id	sid	tid	token	lemma	pos
cana-3486	1	1	communications	communication	NOUN
cana-3486	1	2	on	on	ADP
cana-3486	1	3	applied	apply	VERB
cana-3486	1	4	nonlinear	nonlinear	ADJ
cana-3486	1	5	analysis	analysis	NOUN
cana-3486	1	6	issn	issn	NOUN
cana-3486	1	7	:	:	PUNCT
cana-3486	1	8	1074	1074	NUM
cana-3486	1	9	-	-	PUNCT
cana-3486	1	10	133x	133x	NUM
cana-3486	1	11	vol	vol	NOUN
cana-3486	1	12	32	32	NUM
cana-3486	1	13	no	no	NOUN
cana-3486	1	14	.	.	PUNCT
cana-3486	2	1	7s	7	NOUN
cana-3486	2	2	(	(	PUNCT
cana-3486	2	3	2025	2025	NUM
cana-3486	2	4	)	)	PUNCT
cana-3486	2	5	788	788	NUM
cana-3486	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	2	7	disease	disease	NOUN
cana-3486	2	8	diagnosis	diagnosis	NOUN
cana-3486	2	9	in	in	ADP
cana-3486	2	10	cassava	cassava	NOUN
cana-3486	2	11	leaves	leave	NOUN
cana-3486	2	12	using	use	VERB
cana-3486	2	13	cnn	cnn	PROPN
cana-3486	2	14	design	design	NOUN
cana-3486	2	15	and	and	CCONJ
cana-3486	2	16	resnet	resnet	NOUN
cana-3486	2	17	algorithm	algorithm	NOUN
cana-3486	2	18	m	m	PROPN
cana-3486	2	19	l	l	NOUN
cana-3486	2	20	sneha	sneha	PROPN
cana-3486	2	21	snigdha1	snigdha1	PROPN
cana-3486	2	22	,	,	PUNCT
cana-3486	2	23	bandlamudi	bandlamudi	PROPN
cana-3486	2	24	srilakshmi1	srilakshmi1	PROPN
cana-3486	2	25	,	,	PUNCT
cana-3486	2	26	polagani	polagani	ADJ
cana-3486	2	27	roshini1	roshini1	NOUN
cana-3486	2	28	,	,	PUNCT
cana-3486	2	29	badugu	badugu	PROPN
cana-3486	2	30	deva	deva	PROPN
cana-3486	2	31	harsha1	harsha1	PROPN
cana-3486	2	32	,	,	PUNCT
cana-3486	2	33	shaik	shaik	PROPN
cana-3486	2	34	khajavali1	khajavali1	PROPN
cana-3486	2	35	,	,	PUNCT
cana-3486	2	36	arepalli	arepalli	NOUN
cana-3486	2	37	gopi	gopi	PROPN
cana-3486	2	38	*	*	PUNCT
cana-3486	2	39	2	2	NUM
cana-3486	2	40	1	1	NUM
cana-3486	2	41	department	department	NOUN
cana-3486	2	42	of	of	ADP
cana-3486	2	43	computer	computer	NOUN
cana-3486	2	44	science	science	NOUN
cana-3486	2	45	and	and	CCONJ
cana-3486	2	46	engineering	engineering	NOUN
cana-3486	2	47	,	,	PUNCT
cana-3486	2	48	koneru	koneru	PROPN
cana-3486	2	49	lakshmaiah	lakshmaiah	PROPN
cana-3486	2	50	educational	educational	ADJ
cana-3486	2	51	foundation	foundation	PROPN
cana-3486	2	52	,	,	PUNCT
cana-3486	2	53	vaddeswaram	vaddeswaram	PROPN
cana-3486	2	54	,	,	PUNCT
cana-3486	2	55	andhra	andhra	PROPN
cana-3486	2	56	pradesh	pradesh	PROPN
cana-3486	2	57	,	,	PUNCT
cana-3486	2	58	india	india	PROPN
cana-3486	2	59	.	.	PROPN
cana-3486	2	60	2	2	NUM
cana-3486	2	61	assistant	assistant	NOUN
cana-3486	2	62	professor	professor	NOUN
cana-3486	2	63	,	,	PUNCT
cana-3486	2	64	department	department	NOUN
cana-3486	2	65	of	of	ADP
cana-3486	2	66	computer	computer	NOUN
cana-3486	2	67	science	science	NOUN
cana-3486	2	68	and	and	CCONJ
cana-3486	2	69	engineering	engineering	NOUN
cana-3486	2	70	,	,	PUNCT
cana-3486	2	71	koneru	koneru	PROPN
cana-3486	2	72	lakshmaiah	lakshmaiah	PROPN
cana-3486	2	73	educational	educational	ADJ
cana-3486	2	74	foundation	foundation	PROPN
cana-3486	2	75	,	,	PUNCT
cana-3486	2	76	vaddeswaram	vaddeswaram	PROPN
cana-3486	2	77	,	,	PUNCT
cana-3486	2	78	andhra	andhra	PROPN
cana-3486	2	79	pradesh	pradesh	PROPN
cana-3486	2	80	,	,	PUNCT
cana-3486	2	81	india	india	PROPN
cana-3486	2	82	*	*	PUNCT
cana-3486	2	83	corresponding	correspond	VERB
cana-3486	2	84	author	author	NOUN
cana-3486	2	85	.	.	PUNCT
cana-3486	3	1	tel	tel	PROPN
cana-3486	3	2	.	.	PUNCT
cana-3486	3	3	:	:	PUNCT
cana-3486	4	1	+91	+91	PROPN
cana-3486	4	2	-	-	PUNCT
cana-3486	4	3	91778	91778	NUM
cana-3486	4	4	-	-	PUNCT
cana-3486	4	5	21101	21101	NUM
cana-3486	4	6	;	;	PUNCT
cana-3486	4	7	email	email	NOUN
cana-3486	4	8	address	address	NOUN
cana-3486	4	9	:	:	PUNCT
cana-3486	4	10	gopi.arepalli400@gmail.com	gopi.arepalli400@gmail.com	X
cana-3486	4	11	article	article	NOUN
cana-3486	4	12	history	history	NOUN
cana-3486	4	13	:	:	PUNCT
cana-3486	4	14	received	receive	VERB
cana-3486	4	15	:	:	PUNCT
cana-3486	4	16	28	28	NUM
cana-3486	4	17	-	-	SYM
cana-3486	4	18	10	10	NUM
cana-3486	4	19	-	-	PUNCT
cana-3486	4	20	2024	2024	NUM
cana-3486	4	21	revised:12	revised:12	NOUN
cana-3486	4	22	-	-	PUNCT
cana-3486	4	23	11	11	NUM
cana-3486	4	24	-	-	PUNCT
cana-3486	4	25	2024	2024	NUM
cana-3486	4	26	accepted:19	accepted:19	VERB
cana-3486	4	27	-	-	PUNCT
cana-3486	4	28	12	12	NUM
cana-3486	4	29	-	-	PUNCT
cana-3486	4	30	2024	2024	NUM
cana-3486	4	31	abstract	abstract	NOUN
cana-3486	4	32	:	:	PUNCT
cana-3486	4	33	introduction	introduction	NOUN
cana-3486	4	34	:	:	PUNCT
cana-3486	4	35	growth	growth	NOUN
cana-3486	4	36	rate	rate	NOUN
cana-3486	4	37	of	of	ADP
cana-3486	4	38	crops	crop	NOUN
cana-3486	4	39	is	be	AUX
cana-3486	4	40	significantly	significantly	ADV
cana-3486	4	41	lowered	lower	VERB
cana-3486	4	42	by	by	ADP
cana-3486	4	43	illnesses	illness	NOUN
cana-3486	4	44	that	that	PRON
cana-3486	4	45	affect	affect	VERB
cana-3486	4	46	plants	plant	NOUN
cana-3486	4	47	.	.	PUNCT
cana-3486	5	1	it	it	PRON
cana-3486	5	2	is	be	AUX
cana-3486	5	3	impossible	impossible	ADJ
cana-3486	5	4	for	for	SCONJ
cana-3486	5	5	anyone	anyone	PRON
cana-3486	5	6	to	to	PART
cana-3486	5	7	eat	eat	VERB
cana-3486	5	8	the	the	DET
cana-3486	5	9	crops	crop	NOUN
cana-3486	5	10	since	since	SCONJ
cana-3486	5	11	they	they	PRON
cana-3486	5	12	are	be	AUX
cana-3486	5	13	tainted	taint	VERB
cana-3486	5	14	with	with	ADP
cana-3486	5	15	various	various	ADJ
cana-3486	5	16	diseases	disease	NOUN
cana-3486	5	17	.	.	PUNCT
cana-3486	6	1	farmers	farmer	NOUN
cana-3486	6	2	may	may	AUX
cana-3486	6	3	suffer	suffer	VERB
cana-3486	6	4	enormous	enormous	ADJ
cana-3486	6	5	losses	loss	NOUN
cana-3486	6	6	as	as	ADP
cana-3486	6	7	a	a	DET
cana-3486	6	8	consequence	consequence	NOUN
cana-3486	6	9	.	.	PUNCT
cana-3486	7	1	since	since	SCONJ
cana-3486	7	2	cassava	cassava	NOUN
cana-3486	7	3	is	be	AUX
cana-3486	7	4	an	an	DET
cana-3486	7	5	important	important	ADJ
cana-3486	7	6	food	food	NOUN
cana-3486	7	7	source	source	NOUN
cana-3486	7	8	in	in	ADP
cana-3486	7	9	several	several	ADJ
cana-3486	7	10	countries	country	NOUN
cana-3486	7	11	,	,	PUNCT
cana-3486	7	12	the	the	DET
cana-3486	7	13	financial	financial	ADJ
cana-3486	7	14	system	system	NOUN
cana-3486	7	15	might	might	AUX
cana-3486	7	16	be	be	AUX
cana-3486	7	17	seriously	seriously	ADV
cana-3486	7	18	damaged	damage	VERB
cana-3486	7	19	by	by	ADP
cana-3486	7	20	the	the	DET
cana-3486	7	21	issue	issue	NOUN
cana-3486	7	22	at	at	ADP
cana-3486	7	23	hand	hand	NOUN
cana-3486	7	24	.	.	PUNCT
cana-3486	8	1	objectives	objective	NOUN
cana-3486	8	2	:	:	PUNCT
cana-3486	8	3	traditional	traditional	ADJ
cana-3486	8	4	plant	plant	NOUN
cana-3486	8	5	pathogen	pathogen	NOUN
cana-3486	8	6	detection	detection	NOUN
cana-3486	8	7	is	be	AUX
cana-3486	8	8	labour	labour	NOUN
cana-3486	8	9	-	-	PUNCT
cana-3486	8	10	intensive	intensive	ADJ
cana-3486	8	11	and	and	CCONJ
cana-3486	8	12	errorprone	errorprone	NOUN
cana-3486	8	13	.	.	PUNCT
cana-3486	9	1	it	it	PRON
cana-3486	9	2	is	be	AUX
cana-3486	9	3	not	not	PART
cana-3486	9	4	typically	typically	ADV
cana-3486	9	5	a	a	DET
cana-3486	9	6	dependable	dependable	ADJ
cana-3486	9	7	strategy	strategy	NOUN
cana-3486	9	8	to	to	PART
cana-3486	9	9	identify	identify	VERB
cana-3486	9	10	and	and	CCONJ
cana-3486	9	11	stop	stop	VERB
cana-3486	9	12	the	the	DET
cana-3486	9	13	spread	spread	NOUN
cana-3486	9	14	of	of	ADP
cana-3486	9	15	plant	plant	NOUN
cana-3486	9	16	viruses	virus	NOUN
cana-3486	9	17	.	.	PUNCT
cana-3486	10	1	innovative	innovative	ADJ
cana-3486	10	2	technologies	technology	NOUN
cana-3486	10	3	like	like	ADP
cana-3486	10	4	deep	deep	ADJ
cana-3486	10	5	learning	learning	NOUN
cana-3486	10	6	as	as	ADV
cana-3486	10	7	well	well	ADV
cana-3486	10	8	as	as	ADP
cana-3486	10	9	machine	machine	NOUN
cana-3486	10	10	learning	learning	NOUN
cana-3486	10	11	might	might	AUX
cana-3486	10	12	aid	aid	VERB
cana-3486	10	13	in	in	ADP
cana-3486	10	14	the	the	DET
cana-3486	10	15	early	early	ADJ
cana-3486	10	16	detection	detection	NOUN
cana-3486	10	17	of	of	ADP
cana-3486	10	18	plant	plant	NOUN
cana-3486	10	19	diseases	disease	NOUN
cana-3486	10	20	as	as	ADP
cana-3486	10	21	an	an	DET
cana-3486	10	22	approach	approach	NOUN
cana-3486	10	23	to	to	PART
cana-3486	10	24	get	get	VERB
cana-3486	10	25	around	around	ADP
cana-3486	10	26	these	these	DET
cana-3486	10	27	problems	problem	NOUN
cana-3486	10	28	.	.	PUNCT
cana-3486	11	1	methods	method	NOUN
cana-3486	11	2	:	:	PUNCT
cana-3486	11	3	the	the	DET
cana-3486	11	4	main	main	ADJ
cana-3486	11	5	goal	goal	NOUN
cana-3486	11	6	of	of	ADP
cana-3486	11	7	the	the	DET
cana-3486	11	8	work	work	NOUN
cana-3486	11	9	is	be	AUX
cana-3486	11	10	to	to	PART
cana-3486	11	11	employ	employ	VERB
cana-3486	11	12	deep	deep	ADJ
cana-3486	11	13	learning	learning	NOUN
cana-3486	11	14	to	to	PART
cana-3486	11	15	image	image	VERB
cana-3486	11	16	classification	classification	NOUN
cana-3486	11	17	in	in	ADP
cana-3486	11	18	order	order	NOUN
cana-3486	11	19	to	to	PART
cana-3486	11	20	accurately	accurately	ADV
cana-3486	11	21	identify	identify	VERB
cana-3486	11	22	diseases	disease	NOUN
cana-3486	11	23	that	that	PRON
cana-3486	11	24	especially	especially	ADV
cana-3486	11	25	impact	impact	VERB
cana-3486	11	26	cassava	cassava	NOUN
cana-3486	11	27	plants	plant	NOUN
cana-3486	11	28	.	.	PUNCT
cana-3486	12	1	results	result	NOUN
cana-3486	12	2	:	:	PUNCT
cana-3486	12	3	this	this	DET
cana-3486	12	4	recognition	recognition	NOUN
cana-3486	12	5	may	may	AUX
cana-3486	12	6	make	make	VERB
cana-3486	12	7	it	it	PRON
cana-3486	12	8	possible	possible	ADJ
cana-3486	12	9	to	to	PART
cana-3486	12	10	implement	implement	VERB
cana-3486	12	11	preventative	preventative	ADJ
cana-3486	12	12	measures	measure	NOUN
cana-3486	12	13	like	like	ADP
cana-3486	12	14	the	the	DET
cana-3486	12	15	specific	specific	ADJ
cana-3486	12	16	application	application	NOUN
cana-3486	12	17	of	of	ADP
cana-3486	12	18	chemical	chemical	ADJ
cana-3486	12	19	pesticides	pesticide	NOUN
cana-3486	12	20	or	or	CCONJ
cana-3486	12	21	confinement	confinement	NOUN
cana-3486	12	22	of	of	ADP
cana-3486	12	23	contaminated	contaminate	VERB
cana-3486	12	24	crops	crop	NOUN
cana-3486	12	25	.	.	PUNCT
cana-3486	13	1	each	each	PRON
cana-3486	13	2	and	and	CCONJ
cana-3486	13	3	every	every	DET
cana-3486	13	4	training	training	NOUN
cana-3486	13	5	and	and	CCONJ
cana-3486	13	6	testing	testing	NOUN
cana-3486	13	7	image	image	NOUN
cana-3486	13	8	comes	come	VERB
cana-3486	13	9	from	from	ADP
cana-3486	13	10	a	a	DET
cana-3486	13	11	rural	rural	ADJ
cana-3486	13	12	area	area	NOUN
cana-3486	13	13	in	in	ADP
cana-3486	13	14	the	the	DET
cana-3486	13	15	natural	natural	ADJ
cana-3486	13	16	world	world	NOUN
cana-3486	13	17	.	.	PUNCT
cana-3486	14	1	using	use	VERB
cana-3486	14	2	a	a	DET
cana-3486	14	3	specific	specific	ADJ
cana-3486	14	4	collection	collection	NOUN
cana-3486	14	5	of	of	ADP
cana-3486	14	6	information	information	NOUN
cana-3486	14	7	,	,	PUNCT
cana-3486	14	8	the	the	DET
cana-3486	14	9	simulation	simulation	NOUN
cana-3486	14	10	has	have	AUX
cana-3486	14	11	been	be	AUX
cana-3486	14	12	verified	verify	VERB
cana-3486	14	13	to	to	PART
cana-3486	14	14	ascertain	ascertain	VERB
cana-3486	14	15	its	its	PRON
cana-3486	14	16	true	true	ADJ
cana-3486	14	17	results	result	NOUN
cana-3486	14	18	.	.	PUNCT
cana-3486	15	1	conclusions	conclusion	NOUN
cana-3486	15	2	:	:	PUNCT
cana-3486	15	3	the	the	DET
cana-3486	15	4	installation	installation	NOUN
cana-3486	15	5	of	of	ADP
cana-3486	15	6	a	a	DET
cana-3486	15	7	precise	precise	ADJ
cana-3486	15	8	disease	disease	NOUN
cana-3486	15	9	identification	identification	NOUN
cana-3486	15	10	and	and	CCONJ
cana-3486	15	11	mitigation	mitigation	NOUN
cana-3486	15	12	model	model	NOUN
cana-3486	15	13	has	have	VERB
cana-3486	15	14	the	the	DET
cana-3486	15	15	potential	potential	NOUN
cana-3486	15	16	to	to	PART
cana-3486	15	17	significantly	significantly	ADV
cana-3486	15	18	increase	increase	VERB
cana-3486	15	19	the	the	DET
cana-3486	15	20	durability	durability	NOUN
cana-3486	15	21	of	of	ADP
cana-3486	15	22	the	the	DET
cana-3486	15	23	cassava	cassava	NOUN
cana-3486	15	24	crop	crop	NOUN
cana-3486	15	25	,	,	PUNCT
cana-3486	15	26	improving	improve	VERB
cana-3486	15	27	food	food	NOUN
cana-3486	15	28	production	production	NOUN
cana-3486	15	29	and	and	CCONJ
cana-3486	15	30	the	the	DET
cana-3486	15	31	quality	quality	NOUN
cana-3486	15	32	of	of	ADP
cana-3486	15	33	life	life	NOUN
cana-3486	15	34	for	for	ADP
cana-3486	15	35	millions	million	NOUN
cana-3486	15	36	of	of	ADP
cana-3486	15	37	people	people	NOUN
cana-3486	15	38	who	who	PRON
cana-3486	15	39	are	be	AUX
cana-3486	15	40	dependent	dependent	ADJ
cana-3486	15	41	upon	upon	SCONJ
cana-3486	15	42	this	this	DET
cana-3486	15	43	valuable	valuable	ADJ
cana-3486	15	44	crop	crop	NOUN
cana-3486	15	45	.	.	PUNCT
cana-3486	16	1	keywords	keyword	NOUN
cana-3486	16	2	:	:	PUNCT
cana-3486	16	3	cassava	cassava	NOUN
cana-3486	16	4	leaves	leave	NOUN
cana-3486	16	5	,	,	PUNCT
cana-3486	16	6	deep	deep	ADJ
cana-3486	16	7	learning	learning	NOUN
cana-3486	16	8	,	,	PUNCT
cana-3486	16	9	disease	disease	NOUN
cana-3486	16	10	,	,	PUNCT
cana-3486	16	11	identification	identification	NOUN
cana-3486	16	12	,	,	PUNCT
cana-3486	16	13	testing	testing	NOUN
cana-3486	16	14	,	,	PUNCT
cana-3486	16	15	training	training	NOUN
cana-3486	16	16	.	.	PUNCT
cana-3486	17	1	1	1	X
cana-3486	17	2	.	.	X
cana-3486	17	3	introduction	introduction	NOUN
cana-3486	17	4	despite	despite	SCONJ
cana-3486	17	5	the	the	DET
cana-3486	17	6	fact	fact	NOUN
cana-3486	17	7	that	that	SCONJ
cana-3486	17	8	more	more	ADV
cana-3486	17	9	obscure	obscure	ADJ
cana-3486	17	10	than	than	ADP
cana-3486	17	11	the	the	DET
cana-3486	17	12	plant	plant	NOUN
cana-3486	17	13	's	's	PART
cana-3486	17	14	appetizing	appetize	VERB
cana-3486	17	15	roots	root	NOUN
cana-3486	17	16	,	,	PUNCT
cana-3486	17	17	thousands	thousand	NOUN
cana-3486	17	18	of	of	ADP
cana-3486	17	19	individuals	individual	NOUN
cana-3486	17	20	of	of	ADP
cana-3486	17	21	people	people	NOUN
cana-3486	17	22	in	in	ADP
cana-3486	17	23	south	south	PROPN
cana-3486	17	24	america	america	PROPN
cana-3486	17	25	,	,	PUNCT
cana-3486	17	26	asia	asia	PROPN
cana-3486	17	27	,	,	PUNCT
cana-3486	17	28	and	and	CCONJ
cana-3486	17	29	africa	africa	PROPN
cana-3486	17	30	consume	consume	VERB
cana-3486	17	31	a	a	DET
cana-3486	17	32	lot	lot	NOUN
cana-3486	17	33	of	of	ADP
cana-3486	17	34	cassava	cassava	NOUN
cana-3486	17	35	leaves	leave	VERB
cana-3486	17	36	[	[	X
cana-3486	17	37	3	3	NUM
cana-3486	17	38	]	]	PUNCT
cana-3486	17	39	.	.	PUNCT
cana-3486	18	1	these	these	DET
cana-3486	18	2	nutritious	nutritious	ADJ
cana-3486	18	3	veggies	veggie	NOUN
cana-3486	18	4	are	be	AUX
cana-3486	18	5	an	an	DET
cana-3486	18	6	important	important	ADJ
cana-3486	18	7	source	source	NOUN
cana-3486	18	8	of	of	ADP
cana-3486	18	9	nutrition	nutrition	NOUN
cana-3486	18	10	since	since	SCONJ
cana-3486	18	11	they	they	PRON
cana-3486	18	12	are	be	AUX
cana-3486	18	13	nutrient	nutrient	NOUN
cana-3486	18	14	-	-	PUNCT
cana-3486	18	15	rich	rich	ADJ
cana-3486	18	16	,	,	PUNCT
cana-3486	18	17	particularly	particularly	ADV
cana-3486	18	18	for	for	ADP
cana-3486	18	19	those	those	DET
cana-3486	18	20	areas	area	NOUN
cana-3486	18	21	wherein	wherein	SCONJ
cana-3486	18	22	the	the	DET
cana-3486	18	23	availability	availability	NOUN
cana-3486	18	24	of	of	ADP
cana-3486	18	25	a	a	DET
cana-3486	18	26	wide	wide	ADJ
cana-3486	18	27	variety	variety	NOUN
cana-3486	18	28	of	of	ADP
cana-3486	18	29	foods	food	NOUN
cana-3486	18	30	is	be	AUX
cana-3486	18	31	restricted	restrict	VERB
cana-3486	18	32	[	[	PUNCT
cana-3486	18	33	6	6	NUM
cana-3486	18	34	]	]	PUNCT
cana-3486	18	35	.	.	PUNCT
cana-3486	19	1	cassava	cassava	NOUN
cana-3486	19	2	leaves	leave	NOUN
cana-3486	19	3	are	be	AUX
cana-3486	19	4	packed	pack	VERB
cana-3486	19	5	with	with	ADP
cana-3486	19	6	protein	protein	NOUN
cana-3486	19	7	,	,	PUNCT
cana-3486	19	8	iron	iron	NOUN
cana-3486	19	9	,	,	PUNCT
cana-3486	19	10	calcium	calcium	NOUN
cana-3486	19	11	,	,	PUNCT
cana-3486	19	12	vitamin	vitamin	NOUN
cana-3486	19	13	a	a	PRON
cana-3486	19	14	as	as	ADV
cana-3486	19	15	well	well	ADV
cana-3486	19	16	as	as	ADP
cana-3486	19	17	vitamin	vitamin	NOUN
cana-3486	19	18	c	c	NOUN
cana-3486	19	19	,	,	PUNCT
cana-3486	19	20	and	and	CCONJ
cana-3486	19	21	other	other	ADJ
cana-3486	19	22	nutrients	nutrient	NOUN
cana-3486	19	23	that	that	PRON
cana-3486	19	24	support	support	VERB
cana-3486	19	25	overall	overall	ADJ
cana-3486	19	26	wellness	wellness	NOUN
cana-3486	19	27	and	and	CCONJ
cana-3486	19	28	help	help	VERB
cana-3486	19	29	fight	fight	VERB
cana-3486	19	30	hunger	hunger	NOUN
cana-3486	19	31	in	in	ADP
cana-3486	19	32	communities	community	NOUN
cana-3486	19	33	who	who	PRON
cana-3486	19	34	are	be	AUX
cana-3486	19	35	currently	currently	ADV
cana-3486	19	36	at	at	ADP
cana-3486	19	37	jeopardy	jeopardy	NOUN
cana-3486	19	38	.	.	PUNCT
cana-3486	20	1	communications	communication	NOUN
cana-3486	20	2	on	on	ADP
cana-3486	20	3	applied	apply	VERB
cana-3486	20	4	nonlinear	nonlinear	ADJ
cana-3486	20	5	analysis	analysis	NOUN
cana-3486	20	6	issn	issn	NOUN
cana-3486	20	7	:	:	PUNCT
cana-3486	20	8	1074	1074	NUM
cana-3486	20	9	-	-	PUNCT
cana-3486	20	10	133x	133x	NUM
cana-3486	20	11	vol	vol	NOUN
cana-3486	20	12	32	32	NUM
cana-3486	20	13	no	no	NOUN
cana-3486	20	14	.	.	PUNCT
cana-3486	21	1	7s	7	NOUN
cana-3486	21	2	(	(	PUNCT
cana-3486	21	3	2025	2025	NUM
cana-3486	21	4	)	)	PUNCT
cana-3486	21	5	789	789	NUM
cana-3486	21	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	21	7	the	the	DET
cana-3486	21	8	abundant	abundant	ADJ
cana-3486	21	9	protein	protein	NOUN
cana-3486	21	10	content	content	NOUN
cana-3486	21	11	of	of	ADP
cana-3486	21	12	cassava	cassava	NOUN
cana-3486	21	13	leaves	leave	NOUN
cana-3486	21	14	serves	serve	VERB
cana-3486	21	15	as	as	ADP
cana-3486	21	16	one	one	NUM
cana-3486	21	17	of	of	ADP
cana-3486	21	18	their	their	PRON
cana-3486	21	19	most	most	ADV
cana-3486	21	20	notable	notable	ADJ
cana-3486	21	21	qualities	quality	NOUN
cana-3486	21	22	;	;	PUNCT
cana-3486	21	23	this	this	PRON
cana-3486	21	24	is	be	AUX
cana-3486	21	25	especially	especially	ADV
cana-3486	21	26	welcome	welcome	ADJ
cana-3486	21	27	in	in	ADP
cana-3486	21	28	areas	area	NOUN
cana-3486	21	29	wherein	wherein	SCONJ
cana-3486	21	30	animal	animal	NOUN
cana-3486	21	31	-	-	PUNCT
cana-3486	21	32	based	base	VERB
cana-3486	21	33	protein	protein	NOUN
cana-3486	21	34	is	be	AUX
cana-3486	21	35	unreliable	unreliable	ADJ
cana-3486	21	36	.	.	PUNCT
cana-3486	22	1	furthermore	furthermore	ADV
cana-3486	22	2	,	,	PUNCT
cana-3486	22	3	they	they	PRON
cana-3486	22	4	are	be	AUX
cana-3486	22	5	an	an	DET
cana-3486	22	6	outstanding	outstanding	ADJ
cana-3486	22	7	source	source	NOUN
cana-3486	22	8	of	of	ADP
cana-3486	22	9	antioxidants	antioxidant	NOUN
cana-3486	22	10	and	and	CCONJ
cana-3486	22	11	dietary	dietary	ADJ
cana-3486	22	12	fiber	fiber	NOUN
cana-3486	22	13	,	,	PUNCT
cana-3486	22	14	which	which	PRON
cana-3486	22	15	promote	promote	VERB
cana-3486	22	16	digestive	digestive	ADJ
cana-3486	22	17	function	function	NOUN
cana-3486	22	18	and	and	CCONJ
cana-3486	22	19	cement	cement	NOUN
cana-3486	22	20	resilience	resilience	NOUN
cana-3486	22	21	[	[	X
cana-3486	22	22	11	11	NUM
cana-3486	22	23	]	]	PUNCT
