id	sid	tid	token	lemma	pos
easat-2372	1	1	edelweiss	edelweiss	PROPN
easat-2372	1	2	applied	apply	VERB
easat-2372	1	3	science	science	NOUN
easat-2372	1	4	and	and	CCONJ
easat-2372	1	5	technology	technology	NOUN
easat-2372	1	6	issn	issn	PROPN
easat-2372	1	7	:	:	PUNCT
easat-2372	1	8	2576	2576	NUM
easat-2372	1	9	-	-	SYM
easat-2372	1	10	8484	8484	NUM
easat-2372	1	11	vol	vol	NOUN
easat-2372	1	12	.	.	PROPN
easat-2372	1	13	8	8	NUM
easat-2372	1	14	,	,	PUNCT
easat-2372	1	15	no	no	INTJ
easat-2372	1	16	.	.	NOUN
easat-2372	1	17	6	6	NUM
easat-2372	1	18	,	,	PUNCT
easat-2372	1	19	2015	2015	NUM
easat-2372	1	20	-	-	SYM
easat-2372	1	21	2024	2024	NUM
easat-2372	1	22	2024	2024	NUM
easat-2372	1	23	publisher	publisher	NOUN
easat-2372	1	24	:	:	PUNCT
easat-2372	1	25	learning	learn	VERB
easat-2372	1	26	gate	gate	NOUN
easat-2372	1	27	doi	doi	PROPN
easat-2372	1	28	:	:	PUNCT
easat-2372	1	29	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	1	30	©	©	PROPN
easat-2372	1	31	2024	2024	NUM
easat-2372	1	32	by	by	ADP
easat-2372	1	33	the	the	DET
easat-2372	1	34	authors	author	NOUN
easat-2372	1	35	;	;	PUNCT
easat-2372	1	36	licensee	licensee	PROPN
easat-2372	1	37	learning	learning	NOUN
easat-2372	1	38	gate	gate	NOUN
easat-2372	1	39	©	©	PROPN
easat-2372	1	40	2024	2024	NUM
easat-2372	1	41	by	by	ADP
easat-2372	1	42	the	the	DET
easat-2372	1	43	authors	author	NOUN
easat-2372	1	44	;	;	PUNCT
easat-2372	1	45	licensee	licensee	PROPN
easat-2372	1	46	learning	learn	VERB
easat-2372	1	47	gate	gate	NOUN
easat-2372	1	48	*	*	PUNCT
easat-2372	1	49	correspondence	correspondence	NOUN
easat-2372	1	50	:	:	PUNCT
easat-2372	2	1	er9.pooja@gmail.com	er9.pooja@gmail.com	X
easat-2372	2	2	improving	improve	VERB
easat-2372	2	3	losses	loss	NOUN
easat-2372	2	4	&	&	CCONJ
easat-2372	2	5	accuracy	accuracy	NOUN
easat-2372	2	6	through	through	ADP
easat-2372	2	7	design	design	NOUN
easat-2372	2	8	of	of	ADP
easat-2372	2	9	deep	deep	ADJ
easat-2372	2	10	convolutional	convolutional	ADJ
easat-2372	2	11	generative	generative	ADJ
easat-2372	2	12	adversarial	adversarial	ADJ
easat-2372	2	13	network	network	NOUN
easat-2372	2	14	(	(	PUNCT
easat-2372	2	15	dcgan	dcgan	NOUN
easat-2372	2	16	)	)	PUNCT
easat-2372	2	17	for	for	ADP
easat-2372	2	18	plant	plant	NOUN
easat-2372	2	19	disease	disease	NOUN
easat-2372	2	20	detection	detection	NOUN
easat-2372	2	21	tasks	task	NOUN
easat-2372	2	22	pooja	pooja	PROPN
easat-2372	2	23	sharma1	sharma1	PROPN
easat-2372	2	24	*	*	PROPN
easat-2372	2	25	,	,	PUNCT
easat-2372	2	26	ajay	ajay	NOUN
easat-2372	2	27	khunteta2	khunteta2	NOUN
easat-2372	3	1	1poornima	1poornima	NUM
easat-2372	3	2	university	university	NOUN
easat-2372	3	3	,	,	PUNCT
easat-2372	3	4	jaipur	jaipur	PROPN
easat-2372	3	5	,	,	PUNCT
easat-2372	3	6	india	india	PROPN
easat-2372	3	7	;	;	PUNCT
easat-2372	3	8	er9.pooja@gmail.com	er9.pooja@gmail.com	PROPN
easat-2372	3	9	(	(	PUNCT
easat-2372	3	10	p.s	p.s	PROPN
easat-2372	3	11	.	.	PUNCT
easat-2372	3	12	)	)	PUNCT
easat-2372	4	1	2dept	2dept	NUM
easat-2372	4	2	of	of	ADP
easat-2372	4	3	cse	cse	PROPN
easat-2372	4	4	,	,	PUNCT
easat-2372	4	5	poornima	poornima	PROPN
easat-2372	4	6	university	university	PROPN
easat-2372	4	7	,	,	PUNCT
easat-2372	4	8	jaipur	jaipur	PROPN
easat-2372	4	9	,	,	PUNCT
easat-2372	4	10	india	india	PROPN
easat-2372	4	11	;	;	PUNCT
easat-2372	4	12	ajay.khunteta@poornima.edu.in	ajay.khunteta@poornima.edu.in	PROPN
easat-2372	4	13	(	(	PUNCT
easat-2372	4	14	a.k	a.k	PROPN
easat-2372	4	15	.	.	PROPN
easat-2372	4	16	)	)	PUNCT
easat-2372	4	17	.	.	PUNCT
easat-2372	5	1	abstract	abstract	ADJ
easat-2372	5	2	:	:	PUNCT
easat-2372	5	3	rice	rice	NOUN
easat-2372	5	4	leaf	leaf	NOUN
easat-2372	5	5	diseases	disease	NOUN
easat-2372	5	6	are	be	AUX
easat-2372	5	7	a	a	DET
easat-2372	5	8	significant	significant	ADJ
easat-2372	5	9	issue	issue	NOUN
easat-2372	5	10	that	that	SCONJ
easat-2372	5	11	adversely	adversely	ADV
easat-2372	5	12	impact	impact	VERB
easat-2372	5	13	rice	rice	NOUN
easat-2372	5	14	production	production	NOUN
easat-2372	5	15	in	in	ADP
easat-2372	5	16	india	india	PROPN
easat-2372	5	17	.	.	PUNCT
easat-2372	6	1	identifying	identify	VERB
easat-2372	6	2	these	these	DET
easat-2372	6	3	diseases	disease	NOUN
easat-2372	6	4	manually	manually	ADV
easat-2372	6	5	is	be	AUX
easat-2372	6	6	labour	labour	NOUN
easat-2372	6	7	-	-	PUNCT
easat-2372	6	8	intensive	intensive	ADJ
easat-2372	6	9	and	and	CCONJ
easat-2372	6	10	prone	prone	ADJ
easat-2372	6	11	to	to	ADP
easat-2372	6	12	delays	delay	NOUN
easat-2372	6	13	,	,	PUNCT
easat-2372	6	14	often	often	ADV
easat-2372	6	15	resulting	result	VERB
easat-2372	6	16	in	in	ADP
easat-2372	6	17	substantial	substantial	ADJ
easat-2372	6	18	crop	crop	NOUN
easat-2372	6	19	losses	loss	NOUN
easat-2372	6	20	for	for	ADP
easat-2372	6	21	farmers	farmer	NOUN
easat-2372	6	22	.	.	PUNCT
easat-2372	7	1	therefore	therefore	ADV
easat-2372	7	2	,	,	PUNCT
easat-2372	7	3	the	the	DET
easat-2372	7	4	need	need	NOUN
easat-2372	7	5	for	for	ADP
easat-2372	7	6	an	an	DET
easat-2372	7	7	automated	automate	VERB
easat-2372	7	8	system	system	NOUN
easat-2372	7	9	for	for	ADP
easat-2372	7	10	early	early	ADJ
easat-2372	7	11	detection	detection	NOUN
easat-2372	7	12	of	of	ADP
easat-2372	7	13	plant	plant	NOUN
easat-2372	7	14	diseases	disease	NOUN
easat-2372	7	15	is	be	AUX
easat-2372	7	16	critical	critical	ADJ
easat-2372	7	17	.	.	PUNCT
easat-2372	8	1	recent	recent	ADJ
easat-2372	8	2	advancements	advancement	NOUN
easat-2372	8	3	in	in	ADP
easat-2372	8	4	machine	machine	NOUN
easat-2372	8	5	learning	learning	NOUN
easat-2372	8	6	,	,	PUNCT
easat-2372	8	7	computer	computer	NOUN
easat-2372	8	8	vision	vision	NOUN
easat-2372	8	9	,	,	PUNCT
easat-2372	8	10	and	and	CCONJ
easat-2372	8	11	deep	deep	ADJ
easat-2372	8	12	learning	learning	NOUN
easat-2372	8	13	have	have	AUX
easat-2372	8	14	paved	pave	VERB
easat-2372	8	15	the	the	DET
easat-2372	8	16	way	way	NOUN
easat-2372	8	17	for	for	ADP
easat-2372	8	18	classification	classification	NOUN
easat-2372	8	19	models	model	NOUN
easat-2372	8	20	capable	capable	ADJ
easat-2372	8	21	of	of	ADP
easat-2372	8	22	automatically	automatically	ADV
easat-2372	8	23	identifying	identify	VERB
easat-2372	8	24	these	these	DET
easat-2372	8	25	diseases	disease	NOUN
easat-2372	8	26	.	.	PUNCT
easat-2372	9	1	however	however	ADV
easat-2372	9	2	,	,	PUNCT
easat-2372	9	3	the	the	DET
easat-2372	9	4	challenge	challenge	NOUN
easat-2372	9	5	lies	lie	VERB
easat-2372	9	6	in	in	ADP
easat-2372	9	7	obtaining	obtain	VERB
easat-2372	9	8	a	a	DET
easat-2372	9	9	sufficiently	sufficiently	ADV
easat-2372	9	10	large	large	ADJ
easat-2372	9	11	and	and	CCONJ
easat-2372	9	12	diverse	diverse	ADJ
easat-2372	9	13	image	image	NOUN
easat-2372	9	14	dataset	dataset	VERB
easat-2372	9	15	to	to	PART
easat-2372	9	16	effectively	effectively	ADV
easat-2372	9	17	train	train	VERB
easat-2372	9	18	deep	deep	ADJ
easat-2372	9	19	learning	learning	NOUN
easat-2372	9	20	models	model	NOUN
easat-2372	9	21	.	.	PUNCT
easat-2372	10	1	in	in	ADP
easat-2372	10	2	this	this	DET
easat-2372	10	3	paper	paper	NOUN
easat-2372	10	4	,	,	PUNCT
easat-2372	10	5	we	we	PRON
easat-2372	10	6	address	address	VERB
easat-2372	10	7	this	this	DET
easat-2372	10	8	limitation	limitation	NOUN
easat-2372	10	9	by	by	ADP
easat-2372	10	10	employing	employ	VERB
easat-2372	10	11	advanced	advanced	ADJ
easat-2372	10	12	data	datum	NOUN
easat-2372	10	13	augmentation	augmentation	NOUN
easat-2372	10	14	techniques	technique	NOUN
easat-2372	10	15	,	,	PUNCT
easat-2372	10	16	including	include	VERB
easat-2372	10	17	deep	deep	ADJ
easat-2372	10	18	convolutional	convolutional	ADJ
easat-2372	10	19	generative	generative	ADJ
easat-2372	10	20	adversarial	adversarial	ADJ
easat-2372	10	21	networks	network	NOUN
easat-2372	10	22	(	(	PUNCT
easat-2372	10	23	dcgans	dcgan	NOUN
easat-2372	10	24	)	)	PUNCT
easat-2372	10	25	,	,	PUNCT
easat-2372	10	26	to	to	PART
easat-2372	10	27	generate	generate	VERB
easat-2372	10	28	synthetic	synthetic	ADJ
easat-2372	10	29	images	image	NOUN
easat-2372	10	30	that	that	PRON
easat-2372	10	31	expand	expand	VERB
easat-2372	10	32	the	the	DET
easat-2372	10	33	dataset	dataset	NOUN
easat-2372	10	34	of	of	ADP
easat-2372	10	35	rice	rice	NOUN
easat-2372	10	36	leaf	leaf	NOUN
easat-2372	10	37	diseases	disease	NOUN
easat-2372	10	38	.	.	PUNCT
easat-2372	11	1	by	by	ADP
easat-2372	11	2	integrating	integrate	VERB
easat-2372	11	3	these	these	DET
easat-2372	11	4	synthetic	synthetic	ADJ
easat-2372	11	5	images	image	NOUN
easat-2372	11	6	with	with	ADP
easat-2372	11	7	real	real	ADJ
easat-2372	11	8	images	image	NOUN
easat-2372	11	9	,	,	PUNCT
easat-2372	11	10	a	a	DET
easat-2372	11	11	new	new	ADJ
easat-2372	11	12	convolutional	convolutional	ADJ
easat-2372	11	13	neural	neural	ADJ
easat-2372	11	14	network	network	NOUN
easat-2372	11	15	(	(	PUNCT
easat-2372	11	16	cnn	cnn	PROPN
easat-2372	11	17	)	)	PUNCT
easat-2372	11	18	architecture	architecture	NOUN
easat-2372	11	19	is	be	AUX
easat-2372	11	20	proposed	propose	VERB
easat-2372	11	21	,	,	PUNCT
easat-2372	11	22	which	which	PRON
easat-2372	11	23	offers	offer	VERB
easat-2372	11	24	improved	improve	VERB
easat-2372	11	25	generalization	generalization	NOUN
easat-2372	11	26	capabilities	capability	NOUN
easat-2372	11	27	.	.	PUNCT
easat-2372	12	1	the	the	DET
easat-2372	12	2	performance	performance	NOUN
easat-2372	12	3	of	of	ADP
easat-2372	12	4	the	the	DET
easat-2372	12	5	classification	classification	NOUN
easat-2372	12	6	model	model	NOUN
easat-2372	12	7	is	be	AUX
easat-2372	12	8	evaluated	evaluate	VERB
easat-2372	12	9	with	with	ADP
easat-2372	12	10	and	and	CCONJ
easat-2372	12	11	without	without	ADP
easat-2372	12	12	the	the	DET
easat-2372	12	13	dcgan	dcgan	NOUN
easat-2372	12	14	-	-	PUNCT
easat-2372	12	15	generated	generate	VERB
easat-2372	12	16	images	image	NOUN
easat-2372	12	17	.	.	PUNCT
easat-2372	13	1	the	the	DET
easat-2372	13	2	results	result	NOUN
easat-2372	13	3	demonstrate	demonstrate	VERB
easat-2372	13	4	that	that	SCONJ
easat-2372	13	5	the	the	DET
easat-2372	13	6	inclusion	inclusion	NOUN
easat-2372	13	7	of	of	ADP
easat-2372	13	8	synthetic	synthetic	ADJ
easat-2372	13	9	images	image	NOUN
easat-2372	13	10	significantly	significantly	ADV
easat-2372	13	11	enhances	enhance	VERB
easat-2372	13	12	accuracy	accuracy	NOUN
easat-2372	13	13	,	,	PUNCT
easat-2372	13	14	as	as	SCONJ
easat-2372	13	15	the	the	DET
easat-2372	13	16	enlarged	enlarge	VERB
easat-2372	13	17	dataset	dataset	NOUN
easat-2372	13	18	better	well	ADV
easat-2372	13	19	represents	represent	VERB
easat-2372	13	20	real	real	ADJ
easat-2372	13	21	-	-	PUNCT
easat-2372	13	22	world	world	NOUN
easat-2372	13	23	conditions	condition	NOUN
easat-2372	13	24	.	.	PUNCT
easat-2372	14	1	this	this	DET
easat-2372	14	2	approach	approach	NOUN
easat-2372	14	3	provides	provide	VERB
easat-2372	14	4	a	a	DET
easat-2372	14	5	promising	promising	ADJ
easat-2372	14	6	solution	solution	NOUN
easat-2372	14	7	for	for	ADP
easat-2372	14	8	more	more	ADV
easat-2372	14	9	effective	effective	ADJ
easat-2372	14	10	rice	rice	NOUN
easat-2372	14	11	disease	disease	NOUN
easat-2372	14	12	identification	identification	NOUN
easat-2372	14	13	,	,	PUNCT
easat-2372	14	14	offering	offer	VERB
easat-2372	14	15	higher	high	ADJ
easat-2372	14	16	precision	precision	NOUN
easat-2372	14	17	in	in	ADP
easat-2372	14	18	real	real	ADJ
easat-2372	14	19	-	-	PUNCT
easat-2372	14	20	time	time	NOUN
easat-2372	14	21	scenarios	scenario	NOUN
easat-2372	14	22	.	.	PUNCT
easat-2372	15	1	keywords	keyword	NOUN
easat-2372	15	2	:	:	PUNCT
easat-2372	15	3	automated	automate	VERB
easat-2372	15	4	diagnosis	diagnosis	NOUN
easat-2372	15	5	,	,	PUNCT
easat-2372	15	6	classification	classification	NOUN
easat-2372	15	7	,	,	PUNCT
easat-2372	15	8	cnn	cnn	PROPN
easat-2372	15	9	,	,	PUNCT
easat-2372	15	10	computer	computer	NOUN
easat-2372	15	11	vision	vision	NOUN
easat-2372	15	12	,	,	PUNCT
easat-2372	15	13	deep	deep	ADJ
easat-2372	15	14	learning	learning	NOUN
easat-2372	15	15	,	,	PUNCT
easat-2372	15	16	generative	generative	ADJ
easat-2372	15	17	adversarial	adversarial	ADJ
easat-2372	15	18	networks	network	NOUN
easat-2372	15	19	,	,	PUNCT
easat-2372	15	20	plant	plant	NOUN
easat-2372	15	21	diseases	disease	NOUN
easat-2372	15	22	,	,	PUNCT
easat-2372	15	23	rice	rice	NOUN
easat-2372	15	24	leaf	leaf	NOUN
easat-2372	15	25	diseases	disease	NOUN
easat-2372	15	26	,	,	PUNCT
easat-2372	15	27	smart	smart	ADJ
easat-2372	15	28	farming	farming	NOUN
easat-2372	15	29	,	,	PUNCT
easat-2372	15	30	synthetic	synthetic	ADJ
easat-2372	15	31	images	image	NOUN
easat-2372	15	32	.	.	PUNCT
easat-2372	16	1	1	1	X
easat-2372	16	2	.	.	X
easat-2372	16	3	introduction	introduction	NOUN
easat-2372	16	4	food	food	NOUN
easat-2372	16	5	safety	safety	NOUN
easat-2372	16	6	is	be	AUX
easat-2372	16	7	a	a	DET
easat-2372	16	8	critical	critical	ADJ
easat-2372	16	9	issue	issue	NOUN
easat-2372	16	10	in	in	ADP
easat-2372	16	11	balancing	balance	VERB
easat-2372	16	12	agricultural	agricultural	ADJ
easat-2372	16	13	production	production	NOUN
easat-2372	16	14	with	with	ADP
easat-2372	16	15	increasing	increase	VERB
easat-2372	16	16	demand	demand	NOUN
easat-2372	16	17	[	[	X
easat-2372	16	18	1	1	NUM
easat-2372	16	19	]	]	PUNCT
easat-2372	16	20	.	.	PUNCT
easat-2372	17	1	in	in	ADP
easat-2372	17	2	india	india	PROPN
easat-2372	17	3	,	,	PUNCT
easat-2372	17	4	the	the	DET
easat-2372	17	5	agricultural	agricultural	ADJ
easat-2372	17	6	sector	sector	NOUN
easat-2372	17	7	contributes	contribute	VERB
easat-2372	17	8	17.5	17.5	NUM
easat-2372	17	9	%	%	NOUN
easat-2372	17	10	to	to	ADP
easat-2372	17	11	the	the	DET
easat-2372	17	12	country	country	NOUN
easat-2372	17	13	's	's	PART
easat-2372	17	14	gdp	gdp	NOUN
easat-2372	17	15	,	,	PUNCT
easat-2372	17	16	with	with	ADP
easat-2372	17	17	production	production	NOUN
easat-2372	17	18	levels	level	NOUN
easat-2372	17	19	rising	rise	VERB
easat-2372	17	20	annually	annually	ADV
easat-2372	17	21	[	[	X
easat-2372	17	22	2	2	NUM
easat-2372	17	23	]	]	PUNCT
easat-2372	17	24	.	.	PUNCT
easat-2372	18	1	rice	rice	NOUN
easat-2372	18	2	,	,	PUNCT
easat-2372	18	3	a	a	DET
easat-2372	18	4	staple	staple	NOUN
easat-2372	18	5	crop	crop	NOUN
easat-2372	18	6	and	and	CCONJ
easat-2372	18	7	one	one	NUM
easat-2372	18	8	of	of	ADP
easat-2372	18	9	the	the	DET
easat-2372	18	10	most	most	ADV
easat-2372	18	11	cultivated	cultivate	VERB
easat-2372	18	12	cereals	cereal	NOUN
easat-2372	18	13	in	in	ADP
easat-2372	18	14	india	india	PROPN
easat-2372	18	15	,	,	PUNCT
easat-2372	18	16	plays	play	VERB
easat-2372	18	17	a	a	DET
easat-2372	18	18	pivotal	pivotal	ADJ
easat-2372	18	19	role	role	NOUN
easat-2372	18	20	in	in	ADP
easat-2372	18	21	this	this	DET
easat-2372	18	22	growth	growth	NOUN
easat-2372	18	23	.	.	PUNCT
easat-2372	19	1	it	it	PRON
easat-2372	19	2	is	be	AUX
easat-2372	19	3	primarily	primarily	ADV
easat-2372	19	4	a	a	DET
easat-2372	19	5	kharif	kharif	NOUN
easat-2372	19	6	crop	crop	NOUN
easat-2372	19	7	,	,	PUNCT
easat-2372	19	8	thriving	thrive	VERB
easat-2372	19	9	in	in	ADP
easat-2372	19	10	temperatures	temperature	NOUN
easat-2372	19	11	above	above	ADP
easat-2372	19	12	25	25	NUM
easat-2372	19	13	°	°	NOUN
easat-2372	19	14	c	c	NOUN
easat-2372	19	15	and	and	CCONJ
easat-2372	19	16	requiring	require	VERB
easat-2372	19	17	over	over	ADP
easat-2372	19	18	100	100	NUM
easat-2372	19	19	cm	cm	NOUN
easat-2372	19	20	of	of	ADP
easat-2372	19	21	rainfall	rainfall	NOUN
easat-2372	19	22	.	.	PUNCT
easat-2372	20	1	in	in	ADP
easat-2372	20	2	regions	region	NOUN
easat-2372	20	3	with	with	ADP
easat-2372	20	4	insufficient	insufficient	ADJ
easat-2372	20	5	rainfall	rainfall	NOUN
easat-2372	20	6	,	,	PUNCT
easat-2372	20	7	irrigation	irrigation	NOUN
easat-2372	20	8	systems	system	NOUN
easat-2372	20	9	support	support	VERB
easat-2372	20	10	rice	rice	NOUN
easat-2372	20	11	cultivation	cultivation	NOUN
easat-2372	20	12	.	.	PUNCT
easat-2372	21	1	however	however	ADV
easat-2372	21	2	,	,	PUNCT
easat-2372	21	3	fluctuations	fluctuation	NOUN
easat-2372	21	4	in	in	ADP
easat-2372	21	5	production	production	NOUN
easat-2372	21	6	are	be	AUX
easat-2372	21	7	common	common	ADJ
easat-2372	21	8	;	;	PUNCT
easat-2372	21	9	for	for	ADP
easat-2372	21	10	instance	instance	NOUN
easat-2372	21	11	,	,	PUNCT
easat-2372	21	12	rice	rice	NOUN
easat-2372	21	13	production	production	NOUN
easat-2372	21	14	in	in	ADP
easat-2372	21	15	2009	2009	NUM
easat-2372	21	16	-	-	SYM
easat-2372	21	17	10	10	NUM
easat-2372	21	18	dropped	drop	VERB
easat-2372	21	19	to	to	ADP
easat-2372	21	20	89.13	89.13	NUM
easat-2372	21	21	million	million	NUM
easat-2372	21	22	tons	ton	NOUN
easat-2372	21	23	from	from	ADP
easat-2372	21	24	the	the	DET
easat-2372	21	25	previous	previous	ADJ
easat-2372	21	26	year	year	NOUN
easat-2372	21	27	's	's	PART
easat-2372	21	28	99.8	99.8	NUM
easat-2372	21	29	million	million	NUM
easat-2372	21	30	tons	ton	NOUN
easat-2372	21	31	[	[	X
easat-2372	21	32	3	3	NUM
easat-2372	21	33	]	]	PUNCT
easat-2372	21	34	.	.	PUNCT
easat-2372	22	1	to	to	PART
easat-2372	22	2	address	address	VERB
easat-2372	22	3	this	this	PRON
easat-2372	22	4	,	,	PUNCT
easat-2372	22	5	improving	improve	VERB
easat-2372	22	6	agricultural	agricultural	ADJ
easat-2372	22	7	productivity	productivity	NOUN
easat-2372	22	8	is	be	AUX
easat-2372	22	9	essential	essential	ADJ
easat-2372	22	10	,	,	PUNCT
easat-2372	22	11	especially	especially	ADV
easat-2372	22	12	given	give	VERB
easat-2372	22	13	india	india	PROPN
easat-2372	22	14	's	's	PART
easat-2372	22	15	relatively	relatively	ADV
easat-2372	22	16	low	low	ADJ
easat-2372	22	17	average	average	ADJ
easat-2372	22	18	yield	yield	NOUN
easat-2372	22	19	compared	compare	VERB
easat-2372	22	20	to	to	ADP
easat-2372	22	21	other	other	ADJ
easat-2372	22	22	major	major	ADJ
easat-2372	22	23	rice	rice	NOUN
easat-2372	22	24	-	-	PUNCT
easat-2372	22	25	producing	produce	VERB
easat-2372	22	26	countries	country	NOUN
easat-2372	22	27	[	[	X
easat-2372	22	28	4	4	NUM
easat-2372	22	29	]	]	PUNCT
easat-2372	22	30	.	.	PUNCT
easat-2372	23	1	visible	visible	ADJ
easat-2372	23	2	effects	effect	NOUN
easat-2372	23	3	of	of	ADP
easat-2372	23	4	plant	plant	NOUN
easat-2372	23	5	diseases	disease	NOUN
easat-2372	23	6	,	,	PUNCT
easat-2372	23	7	referred	refer	VERB
easat-2372	23	8	to	to	ADP
easat-2372	23	9	as	as	ADP
easat-2372	23	10	symptoms	symptom	NOUN
easat-2372	23	11	,	,	PUNCT
easat-2372	23	12	are	be	AUX
easat-2372	23	13	critical	critical	ADJ
easat-2372	23	14	indicators	indicator	NOUN
easat-2372	23	15	in	in	ADP
easat-2372	23	16	diagnosing	diagnose	VERB
easat-2372	23	17	issues	issue	NOUN
easat-2372	23	18	.	.	PUNCT
easat-2372	24	1	these	these	DET
easat-2372	24	2	symptoms	symptom	NOUN
easat-2372	24	3	include	include	VERB
easat-2372	24	4	changes	change	NOUN
easat-2372	24	5	in	in	ADP
easat-2372	24	6	color	color	NOUN
easat-2372	24	7	,	,	PUNCT
easat-2372	24	8	shape	shape	NOUN
easat-2372	24	9	,	,	PUNCT
easat-2372	24	10	and	and	CCONJ
easat-2372	24	11	overall	overall	ADJ
easat-2372	24	12	plant	plant	NOUN
easat-2372	24	13	function	function	NOUN
easat-2372	24	14	,	,	PUNCT
easat-2372	24	15	which	which	PRON
easat-2372	24	16	are	be	AUX
easat-2372	24	17	caused	cause	VERB
easat-2372	24	18	by	by	ADP
easat-2372	24	19	either	either	CCONJ
easat-2372	24	20	abiotic	abiotic	ADJ
easat-2372	24	21	(	(	PUNCT
easat-2372	24	22	non	non	ADJ
easat-2372	24	23	-	-	ADJ
easat-2372	24	24	infectious	infectious	ADJ
easat-2372	24	25	)	)	PUNCT
easat-2372	24	26	or	or	CCONJ
easat-2372	24	27	biotic	biotic	ADJ
easat-2372	24	28	(	(	PUNCT
easat-2372	24	29	infectious	infectious	ADJ
easat-2372	24	30	)	)	PUNCT
easat-2372	24	31	factors	factor	NOUN
easat-2372	24	32	.	.	PUNCT
easat-2372	25	1	abiotic	abiotic	ADJ
easat-2372	25	2	diseases	disease	NOUN
easat-2372	25	3	stem	stem	VERB
easat-2372	25	4	from	from	ADP
easat-2372	25	5	external	external	ADJ
easat-2372	25	6	factors	factor	NOUN
easat-2372	25	7	,	,	PUNCT
easat-2372	25	8	such	such	ADJ
easat-2372	25	9	as	as	ADP
easat-2372	25	10	nutrient	nutrient	ADJ
easat-2372	25	11	deficiencies	deficiency	NOUN
easat-2372	25	12	or	or	CCONJ
easat-2372	25	13	soil	soil	NOUN
easat-2372	25	14	problems	problem	NOUN
easat-2372	25	15	,	,	PUNCT
easat-2372	25	16	and	and	CCONJ
easat-2372	25	17	do	do	AUX
easat-2372	25	18	not	not	PART
easat-2372	25	19	spread	spread	VERB
easat-2372	25	20	between	between	ADP
easat-2372	25	21	plants	plant	NOUN
easat-2372	25	22	.	.	PUNCT
easat-2372	26	1	in	in	ADP
easat-2372	26	2	contrast	contrast	NOUN
easat-2372	26	3	,	,	PUNCT
easat-2372	26	4	biotic	biotic	ADJ
easat-2372	26	5	diseases	disease	NOUN
easat-2372	26	6	are	be	AUX
easat-2372	26	7	caused	cause	VERB
easat-2372	26	8	by	by	ADP
easat-2372	26	9	pathogens	pathogen	NOUN
easat-2372	26	10	like	like	ADP
easat-2372	26	11	fungi	fungi	PROPN
easat-2372	26	12	,	,	PUNCT
easat-2372	26	13	bacteria	bacteria	NOUN
easat-2372	26	14	,	,	PUNCT
easat-2372	26	15	viruses	virus	NOUN
easat-2372	26	16	,	,	PUNCT
easat-2372	26	17	and	and	CCONJ
easat-2372	26	18	nematodes	nematode	NOUN
easat-2372	26	19	,	,	PUNCT
easat-2372	26	20	which	which	PRON
easat-2372	26	21	can	can	AUX
easat-2372	26	22	spread	spread	VERB
easat-2372	26	23	and	and	CCONJ
easat-2372	26	24	visibly	visibly	ADV
easat-2372	26	25	affect	affect	VERB
easat-2372	26	26	leaves	leave	NOUN
easat-2372	26	27	,	,	PUNCT
easat-2372	26	28	roots	root	NOUN
easat-2372	26	29	,	,	PUNCT
easat-2372	26	30	seeds	seed	NOUN
easat-2372	26	31	,	,	PUNCT
easat-2372	26	32	fruits	fruit	NOUN
easat-2372	26	33	,	,	PUNCT
easat-2372	26	34	and	and	CCONJ
easat-2372	26	35	stems	stem	NOUN
easat-2372	26	36	.	.	PUNCT
easat-2372	27	1	2016	2016	NUM
easat-2372	27	2	edelweiss	edelweiss	PROPN
easat-2372	27	3	applied	apply	VERB
easat-2372	27	4	science	science	NOUN
easat-2372	27	5	and	and	CCONJ
easat-2372	27	6	technology	technology	NOUN
easat-2372	27	7	issn	issn	PROPN
easat-2372	27	8	:	:	PUNCT
easat-2372	27	9	2576	2576	NUM
easat-2372	27	10	-	-	SYM
easat-2372	27	11	8484	8484	NUM
easat-2372	27	12	vol	vol	NOUN
easat-2372	27	13	.	.	PROPN
easat-2372	27	14	8	8	NUM
easat-2372	27	15	,	,	PUNCT
easat-2372	27	16	no	no	INTJ
easat-2372	27	17	.	.	NOUN
easat-2372	28	1	6	6	NUM
easat-2372	28	2	:	:	SYM
easat-2372	28	3	2015	2015	NUM
easat-2372	28	4	-	-	SYM
easat-2372	28	5	2024	2024	NUM
easat-2372	28	6	,	,	PUNCT
easat-2372	28	7	2024	2024	NUM
easat-2372	28	8	doi	doi	NOUN
easat-2372	28	9	:	:	PUNCT
easat-2372	28	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	28	11	©	©	PROPN
easat-2372	28	12	2024	2024	NUM
easat-2372	28	13	by	by	ADP
easat-2372	28	14	the	the	DET
easat-2372	28	15	authors	author	NOUN
easat-2372	28	16	;	;	PUNCT
easat-2372	28	17	licensee	licensee	PROPN
easat-2372	28	18	learning	learning	NOUN
easat-2372	28	19	gate	gate	NOUN
easat-2372	28	20	this	this	DET
easat-2372	28	21	research	research	NOUN
easat-2372	28	22	focuses	focus	VERB
easat-2372	28	23	on	on	ADP
easat-2372	28	24	the	the	DET
easat-2372	28	25	identification	identification	NOUN
easat-2372	28	26	and	and	CCONJ
easat-2372	28	27	classification	classification	NOUN
easat-2372	28	28	of	of	ADP
easat-2372	28	29	rice	rice	NOUN
easat-2372	28	30	diseases	disease	NOUN
easat-2372	28	31	using	use	VERB
easat-2372	28	32	advanced	advanced	ADJ
easat-2372	28	33	technologies	technology	NOUN
easat-2372	28	34	.	.	PUNCT
easat-2372	29	1	domain	domain	NOUN
easat-2372	29	2	experts	expert	NOUN
easat-2372	29	3	have	have	AUX
easat-2372	29	4	been	be	AUX
easat-2372	29	5	consulted	consult	VERB
easat-2372	29	6	for	for	ADP
easat-2372	29	7	a	a	DET
easat-2372	29	8	deeper	deep	ADJ
easat-2372	29	9	understanding	understanding	NOUN
easat-2372	29	10	of	of	ADP
easat-2372	29	11	common	common	ADJ
easat-2372	29	12	rice	rice	NOUN
easat-2372	29	13	diseases	disease	NOUN
easat-2372	29	14	[	[	X
easat-2372	29	15	5	5	NUM
easat-2372	29	16	]	]	PUNCT
easat-2372	29	17	.	.	PUNCT
easat-2372	30	1	precision	precision	NOUN
easat-2372	30	2	farming	farming	NOUN
easat-2372	30	3	,	,	PUNCT
easat-2372	30	4	leveraging	leverage	VERB
