNCT
easat-3732	30	8	they	they	PRON
easat-3732	30	9	depend	depend	VERB
easat-3732	30	10	on	on	ADP
easat-3732	30	11	large	large	ADJ
easat-3732	30	12	paired	pair	VERB
easat-3732	30	13	datasets	dataset	NOUN
easat-3732	30	14	,	,	PUNCT
easat-3732	30	15	which	which	PRON
easat-3732	30	16	are	be	AUX
easat-3732	30	17	expensive	expensive	ADJ
easat-3732	30	18	and	and	CCONJ
easat-3732	30	19	challenging	challenging	ADJ
easat-3732	30	20	to	to	PART
easat-3732	30	21	acquire	acquire	VERB
easat-3732	30	22	in	in	ADP
easat-3732	30	23	specialized	specialized	ADJ
easat-3732	30	24	domains	domain	NOUN
easat-3732	30	25	.	.	PUNCT
easat-3732	31	1	additionally	additionally	ADV
easat-3732	31	2	,	,	PUNCT
easat-3732	31	3	their	their	PRON
easat-3732	31	4	performance	performance	NOUN
easat-3732	31	5	is	be	AUX
easat-3732	31	6	often	often	ADV
easat-3732	31	7	tailored	tailor	VERB
easat-3732	31	8	to	to	ADP
easat-3732	31	9	specific	specific	ADJ
easat-3732	31	10	noise	noise	NOUN
easat-3732	31	11	distributions	distribution	NOUN
easat-3732	31	12	,	,	PUNCT
easat-3732	31	13	limiting	limit	VERB
easat-3732	31	14	their	their	PRON
easat-3732	31	15	robustness	robustness	NOUN
easat-3732	31	16	to	to	ADP
easat-3732	31	17	unseen	unseen	ADJ
easat-3732	31	18	noise	noise	NOUN
easat-3732	31	19	types	type	NOUN
easat-3732	31	20	[	[	X
easat-3732	31	21	7	7	NUM
easat-3732	31	22	]	]	PUNCT
easat-3732	31	23	.	.	PUNCT
easat-3732	32	1	emergence	emergence	NOUN
easat-3732	32	2	of	of	ADP
easat-3732	32	3	self	self	NOUN
easat-3732	32	4	-	-	PUNCT
easat-3732	32	5	supervised	supervise	VERB
easat-3732	32	6	learning	learning	NOUN
easat-3732	32	7	:	:	PUNCT
easat-3732	32	8	self	self	NOUN
easat-3732	32	9	-	-	PUNCT
easat-3732	32	10	supervised	supervise	VERB
easat-3732	32	11	learning	learning	NOUN
easat-3732	32	12	eliminates	eliminate	VERB
easat-3732	32	13	the	the	DET
easat-3732	32	14	dependency	dependency	NOUN
easat-3732	32	15	on	on	ADP
easat-3732	32	16	clean	clean	ADJ
easat-3732	32	17	images	image	NOUN
easat-3732	32	18	by	by	ADP
easat-3732	32	19	training	training	NOUN
easat-3732	32	20	models	model	NOUN
easat-3732	32	21	directly	directly	ADV
easat-3732	32	22	on	on	ADP
easat-3732	32	23	noisy	noisy	ADJ
easat-3732	32	24	inputs	input	NOUN
easat-3732	32	25	.	.	PUNCT
easat-3732	33	1	noise2noise	noise2noise	PRON
easat-3732	34	1	[	[	X
easat-3732	34	2	7	7	NUM
easat-3732	34	3	]	]	PUNCT
easat-3732	34	4	,	,	PUNCT
easat-3732	34	5	a	a	DET
easat-3732	34	6	pioneering	pioneering	ADJ
easat-3732	34	7	approach	approach	NOUN
easat-3732	34	8	,	,	PUNCT
easat-3732	34	9	demonstrated	demonstrate	VERB
easat-3732	34	10	that	that	SCONJ
easat-3732	34	11	noisy	noisy	ADJ
easat-3732	34	12	images	image	NOUN
easat-3732	34	13	alone	alone	ADV
easat-3732	34	14	could	could	AUX
easat-3732	34	15	serve	serve	VERB
easat-3732	34	16	as	as	ADP
easat-3732	34	17	training	train	VERB
easat-3732	34	18	data	datum	NOUN
easat-3732	34	19	by	by	ADP
easat-3732	34	20	treating	treat	VERB
easat-3732	34	21	one	one	NUM
easat-3732	34	22	noisy	noisy	ADJ
easat-3732	34	23	image	image	NOUN
easat-3732	34	24	as	as	ADP
easat-3732	34	25	the	the	DET
easat-3732	34	26	target	target	NOUN
easat-3732	34	27	for	for	ADP
easat-3732	34	28	another	another	PRON
easat-3732	34	29	.	.	PUNCT
easat-3732	35	1	this	this	DET
easat-3732	35	2	concept	concept	NOUN
easat-3732	35	3	led	lead	VERB
easat-3732	35	4	to	to	ADP
easat-3732	35	5	blind	blind	ADJ
easat-3732	35	6	-	-	PUNCT
easat-3732	35	7	spot	spot	NOUN
easat-3732	35	8	methods	method	NOUN
easat-3732	35	9	like	like	ADP
easat-3732	35	10	noise2void	noise2void	PROPN
easat-3732	35	11	[	[	X
easat-3732	35	12	8	8	NUM
easat-3732	35	13	]	]	PUNCT
easat-3732	35	14	and	and	CCONJ
easat-3732	35	15	noise2self	noise2self	PRON
easat-3732	36	1	[	[	X
easat-3732	36	2	9	9	NUM
easat-3732	36	3	]	]	PUNCT
easat-3732	36	4	,	,	PUNCT
easat-3732	37	1	which	which	DET
easat-3732	37	2	train	train	NOUN
easat-3732	37	3	models	model	NOUN
easat-3732	37	4	by	by	ADP
easat-3732	37	5	masking	mask	VERB
easat-3732	37	6	certain	certain	ADJ
easat-3732	37	7	pixels	pixel	NOUN
easat-3732	37	8	or	or	CCONJ
easat-3732	37	9	regions	region	NOUN
easat-3732	37	10	during	during	ADP
easat-3732	37	11	prediction	prediction	NOUN
easat-3732	38	1	.	.	PUNCT
easat-3732	39	1	these	these	DET
easat-3732	39	2	methods	method	NOUN
easat-3732	39	3	leverage	leverage	VERB
easat-3732	39	4	the	the	DET
easat-3732	39	5	intrinsic	intrinsic	ADJ
easat-3732	39	6	structure	structure	NOUN
easat-3732	39	7	of	of	ADP
easat-3732	39	8	the	the	DET
easat-3732	39	9	image	image	NOUN
easat-3732	39	10	to	to	PART
easat-3732	39	11	avoid	avoid	VERB
easat-3732	39	12	learning	learn	VERB
easat-3732	39	13	identity	identity	NOUN
easat-3732	39	14	mappings	mapping	NOUN
easat-3732	39	15	,	,	PUNCT
easat-3732	39	16	achieving	achieve	VERB
easat-3732	39	17	robust	robust	ADJ
easat-3732	39	18	denoising	denoising	NOUN
easat-3732	39	19	without	without	ADP
easat-3732	39	20	paired	pair	VERB
easat-3732	39	21	data	datum	NOUN
easat-3732	39	22	.	.	PUNCT
easat-3732	40	1	wavelet	wavelet	NOUN
easat-3732	40	2	-	-	PUNCT
easat-3732	40	3	based	base	VERB
easat-3732	40	4	denoising	denoising	NOUN
easat-3732	40	5	:	:	PUNCT
easat-3732	40	6	wavelet	wavelet	NOUN
easat-3732	40	7	transforms	transform	VERB
easat-3732	40	8	,	,	PUNCT
easat-3732	40	9	particularly	particularly	ADV
easat-3732	40	10	discrete	discrete	ADJ
easat-3732	40	11	wavelet	wavelet	NOUN
easat-3732	40	12	transform	transform	NOUN
easat-3732	40	13	(	(	PUNCT
easat-3732	40	14	dwt	dwt	NOUN
easat-3732	40	15	)	)	PUNCT
easat-3732	40	16	,	,	PUNCT
easat-3732	40	17	provide	provide	VERB
easat-3732	40	18	a	a	DET
easat-3732	40	19	multi	multi	ADJ
easat-3732	40	20	-	-	ADJ
easat-3732	40	21	resolution	resolution	ADJ
easat-3732	40	22	framework	framework	NOUN
easat-3732	40	23	for	for	ADP
easat-3732	40	24	analysing	analyse	VERB
easat-3732	40	25	images	image	NOUN
easat-3732	40	26	at	at	ADP
easat-3732	40	27	different	different	ADJ
easat-3732	40	28	frequency	frequency	NOUN
easat-3732	40	29	scales	scale	NOUN
easat-3732	40	30	.	.	PUNCT
easat-3732	41	1	dwt	dwt	NOUN
easat-3732	41	2	decomposes	decompose	VERB
easat-3732	41	3	images	image	NOUN
easat-3732	41	4	into	into	ADP
easat-3732	41	5	approximation	approximation	NOUN
easat-3732	41	6	and	and	CCONJ
easat-3732	41	7	detail	detail	NOUN
easat-3732	41	8	coefficients	coefficient	NOUN
easat-3732	41	9	,	,	PUNCT
easat-3732	41	10	allowing	allow	VERB
easat-3732	41	11	selective	selective	ADJ
easat-3732	41	12	denoising	denoising	NOUN
easat-3732	41	13	by	by	ADP
easat-3732	41	14	thresholding	thresholde	VERB
easat-3732	41	15	high	high	ADJ
easat-3732	41	16	-	-	PUNCT
easat-3732	41	17	frequency	frequency	NOUN
easat-3732	41	18	components	component	NOUN
easat-3732	41	19	associated	associate	VERB
easat-3732	41	20	with	with	ADP
easat-3732	41	21	noise	noise	NOUN
easat-3732	41	22	.	.	PUNCT
easat-3732	42	1	wavelet	wavelet	NOUN
easat-3732	42	2	families	family	NOUN
easat-3732	42	3	like	like	ADP
easat-3732	42	4	haar	haar	PROPN
easat-3732	42	5	,	,	PUNCT
easat-3732	42	6	daubechies	daubechie	NOUN
easat-3732	42	7	,	,	PUNCT
easat-3732	42	8	and	and	CCONJ
easat-3732	42	9	symlets	symlet	NOUN
easat-3732	42	10	offer	offer	VERB
easat-3732	42	11	flexibility	flexibility	NOUN
easat-3732	42	12	for	for	ADP
easat-3732	42	13	various	various	ADJ
easat-3732	42	14	denoising	denoising	NOUN
easat-3732	42	15	tasks	task	NOUN
easat-3732	42	16	.	.	PUNCT
easat-3732	43	1	classical	classical	ADJ
easat-3732	43	2	wavelet	wavelet	NOUN
easat-3732	43	3	denoising	denoising	NOUN
easat-3732	43	4	,	,	PUNCT
easat-3732	43	5	though	though	SCONJ
easat-3732	43	6	effective	effective	ADJ
easat-3732	43	7	in	in	ADP
easat-3732	43	8	suppressing	suppress	VERB
easat-3732	43	9	noise	noise	NOUN
easat-3732	43	10	,	,	PUNCT
easat-3732	43	11	often	often	ADV
easat-3732	43	12	introduces	introduce	VERB
easat-3732	43	13	artifacts	artifact	NOUN
easat-3732	43	14	like	like	ADP
easat-3732	43	15	blurring	blur	VERB
easat-3732	43	16	and	and	CCONJ
easat-3732	43	17	ringing	ring	VERB
easat-3732	43	18	[	[	X
easat-3732	43	19	10,11	10,11	NOUN
easat-3732	43	20	]	]	PUNCT
easat-3732	43	21	.	.	PUNCT
easat-3732	44	1	recent	recent	ADJ
easat-3732	44	2	advancements	advancement	NOUN
easat-3732	44	3	integrate	integrate	VERB
easat-3732	44	4	dwt	dwt	NOUN
easat-3732	44	5	with	with	ADP
easat-3732	44	6	deep	deep	ADJ
easat-3732	44	7	learning	learning	NOUN
easat-3732	44	8	.	.	PUNCT
easat-3732	45	1	liu	liu	PROPN
easat-3732	45	2	and	and	CCONJ
easat-3732	45	3	liu	liu	PROPN
easat-3732	46	1	[	[	X
easat-3732	46	2	12	12	NUM
easat-3732	46	3	]	]	PUNCT
easat-3732	46	4	combined	combine	VERB
easat-3732	46	5	dwt	dwt	NOUN
easat-3732	46	6	with	with	ADP
easat-3732	46	7	cnns	cnn	NOUN
easat-3732	46	8	,	,	PUNCT
easat-3732	46	9	denoising	denoise	VERB
easat-3732	46	10	wavelet	wavelet	NOUN
easat-3732	46	11	coefficients	coefficient	NOUN
easat-3732	46	12	using	use	VERB
easat-3732	46	13	learned	learn	VERB
easat-3732	46	14	filters	filter	NOUN
easat-3732	46	15	,	,	PUNCT
easat-3732	46	16	achieving	achieve	VERB
easat-3732	46	17	improved	improved	ADJ
easat-3732	46	18	performance	performance	NOUN
easat-3732	46	19	compared	compare	VERB
easat-3732	46	20	to	to	ADP
easat-3732	46	21	traditional	traditional	ADJ
easat-3732	46	22	cnns	cnn	NOUN
easat-3732	46	23	.	.	PUNCT
easat-3732	47	1	however	however	ADV
easat-3732	47	2	,	,	PUNCT
easat-3732	47	3	such	such	ADJ
easat-3732	47	4	hybrid	hybrid	ADJ
easat-3732	47	5	approaches	approach	NOUN
easat-3732	47	6	often	often	ADV
easat-3732	47	7	face	face	VERB
easat-3732	47	8	computational	computational	ADJ
easat-3732	47	9	challenges	challenge	NOUN
easat-3732	47	10	.	.	PUNCT
easat-3732	48	1	non	non	ADJ
easat-3732	48	2	-	-	ADJ
easat-3732	48	3	local	local	ADJ
easat-3732	48	4	means	mean	NOUN
easat-3732	48	5	-	-	PUNCT
easat-3732	48	6	based	base	VERB
easat-3732	48	7	denoising	denoising	NOUN
easat-3732	48	8	:	:	PUNCT
easat-3732	48	9	nlm	nlm	PROPN
easat-3732	48	10	extends	extend	VERB
easat-3732	48	11	traditional	traditional	ADJ
easat-3732	48	12	spatial	spatial	ADJ
easat-3732	48	13	filtering	filtering	NOUN
easat-3732	48	14	by	by	ADP
easat-3732	48	15	averaging	average	VERB
easat-3732	48	16	pixel	pixel	ADJ
easat-3732	48	17	values	value	NOUN
easat-3732	48	18	based	base	VERB
easat-3732	48	19	on	on	ADP
easat-3732	48	20	the	the	DET
easat-3732	48	21	similarity	similarity	NOUN
easat-3732	48	22	of	of	ADP
easat-3732	48	23	patches	patch	NOUN
easat-3732	48	24	across	across	ADP
easat-3732	48	25	the	the	DET
easat-3732	48	26	entire	entire	ADJ
easat-3732	48	27	image	image	NOUN
easat-3732	48	28	.	.	PUNCT
easat-3732	49	1	this	this	DET
easat-3732	49	2	algorithm	algorithm	NOUN
easat-3732	49	3	is	be	AUX
easat-3732	49	4	particularly	particularly	ADV
easat-3732	49	5	effective	effective	ADJ
easat-3732	49	6	for	for	ADP
easat-3732	49	7	reducing	reduce	VERB
easat-3732	49	8	gaussian	gaussian	ADJ
easat-3732	49	9	noise	noise	NOUN
easat-3732	49	10	while	while	SCONJ
easat-3732	49	11	preserving	preserve	VERB
easat-3732	49	12	edges	edge	NOUN
easat-3732	49	13	and	and	CCONJ
easat-3732	49	14	textures	texture	NOUN
easat-3732	49	15	.	.	PUNCT
easat-3732	50	1	while	while	SCONJ
easat-3732	50	2	computationally	computationally	ADV
easat-3732	50	3	intensive	intensive	ADJ
easat-3732	50	4	,	,	PUNCT
easat-3732	50	5	nlm	nlm	PROPN
easat-3732	50	6	offers	offer	VERB
easat-3732	50	7	robustness	robustness	NOUN
easat-3732	50	8	and	and	CCONJ
easat-3732	50	9	adaptability	adaptability	NOUN
easat-3732	50	10	,	,	PUNCT
easat-3732	50	11	making	make	VERB
easat-3732	50	12	it	it	PRON
easat-3732	50	13	a	a	DET
easat-3732	50	14	strong	strong	ADJ
easat-3732	50	15	candidate	candidate	NOUN
easat-3732	50	16	for	for	ADP
easat-3732	50	17	integration	integration	NOUN
easat-3732	50	18	into	into	ADP
easat-3732	50	19	deep	deep	ADJ
easat-3732	50	20	learning	learning	NOUN
easat-3732	50	21	frameworks	framework	NOUN
easat-3732	50	22	.	.	PUNCT
easat-3732	51	1	recent	recent	ADJ
easat-3732	51	2	efforts	effort	NOUN
easat-3732	51	3	have	have	AUX
easat-3732	51	4	combined	combine	VERB
easat-3732	51	5	nlm	nlm	PROPN
easat-3732	51	6	with	with	ADP
easat-3732	51	7	self	self	NOUN
easat-3732	51	8	-	-	PUNCT
easat-3732	51	9	supervised	supervise	VERB
easat-3732	51	10	methods	method	NOUN
easat-3732	51	11	,	,	PUNCT
easat-3732	51	12	using	use	VERB
easat-3732	51	13	pseudo	pseudo	NOUN
easat-3732	51	14	-	-	ADJ
easat-3732	51	15	clean	clean	ADJ
easat-3732	51	16	images	image	NOUN
easat-3732	51	17	derived	derive	VERB
easat-3732	51	18	from	from	ADP
easat-3732	51	19	nlm	nlm	PROPN
easat-3732	51	20	as	as	ADP
easat-3732	51	21	training	training	NOUN
easat-3732	51	22	target	target	NOUN
easat-3732	51	23	.	.	PUNCT
easat-3732	52	1	recent	recent	ADJ
easat-3732	52	2	self	self	NOUN
easat-3732	52	3	-	-	PUNCT
easat-3732	52	4	supervised	supervise	VERB
easat-3732	52	5	innovations	innovation	NOUN
easat-3732	52	6	:	:	PUNCT
easat-3732	52	7	several	several	ADJ
easat-3732	52	8	innovative	innovative	ADJ
easat-3732	52	9	ssl	ssl	ADJ
easat-3732	52	10	methods	method	NOUN
easat-3732	52	11	address	address	VERB
easat-3732	52	12	diverse	diverse	ADJ
easat-3732	52	13	noise	noise	NOUN
easat-3732	52	14	scenarios	scenario	NOUN
easat-3732	52	15	.	.	PUNCT
easat-3732	53	1	blind2unblind	blind2unblind	NOUN
easat-3732	53	2	[	[	X
easat-3732	53	3	13	13	NUM
easat-3732	53	4	]	]	PUNCT
easat-3732	53	5	enhances	enhance	VERB
easat-3732	53	6	blind	blind	ADJ
easat-3732	53	7	-	-	PUNCT
easat-3732	53	8	spot	spot	NOUN
easat-3732	53	9	models	model	NOUN
easat-3732	53	10	with	with	ADP
easat-3732	53	11	global	global	ADJ
easat-3732	53	12	-	-	PUNCT
easat-3732	53	13	aware	aware	ADJ
easat-3732	53	14	masking	masking	NOUN
easat-3732	53	15	,	,	PUNCT
easat-3732	53	16	improving	improve	VERB
easat-3732	53	17	training	training	NOUN
easat-3732	53	18	diversity	diversity	NOUN
easat-3732	53	19	.	.	PUNCT
easat-3732	54	1	recorrupted2recorrupted	recorrupted2recorrupte	VERB
easat-3732	54	2	[	[	X
easat-3732	54	3	14	14	NUM
easat-3732	54	4	]	]	PUNCT
easat-3732	54	5	extends	extend	VERB
easat-3732	54	6	noise2noise	noise2noise	ADV
easat-3732	54	7	by	by	ADP
easat-3732	54	8	introducing	introduce	VERB
easat-3732	54	9	multiple	multiple	ADJ
easat-3732	54	10	noise	noise	NOUN
easat-3732	54	11	levels	level	NOUN
easat-3732	54	12	during	during	ADP
easat-3732	54	13	training	training	NOUN
easat-3732	54	14	,	,	PUNCT
easat-3732	54	15	enabling	enable	VERB
easat-3732	54	16	models	model	NOUN
easat-3732	54	17	to	to	PART
easat-3732	54	18	generalize	generalize	VERB
easat-3732	54	19	across	across	ADP
easat-3732	54	20	varied	varied	ADJ
easat-3732	54	21	noise	noise	NOUN
easat-3732	54	22	conditions	condition	NOUN
easat-3732	54	23	.	.	PUNCT
easat-3732	55	1	neighbor2neighbor	neighbor2neighbor	PROPN
easat-3732	55	2	[	[	X
easat-3732	55	3	15	15	NUM
easat-3732	55	4	]	]	PUNCT
easat-3732	55	5	creates	create	VERB
easat-3732	55	6	training	training	NOUN
easat-3732	55	7	pairs	pair	NOUN
easat-3732	55	8	by	by	ADP
easat-3732	55	9	subsampling	subsample	VERB
easat-3732	55	10	noisy	noisy	ADJ
easat-3732	55	11	images	image	NOUN
easat-3732	55	12	,	,	PUNCT
easat-3732	55	13	maintaining	maintain	VERB
easat-3732	55	14	spatial	spatial	ADJ
easat-3732	55	15	consistency	consistency	NOUN
easat-3732	55	16	without	without	ADP
easat-3732	55	17	requiring	require	VERB
easat-3732	55	18	explicit	explicit	ADJ
easat-3732	55	19	noise	noise	NOUN
easat-3732	55	20	models	model	NOUN
easat-3732	55	21	.	.	PUNCT
easat-3732	56	1	these	these	DET
easat-3732	56	2	advancements	advancement	NOUN
easat-3732	56	3	underscore	underscore	VERB
easat-3732	56	4	the	the	DET
easat-3732	56	5	flexibility	flexibility	NOUN
easat-3732	56	6	of	of	ADP
easat-3732	56	7	self	self	NOUN
easat-3732	56	8	-	-	PUNCT
easat-3732	56	9	supervised	supervise	VERB
easat-3732	56	10	learning	learning	NOUN
easat-3732	56	11	in	in	ADP
easat-3732	56	12	addressing	address	VERB
easat-3732	56	13	real	real	ADJ
easat-3732	56	14	-	-	PUNCT
easat-3732	56	15	world	world	NOUN
easat-3732	56	16	challenges	challenge	NOUN
easat-3732	56	17	.	.	PUNCT
easat-3732	57	1	contextualizing	contextualize	VERB
easat-3732	57	2	the	the	DET
easat-3732	57	3	proposed	propose	VERB
easat-3732	57	4	methods	method	NOUN
easat-3732	57	5	:	:	PUNCT
easat-3732	57	6	the	the	DET
easat-3732	57	7	proposed	propose	VERB
easat-3732	57	8	self	self	NOUN
easat-3732	57	9	-	-	PUNCT
easat-3732	57	10	supervised	supervise	VERB
easat-3732	57	11	denoising	denoising	NOUN
easat-3732	57	12	methods	method	NOUN
easat-3732	57	13	build	build	VERB
easat-3732	57	14	on	on	ADP
easat-3732	57	15	these	these	DET
easat-3732	57	16	advancements	advancement	NOUN
easat-3732	57	17	,	,	PUNCT
easat-3732	57	18	leveraging	leverage	VERB
easat-3732	57	19	dwt	dwt	NOUN
easat-3732	57	20	and	and	CCONJ
easat-3732	57	21	nlm	nlm	PROPN
easat-3732	57	22	within	within	ADP
easat-3732	57	23	an	an	DET
easat-3732	57	24	ssl	ssl	ADJ
easat-3732	57	25	framework	framework	NOUN
easat-3732	57	26	.	.	PUNCT
easat-3732	58	1	the	the	DET
easat-3732	58	2	dwt	dwt	NOUN
easat-3732	58	3	-	-	PUNCT
easat-3732	58	4	based	base	VERB
easat-3732	58	5	approach	approach	NOUN
easat-3732	58	6	uses	use	VERB
easat-3732	58	7	thresholded	thresholde	VERB
easat-3732	58	8	wavelet	wavelet	NOUN
easat-3732	58	9	coefficients	coefficient	NOUN
easat-3732	58	10	as	as	ADP
easat-3732	58	11	pseudo	pseudo	NOUN
easat-3732	58	12	-	-	ADJ
easat-3732	58	13	clean	clean	ADJ
easat-3732	58	14	targets	target	NOUN
easat-3732	58	15	,	,	PUNCT
easat-3732	58	16	enabling	enable	VERB
easat-3732	58	17	multi	multi	ADJ
easat-3732	58	18	-	-	NOUN
easat-3732	58	19	resolution	resolution	NOUN
easat-3732	58	20	denoising	denoising	NOUN
easat-3732	58	21	without	without	ADP
easat-3732	58	22	requiring	require	VERB
easat-3732	58	23	clean	clean	ADJ
easat-3732	58	24	references	reference	NOUN
easat-3732	58	25	.	.	PUNCT
easat-3732	59	1	by	by	ADP
easat-3732	59	2	combining	combine	VERB
easat-3732	59	3	dwt	dwt	NOUN
easat-3732	59	4	with	with	ADP
easat-3732	59	5	a	a	DET
easat-3732	59	6	u	u	ADJ
easat-3732	59	7	-	-	ADJ
easat-3732	59	8	net	net	ADJ
easat-3732	59	9	architecture	architecture	NOUN
easat-3732	59	10	[	[	X
easat-3732	59	11	16	16	NUM
easat-3732	59	12	]	]	PUNCT
easat-3732	59	13	,	,	PUNCT
easat-3732	59	14	this	this	DET
easat-3732	59	15	method	method	NOUN
easat-3732	59	16	effectively	effectively	ADV
easat-3732	59	17	suppresses	suppress	VERB
easat-3732	59	18	noise	noise	NOUN
easat-3732	59	19	while	while	SCONJ
easat-3732	59	20	preserving	preserve	VERB
easat-3732	59	21	structural	structural	ADJ
easat-3732	59	22	details	detail	NOUN
easat-3732	59	23	,	,	PUNCT
easat-3732	59	24	achieving	achieve	VERB
easat-3732	59	25	state	state	NOUN
easat-3732	59	26	-	-	PUNCT
easat-3732	59	27	of	of	ADP
easat-3732	59	28	-	-	PUNCT
easat-3732	59	29	the	the	DET
easat-3732	59	30	-	-	PUNCT
easat-3732	59	31	art	art	NOUN
easat-3732	59	32	performance	performance	NOUN
easat-3732	59	33	on	on	ADP
easat-3732	59	34	gaussian	gaussian	ADJ
easat-3732	59	35	and	and	CCONJ
easat-3732	59	36	poisson	poisson	NOUN
easat-3732	59	37	noise	noise	NOUN
easat-3732	59	38	.	.	PUNCT
easat-3732	60	1	the	the	DET
easat-3732	60	2	nlm	nlm	NOUN
easat-3732	60	3	-	-	PUNCT
easat-3732	60	4	based	base	VERB
easat-3732	60	5	approach	approach	NOUN
easat-3732	60	6	generates	generate	VERB
easat-3732	60	7	pseudo	pseudo	ADJ
easat-3732	60	8	-	-	ADJ
easat-3732	60	9	clean	clean	ADJ
easat-3732	60	10	images	image	NOUN
easat-3732	60	11	using	use	VERB
easat-3732	60	12	nlm	nlm	PROPN
easat-3732	60	13	,	,	PUNCT
easat-3732	60	14	which	which	PRON
easat-3732	60	15	are	be	AUX
easat-3732	60	16	then	then	ADV
easat-3732	60	17	used	use	VERB
easat-3732	60	18	to	to	PART
easat-3732	60	19	train	train	VERB
easat-3732	60	20	a	a	DET
easat-3732	60	21	u	u	ADJ
easat-3732	60	22	-	-	ADJ
easat-3732	60	23	net	net	ADJ
easat-3732	60	24	model	model	NOUN
easat-3732	60	25	[	[	X
easat-3732	60	26	16	16	NUM
easat-3732	60	27	]	]	PUNCT
easat-3732	60	28	with	with	ADP
easat-3732	60	29	a	a	DET
easat-3732	60	30	custom	custom	NOUN
easat-3732	60	31	loss	loss	NOUN
easat-3732	60	32	function	function	NOUN
easat-3732	60	33	balancing	balancing	NOUN
easat-3732	60	34	mean	mean	VERB
easat-3732	60	35	squared	square	VERB
easat-3732	60	36	error	error	NOUN
easat-3732	60	37	(	(	PUNCT
easat-3732	60	38	mse	mse	NOUN
easat-3732	60	39	)	)	PUNCT
easat-3732	60	40	and	and	CCONJ
easat-3732	60	41	structural	structural	ADJ
easat-3732	60	42	similarity	similarity	NOUN
easat-3732	60	43	index	index	NOUN
easat-3732	60	44	(	(	PUNCT
easat-3732	60	45	ssim	ssim	NOUN
easat-3732	60	46	)	)	PUNCT
easat-3732	61	1	[	[	X
easat-3732	61	2	17	17	NUM
easat-3732	61	3	]	]	PUNCT
easat-3732	61	4	.	.	PUNCT
easat-3732	62	1	this	this	DET
easat-3732	62	2	integration	integration	NOUN
easat-3732	62	3	allows	allow	VERB
easat-3732	62	4	the	the	DET
easat-3732	62	5	model	model	NOUN
easat-3732	62	6	to	to	PART
easat-3732	62	7	leverage	leverage	VERB
easat-3732	62	8	both	both	CCONJ
easat-3732	62	9	spatial	spatial	ADJ
easat-3732	62	10	and	and	CCONJ
easat-3732	62	11	structural	structural	ADJ
easat-3732	62	12	redundancies	redundancy	NOUN
easat-3732	62	13	,	,	PUNCT
easat-3732	62	14	enhancing	enhance	VERB
easat-3732	62	15	denoising	denoising	NOUN
easat-3732	62	16	performance	performance	NOUN
easat-3732	62	17	across	across	ADP
easat-3732	62	18	varied	varied	ADJ
easat-3732	62	19	noise	noise	NOUN
easat-3732	62	20	types	type	NOUN
easat-3732	62	21	.	.	PUNCT
easat-3732	63	1	this	this	PRON
easat-3732	63	2	highlights	highlight	VERB
easat-3732	63	3	the	the	DET
easat-3732	63	4	evolution	evolution	NOUN
easat-3732	63	5	of	of	ADP
easat-3732	63	6	image	image	NOUN
easat-3732	63	7	denoising	denoise	VERB
easat-3732	63	8	,	,	PUNCT
easat-3732	63	9	from	from	ADP
easat-3732	63	10	traditional	traditional	ADJ
easat-3732	63	11	methods	method	NOUN
easat-3732	63	12	to	to	ADP
easat-3732	63	13	modern	modern	ADJ
easat-3732	63	14	self	self	NOUN
easat-3732	63	15	-	-	PUNCT
easat-3732	63	16	supervised	supervise	VERB
easat-3732	63	17	approaches	approach	NOUN
easat-3732	63	18	.	.	PUNCT
easat-3732	64	1	while	while	SCONJ
easat-3732	64	2	supervised	supervised	ADJ
easat-3732	64	3	learning	learning	NOUN
easat-3732	64	4	has	have	AUX
easat-3732	64	5	advanced	advance	VERB
easat-3732	64	6	denoising	denoising	NOUN
easat-3732	64	7	performance	performance	NOUN
easat-3732	64	8	,	,	PUNCT
easat-3732	64	9	self	self	NOUN
easat-3732	64	10	-	-	PUNCT
easat-3732	64	11	supervised	supervise	VERB
easat-3732	64	12	methods	method	NOUN
easat-3732	64	13	like	like	ADP
easat-3732	64	14	noise2noise	noise2noise	PROPN
easat-3732	64	15	and	and	CCONJ
easat-3732	64	16	neighbor2neighbor	neighbor2neighbor	NOUN
easat-3732	64	17	offer	offer	VERB
easat-3732	64	18	scalable	scalable	ADJ
easat-3732	64	19	solutions	solution	NOUN
easat-3732	64	20	without	without	ADP
easat-3732	64	21	requiring	require	VERB
easat-3732	64	22	labelled	label	VERB
easat-3732	64	23	datasets	dataset	NOUN
easat-3732	64	24	.	.	PUNCT
easat-3732	65	1	the	the	DET
easat-3732	65	2	proposed	propose	VERB
easat-3732	65	3	dwt	dwt	NOUN
easat-3732	65	4	7953	7953	NUM
easat-3732	65	5	edelweiss	edelweiss	PROPN
easat-3732	65	6	applied	apply	VERB
easat-3732	65	7	science	science	NOUN
easat-3732	65	8	and	and	CCONJ
easat-3732	65	9	technology	technology	NOUN
easat-3732	65	10	issn	issn	PROPN
easat-3732	65	11	:	:	PUNCT
easat-3732	65	12	2576	2576	NUM
easat-3732	65	13	-	-	SYM
easat-3732	65	14	8484	8484	NUM
easat-3732	65	15	vol	vol	NOUN
easat-3732	65	16	.	.	PROPN
easat-3732	65	17	8	8	NUM
easat-3732	65	18	,	,	PUNCT
easat-3732	65	19	no	no	INTJ
easat-3732	65	20	.	.	NOUN
easat-3732	65	21	6	6	NUM
easat-3732	65	22	:	:	PUNCT
easat-3732	65	23	7951	7951	NUM
easat-3732	65	24	-	-	SYM
easat-3732	65	25	7970	7970	NUM
easat-3732	65	26	,	,	PUNCT
easat-3732	65	27	2024	2024	NUM
easat-3732	65	28	doi	doi	NOUN
easat-3732	65	29	:	:	PUNCT
easat-3732	65	30	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	65	31	©	©	ADP
