id	sid	tid	token	lemma	pos
cana-3107	1	1	communications	communication	NOUN
cana-3107	1	2	on	on	ADP
cana-3107	1	3	applied	apply	VERB
cana-3107	1	4	nonlinear	nonlinear	ADJ
cana-3107	1	5	analysis	analysis	NOUN
cana-3107	1	6	issn	issn	NOUN
cana-3107	1	7	:	:	PUNCT
cana-3107	1	8	1074	1074	NUM
cana-3107	1	9	-	-	PUNCT
cana-3107	1	10	133x	133x	NUM
cana-3107	1	11	vol	vol	NOUN
cana-3107	1	12	32	32	NUM
cana-3107	1	13	no	no	NOUN
cana-3107	1	14	.	.	PUNCT
cana-3107	2	1	5s	5s	NUM
cana-3107	2	2	(	(	PUNCT
cana-3107	2	3	2025	2025	NUM
cana-3107	2	4	)	)	PUNCT
cana-3107	2	5	361	361	NUM
cana-3107	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	2	7	insect	insect	NOUN
cana-3107	2	8	identification	identification	NOUN
cana-3107	2	9	system	system	NOUN
cana-3107	2	10	using	use	VERB
cana-3107	2	11	faster	fast	ADJ
cana-3107	2	12	rcnn	rcnn	NOUN
cana-3107	2	13	with	with	ADP
cana-3107	2	14	adam	adam	PROPN
cana-3107	2	15	optimizer	optimizer	NOUN
cana-3107	2	16	segmentation	segmentation	NOUN
cana-3107	2	17	model	model	PROPN
cana-3107	2	18	r.padmavathi1	r.padmavathi1	PROPN
cana-3107	2	19	,	,	PUNCT
cana-3107	2	20	dr	dr	PROPN
cana-3107	2	21	.	.	PROPN
cana-3107	2	22	k.kavitha2	k.kavitha2	PROPN
cana-3107	2	23	research	research	PROPN
cana-3107	2	24	scholar	scholar	NOUN
cana-3107	2	25	,	,	PUNCT
cana-3107	2	26	department	department	NOUN
cana-3107	2	27	of	of	ADP
cana-3107	2	28	computer	computer	NOUN
cana-3107	2	29	science	science	NOUN
cana-3107	2	30	.	.	PUNCT
cana-3107	3	1	mother	mother	NOUN
cana-3107	3	2	teresa	teresa	PROPN
cana-3107	3	3	women	woman	NOUN
cana-3107	3	4	's	's	PART
cana-3107	3	5	university	university	NOUN
cana-3107	3	6	,	,	PUNCT
cana-3107	3	7	kodaikanal	kodaikanal	ADJ
cana-3107	3	8	assistant	assistant	NOUN
cana-3107	3	9	professor	professor	NOUN
cana-3107	3	10	,	,	PUNCT
cana-3107	3	11	agurchad	agurchad	VERB
cana-3107	3	12	manmull	manmull	PROPN
cana-3107	3	13	jain	jain	PROPN
cana-3107	3	14	college	college	PROPN
cana-3107	3	15	,	,	PUNCT
cana-3107	3	16	meenambakkam	meenambakkam	NOUN
cana-3107	3	17	.	.	PUNCT
cana-3107	4	1	padmabaviya11@gmail.com	padmabaviya11@gmail.com	NOUN
cana-3107	4	2	,	,	PUNCT
cana-3107	4	3	padmavathi.r@amjaincollege.edu.in	padmavathi.r@amjaincollege.edu.in	PROPN
cana-3107	4	4	.	.	PUNCT
cana-3107	5	1	assistant	assistant	PROPN
cana-3107	5	2	professor	professor	NOUN
cana-3107	5	3	,	,	PUNCT
cana-3107	5	4	department	department	NOUN
cana-3107	5	5	of	of	ADP
cana-3107	5	6	computer	computer	NOUN
cana-3107	5	7	science	science	NOUN
cana-3107	5	8	,	,	PUNCT
cana-3107	5	9	mother	mother	NOUN
cana-3107	5	10	teresa	teresa	PROPN
cana-3107	5	11	women	woman	NOUN
cana-3107	5	12	's	's	PART
