id	sid	tid	token	lemma	pos
cana-4847	1	1	communications	communication	NOUN
cana-4847	1	2	on	on	ADP
cana-4847	1	3	applied	apply	VERB
cana-4847	1	4	nonlinear	nonlinear	ADJ
cana-4847	1	5	analysis	analysis	NOUN
cana-4847	1	6	issn	issn	NOUN
cana-4847	1	7	:	:	PUNCT
cana-4847	1	8	1074	1074	NUM
cana-4847	1	9	-	-	PUNCT
cana-4847	1	10	133x	133x	NUM
cana-4847	1	11	vol	vol	VERB
cana-4847	1	12	32	32	NUM
cana-4847	1	13	no	no	NOUN
cana-4847	1	14	.	.	PUNCT
cana-4847	2	1	10s	10	NOUN
cana-4847	2	2	(	(	PUNCT
cana-4847	2	3	2025	2025	NUM
cana-4847	2	4	)	)	PUNCT
cana-4847	2	5	567	567	NUM
cana-4847	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	2	7	cnn	cnn	PROPN
cana-4847	2	8	and	and	CCONJ
cana-4847	2	9	transfer	transfer	VERB
cana-4847	2	10	learning	learning	NOUN
cana-4847	2	11	methods	method	NOUN
cana-4847	2	12	for	for	ADP
cana-4847	2	13	enhanced	enhanced	ADJ
cana-4847	2	14	dermatological	dermatological	ADJ
cana-4847	2	15	disease	disease	NOUN
cana-4847	2	16	detection	detection	NOUN
cana-4847	2	17	c.venkataiah1	c.venkataiah1	PROPN
cana-4847	2	18	,	,	PUNCT
cana-4847	2	19	t.	t.	PROPN
cana-4847	2	20	jayachandra	jayachandra	PROPN
cana-4847	2	21	prasad2	prasad2	PROPN
cana-4847	2	22	,	,	PUNCT
cana-4847	2	23	g.	g.	PROPN
cana-4847	2	24	gopinath3	gopinath3	PROPN
cana-4847	2	25	,	,	PUNCT
cana-4847	2	26	b.	b.	PROPN
cana-4847	2	27	charitha4	charitha4	PROPN
cana-4847	2	28	,	,	PUNCT
cana-4847	2	29	g.	g.	PROPN
cana-4847	2	30	dharma	dharma	PROPN
cana-4847	2	31	teja5	teja5	PROPN
cana-4847	2	32	and	and	CCONJ
cana-4847	2	33	b.	b.	PROPN
cana-4847	3	1	lomith	lomith	PROPN
cana-4847	3	2	reddy6	reddy6	PROPN
cana-4847	3	3	1	1	NUM
cana-4847	3	4	associate	associate	NOUN
cana-4847	3	5	professor	professor	NOUN
cana-4847	3	6	,	,	PUNCT
cana-4847	3	7	department	department	PROPN
cana-4847	3	8	of	of	ADP
cana-4847	3	9	ece	ece	PROPN
cana-4847	3	10	,	,	PUNCT
cana-4847	3	11	rajeev	rajeev	PROPN
cana-4847	3	12	gandhi	gandhi	PROPN
cana-4847	3	13	memorial	memorial	PROPN
cana-4847	3	14	college	college	PROPN
cana-4847	3	15	of	of	ADP
cana-4847	3	16	engineering	engineering	NOUN
cana-4847	3	17	and	and	CCONJ
cana-4847	3	18	technology	technology	NOUN
cana-4847	3	19	,	,	PUNCT
cana-4847	3	20	nandyal	nandyal	NOUN
cana-4847	3	21	,	,	PUNCT
cana-4847	3	22	ap-518501	ap-518501	PROPN
cana-4847	3	23	,	,	PUNCT
cana-4847	3	24	india	india	PROPN
cana-4847	3	25	2	2	NUM
cana-4847	3	26	professor	professor	NOUN
cana-4847	3	27	,	,	PUNCT
cana-4847	3	28	department	department	PROPN
cana-4847	3	29	of	of	ADP
cana-4847	3	30	ece	ece	PROPN
cana-4847	3	31	,	,	PUNCT
cana-4847	3	32	rajeev	rajeev	PROPN
cana-4847	3	33	gandhi	gandhi	PROPN
cana-4847	3	34	memorial	memorial	PROPN
cana-4847	3	35	college	college	PROPN
cana-4847	3	36	of	of	ADP
cana-4847	3	37	engineering	engineering	NOUN
cana-4847	3	38	and	and	CCONJ
cana-4847	3	39	technology	technology	NOUN
cana-4847	3	40	,	,	PUNCT
cana-4847	3	41	nandyal	nandyal	NOUN
cana-4847	3	42	,	,	PUNCT
cana-4847	3	43	ap518501	ap518501	PROPN
cana-4847	3	44	,	,	PUNCT
cana-4847	3	45	india	india	PROPN
cana-4847	3	46	3	3	NUM
cana-4847	3	47	,	,	PUNCT
cana-4847	3	48	4	4	NUM
cana-4847	3	49	,	,	PUNCT
cana-4847	3	50	5	5	NUM
cana-4847	3	51	,	,	PUNCT
cana-4847	3	52	6	6	NUM
cana-4847	3	53	student	student	NOUN
cana-4847	3	54	,	,	PUNCT
cana-4847	3	55	department	department	PROPN
cana-4847	3	56	of	of	ADP
cana-4847	3	57	ece	ece	PROPN
cana-4847	3	58	,	,	PUNCT
cana-4847	3	59	rajeev	rajeev	PROPN
cana-4847	3	60	gandhi	gandhi	PROPN
cana-4847	3	61	memorial	memorial	PROPN
cana-4847	3	62	college	college	PROPN
cana-4847	3	63	of	of	ADP
cana-4847	3	64	engineering	engineering	NOUN
cana-4847	3	65	and	and	CCONJ
cana-4847	3	66	technology	technology	NOUN
cana-4847	3	67	,	,	PUNCT
cana-4847	3	68	nandyal	nandyal	NOUN
cana-4847	3	69	,	,	PUNCT
cana-4847	3	70	ap518501	ap518501	ADJ
cana-4847	3	71	,	,	PUNCT
cana-4847	3	72	india	india	PROPN
cana-4847	3	73	email	email	NOUN
cana-4847	3	74	:	:	PUNCT
cana-4847	3	75	1venki.challa@gmail.com	1venki.challa@gmail.com	NUM
cana-4847	3	76	,	,	PUNCT
cana-4847	3	77	2jp.talari@gmail.com	2jp.talari@gmail.com	NUM
cana-4847	3	78	,	,	PUNCT
cana-4847	3	79	3gantagopinath03@gmail.com	3gantagopinath03@gmail.com	NUM
cana-4847	3	80	,	,	PUNCT
cana-4847	3	81	4charithabyreddy15@gmail.com	4charithabyreddy15@gmail.com	PROPN
cana-4847	3	82	,	,	PUNCT
cana-4847	3	83	5dharmateja6200@gmail.com	5dharmateja6200@gmail.com	NUM
cana-4847	3	84	,	,	PUNCT
cana-4847	3	85	6lomithreddy@gmail.com	6lomithreddy@gmail.com	NUM
cana-4847	3	86	article	article	NOUN
cana-4847	3	87	history	history	NOUN
cana-4847	3	88	:	:	PUNCT
cana-4847	3	89	received	receive	VERB
cana-4847	3	90	:	:	PUNCT
cana-4847	3	91	12	12	NUM
cana-4847	3	92	-	-	SYM
cana-4847	3	93	01	01	NUM
cana-4847	3	94	-	-	PUNCT
cana-4847	3	95	2025	2025	NUM
cana-4847	3	96	revised	revise	VERB
cana-4847	3	97	:	:	PUNCT
cana-4847	3	98	15	15	NUM
cana-4847	3	99	-	-	NUM
cana-4847	3	100	02	02	NUM
cana-4847	3	101	-	-	PUNCT
cana-4847	3	102	2025	2025	NUM
cana-4847	3	103	accepted	accept	VERB
cana-4847	3	104	:	:	PUNCT
cana-4847	3	105	01	01	NUM
cana-4847	3	106	-	-	SYM
cana-4847	3	107	03	03	NUM
cana-4847	3	108	-	-	PUNCT
cana-4847	3	109	2025	2025	NUM
cana-4847	3	110	abstract	abstract	NOUN
cana-4847	3	111	:	:	PUNCT
cana-4847	3	112	since	since	SCONJ
cana-4847	3	113	skin	skin	NOUN
cana-4847	3	114	diseases	disease	NOUN
cana-4847	3	115	generally	generally	ADV
cana-4847	3	116	badly	badly	ADV
cana-4847	3	117	affect	affect	VERB
cana-4847	3	118	lives	life	NOUN
cana-4847	3	119	,	,	PUNCT
cana-4847	3	120	the	the	DET
cana-4847	3	121	earlier	early	ADJ
cana-4847	3	122	and	and	CCONJ
cana-4847	3	123	more	more	ADV
cana-4847	3	124	accurate	accurate	ADJ
cana-4847	3	125	the	the	DET
cana-4847	3	126	diagnosis	diagnosis	NOUN
cana-4847	3	127	,	,	PUNCT
cana-4847	3	128	the	the	PRON
cana-4847	3	129	better	well	ADJ
cana-4847	3	130	the	the	DET
cana-4847	3	131	chances	chance	NOUN
cana-4847	3	132	of	of	ADP
cana-4847	3	133	effective	effective	ADJ
cana-4847	3	134	treatment	treatment	NOUN
cana-4847	3	135	and	and	CCONJ
cana-4847	3	136	a	a	DET
cana-4847	3	137	better	well	ADJ
cana-4847	3	138	prognosis	prognosis	NOUN
cana-4847	3	139	.	.	PUNCT
cana-4847	4	1	deep	deep	ADJ
cana-4847	4	2	learning	learning	NOUN
cana-4847	4	3	applications	application	NOUN
cana-4847	4	4	,	,	PUNCT
cana-4847	4	5	especially	especially	ADV
cana-4847	4	6	cnns	cnn	NOUN
cana-4847	4	7	,	,	PUNCT
cana-4847	4	8	has	have	AUX
cana-4847	4	9	revolutionized	revolutionize	VERB
cana-4847	4	10	the	the	DET
cana-4847	4	11	domain	domain	NOUN
cana-4847	4	12	of	of	ADP
cana-4847	4	13	disease	disease	NOUN
cana-4847	4	14	classification	classification	NOUN
cana-4847	4	15	,	,	PUNCT
cana-4847	4	16	significantly	significantly	ADV
cana-4847	4	17	increasing	increase	VERB
cana-4847	4	18	the	the	DET
cana-4847	4	19	accuracy	accuracy	NOUN
cana-4847	4	20	of	of	ADP
cana-4847	4	21	diagnoses	diagnosis	NOUN
cana-4847	4	22	for	for	ADP
cana-4847	4	23	such	such	ADJ
cana-4847	4	24	common	common	ADJ
cana-4847	4	25	conditions	condition	NOUN
cana-4847	4	26	and	and	CCONJ
cana-4847	4	27	facilitating	facilitate	VERB
cana-4847	4	28	early	early	ADJ
cana-4847	4	29	interventions	intervention	NOUN
cana-4847	4	30	.	.	PUNCT
cana-4847	5	1	the	the	DET
cana-4847	5	2	huge	huge	ADJ
cana-4847	5	3	success	success	NOUN
cana-4847	5	4	behind	behind	ADP
cana-4847	5	5	the	the	DET
cana-4847	5	6	ongoing	ongoing	ADJ
cana-4847	5	7	project	project	NOUN
cana-4847	5	8	motivated	motivated	ADJ
cana-4847	5	9	advancements	advancement	NOUN
cana-4847	5	10	of	of	ADP
cana-4847	5	11	the	the	DET
cana-4847	5	12	developing	developing	NOUN
cana-4847	5	13	in	in	ADP
cana-4847	5	14	cnn	cnn	PROPN
cana-4847	5	15	techniques	technique	NOUN
cana-4847	5	16	towards	towards	ADP
cana-4847	5	17	detection	detection	NOUN
cana-4847	5	18	of	of	ADP
cana-4847	5	19	skin	skin	NOUN
cana-4847	5	20	disease	disease	NOUN
cana-4847	5	21	by	by	ADP
cana-4847	5	22	using	use	VERB
cana-4847	5	23	the	the	DET
cana-4847	5	24	concept	concept	NOUN
cana-4847	5	25	of	of	ADP
cana-4847	5	26	transfer	transfer	NOUN
cana-4847	5	27	learning	learning	NOUN
cana-4847	5	28	.	.	PUNCT
cana-4847	6	1	so	so	ADV
cana-4847	6	2	,	,	PUNCT
cana-4847	6	3	the	the	DET
cana-4847	6	4	older	old	ADJ
cana-4847	6	5	models	model	NOUN
cana-4847	6	6	,	,	PUNCT
cana-4847	6	7	which	which	PRON
cana-4847	6	8	had	have	AUX
cana-4847	6	9	employed	employ	VERB
cana-4847	6	10	it	it	PRON
cana-4847	6	11	for	for	ADP
cana-4847	6	12	detecting	detect	VERB
cana-4847	6	13	eczema	eczema	NOUN
cana-4847	6	14	and	and	CCONJ
cana-4847	6	15	psoriasis	psoriasis	NOUN
cana-4847	6	16	based	base	VERB
cana-4847	6	17	on	on	ADP
cana-4847	6	18	the	the	DET
cana-4847	6	19	architectures	architecture	NOUN
cana-4847	6	20	involving	involve	VERB
cana-4847	6	21	deep	deep	ADJ
cana-4847	6	22	cnns	cnn	NOUN
cana-4847	6	23	.	.	PUNCT
cana-4847	7	1	the	the	DET
cana-4847	7	2	inception	inception	ADJ
cana-4847	7	3	resnet	resnet	NOUN
cana-4847	7	4	v2	v2	NOUN
cana-4847	7	5	architecture	architecture	NOUN
cana-4847	7	6	improved	improve	VERB
cana-4847	7	7	the	the	DET
cana-4847	7	8	accuracy	accuracy	NOUN
cana-4847	7	9	of	of	ADP
cana-4847	7	10	that	that	DET
cana-4847	7	11	model	model	NOUN
cana-4847	7	12	,	,	PUNCT
cana-4847	7	13	with	with	ADP
cana-4847	7	14	some	some	DET
cana-4847	7	15	practical	practical	ADJ
cana-4847	7	16	implementations	implementation	NOUN
cana-4847	7	17	via	via	ADP
cana-4847	7	18	smartphone	smartphone	NOUN
cana-4847	7	19	integration	integration	NOUN
cana-4847	7	20	and	and	CCONJ
cana-4847	7	21	web	web	NOUN
cana-4847	7	22	server	server	NOUN
cana-4847	7	23	integration	integration	NOUN
cana-4847	7	24	.	.	PUNCT
cana-4847	8	1	some	some	PRON
cana-4847	8	2	of	of	ADP
cana-4847	8	3	those	those	DET
cana-4847	8	4	innovations	innovation	NOUN
cana-4847	8	5	are	be	AUX
cana-4847	8	6	as	as	SCONJ
cana-4847	8	7	follows	follow	VERB
cana-4847	8	8	in	in	ADP
cana-4847	8	9	our	our	PRON
cana-4847	8	10	project	project	NOUN
cana-4847	8	11	.	.	PUNCT
cana-4847	9	1	the	the	DET
cana-4847	9	2	earlier	early	ADJ
cana-4847	9	3	work	work	NOUN
cana-4847	9	4	used	use	VERB
cana-4847	9	5	different	different	ADJ
cana-4847	9	6	cnn	cnn	PROPN
cana-4847	9	7	architectures	architecture	NOUN
cana-4847	9	8	.	.	PUNCT
cana-4847	10	1	our	our	PRON
cana-4847	10	2	approach	approach	NOUN
cana-4847	10	3	involved	involve	VERB
cana-4847	10	4	transfer	transfer	NOUN
cana-4847	10	5	learning	learn	VERB
cana-4847	10	6	with	with	ADP
cana-4847	10	7	a	a	DET
cana-4847	10	8	pre	pre	ADJ
cana-4847	10	9	-	-	ADJ
cana-4847	10	10	trained	train	VERB
cana-4847	10	11	resnet50	resnet50	NOUN
cana-4847	10	12	model	model	NOUN
cana-4847	10	13	to	to	PART
cana-4847	10	14	try	try	VERB
cana-4847	10	15	to	to	PART
cana-4847	10	16	improve	improve	VERB
cana-4847	10	17	performance	performance	NOUN
cana-4847	10	18	and	and	CCONJ
cana-4847	10	19	efficiency	efficiency	NOUN
cana-4847	10	20	using	use	VERB
cana-4847	10	21	features	feature	NOUN
cana-4847	10	22	learned	learn	VERB
cana-4847	10	23	from	from	ADP
cana-4847	10	24	large	large	ADJ
cana-4847	10	25	-	-	PUNCT
cana-4847	10	26	scale	scale	NOUN
cana-4847	10	27	datasets	dataset	NOUN
cana-4847	10	28	.	.	PUNCT
cana-4847	11	1	this	this	PRON
cana-4847	11	2	reduce	reduce	VERB
cana-4847	11	3	the	the	DET
cana-4847	11	4	complexity	complexity	NOUN
cana-4847	11	5	and	and	CCONJ
cana-4847	11	6	enhance	enhance	VERB
cana-4847	11	7	the	the	DET
cana-4847	11	8	accuracy	accuracy	NOUN
cana-4847	11	9	.	.	PUNCT
cana-4847	12	1	besides	besides	SCONJ
cana-4847	12	2	transfer	transfer	VERB
cana-4847	12	3	learning	learning	NOUN
cana-4847	12	4	adaptation	adaptation	NOUN
cana-4847	12	5	,	,	PUNCT
cana-4847	12	6	our	our	PRON
cana-4847	12	7	project	project	NOUN
cana-4847	12	8	encompasses	encompass	VERB
cana-4847	12	9	elaborate	elaborate	ADJ
cana-4847	12	10	preprocessing	preprocessing	NOUN
cana-4847	12	11	techniques	technique	NOUN
cana-4847	12	12	like	like	ADP
cana-4847	12	13	resizing	resizing	NOUN
cana-4847	12	14	,	,	PUNCT
cana-4847	12	15	normalization	normalization	NOUN
cana-4847	12	16	,	,	PUNCT
cana-4847	12	17	and	and	CCONJ
cana-4847	12	18	data	datum	NOUN
cana-4847	12	19	augmentation	augmentation	NOUN
cana-4847	12	20	in	in	ADP
cana-4847	12	21	finetuning	finetune	VERB
cana-4847	12	22	the	the	DET
cana-4847	12	23	dataset	dataset	NOUN
cana-4847	12	24	for	for	ADP
cana-4847	12	25	further	further	ADJ
cana-4847	12	26	model	model	NOUN
cana-4847	12	27	fine	fine	ADV
cana-4847	12	28	-	-	PUNCT
cana-4847	12	29	tuning	tuning	NOUN
cana-4847	12	30	.	.	PUNCT
cana-4847	13	1	it	it	PRON
cana-4847	13	2	has	have	VERB
cana-4847	13	3	97.6	97.6	NUM
cana-4847	13	4	%	%	NOUN
cana-4847	13	5	accuracy	accuracy	NOUN
cana-4847	13	6	,	,	PUNCT
cana-4847	13	7	95	95	NUM
cana-4847	13	8	%	%	NOUN
cana-4847	13	9	precision	precision	NOUN
cana-4847	13	10	,	,	PUNCT
cana-4847	13	11	99.4	99.4	NUM
cana-4847	13	12	%	%	NOUN
cana-4847	13	13	recall	recall	NOUN
cana-4847	13	14	,	,	PUNCT
cana-4847	13	15	and	and	CCONJ
cana-4847	13	16	97.4	97.4	NUM
cana-4847	13	17	%	%	NOUN
cana-4847	13	18	f1	f1	NOUN
cana-4847	13	19	-	-	PUNCT
cana-4847	13	20	score	score	NOUN
cana-4847	13	21	.	.	PUNCT
cana-4847	14	1	rad	rad	ADJ
cana-4847	14	2	-	-	ADJ
cana-4847	14	3	cam	cam	NOUN
cana-4847	14	4	techniques	technique	NOUN
cana-4847	14	5	have	have	AUX
cana-4847	14	6	been	be	AUX
cana-4847	14	7	employed	employ	VERB
cana-4847	14	8	to	to	PART
cana-4847	14	9	visualize	visualize	VERB
cana-4847	14	10	and	and	CCONJ
cana-4847	14	11	interpret	interpret	VERB
cana-4847	14	12	model	model	NOUN
cana-4847	14	13	predictions	prediction	NOUN
cana-4847	14	14	.	.	PUNCT
cana-4847	15	1	this	this	DET
cana-4847	15	2	final	final	ADJ
cana-4847	15	3	model	model	NOUN
cana-4847	15	4	has	have	AUX
cana-4847	15	5	been	be	AUX
cana-4847	15	6	a	a	DET
cana-4847	15	7	pragmatic	pragmatic	ADJ
cana-4847	15	8	and	and	CCONJ
cana-4847	15	9	accessible	accessible	ADJ
cana-4847	15	10	tool	tool	NOUN
cana-4847	15	11	for	for	ADP
cana-4847	15	12	early	early	ADJ
cana-4847	15	13	detection	detection	NOUN
cana-4847	15	14	and	and	CCONJ
cana-4847	15	15	diagnosis	diagnosis	NOUN
cana-4847	15	16	of	of	ADP
cana-4847	15	17	skin	skin	NOUN
cana-4847	15	18	disease	disease	NOUN
cana-4847	15	19	.	.	PUNCT
cana-4847	16	1	the	the	DET
cana-4847	16	2	feature	feature	NOUN
cana-4847	16	3	here	here	ADV
cana-4847	16	4	is	be	AUX
cana-4847	16	5	an	an	DET
cana-4847	16	6	attempt	attempt	NOUN
cana-4847	16	7	to	to	PART
cana-4847	16	8	provide	provide	VERB
cana-4847	16	9	a	a	DET
cana-4847	16	10	more	more	ADV
cana-4847	16	11	accurate	accurate	ADJ
cana-4847	16	12	,	,	PUNCT
cana-4847	16	13	efficient	efficient	ADJ
cana-4847	16	14	,	,	PUNCT
cana-4847	16	15	and	and	CCONJ
cana-4847	16	16	user	user	NOUN
cana-4847	16	17	-	-	PUNCT
cana-4847	16	18	friendly	friendly	ADJ
cana-4847	16	19	diagnostic	diagnostic	ADJ
cana-4847	16	20	solution	solution	NOUN
cana-4847	16	21	through	through	ADP
cana-4847	16	22	the	the	DET
cana-4847	16	23	incorporation	incorporation	NOUN
cana-4847	16	24	of	of	ADP
cana-4847	16	25	advanced	advanced	ADJ
cana-4847	16	26	methods	method	NOUN
cana-4847	16	27	of	of	ADP
cana-4847	16	28	transfer	transfer	NOUN
cana-4847	16	29	learning	learning	NOUN
cana-4847	16	30	and	and	CCONJ
cana-4847	16	31	visualization	visualization	NOUN
cana-4847	16	32	.	.	PUNCT
cana-4847	17	1	keywords	keyword	NOUN
cana-4847	17	2	:	:	PUNCT
cana-4847	17	3	eczema	eczema	NOUN
cana-4847	17	4	,	,	PUNCT
cana-4847	17	5	psoriasis	psoriasis	NOUN
cana-4847	17	6	,	,	PUNCT
cana-4847	17	7	dermatology	dermatology	NOUN
cana-4847	17	8	,	,	PUNCT
cana-4847	17	9	cnn	cnn	PROPN
cana-4847	17	10	,	,	PUNCT
cana-4847	17	11	transfer	transfer	NOUN
cana-4847	17	12	learning	learning	NOUN
cana-4847	17	13	.	.	PUNCT
cana-4847	18	1	1.introduction	1.introduction	NUM
cana-4847	18	2	consider	consider	VERB
cana-4847	18	3	an	an	DET
cana-4847	18	4	example	example	NOUN
cana-4847	18	5	of	of	ADP
cana-4847	18	6	a	a	DET
cana-4847	18	7	skin	skin	NOUN
cana-4847	18	8	disorder	disorder	NOUN
cana-4847	18	9	which	which	PRON
cana-4847	18	10	not	not	PART
cana-4847	18	11	only	only	ADV
cana-4847	18	12	has	have	VERB
cana-4847	18	13	an	an	DET
cana-4847	18	14	impact	impact	NOUN
cana-4847	18	15	on	on	ADP
cana-4847	18	16	the	the	DET
cana-4847	18	17	physical	physical	ADJ
cana-4847	18	18	health	health	NOUN
cana-4847	18	19	of	of	ADP
cana-4847	18	20	an	an	DET
cana-4847	18	21	individual	individual	NOUN
cana-4847	18	22	but	but	CCONJ
cana-4847	18	23	also	also	ADV
cana-4847	18	24	their	their	PRON
cana-4847	18	25	mental	mental	ADJ
cana-4847	18	26	health	health	NOUN
cana-4847	18	27	.	.	PUNCT
cana-4847	19	1	millions	million	NOUN
cana-4847	19	2	of	of	ADP
cana-4847	19	3	people	people	NOUN
cana-4847	19	4	all	all	ADV
cana-4847	19	5	over	over	ADP
cana-4847	19	6	the	the	DET
cana-4847	19	7	world	world	NOUN
cana-4847	19	8	suffer	suffer	VERB
cana-4847	19	9	from	from	ADP
cana-4847	19	10	diseases	disease	NOUN
cana-4847	19	11	such	such	ADJ
cana-4847	19	12	as	as	ADP
cana-4847	19	13	eczema	eczema	NOUN
cana-4847	19	14	and	and	CCONJ
cana-4847	19	15	psoriasis	psoriasis	NOUN
cana-4847	19	16	,	,	PUNCT
cana-4847	19	17	which	which	PRON
cana-4847	19	18	severely	severely	ADV
cana-4847	19	19	impact	impact	VERB
cana-4847	19	20	the	the	DET
cana-4847	19	21	quality	quality	NOUN
cana-4847	19	22	of	of	ADP
cana-4847	19	23	life	life	NOUN
cana-4847	19	24	.	.	PUNCT
cana-4847	20	1	the	the	DET
cana-4847	20	2	catch	catch	NOUN
cana-4847	20	3	here	here	ADV
cana-4847	20	4	is	be	AUX
cana-4847	20	5	,	,	PUNCT
cana-4847	20	6	such	such	ADJ
cana-4847	20	7	diseases	disease	NOUN
cana-4847	20	8	are	be	AUX
cana-4847	20	9	hard	hard	ADJ
cana-4847	20	10	to	to	PART
cana-4847	20	11	diagnose	diagnose	VERB
cana-4847	20	12	in	in	ADP
cana-4847	20	13	the	the	DET
cana-4847	20	14	early	early	ADJ
cana-4847	20	15	stage	stage	NOUN
cana-4847	20	16	and	and	CCONJ
cana-4847	20	17	exactly	exactly	ADV
cana-4847	20	18	because	because	SCONJ
cana-4847	20	19	of	of	ADP
cana-4847	20	20	the	the	DET
cana-4847	20	21	heterogeneity	heterogeneity	NOUN
cana-4847	20	22	and	and	CCONJ
cana-4847	20	23	complexity	complexity	NOUN
cana-4847	20	24	of	of	ADP
cana-4847	20	25	the	the	DET
cana-4847	20	26	mailto:venki.challa@gmail.com	mailto:venki.challa@gmail.com	X
cana-4847	20	27	mailto:2jp.talari@gmail.com	mailto:2jp.talari@gmail.com	X
cana-4847	20	28	mailto:3gantagopinath03@gmail.com	mailto:3gantagopinath03@gmail.com	PROPN
cana-4847	20	29	mailto:5dharmateja6200@gmail.com	mailto:5dharmateja6200@gmail.com	PROPN
cana-4847	20	30	communications	communication	NOUN
cana-4847	20	31	on	on	ADP
cana-4847	20	32	applied	apply	VERB
cana-4847	20	33	nonlinear	nonlinear	ADJ
cana-4847	20	34	analysis	analysis	NOUN
cana-4847	20	35	issn	issn	NOUN
cana-4847	20	36	:	:	PUNCT
cana-4847	20	37	1074	1074	NUM
cana-4847	20	38	-	-	PUNCT
cana-4847	20	39	133x	133x	NUM
cana-4847	20	40	vol	vol	VERB
cana-4847	20	41	32	32	NUM
cana-4847	20	42	no	no	NOUN
cana-4847	20	43	.	.	PUNCT
cana-4847	21	1	10s	10	NOUN
cana-4847	21	2	(	(	PUNCT
cana-4847	21	3	2025	2025	NUM
cana-4847	21	4	)	)	PUNCT
cana-4847	21	5	568	568	NUM
cana-4847	21	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	21	7	symptoms	symptom	NOUN
cana-4847	21	8	involved	involve	VERB
cana-4847	21	9	.	.	PUNCT
cana-4847	22	1	this	this	PRON
cana-4847	22	2	shall	shall	AUX
cana-4847	22	3	be	be	AUX
cana-4847	22	4	overcome	overcome	VERB
cana-4847	22	5	using	use	VERB
cana-4847	22	6	the	the	DET
cana-4847	22	7	convolutional	convolutional	ADJ
cana-4847	22	8	neural	neural	ADJ
cana-4847	22	9	network	network	NOUN
cana-4847	22	10	(	(	PUNCT
cana-4847	22	11	cnn	cnn	PROPN
cana-4847	22	12	)	)	PUNCT
cana-4847	22	13	part	part	NOUN
cana-4847	22	14	of	of	ADP
cana-4847	22	15	deep	deep	ADJ
cana-4847	22	16	learning	learning	NOUN
cana-4847	22	17	and	and	CCONJ
cana-4847	22	18	ai	ai	VERB
cana-4847	22	19	that	that	PRON
cana-4847	22	20	would	would	AUX
cana-4847	22	21	facilitate	facilitate	VERB
cana-4847	22	22	fast	fast	ADJ
cana-4847	22	23	and	and	CCONJ
cana-4847	22	24	accurate	accurate	ADJ
cana-4847	22	25	detection	detection	NOUN
cana-4847	22	26	of	of	ADP
cana-4847	22	27	automated	automate	VERB
cana-4847	22	28	skin	skin	NOUN
cana-4847	22	29	diseases	disease	NOUN
cana-4847	22	30	.	.	PUNCT
cana-4847	23	1	our	our	PRON
cana-4847	23	2	aim	aim	NOUN
cana-4847	23	3	will	will	AUX
cana-4847	23	4	be	be	AUX
cana-4847	23	5	to	to	PART
cana-4847	23	6	expand	expand	VERB
cana-4847	23	7	the	the	DET
cana-4847	23	8	cnn	cnn	PROPN
cana-4847	23	9	-	-	PUNCT
cana-4847	23	10	based	base	VERB
cana-4847	23	11	models	model	NOUN
cana-4847	23	12	by	by	ADP
cana-4847	23	13	exploiting	exploit	VERB
cana-4847	23	14	transfer	transfer	NOUN
cana-4847	23	15	learning	learning	NOUN
cana-4847	23	16	.	.	PUNCT
cana-4847	24	1	it	it	PRON
cana-4847	24	2	is	be	AUX
cana-4847	24	3	relatively	relatively	ADV
cana-4847	24	4	feasible	feasible	ADJ
cana-4847	24	5	to	to	PART
cana-4847	24	6	deploy	deploy	VERB
cana-4847	24	7	pre	pre	ADJ
cana-4847	24	8	-	-	ADJ
cana-4847	24	9	trained	train	VERB
cana-4847	24	10	models	model	NOUN
cana-4847	24	11	like	like	ADP
cana-4847	24	12	resnet50	resnet50	NOUN
cana-4847	24	13	at	at	ADP
cana-4847	24	14	the	the	DET
cana-4847	24	15	cost	cost	NOUN
cana-4847	24	16	of	of	ADP
cana-4847	24	17	enhancements	enhancement	NOUN
cana-4847	24	18	in	in	ADP
cana-4847	24	19	computational	computational	ADJ
cana-4847	24	20	resources	resource	NOUN
cana-4847	24	21	and	and	CCONJ
cana-4847	24	22	accuracy	accuracy	NOUN
cana-4847	24	23	.	.	PUNCT
cana-4847	25	1	looking	look	VERB
cana-4847	25	2	forward	forward	ADV
cana-4847	25	3	to	to	ADP
cana-4847	25	4	being	be	AUX
cana-4847	25	5	able	able	ADJ
cana-4847	25	6	to	to	PART
cana-4847	25	7	develop	develop	VERB
cana-4847	25	8	an	an	DET
cana-4847	25	9	easy	easy	ADJ
cana-4847	25	10	-	-	PUNCT
cana-4847	25	11	to	to	ADP
cana-4847	25	12	-	-	PUNCT
cana-4847	25	13	use	use	VERB
cana-4847	25	14	and	and	CCONJ
cana-4847	25	15	pragmatic	pragmatic	ADJ
cana-4847	25	16	early	early	ADJ
cana-4847	25	17	-	-	PUNCT
cana-4847	25	18	stage	stage	NOUN
cana-4847	25	19	disease	disease	NOUN
cana-4847	25	20	detection	detection	NOUN
cana-4847	25	21	tool	tool	NOUN
cana-4847	25	22	for	for	ADP
cana-4847	25	23	skin	skin	NOUN
cana-4847	25	24	diseases	disease	NOUN
cana-4847	25	25	that	that	PRON
cana-4847	25	26	bridges	bridge	VERB
cana-4847	25	27	the	the	DET
cana-4847	25	28	hype	hype	NOUN
cana-4847	25	29	of	of	ADP
cana-4847	25	30	ai	ai	NOUN
cana-4847	25	31	with	with	ADP
cana-4847	25	32	reality	reality	NOUN
cana-4847	25	33	on	on	ADP
cana-4847	25	34	the	the	DET
cana-4847	25	35	ground	ground	NOUN
cana-4847	25	36	in	in	ADP
cana-4847	25	37	healthcare	healthcare	PROPN
cana-4847	25	38	.	.	PUNCT
cana-4847	26	1	in	in	ADP
cana-4847	26	2	order	order	NOUN
cana-4847	26	3	to	to	PART
cana-4847	26	4	enhance	enhance	VERB
cana-4847	26	5	our	our	PRON
cana-4847	26	6	model	model	NOUN
cana-4847	26	7	,	,	PUNCT
cana-4847	26	8	these	these	PRON
cana-4847	26	9	would	would	AUX
cana-4847	26	10	entail	entail	VERB
cana-4847	26	11	resizing	resize	VERB
cana-4847	26	12	and	and	CCONJ
cana-4847	26	13	standardizing	standardize	VERB
cana-4847	26	14	our	our	PRON
cana-4847	26	15	data	datum	NOUN
cana-4847	26	16	as	as	ADV
cana-4847	26	17	well	well	ADV
cana-4847	26	18	as	as	ADP
cana-4847	26	19	sophisticated	sophisticated	ADJ
cana-4847	26	20	data	datum	NOUN
cana-4847	26	21	augmentation	augmentation	NOUN
cana-4847	26	22	techniques	technique	NOUN
cana-4847	26	23	.	.	PUNCT
cana-4847	27	1	the	the	DET
cana-4847	27	2	confidence	confidence	NOUN
cana-4847	27	3	in	in	ADP
cana-4847	27	4	ai	ai	ADV
cana-4847	27	5	-	-	PUNCT
cana-4847	27	6	based	base	VERB
cana-4847	27	7	healthcare	healthcare	NOUN
cana-4847	27	8	solutions	solution	NOUN
cana-4847	27	9	will	will	AUX
cana-4847	27	10	be	be	AUX
cana-4847	27	11	increased	increase	VERB
cana-4847	27	12	by	by	ADP
cana-4847	27	13	measuring	measure	VERB
cana-4847	27	14	performance	performance	NOUN
cana-4847	27	15	metrics	metric	NOUN
cana-4847	27	16	such	such	ADJ
cana-4847	27	17	as	as	ADP
cana-4847	27	18	precision	precision	NOUN
cana-4847	27	19	,	,	PUNCT
cana-4847	27	20	recall	recall	NOUN
cana-4847	27	21	,	,	PUNCT
cana-4847	27	22	accuracy	accuracy	NOUN
cana-4847	27	23	,	,	PUNCT
cana-4847	27	24	and	and	CCONJ
cana-4847	27	25	f1	f1	NOUN
cana-4847	27	26	-	-	PUNCT
cana-4847	27	27	score	score	NOUN
cana-4847	27	28	for	for	ADP
cana-4847	27	29	the	the	DET
cana-4847	27	30	aforementioned	aforementione	VERB
cana-4847	27	31	models	model	NOUN
cana-4847	27	32	to	to	PART
cana-4847	27	33	explain	explain	VERB
cana-4847	27	34	model	model	NOUN
cana-4847	27	35	predictions	prediction	NOUN
cana-4847	27	36	like	like	ADP
cana-4847	27	37	grad	grad	NOUN
cana-4847	27	38	-	-	PUNCT
cana-4847	27	39	cam	cam	NOUN
cana-4847	28	1	[	[	X
cana-4847	28	2	1	1	NUM
cana-4847	28	3	]	]	PUNCT
cana-4847	28	4	.	.	PUNCT
cana-4847	29	1	ultimately	ultimately	ADV
cana-4847	29	2	,	,	PUNCT
cana-4847	29	3	our	our	PRON
cana-4847	29	4	initiative	initiative	NOUN
cana-4847	29	5	aims	aim	VERB
cana-4847	29	6	to	to	PART
cana-4847	29	7	develop	develop	VERB
cana-4847	29	8	a	a	DET
cana-4847	29	9	quick	quick	ADJ
cana-4847	29	10	and	and	CCONJ
cana-4847	29	11	effective	effective	ADJ
cana-4847	29	12	way	way	NOUN
cana-4847	29	13	to	to	PART
cana-4847	29	14	identify	identify	VERB
cana-4847	29	15	skin	skin	NOUN
cana-4847	29	16	conditions	condition	NOUN
cana-4847	29	17	,	,	PUNCT
cana-4847	29	18	which	which	PRON
cana-4847	29	19	will	will	AUX
cana-4847	29	20	alleviate	alleviate	VERB
cana-4847	29	21	the	the	DET
cana-4847	29	22	strain	strain	NOUN
cana-4847	29	23	on	on	ADP
cana-4847	29	24	healthcare	healthcare	NOUN
cana-4847	29	25	systems	system	NOUN
cana-4847	29	26	and	and	CCONJ
cana-4847	29	27	improve	improve	VERB
cana-4847	29	28	patient	patient	ADJ
cana-4847	29	29	outcomes	outcome	NOUN
cana-4847	29	30	.	.	PUNCT
cana-4847	30	1	it	it	PRON
cana-4847	30	2	is	be	AUX
cana-4847	30	3	a	a	DET
cana-4847	30	4	field	field	NOUN
cana-4847	30	5	of	of	ADP
cana-4847	30	6	ai	ai	NOUN
cana-4847	30	7	-	-	PUNCT
cana-4847	30	8	based	base	VERB
cana-4847	30	9	healthcare	healthcare	NOUN
