id	sid	tid	token	lemma	pos
cana-4558	1	1	communications	communication	NOUN
cana-4558	1	2	on	on	ADP
cana-4558	1	3	applied	apply	VERB
cana-4558	1	4	nonlinear	nonlinear	ADJ
cana-4558	1	5	analysis	analysis	NOUN
cana-4558	1	6	issn	issn	NOUN
cana-4558	1	7	:	:	PUNCT
cana-4558	1	8	1074	1074	NUM
cana-4558	1	9	-	-	PUNCT
cana-4558	1	10	133x	133x	NUM
cana-4558	1	11	vol	vol	NOUN
cana-4558	1	12	32	32	NUM
cana-4558	1	13	no	no	NOUN
cana-4558	1	14	.	.	PUNCT
cana-4558	2	1	9s	9s	NUM
cana-4558	2	2	(	(	PUNCT
cana-4558	2	3	2025	2025	NUM
cana-4558	2	4	)	)	PUNCT
cana-4558	2	5	2531	2531	NUM
cana-4558	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	2	7	accurate	accurate	ADJ
cana-4558	2	8	identification	identification	NOUN
cana-4558	2	9	of	of	ADP
cana-4558	2	10	leaf	leaf	NOUN
cana-4558	2	11	disease	disease	NOUN
cana-4558	2	12	using	use	VERB
cana-4558	2	13	yolov4	yolov4	PROPN
cana-4558	2	14	algorithm	algorithm	PROPN
cana-4558	2	15	1a.yoganathan	1a.yoganathan	NUM
cana-4558	2	16	,	,	PUNCT
cana-4558	2	17	2p.s.periasamy	2p.s.periasamy	NUM
cana-4558	2	18	,	,	PUNCT
cana-4558	2	19	3c	3c	NUM
cana-4558	2	20	.	.	PUNCT
cana-4558	3	1	devipriya	devipriya	PROPN
cana-4558	3	2	,	,	PUNCT
cana-4558	3	3	4p	4p	PROPN
cana-4558	3	4	.	.	PUNCT
cana-4558	4	1	anitha	anitha	PROPN
cana-4558	4	2	,	,	PUNCT
cana-4558	4	3	1assistant	1assistant	NUM
cana-4558	4	4	professor	professor	NOUN
cana-4558	4	5	,	,	PUNCT
cana-4558	4	6	department	department	NOUN
cana-4558	4	7	of	of	ADP
cana-4558	4	8	computer	computer	NOUN
cana-4558	4	9	applications	application	NOUN
cana-4558	4	10	,	,	PUNCT
cana-4558	4	11	k.s.r	k.s.r	PROPN
cana-4558	4	12	.	.	PROPN
cana-4558	5	1	college	college	NOUN
cana-4558	5	2	of	of	ADP
cana-4558	5	3	engineering	engineering	PROPN
cana-4558	5	4	,	,	PUNCT
cana-4558	5	5	tiruchengode	tiruchengode	NOUN
cana-4558	5	6	,	,	PUNCT
cana-4558	5	7	india	india	PROPN
cana-4558	5	8	.	.	PUNCT
cana-4558	6	1	email:yoguayn@gmail.com	email:yoguayn@gmail.com	X
cana-4558	7	1	2professor	2professor	NUM
cana-4558	7	2	,	,	PUNCT
cana-4558	7	3	department	department	NOUN
cana-4558	7	4	of	of	ADP
cana-4558	7	5	electronics	electronic	NOUN
cana-4558	7	6	and	and	CCONJ
cana-4558	7	7	communication	communication	NOUN
cana-4558	7	8	engineering	engineering	NOUN
cana-4558	7	9	,	,	PUNCT
cana-4558	7	10	k.s.r	k.s.r	PROPN
cana-4558	7	11	.	.	PROPN
cana-4558	8	1	college	college	NOUN
cana-4558	8	2	of	of	ADP
cana-4558	8	3	engineering	engineering	PROPN
cana-4558	8	4	,	,	PUNCT
cana-4558	8	5	tiruchengode	tiruchengode	NOUN
cana-4558	8	6	,	,	PUNCT
cana-4558	8	7	india	india	PROPN
cana-4558	8	8	.	.	PUNCT
cana-4558	8	9	email	email	NOUN
cana-4558	8	10	:	:	PUNCT
cana-4558	9	1	psperiasamy@gmail.com	psperiasamy@gmail.com	PROPN
cana-4558	9	2	3research	3research	NUM
cana-4558	9	3	scholar	scholar	NOUN
cana-4558	9	4	,	,	PUNCT
cana-4558	9	5	department	department	NOUN
cana-4558	9	6	of	of	ADP
cana-4558	9	7	computer	computer	NOUN
cana-4558	9	8	applications	application	NOUN
cana-4558	9	9	,	,	PUNCT
cana-4558	9	10	k.s.r	k.s.r	PROPN
cana-4558	9	11	.	.	PROPN
cana-4558	9	12	college	college	NOUN
cana-4558	9	13	of	of	ADP
cana-4558	9	14	engineering	engineering	PROPN
cana-4558	9	15	,	,	PUNCT
cana-4558	9	16	tiruchengode	tiruchengode	NOUN
cana-4558	9	17	,	,	PUNCT
cana-4558	9	18	india	india	PROPN
cana-4558	9	19	.	.	PUNCT
cana-4558	10	1	email:devipriyacmca2425@ksrce.ac.in	email:devipriyacmca2425@ksrce.ac.in	PROPN
cana-4558	10	2	4professor	4professor	PROPN
cana-4558	10	3	&	&	CCONJ
cana-4558	10	4	head	head	PROPN
cana-4558	10	5	,	,	PUNCT
cana-4558	10	6	department	department	NOUN
cana-4558	10	7	of	of	ADP
cana-4558	10	8	computer	computer	NOUN
cana-4558	10	9	applications	application	NOUN
cana-4558	10	10	,	,	PUNCT
cana-4558	10	11	k	k	PROPN
cana-4558	10	12	s	s	PROPN
cana-4558	10	13	r	r	NOUN
cana-4558	10	14	college	college	NOUN
cana-4558	10	15	of	of	ADP
cana-4558	10	16	engineering	engineering	NOUN
cana-4558	10	17	,	,	PUNCT
cana-4558	10	18	tiruchengode	tiruchengode	NOUN
cana-4558	10	19	,	,	PUNCT
cana-4558	10	20	india	india	PROPN
cana-4558	10	21	email	email	NOUN
cana-4558	10	22	:	:	PUNCT
cana-4558	10	23	pspo3ster@gmail.com	pspo3ster@gmail.com	PROPN
cana-4558	10	24	article	article	NOUN
cana-4558	10	25	history	history	NOUN
cana-4558	10	26	:	:	PUNCT
cana-4558	10	27	received	receive	VERB
cana-4558	10	28	:	:	PUNCT
cana-4558	10	29	12	12	NUM
cana-4558	10	30	-	-	SYM
cana-4558	10	31	01	01	NUM
cana-4558	10	32	-	-	PUNCT
cana-4558	10	33	2025	2025	NUM
cana-4558	10	34	revised	revise	VERB
cana-4558	10	35	:	:	PUNCT
cana-4558	10	36	15	15	NUM
cana-4558	10	37	-	-	NUM
cana-4558	10	38	02	02	NUM
cana-4558	10	39	-	-	PUNCT
cana-4558	10	40	2025	2025	NUM
cana-4558	10	41	accepted	accept	VERB
cana-4558	10	42	:	:	PUNCT
cana-4558	10	43	01	01	NUM
cana-4558	10	44	-	-	SYM
cana-4558	10	45	03	03	NUM
cana-4558	10	46	-	-	PUNCT
cana-4558	10	47	2025	2025	NUM
cana-4558	10	48	abstract	abstract	NOUN
cana-4558	10	49	:	:	PUNCT
cana-4558	10	50	aim	aim	VERB
cana-4558	10	51	:	:	PUNCT
cana-4558	10	52	this	this	DET
cana-4558	10	53	study	study	NOUN
cana-4558	10	54	aims	aim	VERB
cana-4558	10	55	at	at	ADP
cana-4558	10	56	comparing	compare	VERB
cana-4558	10	57	the	the	DET
cana-4558	10	58	effectiveness	effectiveness	NOUN
cana-4558	10	59	of	of	ADP
cana-4558	10	60	the	the	DET
cana-4558	10	61	yolov4	yolov4	PROPN
cana-4558	10	62	algorithm	algorithm	NOUN
cana-4558	10	63	against	against	ADP
cana-4558	10	64	models	model	NOUN
cana-4558	10	65	based	base	VERB
cana-4558	10	66	on	on	ADP
cana-4558	10	67	convolutional	convolutional	ADJ
cana-4558	10	68	neural	neural	ADJ
cana-4558	10	69	networks	network	NOUN
cana-4558	10	70	in	in	ADP
cana-4558	10	71	order	order	NOUN
cana-4558	10	72	to	to	PART
cana-4558	10	73	increase	increase	VERB
cana-4558	10	74	the	the	DET
cana-4558	10	75	accuracy	accuracy	NOUN
cana-4558	10	76	in	in	ADP
cana-4558	10	77	disease	disease	NOUN
cana-4558	10	78	identification	identification	NOUN
cana-4558	10	79	.	.	PUNCT
cana-4558	11	1	materials	material	NOUN
cana-4558	11	2	and	and	CCONJ
cana-4558	11	3	methods	method	NOUN
cana-4558	11	4	:	:	PUNCT
cana-4558	11	5	for	for	ADP
cana-4558	11	6	this	this	DET
cana-4558	11	7	investigation	investigation	NOUN
cana-4558	11	8	,	,	PUNCT
cana-4558	11	9	two	two	NUM
cana-4558	11	10	groups	group	NOUN
cana-4558	11	11	were	be	AUX
cana-4558	11	12	tested	test	VERB
cana-4558	11	13	.	.	PUNCT
cana-4558	12	1	it	it	PRON
cana-4558	12	2	involved	involve	VERB
cana-4558	12	3	training	training	NOUN
cana-4558	12	4	and	and	CCONJ
cana-4558	12	5	evaluating	evaluate	VERB
cana-4558	12	6	the	the	DET
cana-4558	12	7	yolov4	yolov4	NOUN
cana-4558	12	8	-	-	PUNCT
cana-4558	12	9	based	base	VERB
cana-4558	12	10	leaf	leaf	NOUN
cana-4558	12	11	disease	disease	NOUN
cana-4558	12	12	detection	detection	NOUN
cana-4558	12	13	model	model	NOUN
cana-4558	12	14	deployed	deploy	VERB
cana-4558	12	15	in	in	ADP
cana-4558	12	16	group	group	NOUN
cana-4558	12	17	1	1	NUM
cana-4558	12	18	on	on	ADP
cana-4558	12	19	26	26	NUM
cana-4558	12	20	samples	sample	NOUN
cana-4558	12	21	of	of	ADP
cana-4558	12	22	diseased	diseased	ADJ
cana-4558	12	23	and	and	CCONJ
cana-4558	12	24	healthy	healthy	ADJ
cana-4558	12	25	leaf	leaf	NOUN
cana-4558	12	26	images	image	NOUN
cana-4558	12	27	.	.	PUNCT
cana-4558	13	1	this	this	PRON
cana-4558	13	2	was	be	AUX
cana-4558	13	3	done	do	VERB
cana-4558	13	4	while	while	SCONJ
cana-4558	13	5	incorporating	incorporate	VERB
cana-4558	13	6	a	a	DET
cana-4558	13	7	number	number	NOUN
cana-4558	13	8	of	of	ADP
cana-4558	13	9	environmental	environmental	ADJ
cana-4558	13	10	factors	factor	NOUN
cana-4558	13	11	including	include	VERB
cana-4558	13	12	variable	variable	ADJ
cana-4558	13	13	illumination	illumination	NOUN
cana-4558	13	14	,	,	PUNCT
cana-4558	13	15	occlusions	occlusion	NOUN
cana-4558	13	16	,	,	PUNCT
cana-4558	13	17	and	and	CCONJ
cana-4558	13	18	orientations	orientation	NOUN
cana-4558	13	19	.	.	PUNCT
cana-4558	14	1	pre	pre	ADJ
cana-4558	14	2	-	-	NOUN
cana-4558	14	3	training	training	ADJ
cana-4558	14	4	,	,	PUNCT
cana-4558	14	5	contrast	contrast	NOUN
cana-4558	14	6	enhancing	enhance	VERB
cana-4558	14	7	and	and	CCONJ
cana-4558	14	8	sharpening	sharpening	NOUN
cana-4558	14	9	of	of	ADP
cana-4558	14	10	edges	edge	NOUN
cana-4558	14	11	were	be	AUX
cana-4558	14	12	performed	perform	VERB
cana-4558	14	13	on	on	ADP
cana-4558	14	14	the	the	DET
cana-4558	14	15	images	image	NOUN
cana-4558	14	16	to	to	PART
cana-4558	14	17	enhance	enhance	VERB
cana-4558	14	18	the	the	DET
cana-4558	14	19	accuracy	accuracy	NOUN
cana-4558	14	20	of	of	ADP
cana-4558	14	21	detection	detection	NOUN
cana-4558	14	22	.	.	PUNCT
cana-4558	15	1	the	the	DET
cana-4558	15	2	same	same	ADJ
cana-4558	15	3	26	26	NUM
cana-4558	15	4	images	image	NOUN
cana-4558	15	5	from	from	ADP
cana-4558	15	6	the	the	DET
cana-4558	15	7	given	give	VERB
cana-4558	15	8	set	set	NOUN
cana-4558	15	9	are	be	AUX
cana-4558	15	10	taken	take	VERB
cana-4558	15	11	for	for	ADP
cana-4558	15	12	training	training	NOUN
cana-4558	15	13	and	and	CCONJ
cana-4558	15	14	testing	testing	NOUN
cana-4558	15	15	of	of	ADP
cana-4558	15	16	the	the	DET
cana-4558	15	17	cnn	cnn	PROPN
cana-4558	15	18	-	-	PUNCT
cana-4558	15	19	based	base	VERB
cana-4558	15	20	group	group	NOUN
cana-4558	15	21	2	2	NUM
cana-4558	15	22	's	's	PART
cana-4558	15	23	leaf	leaf	NOUN
cana-4558	15	24	disease	disease	NOUN
cana-4558	15	25	classifier	classifier	NOUN
cana-4558	15	26	.	.	PUNCT
cana-4558	16	1	it	it	PRON
cana-4558	16	2	had	have	AUX
cana-4558	16	3	extracted	extract	VERB
cana-4558	16	4	features	feature	NOUN
cana-4558	16	5	automatically	automatically	ADV
cana-4558	16	6	with	with	ADP
cana-4558	16	7	the	the	DET
cana-4558	16	8	help	help	NOUN
cana-4558	16	9	of	of	ADP
cana-4558	16	10	convolutional	convolutional	ADJ
cana-4558	16	11	layers	layer	NOUN
cana-4558	16	12	.	.	PUNCT
cana-4558	17	1	accuracy	accuracy	NOUN
cana-4558	17	2	,	,	PUNCT
cana-4558	17	3	precision	precision	NOUN
cana-4558	17	4	,	,	PUNCT
cana-4558	17	5	recall	recall	NOUN
cana-4558	17	6	,	,	PUNCT
cana-4558	17	7	f1	f1	ADJ
cana-4558	17	8	score	score	NOUN
cana-4558	17	9	were	be	AUX
cana-4558	17	10	compared	compare	VERB
cana-4558	17	11	to	to	PART
cana-4558	17	12	evaluate	evaluate	VERB
cana-4558	17	13	the	the	DET
cana-4558	17	14	classification	classification	NOUN
cana-4558	17	15	of	of	ADP
cana-4558	17	16	yolov4	yolov4	PROPN
cana-4558	17	17	,	,	PUNCT
cana-4558	17	18	cnn	cnn	PROPN
cana-4558	17	19	.	.	PUNCT
cana-4558	18	1	a	a	DET
cana-4558	18	2	threshold	threshold	NOUN
cana-4558	18	3	was	be	AUX
cana-4558	18	4	set	set	VERB
cana-4558	18	5	up	up	ADP
cana-4558	18	6	to	to	PART
cana-4558	18	7	observe	observe	VERB
cana-4558	18	8	the	the	DET
cana-4558	18	9	result	result	NOUN
cana-4558	18	10	,	,	PUNCT
cana-4558	18	11	which	which	PRON
cana-4558	18	12	was	be	AUX
cana-4558	18	13	0.05	0.05	NUM
cana-4558	18	14	%	%	NOUN
cana-4558	18	15	and	and	CCONJ
cana-4558	18	16	also	also	ADV
cana-4558	18	17	95	95	NUM
cana-4558	18	18	%	%	NOUN
cana-4558	18	19	confidence	confidence	NOUN
cana-4558	18	20	interval	interval	NOUN
cana-4558	18	21	with	with	ADP
cana-4558	18	22	g	g	NOUN
cana-4558	18	23	power	power	NOUN
cana-4558	18	24	of	of	ADP
cana-4558	18	25	80	80	NUM
cana-4558	18	26	%	%	NOUN
cana-4558	18	27	.	.	PUNCT
cana-4558	19	1	result	result	VERB
cana-4558	19	2	:	:	PUNCT
cana-4558	19	3	the	the	DET
cana-4558	19	4	yolov4	yolov4	PROPN
cana-4558	19	5	model	model	NOUN
cana-4558	19	6	outperforms	outperform	NOUN
cana-4558	19	7	from	from	ADP
cana-4558	19	8	the	the	DET
cana-4558	19	9	cnn	cnn	PROPN
cana-4558	19	10	model	model	NOUN
cana-4558	19	11	,	,	PUNCT
cana-4558	19	12	where	where	SCONJ
cana-4558	19	13	the	the	DET
cana-4558	19	14	cnn	cnn	PROPN
cana-4558	19	15	achieved	achieve	VERB
cana-4558	19	16	an	an	DET
cana-4558	19	17	accuracy	accuracy	NOUN
cana-4558	19	18	of	of	ADP
cana-4558	19	19	87.00	87.00	NUM
cana-4558	19	20	%	%	NOUN
cana-4558	19	21	,	,	PUNCT
cana-4558	19	22	with	with	ADP
cana-4558	19	23	a	a	DET
cana-4558	19	24	processing	processing	NOUN
cana-4558	19	25	time	time	NOUN
cana-4558	19	26	of	of	ADP
cana-4558	19	27	2.30	2.30	NUM
cana-4558	19	28	seconds	second	NOUN
cana-4558	19	29	(	(	PUNCT
cana-4558	19	30	p	p	X
cana-4558	19	31	<	<	X
cana-4558	19	32	0.05	0.05	NUM
cana-4558	19	33	)	)	PUNCT
cana-4558	19	34	,	,	PUNCT
cana-4558	19	35	while	while	SCONJ
cana-4558	19	36	the	the	DET
cana-4558	19	37	yolov4	yolov4	PROPN
cana-4558	19	38	model	model	NOUN
cana-4558	19	39	achieved	achieve	VERB
cana-4558	19	40	an	an	DET
cana-4558	19	41	accuracy	accuracy	NOUN
cana-4558	19	42	of	of	ADP
cana-4558	19	43	96.00	96.00	NUM
cana-4558	19	44	%	%	NOUN
cana-4558	19	45	with	with	ADP
cana-4558	19	46	a	a	DET
cana-4558	19	47	little	little	ADJ
cana-4558	19	48	inference	inference	NOUN
cana-4558	19	49	time	time	NOUN
cana-4558	19	50	,	,	PUNCT
cana-4558	19	51	that	that	PRON
cana-4558	19	52	is	be	AUX
cana-4558	19	53	0.65	0.65	NUM
cana-4558	19	54	seconds	second	NOUN
cana-4558	19	55	.	.	PUNCT
cana-4558	20	1	the	the	DET
cana-4558	20	2	statistical	statistical	ADJ
cana-4558	20	3	analysis	analysis	NOUN
cana-4558	20	4	also	also	ADV
cana-4558	20	5	proved	prove	VERB
cana-4558	20	6	the	the	DET
cana-4558	20	7	performance	performance	NOUN
cana-4558	20	8	and	and	CCONJ
cana-4558	20	9	effectiveness	effectiveness	NOUN
cana-4558	20	10	of	of	ADP
cana-4558	20	11	yolov4	yolov4	NOUN
cana-4558	20	12	in	in	ADP
cana-4558	20	13	real	real	ADJ
cana-4558	20	14	-	-	PUNCT
cana-4558	20	15	time	time	NOUN
cana-4558	20	16	leaf	leaf	NOUN
cana-4558	20	17	disease	disease	NOUN
cana-4558	20	18	detection	detection	NOUN
cana-4558	20	19	.	.	PUNCT
cana-4558	21	1	conclusion	conclusion	NOUN
cana-4558	21	2	:	:	PUNCT
cana-4558	21	3	the	the	DET
cana-4558	21	4	outcome	outcome	NOUN
cana-4558	21	5	of	of	ADP
cana-4558	21	6	the	the	DET
cana-4558	21	7	paper	paper	NOUN
cana-4558	21	8	is	be	AUX
cana-4558	21	9	that	that	SCONJ
cana-4558	21	10	the	the	DET
cana-4558	21	11	advanced	advanced	ADJ
cana-4558	21	12	delicacy	delicacy	NOUN
cana-4558	21	13	and	and	CCONJ
cana-4558	21	14	fast	fast	ADJ
cana-4558	21	15	conclusion	conclusion	NOUN
cana-4558	21	16	time	time	NOUN
cana-4558	21	17	of	of	ADP
cana-4558	21	18	yolov4	yolov4	NOUN
cana-4558	21	19	make	make	VERB
cana-4558	21	20	it	it	PRON
cana-4558	21	21	a	a	DET
cana-4558	21	22	better	well	ADJ
cana-4558	21	23	option	option	NOUN
cana-4558	21	24	than	than	ADP
cana-4558	21	25	cnn	cnn	PROPN
cana-4558	21	26	for	for	ADP
cana-4558	21	27	real	real	ADJ
cana-4558	21	28	-	-	PUNCT
cana-4558	21	29	time	time	NOUN
cana-4558	21	30	splint	splint	NOUN
cana-4558	21	31	complaint	complaint	NOUN
cana-4558	21	32	discovery	discovery	NOUN
cana-4558	21	33	.	.	PUNCT
cana-4558	22	1	using	use	VERB
cana-4558	22	2	yolov4	yolov4	NOUN
cana-4558	22	3	in	in	ADP
cana-4558	22	4	perfect	perfect	ADJ
cana-4558	22	5	husbandry	husbandry	NOUN
cana-4558	22	6	will	will	AUX
cana-4558	22	7	reduce	reduce	VERB
cana-4558	22	8	crop	crop	NOUN
cana-4558	22	9	losses	loss	NOUN
cana-4558	22	10	,	,	PUNCT
cana-4558	22	11	complaints	complaint	NOUN
cana-4558	22	12	will	will	AUX
cana-4558	22	13	be	be	AUX
cana-4558	22	14	identified	identify	VERB
cana-4558	22	15	at	at	ADP
cana-4558	22	16	an	an	DET
cana-4558	22	17	early	early	ADJ
cana-4558	22	18	stage	stage	NOUN
cana-4558	22	19	,	,	PUNCT
cana-4558	22	20	and	and	CCONJ
cana-4558	22	21	total	total	ADJ
cana-4558	22	22	agricultural	agricultural	ADJ
cana-4558	22	23	productivity	productivity	NOUN
cana-4558	22	24	will	will	AUX
cana-4558	22	25	increase	increase	VERB
cana-4558	22	26	.	.	PUNCT
cana-4558	23	1	keywords	keyword	NOUN
cana-4558	23	2	:	:	PUNCT
cana-4558	23	3	leaf	leaf	NOUN
cana-4558	23	4	disease	disease	NOUN
cana-4558	23	5	detection	detection	NOUN
cana-4558	23	6	,	,	PUNCT
cana-4558	23	7	yolov4	yolov4	PROPN
cana-4558	23	8	algorithm	algorithm	PROPN
cana-4558	23	9	,	,	PUNCT
cana-4558	23	10	cnn	cnn	PROPN
cana-4558	23	11	comparison	comparison	NOUN
cana-4558	23	12	,	,	PUNCT
cana-4558	23	13	yolov4	yolov4	PROPN
cana-4558	23	14	,	,	PUNCT
cana-4558	23	15	cnn	cnn	PROPN
cana-4558	23	16	,	,	PUNCT
cana-4558	23	17	accuracy	accuracy	NOUN
cana-4558	23	18	,	,	PUNCT
cana-4558	23	19	precision	precision	NOUN
cana-4558	23	20	agriculture	agriculture	NOUN
cana-4558	23	21	,	,	PUNCT
cana-4558	23	22	real	real	ADJ
cana-4558	23	23	-	-	PUNCT
cana-4558	23	24	time	time	NOUN
cana-4558	23	25	detection	detection	NOUN
cana-4558	23	26	,	,	PUNCT
cana-4558	23	27	deep	deep	ADJ
cana-4558	23	28	learning	learning	NOUN
cana-4558	23	29	,	,	PUNCT
cana-4558	23	30	plant	plant	NOUN
cana-4558	23	31	disease	disease	NOUN
cana-4558	23	32	detection	detection	NOUN
cana-4558	23	33	,	,	PUNCT
cana-4558	23	34	classification	classification	NOUN
cana-4558	23	35	.	.	PUNCT
cana-4558	24	1	communications	communication	NOUN
cana-4558	24	2	on	on	ADP
cana-4558	24	3	applied	apply	VERB
cana-4558	24	4	nonlinear	nonlinear	ADJ
cana-4558	24	5	analysis	analysis	NOUN
cana-4558	24	6	issn	issn	NOUN
cana-4558	24	7	:	:	PUNCT
cana-4558	24	8	1074	1074	NUM
cana-4558	24	9	-	-	PUNCT
cana-4558	24	10	133x	133x	NUM
cana-4558	24	11	vol	vol	NOUN
cana-4558	24	12	32	32	NUM
cana-4558	24	13	no	no	NOUN
cana-4558	24	14	.	.	PUNCT
cana-4558	25	1	9s	9s	NUM
cana-4558	25	2	(	(	PUNCT
cana-4558	25	3	2025	2025	NUM
cana-4558	25	4	)	)	PUNCT
cana-4558	25	5	2532	2532	NUM
cana-4558	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	25	7	i.	i.	NOUN
cana-4558	25	8	introduction	introduction	NOUN
cana-4558	25	9	“	"	PUNCT
cana-4558	25	10	sugu	sugu	PROPN
cana-4558	25	11	et	et	PROPN
cana-4558	25	12	al	al	PROPN
cana-4558	25	13	”	"	PUNCT
cana-4558	25	14	the	the	DET
cana-4558	25	15	identification	identification	NOUN
cana-4558	25	16	of	of	ADP
cana-4558	25	17	accurate	accurate	ADJ
cana-4558	25	18	leaf	leaf	NOUN
cana-4558	25	19	diseases	disease	NOUN
cana-4558	25	20	using	use	VERB
cana-4558	25	21	the	the	DET
cana-4558	25	22	yolov4	yolov4	PROPN
cana-4558	25	23	algorithm	algorithm	PROPN
cana-4558	25	24	overtakes	overtake	VERB
cana-4558	25	25	the	the	DET
cana-4558	25	26	problems	problem	NOUN
cana-4558	25	27	faced	face	VERB
cana-4558	25	28	by	by	ADP
cana-4558	25	29	the	the	DET
cana-4558	25	30	conventional	conventional	ADJ
cana-4558	25	31	cnn	cnn	PROPN
cana-4558	25	32	-	-	PUNCT
cana-4558	25	33	based	base	VERB
cana-4558	25	34	models	model	NOUN
cana-4558	25	35	to	to	PART
cana-4558	25	36	enhance	enhance	VERB
cana-4558	25	37	detection	detection	NOUN
cana-4558	25	38	accuracy	accuracy	NOUN
cana-4558	25	39	and	and	CCONJ
cana-4558	25	40	lessen	lessen	VERB
cana-4558	25	41	the	the	DET
cana-4558	25	42	computational	computational	ADJ
cana-4558	25	43	time	time	NOUN
cana-4558	25	44	[	[	X
cana-4558	25	45	1	1	NUM
cana-4558	25	46	]	]	PUNCT
cana-4558	25	47	.	.	PUNCT
cana-4558	26	1	unlike	unlike	ADP
cana-4558	26	2	conventional	conventional	ADJ
cana-4558	26	3	classification	classification	NOUN
cana-4558	26	4	methods	method	NOUN
cana-4558	26	5	,	,	PUNCT
cana-4558	26	6	yolov4	yolov4	PROPN
cana-4558	26	7	makes	make	VERB
cana-4558	26	8	use	use	NOUN
cana-4558	26	9	of	of	ADP
cana-4558	26	10	deep	deep	ADJ
cana-4558	26	11	learning	learning	NOUN
cana-4558	26	12	for	for	ADP
cana-4558	26	13	real	real	ADJ
cana-4558	26	14	-	-	PUNCT
cana-4558	26	15	time	time	NOUN
cana-4558	26	16	detection	detection	NOUN
cana-4558	26	17	and	and	CCONJ
cana-4558	26	18	is	be	AUX
cana-4558	26	19	therefore	therefore	ADV
cana-4558	26	20	efficient	efficient	ADJ
cana-4558	26	21	in	in	ADP
cana-4558	26	22	handling	handle	VERB
cana-4558	26	23	more	more	ADV
cana-4558	26	24	complex	complex	ADJ
cana-4558	26	25	agricultural	agricultural	ADJ
cana-4558	26	26	conditions	condition	NOUN
cana-4558	26	27	such	such	ADJ
cana-4558	26	28	as	as	ADP
cana-4558	26	29	different	different	ADJ
cana-4558	26	30	lighting	lighting	NOUN
cana-4558	26	31	,	,	PUNCT
cana-4558	26	32	occlusions	occlusion	NOUN
cana-4558	26	33	,	,	PUNCT
cana-4558	26	34	and	and	CCONJ
cana-4558	26	35	diverse	diverse	ADJ
cana-4558	26	36	disease	disease	NOUN
cana-4558	26	37	symptoms	symptom	NOUN
cana-4558	26	38	[	[	X
cana-4558	26	39	2	2	NUM
cana-4558	26	40	]	]	PUNCT
cana-4558	26	41	.	.	PUNCT
cana-4558	27	1	current	current	ADJ
cana-4558	27	2	research	research	NOUN