cana-3107	5	13	university	university	NOUN
cana-3107	5	14	,	,	PUNCT
cana-3107	5	15	kodaikanal	kodaikanal	PROPN
cana-3107	5	16	.	.	PUNCT
cana-3107	6	1	kavitha.urc@gmail.com	kavitha.urc@gmail.com	PROPN
cana-3107	6	2	.	.	PUNCT
cana-3107	7	1	article	article	PROPN
cana-3107	7	2	history	history	NOUN
cana-3107	7	3	:	:	PUNCT
cana-3107	7	4	received	receive	VERB
cana-3107	7	5	:	:	PUNCT
cana-3107	7	6	10	10	NUM
cana-3107	7	7	-	-	SYM
cana-3107	7	8	10	10	NUM
cana-3107	7	9	-	-	PUNCT
cana-3107	7	10	2024	2024	NUM
cana-3107	7	11	revised	revise	VERB
cana-3107	7	12	:	:	PUNCT
cana-3107	7	13	27	27	NUM
cana-3107	7	14	-	-	SYM
cana-3107	7	15	11	11	NUM
cana-3107	7	16	-	-	PUNCT
cana-3107	7	17	2024	2024	NUM
cana-3107	7	18	accepted	accept	VERB
cana-3107	7	19	:	:	PUNCT
cana-3107	7	20	08	08	NUM
cana-3107	7	21	-	-	SYM
cana-3107	7	22	12	12	NUM
cana-3107	7	23	-	-	PUNCT
cana-3107	7	24	2024	2024	NUM
cana-3107	7	25	abstract	abstract	NOUN
cana-3107	7	26	:	:	PUNCT
cana-3107	7	27	researchers	researcher	NOUN
cana-3107	7	28	have	have	AUX
cana-3107	7	29	been	be	AUX
cana-3107	7	30	more	more	ADV
cana-3107	7	31	interested	interested	ADJ
cana-3107	7	32	in	in	ADP
cana-3107	7	33	automated	automate	VERB
cana-3107	7	34	insect	insect	NOUN
cana-3107	7	35	recognition	recognition	NOUN
cana-3107	7	36	in	in	ADP
cana-3107	7	37	recent	recent	ADJ
cana-3107	7	38	years	year	NOUN
cana-3107	7	39	,	,	PUNCT
cana-3107	7	40	and	and	CCONJ
cana-3107	7	41	many	many	ADJ
cana-3107	7	42	different	different	ADJ
cana-3107	7	43	approaches	approach	NOUN
cana-3107	7	44	have	have	AUX
cana-3107	7	45	been	be	AUX
cana-3107	7	46	taken	take	VERB
cana-3107	7	47	to	to	ADP
cana-3107	7	48	studying	study	VERB
cana-3107	7	49	the	the	DET
cana-3107	7	50	practical	practical	ADJ
cana-3107	7	51	implications	implication	NOUN
cana-3107	7	52	of	of	ADP
cana-3107	7	53	this	this	DET
cana-3107	7	54	field	field	NOUN
cana-3107	7	55	.	.	PUNCT
cana-3107	8	1	when	when	SCONJ
cana-3107	8	2	it	it	PRON
cana-3107	8	3	comes	come	VERB
cana-3107	8	4	to	to	ADP
cana-3107	8	5	designing	design	VERB
cana-3107	8	6	pest	pest	NOUN
cana-3107	8	7	management	management	NOUN
cana-3107	8	8	tactics	tactic	NOUN
cana-3107	8	9	and	and	CCONJ
cana-3107	8	10	safeguarding	safeguard	VERB
cana-3107	8	11	beneficial	beneficial	ADJ
cana-3107	8	12	insects	insect	NOUN
cana-3107	8	13	,	,	PUNCT
cana-3107	8	14	accurate	accurate	ADJ
cana-3107	8	15	identification	identification	NOUN
cana-3107	8	16	of	of	ADP
cana-3107	8	17	the	the	DET
cana-3107	8	18	insects	insect	NOUN
cana-3107	8	19	at	at	ADP
cana-3107	8	20	play	play	NOUN
cana-3107	8	21	is	be	AUX
cana-3107	8	22	crucial	crucial	ADJ
cana-3107	8	23	.	.	PUNCT