cana-4847	30	10	solutions	solution	NOUN
cana-4847	30	11	that	that	PRON
cana-4847	30	12	will	will	AUX
cana-4847	30	13	revolutionize	revolutionize	VERB
cana-4847	30	14	patient	patient	NOUN
cana-4847	30	15	care	care	NOUN
cana-4847	30	16	and	and	CCONJ
cana-4847	30	17	diagnostics	diagnostic	NOUN
cana-4847	30	18	by	by	ADP
cana-4847	30	19	using	use	VERB
cana-4847	30	20	sophisticated	sophisticated	ADJ
cana-4847	30	21	visualization	visualization	NOUN
cana-4847	30	22	techniques	technique	NOUN
cana-4847	30	23	and	and	CCONJ
cana-4847	30	24	transfer	transfer	NOUN
cana-4847	30	25	learning	learning	NOUN
cana-4847	30	26	.	.	PUNCT
cana-4847	31	1	2	2	X
cana-4847	31	2	.	.	X
cana-4847	31	3	literature	literature	NOUN
cana-4847	31	4	review	review	PROPN
cana-4847	31	5	skin	skin	NOUN
cana-4847	31	6	diseases	disease	NOUN
cana-4847	31	7	make	make	VERB
cana-4847	31	8	up	up	ADP
cana-4847	31	9	part	part	NOUN
cana-4847	31	10	of	of	ADP
cana-4847	31	11	the	the	DET
cana-4847	31	12	currently	currently	ADV
cana-4847	31	13	sweeping	sweeping	ADJ
cana-4847	31	14	and	and	CCONJ
cana-4847	31	15	on	on	ADP
cana-4847	31	16	-	-	PUNCT
cana-4847	31	17	the	the	DET
cana-4847	31	18	-	-	PUNCT
cana-4847	31	19	rise	rise	NOUN
cana-4847	31	20	global	global	ADJ
cana-4847	31	21	health	health	NOUN
cana-4847	31	22	issues	issue	NOUN
cana-4847	31	23	,	,	PUNCT
cana-4847	31	24	plaguing	plague	VERB
cana-4847	31	25	millions	million	NOUN
cana-4847	31	26	.	.	PUNCT
cana-4847	32	1	the	the	DET
cana-4847	32	2	scale	scale	NOUN
cana-4847	32	3	is	be	AUX
cana-4847	32	4	enormous	enormous	ADJ
cana-4847	32	5	with	with	ADP
cana-4847	32	6	millions	million	NOUN
cana-4847	32	7	unable	unable	ADJ
cana-4847	32	8	to	to	PART
cana-4847	32	9	live	live	VERB
cana-4847	32	10	normal	normal	ADJ
cana-4847	32	11	lives	life	NOUN
cana-4847	32	12	as	as	ADP
cana-4847	32	13	a	a	DET
cana-4847	32	14	result	result	NOUN
cana-4847	32	15	of	of	ADP
cana-4847	32	16	their	their	PRON
cana-4847	32	17	debilitating	debilitate	VERB
cana-4847	32	18	condition	condition	NOUN
cana-4847	32	19	.	.	PUNCT
cana-4847	33	1	however	however	ADV
cana-4847	33	2	,	,	PUNCT
cana-4847	33	3	the	the	DET
cana-4847	33	4	great	great	ADJ
cana-4847	33	5	minds	mind	NOUN
cana-4847	33	6	among	among	ADP
cana-4847	33	7	the	the	DET
cana-4847	33	8	scientists	scientist	NOUN
cana-4847	33	9	and	and	CCONJ
cana-4847	33	10	researchers	researcher	NOUN
cana-4847	33	11	keep	keep	VERB
cana-4847	33	12	striving	strive	VERB
cana-4847	33	13	day	day	NOUN
cana-4847	33	14	and	and	CCONJ
cana-4847	33	15	night	night	NOUN
cana-4847	33	16	for	for	ADP
cana-4847	33	17	some	some	DET
cana-4847	33	18	innovative	innovative	ADJ
cana-4847	33	19	diagnostic	diagnostic	ADJ
cana-4847	33	20	method	method	NOUN
cana-4847	33	21	and	and	CCONJ
cana-4847	33	22	treatment	treatment	NOUN
cana-4847	33	23	for	for	ADP
cana-4847	33	24	these	these	DET
cana-4847	33	25	diseases	disease	NOUN
cana-4847	33	26	.	.	PUNCT
cana-4847	34	1	deep	deep	ADJ
cana-4847	34	2	learning	learning	NOUN
cana-4847	34	3	and	and	CCONJ
cana-4847	34	4	machine	machine	NOUN
cana-4847	34	5	learning	learning	NOUN
cana-4847	34	6	breakthroughs	breakthrough	NOUN
cana-4847	34	7	:	:	PUNCT
cana-4847	34	8	the	the	DET
cana-4847	34	9	last	last	ADJ
cana-4847	34	10	years	year	NOUN
cana-4847	34	11	have	have	AUX
cana-4847	34	12	seen	see	VERB
cana-4847	34	13	spectacular	spectacular	ADJ
cana-4847	34	14	growth	growth	NOUN
cana-4847	34	15	in	in	ADP
cana-4847	34	16	the	the	DET
cana-4847	34	17	fields	field	NOUN
cana-4847	34	18	of	of	ADP
cana-4847	34	19	machine	machine	NOUN
cana-4847	34	20	learning	learning	NOUN
cana-4847	34	21	and	and	CCONJ
cana-4847	34	22	deep	deep	ADJ
cana-4847	34	23	learning	learning	NOUN
cana-4847	34	24	,	,	PUNCT
cana-4847	34	25	giving	give	VERB
cana-4847	34	26	tremendous	tremendous	ADJ
cana-4847	34	27	promise	promise	NOUN
cana-4847	34	28	in	in	ADP
cana-4847	34	29	this	this	DET
cana-4847	34	30	fight	fight	NOUN
cana-4847	34	31	against	against	ADP
cana-4847	34	32	skin	skin	NOUN
cana-4847	34	33	diseases	disease	NOUN
cana-4847	34	34	.	.	PUNCT
cana-4847	35	1	these	these	DET
cana-4847	35	2	advanced	advanced	ADJ
cana-4847	35	3	technologies	technology	NOUN
cana-4847	35	4	have	have	AUX
cana-4847	35	5	finally	finally	ADV
cana-4847	35	6	enabled	enable	VERB
cana-4847	35	7	researchers	researcher	NOUN
cana-4847	35	8	to	to	PART
cana-4847	35	9	construct	construct	VERB
cana-4847	35	10	the	the	DET
cana-4847	35	11	best	good	ADJ
cana-4847	35	12	models	model	NOUN
cana-4847	35	13	and	and	CCONJ
cana-4847	35	14	methods	method	NOUN
cana-4847	35	15	for	for	ADP
cana-4847	35	16	detecting	detect	VERB
cana-4847	35	17	and	and	CCONJ
cana-4847	35	18	diagnosing	diagnose	VERB
cana-4847	35	19	problems	problem	NOUN
cana-4847	35	20	with	with	ADP
cana-4847	35	21	skin	skin	NOUN
cana-4847	35	22	.	.	PUNCT
cana-4847	36	1	two	two	NUM
cana-4847	36	2	of	of	ADP
cana-4847	36	3	them	they	PRON
cana-4847	36	4	are	be	AUX
cana-4847	36	5	:	:	PUNCT
cana-4847	36	6	1	1	X
cana-4847	36	7	.	.	X
cana-4847	36	8	detection	detection	NOUN
cana-4847	36	9	of	of	ADP
cana-4847	36	10	psoriasis	psoriasis	NOUN
cana-4847	36	11	:	:	PUNCT
cana-4847	36	12	this	this	PRON
cana-4847	36	13	will	will	AUX
cana-4847	36	14	detect	detect	VERB
cana-4847	36	15	the	the	DET
cana-4847	36	16	presence	presence	NOUN
cana-4847	36	17	of	of	ADP
cana-4847	36	18	psoriasis	psoriasis	NOUN
cana-4847	36	19	in	in	ADP
cana-4847	36	20	patients	patient	NOUN
cana-4847	36	21	,	,	PUNCT
cana-4847	36	22	depending	depend	VERB
cana-4847	36	23	on	on	ADP
cana-4847	36	24	the	the	DET
cana-4847	36	25	characteristics	characteristic	NOUN
cana-4847	36	26	of	of	ADP
cana-4847	36	27	their	their	PRON
cana-4847	36	28	skin	skin	NOUN
cana-4847	36	29	color	color	NOUN
cana-4847	36	30	and	and	CCONJ
cana-4847	36	31	texture	texture	NOUN
cana-4847	36	32	.	.	PUNCT
cana-4847	37	1	the	the	DET
cana-4847	37	2	system	system	NOUN
cana-4847	37	3	has	have	AUX
cana-4847	37	4	achieved	achieve	VERB
cana-4847	37	5	shocking	shocking	ADJ
cana-4847	37	6	success	success	NOUN
cana-4847	37	7	rates	rate	NOUN
cana-4847	37	8	in	in	ADP
cana-4847	37	9	accuracy	accuracy	NOUN
cana-4847	37	10	,	,	PUNCT
cana-4847	37	11	thus	thus	ADV
cana-4847	37	12	bringing	bring	VERB
cana-4847	37	13	new	new	ADJ
cana-4847	37	14	hope	hope	NOUN
cana-4847	37	15	to	to	ADP
cana-4847	37	16	patients	patient	NOUN
cana-4847	37	17	suffering	suffer	VERB
cana-4847	37	18	from	from	ADP
cana-4847	37	19	this	this	DET
cana-4847	37	20	disabling	disable	VERB
cana-4847	37	21	disease	disease	NOUN
cana-4847	37	22	.	.	PUNCT
cana-4847	38	1	2	2	X
cana-4847	38	2	.	.	X
cana-4847	38	3	eczema	eczema	PROPN
cana-4847	38	4	detection	detection	NOUN
cana-4847	38	5	:	:	PUNCT
cana-4847	38	6	this	this	DET
cana-4847	38	7	model	model	NOUN
cana-4847	38	8	detects	detect	VERB
cana-4847	38	9	the	the	DET
cana-4847	38	10	size	size	NOUN
cana-4847	38	11	of	of	ADP
cana-4847	38	12	the	the	DET
cana-4847	38	13	affected	affected	ADJ
cana-4847	38	14	sites	site	NOUN
cana-4847	38	15	and	and	CCONJ
cana-4847	38	16	severity	severity	NOUN
cana-4847	38	17	of	of	ADP
cana-4847	38	18	eczema	eczema	NOUN
cana-4847	38	19	.	.	PUNCT
cana-4847	39	1	it	it	PRON
cana-4847	39	2	uses	use	VERB
cana-4847	39	3	the	the	DET
cana-4847	39	4	color	color	NOUN
cana-4847	39	5	and	and	CCONJ
cana-4847	39	6	texture	texture	ADJ
cana-4847	39	7	features	feature	NOUN
cana-4847	39	8	of	of	ADP
cana-4847	39	9	an	an	DET
cana-4847	39	10	image	image	NOUN
cana-4847	39	11	,	,	PUNCT
cana-4847	39	12	which	which	PRON
cana-4847	39	13	makes	make	VERB
cana-4847	39	14	it	it	PRON
cana-4847	39	15	display	display	VERB
cana-4847	39	16	the	the	DET
cana-4847	39	17	potential	potential	ADJ
cana-4847	39	18	power	power	NOUN
cana-4847	39	19	that	that	PRON
cana-4847	39	20	may	may	AUX
cana-4847	39	21	be	be	AUX
cana-4847	39	22	offered	offer	VERB
cana-4847	39	23	in	in	ADP
cana-4847	39	24	dermatological	dermatological	ADJ
cana-4847	39	25	analysis	analysis	NOUN
cana-4847	39	26	by	by	ADP
cana-4847	39	27	machine	machine	NOUN
cana-4847	39	28	learning	learning	NOUN
cana-4847	39	29	.	.	PUNCT
cana-4847	40	1	this	this	DET
cana-4847	40	2	research	research	NOUN
cana-4847	40	3	builds	build	VERB
cana-4847	40	4	on	on	ADP
cana-4847	40	5	earlier	early	ADJ
cana-4847	40	6	studies	study	NOUN
cana-4847	40	7	.	.	PUNCT
cana-4847	41	1	lowe	lowe	PROPN
cana-4847	41	2	et	et	PROPN
cana-4847	41	3	al	al	PROPN
cana-4847	41	4	.	.	PROPN
cana-4847	42	1	(	(	PUNCT
cana-4847	42	2	2014	2014	NUM
cana-4847	42	3	)	)	PUNCT
cana-4847	43	1	[	[	X
cana-4847	43	2	2	2	X
cana-4847	43	3	]	]	PUNCT
cana-4847	43	4	discussed	discuss	VERB
cana-4847	43	5	the	the	DET
cana-4847	43	6	immunological	immunological	ADJ
cana-4847	43	7	backgrounds	background	NOUN
cana-4847	43	8	of	of	ADP
cana-4847	43	9	skin	skin	NOUN
cana-4847	43	10	diseases	disease	NOUN
cana-4847	43	11	,	,	PUNCT
cana-4847	43	12	which	which	PRON
cana-4847	43	13	provide	provide	VERB
cana-4847	43	14	a	a	DET
cana-4847	43	15	knowledge	knowledge	NOUN
cana-4847	43	16	basis	basis	NOUN
cana-4847	43	17	for	for	ADP
cana-4847	43	18	molecular	molecular	ADJ
cana-4847	43	19	and	and	CCONJ
cana-4847	43	20	cellular	cellular	ADJ
cana-4847	43	21	structures	structure	NOUN
cana-4847	43	22	concerned	concern	VERB
cana-4847	43	23	in	in	ADP
cana-4847	43	24	image	image	NOUN
cana-4847	43	25	-	-	PUNCT
cana-4847	43	26	based	base	VERB
cana-4847	43	27	classification	classification	NOUN
cana-4847	43	28	.	.	PUNCT
cana-4847	44	1	feature	feature	NOUN
cana-4847	44	2	extraction	extraction	NOUN
cana-4847	44	3	,	,	PUNCT
cana-4847	44	4	as	as	ADP
cana-4847	44	5	al	al	PROPN
cana-4847	44	6	abbadi	abbadi	NOUN
cana-4847	44	7	et	et	PROPN
cana-4847	44	8	al	al	PROPN
cana-4847	44	9	.	.	PROPN
cana-4847	45	1	(	(	PUNCT
cana-4847	45	2	2010	2010	NUM
cana-4847	45	3	)	)	PUNCT
cana-4847	46	1	[	[	X
cana-4847	46	2	3	3	X
cana-4847	46	3	]	]	PUNCT
cana-4847	46	4	emphasized	emphasize	VERB
cana-4847	46	5	,	,	PUNCT
cana-4847	46	6	plays	play	VERB
cana-4847	46	7	an	an	DET
cana-4847	46	8	important	important	ADJ
cana-4847	46	9	role	role	NOUN
cana-4847	46	10	in	in	ADP
cana-4847	46	11	disease	disease	NOUN
cana-4847	46	12	detection	detection	NOUN
cana-4847	46	13	with	with	ADP
cana-4847	46	14	accuracy	accuracy	NOUN
cana-4847	46	15	.	.	PUNCT
cana-4847	47	1	it	it	PRON
cana-4847	47	2	aims	aim	VERB
cana-4847	47	3	to	to	PART
cana-4847	47	4	improve	improve	VERB
cana-4847	47	5	methods	method	NOUN
cana-4847	47	6	for	for	ADP
cana-4847	47	7	feature	feature	NOUN
cana-4847	47	8	extraction	extraction	NOUN
cana-4847	47	9	that	that	PRON
cana-4847	47	10	are	be	AUX
cana-4847	47	11	either	either	ADV
cana-4847	47	12	based	base	VERB
cana-4847	47	13	on	on	ADP
cana-4847	47	14	the	the	DET
cana-4847	47	15	texture	texture	NOUN
cana-4847	47	16	,	,	PUNCT
cana-4847	47	17	color	color	NOUN
cana-4847	47	18	histograms	histogram	NOUN
cana-4847	47	19	,	,	PUNCT
cana-4847	47	20	and	and	CCONJ
cana-4847	47	21	feature	feature	NOUN
cana-4847	47	22	maps	map	NOUN
cana-4847	47	23	through	through	ADP
cana-4847	47	24	deep	deep	ADJ
cana-4847	47	25	learning	learning	NOUN
cana-4847	47	26	that	that	PRON
cana-4847	47	27	can	can	AUX
cana-4847	47	28	help	help	VERB
cana-4847	47	29	boost	boost	VERB
cana-4847	47	30	model	model	NOUN
cana-4847	47	31	performance	performance	NOUN
cana-4847	47	32	maximally	maximally	ADV
cana-4847	47	33	.	.	PUNCT
cana-4847	48	1	alam	alam	PROPN
cana-4847	48	2	et	et	PROPN
cana-4847	48	3	al	al	PROPN
cana-4847	48	4	.	.	PROPN
cana-4847	49	1	(	(	PUNCT
cana-4847	49	2	2016	2016	NUM
cana-4847	49	3	)	)	PUNCT
cana-4847	50	1	[	[	X
cana-4847	50	2	4	4	X
cana-4847	50	3	]	]	PUNCT
cana-4847	50	4	proposed	propose	VERB
cana-4847	50	5	an	an	DET
cana-4847	50	6	eczema	eczema	NOUN
cana-4847	50	7	severity	severity	NOUN
cana-4847	50	8	measurement	measurement	NOUN
cana-4847	50	9	:	:	PUNCT
cana-4847	50	10	the	the	DET
cana-4847	50	11	potential	potential	NOUN
cana-4847	50	12	that	that	PRON
cana-4847	50	13	ai	ai	VERB
cana-4847	50	14	methods	method	NOUN
cana-4847	50	15	are	be	AUX
cana-4847	50	16	able	able	ADJ
cana-4847	50	17	to	to	PART
cana-4847	50	18	facilitate	facilitate	VERB
cana-4847	50	19	automatic	automatic	ADJ
cana-4847	50	20	assessment	assessment	NOUN
cana-4847	50	21	.	.	PUNCT
cana-4847	51	1	the	the	DET
cana-4847	51	2	work	work	NOUN
cana-4847	51	3	of	of	ADP
cana-4847	51	4	this	this	DET
cana-4847	51	5	study	study	NOUN
cana-4847	51	6	aims	aim	VERB
cana-4847	51	7	to	to	PART
cana-4847	51	8	generalize	generalize	VERB
cana-4847	51	9	this	this	DET
cana-4847	51	10	approach	approach	NOUN
cana-4847	51	11	in	in	ADP
cana-4847	51	12	the	the	DET
cana-4847	51	13	determination	determination	NOUN
cana-4847	51	14	of	of	ADP
cana-4847	51	15	the	the	DET
cana-4847	51	16	severity	severity	NOUN
cana-4847	51	17	level	level	NOUN
cana-4847	51	18	of	of	ADP
cana-4847	51	19	a	a	DET
cana-4847	51	20	set	set	NOUN
cana-4847	51	21	of	of	ADP
cana-4847	51	22	communications	communication	NOUN
cana-4847	51	23	on	on	ADP
cana-4847	51	24	applied	apply	VERB
cana-4847	51	25	nonlinear	nonlinear	ADJ
cana-4847	51	26	analysis	analysis	NOUN
cana-4847	51	27	issn	issn	NOUN
cana-4847	51	28	:	:	PUNCT
cana-4847	51	29	1074	1074	NUM
cana-4847	51	30	-	-	PUNCT
cana-4847	51	31	133x	133x	NUM
cana-4847	51	32	vol	vol	VERB
cana-4847	51	33	32	32	NUM
cana-4847	51	34	no	no	NOUN
cana-4847	51	35	.	.	PUNCT
cana-4847	52	1	10s	10	NOUN
cana-4847	52	2	(	(	PUNCT
cana-4847	52	3	2025	2025	NUM
cana-4847	52	4	)	)	PUNCT
cana-4847	52	5	569	569	NUM
cana-4847	52	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	52	7	dermatological	dermatological	ADJ
cana-4847	52	8	conditions	condition	NOUN
cana-4847	52	9	like	like	ADP
cana-4847	52	10	eczema	eczema	NOUN
cana-4847	52	11	,	,	PUNCT
cana-4847	52	12	psoriasis	psoriasis	NOUN
cana-4847	52	13	,	,	PUNCT
cana-4847	52	14	and	and	CCONJ
cana-4847	52	15	acne	acne	VERB
cana-4847	52	16	through	through	ADP
cana-4847	52	17	image	image	NOUN
cana-4847	52	18	processing	processing	NOUN
cana-4847	52	19	and	and	CCONJ
cana-4847	52	20	machine	machine	NOUN
cana-4847	52	21	learning	learning	NOUN
cana-4847	52	22	.	.	PUNCT
cana-4847	53	1	detection	detection	NOUN
cana-4847	53	2	of	of	ADP
cana-4847	53	3	skin	skin	NOUN
cana-4847	53	4	diseases	disease	NOUN
cana-4847	53	5	involves	involve	VERB
cana-4847	53	6	some	some	PRON
cana-4847	53	7	of	of	ADP
cana-4847	53	8	the	the	DET
cana-4847	53	9	biggest	big	ADJ
cana-4847	53	10	challenges	challenge	NOUN
cana-4847	53	11	such	such	ADJ
cana-4847	53	12	as	as	ADP
cana-4847	53	13	the	the	DET
cana-4847	53	14	performance	performance	NOUN
cana-4847	53	15	maximization	maximization	NOUN
cana-4847	53	16	of	of	ADP
cana-4847	53	17	algorithms	algorithm	NOUN
cana-4847	53	18	in	in	ADP
cana-4847	53	19	handling	handle	VERB
cana-4847	53	20	large	large	ADJ
cana-4847	53	21	heterogeneous	heterogeneous	ADJ
cana-4847	53	22	data	datum	NOUN
cana-4847	53	23	.	.	PUNCT
cana-4847	54	1	as	as	SCONJ
cana-4847	54	2	set	set	VERB
cana-4847	54	3	out	out	ADP
cana-4847	54	4	by	by	ADP
cana-4847	54	5	khan	khan	PROPN
cana-4847	54	6	et	et	PROPN
cana-4847	54	7	al	al	PROPN
cana-4847	54	8	.	.	PROPN
cana-4847	55	1	(	(	PUNCT
cana-4847	55	2	2020	2020	NUM
cana-4847	55	3	)	)	PUNCT
cana-4847	56	1	[	[	X
cana-4847	56	2	5	5	NUM
cana-4847	56	3	]	]	PUNCT
cana-4847	56	4	,	,	PUNCT
cana-4847	56	5	comparative	comparative	ADJ
cana-4847	56	6	study	study	NOUN
cana-4847	56	7	of	of	ADP
cana-4847	56	8	machine	machine	NOUN
cana-4847	56	9	learning	learn	VERB
cana-4847	56	10	classifiers	classifier	NOUN
cana-4847	56	11	in	in	ADP
cana-4847	56	12	medical	medical	ADJ
cana-4847	56	13	data	datum	NOUN
cana-4847	56	14	is	be	AUX
cana-4847	56	15	key	key	ADJ
cana-4847	56	16	to	to	ADP
cana-4847	56	17	the	the	DET
cana-4847	56	18	building	building	NOUN
cana-4847	56	19	of	of	ADP
cana-4847	56	20	robust	robust	ADJ
cana-4847	56	21	models	model	NOUN
cana-4847	56	22	for	for	ADP
cana-4847	56	23	generalizability	generalizability	NOUN
cana-4847	56	24	across	across	ADP
cana-4847	56	25	different	different	ADJ
cana-4847	56	26	populations	population	NOUN
cana-4847	56	27	and	and	CCONJ
cana-4847	56	28	large	large	ADJ
cana-4847	56	29	databases	database	NOUN
cana-4847	56	30	of	of	ADP
cana-4847	56	31	images	image	NOUN
cana-4847	56	32	.	.	PUNCT
cana-4847	57	1	this	this	DET
cana-4847	57	2	study	study	NOUN
cana-4847	57	3	overcomes	overcome	VERB
cana-4847	57	4	this	this	DET
cana-4847	57	5	limitation	limitation	NOUN
cana-4847	57	6	by	by	ADP
cana-4847	57	7	capitalizing	capitalize	VERB
cana-4847	57	8	on	on	ADP
cana-4847	57	9	the	the	DET
cana-4847	57	10	strength	strength	NOUN
cana-4847	57	11	of	of	ADP
cana-4847	57	12	cnns	cnn	NOUN
cana-4847	57	13	,	,	PUNCT
cana-4847	57	14	employing	employ	VERB
cana-4847	57	15	the	the	DET
cana-4847	57	16	pre	pre	ADJ
cana-4847	57	17	-	-	ADJ
cana-4847	57	18	trained	train	VERB
cana-4847	57	19	resnet50	resnet50	NOUN
cana-4847	57	20	model	model	NOUN
cana-4847	57	21	.	.	PUNCT
cana-4847	58	1	in	in	ADP
cana-4847	58	2	this	this	DET
cana-4847	58	3	work	work	NOUN
cana-4847	58	4	[	[	X
cana-4847	58	5	7	7	NUM
cana-4847	58	6	]	]	PUNCT
cana-4847	58	7	,	,	PUNCT
cana-4847	58	8	a	a	DET
cana-4847	58	9	study	study	NOUN
cana-4847	58	10	was	be	AUX
cana-4847	58	11	conducted	conduct	VERB
cana-4847	58	12	into	into	ADP
cana-4847	58	13	eczema	eczema	NOUN
cana-4847	58	14	detection	detection	NOUN
cana-4847	58	15	and	and	CCONJ
cana-4847	58	16	recognition	recognition	NOUN
cana-4847	58	17	in	in	ADP
cana-4847	58	18	cloud	cloud	NOUN
cana-4847	58	19	computing	compute	VERB
cana-4847	58	20	environment	environment	NOUN
cana-4847	58	21	with	with	ADP
cana-4847	58	22	focus	focus	NOUN
cana-4847	58	23	on	on	ADP
cana-4847	58	24	scalability	scalability	NOUN
cana-4847	58	25	of	of	ADP
cana-4847	58	26	medical	medical	ADJ
cana-4847	58	27	application	application	NOUN
cana-4847	58	28	.	.	PUNCT
cana-4847	59	1	this	this	DET
cana-4847	59	2	study,[8	study,[8	NOUN
cana-4847	59	3	]	]	PUNCT
cana-4847	59	4	also	also	ADV
cana-4847	59	5	utilize	utilize	VERB
cana-4847	59	6	transfer	transfer	NOUN
cana-4847	59	7	learning	learning	NOUN
cana-4847	59	8	technique	technique	NOUN
cana-4847	59	9	in	in	ADP
cana-4847	59	10	diagnosing	diagnose	VERB
cana-4847	59	11	skin	skin	NOUN
cana-4847	59	12	diseases	disease	NOUN
cana-4847	59	13	from	from	ADP
cana-4847	59	14	images	image	NOUN
cana-4847	59	15	exhibiting	exhibit	VERB
cana-4847	59	16	the	the	DET
cana-4847	59	17	relevance	relevance	NOUN
cana-4847	59	18	of	of	ADP
cana-4847	59	19	pretrained	pretraine	VERB
cana-4847	59	20	models	model	NOUN
cana-4847	59	21	to	to	ADP
cana-4847	59	22	dermatological	dermatological	ADJ
cana-4847	59	23	purposes	purpose	NOUN
cana-4847	59	24	.	.	PUNCT
cana-4847	60	1	the	the	DET
cana-4847	60	2	authors	author	NOUN
cana-4847	60	3	[	[	X
cana-4847	60	4	9	9	NUM
cana-4847	60	5	]	]	PUNCT
cana-4847	60	6	use	use	NOUN
cana-4847	60	7	machine	machine	NOUN
cana-4847	60	8	learning	learn	VERB
cana-4847	60	9	algorithms	algorithm	NOUN
cana-4847	60	10	for	for	ADP
cana-4847	60	11	skin	skin	NOUN
cana-4847	60	12	disease	disease	NOUN
cana-4847	60	13	detection	detection	NOUN
cana-4847	60	14	,	,	PUNCT
cana-4847	60	15	to	to	PART
cana-4847	60	16	illuminate	illuminate	VERB
cana-4847	60	17	improvements	improvement	NOUN
cana-4847	60	18	in	in	ADP
cana-4847	60	19	algorithmic	algorithmic	ADJ
cana-4847	60	20	images	image	NOUN
cana-4847	60	21	in	in	ADP
cana-4847	60	22	classification	classification	NOUN
cana-4847	60	23	.	.	PUNCT
cana-4847	61	1	this	this	DET
cana-4847	61	2	research	research	NOUN
cana-4847	61	3	[	[	X
cana-4847	61	4	10	10	NUM
cana-4847	61	5	]	]	PUNCT
cana-4847	61	6	provide	provide	VERB
cana-4847	61	7	the	the	DET
cana-4847	61	8	use	use	NOUN
cana-4847	61	9	of	of	ADP
cana-4847	61	10	cnn	cnn	PROPN
cana-4847	61	11	skin	skin	NOUN
cana-4847	61	12	disease	disease	NOUN
cana-4847	61	13	detection	detection	NOUN
cana-4847	61	14	with	with	ADP
cana-4847	61	15	the	the	DET
cana-4847	61	16	help	help	NOUN
cana-4847	61	17	of	of	ADP
cana-4847	61	18	deep	deep	ADJ
cana-4847	61	19	learning	learning	NOUN
cana-4847	61	20	in	in	ADP
cana-4847	61	21	the	the	DET
cana-4847	61	22	medical	medical	ADJ
cana-4847	61	23	imaging	imaging	NOUN
cana-4847	61	24	domain	domain	NOUN
cana-4847	61	25	by	by	ADP
cana-4847	61	26	using	use	VERB
cana-4847	61	27	int	int	NOUN
cana-4847	61	28	.	.	PUNCT
cana-4847	62	1	j.	j.	PROPN
cana-4847	62	2	comput	comput	PROPN
cana-4847	62	3	.	.	PUNCT
cana-4847	63	1	dig	dig	PROPN
cana-4847	63	2	.	.	PUNCT
cana-4847	64	1	syst	syst	PROPN
cana-4847	64	2	.	.	PUNCT
cana-4847	65	1	(	(	PUNCT
cana-4847	65	2	ijcds	ijcds	PROPN
cana-4847	65	3	)	)	PUNCT
cana-4847	65	4	9	9	NUM
cana-4847	65	5	(	(	PUNCT
cana-4847	65	6	2021	2021	NUM
cana-4847	65	7	)	)	PUNCT
cana-4847	66	1	[	[	X
cana-4847	66	2	12	12	NUM
cana-4847	66	3	]	]	PUNCT
cana-4847	66	4	.	.	PUNCT
cana-4847	67	1	this	this	DET
cana-4847	67	2	survey	survey	NOUN
cana-4847	67	3	forms	form	VERB
cana-4847	67	4	the	the	DET
cana-4847	67	5	basis	basis	NOUN
cana-4847	67	6	to	to	PART
cana-4847	67	7	get	get	VERB
cana-4847	67	8	an	an	DET
cana-4847	67	9	appreciation	appreciation	NOUN
cana-4847	67	10	of	of	ADP
cana-4847	67	11	the	the	DET
cana-4847	67	12	existing	exist	VERB
cana-4847	67	13	paradigms	paradigm	NOUN
cana-4847	67	14	in	in	ADP
cana-4847	67	15	skin	skin	NOUN
cana-4847	67	16	disease	disease	NOUN
cana-4847	67	17	diagnosis	diagnosis	NOUN
cana-4847	67	18	and	and	CCONJ
cana-4847	67	19	classification	classification	NOUN
cana-4847	67	20	techniques	technique	NOUN
cana-4847	67	21	using	use	VERB
cana-4847	67	22	machine	machine	NOUN
cana-4847	67	23	learning	learning	NOUN
cana-4847	67	24	along	along	ADP
cana-4847	67	25	with	with	ADP
cana-4847	67	26	image	image	NOUN
cana-4847	67	27	processing	processing	NOUN
cana-4847	67	28	and	and	CCONJ
cana-4847	67	29	computational	computational	ADJ
cana-4847	67	30	techniques	technique	NOUN
cana-4847	67	31	.	.	PUNCT
cana-4847	68	1	additionally	additionally	ADV
cana-4847	68	2	,	,	PUNCT
cana-4847	68	3	diagnostic	diagnostic	ADJ
cana-4847	68	4	software	software	NOUN
cana-4847	68	5	availability	availability	NOUN
cana-4847	68	6	is	be	AUX
cana-4847	68	7	also	also	ADV
cana-4847	68	8	necessary	necessary	ADJ
cana-4847	68	9	.	.	PUNCT
cana-4847	69	1	shawkat	shawkat	PROPN
cana-4847	69	2	abdulbaki	abdulbaki	VERB
cana-4847	69	3	et	et	PROPN
cana-4847	69	4	al	al	PROPN
cana-4847	69	5	.	.	PROPN
cana-4847	70	1	(	(	PUNCT
cana-4847	70	2	2019	2019	NUM
cana-4847	70	3	)	)	PUNCT
cana-4847	71	1	[	[	X
cana-4847	71	2	6	6	NUM
cana-4847	71	3	]	]	PUNCT
cana-4847	71	4	emphasized	emphasize	VERB
cana-4847	71	5	the	the	DET
cana-4847	71	6	cloud	cloud	NOUN
cana-4847	71	7	computing	computing	NOUN
cana-4847	71	8	-	-	PUNCT
cana-4847	71	9	based	base	VERB
cana-4847	71	10	detection	detection	NOUN
cana-4847	71	11	of	of	ADP
cana-4847	71	12	eczema	eczema	NOUN
cana-4847	71	13	using	use	VERB
cana-4847	71	14	web	web	NOUN
cana-4847	71	15	-	-	PUNCT
cana-4847	71	16	based	base	VERB
cana-4847	71	17	applications	application	NOUN
cana-4847	71	18	.	.	PUNCT
cana-4847	72	1	the	the	DET
cana-4847	72	2	present	present	ADJ
cana-4847	72	3	work	work	NOUN
cana-4847	72	4	is	be	AUX
cana-4847	72	5	aimed	aim	VERB
cana-4847	72	6	at	at	ADP
cana-4847	72	7	designing	design	VERB
cana-4847	72	8	web	web	NOUN
cana-4847	72	9	-	-	PUNCT
cana-4847	72	10	based	base	VERB
cana-4847	72	11	applications	application	NOUN
cana-4847	72	12	for	for	ADP
cana-4847	72	13	the	the	DET
cana-4847	72	14	classification	classification	NOUN
cana-4847	72	15	of	of	ADP
cana-4847	72	16	skin	skin	NOUN
cana-4847	72	17	diseases	disease	NOUN
cana-4847	72	18	so	so	SCONJ
cana-4847	72	19	that	that	SCONJ
cana-4847	72	20	resource	resource	NOUN
cana-4847	72	21	-	-	PUNCT
cana-4847	72	22	constrained	constrain	VERB
cana-4847	72	23	classification	classification	NOUN
cana-4847	72	24	becomes	become	VERB
cana-4847	72	25	achievable	achievable	ADJ
cana-4847	72	26	for	for	ADP
cana-4847	72	27	clinicians	clinician	NOUN
cana-4847	72	28	and	and	CCONJ
cana-4847	72	29	researchers	researcher	NOUN
cana-4847	72	30	.	.	PUNCT
cana-4847	73	1	a	a	DET
cana-4847	73	2	very	very	ADV
cana-4847	73	3	promising	promising	ADJ
cana-4847	73	4	approach	approach	NOUN
cana-4847	73	5	towards	towards	ADP
cana-4847	73	6	exploitation	exploitation	NOUN
cana-4847	73	7	of	of	ADP
cana-4847	73	8	pre	pre	ADJ
cana-4847	73	9	-	-	ADJ
cana-4847	73	10	trained	train	VERB
cana-4847	73	11	cnn	cnn	PROPN
cana-4847	73	12	models	model	NOUN
cana-4847	73	13	in	in	ADP
cana-4847	73	14	medical	medical	ADJ
cana-4847	73	15	image	image	NOUN
cana-4847	73	16	segmentation	segmentation	NOUN
cana-4847	73	17	,	,	PUNCT
cana-4847	73	18	classification	classification	NOUN
cana-4847	73	19	,	,	PUNCT
cana-4847	73	20	and	and	CCONJ
cana-4847	73	21	even	even	ADV
cana-4847	73	22	decision	decision	NOUN
cana-4847	73	23	support	support	NOUN
cana-4847	73	24	,	,	PUNCT
cana-4847	73	25	heart	heart	NOUN
cana-4847	73	26	disease	disease	NOUN
cana-4847	73	27	prediction	prediction	NOUN
cana-4847	73	28	using	use	VERB
cana-4847	73	29	cnn	cnn	PROPN
cana-4847	73	30	algorithm	algorithm	NOUN
cana-4847	73	31	.	.	PUNCT
cana-4847	74	1	sn	sn	PROPN
cana-4847	74	2	comput	comput	PROPN
cana-4847	74	3	.	.	PUNCT
cana-4847	75	1	sci	sci	PROPN
cana-4847	75	2	.	.	PROPN
cana-4847	76	1	1	1	NUM
cana-4847	76	2	,	,	PUNCT
cana-4847	76	3	170	170	NUM
cana-4847	76	4	(	(	PUNCT
cana-4847	76	5	2020	2020	NUM
cana-4847	76	6	)	)	PUNCT
cana-4847	77	1	[	[	X
cana-4847	77	2	11	11	NUM
cana-4847	77	3	]	]	PUNCT
cana-4847	77	4	it	it	PRON
cana-4847	77	5	employs	employ	VERB
cana-4847	77	6	fine	fine	ADJ
cana-4847	77	7	-	-	PUNCT
cana-4847	77	8	tuning	tuning	NOUN
cana-4847	77	9	of	of	ADP
cana-4847	77	10	the	the	DET
cana-4847	77	11	pre	pre	ADJ
cana-4847	77	12	-	-	ADJ
cana-4847	77	13	trained	train	VERB
cana-4847	77	14	resnet50	resnet50	NOUN
cana-4847	77	15	model	model	NOUN
cana-4847	77	16	for	for	ADP
cana-4847	77	17	our	our	PRON
cana-4847	77	18	skin	skin	NOUN
cana-4847	77	19	disease	disease	NOUN
cana-4847	77	20	.	.	PUNCT
cana-4847	78	1	3	3	X
cana-4847	78	2	.	.	X
cana-4847	78	3	methodology	methodology	NOUN
cana-4847	78	4	the	the	DET
cana-4847	78	5	diagnosis	diagnosis	NOUN