cana-3486	22	24	.	.	PUNCT
cana-3486	23	1	nevertheless	nevertheless	ADV
cana-3486	23	2	these	these	DET
cana-3486	23	3	health	health	NOUN
cana-3486	23	4	advantages	advantage	NOUN
cana-3486	23	5	,	,	PUNCT
cana-3486	23	6	cyanogenic	cyanogenic	ADJ
cana-3486	23	7	compounds	compound	NOUN
cana-3486	23	8	—	—	PUNCT
cana-3486	23	9	which	which	PRON
cana-3486	23	10	,	,	PUNCT
cana-3486	23	11	when	when	SCONJ
cana-3486	23	12	served	serve	VERB
cana-3486	23	13	raw	raw	ADJ
cana-3486	23	14	or	or	CCONJ
cana-3486	23	15	cooked	cook	VERB
cana-3486	23	16	erratically	erratically	ADV
cana-3486	23	17	,	,	PUNCT
cana-3486	23	18	can	can	AUX
cana-3486	23	19	emit	emit	VERB
cana-3486	23	20	poisonous	poisonous	ADJ
cana-3486	23	21	hydrogen	hydrogen	NOUN
cana-3486	23	22	cyanide	cyanide	NOUN
cana-3486	23	23	—	—	PUNCT
cana-3486	23	24	must	must	AUX
cana-3486	23	25	be	be	AUX
cana-3486	23	26	avoided	avoid	VERB
cana-3486	23	27	while	while	SCONJ
cana-3486	23	28	handling	handle	VERB
cana-3486	23	29	cassava	cassava	NOUN
cana-3486	23	30	leaves	leave	NOUN
cana-3486	23	31	.	.	PUNCT
cana-3486	24	1	one	one	NUM
cana-3486	24	2	typical	typical	ADJ
cana-3486	24	3	way	way	NOUN
cana-3486	24	4	to	to	PART
cana-3486	24	5	assure	assure	VERB
cana-3486	24	6	quality	quality	NOUN
cana-3486	24	7	is	be	AUX
cana-3486	24	8	to	to	PART
cana-3486	24	9	simmer	simmer	VERB
cana-3486	24	10	or	or	CCONJ
cana-3486	24	11	ferment	ferment	VERB
cana-3486	24	12	the	the	DET
cana-3486	24	13	foliage	foliage	NOUN
cana-3486	24	14	.	.	PUNCT
cana-3486	25	1	cassava	cassava	NOUN
cana-3486	25	2	leaves	leave	NOUN
cana-3486	25	3	are	be	AUX
cana-3486	25	4	valued	value	VERB
cana-3486	25	5	for	for	ADP
cana-3486	25	6	their	their	PRON
cana-3486	25	7	gastronomic	gastronomic	ADJ
cana-3486	25	8	diversity	diversity	NOUN
cana-3486	25	9	in	in	ADP
cana-3486	25	10	alongside	alongside	ADP
cana-3486	25	11	their	their	PRON
cana-3486	25	12	health	health	NOUN
cana-3486	25	13	perks	perk	NOUN
cana-3486	25	14	[	[	X
cana-3486	25	15	5	5	NUM
cana-3486	25	16	]	]	PUNCT
cana-3486	25	17	.	.	PUNCT
cana-3486	26	1	they	they	PRON
cana-3486	26	2	give	give	VERB
cana-3486	26	3	taste	taste	NOUN
cana-3486	26	4	and	and	CCONJ
cana-3486	26	5	nourishment	nourishment	NOUN
cana-3486	26	6	to	to	ADP
cana-3486	26	7	meals	meal	NOUN
cana-3486	26	8	by	by	ADP
cana-3486	26	9	being	be	AUX
cana-3486	26	10	utilized	utilize	VERB
cana-3486	26	11	as	as	ADP
cana-3486	26	12	accompaniments	accompaniment	NOUN
cana-3486	26	13	,	,	PUNCT
cana-3486	26	14	in	in	ADP
cana-3486	26	15	meals	meal	NOUN
cana-3486	26	16	,	,	PUNCT
cana-3486	26	17	and	and	CCONJ
cana-3486	26	18	in	in	ADP
cana-3486	26	19	recipes	recipe	NOUN
cana-3486	26	20	throughout	throughout	ADP
cana-3486	26	21	many	many	ADJ
cana-3486	26	22	civilizations	civilization	NOUN
cana-3486	26	23	[	[	X
cana-3486	26	24	7	7	NUM
cana-3486	26	25	]	]	PUNCT
cana-3486	26	26	.	.	PUNCT
cana-3486	27	1	the	the	DET
cana-3486	27	2	leaves	leave	NOUN
cana-3486	27	3	of	of	ADP
cana-3486	27	4	cassava	cassava	NOUN
cana-3486	27	5	are	be	AUX
cana-3486	27	6	a	a	DET
cana-3486	27	7	common	common	ADJ
cana-3486	27	8	component	component	NOUN
cana-3486	27	9	in	in	ADP
cana-3486	27	10	many	many	ADJ
cana-3486	27	11	regional	regional	ADJ
cana-3486	27	12	cuisines	cuisine	NOUN
cana-3486	27	13	,	,	PUNCT
cana-3486	27	14	as	as	SCONJ
cana-3486	27	15	seen	see	VERB
cana-3486	27	16	in	in	ADP
cana-3486	27	17	the	the	DET
cana-3486	27	18	countries	country	NOUN
cana-3486	27	19	of	of	ADP
cana-3486	27	20	the	the	DET
cana-3486	27	21	democratic	democratic	PROPN
cana-3486	27	22	republic	republic	NOUN
cana-3486	27	23	of	of	ADP
cana-3486	27	24	the	the	DET
cana-3486	27	25	congo	congo	PROPN
cana-3486	27	26	,	,	PUNCT
cana-3486	27	27	indonesia	indonesia	PROPN
cana-3486	27	28	,	,	PUNCT
cana-3486	27	29	and	and	CCONJ
cana-3486	27	30	the	the	DET
cana-3486	27	31	philippines	philippine	NOUN
cana-3486	27	32	,	,	PUNCT
cana-3486	27	33	demonstrating	demonstrate	VERB
cana-3486	27	34	its	its	PRON
cana-3486	27	35	socioeconomic	socioeconomic	ADJ
cana-3486	27	36	relevance	relevance	NOUN
cana-3486	27	37	[	[	X
cana-3486	27	38	12	12	NUM
cana-3486	27	39	]	]	PUNCT
cana-3486	27	40	.	.	PUNCT
cana-3486	28	1	problem	problem	NOUN
cana-3486	28	2	statement	statement	NOUN
cana-3486	28	3	:	:	PUNCT
cana-3486	28	4	cassava	cassava	NOUN
cana-3486	28	5	disease	disease	NOUN
cana-3486	28	6	outbreaks	outbreak	NOUN
cana-3486	28	7	are	be	AUX
cana-3486	28	8	a	a	DET
cana-3486	28	9	major	major	ADJ
cana-3486	28	10	threat	threat	NOUN
cana-3486	28	11	to	to	ADP
cana-3486	28	12	agricultural	agricultural	ADJ
cana-3486	28	13	production	production	NOUN
cana-3486	28	14	because	because	SCONJ
cana-3486	28	15	they	they	PRON
cana-3486	28	16	lower	lower	VERB
cana-3486	28	17	crop	crop	NOUN
cana-3486	28	18	yields	yield	NOUN
cana-3486	28	19	and	and	CCONJ
cana-3486	28	20	cause	cause	VERB
cana-3486	28	21	farmers	farmer	NOUN
cana-3486	28	22	to	to	PART
cana-3486	28	23	suffer	suffer	VERB
cana-3486	28	24	large	large	ADJ
cana-3486	28	25	financial	financial	ADJ
cana-3486	28	26	losses	loss	NOUN
cana-3486	28	27	.	.	PUNCT
cana-3486	29	1	the	the	DET
cana-3486	29	2	current	current	ADJ
cana-3486	29	3	techniques	technique	NOUN
cana-3486	29	4	for	for	ADP
cana-3486	29	5	diagnosing	diagnose	VERB
cana-3486	29	6	plant	plant	NOUN
cana-3486	29	7	diseases	disease	NOUN
cana-3486	29	8	are	be	AUX
cana-3486	29	9	unsatisfactory	unsatisfactory	ADJ
cana-3486	29	10	for	for	ADP
cana-3486	29	11	controlling	control	VERB
cana-3486	29	12	extensive	extensive	ADJ
cana-3486	29	13	crop	crop	NOUN
cana-3486	29	14	pathogens	pathogen	NOUN
cana-3486	29	15	because	because	SCONJ
cana-3486	29	16	they	they	PRON
cana-3486	29	17	are	be	AUX
cana-3486	29	18	labour	labour	NOUN
cana-3486	29	19	-	-	PUNCT
cana-3486	29	20	intensive	intensive	ADJ
cana-3486	29	21	,	,	PUNCT
cana-3486	29	22	error	error	NOUN
cana-3486	29	23	-	-	PUNCT
cana-3486	29	24	prone	prone	ADJ
cana-3486	29	25	,	,	PUNCT
cana-3486	29	26	and	and	CCONJ
cana-3486	29	27	ineffective	ineffective	ADJ
cana-3486	29	28	.	.	PUNCT
cana-3486	30	1	a	a	DET
cana-3486	30	2	more	more	ADV
cana-3486	30	3	precise	precise	ADJ
cana-3486	30	4	and	and	CCONJ
cana-3486	30	5	effective	effective	ADJ
cana-3486	30	6	method	method	NOUN
cana-3486	30	7	of	of	ADP
cana-3486	30	8	early	early	ADJ
cana-3486	30	9	cassava	cassava	NOUN
cana-3486	30	10	disease	disease	NOUN
cana-3486	30	11	detection	detection	NOUN
cana-3486	30	12	is	be	AUX
cana-3486	30	13	vitally	vitally	ADV
cana-3486	30	14	required	require	VERB
cana-3486	30	15	.	.	PUNCT
cana-3486	31	1	utilizing	utilize	VERB
cana-3486	31	2	cutting	cutting	NOUN
cana-3486	31	3	-	-	PUNCT
cana-3486	31	4	edge	edge	NOUN
cana-3486	31	5	technology	technology	NOUN
cana-3486	31	6	for	for	ADP
cana-3486	31	7	picture	picture	NOUN
cana-3486	31	8	categorization	categorization	NOUN
cana-3486	31	9	,	,	PUNCT
cana-3486	31	10	such	such	ADJ
cana-3486	31	11	as	as	ADP
cana-3486	31	12	deep	deep	ADJ
cana-3486	31	13	learning	learning	NOUN
cana-3486	31	14	,	,	PUNCT
cana-3486	31	15	is	be	AUX
cana-3486	31	16	a	a	DET
cana-3486	31	17	viable	viable	ADJ
cana-3486	31	18	solution	solution	NOUN
cana-3486	31	19	to	to	ADP
cana-3486	31	20	this	this	DET
cana-3486	31	21	problem	problem	NOUN
cana-3486	31	22	.	.	PUNCT
cana-3486	32	1	creating	create	VERB
cana-3486	32	2	an	an	DET
cana-3486	32	3	effective	effective	ADJ
cana-3486	32	4	framework	framework	NOUN
cana-3486	32	5	for	for	ADP
cana-3486	32	6	swift	swift	ADJ
cana-3486	32	7	detection	detection	NOUN
cana-3486	32	8	and	and	CCONJ
cana-3486	32	9	action	action	NOUN
cana-3486	32	10	is	be	AUX
cana-3486	32	11	the	the	DET
cana-3486	32	12	goal	goal	NOUN
cana-3486	32	13	in	in	ADP
cana-3486	32	14	order	order	NOUN
cana-3486	32	15	to	to	PART
cana-3486	32	16	maintain	maintain	VERB
cana-3486	32	17	the	the	DET
cana-3486	32	18	integrity	integrity	NOUN
cana-3486	32	19	of	of	ADP
cana-3486	32	20	the	the	DET
cana-3486	32	21	growing	growing	NOUN
cana-3486	32	22	of	of	ADP
cana-3486	32	23	cassava	cassava	NOUN
cana-3486	32	24	and	and	CCONJ
cana-3486	32	25	enhance	enhance	VERB
cana-3486	32	26	the	the	DET
cana-3486	32	27	quality	quality	NOUN
cana-3486	32	28	of	of	ADP
cana-3486	32	29	life	life	NOUN
cana-3486	32	30	for	for	ADP
cana-3486	32	31	the	the	DET
cana-3486	32	32	people	people	NOUN
cana-3486	32	33	that	that	PRON
cana-3486	32	34	depend	depend	VERB
cana-3486	32	35	on	on	ADP
cana-3486	32	36	this	this	DET
cana-3486	32	37	vital	vital	ADJ
cana-3486	32	38	crop	crop	NOUN
cana-3486	32	39	.	.	PUNCT
cana-3486	33	1	2	2	X
cana-3486	33	2	.	.	X
cana-3486	33	3	materials	material	NOUN
cana-3486	33	4	and	and	CCONJ
cana-3486	33	5	proposed	propose	VERB
cana-3486	33	6	methods	method	NOUN
cana-3486	33	7	dataset	dataset	VERB
cana-3486	33	8	the	the	DET
cana-3486	33	9	dataset	dataset	NOUN
cana-3486	33	10	used	use	VERB
cana-3486	33	11	for	for	ADP
cana-3486	33	12	cassava	cassava	NOUN
cana-3486	33	13	disease	disease	NOUN
cana-3486	33	14	detection	detection	NOUN
cana-3486	33	15	consists	consist	VERB
cana-3486	33	16	of	of	ADP
cana-3486	33	17	labelled	label	VERB
cana-3486	33	18	photos	photo	NOUN
cana-3486	33	19	of	of	ADP
cana-3486	33	20	cassava	cassava	NOUN
cana-3486	33	21	leaves	leave	NOUN
cana-3486	33	22	,	,	PUNCT
cana-3486	33	23	divided	divide	VERB
cana-3486	33	24	into	into	ADP
cana-3486	33	25	several	several	ADJ
cana-3486	33	26	disease	disease	NOUN
cana-3486	33	27	classifications	classification	NOUN
cana-3486	33	28	and	and	CCONJ
cana-3486	33	29	healthy	healthy	ADJ
cana-3486	33	30	leaves	leave	NOUN
cana-3486	33	31	.	.	PUNCT
cana-3486	34	1	this	this	DET
cana-3486	34	2	dataset	dataset	NOUN
cana-3486	34	3	is	be	AUX
cana-3486	34	4	essential	essential	ADJ
cana-3486	34	5	for	for	ADP
cana-3486	34	6	both	both	DET
cana-3486	34	7	training	training	NOUN
cana-3486	34	8	and	and	CCONJ
cana-3486	34	9	evaluating	evaluate	VERB
cana-3486	34	10	the	the	DET
cana-3486	34	11	performance	performance	NOUN
cana-3486	34	12	of	of	ADP
cana-3486	34	13	in	in	ADP
cana-3486	34	14	distinguishing	distinguish	VERB
cana-3486	34	15	between	between	ADP
cana-3486	34	16	various	various	ADJ
cana-3486	34	17	cassava	cassava	NOUN
cana-3486	34	18	diseases	disease	NOUN
cana-3486	34	19	.	.	PUNCT
cana-3486	35	1	the	the	DET
cana-3486	35	2	dataset	dataset	NOUN
cana-3486	35	3	was	be	AUX
cana-3486	35	4	sourced	source	VERB
cana-3486	35	5	from	from	ADP
cana-3486	35	6	the	the	DET
cana-3486	35	7	publicly	publicly	ADV
cana-3486	35	8	available	available	ADJ
cana-3486	35	9	kaggle	kaggle	NOUN
cana-3486	35	10	cassava	cassava	NOUN
cana-3486	35	11	leaf	leaf	NOUN
cana-3486	35	12	disease	disease	NOUN
cana-3486	35	13	dataset	dataset	VERB
cana-3486	35	14	.	.	PUNCT
cana-3486	36	1	it	it	PRON
cana-3486	36	2	includes	include	VERB
cana-3486	36	3	high	high	ADJ
cana-3486	36	4	-	-	PUNCT
cana-3486	36	5	resolution	resolution	NOUN
cana-3486	36	6	images	image	NOUN
cana-3486	36	7	of	of	ADP
cana-3486	36	8	cassava	cassava	NOUN
cana-3486	36	9	leaves	leave	NOUN
cana-3486	36	10	labelled	label	VERB
cana-3486	36	11	with	with	ADP
cana-3486	36	12	specific	specific	ADJ
cana-3486	36	13	types	type	NOUN
cana-3486	36	14	of	of	ADP
cana-3486	36	15	diseases	disease	NOUN
cana-3486	36	16	.	.	PUNCT
cana-3486	37	1	(	(	PUNCT
cana-3486	37	2	a	a	X
cana-3486	37	3	)	)	PUNCT
cana-3486	37	4	sample	sample	NOUN
cana-3486	37	5	set	set	VERB
cana-3486	37	6	-1	-1	ADP
cana-3486	37	7	communications	communication	NOUN
cana-3486	37	8	on	on	ADP
cana-3486	37	9	applied	apply	VERB
cana-3486	37	10	nonlinear	nonlinear	ADJ
cana-3486	37	11	analysis	analysis	NOUN
cana-3486	37	12	issn	issn	NOUN
cana-3486	37	13	:	:	PUNCT
cana-3486	37	14	1074	1074	NUM
cana-3486	37	15	-	-	PUNCT
cana-3486	37	16	133x	133x	NUM
cana-3486	37	17	vol	vol	NOUN
cana-3486	37	18	32	32	NUM
cana-3486	37	19	no	no	NOUN
cana-3486	37	20	.	.	PUNCT
cana-3486	38	1	7s	7	NOUN
cana-3486	38	2	(	(	PUNCT
cana-3486	38	3	2025	2025	NUM
cana-3486	38	4	)	)	PUNCT
cana-3486	38	5	790	790	NUM
cana-3486	38	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	38	7	(	(	PUNCT
cana-3486	38	8	b	b	NOUN
cana-3486	38	9	)	)	PUNCT
cana-3486	38	10	sample	sample	NOUN
cana-3486	38	11	set	set	VERB
cana-3486	38	12	-2	-2	INTJ
cana-3486	38	13	figure	figure	NOUN
cana-3486	38	14	1	1	NUM
cana-3486	38	15	dataset	dataset	NOUN
cana-3486	38	16	of	of	ADP
cana-3486	38	17	cassava	cassava	NOUN
cana-3486	38	18	leaves	leave	NOUN
cana-3486	38	19	(	(	PUNCT
cana-3486	38	20	a	a	X
cana-3486	38	21	)	)	PUNCT
cana-3486	38	22	sample	sample	NOUN
cana-3486	38	23	set	set	VERB
cana-3486	38	24	-1	-1	PUNCT
cana-3486	38	25	(	(	PUNCT
cana-3486	38	26	b	b	X
cana-3486	38	27	)	)	PUNCT
cana-3486	38	28	sample	sample	NOUN
cana-3486	38	29	set	set	VERB
cana-3486	38	30	-2	-2	INTJ
cana-3486	38	31	every	every	DET
cana-3486	38	32	image	image	NOUN
cana-3486	38	33	provides	provide	VERB
cana-3486	38	34	complex	complex	ADJ
cana-3486	38	35	visual	visual	ADJ
cana-3486	38	36	clues	clue	NOUN
cana-3486	38	37	that	that	PRON
cana-3486	38	38	aid	aid	NOUN
cana-3486	38	39	in	in	ADP
cana-3486	38	40	the	the	DET
cana-3486	38	41	development	development	NOUN
cana-3486	38	42	of	of	ADP
cana-3486	38	43	machine	machine	NOUN
cana-3486	38	44	-	-	PUNCT
cana-3486	38	45	learning	learn	VERB
cana-3486	38	46	models	model	NOUN
cana-3486	38	47	for	for	ADP
cana-3486	38	48	accurate	accurate	ADJ
cana-3486	38	49	sickness	sickness	NOUN
cana-3486	38	50	identification	identification	NOUN
cana-3486	38	51	,	,	PUNCT
cana-3486	38	52	as	as	SCONJ
cana-3486	38	53	seen	see	VERB
cana-3486	38	54	in	in	ADP
cana-3486	38	55	sample	sample	NOUN
cana-3486	38	56	datasets	dataset	NOUN
cana-3486	38	57	(	(	PUNCT
cana-3486	38	58	a	a	NOUN
cana-3486	38	59	)	)	PUNCT
cana-3486	38	60	,	,	PUNCT
cana-3486	38	61	(	(	PUNCT
cana-3486	38	62	b	b	X
cana-3486	38	63	)	)	PUNCT
cana-3486	38	64	in	in	ADP
cana-3486	38	65	fig	fig	NOUN
cana-3486	38	66	1	1	NUM
cana-3486	38	67	.	.	PUNCT
cana-3486	38	68	data	datum	NOUN
cana-3486	38	69	preprocessing	preprocesse	VERB
cana-3486	38	70	plant	plant	NOUN
cana-3486	38	71	disease	disease	NOUN
cana-3486	38	72	classification	classification	NOUN
cana-3486	38	73	relies	rely	VERB
cana-3486	38	74	heavily	heavily	ADV
cana-3486	38	75	on	on	ADP
cana-3486	38	76	the	the	DET
cana-3486	38	77	preprocessing	preprocessing	NOUN
cana-3486	38	78	of	of	ADP
cana-3486	38	79	the	the	DET
cana-3486	38	80	cassava	cassava	NOUN
cana-3486	38	81	dataset	dataset	VERB
cana-3486	39	1	[	[	PUNCT
cana-3486	39	2	13	13	NUM
cana-3486	39	3	]	]	PUNCT
cana-3486	39	4	.	.	PUNCT
cana-3486	40	1	to	to	PART
cana-3486	40	2	standardize	standardize	VERB
cana-3486	40	3	input	input	NOUN
cana-3486	40	4	for	for	ADP
cana-3486	40	5	the	the	DET
cana-3486	40	6	model	model	NOUN
cana-3486	40	7	,	,	PUNCT
cana-3486	40	8	the	the	DET
cana-3486	40	9	images	image	NOUN
cana-3486	40	10	are	be	AUX
cana-3486	40	11	first	first	ADV
cana-3486	40	12	resized	resize	VERB
cana-3486	40	13	to	to	ADP
cana-3486	40	14	a	a	DET
cana-3486	40	15	consistent	consistent	ADJ
cana-3486	40	16	dimension	dimension	NOUN
cana-3486	40	17	(	(	PUNCT
cana-3486	40	18	e.g.	e.g.	ADV
cana-3486	40	19	,	,	PUNCT
cana-3486	40	20	224x224	224x224	NUM
cana-3486	40	21	pixels	pixel	NOUN
cana-3486	40	22	)	)	PUNCT
cana-3486	40	23	.	.	PUNCT
cana-3486	41	1	after	after	ADP
cana-3486	41	2	that	that	PRON
cana-3486	41	3	,	,	PUNCT
cana-3486	41	4	normalization	normalization	NOUN
cana-3486	41	5	is	be	AUX
cana-3486	41	6	applied	apply	VERB
cana-3486	41	7	to	to	PART
cana-3486	41	8	scale	scale	VERB
cana-3486	41	9	pixel	pixel	ADJ
cana-3486	41	10	values	value	NOUN
cana-3486	41	11	to	to	ADP
cana-3486	41	12	the	the	DET
cana-3486	41	13	range	range	NOUN
cana-3486	41	14	of	of	ADP
cana-3486	41	15	[	[	X
cana-3486	41	16	0	0	NUM
cana-3486	41	17	,	,	PUNCT
cana-3486	41	18	1	1	NUM
cana-3486	41	19	]	]	PUNCT
cana-3486	41	20	,	,	PUNCT
cana-3486	41	21	aiding	aid	VERB
cana-3486	41	22	in	in	ADP
cana-3486	41	23	training	training	NOUN
cana-3486	41	24	convergence	convergence	NOUN
cana-3486	41	25	.	.	PUNCT
cana-3486	42	1	data	datum	NOUN
cana-3486	42	2	augmentation	augmentation	NOUN
cana-3486	42	3	techniques	technique	NOUN
cana-3486	42	4	,	,	PUNCT
cana-3486	42	5	such	such	ADJ
cana-3486	42	6	as	as	ADP
cana-3486	42	7	rotation	rotation	NOUN
cana-3486	42	8	,	,	PUNCT
cana-3486	42	9	flipping	flipping	NOUN
cana-3486	42	10	,	,	PUNCT
cana-3486	42	11	and	and	CCONJ
cana-3486	42	12	brightness	brightness	NOUN
cana-3486	42	13	adjustment	adjustment	NOUN
cana-3486	42	14	,	,	PUNCT
cana-3486	42	15	are	be	AUX
cana-3486	42	16	employed	employ	VERB
cana-3486	42	17	to	to	PART
cana-3486	42	18	improve	improve	VERB
cana-3486	42	19	dataset	dataset	ADJ
cana-3486	42	20	diversity	diversity	NOUN
cana-3486	42	21	and	and	CCONJ
cana-3486	42	22	reduce	reduce	VERB
cana-3486	42	23	overfitting	overfitte	VERB
cana-3486	42	24	[	[	X
cana-3486	42	25	17	17	NUM
cana-3486	42	26	]	]	PUNCT
cana-3486	42	27	.	.	PUNCT
cana-3486	43	1	additionally	additionally	ADV
cana-3486	43	2	,	,	PUNCT
cana-3486	43	3	images	image	NOUN
cana-3486	43	4	may	may	AUX
cana-3486	43	5	be	be	AUX
cana-3486	43	6	filtered	filter	VERB
cana-3486	43	7	to	to	PART
cana-3486	43	8	reduce	reduce	VERB
cana-3486	43	9	noise	noise	NOUN
cana-3486	43	10	or	or	CCONJ
cana-3486	43	11	unnecessary	unnecessary	ADJ
cana-3486	43	12	background	background	NOUN
cana-3486	43	13	elements	element	NOUN
cana-3486	43	14	,	,	PUNCT
cana-3486	43	15	ensuring	ensure	VERB
cana-3486	43	16	that	that	SCONJ
cana-3486	43	17	the	the	DET
cana-3486	43	18	model	model	NOUN
cana-3486	43	19	focuses	focus	VERB
cana-3486	43	20	on	on	ADP
cana-3486	43	21	the	the	DET
cana-3486	43	22	key	key	ADJ
cana-3486	43	23	aspects	aspect	NOUN
cana-3486	43	24	of	of	ADP
cana-3486	43	25	the	the	DET
cana-3486	43	26	cassava	cassava	NOUN
cana-3486	43	27	leaves	leave	VERB
cana-3486	43	28	[	[	X
cana-3486	43	29	22	22	NUM
cana-3486	43	30	]	]	PUNCT
cana-3486	43	31	.	.	PUNCT
cana-3486	44	1	this	this	DET
cana-3486	44	2	comprehensive	comprehensive	ADJ
cana-3486	44	3	preprocessing	preprocessing	NOUN
cana-3486	44	4	procedure	procedure	NOUN
cana-3486	44	5	optimizes	optimize	VERB
cana-3486	44	6	the	the	DET
cana-3486	44	7	dataset	dataset	NOUN
cana-3486	44	8	for	for	ADP
cana-3486	44	9	subsequent	subsequent	ADJ
cana-3486	44	10	classification	classification	NOUN
cana-3486	44	11	tasks	task	NOUN
cana-3486	44	12	.	.	PUNCT
cana-3486	45	1	figure	figure	NOUN
cana-3486	45	2	2	2	NUM
cana-3486	45	3	flowchart	flowchart	NOUN
cana-3486	45	4	of	of	ADP
cana-3486	45	5	process	process	NOUN
cana-3486	45	6	for	for	ADP
cana-3486	45	7	disease	disease	NOUN
cana-3486	45	8	detection	detection	NOUN
cana-3486	45	9	the	the	DET
cana-3486	45	10	steps	step	NOUN
cana-3486	45	11	involved	involve	VERB
cana-3486	45	12	in	in	ADP
cana-3486	45	13	identifying	identify	VERB
cana-3486	45	14	cassava	cassava	NOUN
cana-3486	45	15	leaf	leaf	NOUN
cana-3486	45	16	disease	disease	NOUN
cana-3486	45	17	are	be	AUX
cana-3486	45	18	depicted	depict	VERB
cana-3486	45	19	in	in	ADP
cana-3486	45	20	fig	fig	NOUN
cana-3486	45	21	.	.	PUNCT
cana-3486	46	1	2	2	NUM
cana-3486	46	2	.	.	NUM
cana-3486	46	3	subsequently	subsequently	ADV
cana-3486	46	4	,	,	PUNCT
cana-3486	46	5	these	these	DET
cana-3486	46	6	features	feature	NOUN
cana-3486	46	7	are	be	AUX
cana-3486	46	8	used	use	VERB