cana-3107	9	1	insect	insect	NOUN
cana-3107	9	2	target	target	NOUN
cana-3107	9	3	detection	detection	NOUN
cana-3107	9	4	has	have	AUX
cana-3107	9	5	always	always	ADV
cana-3107	9	6	relied	rely	VERB
cana-3107	9	7	heavily	heavily	ADV
cana-3107	9	8	on	on	ADP
cana-3107	9	9	artificial	artificial	ADJ
cana-3107	9	10	identification	identification	NOUN
cana-3107	9	11	methods	method	NOUN
cana-3107	9	12	;	;	PUNCT
cana-3107	9	13	however	however	ADV
cana-3107	9	14	,	,	PUNCT
cana-3107	9	15	deep	deep	ADJ
cana-3107	9	16	learning	learning	NOUN
cana-3107	9	17	can	can	AUX
cana-3107	9	18	automatically	automatically	ADV
cana-3107	9	19	extract	extract	VERB
cana-3107	9	20	characteristics	characteristic	NOUN
cana-3107	9	21	for	for	ADP
cana-3107	9	22	detection	detection	NOUN
cana-3107	9	23	,	,	PUNCT
cana-3107	9	24	solving	solve	VERB
cana-3107	9	25	the	the	DET
cana-3107	9	26	issue	issue	NOUN
cana-3107	9	27	of	of	ADP
cana-3107	9	28	poor	poor	ADJ
cana-3107	9	29	detection	detection	NOUN
cana-3107	9	30	accuracy	accuracy	NOUN
cana-3107	9	31	due	due	ADP
cana-3107	9	32	to	to	ADP
cana-3107	9	33	subjective	subjective	ADJ
cana-3107	9	34	considerations	consideration	NOUN
cana-3107	9	35	.	.	PUNCT
cana-3107	10	1	here	here	ADV
cana-3107	10	2	,	,	PUNCT
cana-3107	10	3	we	we	PRON
cana-3107	10	4	present	present	VERB
cana-3107	10	5	our	our	PRON
cana-3107	10	6	work	work	NOUN
cana-3107	10	7	on	on	ADP
cana-3107	10	8	an	an	DET
cana-3107	10	9	improved	improved	ADJ
cana-3107	10	10	method	method	NOUN
cana-3107	10	11	of	of	ADP
cana-3107	10	12	insect	insect	NOUN
cana-3107	10	13	identification	identification	NOUN
cana-3107	10	14	using	use	VERB
cana-3107	10	15	segmentation	segmentation	NOUN
cana-3107	10	16	-	-	PUNCT
cana-3107	10	17	based	base	VERB
cana-3107	10	18	visual	visual	ADJ
cana-3107	10	19	cues	cue	NOUN
cana-3107	10	20	.	.	PUNCT
cana-3107	11	1	the	the	DET
cana-3107	11	2	bug	bug	NOUN
cana-3107	11	3	images	image	NOUN
cana-3107	11	4	were	be	AUX
cana-3107	11	5	segmented	segment	VERB
cana-3107	11	6	using	use	VERB
cana-3107	11	7	faster	fast	ADJ
cana-3107	11	8	rcnn	rcnn	NOUN
cana-3107	11	9	with	with	ADP
cana-3107	11	10	the	the	DET
cana-3107	11	11	adam	adam	PROPN
cana-3107	11	12	optimizer	optimizer	NOUN
cana-3107	11	13	,	,	PUNCT
cana-3107	11	14	and	and	CCONJ
cana-3107	11	15	the	the	DET
cana-3107	11	16	features	feature	NOUN
cana-3107	11	17	were	be	AUX
cana-3107	11	18	extracted	extract	VERB
cana-3107	11	19	using	use	VERB
cana-3107	11	20	inceptionv3	inceptionv3	NOUN
cana-3107	11	21	.	.	PUNCT
cana-3107	12	1	the	the	DET
cana-3107	12	2	findings	finding	NOUN
cana-3107	12	3	show	show	VERB
cana-3107	12	4	that	that	SCONJ
cana-3107	12	5	our	our	PRON