cana-4847	78	6	of	of	ADP
cana-4847	78	7	the	the	DET
cana-4847	78	8	skin	skin	NOUN
cana-4847	78	9	disease	disease	NOUN
cana-4847	78	10	process	process	NOUN
cana-4847	78	11	as	as	ADV
cana-4847	78	12	well	well	ADV
cana-4847	78	13	as	as	ADP
cana-4847	78	14	various	various	ADJ
cana-4847	78	15	cnn	cnn	PROPN
cana-4847	78	16	models	model	NOUN
cana-4847	78	17	is	be	AUX
cana-4847	78	18	elaborated	elaborate	VERB
cana-4847	78	19	under	under	ADP
cana-4847	78	20	proper	proper	ADJ
cana-4847	78	21	subheadings	subheading	NOUN
cana-4847	78	22	.	.	PUNCT
cana-4847	79	1	figure1	figure1	PROPN
cana-4847	79	2	depicts	depict	VERB
cana-4847	79	3	the	the	DET
cana-4847	79	4	details	detail	NOUN
cana-4847	79	5	of	of	ADP
cana-4847	79	6	working	work	VERB
cana-4847	79	7	procedure	procedure	NOUN
cana-4847	79	8	.	.	PUNCT
cana-4847	80	1	the	the	DET
cana-4847	80	2	working	work	VERB
cana-4847	80	3	procedure	procedure	NOUN
cana-4847	80	4	starts	start	VERB
cana-4847	80	5	from	from	ADP
cana-4847	80	6	data	datum	NOUN
cana-4847	80	7	collection	collection	NOUN
cana-4847	80	8	and	and	CCONJ
cana-4847	80	9	followed	follow	VERB
cana-4847	80	10	by	by	ADP
cana-4847	80	11	classification	classification	NOUN
cana-4847	80	12	of	of	ADP
cana-4847	80	13	the	the	DET
cana-4847	80	14	collected	collect	VERB
cana-4847	80	15	images	image	NOUN
cana-4847	80	16	.	.	PUNCT
cana-4847	81	1	removal	removal	NOUN
cana-4847	81	2	of	of	ADP
cana-4847	81	3	noisy	noisy	ADJ
cana-4847	81	4	images	image	NOUN
cana-4847	81	5	and	and	CCONJ
cana-4847	81	6	image	image	NOUN
cana-4847	81	7	resizing	resizing	NOUN
cana-4847	81	8	performed	perform	VERB
cana-4847	81	9	.	.	PUNCT
cana-4847	82	1	image	image	NOUN
cana-4847	82	2	augmentation	augmentation	NOUN
cana-4847	82	3	are	be	AUX
cana-4847	82	4	performed	perform	VERB
cana-4847	82	5	by	by	ADP
cana-4847	82	6	scaling	scale	VERB
cana-4847	82	7	image	image	NOUN
cana-4847	82	8	for	for	ADP
cana-4847	82	9	dataset	dataset	ADJ
cana-4847	82	10	expansion	expansion	NOUN
cana-4847	82	11	then	then	ADV
cana-4847	82	12	performed	perform	VERB
cana-4847	82	13	2	2	NUM
cana-4847	82	14	folding	folding	NOUN
cana-4847	82	15	.	.	PUNCT
cana-4847	83	1	then	then	ADV
cana-4847	83	2	the	the	DET
cana-4847	83	3	features	feature	NOUN
cana-4847	83	4	are	be	AUX
cana-4847	83	5	extracted	extract	VERB
cana-4847	83	6	using	use	VERB
cana-4847	83	7	pretrained	pretraine	VERB
cana-4847	83	8	cnn	cnn	PROPN
cana-4847	83	9	model	model	PROPN
cana-4847	83	10	resnet50	resnet50	PROPN
cana-4847	83	11	and	and	CCONJ
cana-4847	83	12	ultimately	ultimately	ADV
cana-4847	83	13	classification	classification	NOUN
cana-4847	83	14	is	be	AUX
cana-4847	83	15	done	do	VERB
cana-4847	83	16	and	and	CCONJ
cana-4847	83	17	achieved	achieve	VERB
cana-4847	83	18	better	well	ADJ
cana-4847	83	19	accuracy	accuracy	NOUN
cana-4847	83	20	.	.	PUNCT
cana-4847	84	1	3.1	3.1	NUM
cana-4847	84	2	.	.	PUNCT
cana-4847	84	3	dataset	dataset	NOUN
cana-4847	84	4	collection	collection	NOUN
cana-4847	84	5	our	our	PRON
cana-4847	84	6	skin	skin	NOUN
cana-4847	84	7	is	be	AUX
cana-4847	84	8	our	our	PRON
cana-4847	84	9	biggest	big	ADJ
cana-4847	84	10	and	and	CCONJ
cana-4847	84	11	most	most	ADV
cana-4847	84	12	apparent	apparent	ADJ
cana-4847	84	13	organ	organ	NOUN
cana-4847	84	14	it	it	PRON
cana-4847	84	15	is	be	AUX
cana-4847	84	16	an	an	DET
cana-4847	84	17	insulating	insulate	VERB
cana-4847	84	18	barrier	barrier	NOUN
cana-4847	84	19	to	to	ADP
cana-4847	84	20	all	all	DET
cana-4847	84	21	those	those	DET
cana-4847	84	22	environmental	environmental	ADJ
cana-4847	84	23	influences	influence	NOUN
cana-4847	84	24	around	around	ADP
cana-4847	84	25	us	we	PRON
cana-4847	84	26	and	and	CCONJ
cana-4847	84	27	at	at	ADP
cana-4847	84	28	the	the	DET
cana-4847	84	29	same	same	ADJ
cana-4847	84	30	time	time	NOUN
cana-4847	84	31	is	be	AUX
cana-4847	84	32	an	an	DET
cana-4847	84	33	integrated	integrate	VERB
cana-4847	84	34	component	component	NOUN
cana-4847	84	35	of	of	ADP
cana-4847	84	36	our	our	PRON
cana-4847	84	37	health	health	NOUN
cana-4847	84	38	and	and	CCONJ
cana-4847	84	39	hygiene	hygiene	NOUN
cana-4847	84	40	as	as	ADP
cana-4847	84	41	a	a	DET
cana-4847	84	42	whole	whole	NOUN
cana-4847	84	43	.	.	PUNCT
cana-4847	85	1	on	on	ADP
cana-4847	85	2	the	the	DET
cana-4847	85	3	other	other	ADJ
cana-4847	85	4	hand	hand	NOUN
cana-4847	85	5	,	,	PUNCT
cana-4847	85	6	it	it	PRON
cana-4847	85	7	is	be	AUX
cana-4847	85	8	appalling	appalling	ADJ
cana-4847	85	9	that	that	SCONJ
cana-4847	85	10	more	more	ADJ
cana-4847	85	11	than	than	ADP
cana-4847	85	12	900	900	NUM
cana-4847	85	13	million	million	NUM
cana-4847	85	14	people	people	NOUN
cana-4847	85	15	in	in	ADP
cana-4847	85	16	this	this	DET
cana-4847	85	17	world	world	NOUN
cana-4847	85	18	suffer	suffer	VERB
cana-4847	85	19	from	from	ADP
cana-4847	85	20	some	some	DET
cana-4847	85	21	form	form	NOUN
cana-4847	85	22	of	of	ADP
cana-4847	85	23	skin	skin	NOUN
cana-4847	85	24	disease	disease	NOUN
cana-4847	85	25	from	from	ADP
cana-4847	85	26	a	a	DET
cana-4847	85	27	small	small	ADJ
cana-4847	85	28	,	,	PUNCT
cana-4847	85	29	non	non	ADJ
cana-4847	85	30	-	-	ADJ
cana-4847	85	31	significant	significant	ADJ
cana-4847	85	32	irritation	irritation	NOUN
cana-4847	85	33	to	to	ADP
cana-4847	85	34	death	death	NOUN
cana-4847	85	35	-	-	PUNCT
cana-4847	85	36	dealing	deal	VERB
cana-4847	85	37	forms	form	NOUN
cana-4847	85	38	.	.	PUNCT
cana-4847	86	1	effects	effect	NOUN
cana-4847	86	2	of	of	ADP
cana-4847	86	3	skin	skin	NOUN
cana-4847	86	4	diseases	disease	NOUN
cana-4847	86	5	in	in	ADP
cana-4847	86	6	everyday	everyday	ADJ
cana-4847	86	7	life	life	NOUN
cana-4847	86	8	communications	communication	NOUN
cana-4847	86	9	on	on	ADP
cana-4847	86	10	applied	apply	VERB
cana-4847	86	11	nonlinear	nonlinear	ADJ
cana-4847	86	12	analysis	analysis	NOUN
cana-4847	86	13	issn	issn	NOUN
cana-4847	86	14	:	:	PUNCT
cana-4847	86	15	1074	1074	NUM
cana-4847	86	16	-	-	PUNCT
cana-4847	86	17	133x	133x	NUM
cana-4847	86	18	vol	vol	VERB
cana-4847	86	19	32	32	NUM
cana-4847	86	20	no	no	NOUN
cana-4847	86	21	.	.	PUNCT
cana-4847	87	1	10s	10	NOUN
cana-4847	87	2	(	(	PUNCT
cana-4847	87	3	2025	2025	NUM
cana-4847	87	4	)	)	PUNCT
cana-4847	87	5	570	570	NUM
cana-4847	87	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	87	7	diseases	disease	NOUN
cana-4847	87	8	that	that	PRON
cana-4847	87	9	affect	affect	VERB
cana-4847	87	10	the	the	DET
cana-4847	87	11	skin	skin	NOUN
cana-4847	87	12	significantly	significantly	ADV
cana-4847	87	13	restrain	restrain	VERB
cana-4847	87	14	most	most	ADJ
cana-4847	87	15	people	people	NOUN
cana-4847	87	16	from	from	ADP
cana-4847	87	17	going	go	VERB
cana-4847	87	18	about	about	ADP
cana-4847	87	19	daily	daily	ADJ
cana-4847	87	20	life	life	NOUN
cana-4847	87	21	,	,	PUNCT
cana-4847	87	22	causing	cause	VERB
cana-4847	87	23	them	they	PRON
cana-4847	87	24	discomfort	discomfort	ADJ
cana-4847	87	25	and	and	CCONJ
cana-4847	87	26	cause	cause	VERB
cana-4847	87	27	emotional	emotional	ADJ
cana-4847	87	28	distress	distress	NOUN
cana-4847	87	29	as	as	ADV
cana-4847	87	30	well	well	ADV
cana-4847	87	31	as	as	ADP
cana-4847	87	32	social	social	ADJ
cana-4847	87	33	humiliation	humiliation	NOUN
cana-4847	87	34	.	.	PUNCT
cana-4847	88	1	some	some	PRON
cana-4847	88	2	of	of	ADP
cana-4847	88	3	the	the	DET
cana-4847	88	4	most	most	ADV
cana-4847	88	5	common	common	ADJ
cana-4847	88	6	diseases	disease	NOUN
cana-4847	88	7	that	that	PRON
cana-4847	88	8	infect	infect	VERB
cana-4847	88	9	skin	skin	NOUN
cana-4847	88	10	are	be	AUX
cana-4847	88	11	eczema	eczema	NOUN
cana-4847	88	12	and	and	CCONJ
cana-4847	88	13	psoriasis	psoriasis	NOUN
cana-4847	88	14	.	.	PUNCT
cana-4847	89	1	eczema	eczema	PROPN
cana-4847	89	2	is	be	AUX
cana-4847	89	3	atopic	atopic	NOUN
cana-4847	89	4	dermatitis	dermatitis	NOUN
cana-4847	89	5	,	,	PUNCT
cana-4847	89	6	or	or	CCONJ
cana-4847	89	7	inflammation	inflammation	NOUN
cana-4847	89	8	of	of	ADP
cana-4847	89	9	the	the	DET
cana-4847	89	10	skin	skin	NOUN
cana-4847	89	11	caused	cause	VERB
cana-4847	89	12	by	by	ADP
cana-4847	89	13	dry	dry	ADJ
cana-4847	89	14	,	,	PUNCT
cana-4847	89	15	scaly	scaly	NOUN
cana-4847	89	16	,	,	PUNCT
cana-4847	89	17	and	and	CCONJ
cana-4847	89	18	itchy	itchy	ADJ
cana-4847	89	19	skin	skin	NOUN
cana-4847	89	20	.	.	PUNCT
cana-4847	90	1	psoriasis	psoriasis	NOUN
cana-4847	90	2	,	,	PUNCT
cana-4847	90	3	on	on	ADP
cana-4847	90	4	the	the	DET
cana-4847	90	5	other	other	ADJ
cana-4847	90	6	hand	hand	NOUN
cana-4847	90	7	,	,	PUNCT
cana-4847	90	8	is	be	AUX
cana-4847	90	9	an	an	DET
cana-4847	90	10	immune	immune	ADJ
cana-4847	90	11	system	system	NOUN
cana-4847	90	12	-	-	PUNCT
cana-4847	90	13	mediated	mediate	VERB
cana-4847	90	14	disease	disease	NOUN
cana-4847	90	15	where	where	SCONJ
cana-4847	90	16	there	there	PRON
cana-4847	90	17	is	be	VERB
cana-4847	90	18	creation	creation	NOUN
cana-4847	90	19	of	of	ADP
cana-4847	90	20	red	red	ADJ
cana-4847	90	21	scaly	scaly	NOUN
cana-4847	90	22	patchy	patchy	ADJ
cana-4847	90	23	areas	area	NOUN
cana-4847	90	24	of	of	ADP
cana-4847	90	25	the	the	DET
cana-4847	90	26	skin	skin	NOUN
cana-4847	90	27	.	.	PUNCT
cana-4847	91	1	collection	collection	NOUN
cana-4847	91	2	and	and	CCONJ
cana-4847	91	3	preparation	preparation	NOUN
cana-4847	91	4	of	of	ADP
cana-4847	91	5	dataset	dataset	NOUN
cana-4847	91	6	downloaded	download	VERB
cana-4847	91	7	a	a	DET
cana-4847	91	8	complete	complete	ADJ
cana-4847	91	9	dataset	dataset	NOUN
cana-4847	91	10	of	of	ADP
cana-4847	91	11	images	image	NOUN
cana-4847	91	12	from	from	ADP
cana-4847	91	13	trusted	trusted	ADJ
cana-4847	91	14	sources	source	NOUN
cana-4847	91	15	like	like	ADP
cana-4847	91	16	dermnet	dermnet	NOUN
cana-4847	91	17	nz[14	nz[14	PROPN
cana-4847	91	18	]	]	PUNCT
cana-4847	91	19	,	,	PUNCT
cana-4847	91	20	dermnet	dermnet	NOUN
cana-4847	91	21	skin	skin	NOUN
cana-4847	91	22	disease	disease	NOUN
cana-4847	91	23	atlas[15	atlas[15	NOUN
cana-4847	91	24	]	]	PUNCT
cana-4847	91	25	,	,	PUNCT
cana-4847	91	26	and	and	CCONJ
cana-4847	91	27	kaggle	kaggle	VERB
cana-4847	91	28	to	to	PART
cana-4847	91	29	better	well	ADV
cana-4847	91	30	understand	understand	VERB
cana-4847	91	31	and	and	CCONJ
cana-4847	91	32	diagnose	diagnose	VERB
cana-4847	91	33	the	the	DET
cana-4847	91	34	diseases	disease	NOUN
cana-4847	91	35	.	.	PUNCT
cana-4847	92	1	noise	noise	NOUN
cana-4847	92	2	and	and	CCONJ
cana-4847	92	3	low	low	ADJ
cana-4847	92	4	contrast	contrast	NOUN
cana-4847	92	5	images	image	NOUN
cana-4847	92	6	are	be	AUX
cana-4847	92	7	filtered	filter	VERB
cana-4847	92	8	out	out	ADP
cana-4847	92	9	by	by	ADP
cana-4847	92	10	hand	hand	NOUN
cana-4847	92	11	and	and	CCONJ
cana-4847	92	12	got	get	VERB
cana-4847	92	13	a	a	DET
cana-4847	92	14	cleaned	clean	VERB
cana-4847	92	15	-	-	PUNCT
cana-4847	92	16	up	up	ADP
cana-4847	92	17	dataset	dataset	NOUN
cana-4847	92	18	of	of	ADP
cana-4847	92	19	2368	2368	NUM
cana-4847	92	20	images	image	NOUN
cana-4847	92	21	.	.	PUNCT
cana-4847	93	1	with	with	ADP
cana-4847	93	2	our	our	PRON
cana-4847	93	3	dataset	dataset	NOUN
cana-4847	93	4	of	of	ADP
cana-4847	93	5	1301	1301	NUM
cana-4847	93	6	eczema	eczema	NOUN
cana-4847	93	7	and	and	CCONJ
cana-4847	93	8	1067	1067	NUM
cana-4847	93	9	pictures	picture	NOUN
cana-4847	93	10	of	of	ADP
cana-4847	93	11	different	different	ADJ
cana-4847	93	12	regions	region	NOUN
cana-4847	93	13	of	of	ADP
cana-4847	93	14	psoriasis	psoriasis	NOUN
cana-4847	93	15	for	for	ADP
cana-4847	93	16	each	each	DET
cana-4847	93	17	category	category	NOUN
cana-4847	93	18	of	of	ADP
cana-4847	93	19	illness	illness	NOUN
cana-4847	93	20	being	be	AUX
cana-4847	93	21	well	well	ADV
cana-4847	93	22	-	-	PUNCT
cana-4847	93	23	presented	present	VERB
cana-4847	93	24	.	.	PUNCT
cana-4847	94	1	examples	example	NOUN
cana-4847	94	2	can	can	AUX
cana-4847	94	3	be	be	AUX
cana-4847	94	4	viewed	view	VERB
cana-4847	94	5	on	on	ADP
cana-4847	94	6	figure	figure	NOUN
cana-4847	94	7	2	2	NUM
cana-4847	94	8	,	,	PUNCT
cana-4847	94	9	given	give	VERB
cana-4847	94	10	below	below	ADV
cana-4847	94	11	as	as	ADP
cana-4847	94	12	being	be	AUX
cana-4847	94	13	part	part	NOUN
cana-4847	94	14	and	and	CCONJ
cana-4847	94	15	parcel	parcel	NOUN
cana-4847	94	16	of	of	ADP
cana-4847	94	17	the	the	DET
cana-4847	94	18	database	database	NOUN
cana-4847	94	19	used	use	VERB
cana-4847	94	20	as	as	SCONJ
cana-4847	94	21	shown	show	VERB
cana-4847	94	22	in	in	ADP
cana-4847	94	23	table	table	NOUN
cana-4847	94	24	1	1	NUM
cana-4847	94	25	.	.	PUNCT
cana-4847	94	26	to	to	PART
cana-4847	94	27	be	be	AUX
cana-4847	94	28	better	well	ADV
cana-4847	94	29	diagnosed	diagnose	VERB
cana-4847	94	30	,	,	PUNCT
cana-4847	94	31	images	image	NOUN
cana-4847	94	32	played	play	VERB
cana-4847	94	33	a	a	DET
cana-4847	94	34	paramount	paramount	ADJ
cana-4847	94	35	integral	integral	ADJ
cana-4847	94	36	part	part	NOUN
cana-4847	94	37	as	as	ADP
cana-4847	94	38	additions	addition	NOUN
cana-4847	94	39	to	to	ADP
cana-4847	94	40	both	both	DET
cana-4847	94	41	training	training	NOUN
cana-4847	94	42	and	and	CCONJ
cana-4847	94	43	the	the	DET
cana-4847	94	44	testing	testing	NOUN
cana-4847	94	45	set	set	VERB
cana-4847	94	46	on	on	ADP
cana-4847	94	47	machines	machine	NOUN
cana-4847	94	48	to	to	PART
cana-4847	94	49	let	let	VERB
cana-4847	94	50	us	we	PRON
cana-4847	94	51	come	come	VERB
cana-4847	94	52	out	out	ADP
cana-4847	94	53	and	and	CCONJ
cana-4847	94	54	propose	propose	VERB
cana-4847	94	55	far	far	ADV
cana-4847	94	56	much	much	ADV
cana-4847	94	57	more	more	ADV
cana-4847	94	58	appropriate	appropriate	ADJ
cana-4847	94	59	diagnostics	diagnostic	NOUN
cana-4847	94	60	for	for	ADP
cana-4847	94	61	this	this	DET
cana-4847	94	62	range	range	NOUN
cana-4847	94	63	of	of	ADP
cana-4847	94	64	dermatitis	dermatitis	NOUN
cana-4847	94	65	.	.	PUNCT
cana-4847	95	1	improved	improve	VERB
cana-4847	95	2	the	the	DET
cana-4847	95	3	lives	life	NOUN
cana-4847	95	4	of	of	ADP
cana-4847	95	5	millions	million	NOUN
cana-4847	95	6	of	of	ADP
cana-4847	95	7	individuals	individual	NOUN
cana-4847	95	8	worldwide	worldwide	ADV
cana-4847	95	9	through	through	ADP
cana-4847	95	10	the	the	DET
cana-4847	95	11	efficient	efficient	ADJ
cana-4847	95	12	utilization	utilization	NOUN
cana-4847	95	13	of	of	ADP
cana-4847	95	14	these	these	DET
cana-4847	95	15	technologies	technology	NOUN
cana-4847	95	16	and	and	CCONJ
cana-4847	95	17	data	datum	NOUN
cana-4847	95	18	by	by	ADP
cana-4847	95	19	improving	improve	VERB
cana-4847	95	20	on	on	ADP
cana-4847	95	21	diagnosis	diagnosis	NOUN
cana-4847	95	22	and	and	CCONJ
cana-4847	95	23	the	the	DET
cana-4847	95	24	subsequent	subsequent	ADJ
cana-4847	95	25	treatment	treatment	NOUN
cana-4847	95	26	for	for	ADP
cana-4847	95	27	eczema	eczema	NOUN
cana-4847	95	28	and	and	CCONJ
cana-4847	95	29	psoriasis	psoriasis	NOUN
cana-4847	95	30	.	.	PUNCT
cana-4847	96	1	fig.1	fig.1	ADJ
cana-4847	96	2	:	:	PUNCT
cana-4847	96	3	block	block	NOUN
cana-4847	96	4	diagram	diagram	NOUN
cana-4847	96	5	of	of	ADP
cana-4847	96	6	deep	deep	ADJ
cana-4847	96	7	learning	learning	NOUN
cana-4847	96	8	-	-	PUNCT
cana-4847	96	9	based	base	VERB
cana-4847	96	10	skin	skin	NOUN
cana-4847	96	11	disease	disease	NOUN
cana-4847	96	12	prediction	prediction	NOUN
cana-4847	96	13	model	model	NOUN
cana-4847	96	14	(	(	PUNCT
cana-4847	96	15	proposed	propose	VERB
cana-4847	96	16	)	)	PUNCT
cana-4847	96	17	communications	communication	NOUN
cana-4847	96	18	on	on	ADP
cana-4847	96	19	applied	apply	VERB
cana-4847	96	20	nonlinear	nonlinear	ADJ
cana-4847	96	21	analysis	analysis	NOUN
cana-4847	96	22	issn	issn	NOUN
cana-4847	96	23	:	:	PUNCT
cana-4847	96	24	1074	1074	NUM
cana-4847	96	25	-	-	PUNCT
cana-4847	96	26	133x	133x	NUM
cana-4847	96	27	vol	vol	VERB
cana-4847	96	28	32	32	NUM
cana-4847	96	29	no	no	NOUN
cana-4847	96	30	.	.	PUNCT
cana-4847	97	1	10s	10	NOUN
cana-4847	97	2	(	(	PUNCT
cana-4847	97	3	2025	2025	NUM
cana-4847	97	4	)	)	PUNCT
cana-4847	97	5	571	571	NUM
cana-4847	97	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	97	7	fig.2	fig.2	PROPN
cana-4847	97	8	:	:	PUNCT
cana-4847	97	9	image	image	NOUN
cana-4847	97	10	samples	sample	NOUN
cana-4847	97	11	of	of	ADP
cana-4847	97	12	skin	skin	NOUN
cana-4847	97	13	disease	disease	NOUN
cana-4847	97	14	dataset	dataset	VERB
cana-4847	97	15	of	of	ADP
cana-4847	97	16	eczema	eczema	NOUN
cana-4847	97	17	and	and	CCONJ
cana-4847	97	18	psoriasis	psoriasis	VERB
cana-4847	97	19	our	our	PRON
cana-4847	97	20	dataset	dataset	NOUN
cana-4847	97	21	is	be	AUX
cana-4847	97	22	a	a	DET
cana-4847	97	23	treasure	treasure	NOUN
cana-4847	97	24	of	of	ADP
cana-4847	97	25	images	image	NOUN
cana-4847	97	26	that	that	PRON
cana-4847	97	27	can	can	AUX
cana-4847	97	28	all	all	PRON
cana-4847	97	29	relate	relate	VERB
cana-4847	97	30	to	to	ADP
cana-4847	97	31	different	different	ADJ
cana-4847	97	32	diseases	disease	NOUN
cana-4847	97	33	as	as	SCONJ
cana-4847	97	34	regards	regard	VERB
cana-4847	97	35	skin	skin	NOUN
cana-4847	97	36	issues	issue	NOUN
cana-4847	97	37	.	.	PUNCT
cana-4847	98	1	these	these	PRON
cana-4847	98	2	would	would	AUX
cana-4847	98	3	be	be	AUX
cana-4847	98	4	the	the	DET
cana-4847	98	5	training	training	NOUN
cana-4847	98	6	set	set	NOUN
cana-4847	98	7	of	of	ADP
cana-4847	98	8	our	our	PRON
cana-4847	98	9	model	model	NOUN
cana-4847	98	10	for	for	ADP
cana-4847	98	11	the	the	DET
cana-4847	98	12	first	first	ADJ
cana-4847	98	13	time	time	NOUN
cana-4847	98	14	.	.	PUNCT
cana-4847	99	1	being	be	AUX
cana-4847	99	2	so	so	ADV
cana-4847	99	3	massive	massive	ADJ
cana-4847	99	4	,	,	PUNCT
cana-4847	99	5	the	the	DET
cana-4847	99	6	size	size	NOUN
cana-4847	99	7	of	of	ADP
cana-4847	99	8	the	the	DET
cana-4847	99	9	database	database	NOUN
cana-4847	99	10	makes	make	VERB
cana-4847	99	11	it	it	PRON
cana-4847	99	12	a	a	DET
cana-4847	99	13	relatively	relatively	ADV
cana-4847	99	14	straightforward	straightforward	ADJ
cana-4847	99	15	thing	thing	NOUN
cana-4847	99	16	for	for	SCONJ
cana-4847	99	17	us	we	PRON
cana-4847	99	18	to	to	PART
cana-4847	99	19	classify	classify	VERB
cana-4847	99	20	images	image	NOUN
cana-4847	99	21	under	under	ADP
cana-4847	99	22	a	a	DET
cana-4847	99	23	class	class	NOUN
cana-4847	99	24	of	of	ADP
cana-4847	99	25	diseases	disease	NOUN
cana-4847	99	26	the	the	DET
cana-4847	99	27	skin	skin	NOUN
cana-4847	99	28	might	might	AUX
cana-4847	99	29	be	be	AUX
cana-4847	99	30	exposed	expose	VERB
cana-4847	99	31	to	to	ADP
cana-4847	99	32	.	.	PUNCT
cana-4847	100	1	before	before	ADP
cana-4847	100	2	getting	get	VERB
cana-4847	100	3	the	the	DET
cana-4847	100	4	model	model	NOUN
cana-4847	100	5	to	to	PART
cana-4847	100	6	actually	actually	ADV
cana-4847	100	7	train	train	VERB
cana-4847	100	8	,	,	PUNCT
cana-4847	100	9	pre	pre	ADJ
cana-4847	100	10	-	-	ADJ
cana-4847	100	11	processing	process	VERB
cana-4847	100	12	and	and	CCONJ
cana-4847	100	13	cleaning	clean	VERB
cana-4847	100	14	the	the	DET
cana-4847	100	15	dataset	dataset	NOUN
cana-4847	100	16	had	have	AUX
cana-4847	100	17	done	do	VERB
cana-4847	100	18	.	.	PUNCT
cana-4847	101	1	this	this	DET
cana-4847	101	2	careful	careful	ADJ
cana-4847	101	3	process	process	NOUN
cana-4847	101	4	implies	imply	VERB
cana-4847	101	5	that	that	SCONJ
cana-4847	101	6	our	our	PRON
cana-4847	101	7	dataset	dataset	NOUN
cana-4847	101	8	should	should	AUX
cana-4847	101	9	be	be	AUX
cana-4847	101	10	the	the	DET
cana-4847	101	11	best	good	ADJ
cana-4847	101	12	possible	possible	ADJ
cana-4847	101	13	and	and	CCONJ
cana-4847	101	14	from	from	ADP
cana-4847	101	15	it	it	PRON
cana-4847	101	16	is	be	AUX
cana-4847	101	17	where	where	SCONJ
cana-4847	101	18	our	our	PRON
cana-4847	101	19	model	model	NOUN
cana-4847	101	20	learns	learn	VERB
cana-4847	101	21	its	its	PRON
cana-4847	101	22	data	datum	NOUN
cana-4847	101	23	.	.	PUNCT
cana-4847	102	1	for	for	ADP
cana-4847	102	2	that	that	DET
cana-4847	102	3	reason	reason	NOUN
cana-4847	102	4	,	,	PUNCT
cana-4847	102	5	set	set	VERB
cana-4847	102	6	the	the	DET
cana-4847	102	7	stage	stage	NOUN
cana-4847	102	8	for	for	ADP
cana-4847	102	9	the	the	DET
cana-4847	102	10	model	model	NOUN
cana-4847	102	11	so	so	SCONJ
cana-4847	102	12	it	it	PRON
cana-4847	102	13	might	might	AUX
cana-4847	102	14	thrive	thrive	VERB
cana-4847	102	15	well	well	ADV
cana-4847	102	16	during	during	ADP
cana-4847	102	17	the	the	DET
cana-4847	102	18	diagnosis	diagnosis	NOUN
cana-4847	102	19	of	of	ADP
cana-4847	102	20	diseases	disease	NOUN
cana-4847	102	21	in	in	ADP
cana-4847	102	22	relation	relation	NOUN
cana-4847	102	23	to	to	ADP
cana-4847	102	24	skin	skin	NOUN
cana-4847	102	25	issues	issue	NOUN
cana-4847	102	26	.	.	PUNCT
cana-4847	103	1	this	this	DET
cana-4847	103	2	feature	feature	NOUN
cana-4847	103	3	-	-	PUNCT
cana-4847	103	4	based	base	VERB
cana-4847	103	5	model	model	NOUN
cana-4847	103	6	relies	rely	VERB
cana-4847	103	7	completely	completely	ADV
cana-4847	103	8	on	on	ADP
cana-4847	103	9	features	feature	NOUN
cana-4847	103	10	which	which	PRON
cana-4847	103	11	have	have	AUX
cana-4847	103	12	been	be	AUX
cana-4847	103	13	derived	derive	VERB
cana-4847	103	14	from	from	ADP
cana-4847	103	15	images	image	NOUN
cana-4847	103	16	by	by	ADP
cana-4847	103	17	architectures	architecture	NOUN
cana-4847	103	18	of	of	ADP
cana-4847	103	19	the	the	DET
cana-4847	103	20	cnn	cnn	PROPN
cana-4847	103	21	.	.	PUNCT
cana-4847	104	1	those	those	DET
cana-4847	104	2	features	feature	NOUN
cana-4847	104	3	are	be	AUX
cana-4847	104	4	the	the	DET
cana-4847	104	5	precursors	precursor	NOUN
cana-4847	104	6	with	with	ADP
cana-4847	104	7	which	which	PRON
cana-4847	104	8	our	our	PRON
cana-4847	104	9	model	model	NOUN
cana-4847	104	10	distinguishes	distinguish	VERB
cana-4847	104	11	other	other	ADJ
cana-4847	104	12	skin	skin	NOUN
cana-4847	104	13	conditions	condition	NOUN
cana-4847	104	14	affecting	affect	VERB
cana-4847	104	15	a	a	DET
cana-4847	104	16	patient	patient	NOUN
cana-4847	104	17	.	.	PUNCT
cana-4847	105	1	empowered	empower	VERB
cana-4847	105	2	the	the	DET
cana-4847	105	3	model	model	NOUN
cana-4847	105	4	to	to	PART
cana-4847	105	5	identify	identify	VERB
cana-4847	105	6	trends	trend	NOUN
cana-4847	105	7	and	and	CCONJ
cana-4847	105	8	characteristics	characteristic	NOUN
cana-4847	105	9	,	,	PUNCT
cana-4847	105	10	which	which	PRON
cana-4847	105	11	may	may	AUX
cana-4847	105	12	well	well	ADV
cana-4847	105	13	be	be	AUX
cana-4847	105	14	hidden	hide	VERB
cana-4847	105	15	within	within	ADP
cana-4847	105	16	those	those	DET
cana-4847	105	17	images	image	NOUN
cana-4847	105	18	to	to	PART
cana-4847	105	19	not	not	PART
cana-4847	105	20	be	be	AUX
cana-4847	105	21	noted	note	VERB
cana-4847	105	22	by	by	ADP
cana-4847	105	23	experts	expert	NOUN
cana-4847	105	24	and	and	CCONJ
cana-4847	105	25	applying	apply	VERB
cana-4847	105	26	cnns	cnn	NOUN
cana-4847	105	27	.	.	PUNCT
cana-4847	106	1	with	with	SCONJ
cana-4847	106	2	our	our	PRON
cana-4847	106	3	features	feature	NOUN
cana-4847	106	4	extracted	extract	VERB
cana-4847	106	5	the	the	DET
cana-4847	106	6	model	model	NOUN
cana-4847	106	7	proceeds	proceed	NOUN
cana-4847	106	8	for	for	ADP
cana-4847	106	9	classification	classification	NOUN
cana-4847	106	10	using	use	VERB
cana-4847	106	11	a	a	DET
cana-4847	106	12	dense	dense	ADJ
cana-4847	106	13	layer	layer	NOUN
cana-4847	106	14	architecture	architecture	NOUN
cana-4847	106	15	of	of	ADP
cana-4847	106	16	our	our	PRON
cana-4847	106	17	cnn	cnn	PROPN
cana-4847	106	18	.	.	PUNCT
cana-4847	107	1	this	this	DET
cana-4847	107	2	critical	critical	ADJ
cana-4847	107	3	step	step	NOUN
cana-4847	107	4	enables	enable	VERB
cana-4847	107	5	the	the	DET
cana-4847	107	6	model	model	NOUN
cana-4847	107	7	.	.	PUNCT
cana-4847	108	1	it	it	PRON
cana-4847	108	2	provides	provide	VERB
cana-4847	108	3	highly	highly	ADV
cana-4847	108	4	accurate	accurate	ADJ
cana-4847	108	5	diagnosis	diagnosis	NOUN
cana-4847	108	6	and	and	CCONJ
cana-4847	108	7	will	will	AUX
cana-4847	108	8	assist	assist	VERB
cana-4847	108	9	in	in	ADP
cana-4847	108	10	early	early	ADJ
cana-4847	108	11	and	and	CCONJ
cana-4847	108	12	effective	effective	ADJ
cana-4847	108	13	treatment	treatment	NOUN
cana-4847	108	14	.	.	PUNCT
cana-4847	109	1	with	with	ADP
cana-4847	109	2	the	the	DET
cana-4847	109	3	power	power	NOUN
cana-4847	109	4	of	of	ADP
cana-4847	109	5	deep	deep	ADJ
cana-4847	109	6	learning	learning	NOUN
cana-4847	109	7	,	,	PUNCT
cana-4847	109	8	an	an	DET
cana-4847	109	9	outstanding	outstanding	ADJ
cana-4847	109	10	functionality	functionality	NOUN
cana-4847	109	11	to	to	ADP
cana-4847	109	12	our	our	PRON
cana-4847	109	13	model	model	NOUN
cana-4847	109	14	stands	stand	NOUN
cana-4847	109	15	.	.	PUNCT
cana-4847	110	1	it	it	PRON
cana-4847	110	2	picks	pick	VERB
cana-4847	110	3	up	up	ADP
cana-4847	110	4	even	even	ADV
cana-4847	110	5	the	the	DET
cana-4847	110	6	minutest	minute	ADJ
cana-4847	110	7	abnormality	abnormality	NOUN
cana-4847	110	8	present	present	ADJ
cana-4847	110	9	in	in	ADP
cana-4847	110	10	the	the	DET
cana-4847	110	11	image	image	NOUN
cana-4847	110	12	of	of	ADP
cana-4847	110	13	the	the	DET
cana-4847	110	14	skin	skin	NOUN
cana-4847	110	15	which	which	PRON
cana-4847	110	16	may	may	AUX
cana-4847	110	17	go	go	VERB
cana-4847	110	18	unobserved	unobserved	ADJ
cana-4847	110	19	by	by	ADP
cana-4847	110	20	the	the	DET
cana-4847	110	21	keen	keen	ADJ
cana-4847	110	22	eye	eye	NOUN
cana-4847	110	23	of	of	ADP
cana-4847	110	24	an	an	DET
cana-4847	110	25	expert	expert	NOUN
cana-4847	110	26	that	that	PRON
cana-4847	110	27	makes	make	VERB
cana-4847	110	28	the	the	DET
cana-4847	110	29	early	early	ADJ
cana-4847	110	30	and	and	CCONJ
cana-4847	110	31	accurate	accurate	ADJ
cana-4847	110	32	diagnosis	diagnosis	NOUN
cana-4847	110	33	.	.	PUNCT
cana-4847	111	1	creating	create	VERB
cana-4847	111	2	an	an	DET
cana-4847	111	3	effective	effective	ADJ
cana-4847	111	4	system	system	NOUN
cana-4847	111	5	for	for	ADP
cana-4847	111	6	diagnosing	diagnose	VERB
cana-4847	111	7	and	and	CCONJ
cana-4847	111	8	managing	manage	VERB
cana-4847	111	9	eczema	eczema	NOUN
cana-4847	111	10	and	and	CCONJ
cana-4847	111	11	psoriasis	psoriasis	NOUN
cana-4847	111	12	that	that	PRON
cana-4847	111	13	improves	improve	VERB
cana-4847	111	14	the	the	DET