cana-3486	46	9	to	to	PART
cana-3486	46	10	build	build	VERB
cana-3486	46	11	a	a	DET
cana-3486	46	12	machine	machine	NOUN
cana-3486	46	13	learning	learning	NOUN
cana-3486	46	14	model	model	NOUN
cana-3486	46	15	that	that	PRON
cana-3486	46	16	will	will	AUX
cana-3486	46	17	categorize	categorize	VERB
cana-3486	46	18	the	the	DET
cana-3486	46	19	leaves	leave	NOUN
cana-3486	46	20	.	.	PUNCT
cana-3486	47	1	if	if	SCONJ
cana-3486	47	2	a	a	DET
cana-3486	47	3	communications	communication	NOUN
cana-3486	47	4	on	on	ADP
cana-3486	47	5	applied	apply	VERB
cana-3486	47	6	nonlinear	nonlinear	ADJ
cana-3486	47	7	analysis	analysis	NOUN
cana-3486	47	8	issn	issn	NOUN
cana-3486	47	9	:	:	PUNCT
cana-3486	47	10	1074	1074	NUM
cana-3486	47	11	-	-	PUNCT
cana-3486	47	12	133x	133x	NUM
cana-3486	47	13	vol	vol	NOUN
cana-3486	47	14	32	32	NUM
cana-3486	47	15	no	no	NOUN
cana-3486	47	16	.	.	PUNCT
cana-3486	48	1	7s	7	NOUN
cana-3486	48	2	(	(	PUNCT
cana-3486	48	3	2025	2025	NUM
cana-3486	48	4	)	)	PUNCT
cana-3486	48	5	791	791	NUM
cana-3486	48	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	48	7	disease	disease	NOUN
cana-3486	48	8	is	be	AUX
cana-3486	48	9	present	present	ADJ
cana-3486	48	10	,	,	PUNCT
cana-3486	48	11	the	the	DET
cana-3486	48	12	model	model	NOUN
cana-3486	48	13	determines	determine	VERB
cana-3486	48	14	what	what	DET
cana-3486	48	15	kind	kind	NOUN
cana-3486	48	16	of	of	ADP
cana-3486	48	17	sickness	sickness	NOUN
cana-3486	48	18	it	it	PRON
cana-3486	48	19	is	be	AUX
cana-3486	48	20	and	and	CCONJ
cana-3486	48	21	predicts	predict	NOUN
cana-3486	48	22	if	if	SCONJ
cana-3486	48	23	the	the	DET
cana-3486	48	24	leaf	leaf	NOUN
cana-3486	48	25	will	will	AUX
cana-3486	48	26	be	be	AUX
cana-3486	48	27	sick	sick	ADJ
cana-3486	48	28	or	or	CCONJ
cana-3486	48	29	healthy	healthy	ADJ
cana-3486	48	30	.	.	PUNCT
cana-3486	49	1	algorithms	algorithm	NOUN
cana-3486	49	2	a	a	DET
cana-3486	49	3	plant	plant	NOUN
cana-3486	49	4	disease	disease	NOUN
cana-3486	49	5	detection	detection	NOUN
cana-3486	49	6	algorithm	algorithm	NOUN
cana-3486	49	7	is	be	AUX
cana-3486	49	8	a	a	DET
cana-3486	49	9	computational	computational	ADJ
cana-3486	49	10	process	process	NOUN
cana-3486	49	11	used	use	VERB
cana-3486	49	12	to	to	PART
cana-3486	49	13	automatically	automatically	ADV
cana-3486	49	14	detect	detect	VERB
cana-3486	49	15	and	and	CCONJ
cana-3486	49	16	categorize	categorize	VERB
cana-3486	49	17	plant	plant	NOUN
cana-3486	49	18	illnesses	illness	NOUN
cana-3486	49	19	by	by	ADP
cana-3486	49	20	examining	examine	VERB
cana-3486	49	21	photos	photo	NOUN
cana-3486	49	22	of	of	ADP
cana-3486	49	23	leaves	leave	NOUN
cana-3486	49	24	,	,	PUNCT
cana-3486	49	25	stems	stem	NOUN
cana-3486	49	26	,	,	PUNCT
cana-3486	49	27	or	or	CCONJ
cana-3486	49	28	other	other	ADJ
cana-3486	49	29	plant	plant	NOUN
cana-3486	49	30	components	component	NOUN
cana-3486	49	31	[	[	X
cana-3486	49	32	19	19	NUM
cana-3486	49	33	]	]	PUNCT
cana-3486	49	34	.	.	PUNCT
cana-3486	50	1	these	these	DET
cana-3486	50	2	algorithms	algorithm	NOUN
cana-3486	50	3	look	look	VERB
cana-3486	50	4	for	for	ADP
cana-3486	50	5	patterns	pattern	NOUN
cana-3486	50	6	that	that	PRON
cana-3486	50	7	indicate	indicate	VERB
cana-3486	50	8	disease	disease	NOUN
cana-3486	50	9	using	use	VERB
cana-3486	50	10	machine	machine	NOUN
cana-3486	50	11	learning	learning	NOUN
cana-3486	50	12	,	,	PUNCT
cana-3486	50	13	deep	deep	ADJ
cana-3486	50	14	learning	learning	NOUN
cana-3486	50	15	,	,	PUNCT
cana-3486	50	16	or	or	CCONJ
cana-3486	50	17	conventional	conventional	ADJ
cana-3486	50	18	image	image	NOUN
cana-3486	50	19	processing	processing	NOUN
cana-3486	50	20	methods	method	NOUN
cana-3486	50	21	.	.	PUNCT
cana-3486	51	1	several	several	ADJ
cana-3486	51	2	methods	method	NOUN
cana-3486	51	3	have	have	AUX
cana-3486	51	4	been	be	AUX
cana-3486	51	5	used	use	VERB
cana-3486	51	6	to	to	PART
cana-3486	51	7	identify	identify	VERB
cana-3486	51	8	cassava	cassava	NOUN
cana-3486	51	9	disease	disease	NOUN
cana-3486	51	10	,	,	PUNCT
cana-3486	51	11	taking	take	VERB
cana-3486	51	12	advantage	advantage	NOUN
cana-3486	51	13	of	of	ADP
cana-3486	51	14	advancements	advancement	NOUN
cana-3486	51	15	in	in	ADP
cana-3486	51	16	image	image	NOUN
cana-3486	51	17	processing	processing	NOUN
cana-3486	51	18	and	and	CCONJ
cana-3486	51	19	machine	machine	NOUN
cana-3486	51	20	learning	learn	VERB
cana-3486	51	21	[	[	X
cana-3486	51	22	21	21	NUM
cana-3486	51	23	]	]	PUNCT
cana-3486	51	24	.	.	PUNCT
cana-3486	52	1	convolutional	convolutional	ADJ
cana-3486	52	2	neural	neural	ADJ
cana-3486	52	3	networks	network	NOUN
cana-3486	52	4	(	(	PUNCT
cana-3486	52	5	cnns	cnns	PROPN
cana-3486	52	6	)	)	PUNCT
cana-3486	52	7	are	be	AUX
cana-3486	52	8	at	at	ADP
cana-3486	52	9	the	the	DET
cana-3486	52	10	forefront	forefront	NOUN
cana-3486	52	11	when	when	SCONJ
cana-3486	52	12	it	it	PRON
cana-3486	52	13	comes	come	VERB
cana-3486	52	14	to	to	ADP
cana-3486	52	15	automatically	automatically	ADV
cana-3486	52	16	extracting	extract	VERB
cana-3486	52	17	spatial	spatial	ADJ
cana-3486	52	18	characteristics	characteristic	NOUN
cana-3486	52	19	from	from	ADP
cana-3486	52	20	leaf	leaf	NOUN
cana-3486	52	21	images	image	NOUN
cana-3486	52	22	to	to	PART
cana-3486	52	23	identify	identify	VERB
cana-3486	52	24	disease	disease	NOUN
cana-3486	52	25	trends	trend	NOUN
cana-3486	52	26	.	.	PUNCT
cana-3486	53	1	strong	strong	ADJ
cana-3486	53	2	classification	classification	NOUN
cana-3486	53	3	capabilities	capability	NOUN
cana-3486	53	4	are	be	AUX
cana-3486	53	5	provided	provide	VERB
cana-3486	53	6	by	by	ADP
cana-3486	53	7	random	random	ADJ
cana-3486	53	8	forest	forest	NOUN
cana-3486	53	9	methods	method	NOUN
cana-3486	53	10	and	and	CCONJ
cana-3486	53	11	support	support	VERB
cana-3486	53	12	vector	vector	NOUN
cana-3486	53	13	machines	machine	NOUN
cana-3486	53	14	(	(	PUNCT
cana-3486	53	15	svms	svms	NOUN
cana-3486	53	16	)	)	PUNCT
cana-3486	53	17	,	,	PUNCT
cana-3486	53	18	which	which	PRON
cana-3486	53	19	generate	generate	VERB
cana-3486	53	20	decision	decision	NOUN
cana-3486	53	21	boundaries	boundary	NOUN
cana-3486	53	22	and	and	CCONJ
cana-3486	53	23	combine	combine	VERB
cana-3486	53	24	predictions	prediction	NOUN
cana-3486	53	25	from	from	ADP
cana-3486	53	26	several	several	ADJ
cana-3486	53	27	decision	decision	NOUN
cana-3486	53	28	trees	tree	NOUN
cana-3486	53	29	,	,	PUNCT
cana-3486	53	30	respectively	respectively	ADV
cana-3486	53	31	[	[	X
cana-3486	53	32	8	8	NUM
cana-3486	53	33	]	]	PUNCT
cana-3486	53	34	.	.	PUNCT
cana-3486	54	1	furthermore	furthermore	ADV
cana-3486	54	2	,	,	PUNCT
cana-3486	54	3	k	k	X
cana-3486	54	4	-	-	PUNCT
cana-3486	54	5	nearest	near	ADJ
cana-3486	54	6	neighbors	neighbor	NOUN
cana-3486	54	7	(	(	PUNCT
cana-3486	54	8	knn	knn	PROPN
cana-3486	54	9	)	)	PUNCT
cana-3486	54	10	offers	offer	VERB
cana-3486	54	11	a	a	DET
cana-3486	54	12	simple	simple	ADJ
cana-3486	54	13	way	way	NOUN
cana-3486	54	14	to	to	PART
cana-3486	54	15	conduct	conduct	VERB
cana-3486	54	16	fast	fast	ADJ
cana-3486	54	17	evaluations	evaluation	NOUN
cana-3486	54	18	based	base	VERB
cana-3486	54	19	on	on	ADP
cana-3486	54	20	proximity	proximity	NOUN
cana-3486	54	21	to	to	ADP
cana-3486	54	22	labelled	label	VERB
cana-3486	54	23	samples	sample	NOUN
cana-3486	54	24	[	[	X
cana-3486	54	25	4	4	NUM
cana-3486	54	26	]	]	PUNCT
cana-3486	54	27	.	.	PUNCT
cana-3486	55	1	deep	deep	ADJ
cana-3486	55	2	belief	belief	NOUN
cana-3486	55	3	networks	network	NOUN
cana-3486	55	4	(	(	PUNCT
cana-3486	55	5	dbns	dbns	PROPN
cana-3486	55	6	)	)	PUNCT
cana-3486	55	7	and	and	CCONJ
cana-3486	55	8	gradient	gradient	ADJ
cana-3486	55	9	boosting	boost	VERB
cana-3486	55	10	machines	machine	NOUN
cana-3486	55	11	(	(	PUNCT
cana-3486	55	12	gbm	gbm	NOUN
cana-3486	55	13	)	)	PUNCT
cana-3486	55	14	improve	improve	VERB
cana-3486	55	15	prediction	prediction	NOUN
cana-3486	55	16	accuracy	accuracy	NOUN
cana-3486	55	17	through	through	ADP
cana-3486	55	18	layered	layered	ADJ
cana-3486	55	19	feature	feature	NOUN
cana-3486	55	20	extraction	extraction	NOUN
cana-3486	55	21	or	or	CCONJ
cana-3486	55	22	by	by	ADP
cana-3486	55	23	correcting	correct	VERB
cana-3486	55	24	errors	error	NOUN
cana-3486	55	25	in	in	ADP
cana-3486	55	26	successively	successively	ADV
cana-3486	55	27	constructed	construct	VERB
cana-3486	55	28	trees	tree	NOUN
cana-3486	55	29	.	.	PUNCT
cana-3486	56	1	resnet	resnet	ADJ
cana-3486	56	2	algorithm	algorithm	NOUN
cana-3486	56	3	a	a	DET
cana-3486	56	4	particular	particular	ADJ
cana-3486	56	5	kind	kind	NOUN
cana-3486	56	6	of	of	ADP
cana-3486	56	7	deep	deep	ADJ
cana-3486	56	8	learning	learning	NOUN
cana-3486	56	9	architecture	architecture	NOUN
cana-3486	56	10	called	call	VERB
cana-3486	56	11	resnet	resnet	NOUN
cana-3486	56	12	,	,	PUNCT
cana-3486	56	13	or	or	CCONJ
cana-3486	56	14	residual	residual	ADJ
cana-3486	56	15	network	network	NOUN
cana-3486	56	16	,	,	PUNCT
cana-3486	56	17	was	be	AUX
cana-3486	56	18	created	create	VERB
cana-3486	56	19	to	to	PART
cana-3486	56	20	overcome	overcome	VERB
cana-3486	56	21	the	the	DET
cana-3486	56	22	challenges	challenge	NOUN
cana-3486	56	23	involved	involve	VERB
cana-3486	56	24	in	in	ADP
cana-3486	56	25	training	train	VERB
cana-3486	56	26	extremely	extremely	ADV
cana-3486	56	27	deep	deep	ADJ
cana-3486	56	28	neural	neural	ADJ
cana-3486	56	29	networks	network	NOUN
cana-3486	56	30	[	[	X
cana-3486	56	31	17	17	NUM
cana-3486	56	32	]	]	PUNCT
cana-3486	56	33	.	.	PUNCT
cana-3486	57	1	resnet	resnet	PROPN
cana-3486	57	2	has	have	AUX
cana-3486	57	3	established	establish	VERB
cana-3486	57	4	itself	itself	PRON
cana-3486	57	5	as	as	ADP
cana-3486	57	6	a	a	DET
cana-3486	57	7	foundational	foundational	ADJ
cana-3486	57	8	model	model	NOUN
cana-3486	57	9	in	in	ADP
cana-3486	57	10	the	the	DET
cana-3486	57	11	field	field	NOUN
cana-3486	57	12	of	of	ADP
cana-3486	57	13	computer	computer	NOUN
cana-3486	57	14	vision	vision	NOUN
cana-3486	57	15	,	,	PUNCT
cana-3486	57	16	especially	especially	ADV
cana-3486	57	17	for	for	ADP
cana-3486	57	18	tasks	task	NOUN
cana-3486	57	19	like	like	ADP
cana-3486	57	20	semantic	semantic	ADJ
cana-3486	57	21	segmentation	segmentation	NOUN
cana-3486	57	22	,	,	PUNCT
cana-3486	57	23	object	object	NOUN
cana-3486	57	24	detection	detection	NOUN
cana-3486	57	25	,	,	PUNCT
cana-3486	57	26	and	and	CCONJ
cana-3486	57	27	image	image	NOUN
cana-3486	57	28	classification	classification	NOUN
cana-3486	57	29	.	.	PUNCT
cana-3486	58	1	because	because	SCONJ
cana-3486	58	2	it	it	PRON
cana-3486	58	3	can	can	AUX
cana-3486	58	4	learn	learn	VERB
cana-3486	58	5	complex	complex	ADJ
cana-3486	58	6	features	feature	NOUN
cana-3486	58	7	and	and	CCONJ
cana-3486	58	8	address	address	VERB
cana-3486	58	9	fundamental	fundamental	ADJ
cana-3486	58	10	deep	deep	ADJ
cana-3486	58	11	learning	learning	NOUN
cana-3486	58	12	issues	issue	NOUN
cana-3486	58	13	like	like	ADP
cana-3486	58	14	the	the	DET
cana-3486	58	15	vanishing	vanish	VERB
cana-3486	58	16	gradient	gradient	NOUN
cana-3486	58	17	problem	problem	NOUN
cana-3486	58	18	,	,	PUNCT
cana-3486	58	19	the	the	DET
cana-3486	58	20	resnet	resnet	NOUN
cana-3486	58	21	algorithm	algorithm	NOUN
cana-3486	58	22	is	be	AUX
cana-3486	58	23	unique	unique	ADJ
cana-3486	58	24	in	in	ADP
cana-3486	58	25	the	the	DET
cana-3486	58	26	field	field	NOUN
cana-3486	58	27	of	of	ADP
cana-3486	58	28	cassava	cassava	NOUN
cana-3486	58	29	disease	disease	NOUN
cana-3486	58	30	detection	detection	NOUN
cana-3486	58	31	.	.	PUNCT
cana-3486	59	1	in	in	ADP
cana-3486	59	2	contrast	contrast	NOUN
cana-3486	59	3	to	to	ADP
cana-3486	59	4	conventional	conventional	ADJ
cana-3486	59	5	algorithms	algorithm	NOUN
cana-3486	59	6	,	,	PUNCT
cana-3486	59	7	which	which	PRON
cana-3486	59	8	may	may	AUX
cana-3486	59	9	struggle	struggle	VERB
cana-3486	59	10	to	to	PART
cana-3486	59	11	extract	extract	VERB
cana-3486	59	12	features	feature	NOUN
cana-3486	59	13	from	from	ADP
cana-3486	59	14	deeper	deep	ADJ
cana-3486	59	15	networks	network	NOUN
cana-3486	59	16	,	,	PUNCT
cana-3486	59	17	resnet	resnet	NOUN
cana-3486	59	18	employs	employ	VERB
cana-3486	59	19	residual	residual	ADJ
cana-3486	59	20	connections	connection	NOUN
cana-3486	59	21	that	that	PRON
cana-3486	59	22	facilitate	facilitate	VERB
cana-3486	59	23	the	the	DET
cana-3486	59	24	easier	easy	ADJ
cana-3486	59	25	flow	flow	NOUN
cana-3486	59	26	of	of	ADP
cana-3486	59	27	gradients	gradient	NOUN
cana-3486	59	28	during	during	ADP
cana-3486	59	29	training	training	NOUN
cana-3486	59	30	[	[	X
cana-3486	59	31	1	1	NUM
cana-3486	59	32	]	]	PUNCT
cana-3486	59	33	.	.	PUNCT
cana-3486	60	1	with	with	ADP
cana-3486	60	2	this	this	DET
cana-3486	60	3	architecture	architecture	NOUN
cana-3486	60	4	,	,	PUNCT
cana-3486	60	5	the	the	DET
cana-3486	60	6	model	model	NOUN
cana-3486	60	7	can	can	AUX
cana-3486	60	8	identify	identify	VERB
cana-3486	60	9	more	more	ADV
cana-3486	60	10	intricate	intricate	ADJ
cana-3486	60	11	patterns	pattern	NOUN
cana-3486	60	12	from	from	ADP
cana-3486	60	13	images	image	NOUN
cana-3486	60	14	of	of	ADP
cana-3486	60	15	cassava	cassava	NOUN
cana-3486	60	16	leaves	leave	NOUN
cana-3486	60	17	,	,	PUNCT
cana-3486	60	18	improving	improve	VERB
cana-3486	60	19	its	its	PRON
cana-3486	60	20	ability	ability	NOUN
cana-3486	60	21	to	to	PART
cana-3486	60	22	distinguish	distinguish	VERB
cana-3486	60	23	between	between	ADP
cana-3486	60	24	healthy	healthy	ADJ
cana-3486	60	25	and	and	CCONJ
cana-3486	60	26	diseased	diseased	ADJ
cana-3486	60	27	leaves	leave	NOUN
cana-3486	60	28	.	.	PUNCT
cana-3486	61	1	additionally	additionally	ADV
cana-3486	61	2	,	,	PUNCT
cana-3486	61	3	resnet	resnet	NOUN
cana-3486	61	4	can	can	AUX
cana-3486	61	5	leverage	leverage	VERB
cana-3486	61	6	the	the	DET
cana-3486	61	7	knowledge	knowledge	NOUN
cana-3486	61	8	it	it	PRON
cana-3486	61	9	has	have	AUX
cana-3486	61	10	gained	gain	VERB
cana-3486	61	11	from	from	ADP
cana-3486	61	12	large	large	ADJ
cana-3486	61	13	datasets	dataset	NOUN
cana-3486	61	14	through	through	ADP
cana-3486	61	15	its	its	PRON
cana-3486	61	16	transfer	transfer	NOUN
cana-3486	61	17	learning	learning	NOUN
cana-3486	61	18	capability	capability	NOUN
cana-3486	61	19	,	,	PUNCT
cana-3486	61	20	which	which	PRON
cana-3486	61	21	is	be	AUX
cana-3486	61	22	particularly	particularly	ADV
cana-3486	61	23	useful	useful	ADJ
cana-3486	61	24	when	when	SCONJ
cana-3486	61	25	working	work	VERB
cana-3486	61	26	with	with	ADP
cana-3486	61	27	smaller	small	ADJ
cana-3486	61	28	datasets	dataset	NOUN
cana-3486	61	29	.	.	PUNCT
cana-3486	62	1	figure	figure	VERB
cana-3486	62	2	3	3	NUM
cana-3486	62	3	architecture	architecture	NOUN
cana-3486	62	4	of	of	ADP
cana-3486	62	5	resnet	resnet	ADJ
cana-3486	62	6	50	50	NUM
cana-3486	62	7	algorithm	algorithm	NOUN
cana-3486	62	8	communications	communication	NOUN
cana-3486	62	9	on	on	ADP
cana-3486	62	10	applied	apply	VERB
cana-3486	62	11	nonlinear	nonlinear	ADJ
cana-3486	62	12	analysis	analysis	NOUN
cana-3486	62	13	issn	issn	NOUN
cana-3486	62	14	:	:	PUNCT
cana-3486	62	15	1074	1074	NUM
cana-3486	62	16	-	-	PUNCT
cana-3486	62	17	133x	133x	NUM
cana-3486	62	18	vol	vol	NOUN
cana-3486	62	19	32	32	NUM
cana-3486	62	20	no	no	NOUN
cana-3486	62	21	.	.	PUNCT
cana-3486	63	1	7s	7	NOUN
cana-3486	63	2	(	(	PUNCT
cana-3486	63	3	2025	2025	NUM
cana-3486	63	4	)	)	PUNCT
cana-3486	63	5	792	792	NUM
cana-3486	63	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	63	7	with	with	ADP
cana-3486	63	8	many	many	ADJ
cana-3486	63	9	residual	residual	ADJ
cana-3486	63	10	blocks	block	NOUN
cana-3486	63	11	,	,	PUNCT
cana-3486	63	12	the	the	DET
cana-3486	63	13	network	network	NOUN
cana-3486	63	14	may	may	AUX
cana-3486	63	15	effectively	effectively	ADV
cana-3486	63	16	acquire	acquire	VERB
cana-3486	63	17	deeper	deep	ADJ
cana-3486	63	18	features	feature	NOUN
cana-3486	63	19	,	,	PUNCT
cana-3486	63	20	which	which	PRON
cana-3486	63	21	is	be	AUX
cana-3486	63	22	apparent	apparent	ADJ
cana-3486	63	23	in	in	ADP
cana-3486	63	24	fig	fig	NOUN
cana-3486	63	25	.	.	PUNCT
cana-3486	63	26	3	3	NUM
cana-3486	63	27	for	for	ADP
cana-3486	63	28	challenging	challenging	ADJ
cana-3486	63	29	tasks	task	NOUN
cana-3486	63	30	like	like	ADP
cana-3486	63	31	picture	picture	NOUN
cana-3486	63	32	categorization	categorization	NOUN
cana-3486	63	33	.	.	PUNCT
cana-3486	64	1	implementation	implementation	NOUN
cana-3486	64	2	of	of	ADP
cana-3486	64	3	resnet	resnet	ADJ
cana-3486	64	4	50	50	NUM
cana-3486	64	5	algorithm	algorithm	NOUN
cana-3486	64	6	resnet-50	resnet-50	PROPN
cana-3486	64	7	,	,	PUNCT
cana-3486	64	8	a	a	DET
cana-3486	64	9	well	well	ADV
cana-3486	64	10	-	-	PUNCT
cana-3486	64	11	known	know	VERB
cana-3486	64	12	deep	deep	ADJ
cana-3486	64	13	learning	learning	NOUN
cana-3486	64	14	architecture	architecture	NOUN
cana-3486	64	15	,	,	PUNCT
cana-3486	64	16	can	can	AUX
cana-3486	64	17	effectively	effectively	ADV
cana-3486	64	18	learn	learn	VERB
cana-3486	64	19	complicated	complicated	ADJ
cana-3486	64	20	characteristics	characteristic	NOUN
cana-3486	64	21	through	through	ADP
cana-3486	64	22	residual	residual	ADJ
cana-3486	64	23	learning	learning	NOUN
cana-3486	64	24	,	,	PUNCT
cana-3486	64	25	it	it	PRON
cana-3486	64	26	provides	provide	VERB
cana-3486	64	27	a	a	DET
cana-3486	64	28	potent	potent	ADJ
cana-3486	64	29	solution	solution	NOUN
cana-3486	64	30	for	for	ADP
cana-3486	64	31	cassava	cassava	NOUN
cana-3486	64	32	disease	disease	NOUN
cana-3486	64	33	detection	detection	NOUN
cana-3486	64	34	[	[	X
cana-3486	64	35	2	2	NUM
cana-3486	64	36	]	]	PUNCT
cana-3486	64	37	.	.	PUNCT
cana-3486	65	1	to	to	PART
cana-3486	65	2	guarantee	guarantee	VERB
cana-3486	65	3	consistency	consistency	NOUN
cana-3486	65	4	and	and	CCONJ
cana-3486	65	5	improve	improve	VERB
cana-3486	65	6	the	the	DET
cana-3486	65	7	dataset	dataset	NOUN
cana-3486	65	8	,	,	PUNCT
cana-3486	65	9	the	the	DET
cana-3486	65	10	following	follow	VERB
cana-3486	65	11	preprocessing	preprocesse	VERB
cana-3486	65	12	tasks	task	NOUN
cana-3486	65	13	must	must	AUX
cana-3486	65	14	be	be	AUX
cana-3486	65	15	completed	complete	VERB
cana-3486	65	16	before	before	ADP
cana-3486	65	17	training	train	VERB
cana-3486	65	18	the	the	DET
cana-3486	65	19	resnet-50	resnet-50	PROPN
cana-3486	65	20	model	model	NOUN
cana-3486	65	21	:	:	PUNCT
cana-3486	65	22	resizing	resizing	NOUN
cana-3486	65	23	:	:	PUNCT
cana-3486	65	24	to	to	PART
cana-3486	65	25	ensure	ensure	VERB
cana-3486	65	26	equal	equal	ADJ
cana-3486	65	27	input	input	NOUN
cana-3486	65	28	size	size	NOUN
cana-3486	65	29	,	,	PUNCT
cana-3486	65	30	as	as	SCONJ
cana-3486	65	31	stated	state	VERB
cana-3486	65	32	in	in	ADP
cana-3486	65	33	eq(1	eq(1	PROPN
cana-3486	65	34	)	)	PUNCT
cana-3486	65	35	,	,	PUNCT
cana-3486	65	36	each	each	DET
cana-3486	65	37	picture	picture	NOUN
cana-3486	65	38	d	d	NOUN
cana-3486	65	39	in	in	ADP
cana-3486	65	40	the	the	DET
cana-3486	65	41	dataset	dataset	NOUN
cana-3486	65	42	is	be	AUX
cana-3486	65	43	scaled	scale	VERB
cana-3486	65	44	using	use	VERB
cana-3486	65	45	the	the	DET
cana-3486	65	46	interpolation	interpolation	NOUN
cana-3486	65	47	function	function	NOUN
cana-3486	65	48	size	size	NOUN
cana-3486	65	49	(	(	PUNCT
cana-3486	65	50	)	)	PUNCT
cana-3486	65	51	to	to	ADP
cana-3486	65	52	a	a	DET
