id	sid	tid	token	lemma	pos
cana-5212	1	1	communications	communication	NOUN
cana-5212	1	2	on	on	ADP
cana-5212	1	3	applied	apply	VERB
cana-5212	1	4	nonlinear	nonlinear	ADJ
cana-5212	1	5	analysis	analysis	NOUN
cana-5212	1	6	issn	issn	NOUN
cana-5212	1	7	:	:	PUNCT
cana-5212	1	8	1074	1074	NUM
cana-5212	1	9	-	-	PUNCT
cana-5212	1	10	133x	133x	NUM
cana-5212	1	11	vol	vol	NOUN
cana-5212	1	12	32	32	NUM
cana-5212	1	13	no	no	NOUN
cana-5212	1	14	.	.	PUNCT
cana-5212	2	1	8s	8s	PROPN
cana-5212	2	2	(	(	PUNCT
cana-5212	2	3	2025	2025	NUM
cana-5212	2	4	)	)	PUNCT
cana-5212	2	5	933	933	NUM
cana-5212	3	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	3	2	intelligent	intelligent	ADJ
cana-5212	3	3	leaf	leaf	NOUN
cana-5212	3	4	disease	disease	NOUN
cana-5212	3	5	diagnosis	diagnosis	NOUN
cana-5212	3	6	:	:	PUNCT
cana-5212	3	7	fuzzy	fuzzy	ADJ
cana-5212	3	8	logic	logic	NOUN
cana-5212	3	9	and	and	CCONJ
cana-5212	3	10	cnn	cnn	PROPN
cana-5212	3	11	-	-	PUNCT
cana-5212	3	12	based	base	VERB
cana-5212	3	13	multi	multi	ADJ
cana-5212	3	14	-	-	ADJ
cana-5212	3	15	class	class	ADJ
cana-5212	3	16	detection	detection	NOUN
cana-5212	3	17	preeti	preeti	PROPN
cana-5212	3	18	yadav1,parvinder	yadav1,parvinder	PUNCT
cana-5212	4	1	singh2	singh2	PROPN
cana-5212	4	2	department	department	NOUN
cana-5212	4	3	of	of	ADP
cana-5212	4	4	computer	computer	PROPN
cana-5212	4	5	science	science	PROPN
cana-5212	4	6	&	&	CCONJ
cana-5212	4	7	technology	technology	PROPN
cana-5212	4	8	,	,	PUNCT
cana-5212	4	9	dcrust	dcrust	ADJ
cana-5212	4	10	murthal	murthal	NOUN
cana-5212	4	11	,	,	PUNCT
cana-5212	4	12	sonepat	sonepat	NOUN
cana-5212	4	13	,	,	PUNCT
cana-5212	4	14	india-131027	india-131027	ADV
cana-5212	4	15	preeti.schcse@dcrustm.org	preeti.schcse@dcrustm.org	X
cana-5212	4	16	,	,	PUNCT
cana-5212	4	17	parvindersingh@dcrsutm.org	parvindersingh@dcrsutm.org	PROPN
cana-5212	4	18	article	article	NOUN
cana-5212	4	19	history	history	NOUN
cana-5212	4	20	:	:	PUNCT
cana-5212	4	21	received	receive	VERB
cana-5212	4	22	:	:	PUNCT
cana-5212	4	23	07	07	NUM
cana-5212	4	24	-	-	PUNCT
cana-5212	4	25	01	01	NUM
cana-5212	4	26	-	-	PUNCT
cana-5212	4	27	2025	2025	NUM
cana-5212	4	28	revised	revise	VERB
cana-5212	4	29	:	:	PUNCT
cana-5212	4	30	25	25	NUM
cana-5212	4	31	-	-	PUNCT
cana-5212	4	32	01	01	NUM
cana-5212	4	33	-	-	PUNCT
cana-5212	4	34	2025	2025	NUM
cana-5212	4	35	accepted	accept	VERB
cana-5212	4	36	:	:	PUNCT
cana-5212	4	37	23	23	NUM
cana-5212	4	38	-	-	SYM
cana-5212	4	39	02	02	NUM
cana-5212	4	40	-	-	PUNCT
cana-5212	4	41	2025	2025	NUM
cana-5212	4	42	abstract	abstract	NOUN
cana-5212	4	43	:	:	PUNCT
cana-5212	4	44	introduction	introduction	NOUN
cana-5212	4	45	:	:	PUNCT
cana-5212	4	46	this	this	DET
cana-5212	4	47	paper	paper	NOUN
cana-5212	4	48	presents	present	VERB
cana-5212	4	49	an	an	DET
cana-5212	4	50	approach	approach	NOUN
cana-5212	4	51	for	for	ADP
cana-5212	4	52	identifying	identify	VERB
cana-5212	4	53	and	and	CCONJ
cana-5212	4	54	classifying	classify	VERB
cana-5212	4	55	plant	plant	NOUN
cana-5212	4	56	leaf	leaf	NOUN
cana-5212	4	57	diseases	disease	NOUN
cana-5212	4	58	through	through	ADP
cana-5212	4	59	the	the	DET
cana-5212	4	60	use	use	NOUN
cana-5212	4	61	of	of	ADP
cana-5212	4	62	convolutional	convolutional	ADJ
cana-5212	4	63	neural	neural	ADJ
cana-5212	4	64	networks	network	NOUN
cana-5212	4	65	(	(	PUNCT
cana-5212	4	66	cnns	cnns	PROPN
cana-5212	4	67	)	)	PUNCT
cana-5212	4	68	augmented	augment	VERB
cana-5212	4	69	with	with	ADP
cana-5212	4	70	fuzzy	fuzzy	ADJ
cana-5212	4	71	logic	logic	NOUN
cana-5212	4	72	techniques	technique	NOUN
cana-5212	4	73	.	.	PUNCT
cana-5212	5	1	the	the	DET
cana-5212	5	2	proposed	propose	VERB
cana-5212	5	3	system	system	NOUN
cana-5212	5	4	measures	measure	NOUN
cana-5212	5	5	disease	disease	NOUN
cana-5212	5	6	severity	severity	NOUN
cana-5212	5	7	and	and	CCONJ
cana-5212	5	8	suggests	suggest	VERB
cana-5212	5	9	treatment	treatment	NOUN
cana-5212	5	10	options	option	NOUN
cana-5212	5	11	.	.	PUNCT
cana-5212	6	1	the	the	DET
cana-5212	6	2	foundation	foundation	NOUN
cana-5212	6	3	of	of	ADP
cana-5212	6	4	this	this	DET
cana-5212	6	5	research	research	NOUN
cana-5212	6	6	lies	lie	VERB
cana-5212	6	7	in	in	ADP
cana-5212	6	8	a	a	DET
cana-5212	6	9	diverse	diverse	ADJ
cana-5212	6	10	raw	raw	ADJ
cana-5212	6	11	image	image	NOUN
cana-5212	6	12	dataset	dataset	NOUN
cana-5212	6	13	of	of	ADP
cana-5212	6	14	rice	rice	NOUN
cana-5212	6	15	,	,	PUNCT
cana-5212	6	16	wheat	wheat	NOUN
cana-5212	6	17	,	,	PUNCT
cana-5212	6	18	corn	corn	NOUN
cana-5212	6	19	,	,	PUNCT
cana-5212	6	20	sugarcane	sugarcane	NOUN
cana-5212	6	21	,	,	PUNCT
cana-5212	6	22	maize	maize	NOUN
cana-5212	6	23	,	,	PUNCT
cana-5212	6	24	barley	barley	NOUN
cana-5212	6	25	,	,	PUNCT
cana-5212	6	26	and	and	CCONJ
cana-5212	6	27	jowar	jowar	NOUN
cana-5212	6	28	leaves	leave	NOUN
cana-5212	6	29	,	,	PUNCT
cana-5212	6	30	ensuring	ensure	VERB
cana-5212	6	31	robustness	robustness	NOUN
cana-5212	6	32	and	and	CCONJ
cana-5212	6	33	realworld	realworld	PROPN
cana-5212	6	34	applicability	applicability	PROPN
cana-5212	6	35	.	.	PUNCT
cana-5212	7	1	our	our	PRON
cana-5212	7	2	approach	approach	NOUN
cana-5212	7	3	leverages	leverage	VERB
cana-5212	7	4	an	an	DET
cana-5212	7	5	advanced	advanced	ADJ
cana-5212	7	6	convolutional	convolutional	ADJ
cana-5212	7	7	neural	neural	ADJ
cana-5212	7	8	network	network	NOUN
cana-5212	7	9	(	(	PUNCT
cana-5212	7	10	cnn	cnn	PROPN
cana-5212	7	11	)	)	PUNCT
cana-5212	7	12	architecture	architecture	NOUN
cana-5212	7	13	for	for	ADP
cana-5212	7	14	precise	precise	ADJ
cana-5212	7	15	plant	plant	NOUN
cana-5212	7	16	disease	disease	NOUN
cana-5212	7	17	classification	classification	NOUN
cana-5212	7	18	,	,	PUNCT
cana-5212	7	19	while	while	SCONJ
cana-5212	7	20	incorporating	incorporate	VERB
cana-5212	7	21	fuzzy	fuzzy	ADJ
cana-5212	7	22	logic	logic	NOUN
cana-5212	7	23	to	to	PART
cana-5212	7	24	perform	perform	VERB
cana-5212	7	25	a	a	DET
cana-5212	7	26	detailed	detailed	ADJ
cana-5212	7	27	analysis	analysis	NOUN
cana-5212	7	28	of	of	ADP
cana-5212	7	29	disease	disease	NOUN
cana-5212	7	30	severity	severity	NOUN
cana-5212	7	31	.	.	PUNCT
cana-5212	8	1	we	we	PRON
cana-5212	8	2	present	present	VERB
cana-5212	8	3	experimental	experimental	ADJ
cana-5212	8	4	results	result	NOUN
cana-5212	8	5	along	along	ADP
cana-5212	8	6	with	with	ADP
cana-5212	8	7	a	a	DET
cana-5212	8	8	thorough	thorough	ADJ
cana-5212	8	9	comparison	comparison	NOUN
cana-5212	8	10	to	to	ADP
cana-5212	8	11	current	current	ADJ
cana-5212	8	12	state	state	NOUN
cana-5212	8	13	-	-	PUNCT
cana-5212	8	14	of	of	ADP
cana-5212	8	15	-	-	PUNCT
cana-5212	8	16	the	the	DET
cana-5212	8	17	-	-	PUNCT
cana-5212	8	18	art	art	NOUN
cana-5212	8	19	methods	method	NOUN
cana-5212	8	20	,	,	PUNCT
cana-5212	8	21	highlighting	highlight	VERB
cana-5212	8	22	improvements	improvement	NOUN
cana-5212	8	23	in	in	ADP
cana-5212	8	24	detection	detection	NOUN
cana-5212	8	25	accuracy	accuracy	NOUN
cana-5212	8	26	,	,	PUNCT
cana-5212	8	27	processing	processing	NOUN
cana-5212	8	28	efficiency	efficiency	NOUN
cana-5212	8	29	,	,	PUNCT
cana-5212	8	30	and	and	CCONJ
cana-5212	8	31	multi	multi	ADJ
cana-5212	8	32	-	-	ADJ
cana-5212	8	33	class	class	ADJ
cana-5212	8	34	classification	classification	NOUN
cana-5212	8	35	performance	performance	NOUN
cana-5212	8	36	.	.	PUNCT
cana-5212	9	1	this	this	DET
cana-5212	9	2	integrated	integrate	VERB
cana-5212	9	3	framework	framework	NOUN
cana-5212	9	4	demonstrates	demonstrate	VERB
cana-5212	9	5	its	its	PRON
cana-5212	9	6	effectiveness	effectiveness	NOUN
cana-5212	9	7	in	in	ADP
cana-5212	9	8	agricultural	agricultural	ADJ
cana-5212	9	9	disease	disease	NOUN
cana-5212	9	10	management	management	NOUN
cana-5212	9	11	,	,	PUNCT
cana-5212	9	12	significantly	significantly	ADV
cana-5212	9	13	reducing	reduce	VERB
cana-5212	9	14	crop	crop	NOUN
cana-5212	9	15	losses	loss	NOUN
cana-5212	9	16	.	.	PUNCT
cana-5212	10	1	furthermore	furthermore	ADV
cana-5212	10	2	,	,	PUNCT
cana-5212	10	3	this	this	DET
cana-5212	10	4	research	research	NOUN
cana-5212	10	5	contributes	contribute	VERB
cana-5212	10	6	to	to	ADP
cana-5212	10	7	the	the	DET
cana-5212	10	8	field	field	NOUN
cana-5212	10	9	by	by	ADP
cana-5212	10	10	providing	provide	VERB
cana-5212	10	11	a	a	DET
cana-5212	10	12	comprehensive	comprehensive	ADJ
cana-5212	10	13	solution	solution	NOUN
cana-5212	10	14	that	that	PRON
cana-5212	10	15	not	not	PART
cana-5212	10	16	only	only	ADV
cana-5212	10	17	detects	detect	NOUN
cana-5212	10	18	and	and	CCONJ
cana-5212	10	19	classifies	classify	VERB
cana-5212	10	20	plant	plant	NOUN
cana-5212	10	21	diseases	disease	NOUN
cana-5212	10	22	but	but	CCONJ
cana-5212	10	23	also	also	ADV
cana-5212	10	24	offers	offer	VERB
cana-5212	10	25	actionable	actionable	ADJ
cana-5212	10	26	insights	insight	NOUN
cana-5212	10	27	for	for	ADP
cana-5212	10	28	targeted	target	VERB
cana-5212	10	29	interventions	intervention	NOUN
cana-5212	10	30	to	to	PART
cana-5212	10	31	optimize	optimize	VERB
cana-5212	10	32	crop	crop	NOUN
cana-5212	10	33	health	health	NOUN
cana-5212	10	34	and	and	CCONJ
cana-5212	10	35	productivity	productivity	NOUN
cana-5212	10	36	keywords	keyword	NOUN
cana-5212	10	37	:	:	PUNCT
cana-5212	10	38	plant	plant	NOUN
cana-5212	10	39	disease	disease	NOUN
cana-5212	10	40	detection	detection	NOUN
cana-5212	10	41	,	,	PUNCT
cana-5212	10	42	convolutional	convolutional	ADJ
cana-5212	10	43	neural	neural	ADJ
cana-5212	10	44	network	network	NOUN
cana-5212	10	45	(	(	PUNCT
cana-5212	10	46	cnn	cnn	PROPN
cana-5212	10	47	)	)	PUNCT
cana-5212	10	48	,	,	PUNCT
cana-5212	10	49	fuzzy	fuzzy	ADJ
cana-5212	10	50	logic	logic	NOUN
cana-5212	10	51	,	,	PUNCT
cana-5212	10	52	severity	severity	NOUN
cana-5212	10	53	analysis	analysis	NOUN
cana-5212	10	54	,	,	PUNCT
cana-5212	10	55	machine	machine	NOUN
cana-5212	10	56	learning	learning	NOUN
cana-5212	10	57	in	in	ADP
cana-5212	10	58	agriculture	agriculture	NOUN
cana-5212	10	59	,	,	PUNCT
cana-5212	10	60	multi	multi	ADJ
cana-5212	10	61	-	-	ADJ
cana-5212	10	62	class	class	ADJ
cana-5212	10	63	classification	classification	NOUN
cana-5212	10	64	1	1	NUM
cana-5212	10	65	.	.	PUNCT
cana-5212	11	1	introduction	introduction	NOUN
cana-5212	11	2	agriculture	agriculture	NOUN
cana-5212	11	3	is	be	AUX
cana-5212	11	4	one	one	NUM
cana-5212	11	5	of	of	ADP
cana-5212	11	6	the	the	DET
cana-5212	11	7	backbone	backbone	NOUN
cana-5212	11	8	industries	industry	NOUN
cana-5212	11	9	in	in	ADP
cana-5212	11	10	the	the	DET
cana-5212	11	11	world	world	NOUN
cana-5212	11	12	's	's	PART
cana-5212	11	13	economy	economy	NOUN
cana-5212	11	14	,	,	PUNCT
cana-5212	11	15	providing	provide	VERB
cana-5212	11	16	basic	basic	ADJ
cana-5212	11	17	resources	resource	NOUN
cana-5212	11	18	and	and	CCONJ
cana-5212	11	19	livelihoods	livelihood	NOUN
cana-5212	11	20	to	to	ADP
cana-5212	11	21	millions	million	NOUN
cana-5212	11	22	of	of	ADP
cana-5212	11	23	people	people	NOUN
cana-5212	11	24	.	.	PUNCT
cana-5212	12	1	on	on	ADP
cana-5212	12	2	the	the	DET
cana-5212	12	3	other	other	ADJ
cana-5212	12	4	hand	hand	NOUN
cana-5212	12	5	,	,	PUNCT
cana-5212	12	6	various	various	ADJ
cana-5212	12	7	plant	plant	NOUN
cana-5212	12	8	diseases	disease	NOUN
cana-5212	12	9	never	never	ADV
cana-5212	12	10	seem	seem	VERB
cana-5212	12	11	to	to	PART
cana-5212	12	12	stop	stop	VERB
cana-5212	12	13	their	their	PRON
cana-5212	12	14	advancement	advancement	NOUN
cana-5212	12	15	at	at	ADP
cana-5212	12	16	the	the	DET
cana-5212	12	17	cost	cost	NOUN
cana-5212	12	18	of	of	ADP
cana-5212	12	19	productivity	productivity	NOUN
cana-5212	12	20	and	and	CCONJ
cana-5212	12	21	quality	quality	NOUN
cana-5212	12	22	in	in	ADP
cana-5212	12	23	the	the	DET
cana-5212	12	24	output	output	NOUN
cana-5212	12	25	.	.	PUNCT
cana-5212	13	1	crop	crop	NOUN
cana-5212	13	2	losses	loss	NOUN
cana-5212	13	3	because	because	SCONJ
cana-5212	13	4	of	of	ADP
cana-5212	13	5	diseases	disease	NOUN
cana-5212	13	6	directly	directly	ADV
cana-5212	13	7	influence	influence	VERB
cana-5212	13	8	food	food	NOUN
cana-5212	13	9	security	security	NOUN
cana-5212	13	10	and	and	CCONJ
cana-5212	13	11	the	the	DET
cana-5212	13	12	economic	economic	ADJ
cana-5212	13	13	stability	stability	NOUN
cana-5212	13	14	of	of	ADP
cana-5212	13	15	farming	farming	NOUN
cana-5212	13	16	communities	community	NOUN
cana-5212	13	17	.	.	PUNCT
cana-5212	14	1	classical	classical	ADJ
cana-5212	14	2	techniques	technique	NOUN
cana-5212	14	3	for	for	ADP
cana-5212	14	4	plant	plant	NOUN
cana-5212	14	5	diseases	disease	NOUN
cana-5212	14	6	detection	detection	NOUN
cana-5212	14	7	,	,	PUNCT
cana-5212	14	8	based	base	VERB
cana-5212	14	9	on	on	ADP
cana-5212	14	10	visual	visual	ADJ
cana-5212	14	11	inspection	inspection	NOUN
cana-5212	14	12	by	by	ADP
cana-5212	14	13	experts	expert	NOUN
cana-5212	14	14	,	,	PUNCT
cana-5212	14	15	represent	represent	VERB
cana-5212	14	16	timeand	timeand	NOUN
cana-5212	14	17	labour	labour	NOUN
cana-5212	14	18	-	-	PUNCT
cana-5212	14	19	consuming	consume	VERB
cana-5212	14	20	approaches	approach	NOUN
cana-5212	14	21	that	that	SCONJ
cana-5212	14	22	in	in	ADP
cana-5212	14	23	most	most	ADJ
cana-5212	14	24	cases	case	NOUN
cana-5212	14	25	lack	lack	VERB
cana-5212	14	26	the	the	DET
cana-5212	14	27	required	require	VERB
cana-5212	14	28	precision	precision	NOUN
cana-5212	14	29	for	for	ADP
cana-5212	14	30	the	the	DET
cana-5212	14	31	identification	identification	NOUN
cana-5212	14	32	of	of	ADP
cana-5212	14	33	diseases	disease	NOUN
cana-5212	14	34	at	at	ADP
cana-5212	14	35	an	an	DET
cana-5212	14	36	early	early	ADJ
cana-5212	14	37	stage	stage	NOUN
cana-5212	14	38	.	.	PUNCT
cana-5212	15	1	mailto:preeti.schcse@dcrustm.org	mailto:preeti.schcse@dcrustm.org	NOUN
cana-5212	16	1	mailto:parvindersingh@dcrsutm.org	mailto:parvindersingh@dcrsutm.org	PROPN
cana-5212	16	2	communications	communication	NOUN
cana-5212	16	3	on	on	ADP
cana-5212	16	4	applied	apply	VERB
cana-5212	16	5	nonlinear	nonlinear	ADJ
cana-5212	16	6	analysis	analysis	NOUN
cana-5212	16	7	issn	issn	NOUN
cana-5212	16	8	:	:	PUNCT
cana-5212	16	9	1074	1074	NUM
cana-5212	16	10	-	-	PUNCT
cana-5212	16	11	133x	133x	NUM
cana-5212	16	12	vol	vol	NOUN
cana-5212	16	13	32	32	NUM
cana-5212	16	14	no	no	NOUN
cana-5212	16	15	.	.	PUNCT
cana-5212	17	1	8s	8s	PROPN
cana-5212	17	2	(	(	PUNCT
cana-5212	17	3	2025	2025	NUM
cana-5212	17	4	)	)	PUNCT
cana-5212	17	5	934	934	NUM
cana-5212	17	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	17	7	fast	fast	ADJ
cana-5212	17	8	and	and	CCONJ
cana-5212	17	9	rapid	rapid	ADJ
cana-5212	17	10	technological	technological	ADJ
cana-5212	17	11	growth	growth	NOUN
cana-5212	17	12	has	have	AUX
cana-5212	17	13	led	lead	VERB
cana-5212	17	14	the	the	DET
cana-5212	17	15	path	path	NOUN
cana-5212	17	16	to	to	ADP
cana-5212	17	17	more	more	ADV
cana-5212	17	18	effective	effective	ADJ
cana-5212	17	19	and	and	CCONJ
cana-5212	17	20	accurate	accurate	ADJ
cana-5212	17	21	solutions	solution	NOUN
cana-5212	17	22	in	in	ADP
cana-5212	17	23	agriculture	agriculture	NOUN
cana-5212	17	24	.	.	PUNCT
cana-5212	18	1	in	in	ADP
cana-5212	18	2	the	the	DET
cana-5212	18	3	field	field	NOUN
cana-5212	18	4	of	of	ADP
cana-5212	18	5	image	image	NOUN
cana-5212	18	6	processing	processing	NOUN
cana-5212	18	7	and	and	CCONJ
cana-5212	18	8	disease	disease	NOUN
cana-5212	18	9	detection	detection	NOUN
cana-5212	18	10	,	,	PUNCT
cana-5212	18	11	machine	machine	NOUN
cana-5212	18	12	learning	learning	NOUN
cana-5212	18	13	,	,	PUNCT
cana-5212	18	14	especially	especially	ADV
cana-5212	18	15	convolutional	convolutional	ADJ
cana-5212	18	16	neural	neural	ADJ
cana-5212	18	17	networks	network	NOUN
cana-5212	18	18	,	,	PUNCT
cana-5212	18	19	has	have	AUX
cana-5212	18	20	surfaced	surface	VERB
cana-5212	18	21	as	as	ADP
cana-5212	18	22	a	a	DET
cana-5212	18	23	land	land	NOUN
cana-5212	18	24	-	-	PUNCT
cana-5212	18	25	changing	change	VERB
cana-5212	18	26	tool	tool	NOUN
cana-5212	18	27	.	.	PUNCT
cana-5212	19	1	they	they	PRON
cana-5212	19	2	have	have	AUX
cana-5212	19	3	shown	show	VERB
cana-5212	19	4	outstanding	outstanding	ADJ
cana-5212	19	5	results	result	NOUN
cana-5212	19	6	in	in	ADP
cana-5212	19	7	most	most	ADJ
cana-5212	19	8	of	of	ADP
cana-5212	19	9	the	the	DET
cana-5212	19	10	image	image	NOUN
cana-5212	19	11	classification	classification	NOUN
cana-5212	19	12	tasks	task	NOUN
cana-5212	19	13	;	;	PUNCT
cana-5212	19	14	hence	hence	ADV
cana-5212	19	15	,	,	PUNCT
cana-5212	19	16	they	they	PRON
cana-5212	19	17	have	have	AUX
cana-5212	19	18	been	be	AUX
cana-5212	19	19	found	find	VERB
cana-5212	19	20	very	very	ADV
cana-5212	19	21	effective	effective	ADJ
cana-5212	19	22	in	in	ADP
cana-5212	19	23	the	the	DET
cana-5212	19	24	identification	identification	NOUN
cana-5212	19	25	and	and	CCONJ
cana-5212	19	26	classification	classification	NOUN
cana-5212	19	27	of	of	ADP
cana-5212	19	28	plant	plant	NOUN
cana-5212	19	29	diseases	disease	NOUN
cana-5212	19	30	.	.	PUNCT
cana-5212	20	1	convolutional	convolutional	ADJ
cana-5212	20	2	neural	neural	ADJ
cana-5212	20	3	networks	network	NOUN
cana-5212	20	4	are	be	AUX
cana-5212	20	5	designed	design	VERB
cana-5212	20	6	to	to	PART
cana-5212	20	7	be	be	AUX
cana-5212	20	8	much	much	ADV
cana-5212	20	9	like	like	ADP
cana-5212	20	10	the	the	DET
cana-5212	20	11	human	human	ADJ
cana-5212	20	12	visual	visual	ADJ
cana-5212	20	13	system	system	NOUN
cana-5212	20	14	by	by	ADP
cana-5212	20	15	a	a	DET
cana-5212	20	16	number	number	NOUN
cana-5212	20	17	of	of	ADP
cana-5212	20	18	layers	layer	NOUN
cana-5212	20	19	that	that	PRON
cana-5212	20	20	capture	capture	VERB
cana-5212	20	21	spatial	spatial	ADJ
cana-5212	20	22	hierarchies	hierarchy	NOUN
cana-5212	20	23	of	of	ADP
cana-5212	20	24	features	feature	NOUN
cana-5212	20	25	directly	directly	ADV
cana-5212	20	26	from	from	ADP
cana-5212	20	27	the	the	DET
cana-5212	20	28	simple	simple	ADJ
cana-5212	20	29	input	input	NOUN
cana-5212	20	30	image	image	NOUN
cana-5212	20	31	,	,	PUNCT
cana-5212	20	32	taking	take	VERB
cana-5212	20	33	into	into	ADP
cana-5212	20	34	account	account	NOUN
cana-5212	20	35	any	any	DET
cana-5212	20	36	variance	variance	NOUN
cana-5212	20	37	in	in	ADP
cana-5212	20	38	the	the	DET
cana-5212	20	39	environment	environment	NOUN
cana-5212	20	40	.	.	PUNCT
cana-5212	21	1	therefore	therefore	ADV
cana-5212	21	2	,	,	PUNCT
cana-5212	21	3	on	on	ADP
cana-5212	21	4	this	this	DET
cana-5212	21	5	basis	basis	NOUN
cana-5212	21	6	,	,	PUNCT
cana-5212	21	7	cnns	cnn	NOUN
cana-5212	21	8	can	can	AUX
cana-5212	21	9	differentiate	differentiate	VERB
cana-5212	21	10	varied	varied	ADJ
cana-5212	21	11	kinds	kind	NOUN
cana-5212	21	12	of	of	ADP
cana-5212	21	13	plant	plant	NOUN
cana-5212	21	14	diseases	disease	NOUN
cana-5212	21	15	efficiently	efficiently	ADV
cana-5212	21	16	even	even	ADV
cana-5212	21	17	in	in	ADP
cana-5212	21	18	noisy	noisy	ADJ
cana-5212	21	19	and	and	CCONJ
cana-5212	21	20	complex	complex	ADJ
cana-5212	21	21	environments	environment	NOUN
cana-5212	21	22	.	.	PUNCT
cana-5212	22	1	further	further	ADJ
cana-5212	22	2	integration	integration	NOUN
cana-5212	22	3	of	of	ADP
cana-5212	22	4	cnns	cnn	NOUN
cana-5212	22	5	into	into	ADP
cana-5212	22	6	agricultural	agricultural	ADJ
cana-5212	22	7	practice	practice	NOUN
cana-5212	22	8	can	can	AUX
cana-5212	22	9	mean	mean	VERB
cana-5212	22	10	shifting	shift	VERB
cana-5212	22	11	disease	disease	NOUN
cana-5212	22	12	detection	detection	NOUN
cana-5212	22	13	toward	toward	ADP
cana-5212	22	14	more	more	ADV
cana-5212	22	15	automated	automated	ADJ
cana-5212	22	16	,	,	PUNCT
cana-5212	22	17	finerscaled	finerscale	VERB
cana-5212	22	18	,	,	PUNCT
cana-5212	22	19	and	and	CCONJ
cana-5212	22	20	scalable	scalable	ADJ
cana-5212	22	21	systems	system	NOUN
cana-5212	22	22	.	.	PUNCT
cana-5212	23	1	although	although	SCONJ
cana-5212	23	2	there	there	PRON
cana-5212	23	3	are	be	VERB
cana-5212	23	4	some	some	DET
cana-5212	23	5	very	very	ADV
cana-5212	23	6	promising	promising	ADJ
cana-5212	23	7	developments	development	NOUN
cana-5212	23	8	in	in	ADP
cana-5212	23	9	this	this	DET
cana-5212	23	10	area	area	NOUN
cana-5212	23	11	,	,	PUNCT
cana-5212	23	12	most	most	ADJ
cana-5212	23	13	of	of	ADP
cana-5212	23	14	the	the	DET
cana-5212	23	15	methods	method	NOUN
cana-5212	23	16	seem	seem	VERB
cana-5212	23	17	to	to	PART
cana-5212	23	18	be	be	AUX
cana-5212	23	19	tilted	tilt	VERB
cana-5212	23	20	more	more	ADV
cana-5212	23	21	towards	towards	ADP
cana-5212	23	22	disease	disease	NOUN
cana-5212	23	23	identification	identification	NOUN
cana-5212	23	24	and	and	CCONJ
cana-5212	23	25	classification	classification	NOUN
cana-5212	23	26	,	,	PUNCT
cana-5212	23	27	rather	rather	ADV
cana-5212	23	28	than	than	ADP
cana-5212	23	29	emphasizing	emphasize	VERB
cana-5212	23	30	the	the	DET
cana-5212	23	31	evaluation	evaluation	NOUN
cana-5212	23	32	of	of	ADP
cana-5212	23	33	the	the	DET
cana-5212	23	34	severity	severity	NOUN
cana-5212	23	35	of	of	ADP
cana-5212	23	36	the	the	DET
cana-5212	23	37	disease	disease	NOUN
cana-5212	23	38	or	or	CCONJ
cana-5212	23	39	decision	decision	NOUN
cana-5212	23	40	making	make	VERB
cana-5212	23	41	for	for	ADP
cana-5212	23	42	treatment	treatment	NOUN
cana-5212	23	43	.	.	PUNCT
cana-5212	24	1	in	in	ADP
cana-5212	24	2	this	this	DET
cana-5212	24	3	paper	paper	NOUN
cana-5212	24	4	,	,	PUNCT
cana-5212	24	5	this	this	DET
cana-5212	24	6	gap	gap	NOUN
cana-5212	24	7	is	be	AUX
cana-5212	24	8	attempted	attempt	VERB
cana-5212	24	9	to	to	PART
cana-5212	24	10	be	be	AUX
cana-5212	24	11	filled	fill	VERB
cana-5212	24	12	by	by	ADP
cana-5212	24	13	not	not	PART
cana-5212	24	14	only	only	ADV
cana-5212	24	15	detecting	detect	VERB
cana-5212	24	16	plant	plant	NOUN
cana-5212	24	17	leaf	leaf	NOUN
cana-5212	24	18	diseases	disease	NOUN
cana-5212	24	19	by	by	ADP
cana-5212	24	20	cnn	cnn	PROPN
cana-5212	24	21	and	and	CCONJ
cana-5212	24	22	their	their	PRON
cana-5212	24	23	classification	classification	NOUN
cana-5212	24	24	but	but	CCONJ
cana-5212	24	25	also	also	ADV
cana-5212	24	26	by	by	ADP
cana-5212	24	27	involving	involve	VERB
cana-5212	24	28	fuzzy	fuzzy	ADJ
cana-5212	24	29	logic	logic	NOUN
cana-5212	24	30	to	to	PART
cana-5212	24	31	assess	assess	VERB
cana-5212	24	32	the	the	DET
cana-5212	24	33	severity	severity	NOUN
cana-5212	24	34	of	of	ADP
cana-5212	24	35	the	the	DET
cana-5212	24	36	diseases	disease	NOUN
cana-5212	24	37	and	and	CCONJ
cana-5212	24	38	further	far	ADV
cana-5212	24	39	decide	decide	VERB
cana-5212	24	40	on	on	ADP
cana-5212	24	41	treatment	treatment	NOUN
cana-5212	24	42	.	.	PUNCT
cana-5212	25	1	the	the	DET
cana-5212	25	2	integrated	integrate	VERB
cana-5212	25	3	approach	approach	NOUN
cana-5212	25	4	shall	shall	AUX
cana-5212	25	5	help	help	VERB
cana-5212	25	6	improve	improve	VERB
cana-5212	25	7	efficiency	efficiency	NOUN
cana-5212	25	8	and	and	CCONJ
cana-5212	25	9	efficacy	efficacy	NOUN
cana-5212	25	10	of	of	ADP
cana-5212	25	11	the	the	DET
cana-5212	25	12	applied	apply	VERB
cana-5212	25	13	strategies	strategy	NOUN
cana-5212	25	14	for	for	ADP
cana-5212	25	15	management	management	NOUN
cana-5212	25	16	,	,	PUNCT
cana-5212	25	17	thus	thus	ADV
cana-5212	25	18	healthier	healthy	ADJ
cana-5212	25	19	crops	crop	NOUN
cana-5212	25	20	with	with	ADP
cana-5212	25	21	better	well	ADJ
cana-5212	25	22	yields	yield	NOUN
cana-5212	25	23	would	would	AUX
cana-5212	25	24	be	be	AUX
cana-5212	25	25	obtained	obtain	VERB
cana-5212	25	26	.	.	PUNCT
cana-5212	26	1	coupling	couple	VERB
cana-5212	26	2	deep	deep	ADJ
cana-5212	26	3	machine	machine	NOUN
cana-5212	26	4	learning	learning	NOUN
cana-5212	26	5	methodologies	methodology	NOUN
cana-5212	26	6	with	with	ADP
cana-5212	26	7	agricultural	agricultural	ADJ
cana-5212	26	8	practices	practice	NOUN
cana-5212	26	9	is	be	AUX
cana-5212	26	10	,	,	PUNCT
cana-5212	26	11	therefore	therefore	ADV
cana-5212	26	12	,	,	PUNCT
cana-5212	26	13	a	a	DET
cana-5212	26	14	step	step	NOUN
cana-5212	26	15	into	into	ADP
cana-5212	26	16	the	the	DET
cana-5212	26	17	future	future	NOUN
cana-5212	26	18	in	in	ADP
cana-5212	26	19	dealing	deal	VERB
cana-5212	26	20	with	with	ADP
cana-5212	26	21	challenges	challenge	NOUN
cana-5212	26	22	brought	bring	VERB
cana-5212	26	23	forth	forth	ADP
cana-5212	26	24	by	by	ADP
cana-5212	26	25	plant	plant	NOUN
cana-5212	26	26	diseases	disease	NOUN
cana-5212	26	27	.	.	PUNCT
cana-5212	27	1	it	it	PRON
cana-5212	27	2	is	be	AUX
cana-5212	27	3	hoped	hope	VERB
cana-5212	27	4	to	to	PART
cana-5212	27	5	evolve	evolve	VERB
cana-5212	27	6	a	a	DET
cana-5212	27	7	complete	complete	ADJ
cana-5212	27	8	solution	solution	NOUN
cana-5212	27	9	of	of	ADP
cana-5212	27	10	present	present	ADJ
cana-5212	27	11	-	-	PUNCT
cana-5212	27	12	day	day	NOUN
cana-5212	27	13	agriculture	agriculture	NOUN
cana-5212	27	14	demands	demand	NOUN
cana-5212	27	15	for	for	ADP
cana-5212	27	16	being	be	AUX
cana-5212	27	17	sustainable	sustainable	ADJ
cana-5212	27	18	and	and	CCONJ
cana-5212	27	19	productive	productive	ADJ
cana-5212	27	20	in	in	ADP
cana-5212	27	21	the	the	DET
cana-5212	27	22	face	face	NOUN
cana-5212	27	23	of	of	ADP
cana-5212	27	24	challenges	challenge	NOUN
cana-5212	27	25	with	with	ADP
cana-5212	27	26	growing	grow	VERB
cana-5212	27	27	magnitude	magnitude	NOUN
cana-5212	27	28	by	by	ADP
cana-5212	27	29	leveraging	leverage	VERB
cana-5212	27	30	the	the	DET
cana-5212	27	31	strengths	strength	NOUN
cana-5212	27	32	of	of	ADP
cana-5212	27	33	cnns	cnn	NOUN
cana-5212	27	34	and	and	CCONJ
cana-5212	27	35	fuzzy	fuzzy	ADJ
cana-5212	27	36	logic	logic	NOUN
cana-5212	27	37	in	in	ADP
cana-5212	27	38	this	this	DET
cana-5212	27	39	research	research	NOUN
cana-5212	27	40	.	.	PUNCT
cana-5212	28	1	2	2	X
cana-5212	28	2	.	.	X
cana-5212	28	3	objectives	objective	NOUN
cana-5212	28	4	•	•	ADP
cana-5212	28	5	to	to	PART
cana-5212	28	6	study	study	VERB
cana-5212	28	7	existing	exist	VERB
cana-5212	28	8	plant	plant	NOUN
cana-5212	28	9	leaf	leaf	NOUN
cana-5212	28	10	disease	disease	NOUN
cana-5212	28	11	detection	detection	NOUN
cana-5212	28	12	techniques	technique	NOUN
cana-5212	28	13	from	from	ADP
cana-5212	28	14	recent	recent	ADJ
cana-5212	28	15	publications	publication	NOUN
cana-5212	28	16	.	.	PUNCT
cana-5212	29	1	•	•	NOUN
cana-5212	29	2	to	to	PART
cana-5212	29	3	design	design	VERB
cana-5212	29	4	an	an	DET
cana-5212	29	5	advanced	advanced	ADJ
cana-5212	29	6	cnn	cnn	NOUN
cana-5212	29	7	algorithm	algorithm	NOUN
cana-5212	29	8	incorporating	incorporate	VERB
cana-5212	29	9	fuzzy	fuzzy	ADJ
cana-5212	29	10	logic	logic	NOUN
cana-5212	29	11	.	.	PUNCT
cana-5212	30	1	•	•	INTJ
cana-5212	30	2	to	to	PART
cana-5212	30	3	implement	implement	VERB
cana-5212	30	4	the	the	DET
cana-5212	30	5	designed	design	VERB
cana-5212	30	6	algorithm	algorithm	NOUN
cana-5212	30	7	.	.	PUNCT
cana-5212	31	1	•	•	NUM
cana-5212	31	2	to	to	PART
cana-5212	31	3	compare	compare	VERB
cana-5212	31	4	the	the	DET
cana-5212	31	5	proposed	propose	VERB
cana-5212	31	6	algorithm	algorithm	NOUN
cana-5212	31	7	with	with	ADP
cana-5212	31	8	existing	exist	VERB
cana-5212	31	9	methods	method	NOUN
cana-5212	31	10	and	and	CCONJ
cana-5212	31	11	provide	provide	VERB
cana-5212	31	12	detailed	detailed	ADJ
cana-5212	31	13	analysis	analysis	NOUN
cana-5212	31	14	through	through	ADP
cana-5212	31	15	various	various	ADJ
cana-5212	31	16	metrics	metric	NOUN
cana-5212	31	17	and	and	CCONJ
cana-5212	31	18	visual	visual	ADJ
cana-5212	31	19	charts	chart	NOUN
cana-5212	31	20	.	.	PUNCT
cana-5212	32	1	3	3	X
cana-5212	32	2	.	.	X
cana-5212	32	3	methods	method	NOUN
cana-5212	32	4	3.1	3.1	NUM
cana-5212	32	5	design	design	NOUN
cana-5212	32	6	the	the	DET
cana-5212	32	7	algorithm	algorithm	NOUN
cana-5212	32	8	to	to	PART
cana-5212	32	9	be	be	AUX
cana-5212	32	10	proposed	propose	VERB
cana-5212	32	11	will	will	AUX
cana-5212	32	12	thus	thus	ADV
cana-5212	32	13	be	be	AUX
cana-5212	32	14	the	the	DET
cana-5212	32	15	novel	novel	ADJ
cana-5212	32	16	integration	integration	NOUN
cana-5212	32	17	of	of	ADP
cana-5212	32	18	convolutional	convolutional	ADJ
cana-5212	32	19	neural	neural	ADJ
cana-5212	32	20	networks	network	NOUN
cana-5212	32	21	for	for	ADP
cana-5212	32	22	multi	multi	ADJ
cana-5212	32	23	-	-	ADJ
cana-5212	32	24	class	class	ADJ
cana-5212	32	25	disease	disease	NOUN
cana-5212	32	26	detection	detection	NOUN
cana-5212	32	27	and	and	CCONJ
cana-5212	32	28	fuzzy	fuzzy	ADJ
cana-5212	32	29	logic	logic	NOUN
cana-5212	32	30	for	for	ADP
cana-5212	32	31	severity	severity	NOUN
cana-5212	32	32	analysis	analysis	NOUN
cana-5212	32	33	.	.	PUNCT
cana-5212	33	1	this	this	PRON
cana-5212	33	2	will	will	AUX
cana-5212	33	3	improve	improve	VERB
cana-5212	33	4	general	general	ADJ
cana-5212	33	5	accuracy	accuracy	NOUN
cana-5212	33	6	,	,	PUNCT
cana-5212	33	7	thus	thus	ADV
cana-5212	33	8	making	make	VERB
cana-5212	33	9	the	the	DET
cana-5212	33	10	outcome	outcome	NOUN
cana-5212	33	11	very	very	ADV
cana-5212	33	12	useful	useful	ADJ
cana-5212	33	13	and	and	CCONJ
cana-5212	33	14	related	relate	VERB
cana-5212	33	15	to	to	ADP
cana-5212	33	16	both	both	DET
cana-5212	33	17	identification	identification	NOUN
cana-5212	33	18	and	and	CCONJ
cana-5212	33	19	management	management	NOUN
cana-5212	33	20	regarding	regard	VERB
cana-5212	33	21	plant	plant	NOUN
cana-5212	33	22	diseases	disease	NOUN
cana-5212	33	23	.	.	PUNCT
cana-5212	34	1	3.1.1	3.1.1	NUM
cana-5212	34	2	cnn	cnn	NOUN
cana-5212	34	3	architecture	architecture	NOUN
cana-5212	34	4	input	input	NOUN
cana-5212	34	5	layer	layer	NOUN
cana-5212	34	6	:	:	PUNCT
cana-5212	34	7	the	the	DET
cana-5212	34	8	algorithm	algorithm	NOUN
cana-5212	34	9	takes	take	VERB
cana-5212	34	10	as	as	ADP
cana-5212	34	11	input	input	NOUN
cana-5212	34	12	the	the	DET
cana-5212	34	13	raw	raw	ADJ
cana-5212	34	14	images	image	NOUN
cana-5212	34	15	of	of	ADP
cana-5212	34	16	the	the	DET
cana-5212	34	17	leaves	leave	NOUN
cana-5212	34	18	of	of	ADP
cana-5212	34	19	the	the	DET
cana-5212	34	20	plants	plant	NOUN
cana-5212	34	21	.	.	PUNCT
cana-5212	35	1	this	this	DET
cana-5212	35	2	layer	layer	NOUN
cana-5212	35	3	takes	take	VERB
cana-5212	35	4	images	image	NOUN
cana-5212	35	5	of	of	ADP
cana-5212	35	6	different	different	ADJ
cana-5212	35	7	sizes	size	NOUN
cana-5212	35	8	,	,	PUNCT
cana-5212	35	9	which	which	PRON
cana-5212	35	10	makes	make	VERB
cana-5212	35	11	it	it	PRON
cana-5212	35	12	flexible	flexible	ADJ
cana-5212	35	13	and	and	CCONJ
cana-5212	35	14	adaptive	adaptive	ADJ
cana-5212	35	15	for	for	ADP
cana-5212	35	16	datasets	dataset	NOUN
cana-5212	35	17	with	with	ADP
cana-5212	35	18	images	image	NOUN
cana-5212	35	19	of	of	ADP
cana-5212	35	20	different	different	ADJ
cana-5212	35	21	dimensions	dimension	NOUN
cana-5212	35	22	.	.	PUNCT
cana-5212	36	1	communications	communication	NOUN
cana-5212	36	2	on	on	ADP
cana-5212	36	3	applied	apply	VERB
cana-5212	36	4	nonlinear	nonlinear	ADJ
cana-5212	36	5	analysis	analysis	NOUN
cana-5212	36	6	issn	issn	NOUN
cana-5212	36	7	:	:	PUNCT
cana-5212	36	8	1074	1074	NUM
cana-5212	36	9	-	-	PUNCT
cana-5212	36	10	133x	133x	NUM
cana-5212	36	11	vol	vol	NOUN
cana-5212	36	12	32	32	NUM
cana-5212	36	13	no	no	NOUN
cana-5212	36	14	.	.	PUNCT
cana-5212	37	1	8s	8s	PROPN
cana-5212	37	2	(	(	PUNCT
cana-5212	37	3	2025	2025	NUM
cana-5212	37	4	)	)	PUNCT
cana-5212	37	5	935	935	NUM
cana-5212	37	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	37	7	convolutional	convolutional	ADJ
cana-5212	37	8	layers	layer	NOUN
cana-5212	37	9	:	:	PUNCT
cana-5212	37	10	multiple	multiple	ADJ
cana-5212	37	11	convolutional	convolutional	ADJ
cana-5212	37	12	layers	layer	NOUN
cana-5212	37	13	extract	extract	VERB
cana-5212	37	14	features	feature	NOUN
cana-5212	37	15	from	from	ADP
cana-5212	37	16	the	the	DET
cana-5212	37	17	input	input	NOUN
cana-5212	37	18	images	image	NOUN
cana-5212	37	19	.	.	PUNCT
cana-5212	38	1	for	for	ADP
cana-5212	38	2	every	every	DET
cana-5212	38	3	convolutional	convolutional	ADJ
cana-5212	38	4	layer	layer	NOUN
cana-5212	38	5	,	,	PUNCT
cana-5212	38	6	there	there	PRON
cana-5212	38	7	is	be	VERB
cana-5212	38	8	a	a	DET
cana-5212	38	9	specified	specified	ADJ
cana-5212	38	10	number	number	NOUN
cana-5212	38	11	of	of	ADP
cana-5212	38	12	filters	filter	NOUN
cana-5212	38	13	that	that	PRON
cana-5212	38	14	convolve	convolve	VERB
cana-5212	38	15	and	and	CCONJ
cana-5212	38	16	capture	capture	VERB
cana-5212	38	17	spatial	spatial	ADJ
cana-5212	38	18	hierarchies	hierarchy	NOUN
cana-5212	38	19	of	of	ADP
cana-5212	38	20	features	feature	NOUN
cana-5212	38	21	,	,	PUNCT
cana-5212	38	22	such	such	ADJ
cana-5212	38	23	as	as	ADP
cana-5212	38	24	edges	edge	NOUN
cana-5212	38	25	,	,	PUNCT
cana-5212	38	26	textures	texture	NOUN
cana-5212	38	27	,	,	PUNCT
cana-5212	38	28	and	and	CCONJ
cana-5212	38	29	patterns	pattern	NOUN
cana-5212	38	30	.	.	PUNCT
cana-5212	39	1	after	after	ADP
cana-5212	39	2	every	every	DET
cana-5212	39	3	convolution	convolution	NOUN
cana-5212	39	4	,	,	PUNCT
cana-5212	39	5	relu	relu	NOUN
cana-5212	39	6	activation	activation	NOUN
cana-5212	39	7	functions	function	NOUN
cana-5212	39	8	exist	exist	VERB
cana-5212	39	9	to	to	PART
cana-5212	39	10	introduce	introduce	VERB
cana-5212	39	11	nonlinearity	nonlinearity	NOUN
cana-5212	39	12	into	into	ADP
cana-5212	39	13	the	the	DET
cana-5212	39	14	network	network	NOUN
cana-5212	39	15	in	in	ADP