cana-4558	27	3	in	in	ADP
cana-4558	27	4	detection	detection	NOUN
cana-4558	27	5	of	of	ADP
cana-4558	27	6	plant	plant	NOUN
cana-4558	27	7	diseases	disease	NOUN
cana-4558	27	8	has	have	AUX
cana-4558	27	9	extensively	extensively	ADV
cana-4558	27	10	focused	focus	VERB
cana-4558	27	11	on	on	ADP
cana-4558	27	12	machine	machine	NOUN
cana-4558	27	13	learning	learning	NOUN
cana-4558	27	14	and	and	CCONJ
cana-4558	27	15	cnn	cnn	PROPN
cana-4558	27	16	-	-	PUNCT
cana-4558	27	17	based	base	VERB
cana-4558	27	18	models	model	NOUN
cana-4558	27	19	,	,	PUNCT
cana-4558	27	20	but	but	CCONJ
cana-4558	27	21	such	such	ADJ
cana-4558	27	22	methods	method	NOUN
cana-4558	27	23	generally	generally	ADV
cana-4558	27	24	experience	experience	VERB
cana-4558	27	25	high	high	ADJ
cana-4558	27	26	false	false	ADJ
cana-4558	27	27	-	-	PUNCT
cana-4558	27	28	positive	positive	ADJ
cana-4558	27	29	rates	rate	NOUN
cana-4558	27	30	and	and	CCONJ
cana-4558	27	31	low	low	ADJ
cana-4558	27	32	speed	speed	NOUN
cana-4558	27	33	processing	processing	NOUN
cana-4558	27	34	,	,	PUNCT
cana-4558	27	35	making	make	VERB
cana-4558	27	36	them	they	PRON
cana-4558	27	37	inappropriate	inappropriate	ADJ
cana-4558	27	38	for	for	ADP
cana-4558	27	39	large	large	ADJ
cana-4558	27	40	-	-	PUNCT
cana-4558	27	41	scale	scale	NOUN
cana-4558	27	42	agricultural	agricultural	ADJ
cana-4558	27	43	applications	application	NOUN
cana-4558	28	1	[	[	X
cana-4558	28	2	3	3	NUM
cana-4558	28	3	]	]	PUNCT
cana-4558	28	4	.	.	PUNCT
cana-4558	29	1	presently	presently	ADV
cana-4558	29	2	,	,	PUNCT
cana-4558	29	3	innovations	innovation	NOUN
cana-4558	29	4	in	in	ADP
cana-4558	29	5	object	object	NOUN
cana-4558	29	6	detection	detection	NOUN
cana-4558	29	7	algorithms	algorithm	NOUN
cana-4558	29	8	show	show	VERB
cana-4558	29	9	higher	high	ADJ
cana-4558	29	10	and	and	CCONJ
cana-4558	29	11	more	more	ADV
cana-4558	29	12	accurate	accurate	ADJ
cana-4558	29	13	detection	detection	NOUN
cana-4558	29	14	rates	rate	NOUN
cana-4558	29	15	,	,	PUNCT
cana-4558	29	16	especially	especially	ADV
cana-4558	29	17	in	in	ADP
cana-4558	29	18	early	early	ADJ
cana-4558	29	19	disease	disease	NOUN
cana-4558	29	20	diagnosis	diagnosis	NOUN
cana-4558	29	21	and	and	CCONJ
cana-4558	29	22	classification	classification	NOUN
cana-4558	29	23	,	,	PUNCT
cana-4558	29	24	though	though	SCONJ
cana-4558	29	25	still	still	ADV
cana-4558	29	26	require	require	VERB
cana-4558	29	27	further	further	ADJ
cana-4558	29	28	improvements	improvement	NOUN
cana-4558	29	29	for	for	ADP
cana-4558	29	30	agricultural	agricultural	ADJ
cana-4558	29	31	application	application	NOUN
cana-4558	29	32	in	in	ADP
cana-4558	29	33	the	the	DET
cana-4558	29	34	real	real	ADJ
cana-4558	29	35	world	world	NOUN
cana-4558	30	1	[	[	X
cana-4558	30	2	4	4	NUM
cana-4558	30	3	]	]	PUNCT
cana-4558	30	4	.	.	PUNCT
cana-4558	31	1	the	the	DET
cana-4558	31	2	applications	application	NOUN
cana-4558	31	3	of	of	ADP
cana-4558	31	4	yolov4	yolov4	NOUN
cana-4558	31	5	-	-	PUNCT
cana-4558	31	6	based	base	VERB
cana-4558	31	7	disease	disease	NOUN
cana-4558	31	8	detection	detection	NOUN
cana-4558	31	9	are	be	AUX
cana-4558	31	10	precision	precision	NOUN
cana-4558	31	11	farming	farming	NOUN
cana-4558	31	12	,	,	PUNCT
cana-4558	31	13	automated	automate	VERB
cana-4558	31	14	crop	crop	NOUN
cana-4558	31	15	monitoring	monitoring	NOUN
cana-4558	31	16	,	,	PUNCT
cana-4558	31	17	and	and	CCONJ
cana-4558	31	18	iot	iot	ADV
cana-4558	31	19	-	-	PUNCT
cana-4558	31	20	driven	drive	VERB
cana-4558	31	21	smart	smart	ADJ
cana-4558	31	22	agriculture	agriculture	NOUN
cana-4558	31	23	,	,	PUNCT
cana-4558	31	24	enabling	enable	VERB
cana-4558	31	25	real	real	ADJ
cana-4558	31	26	-	-	PUNCT
cana-4558	31	27	time	time	NOUN
cana-4558	31	28	disease	disease	NOUN
cana-4558	31	29	identification	identification	NOUN
cana-4558	31	30	,	,	PUNCT
cana-4558	31	31	early	early	ADJ
cana-4558	31	32	intervention	intervention	NOUN
cana-4558	31	33	,	,	PUNCT
cana-4558	31	34	and	and	CCONJ
cana-4558	31	35	effective	effective	ADJ
cana-4558	31	36	disease	disease	NOUN
cana-4558	31	37	management	management	NOUN
cana-4558	31	38	,	,	PUNCT
cana-4558	31	39	which	which	PRON
cana-4558	31	40	in	in	ADP
cana-4558	31	41	turn	turn	NOUN
cana-4558	31	42	improve	improve	VERB
cana-4558	31	43	crop	crop	NOUN
cana-4558	31	44	yield	yield	NOUN
cana-4558	31	45	and	and	CCONJ
cana-4558	31	46	reduce	reduce	VERB
cana-4558	31	47	economic	economic	ADJ
cana-4558	31	48	losses	loss	NOUN
cana-4558	31	49	[	[	X
cana-4558	31	50	5	5	NUM
cana-4558	31	51	]	]	PUNCT
cana-4558	31	52	.	.	PUNCT
cana-4558	32	1	ii	ii	PROPN
cana-4558	32	2	.	.	PROPN
cana-4558	32	3	related	relate	VERB
cana-4558	32	4	works	work	VERB
cana-4558	32	5	the	the	DET
cana-4558	32	6	yolov4	yolov4	PROPN
cana-4558	32	7	algorithm	algorithm	PROPN
cana-4558	32	8	has	have	AUX
cana-4558	32	9	lately	lately	ADV
cana-4558	32	10	become	become	VERB
cana-4558	32	11	the	the	DET
cana-4558	32	12	talk	talk	NOUN
cana-4558	32	13	of	of	ADP
cana-4558	32	14	the	the	DET
cana-4558	32	15	town	town	NOUN
cana-4558	32	16	in	in	ADP
cana-4558	32	17	research	research	NOUN
cana-4558	32	18	as	as	ADP
cana-4558	32	19	a	a	DET
cana-4558	32	20	result	result	NOUN
cana-4558	32	21	of	of	ADP
cana-4558	32	22	more	more	ADJ
cana-4558	32	23	than	than	ADP
cana-4558	32	24	400	400	NUM
cana-4558	32	25	academic	academic	ADJ
cana-4558	32	26	articles	article	NOUN
cana-4558	32	27	published	publish	VERB
cana-4558	32	28	,	,	PUNCT
cana-4558	32	29	such	such	ADJ
cana-4558	32	30	as	as	ADP
cana-4558	32	31	157	157	NUM
cana-4558	32	32	articles	article	NOUN
cana-4558	32	33	in	in	ADP
cana-4558	32	34	ieee	ieee	PROPN
cana-4558	32	35	xplore	xplore	PROPN
cana-4558	32	36	,	,	PUNCT
cana-4558	32	37	134	134	NUM
cana-4558	32	38	in	in	ADP
cana-4558	32	39	google	google	PROPN
cana-4558	32	40	scholar	scholar	NOUN
cana-4558	32	41	,	,	PUNCT
cana-4558	32	42	and	and	CCONJ
cana-4558	32	43	129	129	NUM
cana-4558	32	44	in	in	ADP
cana-4558	32	45	sciencedirect	sciencedirect	PROPN
cana-4558	33	1	[	[	X
cana-4558	33	2	6	6	NUM
cana-4558	33	3	]	]	PUNCT
cana-4558	33	4	.	.	PUNCT
cana-4558	34	1	cnn	cnn	PROPN
cana-4558	34	2	-	-	PUNCT
cana-4558	34	3	based	base	VERB
cana-4558	34	4	models	model	NOUN
cana-4558	34	5	have	have	AUX
cana-4558	34	6	long	long	ADV
cana-4558	34	7	been	be	AUX
cana-4558	34	8	applied	apply	VERB
cana-4558	34	9	in	in	ADP
cana-4558	34	10	the	the	DET
cana-4558	34	11	field	field	NOUN
cana-4558	34	12	of	of	ADP
cana-4558	34	13	plant	plant	NOUN
cana-4558	34	14	disease	disease	NOUN
cana-4558	34	15	detection	detection	NOUN
cana-4558	34	16	;	;	PUNCT
cana-4558	34	17	however	however	ADV
cana-4558	34	18	,	,	PUNCT
cana-4558	34	19	their	their	PRON
cana-4558	34	20	low	low	ADJ
cana-4558	34	21	accuracy	accuracy	NOUN
cana-4558	34	22	,	,	PUNCT
cana-4558	34	23	slow	slow	ADJ
cana-4558	34	24	inference	inference	NOUN
cana-4558	34	25	speed	speed	NOUN
cana-4558	34	26	,	,	PUNCT
cana-4558	34	27	and	and	CCONJ
cana-4558	34	28	high	high	ADJ
cana-4558	34	29	false	false	ADJ
cana-4558	34	30	-	-	PUNCT
cana-4558	34	31	positive	positive	ADJ
cana-4558	34	32	rates	rate	NOUN
cana-4558	34	33	have	have	AUX
cana-4558	34	34	remained	remain	VERB
cana-4558	34	35	issues	issue	NOUN
cana-4558	34	36	[	[	X
cana-4558	34	37	7],[8	7],[8	NUM
cana-4558	34	38	]	]	PUNCT
cana-4558	34	39	.	.	PUNCT
cana-4558	35	1	yolov4	yolov4	PROPN
cana-4558	35	2	still	still	ADV
cana-4558	35	3	outperforms	outperform	VERB
cana-4558	35	4	the	the	DET
cana-4558	35	5	traditional	traditional	ADJ
cana-4558	35	6	models	model	NOUN
cana-4558	35	7	since	since	SCONJ
cana-4558	35	8	it	it	PRON
cana-4558	35	9	has	have	AUX
cana-4558	35	10	also	also	ADV
cana-4558	35	11	outperformed	outperform	VERB
cana-4558	35	12	with	with	ADP
cana-4558	35	13	more	more	ADJ
cana-4558	35	14	accuracy	accuracy	NOUN
cana-4558	35	15	in	in	ADP
cana-4558	35	16	real	real	ADJ
cana-4558	35	17	-	-	PUNCT
cana-4558	35	18	time	time	NOUN
cana-4558	35	19	detection	detection	NOUN
cana-4558	35	20	but	but	CCONJ
cana-4558	35	21	with	with	ADP
cana-4558	35	22	the	the	DET
cana-4558	35	23	assistance	assistance	NOUN
cana-4558	35	24	of	of	ADP
cana-4558	35	25	complex	complex	ADJ
cana-4558	35	26	backgrounds	background	NOUN
cana-4558	35	27	,	,	PUNCT
cana-4558	35	28	changing	change	VERB
cana-4558	35	29	light	light	ADJ
cana-4558	35	30	conditions	condition	NOUN
cana-4558	35	31	,	,	PUNCT
cana-4558	35	32	and	and	CCONJ
cana-4558	35	33	occlusions	occlusion	NOUN
cana-4558	35	34	,	,	PUNCT
cana-4558	35	35	as	as	SCONJ
cana-4558	35	36	mentioned	mention	VERB
cana-4558	35	37	by	by	ADP
cana-4558	35	38	[	[	X
cana-4558	35	39	9	9	NUM
cana-4558	35	40	]	]	PUNCT
cana-4558	35	41	.	.	PUNCT
cana-4558	36	1	recent	recent	ADJ
cana-4558	36	2	studies	study	NOUN
cana-4558	36	3	have	have	AUX
cana-4558	36	4	demonstrated	demonstrate	VERB
cana-4558	36	5	that	that	SCONJ
cana-4558	36	6	yolov4	yolov4	PROPN
cana-4558	36	7	achieves	achieve	VERB
cana-4558	36	8	87.0	87.0	NUM
cana-4558	36	9	%	%	NOUN
cana-4558	36	10	accuracy	accuracy	NOUN
cana-4558	36	11	,	,	PUNCT
cana-4558	36	12	surpassing	surpass	VERB
cana-4558	36	13	cnn	cnn	PROPN
cana-4558	36	14	-	-	PUNCT
cana-4558	36	15	based	base	VERB
cana-4558	36	16	models	model	NOUN
cana-4558	36	17	(	(	PUNCT
cana-4558	36	18	75.0	75.0	NUM
cana-4558	36	19	%	%	NOUN
cana-4558	36	20	)	)	PUNCT
cana-4558	36	21	and	and	CCONJ
cana-4558	36	22	faster	fast	ADJ
cana-4558	36	23	r	r	X
cana-4558	36	24	-	-	PUNCT
cana-4558	36	25	cnn	cnn	PROPN
cana-4558	36	26	(	(	PUNCT
cana-4558	36	27	82.3	82.3	NUM
cana-4558	36	28	%	%	NOUN
cana-4558	36	29	)	)	PUNCT
cana-4558	36	30	,	,	PUNCT
cana-4558	36	31	while	while	SCONJ
cana-4558	36	32	maintaining	maintain	VERB
cana-4558	36	33	a	a	DET
cana-4558	36	34	30	30	NUM
cana-4558	36	35	%	%	NOUN
cana-4558	36	36	faster	fast	ADJ
cana-4558	36	37	processing	processing	NOUN
cana-4558	36	38	speed	speed	NOUN
cana-4558	36	39	[	[	X
cana-4558	36	40	10	10	NUM
cana-4558	36	41	]	]	PUNCT
cana-4558	36	42	.	.	PUNCT
cana-4558	37	1	comparisons	comparison	NOUN
cana-4558	37	2	with	with	ADP
cana-4558	37	3	segmentation	segmentation	NOUN
cana-4558	37	4	-	-	PUNCT
cana-4558	37	5	based	base	VERB
cana-4558	37	6	models	model	NOUN
cana-4558	37	7	show	show	VERB
cana-4558	37	8	that	that	SCONJ
cana-4558	37	9	deeplabv3	deeplabv3	PROPN
cana-4558	37	10	+	+	CCONJ
cana-4558	37	11	achieves	achieve	VERB
cana-4558	37	12	84.3	84.3	NUM
cana-4558	37	13	%	%	NOUN
cana-4558	37	14	accuracy	accuracy	NOUN
cana-4558	37	15	,	,	PUNCT
cana-4558	37	16	outperforming	outperform	VERB
cana-4558	37	17	u	u	NOUN
cana-4558	37	18	-	-	NOUN
cana-4558	37	19	net	net	ADJ
cana-4558	37	20	(	(	PUNCT
cana-4558	37	21	78.5	78.5	NUM
cana-4558	37	22	%	%	NOUN
cana-4558	37	23	)	)	PUNCT
cana-4558	37	24	and	and	CCONJ
cana-4558	37	25	segnet	segnet	NOUN
cana-4558	37	26	(	(	PUNCT
cana-4558	37	27	76.8	76.8	NUM
cana-4558	37	28	%	%	NOUN
cana-4558	37	29	)	)	PUNCT
cana-4558	37	30	in	in	ADP
cana-4558	37	31	leaf	leaf	NOUN
cana-4558	37	32	disease	disease	NOUN
cana-4558	37	33	classification	classification	NOUN
cana-4558	38	1	[	[	X
cana-4558	38	2	11	11	NUM
cana-4558	38	3	]	]	PUNCT
cana-4558	38	4	.	.	PUNCT
cana-4558	39	1	further	far	ADV
cana-4558	39	2	,	,	PUNCT
cana-4558	39	3	yolov4	yolov4	PROPN
cana-4558	39	4	has	have	VERB
cana-4558	39	5	15	15	NUM
cana-4558	39	6	%	%	NOUN
cana-4558	39	7	lower	low	ADJ
cana-4558	39	8	false	false	ADJ
cana-4558	39	9	-	-	PUNCT
cana-4558	39	10	positive	positive	ADJ
cana-4558	39	11	rates	rate	NOUN
cana-4558	39	12	compared	compare	VERB
cana-4558	39	13	to	to	ADP
cana-4558	39	14	cnn	cnn	PROPN
cana-4558	39	15	-	-	PUNCT
cana-4558	39	16	svm	svm	ADJ
cana-4558	39	17	hybrid	hybrid	NOUN
cana-4558	39	18	models	model	NOUN
cana-4558	39	19	,	,	PUNCT
cana-4558	39	20	thus	thus	ADV
cana-4558	39	21	it	it	PRON
cana-4558	39	22	is	be	AUX
cana-4558	39	23	more	more	ADV
cana-4558	39	24	reliable	reliable	ADJ
cana-4558	39	25	for	for	ADP
cana-4558	39	26	real	real	ADJ
cana-4558	39	27	-	-	PUNCT
cana-4558	39	28	time	time	NOUN
cana-4558	39	29	agricultural	agricultural	ADJ
cana-4558	39	30	applications	application	NOUN
cana-4558	39	31	[	[	X
cana-4558	39	32	12	12	NUM
cana-4558	39	33	]	]	PUNCT
cana-4558	39	34	.	.	PUNCT
cana-4558	40	1	although	although	SCONJ
cana-4558	40	2	the	the	DET
cana-4558	40	3	improvements	improvement	NOUN
cana-4558	40	4	have	have	AUX
cana-4558	40	5	been	be	AUX
cana-4558	40	6	seen	see	VERB
cana-4558	40	7	in	in	ADP
cana-4558	40	8	the	the	DET
cana-4558	40	9	current	current	ADJ
cana-4558	40	10	models	model	NOUN
cana-4558	40	11	,	,	PUNCT
cana-4558	40	12	existing	exist	VERB
cana-4558	40	13	models	model	NOUN
cana-4558	40	14	still	still	ADV
cana-4558	40	15	suffer	suffer	VERB
cana-4558	40	16	from	from	ADP
cana-4558	40	17	the	the	DET
cana-4558	40	18	generalization	generalization	NOUN
cana-4558	40	19	of	of	ADP
cana-4558	40	20	various	various	ADJ
cana-4558	40	21	datasets	dataset	NOUN
cana-4558	40	22	,	,	PUNCT
cana-4558	40	23	and	and	CCONJ
cana-4558	40	24	thus	thus	ADV
cana-4558	40	25	there	there	PRON
cana-4558	40	26	is	be	VERB
cana-4558	40	27	a	a	DET
cana-4558	40	28	research	research	NOUN
cana-4558	40	29	gap	gap	NOUN
cana-4558	40	30	in	in	ADP
cana-4558	40	31	developing	develop	VERB
cana-4558	40	32	a	a	DET
cana-4558	40	33	more	more	ADV
cana-4558	40	34	robust	robust	ADJ
cana-4558	40	35	,	,	PUNCT
cana-4558	40	36	scalable	scalable	ADJ
cana-4558	40	37	,	,	PUNCT
cana-4558	40	38	and	and	CCONJ
cana-4558	40	39	high	high	ADJ
cana-4558	40	40	-	-	PUNCT
cana-4558	40	41	speed	speed	NOUN
cana-4558	40	42	detection	detection	NOUN
cana-4558	40	43	system[13	system[13	NOUN
cana-4558	40	44	]	]	PUNCT
cana-4558	40	45	.	.	PUNCT
cana-4558	41	1	the	the	DET
cana-4558	41	2	base	base	PROPN
cana-4558	41	3	paper	paper	NOUN
cana-4558	41	4	of	of	ADP
cana-4558	41	5	this	this	DET
cana-4558	41	6	study	study	NOUN
cana-4558	41	7	aims	aim	VERB
cana-4558	41	8	to	to	PART
cana-4558	41	9	optimize	optimize	VERB
cana-4558	41	10	yolov4	yolov4	NOUN
cana-4558	41	11	for	for	ADP
cana-4558	41	12	disease	disease	NOUN
cana-4558	41	13	detection	detection	NOUN
cana-4558	41	14	in	in	ADP
cana-4558	41	15	agricultural	agricultural	ADJ
cana-4558	41	16	fields	field	NOUN
cana-4558	41	17	accurately	accurately	ADV
cana-4558	41	18	in	in	ADP
cana-4558	41	19	real	real	ADJ
cana-4558	41	20	-	-	PUNCT
cana-4558	41	21	time	time	NOUN
cana-4558	41	22	[	[	X
cana-4558	41	23	14	14	NUM
cana-4558	41	24	]	]	PUNCT
cana-4558	41	25	.	.	PUNCT
cana-4558	42	1	from	from	ADP
cana-4558	42	2	the	the	DET
cana-4558	42	3	previous	previous	ADJ
cana-4558	42	4	findings	finding	NOUN
cana-4558	42	5	,	,	PUNCT
cana-4558	42	6	it	it	PRON
cana-4558	42	7	is	be	AUX
cana-4558	42	8	observed	observe	VERB
cana-4558	42	9	that	that	SCONJ
cana-4558	42	10	cnn	cnn	PROPN
cana-4558	42	11	-	-	PUNCT
cana-4558	42	12	based	base	VERB
cana-4558	42	13	methods	method	NOUN
cana-4558	42	14	have	have	VERB
cana-4558	42	15	limitations	limitation	NOUN
cana-4558	42	16	in	in	ADP
cana-4558	42	17	real	real	ADJ
cana-4558	42	18	-	-	PUNCT
cana-4558	42	19	time	time	NOUN
cana-4558	42	20	disease	disease	NOUN
cana-4558	42	21	detection	detection	NOUN
cana-4558	42	22	for	for	ADP
cana-4558	42	23	leaves	leave	NOUN
cana-4558	42	24	.	.	PUNCT
cana-4558	43	1	optimizing	optimize	VERB
cana-4558	43	2	the	the	DET
cana-4558	43	3	yolov4	yolov4	PROPN
cana-4558	43	4	model	model	NOUN
cana-4558	43	5	enhances	enhance	VERB
cana-4558	43	6	detection	detection	NOUN
cana-4558	43	7	accuracy	accuracy	NOUN
cana-4558	43	8	and	and	CCONJ
cana-4558	43	9	processing	processing	NOUN
cana-4558	43	10	speed	speed	NOUN
cana-4558	43	11	,	,	PUNCT
cana-4558	43	12	surpassing	surpass	VERB
cana-4558	43	13	traditional	traditional	ADJ
cana-4558	43	14	cnn	cnn	PROPN
cana-4558	43	15	approaches	approach	NOUN
cana-4558	43	16	.	.	PUNCT
cana-4558	44	1	this	this	DET
cana-4558	44	2	approach	approach	NOUN
cana-4558	44	3	aims	aim	VERB
cana-4558	44	4	to	to	PART
cana-4558	44	5	evaluate	evaluate	VERB
cana-4558	44	6	yolov4	yolov4	PROPN
cana-4558	44	7	's	's	PART
cana-4558	44	8	performance	performance	NOUN
cana-4558	44	9	in	in	ADP
cana-4558	44	10	detecting	detect	VERB
cana-4558	44	11	multiple	multiple	ADJ
cana-4558	44	12	disease	disease	NOUN
cana-4558	44	13	classes	class	NOUN
cana-4558	44	14	with	with	ADP
cana-4558	44	15	improved	improved	ADJ
cana-4558	44	16	efficiency	efficiency	NOUN
cana-4558	44	17	compared	compare	VERB
cana-4558	44	18	to	to	ADP
cana-4558	44	19	cnns	cnns	PROPN
cana-4558	44	20	,	,	PUNCT
cana-4558	44	21	faster	fast	ADV
cana-4558	44	22	r	r	NOUN
cana-4558	44	23	-	-	PUNCT
cana-4558	44	24	cnn	cnn	PROPN
cana-4558	44	25	,	,	PUNCT
cana-4558	44	26	and	and	CCONJ
cana-4558	44	27	other	other	ADJ
cana-4558	44	28	yolo	yolo	ADJ
cana-4558	44	29	versions	version	NOUN
cana-4558	44	30	(	(	PUNCT
cana-4558	44	31	v3	v3	PROPN
cana-4558	44	32	,	,	PUNCT
cana-4558	44	33	v4	v4	PROPN
cana-4558	44	34	,	,	PUNCT
cana-4558	44	35	v5	v5	NOUN
cana-4558	44	36	,	,	PUNCT
cana-4558	44	37	v7	v7	NUM
cana-4558	44	38	)	)	PUNCT
cana-4558	44	39	.	.	PUNCT
cana-4558	45	1	the	the	DET
cana-4558	45	2	optimization	optimization	NOUN
cana-4558	45	3	focuses	focus	VERB
cana-4558	45	4	on	on	ADP
cana-4558	45	5	key	key	ADJ
cana-4558	45	6	parameters	parameter	NOUN
cana-4558	45	7	such	such	ADJ
cana-4558	45	8	as	as	ADP
cana-4558	45	9	image	image	NOUN
cana-4558	45	10	resolution	resolution	NOUN
cana-4558	45	11	,	,	PUNCT
cana-4558	45	12	and	and	CCONJ
cana-4558	45	13	data	datum	NOUN
cana-4558	45	14	diversity	diversity	NOUN
cana-4558	45	15	to	to	PART
cana-4558	45	16	ensure	ensure	VERB
cana-4558	45	17	adaptability	adaptability	NOUN
cana-4558	45	18	for	for	ADP
cana-4558	45	19	real	real	ADJ
cana-4558	45	20	-	-	PUNCT
cana-4558	45	21	world	world	NOUN
cana-4558	45	22	deployment	deployment	NOUN
cana-4558	45	23	.	.	PUNCT
cana-4558	46	1	communications	communication	NOUN
cana-4558	46	2	on	on	ADP
cana-4558	46	3	applied	apply	VERB
cana-4558	46	4	nonlinear	nonlinear	ADJ
cana-4558	46	5	analysis	analysis	NOUN
cana-4558	46	6	issn	issn	NOUN
cana-4558	46	7	:	:	PUNCT
cana-4558	46	8	1074	1074	NUM
cana-4558	46	9	-	-	PUNCT
cana-4558	46	10	133x	133x	NUM
cana-4558	46	11	vol	vol	NOUN
cana-4558	46	12	32	32	NUM
cana-4558	46	13	no	no	NOUN
cana-4558	46	14	.	.	PUNCT
cana-4558	47	1	9s	9s	NUM
cana-4558	47	2	(	(	PUNCT
cana-4558	47	3	2025	2025	NUM
cana-4558	47	4	)	)	PUNCT
cana-4558	47	5	2533	2533	NUM
cana-4558	48	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	48	2	iii	iii	X
cana-4558	48	3	.	.	PUNCT
cana-4558	48	4	materials	material	NOUN
cana-4558	48	5	and	and	CCONJ
cana-4558	48	6	methods	method	NOUN
cana-4558	48	7	the	the	DET
cana-4558	48	8	dataset	dataset	NOUN
cana-4558	48	9	of	of	ADP
cana-4558	48	10	this	this	DET
cana-4558	48	11	research	research	NOUN
cana-4558	48	12	is	be	AUX
cana-4558	48	13	accessed	access	VERB
cana-4558	48	14	from	from	ADP
cana-4558	48	15	kaggle.com	kaggle.com	X
cana-4558	48	16	that	that	PRON
cana-4558	48	17	contains	contain	VERB
cana-4558	48	18	high	high	ADJ
cana-4558	48	19	-	-	PUNCT
cana-4558	48	20	resolution	resolution	NOUN
cana-4558	48	21	images	image	NOUN
cana-4558	48	22	of	of	ADP
cana-4558	48	23	diseased	diseased	ADJ
cana-4558	48	24	and	and	CCONJ
cana-4558	48	25	healthy	healthy	ADJ
cana-4558	48	26	leaves	leave	NOUN
cana-4558	48	27	.	.	PUNCT
cana-4558	49	1	an	an	DET
cana-4558	49	2	experiment	experiment	NOUN
cana-4558	49	3	was	be	AUX
cana-4558	49	4	performed	perform	VERB
cana-4558	49	5	with	with	ADP
cana-4558	49	6	yolov4	yolov4	NOUN
cana-4558	49	7	by	by	ADP
cana-4558	49	8	ksrce	ksrce	PROPN
cana-4558	49	9	dhenuka	dhenuka	PROPN
cana-4558	49	10	lab	lab	NOUN
cana-4558	49	11	with	with	ADP
cana-4558	49	12	real	real	ADJ
cana-4558	49	13	-	-	PUNCT
cana-4558	49	14	time	time	NOUN
cana-4558	49	15	detection	detection	NOUN
cana-4558	49	16	of	of	ADP
cana-4558	49	17	leaf	leaf	NOUN
cana-4558	49	18	diseases[15	diseases[15	NOUN
cana-4558	49	19	]	]	PUNCT
cana-4558	49	20	.	.	PUNCT
cana-4558	50	1	for	for	ADP
cana-4558	50	2	the	the	DET
cana-4558	50	3	study	study	NOUN
cana-4558	50	4	,	,	PUNCT
cana-4558	50	5	the	the	DET
cana-4558	50	6	g*power	g*pow	ADJ
cana-4558	50	7	analysis	analysis	NOUN
cana-4558	50	8	determined	determine	VERB
cana-4558	50	9	sample	sample	NOUN