cana-3486	65	53	given	give	VERB
cana-3486	65	54	dimension	dimension	NOUN
cana-3486	66	1	i×j	i×j	PROPN
cana-3486	66	2	(	(	PUNCT
cana-3486	66	3	e.g.	e.g.	ADV
cana-3486	66	4	,	,	PUNCT
cana-3486	66	5	224x224	224x224	NUM
cana-3486	66	6	pixels	pixel	NOUN
cana-3486	66	7	)	)	PUNCT
cana-3486	66	8	.	.	PUNCT
cana-3486	67	1	d	d	X
cana-3486	67	2	’	'	PUNCT
cana-3486	67	3	=	=	SYM
cana-3486	67	4	size(d	size(d	PROPN
cana-3486	67	5	,	,	PUNCT
cana-3486	67	6	i	i	PRON
cana-3486	67	7	,	,	PUNCT
cana-3486	67	8	j	j	PROPN
cana-3486	67	9	)	)	PUNCT
cana-3486	67	10	(	(	PUNCT
cana-3486	67	11	1	1	X
cana-3486	67	12	)	)	PUNCT
cana-3486	67	13	where	where	SCONJ
cana-3486	67	14	:	:	PUNCT
cana-3486	67	15	•	•	X
cana-3486	67	16	d	d	NOUN
cana-3486	67	17	is	be	AUX
cana-3486	67	18	the	the	DET
cana-3486	67	19	original	original	ADJ
cana-3486	67	20	image	image	NOUN
cana-3486	67	21	with	with	ADP
cana-3486	67	22	dimensions	dimension	NOUN
cana-3486	67	23	i	i	PRON
cana-3486	67	24	×j	×j	VERB
cana-3486	67	25	,	,	PUNCT
cana-3486	67	26	•	•	CCONJ
cana-3486	67	27	i×j	i×j	ADV
cana-3486	67	28	is	be	AUX
cana-3486	67	29	the	the	DET
cana-3486	67	30	target	target	NOUN
cana-3486	67	31	size	size	NOUN
cana-3486	67	32	(	(	PUNCT
cana-3486	67	33	e.g.	e.g.	ADV
cana-3486	67	34	,	,	PUNCT
cana-3486	67	35	224x224	224x224	NUM
cana-3486	67	36	pixels	pixel	NOUN
cana-3486	67	37	)	)	PUNCT
cana-3486	67	38	,	,	PUNCT
cana-3486	67	39	•	•	NOUN
cana-3486	67	40	d	d	X
cana-3486	67	41	’	'	PUNCT
cana-3486	67	42	is	be	AUX
cana-3486	67	43	the	the	DET
cana-3486	67	44	resized	resize	VERB
cana-3486	67	45	image	image	NOUN
cana-3486	67	46	.	.	PUNCT
cana-3486	68	1	normalisation	normalisation	NOUN
cana-3486	68	2	:	:	PUNCT
cana-3486	68	3	the	the	DET
cana-3486	68	4	pixel	pixel	PROPN
cana-3486	68	5	values	value	NOUN
cana-3486	68	6	of	of	ADP
cana-3486	68	7	each	each	DET
cana-3486	68	8	picture	picture	NOUN
cana-3486	68	9	are	be	AUX
cana-3486	68	10	scaled	scale	VERB
cana-3486	68	11	,	,	PUNCT
cana-3486	68	12	as	as	SCONJ
cana-3486	68	13	stated	state	VERB
cana-3486	68	14	in	in	ADP
cana-3486	68	15	eq	eq	NOUN
cana-3486	68	16	(	(	PUNCT
cana-3486	68	17	2	2	NUM
cana-3486	68	18	)	)	PUNCT
cana-3486	68	19	,	,	PUNCT
cana-3486	68	20	to	to	PART
cana-3486	68	21	fall	fall	VERB
cana-3486	68	22	inside	inside	ADP
cana-3486	68	23	a	a	DET
cana-3486	68	24	specified	specified	ADJ
cana-3486	68	25	range	range	NOUN
cana-3486	68	26	,	,	PUNCT
cana-3486	68	27	typically	typically	ADV
cana-3486	68	28	[	[	X
cana-3486	68	29	0,1	0,1	X
cana-3486	68	30	]	]	PUNCT
cana-3486	69	1	[	[	X
cana-3486	69	2	0,1	0,1	NUM
cana-3486	69	3	]	]	PUNCT
cana-3486	69	4	,	,	PUNCT
cana-3486	69	5	by	by	ADP
cana-3486	69	6	dividing	divide	VERB
cana-3486	69	7	them	they	PRON
cana-3486	69	8	by	by	ADP
cana-3486	69	9	the	the	DET
cana-3486	69	10	maximum	maximum	PROPN
cana-3486	69	11	pixel	pixel	PROPN
cana-3486	69	12	value	value	NOUN
cana-3486	69	13	p_mn	p_mn	PROPN
cana-3486	69	14	that	that	PRON
cana-3486	69	15	may	may	AUX
cana-3486	69	16	be	be	AUX
cana-3486	69	17	produced	produce	VERB
cana-3486	69	18	(	(	PUNCT
cana-3486	69	19	typically	typically	ADV
cana-3486	69	20	255	255	NUM
cana-3486	69	21	for	for	ADP
cana-3486	69	22	8	8	NUM
cana-3486	69	23	-	-	PUNCT
cana-3486	69	24	bit	bit	NOUN
cana-3486	69	25	images	image	NOUN
cana-3486	69	26	):	):	PUNCT
cana-3486	69	27	𝑃𝑚𝑛	𝑃𝑚𝑛	PROPN
cana-3486	69	28	′	′	NUM
cana-3486	69	29	=	=	PUNCT
cana-3486	69	30	𝑝𝑚𝑛	𝑝𝑚𝑛	NOUN
cana-3486	69	31	255	255	NUM
cana-3486	69	32	𝑃𝑚𝑛	𝑃𝑚𝑛	PROPN
cana-3486	69	33	′	′	NUM
cana-3486	69	34	=	=	PUNCT
cana-3486	69	35	normalized	normalize	VERB
cana-3486	69	36	pixel	pixel	PROPN
cana-3486	69	37	value	value	NOUN
cana-3486	69	38	(	(	PUNCT
cana-3486	69	39	2	2	NUM
cana-3486	69	40	)	)	PUNCT
cana-3486	69	41	data	datum	NOUN
cana-3486	69	42	augmentation	augmentation	NOUN
cana-3486	69	43	:	:	PUNCT
cana-3486	69	44	utilize	utilize	VERB
cana-3486	69	45	the	the	DET
cana-3486	69	46	formula	formula	NOUN
cana-3486	69	47	to	to	PART
cana-3486	69	48	rotate	rotate	VERB
cana-3486	69	49	a	a	DET
cana-3486	69	50	picture	picture	NOUN
cana-3486	69	51	by	by	ADP
cana-3486	69	52	an	an	DET
cana-3486	69	53	angle	angle	NOUN
cana-3486	69	54	𝜃	𝜃	NOUN
cana-3486	69	55	,	,	PUNCT
cana-3486	69	56	as	as	SCONJ
cana-3486	69	57	stated	state	VERB
cana-3486	69	58	in	in	ADP
cana-3486	69	59	eq	eq	NOUN
cana-3486	69	60	(	(	PUNCT
cana-3486	69	61	3	3	NUM
cana-3486	69	62	)	)	PUNCT
cana-3486	69	63	,	,	PUNCT
cana-3486	69	64	to	to	PART
cana-3486	69	65	apply	apply	VERB
cana-3486	69	66	arbitrary	arbitrary	ADJ
cana-3486	69	67	rotations	rotation	NOUN
cana-3486	69	68	to	to	ADP
cana-3486	69	69	images	image	NOUN
cana-3486	69	70	for	for	ADP
cana-3486	69	71	augmentation	augmentation	NOUN
cana-3486	69	72	.	.	PUNCT
cana-3486	70	1	(	(	PUNCT
cana-3486	70	2	𝑞′	𝑞′	NOUN
cana-3486	70	3	𝑝′	𝑝′	NUM
cana-3486	70	4	)	)	PUNCT
cana-3486	70	5	=	=	PRON
cana-3486	70	6	(	(	PUNCT
cana-3486	70	7	𝑐𝑜𝑠(𝜃	𝑐𝑜𝑠(𝜃	NOUN
cana-3486	70	8	)	)	PUNCT
cana-3486	71	1	−	−	PROPN
cana-3486	72	1	𝑠𝑖𝑛(𝜃	𝑠𝑖𝑛(𝜃	PROPN
cana-3486	72	2	)	)	PUNCT
cana-3486	72	3	𝑠𝑖𝑛(𝜃	𝑠𝑖𝑛(𝜃	PROPN
cana-3486	72	4	)	)	PUNCT
cana-3486	72	5	𝑐𝑜𝑠(𝜃	𝑐𝑜𝑠(𝜃	NOUN
cana-3486	72	6	)	)	PUNCT
cana-3486	72	7	)	)	PUNCT
cana-3486	73	1	(	(	PUNCT
cana-3486	73	2	𝑞	𝑞	PROPN
cana-3486	73	3	𝑝	𝑝	NOUN
cana-3486	73	4	)	)	PUNCT
cana-3486	73	5	(	(	PUNCT
cana-3486	73	6	3	3	X
cana-3486	73	7	)	)	PUNCT
cana-3486	73	8	training	training	NOUN
cana-3486	73	9	model	model	NOUN
cana-3486	73	10	:	:	PUNCT
cana-3486	73	11	the	the	DET
cana-3486	73	12	last	last	ADJ
cana-3486	73	13	layer	layer	NOUN
cana-3486	73	14	of	of	ADP
cana-3486	73	15	the	the	DET
cana-3486	73	16	model	model	NOUN
cana-3486	73	17	is	be	AUX
cana-3486	73	18	altered	alter	VERB
cana-3486	73	19	to	to	PART
cana-3486	73	20	categorise	categorise	VERB
cana-3486	73	21	the	the	DET
cana-3486	73	22	particular	particular	ADJ
cana-3486	73	23	diseases	disease	NOUN
cana-3486	73	24	in	in	ADP
cana-3486	73	25	the	the	DET
cana-3486	73	26	cassava	cassava	NOUN
cana-3486	73	27	dataset	dataset	VERB
cana-3486	73	28	once	once	SCONJ
cana-3486	73	29	it	it	PRON
cana-3486	73	30	has	have	AUX
cana-3486	73	31	been	be	AUX
cana-3486	73	32	trained	train	VERB
cana-3486	73	33	on	on	ADP
cana-3486	73	34	the	the	DET
cana-3486	73	35	prepared	prepare	VERB
cana-3486	73	36	dataset	dataset	NOUN
cana-3486	73	37	.	.	PUNCT
cana-3486	74	1	loss	loss	NOUN
cana-3486	74	2	function	function	NOUN
cana-3486	74	3	:	:	PUNCT
cana-3486	74	4	the	the	DET
cana-3486	74	5	categorical	categorical	ADJ
cana-3486	74	6	cross	cross	ADJ
cana-3486	74	7	-	-	ADJ
cana-3486	74	8	entropy	entropy	ADJ
cana-3486	74	9	loss	loss	NOUN
cana-3486	74	10	function	function	NOUN
cana-3486	74	11	is	be	AUX
cana-3486	74	12	used	use	VERB
cana-3486	74	13	to	to	PART
cana-3486	74	14	calculate	calculate	VERB
cana-3486	74	15	the	the	DET
cana-3486	74	16	degree	degree	NOUN
cana-3486	74	17	to	to	PART
cana-3486	74	18	which	which	PRON
cana-3486	74	19	the	the	DET
cana-3486	74	20	projected	project	VERB
cana-3486	74	21	probability	probability	NOUN
cana-3486	74	22	and	and	CCONJ
cana-3486	74	23	the	the	DET
cana-3486	74	24	actual	actual	ADJ
cana-3486	74	25	target	target	NOUN
cana-3486	74	26	labels	label	NOUN
cana-3486	74	27	,	,	PUNCT
cana-3486	74	28	t	t	PROPN
cana-3486	74	29	,	,	PUNCT
cana-3486	74	30	coincide	coincide	NOUN
cana-3486	74	31	,	,	PUNCT
cana-3486	74	32	as	as	SCONJ
cana-3486	74	33	shown	show	VERB
cana-3486	74	34	in	in	ADP
cana-3486	74	35	eq	eq	NOUN
cana-3486	74	36	(	(	PUNCT
cana-3486	74	37	4	4	NUM
cana-3486	74	38	)	)	PUNCT
cana-3486	74	39	.	.	PUNCT
cana-3486	75	1	for	for	ADP
cana-3486	75	2	a	a	DET
cana-3486	75	3	multi	multi	ADJ
cana-3486	75	4	-	-	ADJ
cana-3486	75	5	class	class	ADJ
cana-3486	75	6	classification	classification	NOUN
cana-3486	75	7	problem	problem	NOUN
cana-3486	75	8	with	with	ADP
cana-3486	75	9	m	m	PROPN
cana-3486	75	10	classes	class	NOUN
cana-3486	75	11	,	,	PUNCT
cana-3486	75	12	the	the	DET
cana-3486	75	13	loss	loss	NOUN
cana-3486	75	14	s	s	VERB
cana-3486	75	15	is	be	AUX
cana-3486	75	16	given	give	VERB
cana-3486	75	17	by	by	ADP
cana-3486	75	18	:	:	PUNCT
cana-3486	75	19	𝑠(𝑡	𝑠(𝑡	PROPN
cana-3486	75	20	,	,	PUNCT
cana-3486	75	21	�	�	PROPN
cana-3486	75	22	̂	̂	NOUN
cana-3486	75	23	�	�	NOUN
cana-3486	75	24	)	)	PUNCT
cana-3486	75	25	=	=	SYM
cana-3486	76	1	−	−	PROPN
cana-3486	76	2	∑	∑	PUNCT
cana-3486	76	3	𝑡𝑚	𝑡𝑚	PROPN
cana-3486	76	4	𝑙𝑜𝑔(	𝑙𝑜𝑔(	PROPN
cana-3486	76	5	�	�	PROPN
cana-3486	76	6	̂	̂	NOUN
cana-3486	76	7	�	�	NOUN
cana-3486	76	8	𝑚	𝑚	NOUN
cana-3486	76	9	)	)	PUNCT
cana-3486	76	10	𝑀	𝑀	PROPN
cana-3486	76	11	𝑚=1	𝑚=1	X
cana-3486	76	12	(	(	PUNCT
cana-3486	76	13	4	4	X
cana-3486	76	14	)	)	PUNCT
cana-3486	76	15	evaluation	evaluation	NOUN
cana-3486	76	16	of	of	ADP
cana-3486	76	17	model	model	NOUN
cana-3486	76	18	:	:	PUNCT
cana-3486	76	19	following	follow	VERB
cana-3486	76	20	training	training	NOUN
cana-3486	76	21	,	,	PUNCT
cana-3486	76	22	the	the	DET
cana-3486	76	23	model	model	NOUN
cana-3486	76	24	's	's	PART
cana-3486	76	25	performance	performance	NOUN
cana-3486	76	26	in	in	ADP
cana-3486	76	27	actual	actual	ADJ
cana-3486	76	28	scenarios	scenario	NOUN
cana-3486	76	29	is	be	AUX
cana-3486	76	30	assessed	assess	VERB
cana-3486	76	31	using	use	VERB
cana-3486	76	32	the	the	DET
cana-3486	76	33	test	test	NOUN
cana-3486	76	34	set	set	NOUN
cana-3486	76	35	.	.	PUNCT
cana-3486	77	1	the	the	DET
cana-3486	77	2	model	model	NOUN
cana-3486	77	3	's	's	PART
cana-3486	77	4	accuracy	accuracy	NOUN
cana-3486	77	5	in	in	ADP
cana-3486	77	6	classifying	classify	VERB
cana-3486	77	7	healthy	healthy	ADJ
cana-3486	77	8	and	and	CCONJ
cana-3486	77	9	diseased	diseased	ADJ
cana-3486	77	10	leaves	leave	NOUN
cana-3486	77	11	is	be	AUX
cana-3486	77	12	evaluated	evaluate	VERB
cana-3486	77	13	using	use	VERB
cana-3486	77	14	metrics	metric	NOUN
cana-3486	77	15	like	like	ADP
cana-3486	77	16	accuracy	accuracy	NOUN
cana-3486	77	17	,	,	PUNCT
cana-3486	77	18	precision	precision	NOUN
cana-3486	77	19	,	,	PUNCT
cana-3486	77	20	recall	recall	NOUN
cana-3486	77	21	,	,	PUNCT
cana-3486	77	22	and	and	CCONJ
cana-3486	77	23	the	the	DET
cana-3486	77	24	f1	f1	NOUN
cana-3486	77	25	-	-	PUNCT
cana-3486	77	26	score	score	NOUN
cana-3486	77	27	.	.	PUNCT
cana-3486	78	1	communications	communication	NOUN
cana-3486	78	2	on	on	ADP
cana-3486	78	3	applied	apply	VERB
cana-3486	78	4	nonlinear	nonlinear	ADJ
cana-3486	78	5	analysis	analysis	NOUN
cana-3486	78	6	issn	issn	NOUN
cana-3486	78	7	:	:	PUNCT
cana-3486	78	8	1074	1074	NUM
cana-3486	78	9	-	-	PUNCT
cana-3486	78	10	133x	133x	NUM
cana-3486	78	11	vol	vol	NOUN
cana-3486	78	12	32	32	NUM
cana-3486	78	13	no	no	NOUN
cana-3486	78	14	.	.	PUNCT
cana-3486	79	1	7s	7	NOUN
cana-3486	79	2	(	(	PUNCT
cana-3486	79	3	2025	2025	NUM
cana-3486	79	4	)	)	PUNCT
cana-3486	79	5	793	793	NUM
cana-3486	79	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	79	7	algorithm	algorithm	NOUN
cana-3486	79	8	:	:	PUNCT
cana-3486	79	9	input	input	NOUN
cana-3486	79	10	:	:	PUNCT
cana-3486	79	11	d_im	d_im	ADJ
cana-3486	79	12	input	input	NOUN
cana-3486	79	13	:	:	PUNCT
cana-3486	79	14	set_i	set_i	ADJ
cana-3486	79	15	output	output	NOUN
cana-3486	79	16	:	:	PUNCT
cana-3486	79	17	result	result	VERB
cana-3486	79	18	1	1	NUM
cana-3486	79	19	:	:	PUNCT
cana-3486	79	20	procedure	procedure	NOUN
cana-3486	79	21	rndetection(d_im	rndetection(d_im	NOUN
cana-3486	79	22	,	,	PUNCT
cana-3486	79	23	set_i	set_i	NUM
cana-3486	79	24	)	)	PUNCT
cana-3486	79	25	2	2	NUM
cana-3486	79	26	:	:	PUNCT
cana-3486	79	27	output	output	NOUN
cana-3486	79	28	vector	vector	NOUN
cana-3486	79	29	's	's	PART
cana-3486	79	30	initial	initial	ADJ
cana-3486	79	31	value	value	NOUN
cana-3486	79	32	is	be	AUX
cana-3486	79	33	an	an	DET
cana-3486	79	34	empty	empty	ADJ
cana-3486	79	35	list	list	NOUN
cana-3486	79	36	with	with	ADP
cana-3486	79	37	d_im	d_im	ADJ
cana-3486	79	38	length	length	NOUN
cana-3486	79	39	.	.	PUNCT
cana-3486	80	1	3	3	NUM
cana-3486	80	2	:	:	PUNCT
cana-3486	80	3	int	int	NOUN
cana-3486	80	4	try[length(d_im	try[length(d_im	PROPN
cana-3486	80	5	)	)	PUNCT
cana-3486	80	6	]	]	PUNCT
cana-3486	80	7	;	;	PUNCT
cana-3486	80	8	4	4	NUM
cana-3486	80	9	:	:	PUNCT
cana-3486	80	10	combine	combine	VERB
cana-3486	80	11	=	=	PUNCT
cana-3486	80	12	random.random	random.random	NOUN
cana-3486	80	13	(	(	PUNCT
cana-3486	80	14	)	)	PUNCT
cana-3486	80	15	5	5	NUM
cana-3486	80	16	:	:	PUNCT
cana-3486	80	17	for	for	ADP
cana-3486	80	18	i	i	PRON
cana-3486	80	19	in	in	ADP
cana-3486	80	20	range(0	range(0	PROPN
cana-3486	80	21	,	,	PUNCT
cana-3486	80	22	length(d_im	length(d_im	NOUN
cana-3486	80	23	)	)	PUNCT
cana-3486	80	24	)	)	PUNCT
cana-3486	80	25	do	do	VERB
cana-3486	80	26	6	6	NUM
cana-3486	80	27	:	:	PUNCT
cana-3486	80	28	combine	combine	VERB
cana-3486	80	29	in	in	ADP
cana-3486	80	30	the	the	DET
cana-3486	80	31	event	event	NOUN
cana-3486	80	32	that	that	SCONJ
cana-3486	80	33	the	the	DET
cana-3486	80	34	random	random	ADJ
cana-3486	80	35	number	number	NOUN
cana-3486	80	36	exceeds	exceed	VERB
cana-3486	80	37	the	the	DET
cana-3486	80	38	combine	combine	NOUN
cana-3486	80	39	constant	constant	ADJ
cana-3486	80	40	7	7	NUM
cana-3486	80	41	:	:	PUNCT
cana-3486	80	42	if	if	SCONJ
cana-3486	80	43	combine	combine	VERB
cana-3486	80	44	>	>	X
cana-3486	80	45	=	=	PUNCT
cana-3486	80	46	combine	combine	NOUN
cana-3486	80	47	_	_	PRON
cana-3486	80	48	part	part	NOUN
cana-3486	80	49	then	then	ADV
cana-3486	80	50	8	8	NUM
cana-3486	80	51	:	:	PUNCT
cana-3486	80	52	try[i	try[i	ADJ
cana-3486	80	53	]	]	PUNCT
cana-3486	80	54	←	←	PROPN
cana-3486	80	55	d_im[i	d_im[i	PROPN
cana-3486	80	56	]	]	PUNCT
cana-3486	80	57	9	9	NUM
cana-3486	80	58	:	:	PUNCT
cana-3486	80	59	else	else	ADV
cana-3486	80	60	10	10	NUM
cana-3486	80	61	:	:	PUNCT
cana-3486	80	62	try[i	try[i	NUM
cana-3486	80	63	]	]	PUNCT
cana-3486	80	64	←	←	PROPN
cana-3486	80	65	set_i[i	set_i[i	PROPN
cana-3486	80	66	]	]	X
cana-3486	80	67	11	11	NUM
cana-3486	80	68	:	:	PUNCT
cana-3486	80	69	s_trial	s_trial	ADJ
cana-3486	80	70	=	=	X
cana-3486	80	71	fitness(try	fitness(try	NOUN
cana-3486	80	72	)	)	PUNCT
cana-3486	80	73	12	12	NUM
cana-3486	80	74	:	:	PUNCT
cana-3486	80	75	s_target	s_target	NOUN
cana-3486	80	76	=	=	SYM
cana-3486	80	77	fitness(d_im	fitness(d_im	NOUN
cana-3486	80	78	)	)	PUNCT
cana-3486	80	79	13	13	NUM
cana-3486	80	80	:	:	PUNCT
cana-3486	81	1	if	if	SCONJ
cana-3486	81	2	s_trial	s_trial	ADJ
cana-3486	81	3	>	>	X
cana-3486	81	4	=	=	SYM
cana-3486	81	5	sc_target	sc_target	NOUN
cana-3486	81	6	then	then	ADV
cana-3486	81	7	14	14	NUM
cana-3486	81	8	:	:	PUNCT
cana-3486	81	9	occupants[j	occupants[j	NUM
cana-3486	81	10	]	]	PUNCT
cana-3486	82	1	=	=	PUNCT
cana-3486	82	2	try	try	VERB
cana-3486	82	3	15	15	NUM
cana-3486	82	4	:	:	PUNCT
cana-3486	82	5	result.append(s_trial	result.append(s_trial	ADJ
cana-3486	82	6	)	)	PUNCT
cana-3486	82	7	16	16	NUM
cana-3486	82	8	:	:	PUNCT
cana-3486	82	9	else	else	ADV
cana-3486	82	10	17	17	NUM
cana-3486	82	11	:	:	PUNCT
cana-3486	82	12	result.append(s_target	result.append(s_target	NOUN
cana-3486	82	13	)	)	PUNCT
cana-3486	82	14	18	18	NUM
cana-3486	82	15	:	:	PUNCT
cana-3486	82	16	return	return	NOUN
cana-3486	82	17	result	result	NOUN
cana-3486	82	18	3	3	NUM
cana-3486	82	19	.	.	NOUN
cana-3486	82	20	results	result	VERB
cana-3486	82	21	the	the	DET
cana-3486	82	22	model	model	NOUN
cana-3486	82	23	demonstrates	demonstrate	VERB
cana-3486	82	24	its	its	PRON
cana-3486	82	25	strongest	strong	ADJ
cana-3486	82	26	performance	performance	NOUN
cana-3486	82	27	when	when	SCONJ
cana-3486	82	28	classifying	classify	VERB
cana-3486	82	29	healthy	healthy	ADJ
cana-3486	82	30	plants	plant	NOUN
cana-3486	82	31	,	,	PUNCT
cana-3486	82	32	achieving	achieve	VERB
cana-3486	82	33	remarkable	remarkable	ADJ
cana-3486	82	34	precision	precision	NOUN
cana-3486	82	35	values	value	NOUN
cana-3486	82	36	of	of	ADP
cana-3486	82	37	95.8	95.8	NUM
cana-3486	82	38	%	%	NOUN
cana-3486	82	39	and	and	CCONJ
cana-3486	82	40	96.3	96.3	NUM
cana-3486	82	41	%	%	NOUN
cana-3486	82	42	,	,	PUNCT
cana-3486	82	43	along	along	ADP
cana-3486	82	44	with	with	ADP
cana-3486	82	45	an	an	DET
cana-3486	82	46	impressive	impressive	ADJ
cana-3486	82	47	accuracy	accuracy	NOUN
cana-3486	82	48	of	of	ADP
cana-3486	82	49	96.5	96.5	NUM
cana-3486	82	50	%	%	NOUN
cana-3486	82	51	.	.	PUNCT
cana-3486	83	1	these	these	DET
cana-3486	83	2	results	result	NOUN
cana-3486	83	3	indicate	indicate	VERB
cana-3486	83	4	the	the	DET
cana-3486	83	5	model	model	NOUN
cana-3486	83	6	's	's	PART
cana-3486	83	7	effectiveness	effectiveness	NOUN
cana-3486	83	8	in	in	ADP
cana-3486	83	9	reliably	reliably	ADV
cana-3486	83	10	identifying	identify	VERB
cana-3486	83	11	healthy	healthy	ADJ
cana-3486	83	12	plants	plant	NOUN
cana-3486	83	13	,	,	PUNCT
cana-3486	83	14	suggesting	suggest	VERB
cana-3486	83	15	that	that	SCONJ
cana-3486	83	16	it	it	PRON
cana-3486	83	17	is	be	AUX
cana-3486	83	18	well	well	ADV
cana-3486	83	19	-	-	PUNCT
cana-3486	83	20	tuned	tune	VERB
cana-3486	83	21	for	for	ADP
cana-3486	83	22	this	this	DET
cana-3486	83	23	category	category	NOUN
cana-3486	83	24	.	.	PUNCT
cana-3486	84	1	conversely	conversely	ADV
cana-3486	84	2	,	,	PUNCT
cana-3486	84	3	the	the	DET
cana-3486	84	4	cassava	cassava	NOUN
cana-3486	84	5	brown	brown	PROPN
cana-3486	84	6	streak	streak	PROPN
cana-3486	84	7	virus	virus	NOUN
cana-3486	84	8	shows	show	VERB
cana-3486	84	9	the	the	DET
cana-3486	84	10	weakest	weak	ADJ
cana-3486	84	11	performance	performance	NOUN
cana-3486	84	12	,	,	PUNCT
cana-3486	84	13	with	with	ADP
cana-3486	84	14	accuracy	accuracy	NOUN
cana-3486	84	15	recorded	record	VERB
cana-3486	84	16	at	at	ADP
cana-3486	84	17	only	only	ADV
cana-3486	84	18	88.7	88.7	NUM
cana-3486	84	19	%	%	NOUN
cana-3486	84	20	and	and	CCONJ
cana-3486	84	21	precision	precision	NOUN
cana-3486	84	22	values	value	NOUN
cana-3486	84	23	of	of	ADP
cana-3486	84	24	87.6	87.6	NUM
cana-3486	84	25	%	%	NOUN
cana-3486	84	26	and	and	CCONJ
cana-3486	84	27	90.8	90.8	NUM
cana-3486	84	28	%	%	NOUN
cana-3486	84	29	.	.	PUNCT
cana-3486	85	1	this	this	DET
cana-3486	85	2	significant	significant	ADJ
cana-3486	85	3	drop	drop	NOUN
cana-3486	85	4	in	in	ADP
cana-3486	85	5	metrics	metric	NOUN
cana-3486	85	6	highlights	highlight	NOUN
cana-3486	85	7	the	the	DET
cana-3486	85	8	challenges	challenge	NOUN
cana-3486	85	9	faced	face	VERB
cana-3486	85	10	by	by	ADP
cana-3486	85	11	the	the	DET
cana-3486	85	12	model	model	NOUN
cana-3486	85	13	in	in	ADP
cana-3486	85	14	accurately	accurately	ADV
cana-3486	85	15	identifying	identify	VERB
cana-3486	85	16	this	this	DET
cana-3486	85	17	disease	disease	NOUN
cana-3486	85	18	,	,	PUNCT
cana-3486	85	19	which	which	PRON
cana-3486	85	20	may	may	AUX
cana-3486	85	21	stem	stem	VERB
cana-3486	85	22	from	from	ADP
cana-3486	85	23	factors	factor	NOUN
cana-3486	85	24	such	such	ADJ
cana-3486	85	25	as	as	ADP
cana-3486	85	26	overlapping	overlap	VERB
cana-3486	85	27	symptoms	symptom	NOUN
cana-3486	85	28	with	with	ADP
cana-3486	85	29	other	other	ADJ
cana-3486	85	30	conditions	condition	NOUN
cana-3486	85	31	or	or	CCONJ
cana-3486	85	32	insufficient	insufficient	ADJ
cana-3486	85	33	training	training	NOUN
cana-3486	85	34	data	datum	NOUN
cana-3486	85	35	.	.	PUNCT
cana-3486	86	1	the	the	DET
cana-3486	86	2	performance	performance	NOUN
cana-3486	86	3	for	for	ADP
cana-3486	86	4	green	green	ADJ