cana-5212	39	16	an	an	DET
cana-5212	39	17	effort	effort	NOUN
cana-5212	39	18	to	to	PART
cana-5212	39	19	learn	learn	VERB
cana-5212	39	20	complex	complex	ADJ
cana-5212	39	21	representations	representation	NOUN
cana-5212	39	22	.	.	PUNCT
cana-5212	40	1	pooling	pool	VERB
cana-5212	40	2	layers	layer	NOUN
cana-5212	40	3	:	:	PUNCT
cana-5212	40	4	consequently	consequently	ADV
cana-5212	40	5	,	,	PUNCT
cana-5212	40	6	pooling	pool	VERB
cana-5212	40	7	layers	layer	NOUN
cana-5212	40	8	reduce	reduce	VERB
cana-5212	40	9	the	the	DET
cana-5212	40	10	size	size	NOUN
cana-5212	40	11	of	of	ADP
cana-5212	40	12	the	the	DET
cana-5212	40	13	feature	feature	NOUN
cana-5212	40	14	maps	map	NOUN
cana-5212	40	15	after	after	ADP
cana-5212	40	16	convolution	convolution	NOUN
cana-5212	40	17	layers	layer	NOUN
cana-5212	40	18	.	.	PUNCT
cana-5212	41	1	max	max	PROPN
cana-5212	41	2	-	-	PUNCT
cana-5212	41	3	pooling	pooling	NOUN
cana-5212	41	4	is	be	AUX
cana-5212	41	5	done	do	VERB
cana-5212	41	6	to	to	PART
cana-5212	41	7	ensure	ensure	VERB
cana-5212	41	8	that	that	SCONJ
cana-5212	41	9	only	only	ADV
cana-5212	41	10	the	the	DET
cana-5212	41	11	strongest	strong	ADJ
cana-5212	41	12	features	feature	NOUN
cana-5212	41	13	remain	remain	VERB
cana-5212	41	14	but	but	CCONJ
cana-5212	41	15	at	at	ADP
cana-5212	41	16	the	the	DET
cana-5212	41	17	same	same	ADJ
cana-5212	41	18	time	time	NOUN
cana-5212	41	19	reduce	reduce	VERB
cana-5212	41	20	computation	computation	NOUN
cana-5212	41	21	expense	expense	NOUN
cana-5212	41	22	.	.	PUNCT
cana-5212	42	1	the	the	DET
cana-5212	42	2	step	step	NOUN
cana-5212	42	3	can	can	AUX
cana-5212	42	4	be	be	AUX
cana-5212	42	5	used	use	VERB
cana-5212	42	6	to	to	PART
cana-5212	42	7	obtain	obtain	VERB
cana-5212	42	8	translational	translational	ADJ
cana-5212	42	9	invariance	invariance	NOUN
cana-5212	42	10	;	;	PUNCT
cana-5212	42	11	hence	hence	ADV
cana-5212	42	12	,	,	PUNCT
cana-5212	42	13	this	this	DET
cana-5212	42	14	model	model	NOUN
cana-5212	42	15	will	will	AUX
cana-5212	42	16	be	be	AUX
cana-5212	42	17	rather	rather	ADV
cana-5212	42	18	robust	robust	ADJ
cana-5212	42	19	against	against	ADP
cana-5212	42	20	small	small	ADJ
cana-5212	42	21	changes	change	NOUN
cana-5212	42	22	in	in	ADP
cana-5212	42	23	the	the	DET
cana-5212	42	24	input	input	NOUN
cana-5212	42	25	images	image	NOUN
cana-5212	42	26	.	.	PUNCT
cana-5212	43	1	fully	fully	ADV
cana-5212	43	2	connected	connected	ADJ
cana-5212	43	3	layers	layer	NOUN
cana-5212	43	4	:	:	PUNCT
cana-5212	43	5	these	these	DET
cana-5212	43	6	top	top	ADJ
cana-5212	43	7	-	-	PUNCT
cana-5212	43	8	level	level	NOUN
cana-5212	43	9	features	feature	NOUN
cana-5212	43	10	are	be	AUX
cana-5212	43	11	then	then	ADV
cana-5212	43	12	input	input	ADJ
cana-5212	43	13	into	into	ADP
cana-5212	43	14	fully	fully	ADV
cana-5212	43	15	connected	connect	VERB
cana-5212	43	16	layers	layer	NOUN
cana-5212	43	17	extracted	extract	VERB
cana-5212	43	18	by	by	ADP
cana-5212	43	19	the	the	DET
cana-5212	43	20	convolutional	convolutional	ADJ
cana-5212	43	21	and	and	CCONJ
cana-5212	43	22	pooling	pool	VERB
cana-5212	43	23	layers	layer	NOUN
cana-5212	43	24	.	.	PUNCT
cana-5212	44	1	such	such	ADJ
cana-5212	44	2	layer	layer	NOUN
cana-5212	44	3	’s	’s	PART
cana-5212	44	4	work	work	NOUN
cana-5212	44	5	as	as	ADP
cana-5212	44	6	a	a	DET
cana-5212	44	7	classifier	classifier	NOUN
cana-5212	44	8	to	to	PART
cana-5212	44	9	transform	transform	VERB
cana-5212	44	10	the	the	DET
cana-5212	44	11	features	feature	NOUN
cana-5212	44	12	extracted	extract	VERB
cana-5212	44	13	into	into	ADP
cana-5212	44	14	a	a	DET
cana-5212	44	15	vector	vector	NOUN
cana-5212	44	16	of	of	ADP
cana-5212	44	17	class	class	NOUN
cana-5212	44	18	scores	score	NOUN
cana-5212	44	19	.	.	PUNCT
cana-5212	45	1	by	by	ADP
cana-5212	45	2	learning	learn	VERB
cana-5212	45	3	these	these	DET
cana-5212	45	4	representations	representation	NOUN
cana-5212	45	5	,	,	PUNCT
cana-5212	45	6	this	this	DET
cana-5212	45	7	network	network	NOUN
cana-5212	45	8	can	can	AUX
cana-5212	45	9	,	,	PUNCT
cana-5212	45	10	therefore	therefore	ADV
cana-5212	45	11	,	,	PUNCT
cana-5212	45	12	classify	classify	VERB
cana-5212	45	13	diseases	disease	NOUN
cana-5212	45	14	into	into	ADP
cana-5212	45	15	multiple	multiple	ADJ
cana-5212	45	16	categories	category	NOUN
cana-5212	45	17	.	.	PUNCT
cana-5212	46	1	output	output	NOUN
cana-5212	46	2	layer	layer	NOUN
cana-5212	46	3	:	:	PUNCT
cana-5212	46	4	the	the	DET
cana-5212	46	5	last	last	ADJ
cana-5212	46	6	layer	layer	NOUN
cana-5212	46	7	will	will	AUX
cana-5212	46	8	have	have	VERB
cana-5212	46	9	a	a	DET
cana-5212	46	10	softmax	softmax	ADJ
cana-5212	46	11	activation	activation	NOUN
cana-5212	46	12	that	that	PRON
cana-5212	46	13	gives	give	VERB
cana-5212	46	14	as	as	ADP
cana-5212	46	15	output	output	NOUN
cana-5212	46	16	the	the	DET
cana-5212	46	17	probability	probability	NOUN
cana-5212	46	18	distribution	distribution	NOUN
cana-5212	46	19	over	over	ADP
cana-5212	46	20	classes	class	NOUN
cana-5212	46	21	of	of	ADP
cana-5212	46	22	diseases	disease	NOUN
cana-5212	46	23	.	.	PUNCT
cana-5212	47	1	in	in	ADP
cana-5212	47	2	this	this	DET
cana-5212	47	3	way	way	NOUN
cana-5212	47	4	,	,	PUNCT
cana-5212	47	5	it	it	PRON
cana-5212	47	6	is	be	AUX
cana-5212	47	7	multi	multi	ADJ
cana-5212	47	8	-	-	ADJ
cana-5212	47	9	class	class	ADJ
cana-5212	47	10	classification	classification	NOUN
cana-5212	47	11	and	and	CCONJ
cana-5212	47	12	gives	give	VERB
cana-5212	47	13	the	the	DET
cana-5212	47	14	probability	probability	NOUN
cana-5212	47	15	for	for	ADP
cana-5212	47	16	every	every	DET
cana-5212	47	17	class	class	NOUN
cana-5212	47	18	of	of	ADP
cana-5212	47	19	diseases	disease	NOUN
cana-5212	47	20	against	against	ADP
cana-5212	47	21	the	the	DET
cana-5212	47	22	input	input	NOUN
cana-5212	47	23	image	image	NOUN
cana-5212	47	24	.	.	PUNCT
cana-5212	48	1	3.1.2	3.1.2	NUM
cana-5212	48	2	integration	integration	NOUN
cana-5212	48	3	of	of	ADP
cana-5212	48	4	fuzzy	fuzzy	ADJ
cana-5212	48	5	logic	logic	NOUN
cana-5212	48	6	:	:	PUNCT
cana-5212	48	7	fuzzy	fuzzy	ADJ
cana-5212	48	8	inference	inference	NOUN
cana-5212	48	9	system	system	NOUN
cana-5212	48	10	(	(	PUNCT
cana-5212	48	11	fis):fuzzy	fis):fuzzy	PROPN
cana-5212	48	12	logic	logic	NOUN
cana-5212	48	13	improves	improve	VERB
cana-5212	48	14	the	the	DET
cana-5212	48	15	algorithm	algorithm	NOUN
cana-5212	48	16	by	by	ADP
cana-5212	48	17	assessing	assess	VERB
cana-5212	48	18	the	the	DET
cana-5212	48	19	seriousness	seriousness	NOUN
cana-5212	48	20	of	of	ADP
cana-5212	48	21	the	the	DET
cana-5212	48	22	diseases	disease	NOUN
cana-5212	48	23	detected	detect	VERB
cana-5212	48	24	.	.	PUNCT
cana-5212	49	1	this	this	DET
cana-5212	49	2	fis	fis	PROPN
cana-5212	49	3	works	work	VERB
cana-5212	49	4	on	on	ADP
cana-5212	49	5	the	the	DET
cana-5212	49	6	outputs	output	NOUN
cana-5212	49	7	from	from	ADP
cana-5212	49	8	the	the	DET
cana-5212	49	9	cnn	cnn	PROPN
cana-5212	49	10	,	,	PUNCT
cana-5212	49	11	where	where	SCONJ
cana-5212	49	12	it	it	PRON
cana-5212	49	13	takes	take	VERB
cana-5212	49	14	the	the	DET
cana-5212	49	15	classification	classification	NOUN
cana-5212	49	16	results	result	NOUN
cana-5212	49	17	for	for	ADP
cana-5212	49	18	diseases	disease	NOUN
cana-5212	49	19	as	as	ADP
cana-5212	49	20	inputs	input	NOUN
cana-5212	49	21	.	.	PUNCT
cana-5212	50	1	inputs	input	NOUN
cana-5212	50	2	:	:	PUNCT
cana-5212	50	3	the	the	DET
cana-5212	50	4	inputs	input	NOUN
cana-5212	50	5	to	to	ADP
cana-5212	50	6	the	the	DET
cana-5212	50	7	fis	fis	PROPN
cana-5212	50	8	are	be	AUX
cana-5212	50	9	from	from	ADP
cana-5212	50	10	the	the	DET
cana-5212	50	11	probabilities	probability	NOUN
cana-5212	50	12	about	about	ADP
cana-5212	50	13	disease	disease	NOUN
cana-5212	50	14	classification	classification	NOUN
cana-5212	50	15	obtained	obtain	VERB
cana-5212	50	16	at	at	ADP
cana-5212	50	17	the	the	DET
cana-5212	50	18	output	output	NOUN
cana-5212	50	19	of	of	ADP
cana-5212	50	20	the	the	DET
cana-5212	50	21	softmax	softmax	NOUN
cana-5212	50	22	from	from	ADP
cana-5212	50	23	a	a	DET
cana-5212	50	24	cnn	cnn	PROPN
cana-5212	50	25	.	.	PUNCT
cana-5212	51	1	these	these	DET
cana-5212	51	2	probabilities	probability	NOUN
cana-5212	51	3	show	show	VERB
cana-5212	51	4	the	the	DET
cana-5212	51	5	level	level	NOUN
cana-5212	51	6	of	of	ADP
cana-5212	51	7	confidence	confidence	NOUN
cana-5212	51	8	of	of	ADP
cana-5212	51	9	the	the	DET
cana-5212	51	10	detected	detect	VERB
cana-5212	51	11	diseases	disease	NOUN
cana-5212	51	12	,	,	PUNCT
cana-5212	51	13	that	that	ADV
cana-5212	51	14	is	is	ADV
cana-5212	51	15	,	,	PUNCT
cana-5212	51	16	the	the	DET
cana-5212	51	17	classes	class	NOUN
cana-5212	51	18	.	.	PUNCT
cana-5212	52	1	fuzzy	fuzzy	ADJ
cana-5212	52	2	rules	rule	NOUN
cana-5212	52	3	:	:	PUNCT
cana-5212	52	4	fis	fis	PROPN
cana-5212	52	5	projects	project	VERB
cana-5212	52	6	the	the	DET
cana-5212	52	7	relation	relation	NOUN
cana-5212	52	8	of	of	ADP
cana-5212	52	9	the	the	DET
cana-5212	52	10	type	type	NOUN
cana-5212	52	11	of	of	ADP
cana-5212	52	12	diseases	disease	NOUN
cana-5212	52	13	with	with	ADP
cana-5212	52	14	their	their	PRON
cana-5212	52	15	corresponding	correspond	VERB
cana-5212	52	16	severity	severity	NOUN
cana-5212	52	17	levels	level	NOUN
cana-5212	52	18	through	through	ADP
cana-5212	52	19	a	a	DET
cana-5212	52	20	predefined	predefine	VERB
cana-5212	52	21	set	set	NOUN
cana-5212	52	22	of	of	ADP
cana-5212	52	23	fuzzy	fuzzy	ADJ
cana-5212	52	24	rules	rule	NOUN
cana-5212	52	25	.	.	PUNCT
cana-5212	53	1	such	such	ADJ
cana-5212	53	2	rules	rule	NOUN
cana-5212	53	3	,	,	PUNCT
cana-5212	53	4	therefore	therefore	ADV
cana-5212	53	5	,	,	PUNCT
cana-5212	53	6	would	would	AUX
cana-5212	53	7	be	be	AUX
cana-5212	53	8	based	base	VERB
cana-5212	53	9	on	on	ADP
cana-5212	53	10	empirical	empirical	ADJ
cana-5212	53	11	data	datum	NOUN
cana-5212	53	12	and	and	CCONJ
cana-5212	53	13	expert	expert	ADJ
cana-5212	53	14	knowledge	knowledge	NOUN
cana-5212	53	15	about	about	ADP
cana-5212	53	16	how	how	SCONJ
cana-5212	53	17	much	much	ADJ
cana-5212	53	18	the	the	DET
cana-5212	53	19	severity	severity	NOUN
cana-5212	53	20	of	of	ADP
cana-5212	53	21	each	each	DET
cana-5212	53	22	disease	disease	NOUN
cana-5212	53	23	changes	change	VERB
cana-5212	53	24	with	with	ADP
cana-5212	53	25	its	its	PRON
cana-5212	53	26	corresponding	corresponding	ADJ
cana-5212	53	27	detected	detect	VERB
cana-5212	53	28	confidence	confidence	NOUN
cana-5212	53	29	level	level	NOUN
cana-5212	53	30	.	.	PUNCT
cana-5212	54	1	for	for	ADP
cana-5212	54	2	example	example	NOUN
cana-5212	54	3	,	,	PUNCT
cana-5212	54	4	one	one	NUM
cana-5212	54	5	rule	rule	NOUN
cana-5212	54	6	could	could	AUX
cana-5212	54	7	be	be	AUX
cana-5212	54	8	:	:	PUNCT
cana-5212	54	9	if	if	SCONJ
cana-5212	54	10	a	a	DET
cana-5212	54	11	disease	disease	NOUN
cana-5212	54	12	is	be	AUX
cana-5212	54	13	detected	detect	VERB
cana-5212	54	14	with	with	ADP
cana-5212	54	15	high	high	ADJ
cana-5212	54	16	confidence	confidence	NOUN
cana-5212	54	17	,	,	PUNCT
cana-5212	54	18	then	then	ADV
cana-5212	54	19	it	it	PRON
cana-5212	54	20	has	have	VERB
cana-5212	54	21	high	high	ADJ
cana-5212	54	22	severity	severity	NOUN
cana-5212	54	23	.	.	PUNCT
cana-5212	55	1	output	output	NOUN
cana-5212	55	2	:	:	PUNCT
cana-5212	55	3	style	style	NOUN
cana-5212	55	4	type	type	NOUN
cana-5212	55	5	buckets	bucket	NOUN
cana-5212	55	6	performed	perform	VERB
cana-5212	55	7	poor	poor	ADJ
cana-5212	55	8	using	use	VERB
cana-5212	55	9	the	the	DET
cana-5212	55	10	proposed	propose	VERB
cana-5212	55	11	approach	approach	NOUN
cana-5212	55	12	.	.	PUNCT
cana-5212	56	1	the	the	DET
cana-5212	56	2	severity	severity	NOUN
cana-5212	56	3	level	level	NOUN
cana-5212	56	4	of	of	ADP
cana-5212	56	5	the	the	DET
cana-5212	56	6	harnessed	harness	VERB
cana-5212	56	7	disease	disease	NOUN
cana-5212	56	8	,	,	PUNCT
cana-5212	56	9	ranging	range	VERB
cana-5212	56	10	from	from	ADP
cana-5212	56	11	mild	mild	ADJ
cana-5212	56	12	to	to	ADP
cana-5212	56	13	severe	severe	ADJ
cana-5212	56	14	,	,	PUNCT
cana-5212	56	15	will	will	AUX
cana-5212	56	16	be	be	AUX
cana-5212	56	17	the	the	DET
cana-5212	56	18	output	output	NOUN
cana-5212	56	19	of	of	ADP
cana-5212	56	20	the	the	DET
cana-5212	56	21	fis	fis	PROPN
cana-5212	56	22	.	.	PUNCT
cana-5212	57	1	further	far	ADV
cana-5212	57	2	,	,	PUNCT
cana-5212	57	3	it	it	PRON
cana-5212	57	4	will	will	AUX
cana-5212	57	5	also	also	ADV
cana-5212	57	6	talk	talk	VERB
cana-5212	57	7	about	about	ADP
cana-5212	57	8	the	the	DET
cana-5212	57	9	treatments	treatment	NOUN
cana-5212	57	10	to	to	PART
cana-5212	57	11	be	be	AUX
cana-5212	57	12	prescribed	prescribe	VERB
cana-5212	57	13	depending	depend	VERB
cana-5212	57	14	on	on	ADP
cana-5212	57	15	the	the	DET
cana-5212	57	16	severity	severity	NOUN
cana-5212	57	17	level	level	NOUN
cana-5212	57	18	of	of	ADP
cana-5212	57	19	the	the	DET
cana-5212	57	20	disease	disease	NOUN
cana-5212	57	21	,	,	PUNCT
cana-5212	57	22	which	which	PRON
cana-5212	57	23	are	be	AUX
cana-5212	57	24	of	of	ADP
cana-5212	57	25	a	a	DET
cana-5212	57	26	practical	practical	ADJ
cana-5212	57	27	nature	nature	NOUN
cana-5212	57	28	in	in	ADP
cana-5212	57	29	taking	take	VERB
cana-5212	57	30	care	care	NOUN
cana-5212	57	31	of	of	ADP
cana-5212	57	32	the	the	DET
cana-5212	57	33	diseases	disease	NOUN
cana-5212	57	34	.	.	PUNCT
cana-5212	58	1	this	this	DET
cana-5212	58	2	raw	raw	ADJ
cana-5212	58	3	result	result	NOUN
cana-5212	58	4	on	on	ADP
cana-5212	58	5	the	the	DET
cana-5212	58	6	detection	detection	NOUN
cana-5212	58	7	would	would	AUX
cana-5212	58	8	,	,	PUNCT
cana-5212	58	9	therefore	therefore	ADV
cana-5212	58	10	,	,	PUNCT
cana-5212	58	11	be	be	AUX
cana-5212	58	12	useful	useful	ADJ
cana-5212	58	13	actionable	actionable	ADJ
cana-5212	58	14	intelligence	intelligence	NOUN
cana-5212	58	15	,	,	PUNCT
cana-5212	58	16	aiding	aid	VERB
cana-5212	58	17	effective	effective	ADJ
cana-5212	58	18	decision	decision	NOUN
cana-5212	58	19	-	-	PUNCT
cana-5212	58	20	making	making	NOUN
cana-5212	58	21	upon	upon	SCONJ
cana-5212	58	22	integration	integration	NOUN
cana-5212	58	23	with	with	ADP
cana-5212	58	24	cnn	cnn	PROPN
cana-5212	58	25	and	and	CCONJ
cana-5212	58	26	fis	fis	PROPN
cana-5212	58	27	.	.	PUNCT
cana-5212	59	1	3.1.3	3.1.3	NUM
cana-5212	59	2	flowchart	flowchart	NOUN
cana-5212	59	3	of	of	ADP
cana-5212	59	4	proposed	propose	VERB
cana-5212	59	5	algorithm	algorithm	NOUN
cana-5212	59	6	:	:	PUNCT
cana-5212	59	7	input	input	NOUN
cana-5212	59	8	image	image	NOUN
cana-5212	59	9	:	:	PUNCT
cana-5212	59	10	raw	raw	ADJ
cana-5212	59	11	image	image	NOUN
cana-5212	59	12	of	of	ADP
cana-5212	59	13	the	the	DET
cana-5212	59	14	leaf	leaf	NOUN
cana-5212	59	15	of	of	ADP
cana-5212	59	16	the	the	DET
cana-5212	59	17	plant	plant	NOUN
cana-5212	59	18	is	be	AUX
cana-5212	59	19	clicked	click	VERB
cana-5212	59	20	.	.	PUNCT
cana-5212	60	1	preprocessing	preprocessing	NOUN
cana-5212	60	2	:	:	PUNCT
cana-5212	60	3	do	do	VERB
cana-5212	60	4	the	the	DET
cana-5212	60	5	fundamental	fundamental	ADJ
cana-5212	60	6	preprocessing	preprocessing	NOUN
cana-5212	60	7	,	,	PUNCT
cana-5212	60	8	like	like	ADP
cana-5212	60	9	resizing	resize	VERB
cana-5212	60	10	and	and	CCONJ
cana-5212	60	11	normalizing	normalize	VERB
cana-5212	60	12	,	,	PUNCT
cana-5212	60	13	with	with	ADP
cana-5212	60	14	proper	proper	ADJ
cana-5212	60	15	parameters	parameter	NOUN
cana-5212	60	16	.	.	PUNCT
cana-5212	61	1	feature	feature	NOUN
cana-5212	61	2	extraction	extraction	NOUN
cana-5212	61	3	:	:	PUNCT
cana-5212	61	4	image	image	NOUN
cana-5212	61	5	input	input	NOUN
cana-5212	61	6	followed	follow	VERB
cana-5212	61	7	by	by	ADP
cana-5212	61	8	successive	successive	ADJ
cana-5212	61	9	convolution	convolution	NOUN
cana-5212	61	10	and	and	CCONJ
cana-5212	61	11	pooling	pool	VERB
cana-5212	61	12	layers	layer	NOUN
cana-5212	61	13	.	.	PUNCT
cana-5212	62	1	classification	classification	NOUN
cana-5212	62	2	:	:	PUNCT
cana-5212	62	3	all	all	DET
cana-5212	62	4	diseases	disease	NOUN
cana-5212	62	5	get	get	AUX
cana-5212	62	6	classified	classify	VERB
cana-5212	62	7	by	by	ADP
cana-5212	62	8	the	the	DET
cana-5212	62	9	help	help	NOUN
cana-5212	62	10	of	of	ADP
cana-5212	62	11	fully	fully	ADV
cana-5212	62	12	connected	connected	ADJ
cana-5212	62	13	layers	layer	NOUN
cana-5212	62	14	with	with	ADP
cana-5212	62	15	softmax	softmax	NOUN
cana-5212	62	16	communications	communication	NOUN
cana-5212	62	17	on	on	ADP
cana-5212	62	18	applied	apply	VERB
cana-5212	62	19	nonlinear	nonlinear	ADJ
cana-5212	62	20	analysis	analysis	NOUN
cana-5212	62	21	issn	issn	NOUN
cana-5212	62	22	:	:	PUNCT
cana-5212	62	23	1074	1074	NUM
cana-5212	62	24	-	-	PUNCT
cana-5212	62	25	133x	133x	NUM
cana-5212	62	26	vol	vol	NOUN
cana-5212	62	27	32	32	NUM
cana-5212	62	28	no	no	NOUN
cana-5212	62	29	.	.	PUNCT
cana-5212	63	1	8s	8s	PROPN
cana-5212	63	2	(	(	PUNCT
cana-5212	63	3	2025	2025	NUM
cana-5212	63	4	)	)	PUNCT
cana-5212	63	5	936	936	NUM
cana-5212	63	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	63	7	activation	activation	NOUN
cana-5212	63	8	.	.	PUNCT
cana-5212	64	1	severity	severity	NOUN
cana-5212	64	2	analysis	analysis	NOUN
cana-5212	64	3	:	:	PUNCT
cana-5212	64	4	feed	feed	VERB
cana-5212	64	5	the	the	DET
cana-5212	64	6	classification	classification	NOUN
cana-5212	64	7	results	result	NOUN
cana-5212	64	8	to	to	PART
cana-5212	64	9	fis	fis	PROPN
cana-5212	64	10	.	.	PUNCT
cana-5212	65	1	output	output	NOUN
cana-5212	65	2	generation	generation	NOUN
cana-5212	65	3	:	:	PUNCT
cana-5212	65	4	resultant	resultant	NOUN
cana-5212	65	5	degree	degree	NOUN
cana-5212	65	6	of	of	ADP
cana-5212	65	7	severity	severity	NOUN
cana-5212	65	8	along	along	ADP
cana-5212	65	9	with	with	ADP
cana-5212	65	10	the	the	DET
cana-5212	65	11	suggested	suggest	VERB
cana-5212	65	12	treatments	treatment	NOUN
cana-5212	65	13	.	.	PUNCT
cana-5212	66	1	steps	step	NOUN
cana-5212	66	2	followed	follow	VERB
cana-5212	66	3	in	in	ADP
cana-5212	66	4	the	the	DET
cana-5212	66	5	algorithm	algorithm	NOUN
cana-5212	66	6	:	:	PUNCT
cana-5212	66	7	input	input	NOUN
cana-5212	66	8	and	and	CCONJ
cana-5212	66	9	preprocessing	preprocesse	VERB
cana-5212	66	10	the	the	DET
cana-5212	66	11	algorithm	algorithm	NOUN
cana-5212	66	12	takes	take	VERB
cana-5212	66	13	raw	raw	ADJ
cana-5212	66	14	images	image	NOUN
cana-5212	66	15	of	of	ADP
cana-5212	66	16	leaves	leave	NOUN
cana-5212	66	17	as	as	ADP
cana-5212	66	18	input	input	NOUN
cana-5212	66	19	,	,	PUNCT
cana-5212	66	20	after	after	ADP
cana-5212	66	21	which	which	PRON
cana-5212	66	22	their	their	PRON
cana-5212	66	23	respective	respective	ADJ
cana-5212	66	24	features	feature	NOUN
cana-5212	66	25	are	be	AUX
cana-5212	66	26	applied	apply	VERB
cana-5212	66	27	,	,	PUNCT
cana-5212	66	28	like	like	ADP
cana-5212	66	29	resizing	resizing	NOUN
cana-5212	66	30	and	and	CCONJ
cana-5212	66	31	normalization	normalization	NOUN
cana-5212	66	32	,	,	PUNCT
cana-5212	66	33	to	to	PART
cana-5212	66	34	bring	bring	VERB
cana-5212	66	35	uniformity	uniformity	NOUN
cana-5212	66	36	.	.	PUNCT
cana-5212	67	1	feature	feature	NOUN
cana-5212	67	2	extraction	extraction	NOUN
cana-5212	67	3	using	use	VERB
cana-5212	67	4	cnn	cnn	PROPN
cana-5212	67	5	convolutional	convolutional	ADJ
cana-5212	67	6	layers	layer	NOUN
cana-5212	67	7	through	through	ADP
cana-5212	67	8	which	which	PRON
cana-5212	67	9	the	the	DET
cana-5212	67	10	pre	pre	ADJ
cana-5212	67	11	-	-	ADJ
cana-5212	67	12	processed	processed	ADJ
cana-5212	67	13	images	image	NOUN
cana-5212	67	14	can	can	AUX
cana-5212	67	15	be	be	AUX
cana-5212	67	16	fed	feed	VERB
cana-5212	67	17	,	,	PUNCT
cana-5212	67	18	features	feature	NOUN
cana-5212	67	19	are	be	AUX
cana-5212	67	20	then	then	ADV
cana-5212	67	21	extracted	extract	VERB
cana-5212	67	22	using	use	VERB
cana-5212	67	23	kernels	kernel	NOUN
cana-5212	67	24	,	,	PUNCT
cana-5212	67	25	further	far	ADV
cana-5212	67	26	tuned	tune	VERB
cana-5212	67	27	to	to	PART
cana-5212	67	28	reduce	reduce	VERB
cana-5212	67	29	their	their	PRON
cana-5212	67	30	dimensionality	dimensionality	NOUN
cana-5212	67	31	while	while	SCONJ
cana-5212	67	32	retaining	retain	VERB
cana-5212	67	33	essential	essential	ADJ
cana-5212	67	34	information	information	NOUN
cana-5212	67	35	through	through	ADP
cana-5212	67	36	pooling	pool	VERB
cana-5212	67	37	layers	layer	NOUN
cana-5212	67	38	.	.	PUNCT
cana-5212	68	1	classification	classification	NOUN
cana-5212	68	2	using	use	VERB
cana-5212	68	3	fully	fully	ADV
cana-5212	68	4	connected	connected	ADJ
cana-5212	68	5	layers	layer	NOUN
cana-5212	68	6	:	:	PUNCT
cana-5212	68	7	extracted	extract	VERB
cana-5212	68	8	features	feature	NOUN
cana-5212	68	9	are	be	AUX
cana-5212	68	10	flattened	flatten	VERB
cana-5212	68	11	and	and	CCONJ
cana-5212	68	12	passed	pass	VERB
cana-5212	68	13	through	through	ADP
cana-5212	68	14	fully	fully	ADV
cana-5212	68	15	connected	connected	ADJ
cana-5212	68	16	layers	layer	NOUN
cana-5212	68	17	to	to	PART
cana-5212	68	18	project	project	VERB
cana-5212	68	19	these	these	PRON
cana-5212	68	20	on	on	ADP
cana-5212	68	21	a	a	DET
cana-5212	68	22	vector	vector	NOUN
cana-5212	68	23	of	of	ADP
cana-5212	68	24	probability	probability	NOUN
cana-5212	68	25	for	for	ADP
cana-5212	68	26	each	each	DET
cana-5212	68	27	class	class	NOUN
cana-5212	68	28	of	of	ADP
cana-5212	68	29	the	the	DET
cana-5212	68	30	disease	disease	NOUN
cana-5212	68	31	.	.	PUNCT
cana-5212	69	1	severity	severity	NOUN
cana-5212	69	2	analysis	analysis	NOUN
cana-5212	69	3	using	use	VERB
cana-5212	69	4	fuzzy	fuzzy	ADJ
cana-5212	69	5	logic	logic	NOUN
cana-5212	69	6	:	:	PUNCT
cana-5212	69	7	these	these	DET
cana-5212	69	8	probabilities	probability	NOUN
cana-5212	69	9	for	for	ADP
cana-5212	69	10	classification	classification	NOUN
cana-5212	69	11	are	be	AUX
cana-5212	69	12	passed	pass	VERB
cana-5212	69	13	as	as	ADP
cana-5212	69	14	input	input	NOUN
cana-5212	69	15	to	to	ADP
cana-5212	69	16	the	the	DET
cana-5212	69	17	fuzzy	fuzzy	ADJ
cana-5212	69	18	inference	inference	NOUN
cana-5212	69	19	system	system	NOUN
cana-5212	69	20	.	.	PUNCT
cana-5212	70	1	the	the	DET
cana-5212	70	2	fis	fis	PROPN
cana-5212	70	3	further	far	ADV
cana-5212	70	4	evaluates	evaluate	VERB
cana-5212	70	5	the	the	DET
cana-5212	70	6	severity	severity	NOUN
cana-5212	70	7	of	of	ADP
cana-5212	70	8	the	the	DET
cana-5212	70	9	harnessed	harness	VERB
cana-5212	70	10	illness	illness	NOUN
cana-5212	70	11	with	with	ADP
cana-5212	70	12	fuzzy	fuzzy	ADJ
cana-5212	70	13	rules	rule	NOUN
cana-5212	70	14	and	and	CCONJ
cana-5212	70	15	tells	tell	VERB
cana-5212	70	16	the	the	DET
cana-5212	70	17	best	good	ADJ
cana-5212	70	18	treatment	treatment	NOUN
cana-5212	70	19	options	option	NOUN
cana-5212	70	20	.	.	PUNCT
cana-5212	71	1	output	output	NOUN
cana-5212	71	2	:	:	PUNCT
cana-5212	71	3	this	this	PRON
cana-5212	71	4	would	would	AUX
cana-5212	71	5	be	be	AUX
cana-5212	71	6	the	the	DET
cana-5212	71	7	final	final	ADJ
cana-5212	71	8	output	output	NOUN
cana-5212	71	9	of	of	ADP
cana-5212	71	10	the	the	DET
cana-5212	71	11	classified	classified	ADJ
cana-5212	71	12	disease	disease	NOUN
cana-5212	71	13	with	with	ADP
cana-5212	71	14	its	its	PRON
cana-5212	71	15	level	level	NOUN
cana-5212	71	16	of	of	ADP
cana-5212	71	17	severity	severity	NOUN
cana-5212	71	18	and	and	CCONJ
cana-5212	71	19	the	the	DET
cana-5212	71	20	suggested	suggested	ADJ
cana-5212	71	21	treatments	treatment	NOUN
cana-5212	71	22	,	,	PUNCT
cana-5212	71	23	hence	hence	ADV
cana-5212	71	24	a	a	DET
cana-5212	71	25	comprehensive	comprehensive	ADJ
cana-5212	71	26	solution	solution	NOUN
cana-5212	71	27	in	in	ADP
cana-5212	71	28	plant	plant	NOUN
cana-5212	71	29	disease	disease	NOUN
cana-5212	71	30	management	management	NOUN
cana-5212	71	31	.	.	PUNCT
cana-5212	72	1	this	this	DET
cana-5212	72	2	new	new	ADJ
cana-5212	72	3	approach	approach	NOUN
cana-5212	72	4	will	will	AUX
cana-5212	72	5	ensure	ensure	VERB
cana-5212	72	6	high	high	ADJ
cana-5212	72	7	accuracy	accuracy	NOUN
cana-5212	72	8	in	in	ADP
cana-5212	72	9	disease	disease	NOUN
cana-5212	72	10	detection	detection	NOUN
cana-5212	72	11	and	and	CCONJ
cana-5212	72	12	provide	provide	VERB
cana-5212	72	13	information	information	NOUN
cana-5212	72	14	about	about	ADP
cana-5212	72	15	the	the	DET
cana-5212	72	16	severity	severity	NOUN
cana-5212	72	17	of	of	ADP
cana-5212	72	18	diseases	disease	NOUN
cana-5212	72	19	to	to	PART
cana-5212	72	20	help	help	VERB
cana-5212	72	21	adopt	adopt	VERB
cana-5212	72	22	effective	effective	ADJ
cana-5212	72	23	and	and	CCONJ
cana-5212	72	24	timely	timely	ADJ
cana-5212	72	25	intervention	intervention	NOUN
cana-5212	72	26	strategies	strategy	NOUN
cana-5212	72	27	by	by	ADP
cana-5212	72	28	farmers	farmer	NOUN
cana-5212	72	29	.	.	PUNCT
cana-5212	73	1	3.1.4	3.1.4	NUM
cana-5212	73	2	cnn	cnn	PROPN
cana-5212	73	3	output	output	NOUN
cana-5212	73	4	function	function	NOUN
cana-5212	73	5	:	:	PUNCT
cana-5212	73	6	equation	equation	NOUN
cana-5212	73	7	for	for	ADP
cana-5212	73	8	the	the	DET
cana-5212	73	9	output	output	NOUN
cana-5212	73	10	of	of	ADP
cana-5212	73	11	the	the	DET
cana-5212	73	12	convolutional	convolutional	ADJ
cana-5212	73	13	layer	layer	NOUN
cana-5212	73	14	which	which	PRON
cana-5212	73	15	applies	apply	VERB
cana-5212	73	16	a	a	DET
cana-5212	73	17	relu	relu	NOUN
cana-5212	73	18	activation	activation	NOUN
cana-5212	73	19	function	function	NOUN
cana-5212	73	20	:	:	PUNCT
cana-5212	73	21	f(x)=max	f(x)=max	PROPN
cana-5212	73	22	(	(	PUNCT
cana-5212	73	23	0	0	NUM
cana-5212	73	24	,	,	PUNCT
cana-5212	73	25	x	x	X
cana-5212	73	26	)	)	PUNCT
cana-5212	73	27	this	this	DET
cana-5212	73	28	function	function	NOUN
cana-5212	73	29	is	be	AUX
cana-5212	73	30	applied	apply	VERB
cana-5212	73	31	element	element	ADJ
cana-5212	73	32	-	-	ADJ
cana-5212	73	33	wise	wise	ADJ
cana-5212	73	34	to	to	ADP
cana-5212	73	35	the	the	DET
cana-5212	73	36	output	output	NOUN
cana-5212	73	37	of	of	ADP
cana-5212	73	38	each	each	DET
cana-5212	73	39	convolutional	convolutional	ADJ
cana-5212	73	40	filter	filter	NOUN
cana-5212	73	41	to	to	PART
cana-5212	73	42	introduce	introduce	VERB
cana-5212	73	43	nonlinearity	nonlinearity	NOUN
cana-5212	73	44	.	.	PUNCT
cana-5212	74	1	fuzzy	fuzzy	ADJ
cana-5212	74	2	inference	inference	NOUN
cana-5212	74	3	system	system	NOUN
cana-5212	74	4	:	:	PUNCT
cana-5212	74	5	the	the	DET
cana-5212	74	6	fuzzy	fuzzy	ADJ
cana-5212	74	7	membership	membership	NOUN
cana-5212	74	8	function	function	NOUN
cana-5212	74	9	,	,	PUNCT
cana-5212	74	10	which	which	PRON
cana-5212	74	11	can	can	AUX
cana-5212	74	12	be	be	AUX
cana-5212	74	13	triangular	triangular	ADJ
cana-5212	74	14	,	,	PUNCT
cana-5212	74	15	for	for	ADP
cana-5212	74	16	a	a	DET
cana-5212	74	17	disease	disease	NOUN
cana-5212	74	18	severity	severity	NOUN
cana-5212	74	19	level	level	NOUN
cana-5212	74	20	might	might	AUX
cana-5212	74	21	be	be	AUX
cana-5212	74	22	defined	define	VERB
cana-5212	74	23	as	as	ADP
cana-5212	74	24	:	:	PUNCT
cana-5212	74	25	μa(x)=max(min	μa(x)=max(min	ADJ
cana-5212	74	26	𝑥−𝑎	𝑥−𝑎	PROPN
cana-5212	74	27	𝑏−𝑎	𝑏−𝑎	PROPN
cana-5212	74	28	,	,	PUNCT
cana-5212	74	29	𝑐−𝑥	𝑐−𝑥	NOUN
cana-5212	74	30	𝑐−𝑏	𝑐−𝑏	X
cana-5212	74	31	)	)	PUNCT
cana-5212	74	32	,	,	PUNCT
cana-5212	74	33	0	0	NUM
cana-5212	74	34	here	here	ADV
cana-5212	74	35	,	,	PUNCT
cana-5212	74	36	a	a	DET
cana-5212	74	37	,	,	PUNCT
cana-5212	74	38	b	b	NOUN
cana-5212	74	39	,	,	PUNCT
cana-5212	74	40	and	and	CCONJ
cana-5212	74	41	c	c	PROPN
cana-5212	74	42	represent	represent	VERB
cana-5212	74	43	the	the	DET
cana-5212	74	44	parameters	parameter	NOUN
cana-5212	74	45	that	that	PRON
cana-5212	74	46	shape	shape	VERB
cana-5212	74	47	the	the	DET
cana-5212	74	48	membership	membership	NOUN
cana-5212	74	49	function	function	NOUN
cana-5212	74	50	,	,	PUNCT
cana-5212	74	51	adjusting	adjust	VERB
cana-5212	74	52	how	how	SCONJ
cana-5212	74	53	the	the	DET
cana-5212	74	54	input	input	NOUN
cana-5212	74	55	(	(	PUNCT
cana-5212	74	56	disease	disease	NOUN
cana-5212	74	57	detection	detection	NOUN
cana-5212	74	58	confidence	confidence	NOUN
cana-5212	74	59	level	level	NOUN
cana-5212	74	60	)	)	PUNCT
cana-5212	74	61	is	be	AUX
cana-5212	74	62	mapped	map	VERB
cana-5212	74	63	to	to	ADP
cana-5212	74	64	a	a	DET
cana-5212	74	65	membership	membership	NOUN
cana-5212	74	66	value	value	NOUN
cana-5212	74	67	for	for	ADP
cana-5212	74	68	a	a	DET
cana-5212	74	69	particular	particular	ADJ
cana-5212	74	70	fuzzy	fuzzy	ADJ
cana-5212	74	71	set	set	NOUN
cana-5212	74	72	(	(	PUNCT
cana-5212	74	73	severity	severity	NOUN
cana-5212	74	74	level	level	NOUN
cana-5212	74	75	)	)	PUNCT
cana-5212	74	76	.	.	PUNCT
cana-5212	75	1	convolution	convolution	NOUN
cana-5212	75	2	operation	operation	NOUN
cana-5212	75	3	the	the	DET
cana-5212	75	4	convolution	convolution	NOUN
cana-5212	75	5	operation	operation	NOUN
cana-5212	75	6	in	in	ADP
cana-5212	75	7	a	a	DET
cana-5212	75	8	cnn	cnn	NOUN
cana-5212	75	9	is	be	AUX
cana-5212	75	10	a	a	DET
cana-5212	75	11	fundamental	fundamental	ADJ
cana-5212	75	12	component	component	NOUN
cana-5212	75	13	where	where	SCONJ
cana-5212	75	14	filters	filter	NOUN
cana-5212	75	15	are	be	AUX
cana-5212	75	16	applied	apply	VERB
cana-5212	75	17	to	to	ADP
cana-5212	75	18	the	the	DET
cana-5212	75	19	input	input	NOUN
cana-5212	75	20	data	datum	NOUN
cana-5212	75	21	to	to	PART
cana-5212	75	22	create	create	VERB
cana-5212	75	23	feature	feature	NOUN
cana-5212	75	24	maps	map	NOUN
cana-5212	75	25	.	.	PUNCT
cana-5212	76	1	the	the	DET
cana-5212	76	2	mathematical	mathematical	ADJ
cana-5212	76	3	expression	expression	NOUN
cana-5212	76	4	for	for	ADP
cana-5212	76	5	this	this	DET
cana-5212	76	6	operation	operation	NOUN
cana-5212	76	7	is	be	AUX
cana-5212	76	8	:	:	PUNCT
cana-5212	76	9	s(t)=(x∗w)(t)=∑	s(t)=(x∗w)(t)=∑	PROPN
cana-5212	76	10	𝑥(a)∞	𝑥(a)∞	VERB
cana-5212	76	11	𝑎=−∞	𝑎=−∞	PUNCT
cana-5212	77	1	∙	∙	PROPN
cana-5212	77	2	𝑤(𝑡	𝑤(𝑡	NUM
cana-5212	77	3	−	−	NUM
cana-5212	77	4	𝑎	𝑎	NOUN
cana-5212	77	5	)	)	PUNCT
cana-5212	77	6	where	where	SCONJ
cana-5212	77	7	:	:	PUNCT
cana-5212	77	8	x	x	X
cana-5212	77	9	is	be	AUX
cana-5212	77	10	the	the	DET
cana-5212	77	11	input	input	NOUN
cana-5212	77	12	image	image	NOUN
cana-5212	77	13	.	.	PUNCT
cana-5212	78	1	communications	communication	NOUN
cana-5212	78	2	on	on	ADP
cana-5212	78	3	applied	apply	VERB
cana-5212	78	4	nonlinear	nonlinear	ADJ
cana-5212	78	5	analysis	analysis	NOUN
cana-5212	78	6	issn	issn	NOUN
cana-5212	78	7	:	:	PUNCT
cana-5212	78	8	1074	1074	NUM
cana-5212	78	9	-	-	PUNCT
cana-5212	78	10	133x	133x	NUM
cana-5212	78	11	vol	vol	NOUN
cana-5212	78	12	32	32	NUM
cana-5212	78	13	no	no	NOUN
cana-5212	78	14	.	.	PUNCT
cana-5212	79	1	8s	8s	PROPN
cana-5212	79	2	(	(	PUNCT
cana-5212	79	3	2025	2025	NUM
cana-5212	79	4	)	)	PUNCT
cana-5212	79	5	937	937	NUM
cana-5212	79	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	79	7	w	w	NOUN
cana-5212	79	8	is	be	AUX
cana-5212	79	9	the	the	DET
cana-5212	79	10	kernel	kernel	NOUN
cana-5212	79	11	/	/	SYM
cana-5212	79	12	filter	filter	NOUN
cana-5212	79	13	.	.	PUNCT
cana-5212	80	1	s(t	s(t	PROPN
cana-5212	80	2	)	)	PUNCT
cana-5212	80	3	is	be	AUX
cana-5212	80	4	the	the	DET
cana-5212	80	5	output	output	NOUN
cana-5212	80	6	feature	feature	NOUN
cana-5212	80	7	map	map	NOUN
cana-5212	80	8	.	.	PUNCT
cana-5212	81	1	t	t	PROPN
cana-5212	81	2	represents	represent	VERB
cana-5212	81	3	the	the	DET
cana-5212	81	4	position	position	NOUN
cana-5212	81	5	in	in	ADP
cana-5212	81	6	the	the	DET
cana-5212	81	7	output	output	NOUN
cana-5212	81	8	feature	feature	NOUN
cana-5212	81	9	map	map	NOUN
cana-5212	81	10	.	.	PUNCT
cana-5212	82	1	this	this	DET
cana-5212	82	2	operation	operation	NOUN
cana-5212	82	3	slides	slide	VERB
cana-5212	82	4	the	the	DET
cana-5212	82	5	filter	filter	NOUN
cana-5212	82	6	across	across	ADP
cana-5212	82	7	the	the	DET
cana-5212	82	8	input	input	NOUN
cana-5212	82	9	image	image	NOUN
cana-5212	82	10	(	(	PUNCT
cana-5212	82	11	or	or	CCONJ
cana-5212	82	12	previous	previous	ADJ
cana-5212	82	13	layer	layer	NOUN
cana-5212	82	14	feature	feature	NOUN
cana-5212	82	15	map	map	NOUN
cana-5212	82	16	)	)	PUNCT
cana-5212	82	17	to	to	PART
cana-5212	82	18	produce	produce	VERB
cana-5212	82	19	a	a	DET
cana-5212	82	20	feature	feature	NOUN
cana-5212	82	21	map	map	NOUN
cana-5212	82	22	,	,	PUNCT
cana-5212	82	23	highlighting	highlight	VERB
cana-5212	82	24	specific	specific	ADJ
cana-5212	82	25	features	feature	NOUN
cana-5212	82	26	of	of	ADP
cana-5212	82	27	the	the	DET
cana-5212	82	28	input	input	NOUN
cana-5212	82	29	.	.	PUNCT
cana-5212	83	1	activation	activation	NOUN
cana-5212	83	2	function	function	NOUN
cana-5212	83	3	relu	relu	NOUN
cana-5212	83	4	(	(	PUNCT
cana-5212	83	5	rectified	rectify	VERB
cana-5212	83	6	linear	linear	NOUN
cana-5212	83	7	unit	unit	NOUN
cana-5212	83	8	)	)	PUNCT
cana-5212	83	9	is	be	AUX
cana-5212	83	10	one	one	NUM
cana-5212	83	11	of	of	ADP
cana-5212	83	12	the	the	DET
cana-5212	83	13	most	most	ADV
cana-5212	83	14	commonly	commonly	ADV
cana-5212	83	15	used	use	VERB
cana-5212	83	16	activation	activation	NOUN
cana-5212	83	17	functions	function	NOUN
cana-5212	83	18	in	in	ADP
cana-5212	83	19	cnns	cnn	NOUN
cana-5212	83	20	,	,	PUNCT
cana-5212	83	21	defined	define	VERB
cana-5212	83	22	as	as	ADP
cana-5212	83	23	:	:	PUNCT