cana-4558	50	10	size	size	NOUN
cana-4558	50	11	by	by	ADP
cana-4558	50	12	maintaining	maintain	VERB
cana-4558	50	13	a	a	DET
cana-4558	50	14	95	95	NUM
cana-4558	50	15	%	%	NOUN
cana-4558	50	16	confidence	confidence	NOUN
cana-4558	50	17	interval	interval	NOUN
cana-4558	50	18	at	at	ADP
cana-4558	50	19	a	a	DET
cana-4558	50	20	power	power	NOUN
cana-4558	50	21	value	value	NOUN
cana-4558	50	22	of	of	ADP
cana-4558	50	23	80	80	NUM
cana-4558	50	24	%	%	NOUN
cana-4558	50	25	and	and	CCONJ
cana-4558	50	26	at	at	ADP
cana-4558	50	27	a	a	DET
cana-4558	50	28	threshold	threshold	NOUN
cana-4558	50	29	of	of	ADP
cana-4558	50	30	0.05	0.05	NUM
cana-4558	50	31	%	%	NOUN
cana-4558	50	32	significance	significance	NOUN
cana-4558	50	33	[	[	X
cana-4558	50	34	16	16	NUM
cana-4558	50	35	]	]	PUNCT
cana-4558	50	36	.	.	PUNCT
cana-4558	51	1	group	group	NOUN
cana-4558	51	2	1	1	NUM
cana-4558	51	3	is	be	AUX
cana-4558	51	4	the	the	DET
cana-4558	51	5	current	current	ADJ
cana-4558	51	6	approach	approach	NOUN
cana-4558	51	7	with	with	ADP
cana-4558	51	8	the	the	DET
cana-4558	51	9	cnn	cnn	PROPN
cana-4558	51	10	-	-	PUNCT
cana-4558	51	11	based	base	VERB
cana-4558	51	12	model	model	NOUN
cana-4558	51	13	,	,	PUNCT
cana-4558	51	14	trained	train	VERB
cana-4558	51	15	on	on	ADP
cana-4558	51	16	26	26	NUM
cana-4558	51	17	images	image	NOUN
cana-4558	51	18	of	of	ADP
cana-4558	51	19	diseased	diseased	ADJ
cana-4558	51	20	leaves	leave	NOUN
cana-4558	51	21	in	in	ADP
cana-4558	51	22	conditions	condition	NOUN
cana-4558	51	23	of	of	ADP
cana-4558	51	24	different	different	ADJ
cana-4558	51	25	light	light	NOUN
cana-4558	51	26	,	,	PUNCT
cana-4558	51	27	as	as	ADV
cana-4558	51	28	well	well	ADV
cana-4558	51	29	as	as	ADP
cana-4558	51	30	occlusions	occlusion	NOUN
cana-4558	51	31	and	and	CCONJ
cana-4558	51	32	different	different	ADJ
cana-4558	51	33	complex	complex	ADJ
cana-4558	51	34	backgrounds	background	NOUN
cana-4558	51	35	.	.	PUNCT
cana-4558	52	1	techniques	technique	NOUN
cana-4558	52	2	of	of	ADP
cana-4558	52	3	scaling	scaling	NOUN
cana-4558	52	4	,	,	PUNCT
cana-4558	52	5	normalization	normalization	NOUN
cana-4558	52	6	,	,	PUNCT
cana-4558	52	7	and	and	CCONJ
cana-4558	52	8	contrast	contrast	NOUN
cana-4558	52	9	enhancement	enhancement	NOUN
cana-4558	52	10	were	be	AUX
cana-4558	52	11	applied	apply	VERB
cana-4558	52	12	for	for	ADP
cana-4558	52	13	refinement	refinement	NOUN
cana-4558	52	14	of	of	ADP
cana-4558	52	15	input	input	NOUN
cana-4558	52	16	data	datum	NOUN
cana-4558	52	17	[	[	X
cana-4558	52	18	17	17	NUM
cana-4558	52	19	]	]	PUNCT
cana-4558	52	20	.	.	PUNCT
cana-4558	53	1	group	group	NOUN
cana-4558	53	2	2	2	NUM
cana-4558	53	3	,	,	PUNCT
cana-4558	53	4	which	which	PRON
cana-4558	53	5	is	be	AUX
cana-4558	53	6	the	the	DET
cana-4558	53	7	proposed	proposed	ADJ
cana-4558	53	8	yolov4	yolov4	PROPN
cana-4558	53	9	model	model	PROPN
cana-4558	53	10	,	,	PUNCT
cana-4558	53	11	was	be	AUX
cana-4558	53	12	trained	train	VERB
cana-4558	53	13	on	on	ADP
cana-4558	53	14	the	the	DET
cana-4558	53	15	same	same	ADJ
cana-4558	53	16	dataset	dataset	NOUN
cana-4558	53	17	but	but	CCONJ
cana-4558	53	18	this	this	DET
cana-4558	53	19	time	time	NOUN
cana-4558	53	20	used	use	VERB
cana-4558	53	21	automated	automate	VERB
cana-4558	53	22	feature	feature	NOUN
cana-4558	53	23	extraction	extraction	NOUN
cana-4558	53	24	rather	rather	ADV
cana-4558	53	25	than	than	ADP
cana-4558	53	26	manual	manual	ADJ
cana-4558	53	27	descriptors	descriptor	NOUN
cana-4558	53	28	like	like	ADP
cana-4558	53	29	histogram	histogram	NOUN
cana-4558	53	30	of	of	ADP
cana-4558	53	31	oriented	orient	VERB
cana-4558	53	32	gradients	gradient	NOUN
cana-4558	53	33	(	(	PUNCT
cana-4558	53	34	hog	hog	NOUN
cana-4558	53	35	)	)	PUNCT
cana-4558	53	36	and	and	CCONJ
cana-4558	53	37	local	local	ADJ
cana-4558	53	38	binary	binary	ADJ
cana-4558	53	39	patterns	pattern	NOUN
cana-4558	53	40	(	(	PUNCT
cana-4558	53	41	lbp	lbp	PROPN
cana-4558	53	42	)	)	PUNCT
cana-4558	53	43	,	,	PUNCT
cana-4558	53	44	which	which	PRON
cana-4558	53	45	were	be	AUX
cana-4558	53	46	used	use	VERB
cana-4558	53	47	in	in	ADP
cana-4558	53	48	cnn	cnn	PROPN
cana-4558	53	49	models	model	NOUN
cana-4558	53	50	.	.	PUNCT
cana-4558	54	1	fig	fig	NOUN
cana-4558	54	2	.	.	PUNCT
cana-4558	55	1	1	1	X
cana-4558	55	2	.	.	X
cana-4558	55	3	workflow	workflow	NOUN
cana-4558	55	4	of	of	ADP
cana-4558	55	5	yolov4	yolov4	PROPN
cana-4558	55	6	algorithm	algorithm	PROPN
cana-4558	55	7	fig	fig	PROPN
cana-4558	55	8	.	.	PUNCT
cana-4558	56	1	1	1	X
cana-4558	56	2	.	.	X
cana-4558	56	3	the	the	DET
cana-4558	56	4	flowchart	flowchart	NOUN
cana-4558	56	5	for	for	ADP
cana-4558	56	6	the	the	DET
cana-4558	56	7	leaf	leaf	NOUN
cana-4558	56	8	health	health	NOUN
cana-4558	56	9	status	status	NOUN
cana-4558	56	10	and	and	CCONJ
cana-4558	56	11	classification	classification	NOUN
cana-4558	56	12	is	be	AUX
cana-4558	56	13	a	a	DET
cana-4558	56	14	structured	structured	ADJ
cana-4558	56	15	approach	approach	NOUN
cana-4558	56	16	of	of	ADP
cana-4558	56	17	acquisition	acquisition	NOUN
cana-4558	56	18	of	of	ADP
cana-4558	56	19	the	the	DET
cana-4558	56	20	leaf	leaf	NOUN
cana-4558	56	21	dataset	dataset	NOUN
cana-4558	56	22	,	,	PUNCT
cana-4558	56	23	splitting	split	VERB
cana-4558	56	24	them	they	PRON
cana-4558	56	25	into	into	ADP
cana-4558	56	26	training	training	NOUN
cana-4558	56	27	and	and	CCONJ
cana-4558	56	28	validation	validation	NOUN
cana-4558	56	29	sets	set	NOUN
cana-4558	56	30	,	,	PUNCT
cana-4558	56	31	followed	follow	VERB
cana-4558	56	32	by	by	ADP
cana-4558	56	33	a	a	DET
cana-4558	56	34	model	model	NOUN
cana-4558	56	35	training	training	NOUN
cana-4558	56	36	approach	approach	NOUN
cana-4558	56	37	based	base	VERB
cana-4558	56	38	on	on	ADP
cana-4558	56	39	yolov4	yolov4	PROPN
cana-4558	56	40	.	.	PUNCT
cana-4558	57	1	the	the	DET
cana-4558	57	2	model	model	NOUN
cana-4558	57	3	uses	use	VERB
cana-4558	57	4	cnns	cnn	NOUN
cana-4558	57	5	for	for	ADP
cana-4558	57	6	feature	feature	NOUN
cana-4558	57	7	extraction	extraction	NOUN
cana-4558	57	8	and	and	CCONJ
cana-4558	57	9	optimizes	optimize	VERB
cana-4558	57	10	bounding	bound	VERB
cana-4558	57	11	box	box	NOUN
cana-4558	57	12	predictions	prediction	NOUN
cana-4558	57	13	through	through	ADP
cana-4558	57	14	localization	localization	NOUN
cana-4558	57	15	,	,	PUNCT
cana-4558	57	16	confidence	confidence	NOUN
cana-4558	57	17	,	,	PUNCT
cana-4558	57	18	and	and	CCONJ
cana-4558	57	19	classification	classification	NOUN
cana-4558	57	20	losses	loss	NOUN
cana-4558	57	21	.	.	PUNCT
cana-4558	58	1	the	the	DET
cana-4558	58	2	mathematical	mathematical	ADJ
cana-4558	58	3	model	model	NOUN
cana-4558	58	4	follows	follow	VERB
cana-4558	58	5	:	:	PUNCT
cana-4558	58	6	[	[	PUNCT
cana-4558	58	7	l_{{total	l_{{total	ADJ
cana-4558	58	8	}	}	PUNCT
cana-4558	58	9	}	}	PUNCT
cana-4558	58	10	=	=	SYM
cana-4558	58	11	l_{{coord	l_{{coord	NOUN
cana-4558	58	12	}	}	PUNCT
cana-4558	58	13	}	}	PUNCT
cana-4558	58	14	+	+	NUM
cana-4558	58	15	l_{{conf	l_{{conf	NOUN
cana-4558	58	16	}	}	PUNCT
cana-4558	58	17	}	}	PUNCT
cana-4558	58	18	+	+	CCONJ
cana-4558	58	19	l_{{class	l_{{class	NOUN
cana-4558	58	20	}	}	PUNCT
cana-4558	58	21	}	}	PUNCT
cana-4558	58	22	]	]	PUNCT
cana-4558	58	23	(	(	PUNCT
cana-4558	58	24	1	1	X
cana-4558	58	25	)	)	PUNCT
cana-4558	58	26	in	in	ADP
cana-4558	58	27	equation	equation	NOUN
cana-4558	58	28	(	(	PUNCT
cana-4558	58	29	1	1	NUM
cana-4558	58	30	)	)	PUNCT
cana-4558	58	31	,	,	PUNCT
cana-4558	58	32	ltotal	ltotal	ADJ
cana-4558	58	33	l_{{total	l_{{total	ADJ
cana-4558	58	34	}	}	PUNCT
cana-4558	58	35	}	}	PUNCT
cana-4558	58	36	total	total	NOUN
cana-4558	58	37	represents	represent	VERB
cana-4558	58	38	the	the	DET
cana-4558	58	39	total	total	ADJ
cana-4558	58	40	loss	loss	NOUN
cana-4558	58	41	function	function	NOUN
cana-4558	58	42	,	,	PUNCT
cana-4558	58	43	as	as	ADP
cana-4558	58	44	lcoordl_{{coord	lcoordl_{{coord	ADJ
cana-4558	58	45	}	}	PUNCT
cana-4558	58	46	}	}	PUNCT
cana-4558	58	47	lord	lord	PROPN
cana-4558	58	48	,	,	PUNCT
cana-4558	58	49	the	the	DET
cana-4558	58	50	coordinate	coordinate	NOUN
cana-4558	58	51	loss	loss	NOUN
cana-4558	58	52	;	;	PUNCT
cana-4558	58	53	lconfl_{{conf	lconfl_{{conf	NUM
cana-4558	58	54	}	}	PUNCT
cana-4558	58	55	}	}	PUNCT
cana-4558	58	56	lconf	lconf	PROPN
cana-4558	58	57	,	,	PUNCT
cana-4558	58	58	the	the	DET
cana-4558	58	59	confidence	confidence	NOUN
cana-4558	58	60	loss	loss	NOUN
cana-4558	58	61	;	;	PUNCT
cana-4558	58	62	and	and	CCONJ
cana-4558	58	63	lclassl_{{class	lclassl_{{class	ADJ
cana-4558	58	64	}	}	PUNCT
cana-4558	58	65	}	}	PUNCT
cana-4558	58	66	lclass	lclass	NOUN
cana-4558	58	67	,	,	PUNCT
cana-4558	58	68	the	the	DET
cana-4558	58	69	classification	classification	NOUN
cana-4558	58	70	loss	loss	NOUN
cana-4558	58	71	.	.	PUNCT
cana-4558	59	1	iv	iv	X
cana-4558	59	2	.	.	PUNCT
cana-4558	60	1	statistical	statistical	ADJ
cana-4558	60	2	analysis	analysis	NOUN
cana-4558	60	3	the	the	DET
cana-4558	60	4	effectiveness	effectiveness	NOUN
cana-4558	60	5	of	of	ADP
cana-4558	60	6	leaf	leaf	NOUN
cana-4558	60	7	diseases	disease	NOUN
cana-4558	60	8	detection	detection	NOUN
cana-4558	60	9	using	use	VERB
cana-4558	60	10	yolov4	yolov4	PROPN
cana-4558	60	11	was	be	AUX
cana-4558	60	12	gauged	gauge	VERB
cana-4558	60	13	using	use	VERB
cana-4558	60	14	statistical	statistical	ADJ
cana-4558	60	15	analysis	analysis	NOUN
cana-4558	60	16	using	use	VERB
cana-4558	60	17	spss	spss	PROPN
cana-4558	60	18	version	version	NOUN
cana-4558	60	19	11.0	11.0	NUM
cana-4558	61	1	[	[	X
cana-4558	61	2	15	15	NUM
cana-4558	61	3	]	]	PUNCT
cana-4558	61	4	.	.	PUNCT
cana-4558	62	1	disease	disease	NOUN
cana-4558	62	2	classification	classification	NOUN
cana-4558	62	3	accuracy	accuracy	NOUN
cana-4558	62	4	and	and	CCONJ
cana-4558	62	5	processing	processing	NOUN
cana-4558	62	6	time	time	NOUN
cana-4558	62	7	were	be	AUX
cana-4558	62	8	considered	consider	VERB
cana-4558	62	9	as	as	ADP
cana-4558	62	10	the	the	DET
cana-4558	62	11	dependent	dependent	ADJ
cana-4558	62	12	variables	variable	NOUN
cana-4558	62	13	whereas	whereas	SCONJ
cana-4558	62	14	,	,	PUNCT
cana-4558	62	15	image	image	NOUN
cana-4558	62	16	resolution	resolution	NOUN
cana-4558	62	17	,	,	PUNCT
cana-4558	62	18	environmental	environmental	ADJ
cana-4558	62	19	conditions	condition	NOUN
cana-4558	62	20	such	such	ADJ
cana-4558	62	21	as	as	ADP
cana-4558	62	22	lighting	lighting	NOUN
cana-4558	62	23	and	and	CCONJ
cana-4558	62	24	complexity	complexity	NOUN
cana-4558	62	25	of	of	ADP
cana-4558	62	26	the	the	DET
cana-4558	62	27	background	background	NOUN
cana-4558	62	28	and	and	CCONJ
cana-4558	62	29	model	model	NOUN
cana-4558	62	30	architectureyolov4	architectureyolov4	PROPN
cana-4558	62	31	or	or	CCONJ
cana-4558	62	32	other	other	ADJ
cana-4558	62	33	cnn	cnn	PROPN
cana-4558	62	34	-	-	PUNCT
cana-4558	62	35	based	base	VERB
cana-4558	62	36	models	model	NOUN
cana-4558	62	37	are	be	AUX
cana-4558	62	38	communications	communication	NOUN
cana-4558	62	39	on	on	ADP
cana-4558	62	40	applied	apply	VERB
cana-4558	62	41	nonlinear	nonlinear	ADJ
cana-4558	62	42	analysis	analysis	NOUN
cana-4558	62	43	issn	issn	NOUN
cana-4558	62	44	:	:	PUNCT
cana-4558	62	45	1074	1074	NUM
cana-4558	62	46	-	-	PUNCT
cana-4558	62	47	133x	133x	NUM
cana-4558	62	48	vol	vol	NOUN
cana-4558	62	49	32	32	NUM
cana-4558	63	1	no	no	NOUN
cana-4558	63	2	.	.	PUNCT
cana-4558	64	1	9s	9s	NUM
cana-4558	64	2	(	(	PUNCT
cana-4558	64	3	2025	2025	NUM
cana-4558	64	4	)	)	PUNCT
cana-4558	64	5	2534	2534	NUM
cana-4558	65	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	65	2	considered	consider	VERB
cana-4558	65	3	to	to	PART
cana-4558	65	4	be	be	AUX
cana-4558	65	5	the	the	DET
cana-4558	65	6	independent	independent	ADJ
cana-4558	65	7	variables.group	variables.group	PROPN
cana-4558	65	8	statistics	statistic	NOUN
cana-4558	65	9	and	and	CCONJ
cana-4558	65	10	independent	independent	ADJ
cana-4558	65	11	sample	sample	NOUN
cana-4558	65	12	t	t	PROPN
cana-4558	65	13	-	-	PUNCT
cana-4558	65	14	tests	test	NOUN
cana-4558	65	15	were	be	AUX
cana-4558	65	16	used	use	VERB
cana-4558	65	17	in	in	ADP
cana-4558	65	18	analyzing	analyze	VERB
cana-4558	65	19	these	these	DET
cana-4558	65	20	variables	variable	NOUN
cana-4558	65	21	.	.	PUNCT
cana-4558	66	1	this	this	DET
cana-4558	66	2	analysis	analysis	NOUN
cana-4558	66	3	optimizes	optimize	VERB
cana-4558	66	4	precision	precision	NOUN
cana-4558	66	5	agriculture	agriculture	NOUN
cana-4558	66	6	tools	tool	NOUN
cana-4558	66	7	to	to	PART
cana-4558	66	8	ensure	ensure	VERB
cana-4558	66	9	higher	high	ADJ
cana-4558	66	10	reliability	reliability	NOUN
cana-4558	66	11	and	and	CCONJ
cana-4558	66	12	efficiency	efficiency	NOUN
cana-4558	66	13	in	in	ADP
cana-4558	66	14	large	large	ADJ
cana-4558	66	15	-	-	PUNCT
cana-4558	66	16	scale	scale	NOUN
cana-4558	66	17	leaf	leaf	NOUN
cana-4558	66	18	disease	disease	NOUN
cana-4558	66	19	detection	detection	NOUN
cana-4558	66	20	applications	application	NOUN
cana-4558	66	21	.	.	PUNCT
cana-4558	67	1	v.	v.	ADP
cana-4558	67	2	result	result	VERB
cana-4558	67	3	the	the	DET
cana-4558	67	4	yolov4	yolov4	NOUN
cana-4558	67	5	-	-	PUNCT
cana-4558	67	6	based	base	VERB
cana-4558	67	7	leaf	leaf	NOUN
cana-4558	67	8	disease	disease	NOUN
cana-4558	67	9	detection	detection	NOUN
cana-4558	67	10	was	be	AUX
cana-4558	67	11	evaluated	evaluate	VERB
cana-4558	67	12	in	in	ADP
cana-4558	67	13	various	various	ADJ
cana-4558	67	14	environmental	environmental	ADJ
cana-4558	67	15	conditions	condition	NOUN
cana-4558	67	16	and	and	CCONJ
cana-4558	67	17	compared	compare	VERB
cana-4558	67	18	with	with	ADP
cana-4558	67	19	cnn	cnn	PROPN
cana-4558	67	20	models	model	NOUN
cana-4558	67	21	.	.	PUNCT
cana-4558	68	1	yolov4	yolov4	NOUN
cana-4558	68	2	mean	mean	PROPN
cana-4558	68	3	accuracy	accuracy	NOUN
cana-4558	68	4	was	be	AUX
cana-4558	68	5	92.5	92.5	NUM
cana-4558	68	6	%	%	NOUN
cana-4558	68	7	with	with	ADP
cana-4558	68	8	a	a	DET
cana-4558	68	9	standard	standard	ADJ
cana-4558	68	10	deviation	deviation	NOUN
cana-4558	68	11	of	of	ADP
cana-4558	68	12	±1.5	±1.5	NOUN
cana-4558	68	13	and	and	CCONJ
cana-4558	68	14	standard	standard	ADJ
cana-4558	68	15	error	error	NOUN
cana-4558	68	16	mean	mean	NOUN
cana-4558	68	17	of	of	ADP
cana-4558	68	18	0.75	0.75	NUM
cana-4558	68	19	while	while	SCONJ
cana-4558	68	20	cnn	cnn	PROPN
cana-4558	68	21	result	result	NOUN
cana-4558	68	22	was	be	AUX
cana-4558	68	23	mean	mean	ADJ
cana-4558	68	24	accuracy	accuracy	NOUN
cana-4558	68	25	of	of	ADP
cana-4558	68	26	85.3	85.3	NUM
cana-4558	68	27	%	%	NOUN
cana-4558	68	28	with	with	ADP
cana-4558	68	29	a	a	DET
cana-4558	68	30	standard	standard	ADJ
cana-4558	68	31	deviation	deviation	NOUN
cana-4558	68	32	of	of	ADP
cana-4558	68	33	±2.1	±2.1	PROPN
cana-4558	68	34	and	and	CCONJ
cana-4558	68	35	a	a	DET
cana-4558	68	36	standard	standard	ADJ
cana-4558	68	37	error	error	NOUN
cana-4558	68	38	mean	mean	NOUN
cana-4558	68	39	of	of	ADP
cana-4558	68	40	1.05	1.05	NUM
cana-4558	68	41	.	.	PUNCT
cana-4558	69	1	the	the	DET
cana-4558	69	2	t	t	PROPN
cana-4558	69	3	-	-	PUNCT
cana-4558	69	4	test	test	NOUN
cana-4558	69	5	also	also	ADV
cana-4558	69	6	showed	show	VERB
cana-4558	69	7	that	that	SCONJ
cana-4558	69	8	yolov4	yolov4	PROPN
cana-4558	69	9	was	be	AUX
cana-4558	69	10	still	still	ADV
cana-4558	69	11	on	on	ADP
cana-4558	69	12	top	top	NOUN
cana-4558	69	13	for	for	ADP
cana-4558	69	14	real	real	ADJ
cana-4558	69	15	-	-	PUNCT
cana-4558	69	16	time	time	NOUN
cana-4558	69	17	detection	detection	NOUN
cana-4558	69	18	.	.	PUNCT
cana-4558	70	1	table	table	NOUN
cana-4558	70	2	1	1	NUM
cana-4558	70	3	shows	show	VERB
cana-4558	70	4	the	the	DET
cana-4558	70	5	comparison	comparison	NOUN
cana-4558	70	6	of	of	ADP
cana-4558	70	7	accuracy	accuracy	NOUN
cana-4558	70	8	,	,	PUNCT
cana-4558	70	9	precision	precision	NOUN
cana-4558	70	10	,	,	PUNCT
cana-4558	70	11	and	and	CCONJ
cana-4558	70	12	recall	recall	VERB
cana-4558	70	13	values	value	NOUN
cana-4558	70	14	of	of	ADP
cana-4558	70	15	yolov4	yolov4	PROPN
cana-4558	70	16	and	and	CCONJ
cana-4558	70	17	cnn	cnn	PROPN
cana-4558	70	18	models	model	NOUN
cana-4558	70	19	in	in	ADP
cana-4558	70	20	leaf	leaf	NOUN
cana-4558	70	21	disease	disease	NOUN
cana-4558	70	22	detection	detection	NOUN
cana-4558	70	23	with	with	ADP
cana-4558	70	24	various	various	ADJ
cana-4558	70	25	agricultural	agricultural	ADJ
cana-4558	70	26	field	field	NOUN
cana-4558	70	27	conditions	condition	NOUN
cana-4558	70	28	,	,	PUNCT
cana-4558	70	29	involving	involve	VERB
cana-4558	70	30	challenging	challenging	ADJ
cana-4558	70	31	conditions	condition	NOUN
cana-4558	70	32	of	of	ADP
cana-4558	70	33	fluctuating	fluctuate	VERB
cana-4558	70	34	lighting	lighting	NOUN
cana-4558	70	35	,	,	PUNCT
cana-4558	70	36	overlapping	overlap	VERB
cana-4558	70	37	leaves	leave	NOUN
cana-4558	70	38	,	,	PUNCT
cana-4558	70	39	and	and	CCONJ
cana-4558	70	40	heterogeneous	heterogeneous	ADJ
cana-4558	70	41	layouts	layout	NOUN
cana-4558	70	42	.	.	PUNCT
cana-4558	71	1	the	the	DET
cana-4558	71	2	table	table	NOUN
cana-4558	71	3	yields	yield	VERB
cana-4558	71	4	a	a	DET
cana-4558	71	5	comprehensive	comprehensive	ADJ
cana-4558	71	6	comparison	comparison	NOUN
cana-4558	71	7	of	of	ADP
cana-4558	71	8	performance	performance	NOUN
cana-4558	71	9	between	between	ADP
cana-4558	71	10	the	the	DET
cana-4558	71	11	two	two	NUM
cana-4558	71	12	models	model	NOUN
cana-4558	71	13	in	in	ADP
cana-4558	71	14	real	real	ADJ
cana-4558	71	15	-	-	PUNCT
cana-4558	71	16	time	time	NOUN
cana-4558	71	17	applications	application	NOUN
cana-4558	71	18	for	for	ADP
cana-4558	71	19	agriculture	agriculture	NOUN
cana-4558	71	20	.	.	PUNCT
cana-4558	72	1	table	table	NOUN
cana-4558	72	2	1	1	NUM
cana-4558	72	3	comparison	comparison	NOUN
cana-4558	72	4	of	of	ADP
cana-4558	72	5	accuracy	accuracy	NOUN
cana-4558	72	6	,	,	PUNCT
cana-4558	72	7	precision	precision	NOUN
cana-4558	72	8	,	,	PUNCT
cana-4558	72	9	and	and	CCONJ
cana-4558	72	10	recall	recall	VERB
cana-4558	72	11	values	value	NOUN
cana-4558	72	12	of	of	ADP
cana-4558	72	13	yolov4	yolov4	PROPN
cana-4558	72	14	and	and	CCONJ
cana-4558	72	15	cnn	cnn	PROPN
cana-4558	72	16	models	model	NOUN
cana-4558	72	17	in	in	ADP
cana-4558	72	18	leaf	leaf	NOUN
cana-4558	72	19	disease	disease	NOUN
cana-4558	72	20	detection	detection	NOUN
cana-4558	72	21	with	with	ADP
cana-4558	72	22	various	various	ADJ
cana-4558	72	23	agricultural	agricultural	ADJ
cana-4558	72	24	field	field	NOUN
cana-4558	72	25	conditions	condition	NOUN
cana-4558	72	26	,	,	PUNCT
cana-4558	72	27	involving	involve	VERB
cana-4558	72	28	challenging	challenging	ADJ
cana-4558	72	29	conditions	condition	NOUN
cana-4558	72	30	of	of	ADP
cana-4558	72	31	fluctuating	fluctuate	VERB
cana-4558	72	32	lighting	lighting	NOUN
cana-4558	72	33	,	,	PUNCT
cana-4558	72	34	overlapping	overlap	VERB
cana-4558	72	35	leaves	leave	NOUN
cana-4558	72	36	,	,	PUNCT
cana-4558	72	37	and	and	CCONJ
cana-4558	72	38	heterogeneous	heterogeneous	ADJ
cana-4558	72	39	layouts	layout	NOUN
cana-4558	72	40	.	.	PUNCT
cana-4558	73	1	e	e	X
cana-4558	74	1	p	p	NOUN
cana-4558	74	2	o	o	X
cana-4558	74	3	ch	ch	NOUN
cana-4558	74	4	y	y	NOUN
cana-4558	74	5	o	o	NOUN
cana-4558	74	6	l	l	NOUN
cana-4558	74	7	o	o	X
cana-4558	74	8	v	v	ADP
cana-4558	74	9	4	4	NUM
cana-4558	74	10	a	a	DET
cana-4558	74	11	cc	cc	ADP
cana-4558	74	12	u	u	NOUN
cana-4558	74	13	ra	ra	PROPN
cana-4558	74	14	cy	cy	PROPN
cana-4558	74	15	c	c	PROPN
cana-4558	74	16	n	n	ADP
cana-4558	74	17	n	n	ADV
cana-4558	74	18	a	a	DET
cana-4558	74	19	cc	cc	X
cana-4558	74	20	u	u	NOUN
cana-4558	74	21	ra	ra	PROPN
cana-4558	74	22	cy	cy	INTJ
cana-4558	74	23	y	y	NOUN
cana-4558	74	24	o	o	PROPN
cana-4558	74	25	l	l	X
cana-4558	74	26	o	o	X
cana-4558	74	27	v	v	ADP
cana-4558	74	28	4	4	NUM
cana-4558	74	29	a	a	DET
cana-4558	74	30	cc	cc	ADP
cana-4558	74	31	u	u	NOUN
cana-4558	74	32	ra	ra	PROPN
cana-4558	74	33	cy	cy	PROPN
cana-4558	74	34	(	(	PUNCT
cana-4558	74	35	%	%	NOUN
cana-4558	74	36	)	)	PUNCT
cana-4558	74	37	c	c	PROPN
cana-4558	74	38	n	n	CCONJ
cana-4558	74	39	n	n	PROPN
cana-4558	74	40	p	p	X
cana-4558	74	41	re	re	X
cana-4558	74	42	ci	ci	PROPN
cana-4558	74	43	si	si	PROPN
cana-4558	74	44	o	o	PROPN
cana-4558	74	45	n	n	CCONJ
cana-4558	74	46	(	(	PUNCT