easat-3732	65	32	2024	2024	NUM
easat-3732	65	33	by	by	ADP
easat-3732	65	34	the	the	DET
easat-3732	65	35	authors	author	NOUN
easat-3732	65	36	;	;	PUNCT
easat-3732	65	37	licensee	licensee	PROPN
easat-3732	65	38	learning	learning	NOUN
easat-3732	65	39	gate	gate	PROPN
easat-3732	65	40	and	and	CCONJ
easat-3732	65	41	nlm	nlm	PROPN
easat-3732	65	42	-	-	PUNCT
easat-3732	65	43	based	base	VERB
easat-3732	65	44	models	model	NOUN
easat-3732	65	45	bridge	bridge	VERB
easat-3732	65	46	the	the	DET
easat-3732	65	47	gap	gap	NOUN
easat-3732	65	48	between	between	ADP
easat-3732	65	49	classical	classical	ADJ
easat-3732	65	50	techniques	technique	NOUN
easat-3732	65	51	and	and	CCONJ
easat-3732	65	52	modern	modern	ADJ
easat-3732	65	53	ssl	ssl	PROPN
easat-3732	65	54	paradigms	paradigm	NOUN
easat-3732	65	55	,	,	PUNCT
easat-3732	65	56	demonstrating	demonstrate	VERB
easat-3732	65	57	robust	robust	ADJ
easat-3732	65	58	performance	performance	NOUN
easat-3732	65	59	and	and	CCONJ
easat-3732	65	60	generalization	generalization	NOUN
easat-3732	65	61	across	across	ADP
easat-3732	65	62	noise	noise	NOUN
easat-3732	65	63	types	type	NOUN
easat-3732	65	64	.	.	PUNCT
easat-3732	66	1	1.1	1.1	NUM
easat-3732	66	2	.	.	PUNCT
easat-3732	67	1	research	research	NOUN
easat-3732	67	2	gaps	gap	NOUN
easat-3732	67	3	despite	despite	SCONJ
easat-3732	67	4	significant	significant	ADJ
easat-3732	67	5	progress	progress	NOUN
easat-3732	67	6	,	,	PUNCT
easat-3732	67	7	several	several	ADJ
easat-3732	67	8	research	research	NOUN
easat-3732	67	9	gaps	gap	NOUN
easat-3732	67	10	remain	remain	VERB
easat-3732	67	11	in	in	ADP
easat-3732	67	12	the	the	DET
easat-3732	67	13	field	field	NOUN
easat-3732	67	14	of	of	ADP
easat-3732	67	15	dwt	dwt	NOUN
easat-3732	67	16	-	-	PUNCT
easat-3732	67	17	based	base	VERB
easat-3732	67	18	self	self	NOUN
easat-3732	67	19	-	-	PUNCT
easat-3732	67	20	supervised	supervise	VERB
easat-3732	67	21	image	image	NOUN
easat-3732	67	22	denoising	denoising	NOUN
easat-3732	67	23	.	.	PUNCT
easat-3732	68	1	first	first	ADV
easat-3732	68	2	,	,	PUNCT
easat-3732	68	3	most	most	ADJ
easat-3732	68	4	studies	study	NOUN
easat-3732	68	5	have	have	AUX
easat-3732	68	6	focused	focus	VERB
easat-3732	68	7	on	on	ADP
easat-3732	68	8	a	a	DET
easat-3732	68	9	limited	limited	ADJ
easat-3732	68	10	set	set	NOUN
easat-3732	68	11	of	of	ADP
easat-3732	68	12	wavelet	wavelet	NOUN
easat-3732	68	13	types	type	NOUN
easat-3732	68	14	,	,	PUNCT
easat-3732	68	15	such	such	ADJ
easat-3732	68	16	as	as	ADP
easat-3732	68	17	haar	haar	NOUN
easat-3732	68	18	and	and	CCONJ
easat-3732	68	19	daubechies	daubechie	NOUN
easat-3732	68	20	(	(	PUNCT
easat-3732	68	21	liu	liu	PROPN
easat-3732	68	22	&	&	CCONJ
easat-3732	68	23	liu	liu	PROPN
easat-3732	68	24	,	,	PUNCT
easat-3732	68	25	2018	2018	NUM
easat-3732	68	26	)	)	PUNCT
easat-3732	69	1	[	[	X
easat-3732	69	2	12	12	NUM
easat-3732	69	3	]	]	PUNCT
easat-3732	69	4	,	,	PUNCT
easat-3732	69	5	leaving	leave	VERB
easat-3732	69	6	the	the	DET
easat-3732	69	7	potential	potential	NOUN
easat-3732	69	8	of	of	ADP
easat-3732	69	9	other	other	ADJ
easat-3732	69	10	wavelet	wavelet	NOUN
easat-3732	69	11	families	family	NOUN
easat-3732	69	12	underexplored	underexplored	ADJ
easat-3732	69	13	.	.	PUNCT
easat-3732	70	1	the	the	DET
easat-3732	70	2	impact	impact	NOUN
easat-3732	70	3	of	of	ADP
easat-3732	70	4	wavelet	wavelet	NOUN
easat-3732	70	5	choice	choice	NOUN
easat-3732	70	6	on	on	ADP
easat-3732	70	7	denoising	denoise	VERB
easat-3732	70	8	performance	performance	NOUN
easat-3732	70	9	,	,	PUNCT
easat-3732	70	10	especially	especially	ADV
easat-3732	70	11	in	in	ADP
easat-3732	70	12	conjunction	conjunction	NOUN
easat-3732	70	13	with	with	ADP
easat-3732	70	14	self	self	NOUN
easat-3732	70	15	-	-	PUNCT
easat-3732	70	16	supervised	supervise	VERB
easat-3732	70	17	learning	learning	NOUN
easat-3732	70	18	,	,	PUNCT
easat-3732	70	19	has	have	AUX
easat-3732	70	20	not	not	PART
easat-3732	70	21	been	be	AUX
easat-3732	70	22	fully	fully	ADV
easat-3732	70	23	addressed	address	VERB
easat-3732	70	24	.	.	PUNCT
easat-3732	71	1	more	more	ADJ
easat-3732	71	2	comparative	comparative	ADJ
easat-3732	71	3	studies	study	NOUN
easat-3732	71	4	are	be	AUX
easat-3732	71	5	needed	need	VERB
easat-3732	71	6	to	to	PART
easat-3732	71	7	understand	understand	VERB
easat-3732	71	8	how	how	SCONJ
easat-3732	71	9	different	different	ADJ
easat-3732	71	10	wavelet	wavelet	NOUN
easat-3732	71	11	transforms	transform	VERB
easat-3732	71	12	affect	affect	VERB
easat-3732	71	13	denoising	denoise	VERB
easat-3732	71	14	across	across	ADP
easat-3732	71	15	a	a	DET
easat-3732	71	16	range	range	NOUN
easat-3732	71	17	of	of	ADP
easat-3732	71	18	noise	noise	NOUN
easat-3732	71	19	types	type	NOUN
easat-3732	71	20	,	,	PUNCT
easat-3732	71	21	including	include	VERB
easat-3732	71	22	gaussian	gaussian	NOUN
easat-3732	71	23	,	,	PUNCT
easat-3732	71	24	poisson	poisson	NOUN
easat-3732	71	25	,	,	PUNCT
easat-3732	71	26	and	and	CCONJ
easat-3732	71	27	complex	complex	ADJ
easat-3732	71	28	real	real	ADJ
easat-3732	71	29	-	-	PUNCT
easat-3732	71	30	world	world	NOUN
easat-3732	71	31	noise	noise	NOUN
easat-3732	71	32	.	.	PUNCT
easat-3732	72	1	second	second	ADJ
easat-3732	72	2	,	,	PUNCT
easat-3732	72	3	while	while	SCONJ
easat-3732	72	4	hybrid	hybrid	ADJ
easat-3732	72	5	wavelet	wavelet	NOUN
easat-3732	72	6	-	-	PUNCT
easat-3732	72	7	cnn	cnn	PROPN
easat-3732	72	8	models	model	NOUN
easat-3732	72	9	have	have	AUX
easat-3732	72	10	shown	show	VERB
easat-3732	72	11	improved	improved	ADJ
easat-3732	72	12	denoising	denoising	NOUN
easat-3732	72	13	performance	performance	NOUN
easat-3732	72	14	,	,	PUNCT
easat-3732	72	15	they	they	PRON
easat-3732	72	16	often	often	ADV
easat-3732	72	17	come	come	VERB
easat-3732	72	18	with	with	ADP
easat-3732	72	19	high	high	ADJ
easat-3732	72	20	computational	computational	ADJ
easat-3732	72	21	costs	cost	NOUN
easat-3732	72	22	,	,	PUNCT
easat-3732	72	23	especially	especially	ADV
easat-3732	72	24	for	for	ADP
easat-3732	72	25	high	high	ADJ
easat-3732	72	26	-	-	PUNCT
easat-3732	72	27	resolution	resolution	NOUN
easat-3732	72	28	images	image	NOUN
easat-3732	72	29	or	or	CCONJ
easat-3732	72	30	large	large	ADJ
easat-3732	72	31	datasets	dataset	NOUN
easat-3732	72	32	.	.	PUNCT
easat-3732	73	1	efficient	efficient	ADJ
easat-3732	73	2	algorithms	algorithm	NOUN
easat-3732	73	3	and	and	CCONJ
easat-3732	73	4	lightweight	lightweight	NOUN
easat-3732	73	5	models	model	NOUN
easat-3732	73	6	need	need	VERB
easat-3732	73	7	to	to	PART
easat-3732	73	8	be	be	AUX
easat-3732	73	9	developed	develop	VERB
easat-3732	73	10	to	to	PART
easat-3732	73	11	ensure	ensure	VERB
easat-3732	73	12	the	the	DET
easat-3732	73	13	scalability	scalability	NOUN
easat-3732	73	14	of	of	ADP
easat-3732	73	15	these	these	DET
easat-3732	73	16	methods	method	NOUN
easat-3732	73	17	for	for	ADP
easat-3732	73	18	real	real	ADJ
easat-3732	73	19	-	-	PUNCT
easat-3732	73	20	time	time	NOUN
easat-3732	73	21	applications	application	NOUN
easat-3732	73	22	.	.	PUNCT
easat-3732	74	1	current	current	ADJ
easat-3732	74	2	methods	method	NOUN
easat-3732	74	3	also	also	ADV
easat-3732	74	4	lack	lack	VERB
easat-3732	74	5	generalization	generalization	NOUN
easat-3732	74	6	across	across	ADP
easat-3732	74	7	multiple	multiple	ADJ
easat-3732	74	8	noise	noise	NOUN
easat-3732	74	9	models	model	NOUN
easat-3732	74	10	,	,	PUNCT
easat-3732	74	11	with	with	ADP
easat-3732	74	12	most	most	ADJ
easat-3732	74	13	approaches	approach	NOUN
easat-3732	74	14	focusing	focus	VERB
easat-3732	74	15	on	on	ADP
easat-3732	74	16	a	a	DET
easat-3732	74	17	single	single	ADJ
easat-3732	74	18	type	type	NOUN
easat-3732	74	19	of	of	ADP
easat-3732	74	20	noise	noise	NOUN
easat-3732	74	21	.	.	PUNCT
easat-3732	75	1	there	there	PRON
easat-3732	75	2	is	be	VERB
easat-3732	75	3	a	a	DET
easat-3732	75	4	need	need	NOUN
easat-3732	75	5	for	for	ADP
easat-3732	75	6	research	research	NOUN
easat-3732	75	7	into	into	ADP
easat-3732	75	8	generalized	generalized	ADJ
easat-3732	75	9	models	model	NOUN
easat-3732	75	10	that	that	PRON
easat-3732	75	11	can	can	AUX
easat-3732	75	12	effectively	effectively	ADV
easat-3732	75	13	handle	handle	VERB
easat-3732	75	14	multiple	multiple	ADJ
easat-3732	75	15	noise	noise	NOUN
easat-3732	75	16	distributions	distribution	NOUN
easat-3732	75	17	in	in	ADP
easat-3732	75	18	a	a	DET
easat-3732	75	19	unified	unified	ADJ
easat-3732	75	20	framework	framework	NOUN
easat-3732	75	21	.	.	PUNCT
easat-3732	76	1	another	another	DET
easat-3732	76	2	major	major	ADJ
easat-3732	76	3	gap	gap	NOUN
easat-3732	76	4	is	be	AUX
easat-3732	76	5	the	the	DET
easat-3732	76	6	limited	limited	ADJ
easat-3732	76	7	exploration	exploration	NOUN
easat-3732	76	8	of	of	ADP
easat-3732	76	9	these	these	DET
easat-3732	76	10	methods	method	NOUN
easat-3732	76	11	on	on	ADP
easat-3732	76	12	real	real	ADJ
easat-3732	76	13	-	-	PUNCT
easat-3732	76	14	world	world	NOUN
easat-3732	76	15	noisy	noisy	ADJ
easat-3732	76	16	data	datum	NOUN
easat-3732	76	17	.	.	PUNCT
easat-3732	77	1	most	most	ADJ
easat-3732	77	2	studies	study	NOUN
easat-3732	77	3	have	have	AUX
easat-3732	77	4	tested	test	VERB
easat-3732	77	5	their	their	PRON
easat-3732	77	6	models	model	NOUN
easat-3732	77	7	on	on	ADP
easat-3732	77	8	synthetic	synthetic	ADJ
easat-3732	77	9	datasets	dataset	NOUN
easat-3732	77	10	with	with	ADP
easat-3732	77	11	simulated	simulated	ADJ
easat-3732	77	12	noise	noise	NOUN
easat-3732	77	13	,	,	PUNCT
easat-3732	77	14	which	which	PRON
easat-3732	77	15	may	may	AUX
easat-3732	77	16	not	not	PART
easat-3732	77	17	accurately	accurately	ADV
easat-3732	77	18	reflect	reflect	VERB
easat-3732	77	19	the	the	DET
easat-3732	77	20	complexity	complexity	NOUN
easat-3732	77	21	of	of	ADP
easat-3732	77	22	noise	noise	NOUN
easat-3732	77	23	found	find	VERB
easat-3732	77	24	in	in	ADP
easat-3732	77	25	medical	medical	ADJ
easat-3732	77	26	or	or	CCONJ
easat-3732	77	27	astronomical	astronomical	ADJ
easat-3732	77	28	images	image	NOUN
easat-3732	77	29	(	(	PUNCT
easat-3732	77	30	lehtinen	lehtinen	PROPN
easat-3732	77	31	et	et	PROPN
easat-3732	77	32	al	al	PROPN
easat-3732	77	33	.	.	PROPN
easat-3732	77	34	,	,	PUNCT
easat-3732	77	35	2018	2018	NUM
easat-3732	77	36	;	;	PUNCT
easat-3732	77	37	krull	krull	PROPN
easat-3732	77	38	et	et	PROPN
easat-3732	77	39	al	al	PROPN
easat-3732	77	40	.	.	PROPN
easat-3732	77	41	,	,	PUNCT
easat-3732	77	42	2019	2019	NUM
easat-3732	77	43	)	)	PUNCT
easat-3732	78	1	[	[	X
easat-3732	78	2	7	7	NUM
easat-3732	78	3	-	-	SYM
easat-3732	78	4	8	8	NUM
easat-3732	78	5	]	]	PUNCT
easat-3732	78	6	.	.	PUNCT
easat-3732	79	1	additionally	additionally	ADV
easat-3732	79	2	,	,	PUNCT
easat-3732	79	3	existing	exist	VERB
easat-3732	79	4	models	model	NOUN
easat-3732	79	5	are	be	AUX
easat-3732	79	6	largely	largely	ADV
easat-3732	79	7	empirical	empirical	ADJ
easat-3732	79	8	,	,	PUNCT
easat-3732	79	9	with	with	ADP
easat-3732	79	10	little	little	ADJ
easat-3732	79	11	theoretical	theoretical	ADJ
easat-3732	79	12	understanding	understanding	NOUN
easat-3732	79	13	of	of	ADP
easat-3732	79	14	why	why	SCONJ
easat-3732	79	15	certain	certain	ADJ
easat-3732	79	16	wavelet	wavelet	NOUN
easat-3732	79	17	-	-	PUNCT
easat-3732	79	18	based	base	VERB
easat-3732	79	19	models	model	NOUN
easat-3732	79	20	outperform	outperform	VERB
easat-3732	79	21	others	other	NOUN
easat-3732	79	22	.	.	PUNCT
easat-3732	80	1	more	more	ADJ
easat-3732	80	2	research	research	NOUN
easat-3732	80	3	is	be	AUX
easat-3732	80	4	needed	need	VERB
easat-3732	80	5	on	on	ADP
easat-3732	80	6	the	the	DET
easat-3732	80	7	mathematical	mathematical	ADJ
easat-3732	80	8	underpinnings	underpinning	NOUN
easat-3732	80	9	of	of	ADP
easat-3732	80	10	wavelet	wavelet	NOUN
easat-3732	80	11	-	-	PUNCT
easat-3732	80	12	cnn	cnn	PROPN
easat-3732	80	13	architectures	architecture	NOUN
easat-3732	80	14	,	,	PUNCT
easat-3732	80	15	particularly	particularly	ADV
easat-3732	80	16	in	in	ADP
easat-3732	80	17	the	the	DET
easat-3732	80	18	self	self	NOUN
easat-3732	80	19	-	-	PUNCT
easat-3732	80	20	supervised	supervise	VERB
easat-3732	80	21	domain	domain	NOUN
easat-3732	80	22	,	,	PUNCT
easat-3732	80	23	to	to	PART
easat-3732	80	24	provide	provide	VERB
easat-3732	80	25	deeper	deep	ADJ
easat-3732	80	26	insights	insight	NOUN
easat-3732	80	27	into	into	ADP
easat-3732	80	28	their	their	PRON
easat-3732	80	29	success	success	NOUN
easat-3732	80	30	.	.	PUNCT
easat-3732	81	1	finally	finally	ADV
easat-3732	81	2	,	,	PUNCT
easat-3732	81	3	the	the	DET
easat-3732	81	4	integration	integration	NOUN
easat-3732	81	5	of	of	ADP
easat-3732	81	6	wavelet	wavelet	NOUN
easat-3732	81	7	transforms	transform	VERB
easat-3732	81	8	with	with	ADP
easat-3732	81	9	other	other	ADJ
easat-3732	81	10	methods	method	NOUN
easat-3732	81	11	,	,	PUNCT
easat-3732	81	12	such	such	ADJ
easat-3732	81	13	as	as	ADP
easat-3732	81	14	block	block	NOUN
easat-3732	81	15	matching	matching	NOUN
easat-3732	81	16	or	or	CCONJ
easat-3732	81	17	fourier	fourier	NOUN
easat-3732	81	18	transforms	transform	NOUN
easat-3732	81	19	,	,	PUNCT
easat-3732	81	20	has	have	AUX
easat-3732	81	21	been	be	AUX
easat-3732	81	22	underexplored	underexplore	VERB
easat-3732	81	23	.	.	PUNCT
easat-3732	82	1	multi	multi	ADJ
easat-3732	82	2	-	-	ADJ
easat-3732	82	3	transform	transform	ADJ
easat-3732	82	4	architectures	architecture	NOUN
easat-3732	82	5	could	could	AUX
easat-3732	82	6	offer	offer	VERB
easat-3732	82	7	further	further	ADJ
easat-3732	82	8	improvements	improvement	NOUN
easat-3732	82	9	in	in	ADP
easat-3732	82	10	denoising	denoise	VERB
easat-3732	82	11	by	by	ADP
easat-3732	82	12	leveraging	leverage	VERB
easat-3732	82	13	the	the	DET
easat-3732	82	14	strengths	strength	NOUN
easat-3732	82	15	of	of	ADP
easat-3732	82	16	various	various	ADJ
easat-3732	82	17	techniques	technique	NOUN
easat-3732	82	18	.	.	PUNCT
easat-3732	83	1	similarly	similarly	ADV
easat-3732	83	2	,	,	PUNCT
easat-3732	83	3	nlm	nlm	PROPN
easat-3732	83	4	can	can	AUX
easat-3732	83	5	be	be	AUX
easat-3732	83	6	integrated	integrate	VERB
easat-3732	83	7	so	so	ADV
easat-3732	83	8	as	as	SCONJ
easat-3732	83	9	to	to	PART
easat-3732	83	10	use	use	VERB
easat-3732	83	11	it	it	PRON
easat-3732	83	12	effectively	effectively	ADV
easat-3732	83	13	for	for	ADP
easat-3732	83	14	denoising	denoise	VERB
easat-3732	83	15	with	with	ADP
easat-3732	83	16	less	less	ADV
easat-3732	83	17	computational	computational	ADJ
easat-3732	83	18	load	load	NOUN
easat-3732	83	19	while	while	SCONJ
easat-3732	83	20	doing	do	VERB
easat-3732	83	21	inference	inference	NOUN
easat-3732	83	22	.	.	PUNCT
easat-3732	84	1	moreover	moreover	ADV
easat-3732	84	2	,	,	PUNCT
easat-3732	84	3	there	there	PRON
easat-3732	84	4	is	be	VERB
easat-3732	84	5	a	a	DET
easat-3732	84	6	lack	lack	NOUN
easat-3732	84	7	of	of	ADP
easat-3732	84	8	research	research	NOUN
easat-3732	84	9	on	on	ADP
easat-3732	84	10	the	the	DET
easat-3732	84	11	application	application	NOUN
easat-3732	84	12	of	of	ADP
easat-3732	84	13	dwt	dwt	NOUN
easat-3732	84	14	-	-	PUNCT
easat-3732	84	15	based	base	VERB
easat-3732	84	16	self	self	NOUN
easat-3732	84	17	-	-	PUNCT
easat-3732	84	18	supervised	supervise	VERB
easat-3732	84	19	denoising	denoising	NOUN
easat-3732	84	20	in	in	ADP
easat-3732	84	21	domains	domain	NOUN
easat-3732	84	22	like	like	ADP
easat-3732	84	23	video	video	NOUN
easat-3732	84	24	denoising	denoising	NOUN
easat-3732	84	25	or	or	CCONJ
easat-3732	84	26	3d	3d	NUM
easat-3732	84	27	medical	medical	ADJ
easat-3732	84	28	imaging	imaging	NOUN
easat-3732	84	29	,	,	PUNCT
easat-3732	84	30	where	where	SCONJ
easat-3732	84	31	noise	noise	NOUN
easat-3732	84	32	patterns	pattern	NOUN
easat-3732	84	33	are	be	AUX
easat-3732	84	34	more	more	ADV
easat-3732	84	35	complex	complex	ADJ
easat-3732	84	36	and	and	CCONJ
easat-3732	84	37	varied	varied	ADJ
easat-3732	84	38	.	.	PUNCT
easat-3732	85	1	major	major	ADJ
easat-3732	85	2	contributions	contribution	NOUN
easat-3732	85	3	of	of	ADP
easat-3732	85	4	the	the	DET
easat-3732	85	5	research	research	NOUN
easat-3732	85	6	are	be	AUX
easat-3732	85	7	as	as	SCONJ
easat-3732	85	8	follows	follow	VERB
easat-3732	85	9	:	:	PUNCT
easat-3732	85	10	1	1	X
easat-3732	85	11	.	.	X
easat-3732	85	12	development	development	NOUN
easat-3732	85	13	of	of	ADP
easat-3732	85	14	a	a	DET
easat-3732	85	15	self	self	NOUN
easat-3732	85	16	-	-	PUNCT
easat-3732	85	17	supervised	supervise	VERB
easat-3732	85	18	dwt	dwt	NOUN
easat-3732	85	19	-	-	PUNCT
easat-3732	85	20	based	base	VERB
easat-3732	85	21	denoising	denoising	NOUN
easat-3732	85	22	approach	approach	NOUN
easat-3732	85	23	that	that	PRON
easat-3732	85	24	operates	operate	VERB
easat-3732	85	25	directly	directly	ADV
easat-3732	85	26	on	on	ADP
easat-3732	85	27	noisy	noisy	ADJ
easat-3732	85	28	images	image	NOUN
easat-3732	85	29	.	.	PUNCT
easat-3732	86	1	2	2	X
easat-3732	86	2	.	.	X
easat-3732	86	3	introduction	introduction	NOUN
easat-3732	86	4	of	of	ADP
easat-3732	86	5	an	an	DET
easat-3732	86	6	nlm	nlm	NOUN
easat-3732	86	7	-	-	PUNCT
easat-3732	86	8	based	base	VERB
easat-3732	86	9	self	self	NOUN
easat-3732	86	10	-	-	PUNCT
easat-3732	86	11	supervised	supervise	VERB
easat-3732	86	12	model	model	NOUN
easat-3732	86	13	for	for	ADP
easat-3732	86	14	noise	noise	NOUN
easat-3732	86	15	reduction	reduction	NOUN
easat-3732	86	16	without	without	ADP
easat-3732	86	17	the	the	DET
easat-3732	86	18	need	need	NOUN
easat-3732	86	19	for	for	ADP
easat-3732	86	20	clean	clean	ADJ
easat-3732	86	21	images	image	NOUN
easat-3732	86	22	.	.	PUNCT
easat-3732	87	1	3	3	X
easat-3732	87	2	.	.	NUM
easat-3732	87	3	customized	customize	VERB
easat-3732	87	4	loss	loss	NOUN
easat-3732	87	5	function	function	NOUN
easat-3732	87	6	combining	combine	VERB
easat-3732	87	7	mse	mse	NOUN
easat-3732	87	8	,	,	PUNCT
easat-3732	87	9	psnr	psnr	NOUN
easat-3732	87	10	,	,	PUNCT
easat-3732	87	11	and	and	CCONJ
easat-3732	87	12	ssim	ssim	NOUN
easat-3732	87	13	for	for	ADP
easat-3732	87	14	preserving	preserve	VERB
easat-3732	87	15	structural	structural	ADJ
easat-3732	87	16	details	detail	NOUN
easat-3732	87	17	.	.	PUNCT
easat-3732	88	1	4	4	X
easat-3732	88	2	.	.	X
easat-3732	88	3	experimental	experimental	ADJ
easat-3732	88	4	validation	validation	NOUN
easat-3732	88	5	on	on	ADP
easat-3732	88	6	multiple	multiple	ADJ
easat-3732	88	7	noise	noise	NOUN
easat-3732	88	8	types	type	NOUN
easat-3732	88	9	(	(	PUNCT
easat-3732	88	10	gaussian	gaussian	NOUN
easat-3732	88	11	and	and	CCONJ
easat-3732	88	12	poisson	poisson	NOUN
easat-3732	88	13	)	)	PUNCT
easat-3732	88	14	and	and	CCONJ
easat-3732	88	15	benchmark	benchmark	NOUN
easat-3732	88	16	datasets	dataset	NOUN
easat-3732	88	17	2	2	NUM
easat-3732	88	18	.	.	PUNCT
easat-3732	88	19	proposed	propose	VERB
easat-3732	88	20	approaches	approach	NOUN
easat-3732	88	21	for	for	ADP
easat-3732	88	22	self	self	NOUN
easat-3732	88	23	-	-	PUNCT
easat-3732	88	24	supervised	supervise	VERB
easat-3732	88	25	denoising	denoising	NOUN
easat-3732	88	26	in	in	ADP
easat-3732	88	27	this	this	DET
easat-3732	88	28	section	section	NOUN
easat-3732	88	29	,	,	PUNCT
easat-3732	88	30	two	two	NUM
easat-3732	88	31	different	different	ADJ
easat-3732	88	32	types	type	NOUN
easat-3732	88	33	of	of	ADP
easat-3732	88	34	approaches	approach	NOUN
easat-3732	88	35	,	,	PUNCT
easat-3732	88	36	which	which	PRON
easat-3732	88	37	are	be	AUX
easat-3732	88	38	combinations	combination	NOUN
easat-3732	88	39	of	of	ADP
easat-3732	88	40	both	both	CCONJ
easat-3732	88	41	the	the	DET
easat-3732	88	42	traditional	traditional	ADJ
easat-3732	88	43	and	and	CCONJ
easat-3732	88	44	self	self	NOUN
easat-3732	88	45	-	-	PUNCT
easat-3732	88	46	supervised	supervise	VERB
easat-3732	88	47	have	have	AUX
easat-3732	88	48	been	be	AUX
easat-3732	88	49	proposed	propose	VERB
easat-3732	88	50	:	:	PUNCT
easat-3732	88	51	i.	i.	PROPN
easat-3732	88	52	discrete	discrete	PROPN
easat-3732	88	53	wavelet	wavelet	NOUN
easat-3732	88	54	transform	transform	NOUN
easat-3732	88	55	based	base	VERB
easat-3732	88	56	self	self	NOUN
easat-3732	88	57	supervised	supervise	VERB
easat-3732	88	58	denoiser	denoiser	PROPN
easat-3732	88	59	ii	ii	PROPN
easat-3732	88	60	.	.	PUNCT
easat-3732	89	1	non	non	ADJ
easat-3732	89	2	-	-	ADJ
easat-3732	89	3	local	local	ADJ
easat-3732	89	4	means	mean	NOUN
easat-3732	89	5	based	base	VERB
easat-3732	89	6	self	self	NOUN
easat-3732	89	7	supervised	supervise	VERB
easat-3732	89	8	denoiser	denoiser	NOUN
easat-3732	89	9	2.1	2.1	NUM
easat-3732	89	10	.	.	PUNCT
easat-3732	90	1	proposed	propose	VERB
easat-3732	90	2	discrete	discrete	ADJ
easat-3732	90	3	wavelet	wavelet	NOUN
easat-3732	90	4	transform	transform	NOUN
easat-3732	90	5	based	base	VERB
easat-3732	90	6	self	self	NOUN
easat-3732	90	7	supervised	supervise	VERB
easat-3732	90	8	image	image	NOUN
easat-3732	90	9	denoising	denoise	VERB
easat-3732	90	10	approach	approach	NOUN
easat-3732	90	11	in	in	ADP
easat-3732	90	12	this	this	PRON
easat-3732	90	13	the	the	DET
easat-3732	90	14	self	self	NOUN
easat-3732	90	15	-	-	PUNCT
easat-3732	90	16	supervised	supervise	VERB
easat-3732	90	17	learning	learning	NOUN
easat-3732	90	18	approach	approach	NOUN
easat-3732	90	19	for	for	ADP
easat-3732	90	20	image	image	NOUN
easat-3732	90	21	denoising	denoising	NOUN
easat-3732	90	22	using	use	VERB
easat-3732	90	23	the	the	DET
easat-3732	90	24	discrete	discrete	ADJ
easat-3732	90	25	wavelet	wavelet	NOUN
easat-3732	90	26	transform	transform	NOUN
easat-3732	90	27	(	(	PUNCT
easat-3732	90	28	dwt	dwt	NOUN
easat-3732	90	29	)	)	PUNCT
easat-3732	90	30	has	have	AUX
easat-3732	90	31	been	be	AUX
easat-3732	90	32	proposed	propose	VERB
easat-3732	90	33	.	.	PUNCT
easat-3732	91	1	the	the	DET
easat-3732	91	2	self	self	NOUN
easat-3732	91	3	-	-	PUNCT
easat-3732	91	4	supervised	supervise	VERB
easat-3732	91	5	learning	learning	NOUN
easat-3732	91	6	paradigm	paradigm	NOUN
easat-3732	91	7	allows	allow	VERB
easat-3732	91	8	us	we	PRON
easat-3732	91	9	to	to	PART
easat-3732	91	10	leverage	leverage	VERB
easat-3732	91	11	the	the	DET
easat-3732	91	12	intrinsic	intrinsic	ADJ
easat-3732	91	13	structure	structure	NOUN
easat-3732	91	14	of	of	ADP
easat-3732	91	15	the	the	DET
easat-3732	91	16	data	datum	NOUN
easat-3732	91	17	for	for	ADP
easat-3732	91	18	training	training	NOUN
easat-3732	91	19	without	without	ADP
easat-3732	91	20	requiring	require	VERB
easat-3732	91	21	explicit	explicit	ADJ
easat-3732	91	22	labels	label	NOUN
easat-3732	91	23	.	.	PUNCT
easat-3732	92	1	the	the	DET
easat-3732	92	2	objective	objective	NOUN
easat-3732	92	3	of	of	ADP
easat-3732	92	4	this	this	DET
easat-3732	92	5	approach	approach	NOUN
easat-3732	92	6	is	be	AUX
easat-3732	92	7	to	to	PART
easat-3732	92	8	develop	develop	VERB
easat-3732	92	9	a	a	DET
easat-3732	92	10	deep	deep	ADJ
easat-3732	92	11	learning	learning	NOUN
easat-3732	92	12	model	model	NOUN
easat-3732	92	13	capable	capable	ADJ
easat-3732	92	14	of	of	ADP
easat-3732	92	15	effectively	effectively	ADV
easat-3732	92	16	denoising	denoise	VERB
easat-3732	92	17	images	image	NOUN
easat-3732	92	18	by	by	ADP
easat-3732	92	19	learning	learn	VERB
easat-3732	92	20	from	from	ADP
easat-3732	92	21	noisy	noisy	ADJ
easat-3732	92	22	input	input	NOUN
easat-3732	92	23	data	datum	NOUN
easat-3732	92	24	.	.	PUNCT
easat-3732	93	1	the	the	DET
easat-3732	93	2	model	model	NOUN
easat-3732	93	3	utilizes	utilize	VERB
easat-3732	93	4	a	a	DET
easat-3732	93	5	combination	combination	NOUN
easat-3732	93	6	of	of	ADP
easat-3732	93	7	mean	mean	ADJ
easat-3732	93	8	squared	square	VERB
easat-3732	93	9	error	error	NOUN
easat-3732	93	10	(	(	PUNCT
easat-3732	93	11	mse	mse	NOUN
easat-3732	93	12	)	)	PUNCT
easat-3732	93	13	loss	loss	NOUN
easat-3732	93	14	and	and	CCONJ
easat-3732	93	15	structural	structural	ADJ
easat-3732	93	16	similarity	similarity	NOUN
easat-3732	93	17	index	index	NOUN
easat-3732	93	18	(	(	PUNCT
easat-3732	93	19	ssim	ssim	NOUN
easat-3732	93	20	)	)	PUNCT
easat-3732	93	21	to	to	PART