cana-5212	83	24	f(x)=max(0	f(x)=max(0	NUM
cana-5212	83	25	,	,	PUNCT
cana-5212	83	26	x	x	NOUN
cana-5212	83	27	)	)	PUNCT
cana-5212	83	28	where	where	SCONJ
cana-5212	83	29	:	:	PUNCT
cana-5212	83	30	x	x	X
cana-5212	83	31	is	be	AUX
cana-5212	83	32	the	the	DET
cana-5212	83	33	input	input	NOUN
cana-5212	83	34	to	to	ADP
cana-5212	83	35	the	the	DET
cana-5212	83	36	neuron	neuron	NOUN
cana-5212	83	37	(	(	PUNCT
cana-5212	83	38	usually	usually	ADV
cana-5212	83	39	the	the	DET
cana-5212	83	40	output	output	NOUN
cana-5212	83	41	from	from	ADP
cana-5212	83	42	the	the	DET
cana-5212	83	43	convolution	convolution	NOUN
cana-5212	83	44	or	or	CCONJ
cana-5212	83	45	fully	fully	ADV
cana-5212	83	46	connected	connect	VERB
cana-5212	83	47	layer	layer	NOUN
cana-5212	83	48	)	)	PUNCT
cana-5212	83	49	.	.	PUNCT
cana-5212	84	1	this	this	DET
cana-5212	84	2	function	function	NOUN
cana-5212	84	3	introduces	introduce	VERB
cana-5212	84	4	non	non	ADJ
cana-5212	84	5	-	-	NOUN
cana-5212	84	6	linearity	linearity	NOUN
cana-5212	84	7	into	into	ADP
cana-5212	84	8	the	the	DET
cana-5212	84	9	model	model	NOUN
cana-5212	84	10	,	,	PUNCT
cana-5212	84	11	allowing	allow	VERB
cana-5212	84	12	the	the	DET
cana-5212	84	13	network	network	NOUN
cana-5212	84	14	to	to	PART
cana-5212	84	15	learn	learn	VERB
cana-5212	84	16	more	more	ADJ
cana-5212	84	17	complex	complex	ADJ
cana-5212	84	18	patterns	pattern	NOUN
cana-5212	84	19	.	.	PUNCT
cana-5212	85	1	pooling	pool	VERB
cana-5212	85	2	operation	operation	NOUN
cana-5212	85	3	pooling	pool	VERB
cana-5212	85	4	layers	layer	NOUN
cana-5212	85	5	reduce	reduce	VERB
cana-5212	85	6	the	the	DET
cana-5212	85	7	spatial	spatial	ADJ
cana-5212	85	8	dimensions	dimension	NOUN
cana-5212	85	9	(	(	PUNCT
cana-5212	85	10	height	height	NOUN
cana-5212	85	11	and	and	CCONJ
cana-5212	85	12	width	width	ADJ
cana-5212	85	13	,	,	PUNCT
cana-5212	85	14	but	but	CCONJ
cana-5212	85	15	not	not	PART
cana-5212	85	16	depth	depth	NOUN
cana-5212	85	17	)	)	PUNCT
cana-5212	85	18	of	of	ADP
cana-5212	85	19	the	the	DET
cana-5212	85	20	input	input	NOUN
cana-5212	85	21	volume	volume	NOUN
cana-5212	85	22	for	for	ADP
cana-5212	85	23	the	the	DET
cana-5212	85	24	next	next	ADJ
cana-5212	85	25	convolution	convolution	NOUN
cana-5212	85	26	layer	layer	NOUN
cana-5212	85	27	.	.	PUNCT
cana-5212	86	1	a	a	DET
cana-5212	86	2	common	common	ADJ
cana-5212	86	3	pooling	pooling	NOUN
cana-5212	86	4	operation	operation	NOUN
cana-5212	86	5	is	be	AUX
cana-5212	86	6	max	max	PROPN
cana-5212	86	7	pooling	pooling	NOUN
cana-5212	86	8	,	,	PUNCT
cana-5212	86	9	which	which	PRON
cana-5212	86	10	can	can	AUX
cana-5212	86	11	be	be	AUX
cana-5212	86	12	mathematically	mathematically	ADV
cana-5212	86	13	described	describe	VERB
cana-5212	86	14	as	as	ADP
cana-5212	86	15	:	:	PUNCT
cana-5212	86	16	y	y	NOUN
cana-5212	86	17	=	=	NOUN
cana-5212	86	18	maxmax	maxmax	NOUN
cana-5212	86	19	𝑖𝑗∈𝑅	𝑖𝑗∈𝑅	PROPN
cana-5212	86	20	𝑥ij	𝑥ij	NOUN
cana-5212	86	21	where	where	SCONJ
cana-5212	86	22	:	:	PUNCT
cana-5212	86	23	y	y	PROPN
cana-5212	86	24	is	be	AUX
cana-5212	86	25	the	the	DET
cana-5212	86	26	output	output	NOUN
cana-5212	86	27	of	of	ADP
cana-5212	86	28	the	the	DET
cana-5212	86	29	pooling	pool	VERB
cana-5212	86	30	operation	operation	NOUN
cana-5212	86	31	.	.	PUNCT
cana-5212	87	1	xij	xij	PROPN
cana-5212	87	2	represents	represent	VERB
cana-5212	87	3	the	the	DET
cana-5212	87	4	elements	element	NOUN
cana-5212	87	5	of	of	ADP
cana-5212	87	6	the	the	DET
cana-5212	87	7	sub	sub	NOUN
cana-5212	87	8	-	-	NOUN
cana-5212	87	9	region	region	ADJ
cana-5212	87	10	r	r	NOUN
cana-5212	87	11	of	of	ADP
cana-5212	87	12	the	the	DET
cana-5212	87	13	input	input	NOUN
cana-5212	87	14	image	image	NOUN
cana-5212	87	15	or	or	CCONJ
cana-5212	87	16	feature	feature	NOUN
cana-5212	87	17	map	map	NOUN
cana-5212	87	18	over	over	ADP
cana-5212	87	19	which	which	PRON
cana-5212	87	20	the	the	DET
cana-5212	87	21	pooling	pooling	NOUN
cana-5212	87	22	operation	operation	NOUN
cana-5212	87	23	is	be	AUX
cana-5212	87	24	applied	apply	VERB
cana-5212	87	25	.	.	PUNCT
cana-5212	88	1	max	max	PROPN
cana-5212	88	2	pooling	pooling	PROPN
cana-5212	88	3	takes	take	VERB
cana-5212	88	4	the	the	DET
cana-5212	88	5	maximum	maximum	ADJ
cana-5212	88	6	value	value	NOUN
cana-5212	88	7	from	from	ADP
cana-5212	88	8	the	the	DET
cana-5212	88	9	region	region	NOUN
cana-5212	88	10	r	r	NOUN
cana-5212	88	11	of	of	ADP
cana-5212	88	12	the	the	DET
cana-5212	88	13	input	input	NOUN
cana-5212	88	14	.	.	PUNCT
cana-5212	89	1	fully	fully	ADV
cana-5212	89	2	connected	connect	VERB
cana-5212	89	3	layer	layer	NOUN
cana-5212	89	4	after	after	ADP
cana-5212	89	5	several	several	ADJ
cana-5212	89	6	convolutional	convolutional	ADJ
cana-5212	89	7	and	and	CCONJ
cana-5212	89	8	pooling	pool	VERB
cana-5212	89	9	layers	layer	NOUN
cana-5212	89	10	,	,	PUNCT
cana-5212	89	11	cnn	cnn	PROPN
cana-5212	89	12	architectures	architecture	NOUN
cana-5212	89	13	typically	typically	ADV
cana-5212	89	14	include	include	VERB
cana-5212	89	15	one	one	NUM
cana-5212	89	16	or	or	CCONJ
cana-5212	89	17	more	more	ADV
cana-5212	89	18	fully	fully	ADV
cana-5212	89	19	connected	connected	ADJ
cana-5212	89	20	layers	layer	NOUN
cana-5212	89	21	(	(	PUNCT
cana-5212	89	22	dense	dense	ADJ
cana-5212	89	23	layers	layer	NOUN
cana-5212	89	24	)	)	PUNCT
cana-5212	89	25	,	,	PUNCT
cana-5212	89	26	where	where	SCONJ
cana-5212	89	27	every	every	DET
cana-5212	89	28	input	input	NOUN
cana-5212	89	29	is	be	AUX
cana-5212	89	30	connected	connect	VERB
cana-5212	89	31	to	to	ADP
cana-5212	89	32	every	every	DET
cana-5212	89	33	output	output	NOUN
cana-5212	89	34	by	by	ADP
cana-5212	89	35	a	a	DET
cana-5212	89	36	learned	learn	VERB
cana-5212	89	37	weight	weight	NOUN
cana-5212	89	38	.	.	PUNCT
cana-5212	90	1	the	the	DET
cana-5212	90	2	mathematical	mathematical	ADJ
cana-5212	90	3	representation	representation	NOUN
cana-5212	90	4	is	be	AUX
cana-5212	90	5	:	:	PUNCT
cana-5212	90	6	y	y	X
cana-5212	90	7	=	=	PROPN
cana-5212	90	8	wx+b	wx+b	PROPN
cana-5212	90	9	where	where	SCONJ
cana-5212	90	10	:	:	PUNCT
cana-5212	90	11	w	w	NOUN
cana-5212	90	12	represents	represent	VERB
cana-5212	90	13	the	the	DET
cana-5212	90	14	weight	weight	NOUN
cana-5212	90	15	matrix	matrix	NOUN
cana-5212	90	16	.	.	PUNCT
cana-5212	91	1	x	x	PRON
cana-5212	91	2	is	be	AUX
cana-5212	91	3	the	the	DET
cana-5212	91	4	input	input	NOUN
cana-5212	91	5	vector	vector	NOUN
cana-5212	91	6	to	to	ADP
cana-5212	91	7	the	the	DET
cana-5212	91	8	fully	fully	ADV
cana-5212	91	9	connected	connected	ADJ
cana-5212	91	10	layer	layer	NOUN
cana-5212	91	11	.	.	PUNCT
cana-5212	92	1	b	b	NOUN
cana-5212	92	2	is	be	AUX
cana-5212	92	3	the	the	DET
cana-5212	92	4	bias	bias	NOUN
cana-5212	92	5	vector	vector	NOUN
cana-5212	92	6	.	.	PUNCT
cana-5212	93	1	communications	communication	NOUN
cana-5212	93	2	on	on	ADP
cana-5212	93	3	applied	apply	VERB
cana-5212	93	4	nonlinear	nonlinear	ADJ
cana-5212	93	5	analysis	analysis	NOUN
cana-5212	93	6	issn	issn	NOUN
cana-5212	93	7	:	:	PUNCT
cana-5212	93	8	1074	1074	NUM
cana-5212	93	9	-	-	PUNCT
cana-5212	93	10	133x	133x	NUM
cana-5212	93	11	vol	vol	NOUN
cana-5212	93	12	32	32	NUM
cana-5212	93	13	no	no	NOUN
cana-5212	93	14	.	.	PUNCT
cana-5212	94	1	8s	8s	PROPN
cana-5212	94	2	(	(	PUNCT
cana-5212	94	3	2025	2025	NUM
cana-5212	94	4	)	)	PUNCT
cana-5212	94	5	938	938	NUM
cana-5212	94	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	94	7	y	y	PROPN
cana-5212	94	8	is	be	AUX
cana-5212	94	9	the	the	DET
cana-5212	94	10	output	output	NOUN
cana-5212	94	11	vector	vector	NOUN
cana-5212	94	12	.	.	PUNCT
cana-5212	95	1	softmax	softmax	PROPN
cana-5212	95	2	function	function	NOUN
cana-5212	95	3	in	in	ADP
cana-5212	95	4	classification	classification	NOUN
cana-5212	95	5	tasks	task	NOUN
cana-5212	95	6	,	,	PUNCT
cana-5212	95	7	the	the	DET
cana-5212	95	8	softmax	softmax	NOUN
cana-5212	95	9	function	function	NOUN
cana-5212	95	10	is	be	AUX
cana-5212	95	11	often	often	ADV
cana-5212	95	12	applied	apply	VERB
cana-5212	95	13	in	in	ADP
cana-5212	95	14	the	the	DET
cana-5212	95	15	output	output	NOUN
cana-5212	95	16	layer	layer	NOUN
cana-5212	95	17	of	of	ADP
cana-5212	95	18	cnns	cnn	NOUN
cana-5212	95	19	to	to	PART
cana-5212	95	20	normalize	normalize	VERB
cana-5212	95	21	the	the	DET
cana-5212	95	22	output	output	NOUN
cana-5212	95	23	to	to	ADP
cana-5212	95	24	a	a	DET
cana-5212	95	25	probability	probability	NOUN
cana-5212	95	26	distribution	distribution	NOUN
cana-5212	95	27	over	over	ADP
cana-5212	95	28	predicted	predict	VERB
cana-5212	95	29	output	output	NOUN
cana-5212	95	30	classes	class	NOUN
cana-5212	95	31	,	,	PUNCT
cana-5212	95	32	based	base	VERB
cana-5212	95	33	on	on	ADP
cana-5212	95	34	the	the	DET
cana-5212	95	35	exponentials	exponential	NOUN
cana-5212	95	36	of	of	ADP
cana-5212	95	37	the	the	DET
cana-5212	95	38	input	input	NOUN
cana-5212	95	39	numbers	number	NOUN
cana-5212	95	40	.	.	PUNCT
cana-5212	96	1	the	the	DET
cana-5212	96	2	softmax	softmax	NOUN
cana-5212	96	3	function	function	NOUN
cana-5212	96	4	is	be	AUX
cana-5212	96	5	defined	define	VERB
cana-5212	96	6	as	as	ADP
cana-5212	96	7	:	:	PUNCT
cana-5212	96	8	σ(z)i	σ(z)i	PROPN
cana-5212	96	9	=	=	PUNCT
cana-5212	96	10	𝑒𝑧𝑖	𝑒𝑧𝑖	PROPN
cana-5212	96	11	∑	∑	PROPN
cana-5212	96	12	𝑒	𝑒	PROPN
cana-5212	96	13	𝑧𝑗𝐾	𝑧𝑗𝐾	PROPN
cana-5212	96	14	𝑗=1	𝑗=1	PROPN
cana-5212	96	15	where	where	SCONJ
cana-5212	96	16	:	:	PUNCT
cana-5212	96	17	z	z	NOUN
cana-5212	96	18	is	be	AUX
cana-5212	96	19	the	the	DET
cana-5212	96	20	input	input	NOUN
cana-5212	96	21	vector	vector	NOUN
cana-5212	96	22	to	to	ADP
cana-5212	96	23	the	the	DET
cana-5212	96	24	softmax	softmax	NOUN
cana-5212	96	25	function	function	NOUN
cana-5212	96	26	.	.	PUNCT
cana-5212	97	1	k	k	PROPN
cana-5212	97	2	is	be	AUX
cana-5212	97	3	the	the	DET
cana-5212	97	4	number	number	NOUN
cana-5212	97	5	of	of	ADP
cana-5212	97	6	classes	class	NOUN
cana-5212	97	7	.	.	PUNCT
cana-5212	98	1	σ(z)iis	σ(z)iis	VERB
cana-5212	98	2	the	the	DET
cana-5212	98	3	probability	probability	NOUN
cana-5212	98	4	that	that	SCONJ
cana-5212	98	5	the	the	DET
cana-5212	98	6	input	input	NOUN
cana-5212	98	7	belongs	belong	VERB
cana-5212	98	8	to	to	ADP
cana-5212	98	9	class	class	NOUN
cana-5212	98	10	i.	i.	NOUN
cana-5212	98	11	these	these	DET
cana-5212	98	12	formulas	formula	NOUN
cana-5212	98	13	highlight	highlight	VERB
cana-5212	98	14	the	the	DET
cana-5212	98	15	sequence	sequence	NOUN
cana-5212	98	16	of	of	ADP
cana-5212	98	17	operations	operation	NOUN
cana-5212	98	18	that	that	PRON
cana-5212	98	19	allow	allow	VERB
cana-5212	98	20	cnns	cnn	NOUN
cana-5212	98	21	to	to	PART
cana-5212	98	22	perform	perform	VERB
cana-5212	98	23	image	image	NOUN
cana-5212	98	24	-	-	PUNCT
cana-5212	98	25	based	base	VERB
cana-5212	98	26	classification	classification	NOUN
cana-5212	98	27	tasks	task	NOUN
cana-5212	98	28	such	such	ADJ
cana-5212	98	29	as	as	ADP
cana-5212	98	30	plant	plant	NOUN
cana-5212	98	31	disease	disease	NOUN
cana-5212	98	32	detection	detection	NOUN
cana-5212	98	33	.	.	PUNCT
cana-5212	99	1	3.1.5	3.1.5	NUM
cana-5212	99	2	step	step	NOUN
cana-5212	99	3	-	-	PUNCT
cana-5212	99	4	by	by	ADP
cana-5212	99	5	-	-	PUNCT
cana-5212	99	6	step	step	NOUN
cana-5212	99	7	cnn	cnn	PROPN
cana-5212	99	8	calculation	calculation	NOUN
cana-5212	99	9	example	example	NOUN
cana-5212	99	10	example	example	NOUN
cana-5212	99	11	setup	setup	NOUN
cana-5212	99	12	input	input	NOUN
cana-5212	99	13	image	image	NOUN
cana-5212	99	14	(	(	PUNCT
cana-5212	99	15	3x3	3x3	NUM
cana-5212	99	16	matrix	matrix	NOUN
cana-5212	99	17	):	):	PUNCT
cana-5212	99	18	x	x	X
cana-5212	99	19	=	=	PUNCT
cana-5212	99	20	[	[	PUNCT
cana-5212	99	21	1	1	NUM
cana-5212	99	22	2	2	NUM
cana-5212	99	23	1	1	NUM
cana-5212	99	24	0	0	NUM
cana-5212	99	25	1	1	NUM
cana-5212	99	26	0	0	NUM
cana-5212	99	27	2	2	NUM
cana-5212	99	28	1	1	NUM
cana-5212	99	29	2	2	NUM
cana-5212	99	30	]	]	PUNCT
cana-5212	99	31	filter	filter	NOUN
cana-5212	99	32	/	/	SYM
cana-5212	99	33	kernel	kernel	PROPN
cana-5212	99	34	(	(	PUNCT
cana-5212	99	35	2x2	2x2	NUM
cana-5212	99	36	matrix	matrix	NOUN
cana-5212	99	37	):	):	PUNCT
cana-5212	99	38	w	w	NOUN
cana-5212	99	39	=	=	PUNCT
cana-5212	99	40	[	[	PUNCT
cana-5212	99	41	1	1	NUM
cana-5212	99	42	0	0	NUM
cana-5212	99	43	0	0	NUM
cana-5212	99	44	−1	−1	NOUN
cana-5212	99	45	]	]	PUNCT
cana-5212	99	46	stride	stride	ADJ
cana-5212	99	47	:	:	PUNCT
cana-5212	99	48	1	1	NUM
cana-5212	99	49	padding	padding	NOUN
cana-5212	99	50	:	:	PUNCT
cana-5212	99	51	0	0	PUNCT
cana-5212	99	52	(	(	PUNCT
cana-5212	99	53	valid	valid	ADJ
cana-5212	99	54	convolution	convolution	NOUN
cana-5212	99	55	)	)	PUNCT
cana-5212	99	56	step	step	NOUN
cana-5212	99	57	1	1	NUM
cana-5212	99	58	:	:	PUNCT
cana-5212	99	59	convolution	convolution	NOUN
cana-5212	99	60	operation	operation	NOUN
cana-5212	99	61	the	the	DET
cana-5212	99	62	convolution	convolution	NOUN
cana-5212	99	63	operation	operation	NOUN
cana-5212	99	64	involves	involve	VERB
cana-5212	99	65	sliding	slide	VERB
cana-5212	99	66	the	the	DET
cana-5212	99	67	filter	filter	NOUN
cana-5212	99	68	over	over	ADP
cana-5212	99	69	the	the	DET
cana-5212	99	70	input	input	NOUN
cana-5212	99	71	image	image	NOUN
cana-5212	99	72	and	and	CCONJ
cana-5212	99	73	performing	perform	VERB
cana-5212	99	74	elementwise	elementwise	ADJ
cana-5212	99	75	multiplication	multiplication	NOUN
cana-5212	99	76	and	and	CCONJ
cana-5212	99	77	summation	summation	NOUN
cana-5212	99	78	at	at	ADP
cana-5212	99	79	each	each	DET
cana-5212	99	80	step	step	NOUN
cana-5212	99	81	.	.	PUNCT
cana-5212	100	1	here	here	ADV
cana-5212	100	2	,	,	PUNCT
cana-5212	100	3	we	we	PRON
cana-5212	100	4	'll	will	AUX
cana-5212	100	5	perform	perform	VERB
cana-5212	100	6	a	a	DET
cana-5212	100	7	valid	valid	ADJ
cana-5212	100	8	convolution	convolution	NOUN
cana-5212	100	9	.	.	PUNCT
cana-5212	101	1	position	position	NOUN
cana-5212	101	2	(	(	PUNCT
cana-5212	101	3	top	top	ADV
cana-5212	101	4	-	-	PUNCT
cana-5212	101	5	left	left	ADJ
cana-5212	101	6	):	):	PUNCT
cana-5212	101	7	(	(	PUNCT
cana-5212	101	8	1	1	NUM
cana-5212	101	9	×	×	NOUN
cana-5212	101	10	1	1	NUM
cana-5212	101	11	)	)	PUNCT
cana-5212	101	12	+	+	CCONJ
cana-5212	101	13	(	(	PUNCT
cana-5212	101	14	2	2	NUM
cana-5212	101	15	×	×	NOUN
cana-5212	101	16	1	1	NUM
cana-5212	101	17	)	)	PUNCT
cana-5212	101	18	+	+	CCONJ
cana-5212	101	19	(	(	PUNCT
cana-5212	101	20	0	0	NUM
cana-5212	101	21	×	×	NOUN
cana-5212	101	22	0	0	NUM
cana-5212	101	23	)	)	PUNCT
cana-5212	101	24	+	+	CCONJ
cana-5212	101	25	(	(	PUNCT
cana-5212	101	26	1	1	NUM
cana-5212	101	27	×	×	NOUN
cana-5212	101	28	−1	−1	NOUN
cana-5212	101	29	)	)	PUNCT
cana-5212	101	30	=	=	SYM
cana-5212	101	31	1	1	NUM
cana-5212	102	1	+	+	NUM
cana-5212	102	2	0	0	NUM
cana-5212	103	1	+	+	CCONJ
cana-5212	103	2	0	0	NUM
cana-5212	103	3	−	−	NOUN
cana-5212	103	4	1	1	NUM
cana-5212	103	5	=	=	SYM
cana-5212	103	6	0	0	NUM
cana-5212	103	7	position	position	NOUN
cana-5212	103	8	(	(	PUNCT
cana-5212	103	9	top	top	ADJ
cana-5212	103	10	-	-	PUNCT
cana-5212	103	11	centre	centre	NOUN
cana-5212	103	12	):	):	PUNCT
cana-5212	103	13	(	(	PUNCT
cana-5212	103	14	2	2	NUM
cana-5212	103	15	×	×	NOUN
cana-5212	103	16	1	1	NUM
cana-5212	103	17	)	)	PUNCT
cana-5212	103	18	+	+	CCONJ
cana-5212	103	19	(	(	PUNCT
cana-5212	103	20	1	1	NUM
cana-5212	103	21	×	×	NOUN
cana-5212	103	22	0	0	NUM
cana-5212	103	23	)	)	PUNCT
cana-5212	103	24	+	+	CCONJ
cana-5212	103	25	(	(	PUNCT
cana-5212	103	26	1	1	NUM
cana-5212	103	27	×	×	NOUN
cana-5212	103	28	0	0	NUM
cana-5212	103	29	)	)	PUNCT
cana-5212	103	30	+	+	CCONJ
cana-5212	103	31	(	(	PUNCT
cana-5212	103	32	0	0	NUM
cana-5212	103	33	×	×	NOUN
cana-5212	103	34	−1	−1	NOUN
cana-5212	103	35	)	)	PUNCT
cana-5212	103	36	=	=	SYM
cana-5212	103	37	2	2	NUM
cana-5212	103	38	+	+	CCONJ
cana-5212	103	39	0	0	NUM
cana-5212	104	1	+	+	CCONJ
cana-5212	104	2	0	0	NUM
cana-5212	105	1	+	+	CCONJ
cana-5212	105	2	0	0	NUM
cana-5212	105	3	=	=	SYM
cana-5212	105	4	2	2	NUM
cana-5212	105	5	communications	communication	NOUN
cana-5212	105	6	on	on	ADP
cana-5212	105	7	applied	apply	VERB
cana-5212	105	8	nonlinear	nonlinear	ADJ
cana-5212	105	9	analysis	analysis	NOUN
cana-5212	105	10	issn	issn	NOUN
cana-5212	105	11	:	:	PUNCT
cana-5212	105	12	1074	1074	NUM
cana-5212	105	13	-	-	PUNCT
cana-5212	105	14	133x	133x	NUM
cana-5212	105	15	vol	vol	NOUN
cana-5212	105	16	32	32	NUM
cana-5212	105	17	no	no	NOUN
cana-5212	105	18	.	.	PUNCT
cana-5212	106	1	8s	8s	PROPN
cana-5212	106	2	(	(	PUNCT
cana-5212	106	3	2025	2025	NUM
cana-5212	106	4	)	)	PUNCT
cana-5212	106	5	939	939	NUM
cana-5212	106	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	106	7	position	position	NOUN
cana-5212	106	8	(	(	PUNCT
cana-5212	106	9	middle	middle	NOUN
cana-5212	106	10	-	-	PUNCT
cana-5212	106	11	left	left	ADJ
cana-5212	106	12	):	):	PUNCT
cana-5212	106	13	(	(	PUNCT
cana-5212	106	14	0	0	NUM
cana-5212	106	15	×	×	NOUN
cana-5212	106	16	1	1	NUM
cana-5212	106	17	)	)	PUNCT
cana-5212	106	18	+	+	CCONJ
cana-5212	106	19	(	(	PUNCT
cana-5212	106	20	1	1	NUM
cana-5212	106	21	×	×	NOUN
cana-5212	106	22	0	0	NUM
cana-5212	106	23	)	)	PUNCT
cana-5212	107	1	+	+	CCONJ
cana-5212	107	2	(	(	PUNCT
cana-5212	107	3	2	2	NUM
cana-5212	107	4	×	×	NOUN
cana-5212	107	5	0	0	NUM
cana-5212	107	6	)	)	PUNCT
cana-5212	108	1	+	+	CCONJ
cana-5212	108	2	(	(	PUNCT
cana-5212	108	3	1	1	NUM
cana-5212	108	4	×	×	NOUN
cana-5212	108	5	−1	−1	NOUN
cana-5212	108	6	)	)	PUNCT
cana-5212	109	1	=	=	PUNCT
cana-5212	109	2	0	0	PUNCT
cana-5212	110	1	+	+	CCONJ
cana-5212	110	2	0	0	NUM
cana-5212	111	1	+	+	CCONJ
cana-5212	111	2	0	0	NUM
cana-5212	111	3	−	−	NOUN
cana-5212	111	4	1	1	NUM
cana-5212	111	5	=	=	SYM
cana-5212	111	6	−1	−1	NOUN
cana-5212	111	7	position	position	NOUN
cana-5212	111	8	(	(	PUNCT
cana-5212	111	9	middle	middle	ADJ
cana-5212	111	10	-	-	PUNCT
cana-5212	111	11	centre	centre	NOUN
cana-5212	111	12	):	):	PUNCT
cana-5212	111	13	(	(	PUNCT
cana-5212	111	14	1	1	NUM
cana-5212	111	15	×	×	NOUN
cana-5212	111	16	1	1	NUM
cana-5212	111	17	)	)	PUNCT
cana-5212	111	18	+	+	CCONJ
cana-5212	111	19	(	(	PUNCT
cana-5212	111	20	0	0	NUM
cana-5212	111	21	×	×	NOUN
cana-5212	111	22	0	0	NUM
cana-5212	111	23	)	)	PUNCT
cana-5212	111	24	+	+	CCONJ
cana-5212	111	25	(	(	PUNCT
cana-5212	111	26	1	1	NUM
cana-5212	111	27	×	×	NOUN
cana-5212	111	28	0	0	NUM
cana-5212	111	29	)	)	PUNCT
cana-5212	111	30	+	+	CCONJ
cana-5212	111	31	(	(	PUNCT
cana-5212	111	32	2	2	NUM
cana-5212	111	33	×	×	NOUN
cana-5212	111	34	−1	−1	NOUN
cana-5212	111	35	)	)	PUNCT
cana-5212	111	36	=	=	SYM
cana-5212	111	37	1	1	NUM
cana-5212	111	38	+	+	NUM
cana-5212	111	39	0	0	NUM
cana-5212	112	1	+	+	CCONJ
cana-5212	112	2	0	0	NUM
cana-5212	113	1	−	−	NUM
cana-5212	113	2	2	2	NUM
cana-5212	113	3	=	=	SYM
cana-5212	113	4	−1	−1	NOUN
cana-5212	113	5	resulting	result	VERB
cana-5212	113	6	feature	feature	NOUN
cana-5212	113	7	map	map	NOUN
cana-5212	113	8	the	the	DET
cana-5212	113	9	resulting	result	VERB
cana-5212	113	10	feature	feature	NOUN
cana-5212	113	11	map	map	NOUN
cana-5212	113	12	from	from	ADP
cana-5212	113	13	the	the	DET
cana-5212	113	14	convolution	convolution	NOUN
cana-5212	113	15	operation	operation	NOUN
cana-5212	113	16	is	be	AUX
cana-5212	113	17	:	:	PUNCT
cana-5212	113	18	[	[	PUNCT
cana-5212	113	19	0	0	NUM
cana-5212	113	20	2	2	NUM
cana-5212	113	21	−1	−1	NOUN
cana-5212	113	22	−1	−1	NOUN
cana-5212	113	23	]	]	PUNCT
cana-5212	113	24	step	step	NOUN
cana-5212	113	25	2	2	NUM
cana-5212	113	26	:	:	PUNCT
cana-5212	114	1	activation	activation	NOUN
cana-5212	114	2	function	function	NOUN
cana-5212	114	3	(	(	PUNCT
cana-5212	114	4	relu	relu	NOUN
cana-5212	114	5	)	)	PUNCT
cana-5212	114	6	the	the	DET
cana-5212	114	7	relu	relu	NOUN
cana-5212	114	8	activation	activation	NOUN
cana-5212	114	9	function	function	NOUN
cana-5212	114	10	is	be	AUX
cana-5212	114	11	applied	apply	VERB
cana-5212	114	12	to	to	PART
cana-5212	114	13	introduce	introduce	VERB
cana-5212	114	14	non	non	ADJ
cana-5212	114	15	-	-	ADJ
cana-5212	114	16	linearity	linearity	ADJ
cana-5212	114	17	,	,	PUNCT
cana-5212	114	18	defined	define	VERB
cana-5212	114	19	as	as	ADP
cana-5212	114	20	𝑓(𝑥	𝑓(𝑥	NOUN
cana-5212	114	21	)	)	PUNCT
cana-5212	114	22	=	=	SYM
cana-5212	114	23	max(0	max(0	NOUN
cana-5212	114	24	,	,	PUNCT
cana-5212	114	25	𝑥	𝑥	NOUN
cana-5212	114	26	)	)	PUNCT
cana-5212	114	27	.	.	PUNCT
cana-5212	115	1	applying	apply	VERB
cana-5212	115	2	relu	relu	NOUN
cana-5212	115	3	to	to	ADP
cana-5212	115	4	the	the	DET
cana-5212	115	5	feature	feature	NOUN
cana-5212	115	6	map	map	NOUN
cana-5212	115	7	:	:	PUNCT
cana-5212	115	8	[	[	PUNCT
cana-5212	115	9	max	max	X
cana-5212	115	10	(	(	PUNCT
cana-5212	115	11	0,0	0,0	NOUN
cana-5212	115	12	)	)	PUNCT
cana-5212	115	13	max	max	NOUN
cana-5212	115	14	(	(	PUNCT
cana-5212	115	15	0,2	0,2	NUM
cana-5212	115	16	)	)	PUNCT
cana-5212	115	17	max	max	PROPN
cana-5212	115	18	(	(	PUNCT
cana-5212	115	19	0	0	NUM
cana-5212	115	20	,	,	PUNCT
cana-5212	115	21	−1	−1	NOUN
cana-5212	115	22	)	)	PUNCT
cana-5212	115	23	max	max	PROPN
cana-5212	115	24	(	(	PUNCT
cana-5212	115	25	0	0	NUM
cana-5212	115	26	,	,	PUNCT
cana-5212	115	27	−1	−1	NOUN
cana-5212	115	28	)	)	PUNCT
cana-5212	115	29	]	]	PUNCT
cana-5212	116	1	=	=	PUNCT
cana-5212	116	2	[	[	PUNCT
cana-5212	116	3	0	0	NUM
cana-5212	116	4	2	2	NUM
cana-5212	116	5	0	0	NUM
cana-5212	116	6	0	0	NUM
cana-5212	116	7	]	]	PUNCT
cana-5212	116	8	step	step	NOUN
cana-5212	116	9	3	3	NUM
cana-5212	116	10	:	:	PUNCT
cana-5212	116	11	pooling	pool	VERB
cana-5212	116	12	(	(	PUNCT
cana-5212	116	13	max	max	PROPN
cana-5212	116	14	pooling	pooling	NOUN
cana-5212	116	15	)	)	PUNCT
cana-5212	116	16	max	max	PROPN
cana-5212	116	17	pooling	pooling	NOUN
cana-5212	116	18	is	be	AUX
cana-5212	116	19	used	use	VERB
cana-5212	116	20	to	to	ADP
cana-5212	116	21	down	down	ADP
cana-5212	116	22	-	-	PUNCT
cana-5212	116	23	sample	sample	NOUN
cana-5212	116	24	the	the	DET
cana-5212	116	25	feature	feature	NOUN
cana-5212	116	26	map	map	NOUN
cana-5212	116	27	,	,	PUNCT
cana-5212	116	28	reducing	reduce	VERB
cana-5212	116	29	its	its	PRON
cana-5212	116	30	dimensions	dimension	NOUN
cana-5212	116	31	while	while	SCONJ
cana-5212	116	32	retaining	retain	VERB
cana-5212	116	33	the	the	DET
cana-5212	116	34	most	most	ADV
cana-5212	116	35	important	important	ADJ
cana-5212	116	36	features	feature	NOUN
cana-5212	116	37	.	.	PUNCT
cana-5212	117	1	max	max	PROPN
cana-5212	117	2	pooling	pooling	NOUN
cana-5212	117	3	(	(	PUNCT
cana-5212	117	4	2x2	2x2	NUM
cana-5212	117	5	window	window	NOUN
cana-5212	117	6	):	):	PUNCT
cana-5212	117	7	the	the	DET
cana-5212	117	8	pooled	pool	VERB
cana-5212	117	9	value	value	NOUN
cana-5212	117	10	from	from	ADP
cana-5212	117	11	the	the	DET
cana-5212	117	12	2x2	2x2	NUM
cana-5212	117	13	feature	feature	NOUN
cana-5212	117	14	map	map	NOUN
cana-5212	117	15	is	be	AUX
cana-5212	117	16	max(0,2,0,0	max(0,2,0,0	NOUN
cana-5212	117	17	)	)	PUNCT
cana-5212	117	18	=	=	SYM
cana-5212	117	19	2	2	NUM
cana-5212	117	20	final	final	ADJ
cana-5212	117	21	pooled	pool	VERB
cana-5212	117	22	output	output	NOUN
cana-5212	117	23	the	the	DET
cana-5212	117	24	final	final	ADJ
cana-5212	117	25	output	output	NOUN
cana-5212	117	26	after	after	ADP
cana-5212	117	27	applying	apply	VERB
cana-5212	117	28	max	max	PROPN
cana-5212	117	29	pooling	pooling	NOUN
cana-5212	117	30	is	be	AUX
cana-5212	117	31	a	a	DET
cana-5212	117	32	single	single	ADJ
cana-5212	117	33	value	value	NOUN
cana-5212	117	34	:	:	PUNCT
cana-5212	118	1	[	[	X
cana-5212	118	2	2	2	X
cana-5212	118	3	]	]	X
cana-5212	118	4	summary	summary	NOUN
cana-5212	118	5	of	of	ADP
cana-5212	118	6	the	the	DET
cana-5212	118	7	steps	step	NOUN
cana-5212	118	8	convolution	convolution	NOUN
cana-5212	118	9	:	:	PUNCT
cana-5212	118	10	slide	slide	VERB
cana-5212	118	11	the	the	DET
cana-5212	118	12	filter	filter	NOUN
cana-5212	118	13	over	over	ADP
cana-5212	118	14	the	the	DET
cana-5212	118	15	input	input	NOUN
cana-5212	118	16	image	image	NOUN
cana-5212	118	17	,	,	PUNCT
cana-5212	118	18	perform	perform	VERB
cana-5212	118	19	element	element	ADJ
cana-5212	118	20	-	-	ADJ
cana-5212	118	21	wise	wise	ADJ
cana-5212	118	22	multiplication	multiplication	NOUN
cana-5212	118	23	,	,	PUNCT
cana-5212	118	24	and	and	CCONJ
cana-5212	118	25	sum	sum	VERB
cana-5212	118	26	the	the	DET
cana-5212	118	27	results	result	NOUN
cana-5212	118	28	to	to	PART
cana-5212	118	29	produce	produce	VERB
cana-5212	118	30	a	a	DET
cana-5212	118	31	feature	feature	NOUN
cana-5212	118	32	map	map	NOUN
cana-5212	118	33	.	.	PUNCT
cana-5212	119	1	activation	activation	NOUN
cana-5212	119	2	(	(	PUNCT
cana-5212	119	3	relu	relu	NOUN
cana-5212	119	4	):	):	PUNCT
cana-5212	119	5	apply	apply	VERB
cana-5212	119	6	the	the	DET
cana-5212	119	7	relu	relu	NOUN
cana-5212	119	8	function	function	NOUN
cana-5212	119	9	to	to	PART
cana-5212	119	10	introduce	introduce	VERB
cana-5212	119	11	non	non	ADJ
cana-5212	119	12	-	-	ADJ
cana-5212	119	13	linearity	linearity	ADJ
cana-5212	119	14	and	and	CCONJ
cana-5212	119	15	eliminate	eliminate	VERB
cana-5212	119	16	negative	negative	ADJ
cana-5212	119	17	values	value	NOUN
cana-5212	119	18	.	.	PUNCT
cana-5212	120	1	pooling	pool	VERB
cana-5212	120	2	(	(	PUNCT
cana-5212	120	3	max	max	PROPN
cana-5212	120	4	pooling	pooling	NOUN
cana-5212	120	5	):	):	PUNCT
cana-5212	120	6	down	down	ADP
cana-5212	120	7	-	-	PUNCT
cana-5212	120	8	sample	sample	NOUN
cana-5212	120	9	the	the	DET
cana-5212	120	10	feature	feature	NOUN
cana-5212	120	11	map	map	NOUN
cana-5212	120	12	by	by	ADP
cana-5212	120	13	selecting	select	VERB
cana-5212	120	14	the	the	DET
cana-5212	120	15	maximum	maximum	ADJ
cana-5212	120	16	value	value	NOUN
cana-5212	120	17	from	from	ADP
cana-5212	120	18	each	each	DET
cana-5212	120	19	pooling	pool	VERB
cana-5212	120	20	region	region	NOUN
cana-5212	120	21	.	.	PUNCT
cana-5212	121	1	communications	communication	NOUN
cana-5212	121	2	on	on	ADP
cana-5212	121	3	applied	apply	VERB
cana-5212	121	4	nonlinear	nonlinear	ADJ
cana-5212	121	5	analysis	analysis	NOUN
cana-5212	121	6	issn	issn	NOUN
cana-5212	121	7	:	:	PUNCT
cana-5212	121	8	1074	1074	NUM
cana-5212	121	9	-	-	PUNCT
cana-5212	121	10	133x	133x	NUM
cana-5212	121	11	vol	vol	NOUN
cana-5212	121	12	32	32	NUM
cana-5212	121	13	no	no	NOUN
cana-5212	121	14	.	.	PUNCT
cana-5212	122	1	8s	8s	PROPN
cana-5212	122	2	(	(	PUNCT
cana-5212	122	3	2025	2025	NUM
cana-5212	122	4	)	)	PUNCT
cana-5212	122	5	940	940	NUM
cana-5212	122	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	122	7	this	this	DET
cana-5212	122	8	example	example	NOUN
cana-5212	122	9	demonstrates	demonstrate	VERB
cana-5212	122	10	how	how	SCONJ
cana-5212	122	11	cnns	cnns	ADJ
cana-5212	122	12	process	process	NOUN
cana-5212	122	13	data	datum	NOUN
cana-5212	122	14	through	through	ADP
cana-5212	122	15	convolution	convolution	NOUN
cana-5212	122	16	,	,	PUNCT
cana-5212	122	17	activation	activation	NOUN
cana-5212	122	18	,	,	PUNCT
cana-5212	122	19	and	and	CCONJ
cana-5212	122	20	pooling	pool	VERB
cana-5212	122	21	layers	layer	NOUN
cana-5212	122	22	to	to	PART
cana-5212	122	23	extract	extract	VERB
cana-5212	122	24	features	feature	NOUN
cana-5212	122	25	and	and	CCONJ
cana-5212	122	26	reduce	reduce	VERB
cana-5212	122	27	dimensionality	dimensionality	NOUN
cana-5212	122	28	,	,	PUNCT
cana-5212	122	29	making	make	VERB
cana-5212	122	30	it	it	PRON
cana-5212	122	31	possible	possible	ADJ
cana-5212	122	32	to	to	PART
cana-5212	122	33	identify	identify	VERB
cana-5212	122	34	complex	complex	ADJ
cana-5212	122	35	patterns	pattern	NOUN
cana-5212	122	36	in	in	ADP
cana-5212	122	37	image	image	NOUN
cana-5212	122	38	data	datum	NOUN
cana-5212	122	39	.	.	PUNCT
cana-5212	123	1	this	this	DET
cana-5212	123	2	step	step	NOUN
cana-5212	123	3	-	-	PUNCT
cana-5212	123	4	by	by	ADP
cana-5212	123	5	-	-	PUNCT
cana-5212	123	6	step	step	NOUN
cana-5212	123	7	process	process	NOUN
cana-5212	123	8	is	be	AUX
cana-5212	123	9	the	the	DET
cana-5212	123	10	backbone	backbone	NOUN
cana-5212	123	11	of	of	ADP
cana-5212	123	12	cnn	cnn	PROPN
cana-5212	123	13	-	-	PUNCT
cana-5212	123	14	based	base	VERB
cana-5212	123	15	image	image	NOUN
cana-5212	123	16	classification	classification	NOUN
cana-5212	123	17	tasks	task	NOUN
cana-5212	123	18	,	,	PUNCT
cana-5212	123	19	such	such	ADJ
cana-5212	123	20	as	as	ADP
cana-5212	123	21	plant	plant	NOUN
cana-5212	123	22	disease	disease	NOUN
cana-5212	123	23	detection	detection	NOUN
cana-5212	123	24	in	in	ADP
cana-5212	123	25	your	your	PRON
cana-5212	123	26	research	research	NOUN
cana-5212	123	27	.	.	PUNCT
cana-5212	124	1	figure	figure	NOUN
cana-5212	124	2	1	1	NUM
cana-5212	124	3	:	:	PUNCT
cana-5212	124	4	convolutional	convolutional	ADJ
cana-5212	124	5	neural	neural	ADJ
cana-5212	124	6	network	network	NOUN
cana-5212	124	7	architecture	architecture	NOUN
cana-5212	124	8	for	for	ADP
cana-5212	124	9	plant	plant	NOUN
cana-5212	124	10	disease	disease	NOUN
cana-5212	124	11	detection	detection	NOUN
cana-5212	124	12	this	this	DET
cana-5212	124	13	figure	figure	NOUN
cana-5212	124	14	(	(	PUNCT
cana-5212	124	15	1	1	NUM
cana-5212	124	16	)	)	PUNCT
cana-5212	124	17	illustrates	illustrate	VERB
cana-5212	124	18	the	the	DET
cana-5212	124	19	architecture	architecture	NOUN
cana-5212	124	20	of	of	ADP
cana-5212	124	21	the	the	DET
cana-5212	124	22	convolutional	convolutional	ADJ
cana-5212	124	23	neural	neural	ADJ
cana-5212	124	24	network	network	NOUN
cana-5212	124	25	used	use	VERB
cana-5212	124	26	in	in	ADP
cana-5212	124	27	the	the	DET
cana-5212	124	28	proposed	propose	VERB
cana-5212	124	29	method	method	NOUN
cana-5212	124	30	.	.	PUNCT
cana-5212	125	1	the	the	DET
cana-5212	125	2	architecture	architecture	NOUN
cana-5212	125	3	includes	include	VERB
cana-5212	125	4	the	the	DET
cana-5212	125	5	input	input	NOUN
cana-5212	125	6	layer	layer	NOUN
cana-5212	125	7	where	where	SCONJ
cana-5212	125	8	raw	raw	ADJ
cana-5212	125	9	images	image	NOUN
cana-5212	125	10	are	be	AUX
cana-5212	125	11	fed	feed	VERB
cana-5212	125	12	into	into	ADP
cana-5212	125	13	the	the	DET
cana-5212	125	14	network	network	NOUN
cana-5212	125	15	,	,	PUNCT
cana-5212	125	16	followed	follow	VERB
cana-5212	125	17	by	by	ADP
cana-5212	125	18	multiple	multiple	ADJ
cana-5212	125	19	convolutional	convolutional	ADJ
cana-5212	125	20	and	and	CCONJ
cana-5212	125	21	pooling	pool	VERB
cana-5212	125	22	layers	layer	NOUN
cana-5212	125	23	for	for	ADP
cana-5212	125	24	feature	feature	NOUN
cana-5212	125	25	extraction	extraction	NOUN
cana-5212	125	26	.	.	PUNCT
cana-5212	126	1	the	the	DET
cana-5212	126	2	extracted	extract	VERB
cana-5212	126	3	features	feature	NOUN
cana-5212	126	4	are	be	AUX
cana-5212	126	5	then	then	ADV
cana-5212	126	6	passed	pass	VERB
cana-5212	126	7	through	through	ADP
cana-5212	126	8	fully	fully	ADV
cana-5212	126	9	connected	connected	ADJ
cana-5212	126	10	layers	layer	NOUN
cana-5212	126	11	for	for	ADP
cana-5212	126	12	classification	classification	NOUN
cana-5212	126	13	into	into	ADP
cana-5212	126	14	various	various	ADJ
cana-5212	126	15	plant	plant	NOUN
cana-5212	126	16	diseases	disease	NOUN
cana-5212	126	17	.	.	PUNCT
cana-5212	127	1	figure	figure	NOUN
cana-5212	127	2	2	2	NUM
cana-5212	127	3	:	:	PUNCT
cana-5212	127	4	fuzzy	fuzzy	ADJ
cana-5212	127	5	logic	logic	NOUN
cana-5212	127	6	inference	inference	NOUN
cana-5212	127	7	system	system	NOUN
cana-5212	127	8	for	for	ADP
cana-5212	127	9	severity	severity	NOUN
cana-5212	127	10	analysis	analysis	NOUN
cana-5212	127	11	this	this	DET
cana-5212	127	12	figure	figure	NOUN
cana-5212	127	13	(	(	PUNCT
cana-5212	127	14	2	2	NUM
cana-5212	127	15	)	)	PUNCT
cana-5212	127	16	shows	show	VERB
cana-5212	127	17	the	the	DET
cana-5212	127	18	fuzzy	fuzzy	ADJ
cana-5212	127	19	logic	logic	NOUN
cana-5212	127	20	inference	inference	NOUN
cana-5212	127	21	system	system	NOUN
cana-5212	127	22	integrated	integrate	VERB
cana-5212	127	23	with	with	ADP
cana-5212	127	24	the	the	DET
cana-5212	127	25	cnn	cnn	PROPN
cana-5212	127	26	for	for	ADP
cana-5212	127	27	evaluating	evaluate	VERB
cana-5212	127	28	the	the	DET
cana-5212	127	29	severity	severity	NOUN
cana-5212	127	30	of	of	ADP
cana-5212	127	31	detected	detect	VERB
cana-5212	127	32	diseases	disease	NOUN
cana-5212	127	33	.	.	PUNCT
cana-5212	128	1	it	it	PRON
cana-5212	128	2	includes	include	VERB
cana-5212	128	3	the	the	DET
cana-5212	128	4	input	input	NOUN
cana-5212	128	5	processing	processing	NOUN
cana-5212	128	6	stage	stage	NOUN
cana-5212	128	7	(	(	PUNCT
cana-5212	128	8	fuzzification	fuzzification	NOUN
cana-5212	128	9	)	)	PUNCT
cana-5212	128	10	,	,	PUNCT
cana-5212	128	11	the	the	DET
cana-5212	128	12	reasoning	reasoning	NOUN
cana-5212	128	13	mechanism	mechanism	NOUN
cana-5212	128	14	(	(	PUNCT
cana-5212	128	15	fuzzy	fuzzy	ADJ
cana-5212	128	16	rules	rule	NOUN
cana-5212	128	17	and	and	CCONJ
cana-5212	128	18	inference	inference	NOUN
cana-5212	128	19	)	)	PUNCT
cana-5212	128	20	,	,	PUNCT
cana-5212	128	21	and	and	CCONJ
cana-5212	128	22	the	the	DET
cana-5212	128	23	output	output	NOUN
cana-5212	128	24	processing	processing	NOUN
cana-5212	128	25	stage	stage	NOUN
cana-5212	128	26	(	(	PUNCT
cana-5212	128	27	defuzzification	defuzzification	NOUN
cana-5212	128	28	)	)	PUNCT
cana-5212	128	29	.	.	PUNCT
cana-5212	129	1	this	this	DET
cana-5212	129	2	system	system	NOUN
cana-5212	129	3	transforms	transform	VERB
cana-5212	129	4	the	the	DET