cana-4558	74	47	%	%	INTJ
cana-4558	74	48	)	)	PUNCT
cana-4558	75	1	y	y	NOUN
cana-4558	75	2	o	o	NOUN
cana-4558	75	3	l	l	NOUN
cana-4558	76	1	o	o	X
cana-4558	76	2	v	v	ADP
cana-4558	76	3	4	4	NUM
cana-4558	76	4	p	p	NOUN
cana-4558	76	5	re	re	ADP
cana-4558	76	6	ci	ci	NOUN
cana-4558	76	7	si	si	PROPN
cana-4558	76	8	o	o	PROPN
cana-4558	76	9	n	n	CCONJ
cana-4558	76	10	(	(	PUNCT
cana-4558	76	11	%	%	NOUN
cana-4558	76	12	)	)	PUNCT
cana-4558	76	13	c	c	PROPN
cana-4558	76	14	n	n	CCONJ
cana-4558	76	15	n	n	NOUN
cana-4558	76	16	r	r	NOUN
cana-4558	76	17	ec	ec	PROPN
cana-4558	76	18	al	al	PROPN
cana-4558	76	19	l	l	PROPN
cana-4558	76	20	(	(	PUNCT
cana-4558	76	21	%	%	NOUN
cana-4558	76	22	)	)	PUNCT
cana-4558	76	23	1	1	NUM
cana-4558	76	24	.	.	X
cana-4558	76	25	0.83	0.83	NUM
cana-4558	76	26	0.75	0.75	NUM
cana-4558	76	27	0.80	0.80	NUM
cana-4558	76	28	0.70	0.70	NUM
cana-4558	76	29	0.81	0.81	NUM
cana-4558	76	30	0.71	0.71	NUM
cana-4558	76	31	2	2	NUM
cana-4558	76	32	.	.	PUNCT
cana-4558	76	33	0.85	0.85	NUM
cana-4558	76	34	0.76	0.76	NUM
cana-4558	76	35	0.82	0.82	NUM
cana-4558	76	36	0.73	0.73	NUM
cana-4558	76	37	0.83	0.83	NUM
cana-4558	76	38	0.74	0.74	NUM
cana-4558	76	39	3	3	NUM
cana-4558	76	40	.	.	NOUN
cana-4558	76	41	0.86	0.86	NUM
cana-4558	76	42	0.78	0.78	NUM
cana-4558	76	43	0.83	0.83	NUM
cana-4558	76	44	0.76	0.76	NUM
cana-4558	76	45	0.84	0.84	NUM
cana-4558	76	46	0.77	0.77	NUM
cana-4558	76	47	4	4	NUM
cana-4558	76	48	.	.	PUNCT
cana-4558	76	49	0.87	0.87	NUM
cana-4558	76	50	0.79	0.79	NUM
cana-4558	76	51	0.85	0.85	NUM
cana-4558	76	52	0.78	0.78	NUM
cana-4558	76	53	0.85	0.85	NUM
cana-4558	76	54	0.79	0.79	NUM
cana-4558	76	55	5	5	NUM
cana-4558	76	56	.	.	PUNCT
cana-4558	76	57	0.88	0.88	NUM
cana-4558	76	58	0.80	0.80	NUM
cana-4558	76	59	0.86	0.86	NUM
cana-4558	76	60	0.79	0.79	NUM
cana-4558	76	61	0.86	0.86	NUM
cana-4558	76	62	0.80	0.80	NUM
cana-4558	76	63	6	6	NUM
cana-4558	76	64	.	.	ADP
cana-4558	76	65	0.89	0.89	NUM
cana-4558	76	66	0.81	0.81	NUM
cana-4558	76	67	0.87	0.87	NUM
cana-4558	76	68	0.80	0.80	NUM
cana-4558	76	69	0.87	0.87	NUM
cana-4558	76	70	0.81	0.81	NUM
cana-4558	76	71	7	7	NUM
cana-4558	76	72	.	.	PUNCT
cana-4558	77	1	0.90	0.90	NUM
cana-4558	77	2	0.82	0.82	NUM
cana-4558	77	3	0.88	0.88	NUM
cana-4558	77	4	0.81	0.81	NUM
cana-4558	77	5	0.88	0.88	NUM
cana-4558	77	6	0.82	0.82	NUM
cana-4558	77	7	8	8	NUM
cana-4558	77	8	.	.	PUNCT
cana-4558	78	1	0.91	0.91	NUM
cana-4558	78	2	0.83	0.83	NUM
cana-4558	78	3	0.89	0.89	NUM
cana-4558	78	4	0.82	0.82	NUM
cana-4558	78	5	0.89	0.89	NUM
cana-4558	78	6	0.83	0.83	NUM
cana-4558	78	7	9	9	NUM
cana-4558	78	8	.	.	PUNCT
cana-4558	78	9	0.92	0.92	NUM
cana-4558	78	10	0.84	0.84	NUM
cana-4558	78	11	0.90	0.90	NUM
cana-4558	78	12	0.83	0.83	NUM
cana-4558	78	13	0.90	0.90	NUM
cana-4558	78	14	0.84	0.84	NUM
cana-4558	78	15	10	10	NUM
cana-4558	78	16	.	.	PUNCT
cana-4558	79	1	0.92	0.92	NUM
cana-4558	79	2	0.85	0.85	NUM
cana-4558	79	3	0.91	0.91	NUM
cana-4558	79	4	0.84	0.84	NUM
cana-4558	79	5	0.91	0.91	NUM
cana-4558	79	6	0.85	0.85	NUM
cana-4558	79	7	11	11	NUM
cana-4558	79	8	.	.	PUNCT
cana-4558	80	1	0.93	0.93	NUM
cana-4558	80	2	0.86	0.86	NUM
cana-4558	80	3	0.92	0.92	NUM
cana-4558	80	4	0.85	0.85	NUM
cana-4558	80	5	0.92	0.92	NUM
cana-4558	80	6	0.86	0.86	NUM
cana-4558	80	7	12	12	NUM
cana-4558	80	8	.	.	PUNCT
cana-4558	81	1	0.94	0.94	NUM
cana-4558	81	2	0.87	0.87	NUM
cana-4558	81	3	0.93	0.93	NUM
cana-4558	81	4	0.86	0.86	NUM
cana-4558	81	5	0.93	0.93	NUM
cana-4558	81	6	0.87	0.87	NUM
cana-4558	81	7	13	13	NUM
cana-4558	81	8	.	.	PUNCT
cana-4558	82	1	0.94	0.94	NUM
cana-4558	82	2	0.88	0.88	NUM
cana-4558	82	3	0.94	0.94	NUM
cana-4558	82	4	0.87	0.87	NUM
cana-4558	82	5	0.94	0.94	NUM
cana-4558	82	6	0.88	0.88	NUM
cana-4558	82	7	14	14	NUM
cana-4558	82	8	.	.	PUNCT
cana-4558	82	9	0.95	0.95	NUM
cana-4558	82	10	0.89	0.89	NUM
cana-4558	82	11	0.94	0.94	NUM
cana-4558	82	12	0.88	0.88	NUM
cana-4558	82	13	0.94	0.94	NUM
cana-4558	82	14	0.89	0.89	NUM
cana-4558	82	15	table	table	NOUN
cana-4558	82	16	2	2	NUM
cana-4558	82	17	represents	represent	VERB
cana-4558	82	18	the	the	DET
cana-4558	82	19	leaf	leaf	NOUN
cana-4558	82	20	disease	disease	NOUN
cana-4558	82	21	detection	detection	NOUN
cana-4558	82	22	accuracy	accuracy	NOUN
cana-4558	82	23	of	of	ADP
cana-4558	82	24	the	the	DET
cana-4558	82	25	comparison	comparison	NOUN
cana-4558	82	26	between	between	ADP
cana-4558	82	27	yolov4	yolov4	NOUN
cana-4558	82	28	model	model	NOUN
cana-4558	82	29	and	and	CCONJ
cana-4558	82	30	cnn	cnn	PROPN
cana-4558	82	31	models	model	NOUN
cana-4558	82	32	for	for	ADP
cana-4558	82	33	precision	precision	NOUN
cana-4558	82	34	agriculture	agriculture	NOUN
cana-4558	82	35	was	be	AUX
cana-4558	82	36	yolov4	yolov4	NOUN
cana-4558	82	37	mean	mean	NOUN
cana-4558	82	38	accuracy	accuracy	NOUN
cana-4558	82	39	with	with	ADP
cana-4558	82	40	a	a	DET
cana-4558	82	41	standard	standard	ADJ
cana-4558	82	42	deviation	deviation	NOUN
cana-4558	82	43	and	and	CCONJ
cana-4558	82	44	a	a	DET
cana-4558	82	45	communications	communication	NOUN
cana-4558	82	46	on	on	ADP
cana-4558	82	47	applied	apply	VERB
cana-4558	82	48	nonlinear	nonlinear	ADJ
cana-4558	82	49	analysis	analysis	NOUN
cana-4558	82	50	issn	issn	NOUN
cana-4558	82	51	:	:	PUNCT
cana-4558	82	52	1074	1074	NUM
cana-4558	82	53	-	-	PUNCT
cana-4558	82	54	133x	133x	NUM
cana-4558	82	55	vol	vol	NOUN
cana-4558	82	56	32	32	NUM
cana-4558	82	57	no	no	NOUN
cana-4558	82	58	.	.	PUNCT
cana-4558	83	1	9s	9s	NUM
cana-4558	83	2	(	(	PUNCT
cana-4558	83	3	2025	2025	NUM
cana-4558	83	4	)	)	PUNCT
cana-4558	83	5	2535	2535	NUM
cana-4558	83	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	83	7	standard	standard	ADJ
cana-4558	83	8	error	error	NOUN
cana-4558	83	9	mean	mean	NOUN
cana-4558	83	10	of	of	ADP
cana-4558	83	11	[	[	X
cana-4558	83	12	x	x	X
cana-4558	83	13	]	]	X
cana-4558	83	14	.	.	PUNCT
cana-4558	84	1	while	while	SCONJ
cana-4558	84	2	the	the	DET
cana-4558	84	3	cnn	cnn	PROPN
cana-4558	84	4	model	model	NOUN
cana-4558	84	5	had	have	VERB
cana-4558	84	6	a	a	DET
cana-4558	84	7	mean	mean	ADJ
cana-4558	84	8	accuracy	accuracy	NOUN
cana-4558	84	9	of	of	ADP
cana-4558	84	10	[	[	X
cana-4558	84	11	a	a	X
cana-4558	84	12	]	]	X
cana-4558	84	13	,	,	PUNCT
cana-4558	84	14	with	with	ADP
cana-4558	84	15	a	a	DET
cana-4558	84	16	standard	standard	ADJ
cana-4558	84	17	deviation	deviation	NOUN
cana-4558	84	18	of	of	ADP
cana-4558	84	19	[	[	X
cana-4558	84	20	b	b	X
cana-4558	84	21	]	]	X
cana-4558	84	22	and	and	CCONJ
cana-4558	84	23	a	a	DET
cana-4558	84	24	standard	standard	ADJ
cana-4558	84	25	error	error	NOUN
cana-4558	84	26	mean	mean	NOUN
cana-4558	84	27	of	of	ADP
cana-4558	84	28	[	[	X
cana-4558	84	29	c	c	X
cana-4558	84	30	]	]	X
cana-4558	84	31	,	,	PUNCT
cana-4558	84	32	implying	imply	VERB
cana-4558	84	33	that	that	SCONJ
cana-4558	84	34	there	there	PRON
cana-4558	84	35	is	be	VERB
cana-4558	84	36	significantly	significantly	ADV
cana-4558	84	37	more	more	ADV
cana-4558	84	38	significant	significant	ADJ
cana-4558	84	39	results	result	NOUN
cana-4558	84	40	.	.	PUNCT
cana-4558	85	1	the	the	DET
cana-4558	85	2	performance	performance	NOUN
cana-4558	85	3	of	of	ADP
cana-4558	85	4	yolov4	yolov4	PROPN
cana-4558	85	5	and	and	CCONJ
cana-4558	85	6	cnn	cnn	PROPN
cana-4558	85	7	models	model	NOUN
cana-4558	85	8	over	over	ADP
cana-4558	85	9	the	the	DET
cana-4558	85	10	varying	vary	VERB
cana-4558	85	11	sample	sample	NOUN
cana-4558	85	12	size	size	NOUN
cana-4558	85	13	helps	help	VERB
cana-4558	85	14	in	in	ADP
cana-4558	85	15	understanding	understand	VERB
cana-4558	85	16	the	the	DET
cana-4558	85	17	models	model	NOUN
cana-4558	85	18	'	'	PART
cana-4558	85	19	consistency	consistency	NOUN
cana-4558	85	20	across	across	ADP
cana-4558	85	21	the	the	DET
cana-4558	85	22	different	different	ADJ
cana-4558	85	23	datasets	dataset	NOUN
cana-4558	85	24	in	in	ADP
cana-4558	85	25	the	the	DET
cana-4558	85	26	context	context	NOUN
cana-4558	85	27	of	of	ADP
cana-4558	85	28	leaf	leaf	NOUN
cana-4558	85	29	disease	disease	NOUN
cana-4558	85	30	detection	detection	NOUN
cana-4558	85	31	.	.	PUNCT
cana-4558	86	1	the	the	DET
cana-4558	86	2	data	datum	NOUN
cana-4558	86	3	supports	support	VERB
cana-4558	86	4	the	the	DET
cana-4558	86	5	view	view	NOUN
cana-4558	86	6	that	that	SCONJ
cana-4558	86	7	yolov4	yolov4	PROPN
cana-4558	86	8	shows	show	VERB
cana-4558	86	9	consistent	consistent	ADJ
cana-4558	86	10	higher	high	ADJ
cana-4558	86	11	accuracy	accuracy	NOUN
cana-4558	86	12	compared	compare	VERB
cana-4558	86	13	to	to	ADP
cana-4558	86	14	cnn	cnn	PROPN
cana-4558	86	15	for	for	ADP
cana-4558	86	16	any	any	DET
cana-4558	86	17	different	different	ADJ
cana-4558	86	18	group	group	NOUN
cana-4558	86	19	size	size	NOUN
cana-4558	86	20	.	.	PUNCT
cana-4558	87	1	table	table	NOUN
cana-4558	87	2	2	2	NUM
cana-4558	87	3	the	the	DET
cana-4558	87	4	leaf	leaf	NOUN
cana-4558	87	5	disease	disease	NOUN
cana-4558	87	6	detection	detection	NOUN
cana-4558	87	7	accuracy	accuracy	NOUN
cana-4558	87	8	of	of	ADP
cana-4558	87	9	the	the	DET
cana-4558	87	10	comparison	comparison	NOUN
cana-4558	87	11	between	between	ADP
cana-4558	87	12	yolov4	yolov4	NOUN
cana-4558	87	13	model	model	NOUN
cana-4558	87	14	and	and	CCONJ
cana-4558	87	15	cnn	cnn	PROPN
cana-4558	87	16	models	model	NOUN
cana-4558	87	17	for	for	ADP
cana-4558	87	18	precision	precision	NOUN
cana-4558	87	19	agriculture	agriculture	NOUN
cana-4558	87	20	was	be	AUX
cana-4558	87	21	yolov4	yolov4	NOUN
cana-4558	87	22	mean	mean	NOUN
cana-4558	87	23	accuracy	accuracy	NOUN
cana-4558	87	24	with	with	ADP
cana-4558	87	25	a	a	DET
cana-4558	87	26	standard	standard	ADJ
cana-4558	87	27	deviation	deviation	NOUN
cana-4558	87	28	and	and	CCONJ
cana-4558	87	29	a	a	DET
cana-4558	87	30	standard	standard	ADJ
cana-4558	87	31	error	error	NOUN
cana-4558	87	32	mean	mean	NOUN
cana-4558	87	33	of	of	ADP
cana-4558	87	34	[	[	X
cana-4558	87	35	x	x	X
cana-4558	87	36	]	]	X
cana-4558	87	37	.	.	PUNCT
cana-4558	88	1	g	g	PROPN
cana-4558	88	2	ro	ro	PROPN
cana-4558	88	3	u	u	PROPN
cana-4558	88	4	p	p	PROPN
cana-4558	88	5	n	n	ADV
cana-4558	88	6	m	m	NOUN
cana-4558	88	7	ea	ea	NOUN
cana-4558	88	8	n	n	CCONJ
cana-4558	88	9	a	a	DET
cana-4558	88	10	cc	cc	X
cana-4558	88	11	u	u	NOUN
cana-4558	88	12	ra	ra	PROPN
cana-4558	88	13	c	c	NOUN
cana-4558	88	14	y	y	PROPN
cana-4558	88	15	(	(	PUNCT
cana-4558	88	16	%	%	NOUN
cana-4558	88	17	)	)	PUNCT
cana-4558	88	18	s	s	VERB
cana-4558	88	19	td	td	NOUN
cana-4558	88	20	.	.	PUNCT
cana-4558	89	1	d	d	X
cana-4558	89	2	ev	ev	X
cana-4558	89	3	ia	ia	PROPN
cana-4558	89	4	ti	ti	PROPN
cana-4558	89	5	o	o	PROPN
cana-4558	89	6	n	n	PROPN
cana-4558	89	7	s	s	NOUN
cana-4558	89	8	td	td	NOUN
cana-4558	89	9	.	.	PUNCT
cana-4558	90	1	e	e	X
cana-4558	90	2	rr	rr	NOUN
cana-4558	91	1	o	o	NOUN
cana-4558	91	2	r	r	NOUN
cana-4558	91	3	m	m	VERB
cana-4558	91	4	ea	ea	NOUN
cana-4558	91	5	n	n	NUM
cana-4558	91	6	yolov4	yolov4	NOUN
cana-4558	91	7	30	30	NUM
cana-4558	91	8	91.4	91.4	NUM
cana-4558	91	9	0.052	0.052	NUM
cana-4558	91	10	0.009	0.009	NUM
cana-4558	91	11	yolov4	yolov4	NOUN
cana-4558	91	12	60	60	NUM
cana-4558	91	13	90.8	90.8	NUM
cana-4558	91	14	0.055	0.055	NUM
cana-4558	91	15	0.007	0.007	NUM
cana-4558	91	16	yolov4	yolov4	NOUN
cana-4558	92	1	90	90	NUM
cana-4558	92	2	92.1	92.1	NUM
cana-4558	92	3	0.053	0.053	NUM
cana-4558	92	4	0.008	0.008	NUM
cana-4558	92	5	yolov4	yolov4	NOUN
cana-4558	92	6	120	120	NUM
cana-4558	92	7	91.7	91.7	NUM
cana-4558	92	8	0.050	0.050	NUM
cana-4558	92	9	0.007	0.007	NUM
cana-4558	92	10	yolov4	yolov4	NOUN
cana-4558	92	11	150	150	NUM
cana-4558	92	12	91.5	91.5	NUM
cana-4558	92	13	0.051	0.051	NUM
cana-4558	92	14	0.007	0.007	NUM
cana-4558	92	15	cnn	cnn	PROPN
cana-4558	92	16	30	30	NUM
cana-4558	92	17	80.2	80.2	NUM
cana-4558	92	18	0.062	0.062	NUM
cana-4558	92	19	0.011	0.011	NUM
cana-4558	92	20	cnn	cnn	PROPN
cana-4558	92	21	60	60	NUM
cana-4558	92	22	78.9	78.9	NUM
cana-4558	92	23	0.060	0.060	NUM
cana-4558	92	24	0.008	0.008	NUM
cana-4558	92	25	cnn	cnn	NOUN
cana-4558	92	26	90	90	NUM
cana-4558	92	27	79.5	79.5	NUM
cana-4558	92	28	0.058	0.058	NUM
cana-4558	92	29	0.007	0.007	NUM
cana-4558	92	30	cnn	cnn	PROPN
cana-4558	92	31	120	120	NUM
cana-4558	92	32	79.2	79.2	NUM
cana-4558	92	33	0.059	0.059	NUM
cana-4558	92	34	0.008	0.008	NUM
cana-4558	92	35	cnn	cnn	PROPN
cana-4558	92	36	150	150	NUM
cana-4558	92	37	80.2	80.2	NUM
cana-4558	92	38	0.061	0.061	NUM
cana-4558	92	39	0.009	0.009	NUM
cana-4558	92	40	the	the	DET
cana-4558	92	41	fig	fig	NOUN
cana-4558	92	42	.	.	PUNCT
cana-4558	93	1	2	2	X
cana-4558	93	2	.	.	X
cana-4558	93	3	shows	show	VERB
cana-4558	93	4	the	the	DET
cana-4558	93	5	comparison	comparison	NOUN
cana-4558	93	6	of	of	ADP
cana-4558	93	7	yolov4	yolov4	PROPN
cana-4558	93	8	and	and	CCONJ
cana-4558	93	9	cnn	cnn	PROPN
cana-4558	93	10	under	under	ADP
cana-4558	93	11	various	various	ADJ
cana-4558	93	12	test	test	NOUN
cana-4558	93	13	scenarios	scenario	NOUN
cana-4558	93	14	,	,	PUNCT
cana-4558	93	15	determining	determine	VERB
cana-4558	93	16	yolov4	yolov4	PROPN
cana-4558	93	17	's	's	PART
cana-4558	93	18	increased	increase	VERB
cana-4558	93	19	accuracy	accuracy	NOUN
cana-4558	93	20	in	in	ADP
cana-4558	93	21	plant	plant	NOUN
cana-4558	93	22	disease	disease	NOUN
cana-4558	93	23	detection	detection	NOUN
cana-4558	93	24	.	.	PUNCT
cana-4558	94	1	yolov4	yolov4	PROPN
cana-4558	94	2	is	be	AUX
cana-4558	94	3	unique	unique	ADJ
cana-4558	94	4	because	because	SCONJ
cana-4558	94	5	of	of	ADP
cana-4558	94	6	its	its	PRON
cana-4558	94	7	real	real	ADJ
cana-4558	94	8	-	-	PUNCT
cana-4558	94	9	time	time	NOUN
cana-4558	94	10	multi	multi	ADJ
cana-4558	94	11	-	-	ADJ
cana-4558	94	12	object	object	ADJ
cana-4558	94	13	detection	detection	NOUN
cana-4558	94	14	and	and	CCONJ
cana-4558	94	15	performance	performance	NOUN
cana-4558	94	16	with	with	ADP
cana-4558	94	17	difficult	difficult	ADJ
cana-4558	94	18	backgrounds	background	NOUN
cana-4558	94	19	.	.	PUNCT
cana-4558	95	1	while	while	SCONJ
cana-4558	95	2	cnn	cnn	PROPN
cana-4558	95	3	achieves	achieve	VERB
cana-4558	95	4	a	a	DET
cana-4558	95	5	maximum	maximum	NOUN
cana-4558	95	6	of	of	ADP
cana-4558	95	7	80	80	NUM
cana-4558	95	8	%	%	NOUN
cana-4558	95	9	accuracy	accuracy	NOUN
cana-4558	95	10	,	,	PUNCT
cana-4558	95	11	yolov4	yolov4	PROPN
cana-4558	95	12	achieves	achieve	VERB
cana-4558	95	13	92	92	NUM
cana-4558	95	14	%	%	NOUN
cana-4558	95	15	and	and	CCONJ
cana-4558	95	16	maintains	maintain	VERB
cana-4558	95	17	83	83	NUM
cana-4558	95	18	%	%	NOUN
cana-4558	95	19	even	even	ADV
cana-4558	95	20	in	in	ADP
cana-4558	95	21	poor	poor	ADJ
cana-4558	95	22	conditions	condition	NOUN
cana-4558	95	23	,	,	PUNCT
cana-4558	95	24	surpassing	surpass	VERB
cana-4558	95	25	cnn	cnn	PROPN
cana-4558	95	26	's	's	PART
cana-4558	95	27	lowest	low	ADJ
cana-4558	95	28	accuracy	accuracy	NOUN
cana-4558	95	29	of	of	ADP
cana-4558	95	30	72	72	NUM
cana-4558	95	31	%	%	NOUN
cana-4558	95	32	.	.	PUNCT
cana-4558	96	1	this	this	DET
cana-4558	96	2	stability	stability	NOUN
cana-4558	96	3	makes	make	VERB
cana-4558	96	4	yolov4	yolov4	PRON
cana-4558	96	5	a	a	DET
cana-4558	96	6	more	more	ADV
cana-4558	96	7	scalable	scalable	ADJ
cana-4558	96	8	and	and	CCONJ
cana-4558	96	9	reliable	reliable	ADJ
cana-4558	96	10	option	option	NOUN
cana-4558	96	11	for	for	ADP
cana-4558	96	12	plant	plant	NOUN
cana-4558	96	13	disease	disease	NOUN
cana-4558	96	14	detection	detection	NOUN
cana-4558	96	15	.	.	PUNCT
cana-4558	97	1	its	its	PRON
cana-4558	97	2	efficiency	efficiency	NOUN
cana-4558	97	3	in	in	ADP
cana-4558	97	4	image	image	NOUN
cana-4558	97	5	processing	processing	NOUN
cana-4558	97	6	makes	make	VERB
cana-4558	97	7	it	it	PRON
cana-4558	97	8	an	an	DET
cana-4558	97	9	ideal	ideal	ADJ
cana-4558	97	10	option	option	NOUN
cana-4558	97	11	for	for	ADP
cana-4558	97	12	real	real	ADJ
cana-4558	97	13	-	-	PUNCT
cana-4558	97	14	time	time	NOUN
cana-4558	97	15	agriculture	agriculture	NOUN
cana-4558	97	16	applications	application	NOUN
cana-4558	97	17	.	.	PUNCT
cana-4558	98	1	fig	fig	NOUN
cana-4558	98	2	.	.	PUNCT
cana-4558	99	1	2	2	X
cana-4558	99	2	.	.	X
cana-4558	99	3	the	the	DET
cana-4558	99	4	graph	graph	NOUN
cana-4558	99	5	compares	compare	VERB
cana-4558	99	6	yolov4	yolov4	PROPN
cana-4558	99	7	and	and	CCONJ
cana-4558	99	8	cnn	cnn	PROPN
cana-4558	99	9	under	under	ADP
cana-4558	99	10	various	various	ADJ
cana-4558	99	11	test	test	NOUN
cana-4558	99	12	scenarios	scenario	NOUN
cana-4558	99	13	,	,	PUNCT
cana-4558	99	14	determining	determine	VERB
cana-4558	99	15	yolov4	yolov4	PROPN
cana-4558	99	16	's	's	PART
cana-4558	99	17	increased	increase	VERB
cana-4558	99	18	accuracy	accuracy	NOUN
cana-4558	99	19	in	in	ADP
cana-4558	99	20	plant	plant	NOUN
cana-4558	99	21	disease	disease	NOUN
cana-4558	99	22	detection	detection	NOUN
cana-4558	99	23	.	.	PUNCT
cana-4558	100	1	yolov4	yolov4	PROPN
cana-4558	100	2	is	be	AUX
cana-4558	100	3	unique	unique	ADJ
cana-4558	100	4	because	because	SCONJ
cana-4558	100	5	of	of	ADP
cana-4558	100	6	its	its	PRON
cana-4558	100	7	real	real	ADJ
cana-4558	100	8	-	-	PUNCT
cana-4558	100	9	time	time	NOUN
cana-4558	100	10	multi	multi	ADJ
cana-4558	100	11	-	-	ADJ
cana-4558	100	12	object	object	ADJ
cana-4558	100	13	detection	detection	NOUN
cana-4558	100	14	and	and	CCONJ
cana-4558	100	15	performance	performance	NOUN
cana-4558	100	16	with	with	ADP
cana-4558	100	17	difficult	difficult	ADJ
cana-4558	100	18	backgrounds	background	NOUN
cana-4558	100	19	.	.	PUNCT
cana-4558	101	1	communications	communication	NOUN
cana-4558	101	2	on	on	ADP
cana-4558	101	3	applied	apply	VERB
cana-4558	101	4	nonlinear	nonlinear	ADJ
cana-4558	101	5	analysis	analysis	NOUN
cana-4558	101	6	issn	issn	NOUN
cana-4558	101	7	:	:	PUNCT
cana-4558	101	8	1074	1074	NUM
cana-4558	101	9	-	-	PUNCT
cana-4558	101	10	133x	133x	NUM
cana-4558	101	11	vol	vol	NOUN
cana-4558	101	12	32	32	NUM
cana-4558	101	13	no	no	NOUN
cana-4558	101	14	.	.	PUNCT
cana-4558	102	1	9s	9s	NUM
cana-4558	102	2	(	(	PUNCT
cana-4558	102	3	2025	2025	NUM
cana-4558	102	4	)	)	PUNCT
cana-4558	102	5	2536	2536	NUM
cana-4558	102	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	102	7	the	the	DET
cana-4558	102	8	fig	fig	NOUN
cana-4558	102	9	.	.	PUNCT
cana-4558	103	1	3	3	X
cana-4558	103	2	.	.	X
cana-4558	103	3	shows	show	VERB
cana-4558	103	4	the	the	DET
cana-4558	103	5	comparison	comparison	NOUN
cana-4558	103	6	of	of	ADP
cana-4558	103	7	yolov4	yolov4	PROPN
cana-4558	103	8	and	and	CCONJ
cana-4558	103	9	cnn	cnn	PROPN
cana-4558	103	10	,	,	PUNCT
cana-4558	103	11	proving	prove	VERB
cana-4558	103	12	yolov4	yolov4	PROPN
cana-4558	103	13	’s	’s	PART
cana-4558	103	14	superior	superior	ADJ
cana-4558	103	15	in	in	ADP
cana-4558	103	16	detecting	detect	VERB
cana-4558	103	17	plant	plant	NOUN
cana-4558	103	18	diseases	disease	NOUN
cana-4558	103	19	.	.	PUNCT
cana-4558	104	1	yolov4	yolov4	NOUN
cana-4558	104	2	excels	excel	VERB
cana-4558	104	3	due	due	ADP
cana-4558	104	4	to	to	ADP
cana-4558	104	5	its	its	PRON
cana-4558	104	6	real	real	ADJ
cana-4558	104	7	-	-	PUNCT
cana-4558	104	8	time	time	NOUN
cana-4558	104	9	multi	multi	ADJ
cana-4558	104	10	-	-	ADJ
cana-4558	104	11	object	object	ADJ
cana-4558	104	12	detection	detection	NOUN
cana-4558	104	13	and	and	CCONJ
cana-4558	104	14	ability	ability	NOUN
cana-4558	104	15	to	to	PART
cana-4558	104	16	handle	handle	VERB
cana-4558	104	17	complex	complex	ADJ
cana-4558	104	18	backgrounds	background	NOUN
cana-4558	104	19	efficiently	efficiently	ADV
cana-4558	104	20	.	.	PUNCT
cana-4558	105	1	while	while	SCONJ
cana-4558	105	2	cnn	cnn	PROPN
cana-4558	105	3	reaches	reach	VERB
cana-4558	105	4	a	a	DET
cana-4558	105	5	maximum	maximum	ADJ
cana-4558	105	6	accuracy	accuracy	NOUN
cana-4558	105	7	of	of	ADP
cana-4558	105	8	80	80	NUM
cana-4558	105	9	%	%	NOUN
cana-4558	105	10	,	,	PUNCT
cana-4558	105	11	yolov4	yolov4	PROPN
cana-4558	105	12	achieves	achieve	VERB
cana-4558	105	13	92	92	NUM
cana-4558	105	14	%	%	NOUN
cana-4558	105	15	and	and	CCONJ
cana-4558	105	16	maintains	maintain	VERB
cana-4558	105	17	83	83	NUM
cana-4558	105	18	%	%	NOUN
cana-4558	105	19	even	even	ADV
cana-4558	105	20	in	in	ADP
cana-4558	105	21	challenging	challenging	ADJ
cana-4558	105	22	conditions	condition	NOUN
cana-4558	105	23	,	,	PUNCT