cana-3107	12	6	suggested	suggest	VERB
cana-3107	12	7	model	model	NOUN
cana-3107	12	8	outperformed	outperform	VERB
cana-3107	12	9	competing	compete	VERB
cana-3107	12	10	methods	method	NOUN
cana-3107	12	11	in	in	ADP
cana-3107	12	12	terms	term	NOUN
cana-3107	12	13	of	of	ADP
cana-3107	12	14	accuracy	accuracy	NOUN
cana-3107	12	15	and	and	CCONJ
cana-3107	12	16	performance	performance	NOUN
cana-3107	12	17	.	.	PUNCT
cana-3107	13	1	keywords	keyword	NOUN
cana-3107	13	2	:	:	PUNCT
cana-3107	13	3	image	image	NOUN
cana-3107	13	4	segmentation	segmentation	NOUN
cana-3107	13	5	,	,	PUNCT
cana-3107	13	6	preprocessing	preprocesse	VERB
cana-3107	13	7	.	.	PUNCT
cana-3107	14	1	faster	fast	ADJ
cana-3107	14	2	rcnn	rcnn	PROPN
cana-3107	14	3	,	,	PUNCT
cana-3107	14	4	adam	adam	PROPN
cana-3107	14	5	optimizer	optimizer	NOUN
cana-3107	14	6	,	,	PUNCT
cana-3107	14	7	inceptionv3	inceptionv3	NOUN
cana-3107	14	8	1	1	NUM
cana-3107	14	9	.	.	X
cana-3107	14	10	introduction	introduction	NOUN
cana-3107	14	11	approximately	approximately	ADV
cana-3107	14	12	75	75	NUM
cana-3107	14	13	%	%	NOUN
cana-3107	14	14	of	of	ADP
cana-3107	14	15	all	all	DET
cana-3107	14	16	animal	animal	NOUN
cana-3107	14	17	species	specie	NOUN
cana-3107	14	18	may	may	AUX
cana-3107	14	19	be	be	AUX
cana-3107	14	20	found	find	VERB
cana-3107	14	21	in	in	ADP
cana-3107	14	22	the	the	DET
cana-3107	14	23	insect	insect	NOUN
cana-3107	14	24	kingdom	kingdom	NOUN
cana-3107	14	25	,	,	PUNCT
cana-3107	14	26	making	make	VERB
cana-3107	14	27	them	they	PRON
cana-3107	14	28	a	a	DET
cana-3107	14	29	massive	massive	ADJ
cana-3107	14	30	and	and	CCONJ
cana-3107	14	31	pivotal	pivotal	ADJ
cana-3107	14	32	part	part	NOUN
cana-3107	14	33	of	of	ADP
cana-3107	14	34	the	the	DET
cana-3107	14	35	natural	natural	ADJ
cana-3107	14	36	food	food	NOUN
cana-3107	14	37	chain	chain	NOUN
cana-3107	14	38	.	.	PUNCT
cana-3107	15	1	since	since	SCONJ
cana-3107	15	2	most	most	ADJ
cana-3107	15	3	insects	insect	NOUN
cana-3107	15	4	eat	eat	VERB
cana-3107	15	5	plants	plant	NOUN
cana-3107	15	6	,	,	PUNCT
cana-3107	15	7	pest	pest	VERB
cana-3107	15	8	infestation	infestation	NOUN
cana-3107	15	9	is	be	AUX
cana-3107	15	10	a	a	DET
cana-3107	15	11	key	key	ADJ
cana-3107	15	12	issue	issue	NOUN
cana-3107	15	13	restricting	restrict	VERB
cana-3107	15	14	agricultural	agricultural	ADJ
cana-3107	15	15	productivity	productivity	NOUN
cana-3107	15	16	because	because	SCONJ
cana-3107	15	17	of	of	ADP
cana-3107	15	18	the	the	DET
cana-3107	15	19	negative	negative	ADJ
cana-3107	15	20	impact	impact	NOUN
cana-3107	15	21	it	it	PRON
cana-3107	15	22	has	have	VERB
cana-3107	15	23	on	on	ADP
cana-3107	15	24	crop	crop	NOUN