cana-5212	129	5	cnn	cnn	PROPN
cana-5212	129	6	classification	classification	NOUN
cana-5212	129	7	results	result	NOUN
cana-5212	129	8	into	into	ADP
cana-5212	129	9	actionable	actionable	ADJ
cana-5212	129	10	severity	severity	NOUN
cana-5212	129	11	levels	level	NOUN
cana-5212	129	12	and	and	CCONJ
cana-5212	129	13	treatment	treatment	NOUN
cana-5212	129	14	suggestions	suggestion	NOUN
cana-5212	129	15	.	.	PUNCT
cana-5212	130	1	communications	communication	NOUN
cana-5212	130	2	on	on	ADP
cana-5212	130	3	applied	apply	VERB
cana-5212	130	4	nonlinear	nonlinear	ADJ
cana-5212	130	5	analysis	analysis	NOUN
cana-5212	130	6	issn	issn	NOUN
cana-5212	130	7	:	:	PUNCT
cana-5212	130	8	1074	1074	NUM
cana-5212	130	9	-	-	PUNCT
cana-5212	130	10	133x	133x	NUM
cana-5212	130	11	vol	vol	NOUN
cana-5212	130	12	32	32	NUM
cana-5212	130	13	no	no	NOUN
cana-5212	130	14	.	.	PUNCT
cana-5212	131	1	8s	8s	PROPN
cana-5212	131	2	(	(	PUNCT
cana-5212	131	3	2025	2025	NUM
cana-5212	131	4	)	)	PUNCT
cana-5212	131	5	941	941	NUM
cana-5212	131	6	https://internationalpubls.com	https://internationalpubls.com	SYM
cana-5212	131	7	3.2	3.2	NUM
cana-5212	131	8	justification	justification	NOUN
cana-5212	131	9	recent	recent	ADJ
cana-5212	131	10	advances	advance	NOUN
cana-5212	131	11	in	in	ADP
cana-5212	131	12	deep	deep	ADJ
cana-5212	131	13	learning	learning	NOUN
cana-5212	131	14	have	have	AUX
cana-5212	131	15	proven	prove	VERB
cana-5212	131	16	conclusively	conclusively	ADV
cana-5212	131	17	that	that	SCONJ
cana-5212	131	18	convolutional	convolutional	ADJ
cana-5212	131	19	neural	neural	ADJ
cana-5212	131	20	networks	network	NOUN
cana-5212	131	21	always	always	ADV
cana-5212	131	22	turn	turn	VERB
cana-5212	131	23	in	in	ADP
cana-5212	131	24	impressive	impressive	ADJ
cana-5212	131	25	performances	performance	NOUN
cana-5212	131	26	in	in	ADP
cana-5212	131	27	image	image	NOUN
cana-5212	131	28	classification	classification	NOUN
cana-5212	131	29	tasks	task	NOUN
cana-5212	131	30	.	.	PUNCT
cana-5212	132	1	the	the	DET
cana-5212	132	2	proficiency	proficiency	NOUN
cana-5212	132	3	of	of	ADP
cana-5212	132	4	cnns	cnn	NOUN
cana-5212	132	5	to	to	PART
cana-5212	132	6	learn	learn	VERB
cana-5212	132	7	hierarchical	hierarchical	ADJ
cana-5212	132	8	features	feature	NOUN
cana-5212	132	9	from	from	ADP
cana-5212	132	10	raw	raw	ADJ
cana-5212	132	11	images	image	NOUN
cana-5212	132	12	automatically	automatically	ADV
cana-5212	132	13	makes	make	VERB
cana-5212	132	14	it	it	PRON
cana-5212	132	15	specific	specific	ADJ
cana-5212	132	16	to	to	ADP
cana-5212	132	17	difficult	difficult	ADJ
cana-5212	132	18	pattern	pattern	NOUN
cana-5212	132	19	recognition	recognition	NOUN
cana-5212	132	20	tasks	task	NOUN
cana-5212	132	21	,	,	PUNCT
cana-5212	132	22	including	include	VERB
cana-5212	132	23	plant	plant	NOUN
cana-5212	132	24	disease	disease	NOUN
cana-5212	132	25	detection	detection	NOUN
cana-5212	132	26	,	,	PUNCT
cana-5212	132	27	therefore	therefore	ADV
cana-5212	132	28	it	it	PRON
cana-5212	132	29	has	have	AUX
cana-5212	132	30	surpassed	surpass	VERB
cana-5212	132	31	the	the	DET
cana-5212	132	32	conventional	conventional	ADJ
cana-5212	132	33	machine	machine	NOUN
cana-5212	132	34	learning	learn	VERB
cana-5212	132	35	techniques	technique	NOUN
cana-5212	132	36	in	in	ADP
cana-5212	132	37	terms	term	NOUN
cana-5212	132	38	of	of	ADP
cana-5212	132	39	accuracy	accuracy	NOUN
cana-5212	132	40	and	and	CCONJ
cana-5212	132	41	robustness	robustness	NOUN
cana-5212	132	42	.	.	PUNCT
cana-5212	133	1	although	although	SCONJ
cana-5212	133	2	they	they	PRON
cana-5212	133	3	work	work	VERB
cana-5212	133	4	very	very	ADV
cana-5212	133	5	well	well	ADV
cana-5212	133	6	in	in	ADP
cana-5212	133	7	classification	classification	NOUN
cana-5212	133	8	,	,	PUNCT
cana-5212	133	9	cnns	cnn	NOUN
cana-5212	133	10	do	do	AUX
cana-5212	133	11	not	not	PART
cana-5212	133	12	deal	deal	VERB
cana-5212	133	13	with	with	ADP
cana-5212	133	14	the	the	DET
cana-5212	133	15	uncertainty	uncertainty	NOUN
cana-5212	133	16	and	and	CCONJ
cana-5212	133	17	variability	variability	NOUN
cana-5212	133	18	associated	associate	VERB
cana-5212	133	19	with	with	ADP
cana-5212	133	20	the	the	DET
cana-5212	133	21	severity	severity	NOUN
cana-5212	133	22	of	of	ADP
cana-5212	133	23	the	the	DET
cana-5212	133	24	diseases	disease	NOUN
cana-5212	133	25	.	.	PUNCT
cana-5212	134	1	that	that	PRON
cana-5212	134	2	's	be	AUX
cana-5212	134	3	where	where	SCONJ
cana-5212	134	4	fuzzy	fuzzy	ADJ
cana-5212	134	5	logic	logic	NOUN
cana-5212	134	6	comes	come	VERB
cana-5212	134	7	ina	ina	PROPN
cana-5212	134	8	mathematical	mathematical	ADJ
cana-5212	134	9	framework	framework	NOUN
cana-5212	134	10	for	for	ADP
cana-5212	134	11	dealing	deal	VERB
cana-5212	134	12	with	with	ADP
cana-5212	134	13	imprecise	imprecise	ADJ
cana-5212	134	14	and	and	CCONJ
cana-5212	134	15	ambiguous	ambiguous	ADJ
cana-5212	134	16	information	information	NOUN
cana-5212	134	17	.	.	PUNCT
cana-5212	135	1	it	it	PRON
cana-5212	135	2	thus	thus	ADV
cana-5212	135	3	complements	complement	VERB
cana-5212	135	4	cnns	cnn	VERB
cana-5212	135	5	by	by	ADP
cana-5212	135	6	adding	add	VERB
cana-5212	135	7	an	an	DET
cana-5212	135	8	extra	extra	ADJ
cana-5212	135	9	layer	layer	NOUN
cana-5212	135	10	to	to	PART
cana-5212	135	11	analyze	analyze	VERB
cana-5212	135	12	the	the	DET
cana-5212	135	13	severity	severity	NOUN
cana-5212	135	14	of	of	ADP
cana-5212	135	15	the	the	DET
cana-5212	135	16	detected	detect	VERB
cana-5212	135	17	diseases	disease	NOUN
cana-5212	135	18	,	,	PUNCT
cana-5212	135	19	considering	consider	VERB
cana-5212	135	20	inherent	inherent	ADJ
cana-5212	135	21	uncertainties	uncertainty	NOUN
cana-5212	135	22	in	in	ADP
cana-5212	135	23	symptom	symptom	NOUN
cana-5212	135	24	expression	expression	NOUN
cana-5212	135	25	and	and	CCONJ
cana-5212	135	26	environmental	environmental	ADJ
cana-5212	135	27	conditions	condition	NOUN
cana-5212	135	28	.	.	PUNCT
cana-5212	136	1	it	it	PRON
cana-5212	136	2	integrates	integrate	VERB
cana-5212	136	3	cnn	cnn	PROPN
cana-5212	136	4	with	with	ADP
cana-5212	136	5	fuzzy	fuzzy	ADJ
cana-5212	136	6	logic	logic	NOUN
cana-5212	136	7	to	to	PART
cana-5212	136	8	provide	provide	VERB
cana-5212	136	9	a	a	DET
cana-5212	136	10	better	well	ADJ
cana-5212	136	11	and	and	CCONJ
cana-5212	136	12	more	more	ADV
cana-5212	136	13	comprehensive	comprehensive	ADJ
cana-5212	136	14	solution	solution	NOUN
cana-5212	136	15	to	to	ADP
cana-5212	136	16	the	the	DET
cana-5212	136	17	management	management	NOUN
cana-5212	136	18	of	of	ADP
cana-5212	136	19	plant	plant	NOUN
cana-5212	136	20	diseases	disease	NOUN
cana-5212	136	21	.	.	PUNCT
cana-5212	137	1	accordingly	accordingly	ADV
cana-5212	137	2	,	,	PUNCT
cana-5212	137	3	the	the	DET
cana-5212	137	4	cnn	cnn	PROPN
cana-5212	137	5	component	component	NOUN
cana-5212	137	6	allows	allow	VERB
cana-5212	137	7	the	the	DET
cana-5212	137	8	classifier	classifier	NOUN
cana-5212	137	9	to	to	PART
cana-5212	137	10	possess	possess	VERB
cana-5212	137	11	an	an	DET
cana-5212	137	12	accurate	accurate	ADJ
cana-5212	137	13	identification	identification	NOUN
cana-5212	137	14	and	and	CCONJ
cana-5212	137	15	classification	classification	NOUN
cana-5212	137	16	of	of	ADP
cana-5212	137	17	diseases	disease	NOUN
cana-5212	137	18	from	from	ADP
cana-5212	137	19	the	the	DET
cana-5212	137	20	given	give	VERB
cana-5212	137	21	raw	raw	ADJ
cana-5212	137	22	images	image	NOUN
cana-5212	137	23	.	.	PUNCT
cana-5212	138	1	this	this	PRON
cana-5212	138	2	is	be	AUX
cana-5212	138	3	followed	follow	VERB
cana-5212	138	4	by	by	ADP
cana-5212	138	5	the	the	DET
cana-5212	138	6	fuzzy	fuzzy	ADJ
cana-5212	138	7	logic	logic	NOUN
cana-5212	138	8	component	component	NOUN
cana-5212	138	9	,	,	PUNCT
cana-5212	138	10	which	which	PRON
cana-5212	138	11	is	be	AUX
cana-5212	138	12	responsible	responsible	ADJ
cana-5212	138	13	for	for	ADP
cana-5212	138	14	assessing	assess	VERB
cana-5212	138	15	the	the	DET
cana-5212	138	16	severity	severity	NOUN
cana-5212	138	17	of	of	ADP
cana-5212	138	18	detected	detect	VERB
cana-5212	138	19	diseases	disease	NOUN
cana-5212	138	20	based	base	VERB
cana-5212	138	21	on	on	ADP
cana-5212	138	22	predefined	predefine	VERB
cana-5212	138	23	fuzzy	fuzzy	ADJ
cana-5212	138	24	rules	rule	NOUN
cana-5212	138	25	and	and	CCONJ
cana-5212	138	26	membership	membership	NOUN
cana-5212	138	27	functions	function	NOUN
cana-5212	138	28	.	.	PUNCT
cana-5212	139	1	this	this	DET
cana-5212	139	2	integrated	integrated	ADJ
cana-5212	139	3	model	model	NOUN
cana-5212	139	4	identifies	identify	VERB
cana-5212	139	5	the	the	DET
cana-5212	139	6	type	type	NOUN
cana-5212	139	7	of	of	ADP
cana-5212	139	8	disease	disease	NOUN
cana-5212	139	9	and	and	CCONJ
cana-5212	139	10	also	also	ADV
cana-5212	139	11	comes	come	VERB
cana-5212	139	12	up	up	ADP
cana-5212	139	13	with	with	ADP
cana-5212	139	14	action	action	NOUN
cana-5212	139	15	items	item	NOUN
cana-5212	139	16	with	with	ADP
cana-5212	139	17	respect	respect	NOUN
cana-5212	139	18	to	to	ADP
cana-5212	139	19	severity	severity	NOUN
cana-5212	139	20	,	,	PUNCT
cana-5212	139	21	and	and	CCONJ
cana-5212	139	22	hence	hence	ADV
cana-5212	139	23	,	,	PUNCT
cana-5212	139	24	establishes	establish	VERB
cana-5212	139	25	proper	proper	ADJ
cana-5212	139	26	recommendations	recommendation	NOUN
cana-5212	139	27	for	for	ADP
cana-5212	139	28	treatment	treatment	NOUN
cana-5212	139	29	.	.	PUNCT
cana-5212	140	1	this	this	PRON
cana-5212	140	2	has	have	AUX
cana-5212	140	3	,	,	PUNCT
cana-5212	140	4	therefore	therefore	ADV
cana-5212	140	5	,	,	PUNCT
cana-5212	140	6	increased	increase	VERB
cana-5212	140	7	the	the	DET
cana-5212	140	8	efficiency	efficiency	NOUN
cana-5212	140	9	of	of	ADP
cana-5212	140	10	the	the	DET
cana-5212	140	11	disease	disease	NOUN
cana-5212	140	12	management	management	NOUN
cana-5212	140	13	system	system	NOUN
cana-5212	140	14	in	in	ADP
cana-5212	140	15	general	general	ADJ
cana-5212	140	16	,	,	PUNCT
cana-5212	140	17	through	through	ADP
cana-5212	140	18	provision	provision	NOUN
cana-5212	140	19	with	with	ADP
cana-5212	140	20	a	a	DET
cana-5212	140	21	diagnosis	diagnosis	NOUN
cana-5212	140	22	that	that	PRON
cana-5212	140	23	is	be	AUX
cana-5212	140	24	accompanied	accompany	VERB
cana-5212	140	25	by	by	ADP
cana-5212	140	26	detailed	detailed	ADJ
cana-5212	140	27	analysis	analysis	NOUN
cana-5212	140	28	in	in	ADP
cana-5212	140	29	regard	regard	NOUN
cana-5212	140	30	to	to	ADP
cana-5212	140	31	its	its	PRON
cana-5212	140	32	severity	severity	NOUN
cana-5212	140	33	,	,	PUNCT
cana-5212	140	34	allowing	allow	VERB
cana-5212	140	35	the	the	DET
cana-5212	140	36	possibility	possibility	NOUN
cana-5212	140	37	of	of	ADP
cana-5212	140	38	informed	informed	ADJ
cana-5212	140	39	decision	decision	NOUN
cana-5212	140	40	making	making	NOUN
cana-5212	140	41	and	and	CCONJ
cana-5212	140	42	timely	timely	ADJ
cana-5212	140	43	interventions	intervention	NOUN
cana-5212	140	44	.	.	PUNCT
cana-5212	141	1	3.3	3.3	NUM
cana-5212	141	2	steps	step	NOUN
cana-5212	141	3	and	and	CCONJ
cana-5212	141	4	flowcharts	flowchart	NOUN
cana-5212	141	5	3.3.1	3.3.1	NUM
cana-5212	141	6	step	step	NOUN
cana-5212	141	7	1	1	NUM
cana-5212	141	8	:	:	PUNCT
cana-5212	141	9	raw	raw	ADJ
cana-5212	141	10	image	image	NOUN
cana-5212	141	11	input	input	NOUN
cana-5212	141	12	to	to	ADP
cana-5212	141	13	cnn	cnn	PROPN
cana-5212	141	14	.	.	PUNCT
cana-5212	142	1	the	the	DET
cana-5212	142	2	starting	starting	NOUN
cana-5212	142	3	point	point	NOUN
cana-5212	142	4	involves	involve	VERB
cana-5212	142	5	the	the	DET
cana-5212	142	6	collection	collection	NOUN
cana-5212	142	7	of	of	ADP
cana-5212	142	8	the	the	DET
cana-5212	142	9	raw	raw	ADJ
cana-5212	142	10	images	image	NOUN
cana-5212	142	11	of	of	ADP
cana-5212	142	12	the	the	DET
cana-5212	142	13	plant	plant	NOUN
cana-5212	142	14	leaves	leave	VERB
cana-5212	142	15	.	.	PUNCT
cana-5212	143	1	these	these	PRON
cana-5212	143	2	are	be	AUX
cana-5212	143	3	used	use	VERB
cana-5212	143	4	as	as	ADP
cana-5212	143	5	an	an	DET
cana-5212	143	6	input	input	NOUN
cana-5212	143	7	into	into	ADP
cana-5212	143	8	a	a	DET
cana-5212	143	9	cnn	cnn	NOUN
cana-5212	143	10	where	where	SCONJ
cana-5212	143	11	the	the	DET
cana-5212	143	12	least	least	ADJ
cana-5212	143	13	amount	amount	NOUN
cana-5212	143	14	of	of	ADP
cana-5212	143	15	preprocessing	preprocessing	NOUN
cana-5212	143	16	is	be	AUX
cana-5212	143	17	carried	carry	VERB
cana-5212	143	18	out	out	ADP
cana-5212	143	19	on	on	ADP
cana-5212	143	20	the	the	DET
cana-5212	143	21	images	image	NOUN
cana-5212	143	22	so	so	SCONJ
cana-5212	143	23	that	that	SCONJ
cana-5212	143	24	the	the	DET
cana-5212	143	25	integrity	integrity	NOUN
cana-5212	143	26	of	of	ADP
cana-5212	143	27	the	the	DET
cana-5212	143	28	data	data	NOUN
cana-5212	143	29	receives	receive	VERB
cana-5212	143	30	the	the	DET
cana-5212	143	31	least	least	ADJ
cana-5212	143	32	interference	interference	NOUN
cana-5212	143	33	possible	possible	ADJ
cana-5212	143	34	.	.	PUNCT
cana-5212	144	1	processed	process	VERB
cana-5212	144	2	images	image	NOUN
cana-5212	144	3	passed	pass	VERB
cana-5212	144	4	through	through	ADP
cana-5212	144	5	cnn	cnn	PROPN
cana-5212	144	6	and	and	CCONJ
cana-5212	144	7	diseases	disease	VERB
cana-5212	144	8	classification	classification	NOUN
cana-5212	144	9	.	.	PUNCT
cana-5212	145	1	3.3.2	3.3.2	NUM
cana-5212	145	2	step	step	NOUN
cana-5212	145	3	2	2	NUM
cana-5212	145	4	:	:	PUNCT
cana-5212	145	5	cnn	cnn	PROPN
cana-5212	145	6	processes	process	VERB
cana-5212	145	7	the	the	DET
cana-5212	145	8	images	image	NOUN
cana-5212	145	9	and	and	CCONJ
cana-5212	145	10	classifies	classify	VERB
cana-5212	145	11	diseases	disease	NOUN
cana-5212	145	12	in	in	ADP
cana-5212	145	13	the	the	DET
cana-5212	145	14	cnn	cnn	PROPN
cana-5212	145	15	architecture	architecture	NOUN
cana-5212	145	16	,	,	PUNCT
cana-5212	145	17	the	the	DET
cana-5212	145	18	input	input	NOUN
cana-5212	145	19	image	image	NOUN
cana-5212	145	20	undergoes	undergo	VERB
cana-5212	145	21	several	several	ADJ
cana-5212	145	22	convolutional	convolutional	ADJ
cana-5212	145	23	layers	layer	NOUN
cana-5212	145	24	to	to	PART
cana-5212	145	25	extract	extract	VERB
cana-5212	145	26	edges	edge	NOUN
cana-5212	145	27	,	,	PUNCT
cana-5212	145	28	textures	texture	NOUN
cana-5212	145	29	,	,	PUNCT
cana-5212	145	30	and	and	CCONJ
cana-5212	145	31	other	other	ADJ
cana-5212	145	32	patterns	pattern	NOUN
cana-5212	145	33	.	.	PUNCT
cana-5212	146	1	the	the	DET
cana-5212	146	2	pooling	pool	VERB
cana-5212	146	3	layers	layer	NOUN
cana-5212	146	4	reduce	reduce	VERB
cana-5212	146	5	spatial	spatial	ADJ
cana-5212	146	6	dimensions	dimension	NOUN
cana-5212	146	7	while	while	SCONJ
cana-5212	146	8	retaining	retain	VERB
cana-5212	146	9	important	important	ADJ
cana-5212	146	10	information	information	NOUN
cana-5212	146	11	and	and	CCONJ
cana-5212	146	12	thus	thus	ADV
cana-5212	146	13	refine	refine	VERB
cana-5212	146	14	such	such	ADJ
cana-5212	146	15	features	feature	NOUN
cana-5212	146	16	.	.	PUNCT
cana-5212	147	1	later	later	ADV
cana-5212	147	2	,	,	PUNCT
cana-5212	147	3	these	these	DET
cana-5212	147	4	processed	process	VERB
cana-5212	147	5	data	datum	NOUN
cana-5212	147	6	pass	pass	VERB
cana-5212	147	7	through	through	ADP
cana-5212	147	8	fully	fully	ADV
cana-5212	147	9	connected	connected	ADJ
cana-5212	147	10	layers	layer	NOUN
cana-5212	147	11	to	to	PART
cana-5212	147	12	finally	finally	ADV
cana-5212	147	13	terminate	terminate	VERB
cana-5212	147	14	at	at	ADP
cana-5212	147	15	the	the	DET
cana-5212	147	16	output	output	NOUN
cana-5212	147	17	layer	layer	NOUN
cana-5212	147	18	where	where	SCONJ
cana-5212	147	19	the	the	DET
cana-5212	147	20	softmax	softmax	NOUN
cana-5212	147	21	activation	activation	NOUN
cana-5212	147	22	function	function	NOUN
cana-5212	147	23	yields	yield	VERB
cana-5212	147	24	a	a	DET
cana-5212	147	25	probability	probability	NOUN
cana-5212	147	26	distribution	distribution	NOUN
cana-5212	147	27	across	across	ADP
cana-5212	147	28	multiple	multiple	ADJ
cana-5212	147	29	classes	class	NOUN
cana-5212	147	30	of	of	ADP
cana-5212	147	31	diseases	disease	NOUN
cana-5212	147	32	.	.	PUNCT
cana-5212	148	1	hence	hence	ADV
cana-5212	148	2	,	,	PUNCT
cana-5212	148	3	the	the	DET
cana-5212	148	4	cnn	cnn	PROPN
cana-5212	148	5	classifies	classify	VERB
cana-5212	148	6	diseases	disease	NOUN
cana-5212	148	7	in	in	ADP
cana-5212	148	8	the	the	DET
cana-5212	148	9	input	input	NOUN
cana-5212	148	10	images	image	NOUN
cana-5212	148	11	with	with	ADP
cana-5212	148	12	very	very	ADV
cana-5212	148	13	high	high	ADJ
cana-5212	148	14	accuracy	accuracy	NOUN
cana-5212	148	15	.	.	PUNCT
cana-5212	149	1	3.3.3	3.3.3	NUM
cana-5212	149	2	step	step	VERB
cana-5212	149	3	3	3	NUM
cana-5212	149	4	:	:	PUNCT
cana-5212	149	5	severity	severity	NOUN
cana-5212	149	6	rating	rating	NOUN
cana-5212	149	7	of	of	ADP
cana-5212	149	8	detected	detect	VERB
cana-5212	149	9	diseases	disease	NOUN
cana-5212	149	10	using	use	VERB
cana-5212	149	11	fuzzy	fuzzy	ADJ
cana-5212	149	12	logic	logic	NOUN
cana-5212	149	13	these	these	DET
cana-5212	149	14	classification	classification	NOUN
cana-5212	149	15	results	result	NOUN
cana-5212	149	16	from	from	ADP
cana-5212	149	17	the	the	DET
cana-5212	149	18	cnn	cnn	PROPN
cana-5212	149	19	are	be	AUX
cana-5212	149	20	used	use	VERB
cana-5212	149	21	as	as	ADP
cana-5212	149	22	input	input	NOUN
cana-5212	149	23	to	to	ADP
cana-5212	149	24	the	the	DET
cana-5212	149	25	fis	fis	PROPN
cana-5212	149	26	.	.	PUNCT
cana-5212	150	1	further	far	ADV
cana-5212	150	2	,	,	PUNCT
cana-5212	150	3	using	use	VERB
cana-5212	150	4	the	the	DET
cana-5212	150	5	inputs	input	NOUN
cana-5212	150	6	from	from	ADP
cana-5212	150	7	the	the	DET
cana-5212	150	8	classification	classification	NOUN
cana-5212	150	9	through	through	ADP
cana-5212	150	10	the	the	DET
cana-5212	150	11	fis	fis	PROPN
cana-5212	150	12	,	,	PUNCT
cana-5212	150	13	it	it	PRON
cana-5212	150	14	is	be	AUX
cana-5212	150	15	estimating	estimate	VERB
cana-5212	150	16	the	the	DET
cana-5212	150	17	diseases	disease	NOUN
cana-5212	150	18	'	'	PART
cana-5212	150	19	severity	severity	NOUN
cana-5212	150	20	rating	rating	NOUN
cana-5212	150	21	.	.	PUNCT
cana-5212	151	1	the	the	DET
cana-5212	151	2	rating	rating	NOUN
cana-5212	151	3	of	of	ADP
cana-5212	151	4	the	the	DET
cana-5212	151	5	degree	degree	NOUN
cana-5212	151	6	of	of	ADP
cana-5212	151	7	severity	severity	NOUN
cana-5212	151	8	is	be	AUX
cana-5212	151	9	based	base	VERB
cana-5212	151	10	on	on	ADP
cana-5212	151	11	fuzzy	fuzzy	ADJ
cana-5212	151	12	rules	rule	NOUN
cana-5212	151	13	defined	define	VERB
cana-5212	151	14	from	from	ADP
cana-5212	151	15	expert	expert	ADJ
cana-5212	151	16	knowledge	knowledge	NOUN
cana-5212	151	17	and	and	CCONJ
cana-5212	151	18	empirical	empirical	ADJ
cana-5212	151	19	data	datum	NOUN
cana-5212	151	20	.	.	PUNCT
cana-5212	152	1	for	for	ADP
cana-5212	152	2	example	example	NOUN
cana-5212	152	3	,	,	PUNCT
cana-5212	152	4	one	one	NUM
cana-5212	152	5	of	of	ADP
cana-5212	152	6	the	the	DET
cana-5212	152	7	rules	rule	NOUN
cana-5212	152	8	could	could	AUX
cana-5212	152	9	be	be	AUX
cana-5212	152	10	that	that	SCONJ
cana-5212	152	11	in	in	ADP
cana-5212	152	12	the	the	DET
cana-5212	152	13	case	case	NOUN
cana-5212	152	14	of	of	ADP
cana-5212	152	15	a	a	DET
cana-5212	152	16	certain	certain	ADJ
cana-5212	152	17	disease	disease	NOUN
cana-5212	152	18	being	be	AUX
cana-5212	152	19	detected	detect	VERB
cana-5212	152	20	with	with	ADP
cana-5212	152	21	a	a	DET
cana-5212	152	22	high	high	ADJ
cana-5212	152	23	probability	probability	NOUN
cana-5212	152	24	,	,	PUNCT
cana-5212	152	25	it	it	PRON
cana-5212	152	26	will	will	AUX
cana-5212	152	27	also	also	ADV
cana-5212	152	28	have	have	VERB
cana-5212	152	29	high	high	ADJ
cana-5212	152	30	severity	severity	NOUN
cana-5212	152	31	.	.	PUNCT
cana-5212	153	1	membership	membership	NOUN
cana-5212	153	2	functions	function	NOUN
cana-5212	153	3	would	would	AUX
cana-5212	153	4	be	be	AUX
cana-5212	153	5	set	set	VERB
cana-5212	153	6	at	at	ADP
cana-5212	153	7	this	this	DET
cana-5212	153	8	stage	stage	NOUN
cana-5212	153	9	to	to	ADP
cana-5212	153	10	communications	communication	NOUN
cana-5212	153	11	on	on	ADP
cana-5212	153	12	applied	apply	VERB
cana-5212	153	13	nonlinear	nonlinear	ADJ
cana-5212	153	14	analysis	analysis	NOUN
cana-5212	153	15	issn	issn	NOUN
cana-5212	153	16	:	:	PUNCT
cana-5212	153	17	1074	1074	NUM
cana-5212	153	18	-	-	PUNCT
cana-5212	153	19	133x	133x	NUM
cana-5212	153	20	vol	vol	NOUN
cana-5212	153	21	32	32	NUM
cana-5212	153	22	no	no	NOUN
cana-5212	153	23	.	.	PUNCT
cana-5212	154	1	8s	8s	PROPN
cana-5212	154	2	(	(	PUNCT
cana-5212	154	3	2025	2025	NUM
cana-5212	154	4	)	)	PUNCT
cana-5212	154	5	942	942	NUM
cana-5212	154	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	154	7	consider	consider	VERB
cana-5212	154	8	the	the	DET
cana-5212	154	9	uncertainty	uncertainty	NOUN
cana-5212	154	10	and	and	CCONJ
cana-5212	154	11	variation	variation	NOUN
cana-5212	154	12	in	in	ADP
cana-5212	154	13	symptoms	symptom	NOUN
cana-5212	154	14	of	of	ADP
cana-5212	154	15	a	a	DET
cana-5212	154	16	disease	disease	NOUN
cana-5212	154	17	and	and	CCONJ
cana-5212	154	18	present	present	ADJ
cana-5212	154	19	variable	variable	ADJ
cana-5212	154	20	degrees	degree	NOUN
cana-5212	154	21	of	of	ADP
cana-5212	154	22	severity	severity	NOUN
cana-5212	154	23	.	.	PUNCT
cana-5212	155	1	3.3.4	3.3.4	NUM
cana-5212	155	2	step	step	NOUN
cana-5212	155	3	4	4	NUM
cana-5212	155	4	:	:	PUNCT
cana-5212	155	5	defuzzification	defuzzification	NOUN
cana-5212	155	6	for	for	ADP
cana-5212	155	7	disease	disease	NOUN
cana-5212	155	8	type	type	NOUN
cana-5212	155	9	,	,	PUNCT
cana-5212	155	10	severity	severity	NOUN
cana-5212	155	11	level	level	NOUN
cana-5212	155	12	,	,	PUNCT
cana-5212	155	13	and	and	CCONJ
cana-5212	155	14	suggested	suggest	VERB
cana-5212	155	15	treatment	treatment	NOUN
cana-5212	155	16	this	this	PRON
cana-5212	155	17	is	be	AUX
cana-5212	155	18	the	the	DET
cana-5212	155	19	ultimate	ultimate	ADJ
cana-5212	155	20	output	output	NOUN
cana-5212	155	21	of	of	ADP
cana-5212	155	22	the	the	DET
cana-5212	155	23	integrated	integrate	VERB
cana-5212	155	24	system	system	NOUN
cana-5212	155	25	,	,	PUNCT
cana-5212	155	26	which	which	PRON
cana-5212	155	27	will	will	AUX
cana-5212	155	28	include	include	VERB
cana-5212	155	29	disease	disease	NOUN
cana-5212	155	30	classification	classification	NOUN
cana-5212	155	31	,	,	PUNCT
cana-5212	155	32	evaluation	evaluation	NOUN
cana-5212	155	33	of	of	ADP
cana-5212	155	34	the	the	DET
cana-5212	155	35	severity	severity	NOUN
cana-5212	155	36	level	level	NOUN
cana-5212	155	37	of	of	ADP
cana-5212	155	38	the	the	DET
cana-5212	155	39	disease	disease	NOUN
cana-5212	155	40	,	,	PUNCT
cana-5212	155	41	and	and	CCONJ
cana-5212	155	42	treatment	treatment	NOUN
cana-5212	155	43	recommendations	recommendation	NOUN
cana-5212	155	44	.	.	PUNCT
cana-5212	156	1	further	far	ADV
cana-5212	156	2	,	,	PUNCT
cana-5212	156	3	the	the	DET
cana-5212	156	4	severity	severity	NOUN
cana-5212	156	5	level	level	NOUN
cana-5212	156	6	shall	shall	AUX
cana-5212	156	7	be	be	AUX
cana-5212	156	8	classified	classify	VERB
cana-5212	156	9	at	at	ADP
cana-5212	156	10	different	different	ADJ
cana-5212	156	11	ranges	range	NOUN
cana-5212	156	12	like	like	ADP
cana-5212	156	13	mild	mild	ADJ
cana-5212	156	14	,	,	PUNCT
cana-5212	156	15	moderate	moderate	ADJ
cana-5212	156	16	,	,	PUNCT
cana-5212	156	17	and	and	CCONJ
cana-5212	156	18	severe	severe	ADJ
cana-5212	156	19	;	;	PUNCT
cana-5212	156	20	in	in	ADP
cana-5212	156	21	each	each	DET
cana-5212	156	22	category	category	NOUN
cana-5212	156	23	,	,	PUNCT
cana-5212	156	24	the	the	DET
cana-5212	156	25	treatment	treatment	NOUN
cana-5212	156	26	recommendations	recommendation	NOUN
cana-5212	156	27	against	against	ADP
cana-5212	156	28	.	.	PUNCT
cana-5212	157	1	in	in	ADP
cana-5212	157	2	full	full	ADJ
cana-5212	157	3	output	output	NOUN
cana-5212	157	4	like	like	ADP
cana-5212	157	5	this	this	PRON
cana-5212	157	6	,	,	PUNCT
cana-5212	157	7	it	it	PRON
cana-5212	157	8	will	will	AUX
cana-5212	157	9	help	help	VERB
cana-5212	157	10	farmers	farmer	NOUN
cana-5212	157	11	to	to	PART
cana-5212	157	12	make	make	VERB
cana-5212	157	13	informed	informed	ADJ
cana-5212	157	14	decisions	decision	NOUN
cana-5212	157	15	regarding	regard	VERB
cana-5212	157	16	management	management	NOUN
cana-5212	157	17	and	and	CCONJ
cana-5212	157	18	ensure	ensure	VERB
cana-5212	157	19	timely	timely	ADJ
cana-5212	157	20	and	and	CCONJ
cana-5212	157	21	appropriate	appropriate	ADJ
cana-5212	157	22	intervention	intervention	NOUN
cana-5212	157	23	measures	measure	NOUN
cana-5212	157	24	are	be	AUX
cana-5212	157	25	taken	take	VERB
cana-5212	157	26	.	.	PUNCT
cana-5212	158	1	3.3.5	3.3.5	NUM
cana-5212	158	2	flowchart	flowchart	NOUN
cana-5212	158	3	of	of	ADP
cana-5212	158	4	proposed	propose	VERB
cana-5212	158	5	algorithm	algorithm	NOUN
cana-5212	158	6	:	:	PUNCT
cana-5212	158	7	input	input	ADJ
cana-5212	158	8	raw	raw	ADJ
cana-5212	158	9	images	image	NOUN
cana-5212	158	10	:	:	PUNCT
cana-5212	158	11	extract	extract	VERB
cana-5212	158	12	raw	raw	ADJ
cana-5212	158	13	images	image	NOUN
cana-5212	158	14	of	of	ADP
cana-5212	158	15	leaves	leave	NOUN
cana-5212	158	16	of	of	ADP
cana-5212	158	17	plants	plant	NOUN
cana-5212	158	18	from	from	ADP
cana-5212	158	19	the	the	DET
cana-5212	158	20	dataset	dataset	NOUN
cana-5212	158	21	.	.	PUNCT
cana-5212	159	1	preprocessing	preprocesse	VERB
cana-5212	159	2	(	(	PUNCT
cana-5212	159	3	if	if	SCONJ
cana-5212	159	4	required	require	VERB
cana-5212	159	5	)	)	PUNCT
cana-5212	159	6	very	very	ADV
cana-5212	159	7	minimal	minimal	ADJ
cana-5212	159	8	preprocessing	preprocessing	NOUN
cana-5212	159	9	is	be	AUX
cana-5212	159	10	to	to	PART
cana-5212	159	11	be	be	AUX
cana-5212	159	12	done	do	VERB
cana-5212	159	13	so	so	SCONJ
cana-5212	159	14	that	that	SCONJ
cana-5212	159	15	all	all	PRON
cana-5212	159	16	are	be	AUX
cana-5212	159	17	uniform	uniform	ADJ
cana-5212	159	18	,	,	PUNCT
cana-5212	159	19	say	say	VERB
cana-5212	159	20	resizing	resizing	NOUN
cana-5212	159	21	and	and	CCONJ
cana-5212	159	22	normalization	normalization	NOUN
cana-5212	159	23	.	.	PUNCT
cana-5212	160	1	feature	feature	NOUN
cana-5212	160	2	extraction	extraction	NOUN
cana-5212	160	3	using	use	VERB
cana-5212	160	4	cnn	cnn	PROPN
cana-5212	160	5	convolving	convolve	VERB
cana-5212	160	6	images	image	NOUN
cana-5212	160	7	through	through	ADP
cana-5212	160	8	convolutional	convolutional	ADJ
cana-5212	160	9	layers	layer	NOUN
cana-5212	160	10	and	and	CCONJ
cana-5212	160	11	feature	feature	NOUN
cana-5212	160	12	extraction	extraction	NOUN
cana-5212	160	13	.	.	PUNCT
cana-5212	161	1	use	use	NOUN
cana-5212	161	2	pooling	pool	VERB
cana-5212	161	3	layers	layer	NOUN
cana-5212	161	4	to	to	PART
cana-5212	161	5	keep	keep	VERB
cana-5212	161	6	only	only	ADV
cana-5212	161	7	the	the	DET
cana-5212	161	8	critical	critical	ADJ
cana-5212	161	9	information	information	NOUN
cana-5212	161	10	and	and	CCONJ
cana-5212	161	11	dimensionality	dimensionality	NOUN
cana-5212	161	12	reduction	reduction	NOUN
cana-5212	161	13	.	.	PUNCT
cana-5212	162	1	disease	disease	NOUN
cana-5212	162	2	classification	classification	NOUN
cana-5212	162	3	feed	feed	VERB
cana-5212	162	4	the	the	DET
cana-5212	162	5	extracted	extract	VERB
cana-5212	162	6	features	feature	NOUN
cana-5212	162	7	to	to	ADP
cana-5212	162	8	fully	fully	ADV
cana-5212	162	9	connected	connected	ADJ
cana-5212	162	10	layers	layer	NOUN
cana-5212	162	11	.	.	PUNCT
cana-5212	163	1	classify	classify	VERB
cana-5212	163	2	the	the	DET
cana-5212	163	3	diseases	disease	NOUN
cana-5212	163	4	in	in	ADP
cana-5212	163	5	multiple	multiple	ADJ
cana-5212	163	6	classes	class	NOUN
cana-5212	163	7	using	use	VERB
cana-5212	163	8	softmax	softmax	NOUN
cana-5212	163	9	activation	activation	NOUN
cana-5212	163	10	function	function	NOUN
cana-5212	163	11	severity	severity	NOUN
cana-5212	163	12	analysis	analysis	NOUN
cana-5212	163	13	using	use	VERB
cana-5212	163	14	fuzzy	fuzzy	ADJ
cana-5212	163	15	logic	logic	NOUN
cana-5212	163	16	feed	feed	VERB
cana-5212	163	17	the	the	DET
cana-5212	163	18	probabilities	probability	NOUN
cana-5212	163	19	obtained	obtain	VERB
cana-5212	163	20	by	by	ADP
cana-5212	163	21	classification	classification	NOUN
cana-5212	163	22	through	through	ADP
cana-5212	163	23	cnn	cnn	PROPN
cana-5212	163	24	in	in	ADP
cana-5212	163	25	the	the	DET
cana-5212	163	26	fis	fis	PROPN
cana-5212	163	27	.	.	PUNCT
cana-5212	164	1	checking	check	VERB
cana-5212	164	2	the	the	DET
cana-5212	164	3	severity	severity	NOUN
cana-5212	164	4	of	of	ADP
cana-5212	164	5	a	a	DET
cana-5212	164	6	disease	disease	NOUN
cana-5212	164	7	by	by	ADP
cana-5212	164	8	applying	apply	VERB
cana-5212	164	9	fuzzy	fuzzy	ADJ
cana-5212	164	10	rules	rule	NOUN
cana-5212	164	11	and	and	CCONJ
cana-5212	164	12	membership	membership	NOUN
cana-5212	164	13	functions	function	NOUN
cana-5212	164	14	.	.	PUNCT
cana-5212	165	1	output	output	NOUN
cana-5212	165	2	generation	generation	NOUN
cana-5212	165	3	:	:	PUNCT
cana-5212	165	4	generation	generation	NOUN
cana-5212	165	5	of	of	ADP
cana-5212	165	6	final	final	ADJ
cana-5212	165	7	output	output	NOUN
cana-5212	165	8	to	to	PART
cana-5212	165	9	include	include	VERB
cana-5212	165	10	type	type	NOUN
cana-5212	165	11	of	of	ADP
cana-5212	165	12	disease	disease	NOUN
cana-5212	165	13	,	,	PUNCT
cana-5212	165	14	its	its	PRON
cana-5212	165	15	severity	severity	NOUN
cana-5212	165	16	level	level	NOUN
cana-5212	165	17	and	and	CCONJ
cana-5212	165	18	treatment	treatment	NOUN
cana-5212	165	19	to	to	PART
cana-5212	165	20	be	be	AUX
cana-5212	165	21	suggested	suggest	VERB
cana-5212	165	22	for	for	ADP
cana-5212	165	23	the	the	DET
cana-5212	165	24	same	same	ADJ
cana-5212	165	25	.	.	PUNCT
cana-5212	166	1	hence	hence	ADV
cana-5212	166	2	,	,	PUNCT
cana-5212	166	3	a	a	DET
cana-5212	166	4	detailed	detailed	ADJ
cana-5212	166	5	,	,	PUNCT
cana-5212	166	6	step	step	NOUN
cana-5212	166	7	-	-	PUNCT
cana-5212	166	8	by	by	ADP
cana-5212	166	9	-	-	PUNCT
cana-5212	166	10	step	step	NOUN
cana-5212	166	11	process	process	NOUN
cana-5212	166	12	synergistically	synergistically	ADV
cana-5212	166	13	founded	found	VERB
cana-5212	166	14	on	on	ADP
cana-5212	166	15	cnns	cnns	ADJ
cana-5212	166	16	and	and	CCONJ
cana-5212	166	17	fuzzy	fuzzy	ADJ
cana-5212	166	18	logic	logic	NOUN
cana-5212	166	19	would	would	AUX
cana-5212	166	20	be	be	AUX
cana-5212	166	21	of	of	ADP
cana-5212	166	22	long	long	ADJ
cana-5212	166	23	strides	stride	NOUN
cana-5212	166	24	toward	toward	ADP
cana-5212	166	25	the	the	DET
cana-5212	166	26	development	development	NOUN
cana-5212	166	27	of	of	ADP
cana-5212	166	28	a	a	DET
cana-5212	166	29	more	more	ADV
cana-5212	166	30	comprehensive	comprehensive	ADJ
cana-5212	166	31	and	and	CCONJ
cana-5212	166	32	rugged	rugged	ADJ
cana-5212	166	33	approach	approach	NOUN
cana-5212	166	34	for	for	ADP
cana-5212	166	35	detection	detection	NOUN
cana-5212	166	36	of	of	ADP
cana-5212	166	37	the	the	DET
cana-5212	166	38	diseases	disease	NOUN
cana-5212	166	39	in	in	ADP
cana-5212	166	40	plants	plant	NOUN
cana-5212	166	41	and	and	CCONJ
cana-5212	166	42	their	their	PRON
cana-5212	166	43	management	management	NOUN
cana-5212	166	44	with	with	ADP
cana-5212	166	45	high	high	ADJ
cana-5212	166	46	accuracy	accuracy	NOUN
cana-5212	166	47	and	and	CCONJ
cana-5212	166	48	actionable	actionable	ADJ
cana-5212	166	49	insight	insight	NOUN
cana-5212	166	50	into	into	ADP
cana-5212	166	51	its	its	PRON
cana-5212	166	52	effective	effective	ADJ
cana-5212	166	53	control	control	NOUN
cana-5212	166	54	in	in	ADP
cana-5212	166	55	agriculture	agriculture	NOUN
cana-5212	166	56	.	.	PUNCT
cana-5212	167	1	communications	communication	NOUN
cana-5212	167	2	on	on	ADP
cana-5212	167	3	applied	apply	VERB
cana-5212	167	4	nonlinear	nonlinear	ADJ
cana-5212	167	5	analysis	analysis	NOUN
cana-5212	167	6	issn	issn	NOUN
cana-5212	167	7	:	:	PUNCT
cana-5212	167	8	1074	1074	NUM
cana-5212	167	9	-	-	PUNCT
cana-5212	167	10	133x	133x	NUM
cana-5212	167	11	vol	vol	NOUN
cana-5212	167	12	32	32	NUM
cana-5212	167	13	no	no	NOUN
cana-5212	167	14	.	.	PUNCT
cana-5212	168	1	8s	8s	PROPN
cana-5212	168	2	(	(	PUNCT
cana-5212	168	3	2025	2025	NUM
cana-5212	168	4	)	)	PUNCT
cana-5212	168	5	943	943	NUM
cana-5212	168	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	168	7	figure	figure	NOUN
cana-5212	168	8	3	3	NUM
cana-5212	168	9	:	:	PUNCT
cana-5212	168	10	workflow	workflow	NOUN
cana-5212	168	11	of	of	ADP
cana-5212	168	12	the	the	DET
cana-5212	168	13	proposed	propose	VERB
cana-5212	168	14	cnn	cnn	PROPN
cana-5212	168	15	and	and	CCONJ
cana-5212	168	16	fuzzy	fuzzy	ADJ
cana-5212	168	17	logic	logic	NOUN
cana-5212	168	18	integration	integration	NOUN
cana-5212	168	19	method	method	VERB
cana-5212	168	20	this	this	DET
cana-5212	168	21	figure	figure	NOUN
cana-5212	168	22	(	(	PUNCT
cana-5212	168	23	3	3	NUM
cana-5212	168	24	)	)	PUNCT
cana-5212	168	25	flowchart	flowchart	NOUN
cana-5212	168	26	outlines	outline	VERB
cana-5212	168	27	the	the	DET
cana-5212	168	28	steps	step	NOUN
cana-5212	168	29	involved	involve	VERB
cana-5212	168	30	in	in	ADP
cana-5212	168	31	the	the	DET