easat-2372	30	5	technological	technological	ADJ
easat-2372	30	6	advancements	advancement	NOUN
easat-2372	30	7	such	such	ADJ
easat-2372	30	8	as	as	ADP
easat-2372	30	9	remote	remote	ADJ
easat-2372	30	10	sensing	sensing	NOUN
easat-2372	30	11	and	and	CCONJ
easat-2372	30	12	gis	gis	NOUN
easat-2372	30	13	,	,	PUNCT
easat-2372	30	14	helps	help	VERB
easat-2372	30	15	farmers	farmer	NOUN
easat-2372	30	16	optimize	optimize	VERB
easat-2372	30	17	inputs	input	NOUN
easat-2372	30	18	like	like	ADP
easat-2372	30	19	water	water	NOUN
easat-2372	30	20	,	,	PUNCT
easat-2372	30	21	pesticides	pesticide	NOUN
easat-2372	30	22	,	,	PUNCT
easat-2372	30	23	and	and	CCONJ
easat-2372	30	24	fertilizers	fertilizer	NOUN
easat-2372	30	25	.	.	PUNCT
easat-2372	31	1	recent	recent	ADJ
easat-2372	31	2	developments	development	NOUN
easat-2372	31	3	in	in	ADP
easat-2372	31	4	computer	computer	NOUN
easat-2372	31	5	vision	vision	NOUN
easat-2372	31	6	and	and	CCONJ
easat-2372	31	7	deep	deep	ADJ
easat-2372	31	8	learning	learning	NOUN
easat-2372	31	9	techniques	technique	NOUN
easat-2372	31	10	,	,	PUNCT
easat-2372	31	11	particularly	particularly	ADV
easat-2372	31	12	convolutional	convolutional	ADJ
easat-2372	31	13	neural	neural	ADJ
easat-2372	31	14	networks	network	NOUN
easat-2372	31	15	(	(	PUNCT
easat-2372	31	16	cnns	cnns	PROPN
easat-2372	31	17	)	)	PUNCT
easat-2372	31	18	,	,	PUNCT
easat-2372	31	19	offer	offer	VERB
easat-2372	31	20	promising	promise	VERB
easat-2372	31	21	solutions	solution	NOUN
easat-2372	31	22	for	for	ADP
easat-2372	31	23	automatic	automatic	ADJ
easat-2372	31	24	image	image	NOUN
easat-2372	31	25	classification	classification	NOUN
easat-2372	31	26	,	,	PUNCT
easat-2372	31	27	addressing	address	VERB
easat-2372	31	28	complex	complex	ADJ
easat-2372	31	29	agricultural	agricultural	ADJ
easat-2372	31	30	challenges	challenge	NOUN
easat-2372	31	31	[	[	X
easat-2372	31	32	6,7	6,7	NUM
easat-2372	31	33	]	]	PUNCT
easat-2372	31	34	.	.	PUNCT
easat-2372	32	1	1.1	1.1	NUM
easat-2372	32	2	.	.	PUNCT
easat-2372	32	3	related	relate	VERB
easat-2372	32	4	work	work	NOUN
easat-2372	32	5	convolutional	convolutional	ADJ
easat-2372	32	6	neural	neural	ADJ
easat-2372	32	7	networks	network	NOUN
easat-2372	32	8	(	(	PUNCT
easat-2372	32	9	cnn	cnn	PROPN
easat-2372	32	10	)	)	PUNCT
easat-2372	32	11	are	be	AUX
easat-2372	32	12	widely	widely	ADV
easat-2372	32	13	used	use	VERB
easat-2372	32	14	in	in	ADP
easat-2372	32	15	the	the	DET
easat-2372	32	16	development	development	NOUN
easat-2372	32	17	of	of	ADP
easat-2372	32	18	image	image	NOUN
easat-2372	32	19	classification	classification	NOUN
easat-2372	32	20	and	and	CCONJ
easat-2372	32	21	object	object	VERB
easat-2372	32	22	detection	detection	NOUN
easat-2372	32	23	models	model	NOUN
easat-2372	32	24	.	.	PUNCT
easat-2372	33	1	phadikar	phadikar	PROPN
easat-2372	33	2	et	et	PROPN
easat-2372	33	3	al	al	PROPN
easat-2372	33	4	.	.	PUNCT
easat-2372	34	1	[	[	X
easat-2372	34	2	8	8	NUM
easat-2372	34	3	]	]	PUNCT
easat-2372	34	4	proposed	propose	VERB
easat-2372	34	5	a	a	DET
easat-2372	34	6	method	method	NOUN
easat-2372	34	7	for	for	ADP
easat-2372	34	8	identifying	identify	VERB
easat-2372	34	9	rice	rice	NOUN
easat-2372	34	10	diseases	disease	NOUN
easat-2372	34	11	using	use	VERB
easat-2372	34	12	pattern	pattern	NOUN
easat-2372	34	13	detection	detection	NOUN
easat-2372	34	14	techniques	technique	NOUN
easat-2372	34	15	,	,	PUNCT
easat-2372	34	16	specifically	specifically	ADV
easat-2372	34	17	the	the	DET
easat-2372	34	18	self	self	NOUN
easat-2372	34	19	-	-	PUNCT
easat-2372	34	20	organizing	organize	VERB
easat-2372	34	21	map	map	NOUN
easat-2372	34	22	(	(	PUNCT
easat-2372	34	23	som	som	NOUN
easat-2372	34	24	)	)	PUNCT
easat-2372	34	25	neural	neural	ADJ
easat-2372	34	26	network	network	NOUN
easat-2372	34	27	.	.	PUNCT
easat-2372	35	1	the	the	DET
easat-2372	35	2	authors	author	NOUN
easat-2372	35	3	introduced	introduce	VERB
easat-2372	35	4	a	a	DET
easat-2372	35	5	zoom	zoom	NOUN
easat-2372	35	6	-	-	PUNCT
easat-2372	35	7	in	in	ADP
easat-2372	35	8	algorithm	algorithm	NOUN
easat-2372	35	9	that	that	PRON
easat-2372	35	10	renders	render	VERB
easat-2372	35	11	image	image	NOUN
easat-2372	35	12	features	feature	VERB
easat-2372	35	13	through	through	ADP
easat-2372	35	14	a	a	DET
easat-2372	35	15	simple	simple	ADJ
easat-2372	35	16	,	,	PUNCT
easat-2372	35	17	computationally	computationally	ADV
easat-2372	35	18	efficient	efficient	ADJ
easat-2372	35	19	process	process	NOUN
easat-2372	35	20	.	.	PUNCT
easat-2372	36	1	sanyal	sanyal	PROPN
easat-2372	36	2	,	,	PUNCT
easat-2372	36	3	p.	p.	NOUN
easat-2372	36	4	,	,	PUNCT
easat-2372	36	5	and	and	CCONJ
easat-2372	36	6	patel	patel	PROPN
easat-2372	36	7	,	,	PUNCT
easat-2372	36	8	s.c	s.c	PROPN
easat-2372	36	9	.	.	PUNCT
easat-2372	37	1	[	[	X
easat-2372	37	2	9	9	NUM
easat-2372	37	3	]	]	PUNCT
easat-2372	37	4	focused	focus	VERB
easat-2372	37	5	on	on	ADP
easat-2372	37	6	detecting	detect	VERB
easat-2372	37	7	patterns	pattern	NOUN
easat-2372	37	8	of	of	ADP
easat-2372	37	9	two	two	NUM
easat-2372	37	10	rice	rice	NOUN
easat-2372	37	11	plant	plant	NOUN
easat-2372	37	12	diseases	disease	NOUN
easat-2372	37	13	using	use	VERB
easat-2372	37	14	a	a	DET
easat-2372	37	15	multi	multi	ADJ
easat-2372	37	16	-	-	ADJ
easat-2372	37	17	layer	layer	ADJ
easat-2372	37	18	perceptron	perceptron	NOUN
easat-2372	37	19	(	(	PUNCT
easat-2372	37	20	mlp	mlp	NOUN
easat-2372	37	21	)	)	PUNCT
easat-2372	37	22	classifier	classifier	NOUN
easat-2372	37	23	.	.	PUNCT
easat-2372	38	1	their	their	PRON
easat-2372	38	2	validated	validated	ADJ
easat-2372	38	3	analysis	analysis	NOUN
easat-2372	38	4	showed	show	VERB
easat-2372	38	5	that	that	SCONJ
easat-2372	38	6	89.26	89.26	NUM
easat-2372	38	7	%	%	NOUN
easat-2372	38	8	of	of	ADP
easat-2372	38	9	pixels	pixel	NOUN
easat-2372	38	10	were	be	AUX
easat-2372	38	11	accurately	accurately	ADV
easat-2372	38	12	organized	organize	VERB
easat-2372	38	13	.	.	PUNCT
easat-2372	39	1	a.	a.	PROPN
easat-2372	39	2	smith	smith	PROPN
easat-2372	39	3	,	,	PUNCT
easat-2372	39	4	j.s	j.s	PROPN
easat-2372	39	5	.	.	PUNCT
easat-2372	40	1	[	[	X
easat-2372	40	2	10	10	NUM
easat-2372	40	3	]	]	PUNCT
easat-2372	40	4	proposed	propose	VERB
easat-2372	40	5	a	a	DET
easat-2372	40	6	method	method	NOUN
easat-2372	40	7	for	for	ADP
easat-2372	40	8	identifying	identify	VERB
easat-2372	40	9	plant	plant	NOUN
easat-2372	40	10	pathogens	pathogen	NOUN
easat-2372	40	11	based	base	VERB
easat-2372	40	12	on	on	ADP
easat-2372	40	13	visible	visible	ADJ
easat-2372	40	14	signs	sign	NOUN
easat-2372	40	15	of	of	ADP
easat-2372	40	16	disease	disease	NOUN
easat-2372	40	17	in	in	ADP
easat-2372	40	18	color	color	NOUN
easat-2372	40	19	photographs	photograph	NOUN
easat-2372	40	20	.	.	PUNCT
easat-2372	41	1	the	the	DET
easat-2372	41	2	authors	author	NOUN
easat-2372	41	3	used	use	VERB
easat-2372	41	4	a	a	DET
easat-2372	41	5	support	support	NOUN
easat-2372	41	6	vector	vector	NOUN
easat-2372	41	7	machine	machine	NOUN
easat-2372	41	8	(	(	PUNCT
easat-2372	41	9	svm	svm	PROPN
easat-2372	41	10	)	)	PUNCT
easat-2372	41	11	to	to	PART
easat-2372	41	12	analyze	analyze	VERB
easat-2372	41	13	117	117	NUM
easat-2372	41	14	images	image	NOUN
easat-2372	41	15	of	of	ADP
easat-2372	41	16	cotton	cotton	NOUN
easat-2372	41	17	plants	plant	NOUN
easat-2372	41	18	,	,	PUNCT
easat-2372	41	19	considering	consider	VERB
easat-2372	41	20	features	feature	NOUN
easat-2372	41	21	like	like	ADP
easat-2372	41	22	gray	gray	ADJ
easat-2372	41	23	levels	level	NOUN
easat-2372	41	24	,	,	PUNCT
easat-2372	41	25	connectivity	connectivity	NOUN
easat-2372	41	26	,	,	PUNCT
easat-2372	41	27	and	and	CCONJ
easat-2372	41	28	texture	texture	NOUN
easat-2372	41	29	.	.	PUNCT
easat-2372	42	1	h.	h.	PROPN
easat-2372	42	2	al	al	PROPN
easat-2372	42	3	-	-	PROPN
easat-2372	42	4	hiary	hiary	PROPN
easat-2372	42	5	and	and	CCONJ
easat-2372	42	6	s.	s.	PROPN
easat-2372	42	7	bani	bani	PROPN
easat-2372	42	8	-	-	PUNCT
easat-2372	42	9	ahmad	ahmad	PROPN
easat-2372	42	10	[	[	X
easat-2372	42	11	11	11	NUM
easat-2372	42	12	]	]	PUNCT
easat-2372	42	13	suggested	suggest	VERB
easat-2372	42	14	a	a	DET
easat-2372	42	15	rapid	rapid	ADJ
easat-2372	42	16	and	and	CCONJ
easat-2372	42	17	precise	precise	ADJ
easat-2372	42	18	method	method	NOUN
easat-2372	42	19	for	for	ADP
easat-2372	42	20	diagnosing	diagnose	VERB
easat-2372	42	21	and	and	CCONJ
easat-2372	42	22	classifying	classify	VERB
easat-2372	42	23	plant	plant	NOUN
easat-2372	42	24	-	-	PUNCT
easat-2372	42	25	borne	bear	VERB
easat-2372	42	26	pathogens	pathogen	NOUN
easat-2372	42	27	by	by	ADP
easat-2372	42	28	integrating	integrate	VERB
easat-2372	42	29	k	k	PROPN
easat-2372	42	30	-	-	PUNCT
easat-2372	42	31	means	means	NOUN
easat-2372	42	32	clustering	cluster	VERB
easat-2372	42	33	with	with	ADP
easat-2372	42	34	neural	neural	ADJ
easat-2372	42	35	networks	network	NOUN
easat-2372	42	36	(	(	PUNCT
easat-2372	42	37	nns	nns	PROPN
easat-2372	42	38	)	)	PUNCT
easat-2372	42	39	.	.	PUNCT
easat-2372	43	1	bashir	bashir	PROPN
easat-2372	43	2	and	and	CCONJ
easat-2372	43	3	sabah	sabah	PROPN
easat-2372	44	1	[	[	X
easat-2372	44	2	12	12	NUM
easat-2372	44	3	]	]	PUNCT
easat-2372	44	4	introduced	introduce	VERB
easat-2372	44	5	a	a	DET
easat-2372	44	6	method	method	NOUN
easat-2372	44	7	for	for	ADP
easat-2372	44	8	remote	remote	ADJ
easat-2372	44	9	disease	disease	NOUN
easat-2372	44	10	diagnosis	diagnosis	NOUN
easat-2372	44	11	in	in	ADP
easat-2372	44	12	malus	malus	PROPN
easat-2372	44	13	domestica	domestica	PROPN
easat-2372	44	14	using	use	VERB
easat-2372	44	15	image	image	NOUN
easat-2372	44	16	analysis	analysis	NOUN
easat-2372	44	17	and	and	CCONJ
easat-2372	44	18	k	k	NOUN
easat-2372	44	19	-	-	PUNCT
easat-2372	44	20	means	means	NOUN
easat-2372	44	21	clustering	clustering	NOUN
easat-2372	44	22	.	.	PUNCT
easat-2372	45	1	neumann	neumann	PROPN
easat-2372	45	2	et	et	PROPN
easat-2372	45	3	al	al	PROPN
easat-2372	45	4	.	.	PUNCT
easat-2372	46	1	[	[	X
easat-2372	46	2	13	13	NUM
easat-2372	46	3	]	]	PUNCT
easat-2372	46	4	proposed	propose	VERB
easat-2372	46	5	an	an	DET
easat-2372	46	6	approach	approach	NOUN
easat-2372	46	7	for	for	ADP
easat-2372	46	8	cell	cell	NOUN
easat-2372	46	9	disease	disease	NOUN
easat-2372	46	10	detection	detection	NOUN
easat-2372	46	11	using	use	VERB
easat-2372	46	12	core	core	NOUN
easat-2372	46	13	-	-	PUNCT
easat-2372	46	14	specific	specific	ADJ
easat-2372	46	15	features	feature	NOUN
easat-2372	46	16	,	,	PUNCT
easat-2372	46	17	achieving	achieve	VERB
easat-2372	46	18	highly	highly	ADV
easat-2372	46	19	accurate	accurate	ADJ
easat-2372	46	20	predictions	prediction	NOUN
easat-2372	46	21	on	on	ADP
easat-2372	46	22	mobile	mobile	ADJ
easat-2372	46	23	devices	device	NOUN
easat-2372	46	24	with	with	ADP
easat-2372	46	25	low	low	ADJ
easat-2372	46	26	-	-	PUNCT
easat-2372	46	27	cost	cost	NOUN
easat-2372	46	28	computing	computing	NOUN
easat-2372	46	29	.	.	PUNCT
easat-2372	47	1	sachin	sachin	PROPN
easat-2372	47	2	d.	d.	PROPN
easat-2372	47	3	khirade	khirade	VERB
easat-2372	47	4	[	[	X
easat-2372	47	5	14	14	NUM
easat-2372	47	6	]	]	PUNCT
easat-2372	47	7	developed	develop	VERB
easat-2372	47	8	a	a	DET
easat-2372	47	9	method	method	NOUN
easat-2372	47	10	for	for	ADP
easat-2372	47	11	plant	plant	NOUN
easat-2372	47	12	disease	disease	NOUN
easat-2372	47	13	diagnosis	diagnosis	NOUN
easat-2372	47	14	using	use	VERB
easat-2372	47	15	artificial	artificial	ADJ
easat-2372	47	16	neural	neural	ADJ
easat-2372	47	17	networks	network	NOUN
easat-2372	47	18	(	(	PUNCT
easat-2372	47	19	ann	ann	PROPN
easat-2372	47	20	)	)	PUNCT
easat-2372	47	21	,	,	PUNCT
easat-2372	47	22	classifying	classify	VERB
easat-2372	47	23	diseases	disease	NOUN
easat-2372	47	24	from	from	ADP
easat-2372	47	25	rgb	rgb	PROPN
easat-2372	47	26	leaf	leaf	NOUN
easat-2372	47	27	images	image	NOUN
easat-2372	47	28	.	.	PUNCT
easat-2372	48	1	various	various	ADJ
easat-2372	48	2	methods	method	NOUN
easat-2372	48	3	such	such	ADJ
easat-2372	48	4	as	as	ADP
easat-2372	48	5	feature	feature	NOUN
easat-2372	48	6	mapping	mapping	NOUN
easat-2372	48	7	,	,	PUNCT
easat-2372	48	8	backpropagation	backpropagation	NOUN
easat-2372	48	9	algorithms	algorithm	NOUN
easat-2372	48	10	,	,	PUNCT
easat-2372	48	11	and	and	CCONJ
easat-2372	48	12	svms	svms	NOUN
easat-2372	48	13	were	be	AUX
easat-2372	48	14	effectively	effectively	ADV
easat-2372	48	15	employed	employ	VERB
easat-2372	48	16	.	.	PUNCT
easat-2372	49	1	p.	p.	NOUN
easat-2372	49	2	mohanty	mohanty	PROPN
easat-2372	49	3	et	et	PROPN
easat-2372	49	4	al	al	PROPN
easat-2372	49	5	.	.	PUNCT
easat-2372	50	1	[	[	X
easat-2372	50	2	15	15	NUM
easat-2372	50	3	]	]	PUNCT
easat-2372	50	4	developed	develop	VERB
easat-2372	50	5	a	a	DET
easat-2372	50	6	deep	deep	ADJ
easat-2372	50	7	learning	learning	NOUN
easat-2372	50	8	model	model	NOUN
easat-2372	50	9	on	on	ADP
easat-2372	50	10	a	a	DET
easat-2372	50	11	public	public	ADJ
easat-2372	50	12	dataset	dataset	NOUN
easat-2372	50	13	and	and	CCONJ
easat-2372	50	14	created	create	VERB
easat-2372	50	15	a	a	DET
easat-2372	50	16	mobile	mobile	ADJ
easat-2372	50	17	application	application	NOUN
easat-2372	50	18	for	for	ADP
easat-2372	50	19	real	real	ADJ
easat-2372	50	20	-	-	PUNCT
easat-2372	50	21	time	time	NOUN
easat-2372	50	22	plant	plant	NOUN
easat-2372	50	23	disease	disease	NOUN
easat-2372	50	24	detection	detection	NOUN
easat-2372	50	25	.	.	PUNCT
easat-2372	51	1	sladojevic	sladojevic	PROPN
easat-2372	51	2	et	et	PROPN
easat-2372	51	3	al	al	PROPN
easat-2372	51	4	.	.	PUNCT
easat-2372	52	1	[	[	X
easat-2372	52	2	16	16	NUM
easat-2372	52	3	]	]	PUNCT
easat-2372	52	4	proposed	propose	VERB
easat-2372	52	5	a	a	DET
easat-2372	52	6	model	model	NOUN
easat-2372	52	7	capable	capable	ADJ
easat-2372	52	8	of	of	ADP
easat-2372	52	9	distinguishing	distinguish	VERB
easat-2372	52	10	13	13	NUM
easat-2372	52	11	different	different	ADJ
easat-2372	52	12	plant	plant	NOUN
easat-2372	52	13	pathogens	pathogen	NOUN
easat-2372	52	14	using	use	VERB
easat-2372	52	15	a	a	DET
easat-2372	52	16	deep	deep	ADJ
easat-2372	52	17	neural	neural	ADJ
easat-2372	52	18	network	network	NOUN
easat-2372	52	19	,	,	PUNCT
easat-2372	52	20	offering	offer	VERB
easat-2372	52	21	potential	potential	NOUN
easat-2372	52	22	for	for	ADP
easat-2372	52	23	global	global	ADJ
easat-2372	52	24	application	application	NOUN
easat-2372	52	25	in	in	ADP
easat-2372	52	26	leaf	leaf	NOUN
easat-2372	52	27	disease	disease	NOUN
easat-2372	52	28	detection	detection	NOUN
easat-2372	52	29	.	.	PUNCT
easat-2372	53	1	grinblat	grinblat	NOUN
easat-2372	53	2	et	et	PROPN
easat-2372	53	3	al	al	PROPN
easat-2372	53	4	.	.	PUNCT
easat-2372	54	1	[	[	X
easat-2372	54	2	17	17	NUM
easat-2372	54	3	]	]	PUNCT
easat-2372	54	4	suggested	suggest	VERB
easat-2372	54	5	an	an	DET
easat-2372	54	6	in	in	ADP
easat-2372	54	7	-	-	PUNCT
easat-2372	54	8	depth	depth	NOUN
easat-2372	54	9	study	study	NOUN
easat-2372	54	10	of	of	ADP
easat-2372	54	11	plant	plant	NOUN
easat-2372	54	12	identification	identification	NOUN
easat-2372	54	13	using	use	VERB
easat-2372	54	14	morphological	morphological	ADJ
easat-2372	54	15	vein	vein	ADJ
easat-2372	54	16	patterns	pattern	NOUN
easat-2372	54	17	,	,	PUNCT
easat-2372	54	18	while	while	SCONJ
easat-2372	54	19	barbedo	barbedo	VERB
easat-2372	54	20	et	et	PROPN
easat-2372	54	21	al	al	PROPN
easat-2372	54	22	.	.	PUNCT
easat-2372	55	1	[	[	X
easat-2372	55	2	18	18	NUM
easat-2372	55	3	]	]	PUNCT
easat-2372	55	4	focused	focus	VERB
easat-2372	55	5	on	on	ADP
easat-2372	55	6	identifying	identify	VERB
easat-2372	55	7	multiple	multiple	ADJ
easat-2372	55	8	plant	plant	NOUN
easat-2372	55	9	diseases	disease	NOUN
easat-2372	55	10	using	use	VERB
easat-2372	55	11	digital	digital	ADJ
easat-2372	55	12	image	image	NOUN
easat-2372	55	13	processing	processing	NOUN
easat-2372	55	14	,	,	PUNCT
easat-2372	55	15	addressing	address	VERB
easat-2372	55	16	the	the	DET
easat-2372	55	17	gap	gap	NOUN
easat-2372	55	18	between	between	ADP
easat-2372	55	19	current	current	ADJ
easat-2372	55	20	image	image	NOUN
easat-2372	55	21	-	-	PUNCT
easat-2372	55	22	based	base	VERB
easat-2372	55	23	diagnostics	diagnostic	NOUN
easat-2372	55	24	and	and	CCONJ
easat-2372	55	25	real	real	ADJ
easat-2372	55	26	-	-	PUNCT
easat-2372	55	27	world	world	NOUN
easat-2372	55	28	needs	need	NOUN
easat-2372	55	29	.	.	PUNCT
easat-2372	56	1	alvaro	alvaro	PROPN
easat-2372	56	2	f.	f.	PROPN
easat-2372	56	3	fuentes	fuentes	PROPN
easat-2372	57	1	[	[	X
easat-2372	57	2	19	19	NUM
easat-2372	57	3	]	]	PUNCT
easat-2372	57	4	introduced	introduce	VERB
easat-2372	57	5	a	a	DET
easat-2372	57	6	three	three	NUM
easat-2372	57	7	-	-	PUNCT
easat-2372	57	8	step	step	NOUN
easat-2372	57	9	process	process	NOUN
easat-2372	57	10	that	that	PRON
easat-2372	57	11	improved	improve	VERB
easat-2372	57	12	the	the	DET
easat-2372	57	13	identification	identification	NOUN
easat-2372	57	14	of	of	ADP
easat-2372	57	15	plant	plant	NOUN
easat-2372	57	16	diseases	disease	NOUN
easat-2372	57	17	by	by	ADP
easat-2372	57	18	focusing	focus	VERB
easat-2372	57	19	on	on	ADP
easat-2372	57	20	different	different	ADJ
easat-2372	57	21	plant	plant	NOUN
easat-2372	57	22	parts	part	NOUN
easat-2372	57	23	(	(	PUNCT
easat-2372	57	24	stems	stem	NOUN
easat-2372	57	25	,	,	PUNCT
easat-2372	57	26	leaves	leave	NOUN
easat-2372	57	27	,	,	PUNCT
easat-2372	57	28	and	and	CCONJ
easat-2372	57	29	fruits	fruit	NOUN
easat-2372	57	30	)	)	PUNCT
easat-2372	57	31	,	,	PUNCT
easat-2372	57	32	achieving	achieve	VERB
easat-2372	57	33	approximately	approximately	ADV
easat-2372	57	34	96	96	NUM
easat-2372	57	35	%	%	NOUN
easat-2372	57	36	accuracy	accuracy	NOUN
easat-2372	57	37	.	.	PUNCT
easat-2372	58	1	1.2	1.2	NUM
easat-2372	58	2	.	.	PUNCT
easat-2372	58	3	problem	problem	NOUN
easat-2372	58	4	statement	statement	NOUN
easat-2372	58	5	deep	deep	ADJ
easat-2372	58	6	learning	learning	NOUN
easat-2372	58	7	experiments	experiment	NOUN
easat-2372	58	8	,	,	PUNCT
easat-2372	58	9	particularly	particularly	ADV
easat-2372	58	10	those	those	PRON
easat-2372	58	11	involving	involve	VERB
easat-2372	58	12	convolutional	convolutional	ADJ
easat-2372	58	13	neural	neural	ADJ
easat-2372	58	14	networks	network	NOUN
easat-2372	58	15	(	(	PUNCT
easat-2372	58	16	cnns	cnns	PROPN
easat-2372	58	17	)	)	PUNCT
easat-2372	58	18	,	,	PUNCT
easat-2372	58	19	require	require	VERB
easat-2372	58	20	large	large	ADJ
easat-2372	58	21	datasets	dataset	NOUN
easat-2372	58	22	to	to	PART
easat-2372	58	23	effectively	effectively	ADV
easat-2372	58	24	train	train	NOUN
easat-2372	58	25	models	model	NOUN
easat-2372	58	26	.	.	PUNCT
easat-2372	59	1	in	in	ADP
easat-2372	59	2	cases	case	NOUN
easat-2372	59	3	where	where	SCONJ
easat-2372	59	4	large	large	ADJ
easat-2372	59	5	datasets	dataset	NOUN
easat-2372	59	6	are	be	AUX
easat-2372	59	7	unavailable	unavailable	ADJ
easat-2372	59	8	,	,	PUNCT
easat-2372	59	9	model	model	NOUN
easat-2372	59	10	accuracy	accuracy	NOUN
easat-2372	59	11	and	and	CCONJ
easat-2372	59	12	precision	precision	NOUN
easat-2372	59	13	often	often	ADV
easat-2372	59	14	decline	decline	VERB
easat-2372	59	15	.	.	PUNCT
easat-2372	60	1	to	to	PART
easat-2372	60	2	address	address	VERB
easat-2372	60	3	this	this	DET
easat-2372	60	4	challenge	challenge	NOUN
easat-2372	60	5	,	,	PUNCT
easat-2372	60	6	a	a	DET
easat-2372	60	7	deep	deep	ADJ
easat-2372	60	8	convolutional	convolutional	ADJ
easat-2372	60	9	generative	generative	ADJ
easat-2372	60	10	adversarial	adversarial	ADJ
easat-2372	60	11	network	network	NOUN
easat-2372	60	12	(	(	PUNCT
easat-2372	60	13	dcgan	dcgan	NOUN
easat-2372	60	14	)	)	PUNCT
easat-2372	60	15	is	be	AUX
easat-2372	60	16	utilized	utilize	VERB
easat-2372	60	17	to	to	PART
easat-2372	60	18	generate	generate	VERB
easat-2372	60	19	synthetic	synthetic	ADJ
easat-2372	60	20	images	image	NOUN
easat-2372	60	21	.	.	PUNCT
easat-2372	61	1	the	the	DET
easat-2372	61	2	model	model	NOUN
easat-2372	61	3	's	's	PART
easat-2372	61	4	accuracy	accuracy	NOUN
easat-2372	61	5	is	be	AUX
easat-2372	61	6	then	then	ADV
easat-2372	61	7	evaluated	evaluate	VERB
easat-2372	61	8	using	use	VERB
easat-2372	61	9	a	a	DET
easat-2372	61	10	combined	combine	VERB
easat-2372	61	11	dataset	dataset	NOUN
easat-2372	61	12	of	of	ADP
easat-2372	61	13	original	original	ADJ
easat-2372	61	14	and	and	CCONJ
easat-2372	61	15	synthetic	synthetic	ADJ
easat-2372	61	16	images	image	NOUN
easat-2372	61	17	.	.	PUNCT
easat-2372	62	1	this	this	DET
easat-2372	62	2	paper	paper	NOUN
easat-2372	62	3	is	be	AUX
easat-2372	62	4	organized	organize	VERB
easat-2372	62	5	as	as	SCONJ
easat-2372	62	6	follows	follow	VERB
easat-2372	62	7	:	:	PUNCT
easat-2372	62	8	•	•	ADP
easat-2372	62	9	the	the	DET
easat-2372	62	10	architecture	architecture	NOUN
easat-2372	62	11	used	use	VERB
easat-2372	62	12	to	to	PART
easat-2372	62	13	generate	generate	VERB
easat-2372	62	14	synthetic	synthetic	ADJ
easat-2372	62	15	images	image	NOUN
easat-2372	62	16	using	use	VERB
easat-2372	62	17	dcgan	dcgan	NOUN
easat-2372	62	18	.	.	PUNCT
easat-2372	63	1	•	•	NUM
easat-2372	63	2	the	the	DET
easat-2372	63	3	dcgan	dcgan	NOUN
easat-2372	63	4	architecture	architecture	NOUN
easat-2372	63	5	,	,	PUNCT
easat-2372	63	6	which	which	PRON
easat-2372	63	7	includes	include	VERB
easat-2372	63	8	a	a	DET
easat-2372	63	9	generator	generator	NOUN
easat-2372	63	10	network	network	NOUN
easat-2372	63	11	to	to	PART
easat-2372	63	12	create	create	VERB
easat-2372	63	13	images	image	NOUN
easat-2372	63	14	and	and	CCONJ
easat-2372	63	15	a	a	DET
easat-2372	63	16	discriminator	discriminator	NOUN
easat-2372	63	17	network	network	NOUN
easat-2372	63	18	to	to	PART
easat-2372	63	19	differentiate	differentiate	VERB
easat-2372	63	20	between	between	ADP
easat-2372	63	21	generated	generate	VERB
easat-2372	63	22	and	and	CCONJ
easat-2372	63	23	original	original	ADJ
easat-2372	63	24	images	image	NOUN
easat-2372	63	25	.	.	PUNCT
easat-2372	64	1	•	•	NUM
easat-2372	64	2	the	the	DET
easat-2372	64	3	cnn	cnn	PROPN
easat-2372	64	4	model	model	NOUN
easat-2372	64	5	used	use	VERB
easat-2372	64	6	to	to	PART
easat-2372	64	7	classify	classify	VERB
easat-2372	64	8	diseased	diseased	ADJ
easat-2372	64	9	images	image	NOUN
easat-2372	64	10	after	after	ADP
easat-2372	64	11	integrating	integrate	VERB
easat-2372	64	12	synthetic	synthetic	ADJ
easat-2372	64	13	images	image	NOUN
easat-2372	64	14	with	with	ADP
easat-2372	64	15	the	the	DET
easat-2372	64	16	original	original	ADJ
easat-2372	64	17	dataset	dataset	NOUN
easat-2372	64	18	.	.	PUNCT
easat-2372	65	1	2017	2017	NUM
easat-2372	65	2	edelweiss	edelweiss	PROPN
easat-2372	65	3	applied	apply	VERB
easat-2372	65	4	science	science	NOUN
easat-2372	65	5	and	and	CCONJ
easat-2372	65	6	technology	technology	NOUN
easat-2372	65	7	issn	issn	PROPN
easat-2372	65	8	:	:	PUNCT
easat-2372	65	9	2576	2576	NUM
easat-2372	65	10	-	-	SYM
easat-2372	65	11	8484	8484	NUM
easat-2372	65	12	vol	vol	NOUN
easat-2372	65	13	.	.	PROPN
easat-2372	65	14	8	8	NUM
easat-2372	65	15	,	,	PUNCT
easat-2372	65	16	no	no	INTJ
easat-2372	65	17	.	.	NOUN
easat-2372	66	1	6	6	NUM
easat-2372	66	2	:	:	SYM
easat-2372	66	3	2015	2015	NUM
easat-2372	66	4	-	-	SYM
easat-2372	66	5	2024	2024	NUM
easat-2372	66	6	,	,	PUNCT
easat-2372	66	7	2024	2024	NUM
easat-2372	66	8	doi	doi	NOUN
easat-2372	66	9	:	:	PUNCT
easat-2372	66	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	66	11	©	©	PROPN
easat-2372	66	12	2024	2024	NUM
easat-2372	66	13	by	by	ADP
easat-2372	66	14	the	the	DET
easat-2372	66	15	authors	author	NOUN
easat-2372	66	16	;	;	PUNCT
easat-2372	66	17	licensee	licensee	PROPN
easat-2372	66	18	learning	learning	NOUN
easat-2372	66	19	gate	gate	NOUN
easat-2372	66	20	•	•	NOUN
easat-2372	66	21	evaluation	evaluation	NOUN
easat-2372	66	22	of	of	ADP
easat-2372	66	23	the	the	DET
easat-2372	66	24	deep	deep	ADJ
easat-2372	66	25	learning	learning	NOUN
easat-2372	66	26	model	model	NOUN
easat-2372	66	27	's	's	PART
easat-2372	66	28	performance	performance	NOUN