cana-3486	86	5	mite	mite	PROPN
cana-3486	86	6	damage	damage	NOUN
cana-3486	86	7	and	and	CCONJ
cana-3486	86	8	cassava	cassava	NOUN
cana-3486	86	9	mosaic	mosaic	ADJ
cana-3486	86	10	disease	disease	NOUN
cana-3486	86	11	is	be	AUX
cana-3486	86	12	more	more	ADV
cana-3486	86	13	moderate	moderate	ADJ
cana-3486	86	14	,	,	PUNCT
cana-3486	86	15	with	with	ADP
cana-3486	86	16	accuracy	accuracy	NOUN
cana-3486	86	17	levels	level	NOUN
cana-3486	86	18	at	at	ADP
cana-3486	86	19	91.1	91.1	NUM
cana-3486	86	20	%	%	NOUN
cana-3486	86	21	and	and	CCONJ
cana-3486	86	22	92.4	92.4	NUM
cana-3486	86	23	%	%	NOUN
cana-3486	86	24	,	,	PUNCT
cana-3486	86	25	respectively	respectively	ADV
cana-3486	86	26	.	.	PUNCT
cana-3486	87	1	while	while	SCONJ
cana-3486	87	2	these	these	DET
cana-3486	87	3	results	result	NOUN
cana-3486	87	4	are	be	AUX
cana-3486	87	5	respectable	respectable	ADJ
cana-3486	87	6	,	,	PUNCT
cana-3486	87	7	they	they	PRON
cana-3486	87	8	indicate	indicate	VERB
cana-3486	87	9	that	that	SCONJ
cana-3486	87	10	there	there	PRON
cana-3486	87	11	is	be	VERB
cana-3486	87	12	room	room	NOUN
cana-3486	87	13	for	for	ADP
cana-3486	87	14	improvement	improvement	NOUN
cana-3486	87	15	,	,	PUNCT
cana-3486	87	16	especially	especially	ADV
cana-3486	87	17	compared	compare	VERB
cana-3486	87	18	to	to	ADP
cana-3486	87	19	the	the	DET
cana-3486	87	20	performance	performance	NOUN
cana-3486	87	21	on	on	ADP
cana-3486	87	22	healthy	healthy	ADJ
cana-3486	87	23	communications	communication	NOUN
cana-3486	87	24	on	on	ADP
cana-3486	87	25	applied	apply	VERB
cana-3486	87	26	nonlinear	nonlinear	ADJ
cana-3486	87	27	analysis	analysis	NOUN
cana-3486	87	28	issn	issn	NOUN
cana-3486	87	29	:	:	PUNCT
cana-3486	87	30	1074	1074	NUM
cana-3486	87	31	-	-	PUNCT
cana-3486	87	32	133x	133x	NUM
cana-3486	87	33	vol	vol	NOUN
cana-3486	87	34	32	32	NUM
cana-3486	87	35	no	no	NOUN
cana-3486	87	36	.	.	PUNCT
cana-3486	88	1	7s	7	NOUN
cana-3486	88	2	(	(	PUNCT
cana-3486	88	3	2025	2025	NUM
cana-3486	88	4	)	)	PUNCT
cana-3486	88	5	794	794	NUM
cana-3486	88	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	88	7	plants	plant	NOUN
cana-3486	88	8	.	.	PUNCT
cana-3486	89	1	the	the	DET
cana-3486	89	2	precision	precision	NOUN
cana-3486	89	3	values	value	NOUN
cana-3486	89	4	for	for	ADP
cana-3486	89	5	these	these	DET
cana-3486	89	6	two	two	NUM
cana-3486	89	7	categories	category	NOUN
cana-3486	89	8	remain	remain	VERB
cana-3486	89	9	relatively	relatively	ADV
cana-3486	89	10	stable	stable	ADJ
cana-3486	89	11	,	,	PUNCT
cana-3486	89	12	both	both	PRON
cana-3486	89	13	exceeding	exceed	VERB
cana-3486	89	14	89	89	NUM
cana-3486	89	15	%	%	NOUN
cana-3486	89	16	,	,	PUNCT
cana-3486	89	17	suggesting	suggest	VERB
cana-3486	89	18	that	that	SCONJ
cana-3486	89	19	the	the	DET
cana-3486	89	20	model	model	NOUN
cana-3486	89	21	maintains	maintain	VERB
cana-3486	89	22	a	a	DET
cana-3486	89	23	consistent	consistent	ADJ
cana-3486	89	24	ability	ability	NOUN
cana-3486	89	25	to	to	PART
cana-3486	89	26	correctly	correctly	ADV
cana-3486	89	27	identify	identify	VERB
cana-3486	89	28	true	true	ADJ
cana-3486	89	29	positives	positive	NOUN
cana-3486	89	30	among	among	ADP
cana-3486	89	31	these	these	DET
cana-3486	89	32	plant	plant	NOUN
cana-3486	89	33	conditions	condition	NOUN
cana-3486	89	34	.	.	PUNCT
cana-3486	90	1	overall	overall	ADV
cana-3486	90	2	,	,	PUNCT
cana-3486	90	3	while	while	SCONJ
cana-3486	90	4	the	the	DET
cana-3486	90	5	model	model	NOUN
cana-3486	90	6	excels	excel	VERB
cana-3486	90	7	in	in	ADP
cana-3486	90	8	detecting	detect	VERB
cana-3486	90	9	healthy	healthy	ADJ
cana-3486	90	10	plants	plant	NOUN
cana-3486	90	11	,	,	PUNCT
cana-3486	90	12	enhancements	enhancement	NOUN
cana-3486	90	13	are	be	AUX
cana-3486	90	14	necessary	necessary	ADJ
cana-3486	90	15	to	to	PART
cana-3486	90	16	improve	improve	VERB
cana-3486	90	17	the	the	DET
cana-3486	90	18	detection	detection	NOUN
cana-3486	90	19	of	of	ADP
cana-3486	90	20	the	the	DET
cana-3486	90	21	cassava	cassava	NOUN
cana-3486	90	22	brown	brown	PROPN
cana-3486	90	23	streak	streak	PROPN
cana-3486	90	24	virus	virus	NOUN
cana-3486	90	25	,	,	PUNCT
cana-3486	90	26	as	as	ADV
cana-3486	90	27	well	well	ADV
cana-3486	90	28	as	as	ADP
cana-3486	90	29	to	to	PART
cana-3486	90	30	bolster	bolster	VERB
cana-3486	90	31	performance	performance	NOUN
cana-3486	90	32	for	for	ADP
cana-3486	90	33	other	other	ADJ
cana-3486	90	34	diseases	disease	NOUN
cana-3486	90	35	like	like	ADP
cana-3486	90	36	green	green	ADJ
cana-3486	90	37	mite	mite	PROPN
cana-3486	90	38	damage	damage	NOUN
cana-3486	90	39	and	and	CCONJ
cana-3486	90	40	cassava	cassava	NOUN
cana-3486	90	41	mosaic	mosaic	ADJ
cana-3486	90	42	disease	disease	NOUN
cana-3486	90	43	.	.	PUNCT
cana-3486	91	1	these	these	DET
cana-3486	91	2	findings	finding	NOUN
cana-3486	91	3	underscore	underscore	VERB
cana-3486	91	4	the	the	DET
cana-3486	91	5	need	need	NOUN
cana-3486	91	6	for	for	ADP
cana-3486	91	7	ongoing	ongoing	ADJ
cana-3486	91	8	research	research	NOUN
cana-3486	91	9	and	and	CCONJ
cana-3486	91	10	potential	potential	ADJ
cana-3486	91	11	adjustments	adjustment	NOUN
cana-3486	91	12	to	to	ADP
cana-3486	91	13	the	the	DET
cana-3486	91	14	model	model	NOUN
cana-3486	91	15	to	to	PART
cana-3486	91	16	achieve	achieve	VERB
cana-3486	91	17	higher	high	ADJ
cana-3486	91	18	classification	classification	NOUN
cana-3486	91	19	accuracy	accuracy	NOUN
cana-3486	91	20	and	and	CCONJ
cana-3486	91	21	reliability	reliability	NOUN
cana-3486	91	22	across	across	ADP
cana-3486	91	23	all	all	DET
cana-3486	91	24	plant	plant	NOUN
cana-3486	91	25	categories	category	NOUN
cana-3486	91	26	.	.	PUNCT
cana-3486	92	1	table	table	NOUN
cana-3486	92	2	1	1	NUM
cana-3486	92	3	performance	performance	NOUN
cana-3486	92	4	metrics	metric	NOUN
cana-3486	92	5	for	for	ADP
cana-3486	92	6	cassava	cassava	NOUN
cana-3486	92	7	disease	disease	NOUN
cana-3486	92	8	class	class	NOUN
cana-3486	92	9	accuracy	accuracy	NOUN
cana-3486	92	10	(	(	PUNCT
cana-3486	92	11	%	%	INTJ
cana-3486	92	12	)	)	PUNCT
cana-3486	92	13	precision	precision	NOUN
cana-3486	92	14	(	(	PUNCT
cana-3486	92	15	%	%	INTJ
cana-3486	92	16	)	)	PUNCT
cana-3486	92	17	recall	recall	NOUN
cana-3486	92	18	(	(	PUNCT
cana-3486	92	19	%	%	INTJ
cana-3486	92	20	)	)	PUNCT
cana-3486	92	21	cassava	cassava	NOUN
cana-3486	92	22	mosaic	mosaic	ADJ
cana-3486	92	23	disease	disease	NOUN
cana-3486	92	24	92.4	92.4	NUM
cana-3486	92	25	91.6	91.6	NUM
cana-3486	92	26	91.8	91.8	NUM
cana-3486	92	27	cassava	cassava	NOUN
cana-3486	92	28	brown	brown	PROPN
cana-3486	92	29	streak	streak	NOUN
cana-3486	92	30	virus	virus	NOUN
cana-3486	92	31	88.7	88.7	NUM
cana-3486	92	32	87.6	87.6	NUM
cana-3486	92	33	90.8	90.8	NUM
cana-3486	92	34	green	green	ADJ
cana-3486	92	35	mite	mite	PROPN
cana-3486	92	36	damage	damage	NOUN
cana-3486	92	37	91.1	91.1	NUM
cana-3486	92	38	89.9	89.9	NUM
cana-3486	92	39	90.7	90.7	NUM
cana-3486	92	40	healthy	healthy	ADJ
cana-3486	92	41	96.5	96.5	NUM
cana-3486	92	42	95.8	95.8	NUM
cana-3486	92	43	96.3	96.3	NUM
cana-3486	92	44	in	in	ADP
cana-3486	92	45	the	the	DET
cana-3486	92	46	above	above	ADJ
cana-3486	92	47	table	table	NOUN
cana-3486	92	48	1	1	NUM
cana-3486	92	49	,	,	PUNCT
cana-3486	92	50	the	the	DET
cana-3486	92	51	cassava	cassava	NOUN
cana-3486	92	52	brown	brown	PROPN
cana-3486	92	53	streak	streak	NOUN
cana-3486	92	54	virus	virus	NOUN
cana-3486	92	55	has	have	AUX
cana-3486	92	56	the	the	DET
cana-3486	92	57	lowest	low	ADJ
cana-3486	92	58	accuracy	accuracy	NOUN
cana-3486	92	59	(	(	PUNCT
cana-3486	92	60	88.7	88.7	NUM
cana-3486	92	61	%	%	NOUN
cana-3486	92	62	)	)	PUNCT
cana-3486	92	63	among	among	ADP
cana-3486	92	64	the	the	DET
cana-3486	92	65	classification	classification	NOUN
cana-3486	92	66	performance	performance	NOUN
cana-3486	92	67	indicators	indicator	NOUN
cana-3486	92	68	,	,	PUNCT
cana-3486	92	69	highlighting	highlight	VERB
cana-3486	92	70	cassava	cassava	NOUN
cana-3486	92	71	illnesses	illness	NOUN
cana-3486	92	72	and	and	CCONJ
cana-3486	92	73	healthy	healthy	ADJ
cana-3486	92	74	plants	plant	NOUN
cana-3486	92	75	.	.	PUNCT
cana-3486	93	1	healthy	healthy	ADJ
cana-3486	93	2	plants	plant	NOUN
cana-3486	93	3	,	,	PUNCT
cana-3486	93	4	on	on	ADP
cana-3486	93	5	the	the	DET
cana-3486	93	6	other	other	ADJ
cana-3486	93	7	hand	hand	NOUN
cana-3486	93	8	,	,	PUNCT
cana-3486	93	9	attain	attain	VERB
cana-3486	93	10	the	the	DET
cana-3486	93	11	highest	high	ADJ
cana-3486	93	12	levels	level	NOUN
cana-3486	93	13	of	of	ADP
cana-3486	93	14	accuracy	accuracy	NOUN
cana-3486	93	15	(	(	PUNCT
cana-3486	93	16	96.3	96.3	NUM
cana-3486	93	17	%	%	NOUN
cana-3486	93	18	)	)	PUNCT
cana-3486	93	19	and	and	CCONJ
cana-3486	93	20	precision	precision	NOUN
cana-3486	93	21	(	(	PUNCT
cana-3486	93	22	96.5	96.5	NUM
cana-3486	93	23	%	%	NOUN
cana-3486	93	24	)	)	PUNCT
cana-3486	93	25	.	.	PUNCT
cana-3486	94	1	figure	figure	VERB
cana-3486	94	2	4	4	NUM
cana-3486	94	3	combination	combination	NOUN
cana-3486	94	4	chart	chart	NOUN
cana-3486	94	5	depicting	depict	VERB
cana-3486	94	6	activity	activity	NOUN
cana-3486	94	7	measures	measure	NOUN
cana-3486	94	8	the	the	DET
cana-3486	94	9	above	above	ADJ
cana-3486	94	10	fig	fig	NOUN
cana-3486	94	11	4	4	NUM
cana-3486	94	12	,	,	PUNCT
cana-3486	94	13	shows	show	VERB
cana-3486	94	14	the	the	DET
cana-3486	94	15	four	four	NUM
cana-3486	94	16	categories	category	NOUN
cana-3486	94	17	—	—	PUNCT
cana-3486	94	18	cassava	cassava	NOUN
cana-3486	94	19	mosaic	mosaic	ADJ
cana-3486	94	20	disease	disease	NOUN
cana-3486	94	21	,	,	PUNCT
cana-3486	94	22	cassava	cassava	NOUN
cana-3486	94	23	brown	brown	PROPN
cana-3486	94	24	streak	streak	PROPN
cana-3486	94	25	virus	virus	NOUN
cana-3486	94	26	,	,	PUNCT
cana-3486	94	27	green	green	ADJ
cana-3486	94	28	mite	mite	NOUN
cana-3486	94	29	damage	damage	NOUN
cana-3486	94	30	,	,	PUNCT
cana-3486	94	31	and	and	CCONJ
cana-3486	94	32	healthy	healthy	ADJ
cana-3486	94	33	plants	plant	NOUN
cana-3486	94	34	—	—	PUNCT
cana-3486	94	35	accuracy	accuracy	NOUN
cana-3486	94	36	and	and	CCONJ
cana-3486	94	37	two	two	NUM
cana-3486	94	38	precision	precision	NOUN
cana-3486	94	39	measures	measure	NOUN
cana-3486	94	40	are	be	AUX
cana-3486	94	41	available	available	ADJ
cana-3486	94	42	.	.	PUNCT
cana-3486	95	1	cassava	cassava	NOUN
cana-3486	95	2	brown	brown	PROPN
cana-3486	95	3	streak	streak	NOUN
cana-3486	95	4	virus	virus	NOUN
cana-3486	95	5	plants	plant	NOUN
cana-3486	95	6	have	have	VERB
cana-3486	95	7	the	the	DET
cana-3486	95	8	lowest	low	ADJ
cana-3486	95	9	accuracy	accuracy	NOUN
cana-3486	95	10	and	and	CCONJ
cana-3486	95	11	precision	precision	NOUN
cana-3486	95	12	across	across	ADP
cana-3486	95	13	all	all	DET
cana-3486	95	14	measures	measure	NOUN
cana-3486	95	15	,	,	PUNCT
cana-3486	95	16	while	while	SCONJ
cana-3486	95	17	healthy	healthy	ADJ
cana-3486	95	18	plants	plant	NOUN
cana-3486	95	19	have	have	VERB
cana-3486	95	20	the	the	DET
cana-3486	95	21	greatest	great	ADJ
cana-3486	95	22	levels	level	NOUN
cana-3486	95	23	.	.	PUNCT
cana-3486	96	1	the	the	DET
cana-3486	96	2	accuracy	accuracy	NOUN
cana-3486	96	3	measure	measure	NOUN
cana-3486	96	4	(	(	PUNCT
cana-3486	96	5	blue	blue	ADJ
cana-3486	96	6	)	)	PUNCT
cana-3486	96	7	varies	vary	VERB
cana-3486	96	8	more	more	ADJ
cana-3486	96	9	than	than	ADP
cana-3486	96	10	the	the	DET
cana-3486	96	11	precision	precision	NOUN
cana-3486	96	12	meter	meter	NOUN
cana-3486	96	13	(	(	PUNCT
cana-3486	96	14	orange	orange	ADJ
cana-3486	96	15	and	and	CCONJ
cana-3486	96	16	green	green	ADJ
cana-3486	96	17	)	)	PUNCT
cana-3486	96	18	,	,	PUNCT
cana-3486	96	19	which	which	PRON
cana-3486	96	20	are	be	AUX
cana-3486	96	21	similar	similar	ADJ
cana-3486	96	22	in	in	ADP
cana-3486	96	23	all	all	DET
cana-3486	96	24	categories	category	NOUN
cana-3486	96	25	.	.	PUNCT
cana-3486	97	1	communications	communication	NOUN
cana-3486	97	2	on	on	ADP
cana-3486	97	3	applied	apply	VERB
cana-3486	97	4	nonlinear	nonlinear	ADJ
cana-3486	97	5	analysis	analysis	NOUN
cana-3486	97	6	issn	issn	NOUN
cana-3486	97	7	:	:	PUNCT
cana-3486	97	8	1074	1074	NUM
cana-3486	97	9	-	-	PUNCT
cana-3486	97	10	133x	133x	NUM
cana-3486	97	11	vol	vol	NOUN
cana-3486	97	12	32	32	NUM
cana-3486	97	13	no	no	NOUN
cana-3486	97	14	.	.	PUNCT
cana-3486	98	1	7s	7	NOUN
cana-3486	98	2	(	(	PUNCT
cana-3486	98	3	2025	2025	NUM
cana-3486	98	4	)	)	PUNCT
cana-3486	98	5	795	795	NUM
cana-3486	98	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	98	7	figure	figure	NOUN
cana-3486	98	8	5	5	NUM
cana-3486	98	9	accuracy	accuracy	NOUN
cana-3486	98	10	and	and	CCONJ
cana-3486	98	11	precision	precision	NOUN
cana-3486	98	12	(	(	PUNCT
cana-3486	98	13	%	%	INTJ
cana-3486	98	14	)	)	PUNCT
cana-3486	98	15	trends	trend	NOUN
cana-3486	98	16	for	for	ADP
cana-3486	98	17	cassava	cassava	NOUN
cana-3486	98	18	disease	disease	NOUN
cana-3486	98	19	classification	classification	NOUN
cana-3486	98	20	.	.	PUNCT
cana-3486	99	1	in	in	ADP
cana-3486	99	2	the	the	DET
cana-3486	99	3	above	above	ADJ
cana-3486	99	4	fig	fig	NOUN
cana-3486	99	5	5	5	NUM
cana-3486	99	6	,	,	PUNCT
cana-3486	99	7	the	the	DET
cana-3486	99	8	lines	line	NOUN
cana-3486	99	9	that	that	PRON
cana-3486	99	10	represent	represent	VERB
cana-3486	99	11	the	the	DET
cana-3486	99	12	four	four	NUM
cana-3486	99	13	plant	plant	NOUN
cana-3486	99	14	categories	category	NOUN
cana-3486	99	15	are	be	AUX
cana-3486	99	16	coloured	colour	VERB
cana-3486	99	17	blue	blue	ADJ
cana-3486	99	18	for	for	ADP
cana-3486	99	19	accuracy	accuracy	NOUN
cana-3486	99	20	,	,	PUNCT
cana-3486	99	21	orange	orange	NOUN
cana-3486	99	22	for	for	ADP
cana-3486	99	23	precision	precision	NOUN
cana-3486	99	24	1	1	NUM
cana-3486	99	25	,	,	PUNCT
cana-3486	99	26	and	and	CCONJ
cana-3486	99	27	green	green	ADJ
cana-3486	99	28	for	for	ADP
cana-3486	99	29	precision	precision	NOUN
cana-3486	99	30	2	2	NUM
cana-3486	99	31	.	.	PUNCT
cana-3486	99	32	point	point	NOUN
cana-3486	99	33	4	4	NUM
cana-3486	99	34	(	(	PUNCT
cana-3486	99	35	healthy	healthy	ADJ
cana-3486	99	36	plants	plant	NOUN
cana-3486	99	37	)	)	PUNCT
cana-3486	99	38	has	have	VERB
cana-3486	99	39	the	the	DET
cana-3486	99	40	best	good	ADJ
cana-3486	99	41	precision	precision	NOUN
cana-3486	99	42	and	and	CCONJ
cana-3486	99	43	accuracy	accuracy	NOUN
cana-3486	99	44	,	,	PUNCT
cana-3486	99	45	whereas	whereas	SCONJ
cana-3486	99	46	point	point	NOUN
cana-3486	99	47	2	2	NUM
cana-3486	99	48	(	(	PUNCT
cana-3486	99	49	the	the	DET
cana-3486	99	50	cassava	cassava	NOUN
cana-3486	99	51	brown	brown	PROPN
cana-3486	99	52	streak	streak	PROPN
cana-3486	99	53	virus	virus	NOUN
cana-3486	99	54	)	)	PUNCT
cana-3486	99	55	displays	display	VERB
cana-3486	99	56	the	the	DET
cana-3486	99	57	lowest	low	ADJ
cana-3486	99	58	numbers	number	NOUN
cana-3486	99	59	.	.	PUNCT
cana-3486	100	1	the	the	DET
cana-3486	100	2	precision	precision	NOUN
cana-3486	100	3	measurements	measurement	NOUN
cana-3486	100	4	show	show	VERB
cana-3486	100	5	a	a	DET
cana-3486	100	6	discernible	discernible	ADJ
cana-3486	100	7	decline	decline	NOUN
cana-3486	100	8	at	at	ADP
cana-3486	100	9	point	point	NOUN
cana-3486	100	10	2	2	NUM
cana-3486	100	11	,	,	PUNCT
cana-3486	100	12	but	but	CCONJ
cana-3486	100	13	otherwise	otherwise	ADV
cana-3486	100	14	stay	stay	VERB
cana-3486	100	15	pretty	pretty	ADV
cana-3486	100	16	steady	steady	ADJ
cana-3486	100	17	across	across	ADP
cana-3486	100	18	the	the	DET
cana-3486	100	19	categories	category	NOUN
cana-3486	100	20	.	.	PUNCT
cana-3486	101	1	more	more	ADJ
cana-3486	101	2	variation	variation	NOUN
cana-3486	101	3	occurs	occur	VERB
cana-3486	101	4	in	in	ADP
cana-3486	101	5	accuracy	accuracy	NOUN
cana-3486	101	6	.	.	PUNCT
cana-3486	102	1	the	the	DET
cana-3486	102	2	categorization	categorization	NOUN
cana-3486	102	3	performance	performance	NOUN
cana-3486	102	4	is	be	AUX
cana-3486	102	5	compared	compare	VERB
cana-3486	102	6	across	across	ADP
cana-3486	102	7	various	various	ADJ
cana-3486	102	8	plant	plant	NOUN
cana-3486	102	9	environments	environment	NOUN
cana-3486	102	10	in	in	ADP
cana-3486	102	11	the	the	DET
cana-3486	102	12	graph	graph	NOUN
cana-3486	102	13	.	.	PUNCT
cana-3486	103	1	4	4	X
cana-3486	103	2	.	.	X
cana-3486	103	3	discussion	discussion	VERB
cana-3486	103	4	the	the	DET
cana-3486	103	5	application	application	NOUN
cana-3486	103	6	of	of	ADP
cana-3486	103	7	deep	deep	ADJ
cana-3486	103	8	learning	learning	NOUN
cana-3486	103	9	architectures	architecture	NOUN
cana-3486	103	10	to	to	ADP
cana-3486	103	11	agricultural	agricultural	ADJ
cana-3486	103	12	crop	crop	NOUN
cana-3486	103	13	disease	disease	NOUN
cana-3486	103	14	diagnosis	diagnosis	NOUN
cana-3486	103	15	has	have	AUX
cana-3486	103	16	drawn	draw	VERB
cana-3486	103	17	a	a	DET
cana-3486	103	18	lot	lot	NOUN
cana-3486	103	19	of	of	ADP
cana-3486	103	20	interest	interest	NOUN
cana-3486	103	21	lately	lately	ADV
cana-3486	103	22	[	[	X
cana-3486	103	23	9	9	NUM
cana-3486	103	24	]	]	PUNCT
cana-3486	103	25	.	.	PUNCT
cana-3486	104	1	among	among	ADP
cana-3486	104	2	these	these	DET
cana-3486	104	3	architectures	architecture	NOUN
cana-3486	104	4	,	,	PUNCT
cana-3486	104	5	resnet	resnet	NOUN
cana-3486	104	6	and	and	CCONJ
cana-3486	104	7	vgg-16	vgg-16	NOUN
cana-3486	104	8	have	have	AUX
cana-3486	104	9	become	become	VERB
cana-3486	104	10	wellliked	wellliked	ADJ
cana-3486	104	11	options	option	NOUN
cana-3486	104	12	for	for	ADP
cana-3486	104	13	image	image	NOUN
cana-3486	104	14	classification	classification	NOUN
cana-3486	104	15	applications	application	NOUN
cana-3486	104	16	,	,	PUNCT
cana-3486	104	17	such	such	ADJ
cana-3486	104	18	as	as	ADP
cana-3486	104	19	diagnosing	diagnose	VERB
cana-3486	104	20	illnesses	illness	NOUN
cana-3486	104	21	in	in	ADP
cana-3486	104	22	cassava	cassava	NOUN
cana-3486	104	23	leaves	leave	VERB
cana-3486	104	24	[	[	X
cana-3486	104	25	14	14	NUM
cana-3486	104	26	]	]	PUNCT
cana-3486	104	27	.	.	PUNCT
cana-3486	105	1	recognized	recognize	VERB
cana-3486	105	2	for	for	ADP
cana-3486	105	3	its	its	PRON
cana-3486	105	4	simplicity	simplicity	NOUN
cana-3486	105	5	and	and	CCONJ
cana-3486	105	6	efficiency	efficiency	NOUN
cana-3486	105	7	,	,	PUNCT
cana-3486	105	8	vgg-16	vgg-16	X
cana-3486	105	9	has	have	VERB
cana-3486	105	10	a	a	DET
cana-3486	105	11	simple	simple	ADJ
cana-3486	105	12	architecture	architecture	NOUN
cana-3486	105	13	with	with	ADP
cana-3486	105	14	16	16	NUM
cana-3486	105	15	layers	layer	NOUN
cana-3486	105	16	,	,	PUNCT
cana-3486	105	17	mostly	mostly	ADV
cana-3486	105	18	pooling	pool	VERB
cana-3486	105	19	layers	layer	NOUN
cana-3486	105	20	after	after	ADP
cana-3486	105	21	convolutional	convolutional	ADJ
cana-3486	105	22	layers	layer	NOUN
cana-3486	105	23	.	.	PUNCT
cana-3486	106	1	by	by	ADP
cana-3486	106	2	examining	examine	VERB
cana-3486	106	3	features	feature	NOUN
cana-3486	106	4	at	at	ADP
cana-3486	106	5	different	different	ADJ
cana-3486	106	6	dimensions	dimension	NOUN
cana-3486	106	7	,	,	PUNCT
cana-3486	106	8	this	this	DET
cana-3486	106	9	deep	deep	ADJ
cana-3486	106	10	network	network	NOUN
cana-3486	106	11	can	can	AUX
cana-3486	106	12	diagnose	diagnose	VERB
cana-3486	106	13	a	a	DET
cana-3486	106	14	variety	variety	NOUN
cana-3486	106	15	of	of	ADP
cana-3486	106	16	diseases	disease	NOUN
cana-3486	106	17	by	by	ADP
cana-3486	106	18	identifying	identify	VERB