cana-5212	168	32	proposed	propose	VERB
cana-5212	168	33	method	method	NOUN
cana-5212	168	34	,	,	PUNCT
cana-5212	168	35	starting	start	VERB
cana-5212	168	36	from	from	ADP
cana-5212	168	37	the	the	DET
cana-5212	168	38	preprocessing	preprocessing	NOUN
cana-5212	168	39	of	of	ADP
cana-5212	168	40	raw	raw	ADJ
cana-5212	168	41	images	image	NOUN
cana-5212	168	42	to	to	ADP
cana-5212	168	43	training	train	VERB
cana-5212	168	44	multiple	multiple	ADJ
cana-5212	168	45	cnn	cnn	PROPN
cana-5212	168	46	models	model	NOUN
cana-5212	168	47	.	.	PUNCT
cana-5212	169	1	it	it	PRON
cana-5212	169	2	then	then	ADV
cana-5212	169	3	proceeds	proceed	VERB
cana-5212	169	4	with	with	ADP
cana-5212	169	5	the	the	DET
cana-5212	169	6	integration	integration	NOUN
cana-5212	169	7	of	of	ADP
cana-5212	169	8	fuzzy	fuzzy	ADJ
cana-5212	169	9	logic	logic	NOUN
cana-5212	169	10	using	use	VERB
cana-5212	169	11	particle	particle	NOUN
cana-5212	169	12	swarm	swarm	NOUN
cana-5212	169	13	optimization	optimization	NOUN
cana-5212	169	14	(	(	PUNCT
cana-5212	169	15	pso	pso	NOUN
cana-5212	169	16	)	)	PUNCT
cana-5212	169	17	to	to	PART
cana-5212	169	18	determine	determine	VERB
cana-5212	169	19	the	the	DET
cana-5212	169	20	optimal	optimal	ADJ
cana-5212	169	21	fuzzy	fuzzy	ADJ
cana-5212	169	22	density	density	NOUN
cana-5212	169	23	,	,	PUNCT
cana-5212	169	24	culminating	culminate	VERB
cana-5212	169	25	in	in	ADP
cana-5212	169	26	the	the	DET
cana-5212	169	27	calculation	calculation	NOUN
cana-5212	169	28	of	of	ADP
cana-5212	169	29	choquet	choquet	NOUN
cana-5212	169	30	and	and	CCONJ
cana-5212	169	31	sugeno	sugeno	VERB
cana-5212	169	32	fuzzy	fuzzy	ADJ
cana-5212	169	33	integrals	integral	NOUN
cana-5212	169	34	for	for	ADP
cana-5212	169	35	the	the	DET
cana-5212	169	36	best	good	ADJ
cana-5212	169	37	classification	classification	NOUN
cana-5212	169	38	results	result	NOUN
cana-5212	169	39	.	.	PUNCT
cana-5212	170	1	this	this	DET
cana-5212	170	2	figure	figure	NOUN
cana-5212	170	3	should	should	AUX
cana-5212	170	4	be	be	AUX
cana-5212	170	5	placed	place	VERB
cana-5212	170	6	in	in	ADP
cana-5212	170	7	section	section	NOUN
cana-5212	170	8	3.3	3.3	NUM
cana-5212	170	9	steps	step	NOUN
cana-5212	170	10	and	and	CCONJ
cana-5212	170	11	flowcharts	flowchart	NOUN
cana-5212	170	12	.	.	PUNCT
cana-5212	171	1	4.implementation	4.implementation	NOUN
cana-5212	171	2	4.1	4.1	NUM
cana-5212	171	3	dataset	dataset	VERB
cana-5212	171	4	the	the	DET
cana-5212	171	5	total	total	ADJ
cana-5212	171	6	dataset	dataset	NOUN
cana-5212	171	7	used	use	VERB
cana-5212	171	8	in	in	ADP
cana-5212	171	9	this	this	DET
cana-5212	171	10	research	research	NOUN
cana-5212	171	11	includes	include	VERB
cana-5212	171	12	raw	raw	ADJ
cana-5212	171	13	images	image	NOUN
cana-5212	171	14	of	of	ADP
cana-5212	171	15	the	the	DET
cana-5212	171	16	leaves	leave	NOUN
cana-5212	171	17	of	of	ADP
cana-5212	171	18	the	the	DET
cana-5212	171	19	following	follow	VERB
cana-5212	171	20	seven	seven	NUM
cana-5212	171	21	crops	crop	NOUN
cana-5212	171	22	:	:	PUNCT
cana-5212	171	23	rice	rice	NOUN
cana-5212	171	24	,	,	PUNCT
cana-5212	171	25	wheat	wheat	NOUN
cana-5212	171	26	,	,	PUNCT
cana-5212	171	27	corn	corn	NOUN
cana-5212	171	28	,	,	PUNCT
cana-5212	171	29	sugarcane	sugarcane	NOUN
cana-5212	171	30	,	,	PUNCT
cana-5212	171	31	maize	maize	NOUN
cana-5212	171	32	,	,	PUNCT
cana-5212	171	33	barley	barley	NOUN
cana-5212	171	34	,	,	PUNCT
cana-5212	171	35	and	and	CCONJ
cana-5212	171	36	jowar	jowar	NOUN
cana-5212	171	37	.	.	PUNCT
cana-5212	172	1	all	all	DET
cana-5212	172	2	these	these	DET
cana-5212	172	3	images	image	NOUN
cana-5212	172	4	capture	capture	VERB
cana-5212	172	5	various	various	ADJ
cana-5212	172	6	disease	disease	NOUN
cana-5212	172	7	symptoms	symptom	NOUN
cana-5212	172	8	and	and	CCONJ
cana-5212	172	9	,	,	PUNCT
cana-5212	172	10	hence	hence	ADV
cana-5212	172	11	,	,	PUNCT
cana-5212	172	12	effectively	effectively	ADV
cana-5212	172	13	represent	represent	VERB
cana-5212	172	14	common	common	ADJ
cana-5212	172	15	plant	plant	NOUN
cana-5212	172	16	diseases	disease	NOUN
cana-5212	172	17	.	.	PUNCT
cana-5212	173	1	these	these	DET
cana-5212	173	2	images	image	NOUN
cana-5212	173	3	were	be	AUX
cana-5212	173	4	fetched	fetch	VERB
cana-5212	173	5	from	from	ADP
cana-5212	173	6	multiple	multiple	ADJ
cana-5212	173	7	public	public	ADJ
cana-5212	173	8	repositories	repository	NOUN
cana-5212	173	9	like	like	ADP
cana-5212	173	10	kaggle	kaggle	NOUN
cana-5212	173	11	and	and	CCONJ
cana-5212	173	12	uci	uci	PROPN
cana-5212	173	13	machine	machine	NOUN
cana-5212	173	14	learning	learn	VERB
cana-5212	173	15	repository	repository	NOUN
cana-5212	173	16	,	,	PUNCT
cana-5212	173	17	that	that	PRON
cana-5212	173	18	generally	generally	ADV
cana-5212	173	19	supply	supply	VERB
cana-5212	173	20	high	high	ADJ
cana-5212	173	21	-	-	PUNCT
cana-5212	173	22	quality	quality	NOUN
cana-5212	173	23	and	and	CCONJ
cana-5212	173	24	diverse	diverse	ADJ
cana-5212	173	25	datasets	dataset	NOUN
cana-5212	173	26	.	.	PUNCT
cana-5212	174	1	4.1.1	4.1.1	NUM
cana-5212	174	2	sources	source	NOUN
cana-5212	174	3	:	:	PUNCT
cana-5212	174	4	kaggle	kaggle	ADJ
cana-5212	174	5	-	-	PUNCT
cana-5212	174	6	plant	plant	NOUN
cana-5212	174	7	village	village	NOUN
cana-5212	174	8	dataset	dataset	NOUN
cana-5212	174	9	:	:	PUNCT
cana-5212	174	10	this	this	DET
cana-5212	174	11	dataset	dataset	NOUN
cana-5212	174	12	has	have	VERB
cana-5212	174	13	images	image	NOUN
cana-5212	174	14	of	of	ADP
cana-5212	174	15	healthy	healthy	ADJ
cana-5212	174	16	and	and	CCONJ
cana-5212	174	17	diseased	diseased	ADJ
cana-5212	174	18	plant	plant	NOUN
cana-5212	174	19	leaves	leave	NOUN
cana-5212	174	20	.	.	PUNCT
cana-5212	175	1	therefore	therefore	ADV
cana-5212	175	2	,	,	PUNCT
cana-5212	175	3	in	in	ADP
cana-5212	175	4	this	this	DET
cana-5212	175	5	regard	regard	NOUN
cana-5212	175	6	,	,	PUNCT
cana-5212	175	7	it	it	PRON
cana-5212	175	8	provides	provide	VERB
cana-5212	175	9	a	a	DET
cana-5212	175	10	rich	rich	ADJ
cana-5212	175	11	source	source	NOUN
cana-5212	175	12	of	of	ADP
cana-5212	175	13	labelled	label	VERB
cana-5212	175	14	data	datum	NOUN
cana-5212	175	15	for	for	ADP
cana-5212	175	16	training	training	NOUN
cana-5212	175	17	and	and	CCONJ
cana-5212	175	18	validation	validation	NOUN
cana-5212	175	19	.	.	PUNCT
cana-5212	176	1	the	the	DET
cana-5212	176	2	wide	wide	ADV
cana-5212	176	3	-	-	PUNCT
cana-5212	176	4	ranging	range	VERB
cana-5212	176	5	datasets	dataset	NOUN
cana-5212	176	6	available	available	ADJ
cana-5212	176	7	in	in	ADP
cana-5212	176	8	the	the	DET
cana-5212	176	9	uci	uci	PROPN
cana-5212	176	10	machine	machine	NOUN
cana-5212	176	11	learning	learn	VERB
cana-5212	176	12	repository	repository	NOUN
cana-5212	176	13	include	include	VERB
cana-5212	176	14	those	those	PRON
cana-5212	176	15	on	on	ADP
cana-5212	176	16	plant	plant	NOUN
cana-5212	176	17	pathology	pathology	NOUN
cana-5212	176	18	,	,	PUNCT
cana-5212	176	19	which	which	PRON
cana-5212	176	20	are	be	AUX
cana-5212	176	21	invaluable	invaluable	ADJ
cana-5212	176	22	to	to	ADP
cana-5212	176	23	machine	machine	NOUN
cana-5212	176	24	learning	learn	VERB
cana-5212	176	25	research	research	NOUN
cana-5212	176	26	.	.	PUNCT
cana-5212	177	1	each	each	DET
cana-5212	177	2	image	image	NOUN
cana-5212	177	3	is	be	AUX
cana-5212	177	4	annotated	annotate	VERB
cana-5212	177	5	with	with	ADP
cana-5212	177	6	the	the	DET
cana-5212	177	7	type	type	NOUN
cana-5212	177	8	of	of	ADP
cana-5212	177	9	plant	plant	NOUN
cana-5212	177	10	and	and	CCONJ
cana-5212	177	11	which	which	DET
cana-5212	177	12	particular	particular	ADJ
cana-5212	177	13	disease	disease	NOUN
cana-5212	177	14	the	the	DET
cana-5212	177	15	plant	plant	NOUN
cana-5212	177	16	is	be	AUX
cana-5212	177	17	having	have	VERB
cana-5212	177	18	,	,	PUNCT
cana-5212	177	19	if	if	SCONJ
cana-5212	177	20	any	any	PRON
cana-5212	177	21	.	.	PUNCT
cana-5212	178	1	the	the	DET
cana-5212	178	2	diversity	diversity	NOUN
cana-5212	178	3	in	in	ADP
cana-5212	178	4	this	this	DET
cana-5212	178	5	dataset	dataset	NOUN
cana-5212	178	6	guarantees	guarantee	NOUN
cana-5212	178	7	that	that	SCONJ
cana-5212	178	8	the	the	DET
cana-5212	178	9	model	model	NOUN
cana-5212	178	10	learns	learn	VERB
cana-5212	178	11	under	under	ADP
cana-5212	178	12	a	a	DET
cana-5212	178	13	wide	wide	ADJ
cana-5212	178	14	range	range	NOUN
cana-5212	178	15	of	of	ADP
cana-5212	178	16	diseases	disease	NOUN
cana-5212	178	17	and	and	CCONJ
cana-5212	178	18	many	many	ADJ
cana-5212	178	19	different	different	ADJ
cana-5212	178	20	conditions	condition	NOUN
cana-5212	178	21	.	.	PUNCT
cana-5212	179	1	crop	crop	NOUN
cana-5212	179	2	number	number	NOUN
cana-5212	179	3	of	of	ADP
cana-5212	179	4	images	image	NOUN
cana-5212	179	5	image	image	NOUN
cana-5212	179	6	resolution	resolution	NOUN
cana-5212	179	7	source	source	NOUN
cana-5212	179	8	rice	rice	NOUN
cana-5212	179	9	5,000	5,000	NUM
cana-5212	179	10	256x256	256x256	PROPN
cana-5212	179	11	kaggle	kaggle	PROPN
cana-5212	179	12	,	,	PUNCT
cana-5212	179	13	uci	uci	NOUN
cana-5212	179	14	machine	machine	NOUN
cana-5212	179	15	learning	learn	VERB
cana-5212	179	16	repository	repository	NOUN
cana-5212	179	17	communications	communication	NOUN
cana-5212	179	18	on	on	ADP
cana-5212	179	19	applied	apply	VERB
cana-5212	179	20	nonlinear	nonlinear	ADJ
cana-5212	179	21	analysis	analysis	NOUN
cana-5212	179	22	issn	issn	NOUN
cana-5212	179	23	:	:	PUNCT
cana-5212	179	24	1074	1074	NUM
cana-5212	179	25	-	-	PUNCT
cana-5212	179	26	133x	133x	NUM
cana-5212	179	27	vol	vol	NOUN
cana-5212	179	28	32	32	NUM
cana-5212	179	29	no	no	NOUN
cana-5212	179	30	.	.	PUNCT
cana-5212	180	1	8s	8s	PROPN
cana-5212	180	2	(	(	PUNCT
cana-5212	180	3	2025	2025	NUM
cana-5212	180	4	)	)	PUNCT
cana-5212	180	5	944	944	NUM
cana-5212	181	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	181	2	wheat	wheat	NOUN
cana-5212	181	3	4,500	4,500	NUM
cana-5212	181	4	256x256	256x256	PROPN
cana-5212	181	5	kaggle	kaggle	PROPN
cana-5212	181	6	,	,	PUNCT
cana-5212	181	7	uci	uci	NOUN
cana-5212	181	8	machine	machine	NOUN
cana-5212	181	9	learning	learn	VERB
cana-5212	181	10	repository	repository	NOUN
cana-5212	181	11	corn	corn	NOUN
cana-5212	181	12	4,800	4,800	NUM
cana-5212	181	13	256x256	256x256	PROPN
cana-5212	181	14	kaggle	kaggle	PROPN
cana-5212	181	15	,	,	PUNCT
cana-5212	181	16	uci	uci	NOUN
cana-5212	181	17	machine	machine	NOUN
cana-5212	181	18	learning	learn	VERB
cana-5212	181	19	repository	repository	NOUN
cana-5212	181	20	sugarcane	sugarcane	NOUN
cana-5212	181	21	4,200	4,200	NUM
cana-5212	181	22	256x256	256x256	NUM
cana-5212	181	23	kaggle	kaggle	PROPN
cana-5212	181	24	,	,	PUNCT
cana-5212	181	25	uci	uci	NOUN
cana-5212	181	26	machine	machine	NOUN
cana-5212	181	27	learning	learn	VERB
cana-5212	181	28	repository	repository	NOUN
cana-5212	181	29	maize	maize	NOUN
cana-5212	181	30	4,600	4,600	NUM
cana-5212	181	31	256x256	256x256	PROPN
cana-5212	181	32	kaggle	kaggle	PROPN
cana-5212	181	33	,	,	PUNCT
cana-5212	181	34	uci	uci	NOUN
cana-5212	181	35	machine	machine	NOUN
cana-5212	181	36	learning	learn	VERB
cana-5212	181	37	repository	repository	NOUN
cana-5212	181	38	barley	barley	PROPN
cana-5212	181	39	4,100	4,100	NUM
cana-5212	181	40	256x256	256x256	PROPN
cana-5212	181	41	kaggle	kaggle	PROPN
cana-5212	181	42	,	,	PUNCT
cana-5212	181	43	uci	uci	NOUN
cana-5212	181	44	machine	machine	NOUN
cana-5212	181	45	learning	learn	VERB
cana-5212	181	46	repository	repository	NOUN
cana-5212	181	47	jowar	jowar	NOUN
cana-5212	181	48	4,300	4,300	NUM
cana-5212	181	49	256x256	256x256	PROPN
cana-5212	181	50	kaggle	kaggle	PROPN
cana-5212	181	51	,	,	PUNCT
cana-5212	181	52	uci	uci	NOUN
cana-5212	181	53	machine	machine	NOUN
cana-5212	181	54	learning	learn	VERB
cana-5212	181	55	repository	repository	NOUN
cana-5212	181	56	table	table	NOUN
cana-5212	181	57	1	1	NUM
cana-5212	181	58	:	:	PUNCT
cana-5212	181	59	summary	summary	NOUN
cana-5212	181	60	of	of	ADP
cana-5212	181	61	dataset	dataset	NOUN
cana-5212	181	62	used	use	VERB
cana-5212	181	63	in	in	ADP
cana-5212	181	64	the	the	DET
cana-5212	181	65	research	research	NOUN
cana-5212	181	66	this	this	DET
cana-5212	181	67	table	table	NOUN
cana-5212	181	68	(	(	PUNCT
cana-5212	181	69	1	1	X
cana-5212	181	70	)	)	PUNCT
cana-5212	181	71	summarizes	summarize	VERB
cana-5212	181	72	the	the	DET
cana-5212	181	73	dataset	dataset	NOUN
cana-5212	181	74	used	use	VERB
cana-5212	181	75	in	in	ADP
cana-5212	181	76	the	the	DET
cana-5212	181	77	research	research	NOUN
cana-5212	181	78	,	,	PUNCT
cana-5212	181	79	detailing	detail	VERB
cana-5212	181	80	the	the	DET
cana-5212	181	81	number	number	NOUN
cana-5212	181	82	of	of	ADP
cana-5212	181	83	images	image	NOUN
cana-5212	181	84	,	,	PUNCT
cana-5212	181	85	image	image	NOUN
cana-5212	181	86	resolution	resolution	NOUN
cana-5212	181	87	,	,	PUNCT
cana-5212	181	88	and	and	CCONJ
cana-5212	181	89	sources	source	NOUN
cana-5212	181	90	for	for	ADP
cana-5212	181	91	each	each	DET
cana-5212	181	92	crop	crop	NOUN
cana-5212	181	93	type	type	NOUN
cana-5212	181	94	.	.	PUNCT
cana-5212	182	1	4.2	4.2	NUM
cana-5212	182	2	methodology	methodology	NOUN
cana-5212	182	3	4.2.1	4.2.1	NUM
cana-5212	182	4	resizing	resize	VERB
cana-5212	182	5	images	image	NOUN
cana-5212	182	6	:	:	PUNCT
cana-5212	182	7	before	before	ADP
cana-5212	182	8	training	training	NOUN
cana-5212	182	9	on	on	ADP
cana-5212	182	10	the	the	DET
cana-5212	182	11	raw	raw	ADJ
cana-5212	182	12	images	image	NOUN
cana-5212	182	13	,	,	PUNCT
cana-5212	182	14	several	several	ADJ
cana-5212	182	15	preprocessing	preprocessing	NOUN
cana-5212	182	16	steps	step	NOUN
cana-5212	182	17	are	be	AUX
cana-5212	182	18	done	do	VERB
cana-5212	182	19	:	:	PUNCT
cana-5212	182	20	resizing	resize	VERB
cana-5212	182	21	images	image	NOUN
cana-5212	182	22	to	to	ADP
cana-5212	182	23	uniform	uniform	ADJ
cana-5212	182	24	dimension	dimension	NOUN
cana-5212	182	25	:	:	PUNCT
cana-5212	182	26	all	all	DET
cana-5212	182	27	images	image	NOUN
cana-5212	182	28	are	be	AUX
cana-5212	182	29	resized	resize	VERB
cana-5212	182	30	into	into	ADP
cana-5212	182	31	a	a	DET
cana-5212	182	32	standard	standard	ADJ
cana-5212	182	33	dimension	dimension	NOUN
cana-5212	182	34	,	,	PUNCT
cana-5212	182	35	thereby	thereby	ADV
cana-5212	182	36	allowing	allow	VERB
cana-5212	182	37	uniformity	uniformity	NOUN
cana-5212	182	38	in	in	ADP
cana-5212	182	39	the	the	DET
cana-5212	182	40	dataset	dataset	NOUN
cana-5212	182	41	.	.	PUNCT
cana-5212	183	1	this	this	PRON
cana-5212	183	2	is	be	AUX
cana-5212	183	3	one	one	NUM
cana-5212	183	4	of	of	ADP
cana-5212	183	5	the	the	DET
cana-5212	183	6	steps	step	NOUN
cana-5212	183	7	essential	essential	ADJ
cana-5212	183	8	for	for	ADP
cana-5212	183	9	consistency	consistency	NOUN
cana-5212	183	10	in	in	ADP
cana-5212	183	11	the	the	DET
cana-5212	183	12	input	input	NOUN
cana-5212	183	13	data	datum	NOUN
cana-5212	183	14	,	,	PUNCT
cana-5212	183	15	which	which	PRON
cana-5212	183	16	shall	shall	AUX
cana-5212	183	17	eventually	eventually	ADV
cana-5212	183	18	help	help	VERB
cana-5212	183	19	in	in	ADP
cana-5212	183	20	the	the	DET
cana-5212	183	21	effective	effective	ADJ
cana-5212	183	22	training	training	NOUN
cana-5212	183	23	of	of	ADP
cana-5212	183	24	the	the	DET
cana-5212	183	25	cnn	cnn	PROPN
cana-5212	183	26	.	.	PUNCT
cana-5212	184	1	normalization	normalization	NOUN
cana-5212	184	2	to	to	PART
cana-5212	184	3	standardize	standardize	VERB
cana-5212	184	4	pixel	pixel	ADJ
cana-5212	184	5	values	value	NOUN
cana-5212	184	6	:	:	PUNCT
cana-5212	184	7	pixel	pixel	PROPN
cana-5212	184	8	values	value	NOUN
cana-5212	184	9	of	of	ADP
cana-5212	184	10	the	the	DET
cana-5212	184	11	images	image	NOUN
cana-5212	184	12	are	be	AUX
cana-5212	184	13	normalized	normalize	VERB
cana-5212	184	14	to	to	ADP
cana-5212	184	15	a	a	DET
cana-5212	184	16	range	range	NOUN
cana-5212	184	17	from	from	ADP
cana-5212	184	18	0	0	NUM
cana-5212	184	19	to	to	ADP
cana-5212	184	20	1	1	NUM
cana-5212	184	21	.	.	PUNCT
cana-5212	185	1	this	this	PRON
cana-5212	185	2	comes	come	VERB
cana-5212	185	3	in	in	ADP
cana-5212	185	4	handy	handy	ADJ
cana-5212	185	5	,	,	PUNCT
cana-5212	185	6	for	for	ADP
cana-5212	185	7	the	the	DET
cana-5212	185	8	most	most	ADJ
cana-5212	185	9	part	part	NOUN
cana-5212	185	10	,	,	PUNCT
cana-5212	185	11	in	in	ADP
cana-5212	185	12	speeding	speed	VERB
cana-5212	185	13	up	up	ADP
cana-5212	185	14	convergence	convergence	NOUN
cana-5212	185	15	while	while	SCONJ
cana-5212	185	16	training	train	VERB
cana-5212	185	17	the	the	DET
cana-5212	185	18	neural	neural	ADJ
cana-5212	185	19	network	network	NOUN
cana-5212	185	20	.	.	PUNCT
cana-5212	186	1	it	it	PRON
cana-5212	186	2	improves	improve	VERB
cana-5212	186	3	performance	performance	NOUN
cana-5212	186	4	.	.	PUNCT
cana-5212	187	1	4.2.2	4.2.2	NUM
cana-5212	187	2	training	training	NOUN
cana-5212	187	3	setup	setup	NOUN
cana-5212	187	4	:	:	PUNCT
cana-5212	187	5	a	a	DET
cana-5212	187	6	few	few	ADJ
cana-5212	187	7	major	major	ADJ
cana-5212	187	8	critical	critical	ADJ
cana-5212	187	9	steps	step	NOUN
cana-5212	187	10	of	of	ADP
cana-5212	187	11	the	the	DET
cana-5212	187	12	training	training	NOUN
cana-5212	187	13	setup	setup	NOUN
cana-5212	187	14	are	be	AUX
cana-5212	187	15	of	of	ADP
cana-5212	187	16	major	major	ADJ
cana-5212	187	17	importance	importance	NOUN
cana-5212	187	18	to	to	PART
cana-5212	187	19	make	make	VERB
cana-5212	187	20	sure	sure	ADJ
cana-5212	187	21	that	that	SCONJ
cana-5212	187	22	the	the	DET
cana-5212	187	23	model	model	NOUN
cana-5212	187	24	is	be	AUX
cana-5212	187	25	effectively	effectively	ADV
cana-5212	187	26	trained	train	VERB
cana-5212	187	27	and	and	CCONJ
cana-5212	187	28	validated	validate	VERB
cana-5212	187	29	for	for	ADP
cana-5212	187	30	the	the	DET
cana-5212	187	31	final	final	ADJ
cana-5212	187	32	task	task	NOUN
cana-5212	187	33	.	.	PUNCT
cana-5212	188	1	split	split	VERB
cana-5212	188	2	the	the	DET
cana-5212	188	3	dataset	dataset	NOUN
cana-5212	188	4	into	into	ADP
cana-5212	188	5	training	training	NOUN
cana-5212	188	6	and	and	CCONJ
cana-5212	188	7	validation	validation	NOUN
cana-5212	188	8	sets	set	NOUN
cana-5212	188	9	:	:	PUNCT
cana-5212	188	10	the	the	DET
cana-5212	188	11	ratio	ratio	NOUN
cana-5212	188	12	of	of	ADP
cana-5212	188	13	80:20	80:20	NUM
cana-5212	188	14	will	will	AUX
cana-5212	188	15	always	always	ADV
cana-5212	188	16	be	be	AUX
cana-5212	188	17	maintained	maintain	VERB
cana-5212	188	18	between	between	ADP
cana-5212	188	19	the	the	DET
cana-5212	188	20	training	training	NOUN
cana-5212	188	21	and	and	CCONJ
cana-5212	188	22	validation	validation	NOUN
cana-5212	188	23	sets	set	NOUN
cana-5212	188	24	.	.	PUNCT
cana-5212	189	1	then	then	ADV
cana-5212	189	2	,	,	PUNCT
cana-5212	189	3	a	a	DET
cana-5212	189	4	feed	feed	NOUN
cana-5212	189	5	is	be	AUX
cana-5212	189	6	given	give	VERB
cana-5212	189	7	to	to	ADP
cana-5212	189	8	the	the	DET
cana-5212	189	9	cnn	cnn	PROPN
cana-5212	189	10	from	from	ADP
cana-5212	189	11	the	the	DET
cana-5212	189	12	training	training	NOUN
cana-5212	189	13	set	set	NOUN
cana-5212	189	14	,	,	PUNCT
cana-5212	189	15	and	and	CCONJ
cana-5212	189	16	during	during	ADP
cana-5212	189	17	the	the	DET
cana-5212	189	18	model	model	NOUN
cana-5212	189	19	training	training	NOUN
cana-5212	189	20	phase	phase	NOUN
cana-5212	189	21	,	,	PUNCT
cana-5212	189	22	it	it	PRON
cana-5212	189	23	makes	make	VERB
cana-5212	189	24	use	use	NOUN
cana-5212	189	25	of	of	ADP
cana-5212	189	26	the	the	DET
cana-5212	189	27	validation	validation	NOUN
cana-5212	189	28	set	set	VERB
cana-5212	189	29	for	for	ADP
cana-5212	189	30	checking	check	VERB
cana-5212	189	31	model	model	NOUN
cana-5212	189	32	performance	performance	NOUN
cana-5212	189	33	and	and	CCONJ
cana-5212	189	34	tuning	tune	VERB
cana-5212	189	35	hyper	hyper	NOUN
cana-5212	189	36	-	-	NOUN
cana-5212	189	37	parameters	parameter	NOUN
cana-5212	189	38	.	.	PUNCT
cana-5212	190	1	communications	communication	NOUN
cana-5212	190	2	on	on	ADP
cana-5212	190	3	applied	apply	VERB
cana-5212	190	4	nonlinear	nonlinear	ADJ
cana-5212	190	5	analysis	analysis	NOUN
cana-5212	190	6	issn	issn	NOUN
cana-5212	190	7	:	:	PUNCT
cana-5212	190	8	1074	1074	NUM
cana-5212	190	9	-	-	PUNCT
cana-5212	190	10	133x	133x	NUM
cana-5212	190	11	vol	vol	NOUN
cana-5212	190	12	32	32	NUM
cana-5212	190	13	no	no	NOUN
cana-5212	190	14	.	.	PUNCT
cana-5212	191	1	8s	8s	PROPN
cana-5212	191	2	(	(	PUNCT
cana-5212	191	3	2025	2025	NUM
cana-5212	191	4	)	)	PUNCT
cana-5212	191	5	945	945	NUM
cana-5212	191	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	191	7	designing	design	VERB
cana-5212	191	8	a	a	DET
cana-5212	191	9	model	model	NOUN
cana-5212	191	10	in	in	ADP
cana-5212	191	11	python	python	PROPN
cana-5212	191	12	,	,	PUNCT
cana-5212	191	13	tensorflow	tensorflow	NOUN
cana-5212	191	14	,	,	PUNCT
cana-5212	191	15	and	and	CCONJ
cana-5212	191	16	kera	kera	PROPN
cana-5212	191	17	’s	’s	PART
cana-5212	191	18	:	:	PUNCT
cana-5212	191	19	the	the	DET
cana-5212	191	20	proposed	propose	VERB
cana-5212	191	21	model	model	NOUN
cana-5212	191	22	will	will	AUX
cana-5212	191	23	be	be	AUX
cana-5212	191	24	designed	design	VERB
cana-5212	191	25	and	and	CCONJ
cana-5212	191	26	trained	train	VERB
cana-5212	191	27	in	in	ADP
cana-5212	191	28	python	python	NOUN
cana-5212	191	29	,	,	PUNCT
cana-5212	191	30	more	more	ADV
cana-5212	191	31	particularly	particularly	ADV
cana-5212	191	32	through	through	ADP
cana-5212	191	33	the	the	DET
cana-5212	191	34	key	key	ADJ
cana-5212	191	35	libraries	library	NOUN
cana-5212	191	36	available	available	ADJ
cana-5212	191	37	in	in	ADP
cana-5212	191	38	the	the	DET
cana-5212	191	39	form	form	NOUN
cana-5212	191	40	of	of	ADP
cana-5212	191	41	tensorflow	tensorflow	NOUN
cana-5212	191	42	and	and	CCONJ
cana-5212	191	43	kera	kera	PROPN
cana-5212	191	44	’s	’s	PART
cana-5212	191	45	.	.	PUNCT
cana-5212	192	1	the	the	DET
cana-5212	192	2	first	first	ADJ
cana-5212	192	3	one	one	NUM
cana-5212	192	4	was	be	AUX
cana-5212	192	5	used	use	VERB
cana-5212	192	6	to	to	PART
cana-5212	192	7	build	build	VERB
cana-5212	192	8	robust	robust	ADJ
cana-5212	192	9	frameworks	framework	NOUN
cana-5212	192	10	for	for	ADP
cana-5212	192	11	machine	machine	NOUN
cana-5212	192	12	learning	learning	NOUN
cana-5212	192	13	models	model	NOUN
cana-5212	192	14	,	,	PUNCT
cana-5212	192	15	and	and	CCONJ
cana-5212	192	16	the	the	DET
cana-5212	192	17	latter	latter	ADJ
cana-5212	192	18	is	be	AUX
cana-5212	192	19	a	a	DET
cana-5212	192	20	user	user	NOUN
cana-5212	192	21	-	-	PUNCT
cana-5212	192	22	friendly	friendly	ADJ
cana-5212	192	23	api	api	NOUN
cana-5212	192	24	,	,	PUNCT
cana-5212	192	25	generally	generally	ADV
cana-5212	192	26	used	use	VERB
cana-5212	192	27	in	in	ADP
cana-5212	192	28	the	the	DET
cana-5212	192	29	design	design	NOUN
cana-5212	192	30	and	and	CCONJ
cana-5212	192	31	training	training	NOUN
cana-5212	192	32	of	of	ADP
cana-5212	192	33	neural	neural	ADJ
cana-5212	192	34	networks	network	NOUN
cana-5212	192	35	.	.	PUNCT
cana-5212	193	1	4.2.3	4.2.3	NUM
cana-5212	193	2	model	model	PROPN
cana-5212	193	3	development	development	PROPN
cana-5212	193	4	:	:	PUNCT
cana-5212	193	5	cnn	cnn	PROPN
cana-5212	193	6	architecture	architecture	NOUN
cana-5212	193	7	:	:	PUNCT
cana-5212	193	8	this	this	PRON
cana-5212	193	9	will	will	AUX
cana-5212	193	10	ensure	ensure	VERB
cana-5212	193	11	that	that	SCONJ
cana-5212	193	12	a	a	DET
cana-5212	193	13	number	number	NOUN
cana-5212	193	14	of	of	ADP
cana-5212	193	15	convolutional	convolutional	ADJ
cana-5212	193	16	layers	layer	NOUN
cana-5212	193	17	are	be	AUX
cana-5212	193	18	followed	follow	VERB
cana-5212	193	19	by	by	ADP
cana-5212	193	20	the	the	DET
cana-5212	193	21	pooling	pool	VERB
cana-5212	193	22	layers	layer	NOUN
cana-5212	193	23	,	,	PUNCT
cana-5212	193	24	then	then	ADV
cana-5212	193	25	fully	fully	ADV
cana-5212	193	26	connected	connected	ADJ
cana-5212	193	27	layers	layer	NOUN
cana-5212	193	28	,	,	PUNCT
cana-5212	193	29	and	and	CCONJ
cana-5212	193	30	finally	finally	ADV
cana-5212	193	31	the	the	DET
cana-5212	193	32	softmax	softmax	ADJ
cana-5212	193	33	output	output	NOUN
cana-5212	193	34	layer	layer	NOUN
cana-5212	193	35	.	.	PUNCT
cana-5212	194	1	such	such	DET
cana-5212	194	2	an	an	DET
cana-5212	194	3	architecture	architecture	NOUN
cana-5212	194	4	is	be	AUX
cana-5212	194	5	fine	fine	ADV
cana-5212	194	6	-	-	PUNCT
cana-5212	194	7	tuned	tune	VERB
cana-5212	194	8	to	to	PART
cana-5212	194	9	achieve	achieve	VERB
cana-5212	194	10	the	the	DET
cana-5212	194	11	best	good	ADJ
cana-5212	194	12	performance	performance	NOUN
cana-5212	194	13	through	through	ADP
cana-5212	194	14	experiments	experiment	NOUN
cana-5212	194	15	.	.	PUNCT
cana-5212	195	1	fuzzy	fuzzy	ADJ
cana-5212	195	2	logic	logic	NOUN
cana-5212	195	3	integration	integration	NOUN
cana-5212	195	4	:	:	PUNCT
cana-5212	195	5	this	this	PRON
cana-5212	195	6	will	will	AUX
cana-5212	195	7	take	take	VERB
cana-5212	195	8	the	the	DET
cana-5212	195	9	output	output	NOUN
cana-5212	195	10	of	of	ADP
cana-5212	195	11	the	the	DET
cana-5212	195	12	cnn	cnn	PROPN
cana-5212	195	13	and	and	CCONJ
cana-5212	195	14	feed	feed	VERB
cana-5212	195	15	it	it	PRON
cana-5212	195	16	into	into	ADP
cana-5212	195	17	a	a	DET
cana-5212	195	18	fuzzy	fuzzy	ADJ
cana-5212	195	19	inference	inference	NOUN
cana-5212	195	20	system	system	NOUN
cana-5212	195	21	to	to	PART
cana-5212	195	22	gauge	gauge	VERB
cana-5212	195	23	the	the	DET
cana-5212	195	24	severity	severity	NOUN
cana-5212	195	25	of	of	ADP
cana-5212	195	26	diseases	disease	NOUN
cana-5212	195	27	detected	detect	VERB
cana-5212	195	28	by	by	ADP
cana-5212	195	29	the	the	DET
cana-5212	195	30	system	system	NOUN
cana-5212	195	31	.	.	PUNCT
cana-5212	196	1	with	with	ADP
cana-5212	196	2	these	these	DET
cana-5212	196	3	results	result	NOUN
cana-5212	196	4	of	of	ADP
cana-5212	196	5	classification	classification	NOUN
cana-5212	196	6	with	with	ADP
cana-5212	196	7	predefined	predefine	VERB
cana-5212	196	8	fuzzy	fuzzy	ADJ
cana-5212	196	9	rules	rule	NOUN
cana-5212	196	10	,	,	PUNCT
cana-5212	196	11	the	the	DET
cana-5212	196	12	fis	fis	PROPN
cana-5212	196	13	will	will	AUX
cana-5212	196	14	decide	decide	VERB
cana-5212	196	15	on	on	ADP
cana-5212	196	16	the	the	DET
cana-5212	196	17	levels	level	NOUN
cana-5212	196	18	for	for	ADP
cana-5212	196	19	the	the	DET
cana-5212	196	20	degree	degree	NOUN
cana-5212	196	21	of	of	ADP
cana-5212	196	22	severity	severity	NOUN
cana-5212	196	23	.	.	PUNCT
cana-5212	197	1	4.2.4	4.2.4	NUM
cana-5212	197	2	comparative	comparative	ADJ
cana-5212	197	3	analysis	analysis	NOUN
cana-5212	197	4	:	:	PUNCT
cana-5212	197	5	the	the	DET
cana-5212	197	6	proposed	propose	VERB
cana-5212	197	7	cnns	cnn	NOUN
cana-5212	197	8	with	with	ADP
cana-5212	197	9	fuzzy	fuzzy	ADJ
cana-5212	197	10	logic	logic	NOUN
cana-5212	197	11	integration	integration	NOUN
cana-5212	197	12	are	be	AUX
cana-5212	197	13	compared	compare	VERB
cana-5212	197	14	in	in	ADP
cana-5212	197	15	performance	performance	NOUN
cana-5212	197	16	evaluation	evaluation	NOUN
cana-5212	197	17	against	against	ADP
cana-5212	197	18	existing	exist	VERB
cana-5212	197	19	techniques	technique	NOUN
cana-5212	197	20	:	:	PUNCT
cana-5212	197	21	performance	performance	NOUN
cana-5212	197	22	metrics	metric	NOUN
cana-5212	197	23	:	:	PUNCT
cana-5212	197	24	the	the	DET
cana-5212	197	25	model	model	NOUN
cana-5212	197	26	's	's	PART
cana-5212	197	27	standard	standard	ADJ
cana-5212	197	28	metrics	metric	NOUN
cana-5212	197	29	are	be	AUX
cana-5212	197	30	accuracy	accuracy	NOUN
cana-5212	197	31	,	,	PUNCT
cana-5212	197	32	precision	precision	NOUN
cana-5212	197	33	,	,	PUNCT
cana-5212	197	34	recall	recall	NOUN
cana-5212	197	35	,	,	PUNCT
cana-5212	197	36	and	and	CCONJ
cana-5212	197	37	f1	f1	NOUN
cana-5212	197	38	-	-	PUNCT
cana-5212	197	39	score	score	NOUN
cana-5212	197	40	.	.	PUNCT
cana-5212	198	1	this	this	PRON
cana-5212	198	2	,	,	PUNCT
cana-5212	198	3	in	in	ADP
cana-5212	198	4	fact	fact	NOUN
cana-5212	198	5	,	,	PUNCT
cana-5212	198	6	will	will	AUX
cana-5212	198	7	return	return	VERB
cana-5212	198	8	a	a	DET
cana-5212	198	9	comprehensive	comprehensive	ADJ
cana-5212	198	10	idea	idea	NOUN
cana-5212	198	11	about	about	ADP
cana-5212	198	12	the	the	DET
cana-5212	198	13	performance	performance	NOUN
cana-5212	198	14	of	of	ADP
cana-5212	198	15	this	this	DET
cana-5212	198	16	model	model	NOUN
cana-5212	198	17	,	,	PUNCT
cana-5212	198	18	especially	especially	ADV
cana-5212	198	19	on	on	ADP
cana-5212	198	20	the	the	DET
cana-5212	198	21	accuracy	accuracy	NOUN
cana-5212	198	22	and	and	CCONJ
cana-5212	198	23	reliability	reliability	NOUN
cana-5212	198	24	of	of	ADP
cana-5212	198	25	the	the	DET
cana-5212	198	26	classification	classification	NOUN
cana-5212	198	27	.	.	PUNCT
cana-5212	199	1	comparative	comparative	ADJ
cana-5212	199	2	analysis	analysis	NOUN
cana-5212	199	3	with	with	ADP
cana-5212	199	4	respective	respective	ADJ
cana-5212	199	5	existing	exist	VERB
cana-5212	199	6	techniques	technique	NOUN
cana-5212	199	7	:	:	PUNCT
cana-5212	199	8	the	the	DET
cana-5212	199	9	outcome	outcome	NOUN
cana-5212	199	10	will	will	AUX
cana-5212	199	11	be	be	AUX
cana-5212	199	12	compared	compare	VERB
cana-5212	199	13	to	to	ADP
cana-5212	199	14	traditional	traditional	ADJ
cana-5212	199	15	machine	machine	NOUN
cana-5212	199	16	learning	learn	VERB
cana-5212	199	17	methods	method	NOUN
cana-5212	199	18	like	like	ADP
cana-5212	199	19	svm	svm	PROPN
cana-5212	199	20	and	and	CCONJ
cana-5212	199	21	k	k	PROPN
cana-5212	199	22	-	-	PUNCT
cana-5212	199	23	nn	nn	NOUN
cana-5212	199	24	,	,	PUNCT
cana-5212	199	25	as	as	ADV
cana-5212	199	26	well	well	ADV
cana-5212	199	27	as	as	ADP
cana-5212	199	28	other	other	ADJ
cana-5212	199	29	deep	deep	ADJ
cana-5212	199	30	learning	learning	NOUN
cana-5212	199	31	models	model	NOUN
cana-5212	199	32	.	.	PUNCT
cana-5212	200	1	visual	visual	ADJ
cana-5212	200	2	charts	chart	NOUN
cana-5212	200	3	and	and	CCONJ
cana-5212	200	4	tables	table	NOUN
cana-5212	200	5	are	be	AUX
cana-5212	200	6	used	use	VERB
cana-5212	200	7	to	to	PART
cana-5212	200	8	present	present	VERB
cana-5212	200	9	the	the	DET
cana-5212	200	10	comparative	comparative	ADJ
cana-5212	200	11	analysis	analysis	NOUN
cana-5212	200	12	that	that	PRON
cana-5212	200	13	looks	look	VERB
cana-5212	200	14	into	into	ADP
cana-5212	200	15	improvements	improvement	NOUN
cana-5212	200	16	in	in	ADP
cana-5212	200	17	accuracy	accuracy	NOUN
cana-5212	200	18	and	and	CCONJ
cana-5212	200	19	robustness	robustness	NOUN
cana-5212	200	20	imparted	impart	VERB
cana-5212	200	21	by	by	ADP
cana-5212	200	22	the	the	DET
cana-5212	200	23	proposed	propose	VERB
cana-5212	200	24	methodology	methodology	NOUN
cana-5212	200	25	.	.	PUNCT
cana-5212	201	1	4.2.5	4.2.5	NUM
cana-5212	201	2	methodology	methodology	NOUN
cana-5212	201	3	steps	step	NOUN
cana-5212	201	4	:	:	PUNCT
cana-5212	201	5	data	datum	NOUN
cana-5212	201	6	collection	collection	NOUN
cana-5212	201	7	and	and	CCONJ
cana-5212	201	8	preprocessing	preprocessing	NOUN
cana-5212	201	9	:	:	PUNCT
cana-5212	201	10	raw	raw	ADJ
cana-5212	201	11	images	image	NOUN
cana-5212	201	12	will	will	AUX
cana-5212	201	13	be	be	AUX
cana-5212	201	14	collected	collect	VERB
cana-5212	201	15	from	from	ADP
cana-5212	201	16	kaggle	kaggle	PROPN
cana-5212	201	17	and	and	CCONJ
cana-5212	201	18	the	the	DET
cana-5212	201	19	uci	uci	PROPN
cana-5212	201	20	machine	machine	NOUN
cana-5212	201	21	learning	learn	VERB
cana-5212	201	22	repository	repository	NOUN
cana-5212	201	23	.	.	PUNCT
cana-5212	202	1	resize	resize	VERB
cana-5212	202	2	images	image	NOUN
cana-5212	202	3	to	to	ADP
cana-5212	202	4	standard	standard	ADJ
cana-5212	202	5	dimensions	dimension	NOUN
cana-5212	202	6	.	.	PUNCT
cana-5212	203	1	in	in	ADP
cana-5212	203	2	this	this	DET
cana-5212	203	3	case	case	NOUN
cana-5212	203	4	,	,	PUNCT
cana-5212	203	5	normalize	normalize	VERB
cana-5212	203	6	the	the	DET
cana-5212	203	7	pixel	pixel	PROPN
cana-5212	203	8	values	value	NOUN
cana-5212	203	9	between	between	ADP
cana-5212	203	10	0	0	NUM
cana-5212	203	11	and	and	CCONJ
cana-5212	203	12	1	1	NUM
cana-5212	203	13	.	.	X
cana-5212	204	1	4.2.6	4.2.6	PRON
cana-5212	204	2	dataset	dataset	ADJ
cana-5212	204	3	splitting	splitting	NOUN
cana-5212	204	4	:	:	PUNCT
cana-5212	204	5	split	split	VERB
cana-5212	204	6	the	the	DET
cana-5212	204	7	dataset	dataset	NOUN
cana-5212	204	8	into	into	ADP
cana-5212	204	9	a	a	DET
cana-5212	204	10	training	training	NOUN
cana-5212	204	11	set	set	NOUN
cana-5212	204	12	and	and	CCONJ
cana-5212	204	13	a	a	DET
cana-5212	204	14	validation	validation	NOUN
cana-5212	204	15	set	set	VERB
cana-5212	204	16	in	in	ADP
cana-5212	204	17	an	an	DET
cana-5212	204	18	80:20	80:20	NUM
cana-5212	204	19	ratio	ratio	NOUN
cana-5212	204	20	.	.	PUNCT
cana-5212	205	1	model	model	PROPN
cana-5212	205	2	development	development	PROPN
cana-5212	205	3	the	the	DET
cana-5212	205	4	cnn	cnn	PROPN
cana-5212	205	5	is	be	AUX
cana-5212	205	6	to	to	PART
cana-5212	205	7	be	be	AUX
cana-5212	205	8	designed	design	VERB
cana-5212	205	9	with	with	ADP
cana-5212	205	10	specific	specific	ADJ
cana-5212	205	11	architecture	architecture	NOUN
cana-5212	205	12	involving	involve	VERB
cana-5212	205	13	the	the	DET
cana-5212	205	14	design	design	NOUN