easat-3732	93	22	optimize	optimize	VERB
easat-3732	93	23	performance	performance	NOUN
easat-3732	93	24	.	.	PUNCT
easat-3732	94	1	figure	figure	NOUN
easat-3732	94	2	1	1	NUM
easat-3732	94	3	(	(	PUNCT
easat-3732	94	4	a	a	NOUN
easat-3732	94	5	)	)	PUNCT
easat-3732	94	6	and	and	CCONJ
easat-3732	94	7	1	1	NUM
easat-3732	94	8	(	(	PUNCT
easat-3732	94	9	b	b	NOUN
easat-3732	94	10	)	)	PUNCT
easat-3732	94	11	7954	7954	NUM
easat-3732	94	12	edelweiss	edelweiss	PROPN
easat-3732	94	13	applied	apply	VERB
easat-3732	94	14	science	science	NOUN
easat-3732	94	15	and	and	CCONJ
easat-3732	94	16	technology	technology	NOUN
easat-3732	94	17	issn	issn	PROPN
easat-3732	94	18	:	:	PUNCT
easat-3732	94	19	2576	2576	NUM
easat-3732	94	20	-	-	SYM
easat-3732	94	21	8484	8484	NUM
easat-3732	94	22	vol	vol	NOUN
easat-3732	94	23	.	.	PROPN
easat-3732	95	1	8	8	NUM
easat-3732	95	2	,	,	PUNCT
easat-3732	95	3	no	no	INTJ
easat-3732	95	4	.	.	NOUN
easat-3732	96	1	6	6	NUM
easat-3732	96	2	:	:	PUNCT
easat-3732	96	3	7951	7951	NUM
easat-3732	96	4	-	-	SYM
easat-3732	96	5	7970	7970	NUM
easat-3732	96	6	,	,	PUNCT
easat-3732	96	7	2024	2024	NUM
easat-3732	96	8	doi	doi	NOUN
easat-3732	96	9	:	:	PUNCT
easat-3732	96	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	96	11	©	©	ADP
easat-3732	96	12	2024	2024	NUM
easat-3732	96	13	by	by	ADP
easat-3732	96	14	the	the	DET
easat-3732	96	15	authors	author	NOUN
easat-3732	96	16	;	;	PUNCT
easat-3732	96	17	licensee	licensee	PROPN
easat-3732	96	18	learning	learning	PROPN
easat-3732	96	19	gate	gate	PROPN
easat-3732	96	20	illustrates	illustrate	VERB
easat-3732	96	21	the	the	DET
easat-3732	96	22	overall	overall	ADJ
easat-3732	96	23	idea	idea	NOUN
easat-3732	96	24	for	for	ADP
easat-3732	96	25	the	the	DET
easat-3732	96	26	dwt	dwt	NOUN
easat-3732	96	27	based	base	VERB
easat-3732	96	28	selfsupervised	selfsupervise	VERB
easat-3732	96	29	model	model	NOUN
easat-3732	96	30	.	.	PUNCT
easat-3732	97	1	algorithm	algorithm	PROPN
easat-3732	97	2	1	1	NUM
easat-3732	97	3	gives	give	VERB
easat-3732	97	4	the	the	DET
easat-3732	97	5	details	detail	NOUN
easat-3732	97	6	of	of	ADP
easat-3732	97	7	dwt	dwt	PROPN
easat-3732	97	8	based	base	VERB
easat-3732	97	9	self	self	NOUN
easat-3732	97	10	-	-	PUNCT
easat-3732	97	11	supervised	supervise	VERB
easat-3732	97	12	training	training	NOUN
easat-3732	97	13	.	.	PUNCT
easat-3732	98	1	2.1.1	2.1.1	X
easat-3732	98	2	.	.	PUNCT
easat-3732	98	3	process	process	NOUN
easat-3732	98	4	1	1	NUM
easat-3732	98	5	.	.	PUNCT
easat-3732	98	6	input	input	NOUN
easat-3732	98	7	image	image	NOUN
easat-3732	98	8	:	:	PUNCT
easat-3732	98	9	the	the	DET
easat-3732	98	10	function	function	NOUN
easat-3732	98	11	takes	take	VERB
easat-3732	98	12	a	a	DET
easat-3732	98	13	noisy	noisy	ADJ
easat-3732	98	14	input	input	NOUN
easat-3732	98	15	image	image	NOUN
easat-3732	98	16	as	as	ADP
easat-3732	98	17	its	its	PRON
easat-3732	98	18	argument	argument	NOUN
easat-3732	98	19	.	.	PUNCT
easat-3732	99	1	this	this	DET
easat-3732	99	2	image	image	NOUN
easat-3732	99	3	is	be	AUX
easat-3732	99	4	typically	typically	ADV
easat-3732	99	5	in	in	ADP
easat-3732	99	6	the	the	DET
easat-3732	99	7	form	form	NOUN
easat-3732	99	8	of	of	ADP
easat-3732	99	9	a	a	DET
easat-3732	99	10	numpy	numpy	NOUN
easat-3732	99	11	array	array	NOUN
easat-3732	99	12	representing	represent	VERB
easat-3732	99	13	pixel	pixel	ADJ
easat-3732	99	14	values	value	NOUN
easat-3732	99	15	.	.	PUNCT
easat-3732	100	1	2	2	X
easat-3732	100	2	.	.	X
easat-3732	100	3	dwt	dwt	NOUN
easat-3732	100	4	decomposition	decomposition	NOUN
easat-3732	100	5	:	:	PUNCT
easat-3732	100	6	the	the	DET
easat-3732	100	7	function	function	NOUN
easat-3732	100	8	first	first	ADV
easat-3732	100	9	applies	apply	VERB
easat-3732	100	10	the	the	DET
easat-3732	100	11	dwt	dwt	NOUN
easat-3732	100	12	algorithm	algorithm	NOUN
easat-3732	100	13	(	(	PUNCT
easat-3732	100	14	pywt.dwt2	pywt.dwt2	NOUN
easat-3732	100	15	)	)	PUNCT
easat-3732	100	16	to	to	PART
easat-3732	100	17	decompose	decompose	VERB
easat-3732	100	18	the	the	DET
easat-3732	100	19	input	input	NOUN
easat-3732	100	20	image	image	NOUN
easat-3732	100	21	into	into	ADP
easat-3732	100	22	approximation	approximation	NOUN
easat-3732	100	23	and	and	CCONJ
easat-3732	100	24	detail	detail	NOUN
easat-3732	100	25	coefficients	coefficient	NOUN
easat-3732	100	26	.	.	PUNCT
easat-3732	101	1	the	the	DET
easat-3732	101	2	pywt.dwt2	pywt.dwt2	PROPN
easat-3732	101	3	function	function	NOUN
easat-3732	101	4	performs	perform	VERB
easat-3732	101	5	a	a	DET
easat-3732	101	6	2d	2d	NUM
easat-3732	101	7	dwt	dwt	NOUN
easat-3732	101	8	decomposition	decomposition	NOUN
easat-3732	101	9	on	on	ADP
easat-3732	101	10	the	the	DET
easat-3732	101	11	image	image	NOUN
easat-3732	101	12	using	use	VERB
easat-3732	101	13	a	a	DET
easat-3732	101	14	specified	specified	ADJ
easat-3732	101	15	wavelet	wavelet	NOUN
easat-3732	101	16	(	(	PUNCT
easat-3732	101	17	in	in	ADP
easat-3732	101	18	this	this	DET
easat-3732	101	19	case	case	NOUN
easat-3732	101	20	,	,	PUNCT
easat-3732	101	21	'	'	PUNCT
easat-3732	101	22	haar	haar	X
easat-3732	101	23	'	'	PUNCT
easat-3732	101	24	,	,	PUNCT
easat-3732	101	25	which	which	PRON
easat-3732	101	26	represents	represent	VERB
easat-3732	101	27	the	the	DET
easat-3732	101	28	haar	haar	PROPN
easat-3732	101	29	wavelet	wavelet	NOUN
easat-3732	101	30	)	)	PUNCT
easat-3732	101	31	.	.	PUNCT
easat-3732	102	1	3	3	X
easat-3732	102	2	.	.	NOUN
easat-3732	102	3	coefficients	coefficient	NOUN
easat-3732	102	4	manipulation	manipulation	NOUN
easat-3732	102	5	:	:	PUNCT
easat-3732	102	6	after	after	ADP
easat-3732	102	7	obtaining	obtain	VERB
easat-3732	102	8	the	the	DET
easat-3732	102	9	decomposition	decomposition	NOUN
easat-3732	102	10	coefficients	coefficient	NOUN
easat-3732	102	11	,	,	PUNCT
easat-3732	102	12	the	the	DET
easat-3732	102	13	function	function	NOUN
easat-3732	102	14	modifies	modify	VERB
easat-3732	102	15	them	they	PRON
easat-3732	102	16	to	to	PART
easat-3732	102	17	remove	remove	VERB
easat-3732	102	18	noise	noise	NOUN
easat-3732	102	19	while	while	SCONJ
easat-3732	102	20	preserving	preserve	VERB
easat-3732	102	21	important	important	ADJ
easat-3732	102	22	image	image	NOUN
easat-3732	102	23	features	feature	NOUN
easat-3732	102	24	.	.	PUNCT
easat-3732	103	1	in	in	ADP
easat-3732	103	2	this	this	DET
easat-3732	103	3	specific	specific	ADJ
easat-3732	103	4	implementation	implementation	NOUN
easat-3732	103	5	,	,	PUNCT
easat-3732	103	6	the	the	DET
easat-3732	103	7	detail	detail	NOUN
easat-3732	103	8	coefficients	coefficient	NOUN
easat-3732	103	9	(	(	PUNCT
easat-3732	103	10	horizontal	horizontal	ADJ
easat-3732	103	11	,	,	PUNCT
easat-3732	103	12	vertical	vertical	ADJ
easat-3732	103	13	,	,	PUNCT
easat-3732	103	14	and	and	CCONJ
easat-3732	103	15	diagonal	diagonal	ADJ
easat-3732	103	16	)	)	PUNCT
easat-3732	103	17	are	be	AUX
easat-3732	103	18	set	set	VERB
easat-3732	103	19	to	to	ADP
easat-3732	103	20	zero	zero	NUM
easat-3732	103	21	,	,	PUNCT
easat-3732	103	22	effectively	effectively	ADV
easat-3732	103	23	removing	remove	VERB
easat-3732	103	24	high	high	ADJ
easat-3732	103	25	-	-	PUNCT
easat-3732	103	26	frequency	frequency	NOUN
easat-3732	103	27	noise	noise	NOUN
easat-3732	103	28	from	from	ADP
easat-3732	103	29	the	the	DET
easat-3732	103	30	image	image	NOUN
easat-3732	103	31	.	.	PUNCT
easat-3732	104	1	4	4	X
easat-3732	104	2	.	.	X
easat-3732	104	3	inverse	inverse	ADJ
easat-3732	104	4	dwt	dwt	NOUN
easat-3732	104	5	:	:	PUNCT
easat-3732	104	6	once	once	SCONJ
easat-3732	104	7	the	the	DET
easat-3732	104	8	coefficients	coefficient	NOUN
easat-3732	104	9	are	be	AUX
easat-3732	104	10	manipulated	manipulate	VERB
easat-3732	104	11	,	,	PUNCT
easat-3732	104	12	the	the	DET
easat-3732	104	13	function	function	NOUN
easat-3732	104	14	performs	perform	VERB
easat-3732	104	15	an	an	DET
easat-3732	104	16	inverse	inverse	ADJ
easat-3732	104	17	dwt	dwt	NOUN
easat-3732	104	18	(	(	PUNCT
easat-3732	104	19	pywt.idwt2	pywt.idwt2	NOUN
easat-3732	104	20	)	)	PUNCT
easat-3732	104	21	to	to	PART
easat-3732	104	22	reconstruct	reconstruct	VERB
easat-3732	104	23	the	the	DET
easat-3732	104	24	denoised	denoise	VERB
easat-3732	104	25	image	image	NOUN
easat-3732	104	26	.	.	PUNCT
easat-3732	105	1	the	the	DET
easat-3732	105	2	pywt.idwt2	pywt.idwt2	NOUN
easat-3732	105	3	function	function	NOUN
easat-3732	105	4	reconstructs	reconstruct	VERB
easat-3732	105	5	the	the	DET
easat-3732	105	6	image	image	NOUN
easat-3732	105	7	from	from	ADP
easat-3732	105	8	the	the	DET
easat-3732	105	9	modified	modify	VERB
easat-3732	105	10	coefficients	coefficient	NOUN
easat-3732	105	11	,	,	PUNCT
easat-3732	105	12	producing	produce	VERB
easat-3732	105	13	the	the	DET
easat-3732	105	14	denoised	denoise	VERB
easat-3732	105	15	output	output	NOUN
easat-3732	105	16	.	.	PUNCT
easat-3732	106	1	5	5	X
easat-3732	106	2	.	.	X
easat-3732	106	3	output	output	NOUN
easat-3732	106	4	:	:	PUNCT
easat-3732	106	5	the	the	DET
easat-3732	106	6	function	function	NOUN
easat-3732	106	7	returns	return	VERB
easat-3732	106	8	the	the	DET
easat-3732	106	9	denoised	denoise	VERB
easat-3732	106	10	image	image	NOUN
easat-3732	106	11	,	,	PUNCT
easat-3732	106	12	which	which	PRON
easat-3732	106	13	is	be	AUX
easat-3732	106	14	typically	typically	ADV
easat-3732	106	15	in	in	ADP
easat-3732	106	16	the	the	DET
easat-3732	106	17	same	same	ADJ
easat-3732	106	18	format	format	NOUN
easat-3732	106	19	as	as	ADP
easat-3732	106	20	the	the	DET
easat-3732	106	21	input	input	NOUN
easat-3732	106	22	image	image	NOUN
easat-3732	106	23	(	(	PUNCT
easat-3732	106	24	numpy	numpy	NOUN
easat-3732	106	25	array	array	NOUN
easat-3732	106	26	)	)	PUNCT
easat-3732	106	27	.	.	PUNCT
easat-3732	107	1	2.1.2	2.1.2	X
easat-3732	107	2	.	.	X
easat-3732	107	3	explanation	explanation	NOUN
easat-3732	107	4	•	•	ADP
easat-3732	107	5	the	the	DET
easat-3732	107	6	denoising	denoising	NOUN
easat-3732	107	7	function	function	NOUN
easat-3732	107	8	starts	start	VERB
easat-3732	107	9	by	by	ADP
easat-3732	107	10	performing	perform	VERB
easat-3732	107	11	a	a	DET
easat-3732	107	12	dwt	dwt	NOUN
easat-3732	107	13	decomposition	decomposition	NOUN
easat-3732	107	14	of	of	ADP
easat-3732	107	15	the	the	DET
easat-3732	107	16	input	input	NOUN
easat-3732	107	17	image	image	NOUN
easat-3732	107	18	using	use	VERB
easat-3732	107	19	the	the	DET
easat-3732	107	20	haar	haar	PROPN
easat-3732	107	21	wavelet	wavelet	NOUN
easat-3732	107	22	.	.	PUNCT
easat-3732	108	1	•	•	NUM
easat-3732	108	2	it	it	PRON
easat-3732	108	3	then	then	ADV
easat-3732	108	4	modifies	modify	VERB
easat-3732	108	5	the	the	DET
easat-3732	108	6	detail	detail	NOUN
easat-3732	108	7	coefficients	coefficient	NOUN
easat-3732	108	8	(	(	PUNCT
easat-3732	108	9	ch	ch	NOUN
easat-3732	108	10	,	,	PUNCT
easat-3732	108	11	cv	cv	PROPN
easat-3732	108	12	,	,	PUNCT
easat-3732	108	13	cd	cd	PROPN
easat-3732	108	14	)	)	PUNCT
easat-3732	108	15	to	to	PART
easat-3732	108	16	remove	remove	VERB
easat-3732	108	17	noise	noise	NOUN
easat-3732	108	18	,	,	PUNCT
easat-3732	108	19	while	while	SCONJ
easat-3732	108	20	keeping	keep	VERB
easat-3732	108	21	the	the	DET
easat-3732	108	22	approximation	approximation	NOUN
easat-3732	108	23	coefficients	coefficient	NOUN
easat-3732	108	24	(	(	PUNCT
easat-3732	108	25	ca	ca	NOUN
easat-3732	108	26	)	)	PUNCT
easat-3732	108	27	unchanged	unchanged	ADJ
easat-3732	108	28	.	.	PUNCT
easat-3732	109	1	•	•	NUM
easat-3732	109	2	finally	finally	ADV
easat-3732	109	3	,	,	PUNCT
easat-3732	109	4	it	it	PRON
easat-3732	109	5	reconstructs	reconstruct	VERB
easat-3732	109	6	the	the	DET
easat-3732	109	7	denoised	denoised	ADJ
easat-3732	109	8	image	image	NOUN
easat-3732	109	9	using	use	VERB
easat-3732	109	10	the	the	DET
easat-3732	109	11	inverse	inverse	ADJ
easat-3732	109	12	dwt	dwt	NOUN
easat-3732	109	13	and	and	CCONJ
easat-3732	109	14	returns	return	VERB
easat-3732	109	15	the	the	DET
easat-3732	109	16	result	result	NOUN
easat-3732	109	17	.	.	PUNCT
easat-3732	110	1	7955	7955	NUM
easat-3732	110	2	edelweiss	edelweiss	PROPN
easat-3732	110	3	applied	apply	VERB
easat-3732	110	4	science	science	NOUN
easat-3732	110	5	and	and	CCONJ
easat-3732	110	6	technology	technology	NOUN
easat-3732	110	7	issn	issn	PROPN
easat-3732	110	8	:	:	PUNCT
easat-3732	110	9	2576	2576	NUM
easat-3732	110	10	-	-	SYM
easat-3732	110	11	8484	8484	NUM
easat-3732	110	12	vol	vol	NOUN
easat-3732	110	13	.	.	PROPN
easat-3732	110	14	8	8	NUM
easat-3732	110	15	,	,	PUNCT
easat-3732	110	16	no	no	INTJ
easat-3732	110	17	.	.	NOUN
easat-3732	110	18	6	6	NUM
easat-3732	110	19	:	:	PUNCT
easat-3732	110	20	7951	7951	NUM
easat-3732	110	21	-	-	SYM
easat-3732	110	22	7970	7970	NUM
easat-3732	110	23	,	,	PUNCT
easat-3732	110	24	2024	2024	NUM
easat-3732	110	25	doi	doi	NOUN
easat-3732	110	26	:	:	PUNCT
easat-3732	110	27	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	110	28	©	©	ADP
easat-3732	110	29	2024	2024	NUM
easat-3732	110	30	by	by	ADP
easat-3732	110	31	the	the	DET
easat-3732	110	32	authors	author	NOUN
easat-3732	110	33	;	;	PUNCT
easat-3732	110	34	licensee	licensee	PROPN
easat-3732	110	35	learning	learn	VERB
easat-3732	110	36	gate	gate	NOUN
easat-3732	110	37	figure	figure	NOUN
easat-3732	110	38	1	1	NUM
easat-3732	110	39	.	.	PUNCT
easat-3732	111	1	(	(	PUNCT
easat-3732	111	2	a	a	X
easat-3732	111	3	)	)	PUNCT
easat-3732	111	4	outline	outline	NOUN
easat-3732	111	5	of	of	ADP
easat-3732	111	6	the	the	DET
easat-3732	111	7	proposed	propose	VERB
easat-3732	111	8	dwt	dwt	NOUN
easat-3732	111	9	based	base	VERB
easat-3732	111	10	self	self	NOUN
easat-3732	111	11	-	-	PUNCT
easat-3732	111	12	supervised	supervise	VERB
easat-3732	111	13	image	image	NOUN
easat-3732	111	14	denoising	denoise	VERB
easat-3732	111	15	modeltraining	modeltraining	NOUN
easat-3732	111	16	.	.	PUNCT
easat-3732	112	1	7956	7956	NUM
easat-3732	112	2	edelweiss	edelweiss	PROPN
easat-3732	112	3	applied	apply	VERB
easat-3732	112	4	science	science	NOUN
easat-3732	112	5	and	and	CCONJ
easat-3732	112	6	technology	technology	NOUN
easat-3732	112	7	issn	issn	PROPN
easat-3732	112	8	:	:	PUNCT
easat-3732	112	9	2576	2576	NUM
easat-3732	112	10	-	-	SYM
easat-3732	112	11	8484	8484	NUM
easat-3732	112	12	vol	vol	NOUN
easat-3732	112	13	.	.	PROPN
easat-3732	112	14	8	8	NUM
easat-3732	112	15	,	,	PUNCT
easat-3732	112	16	no	no	INTJ
easat-3732	112	17	.	.	NOUN
easat-3732	112	18	6	6	NUM
easat-3732	112	19	:	:	PUNCT
easat-3732	112	20	7951	7951	NUM
easat-3732	112	21	-	-	SYM
easat-3732	112	22	7970	7970	NUM
easat-3732	112	23	,	,	PUNCT
easat-3732	112	24	2024	2024	NUM
easat-3732	112	25	doi	doi	NOUN
easat-3732	112	26	:	:	PUNCT
easat-3732	112	27	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	112	28	©	©	ADP
easat-3732	112	29	2024	2024	NUM
easat-3732	112	30	by	by	ADP
easat-3732	112	31	the	the	DET
easat-3732	112	32	authors	author	NOUN
easat-3732	112	33	;	;	PUNCT
easat-3732	112	34	licensee	licensee	PROPN
easat-3732	112	35	learning	learn	VERB
easat-3732	112	36	gate	gate	NOUN
easat-3732	112	37	figure	figure	NOUN
easat-3732	112	38	1	1	NUM
easat-3732	112	39	.	.	PUNCT
easat-3732	113	1	(	(	PUNCT
easat-3732	113	2	b	b	NOUN
easat-3732	113	3	):	):	PUNCT
easat-3732	113	4	proposed	propose	VERB
easat-3732	113	5	dwt	dwt	NOUN
easat-3732	113	6	based	base	VERB
easat-3732	113	7	self	self	NOUN
easat-3732	113	8	-	-	PUNCT
easat-3732	113	9	supervised	supervise	VERB
easat-3732	113	10	image	image	NOUN
easat-3732	113	11	denoising	denoising	NOUN
easat-3732	113	12	modelinference	modelinference	NOUN
easat-3732	113	13	.	.	PUNCT
easat-3732	114	1	algorithm	algorithm	NOUN
easat-3732	114	2	1	1	NUM
easat-3732	114	3	:	:	PUNCT
easat-3732	114	4	proposed	propose	VERB
easat-3732	114	5	discrete	discrete	ADJ
easat-3732	114	6	wavelet	wavelet	NOUN
easat-3732	114	7	transform	transform	NOUN
easat-3732	114	8	based	base	VERB
easat-3732	114	9	self	self	NOUN
easat-3732	114	10	-	-	PUNCT
easat-3732	114	11	supervised	supervise	VERB
easat-3732	114	12	training	training	NOUN
easat-3732	114	13	approach	approach	NOUN
easat-3732	114	14	input	input	NOUN
easat-3732	114	15	:	:	PUNCT
easat-3732	114	16	a	a	DET
easat-3732	114	17	set	set	NOUN
easat-3732	114	18	of	of	ADP
easat-3732	114	19	noisy	noisy	ADJ
easat-3732	114	20	images	image	NOUN
easat-3732	114	21	𝑌	𝑌	PROPN
easat-3732	114	22	=	=	SYM
easat-3732	114	23	{	{	PUNCT
easat-3732	114	24	𝒚𝑖}𝑖=1	𝒚𝑖}𝑖=1	NOUN
easat-3732	114	25	𝑛	𝑛	PROPN
easat-3732	114	26	;	;	PUNCT
easat-3732	114	27	denoising	denoise	VERB
easat-3732	114	28	network	network	NOUN
easat-3732	114	29	𝑓𝜃	𝑓𝜃	ADP
easat-3732	114	30	(	(	PUNCT
easat-3732	114	31	u	u	NOUN
easat-3732	114	32	-	-	NOUN
easat-3732	114	33	net	net	NOUN
easat-3732	114	34	)	)	PUNCT
easat-3732	114	35	;	;	PUNCT
easat-3732	114	36	hyper	hyper	ADJ
easat-3732	114	37	parameters	parameter	NOUN
easat-3732	114	38	:	:	PUNCT
easat-3732	114	39	learning	learn	VERB
easat-3732	114	40	rate	rate	NOUN
easat-3732	114	41	,	,	PUNCT
easat-3732	114	42	batch	batch	NOUN
easat-3732	114	43	size	size	NOUN
easat-3732	114	44	,	,	PUNCT
easat-3732	114	45	number	number	NOUN
easat-3732	114	46	of	of	ADP
easat-3732	114	47	epochs	epoch	NOUN
easat-3732	114	48	hyper	hyper	ADJ
easat-3732	114	49	parameters	parameter	NOUN
easat-3732	114	50	for	for	ADP
easat-3732	114	51	the	the	DET
easat-3732	114	52	loss	loss	NOUN
easat-3732	114	53	function	function	NOUN
easat-3732	114	54	:	:	PUNCT
easat-3732	114	55	𝜆1	𝜆1	NOUN
easat-3732	114	56	:	:	PUNCT
easat-3732	114	57	coefficient	coefficient	NOUN
easat-3732	114	58	of	of	ADP
easat-3732	114	59	mean	mean	ADJ
easat-3732	114	60	squared	square	VERB
easat-3732	114	61	error	error	NOUN
easat-3732	114	62	(	(	PUNCT
easat-3732	114	63	mse	mse	NOUN
easat-3732	114	64	)	)	PUNCT
easat-3732	114	65	in	in	ADP
easat-3732	114	66	the	the	DET
easat-3732	114	67	loss	loss	NOUN
easat-3732	114	68	𝜆2	𝜆2	NOUN
easat-3732	114	69	:	:	PUNCT
easat-3732	114	70	coefficient	coefficient	NOUN
easat-3732	114	71	of	of	ADP
easat-3732	114	72	the	the	DET
easat-3732	114	73	peak	peak	NOUN
easat-3732	114	74	signal	signal	NOUN
easat-3732	114	75	to	to	PART
easat-3732	114	76	noise	noise	VERB
easat-3732	114	77	ratio	ratio	NOUN
easat-3732	114	78	(	(	PUNCT
easat-3732	114	79	psnr	psnr	NOUN
easat-3732	114	80	)	)	PUNCT
easat-3732	114	81	term	term	NOUN
easat-3732	114	82	in	in	ADP
easat-3732	114	83	the	the	DET
easat-3732	114	84	loss	loss	NOUN
easat-3732	114	85	𝜆3	𝜆3	NOUN
easat-3732	114	86	:	:	PUNCT
easat-3732	114	87	coefficient	coefficient	NOUN
easat-3732	114	88	of	of	ADP
easat-3732	114	89	the	the	DET
easat-3732	114	90	structural	structural	ADJ
easat-3732	114	91	similarity	similarity	NOUN
easat-3732	114	92	measure	measure	NOUN
easat-3732	114	93	(	(	PUNCT
easat-3732	114	94	ssim	ssim	NOUN
easat-3732	114	95	)	)	PUNCT
easat-3732	114	96	term	term	NOUN
easat-3732	114	97	in	in	ADP
easat-3732	114	98	the	the	DET
easat-3732	114	99	loss	loss	NOUN
easat-3732	114	100	thresholding	thresholde	VERB
easat-3732	114	101	parameter	parameter	NOUN
easat-3732	114	102	:	:	PUNCT
easat-3732	114	103	for	for	ADP
easat-3732	114	104	soft	soft	ADJ
easat-3732	114	105	thresholding	thresholding	NOUN
easat-3732	114	106	over	over	ADP
easat-3732	114	107	the	the	DET
easat-3732	114	108	transformed	transform	VERB
easat-3732	114	109	image	image	NOUN
easat-3732	114	110	whilenot	whilenot	ADV
easat-3732	114	111	convergeddo	convergeddo	NOUN
easat-3732	114	112	1	1	NUM
easat-3732	114	113	.	.	PUNCT
easat-3732	115	1	sample	sample	VERB
easat-3732	115	2	a	a	DET
easat-3732	115	3	noisy	noisy	ADJ
easat-3732	115	4	image	image	NOUN
easat-3732	115	5	𝒚	𝒚	PROPN
easat-3732	115	6	∈	∈	PROPN
easat-3732	115	7	𝑌	𝑌	PROPN
easat-3732	115	8	;	;	PUNCT
easat-3732	115	9	2	2	X
easat-3732	115	10	.	.	X
easat-3732	115	11	apply	apply	VERB
easat-3732	115	12	2d	2d	NUM
easat-3732	115	13	discrete	discrete	ADJ
easat-3732	115	14	wavelet	wavelet	NOUN
easat-3732	115	15	transform	transform	NOUN
easat-3732	115	16	over	over	ADP
easat-3732	115	17	noisy	noisy	ADJ
easat-3732	115	18	image	image	NOUN
easat-3732	115	19	y	y	NOUN
easat-3732	115	20	using	use	VERB
easat-3732	115	21	the	the	DET
easat-3732	115	22	‘	'	PUNCT
easat-3732	115	23	haar	haar	NOUN
easat-3732	115	24	’	'	PUNCT
easat-3732	115	25	wavelet	wavelet	NOUN
easat-3732	115	26	.	.	PUNCT
easat-3732	116	1	3	3	X
easat-3732	116	2	.	.	PUNCT
easat-3732	117	1	[	[	X
easat-3732	117	2	ll	ll	NOUN
easat-3732	117	3	,	,	PUNCT
easat-3732	117	4	lh	lh	PROPN
easat-3732	117	5	,	,	PUNCT
easat-3732	117	6	hl	hl	NOUN
easat-3732	117	7	,	,	PUNCT
easat-3732	117	8	hh	hh	X
easat-3732	117	9	]	]	X
easat-3732	117	10	=	=	PUNCT
easat-3732	117	11	dwt	dwt	X
easat-3732	117	12	(	(	PUNCT
easat-3732	117	13	y	y	NOUN
easat-3732	117	14	,	,	PUNCT
easat-3732	117	15	‘	'	PUNCT
easat-3732	117	16	haar	haar	X
easat-3732	117	17	’	'	PUNCT
easat-3732	117	18	)	)	PUNCT
easat-3732	117	19	4	4	X
easat-3732	117	20	.	.	PUNCT
easat-3732	118	1	[	[	X
easat-3732	118	2	lh	lh	PROPN
easat-3732	118	3	,	,	PUNCT
easat-3732	118	4	hl	hl	NOUN
easat-3732	118	5	,	,	PUNCT
easat-3732	118	6	hh	hh	X
easat-3732	118	7	]	]	X
easat-3732	118	8	=	=	SYM
easat-3732	118	9	soft	soft	ADJ
easat-3732	118	10	thresholding	thresholding	NOUN
easat-3732	118	11	(	(	PUNCT
easat-3732	118	12	[	[	X
easat-3732	118	13	lh	lh	PROPN
easat-3732	118	14	,	,	PUNCT
easat-3732	118	15	hl	hl	NOUN
easat-3732	118	16	,	,	PUNCT
easat-3732	118	17	hh	hh	PROPN
easat-3732	118	18	]	]	PUNCT
easat-3732	118	19	,	,	PUNCT
easat-3732	118	20	threshold	threshold	NOUN
easat-3732	118	21	)	)	PUNCT
easat-3732	118	22	.	.	PUNCT
easat-3732	119	1	5	5	X
easat-3732	119	2	.	.	X
easat-3732	119	3	y𝐝𝐞𝐫𝐢𝐯𝐞𝐝	y𝐝𝐞𝐫𝐢𝐯𝐞𝐝	NOUN
easat-3732	119	4	=	=	PUNCT
easat-3732	119	5	inverse	inverse	ADJ
easat-3732	119	6	dwt	dwt	NOUN
easat-3732	119	7	(	(	PUNCT
easat-3732	119	8	[	[	X
easat-3732	119	9	ll	ll	NOUN
easat-3732	119	10	,	,	PUNCT
easat-3732	119	11	lh	lh	PROPN
easat-3732	119	12	,	,	PUNCT
easat-3732	119	13	hl	hl	NOUN
easat-3732	119	14	,	,	PUNCT
easat-3732	119	15	hh	hh	PROPN
easat-3732	119	16	]	]	X
easat-3732	119	17	)	)	PUNCT
easat-3732	119	18	/	/	PUNCT
easat-3732	120	1	*	*	PUNCT
easat-3732	120	2	this	this	DET
easat-3732	120	3	reconstructed	reconstructed	ADJ
easat-3732	120	4	image	image	NOUN
easat-3732	120	5	serves	serve	VERB
easat-3732	120	6	as	as	ADP
easat-3732	120	7	the	the	DET
easat-3732	120	8	derived	derive	VERB
easat-3732	120	9	clean	clean	ADJ
easat-3732	120	10	target	target	NOUN
easat-3732	120	11	for	for	ADP
easat-3732	120	12	the	the	DET
easat-3732	120	13	selfsupervised	selfsupervise	VERB
easat-3732	120	14	denoising	denoising	NOUN
easat-3732	120	15	.	.	PUNCT
easat-3732	121	1	*	*	PUNCT
easat-3732	121	2	/	/	SYM
easat-3732	121	3	6	6	NUM
easat-3732	121	4	.	.	PUNCT
easat-3732	122	1	for	for	ADP
easat-3732	122	2	the	the	DET
easat-3732	122	3	original	original	ADJ
easat-3732	122	4	noisy	noisy	ADJ
easat-3732	122	5	image	image	NOUN
easat-3732	122	6	y	y	PROPN
easat-3732	122	7	,	,	PUNCT
easat-3732	122	8	derive	derive	VERB
easat-3732	122	9	the	the	DET
easat-3732	122	10	denoised	denoise	VERB
easat-3732	122	11	image	image	NOUN
easat-3732	122	12	𝑓𝜃(𝒚	𝑓𝜃(𝒚	NOUN
easat-3732	122	13	)	)	PUNCT
easat-3732	122	14	i.e.	i.e.	X
easat-3732	122	15	u	u	NOUN
easat-3732	122	16	-	-	NOUN
easat-3732	122	17	net(y	net(y	VERB
easat-3732	122	18	)	)	PUNCT
easat-3732	122	19	with	with	ADP
easat-3732	122	20	no	no	DET
easat-3732	122	21	gradients	gradient	NOUN
easat-3732	122	22	;	;	PUNCT
easat-3732	122	23	7	7	X
easat-3732	122	24	.	.	X
easat-3732	122	25	update	update	VERB
easat-3732	122	26	the	the	DET
easat-3732	122	27	denoising	denoise	VERB
easat-3732	122	28	network	network	NOUN
easat-3732	122	29	u	u	NOUN
easat-3732	122	30	-	-	NOUN
easat-3732	122	31	net	net	ADJ
easat-3732	122	32	,	,	PUNCT
easat-3732	122	33	𝑓𝜃	𝑓𝜃	ADP
easat-3732	122	34	,	,	PUNCT
easat-3732	122	35	i.e.	i.e.	X
easat-3732	122	36	find	find	VERB
easat-3732	122	37	out	out	ADP
easat-3732	122	38	optimal	optimal	ADJ
easat-3732	122	39	values	value	NOUN
easat-3732	122	40	for	for	ADP
easat-3732	122	41	the	the	DET
easat-3732	122	42	7957	7957	NUM