easat-2372	66	29	using	use	VERB
easat-2372	66	30	standard	standard	ADJ
easat-2372	66	31	metrics	metric	NOUN
easat-2372	66	32	after	after	ADP
easat-2372	66	33	training	training	NOUN
easat-2372	66	34	with	with	ADP
easat-2372	66	35	the	the	DET
easat-2372	66	36	combined	combine	VERB
easat-2372	66	37	dataset	dataset	NOUN
easat-2372	66	38	.	.	PUNCT
easat-2372	67	1	2	2	X
easat-2372	67	2	.	.	X
easat-2372	67	3	dataset	dataset	PROPN
easat-2372	67	4	&	&	CCONJ
easat-2372	67	5	methodology	methodology	PROPN
easat-2372	67	6	2.1	2.1	NUM
easat-2372	67	7	.	.	PUNCT
easat-2372	68	1	dataset	dataset	VERB
easat-2372	68	2	in	in	ADP
easat-2372	68	3	this	this	DET
easat-2372	68	4	paper	paper	NOUN
easat-2372	68	5	,	,	PUNCT
easat-2372	68	6	the	the	DET
easat-2372	68	7	rice	rice	NOUN
easat-2372	68	8	image	image	NOUN
easat-2372	68	9	dataset	dataset	VERB
easat-2372	68	10	[	[	X
easat-2372	68	11	20	20	NUM
easat-2372	68	12	]	]	PUNCT
easat-2372	68	13	was	be	AUX
easat-2372	68	14	selected	select	VERB
easat-2372	68	15	,	,	PUNCT
easat-2372	68	16	which	which	PRON
easat-2372	68	17	comprises	comprise	VERB
easat-2372	68	18	a	a	DET
easat-2372	68	19	total	total	NOUN
easat-2372	68	20	of	of	ADP
easat-2372	68	21	5,932	5,932	NUM
easat-2372	68	22	images	image	NOUN
easat-2372	68	23	across	across	ADP
easat-2372	68	24	various	various	ADJ
easat-2372	68	25	categories	category	NOUN
easat-2372	68	26	of	of	ADP
easat-2372	68	27	rice	rice	NOUN
easat-2372	68	28	diseases	disease	NOUN
easat-2372	68	29	,	,	PUNCT
easat-2372	68	30	including	include	VERB
easat-2372	68	31	bacterial	bacterial	ADJ
easat-2372	68	32	blight	blight	NOUN
easat-2372	68	33	,	,	PUNCT
easat-2372	68	34	blast	blast	NOUN
easat-2372	68	35	,	,	PUNCT
easat-2372	68	36	brown	brown	ADJ
easat-2372	68	37	spot	spot	NOUN
easat-2372	68	38	,	,	PUNCT
easat-2372	68	39	and	and	CCONJ
easat-2372	68	40	tungro	tungro	VERB
easat-2372	68	41	.	.	PUNCT
easat-2372	69	1	to	to	PART
easat-2372	69	2	address	address	VERB
easat-2372	69	3	the	the	DET
easat-2372	69	4	challenge	challenge	NOUN
easat-2372	69	5	of	of	ADP
easat-2372	69	6	limited	limited	ADJ
easat-2372	69	7	data	datum	NOUN
easat-2372	69	8	,	,	PUNCT
easat-2372	69	9	basic	basic	ADJ
easat-2372	69	10	data	datum	NOUN
easat-2372	69	11	augmentation	augmentation	NOUN
easat-2372	69	12	techniques	technique	NOUN
easat-2372	69	13	were	be	AUX
easat-2372	69	14	applied	apply	VERB
easat-2372	69	15	to	to	PART
easat-2372	69	16	enhance	enhance	VERB
easat-2372	69	17	the	the	DET
easat-2372	69	18	diversity	diversity	NOUN
easat-2372	69	19	of	of	ADP
easat-2372	69	20	the	the	DET
easat-2372	69	21	training	training	NOUN
easat-2372	69	22	set	set	NOUN
easat-2372	69	23	.	.	PUNCT
easat-2372	70	1	these	these	DET
easat-2372	70	2	techniques	technique	NOUN
easat-2372	70	3	included	include	VERB
easat-2372	70	4	transformations	transformation	NOUN
easat-2372	70	5	such	such	ADJ
easat-2372	70	6	as	as	ADP
easat-2372	70	7	image	image	NOUN
easat-2372	70	8	rotation	rotation	NOUN
easat-2372	70	9	,	,	PUNCT
easat-2372	70	10	flipping	flip	VERB
easat-2372	70	11	,	,	PUNCT
easat-2372	70	12	scaling	scaling	NOUN
easat-2372	70	13	,	,	PUNCT
easat-2372	70	14	and	and	CCONJ
easat-2372	70	15	cropping	cropping	NOUN
easat-2372	70	16	.	.	PUNCT
easat-2372	71	1	by	by	ADP
easat-2372	71	2	artificially	artificially	ADV
easat-2372	71	3	expanding	expand	VERB
easat-2372	71	4	the	the	DET
easat-2372	71	5	dataset	dataset	NOUN
easat-2372	71	6	,	,	PUNCT
easat-2372	71	7	the	the	DET
easat-2372	71	8	model	model	NOUN
easat-2372	71	9	was	be	AUX
easat-2372	71	10	provided	provide	VERB
easat-2372	71	11	with	with	ADP
easat-2372	71	12	a	a	DET
easat-2372	71	13	greater	great	ADJ
easat-2372	71	14	variety	variety	NOUN
easat-2372	71	15	of	of	ADP
easat-2372	71	16	image	image	NOUN
easat-2372	71	17	patterns	pattern	NOUN
easat-2372	71	18	,	,	PUNCT
easat-2372	71	19	which	which	PRON
easat-2372	71	20	helped	help	VERB
easat-2372	71	21	reduce	reduce	VERB
easat-2372	71	22	overfitting	overfitting	NOUN
easat-2372	71	23	,	,	PUNCT
easat-2372	71	24	improve	improve	VERB
easat-2372	71	25	generalization	generalization	NOUN
easat-2372	71	26	,	,	PUNCT
easat-2372	71	27	and	and	CCONJ
easat-2372	71	28	enhance	enhance	VERB
easat-2372	71	29	the	the	DET
easat-2372	71	30	precision	precision	NOUN
easat-2372	71	31	of	of	ADP
easat-2372	71	32	the	the	DET
easat-2372	71	33	deep	deep	ADJ
easat-2372	71	34	learning	learning	NOUN
easat-2372	71	35	model	model	NOUN
easat-2372	71	36	.	.	PUNCT
easat-2372	72	1	this	this	DET
easat-2372	72	2	approach	approach	NOUN
easat-2372	72	3	ensured	ensure	VERB
easat-2372	72	4	that	that	SCONJ
easat-2372	72	5	the	the	DET
easat-2372	72	6	model	model	NOUN
easat-2372	72	7	could	could	AUX
easat-2372	72	8	better	well	ADV
easat-2372	72	9	recognize	recognize	VERB
easat-2372	72	10	and	and	CCONJ
easat-2372	72	11	classify	classify	VERB
easat-2372	72	12	different	different	ADJ
easat-2372	72	13	disease	disease	NOUN
easat-2372	72	14	types	type	NOUN
easat-2372	72	15	,	,	PUNCT
easat-2372	72	16	even	even	ADV
easat-2372	72	17	with	with	ADP
easat-2372	72	18	variations	variation	NOUN
easat-2372	72	19	in	in	ADP
easat-2372	72	20	image	image	NOUN
easat-2372	72	21	orientation	orientation	NOUN
easat-2372	72	22	or	or	CCONJ
easat-2372	72	23	scale	scale	NOUN
easat-2372	72	24	.	.	PUNCT
easat-2372	73	1	figure	figure	NOUN
easat-2372	73	2	1	1	NUM
easat-2372	73	3	.	.	PUNCT
easat-2372	74	1	(	(	PUNCT
easat-2372	74	2	a)bacterial	a)bacterial	ADJ
easat-2372	74	3	blight	blight	NOUN
easat-2372	74	4	,	,	PUNCT
easat-2372	74	5	(	(	PUNCT
easat-2372	74	6	b)blast	b)blast	NOUN
easat-2372	74	7	,	,	PUNCT
easat-2372	74	8	(	(	PUNCT
easat-2372	74	9	c)brown	c)brown	NUM
easat-2372	74	10	spot	spot	NOUN
easat-2372	74	11	and(d)tungro	and(d)tungro	NOUN
easat-2372	74	12	.	.	PUNCT
easat-2372	75	1	3	3	X
easat-2372	75	2	.	.	X
easat-2372	75	3	methods	method	NOUN
easat-2372	75	4	3.1	3.1	NUM
easat-2372	75	5	.	.	PUNCT
easat-2372	76	1	generative	generative	ADJ
easat-2372	76	2	adversarial	adversarial	ADJ
easat-2372	76	3	network	network	NOUN
easat-2372	76	4	(	(	PUNCT
easat-2372	76	5	gan	gan	PROPN
easat-2372	76	6	)	)	PUNCT
easat-2372	76	7	the	the	DET
easat-2372	76	8	goal	goal	NOUN
easat-2372	76	9	for	for	ADP
easat-2372	76	10	gan	gan	PROPN
easat-2372	76	11	is	be	AUX
easat-2372	76	12	to	to	PART
easat-2372	76	13	model	model	VERB
easat-2372	76	14	“	"	PUNCT
easat-2372	76	15	how	how	SCONJ
easat-2372	76	16	the	the	DET
easat-2372	76	17	data	datum	NOUN
easat-2372	76	18	looks	look	VERB
easat-2372	76	19	like	like	ADP
easat-2372	76	20	(	(	PUNCT
easat-2372	76	21	density	density	NOUN
easat-2372	76	22	estimation	estimation	NOUN
easat-2372	76	23	)	)	PUNCT
easat-2372	76	24	”	"	PUNCT
easat-2372	76	25	and	and	CCONJ
easat-2372	76	26	generate	generate	VERB
easat-2372	76	27	new	new	ADJ
easat-2372	76	28	data	datum	NOUN
easat-2372	76	29	based	base	VERB
easat-2372	76	30	on	on	ADP
easat-2372	76	31	what	what	PRON
easat-2372	76	32	it	it	PRON
easat-2372	76	33	has	have	AUX
easat-2372	76	34	learned	learn	VERB
easat-2372	76	35	.	.	PUNCT
easat-2372	77	1	gans	gan	NOUN
easat-2372	77	2	are	be	AUX
easat-2372	77	3	unsupervised	unsupervised	ADJ
easat-2372	77	4	learning	learn	VERB
easat-2372	77	5	algorithms	algorithm	NOUN
easat-2372	77	6	with	with	ADP
easat-2372	77	7	loss	loss	NOUN
easat-2372	77	8	as	as	ADP
easat-2372	77	9	a	a	DET
easat-2372	77	10	supervised	supervised	ADJ
easat-2372	77	11	learning	learning	NOUN
easat-2372	77	12	component	component	NOUN
easat-2372	77	13	that	that	PRON
easat-2372	77	14	becomes	become	VERB
easat-2372	77	15	part	part	NOUN
easat-2372	77	16	of	of	ADP
easat-2372	77	17	the	the	DET
easat-2372	77	18	training	training	NOUN
easat-2372	77	19	.	.	PUNCT
easat-2372	78	1	in	in	ADP
easat-2372	78	2	2014	2014	NUM
easat-2372	78	3	,	,	PUNCT
easat-2372	78	4	ian	ian	PROPN
easat-2372	78	5	goodfellow	goodfellow	PROPN
easat-2372	78	6	introduced	introduce	VERB
easat-2372	78	7	a	a	DET
easat-2372	78	8	deep	deep	ADJ
easat-2372	78	9	neural	neural	ADJ
easat-2372	78	10	network	network	NOUN
easat-2372	78	11	architecture	architecture	NOUN
easat-2372	78	12	that	that	PRON
easat-2372	78	13	leverages	leverage	VERB
easat-2372	78	14	unsupervised	unsupervised	ADJ
easat-2372	78	15	machine	machine	NOUN
easat-2372	78	16	learning	learn	VERB
easat-2372	78	17	to	to	PART
easat-2372	78	18	produce	produce	VERB
easat-2372	78	19	data	datum	NOUN
easat-2372	78	20	[	[	X
easat-2372	78	21	21,22	21,22	X
easat-2372	78	22	]	]	X
easat-2372	78	23	.	.	PUNCT
easat-2372	79	1	a	a	DET
easat-2372	79	2	generative	generative	ADJ
easat-2372	79	3	model	model	NOUN
easat-2372	79	4	's	's	PART
easat-2372	79	5	specialized	specialized	ADJ
easat-2372	79	6	frameworks	framework	NOUN
easat-2372	79	7	are	be	AUX
easat-2372	79	8	called	call	VERB
easat-2372	79	9	gans	gan	NOUN
easat-2372	79	10	.	.	PUNCT
easat-2372	80	1	when	when	SCONJ
easat-2372	80	2	given	give	VERB
easat-2372	80	3	a	a	DET
easat-2372	80	4	set	set	NOUN
easat-2372	80	5	of	of	ADP
easat-2372	80	6	sample	sample	NOUN
easat-2372	80	7	images	image	NOUN
easat-2372	80	8	,	,	PUNCT
easat-2372	80	9	such	such	ADJ
easat-2372	80	10	as	as	ADP
easat-2372	80	11	x1	x1	PROPN
easat-2372	80	12	,	,	PUNCT
easat-2372	80	13	x2	x2	PROPN
easat-2372	80	14	a	a	DET
easat-2372	80	15	model	model	NOUN
easat-2372	80	16	learns	learn	VERB
easat-2372	80	17	the	the	DET
easat-2372	80	18	data	data	NOUN
easat-2372	80	19	distribution	distribution	NOUN
easat-2372	80	20	(	(	PUNCT
easat-2372	80	21	pdata	pdata	NOUN
easat-2372	80	22	)	)	PUNCT
easat-2372	80	23	in	in	ADP
easat-2372	80	24	order	order	NOUN
easat-2372	80	25	to	to	PART
easat-2372	80	26	produce	produce	VERB
easat-2372	80	27	new	new	ADJ
easat-2372	80	28	sample	sample	NOUN
easat-2372	80	29	.	.	PUNCT
easat-2372	81	1	it	it	PRON
easat-2372	81	2	is	be	AUX
easat-2372	81	3	made	make	VERB
easat-2372	81	4	up	up	ADP
easat-2372	81	5	of	of	ADP
easat-2372	81	6	the	the	DET
easat-2372	81	7	discriminator	discriminator	NOUN
easat-2372	81	8	(	(	PUNCT
easat-2372	81	9	d	d	NOUN
easat-2372	81	10	)	)	PUNCT
easat-2372	81	11	and	and	CCONJ
easat-2372	81	12	the	the	DET
easat-2372	81	13	generator	generator	NOUN
easat-2372	81	14	networks	network	NOUN
easat-2372	81	15	,	,	PUNCT
easat-2372	81	16	which	which	PRON
easat-2372	81	17	were	be	AUX
easat-2372	81	18	trained	train	VERB
easat-2372	81	19	concurrently	concurrently	ADV
easat-2372	81	20	(	(	PUNCT
easat-2372	81	21	g	g	NOUN
easat-2372	81	22	)	)	PUNCT
easat-2372	81	23	.	.	PUNCT
easat-2372	82	1	d	d	X
easat-2372	82	2	makes	make	VERB
easat-2372	82	3	a	a	DET
easat-2372	82	4	distinction	distinction	NOUN
easat-2372	82	5	between	between	ADP
easat-2372	82	6	the	the	DET
easat-2372	82	7	actual	actual	ADJ
easat-2372	82	8	and	and	CCONJ
easat-2372	82	9	fraudulent	fraudulent	ADJ
easat-2372	82	10	images	image	NOUN
easat-2372	82	11	it	it	PRON
easat-2372	82	12	has	have	AUX
easat-2372	82	13	obtained	obtain	VERB
easat-2372	82	14	.	.	PUNCT
easat-2372	83	1	it	it	PRON
easat-2372	83	2	receives	receive	VERB
easat-2372	83	3	an	an	DET
easat-2372	83	4	input	input	NOUN
easat-2372	83	5	of	of	ADP
easat-2372	83	6	i	i	PRON
easat-2372	83	7	and	and	CCONJ
easat-2372	83	8	produces	produce	VERB
easat-2372	83	9	d	d	NOUN
easat-2372	83	10	,	,	PUNCT
easat-2372	83	11	that	that	PRON
easat-2372	83	12	is	be	AUX
easat-2372	83	13	called	call	VERB
easat-2372	83	14	as	as	ADP
easat-2372	83	15	probability	probability	NOUN
easat-2372	83	16	of	of	ADP
easat-2372	83	17	original	original	ADJ
easat-2372	83	18	sample	sample	NOUN
easat-2372	83	19	(	(	PUNCT
easat-2372	83	20	i	i	NOUN
easat-2372	83	21	)	)	PUNCT
easat-2372	83	22	.	.	PUNCT
easat-2372	84	1	on	on	ADP
easat-2372	84	2	the	the	DET
easat-2372	84	3	other	other	ADJ
easat-2372	84	4	hand	hand	NOUN
easat-2372	84	5	generator	generator	NOUN
easat-2372	84	6	module	module	NOUN
easat-2372	84	7	create	create	VERB
easat-2372	84	8	new	new	ADJ
easat-2372	84	9	samples	sample	NOUN
easat-2372	84	10	by	by	ADP
easat-2372	84	11	mechanism	mechanism	NOUN
easat-2372	84	12	of	of	ADP
easat-2372	84	13	synthesis	synthesis	NOUN
easat-2372	84	14	input	input	NOUN
easat-2372	84	15	j1	j1	PROPN
easat-2372	84	16	,	,	PUNCT
easat-2372	84	17	j2	j2	PROPN
easat-2372	84	18	..	..	PUNCT
easat-2372	84	19	,jn	,jn	PUNCT
easat-2372	84	20	from	from	ADP
easat-2372	84	21	a	a	DET
easat-2372	84	22	kind	kind	NOUN
easat-2372	84	23	of	of	ADP
easat-2372	84	24	uniform	uniform	ADJ
easat-2372	84	25	distribution	distribution	NOUN
easat-2372	84	26	p(i	p(i	PROPN
easat-2372	84	27	)	)	PUNCT
easat-2372	84	28	and	and	CCONJ
easat-2372	84	29	pairing	pair	VERB
easat-2372	84	30	with	with	ADP
easat-2372	84	31	g(j	g(j	PROPN
easat-2372	84	32	)	)	PUNCT
easat-2372	84	33	to	to	PART
easat-2372	84	34	create	create	VERB
easat-2372	84	35	new	new	ADJ
easat-2372	84	36	image	image	NOUN
easat-2372	84	37	dimension	dimension	NOUN
easat-2372	84	38	p(g).generator	p(g).generator	NOUN
easat-2372	84	39	tries	try	VERB
easat-2372	84	40	to	to	PART
easat-2372	84	41	achieve	achieve	VERB
easat-2372	84	42	f(g)=f.(data)[35	f(g)=f.(data)[35	PROPN
easat-2372	84	43	]	]	PUNCT
easat-2372	84	44	.	.	PUNCT
easat-2372	85	1	to	to	PART
easat-2372	85	2	minimize	minimize	VERB
easat-2372	85	3	1	1	NUM
easat-2372	85	4	d(g(j	d(g(j	NOUN
easat-2372	85	5	)	)	PUNCT
easat-2372	85	6	)	)	PUNCT
easat-2372	85	7	or	or	CCONJ
easat-2372	85	8	maximize	maximize	VERB
easat-2372	85	9	d(g(j	d(g(j	PROPN
easat-2372	85	10	)	)	PUNCT
easat-2372	85	11	)	)	PUNCT
easat-2372	85	12	,	,	PUNCT
easat-2372	85	13	the	the	DET
easat-2372	85	14	generator	generator	NOUN
easat-2372	85	15	is	be	AUX
easat-2372	85	16	trained	train	VERB
easat-2372	85	17	,	,	PUNCT
easat-2372	85	18	during	during	ADP
easat-2372	85	19	training	training	NOUN
easat-2372	85	20	,	,	PUNCT
easat-2372	85	21	g	g	NOUN
easat-2372	85	22	increases	increase	VERB
easat-2372	85	23	its	its	PRON
easat-2372	85	24	ability	ability	NOUN
easat-2372	85	25	to	to	PART
easat-2372	85	26	create	create	VERB
easat-2372	85	27	more	more	ADV
easat-2372	85	28	realistic	realistic	ADJ
easat-2372	85	29	images	image	NOUN
easat-2372	85	30	.	.	PUNCT
easat-2372	86	1	d	d	NOUN
easat-2372	86	2	increases	increase	VERB
easat-2372	86	3	its	its	PRON
easat-2372	86	4	ability	ability	NOUN
easat-2372	86	5	to	to	PART
easat-2372	86	6	distinguish	distinguish	VERB
easat-2372	86	7	between	between	ADP
easat-2372	86	8	real	real	ADJ
easat-2372	86	9	and	and	CCONJ
easat-2372	86	10	artificial	artificial	ADJ
easat-2372	86	11	visuals.[35	visuals.[35	PROPN
easat-2372	86	12	]	]	PUNCT
easat-2372	86	13	the	the	DET
easat-2372	86	14	generator	generator	NOUN
easat-2372	86	15	produces	produce	VERB
easat-2372	86	16	a	a	DET
easat-2372	86	17	128x128x1	128x128x1	NUM
easat-2372	86	18	sized	sized	ADJ
easat-2372	86	19	image	image	NOUN
easat-2372	86	20	by	by	ADP
easat-2372	86	21	utilizing	utilize	VERB
easat-2372	86	22	a	a	DET
easat-2372	86	23	100	100	NUM
easat-2372	86	24	-	-	PUNCT
easat-2372	86	25	dimensional	dimensional	ADJ
easat-2372	86	26	input	input	NOUN
easat-2372	86	27	vector	vector	NOUN
easat-2372	86	28	containing	contain	VERB
easat-2372	86	29	random	random	ADJ
easat-2372	86	30	values	value	NOUN
easat-2372	86	31	drawn	draw	VERB
easat-2372	86	32	from	from	ADP
easat-2372	86	33	a	a	DET
easat-2372	86	34	uniform	uniform	ADJ
easat-2372	86	35	distribution	distribution	NOUN
easat-2372	86	36	.	.	PUNCT
easat-2372	87	1	the	the	DET
easat-2372	87	2	network	network	NOUN
easat-2372	87	3	architecture	architecture	NOUN
easat-2372	87	4	includes	include	VERB
easat-2372	87	5	four	four	NUM
easat-2372	87	6	fractional	fractional	ADJ
easat-2372	87	7	-	-	PUNCT
easat-2372	87	8	stride	stride	NOUN
easat-2372	87	9	convolutions	convolution	NOUN
easat-2372	87	10	with	with	ADP
easat-2372	87	11	4x4	4x4	NUM
easat-2372	87	12	sized	sized	ADJ
easat-2372	87	13	kernels	kernel	NOUN
easat-2372	87	14	to	to	ADP
easat-2372	87	15	up	up	ADJ
easat-2372	87	16	-	-	PUNCT
easat-2372	87	17	sample	sample	VERB
easat-2372	87	18	the	the	DET
easat-2372	87	19	image	image	NOUN
easat-2372	87	20	,	,	PUNCT
easat-2372	87	21	along	along	ADP
easat-2372	87	22	with	with	ADP
easat-2372	87	23	a	a	DET
easat-2372	87	24	fully	fully	ADV
easat-2372	87	25	connected	connect	VERB
easat-2372	87	26	layer	layer	NOUN
easat-2372	87	27	scaled	scale	VERB
easat-2372	87	28	to	to	ADP
easat-2372	87	29	4x4x128	4x4x128	NUM
easat-2372	87	30	.	.	PUNCT
easat-2372	88	1	appending	append	VERB
easat-2372	88	2	zeros	zero	NOUN
easat-2372	88	3	in	in	ADP
easat-2372	88	4	the	the	DET
easat-2372	88	5	pixels	pixel	NOUN
easat-2372	88	6	expands	expand	VERB
easat-2372	88	7	our	our	PRON
easat-2372	88	8	output	output	NOUN
easat-2372	88	9	of	of	ADP
easat-2372	88	10	each	each	DET
easat-2372	88	11	fractional	fractional	ADJ
easat-2372	88	12	stride	stride	NOUN
easat-2372	88	13	convolution	convolution	NOUN
easat-2372	88	14	.	.	PUNCT
easat-2372	89	1	at	at	ADP
easat-2372	89	2	every	every	DET
easat-2372	89	3	layer	layer	NOUN
easat-2372	89	4	to	to	PART
easat-2372	89	5	handle	handle	VERB
easat-2372	89	6	gradient	gradient	ADJ
easat-2372	89	7	vanishing	vanishing	NOUN
easat-2372	89	8	problem	problem	NOUN
easat-2372	89	9	batch	batch	NOUN
easat-2372	89	10	normalization	normalization	NOUN
easat-2372	89	11	is	be	AUX
easat-2372	89	12	added	add	VERB
easat-2372	89	13	at	at	ADP
easat-2372	89	14	every	every	DET
easat-2372	89	15	layer	layer	NOUN
easat-2372	89	16	,	,	PUNCT
easat-2372	89	17	including	include	VERB
easat-2372	89	18	the	the	DET
easat-2372	89	19	output	output	NOUN
easat-2372	89	20	layer	layer	NOUN
easat-2372	89	21	,	,	PUNCT
easat-2372	89	22	to	to	PART
easat-2372	89	23	normalize	normalize	VERB
easat-2372	89	24	the	the	DET
easat-2372	89	25	output	output	NOUN
easat-2372	89	26	across	across	ADP
easat-2372	89	27	the	the	DET
easat-2372	89	28	mini	mini	ADJ
easat-2372	89	29	batch	batch	NOUN
easat-2372	89	30	.	.	PUNCT
easat-2372	90	1	this	this	DET
easat-2372	90	2	2018	2018	NUM
easat-2372	90	3	edelweiss	edelweiss	PROPN
easat-2372	90	4	applied	apply	VERB
easat-2372	90	5	science	science	NOUN
easat-2372	90	6	and	and	CCONJ
easat-2372	90	7	technology	technology	NOUN
easat-2372	90	8	issn	issn	PROPN
easat-2372	90	9	:	:	PUNCT
easat-2372	90	10	2576	2576	NUM
easat-2372	90	11	-	-	SYM
easat-2372	90	12	8484	8484	NUM
easat-2372	90	13	vol	vol	NOUN
easat-2372	90	14	.	.	PROPN
easat-2372	90	15	8	8	NUM
easat-2372	90	16	,	,	PUNCT
easat-2372	90	17	no	no	INTJ
easat-2372	90	18	.	.	NOUN
easat-2372	91	1	6	6	NUM
easat-2372	91	2	:	:	SYM
easat-2372	91	3	2015	2015	NUM
easat-2372	91	4	-	-	SYM
easat-2372	91	5	2024	2024	NUM
easat-2372	91	6	,	,	PUNCT
easat-2372	91	7	2024	2024	NUM
easat-2372	91	8	doi	doi	NOUN
easat-2372	91	9	:	:	PUNCT
easat-2372	91	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	91	11	©	©	PROPN
easat-2372	91	12	2024	2024	NUM
easat-2372	91	13	by	by	ADP
easat-2372	91	14	the	the	DET
easat-2372	91	15	authors	author	NOUN
easat-2372	91	16	;	;	PUNCT
easat-2372	91	17	licensee	licensee	PROPN
easat-2372	91	18	learning	learn	VERB
easat-2372	91	19	gate	gate	PROPN
easat-2372	91	20	normalization	normalization	NOUN
easat-2372	91	21	prevents	prevent	VERB
easat-2372	91	22	the	the	DET
easat-2372	91	23	generator	generator	NOUN
easat-2372	91	24	from	from	ADP
easat-2372	91	25	failing	fail	VERB
easat-2372	91	26	all	all	DET
easat-2372	91	27	samples	sample	NOUN
easat-2372	91	28	to	to	ADP
easat-2372	91	29	a	a	DET
easat-2372	91	30	single	single	ADJ
easat-2372	91	31	point	point	NOUN
easat-2372	91	32	and	and	CCONJ
easat-2372	91	33	helps	help	VERB
easat-2372	91	34	stabilize	stabilize	VERB
easat-2372	91	35	the	the	DET
easat-2372	91	36	learning	learning	NOUN
easat-2372	91	37	process	process	NOUN
easat-2372	91	38	of	of	ADP
easat-2372	91	39	the	the	DET
easat-2372	91	40	dcgan	dcgan	NOUN
easat-2372	91	41	.	.	PUNCT
easat-2372	92	1	the	the	DET
easat-2372	92	2	output	output	NOUN
easat-2372	92	3	layer	layer	NOUN
easat-2372	92	4	employs	employ	VERB
easat-2372	92	5	the	the	DET
easat-2372	92	6	tanh	tanh	PROPN
easat-2372	92	7	activation	activation	NOUN
easat-2372	92	8	function	function	NOUN
easat-2372	92	9	,	,	PUNCT
easat-2372	92	10	while	while	SCONJ
easat-2372	92	11	all	all	DET
easat-2372	92	12	other	other	ADJ
easat-2372	92	13	layer	layer	NOUN
easat-2372	92	14	’s	’s	PART
easat-2372	92	15	use	use	NOUN
easat-2372	92	16	relu	relu	NOUN
easat-2372	92	17	.	.	PUNCT
easat-2372	93	1	the	the	DET
easat-2372	93	2	discriminator	discriminator	NOUN
easat-2372	93	3	network	network	NOUN
easat-2372	93	4	receives	receive	VERB
easat-2372	93	5	128x128x1	128x128x1	NUM
easat-2372	93	6	images	image	NOUN
easat-2372	93	7	as	as	ADP
easat-2372	93	8	input	input	NOUN
easat-2372	93	9	and	and	CCONJ
easat-2372	93	10	produces	produce	VERB
easat-2372	93	11	result	result	NOUN
easat-2372	93	12	regarding	regard	VERB
easat-2372	93	13	the	the	DET
easat-2372	93	14	validity	validity	NOUN
easat-2372	93	15	of	of	ADP
easat-2372	93	16	the	the	DET
easat-2372	93	17	images	image	NOUN
easat-2372	93	18	.	.	PUNCT
easat-2372	94	1	it	it	PRON
easat-2372	94	2	has	have	VERB
easat-2372	94	3	five	five	NUM
easat-2372	94	4	completely	completely	ADV
easat-2372	94	5	connected	connected	ADJ
easat-2372	94	6	layers	layer	NOUN
easat-2372	94	7	with	with	ADP
easat-2372	94	8	and	and	CCONJ
easat-2372	94	9	four	four	NUM
easat-2372	94	10	convolutions	convolution	NOUN
easat-2372	94	11	.	.	PUNCT
easat-2372	95	1	stride	stride	NOUN
easat-2372	95	2	convolutions	convolution	NOUN
easat-2372	95	3	are	be	AUX
easat-2372	95	4	used	use	VERB
easat-2372	95	5	to	to	PART
easat-2372	95	6	reduce	reduce	VERB
easat-2372	95	7	the	the	DET
easat-2372	95	8	spatial	spatial	ADJ
easat-2372	95	9	dimensionality	dimensionality	NOUN
easat-2372	95	10	.	.	PUNCT
easat-2372	96	1	the	the	DET
easat-2372	96	2	likelihood	likelihood	NOUN
easat-2372	96	3	probability	probability	NOUN
easat-2372	96	4	score	score	NOUN
easat-2372	96	5	of	of	ADP
easat-2372	96	6	images	image	NOUN
easat-2372	96	7	is	be	AUX
easat-2372	96	8	output	output	NOUN
easat-2372	96	9	using	use	VERB
easat-2372	96	10	the	the	DET
easat-2372	96	11	sigmoid	sigmoid	NOUN
easat-2372	96	12	function	function	NOUN
easat-2372	96	13	as	as	ADP
easat-2372	96	14	[	[	X
easat-2372	96	15	0	0	NUM
easat-2372	96	16	,	,	PUNCT
easat-2372	96	17	1	1	NUM
easat-2372	96	18	]	]	PUNCT
easat-2372	96	19	.	.	PUNCT
easat-2372	97	1	additionally	additionally	ADV
easat-2372	97	2	,	,	PUNCT
easat-2372	97	3	every	every	DET
easat-2372	97	4	layer	layer	NOUN
easat-2372	97	5	—	—	PUNCT
easat-2372	97	6	aside	aside	ADV
easat-2372	97	7	from	from	ADP
easat-2372	97	8	the	the	DET
easat-2372	97	9	second	second	NOUN
easat-2372	97	10	and	and	CCONJ
easat-2372	97	11	the	the	DET
easat-2372	97	12	output	output	NOUN
easat-2372	97	13	layers	layer	NOUN
easat-2372	97	14	—	—	PUNCT
easat-2372	97	15	uses	use	VERB
easat-2372	97	16	the	the	DET
easat-2372	97	17	dropout	dropout	NOUN
easat-2372	97	18	technique	technique	NOUN
easat-2372	97	19	to	to	PART
easat-2372	97	20	avoid	avoid	VERB
easat-2372	97	21	the	the	DET
easat-2372	97	22	over	over	ADV
easat-2372	97	23	-	-	PUNCT
easat-2372	97	24	fitting	fitting	ADJ
easat-2372	97	25	problem	problem	NOUN
easat-2372	97	26	.	.	PUNCT
easat-2372	98	1	3.2	3.2	NUM
easat-2372	98	2	.	.	PUNCT
easat-2372	99	1	convolutional	convolutional	ADJ
easat-2372	99	2	neural	neural	ADJ
easat-2372	99	3	networks	network	NOUN
easat-2372	99	4	(	(	PUNCT
easat-2372	99	5	cnn	cnn	PROPN
easat-2372	99	6	)	)	PUNCT
easat-2372	99	7	neural	neural	ADJ
easat-2372	99	8	network	network	NOUN
easat-2372	99	9	that	that	PRON
easat-2372	99	10	has	have	VERB
easat-2372	99	11	multiple	multiple	ADJ
easat-2372	99	12	convolutional	convolutional	ADJ
easat-2372	99	13	layers	layer	NOUN
easat-2372	99	14	and	and	CCONJ
easat-2372	99	15	used	use	VERB
easat-2372	99	16	for	for	ADP
easat-2372	99	17	image	image	NOUN
easat-2372	99	18	processing	processing	NOUN
easat-2372	99	19	,	,	PUNCT
easat-2372	99	20	segmentation	segmentation	NOUN