cana-5212	205	15	of	of	ADP
cana-5212	205	16	convolution	convolution	NOUN
cana-5212	205	17	,	,	PUNCT
cana-5212	205	18	pooling	pooling	NOUN
cana-5212	205	19	,	,	PUNCT
cana-5212	205	20	and	and	CCONJ
cana-5212	205	21	fully	fully	ADV
cana-5212	205	22	connected	connected	ADJ
cana-5212	205	23	layers	layer	NOUN
cana-5212	205	24	.	.	PUNCT
cana-5212	206	1	develop	develop	VERB
cana-5212	206	2	a	a	DET
cana-5212	206	3	fuzzy	fuzzy	ADJ
cana-5212	206	4	inference	inference	NOUN
cana-5212	206	5	system	system	NOUN
cana-5212	206	6	for	for	ADP
cana-5212	206	7	the	the	DET
cana-5212	206	8	analysis	analysis	NOUN
cana-5212	206	9	of	of	ADP
cana-5212	206	10	severity	severity	NOUN
cana-5212	206	11	.	.	PUNCT
cana-5212	207	1	train	train	VERB
cana-5212	207	2	the	the	DET
cana-5212	207	3	cnn	cnn	NOUN
cana-5212	207	4	using	use	VERB
cana-5212	207	5	a	a	DET
cana-5212	207	6	training	training	NOUN
cana-5212	207	7	set	set	NOUN
cana-5212	207	8	.	.	PUNCT
cana-5212	208	1	evaluation	evaluation	NOUN
cana-5212	208	2	communications	communication	NOUN
cana-5212	208	3	on	on	ADP
cana-5212	208	4	applied	apply	VERB
cana-5212	208	5	nonlinear	nonlinear	ADJ
cana-5212	208	6	analysis	analysis	NOUN
cana-5212	208	7	issn	issn	NOUN
cana-5212	208	8	:	:	PUNCT
cana-5212	208	9	1074	1074	NUM
cana-5212	208	10	-	-	PUNCT
cana-5212	208	11	133x	133x	NUM
cana-5212	208	12	vol	vol	NOUN
cana-5212	208	13	32	32	NUM
cana-5212	208	14	no	no	NOUN
cana-5212	208	15	.	.	PUNCT
cana-5212	209	1	8s	8s	PROPN
cana-5212	209	2	(	(	PUNCT
cana-5212	209	3	2025	2025	NUM
cana-5212	209	4	)	)	PUNCT
cana-5212	209	5	946	946	NUM
cana-5212	209	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	209	7	5	5	X
cana-5212	209	8	.	.	PUNCT
cana-5212	209	9	results	result	VERB
cana-5212	209	10	5.1	5.1	NUM
cana-5212	209	11	comparative	comparative	ADJ
cana-5212	209	12	analysis	analysis	NOUN
cana-5212	209	13	the	the	DET
cana-5212	209	14	proposed	propose	VERB
cana-5212	209	15	method	method	NOUN
cana-5212	209	16	,	,	PUNCT
cana-5212	209	17	which	which	PRON
cana-5212	209	18	combined	combine	VERB
cana-5212	209	19	convolutional	convolutional	ADJ
cana-5212	209	20	neural	neural	ADJ
cana-5212	209	21	networks	network	NOUN
cana-5212	209	22	with	with	ADP
cana-5212	209	23	fuzzy	fuzzy	ADJ
cana-5212	209	24	logic	logic	NOUN
cana-5212	209	25	,	,	PUNCT
cana-5212	209	26	was	be	AUX
cana-5212	209	27	tested	test	VERB
cana-5212	209	28	vigorously	vigorously	ADV
cana-5212	209	29	against	against	ADP
cana-5212	209	30	the	the	DET
cana-5212	209	31	existing	exist	VERB
cana-5212	209	32	techniques	technique	NOUN
cana-5212	209	33	for	for	ADP
cana-5212	209	34	its	its	PRON
cana-5212	209	35	effectiveness	effectiveness	NOUN
cana-5212	209	36	.	.	PUNCT
cana-5212	210	1	the	the	DET
cana-5212	210	2	following	follow	VERB
cana-5212	210	3	performance	performance	NOUN
cana-5212	210	4	metrics	metric	NOUN
cana-5212	210	5	have	have	AUX
cana-5212	210	6	been	be	AUX
cana-5212	210	7	used	use	VERB
cana-5212	210	8	:	:	PUNCT
cana-5212	210	9	accuracy	accuracy	NOUN
cana-5212	210	10	,	,	PUNCT
cana-5212	210	11	precision	precision	NOUN
cana-5212	210	12	,	,	PUNCT
cana-5212	210	13	recall	recall	NOUN
cana-5212	210	14	,	,	PUNCT
cana-5212	210	15	and	and	CCONJ
cana-5212	210	16	f1	f1	NOUN
cana-5212	210	17	-	-	PUNCT
cana-5212	210	18	score	score	NOUN
cana-5212	210	19	,	,	PUNCT
cana-5212	210	20	all	all	PRON
cana-5212	210	21	of	of	ADP
cana-5212	210	22	which	which	PRON
cana-5212	210	23	give	give	VERB
cana-5212	210	24	an	an	DET
cana-5212	210	25	all	all	ADV
cana-5212	210	26	-	-	PUNCT
cana-5212	210	27	rounded	rounded	ADJ
cana-5212	210	28	view	view	NOUN
cana-5212	210	29	of	of	ADP
cana-5212	210	30	how	how	SCONJ
cana-5212	210	31	exemplary	exemplary	ADJ
cana-5212	210	32	the	the	DET
cana-5212	210	33	model	model	NOUN
cana-5212	210	34	is	be	AUX
cana-5212	210	35	.	.	PUNCT
cana-5212	211	1	accuracy	accuracy	NOUN
cana-5212	211	2	:	:	PUNCT
cana-5212	211	3	accuracy	accuracy	NOUN
cana-5212	211	4	expresses	express	VERB
cana-5212	211	5	the	the	DET
cana-5212	211	6	proportion	proportion	NOUN
cana-5212	211	7	of	of	ADP
cana-5212	211	8	correct	correct	ADJ
cana-5212	211	9	resultsthat	resultsthat	NOUN
cana-5212	211	10	is	be	AUX
cana-5212	211	11	,	,	PUNCT
cana-5212	211	12	the	the	DET
cana-5212	211	13	sum	sum	NOUN
cana-5212	211	14	of	of	ADP
cana-5212	211	15	true	true	ADJ
cana-5212	211	16	positives	positive	NOUN
cana-5212	211	17	and	and	CCONJ
cana-5212	211	18	true	true	ADJ
cana-5212	211	19	negativesagainst	negativesagainst	ADP
cana-5212	211	20	the	the	DET
cana-5212	211	21	total	total	ADJ
cana-5212	211	22	number	number	NOUN
cana-5212	211	23	of	of	ADP
cana-5212	211	24	cases	case	NOUN
cana-5212	211	25	tested	test	VERB
cana-5212	211	26	.	.	PUNCT
cana-5212	212	1	in	in	ADP
cana-5212	212	2	this	this	DET
cana-5212	212	3	work	work	NOUN
cana-5212	212	4	,	,	PUNCT
cana-5212	212	5	the	the	DET
cana-5212	212	6	proposed	propose	VERB
cana-5212	212	7	technique	technique	NOUN
cana-5212	212	8	achieved	achieve	VERB
cana-5212	212	9	an	an	DET
cana-5212	212	10	accuracy	accuracy	NOUN
cana-5212	212	11	of	of	ADP
cana-5212	212	12	95	95	NUM
cana-5212	212	13	%	%	NOUN
cana-5212	212	14	,	,	PUNCT
cana-5212	212	15	far	far	ADV
cana-5212	212	16	higher	high	ADJ
cana-5212	212	17	compared	compare	VERB
cana-5212	212	18	to	to	ADP
cana-5212	212	19	some	some	DET
cana-5212	212	20	traditional	traditional	ADJ
cana-5212	212	21	methods	method	NOUN
cana-5212	212	22	,	,	PUNCT
cana-5212	212	23	like	like	ADP
cana-5212	212	24	support	support	NOUN
cana-5212	212	25	vector	vector	NOUN
cana-5212	212	26	machines	machine	NOUN
cana-5212	212	27	and	and	CCONJ
cana-5212	212	28	k	k	NOUN
cana-5212	212	29	-	-	PUNCT
cana-5212	212	30	nearest	near	ADJ
cana-5212	212	31	neighbours	neighbour	NOUN
cana-5212	212	32	,	,	PUNCT
cana-5212	212	33	that	that	PRON
cana-5212	212	34	came	come	VERB
cana-5212	212	35	in	in	ADP
cana-5212	212	36	at	at	ADP
cana-5212	212	37	85	85	NUM
cana-5212	212	38	%	%	NOUN
cana-5212	212	39	and	and	CCONJ
cana-5212	212	40	82	82	NUM
cana-5212	212	41	%	%	NOUN
cana-5212	212	42	,	,	PUNCT
cana-5212	212	43	respectively	respectively	ADV
cana-5212	212	44	.	.	PUNCT
cana-5212	213	1	precision	precision	NOUN
cana-5212	213	2	:	:	PUNCT
cana-5212	213	3	it	it	PRON
cana-5212	213	4	's	be	AUX
cana-5212	213	5	the	the	DET
cana-5212	213	6	ratio	ratio	NOUN
cana-5212	213	7	of	of	ADP
cana-5212	213	8	correctly	correctly	ADV
cana-5212	213	9	predicted	predict	VERB
cana-5212	213	10	positive	positive	ADJ
cana-5212	213	11	observations	observation	NOUN
cana-5212	213	12	against	against	ADP
cana-5212	213	13	the	the	DET
cana-5212	213	14	total	total	NOUN
cana-5212	213	15	predicted	predict	VERB
cana-5212	213	16	positive	positive	ADJ
cana-5212	213	17	observations	observation	NOUN
cana-5212	213	18	.	.	PUNCT
cana-5212	214	1	it	it	PRON
cana-5212	214	2	depicts	depict	VERB
cana-5212	214	3	the	the	DET
cana-5212	214	4	exactness	exactness	NOUN
cana-5212	214	5	of	of	ADP
cana-5212	214	6	the	the	DET
cana-5212	214	7	model	model	NOUN
cana-5212	214	8	.	.	PUNCT
cana-5212	215	1	the	the	DET
cana-5212	215	2	cnn	cnn	PROPN
cana-5212	215	3	integrated	integrate	VERB
cana-5212	215	4	with	with	ADP
cana-5212	215	5	fuzzy	fuzzy	ADJ
cana-5212	215	6	logic	logic	NOUN
cana-5212	215	7	got	get	VERB
cana-5212	215	8	a	a	DET
cana-5212	215	9	precision	precision	NOUN
cana-5212	215	10	of	of	ADP
cana-5212	215	11	94	94	NUM
cana-5212	215	12	%	%	NOUN
cana-5212	215	13	,	,	PUNCT
cana-5212	215	14	while	while	SCONJ
cana-5212	215	15	that	that	PRON
cana-5212	215	16	for	for	ADP
cana-5212	215	17	svm	svm	NOUN
cana-5212	215	18	was	be	AUX
cana-5212	215	19	84	84	NUM
cana-5212	215	20	%	%	NOUN
cana-5212	215	21	and	and	CCONJ
cana-5212	215	22	81	81	NUM
cana-5212	215	23	%	%	NOUN
cana-5212	215	24	for	for	ADP
cana-5212	215	25	k	k	PROPN
cana-5212	215	26	-	-	PUNCT
cana-5212	215	27	nn	nn	PROPN
cana-5212	215	28	.	.	PROPN
cana-5212	215	29	recall	recall	PROPN
cana-5212	215	30	:	:	PUNCT
cana-5212	215	31	recall	recall	NOUN
cana-5212	215	32	,	,	PUNCT
cana-5212	215	33	or	or	CCONJ
cana-5212	215	34	sensitivity	sensitivity	NOUN
cana-5212	215	35	,	,	PUNCT
cana-5212	215	36	is	be	AUX
cana-5212	215	37	the	the	DET
cana-5212	215	38	ratio	ratio	NOUN
cana-5212	215	39	of	of	ADP
cana-5212	215	40	correctly	correctly	ADV
cana-5212	215	41	predicted	predict	VERB
cana-5212	215	42	positive	positive	ADJ
cana-5212	215	43	observations	observation	NOUN
cana-5212	215	44	to	to	ADP
cana-5212	215	45	all	all	DET
cana-5212	215	46	observations	observation	NOUN
cana-5212	215	47	in	in	ADP
cana-5212	215	48	the	the	DET
cana-5212	215	49	actual	actual	ADJ
cana-5212	215	50	class	class	NOUN
cana-5212	215	51	.	.	PUNCT
cana-5212	216	1	recall	recall	PROPN
cana-5212	216	2	is	be	AUX
cana-5212	216	3	a	a	DET
cana-5212	216	4	measure	measure	NOUN
cana-5212	216	5	of	of	ADP
cana-5212	216	6	how	how	SCONJ
cana-5212	216	7	good	good	ADJ
cana-5212	216	8	the	the	DET
cana-5212	216	9	model	model	NOUN
cana-5212	216	10	is	be	AUX
cana-5212	216	11	at	at	ADP
cana-5212	216	12	detecting	detect	VERB
cana-5212	216	13	relevant	relevant	ADJ
cana-5212	216	14	instances	instance	NOUN
cana-5212	216	15	.	.	PUNCT
cana-5212	217	1	the	the	DET
cana-5212	217	2	recall	recall	NOUN
cana-5212	217	3	for	for	ADP
cana-5212	217	4	the	the	DET
cana-5212	217	5	proposed	propose	VERB
cana-5212	217	6	method	method	NOUN
cana-5212	217	7	was	be	AUX
cana-5212	217	8	93	93	NUM
cana-5212	217	9	%	%	NOUN
cana-5212	217	10	,	,	PUNCT
cana-5212	217	11	thus	thus	ADV
cana-5212	217	12	outperforming	outperform	VERB
cana-5212	217	13	both	both	CCONJ
cana-5212	217	14	svm	svm	VERB
cana-5212	217	15	with	with	ADP
cana-5212	217	16	83	83	NUM
cana-5212	217	17	%	%	NOUN
cana-5212	217	18	and	and	CCONJ
cana-5212	217	19	k	k	NOUN
cana-5212	217	20	-	-	PUNCT
cana-5212	217	21	nn	nn	PROPN
cana-5212	217	22	with	with	ADP
cana-5212	217	23	80	80	NUM
cana-5212	217	24	%	%	NOUN
cana-5212	217	25	.	.	PUNCT
cana-5212	218	1	f1	f1	NOUN
cana-5212	218	2	-	-	PUNCT
cana-5212	218	3	score	score	NOUN
cana-5212	218	4	:	:	PUNCT
cana-5212	218	5	the	the	DET
cana-5212	218	6	f1	f1	NOUN
cana-5212	218	7	score	score	NOUN
cana-5212	218	8	is	be	AUX
cana-5212	218	9	the	the	DET
cana-5212	218	10	harmonic	harmonic	ADJ
cana-5212	218	11	mean	mean	NOUN
cana-5212	218	12	of	of	ADP
cana-5212	218	13	precision	precision	NOUN
cana-5212	218	14	and	and	CCONJ
cana-5212	218	15	recall	recall	NOUN
cana-5212	218	16	,	,	PUNCT
cana-5212	218	17	and	and	CCONJ
cana-5212	218	18	hence	hence	ADV
cana-5212	218	19	it	it	PRON
cana-5212	218	20	provides	provide	VERB
cana-5212	218	21	a	a	DET
cana-5212	218	22	balance	balance	NOUN
cana-5212	218	23	between	between	ADP
cana-5212	218	24	the	the	DET
cana-5212	218	25	two	two	NUM
cana-5212	218	26	metrics	metric	NOUN
cana-5212	218	27	.	.	PUNCT
cana-5212	219	1	this	this	PRON
cana-5212	219	2	returned	return	VERB
cana-5212	219	3	an	an	DET
cana-5212	219	4	f1	f1	NOUN
cana-5212	219	5	-	-	PUNCT
cana-5212	219	6	score	score	NOUN
cana-5212	219	7	of	of	ADP
cana-5212	219	8	93.5	93.5	NUM
cana-5212	219	9	%	%	NOUN
cana-5212	219	10	,	,	PUNCT
cana-5212	219	11	outperforming	outperform	VERB
cana-5212	219	12	an	an	DET
cana-5212	219	13	f1	f1	NOUN
cana-5212	219	14	-	-	PUNCT
cana-5212	219	15	score	score	NOUN
cana-5212	219	16	of	of	ADP
cana-5212	219	17	83.5	83.5	NUM
cana-5212	219	18	%	%	NOUN
cana-5212	219	19	for	for	ADP
cana-5212	219	20	svm	svm	NOUN
cana-5212	219	21	and	and	CCONJ
cana-5212	219	22	80.5	80.5	NUM
cana-5212	219	23	%	%	NOUN
cana-5212	219	24	for	for	ADP
cana-5212	219	25	k	k	PROPN
cana-5212	219	26	-	-	PUNCT
cana-5212	219	27	nn	nn	PROPN
cana-5212	219	28	.	.	PROPN
cana-5212	219	29	figure	figure	NOUN
cana-5212	219	30	4	4	NUM
cana-5212	219	31	:	:	PUNCT
cana-5212	219	32	comparative	comparative	ADJ
cana-5212	219	33	analysis	analysis	NOUN
cana-5212	219	34	of	of	ADP
cana-5212	219	35	accuracy	accuracy	NOUN
cana-5212	219	36	,	,	PUNCT
cana-5212	219	37	precision	precision	NOUN
cana-5212	219	38	,	,	PUNCT
cana-5212	219	39	recall	recall	NOUN
cana-5212	219	40	,	,	PUNCT
cana-5212	219	41	and	and	CCONJ
cana-5212	219	42	f1	f1	NOUN
cana-5212	219	43	-	-	PUNCT
cana-5212	219	44	score	score	NOUN
cana-5212	219	45	this	this	DET
cana-5212	219	46	figure	figure	NOUN
cana-5212	219	47	(	(	PUNCT
cana-5212	219	48	4	4	NUM
cana-5212	219	49	)	)	PUNCT
cana-5212	219	50	bar	bar	NOUN
cana-5212	219	51	chart	chart	NOUN
cana-5212	219	52	compares	compare	VERB
cana-5212	219	53	the	the	DET
cana-5212	219	54	performance	performance	NOUN
cana-5212	219	55	metrics	metric	NOUN
cana-5212	219	56	(	(	PUNCT
cana-5212	219	57	accuracy	accuracy	NOUN
cana-5212	219	58	,	,	PUNCT
cana-5212	219	59	precision	precision	NOUN
cana-5212	219	60	,	,	PUNCT
cana-5212	219	61	recall	recall	NOUN
cana-5212	219	62	,	,	PUNCT
cana-5212	219	63	and	and	CCONJ
cana-5212	219	64	f1score	f1score	NOUN
cana-5212	219	65	)	)	PUNCT
cana-5212	219	66	of	of	ADP
cana-5212	219	67	the	the	DET
cana-5212	219	68	proposed	propose	VERB
cana-5212	219	69	cnn	cnn	PROPN
cana-5212	219	70	with	with	ADP
cana-5212	219	71	fuzzy	fuzzy	ADJ
cana-5212	219	72	logic	logic	NOUN
cana-5212	219	73	model	model	NOUN
cana-5212	219	74	against	against	ADP
cana-5212	219	75	svm	svm	PROPN
cana-5212	219	76	and	and	CCONJ
cana-5212	219	77	k	k	PROPN
cana-5212	219	78	-	-	PUNCT
cana-5212	219	79	nn	nn	ADJ
cana-5212	219	80	models	model	NOUN
cana-5212	219	81	.	.	PUNCT
cana-5212	220	1	communications	communication	NOUN
cana-5212	220	2	on	on	ADP
cana-5212	220	3	applied	apply	VERB
cana-5212	220	4	nonlinear	nonlinear	ADJ
cana-5212	220	5	analysis	analysis	NOUN
cana-5212	220	6	issn	issn	NOUN
cana-5212	220	7	:	:	PUNCT
cana-5212	220	8	1074	1074	NUM
cana-5212	220	9	-	-	PUNCT
cana-5212	220	10	133x	133x	NUM
cana-5212	220	11	vol	vol	NOUN
cana-5212	220	12	32	32	NUM
cana-5212	220	13	no	no	NOUN
cana-5212	220	14	.	.	PUNCT
cana-5212	221	1	8s	8s	PROPN
cana-5212	221	2	(	(	PUNCT
cana-5212	221	3	2025	2025	NUM
cana-5212	221	4	)	)	PUNCT
cana-5212	221	5	947	947	NUM
cana-5212	221	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	221	7	model	model	NOUN
cana-5212	221	8	accuracy	accuracy	NOUN
cana-5212	221	9	(	(	PUNCT
cana-5212	221	10	%	%	INTJ
cana-5212	221	11	)	)	PUNCT
cana-5212	221	12	precision	precision	NOUN
cana-5212	221	13	(	(	PUNCT
cana-5212	221	14	%	%	INTJ
cana-5212	221	15	)	)	PUNCT
cana-5212	221	16	recall	recall	NOUN
cana-5212	221	17	(	(	PUNCT
cana-5212	221	18	%	%	NOUN
cana-5212	221	19	)	)	PUNCT
cana-5212	221	20	f1	f1	NOUN
cana-5212	221	21	-	-	PUNCT
cana-5212	221	22	score	score	NOUN
cana-5212	221	23	(	(	PUNCT
cana-5212	221	24	%	%	INTJ
cana-5212	221	25	)	)	PUNCT
cana-5212	221	26	proposed	propose	VERB
cana-5212	221	27	cnn	cnn	PROPN
cana-5212	222	1	+	+	CCONJ
cana-5212	222	2	fuzzy	fuzzy	ADJ
cana-5212	222	3	logic	logic	NOUN
cana-5212	222	4	95	95	NUM
cana-5212	222	5	94	94	NUM
cana-5212	222	6	93	93	NUM
cana-5212	222	7	93.5	93.5	NUM
cana-5212	222	8	svm	svm	NOUN
cana-5212	222	9	85	85	NUM
cana-5212	222	10	84	84	NUM
cana-5212	222	11	83	83	NUM
cana-5212	222	12	83.5	83.5	NUM
cana-5212	222	13	k	k	PROPN
cana-5212	222	14	-	-	PROPN
cana-5212	222	15	nn	nn	PROPN
cana-5212	222	16	82	82	NUM
cana-5212	222	17	81	81	NUM
cana-5212	222	18	80	80	NUM
cana-5212	222	19	80.5	80.5	NUM
cana-5212	222	20	table	table	NOUN
cana-5212	222	21	2	2	NUM
cana-5212	222	22	:	:	PUNCT
cana-5212	222	23	comparative	comparative	ADJ
cana-5212	222	24	performance	performance	NOUN
cana-5212	222	25	metrics	metric	NOUN
cana-5212	222	26	of	of	ADP
cana-5212	222	27	different	different	ADJ
cana-5212	222	28	models	model	NOUN
cana-5212	222	29	this	this	DET
cana-5212	222	30	table	table	NOUN
cana-5212	222	31	(	(	PUNCT
cana-5212	222	32	2	2	NUM
cana-5212	222	33	)	)	PUNCT
cana-5212	222	34	presents	present	VERB
cana-5212	222	35	the	the	DET
cana-5212	222	36	comparative	comparative	ADJ
cana-5212	222	37	performance	performance	NOUN
cana-5212	222	38	metrics	metric	NOUN
cana-5212	222	39	(	(	PUNCT
cana-5212	222	40	accuracy	accuracy	NOUN
cana-5212	222	41	,	,	PUNCT
cana-5212	222	42	precision	precision	NOUN
cana-5212	222	43	,	,	PUNCT
cana-5212	222	44	recall	recall	NOUN
cana-5212	222	45	,	,	PUNCT
cana-5212	222	46	and	and	CCONJ
cana-5212	222	47	f1score	f1score	NOUN
cana-5212	222	48	)	)	PUNCT
cana-5212	222	49	of	of	ADP
cana-5212	222	50	the	the	DET
cana-5212	222	51	proposed	propose	VERB
cana-5212	222	52	cnn	cnn	PROPN
cana-5212	222	53	with	with	ADP
cana-5212	222	54	fuzzy	fuzzy	ADJ
cana-5212	222	55	logic	logic	NOUN
cana-5212	222	56	model	model	NOUN
cana-5212	222	57	against	against	ADP
cana-5212	222	58	svm	svm	PROPN
cana-5212	222	59	and	and	CCONJ
cana-5212	222	60	k	k	PROPN
cana-5212	222	61	-	-	PUNCT
cana-5212	222	62	nn	nn	ADJ
cana-5212	222	63	models	model	NOUN
cana-5212	222	64	.	.	PUNCT
cana-5212	223	1	5.2	5.2	NUM
cana-5212	223	2	discussion	discussion	NOUN
cana-5212	223	3	results	result	NOUN
cana-5212	223	4	underline	underline	VERB
cana-5212	223	5	some	some	PRON
cana-5212	223	6	of	of	ADP
cana-5212	223	7	the	the	DET
cana-5212	223	8	prime	prime	ADJ
cana-5212	223	9	advantages	advantage	NOUN
cana-5212	223	10	of	of	ADP
cana-5212	223	11	integrating	integrate	VERB
cana-5212	223	12	fuzzy	fuzzy	ADJ
cana-5212	223	13	logic	logic	NOUN
cana-5212	223	14	with	with	ADP
cana-5212	223	15	cnn	cnn	PROPN
cana-5212	223	16	in	in	ADP
cana-5212	223	17	plant	plant	NOUN
cana-5212	223	18	disease	disease	NOUN
cana-5212	223	19	detection	detection	NOUN
cana-5212	223	20	and	and	CCONJ
cana-5212	223	21	severity	severity	NOUN
cana-5212	223	22	analysis	analysis	NOUN
cana-5212	223	23	.	.	PUNCT
cana-5212	224	1	higher	high	ADJ
cana-5212	224	2	accuracy	accuracy	NOUN
cana-5212	224	3	:	:	PUNCT
cana-5212	224	4	the	the	DET
cana-5212	224	5	proposed	propose	VERB
cana-5212	224	6	method	method	NOUN
cana-5212	224	7	gives	give	VERB
cana-5212	224	8	much	much	ADV
cana-5212	224	9	better	well	ADJ
cana-5212	224	10	accuracy	accuracy	NOUN
cana-5212	224	11	in	in	ADP
cana-5212	224	12	the	the	DET
cana-5212	224	13	detection	detection	NOUN
cana-5212	224	14	of	of	ADP
cana-5212	224	15	plant	plant	NOUN
cana-5212	224	16	diseases	disease	NOUN
cana-5212	224	17	than	than	ADP
cana-5212	224	18	that	that	PRON
cana-5212	224	19	offered	offer	VERB
cana-5212	224	20	by	by	ADP
cana-5212	224	21	traditional	traditional	ADJ
cana-5212	224	22	methods	method	NOUN
cana-5212	224	23	.	.	PUNCT
cana-5212	225	1	while	while	SCONJ
cana-5212	225	2	the	the	DET
cana-5212	225	3	cnn	cnn	PROPN
cana-5212	225	4	component	component	NOUN
cana-5212	225	5	itself	itself	PRON
cana-5212	225	6	is	be	AUX
cana-5212	225	7	very	very	ADV
cana-5212	225	8	good	good	ADJ
cana-5212	225	9	at	at	ADP
cana-5212	225	10	feature	feature	NOUN
cana-5212	225	11	extraction	extraction	NOUN
cana-5212	225	12	and	and	CCONJ
cana-5212	225	13	classification	classification	NOUN
cana-5212	225	14	,	,	PUNCT
cana-5212	225	15	it	it	PRON
cana-5212	225	16	is	be	AUX
cana-5212	225	17	the	the	DET
cana-5212	225	18	fuzzy	fuzzy	ADJ
cana-5212	225	19	logic	logic	NOUN
cana-5212	225	20	component	component	NOUN
cana-5212	225	21	that	that	PRON
cana-5212	225	22	adds	add	VERB
cana-5212	225	23	a	a	DET
cana-5212	225	24	fine	fine	ADV
cana-5212	225	25	-	-	PUNCT
cana-5212	225	26	grained	grain	VERB
cana-5212	225	27	severity	severity	NOUN
cana-5212	225	28	analysis	analysis	NOUN
cana-5212	225	29	that	that	PRON
cana-5212	225	30	can	can	AUX
cana-5212	225	31	further	far	ADV
cana-5212	225	32	improve	improve	VERB
cana-5212	225	33	overall	overall	ADJ
cana-5212	225	34	accuracy	accuracy	NOUN
cana-5212	225	35	.	.	PUNCT
cana-5212	226	1	thorough	thorough	ADJ
cana-5212	226	2	severity	severity	NOUN
cana-5212	226	3	analysis	analysis	NOUN
cana-5212	226	4	:	:	PUNCT
cana-5212	226	5	one	one	NUM
cana-5212	226	6	of	of	ADP
cana-5212	226	7	the	the	DET
cana-5212	226	8	foremost	foremost	ADJ
cana-5212	226	9	strengths	strength	NOUN
cana-5212	226	10	of	of	ADP
cana-5212	226	11	the	the	DET
cana-5212	226	12	integrated	integrate	VERB
cana-5212	226	13	approach	approach	NOUN
cana-5212	226	14	is	be	AUX
cana-5212	226	15	that	that	SCONJ
cana-5212	226	16	it	it	PRON
cana-5212	226	17	provides	provide	VERB
cana-5212	226	18	the	the	DET
cana-5212	226	19	details	detail	NOUN
cana-5212	226	20	regarding	regard	VERB
cana-5212	226	21	the	the	DET
cana-5212	226	22	severity	severity	NOUN
cana-5212	226	23	of	of	ADP
cana-5212	226	24	the	the	DET
cana-5212	226	25	disease	disease	NOUN
cana-5212	226	26	.	.	PUNCT
cana-5212	227	1	this	this	PRON
cana-5212	227	2	,	,	PUNCT
cana-5212	227	3	most	most	ADJ
cana-5212	227	4	of	of	ADP
cana-5212	227	5	the	the	DET
cana-5212	227	6	traditional	traditional	ADJ
cana-5212	227	7	techniques	technique	NOUN
cana-5212	227	8	do	do	AUX
cana-5212	227	9	not	not	PART
cana-5212	227	10	talk	talk	VERB
cana-5212	227	11	about	about	ADP
cana-5212	227	12	;	;	PUNCT
cana-5212	227	13	they	they	PRON
cana-5212	227	14	are	be	AUX
cana-5212	227	15	simply	simply	ADV
cana-5212	227	16	confined	confine	VERB
cana-5212	227	17	to	to	ADP
cana-5212	227	18	the	the	DET
cana-5212	227	19	techniques	technique	NOUN
cana-5212	227	20	for	for	ADP
cana-5212	227	21	disease	disease	NOUN
cana-5212	227	22	detection	detection	NOUN
cana-5212	227	23	and	and	CCONJ
cana-5212	227	24	do	do	AUX
cana-5212	227	25	not	not	PART
cana-5212	227	26	comment	comment	VERB
cana-5212	227	27	on	on	ADP
cana-5212	227	28	its	its	PRON
cana-5212	227	29	severity	severity	NOUN
cana-5212	227	30	aspect	aspect	NOUN
cana-5212	227	31	.	.	PUNCT
cana-5212	228	1	integrating	integrate	VERB
cana-5212	228	2	fuzzy	fuzzy	ADJ
cana-5212	228	3	logic	logic	NOUN
cana-5212	228	4	,	,	PUNCT
cana-5212	228	5	this	this	DET
cana-5212	228	6	proposed	propose	VERB
cana-5212	228	7	method	method	NOUN
cana-5212	228	8	gives	give	VERB
cana-5212	228	9	a	a	DET
cana-5212	228	10	complete	complete	ADJ
cana-5212	228	11	solution	solution	NOUN
cana-5212	228	12	and	and	CCONJ
cana-5212	228	13	allows	allow	VERB
cana-5212	228	14	for	for	ADP
cana-5212	228	15	suitable	suitable	ADJ
cana-5212	228	16	decision	decision	NOUN
cana-5212	228	17	-	-	PUNCT
cana-5212	228	18	making	making	NOUN
cana-5212	228	19	about	about	ADP
cana-5212	228	20	treatment	treatment	NOUN
cana-5212	228	21	and	and	CCONJ
cana-5212	228	22	management	management	NOUN
cana-5212	228	23	.	.	PUNCT
cana-5212	229	1	robustness	robustness	NOUN
cana-5212	229	2	and	and	CCONJ
cana-5212	229	3	generalization	generalization	NOUN
cana-5212	229	4	:	:	PUNCT
cana-5212	229	5	the	the	DET
cana-5212	229	6	integrated	integrate	VERB
cana-5212	229	7	model	model	NOUN
cana-5212	229	8	has	have	AUX
cana-5212	229	9	been	be	AUX
cana-5212	229	10	proven	prove	VERB
cana-5212	229	11	to	to	PART
cana-5212	229	12	be	be	AUX
cana-5212	229	13	quite	quite	ADV
cana-5212	229	14	robust	robust	ADJ
cana-5212	229	15	with	with	ADP
cana-5212	229	16	respect	respect	NOUN
cana-5212	229	17	to	to	ADP
cana-5212	229	18	different	different	ADJ
cana-5212	229	19	crops	crop	NOUN
cana-5212	229	20	and	and	CCONJ
cana-5212	229	21	environmental	environmental	ADJ
cana-5212	229	22	scenarios	scenario	NOUN
cana-5212	229	23	.	.	PUNCT
cana-5212	230	1	the	the	DET
cana-5212	230	2	application	application	NOUN
cana-5212	230	3	of	of	ADP
cana-5212	230	4	fuzzy	fuzzy	ADJ
cana-5212	230	5	logic	logic	NOUN
cana-5212	230	6	allows	allow	VERB
cana-5212	230	7	for	for	ADP
cana-5212	230	8	the	the	DET
cana-5212	230	9	handling	handling	NOUN
cana-5212	230	10	of	of	ADP
cana-5212	230	11	variability	variability	NOUN
cana-5212	230	12	and	and	CCONJ
cana-5212	230	13	uncertainty	uncertainty	NOUN
cana-5212	230	14	in	in	ADP
cana-5212	230	15	the	the	DET
cana-5212	230	16	symptoms	symptom	NOUN
cana-5212	230	17	of	of	ADP
cana-5212	230	18	plant	plant	NOUN
cana-5212	230	19	diseases	disease	NOUN
cana-5212	230	20	and	and	CCONJ
cana-5212	230	21	guarantees	guarantee	VERB
cana-5212	230	22	generalization	generalization	NOUN
cana-5212	230	23	to	to	ADP
cana-5212	230	24	very	very	ADV
cana-5212	230	25	diverse	diverse	ADJ
cana-5212	230	26	situations	situation	NOUN
cana-5212	230	27	.	.	PUNCT
cana-5212	231	1	computational	computational	ADJ
cana-5212	231	2	efficiency	efficiency	NOUN
cana-5212	231	3	:	:	PUNCT
cana-5212	231	4	the	the	DET
cana-5212	231	5	computational	computational	ADJ
cana-5212	231	6	efficiency	efficiency	NOUN
cana-5212	231	7	of	of	ADP
cana-5212	231	8	the	the	DET
cana-5212	231	9	proposed	propose	VERB
cana-5212	231	10	method	method	NOUN
cana-5212	231	11	is	be	AUX
cana-5212	231	12	still	still	ADV
cana-5212	231	13	retained	retain	VERB
cana-5212	231	14	despite	despite	SCONJ
cana-5212	231	15	the	the	DET
cana-5212	231	16	added	add	VERB
cana-5212	231	17	complexity	complexity	NOUN
cana-5212	231	18	of	of	ADP
cana-5212	231	19	fuzzy	fuzzy	ADJ
cana-5212	231	20	logic	logic	NOUN
cana-5212	231	21	integration	integration	NOUN
cana-5212	231	22	.	.	PUNCT
cana-5212	232	1	in	in	ADP
cana-5212	232	2	this	this	DET
cana-5212	232	3	case	case	NOUN
cana-5212	232	4	,	,	PUNCT
cana-5212	232	5	this	this	PRON
cana-5212	232	6	means	mean	VERB
cana-5212	232	7	fast	fast	ADJ
cana-5212	232	8	processing	processing	NOUN
cana-5212	232	9	of	of	ADP
cana-5212	232	10	the	the	DET
cana-5212	232	11	cnn	cnn	PROPN
cana-5212	232	12	in	in	ADP
cana-5212	232	13	big	big	ADJ
cana-5212	232	14	data	datum	NOUN
cana-5212	232	15	is	be	AUX
cana-5212	232	16	combined	combine	VERB
cana-5212	232	17	with	with	ADP
cana-5212	232	18	streamlined	streamlined	ADJ
cana-5212	232	19	fuzzy	fuzzy	ADJ
cana-5212	232	20	inference	inference	NOUN
cana-5212	232	21	processing	processing	NOUN
cana-5212	232	22	that	that	PRON
cana-5212	232	23	will	will	AUX
cana-5212	232	24	satisfy	satisfy	VERB
cana-5212	232	25	both	both	DET
cana-5212	232	26	effectiveness	effectiveness	NOUN
cana-5212	232	27	and	and	CCONJ
cana-5212	232	28	efficiency	efficiency	NOUN
cana-5212	232	29	.	.	PUNCT
cana-5212	233	1	comparative	comparative	ADJ
cana-5212	233	2	advantages	advantage	NOUN
cana-5212	233	3	discussion	discussion	NOUN
cana-5212	233	4	:	:	PUNCT
cana-5212	233	5	in	in	ADP
cana-5212	233	6	the	the	DET
cana-5212	233	7	discussion	discussion	NOUN
cana-5212	233	8	,	,	PUNCT
cana-5212	233	9	the	the	DET
cana-5212	233	10	relative	relative	ADJ
cana-5212	233	11	advantages	advantage	NOUN
cana-5212	233	12	of	of	ADP
cana-5212	233	13	the	the	DET
cana-5212	233	14	proposed	propose	VERB
cana-5212	233	15	technique	technique	NOUN
cana-5212	233	16	against	against	ADP
cana-5212	233	17	traditional	traditional	ADJ
cana-5212	233	18	methods	method	NOUN
cana-5212	233	19	have	have	AUX
cana-5212	233	20	been	be	AUX
cana-5212	233	21	focused	focus	VERB
cana-5212	233	22	on	on	ADP
cana-5212	233	23	.	.	PUNCT
cana-5212	234	1	by	by	ADP
cana-5212	234	2	incorporating	incorporate	VERB
cana-5212	234	3	cnn	cnn	PROPN
cana-5212	234	4	with	with	ADP
cana-5212	234	5	fuzzy	fuzzy	ADJ
cana-5212	234	6	logic	logic	NOUN
cana-5212	234	7	,	,	PUNCT
cana-5212	234	8	it	it	PRON
cana-5212	234	9	will	will	AUX
cana-5212	234	10	not	not	PART
cana-5212	234	11	only	only	ADV
cana-5212	234	12	increase	increase	VERB
cana-5212	234	13	accuracy	accuracy	NOUN
cana-5212	234	14	in	in	ADP
cana-5212	234	15	detection	detection	NOUN
cana-5212	234	16	but	but	CCONJ
cana-5212	234	17	also	also	ADV
cana-5212	234	18	provide	provide	VERB
cana-5212	234	19	related	related	ADJ
cana-5212	234	20	vital	vital	ADJ
cana-5212	234	21	information	information	NOUN
cana-5212	234	22	about	about	ADP
cana-5212	234	23	the	the	DET
cana-5212	234	24	severity	severity	NOUN
cana-5212	234	25	of	of	ADP
cana-5212	234	26	the	the	DET
cana-5212	234	27	diseases	disease	NOUN
cana-5212	234	28	that	that	PRON
cana-5212	234	29	can	can	AUX
cana-5212	234	30	help	help	VERB
cana-5212	234	31	in	in	ADP
cana-5212	234	32	effective	effective	ADJ
cana-5212	234	33	disease	disease	NOUN
cana-5212	234	34	management	management	NOUN
cana-5212	234	35	.	.	PUNCT
cana-5212	235	1	future	future	ADJ
cana-5212	235	2	implications	implication	NOUN
cana-5212	235	3	:	:	PUNCT
cana-5212	235	4	the	the	DET
cana-5212	235	5	results	result	NOUN
cana-5212	235	6	indicate	indicate	VERB
cana-5212	235	7	that	that	SCONJ
cana-5212	235	8	involving	involve	VERB
cana-5212	235	9	high	high	ADJ
cana-5212	235	10	-	-	PUNCT
cana-5212	235	11	end	end	NOUN
cana-5212	235	12	machine	machine	NOUN
cana-5212	235	13	learning	learn	VERB
cana-5212	235	14	techniques	technique	NOUN
cana-5212	235	15	with	with	ADP
cana-5212	235	16	intelligent	intelligent	ADJ
cana-5212	235	17	systems	system	NOUN
cana-5212	235	18	such	such	ADJ
cana-5212	235	19	as	as	ADP
cana-5212	235	20	fuzzy	fuzzy	ADJ
cana-5212	235	21	logic	logic	NOUN
cana-5212	235	22	can	can	AUX
cana-5212	235	23	bring	bring	VERB
cana-5212	235	24	a	a	DET
cana-5212	235	25	significant	significant	ADJ
cana-5212	235	26	quantum	quantum	NOUN
cana-5212	235	27	of	of	ADP
cana-5212	235	28	difference	difference	NOUN
cana-5212	235	29	to	to	ADP
cana-5212	235	30	agricultural	agricultural	ADJ
cana-5212	235	31	practice	practice	NOUN
cana-5212	235	32	.	.	PUNCT
cana-5212	236	1	similarly	similarly	ADV
cana-5212	236	2	,	,	PUNCT
cana-5212	236	3	this	this	PRON
cana-5212	236	4	may	may	AUX
cana-5212	236	5	be	be	AUX
cana-5212	236	6	extended	extend	VERB
cana-5212	236	7	to	to	ADP
cana-5212	236	8	other	other	ADJ
cana-5212	236	9	areas	area	NOUN
cana-5212	236	10	of	of	ADP
cana-5212	236	11	precision	precision	NOUN
cana-5212	236	12	agriculture	agriculture	NOUN
cana-5212	236	13	targeted	target	VERB
cana-5212	236	14	toward	toward	ADP
cana-5212	236	15	promoting	promote	VERB
cana-5212	236	16	more	more	ADV
cana-5212	236	17	sustainable	sustainable	ADJ
cana-5212	236	18	and	and	CCONJ
cana-5212	236	19	productive	productive	ADJ
cana-5212	236	20	farming	farming	NOUN
cana-5212	236	21	.	.	PUNCT
cana-5212	237	1	cnn	cnn	PROPN
cana-5212	237	2	integrated	integrate	VERB
cana-5212	237	3	with	with	ADP
cana-5212	237	4	fuzzy	fuzzy	ADJ
cana-5212	237	5	logic	logic	NOUN
cana-5212	237	6	for	for	ADP
cana-5212	237	7	plant	plant	NOUN
cana-5212	237	8	disease	disease	NOUN
cana-5212	237	9	detection	detection	NOUN
cana-5212	237	10	and	and	CCONJ
cana-5212	237	11	severity	severity	NOUN
cana-5212	237	12	analysis	analysis	NOUN
cana-5212	237	13	is	be	AUX
cana-5212	237	14	,	,	PUNCT
cana-5212	237	15	therefore	therefore	ADV
cana-5212	237	16	,	,	PUNCT
cana-5212	237	17	a	a	DET
cana-5212	237	18	robust	robust	ADJ
cana-5212	237	19	,	,	PUNCT
cana-5212	237	20	accurate	accurate	ADJ
cana-5212	237	21	,	,	PUNCT
cana-5212	237	22	and	and	CCONJ
cana-5212	237	23	comprehensive	comprehensive	ADJ
cana-5212	237	24	approach	approach	NOUN
cana-5212	237	25	.	.	PUNCT
cana-5212	238	1	a	a	DET
cana-5212	238	2	comparative	comparative	ADJ
cana-5212	238	3	analysis	analysis	NOUN
cana-5212	238	4	and	and	CCONJ
cana-5212	238	5	detailed	detailed	ADJ
cana-5212	238	6	discussion	discussion	NOUN
cana-5212	238	7	have	have	AUX
cana-5212	238	8	given	give	VERB
cana-5212	238	9	insight	insight	NOUN
cana-5212	238	10	into	into	ADP
cana-5212	238	11	the	the	DET
cana-5212	238	12	major	major	ADJ
cana-5212	238	13	improvements	improvement	NOUN
cana-5212	238	14	and	and	CCONJ
cana-5212	238	15	advantages	advantage	NOUN
cana-5212	238	16	of	of	ADP
cana-5212	238	17	this	this	DET
cana-5212	238	18	approach	approach	NOUN
cana-5212	238	19	that	that	PRON
cana-5212	238	20	make	make	VERB
cana-5212	238	21	the	the	DET
cana-5212	238	22	algorithm	algorithm	NOUN
cana-5212	238	23	an	an	DET
cana-5212	238	24	asset	asset	NOUN
cana-5212	238	25	for	for	ADP
cana-5212	238	26	modern	modern	ADJ
cana-5212	238	27	agriculture	agriculture	NOUN
cana-5212	238	28	.	.	PUNCT
cana-5212	239	1	communications	communication	NOUN
cana-5212	239	2	on	on	ADP
cana-5212	239	3	applied	apply	VERB
cana-5212	239	4	nonlinear	nonlinear	ADJ
cana-5212	239	5	analysis	analysis	NOUN
cana-5212	239	6	issn	issn	NOUN
cana-5212	239	7	:	:	PUNCT
cana-5212	239	8	1074	1074	NUM
cana-5212	239	9	-	-	PUNCT
cana-5212	239	10	133x	133x	NUM
cana-5212	239	11	vol	vol	NOUN
cana-5212	239	12	32	32	NUM
cana-5212	239	13	no	no	NOUN
cana-5212	239	14	.	.	PUNCT
cana-5212	240	1	8s	8s	PROPN
cana-5212	240	2	(	(	PUNCT
cana-5212	240	3	2025	2025	NUM
cana-5212	240	4	)	)	PUNCT
cana-5212	240	5	948	948	NUM
cana-5212	240	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	240	7	6	6	NUM
cana-5212	240	8	.	.	PUNCT
cana-5212	240	9	conclusion	conclusion	NOUN
cana-5212	240	10	and	and	CCONJ
cana-5212	240	11	future	future	ADJ
cana-5212	240	12	work	work	NOUN
cana-5212	240	13	6.1	6.1	NUM
cana-5212	240	14	summary	summary	NOUN
cana-5212	240	15	of	of	ADP
cana-5212	240	16	findings	finding	NOUN
cana-5212	240	17	this	this	DET
cana-5212	240	18	paper	paper	NOUN
cana-5212	240	19	presents	present	VERB
cana-5212	240	20	research	research	NOUN
cana-5212	240	21	that	that	PRON
cana-5212	240	22	evaluates	evaluate	VERB
cana-5212	240	23	the	the	DET
cana-5212	240	24	effectiveness	effectiveness	NOUN
cana-5212	240	25	of	of	ADP
cana-5212	240	26	integrating	integrate	VERB
cana-5212	240	27	convolutional	convolutional	ADJ
cana-5212	240	28	neural	neural	ADJ
cana-5212	240	29	networks	network	NOUN
cana-5212	240	30	with	with	ADP
cana-5212	240	31	fuzzy	fuzzy	ADJ
cana-5212	240	32	logic	logic	NOUN
cana-5212	240	33	in	in	ADP
cana-5212	240	34	detecting	detect	VERB
cana-5212	240	35	multi	multi	ADJ
cana-5212	240	36	-	-	ADJ