cana-3486	106	19	complex	complex	ADJ
cana-3486	106	20	patterns	pattern	NOUN
cana-3486	106	21	in	in	ADP
cana-3486	106	22	photos	photo	NOUN
cana-3486	106	23	of	of	ADP
cana-3486	106	24	cassava	cassava	NOUN
cana-3486	106	25	leaves	leave	NOUN
cana-3486	106	26	.	.	PUNCT
cana-3486	107	1	but	but	CCONJ
cana-3486	107	2	as	as	ADP
cana-3486	107	3	depth	depth	NOUN
cana-3486	107	4	increases	increase	NOUN
cana-3486	107	5	,	,	PUNCT
cana-3486	107	6	vgg-16	vgg-16	NOUN
cana-3486	107	7	's	's	PART
cana-3486	107	8	deep	deep	ADJ
cana-3486	107	9	design	design	NOUN
cana-3486	107	10	may	may	AUX
cana-3486	107	11	cause	cause	VERB
cana-3486	107	12	problems	problem	NOUN
cana-3486	107	13	like	like	ADP
cana-3486	107	14	vanishing	vanish	VERB
cana-3486	107	15	gradients	gradient	NOUN
cana-3486	107	16	,	,	PUNCT
cana-3486	107	17	which	which	PRON
cana-3486	107	18	reduces	reduce	VERB
cana-3486	107	19	its	its	PRON
cana-3486	107	20	effectiveness	effectiveness	NOUN
cana-3486	107	21	when	when	SCONJ
cana-3486	107	22	learning	learn	VERB
cana-3486	107	23	from	from	ADP
cana-3486	107	24	bigger	big	ADJ
cana-3486	107	25	datasets	dataset	NOUN
cana-3486	107	26	[	[	X
cana-3486	107	27	10	10	NUM
cana-3486	107	28	]	]	PUNCT
cana-3486	107	29	.	.	PUNCT
cana-3486	108	1	notwithstanding	notwithstanding	ADP
cana-3486	108	2	these	these	DET
cana-3486	108	3	difficulties	difficulty	NOUN
cana-3486	108	4	,	,	PUNCT
cana-3486	108	5	the	the	DET
cana-3486	108	6	vgg-16	vgg-16	NOUN
cana-3486	108	7	model	model	NOUN
cana-3486	108	8	has	have	AUX
cana-3486	108	9	demonstrated	demonstrate	VERB
cana-3486	108	10	efficacy	efficacy	NOUN
cana-3486	108	11	in	in	ADP
cana-3486	108	12	detecting	detect	VERB
cana-3486	108	13	cassava	cassava	NOUN
cana-3486	108	14	leaf	leaf	NOUN
cana-3486	108	15	diseases	disease	NOUN
cana-3486	108	16	,	,	PUNCT
cana-3486	108	17	especially	especially	ADV
cana-3486	108	18	when	when	SCONJ
cana-3486	108	19	paired	pair	VERB
cana-3486	108	20	with	with	ADP
cana-3486	108	21	data	datum	NOUN
cana-3486	108	22	augmentation	augmentation	NOUN
cana-3486	108	23	methods	method	NOUN
cana-3486	108	24	to	to	PART
cana-3486	108	25	boost	boost	VERB
cana-3486	108	26	the	the	DET
cana-3486	108	27	model	model	NOUN
cana-3486	108	28	's	's	PART
cana-3486	108	29	resilience	resilience	NOUN
cana-3486	108	30	[	[	X
cana-3486	108	31	15	15	NUM
cana-3486	108	32	]	]	PUNCT
cana-3486	108	33	.	.	PUNCT
cana-3486	109	1	resnet	resnet	PROPN
cana-3486	109	2	(	(	PUNCT
cana-3486	109	3	residual	residual	ADJ
cana-3486	109	4	network	network	NOUN
cana-3486	109	5	)	)	PUNCT
cana-3486	109	6	,	,	PUNCT
cana-3486	109	7	on	on	ADP
cana-3486	109	8	the	the	DET
cana-3486	109	9	other	other	ADJ
cana-3486	109	10	hand	hand	NOUN
cana-3486	109	11	,	,	PUNCT
cana-3486	109	12	presents	present	VERB
cana-3486	109	13	a	a	DET
cana-3486	109	14	novel	novel	ADJ
cana-3486	109	15	idea	idea	NOUN
cana-3486	109	16	of	of	ADP
cana-3486	109	17	residual	residual	ADJ
cana-3486	109	18	learning	learning	NOUN
cana-3486	109	19	via	via	ADP
cana-3486	109	20	skip	skip	ADJ
cana-3486	109	21	connections	connection	NOUN
cana-3486	109	22	,	,	PUNCT
cana-3486	109	23	allowing	allow	VERB
cana-3486	109	24	gradients	gradient	NOUN
cana-3486	109	25	to	to	PART
cana-3486	109	26	move	move	VERB
cana-3486	109	27	more	more	ADV
cana-3486	109	28	freely	freely	ADV
cana-3486	109	29	during	during	ADP
cana-3486	109	30	backpropagation	backpropagation	NOUN
cana-3486	109	31	[	[	X
cana-3486	109	32	18	18	NUM
cana-3486	109	33	]	]	PUNCT
cana-3486	109	34	.	.	PUNCT
cana-3486	110	1	with	with	ADP
cana-3486	110	2	this	this	DET
cana-3486	110	3	approach	approach	NOUN
cana-3486	110	4	,	,	PUNCT
cana-3486	110	5	the	the	DET
cana-3486	110	6	vanishing	vanish	VERB
cana-3486	110	7	gradient	gradient	NOUN
cana-3486	110	8	problem	problem	NOUN
cana-3486	110	9	is	be	AUX
cana-3486	110	10	avoided	avoid	VERB
cana-3486	110	11	and	and	CCONJ
cana-3486	110	12	considerably	considerably	ADV
cana-3486	110	13	deeper	deep	ADJ
cana-3486	110	14	structures	structure	NOUN
cana-3486	110	15	can	can	AUX
cana-3486	110	16	be	be	AUX
cana-3486	110	17	built	build	VERB
cana-3486	110	18	,	,	PUNCT
cana-3486	110	19	circumventing	circumvent	VERB
cana-3486	110	20	the	the	DET
cana-3486	110	21	drawbacks	drawback	NOUN
cana-3486	110	22	of	of	ADP
cana-3486	110	23	conventional	conventional	ADJ
cana-3486	110	24	deep	deep	ADJ
cana-3486	110	25	networks	network	NOUN
cana-3486	111	1	[	[	X
cana-3486	111	2	5	5	NUM
cana-3486	111	3	]	]	PUNCT
cana-3486	111	4	.	.	PUNCT
cana-3486	112	1	because	because	SCONJ
cana-3486	112	2	resnet	resnet	NOUN
cana-3486	112	3	can	can	AUX
cana-3486	112	4	learn	learn	VERB
cana-3486	112	5	residuals	residual	NOUN
cana-3486	112	6	,	,	PUNCT
cana-3486	112	7	it	it	PRON
cana-3486	112	8	can	can	AUX
cana-3486	112	9	efficiently	efficiently	ADV
cana-3486	112	10	extract	extract	VERB
cana-3486	112	11	complicated	complicated	ADJ
cana-3486	112	12	information	information	NOUN
cana-3486	112	13	from	from	ADP
cana-3486	112	14	photos	photo	NOUN
cana-3486	112	15	of	of	ADP
cana-3486	112	16	cassava	cassava	NOUN
cana-3486	112	17	leaves	leave	NOUN
cana-3486	112	18	,	,	PUNCT
cana-3486	112	19	which	which	PRON
cana-3486	112	20	improves	improve	VERB
cana-3486	112	21	its	its	PRON
cana-3486	112	22	accuracy	accuracy	NOUN
cana-3486	112	23	in	in	ADP
cana-3486	112	24	tasks	task	NOUN
cana-3486	112	25	involving	involve	VERB
cana-3486	112	26	the	the	DET
cana-3486	112	27	categorization	categorization	NOUN
cana-3486	112	28	of	of	ADP
cana-3486	112	29	diseases	disease	NOUN
cana-3486	112	30	.	.	PUNCT
cana-3486	113	1	in	in	ADP
cana-3486	113	2	terms	term	NOUN
cana-3486	113	3	of	of	ADP
cana-3486	113	4	accuracy	accuracy	NOUN
cana-3486	113	5	and	and	CCONJ
cana-3486	113	6	generalization	generalization	NOUN
cana-3486	113	7	,	,	PUNCT
cana-3486	113	8	resnet	resnet	NOUN
cana-3486	113	9	frequently	frequently	ADV
cana-3486	113	10	outperforms	outperform	VERB
cana-3486	113	11	vgg-16	vgg-16	NOUN
cana-3486	113	12	in	in	ADP
cana-3486	113	13	the	the	DET
cana-3486	113	14	detection	detection	NOUN
cana-3486	113	15	of	of	ADP
cana-3486	113	16	illnesses	illness	NOUN
cana-3486	113	17	like	like	ADP
cana-3486	113	18	bacterial	bacterial	ADJ
cana-3486	113	19	blight	blight	NOUN
cana-3486	113	20	and	and	CCONJ
cana-3486	113	21	cassava	cassava	NOUN
cana-3486	113	22	mosaic	mosaic	ADJ
cana-3486	113	23	disease	disease	NOUN
cana-3486	113	24	,	,	PUNCT
cana-3486	113	25	especially	especially	ADV
cana-3486	113	26	when	when	SCONJ
cana-3486	113	27	trained	train	VERB
cana-3486	113	28	on	on	ADP
cana-3486	113	29	large	large	ADJ
cana-3486	113	30	,	,	PUNCT
cana-3486	113	31	diverse	diverse	ADJ
cana-3486	113	32	datasets	dataset	NOUN
cana-3486	113	33	.	.	PUNCT
cana-3486	114	1	in	in	ADP
cana-3486	114	2	the	the	DET
cana-3486	114	3	end	end	NOUN
cana-3486	114	4	,	,	PUNCT
cana-3486	114	5	there	there	PRON
cana-3486	114	6	are	be	VERB
cana-3486	114	7	advantages	advantage	NOUN
cana-3486	114	8	and	and	CCONJ
cana-3486	114	9	disadvantages	disadvantage	NOUN
cana-3486	114	10	for	for	ADP
cana-3486	114	11	both	both	DET
cana-3486	114	12	vgg-16	vgg-16	NOUN
cana-3486	114	13	and	and	CCONJ
cana-3486	114	14	resnet	resnet	VERB
cana-3486	114	15	when	when	SCONJ
cana-3486	114	16	it	it	PRON
cana-3486	114	17	comes	come	VERB
cana-3486	114	18	to	to	ADP
cana-3486	114	19	detecting	detect	VERB
cana-3486	114	20	cassava	cassava	NOUN
cana-3486	114	21	leaf	leaf	NOUN
cana-3486	114	22	disease	disease	NOUN
cana-3486	115	1	[	[	X
cana-3486	115	2	20	20	NUM
cana-3486	115	3	]	]	PUNCT
cana-3486	115	4	.	.	PUNCT
cana-3486	116	1	resnet	resnet	PROPN
cana-3486	116	2	provides	provide	VERB
cana-3486	116	3	a	a	DET
cana-3486	116	4	more	more	ADV
cana-3486	116	5	complex	complex	ADJ
cana-3486	116	6	framework	framework	NOUN
cana-3486	116	7	that	that	PRON
cana-3486	116	8	can	can	AUX
cana-3486	116	9	achieve	achieve	VERB
cana-3486	116	10	higher	high	ADJ
cana-3486	116	11	accuracy	accuracy	NOUN
cana-3486	116	12	on	on	ADP
cana-3486	116	13	larger	large	ADJ
cana-3486	116	14	datasets	dataset	NOUN
cana-3486	116	15	because	because	SCONJ
cana-3486	116	16	of	of	ADP
cana-3486	116	17	its	its	PRON
cana-3486	116	18	deep	deep	ADJ
cana-3486	116	19	architecture	architecture	NOUN
cana-3486	116	20	and	and	CCONJ
cana-3486	116	21	novel	novel	ADJ
cana-3486	116	22	residual	residual	ADJ
cana-3486	116	23	learning	learning	NOUN
cana-3486	116	24	,	,	PUNCT
cana-3486	116	25	while	while	SCONJ
cana-3486	116	26	vgg-16	vgg-16	PRON
cana-3486	116	27	offers	offer	VERB
cana-3486	116	28	a	a	DET
cana-3486	116	29	straightforward	straightforward	ADJ
cana-3486	116	30	method	method	NOUN
cana-3486	116	31	that	that	PRON
cana-3486	116	32	can	can	AUX
cana-3486	116	33	produce	produce	VERB
cana-3486	116	34	good	good	ADJ
cana-3486	116	35	results	result	NOUN
cana-3486	116	36	with	with	ADP
cana-3486	116	37	communications	communication	NOUN
cana-3486	116	38	on	on	ADP
cana-3486	116	39	applied	apply	VERB
cana-3486	116	40	nonlinear	nonlinear	ADJ
cana-3486	116	41	analysis	analysis	NOUN
cana-3486	116	42	issn	issn	NOUN
cana-3486	116	43	:	:	PUNCT
cana-3486	116	44	1074	1074	NUM
cana-3486	116	45	-	-	PUNCT
cana-3486	116	46	133x	133x	NUM
cana-3486	116	47	vol	vol	NOUN
cana-3486	116	48	32	32	NUM
cana-3486	116	49	no	no	NOUN
cana-3486	116	50	.	.	PUNCT
cana-3486	117	1	7s	7	NOUN
cana-3486	117	2	(	(	PUNCT
cana-3486	117	3	2025	2025	NUM
cana-3486	117	4	)	)	PUNCT
cana-3486	117	5	796	796	NUM
cana-3486	117	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	117	7	smaller	small	ADJ
cana-3486	117	8	datasets	dataset	NOUN
cana-3486	117	9	and	and	CCONJ
cana-3486	117	10	less	less	ADJ
cana-3486	117	11	complexity	complexity	NOUN
cana-3486	118	1	[	[	X
cana-3486	118	2	21	21	NUM
cana-3486	118	3	]	]	PUNCT
cana-3486	118	4	.	.	PUNCT
cana-3486	119	1	the	the	DET
cana-3486	119	2	application	application	NOUN
cana-3486	119	3	's	's	PART
cana-3486	119	4	particular	particular	ADJ
cana-3486	119	5	needs	need	NOUN
cana-3486	119	6	,	,	PUNCT
cana-3486	119	7	such	such	ADJ
cana-3486	119	8	as	as	ADP
cana-3486	119	9	the	the	DET
cana-3486	119	10	size	size	NOUN
cana-3486	119	11	of	of	ADP
cana-3486	119	12	the	the	DET
cana-3486	119	13	dataset	dataset	NOUN
cana-3486	119	14	,	,	PUNCT
cana-3486	119	15	the	the	DET
cana-3486	119	16	availability	availability	NOUN
cana-3486	119	17	of	of	ADP
cana-3486	119	18	computational	computational	ADJ
cana-3486	119	19	power	power	NOUN
cana-3486	119	20	,	,	PUNCT
cana-3486	119	21	and	and	CCONJ
cana-3486	119	22	the	the	DET
cana-3486	119	23	demand	demand	NOUN
cana-3486	119	24	for	for	ADP
cana-3486	119	25	accurate	accurate	ADJ
cana-3486	119	26	illness	illness	NOUN
cana-3486	119	27	detection	detection	NOUN
cana-3486	119	28	,	,	PUNCT
cana-3486	119	29	should	should	AUX
cana-3486	119	30	be	be	AUX
cana-3486	119	31	taken	take	VERB
cana-3486	119	32	into	into	ADP
cana-3486	119	33	consideration	consideration	NOUN
cana-3486	119	34	while	while	SCONJ
cana-3486	119	35	selecting	select	VERB
cana-3486	119	36	between	between	ADP
cana-3486	119	37	these	these	DET
cana-3486	119	38	models	model	NOUN
cana-3486	119	39	.	.	PUNCT
cana-3486	120	1	5	5	X
cana-3486	120	2	.	.	X
cana-3486	120	3	conclusion	conclusion	NOUN
cana-3486	120	4	resnet-50	resnet-50	PROPN
cana-3486	120	5	's	's	PART
cana-3486	120	6	strong	strong	ADJ
cana-3486	120	7	feature	feature	NOUN
cana-3486	120	8	extraction	extraction	NOUN
cana-3486	120	9	capabilities	capability	NOUN
cana-3486	120	10	have	have	AUX
cana-3486	120	11	made	make	VERB
cana-3486	120	12	it	it	PRON
cana-3486	120	13	a	a	DET
cana-3486	120	14	successful	successful	ADJ
cana-3486	120	15	deep	deep	ADJ
cana-3486	120	16	learning	learning	NOUN
cana-3486	120	17	model	model	NOUN
cana-3486	120	18	for	for	ADP
cana-3486	120	19	disease	disease	NOUN
cana-3486	120	20	detection	detection	NOUN
cana-3486	120	21	in	in	ADP
cana-3486	120	22	cassava	cassava	NOUN
cana-3486	120	23	leaves	leave	NOUN
cana-3486	120	24	.	.	PUNCT
cana-3486	121	1	it	it	PRON
cana-3486	121	2	solves	solve	VERB
cana-3486	121	3	the	the	DET
cana-3486	121	4	vanishing	vanish	VERB
cana-3486	121	5	gradient	gradient	NOUN
cana-3486	121	6	issue	issue	NOUN
cana-3486	121	7	by	by	ADP
cana-3486	121	8	utilizing	utilize	VERB
cana-3486	121	9	residual	residual	ADJ
cana-3486	121	10	connections	connection	NOUN
cana-3486	121	11	in	in	ADP
cana-3486	121	12	its	its	PRON
cana-3486	121	13	deep	deep	ADJ
cana-3486	121	14	design	design	NOUN
cana-3486	121	15	,	,	PUNCT
cana-3486	121	16	which	which	PRON
cana-3486	121	17	makes	make	VERB
cana-3486	121	18	deep	deep	ADJ
cana-3486	121	19	network	network	NOUN
cana-3486	121	20	training	train	VERB
cana-3486	121	21	more	more	ADV
cana-3486	121	22	effective	effective	ADJ
cana-3486	121	23	.	.	PUNCT
cana-3486	122	1	especially	especially	ADV
cana-3486	122	2	well	well	ADV
cana-3486	122	3	-	-	PUNCT
cana-3486	122	4	suited	suit	VERB
cana-3486	122	5	for	for	ADP
cana-3486	122	6	detecting	detect	VERB
cana-3486	122	7	minute	minute	ADJ
cana-3486	122	8	variations	variation	NOUN
cana-3486	122	9	in	in	ADP
cana-3486	122	10	leaf	leaf	NOUN
cana-3486	122	11	texture	texture	NOUN
cana-3486	122	12	,	,	PUNCT
cana-3486	122	13	color	color	NOUN
cana-3486	122	14	,	,	PUNCT
cana-3486	122	15	and	and	CCONJ
cana-3486	122	16	shape	shape	NOUN
cana-3486	122	17	,	,	PUNCT
cana-3486	122	18	which	which	PRON
cana-3486	122	19	are	be	AUX
cana-3486	122	20	crucial	crucial	ADJ
cana-3486	122	21	indications	indication	NOUN
cana-3486	122	22	of	of	ADP
cana-3486	122	23	illnesses	illness	NOUN
cana-3486	122	24	in	in	ADP
cana-3486	122	25	cassava	cassava	NOUN
cana-3486	122	26	plants	plant	NOUN
cana-3486	122	27	because	because	SCONJ
cana-3486	122	28	to	to	ADP
cana-3486	122	29	its	its	PRON
cana-3486	122	30	capacity	capacity	NOUN
cana-3486	122	31	to	to	PART
cana-3486	122	32	learn	learn	VERB
cana-3486	122	33	complicated	complicated	ADJ
cana-3486	122	34	patterns	pattern	NOUN
cana-3486	122	35	from	from	ADP
cana-3486	122	36	huge	huge	ADJ
cana-3486	122	37	datasets	dataset	NOUN
cana-3486	122	38	.	.	PUNCT
cana-3486	123	1	resnet-50	resnet-50	NOUN
cana-3486	123	2	offers	offer	VERB
cana-3486	123	3	a	a	DET
cana-3486	123	4	number	number	NOUN
cana-3486	123	5	of	of	ADP
cana-3486	123	6	benefits	benefit	NOUN
cana-3486	123	7	over	over	ADP
cana-3486	123	8	conventional	conventional	ADJ
cana-3486	123	9	image	image	NOUN
cana-3486	123	10	processing	processing	NOUN
cana-3486	123	11	methods	method	NOUN
cana-3486	123	12	,	,	PUNCT
cana-3486	123	13	including	include	VERB
cana-3486	123	14	simpler	simple	ADJ
cana-3486	123	15	convolutional	convolutional	ADJ
cana-3486	123	16	networks	network	NOUN
cana-3486	123	17	and	and	CCONJ
cana-3486	123	18	higher	high	ADJ
cana-3486	123	19	accuracy	accuracy	NOUN
cana-3486	123	20	in	in	ADP
cana-3486	123	21	cassava	cassava	NOUN
cana-3486	123	22	leaf	leaf	NOUN
cana-3486	123	23	disease	disease	NOUN
cana-3486	123	24	diagnosis	diagnosis	NOUN
cana-3486	123	25	.	.	PUNCT
cana-3486	124	1	its	its	PRON
cana-3486	124	2	pretrained	pretraine	VERB
cana-3486	124	3	weights	weight	NOUN
cana-3486	124	4	can	can	AUX
cana-3486	124	5	be	be	AUX
cana-3486	124	6	adjusted	adjust	VERB
cana-3486	124	7	for	for	ADP
cana-3486	124	8	this	this	DET
cana-3486	124	9	particular	particular	ADJ
cana-3486	124	10	job	job	NOUN
cana-3486	124	11	,	,	PUNCT
cana-3486	124	12	minimizing	minimize	VERB
cana-3486	124	13	training	training	NOUN
cana-3486	124	14	time	time	NOUN
cana-3486	124	15	and	and	CCONJ
cana-3486	124	16	enhancing	enhance	VERB
cana-3486	124	17	generalization	generalization	NOUN
cana-3486	124	18	.	.	PUNCT
cana-3486	125	1	these	these	DET
cana-3486	125	2	weights	weight	NOUN
cana-3486	125	3	are	be	AUX
cana-3486	125	4	frequently	frequently	ADV
cana-3486	125	5	obtained	obtain	VERB
cana-3486	125	6	from	from	ADP
cana-3486	125	7	huge	huge	ADJ
cana-3486	125	8	image	image	NOUN
cana-3486	125	9	datasets	dataset	NOUN
cana-3486	125	10	such	such	ADJ
cana-3486	125	11	as	as	ADP
cana-3486	125	12	imagenet	imagenet	NOUN
cana-3486	125	13	[	[	X
cana-3486	125	14	18	18	NUM
cana-3486	125	15	]	]	PUNCT
cana-3486	125	16	.	.	PUNCT
cana-3486	126	1	consequently	consequently	ADV
cana-3486	126	2	,	,	PUNCT
cana-3486	126	3	it	it	PRON
cana-3486	126	4	has	have	VERB
cana-3486	126	5	the	the	DET
cana-3486	126	6	ability	ability	NOUN
cana-3486	126	7	to	to	PART
cana-3486	126	8	accurately	accurately	ADV
cana-3486	126	9	discriminate	discriminate	VERB
cana-3486	126	10	between	between	ADP
cana-3486	126	11	a	a	DET
cana-3486	126	12	variety	variety	NOUN
cana-3486	126	13	of	of	ADP
cana-3486	126	14	cassava	cassava	NOUN
cana-3486	126	15	disorders	disorder	NOUN
cana-3486	126	16	,	,	PUNCT
cana-3486	126	17	including	include	VERB
cana-3486	126	18	cassava	cassava	NOUN
cana-3486	126	19	mosaic	mosaic	ADJ
cana-3486	126	20	disease	disease	NOUN
cana-3486	126	21	and	and	CCONJ
cana-3486	126	22	brown	brown	ADJ
cana-3486	126	23	streak	streak	NOUN
cana-3486	126	24	disease	disease	NOUN
cana-3486	126	25	,	,	PUNCT
cana-3486	126	26	which	which	PRON
cana-3486	126	27	are	be	AUX
cana-3486	126	28	frequently	frequently	ADV
cana-3486	126	29	difficult	difficult	ADJ
cana-3486	126	30	to	to	PART
cana-3486	126	31	discern	discern	VERB
cana-3486	126	32	with	with	ADP
cana-3486	126	33	the	the	DET
cana-3486	126	34	untrained	untrained	ADJ
cana-3486	126	35	eye	eye	NOUN
cana-3486	126	36	.	.	PUNCT
cana-3486	127	1	resnet-50	resnet-50	PROPN
cana-3486	127	2	has	have	VERB
cana-3486	127	3	many	many	ADJ
cana-3486	127	4	advantages	advantage	NOUN
cana-3486	127	5	,	,	PUNCT
cana-3486	127	6	but	but	CCONJ
cana-3486	127	7	because	because	SCONJ
cana-3486	127	8	of	of	ADP
cana-3486	127	9	its	its	PRON
cana-3486	127	10	deep	deep	ADJ
cana-3486	127	11	structure	structure	NOUN
cana-3486	127	12	,	,	PUNCT
cana-3486	127	13	it	it	PRON
cana-3486	127	14	also	also	ADV
cana-3486	127	15	needs	need	VERB
cana-3486	127	16	a	a	DET
cana-3486	127	17	lot	lot	NOUN
cana-3486	127	18	of	of	ADP
cana-3486	127	19	computational	computational	ADJ
cana-3486	127	20	power	power	NOUN
cana-3486	127	21	,	,	PUNCT
cana-3486	127	22	which	which	PRON
cana-3486	127	23	can	can	AUX
cana-3486	127	24	make	make	VERB
cana-3486	127	25	it	it	PRON
cana-3486	127	26	difficult	difficult	ADJ
cana-3486	127	27	to	to	PART
cana-3486	127	28	use	use	VERB
cana-3486	127	29	in	in	ADP
cana-3486	127	30	places	place	NOUN
cana-3486	127	31	with	with	ADP
cana-3486	127	32	limited	limited	ADJ
cana-3486	127	33	resources	resource	NOUN
cana-3486	127	34	,	,	PUNCT
cana-3486	127	35	like	like	ADP
cana-3486	127	36	to	to	PART
cana-3486	127	37	use	use	VERB
cana-3486	127	38	in	in	ADP
cana-3486	127	39	places	place	NOUN
cana-3486	127	40	with	with	ADP
cana-3486	127	41	limited	limited	ADJ
cana-3486	127	42	difficult	difficult	ADJ
cana-3486	127	43	rural	rural	ADJ
cana-3486	127	44	,	,	PUNCT
cana-3486	127	45	like	like	ADP
cana-3486	127	46	rural	rural	ADJ
cana-3486	127	47	cassava	cassava	NOUN
cana-3486	127	48	farming	farming	NOUN
cana-3486	127	49	areas	area	NOUN
cana-3486	127	50	[	[	X
cana-3486	127	51	22	22	NUM
cana-3486	127	52	]	]	PUNCT
cana-3486	127	53	.	.	PUNCT
cana-3486	128	1	although	although	SCONJ
cana-3486	128	2	the	the	DET
cana-3486	128	3	model	model	NOUN
cana-3486	128	4	performs	perform	VERB
cana-3486	128	5	exceptionally	exceptionally	ADV