cana-3107	15	25	quality	quality	NOUN
cana-3107	15	26	and	and	CCONJ
cana-3107	15	27	yield	yield	NOUN
cana-3107	15	28	.	.	PUNCT
cana-3107	16	1	because	because	SCONJ
cana-3107	16	2	of	of	ADP
cana-3107	16	3	this	this	PRON
cana-3107	16	4	,	,	PUNCT
cana-3107	16	5	it	it	PRON
cana-3107	16	6	's	be	AUX
cana-3107	16	7	crucial	crucial	ADJ
cana-3107	16	8	to	to	PART
cana-3107	16	9	investigate	investigate	VERB
cana-3107	16	10	insect	insect	NOUN
cana-3107	16	11	image	image	NOUN
cana-3107	16	12	recognition	recognition	NOUN
cana-3107	16	13	and	and	CCONJ
cana-3107	16	14	discover	discover	VERB
cana-3107	16	15	possible	possible	ADJ
cana-3107	16	16	patterns	pattern	NOUN
cana-3107	16	17	for	for	ADP
cana-3107	16	18	the	the	DET
cana-3107	16	19	development	development	NOUN
cana-3107	16	20	of	of	ADP
cana-3107	16	21	pest	pest	NOUN
cana-3107	16	22	management	management	NOUN
cana-3107	16	23	methods	method	NOUN
cana-3107	16	24	[	[	X
cana-3107	16	25	1	1	NUM
cana-3107	16	26	]	]	PUNCT
cana-3107	16	27	.	.	PUNCT
cana-3107	17	1	insects	insect	NOUN
cana-3107	17	2	have	have	AUX
cana-3107	17	3	traditionally	traditionally	ADV
cana-3107	17	4	been	be	AUX
cana-3107	17	5	identified	identify	VERB
cana-3107	17	6	by	by	ADP
cana-3107	17	7	specialists	specialist	NOUN
cana-3107	17	8	or	or	CCONJ
cana-3107	17	9	professionals	professional	NOUN
cana-3107	17	10	with	with	ADP
cana-3107	17	11	specialized	specialized	ADJ
cana-3107	17	12	understanding	understanding	NOUN
cana-3107	17	13	of	of	ADP
cana-3107	17	14	insects	insect	NOUN
cana-3107	17	15	.	.	PUNCT
cana-3107	18	1	however	however	ADV
cana-3107	18	2	,	,	PUNCT
cana-3107	18	3	the	the	DET
cana-3107	18	4	current	current	ADJ
cana-3107	18	5	pool	pool	NOUN
cana-3107	18	6	of	of	ADP
cana-3107	18	7	classification	classification	NOUN
cana-3107	18	8	specialists	specialist	NOUN
cana-3107	18	9	and	and	CCONJ
cana-3107	18	10	technologists	technologist	NOUN
cana-3107	18	11	is	be	AUX
cana-3107	18	12	woefully	woefully	ADV
cana-3107	18	13	inadequate	inadequate	ADJ
cana-3107	18	14	to	to	PART
cana-3107	18	15	satisfy	satisfy	VERB
cana-3107	18	16	the	the	DET
cana-3107	18	17	demands	demand	NOUN
cana-3107	18	18	of	of	ADP
cana-3107	18	19	the	the	DET
cana-3107	18	20	ever	ever	ADV
cana-3107	18	21	-	-	PUNCT
cana-3107	18	22	expanding	expand	VERB
cana-3107	18	23	number	number	NOUN
cana-3107	18	24	of	of	ADP
cana-3107	18	25	real	real	ADJ
cana-3107	18	26	-	-	PUNCT
cana-3107	18	27	world	world	NOUN
cana-3107	18	28	use	use	NOUN
cana-3107	18	29	cases	case	NOUN
cana-3107	18	30	.	.	PUNCT
cana-3107	19	1	however	however	ADV
cana-3107	19	2	,	,	PUNCT
cana-3107	19	3	the	the	DET
cana-3107	19	4	varied	varied	ADJ