cana-4847	111	15	lives	life	NOUN
cana-4847	111	16	of	of	ADP
cana-4847	111	17	millions	million	NOUN
cana-4847	111	18	will	will	AUX
cana-4847	111	19	be	be	AUX
cana-4847	111	20	the	the	DET
cana-4847	111	21	purpose	purpose	NOUN
cana-4847	111	22	.	.	PUNCT
cana-4847	112	1	table1	table1	NOUN
cana-4847	112	2	:	:	PUNCT
cana-4847	112	3	images	image	NOUN
cana-4847	112	4	of	of	ADP
cana-4847	112	5	eczema	eczema	NOUN
cana-4847	112	6	and	and	CCONJ
cana-4847	112	7	psoriasis	psoriasis	NOUN
cana-4847	112	8	disease	disease	NOUN
cana-4847	112	9	type	type	NOUN
cana-4847	112	10	eczema	eczema	NOUN
cana-4847	112	11	psoriasis	psoriasis	NOUN
cana-4847	112	12	training	training	NOUN
cana-4847	112	13	data	datum	NOUN
cana-4847	112	14	1040	1040	NUM
cana-4847	112	15	856	856	NUM
cana-4847	112	16	validation	validation	NOUN
cana-4847	112	17	data	datum	NOUN
cana-4847	112	18	261	261	NUM
cana-4847	112	19	211	211	NUM
cana-4847	112	20	total	total	ADJ
cana-4847	112	21	1301	1301	NUM
cana-4847	112	22	1067	1067	NUM
cana-4847	112	23	communications	communication	NOUN
cana-4847	112	24	on	on	ADP
cana-4847	112	25	applied	apply	VERB
cana-4847	112	26	nonlinear	nonlinear	ADJ
cana-4847	112	27	analysis	analysis	NOUN
cana-4847	112	28	issn	issn	NOUN
cana-4847	112	29	:	:	PUNCT
cana-4847	112	30	1074	1074	NUM
cana-4847	112	31	-	-	PUNCT
cana-4847	112	32	133x	133x	NUM
cana-4847	112	33	vol	vol	VERB
cana-4847	112	34	32	32	NUM
cana-4847	112	35	no	no	NOUN
cana-4847	112	36	.	.	PUNCT
cana-4847	113	1	10s	10	NOUN
cana-4847	113	2	(	(	PUNCT
cana-4847	113	3	2025	2025	NUM
cana-4847	113	4	)	)	PUNCT
cana-4847	113	5	572	572	NUM
cana-4847	113	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	113	7	3.2	3.2	NUM
cana-4847	113	8	.	.	PUNCT
cana-4847	113	9	variance	variance	NOUN
cana-4847	113	10	in	in	ADP
cana-4847	113	11	the	the	DET
cana-4847	113	12	data	data	NOUN
cana-4847	113	13	variation	variation	NOUN
cana-4847	113	14	in	in	ADP
cana-4847	113	15	the	the	DET
cana-4847	113	16	data	data	NOUN
cana-4847	113	17	is	be	AUX
cana-4847	113	18	a	a	DET
cana-4847	113	19	very	very	ADV
cana-4847	113	20	strong	strong	ADJ
cana-4847	113	21	method	method	NOUN
cana-4847	113	22	that	that	PRON
cana-4847	113	23	helps	help	VERB
cana-4847	113	24	to	to	PART
cana-4847	113	25	artificially	artificially	ADV
cana-4847	113	26	augment	augment	VERB
cana-4847	113	27	our	our	PRON
cana-4847	113	28	dataset	dataset	NOUN
cana-4847	113	29	.	.	PUNCT
cana-4847	114	1	let	let	VERB
cana-4847	114	2	us	we	PRON
cana-4847	114	3	create	create	VERB
cana-4847	114	4	a	a	DET
cana-4847	114	5	whole	whole	ADJ
cana-4847	114	6	new	new	ADJ
cana-4847	114	7	image	image	NOUN
cana-4847	114	8	different	different	ADJ
cana-4847	114	9	from	from	ADP
cana-4847	114	10	all	all	PRON
cana-4847	114	11	that	that	PRON
cana-4847	114	12	has	have	AUX
cana-4847	114	13	already	already	ADV
cana-4847	114	14	come	come	VERB
cana-4847	114	15	from	from	ADP
cana-4847	114	16	earlier	early	ADJ
cana-4847	114	17	ones	one	NOUN
cana-4847	114	18	such	such	ADJ
cana-4847	114	19	images	image	NOUN
cana-4847	114	20	may	may	AUX
cana-4847	114	21	tend	tend	VERB
cana-4847	114	22	to	to	PART
cana-4847	114	23	commit	commit	VERB
cana-4847	114	24	less	less	ADJ
cana-4847	114	25	overfitting	overfitting	NOUN
cana-4847	114	26	and	and	CCONJ
cana-4847	114	27	the	the	DET
cana-4847	114	28	ability	ability	NOUN
cana-4847	114	29	for	for	ADP
cana-4847	114	30	generalization	generalization	NOUN
cana-4847	114	31	.	.	PUNCT
cana-4847	115	1	the	the	DET
cana-4847	115	2	data	data	NOUN
cana-4847	115	3	augmentation	augmentation	NOUN
cana-4847	115	4	procedures	procedure	NOUN
cana-4847	115	5	are	be	AUX
cana-4847	115	6	described	describe	VERB
cana-4847	115	7	here	here	ADV
cana-4847	115	8	:	:	PUNCT
cana-4847	115	9	the	the	DET
cana-4847	115	10	brightness	brightness	NOUN
cana-4847	115	11	of	of	ADP
cana-4847	115	12	our	our	PRON
cana-4847	115	13	images	image	NOUN
cana-4847	115	14	enhanced	enhance	VERB
cana-4847	115	15	by	by	ADP
cana-4847	115	16	20	20	NUM
cana-4847	115	17	%	%	NOUN
cana-4847	115	18	to	to	PART
cana-4847	115	19	simulate	simulate	VERB
cana-4847	115	20	different	different	ADJ
cana-4847	115	21	lighting	lighting	NOUN
cana-4847	115	22	conditions	condition	NOUN
cana-4847	115	23	.	.	PUNCT
cana-4847	116	1	enhancing	enhance	VERB
cana-4847	116	2	the	the	DET
cana-4847	116	3	contrast	contrast	NOUN
cana-4847	116	4	of	of	ADP
cana-4847	116	5	our	our	PRON
cana-4847	116	6	images	image	NOUN
cana-4847	116	7	by	by	ADP
cana-4847	116	8	10	10	NUM
cana-4847	116	9	%	%	NOUN
cana-4847	116	10	to	to	PART
cana-4847	116	11	accentuate	accentuate	VERB
cana-4847	116	12	details	detail	NOUN
cana-4847	116	13	.	.	PUNCT
cana-4847	117	1	random	random	ADJ
cana-4847	117	2	rotation	rotation	NOUN
cana-4847	117	3	:	:	PUNCT
cana-4847	117	4	randomly	randomly	ADV
cana-4847	117	5	rotate	rotate	VERB
cana-4847	117	6	our	our	PRON
cana-4847	117	7	images	image	NOUN
cana-4847	117	8	by	by	ADP
cana-4847	117	9	5	5	NUM
cana-4847	117	10	degrees	degree	NOUN
cana-4847	117	11	to	to	PART
cana-4847	117	12	simulate	simulate	VERB
cana-4847	117	13	different	different	ADJ
cana-4847	117	14	orientations	orientation	NOUN
cana-4847	117	15	.	.	PUNCT
cana-4847	118	1	horizontal	horizontal	ADJ
cana-4847	118	2	flip	flip	NOUN
cana-4847	118	3	:	:	PUNCT
cana-4847	118	4	flip	flip	VERB
cana-4847	118	5	the	the	DET
cana-4847	118	6	images	image	NOUN
cana-4847	118	7	horizontally	horizontally	ADV
cana-4847	118	8	to	to	PART
cana-4847	118	9	simulate	simulate	VERB
cana-4847	118	10	mirror	mirror	NOUN
cana-4847	118	11	reflections	reflection	NOUN
cana-4847	118	12	.	.	PUNCT
cana-4847	119	1	combining	combine	VERB
cana-4847	119	2	them	they	PRON
cana-4847	119	3	to	to	PART
cana-4847	119	4	generate	generate	VERB
cana-4847	119	5	five	five	NUM
cana-4847	119	6	variations	variation	NOUN
cana-4847	119	7	for	for	ADP
cana-4847	119	8	each	each	DET
cana-4847	119	9	sample	sample	NOUN
cana-4847	119	10	image	image	NOUN
cana-4847	119	11	into	into	ADP
cana-4847	119	12	a	a	DET
cana-4847	119	13	more	more	ADV
cana-4847	119	14	comprehensive	comprehensive	ADJ
cana-4847	119	15	and	and	CCONJ
cana-4847	119	16	diverse	diverse	ADJ
cana-4847	119	17	set	set	NOUN
cana-4847	119	18	.	.	PUNCT
cana-4847	120	1	3.3	3.3	NUM
cana-4847	120	2	.	.	PUNCT
cana-4847	121	1	dataset	dataset	VERB
cana-4847	121	2	analysis	analysis	NOUN
cana-4847	121	3	after	after	SCONJ
cana-4847	121	4	that	that	SCONJ
cana-4847	121	5	we	we	PRON
cana-4847	121	6	add	add	VERB
cana-4847	121	7	the	the	DET
cana-4847	121	8	new	new	ADJ
cana-4847	121	9	data	datum	NOUN
cana-4847	121	10	to	to	ADP
cana-4847	121	11	our	our	PRON
cana-4847	121	12	dataset	dataset	NOUN
cana-4847	122	1	had	have	VERB
cana-4847	122	2	totally	totally	ADV
cana-4847	122	3	2368	2368	NUM
cana-4847	122	4	images	image	NOUN
cana-4847	122	5	for	for	ADP
cana-4847	122	6	the	the	DET
cana-4847	122	7	dataset	dataset	NOUN
cana-4847	122	8	.	.	PUNCT
cana-4847	123	1	dataset	dataset	PROPN
cana-4847	123	2	is	be	AUX
cana-4847	123	3	divided	divide	VERB
cana-4847	123	4	into	into	ADP
cana-4847	123	5	training	training	NOUN
cana-4847	123	6	and	and	CCONJ
cana-4847	123	7	testing	testing	NOUN
cana-4847	123	8	sets	set	NOUN
cana-4847	123	9	with	with	ADP
cana-4847	123	10	80:20	80:20	NUM
cana-4847	123	11	split	split	NOUN
cana-4847	123	12	.	.	PUNCT
cana-4847	124	1	training	training	NOUN
cana-4847	124	2	set	set	NOUN
cana-4847	124	3	had	have	VERB
cana-4847	124	4	80	80	NUM
cana-4847	124	5	%	%	NOUN
cana-4847	124	6	of	of	ADP
cana-4847	124	7	the	the	DET
cana-4847	124	8	total	total	ADJ
cana-4847	124	9	images	image	NOUN
cana-4847	124	10	(	(	PUNCT
cana-4847	124	11	1894	1894	NUM
cana-4847	124	12	images	image	NOUN
cana-4847	124	13	)	)	PUNCT
cana-4847	124	14	,	,	PUNCT
cana-4847	124	15	and	and	CCONJ
cana-4847	124	16	our	our	PRON
cana-4847	124	17	testing	testing	NOUN
cana-4847	124	18	set	set	NOUN
cana-4847	124	19	consisted	consist	VERB
cana-4847	124	20	of	of	ADP
cana-4847	124	21	20	20	NUM
cana-4847	124	22	%	%	NOUN
cana-4847	124	23	(	(	PUNCT
cana-4847	124	24	474	474	NUM
cana-4847	124	25	images	image	NOUN
cana-4847	124	26	)	)	PUNCT
cana-4847	124	27	.	.	PUNCT
cana-4847	125	1	in	in	ADP
cana-4847	125	2	this	this	DET
cana-4847	125	3	way	way	NOUN
cana-4847	125	4	,	,	PUNCT
cana-4847	125	5	the	the	DET
cana-4847	125	6	model	model	NOUN
cana-4847	125	7	would	would	AUX
cana-4847	125	8	have	have	AUX
cana-4847	125	9	been	be	AUX
cana-4847	125	10	trained	train	VERB
cana-4847	125	11	on	on	ADP
cana-4847	125	12	a	a	DET
cana-4847	125	13	variety	variety	NOUN
cana-4847	125	14	of	of	ADP
cana-4847	125	15	images	image	NOUN
cana-4847	125	16	and	and	CCONJ
cana-4847	125	17	tested	test	VERB
cana-4847	125	18	on	on	ADP
cana-4847	125	19	another	another	DET
cana-4847	125	20	independent	independent	ADJ
cana-4847	125	21	,	,	PUNCT
cana-4847	125	22	unbiased	unbiased	ADJ
cana-4847	125	23	set	set	NOUN
cana-4847	125	24	.	.	PUNCT
cana-4847	126	1	in	in	ADP
cana-4847	126	2	order	order	NOUN
cana-4847	126	3	to	to	PART
cana-4847	126	4	avoid	avoid	VERB
cana-4847	126	5	biased	biased	ADJ
cana-4847	126	6	outcome	outcome	NOUN
cana-4847	126	7	,	,	PUNCT
cana-4847	126	8	make	make	VERB
cana-4847	126	9	sure	sure	ADJ
cana-4847	126	10	that	that	SCONJ
cana-4847	126	11	our	our	PRON
cana-4847	126	12	testing	testing	NOUN
cana-4847	126	13	images	image	NOUN
cana-4847	126	14	never	never	ADV
cana-4847	126	15	mixed	mix	VERB
cana-4847	126	16	with	with	ADP
cana-4847	126	17	training	training	NOUN
cana-4847	126	18	and	and	CCONJ
cana-4847	126	19	validation	validation	NOUN
cana-4847	126	20	sets	set	NOUN
cana-4847	126	21	.	.	PUNCT
cana-4847	127	1	it	it	PRON
cana-4847	127	2	meant	mean	VERB
cana-4847	127	3	our	our	PRON
cana-4847	127	4	test	test	NOUN
cana-4847	127	5	set	set	NOUN
cana-4847	127	6	would	would	AUX
cana-4847	127	7	comprise	comprise	VERB
cana-4847	127	8	a	a	DET
cana-4847	127	9	whole	whole	ADJ
cana-4847	127	10	different	different	ADJ
cana-4847	127	11	set	set	NOUN
cana-4847	127	12	of	of	ADP
cana-4847	127	13	images	image	NOUN
cana-4847	127	14	,	,	PUNCT
cana-4847	127	15	thus	thus	ADV
cana-4847	127	16	giving	give	VERB
cana-4847	127	17	a	a	DET
cana-4847	127	18	proper	proper	ADJ
cana-4847	127	19	and	and	CCONJ
cana-4847	127	20	performative	performative	ADJ
cana-4847	127	21	measure	measure	NOUN
cana-4847	127	22	of	of	ADP
cana-4847	127	23	its	its	PRON
cana-4847	127	24	abilities	ability	NOUN
cana-4847	127	25	.	.	PUNCT
cana-4847	128	1	3.4	3.4	NUM
cana-4847	128	2	.	.	PUNCT
cana-4847	129	1	deep	deep	PROPN
cana-4847	129	2	cnn	cnn	PROPN
cana-4847	129	3	architectures	architecture	NOUN
cana-4847	129	4	in	in	ADP
cana-4847	129	5	fact	fact	NOUN
cana-4847	129	6	,	,	PUNCT
cana-4847	129	7	cnns	cnn	NOUN
cana-4847	129	8	are	be	AUX
cana-4847	129	9	supervised	supervised	ADJ
cana-4847	129	10	machine	machine	NOUN
cana-4847	129	11	learning	learning	NOUN
cana-4847	129	12	algorithms	algorithm	NOUN
cana-4847	129	13	,	,	PUNCT
cana-4847	129	14	and	and	CCONJ
cana-4847	129	15	they	they	PRON
cana-4847	129	16	're	be	AUX
cana-4847	129	17	very	very	ADV
cana-4847	129	18	good	good	ADJ
cana-4847	129	19	for	for	ADP
cana-4847	129	20	image	image	NOUN
cana-4847	129	21	recognition	recognition	NOUN
cana-4847	129	22	and	and	CCONJ
cana-4847	129	23	classification,[16],[17	classification,[16],[17	NOUN
cana-4847	129	24	]	]	PUNCT
cana-4847	129	25	.	.	PUNCT
cana-4847	130	1	in	in	ADP
cana-4847	130	2	the	the	DET
cana-4847	130	3	case	case	NOUN
cana-4847	130	4	of	of	ADP
cana-4847	130	5	skin	skin	NOUN
cana-4847	130	6	disease	disease	NOUN
cana-4847	130	7	diagnosis	diagnosis	NOUN
cana-4847	130	8	,	,	PUNCT
cana-4847	130	9	cnns	cnn	NOUN
cana-4847	130	10	perform	perform	VERB
cana-4847	130	11	very	very	ADV
cana-4847	130	12	well	well	ADV
cana-4847	130	13	.	.	PUNCT
cana-4847	131	1	five	five	NUM
cana-4847	131	2	different	different	ADJ
cana-4847	131	3	architectures	architecture	NOUN
cana-4847	131	4	of	of	ADP
cana-4847	131	5	cnn	cnn	PROPN
cana-4847	131	6	are	be	AUX
cana-4847	131	7	tested	test	VERB
cana-4847	131	8	as	as	SCONJ
cana-4847	131	9	shown	show	VERB
cana-4847	131	10	in	in	ADP
cana-4847	131	11	figure	figure	NOUN
cana-4847	131	12	3	3	NUM
cana-4847	131	13	,	,	PUNCT
cana-4847	131	14	all	all	PRON
cana-4847	131	15	distinctive	distinctive	ADJ
cana-4847	131	16	in	in	ADP
cana-4847	131	17	their	their	PRON
cana-4847	131	18	unique	unique	ADJ
cana-4847	131	19	strengths	strength	NOUN
cana-4847	131	20	and	and	CCONJ
cana-4847	131	21	characteristics	characteristic	NOUN
cana-4847	131	22	.	.	PUNCT
cana-4847	132	1	fig.3	fig.3	ADJ
cana-4847	132	2	:	:	PUNCT
cana-4847	132	3	convolutional	convolutional	ADJ
cana-4847	132	4	neural	neural	ADJ
cana-4847	132	5	network	network	NOUN
cana-4847	132	6	(	(	PUNCT
cana-4847	132	7	cnn	cnn	PROPN
cana-4847	132	8	)	)	PUNCT
cana-4847	132	9	architecture	architecture	NOUN
cana-4847	132	10	communications	communication	NOUN
cana-4847	132	11	on	on	ADP
cana-4847	132	12	applied	apply	VERB
cana-4847	132	13	nonlinear	nonlinear	ADJ
cana-4847	132	14	analysis	analysis	NOUN
cana-4847	132	15	issn	issn	NOUN
cana-4847	132	16	:	:	PUNCT
cana-4847	132	17	1074	1074	NUM
cana-4847	132	18	-	-	PUNCT
cana-4847	132	19	133x	133x	NUM
cana-4847	132	20	vol	vol	VERB
cana-4847	132	21	32	32	NUM
cana-4847	132	22	no	no	NOUN
cana-4847	132	23	.	.	PUNCT
cana-4847	133	1	10s	10	NOUN
cana-4847	133	2	(	(	PUNCT
cana-4847	133	3	2025	2025	NUM
cana-4847	133	4	)	)	PUNCT
cana-4847	133	5	573	573	NUM
cana-4847	133	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	133	7	resnet-50	resnet-50	PROPN
cana-4847	133	8	is	be	AUX
cana-4847	133	9	the	the	DET
cana-4847	133	10	strongest	strong	ADJ
cana-4847	133	11	image	image	NOUN
cana-4847	133	12	classification	classification	NOUN
cana-4847	133	13	model	model	NOUN
cana-4847	133	14	utilized	utilize	VERB
cana-4847	133	15	in	in	ADP
cana-4847	133	16	skin	skin	NOUN
cana-4847	133	17	disease	disease	NOUN
cana-4847	133	18	detection	detection	NOUN
cana-4847	133	19	applications	application	NOUN
cana-4847	133	20	.	.	PUNCT
cana-4847	134	1	utilizing	utilize	VERB
cana-4847	134	2	resnet-50	resnet-50	PROPN
cana-4847	134	3	in	in	ADP
cana-4847	134	4	an	an	DET
cana-4847	134	5	effort	effort	NOUN
cana-4847	134	6	to	to	PART
cana-4847	134	7	obtain	obtain	VERB
cana-4847	134	8	precise	precise	ADJ
cana-4847	134	9	skin	skin	NOUN
cana-4847	134	10	disease	disease	NOUN
cana-4847	134	11	classification	classification	NOUN
cana-4847	134	12	.	.	PUNCT
cana-4847	135	1	it	it	PRON
cana-4847	135	2	has	have	AUX
cana-4847	135	3	assisted	assist	VERB
cana-4847	135	4	us	we	PRON
cana-4847	135	5	in	in	ADP
cana-4847	135	6	creating	create	VERB
cana-4847	135	7	a	a	DET
cana-4847	135	8	trustworthy	trustworthy	ADJ
cana-4847	135	9	diagnostic	diagnostic	ADJ
cana-4847	135	10	tool	tool	NOUN
cana-4847	135	11	.	.	PUNCT
cana-4847	136	1	it	it	PRON
cana-4847	136	2	means	mean	VERB
cana-4847	136	3	the	the	DET
cana-4847	136	4	utilization	utilization	NOUN
cana-4847	136	5	of	of	ADP
cana-4847	136	6	resnet-50	resnet-50	PROPN
cana-4847	136	7	for	for	ADP
cana-4847	136	8	the	the	DET
cana-4847	136	9	best	good	ADJ
cana-4847	136	10	available	available	ADJ
cana-4847	136	11	power	power	NOUN
cana-4847	136	12	in	in	ADP
cana-4847	136	13	complex	complex	ADJ
cana-4847	136	14	patterns	pattern	NOUN
cana-4847	136	15	and	and	CCONJ
cana-4847	136	16	features	feature	NOUN
cana-4847	136	17	extracted	extract	VERB
cana-4847	136	18	by	by	ADP
cana-4847	136	19	images	image	NOUN
cana-4847	136	20	in	in	ADP
cana-4847	136	21	making	make	VERB
cana-4847	136	22	our	our	PRON
cana-4847	136	23	model	model	NOUN
cana-4847	136	24	more	more	ADV
cana-4847	136	25	robust	robust	ADJ
cana-4847	136	26	for	for	ADP
cana-4847	136	27	disease	disease	NOUN
cana-4847	136	28	detection	detection	NOUN
cana-4847	136	29	.	.	PUNCT
cana-4847	137	1	resnet-50	resnet-50	PROPN
cana-4847	137	2	is	be	AUX
cana-4847	137	3	a	a	DET
cana-4847	137	4	deep	deep	ADJ
cana-4847	137	5	neural	neural	ADJ
cana-4847	137	6	network	network	NOUN
cana-4847	137	7	that	that	PRON
cana-4847	137	8	contains	contain	VERB
cana-4847	137	9	residual	residual	ADJ
cana-4847	137	10	connections	connection	NOUN
cana-4847	137	11	,	,	PUNCT
cana-4847	137	12	which	which	PRON
cana-4847	137	13	has	have	AUX
cana-4847	137	14	been	be	AUX
cana-4847	137	15	famous	famous	ADJ
cana-4847	137	16	for	for	ADP
cana-4847	137	17	its	its	PRON
cana-4847	137	18	excellent	excellent	ADJ
cana-4847	137	19	ability	ability	NOUN
cana-4847	137	20	to	to	PART
cana-4847	137	21	learn	learn	VERB
cana-4847	137	22	complex	complex	ADJ
cana-4847	137	23	patterns	pattern	NOUN
cana-4847	137	24	with	with	ADP
cana-4847	137	25	ease	ease	NOUN
cana-4847	137	26	and	and	CCONJ
cana-4847	137	27	efficiency	efficiency	NOUN
cana-4847	137	28	during	during	ADP
cana-4847	137	29	training	training	NOUN
cana-4847	137	30	.	.	PUNCT
cana-4847	138	1	hence	hence	ADV
cana-4847	138	2	,	,	PUNCT
cana-4847	138	3	we	we	PRON
cana-4847	138	4	utilized	utilize	VERB
cana-4847	138	5	the	the	DET
cana-4847	138	6	pre	pre	ADJ
cana-4847	138	7	-	-	ADJ
cana-4847	138	8	trained	train	VERB
cana-4847	138	9	model	model	NOUN
cana-4847	138	10	called	call	VERB
cana-4847	138	11	resnet-50	resnet-50	PROPN
cana-4847	138	12	that	that	PRON
cana-4847	138	13	was	be	AUX
cana-4847	138	14	trained	train	VERB
cana-4847	138	15	on	on	ADP
cana-4847	138	16	a	a	DET
cana-4847	138	17	vast	vast	ADJ
cana-4847	138	18	collection	collection	NOUN
cana-4847	138	19	of	of	ADP
cana-4847	138	20	images	image	NOUN
cana-4847	138	21	.	.	PUNCT
cana-4847	139	1	in	in	ADP
cana-4847	139	2	this	this	DET
cana-4847	139	3	way	way	NOUN
cana-4847	139	4	,	,	PUNCT
cana-4847	139	5	the	the	DET
cana-4847	139	6	model	model	NOUN
cana-4847	139	7	tapped	tap	VERB
cana-4847	139	8	into	into	ADP
cana-4847	139	9	the	the	DET
cana-4847	139	10	knowledge	knowledge	NOUN
cana-4847	139	11	acquired	acquire	VERB
cana-4847	139	12	by	by	ADP
cana-4847	139	13	its	its	PRON
cana-4847	139	14	initial	initial	ADJ
cana-4847	139	15	training	training	NOUN
cana-4847	139	16	phase	phase	NOUN
cana-4847	139	17	,	,	PUNCT
cana-4847	139	18	thus	thus	ADV
cana-4847	139	19	improving	improve	VERB
cana-4847	139	20	performance	performance	NOUN
cana-4847	139	21	and	and	CCONJ
cana-4847	139	22	faster	fast	ADJ
cana-4847	139	23	convergence	convergence	NOUN
cana-4847	139	24	.	.	PUNCT
cana-4847	140	1	the	the	DET
cana-4847	140	2	pre	pre	ADJ
cana-4847	140	3	-	-	ADJ
cana-4847	140	4	trained	train	VERB
cana-4847	140	5	resnet-50	resnet-50	NOUN
cana-4847	140	6	architecture	architecture	NOUN
cana-4847	140	7	,	,	PUNCT
cana-4847	140	8	unfroze	unfreeze	VERB
cana-4847	140	9	only	only	ADV
cana-4847	140	10	the	the	DET
cana-4847	140	11	final	final	ADJ
cana-4847	140	12	dense	dense	ADJ
cana-4847	140	13	layer	layer	NOUN
cana-4847	140	14	with	with	ADP
cana-4847	140	15	frozen	frozen	ADJ
cana-4847	140	16	weights	weight	NOUN
cana-4847	140	17	of	of	ADP
cana-4847	140	18	the	the	DET
cana-4847	140	19	rest	rest	NOUN
cana-4847	140	20	of	of	ADP
cana-4847	140	21	the	the	DET
cana-4847	140	22	layers	layer	NOUN
cana-4847	140	23	.	.	PUNCT
cana-4847	141	1	this	this	DET
cana-4847	141	2	cautious	cautious	ADJ
cana-4847	141	3	design	design	NOUN
cana-4847	141	4	approach	approach	NOUN
cana-4847	141	5	facilitated	facilitate	VERB
cana-4847	141	6	fine	fine	ADV
cana-4847	141	7	-	-	PUNCT
cana-4847	141	8	tuning	tuning	NOUN
cana-4847	141	9	of	of	ADP
cana-4847	141	10	this	this	DET
cana-4847	141	11	model	model	NOUN
cana-4847	141	12	for	for	ADP
cana-4847	141	13	finding	find	VERB
cana-4847	141	14	those	those	DET
cana-4847	141	15	characteristics	characteristic	NOUN
cana-4847	141	16	peculiar	peculiar	ADJ
cana-4847	141	17	to	to	ADP
cana-4847	141	18	our	our	PRON
cana-4847	141	19	skin	skin	NOUN
cana-4847	141	20	disease	disease	NOUN
cana-4847	141	21	dataset	dataset	VERB
cana-4847	141	22	and	and	CCONJ
cana-4847	141	23	yet	yet	ADV
cana-4847	141	24	not	not	PART
cana-4847	141	25	losing	lose	VERB
cana-4847	141	26	features	feature	NOUN
cana-4847	141	27	inducted	induct	VERB
cana-4847	141	28	by	by	ADP
cana-4847	141	29	the	the	DET
cana-4847	141	30	strength	strength	NOUN
cana-4847	141	31	of	of	ADP
cana-4847	141	32	the	the	DET
cana-4847	141	33	pre	pre	ADJ
cana-4847	141	34	-	-	ADJ
cana-4847	141	35	trained	train	VERB
cana-4847	141	36	weights	weight	NOUN
cana-4847	141	37	.	.	PUNCT
cana-4847	142	1	initialize	initialize	VERB
cana-4847	142	2	the	the	DET
cana-4847	142	3	dense	dense	ADJ
cana-4847	142	4	layer	layer	NOUN
cana-4847	142	5	randomly	randomly	ADV
cana-4847	142	6	,	,	PUNCT
cana-4847	142	7	fed	feed	VERB
cana-4847	142	8	it	it	PRON
cana-4847	142	9	our	our	PRON
cana-4847	142	10	skin	skin	NOUN
cana-4847	142	11	disease	disease	NOUN
cana-4847	142	12	dataset	dataset	VERB
cana-4847	142	13	,	,	PUNCT
cana-4847	142	14	and	and	CCONJ
cana-4847	142	15	then	then	ADV
cana-4847	142	16	fine	fine	ADV
cana-4847	142	17	-	-	PUNCT
cana-4847	142	18	tuned	tune	VERB
cana-4847	142	19	the	the	DET
cana-4847	142	20	related	related	ADJ
cana-4847	142	21	weights	weight	NOUN
cana-4847	142	22	using	use	VERB
cana-4847	142	23	optimization	optimization	NOUN
cana-4847	142	24	techniques	technique	NOUN
cana-4847	142	25	through	through	ADP
cana-4847	142	26	back	back	ADJ
cana-4847	142	27	-	-	PUNCT
cana-4847	142	28	propagation	propagation	NOUN
cana-4847	142	29	.	.	PUNCT
cana-4847	143	1	in	in	ADP
cana-4847	143	2	this	this	DET
cana-4847	143	3	manner	manner	NOUN
cana-4847	143	4	,	,	PUNCT
cana-4847	143	5	the	the	DET
cana-4847	143	6	strengths	strength	NOUN
cana-4847	143	7	of	of	ADP
cana-4847	143	8	resnet-50	resnet-50	PROPN
cana-4847	143	9	was	be	AUX
cana-4847	143	10	leveraged	leveraged	ADJ
cana-4847	143	11	and	and	CCONJ
cana-4847	143	12	accomplished	accomplished	ADJ
cana-4847	143	13	transfer	transfer	NOUN
cana-4847	143	14	learning	learning	NOUN
cana-4847	143	15	for	for	ADP
cana-4847	143	16	skin	skin	NOUN
cana-4847	143	17	disease	disease	NOUN
cana-4847	143	18	classification	classification	NOUN
cana-4847	143	19	.	.	PUNCT
cana-4847	144	1	with	with	ADP
cana-4847	144	2	the	the	DET
cana-4847	144	3	help	help	NOUN
cana-4847	144	4	of	of	ADP
cana-4847	144	5	resnet-50	resnet-50	PROPN
cana-4847	144	6	and	and	CCONJ
cana-4847	144	7	after	after	ADP
cana-4847	144	8	fine	fine	ADV
cana-4847	144	9	-	-	PUNCT
cana-4847	144	10	tuning	tuning	NOUN
cana-4847	144	11	for	for	ADP
cana-4847	144	12	our	our	PRON
cana-4847	144	13	very	very	ADJ
cana-4847	144	14	task	task	NOUN
cana-4847	144	15	,	,	PUNCT
cana-4847	144	16	it	it	PRON
cana-4847	144	17	made	make	VERB
cana-4847	144	18	a	a	DET
cana-4847	144	19	fairly	fairly	ADV
cana-4847	144	20	strong	strong	ADJ
cana-4847	144	21	model	model	NOUN
cana-4847	144	22	good	good	ADJ
cana-4847	144	23	at	at	ADP
cana-4847	144	24	classifying	classify	VERB
cana-4847	144	25	the	the	DET
cana-4847	144	26	diseases	disease	NOUN
cana-4847	144	27	as	as	ADV
cana-4847	144	28	such	such	ADJ
cana-4847	144	29	.	.	PUNCT
cana-4847	145	1	as	as	SCONJ
cana-4847	145	2	it	it	PRON
cana-4847	145	3	stands	stand	VERB
cana-4847	145	4	out	out	ADV
cana-4847	145	5	here	here	ADV
cana-4847	145	6	,	,	PUNCT
cana-4847	145	7	an	an	DET
cana-4847	145	8	approach	approach	NOUN
cana-4847	145	9	using	use	VERB
cana-4847	145	10	a	a	DET
cana-4847	145	11	powerful	powerful	ADJ
cana-4847	145	12	resnet-50	resnet-50	PROPN
cana-4847	145	13	helps	help	VERB
cana-4847	145	14	demonstrate	demonstrate	VERB
cana-4847	145	15	the	the	DET
cana-4847	145	16	strengths	strength	NOUN
cana-4847	145	17	of	of	ADP
cana-4847	145	18	transfer	transfer	NOUN
cana-4847	145	19	learning	learning	NOUN
cana-4847	145	20	in	in	ADP
cana-4847	145	21	handling	handle	VERB
cana-4847	145	22	big	big	ADJ
cana-4847	145	23	complex	complex	ADJ
cana-4847	145	24	medical	medical	ADJ
cana-4847	145	25	classifications	classification	NOUN
cana-4847	145	26	using	use	VERB
cana-4847	145	27	deep	deep	ADJ
cana-4847	145	28	networks[19	networks[19	NOUN
cana-4847	145	29	]	]	PUNCT
cana-4847	145	30	.	.	PUNCT
cana-4847	146	1	3.5	3.5	NUM
cana-4847	146	2	optimization	optimization	NOUN
cana-4847	146	3	algorithms	algorithms	NOUN
cana-4847	146	4	optimizers	optimizer	NOUN
cana-4847	146	5	are	be	AUX
cana-4847	146	6	most	most	ADV
cana-4847	146	7	essential	essential	ADJ
cana-4847	146	8	to	to	ADP
cana-4847	146	9	deep	deep	ADJ
cana-4847	146	10	learning	learning	NOUN
cana-4847	146	11	since	since	SCONJ
cana-4847	146	12	they	they	PRON
cana-4847	146	13	work	work	VERB
cana-4847	146	14	behind	behind	ADP
cana-4847	146	15	the	the	DET
cana-4847	146	16	scenes	scene	NOUN
cana-4847	146	17	of	of	ADP
cana-4847	146	18	weights	weight	NOUN
cana-4847	146	19	and	and	CCONJ
cana-4847	146	20	learning	learn	VERB
cana-4847	146	21	rates	rate	NOUN
cana-4847	146	22	for	for	ADP
cana-4847	146	23	fine	fine	ADV
cana-4847	146	24	-	-	PUNCT
cana-4847	146	25	tuning	tune	VERB
cana-4847	146	26	those	those	PRON
cana-4847	146	27	behind	behind	ADP
cana-4847	146	28	convolutional	convolutional	ADJ
cana-4847	146	29	neural	neural	ADJ
cana-4847	146	30	networks	network	NOUN
cana-4847	146	31	,	,	PUNCT
cana-4847	146	32	or	or	CCONJ
cana-4847	146	33	cnns	cnn	NOUN
cana-4847	146	34	.	.	PUNCT
cana-4847	147	1	adam	adam	PROPN
cana-4847	147	2	optimizer	optimizer	PROPN
cana-4847	147	3	:	:	PUNCT
cana-4847	147	4	adaptive	adaptive	ADJ
cana-4847	147	5	moment	moment	NOUN
cana-4847	147	6	estimation	estimation	NOUN
cana-4847	147	7	adam	adam	PROPN
cana-4847	147	8	is	be	AUX
cana-4847	147	9	an	an	DET
cana-4847	147	10	optimizer	optimizer	NOUN
cana-4847	147	11	that	that	PRON
cana-4847	147	12	utilizes	utilize	VERB
cana-4847	147	13	the	the	DET
cana-4847	147	14	learning	learning	NOUN
cana-4847	147	15	process	process	NOUN
cana-4847	147	16	as	as	ADP
cana-4847	147	17	the	the	DET
cana-4847	147	18	foundation	foundation	NOUN
cana-4847	147	19	for	for	ADP
cana-4847	147	20	a	a	DET
cana-4847	147	21	modification	modification	NOUN
cana-4847	147	22	in	in	ADP
cana-4847	147	23	the	the	DET
cana-4847	147	24	learning	learning	NOUN
cana-4847	147	25	rate	rate	NOUN
cana-4847	147	26	.	.	PUNCT
cana-4847	148	1	it	it	PRON
cana-4847	148	2	adjusts	adjust	VERB
cana-4847	148	3	each	each	DET
cana-4847	148	4	parameter	parameter	NOUN
cana-4847	148	5	as	as	ADP