easat-2372	99	21	,	,	PUNCT
easat-2372	99	22	classification	classification	NOUN
easat-2372	99	23	and	and	CCONJ
easat-2372	99	24	for	for	ADP
easat-2372	99	25	data	datum	NOUN
easat-2372	99	26	,	,	PUNCT
easat-2372	99	27	which	which	PRON
easat-2372	99	28	is	be	AUX
easat-2372	99	29	auto	auto	NOUN
easat-2372	99	30	corrected	correct	VERB
easat-2372	99	31	,	,	PUNCT
easat-2372	99	32	is	be	AUX
easat-2372	99	33	known	know	VERB
easat-2372	99	34	to	to	PART
easat-2372	99	35	be	be	AUX
easat-2372	99	36	convolutional	convolutional	ADJ
easat-2372	99	37	neural	neural	ADJ
easat-2372	99	38	network	network	NOUN
easat-2372	99	39	(	(	PUNCT
easat-2372	99	40	cnn	cnn	PROPN
easat-2372	99	41	)	)	PUNCT
easat-2372	99	42	,	,	PUNCT
easat-2372	99	43	cnn	cnn	PROPN
easat-2372	99	44	is	be	AUX
easat-2372	99	45	created	create	VERB
easat-2372	99	46	using	use	VERB
easat-2372	99	47	many	many	ADJ
easat-2372	99	48	layers	layer	NOUN
easat-2372	99	49	,	,	PUNCT
easat-2372	99	50	main	main	ADJ
easat-2372	99	51	layers	layer	NOUN
easat-2372	99	52	of	of	ADP
easat-2372	99	53	cnn	cnn	PROPN
easat-2372	99	54	are	be	AUX
easat-2372	99	55	:	:	PUNCT
easat-2372	99	56	the	the	DET
easat-2372	99	57	feature	feature	NOUN
easat-2372	99	58	extraction	extraction	NOUN
easat-2372	99	59	layer	layer	NOUN
easat-2372	99	60	i.e.	i.e.	X
easat-2372	99	61	convolutional	convolutional	ADJ
easat-2372	99	62	layer	layer	NOUN
easat-2372	99	63	.	.	PUNCT
easat-2372	100	1	when	when	SCONJ
easat-2372	100	2	an	an	DET
easat-2372	100	3	image	image	NOUN
easat-2372	100	4	is	be	AUX
easat-2372	100	5	passed	pass	VERB
easat-2372	100	6	as	as	ADP
easat-2372	100	7	input	input	NOUN
easat-2372	100	8	to	to	ADP
easat-2372	100	9	a	a	DET
easat-2372	100	10	cnn	cnn	PROPN
easat-2372	100	11	,	,	PUNCT
easat-2372	100	12	a	a	DET
easat-2372	100	13	specific	specific	ADJ
easat-2372	100	14	layer	layer	NOUN
easat-2372	100	15	in	in	ADP
easat-2372	100	16	the	the	DET
easat-2372	100	17	network	network	NOUN
easat-2372	100	18	detects	detect	VERB
easat-2372	100	19	the	the	DET
easat-2372	100	20	existence	existence	NOUN
easat-2372	100	21	of	of	ADP
easat-2372	100	22	a	a	DET
easat-2372	100	23	predefined	predefine	VERB
easat-2372	100	24	set	set	NOUN
easat-2372	100	25	of	of	ADP
easat-2372	100	26	features	feature	NOUN
easat-2372	100	27	within	within	ADP
easat-2372	100	28	the	the	DET
easat-2372	100	29	image	image	NOUN
easat-2372	100	30	.	.	PUNCT
easat-2372	101	1	each	each	DET
easat-2372	101	2	layer	layer	NOUN
easat-2372	101	3	in	in	ADP
easat-2372	101	4	the	the	DET
easat-2372	101	5	cnn	cnn	PROPN
easat-2372	101	6	can	can	AUX
easat-2372	101	7	be	be	AUX
easat-2372	101	8	seen	see	VERB
easat-2372	101	9	as	as	ADP
easat-2372	101	10	a	a	DET
easat-2372	101	11	filter	filter	NOUN
easat-2372	101	12	applied	apply	VERB
easat-2372	101	13	to	to	ADP
easat-2372	101	14	the	the	DET
easat-2372	101	15	image	image	NOUN
easat-2372	101	16	,	,	PUNCT
easat-2372	101	17	where	where	SCONJ
easat-2372	101	18	this	this	DET
easat-2372	101	19	layer	layer	NOUN
easat-2372	101	20	performs	perform	VERB
easat-2372	101	21	a	a	DET
easat-2372	101	22	convolution	convolution	NOUN
easat-2372	101	23	operation	operation	NOUN
easat-2372	101	24	between	between	ADP
easat-2372	101	25	the	the	DET
easat-2372	101	26	feature	feature	NOUN
easat-2372	101	27	and	and	CCONJ
easat-2372	101	28	the	the	DET
easat-2372	101	29	scanned	scan	VERB
easat-2372	101	30	image	image	NOUN
easat-2372	101	31	.	.	PUNCT
easat-2372	102	1	next	next	ADJ
easat-2372	102	2	layer	layer	NOUN
easat-2372	102	3	is	be	AUX
easat-2372	102	4	called	call	VERB
easat-2372	102	5	sub	sub	NOUN
easat-2372	102	6	sampling	sample	VERB
easat-2372	102	7	or	or	CCONJ
easat-2372	102	8	pooling	pool	VERB
easat-2372	102	9	layer	layer	NOUN
easat-2372	102	10	.	.	PUNCT
easat-2372	103	1	this	this	DET
easat-2372	103	2	layer	layer	NOUN
easat-2372	103	3	is	be	AUX
easat-2372	103	4	a	a	DET
easat-2372	103	5	mediator	mediator	NOUN
easat-2372	103	6	of	of	ADP
easat-2372	103	7	two	two	NUM
easat-2372	103	8	layers	layer	NOUN
easat-2372	103	9	to	to	PART
easat-2372	103	10	perform	perform	VERB
easat-2372	103	11	pooling	pool	VERB
easat-2372	103	12	features	feature	NOUN
easat-2372	103	13	from	from	ADP
easat-2372	103	14	one	one	NUM
easat-2372	103	15	layer	layer	NOUN
easat-2372	103	16	and	and	CCONJ
easat-2372	103	17	transfer	transfer	VERB
easat-2372	103	18	to	to	ADP
easat-2372	103	19	another	another	PRON
easat-2372	103	20	without	without	ADP
easat-2372	103	21	affecting	affect	VERB
easat-2372	103	22	their	their	PRON
easat-2372	103	23	properties	property	NOUN
easat-2372	103	24	and	and	CCONJ
easat-2372	103	25	reducing	reduce	VERB
easat-2372	103	26	the	the	DET
easat-2372	103	27	size	size	NOUN
easat-2372	103	28	of	of	ADP
easat-2372	103	29	input	input	NOUN
easat-2372	103	30	image	image	NOUN
easat-2372	103	31	[	[	X
easat-2372	103	32	23,24	23,24	NOUN
easat-2372	103	33	]	]	PUNCT
easat-2372	103	34	.	.	PUNCT
easat-2372	104	1	to	to	PART
easat-2372	104	2	replace	replace	VERB
easat-2372	104	3	all	all	DET
easat-2372	104	4	values	value	NOUN
easat-2372	104	5	which	which	PRON
easat-2372	104	6	are	be	AUX
easat-2372	104	7	negative	negative	ADJ
easat-2372	104	8	by	by	ADP
easat-2372	104	9	zeros	zero	NOUN
easat-2372	104	10	taken	take	VERB
easat-2372	104	11	in	in	ADP
easat-2372	104	12	input	input	NOUN
easat-2372	104	13	,	,	PUNCT
easat-2372	104	14	performed	perform	VERB
easat-2372	104	15	by	by	ADP
easat-2372	104	16	relu	relu	NOUN
easat-2372	104	17	which	which	PRON
easat-2372	104	18	is	be	AUX
easat-2372	104	19	rectified	rectify	VERB
easat-2372	104	20	linear	linear	ADJ
easat-2372	104	21	unit	unit	NOUN
easat-2372	104	22	function	function	NOUN
easat-2372	104	23	works	work	VERB
easat-2372	104	24	as	as	ADP
easat-2372	104	25	an	an	DET
easat-2372	104	26	activation	activation	NOUN
easat-2372	104	27	function	function	NOUN
easat-2372	104	28	.	.	PUNCT
easat-2372	105	1	its	its	PRON
easat-2372	105	2	function	function	NOUN
easat-2372	105	3	is	be	AUX
easat-2372	105	4	defined	define	VERB
easat-2372	105	5	as	as	SCONJ
easat-2372	105	6	:	:	PUNCT
easat-2372	105	7	relu(x)=max(0,x	relu(x)=max(0,x	PROPN
easat-2372	105	8	)	)	PUNCT
easat-2372	105	9	(	(	PUNCT
easat-2372	105	10	1	1	X
easat-2372	105	11	)	)	PUNCT
easat-2372	105	12	activation	activation	NOUN
easat-2372	105	13	layers	layer	NOUN
easat-2372	105	14	activation	activation	NOUN
easat-2372	105	15	layers	layer	NOUN
easat-2372	105	16	are	be	AUX
easat-2372	105	17	used	use	VERB
easat-2372	105	18	in	in	ADP
easat-2372	105	19	-	-	PUNCT
easat-2372	105	20	between	between	ADP
easat-2372	105	21	each	each	DET
easat-2372	105	22	nonlinear	nonlinear	ADJ
easat-2372	105	23	function	function	NOUN
easat-2372	105	24	layer	layer	NOUN
easat-2372	105	25	to	to	PART
easat-2372	105	26	activate	activate	VERB
easat-2372	105	27	the	the	DET
easat-2372	105	28	layers	layer	NOUN
easat-2372	105	29	such	such	ADJ
easat-2372	105	30	as	as	ADP
easat-2372	105	31	relu	relu	NOUN
easat-2372	105	32	and	and	CCONJ
easat-2372	105	33	convolutional	convolutional	ADJ
easat-2372	105	34	layer	layer	NOUN
easat-2372	105	35	.	.	PUNCT
easat-2372	106	1	dropout	dropout	NOUN
easat-2372	106	2	layer	layer	NOUN
easat-2372	106	3	regularizes	regularize	NOUN
easat-2372	106	4	and	and	CCONJ
easat-2372	106	5	prevents	prevent	VERB
easat-2372	106	6	overfitting	overfitte	VERB
easat-2372	106	7	through	through	ADP
easat-2372	106	8	increasing	increase	VERB
easat-2372	106	9	testing	testing	NOUN
easat-2372	106	10	accuracy	accuracy	NOUN
easat-2372	106	11	based	base	VERB
easat-2372	106	12	on	on	ADP
easat-2372	106	13	training	training	NOUN
easat-2372	106	14	accuracy	accuracy	NOUN
easat-2372	106	15	is	be	AUX
easat-2372	106	16	dropout	dropout	NOUN
easat-2372	106	17	layer	layer	NOUN
easat-2372	106	18	.	.	PUNCT
easat-2372	107	1	it	it	PRON
easat-2372	107	2	disconnects	disconnect	VERB
easat-2372	107	3	the	the	DET
easat-2372	107	4	inputs	input	NOUN
easat-2372	107	5	by	by	ADP
easat-2372	107	6	probability	probability	NOUN
easat-2372	107	7	p	p	NOUN
easat-2372	107	8	and	and	CCONJ
easat-2372	107	9	improves	improve	VERB
easat-2372	107	10	the	the	DET
easat-2372	107	11	further	further	ADJ
easat-2372	107	12	layers	layer	NOUN
easat-2372	107	13	.	.	PUNCT
easat-2372	108	1	the	the	DET
easat-2372	108	2	last	last	ADJ
easat-2372	108	3	layer	layer	NOUN
easat-2372	108	4	in	in	ADP
easat-2372	108	5	cnn	cnn	PROPN
easat-2372	108	6	architecture	architecture	NOUN
easat-2372	108	7	is	be	AUX
easat-2372	108	8	fully	fully	ADV
easat-2372	108	9	connected	connect	VERB
easat-2372	108	10	layer	layer	NOUN
easat-2372	108	11	.	.	PUNCT
easat-2372	109	1	softmax	softmax	NOUN
easat-2372	109	2	/	/	SYM
easat-2372	109	3	logistic	logistic	ADJ
easat-2372	109	4	layer	layer	NOUN
easat-2372	109	5	softmax	softmax	NOUN
easat-2372	109	6	or	or	CCONJ
easat-2372	109	7	logistic	logistic	ADJ
easat-2372	109	8	layer	layer	NOUN
easat-2372	109	9	is	be	AUX
easat-2372	109	10	used	use	VERB
easat-2372	109	11	as	as	ADP
easat-2372	109	12	binary	binary	ADJ
easat-2372	109	13	classification	classification	NOUN
easat-2372	109	14	and	and	CCONJ
easat-2372	109	15	multi	multi	ADJ
easat-2372	109	16	-	-	ADJ
easat-2372	109	17	classification	classification	NOUN
easat-2372	109	18	and	and	CCONJ
easat-2372	109	19	used	use	VERB
easat-2372	109	20	just	just	ADV
easat-2372	109	21	after	after	ADP
easat-2372	109	22	fully	fully	ADV
easat-2372	109	23	connected	connect	VERB
easat-2372	109	24	layer	layer	NOUN
easat-2372	109	25	.	.	PUNCT
easat-2372	110	1	batch	batch	NOUN
easat-2372	110	2	normalization	normalization	NOUN
easat-2372	110	3	batch	batch	NOUN
easat-2372	110	4	normalization	normalization	NOUN
easat-2372	110	5	is	be	AUX
easat-2372	110	6	the	the	DET
easat-2372	110	7	processes	process	NOUN
easat-2372	110	8	of	of	ADP
easat-2372	110	9	normalization	normalization	NOUN
easat-2372	110	10	within	within	ADP
easat-2372	110	11	the	the	DET
easat-2372	110	12	activation	activation	NOUN
easat-2372	110	13	layer	layer	NOUN
easat-2372	110	14	batch	batch	NOUN
easat-2372	110	15	including	include	VERB
easat-2372	110	16	subtraction	subtraction	NOUN
easat-2372	110	17	of	of	ADP
easat-2372	110	18	mean	mean	NOUN
easat-2372	110	19	and	and	CCONJ
easat-2372	110	20	deviation	deviation	NOUN
easat-2372	110	21	by	by	ADP
easat-2372	110	22	the	the	DET
easat-2372	110	23	standard	standard	ADJ
easat-2372	110	24	deviation	deviation	NOUN
easat-2372	110	25	.	.	PUNCT
easat-2372	111	1	to	to	PART
easat-2372	111	2	make	make	VERB
easat-2372	111	3	neural	neural	ADJ
easat-2372	111	4	network	network	NOUN
easat-2372	111	5	more	more	ADV
easat-2372	111	6	predictive	predictive	ADJ
easat-2372	111	7	it	it	PRON
easat-2372	111	8	is	be	AUX
easat-2372	111	9	required	require	VERB
easat-2372	111	10	to	to	PART
easat-2372	111	11	minimize	minimize	VERB
easat-2372	111	12	or	or	CCONJ
easat-2372	111	13	remove	remove	VERB
easat-2372	111	14	prediction	prediction	NOUN
easat-2372	111	15	error	error	NOUN
easat-2372	111	16	,	,	PUNCT
easat-2372	111	17	it	it	PRON
easat-2372	111	18	is	be	AUX
easat-2372	111	19	simply	simply	ADV
easat-2372	111	20	as	as	SCONJ
easat-2372	111	21	the	the	DET
easat-2372	111	22	errors	error	NOUN
easat-2372	111	23	are	be	AUX
easat-2372	111	24	loss	loss	NOUN
easat-2372	111	25	,	,	PUNCT
easat-2372	111	26	that	that	PRON
easat-2372	111	27	is	be	AUX
easat-2372	111	28	what	what	PRON
easat-2372	111	29	loss	loss	NOUN
easat-2372	111	30	function	function	NOUN
easat-2372	111	31	works	work	VERB
easat-2372	111	32	and	and	CCONJ
easat-2372	111	33	calculates	calculate	VERB
easat-2372	111	34	gradients	gradient	NOUN
easat-2372	111	35	.	.	PUNCT
easat-2372	112	1	loss	loss	NOUN
easat-2372	112	2	functions	function	NOUN
easat-2372	112	3	update	update	VERB
easat-2372	112	4	the	the	DET
easat-2372	112	5	weights	weight	NOUN
easat-2372	112	6	of	of	ADP
easat-2372	112	7	the	the	DET
easat-2372	112	8	network	network	NOUN
easat-2372	112	9	and	and	CCONJ
easat-2372	112	10	network	network	NOUN
easat-2372	112	11	trained	train	VERB
easat-2372	112	12	.	.	PUNCT
easat-2372	113	1	softmax	softmax	NOUN
easat-2372	113	2	or	or	CCONJ
easat-2372	113	3	logistic	logistic	ADJ
easat-2372	113	4	layer	layer	NOUN
easat-2372	113	5	used	use	VERB
easat-2372	113	6	separate	separate	ADJ
easat-2372	113	7	cross	cross	NOUN
easat-2372	113	8	entropy	entropy	NOUN
easat-2372	113	9	for	for	ADP
easat-2372	113	10	binary	binary	ADJ
easat-2372	113	11	and	and	CCONJ
easat-2372	113	12	multi	multi	ADJ
easat-2372	113	13	-	-	ADJ
easat-2372	113	14	class	class	ADJ
easat-2372	113	15	classification	classification	NOUN
easat-2372	113	16	as	as	ADP
easat-2372	113	17	:	:	PUNCT
easat-2372	113	18	binary	binary	PROPN
easat-2372	113	19	cross	cross	PROPN
easat-2372	113	20	entropy	entropy	PROPN
easat-2372	113	21	is	be	AUX
easat-2372	113	22	used	use	VERB
easat-2372	113	23	for	for	ADP
easat-2372	113	24	binary	binary	ADJ
easat-2372	113	25	classification	classification	NOUN
easat-2372	113	26	process	process	NOUN
easat-2372	113	27	by	by	ADP
easat-2372	113	28	passing	pass	VERB
easat-2372	113	29	output	output	NOUN
easat-2372	113	30	value	value	NOUN
easat-2372	113	31	through	through	ADP
easat-2372	113	32	sigmoid	sigmoid	NOUN
easat-2372	113	33	activation	activation	NOUN
easat-2372	113	34	function	function	NOUN
easat-2372	113	35	as	as	ADP
easat-2372	113	36	:	:	PUNCT
easat-2372	113	37	𝐿	𝐿	PROPN
easat-2372	113	38	=	=	PROPN
easat-2372	113	39	−(𝑦𝑖	−(𝑦𝑖	PROPN
easat-2372	113	40	log(𝑦	log(𝑦	PROPN
easat-2372	113	41	�	�	PROPN
easat-2372	113	42	̂	̂	NOUN
easat-2372	113	43	�	�	PROPN
easat-2372	113	44	)	)	PUNCT
easat-2372	114	1	+	+	CCONJ
easat-2372	114	2	(	(	PUNCT
easat-2372	114	3	1	1	NUM
easat-2372	114	4	−	−	PROPN
easat-2372	114	5	𝑦𝑖)𝑙𝑜𝑔(1	𝑦𝑖)𝑙𝑜𝑔(1	PROPN
easat-2372	114	6	−	−	PROPN
easat-2372	114	7	𝑦	𝑦	SYM
easat-2372	114	8	�	�	PROPN
easat-2372	114	9	̂	̂	SYM
easat-2372	114	10	�	�	NOUN
easat-2372	114	11	)	)	PUNCT
easat-2372	114	12	(	(	PUNCT
easat-2372	114	13	2	2	X
easat-2372	114	14	)	)	PUNCT
easat-2372	114	15	categorical	categorical	ADJ
easat-2372	114	16	cross	cross	NOUN
easat-2372	114	17	entropy	entropy	NOUN
easat-2372	114	18	is	be	AUX
easat-2372	114	19	used	use	VERB
easat-2372	114	20	for	for	ADP
easat-2372	114	21	a	a	DET
easat-2372	114	22	multiclass	multiclass	ADJ
easat-2372	114	23	classification	classification	NOUN
easat-2372	114	24	process	process	NOUN
easat-2372	114	25	by	by	ADP
easat-2372	114	26	passing	pass	VERB
easat-2372	114	27	output	output	NOUN
easat-2372	114	28	value	value	NOUN
easat-2372	114	29	through	through	ADP
easat-2372	114	30	softmax	softmax	NOUN
easat-2372	114	31	activation	activation	NOUN
easat-2372	114	32	as	as	ADP
easat-2372	114	33	:	:	PUNCT
easat-2372	114	34	𝐿	𝐿	PROPN
easat-2372	114	35	=	=	SYM
easat-2372	114	36	∑	∑	PROPN
easat-2372	114	37	𝑦𝑗	𝑦𝑗	PROPN
easat-2372	114	38	log(𝑦	log(𝑦	PROPN
easat-2372	114	39	�	�	PROPN
easat-2372	114	40	̂	̂	NOUN
easat-2372	114	41	�	�	PROPN
easat-2372	114	42	)	)	PUNCT
easat-2372	114	43	𝑀	𝑀	PROPN
easat-2372	114	44	𝑗=1	𝑗=1	PROPN
easat-2372	114	45	(	(	PUNCT
easat-2372	114	46	3	3	X
easat-2372	114	47	)	)	PUNCT
easat-2372	114	48	cnn	cnn	NOUN
easat-2372	114	49	optimizer	optimizer	NOUN
easat-2372	114	50	calculating	calculate	VERB
easat-2372	114	51	the	the	DET
easat-2372	114	52	gradients	gradient	NOUN
easat-2372	114	53	for	for	ADP
easat-2372	114	54	each	each	DET
easat-2372	114	55	training	training	NOUN
easat-2372	114	56	examples	example	NOUN
easat-2372	114	57	is	be	AUX
easat-2372	114	58	not	not	PART
easat-2372	114	59	practical	practical	ADJ
easat-2372	114	60	,	,	PUNCT
easat-2372	114	61	as	as	SCONJ
easat-2372	114	62	it	it	PRON
easat-2372	114	63	will	will	AUX
easat-2372	114	64	lag	lag	VERB
easat-2372	114	65	in	in	ADP
easat-2372	114	66	prediction	prediction	NOUN
easat-2372	114	67	accuracy	accuracy	NOUN
easat-2372	114	68	.	.	PUNCT
easat-2372	115	1	to	to	PART
easat-2372	115	2	optimize	optimize	VERB
easat-2372	115	3	the	the	DET
easat-2372	115	4	process	process	NOUN
easat-2372	115	5	various	various	ADJ
easat-2372	115	6	methods	method	NOUN
easat-2372	115	7	are	be	AUX
easat-2372	115	8	used	use	VERB
easat-2372	115	9	,	,	PUNCT
easat-2372	115	10	from	from	ADP
easat-2372	115	11	that	that	PRON
easat-2372	115	12	most	most	ADV
easat-2372	115	13	used	use	VERB
easat-2372	115	14	are	be	AUX
easat-2372	115	15	:	:	PUNCT
easat-2372	115	16	stochastic	stochastic	ADJ
easat-2372	115	17	gradient	gradient	ADJ
easat-2372	115	18	descent	descent	NOUN
easat-2372	115	19	:	:	PUNCT
easat-2372	115	20	using	use	VERB
easat-2372	115	21	batches	batch	NOUN
easat-2372	115	22	at	at	ADP
easat-2372	115	23	a	a	DET
easat-2372	115	24	time	time	NOUN
easat-2372	115	25	or	or	CCONJ
easat-2372	115	26	randomly	randomly	ADV
easat-2372	115	27	selecting	select	VERB
easat-2372	115	28	examples	example	NOUN
easat-2372	115	29	on	on	ADP
easat-2372	115	30	each	each	DET
easat-2372	115	31	pass	pass	NOUN
easat-2372	115	32	.	.	PUNCT
easat-2372	116	1	rmsprop	rmsprop	NOUN
easat-2372	116	2	:	:	PUNCT
easat-2372	116	3	gradients	gradient	NOUN
easat-2372	116	4	of	of	ADP
easat-2372	116	5	all	all	DET
easat-2372	116	6	examples	example	NOUN
easat-2372	116	7	are	be	AUX
easat-2372	116	8	collected	collect	VERB
easat-2372	116	9	in	in	ADP
easat-2372	116	10	a	a	DET
easat-2372	116	11	fixed	fix	VERB
easat-2372	116	12	window	window	NOUN
easat-2372	116	13	and	and	CCONJ
easat-2372	116	14	avoid	avoid	VERB
easat-2372	116	15	collecting	collect	VERB
easat-2372	116	16	all	all	PRON
easat-2372	116	17	for	for	ADP
easat-2372	116	18	moment	moment	NOUN
easat-2372	116	19	.	.	PUNCT
easat-2372	117	1	adam	adam	PROPN
easat-2372	117	2	:	:	PUNCT
easat-2372	117	3	it	it	PRON
easat-2372	117	4	calculates	calculate	VERB
easat-2372	117	5	the	the	DET
easat-2372	117	6	current	current	ADJ
easat-2372	117	7	gradients	gradient	NOUN
easat-2372	117	8	based	base	VERB
easat-2372	117	9	on	on	ADP
easat-2372	117	10	past	past	ADJ
easat-2372	117	11	gradients	gradient	NOUN
easat-2372	117	12	by	by	ADP
easat-2372	117	13	using	use	VERB
easat-2372	117	14	momentum	momentum	NOUN
easat-2372	117	15	by	by	ADP
easat-2372	117	16	adding	add	VERB
easat-2372	117	17	fractions	fraction	NOUN
easat-2372	117	18	from	from	ADP
easat-2372	117	19	previous	previous	ADJ
easat-2372	117	20	gradients	gradient	NOUN
easat-2372	117	21	.	.	PUNCT
easat-2372	118	1	3.3	3.3	NUM
easat-2372	118	2	.	.	PUNCT
easat-2372	118	3	experiment	experiment	NOUN
easat-2372	118	4	&	&	CCONJ
easat-2372	118	5	analysis	analysis	NOUN
easat-2372	118	6	2019	2019	NUM
easat-2372	118	7	edelweiss	edelweiss	PROPN
easat-2372	118	8	applied	apply	VERB
easat-2372	118	9	science	science	NOUN
easat-2372	118	10	and	and	CCONJ
easat-2372	118	11	technology	technology	NOUN
easat-2372	118	12	issn	issn	PROPN
easat-2372	118	13	:	:	PUNCT
easat-2372	118	14	2576	2576	NUM
easat-2372	118	15	-	-	SYM
easat-2372	118	16	8484	8484	NUM
easat-2372	118	17	vol	vol	NOUN
easat-2372	118	18	.	.	PROPN
easat-2372	119	1	8	8	NUM
easat-2372	119	2	,	,	PUNCT
easat-2372	119	3	no	no	INTJ
easat-2372	119	4	.	.	NOUN
easat-2372	120	1	6	6	NUM
easat-2372	120	2	:	:	SYM
easat-2372	120	3	2015	2015	NUM
easat-2372	120	4	-	-	SYM
easat-2372	120	5	2024	2024	NUM
easat-2372	120	6	,	,	PUNCT
easat-2372	120	7	2024	2024	NUM
easat-2372	120	8	doi	doi	NOUN
easat-2372	120	9	:	:	PUNCT
easat-2372	120	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	120	11	©	©	PROPN
easat-2372	120	12	2024	2024	NUM
easat-2372	120	13	by	by	ADP
easat-2372	120	14	the	the	DET
easat-2372	120	15	authors	author	NOUN
easat-2372	120	16	;	;	PUNCT
easat-2372	120	17	licensee	licensee	PROPN
easat-2372	120	18	learning	learn	VERB
easat-2372	120	19	gate	gate	NOUN
easat-2372	120	20	in	in	ADP
easat-2372	120	21	the	the	DET
easat-2372	120	22	proposed	propose	VERB
easat-2372	120	23	model	model	NOUN
easat-2372	120	24	for	for	ADP
easat-2372	120	25	rice	rice	NOUN
easat-2372	120	26	disease	disease	NOUN
easat-2372	120	27	identification	identification	NOUN
easat-2372	120	28	,	,	PUNCT
easat-2372	120	29	the	the	DET
easat-2372	120	30	training	training	NOUN
easat-2372	120	31	and	and	CCONJ
easat-2372	120	32	test	test	NOUN
easat-2372	120	33	datasets	dataset	NOUN
easat-2372	120	34	were	be	AUX
easat-2372	120	35	first	first	ADV
easat-2372	120	36	augmented	augment	VERB
easat-2372	120	37	using	use	VERB
easat-2372	120	38	the	the	DET
easat-2372	120	39	keras	keras	PROPN
easat-2372	120	40	image	image	PROPN
easat-2372	120	41	data	data	PROPN
easat-2372	120	42	generator	generator	PROPN
easat-2372	120	43	.	.	PUNCT
easat-2372	121	1	the	the	DET
easat-2372	121	2	rice	rice	NOUN
easat-2372	121	3	image	image	NOUN
easat-2372	121	4	dataset	dataset	NOUN
easat-2372	121	5	contains	contain	VERB
easat-2372	121	6	images	image	NOUN
easat-2372	121	7	of	of	ADP
easat-2372	121	8	four	four	NUM
easat-2372	121	9	disease	disease	NOUN
easat-2372	121	10	types	type	NOUN
easat-2372	121	11	.	.	PUNCT
easat-2372	122	1	to	to	PART
easat-2372	122	2	further	far	ADV
easat-2372	122	3	enhance	enhance	VERB
easat-2372	122	4	the	the	DET
easat-2372	122	5	dataset	dataset	NOUN
easat-2372	122	6	,	,	PUNCT
easat-2372	122	7	a	a	DET
easat-2372	122	8	deep	deep	ADJ
easat-2372	122	9	convolutional	convolutional	ADJ
easat-2372	122	10	generative	generative	ADJ
easat-2372	122	11	adversarial	adversarial	ADJ
easat-2372	122	12	network	network	NOUN
easat-2372	122	13	(	(	PUNCT
easat-2372	122	14	dcgan	dcgan	NOUN
easat-2372	122	15	)	)	PUNCT
easat-2372	122	16	was	be	AUX
easat-2372	122	17	employed	employ	VERB
easat-2372	122	18	to	to	PART
easat-2372	122	19	generate	generate	VERB
easat-2372	122	20	synthetic	synthetic	ADJ
easat-2372	122	21	images	image	NOUN
easat-2372	122	22	for	for	ADP
easat-2372	122	23	two	two	NUM
easat-2372	122	24	specific	specific	ADJ
easat-2372	122	25	disease	disease	NOUN
easat-2372	122	26	types	type	NOUN
easat-2372	122	27	:	:	PUNCT
easat-2372	122	28	blast	blast	NOUN
easat-2372	122	29	and	and	CCONJ
easat-2372	122	30	tungro	tungro	NOUN
easat-2372	122	31	.	.	PUNCT
easat-2372	123	1	initially	initially	ADV
easat-2372	123	2	,	,	PUNCT
easat-2372	123	3	the	the	DET
easat-2372	123	4	dataset	dataset	NOUN
easat-2372	123	5	comprised	comprise	VERB
easat-2372	123	6	5,932	5,932	NUM
easat-2372	123	7	images	image	NOUN
easat-2372	123	8	,	,	PUNCT
easat-2372	123	9	but	but	CCONJ
easat-2372	123	10	the	the	DET
easat-2372	123	11	application	application	NOUN
easat-2372	123	12	of	of	ADP
easat-2372	123	13	dcgan	dcgan	NOUN
easat-2372	123	14	,	,	PUNCT
easat-2372	123	15	trained	train	VERB
easat-2372	123	16	over	over	ADP
easat-2372	123	17	1,000	1,000	NUM
easat-2372	123	18	epochs	epoch	NOUN
easat-2372	123	19	,	,	PUNCT
easat-2372	123	20	generated	generate	VERB
easat-2372	123	21	an	an	DET
easat-2372	123	22	additional	additional	ADJ
easat-2372	123	23	2,000	2,000	NUM
easat-2372	123	24	synthetic	synthetic	ADJ
easat-2372	123	25	images	image	NOUN
easat-2372	123	26	(	(	PUNCT
easat-2372	123	27	1,000	1,000	NUM
easat-2372	123	28	images	image	NOUN
easat-2372	123	29	for	for	ADP
easat-2372	123	30	each	each	DET
easat-2372	123	31	disease	disease	NOUN
easat-2372	123	32	)	)	PUNCT
easat-2372	123	33	.	.	PUNCT
easat-2372	124	1	figure	figure	NOUN
easat-2372	124	2	2	2	NUM
easat-2372	124	3	.	.	PUNCT
easat-2372	124	4	dcgan	dcgan	NOUN
easat-2372	124	5	architecture	architecture	NOUN
easat-2372	124	6	.	.	PUNCT
easat-2372	125	1	for	for	ADP
easat-2372	125	2	the	the	DET
easat-2372	125	3	dcgan	dcgan	NOUN
easat-2372	125	4	training	training	NOUN
easat-2372	125	5	,	,	PUNCT
easat-2372	125	6	key	key	ADJ
easat-2372	125	7	parameters	parameter	NOUN
easat-2372	125	8	such	such	ADJ
easat-2372	125	9	as	as	ADP
easat-2372	125	10	d(g(j1	d(g(j1	NOUN
easat-2372	125	11	)	)	PUNCT
easat-2372	125	12	)	)	PUNCT
easat-2372	125	13	,	,	PUNCT
easat-2372	125	14	d(g(j2	d(g(j2	NOUN
easat-2372	125	15	)	)	PUNCT
easat-2372	125	16	)	)	PUNCT
easat-2372	125	17	,	,	PUNCT
easat-2372	125	18	d(i	d(i	PROPN
easat-2372	125	19	)	)	PUNCT
easat-2372	125	20	,	,	PUNCT
easat-2372	125	21	loss	loss	NOUN