cana-4558	105	24	outperforming	outperform	VERB
cana-4558	105	25	cnn	cnn	PROPN
cana-4558	105	26	’s	’s	PART
cana-4558	105	27	lowest	low	ADJ
cana-4558	105	28	accuracy	accuracy	NOUN
cana-4558	105	29	of	of	ADP
cana-4558	105	30	72	72	NUM
cana-4558	105	31	%	%	NOUN
cana-4558	105	32	.	.	PUNCT
cana-4558	106	1	the	the	DET
cana-4558	106	2	outcomes	outcome	NOUN
cana-4558	106	3	show	show	VERB
cana-4558	106	4	the	the	DET
cana-4558	106	5	great	great	ADJ
cana-4558	106	6	practical	practical	ADJ
cana-4558	106	7	value	value	NOUN
cana-4558	106	8	of	of	ADP
cana-4558	106	9	yolov4	yolov4	PROPN
cana-4558	106	10	,	,	PUNCT
cana-4558	106	11	which	which	PRON
cana-4558	106	12	guarantees	guarantee	VERB
cana-4558	106	13	faster	fast	ADV
cana-4558	106	14	and	and	CCONJ
cana-4558	106	15	more	more	ADV
cana-4558	106	16	precise	precise	ADJ
cana-4558	106	17	illness	illness	NOUN
cana-4558	106	18	diagnosis	diagnosis	NOUN
cana-4558	106	19	in	in	ADP
cana-4558	106	20	extensive	extensive	ADJ
cana-4558	106	21	agricultural	agricultural	ADJ
cana-4558	106	22	systems	system	NOUN
cana-4558	106	23	.	.	PUNCT
cana-4558	107	1	fig	fig	NOUN
cana-4558	107	2	.	.	PUNCT
cana-4558	108	1	3	3	X
cana-4558	108	2	.	.	PUNCT
cana-4558	108	3	the	the	DET
cana-4558	108	4	comparison	comparison	NOUN
cana-4558	108	5	of	of	ADP
cana-4558	108	6	yolov4	yolov4	PROPN
cana-4558	108	7	and	and	CCONJ
cana-4558	108	8	cnn	cnn	PROPN
cana-4558	108	9	,	,	PUNCT
cana-4558	108	10	proving	prove	VERB
cana-4558	108	11	yolov4	yolov4	PROPN
cana-4558	108	12	’s	’s	PART
cana-4558	108	13	superior	superior	ADJ
cana-4558	108	14	in	in	ADP
cana-4558	108	15	detecting	detect	VERB
cana-4558	108	16	plant	plant	NOUN
cana-4558	108	17	diseases	disease	NOUN
cana-4558	108	18	.	.	PUNCT
cana-4558	109	1	yolov4	yolov4	NOUN
cana-4558	109	2	excels	excel	VERB
cana-4558	109	3	due	due	ADP
cana-4558	109	4	to	to	ADP
cana-4558	109	5	its	its	PRON
cana-4558	109	6	real	real	ADJ
cana-4558	109	7	-	-	PUNCT
cana-4558	109	8	time	time	NOUN
cana-4558	109	9	multi	multi	ADJ
cana-4558	109	10	-	-	ADJ
cana-4558	109	11	object	object	ADJ
cana-4558	109	12	detection	detection	NOUN
cana-4558	109	13	and	and	CCONJ
cana-4558	109	14	ability	ability	NOUN
cana-4558	109	15	to	to	PART
cana-4558	109	16	handle	handle	VERB
cana-4558	109	17	complex	complex	ADJ
cana-4558	109	18	backgrounds	background	NOUN
cana-4558	109	19	efficiently	efficiently	ADV
cana-4558	109	20	.	.	PUNCT
cana-4558	110	1	while	while	SCONJ
cana-4558	110	2	cnn	cnn	PROPN
cana-4558	110	3	reaches	reach	VERB
cana-4558	110	4	a	a	DET
cana-4558	110	5	maximum	maximum	ADJ
cana-4558	110	6	accuracy	accuracy	NOUN
cana-4558	110	7	of	of	ADP
cana-4558	110	8	80	80	NUM
cana-4558	110	9	%	%	NOUN
cana-4558	110	10	,	,	PUNCT
cana-4558	110	11	yolov4	yolov4	PROPN
cana-4558	110	12	achieves	achieve	VERB
cana-4558	110	13	92	92	NUM
cana-4558	110	14	%	%	NOUN
cana-4558	110	15	and	and	CCONJ
cana-4558	110	16	maintains	maintain	VERB
cana-4558	110	17	83	83	NUM
cana-4558	110	18	%	%	NOUN
cana-4558	110	19	even	even	ADV
cana-4558	110	20	in	in	ADP
cana-4558	110	21	challenging	challenging	ADJ
cana-4558	110	22	conditions	condition	NOUN
cana-4558	110	23	,	,	PUNCT
cana-4558	110	24	outperforming	outperform	VERB
cana-4558	110	25	cnn	cnn	PROPN
cana-4558	110	26	’s	’s	PART
cana-4558	110	27	lowest	low	ADJ
cana-4558	110	28	accuracy	accuracy	NOUN
cana-4558	110	29	of	of	ADP
cana-4558	110	30	72	72	NUM
cana-4558	110	31	%	%	NOUN
cana-4558	110	32	.	.	PUNCT
cana-4558	111	1	the	the	DET
cana-4558	111	2	outcomes	outcome	NOUN
cana-4558	111	3	show	show	VERB
cana-4558	111	4	the	the	DET
cana-4558	111	5	great	great	ADJ
cana-4558	111	6	practical	practical	ADJ
cana-4558	111	7	value	value	NOUN
cana-4558	111	8	of	of	ADP
cana-4558	111	9	yolov4	yolov4	PROPN
cana-4558	111	10	,	,	PUNCT
cana-4558	111	11	which	which	PRON
cana-4558	111	12	guarantees	guarantee	VERB
cana-4558	111	13	faster	fast	ADV
cana-4558	111	14	and	and	CCONJ
cana-4558	111	15	more	more	ADV
cana-4558	111	16	precise	precise	ADJ
cana-4558	111	17	illness	illness	NOUN
cana-4558	111	18	diagnosis	diagnosis	NOUN
cana-4558	111	19	in	in	ADP
cana-4558	111	20	extensive	extensive	ADJ
cana-4558	111	21	agricultural	agricultural	ADJ
cana-4558	111	22	systems	system	NOUN
cana-4558	111	23	.	.	PUNCT
cana-4558	112	1	fig	fig	NOUN
cana-4558	112	2	.	.	PUNCT
cana-4558	113	1	4	4	X
cana-4558	113	2	.	.	X
cana-4558	113	3	shows	show	VERB
cana-4558	113	4	the	the	DET
cana-4558	113	5	precision	precision	NOUN
cana-4558	113	6	comparison	comparison	NOUN
cana-4558	113	7	between	between	ADP
cana-4558	113	8	yolov4	yolov4	PROPN
cana-4558	113	9	and	and	CCONJ
cana-4558	113	10	cnn	cnn	PROPN
cana-4558	113	11	in	in	ADP
cana-4558	113	12	leaf	leaf	NOUN
cana-4558	113	13	disease	disease	NOUN
cana-4558	113	14	detection	detection	NOUN
cana-4558	113	15	.	.	PUNCT
cana-4558	114	1	yolov4	yolov4	PROPN
cana-4558	114	2	demonstrates	demonstrate	VERB
cana-4558	114	3	superior	superior	ADJ
cana-4558	114	4	performance	performance	NOUN
cana-4558	114	5	,	,	PUNCT
cana-4558	114	6	achieving	achieve	VERB
cana-4558	114	7	an	an	DET
cana-4558	114	8	accuracy	accuracy	NOUN
cana-4558	114	9	of	of	ADP
cana-4558	114	10	88	88	NUM
cana-4558	114	11	%	%	NOUN
cana-4558	114	12	,	,	PUNCT
cana-4558	114	13	whereas	whereas	SCONJ
cana-4558	114	14	cnn	cnn	PROPN
cana-4558	114	15	reaches	reach	VERB
cana-4558	114	16	73	73	NUM
cana-4558	114	17	%	%	NOUN
cana-4558	114	18	.	.	PUNCT
cana-4558	115	1	the	the	DET
cana-4558	115	2	significant	significant	ADJ
cana-4558	115	3	difference	difference	NOUN
cana-4558	115	4	highlights	highlight	NOUN
cana-4558	115	5	yolov4	yolov4	PROPN
cana-4558	115	6	’s	’s	PART
cana-4558	115	7	advanced	advanced	ADJ
cana-4558	115	8	feature	feature	NOUN
cana-4558	115	9	extraction	extraction	NOUN
cana-4558	115	10	capabilities	capability	NOUN
cana-4558	115	11	and	and	CCONJ
cana-4558	115	12	real	real	ADJ
cana-4558	115	13	-	-	PUNCT
cana-4558	115	14	time	time	NOUN
cana-4558	115	15	detection	detection	NOUN
cana-4558	115	16	efficiency	efficiency	NOUN
cana-4558	115	17	.	.	PUNCT
cana-4558	116	1	the	the	DET
cana-4558	116	2	higher	high	ADJ
cana-4558	116	3	accuracy	accuracy	NOUN
cana-4558	116	4	of	of	ADP
cana-4558	116	5	yolov4	yolov4	PROPN
cana-4558	116	6	suggests	suggest	VERB
cana-4558	116	7	its	its	PRON
cana-4558	116	8	robustness	robustness	NOUN
cana-4558	116	9	in	in	ADP
cana-4558	116	10	handling	handle	VERB
cana-4558	116	11	complex	complex	ADJ
cana-4558	116	12	patterns	pattern	NOUN
cana-4558	116	13	and	and	CCONJ
cana-4558	116	14	variations	variation	NOUN
cana-4558	116	15	in	in	ADP
cana-4558	116	16	leaf	leaf	NOUN
cana-4558	116	17	images	image	NOUN
cana-4558	116	18	,	,	PUNCT
cana-4558	116	19	making	make	VERB
cana-4558	116	20	it	it	PRON
cana-4558	116	21	a	a	DET
cana-4558	116	22	preferable	preferable	ADJ
cana-4558	116	23	choice	choice	NOUN
cana-4558	116	24	over	over	ADP
cana-4558	116	25	cnn	cnn	PROPN
cana-4558	116	26	for	for	ADP
cana-4558	116	27	precision	precision	NOUN
cana-4558	116	28	agriculture	agriculture	NOUN
cana-4558	116	29	applications	application	NOUN
cana-4558	116	30	.	.	PUNCT
cana-4558	117	1	fig	fig	NOUN
cana-4558	117	2	.	.	PUNCT
cana-4558	118	1	4	4	X
cana-4558	118	2	.	.	X
cana-4558	118	3	the	the	DET
cana-4558	118	4	comparison	comparison	NOUN
cana-4558	118	5	between	between	ADP
cana-4558	118	6	yolov4	yolov4	PROPN
cana-4558	118	7	and	and	CCONJ
cana-4558	118	8	cnn	cnn	PROPN
cana-4558	118	9	in	in	ADP
cana-4558	118	10	leaf	leaf	NOUN
cana-4558	118	11	disease	disease	NOUN
cana-4558	118	12	detection	detection	NOUN
cana-4558	118	13	.	.	PUNCT
cana-4558	119	1	yolov4	yolov4	PROPN
cana-4558	119	2	demonstrates	demonstrate	VERB
cana-4558	119	3	superior	superior	ADJ
cana-4558	119	4	performance	performance	NOUN
cana-4558	119	5	,	,	PUNCT
cana-4558	119	6	achieving	achieve	VERB
cana-4558	119	7	an	an	DET
cana-4558	119	8	accuracy	accuracy	NOUN
cana-4558	119	9	of	of	ADP
cana-4558	119	10	88	88	NUM
cana-4558	119	11	%	%	NOUN
cana-4558	119	12	,	,	PUNCT
cana-4558	119	13	whereas	whereas	SCONJ
cana-4558	119	14	cnn	cnn	PROPN
cana-4558	119	15	reaches	reach	VERB
cana-4558	119	16	73	73	NUM
cana-4558	119	17	%	%	NOUN
cana-4558	119	18	.	.	PUNCT
cana-4558	120	1	communications	communication	NOUN
cana-4558	120	2	on	on	ADP
cana-4558	120	3	applied	apply	VERB
cana-4558	120	4	nonlinear	nonlinear	ADJ
cana-4558	120	5	analysis	analysis	NOUN
cana-4558	120	6	issn	issn	NOUN
cana-4558	120	7	:	:	PUNCT
cana-4558	120	8	1074	1074	NUM
cana-4558	120	9	-	-	PUNCT
cana-4558	120	10	133x	133x	NUM
cana-4558	120	11	vol	vol	NOUN
cana-4558	120	12	32	32	NUM
cana-4558	120	13	no	no	NOUN
cana-4558	120	14	.	.	PUNCT
cana-4558	121	1	9s	9s	NUM
cana-4558	121	2	(	(	PUNCT
cana-4558	121	3	2025	2025	NUM
cana-4558	121	4	)	)	PUNCT
cana-4558	121	5	2537	2537	NUM
cana-4558	121	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	121	7	fig	fig	NOUN
cana-4558	121	8	.	.	PUNCT
cana-4558	122	1	5	5	NUM
cana-4558	122	2	.	.	X
cana-4558	122	3	shows	show	VERB
cana-4558	122	4	the	the	DET
cana-4558	122	5	comparison	comparison	NOUN
cana-4558	122	6	between	between	ADP
cana-4558	122	7	yolov4	yolov4	PROPN
cana-4558	122	8	and	and	CCONJ
cana-4558	122	9	cnn	cnn	PROPN
cana-4558	122	10	is	be	AUX
cana-4558	122	11	depicted	depict	VERB
cana-4558	122	12	in	in	ADP
cana-4558	122	13	this	this	DET
cana-4558	122	14	diagram	diagram	NOUN
cana-4558	122	15	.	.	PUNCT
cana-4558	123	1	yolov4	yolov4	PROPN
cana-4558	123	2	achieves	achieve	VERB
cana-4558	123	3	a	a	DET
cana-4558	123	4	higher	high	ADJ
cana-4558	123	5	accuracy	accuracy	NOUN
cana-4558	123	6	of	of	ADP
cana-4558	123	7	87	87	NUM
cana-4558	123	8	%	%	NOUN
cana-4558	123	9	,	,	PUNCT
cana-4558	123	10	whereas	whereas	SCONJ
cana-4558	123	11	cnn	cnn	PROPN
cana-4558	123	12	attains	attain	VERB
cana-4558	123	13	75	75	NUM
cana-4558	123	14	%	%	NOUN
cana-4558	123	15	,	,	PUNCT
cana-4558	123	16	indicating	indicate	VERB
cana-4558	123	17	a	a	DET
cana-4558	123	18	notable	notable	ADJ
cana-4558	123	19	difference	difference	NOUN
cana-4558	123	20	in	in	ADP
cana-4558	123	21	performance	performance	NOUN
cana-4558	123	22	like	like	ADP
cana-4558	123	23	plant	plant	NOUN
cana-4558	123	24	disease	disease	NOUN
cana-4558	123	25	detection	detection	NOUN
cana-4558	123	26	.	.	PUNCT
cana-4558	124	1	the	the	DET
cana-4558	124	2	results	result	NOUN
cana-4558	124	3	highlight	highlight	VERB
cana-4558	124	4	yolov4	yolov4	PROPN
cana-4558	124	5	's	's	PART
cana-4558	124	6	ability	ability	NOUN
cana-4558	124	7	to	to	PART
cana-4558	124	8	provide	provide	VERB
cana-4558	124	9	more	more	ADV
cana-4558	124	10	reliable	reliable	ADJ
cana-4558	124	11	and	and	CCONJ
cana-4558	124	12	consistent	consistent	ADJ
cana-4558	124	13	detections	detection	NOUN
cana-4558	124	14	,	,	PUNCT
cana-4558	124	15	making	make	VERB
cana-4558	124	16	it	it	PRON
cana-4558	124	17	a	a	DET
cana-4558	124	18	superior	superior	ADJ
cana-4558	124	19	model	model	NOUN
cana-4558	124	20	for	for	ADP
cana-4558	124	21	plant	plant	NOUN
cana-4558	124	22	disease	disease	NOUN
cana-4558	124	23	identification	identification	NOUN
cana-4558	124	24	.	.	PUNCT
cana-4558	125	1	in	in	ADP
cana-4558	125	2	contrast	contrast	NOUN
cana-4558	125	3	,	,	PUNCT
cana-4558	125	4	cnn	cnn	PROPN
cana-4558	125	5	,	,	PUNCT
cana-4558	125	6	though	though	SCONJ
cana-4558	125	7	effective	effective	ADJ
cana-4558	125	8	,	,	PUNCT
cana-4558	125	9	exhibits	exhibit	VERB
cana-4558	125	10	comparatively	comparatively	ADV
cana-4558	125	11	lower	low	ADJ
cana-4558	125	12	accuracy	accuracy	NOUN
cana-4558	125	13	,	,	PUNCT
cana-4558	125	14	suggesting	suggest	VERB
cana-4558	125	15	limitations	limitation	NOUN
cana-4558	125	16	in	in	ADP
cana-4558	125	17	handling	handle	VERB
cana-4558	125	18	complex	complex	ADJ
cana-4558	125	19	patterns	pattern	NOUN
cana-4558	125	20	.	.	PUNCT
cana-4558	126	1	this	this	DET
cana-4558	126	2	comparison	comparison	NOUN
cana-4558	126	3	demonstrates	demonstrate	VERB
cana-4558	126	4	that	that	SCONJ
cana-4558	126	5	yolov4	yolov4	PROPN
cana-4558	126	6	is	be	AUX
cana-4558	126	7	a	a	DET
cana-4558	126	8	more	more	ADV
cana-4558	126	9	efficient	efficient	ADJ
cana-4558	126	10	and	and	CCONJ
cana-4558	126	11	dependable	dependable	ADJ
cana-4558	126	12	choice	choice	NOUN
cana-4558	126	13	for	for	ADP
cana-4558	126	14	precision	precision	NOUN
cana-4558	126	15	agriculture	agriculture	NOUN
cana-4558	126	16	applications	application	NOUN
cana-4558	126	17	.	.	PUNCT
cana-4558	127	1	fig	fig	NOUN
cana-4558	127	2	.	.	PUNCT
cana-4558	128	1	5	5	X
cana-4558	128	2	.	.	PUNCT
cana-4558	128	3	the	the	DET
cana-4558	128	4	accuracy	accuracy	NOUN
cana-4558	128	5	comparison	comparison	NOUN
cana-4558	128	6	between	between	ADP
cana-4558	128	7	yolov4	yolov4	PROPN
cana-4558	128	8	and	and	CCONJ
cana-4558	128	9	cnn	cnn	PROPN
cana-4558	128	10	is	be	AUX
cana-4558	128	11	depicted	depict	VERB
cana-4558	128	12	in	in	ADP
cana-4558	128	13	this	this	DET
cana-4558	128	14	diagram	diagram	NOUN
cana-4558	128	15	.	.	PUNCT
cana-4558	129	1	yolov4	yolov4	PROPN
cana-4558	129	2	achieves	achieve	VERB
cana-4558	129	3	a	a	DET
cana-4558	129	4	higher	high	ADJ
cana-4558	129	5	accuracy	accuracy	NOUN
cana-4558	129	6	of	of	ADP
cana-4558	129	7	87	87	NUM
cana-4558	129	8	%	%	NOUN
cana-4558	129	9	,	,	PUNCT
cana-4558	129	10	whereas	whereas	SCONJ
cana-4558	129	11	cnn	cnn	PROPN
cana-4558	129	12	attains	attain	VERB
cana-4558	129	13	75	75	NUM
cana-4558	129	14	%	%	NOUN
cana-4558	129	15	,	,	PUNCT
cana-4558	129	16	indicating	indicate	VERB
cana-4558	129	17	a	a	DET
cana-4558	129	18	notable	notable	ADJ
cana-4558	129	19	difference	difference	NOUN
cana-4558	129	20	in	in	ADP
cana-4558	129	21	performance	performance	NOUN
cana-4558	129	22	like	like	ADP
cana-4558	129	23	plant	plant	NOUN
cana-4558	129	24	disease	disease	NOUN
cana-4558	129	25	detection	detection	NOUN
cana-4558	129	26	.	.	PUNCT
cana-4558	130	1	vi	vi	X
cana-4558	130	2	.	.	NOUN
cana-4558	130	3	discussion	discussion	NOUN
cana-4558	130	4	in	in	ADP
cana-4558	130	5	terms	term	NOUN
cana-4558	130	6	of	of	ADP
cana-4558	130	7	accuracy	accuracy	NOUN
cana-4558	130	8	,	,	PUNCT
cana-4558	130	9	precision	precision	NOUN
cana-4558	130	10	,	,	PUNCT
cana-4558	130	11	recall	recall	NOUN
cana-4558	130	12	,	,	PUNCT
cana-4558	130	13	and	and	CCONJ
cana-4558	130	14	processing	processing	NOUN
cana-4558	130	15	time	time	NOUN
cana-4558	130	16	,	,	PUNCT
cana-4558	130	17	the	the	DET
cana-4558	130	18	yolov4	yolov4	NOUN
cana-4558	130	19	-	-	PUNCT
cana-4558	130	20	based	base	VERB
cana-4558	130	21	leaf	leaf	NOUN
cana-4558	130	22	disease	disease	NOUN
cana-4558	130	23	detection	detection	NOUN
cana-4558	130	24	system	system	NOUN
cana-4558	130	25	performed	perform	VERB
cana-4558	130	26	significantly	significantly	ADV
cana-4558	130	27	better	well	ADJ
cana-4558	130	28	than	than	ADP
cana-4558	130	29	traditional	traditional	ADJ
cana-4558	130	30	convolutional	convolutional	ADJ
cana-4558	130	31	neural	neural	ADJ
cana-4558	130	32	networks	network	NOUN
cana-4558	130	33	(	(	PUNCT
cana-4558	130	34	cnns)[18	cnns)[18	PROPN
cana-4558	130	35	]	]	PUNCT
cana-4558	130	36	.	.	PUNCT
cana-4558	131	1	statistical	statistical	ADJ
cana-4558	131	2	analysis	analysis	NOUN
cana-4558	131	3	revealed	reveal	VERB
cana-4558	131	4	that	that	SCONJ
cana-4558	131	5	yolov4	yolov4	PROPN
cana-4558	131	6	achieved	achieve	VERB
cana-4558	131	7	a	a	DET
cana-4558	131	8	mean	mean	ADJ
cana-4558	131	9	accuracy	accuracy	NOUN
cana-4558	131	10	of	of	ADP
cana-4558	131	11	92.5	92.5	NUM
cana-4558	131	12	%	%	NOUN
cana-4558	131	13	,	,	PUNCT
cana-4558	131	14	whereas	whereas	SCONJ
cana-4558	131	15	cnn	cnn	PROPN
cana-4558	131	16	recorded	record	VERB
cana-4558	131	17	85.3	85.3	NUM
cana-4558	131	18	%	%	NOUN
cana-4558	131	19	.	.	PUNCT
cana-4558	132	1	a	a	DET
cana-4558	132	2	t	t	NOUN
cana-4558	132	3	-	-	PUNCT
cana-4558	132	4	test	test	NOUN
cana-4558	132	5	(	(	PUNCT
cana-4558	132	6	p	p	X
cana-4558	132	7	=	=	NOUN
cana-4558	132	8	0.003	0.003	NUM
cana-4558	132	9	)	)	PUNCT
cana-4558	132	10	confirmed	confirm	VERB
cana-4558	132	11	the	the	DET
cana-4558	132	12	statistical	statistical	ADJ
cana-4558	132	13	significance	significance	NOUN
cana-4558	132	14	of	of	ADP
cana-4558	132	15	yolov4	yolov4	PROPN
cana-4558	132	16	’s	’s	PART
cana-4558	132	17	superior	superior	ADJ
cana-4558	132	18	performance	performance	NOUN
cana-4558	132	19	[	[	X
cana-4558	132	20	19],[20	19],[20	X
cana-4558	132	21	]	]	PUNCT
cana-4558	132	22	.	.	PUNCT
cana-4558	133	1	these	these	DET
cana-4558	133	2	findings	finding	NOUN
cana-4558	133	3	highlight	highlight	VERB
cana-4558	133	4	yolov4	yolov4	PROPN
cana-4558	133	5	’s	’s	PART
cana-4558	133	6	robustness	robustness	NOUN
cana-4558	133	7	in	in	ADP
cana-4558	133	8	handling	handle	VERB
cana-4558	133	9	challenges	challenge	NOUN
cana-4558	133	10	such	such	ADJ
cana-4558	133	11	as	as	ADP
cana-4558	133	12	varying	vary	VERB
cana-4558	133	13	lighting	lighting	NOUN
cana-4558	133	14	conditions	condition	NOUN
cana-4558	133	15	,	,	PUNCT
cana-4558	133	16	overlapping	overlap	VERB
cana-4558	133	17	leaves	leave	NOUN
cana-4558	133	18	,	,	PUNCT
cana-4558	133	19	and	and	CCONJ
cana-4558	133	20	complex	complex	ADJ
cana-4558	133	21	disease	disease	NOUN
cana-4558	133	22	patterns	pattern	NOUN
cana-4558	133	23	,	,	PUNCT
cana-4558	133	24	making	make	VERB
cana-4558	133	25	it	it	PRON
cana-4558	133	26	more	more	ADV
cana-4558	133	27	suitable	suitable	ADJ
cana-4558	133	28	for	for	ADP
cana-4558	133	29	real	real	ADJ
cana-4558	133	30	-	-	PUNCT
cana-4558	133	31	time	time	NOUN
cana-4558	133	32	disease	disease	NOUN
cana-4558	133	33	detection	detection	NOUN
cana-4558	133	34	in	in	ADP
cana-4558	133	35	agricultural	agricultural	ADJ
cana-4558	133	36	environments	environment	NOUN
cana-4558	133	37	[	[	X
cana-4558	133	38	21	21	NUM
cana-4558	133	39	]	]	PUNCT
cana-4558	133	40	.	.	PUNCT
cana-4558	134	1	the	the	DET
cana-4558	134	2	yolov4	yolov4	PROPN
cana-4558	134	3	algorithm	algorithm	PROPN
cana-4558	134	4	,	,	PUNCT
cana-4558	134	5	when	when	SCONJ
cana-4558	134	6	combined	combine	VERB
cana-4558	134	7	with	with	ADP
cana-4558	134	8	iot	iot	PROPN
cana-4558	134	9	devices	device	NOUN
cana-4558	134	10	like	like	ADP
cana-4558	134	11	drones	drone	NOUN
cana-4558	134	12	and	and	CCONJ
cana-4558	134	13	smart	smart	ADJ
cana-4558	134	14	sensors	sensor	NOUN
cana-4558	134	15	,	,	PUNCT
cana-4558	134	16	enables	enable	VERB
cana-4558	134	17	autonomous	autonomous	ADJ
cana-4558	134	18	disease	disease	NOUN
cana-4558	134	19	monitoring	monitor	VERB
cana-4558	134	20	over	over	ADP
cana-4558	134	21	large	large	ADJ
cana-4558	134	22	fields	field	NOUN
cana-4558	134	23	,	,	PUNCT
cana-4558	134	24	enabling	enable	VERB
cana-4558	134	25	green	green	ADJ
cana-4558	134	26	precision	precision	NOUN
cana-4558	134	27	agriculture(89.3	agriculture(89.3	NUM
cana-4558	134	28	%	%	NOUN
cana-4558	134	29	)	)	PUNCT
cana-4558	134	30	through	through	ADP
cana-4558	134	31	reduced	reduce	VERB
cana-4558	134	32	crop	crop	NOUN
cana-4558	134	33	loss	loss	NOUN
cana-4558	134	34	and	and	CCONJ
cana-4558	134	35	chemical	chemical	NOUN
cana-4558	134	36	usage	usage	NOUN
cana-4558	134	37	.	.	PUNCT
cana-4558	135	1	real	real	ADJ
cana-4558	135	2	-	-	PUNCT
cana-4558	135	3	time	time	NOUN
cana-4558	135	4	image	image	NOUN
cana-4558	135	5	processing	processing	NOUN
cana-4558	135	6	enables	enable	VERB
cana-4558	135	7	faster	fast	ADJ
cana-4558	135	8	decision	decision	NOUN
cana-4558	135	9	-	-	PUNCT
cana-4558	135	10	making	making	NOUN
cana-4558	135	11	about	about	ADP
cana-4558	135	12	disease	disease	NOUN
cana-4558	135	13	by	by	ADP
cana-4558	135	14	farmers	farmer	NOUN
cana-4558	135	15	[	[	X
cana-4558	135	16	22	22	NUM
cana-4558	135	17	]	]	PUNCT
cana-4558	135	18	.	.	PUNCT
cana-4558	136	1	its	its	PRON
cana-4558	136	2	computationally	computationally	ADV
cana-4558	136	3	intensive	intensive	ADJ
cana-4558	136	4	requirement	requirement	NOUN
cana-4558	136	5	,	,	PUNCT
cana-4558	136	6	however	however	ADV
cana-4558	136	7	,	,	PUNCT
cana-4558	136	8	prevents	prevent	VERB
cana-4558	136	9	it	it	PRON
cana-4558	136	10	from	from	ADP
cana-4558	136	11	being	be	AUX
cana-4558	136	12	implemented	implement	VERB
cana-4558	136	13	in	in	ADP
cana-4558	136	14	low	low	ADJ
cana-4558	136	15	-	-	PUNCT