cana-4847	148	6	an	an	DET
cana-4847	148	7	individual	individual	NOUN
cana-4847	148	8	in	in	ADP
cana-4847	148	9	equations	equation	NOUN
cana-4847	148	10	(	(	PUNCT
cana-4847	148	11	i	i	NOUN
cana-4847	148	12	)	)	PUNCT
cana-4847	148	13	to	to	ADP
cana-4847	148	14	(	(	PUNCT
cana-4847	148	15	iv	iv	X
cana-4847	148	16	)	)	PUNCT
cana-4847	148	17	.	.	PUNCT
cana-4847	149	1	it	it	PRON
cana-4847	149	2	maintains	maintain	VERB
cana-4847	149	3	the	the	DET
cana-4847	149	4	exponentially	exponentially	ADV
cana-4847	149	5	decaying	decay	VERB
cana-4847	149	6	past	past	ADJ
cana-4847	149	7	gradients	gradient	NOUN
cana-4847	149	8	and	and	CCONJ
cana-4847	149	9	maintains	maintain	VERB
cana-4847	149	10	the	the	DET
cana-4847	149	11	average	average	NOUN
cana-4847	149	12	of	of	ADP
cana-4847	149	13	past	past	ADJ
cana-4847	149	14	squared	square	VERB
cana-4847	149	15	gradients	gradient	NOUN
cana-4847	149	16	too	too	ADV
cana-4847	149	17	.	.	PUNCT
cana-4847	150	1	the	the	DET
cana-4847	150	2	equations	equation	NOUN
cana-4847	150	3	as	as	SCONJ
cana-4847	150	4	presented	present	VERB
cana-4847	150	5	in	in	ADP
cana-4847	150	6	(	(	PUNCT
cana-4847	150	7	i	i	NOUN
cana-4847	150	8	)	)	PUNCT
cana-4847	150	9	to	to	ADP
cana-4847	150	10	(	(	PUNCT
cana-4847	150	11	iv	iv	X
cana-4847	150	12	)	)	PUNCT
cana-4847	150	13	with	with	ADP
cana-4847	150	14	which	which	PRON
cana-4847	150	15	the	the	DET
cana-4847	150	16	adam	adam	PROPN
cana-4847	150	17	optimizer	optimizer	NOUN
cana-4847	150	18	operates	operate	VERB
cana-4847	150	19	to	to	PART
cana-4847	150	20	update	update	VERB
cana-4847	150	21	the	the	DET
cana-4847	150	22	weights	weight	NOUN
cana-4847	150	23	.	.	PUNCT
cana-4847	151	1	vt	vt	PROPN
cana-4847	151	2	=	=	PUNCT
cana-4847	151	3	β1	β1	PROPN
cana-4847	151	4	*	*	PUNCT
cana-4847	151	5	vt-1-(1β1	vt-1-(1β1	NOUN
cana-4847	151	6	)	)	PUNCT
cana-4847	151	7	*	*	PUNCT
cana-4847	152	1	9	9	NUM
cana-4847	152	2	t	t	NOUN
cana-4847	152	3	(	(	PUNCT
cana-4847	152	4	i	i	NOUN
cana-4847	152	5	)	)	PUNCT
cana-4847	152	6	st	st	PROPN
cana-4847	152	7	=	=	PROPN
cana-4847	152	8	β2	β2	PROPN
cana-4847	152	9	*	*	PUNCT
cana-4847	152	10	st-1-(1β2	st-1-(1β2	ADJ
cana-4847	152	11	)	)	PUNCT
cana-4847	152	12	*	*	PUNCT
cana-4847	153	1	gt	gt	PROPN
cana-4847	153	2	(	(	PUNCT
cana-4847	153	3	ii	ii	NOUN
cana-4847	153	4	)	)	PUNCT
cana-4847	153	5	δωt=	δωt=	NOUN
cana-4847	153	6	−η	−η	NOUN
cana-4847	153	7	𝑉𝑡	𝑉𝑡	PROPN
cana-4847	153	8	√	√	NUM
cana-4847	153	9	(	(	PUNCT
cana-4847	153	10	st	st	PROPN
cana-4847	153	11	+	+	CCONJ
cana-4847	153	12	€	€	NOUN
cana-4847	153	13	)	)	PUNCT
cana-4847	153	14	∗	∗	NOUN
cana-4847	153	15	gt	gt	PROPN
cana-4847	153	16	(	(	PUNCT
cana-4847	153	17	iii	iii	NOUN
cana-4847	153	18	)	)	PUNCT
cana-4847	153	19	ωt+1	ωt+1	NUM
cana-4847	153	20	=	=	SYM
cana-4847	153	21	ωt	ωt	PROPN
cana-4847	153	22	+	+	CCONJ
cana-4847	153	23	δωt	δωt	ADJ
cana-4847	153	24	(	(	PUNCT
cana-4847	153	25	iv	iv	X
cana-4847	153	26	)	)	PUNCT
cana-4847	153	27	communications	communication	NOUN
cana-4847	153	28	on	on	ADP
cana-4847	153	29	applied	apply	VERB
cana-4847	153	30	nonlinear	nonlinear	ADJ
cana-4847	153	31	analysis	analysis	NOUN
cana-4847	153	32	issn	issn	NOUN
cana-4847	153	33	:	:	PUNCT
cana-4847	153	34	1074	1074	NUM
cana-4847	153	35	-	-	PUNCT
cana-4847	153	36	133x	133x	NUM
cana-4847	153	37	vol	vol	VERB
cana-4847	153	38	32	32	NUM
cana-4847	153	39	no	no	NOUN
cana-4847	153	40	.	.	PUNCT
cana-4847	154	1	10s	10	NOUN
cana-4847	154	2	(	(	PUNCT
cana-4847	154	3	2025	2025	NUM
cana-4847	154	4	)	)	PUNCT
cana-4847	154	5	574	574	NUM
cana-4847	155	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	155	2	η	η	PROPN
cana-4847	155	3	:	:	PUNCT
cana-4847	155	4	learning	learn	VERB
cana-4847	155	5	rate	rate	NOUN
cana-4847	155	6	initially	initially	ADV
cana-4847	155	7	,	,	PUNCT
cana-4847	155	8	gt	gt	PROPN
cana-4847	155	9	:	:	PUNCT
cana-4847	155	10	gradient	gradient	NOUN
cana-4847	155	11	at	at	ADP
cana-4847	155	12	t	t	PROPN
cana-4847	155	13	along	along	ADP
cana-4847	155	14	ωj	ωj	ADP
cana-4847	155	15	,	,	PUNCT
cana-4847	155	16	vt	vt	NOUN
cana-4847	155	17	:	:	PUNCT
cana-4847	155	18	exponential	exponential	ADJ
cana-4847	155	19	average	average	NOUN
cana-4847	155	20	of	of	ADP
cana-4847	155	21	gradients	gradient	NOUN
cana-4847	155	22	along	along	ADP
cana-4847	155	23	ωj	ωj	ADP
cana-4847	155	24	,	,	PUNCT
cana-4847	155	25	st	st	ADJ
cana-4847	155	26	:	:	PUNCT
cana-4847	155	27	exponential	exponential	ADJ
cana-4847	155	28	average	average	NOUN
cana-4847	155	29	of	of	ADP
cana-4847	155	30	squares	square	NOUN
cana-4847	155	31	of	of	ADP
cana-4847	155	32	gradients	gradient	NOUN
cana-4847	155	33	along	along	ADP
cana-4847	155	34	ωj	ωj	ADP
cana-4847	155	35	,	,	PUNCT
cana-4847	155	36	β1	β1	PROPN
cana-4847	155	37	,	,	PUNCT
cana-4847	155	38	β2	β2	PROPN
cana-4847	155	39	:	:	PUNCT
cana-4847	155	40	нурегparameters	нурегparameter	VERB
cana-4847	155	41	the	the	DET
cana-4847	155	42	adam	adam	PROPN
cana-4847	155	43	optimizer	optimizer	NOUN
cana-4847	155	44	updates	update	VERB
cana-4847	155	45	the	the	DET
cana-4847	155	46	node	node	ADJ
cana-4847	155	47	weight	weight	NOUN
cana-4847	155	48	considering	consider	VERB
cana-4847	155	49	historical	historical	ADJ
cana-4847	155	50	average	average	ADJ
cana-4847	155	51	gradients	gradient	NOUN
cana-4847	155	52	.	.	PUNCT
cana-4847	156	1	the	the	DET
cana-4847	156	2	default	default	NOUN
cana-4847	156	3	for	for	ADP
cana-4847	156	4	β1	β1	PROPN
cana-4847	156	5	,	,	PUNCT
cana-4847	156	6	β2	β2	PROPN
cana-4847	156	7	are	be	AUX
cana-4847	156	8	0.9	0.9	NUM
cana-4847	156	9	&	&	CCONJ
cana-4847	156	10	0.999	0.999	NUM
cana-4847	156	11	respectively	respectively	ADV
cana-4847	156	12	.	.	PUNCT
cana-4847	157	1	softmax	softmax	NOUN
cana-4847	157	2	activation	activation	NOUN
cana-4847	157	3	softmax	softmax	NOUN
cana-4847	157	4	function	function	NOUN
cana-4847	157	5	is	be	AUX
cana-4847	157	6	applied	apply	VERB
cana-4847	157	7	to	to	ADP
cana-4847	157	8	different	different	ADJ
cana-4847	157	9	machine	machine	NOUN
cana-4847	157	10	learning	learn	VERB
cana-4847	157	11	algorithms	algorithm	NOUN
cana-4847	157	12	,	,	PUNCT
cana-4847	157	13	most	most	ADV
cana-4847	157	14	notably	notably	ADV
cana-4847	157	15	in	in	ADP
cana-4847	157	16	a	a	DET
cana-4847	157	17	neural	neural	ADJ
cana-4847	157	18	network	network	NOUN
cana-4847	157	19	classification	classification	NOUN
cana-4847	157	20	.	.	PUNCT
cana-4847	158	1	the	the	DET
cana-4847	158	2	softmax	softmax	NOUN
cana-4847	158	3	function	function	NOUN
cana-4847	158	4	derived	derive	VERB
cana-4847	158	5	in	in	ADP
cana-4847	158	6	the	the	DET
cana-4847	158	7	equations	equation	NOUN
cana-4847	158	8	(	(	PUNCT
cana-4847	158	9	v	v	NOUN
cana-4847	158	10	)	)	PUNCT
cana-4847	158	11	and	and	CCONJ
cana-4847	158	12	(	(	PUNCT
cana-4847	158	13	vi	vi	NOUN
cana-4847	158	14	)	)	PUNCT
cana-4847	158	15	to	to	PART
cana-4847	158	16	is	be	AUX
cana-4847	158	17	applied	apply	VERB
cana-4847	158	18	for	for	ADP
cana-4847	158	19	the	the	DET
cana-4847	158	20	transformation	transformation	NOUN
cana-4847	158	21	of	of	ADP
cana-4847	158	22	raw	raw	ADJ
cana-4847	158	23	scores	score	NOUN
cana-4847	158	24	,	,	PUNCT
cana-4847	158	25	or	or	CCONJ
cana-4847	158	26	neural	neural	ADJ
cana-4847	158	27	network	network	NOUN
cana-4847	158	28	logits	logit	NOUN
cana-4847	158	29	into	into	ADP
cana-4847	158	30	probabilities	probability	NOUN
cana-4847	158	31	.	.	PUNCT
cana-4847	159	1	it	it	PRON
cana-4847	159	2	maintains	maintain	VERB
cana-4847	159	3	the	the	DET
cana-4847	159	4	values	value	NOUN
cana-4847	159	5	of	of	ADP
cana-4847	159	6	the	the	DET
cana-4847	159	7	outputs	output	NOUN
cana-4847	159	8	within	within	ADP
cana-4847	159	9	the	the	DET
cana-4847	159	10	interval	interval	NOUN
cana-4847	159	11	(	(	PUNCT
cana-4847	159	12	0	0	NUM
cana-4847	159	13	,	,	PUNCT
cana-4847	159	14	1	1	NUM
cana-4847	159	15	)	)	PUNCT
cana-4847	159	16	and	and	CCONJ
cana-4847	159	17	sums	sum	NOUN
cana-4847	159	18	to	to	ADP
cana-4847	159	19	1	1	NUM
cana-4847	159	20	,	,	PUNCT
cana-4847	159	21	thus	thus	ADV
cana-4847	159	22	it	it	PRON
cana-4847	159	23	can	can	AUX
cana-4847	159	24	be	be	AUX
cana-4847	159	25	treated	treat	VERB
cana-4847	159	26	as	as	ADP
cana-4847	159	27	probabilities	probability	NOUN
cana-4847	159	28	these	these	DET
cana-4847	159	29	output	output	NOUN
cana-4847	159	30	values	value	NOUN
cana-4847	159	31	.	.	PUNCT
cana-4847	160	1	it	it	PRON
cana-4847	160	2	is	be	AUX
cana-4847	160	3	used	use	VERB
cana-4847	160	4	to	to	PART
cana-4847	160	5	solve	solve	VERB
cana-4847	160	6	the	the	DET
cana-4847	160	7	multi	multi	ADJ
cana-4847	160	8	-	-	ADJ
cana-4847	160	9	class	class	ADJ
cana-4847	160	10	classification	classification	NOUN
cana-4847	160	11	problem	problem	NOUN
cana-4847	160	12	.	.	PUNCT
cana-4847	161	1	derivative	derivative	NOUN
cana-4847	161	2	of	of	ADP
cana-4847	161	3	softmax	softmax	NOUN
cana-4847	161	4	let	let	VERB
cana-4847	161	5	's	us	PRON
cana-4847	161	6	compute	compute	VERB
cana-4847	161	7	djsi	djsi	NOUN
cana-4847	161	8	for	for	ADP
cana-4847	161	9	arbitrary	arbitrary	ADJ
cana-4847	161	10	i	i	PRON
cana-4847	161	11	and	and	CCONJ
cana-4847	161	12	j	j	NOUN
cana-4847	161	13	:	:	PUNCT
cana-4847	161	14	𝐷𝑗𝑆𝑖	𝐷𝑗𝑆𝑖	PROPN
cana-4847	161	15	=	=	PUNCT
cana-4847	161	16	𝜕𝑠𝑖	𝜕𝑠𝑖	VERB
cana-4847	161	17	𝜕𝑎𝑗	𝜕𝑎𝑗	PUNCT
cana-4847	162	1	=	=	PRON
cana-4847	162	2	𝜕	𝜕	NOUN
cana-4847	162	3	𝑒𝑎𝑖	𝑒𝑎𝑖	ADV
cana-4847	162	4	∑	∑	ADP
cana-4847	162	5	𝑒𝑎𝑘	𝑒𝑎𝑘	PRON
cana-4847	162	6	𝑁	𝑁	PROPN
cana-4847	162	7	𝑘=1	𝑘=1	PROPN
cana-4847	162	8	𝜕𝑎𝑗	𝜕𝑎𝑗	PUNCT
cana-4847	162	9	(	(	PUNCT
cana-4847	162	10	v	v	NOUN
cana-4847	162	11	)	)	PUNCT
cana-4847	162	12	using	use	VERB
cana-4847	162	13	the	the	DET
cana-4847	162	14	quotient	quotient	NOUN
cana-4847	162	15	rule	rule	NOUN
cana-4847	162	16	of	of	ADP
cana-4847	162	17	derivatives	derivative	NOUN
cana-4847	162	18	.	.	PUNCT
cana-4847	163	1	for	for	ADP
cana-4847	163	2	:	:	PUNCT
cana-4847	163	3	𝑓′	𝑓′	NOUN
cana-4847	163	4	=	=	SYM
cana-4847	163	5	𝑔(𝑥	𝑔(𝑥	NOUN
cana-4847	163	6	)	)	PUNCT
cana-4847	163	7	ℎ(𝑥	ℎ(𝑥	NUM
cana-4847	163	8	)	)	PUNCT
cana-4847	163	9	𝑓′(𝑥	𝑓′(𝑥	PROPN
cana-4847	163	10	)	)	PUNCT
cana-4847	163	11	=	=	SYM
cana-4847	163	12	𝑔′(𝑥)ℎ(𝑥)−ℎ′(𝑥)𝑔(𝑥	𝑔′(𝑥)ℎ(𝑥)−ℎ′(𝑥)𝑔(𝑥	PROPN
cana-4847	163	13	)	)	PUNCT
cana-4847	164	1	[	[	X
cana-4847	164	2	ℎ(𝑥)]^2	ℎ(𝑥)]^2	PROPN
cana-4847	164	3	(	(	PUNCT
cana-4847	164	4	vi	vi	NOUN
cana-4847	164	5	)	)	PUNCT
cana-4847	164	6	in	in	ADP
cana-4847	164	7	our	our	PRON
cana-4847	164	8	case	case	NOUN
cana-4847	164	9	:	:	PUNCT
cana-4847	164	10	gi	gi	X
cana-4847	164	11	=	=	PUNCT
cana-4847	164	12	e	e	X
cana-4847	164	13	ai	ai	VERB
cana-4847	164	14	ℎ𝑖	ℎ𝑖	NOUN
cana-4847	164	15	=	=	PUNCT
cana-4847	164	16	∑	∑	PUNCT
cana-4847	164	17	ⅇ𝑎𝑘	ⅇ𝑎𝑘	ADP
cana-4847	164	18	𝑁	𝑁	PROPN
cana-4847	164	19	𝑘=1	𝑘=1	ADJ
cana-4847	164	20	note	note	NOUN
cana-4847	164	21	that	that	SCONJ
cana-4847	164	22	no	no	ADV
cana-4847	164	23	matter	matter	ADV
cana-4847	164	24	which	which	PRON
cana-4847	164	25	ai	ai	VERB
cana-4847	164	26	we	we	PRON
cana-4847	164	27	compute	compute	VERB
cana-4847	164	28	the	the	DET
cana-4847	164	29	derivative	derivative	NOUN
cana-4847	164	30	of	of	ADP
cana-4847	164	31	ℎ𝑖	ℎ𝑖	NOUN
cana-4847	164	32	present	present	ADJ
cana-4847	164	33	in	in	ADP
cana-4847	164	34	the	the	DET
cana-4847	164	35	equation	equation	NOUN
cana-4847	164	36	(	(	PUNCT
cana-4847	164	37	vi	vi	NOUN
cana-4847	164	38	)	)	PUNCT
cana-4847	164	39	for	for	ADP
cana-4847	164	40	,	,	PUNCT
cana-4847	164	41	the	the	DET
cana-4847	164	42	answer	answer	NOUN
cana-4847	164	43	will	will	AUX
cana-4847	164	44	always	always	ADV
cana-4847	164	45	be	be	AUX
cana-4847	164	46	eaj	eaj	ADJ
cana-4847	164	47	.	.	PUNCT
cana-4847	165	1	this	this	PRON
cana-4847	165	2	is	be	AUX
cana-4847	165	3	not	not	PART
cana-4847	165	4	the	the	DET
cana-4847	165	5	case	case	NOUN
cana-4847	165	6	for	for	ADP
cana-4847	165	7	gi	gi	NOUN
cana-4847	165	8	,	,	PUNCT
cana-4847	165	9	however	however	ADV
cana-4847	165	10	.	.	PUNCT
cana-4847	166	1	the	the	DET
cana-4847	166	2	derivative	derivative	NOUN
cana-4847	166	3	of	of	ADP
cana-4847	166	4	gi	gi	NUM
cana-4847	166	5	w.r.t	w.r.t	PROPN
cana-4847	166	6	.	.	PUNCT
cana-4847	167	1	aj	aj	PROPN
cana-4847	167	2	is	be	AUX
cana-4847	167	3	eaj	eaj	ADJ
cana-4847	167	4	only	only	ADV
cana-4847	167	5	if	if	SCONJ
cana-4847	167	6	i	i	PROPN
cana-4847	167	7	=	=	PROPN
cana-4847	167	8	j	j	PROPN
cana-4847	167	9	,	,	PUNCT
cana-4847	167	10	because	because	SCONJ
cana-4847	167	11	only	only	ADV
cana-4847	167	12	then	then	ADV
cana-4847	167	13	gi	gi	INTJ
cana-4847	167	14	has	have	AUX
cana-4847	167	15	aj	aj	PROPN
cana-4847	167	16	anywhere	anywhere	ADV
cana-4847	167	17	in	in	ADP
cana-4847	167	18	it	it	PRON
cana-4847	167	19	.	.	PUNCT
cana-4847	168	1	otherwise	otherwise	ADV
cana-4847	168	2	,	,	PUNCT
cana-4847	168	3	the	the	DET
cana-4847	168	4	derivative	derivative	NOUN
cana-4847	168	5	is	be	AUX
cana-4847	168	6	0	0	NUM
cana-4847	168	7	.	.	PUNCT
cana-4847	169	1	going	go	VERB
cana-4847	169	2	back	back	ADV
cana-4847	169	3	to	to	ADP
cana-4847	169	4	djsi	djsi	NUM
cana-4847	169	5	;	;	PUNCT
cana-4847	169	6	started	start	VERB
cana-4847	169	7	with	with	ADP
cana-4847	169	8	the	the	DET
cana-4847	169	9	i	i	PROPN
cana-4847	169	10	=	=	PROPN
cana-4847	169	11	j	j	PROPN
cana-4847	169	12	case	case	NOUN
cana-4847	169	13	.	.	PUNCT
cana-4847	170	1	then	then	ADV
cana-4847	170	2	,	,	PUNCT
cana-4847	170	3	using	use	VERB
cana-4847	170	4	the	the	DET
cana-4847	170	5	quotient	quotient	NOUN
cana-4847	170	6	rule	rule	NOUN
cana-4847	170	7	have	have	VERB
cana-4847	170	8	equation	equation	NOUN
cana-4847	170	9	(	(	PUNCT
cana-4847	170	10	iii	iii	NOUN
cana-4847	170	11	)	)	PUNCT
cana-4847	170	12	𝜕	𝜕	NOUN
cana-4847	170	13	𝑒𝑎𝑖	𝑒𝑎𝑖	ADV
cana-4847	170	14	∑	∑	ADP
cana-4847	170	15	𝑒𝑎𝑘	𝑒𝑎𝑘	PRON
cana-4847	170	16	𝑁	𝑁	PROPN
cana-4847	170	17	𝑘=1	𝑘=1	NOUN
cana-4847	170	18	𝜕𝑎𝑗	𝜕𝑎𝑗	PUNCT
cana-4847	171	1	=	=	PRON
cana-4847	171	2	ⅇ𝑎𝑖∑−ⅇ𝑎𝑗ⅇ𝑎𝑖	ⅇ𝑎𝑖∑−ⅇ𝑎𝑗ⅇ𝑎𝑖	PROPN
cana-4847	171	3	𝛴2	𝛴2	NOUN
cana-4847	171	4	(	(	PUNCT
cana-4847	171	5	vii	vii	PROPN
cana-4847	171	6	)	)	PUNCT
cana-4847	171	7	𝜕	𝜕	NOUN
cana-4847	171	8	𝑒𝑎𝑖	𝑒𝑎𝑖	ADV
cana-4847	171	9	∑	∑	ADP
cana-4847	171	10	𝑒𝑎𝑘	𝑒𝑎𝑘	PRON
cana-4847	171	11	𝑁	𝑁	PROPN
cana-4847	171	12	𝑘=1	𝑘=1	NOUN
cana-4847	171	13	𝜕𝑎𝑗	𝜕𝑎𝑗	PUNCT
cana-4847	172	1	=	=	PRON
cana-4847	172	2	ⅇ𝑎𝑖∑	ⅇ𝑎𝑖∑	PROPN
cana-4847	172	3	−	−	PROPN
cana-4847	172	4	ⅇ𝑎𝑗ⅇ𝑎𝑖	ⅇ𝑎𝑗ⅇ𝑎𝑖	ADP
cana-4847	172	5	𝛴2	𝛴2	PROPN
cana-4847	172	6	=	=	PUNCT
cana-4847	172	7	ⅇ𝑎𝑖	ⅇ𝑎𝑖	PROPN
cana-4847	173	1	𝛴	𝛴	PROPN
cana-4847	173	2	𝛴	𝛴	PROPN
cana-4847	173	3	−	−	PROPN
cana-4847	173	4	ⅇ𝑎𝑗	ⅇ𝑎𝑗	NOUN
cana-4847	173	5	𝛴	𝛴	PROPN
cana-4847	173	6	=	=	PROPN
cana-4847	173	7	𝑆𝑖	𝑆𝑖	PROPN
cana-4847	173	8	(	(	PUNCT
cana-4847	173	9	1	1	NUM
cana-4847	173	10	−	−	PROPN
cana-4847	173	11	𝑆𝑗	𝑆𝑗	PROPN
cana-4847	173	12	)	)	PUNCT
cana-4847	173	13	(	(	PUNCT
cana-4847	173	14	viii	viii	NOUN
cana-4847	173	15	)	)	PUNCT
cana-4847	173	16	communications	communication	NOUN
cana-4847	173	17	on	on	ADP
cana-4847	173	18	applied	apply	VERB
cana-4847	173	19	nonlinear	nonlinear	ADJ
cana-4847	173	20	analysis	analysis	NOUN
cana-4847	173	21	issn	issn	NOUN
cana-4847	173	22	:	:	PUNCT
cana-4847	173	23	1074	1074	NUM
cana-4847	173	24	-	-	PUNCT
cana-4847	173	25	133x	133x	NUM
cana-4847	173	26	vol	vol	VERB
cana-4847	173	27	32	32	NUM
cana-4847	173	28	no	no	NOUN
cana-4847	173	29	.	.	PUNCT
cana-4847	174	1	10s	10	NOUN
cana-4847	174	2	(	(	PUNCT
cana-4847	174	3	2025	2025	NUM
cana-4847	174	4	)	)	PUNCT
cana-4847	174	5	575	575	NUM
cana-4847	174	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	174	7	for	for	ADP
cana-4847	174	8	simplicity	simplicity	NOUN
cana-4847	174	9	∑	∑	PUNCT
cana-4847	174	10	stands	stand	VERB
cana-4847	174	11	for	for	ADP
cana-4847	174	12	∑	∑	DET
cana-4847	174	13	ⅇ𝑎𝑘𝑁	ⅇ𝑎𝑘𝑁	NOUN
cana-4847	174	14	𝑘=1	𝑘=1	X
cana-4847	174	15	.	.	PUNCT
cana-4847	175	1	reordering	reorder	VERB
cana-4847	175	2	a	a	DET
cana-4847	175	3	bit	bit	NOUN
cana-4847	175	4	.	.	PUNCT
cana-4847	176	1	the	the	DET
cana-4847	176	2	final	final	ADJ
cana-4847	176	3	formula	formula	NOUN
cana-4847	176	4	expresses	express	VERB
cana-4847	176	5	the	the	DET
cana-4847	176	6	derivative	derivative	NOUN
cana-4847	176	7	in	in	ADP
cana-4847	176	8	terms	term	NOUN
cana-4847	176	9	of	of	ADP
cana-4847	176	10	itself	itself	PRON
cana-4847	176	11	as	as	ADP
cana-4847	176	12	in	in	ADP
cana-4847	176	13	equation	equation	NOUN
cana-4847	176	14	(	(	PUNCT
cana-4847	176	15	ix	ix	ADJ
cana-4847	176	16	)	)	PUNCT
cana-4847	176	17	similarly	similarly	ADV
cana-4847	176	18	,	,	PUNCT
cana-4847	176	19	another	another	DET
cana-4847	176	20	case	case	NOUN
cana-4847	176	21	:	:	PUNCT
cana-4847	176	22	to	to	PART
cana-4847	176	23	summarize	summarize	VERB
cana-4847	176	24	:	:	PUNCT
cana-4847	176	25	observing	observe	VERB
cana-4847	176	26	this	this	DET
cana-4847	176	27	clear	clear	ADJ
cana-4847	176	28	case	case	NOUN
cana-4847	176	29	-	-	PUNCT
cana-4847	176	30	by	by	ADP
cana-4847	176	31	-	-	PUNCT
cana-4847	176	32	case	case	NOUN
cana-4847	176	33	dissection	dissection	NOUN
cana-4847	176	34	,	,	PUNCT
cana-4847	176	35	but	but	CCONJ
cana-4847	176	36	mathematicians	mathematician	NOUN
cana-4847	176	37	are	be	AUX
cana-4847	176	38	the	the	DET
cana-4847	176	39	ones	one	NOUN
cana-4847	176	40	who	who	PRON
cana-4847	176	41	take	take	VERB
cana-4847	176	42	greater	great	ADJ
cana-4847	176	43	delight	delight	NOUN
cana-4847	176	44	in	in	ADP
cana-4847	176	45	being	be	AUX
cana-4847	176	46	succinct	succinct	ADJ
cana-4847	176	47	and	and	CCONJ
cana-4847	176	48	astute	astute	ADJ
cana-4847	176	49	than	than	ADP
cana-4847	176	50	programmers	programmer	NOUN
cana-4847	176	51	.	.	PUNCT
cana-4847	177	1	for	for	ADP
cana-4847	177	2	this	this	DET
cana-4847	177	3	reason	reason	NOUN
cana-4847	177	4	,	,	PUNCT
cana-4847	177	5	several	several	ADJ
cana-4847	177	6	"	"	PUNCT
cana-4847	177	7	condensed	condensed	ADJ
cana-4847	177	8	"	"	PUNCT
cana-4847	177	9	versions	version	NOUN
cana-4847	177	10	of	of	ADP
cana-4847	177	11	the	the	DET
cana-4847	177	12	same	same	ADJ
cana-4847	177	13	equation	equation	NOUN
cana-4847	177	14	can	can	AUX
cana-4847	177	15	be	be	AUX
cana-4847	177	16	found	find	VERB
cana-4847	177	17	in	in	ADP
cana-4847	177	18	different	different	ADJ
cana-4847	177	19	parts	part	NOUN
cana-4847	177	20	of	of	ADP
cana-4847	177	21	the	the	DET
cana-4847	177	22	literature	literature	NOUN
cana-4847	177	23	.	.	PUNCT
cana-4847	178	1	using	use	VERB
cana-4847	178	2	the	the	DET
cana-4847	178	3	kronecker	kronecker	NOUN
cana-4847	178	4	delta	delta	NOUN
cana-4847	178	5	equation	equation	NOUN
cana-4847	178	6	(	(	PUNCT
cana-4847	178	7	x	x	X
cana-4847	178	8	)	)	PUNCT
cana-4847	178	9	function	function	NOUN
cana-4847	178	10	is	be	AUX
cana-4847	178	11	among	among	ADP
cana-4847	178	12	the	the	DET
cana-4847	178	13	most	most	ADV
cana-4847	178	14	popular	popular	ADJ
cana-4847	178	15	ones	one	NOUN
cana-4847	178	16	to	to	PART
cana-4847	178	17	write	write	VERB
cana-4847	178	18	.	.	PUNCT
cana-4847	179	1	which	which	PRON
cana-4847	179	2	is	be	AUX
cana-4847	179	3	the	the	DET
cana-4847	179	4	same	same	ADJ
cana-4847	179	5	thing	thing	NOUN
cana-4847	179	6	,	,	PUNCT
cana-4847	179	7	of	of	ADP
cana-4847	179	8	course	course	NOUN
cana-4847	179	9	.	.	PUNCT
cana-4847	180	1	a	a	DET
cana-4847	180	2	few	few	ADJ
cana-4847	180	3	further	further	ADJ
cana-4847	180	4	formulations	formulation	NOUN
cana-4847	180	5	can	can	AUX
cana-4847	180	6	be	be	AUX
cana-4847	180	7	found	find	VERB
cana-4847	180	8	in	in	ADP
cana-4847	180	9	the	the	DET
cana-4847	180	10	literature	literature	NOUN
cana-4847	180	11	is	be	AUX
cana-4847	180	12	substituting	substitute	VERB
cana-4847	180	13	i	i	PRON
cana-4847	180	14	,	,	PUNCT
cana-4847	180	15	the	the	DET
cana-4847	180	16	identity	identity	NOUN
cana-4847	180	17	matrix	matrix	NOUN
cana-4847	180	18	,	,	PUNCT
cana-4847	180	19	whose	whose	DET
cana-4847	180	20	members	member	NOUN
cana-4847	180	21	express	express	VERB
cana-4847	180	22	𝛿	𝛿	NOUN
cana-4847	180	23	in	in	ADP
cana-4847	180	24	the	the	DET
cana-4847	180	25	matrix	matrix	NOUN
cana-4847	180	26	form	form	NOUN
cana-4847	180	27	,	,	PUNCT
cana-4847	180	28	for	for	ADP
cana-4847	180	29	𝛿	𝛿	ADJ
cana-4847	180	30	by	by	ADP
cana-4847	180	31	matrix	matrix	NOUN
cana-4847	180	32	form	form	NOUN
cana-4847	180	33	of	of	ADP
cana-4847	180	34	jacobian	jacobian	PROPN
cana-4847	180	35	.	.	PUNCT
cana-4847	181	1	instead	instead	ADV
cana-4847	181	2	of	of	ADP
cana-4847	181	3	using	use	VERB
cana-4847	181	4	kronecker	kronecker	NOUN
cana-4847	181	5	delta	delta	NOUN
cana-4847	181	6	,	,	PUNCT
cana-4847	181	7	use	use	VERB
cana-4847	181	8	"	"	PUNCT
cana-4847	181	9	1	1	NUM
cana-4847	181	10	"	"	PUNCT
cana-4847	181	11	as	as	ADP
cana-4847	181	12	the	the	DET
cana-4847	181	13	function	function	NOUN
cana-4847	181	14	name	name	NOUN
cana-4847	181	15	in	in	ADP
cana-4847	181	16	this	this	DET
cana-4847	181	17	way	way	NOUN
cana-4847	181	18	,	,	PUNCT
cana-4847	181	19	𝐷-𝑗.	𝐷-𝑗.	PRON
cana-4847	181	20	,	,	PUNCT
cana-4847	181	21	𝑆-1	𝑆-1	NOUN
cana-4847	181	22	.	.	PUNCT
cana-4847	182	1	=	=	X
cana-4847	182	2	,	,	PUNCT
cana-4847	182	3	𝑆-𝑖.,1	𝑆-𝑖.,1	PROPN
cana-4847	182	4	,	,	PUNCT
cana-4847	182	5	𝑖=𝑗.	𝑖=𝑗.	PRON
cana-4847	182	6	−,𝑠-𝑗	−,𝑠-𝑗	NOUN
cana-4847	182	7	...	...	PUNCT
cana-4847	182	8	in	in	ADP
cana-4847	182	9	this	this	DET
cana-4847	182	10	case	case	NOUN
cana-4847	182	11	,	,	PUNCT
cana-4847	182	12	1(i	1(i	NUM
cana-4847	182	13	=	=	SYM
cana-4847	182	14	j	j	NOUN
cana-4847	182	15	)	)	PUNCT
cana-4847	182	16	denotes	denote	VERB
cana-4847	182	17	a	a	DET
cana-4847	182	18	value	value	NOUN
cana-4847	182	19	of	of	ADP
cana-4847	182	20	1	1	NUM
cana-4847	182	21	when	when	SCONJ
cana-4847	182	22	i	i	PROPN
cana-4847	182	23	=	=	PROPN
cana-4847	182	24	j	j	PROPN
cana-4847	182	25	and	and	CCONJ
cana-4847	182	26	0	0	NUM
cana-4847	182	27	otherwise	otherwise	ADV
cana-4847	182	28	.	.	PUNCT
cana-4847	183	1	when	when	SCONJ
cana-4847	183	2	calculating	calculate	VERB
cana-4847	183	3	more	more	ADV
cana-4847	183	4	complicated	complicated	ADJ
cana-4847	183	5	derivatives	derivative	NOUN
cana-4847	183	6	that	that	PRON
cana-4847	183	7	rely	rely	VERB
cana-4847	183	8	on	on	ADP
cana-4847	183	9	the	the	DET
cana-4847	183	10	softmax	softmax	NOUN
cana-4847	183	11	derivative	derivative	NOUN
cana-4847	183	12	,	,	PUNCT
cana-4847	183	13	the	the	DET
cana-4847	183	14	condensed	condense	VERB
cana-4847	183	15	notation	notation	NOUN
cana-4847	183	16	is	be	AUX
cana-4847	183	17	helpful	helpful	ADJ
cana-4847	183	18	because	because	SCONJ
cana-4847	183	19	otherwise	otherwise	ADV
cana-4847	183	20	,	,	PUNCT
cana-4847	183	21	it	it	PRON
cana-4847	183	22	would	would	AUX
cana-4847	183	23	have	have	VERB
cana-4847	183	24	to	to	PART
cana-4847	183	25	spread	spread	VERB
cana-4847	183	26	the	the	DET
cana-4847	183	27	condition	condition	NOUN
cana-4847	183	28	everywhere	everywhere	ADV
cana-4847	183	29	4	4	NUM
cana-4847	183	30	.	.	PUNCT
cana-4847	183	31	performance	performance	NOUN
cana-4847	183	32	analysis	analysis	NOUN
cana-4847	183	33	a	a	DET
cana-4847	183	34	computer	computer	NOUN
cana-4847	183	35	system	system	NOUN
cana-4847	183	36	with	with	ADP
cana-4847	183	37	an	an	DET
cana-4847	183	38	intel	intel	PROPN
cana-4847	183	39	core	core	PROPN
cana-4847	183	40	i5	i5	PROPN
cana-4847	183	41	processor	processor	NOUN
cana-4847	183	42	,	,	PUNCT
cana-4847	183	43	16	16	NUM
cana-4847	183	44	gb	gb	NOUN
cana-4847	183	45	of	of	ADP
cana-4847	183	46	ram	ram	NOUN
cana-4847	183	47	,	,	PUNCT
cana-4847	183	48	and	and	CCONJ
cana-4847	183	49	nvidia	nvidia	PROPN
cana-4847	183	50	rtx-3050	rtx-3050	PROPN
cana-4847	183	51	graphics	graphic	NOUN
cana-4847	183	52	was	be	AUX
cana-4847	183	53	used	use	VERB
cana-4847	183	54	for	for	ADP
cana-4847	183	55	the	the	DET
cana-4847	183	56	execution	execution	NOUN
cana-4847	183	57	.	.	PUNCT
cana-4847	184	1	the	the	DET
cana-4847	184	2	models	model	NOUN
cana-4847	184	3	have	have	AUX
cana-4847	184	4	been	be	AUX
cana-4847	184	5	collaboratively	collaboratively	ADV
cana-4847	184	6	trained	train	VERB
cana-4847	184	7	using	use	VERB
cana-4847	184	8	the	the	DET
cana-4847	184	9	keras	keras	PROPN
cana-4847	184	10	framework	framework	NOUN
cana-4847	184	11	with	with	ADP
cana-4847	184	12	a	a	DET
cana-4847	184	13	tensorflow	tensorflow	NOUN
cana-4847	184	14	.	.	PUNCT
cana-4847	185	1	the	the	DET
cana-4847	185	2	information	information	NOUN
cana-4847	185	3	has	have	AUX
cana-4847	185	4	been	be	AUX
cana-4847	185	5	split	split	VERB
cana-4847	185	6	80–20	80–20	NUM
cana-4847	185	7	for	for	ADP
cana-4847	185	8	training	training	NOUN
cana-4847	185	9	and	and	CCONJ
cana-4847	185	10	validation	validation	NOUN
cana-4847	185	11	respectively	respectively	ADV
cana-4847	185	12	.	.	PUNCT
cana-4847	186	1	813	813	NUM
cana-4847	186	2	images	image	NOUN
cana-4847	186	3	have	have	AUX
cana-4847	186	4	been	be	AUX
cana-4847	186	5	added	add	VERB
cana-4847	186	6	for	for	ADP
cana-4847	186	7	model	model	NOUN
cana-4847	186	8	testing.20	testing.20	NOUN
cana-4847	186	9	-	-	PUNCT
cana-4847	186	10	epochs	epochs	ADJ
cana-4847	186	11	2	2	NUM
cana-4847	186	12	-	-	ADJ
cana-4847	186	13	fold	fold	ADJ
cana-4847	186	14	cross	cross	NOUN
cana-4847	186	15	validation	validation	NOUN
cana-4847	186	16	has	have	AUX
cana-4847	186	17	been	be	AUX
cana-4847	186	18	considered	consider	VERB
cana-4847	186	19	at	at	ADP
cana-4847	186	20	training	training	NOUN
cana-4847	186	21	and	and	CCONJ
cana-4847	186	22	validation	validation	NOUN
cana-4847	186	23	.	.	PUNCT
cana-4847	187	1	for	for	ADP
cana-4847	187	2	updating	update	VERB
cana-4847	187	3	the	the	DET
cana-4847	187	4	weights	weight	NOUN
cana-4847	187	5	adam	adam	PROPN
cana-4847	187	6	optimizer	optimizer	NOUN
cana-4847	187	7	algorithm	algorithm	NOUN
cana-4847	187	8	has	have	AUX
cana-4847	187	9	been	be	AUX
cana-4847	187	10	used	use	VERB
cana-4847	187	11	.	.	PUNCT
cana-4847	188	1	the	the	DET
cana-4847	188	2	hyper	hyper	ADJ
cana-4847	188	3	parameters	parameter	NOUN
cana-4847	188	4	used	use	VERB
cana-4847	188	5	are	be	AUX
cana-4847	188	6	as	as	SCONJ
cana-4847	188	7	follows	follow	VERB
cana-4847	188	8	:	:	PUNCT
cana-4847	188	9	inputimagesize:240	inputimagesize:240	X
cana-4847	188	10	*	*	NOUN