cana-3486	128	6	well	well	ADV
cana-3486	128	7	in	in	ADP
cana-3486	128	8	controlled	control	VERB
cana-3486	128	9	environments	environment	NOUN
cana-3486	128	10	,	,	PUNCT
cana-3486	128	11	it	it	PRON
cana-3486	128	12	is	be	AUX
cana-3486	128	13	still	still	ADV
cana-3486	128	14	difficult	difficult	ADJ
cana-3486	128	15	to	to	PART
cana-3486	128	16	optimize	optimize	VERB
cana-3486	128	17	it	it	PRON
cana-3486	128	18	for	for	ADP
cana-3486	128	19	real	real	ADJ
cana-3486	128	20	-	-	PUNCT
cana-3486	128	21	time	time	NOUN
cana-3486	128	22	detection	detection	NOUN
cana-3486	128	23	in	in	ADP
cana-3486	128	24	the	the	DET
cana-3486	128	25	field	field	NOUN
cana-3486	128	26	,	,	PUNCT
cana-3486	128	27	on	on	ADP
cana-3486	128	28	mobile	mobile	ADJ
cana-3486	128	29	devices	device	NOUN
cana-3486	128	30	,	,	PUNCT
cana-3486	128	31	or	or	CCONJ
cana-3486	128	32	on	on	ADP
cana-3486	128	33	low	low	ADJ
cana-3486	128	34	-	-	PUNCT
cana-3486	128	35	powered	power	VERB
cana-3486	128	36	systems	system	NOUN
cana-3486	128	37	.	.	PUNCT
cana-3486	129	1	overall	overall	ADV
cana-3486	129	2	,	,	PUNCT
cana-3486	129	3	resnet-50	resnet-50	PROPN
cana-3486	129	4	continues	continue	VERB
cana-3486	129	5	to	to	PART
cana-3486	129	6	be	be	AUX
cana-3486	129	7	the	the	DET
cana-3486	129	8	best	good	ADJ
cana-3486	129	9	option	option	NOUN
cana-3486	129	10	for	for	ADP
cana-3486	129	11	detecting	detect	VERB
cana-3486	129	12	cassava	cassava	NOUN
cana-3486	129	13	leaf	leaf	NOUN
cana-3486	129	14	disease	disease	NOUN
cana-3486	129	15	;	;	PUNCT
cana-3486	129	16	however	however	ADV
cana-3486	129	17	,	,	PUNCT
cana-3486	129	18	additional	additional	ADJ
cana-3486	129	19	work	work	NOUN
cana-3486	129	20	must	must	AUX
cana-3486	129	21	be	be	AUX
cana-3486	129	22	done	do	VERB
cana-3486	129	23	to	to	PART
cana-3486	129	24	improve	improve	VERB
cana-3486	129	25	its	its	PRON
cana-3486	129	26	usability	usability	NOUN
cana-3486	129	27	before	before	SCONJ
cana-3486	129	28	it	it	PRON
cana-3486	129	29	can	can	AUX
cana-3486	129	30	be	be	AUX
cana-3486	129	31	widely	widely	ADV
cana-3486	129	32	applied	apply	VERB
cana-3486	129	33	in	in	ADP
cana-3486	129	34	agriculture	agriculture	NOUN
cana-3486	129	35	.	.	PUNCT
cana-3486	130	1	6.acknowledgements	6.acknowledgements	NUM
cana-3486	130	2	sincere	sincere	ADJ
cana-3486	130	3	thanks	thank	NOUN
cana-3486	130	4	are	be	AUX
cana-3486	130	5	extended	extend	VERB
cana-3486	130	6	by	by	ADP
cana-3486	130	7	the	the	DET
cana-3486	130	8	authors	author	NOUN
cana-3486	130	9	to	to	ADP
cana-3486	130	10	kl	kl	PROPN
cana-3486	130	11	university	university	PROPN
cana-3486	130	12	,	,	PUNCT
cana-3486	130	13	vijayawada	vijayawada	PROPN
cana-3486	130	14	,	,	PUNCT
cana-3486	130	15	for	for	ADP
cana-3486	130	16	providing	provide	VERB
cana-3486	130	17	the	the	DET
cana-3486	130	18	tools	tool	NOUN
cana-3486	130	19	and	and	CCONJ
cana-3486	130	20	assistance	assistance	NOUN
cana-3486	130	21	needed	need	VERB
cana-3486	130	22	for	for	ADP
cana-3486	130	23	this	this	DET
cana-3486	130	24	research	research	NOUN
cana-3486	130	25	.	.	PUNCT
cana-3486	131	1	we	we	PRON
cana-3486	131	2	express	express	VERB
cana-3486	131	3	our	our	PRON
cana-3486	131	4	special	special	ADJ
cana-3486	131	5	gratitude	gratitude	NOUN
cana-3486	131	6	for	for	ADP
cana-3486	131	7	the	the	DET
cana-3486	131	8	financing	financing	NOUN
cana-3486	131	9	,	,	PUNCT
cana-3486	131	10	academic	academic	ADJ
cana-3486	131	11	support	support	NOUN
cana-3486	131	12	,	,	PUNCT
cana-3486	131	13	and	and	CCONJ
cana-3486	131	14	facility	facility	NOUN
cana-3486	131	15	access	access	NOUN
cana-3486	131	16	that	that	PRON
cana-3486	131	17	enabled	enable	VERB
cana-3486	131	18	this	this	DET
cana-3486	131	19	work	work	NOUN
cana-3486	131	20	.	.	PUNCT
cana-3486	132	1	this	this	DET
cana-3486	132	2	task	task	NOUN
cana-3486	132	3	was	be	AUX
cana-3486	132	4	successfully	successfully	ADV
cana-3486	132	5	completed	complete	VERB
cana-3486	132	6	in	in	ADP
cana-3486	132	7	large	large	ADJ
cana-3486	132	8	part	part	NOUN
cana-3486	132	9	because	because	SCONJ
cana-3486	132	10	of	of	ADP
cana-3486	132	11	the	the	DET
cana-3486	132	12	collaborative	collaborative	ADJ
cana-3486	132	13	environment	environment	NOUN
cana-3486	132	14	that	that	PRON
cana-3486	132	15	the	the	DET
cana-3486	132	16	academics	academic	NOUN
cana-3486	132	17	and	and	CCONJ
cana-3486	132	18	staff	staff	NOUN
cana-3486	132	19	developed	develop	VERB
cana-3486	132	20	.	.	PUNCT
cana-3486	133	1	we	we	PRON
cana-3486	133	2	also	also	ADV
cana-3486	133	3	acknowledge	acknowledge	VERB
cana-3486	133	4	the	the	DET
cana-3486	133	5	support	support	NOUN
cana-3486	133	6	and	and	CCONJ
cana-3486	133	7	helpful	helpful	ADJ
cana-3486	133	8	criticism	criticism	NOUN
cana-3486	133	9	from	from	ADP
cana-3486	133	10	the	the	DET
cana-3486	133	11	academic	academic	ADJ
cana-3486	133	12	community	community	NOUN
cana-3486	133	13	,	,	PUNCT
cana-3486	133	14	which	which	PRON
cana-3486	133	15	has	have	AUX
cana-3486	133	16	shaped	shape	VERB
cana-3486	133	17	the	the	DET
cana-3486	133	18	course	course	NOUN
cana-3486	133	19	of	of	ADP
cana-3486	133	20	this	this	DET
cana-3486	133	21	study	study	NOUN
cana-3486	133	22	.	.	PUNCT
cana-3486	134	1	references	reference	NOUN
cana-3486	134	2	[	[	X
cana-3486	134	3	1	1	X
cana-3486	134	4	]	]	X
cana-3486	134	5	v.	v.	ADP
cana-3486	134	6	n	n	CCONJ
cana-3486	134	7	,	,	PUNCT
cana-3486	134	8	m.	m.	NOUN
cana-3486	134	9	chinta	chinta	NOUN
cana-3486	134	10	,	,	PUNCT
cana-3486	134	11	k.	k.	PROPN
cana-3486	134	12	e	e	PROPN
cana-3486	134	13	and	and	CCONJ
cana-3486	134	14	s.	s.	PROPN
cana-3486	134	15	v.	v.	PROPN
cana-3486	134	16	l	l	PROPN
cana-3486	134	17	,	,	PUNCT
cana-3486	134	18	"	"	PUNCT
cana-3486	134	19	classification	classification	NOUN
cana-3486	134	20	of	of	ADP
cana-3486	134	21	pneumonia	pneumonia	NOUN
cana-3486	134	22	using	use	VERB
cana-3486	134	23	inceptionnet	inceptionnet	NOUN
cana-3486	134	24	,	,	PUNCT
cana-3486	134	25	resnet	resnet	NOUN
cana-3486	134	26	and	and	CCONJ
cana-3486	134	27	cnn	cnn	PROPN
cana-3486	134	28	,	,	PUNCT
cana-3486	134	29	"	"	PUNCT
cana-3486	134	30	2022	2022	NUM
cana-3486	134	31	6th	6th	ADJ
cana-3486	134	32	international	international	ADJ
cana-3486	134	33	conference	conference	NOUN
cana-3486	134	34	on	on	ADP
cana-3486	134	35	computation	computation	NOUN
cana-3486	134	36	system	system	NOUN
cana-3486	134	37	and	and	CCONJ
cana-3486	134	38	information	information	NOUN
cana-3486	134	39	technology	technology	NOUN
cana-3486	134	40	for	for	ADP
cana-3486	134	41	sustainable	sustainable	ADJ
cana-3486	134	42	solutions	solution	NOUN
cana-3486	134	43	(	(	PUNCT
cana-3486	134	44	csitss	csitss	NOUN
cana-3486	134	45	)	)	PUNCT
cana-3486	134	46	,	,	PUNCT
cana-3486	134	47	bangalore	bangalore	PROPN
cana-3486	134	48	,	,	PUNCT
cana-3486	134	49	india	india	PROPN
cana-3486	134	50	,	,	PUNCT
cana-3486	134	51	2022	2022	NUM
cana-3486	134	52	,	,	PUNCT
cana-3486	134	53	pp	pp	ADJ
cana-3486	134	54	.	.	PUNCT
cana-3486	135	1	1	1	NUM
cana-3486	135	2	-	-	SYM
cana-3486	135	3	6	6	NUM
cana-3486	135	4	,	,	PUNCT
cana-3486	135	5	doi	doi	NOUN
cana-3486	135	6	:	:	PUNCT
cana-3486	135	7	10.1109	10.1109	NUM
cana-3486	135	8	/	/	SYM
cana-3486	135	9	csitss57437.2022.10026402	csitss57437.2022.10026402	NOUN
cana-3486	135	10	.	.	PUNCT
cana-3486	136	1	[	[	X
cana-3486	136	2	2	2	X
cana-3486	136	3	]	]	X
cana-3486	136	4	h.	h.	PROPN
cana-3486	136	5	c.	c.	PROPN
cana-3486	136	6	choi	choi	PROPN
cana-3486	136	7	and	and	CCONJ
cana-3486	136	8	t.	t.	PROPN
cana-3486	136	9	-c	-c	PROPN
cana-3486	136	10	.	.	PUNCT
cana-3486	137	1	hsiao	hsiao	PROPN
cana-3486	137	2	,	,	PUNCT
cana-3486	137	3	"	"	PUNCT
cana-3486	137	4	image	image	NOUN
cana-3486	137	5	classification	classification	NOUN
cana-3486	137	6	of	of	ADP
cana-3486	137	7	cassava	cassava	NOUN
cana-3486	137	8	leaf	leaf	NOUN
cana-3486	137	9	disease	disease	NOUN
cana-3486	137	10	based	base	VERB
cana-3486	137	11	on	on	ADP
cana-3486	137	12	residual	residual	ADJ
cana-3486	137	13	network	network	NOUN
cana-3486	137	14	,	,	PUNCT
cana-3486	137	15	"	"	PUNCT
cana-3486	137	16	2021	2021	NUM
cana-3486	137	17	ieee	ieee	NOUN
cana-3486	137	18	3rd	3rd	PROPN
cana-3486	137	19	eurasia	eurasia	PROPN
cana-3486	137	20	conference	conference	PROPN
cana-3486	137	21	on	on	ADP
cana-3486	137	22	biomedical	biomedical	ADJ
cana-3486	137	23	engineering	engineering	NOUN
cana-3486	137	24	,	,	PUNCT
cana-3486	137	25	healthcare	healthcare	NOUN
cana-3486	137	26	and	and	CCONJ
cana-3486	137	27	sustainability	sustainability	NOUN
cana-3486	137	28	(	(	PUNCT
cana-3486	137	29	ecbios	ecbios	PROPN
cana-3486	137	30	)	)	PUNCT
cana-3486	137	31	,	,	PUNCT
cana-3486	137	32	tainan	tainan	PROPN
cana-3486	137	33	,	,	PUNCT
cana-3486	137	34	taiwan	taiwan	PROPN
cana-3486	137	35	,	,	PUNCT
cana-3486	137	36	2021	2021	NUM
cana-3486	137	37	,	,	PUNCT
cana-3486	137	38	pp	pp	ADJ
cana-3486	137	39	.	.	PUNCT
cana-3486	138	1	185	185	NUM
cana-3486	138	2	-	-	SYM
cana-3486	138	3	186	186	NUM
cana-3486	138	4	,	,	PUNCT
cana-3486	138	5	doi	doi	NOUN
cana-3486	138	6	:	:	PUNCT
cana-3486	138	7	10.1109	10.1109	NUM
cana-3486	138	8	/	/	SYM
cana-3486	138	9	ecbios51820.2021.9510414	ecbios51820.2021.9510414	NOUN
cana-3486	138	10	.	.	PUNCT
cana-3486	139	1	[	[	X
cana-3486	139	2	3	3	X
cana-3486	139	3	]	]	X
cana-3486	139	4	w.	w.	PROPN
cana-3486	139	5	hou	hou	PROPN
cana-3486	139	6	,	,	PUNCT
cana-3486	139	7	s.	s.	PROPN
cana-3486	139	8	wen	wen	PROPN
cana-3486	139	9	,	,	PUNCT
cana-3486	139	10	p.	p.	PROPN
cana-3486	139	11	li	li	PROPN
cana-3486	139	12	and	and	CCONJ
cana-3486	139	13	s.	s.	PROPN
cana-3486	139	14	feng	feng	PROPN
cana-3486	139	15	,	,	PUNCT
cana-3486	139	16	"	"	PUNCT
cana-3486	139	17	surface	surface	NOUN
cana-3486	139	18	defect	defect	NOUN
cana-3486	139	19	detection	detection	NOUN
cana-3486	139	20	of	of	ADP
cana-3486	139	21	fabric	fabric	NOUN
cana-3486	139	22	based	base	VERB
cana-3486	139	23	on	on	ADP
cana-3486	139	24	improved	improved	ADJ
cana-3486	139	25	faster	fast	ADV
cana-3486	139	26	r	r	NOUN
cana-3486	139	27	-	-	PUNCT
cana-3486	139	28	cnn	cnn	PROPN
cana-3486	139	29	,	,	PUNCT
cana-3486	139	30	"	"	PUNCT
cana-3486	139	31	2023	2023	NUM
cana-3486	139	32	ieee	ieee	NOUN
cana-3486	139	33	international	international	ADJ
cana-3486	139	34	conference	conference	NOUN
cana-3486	139	35	on	on	ADP
cana-3486	139	36	sensors	sensor	NOUN
cana-3486	139	37	,	,	PUNCT
cana-3486	139	38	electronics	electronic	NOUN
cana-3486	139	39	and	and	CCONJ
cana-3486	139	40	computer	computer	NOUN
cana-3486	139	41	engineering	engineering	NOUN
cana-3486	139	42	(	(	PUNCT
cana-3486	139	43	icsece	icsece	NOUN
cana-3486	139	44	)	)	PUNCT
cana-3486	139	45	,	,	PUNCT
cana-3486	139	46	jinzhou	jinzhou	PROPN
cana-3486	139	47	,	,	PUNCT
cana-3486	139	48	china	china	PROPN
cana-3486	139	49	,	,	PUNCT
cana-3486	139	50	2023	2023	NUM
cana-3486	139	51	,	,	PUNCT
cana-3486	139	52	pp	pp	ADJ
cana-3486	139	53	.	.	PUNCT
cana-3486	140	1	600	600	NUM
cana-3486	140	2	-	-	SYM
cana-3486	140	3	604	604	NUM
cana-3486	140	4	,	,	PUNCT
cana-3486	140	5	doi	doi	NOUN
cana-3486	140	6	:	:	PUNCT
cana-3486	140	7	10.1109	10.1109	NUM
cana-3486	140	8	/	/	SYM
cana-3486	141	1	icsece58870.2023.10263522	icsece58870.2023.10263522	NOUN
cana-3486	141	2	.	.	PUNCT
cana-3486	141	3	communications	communication	NOUN
cana-3486	141	4	on	on	ADP
cana-3486	141	5	applied	apply	VERB
cana-3486	141	6	nonlinear	nonlinear	ADJ
cana-3486	141	7	analysis	analysis	NOUN
cana-3486	141	8	issn	issn	NOUN
cana-3486	141	9	:	:	PUNCT
cana-3486	141	10	1074	1074	NUM
cana-3486	141	11	-	-	PUNCT
cana-3486	141	12	133x	133x	NUM
cana-3486	141	13	vol	vol	NOUN
cana-3486	141	14	32	32	NUM
cana-3486	141	15	no	no	NOUN
cana-3486	141	16	.	.	PUNCT
cana-3486	142	1	7s	7	NOUN
cana-3486	142	2	(	(	PUNCT
cana-3486	142	3	2025	2025	NUM
cana-3486	142	4	)	)	PUNCT
cana-3486	142	5	797	797	NUM
cana-3486	142	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3486	143	1	[	[	X
cana-3486	143	2	4	4	X
cana-3486	143	3	]	]	X
cana-3486	143	4	g.	g.	PROPN
cana-3486	143	5	owomugisha	owomugisha	PROPN
cana-3486	143	6	,	,	PUNCT
cana-3486	143	7	f.	f.	PROPN
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cana-3486	143	10	e.	e.	PROPN
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cana-3486	143	14	a.	a.	PROPN
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cana-3486	143	16	and	and	CCONJ
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cana-3486	143	18	biehl	biehl	NOUN
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cana-3486	143	20	"	"	PUNCT
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cana-3486	143	24	from	from	ADP
cana-3486	143	25	spectral	spectral	ADJ
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cana-3486	143	28	diagnosing	diagnose	VERB
cana-3486	143	29	cassava	cassava	NOUN
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cana-3486	143	31	,	,	PUNCT
cana-3486	143	32	"	"	PUNCT
cana-3486	143	33	in	in	ADP
cana-3486	143	34	ieee	ieee	NOUN
cana-3486	143	35	access	access	NOUN
cana-3486	143	36	,	,	PUNCT
cana-3486	143	37	vol	vol	NOUN
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cana-3486	143	41	pp	pp	ADJ
cana-3486	143	42	.	.	PUNCT
cana-3486	143	43	83355	83355	NUM
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cana-3486	143	45	83363	83363	NUM
cana-3486	143	46	,	,	PUNCT
cana-3486	143	47	2021	2021	NUM
cana-3486	143	48	,	,	PUNCT
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cana-3486	143	50	:	:	PUNCT
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cana-3486	144	2	5	5	NUM
cana-3486	144	3	]	]	PUNCT
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cana-3486	144	10	m.	m.	PROPN
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cana-3486	144	19	b.	b.	PROPN
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cana-3486	144	28	with	with	ADP
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cana-3486	144	31	for	for	ADP
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cana-3486	144	40	2024	2024	NUM
cana-3486	144	41	international	international	ADJ
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cana-3486	144	43	on	on	ADP
cana-3486	144	44	expert	expert	NOUN
cana-3486	144	45	clouds	cloud	NOUN
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cana-3486	144	47	applications	application	NOUN
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cana-3486	145	1	1	1	NUM
cana-3486	145	2	-	-	SYM
cana-3486	145	3	8	8	NUM
cana-3486	145	4	,	,	PUNCT
cana-3486	145	5	doi	doi	NOUN
cana-3486	145	6	:	:	PUNCT
cana-3486	145	7	10.1109	10.1109	NUM
cana-3486	145	8	/	/	SYM
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cana-3486	145	10	.	.	PUNCT
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cana-3486	146	2	6	6	NUM
cana-3486	146	3	]	]	PUNCT
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cana-3486	146	13	k.	k.	PROPN
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cana-3486	146	64	6	6	NUM
cana-3486	146	65	,	,	PUNCT
cana-3486	146	66	doi	doi	NOUN
cana-3486	146	67	:	:	PUNCT
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cana-3486	146	69	/	/	SYM
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cana-3486	146	71	.	.	PUNCT
cana-3486	147	1	[	[	X
cana-3486	147	2	7	7	X
cana-3486	147	3	]	]	X
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cana-3486	147	71	:	:	PUNCT
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cana-3486	148	35	(	(	PUNCT
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cana-3486	148	37	)	)	PUNCT
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cana-3486	149	2	-	-	SYM
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cana-3486	150	40	)	)	PUNCT
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cana-3486	151	34	in	in	ADP
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cana-3486	151	36	agriculture	agriculture	NOUN
cana-3486	151	37	,	,	PUNCT
cana-3486	151	38	"	"	PUNCT
cana-3486	151	39	2024	2024	NUM
cana-3486	151	40	mit	mit	NOUN
cana-3486	151	41	art	art	NOUN
cana-3486	151	42	,	,	PUNCT
cana-3486	151	43	design	design	NOUN
cana-3486	151	44	and	and	CCONJ
cana-3486	151	45	technology	technology	NOUN
cana-3486	151	46	school	school	NOUN
cana-3486	151	47	of	of	ADP
cana-3486	151	48	computing	compute	VERB
cana-3486	151	49	international	international	ADJ
cana-3486	151	50	conference	conference	NOUN
cana-3486	151	51	(	(	PUNCT
cana-3486	151	52	mitadtsocicon),pune	mitadtsocicon),pune	NOUN
cana-3486	151	53	,	,	PUNCT
cana-3486	151	54	india,2024,pp.1	india,2024,pp.1	NOUN
cana-3486	151	55	-	-	PUNCT
cana-3486	151	56	5,doi	5,doi	NUM
cana-3486	151	57	:	:	PUNCT
cana-3486	151	58	10.1109	10.1109	NUM
cana-3486	151	59	/	/	SYM
cana-3486	151	60	mitadtsocicon60330.2024.10575651	mitadtsocicon60330.2024.10575651	NOUN
cana-3486	151	61	.	.	PUNCT
cana-3486	152	1	[	[	X
cana-3486	152	2	11	11	NUM
cana-3486	152	3	]	]	PUNCT
cana-3486	152	4	s.	s.	PROPN
cana-3486	152	5	m.	m.	PROPN
cana-3486	152	6	riaz	riaz	PROPN
cana-3486	152	7	,	,	PUNCT
cana-3486	152	8	m.	m.	NOUN
cana-3486	152	9	ahsan	ahsan	PROPN
cana-3486	152	10	and	and	CCONJ
cana-3486	152	11	m.	m.	PROPN
cana-3486	152	12	u.	u.	PROPN
cana-3486	152	13	akram	akram	PROPN
cana-3486	152	14	,	,	PUNCT
cana-3486	152	15	"	"	PUNCT
cana-3486	152	16	diagnosis	diagnosis	NOUN
cana-3486	152	17	of	of	ADP
cana-3486	152	18	cassava	cassava	NOUN
cana-3486	152	19	leaf	leaf	NOUN
cana-3486	152	20	diseases	disease	NOUN
cana-3486	152	21	and	and	CCONJ
cana-3486	152	22	classification	classification	NOUN
cana-3486	152	23	using	use	VERB
cana-3486	152	24	deep	deep	ADJ
cana-3486	152	25	learning	learning	NOUN
cana-3486	152	26	techniques	technique	NOUN
cana-3486	152	27	,	,	PUNCT
cana-3486	152	28	"	"	PUNCT
cana-3486	152	29	2022	2022	NUM
cana-3486	152	30	16th	16th	ADJ
cana-3486	152	31	international	international	ADJ
cana-3486	152	32	conference	conference	NOUN
cana-3486	152	33	on	on	ADP
cana-3486	152	34	open	open	ADJ
cana-3486	152	35	source	source	NOUN
cana-3486	152	36	systems	system	NOUN
cana-3486	152	37	and	and	CCONJ
cana-3486	152	38	technologies	technology	NOUN
cana-3486	152	39	(	(	PUNCT
cana-3486	152	40	icosst	icosst	NOUN
cana-3486	152	41	)	)	PUNCT
cana-3486	152	42	,	,	PUNCT
cana-3486	152	43	lahore	lahore	NOUN
cana-3486	152	44	,	,	PUNCT
cana-3486	152	45	pakistan	pakistan	PROPN
cana-3486	152	46	,	,	PUNCT
cana-3486	152	47	2022	2022	NUM
cana-3486	152	48	,	,	PUNCT
cana-3486	152	49	pp	pp	ADJ
cana-3486	152	50	.	.	PUNCT
cana-3486	153	1	1	1	NUM
cana-3486	153	2	-	-	SYM
cana-3486	153	3	8	8	NUM
cana-3486	153	4	,	,	PUNCT
cana-3486	153	5	doi	doi	NOUN
cana-3486	153	6	:	:	PUNCT
cana-3486	153	7	10.1109	10.1109	NUM
cana-3486	153	8	/	/	SYM
cana-3486	153	9	icosst57195.2022.10016854	icosst57195.2022.10016854	PROPN
cana-3486	153	10	.	.	PUNCT
cana-3486	154	1	[	[	X
cana-3486	154	2	12	12	NUM
cana-3486	154	3	]	]	PUNCT
cana-3486	154	4	s.	s.	PROPN
cana-3486	154	5	endargiri	endargiri	PROPN
cana-3486	154	6	and	and	CCONJ
cana-3486	154	7	k.	k.	PROPN
cana-3486	154	8	laabidi	laabidi	PROPN
cana-3486	154	9	,	,	PUNCT
cana-3486	154	10	"	"	PUNCT
cana-3486	154	11	automatic	automatic	ADJ
cana-3486	154	12	healthcare	healthcare	NOUN
cana-3486	154	13	diagnosis	diagnosis	NOUN
cana-3486	154	14	and	and	CCONJ
cana-3486	154	15	prediction	prediction	NOUN