cana-3107	19	5	texture	texture	NOUN
cana-3107	19	6	,	,	PUNCT
cana-3107	19	7	tiny	tiny	ADJ
cana-3107	19	8	characteristics	characteristic	NOUN
cana-3107	19	9	,	,	PUNCT
cana-3107	19	10	and	and	CCONJ
cana-3107	19	11	changeable	changeable	ADJ
cana-3107	19	12	habitat	habitat	NOUN
cana-3107	19	13	of	of	ADP
cana-3107	19	14	insects	insect	NOUN
cana-3107	19	15	make	make	VERB
cana-3107	19	16	insect	insect	NOUN
cana-3107	19	17	image	image	NOUN
cana-3107	19	18	identification	identification	NOUN
cana-3107	19	19	a	a	DET
cana-3107	19	20	challenging	challenging	ADJ
cana-3107	19	21	image	image	NOUN
cana-3107	19	22	recognition	recognition	NOUN
cana-3107	19	23	task	task	NOUN
cana-3107	19	24	.	.	PUNCT
cana-3107	20	1	the	the	DET
cana-3107	20	2	already	already	ADV
cana-3107	20	3	challenging	challenging	ADJ
cana-3107	20	4	challenge	challenge	NOUN
cana-3107	20	5	of	of	ADP
cana-3107	20	6	picture	picture	NOUN
cana-3107	20	7	identification	identification	NOUN
cana-3107	20	8	is	be	AUX
cana-3107	20	9	made	make	VERB
cana-3107	20	10	much	much	ADV
cana-3107	20	11	more	more	ADV
cana-3107	20	12	so	so	ADV
cana-3107	20	13	by	by	ADP
cana-3107	20	14	the	the	DET
cana-3107	20	15	interspecies	interspecie	NOUN
cana-3107	20	16	resemblance	resemblance	VERB
cana-3107	20	17	across	across	ADP
cana-3107	20	18	insect	insect	NOUN
cana-3107	20	19	groups	group	NOUN
cana-3107	20	20	&	&	CCONJ
cana-3107	20	21	the	the	DET
cana-3107	20	22	variances	variance	NOUN
cana-3107	20	23	induced	induce	VERB
cana-3107	20	24	by	by	ADP
cana-3107	20	25	varied	varied	ADJ
cana-3107	20	26	gestures	gesture	NOUN
cana-3107	20	27	and	and	CCONJ
cana-3107	20	28	motions	motion	NOUN
cana-3107	20	29	.	.	PUNCT
cana-3107	21	1	there	there	PRON
cana-3107	21	2	are	be	VERB
cana-3107	21	3	so	so	ADV
cana-3107	21	4	many	many	ADJ
cana-3107	21	5	different	different	ADJ
cana-3107	21	6	kinds	kind	NOUN
cana-3107	21	7	of	of	ADP
cana-3107	21	8	insects	insect	NOUN
cana-3107	21	9	that	that	PRON
cana-3107	21	10	it	it	PRON
cana-3107	21	11	's	be	AUX
cana-3107	21	12	simple	simple	ADJ
cana-3107	21	13	for	for	SCONJ
cana-3107	21	14	humans	human	NOUN
cana-3107	21	15	to	to	PART
cana-3107	21	16	overlook	overlook	VERB
cana-3107	21	17	important	important	ADJ
cana-3107	21	18	details	detail	NOUN
cana-3107	21	19	while	while	SCONJ
cana-3107	21	20	building	build	VERB
cana-3107	21	21	screening	screen	VERB
cana-3107	21	22	features	feature	NOUN
cana-3107	21	23	,	,	PUNCT
cana-3107	21	24	leading	lead	VERB
cana-3107	21	25	to	to	ADP
cana-3107	21	26	misclassification	misclassification	NOUN
cana-3107	21	27	[	[	X
cana-3107	21	28	2	2	NUM
cana-3107	21	29	]	]	PUNCT
cana-3107	21	30	.	.	PUNCT