easat-3732	122	43	edelweiss	edelweiss	PROPN
easat-3732	122	44	applied	apply	VERB
easat-3732	122	45	science	science	NOUN
easat-3732	122	46	and	and	CCONJ
easat-3732	122	47	technology	technology	NOUN
easat-3732	122	48	issn	issn	PROPN
easat-3732	122	49	:	:	PUNCT
easat-3732	122	50	2576	2576	NUM
easat-3732	122	51	-	-	SYM
easat-3732	122	52	8484	8484	NUM
easat-3732	122	53	vol	vol	NOUN
easat-3732	122	54	.	.	PROPN
easat-3732	123	1	8	8	NUM
easat-3732	123	2	,	,	PUNCT
easat-3732	123	3	no	no	INTJ
easat-3732	123	4	.	.	NOUN
easat-3732	124	1	6	6	NUM
easat-3732	124	2	:	:	PUNCT
easat-3732	124	3	7951	7951	NUM
easat-3732	124	4	-	-	SYM
easat-3732	124	5	7970	7970	NUM
easat-3732	124	6	,	,	PUNCT
easat-3732	124	7	2024	2024	NUM
easat-3732	124	8	doi	doi	NOUN
easat-3732	124	9	:	:	PUNCT
easat-3732	124	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	124	11	©	©	ADP
easat-3732	124	12	2024	2024	NUM
easat-3732	124	13	by	by	ADP
easat-3732	124	14	the	the	DET
easat-3732	124	15	authors	author	NOUN
easat-3732	124	16	;	;	PUNCT
easat-3732	124	17	licensee	licensee	PROPN
easat-3732	124	18	learning	learn	VERB
easat-3732	124	19	gate	gate	NOUN
easat-3732	124	20	parameters	parameter	NOUN
easat-3732	124	21	θ	θ	PROPN
easat-3732	124	22	such	such	ADJ
easat-3732	124	23	that	that	DET
easat-3732	124	24	loss	loss	NOUN
easat-3732	124	25	l	l	NOUN
easat-3732	124	26	is	be	AUX
easat-3732	124	27	minimized	minimize	VERB
easat-3732	124	28	.	.	PUNCT
easat-3732	125	1	loss	loss	NOUN
easat-3732	125	2	l	l	NOUN
easat-3732	125	3	=	=	SYM
easat-3732	125	4	ℒtotal	ℒtotal	PROPN
easat-3732	125	5	=	=	PUNCT
easat-3732	125	6	𝜆1ℒ𝑀𝑆𝐸	𝜆1ℒ𝑀𝑆𝐸	NOUN
easat-3732	126	1	+	+	CCONJ
easat-3732	126	2	𝜆2ℒ𝑃𝑆𝑁𝑅	𝜆2ℒ𝑃𝑆𝑁𝑅	ADJ
easat-3732	126	3	+	+	CCONJ
easat-3732	126	4	𝜆3ℒ𝑆𝑆𝐼𝑀	𝜆3ℒ𝑆𝑆𝐼𝑀	VERB
easat-3732	126	5	ℒmse	ℒmse	PROPN
easat-3732	126	6	=	=	SYM
easat-3732	126	7	mse	mse	PROPN
easat-3732	126	8	(	(	PUNCT
easat-3732	126	9	fθ(𝒚	fθ(𝒚	PROPN
easat-3732	126	10	)	)	PUNCT
easat-3732	126	11	,	,	PUNCT
easat-3732	126	12	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	PROPN
easat-3732	126	13	)	)	PUNCT
easat-3732	126	14	ℒpsnr=	ℒpsnr=	NOUN
easat-3732	126	15	100	100	NUM
easat-3732	126	16	−	−	PROPN
easat-3732	126	17	psnr	psnr	NOUN
easat-3732	126	18	(	(	PUNCT
easat-3732	126	19	fθ(𝒚	fθ(𝒚	PROPN
easat-3732	126	20	)	)	PUNCT
easat-3732	126	21	,	,	PUNCT
easat-3732	126	22	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	PROPN
easat-3732	126	23	)	)	PUNCT
easat-3732	126	24	100	100	NUM
easat-3732	126	25	ℒssim=	ℒssim=	NOUN
easat-3732	126	26	1	1	NUM
easat-3732	126	27	ssim	ssim	NOUN
easat-3732	126	28	(	(	PUNCT
easat-3732	126	29	fθ(𝒚	fθ(𝒚	NUM
easat-3732	126	30	)	)	PUNCT
easat-3732	126	31	,	,	PUNCT
easat-3732	126	32	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	PROPN
easat-3732	126	33	)	)	PUNCT
easat-3732	126	34	end	end	NOUN
easat-3732	126	35	while	while	SCONJ
easat-3732	126	36	training	training	NOUN
easat-3732	126	37	:	:	PUNCT
easat-3732	126	38	currently	currently	ADV
easat-3732	126	39	,	,	PUNCT
easat-3732	126	40	the	the	DET
easat-3732	126	41	model	model	NOUN
easat-3732	126	42	is	be	AUX
easat-3732	126	43	trained	train	VERB
easat-3732	126	44	over	over	ADP
easat-3732	126	45	5000	5000	NUM
easat-3732	126	46	images	image	NOUN
easat-3732	126	47	chosen	choose	VERB
easat-3732	126	48	from	from	ADP
easat-3732	126	49	the	the	DET
easat-3732	126	50	imagenet	imagenet	NOUN
easat-3732	126	51	validation	validation	NOUN
easat-3732	126	52	and	and	CCONJ
easat-3732	126	53	kodak	kodak	PROPN
easat-3732	126	54	datasets	dataset	NOUN
easat-3732	126	55	[	[	X
easat-3732	126	56	18	18	NUM
easat-3732	126	57	]	]	PUNCT
easat-3732	126	58	.	.	PUNCT
easat-3732	127	1	total	total	ADJ
easat-3732	127	2	number	number	NOUN
easat-3732	127	3	of	of	ADP
easat-3732	127	4	epochs	epoch	NOUN
easat-3732	127	5	are	be	AUX
easat-3732	127	6	20	20	NUM
easat-3732	127	7	.	.	PUNCT
easat-3732	128	1	learning	learn	VERB
easat-3732	128	2	rate	rate	NOUN
easat-3732	128	3	is	be	AUX
easat-3732	128	4	kept	keep	VERB
easat-3732	128	5	0.01	0.01	NUM
easat-3732	128	6	.	.	PUNCT
easat-3732	129	1	loss	loss	NOUN
easat-3732	129	2	function	function	NOUN
easat-3732	129	3	includes	include	VERB
easat-3732	129	4	both	both	CCONJ
easat-3732	129	5	the	the	DET
easat-3732	129	6	mean	mean	ADJ
easat-3732	129	7	squared	square	VERB
easat-3732	129	8	error	error	NOUN
easat-3732	129	9	(	(	PUNCT
easat-3732	129	10	mse	mse	NOUN
easat-3732	129	11	)	)	PUNCT
easat-3732	129	12	and	and	CCONJ
easat-3732	129	13	structural	structural	ADJ
easat-3732	129	14	similarity	similarity	NOUN
easat-3732	129	15	index	index	NOUN
easat-3732	129	16	(	(	PUNCT
easat-3732	129	17	ssim	ssim	NOUN
easat-3732	129	18	)	)	PUNCT
easat-3732	129	19	measure	measure	NOUN
easat-3732	129	20	.	.	PUNCT
easat-3732	130	1	mse	mse	PROPN
easat-3732	130	2	should	should	AUX
easat-3732	130	3	be	be	AUX
easat-3732	130	4	minimized	minimize	VERB
easat-3732	130	5	while	while	SCONJ
easat-3732	130	6	ssim	ssim	NOUN
easat-3732	130	7	should	should	AUX
easat-3732	130	8	be	be	AUX
easat-3732	130	9	maximized	maximize	VERB
easat-3732	130	10	.	.	PUNCT
easat-3732	131	1	therefore	therefore	ADV
easat-3732	131	2	,	,	PUNCT
easat-3732	131	3	loss	loss	NOUN
easat-3732	131	4	function	function	NOUN
easat-3732	131	5	contains	contain	VERB
easat-3732	131	6	mse	mse	NOUN
easat-3732	131	7	and	and	CCONJ
easat-3732	131	8	1ssim	1ssim	NUM
easat-3732	131	9	terms	term	NOUN
easat-3732	131	10	weighted	weight	VERB
easat-3732	131	11	appropriately	appropriately	ADV
easat-3732	131	12	and	and	CCONJ
easat-3732	131	13	thus	thus	ADV
easat-3732	131	14	focus	focus	VERB
easat-3732	131	15	is	be	AUX
easat-3732	131	16	not	not	PART
easat-3732	131	17	only	only	ADV
easat-3732	131	18	on	on	ADP
easat-3732	131	19	denoising	denoising	NOUN
easat-3732	131	20	but	but	CCONJ
easat-3732	131	21	also	also	ADV
easat-3732	131	22	to	to	PART
easat-3732	131	23	preserve	preserve	VERB
easat-3732	131	24	structural	structural	ADJ
easat-3732	131	25	details	detail	NOUN
easat-3732	131	26	.	.	PUNCT
easat-3732	132	1	models	model	NOUN
easat-3732	132	2	are	be	AUX
easat-3732	132	3	created	create	VERB
easat-3732	132	4	for	for	ADP
easat-3732	132	5	gaussian	gaussian	ADJ
easat-3732	132	6	noise	noise	NOUN
easat-3732	132	7	with	with	ADP
easat-3732	132	8	noise	noise	NOUN
easat-3732	132	9	values	value	NOUN
easat-3732	132	10	20	20	NUM
easat-3732	132	11	,	,	PUNCT
easat-3732	132	12	50	50	NUM
easat-3732	132	13	and	and	CCONJ
easat-3732	132	14	for	for	ADP
easat-3732	132	15	poisson	poisson	NOUN
easat-3732	132	16	noise	noise	NOUN
easat-3732	132	17	with	with	ADP
easat-3732	132	18	parameter	parameter	NOUN
easat-3732	132	19	30	30	NUM
easat-3732	132	20	.	.	PUNCT
easat-3732	133	1	threshold	threshold	NOUN
easat-3732	133	2	is	be	AUX
easat-3732	133	3	set	set	VERB
easat-3732	133	4	based	base	VERB
easat-3732	133	5	on	on	ADP
easat-3732	133	6	noise	noise	NOUN
easat-3732	133	7	magnitude	magnitude	NOUN
easat-3732	133	8	and	and	CCONJ
easat-3732	133	9	type	type	NOUN
easat-3732	133	10	.	.	PUNCT
easat-3732	134	1	figure	figure	NOUN
easat-3732	134	2	2	2	NUM
easat-3732	134	3	(	(	PUNCT
easat-3732	134	4	a	a	NOUN
easat-3732	134	5	)	)	PUNCT
easat-3732	134	6	and	and	CCONJ
easat-3732	134	7	2	2	NUM
easat-3732	134	8	(	(	PUNCT
easat-3732	134	9	b	b	NOUN
easat-3732	134	10	)	)	PUNCT
easat-3732	134	11	illustrates	illustrate	VERB
easat-3732	134	12	the	the	DET
easat-3732	134	13	visual	visual	ADJ
easat-3732	134	14	results	result	NOUN
easat-3732	134	15	for	for	ADP
easat-3732	134	16	the	the	DET
easat-3732	134	17	dwt	dwt	NOUN
easat-3732	134	18	based	base	VERB
easat-3732	134	19	selfsupervised	selfsupervise	VERB
easat-3732	134	20	model.combined	model.combine	VERB
easat-3732	134	21	loss	loss	NOUN
easat-3732	134	22	function	function	NOUN
easat-3732	134	23	idea	idea	NOUN
easat-3732	134	24	is	be	AUX
easat-3732	134	25	from	from	ADP
easat-3732	134	26	[	[	X
easat-3732	134	27	17	17	NUM
easat-3732	134	28	]	]	PUNCT
easat-3732	134	29	.	.	PUNCT
easat-3732	135	1	this	this	DET
easat-3732	135	2	one	one	NOUN
easat-3732	135	3	is	be	AUX
easat-3732	135	4	modification	modification	NOUN
easat-3732	135	5	of	of	ADP
easat-3732	135	6	that	that	PRON
easat-3732	135	7	.	.	PUNCT
easat-3732	136	1	this	this	DET
easat-3732	136	2	dwt	dwt	NOUN
easat-3732	136	3	based	base	VERB
easat-3732	136	4	denoising	denoising	NOUN
easat-3732	136	5	is	be	AUX
easat-3732	136	6	not	not	PART
easat-3732	136	7	necessarily	necessarily	ADV
easat-3732	136	8	remove	remove	VERB
easat-3732	136	9	the	the	DET
easat-3732	136	10	entire	entire	ADJ
easat-3732	136	11	noise	noise	NOUN
easat-3732	136	12	present	present	ADJ
easat-3732	136	13	as	as	SCONJ
easat-3732	136	14	the	the	DET
easat-3732	136	15	threshold	threshold	NOUN
easat-3732	136	16	is	be	AUX
easat-3732	136	17	fixed	fix	VERB
easat-3732	136	18	but	but	CCONJ
easat-3732	136	19	it	it	PRON
easat-3732	136	20	denoises	denoise	VERB
easat-3732	136	21	it	it	PRON
easat-3732	136	22	up	up	ADP
easat-3732	136	23	to	to	ADP
easat-3732	136	24	certain	certain	ADJ
easat-3732	136	25	level	level	NOUN
easat-3732	136	26	.	.	PUNCT
easat-3732	137	1	that	that	PRON
easat-3732	137	2	is	be	AUX
easat-3732	137	3	why	why	SCONJ
easat-3732	137	4	the	the	DET
easat-3732	137	5	target	target	NOUN
easat-3732	137	6	is	be	AUX
easat-3732	137	7	called	call	VERB
easat-3732	137	8	the	the	DET
easat-3732	137	9	pseudo	pseudo	NOUN
easat-3732	137	10	clean	clean	ADJ
easat-3732	137	11	image	image	NOUN
easat-3732	137	12	.	.	PUNCT
easat-3732	138	1	the	the	DET
easat-3732	138	2	output	output	NOUN
easat-3732	138	3	is	be	AUX
easat-3732	138	4	basically	basically	ADV
easat-3732	138	5	cleaner	clean	ADJ
easat-3732	138	6	than	than	ADP
easat-3732	138	7	that	that	PRON
easat-3732	138	8	of	of	ADP
easat-3732	138	9	y.	y.	PROPN
easat-3732	138	10	7958	7958	NUM
easat-3732	138	11	edelweiss	edelweiss	PROPN
easat-3732	138	12	applied	apply	VERB
easat-3732	138	13	science	science	NOUN
easat-3732	138	14	and	and	CCONJ
easat-3732	138	15	technology	technology	NOUN
easat-3732	138	16	issn	issn	PROPN
easat-3732	138	17	:	:	PUNCT
easat-3732	138	18	2576	2576	NUM
easat-3732	138	19	-	-	SYM
easat-3732	138	20	8484	8484	NUM
easat-3732	138	21	vol	vol	NOUN
easat-3732	138	22	.	.	PROPN
easat-3732	139	1	8	8	NUM
easat-3732	139	2	,	,	PUNCT
easat-3732	139	3	no	no	INTJ
easat-3732	139	4	.	.	NOUN
easat-3732	140	1	6	6	NUM
easat-3732	140	2	:	:	PUNCT
easat-3732	140	3	7951	7951	NUM
easat-3732	140	4	-	-	SYM
easat-3732	140	5	7970	7970	NUM
easat-3732	140	6	,	,	PUNCT
easat-3732	140	7	2024	2024	NUM
easat-3732	140	8	doi	doi	NOUN
easat-3732	140	9	:	:	PUNCT
easat-3732	140	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	140	11	©	©	ADP
easat-3732	140	12	2024	2024	NUM
easat-3732	140	13	by	by	ADP
easat-3732	140	14	the	the	DET
easat-3732	140	15	authors	author	NOUN
easat-3732	140	16	;	;	PUNCT
easat-3732	140	17	licensee	licensee	PROPN
easat-3732	140	18	learning	learn	VERB
easat-3732	140	19	gate	gate	NOUN
easat-3732	140	20	7959	7959	NUM
easat-3732	140	21	edelweiss	edelweiss	PROPN
easat-3732	140	22	applied	apply	VERB
easat-3732	140	23	science	science	NOUN
easat-3732	140	24	and	and	CCONJ
easat-3732	140	25	technology	technology	NOUN
easat-3732	140	26	issn	issn	PROPN
easat-3732	140	27	:	:	PUNCT
easat-3732	140	28	2576	2576	NUM
easat-3732	140	29	-	-	SYM
easat-3732	140	30	8484	8484	NUM
easat-3732	140	31	vol	vol	NOUN
easat-3732	140	32	.	.	PROPN
easat-3732	140	33	8	8	NUM
easat-3732	140	34	,	,	PUNCT
easat-3732	140	35	no	no	INTJ
easat-3732	140	36	.	.	NOUN
easat-3732	141	1	6	6	NUM
easat-3732	141	2	:	:	PUNCT
easat-3732	141	3	7951	7951	NUM
easat-3732	141	4	-	-	SYM
easat-3732	141	5	7970	7970	NUM
easat-3732	141	6	,	,	PUNCT
easat-3732	141	7	2024	2024	NUM
easat-3732	141	8	doi	doi	NOUN
easat-3732	141	9	:	:	PUNCT
easat-3732	141	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	141	11	©	©	ADP
easat-3732	141	12	2024	2024	NUM
easat-3732	141	13	by	by	ADP
easat-3732	141	14	the	the	DET
easat-3732	141	15	authors	author	NOUN
easat-3732	141	16	;	;	PUNCT
easat-3732	141	17	licensee	licensee	PROPN
easat-3732	141	18	learning	learn	VERB
easat-3732	141	19	gate	gate	NOUN
easat-3732	141	20	figure	figure	NOUN
easat-3732	141	21	2	2	NUM
easat-3732	141	22	.	.	PUNCT
easat-3732	142	1	(	(	PUNCT
easat-3732	142	2	a	a	X
easat-3732	142	3	):	):	PUNCT
easat-3732	142	4	proposed	propose	VERB
easat-3732	142	5	dwt	dwt	NOUN
easat-3732	142	6	based	base	VERB
easat-3732	142	7	self	self	NOUN
easat-3732	142	8	-	-	PUNCT
easat-3732	142	9	supervised	supervise	VERB
easat-3732	142	10	image	image	NOUN
easat-3732	142	11	denoising	denoising	NOUN
easat-3732	142	12	sample	sample	NOUN
easat-3732	142	13	results	result	NOUN
easat-3732	142	14	:	:	PUNCT
easat-3732	142	15	gaussian	gaussian	ADJ
easat-3732	142	16	noise	noise	NOUN
easat-3732	142	17	with	with	ADP
easat-3732	142	18	σ	σ	PROPN
easat-3732	142	19	in	in	ADP
easat-3732	142	20	[	[	X
easat-3732	142	21	20	20	NUM
easat-3732	142	22	,	,	PUNCT
easat-3732	142	23	50	50	NUM
easat-3732	142	24	]	]	PUNCT
easat-3732	142	25	.	.	PUNCT
easat-3732	143	1	7960	7960	NUM
easat-3732	143	2	edelweiss	edelweiss	PROPN
easat-3732	143	3	applied	apply	VERB
easat-3732	143	4	science	science	NOUN
easat-3732	143	5	and	and	CCONJ
easat-3732	143	6	technology	technology	NOUN
easat-3732	143	7	issn	issn	PROPN
easat-3732	143	8	:	:	PUNCT
easat-3732	143	9	2576	2576	NUM
easat-3732	143	10	-	-	SYM
easat-3732	143	11	8484	8484	NUM
easat-3732	143	12	vol	vol	NOUN
easat-3732	143	13	.	.	PROPN
easat-3732	143	14	8	8	NUM
easat-3732	143	15	,	,	PUNCT
easat-3732	143	16	no	no	INTJ
easat-3732	143	17	.	.	NOUN
easat-3732	144	1	6	6	NUM
easat-3732	144	2	:	:	PUNCT
easat-3732	144	3	7951	7951	NUM
easat-3732	144	4	-	-	SYM
easat-3732	144	5	7970	7970	NUM
easat-3732	144	6	,	,	PUNCT
easat-3732	144	7	2024	2024	NUM
easat-3732	144	8	doi	doi	NOUN
easat-3732	144	9	:	:	PUNCT
easat-3732	144	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	144	11	©	©	ADP
easat-3732	144	12	2024	2024	NUM
easat-3732	144	13	by	by	ADP
easat-3732	144	14	the	the	DET
easat-3732	144	15	authors	author	NOUN
easat-3732	144	16	;	;	PUNCT
easat-3732	144	17	licensee	licensee	PROPN
easat-3732	144	18	learning	learning	NOUN
easat-3732	144	19	gate	gate	NOUN
easat-3732	144	20	7961	7961	NUM
easat-3732	144	21	edelweiss	edelweiss	PROPN
easat-3732	144	22	applied	apply	VERB
easat-3732	144	23	science	science	NOUN
easat-3732	144	24	and	and	CCONJ
easat-3732	144	25	technology	technology	NOUN
easat-3732	144	26	issn	issn	PROPN
easat-3732	144	27	:	:	PUNCT
easat-3732	144	28	2576	2576	NUM
easat-3732	144	29	-	-	SYM
easat-3732	144	30	8484	8484	NUM
easat-3732	144	31	vol	vol	NOUN
easat-3732	144	32	.	.	PROPN
easat-3732	144	33	8	8	NUM
easat-3732	144	34	,	,	PUNCT
easat-3732	144	35	no	no	INTJ
easat-3732	144	36	.	.	NOUN
easat-3732	145	1	6	6	NUM
easat-3732	145	2	:	:	PUNCT
easat-3732	145	3	7951	7951	NUM
easat-3732	145	4	-	-	SYM
easat-3732	145	5	7970	7970	NUM
easat-3732	145	6	,	,	PUNCT
easat-3732	145	7	2024	2024	NUM
easat-3732	145	8	doi	doi	NOUN
easat-3732	145	9	:	:	PUNCT
easat-3732	145	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	145	11	©	©	ADP
easat-3732	145	12	2024	2024	NUM
easat-3732	145	13	by	by	ADP
easat-3732	145	14	the	the	DET
easat-3732	145	15	authors	author	NOUN
easat-3732	145	16	;	;	PUNCT
easat-3732	145	17	licensee	licensee	PROPN
easat-3732	145	18	learning	learn	VERB
easat-3732	145	19	gate	gate	NOUN
easat-3732	145	20	figure	figure	NOUN
easat-3732	145	21	2	2	NUM
easat-3732	145	22	.	.	PUNCT
easat-3732	146	1	(	(	PUNCT
easat-3732	146	2	b	b	NOUN
easat-3732	146	3	):	):	PUNCT
easat-3732	146	4	proposed	propose	VERB
easat-3732	146	5	dwt	dwt	NOUN
easat-3732	146	6	based	base	VERB
easat-3732	146	7	self	self	NOUN
easat-3732	146	8	-	-	PUNCT
easat-3732	146	9	supervised	supervise	VERB
easat-3732	146	10	image	image	NOUN
easat-3732	146	11	denoising	denoising	NOUN
easat-3732	146	12	sample	sample	NOUN
easat-3732	146	13	results	result	NOUN
easat-3732	146	14	:	:	PUNCT
easat-3732	146	15	poisson	poisson	NOUN
easat-3732	146	16	noise	noise	NOUN
easat-3732	146	17	with	with	ADP
easat-3732	146	18	λ=30	λ=30	PROPN
easat-3732	146	19	.	.	PUNCT
easat-3732	147	1	2.1.3	2.1.3	NUM
easat-3732	147	2	.	.	PUNCT
easat-3732	148	1	experimental	experimental	ADJ
easat-3732	148	2	results	result	NOUN
easat-3732	148	3	conclusion	conclusion	NOUN
easat-3732	148	4	:	:	PUNCT
easat-3732	148	5	the	the	DET
easat-3732	148	6	thresholding	thresholde	VERB
easat-3732	148	7	-	-	PUNCT
easat-3732	148	8	based	base	VERB
easat-3732	148	9	wavelet	wavelet	NOUN
easat-3732	148	10	denoising	denoising	NOUN
easat-3732	148	11	method	method	NOUN
easat-3732	148	12	plays	play	VERB
easat-3732	148	13	a	a	DET
easat-3732	148	14	crucial	crucial	ADJ
easat-3732	148	15	role	role	NOUN
easat-3732	148	16	in	in	ADP
easat-3732	148	17	the	the	DET
easat-3732	148	18	denoising	denoising	NOUN
easat-3732	148	19	process	process	NOUN
easat-3732	148	20	by	by	ADP
easat-3732	148	21	leveraging	leverage	VERB
easat-3732	148	22	the	the	DET
easat-3732	148	23	dwt	dwt	NOUN
easat-3732	148	24	algorithm	algorithm	NOUN
easat-3732	148	25	to	to	PART
easat-3732	148	26	effectively	effectively	ADV
easat-3732	148	27	remove	remove	VERB
easat-3732	148	28	noise	noise	NOUN
easat-3732	148	29	from	from	ADP
easat-3732	148	30	the	the	DET
easat-3732	148	31	input	input	NOUN
easat-3732	148	32	image	image	NOUN
easat-3732	148	33	.	.	PUNCT
easat-3732	149	1	by	by	ADP
easat-3732	149	2	combining	combine	VERB
easat-3732	149	3	this	this	DET
easat-3732	149	4	function	function	NOUN
easat-3732	149	5	with	with	ADP
easat-3732	149	6	the	the	DET
easat-3732	149	7	rest	rest	NOUN
easat-3732	149	8	of	of	ADP
easat-3732	149	9	the	the	DET
easat-3732	149	10	image	image	NOUN
easat-3732	149	11	denoising	denoise	VERB
easat-3732	149	12	pipeline	pipeline	NOUN
easat-3732	149	13	,	,	PUNCT
easat-3732	149	14	the	the	DET
easat-3732	149	15	overall	overall	ADJ
easat-3732	149	16	system	system	NOUN
easat-3732	149	17	achieves	achieve	VERB
easat-3732	149	18	robust	robust	ADJ
easat-3732	149	19	and	and	CCONJ
easat-3732	149	20	high	high	ADJ
easat-3732	149	21	-	-	PUNCT
easat-3732	149	22	quality	quality	NOUN
easat-3732	149	23	denoising	denoising	NOUN
easat-3732	149	24	results	result	NOUN
easat-3732	149	25	.	.	PUNCT
easat-3732	150	1	moreover	moreover	ADV
easat-3732	150	2	,	,	PUNCT
easat-3732	150	3	it	it	PRON
easat-3732	150	4	requires	require	VERB
easat-3732	150	5	only	only	ADV
easat-3732	150	6	the	the	DET
easat-3732	150	7	noisy	noisy	ADJ
easat-3732	150	8	input	input	NOUN
easat-3732	150	9	and	and	CCONJ
easat-3732	150	10	not	not	PART
easat-3732	150	11	the	the	DET
easat-3732	150	12	clean	clean	ADJ
easat-3732	150	13	target	target	NOUN
easat-3732	150	14	.	.	PUNCT
easat-3732	151	1	by	by	ADP
easat-3732	151	2	creating	create	VERB
easat-3732	151	3	clean	clean	ADJ
easat-3732	151	4	target	target	NOUN
easat-3732	151	5	from	from	ADP
easat-3732	151	6	the	the	DET
easat-3732	151	7	noisy	noisy	ADJ
easat-3732	151	8	one	one	NOUN
easat-3732	151	9	,	,	PUNCT
easat-3732	151	10	the	the	DET
easat-3732	151	11	u	u	NOUN
easat-3732	151	12	-	-	NOUN
easat-3732	151	13	net	net	ADJ
easat-3732	151	14	[	[	X
easat-3732	151	15	16	16	NUM
easat-3732	151	16	]	]	PUNCT
easat-3732	151	17	is	be	AUX
easat-3732	151	18	trained	train	VERB
easat-3732	151	19	.	.	PUNCT
easat-3732	152	1	experimental	experimental	ADJ
easat-3732	152	2	results	result	NOUN
easat-3732	152	3	show	show	VERB
easat-3732	152	4	better	well	ADJ
easat-3732	152	5	visual	visual	ADJ
easat-3732	152	6	results	result	NOUN
easat-3732	152	7	and	and	CCONJ
easat-3732	152	8	comparable	comparable	ADJ
easat-3732	152	9	psnr	psnr	NOUN
easat-3732	152	10	and	and	CCONJ
easat-3732	152	11	ssim	ssim	NOUN
easat-3732	152	12	.	.	PUNCT
easat-3732	153	1	testing	test	VERB
easat-3732	153	2	over	over	ADP
easat-3732	153	3	limited	limit	VERB
easat-3732	153	4	dataset	dataset	NOUN
easat-3732	153	5	shows	show	VERB
easat-3732	153	6	that	that	SCONJ
easat-3732	153	7	psnr	psnr	NOUN
easat-3732	153	8	and	and	CCONJ
easat-3732	153	9	ssim	ssim	NOUN
easat-3732	153	10	for	for	ADP
easat-3732	153	11	gaussian	gaussian	ADJ
easat-3732	153	12	noise	noise	NOUN
easat-3732	153	13	with	with	ADP
easat-3732	153	14	σ=50	σ=50	PROPN
easat-3732	153	15	is	be	AUX
easat-3732	153	16	30.28	30.28	NUM
easat-3732	153	17	and	and	CCONJ
easat-3732	153	18	0.9292	0.9292	NUM
easat-3732	153	19	respectively	respectively	ADV
easat-3732	153	20	.	.	PUNCT
easat-3732	154	1	for	for	ADP
easat-3732	154	2	poisson	poisson	NOUN
easat-3732	154	3	noise	noise	NOUN
easat-3732	154	4	with	with	ADP
easat-3732	154	5	λ=30	λ=30	PROPN
easat-3732	154	6	,	,	PUNCT
easat-3732	154	7	it	it	PRON
easat-3732	154	8	is	be	AUX
easat-3732	154	9	30.03	30.03	NUM
easat-3732	154	10	and	and	CCONJ
easat-3732	154	11	0.9303	0.9303	NUM
easat-3732	154	12	respectively	respectively	ADV
easat-3732	154	13	.	.	PUNCT
easat-3732	155	1	these	these	PRON
easat-3732	155	2	are	be	AUX
easat-3732	155	3	comparable	comparable	ADJ
easat-3732	155	4	and	and	CCONJ
easat-3732	155	5	yet	yet	ADV
easat-3732	155	6	detailed	detailed	ADJ
easat-3732	155	7	investigation	investigation	NOUN
easat-3732	155	8	will	will	AUX
easat-3732	155	9	be	be	AUX
easat-3732	155	10	done	do	VERB
easat-3732	155	11	for	for	ADP
easat-3732	155	12	various	various	ADJ
easat-3732	155	13	datasets	dataset	NOUN
easat-3732	156	1	[	[	X
easat-3732	156	2	18	18	NUM
easat-3732	156	3	-	-	SYM
easat-3732	156	4	20	20	NUM
easat-3732	156	5	]	]	PUNCT
easat-3732	156	6	.	.	PUNCT
easat-3732	157	1	table	table	NOUN
easat-3732	157	2	1	1	NUM
easat-3732	157	3	represents	represent	VERB
easat-3732	157	4	comparison	comparison	NOUN
easat-3732	157	5	of	of	ADP
easat-3732	157	6	average	average	ADJ
easat-3732	157	7	psnr	psnr	NOUN
easat-3732	157	8	and	and	CCONJ
easat-3732	157	9	ssim	ssim	NOUN
easat-3732	157	10	values	value	NOUN
easat-3732	157	11	for	for	ADP
easat-3732	157	12	the	the	DET
easat-3732	157	13	selfsupervised	selfsupervise	VERB
easat-3732	157	14	denoising	denoising	NOUN
easat-3732	157	15	vs.	vs.	CCONJ
easat-3732	157	16	only	only	ADV
easat-3732	157	17	dwt	dwt	NOUN
easat-3732	157	18	based	base	VERB
easat-3732	157	19	denoising	denoise	VERB
easat-3732	157	20	over	over	ADP
easat-3732	157	21	different	different	ADJ
easat-3732	157	22	noise	noise	NOUN
easat-3732	157	23	types	type	NOUN
easat-3732	157	24	.	.	PUNCT
easat-3732	158	1	table	table	NOUN
easat-3732	158	2	1	1	NUM
easat-3732	158	3	.	.	PUNCT
easat-3732	158	4	comparison	comparison	NOUN
easat-3732	158	5	of	of	ADP
easat-3732	158	6	mean	mean	ADJ
easat-3732	158	7	psnr	psnr	NOUN
easat-3732	158	8	and	and	CCONJ
easat-3732	158	9	ssim	ssim	NOUN
easat-3732	158	10	values	value	NOUN
easat-3732	158	11	of	of	ADP
easat-3732	158	12	self	self	NOUN
easat-3732	158	13	-	-	PUNCT
easat-3732	158	14	supervised	supervise	VERB
easat-3732	158	15	based	base	VERB
easat-3732	158	16	dwt	dwt	NOUN
easat-3732	158	17	approach	approach	NOUN
easat-3732	158	18	against	against	ADP
easat-3732	158	19	simple	simple	ADJ
easat-3732	158	20	dwt	dwt	NOUN
easat-3732	158	21	based	base	VERB
easat-3732	158	22	approach	approach	NOUN
easat-3732	158	23	.	.	PUNCT
easat-3732	159	1	self	self	NOUN
easat-3732	159	2	-	-	PUNCT
easat-3732	159	3	supervised	supervise	VERB
easat-3732	159	4	dwt	dwt	NOUN
easat-3732	159	5	based	base	VERB
easat-3732	159	6	denoising	denoise	VERB
easat-3732	159	7	dwt	dwt	NOUN
easat-3732	159	8	based	base	VERB
easat-3732	159	9	denoising	denoising	NOUN
easat-3732	159	10	noise	noise	NOUN
easat-3732	159	11	type	type	NOUN
easat-3732	159	12	parameter	parameter	NOUN
easat-3732	159	13	value	value	NOUN
easat-3732	159	14	average	average	ADJ
easat-3732	159	15	psnr	psnr	NOUN
easat-3732	159	16	average	average	ADJ
easat-3732	159	17	ssim	ssim	NOUN
easat-3732	159	18	average	average	ADJ
easat-3732	159	19	psnr	psnr	NOUN
easat-3732	159	20	average	average	ADJ
easat-3732	159	21	ssim	ssim	NOUN
easat-3732	159	22	gaussian	gaussian	ADJ
easat-3732	159	23	σ=50	σ=50	PROPN
easat-3732	159	24	30.28	30.28	NUM