easat-2372	125	22	d	d	NOUN
easat-2372	125	23	,	,	PUNCT
easat-2372	125	24	and	and	CCONJ
easat-2372	125	25	loss	loss	NOUN
easat-2372	125	26	g	g	NOUN
easat-2372	125	27	were	be	AUX
easat-2372	125	28	monitored	monitor	VERB
easat-2372	125	29	and	and	CCONJ
easat-2372	125	30	plotted	plot	VERB
easat-2372	125	31	against	against	ADP
easat-2372	125	32	the	the	DET
easat-2372	125	33	number	number	NOUN
easat-2372	125	34	of	of	ADP
easat-2372	125	35	epochs	epoch	NOUN
easat-2372	125	36	to	to	PART
easat-2372	125	37	analyze	analyze	VERB
easat-2372	125	38	the	the	DET
easat-2372	125	39	training	training	NOUN
easat-2372	125	40	process	process	NOUN
easat-2372	125	41	for	for	ADP
easat-2372	125	42	both	both	CCONJ
easat-2372	125	43	the	the	DET
easat-2372	125	44	generator	generator	NOUN
easat-2372	125	45	and	and	CCONJ
easat-2372	125	46	discriminator	discriminator	NOUN
easat-2372	125	47	networks	network	NOUN
easat-2372	125	48	.	.	PUNCT
easat-2372	126	1	figure	figure	NOUN
easat-2372	126	2	3	3	NUM
easat-2372	126	3	illustrates	illustrate	VERB
easat-2372	126	4	the	the	DET
easat-2372	126	5	performance	performance	NOUN
easat-2372	126	6	comparison	comparison	NOUN
easat-2372	126	7	between	between	ADP
easat-2372	126	8	the	the	DET
easat-2372	126	9	real	real	ADJ
easat-2372	126	10	images	image	NOUN
easat-2372	126	11	of	of	ADP
easat-2372	126	12	blast	blast	NOUN
easat-2372	126	13	and	and	CCONJ
easat-2372	126	14	tungro	tungro	VERB
easat-2372	126	15	from	from	ADP
easat-2372	126	16	the	the	DET
easat-2372	126	17	original	original	ADJ
easat-2372	126	18	dataset	dataset	NOUN
easat-2372	126	19	and	and	CCONJ
easat-2372	126	20	the	the	DET
easat-2372	126	21	synthetic	synthetic	ADJ
easat-2372	126	22	images	image	NOUN
easat-2372	126	23	generated	generate	VERB
easat-2372	126	24	by	by	ADP
easat-2372	126	25	the	the	DET
easat-2372	126	26	dcgan	dcgan	NOUN
easat-2372	126	27	.	.	PUNCT
easat-2372	127	1	the	the	DET
easat-2372	127	2	results	result	NOUN
easat-2372	127	3	indicate	indicate	VERB
easat-2372	127	4	that	that	SCONJ
easat-2372	127	5	as	as	ADP
easat-2372	127	6	the	the	DET
easat-2372	127	7	number	number	NOUN
easat-2372	127	8	of	of	ADP
easat-2372	127	9	epochs	epoch	NOUN
easat-2372	127	10	increases	increase	NOUN
easat-2372	127	11	,	,	PUNCT
easat-2372	127	12	both	both	DET
easat-2372	127	13	networks	network	NOUN
easat-2372	127	14	achieve	achieve	VERB
easat-2372	127	15	greater	great	ADJ
easat-2372	127	16	stability	stability	NOUN
easat-2372	127	17	.	.	PUNCT
easat-2372	128	1	for	for	ADP
easat-2372	128	2	disease	disease	NOUN
easat-2372	128	3	classification	classification	NOUN
easat-2372	128	4	,	,	PUNCT
easat-2372	128	5	a	a	DET
easat-2372	128	6	novel	novel	ADJ
easat-2372	128	7	convolutional	convolutional	ADJ
easat-2372	128	8	neural	neural	ADJ
easat-2372	128	9	network	network	NOUN
easat-2372	128	10	(	(	PUNCT
easat-2372	128	11	cnn	cnn	PROPN
easat-2372	128	12	)	)	PUNCT
easat-2372	128	13	architecture	architecture	NOUN
easat-2372	128	14	was	be	AUX
easat-2372	128	15	utilized	utilize	VERB
easat-2372	128	16	.	.	PUNCT
easat-2372	129	1	the	the	DET
easat-2372	129	2	architecture	architecture	NOUN
easat-2372	129	3	comprises	comprise	VERB
easat-2372	129	4	five	five	NUM
easat-2372	129	5	convolutional	convolutional	ADJ
easat-2372	129	6	layers	layer	NOUN
easat-2372	129	7	,	,	PUNCT
easat-2372	129	8	with	with	ADP
easat-2372	129	9	batch	batch	NOUN
easat-2372	129	10	normalization	normalization	NOUN
easat-2372	129	11	added	add	VERB
easat-2372	129	12	to	to	PART
easat-2372	129	13	mitigate	mitigate	VERB
easat-2372	129	14	overfitting	overfitting	NOUN
easat-2372	129	15	,	,	PUNCT
easat-2372	129	16	and	and	CCONJ
easat-2372	129	17	a	a	DET
easat-2372	129	18	dropout	dropout	NOUN
easat-2372	129	19	rate	rate	NOUN
easat-2372	129	20	of	of	ADP
easat-2372	129	21	0.25	0.25	NUM
easat-2372	129	22	to	to	PART
easat-2372	129	23	enhance	enhance	VERB
easat-2372	129	24	test	test	NOUN
easat-2372	129	25	accuracy	accuracy	NOUN
easat-2372	129	26	.	.	PUNCT
easat-2372	130	1	the	the	DET
easat-2372	130	2	output	output	NOUN
easat-2372	130	3	layer	layer	NOUN
easat-2372	130	4	employs	employ	VERB
easat-2372	130	5	the	the	DET
easat-2372	130	6	softmax	softmax	NOUN
easat-2372	130	7	activation	activation	NOUN
easat-2372	130	8	function	function	NOUN
easat-2372	130	9	.	.	PUNCT
easat-2372	131	1	the	the	DET
easat-2372	131	2	model	model	NOUN
easat-2372	131	3	was	be	AUX
easat-2372	131	4	fine	fine	ADV
easat-2372	131	5	-	-	PUNCT
easat-2372	131	6	tuned	tune	VERB
easat-2372	131	7	with	with	ADP
easat-2372	131	8	hyperparameters	hyperparameter	NOUN
easat-2372	131	9	such	such	ADJ
easat-2372	131	10	as	as	ADP
easat-2372	131	11	25	25	NUM
easat-2372	131	12	epochs	epoch	NOUN
easat-2372	131	13	and	and	CCONJ
easat-2372	131	14	a	a	DET
easat-2372	131	15	learning	learning	NOUN
easat-2372	131	16	rate	rate	NOUN
easat-2372	131	17	of	of	ADP
easat-2372	131	18	0.0001	0.0001	NUM
easat-2372	131	19	.	.	PUNCT
easat-2372	132	1	additionally	additionally	ADV
easat-2372	132	2	,	,	PUNCT
easat-2372	132	3	the	the	DET
easat-2372	132	4	model	model	NOUN
easat-2372	132	5	's	's	PART
easat-2372	132	6	performance	performance	NOUN
easat-2372	132	7	was	be	AUX
easat-2372	132	8	evaluated	evaluate	VERB
easat-2372	132	9	using	use	VERB
easat-2372	132	10	three	three	NUM
easat-2372	132	11	cnn	cnn	PROPN
easat-2372	132	12	optimizers	optimizer	NOUN
easat-2372	132	13	:	:	PUNCT
easat-2372	132	14	adam	adam	PROPN
easat-2372	132	15	,	,	PUNCT
easat-2372	132	16	sgd	sgd	PROPN
easat-2372	132	17	,	,	PUNCT
easat-2372	132	18	and	and	CCONJ
easat-2372	132	19	rmsprop	rmsprop	NOUN
easat-2372	132	20	.	.	PUNCT
easat-2372	133	1	accuracy	accuracy	NOUN
easat-2372	133	2	and	and	CCONJ
easat-2372	133	3	top-5	top-5	PUNCT
easat-2372	133	4	accuracy	accuracy	NOUN
easat-2372	133	5	were	be	AUX
easat-2372	133	6	used	use	VERB
easat-2372	133	7	as	as	ADP
easat-2372	133	8	evaluation	evaluation	NOUN
easat-2372	133	9	metrics	metric	NOUN
easat-2372	133	10	,	,	PUNCT
easat-2372	133	11	with	with	ADP
easat-2372	133	12	categorical	categorical	PROPN
easat-2372	133	13	cross	cross	NOUN
easat-2372	133	14	entropy	entropy	NOUN
easat-2372	133	15	as	as	SCONJ
easat-2372	133	16	the	the	DET
easat-2372	133	17	loss	loss	NOUN
easat-2372	133	18	function	function	NOUN
easat-2372	133	19	to	to	PART
easat-2372	133	20	assess	assess	VERB
easat-2372	133	21	the	the	DET
easat-2372	133	22	difference	difference	NOUN
easat-2372	133	23	between	between	ADP
easat-2372	133	24	actual	actual	ADJ
easat-2372	133	25	and	and	CCONJ
easat-2372	133	26	predicted	predict	VERB
easat-2372	133	27	classes	class	NOUN
easat-2372	133	28	.	.	PUNCT
easat-2372	134	1	the	the	DET
easat-2372	134	2	following	follow	VERB
easat-2372	134	3	steps	step	NOUN
easat-2372	134	4	were	be	AUX
easat-2372	134	5	carried	carry	VERB
easat-2372	134	6	out	out	ADP
easat-2372	134	7	:	:	PUNCT
easat-2372	135	1	1	1	X
easat-2372	135	2	.	.	PUNCT
easat-2372	136	1	the	the	DET
easat-2372	136	2	original	original	ADJ
easat-2372	136	3	rice	rice	NOUN
easat-2372	136	4	image	image	NOUN
easat-2372	136	5	dataset	dataset	NOUN
easat-2372	136	6	was	be	AUX
easat-2372	136	7	augmented	augment	VERB
easat-2372	136	8	and	and	CCONJ
easat-2372	136	9	used	use	VERB
easat-2372	136	10	to	to	PART
easat-2372	136	11	train	train	VERB
easat-2372	136	12	the	the	DET
easat-2372	136	13	cnn	cnn	PROPN
easat-2372	136	14	model	model	NOUN
easat-2372	136	15	,	,	PUNCT
easat-2372	136	16	and	and	CCONJ
easat-2372	136	17	the	the	DET
easat-2372	136	18	model	model	NOUN
easat-2372	136	19	's	's	PART
easat-2372	136	20	accuracy	accuracy	NOUN
easat-2372	136	21	was	be	AUX
easat-2372	136	22	evaluated	evaluate	VERB
easat-2372	136	23	.	.	PUNCT
easat-2372	137	1	2	2	X
easat-2372	137	2	.	.	X
easat-2372	137	3	a	a	DET
easat-2372	137	4	new	new	ADJ
easat-2372	137	5	dataset	dataset	NOUN
easat-2372	137	6	consisting	consist	VERB
easat-2372	137	7	of	of	ADP
easat-2372	137	8	synthetic	synthetic	ADJ
easat-2372	137	9	images	image	NOUN
easat-2372	137	10	of	of	ADP
easat-2372	137	11	blast	blast	NOUN
easat-2372	137	12	and	and	CCONJ
easat-2372	137	13	tungro	tungro	NOUN
easat-2372	137	14	,	,	PUNCT
easat-2372	137	15	generated	generate	VERB
easat-2372	137	16	by	by	ADP
easat-2372	137	17	dcgan	dcgan	NOUN
easat-2372	137	18	,	,	PUNCT
easat-2372	137	19	was	be	AUX
easat-2372	137	20	used	use	VERB
easat-2372	137	21	for	for	ADP
easat-2372	137	22	data	datum	NOUN
easat-2372	137	23	augmentation	augmentation	NOUN
easat-2372	137	24	.	.	PUNCT
easat-2372	138	1	this	this	DET
easat-2372	138	2	augmented	augment	VERB
easat-2372	138	3	dataset	dataset	NOUN
easat-2372	138	4	was	be	AUX
easat-2372	138	5	then	then	ADV
easat-2372	138	6	employed	employ	VERB
easat-2372	138	7	for	for	ADP
easat-2372	138	8	further	further	ADJ
easat-2372	138	9	model	model	NOUN
easat-2372	138	10	training	training	NOUN
easat-2372	138	11	.	.	PUNCT
easat-2372	139	1	the	the	DET
easat-2372	139	2	performance	performance	NOUN
easat-2372	139	3	metrics	metric	NOUN
easat-2372	139	4	of	of	ADP
easat-2372	139	5	the	the	DET
easat-2372	139	6	proposed	propose	VERB
easat-2372	139	7	cnn	cnn	PROPN
easat-2372	139	8	model	model	NOUN
easat-2372	139	9	and	and	CCONJ
easat-2372	139	10	comparative	comparative	ADJ
easat-2372	139	11	analyses	analysis	NOUN
easat-2372	139	12	are	be	AUX
easat-2372	139	13	detailed	detail	VERB
easat-2372	139	14	in	in	ADP
easat-2372	139	15	the	the	DET
easat-2372	139	16	results	result	NOUN
easat-2372	139	17	section	section	NOUN
easat-2372	139	18	.	.	PUNCT
easat-2372	140	1	the	the	DET
easat-2372	140	2	keras	keras	PROPN
easat-2372	140	3	deep	deep	PROPN
easat-2372	140	4	learning	learning	NOUN
easat-2372	140	5	library	library	NOUN
easat-2372	140	6	was	be	AUX
easat-2372	140	7	used	use	VERB
easat-2372	140	8	for	for	ADP
easat-2372	140	9	model	model	NOUN
easat-2372	140	10	training	training	NOUN
easat-2372	140	11	,	,	PUNCT
easat-2372	140	12	and	and	CCONJ
easat-2372	140	13	both	both	CCONJ
easat-2372	140	14	the	the	DET
easat-2372	140	15	dcgan	dcgan	NOUN
easat-2372	140	16	and	and	CCONJ
easat-2372	140	17	cnn	cnn	PROPN
easat-2372	140	18	models	model	NOUN
easat-2372	140	19	were	be	AUX
easat-2372	140	20	trained	train	VERB
easat-2372	140	21	on	on	ADP
easat-2372	140	22	google	google	PROPN
easat-2372	140	23	colab	colab	PROPN
easat-2372	140	24	.	.	PUNCT
easat-2372	141	1	2020	2020	NUM
easat-2372	141	2	edelweiss	edelweiss	PROPN
easat-2372	141	3	applied	apply	VERB
easat-2372	141	4	science	science	NOUN
easat-2372	141	5	and	and	CCONJ
easat-2372	141	6	technology	technology	NOUN
easat-2372	141	7	issn	issn	PROPN
easat-2372	141	8	:	:	PUNCT
easat-2372	141	9	2576	2576	NUM
easat-2372	141	10	-	-	SYM
easat-2372	141	11	8484	8484	NUM
easat-2372	141	12	vol	vol	NOUN
easat-2372	141	13	.	.	PROPN
easat-2372	141	14	8	8	NUM
easat-2372	141	15	,	,	PUNCT
easat-2372	141	16	no	no	INTJ
easat-2372	141	17	.	.	NOUN
easat-2372	142	1	6	6	NUM
easat-2372	142	2	:	:	SYM
easat-2372	142	3	2015	2015	NUM
easat-2372	142	4	-	-	SYM
easat-2372	142	5	2024	2024	NUM
easat-2372	142	6	,	,	PUNCT
easat-2372	142	7	2024	2024	NUM
easat-2372	142	8	doi	doi	NOUN
easat-2372	142	9	:	:	PUNCT
easat-2372	142	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	142	11	©	©	PROPN
easat-2372	142	12	2024	2024	NUM
easat-2372	142	13	by	by	ADP
easat-2372	142	14	the	the	DET
easat-2372	142	15	authors	author	NOUN
easat-2372	142	16	;	;	PUNCT
easat-2372	142	17	licensee	licensee	PROPN
easat-2372	142	18	learning	learning	NOUN
easat-2372	142	19	gate	gate	NOUN
easat-2372	142	20	4	4	PROPN
easat-2372	142	21	.	.	PUNCT
easat-2372	142	22	results	result	NOUN
easat-2372	142	23	&	&	CCONJ
easat-2372	142	24	discussions	discussion	NOUN
easat-2372	142	25	the	the	DET
easat-2372	142	26	proposed	propose	VERB
easat-2372	142	27	dcgan	dcgan	NOUN
easat-2372	142	28	model	model	NOUN
easat-2372	142	29	for	for	ADP
easat-2372	142	30	generating	generate	VERB
easat-2372	142	31	synthetic	synthetic	ADJ
easat-2372	142	32	data	datum	NOUN
easat-2372	142	33	in	in	ADP
easat-2372	142	34	the	the	DET
easat-2372	142	35	form	form	NOUN
easat-2372	142	36	of	of	ADP
easat-2372	142	37	blast	blast	NOUN
easat-2372	142	38	and	and	CCONJ
easat-2372	142	39	tungro	tungro	NOUN
easat-2372	142	40	disease	disease	NOUN
easat-2372	142	41	images	image	NOUN
easat-2372	142	42	has	have	AUX
easat-2372	142	43	been	be	AUX
easat-2372	142	44	evaluated	evaluate	VERB
easat-2372	142	45	to	to	PART
easat-2372	142	46	improve	improve	VERB
easat-2372	142	47	cnn	cnn	PROPN
easat-2372	142	48	classification	classification	NOUN
easat-2372	142	49	performance	performance	NOUN
easat-2372	142	50	.	.	PUNCT
easat-2372	143	1	the	the	DET
easat-2372	143	2	generated	generate	VERB
easat-2372	143	3	images	image	NOUN
easat-2372	143	4	are	be	AUX
easat-2372	143	5	mixed	mix	VERB
easat-2372	143	6	with	with	ADP
easat-2372	143	7	the	the	DET
easat-2372	143	8	original	original	ADJ
easat-2372	143	9	dataset	dataset	NOUN
easat-2372	143	10	to	to	PART
easat-2372	143	11	increase	increase	VERB
easat-2372	143	12	the	the	DET
easat-2372	143	13	diversity	diversity	NOUN
easat-2372	143	14	of	of	ADP
easat-2372	143	15	the	the	DET
easat-2372	143	16	training	training	NOUN
easat-2372	143	17	data	datum	NOUN
easat-2372	143	18	.	.	PUNCT
easat-2372	144	1	by	by	ADP
easat-2372	144	2	utilizing	utilize	VERB
easat-2372	144	3	dcgan	dcgan	NOUN
easat-2372	144	4	-	-	PUNCT
easat-2372	144	5	generated	generate	VERB
easat-2372	144	6	synthetic	synthetic	ADJ
easat-2372	144	7	data	datum	NOUN
easat-2372	144	8	,	,	PUNCT
easat-2372	144	9	the	the	DET
easat-2372	144	10	cnn	cnn	PROPN
easat-2372	144	11	model	model	NOUN
easat-2372	144	12	's	's	PART
easat-2372	144	13	training	training	NOUN
easat-2372	144	14	process	process	NOUN
easat-2372	144	15	can	can	AUX
easat-2372	144	16	be	be	AUX
easat-2372	144	17	enriched	enrich	VERB
easat-2372	144	18	,	,	PUNCT
easat-2372	144	19	leading	lead	VERB
easat-2372	144	20	to	to	ADP
easat-2372	144	21	improved	improve	VERB
easat-2372	144	22	generalization	generalization	NOUN
easat-2372	144	23	,	,	PUNCT
easat-2372	144	24	particularly	particularly	ADV
easat-2372	144	25	for	for	ADP
easat-2372	144	26	real	real	ADJ
easat-2372	144	27	-	-	PUNCT
easat-2372	144	28	world	world	NOUN
easat-2372	144	29	test	test	NOUN
easat-2372	144	30	cases	case	NOUN
easat-2372	144	31	.	.	PUNCT
easat-2372	145	1	original	original	ADJ
easat-2372	145	2	image	image	NOUN
easat-2372	145	3	(	(	PUNCT
easat-2372	145	4	blast	blast	NOUN
easat-2372	145	5	&	&	CCONJ
easat-2372	145	6	tungro	tungro	PROPN
easat-2372	145	7	)	)	PUNCT
easat-2372	145	8	generated	generate	VERB
easat-2372	145	9	image	image	NOUN
easat-2372	145	10	(	(	PUNCT
easat-2372	145	11	blast	blast	NOUN
easat-2372	145	12	&	&	CCONJ
easat-2372	145	13	tungro	tungro	PROPN
easat-2372	145	14	)	)	PUNCT
easat-2372	145	15	figure	figure	NOUN
easat-2372	145	16	3	3	NUM
easat-2372	145	17	.	.	PUNCT
easat-2372	145	18	generated	generate	VERB
easat-2372	145	19	images	image	NOUN
easat-2372	145	20	of	of	ADP
easat-2372	145	21	blast	blast	NOUN
easat-2372	145	22	&	&	CCONJ
easat-2372	145	23	tungro	tungro	VERB
easat-2372	145	24	through	through	ADP
easat-2372	145	25	dcgan	dcgan	NOUN
easat-2372	145	26	.	.	PUNCT
easat-2372	146	1	the	the	DET
easat-2372	146	2	gan	gan	PROPN
easat-2372	146	3	network	network	NOUN
easat-2372	146	4	attempts	attempt	VERB
easat-2372	146	5	to	to	PART
easat-2372	146	6	optimize	optimize	VERB
easat-2372	146	7	the	the	DET
easat-2372	146	8	loss	loss	NOUN
easat-2372	146	9	function	function	NOUN
easat-2372	146	10	v(d	v(d	PROPN
easat-2372	146	11	,	,	PUNCT
easat-2372	146	12	g	g	NOUN
easat-2372	146	13	)	)	PUNCT
easat-2372	146	14	given	give	VERB
easat-2372	146	15	below[22	below[22	NOUN
easat-2372	146	16	]	]	X
easat-2372	146	17	(	(	PUNCT
easat-2372	146	18	6	6	X
easat-2372	146	19	)	)	PUNCT
easat-2372	146	20	the	the	DET
easat-2372	146	21	use	use	NOUN
easat-2372	146	22	of	of	ADP
easat-2372	146	23	generator	generator	NOUN
easat-2372	146	24	which	which	PRON
easat-2372	146	25	is	be	AUX
easat-2372	146	26	here	here	ADV
easat-2372	146	27	g(z	g(z	PROPN
easat-2372	146	28	)	)	PUNCT
easat-2372	146	29	is	be	AUX
easat-2372	146	30	used	use	VERB
easat-2372	146	31	to	to	PART
easat-2372	146	32	convert	convert	VERB
easat-2372	146	33	noise	noise	NOUN
easat-2372	146	34	z	z	NOUN
easat-2372	146	35	into	into	ADP
easat-2372	146	36	which	which	PRON
easat-2372	146	37	is	be	AUX
easat-2372	146	38	input	input	VERB
easat-2372	146	39	into	into	ADP
easat-2372	146	40	some	some	DET
easat-2372	146	41	kind	kind	NOUN
easat-2372	146	42	of	of	ADP
easat-2372	146	43	data	datum	NOUN
easat-2372	146	44	,	,	PUNCT
easat-2372	146	45	as	as	ADP
easat-2372	146	46	images	image	NOUN
easat-2372	146	47	.	.	PUNCT
easat-2372	147	1	the	the	DET
easat-2372	147	2	role	role	NOUN
easat-2372	147	3	of	of	ADP
easat-2372	147	4	discriminator	discriminator	NOUN
easat-2372	147	5	d(x	d(x	PROPN
easat-2372	147	6	)	)	PUNCT
easat-2372	147	7	is	be	AUX
easat-2372	147	8	to	to	PART
easat-2372	147	9	discriminate	discriminate	VERB
easat-2372	147	10	and	and	CCONJ
easat-2372	147	11	output	output	VERB
easat-2372	147	12	the	the	DET
easat-2372	147	13	probability	probability	NOUN
easat-2372	147	14	of	of	ADP
easat-2372	147	15	to	to	PART
easat-2372	147	16	identify	identify	VERB
easat-2372	147	17	input	input	NOUN
easat-2372	147	18	coming	come	VERB
easat-2372	147	19	is	be	AUX
easat-2372	147	20	from	from	ADP
easat-2372	147	21	real	real	ADJ
easat-2372	147	22	images	image	NOUN
easat-2372	147	23	or	or	CCONJ
easat-2372	147	24	not	not	PART
easat-2372	147	25	.	.	PUNCT
easat-2372	148	1	this	this	PRON
easat-2372	148	2	is	be	AUX
easat-2372	148	3	achieved	achieve	VERB
easat-2372	148	4	by	by	ADP
easat-2372	148	5	using	use	VERB
easat-2372	148	6	log	log	NOUN
easat-2372	148	7	-	-	PUNCT
easat-2372	148	8	likelihood	likelihood	NOUN
easat-2372	148	9	function	function	NOUN
easat-2372	148	10	of	of	ADP
easat-2372	148	11	d(x	d(x	PROPN
easat-2372	148	12	)	)	PUNCT
easat-2372	148	13	and	and	CCONJ
easat-2372	148	14	1	1	NUM
easat-2372	148	15	-	-	SYM
easat-2372	148	16	d	d	X
easat-2372	148	17	(	(	PUNCT
easat-2372	148	18	z	z	NOUN
easat-2372	148	19	)	)	PUNCT
easat-2372	148	20	that	that	PRON
easat-2372	148	21	is	be	AUX
easat-2372	148	22	defined	define	VERB
easat-2372	148	23	in	in	ADP
easat-2372	148	24	objective	objective	ADJ
easat-2372	148	25	function	function	NOUN
easat-2372	148	26	.	.	PUNCT
easat-2372	149	1	the	the	DET
easat-2372	149	2	performance	performance	NOUN
easat-2372	149	3	of	of	ADP
easat-2372	149	4	dgcan	dgcan	PROPN
easat-2372	149	5	is	be	AUX
easat-2372	149	6	assessed	assess	VERB
easat-2372	149	7	using	use	VERB
easat-2372	149	8	the	the	DET
easat-2372	149	9	average	average	ADJ
easat-2372	149	10	testing	testing	NOUN
easat-2372	149	11	accuracy	accuracy	NOUN
easat-2372	149	12	value	value	NOUN
easat-2372	149	13	.	.	PUNCT
easat-2372	150	1	for	for	ADP
easat-2372	150	2	each	each	DET
easat-2372	150	3	category	category	NOUN
easat-2372	150	4	,	,	PUNCT
easat-2372	150	5	additional	additional	ADJ
easat-2372	150	6	metrics	metric	NOUN
easat-2372	150	7	like	like	ADP
easat-2372	150	8	accuracy	accuracy	NOUN
easat-2372	150	9	,	,	PUNCT
easat-2372	150	10	f1	f1	NOUN
easat-2372	150	11	-	-	PUNCT
easat-2372	150	12	score	score	NOUN
easat-2372	150	13	,	,	PUNCT
easat-2372	150	14	recall	recall	NOUN
easat-2372	150	15	,	,	PUNCT
easat-2372	150	16	precision	precision	NOUN
easat-2372	150	17	computed	compute	VERB
easat-2372	150	18	&	&	CCONJ
easat-2372	150	19	analyzed	analyze	VERB
easat-2372	150	20	.	.	PUNCT
easat-2372	151	1	2021	2021	NUM
easat-2372	151	2	edelweiss	edelweiss	PROPN
easat-2372	151	3	applied	apply	VERB
easat-2372	151	4	science	science	NOUN
easat-2372	151	5	and	and	CCONJ
easat-2372	151	6	technology	technology	NOUN
easat-2372	151	7	issn	issn	PROPN
easat-2372	151	8	:	:	PUNCT
easat-2372	151	9	2576	2576	NUM
easat-2372	151	10	-	-	SYM
easat-2372	151	11	8484	8484	NUM
easat-2372	151	12	vol	vol	NOUN
easat-2372	151	13	.	.	PROPN
easat-2372	151	14	8	8	NUM
easat-2372	151	15	,	,	PUNCT
easat-2372	151	16	no	no	INTJ
easat-2372	151	17	.	.	NOUN
easat-2372	152	1	6	6	NUM
easat-2372	152	2	:	:	SYM
easat-2372	152	3	2015	2015	NUM
easat-2372	152	4	-	-	SYM
easat-2372	152	5	2024	2024	NUM
easat-2372	152	6	,	,	PUNCT
easat-2372	152	7	2024	2024	NUM
easat-2372	152	8	doi	doi	NOUN
easat-2372	152	9	:	:	PUNCT
easat-2372	152	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	152	11	©	©	PROPN
easat-2372	152	12	2024	2024	NUM
easat-2372	152	13	by	by	ADP
easat-2372	152	14	the	the	DET
easat-2372	152	15	authors	author	NOUN
easat-2372	152	16	;	;	PUNCT
easat-2372	152	17	licensee	licensee	PROPN
easat-2372	152	18	learning	learn	VERB
easat-2372	152	19	gate	gate	NOUN
easat-2372	152	20	figure	figure	NOUN
easat-2372	152	21	4	4	NUM
easat-2372	152	22	.	.	PUNCT
easat-2372	153	1	epoch	epoch	NOUN
easat-2372	153	2	analysis	analysis	NOUN
easat-2372	153	3	(	(	PUNCT
easat-2372	153	4	1	1	NUM
easat-2372	153	5	-	-	SYM
easat-2372	153	6	1000	1000	NUM
easat-2372	153	7	)	)	PUNCT
easat-2372	153	8	for	for	ADP
easat-2372	153	9	blast	blast	NOUN
easat-2372	153	10	.	.	PUNCT
easat-2372	154	1	figure	figure	NOUN
easat-2372	154	2	5	5	NUM
easat-2372	154	3	.	.	PUNCT
easat-2372	155	1	epoch	epoch	NOUN
easat-2372	155	2	analysis	analysis	NOUN
easat-2372	155	3	(	(	PUNCT
easat-2372	155	4	1	1	NUM
easat-2372	155	5	-	-	SYM
easat-2372	155	6	1000	1000	NUM
easat-2372	155	7	)	)	PUNCT
easat-2372	155	8	for	for	ADP
easat-2372	155	9	tungro	tungro	NOUN
easat-2372	155	10	.	.	PUNCT
easat-2372	156	1	table	table	NOUN
easat-2372	156	2	1	1	NUM
easat-2372	156	3	.	.	PUNCT
easat-2372	156	4	cnn	cnn	PROPN
easat-2372	156	5	model	model	PROPN
easat-2372	156	6	accuracy	accuracy	NOUN
easat-2372	156	7	without	without	ADP
easat-2372	156	8	gan	gan	PROPN
easat-2372	156	9	.	.	PROPN
easat-2372	156	10	method	method	PROPN
easat-2372	156	11	optimizer	optimizer	NOUN
easat-2372	156	12	loss	loss	NOUN
easat-2372	156	13	function	function	VERB
easat-2372	156	14	epoch	epoch	PROPN
easat-2372	156	15	validation	validation	PROPN
easat-2372	156	16	accuracy	accuracy	NOUN
easat-2372	156	17	cnn	cnn	PROPN
easat-2372	156	18	(	(	PUNCT
easat-2372	156	19	from	from	ADP
easat-2372	156	20	scratch	scratch	NOUN
easat-2372	156	21	)	)	PUNCT
easat-2372	156	22	sgd	sgd	PROPN
easat-2372	156	23	categorical_crossentropy	categorical_crossentropy	NOUN
easat-2372	156	24	25	25	NUM
easat-2372	156	25	98.75	98.75	NUM
easat-2372	156	26	2022	2022	NUM
easat-2372	156	27	edelweiss	edelweiss	PROPN
easat-2372	156	28	applied	apply	VERB
easat-2372	156	29	science	science	NOUN
easat-2372	156	30	and	and	CCONJ
easat-2372	156	31	technology	technology	NOUN
easat-2372	156	32	issn	issn	PROPN
easat-2372	156	33	:	:	PUNCT
easat-2372	156	34	2576	2576	NUM
easat-2372	156	35	-	-	SYM
easat-2372	156	36	8484	8484	NUM
easat-2372	156	37	vol	vol	NOUN
easat-2372	156	38	.	.	PROPN
easat-2372	157	1	8	8	NUM
easat-2372	157	2	,	,	PUNCT
easat-2372	157	3	no	no	INTJ
easat-2372	157	4	.	.	NOUN
easat-2372	158	1	6	6	NUM
easat-2372	158	2	:	:	SYM
easat-2372	158	3	2015	2015	NUM
easat-2372	158	4	-	-	SYM
easat-2372	158	5	2024	2024	NUM
easat-2372	158	6	,	,	PUNCT
easat-2372	158	7	2024	2024	NUM
easat-2372	158	8	doi	doi	NOUN
easat-2372	158	9	:	:	PUNCT
easat-2372	158	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	158	11	©	©	PROPN
easat-2372	158	12	2024	2024	NUM
easat-2372	158	13	by	by	ADP
easat-2372	158	14	the	the	DET
easat-2372	158	15	authors	author	NOUN
easat-2372	158	16	;	;	PUNCT
easat-2372	158	17	licensee	licensee	PROPN
easat-2372	158	18	learning	learn	VERB
easat-2372	158	19	gate	gate	NOUN
easat-2372	158	20	table	table	NOUN
easat-2372	158	21	2	2	NUM
easat-2372	158	22	.	.	PUNCT
easat-2372	158	23	accuracy	accuracy	NOUN
easat-2372	158	24	of	of	ADP
easat-2372	158	25	cnn	cnn	PROPN
easat-2372	158	26	with	with	ADP
easat-2372	158	27	dcgan	dcgan	PROPN
easat-2372	158	28	.	.	PUNCT
easat-2372	159	1	method	method	PROPN
easat-2372	159	2	optimizer	optimizer	NOUN