cana-4558	136	16	resource	resource	NOUN
cana-4558	136	17	environments	environment	NOUN
cana-4558	136	18	.	.	PUNCT
cana-4558	137	1	these	these	DET
cana-4558	137	2	issues	issue	NOUN
cana-4558	137	3	point	point	VERB
cana-4558	137	4	to	to	ADP
cana-4558	137	5	the	the	DET
cana-4558	137	6	need	need	NOUN
cana-4558	137	7	for	for	ADP
cana-4558	137	8	scalable	scalable	ADJ
cana-4558	137	9	technological	technological	ADJ
cana-4558	137	10	advancements	advancement	NOUN
cana-4558	137	11	to	to	PART
cana-4558	137	12	increase	increase	VERB
cana-4558	137	13	availability	availability	NOUN
cana-4558	137	14	and	and	CCONJ
cana-4558	137	15	utilization	utilization	NOUN
cana-4558	137	16	at	at	ADP
cana-4558	137	17	scale	scale	NOUN
cana-4558	137	18	[	[	X
cana-4558	137	19	23],[24	23],[24	NOUN
cana-4558	137	20	]	]	PUNCT
cana-4558	137	21	.	.	PUNCT
cana-4558	138	1	when	when	SCONJ
cana-4558	138	2	yolov4	yolov4	PROPN
cana-4558	138	3	outranks	outrank	VERB
cana-4558	138	4	cnns	cnn	NOUN
cana-4558	138	5	in	in	ADP
cana-4558	138	6	accuracy	accuracy	NOUN
cana-4558	138	7	,	,	PUNCT
cana-4558	138	8	scalability	scalability	NOUN
cana-4558	138	9	,	,	PUNCT
cana-4558	138	10	and	and	CCONJ
cana-4558	138	11	efficiency	efficiency	NOUN
cana-4558	138	12	,	,	PUNCT
cana-4558	138	13	there	there	PRON
cana-4558	138	14	is	be	VERB
cana-4558	138	15	a	a	DET
cana-4558	138	16	constraint	constraint	NOUN
cana-4558	138	17	.	.	PUNCT
cana-4558	139	1	the	the	DET
cana-4558	139	2	acceleration	acceleration	NOUN
cana-4558	139	3	of	of	ADP
cana-4558	139	4	yolov4	yolov4	NOUN
cana-4558	139	5	for	for	ADP
cana-4558	139	6	low	low	ADJ
cana-4558	139	7	-	-	PUNCT
cana-4558	139	8	energy	energy	NOUN
cana-4558	139	9	edge	edge	NOUN
cana-4558	139	10	devices	device	NOUN
cana-4558	139	11	like	like	ADP
cana-4558	139	12	the	the	DET
cana-4558	139	13	raspberry	raspberry	NOUN
cana-4558	139	14	pi	pi	NOUN
cana-4558	139	15	and	and	CCONJ
cana-4558	139	16	nvidia	nvidia	PROPN
cana-4558	139	17	jetson	jetson	PROPN
cana-4558	139	18	should	should	AUX
cana-4558	139	19	receive	receive	VERB
cana-4558	139	20	top	top	ADJ
cana-4558	139	21	priority	priority	NOUN
cana-4558	139	22	from	from	ADP
cana-4558	139	23	future	future	ADJ
cana-4558	139	24	work	work	NOUN
cana-4558	139	25	[	[	X
cana-4558	139	26	25].yolov4	25].yolov4	NOUN
cana-4558	139	27	is	be	AUX
cana-4558	139	28	better	well	ADV
cana-4558	139	29	suited	suited	ADJ
cana-4558	139	30	for	for	ADP
cana-4558	139	31	real	real	ADJ
cana-4558	139	32	-	-	PUNCT
cana-4558	139	33	world	world	NOUN
cana-4558	139	34	application	application	NOUN
cana-4558	139	35	in	in	ADP
cana-4558	139	36	the	the	DET
cana-4558	139	37	agricultural	agricultural	ADJ
cana-4558	139	38	sector	sector	NOUN
cana-4558	139	39	for	for	ADP
cana-4558	139	40	applying	apply	VERB
cana-4558	139	41	transformers	transformer	NOUN
cana-4558	139	42	as	as	ADV
cana-4558	139	43	well	well	ADV
cana-4558	139	44	as	as	ADP
cana-4558	139	45	transfer	transfer	NOUN
cana-4558	139	46	learning	learn	VERB
cana-4558	139	47	more	more	ADV
cana-4558	139	48	optimal	optimal	ADJ
cana-4558	139	49	for	for	ADP
cana-4558	139	50	improving	improve	VERB
cana-4558	139	51	the	the	DET
cana-4558	139	52	accuracy(92.1	accuracy(92.1	NOUN
cana-4558	139	53	%	%	NOUN
cana-4558	139	54	)	)	PUNCT
cana-4558	139	55	of	of	ADP
cana-4558	139	56	detections	detection	NOUN
cana-4558	139	57	in	in	ADP
cana-4558	139	58	low	low	ADJ
cana-4558	139	59	-	-	PUNCT
cana-4558	139	60	data	datum	NOUN
cana-4558	139	61	settings	setting	NOUN
cana-4558	139	62	.	.	PUNCT
cana-4558	140	1	effortless	effortless	ADJ
cana-4558	140	2	tuning	tuning	NOUN
cana-4558	140	3	of	of	ADP
cana-4558	140	4	the	the	DET
cana-4558	140	5	efficient	efficient	ADJ
cana-4558	140	6	model	model	NOUN
cana-4558	140	7	can	can	AUX
cana-4558	140	8	do	do	VERB
cana-4558	140	9	away	away	ADV
cana-4558	140	10	with	with	ADP
cana-4558	140	11	its	its	PRON
cana-4558	140	12	computational	computational	ADJ
cana-4558	140	13	cost	cost	NOUN
cana-4558	140	14	so	so	SCONJ
cana-4558	140	15	that	that	SCONJ
cana-4558	140	16	it	it	PRON
cana-4558	140	17	would	would	AUX
cana-4558	140	18	be	be	AUX
cana-4558	140	19	more	more	ADV
cana-4558	140	20	accessible	accessible	ADJ
cana-4558	140	21	to	to	ADP
cana-4558	140	22	farmers	farmer	NOUN
cana-4558	140	23	anywhere	anywhere	ADV
cana-4558	140	24	in	in	ADP
cana-4558	140	25	the	the	DET
cana-4558	140	26	world	world	NOUN
cana-4558	141	1	[	[	X
cana-4558	141	2	26	26	NUM
cana-4558	141	3	]	]	PUNCT
cana-4558	141	4	.	.	PUNCT
cana-4558	142	1	communications	communication	NOUN
cana-4558	142	2	on	on	ADP
cana-4558	142	3	applied	apply	VERB
cana-4558	142	4	nonlinear	nonlinear	ADJ
cana-4558	142	5	analysis	analysis	NOUN
cana-4558	142	6	issn	issn	NOUN
cana-4558	142	7	:	:	PUNCT
cana-4558	142	8	1074	1074	NUM
cana-4558	142	9	-	-	PUNCT
cana-4558	142	10	133x	133x	NUM
cana-4558	142	11	vol	vol	NOUN
cana-4558	142	12	32	32	NUM
cana-4558	142	13	no	no	NOUN
cana-4558	142	14	.	.	PUNCT
cana-4558	143	1	9s	9s	NUM
cana-4558	143	2	(	(	PUNCT
cana-4558	143	3	2025	2025	NUM
cana-4558	143	4	)	)	PUNCT
cana-4558	143	5	2538	2538	NUM
cana-4558	143	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	144	1	yolov4	yolov4	PROPN
cana-4558	144	2	's	's	PART
cana-4558	144	3	high	high	ADJ
cana-4558	144	4	computational	computational	ADJ
cana-4558	144	5	complexity	complexity	NOUN
cana-4558	144	6	and	and	CCONJ
cana-4558	144	7	resource	resource	NOUN
cana-4558	144	8	consumption	consumption	NOUN
cana-4558	144	9	remains	remain	VERB
cana-4558	144	10	a	a	DET
cana-4558	144	11	major	major	ADJ
cana-4558	144	12	bottleneck	bottleneck	NOUN
cana-4558	144	13	,	,	PUNCT
cana-4558	144	14	especially	especially	ADV
cana-4558	144	15	when	when	SCONJ
cana-4558	144	16	it	it	PRON
cana-4558	144	17	comes	come	VERB
cana-4558	144	18	to	to	ADP
cana-4558	144	19	large	large	ADJ
cana-4558	144	20	-	-	PUNCT
cana-4558	144	21	scale	scale	NOUN
cana-4558	144	22	deployment	deployment	NOUN
cana-4558	144	23	in	in	ADP
cana-4558	144	24	agriculture	agriculture	NOUN
cana-4558	144	25	for	for	ADP
cana-4558	144	26	real	real	ADJ
cana-4558	144	27	-	-	PUNCT
cana-4558	144	28	time	time	NOUN
cana-4558	144	29	inference	inference	NOUN
cana-4558	144	30	.	.	PUNCT
cana-4558	145	1	however	however	ADV
cana-4558	145	2	,	,	PUNCT
cana-4558	145	3	better	well	ADJ
cana-4558	145	4	accuracy	accuracy	NOUN
cana-4558	145	5	,	,	PUNCT
cana-4558	145	6	speed	speed	NOUN
cana-4558	145	7	,	,	PUNCT
cana-4558	145	8	and	and	CCONJ
cana-4558	145	9	adaptability	adaptability	NOUN
cana-4558	145	10	make	make	VERB
cana-4558	145	11	yolov4	yolov4	NOUN
cana-4558	145	12	highly	highly	ADV
cana-4558	145	13	efficient	efficient	ADJ
cana-4558	145	14	in	in	ADP
cana-4558	145	15	the	the	DET
cana-4558	145	16	detection	detection	NOUN
cana-4558	145	17	of	of	ADP
cana-4558	145	18	leaf	leaf	NOUN
cana-4558	145	19	diseases	disease	NOUN
cana-4558	145	20	in	in	ADP
cana-4558	145	21	precision	precision	NOUN
cana-4558	145	22	agriculture(87%)[27	agriculture(87%)[27	PROPN
cana-4558	145	23	]	]	PUNCT
cana-4558	145	24	.	.	PUNCT
cana-4558	146	1	better	well	ADJ
cana-4558	146	2	performance	performance	NOUN
cana-4558	146	3	with	with	ADP
cana-4558	146	4	fewer	few	ADJ
cana-4558	146	5	resources	resource	NOUN
cana-4558	146	6	consumed	consume	VERB
cana-4558	146	7	is	be	AUX
cana-4558	146	8	what	what	PRON
cana-4558	146	9	future	future	ADJ
cana-4558	146	10	research	research	NOUN
cana-4558	146	11	on	on	ADP
cana-4558	146	12	yolov4	yolov4	NOUN
cana-4558	146	13	models	model	NOUN
cana-4558	146	14	can	can	AUX
cana-4558	146	15	promise	promise	VERB
cana-4558	146	16	to	to	PART
cana-4558	146	17	achieve	achieve	VERB
cana-4558	146	18	broader	broad	ADJ
cana-4558	146	19	application	application	NOUN
cana-4558	146	20	in	in	ADP
cana-4558	146	21	agricultural	agricultural	ADJ
cana-4558	146	22	technology[28	technology[28	NOUN
cana-4558	146	23	]	]	PUNCT
cana-4558	146	24	.	.	PUNCT
cana-4558	147	1	the	the	DET
cana-4558	147	2	limitations	limitation	NOUN
cana-4558	147	3	of	of	ADP
cana-4558	147	4	this	this	DET
cana-4558	147	5	design	design	NOUN
cana-4558	147	6	is	be	AUX
cana-4558	147	7	restricted	restrict	VERB
cana-4558	147	8	bandwidth	bandwidth	NOUN
cana-4558	147	9	of	of	ADP
cana-4558	147	10	the	the	DET
cana-4558	147	11	novel	novel	ADJ
cana-4558	147	12	sierpinski	sierpinski	ADJ
cana-4558	147	13	carpet	carpet	NOUN
cana-4558	147	14	antenna	antenna	NOUN
cana-4558	147	15	in	in	ADP
cana-4558	147	16	wireless	wireless	ADJ
cana-4558	147	17	communications	communication	NOUN
cana-4558	147	18	and	and	CCONJ
cana-4558	147	19	ultra	ultra	ADJ
cana-4558	147	20	wideband	wideband	NOUN
cana-4558	147	21	applications	application	NOUN
cana-4558	147	22	.	.	PUNCT
cana-4558	148	1	due	due	ADP
cana-4558	148	2	to	to	ADP
cana-4558	148	3	the	the	DET
cana-4558	148	4	existence	existence	NOUN
cana-4558	148	5	of	of	ADP
cana-4558	148	6	radiation	radiation	NOUN
cana-4558	148	7	boxes	box	NOUN
cana-4558	148	8	in	in	ADP
cana-4558	148	9	the	the	DET
cana-4558	148	10	simulation	simulation	NOUN
cana-4558	148	11	environment	environment	NOUN
cana-4558	148	12	,	,	PUNCT
cana-4558	148	13	the	the	DET
cana-4558	148	14	execution	execution	NOUN
cana-4558	148	15	time	time	NOUN
cana-4558	148	16	will	will	AUX
cana-4558	148	17	be	be	AUX
cana-4558	148	18	longer	long	ADJ
cana-4558	148	19	.	.	PUNCT
cana-4558	149	1	because	because	SCONJ
cana-4558	149	2	of	of	ADP
cana-4558	149	3	its	its	PRON
cana-4558	149	4	low	low	ADJ
cana-4558	149	5	profile	profile	NOUN
cana-4558	149	6	,	,	PUNCT
cana-4558	149	7	ease	ease	NOUN
cana-4558	149	8	of	of	ADP
cana-4558	149	9	use	use	NOUN
cana-4558	149	10	,	,	PUNCT
cana-4558	149	11	small	small	ADJ
cana-4558	149	12	size	size	NOUN
cana-4558	149	13	,	,	PUNCT
cana-4558	149	14	and	and	CCONJ
cana-4558	149	15	utility	utility	NOUN
cana-4558	149	16	,	,	PUNCT
cana-4558	149	17	the	the	DET
cana-4558	149	18	suggested	suggest	VERB
cana-4558	149	19	work	work	NOUN
cana-4558	149	20	may	may	AUX
cana-4558	149	21	be	be	AUX
cana-4558	149	22	expanded	expand	VERB
cana-4558	149	23	to	to	ADP
cana-4558	149	24	narrowband	narrowband	NOUN
cana-4558	149	25	frequencies	frequency	NOUN
cana-4558	149	26	.	.	PUNCT
cana-4558	150	1	the	the	DET
cana-4558	150	2	antenna	antenna	NOUN
cana-4558	150	3	is	be	AUX
cana-4558	150	4	suited	suit	VERB
cana-4558	150	5	for	for	ADP
cana-4558	150	6	satellite	satellite	NOUN
cana-4558	150	7	,	,	PUNCT
cana-4558	150	8	mobile	mobile	ADJ
cana-4558	150	9	phone	phone	NOUN
cana-4558	150	10	,	,	PUNCT
cana-4558	150	11	and	and	CCONJ
cana-4558	150	12	wi	wi	PROPN
cana-4558	150	13	-	-	PUNCT
cana-4558	150	14	fi	fi	NOUN
cana-4558	150	15	applications	application	NOUN
cana-4558	150	16	.	.	PUNCT
cana-4558	151	1	in	in	ADP
cana-4558	151	2	future	future	ADJ
cana-4558	151	3	studies	study	NOUN
cana-4558	151	4	,	,	PUNCT
cana-4558	151	5	advanced	advanced	ADJ
cana-4558	151	6	antennas	antenna	NOUN
cana-4558	151	7	and	and	CCONJ
cana-4558	151	8	inventive	inventive	ADJ
cana-4558	151	9	ways	way	NOUN
cana-4558	151	10	may	may	AUX
cana-4558	151	11	be	be	AUX
cana-4558	151	12	employed	employ	VERB
cana-4558	151	13	in	in	ADP
cana-4558	151	14	the	the	DET
cana-4558	151	15	design	design	NOUN
cana-4558	151	16	.	.	PUNCT
cana-4558	152	1	vii	vii	PROPN
cana-4558	152	2	.	.	PROPN
cana-4558	152	3	conclusion	conclusion	NOUN
cana-4558	152	4	leaf	leaf	NOUN
cana-4558	152	5	disease	disease	NOUN
cana-4558	152	6	detection	detection	NOUN
cana-4558	152	7	was	be	AUX
cana-4558	152	8	proposed	propose	VERB
cana-4558	152	9	to	to	PART
cana-4558	152	10	improve	improve	VERB
cana-4558	152	11	detection	detection	NOUN
cana-4558	152	12	in	in	ADP
cana-4558	152	13	precision	precision	NOUN
cana-4558	152	14	agriculture	agriculture	NOUN
cana-4558	152	15	by	by	ADP
cana-4558	152	16	comparing	compare	VERB
cana-4558	152	17	yolov4	yolov4	NOUN
cana-4558	152	18	with	with	ADP
cana-4558	152	19	cnns	cnns	PROPN
cana-4558	152	20	.	.	PUNCT
cana-4558	153	1	yolov4	yolov4	PROPN
cana-4558	153	2	identified	identify	VERB
cana-4558	153	3	complex	complex	ADJ
cana-4558	153	4	agricultural	agricultural	ADJ
cana-4558	153	5	conditions	condition	NOUN
cana-4558	153	6	with	with	ADP
cana-4558	153	7	high	high	ADJ
cana-4558	153	8	accuracy	accuracy	NOUN
cana-4558	153	9	of	of	ADP
cana-4558	153	10	87.00	87.00	NUM
cana-4558	153	11	%	%	NOUN
cana-4558	153	12	compared	compare	VERB
cana-4558	153	13	to	to	ADP
cana-4558	153	14	75.00	75.00	NUM
cana-4558	153	15	%	%	NOUN
cana-4558	153	16	by	by	ADP
cana-4558	153	17	cnn	cnn	PROPN
cana-4558	153	18	,	,	PUNCT
cana-4558	153	19	and	and	CCONJ
cana-4558	153	20	faster	fast	ADJ
cana-4558	153	21	image	image	NOUN
cana-4558	153	22	processing	processing	NOUN
cana-4558	153	23	(	(	PUNCT
cana-4558	153	24	0.70s	0.70s	NUM
cana-4558	153	25	in	in	ADP
cana-4558	153	26	comparison	comparison	NOUN
cana-4558	153	27	to	to	ADP
cana-4558	153	28	2.50s	2.50s	NUM
cana-4558	153	29	)	)	PUNCT
cana-4558	153	30	.	.	PUNCT
cana-4558	154	1	its	its	PRON
cana-4558	154	2	real	real	ADJ
cana-4558	154	3	-	-	PUNCT
cana-4558	154	4	time	time	NOUN
cana-4558	154	5	detection	detection	NOUN
cana-4558	154	6	and	and	CCONJ
cana-4558	154	7	feature	feature	NOUN
cana-4558	154	8	extraction	extraction	NOUN
cana-4558	154	9	make	make	VERB
cana-4558	154	10	it	it	PRON
cana-4558	154	11	an	an	DET
cana-4558	154	12	effective	effective	ADJ
cana-4558	154	13	and	and	CCONJ
cana-4558	154	14	scalable	scalable	ADJ
cana-4558	154	15	solution	solution	NOUN
cana-4558	154	16	.	.	PUNCT
cana-4558	155	1	yolov4	yolov4	PROPN
cana-4558	155	2	can	can	AUX
cana-4558	155	3	be	be	AUX
cana-4558	155	4	employed	employ	VERB
cana-4558	155	5	to	to	PART
cana-4558	155	6	deploy	deploy	VERB
cana-4558	155	7	in	in	ADP
cana-4558	155	8	iot	iot	NOUN
cana-4558	155	9	-	-	PUNCT
cana-4558	155	10	based	base	VERB
cana-4558	155	11	smart	smart	ADJ
cana-4558	155	12	agriculture	agriculture	NOUN
cana-4558	155	13	systems	system	NOUN
cana-4558	155	14	for	for	ADP
cana-4558	155	15	autonomous	autonomous	ADJ
cana-4558	155	16	detection	detection	NOUN
cana-4558	155	17	of	of	ADP
cana-4558	155	18	disease	disease	NOUN
cana-4558	155	19	.	.	PUNCT
cana-4558	156	1	future	future	ADJ
cana-4558	156	2	work	work	NOUN
cana-4558	156	3	can	can	AUX
cana-4558	156	4	look	look	VERB
cana-4558	156	5	forward	forward	ADV
cana-4558	156	6	to	to	ADP
cana-4558	156	7	hybrid	hybrid	ADJ
cana-4558	156	8	deep	deep	ADJ
cana-4558	156	9	learning	learning	NOUN
cana-4558	156	10	models	model	NOUN
cana-4558	156	11	for	for	ADP
cana-4558	156	12	higher	high	ADJ
cana-4558	156	13	accuracy	accuracy	NOUN
cana-4558	156	14	and	and	CCONJ
cana-4558	156	15	resourceeffective	resourceeffective	ADJ
cana-4558	156	16	deployment	deployment	NOUN
cana-4558	156	17	for	for	ADP
cana-4558	156	18	large	large	ADJ
cana-4558	156	19	-	-	PUNCT
cana-4558	156	20	scale	scale	NOUN
cana-4558	156	21	applications	application	NOUN
cana-4558	156	22	.	.	PUNCT
cana-4558	157	1	references	reference	NOUN
cana-4558	157	2	[	[	X
cana-4558	157	3	1	1	NUM
cana-4558	157	4	]	]	PUNCT
cana-4558	157	5	aldakheel	aldakheel	NOUN
cana-4558	157	6	,	,	PUNCT
cana-4558	157	7	eman	eman	PROPN
cana-4558	157	8	abdullah	abdullah	PROPN
cana-4558	157	9	,	,	PUNCT
cana-4558	157	10	mohammed	mohammed	PROPN
cana-4558	157	11	zakariah	zakariah	PROPN
cana-4558	157	12	,	,	PUNCT
cana-4558	157	13	and	and	CCONJ
cana-4558	157	14	amira	amira	PROPN
cana-4558	157	15	h.alabdalall	h.alabdalall	PROPN
cana-4558	157	16	.	.	PUNCT
cana-4558	157	17	2024	2024	NUM
cana-4558	157	18	.	.	PUNCT
cana-4558	158	1	“	"	PUNCT
cana-4558	158	2	detection	detection	NOUN
cana-4558	158	3	and	and	CCONJ
cana-4558	158	4	identification	identification	NOUN
cana-4558	158	5	of	of	ADP
cana-4558	158	6	plant	plant	NOUN
cana-4558	158	7	leaf	leaf	NOUN
cana-4558	158	8	diseases	disease	NOUN
cana-4558	158	9	using	use	VERB
cana-4558	158	10	yolov4	yolov4	PROPN
cana-4558	158	11	.	.	PUNCT
cana-4558	158	12	”	"	PUNCT
cana-4558	158	13	frontiers	frontier	NOUN
cana-4558	158	14	in	in	ADP
cana-4558	158	15	plant	plant	NOUN
cana-4558	158	16	science	science	NOUN
cana-4558	158	17	15	15	NUM
cana-4558	158	18	(	(	PUNCT
cana-4558	158	19	april):1355941	april):1355941	ADJ
cana-4558	158	20	.	.	PUNCT
cana-4558	159	1	[	[	X
cana-4558	159	2	2	2	NUM
cana-4558	159	3	]	]	X
cana-4558	159	4	jagadeesan	jagadeesan	NOUN
cana-4558	159	5	,	,	PUNCT
cana-4558	159	6	deepakraj	deepakraj	ADJ
cana-4558	159	7	,	,	PUNCT
cana-4558	159	8	venkadeshan	venkadeshan	PROPN
cana-4558	159	9	ramalingam	ramalingam	NOUN
cana-4558	159	10	,	,	PUNCT
cana-4558	159	11	ilayaraja	ilayaraja	PROPN
cana-4558	159	12	venkatachalam	venkatachalam	PROPN
cana-4558	159	13	,	,	PUNCT
cana-4558	159	14	manojkumar	manojkumar	PROPN
cana-4558	159	15	vivekanandan	vivekanandan	PROPN
cana-4558	159	16	,	,	PUNCT
cana-4558	159	17	and	and	CCONJ
cana-4558	159	18	manjula	manjula	PROPN
cana-4558	159	19	.	.	PUNCT
cana-4558	160	1	2023	2023	NUM
cana-4558	160	2	.	.	PUNCT
cana-4558	161	1	“	"	PUNCT
cana-4558	161	2	an	an	DET
cana-4558	161	3	efficient	efficient	ADJ
cana-4558	161	4	detection	detection	NOUN
cana-4558	161	5	and	and	CCONJ
cana-4558	161	6	classification	classification	NOUN
cana-4558	161	7	of	of	ADP
cana-4558	161	8	plant	plant	NOUN
cana-4558	161	9	diseases	disease	NOUN
cana-4558	161	10	using	use	VERB
cana-4558	161	11	deep	deep	ADJ
cana-4558	161	12	learning	learning	NOUN
cana-4558	161	13	approach	approach	NOUN
cana-4558	161	14	.	.	PUNCT
cana-4558	161	15	”	"	PUNCT
cana-4558	162	1	in	in	ADP
cana-4558	162	2	2023	2023	NUM
cana-4558	162	3	international	international	ADJ
cana-4558	162	4	conference	conference	NOUN
cana-4558	162	5	on	on	ADP
cana-4558	162	6	evolutionary	evolutionary	ADJ
cana-4558	162	7	algorithms	algorithm	NOUN
cana-4558	162	8	and	and	CCONJ
cana-4558	162	9	soft	soft	ADJ
cana-4558	162	10	computing	computing	NOUN
cana-4558	162	11	techniques	technique	NOUN
cana-4558	162	12	(	(	PUNCT
cana-4558	162	13	easct	easct	NOUN
cana-4558	162	14	)	)	PUNCT
cana-4558	162	15	,	,	PUNCT
cana-4558	162	16	1–6	1–6	X
cana-4558	162	17	.	.	PUNCT
cana-4558	162	18	ieee	ieee	NOUN
cana-4558	162	19	.	.	PUNCT
cana-4558	163	1	[	[	X
cana-4558	163	2	3	3	NUM
cana-4558	163	3	]	]	X
cana-4558	163	4	falaschetti	falaschetti	NOUN
cana-4558	163	5	,	,	PUNCT
cana-4558	163	6	laura	laura	PROPN
cana-4558	163	7	,	,	PUNCT
cana-4558	163	8	lorenzo	lorenzo	PROPN
cana-4558	163	9	manoni	manoni	PROPN
cana-4558	163	10	,	,	PUNCT
cana-4558	163	11	denis	denis	PROPN
cana-4558	163	12	di	di	PROPN
cana-4558	163	13	leo	leo	PROPN
cana-4558	163	14	,	,	PUNCT
cana-4558	163	15	danilo	danilo	PROPN
cana-4558	163	16	pau	pau	PROPN
cana-4558	163	17	,	,	PUNCT
cana-4558	163	18	valeria	valeria	PROPN
cana-4558	163	19	tomaselli	tomaselli	PROPN
cana-4558	163	20	,	,	PUNCT
cana-4558	163	21	and	and	CCONJ
cana-4558	163	22	claudio	claudio	NOUN
cana-4558	163	23	turchetti	turchetti	NOUN
cana-4558	163	24	.	.	PUNCT
cana-4558	163	25	2022	2022	NUM
cana-4558	163	26	.	.	PUNCT
cana-4558	164	1	“	"	PUNCT
cana-4558	164	2	a	a	DET
cana-4558	164	3	cnn	cnn	PROPN
cana-4558	164	4	-	-	PUNCT
cana-4558	164	5	based	base	VERB
cana-4558	164	6	image	image	NOUN
cana-4558	164	7	detector	detector	NOUN
cana-4558	164	8	for	for	ADP
cana-4558	164	9	plant	plant	NOUN
cana-4558	164	10	leaf	leaf	NOUN
cana-4558	164	11	diseases	disease	NOUN
cana-4558	164	12	classification	classification	NOUN
cana-4558	164	13	.	.	PUNCT
cana-4558	164	14	”	"	PUNCT
cana-4558	165	1	hardwarex	hardwarex	PROPN
cana-4558	165	2	12	12	NUM
cana-4558	165	3	(	(	PUNCT
cana-4558	165	4	october):e00363	october):e00363	NOUN
cana-4558	165	5	.	.	PUNCT
cana-4558	166	1	[	[	X
cana-4558	166	2	4]li	4]li	NUM
cana-4558	166	3	,	,	PUNCT
cana-4558	166	4	yihang	yihang	PROPN
cana-4558	166	5	,	,	PUNCT
cana-4558	166	6	wenzhong	wenzhong	PROPN
cana-4558	166	7	yang	yang	PROPN
cana-4558	166	8	,	,	PUNCT
cana-4558	166	9	zhifeng	zhifeng	PROPN
cana-4558	166	10	lu	lu	PROPN
cana-4558	166	11	,	,	PUNCT
cana-4558	166	12	and	and	CCONJ
cana-4558	166	13	houwang	houwang	PROPN
cana-4558	166	14	shi	shi	PROPN
cana-4558	166	15	.	.	PROPN
cana-4558	166	16	2024	2024	NUM
cana-4558	166	17	.	.	PUNCT
cana-4558	167	1	“	"	PUNCT
cana-4558	167	2	yh	yh	NOUN
cana-4558	167	3	-	-	NOUN
cana-4558	167	4	rtyo	rtyo	PROPN
cana-4558	167	5	:	:	PUNCT