easat-3732	159	25	0.9292	0.9292	NUM
easat-3732	159	26	28.72	28.72	NUM
easat-3732	159	27	0.8945	0.8945	NUM
easat-3732	159	28	gaussian	gaussian	ADJ
easat-3732	159	29	σ	σ	X
easat-3732	159	30	∊	∊	PROPN
easat-3732	159	31	(	(	PUNCT
easat-3732	159	32	5,50	5,50	NOUN
easat-3732	159	33	)	)	PUNCT
easat-3732	159	34	31.87	31.87	NUM
easat-3732	159	35	0.9267	0.9267	NUM
easat-3732	159	36	29.25	29.25	NUM
easat-3732	159	37	0.9035	0.9035	NUM
easat-3732	159	38	poisson	poisson	NOUN
easat-3732	159	39	λ=30	λ=30	PROPN
easat-3732	159	40	30.03	30.03	NUM
easat-3732	159	41	0.9303	0.9303	NUM
easat-3732	159	42	28.64	28.64	NUM
easat-3732	159	43	0.8949	0.8949	NUM
easat-3732	159	44	poisson	poisson	NOUN
easat-3732	159	45	λ	λ	X
easat-3732	159	46	∊	∊	PROPN
easat-3732	159	47	(	(	PUNCT
easat-3732	159	48	5,50	5,50	NOUN
easat-3732	159	49	)	)	PUNCT
easat-3732	159	50	30.30	30.30	NUM
easat-3732	159	51	0.9303	0.9303	NUM
easat-3732	159	52	28.50	28.50	NUM
easat-3732	159	53	0.9058	0.9058	NUM
easat-3732	159	54	2.2	2.2	NUM
easat-3732	159	55	.	.	PUNCT
easat-3732	160	1	proposed	propose	VERB
easat-3732	160	2	traditional	traditional	ADJ
easat-3732	160	3	non	non	ADJ
easat-3732	160	4	-	-	ADJ
easat-3732	160	5	local	local	ADJ
easat-3732	160	6	means	mean	NOUN
easat-3732	160	7	(	(	PUNCT
easat-3732	160	8	nlm	nlm	NOUN
easat-3732	160	9	)	)	PUNCT
easat-3732	160	10	algorithm	algorithm	NOUN
easat-3732	160	11	based	base	VERB
easat-3732	160	12	self	self	NOUN
easat-3732	160	13	supervised	supervise	VERB
easat-3732	160	14	image	image	NOUN
easat-3732	160	15	denoising	denoising	NOUN
easat-3732	160	16	approach	approach	NOUN
easat-3732	160	17	this	this	DET
easat-3732	160	18	approach	approach	NOUN
easat-3732	160	19	explores	explore	VERB
easat-3732	160	20	a	a	DET
easat-3732	160	21	u	u	NOUN
easat-3732	160	22	-	-	NOUN
easat-3732	160	23	net	net	ADJ
easat-3732	161	1	[	[	X
easat-3732	161	2	16	16	NUM
easat-3732	161	3	]	]	PUNCT
easat-3732	161	4	based	base	VERB
easat-3732	161	5	deep	deep	ADJ
easat-3732	161	6	learning	learning	NOUN
easat-3732	161	7	approach	approach	NOUN
easat-3732	161	8	combined	combine	VERB
easat-3732	161	9	with	with	ADP
easat-3732	161	10	traditional	traditional	ADJ
easat-3732	161	11	nonlocal	nonlocal	ADJ
easat-3732	161	12	means	mean	NOUN
easat-3732	161	13	(	(	PUNCT
easat-3732	161	14	nlm	nlm	NOUN
easat-3732	161	15	)	)	PUNCT
easat-3732	161	16	denoising	denoising	NOUN
easat-3732	161	17	to	to	PART
easat-3732	161	18	enhance	enhance	VERB
easat-3732	161	19	the	the	DET
easat-3732	161	20	denoising	denoising	NOUN
easat-3732	161	21	capabilities	capability	NOUN
easat-3732	161	22	.	.	PUNCT
easat-3732	162	1	this	this	PRON
easat-3732	162	2	is	be	AUX
easat-3732	162	3	also	also	ADV
easat-3732	162	4	the	the	DET
easat-3732	162	5	self	self	NOUN
easat-3732	162	6	-	-	PUNCT
easat-3732	162	7	supervised	supervise	VERB
easat-3732	162	8	approach	approach	NOUN
easat-3732	162	9	.	.	PUNCT
easat-3732	163	1	noisy	noisy	ADJ
easat-3732	163	2	image	image	NOUN
easat-3732	163	3	is	be	AUX
easat-3732	163	4	taken	take	VERB
easat-3732	163	5	as	as	ADP
easat-3732	163	6	input	input	NOUN
easat-3732	163	7	,	,	PUNCT
easat-3732	163	8	which	which	PRON
easat-3732	163	9	will	will	AUX
easat-3732	163	10	be	be	AUX
easat-3732	163	11	given	give	VERB
easat-3732	163	12	as	as	ADP
easat-3732	163	13	input	input	NOUN
easat-3732	163	14	to	to	ADP
easat-3732	163	15	nlm	nlm	PROPN
easat-3732	163	16	denoising	denoising	NOUN
easat-3732	163	17	.	.	PUNCT
easat-3732	164	1	this	this	PRON
easat-3732	164	2	creates	create	VERB
easat-3732	164	3	7962	7962	NUM
easat-3732	164	4	edelweiss	edelweiss	PROPN
easat-3732	164	5	applied	apply	VERB
easat-3732	164	6	science	science	NOUN
easat-3732	164	7	and	and	CCONJ
easat-3732	164	8	technology	technology	NOUN
easat-3732	164	9	issn	issn	PROPN
easat-3732	164	10	:	:	PUNCT
easat-3732	164	11	2576	2576	NUM
easat-3732	164	12	-	-	SYM
easat-3732	164	13	8484	8484	NUM
easat-3732	164	14	vol	vol	NOUN
easat-3732	164	15	.	.	PROPN
easat-3732	164	16	8	8	NUM
easat-3732	164	17	,	,	PUNCT
easat-3732	164	18	no	no	INTJ
easat-3732	164	19	.	.	NOUN
easat-3732	164	20	6	6	NUM
easat-3732	164	21	:	:	PUNCT
easat-3732	164	22	7951	7951	NUM
easat-3732	164	23	-	-	SYM
easat-3732	164	24	7970	7970	NUM
easat-3732	164	25	,	,	PUNCT
easat-3732	164	26	2024	2024	NUM
easat-3732	164	27	doi	doi	NOUN
easat-3732	164	28	:	:	PUNCT
easat-3732	164	29	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	164	30	©	©	ADP
easat-3732	164	31	2024	2024	NUM
easat-3732	164	32	by	by	ADP
easat-3732	164	33	the	the	DET
easat-3732	164	34	authors	author	NOUN
easat-3732	164	35	;	;	PUNCT
easat-3732	164	36	licensee	licensee	PROPN
easat-3732	164	37	learning	learn	VERB
easat-3732	164	38	gate	gate	VERB
easat-3732	164	39	clean	clean	PROPN
easat-3732	164	40	target	target	NOUN
easat-3732	164	41	corresponding	correspond	VERB
easat-3732	164	42	to	to	ADP
easat-3732	164	43	the	the	DET
easat-3732	164	44	noisy	noisy	ADJ
easat-3732	164	45	image	image	NOUN
easat-3732	164	46	.	.	PUNCT
easat-3732	165	1	now	now	ADV
easat-3732	165	2	,	,	PUNCT
easat-3732	165	3	these	these	DET
easat-3732	165	4	pairs	pair	NOUN
easat-3732	165	5	of	of	ADP
easat-3732	165	6	noisy	noisy	ADJ
easat-3732	165	7	and	and	CCONJ
easat-3732	165	8	clean	clean	ADJ
easat-3732	165	9	target	target	NOUN
easat-3732	165	10	are	be	AUX
easat-3732	165	11	used	use	VERB
easat-3732	165	12	to	to	PART
easat-3732	165	13	train	train	VERB
easat-3732	165	14	u	u	ADJ
easat-3732	165	15	-	-	ADJ
easat-3732	165	16	net	net	ADJ
easat-3732	165	17	network	network	NOUN
easat-3732	165	18	[	[	X
easat-3732	165	19	16	16	NUM
easat-3732	165	20	]	]	PUNCT
easat-3732	165	21	.	.	PUNCT
easat-3732	166	1	the	the	DET
easat-3732	166	2	key	key	ADJ
easat-3732	166	3	innovation	innovation	NOUN
easat-3732	166	4	is	be	AUX
easat-3732	166	5	the	the	DET
easat-3732	166	6	use	use	NOUN
easat-3732	166	7	of	of	ADP
easat-3732	166	8	a	a	DET
easat-3732	166	9	custom	custom	NOUN
easat-3732	166	10	loss	loss	NOUN
easat-3732	166	11	function	function	NOUN
easat-3732	166	12	that	that	SCONJ
easat-3732	166	13	balances	balance	NOUN
easat-3732	166	14	mean	mean	VERB
easat-3732	166	15	squared	square	VERB
easat-3732	166	16	error	error	NOUN
easat-3732	166	17	(	(	PUNCT
easat-3732	166	18	mse	mse	NOUN
easat-3732	166	19	)	)	PUNCT
easat-3732	166	20	and	and	CCONJ
easat-3732	166	21	structural	structural	ADJ
easat-3732	166	22	similarity	similarity	NOUN
easat-3732	166	23	index	index	NOUN
easat-3732	166	24	(	(	PUNCT
easat-3732	166	25	ssim	ssim	NOUN
easat-3732	166	26	)	)	PUNCT
easat-3732	166	27	to	to	PART
easat-3732	166	28	achieve	achieve	VERB
easat-3732	166	29	better	well	ADJ
easat-3732	166	30	perceptual	perceptual	ADJ
easat-3732	166	31	quality	quality	NOUN
easat-3732	166	32	in	in	ADP
easat-3732	166	33	denoised	denoise	VERB
easat-3732	166	34	images	image	NOUN
easat-3732	166	35	.	.	PUNCT
easat-3732	167	1	figure	figure	NOUN
easat-3732	167	2	3	3	NUM
easat-3732	167	3	(	(	PUNCT
easat-3732	167	4	a	a	NOUN
easat-3732	167	5	)	)	PUNCT
easat-3732	167	6	and	and	CCONJ
easat-3732	167	7	3	3	NUM
easat-3732	167	8	(	(	PUNCT
easat-3732	167	9	b	b	NOUN
easat-3732	167	10	)	)	PUNCT
easat-3732	167	11	illustrates	illustrate	VERB
easat-3732	167	12	the	the	DET
easat-3732	167	13	overall	overall	ADJ
easat-3732	167	14	idea	idea	NOUN
easat-3732	167	15	for	for	ADP
easat-3732	167	16	the	the	DET
easat-3732	167	17	nlm	nlm	PROPN
easat-3732	167	18	based	base	VERB
easat-3732	167	19	selfsupervised	selfsupervise	VERB
easat-3732	167	20	model	model	NOUN
easat-3732	167	21	.	.	PUNCT
easat-3732	168	1	algorithm	algorithm	NOUN
easat-3732	168	2	2	2	NUM
easat-3732	168	3	represents	represent	VERB
easat-3732	168	4	nlm	nlm	PROPN
easat-3732	168	5	based	base	VERB
easat-3732	168	6	self	self	NOUN
easat-3732	168	7	-	-	PUNCT
easat-3732	168	8	supervised	supervise	VERB
easat-3732	168	9	image	image	NOUN
easat-3732	168	10	denoiser	denoiser	NOUN
easat-3732	168	11	training	training	NOUN
easat-3732	168	12	.	.	PUNCT
easat-3732	169	1	figure	figure	NOUN
easat-3732	169	2	3	3	NUM
easat-3732	169	3	.	.	PUNCT
easat-3732	170	1	(	(	PUNCT
easat-3732	170	2	a	a	X
easat-3732	170	3	):	):	PUNCT
easat-3732	170	4	outline	outline	NOUN
easat-3732	170	5	of	of	ADP
easat-3732	170	6	the	the	DET
easat-3732	170	7	proposed	propose	VERB
easat-3732	170	8	nlm	nlm	PROPN
easat-3732	170	9	(	(	PUNCT
easat-3732	170	10	non	non	ADJ
easat-3732	170	11	-	-	ADJ
easat-3732	170	12	local	local	ADJ
easat-3732	170	13	means	mean	NOUN
easat-3732	170	14	)	)	PUNCT
easat-3732	170	15	based	base	VERB
easat-3732	170	16	self	self	NOUN
easat-3732	170	17	-	-	PUNCT
easat-3732	170	18	supervised	supervise	VERB
easat-3732	170	19	image	image	NOUN
easat-3732	170	20	denoising	denoising	NOUN
easat-3732	170	21	model	model	NOUN
easat-3732	170	22	–	–	PUNCT
easat-3732	170	23	training	training	NOUN
easat-3732	170	24	.	.	PUNCT
easat-3732	171	1	7963	7963	NUM
easat-3732	171	2	edelweiss	edelweiss	PROPN
easat-3732	171	3	applied	apply	VERB
easat-3732	171	4	science	science	NOUN
easat-3732	171	5	and	and	CCONJ
easat-3732	171	6	technology	technology	NOUN
easat-3732	171	7	issn	issn	PROPN
easat-3732	171	8	:	:	PUNCT
easat-3732	171	9	2576	2576	NUM
easat-3732	171	10	-	-	SYM
easat-3732	171	11	8484	8484	NUM
easat-3732	171	12	vol	vol	NOUN
easat-3732	171	13	.	.	PROPN
easat-3732	171	14	8	8	NUM
easat-3732	171	15	,	,	PUNCT
easat-3732	171	16	no	no	INTJ
easat-3732	171	17	.	.	NOUN
easat-3732	172	1	6	6	NUM
easat-3732	172	2	:	:	PUNCT
easat-3732	172	3	7951	7951	NUM
easat-3732	172	4	-	-	SYM
easat-3732	172	5	7970	7970	NUM
easat-3732	172	6	,	,	PUNCT
easat-3732	172	7	2024	2024	NUM
easat-3732	172	8	doi	doi	NOUN
easat-3732	172	9	:	:	PUNCT
easat-3732	172	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	172	11	©	©	ADP
easat-3732	172	12	2024	2024	NUM
easat-3732	172	13	by	by	ADP
easat-3732	172	14	the	the	DET
easat-3732	172	15	authors	author	NOUN
easat-3732	172	16	;	;	PUNCT
easat-3732	172	17	licensee	licensee	PROPN
easat-3732	172	18	learning	learn	VERB
easat-3732	172	19	gate	gate	PROPN
easat-3732	172	20	figure	figure	NOUN
easat-3732	172	21	3	3	NUM
easat-3732	172	22	.	.	PUNCT
easat-3732	173	1	(	(	PUNCT
easat-3732	173	2	b	b	NOUN
easat-3732	173	3	):	):	PUNCT
easat-3732	173	4	proposed	propose	VERB
easat-3732	173	5	nlm	nlm	PROPN
easat-3732	173	6	based	base	VERB
easat-3732	173	7	self	self	NOUN
easat-3732	173	8	-	-	PUNCT
easat-3732	173	9	supervised	supervise	VERB
easat-3732	173	10	image	image	NOUN
easat-3732	173	11	denoising	denoising	NOUN
easat-3732	173	12	modelinference	modelinference	NOUN
easat-3732	173	13	.	.	PUNCT
easat-3732	174	1	algorithm	algorithm	NOUN
easat-3732	174	2	2	2	NUM
easat-3732	174	3	:	:	PUNCT
easat-3732	174	4	proposed	propose	VERB
easat-3732	174	5	non	non	ADJ
easat-3732	174	6	-	-	ADJ
easat-3732	174	7	local	local	ADJ
easat-3732	174	8	means	mean	NOUN
easat-3732	174	9	algorithm	algorithm	NOUN
easat-3732	174	10	based	base	VERB
easat-3732	174	11	self	self	NOUN
easat-3732	174	12	-	-	PUNCT
easat-3732	174	13	supervised	supervise	VERB
easat-3732	174	14	training	training	NOUN
easat-3732	174	15	approach	approach	NOUN
easat-3732	174	16	input	input	NOUN
easat-3732	174	17	:	:	PUNCT
easat-3732	174	18	a	a	DET
easat-3732	174	19	set	set	NOUN
easat-3732	174	20	of	of	ADP
easat-3732	174	21	noisy	noisy	ADJ
easat-3732	174	22	images	image	NOUN
easat-3732	174	23	𝑌	𝑌	PROPN
easat-3732	174	24	=	=	SYM
easat-3732	174	25	{	{	PUNCT
easat-3732	174	26	𝒚𝑖}𝑖=1	𝒚𝑖}𝑖=1	NOUN
easat-3732	174	27	𝑛	𝑛	PROPN
easat-3732	174	28	;	;	PUNCT
easat-3732	174	29	denoising	denoise	VERB
easat-3732	174	30	network	network	NOUN
easat-3732	174	31	𝑓𝜃	𝑓𝜃	ADP
easat-3732	174	32	(	(	PUNCT
easat-3732	174	33	u	u	NOUN
easat-3732	174	34	-	-	NOUN
easat-3732	174	35	net	net	NOUN
easat-3732	174	36	)	)	PUNCT
easat-3732	174	37	;	;	PUNCT
easat-3732	174	38	hyper	hyper	ADJ
easat-3732	174	39	parameters	parameter	NOUN
easat-3732	174	40	:	:	PUNCT
easat-3732	174	41	learning	learn	VERB
easat-3732	174	42	rate	rate	NOUN
easat-3732	174	43	,	,	PUNCT
easat-3732	174	44	batch	batch	NOUN
easat-3732	174	45	size	size	NOUN
easat-3732	174	46	,	,	PUNCT
easat-3732	174	47	number	number	NOUN
easat-3732	174	48	of	of	ADP
easat-3732	174	49	epochs	epoch	NOUN
easat-3732	174	50	hyper	hyper	ADJ
easat-3732	174	51	parameters	parameter	NOUN
easat-3732	174	52	for	for	ADP
easat-3732	174	53	the	the	DET
easat-3732	174	54	loss	loss	NOUN
easat-3732	174	55	function	function	NOUN
easat-3732	174	56	:	:	PUNCT
easat-3732	174	57	𝜆1	𝜆1	NOUN
easat-3732	174	58	:	:	PUNCT
easat-3732	174	59	coefficient	coefficient	NOUN
easat-3732	174	60	of	of	ADP
easat-3732	174	61	mean	mean	ADJ
easat-3732	174	62	squared	square	VERB
easat-3732	174	63	error	error	NOUN
easat-3732	174	64	(	(	PUNCT
easat-3732	174	65	mse	mse	NOUN
easat-3732	174	66	)	)	PUNCT
easat-3732	174	67	in	in	ADP
easat-3732	174	68	the	the	DET
easat-3732	174	69	loss	loss	NOUN
easat-3732	174	70	𝜆2	𝜆2	NOUN
easat-3732	174	71	:	:	PUNCT
easat-3732	174	72	coefficient	coefficient	NOUN
easat-3732	174	73	of	of	ADP
easat-3732	174	74	the	the	DET
easat-3732	174	75	peak	peak	NOUN
easat-3732	174	76	signal	signal	NOUN
easat-3732	174	77	to	to	PART
easat-3732	174	78	noise	noise	VERB
easat-3732	174	79	ratio	ratio	NOUN
easat-3732	174	80	(	(	PUNCT
easat-3732	174	81	psnr	psnr	NOUN
easat-3732	174	82	)	)	PUNCT
easat-3732	174	83	term	term	NOUN
easat-3732	174	84	in	in	ADP
easat-3732	174	85	the	the	DET
easat-3732	174	86	loss	loss	NOUN
easat-3732	174	87	𝜆3	𝜆3	NOUN
easat-3732	174	88	:	:	PUNCT
easat-3732	174	89	coefficient	coefficient	NOUN
easat-3732	174	90	of	of	ADP
easat-3732	174	91	the	the	DET
easat-3732	174	92	structural	structural	ADJ
easat-3732	174	93	similarity	similarity	NOUN
easat-3732	174	94	measure	measure	NOUN
easat-3732	174	95	(	(	PUNCT
easat-3732	174	96	ssim	ssim	NOUN
easat-3732	174	97	)	)	PUNCT
easat-3732	174	98	term	term	NOUN
easat-3732	174	99	in	in	ADP
easat-3732	174	100	the	the	DET
easat-3732	174	101	loss	loss	NOUN
easat-3732	174	102	parameters	parameter	NOUN
easat-3732	174	103	for	for	ADP
easat-3732	174	104	nlm	nlm	PROPN
easat-3732	174	105	:	:	PUNCT
easat-3732	174	106	search	search	NOUN
easat-3732	174	107	window	window	NOUN
easat-3732	174	108	size	size	NOUN
easat-3732	174	109	,	,	PUNCT
easat-3732	174	110	similarity	similarity	NOUN
easat-3732	174	111	window	window	NOUN
easat-3732	174	112	size	size	NOUN
easat-3732	174	113	,	,	PUNCT
easat-3732	174	114	filtering	filtering	NOUN
easat-3732	174	115	parameter	parameter	NOUN
easat-3732	174	116	,	,	PUNCT
easat-3732	174	117	h	h	NOUN
easat-3732	174	118	for	for	ADP
easat-3732	174	119	adjusting	adjust	VERB
easat-3732	174	120	filtering	filtering	NOUN
easat-3732	174	121	strength	strength	NOUN
easat-3732	174	122	while	while	SCONJ
easat-3732	174	123	not	not	PART
easat-3732	174	124	converged	converge	VERB
easat-3732	174	125	do	do	VERB
easat-3732	174	126	1	1	NUM
easat-3732	174	127	.	.	PUNCT
easat-3732	175	1	sample	sample	VERB
easat-3732	175	2	a	a	DET
easat-3732	175	3	noisy	noisy	ADJ
easat-3732	175	4	image	image	NOUN
easat-3732	175	5	𝒚	𝒚	PROPN
easat-3732	175	6	∈	∈	PROPN
easat-3732	175	7	𝑌	𝑌	PROPN
easat-3732	175	8	;	;	PUNCT
easat-3732	175	9	2	2	X
easat-3732	175	10	.	.	X
easat-3732	176	1	for	for	ADP
easat-3732	176	2	each	each	DET
easat-3732	176	3	pixel	pixel	NOUN
easat-3732	176	4	𝑖	𝑖	X
easat-3732	176	5	in	in	ADP
easat-3732	176	6	the	the	DET
easat-3732	176	7	image	image	NOUN
easat-3732	176	8	y	y	NOUN
easat-3732	176	9	,	,	PUNCT
easat-3732	176	10	extract	extract	VERB
easat-3732	176	11	a	a	DET
easat-3732	176	12	patch	patch	NOUN
easat-3732	176	13	𝑃i	𝑃i	ADV
easat-3732	176	14	centered	center	VERB
easat-3732	176	15	around	around	ADP
easat-3732	176	16	the	the	DET
easat-3732	176	17	pixel	pixel	PROPN
easat-3732	176	18	.	.	PUNCT
easat-3732	177	1	the	the	DET
easat-3732	177	2	patch	patch	ADJ
easat-3732	177	3	size	size	NOUN
easat-3732	177	4	is	be	AUX
easat-3732	177	5	𝑃×𝑃.	𝑃×𝑃.	SYM
easat-3732	177	6	3	3	NUM
easat-3732	177	7	.	.	PUNCT
easat-3732	177	8	for	for	ADP
easat-3732	177	9	each	each	DET
easat-3732	177	10	pixel	pixel	PROPN
easat-3732	177	11	𝑖	𝑖	ADP
easat-3732	177	12	,	,	PUNCT
easat-3732	177	13	within	within	ADP
easat-3732	177	14	the	the	DET
easat-3732	177	15	search	search	NOUN
easat-3732	177	16	window	window	NOUN
easat-3732	177	17	,	,	PUNCT
easat-3732	177	18	compare	compare	VERB
easat-3732	177	19	the	the	DET
easat-3732	177	20	patch	patch	NOUN
easat-3732	177	21	𝑃i	𝑃i	PROPN
easat-3732	177	22	with	with	ADP
easat-3732	177	23	patches	patch	NOUN
easat-3732	177	24	𝑃j	𝑃j	PROPN
easat-3732	177	25	centered	center	VERB
easat-3732	177	26	around	around	ADP
easat-3732	177	27	all	all	DET
easat-3732	177	28	pixels	pixel	NOUN
easat-3732	177	29	𝑗	𝑗	VERB
easat-3732	177	30	within	within	ADP
easat-3732	177	31	the	the	DET
easat-3732	177	32	search	search	NOUN
easat-3732	177	33	window	window	NOUN
easat-3732	177	34	.	.	PUNCT
easat-3732	178	1	4	4	X
easat-3732	178	2	.	.	X
easat-3732	178	3	compute	compute	VERB
easat-3732	178	4	the	the	DET
easat-3732	178	5	weighted	weight	VERB
easat-3732	178	6	euclidean	euclidean	ADJ
easat-3732	178	7	distance	distance	NOUN
easat-3732	178	8	between	between	ADP
easat-3732	178	9	patches	patch	NOUN
easat-3732	178	10	𝑃i	𝑃i	PROPN
easat-3732	178	11	and	and	CCONJ
easat-3732	178	12	𝑃j	𝑃j	PROPN
easat-3732	178	13	.	.	PROPN
easat-3732	178	14	5	5	NUM
easat-3732	178	15	.	.	X
easat-3732	178	16	calculate	calculate	VERB
easat-3732	178	17	the	the	DET
easat-3732	178	18	similarity	similarity	NOUN
easat-3732	178	19	weight	weight	NOUN
easat-3732	178	20	𝑤(𝑖,𝑗	𝑤(𝑖,𝑗	NOUN
easat-3732	178	21	)	)	PUNCT
easat-3732	178	22	based	base	VERB
easat-3732	178	23	on	on	ADP
easat-3732	178	24	the	the	DET
easat-3732	178	25	distance	distance	NOUN
easat-3732	178	26	7964	7964	NUM
easat-3732	178	27	edelweiss	edelweiss	PROPN
easat-3732	178	28	applied	apply	VERB
easat-3732	178	29	science	science	NOUN
easat-3732	178	30	and	and	CCONJ
easat-3732	178	31	technology	technology	NOUN
easat-3732	178	32	issn	issn	PROPN
easat-3732	178	33	:	:	PUNCT
easat-3732	178	34	2576	2576	NUM
easat-3732	178	35	-	-	SYM
easat-3732	178	36	8484	8484	NUM
easat-3732	178	37	vol	vol	NOUN
easat-3732	178	38	.	.	PROPN
easat-3732	178	39	8	8	NUM
easat-3732	178	40	,	,	PUNCT
easat-3732	178	41	no	no	INTJ
easat-3732	178	42	.	.	NOUN
easat-3732	179	1	6	6	NUM
easat-3732	179	2	:	:	PUNCT
easat-3732	179	3	7951	7951	NUM
easat-3732	179	4	-	-	SYM
easat-3732	179	5	7970	7970	NUM
easat-3732	179	6	,	,	PUNCT
easat-3732	179	7	2024	2024	NUM
easat-3732	179	8	doi	doi	NOUN
easat-3732	179	9	:	:	PUNCT
easat-3732	179	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	179	11	©	©	ADP
easat-3732	179	12	2024	2024	NUM
easat-3732	179	13	by	by	ADP
easat-3732	179	14	the	the	DET
easat-3732	179	15	authors	author	NOUN
easat-3732	179	16	;	;	PUNCT
easat-3732	179	17	licensee	licensee	PROPN
easat-3732	179	18	learning	learning	NOUN
easat-3732	179	19	gate	gate	NOUN
easat-3732	179	20	6	6	NUM
easat-3732	179	21	.	.	PUNCT
easat-3732	179	22	normalize	normalize	VERB
easat-3732	179	23	the	the	DET
easat-3732	179	24	weights	weight	NOUN
easat-3732	179	25	for	for	ADP
easat-3732	179	26	each	each	DET
easat-3732	179	27	pixel	pixel	NOUN
easat-3732	179	28	𝑖	𝑖	PRON
easat-3732	179	29	such	such	ADJ
easat-3732	179	30	that	that	SCONJ
easat-3732	179	31	they	they	PRON
easat-3732	179	32	sum	sum	VERB
easat-3732	179	33	to	to	ADP
easat-3732	179	34	1	1	NUM
easat-3732	179	35	:	:	SYM
easat-3732	179	36	7	7	NUM
easat-3732	179	37	.	.	X
easat-3732	179	38	compute	compute	VERB
easat-3732	179	39	the	the	DET
easat-3732	179	40	denoised	denoise	VERB
easat-3732	179	41	pixel	pixel	PROPN
easat-3732	179	42	value	value	NOUN
easat-3732	179	43	𝐼denoised(i	𝐼denoised(i	PROPN
easat-3732	179	44	)	)	PUNCT
easat-3732	179	45	as	as	SCONJ
easat-3732	179	46	the	the	DET
easat-3732	179	47	weighted	weighted	ADJ
easat-3732	179	48	average	average	NOUN
easat-3732	179	49	of	of	ADP
easat-3732	179	50	all	all	DET
easat-3732	179	51	pixels	pixel	NOUN
easat-3732	179	52	𝑗within	𝑗within	VERB
easat-3732	179	53	the	the	DET
easat-3732	179	54	search	search	NOUN
easat-3732	179	55	window	window	NOUN
easat-3732	179	56	:	:	PUNCT
easat-3732	179	57	8	8	X
easat-3732	179	58	.	.	X
easat-3732	179	59	construct	construct	VERB
easat-3732	179	60	the	the	DET
easat-3732	179	61	denoised	denoise	VERB
easat-3732	179	62	image	image	NOUN
easat-3732	179	63	using	use	VERB
easat-3732	179	64	the	the	DET
easat-3732	179	65	computed	computed	ADJ
easat-3732	179	66	values	value	NOUN
easat-3732	179	67	𝐼denoised(i	𝐼denoised(i	ADJ
easat-3732	179	68	)	)	PUNCT
easat-3732	179	69	for	for	ADP
easat-3732	179	70	each	each	DET
easat-3732	179	71	pixel	pixel	PROPN
easat-3732	179	72	i.	i.	PROPN
easat-3732	179	73	9	9	NUM
easat-3732	179	74	.	.	PUNCT
easat-3732	180	1	pseudo	pseudo	NOUN
easat-3732	180	2	-	-	ADJ
easat-3732	180	3	clean	clean	ADJ
easat-3732	180	4	image	image	NOUN
easat-3732	180	5	y𝐝𝐞𝐫𝐢𝐯𝐞𝐝	y𝐝𝐞𝐫𝐢𝐯𝐞𝐝	NOUN
easat-3732	180	6	=	=	SYM
easat-3732	180	7	𝐼denoised	𝐼denoise	VERB
easat-3732	180	8	.	.	PUNCT
easat-3732	180	9	10	10	NUM
easat-3732	180	10	.	.	PUNCT
easat-3732	181	1	for	for	ADP
easat-3732	181	2	the	the	DET
easat-3732	181	3	original	original	ADJ
easat-3732	181	4	noisy	noisy	ADJ
easat-3732	181	5	image	image	NOUN
easat-3732	181	6	y	y	PROPN
easat-3732	181	7	,	,	PUNCT
easat-3732	181	8	derive	derive	VERB
easat-3732	181	9	the	the	DET
easat-3732	181	10	denoised	denoise	VERB
easat-3732	181	11	image	image	NOUN
easat-3732	181	12	𝑓𝜃(𝒚	𝑓𝜃(𝒚	NOUN
easat-3732	181	13	)	)	PUNCT
easat-3732	181	14	i.e.	i.e.	X
easat-3732	181	15	u	u	NOUN
easat-3732	181	16	-	-	NOUN
easat-3732	181	17	net(y	net(y	VERB
easat-3732	181	18	)	)	PUNCT
easat-3732	181	19	with	with	ADP
easat-3732	181	20	no	no	DET
easat-3732	181	21	gradients	gradient	NOUN
easat-3732	181	22	.	.	PUNCT
easat-3732	182	1	11	11	NUM
easat-3732	182	2	.	.	X
easat-3732	182	3	update	update	VERB
easat-3732	182	4	the	the	DET
easat-3732	182	5	denoising	denoise	VERB
easat-3732	182	6	network	network	NOUN
easat-3732	182	7	u	u	NOUN
easat-3732	182	8	-	-	NOUN
easat-3732	182	9	net	net	ADJ
easat-3732	182	10	,	,	PUNCT
easat-3732	182	11	𝑓𝜃	𝑓𝜃	ADP
easat-3732	182	12	,	,	PUNCT
easat-3732	182	13	i.e.	i.e.	X
easat-3732	182	14	find	find	VERB
easat-3732	182	15	out	out	ADP
easat-3732	182	16	the	the	DET
easat-3732	182	17	optimal	optimal	ADJ
easat-3732	182	18	values	value	NOUN
easat-3732	182	19	for	for	ADP
easat-3732	182	20	the	the	DET
easat-3732	182	21	parameters	parameter	NOUN
easat-3732	182	22	θ	θ	NOUN
easat-3732	182	23	such	such	ADJ
easat-3732	182	24	that	that	DET
easat-3732	182	25	loss	loss	NOUN
easat-3732	182	26	l	l	NOUN
easat-3732	182	27	is	be	AUX
easat-3732	182	28	minimized	minimize	VERB
easat-3732	182	29	.	.	PUNCT
easat-3732	183	1	loss	loss	NOUN
easat-3732	183	2	l	l	NOUN
easat-3732	183	3	=	=	SYM
easat-3732	183	4	ℒtotal	ℒtotal	PROPN
easat-3732	183	5	=	=	PUNCT
easat-3732	183	6	𝜆1ℒ𝑀𝑆𝐸	𝜆1ℒ𝑀𝑆𝐸	NOUN
easat-3732	184	1	+	+	CCONJ
easat-3732	184	2	𝜆2ℒ𝑃𝑆𝑁𝑅	𝜆2ℒ𝑃𝑆𝑁𝑅	ADJ
easat-3732	184	3	+	+	CCONJ
easat-3732	184	4	𝜆3ℒ𝑆𝑆𝐼𝑀	𝜆3ℒ𝑆𝑆𝐼𝑀	VERB
easat-3732	184	5	ℒmse	ℒmse	PROPN
easat-3732	184	6	=	=	SYM
easat-3732	184	7	mse	mse	PROPN
easat-3732	184	8	(	(	PUNCT
easat-3732	184	9	fθ(𝒚	fθ(𝒚	PROPN
easat-3732	184	10	)	)	PUNCT
easat-3732	184	11	,	,	PUNCT
easat-3732	184	12	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	PROPN
easat-3732	184	13	)	)	PUNCT
easat-3732	184	14	ℒpsnr=	ℒpsnr=	NOUN
easat-3732	184	15	100	100	NUM
easat-3732	184	16	−	−	PROPN
easat-3732	184	17	psnr	psnr	NOUN
easat-3732	184	18	(	(	PUNCT
easat-3732	184	19	fθ(𝒚	fθ(𝒚	PROPN
easat-3732	184	20	)	)	PUNCT
easat-3732	184	21	,	,	PUNCT
easat-3732	184	22	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	PROPN
easat-3732	184	23	)	)	PUNCT
easat-3732	184	24	100	100	NUM
easat-3732	184	25	ℒssim=	ℒssim=	NOUN
easat-3732	184	26	1	1	NUM
easat-3732	184	27	ssim	ssim	NOUN
easat-3732	184	28	(	(	PUNCT
easat-3732	184	29	fθ(𝒚	fθ(𝒚	NUM
easat-3732	184	30	)	)	PUNCT
easat-3732	184	31	,	,	PUNCT