easat-2372	159	3	loss	loss	NOUN
easat-2372	159	4	function	function	VERB
easat-2372	159	5	epoch	epoch	PROPN
easat-2372	159	6	validation	validation	PROPN
easat-2372	159	7	accuracy	accuracy	NOUN
easat-2372	159	8	cnn	cnn	PROPN
easat-2372	159	9	(	(	PUNCT
easat-2372	159	10	from	from	ADP
easat-2372	159	11	scratch	scratch	NOUN
easat-2372	159	12	)	)	PUNCT
easat-2372	159	13	sgd	sgd	PROPN
easat-2372	159	14	categorical	categorical	PROPN
easat-2372	159	15	cross	cross	PROPN
easat-2372	159	16	entropy	entropy	VERB
easat-2372	159	17	25	25	NUM
easat-2372	159	18	99.75	99.75	NUM
easat-2372	159	19	figure	figure	NOUN
easat-2372	159	20	6	6	NUM
easat-2372	159	21	.	.	PUNCT
easat-2372	159	22	cnn(dcgan	cnn(dcgan	ADJ
easat-2372	159	23	)	)	PUNCT
easat-2372	159	24	training	training	NOUN
easat-2372	159	25	&	&	CCONJ
easat-2372	159	26	validation	validation	NOUN
easat-2372	159	27	loss	loss	NOUN
easat-2372	159	28	.	.	PUNCT
easat-2372	160	1	5	5	X
easat-2372	160	2	.	.	X
easat-2372	160	3	discussions	discussion	NOUN
easat-2372	160	4	1	1	NUM
easat-2372	160	5	.	.	PUNCT
easat-2372	160	6	cnn	cnn	PROPN
easat-2372	160	7	with	with	ADP
easat-2372	160	8	and	and	CCONJ
easat-2372	160	9	without	without	ADP
easat-2372	160	10	gan	gan	ADJ
easat-2372	160	11	integration	integration	NOUN
easat-2372	160	12	:	:	PUNCT
easat-2372	160	13	table	table	NOUN
easat-2372	160	14	1	1	NUM
easat-2372	160	15	shows	show	VERB
easat-2372	160	16	that	that	SCONJ
easat-2372	160	17	the	the	DET
easat-2372	160	18	baseline	baseline	PROPN
easat-2372	160	19	cnn	cnn	PROPN
easat-2372	160	20	model	model	NOUN
easat-2372	160	21	,	,	PUNCT
easat-2372	160	22	trained	train	VERB
easat-2372	160	23	from	from	ADP
easat-2372	160	24	scratch	scratch	NOUN
easat-2372	160	25	without	without	ADP
easat-2372	160	26	synthetic	synthetic	ADJ
easat-2372	160	27	data	datum	NOUN
easat-2372	160	28	,	,	PUNCT
easat-2372	160	29	achieved	achieve	VERB
easat-2372	160	30	a	a	DET
easat-2372	160	31	validation	validation	NOUN
easat-2372	160	32	accuracy	accuracy	NOUN
easat-2372	160	33	of	of	ADP
easat-2372	160	34	98.75	98.75	NUM
easat-2372	160	35	%	%	NOUN
easat-2372	160	36	.	.	PUNCT
easat-2372	161	1	however	however	ADV
easat-2372	161	2	,	,	PUNCT
easat-2372	161	3	as	as	SCONJ
easat-2372	161	4	shown	show	VERB
easat-2372	161	5	in	in	ADP
easat-2372	161	6	table	table	NOUN
easat-2372	161	7	2	2	NUM
easat-2372	161	8	,	,	PUNCT
easat-2372	161	9	after	after	ADP
easat-2372	161	10	introducing	introduce	VERB
easat-2372	161	11	dcgan	dcgan	NOUN
easat-2372	161	12	-	-	PUNCT
easat-2372	161	13	generated	generate	VERB
easat-2372	161	14	images	image	NOUN
easat-2372	161	15	,	,	PUNCT
easat-2372	161	16	the	the	DET
easat-2372	161	17	validation	validation	NOUN
easat-2372	161	18	accuracy	accuracy	NOUN
easat-2372	161	19	rose	rise	VERB
easat-2372	161	20	to	to	ADP
easat-2372	161	21	99.75	99.75	NUM
easat-2372	161	22	%	%	NOUN
easat-2372	161	23	.	.	PUNCT
easat-2372	162	1	this	this	DET
easat-2372	162	2	increase	increase	NOUN
easat-2372	162	3	in	in	ADP
easat-2372	162	4	accuracy	accuracy	NOUN
easat-2372	162	5	underscores	underscore	VERB
easat-2372	162	6	the	the	DET
easat-2372	162	7	advantage	advantage	NOUN
easat-2372	162	8	of	of	ADP
easat-2372	162	9	using	use	VERB
easat-2372	162	10	synthetic	synthetic	ADJ
easat-2372	162	11	images	image	NOUN
easat-2372	162	12	generated	generate	VERB
easat-2372	162	13	by	by	ADP
easat-2372	162	14	dcgan	dcgan	NOUN
easat-2372	162	15	,	,	PUNCT
easat-2372	162	16	suggesting	suggest	VERB
easat-2372	162	17	that	that	SCONJ
easat-2372	162	18	the	the	DET
easat-2372	162	19	model	model	NOUN
easat-2372	162	20	was	be	AUX
easat-2372	162	21	better	well	ADV
easat-2372	162	22	equipped	equip	VERB
easat-2372	162	23	to	to	PART
easat-2372	162	24	generalize	generalize	VERB
easat-2372	162	25	to	to	ADP
easat-2372	162	26	unseen	unseen	ADJ
easat-2372	162	27	data	datum	NOUN
easat-2372	162	28	.	.	PUNCT
easat-2372	163	1	2	2	X
easat-2372	163	2	.	.	X
easat-2372	163	3	training	training	NOUN
easat-2372	163	4	and	and	CCONJ
easat-2372	163	5	validation	validation	NOUN
easat-2372	163	6	metrics	metric	NOUN
easat-2372	163	7	:	:	PUNCT
easat-2372	163	8	the	the	DET
easat-2372	163	9	training	training	NOUN
easat-2372	163	10	and	and	CCONJ
easat-2372	163	11	validation	validation	NOUN
easat-2372	163	12	loss	loss	NOUN
easat-2372	163	13	and	and	CCONJ
easat-2372	163	14	accuracy	accuracy	NOUN
easat-2372	163	15	plots	plot	NOUN
easat-2372	163	16	(	(	PUNCT
easat-2372	163	17	shown	show	VERB
easat-2372	163	18	in	in	ADP
easat-2372	163	19	the	the	DET
easat-2372	163	20	figures	figure	NOUN
easat-2372	163	21	)	)	PUNCT
easat-2372	163	22	provide	provide	VERB
easat-2372	163	23	insights	insight	NOUN
easat-2372	163	24	into	into	ADP
easat-2372	163	25	the	the	DET
easat-2372	163	26	model	model	NOUN
easat-2372	163	27	's	's	PART
easat-2372	163	28	learning	learning	NOUN
easat-2372	163	29	process	process	NOUN
easat-2372	163	30	.	.	PUNCT
easat-2372	164	1	the	the	DET
easat-2372	164	2	validation	validation	NOUN
easat-2372	164	3	loss	loss	NOUN
easat-2372	164	4	consistently	consistently	ADV
easat-2372	164	5	tracks	track	VERB
easat-2372	164	6	the	the	DET
easat-2372	164	7	training	training	NOUN
easat-2372	164	8	loss	loss	NOUN
easat-2372	164	9	,	,	PUNCT
easat-2372	164	10	indicating	indicate	VERB
easat-2372	164	11	that	that	SCONJ
easat-2372	164	12	the	the	DET
easat-2372	164	13	model	model	NOUN
easat-2372	164	14	is	be	AUX
easat-2372	164	15	not	not	PART
easat-2372	164	16	significantly	significantly	ADV
easat-2372	164	17	overfitting	overfitte	VERB
easat-2372	164	18	.	.	PUNCT
easat-2372	165	1	over	over	ADP
easat-2372	165	2	the	the	DET
easat-2372	165	3	course	course	NOUN
easat-2372	165	4	of	of	ADP
easat-2372	165	5	25	25	NUM
easat-2372	165	6	epochs	epoch	NOUN
easat-2372	165	7	,	,	PUNCT
easat-2372	165	8	the	the	DET
easat-2372	165	9	validation	validation	NOUN
easat-2372	165	10	accuracy	accuracy	NOUN
easat-2372	165	11	remained	remain	VERB
easat-2372	165	12	stable	stable	ADJ
easat-2372	165	13	and	and	CCONJ
easat-2372	165	14	high	high	ADJ
easat-2372	165	15	,	,	PUNCT
easat-2372	165	16	reaching	reach	VERB
easat-2372	165	17	close	close	ADV
easat-2372	165	18	to	to	PART
easat-2372	165	19	99.5	99.5	NUM
easat-2372	165	20	%	%	NOUN
easat-2372	165	21	.	.	PUNCT
easat-2372	166	1	the	the	DET
easat-2372	166	2	training	training	NOUN
easat-2372	166	3	loss	loss	NOUN
easat-2372	166	4	steadily	steadily	ADV
easat-2372	166	5	decreased	decrease	VERB
easat-2372	166	6	over	over	ADP
easat-2372	166	7	time	time	NOUN
easat-2372	166	8	,	,	PUNCT
easat-2372	166	9	with	with	ADP
easat-2372	166	10	validation	validation	NOUN
easat-2372	166	11	loss	loss	NOUN
easat-2372	166	12	showing	show	VERB
easat-2372	166	13	more	more	ADJ
easat-2372	166	14	fluctuations	fluctuation	NOUN
easat-2372	166	15	but	but	CCONJ
easat-2372	166	16	overall	overall	ADV
easat-2372	166	17	following	follow	VERB
easat-2372	166	18	the	the	DET
easat-2372	166	19	same	same	ADJ
easat-2372	166	20	downward	downward	ADJ
easat-2372	166	21	trend	trend	NOUN
easat-2372	166	22	.	.	PUNCT
easat-2372	167	1	the	the	DET
easat-2372	167	2	proximity	proximity	NOUN
easat-2372	167	3	of	of	ADP
easat-2372	167	4	the	the	DET
easat-2372	167	5	two	two	NUM
easat-2372	167	6	curves	curve	NOUN
easat-2372	167	7	indicates	indicate	VERB
easat-2372	167	8	minimal	minimal	ADJ
easat-2372	167	9	overfitting	overfitting	NOUN
easat-2372	167	10	.	.	PUNCT
easat-2372	168	1	3	3	X
easat-2372	168	2	.	.	X
easat-2372	168	3	dcgan	dcgan	VERB
easat-2372	168	4	epoch	epoch	PROPN
easat-2372	168	5	analysis	analysis	NOUN
easat-2372	168	6	:	:	PUNCT
easat-2372	168	7	figures	figure	NOUN
easat-2372	168	8	depicting	depict	VERB
easat-2372	168	9	the	the	DET
easat-2372	168	10	quality	quality	NOUN
easat-2372	168	11	of	of	ADP
easat-2372	168	12	dcgan	dcgan	NOUN
easat-2372	168	13	-	-	PUNCT
easat-2372	168	14	generated	generate	VERB
easat-2372	168	15	images	image	NOUN
easat-2372	168	16	for	for	ADP
easat-2372	168	17	blast	blast	NOUN
easat-2372	168	18	and	and	CCONJ
easat-2372	168	19	tungro	tungro	VERB
easat-2372	168	20	diseases	disease	NOUN
easat-2372	168	21	across	across	ADP
easat-2372	168	22	different	different	ADJ
easat-2372	168	23	epoch	epoch	NOUN
easat-2372	168	24	values	value	NOUN
easat-2372	168	25	(	(	PUNCT
easat-2372	168	26	200	200	NUM
easat-2372	168	27	,	,	PUNCT
easat-2372	168	28	500	500	NUM
easat-2372	168	29	,	,	PUNCT
easat-2372	168	30	1000	1000	NUM
easat-2372	168	31	)	)	PUNCT
easat-2372	168	32	indicate	indicate	VERB
easat-2372	168	33	that	that	SCONJ
easat-2372	168	34	as	as	ADP
easat-2372	168	35	the	the	DET
easat-2372	168	36	number	number	NOUN
easat-2372	168	37	of	of	ADP
easat-2372	168	38	epochs	epoch	NOUN
easat-2372	168	39	increases	increase	NOUN
easat-2372	168	40	,	,	PUNCT
easat-2372	168	41	the	the	DET
easat-2372	168	42	quality	quality	NOUN
easat-2372	168	43	of	of	ADP
easat-2372	168	44	the	the	DET
easat-2372	168	45	generated	generate	VERB
easat-2372	168	46	images	image	NOUN
easat-2372	168	47	improves	improve	VERB
easat-2372	168	48	.	.	PUNCT
easat-2372	169	1	this	this	PRON
easat-2372	169	2	is	be	AUX
easat-2372	169	3	particularly	particularly	ADV
easat-2372	169	4	noticeable	noticeable	ADJ
easat-2372	169	5	for	for	ADP
easat-2372	169	6	epoch	epoch	NOUN
easat-2372	169	7	values	value	NOUN
easat-2372	169	8	of	of	ADP
easat-2372	169	9	1000	1000	NUM
easat-2372	169	10	,	,	PUNCT
easat-2372	169	11	where	where	SCONJ
easat-2372	169	12	the	the	DET
easat-2372	169	13	synthetic	synthetic	ADJ
easat-2372	169	14	images	image	NOUN
easat-2372	169	15	are	be	AUX
easat-2372	169	16	almost	almost	ADV
easat-2372	169	17	indistinguishable	indistinguishable	ADJ
easat-2372	169	18	from	from	ADP
easat-2372	169	19	real	real	ADJ
easat-2372	169	20	ones	one	NOUN
easat-2372	169	21	.	.	PUNCT
easat-2372	170	1	the	the	DET
easat-2372	170	2	visual	visual	ADJ
easat-2372	170	3	improvement	improvement	NOUN
easat-2372	170	4	suggests	suggest	VERB
easat-2372	170	5	that	that	SCONJ
easat-2372	170	6	the	the	DET
easat-2372	170	7	generator	generator	NOUN
easat-2372	170	8	network	network	NOUN
easat-2372	170	9	in	in	ADP
easat-2372	170	10	the	the	DET
easat-2372	170	11	dcgan	dcgan	NOUN
easat-2372	170	12	becomes	become	VERB
easat-2372	170	13	more	more	ADV
easat-2372	170	14	adept	adept	ADJ
easat-2372	170	15	at	at	ADP
easat-2372	170	16	producing	produce	VERB
easat-2372	170	17	realistic	realistic	ADJ
easat-2372	170	18	images	image	NOUN
easat-2372	170	19	with	with	ADP
easat-2372	170	20	more	more	ADJ
easat-2372	170	21	training	training	NOUN
easat-2372	170	22	iterations	iteration	NOUN
easat-2372	170	23	.	.	PUNCT
easat-2372	171	1	4	4	X
easat-2372	171	2	.	.	X
easat-2372	171	3	loss	loss	NOUN
easat-2372	171	4	function	function	NOUN
easat-2372	171	5	behaviour	behaviour	NOUN
easat-2372	171	6	:	:	PUNCT
easat-2372	171	7	the	the	DET
easat-2372	171	8	generator	generator	NOUN
easat-2372	171	9	and	and	CCONJ
easat-2372	171	10	discriminator	discriminator	NOUN
easat-2372	171	11	losses	loss	NOUN
easat-2372	171	12	reveal	reveal	VERB
easat-2372	171	13	an	an	DET
easat-2372	171	14	interesting	interesting	ADJ
easat-2372	171	15	trend	trend	NOUN
easat-2372	171	16	.	.	PUNCT
easat-2372	172	1	initially	initially	ADV
easat-2372	172	2	,	,	PUNCT
easat-2372	172	3	the	the	DET
easat-2372	172	4	generator	generator	NOUN
easat-2372	172	5	loss	loss	NOUN
easat-2372	172	6	increases	increase	NOUN
easat-2372	172	7	,	,	PUNCT
easat-2372	172	8	which	which	PRON
easat-2372	172	9	might	might	AUX
easat-2372	172	10	indicate	indicate	VERB
easat-2372	172	11	that	that	SCONJ
easat-2372	172	12	it	it	PRON
easat-2372	172	13	struggles	struggle	VERB
easat-2372	172	14	to	to	PART
easat-2372	172	15	fool	fool	VERB
easat-2372	172	16	the	the	DET
easat-2372	172	17	discriminator	discriminator	NOUN
easat-2372	172	18	.	.	PUNCT
easat-2372	173	1	however	however	ADV
easat-2372	173	2	,	,	PUNCT
easat-2372	173	3	as	as	SCONJ
easat-2372	173	4	the	the	DET
easat-2372	173	5	epochs	epoch	NOUN
easat-2372	173	6	increase	increase	VERB
easat-2372	173	7	,	,	PUNCT
easat-2372	173	8	the	the	DET
easat-2372	173	9	discriminator	discriminator	NOUN
easat-2372	173	10	loss	loss	NOUN
easat-2372	173	11	decreases	decrease	VERB
easat-2372	173	12	,	,	PUNCT
easat-2372	173	13	eventually	eventually	ADV
easat-2372	173	14	reaching	reach	VERB
easat-2372	173	15	a	a	DET
easat-2372	173	16	minimum	minimum	NOUN
easat-2372	173	17	at	at	ADP
easat-2372	173	18	1000	1000	NUM
easat-2372	173	19	epochs	epoch	NOUN
easat-2372	173	20	.	.	PUNCT
easat-2372	174	1	this	this	PRON
easat-2372	174	2	is	be	AUX
easat-2372	174	3	a	a	DET
easat-2372	174	4	common	common	ADJ
easat-2372	174	5	observation	observation	NOUN
easat-2372	174	6	in	in	ADP
easat-2372	174	7	gan	gan	NOUN
easat-2372	174	8	-	-	PUNCT
easat-2372	174	9	based	base	VERB
easat-2372	174	10	models	model	NOUN
easat-2372	174	11	where	where	SCONJ
easat-2372	174	12	,	,	PUNCT
easat-2372	174	13	over	over	ADP
easat-2372	174	14	time	time	NOUN
easat-2372	174	15	,	,	PUNCT
easat-2372	174	16	the	the	DET
easat-2372	174	17	generator	generator	NOUN
easat-2372	174	18	becomes	become	VERB
easat-2372	174	19	more	more	ADV
easat-2372	174	20	effective	effective	ADJ
easat-2372	174	21	at	at	ADP
easat-2372	174	22	producing	produce	VERB
easat-2372	174	23	realistic	realistic	ADJ
easat-2372	174	24	images	image	NOUN
easat-2372	174	25	,	,	PUNCT
easat-2372	174	26	while	while	SCONJ
easat-2372	174	27	the	the	DET
easat-2372	174	28	discriminator	discriminator	NOUN
easat-2372	174	29	becomes	become	VERB
easat-2372	174	30	less	less	ADV
easat-2372	174	31	able	able	ADJ
easat-2372	174	32	to	to	PART
easat-2372	174	33	distinguish	distinguish	VERB
easat-2372	174	34	between	between	ADP
easat-2372	174	35	real	real	ADJ
easat-2372	174	36	and	and	CCONJ
easat-2372	174	37	fake	fake	ADJ
easat-2372	174	38	images	image	NOUN
easat-2372	174	39	.	.	PUNCT
easat-2372	175	1	5	5	X
easat-2372	175	2	.	.	X
easat-2372	175	3	quantitative	quantitative	ADJ
easat-2372	175	4	metrics	metric	NOUN
easat-2372	175	5	and	and	CCONJ
easat-2372	175	6	performance	performance	NOUN
easat-2372	175	7	:	:	PUNCT
easat-2372	175	8	the	the	DET
easat-2372	175	9	research	research	NOUN
easat-2372	175	10	highlights	highlight	VERB
easat-2372	175	11	various	various	ADJ
easat-2372	175	12	metrics	metric	NOUN
easat-2372	175	13	for	for	ADP
easat-2372	175	14	assessing	assess	VERB
easat-2372	175	15	the	the	DET
easat-2372	175	16	model	model	NOUN
easat-2372	175	17	's	's	PART
easat-2372	175	18	performance	performance	NOUN
easat-2372	175	19	.	.	PUNCT
easat-2372	176	1	in	in	ADP
easat-2372	176	2	addition	addition	NOUN
easat-2372	176	3	to	to	ADP
easat-2372	176	4	accuracy	accuracy	NOUN
easat-2372	176	5	,	,	PUNCT
easat-2372	176	6	precision	precision	NOUN
easat-2372	176	7	,	,	PUNCT
easat-2372	176	8	recall	recall	NOUN
easat-2372	176	9	,	,	PUNCT
easat-2372	176	10	and	and	CCONJ
easat-2372	176	11	f1	f1	NOUN
easat-2372	176	12	-	-	PUNCT
easat-2372	176	13	score	score	NOUN
easat-2372	176	14	are	be	AUX
easat-2372	176	15	computed	compute	VERB
easat-2372	176	16	for	for	ADP
easat-2372	176	17	both	both	CCONJ
easat-2372	176	18	the	the	DET
easat-2372	176	19	real	real	ADJ
easat-2372	176	20	and	and	CCONJ
easat-2372	176	21	synthetic	synthetic	ADJ
easat-2372	176	22	datasets	dataset	NOUN
easat-2372	176	23	.	.	PUNCT
easat-2372	177	1	the	the	DET
easat-2372	177	2	cnn	cnn	PROPN
easat-2372	177	3	model	model	NOUN
easat-2372	177	4	trained	train	VERB
easat-2372	177	5	with	with	ADP
easat-2372	177	6	dcgan	dcgan	NOUN
easat-2372	177	7	images	image	NOUN
easat-2372	177	8	outperforms	outperform	VERB
easat-2372	177	9	the	the	DET
easat-2372	177	10	baseline	baseline	NOUN
easat-2372	177	11	in	in	ADP
easat-2372	177	12	almost	almost	ADV
easat-2372	177	13	every	every	PRON
easat-2372	177	14	metric	metric	NOUN
easat-2372	177	15	.	.	PUNCT
easat-2372	178	1	the	the	DET
easat-2372	178	2	increase	increase	NOUN
easat-2372	178	3	in	in	ADP
easat-2372	178	4	accuracy	accuracy	NOUN
easat-2372	178	5	and	and	CCONJ
easat-2372	178	6	other	other	ADJ
easat-2372	178	7	performance	performance	NOUN
easat-2372	178	8	metrics	metric	NOUN
easat-2372	178	9	can	can	AUX
easat-2372	178	10	be	be	AUX
easat-2372	178	11	attributed	attribute	VERB
easat-2372	178	12	to	to	ADP
easat-2372	178	13	the	the	DET
easat-2372	178	14	enlarged	enlarge	VERB
easat-2372	178	15	and	and	CCONJ
easat-2372	178	16	diversified	diversify	VERB
easat-2372	178	17	dataset	dataset	NOUN
easat-2372	178	18	created	create	VERB
easat-2372	178	19	by	by	ADP
easat-2372	178	20	adding	add	VERB
easat-2372	178	21	synthetic	synthetic	ADJ
easat-2372	178	22	images	image	NOUN
easat-2372	178	23	to	to	ADP
easat-2372	178	24	the	the	DET
easat-2372	178	25	training	training	NOUN
easat-2372	178	26	set	set	NOUN
easat-2372	178	27	.	.	PUNCT
easat-2372	179	1	2023	2023	NUM
easat-2372	179	2	edelweiss	edelweiss	PROPN
easat-2372	179	3	applied	apply	VERB
easat-2372	179	4	science	science	NOUN
easat-2372	179	5	and	and	CCONJ
easat-2372	179	6	technology	technology	NOUN
easat-2372	179	7	issn	issn	PROPN
easat-2372	179	8	:	:	PUNCT
easat-2372	179	9	2576	2576	NUM
easat-2372	179	10	-	-	SYM
easat-2372	179	11	8484	8484	NUM
easat-2372	179	12	vol	vol	NOUN
easat-2372	179	13	.	.	PROPN
easat-2372	179	14	8	8	NUM
easat-2372	179	15	,	,	PUNCT
easat-2372	179	16	no	no	INTJ
easat-2372	179	17	.	.	NOUN
easat-2372	180	1	6	6	NUM
easat-2372	180	2	:	:	SYM
easat-2372	180	3	2015	2015	NUM
easat-2372	180	4	-	-	SYM
easat-2372	180	5	2024	2024	NUM
easat-2372	180	6	,	,	PUNCT
easat-2372	180	7	2024	2024	NUM
easat-2372	180	8	doi	doi	NOUN
easat-2372	180	9	:	:	PUNCT
easat-2372	180	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	180	11	©	©	PROPN
easat-2372	180	12	2024	2024	NUM
easat-2372	180	13	by	by	ADP
easat-2372	180	14	the	the	DET
easat-2372	180	15	authors	author	NOUN
easat-2372	180	16	;	;	PUNCT
easat-2372	180	17	licensee	licensee	PROPN
easat-2372	180	18	learning	learning	NOUN
easat-2372	180	19	gate	gate	NOUN
easat-2372	180	20	6	6	NUM
easat-2372	180	21	.	.	PUNCT
easat-2372	180	22	training	training	NOUN
easat-2372	180	23	and	and	CCONJ
easat-2372	180	24	validation	validation	NOUN
easat-2372	180	25	loss	loss	NOUN
easat-2372	180	26	comparison	comparison	NOUN
easat-2372	180	27	:	:	PUNCT
easat-2372	180	28	the	the	DET
easat-2372	180	29	training	training	NOUN
easat-2372	180	30	and	and	CCONJ
easat-2372	180	31	validation	validation	NOUN
easat-2372	180	32	loss	loss	NOUN
easat-2372	180	33	curves	curve	NOUN
easat-2372	180	34	for	for	ADP
easat-2372	180	35	the	the	DET
easat-2372	180	36	cnn	cnn	PROPN
easat-2372	180	37	model	model	NOUN
easat-2372	180	38	with	with	ADP
easat-2372	180	39	dcgan	dcgan	NOUN
easat-2372	180	40	reveal	reveal	VERB
easat-2372	180	41	that	that	SCONJ
easat-2372	180	42	the	the	DET
easat-2372	180	43	model	model	NOUN
easat-2372	180	44	is	be	AUX
easat-2372	180	45	learning	learn	VERB
easat-2372	180	46	effectively	effectively	ADV
easat-2372	180	47	without	without	ADP
easat-2372	180	48	major	major	ADJ
easat-2372	180	49	signs	sign	NOUN
easat-2372	180	50	of	of	ADP
easat-2372	180	51	overfitting	overfitte	VERB
easat-2372	180	52	.	.	PUNCT
easat-2372	181	1	both	both	CCONJ
easat-2372	181	2	the	the	DET
easat-2372	181	3	training	training	NOUN
easat-2372	181	4	and	and	CCONJ
easat-2372	181	5	validation	validation	NOUN
easat-2372	181	6	losses	loss	NOUN
easat-2372	181	7	decrease	decrease	VERB
easat-2372	181	8	steadily	steadily	ADV
easat-2372	181	9	throughout	throughout	ADP
easat-2372	181	10	the	the	DET
easat-2372	181	11	epochs	epoch	NOUN
easat-2372	181	12	.	.	PUNCT
easat-2372	182	1	the	the	DET
easat-2372	182	2	fact	fact	NOUN
easat-2372	182	3	that	that	SCONJ
easat-2372	182	4	the	the	DET
easat-2372	182	5	loss	loss	NOUN
easat-2372	182	6	curves	curve	VERB
easat-2372	182	7	for	for	ADP
easat-2372	182	8	both	both	DET
easat-2372	182	9	datasets	dataset	NOUN
easat-2372	182	10	—	—	PUNCT
easat-2372	182	11	real	real	ADJ
easat-2372	182	12	and	and	CCONJ
easat-2372	182	13	augmented	augment	VERB
easat-2372	182	14	with	with	ADP
easat-2372	182	15	synthetic	synthetic	ADJ
easat-2372	182	16	images	image	NOUN
easat-2372	182	17	—	—	PUNCT
easat-2372	182	18	are	be	AUX
easat-2372	182	19	very	very	ADV
easat-2372	182	20	similar	similar	ADJ
easat-2372	182	21	further	far	ADV
easat-2372	182	22	validates	validate	VERB
easat-2372	182	23	the	the	DET
easat-2372	182	24	effectiveness	effectiveness	NOUN
easat-2372	182	25	of	of	ADP
easat-2372	182	26	dcgan	dcgan	NOUN
easat-2372	182	27	in	in	ADP
easat-2372	182	28	generating	generate	VERB
easat-2372	182	29	meaningful	meaningful	ADJ
easat-2372	182	30	data	datum	NOUN
easat-2372	182	31	for	for	ADP
easat-2372	182	32	the	the	DET
easat-2372	182	33	training	training	NOUN
easat-2372	182	34	process	process	NOUN
easat-2372	182	35	.	.	PUNCT
easat-2372	183	1	the	the	DET
easat-2372	183	2	results	result	NOUN
easat-2372	183	3	presented	present	VERB
easat-2372	183	4	in	in	ADP
easat-2372	183	5	this	this	DET
easat-2372	183	6	analysis	analysis	NOUN
easat-2372	183	7	highlight	highlight	VERB
easat-2372	183	8	the	the	DET
easat-2372	183	9	power	power	NOUN
easat-2372	183	10	of	of	ADP
easat-2372	183	11	synthetic	synthetic	ADJ
easat-2372	183	12	data	data	NOUN
easat-2372	183	13	generation	generation	NOUN
easat-2372	183	14	using	use	VERB
easat-2372	183	15	dcgan	dcgan	NOUN
easat-2372	183	16	,	,	PUNCT
easat-2372	183	17	especially	especially	ADV
easat-2372	183	18	in	in	ADP
easat-2372	183	19	scenarios	scenario	NOUN
easat-2372	183	20	where	where	SCONJ
easat-2372	183	21	the	the	DET
easat-2372	183	22	dataset	dataset	NOUN
easat-2372	183	23	is	be	AUX
easat-2372	183	24	small	small	ADJ
easat-2372	183	25	or	or	CCONJ
easat-2372	183	26	imbalanced	imbalanced	ADJ
easat-2372	183	27	.	.	PUNCT
easat-2372	184	1	this	this	DET
easat-2372	184	2	study	study	NOUN
easat-2372	184	3	lays	lay	VERB
easat-2372	184	4	a	a	DET
easat-2372	184	5	foundation	foundation	NOUN
easat-2372	184	6	for	for	ADP
easat-2372	184	7	future	future	ADJ
easat-2372	184	8	research	research	NOUN
easat-2372	184	9	into	into	ADP
easat-2372	184	10	the	the	DET
easat-2372	184	11	benefits	benefit	NOUN
easat-2372	184	12	of	of	ADP
easat-2372	184	13	gans	gan	NOUN
easat-2372	184	14	in	in	ADP
easat-2372	184	15	generating	generate	VERB
easat-2372	184	16	data	datum	NOUN
easat-2372	184	17	across	across	ADP
easat-2372	184	18	various	various	ADJ
easat-2372	184	19	domains	domain	NOUN
easat-2372	184	20	,	,	PUNCT
easat-2372	184	21	including	include	VERB
easat-2372	184	22	agriculture	agriculture	NOUN
easat-2372	184	23	,	,	PUNCT
easat-2372	184	24	medical	medical	ADJ
easat-2372	184	25	imaging	imaging	NOUN
easat-2372	184	26	,	,	PUNCT
easat-2372	184	27	and	and	CCONJ
easat-2372	184	28	other	other	ADJ
easat-2372	184	29	industries	industry	NOUN
easat-2372	184	30	requiring	require	VERB
easat-2372	184	31	image	image	NOUN
easat-2372	184	32	classification	classification	NOUN
easat-2372	184	33	.	.	PUNCT
easat-2372	185	1	future	future	ADJ
easat-2372	185	2	research	research	NOUN
easat-2372	185	3	could	could	AUX
easat-2372	185	4	explore	explore	VERB
easat-2372	185	5	different	different	ADJ
easat-2372	185	6	gan	gan	PROPN
easat-2372	185	7	architectures	architecture	NOUN
easat-2372	185	8	,	,	PUNCT
easat-2372	185	9	such	such	ADJ
easat-2372	185	10	as	as	ADP
easat-2372	185	11	wasserstein	wasserstein	NOUN
easat-2372	185	12	gans	gan	NOUN
easat-2372	185	13	(	(	PUNCT
easat-2372	185	14	wgans	wgans	PROPN
easat-2372	185	15	)	)	PUNCT
easat-2372	185	16	,	,	PUNCT
easat-2372	185	17	to	to	PART
easat-2372	185	18	see	see	VERB
easat-2372	185	19	if	if	SCONJ
easat-2372	185	20	further	further	ADJ
easat-2372	185	21	improvements	improvement	NOUN
easat-2372	185	22	in	in	ADP
easat-2372	185	23	the	the	DET
easat-2372	185	24	quality	quality	NOUN
easat-2372	185	25	of	of	ADP
easat-2372	185	26	synthetic	synthetic	ADJ
easat-2372	185	27	data	datum	NOUN
easat-2372	185	28	and	and	CCONJ