cana-4847	188	11	240	240	NUM
cana-4847	188	12	,	,	PUNCT
cana-4847	188	13	epoch	epoch	NOUN
cana-4847	188	14	:	:	PUNCT
cana-4847	188	15	20	20	NUM
cana-4847	188	16	,	,	PUNCT
cana-4847	188	17	learning	learn	VERB
cana-4847	188	18	rate	rate	NOUN
cana-4847	188	19	is	be	AUX
cana-4847	188	20	0.0001	0.0001	NUM
cana-4847	188	21	with	with	ADP
cana-4847	188	22	softmax	softmax	NOUN
cana-4847	188	23	classifier	classifier	NOUN
cana-4847	188	24	and	and	CCONJ
cana-4847	188	25	adam	adam	PROPN
cana-4847	188	26	optimizer	optimizer	NOUN
cana-4847	188	27	has	have	AUX
cana-4847	188	28	been	be	AUX
cana-4847	188	29	used	use	VERB
cana-4847	188	30	.	.	PUNCT
cana-4847	189	1	𝐷𝑗𝑆𝑖	𝐷𝑗𝑆𝑖	NOUN
cana-4847	189	2	=	=	SYM
cana-4847	189	3	𝑖(𝛿𝑖𝑗	𝑖(𝛿𝑖𝑗	PROPN
cana-4847	190	1	−	−	NOUN
cana-4847	190	2	𝑠𝑗)𝛿𝑖𝑗	𝑠𝑗)𝛿𝑖𝑗	NOUN
cana-4847	191	1	=	=	PRON
cana-4847	191	2	{	{	PUNCT
cana-4847	191	3	1	1	NUM
cana-4847	191	4	𝑖	𝑖	X
cana-4847	191	5	=	=	PUNCT
cana-4847	191	6	𝑗	𝑗	PROPN
cana-4847	191	7	0	0	NUM
cana-4847	191	8	𝑖	𝑖	SYM
cana-4847	191	9	≠	≠	PROPN
cana-4847	191	10	𝐽	𝐽	PROPN
cana-4847	191	11	(	(	PUNCT
cana-4847	191	12	x	x	X
cana-4847	191	13	)	)	PUNCT
cana-4847	191	14	𝜕	𝜕	NOUN
cana-4847	191	15	𝑒𝑎𝑖	𝑒𝑎𝑖	ADV
cana-4847	191	16	∑	∑	ADP
cana-4847	191	17	𝑒𝑎𝑘	𝑒𝑎𝑘	PRON
cana-4847	191	18	𝑁	𝑁	PROPN
cana-4847	191	19	𝑘=1	𝑘=1	NOUN
cana-4847	191	20	𝜕𝑎𝑗	𝜕𝑎𝑗	PUNCT
cana-4847	192	1	=	=	SYM
cana-4847	192	2	0	0	NUM
cana-4847	192	3	−	−	PROPN
cana-4847	192	4	ⅇ𝑎𝑗ⅇ𝑎𝑖	ⅇ𝑎𝑗ⅇ𝑎𝑖	ADP
cana-4847	192	5	𝛴2	𝛴2	PROPN
cana-4847	192	6	=	=	PUNCT
cana-4847	192	7	−ⅇ𝑎𝑗	−ⅇ𝑎𝑗	PROPN
cana-4847	193	1	𝛴	𝛴	NOUN
cana-4847	193	2	ⅇ𝑎𝑖	ⅇ𝑎𝑖	ADJ
cana-4847	193	3	𝛴	𝛴	PROPN
cana-4847	193	4	=	=	NOUN
cana-4847	193	5	𝑆𝑗𝑆𝑖	𝑆𝑗𝑆𝑖	PROPN
cana-4847	193	6	𝐷𝑗𝑆𝑖	𝐷𝑗𝑆𝑖	PROPN
cana-4847	193	7	=	=	PUNCT
cana-4847	193	8	{	{	PUNCT
cana-4847	193	9	𝑠𝑖(1	𝑠𝑖(1	PROPN
cana-4847	193	10	−	−	PROPN
cana-4847	193	11	𝑠𝑗	𝑠𝑗	NOUN
cana-4847	193	12	)	)	PUNCT
cana-4847	193	13	𝑖	𝑖	NOUN
cana-4847	194	1	=	=	PUNCT
cana-4847	194	2	𝑗	𝑗	PRON
cana-4847	194	3	−𝑠𝑗𝑠𝑖	−𝑠𝑗𝑠𝑖	NOUN
cana-4847	194	4	𝑖	𝑖	SYM
cana-4847	194	5	≠	≠	PROPN
cana-4847	194	6	𝑗	𝑗	PROPN
cana-4847	194	7	(	(	PUNCT
cana-4847	194	8	ix	ix	ADJ
cana-4847	194	9	)	)	PUNCT
cana-4847	194	10	communications	communication	NOUN
cana-4847	194	11	on	on	ADP
cana-4847	194	12	applied	apply	VERB
cana-4847	194	13	nonlinear	nonlinear	ADJ
cana-4847	194	14	analysis	analysis	NOUN
cana-4847	194	15	issn	issn	NOUN
cana-4847	194	16	:	:	PUNCT
cana-4847	194	17	1074	1074	NUM
cana-4847	194	18	-	-	PUNCT
cana-4847	194	19	133x	133x	NUM
cana-4847	194	20	vol	vol	VERB
cana-4847	194	21	32	32	NUM
cana-4847	194	22	no	no	NOUN
cana-4847	194	23	.	.	PUNCT
cana-4847	195	1	10s	10	NOUN
cana-4847	195	2	(	(	PUNCT
cana-4847	195	3	2025	2025	NUM
cana-4847	195	4	)	)	PUNCT
cana-4847	195	5	576	576	NUM
cana-4847	195	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	195	7	4.1	4.1	NUM
cana-4847	195	8	cnn	cnn	PROPN
cana-4847	195	9	performance	performance	NOUN
cana-4847	195	10	analysis	analysis	NOUN
cana-4847	195	11	of	of	ADP
cana-4847	195	12	training	training	NOUN
cana-4847	195	13	accuracy	accuracy	NOUN
cana-4847	195	14	,	,	PUNCT
cana-4847	195	15	validation	validation	NOUN
cana-4847	195	16	accuracy	accuracy	NOUN
cana-4847	195	17	,	,	PUNCT
cana-4847	195	18	test	test	NOUN
cana-4847	195	19	accuracy	accuracy	NOUN
cana-4847	195	20	,	,	PUNCT
cana-4847	195	21	and	and	CCONJ
cana-4847	195	22	confusion	confusion	NOUN
cana-4847	195	23	matrices	matrix	NOUN
cana-4847	195	24	in	in	ADP
cana-4847	195	25	the	the	DET
cana-4847	195	26	table	table	NOUN
cana-4847	195	27	2	2	NUM
cana-4847	195	28	,	,	PUNCT
cana-4847	195	29	comparisons	comparison	NOUN
cana-4847	195	30	of	of	ADP
cana-4847	195	31	inception	inception	ADJ
cana-4847	195	32	resnet	resnet	PROPN
cana-4847	195	33	v2	v2	PROPN
cana-4847	195	34	,	,	PUNCT
cana-4847	195	35	resnet50	resnet50	NOUN
cana-4847	195	36	,	,	PUNCT
cana-4847	195	37	for	for	ADP
cana-4847	195	38	skin	skin	NOUN
cana-4847	195	39	disease	disease	NOUN
cana-4847	195	40	classification	classification	NOUN
cana-4847	195	41	across	across	ADP
cana-4847	195	42	tasks	task	NOUN
cana-4847	195	43	involving	involve	VERB
cana-4847	195	44	two	two	NUM
cana-4847	195	45	are	be	AUX
cana-4847	195	46	present	present	ADJ
cana-4847	195	47	.	.	PUNCT
cana-4847	196	1	for	for	ADP
cana-4847	196	2	two	two	NUM
cana-4847	196	3	-	-	PUNCT
cana-4847	196	4	class	class	NOUN
cana-4847	196	5	classification	classification	NOUN
cana-4847	196	6	,	,	PUNCT
cana-4847	196	7	all	all	DET
cana-4847	196	8	models	model	NOUN
cana-4847	196	9	achieved	achieve	VERB
cana-4847	196	10	near	near	ADV
cana-4847	196	11	-	-	PUNCT
cana-4847	196	12	perfect	perfect	ADJ
cana-4847	196	13	training	training	NOUN
cana-4847	196	14	accuracy	accuracy	NOUN
cana-4847	196	15	(	(	PUNCT
cana-4847	196	16	~99	~99	NUM
cana-4847	196	17	%	%	NOUN
cana-4847	196	18	)	)	PUNCT
cana-4847	196	19	.	.	PUNCT
cana-4847	197	1	inception	inception	NOUN
cana-4847	197	2	resnet	resnet	NOUN
cana-4847	197	3	v2	v2	PROPN
cana-4847	197	4	and	and	CCONJ
cana-4847	197	5	resnet50	resnet50	NOUN
cana-4847	197	6	demonstrated	demonstrate	VERB
cana-4847	197	7	the	the	DET
cana-4847	197	8	highest	high	ADJ
cana-4847	197	9	validation	validation	NOUN
cana-4847	197	10	accuracy	accuracy	NOUN
cana-4847	197	11	(	(	PUNCT
cana-4847	197	12	97.1	97.1	NUM
cana-4847	197	13	%	%	NOUN
cana-4847	197	14	)	)	PUNCT
cana-4847	197	15	,	,	PUNCT
cana-4847	197	16	outperforming	outperform	VERB
cana-4847	197	17	resnet50	resnet50	NOUN
cana-4847	197	18	(	(	PUNCT
cana-4847	197	19	97.3	97.3	NUM
cana-4847	197	20	%	%	NOUN
cana-4847	197	21	)	)	PUNCT
cana-4847	197	22	.	.	PUNCT
cana-4847	198	1	inception	inception	NOUN
cana-4847	198	2	resnet	resnet	NOUN
cana-4847	198	3	v2	v2	PROPN
cana-4847	198	4	(	(	PUNCT
cana-4847	198	5	93.0%).overall	93.0%).overall	NOUN
cana-4847	198	6	,	,	PUNCT
cana-4847	198	7	inception	inception	NOUN
cana-4847	198	8	-	-	PUNCT
cana-4847	198	9	based	base	VERB
cana-4847	198	10	models	model	NOUN
cana-4847	198	11	performed	perform	VERB
cana-4847	198	12	best	well	ADV
cana-4847	198	13	in	in	ADP
cana-4847	198	14	simpler	simple	ADJ
cana-4847	198	15	tasks	task	NOUN
cana-4847	198	16	,	,	PUNCT
cana-4847	198	17	while	while	SCONJ
cana-4847	198	18	resnet50	resnet50	NOUN
cana-4847	198	19	generalized	generalize	VERB
cana-4847	198	20	better	well	ADV
cana-4847	198	21	for	for	ADP
cana-4847	198	22	three	three	NUM
cana-4847	198	23	-	-	PUNCT
cana-4847	198	24	class	class	NOUN
cana-4847	198	25	classification	classification	NOUN
cana-4847	198	26	.	.	PUNCT
cana-4847	199	1	table2	table2	NOUN
cana-4847	199	2	:	:	PUNCT
cana-4847	200	1	accuracy	accuracy	NOUN
cana-4847	200	2	of	of	ADP
cana-4847	200	3	various	various	ADJ
cana-4847	200	4	cnn	cnn	PROPN
cana-4847	200	5	architectures	architecture	NOUN
cana-4847	200	6	using	use	VERB
cana-4847	200	7	adam	adam	PROPN
cana-4847	200	8	fig	fig	PROPN
cana-4847	200	9	4	4	NUM
cana-4847	200	10	:	:	PUNCT
cana-4847	200	11	accuracy	accuracy	NOUN
cana-4847	200	12	graph	graph	NOUN
cana-4847	200	13	and	and	CCONJ
cana-4847	200	14	confusion	confusion	NOUN
cana-4847	200	15	matrix	matrix	NOUN
cana-4847	200	16	of	of	ADP
cana-4847	200	17	inceptionresnetv2	inceptionresnetv2	NOUN
cana-4847	200	18	with	with	ADP
cana-4847	200	19	two	two	NUM
cana-4847	200	20	classifications	classification	NOUN
cana-4847	200	21	.	.	PUNCT
cana-4847	201	1	fig	fig	NOUN
cana-4847	201	2	5	5	NUM
cana-4847	201	3	:	:	PUNCT
cana-4847	201	4	accuracy	accuracy	NOUN
cana-4847	201	5	plot	plot	NOUN
cana-4847	201	6	and	and	CCONJ
cana-4847	201	7	confusion	confusion	NOUN
cana-4847	201	8	matrix	matrix	NOUN
cana-4847	201	9	of	of	ADP
cana-4847	201	10	resnet50	resnet50	NOUN
cana-4847	201	11	with	with	ADP
cana-4847	201	12	two	two	NUM
cana-4847	201	13	classes	class	NOUN
cana-4847	201	14	.	.	PUNCT
cana-4847	202	1	architecture	architecture	NOUN
cana-4847	202	2	training	training	NOUN
cana-4847	202	3	accuracy	accuracy	NOUN
cana-4847	202	4	(	(	PUNCT
cana-4847	202	5	%	%	INTJ
cana-4847	202	6	)	)	PUNCT
cana-4847	202	7	validation	validation	NOUN
cana-4847	202	8	accuracy	accuracy	NOUN
cana-4847	202	9	(	(	PUNCT
cana-4847	202	10	%	%	INTJ
cana-4847	202	11	)	)	PUNCT
cana-4847	202	12	test	test	NOUN
cana-4847	202	13	accuracy(%	accuracy(%	ADJ
cana-4847	202	14	)	)	PUNCT
cana-4847	202	15	inception	inception	NOUN
cana-4847	202	16	resnet	resnet	NOUN
cana-4847	202	17	v2	v2	NOUN
cana-4847	202	18	with	with	ADP
cana-4847	202	19	two	two	NUM
cana-4847	202	20	classifications	classification	NOUN
cana-4847	202	21	99.7	99.7	NUM
cana-4847	202	22	97.1	97.1	NUM
cana-4847	202	23	95.8	95.8	NUM
cana-4847	202	24	resnet50	resnet50	NOUN
cana-4847	202	25	with	with	ADP
cana-4847	202	26	two	two	NUM
cana-4847	202	27	classification	classification	NOUN
cana-4847	202	28	99.5	99.5	NUM
cana-4847	202	29	97.3	97.3	NUM
cana-4847	202	30	99.49	99.49	NUM
cana-4847	202	31	communications	communication	NOUN
cana-4847	202	32	on	on	ADP
cana-4847	202	33	applied	apply	VERB
cana-4847	202	34	nonlinear	nonlinear	ADJ
cana-4847	202	35	analysis	analysis	NOUN
cana-4847	202	36	issn	issn	NOUN
cana-4847	202	37	:	:	PUNCT
cana-4847	202	38	1074	1074	NUM
cana-4847	202	39	-	-	PUNCT
cana-4847	202	40	133x	133x	NUM
cana-4847	202	41	vol	vol	VERB
cana-4847	202	42	32	32	NUM
cana-4847	202	43	no	no	NOUN
cana-4847	202	44	.	.	PUNCT
cana-4847	203	1	10s	10	NOUN
cana-4847	203	2	(	(	PUNCT
cana-4847	203	3	2025	2025	NUM
cana-4847	203	4	)	)	PUNCT
cana-4847	203	5	577	577	NUM
cana-4847	203	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	203	7	figure	figure	NOUN
cana-4847	203	8	4	4	NUM
cana-4847	203	9	shows	show	VERB
cana-4847	203	10	the	the	DET
cana-4847	203	11	learning	learn	VERB
cana-4847	203	12	curve	curve	NOUN
cana-4847	203	13	of	of	ADP
cana-4847	203	14	the	the	DET
cana-4847	203	15	first	first	ADJ
cana-4847	203	16	model	model	NOUN
cana-4847	203	17	and	and	CCONJ
cana-4847	203	18	its	its	PRON
cana-4847	203	19	confusion	confusion	NOUN
cana-4847	203	20	matrix	matrix	NOUN
cana-4847	203	21	.	.	PUNCT
cana-4847	204	1	figure	figure	NOUN
cana-4847	204	2	4	4	NUM
cana-4847	204	3	,	,	PUNCT
cana-4847	204	4	the	the	DET
cana-4847	204	5	training	training	NOUN
cana-4847	204	6	accuracy	accuracy	NOUN
cana-4847	204	7	has	have	AUX
cana-4847	204	8	been	be	AUX
cana-4847	204	9	steadily	steadily	ADV
cana-4847	204	10	increasing	increase	VERB
cana-4847	204	11	in	in	ADP
cana-4847	204	12	figure	figure	NOUN
cana-4847	204	13	4	4	NUM
cana-4847	204	14	,	,	PUNCT
cana-4847	204	15	to	to	ADP
cana-4847	204	16	nearly	nearly	ADV
cana-4847	204	17	100	100	NUM
cana-4847	204	18	%	%	NOUN
cana-4847	204	19	after	after	ADP
cana-4847	204	20	just	just	ADV
cana-4847	204	21	a	a	DET
cana-4847	204	22	few	few	ADJ
cana-4847	204	23	epochs	epoch	NOUN
cana-4847	204	24	show	show	VERB
cana-4847	204	25	that	that	SCONJ
cana-4847	204	26	,	,	PUNCT
cana-4847	204	27	the	the	DET
cana-4847	204	28	model	model	NOUN
cana-4847	204	29	could	could	AUX
cana-4847	204	30	fit	fit	VERB
cana-4847	204	31	training	training	NOUN
cana-4847	204	32	data	datum	NOUN
cana-4847	204	33	very	very	ADV
cana-4847	204	34	well	well	ADV
cana-4847	204	35	.	.	PUNCT
cana-4847	205	1	validation	validation	NOUN
cana-4847	205	2	accuracy	accuracy	NOUN
cana-4847	205	3	is	be	AUX
cana-4847	205	4	very	very	ADV
cana-4847	205	5	close	close	ADJ
cana-4847	205	6	to	to	ADP
cana-4847	205	7	being	be	AUX
cana-4847	205	8	constant	constant	ADJ
cana-4847	205	9	at	at	ADP
cana-4847	205	10	levels	level	NOUN
cana-4847	205	11	near	near	ADP
cana-4847	205	12	training	training	NOUN
cana-4847	205	13	accuracy	accuracy	NOUN
cana-4847	205	14	,	,	PUNCT
cana-4847	205	15	thus	thus	ADV
cana-4847	205	16	suggesting	suggest	VERB
cana-4847	205	17	minimal	minimal	ADJ
cana-4847	205	18	overfitting	overfitting	NOUN
cana-4847	205	19	.	.	PUNCT
cana-4847	206	1	the	the	DET
cana-4847	206	2	test	test	NOUN
cana-4847	206	3	accuracy	accuracy	NOUN
cana-4847	206	4	curve	curve	NOUN
cana-4847	206	5	,	,	PUNCT
cana-4847	206	6	however	however	ADV
cana-4847	206	7	has	have	VERB
cana-4847	206	8	some	some	DET
cana-4847	206	9	oscillations	oscillation	NOUN
cana-4847	206	10	,	,	PUNCT
cana-4847	206	11	indicating	indicate	VERB
cana-4847	206	12	that	that	SCONJ
cana-4847	206	13	even	even	ADV
cana-4847	206	14	though	though	SCONJ
cana-4847	206	15	the	the	DET
cana-4847	206	16	model	model	NOUN
cana-4847	206	17	was	be	AUX
cana-4847	206	18	accurate	accurate	ADJ
cana-4847	206	19	on	on	ADP
cana-4847	206	20	new	new	ADJ
cana-4847	206	21	data	datum	NOUN
cana-4847	206	22	,	,	PUNCT
cana-4847	206	23	its	its	PRON
cana-4847	206	24	generalization	generalization	NOUN
cana-4847	206	25	performance	performance	NOUN
cana-4847	206	26	sometimes	sometimes	ADV
cana-4847	206	27	varied	varied	ADJ
cana-4847	206	28	.	.	PUNCT
cana-4847	207	1	in	in	ADP
cana-4847	207	2	figure	figure	NOUN
cana-4847	207	3	4	4	NUM
cana-4847	207	4	,	,	PUNCT
cana-4847	207	5	the	the	DET
cana-4847	207	6	confusion	confusion	NOUN
cana-4847	207	7	matrix	matrix	NOUN
cana-4847	207	8	reveals	reveal	VERB
cana-4847	207	9	an	an	DET
cana-4847	207	10	overwhelming	overwhelming	ADJ
cana-4847	207	11	amount	amount	NOUN
cana-4847	207	12	of	of	ADP
cana-4847	207	13	correct	correct	ADJ
cana-4847	207	14	predictions	prediction	NOUN
cana-4847	207	15	due	due	ADJ
cana-4847	207	16	to	to	ADP
cana-4847	207	17	high	high	ADJ
cana-4847	207	18	values	value	NOUN
cana-4847	207	19	on	on	ADP
cana-4847	207	20	the	the	DET
cana-4847	207	21	diagonal	diagonal	NOUN
cana-4847	207	22	.	.	PUNCT
cana-4847	208	1	a	a	DET
cana-4847	208	2	few	few	ADJ
cana-4847	208	3	low	low	ADJ
cana-4847	208	4	values	value	NOUN
cana-4847	208	5	off	off	ADP
cana-4847	208	6	the	the	DET
cana-4847	208	7	diagonal	diagonal	ADJ
cana-4847	208	8	indicate	indicate	VERB
cana-4847	208	9	small	small	ADJ
cana-4847	208	10	classification	classification	NOUN
cana-4847	208	11	errors	error	NOUN
cana-4847	208	12	but	but	CCONJ
cana-4847	208	13	overall	overall	ADJ
cana-4847	208	14	is	be	AUX
cana-4847	208	15	high	high	ADJ
cana-4847	208	16	classification	classification	NOUN
cana-4847	208	17	accuracy	accuracy	NOUN
cana-4847	208	18	.	.	PUNCT
cana-4847	209	1	figures	figure	NOUN
cana-4847	209	2	5	5	NUM
cana-4847	209	3	demonstrate	demonstrate	VERB
cana-4847	209	4	a	a	DET
cana-4847	209	5	characteristic	characteristic	ADJ
cana-4847	209	6	delayed	delay	VERB
cana-4847	209	7	learning	learning	NOUN
cana-4847	209	8	curve	curve	NOUN
cana-4847	209	9	,	,	PUNCT
cana-4847	209	10	in	in	ADP
cana-4847	209	11	which	which	PRON
cana-4847	209	12	accuracy	accuracy	NOUN
cana-4847	209	13	levels	level	NOUN
cana-4847	209	14	off	off	ADP
cana-4847	209	15	at	at	ADP
cana-4847	209	16	20	20	NUM
cana-4847	209	17	%	%	NOUN
cana-4847	209	18	for	for	ADP
cana-4847	209	19	40	40	NUM
cana-4847	209	20	epochs	epoch	NOUN
cana-4847	209	21	before	before	ADP
cana-4847	209	22	rapidly	rapidly	ADV
cana-4847	209	23	increasing	increase	VERB
cana-4847	209	24	to	to	ADP
cana-4847	209	25	90	90	NUM
cana-4847	209	26	%	%	NOUN
cana-4847	209	27	,	,	PUNCT
cana-4847	209	28	and	and	CCONJ
cana-4847	209	29	eventually	eventually	ADV
cana-4847	209	30	stabilizing	stabilize	VERB
cana-4847	209	31	at	at	ADP
cana-4847	209	32	95	95	NUM
cana-4847	209	33	%	%	NOUN
cana-4847	209	34	with	with	ADP
cana-4847	209	35	strong	strong	ADJ
cana-4847	209	36	diagonal	diagonal	ADJ
cana-4847	209	37	confusion	confusion	NOUN
cana-4847	209	38	matrix	matrix	NOUN
cana-4847	209	39	values	value	NOUN
cana-4847	209	40	,	,	PUNCT
cana-4847	209	41	ultimately	ultimately	ADV
cana-4847	209	42	reaching	reach	VERB
cana-4847	209	43	comparable	comparable	ADJ
cana-4847	209	44	final	final	ADJ
cana-4847	209	45	performance	performance	NOUN
cana-4847	209	46	.	.	PUNCT
cana-4847	210	1	4.2	4.2	NUM
cana-4847	210	2	roc	roc	PROPN
cana-4847	210	3	curve	curve	NOUN
cana-4847	210	4	analysis	analysis	NOUN
cana-4847	210	5	the	the	DET
cana-4847	210	6	model	model	NOUN
cana-4847	210	7	capability	capability	NOUN
cana-4847	210	8	of	of	ADP
cana-4847	210	9	separate	separate	ADJ
cana-4847	210	10	classes	class	NOUN
cana-4847	210	11	are	be	AUX
cana-4847	210	12	measured	measure	VERB
cana-4847	210	13	through	through	ADP
cana-4847	210	14	roc	roc	PROPN
cana-4847	210	15	curves	curve	NOUN
cana-4847	210	16	.	.	PUNCT
cana-4847	211	1	in	in	ADP
cana-4847	211	2	this	this	DET
cana-4847	211	3	article	article	NOUN
cana-4847	211	4	compares	compare	VERB
cana-4847	211	5	two	two	NUM
cana-4847	211	6	deep	deep	ADJ
cana-4847	211	7	networks	network	NOUN
cana-4847	211	8	inceptionresnetv2	inceptionresnetv2	NOUN
cana-4847	211	9	and	and	CCONJ
cana-4847	211	10	resnet50	resnet50	NOUN
cana-4847	211	11	for	for	ADP
cana-4847	211	12	binary	binary	ADJ
cana-4847	211	13	and	and	CCONJ
cana-4847	211	14	multi	multi	ADJ
cana-4847	211	15	-	-	ADJ
cana-4847	211	16	class	class	ADJ
cana-4847	211	17	classification	classification	NOUN
cana-4847	211	18	[	[	X
cana-4847	211	19	13	13	NUM
cana-4847	211	20	]	]	PUNCT
cana-4847	211	21	.	.	PUNCT
cana-4847	212	1	figure	figure	VERB
cana-4847	212	2	6a	6a	NOUN
cana-4847	212	3	.	.	PUNCT
cana-4847	213	1	shows	show	VERB
cana-4847	213	2	the	the	DET
cana-4847	213	3	roc	roc	PROPN
cana-4847	213	4	curve	curve	NOUN
cana-4847	213	5	of	of	ADP
cana-4847	213	6	inceptionresnetv2	inceptionresnetv2	NOUN
cana-4847	213	7	for	for	ADP
cana-4847	213	8	binary	binary	ADJ
cana-4847	213	9	classification	classification	NOUN
cana-4847	213	10	.	.	PUNCT
cana-4847	214	1	highly	highly	ADV
cana-4847	214	2	close	close	ADJ
cana-4847	214	3	to	to	ADP
cana-4847	214	4	the	the	DET
cana-4847	214	5	top	top	ADV
cana-4847	214	6	-	-	PUNCT
cana-4847	214	7	left	left	ADJ
cana-4847	214	8	area	area	NOUN
cana-4847	214	9	,	,	PUNCT
cana-4847	214	10	the	the	DET
cana-4847	214	11	curve	curve	NOUN
cana-4847	214	12	illustrates	illustrate	VERB
cana-4847	214	13	the	the	DET
cana-4847	214	14	balance	balance	NOUN
cana-4847	214	15	between	between	ADP
cana-4847	214	16	true	true	ADJ
cana-4847	214	17	positive	positive	ADJ
cana-4847	214	18	rate	rate	NOUN
cana-4847	214	19	and	and	CCONJ
cana-4847	214	20	false	false	ADJ
cana-4847	214	21	positive	positive	ADJ
cana-4847	214	22	rate	rate	NOUN
cana-4847	214	23	.	.	PUNCT
cana-4847	215	1	the	the	DET
cana-4847	215	2	value	value	NOUN
cana-4847	215	3	of	of	ADP
cana-4847	215	4	auc	auc	NOUN
cana-4847	215	5	for	for	ADP
cana-4847	215	6	this	this	DET
cana-4847	215	7	plot	plot	NOUN
cana-4847	215	8	is	be	AUX
cana-4847	215	9	1.00	1.00	NUM
cana-4847	215	10	,	,	PUNCT
cana-4847	215	11	which	which	PRON
cana-4847	215	12	means	mean	VERB
cana-4847	215	13	a	a	DET
cana-4847	215	14	perfect	perfect	ADJ
cana-4847	215	15	model	model	NOUN
cana-4847	215	16	performance	performance	NOUN
cana-4847	215	17	where	where	SCONJ
cana-4847	215	18	both	both	DET
cana-4847	215	19	classes	class	NOUN
cana-4847	215	20	are	be	AUX
cana-4847	215	21	completely	completely	ADV
cana-4847	215	22	separated	separate	VERB
cana-4847	215	23	with	with	ADP
cana-4847	215	24	no	no	DET
cana-4847	215	25	classification	classification	NOUN
cana-4847	215	26	errors	error	NOUN
cana-4847	215	27	.	.	PUNCT
cana-4847	216	1	figure	figure	NOUN
cana-4847	216	2	6b	6b	NOUN
cana-4847	216	3	.	.	PUNCT
cana-4847	217	1	as	as	ADP
cana-4847	217	2	in	in	ADP
cana-4847	217	3	the	the	DET
cana-4847	217	4	above	above	ADJ
cana-4847	217	5	figure	figure	NOUN
cana-4847	217	6	for	for	ADP
cana-4847	217	7	inceptionresnetv2	inceptionresnetv2	NOUN
cana-4847	217	8	,	,	PUNCT
cana-4847	217	9	the	the	DET
cana-4847	217	10	roc	roc	PROPN
cana-4847	217	11	curve	curve	NOUN
cana-4847	217	12	of	of	ADP
cana-4847	217	13	resnet50	resnet50	NOUN
cana-4847	217	14	on	on	ADP
cana-4847	217	15	the	the	DET
cana-4847	217	16	same	same	ADJ
cana-4847	217	17	binary	binary	ADJ
cana-4847	217	18	classification	classification	NOUN
cana-4847	217	19	task	task	NOUN
cana-4847	217	20	with	with	ADP
cana-4847	217	21	an	an	DET
cana-4847	217	22	auc	auc	ADJ
cana-4847	217	23	value	value	NOUN
cana-4847	217	24	of	of	ADP
cana-4847	217	25	1.00	1.00	NUM
cana-4847	217	26	,	,	PUNCT
cana-4847	217	27	completely	completely	ADV
cana-4847	217	28	follows	follow	VERB
cana-4847	217	29	the	the	DET
cana-4847	217	30	ideal	ideal	ADJ
cana-4847	217	31	path	path	NOUN
cana-4847	217	32	of	of	ADP
cana-4847	217	33	roc	roc	PROPN
cana-4847	217	34	curve	curve	NOUN
cana-4847	217	35	.	.	PUNCT
cana-4847	218	1	this	this	PRON
cana-4847	218	2	means	mean	VERB
cana-4847	218	3	that	that	SCONJ
cana-4847	218	4	resnet50	resnet50	NOUN
cana-4847	218	5	has	have	VERB
cana-4847	218	6	the	the	DET
cana-4847	218	7	same	same	ADJ
cana-4847	218	8	performance	performance	NOUN
cana-4847	218	9	as	as	ADP
cana-4847	218	10	inceptionresnetv2	inceptionresnetv2	NOUN
cana-4847	218	11	,	,	PUNCT
cana-4847	218	12	making	make	VERB
cana-4847	218	13	no	no	DET
cana-4847	218	14	mistakes	mistake	NOUN
cana-4847	218	15	at	at	ADV
cana-4847	218	16	all	all	ADV
cana-4847	218	17	in	in	ADP
cana-4847	218	18	discriminating	discriminate	VERB
cana-4847	218	19	between	between	ADP
cana-4847	218	20	the	the	DET
cana-4847	218	21	two	two	NUM
cana-4847	218	22	classes	class	NOUN
cana-4847	218	23	.	.	PUNCT
cana-4847	219	1	the	the	DET
cana-4847	219	2	comparison	comparison	NOUN
cana-4847	219	3	of	of	ADP
cana-4847	219	4	roc	roc	PROPN
cana-4847	219	5	curves	curve	NOUN
cana-4847	219	6	and	and	CCONJ
cana-4847	219	7	auc	auc	NOUN
cana-4847	219	8	values	value	NOUN
cana-4847	219	9	from	from	ADP
cana-4847	219	10	different	different	ADJ
cana-4847	219	11	models	model	NOUN
cana-4847	219	12	and	and	CCONJ
cana-4847	219	13	tasks	task	NOUN
cana-4847	219	14	indicates	indicate	VERB
cana-4847	219	15	that	that	SCONJ
cana-4847	219	16	inceptionresnetv2	inceptionresnetv2	PROPN
cana-4847	219	17	and	and	CCONJ
cana-4847	219	18	resnet50	resnet50	NOUN
cana-4847	219	19	are	be	AUX
cana-4847	219	20	well	well	ADV
cana-4847	219	21	-	-	PUNCT
cana-4847	219	22	performing	perform	VERB
cana-4847	219	23	on	on	ADP
cana-4847	219	24	both	both	CCONJ
cana-4847	219	25	binary	binary	ADJ
cana-4847	219	26	and	and	CCONJ
cana-4847	219	27	multi	multi	ADJ
cana-4847	219	28	-	-	ADJ
cana-4847	219	29	class	class	ADJ
cana-4847	219	30	classification	classification	NOUN
cana-4847	219	31	tasks	task	NOUN
cana-4847	219	32	.	.	PUNCT
cana-4847	220	1	binary	binary	ADJ
cana-4847	220	2	classification	classification	NOUN
cana-4847	220	3	task	task	NOUN
cana-4847	220	4	-inceptionresnetv2	-inceptionresnetv2	PUNCT
cana-4847	220	5	had	have	VERB
cana-4847	220	6	an	an	DET
cana-4847	220	7	auc	auc	ADJ
cana-4847	220	8	value	value	NOUN
cana-4847	220	9	of	of	ADP
cana-4847	220	10	1.00	1.00	NUM
cana-4847	220	11	,	,	PUNCT
cana-4847	220	12	implying	imply	VERB
cana-4847	220	13	perfect	perfect	ADJ
cana-4847	220	14	separation	separation	NOUN
cana-4847	220	15	of	of	ADP
cana-4847	220	16	the	the	DET
cana-4847	220	17	two	two	NUM
cana-4847	220	18	classes	class	NOUN
cana-4847	220	19	.	.	PUNCT
cana-4847	221	1	-resnet50	-resnet50	PUNCT
cana-4847	221	2	had	have	VERB
cana-4847	221	3	an	an	DET
cana-4847	221	4	auc	auc	ADJ
cana-4847	221	5	value	value	NOUN
cana-4847	221	6	of	of	ADP
cana-4847	221	7	1.00	1.00	NUM
cana-4847	221	8	,	,	PUNCT
cana-4847	221	9	perfect	perfect	ADJ
cana-4847	221	10	to	to	PART
cana-4847	221	11	distinguish	distinguish	VERB
cana-4847	221	12	the	the	DET
cana-4847	221	13	two	two	NUM
cana-4847	221	14	classes	class	NOUN
cana-4847	221	15	with	with	ADP
cana-4847	221	16	no	no	DET
cana-4847	221	17	errors	error	NOUN
cana-4847	221	18	.	.	PUNCT
cana-4847	222	1	6a	6a	NOUN
cana-4847	222	2	)	)	PUNCT
cana-4847	222	3	roc	roc	PROPN
cana-4847	222	4	curve	curve	NOUN
cana-4847	222	5	of	of	ADP
cana-4847	222	6	inceptionresnetv2	inceptionresnetv2	NOUN
cana-4847	222	7	with	with	ADP
cana-4847	222	8	two	two	NUM
cana-4847	222	9	classifications	classification	NOUN
cana-4847	222	10	6b	6b	NUM
cana-4847	222	11	)	)	PUNCT
cana-4847	222	12	resnet50	resnet50	PROPN
cana-4847	222	13	's	's	PART
cana-4847	222	14	roc	roc	PROPN
cana-4847	222	15	curve	curve	NOUN
cana-4847	222	16	with	with	ADP
cana-4847	222	17	two	two	NUM
cana-4847	222	18	classifications	classification	NOUN
cana-4847	222	19	communications	communication	NOUN
cana-4847	222	20	on	on	ADP
cana-4847	222	21	applied	apply	VERB
cana-4847	222	22	nonlinear	nonlinear	ADJ
cana-4847	222	23	analysis	analysis	NOUN
cana-4847	222	24	issn	issn	NOUN
cana-4847	222	25	:	:	PUNCT
cana-4847	222	26	1074	1074	NUM
cana-4847	222	27	-	-	PUNCT
cana-4847	222	28	133x	133x	NUM
cana-4847	222	29	vol	vol	VERB
cana-4847	222	30	32	32	NUM
cana-4847	222	31	no	no	NOUN
cana-4847	222	32	.	.	PUNCT
cana-4847	223	1	10s	10	NOUN
cana-4847	223	2	(	(	PUNCT
cana-4847	223	3	2025	2025	NUM
cana-4847	223	4	)	)	PUNCT
cana-4847	223	5	578	578	NUM
cana-4847	223	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	224	1	they	they	PRON
cana-4847	224	2	differed	differ	VERB
cana-4847	224	3	but	but	CCONJ
cana-4847	224	4	still	still	ADV
cana-4847	224	5	not	not	PART
cana-4847	224	6	very	very	ADV
cana-4847	224	7	different	different	ADJ
cana-4847	224	8	in	in	ADP
cana-4847	224	9	auc	auc	NOUN
cana-4847	224	10	,	,	PUNCT
cana-4847	224	11	in	in	SCONJ
cana-4847	224	12	that	that	PRON
cana-4847	224	13	most	most	ADJ
cana-4847	224	14	of	of	ADP
cana-4847	224	15	the	the	DET
cana-4847	224	16	values	value	NOUN
cana-4847	224	17	in	in	ADP
cana-4847	224	18	some	some	DET
cana-4847	224	19	models	model	NOUN
cana-4847	224	20	had	have	VERB
cana-4847	224	21	an	an	DET
cana-4847	224	22	auc	auc	ADJ
cana-4847	224	23	value	value	NOUN
cana-4847	224	24	of	of	ADP
cana-4847	224	25	1.00	1.00	NUM
cana-4847	224	26	.	.	PUNCT
cana-4847	225	1	the	the	DET
cana-4847	225	2	roc	roc	PROPN
cana-4847	225	3	curves	curve	NOUN
cana-4847	225	4	and	and	CCONJ
cana-4847	225	5	auc	auc	NOUN
cana-4847	225	6	values	value	NOUN
cana-4847	225	7	provided	provide	VERB
cana-4847	225	8	in	in	ADP
cana-4847	225	9	the	the	DET
cana-4847	225	10	results	result	NOUN
cana-4847	225	11	describe	describe	VERB
cana-4847	225	12	how	how	SCONJ
cana-4847	225	13	the	the	DET
cana-4847	225	14	inceptionresnetv2	inceptionresnetv2	ADJ
cana-4847	225	15	and	and	CCONJ
cana-4847	225	16	resnet50	resnet50	NOUN
cana-4847	225	17	models	model	NOUN
cana-4847	225	18	are	be	AUX
cana-4847	225	19	extremely	extremely	ADV