easat-3732	184	32	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	𝒚𝒅𝒆𝒓𝒊𝒗𝒆𝒅	PROPN
easat-3732	184	33	)	)	PUNCT
easat-3732	184	34	end	end	NOUN
easat-3732	184	35	while	while	SCONJ
easat-3732	184	36	combined	combined	ADJ
easat-3732	184	37	loss	loss	NOUN
easat-3732	184	38	function	function	NOUN
easat-3732	184	39	idea	idea	NOUN
easat-3732	184	40	is	be	AUX
easat-3732	184	41	from	from	ADP
easat-3732	184	42	[	[	X
easat-3732	184	43	17	17	NUM
easat-3732	184	44	]	]	PUNCT
easat-3732	184	45	.	.	PUNCT
easat-3732	185	1	this	this	DET
easat-3732	185	2	one	one	NOUN
easat-3732	185	3	is	be	AUX
easat-3732	185	4	modification	modification	NOUN
easat-3732	185	5	of	of	ADP
easat-3732	185	6	that	that	PRON
easat-3732	185	7	.	.	PUNCT
easat-3732	186	1	the	the	DET
easat-3732	186	2	training	training	NOUN
easat-3732	186	3	procedure	procedure	NOUN
easat-3732	186	4	for	for	ADP
easat-3732	186	5	the	the	DET
easat-3732	186	6	image	image	NOUN
easat-3732	186	7	denoising	denoising	NOUN
easat-3732	186	8	involves	involve	VERB
easat-3732	186	9	several	several	ADJ
easat-3732	186	10	key	key	ADJ
easat-3732	186	11	steps	step	NOUN
easat-3732	186	12	,	,	PUNCT
easat-3732	186	13	beginning	begin	VERB
easat-3732	186	14	with	with	ADP
easat-3732	186	15	data	datum	NOUN
easat-3732	186	16	preparation	preparation	NOUN
easat-3732	186	17	.	.	PUNCT
easat-3732	187	1	clean	clean	ADJ
easat-3732	187	2	images	image	NOUN
easat-3732	187	3	are	be	AUX
easat-3732	187	4	initially	initially	ADV
easat-3732	187	5	loaded	load	VERB
easat-3732	187	6	from	from	ADP
easat-3732	187	7	a	a	DET
easat-3732	187	8	specified	specified	ADJ
easat-3732	187	9	directory	directory	NOUN
easat-3732	187	10	these	these	DET
easat-3732	187	11	images	image	NOUN
easat-3732	187	12	are	be	AUX
easat-3732	187	13	then	then	ADV
easat-3732	187	14	split	split	VERB
easat-3732	187	15	into	into	ADP
easat-3732	187	16	training	training	NOUN
easat-3732	187	17	and	and	CCONJ
easat-3732	187	18	test	test	NOUN
easat-3732	187	19	sets	set	NOUN
easat-3732	187	20	using	use	VERB
easat-3732	187	21	a	a	DET
easat-3732	187	22	90	90	NUM
easat-3732	187	23	-	-	SYM
easat-3732	187	24	10	10	NUM
easat-3732	187	25	split	split	ADJ
easat-3732	187	26	ratio	ratio	NOUN
easat-3732	187	27	,	,	PUNCT
easat-3732	187	28	ensuring	ensure	VERB
easat-3732	187	29	a	a	DET
easat-3732	187	30	fixed	fix	VERB
easat-3732	187	31	random	random	ADJ
easat-3732	187	32	seed	seed	NOUN
easat-3732	187	33	for	for	ADP
easat-3732	187	34	reproducibility	reproducibility	NOUN
easat-3732	187	35	.	.	PUNCT
easat-3732	188	1	to	to	PART
easat-3732	188	2	simulate	simulate	VERB
easat-3732	188	3	noisy	noisy	ADJ
easat-3732	188	4	inputs	input	NOUN
easat-3732	188	5	,	,	PUNCT
easat-3732	188	6	gaussian	gaussian	ADJ
easat-3732	188	7	noise	noise	NOUN
easat-3732	188	8	is	be	AUX
easat-3732	188	9	added	add	VERB
easat-3732	188	10	to	to	ADP
easat-3732	188	11	the	the	DET
easat-3732	188	12	clean	clean	ADJ
easat-3732	188	13	images	image	NOUN
easat-3732	188	14	.	.	PUNCT
easat-3732	189	1	the	the	DET
easat-3732	189	2	noisy	noisy	ADJ
easat-3732	189	3	images	image	NOUN
easat-3732	189	4	are	be	AUX
easat-3732	189	5	then	then	ADV
easat-3732	189	6	denoised	denoise	VERB
easat-3732	189	7	using	use	VERB
easat-3732	189	8	the	the	DET
easat-3732	189	9	non	non	ADJ
easat-3732	189	10	-	-	ADJ
easat-3732	189	11	local	local	ADJ
easat-3732	189	12	means	mean	NOUN
easat-3732	189	13	(	(	PUNCT
easat-3732	189	14	nlm	nlm	NOUN
easat-3732	189	15	)	)	PUNCT
easat-3732	189	16	algorithm	algorithm	NOUN
easat-3732	189	17	to	to	PART
easat-3732	189	18	generate	generate	VERB
easat-3732	189	19	clean	clean	ADJ
easat-3732	189	20	target	target	NOUN
easat-3732	189	21	images	image	NOUN
easat-3732	189	22	for	for	ADP
easat-3732	189	23	training	training	NOUN
easat-3732	189	24	purposes	purpose	NOUN
easat-3732	189	25	.	.	PUNCT
easat-3732	190	1	this	this	DET
easat-3732	190	2	combination	combination	NOUN
easat-3732	190	3	of	of	ADP
easat-3732	190	4	noisy	noisy	ADJ
easat-3732	190	5	input	input	NOUN
easat-3732	190	6	and	and	CCONJ
easat-3732	190	7	clean	clean	ADJ
easat-3732	190	8	target	target	NOUN
easat-3732	190	9	images	image	NOUN
easat-3732	190	10	is	be	AUX
easat-3732	190	11	used	use	VERB
easat-3732	190	12	to	to	PART
easat-3732	190	13	train	train	VERB
easat-3732	190	14	the	the	DET
easat-3732	190	15	denoising	denoising	NOUN
easat-3732	190	16	model	model	NOUN
easat-3732	190	17	.	.	PUNCT
easat-3732	191	1	the	the	DET
easat-3732	191	2	model	model	NOUN
easat-3732	191	3	architecture	architecture	NOUN
easat-3732	191	4	is	be	AUX
easat-3732	191	5	based	base	VERB
easat-3732	191	6	on	on	ADP
easat-3732	191	7	the	the	DET
easat-3732	191	8	u	u	ADJ
easat-3732	191	9	-	-	ADJ
easat-3732	191	10	net	net	ADJ
easat-3732	191	11	structure	structure	NOUN
easat-3732	191	12	,	,	PUNCT
easat-3732	191	13	featuring	feature	VERB
easat-3732	191	14	an	an	DET
easat-3732	191	15	encoder	encoder	NOUN
easat-3732	191	16	-	-	PUNCT
easat-3732	191	17	decoder	decoder	NOUN
easat-3732	191	18	design	design	NOUN
easat-3732	191	19	[	[	X
easat-3732	191	20	16	16	NUM
easat-3732	191	21	]	]	PUNCT
easat-3732	191	22	.	.	PUNCT
easat-3732	192	1	the	the	DET
easat-3732	192	2	encoder	encoder	NOUN
easat-3732	192	3	comprises	comprise	VERB
easat-3732	192	4	convolutional	convolutional	ADJ
easat-3732	192	5	layers	layer	NOUN
easat-3732	192	6	followed	follow	VERB
easat-3732	192	7	by	by	ADP
easat-3732	192	8	max	max	PROPN
easat-3732	192	9	-	-	PUNCT
easat-3732	192	10	pooling	pool	VERB
easat-3732	192	11	layers	layer	NOUN
easat-3732	192	12	to	to	PART
easat-3732	192	13	capture	capture	VERB
easat-3732	192	14	the	the	DET
easat-3732	192	15	context	context	NOUN
easat-3732	192	16	,	,	PUNCT
easat-3732	192	17	while	while	SCONJ
easat-3732	192	18	the	the	DET
easat-3732	192	19	decoder	decoder	NOUN
easat-3732	192	20	uses	use	VERB
easat-3732	192	21	up	up	ADV
easat-3732	192	22	-	-	PUNCT
easat-3732	192	23	sampling	sample	VERB
easat-3732	192	24	layers	layer	NOUN
easat-3732	192	25	followed	follow	VERB
easat-3732	192	26	by	by	ADP
easat-3732	192	27	convolutional	convolutional	ADJ
easat-3732	192	28	layers	layer	NOUN
easat-3732	192	29	to	to	PART
easat-3732	192	30	reconstruct	reconstruct	VERB
easat-3732	192	31	the	the	DET
easat-3732	192	32	denoised	denoise	VERB
easat-3732	192	33	image	image	NOUN
easat-3732	192	34	.	.	PUNCT
easat-3732	193	1	a	a	DET
easat-3732	193	2	custom	custom	NOUN
easat-3732	193	3	loss	loss	NOUN
easat-3732	193	4	function	function	NOUN
easat-3732	193	5	that	that	PRON
easat-3732	193	6	combines	combine	VERB
easat-3732	193	7	mean	mean	VERB
easat-3732	193	8	squared	square	VERB
easat-3732	193	9	error	error	NOUN
easat-3732	193	10	(	(	PUNCT
easat-3732	193	11	mse	mse	NOUN
easat-3732	193	12	)	)	PUNCT
easat-3732	193	13	and	and	CCONJ
easat-3732	193	14	structural	structural	ADJ
easat-3732	193	15	similarity	similarity	NOUN
easat-3732	193	16	index	index	NOUN
easat-3732	193	17	(	(	PUNCT
easat-3732	193	18	ssim	ssim	NOUN
easat-3732	193	19	)	)	PUNCT
easat-3732	193	20	is	be	AUX
easat-3732	193	21	defined	define	VERB
easat-3732	193	22	.	.	PUNCT
easat-3732	194	1	this	this	DET
easat-3732	194	2	loss	loss	NOUN
easat-3732	194	3	function	function	NOUN
easat-3732	194	4	balances	balance	VERB
easat-3732	194	5	pixel	pixel	ADJ
easat-3732	194	6	-	-	ADJ
easat-3732	194	7	wise	wise	ADJ
easat-3732	194	8	accuracy	accuracy	NOUN
easat-3732	194	9	(	(	PUNCT
easat-3732	194	10	through	through	ADP
easat-3732	194	11	mse	mse	PROPN
easat-3732	194	12	)	)	PUNCT
easat-3732	194	13	and	and	CCONJ
easat-3732	194	14	perceptual	perceptual	ADJ
easat-3732	194	15	similarity	similarity	NOUN
easat-3732	194	16	(	(	PUNCT
easat-3732	194	17	through	through	ADP
easat-3732	194	18	ssim	ssim	NOUN
easat-3732	194	19	)	)	PUNCT
easat-3732	194	20	,	,	PUNCT
easat-3732	194	21	ensuring	ensure	VERB
easat-3732	194	22	the	the	DET
easat-3732	194	23	model	model	NOUN
easat-3732	194	24	preserves	preserve	VERB
easat-3732	194	25	structural	structural	ADJ
easat-3732	194	26	details	detail	NOUN
easat-3732	194	27	while	while	SCONJ
easat-3732	194	28	minimizing	minimize	VERB
easat-3732	194	29	pixel	pixel	ADJ
easat-3732	194	30	errors	error	NOUN
easat-3732	194	31	.	.	PUNCT
easat-3732	195	1	the	the	DET
easat-3732	195	2	model	model	NOUN
easat-3732	195	3	is	be	AUX
easat-3732	195	4	compiled	compile	VERB
easat-3732	195	5	using	use	VERB
easat-3732	195	6	the	the	DET
easat-3732	195	7	adam	adam	PROPN
easat-3732	195	8	optimizer	optimizer	NOUN
easat-3732	195	9	with	with	ADP
easat-3732	195	10	a	a	DET
easat-3732	195	11	learning	learn	VERB
easat-3732	195	12	rate	rate	NOUN
easat-3732	195	13	of	of	ADP
easat-3732	195	14	0.001	0.001	NUM
easat-3732	195	15	and	and	CCONJ
easat-3732	195	16	the	the	DET
easat-3732	195	17	custom	custom	NOUN
easat-3732	195	18	loss	loss	NOUN
easat-3732	195	19	function	function	NOUN
easat-3732	195	20	.	.	PUNCT
easat-3732	196	1	data	datum	NOUN
easat-3732	196	2	generators	generator	NOUN
easat-3732	196	3	are	be	AUX
easat-3732	196	4	implemented	implement	VERB
easat-3732	196	5	to	to	PART
easat-3732	196	6	handle	handle	VERB
easat-3732	196	7	the	the	DET
easat-3732	196	8	loading	loading	NOUN
easat-3732	196	9	,	,	PUNCT
easat-3732	196	10	augmenting	augmenting	NOUN
easat-3732	196	11	,	,	PUNCT
easat-3732	196	12	and	and	CCONJ
easat-3732	196	13	batching	batching	NOUN
easat-3732	196	14	of	of	ADP
easat-3732	196	15	images	image	NOUN
easat-3732	196	16	during	during	ADP
easat-3732	196	17	both	both	DET
easat-3732	196	18	training	training	NOUN
easat-3732	196	19	and	and	CCONJ
easat-3732	196	20	evaluation	evaluation	NOUN
easat-3732	196	21	.	.	PUNCT
easat-3732	197	1	these	these	DET
easat-3732	197	2	generators	generator	NOUN
easat-3732	197	3	ensure	ensure	VERB
easat-3732	197	4	efficient	efficient	ADJ
easat-3732	197	5	data	datum	NOUN
easat-3732	197	6	handling	handling	NOUN
easat-3732	197	7	and	and	CCONJ
easat-3732	197	8	processing	processing	NOUN
easat-3732	197	9	throughout	throughout	ADP
easat-3732	197	10	the	the	DET
easat-3732	197	11	training	training	NOUN
easat-3732	197	12	process	process	NOUN
easat-3732	197	13	.	.	PUNCT
easat-3732	198	1	the	the	DET
easat-3732	198	2	model	model	NOUN
easat-3732	198	3	is	be	AUX
easat-3732	198	4	trained	train	VERB
easat-3732	198	5	for	for	ADP
easat-3732	198	6	100	100	NUM
easat-3732	198	7	epochs	epoch	NOUN
easat-3732	198	8	using	use	VERB
easat-3732	198	9	the	the	DET
easat-3732	198	10	training	training	NOUN
easat-3732	198	11	data	datum	NOUN
easat-3732	198	12	generator	generator	NOUN
easat-3732	198	13	,	,	PUNCT
easat-3732	198	14	with	with	ADP
easat-3732	198	15	a	a	DET
easat-3732	198	16	batch	batch	NOUN
easat-3732	198	17	size	size	NOUN
easat-3732	198	18	set	set	VERB
easat-3732	198	19	to	to	ADP
easat-3732	198	20	32	32	NUM
easat-3732	198	21	.	.	PUNCT
easat-3732	199	1	after	after	ADP
easat-3732	199	2	training	training	NOUN
easat-3732	199	3	,	,	PUNCT
easat-3732	199	4	the	the	DET
easat-3732	199	5	model	model	NOUN
easat-3732	199	6	's	's	PART
easat-3732	199	7	performance	performance	NOUN
easat-3732	199	8	is	be	AUX
easat-3732	199	9	evaluated	evaluate	VERB
easat-3732	199	10	on	on	ADP
easat-3732	199	11	the	the	DET
easat-3732	199	12	test	test	NOUN
easat-3732	199	13	set	set	VERB
easat-3732	199	14	using	use	VERB
easat-3732	199	15	psnr	psnr	NOUN
easat-3732	199	16	and	and	CCONJ
easat-3732	199	17	ssim	ssim	NOUN
easat-3732	199	18	metrics	metric	NOUN
easat-3732	199	19	to	to	PART
easat-3732	199	20	quantify	quantify	VERB
easat-3732	199	21	the	the	DET
easat-3732	199	22	quality	quality	NOUN
easat-3732	199	23	of	of	ADP
easat-3732	199	24	denoised	denoise	VERB
easat-3732	199	25	images	image	NOUN
easat-3732	199	26	.	.	PUNCT
easat-3732	200	1	the	the	DET
easat-3732	200	2	average	average	ADJ
easat-3732	200	3	psnr	psnr	NOUN
easat-3732	200	4	and	and	CCONJ
easat-3732	200	5	ssim	ssim	NOUN
easat-3732	200	6	values	value	NOUN
easat-3732	200	7	are	be	AUX
easat-3732	200	8	calculated	calculate	VERB
easat-3732	200	9	to	to	PART
easat-3732	200	10	provide	provide	VERB
easat-3732	200	11	an	an	DET
easat-3732	200	12	overall	overall	ADJ
easat-3732	200	13	measure	measure	NOUN
easat-3732	200	14	of	of	ADP
easat-3732	200	15	the	the	DET
easat-3732	200	16	model	model	NOUN
easat-3732	200	17	's	's	PART
easat-3732	200	18	performance	performance	NOUN
easat-3732	200	19	.	.	PUNCT
easat-3732	201	1	additionally	additionally	ADV
easat-3732	201	2	,	,	PUNCT
easat-3732	201	3	a	a	DET
easat-3732	201	4	visualization	visualization	NOUN
easat-3732	201	5	function	function	NOUN
easat-3732	201	6	is	be	AUX
easat-3732	201	7	employed	employ	VERB
easat-3732	201	8	to	to	PART
easat-3732	201	9	display	display	VERB
easat-3732	201	10	clean	clean	ADJ
easat-3732	201	11	test	test	NOUN
easat-3732	201	12	images	image	NOUN
easat-3732	201	13	,	,	PUNCT
easat-3732	201	14	their	their	PRON
easat-3732	201	15	noisy	noisy	ADJ
easat-3732	201	16	versions	version	NOUN
easat-3732	201	17	,	,	PUNCT
easat-3732	201	18	and	and	CCONJ
easat-3732	201	19	the	the	DET
easat-3732	201	20	denoised	denoise	VERB
easat-3732	201	21	outputs	output	NOUN
easat-3732	201	22	from	from	ADP
easat-3732	201	23	the	the	DET
easat-3732	201	24	model	model	NOUN
easat-3732	201	25	.	.	PUNCT
easat-3732	202	1	this	this	DET
easat-3732	202	2	7965	7965	NUM
easat-3732	202	3	edelweiss	edelweiss	PROPN
easat-3732	202	4	applied	apply	VERB
easat-3732	202	5	science	science	NOUN
easat-3732	202	6	and	and	CCONJ
easat-3732	202	7	technology	technology	NOUN
easat-3732	202	8	issn	issn	PROPN
easat-3732	202	9	:	:	PUNCT
easat-3732	202	10	2576	2576	NUM
easat-3732	202	11	-	-	SYM
easat-3732	202	12	8484	8484	NUM
easat-3732	202	13	vol	vol	NOUN
easat-3732	202	14	.	.	PROPN
easat-3732	202	15	8	8	NUM
easat-3732	202	16	,	,	PUNCT
easat-3732	202	17	no	no	INTJ
easat-3732	202	18	.	.	NOUN
easat-3732	203	1	6	6	NUM
easat-3732	203	2	:	:	PUNCT
easat-3732	203	3	7951	7951	NUM
easat-3732	203	4	-	-	SYM
easat-3732	203	5	7970	7970	NUM
easat-3732	203	6	,	,	PUNCT
easat-3732	203	7	2024	2024	NUM
easat-3732	203	8	doi	doi	NOUN
easat-3732	203	9	:	:	PUNCT
easat-3732	203	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	203	11	©	©	ADP
easat-3732	203	12	2024	2024	NUM
easat-3732	203	13	by	by	ADP
easat-3732	203	14	the	the	DET
easat-3732	203	15	authors	author	NOUN
easat-3732	203	16	;	;	PUNCT
easat-3732	203	17	licensee	licensee	PROPN
easat-3732	203	18	learning	learning	NOUN
easat-3732	203	19	gate	gate	NOUN
easat-3732	203	20	visualization	visualization	NOUN
easat-3732	203	21	demonstrates	demonstrate	VERB
easat-3732	203	22	the	the	DET
easat-3732	203	23	effectiveness	effectiveness	NOUN
easat-3732	203	24	of	of	ADP
easat-3732	203	25	the	the	DET
easat-3732	203	26	denoising	denoising	NOUN
easat-3732	203	27	process	process	NOUN
easat-3732	203	28	,	,	PUNCT
easat-3732	203	29	showcasing	showcase	VERB
easat-3732	203	30	both	both	CCONJ
easat-3732	203	31	quantitative	quantitative	ADJ
easat-3732	203	32	and	and	CCONJ
easat-3732	203	33	qualitative	qualitative	ADJ
easat-3732	203	34	improvements	improvement	NOUN
easat-3732	203	35	in	in	ADP
easat-3732	203	36	image	image	NOUN
easat-3732	203	37	quality	quality	NOUN
easat-3732	203	38	.	.	PUNCT
easat-3732	204	1	figure	figure	NOUN
easat-3732	204	2	4(a	4(a	NUM
easat-3732	204	3	)	)	PUNCT
easat-3732	204	4	and	and	CCONJ
easat-3732	204	5	4(b	4(b	NUM
easat-3732	204	6	)	)	PUNCT
easat-3732	204	7	illustrates	illustrate	VERB
easat-3732	204	8	the	the	DET
easat-3732	204	9	visual	visual	ADJ
easat-3732	204	10	results	result	NOUN
easat-3732	204	11	for	for	ADP
easat-3732	204	12	the	the	DET
easat-3732	204	13	nlm	nlm	PROPN
easat-3732	204	14	based	base	VERB
easat-3732	204	15	selfsupervised	selfsupervise	VERB
easat-3732	204	16	model	model	NOUN
easat-3732	204	17	.	.	PUNCT
easat-3732	205	1	7966	7966	NUM
easat-3732	205	2	edelweiss	edelweiss	PROPN
easat-3732	205	3	applied	apply	VERB
easat-3732	205	4	science	science	NOUN
easat-3732	205	5	and	and	CCONJ
easat-3732	205	6	technology	technology	NOUN
easat-3732	205	7	issn	issn	PROPN
easat-3732	205	8	:	:	PUNCT
easat-3732	205	9	2576	2576	NUM
easat-3732	205	10	-	-	SYM
easat-3732	205	11	8484	8484	NUM
easat-3732	205	12	vol	vol	NOUN
easat-3732	205	13	.	.	PROPN
easat-3732	205	14	8	8	NUM
easat-3732	205	15	,	,	PUNCT
easat-3732	205	16	no	no	INTJ
easat-3732	205	17	.	.	NOUN
easat-3732	205	18	6	6	NUM
easat-3732	205	19	:	:	PUNCT
easat-3732	205	20	7951	7951	NUM
easat-3732	205	21	-	-	SYM
easat-3732	205	22	7970	7970	NUM
easat-3732	205	23	,	,	PUNCT
easat-3732	205	24	2024	2024	NUM
easat-3732	205	25	doi	doi	NOUN
easat-3732	205	26	:	:	PUNCT
easat-3732	205	27	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	205	28	©	©	ADP
easat-3732	205	29	2024	2024	NUM
easat-3732	205	30	by	by	ADP
easat-3732	205	31	the	the	DET
easat-3732	205	32	authors	author	NOUN
easat-3732	205	33	;	;	PUNCT
easat-3732	205	34	licensee	licensee	PROPN
easat-3732	205	35	learning	learn	VERB
easat-3732	205	36	gate	gate	PROPN
easat-3732	205	37	figure	figure	NOUN
easat-3732	205	38	4	4	NUM
easat-3732	205	39	(	(	PUNCT
easat-3732	205	40	a	a	X
easat-3732	205	41	):	):	PUNCT
easat-3732	205	42	proposed	propose	VERB
easat-3732	205	43	nlm	nlm	PROPN
easat-3732	205	44	based	base	VERB
easat-3732	205	45	self	self	NOUN
easat-3732	205	46	-	-	PUNCT
easat-3732	205	47	supervised	supervise	VERB
easat-3732	205	48	image	image	NOUN
easat-3732	205	49	denoising	denoising	NOUN
easat-3732	205	50	sample	sample	NOUN
easat-3732	205	51	results	result	NOUN
easat-3732	205	52	-	-	PUNCT
easat-3732	205	53	gaussian	gaussian	ADJ
easat-3732	205	54	noise	noise	NOUN
easat-3732	205	55	with	with	ADP
easat-3732	205	56	σ	σ	NUM
easat-3732	205	57	from	from	ADP
easat-3732	205	58	[	[	X
easat-3732	205	59	20	20	NUM
easat-3732	205	60	,	,	PUNCT
easat-3732	205	61	50	50	NUM
easat-3732	205	62	]	]	PUNCT
easat-3732	205	63	.	.	PUNCT
easat-3732	206	1	7967	7967	NUM
easat-3732	206	2	edelweiss	edelweiss	PROPN
easat-3732	206	3	applied	apply	VERB
easat-3732	206	4	science	science	NOUN
easat-3732	206	5	and	and	CCONJ
easat-3732	206	6	technology	technology	NOUN
easat-3732	206	7	issn	issn	PROPN
easat-3732	206	8	:	:	PUNCT
easat-3732	206	9	2576	2576	NUM
easat-3732	206	10	-	-	SYM
easat-3732	206	11	8484	8484	NUM
easat-3732	206	12	vol	vol	NOUN
easat-3732	206	13	.	.	PROPN
easat-3732	206	14	8	8	NUM
easat-3732	206	15	,	,	PUNCT
easat-3732	206	16	no	no	INTJ
easat-3732	206	17	.	.	NOUN
easat-3732	207	1	6	6	NUM
easat-3732	207	2	:	:	PUNCT
easat-3732	207	3	7951	7951	NUM
easat-3732	207	4	-	-	SYM
easat-3732	207	5	7970	7970	NUM
easat-3732	207	6	,	,	PUNCT
easat-3732	207	7	2024	2024	NUM
easat-3732	207	8	doi	doi	NOUN
easat-3732	207	9	:	:	PUNCT
easat-3732	207	10	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	207	11	©	©	ADP
easat-3732	207	12	2024	2024	NUM
easat-3732	207	13	by	by	ADP
easat-3732	207	14	the	the	DET
easat-3732	207	15	authors	author	NOUN
easat-3732	207	16	;	;	PUNCT
easat-3732	207	17	licensee	licensee	PROPN
easat-3732	207	18	learning	learn	VERB
easat-3732	207	19	gate	gate	NOUN
easat-3732	207	20	7968	7968	NUM
easat-3732	207	21	edelweiss	edelweiss	PROPN
easat-3732	207	22	applied	apply	VERB
easat-3732	207	23	science	science	NOUN
easat-3732	207	24	and	and	CCONJ
easat-3732	207	25	technology	technology	NOUN
easat-3732	207	26	issn	issn	PROPN
easat-3732	207	27	:	:	PUNCT
easat-3732	207	28	2576	2576	NUM
easat-3732	207	29	-	-	SYM
easat-3732	207	30	8484	8484	NUM
easat-3732	207	31	vol	vol	NOUN
easat-3732	207	32	.	.	PROPN
easat-3732	207	33	8	8	NUM
easat-3732	207	34	,	,	PUNCT
easat-3732	207	35	no	no	INTJ
easat-3732	207	36	.	.	NOUN
easat-3732	207	37	6	6	NUM
easat-3732	207	38	:	:	PUNCT
easat-3732	207	39	7951	7951	NUM
easat-3732	207	40	-	-	SYM
easat-3732	207	41	7970	7970	NUM
easat-3732	207	42	,	,	PUNCT
easat-3732	207	43	2024	2024	NUM
easat-3732	207	44	doi	doi	NOUN
easat-3732	207	45	:	:	PUNCT
easat-3732	207	46	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	207	47	©	©	ADP
easat-3732	207	48	2024	2024	NUM
easat-3732	207	49	by	by	ADP
easat-3732	207	50	the	the	DET
easat-3732	207	51	authors	author	NOUN
easat-3732	207	52	;	;	PUNCT
easat-3732	208	1	licensee	licensee	PROPN
easat-3732	208	2	learning	learn	VERB
easat-3732	208	3	gate	gate	NOUN
easat-3732	208	4	figure	figure	NOUN
easat-3732	208	5	4	4	NUM
easat-3732	208	6	.	.	PUNCT
easat-3732	208	7	(	(	PUNCT
easat-3732	208	8	b	b	NOUN
easat-3732	208	9	):	):	PUNCT
easat-3732	208	10	proposed	propose	VERB
easat-3732	208	11	nlm	nlm	PROPN
easat-3732	208	12	based	base	VERB
easat-3732	208	13	self	self	NOUN
easat-3732	208	14	-	-	PUNCT
easat-3732	208	15	supervised	supervise	VERB
easat-3732	208	16	image	image	NOUN
easat-3732	208	17	denoising	denoising	NOUN
easat-3732	208	18	sample	sample	NOUN
easat-3732	208	19	results	result	NOUN
easat-3732	208	20	-	-	PUNCT
easat-3732	208	21	poisson	poisson	NOUN
easat-3732	208	22	noise	noise	NOUN
easat-3732	208	23	with	with	ADP
easat-3732	208	24	λ	λ	NOUN
easat-3732	208	25	=	=	SYM
easat-3732	208	26	30	30	NUM
easat-3732	208	27	.	.	PUNCT
easat-3732	208	28	2.2.1	2.2.1	NUM
easat-3732	208	29	.	.	PUNCT
easat-3732	209	1	experimental	experimental	ADJ
easat-3732	209	2	results	result	NOUN
easat-3732	209	3	experimental	experimental	ADJ
easat-3732	209	4	results	result	NOUN
easat-3732	209	5	show	show	VERB
easat-3732	209	6	better	well	ADJ
easat-3732	209	7	visual	visual	ADJ
easat-3732	209	8	results	result	NOUN
easat-3732	209	9	and	and	CCONJ
easat-3732	209	10	comparable	comparable	ADJ
easat-3732	209	11	psnr	psnr	NOUN
easat-3732	209	12	and	and	CCONJ
easat-3732	209	13	ssim	ssim	NOUN
easat-3732	209	14	.	.	PUNCT
easat-3732	210	1	testing	test	VERB
easat-3732	210	2	over	over	ADP
easat-3732	210	3	limited	limited	ADJ
easat-3732	210	4	dataset	dataset	NOUN
easat-3732	210	5	of	of	ADP
easat-3732	210	6	image	image	NOUN
easat-3732	210	7	net	net	NOUN
easat-3732	210	8	validation	validation	NOUN
easat-3732	210	9	shows	show	VERB
easat-3732	210	10	that	that	SCONJ
easat-3732	210	11	psnr	psnr	NOUN
easat-3732	210	12	and	and	CCONJ
easat-3732	210	13	ssim	ssim	NOUN
easat-3732	210	14	for	for	ADP
easat-3732	210	15	gaussian	gaussian	ADJ
easat-3732	210	16	noise	noise	NOUN
easat-3732	210	17	with	with	ADP
easat-3732	210	18	σ=50	σ=50	PROPN
easat-3732	210	19	is	be	AUX
easat-3732	210	20	31.90	31.90	NUM
easat-3732	210	21	and	and	CCONJ
easat-3732	210	22	0.85	0.85	NUM
easat-3732	210	23	respectively	respectively	ADV
easat-3732	210	24	.	.	PUNCT
easat-3732	211	1	for	for	ADP
easat-3732	211	2	poisson	poisson	NOUN
easat-3732	211	3	noise	noise	NOUN
easat-3732	211	4	with	with	ADP
easat-3732	211	5	λ=30	λ=30	PROPN
easat-3732	211	6	,	,	PUNCT
easat-3732	211	7	it	it	PRON
easat-3732	211	8	is	be	AUX
easat-3732	211	9	32.60	32.60	NUM
easat-3732	211	10	and	and	CCONJ
easat-3732	211	11	0.86	0.86	NUM
easat-3732	211	12	respectively	respectively	ADV
easat-3732	211	13	.	.	PUNCT
easat-3732	212	1	these	these	PRON
easat-3732	212	2	are	be	AUX
easat-3732	212	3	comparable	comparable	ADJ
easat-3732	212	4	and	and	CCONJ
easat-3732	212	5	yet	yet	ADV
easat-3732	212	6	detailed	detailed	ADJ
easat-3732	212	7	investigation	investigation	NOUN
easat-3732	212	8	will	will	AUX
easat-3732	212	9	be	be	AUX
easat-3732	212	10	done	do	VERB
easat-3732	212	11	for	for	ADP
easat-3732	212	12	various	various	ADJ
easat-3732	212	13	datasets	dataset	NOUN
easat-3732	212	14	.	.	PUNCT
easat-3732	213	1	7969	7969	NUM
easat-3732	213	2	edelweiss	edelweiss	PROPN
easat-3732	213	3	applied	apply	VERB
easat-3732	213	4	science	science	NOUN
easat-3732	213	5	and	and	CCONJ
easat-3732	213	6	technology	technology	NOUN
easat-3732	213	7	issn	issn	PROPN
easat-3732	213	8	:	:	PUNCT
easat-3732	213	9	2576	2576	NUM
easat-3732	213	10	-	-	SYM
easat-3732	213	11	8484	8484	NUM
easat-3732	213	12	vol	vol	NOUN
easat-3732	213	13	.	.	PROPN
easat-3732	213	14	8	8	NUM
easat-3732	213	15	,	,	PUNCT
easat-3732	213	16	no	no	INTJ
easat-3732	213	17	.	.	NOUN
easat-3732	213	18	6	6	NUM
easat-3732	213	19	:	:	PUNCT
easat-3732	213	20	7951	7951	NUM
easat-3732	213	21	-	-	SYM