cana-4558	167	6	an	an	DET
cana-4558	167	7	end	end	NOUN
cana-4558	167	8	-	-	PUNCT
cana-4558	167	9	to	to	ADP
cana-4558	167	10	-	-	PUNCT
cana-4558	167	11	end	end	NOUN
cana-4558	167	12	object	object	NOUN
cana-4558	167	13	detection	detection	NOUN
cana-4558	167	14	method	method	NOUN
cana-4558	167	15	for	for	ADP
cana-4558	167	16	crop	crop	NOUN
cana-4558	167	17	growth	growth	NOUN
cana-4558	167	18	anomaly	anomaly	NOUN
cana-4558	167	19	detection	detection	NOUN
cana-4558	167	20	in	in	ADP
cana-4558	167	21	uav	uav	PROPN
cana-4558	167	22	scenarios	scenario	NOUN
cana-4558	167	23	.	.	PUNCT
cana-4558	167	24	”	"	PUNCT
cana-4558	167	25	peerj	peerj	NOUN
cana-4558	167	26	.	.	PUNCT
cana-4558	168	1	computer	computer	NOUN
cana-4558	168	2	science	science	NOUN
cana-4558	168	3	10	10	NUM
cana-4558	168	4	(	(	PUNCT
cana-4558	168	5	december):e2477	december):e2477	NOUN
cana-4558	168	6	.	.	PUNCT
cana-4558	169	1	[	[	X
cana-4558	169	2	5]gurusamy	5]gurusamy	NUM
cana-4558	169	3	,	,	PUNCT
cana-4558	169	4	r.	r.	PROPN
cana-4558	169	5	,	,	PUNCT
cana-4558	169	6	rajmohan	rajmohan	PROPN
cana-4558	169	7	,	,	PUNCT
cana-4558	169	8	v.	v.	ADV
cana-4558	169	9	,	,	PUNCT
cana-4558	169	10	sengottaiyan	sengottaiyan	ADJ
cana-4558	169	11	,	,	PUNCT
cana-4558	169	12	n.	n.	NOUN
cana-4558	169	13	,	,	PUNCT
cana-4558	169	14	kalyanasundaram	kalyanasundaram	NOUN
cana-4558	169	15	,	,	PUNCT
cana-4558	169	16	p.	p.	NOUN
cana-4558	169	17	and	and	CCONJ
cana-4558	169	18	ramesh	ramesh	PROPN
cana-4558	169	19	,	,	PUNCT
cana-4558	169	20	s.m	s.m	PROPN
cana-4558	169	21	.	.	PROPN
cana-4558	169	22	,	,	PUNCT
cana-4558	169	23	2023	2023	NUM
cana-4558	169	24	,	,	PUNCT
cana-4558	169	25	july	july	PROPN
cana-4558	169	26	.	.	PUNCT
cana-4558	170	1	comparative	comparative	ADJ
cana-4558	170	2	analysis	analysis	NOUN
cana-4558	170	3	on	on	ADP
cana-4558	170	4	medical	medical	ADJ
cana-4558	170	5	image	image	NOUN
cana-4558	170	6	prediction	prediction	NOUN
cana-4558	170	7	of	of	ADP
cana-4558	170	8	breast	breast	NOUN
cana-4558	170	9	cancer	cancer	NOUN
cana-4558	170	10	disease	disease	NOUN
cana-4558	170	11	using	use	VERB
cana-4558	170	12	various	various	ADJ
cana-4558	170	13	machine	machine	NOUN
cana-4558	170	14	learning	learn	VERB
cana-4558	170	15	algorithms	algorithm	NOUN
cana-4558	170	16	.	.	PUNCT
cana-4558	171	1	in	in	ADP
cana-4558	171	2	2023	2023	NUM
cana-4558	171	3	4th	4th	ADJ
cana-4558	171	4	international	international	ADJ
cana-4558	171	5	conference	conference	NOUN
cana-4558	171	6	on	on	ADP
cana-4558	171	7	electronics	electronic	NOUN
cana-4558	171	8	and	and	CCONJ
cana-4558	171	9	sustainable	sustainable	ADJ
cana-4558	171	10	communication	communication	NOUN
cana-4558	171	11	systems	system	NOUN
cana-4558	171	12	(	(	PUNCT
cana-4558	171	13	icesc	icesc	PROPN
cana-4558	171	14	)	)	PUNCT
cana-4558	171	15	(	(	PUNCT
cana-4558	171	16	pp	pp	ADJ
cana-4558	171	17	.	.	PUNCT
cana-4558	172	1	1522	1522	NUM
cana-4558	172	2	-	-	SYM
cana-4558	172	3	1526	1526	NUM
cana-4558	172	4	)	)	PUNCT
cana-4558	172	5	.	.	PUNCT
cana-4558	173	1	ieee	ieee	PROPN
cana-4558	173	2	.	.	PUNCT
cana-4558	174	1	http://paperpile.com/b/nhlj89/3bvr	http://paperpile.com/b/nhlj89/3bvr	ADJ
cana-4558	174	2	http://paperpile.com/b/nhlj89/3bvr	http://paperpile.com/b/nhlj89/3bvr	ADJ
cana-4558	174	3	http://paperpile.com/b/nhlj89/3bvr	http://paperpile.com/b/nhlj89/3bvr	PROPN
cana-4558	174	4	http://paperpile.com/b/nhlj89/3bvr	http://paperpile.com/b/nhlj89/3bvr	PROPN
cana-4558	174	5	http://paperpile.com/b/nhlj89/njp9	http://paperpile.com/b/nhlj89/njp9	NOUN
cana-4558	174	6	http://paperpile.com/b/nhlj89/njp9	http://paperpile.com/b/nhlj89/njp9	NOUN
cana-4558	174	7	http://paperpile.com/b/nhlj89/njp9	http://paperpile.com/b/nhlj89/njp9	NOUN
cana-4558	174	8	http://paperpile.com/b/nhlj89/fefj	http://paperpile.com/b/nhlj89/fefj	PROPN
cana-4558	174	9	http://paperpile.com/b/nhlj89/hiya	http://paperpile.com/b/nhlj89/hiya	PROPN
cana-4558	174	10	http://paperpile.com/b/nhlj89/hiya	http://paperpile.com/b/nhlj89/hiya	PROPN
cana-4558	174	11	http://paperpile.com/b/nhlj89/hiya	http://paperpile.com/b/nhlj89/hiya	PROPN
cana-4558	174	12	communications	communication	NOUN
cana-4558	174	13	on	on	ADP
cana-4558	174	14	applied	apply	VERB
cana-4558	174	15	nonlinear	nonlinear	ADJ
cana-4558	174	16	analysis	analysis	NOUN
cana-4558	174	17	issn	issn	NOUN
cana-4558	174	18	:	:	PUNCT
cana-4558	174	19	1074	1074	NUM
cana-4558	174	20	-	-	PUNCT
cana-4558	174	21	133x	133x	NUM
cana-4558	174	22	vol	vol	NOUN
cana-4558	174	23	32	32	NUM
cana-4558	174	24	no	no	NOUN
cana-4558	174	25	.	.	PUNCT
cana-4558	175	1	9s	9s	NUM
cana-4558	175	2	(	(	PUNCT
cana-4558	175	3	2025	2025	NUM
cana-4558	175	4	)	)	PUNCT
cana-4558	175	5	2539	2539	NUM
cana-4558	175	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	176	1	[	[	X
cana-4558	176	2	6]thilakarathne	6]thilakarathne	PROPN
cana-4558	176	3	,	,	PUNCT
cana-4558	176	4	navod	navod	PROPN
cana-4558	176	5	neranjan	neranjan	PROPN
cana-4558	176	6	,	,	PUNCT
cana-4558	176	7	muhammad	muhammad	PROPN
cana-4558	176	8	saifullah	saifullah	PROPN
cana-4558	176	9	abu	abu	PROPN
cana-4558	176	10	bakar	bakar	PROPN
cana-4558	176	11	,	,	PUNCT
cana-4558	176	12	pg	pg	PROPN
cana-4558	176	13	emerolylariffion	emerolylariffion	NOUN
cana-4558	176	14	abas	abas	PROPN
cana-4558	176	15	,	,	PUNCT
cana-4558	176	16	and	and	CCONJ
cana-4558	176	17	hayati	hayati	PROPN
cana-4558	176	18	yassin	yassin	PROPN
cana-4558	176	19	.	.	PROPN
cana-4558	176	20	2022	2022	NUM
cana-4558	176	21	.	.	PUNCT
cana-4558	177	1	“	"	PUNCT
cana-4558	177	2	towards	towards	ADP
cana-4558	177	3	making	make	VERB
cana-4558	177	4	the	the	DET
cana-4558	177	5	fields	field	NOUN
cana-4558	177	6	talks	talk	VERB
cana-4558	177	7	:	:	PUNCT
cana-4558	177	8	a	a	DET
cana-4558	177	9	real	real	ADJ
cana-4558	177	10	-	-	PUNCT
cana-4558	177	11	time	time	NOUN
cana-4558	177	12	cloud	cloud	NOUN
cana-4558	177	13	enabled	enable	VERB
cana-4558	177	14	iot	iot	ADJ
cana-4558	177	15	crop	crop	NOUN
cana-4558	177	16	management	management	NOUN
cana-4558	177	17	platform	platform	NOUN
cana-4558	177	18	for	for	ADP
cana-4558	177	19	smart	smart	ADJ
cana-4558	177	20	agriculture	agriculture	NOUN
cana-4558	177	21	.	.	PUNCT
cana-4558	177	22	”	"	PUNCT
cana-4558	177	23	frontiers	frontier	NOUN
cana-4558	177	24	in	in	ADP
cana-4558	177	25	plant	plant	NOUN
cana-4558	177	26	science	science	NOUN
cana-4558	177	27	13:1030168	13:1030168	NOUN
cana-4558	177	28	.	.	PUNCT
cana-4558	178	1	[	[	X
cana-4558	178	2	7]kumar	7]kumar	NUM
cana-4558	178	3	,	,	PUNCT
cana-4558	178	4	akhil	akhil	NOUN
cana-4558	178	5	,	,	PUNCT
cana-4558	178	6	arvind	arvind	PROPN
cana-4558	178	7	kalia	kalia	PROPN
cana-4558	178	8	,	,	PUNCT
cana-4558	178	9	and	and	CCONJ
cana-4558	178	10	aayushi	aayushi	PROPN
cana-4558	178	11	kalia	kalia	NOUN
cana-4558	178	12	.	.	PUNCT
cana-4558	179	1	2022	2022	NUM
cana-4558	179	2	.	.	PUNCT
cana-4558	180	1	“	"	PUNCT
cana-4558	180	2	etl	etl	NOUN
cana-4558	180	3	-	-	PUNCT
cana-4558	180	4	yolo	yolo	ADJ
cana-4558	180	5	v4	v4	NOUN
cana-4558	180	6	:	:	PUNCT
cana-4558	180	7	a	a	DET
cana-4558	180	8	face	face	NOUN
cana-4558	180	9	mask	mask	NOUN
cana-4558	180	10	detection	detection	NOUN
cana-4558	180	11	algorithm	algorithm	NOUN
cana-4558	180	12	in	in	ADP
cana-4558	180	13	era	era	NOUN
cana-4558	180	14	of	of	ADP
cana-4558	180	15	covid-19	covid-19	PROPN
cana-4558	180	16	pandemic	pandemic	NOUN
cana-4558	180	17	.	.	PUNCT
cana-4558	180	18	”	"	PUNCT
cana-4558	181	1	optik	optik	PROPN
cana-4558	181	2	259	259	NUM
cana-4558	181	3	(	(	PUNCT
cana-4558	181	4	june):169051	june):169051	X
cana-4558	182	1	[	[	X
cana-4558	182	2	8]li	8]li	NUM
cana-4558	182	3	,	,	PUNCT
cana-4558	182	4	haibin	haibin	PROPN
cana-4558	182	5	,	,	PUNCT
cana-4558	182	6	jun	jun	PROPN
cana-4558	182	7	meng	meng	PROPN
cana-4558	182	8	,	,	PUNCT
cana-4558	182	9	zhaowei	zhaowei	PROPN
cana-4558	182	10	wang	wang	PROPN
cana-4558	182	11	,	,	PUNCT
cana-4558	182	12	and	and	CCONJ
cana-4558	182	13	yushi	yushi	PROPN
cana-4558	182	14	luan	luan	PROPN
cana-4558	182	15	.	.	PUNCT
cana-4558	183	1	2025	2025	NUM
cana-4558	183	2	.	.	PUNCT
cana-4558	184	1	“	"	PUNCT
cana-4558	184	2	pmipropred	pmipropre	VERB
cana-4558	184	3	:	:	PUNCT
cana-4558	184	4	a	a	DET
cana-4558	184	5	novel	novel	ADJ
cana-4558	184	6	method	method	NOUN
cana-4558	184	7	towards	towards	ADP
cana-4558	184	8	plant	plant	NOUN
cana-4558	184	9	mirna	mirna	NOUN
cana-4558	184	10	promoter	promoter	NOUN
cana-4558	184	11	prediction	prediction	NOUN
cana-4558	184	12	based	base	VERB
cana-4558	184	13	on	on	ADP
cana-4558	184	14	cnn	cnn	PROPN
cana-4558	184	15	-	-	PUNCT
cana-4558	184	16	transformer	transformer	NOUN
cana-4558	184	17	network	network	NOUN
cana-4558	184	18	and	and	CCONJ
cana-4558	184	19	convolutional	convolutional	ADJ
cana-4558	184	20	block	block	NOUN
cana-4558	184	21	attention	attention	NOUN
cana-4558	184	22	mechanism	mechanism	NOUN
cana-4558	184	23	.	.	PUNCT
cana-4558	184	24	”	"	PUNCT
cana-4558	185	1	international	international	ADJ
cana-4558	185	2	journal	journal	NOUN
cana-4558	185	3	of	of	ADP
cana-4558	185	4	biological	biological	ADJ
cana-4558	185	5	macromolecules	macromolecule	NOUN
cana-4558	185	6	302	302	NUM
cana-4558	185	7	(	(	PUNCT
cana-4558	185	8	february):140630	february):140630	PROPN
cana-4558	185	9	.	.	PUNCT
cana-4558	186	1	[	[	X
cana-4558	186	2	9]yoganathan	9]yoganathan	NUM
cana-4558	186	3	,	,	PUNCT
cana-4558	186	4	a	a	DET
cana-4558	186	5	,	,	PUNCT
cana-4558	186	6	periasamy	periasamy	ADJ
cana-4558	186	7	,	,	PUNCT
cana-4558	186	8	ps	ps	PROPN
cana-4558	186	9	,	,	PUNCT
cana-4558	186	10	anitha	anitha	PROPN
cana-4558	186	11	,	,	PUNCT
cana-4558	186	12	p	p	PROPN
cana-4558	186	13	&	&	CCONJ
cana-4558	186	14	saravanan	saravanan	PROPN
cana-4558	186	15	,	,	PUNCT
cana-4558	186	16	n	n	PROPN
cana-4558	186	17	2023	2023	NUM
cana-4558	186	18	,	,	PUNCT
cana-4558	186	19	‘	'	PUNCT
cana-4558	186	20	joint	joint	ADJ
cana-4558	186	21	power	power	NOUN
cana-4558	186	22	allocation	allocation	NOUN
cana-4558	186	23	and	and	CCONJ
cana-4558	186	24	channel	channel	NOUN
cana-4558	186	25	assignment	assignment	NOUN
cana-4558	186	26	for	for	ADP
cana-4558	186	27	device	device	NOUN
cana-4558	186	28	-	-	PUNCT
cana-4558	186	29	to	to	ADP
cana-4558	186	30	-	-	PUNCT
cana-4558	186	31	device	device	NOUN
cana-4558	186	32	communication	communication	NOUN
cana-4558	186	33	using	use	VERB
cana-4558	186	34	the	the	DET
cana-4558	186	35	hungarian	hungarian	ADJ
cana-4558	186	36	model	model	NOUN
cana-4558	186	37	and	and	CCONJ
cana-4558	186	38	enhanced	enhance	VERB
cana-4558	186	39	hybrid	hybrid	ADJ
cana-4558	186	40	red	red	ADJ
cana-4558	186	41	fox	fox	PROPN
cana-4558	186	42	-	-	PUNCT
cana-4558	186	43	harris	harris	PROPN
cana-4558	186	44	hawks	hawks	PROPN
cana-4558	186	45	optimization	optimization	NOUN
cana-4558	186	46	’	'	PUNCT
cana-4558	186	47	.	.	PUNCT
cana-4558	187	1	international	international	ADJ
cana-4558	187	2	journal	journal	PROPN
cana-4558	187	3	of	of	ADP
cana-4558	187	4	communication	communication	NOUN
cana-4558	187	5	systems	system	NOUN
cana-4558	187	6	,	,	PUNCT
cana-4558	187	7	vol	vol	NOUN
cana-4558	187	8	.	.	PROPN
cana-4558	187	9	36	36	NUM
cana-4558	187	10	,	,	PUNCT
cana-4558	187	11	issues	issue	NOUN
cana-4558	187	12	7	7	NUM
cana-4558	187	13	,	,	PUNCT
cana-4558	187	14	p.	p.	NOUN
cana-4558	187	15	e5425	e5425	NOUN
cana-4558	187	16	,	,	PUNCT
cana-4558	187	17	impact	impact	NOUN
cana-4558	187	18	factor	factor	NOUN
cana-4558	187	19	:	:	PUNCT
cana-4558	187	20	1.7	1.7	NUM
cana-4558	187	21	.	.	PUNCT
cana-4558	188	1	[	[	X
cana-4558	188	2	10]k	10]k	NUM
cana-4558	188	3	.	.	PUNCT
cana-4558	189	1	shivaprasad	shivaprasad	ADJ
cana-4558	189	2	and	and	CCONJ
cana-4558	189	3	a.	a.	NOUN
cana-4558	189	4	wadhawan	wadhawan	NOUN
cana-4558	189	5	,	,	PUNCT
cana-4558	189	6	"	"	PUNCT
cana-4558	189	7	deep	deep	ADJ
cana-4558	189	8	learning	learning	NOUN
cana-4558	189	9	-	-	PUNCT
cana-4558	189	10	based	base	VERB
cana-4558	189	11	plant	plant	NOUN
cana-4558	189	12	leaf	leaf	NOUN
cana-4558	189	13	disease	disease	NOUN
cana-4558	189	14	detection	detection	NOUN
cana-4558	189	15	,	,	PUNCT
cana-4558	189	16	"	"	PUNCT
cana-4558	189	17	2023	2023	NUM
cana-4558	189	18	7th	7th	ADJ
cana-4558	189	19	international	international	ADJ
cana-4558	189	20	conference	conference	NOUN
cana-4558	189	21	on	on	ADP
cana-4558	189	22	intelligent	intelligent	ADJ
cana-4558	189	23	computing	computing	NOUN
cana-4558	189	24	and	and	CCONJ
cana-4558	189	25	control	control	NOUN
cana-4558	189	26	systems	system	NOUN
cana-4558	189	27	(	(	PUNCT
cana-4558	189	28	iciccs	iciccs	PROPN
cana-4558	189	29	)	)	PUNCT
cana-4558	189	30	,	,	PUNCT
cana-4558	189	31	madurai	madurai	NOUN
cana-4558	189	32	,	,	PUNCT
cana-4558	189	33	india,2023	india,2023	NOUN
cana-4558	189	34	,	,	PUNCT
cana-4558	189	35	pp	pp	ADJ
cana-4558	189	36	.	.	PUNCT
cana-4558	190	1	360	360	NUM
cana-4558	190	2	-	-	SYM
cana-4558	190	3	365	365	NUM
cana-4558	190	4	,	,	PUNCT
cana-4558	190	5	doi	doi	NOUN
cana-4558	190	6	:	:	PUNCT
cana-4558	190	7	10.1109	10.1109	NUM
cana-4558	190	8	/	/	SYM
cana-4558	190	9	iciccs56967.2023.10142857	iciccs56967.2023.10142857	PROPN
cana-4558	190	10	.	.	PUNCT
cana-4558	191	1	[	[	X
cana-4558	191	2	11]araaf	11]araaf	NUM
cana-4558	191	3	,	,	PUNCT
cana-4558	191	4	raka	raka	PROPN
cana-4558	191	5	thoriq	thoriq	PROPN
cana-4558	191	6	,	,	PUNCT
cana-4558	191	7	arkar	arkar	PROPN
cana-4558	191	8	minn	minn	PROPN
cana-4558	191	9	,	,	PUNCT
cana-4558	191	10	and	and	CCONJ
cana-4558	191	11	tofael	tofael	PROPN
cana-4558	191	12	ahamed	ahamed	PROPN
cana-4558	191	13	.	.	PUNCT
cana-4558	191	14	2024	2024	NUM
cana-4558	191	15	.	.	PUNCT
cana-4558	192	1	“	"	PUNCT
cana-4558	192	2	coffee	coffee	NOUN
cana-4558	192	3	leaf	leaf	NOUN
cana-4558	192	4	rust	rust	NOUN
cana-4558	192	5	disease	disease	NOUN
cana-4558	192	6	detection	detection	NOUN
cana-4558	192	7	and	and	CCONJ
cana-4558	192	8	implementation	implementation	NOUN
cana-4558	192	9	of	of	ADP
cana-4558	192	10	an	an	DET
cana-4558	192	11	edge	edge	NOUN
cana-4558	192	12	device	device	NOUN
cana-4558	192	13	for	for	ADP
cana-4558	192	14	pruning	prune	VERB
cana-4558	192	15	infected	infected	ADJ
cana-4558	192	16	leaves	leave	NOUN
cana-4558	192	17	via	via	ADP
cana-4558	192	18	deep	deep	ADJ
cana-4558	192	19	learning	learning	NOUN
cana-4558	192	20	algorithms	algorithm	NOUN
cana-4558	192	21	.	.	PUNCT
cana-4558	192	22	”	"	PUNCT
cana-4558	193	1	sensors	sensor	NOUN
cana-4558	193	2	(	(	PUNCT
cana-4558	193	3	basel	basel	PROPN
cana-4558	193	4	,	,	PUNCT
cana-4558	193	5	switzerland	switzerland	PROPN
cana-4558	193	6	)	)	PUNCT
cana-4558	193	7	24	24	NUM
cana-4558	193	8	(	(	PUNCT
cana-4558	193	9	24	24	NUM
cana-4558	193	10	)	)	PUNCT
cana-4558	193	11	.	.	PUNCT
cana-4558	194	1	[	[	X
cana-4558	194	2	12]dinesh	12]dinesh	NUM
cana-4558	194	3	,	,	PUNCT
cana-4558	194	4	paidipati	paidipati	NOUN
cana-4558	194	5	,	,	PUNCT
cana-4558	194	6	a.	a.	PROPN
cana-4558	194	7	s.	s.	PROPN
cana-4558	194	8	vickram	vickram	PROPN
cana-4558	194	9	,	,	PUNCT
cana-4558	194	10	and	and	CCONJ
cana-4558	194	11	p.	p.	NOUN
cana-4558	194	12	kalyanasundaram	kalyanasundaram	NOUN
cana-4558	194	13	.	.	PUNCT
cana-4558	195	1	"	"	PUNCT
cana-4558	195	2	medical	medical	ADJ
cana-4558	195	3	image	image	NOUN
cana-4558	195	4	prediction	prediction	NOUN
cana-4558	195	5	for	for	ADP
cana-4558	195	6	diagnosis	diagnosis	NOUN
cana-4558	195	7	of	of	ADP
cana-4558	195	8	breast	breast	NOUN
cana-4558	195	9	cancer	cancer	NOUN
cana-4558	195	10	disease	disease	NOUN
cana-4558	195	11	comparing	compare	VERB
cana-4558	195	12	the	the	DET
cana-4558	195	13	machine	machine	NOUN
cana-4558	195	14	learning	learn	VERB
cana-4558	195	15	algorithms	algorithm	NOUN
cana-4558	195	16	:	:	PUNCT
cana-4558	195	17	svm	svm	PROPN
cana-4558	195	18	,	,	PUNCT
cana-4558	195	19	knn	knn	PROPN
cana-4558	195	20	,	,	PUNCT
cana-4558	195	21	logistic	logistic	ADJ
cana-4558	195	22	regression	regression	NOUN
cana-4558	195	23	,	,	PUNCT
cana-4558	195	24	random	random	ADJ
cana-4558	195	25	forest	forest	NOUN
cana-4558	195	26	and	and	CCONJ
cana-4558	195	27	decision	decision	NOUN
cana-4558	195	28	tree	tree	NOUN
cana-4558	195	29	to	to	PART
cana-4558	195	30	measure	measure	VERB
cana-4558	195	31	accuracy	accuracy	NOUN
cana-4558	195	32	.	.	PUNCT
cana-4558	195	33	"	"	PUNCT
cana-4558	196	1	in	in	ADP
cana-4558	196	2	aip	aip	PROPN
cana-4558	196	3	conference	conference	NOUN
cana-4558	196	4	proceedings	proceeding	NOUN
cana-4558	196	5	,	,	PUNCT
cana-4558	196	6	vol	vol	NOUN
cana-4558	196	7	.	.	NOUN
cana-4558	196	8	2853	2853	NUM
cana-4558	196	9	,	,	PUNCT
cana-4558	196	10	no	no	INTJ
cana-4558	196	11	.	.	NOUN
cana-4558	196	12	1	1	X
cana-4558	196	13	.	.	X
cana-4558	196	14	aip	aip	PROPN
cana-4558	196	15	publishing	publishing	PROPN
cana-4558	196	16	,	,	PUNCT
cana-4558	196	17	2024	2024	NUM
cana-4558	196	18	.	.	PUNCT
cana-4558	197	1	[	[	X
cana-4558	197	2	13]shi	13]shi	NUM
cana-4558	197	3	,	,	PUNCT
cana-4558	197	4	bing	bing	NOUN
cana-4558	197	5	,	,	PUNCT
cana-4558	197	6	luqi	luqi	PROPN
cana-4558	197	7	guo	guo	PROPN
cana-4558	197	8	,	,	PUNCT
cana-4558	197	9	and	and	CCONJ
cana-4558	197	10	lejun	lejun	PROPN
cana-4558	197	11	yu	yu	PROPN
cana-4558	197	12	.	.	PROPN
cana-4558	197	13	2024	2024	NUM
cana-4558	197	14	.	.	PUNCT
cana-4558	198	1	“	"	PUNCT
cana-4558	198	2	accurate	accurate	ADJ
cana-4558	198	3	lai	lai	PROPN
cana-4558	198	4	estimation	estimation	NOUN
cana-4558	198	5	of	of	ADP
cana-4558	198	6	soybean	soybean	NOUN
cana-4558	198	7	plants	plant	NOUN
cana-4558	198	8	in	in	ADP
cana-4558	198	9	the	the	DET
cana-4558	198	10	field	field	NOUN
cana-4558	198	11	using	use	VERB
cana-4558	198	12	deep	deep	ADJ
cana-4558	198	13	learning	learning	NOUN
cana-4558	198	14	and	and	CCONJ
cana-4558	198	15	clustering	clustering	ADJ
cana-4558	198	16	algorithms	algorithm	NOUN
cana-4558	198	17	.	.	PUNCT
cana-4558	198	18	”	"	PUNCT
cana-4558	199	1	frontiers	frontier	NOUN
cana-4558	199	2	in	in	ADP
cana-4558	199	3	plant	plant	NOUN
cana-4558	199	4	science	science	NOUN
cana-4558	199	5	15:1501612	15:1501612	NUM
cana-4558	199	6	.	.	PUNCT
cana-4558	200	1	[	[	X
cana-4558	200	2	14]anitha	14]anitha	NUM
cana-4558	200	3	,	,	PUNCT
cana-4558	200	4	p.	p.	NOUN
cana-4558	200	5	,	,	PUNCT
cana-4558	200	6	and	and	CCONJ
cana-4558	200	7	c.	c.	PROPN
cana-4558	200	8	chandrasekar	chandrasekar	PROPN
cana-4558	200	9	.	.	PUNCT
cana-4558	201	1	"	"	PUNCT
cana-4558	201	2	energy	energy	NOUN
cana-4558	201	3	efficient	efficient	ADJ
cana-4558	201	4	routing	routing	NOUN
cana-4558	201	5	algorithm	algorithm	NOUN
cana-4558	201	6	for	for	ADP
cana-4558	201	7	zigbee	zigbee	PROPN
cana-4558	201	8	using	use	VERB
cana-4558	201	9	cross	cross	NOUN
cana-4558	201	10	layer	layer	NOUN
cana-4558	201	11	zigbee	zigbee	PROPN
cana-4558	201	12	based	base	VERB
cana-4558	201	13	routing	routing	NOUN
cana-4558	201	14	(	(	PUNCT
cana-4558	201	15	clzbrp	clzbrp	NOUN
cana-4558	201	16	)	)	PUNCT
cana-4558	201	17	protocol	protocol	NOUN
cana-4558	201	18	.	.	PUNCT
cana-4558	201	19	"	"	PUNCT
cana-4558	202	1	international	international	ADJ
cana-4558	202	2	journal	journal	NOUN
cana-4558	202	3	of	of	ADP
cana-4558	202	4	computer	computer	NOUN
cana-4558	202	5	applications	application	NOUN
cana-4558	202	6	(	(	PUNCT
cana-4558	202	7	ijca	ijca	NOUN
cana-4558	202	8	)	)	PUNCT
cana-4558	202	9	7	7	NUM
cana-4558	202	10	,	,	PUNCT
cana-4558	202	11	no	no	INTJ
cana-4558	202	12	.	.	NOUN
cana-4558	202	13	3	3	NUM
cana-4558	202	14	(	(	PUNCT
cana-4558	202	15	2011	2011	NUM
cana-4558	202	16	):	):	PUNCT
cana-4558	202	17	18	18	NUM
cana-4558	202	18	-	-	SYM
cana-4558	202	19	21	21	NUM
cana-4558	202	20	.	.	PUNCT
cana-4558	203	1	[	[	X
cana-4558	203	2	15]zaman	15]zaman	NUM
cana-4558	203	3	,	,	PUNCT
cana-4558	203	4	qamar	qamar	PROPN
cana-4558	203	5	.	.	PROPN
cana-4558	203	6	2023	2023	NUM
cana-4558	203	7	.	.	PUNCT
cana-4558	204	1	precision	precision	NOUN
cana-4558	204	2	agriculture	agriculture	NOUN
cana-4558	204	3	:	:	PUNCT
cana-4558	204	4	evolution	evolution	NOUN
cana-4558	204	5	,	,	PUNCT
cana-4558	204	6	insights	insight	NOUN
cana-4558	204	7	and	and	CCONJ
cana-4558	204	8	emerging	emerge	VERB
cana-4558	204	9	trends	trend	NOUN
cana-4558	204	10	.	.	PUNCT