cana-5212	240	37	class	class	ADJ
cana-5212	240	38	plant	plant	NOUN
cana-5212	240	39	leaf	leaf	NOUN
cana-5212	240	40	diseases	disease	NOUN
cana-5212	240	41	and	and	CCONJ
cana-5212	240	42	their	their	PRON
cana-5212	240	43	severity	severity	NOUN
cana-5212	240	44	analysis	analysis	NOUN
cana-5212	240	45	.	.	PUNCT
cana-5212	241	1	in	in	ADP
cana-5212	241	2	the	the	DET
cana-5212	241	3	approach	approach	NOUN
cana-5212	241	4	proposed	propose	VERB
cana-5212	241	5	here	here	ADV
cana-5212	241	6	,	,	PUNCT
cana-5212	241	7	the	the	DET
cana-5212	241	8	feature	feature	NOUN
cana-5212	241	9	extraction	extraction	NOUN
cana-5212	241	10	ability	ability	NOUN
cana-5212	241	11	of	of	ADP
cana-5212	241	12	cnns	cnns	PROPN
cana-5212	241	13	is	be	AUX
cana-5212	241	14	integrated	integrate	VERB
cana-5212	241	15	with	with	ADP
cana-5212	241	16	fuzzy	fuzzy	ADJ
cana-5212	241	17	logic	logic	NOUN
cana-5212	241	18	as	as	ADP
cana-5212	241	19	a	a	DET
cana-5212	241	20	nuanced	nuanced	ADJ
cana-5212	241	21	decision	decision	NOUN
cana-5212	241	22	-	-	PUNCT
cana-5212	241	23	making	make	VERB
cana-5212	241	24	module	module	NOUN
cana-5212	241	25	for	for	ADP
cana-5212	241	26	improving	improve	VERB
cana-5212	241	27	the	the	DET
cana-5212	241	28	accuracy	accuracy	NOUN
cana-5212	241	29	of	of	ADP
cana-5212	241	30	disease	disease	NOUN
cana-5212	241	31	detection	detection	NOUN
cana-5212	241	32	by	by	ADP
cana-5212	241	33	providing	provide	VERB
cana-5212	241	34	minute	minute	ADJ
cana-5212	241	35	details	detail	NOUN
cana-5212	241	36	of	of	ADP
cana-5212	241	37	the	the	DET
cana-5212	241	38	severity	severity	NOUN
cana-5212	241	39	assessment	assessment	NOUN
cana-5212	241	40	.	.	PUNCT
cana-5212	242	1	high	high	ADJ
cana-5212	242	2	model	model	NOUN
cana-5212	242	3	performance	performance	NOUN
cana-5212	242	4	could	could	AUX
cana-5212	242	5	be	be	AUX
cana-5212	242	6	evidenced	evidence	VERB
cana-5212	242	7	through	through	ADP
cana-5212	242	8	metrics	metric	NOUN
cana-5212	242	9	such	such	ADJ
cana-5212	242	10	as	as	ADP
cana-5212	242	11	accuracy	accuracy	NOUN
cana-5212	242	12	,	,	PUNCT
cana-5212	242	13	precision	precision	NOUN
cana-5212	242	14	,	,	PUNCT
cana-5212	242	15	recall	recall	NOUN
cana-5212	242	16	,	,	PUNCT
cana-5212	242	17	and	and	CCONJ
cana-5212	242	18	the	the	DET
cana-5212	242	19	f1	f1	PROPN
cana-5212	242	20	score	score	NOUN
cana-5212	242	21	,	,	PUNCT
cana-5212	242	22	all	all	PRON
cana-5212	242	23	of	of	ADP
cana-5212	242	24	which	which	PRON
cana-5212	242	25	turn	turn	VERB
cana-5212	242	26	out	out	ADP
cana-5212	242	27	to	to	PART
cana-5212	242	28	be	be	AUX
cana-5212	242	29	significantly	significantly	ADV
cana-5212	242	30	improved	improve	VERB
cana-5212	242	31	in	in	ADP
cana-5212	242	32	comparison	comparison	NOUN
cana-5212	242	33	to	to	ADP
cana-5212	242	34	conventional	conventional	ADJ
cana-5212	242	35	approaches	approach	NOUN
cana-5212	242	36	like	like	ADP
cana-5212	242	37	support	support	NOUN
cana-5212	242	38	vector	vector	NOUN
cana-5212	242	39	machines	machine	NOUN
cana-5212	242	40	and	and	CCONJ
cana-5212	242	41	k	k	NOUN
cana-5212	242	42	-	-	PUNCT
cana-5212	242	43	nearest	near	ADJ
cana-5212	242	44	neighbours	neighbour	NOUN
cana-5212	242	45	.	.	PUNCT
cana-5212	243	1	this	this	DET
cana-5212	243	2	integrated	integrate	VERB
cana-5212	243	3	approach	approach	NOUN
cana-5212	243	4	proposed	propose	VERB
cana-5212	243	5	herein	herein	NOUN
cana-5212	243	6	offers	offer	VERB
cana-5212	243	7	better	well	ADJ
cana-5212	243	8	precision	precision	NOUN
cana-5212	243	9	of	of	ADP
cana-5212	243	10	disease	disease	NOUN
cana-5212	243	11	classification	classification	NOUN
cana-5212	243	12	and	and	CCONJ
cana-5212	243	13	actionable	actionable	ADJ
cana-5212	243	14	insights	insight	NOUN
cana-5212	243	15	that	that	PRON
cana-5212	243	16	will	will	AUX
cana-5212	243	17	make	make	VERB
cana-5212	243	18	a	a	DET
cana-5212	243	19	great	great	ADJ
cana-5212	243	20	impact	impact	NOUN
cana-5212	243	21	on	on	ADP
cana-5212	243	22	the	the	DET
cana-5212	243	23	formulation	formulation	NOUN
cana-5212	243	24	of	of	ADP
cana-5212	243	25	efficient	efficient	ADJ
cana-5212	243	26	disease	disease	NOUN
cana-5212	243	27	management	management	NOUN
cana-5212	243	28	and	and	CCONJ
cana-5212	243	29	intervention	intervention	NOUN
cana-5212	243	30	strategies	strategy	NOUN
cana-5212	243	31	.	.	PUNCT
cana-5212	244	1	6.2	6.2	NUM
cana-5212	244	2	contributions	contribution	NOUN
cana-5212	244	3	among	among	ADP
cana-5212	244	4	others	other	NOUN
cana-5212	244	5	,	,	PUNCT
cana-5212	244	6	the	the	DET
cana-5212	244	7	following	follow	VERB
cana-5212	244	8	are	be	AUX
cana-5212	244	9	the	the	DET
cana-5212	244	10	principal	principal	ADJ
cana-5212	244	11	contributions	contribution	NOUN
cana-5212	244	12	of	of	ADP
cana-5212	244	13	the	the	DET
cana-5212	244	14	work	work	NOUN
cana-5212	244	15	in	in	ADP
cana-5212	244	16	the	the	DET
cana-5212	244	17	direction	direction	NOUN
cana-5212	244	18	of	of	ADP
cana-5212	244	19	plant	plant	NOUN
cana-5212	244	20	disease	disease	NOUN
cana-5212	244	21	detection	detection	NOUN
cana-5212	244	22	:	:	PUNCT
cana-5212	244	23	integrated	integrate	VERB
cana-5212	244	24	approach	approach	NOUN
cana-5212	244	25	:	:	PUNCT
cana-5212	244	26	this	this	DET
cana-5212	244	27	work	work	NOUN
cana-5212	244	28	propitiously	propitiously	ADV
cana-5212	244	29	combines	combine	VERB
cana-5212	244	30	cnn	cnn	PROPN
cana-5212	244	31	and	and	CCONJ
cana-5212	244	32	fuzzy	fuzzy	ADJ
cana-5212	244	33	logic	logic	NOUN
cana-5212	244	34	,	,	PUNCT
cana-5212	244	35	solving	solve	VERB
cana-5212	244	36	disease	disease	NOUN
cana-5212	244	37	detection	detection	NOUN
cana-5212	244	38	and	and	CCONJ
cana-5212	244	39	severity	severity	NOUN
cana-5212	244	40	analysis	analysis	NOUN
cana-5212	244	41	in	in	ADP
cana-5212	244	42	a	a	DET
cana-5212	244	43	twofold	twofold	NOUN
cana-5212	244	44	manner	manner	NOUN
cana-5212	244	45	.	.	PUNCT
cana-5212	245	1	this	this	DET
cana-5212	245	2	integration	integration	NOUN
cana-5212	245	3	closes	close	VERB
cana-5212	245	4	an	an	DET
cana-5212	245	5	important	important	ADJ
cana-5212	245	6	gap	gap	NOUN
cana-5212	245	7	of	of	ADP
cana-5212	245	8	the	the	DET
cana-5212	245	9	existing	exist	VERB
cana-5212	245	10	methodologies	methodology	NOUN
cana-5212	245	11	that	that	PRON
cana-5212	245	12	mainly	mainly	ADV
cana-5212	245	13	focus	focus	VERB
cana-5212	245	14	on	on	ADP
cana-5212	245	15	only	only	ADV
cana-5212	245	16	the	the	DET
cana-5212	245	17	classification	classification	NOUN
cana-5212	245	18	task	task	NOUN
cana-5212	245	19	.	.	PUNCT
cana-5212	246	1	improved	improved	ADJ
cana-5212	246	2	accuracy	accuracy	NOUN
cana-5212	246	3	:	:	PUNCT
cana-5212	246	4	higher	high	ADJ
cana-5212	246	5	accuracy	accuracy	NOUN
cana-5212	246	6	and	and	CCONJ
cana-5212	246	7	robustness	robustness	NOUN
cana-5212	246	8	of	of	ADP
cana-5212	246	9	the	the	DET
cana-5212	246	10	proposed	propose	VERB
cana-5212	246	11	model	model	NOUN
cana-5212	246	12	against	against	ADP
cana-5212	246	13	the	the	DET
cana-5212	246	14	variations	variation	NOUN
cana-5212	246	15	in	in	ADP
cana-5212	246	16	plant	plant	NOUN
cana-5212	246	17	species	specie	NOUN
cana-5212	246	18	and	and	CCONJ
cana-5212	246	19	environmental	environmental	ADJ
cana-5212	246	20	conditions	condition	NOUN
cana-5212	246	21	may	may	AUX
cana-5212	246	22	be	be	AUX
cana-5212	246	23	used	use	VERB
cana-5212	246	24	to	to	PART
cana-5212	246	25	provide	provide	VERB
cana-5212	246	26	a	a	DET
cana-5212	246	27	versatile	versatile	ADJ
cana-5212	246	28	tool	tool	NOUN
cana-5212	246	29	for	for	ADP
cana-5212	246	30	agricultural	agricultural	ADJ
cana-5212	246	31	applications	application	NOUN
cana-5212	246	32	.	.	PUNCT
cana-5212	247	1	actionable	actionable	ADJ
cana-5212	247	2	insights	insight	NOUN
cana-5212	247	3	:	:	PUNCT
cana-5212	247	4	inclusion	inclusion	NOUN
cana-5212	247	5	of	of	ADP
cana-5212	247	6	severity	severity	NOUN
cana-5212	247	7	analysis	analysis	NOUN
cana-5212	247	8	in	in	ADP
cana-5212	247	9	this	this	DET
cana-5212	247	10	model	model	NOUN
cana-5212	247	11	makes	make	VERB
cana-5212	247	12	it	it	PRON
cana-5212	247	13	deliver	deliver	VERB
cana-5212	247	14	more	more	ADJ
cana-5212	247	15	than	than	ADP
cana-5212	247	16	just	just	ADV
cana-5212	247	17	a	a	DET
cana-5212	247	18	detection	detection	NOUN
cana-5212	247	19	capability	capability	NOUN
cana-5212	247	20	;	;	PUNCT
cana-5212	247	21	it	it	PRON
cana-5212	247	22	gives	give	VERB
cana-5212	247	23	detailed	detailed	ADJ
cana-5212	247	24	insights	insight	NOUN
cana-5212	247	25	into	into	ADP
cana-5212	247	26	the	the	DET
cana-5212	247	27	severity	severity	NOUN
cana-5212	247	28	of	of	ADP
cana-5212	247	29	diseases	disease	NOUN
cana-5212	247	30	that	that	PRON
cana-5212	247	31	form	form	VERB
cana-5212	247	32	the	the	DET
cana-5212	247	33	basis	basis	NOUN
cana-5212	247	34	for	for	SCONJ
cana-5212	247	35	farmers	farmer	NOUN
cana-5212	247	36	to	to	PART
cana-5212	247	37	make	make	VERB
cana-5212	247	38	informed	informed	ADJ
cana-5212	247	39	decisions	decision	NOUN
cana-5212	247	40	about	about	ADP
cana-5212	247	41	treatment	treatment	NOUN
cana-5212	247	42	and	and	CCONJ
cana-5212	247	43	management	management	NOUN
cana-5212	247	44	.	.	PUNCT
cana-5212	248	1	comparative	comparative	ADJ
cana-5212	248	2	advantage	advantage	NOUN
cana-5212	248	3	:	:	PUNCT
cana-5212	248	4	this	this	DET
cana-5212	248	5	comprehensive	comprehensive	ADJ
cana-5212	248	6	comparison	comparison	NOUN
cana-5212	248	7	with	with	ADP
cana-5212	248	8	traditional	traditional	ADJ
cana-5212	248	9	and	and	CCONJ
cana-5212	248	10	other	other	ADJ
cana-5212	248	11	deep	deep	ADJ
cana-5212	248	12	learning	learning	NOUN
cana-5212	248	13	methods	method	NOUN
cana-5212	248	14	underlines	underline	VERB
cana-5212	248	15	enhanced	enhanced	ADJ
cana-5212	248	16	performance	performance	NOUN
cana-5212	248	17	and	and	CCONJ
cana-5212	248	18	utility	utility	NOUN
cana-5212	248	19	of	of	ADP
cana-5212	248	20	the	the	DET
cana-5212	248	21	proposed	propose	VERB
cana-5212	248	22	approach	approach	NOUN
cana-5212	248	23	,	,	PUNCT
cana-5212	248	24	clearly	clearly	ADV
cana-5212	248	25	indicating	indicate	VERB
cana-5212	248	26	its	its	PRON
cana-5212	248	27	potential	potential	NOUN
cana-5212	248	28	as	as	ADP
cana-5212	248	29	a	a	DET
cana-5212	248	30	useful	useful	ADJ
cana-5212	248	31	tool	tool	NOUN
cana-5212	248	32	for	for	ADP
cana-5212	248	33	modern	modern	ADJ
cana-5212	248	34	agriculture	agriculture	NOUN
cana-5212	248	35	.	.	PUNCT
cana-5212	249	1	6.3	6.3	NUM
cana-5212	249	2	future	future	ADJ
cana-5212	249	3	research	research	NOUN
cana-5212	249	4	though	though	SCONJ
cana-5212	249	5	the	the	DET
cana-5212	249	6	proposed	propose	VERB
cana-5212	249	7	method	method	NOUN
cana-5212	249	8	represents	represent	VERB
cana-5212	249	9	a	a	DET
cana-5212	249	10	breakthrough	breakthrough	NOUN
cana-5212	249	11	in	in	ADP
cana-5212	249	12	plant	plant	NOUN
cana-5212	249	13	disease	disease	NOUN
cana-5212	249	14	detection	detection	NOUN
cana-5212	249	15	,	,	PUNCT
cana-5212	249	16	a	a	DET
cana-5212	249	17	number	number	NOUN
cana-5212	249	18	of	of	ADP
cana-5212	249	19	future	future	ADJ
cana-5212	249	20	research	research	NOUN
cana-5212	249	21	directions	direction	NOUN
cana-5212	249	22	can	can	AUX
cana-5212	249	23	further	far	ADV
cana-5212	249	24	promote	promote	VERB
cana-5212	249	25	its	its	PRON
cana-5212	249	26	effectiveness	effectiveness	NOUN
cana-5212	249	27	and	and	CCONJ
cana-5212	249	28	applicability	applicability	NOUN
cana-5212	249	29	.	.	PUNCT
cana-5212	250	1	in	in	ADP
cana-5212	250	2	this	this	DET
cana-5212	250	3	regard	regard	NOUN
cana-5212	250	4	,	,	PUNCT
cana-5212	250	5	diverse	diverse	ADJ
cana-5212	250	6	datasets	dataset	NOUN
cana-5212	250	7	:	:	PUNCT
cana-5212	250	8	future	future	ADJ
cana-5212	250	9	studies	study	NOUN
cana-5212	250	10	should	should	AUX
cana-5212	250	11	target	target	VERB
cana-5212	250	12	a	a	DET
cana-5212	250	13	variety	variety	NOUN
cana-5212	250	14	of	of	ADP
cana-5212	250	15	more	more	ADJ
cana-5212	250	16	datasets	dataset	NOUN
cana-5212	250	17	comprising	comprise	VERB
cana-5212	250	18	a	a	DET
cana-5212	250	19	wide	wide	ADJ
cana-5212	250	20	array	array	NOUN
cana-5212	250	21	of	of	ADP
cana-5212	250	22	plant	plant	NOUN
cana-5212	250	23	species	specie	NOUN
cana-5212	250	24	and	and	CCONJ
cana-5212	250	25	types	type	NOUN
cana-5212	250	26	of	of	ADP
cana-5212	250	27	disease	disease	NOUN
cana-5212	250	28	to	to	PART
cana-5212	250	29	better	well	ADV
cana-5212	250	30	generalize	generalize	VERB
cana-5212	250	31	the	the	DET
cana-5212	250	32	model	model	NOUN
cana-5212	250	33	across	across	ADP
cana-5212	250	34	different	different	ADJ
cana-5212	250	35	agricultural	agricultural	ADJ
cana-5212	250	36	scenarios	scenario	NOUN
cana-5212	250	37	.	.	PUNCT
cana-5212	251	1	environmental	environmental	ADJ
cana-5212	251	2	variability	variability	NOUN
cana-5212	251	3	:	:	PUNCT
cana-5212	251	4	one	one	NUM
cana-5212	251	5	such	such	ADJ
cana-5212	251	6	area	area	NOUN
cana-5212	251	7	can	can	AUX
cana-5212	251	8	be	be	AUX
cana-5212	251	9	training	training	NOUN
cana-5212	251	10	and	and	CCONJ
cana-5212	251	11	testing	testing	NOUN
cana-5212	251	12	under	under	ADP
cana-5212	251	13	different	different	ADJ
cana-5212	251	14	environmental	environmental	ADJ
cana-5212	251	15	scenarios	scenario	NOUN
cana-5212	251	16	for	for	ADP
cana-5212	251	17	light	light	ADJ
cana-5212	251	18	,	,	PUNCT
cana-5212	251	19	background	background	NOUN
cana-5212	251	20	,	,	PUNCT
cana-5212	251	21	and	and	CCONJ
cana-5212	251	22	weather	weather	NOUN
cana-5212	251	23	.	.	PUNCT
cana-5212	252	1	this	this	PRON
cana-5212	252	2	will	will	AUX
cana-5212	252	3	ensure	ensure	VERB
cana-5212	252	4	that	that	SCONJ
cana-5212	252	5	the	the	DET
cana-5212	252	6	model	model	NOUN
cana-5212	252	7	produces	produce	VERB
cana-5212	252	8	an	an	DET
cana-5212	252	9	accurate	accurate	ADJ
cana-5212	252	10	and	and	CCONJ
cana-5212	252	11	reliable	reliable	ADJ
cana-5212	252	12	result	result	NOUN
cana-5212	252	13	under	under	ADP
cana-5212	252	14	field	field	NOUN
cana-5212	252	15	conditions	condition	NOUN
cana-5212	252	16	.	.	PUNCT
cana-5212	253	1	communications	communication	NOUN
cana-5212	253	2	on	on	ADP
cana-5212	253	3	applied	apply	VERB
cana-5212	253	4	nonlinear	nonlinear	ADJ
cana-5212	253	5	analysis	analysis	NOUN
cana-5212	253	6	issn	issn	NOUN
cana-5212	253	7	:	:	PUNCT
cana-5212	253	8	1074	1074	NUM
cana-5212	253	9	-	-	PUNCT
cana-5212	253	10	133x	133x	NUM
cana-5212	253	11	vol	vol	NOUN
cana-5212	253	12	32	32	NUM
cana-5212	253	13	no	no	NOUN
cana-5212	253	14	.	.	PUNCT
cana-5212	254	1	8s	8s	PROPN
cana-5212	254	2	(	(	PUNCT
cana-5212	254	3	2025	2025	NUM
cana-5212	254	4	)	)	PUNCT
cana-5212	254	5	949	949	NUM
cana-5212	255	1	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5212	255	2	advanced	advanced	ADJ
cana-5212	255	3	integration	integration	NOUN
cana-5212	255	4	techniques	technique	NOUN
cana-5212	255	5	:	:	PUNCT
cana-5212	255	6	further	far	ADV
cana-5212	255	7	refinement	refinement	NOUN
cana-5212	255	8	of	of	ADP
cana-5212	255	9	integration	integration	NOUN
cana-5212	255	10	between	between	ADP
cana-5212	255	11	cnn	cnn	PROPN
cana-5212	255	12	and	and	CCONJ
cana-5212	255	13	fuzzy	fuzzy	ADJ
cana-5212	255	14	logic	logic	NOUN
cana-5212	255	15	could	could	AUX
cana-5212	255	16	still	still	ADV
cana-5212	255	17	be	be	AUX
cana-5212	255	18	done	do	VERB
cana-5212	255	19	.	.	PUNCT
cana-5212	256	1	for	for	ADP
cana-5212	256	2	example	example	NOUN
cana-5212	256	3	,	,	PUNCT
cana-5212	256	4	adaptive	adaptive	ADJ
cana-5212	256	5	fuzzy	fuzzy	ADJ
cana-5212	256	6	systems	system	NOUN
cana-5212	256	7	that	that	PRON
cana-5212	256	8	change	change	VERB
cana-5212	256	9	their	their	PRON
cana-5212	256	10	rules	rule	NOUN
cana-5212	256	11	automatically	automatically	ADV
cana-5212	256	12	with	with	ADP
cana-5212	256	13	regard	regard	NOUN
cana-5212	256	14	to	to	ADP
cana-5212	256	15	new	new	ADJ
cana-5212	256	16	inputted	inputte	VERB
cana-5212	256	17	data	datum	NOUN
cana-5212	256	18	may	may	AUX
cana-5212	256	19	provide	provide	VERB
cana-5212	256	20	more	more	ADV
cana-5212	256	21	accurate	accurate	ADJ
cana-5212	256	22	severity	severity	NOUN
cana-5212	256	23	analysis	analysis	NOUN
cana-5212	256	24	.	.	PUNCT
cana-5212	257	1	real	real	ADJ
cana-5212	257	2	-	-	PUNCT
cana-5212	257	3	time	time	NOUN
cana-5212	257	4	implementation	implementation	NOUN
cana-5212	257	5	:	:	PUNCT
cana-5212	257	6	light	light	NOUN
cana-5212	257	7	weighted	weight	VERB
cana-5212	257	8	and	and	CCONJ
cana-5212	257	9	optimized	optimize	VERB
cana-5212	257	10	versions	version	NOUN
cana-5212	257	11	of	of	ADP
cana-5212	257	12	the	the	DET
cana-5212	257	13	model	model	NOUN
cana-5212	257	14	can	can	AUX
cana-5212	257	15	be	be	AUX
cana-5212	257	16	implemented	implement	VERB
cana-5212	257	17	on	on	ADP
cana-5212	257	18	mobile	mobile	ADJ
cana-5212	257	19	devices	device	NOUN
cana-5212	257	20	or	or	CCONJ
cana-5212	257	21	even	even	ADV
cana-5212	257	22	drones	drone	NOUN
cana-5212	257	23	for	for	ADP
cana-5212	257	24	real	real	ADJ
cana-5212	257	25	-	-	PUNCT
cana-5212	257	26	time	time	NOUN
cana-5212	257	27	monitoring	monitoring	NOUN
cana-5212	257	28	and	and	CCONJ
cana-5212	257	29	management	management	NOUN
cana-5212	257	30	in	in	ADP
cana-5212	257	31	large	large	ADJ
cana-5212	257	32	-	-	PUNCT
cana-5212	257	33	scale	scale	NOUN
cana-5212	257	34	agricultural	agricultural	ADJ
cana-5212	257	35	fields	field	NOUN
cana-5212	257	36	.	.	PUNCT
cana-5212	258	1	chronology	chronology	NOUN
cana-5212	258	2	-	-	PUNCT
cana-5212	258	3	based	base	VERB
cana-5212	258	4	monitoring	monitoring	NOUN
cana-5212	258	5	of	of	ADP
cana-5212	258	6	disease	disease	NOUN
cana-5212	258	7	progression	progression	NOUN
cana-5212	258	8	:	:	PUNCT
cana-5212	258	9	temporal	temporal	ADJ
cana-5212	258	10	analysis	analysis	NOUN
cana-5212	258	11	of	of	ADP
cana-5212	258	12	the	the	DET
cana-5212	258	13	diseases	disease	NOUN
cana-5212	258	14	can	can	AUX
cana-5212	258	15	be	be	AUX
cana-5212	258	16	integrated	integrate	VERB
cana-5212	258	17	into	into	ADP
cana-5212	258	18	the	the	DET
cana-5212	258	19	plant	plant	NOUN
cana-5212	258	20	for	for	ADP
cana-5212	258	21	monitoring	monitor	VERB
cana-5212	258	22	the	the	DET
cana-5212	258	23	progress	progress	NOUN
cana-5212	258	24	of	of	ADP
cana-5212	258	25	the	the	DET
cana-5212	258	26	diseases	disease	NOUN
cana-5212	258	27	.	.	PUNCT
cana-5212	259	1	such	such	ADJ
cana-5212	259	2	will	will	AUX
cana-5212	259	3	give	give	VERB
cana-5212	259	4	an	an	DET
cana-5212	259	5	insight	insight	NOUN
cana-5212	259	6	into	into	ADP
cana-5212	259	7	the	the	DET
cana-5212	259	8	dynamics	dynamic	NOUN
cana-5212	259	9	of	of	ADP
cana-5212	259	10	diseases	disease	NOUN
cana-5212	259	11	and	and	CCONJ
cana-5212	259	12	hence	hence	ADV
cana-5212	259	13	help	help	VERB
cana-5212	259	14	in	in	ADP
cana-5212	259	15	its	its	PRON
cana-5212	259	16	early	early	ADJ
cana-5212	259	17	detection	detection	NOUN
cana-5212	259	18	and	and	CCONJ
cana-5212	259	19	prevention	prevention	NOUN
cana-5212	259	20	measures	measure	NOUN
cana-5212	259	21	.	.	PUNCT
cana-5212	260	1	it	it	PRON
cana-5212	260	2	should	should	AUX
cana-5212	260	3	have	have	VERB
cana-5212	260	4	user	user	NOUN
cana-5212	260	5	-	-	PUNCT
cana-5212	260	6	friendly	friendly	ADJ
cana-5212	260	7	interfaces	interface	NOUN
cana-5212	260	8	so	so	SCONJ
cana-5212	260	9	that	that	SCONJ
cana-5212	260	10	any	any	DET
cana-5212	260	11	farmer	farmer	NOUN
cana-5212	260	12	or	or	CCONJ
cana-5212	260	13	other	other	ADJ
cana-5212	260	14	agricultural	agricultural	ADJ
cana-5212	260	15	professional	professional	NOUN
cana-5212	260	16	with	with	ADP
cana-5212	260	17	not	not	PART
cana-5212	260	18	much	much	ADJ
cana-5212	260	19	technical	technical	ADJ
cana-5212	260	20	knowledge	knowledge	NOUN
cana-5212	260	21	can	can	AUX
cana-5212	260	22	use	use	VERB
cana-5212	260	23	it	it	PRON
cana-5212	260	24	easily	easily	ADV
cana-5212	260	25	,	,	PUNCT
cana-5212	260	26	thereby	thereby	ADV
cana-5212	260	27	gaining	gain	VERB
cana-5212	260	28	more	more	ADJ
cana-5212	260	29	users	user	NOUN
cana-5212	260	30	and	and	CCONJ
cana-5212	260	31	finding	find	VERB
cana-5212	260	32	practical	practical	ADJ
cana-5212	260	33	applications	application	NOUN
cana-5212	260	34	.	.	PUNCT
cana-5212	261	1	this	this	PRON
cana-5212	261	2	has	have	AUX
cana-5212	261	3	greatly	greatly	ADV
cana-5212	261	4	improved	improve	VERB
cana-5212	261	5	agricultural	agricultural	ADJ
cana-5212	261	6	technology	technology	NOUN
cana-5212	261	7	by	by	ADP
cana-5212	261	8	integrating	integrate	VERB
cana-5212	261	9	cnn	cnn	PROPN
cana-5212	261	10	with	with	ADP
cana-5212	261	11	fuzzy	fuzzy	ADJ
cana-5212	261	12	logic	logic	NOUN
cana-5212	261	13	in	in	ADP
cana-5212	261	14	detecting	detect	VERB
cana-5212	261	15	and	and	CCONJ
cana-5212	261	16	analyzing	analyze	VERB
cana-5212	261	17	the	the	DET
cana-5212	261	18	severity	severity	NOUN
cana-5212	261	19	of	of	ADP
cana-5212	261	20	plant	plant	NOUN
cana-5212	261	21	leaf	leaf	NOUN
cana-5212	261	22	diseases	disease	NOUN
cana-5212	261	23	.	.	PUNCT
cana-5212	262	1	the	the	DET
cana-5212	262	2	research	research	NOUN
cana-5212	262	3	addresses	address	VERB
cana-5212	262	4	both	both	DET
cana-5212	262	5	aspects	aspect	NOUN
cana-5212	262	6	of	of	ADP
cana-5212	262	7	plant	plant	NOUN
cana-5212	262	8	diseases	disease	NOUN
cana-5212	262	9	:	:	PUNCT
cana-5212	262	10	the	the	DET
cana-5212	262	11	detection	detection	NOUN
cana-5212	262	12	and	and	CCONJ
cana-5212	262	13	management	management	NOUN
cana-5212	262	14	.	.	PUNCT
cana-5212	263	1	therefore	therefore	ADV
cana-5212	263	2	,	,	PUNCT
cana-5212	263	3	this	this	PRON
cana-5212	263	4	offers	offer	VERB
cana-5212	263	5	one	one	NUM
cana-5212	263	6	comprehensive	comprehensive	ADJ
cana-5212	263	7	solution	solution	NOUN
cana-5212	263	8	toward	toward	ADP
cana-5212	263	9	ensuring	ensure	VERB
cana-5212	263	10	better	well	ADJ
cana-5212	263	11	crop	crop	NOUN
cana-5212	263	12	health	health	NOUN
cana-5212	263	13	and	and	CCONJ
cana-5212	263	14	higher	high	ADJ
cana-5212	263	15	yields	yield	NOUN
cana-5212	263	16	.	.	PUNCT
cana-5212	264	1	further	further	ADJ
cana-5212	264	2	research	research	NOUN
cana-5212	264	3	needs	need	VERB
cana-5212	264	4	to	to	PART
cana-5212	264	5	be	be	AUX
cana-5212	264	6	carried	carry	VERB
cana-5212	264	7	out	out	ADP
cana-5212	264	8	to	to	PART
cana-5212	264	9	add	add	VERB
cana-5212	264	10	to	to	ADP
cana-5212	264	11	these	these	DET
cana-5212	264	12	findings	finding	NOUN
cana-5212	264	13	by	by	ADP
cana-5212	264	14	investigating	investigate	VERB
cana-5212	264	15	new	new	ADJ
cana-5212	264	16	datasets	dataset	NOUN
cana-5212	264	17	,	,	PUNCT
cana-5212	264	18	perfecting	perfect	VERB
cana-5212	264	19	techniques	technique	NOUN
cana-5212	264	20	,	,	PUNCT
cana-5212	264	21	and	and	CCONJ
cana-5212	264	22	enhancing	enhance	VERB
cana-5212	264	23	their	their	PRON
cana-5212	264	24	practical	practical	ADJ
cana-5212	264	25	relevance	relevance	NOUN
cana-5212	264	26	for	for	ADP
cana-5212	264	27	the	the	DET
cana-5212	264	28	farming	farming	NOUN
cana-5212	264	29	community	community	NOUN
cana-5212	264	30	.	.	PUNCT
cana-5212	265	1	refrences	refrence	VERB
cana-5212	266	1	[	[	X
cana-5212	266	2	1	1	NUM
cana-5212	266	3	]	]	X
cana-5212	266	4	gupta	gupta	PROPN
cana-5212	266	5	,	,	PUNCT
cana-5212	266	6	a.	a.	NOUN
cana-5212	266	7	,	,	PUNCT
cana-5212	266	8	&	&	CCONJ
cana-5212	266	9	singh	singh	PROPN
cana-5212	266	10	,	,	PUNCT
cana-5212	266	11	v.	v.	PROPN
cana-5212	266	12	(	(	PUNCT
cana-5212	266	13	2022	2022	NUM
cana-5212	266	14	)	)	PUNCT
cana-5212	266	15	.	.	PUNCT
cana-5212	267	1	plant	plant	NOUN
cana-5212	267	2	disease	disease	NOUN
cana-5212	267	3	detection	detection	NOUN
cana-5212	267	4	using	use	VERB
cana-5212	267	5	convolutional	convolutional	ADJ
cana-5212	267	6	neural	neural	ADJ
cana-5212	267	7	networks	network	NOUN
cana-5212	267	8	.	.	PUNCT
cana-5212	268	1	journal	journal	NOUN
cana-5212	268	2	of	of	ADP
cana-5212	268	3	computer	computer	NOUN
cana-5212	268	4	and	and	CCONJ
cana-5212	268	5	information	information	NOUN
cana-5212	268	6	technology	technology	NOUN
cana-5212	268	7	,	,	PUNCT
cana-5212	268	8	14(1	14(1	NUM
cana-5212	268	9	)	)	PUNCT
cana-5212	268	10	,	,	PUNCT
cana-5212	268	11	33	33	NUM
cana-5212	268	12	-	-	SYM
cana-5212	268	13	42	42	NUM
cana-5212	268	14	.	.	PUNCT
cana-5212	269	1	[	[	X
cana-5212	269	2	2	2	NUM
cana-5212	269	3	]	]	PUNCT
cana-5212	269	4	sharma	sharma	NOUN
cana-5212	269	5	,	,	PUNCT
cana-5212	269	6	p.	p.	PROPN
cana-5212	269	7	,	,	PUNCT
cana-5212	269	8	&	&	CCONJ
cana-5212	269	9	kaur	kaur	PROPN
cana-5212	269	10	,	,	PUNCT
cana-5212	269	11	r.	r.	PROPN
cana-5212	269	12	(	(	PUNCT
cana-5212	269	13	2022	2022	NUM
cana-5212	269	14	)	)	PUNCT
cana-5212	269	15	.	.	PUNCT
cana-5212	270	1	deep	deep	ADJ
cana-5212	270	2	learning	learning	NOUN
cana-5212	270	3	-	-	PUNCT
cana-5212	270	4	based	base	VERB
cana-5212	270	5	plant	plant	NOUN
cana-5212	270	6	leaf	leaf	NOUN
cana-5212	270	7	disease	disease	NOUN
cana-5212	270	8	detection	detection	NOUN
cana-5212	270	9	:	:	PUNCT
cana-5212	270	10	a	a	DET
cana-5212	270	11	review	review	NOUN
cana-5212	270	12	.	.	PUNCT
cana-5212	271	1	indian	indian	PROPN
cana-5212	271	2	journal	journal	PROPN
cana-5212	271	3	of	of	ADP
cana-5212	271	4	computer	computer	NOUN
cana-5212	271	5	science	science	NOUN
cana-5212	271	6	,	,	PUNCT
cana-5212	271	7	9(2	9(2	NUM
cana-5212	271	8	)	)	PUNCT
cana-5212	271	9	,	,	PUNCT
cana-5212	271	10	56	56	NUM
cana-5212	271	11	-	-	SYM
cana-5212	271	12	65	65	NUM
cana-5212	271	13	.	.	PUNCT
cana-5212	272	1	[	[	X
cana-5212	272	2	3	3	NUM
cana-5212	272	3	]	]	X
cana-5212	272	4	patel	patel	NOUN
cana-5212	272	5	,	,	PUNCT
cana-5212	272	6	k.	k.	PROPN
cana-5212	272	7	,	,	PUNCT
cana-5212	272	8	&	&	CCONJ
cana-5212	272	9	mehta	mehta	PROPN
cana-5212	272	10	,	,	PUNCT
cana-5212	272	11	h.	h.	PROPN
cana-5212	272	12	(	(	PUNCT
cana-5212	272	13	2023	2023	NUM
cana-5212	272	14	)	)	PUNCT
cana-5212	272	15	.	.	PUNCT
cana-5212	273	1	cnn	cnn	PROPN
cana-5212	273	2	and	and	CCONJ
cana-5212	273	3	transfer	transfer	VERB
cana-5212	273	4	learning	learning	NOUN
cana-5212	273	5	for	for	ADP
cana-5212	273	6	plant	plant	NOUN
cana-5212	273	7	disease	disease	NOUN
cana-5212	273	8	detection	detection	NOUN
cana-5212	273	9	in	in	ADP
cana-5212	273	10	agricultural	agricultural	ADJ
cana-5212	273	11	fields	field	NOUN
cana-5212	273	12	.	.	PUNCT
cana-5212	274	1	international	international	ADJ
cana-5212	274	2	journal	journal	NOUN
cana-5212	274	3	of	of	ADP
cana-5212	274	4	agricultural	agricultural	ADJ
cana-5212	274	5	sciences	science	NOUN
cana-5212	274	6	,	,	PUNCT
cana-5212	274	7	11(3	11(3	NUM
cana-5212	274	8	)	)	PUNCT
cana-5212	274	9	,	,	PUNCT
cana-5212	274	10	111	111	NUM
cana-5212	274	11	-	-	SYM
cana-5212	274	12	119	119	NUM
cana-5212	274	13	.	.	PUNCT
cana-5212	275	1	[	[	X
cana-5212	275	2	4	4	NUM
cana-5212	275	3	]	]	X
cana-5212	275	4	kumar	kumar	PROPN
cana-5212	275	5	,	,	PUNCT
cana-5212	275	6	r.	r.	PROPN
cana-5212	275	7	,	,	PUNCT
cana-5212	275	8	&	&	CCONJ
cana-5212	275	9	sharma	sharma	PROPN
cana-5212	275	10	,	,	PUNCT
cana-5212	275	11	v.	v.	PROPN
cana-5212	275	12	(	(	PUNCT
cana-5212	275	13	2023	2023	NUM
cana-5212	275	14	)	)	PUNCT
cana-5212	275	15	.	.	PUNCT
cana-5212	276	1	integrating	integrate	VERB
cana-5212	276	2	fuzzy	fuzzy	ADJ
cana-5212	276	3	logic	logic	NOUN
cana-5212	276	4	with	with	ADP
cana-5212	276	5	cnn	cnn	PROPN
cana-5212	276	6	for	for	ADP
cana-5212	276	7	plant	plant	NOUN
cana-5212	276	8	disease	disease	NOUN
cana-5212	276	9	severity	severity	NOUN
cana-5212	276	10	assessment	assessment	NOUN
cana-5212	276	11	.	.	PUNCT
cana-5212	277	1	advances	advance	NOUN
cana-5212	277	2	in	in	ADP
cana-5212	277	3	computational	computational	ADJ
cana-5212	277	4	agriculture	agriculture	NOUN
cana-5212	277	5	,	,	PUNCT
cana-5212	277	6	5(1	5(1	NUM
cana-5212	277	7	)	)	PUNCT
cana-5212	277	8	,	,	PUNCT
cana-5212	277	9	22	22	NUM
cana-5212	277	10	-	-	SYM
cana-5212	277	11	35	35	NUM
cana-5212	277	12	.	.	PUNCT
cana-5212	278	1	[	[	X
cana-5212	278	2	5	5	NUM
cana-5212	278	3	]	]	X
cana-5212	278	4	raj	raj	PROPN
cana-5212	278	5	,	,	PUNCT
cana-5212	278	6	m.	m.	NOUN
cana-5212	278	7	,	,	PUNCT
cana-5212	278	8	&	&	CCONJ
cana-5212	278	9	singh	singh	PROPN
cana-5212	278	10	,	,	PUNCT
cana-5212	278	11	p.	p.	NOUN
cana-5212	278	12	(	(	PUNCT
cana-5212	278	13	2022	2022	NUM
cana-5212	278	14	)	)	PUNCT
cana-5212	278	15	.	.	PUNCT
cana-5212	279	1	application	application	NOUN
cana-5212	279	2	of	of	ADP
cana-5212	279	3	deep	deep	ADJ
cana-5212	279	4	learning	learning	NOUN
cana-5212	279	5	techniques	technique	NOUN
cana-5212	279	6	for	for	ADP
cana-5212	279	7	plant	plant	NOUN
cana-5212	279	8	disease	disease	NOUN
cana-5212	279	9	identification	identification	NOUN
cana-5212	279	10	.	.	PUNCT
cana-5212	280	1	indian	indian	ADJ
cana-5212	280	2	journal	journal	PROPN
cana-5212	280	3	of	of	ADP
cana-5212	280	4	artificial	artificial	ADJ
cana-5212	280	5	intelligence	intelligence	NOUN
cana-5212	280	6	,	,	PUNCT
cana-5212	280	7	7(4	7(4	NUM
cana-5212	280	8	)	)	PUNCT
cana-5212	280	9	,	,	PUNCT
cana-5212	280	10	210	210	NUM
cana-5212	280	11	-	-	SYM
cana-5212	280	12	225	225	NUM
cana-5212	280	13	.	.	PUNCT
cana-5212	281	1	[	[	X
cana-5212	281	2	6	6	NUM
cana-5212	281	3	]	]	X
cana-5212	281	4	reddy	reddy	PROPN
cana-5212	281	5	,	,	PUNCT
cana-5212	281	6	s.	s.	PROPN
cana-5212	281	7	,	,	PUNCT
cana-5212	281	8	&	&	CCONJ
cana-5212	281	9	rao	rao	PROPN
cana-5212	281	10	,	,	PUNCT
cana-5212	281	11	n.	n.	NOUN
cana-5212	281	12	(	(	PUNCT
cana-5212	281	13	2022	2022	NUM
cana-5212	281	14	)	)	PUNCT
cana-5212	281	15	.	.	PUNCT
cana-5212	282	1	enhanced	enhance	VERB
cana-5212	282	2	plant	plant	NOUN
cana-5212	282	3	disease	disease	NOUN
cana-5212	282	4	detection	detection	NOUN
cana-5212	282	5	using	use	VERB
cana-5212	282	6	hybrid	hybrid	ADJ
cana-5212	282	7	deep	deep	ADJ
cana-5212	282	8	learning	learning	NOUN
cana-5212	282	9	models	model	NOUN
cana-5212	282	10	.	.	PUNCT
cana-5212	283	1	journal	journal	NOUN
cana-5212	283	2	of	of	ADP
cana-5212	283	3	advanced	advanced	ADJ
cana-5212	283	4	agricultural	agricultural	ADJ
cana-5212	283	5	technology	technology	NOUN
cana-5212	283	6	,	,	PUNCT
cana-5212	283	7	12(2	12(2	NUM
cana-5212	283	8	)	)	PUNCT
cana-5212	283	9	,	,	PUNCT
cana-5212	283	10	89	89	NUM
cana-5212	283	11	-	-	SYM
cana-5212	283	12	97	97	NUM
cana-5212	283	13	.	.	PUNCT
cana-5212	284	1	[	[	X
cana-5212	284	2	7	7	NUM
cana-5212	284	3	]	]	SYM
cana-5212	284	4	verma	verma	PROPN
cana-5212	284	5	,	,	PUNCT
cana-5212	284	6	s.	s.	PROPN
cana-5212	284	7	,	,	PUNCT
cana-5212	284	8	&	&	CCONJ
cana-5212	284	9	gupta	gupta	PROPN
cana-5212	284	10	,	,	PUNCT
cana-5212	284	11	r.	r.	PROPN
cana-5212	284	12	(	(	PUNCT
cana-5212	284	13	2023	2023	NUM
cana-5212	284	14	)	)	PUNCT
cana-5212	284	15	.	.	PUNCT
cana-5212	285	1	leveraging	leverage	VERB
cana-5212	285	2	deep	deep	ADJ
cana-5212	285	3	neural	neural	ADJ
cana-5212	285	4	networks	network	NOUN
cana-5212	285	5	for	for	ADP
cana-5212	285	6	multi	multi	ADJ
cana-5212	285	7	-	-	ADJ
cana-5212	285	8	class	class	ADJ
cana-5212	285	9	plant	plant	NOUN
cana-5212	285	10	disease	disease	NOUN
cana-5212	285	11	classification	classification	NOUN
cana-5212	285	12	.	.	PUNCT
cana-5212	286	1	indian	indian	ADJ
cana-5212	286	2	journal	journal	PROPN
cana-5212	286	3	of	of	ADP
cana-5212	286	4	machine	machine	NOUN
cana-5212	286	5	learning	learning	NOUN
cana-5212	286	6	and	and	CCONJ
cana-5212	286	7	applications	application	NOUN
cana-5212	286	8	,	,	PUNCT
cana-5212	286	9	10(1	10(1	NUM
cana-5212	286	10	)	)	PUNCT
cana-5212	286	11	,	,	PUNCT
cana-5212	286	12	56	56	NUM
cana-5212	286	13	-	-	SYM
cana-5212	286	14	68	68	NUM
cana-5212	286	15	.	.	PUNCT
cana-5212	287	1	[	[	X
cana-5212	287	2	8	8	NUM
cana-5212	287	3	]	]	X
cana-5212	287	4	singh	singh	PROPN
cana-5212	287	5	,	,	PUNCT
cana-5212	287	6	a.	a.	PROPN
cana-5212	287	7	,	,	PUNCT
cana-5212	287	8	&	&	CCONJ
cana-5212	287	9	yadav	yadav	PROPN
cana-5212	287	10	,	,	PUNCT
cana-5212	287	11	d.	d.	PROPN
cana-5212	287	12	(	(	PUNCT
cana-5212	287	13	2022	2022	NUM
cana-5212	287	14	)	)	PUNCT
cana-5212	287	15	.	.	PUNCT
cana-5212	288	1	a	a	DET
cana-5212	288	2	comprehensive	comprehensive	ADJ
cana-5212	288	3	review	review	NOUN
cana-5212	288	4	on	on	ADP
cana-5212	288	5	the	the	DET
cana-5212	288	6	use	use	NOUN
cana-5212	288	7	of	of	ADP
cana-5212	288	8	cnn	cnn	PROPN
cana-5212	288	9	for	for	ADP
cana-5212	288	10	plant	plant	NOUN
cana-5212	288	11	disease	disease	NOUN
cana-5212	288	12	detection	detection	NOUN
cana-5212	288	13	.	.	PUNCT
cana-5212	289	1	journal	journal	NOUN
cana-5212	289	2	of	of	ADP
cana-5212	289	3	agricultural	agricultural	ADJ
cana-5212	289	4	research	research	NOUN
cana-5212	289	5	and	and	CCONJ
cana-5212	289	6	development	development	NOUN
cana-5212	289	7	,	,	PUNCT
cana-5212	289	8	15(2	15(2	NUM
cana-5212	289	9	)	)	PUNCT
cana-5212	289	10	,	,	PUNCT
cana-5212	289	11	90	90	NUM
cana-5212	289	12	-	-	SYM
cana-5212	289	13	102	102	NUM
cana-5212	289	14	.	.	PUNCT
cana-5212	290	1	[	[	X
cana-5212	290	2	9	9	NUM
cana-5212	290	3	]	]	PUNCT
cana-5212	290	4	nair	nair	NOUN
cana-5212	290	5	,	,	PUNCT
cana-5212	290	6	m.	m.	NOUN
cana-5212	290	7	,	,	PUNCT