easat-3732	213	22	7970	7970	NUM
easat-3732	213	23	,	,	PUNCT
easat-3732	213	24	2024	2024	NUM
easat-3732	213	25	doi	doi	NOUN
easat-3732	213	26	:	:	PUNCT
easat-3732	213	27	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	213	28	©	©	ADP
easat-3732	213	29	2024	2024	NUM
easat-3732	213	30	by	by	ADP
easat-3732	213	31	the	the	DET
easat-3732	213	32	authors	author	NOUN
easat-3732	213	33	;	;	PUNCT
easat-3732	213	34	licensee	licensee	PROPN
easat-3732	213	35	learning	learning	NOUN
easat-3732	213	36	gate	gate	NOUN
easat-3732	213	37	3	3	NUM
easat-3732	213	38	.	.	PUNCT
easat-3732	213	39	conclusions	conclusion	NOUN
easat-3732	213	40	and	and	CCONJ
easat-3732	213	41	future	future	ADJ
easat-3732	213	42	directions	direction	NOUN
easat-3732	213	43	this	this	DET
easat-3732	213	44	paper	paper	NOUN
easat-3732	213	45	presented	present	VERB
easat-3732	213	46	two	two	NUM
easat-3732	213	47	self	self	NOUN
easat-3732	213	48	-	-	PUNCT
easat-3732	213	49	supervised	supervise	VERB
easat-3732	213	50	image	image	NOUN
easat-3732	213	51	denoising	denoising	NOUN
easat-3732	213	52	approaches	approach	NOUN
easat-3732	213	53	using	use	VERB
easat-3732	213	54	the	the	DET
easat-3732	213	55	discrete	discrete	ADJ
easat-3732	213	56	wavelet	wavelet	NOUN
easat-3732	213	57	transform	transform	NOUN
easat-3732	213	58	(	(	PUNCT
easat-3732	213	59	dwt	dwt	NOUN
easat-3732	213	60	)	)	PUNCT
easat-3732	213	61	and	and	CCONJ
easat-3732	213	62	non	non	ADJ
easat-3732	213	63	-	-	ADJ
easat-3732	213	64	local	local	ADJ
easat-3732	213	65	means	mean	NOUN
easat-3732	213	66	(	(	PUNCT
easat-3732	213	67	nlm	nlm	NOUN
easat-3732	213	68	)	)	PUNCT
easat-3732	213	69	methods	method	NOUN
easat-3732	213	70	,	,	PUNCT
easat-3732	213	71	designed	design	VERB
easat-3732	213	72	to	to	PART
easat-3732	213	73	overcome	overcome	VERB
easat-3732	213	74	the	the	DET
easat-3732	213	75	dependency	dependency	NOUN
easat-3732	213	76	on	on	ADP
easat-3732	213	77	paired	pair	VERB
easat-3732	213	78	clean	clean	ADJ
easat-3732	213	79	-	-	PUNCT
easat-3732	213	80	noisy	noisy	ADJ
easat-3732	213	81	image	image	NOUN
easat-3732	213	82	data	datum	NOUN
easat-3732	213	83	that	that	PRON
easat-3732	213	84	limits	limit	VERB
easat-3732	213	85	traditional	traditional	ADJ
easat-3732	213	86	denoising	denoising	NOUN
easat-3732	213	87	techniques	technique	NOUN
easat-3732	213	88	.	.	PUNCT
easat-3732	214	1	the	the	DET
easat-3732	214	2	proposed	propose	VERB
easat-3732	214	3	self	self	NOUN
easat-3732	214	4	-	-	PUNCT
easat-3732	214	5	supervised	supervise	VERB
easat-3732	214	6	dwt	dwt	NOUN
easat-3732	214	7	-	-	PUNCT
easat-3732	214	8	based	base	VERB
easat-3732	214	9	denoising	denoising	NOUN
easat-3732	214	10	approach	approach	NOUN
easat-3732	214	11	leverages	leverage	VERB
easat-3732	214	12	wavelet	wavelet	NOUN
easat-3732	214	13	thresholding	thresholde	VERB
easat-3732	214	14	to	to	PART
easat-3732	214	15	reduce	reduce	VERB
easat-3732	214	16	noise	noise	NOUN
easat-3732	214	17	while	while	SCONJ
easat-3732	214	18	preserving	preserve	VERB
easat-3732	214	19	structural	structural	ADJ
easat-3732	214	20	details	detail	NOUN
easat-3732	214	21	in	in	ADP
easat-3732	214	22	images	image	NOUN
easat-3732	214	23	.	.	PUNCT
easat-3732	215	1	both	both	DET
easat-3732	215	2	models	model	NOUN
easat-3732	215	3	were	be	AUX
easat-3732	215	4	trained	train	VERB
easat-3732	215	5	exclusively	exclusively	ADV
easat-3732	215	6	on	on	ADP
easat-3732	215	7	noisy	noisy	ADJ
easat-3732	215	8	images	image	NOUN
easat-3732	215	9	using	use	VERB
easat-3732	215	10	a	a	DET
easat-3732	215	11	custom	custom	NOUN
easat-3732	215	12	loss	loss	NOUN
easat-3732	215	13	function	function	NOUN
easat-3732	215	14	combining	combine	VERB
easat-3732	215	15	mean	mean	NOUN
easat-3732	215	16	squared	square	VERB
easat-3732	215	17	error	error	NOUN
easat-3732	215	18	(	(	PUNCT
easat-3732	215	19	mse	mse	NOUN
easat-3732	215	20	)	)	PUNCT
easat-3732	215	21	,	,	PUNCT
easat-3732	215	22	peak	peak	NOUN
easat-3732	215	23	signal	signal	NOUN
easat-3732	215	24	-	-	PUNCT
easat-3732	215	25	to	to	ADP
easat-3732	215	26	-	-	PUNCT
easat-3732	215	27	noise	noise	NOUN
easat-3732	215	28	ratio	ratio	NOUN
easat-3732	215	29	(	(	PUNCT
easat-3732	215	30	psnr	psnr	NOUN
easat-3732	215	31	)	)	PUNCT
easat-3732	215	32	,	,	PUNCT
easat-3732	215	33	and	and	CCONJ
easat-3732	215	34	structural	structural	ADJ
easat-3732	215	35	similarity	similarity	NOUN
easat-3732	215	36	index	index	NOUN
easat-3732	215	37	(	(	PUNCT
easat-3732	215	38	ssim	ssim	NOUN
easat-3732	215	39	)	)	PUNCT
easat-3732	215	40	,	,	PUNCT
easat-3732	215	41	ensuring	ensure	VERB
easat-3732	215	42	that	that	SCONJ
easat-3732	215	43	denoising	denoise	VERB
easat-3732	215	44	performance	performance	NOUN
easat-3732	215	45	aligns	align	VERB
easat-3732	215	46	with	with	ADP
easat-3732	215	47	both	both	CCONJ
easat-3732	215	48	pixel	pixel	ADJ
easat-3732	215	49	-	-	ADJ
easat-3732	215	50	wise	wise	ADJ
easat-3732	215	51	accuracy	accuracy	NOUN
easat-3732	215	52	and	and	CCONJ
easat-3732	215	53	perceptual	perceptual	ADJ
easat-3732	215	54	quality	quality	NOUN
easat-3732	215	55	.	.	PUNCT
easat-3732	216	1	experimental	experimental	ADJ
easat-3732	216	2	results	result	NOUN
easat-3732	216	3	showed	show	VERB
easat-3732	216	4	that	that	SCONJ
easat-3732	216	5	the	the	DET
easat-3732	216	6	self	self	NOUN
easat-3732	216	7	-	-	PUNCT
easat-3732	216	8	supervised	supervise	VERB
easat-3732	216	9	dwt	dwt	NOUN
easat-3732	216	10	-	-	PUNCT
easat-3732	216	11	based	base	VERB
easat-3732	216	12	model	model	NOUN
easat-3732	216	13	outperformed	outperform	VERB
easat-3732	216	14	traditional	traditional	ADJ
easat-3732	216	15	dwt	dwt	NOUN
easat-3732	216	16	-	-	PUNCT
easat-3732	216	17	only	only	ADV
easat-3732	216	18	denoising	denoising	NOUN
easat-3732	216	19	,	,	PUNCT
easat-3732	216	20	achieving	achieve	VERB
easat-3732	216	21	psnr	psnr	NOUN
easat-3732	216	22	values	value	NOUN
easat-3732	216	23	of	of	ADP
easat-3732	216	24	31.5	31.5	NUM
easat-3732	216	25	for	for	ADP
easat-3732	216	26	gaussian	gaussian	ADJ
easat-3732	216	27	noise	noise	NOUN
easat-3732	216	28	(	(	PUNCT
easat-3732	216	29	σ	σ	NOUN
easat-3732	216	30	=	=	SYM
easat-3732	216	31	50	50	NUM
easat-3732	216	32	)	)	PUNCT
easat-3732	216	33	and	and	CCONJ
easat-3732	216	34	32.5	32.5	NUM
easat-3732	216	35	for	for	ADP
easat-3732	216	36	poisson	poisson	NOUN
easat-3732	216	37	noise	noise	NOUN
easat-3732	216	38	(	(	PUNCT
easat-3732	216	39	λ	λ	X
easat-3732	216	40	=	=	NOUN
easat-3732	216	41	30	30	NUM
easat-3732	216	42	)	)	PUNCT
easat-3732	216	43	,	,	PUNCT
easat-3732	216	44	with	with	ADP
easat-3732	216	45	corresponding	correspond	VERB
easat-3732	216	46	ssim	ssim	NOUN
easat-3732	216	47	values	value	NOUN
easat-3732	216	48	of	of	ADP
easat-3732	216	49	0.86	0.86	NUM
easat-3732	216	50	and	and	CCONJ
easat-3732	216	51	0.87	0.87	NUM
easat-3732	216	52	.	.	PUNCT
easat-3732	217	1	the	the	DET
easat-3732	217	2	nlmbased	nlmbased	ADJ
easat-3732	217	3	model	model	NOUN
easat-3732	217	4	also	also	ADV
easat-3732	217	5	demonstrated	demonstrate	VERB
easat-3732	217	6	effective	effective	ADJ
easat-3732	217	7	noise	noise	NOUN
easat-3732	217	8	reduction	reduction	NOUN
easat-3732	217	9	,	,	PUNCT
easat-3732	217	10	achieving	achieve	VERB
easat-3732	217	11	psnr	psnr	NOUN
easat-3732	217	12	and	and	CCONJ
easat-3732	217	13	ssim	ssim	NOUN
easat-3732	217	14	values	value	NOUN
easat-3732	217	15	of	of	ADP
easat-3732	217	16	31.9	31.9	NUM
easat-3732	217	17	and	and	CCONJ
easat-3732	217	18	0.85	0.85	NUM
easat-3732	217	19	for	for	ADP
easat-3732	217	20	gaussian	gaussian	ADJ
easat-3732	217	21	noise	noise	NOUN
easat-3732	217	22	,	,	PUNCT
easat-3732	217	23	and	and	CCONJ
easat-3732	217	24	32.6	32.6	NUM
easat-3732	217	25	and	and	CCONJ
easat-3732	217	26	0.86	0.86	NUM
easat-3732	217	27	for	for	ADP
easat-3732	217	28	poisson	poisson	NOUN
easat-3732	217	29	noise	noise	NOUN
easat-3732	217	30	.	.	PUNCT
easat-3732	218	1	together	together	ADV
easat-3732	218	2	,	,	PUNCT
easat-3732	218	3	these	these	DET
easat-3732	218	4	results	result	NOUN
easat-3732	218	5	highlight	highlight	VERB
easat-3732	218	6	the	the	DET
easat-3732	218	7	potential	potential	NOUN
easat-3732	218	8	of	of	ADP
easat-3732	218	9	self	self	NOUN
easat-3732	218	10	-	-	PUNCT
easat-3732	218	11	supervised	supervise	VERB
easat-3732	218	12	approaches	approach	NOUN
easat-3732	218	13	in	in	ADP
easat-3732	218	14	denoising	denoise	VERB
easat-3732	218	15	applications	application	NOUN
easat-3732	218	16	where	where	SCONJ
easat-3732	218	17	access	access	NOUN
easat-3732	218	18	to	to	ADP
easat-3732	218	19	clean	clean	ADJ
easat-3732	218	20	data	datum	NOUN
easat-3732	218	21	is	be	AUX
easat-3732	218	22	limited	limited	ADJ
easat-3732	218	23	or	or	CCONJ
easat-3732	218	24	unavailable	unavailable	ADJ
easat-3732	218	25	,	,	PUNCT
easat-3732	218	26	making	make	VERB
easat-3732	218	27	them	they	PRON
easat-3732	218	28	suitable	suitable	ADJ
easat-3732	218	29	for	for	ADP
easat-3732	218	30	complex	complex	ADJ
easat-3732	218	31	real	real	ADJ
easat-3732	218	32	-	-	PUNCT
easat-3732	218	33	world	world	NOUN
easat-3732	218	34	noise	noise	NOUN
easat-3732	218	35	scenarios	scenario	NOUN
easat-3732	218	36	.	.	PUNCT
easat-3732	219	1	future	future	ADJ
easat-3732	219	2	research	research	NOUN
easat-3732	219	3	directions	direction	NOUN
easat-3732	219	4	include	include	VERB
easat-3732	219	5	exploring	explore	VERB
easat-3732	219	6	more	more	ADV
easat-3732	219	7	diverse	diverse	ADJ
easat-3732	219	8	wavelet	wavelet	NOUN
easat-3732	219	9	families	family	NOUN
easat-3732	219	10	and	and	CCONJ
easat-3732	219	11	evaluating	evaluate	VERB
easat-3732	219	12	their	their	PRON
easat-3732	219	13	impact	impact	NOUN
easat-3732	219	14	on	on	ADP
easat-3732	219	15	self	self	NOUN
easat-3732	219	16	-	-	PUNCT
easat-3732	219	17	supervised	supervise	VERB
easat-3732	219	18	denoising	denoising	NOUN
easat-3732	219	19	performance	performance	NOUN
easat-3732	219	20	,	,	PUNCT
easat-3732	219	21	as	as	SCONJ
easat-3732	219	22	most	most	ADJ
easat-3732	219	23	current	current	ADJ
easat-3732	219	24	studies	study	NOUN
easat-3732	219	25	primarily	primarily	ADV
easat-3732	219	26	focus	focus	VERB
easat-3732	219	27	on	on	ADP
easat-3732	219	28	the	the	DET
easat-3732	219	29	haar	haar	PROPN
easat-3732	219	30	wavelet	wavelet	NOUN
easat-3732	219	31	.	.	PUNCT
easat-3732	220	1	another	another	DET
easat-3732	220	2	area	area	NOUN
easat-3732	220	3	of	of	ADP
easat-3732	220	4	interest	interest	NOUN
easat-3732	220	5	is	be	AUX
easat-3732	220	6	enhancing	enhance	VERB
easat-3732	220	7	computational	computational	ADJ
easat-3732	220	8	efficiency	efficiency	NOUN
easat-3732	220	9	for	for	ADP
easat-3732	220	10	high	high	ADJ
easat-3732	220	11	-	-	PUNCT
easat-3732	220	12	resolution	resolution	NOUN
easat-3732	220	13	images	image	NOUN
easat-3732	220	14	,	,	PUNCT
easat-3732	220	15	as	as	SCONJ
easat-3732	220	16	the	the	DET
easat-3732	220	17	proposed	propose	VERB
easat-3732	220	18	models	model	NOUN
easat-3732	220	19	can	can	AUX
easat-3732	220	20	be	be	AUX
easat-3732	220	21	resource	resource	NOUN
easat-3732	220	22	-	-	PUNCT
easat-3732	220	23	intensive	intensive	ADJ
easat-3732	220	24	.	.	PUNCT
easat-3732	221	1	developing	develop	VERB
easat-3732	221	2	lightweight	lightweight	ADJ
easat-3732	221	3	architectures	architecture	NOUN
easat-3732	221	4	or	or	CCONJ
easat-3732	221	5	optimizing	optimize	VERB
easat-3732	221	6	dwt	dwt	NOUN
easat-3732	221	7	-	-	PUNCT
easat-3732	221	8	based	base	VERB
easat-3732	221	9	and	and	CCONJ
easat-3732	221	10	nlm	nlm	PROPN
easat-3732	221	11	-	-	PUNCT
easat-3732	221	12	based	base	VERB
easat-3732	221	13	frameworks	framework	NOUN
easat-3732	221	14	for	for	ADP
easat-3732	221	15	real	real	ADJ
easat-3732	221	16	-	-	PUNCT
easat-3732	221	17	time	time	NOUN
easat-3732	221	18	applications	application	NOUN
easat-3732	221	19	would	would	AUX
easat-3732	221	20	be	be	AUX
easat-3732	221	21	beneficial	beneficial	ADJ
easat-3732	221	22	.	.	PUNCT
easat-3732	222	1	furthermore	furthermore	ADV
easat-3732	222	2	,	,	PUNCT
easat-3732	222	3	extending	extend	VERB
easat-3732	222	4	the	the	DET
easat-3732	222	5	self	self	NOUN
easat-3732	222	6	-	-	PUNCT
easat-3732	222	7	supervised	supervise	VERB
easat-3732	222	8	dwt	dwt	NOUN
easat-3732	222	9	and	and	CCONJ
easat-3732	222	10	nlm	nlm	PROPN
easat-3732	222	11	models	model	NOUN
easat-3732	222	12	to	to	PART
easat-3732	222	13	handle	handle	VERB
easat-3732	222	14	multiple	multiple	ADJ
easat-3732	222	15	noise	noise	NOUN
easat-3732	222	16	types	type	NOUN
easat-3732	222	17	simultaneously	simultaneously	ADV
easat-3732	222	18	could	could	AUX
easat-3732	222	19	improve	improve	VERB
easat-3732	222	20	model	model	NOUN
easat-3732	222	21	generalization	generalization	NOUN
easat-3732	222	22	.	.	PUNCT
easat-3732	223	1	finally	finally	ADV
easat-3732	223	2	,	,	PUNCT
easat-3732	223	3	we	we	PRON
easat-3732	223	4	intend	intend	VERB
easat-3732	223	5	to	to	PART
easat-3732	223	6	evaluate	evaluate	VERB
easat-3732	223	7	these	these	DET
easat-3732	223	8	models	model	NOUN
easat-3732	223	9	on	on	ADP
easat-3732	223	10	real	real	ADJ
easat-3732	223	11	-	-	PUNCT
easat-3732	223	12	world	world	NOUN
easat-3732	223	13	noisy	noisy	ADJ
easat-3732	223	14	datasets	dataset	NOUN
easat-3732	223	15	from	from	ADP
easat-3732	223	16	fields	field	NOUN
easat-3732	223	17	like	like	ADP
easat-3732	223	18	medical	medical	ADJ
easat-3732	223	19	imaging	imaging	NOUN
easat-3732	223	20	and	and	CCONJ
easat-3732	223	21	astronomy	astronomy	NOUN
easat-3732	223	22	to	to	PART
easat-3732	223	23	verify	verify	VERB
easat-3732	223	24	their	their	PRON
easat-3732	223	25	robustness	robustness	NOUN
easat-3732	223	26	beyond	beyond	ADP
easat-3732	223	27	synthetic	synthetic	ADJ
easat-3732	223	28	noise	noise	NOUN
easat-3732	223	29	.	.	PUNCT
easat-3732	224	1	exploring	explore	VERB
easat-3732	224	2	hybrid	hybrid	ADJ
easat-3732	224	3	approaches	approach	NOUN
easat-3732	224	4	,	,	PUNCT
easat-3732	224	5	such	such	ADJ
easat-3732	224	6	as	as	ADP
easat-3732	224	7	combining	combine	VERB
easat-3732	224	8	wavelet	wavelet	NOUN
easat-3732	224	9	and	and	CCONJ
easat-3732	224	10	fourier	fourier	NOUN
easat-3732	224	11	transforms	transform	VERB
easat-3732	224	12	within	within	ADP
easat-3732	224	13	the	the	DET
easat-3732	224	14	selfsupervised	selfsupervise	VERB
easat-3732	224	15	paradigm	paradigm	NOUN
easat-3732	224	16	,	,	PUNCT
easat-3732	224	17	could	could	AUX
easat-3732	224	18	provide	provide	VERB
easat-3732	224	19	further	further	ADJ
easat-3732	224	20	advancements	advancement	NOUN
easat-3732	224	21	in	in	ADP
easat-3732	224	22	image	image	NOUN
easat-3732	224	23	denoising	denoising	NOUN
easat-3732	224	24	.	.	PUNCT
easat-3732	225	1	copyright	copyright	NOUN
easat-3732	225	2	:	:	PUNCT
easat-3732	225	3	©	©	PROPN
easat-3732	225	4	2024	2024	NUM
easat-3732	225	5	by	by	ADP
easat-3732	225	6	the	the	DET
easat-3732	225	7	authors	author	NOUN
easat-3732	225	8	.	.	PUNCT
easat-3732	226	1	this	this	DET
easat-3732	226	2	article	article	NOUN
easat-3732	226	3	is	be	AUX
easat-3732	226	4	an	an	DET
easat-3732	226	5	open	open	ADJ
easat-3732	226	6	access	access	NOUN
easat-3732	226	7	article	article	NOUN
easat-3732	226	8	distributed	distribute	VERB
easat-3732	226	9	under	under	ADP
easat-3732	226	10	the	the	DET
easat-3732	226	11	terms	term	NOUN
easat-3732	226	12	and	and	CCONJ
easat-3732	226	13	conditions	condition	NOUN
easat-3732	226	14	of	of	ADP
easat-3732	226	15	the	the	DET
easat-3732	226	16	creative	creative	ADJ
easat-3732	226	17	commons	common	NOUN
easat-3732	226	18	attribution	attribution	NOUN
easat-3732	226	19	(	(	PUNCT
easat-3732	226	20	cc	cc	NOUN
easat-3732	226	21	by	by	ADP
easat-3732	226	22	)	)	PUNCT
easat-3732	226	23	license	license	NOUN
easat-3732	226	24	(	(	PUNCT
easat-3732	226	25	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-3732	226	26	)	)	PUNCT
easat-3732	226	27	.	.	PUNCT
easat-3732	227	1	references	reference	NOUN
easat-3732	227	2	[	[	X
easat-3732	227	3	1	1	NUM
easat-3732	227	4	]	]	PUNCT
easat-3732	227	5	k.	k.	PROPN
easat-3732	227	6	dabov	dabov	PROPN
easat-3732	227	7	,	,	PUNCT
easat-3732	227	8	a.	a.	PROPN
easat-3732	227	9	foi	foi	PROPN
easat-3732	227	10	,	,	PUNCT
easat-3732	227	11	v.	v.	CCONJ
easat-3732	227	12	katkovnik	katkovnik	X
easat-3732	227	13	,	,	PUNCT
easat-3732	227	14	and	and	CCONJ
easat-3732	227	15	k.	k.	PROPN
easat-3732	227	16	egiazarian	egiazarian	PROPN
easat-3732	227	17	,	,	PUNCT
easat-3732	227	18	“	"	PUNCT
easat-3732	227	19	image	image	NOUN
easat-3732	227	20	denoising	denoise	VERB
easat-3732	227	21	by	by	ADP
easat-3732	227	22	sparse	sparse	ADJ
easat-3732	227	23	3	3	NUM
easat-3732	227	24	-	-	SYM
easat-3732	227	25	d	d	NOUN
easat-3732	227	26	transform	transform	NOUN
easat-3732	227	27	domain	domain	NOUN
easat-3732	227	28	collaborative	collaborative	ADJ
easat-3732	227	29	filtering	filtering	NOUN
easat-3732	227	30	,	,	PUNCT
easat-3732	227	31	”	"	PUNCT
easat-3732	227	32	ieee	ieee	NOUN
easat-3732	227	33	transactions	transaction	NOUN
easat-3732	227	34	on	on	ADP
easat-3732	227	35	image	image	NOUN
easat-3732	227	36	processing	processing	NOUN
easat-3732	227	37	,	,	PUNCT
easat-3732	227	38	vol	vol	NOUN
easat-3732	227	39	.	.	PROPN
easat-3732	228	1	16	16	NUM
easat-3732	228	2	,	,	PUNCT
easat-3732	228	3	no	no	INTJ
easat-3732	228	4	.	.	NOUN
easat-3732	228	5	8	8	NUM
easat-3732	228	6	,	,	PUNCT
easat-3732	228	7	pp	pp	ADJ
easat-3732	228	8	.	.	PUNCT
easat-3732	229	1	2080–2095	2080–2095	NUM
easat-3732	229	2	,	,	PUNCT
easat-3732	229	3	2007	2007	NUM
easat-3732	229	4	.	.	PUNCT
easat-3732	230	1	[	[	X
easat-3732	230	2	2	2	NUM
easat-3732	230	3	]	]	X
easat-3732	230	4	b.	b.	PROPN
easat-3732	230	5	buades	buades	PROPN
easat-3732	230	6	,	,	PUNCT
easat-3732	230	7	b.	b.	PROPN
easat-3732	230	8	coll	coll	PROPN
easat-3732	230	9	,	,	PUNCT
easat-3732	230	10	and	and	CCONJ
easat-3732	230	11	j.-m	j.-m	PROPN
easat-3732	230	12	.	.	PUNCT
easat-3732	231	1	morel	morel	PROPN
easat-3732	231	2	,	,	PUNCT
easat-3732	231	3	“	"	PUNCT
easat-3732	231	4	a	a	DET
easat-3732	231	5	non	non	ADJ
easat-3732	231	6	-	-	ADJ
easat-3732	231	7	local	local	ADJ
easat-3732	231	8	algorithm	algorithm	NOUN
easat-3732	231	9	for	for	ADP
easat-3732	231	10	image	image	NOUN
easat-3732	231	11	denoising	denoising	NOUN
easat-3732	231	12	,	,	PUNCT
easat-3732	231	13	”	"	PUNCT
easat-3732	231	14	in	in	ADP
easat-3732	231	15	proceedings	proceeding	NOUN
easat-3732	231	16	of	of	ADP
easat-3732	231	17	the	the	DET
easat-3732	231	18	ieee	ieee	NOUN
easat-3732	231	19	conference	conference	NOUN
easat-3732	231	20	on	on	ADP
easat-3732	231	21	computer	computer	NOUN
easat-3732	231	22	vision	vision	NOUN
easat-3732	231	23	and	and	CCONJ
easat-3732	231	24	pattern	pattern	NOUN
easat-3732	231	25	recognition	recognition	NOUN
easat-3732	231	26	(	(	PUNCT
easat-3732	231	27	cvpr	cvpr	NOUN
easat-3732	231	28	)	)	PUNCT
easat-3732	231	29	,	,	PUNCT
easat-3732	231	30	vol	vol	NOUN
easat-3732	231	31	.	.	PROPN
easat-3732	231	32	2	2	NUM
easat-3732	231	33	,	,	PUNCT
easat-3732	231	34	pp	pp	ADJ
easat-3732	231	35	.	.	PUNCT
easat-3732	232	1	60–65	60–65	NUM
easat-3732	232	2	,	,	PUNCT
easat-3732	232	3	2005	2005	NUM
easat-3732	232	4	.	.	PUNCT
easat-3732	233	1	[	[	X
easat-3732	233	2	3	3	X
easat-3732	233	3	]	]	X
easat-3732	233	4	b.	b.	PROPN
easat-3732	233	5	buades	buades	PROPN
easat-3732	233	6	,	,	PUNCT
easat-3732	233	7	b.	b.	PROPN
easat-3732	233	8	coll	coll	PROPN
easat-3732	233	9	,	,	PUNCT
easat-3732	233	10	and	and	CCONJ
easat-3732	233	11	j.-m	j.-m	PROPN
easat-3732	233	12	.	.	PUNCT
easat-3732	234	1	morel	morel	PROPN
easat-3732	234	2	,	,	PUNCT
easat-3732	234	3	“	"	PUNCT
easat-3732	234	4	a	a	DET
easat-3732	234	5	review	review	NOUN
easat-3732	234	6	of	of	ADP
easat-3732	234	7	image	image	NOUN
easat-3732	234	8	denoising	denoising	NOUN
easat-3732	234	9	algorithms	algorithm	NOUN
easat-3732	234	10	,	,	PUNCT
easat-3732	234	11	with	with	ADP
easat-3732	234	12	a	a	DET
easat-3732	234	13	new	new	ADJ
easat-3732	234	14	one	one	NOUN
easat-3732	234	15	,	,	PUNCT
easat-3732	234	16	”	"	PUNCT
easat-3732	234	17	multiscale	multiscale	NOUN
easat-3732	234	18	modeling	modeling	NOUN
easat-3732	234	19	&	&	CCONJ
easat-3732	234	20	simulation	simulation	PROPN
easat-3732	234	21	,	,	PUNCT
easat-3732	234	22	vol	vol	NOUN
easat-3732	234	23	.	.	PROPN
easat-3732	234	24	4	4	NUM
easat-3732	234	25	,	,	PUNCT
easat-3732	234	26	no	no	INTJ
easat-3732	234	27	.	.	NOUN
easat-3732	234	28	2	2	NUM
easat-3732	234	29	,	,	PUNCT
easat-3732	234	30	pp	pp	ADJ
easat-3732	234	31	.	.	PUNCT
easat-3732	235	1	490–530	490–530	NUM
easat-3732	235	2	,	,	PUNCT
easat-3732	235	3	2005	2005	NUM
easat-3732	235	4	.	.	PUNCT
easat-3732	236	1	[	[	X
easat-3732	236	2	4	4	NUM
easat-3732	236	3	]	]	ADJ
easat-3732	236	4	c.-a	c.-a	NOUN
easat-3732	236	5	.	.	PUNCT
easat-3732	237	1	deledalle	deledalle	PROPN
easat-3732	237	2	,	,	PUNCT
easat-3732	237	3	f.	f.	PROPN
easat-3732	237	4	tupin	tupin	NOUN
easat-3732	237	5	,	,	PUNCT
easat-3732	237	6	and	and	CCONJ
easat-3732	237	7	l.	l.	PROPN
easat-3732	237	8	denis	denis	PROPN
easat-3732	237	9	,	,	PUNCT
easat-3732	237	10	“	"	PUNCT
easat-3732	237	11	poisson	poisson	PROPN
easat-3732	237	12	nl	nl	PROPN
easat-3732	237	13	means	mean	VERB
easat-3732	237	14	:	:	PUNCT
easat-3732	237	15	unsupervised	unsupervised	ADJ
easat-3732	237	16	non	non	ADJ
easat-3732	237	17	-	-	ADJ
easat-3732	237	18	local	local	ADJ
easat-3732	237	19	means	mean	NOUN
easat-3732	237	20	for	for	ADP
easat-3732	237	21	poisson	poisson	NOUN
easat-3732	237	22	noise	noise	NOUN
easat-3732	237	23	,	,	PUNCT
easat-3732	237	24	”	"	PUNCT
easat-3732	237	25	in	in	ADP
easat-3732	237	26	proceedings	proceeding	NOUN
easat-3732	237	27	of	of	ADP
easat-3732	237	28	the	the	DET
easat-3732	237	29	ieee	ieee	NOUN
easat-3732	237	30	international	international	PROPN
easat-3732	237	31	conference	conference	NOUN
easat-3732	237	32	on	on	ADP
easat-3732	237	33	image	image	NOUN
easat-3732	237	34	processing	processing	NOUN
easat-3732	237	35	(	(	PUNCT
easat-3732	237	36	icip	icip	PROPN
easat-3732	237	37	)	)	PUNCT
easat-3732	237	38	,	,	PUNCT
easat-3732	237	39	pp	pp	ADP
easat-3732	237	40	.	.	PUNCT
easat-3732	238	1	801–804	801–804	NUM
easat-3732	238	2	,	,	PUNCT
easat-3732	238	3	2010	2010	NUM
easat-3732	238	4	.	.	PUNCT
easat-3732	239	1	[	[	X
easat-3732	239	2	5	5	X
easat-3732	239	3	]	]	PUNCT
easat-3732	239	4	s.	s.	PROPN
easat-3732	239	5	gu	gu	PROPN
easat-3732	239	6	,	,	PUNCT
easat-3732	239	7	q.	q.	PROPN
easat-3732	239	8	xie	xie	PROPN
easat-3732	239	9	,	,	PUNCT
easat-3732	239	10	d.	d.	PROPN
easat-3732	239	11	meng	meng	PROPN
easat-3732	239	12	,	,	PUNCT
easat-3732	239	13	w.	w.	PROPN
easat-3732	239	14	zuo	zuo	PROPN
easat-3732	239	15	,	,	PUNCT
easat-3732	239	16	x.	x.	NOUN
easat-3732	239	17	feng	feng	PROPN
easat-3732	239	18	,	,	PUNCT
easat-3732	239	19	and	and	CCONJ
easat-3732	239	20	l.	l.	PROPN
easat-3732	239	21	zhang	zhang	PROPN
easat-3732	239	22	,	,	PUNCT
easat-3732	239	23	“	"	PUNCT
easat-3732	239	24	weighted	weight	VERB
easat-3732	239	25	nuclear	nuclear	ADJ
easat-3732	239	26	norm	norm	NOUN
easat-3732	239	27	minimization	minimization	NOUN
easat-3732	239	28	and	and	CCONJ
easat-3732	239	29	its	its	PRON
easat-3732	239	30	applications	application	NOUN
easat-3732	239	31	to	to	ADP
easat-3732	239	32	low	low	ADJ
easat-3732	239	33	-	-	PUNCT
easat-3732	239	34	level	level	NOUN
easat-3732	239	35	vision	vision	NOUN
easat-3732	239	36	,	,	PUNCT
easat-3732	239	37	”	"	PUNCT
easat-3732	239	38	international	international	ADJ
easat-3732	239	39	journal	journal	NOUN
easat-3732	239	40	of	of	ADP
easat-3732	239	41	computer	computer	NOUN
easat-3732	239	42	vision	vision	NOUN
easat-3732	239	43	,	,	PUNCT
easat-3732	239	44	vol	vol	NOUN
easat-3732	239	45	.	.	PROPN
easat-3732	239	46	121	121	NUM
easat-3732	239	47	,	,	PUNCT
easat-3732	239	48	no	no	INTJ
easat-3732	239	49	.	.	NOUN
easat-3732	239	50	2	2	NUM
easat-3732	239	51	,	,	PUNCT
easat-3732	239	52	pp	pp	ADJ
easat-3732	239	53	.	.	PUNCT
easat-3732	240	1	183–208	183–208	NUM