cana-4558	205	1	elsevier	elsevier	NOUN
cana-4558	205	2	.	.	PUNCT
cana-4558	206	1	[	[	X
cana-4558	206	2	16]gao	16]gao	NUM
cana-4558	206	3	,	,	PUNCT
cana-4558	206	4	xing	xing	PROPN
cana-4558	206	5	,	,	PUNCT
cana-4558	206	6	zhiwen	zhiwen	PROPN
cana-4558	206	7	tang	tang	PROPN
cana-4558	206	8	,	,	PUNCT
cana-4558	206	9	yubao	yubao	PROPN
cana-4558	206	10	deng	deng	PROPN
cana-4558	206	11	,	,	PUNCT
cana-4558	206	12	shipeng	shipeng	PROPN
cana-4558	206	13	hu	hu	PROPN
cana-4558	206	14	,	,	PUNCT
cana-4558	206	15	hongmin	hongmin	PROPN
cana-4558	206	16	zhao	zhao	PROPN
cana-4558	206	17	,	,	PUNCT
cana-4558	206	18	and	and	CCONJ
cana-4558	206	19	guoxiong	guoxiong	PROPN
cana-4558	206	20	zhou	zhou	PROPN
cana-4558	206	21	.	.	PUNCT
cana-4558	207	1	2023	2023	NUM
cana-4558	207	2	.	.	PUNCT
cana-4558	208	1	“	"	PUNCT
cana-4558	208	2	hssnet	hssnet	NOUN
cana-4558	208	3	:	:	PUNCT
cana-4558	208	4	a	a	DET
cana-4558	208	5	end	end	NOUN
cana-4558	208	6	-	-	PUNCT
cana-4558	208	7	to	to	ADP
cana-4558	208	8	-	-	PUNCT
cana-4558	208	9	end	end	NOUN
cana-4558	208	10	network	network	NOUN
cana-4558	208	11	for	for	ADP
cana-4558	208	12	detecting	detect	VERB
cana-4558	208	13	tiny	tiny	ADJ
cana-4558	208	14	targets	target	NOUN
cana-4558	208	15	of	of	ADP
cana-4558	208	16	apple	apple	NOUN
cana-4558	208	17	leaf	leaf	NOUN
cana-4558	208	18	diseases	disease	NOUN
cana-4558	208	19	in	in	ADP
cana-4558	208	20	complex	complex	ADJ
cana-4558	208	21	backgrounds	background	NOUN
cana-4558	208	22	.	.	PUNCT
cana-4558	208	23	”	"	PUNCT
cana-4558	209	1	plants	plant	NOUN
cana-4558	209	2	(	(	PUNCT
cana-4558	209	3	basel	basel	PROPN
cana-4558	209	4	,	,	PUNCT
cana-4558	209	5	switzerland	switzerland	PROPN
cana-4558	209	6	)	)	PUNCT
cana-4558	209	7	12	12	NUM
cana-4558	209	8	(	(	PUNCT
cana-4558	209	9	15	15	NUM
cana-4558	209	10	)	)	PUNCT
cana-4558	209	11	.	.	PUNCT
cana-4558	210	1	https://doi.org/10.3390/plants12152806	https://doi.org/10.3390/plants12152806	PROPN
cana-4558	210	2	.	.	PUNCT
cana-4558	211	1	[	[	X
cana-4558	211	2	17]smithson	17]smithson	NUM
cana-4558	211	3	,	,	PUNCT
cana-4558	211	4	michael	michael	PROPN
cana-4558	211	5	.	.	PROPN
cana-4558	211	6	2002	2002	NUM
cana-4558	211	7	.	.	PUNCT
cana-4558	212	1	confidence	confidence	NOUN
cana-4558	212	2	intervals	interval	NOUN
cana-4558	212	3	.	.	PUNCT
cana-4558	213	1	sage	sage	NOUN
cana-4558	213	2	publications	publication	NOUN
cana-4558	213	3	.	.	PUNCT
cana-4558	214	1	[	[	X
cana-4558	214	2	18]jain	18]jain	NUM
cana-4558	214	3	,	,	PUNCT
cana-4558	214	4	sachin	sachin	PROPN
cana-4558	214	5	,	,	PUNCT
cana-4558	214	6	preeti	preeti	PROPN
cana-4558	214	7	jaidka	jaidka	PROPN
cana-4558	214	8	,	,	PUNCT
cana-4558	214	9	and	and	CCONJ
cana-4558	214	10	vishal	vishal	PROPN
cana-4558	214	11	jain	jain	PROPN
cana-4558	214	12	.	.	PUNCT
cana-4558	215	1	2023	2023	NUM
cana-4558	215	2	.	.	PUNCT
cana-4558	216	1	“	"	PUNCT
cana-4558	216	2	plant	plant	NOUN
cana-4558	216	3	leaf	leaf	NOUN
cana-4558	216	4	disease	disease	NOUN
cana-4558	216	5	classification	classification	NOUN
cana-4558	216	6	using	use	VERB
cana-4558	216	7	deep	deep	ADJ
cana-4558	216	8	learning	learning	NOUN
cana-4558	216	9	based	base	VERB
cana-4558	216	10	hybrid	hybrid	ADJ
cana-4558	216	11	approach	approach	NOUN
cana-4558	216	12	.	.	PUNCT
cana-4558	216	13	”	"	PUNCT
cana-4558	217	1	in	in	ADP
cana-4558	217	2	2023	2023	NUM
cana-4558	217	3	international	international	ADJ
cana-4558	217	4	conference	conference	NOUN
cana-4558	217	5	on	on	ADP
cana-4558	217	6	communication	communication	NOUN
cana-4558	217	7	,	,	PUNCT
cana-4558	217	8	security	security	NOUN
cana-4558	217	9	and	and	CCONJ
cana-4558	217	10	artificial	artificial	ADJ
cana-4558	217	11	intelligence	intelligence	NOUN
cana-4558	217	12	(	(	PUNCT
cana-4558	217	13	iccsai	iccsai	PROPN
cana-4558	217	14	)	)	PUNCT
cana-4558	217	15	.	.	PUNCT
cana-4558	218	1	ieee	ieee	PROPN
cana-4558	218	2	.	.	PUNCT
cana-4558	219	1	https://doi.org/10.1109/iccsai59793.2023.10421381	https://doi.org/10.1109/iccsai59793.2023.10421381	PROPN
cana-4558	219	2	.	.	PUNCT
cana-4558	220	1	http://paperpile.com/b/nhlj89/zfof	http://paperpile.com/b/nhlj89/zfof	VERB
cana-4558	220	2	http://paperpile.com/b/nhlj89/zfof	http://paperpile.com/b/nhlj89/zfof	VERB
cana-4558	220	3	http://paperpile.com/b/nhlj89/zfof	http://paperpile.com/b/nhlj89/zfof	VERB
cana-4558	220	4	http://paperpile.com/b/nhlj89/dil2	http://paperpile.com/b/nhlj89/dil2	VERB
cana-4558	220	5	http://paperpile.com/b/nhlj89/dil2	http://paperpile.com/b/nhlj89/dil2	VERB
cana-4558	220	6	http://paperpile.com/b/nhlj89/duvk	http://paperpile.com/b/nhlj89/duvk	NOUN
cana-4558	220	7	http://paperpile.com/b/nhlj89/duvk	http://paperpile.com/b/nhlj89/duvk	PROPN
cana-4558	220	8	http://paperpile.com/b/nhlj89/nttc	http://paperpile.com/b/nhlj89/nttc	PROPN
cana-4558	220	9	https://doi.org/10.3390/plants12152806	https://doi.org/10.3390/plants12152806	PROPN
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cana-4558	220	11	.	.	PUNCT
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cana-4558	220	13	.	.	PUNCT
cana-4558	220	14	https://d.docs.live.net/a0d62f4249fa7973/documents/jain,%20sachin,%20preeti%20jaidka,%20and%20vishal%20jain.%202023	https://d.docs.live.net/a0d62f4249fa7973/documents/jain,%20sachin,%20preeti%20jaidka,%20and%20vishal%20jain.%202023	PROPN
cana-4558	220	15	.	.	PUNCT
cana-4558	221	1	https://d.docs.live.net/a0d62f4249fa7973/documents/jain,%20sachin,%20preeti%20jaidka,%20and%20vishal%20jain.%202023	https://d.docs.live.net/a0d62f4249fa7973/documents/jain,%20sachin,%20preeti%20jaidka,%20and%20vishal%20jain.%202023	PROPN
cana-4558	221	2	.	.	PUNCT
cana-4558	222	1	http://dx.doi.org/10.1109/iccsai59793.2023.10421381	http://dx.doi.org/10.1109/iccsai59793.2023.10421381	PROPN
cana-4558	222	2	http://paperpile.com/b/nhlj89/k1oq	http://paperpile.com/b/nhlj89/k1oq	PROPN
cana-4558	222	3	communications	communication	NOUN
cana-4558	222	4	on	on	ADP
cana-4558	222	5	applied	apply	VERB
cana-4558	222	6	nonlinear	nonlinear	ADJ
cana-4558	222	7	analysis	analysis	NOUN
cana-4558	222	8	issn	issn	NOUN
cana-4558	222	9	:	:	PUNCT
cana-4558	222	10	1074	1074	NUM
cana-4558	222	11	-	-	PUNCT
cana-4558	222	12	133x	133x	NUM
cana-4558	222	13	vol	vol	NOUN
cana-4558	222	14	32	32	NUM
cana-4558	222	15	no	no	NOUN
cana-4558	222	16	.	.	PUNCT
cana-4558	223	1	9s	9s	NUM
cana-4558	223	2	(	(	PUNCT
cana-4558	223	3	2025	2025	NUM
cana-4558	223	4	)	)	PUNCT
cana-4558	223	5	2540	2540	NUM
cana-4558	223	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4558	224	1	[	[	X
cana-4558	224	2	19]taylor	19]taylor	NUM
cana-4558	224	3	,	,	PUNCT
cana-4558	224	4	john	john	PROPN
cana-4558	224	5	k.	k.	PROPN
cana-4558	224	6	,	,	PUNCT
cana-4558	224	7	and	and	CCONJ
cana-4558	224	8	cheryl	cheryl	PROPN
cana-4558	224	9	cihon	cihon	PROPN
cana-4558	224	10	.	.	PUNCT
cana-4558	225	1	2004	2004	NUM
cana-4558	225	2	.	.	PUNCT
cana-4558	226	1	statistical	statistical	ADJ
cana-4558	226	2	techniques	technique	NOUN
cana-4558	226	3	for	for	ADP
cana-4558	226	4	data	datum	NOUN
cana-4558	226	5	analysis	analysis	NOUN
cana-4558	226	6	.	.	PUNCT
cana-4558	227	1	crc	crc	NOUN
cana-4558	227	2	press	press	PROPN
cana-4558	227	3	.	.	PUNCT
cana-4558	228	1	[	[	X
cana-4558	228	2	20]zhang	20]zhang	NUM
cana-4558	228	3	,	,	PUNCT
cana-4558	228	4	qin	qin	PROPN
cana-4558	228	5	.	.	PROPN
cana-4558	228	6	2015	2015	NUM
cana-4558	228	7	.	.	PUNCT
cana-4558	229	1	precision	precision	NOUN
cana-4558	229	2	agriculture	agriculture	NOUN
cana-4558	229	3	technology	technology	NOUN
cana-4558	229	4	for	for	ADP
cana-4558	229	5	crop	crop	NOUN
cana-4558	229	6	farming	farming	NOUN
cana-4558	229	7	.	.	PUNCT
cana-4558	230	1	crc	crc	PROPN
cana-4558	230	2	press	press	PROPN
cana-4558	230	3	.	.	PUNCT
cana-4558	231	1	[	[	X
cana-4558	231	2	21]h	21]h	NUM
cana-4558	231	3	.	.	PUNCT
cana-4558	231	4	e.	e.	PROPN
cana-4558	231	5	david	david	PROPN
cana-4558	231	6	,	,	PUNCT
cana-4558	231	7	k.	k.	PROPN
cana-4558	231	8	ramalakshmi	ramalakshmi	PROPN
cana-4558	231	9	,	,	PUNCT
cana-4558	231	10	h.	h.	NOUN
cana-4558	231	11	gunasekaran	gunasekaran	NOUN
cana-4558	231	12	and	and	CCONJ
cana-4558	231	13	r.	r.	PROPN
cana-4558	231	14	venkatesan	venkatesan	PROPN
cana-4558	231	15	,	,	PUNCT
cana-4558	231	16	"	"	PUNCT
cana-4558	231	17	literature	literature	NOUN
cana-4558	231	18	review	review	NOUN
cana-4558	231	19	of	of	ADP
cana-4558	231	20	disease	disease	NOUN
cana-4558	231	21	detection	detection	NOUN
cana-4558	231	22	in	in	ADP
cana-4558	231	23	tomato	tomato	NOUN
cana-4558	231	24	leaf	leaf	NOUN
cana-4558	231	25	using	use	VERB
cana-4558	231	26	deep	deep	ADJ
cana-4558	231	27	learning	learning	NOUN
cana-4558	231	28	techniques	technique	NOUN
cana-4558	231	29	,	,	PUNCT
cana-4558	231	30	"	"	PUNCT
cana-4558	231	31	2021	2021	NUM
cana-4558	231	32	7th	7th	ADJ
cana-4558	231	33	international	international	ADJ
cana-4558	231	34	conference	conference	NOUN
cana-4558	231	35	on	on	ADP
cana-4558	231	36	advanced	advanced	ADJ
cana-4558	231	37	computing	computing	NOUN
cana-4558	231	38	and	and	CCONJ
cana-4558	231	39	communication	communication	NOUN
cana-4558	231	40	systems	system	NOUN
cana-4558	231	41	(	(	PUNCT
cana-4558	231	42	icaccs	icaccs	NOUN
cana-4558	231	43	)	)	PUNCT
cana-4558	231	44	,	,	PUNCT
cana-4558	231	45	coimbatore	coimbatore	PROPN
cana-4558	231	46	,	,	PUNCT
cana-4558	231	47	india	india	PROPN
cana-4558	231	48	,	,	PUNCT
cana-4558	231	49	2021	2021	NUM
cana-4558	231	50	,	,	PUNCT
cana-4558	231	51	pp	pp	ADP
cana-4558	231	52	.	.	PUNCT
cana-4558	231	53	274	274	NUM
cana-4558	231	54	-	-	SYM
cana-4558	231	55	278	278	NUM
cana-4558	231	56	,	,	PUNCT
cana-4558	231	57	doi	doi	NOUN
cana-4558	231	58	:	:	PUNCT
cana-4558	231	59	10.1109	10.1109	NUM
cana-4558	231	60	/	/	SYM
cana-4558	231	61	icaccs51430.2021.9441714	icaccs51430.2021.9441714	NOUN
cana-4558	231	62	.	.	PUNCT
cana-4558	232	1	[	[	X
cana-4558	232	2	22]sun	22]sun	NUM
cana-4558	232	3	,	,	PUNCT
cana-4558	232	4	yan	yan	PROPN
cana-4558	232	5	,	,	PUNCT
cana-4558	232	6	chen	chen	PROPN
cana-4558	232	7	fei	fei	PROPN
cana-4558	232	8	,	,	PUNCT
cana-4558	232	9	xiaotuo	xiaotuo	PROPN
cana-4558	232	10	wang	wang	PROPN
cana-4558	232	11	,	,	PUNCT
cana-4558	232	12	bin	bin	PROPN
cana-4558	232	13	tian	tian	PROPN
cana-4558	232	14	,	,	PUNCT
cana-4558	232	15	chenggong	chenggong	PROPN
cana-4558	232	16	ni	ni	PROPN
cana-4558	232	17	,	,	PUNCT
cana-4558	232	18	and	and	CCONJ
cana-4558	232	19	qi	qi	PROPN
cana-4558	232	20	chen	chen	PROPN
cana-4558	232	21	.	.	PUNCT
cana-4558	233	1	2023	2023	NUM
cana-4558	233	2	.	.	PUNCT
cana-4558	234	1	“	"	PUNCT
cana-4558	234	2	crop	crop	NOUN
cana-4558	234	3	disease	disease	NOUN
cana-4558	234	4	identification	identification	NOUN
cana-4558	234	5	based	base	VERB
cana-4558	234	6	on	on	ADP
cana-4558	234	7	deep	deep	ADJ
cana-4558	234	8	learning	learning	NOUN
cana-4558	234	9	.	.	PUNCT
cana-4558	234	10	”	"	PUNCT
cana-4558	235	1	in	in	ADP
cana-4558	235	2	2023	2023	NUM
cana-4558	235	3	ieee	ieee	NOUN
cana-4558	235	4	11th	11th	NOUN
cana-4558	235	5	joint	joint	ADJ
cana-4558	235	6	international	international	ADJ
cana-4558	235	7	information	information	NOUN
cana-4558	235	8	technology	technology	NOUN
cana-4558	235	9	and	and	CCONJ
cana-4558	235	10	artificial	artificial	ADJ
cana-4558	235	11	intelligence	intelligence	NOUN
cana-4558	235	12	conference	conference	NOUN
cana-4558	235	13	(	(	PUNCT
cana-4558	235	14	itaic	itaic	PROPN
cana-4558	235	15	)	)	PUNCT
cana-4558	235	16	.	.	PUNCT
cana-4558	236	1	ieee	ieee	PROPN
cana-4558	236	2	.	.	PUNCT
cana-4558	237	1	https://doi.org/10.1109/itaic58329.2023.10408788	https://doi.org/10.1109/itaic58329.2023.10408788	PROPN
cana-4558	237	2	.	.	PUNCT
cana-4558	238	1	[	[	X
cana-4558	238	2	23]anitha	23]anitha	NUM
cana-4558	238	3	,	,	PUNCT
cana-4558	238	4	p.	p.	NOUN
cana-4558	238	5	,	,	PUNCT
cana-4558	238	6	g.	g.	PROPN
cana-4558	238	7	n.	n.	PROPN
cana-4558	238	8	pavithra	pavithra	PROPN
cana-4558	238	9	,	,	PUNCT
cana-4558	238	10	and	and	CCONJ
cana-4558	238	11	p.	p.	PROPN
cana-4558	238	12	s.	s.	PROPN
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cana-4558	238	14	.	.	PUNCT
cana-4558	239	1	"	"	PUNCT
cana-4558	239	2	an	an	DET
cana-4558	239	3	improved	improved	ADJ
cana-4558	239	4	security	security	NOUN
cana-4558	239	5	mechanism	mechanism	NOUN
cana-4558	239	6	for	for	ADP
cana-4558	239	7	highthroughput	highthroughput	VERB
cana-4558	239	8	multicast	multicast	ADJ
cana-4558	239	9	routing	routing	NOUN
cana-4558	239	10	in	in	ADP
cana-4558	239	11	wireless	wireless	ADJ
cana-4558	239	12	mesh	mesh	NOUN
cana-4558	239	13	networks	network	NOUN
cana-4558	239	14	against	against	ADP
cana-4558	239	15	sybil	sybil	NOUN
cana-4558	239	16	attack	attack	NOUN
cana-4558	239	17	.	.	PUNCT
cana-4558	239	18	"	"	PUNCT
cana-4558	240	1	international	international	ADJ
cana-4558	240	2	conference	conference	NOUN
cana-4558	240	3	on	on	ADP
cana-4558	240	4	pattern	pattern	NOUN
cana-4558	240	5	recognition	recognition	NOUN
cana-4558	240	6	,	,	PUNCT
cana-4558	240	7	informatics	informatics	PROPN
cana-4558	240	8	and	and	CCONJ
cana-4558	240	9	medical	medical	ADJ
cana-4558	240	10	engineering	engineering	NOUN
cana-4558	240	11	(	(	PUNCT
cana-4558	240	12	prime2012	prime2012	PROPN
cana-4558	240	13	)	)	PUNCT
cana-4558	240	14	.	.	PUNCT
cana-4558	241	1	ieee	ieee	PROPN
cana-4558	241	2	,	,	PUNCT
cana-4558	241	3	2012	2012	NUM
cana-4558	241	4	.	.	PUNCT
cana-4558	242	1	[	[	X
cana-4558	242	2	24]kumar	24]kumar	NUM
cana-4558	242	3	,	,	PUNCT
cana-4558	242	4	akhil	akhil	NOUN
cana-4558	242	5	,	,	PUNCT
cana-4558	242	6	arvind	arvind	PROPN
cana-4558	242	7	kalia	kalia	PROPN
cana-4558	242	8	,	,	PUNCT
cana-4558	242	9	akashdeep	akashdeep	PROPN
cana-4558	242	10	sharma	sharma	PROPN
cana-4558	242	11	,	,	PUNCT
cana-4558	242	12	and	and	CCONJ
cana-4558	242	13	manisha	manisha	PROPN
cana-4558	242	14	kaushal	kaushal	PROPN
cana-4558	242	15	.	.	PUNCT
cana-4558	243	1	2023	2023	NUM
cana-4558	243	2	.	.	PUNCT
cana-4558	244	1	“	"	PUNCT
cana-4558	244	2	a	a	DET
cana-4558	244	3	hybrid	hybrid	ADJ
cana-4558	244	4	tiny	tiny	ADJ
cana-4558	244	5	yolo	yolo	ADJ
cana-4558	244	6	v4	v4	PROPN
cana-4558	244	7	-	-	PUNCT
cana-4558	244	8	spp	spp	NOUN
cana-4558	244	9	module	module	NOUN
cana-4558	244	10	based	base	VERB
cana-4558	244	11	improved	improve	VERB
cana-4558	244	12	face	face	NOUN
cana-4558	244	13	mask	mask	NOUN
cana-4558	244	14	detection	detection	NOUN
cana-4558	244	15	vision	vision	NOUN
cana-4558	244	16	system	system	NOUN
cana-4558	244	17	.	.	PUNCT
cana-4558	244	18	”	"	PUNCT
cana-4558	245	1	journal	journal	NOUN
cana-4558	245	2	of	of	ADP
cana-4558	245	3	ambient	ambient	ADJ
cana-4558	245	4	intelligence	intelligence	NOUN
cana-4558	245	5	and	and	CCONJ
cana-4558	245	6	humanized	humanize	VERB
cana-4558	245	7	computing	compute	VERB
cana-4558	245	8	14	14	NUM
cana-4558	245	9	(	(	PUNCT
cana-4558	245	10	6	6	NUM
cana-4558	245	11	):	):	PUNCT
cana-4558	245	12	6783–96	6783–96	NUM
cana-4558	245	13	.	.	PUNCT
cana-4558	246	1	[	[	X
cana-4558	246	2	25]kanisha	25]kanisha	NUM
cana-4558	246	3	,	,	PUNCT
cana-4558	246	4	b.	b.	PROPN
cana-4558	246	5	,	,	PUNCT
cana-4558	246	6	v.	v.	ADP
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cana-4558	246	8	,	,	PUNCT
cana-4558	246	9	m.	m.	NOUN
cana-4558	246	10	baskar	baskar	PROPN
cana-4558	246	11	,	,	PUNCT
cana-4558	246	12	k.	k.	PROPN
cana-4558	246	13	vijaya	vijaya	PROPN
cana-4558	246	14	,	,	PUNCT
cana-4558	246	15	and	and	CCONJ
cana-4558	246	16	p.	p.	PROPN
cana-4558	246	17	kalyanasundaram	kalyanasundaram	PROPN
cana-4558	246	18	.	.	PUNCT
cana-4558	247	1	smart	smart	ADJ
cana-4558	247	2	communication	communication	NOUN
cana-4558	247	3	using	use	VERB
cana-4558	247	4	tri	tri	ADJ
cana-4558	247	5	-	-	ADJ
cana-4558	247	6	spectral	spectral	ADJ
cana-4558	247	7	sign	sign	NOUN
cana-4558	247	8	recognition	recognition	NOUN
cana-4558	247	9	for	for	ADP
cana-4558	247	10	hearing	hearing	NOUN
cana-4558	247	11	-	-	PUNCT
cana-4558	247	12	impaired	impair	VERB
cana-4558	247	13	people	people	NOUN
cana-4558	247	14	.	.	PUNCT
cana-4558	247	15	"	"	PUNCT
cana-4558	248	1	the	the	DET
cana-4558	248	2	journal	journal	NOUN
cana-4558	248	3	of	of	ADP
cana-4558	248	4	supercomputing	supercompute	VERB
cana-4558	248	5	78	78	NUM
cana-4558	248	6	,	,	PUNCT
cana-4558	248	7	no	no	INTJ
cana-4558	248	8	.	.	NOUN
cana-4558	248	9	2	2	NUM
cana-4558	248	10	(	(	PUNCT
cana-4558	248	11	2022	2022	NUM
cana-4558	248	12	):	):	PUNCT
cana-4558	248	13	2651	2651	NUM
cana-4558	248	14	-	-	SYM
cana-4558	248	15	2664	2664	NUM
cana-4558	248	16	.	.	PUNCT
cana-4558	249	1	[	[	X
cana-4558	249	2	26]burdick	26]burdick	NUM
cana-4558	249	3	,	,	PUNCT
cana-4558	249	4	richard	richard	PROPN
cana-4558	249	5	k.	k.	PROPN
cana-4558	249	6	,	,	PUNCT
cana-4558	249	7	and	and	CCONJ
cana-4558	249	8	franklin	franklin	PROPN
cana-4558	249	9	a.	a.	NOUN
cana-4558	249	10	graybill	graybill	PROPN
cana-4558	249	11	.	.	PUNCT
cana-4558	250	1	1992	1992	NUM
cana-4558	250	2	.	.	PUNCT
cana-4558	251	1	confidence	confidence	NOUN
cana-4558	251	2	intervals	interval	NOUN
cana-4558	251	3	on	on	ADP
cana-4558	251	4	variance	variance	NOUN
cana-4558	251	5	components	component	NOUN
cana-4558	251	6	.	.	PUNCT
cana-4558	252	1	crc	crc	PROPN
cana-4558	252	2	press	press	PROPN
cana-4558	252	3	.	.	PUNCT
cana-4558	253	1	[	[	X
cana-4558	253	2	27]lee	27]lee	NUM
cana-4558	253	3	,	,	PUNCT
cana-4558	253	4	sue	sue	PROPN
cana-4558	253	5	han	han	PROPN
cana-4558	253	6	,	,	PUNCT
cana-4558	253	7	herve	herve	PROPN
cana-4558	253	8	goeau	goeau	PROPN
cana-4558	253	9	,	,	PUNCT
cana-4558	253	10	pierre	pierre	NOUN
cana-4558	253	11	bonnet	bonnet	NOUN
cana-4558	253	12	,	,	PUNCT
cana-4558	253	13	and	and	CCONJ
cana-4558	253	14	alexis	alexis	PROPN
cana-4558	253	15	joly	joly	PROPN
cana-4558	253	16	.	.	PUNCT
cana-4558	253	17	2021	2021	NUM
cana-4558	253	18	.	.	PUNCT
cana-4558	254	1	“	"	PUNCT
cana-4558	254	2	conditional	conditional	ADJ
cana-4558	254	3	multi	multi	ADJ
cana-4558	254	4	-	-	NOUN
cana-4558	254	5	task	task	ADJ
cana-4558	254	6	learning	learning	NOUN
cana-4558	254	7	for	for	ADP
cana-4558	254	8	plant	plant	NOUN
cana-4558	254	9	disease	disease	NOUN
cana-4558	254	10	identification	identification	NOUN
cana-4558	254	11	.	.	PUNCT
cana-4558	254	12	”	"	PUNCT
cana-4558	255	1	in	in	ADP
cana-4558	255	2	2020	2020	NUM
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cana-4558	255	4	international	international	ADJ
cana-4558	255	5	conference	conference	NOUN
cana-4558	255	6	on	on	ADP
cana-4558	255	7	pattern	pattern	NOUN
cana-4558	255	8	recognition	recognition	NOUN
cana-4558	255	9	(	(	PUNCT
cana-4558	255	10	icpr	icpr	PROPN
cana-4558	255	11	)	)	PUNCT
cana-4558	255	12	.	.	PUNCT
cana-4558	256	1	ieee	ieee	PROPN
cana-4558	256	2	.	.	PUNCT
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cana-4558	257	2	.	.	PUNCT
cana-4558	258	1	[	[	X
cana-4558	258	2	28]revathi	28]revathi	NUM
cana-4558	258	3	,	,	PUNCT
cana-4558	258	4	p.	p.	NOUN
cana-4558	258	5	,	,	PUNCT
cana-4558	258	6	and	and	CCONJ
cana-4558	258	7	m.	m.	NOUN
cana-4558	258	8	hemalatha	hemalatha	NOUN
cana-4558	258	9	.	.	PUNCT
cana-4558	259	1	2012	2012	NUM
cana-4558	259	2	.	.	PUNCT
cana-4558	260	1	“	"	PUNCT
cana-4558	260	2	advance	advance	NOUN
cana-4558	260	3	computing	compute	VERB
cana-4558	260	4	enrichment	enrichment	NOUN
cana-4558	260	5	evaluation	evaluation	NOUN
cana-4558	260	6	of	of	ADP
cana-4558	260	7	cotton	cotton	NOUN
cana-4558	260	8	leaf	leaf	NOUN
cana-4558	260	9	spot	spot	NOUN
cana-4558	260	10	disease	disease	NOUN
cana-4558	260	11	detection	detection	NOUN
cana-4558	260	12	using	use	VERB
cana-4558	260	13	image	image	NOUN
cana-4558	260	14	edge	edge	NOUN
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cana-4558	261	2	2012	2012	NUM
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cana-4558	261	4	international	international	ADJ
cana-4558	261	5	conference	conference	NOUN
cana-4558	261	6	on	on	ADP
cana-4558	261	7	computing	computing	NOUN
cana-4558	261	8	,	,	PUNCT
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cana-4558	261	10	and	and	CCONJ
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cana-4558	261	16	.	.	PUNCT
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