easat-2372	185	29	model	model	NOUN
easat-2372	185	30	performance	performance	NOUN
easat-2372	185	31	can	can	AUX
easat-2372	185	32	be	be	AUX
easat-2372	185	33	achieved	achieve	VERB
easat-2372	185	34	.	.	PUNCT
easat-2372	186	1	in	in	ADP
easat-2372	186	2	conclusion	conclusion	NOUN
easat-2372	186	3	,	,	PUNCT
easat-2372	186	4	by	by	ADP
easat-2372	186	5	utilizing	utilize	VERB
easat-2372	186	6	dcgan	dcgan	NOUN
easat-2372	186	7	-	-	PUNCT
easat-2372	186	8	generated	generate	VERB
easat-2372	186	9	images	image	NOUN
easat-2372	186	10	,	,	PUNCT
easat-2372	186	11	the	the	DET
easat-2372	186	12	cnn	cnn	PROPN
easat-2372	186	13	model	model	NOUN
easat-2372	186	14	not	not	PART
easat-2372	186	15	only	only	ADV
easat-2372	186	16	increased	increase	VERB
easat-2372	186	17	in	in	ADP
easat-2372	186	18	accuracy	accuracy	NOUN
easat-2372	186	19	but	but	CCONJ
easat-2372	186	20	also	also	ADV
easat-2372	186	21	became	become	VERB
easat-2372	186	22	more	more	ADV
easat-2372	186	23	robust	robust	ADJ
easat-2372	186	24	and	and	CCONJ
easat-2372	186	25	capable	capable	ADJ
easat-2372	186	26	of	of	ADP
easat-2372	186	27	handling	handle	VERB
easat-2372	186	28	diverse	diverse	ADJ
easat-2372	186	29	real	real	ADJ
easat-2372	186	30	-	-	PUNCT
easat-2372	186	31	world	world	NOUN
easat-2372	186	32	data	datum	NOUN
easat-2372	186	33	.	.	PUNCT
easat-2372	187	1	the	the	DET
easat-2372	187	2	successful	successful	ADJ
easat-2372	187	3	application	application	NOUN
easat-2372	187	4	of	of	ADP
easat-2372	187	5	dcgan	dcgan	NOUN
easat-2372	187	6	in	in	ADP
easat-2372	187	7	this	this	DET
easat-2372	187	8	study	study	NOUN
easat-2372	187	9	suggests	suggest	VERB
easat-2372	187	10	that	that	SCONJ
easat-2372	187	11	such	such	ADJ
easat-2372	187	12	synthetic	synthetic	ADJ
easat-2372	187	13	data	data	NOUN
easat-2372	187	14	generation	generation	NOUN
easat-2372	187	15	techniques	technique	NOUN
easat-2372	187	16	could	could	AUX
easat-2372	187	17	play	play	VERB
easat-2372	187	18	a	a	DET
easat-2372	187	19	vital	vital	ADJ
easat-2372	187	20	role	role	NOUN
easat-2372	187	21	in	in	ADP
easat-2372	187	22	improving	improve	VERB
easat-2372	187	23	ai	ai	PROPN
easat-2372	187	24	models	model	NOUN
easat-2372	187	25	'	'	PART
easat-2372	187	26	performance	performance	NOUN
easat-2372	187	27	in	in	ADP
easat-2372	187	28	areas	area	NOUN
easat-2372	187	29	where	where	SCONJ
easat-2372	187	30	data	datum	NOUN
easat-2372	187	31	is	be	AUX
easat-2372	187	32	limited	limited	ADJ
easat-2372	187	33	or	or	CCONJ
easat-2372	187	34	difficult	difficult	ADJ
easat-2372	187	35	to	to	PART
easat-2372	187	36	obtain	obtain	VERB
easat-2372	187	37	.	.	PUNCT
easat-2372	188	1	6	6	X
easat-2372	188	2	.	.	X
easat-2372	188	3	conclusions	conclusion	NOUN
easat-2372	188	4	and	and	CCONJ
easat-2372	188	5	future	future	ADJ
easat-2372	188	6	plans	plan	NOUN
easat-2372	188	7	in	in	ADP
easat-2372	188	8	this	this	DET
easat-2372	188	9	study	study	NOUN
easat-2372	188	10	,	,	PUNCT
easat-2372	188	11	we	we	PRON
easat-2372	188	12	explored	explore	VERB
easat-2372	188	13	the	the	DET
easat-2372	188	14	efficacy	efficacy	NOUN
easat-2372	188	15	of	of	ADP
easat-2372	188	16	employing	employ	VERB
easat-2372	188	17	deep	deep	ADJ
easat-2372	188	18	convolutional	convolutional	ADJ
easat-2372	188	19	generative	generative	ADJ
easat-2372	188	20	adversarial	adversarial	ADJ
easat-2372	188	21	networks	network	NOUN
easat-2372	188	22	(	(	PUNCT
easat-2372	188	23	dcgan	dcgan	NOUN
easat-2372	188	24	)	)	PUNCT
easat-2372	188	25	for	for	ADP
easat-2372	188	26	enhancing	enhance	VERB
easat-2372	188	27	the	the	DET
easat-2372	188	28	accuracy	accuracy	NOUN
easat-2372	188	29	of	of	ADP
easat-2372	188	30	plant	plant	NOUN
easat-2372	188	31	disease	disease	NOUN
easat-2372	188	32	classification	classification	NOUN
easat-2372	188	33	,	,	PUNCT
easat-2372	188	34	specifically	specifically	ADV
easat-2372	188	35	for	for	ADP
easat-2372	188	36	rice	rice	NOUN
easat-2372	188	37	diseases	disease	NOUN
easat-2372	188	38	.	.	PUNCT
easat-2372	189	1	by	by	ADP
easat-2372	189	2	generating	generate	VERB
easat-2372	189	3	synthetic	synthetic	ADJ
easat-2372	189	4	images	image	NOUN
easat-2372	189	5	through	through	ADP
easat-2372	189	6	dcgan	dcgan	NOUN
easat-2372	189	7	,	,	PUNCT
easat-2372	189	8	we	we	PRON
easat-2372	189	9	successfully	successfully	ADV
easat-2372	189	10	augmented	augment	VERB
easat-2372	189	11	the	the	DET
easat-2372	189	12	original	original	ADJ
easat-2372	189	13	dataset	dataset	NOUN
easat-2372	189	14	,	,	PUNCT
easat-2372	189	15	thus	thus	ADV
easat-2372	189	16	significantly	significantly	ADV
easat-2372	189	17	increasing	increase	VERB
easat-2372	189	18	the	the	DET
easat-2372	189	19	total	total	ADJ
easat-2372	189	20	number	number	NOUN
easat-2372	189	21	of	of	ADP
easat-2372	189	22	training	training	NOUN
easat-2372	189	23	samples	sample	NOUN
easat-2372	189	24	.	.	PUNCT
easat-2372	190	1	this	this	DET
easat-2372	190	2	approach	approach	NOUN
easat-2372	190	3	not	not	PART
easat-2372	190	4	only	only	ADV
easat-2372	190	5	addressed	address	VERB
easat-2372	190	6	the	the	DET
easat-2372	190	7	challenge	challenge	NOUN
easat-2372	190	8	of	of	ADP
easat-2372	190	9	limited	limited	ADJ
easat-2372	190	10	data	datum	NOUN
easat-2372	190	11	availability	availability	NOUN
easat-2372	190	12	but	but	CCONJ
easat-2372	190	13	also	also	ADV
easat-2372	190	14	ensured	ensure	VERB
easat-2372	190	15	that	that	SCONJ
easat-2372	190	16	the	the	DET
easat-2372	190	17	newly	newly	ADV
easat-2372	190	18	generated	generate	VERB
easat-2372	190	19	images	image	NOUN
easat-2372	190	20	closely	closely	ADV
easat-2372	190	21	resembled	resemble	VERB
easat-2372	190	22	real	real	ADJ
easat-2372	190	23	-	-	PUNCT
easat-2372	190	24	world	world	NOUN
easat-2372	190	25	data	datum	NOUN
easat-2372	190	26	,	,	PUNCT
easat-2372	190	27	thereby	thereby	ADV
easat-2372	190	28	improving	improve	VERB
easat-2372	190	29	the	the	DET
easat-2372	190	30	generalization	generalization	NOUN
easat-2372	190	31	capabilities	capability	NOUN
easat-2372	190	32	of	of	ADP
easat-2372	190	33	the	the	DET
easat-2372	190	34	cnn	cnn	PROPN
easat-2372	190	35	model	model	NOUN
easat-2372	190	36	.	.	PUNCT
easat-2372	191	1	the	the	DET
easat-2372	191	2	comparative	comparative	ADJ
easat-2372	191	3	analysis	analysis	NOUN
easat-2372	191	4	between	between	ADP
easat-2372	191	5	the	the	DET
easat-2372	191	6	models	model	NOUN
easat-2372	191	7	trained	train	VERB
easat-2372	191	8	with	with	ADP
easat-2372	191	9	and	and	CCONJ
easat-2372	191	10	without	without	ADP
easat-2372	191	11	dcgan	dcgan	NOUN
easat-2372	191	12	-	-	PUNCT
easat-2372	191	13	generated	generate	VERB
easat-2372	191	14	images	image	NOUN
easat-2372	191	15	revealed	reveal	VERB
easat-2372	191	16	a	a	DET
easat-2372	191	17	marked	mark	VERB
easat-2372	191	18	improvement	improvement	NOUN
easat-2372	191	19	in	in	ADP
easat-2372	191	20	classification	classification	NOUN
easat-2372	191	21	accuracy	accuracy	NOUN
easat-2372	191	22	when	when	SCONJ
easat-2372	191	23	synthetic	synthetic	ADJ
easat-2372	191	24	images	image	NOUN
easat-2372	191	25	were	be	AUX
easat-2372	191	26	included	include	VERB
easat-2372	191	27	.	.	PUNCT
easat-2372	192	1	the	the	DET
easat-2372	192	2	augmented	augment	VERB
easat-2372	192	3	dataset	dataset	NOUN
easat-2372	192	4	allowed	allow	VERB
easat-2372	192	5	the	the	DET
easat-2372	192	6	cnn	cnn	PROPN
easat-2372	192	7	to	to	PART
easat-2372	192	8	learn	learn	VERB
easat-2372	192	9	more	more	ADV
easat-2372	192	10	diverse	diverse	ADJ
easat-2372	192	11	features	feature	NOUN
easat-2372	192	12	,	,	PUNCT
easat-2372	192	13	thereby	thereby	ADV
easat-2372	192	14	equipping	equip	VERB
easat-2372	192	15	it	it	PRON
easat-2372	192	16	with	with	ADP
easat-2372	192	17	the	the	DET
easat-2372	192	18	ability	ability	NOUN
easat-2372	192	19	to	to	PART
easat-2372	192	20	recognize	recognize	VERB
easat-2372	192	21	plant	plant	NOUN
easat-2372	192	22	diseases	disease	NOUN
easat-2372	192	23	with	with	ADP
easat-2372	192	24	higher	high	ADJ
easat-2372	192	25	precision	precision	NOUN
easat-2372	192	26	in	in	ADP
easat-2372	192	27	real	real	ADJ
easat-2372	192	28	-	-	PUNCT
easat-2372	192	29	time	time	NOUN
easat-2372	192	30	scenarios	scenario	NOUN
easat-2372	192	31	.	.	PUNCT
easat-2372	193	1	the	the	DET
easat-2372	193	2	stability	stability	NOUN
easat-2372	193	3	of	of	ADP
easat-2372	193	4	training	training	NOUN
easat-2372	193	5	and	and	CCONJ
easat-2372	193	6	validation	validation	NOUN
easat-2372	193	7	loss	loss	NOUN
easat-2372	193	8	metrics	metric	NOUN
easat-2372	193	9	across	across	ADP
easat-2372	193	10	epochs	epoch	NOUN
easat-2372	193	11	further	far	ADV
easat-2372	193	12	validated	validate	VERB
easat-2372	193	13	the	the	DET
easat-2372	193	14	robustness	robustness	NOUN
easat-2372	193	15	of	of	ADP
easat-2372	193	16	the	the	DET
easat-2372	193	17	proposed	propose	VERB
easat-2372	193	18	approach	approach	NOUN
easat-2372	193	19	,	,	PUNCT
easat-2372	193	20	indicating	indicate	VERB
easat-2372	193	21	minimal	minimal	ADJ
easat-2372	193	22	overfitting	overfitting	NOUN
easat-2372	193	23	and	and	CCONJ
easat-2372	193	24	effective	effective	ADJ
easat-2372	193	25	learning	learning	NOUN
easat-2372	193	26	dynamics	dynamic	NOUN
easat-2372	193	27	.	.	PUNCT
easat-2372	194	1	moreover	moreover	ADV
easat-2372	194	2	,	,	PUNCT
easat-2372	194	3	the	the	DET
easat-2372	194	4	evaluation	evaluation	NOUN
easat-2372	194	5	of	of	ADP
easat-2372	194	6	generator	generator	NOUN
easat-2372	194	7	and	and	CCONJ
easat-2372	194	8	discriminator	discriminator	NOUN
easat-2372	194	9	losses	loss	NOUN
easat-2372	194	10	highlighted	highlight	VERB
easat-2372	194	11	the	the	DET
easat-2372	194	12	adaptive	adaptive	ADJ
easat-2372	194	13	learning	learning	NOUN
easat-2372	194	14	process	process	NOUN
easat-2372	194	15	of	of	ADP
easat-2372	194	16	the	the	DET
easat-2372	194	17	dcgan	dcgan	NOUN
easat-2372	194	18	framework	framework	NOUN
easat-2372	194	19	,	,	PUNCT
easat-2372	194	20	where	where	SCONJ
easat-2372	194	21	an	an	DET
easat-2372	194	22	increase	increase	NOUN
easat-2372	194	23	in	in	ADP
easat-2372	194	24	generator	generator	NOUN
easat-2372	194	25	loss	loss	NOUN
easat-2372	194	26	coincided	coincide	VERB
easat-2372	194	27	with	with	ADP
easat-2372	194	28	a	a	DET
easat-2372	194	29	decrease	decrease	NOUN
easat-2372	194	30	in	in	ADP
easat-2372	194	31	discriminator	discriminator	NOUN
easat-2372	194	32	loss	loss	NOUN
easat-2372	194	33	,	,	PUNCT
easat-2372	194	34	stabilizing	stabilize	VERB
easat-2372	194	35	at	at	ADP
easat-2372	194	36	the	the	DET
easat-2372	194	37	1000	1000	NUM
easat-2372	194	38	-	-	PUNCT
easat-2372	194	39	epoch	epoch	NOUN
easat-2372	194	40	mark	mark	NOUN
easat-2372	194	41	.	.	PUNCT
easat-2372	195	1	this	this	DET
easat-2372	195	2	behaviour	behaviour	NOUN
easat-2372	195	3	exemplifies	exemplify	VERB
easat-2372	195	4	the	the	DET
easat-2372	195	5	complementary	complementary	ADJ
easat-2372	195	6	relationship	relationship	NOUN
easat-2372	195	7	between	between	ADP
easat-2372	195	8	the	the	DET
easat-2372	195	9	generator	generator	NOUN
easat-2372	195	10	and	and	CCONJ
easat-2372	195	11	discriminator	discriminator	NOUN
easat-2372	195	12	,	,	PUNCT
easat-2372	195	13	emphasizing	emphasize	VERB
easat-2372	195	14	the	the	DET
easat-2372	195	15	dcgan	dcgan	NOUN
easat-2372	195	16	's	's	PART
easat-2372	195	17	effectiveness	effectiveness	NOUN
easat-2372	195	18	in	in	ADP
easat-2372	195	19	generating	generate	VERB
easat-2372	195	20	high	high	ADJ
easat-2372	195	21	-	-	PUNCT
easat-2372	195	22	quality	quality	NOUN
easat-2372	195	23	synthetic	synthetic	ADJ
easat-2372	195	24	images	image	NOUN
easat-2372	195	25	that	that	PRON
easat-2372	195	26	enhance	enhance	VERB
easat-2372	195	27	model	model	NOUN
easat-2372	195	28	training	training	NOUN
easat-2372	195	29	.	.	PUNCT
easat-2372	196	1	overall	overall	ADV
easat-2372	196	2	,	,	PUNCT
easat-2372	196	3	the	the	DET
easat-2372	196	4	findings	finding	NOUN
easat-2372	196	5	suggest	suggest	VERB
easat-2372	196	6	that	that	SCONJ
easat-2372	196	7	leveraging	leverage	VERB
easat-2372	196	8	dcgan	dcgan	NOUN
easat-2372	196	9	for	for	ADP
easat-2372	196	10	synthetic	synthetic	ADJ
easat-2372	196	11	data	data	NOUN
easat-2372	196	12	generation	generation	NOUN
easat-2372	196	13	is	be	AUX
easat-2372	196	14	a	a	DET
easat-2372	196	15	promising	promising	ADJ
easat-2372	196	16	strategy	strategy	NOUN
easat-2372	196	17	in	in	ADP
easat-2372	196	18	the	the	DET
easat-2372	196	19	field	field	NOUN
easat-2372	196	20	of	of	ADP
easat-2372	196	21	plant	plant	NOUN
easat-2372	196	22	disease	disease	NOUN
easat-2372	196	23	recognition	recognition	NOUN
easat-2372	196	24	.	.	PUNCT
easat-2372	197	1	future	future	ADJ
easat-2372	197	2	research	research	NOUN
easat-2372	197	3	may	may	AUX
easat-2372	197	4	expand	expand	VERB
easat-2372	197	5	upon	upon	SCONJ
easat-2372	197	6	this	this	DET
easat-2372	197	7	foundation	foundation	NOUN
easat-2372	197	8	by	by	ADP
easat-2372	197	9	exploring	explore	VERB
easat-2372	197	10	alternative	alternative	ADJ
easat-2372	197	11	gan	gan	ADJ
easat-2372	197	12	architectures	architecture	NOUN
easat-2372	197	13	and	and	CCONJ
easat-2372	197	14	further	far	ADV
easat-2372	197	15	refining	refine	VERB
easat-2372	197	16	the	the	DET
easat-2372	197	17	generated	generate	VERB
easat-2372	197	18	images	image	NOUN
easat-2372	197	19	to	to	PART
easat-2372	197	20	optimize	optimize	VERB
easat-2372	197	21	classification	classification	NOUN
easat-2372	197	22	outcomes	outcome	NOUN
easat-2372	197	23	.	.	PUNCT
easat-2372	198	1	the	the	DET
easat-2372	198	2	implications	implication	NOUN
easat-2372	198	3	of	of	ADP
easat-2372	198	4	this	this	DET
easat-2372	198	5	study	study	NOUN
easat-2372	198	6	extend	extend	VERB
easat-2372	198	7	beyond	beyond	ADP
easat-2372	198	8	agricultural	agricultural	ADJ
easat-2372	198	9	applications	application	NOUN
easat-2372	198	10	,	,	PUNCT
easat-2372	198	11	potentially	potentially	ADV
easat-2372	198	12	benefiting	benefit	VERB
easat-2372	198	13	various	various	ADJ
easat-2372	198	14	domains	domain	NOUN
easat-2372	198	15	where	where	SCONJ
easat-2372	198	16	data	datum	NOUN
easat-2372	198	17	scarcity	scarcity	NOUN
easat-2372	198	18	hampers	hamper	VERB
easat-2372	198	19	the	the	DET
easat-2372	198	20	performance	performance	NOUN
easat-2372	198	21	of	of	ADP
easat-2372	198	22	machine	machine	NOUN
easat-2372	198	23	learning	learning	NOUN
easat-2372	198	24	models	model	NOUN
easat-2372	198	25	.	.	PUNCT
easat-2372	199	1	copyright	copyright	NOUN
easat-2372	199	2	:	:	PUNCT
easat-2372	199	3	©	©	PROPN
easat-2372	199	4	2024	2024	NUM
easat-2372	199	5	by	by	ADP
easat-2372	199	6	the	the	DET
easat-2372	199	7	authors	author	NOUN
easat-2372	199	8	.	.	PUNCT
easat-2372	200	1	this	this	DET
easat-2372	200	2	article	article	NOUN
easat-2372	200	3	is	be	AUX
easat-2372	200	4	an	an	DET
easat-2372	200	5	open	open	ADJ
easat-2372	200	6	access	access	NOUN
easat-2372	200	7	article	article	NOUN
easat-2372	200	8	distributed	distribute	VERB
easat-2372	200	9	under	under	ADP
easat-2372	200	10	the	the	DET
easat-2372	200	11	terms	term	NOUN
easat-2372	200	12	and	and	CCONJ
easat-2372	200	13	conditions	condition	NOUN
easat-2372	200	14	of	of	ADP
easat-2372	200	15	the	the	DET
easat-2372	200	16	creative	creative	ADJ
easat-2372	200	17	commons	common	NOUN
easat-2372	200	18	attribution	attribution	NOUN
easat-2372	200	19	(	(	PUNCT
easat-2372	200	20	cc	cc	NOUN
easat-2372	200	21	by	by	ADP
easat-2372	200	22	)	)	PUNCT
easat-2372	200	23	license	license	NOUN
easat-2372	200	24	(	(	PUNCT
easat-2372	200	25	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-2372	200	26	)	)	PUNCT
easat-2372	200	27	.	.	PUNCT
easat-2372	201	1	references	reference	NOUN
easat-2372	201	2	[	[	X
easat-2372	201	3	1	1	NUM
easat-2372	201	4	]	]	X
easat-2372	201	5	moshou	moshou	ADJ
easat-2372	201	6	,	,	PUNCT
easat-2372	201	7	dimitrios	dimitrio	NOUN
easat-2372	201	8	,	,	PUNCT
easat-2372	201	9	michael	michael	PROPN
easat-2372	201	10	a.	a.	PROPN
easat-2372	201	11	s.	s.	PROPN
easat-2372	201	12	m.	m.	PROPN
easat-2372	201	13	stamboulis	stamboulis	PROPN
easat-2372	201	14	,	,	PUNCT
easat-2372	201	15	and	and	CCONJ
easat-2372	201	16	peter	peter	PROPN
easat-2372	201	17	d.	d.	PROPN
easat-2372	201	18	k.	k.	PROPN
easat-2372	202	1	p.	p.	PROPN
easat-2372	203	1	c.	c.	PROPN
easat-2372	203	2	p.	p.	PROPN
easat-2372	203	3	g.	g.	PROPN
easat-2372	204	1	m.	m.	NOUN
easat-2372	204	2	a.	a.	NOUN
easat-2372	204	3	"	"	PUNCT
easat-2372	204	4	plant	plant	NOUN
easat-2372	204	5	disease	disease	NOUN
easat-2372	204	6	detection	detection	NOUN
easat-2372	204	7	based	base	VERB
easat-2372	204	8	on	on	ADP
easat-2372	204	9	data	data	NOUN
easat-2372	204	10	fusion	fusion	NOUN
easat-2372	204	11	of	of	ADP
easat-2372	204	12	hyper	hyper	ADJ
easat-2372	204	13	-	-	ADJ
easat-2372	204	14	spectral	spectral	ADJ
easat-2372	204	15	and	and	CCONJ
easat-2372	204	16	multi	multi	ADJ
easat-2372	204	17	-	-	ADJ
easat-2372	204	18	spectral	spectral	ADJ
easat-2372	204	19	fluorescence	fluorescence	NOUN
easat-2372	204	20	imaging	imaging	NOUN
easat-2372	204	21	using	use	VERB
easat-2372	204	22	kohonen	kohonen	PROPN
easat-2372	204	23	maps	map	NOUN
easat-2372	204	24	.	.	PUNCT
easat-2372	204	25	"	"	PUNCT
easat-2372	205	1	real	real	ADJ
easat-2372	205	2	-	-	PUNCT
easat-2372	205	3	time	time	NOUN
easat-2372	205	4	imaging	imaging	NOUN
easat-2372	205	5	11	11	NUM
easat-2372	205	6	,	,	PUNCT
easat-2372	205	7	no	no	INTJ
easat-2372	205	8	.	.	NOUN
easat-2372	205	9	2	2	NUM
easat-2372	205	10	(	(	PUNCT
easat-2372	205	11	2005	2005	NUM
easat-2372	205	12	):	):	PUNCT
easat-2372	205	13	75	75	NUM
easat-2372	205	14	-	-	SYM
easat-2372	205	15	83	83	NUM
easat-2372	205	16	.	.	PUNCT
easat-2372	206	1	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-2372	206	2	2024	2024	NUM
easat-2372	206	3	edelweiss	edelweiss	PROPN
easat-2372	206	4	applied	apply	VERB
easat-2372	206	5	science	science	NOUN
easat-2372	206	6	and	and	CCONJ
easat-2372	206	7	technology	technology	NOUN
easat-2372	206	8	issn	issn	PROPN
easat-2372	206	9	:	:	PUNCT
easat-2372	206	10	2576	2576	NUM
easat-2372	206	11	-	-	SYM
easat-2372	206	12	8484	8484	NUM
easat-2372	206	13	vol	vol	NOUN
easat-2372	206	14	.	.	PROPN
easat-2372	206	15	8	8	NUM
easat-2372	206	16	,	,	PUNCT
easat-2372	206	17	no	no	INTJ
easat-2372	206	18	.	.	NOUN
easat-2372	207	1	6	6	NUM
easat-2372	207	2	:	:	SYM
easat-2372	207	3	2015	2015	NUM
easat-2372	207	4	-	-	SYM
easat-2372	207	5	2024	2024	NUM
easat-2372	207	6	,	,	PUNCT
easat-2372	207	7	2024	2024	NUM
easat-2372	207	8	doi	doi	NOUN
easat-2372	207	9	:	:	PUNCT
easat-2372	207	10	10.55214/25768484.v8i6.2372	10.55214/25768484.v8i6.2372	NUM
easat-2372	207	11	©	©	PROPN
easat-2372	207	12	2024	2024	NUM
easat-2372	207	13	by	by	ADP
easat-2372	207	14	the	the	DET
easat-2372	207	15	authors	author	NOUN
easat-2372	207	16	;	;	PUNCT
easat-2372	207	17	licensee	licensee	PROPN
easat-2372	207	18	learning	learning	NOUN
easat-2372	207	19	gate	gate	NOUN
easat-2372	208	1	[	[	X
easat-2372	208	2	2	2	NUM
easat-2372	208	3	]	]	PUNCT
easat-2372	208	4	phadikar	phadikar	NOUN
easat-2372	208	5	,	,	PUNCT
easat-2372	208	6	santanu	santanu	NOUN
easat-2372	208	7	,	,	PUNCT
easat-2372	208	8	and	and	CCONJ
easat-2372	208	9	jaya	jaya	PROPN
easat-2372	208	10	sil	sil	PROPN
easat-2372	208	11	.	.	PUNCT
easat-2372	209	1	"	"	PUNCT
easat-2372	209	2	rice	rice	NOUN
easat-2372	209	3	disease	disease	NOUN
easat-2372	209	4	identification	identification	NOUN
easat-2372	209	5	using	use	VERB
easat-2372	209	6	pattern	pattern	NOUN
easat-2372	209	7	recognition	recognition	NOUN
easat-2372	209	8	techniques	technique	NOUN
easat-2372	209	9	.	.	PUNCT
easat-2372	209	10	"	"	PUNCT
easat-2372	210	1	in	in	ADP
easat-2372	210	2	proceedings	proceeding	NOUN
easat-2372	210	3	of	of	ADP
easat-2372	210	4	the	the	DET
easat-2372	210	5	2008	2008	NUM
easat-2372	210	6	11th	11th	ADJ
easat-2372	210	7	international	international	ADJ
easat-2372	210	8	conference	conference	NOUN
easat-2372	210	9	on	on	ADP
easat-2372	210	10	computer	computer	NOUN
easat-2372	210	11	and	and	CCONJ
easat-2372	210	12	information	information	NOUN
easat-2372	210	13	technology	technology	NOUN
easat-2372	210	14	,	,	PUNCT
easat-2372	210	15	2008	2008	NUM
easat-2372	210	16	.	.	PUNCT
easat-2372	211	1	[	[	X
easat-2372	211	2	3	3	NUM
easat-2372	211	3	]	]	X
easat-2372	211	4	sanyal	sanyal	NOUN
easat-2372	211	5	,	,	PUNCT
easat-2372	211	6	p.	p.	NOUN
easat-2372	211	7	,	,	PUNCT
easat-2372	211	8	and	and	CCONJ
easat-2372	211	9	s.	s.	PROPN
easat-2372	211	10	c.	c.	PROPN
easat-2372	211	11	patel	patel	PROPN
easat-2372	211	12	.	.	PUNCT
easat-2372	212	1	"	"	PUNCT
easat-2372	212	2	pattern	pattern	NOUN
easat-2372	212	3	recognition	recognition	NOUN
easat-2372	212	4	method	method	NOUN
easat-2372	212	5	to	to	PART
easat-2372	212	6	detect	detect	VERB
easat-2372	212	7	two	two	NUM
easat-2372	212	8	diseases	disease	NOUN
easat-2372	212	9	in	in	ADP
easat-2372	212	10	rice	rice	NOUN
easat-2372	212	11	plants	plant	NOUN
easat-2372	212	12	.	.	PUNCT
easat-2372	212	13	"	"	PUNCT
easat-2372	213	1	the	the	DET
easat-2372	213	2	imaging	imaging	PROPN
easat-2372	213	3	science	science	PROPN
easat-2372	213	4	journal	journal	PROPN
easat-2372	213	5	56	56	NUM
easat-2372	213	6	,	,	PUNCT
easat-2372	213	7	no	no	INTJ
easat-2372	213	8	.	.	NOUN
easat-2372	213	9	6	6	NUM
easat-2372	213	10	(	(	PUNCT
easat-2372	213	11	2008	2008	NUM
easat-2372	213	12	):	):	PUNCT
easat-2372	213	13	319	319	NUM
easat-2372	213	14	-	-	SYM
easat-2372	213	15	325	325	NUM
easat-2372	213	16	.	.	PUNCT
easat-2372	214	1	[	[	X
easat-2372	214	2	4	4	NUM
easat-2372	214	3	]	]	X
easat-2372	214	4	camargo	camargo	PROPN
easat-2372	214	5	,	,	PUNCT
easat-2372	214	6	a.	a.	PROPN
easat-2372	214	7	,	,	PUNCT
easat-2372	214	8	and	and	CCONJ
easat-2372	214	9	j.	j.	PROPN
easat-2372	214	10	s.	s.	PROPN
easat-2372	214	11	smith	smith	PROPN
easat-2372	214	12	.	.	PUNCT
easat-2372	215	1	"	"	PUNCT
easat-2372	215	2	an	an	DET
easat-2372	215	3	image	image	NOUN
easat-2372	215	4	-	-	PUNCT
easat-2372	215	5	processing	processing	NOUN
easat-2372	215	6	based	base	VERB
easat-2372	215	7	algorithm	algorithm	NOUN
easat-2372	215	8	to	to	PART
easat-2372	215	9	automatically	automatically	ADV
easat-2372	215	10	identify	identify	VERB
easat-2372	215	11	plant	plant	NOUN
easat-2372	215	12	disease	disease	NOUN
easat-2372	215	13	visual	visual	ADJ
easat-2372	215	14	symptoms	symptom	NOUN
easat-2372	215	15	.	.	PUNCT
easat-2372	215	16	"	"	PUNCT
easat-2372	216	1	biosystems	biosystem	NOUN
easat-2372	216	2	engineering	engineer	VERB
easat-2372	216	3	102	102	NUM
easat-2372	216	4	,	,	PUNCT
easat-2372	216	5	no	no	INTJ
easat-2372	216	6	.	.	NOUN
easat-2372	216	7	1	1	NUM
easat-2372	216	8	(	(	PUNCT
easat-2372	216	9	2009	2009	NUM
easat-2372	216	10	):	):	PUNCT
easat-2372	216	11	9	9	NUM
easat-2372	216	12	-	-	SYM
easat-2372	216	13	21	21	NUM
easat-2372	216	14	.	.	PUNCT
easat-2372	217	1	[	[	X
easat-2372	217	2	5	5	NUM
easat-2372	217	3	]	]	X
easat-2372	217	4	bashir	bashir	PROPN
easat-2372	217	5	,	,	PUNCT
easat-2372	217	6	sabah	sabah	PROPN
easat-2372	217	7	,	,	PUNCT
easat-2372	217	8	and	and	CCONJ
easat-2372	217	9	navdeep	navdeep	PROPN
easat-2372	217	10	sharma	sharma	PROPN
easat-2372	217	11	.	.	PUNCT
easat-2372	218	1	"	"	PUNCT
easat-2372	218	2	remote	remote	ADJ
easat-2372	218	3	area	area	NOUN
easat-2372	218	4	plant	plant	NOUN
easat-2372	218	5	disease	disease	NOUN
easat-2372	218	6	detection	detection	NOUN
easat-2372	218	7	using	use	VERB
easat-2372	218	8	image	image	NOUN
easat-2372	218	9	processing	processing	NOUN
easat-2372	218	10	.	.	PUNCT
easat-2372	218	11	"	"	PUNCT
easat-2372	219	1	iosr	iosr	ADJ
easat-2372	219	2	journal	journal	NOUN
easat-2372	219	3	of	of	ADP
easat-2372	219	4	electronics	electronic	NOUN
easat-2372	219	5	and	and	CCONJ
easat-2372	219	6	communication	communication	NOUN
easat-2372	219	7	engineering	engineering	NOUN
easat-2372	219	8	2	2	NUM
easat-2372	219	9	,	,	PUNCT