cana-4847	225	20	potent	potent	ADJ
cana-4847	225	21	for	for	ADP
cana-4847	225	22	classifying	classify	VERB
cana-4847	225	23	skin	skin	NOUN
cana-4847	225	24	diseases	disease	NOUN
cana-4847	225	25	.	.	PUNCT
cana-4847	226	1	notable	notable	ADJ
cana-4847	226	2	outcomes	outcome	NOUN
cana-4847	226	3	from	from	ADP
cana-4847	226	4	the	the	DET
cana-4847	226	5	classifications	classification	NOUN
cana-4847	226	6	,	,	PUNCT
cana-4847	226	7	whether	whether	SCONJ
cana-4847	226	8	they	they	PRON
cana-4847	226	9	are	be	AUX
cana-4847	226	10	binary	binary	ADJ
cana-4847	226	11	or	or	CCONJ
cana-4847	226	12	multi	multi	ADJ
cana-4847	226	13	-	-	ADJ
cana-4847	226	14	class	class	ADJ
cana-4847	226	15	classifications	classification	NOUN
cana-4847	226	16	,	,	PUNCT
cana-4847	226	17	serve	serve	VERB
cana-4847	226	18	as	as	ADP
cana-4847	226	19	a	a	DET
cana-4847	226	20	testimony	testimony	NOUN
cana-4847	226	21	to	to	ADP
cana-4847	226	22	the	the	DET
cana-4847	226	23	success	success	NOUN
cana-4847	226	24	these	these	DET
cana-4847	226	25	models	model	NOUN
cana-4847	226	26	hold	hold	VERB
cana-4847	226	27	while	while	SCONJ
cana-4847	226	28	diagnosing	diagnose	VERB
cana-4847	226	29	and	and	CCONJ
cana-4847	226	30	detecting	detect	VERB
cana-4847	226	31	several	several	ADJ
cana-4847	226	32	skin	skin	NOUN
cana-4847	226	33	diseases	disease	NOUN
cana-4847	226	34	.	.	PUNCT
cana-4847	227	1	in	in	ADP
cana-4847	227	2	figure7	figure7	NOUN
cana-4847	227	3	,	,	PUNCT
cana-4847	227	4	comparison	comparison	NOUN
cana-4847	227	5	on	on	ADP
cana-4847	227	6	proposed	propose	VERB
cana-4847	227	7	work	work	NOUN
cana-4847	227	8	based	base	VERB
cana-4847	227	9	on	on	ADP
cana-4847	227	10	detection	detection	NOUN
cana-4847	227	11	of	of	ADP
cana-4847	227	12	skin	skin	NOUN
cana-4847	227	13	diseases	disease	NOUN
cana-4847	227	14	named	name	VERB
cana-4847	227	15	psoriasis	psoriasis	NOUN
cana-4847	227	16	,	,	PUNCT
cana-4847	227	17	eczema	eczema	NOUN
cana-4847	227	18	with	with	ADP
cana-4847	227	19	different	different	ADJ
cana-4847	227	20	networks	network	NOUN
cana-4847	227	21	named	name	VERB
cana-4847	227	22	mobilenet	mobilenet	NOUN
cana-4847	227	23	,	,	PUNCT
cana-4847	227	24	inception	inception	PROPN
cana-4847	227	25	v3	v3	PROPN
cana-4847	227	26	,	,	PUNCT
cana-4847	227	27	densenet	densenet	NOUN
cana-4847	227	28	,	,	PUNCT
cana-4847	227	29	inception50	inception50	NOUN
cana-4847	227	30	etc	etc	X
cana-4847	227	31	.	.	X
cana-4847	228	1	with	with	ADP
cana-4847	228	2	3	3	NUM
cana-4847	228	3	classifications	classification	NOUN
cana-4847	228	4	.	.	PUNCT
cana-4847	229	1	on	on	ADP
cana-4847	229	2	the	the	DET
cana-4847	229	3	basis	basis	NOUN
cana-4847	229	4	of	of	ADP
cana-4847	229	5	information	information	NOUN
cana-4847	229	6	received	receive	VERB
cana-4847	229	7	the	the	DET
cana-4847	229	8	following	follow	VERB
cana-4847	229	9	graph	graph	NOUN
cana-4847	229	10	be	be	AUX
cana-4847	229	11	plotted	plot	VERB
cana-4847	229	12	.	.	PUNCT
cana-4847	230	1	numerous	numerous	ADJ
cana-4847	230	2	researchers	researcher	NOUN
cana-4847	230	3	had	have	AUX
cana-4847	230	4	proposed	propose	VERB
cana-4847	230	5	different	different	ADJ
cana-4847	230	6	skin	skin	NOUN
cana-4847	230	7	disease	disease	NOUN
cana-4847	230	8	detecting	detect	VERB
cana-4847	230	9	methods	method	NOUN
cana-4847	230	10	.	.	PUNCT
cana-4847	231	1	statistical	statistical	ADJ
cana-4847	231	2	comparison	comparison	NOUN
cana-4847	231	3	between	between	ADP
cana-4847	231	4	various	various	ADJ
cana-4847	231	5	works	work	NOUN
cana-4847	231	6	and	and	CCONJ
cana-4847	231	7	the	the	DET
cana-4847	231	8	solution	solution	NOUN
cana-4847	231	9	proposed	propose	VERB
cana-4847	231	10	is	be	AUX
cana-4847	231	11	given	give	VERB
cana-4847	231	12	in	in	ADP
cana-4847	231	13	table	table	NOUN
cana-4847	231	14	2	2	NUM
cana-4847	231	15	.	.	PUNCT
cana-4847	232	1	with	with	ADP
cana-4847	232	2	the	the	DET
cana-4847	232	3	results	result	NOUN
cana-4847	232	4	obtained	obtain	VERB
cana-4847	232	5	in	in	ADP
cana-4847	232	6	table	table	NOUN
cana-4847	232	7	3	3	NUM
cana-4847	232	8	,	,	PUNCT
cana-4847	232	9	one	one	PRON
cana-4847	232	10	can	can	AUX
cana-4847	232	11	observe	observe	VERB
cana-4847	232	12	,	,	PUNCT
cana-4847	232	13	because	because	SCONJ
cana-4847	232	14	various	various	ADJ
cana-4847	232	15	skin	skin	NOUN
cana-4847	232	16	disease	disease	NOUN
cana-4847	232	17	involves	involve	VERB
cana-4847	232	18	varying	vary	VERB
cana-4847	232	19	colors	color	NOUN
cana-4847	232	20	and	and	CCONJ
cana-4847	232	21	forms	form	NOUN
cana-4847	232	22	that	that	SCONJ
cana-4847	232	23	most	most	ADJ
cana-4847	232	24	of	of	ADP
cana-4847	232	25	the	the	DET
cana-4847	232	26	works	work	NOUN
cana-4847	232	27	stressed	stress	VERB
cana-4847	232	28	on	on	ADP
cana-4847	232	29	feature	feature	NOUN
cana-4847	232	30	choice	choice	NOUN
cana-4847	232	31	and	and	CCONJ
cana-4847	232	32	texture	texture	ADJ
cana-4847	232	33	choice	choice	NOUN
cana-4847	232	34	process	process	NOUN
cana-4847	232	35	.	.	PUNCT
cana-4847	233	1	and	and	CCONJ
cana-4847	233	2	the	the	DET
cana-4847	233	3	majority	majority	NOUN
cana-4847	233	4	of	of	ADP
cana-4847	233	5	the	the	DET
cana-4847	233	6	cnn	cnn	PROPN
cana-4847	233	7	solutions	solution	NOUN
cana-4847	233	8	achieved	achieve	VERB
cana-4847	233	9	a	a	DET
cana-4847	233	10	comparable	comparable	ADJ
cana-4847	233	11	level	level	NOUN
cana-4847	233	12	of	of	ADP
cana-4847	233	13	accuracy	accuracy	NOUN
cana-4847	233	14	.	.	PUNCT
cana-4847	234	1	the	the	DET
cana-4847	234	2	following	follow	VERB
cana-4847	234	3	observations	observation	NOUN
cana-4847	234	4	are	be	AUX
cana-4847	234	5	derived	derive	VERB
cana-4847	234	6	from	from	ADP
cana-4847	234	7	the	the	DET
cana-4847	234	8	experimental	experimental	ADJ
cana-4847	234	9	study	study	NOUN
cana-4847	234	10	of	of	ADP
cana-4847	234	11	the	the	DET
cana-4847	234	12	skin	skin	NOUN
cana-4847	234	13	disease	disease	NOUN
cana-4847	234	14	dataset	dataset	VERB
cana-4847	234	15	:	:	PUNCT
cana-4847	234	16	fig	fig	NOUN
cana-4847	234	17	7	7	NUM
cana-4847	234	18	:	:	PUNCT
cana-4847	234	19	comparison	comparison	NOUN
cana-4847	234	20	of	of	ADP
cana-4847	234	21	proposed	propose	VERB
cana-4847	234	22	work	work	NOUN
cana-4847	234	23	with	with	ADP
cana-4847	234	24	other	other	ADJ
cana-4847	234	25	networks	network	NOUN
cana-4847	234	26	.	.	PUNCT
cana-4847	235	1	any	any	DET
cana-4847	235	2	cnn	cnn	PROPN
cana-4847	235	3	model	model	NOUN
cana-4847	235	4	's	's	PART
cana-4847	235	5	accuracy	accuracy	NOUN
cana-4847	235	6	on	on	ADP
cana-4847	235	7	a	a	DET
cana-4847	235	8	given	give	VERB
cana-4847	235	9	dataset	dataset	NOUN
cana-4847	235	10	is	be	AUX
cana-4847	235	11	greatly	greatly	ADV
cana-4847	235	12	increased	increase	VERB
cana-4847	235	13	using	use	VERB
cana-4847	235	14	the	the	DET
cana-4847	235	15	transfer	transfer	NOUN
cana-4847	235	16	learning	learning	NOUN
cana-4847	235	17	technique	technique	NOUN
cana-4847	235	18	.	.	PUNCT
cana-4847	236	1	the	the	DET
cana-4847	236	2	adam	adam	PROPN
cana-4847	236	3	optimizer	optimizer	NOUN
cana-4847	236	4	completed	complete	VERB
cana-4847	236	5	the	the	DET
cana-4847	236	6	categorization	categorization	NOUN
cana-4847	236	7	operation	operation	NOUN
cana-4847	236	8	more	more	ADV
cana-4847	236	9	quickly	quickly	ADV
cana-4847	236	10	in	in	ADP
cana-4847	236	11	terms	term	NOUN
cana-4847	236	12	of	of	ADP
cana-4847	236	13	execution	execution	NOUN
cana-4847	236	14	time	time	NOUN
cana-4847	236	15	.	.	PUNCT
cana-4847	237	1	highest	high	ADJ
cana-4847	237	2	training	training	NOUN
cana-4847	237	3	,	,	PUNCT
cana-4847	237	4	validation	validation	NOUN
cana-4847	237	5	,	,	PUNCT
cana-4847	237	6	and	and	CCONJ
cana-4847	237	7	test	test	NOUN
cana-4847	237	8	accuracy	accuracy	NOUN
cana-4847	237	9	were	be	AUX
cana-4847	237	10	achieved	achieve	VERB
cana-4847	237	11	by	by	ADP
cana-4847	237	12	resnet50	resnet50	NOUN
cana-4847	237	13	and	and	CCONJ
cana-4847	237	14	inception	inception	ADJ
cana-4847	237	15	resnetv2	resnetv2	NOUN
cana-4847	237	16	models	model	NOUN
cana-4847	237	17	with	with	ADP
cana-4847	237	18	adam	adam	PROPN
cana-4847	237	19	optimizer	optimizer	NOUN
cana-4847	237	20	.	.	PUNCT
cana-4847	238	1	adam	adam	PROPN
cana-4847	238	2	optimizer	optimizer	NOUN
cana-4847	238	3	can	can	AUX
cana-4847	238	4	be	be	AUX
cana-4847	238	5	utilized	utilize	VERB
cana-4847	238	6	for	for	ADP
cana-4847	238	7	classification	classification	NOUN
cana-4847	238	8	task	task	NOUN
cana-4847	238	9	based	base	VERB
cana-4847	238	10	on	on	ADP
cana-4847	238	11	accuracy	accuracy	NOUN
cana-4847	238	12	.	.	PUNCT
cana-4847	239	1	over	over	ADP
cana-4847	239	2	-	-	PUNCT
cana-4847	239	3	fitting	fit	VERB
cana-4847	239	4	behaviors	behavior	NOUN
cana-4847	239	5	are	be	AUX
cana-4847	239	6	exhibited	exhibit	VERB
cana-4847	239	7	by	by	ADP
cana-4847	239	8	resnet-50	resnet-50	PROPN
cana-4847	239	9	architectures	architecture	NOUN
cana-4847	239	10	with	with	ADP
cana-4847	239	11	adam	adam	PROPN
cana-4847	239	12	optimizer	optimizer	NOUN
cana-4847	239	13	.	.	PUNCT
cana-4847	240	1	inception	inception	ADJ
cana-4847	240	2	resnetv2	resnetv2	NOUN
cana-4847	240	3	shows	show	VERB
cana-4847	240	4	improved	improved	ADJ
cana-4847	240	5	performance	performance	NOUN
cana-4847	240	6	compared	compare	VERB
cana-4847	240	7	to	to	ADP
cana-4847	240	8	its	its	PRON
cana-4847	240	9	hybrid	hybrid	ADJ
cana-4847	240	10	architecture	architecture	NOUN
cana-4847	240	11	.	.	PUNCT
cana-4847	241	1	improved	improve	VERB
cana-4847	241	2	weight	weight	NOUN
cana-4847	241	3	updation	updation	NOUN
cana-4847	241	4	is	be	AUX
cana-4847	241	5	achieved	achieve	VERB
cana-4847	241	6	using	use	VERB
cana-4847	241	7	learning	learn	VERB
cana-4847	241	8	rate	rate	NOUN
cana-4847	241	9	0.0001	0.0001	NUM
cana-4847	241	10	and	and	CCONJ
cana-4847	241	11	momentum	momentum	NOUN
cana-4847	241	12	0.9	0.9	NUM
cana-4847	241	13	.	.	PUNCT
cana-4847	242	1	0.01	0.01	NUM
cana-4847	242	2	and	and	CCONJ
cana-4847	242	3	0.001	0.001	NUM
cana-4847	242	4	learning	learning	NOUN
cana-4847	242	5	rate	rate	NOUN
cana-4847	242	6	also	also	ADV
cana-4847	242	7	worked	work	VERB
cana-4847	242	8	equally	equally	ADV
cana-4847	242	9	well	well	ADV
cana-4847	242	10	.	.	PUNCT
cana-4847	243	1	communications	communication	NOUN
cana-4847	243	2	on	on	ADP
cana-4847	243	3	applied	apply	VERB
cana-4847	243	4	nonlinear	nonlinear	ADJ
cana-4847	243	5	analysis	analysis	NOUN
cana-4847	243	6	issn	issn	NOUN
cana-4847	243	7	:	:	PUNCT
cana-4847	243	8	1074	1074	NUM
cana-4847	243	9	-	-	PUNCT
cana-4847	243	10	133x	133x	NUM
cana-4847	243	11	vol	vol	VERB
cana-4847	243	12	32	32	NUM
cana-4847	243	13	no	no	NOUN
cana-4847	243	14	.	.	PUNCT
cana-4847	244	1	10s	10	NOUN
cana-4847	244	2	(	(	PUNCT
cana-4847	244	3	2025	2025	NUM
cana-4847	244	4	)	)	PUNCT
cana-4847	244	5	579	579	NUM
cana-4847	244	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	244	7	table3	table3	PROPN
cana-4847	244	8	:	:	PUNCT
cana-4847	244	9	comparison	comparison	NOUN
cana-4847	244	10	of	of	ADP
cana-4847	244	11	proposed	propose	VERB
cana-4847	244	12	model	model	NOUN
cana-4847	244	13	with	with	ADP
cana-4847	244	14	existing	exist	VERB
cana-4847	244	15	work	work	NOUN
cana-4847	244	16	5	5	NUM
cana-4847	244	17	.	.	PUNCT
cana-4847	244	18	conclusion	conclusion	NOUN
cana-4847	244	19	this	this	DET
cana-4847	244	20	study	study	NOUN
cana-4847	244	21	focused	focus	VERB
cana-4847	244	22	on	on	ADP
cana-4847	244	23	the	the	DET
cana-4847	244	24	development	development	NOUN
cana-4847	244	25	of	of	ADP
cana-4847	244	26	deep	deep	ADJ
cana-4847	244	27	learning	learning	NOUN
cana-4847	244	28	techniques	technique	NOUN
cana-4847	244	29	for	for	ADP
cana-4847	244	30	identifying	identify	VERB
cana-4847	244	31	the	the	DET
cana-4847	244	32	three	three	NUM
cana-4847	244	33	most	most	ADV
cana-4847	244	34	prevalent	prevalent	ADJ
cana-4847	244	35	skin	skin	NOUN
cana-4847	244	36	conditions	condition	NOUN
cana-4847	244	37	:	:	PUNCT
cana-4847	244	38	eczema	eczema	NOUN
cana-4847	244	39	,	,	PUNCT
cana-4847	244	40	psoriasis	psoriasis	NOUN
cana-4847	244	41	,	,	PUNCT
cana-4847	244	42	and	and	CCONJ
cana-4847	244	43	cancer	cancer	NOUN
cana-4847	244	44	.	.	PUNCT
cana-4847	245	1	to	to	PART
cana-4847	245	2	create	create	VERB
cana-4847	245	3	a	a	DET
cana-4847	245	4	precise	precise	ADJ
cana-4847	245	5	and	and	CCONJ
cana-4847	245	6	reliable	reliable	ADJ
cana-4847	245	7	automated	automate	VERB
cana-4847	245	8	diagnosis	diagnosis	NOUN
cana-4847	245	9	system	system	NOUN
cana-4847	245	10	for	for	ADP
cana-4847	245	11	skin	skin	NOUN
cana-4847	245	12	conditions	condition	NOUN
cana-4847	245	13	,	,	PUNCT
cana-4847	245	14	employed	employ	VERB
cana-4847	245	15	various	various	ADJ
cana-4847	245	16	convolutional	convolutional	ADJ
cana-4847	245	17	neural	neural	ADJ
cana-4847	245	18	network	network	NOUN
cana-4847	245	19	(	(	PUNCT
cana-4847	245	20	cnn	cnn	PROPN
cana-4847	245	21	)	)	PUNCT
cana-4847	245	22	architectures	architecture	NOUN
cana-4847	245	23	.	.	PUNCT
cana-4847	246	1	our	our	PRON
cana-4847	246	2	investigation	investigation	NOUN
cana-4847	246	3	revealed	reveal	VERB
cana-4847	246	4	that	that	SCONJ
cana-4847	246	5	the	the	DET
cana-4847	246	6	resnet50	resnet50	NOUN
cana-4847	246	7	architecture	architecture	NOUN
cana-4847	246	8	,	,	PUNCT
cana-4847	246	9	combined	combine	VERB
cana-4847	246	10	with	with	ADP
cana-4847	246	11	transfer	transfer	NOUN
cana-4847	246	12	learning	learning	NOUN
cana-4847	246	13	and	and	CCONJ
cana-4847	246	14	the	the	DET
cana-4847	246	15	adam	adam	PROPN
cana-4847	246	16	optimizer	optimizer	NOUN
cana-4847	246	17	,	,	PUNCT
cana-4847	246	18	outperformed	outperform	VERB
cana-4847	246	19	previous	previous	ADJ
cana-4847	246	20	cnn	cnn	PROPN
cana-4847	246	21	models	model	NOUN
cana-4847	246	22	.	.	PUNCT
cana-4847	247	1	this	this	DET
cana-4847	247	2	configuration	configuration	NOUN
cana-4847	247	3	had	have	AUX
cana-4847	247	4	achieved	achieve	VERB
cana-4847	247	5	a	a	DET
cana-4847	247	6	testing	testing	NOUN
cana-4847	247	7	accuracy	accuracy	NOUN
cana-4847	247	8	and	and	CCONJ
cana-4847	247	9	training	training	NOUN
cana-4847	247	10	accuracy	accuracy	NOUN
cana-4847	247	11	of	of	ADP
cana-4847	247	12	99.49	99.49	NUM
cana-4847	247	13	%	%	NOUN
cana-4847	247	14	and	and	CCONJ
cana-4847	247	15	99.9	99.9	NUM
cana-4847	247	16	%	%	NOUN
cana-4847	247	17	,	,	PUNCT
cana-4847	247	18	respectively	respectively	ADV
cana-4847	247	19	.	.	PUNCT
cana-4847	248	1	demonstrating	demonstrate	VERB
cana-4847	248	2	that	that	SCONJ
cana-4847	248	3	the	the	DET
cana-4847	248	4	potential	potential	NOUN
cana-4847	248	5	of	of	ADP
cana-4847	248	6	deep	deep	ADJ
cana-4847	248	7	learning	learning	NOUN
cana-4847	248	8	in	in	ADP
cana-4847	248	9	transforming	transform	VERB
cana-4847	248	10	dermatological	dermatological	ADJ
cana-4847	248	11	diagnostics	diagnostic	NOUN
cana-4847	248	12	.	.	PUNCT
cana-4847	249	1	the	the	DET
cana-4847	249	2	effective	effective	ADJ
cana-4847	249	3	deployment	deployment	NOUN
cana-4847	249	4	of	of	ADP
cana-4847	249	5	such	such	DET
cana-4847	249	6	a	a	DET
cana-4847	249	7	system	system	NOUN
cana-4847	249	8	has	have	VERB
cana-4847	249	9	significant	significant	ADJ
cana-4847	249	10	implications	implication	NOUN
cana-4847	249	11	for	for	ADP
cana-4847	249	12	healthcare	healthcare	NOUN
cana-4847	249	13	.	.	PUNCT
cana-4847	250	1	early	early	ADJ
cana-4847	250	2	and	and	CCONJ
cana-4847	250	3	accurate	accurate	ADJ
cana-4847	250	4	diagnosis	diagnosis	NOUN
cana-4847	250	5	of	of	ADP
cana-4847	250	6	skin	skin	NOUN
cana-4847	250	7	diseases	disease	NOUN
cana-4847	250	8	will	will	AUX
cana-4847	250	9	substantially	substantially	ADV
cana-4847	250	10	improve	improve	VERB
cana-4847	250	11	patient	patient	ADJ
cana-4847	250	12	outcomes	outcome	NOUN
cana-4847	250	13	and	and	CCONJ
cana-4847	250	14	enable	enable	VERB
cana-4847	250	15	timely	timely	ADJ
cana-4847	250	16	interventions	intervention	NOUN
cana-4847	250	17	.	.	PUNCT
cana-4847	251	1	this	this	DET
cana-4847	251	2	technology	technology	NOUN
cana-4847	251	3	will	will	AUX
cana-4847	251	4	also	also	ADV
cana-4847	251	5	enable	enable	VERB
cana-4847	251	6	healthcare	healthcare	NOUN
cana-4847	251	7	professionals	professional	NOUN
cana-4847	251	8	to	to	PART
cana-4847	251	9	focus	focus	VERB
cana-4847	251	10	on	on	ADP
cana-4847	251	11	more	more	ADJ
cana-4847	251	12	complex	complex	ADJ
cana-4847	251	13	cases	case	NOUN
cana-4847	251	14	,	,	PUNCT
cana-4847	251	15	making	make	VERB
cana-4847	251	16	quality	quality	NOUN
cana-4847	251	17	healthcare	healthcare	NOUN
cana-4847	251	18	more	more	ADV
cana-4847	251	19	accessible	accessible	ADJ
cana-4847	251	20	,	,	PUNCT
cana-4847	251	21	particularly	particularly	ADV
cana-4847	251	22	in	in	ADP
cana-4847	251	23	regions	region	NOUN
cana-4847	251	24	with	with	ADP
cana-4847	251	25	limited	limited	ADJ
cana-4847	251	26	dermatology	dermatology	NOUN
cana-4847	251	27	expertise	expertise	NOUN
cana-4847	251	28	.	.	PUNCT
cana-4847	252	1	while	while	SCONJ
cana-4847	252	2	this	this	DET
cana-4847	252	3	study	study	NOUN
cana-4847	252	4	represents	represent	VERB
cana-4847	252	5	a	a	DET
cana-4847	252	6	significant	significant	ADJ
cana-4847	252	7	advancement	advancement	NOUN
cana-4847	252	8	,	,	PUNCT
cana-4847	252	9	further	further	ADJ
cana-4847	252	10	research	research	NOUN
cana-4847	252	11	is	be	AUX
cana-4847	252	12	necessary	necessary	ADJ
cana-4847	252	13	to	to	PART
cana-4847	252	14	develop	develop	VERB
cana-4847	252	15	and	and	CCONJ
cana-4847	252	16	extend	extend	VERB
cana-4847	252	17	deep	deep	ADJ
cana-4847	252	18	authors	author	NOUN
cana-4847	252	19	no.of	no.of	ADJ
cana-4847	252	20	disease	disease	NOUN
cana-4847	252	21	proposed	propose	VERB
cana-4847	252	22	method	method	NOUN
cana-4847	252	23	performance(%	performance(%	NOUN
cana-4847	252	24	)	)	PUNCT
cana-4847	252	25	abbadi[3	abbadi[3	PART
cana-4847	252	26	]	]	X
cana-4847	252	27	1(psoriasis	1(psoriasis	NUM
cana-4847	252	28	)	)	PUNCT
cana-4847	252	29	glcm	glcm	NOUN
cana-4847	252	30	feature	feature	NOUN
cana-4847	252	31	extraction	extraction	NOUN
cana-4847	252	32	with	with	ADP
cana-4847	252	33	feed	feed	NOUN
cana-4847	252	34	forward	forward	ADV
cana-4847	252	35	neural	neural	ADJ
cana-4847	252	36	network	network	NOUN
cana-4847	252	37	all	all	DET
cana-4847	252	38	samples	sample	NOUN
cana-4847	252	39	are	be	AUX
cana-4847	252	40	detected	detect	VERB
cana-4847	252	41	correctly	correctly	ADV
cana-4847	252	42	srivastava	srivastava	PROPN
cana-4847	253	1	[	[	X
cana-4847	253	2	5	5	NUM
cana-4847	253	3	]	]	SYM
cana-4847	253	4	1(eczema	1(eczema	NUM
cana-4847	253	5	)	)	PUNCT
cana-4847	253	6	neural	neural	ADJ
cana-4847	253	7	network	network	NOUN
cana-4847	253	8	model	model	NOUN
cana-4847	253	9	.	.	PUNCT
cana-4847	254	1	accuracy	accuracy	NOUN
cana-4847	254	2	=	=	SYM
cana-4847	254	3	90	90	NUM
cana-4847	254	4	%	%	NOUN
cana-4847	254	5	bhadula	bhadula	NOUN
cana-4847	254	6	[	[	X
cana-4847	254	7	9	9	NUM
cana-4847	254	8	]	]	PUNCT
cana-4847	254	9	3(lichen	3(lichen	NUM
cana-4847	254	10	planus	planus	NOUN
cana-4847	254	11	,	,	PUNCT
cana-4847	254	12	acne	acne	PROPN
cana-4847	254	13	,	,	PUNCT
cana-4847	254	14	sjs	sjs	PROPN
cana-4847	254	15	-	-	PUNCT
cana-4847	254	16	ten	ten	NUM
cana-4847	254	17	)	)	PUNCT
cana-4847	254	18	machine	machine	NOUN
cana-4847	254	19	learning	learn	VERB
cana-4847	254	20	classifiers	classifier	NOUN
cana-4847	254	21	-	-	PUNCT
cana-4847	254	22	based	base	VERB
cana-4847	254	23	approach	approach	NOUN
cana-4847	254	24	96	96	NUM
cana-4847	254	25	%	%	NOUN
cana-4847	254	26	accuracy	accuracy	NOUN
cana-4847	254	27	on	on	ADP
cana-4847	254	28	testing	test	VERB
cana-4847	254	29	dataset	dataset	NOUN
cana-4847	254	30	shanthi[10	shanthi[10	NOUN
cana-4847	254	31	]	]	X
cana-4847	254	32	4	4	NUM
cana-4847	254	33	(	(	PUNCT
cana-4847	254	34	acne	acne	NOUN
cana-4847	254	35	,	,	PUNCT
cana-4847	254	36	keratosis	keratosis	NOUN
cana-4847	254	37	,	,	PUNCT
cana-4847	254	38	eczema	eczema	NOUN
cana-4847	254	39	,	,	PUNCT
cana-4847	254	40	urticaria	urticaria	PROPN
cana-4847	254	41	)	)	PUNCT
cana-4847	254	42	cnn	cnn	PROPN
cana-4847	254	43	based	base	VERB
cana-4847	254	44	classification	classification	NOUN
cana-4847	254	45	approach	approach	NOUN
cana-4847	254	46	accuracy:98.6–99.04	accuracy:98.6–99.04	NOUN
cana-4847	254	47	%	%	NOUN
cana-4847	254	48	goceri	goceri	NOUN
cana-4847	254	49	[	[	X
cana-4847	254	50	18	18	NUM
cana-4847	254	51	]	]	SYM
cana-4847	254	52	8	8	NUM
cana-4847	254	53	skin	skin	NOUN
cana-4847	254	54	diseases	disease	NOUN
cana-4847	254	55	mobilenet	mobilenet	NOUN
cana-4847	254	56	accuracy=94.7	accuracy=94.7	VERB
cana-4847	254	57	precision=90.6	precision=90.6	ADJ
cana-4847	254	58	f1	f1	PROPN
cana-4847	254	59	-	-	PUNCT
cana-4847	254	60	score=91.3	score=91.3	NOUN
cana-4847	254	61	proposed	propose	VERB
cana-4847	254	62	model	model	NOUN
cana-4847	254	63	2	2	NUM
cana-4847	254	64	(	(	PUNCT
cana-4847	254	65	eczema	eczema	NOUN
cana-4847	254	66	,	,	PUNCT
cana-4847	254	67	psoriasis	psoriasis	NOUN
cana-4847	254	68	)	)	PUNCT
cana-4847	254	69	resnet50	resnet50	NOUN
cana-4847	254	70	architecture	architecture	NOUN
cana-4847	254	71	with	with	ADP
cana-4847	254	72	adam	adam	PROPN
cana-4847	254	73	optimizer	optimizer	NOUN
cana-4847	254	74	accuracy=99.4	accuracy=99.4	NOUN
cana-4847	254	75	precision=1.0	precision=1.0	NOUN
cana-4847	254	76	recall=1.0	recall=1.0	NOUN
cana-4847	254	77	f1	f1	ADJ
cana-4847	254	78	-	-	PUNCT
cana-4847	254	79	score=1.0	score=1.0	NOUN
cana-4847	254	80	communications	communication	NOUN
cana-4847	254	81	on	on	ADP
cana-4847	254	82	applied	apply	VERB
cana-4847	254	83	nonlinear	nonlinear	ADJ
cana-4847	254	84	analysis	analysis	NOUN
cana-4847	254	85	issn	issn	NOUN
cana-4847	254	86	:	:	PUNCT
cana-4847	254	87	1074	1074	NUM
cana-4847	254	88	-	-	PUNCT
cana-4847	254	89	133x	133x	NUM
cana-4847	254	90	vol	vol	VERB
cana-4847	254	91	32	32	NUM
cana-4847	254	92	no	no	NOUN
cana-4847	254	93	.	.	PUNCT
cana-4847	255	1	10s	10	NOUN
cana-4847	255	2	(	(	PUNCT
cana-4847	255	3	2025	2025	NUM
cana-4847	255	4	)	)	PUNCT
cana-4847	255	5	580	580	NUM
cana-4847	255	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4847	255	7	learning	learning	NOUN
cana-4847	255	8	-	-	PUNCT
cana-4847	255	9	based	base	VERB
cana-4847	255	10	skin	skin	NOUN
cana-4847	255	11	disease	disease	NOUN
cana-4847	255	12	detection	detection	NOUN
cana-4847	255	13	.	.	PUNCT
cana-4847	256	1	future	future	ADJ
cana-4847	256	2	studies	study	NOUN
cana-4847	256	3	should	should	AUX
cana-4847	256	4	investigate	investigate	VERB
cana-4847	256	5	the	the	DET
cana-4847	256	6	inclusion	inclusion	NOUN
cana-4847	256	7	of	of	ADP
cana-4847	256	8	a	a	DET
cana-4847	256	9	broader	broad	ADJ
cana-4847	256	10	range	range	NOUN
cana-4847	256	11	of	of	ADP
cana-4847	256	12	skin	skin	NOUN
cana-4847	256	13	conditions	condition	NOUN
cana-4847	256	14	,	,	PUNCT
cana-4847	256	15	optimal	optimal	ADJ
cana-4847	256	16	architectures	architecture	NOUN
cana-4847	256	17	,	,	PUNCT
cana-4847	256	18	and	and	CCONJ
cana-4847	256	19	the	the	DET
cana-4847	256	20	use	use	NOUN
cana-4847	256	21	of	of	ADP
cana-4847	256	22	larger	large	ADJ
cana-4847	256	23	and	and	CCONJ
cana-4847	256	24	more	more	ADV
cana-4847	256	25	diverse	diverse	ADJ
cana-4847	256	26	datasets	dataset	NOUN
cana-4847	256	27	.	.	PUNCT
cana-4847	257	1	these	these	DET
cana-4847	257	2	efforts	effort	NOUN
cana-4847	257	3	will	will	AUX
cana-4847	257	4	likely	likely	ADV
cana-4847	257	5	lead	lead	VERB
cana-4847	257	6	to	to	ADP
cana-4847	257	7	improvements	improvement	NOUN
cana-4847	257	8	in	in	ADP
cana-4847	257	9	accuracy	accuracy	NOUN
cana-4847	257	10	,	,	PUNCT
cana-4847	257	11	robustness	robustness	NOUN
cana-4847	257	12	,	,	PUNCT
cana-4847	257	13	and	and	CCONJ
cana-4847	257	14	clinical	clinical	ADJ
cana-4847	257	15	utility	utility	NOUN
cana-4847	257	16	,	,	PUNCT
cana-4847	257	17	ultimately	ultimately	ADV
cana-4847	257	18	enhancing	enhance	VERB
cana-4847	257	19	the	the	DET
cana-4847	257	20	diagnosis	diagnosis	NOUN
cana-4847	257	21	and	and	CCONJ
cana-4847	257	22	treatment	treatment	NOUN
cana-4847	257	23	of	of	ADP
cana-4847	257	24	skin	skin	NOUN
cana-4847	257	25	diseases	disease	NOUN
cana-4847	257	26	.	.	PUNCT
cana-4847	258	1	references	reference	NOUN
cana-4847	258	2	[	[	X
cana-4847	258	3	1	1	NUM
cana-4847	258	4	]	]	PUNCT
cana-4847	258	5	.	.	PUNCT
cana-4847	259	1	the	the	DET
cana-4847	259	2	author(s	author(s	PROPN
cana-4847	259	3	)	)	PUNCT
cana-4847	259	4	,	,	PUNCT
cana-4847	260	1	md	md	PROPN
cana-4847	260	2	.	.	PROPN
cana-4847	260	3	sazzadul	sazzadul	PROPN
cana-4847	260	4	islam	islam	PROPN
cana-4847	260	5	prottasha	prottasha	PROPN
cana-4847	260	6	,	,	PUNCT
cana-4847	260	7	sanjanmahjabinfarin	sanjanmahjabinfarin	PROPN
cana-4847	260	8	,	,	PUNCT
cana-4847	260	9	md	md	PROPN
cana-4847	260	10	.	.	PROPN
cana-4847	261	1	bulbul	bulbul	PROPN
cana-4847	261	2	ahmed	ahmed	PROPN
cana-4847	261	3	,	,	PUNCT
cana-4847	261	4	md	md	PROPN
cana-4847	261	5	.	.	PROPN
cana-4847	262	1	zihadur	zihadur	PROPN
cana-4847	262	2	rahman	rahman	PROPN
cana-4847	262	3	,	,	PUNCT
cana-4847	262	4	a.	a.	PROPN
cana-4847	262	5	b.	b.	PROPN
cana-4847	262	6	m.	m.	PROPN
cana-4847	262	7	kabir	kabir	PROPN
cana-4847	262	8	hossain	hossain	PROPN
cana-4847	262	9	,	,	PUNCT
cana-4847	262	10	and	and	CCONJ
cana-4847	262	11	m.	m.	PROPN
cana-4847	262	12	shamim	shamim	PROPN
cana-4847	262	13	kaiser	kaiser	PROPN
cana-4847	262	14	under	under	ADP
cana-4847	262	15	exclusive	exclusive	ADJ
cana-4847	262	16	license	license	NOUN
cana-4847	262	17	to	to	ADP
cana-4847	262	18	springer	springer	NOUN
cana-4847	262	19	nature	nature	PROPN
cana-4847	262	20	singapore	singapore	PROPN
cana-4847	262	21	pte	pte	PROPN
cana-4847	262	22	ltd	ltd	PROPN
cana-4847	262	23	.	.	PROPN
cana-4847	263	1	a	a	DET
cana-4847	263	2	deep	deep	ADJ
cana-4847	263	3	learning	learning	NOUN
cana-4847	263	4	-	-	PUNCT
cana-4847	263	5	based	base	VERB
cana-4847	263	6	skin	skin	NOUN
cana-4847	263	7	disease	disease	NOUN
cana-4847	263	8	detection	detection	NOUN
cana-4847	263	9	using	use	VERB
cana-4847	263	10	convolutional	convolutional	ADJ
cana-4847	263	11	neural	neural	ADJ