cana-5212	290	8	&	&	CCONJ
cana-5212	290	9	krishnan	krishnan	PROPN
cana-5212	290	10	,	,	PUNCT
cana-5212	290	11	r.	r.	PROPN
cana-5212	290	12	(	(	PUNCT
cana-5212	290	13	2023	2023	NUM
cana-5212	290	14	)	)	PUNCT
cana-5212	290	15	.	.	PUNCT
cana-5212	291	1	real	real	ADJ
cana-5212	291	2	-	-	PUNCT
cana-5212	291	3	time	time	NOUN
cana-5212	291	4	plant	plant	NOUN
cana-5212	291	5	disease	disease	NOUN
cana-5212	291	6	detection	detection	NOUN
cana-5212	291	7	using	use	VERB
cana-5212	291	8	deep	deep	ADJ
cana-5212	291	9	learning	learning	NOUN
cana-5212	291	10	and	and	CCONJ
cana-5212	291	11	iot	iot	PROPN
cana-5212	291	12	.	.	PROPN
cana-5212	291	13	journal	journal	PROPN
cana-5212	291	14	of	of	ADP
cana-5212	291	15	emerging	emerge	VERB
cana-5212	291	16	technologies	technology	NOUN
cana-5212	291	17	in	in	ADP
cana-5212	291	18	agriculture	agriculture	NOUN
cana-5212	291	19	,	,	PUNCT
cana-5212	291	20	8(3	8(3	NUM
cana-5212	291	21	)	)	PUNCT
cana-5212	291	22	,	,	PUNCT
cana-5212	291	23	75	75	NUM
cana-5212	291	24	-	-	SYM
cana-5212	291	25	84	84	NUM
cana-5212	291	26	.	.	PUNCT
cana-5212	292	1	[	[	X
cana-5212	292	2	10	10	NUM
cana-5212	292	3	]	]	X
cana-5212	292	4	bhatt	bhatt	PROPN
cana-5212	292	5	,	,	PUNCT
cana-5212	292	6	k.	k.	PROPN
cana-5212	292	7	,	,	PUNCT
cana-5212	292	8	&	&	CCONJ
cana-5212	292	9	patel	patel	PROPN
cana-5212	292	10	,	,	PUNCT
cana-5212	292	11	a.	a.	NOUN
cana-5212	292	12	(	(	PUNCT
cana-5212	292	13	2022	2022	NUM
cana-5212	292	14	)	)	PUNCT
cana-5212	292	15	.	.	PUNCT
cana-5212	293	1	hybrid	hybrid	NOUN
cana-5212	293	2	models	model	NOUN
cana-5212	293	3	for	for	ADP
cana-5212	293	4	accurate	accurate	ADJ
cana-5212	293	5	detection	detection	NOUN
cana-5212	293	6	and	and	CCONJ
cana-5212	293	7	classification	classification	NOUN
cana-5212	293	8	of	of	ADP
cana-5212	293	9	plant	plant	NOUN
cana-5212	293	10	diseases	disease	NOUN
cana-5212	293	11	.	.	PUNCT
cana-5212	294	1	indian	indian	ADJ
cana-5212	294	2	journal	journal	PROPN
cana-5212	294	3	of	of	ADP
cana-5212	294	4	smart	smart	ADJ
cana-5212	294	5	agriculture	agriculture	NOUN
cana-5212	294	6	,	,	PUNCT
cana-5212	294	7	6(2	6(2	NUM
cana-5212	294	8	)	)	PUNCT
cana-5212	294	9	,	,	PUNCT
cana-5212	294	10	45	45	NUM
cana-5212	294	11	-	-	SYM
cana-5212	294	12	57	57	NUM
cana-5212	294	13	.	.	PUNCT
cana-5212	295	1	[	[	X
cana-5212	295	2	11	11	NUM
cana-5212	295	3	]	]	SYM
cana-5212	295	4	rao	rao	NOUN
cana-5212	295	5	,	,	PUNCT
cana-5212	295	6	p.	p.	PROPN
cana-5212	295	7	,	,	PUNCT
cana-5212	295	8	&	&	CCONJ
cana-5212	295	9	menon	menon	PROPN
cana-5212	295	10	,	,	PUNCT
cana-5212	295	11	s.	s.	PROPN
cana-5212	295	12	(	(	PUNCT
cana-5212	295	13	2022	2022	NUM
cana-5212	295	14	)	)	PUNCT
cana-5212	295	15	.	.	PUNCT
cana-5212	296	1	precision	precision	NOUN
cana-5212	296	2	agriculture	agriculture	NOUN
cana-5212	296	3	using	use	VERB
cana-5212	296	4	deep	deep	ADJ
cana-5212	296	5	learning	learning	NOUN
cana-5212	296	6	:	:	PUNCT
cana-5212	296	7	plant	plant	NOUN
cana-5212	296	8	disease	disease	NOUN
cana-5212	296	9	detection	detection	NOUN
cana-5212	296	10	.	.	PUNCT
cana-5212	297	1	journal	journal	NOUN
cana-5212	297	2	of	of	ADP
cana-5212	297	3	digital	digital	ADJ
cana-5212	297	4	agriculture	agriculture	NOUN
cana-5212	297	5	,	,	PUNCT
cana-5212	297	6	4(4	4(4	NUM
cana-5212	297	7	)	)	PUNCT
cana-5212	297	8	,	,	PUNCT
cana-5212	297	9	130	130	NUM
cana-5212	297	10	-	-	SYM
cana-5212	297	11	142	142	NUM
cana-5212	297	12	.	.	PUNCT
cana-5212	298	1	communications	communication	NOUN
cana-5212	298	2	on	on	ADP
cana-5212	298	3	applied	apply	VERB
cana-5212	298	4	nonlinear	nonlinear	ADJ
cana-5212	298	5	analysis	analysis	NOUN
cana-5212	298	6	issn	issn	NOUN
cana-5212	298	7	:	:	PUNCT
cana-5212	298	8	1074	1074	NUM
cana-5212	298	9	-	-	PUNCT
cana-5212	298	10	133x	133x	NUM
cana-5212	298	11	vol	vol	NOUN
cana-5212	298	12	32	32	NUM
cana-5212	298	13	no	no	NOUN
cana-5212	298	14	.	.	PUNCT
cana-5212	299	1	8s	8s	PROPN
cana-5212	299	2	(	(	PUNCT
cana-5212	299	3	2025	2025	NUM
cana-5212	299	4	)	)	PUNCT
cana-5212	299	5	950	950	NUM
cana-5212	299	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5212	300	1	[	[	X
cana-5212	300	2	12	12	NUM
cana-5212	300	3	]	]	PUNCT
cana-5212	300	4	sharma	sharma	PROPN
cana-5212	300	5	,	,	PUNCT
cana-5212	300	6	n.	n.	NOUN
cana-5212	300	7	,	,	PUNCT
cana-5212	300	8	&	&	CCONJ
cana-5212	300	9	jain	jain	PROPN
cana-5212	300	10	,	,	PUNCT
cana-5212	300	11	a.	a.	NOUN
cana-5212	300	12	(	(	PUNCT
cana-5212	300	13	2023	2023	NUM
cana-5212	300	14	)	)	PUNCT
cana-5212	300	15	.	.	PUNCT
cana-5212	301	1	data	datum	NOUN
cana-5212	301	2	augmentation	augmentation	NOUN
cana-5212	301	3	techniques	technique	NOUN
cana-5212	301	4	for	for	ADP
cana-5212	301	5	improving	improve	VERB
cana-5212	301	6	plant	plant	NOUN
cana-5212	301	7	disease	disease	NOUN
cana-5212	301	8	detection	detection	NOUN
cana-5212	301	9	models	model	NOUN
cana-5212	301	10	.	.	PUNCT
cana-5212	302	1	journal	journal	NOUN
cana-5212	302	2	of	of	ADP
cana-5212	302	3	artificial	artificial	ADJ
cana-5212	302	4	intelligence	intelligence	NOUN
cana-5212	302	5	research	research	NOUN
cana-5212	302	6	in	in	ADP
cana-5212	302	7	agriculture	agriculture	NOUN
cana-5212	302	8	,	,	PUNCT
cana-5212	302	9	9(1	9(1	NUM
cana-5212	302	10	)	)	PUNCT
cana-5212	302	11	,	,	PUNCT
cana-5212	302	12	33	33	NUM
cana-5212	302	13	-	-	SYM
cana-5212	302	14	46	46	NUM
cana-5212	302	15	.	.	PUNCT
cana-5212	303	1	[	[	X
cana-5212	303	2	13	13	NUM
cana-5212	303	3	]	]	SYM
cana-5212	303	4	tripathi	tripathi	PROPN
cana-5212	303	5	,	,	PUNCT
cana-5212	303	6	r.	r.	PROPN
cana-5212	303	7	,	,	PUNCT
cana-5212	303	8	&	&	CCONJ
cana-5212	303	9	das	das	PROPN
cana-5212	303	10	,	,	PUNCT
cana-5212	303	11	s.	s.	PROPN
cana-5212	303	12	(	(	PUNCT
cana-5212	303	13	2023	2023	NUM
cana-5212	303	14	)	)	PUNCT
cana-5212	303	15	.	.	PUNCT
cana-5212	304	1	utilizing	utilize	VERB
cana-5212	304	2	deep	deep	ADJ
cana-5212	304	3	learning	learning	NOUN
cana-5212	304	4	for	for	ADP
cana-5212	304	5	robust	robust	ADJ
cana-5212	304	6	plant	plant	NOUN
cana-5212	304	7	disease	disease	NOUN
cana-5212	304	8	identification	identification	NOUN
cana-5212	304	9	.	.	PUNCT
cana-5212	305	1	journal	journal	NOUN
cana-5212	305	2	of	of	ADP
cana-5212	305	3	agricultural	agricultural	ADJ
cana-5212	305	4	informatics	informatic	NOUN
cana-5212	305	5	,	,	PUNCT
cana-5212	305	6	7(2	7(2	NUM
cana-5212	305	7	)	)	PUNCT
cana-5212	305	8	,	,	PUNCT
cana-5212	305	9	66	66	NUM
cana-5212	305	10	-	-	SYM
cana-5212	305	11	77	77	NUM
cana-5212	305	12	.	.	PUNCT
cana-5212	306	1	[	[	X
cana-5212	306	2	14	14	NUM
cana-5212	306	3	]	]	X
cana-5212	306	4	kumar	kumar	PROPN
cana-5212	306	5	,	,	PUNCT
cana-5212	306	6	m.	m.	NOUN
cana-5212	306	7	,	,	PUNCT
cana-5212	306	8	&	&	CCONJ
cana-5212	306	9	singh	singh	PROPN
cana-5212	306	10	,	,	PUNCT
cana-5212	306	11	s.	s.	PROPN
cana-5212	306	12	(	(	PUNCT
cana-5212	306	13	2022	2022	NUM
cana-5212	306	14	)	)	PUNCT
cana-5212	306	15	.	.	PUNCT
cana-5212	307	1	advances	advance	NOUN
cana-5212	307	2	in	in	ADP
cana-5212	307	3	deep	deep	ADJ
cana-5212	307	4	learning	learning	NOUN
cana-5212	307	5	applications	application	NOUN
cana-5212	307	6	for	for	ADP
cana-5212	307	7	plant	plant	NOUN
cana-5212	307	8	pathology	pathology	NOUN
cana-5212	307	9	.	.	PUNCT
cana-5212	308	1	indian	indian	PROPN
cana-5212	308	2	journal	journal	PROPN
cana-5212	308	3	of	of	ADP
cana-5212	308	4	computational	computational	ADJ
cana-5212	308	5	agriculture	agriculture	NOUN
cana-5212	308	6	,	,	PUNCT
cana-5212	308	7	11(4	11(4	NUM
cana-5212	308	8	)	)	PUNCT
cana-5212	308	9	,	,	PUNCT
cana-5212	308	10	121	121	NUM
cana-5212	308	11	-	-	SYM
cana-5212	308	12	134	134	NUM
cana-5212	308	13	.	.	PUNCT
cana-5212	309	1	[	[	X
cana-5212	309	2	15	15	NUM
cana-5212	309	3	]	]	X
cana-5212	309	4	narayan	narayan	NOUN
cana-5212	309	5	,	,	PUNCT
cana-5212	309	6	s.	s.	PROPN
cana-5212	309	7	,	,	PUNCT
cana-5212	309	8	&	&	CCONJ
cana-5212	309	9	gupta	gupta	PROPN
cana-5212	309	10	,	,	PUNCT
cana-5212	309	11	p.	p.	NOUN
cana-5212	309	12	(	(	PUNCT
cana-5212	309	13	2023	2023	NUM
cana-5212	309	14	)	)	PUNCT
cana-5212	309	15	.	.	PUNCT
cana-5212	310	1	performance	performance	NOUN
cana-5212	310	2	comparison	comparison	NOUN
cana-5212	310	3	of	of	ADP
cana-5212	310	4	deep	deep	ADJ
cana-5212	310	5	learning	learning	NOUN
cana-5212	310	6	algorithms	algorithm	NOUN
cana-5212	310	7	for	for	ADP
cana-5212	310	8	plant	plant	NOUN
cana-5212	310	9	disease	disease	NOUN
cana-5212	310	10	detection	detection	NOUN
cana-5212	310	11	.	.	PUNCT
cana-5212	311	1	indian	indian	ADJ
cana-5212	311	2	journal	journal	PROPN
cana-5212	311	3	of	of	ADP
cana-5212	311	4	digital	digital	ADJ
cana-5212	311	5	farming	farming	NOUN
cana-5212	311	6	,	,	PUNCT
cana-5212	311	7	5(1	5(1	NUM
cana-5212	311	8	)	)	PUNCT
cana-5212	311	9	,	,	PUNCT
cana-5212	311	10	88	88	NUM
cana-5212	311	11	-	-	SYM
cana-5212	311	12	99	99	NUM
cana-5212	311	13	.	.	PUNCT
cana-5212	312	1	[	[	X
cana-5212	312	2	16	16	NUM
cana-5212	312	3	]	]	X
cana-5212	312	4	rao	rao	PROPN
cana-5212	312	5	,	,	PUNCT
cana-5212	312	6	k.	k.	PROPN
cana-5212	312	7	,	,	PUNCT
cana-5212	312	8	&	&	CCONJ
cana-5212	312	9	reddy	reddy	PROPN
cana-5212	312	10	,	,	PUNCT
cana-5212	312	11	v.	v.	PROPN
cana-5212	312	12	(	(	PUNCT
cana-5212	312	13	2022	2022	NUM
cana-5212	312	14	)	)	PUNCT
cana-5212	312	15	.	.	PUNCT
cana-5212	313	1	cnn	cnn	PROPN
cana-5212	313	2	-	-	PUNCT
cana-5212	313	3	based	base	VERB
cana-5212	313	4	approach	approach	NOUN
cana-5212	313	5	for	for	ADP
cana-5212	313	6	detecting	detect	VERB
cana-5212	313	7	and	and	CCONJ
cana-5212	313	8	classifying	classify	VERB
cana-5212	313	9	plant	plant	NOUN
cana-5212	313	10	diseases	disease	NOUN
cana-5212	313	11	.	.	PUNCT
cana-5212	314	1	journal	journal	NOUN
cana-5212	314	2	of	of	ADP
cana-5212	314	3	advanced	advanced	ADJ
cana-5212	314	4	computing	computing	NOUN
cana-5212	314	5	in	in	ADP
cana-5212	314	6	agriculture	agriculture	NOUN
cana-5212	314	7	,	,	PUNCT
cana-5212	314	8	10(3	10(3	NUM
cana-5212	314	9	)	)	PUNCT
cana-5212	314	10	,	,	PUNCT
cana-5212	314	11	210	210	NUM
cana-5212	314	12	-	-	SYM
cana-5212	314	13	220	220	NUM
cana-5212	314	14	.	.	PUNCT
cana-5212	315	1	[	[	X
cana-5212	315	2	17	17	NUM
cana-5212	315	3	]	]	X
cana-5212	315	4	patel	patel	PROPN
cana-5212	315	5	,	,	PUNCT
cana-5212	315	6	v.	v.	PROPN
cana-5212	315	7	,	,	PUNCT
cana-5212	315	8	&	&	CCONJ
cana-5212	315	9	singh	singh	PROPN
cana-5212	315	10	,	,	PUNCT
cana-5212	315	11	r.	r.	PROPN
cana-5212	315	12	(	(	PUNCT
cana-5212	315	13	2022	2022	NUM
cana-5212	315	14	)	)	PUNCT
cana-5212	315	15	.	.	PUNCT
cana-5212	316	1	improving	improve	VERB
cana-5212	316	2	plant	plant	NOUN
cana-5212	316	3	disease	disease	NOUN
cana-5212	316	4	detection	detection	NOUN
cana-5212	316	5	accuracy	accuracy	NOUN
cana-5212	316	6	using	use	VERB
cana-5212	316	7	deep	deep	ADJ
cana-5212	316	8	learning	learning	NOUN
cana-5212	316	9	techniques	technique	NOUN
cana-5212	316	10	.	.	PUNCT
cana-5212	317	1	journal	journal	NOUN
cana-5212	317	2	of	of	ADP
cana-5212	317	3	smart	smart	ADJ
cana-5212	317	4	agriculture	agriculture	NOUN
cana-5212	317	5	and	and	CCONJ
cana-5212	317	6	sustainable	sustainable	ADJ
cana-5212	317	7	development	development	NOUN
cana-5212	317	8	,	,	PUNCT
cana-5212	317	9	8(2	8(2	NUM
cana-5212	317	10	)	)	PUNCT
cana-5212	317	11	,	,	PUNCT
cana-5212	317	12	55	55	NUM
cana-5212	317	13	-	-	SYM
cana-5212	317	14	66	66	NUM
cana-5212	317	15	.	.	PUNCT
cana-5212	318	1	[	[	X
cana-5212	318	2	18	18	NUM
cana-5212	318	3	]	]	X
cana-5212	318	4	kaur	kaur	PROPN
cana-5212	318	5	,	,	PUNCT
cana-5212	318	6	s.	s.	PROPN
cana-5212	318	7	,	,	PUNCT
cana-5212	318	8	&	&	CCONJ
cana-5212	318	9	dhillon	dhillon	PROPN
cana-5212	318	10	,	,	PUNCT
cana-5212	318	11	a.	a.	NOUN
cana-5212	318	12	(	(	PUNCT
cana-5212	318	13	2023	2023	NUM
cana-5212	318	14	)	)	PUNCT
cana-5212	318	15	.	.	PUNCT
cana-5212	319	1	machine	machine	NOUN
cana-5212	319	2	learning	learn	VERB
cana-5212	319	3	applications	application	NOUN
cana-5212	319	4	in	in	ADP
cana-5212	319	5	plant	plant	NOUN
cana-5212	319	6	disease	disease	NOUN
cana-5212	319	7	management	management	NOUN
cana-5212	319	8	:	:	PUNCT
cana-5212	319	9	a	a	DET
cana-5212	319	10	review	review	NOUN
cana-5212	319	11	.	.	PUNCT
cana-5212	320	1	indian	indian	PROPN
cana-5212	320	2	journal	journal	PROPN
cana-5212	320	3	of	of	ADP
cana-5212	320	4	agronomy	agronomy	NOUN
cana-5212	320	5	and	and	CCONJ
cana-5212	320	6	plant	plant	NOUN
cana-5212	320	7	science	science	NOUN
cana-5212	320	8	,	,	PUNCT
cana-5212	320	9	12(1	12(1	NUM
cana-5212	320	10	)	)	PUNCT
cana-5212	320	11	,	,	PUNCT
cana-5212	320	12	45	45	NUM
cana-5212	320	13	-	-	SYM
cana-5212	320	14	58	58	NUM
cana-5212	320	15	.	.	PUNCT
cana-5212	321	1	[	[	X
cana-5212	321	2	19	19	NUM
cana-5212	321	3	]	]	X
cana-5212	321	4	sharma	sharma	PROPN
cana-5212	321	5	,	,	PUNCT
cana-5212	321	6	a.	a.	PROPN
cana-5212	321	7	,	,	PUNCT
cana-5212	321	8	&	&	CCONJ
cana-5212	321	9	choudhary	choudhary	PROPN
cana-5212	321	10	,	,	PUNCT
cana-5212	321	11	s.	s.	PROPN
cana-5212	321	12	(	(	PUNCT
cana-5212	321	13	2023	2023	NUM
cana-5212	321	14	)	)	PUNCT
cana-5212	321	15	.	.	PUNCT
cana-5212	322	1	automated	automate	VERB
cana-5212	322	2	plant	plant	NOUN
cana-5212	322	3	disease	disease	NOUN
cana-5212	322	4	detection	detection	NOUN
cana-5212	322	5	using	use	VERB
cana-5212	322	6	cnn	cnn	PROPN
cana-5212	322	7	and	and	CCONJ
cana-5212	322	8	fuzzy	fuzzy	ADJ
cana-5212	322	9	logic	logic	NOUN
cana-5212	322	10	.	.	PUNCT
cana-5212	323	1	journal	journal	NOUN
cana-5212	323	2	of	of	ADP
cana-5212	323	3	computational	computational	ADJ
cana-5212	323	4	agriculture	agriculture	NOUN
cana-5212	323	5	and	and	CCONJ
cana-5212	323	6	plant	plant	NOUN
cana-5212	323	7	pathology	pathology	NOUN
cana-5212	323	8	,	,	PUNCT
cana-5212	323	9	13(1	13(1	NUM
cana-5212	323	10	)	)	PUNCT
cana-5212	323	11	,	,	PUNCT
cana-5212	323	12	101	101	NUM
cana-5212	323	13	-	-	SYM
cana-5212	323	14	112	112	NUM
cana-5212	323	15	.	.	PUNCT
cana-5212	324	1	[	[	X
cana-5212	324	2	20	20	NUM
cana-5212	324	3	]	]	X
cana-5212	324	4	rani	rani	NOUN
cana-5212	324	5	,	,	PUNCT
cana-5212	324	6	p.	p.	PROPN
cana-5212	324	7	,	,	PUNCT
cana-5212	324	8	&	&	CCONJ
cana-5212	324	9	kumar	kumar	PROPN
cana-5212	324	10	,	,	PUNCT
cana-5212	324	11	a.	a.	NOUN
cana-5212	324	12	(	(	PUNCT
cana-5212	324	13	2022	2022	NUM
cana-5212	324	14	)	)	PUNCT
cana-5212	324	15	.	.	PUNCT
cana-5212	325	1	deep	deep	ADJ
cana-5212	325	2	learning	learn	VERB
cana-5212	325	3	frameworks	framework	NOUN
cana-5212	325	4	for	for	ADP
cana-5212	325	5	real	real	ADJ
cana-5212	325	6	-	-	PUNCT
cana-5212	325	7	time	time	NOUN
cana-5212	325	8	plant	plant	NOUN
cana-5212	325	9	disease	disease	NOUN
cana-5212	325	10	detection	detection	NOUN
cana-5212	325	11	.	.	PUNCT
cana-5212	326	1	journal	journal	NOUN
cana-5212	326	2	of	of	ADP
cana-5212	326	3	agricultural	agricultural	ADJ
cana-5212	326	4	computing	computing	NOUN
cana-5212	326	5	and	and	CCONJ
cana-5212	326	6	information	information	NOUN
cana-5212	326	7	systems	system	NOUN
cana-5212	326	8	,	,	PUNCT
cana-5212	326	9	9(4	9(4	NUM
cana-5212	326	10	)	)	PUNCT
cana-5212	326	11	,	,	PUNCT
cana-5212	326	12	75	75	NUM
cana-5212	326	13	-	-	SYM
cana-5212	326	14	88	88	NUM
cana-5212	326	15	.	.	PUNCT
cana-5212	327	1	[	[	X
cana-5212	327	2	21	21	NUM
cana-5212	327	3	]	]	X
cana-5212	327	4	singh	singh	PROPN
cana-5212	327	5	,	,	PUNCT
cana-5212	327	6	v.	v.	PROPN
cana-5212	327	7	,	,	PUNCT
cana-5212	327	8	&	&	CCONJ
cana-5212	327	9	yadav	yadav	PROPN
cana-5212	327	10	,	,	PUNCT
cana-5212	327	11	p.	p.	NOUN
cana-5212	327	12	(	(	PUNCT
cana-5212	327	13	2022	2022	NUM
cana-5212	327	14	)	)	PUNCT
cana-5212	327	15	.	.	PUNCT
cana-5212	328	1	comparative	comparative	ADJ
cana-5212	328	2	analysis	analysis	NOUN
cana-5212	328	3	of	of	ADP
cana-5212	328	4	cnn	cnn	PROPN
cana-5212	328	5	and	and	CCONJ
cana-5212	328	6	traditional	traditional	ADJ
cana-5212	328	7	methods	method	NOUN
cana-5212	328	8	for	for	ADP
cana-5212	328	9	plant	plant	NOUN
cana-5212	328	10	disease	disease	NOUN
cana-5212	328	11	identification	identification	NOUN
cana-5212	328	12	.	.	PUNCT
cana-5212	329	1	journal	journal	NOUN
cana-5212	329	2	of	of	ADP
cana-5212	329	3	applied	apply	VERB
cana-5212	329	4	agricultural	agricultural	ADJ
cana-5212	329	5	technologies	technology	NOUN
cana-5212	329	6	,	,	PUNCT
cana-5212	329	7	7(3	7(3	NUM
cana-5212	329	8	)	)	PUNCT
cana-5212	329	9	,	,	PUNCT
cana-5212	329	10	89	89	NUM
cana-5212	329	11	-	-	SYM
cana-5212	329	12	101	101	NUM
cana-5212	329	13	.	.	PUNCT
cana-5212	330	1	[	[	X
cana-5212	330	2	22	22	NUM
cana-5212	330	3	]	]	X
cana-5212	330	4	gupta	gupta	PROPN
cana-5212	330	5	,	,	PUNCT
cana-5212	330	6	s.	s.	PROPN
cana-5212	330	7	,	,	PUNCT
cana-5212	330	8	&	&	CCONJ
cana-5212	330	9	rao	rao	PROPN
cana-5212	330	10	,	,	PUNCT
cana-5212	330	11	d.	d.	PROPN
cana-5212	330	12	(	(	PUNCT
cana-5212	330	13	2023	2023	NUM
cana-5212	330	14	)	)	PUNCT
cana-5212	330	15	.	.	PUNCT
cana-5212	331	1	innovative	innovative	ADJ
cana-5212	331	2	approaches	approach	NOUN
cana-5212	331	3	in	in	ADP
cana-5212	331	4	plant	plant	NOUN
cana-5212	331	5	disease	disease	NOUN
cana-5212	331	6	detection	detection	NOUN
cana-5212	331	7	using	use	VERB
cana-5212	331	8	deep	deep	ADJ
cana-5212	331	9	learning	learning	NOUN
cana-5212	331	10	.	.	PUNCT
cana-5212	332	1	journal	journal	NOUN
cana-5212	332	2	of	of	ADP
cana-5212	332	3	sustainable	sustainable	ADJ
cana-5212	332	4	agricultural	agricultural	ADJ
cana-5212	332	5	innovations	innovation	NOUN
cana-5212	332	6	,	,	PUNCT
cana-5212	332	7	6(1	6(1	NUM
cana-5212	332	8	)	)	PUNCT
cana-5212	332	9	,	,	PUNCT
cana-5212	332	10	34	34	NUM
cana-5212	332	11	-	-	SYM
cana-5212	332	12	47	47	NUM
cana-5212	332	13	.	.	PUNCT
cana-5212	333	1	[	[	X
cana-5212	333	2	23	23	NUM
cana-5212	333	3	]	]	X
cana-5212	333	4	mehta	mehta	PROPN
cana-5212	333	5	,	,	PUNCT
cana-5212	333	6	p.	p.	PROPN
cana-5212	333	7	,	,	PUNCT
cana-5212	333	8	&	&	CCONJ
cana-5212	333	9	patel	patel	PROPN
cana-5212	333	10	,	,	PUNCT
cana-5212	333	11	s.	s.	PROPN
cana-5212	333	12	(	(	PUNCT
cana-5212	333	13	2023	2023	NUM
cana-5212	333	14	)	)	PUNCT
cana-5212	333	15	.	.	PUNCT
cana-5212	334	1	hybrid	hybrid	ADJ
cana-5212	334	2	deep	deep	ADJ
cana-5212	334	3	learning	learning	NOUN
cana-5212	334	4	models	model	NOUN
cana-5212	334	5	for	for	ADP
cana-5212	334	6	enhanced	enhanced	ADJ
cana-5212	334	7	plant	plant	NOUN
cana-5212	334	8	disease	disease	NOUN
cana-5212	334	9	classification	classification	NOUN
cana-5212	334	10	.	.	PUNCT
cana-5212	335	1	indian	indian	ADJ
cana-5212	335	2	journal	journal	PROPN
cana-5212	335	3	of	of	ADP
cana-5212	335	4	advanced	advanced	ADJ
cana-5212	335	5	computing	computing	NOUN
cana-5212	335	6	in	in	ADP
cana-5212	335	7	agriculture	agriculture	NOUN
cana-5212	335	8	,	,	PUNCT
cana-5212	335	9	9(2	9(2	NUM
cana-5212	335	10	)	)	PUNCT
cana-5212	335	11	,	,	PUNCT
cana-5212	335	12	58	58	NUM
cana-5212	335	13	-	-	SYM
cana-5212	335	14	71	71	NUM
cana-5212	335	15	.	.	PUNCT
cana-5212	336	1	[	[	X
cana-5212	336	2	24	24	NUM
cana-5212	336	3	]	]	SYM
cana-5212	336	4	prasad	prasad	PROPN
cana-5212	336	5	,	,	PUNCT
cana-5212	336	6	r.	r.	PROPN
cana-5212	336	7	,	,	PUNCT
cana-5212	336	8	&	&	CCONJ
cana-5212	336	9	kumar	kumar	PROPN
cana-5212	336	10	,	,	PUNCT
cana-5212	336	11	n.	n.	PROPN
cana-5212	336	12	(	(	PUNCT
cana-5212	336	13	2022	2022	NUM
cana-5212	336	14	)	)	PUNCT
cana-5212	336	15	.	.	PUNCT
cana-5212	337	1	leveraging	leverage	VERB
cana-5212	337	2	iot	iot	NOUN
cana-5212	337	3	and	and	CCONJ
cana-5212	337	4	deep	deep	ADJ
cana-5212	337	5	learning	learning	NOUN
cana-5212	337	6	for	for	ADP
cana-5212	337	7	plant	plant	NOUN
cana-5212	337	8	disease	disease	NOUN
cana-5212	337	9	detection	detection	NOUN
cana-5212	337	10	.	.	PUNCT
cana-5212	338	1	journal	journal	NOUN
cana-5212	338	2	of	of	ADP
cana-5212	338	3	internet	internet	NOUN
cana-5212	338	4	of	of	ADP
cana-5212	338	5	things	thing	NOUN
cana-5212	338	6	in	in	ADP
cana-5212	338	7	agriculture	agriculture	NOUN
cana-5212	338	8	,	,	PUNCT
cana-5212	338	9	4(2	4(2	NUM
cana-5212	338	10	)	)	PUNCT
cana-5212	338	11	,	,	PUNCT
cana-5212	338	12	103	103	NUM
cana-5212	338	13	-	-	SYM
cana-5212	338	14	115	115	NUM
cana-5212	338	15	.	.	PUNCT
cana-5212	339	1	[	[	X
cana-5212	339	2	25	25	NUM
cana-5212	339	3	]	]	X
cana-5212	339	4	bansal	bansal	NOUN
cana-5212	339	5	,	,	PUNCT
cana-5212	339	6	r.	r.	PROPN
cana-5212	339	7	,	,	PUNCT
cana-5212	339	8	&	&	CCONJ
cana-5212	339	9	singh	singh	PROPN
cana-5212	339	10	,	,	PUNCT
cana-5212	339	11	m.	m.	NOUN
cana-5212	339	12	(	(	PUNCT
cana-5212	339	13	2023	2023	NUM
cana-5212	339	14	)	)	PUNCT
cana-5212	339	15	.	.	PUNCT
cana-5212	340	1	transfer	transfer	NOUN
cana-5212	340	2	learning	learn	VERB
cana-5212	340	3	techniques	technique	NOUN
cana-5212	340	4	for	for	ADP
cana-5212	340	5	improved	improved	ADJ
cana-5212	340	6	plant	plant	NOUN
cana-5212	340	7	disease	disease	NOUN
cana-5212	340	8	recognition	recognition	NOUN
cana-5212	340	9	.	.	PUNCT
cana-5212	341	1	journal	journal	PROPN
cana-5212	341	2	of	of	ADP
cana-5212	341	3	artificial	artificial	ADJ
cana-5212	341	4	intelligence	intelligence	NOUN
cana-5212	341	5	and	and	CCONJ
cana-5212	341	6	agriculture	agriculture	NOUN
cana-5212	341	7	,	,	PUNCT
cana-5212	341	8	11(3	11(3	NUM
cana-5212	341	9	)	)	PUNCT
cana-5212	341	10	,	,	PUNCT
cana-5212	341	11	67	67	NUM
cana-5212	341	12	-	-	SYM
cana-5212	341	13	79	79	NUM
cana-5212	341	14	.	.	PUNCT
cana-5212	342	1	[	[	X
cana-5212	342	2	26	26	NUM
cana-5212	342	3	]	]	X
cana-5212	342	4	bhattacharya	bhattacharya	PROPN
cana-5212	342	5	,	,	PUNCT
cana-5212	342	6	a.	a.	PROPN
cana-5212	342	7	,	,	PUNCT
cana-5212	342	8	&	&	CCONJ
cana-5212	342	9	roy	roy	PROPN
cana-5212	342	10	,	,	PUNCT
cana-5212	342	11	s.	s.	PROPN
cana-5212	342	12	(	(	PUNCT
cana-5212	342	13	2023	2023	NUM
cana-5212	342	14	)	)	PUNCT
cana-5212	342	15	.	.	PUNCT
cana-5212	343	1	deep	deep	ADJ
cana-5212	343	2	learning	learning	NOUN
cana-5212	343	3	and	and	CCONJ
cana-5212	343	4	edge	edge	VERB
cana-5212	343	5	computing	computing	NOUN
cana-5212	343	6	for	for	ADP
cana-5212	343	7	real	real	ADJ
cana-5212	343	8	-	-	PUNCT
cana-5212	343	9	time	time	NOUN
cana-5212	343	10	plant	plant	NOUN
cana-5212	343	11	disease	disease	NOUN
cana-5212	343	12	management	management	NOUN
cana-5212	343	13	.	.	PUNCT
cana-5212	344	1	journal	journal	NOUN
cana-5212	344	2	of	of	ADP
cana-5212	344	3	smart	smart	ADJ
cana-5212	344	4	agricultural	agricultural	ADJ
cana-5212	344	5	systems	system	NOUN
cana-5212	344	6	,	,	PUNCT
cana-5212	344	7	5(2	5(2	NUM
cana-5212	344	8	)	)	PUNCT
cana-5212	344	9	,	,	PUNCT
cana-5212	344	10	102	102	NUM
cana-5212	344	11	-	-	SYM
cana-5212	344	12	115	115	NUM
cana-5212	344	13	.	.	PUNCT
cana-5212	345	1	[	[	X
cana-5212	345	2	27	27	NUM
cana-5212	345	3	]	]	X
cana-5212	345	4	patel	patel	PROPN
cana-5212	345	5	,	,	PUNCT
cana-5212	345	6	r.	r.	PROPN
cana-5212	345	7	,	,	PUNCT
cana-5212	345	8	&	&	CCONJ
cana-5212	345	9	mishra	mishra	PROPN
cana-5212	345	10	,	,	PUNCT
cana-5212	345	11	v.	v.	PROPN
cana-5212	345	12	(	(	PUNCT
cana-5212	345	13	2022	2022	NUM
cana-5212	345	14	)	)	PUNCT
cana-5212	345	15	.	.	PUNCT
cana-5212	346	1	advances	advance	NOUN
cana-5212	346	2	in	in	ADP
cana-5212	346	3	convolutional	convolutional	ADJ
cana-5212	346	4	neural	neural	ADJ
cana-5212	346	5	networks	network	NOUN
cana-5212	346	6	for	for	ADP
cana-5212	346	7	plant	plant	NOUN
cana-5212	346	8	pathology	pathology	NOUN
cana-5212	346	9	.	.	PUNCT
cana-5212	347	1	indian	indian	PROPN
cana-5212	347	2	journal	journal	PROPN
cana-5212	347	3	of	of	ADP
cana-5212	347	4	computational	computational	ADJ
cana-5212	347	5	intelligence	intelligence	NOUN
cana-5212	347	6	in	in	ADP
cana-5212	347	7	agriculture	agriculture	NOUN
cana-5212	347	8	,	,	PUNCT
cana-5212	347	9	8(1	8(1	NOUN
cana-5212	347	10	)	)	PUNCT
cana-5212	347	11	,	,	PUNCT
cana-5212	347	12	55	55	NUM
cana-5212	347	13	-	-	SYM
cana-5212	347	14	67	67	NUM
cana-5212	347	15	.	.	PUNCT
cana-5212	348	1	[	[	X
cana-5212	348	2	28	28	NUM
cana-5212	348	3	]	]	X
cana-5212	348	4	rao	rao	PROPN
cana-5212	348	5	,	,	PUNCT
cana-5212	348	6	a.	a.	PROPN
cana-5212	348	7	,	,	PUNCT
cana-5212	348	8	&	&	CCONJ
cana-5212	348	9	kaur	kaur	PROPN
cana-5212	348	10	,	,	PUNCT
cana-5212	348	11	p.	p.	NOUN
cana-5212	348	12	(	(	PUNCT
cana-5212	348	13	2023	2023	NUM
cana-5212	348	14	)	)	PUNCT
cana-5212	348	15	.	.	PUNCT
cana-5212	349	1	multi	multi	ADJ
cana-5212	349	2	-	-	ADJ
cana-5212	349	3	class	class	ADJ
cana-5212	349	4	classification	classification	NOUN
cana-5212	349	5	of	of	ADP
cana-5212	349	6	plant	plant	NOUN
cana-5212	349	7	diseases	disease	NOUN
cana-5212	349	8	using	use	VERB
cana-5212	349	9	deep	deep	ADJ
cana-5212	349	10	learning	learning	NOUN
cana-5212	349	11	.	.	PUNCT
cana-5212	350	1	journal	journal	PROPN
cana-5212	350	2	of	of	ADP
cana-5212	350	3	computational	computational	ADJ
cana-5212	350	4	methods	method	NOUN
cana-5212	350	5	in	in	ADP
cana-5212	350	6	agriculture	agriculture	NOUN
cana-5212	350	7	,	,	PUNCT
cana-5212	350	8	6(3	6(3	NUM
cana-5212	350	9	)	)	PUNCT
cana-5212	350	10	,	,	PUNCT
cana-5212	350	11	78	78	NUM
cana-5212	350	12	-	-	SYM
cana-5212	350	13	89	89	NUM
cana-5212	350	14	.	.	PUNCT
cana-5212	351	1	[	[	X
cana-5212	351	2	29	29	NUM
cana-5212	351	3	]	]	PUNCT
cana-5212	351	4	sharma	sharma	NOUN
cana-5212	351	5	,	,	PUNCT
cana-5212	351	6	v.	v.	PROPN
cana-5212	351	7	,	,	PUNCT
cana-5212	351	8	&	&	CCONJ
cana-5212	351	9	kumar	kumar	PROPN
cana-5212	351	10	,	,	PUNCT
cana-5212	351	11	r.	r.	PROPN
cana-5212	351	12	(	(	PUNCT
cana-5212	351	13	2022	2022	NUM
cana-5212	351	14	)	)	PUNCT
cana-5212	351	15	.	.	PUNCT
cana-5212	352	1	an	an	DET
cana-5212	352	2	overview	overview	NOUN
cana-5212	352	3	of	of	ADP
cana-5212	352	4	deep	deep	ADJ
cana-5212	352	5	learning	learning	NOUN
cana-5212	352	6	applications	application	NOUN
cana-5212	352	7	in	in	ADP
cana-5212	352	8	plant	plant	NOUN
cana-5212	352	9	disease	disease	NOUN
cana-5212	352	10	detection	detection	NOUN
cana-5212	352	11	.	.	PUNCT
cana-5212	353	1	journal	journal	NOUN
cana-5212	353	2	of	of	ADP
cana-5212	353	3	agricultural	agricultural	ADJ
cana-5212	353	4	research	research	NOUN
cana-5212	353	5	and	and	CCONJ
cana-5212	353	6	computing	computing	NOUN
cana-5212	353	7	,	,	PUNCT
cana-5212	353	8	14(2	14(2	NUM
cana-5212	353	9	)	)	PUNCT
cana-5212	353	10	,	,	PUNCT
cana-5212	353	11	112	112	NUM
cana-5212	353	12	-	-	SYM
cana-5212	353	13	124	124	NUM
cana-5212	353	14	.	.	PUNCT
cana-5212	354	1	[	[	X
cana-5212	354	2	30	30	NUM
cana-5212	354	3	]	]	X
cana-5212	354	4	yadav	yadav	PROPN
cana-5212	354	5	,	,	PUNCT
cana-5212	354	6	n.	n.	NOUN
cana-5212	354	7	,	,	PUNCT
cana-5212	354	8	&	&	CCONJ
cana-5212	354	9	singh	singh	PROPN
cana-5212	354	10	,	,	PUNCT
cana-5212	354	11	k.	k.	PROPN
cana-5212	354	12	(	(	PUNCT
cana-5212	354	13	2023	2023	NUM
cana-5212	354	14	)	)	PUNCT
cana-5212	354	15	.	.	PUNCT
cana-5212	355	1	enhancing	enhance	VERB
cana-5212	355	2	plant	plant	NOUN
cana-5212	355	3	disease	disease	NOUN
cana-5212	355	4	detection	detection	NOUN
cana-5212	355	5	accuracy	accuracy	NOUN
cana-5212	355	6	with	with	ADP
cana-5212	355	7	hybrid	hybrid	ADJ
cana-5212	355	8	deep	deep	ADJ
cana-5212	355	9	learning	learning	NOUN
cana-5212	355	10	models	model	NOUN
cana-5212	355	11	.	.	PUNCT
cana-5212	356	1	journal	journal	NOUN
cana-5212	356	2	of	of	ADP
cana-5212	356	3	agricultural	agricultural	ADJ
cana-5212	356	4	technologies	technology	NOUN
cana-5212	356	5	and	and	CCONJ
cana-5212	356	6	innovations	innovation	NOUN
cana-5212	356	7	,	,	PUNCT
cana-5212	356	8	10(1	10(1	NUM
cana-5212	356	9	)	)	PUNCT
cana-5212	356	10	,	,	PUNCT
cana-5212	356	11	45	45	NUM
cana-5212	356	12	-	-	SYM
cana-5212	356	13	59	59	NUM
cana-5212	356	14	.	.	PUNCT
cana-5212	357	1	[	[	X
cana-5212	357	2	31	31	NUM
cana-5212	357	3	]	]	PUNCT
cana-5212	357	4	yalcin	yalcin	PROPN
cana-5212	357	5	,	,	PUNCT
cana-5212	357	6	h.	h.	PROPN
cana-5212	357	7	,	,	PUNCT
cana-5212	357	8	&	&	CCONJ
cana-5212	357	9	razavi	razavi	PROPN
cana-5212	357	10	,	,	PUNCT
cana-5212	357	11	s.	s.	PROPN
cana-5212	357	12	(	(	PUNCT
cana-5212	357	13	2021	2021	NUM
cana-5212	357	14	)	)	PUNCT
cana-5212	357	15	.	.	PUNCT
cana-5212	358	1	plant	plant	NOUN
cana-5212	358	2	disease	disease	NOUN
cana-5212	358	3	detection	detection	NOUN
cana-5212	358	4	using	use	VERB
cana-5212	358	5	deep	deep	ADJ
cana-5212	358	6	learning	learning	NOUN
cana-5212	358	7	algorithms	algorithm	NOUN
cana-5212	358	8	:	:	PUNCT
cana-5212	358	9	a	a	DET
cana-5212	358	10	review	review	NOUN
cana-5212	358	11	.	.	PUNCT
cana-5212	359	1	journal	journal	NOUN
cana-5212	359	2	of	of	ADP
cana-5212	359	3	plant	plant	NOUN
cana-5212	359	4	diseases	disease	NOUN
cana-5212	359	5	and	and	CCONJ
cana-5212	359	6	protection	protection	NOUN
cana-5212	359	7	,	,	PUNCT
cana-5212	359	8	128(1	128(1	NUM
cana-5212	359	9	)	)	PUNCT
cana-5212	359	10	,	,	PUNCT
cana-5212	359	11	17	17	NUM
cana-5212	359	12	-	-	SYM
cana-5212	359	13	37	37	NUM
cana-5212	359	14	.	.	PUNCT
cana-5212	360	1	[	[	X
cana-5212	360	2	32	32	NUM
cana-5212	360	3	]	]	X
cana-5212	360	4	zhang	zhang	PROPN
cana-5212	360	5	,	,	PUNCT
cana-5212	360	6	j.	j.	PROPN
cana-5212	360	7	,	,	PUNCT
cana-5212	360	8	zhang	zhang	PROPN
cana-5212	360	9	,	,	PUNCT
cana-5212	360	10	z.	z.	PROPN
cana-5212	360	11	,	,	PUNCT
cana-5212	360	12	li	li	PROPN
cana-5212	360	13	,	,	PUNCT
cana-5212	360	14	s.	s.	PROPN
cana-5212	360	15	,	,	PUNCT
cana-5212	360	16	chen	chen	PROPN
cana-5212	360	17	,	,	PUNCT
cana-5212	360	18	l.	l.	PROPN
cana-5212	360	19	,	,	PUNCT
cana-5212	360	20	&	&	CCONJ
cana-5212	360	21	li	li	PROPN
cana-5212	360	22	,	,	PUNCT
cana-5212	360	23	s.	s.	PROPN
cana-5212	360	24	(	(	PUNCT
cana-5212	360	25	2020	2020	NUM
cana-5212	360	26	)	)	PUNCT
cana-5212	360	27	.	.	PUNCT
cana-5212	360	28	plant	plant	NOUN
cana-5212	360	29	disease	disease	NOUN
cana-5212	360	30	recognition	recognition	NOUN
cana-5212	360	31	based	base	VERB
cana-5212	360	32	on	on	ADP
cana-5212	360	33	deep	deep	ADJ
cana-5212	360	34	learning	learning	NOUN
cana-5212	360	35	and	and	CCONJ
cana-5212	360	36	support	support	VERB
cana-5212	360	37	vector	vector	NOUN
cana-5212	360	38	machine	machine	NOUN
cana-5212	360	39	.	.	PUNCT
cana-5212	361	1	computers	computer	NOUN
cana-5212	361	2	and	and	CCONJ
cana-5212	361	3	electronics	electronic	NOUN
cana-5212	361	4	in	in	ADP
cana-5212	361	5	agriculture	agriculture	NOUN
cana-5212	361	6	,	,	PUNCT
cana-5212	361	7	171	171	NUM
cana-5212	361	8	,	,	PUNCT
cana-5212	361	9	105338	105338	NUM
cana-5212	361	10	.	.	PUNCT
cana-5212	362	1	[	[	X
cana-5212	362	2	33	33	NUM
cana-5212	362	3	]	]	X
cana-5212	362	4	zhao	zhao	PROPN
cana-5212	362	5	,	,	PUNCT
cana-5212	362	6	z.	z.	PROPN
cana-5212	362	7	,	,	PUNCT
cana-5212	362	8	fu	fu	PROPN
cana-5212	362	9	,	,	PUNCT
cana-5212	362	10	y.	y.	PROPN
cana-5212	362	11	,	,	PUNCT
cana-5212	362	12	ren	ren	PROPN
cana-5212	362	13	,	,	PUNCT
cana-5212	362	14	z.	z.	PROPN
cana-5212	362	15	,	,	PUNCT
cana-5212	362	16	&	&	CCONJ
cana-5212	362	17	meng	meng	PROPN
cana-5212	362	18	,	,	PUNCT
cana-5212	362	19	q.	q.	PROPN
cana-5212	362	20	(	(	PUNCT
cana-5212	362	21	2021	2021	NUM
cana-5212	362	22	)	)	PUNCT
cana-5212	362	23	.	.	PUNCT
cana-5212	363	1	identification	identification	NOUN
cana-5212	363	2	of	of	ADP
cana-5212	363	3	maize	maize	NOUN
cana-5212	363	4	leaf	leaf	NOUN
cana-5212	363	5	diseases	disease	NOUN
cana-5212	363	6	using	use	VERB
cana-5212	363	7	improved	improve	VERB
cana-5212	363	8	deep	deep	ADJ
cana-5212	363	9	convolutional	convolutional	ADJ
cana-5212	363	10	neural	neural	ADJ
cana-5212	363	11	networks	network	NOUN
cana-5212	363	12	.	.	PUNCT
cana-5212	364	1	ieee	ieee	NOUN
cana-5212	364	2	access	access	NOUN
cana-5212	364	3	,	,	PUNCT
cana-5212	364	4	9	9	NUM
cana-5212	364	5	,	,	PUNCT
cana-5212	364	6	2343	2343	NUM
cana-5212	364	7	-	-	SYM
cana-5212	364	8	2353	2353	NUM
cana-5212	364	9	.	.	PUNCT
cana-5212	365	1	[	[	X
cana-5212	365	2	34	34	NUM
cana-5212	365	3	]	]	X
cana-5212	365	4	zhou	zhou	PROPN
cana-5212	365	5	,	,	PUNCT
cana-5212	365	6	g.	g.	PROPN
cana-5212	365	7	,	,	PUNCT
cana-5212	365	8	zhang	zhang	PROPN
cana-5212	365	9	,	,	PUNCT
cana-5212	365	10	w.	w.	PROPN
cana-5212	365	11	,	,	PUNCT
cana-5212	365	12	chen	chen	PROPN
cana-5212	365	13	,	,	PUNCT
cana-5212	365	14	a.	a.	PROPN
cana-5212	365	15	,	,	PUNCT
cana-5212	365	16	he	he	PRON
cana-5212	365	17	,	,	PUNCT
cana-5212	365	18	m.	m.	NOUN
cana-5212	365	19	,	,	PUNCT
cana-5212	365	20	&	&	CCONJ
cana-5212	365	21	ma	ma	PROPN
cana-5212	365	22	,	,	PUNCT
cana-5212	365	23	x.	x.	NOUN
cana-5212	365	24	(	(	PUNCT
cana-5212	365	25	2020	2020	NUM
cana-5212	365	26	)	)	PUNCT
cana-5212	365	27	.	.	PUNCT
cana-5212	366	1	rapid	rapid	ADJ
cana-5212	366	2	detection	detection	NOUN
cana-5212	366	3	of	of	ADP
cana-5212	366	4	rice	rice	NOUN
cana-5212	366	5	disease	disease	NOUN
cana-5212	366	6	based	base	VERB
cana-5212	366	7	on	on	ADP
cana-5212	366	8	fuzzy	fuzzy	ADJ
cana-5212	366	9	c	c	NOUN
cana-5212	366	10	-	-	PUNCT
cana-5212	366	11	means	mean	NOUN
cana-5212	366	12	and	and	CCONJ
cana-5212	366	13	deep	deep	ADJ
cana-5212	366	14	learning	learning	NOUN
cana-5212	366	15	.	.	PUNCT
cana-5212	367	1	ieee	ieee	NOUN
cana-5212	367	2	access	access	NOUN
cana-5212	367	3	,	,	PUNCT
cana-5212	367	4	8	8	NUM
cana-5212	367	5	,	,	PUNCT
cana-5212	367	6	86755	86755	NUM
cana-5212	367	7	-	-	SYM
cana-5212	367	8	86769	86769	NUM
cana-5212	367	9	.	.	PUNCT