easat-2372	219	10	no	no	INTJ
easat-2372	219	11	.	.	NOUN
easat-2372	219	12	6	6	NUM
easat-2372	219	13	(	(	PUNCT
easat-2372	219	14	2012	2012	NUM
easat-2372	219	15	):	):	PUNCT
easat-2372	219	16	31	31	NUM
easat-2372	219	17	-	-	SYM
easat-2372	219	18	34	34	NUM
easat-2372	219	19	.	.	PUNCT
easat-2372	220	1	[	[	X
easat-2372	220	2	6	6	NUM
easat-2372	220	3	]	]	X
easat-2372	220	4	wang	wang	PROPN
easat-2372	220	5	,	,	PUNCT
easat-2372	220	6	haiguang	haiguang	PROPN
easat-2372	220	7	,	,	PUNCT
easat-2372	220	8	x.	x.	PROPN
easat-2372	220	9	h.	h.	PROPN
easat-2372	220	10	j.	j.	PROPN
easat-2372	220	11	l.	l.	PROPN
easat-2372	220	12	h.	h.	PROPN
easat-2372	220	13	l.	l.	PROPN
easat-2372	220	14	s.	s.	PROPN
easat-2372	220	15	m.	m.	PROPN
easat-2372	220	16	c.	c.	PROPN
easat-2372	220	17	z.	z.	PROPN
easat-2372	220	18	y.	y.	PROPN
easat-2372	220	19	,	,	PUNCT
easat-2372	220	20	and	and	CCONJ
easat-2372	220	21	h.	h.	PROPN
easat-2372	220	22	g.	g.	PROPN
easat-2372	220	23	"	"	PUNCT
easat-2372	220	24	image	image	NOUN
easat-2372	220	25	recognition	recognition	NOUN
easat-2372	220	26	of	of	ADP
easat-2372	220	27	plant	plant	NOUN
easat-2372	220	28	diseases	disease	NOUN
easat-2372	220	29	based	base	VERB
easat-2372	220	30	on	on	ADP
easat-2372	220	31	backpropagation	backpropagation	NOUN
easat-2372	220	32	networks	network	NOUN
easat-2372	220	33	.	.	PUNCT
easat-2372	220	34	"	"	PUNCT
easat-2372	221	1	in	in	ADP
easat-2372	221	2	2012	2012	NUM
easat-2372	221	3	5th	5th	ADJ
easat-2372	221	4	international	international	ADJ
easat-2372	221	5	congress	congress	PROPN
easat-2372	221	6	on	on	ADP
easat-2372	221	7	image	image	NOUN
easat-2372	221	8	and	and	CCONJ
easat-2372	221	9	signal	signal	NOUN
easat-2372	221	10	processing	processing	NOUN
easat-2372	221	11	,	,	PUNCT
easat-2372	221	12	2012	2012	NUM
easat-2372	221	13	.	.	PUNCT
easat-2372	222	1	[	[	X
easat-2372	222	2	7	7	NUM
easat-2372	222	3	]	]	X
easat-2372	222	4	wang	wang	PROPN
easat-2372	222	5	,	,	PUNCT
easat-2372	222	6	haiguang	haiguang	PROPN
easat-2372	222	7	,	,	PUNCT
easat-2372	222	8	and	and	CCONJ
easat-2372	222	9	wang	wang	PROPN
easat-2372	222	10	y.	y.	PROPN
easat-2372	222	11	"	"	PUNCT
easat-2372	222	12	image	image	NOUN
easat-2372	222	13	recognition	recognition	NOUN
easat-2372	222	14	of	of	ADP
easat-2372	222	15	plant	plant	NOUN
easat-2372	222	16	diseases	disease	NOUN
easat-2372	222	17	based	base	VERB
easat-2372	222	18	on	on	ADP
easat-2372	222	19	principal	principal	ADJ
easat-2372	222	20	component	component	NOUN
easat-2372	222	21	analysis	analysis	NOUN
easat-2372	222	22	and	and	CCONJ
easat-2372	222	23	neural	neural	ADJ
easat-2372	222	24	networks	network	NOUN
easat-2372	222	25	.	.	PUNCT
easat-2372	222	26	"	"	PUNCT
easat-2372	223	1	in	in	ADP
easat-2372	223	2	2012	2012	NUM
easat-2372	223	3	8th	8th	ADJ
easat-2372	223	4	international	international	ADJ
easat-2372	223	5	conference	conference	NOUN
easat-2372	223	6	on	on	ADP
easat-2372	223	7	natural	natural	ADJ
easat-2372	223	8	computation	computation	NOUN
easat-2372	223	9	,	,	PUNCT
easat-2372	223	10	2012	2012	NUM
easat-2372	223	11	.	.	PUNCT
easat-2372	224	1	[	[	X
easat-2372	224	2	8	8	NUM
easat-2372	224	3	]	]	X
easat-2372	224	4	phadikar	phadikar	NOUN
easat-2372	224	5	,	,	PUNCT
easat-2372	224	6	santanu	santanu	NOUN
easat-2372	224	7	,	,	PUNCT
easat-2372	224	8	jaya	jaya	PROPN
easat-2372	224	9	sil	sil	PROPN
easat-2372	224	10	,	,	PUNCT
easat-2372	224	11	and	and	CCONJ
easat-2372	224	12	asit	asit	PROPN
easat-2372	224	13	kumar	kumar	PROPN
easat-2372	224	14	das	das	PROPN
easat-2372	224	15	.	.	PUNCT
easat-2372	225	1	"	"	PUNCT
easat-2372	225	2	classification	classification	NOUN
easat-2372	225	3	of	of	ADP
easat-2372	225	4	rice	rice	NOUN
easat-2372	225	5	leaf	leaf	NOUN
easat-2372	225	6	diseases	disease	NOUN
easat-2372	225	7	based	base	VERB
easat-2372	225	8	on	on	ADP
easat-2372	225	9	morphological	morphological	ADJ
easat-2372	225	10	changes	change	NOUN
easat-2372	225	11	.	.	PUNCT
easat-2372	225	12	"	"	PUNCT
easat-2372	226	1	international	international	ADJ
easat-2372	226	2	journal	journal	NOUN
easat-2372	226	3	of	of	ADP
easat-2372	226	4	information	information	NOUN
easat-2372	226	5	and	and	CCONJ
easat-2372	226	6	electronics	electronic	NOUN
easat-2372	226	7	engineering	engineering	NOUN
easat-2372	226	8	2	2	NUM
easat-2372	226	9	,	,	PUNCT
easat-2372	226	10	no	no	INTJ
easat-2372	226	11	.	.	NOUN
easat-2372	226	12	3	3	NUM
easat-2372	226	13	(	(	PUNCT
easat-2372	226	14	2012	2012	NUM
easat-2372	226	15	):	):	PUNCT
easat-2372	226	16	460	460	NUM
easat-2372	226	17	-	-	SYM
easat-2372	226	18	463	463	NUM
easat-2372	226	19	.	.	PUNCT
easat-2372	227	1	[	[	X
easat-2372	227	2	9	9	NUM
easat-2372	227	3	]	]	X
easat-2372	227	4	sanyal	sanyal	NOUN
easat-2372	227	5	,	,	PUNCT
easat-2372	227	6	p.	p.	NOUN
easat-2372	227	7	,	,	PUNCT
easat-2372	227	8	and	and	CCONJ
easat-2372	227	9	s.	s.	PROPN
easat-2372	227	10	c.	c.	PROPN
easat-2372	227	11	patel	patel	PROPN
easat-2372	227	12	.	.	PUNCT
easat-2372	228	1	"	"	PUNCT
easat-2372	228	2	pattern	pattern	NOUN
easat-2372	228	3	recognition	recognition	NOUN
easat-2372	228	4	method	method	NOUN
easat-2372	228	5	to	to	PART
easat-2372	228	6	detect	detect	VERB
easat-2372	228	7	two	two	NUM
easat-2372	228	8	diseases	disease	NOUN
easat-2372	228	9	in	in	ADP
easat-2372	228	10	rice	rice	NOUN
easat-2372	228	11	plants	plant	NOUN
easat-2372	228	12	.	.	PUNCT
easat-2372	228	13	"	"	PUNCT
easat-2372	229	1	the	the	DET
easat-2372	229	2	imaging	imaging	PROPN
easat-2372	229	3	science	science	PROPN
easat-2372	229	4	journal	journal	PROPN
easat-2372	229	5	56.6	56.6	NUM
easat-2372	229	6	(	(	PUNCT
easat-2372	229	7	2008	2008	NUM
easat-2372	229	8	):	):	PUNCT
easat-2372	229	9	319	319	NUM
easat-2372	229	10	-	-	SYM
easat-2372	229	11	325	325	NUM
easat-2372	229	12	.	.	PUNCT
easat-2372	230	1	[	[	X
easat-2372	230	2	10	10	NUM
easat-2372	230	3	]	]	X
easat-2372	230	4	camargo	camargo	PROPN
easat-2372	230	5	,	,	PUNCT
easat-2372	230	6	a.	a.	PROPN
easat-2372	230	7	,	,	PUNCT
easat-2372	230	8	and	and	CCONJ
easat-2372	230	9	j.	j.	PROPN
easat-2372	230	10	s.	s.	PROPN
easat-2372	230	11	smith	smith	PROPN
easat-2372	230	12	.	.	PUNCT
easat-2372	231	1	"	"	PUNCT
easat-2372	231	2	image	image	NOUN
easat-2372	231	3	pattern	pattern	NOUN
easat-2372	231	4	classification	classification	NOUN
easat-2372	231	5	for	for	ADP
easat-2372	231	6	the	the	DET
easat-2372	231	7	identification	identification	NOUN
easat-2372	231	8	of	of	ADP
easat-2372	231	9	disease	disease	NOUN
easat-2372	231	10	-	-	PUNCT
easat-2372	231	11	causing	cause	VERB
easat-2372	231	12	agents	agent	NOUN
easat-2372	231	13	in	in	ADP
easat-2372	231	14	plants	plant	NOUN
easat-2372	231	15	.	.	PUNCT
easat-2372	231	16	"	"	PUNCT
easat-2372	232	1	computers	computer	NOUN
easat-2372	232	2	and	and	CCONJ
easat-2372	232	3	electronics	electronic	NOUN
easat-2372	232	4	in	in	ADP
easat-2372	232	5	agriculture	agriculture	NOUN
easat-2372	232	6	66	66	NUM
easat-2372	232	7	,	,	PUNCT
easat-2372	232	8	no	no	INTJ
easat-2372	232	9	.	.	NOUN
easat-2372	232	10	2	2	NUM
easat-2372	232	11	(	(	PUNCT
easat-2372	232	12	2009	2009	NUM
easat-2372	232	13	):	):	PUNCT
easat-2372	232	14	121	121	NUM
easat-2372	232	15	-	-	SYM
easat-2372	232	16	125	125	NUM
easat-2372	232	17	.	.	PUNCT
easat-2372	233	1	[	[	X
easat-2372	233	2	11	11	NUM
easat-2372	233	3	]	]	X
easat-2372	233	4	al	al	PROPN
easat-2372	233	5	-	-	PUNCT
easat-2372	233	6	hiary	hiary	PROPN
easat-2372	233	7	,	,	PUNCT
easat-2372	233	8	heba	heba	PROPN
easat-2372	233	9	,	,	PUNCT
easat-2372	233	10	r.	r.	PROPN
easat-2372	233	11	a.	a.	PROPN
easat-2372	233	12	a.	a.	PROPN
easat-2372	233	13	al	al	PROPN
easat-2372	233	14	-	-	PUNCT
easat-2372	233	15	omari	omari	PROPN
easat-2372	233	16	,	,	PUNCT
easat-2372	233	17	o.	o.	PROPN
easat-2372	233	18	h.	h.	PROPN
easat-2372	233	19	k.	k.	PROPN
easat-2372	233	20	a.	a.	PROPN
easat-2372	233	21	h.	h.	PROPN
easat-2372	233	22	h.	h.	PROPN
easat-2372	233	23	j.	j.	PROPN
easat-2372	233	24	o.	o.	PROPN
easat-2372	233	25	m.	m.	PROPN
easat-2372	233	26	a.	a.	PROPN
easat-2372	233	27	,	,	PUNCT
easat-2372	233	28	and	and	CCONJ
easat-2372	233	29	t.	t.	PROPN
easat-2372	233	30	j.	j.	PROPN
easat-2372	233	31	o.	o.	PROPN
easat-2372	233	32	a.	a.	PROPN
easat-2372	233	33	a.	a.	PROPN
easat-2372	233	34	h.	h.	PROPN
easat-2372	233	35	"	"	PUNCT
easat-2372	233	36	fast	fast	ADJ
easat-2372	233	37	and	and	CCONJ
easat-2372	233	38	accurate	accurate	ADJ
easat-2372	233	39	detection	detection	NOUN
easat-2372	233	40	and	and	CCONJ
easat-2372	233	41	classification	classification	NOUN
easat-2372	233	42	of	of	ADP
easat-2372	233	43	plant	plant	NOUN
easat-2372	233	44	diseases	disease	NOUN
easat-2372	233	45	.	.	PUNCT
easat-2372	233	46	"	"	PUNCT
easat-2372	234	1	international	international	ADJ
easat-2372	234	2	journal	journal	NOUN
easat-2372	234	3	of	of	ADP
easat-2372	234	4	computer	computer	NOUN
easat-2372	234	5	applications	application	NOUN
easat-2372	234	6	17	17	NUM
easat-2372	234	7	,	,	PUNCT
easat-2372	234	8	no	no	INTJ
easat-2372	234	9	.	.	NOUN
easat-2372	234	10	1	1	NUM
easat-2372	234	11	(	(	PUNCT
easat-2372	234	12	2011	2011	NUM
easat-2372	234	13	):	):	PUNCT
easat-2372	234	14	31	31	NUM
easat-2372	234	15	-	-	SYM
easat-2372	234	16	38	38	NUM
easat-2372	234	17	.	.	PUNCT
easat-2372	235	1	[	[	X
easat-2372	235	2	12	12	NUM
easat-2372	235	3	]	]	X
easat-2372	235	4	bashir	bashir	PROPN
easat-2372	235	5	,	,	PUNCT
easat-2372	235	6	sabah	sabah	PROPN
easat-2372	235	7	,	,	PUNCT
easat-2372	235	8	and	and	CCONJ
easat-2372	235	9	navdeep	navdeep	PROPN
easat-2372	235	10	sharma	sharma	PROPN
easat-2372	235	11	.	.	PUNCT
easat-2372	236	1	"	"	PUNCT
easat-2372	236	2	remote	remote	ADJ
easat-2372	236	3	area	area	NOUN
easat-2372	236	4	plant	plant	NOUN
easat-2372	236	5	disease	disease	NOUN
easat-2372	236	6	detection	detection	NOUN
easat-2372	236	7	using	use	VERB
easat-2372	236	8	image	image	NOUN
easat-2372	236	9	processing	processing	NOUN
easat-2372	236	10	.	.	PUNCT
easat-2372	236	11	"	"	PUNCT
easat-2372	237	1	iosr	iosr	ADJ
easat-2372	237	2	journal	journal	NOUN
easat-2372	237	3	of	of	ADP
easat-2372	237	4	electronics	electronic	NOUN
easat-2372	237	5	and	and	CCONJ
easat-2372	237	6	communication	communication	NOUN
easat-2372	237	7	engineering	engineering	NOUN
easat-2372	237	8	2.6	2.6	NUM
easat-2372	237	9	(	(	PUNCT
easat-2372	237	10	2012	2012	NUM
easat-2372	237	11	):	):	PUNCT
easat-2372	237	12	31	31	NUM
easat-2372	237	13	-	-	SYM
easat-2372	237	14	34	34	NUM
easat-2372	237	15	.	.	PUNCT
easat-2372	238	1	[	[	X
easat-2372	238	2	13	13	NUM
easat-2372	238	3	]	]	X
easat-2372	238	4	neumann	neumann	PROPN
easat-2372	238	5	,	,	PUNCT
easat-2372	238	6	marion	marion	PROPN
easat-2372	238	7	,	,	PUNCT
easat-2372	238	8	et	et	PROPN
easat-2372	238	9	al	al	PROPN
easat-2372	238	10	.	.	PUNCT
easat-2372	238	11	"	"	PUNCT
easat-2372	238	12	erosion	erosion	NOUN
easat-2372	238	13	band	band	NOUN
easat-2372	238	14	features	feature	NOUN
easat-2372	238	15	for	for	ADP
easat-2372	238	16	cell	cell	NOUN
easat-2372	238	17	phone	phone	NOUN
easat-2372	238	18	image	image	NOUN
easat-2372	238	19	based	base	VERB
easat-2372	238	20	plant	plant	NOUN
easat-2372	238	21	disease	disease	NOUN
easat-2372	238	22	classification	classification	NOUN
easat-2372	238	23	.	.	PUNCT
easat-2372	238	24	"	"	PUNCT
easat-2372	239	1	in	in	ADP
easat-2372	239	2	2014	2014	NUM
easat-2372	239	3	22nd	22nd	NOUN
easat-2372	239	4	international	international	ADJ
easat-2372	239	5	conference	conference	NOUN
easat-2372	239	6	on	on	ADP
easat-2372	239	7	pattern	pattern	NOUN
easat-2372	239	8	recognition	recognition	NOUN
easat-2372	239	9	,	,	PUNCT
easat-2372	239	10	2014	2014	NUM
easat-2372	239	11	.	.	PUNCT
easat-2372	240	1	[	[	X
easat-2372	240	2	14	14	NUM
easat-2372	240	3	]	]	X
easat-2372	240	4	khirade	khirade	NOUN
easat-2372	240	5	,	,	PUNCT
easat-2372	240	6	sachin	sachin	PROPN
easat-2372	240	7	d.	d.	PROPN
easat-2372	240	8	,	,	PUNCT
easat-2372	240	9	and	and	CCONJ
easat-2372	240	10	a.	a.	PROPN
easat-2372	240	11	b.	b.	PROPN
easat-2372	240	12	patil	patil	PROPN
easat-2372	240	13	.	.	PUNCT
easat-2372	241	1	"	"	PUNCT
easat-2372	241	2	plant	plant	NOUN
easat-2372	241	3	disease	disease	NOUN
easat-2372	241	4	detection	detection	NOUN
easat-2372	241	5	using	use	VERB
easat-2372	241	6	image	image	NOUN
easat-2372	241	7	processing	processing	NOUN
easat-2372	241	8	.	.	PUNCT
easat-2372	241	9	"	"	PUNCT
easat-2372	242	1	in	in	ADP
easat-2372	242	2	2015	2015	NUM
easat-2372	242	3	international	international	ADJ
easat-2372	242	4	conference	conference	NOUN
easat-2372	242	5	on	on	ADP
easat-2372	242	6	computing	compute	VERB
easat-2372	242	7	communication	communication	NOUN
easat-2372	242	8	control	control	NOUN
easat-2372	242	9	and	and	CCONJ
easat-2372	242	10	automation	automation	NOUN
easat-2372	242	11	,	,	PUNCT
easat-2372	242	12	2015	2015	NUM
easat-2372	242	13	.	.	PUNCT
easat-2372	243	1	[	[	X
easat-2372	243	2	15	15	NUM
easat-2372	243	3	]	]	PUNCT
easat-2372	243	4	mohanty	mohanty	NOUN
easat-2372	243	5	,	,	PUNCT
easat-2372	243	6	sharada	sharada	PROPN
easat-2372	243	7	p.	p.	PROPN
easat-2372	243	8	,	,	PUNCT
easat-2372	243	9	david	david	PROPN
easat-2372	243	10	p.	p.	PROPN
easat-2372	243	11	hughes	hughes	PROPN
easat-2372	243	12	,	,	PUNCT
easat-2372	243	13	and	and	CCONJ
easat-2372	243	14	marcel	marcel	PROPN
easat-2372	243	15	salathé	salathé	PROPN
easat-2372	243	16	.	.	PUNCT
easat-2372	244	1	"	"	PUNCT
easat-2372	244	2	using	use	VERB
easat-2372	244	3	deep	deep	ADJ
easat-2372	244	4	learning	learning	NOUN
easat-2372	244	5	for	for	ADP
easat-2372	244	6	image	image	NOUN
easat-2372	244	7	-	-	PUNCT
easat-2372	244	8	based	base	VERB
easat-2372	244	9	plant	plant	NOUN
easat-2372	244	10	disease	disease	NOUN
easat-2372	244	11	detection	detection	NOUN
easat-2372	244	12	.	.	PUNCT
easat-2372	244	13	"	"	PUNCT
easat-2372	244	14	frontiers	frontier	NOUN
easat-2372	244	15	in	in	ADP
easat-2372	244	16	plant	plant	NOUN
easat-2372	244	17	science	science	NOUN
easat-2372	244	18	7	7	NUM
easat-2372	244	19	(	(	PUNCT
easat-2372	244	20	2016	2016	NUM
easat-2372	244	21	):	):	PUNCT
easat-2372	244	22	1419	1419	NUM
easat-2372	244	23	.	.	PUNCT
easat-2372	245	1	[	[	X
easat-2372	245	2	16	16	NUM
easat-2372	245	3	]	]	X
easat-2372	245	4	sladojevic	sladojevic	PROPN
easat-2372	245	5	,	,	PUNCT
easat-2372	245	6	srdjan	srdjan	NOUN
easat-2372	245	7	,	,	PUNCT
easat-2372	245	8	et	et	PROPN
easat-2372	245	9	al	al	PROPN
easat-2372	245	10	.	.	PUNCT
easat-2372	246	1	"	"	PUNCT
easat-2372	246	2	deep	deep	ADJ
easat-2372	246	3	neural	neural	ADJ
easat-2372	246	4	networks	network	NOUN
easat-2372	246	5	based	base	VERB
easat-2372	246	6	recognition	recognition	NOUN
easat-2372	246	7	of	of	ADP
easat-2372	246	8	plant	plant	NOUN
easat-2372	246	9	diseases	disease	NOUN
easat-2372	246	10	by	by	ADP
easat-2372	246	11	leaf	leaf	NOUN
easat-2372	246	12	image	image	NOUN
easat-2372	246	13	classification	classification	NOUN
easat-2372	246	14	.	.	PUNCT
easat-2372	246	15	"	"	PUNCT
easat-2372	247	1	computational	computational	ADJ
easat-2372	247	2	intelligence	intelligence	NOUN
easat-2372	247	3	and	and	CCONJ
easat-2372	247	4	neuroscience	neuroscience	NOUN
easat-2372	247	5	(	(	PUNCT
easat-2372	247	6	2016	2016	NUM
easat-2372	247	7	)	)	PUNCT
easat-2372	247	8	.	.	PUNCT
easat-2372	248	1	[	[	X
easat-2372	248	2	17	17	NUM
easat-2372	248	3	]	]	X
easat-2372	248	4	grinblat	grinblat	PROPN
easat-2372	248	5	,	,	PUNCT
easat-2372	248	6	guillermo	guillermo	PROPN
easat-2372	248	7	l.	l.	PROPN
easat-2372	248	8	,	,	PUNCT
easat-2372	248	9	et	et	PROPN
easat-2372	248	10	al	al	PROPN
easat-2372	248	11	.	.	PUNCT
easat-2372	249	1	"	"	PUNCT
easat-2372	249	2	deep	deep	ADJ
easat-2372	249	3	learning	learning	NOUN
easat-2372	249	4	for	for	ADP
easat-2372	249	5	plant	plant	NOUN
easat-2372	249	6	identification	identification	NOUN
easat-2372	249	7	using	use	VERB
easat-2372	249	8	vein	vein	ADJ
easat-2372	249	9	morphological	morphological	ADJ
easat-2372	249	10	patterns	pattern	NOUN
easat-2372	249	11	.	.	PUNCT
easat-2372	249	12	"	"	PUNCT
easat-2372	250	1	computers	computer	NOUN
easat-2372	250	2	and	and	CCONJ
easat-2372	250	3	electronics	electronic	NOUN
easat-2372	250	4	in	in	ADP
easat-2372	250	5	agriculture	agriculture	NOUN
easat-2372	250	6	127	127	NUM
easat-2372	250	7	(	(	PUNCT
easat-2372	250	8	2016	2016	NUM
easat-2372	250	9	):	):	PUNCT
easat-2372	250	10	418	418	NUM
easat-2372	250	11	-	-	SYM
easat-2372	250	12	424	424	NUM
easat-2372	250	13	.	.	PUNCT
easat-2372	251	1	[	[	X
easat-2372	251	2	18	18	NUM
easat-2372	251	3	]	]	PUNCT
easat-2372	251	4	barbedo	barbedo	NOUN
easat-2372	251	5	,	,	PUNCT
easat-2372	251	6	jayme	jayme	NOUN
easat-2372	251	7	garcia	garcia	PROPN
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easat-2372	251	9	,	,	PUNCT
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easat-2372	251	12	koenigkan	koenigkan	PROPN
easat-2372	251	13	,	,	PUNCT
easat-2372	251	14	and	and	CCONJ
easat-2372	251	15	thiago	thiago	PROPN
easat-2372	251	16	teixeira	teixeira	PROPN
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easat-2372	251	18	.	.	PUNCT
easat-2372	252	1	"	"	PUNCT
easat-2372	252	2	identifying	identify	VERB
easat-2372	252	3	multiple	multiple	ADJ
easat-2372	252	4	plant	plant	NOUN
easat-2372	252	5	diseases	disease	NOUN
easat-2372	252	6	using	use	VERB
easat-2372	252	7	digital	digital	ADJ
easat-2372	252	8	image	image	NOUN
easat-2372	252	9	processing	processing	NOUN
easat-2372	252	10	.	.	PUNCT
easat-2372	252	11	"	"	PUNCT
easat-2372	253	1	biosystems	biosystems	PROPN
easat-2372	253	2	engineering	engineer	VERB
easat-2372	253	3	147	147	NUM
easat-2372	253	4	(	(	PUNCT
easat-2372	253	5	2016	2016	NUM
easat-2372	253	6	):	):	PUNCT
easat-2372	253	7	104	104	NUM
easat-2372	253	8	-	-	SYM
easat-2372	253	9	116	116	NUM
easat-2372	253	10	.	.	PUNCT
easat-2372	254	1	[	[	X
easat-2372	254	2	19	19	NUM
easat-2372	254	3	]	]	X
easat-2372	254	4	fuentes	fuentes	PROPN
easat-2372	254	5	,	,	PUNCT
easat-2372	254	6	alvaro	alvaro	PROPN
easat-2372	254	7	,	,	PUNCT
easat-2372	254	8	et	et	PROPN
easat-2372	254	9	al	al	PROPN
easat-2372	254	10	.	.	PUNCT
easat-2372	255	1	"	"	PUNCT
easat-2372	255	2	a	a	DET
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easat-2372	255	4	deep	deep	ADJ
easat-2372	255	5	-	-	PUNCT
easat-2372	255	6	learning	learning	NOUN
easat-2372	255	7	-	-	PUNCT
easat-2372	255	8	based	base	VERB
easat-2372	255	9	detector	detector	NOUN
easat-2372	255	10	for	for	ADP
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easat-2372	255	12	-	-	PUNCT
easat-2372	255	13	time	time	NOUN
easat-2372	255	14	tomato	tomato	NOUN
easat-2372	255	15	plant	plant	NOUN
easat-2372	255	16	diseases	disease	NOUN
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easat-2372	255	19	recognition	recognition	NOUN
easat-2372	255	20	.	.	PUNCT
easat-2372	255	21	"	"	PUNCT
easat-2372	256	1	sensors	sensor	NOUN
easat-2372	256	2	17	17	NUM
easat-2372	256	3	,	,	PUNCT
easat-2372	256	4	no	no	INTJ
easat-2372	256	5	.	.	NOUN
easat-2372	256	6	9	9	NUM
easat-2372	256	7	(	(	PUNCT
easat-2372	256	8	2017	2017	NUM
easat-2372	256	9	):	):	PUNCT
easat-2372	256	10	2022	2022	NUM
easat-2372	256	11	.	.	PUNCT
easat-2372	257	1	[	[	X
easat-2372	257	2	20	20	NUM
easat-2372	257	3	]	]	X
easat-2372	257	4	sethy	sethy	ADJ
easat-2372	257	5	,	,	PUNCT
easat-2372	257	6	prabira	prabira	PROPN
easat-2372	257	7	kumar	kumar	PROPN
easat-2372	257	8	.	.	PUNCT
easat-2372	258	1	“	"	PUNCT
easat-2372	258	2	rice	rice	NOUN
easat-2372	258	3	leaf	leaf	NOUN
easat-2372	258	4	disease	disease	NOUN
easat-2372	258	5	image	image	NOUN
easat-2372	258	6	samples	sample	NOUN
easat-2372	258	7	.	.	PUNCT
easat-2372	258	8	”	"	PUNCT
easat-2372	259	1	mendeley	mendeley	PROPN
easat-2372	259	2	data	data	PROPN
easat-2372	259	3	,	,	PUNCT
easat-2372	259	4	v1	v1	PROPN
easat-2372	259	5	(	(	PUNCT
easat-2372	259	6	2020	2020	NUM
easat-2372	259	7	)	)	PUNCT
easat-2372	259	8	.	.	PUNCT
easat-2372	260	1	doi:10.17632	doi:10.17632	PROPN
easat-2372	260	2	/	/	SYM
easat-2372	260	3	fwcj7stb8r.1	fwcj7stb8r.1	PROPN
easat-2372	260	4	.	.	PUNCT
easat-2372	261	1	[	[	X
easat-2372	261	2	21	21	NUM
easat-2372	261	3	]	]	SYM
easat-2372	261	4	laddha	laddha	ADJ
easat-2372	261	5	,	,	PUNCT
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easat-2372	261	7	,	,	PUNCT
easat-2372	261	8	and	and	CCONJ
easat-2372	261	9	vijay	vijay	PROPN
easat-2372	261	10	kumar	kumar	PROPN
easat-2372	261	11	.	.	PUNCT
easat-2372	262	1	"	"	PUNCT
easat-2372	262	2	dgcnn	dgcnn	ADJ
easat-2372	262	3	:	:	PUNCT
easat-2372	262	4	deep	deep	ADJ
easat-2372	262	5	convolutional	convolutional	ADJ
easat-2372	262	6	generative	generative	ADJ
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easat-2372	262	8	network	network	NOUN
easat-2372	262	9	based	base	VERB
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easat-2372	262	13	for	for	ADP
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easat-2372	262	16	covid-19	covid-19	PROPN
easat-2372	262	17	.	.	PUNCT
easat-2372	262	18	"	"	PUNCT
easat-2372	262	19	multimedia	multimedia	NOUN
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easat-2372	262	21	and	and	CCONJ
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easat-2372	262	23	(	(	PUNCT
easat-2372	262	24	2022	2022	NUM
easat-2372	262	25	)	)	PUNCT
easat-2372	262	26	.	.	PUNCT
easat-2372	263	1	[	[	X
easat-2372	263	2	22	22	NUM
easat-2372	263	3	]	]	X
easat-2372	263	4	goodfellow	goodfellow	PROPN
easat-2372	263	5	,	,	PUNCT
easat-2372	263	6	ian	ian	PROPN
easat-2372	263	7	,	,	PUNCT
easat-2372	263	8	et	et	PROPN
easat-2372	263	9	al	al	PROPN
easat-2372	263	10	.	.	PUNCT
easat-2372	264	1	"	"	PUNCT
easat-2372	264	2	generative	generative	ADJ
easat-2372	264	3	adversarial	adversarial	ADJ
easat-2372	264	4	nets	net	NOUN
easat-2372	264	5	.	.	PUNCT
easat-2372	264	6	"	"	PUNCT
easat-2372	265	1	in	in	ADP
easat-2372	265	2	advances	advance	NOUN
easat-2372	265	3	in	in	ADP
easat-2372	265	4	neural	neural	ADJ
easat-2372	265	5	information	information	NOUN
easat-2372	265	6	processing	processing	NOUN
easat-2372	265	7	systems	system	NOUN
easat-2372	265	8	,	,	PUNCT
easat-2372	265	9	27	27	NUM
easat-2372	265	10	(	(	PUNCT
easat-2372	265	11	2014	2014	NUM
easat-2372	265	12	)	)	PUNCT
easat-2372	265	13	.	.	PUNCT
easat-2372	266	1	[	[	X
easat-2372	266	2	23	23	NUM
easat-2372	266	3	]	]	SYM
easat-2372	266	4	o'shea	o'shea	PROPN
easat-2372	266	5	,	,	PUNCT
easat-2372	266	6	keiron	keiron	NOUN
easat-2372	266	7	,	,	PUNCT
easat-2372	266	8	and	and	CCONJ
easat-2372	266	9	ryan	ryan	PROPN
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easat-2372	266	11	.	.	PUNCT
easat-2372	267	1	"	"	PUNCT
easat-2372	267	2	an	an	DET
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easat-2372	267	4	to	to	ADP
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easat-2372	267	7	networks	network	NOUN
easat-2372	267	8	.	.	PUNCT
easat-2372	267	9	"	"	PUNCT
easat-2372	268	1	arxiv	arxiv	PROPN
easat-2372	268	2	preprint	preprint	NOUN
easat-2372	268	3	(	(	PUNCT
easat-2372	268	4	2015	2015	NUM
easat-2372	268	5	):	):	PUNCT
easat-2372	268	6	arxiv:1511.08458	arxiv:1511.08458	NUM
easat-2372	268	7	.	.	PUNCT
easat-2372	269	1	[	[	X
easat-2372	269	2	24	24	NUM
easat-2372	269	3	]	]	SYM
easat-2372	269	4	lu	lu	PROPN
easat-2372	269	5	,	,	PUNCT
easat-2372	269	6	yang	yang	PROPN
easat-2372	269	7	,	,	PUNCT
easat-2372	269	8	et	et	PROPN
easat-2372	269	9	al	al	PROPN
easat-2372	269	10	.	.	PUNCT
easat-2372	270	1	"	"	PUNCT
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easat-2372	270	8	convolutional	convolutional	ADJ
easat-2372	270	9	neural	neural	ADJ
easat-2372	270	10	networks	network	NOUN
easat-2372	270	11	.	.	PUNCT
easat-2372	270	12	"	"	PUNCT
easat-2372	271	1	neurocomputing	neurocompute	VERB
easat-2372	271	2	267	267	NUM
easat-2372	271	3	(	(	PUNCT
easat-2372	271	4	2017	2017	NUM
easat-2372	271	5	):	):	PUNCT
easat-2372	271	6	378	378	NUM
easat-2372	271	7	-	-	SYM
easat-2372	271	8	384	384	NUM
easat-2372	271	9	.	.	PUNCT