cana-3486	154	16	assessment	assessment	NOUN
cana-3486	154	17	based	base	VERB
cana-3486	154	18	on	on	ADP
cana-3486	154	19	ai	ai	PROPN
cana-3486	154	20	multiclassification	multiclassification	NOUN
cana-3486	154	21	algorithm	algorithm	NOUN
cana-3486	154	22	,	,	PUNCT
cana-3486	154	23	"	"	PUNCT
cana-3486	154	24	2020	2020	NUM
cana-3486	154	25	16th	16th	ADJ
cana-3486	154	26	international	international	ADJ
cana-3486	154	27	computer	computer	NOUN
cana-3486	154	28	engineering	engineering	NOUN
cana-3486	154	29	conference	conference	NOUN
cana-3486	154	30	(	(	PUNCT
cana-3486	154	31	icenco	icenco	NOUN
cana-3486	154	32	)	)	PUNCT
cana-3486	154	33	,	,	PUNCT
cana-3486	154	34	cairo	cairo	PROPN
cana-3486	154	35	,	,	PUNCT
cana-3486	154	36	egypt	egypt	PROPN
cana-3486	154	37	,	,	PUNCT
cana-3486	154	38	2020	2020	NUM
cana-3486	154	39	,	,	PUNCT
cana-3486	154	40	pp	pp	ADV
cana-3486	154	41	.	.	PUNCT
cana-3486	155	1	112	112	NUM
cana-3486	155	2	-	-	SYM
cana-3486	155	3	117	117	NUM
cana-3486	155	4	,	,	PUNCT
cana-3486	155	5	doi	doi	NOUN
cana-3486	155	6	:	:	PUNCT
cana-3486	155	7	10.1109	10.1109	NUM
cana-3486	155	8	/	/	SYM
cana-3486	155	9	icenco49778.2020.9357385	icenco49778.2020.9357385	PROPN
cana-3486	155	10	.	.	PUNCT
cana-3486	156	1	[	[	X
cana-3486	156	2	13	13	NUM
cana-3486	156	3	]	]	PUNCT
cana-3486	156	4	p.	p.	NOUN
cana-3486	156	5	a	a	PROPN
cana-3486	156	6	,	,	PUNCT
cana-3486	156	7	s.	s.	PROPN
cana-3486	156	8	kumar	kumar	PROPN
cana-3486	156	9	and	and	CCONJ
cana-3486	156	10	s.	s.	PROPN
cana-3486	156	11	pundeer	pundeer	PROPN
cana-3486	156	12	,	,	PUNCT
cana-3486	156	13	"	"	PUNCT
cana-3486	156	14	performance	performance	NOUN
cana-3486	156	15	assessment	assessment	NOUN
cana-3486	156	16	of	of	ADP
cana-3486	156	17	data	datum	NOUN
cana-3486	156	18	centric	centric	NOUN
cana-3486	156	19	and	and	CCONJ
cana-3486	156	20	model	model	NOUN
cana-3486	156	21	centric	centric	ADJ
cana-3486	156	22	approach	approach	NOUN
cana-3486	156	23	for	for	ADP
cana-3486	156	24	premature	premature	ADJ
cana-3486	156	25	detection	detection	NOUN
cana-3486	156	26	of	of	ADP
cana-3486	156	27	leaf	leaf	NOUN
cana-3486	156	28	disease	disease	NOUN
cana-3486	156	29	,	,	PUNCT
cana-3486	156	30	"	"	PUNCT
cana-3486	156	31	2024	2024	NUM
cana-3486	156	32	international	international	ADJ
cana-3486	156	33	conference	conference	NOUN
cana-3486	156	34	on	on	ADP
cana-3486	156	35	communication	communication	NOUN
cana-3486	156	36	,	,	PUNCT
cana-3486	156	37	computer	computer	NOUN
cana-3486	156	38	sciences	science	NOUN
cana-3486	156	39	and	and	CCONJ
cana-3486	156	40	engineering	engineering	NOUN
cana-3486	156	41	(	(	PUNCT
cana-3486	156	42	ic3se	ic3se	NUM
cana-3486	156	43	)	)	PUNCT
cana-3486	156	44	,	,	PUNCT
cana-3486	156	45	gautam	gautam	PROPN
cana-3486	156	46	buddha	buddha	PROPN
cana-3486	156	47	nagar	nagar	PROPN
cana-3486	156	48	,	,	PUNCT
cana-3486	156	49	india	india	PROPN
cana-3486	156	50	,	,	PUNCT
cana-3486	156	51	2024	2024	NUM
cana-3486	156	52	,	,	PUNCT
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cana-3486	156	54	.	.	PUNCT
cana-3486	157	1	172	172	NUM
cana-3486	157	2	-	-	SYM
cana-3486	157	3	176	176	NUM
cana-3486	157	4	,	,	PUNCT
cana-3486	157	5	doi	doi	NOUN
cana-3486	157	6	:	:	PUNCT
cana-3486	157	7	10.1109	10.1109	NUM
cana-3486	157	8	/	/	SYM
cana-3486	157	9	ic3se62002.2024.10593510	ic3se62002.2024.10593510	NOUN
cana-3486	157	10	.	.	PUNCT
cana-3486	158	1	[	[	X
cana-3486	158	2	14	14	NUM
cana-3486	158	3	]	]	X
cana-3486	158	4	y.	y.	PROPN
cana-3486	158	5	liang	liang	PROPN
cana-3486	158	6	,	,	PUNCT
cana-3486	158	7	l.	l.	PROPN
cana-3486	158	8	lu	lu	PROPN
cana-3486	158	9	,	,	PUNCT
cana-3486	158	10	q.	q.	PROPN
cana-3486	158	11	xiao	xiao	PROPN
cana-3486	158	12	and	and	CCONJ
cana-3486	158	13	s.	s.	PROPN
cana-3486	158	14	yan	yan	PROPN
cana-3486	158	15	,	,	PUNCT
cana-3486	158	16	"	"	PUNCT
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cana-3486	158	20	for	for	ADP
cana-3486	158	21	convolutional	convolutional	ADJ
cana-3486	158	22	neural	neural	ADJ
cana-3486	158	23	networks	network	NOUN
cana-3486	158	24	on	on	ADP
cana-3486	158	25	fpgas	fpgas	NOUN
cana-3486	158	26	,	,	PUNCT
cana-3486	158	27	"	"	PUNCT
cana-3486	158	28	in	in	ADP
cana-3486	158	29	ieee	ieee	NOUN
cana-3486	158	30	transactions	transaction	NOUN
cana-3486	158	31	on	on	ADP
cana-3486	158	32	computer	computer	NOUN
cana-3486	158	33	-	-	PUNCT
cana-3486	158	34	aided	aid	VERB
cana-3486	158	35	design	design	NOUN
cana-3486	158	36	of	of	ADP
cana-3486	158	37	integrated	integrated	ADJ
cana-3486	158	38	circuits	circuit	NOUN
cana-3486	158	39	and	and	CCONJ
cana-3486	158	40	systems	system	NOUN
cana-3486	158	41	,	,	PUNCT
cana-3486	158	42	vol	vol	NOUN
cana-3486	158	43	.	.	PROPN
cana-3486	158	44	39	39	NUM
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cana-3486	158	49	,	,	PUNCT
cana-3486	158	50	pp	pp	ADJ
cana-3486	158	51	.	.	PUNCT
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cana-3486	158	53	-	-	SYM
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cana-3486	158	58	,	,	PUNCT
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cana-3486	158	60	:	:	PUNCT
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cana-3486	158	62	/	/	SYM
cana-3486	158	63	tcad.2019.2897701	tcad.2019.2897701	NOUN
cana-3486	158	64	.	.	PUNCT
cana-3486	159	1	[	[	X
cana-3486	159	2	15	15	NUM
cana-3486	159	3	]	]	X
cana-3486	159	4	s.	s.	PROPN
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cana-3486	159	6	,	,	PUNCT
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cana-3486	159	20	in	in	ADP
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cana-3486	159	30	on	on	ADP
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cana-3486	159	36	industry	industry	NOUN
cana-3486	159	37	(	(	PUNCT
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cana-3486	159	39	)	)	PUNCT
cana-3486	159	40	,	,	PUNCT
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cana-3486	159	44	,	,	PUNCT
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cana-3486	159	46	,	,	PUNCT
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cana-3486	160	2	-	-	SYM
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cana-3486	161	3	]	]	X
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cana-3486	161	35	conference	conference	NOUN
cana-3486	161	36	in	in	ADP
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cana-3486	161	43	systems	system	NOUN
cana-3486	161	44	(	(	PUNCT
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cana-3486	162	2	-	-	SYM
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cana-3486	162	4	,	,	PUNCT
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cana-3486	162	6	:	:	PUNCT
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cana-3486	162	8	/	/	SYM
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cana-3486	162	10	.	.	PUNCT
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cana-3486	163	7	:	:	PUNCT
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cana-3486	163	10	133x	133x	NUM
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cana-3486	163	14	.	.	PUNCT
cana-3486	164	1	7s	7	NOUN
cana-3486	164	2	(	(	PUNCT
cana-3486	164	3	2025	2025	NUM
cana-3486	164	4	)	)	PUNCT
cana-3486	164	5	798	798	NUM
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cana-3486	165	1	[	[	X
cana-3486	165	2	17	17	NUM
cana-3486	165	3	]	]	X
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cana-3486	165	10	r.	r.	PROPN
cana-3486	165	11	gupta	gupta	PROPN
cana-3486	165	12	and	and	CCONJ
cana-3486	165	13	a.	a.	NOUN
cana-3486	165	14	sharma	sharma	PROPN
cana-3486	165	15	,	,	PUNCT
cana-3486	165	16	"	"	PUNCT
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cana-3486	165	18	of	of	ADP
cana-3486	165	19	plant	plant	NOUN
cana-3486	165	20	diseases	disease	NOUN
cana-3486	165	21	using	use	VERB
cana-3486	165	22	densenet	densenet	NOUN
cana-3486	165	23	121	121	NUM
cana-3486	165	24	transfer	transfer	NOUN
cana-3486	165	25	learning	learning	NOUN
cana-3486	165	26	model	model	NOUN
cana-3486	165	27	,	,	PUNCT
cana-3486	165	28	"	"	PUNCT
cana-3486	165	29	2023	2023	NUM
cana-3486	165	30	international	international	ADJ
cana-3486	165	31	conference	conference	NOUN
cana-3486	165	32	on	on	ADP
cana-3486	165	33	advances	advance	NOUN
cana-3486	165	34	in	in	ADP
cana-3486	165	35	computing	computing	NOUN
cana-3486	165	36	,	,	PUNCT
cana-3486	165	37	communication	communication	NOUN
cana-3486	165	38	and	and	CCONJ
cana-3486	165	39	applied	apply	VERB
cana-3486	165	40	informatics	informatic	NOUN
cana-3486	165	41	(	(	PUNCT
cana-3486	165	42	accai	accai	ADJ
cana-3486	165	43	)	)	PUNCT
cana-3486	165	44	,	,	PUNCT
cana-3486	165	45	chennai	chennai	PROPN
cana-3486	165	46	,	,	PUNCT
cana-3486	165	47	india	india	PROPN
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cana-3486	165	49	2023	2023	NUM
cana-3486	165	50	,	,	PUNCT
cana-3486	165	51	pp	pp	ADJ
cana-3486	165	52	.	.	PUNCT
cana-3486	166	1	1	1	NUM
cana-3486	166	2	-	-	SYM
cana-3486	166	3	6	6	NUM
cana-3486	166	4	,	,	PUNCT
cana-3486	166	5	doi	doi	NOUN
cana-3486	166	6	:	:	PUNCT
cana-3486	166	7	10.1109	10.1109	NUM
cana-3486	166	8	/	/	SYM
cana-3486	167	1	accai58221.2023.10200401	accai58221.2023.10200401	PROPN
cana-3486	167	2	.	.	PUNCT
cana-3486	168	1	[	[	X
cana-3486	168	2	18	18	NUM
cana-3486	168	3	]	]	PUNCT
cana-3486	168	4	a.	a.	NOUN
cana-3486	168	5	li	li	PROPN
cana-3486	168	6	,	,	PUNCT
cana-3486	168	7	r.	r.	PROPN
cana-3486	168	8	gao	gao	PROPN
cana-3486	168	9	,	,	PUNCT
cana-3486	168	10	j.	j.	PROPN
cana-3486	168	11	fu	fu	PROPN
cana-3486	168	12	and	and	CCONJ
cana-3486	168	13	f.	f.	PROPN
cana-3486	168	14	yang	yang	PROPN
cana-3486	168	15	,	,	PUNCT
cana-3486	168	16	"	"	PUNCT
cana-3486	168	17	research	research	NOUN
cana-3486	168	18	on	on	ADP
cana-3486	168	19	the	the	DET
cana-3486	168	20	target	target	NOUN
cana-3486	168	21	cargo	cargo	NOUN
cana-3486	168	22	identification	identification	NOUN
cana-3486	168	23	method	method	NOUN
cana-3486	168	24	based	base	VERB
cana-3486	168	25	on	on	ADP
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cana-3486	168	27	,	,	PUNCT
cana-3486	168	28	"	"	PUNCT
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cana-3486	168	30	14th	14th	ADJ
cana-3486	168	31	international	international	ADJ
cana-3486	168	32	symposium	symposium	NOUN
cana-3486	168	33	on	on	ADP
cana-3486	168	34	computational	computational	ADJ
cana-3486	168	35	intelligence	intelligence	NOUN
cana-3486	168	36	and	and	CCONJ
cana-3486	168	37	design	design	NOUN
cana-3486	168	38	(	(	PUNCT
cana-3486	168	39	iscid	iscid	NOUN
cana-3486	168	40	)	)	PUNCT
cana-3486	168	41	,	,	PUNCT
cana-3486	168	42	hangzhou	hangzhou	PROPN
cana-3486	168	43	,	,	PUNCT
cana-3486	168	44	china	china	PROPN
cana-3486	168	45	,	,	PUNCT
cana-3486	168	46	2021	2021	NUM
cana-3486	168	47	,	,	PUNCT
cana-3486	168	48	pp	pp	ADV
cana-3486	168	49	.	.	PUNCT
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cana-3486	169	2	-	-	SYM
cana-3486	169	3	35	35	NUM
cana-3486	169	4	,	,	PUNCT
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cana-3486	169	6	:	:	PUNCT
cana-3486	169	7	10.1109	10.1109	NUM
cana-3486	169	8	/	/	SYM
cana-3486	169	9	iscid52796.2021.00015	iscid52796.2021.00015	NOUN
cana-3486	169	10	.	.	PUNCT
cana-3486	170	1	[	[	X
cana-3486	170	2	19	19	NUM
cana-3486	170	3	]	]	X
cana-3486	170	4	p.	p.	PROPN
cana-3486	170	5	r.	r.	PROPN
cana-3486	170	6	jeyaraj	jeyaraj	PROPN
cana-3486	170	7	,	,	PUNCT
cana-3486	170	8	e.	e.	PROPN
cana-3486	170	9	r.	r.	PROPN
cana-3486	170	10	samuel	samuel	PROPN
cana-3486	170	11	nadar	nadar	PROPN
cana-3486	170	12	and	and	CCONJ
cana-3486	170	13	b.	b.	PROPN
cana-3486	170	14	k.	k.	PROPN
cana-3486	170	15	panigrahi	panigrahi	PROPN
cana-3486	170	16	,	,	PUNCT
cana-3486	170	17	"	"	PUNCT
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cana-3486	170	19	convolution	convolution	NOUN
cana-3486	170	20	neural	neural	ADJ
cana-3486	170	21	network	network	NOUN
cana-3486	170	22	based	base	VERB
cana-3486	170	23	hyperspectral	hyperspectral	ADJ
cana-3486	170	24	imagery	imagery	NOUN
cana-3486	170	25	classification	classification	NOUN
cana-3486	170	26	for	for	ADP
cana-3486	170	27	accurate	accurate	ADJ
cana-3486	170	28	cancerous	cancerous	ADJ
cana-3486	170	29	region	region	NOUN
cana-3486	170	30	detection	detection	NOUN
cana-3486	170	31	,	,	PUNCT
cana-3486	170	32	"	"	PUNCT
cana-3486	170	33	2019	2019	NUM
cana-3486	170	34	ieee	ieee	NOUN
cana-3486	170	35	conference	conference	NOUN
cana-3486	170	36	on	on	ADP
cana-3486	170	37	information	information	NOUN
cana-3486	170	38	and	and	CCONJ
cana-3486	170	39	communication	communication	NOUN
cana-3486	170	40	technology	technology	NOUN
cana-3486	170	41	,	,	PUNCT
cana-3486	170	42	allahabad	allahabad	PROPN
cana-3486	170	43	,	,	PUNCT
cana-3486	170	44	india	india	PROPN
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cana-3486	170	46	2019	2019	NUM
cana-3486	170	47	,	,	PUNCT
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cana-3486	171	2	-	-	SYM
cana-3486	171	3	6	6	NUM
cana-3486	171	4	,	,	PUNCT
cana-3486	171	5	doi	doi	NOUN
cana-3486	171	6	:	:	PUNCT
cana-3486	171	7	10.1109	10.1109	NUM
cana-3486	171	8	/	/	SYM
cana-3486	171	9	cict48419.2019.9066215	cict48419.2019.9066215	NOUN
cana-3486	171	10	.	.	PUNCT
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cana-3486	172	2	20	20	NUM
cana-3486	172	3	]	]	PUNCT
cana-3486	172	4	j.	j.	PROPN
cana-3486	172	5	zhang	zhang	PROPN
cana-3486	172	6	and	and	CCONJ
cana-3486	172	7	w.	w.	PROPN
cana-3486	172	8	liu	liu	PROPN
cana-3486	172	9	,	,	PUNCT
cana-3486	172	10	"	"	PUNCT
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cana-3486	172	12	and	and	CCONJ
cana-3486	172	13	analyzing	analyze	VERB
cana-3486	172	14	iot	iot	ADJ
cana-3486	172	15	performance	performance	NOUN
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cana-3486	172	20	,	,	PUNCT
cana-3486	172	21	"	"	PUNCT
cana-3486	172	22	2023	2023	NUM
cana-3486	172	23	ieee	ieee	NOUN
cana-3486	172	24	2nd	2nd	ADJ
cana-3486	172	25	industrial	industrial	ADJ
cana-3486	172	26	electronics	electronic	NOUN
cana-3486	172	27	society	society	NOUN
cana-3486	172	28	annual	annual	ADJ
cana-3486	172	29	on	on	ADP
cana-3486	172	30	-	-	PUNCT
cana-3486	172	31	line	line	NOUN
cana-3486	172	32	conference	conference	NOUN
cana-3486	172	33	(	(	PUNCT
cana-3486	172	34	oncon	oncon	NOUN
cana-3486	172	35	)	)	PUNCT
cana-3486	172	36	,	,	PUNCT
cana-3486	172	37	sc	sc	PROPN
cana-3486	172	38	,	,	PUNCT
cana-3486	172	39	usa	usa	PROPN
cana-3486	172	40	,	,	PUNCT
cana-3486	172	41	2023	2023	NUM
cana-3486	172	42	,	,	PUNCT
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cana-3486	172	44	.	.	PUNCT
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cana-3486	173	2	-	-	SYM
cana-3486	173	3	6	6	NUM
cana-3486	173	4	,	,	PUNCT
cana-3486	173	5	doi	doi	NOUN
cana-3486	173	6	:	:	PUNCT
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cana-3486	173	8	/	/	SYM
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cana-3486	174	2	21	21	NUM
cana-3486	174	3	]	]	X
cana-3486	174	4	g.	g.	PROPN
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cana-3486	174	6	,	,	PUNCT
cana-3486	174	7	r.	r.	PROPN
cana-3486	174	8	s.	s.	PROPN
cana-3486	174	9	kumari	kumari	PROPN
cana-3486	174	10	,	,	PUNCT
cana-3486	174	11	s.	s.	PROPN
cana-3486	174	12	suganthi	suganthi	PROPN
cana-3486	174	13	,	,	PUNCT
cana-3486	174	14	k.	k.	PROPN
cana-3486	174	15	agalya	agalya	PROPN
cana-3486	174	16	,	,	PUNCT
cana-3486	174	17	t.	t.	PROPN
cana-3486	174	18	elangovan	elangovan	PROPN
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cana-3486	174	20	d.	d.	PROPN
cana-3486	174	21	s.	s.	PROPN
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cana-3486	174	23	,	,	PUNCT
cana-3486	174	24	"	"	PUNCT
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cana-3486	174	26	yield	yield	NOUN
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cana-3486	174	29	cnn	cnn	PROPN
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cana-3486	174	31	"	"	PUNCT
cana-3486	174	32	2023	2023	NUM
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cana-3486	174	34	conference	conference	NOUN
cana-3486	174	35	on	on	ADP
cana-3486	174	36	artificial	artificial	ADJ
cana-3486	174	37	intelligence	intelligence	NOUN
cana-3486	174	38	and	and	CCONJ
cana-3486	174	39	knowledge	knowledge	NOUN
cana-3486	174	40	discovery	discovery	NOUN
cana-3486	174	41	in	in	ADP
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cana-3486	174	44	(	(	PUNCT
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cana-3486	174	58	4	4	NUM
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cana-3486	174	60	doi	doi	NOUN
cana-3486	174	61	:	:	PUNCT
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cana-3486	174	63	/	/	SYM
cana-3486	174	64	iceconf57129.2023.10084304	iceconf57129.2023.10084304	PROPN
cana-3486	174	65	.	.	PUNCT
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cana-3486	175	2	22	22	NUM
cana-3486	175	3	]	]	PUNCT
cana-3486	175	4	j.	j.	PROPN
cana-3486	175	5	zhao	zhao	PROPN
cana-3486	175	6	,	,	PUNCT
cana-3486	175	7	a.	a.	PROPN
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cana-3486	175	13	q.	q.	PROPN
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cana-3486	175	25	for	for	ADP
cana-3486	175	26	vvc	vvc	NOUN
cana-3486	175	27	,	,	PUNCT
cana-3486	175	28	"	"	PUNCT
cana-3486	175	29	in	in	ADP
cana-3486	175	30	ieee	ieee	NOUN
cana-3486	175	31	access	access	NOUN
cana-3486	175	32	,	,	PUNCT
cana-3486	175	33	vol	vol	NOUN
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cana-3486	175	35	10	10	NUM
cana-3486	175	36	,	,	PUNCT
cana-3486	175	37	pp	pp	ADJ
cana-3486	175	38	.	.	PUNCT
cana-3486	175	39	100337	100337	NUM
cana-3486	175	40	-	-	SYM
cana-3486	175	41	100347	100347	NUM
cana-3486	175	42	,	,	PUNCT
cana-3486	175	43	2022	2022	NUM
cana-3486	175	44	,	,	PUNCT
cana-3486	175	45	doi	doi	NOUN
cana-3486	175	46	:	:	PUNCT
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cana-3486	175	50	.	.	PUNCT
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cana-3486	176	6	dharani	dharani	PROPN
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cana-3486	176	8	r.	r.	PROPN
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cana-3486	176	10	,	,	PUNCT
cana-3486	176	11	s.	s.	PROPN
cana-3486	176	12	p.	p.	PROPN
cana-3486	176	13	gudadhe	gudadhe	PROPN
cana-3486	176	14	,	,	PUNCT
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cana-3486	176	16	a.	a.	PROPN
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cana-3486	176	31	"	"	PUNCT
cana-3486	176	32	2022	2022	NUM
cana-3486	176	33	2nd	2nd	ADJ
cana-3486	176	34	international	international	ADJ
cana-3486	176	35	conference	conference	NOUN
cana-3486	176	36	on	on	ADP
cana-3486	176	37	technological	technological	ADJ
cana-3486	176	38	advancements	advancement	NOUN
cana-3486	176	39	in	in	ADP
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cana-3486	176	41	sciences	science	NOUN
cana-3486	176	42	(	(	PUNCT
cana-3486	176	43	ictacs	ictac	NOUN
cana-3486	176	44	)	)	PUNCT
cana-3486	176	45	,	,	PUNCT
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cana-3486	176	55	-	-	SYM
cana-3486	176	56	650	650	NUM
cana-3486	176	57	,	,	PUNCT
cana-3486	176	58	doi	doi	NOUN
cana-3486	176	59	:	:	PUNCT
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