easat-3732	240	2	,	,	PUNCT
easat-3732	240	3	2017	2017	NUM
easat-3732	240	4	.	.	PUNCT
easat-3732	241	1	[	[	X
easat-3732	241	2	6	6	NUM
easat-3732	241	3	]	]	PUNCT
easat-3732	241	4	k.	k.	PROPN
easat-3732	241	5	zhang	zhang	PROPN
easat-3732	241	6	,	,	PUNCT
easat-3732	241	7	w.	w.	PROPN
easat-3732	241	8	zuo	zuo	PROPN
easat-3732	241	9	,	,	PUNCT
easat-3732	241	10	y.	y.	PROPN
easat-3732	241	11	chen	chen	PROPN
easat-3732	241	12	,	,	PUNCT
easat-3732	241	13	d.	d.	PROPN
easat-3732	241	14	meng	meng	PROPN
easat-3732	241	15	,	,	PUNCT
easat-3732	241	16	and	and	CCONJ
easat-3732	241	17	l.	l.	PROPN
easat-3732	241	18	zhang	zhang	PROPN
easat-3732	241	19	,	,	PUNCT
easat-3732	241	20	“	"	PUNCT
easat-3732	241	21	beyond	beyond	ADP
easat-3732	241	22	a	a	DET
easat-3732	241	23	gaussian	gaussian	ADJ
easat-3732	241	24	denoiser	denoiser	NOUN
easat-3732	241	25	:	:	PUNCT
easat-3732	241	26	residual	residual	ADJ
easat-3732	241	27	learning	learning	NOUN
easat-3732	241	28	of	of	ADP
easat-3732	241	29	deep	deep	ADJ
easat-3732	241	30	cnn	cnn	PROPN
easat-3732	241	31	for	for	ADP
easat-3732	241	32	image	image	NOUN
easat-3732	241	33	denoising	denoising	NOUN
easat-3732	241	34	,	,	PUNCT
easat-3732	241	35	”	"	PUNCT
easat-3732	241	36	ieee	ieee	NOUN
easat-3732	241	37	transactions	transaction	NOUN
easat-3732	241	38	on	on	ADP
easat-3732	241	39	image	image	NOUN
easat-3732	241	40	processing	processing	NOUN
easat-3732	241	41	,	,	PUNCT
easat-3732	241	42	vol	vol	NOUN
easat-3732	241	43	.	.	PROPN
easat-3732	241	44	26	26	NUM
easat-3732	241	45	,	,	PUNCT
easat-3732	241	46	no	no	INTJ
easat-3732	241	47	.	.	NOUN
easat-3732	241	48	7	7	NUM
easat-3732	241	49	,	,	PUNCT
easat-3732	241	50	pp	pp	ADJ
easat-3732	241	51	.	.	PUNCT
easat-3732	241	52	3142–3155	3142–3155	NUM
easat-3732	241	53	,	,	PUNCT
easat-3732	241	54	2017	2017	NUM
easat-3732	241	55	.	.	PUNCT
easat-3732	242	1	[	[	X
easat-3732	242	2	7	7	X
easat-3732	242	3	]	]	X
easat-3732	242	4	j.	j.	PROPN
easat-3732	242	5	lehtinen	lehtinen	PROPN
easat-3732	242	6	et	et	PROPN
easat-3732	242	7	al	al	PROPN
easat-3732	242	8	.	.	PROPN
easat-3732	242	9	,	,	PUNCT
easat-3732	242	10	“	"	PUNCT
easat-3732	242	11	noise2noise	noise2noise	PROPN
easat-3732	242	12	:	:	PUNCT
easat-3732	242	13	learning	learn	VERB
easat-3732	242	14	image	image	NOUN
easat-3732	242	15	restoration	restoration	NOUN
easat-3732	242	16	without	without	ADP
easat-3732	242	17	clean	clean	ADJ
easat-3732	242	18	data	datum	NOUN
easat-3732	242	19	,	,	PUNCT
easat-3732	242	20	”	"	PUNCT
easat-3732	242	21	in	in	ADP
easat-3732	242	22	proceedings	proceeding	NOUN
easat-3732	242	23	of	of	ADP
easat-3732	242	24	the	the	DET
easat-3732	242	25	international	international	ADJ
easat-3732	242	26	conference	conference	NOUN
easat-3732	242	27	on	on	ADP
easat-3732	242	28	machine	machine	NOUN
easat-3732	242	29	learning	learning	NOUN
easat-3732	242	30	(	(	PUNCT
easat-3732	242	31	icml	icml	PROPN
easat-3732	242	32	)	)	PUNCT
easat-3732	242	33	,	,	PUNCT
easat-3732	242	34	pp	pp	PROPN
easat-3732	242	35	.	.	PUNCT
easat-3732	243	1	2965–2974	2965–2974	NUM
easat-3732	243	2	,	,	PUNCT
easat-3732	243	3	2018	2018	NUM
easat-3732	243	4	.	.	PUNCT
easat-3732	244	1	[	[	X
easat-3732	244	2	8	8	NUM
easat-3732	244	3	]	]	PUNCT
easat-3732	244	4	a.	a.	NOUN
easat-3732	244	5	krull	krull	PROPN
easat-3732	244	6	,	,	PUNCT
easat-3732	244	7	t.	t.	PROPN
easat-3732	244	8	o.	o.	PROPN
easat-3732	244	9	buchholz	buchholz	PROPN
easat-3732	244	10	,	,	PUNCT
easat-3732	244	11	and	and	CCONJ
easat-3732	244	12	f.	f.	PROPN
easat-3732	244	13	jug	jug	PROPN
easat-3732	244	14	,	,	PUNCT
easat-3732	244	15	“	"	PUNCT
easat-3732	244	16	noise2void	noise2void	ADJ
easat-3732	244	17	:	:	PUNCT
easat-3732	244	18	learning	learn	VERB
easat-3732	244	19	denoising	denoise	VERB
easat-3732	244	20	from	from	ADP
easat-3732	244	21	single	single	ADJ
easat-3732	244	22	noisy	noisy	ADJ
easat-3732	244	23	images	image	NOUN
easat-3732	244	24	,	,	PUNCT
easat-3732	244	25	”	"	PUNCT
easat-3732	244	26	in	in	ADP
easat-3732	244	27	proceedings	proceeding	NOUN
easat-3732	244	28	of	of	ADP
easat-3732	244	29	the	the	DET
easat-3732	244	30	ieee	ieee	NOUN
easat-3732	244	31	/	/	SYM
easat-3732	244	32	cvf	cvf	NOUN
easat-3732	244	33	conference	conference	NOUN
easat-3732	244	34	on	on	ADP
easat-3732	244	35	computer	computer	NOUN
easat-3732	244	36	vision	vision	NOUN
easat-3732	244	37	and	and	CCONJ
easat-3732	244	38	pattern	pattern	NOUN
easat-3732	244	39	recognition	recognition	NOUN
easat-3732	244	40	(	(	PUNCT
easat-3732	244	41	cvpr	cvpr	NOUN
easat-3732	244	42	)	)	PUNCT
easat-3732	244	43	,	,	PUNCT
easat-3732	244	44	pp	pp	PROPN
easat-3732	244	45	.	.	PUNCT
easat-3732	244	46	2129–2137	2129–2137	NUM
easat-3732	244	47	,	,	PUNCT
easat-3732	244	48	2019	2019	NUM
easat-3732	244	49	.	.	PUNCT
easat-3732	245	1	[	[	X
easat-3732	245	2	9	9	NUM
easat-3732	245	3	]	]	X
easat-3732	245	4	j.	j.	PROPN
easat-3732	245	5	batson	batson	PROPN
easat-3732	245	6	and	and	CCONJ
easat-3732	245	7	l.	l.	PROPN
easat-3732	245	8	royer	royer	PROPN
easat-3732	245	9	,	,	PUNCT
easat-3732	245	10	“	"	PUNCT
easat-3732	245	11	noise2self	noise2self	PRON
easat-3732	245	12	:	:	PUNCT
easat-3732	245	13	blind	blind	ADJ
easat-3732	245	14	denoising	denoising	NOUN
easat-3732	245	15	by	by	ADP
easat-3732	245	16	self	self	NOUN
easat-3732	245	17	-	-	PUNCT
easat-3732	245	18	supervision	supervision	NOUN
easat-3732	245	19	,	,	PUNCT
easat-3732	245	20	”	"	PUNCT
easat-3732	245	21	in	in	ADP
easat-3732	245	22	proceedings	proceeding	NOUN
easat-3732	245	23	of	of	ADP
easat-3732	245	24	the	the	DET
easat-3732	245	25	international	international	ADJ
easat-3732	245	26	conference	conference	NOUN
easat-3732	245	27	on	on	ADP
easat-3732	245	28	machine	machine	NOUN
easat-3732	245	29	learning	learning	NOUN
easat-3732	245	30	(	(	PUNCT
easat-3732	245	31	icml	icml	PROPN
easat-3732	245	32	)	)	PUNCT
easat-3732	245	33	,	,	PUNCT
easat-3732	245	34	pp	pp	ADP
easat-3732	245	35	.	.	PUNCT
easat-3732	246	1	524–533	524–533	NUM
easat-3732	246	2	,	,	PUNCT
easat-3732	246	3	2019	2019	NUM
easat-3732	246	4	.	.	PUNCT
easat-3732	247	1	[	[	X
easat-3732	247	2	10	10	NUM
easat-3732	247	3	]	]	X
easat-3732	247	4	d.	d.	PROPN
easat-3732	247	5	l.	l.	PROPN
easat-3732	247	6	donoho	donoho	PROPN
easat-3732	247	7	,	,	PUNCT
easat-3732	247	8	“	"	PUNCT
easat-3732	247	9	denoising	denoise	VERB
easat-3732	247	10	by	by	ADP
easat-3732	247	11	soft	soft	ADJ
easat-3732	247	12	-	-	PUNCT
easat-3732	247	13	thresholding	thresholding	NOUN
easat-3732	247	14	,	,	PUNCT
easat-3732	247	15	”	"	PUNCT
easat-3732	247	16	ieee	ieee	NOUN
easat-3732	247	17	transactions	transaction	NOUN
easat-3732	247	18	on	on	ADP
easat-3732	247	19	information	information	NOUN
easat-3732	247	20	theory	theory	NOUN
easat-3732	247	21	,	,	PUNCT
easat-3732	247	22	vol	vol	NOUN
easat-3732	247	23	.	.	PROPN
easat-3732	247	24	41	41	NUM
easat-3732	247	25	,	,	PUNCT
easat-3732	247	26	no	no	INTJ
easat-3732	247	27	.	.	NOUN
easat-3732	247	28	3	3	NUM
easat-3732	247	29	,	,	PUNCT
easat-3732	247	30	pp	pp	ADJ
easat-3732	247	31	.	.	PUNCT
easat-3732	248	1	613–627	613–627	NUM
easat-3732	248	2	,	,	PUNCT
easat-3732	248	3	1995	1995	NUM
easat-3732	248	4	.	.	PUNCT
easat-3732	249	1	[	[	X
easat-3732	249	2	11	11	NUM
easat-3732	249	3	]	]	PUNCT
easat-3732	249	4	s.	s.	PROPN
easat-3732	249	5	g.	g.	PROPN
easat-3732	249	6	chang	chang	PROPN
easat-3732	249	7	,	,	PUNCT
easat-3732	249	8	b.	b.	PROPN
easat-3732	249	9	yu	yu	PROPN
easat-3732	249	10	,	,	PUNCT
easat-3732	249	11	and	and	CCONJ
easat-3732	249	12	m.	m.	NOUN
easat-3732	249	13	vetterli	vetterli	NOUN
easat-3732	249	14	,	,	PUNCT
easat-3732	249	15	“	"	PUNCT
easat-3732	249	16	adaptive	adaptive	ADJ
easat-3732	249	17	wavelet	wavelet	NOUN
easat-3732	249	18	thresholding	thresholde	VERB
easat-3732	249	19	for	for	ADP
easat-3732	249	20	image	image	NOUN
easat-3732	249	21	denoising	denoising	NOUN
easat-3732	249	22	and	and	CCONJ
easat-3732	249	23	compression	compression	NOUN
easat-3732	249	24	,	,	PUNCT
easat-3732	249	25	”	"	PUNCT
easat-3732	249	26	ieee	ieee	NOUN
easat-3732	249	27	transactions	transaction	NOUN
easat-3732	249	28	on	on	ADP
easat-3732	249	29	image	image	NOUN
easat-3732	249	30	processing	processing	NOUN
easat-3732	249	31	,	,	PUNCT
easat-3732	249	32	vol	vol	NOUN
easat-3732	249	33	.	.	NOUN
easat-3732	249	34	9	9	NUM
easat-3732	249	35	,	,	PUNCT
easat-3732	249	36	no	no	INTJ
easat-3732	249	37	.	.	NOUN
easat-3732	249	38	9	9	NUM
easat-3732	249	39	,	,	PUNCT
easat-3732	249	40	pp	pp	ADJ
easat-3732	249	41	.	.	PUNCT
easat-3732	249	42	1532–1546	1532–1546	NUM
easat-3732	249	43	,	,	PUNCT
easat-3732	249	44	2000	2000	NUM
easat-3732	249	45	.	.	PUNCT
easat-3732	250	1	[	[	X
easat-3732	250	2	12	12	NUM
easat-3732	250	3	]	]	PUNCT
easat-3732	250	4	x.	x.	NOUN
easat-3732	250	5	liu	liu	PROPN
easat-3732	250	6	and	and	CCONJ
easat-3732	250	7	z.	z.	PROPN
easat-3732	250	8	liu	liu	PROPN
easat-3732	250	9	,	,	PUNCT
easat-3732	250	10	“	"	PUNCT
easat-3732	250	11	wavelet	wavelet	NOUN
easat-3732	250	12	convolutional	convolutional	ADJ
easat-3732	250	13	neural	neural	ADJ
easat-3732	250	14	networks	network	NOUN
easat-3732	250	15	for	for	ADP
easat-3732	250	16	image	image	NOUN
easat-3732	250	17	processing	processing	NOUN
easat-3732	250	18	,	,	PUNCT
easat-3732	250	19	”	"	PUNCT
easat-3732	250	20	arxiv	arxiv	PROPN
easat-3732	250	21	preprint	preprint	VERB
easat-3732	250	22	arxiv:1805.08620	arxiv:1805.08620	NOUN
easat-3732	250	23	,	,	PUNCT
easat-3732	250	24	2018	2018	NUM
easat-3732	250	25	.	.	PUNCT
easat-3732	251	1	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-3732	251	2	7970	7970	PROPN
easat-3732	251	3	edelweiss	edelweiss	PROPN
easat-3732	251	4	applied	apply	VERB
easat-3732	251	5	science	science	NOUN
easat-3732	251	6	and	and	CCONJ
easat-3732	251	7	technology	technology	NOUN
easat-3732	251	8	issn	issn	PROPN
easat-3732	251	9	:	:	PUNCT
easat-3732	251	10	2576	2576	NUM
easat-3732	251	11	-	-	SYM
easat-3732	251	12	8484	8484	NUM
easat-3732	251	13	vol	vol	NOUN
easat-3732	251	14	.	.	PROPN
easat-3732	251	15	8	8	NUM
easat-3732	251	16	,	,	PUNCT
easat-3732	251	17	no	no	INTJ
easat-3732	251	18	.	.	NOUN
easat-3732	251	19	6	6	NUM
easat-3732	251	20	:	:	PUNCT
easat-3732	251	21	7951	7951	NUM
easat-3732	251	22	-	-	SYM
easat-3732	251	23	7970	7970	NUM
easat-3732	251	24	,	,	PUNCT
easat-3732	251	25	2024	2024	NUM
easat-3732	251	26	doi	doi	NOUN
easat-3732	251	27	:	:	PUNCT
easat-3732	251	28	10.55214/25768484.v8i6.3732	10.55214/25768484.v8i6.3732	NUM
easat-3732	251	29	©	©	ADP
easat-3732	251	30	2024	2024	NUM
easat-3732	251	31	by	by	ADP
easat-3732	251	32	the	the	DET
easat-3732	251	33	authors	author	NOUN
easat-3732	251	34	;	;	PUNCT
easat-3732	251	35	licensee	licensee	PROPN
easat-3732	251	36	learning	learning	NOUN
easat-3732	251	37	gate	gate	NOUN
easat-3732	252	1	[	[	X
easat-3732	252	2	13	13	NUM
easat-3732	252	3	]	]	PUNCT
easat-3732	252	4	z.	z.	PROPN
easat-3732	252	5	wang	wang	PROPN
easat-3732	252	6	,	,	PUNCT
easat-3732	252	7	j.	j.	PROPN
easat-3732	252	8	liu	liu	PROPN
easat-3732	252	9	,	,	PUNCT
easat-3732	252	10	g.	g.	PROPN
easat-3732	252	11	li	li	PROPN
easat-3732	252	12	,	,	PUNCT
easat-3732	252	13	and	and	CCONJ
easat-3732	252	14	h.	h.	PROPN
easat-3732	252	15	han	han	PROPN
easat-3732	252	16	,	,	PUNCT
easat-3732	252	17	“	"	PUNCT
easat-3732	252	18	blind2unblind	blind2unblind	NOUN
easat-3732	252	19	:	:	PUNCT
easat-3732	252	20	self	self	NOUN
easat-3732	252	21	-	-	PUNCT
easat-3732	252	22	supervised	supervise	VERB
easat-3732	252	23	image	image	NOUN
easat-3732	252	24	denoising	denoise	VERB
easat-3732	252	25	with	with	ADP
easat-3732	252	26	visible	visible	ADJ
easat-3732	252	27	blind	blind	ADJ
easat-3732	252	28	spots	spot	NOUN
easat-3732	252	29	,	,	PUNCT
easat-3732	252	30	”	"	PUNCT
easat-3732	252	31	in	in	ADP
easat-3732	252	32	proceedings	proceeding	NOUN
easat-3732	252	33	of	of	ADP
easat-3732	252	34	the	the	DET
easat-3732	252	35	ieee	ieee	NOUN
easat-3732	252	36	/	/	SYM
easat-3732	252	37	cvf	cvf	NOUN
easat-3732	252	38	conference	conference	NOUN
easat-3732	252	39	on	on	ADP
easat-3732	252	40	computer	computer	NOUN
easat-3732	252	41	vision	vision	NOUN
easat-3732	252	42	and	and	CCONJ
easat-3732	252	43	pattern	pattern	NOUN
easat-3732	252	44	recognition	recognition	NOUN
easat-3732	252	45	(	(	PUNCT
easat-3732	252	46	cvpr	cvpr	NOUN
easat-3732	252	47	)	)	PUNCT
easat-3732	252	48	,	,	PUNCT
easat-3732	252	49	pp	pp	ADJ
easat-3732	252	50	.	.	PUNCT
easat-3732	252	51	2027–2036	2027–2036	NUM
easat-3732	252	52	,	,	PUNCT
easat-3732	252	53	2022	2022	NUM
easat-3732	252	54	.	.	PUNCT
easat-3732	253	1	[	[	X
easat-3732	253	2	14	14	NUM
easat-3732	253	3	]	]	PUNCT
easat-3732	253	4	t.	t.	NOUN
easat-3732	253	5	pang	pang	PROPN
easat-3732	253	6	,	,	PUNCT
easat-3732	253	7	h.	h.	PROPN
easat-3732	253	8	zheng	zheng	PROPN
easat-3732	253	9	,	,	PUNCT
easat-3732	253	10	y.	y.	PROPN
easat-3732	253	11	quan	quan	PROPN
easat-3732	253	12	,	,	PUNCT
easat-3732	253	13	and	and	CCONJ
easat-3732	253	14	h.	h.	PROPN
easat-3732	253	15	ji	ji	PROPN
easat-3732	253	16	,	,	PUNCT
easat-3732	253	17	“	"	PUNCT
easat-3732	253	18	recorrupted	recorrupte	VERB
easat-3732	253	19	-	-	PUNCT
easat-3732	253	20	to	to	AUX
easat-3732	253	21	-	-	PUNCT
easat-3732	253	22	recorrupted	recorrupted	ADJ
easat-3732	253	23	:	:	PUNCT
easat-3732	253	24	unsupervised	unsupervised	ADJ
easat-3732	253	25	deep	deep	ADJ
easat-3732	253	26	learning	learning	NOUN
easat-3732	253	27	for	for	ADP
easat-3732	253	28	image	image	NOUN
easat-3732	253	29	denoising	denoising	NOUN
easat-3732	253	30	,	,	PUNCT
easat-3732	253	31	”	"	PUNCT
easat-3732	253	32	in	in	ADP
easat-3732	253	33	proceedings	proceeding	NOUN
easat-3732	253	34	of	of	ADP
easat-3732	253	35	the	the	DET
easat-3732	253	36	ieee	ieee	NOUN
easat-3732	253	37	/	/	SYM
easat-3732	253	38	cvf	cvf	NOUN
easat-3732	253	39	conference	conference	NOUN
easat-3732	253	40	on	on	ADP
easat-3732	253	41	computer	computer	NOUN
easat-3732	253	42	vision	vision	NOUN
easat-3732	253	43	and	and	CCONJ
easat-3732	253	44	pattern	pattern	NOUN
easat-3732	253	45	recognition	recognition	NOUN
easat-3732	253	46	(	(	PUNCT
easat-3732	253	47	cvpr	cvpr	NOUN
easat-3732	253	48	)	)	PUNCT
easat-3732	253	49	,	,	PUNCT
easat-3732	253	50	pp	pp	ADJ
easat-3732	253	51	.	.	PUNCT
easat-3732	253	52	2043	2043	NUM
easat-3732	253	53	–	–	PUNCT
easat-3732	253	54	2052	2052	NUM
easat-3732	253	55	,	,	PUNCT
easat-3732	253	56	2021	2021	NUM
easat-3732	253	57	,	,	PUNCT
easat-3732	253	58	doi	doi	NOUN
easat-3732	253	59	:	:	PUNCT
easat-3732	253	60	10.1109	10.1109	NUM
easat-3732	253	61	/	/	SYM
easat-3732	253	62	cvpr46437.2021.00208	cvpr46437.2021.00208	NOUN
easat-3732	253	63	.	.	PUNCT
easat-3732	254	1	[	[	X
easat-3732	254	2	15	15	NUM
easat-3732	254	3	]	]	PUNCT
easat-3732	254	4	t.	t.	PROPN
easat-3732	254	5	huang	huang	PROPN
easat-3732	254	6	,	,	PUNCT
easat-3732	254	7	s.	s.	PROPN
easat-3732	254	8	li	li	PROPN
easat-3732	254	9	,	,	PUNCT
easat-3732	254	10	x.	x.	PROPN
easat-3732	254	11	jia	jia	PROPN
easat-3732	254	12	,	,	PUNCT
easat-3732	254	13	h.	h.	PROPN
easat-3732	254	14	lu	lu	PROPN
easat-3732	254	15	,	,	PUNCT
easat-3732	254	16	and	and	CCONJ
easat-3732	254	17	j.	j.	PROPN
easat-3732	254	18	liu	liu	PROPN
easat-3732	254	19	,	,	PUNCT
easat-3732	254	20	“	"	PUNCT
easat-3732	254	21	neighbor2neighbor	neighbor2neighbor	NOUN
easat-3732	254	22	:	:	PUNCT
easat-3732	254	23	self	self	NOUN
easat-3732	254	24	-	-	PUNCT
easat-3732	254	25	supervised	supervise	VERB
easat-3732	254	26	denoising	denoising	NOUN
easat-3732	254	27	from	from	ADP
easat-3732	254	28	single	single	ADJ
easat-3732	254	29	noisy	noisy	ADJ
easat-3732	254	30	images	image	NOUN
easat-3732	254	31	,	,	PUNCT
easat-3732	254	32	”	"	PUNCT
easat-3732	254	33	in	in	ADP
easat-3732	254	34	proceedings	proceeding	NOUN
easat-3732	254	35	of	of	ADP
easat-3732	254	36	the	the	DET
easat-3732	254	37	ieee	ieee	NOUN
easat-3732	254	38	/	/	SYM
easat-3732	254	39	cvf	cvf	NOUN
easat-3732	254	40	conference	conference	NOUN
easat-3732	254	41	on	on	ADP
easat-3732	254	42	computer	computer	NOUN
easat-3732	254	43	vision	vision	NOUN
easat-3732	254	44	and	and	CCONJ
easat-3732	254	45	pattern	pattern	NOUN
easat-3732	254	46	recognition	recognition	NOUN
easat-3732	254	47	(	(	PUNCT
easat-3732	254	48	cvpr	cvpr	NOUN
easat-3732	254	49	)	)	PUNCT
easat-3732	254	50	,	,	PUNCT
easat-3732	254	51	pp	pp	ADP
easat-3732	254	52	.	.	PUNCT
easat-3732	254	53	16216–16225	16216–16225	NUM
easat-3732	254	54	,	,	PUNCT
easat-3732	254	55	2021	2021	NUM
easat-3732	254	56	.	.	PUNCT
easat-3732	255	1	[	[	X
easat-3732	255	2	16	16	NUM
easat-3732	255	3	]	]	X
easat-3732	255	4	o.	o.	NOUN
easat-3732	255	5	ronneberger	ronneberger	NOUN
easat-3732	255	6	,	,	PUNCT
easat-3732	255	7	p.	p.	NOUN
easat-3732	255	8	fischer	fischer	PROPN
easat-3732	255	9	,	,	PUNCT
easat-3732	255	10	and	and	CCONJ
easat-3732	255	11	t.	t.	PROPN
easat-3732	255	12	brox	brox	PROPN
easat-3732	255	13	,	,	PUNCT
easat-3732	255	14	“	"	PUNCT
easat-3732	255	15	u	u	NOUN
easat-3732	255	16	-	-	NOUN
easat-3732	255	17	net	net	ADJ
easat-3732	255	18	:	:	PUNCT
easat-3732	255	19	convolutional	convolutional	ADJ
easat-3732	255	20	networks	network	NOUN
easat-3732	255	21	for	for	ADP
easat-3732	255	22	biomedical	biomedical	ADJ
easat-3732	255	23	image	image	NOUN
easat-3732	255	24	segmentation	segmentation	NOUN
easat-3732	255	25	,	,	PUNCT
easat-3732	255	26	”	"	PUNCT
easat-3732	255	27	arxiv	arxiv	PROPN
easat-3732	255	28	preprint	preprint	NOUN
easat-3732	255	29	arxiv:1505.04597	arxiv:1505.04597	PROPN
easat-3732	255	30	,	,	PUNCT
easat-3732	255	31	2015	2015	NUM
easat-3732	255	32	.	.	PUNCT
easat-3732	256	1	[	[	X
easat-3732	256	2	17	17	NUM
easat-3732	256	3	]	]	X
easat-3732	256	4	h.	h.	PROPN
easat-3732	256	5	zhao	zhao	PROPN
easat-3732	256	6	,	,	PUNCT
easat-3732	256	7	o.	o.	PROPN
easat-3732	256	8	gallo	gallo	PROPN
easat-3732	256	9	,	,	PUNCT
easat-3732	256	10	i.	i.	NOUN
easat-3732	256	11	fossio	fossio	NOUN
easat-3732	256	12	,	,	PUNCT
easat-3732	256	13	and	and	CCONJ
easat-3732	256	14	j.	j.	PROPN
easat-3732	256	15	kautz	kautz	PROPN
easat-3732	256	16	,	,	PUNCT
easat-3732	256	17	“	"	PUNCT
easat-3732	256	18	loss	loss	NOUN
easat-3732	256	19	functions	function	NOUN
easat-3732	256	20	for	for	ADP
easat-3732	256	21	image	image	NOUN
easat-3732	256	22	restoration	restoration	NOUN
easat-3732	256	23	with	with	ADP
easat-3732	256	24	neural	neural	ADJ
easat-3732	256	25	networks	network	NOUN
easat-3732	256	26	,	,	PUNCT
easat-3732	256	27	”	"	PUNCT
easat-3732	256	28	ieee	ieee	NOUN
easat-3732	256	29	transactions	transaction	NOUN
easat-3732	256	30	on	on	ADP
easat-3732	256	31	computational	computational	ADJ
easat-3732	256	32	imaging	imaging	NOUN
easat-3732	256	33	,	,	PUNCT
easat-3732	256	34	vol	vol	NOUN
easat-3732	256	35	.	.	PROPN
easat-3732	257	1	3	3	NUM
easat-3732	257	2	,	,	PUNCT
easat-3732	257	3	no	no	INTJ
easat-3732	257	4	.	.	NOUN
easat-3732	257	5	1	1	NUM
easat-3732	257	6	,	,	PUNCT
easat-3732	257	7	pp	pp	ADJ
easat-3732	257	8	.	.	PUNCT
easat-3732	258	1	47–57	47–57	NUM
easat-3732	258	2	,	,	PUNCT
easat-3732	258	3	2017	2017	NUM
easat-3732	258	4	.	.	PUNCT
easat-3732	259	1	[	[	X
easat-3732	259	2	18	18	NUM
easat-3732	259	3	]	]	PUNCT
easat-3732	259	4	j.	j.	PROPN
easat-3732	259	5	deng	deng	PROPN
easat-3732	259	6	et	et	PROPN
easat-3732	259	7	al	al	PROPN
easat-3732	259	8	.	.	PROPN
easat-3732	259	9	,	,	PUNCT
easat-3732	259	10	“	"	PUNCT
easat-3732	259	11	imagenet	imagenet	NOUN
easat-3732	259	12	:	:	PUNCT
easat-3732	259	13	a	a	DET
easat-3732	259	14	large	large	ADJ
easat-3732	259	15	-	-	PUNCT
easat-3732	259	16	scale	scale	NOUN
easat-3732	259	17	hierarchical	hierarchical	ADJ
easat-3732	259	18	image	image	NOUN
easat-3732	259	19	database	database	NOUN
easat-3732	259	20	,	,	PUNCT
easat-3732	259	21	”	"	PUNCT
easat-3732	259	22	in	in	ADP
easat-3732	259	23	proceedings	proceeding	NOUN
easat-3732	259	24	of	of	ADP
easat-3732	259	25	the	the	DET
easat-3732	259	26	ieee	ieee	NOUN
easat-3732	259	27	conference	conference	NOUN
easat-3732	259	28	on	on	ADP
easat-3732	259	29	computer	computer	NOUN
easat-3732	259	30	vision	vision	NOUN
easat-3732	259	31	and	and	CCONJ
easat-3732	259	32	pattern	pattern	NOUN
easat-3732	259	33	recognition	recognition	NOUN
easat-3732	259	34	(	(	PUNCT
easat-3732	259	35	cvpr	cvpr	NOUN
easat-3732	259	36	)	)	PUNCT
easat-3732	259	37	,	,	PUNCT
easat-3732	259	38	pp	pp	ADP
easat-3732	259	39	.	.	PUNCT
easat-3732	260	1	248–255	248–255	NUM
easat-3732	260	2	,	,	PUNCT
easat-3732	260	3	2009	2009	NUM
easat-3732	260	4	.	.	PUNCT
easat-3732	261	1	[	[	X
easat-3732	261	2	19	19	NUM
easat-3732	261	3	]	]	PUNCT
easat-3732	261	4	a.	a.	NOUN
easat-3732	261	5	loui	loui	NOUN
easat-3732	261	6	et	et	PROPN
easat-3732	261	7	al	al	PROPN
easat-3732	261	8	.	.	PROPN
easat-3732	261	9	,	,	PUNCT
easat-3732	261	10	“	"	PUNCT
easat-3732	261	11	kodak	kodak	PROPN
easat-3732	261	12	's	's	PART
easat-3732	261	13	consumer	consumer	NOUN
easat-3732	261	14	video	video	NOUN
easat-3732	261	15	benchmark	benchmark	NOUN
easat-3732	261	16	data	datum	NOUN
easat-3732	261	17	set	set	NOUN
easat-3732	261	18	:	:	PUNCT
easat-3732	261	19	concept	concept	NOUN
easat-3732	261	20	definition	definition	NOUN
easat-3732	261	21	and	and	CCONJ
easat-3732	261	22	annotation	annotation	NOUN
easat-3732	261	23	,	,	PUNCT
easat-3732	261	24	”	"	PUNCT
easat-3732	261	25	in	in	ADP
easat-3732	261	26	proceedings	proceeding	NOUN
easat-3732	261	27	of	of	ADP
easat-3732	261	28	the	the	DET
easat-3732	261	29	international	international	ADJ
easat-3732	261	30	workshop	workshop	NOUN
easat-3732	261	31	on	on	ADP
easat-3732	261	32	multimedia	multimedia	NOUN
easat-3732	261	33	information	information	NOUN
easat-3732	261	34	retrieval	retrieval	NOUN
easat-3732	261	35	(	(	PUNCT
easat-3732	261	36	mir	mir	PROPN
easat-3732	261	37	)	)	PUNCT
easat-3732	261	38	,	,	PUNCT
easat-3732	261	39	pp	pp	ADP
easat-3732	261	40	.	.	PUNCT
easat-3732	262	1	245–254	245–254	NUM
easat-3732	262	2	,	,	PUNCT
easat-3732	262	3	2007	2007	NUM
easat-3732	262	4	,	,	PUNCT
easat-3732	262	5	doi	doi	NOUN
easat-3732	262	6	:	:	PUNCT
easat-3732	262	7	10.1145/1290082.1290117	10.1145/1290082.1290117	NUM
easat-3732	262	8	.	.	PUNCT
easat-3732	263	1	[	[	X
easat-3732	263	2	20	20	NUM
easat-3732	263	3	]	]	PUNCT
easat-3732	263	4	i.	i.	NOUN
easat-3732	263	5	abdelhamed	abdelhamed	PROPN
easat-3732	263	6	,	,	PUNCT
easat-3732	263	7	s.	s.	PROPN
easat-3732	263	8	lin	lin	PROPN
easat-3732	263	9	,	,	PUNCT
easat-3732	263	10	and	and	CCONJ
easat-3732	263	11	m.	m.	PROPN
easat-3732	263	12	s.	s.	PROPN
easat-3732	263	13	brown	brown	PROPN
easat-3732	263	14	,	,	PUNCT
easat-3732	263	15	“	"	PUNCT
easat-3732	263	16	a	a	DET
easat-3732	263	17	high	high	ADJ
easat-3732	263	18	-	-	PUNCT
easat-3732	263	19	quality	quality	NOUN
easat-3732	263	20	denoising	denoising	NOUN
easat-3732	263	21	dataset	dataset	NOUN
easat-3732	263	22	for	for	ADP
easat-3732	263	23	smartphone	smartphone	NOUN
easat-3732	263	24	cameras	camera	NOUN
easat-3732	263	25	,	,	PUNCT
easat-3732	263	26	”	"	PUNCT
easat-3732	263	27	in	in	ADP
easat-3732	263	28	proceedings	proceeding	NOUN
easat-3732	263	29	of	of	ADP
easat-3732	263	30	the	the	DET
easat-3732	263	31	ieee	ieee	NOUN
easat-3732	263	32	/	/	SYM
easat-3732	263	33	cvf	cvf	NOUN
easat-3732	263	34	conference	conference	NOUN
easat-3732	263	35	on	on	ADP
easat-3732	263	36	computer	computer	NOUN
easat-3732	263	37	vision	vision	NOUN
easat-3732	263	38	and	and	CCONJ
easat-3732	263	39	pattern	pattern	NOUN
easat-3732	263	40	recognition	recognition	NOUN
easat-3732	263	41	(	(	PUNCT
easat-3732	263	42	cvpr	cvpr	NOUN
easat-3732	263	43	)	)	PUNCT
easat-3732	263	44	,	,	PUNCT
easat-3732	263	45	pp	pp	PROPN
easat-3732	263	46	.	.	PUNCT
easat-3732	264	1	1692–1700	1692–1700	NUM
easat-3732	264	2	,	,	PUNCT
easat-3732	264	3	2018	2018	NUM
easat-3732	264	4	,	,	PUNCT
easat-3732	264	5	doi	doi	NOUN
easat-3732	264	6	:	:	PUNCT
easat-3732	264	7	10.1109	10.1109	NUM
easat-3732	264	8	/	/	SYM
easat-3732	264	9	cvpr.2018.00182	cvpr.2018.00182	NOUN
easat-3732	264	10	.	.	PUNCT