cana-4847	263	12	networks	network	NOUN
cana-4847	263	13	(	(	PUNCT
cana-4847	263	14	cnn	cnn	PROPN
cana-4847	263	15	)	)	PUNCT
cana-4847	263	16	.	.	PUNCT
cana-4847	264	1	2023	2023	NUM
cana-4847	265	1	[	[	X
cana-4847	265	2	crossref	crossref	X
cana-4847	265	3	:]	:]	PUNCT
cana-4847	265	4	[	[	X
cana-4847	265	5	2	2	NUM
cana-4847	265	6	]	]	PUNCT
cana-4847	265	7	data	datum	NOUN
cana-4847	265	8	set	set	VERB
cana-4847	265	9	link	link	NOUN
cana-4847	265	10	:	:	PUNCT
cana-4847	265	11	https://www.kaggle.com/datasets/gopinath12316/skindiseasedatase1/settings	https://www.kaggle.com/datasets/gopinath12316/skindiseasedatase1/setting	NOUN
cana-4847	266	1	[	[	X
cana-4847	266	2	3	3	NUM
cana-4847	266	3	]	]	PUNCT
cana-4847	266	4	.	.	PUNCT
cana-4847	267	1	al	al	PROPN
cana-4847	267	2	abbadi	abbadi	PROPN
cana-4847	267	3	,	,	PUNCT
cana-4847	267	4	n.k	n.k	PROPN
cana-4847	267	5	.	.	PROPN
cana-4847	267	6	,	,	PUNCT
cana-4847	267	7	dahir	dahir	NOUN
cana-4847	267	8	,	,	PUNCT
cana-4847	267	9	n.s	n.s	PROPN
cana-4847	267	10	.	.	PROPN
cana-4847	267	11	,	,	PUNCT
cana-4847	267	12	al	al	PROPN
cana-4847	267	13	-	-	PUNCT
cana-4847	267	14	dhalimi	dhalimi	PROPN
cana-4847	267	15	,	,	PUNCT
cana-4847	267	16	m.a	m.a	PROPN
cana-4847	267	17	.	.	PROPN
cana-4847	267	18	,	,	PUNCT
cana-4847	267	19	restom	restom	PROPN
cana-4847	267	20	,	,	PUNCT
cana-4847	267	21	h.	h.	NOUN
cana-4847	267	22	:	:	PUNCT
cana-4847	267	23	psoriasis	psoriasis	NOUN
cana-4847	267	24	detection	detection	NOUN
cana-4847	267	25	using	use	VERB
cana-4847	267	26	skin	skin	NOUN
cana-4847	267	27	color	color	NOUN
cana-4847	267	28	and	and	CCONJ
cana-4847	267	29	texture	texture	NOUN
cana-4847	267	30	features	feature	NOUN
cana-4847	267	31	.	.	PUNCT
cana-4847	268	1	j.	j.	PROPN
cana-4847	268	2	comput	comput	PROPN
cana-4847	268	3	.	.	PUNCT
cana-4847	269	1	sci	sci	PROPN
cana-4847	269	2	.	.	PUNCT
cana-4847	270	1	6(6	6(6	NUM
cana-4847	270	2	)	)	PUNCT
cana-4847	270	3	,	,	PUNCT
cana-4847	270	4	648–652	648–652	NUM
cana-4847	270	5	(	(	PUNCT
cana-4847	270	6	2010	2010	NUM
cana-4847	270	7	)	)	PUNCT
cana-4847	270	8	.	.	PUNCT
cana-4847	271	1	[	[	X
cana-4847	271	2	4].source	4].source	NUM
cana-4847	271	3	code	code	NOUN
cana-4847	271	4	link	link	NOUN
cana-4847	271	5	for	for	ADP
cana-4847	271	6	some	some	DET
cana-4847	271	7	part	part	NOUN
cana-4847	271	8	of	of	ADP
cana-4847	271	9	the	the	DET
cana-4847	271	10	method	method	NOUN
cana-4847	271	11	:	:	PUNCT
cana-4847	271	12	https://www.kaggle.com/code/gopinath12316/resnet50-with-2	https://www.kaggle.com/code/gopinath12316/resnet50-with-2	PROPN
cana-4847	272	1	[	[	X
cana-4847	272	2	5	5	NUM
cana-4847	272	3	]	]	PUNCT
cana-4847	272	4	.	.	PUNCT
cana-4847	273	1	automatic	automatic	ADJ
cana-4847	273	2	detection	detection	NOUN
cana-4847	273	3	and	and	CCONJ
cana-4847	273	4	severity	severity	NOUN
cana-4847	273	5	measurement	measurement	NOUN
cana-4847	273	6	of	of	ADP
cana-4847	273	7	eczema	eczema	NOUN
cana-4847	273	8	using	use	VERB
cana-4847	273	9	image	image	NOUN
cana-4847	273	10	processing	processing	NOUN
cana-4847	273	11	written	write	VERB
cana-4847	273	12	by	by	ADP
cana-4847	273	13	authors	author	NOUN
cana-4847	273	14	alam	alam	PROPN
cana-4847	273	15	,	,	PUNCT
cana-4847	273	16	m.n	m.n	PROPN
cana-4847	273	17	.	.	PROPN
cana-4847	273	18	,munia	,munia	PUNCT
cana-4847	273	19	,	,	PUNCT
cana-4847	273	20	t.t.k	t.t.k	ADP
cana-4847	273	21	.	.	PROPN
cana-4847	273	22	,	,	PUNCT
cana-4847	273	23	tavakolian	tavakolian	NOUN
cana-4847	273	24	,	,	PUNCT
cana-4847	273	25	k.	k.	PROPN
cana-4847	273	26	,	,	PUNCT
cana-4847	273	27	vasefi	vasefi	PROPN
cana-4847	273	28	,	,	PUNCT
cana-4847	273	29	f.	f.	PROPN
cana-4847	273	30	,	,	PUNCT
cana-4847	273	31	mackinnon	mackinnon	PROPN
cana-4847	273	32	,	,	PUNCT
cana-4847	273	33	n.	n.	NOUN
cana-4847	273	34	,	,	PUNCT
cana-4847	273	35	fazel	fazel	ADJ
cana-4847	273	36	-	-	PUNCT
cana-4847	273	37	rezai	rezai	NOUN
cana-4847	273	38	,	,	PUNCT
cana-4847	273	39	r	r	NOUN
cana-4847	273	40	..	..	PUNCT
cana-4847	273	41	in	in	ADP
cana-4847	273	42	:	:	PUNCT
cana-4847	273	43	2016	2016	NUM
cana-4847	273	44	38th	38th	ADJ
cana-4847	273	45	annual	annual	ADJ
cana-4847	273	46	international	international	ADJ
cana-4847	273	47	conference	conference	NOUN
cana-4847	273	48	of	of	ADP
cana-4847	273	49	the	the	DET
cana-4847	273	50	ieee	ieee	NOUN
cana-4847	273	51	engineering	engineering	NOUN
cana-4847	273	52	in	in	ADP
cana-4847	273	53	medicine	medicine	NOUN
cana-4847	273	54	and	and	CCONJ
cana-4847	273	55	biology	biology	NOUN
cana-4847	273	56	society	society	NOUN
cana-4847	273	57	,	,	PUNCT
cana-4847	273	58	pp	pp	ADV
cana-4847	273	59	.	.	PUNCT
cana-4847	274	1	1365–1368	1365–1368	NUM
cana-4847	274	2	.	.	PUNCT
cana-4847	275	1	ieee	ieee	NOUN
cana-4847	275	2	(	(	PUNCT
cana-4847	275	3	2016	2016	NUM
cana-4847	275	4	)	)	PUNCT
cana-4847	275	5	.	.	PUNCT
cana-4847	276	1	[	[	X
cana-4847	276	2	6	6	NUM
cana-4847	276	3	]	]	PUNCT
cana-4847	276	4	s.	s.	PROPN
cana-4847	276	5	taj	taj	PROPN
cana-4847	276	6	,	,	PUNCT
cana-4847	276	7	g.	g.	PROPN
cana-4847	276	8	m.	m.	PROPN
cana-4847	276	9	shaikh	shaikh	PROPN
cana-4847	276	10	,	,	PUNCT
cana-4847	276	11	s.	s.	PROPN
cana-4847	276	12	hassan	hassan	PROPN
cana-4847	276	13	,	,	PUNCT
cana-4847	276	14	"	"	PUNCT
cana-4847	276	15	urdu	urdu	NOUN
cana-4847	276	16	speech	speech	NOUN
cana-4847	276	17	emotion	emotion	NOUN
cana-4847	276	18	recognition	recognition	NOUN
cana-4847	276	19	using	use	VERB
cana-4847	276	20	speech	speech	NOUN
cana-4847	276	21	spectral	spectral	ADJ
cana-4847	276	22	features	feature	NOUN
cana-4847	276	23	and	and	CCONJ
cana-4847	276	24	deep	deep	ADJ
cana-4847	276	25	learning	learning	NOUN
cana-4847	276	26	techniques	technique	NOUN
cana-4847	276	27	"	"	PUNCT
cana-4847	276	28	,	,	PUNCT
cana-4847	276	29	proceedings	proceeding	NOUN
cana-4847	276	30	of	of	ADP
cana-4847	276	31	the	the	DET
cana-4847	276	32	4th	4th	ADJ
cana-4847	276	33	international	international	ADJ
cana-4847	276	34	conference	conference	NOUN
cana-4847	276	35	on	on	ADP
cana-4847	276	36	computing	computing	NOUN
cana-4847	276	37	,	,	PUNCT
cana-4847	276	38	mathematics	mathematic	NOUN
cana-4847	276	39	and	and	CCONJ
cana-4847	276	40	engineering	engineering	NOUN
cana-4847	276	41	technologies	technology	NOUN
cana-4847	276	42	,	,	PUNCT
cana-4847	276	43	sukkur	sukkur	PROPN
cana-4847	276	44	,	,	PUNCT
cana-4847	276	45	pakistan	pakistan	PROPN
cana-4847	276	46	,	,	PUNCT
cana-4847	276	47	17	17	NUM
cana-4847	276	48	-	-	SYM
cana-4847	276	49	18	18	NUM
cana-4847	276	50	march	march	NOUN
cana-4847	276	51	2023	2023	NUM
cana-4847	276	52	,	,	PUNCT
cana-4847	276	53	pp	pp	ADJ
cana-4847	276	54	.	.	PUNCT
cana-4847	277	1	1	1	NUM
cana-4847	277	2	-	-	SYM
cana-4847	277	3	6	6	NUM
cana-4847	277	4	.	.	PUNCT
cana-4847	278	1	[	[	X
cana-4847	278	2	7	7	X
cana-4847	278	3	]	]	X
cana-4847	278	4	m.	m.	NOUN
cana-4847	278	5	hamidi	hamidi	PROPN
cana-4847	278	6	,	,	PUNCT
cana-4847	278	7	f.	f.	PROPN
cana-4847	278	8	barkani	barkani	PROPN
cana-4847	278	9	,	,	PUNCT
cana-4847	278	10	o.	o.	PROPN
cana-4847	278	11	zealouk	zealouk	PROPN
cana-4847	278	12	,	,	PUNCT
cana-4847	278	13	h.	h.	PROPN
cana-4847	278	14	satori	satori	PROPN
cana-4847	278	15	,	,	PUNCT
cana-4847	278	16	"	"	PUNCT
cana-4847	278	17	assessing	assess	VERB
cana-4847	278	18	the	the	DET
cana-4847	278	19	performance	performance	NOUN
cana-4847	278	20	of	of	ADP
cana-4847	278	21	a	a	DET
cana-4847	278	22	speech	speech	NOUN
cana-4847	278	23	recognition	recognition	NOUN
cana-4847	278	24	system	system	NOUN
cana-4847	278	25	embedded	embed	VERB
cana-4847	278	26	in	in	ADP
cana-4847	278	27	low	low	ADJ
cana-4847	278	28	-	-	PUNCT
cana-4847	278	29	cost	cost	NOUN
cana-4847	278	30	devices	device	NOUN
cana-4847	278	31	"	"	PUNCT
cana-4847	278	32	,	,	PUNCT
cana-4847	278	33	international	international	ADJ
cana-4847	278	34	journal	journal	NOUN
cana-4847	278	35	of	of	ADP
cana-4847	278	36	electrical	electrical	ADJ
cana-4847	278	37	and	and	CCONJ
cana-4847	278	38	computer	computer	NOUN
cana-4847	278	39	engineering	engineering	NOUN
cana-4847	278	40	systems	system	NOUN
cana-4847	278	41	,	,	PUNCT
cana-4847	278	42	vol	vol	NOUN
cana-4847	278	43	.	.	PROPN
cana-4847	278	44	14	14	NUM
cana-4847	278	45	,	,	PUNCT
cana-4847	278	46	no	no	INTJ
cana-4847	278	47	.	.	NOUN
cana-4847	278	48	6	6	NUM
cana-4847	278	49	,	,	PUNCT
cana-4847	278	50	2023	2023	NUM
cana-4847	278	51	,	,	PUNCT
cana-4847	278	52	pp	pp	ADJ
cana-4847	278	53	.	.	PUNCT
cana-4847	279	1	677	677	NUM
cana-4847	279	2	-	-	SYM
cana-4847	279	3	683	683	NUM
cana-4847	279	4	.	.	PUNCT
cana-4847	280	1	[	[	X
cana-4847	280	2	8	8	X
cana-4847	280	3	]	]	PUNCT
cana-4847	280	4	s.	s.	PROPN
cana-4847	280	5	k.	k.	PROPN
cana-4847	280	6	nayak	nayak	PROPN
cana-4847	280	7	,	,	PUNCT
cana-4847	280	8	a.	a.	PROPN
cana-4847	280	9	k.	k.	PROPN
cana-4847	280	10	nayak	nayak	PROPN
cana-4847	280	11	,	,	PUNCT
cana-4847	280	12	s.	s.	PROPN
cana-4847	280	13	mishra	mishra	PROPN
cana-4847	280	14	,	,	PUNCT
cana-4847	280	15	p.	p.	PROPN
cana-4847	280	16	mohanty	mohanty	PROPN
cana-4847	280	17	,	,	PUNCT
cana-4847	280	18	n.	n.	PROPN
cana-4847	280	19	tripathy	tripathy	PROPN
cana-4847	280	20	,	,	PUNCT
cana-4847	280	21	s.	s.	PROPN
cana-4847	280	22	prusty	prusty	PROPN
cana-4847	280	23	,	,	PUNCT
cana-4847	280	24	an	an	DET
cana-4847	280	25	indonesian	indonesian	ADJ
cana-4847	280	26	journal	journal	NOUN
cana-4847	280	27	of	of	ADP
cana-4847	280	28	electrical	electrical	ADJ
cana-4847	280	29	engineering	engineering	NOUN
cana-4847	280	30	and	and	CCONJ
cana-4847	280	31	computer	computer	NOUN
cana-4847	280	32	science	science	NOUN
cana-4847	280	33	named	name	VERB
cana-4847	280	34	“	"	PUNCT
cana-4847	280	35	improving	improve	VERB
cana-4847	280	36	kui	kui	PROPN
cana-4847	280	37	digit	digit	NOUN
cana-4847	280	38	recognition	recognition	NOUN
cana-4847	280	39	through	through	ADP
cana-4847	280	40	machine	machine	NOUN
cana-4847	280	41	learning	learning	NOUN
cana-4847	280	42	and	and	CCONJ
cana-4847	280	43	data	datum	NOUN
cana-4847	280	44	augmentation	augmentation	NOUN
cana-4847	280	45	techniques	technique	NOUN
cana-4847	280	46	”	"	PUNCT
cana-4847	280	47	,	,	PUNCT
cana-4847	280	48	,	,	PUNCT
cana-4847	280	49	vol	vol	NOUN
cana-4847	280	50	.	.	PROPN
cana-4847	280	51	35	35	NUM
cana-4847	280	52	,	,	PUNCT
cana-4847	280	53	no	no	INTJ
cana-4847	280	54	.	.	NOUN
cana-4847	280	55	2	2	NUM
cana-4847	280	56	,	,	PUNCT
cana-4847	280	57	2024	2024	NUM
cana-4847	280	58	,	,	PUNCT
cana-4847	280	59	pp	pp	ADJ
cana-4847	280	60	.	.	PUNCT
cana-4847	280	61	867	867	NUM
cana-4847	280	62	-	-	SYM
cana-4847	280	63	877	877	NUM
cana-4847	281	1	[	[	X
cana-4847	281	2	9	9	NUM
cana-4847	281	3	]	]	SYM
cana-4847	281	4	.	.	PUNCT
cana-4847	282	1	bhadula	bhadula	PROPN
cana-4847	282	2	,	,	PUNCT
cana-4847	282	3	s.	s.	PROPN
cana-4847	282	4	,	,	PUNCT
cana-4847	282	5	sharma	sharma	PROPN
cana-4847	282	6	,	,	PUNCT
cana-4847	282	7	s.	s.	PROPN
cana-4847	282	8	,	,	PUNCT
cana-4847	282	9	juyal	juyal	PROPN
cana-4847	282	10	,	,	PUNCT
cana-4847	282	11	p.	p.	PROPN
cana-4847	282	12	,	,	PUNCT
cana-4847	282	13	kulshrestha	kulshrestha	PROPN
cana-4847	282	14	,	,	PUNCT
cana-4847	282	15	c.	c.	NOUN
cana-4847	282	16	:	:	PUNCT
cana-4847	282	17	machine	machine	NOUN
cana-4847	282	18	learning	learn	VERB
cana-4847	282	19	algorithms	algorithms	NOUN
cana-4847	282	20	-	-	PUNCT
cana-4847	282	21	based	base	VERB
cana-4847	282	22	skin	skin	NOUN
cana-4847	282	23	disease	disease	NOUN
cana-4847	282	24	detection	detection	NOUN
cana-4847	282	25	.	.	PUNCT
cana-4847	283	1	ijitee	ijitee	NOUN
cana-4847	283	2	9(2	9(2	NUM
cana-4847	283	3	)	)	PUNCT
cana-4847	283	4	,	,	PUNCT
cana-4847	283	5	4044–4049	4044–4049	NUM
cana-4847	283	6	(	(	PUNCT
cana-4847	283	7	2019	2019	NUM
cana-4847	283	8	)	)	PUNCT
cana-4847	283	9	.	.	PUNCT
cana-4847	284	1	[	[	X
cana-4847	284	2	10	10	NUM
cana-4847	284	3	]	]	PUNCT
cana-4847	284	4	.	.	PUNCT
cana-4847	285	1	shanthi	shanthi	PROPN
cana-4847	285	2	t.	t.	PROPN
cana-4847	285	3	,	,	PUNCT
cana-4847	285	4	sabeenian	sabeenian	PROPN
cana-4847	285	5	r.s	r.s	PROPN
cana-4847	285	6	.	.	PROPN
cana-4847	285	7	,	,	PUNCT
cana-4847	285	8	anand	anand	PROPN
cana-4847	285	9	r	r	PROPN
cana-4847	285	10	,	,	PUNCT
cana-4847	285	11	automatic	automatic	ADJ
cana-4847	285	12	diagnosis	diagnosis	NOUN
cana-4847	285	13	of	of	ADP
cana-4847	285	14	skin	skin	NOUN
cana-4847	285	15	diseases	disease	NOUN
cana-4847	285	16	using	use	VERB
cana-4847	285	17	convolution	convolution	NOUN
cana-4847	285	18	neural	neural	ADJ
cana-4847	285	19	network	network	NOUN
cana-4847	285	20	.	.	PUNCT
cana-4847	286	1	microprocess	microprocess	NOUN
cana-4847	286	2	.	.	PUNCT
cana-4847	287	1	microsyst	microsyst	NOUN
cana-4847	287	2	.	.	PUNCT
cana-4847	288	1	76	76	NUM
cana-4847	288	2	,	,	PUNCT
cana-4847	288	3	103074	103074	NUM
cana-4847	288	4	(	(	PUNCT
cana-4847	288	5	2020	2020	NUM
cana-4847	288	6	)	)	PUNCT
cana-4847	289	1	[	[	X
cana-4847	289	2	11	11	NUM
cana-4847	289	3	]	]	PUNCT
cana-4847	289	4	.	.	PUNCT
cana-4847	290	1	shankar	shankar	PROPN
cana-4847	290	2	,	,	PUNCT
cana-4847	290	3	v.	v.	PROPN
cana-4847	290	4	,	,	PUNCT
cana-4847	290	5	kumar	kumar	PROPN
cana-4847	290	6	,	,	PUNCT
cana-4847	290	7	v.	v.	PROPN
cana-4847	290	8	,	,	PUNCT
cana-4847	290	9	devagade	devagade	PROPN
cana-4847	290	10	,	,	PUNCT
cana-4847	290	11	u.	u.	PROPN
cana-4847	290	12	,	,	PUNCT
cana-4847	290	13	karanth	karanth	NOUN
cana-4847	290	14	,	,	PUNCT
cana-4847	290	15	v.	v.	PROPN
cana-4847	290	16	,	,	PUNCT
cana-4847	290	17	rohitaksha	rohitaksha	PROPN
cana-4847	290	18	,	,	PUNCT
cana-4847	290	19	k.	k.	NOUN
cana-4847	290	20	:	:	PUNCT
cana-4847	290	21	heart	heart	NOUN
cana-4847	290	22	disease	disease	NOUN
cana-4847	290	23	prediction	prediction	NOUN
cana-4847	290	24	using	use	VERB
cana-4847	290	25	cnn	cnn	PROPN
cana-4847	290	26	algorithm	algorithm	NOUN
cana-4847	290	27	.	.	PUNCT
cana-4847	291	1	sn	sn	PROPN
cana-4847	291	2	comput	comput	PROPN
cana-4847	291	3	.	.	PUNCT
cana-4847	292	1	sci	sci	PROPN
cana-4847	292	2	.	.	PROPN
cana-4847	293	1	1	1	NUM
cana-4847	293	2	,	,	PUNCT
cana-4847	293	3	170	170	NUM
cana-4847	293	4	(	(	PUNCT
cana-4847	293	5	2020	2020	NUM
cana-4847	293	6	)	)	PUNCT
cana-4847	294	1	[	[	X
cana-4847	294	2	12	12	NUM
cana-4847	294	3	]	]	PUNCT
cana-4847	294	4	.	.	PUNCT
cana-4847	295	1	prottasha	prottasha	PROPN
cana-4847	295	2	,	,	PUNCT
cana-4847	295	3	m.s.i	m.s.i	NOUN
cana-4847	295	4	.	.	PROPN
cana-4847	295	5	,	,	PUNCT
cana-4847	295	6	hossain	hossain	PROPN
cana-4847	295	7	,	,	PUNCT
cana-4847	295	8	a.b.m	a.b.m	ADJ
cana-4847	295	9	.	.	PROPN
cana-4847	295	10	,	,	PUNCT
cana-4847	295	11	rahman	rahman	PROPN
cana-4847	295	12	,	,	PUNCT
cana-4847	295	13	m.z	m.z	PROPN
cana-4847	295	14	.	.	PROPN
cana-4847	295	15	,	,	PUNCT
cana-4847	295	16	reza	reza	PROPN
cana-4847	295	17	,	,	PUNCT
cana-4847	295	18	s.m.s	s.m.s	NOUN
cana-4847	295	19	.	.	PUNCT
cana-4847	295	20	,	,	PUNCT
cana-4847	295	21	hossain	hossain	PROPN
cana-4847	295	22	,	,	PUNCT
cana-4847	295	23	d.a	d.a	PROPN
cana-4847	295	24	.	.	PROPN
cana-4847	295	25	:	:	PUNCT
cana-4847	296	1	identification	identification	NOUN
cana-4847	296	2	of	of	ADP
cana-4847	296	3	various	various	ADJ
cana-4847	296	4	rice	rice	NOUN
cana-4847	296	5	plant	plant	NOUN
cana-4847	296	6	diseases	disease	NOUN
cana-4847	296	7	using	use	VERB
cana-4847	296	8	optimized	optimize	VERB
cana-4847	296	9	convolutional	convolutional	ADJ
cana-4847	296	10	neural	neural	ADJ
cana-4847	296	11	network	network	NOUN
cana-4847	296	12	.	.	PUNCT
cana-4847	297	1	int	int	NOUN
cana-4847	297	2	.	.	PUNCT
cana-4847	298	1	j.	j.	PROPN
cana-4847	298	2	comput	comput	PROPN
cana-4847	298	3	.	.	PUNCT
cana-4847	299	1	dig	dig	PROPN
cana-4847	299	2	.	.	PUNCT
cana-4847	300	1	syst	syst	PROPN
cana-4847	300	2	.	.	PUNCT
cana-4847	301	1	(	(	PUNCT
cana-4847	301	2	ijcds	ijcds	PROPN
cana-4847	301	3	)	)	PUNCT
cana-4847	301	4	9	9	NUM
cana-4847	301	5	(	(	PUNCT
cana-4847	301	6	2021	2021	NUM
cana-4847	301	7	)	)	PUNCT
cana-4847	301	8	https://link.springer.com/chapter/10.1007/978-981-19-8032-9_39	https://link.springer.com/chapter/10.1007/978-981-19-8032-9_39	NOUN
cana-4847	301	9	https://www.kaggle.com/datasets/gopinath12316/skindiseasedatase1/settings	https://www.kaggle.com/datasets/gopinath12316/skindiseasedatase1/setting	NOUN
cana-4847	301	10	https://www.kaggle.com/code/gopinath12316/resnet50-with-2	https://www.kaggle.com/code/gopinath12316/resnet50-with-2	VERB
cana-4847	301	11	communications	communication	NOUN
cana-4847	301	12	on	on	ADP
cana-4847	301	13	applied	apply	VERB
cana-4847	301	14	nonlinear	nonlinear	ADJ
cana-4847	301	15	analysis	analysis	NOUN
cana-4847	301	16	issn	issn	NOUN
cana-4847	301	17	:	:	PUNCT
cana-4847	301	18	1074	1074	NUM
cana-4847	301	19	-	-	PUNCT
cana-4847	301	20	133x	133x	NUM
cana-4847	301	21	vol	vol	VERB
cana-4847	301	22	32	32	NUM
cana-4847	301	23	no	no	NOUN
cana-4847	301	24	.	.	PUNCT
cana-4847	302	1	10s	10	NOUN
cana-4847	302	2	(	(	PUNCT
cana-4847	302	3	2025	2025	NUM
cana-4847	302	4	)	)	PUNCT
cana-4847	302	5	581	581	NUM
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cana-4847	303	1	[	[	X
cana-4847	303	2	13	13	NUM
cana-4847	303	3	]	]	PUNCT
cana-4847	303	4	.	.	PUNCT
cana-4847	304	1	farooq	farooq	PROPN
cana-4847	304	2	,	,	PUNCT
cana-4847	304	3	a.	a.	PROPN
cana-4847	304	4	,	,	PUNCT
cana-4847	304	5	anwar	anwar	PROPN
cana-4847	304	6	,	,	PUNCT
cana-4847	304	7	s.	s.	PROPN
cana-4847	304	8	,	,	PUNCT
cana-4847	304	9	awais	awais	PROPN
cana-4847	304	10	,	,	PUNCT
cana-4847	304	11	m.	m.	NOUN
cana-4847	304	12	,	,	PUNCT
cana-4847	304	13	rehman	rehman	PROPN
cana-4847	304	14	,	,	PUNCT
cana-4847	304	15	s.	s.	PROPN
cana-4847	304	16	:	:	PUNCT
cana-4847	304	17	a	a	DET
cana-4847	304	18	deep	deep	ADJ
cana-4847	304	19	cnn	cnn	NOUN
cana-4847	304	20	based	base	VERB
cana-4847	304	21	multi	multi	ADJ
cana-4847	304	22	-	-	ADJ
cana-4847	304	23	class	class	ADJ
cana-4847	304	24	classification	classification	NOUN
cana-4847	304	25	of	of	ADP
cana-4847	304	26	alzheimer	alzheimer	PROPN
cana-4847	304	27	’s	’s	PART
cana-4847	304	28	disease	disease	NOUN
cana-4847	304	29	using	use	VERB
cana-4847	304	30	mri	mri	NOUN
cana-4847	304	31	.	.	PUNCT
cana-4847	305	1	in	in	ADP
cana-4847	305	2	:	:	PUNCT
cana-4847	305	3	2017	2017	NUM
cana-4847	305	4	ieee	ieee	NOUN
cana-4847	305	5	international	international	ADJ
cana-4847	305	6	conference	conference	NOUN
cana-4847	305	7	on	on	ADP
cana-4847	305	8	imaging	imaging	NOUN
cana-4847	305	9	systems	system	NOUN
cana-4847	305	10	and	and	CCONJ
cana-4847	305	11	techniques	technique	NOUN
cana-4847	305	12	(	(	PUNCT
cana-4847	305	13	ist	ist	NOUN
cana-4847	305	14	)	)	PUNCT
cana-4847	305	15	.	.	PUNCT
cana-4847	306	1	[	[	X
cana-4847	306	2	14].dermnet	14].dermnet	NUM
cana-4847	306	3	:	:	PUNCT
cana-4847	306	4	dermatology	dermatology	NOUN
cana-4847	306	5	skin	skin	NOUN
cana-4847	306	6	disease	disease	NOUN
cana-4847	306	7	pictures	picture	VERB
cana-4847	306	8	.	.	PUNCT
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cana-4847	307	2	eczema	eczema	NOUN
cana-4847	307	3	-	-	PUNCT
cana-4847	307	4	photos	photo	NOUN
cana-4847	307	5	.	.	PUNCT
cana-4847	308	1	last	last	ADJ
cana-4847	308	2	accessed	access	VERB
cana-4847	308	3	30	30	NUM
cana-4847	308	4	aug	aug	NOUN
cana-4847	308	5	.	.	PROPN
cana-4847	308	6	2019	2019	NUM
cana-4847	309	1	[	[	X
cana-4847	309	2	15	15	NUM
cana-4847	309	3	]	]	PUNCT
cana-4847	309	4	.	.	PUNCT
cana-4847	310	1	psoriasis	psoriasis	NOUN
cana-4847	310	2	department	department	NOUN
cana-4847	310	3	of	of	ADP
cana-4847	310	4	dermatology	dermatology	NOUN
cana-4847	310	5	.	.	PUNCT
cana-4847	311	1	https://medicine.uiowa.edu/dermatology/psoriasis	https://medicine.uiowa.edu/dermatology/psoriasis	PROPN
cana-4847	311	2	.	.	PUNCT
cana-4847	312	1	last	last	ADJ
cana-4847	312	2	accessed	access	VERB
cana-4847	312	3	27	27	NUM
cana-4847	312	4	aug	aug	NOUN
cana-4847	312	5	.	.	PROPN
cana-4847	312	6	2019	2019	NUM
cana-4847	313	1	[	[	X
cana-4847	313	2	16	16	NUM
cana-4847	313	3	]	]	PUNCT
cana-4847	313	4	.	.	PUNCT
cana-4847	314	1	t.	t.	PROPN
cana-4847	314	2	venkata	venkata	PROPN
cana-4847	314	3	krishnamoorthy	krishnamoorthy	PROPN
cana-4847	314	4	,	,	PUNCT
cana-4847	314	5	c.	c.	PROPN
cana-4847	314	6	venkataiah	venkataiah	PROPN
cana-4847	314	7	,	,	PUNCT
cana-4847	314	8	y.	y.	PROPN
cana-4847	314	9	mallikarjuna	mallikarjuna	PROPN
cana-4847	314	10	rao	rao	PROPN
cana-4847	314	11	,	,	PUNCT
cana-4847	314	12	d.	d.	PROPN
cana-4847	314	13	rajendra	rajendra	PROPN
cana-4847	314	14	prasad	prasad	PROPN
cana-4847	314	15	,	,	PUNCT
cana-4847	314	16	kurra	kurra	PROPN
cana-4847	314	17	upendra	upendra	PROPN
cana-4847	314	18	chowdary	chowdary	PROPN
cana-4847	314	19	,	,	PUNCT
cana-4847	314	20	manjula	manjula	PROPN
cana-4847	314	21	jayamma	jayamma	PROPN
cana-4847	314	22	,	,	PUNCT
cana-4847	314	23	r.	r.	PROPN
cana-4847	314	24	sireesha,"a	sireesha,"a	PROPN
cana-4847	314	25	novel	novel	PROPN
cana-4847	314	26	nasnet	nasnet	NOUN
cana-4847	314	27	model	model	NOUN
cana-4847	314	28	with	with	ADP
cana-4847	314	29	lime	lime	NOUN
cana-4847	314	30	explanability	explanability	NOUN
cana-4847	314	31	for	for	ADP
cana-4847	314	32	lung	lung	NOUN
cana-4847	314	33	disease	disease	NOUN
cana-4847	314	34	classification	classification	NOUN
cana-4847	314	35	"	"	PUNCT
cana-4847	314	36	,	,	PUNCT
cana-4847	314	37	biomedical	biomedical	ADJ
cana-4847	314	38	signal	signal	NOUN
cana-4847	314	39	processing	processing	NOUN
cana-4847	314	40	and	and	CCONJ
cana-4847	314	41	control	control	NOUN
cana-4847	314	42	,	,	PUNCT
cana-4847	314	43	volume	volume	NOUN
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cana-4847	314	45	,	,	PUNCT
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cana-4847	314	47	.	.	PUNCT
cana-4847	315	1	[	[	X
cana-4847	315	2	17	17	NUM
cana-4847	315	3	]	]	PUNCT
cana-4847	315	4	.	.	PUNCT
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cana-4847	315	6	,	,	PUNCT
cana-4847	315	7	k.	k.	PROPN
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cana-4847	315	10	,	,	PUNCT
cana-4847	315	11	a.	a.	NOUN
cana-4847	315	12	:	:	PUNCT
cana-4847	315	13	very	very	ADV
cana-4847	315	14	deep	deep	ADJ
cana-4847	315	15	convolutional	convolutional	ADJ
cana-4847	315	16	networks	network	NOUN
cana-4847	315	17	for	for	ADP
cana-4847	315	18	large	large	ADJ
cana-4847	315	19	-	-	PUNCT
cana-4847	315	20	scale	scale	NOUN
cana-4847	315	21	image	image	NOUN
cana-4847	315	22	recognition	recognition	NOUN
cana-4847	315	23	.	.	PUNCT
cana-4847	316	1	corr	corr	PROPN
cana-4847	316	2	.	.	PUNCT
cana-4847	317	1	abs/1409.1556	abs/1409.1556	PROPN
cana-4847	317	2	(	(	PUNCT
cana-4847	317	3	2015	2015	NUM
cana-4847	317	4	)	)	PUNCT
cana-4847	317	5	564	564	NUM
cana-4847	317	6	md	md	PROPN
cana-4847	317	7	.	.	PROPN
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cana-4847	319	1	islam	islam	PROPN
cana-4847	319	2	prottasha	prottasha	PROPN
cana-4847	319	3	et	et	PROPN
cana-4847	319	4	al	al	PROPN
cana-4847	319	5	.	.	PUNCT
cana-4847	320	1	[	[	X
cana-4847	320	2	18	18	NUM
cana-4847	320	3	]	]	PUNCT
cana-4847	320	4	.	.	PUNCT
cana-4847	320	5	goceri	goceri	PROPN
cana-4847	320	6	,	,	PUNCT
cana-4847	320	7	e.	e.	PROPN
cana-4847	320	8	diagnosis	diagnosis	PROPN
cana-4847	320	9	of	of	ADP
cana-4847	320	10	skin	skin	NOUN
cana-4847	320	11	diseases	disease	NOUN
cana-4847	320	12	in	in	ADP
cana-4847	320	13	the	the	DET
cana-4847	320	14	era	era	NOUN
cana-4847	320	15	of	of	ADP
cana-4847	320	16	deep	deep	ADJ
cana-4847	320	17	learning	learning	NOUN
cana-4847	320	18	and	and	CCONJ
cana-4847	320	19	mobile	mobile	ADJ
cana-4847	320	20	technology	technology	NOUN
cana-4847	320	21	.	.	PUNCT
cana-4847	321	1	comput	comput	NOUN
cana-4847	321	2	.	.	PUNCT
cana-4847	322	1	biol	biol	PROPN
cana-4847	322	2	.	.	PUNCT
cana-4847	323	1	med.2021,134,104458	med.2021,134,104458	NOUN
cana-4847	323	2	.	.	PUNCT
cana-4847	324	1	[	[	X
cana-4847	324	2	crossref	crossref	X
cana-4847	324	3	]	]	X
cana-4847	324	4	[	[	X
cana-4847	324	5	19	19	NUM
cana-4847	324	6	]	]	PUNCT
cana-4847	324	7	.	.	PUNCT
cana-4847	325	1	c.	c.	PROPN
cana-4847	325	2	venkataiah	venkataiah	PROPN
cana-4847	325	3	,	,	PUNCT
cana-4847	325	4	m.	m.	NOUN
cana-4847	325	5	chennakesavulu	chennakesavulu	NOUN
cana-4847	325	6	,	,	PUNCT
cana-4847	325	7	y.	y.	PROPN
cana-4847	325	8	mallikarjuna	mallikarjuna	PROPN
cana-4847	325	9	rao	rao	PROPN
cana-4847	325	10	,	,	PUNCT
cana-4847	325	11	b.	b.	PROPN
cana-4847	325	12	janardhana	janardhana	PROPN
cana-4847	325	13	rao	rao	PROPN
cana-4847	325	14	,	,	PUNCT
cana-4847	325	15	g.	g.	PROPN
cana-4847	325	16	ramesh	ramesh	PROPN
cana-4847	325	17	,	,	PUNCT
cana-4847	325	18	j.	j.	PROPN
cana-4847	325	19	sofia	sofia	PROPN
cana-4847	325	20	priya	priya	PROPN
cana-4847	325	21	dharshini	dharshini	PROPN
cana-4847	325	22	,	,	PUNCT
cana-4847	325	23	manjula	manjula	PROPN
cana-4847	325	24	jayamma,"a	jayamma,"a	PROPN
cana-4847	325	25	novel	novel	PROPN
cana-4847	325	26	eye	eye	NOUN
cana-4847	325	27	disease	disease	NOUN
cana-4847	325	28	segmentation	segmentation	NOUN
cana-4847	325	29	and	and	CCONJ
cana-4847	325	30	classification	classification	NOUN
cana-4847	325	31	model	model	NOUN
cana-4847	325	32	using	use	VERB
cana-4847	325	33	advanced	advanced	ADJ
cana-4847	325	34	deep	deep	ADJ
cana-4847	325	35	learning	learning	NOUN
cana-4847	325	36	network	network	NOUN
cana-4847	325	37	"	"	PUNCT
cana-4847	325	38	,	,	PUNCT
cana-4847	325	39	biomedical	biomedical	ADJ
cana-4847	325	40	signal	signal	NOUN
cana-4847	325	41	processing	processing	NOUN
cana-4847	325	42	and	and	CCONJ
cana-4847	325	43	control	control	NOUN
cana-4847	325	44	,	,	PUNCT
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cana-4847	325	47	/	/	SYM
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cana-4847	325	49	.	.	PUNCT
cana-4847	326	1	https://medicine.uiowa.edu/dermatology/psoriasis	https://medicine.uiowa.edu/dermatology/psoriasis	NOUN
cana-4847	326	2	.	.	PUNCT
cana-4847	327	1	https://doi.org/10.1016/j.bspc.2024.106114	https://doi.org/10.1016/j.bspc.2024.106114	PROPN
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cana-4847	327	3	https://doi.org/10.1016/j.bspc.2025.107565	https://doi.org/10.1016/j.bspc.2025.107565	PROPN