cana-3107	22	1	there	there	PRON
cana-3107	22	2	are	be	VERB
cana-3107	22	3	so	so	ADV
cana-3107	22	4	many	many	ADJ
cana-3107	22	5	different	different	ADJ
cana-3107	22	6	kinds	kind	NOUN
cana-3107	22	7	of	of	ADP
cana-3107	22	8	insects	insect	NOUN
cana-3107	22	9	that	that	PRON
cana-3107	22	10	it	it	PRON
cana-3107	22	11	may	may	AUX
cana-3107	22	12	be	be	AUX
cana-3107	22	13	difficult	difficult	ADJ
cana-3107	22	14	to	to	PART
cana-3107	22	15	tell	tell	VERB
cana-3107	22	16	them	they	PRON
cana-3107	22	17	apart	apart	ADV
cana-3107	22	18	,	,	PUNCT
cana-3107	22	19	which	which	PRON
cana-3107	22	20	in	in	ADP
cana-3107	22	21	turn	turn	NOUN
cana-3107	22	22	threatens	threaten	VERB
cana-3107	22	23	the	the	DET
cana-3107	22	24	foundations	foundation	NOUN
cana-3107	22	25	of	of	ADP
cana-3107	22	26	biodiversity	biodiversity	NOUN
cana-3107	22	27	,	,	PUNCT
cana-3107	22	28	conservation	conservation	NOUN
cana-3107	22	29	,	,	PUNCT
cana-3107	22	30	and	and	CCONJ
cana-3107	22	31	related	related	ADJ
cana-3107	22	32	studies	study	NOUN
cana-3107	22	33	.	.	PUNCT
cana-3107	23	1	traditional	traditional	ADJ
cana-3107	23	2	insect	insect	NOUN
cana-3107	23	3	identification	identification	NOUN
cana-3107	23	4	techniques	technique	NOUN
cana-3107	23	5	are	be	AUX
cana-3107	23	6	complex	complex	ADJ
cana-3107	23	7	,	,	PUNCT
cana-3107	23	8	and	and	CCONJ
cana-3107	23	9	there	there	PRON
cana-3107	23	10	are	be	VERB
cana-3107	23	11	fewer	few	ADJ
cana-3107	23	12	insect	insect	NOUN
cana-3107	23	13	taxonomists	taxonomist	NOUN
cana-3107	23	14	available	available	ADJ
cana-3107	23	15	to	to	PART
cana-3107	23	16	work	work	VERB
cana-3107	23	17	on	on	ADP
cana-3107	23	18	this	this	DET
cana-3107	23	19	problem	problem	NOUN
cana-3107	23	20	.	.	PUNCT
cana-3107	24	1	taxonomists	taxonomist	NOUN
cana-3107	24	2	have	have	AUX
cana-3107	24	3	been	be	AUX
cana-3107	24	4	on	on	ADP
cana-3107	24	5	the	the	DET
cana-3107	24	6	lookout	lookout	NOUN
cana-3107	24	7	for	for	ADP
cana-3107	24	8	effective	effective	ADJ
cana-3107	24	9	strategies	strategy	NOUN
cana-3107	24	10	to	to	PART
cana-3107	24	11	fulfill	fulfill	VERB
cana-3107	24	12	practical	practical	ADJ
cana-3107	24	13	needs	need	NOUN
cana-3107	24	14	communications	communication	NOUN
cana-3107	24	15	on	on	ADP
cana-3107	24	16	applied	apply	VERB
cana-3107	24	17	nonlinear	nonlinear	ADJ
cana-3107	24	18	analysis	analysis	NOUN
cana-3107	24	19	issn	issn	NOUN
cana-3107	24	20	:	:	PUNCT
cana-3107	24	21	1074	1074	NUM
cana-3107	24	22	-	-	PUNCT
cana-3107	24	23	133x	133x	NUM
cana-3107	24	24	vol	vol	NOUN
cana-3107	24	25	32	32	NUM
cana-3107	24	26	no	no	NOUN
cana-3107	24	27	.	.	PUNCT
cana-3107	25	1	5s	5s	NUM
cana-3107	25	2	(	(	PUNCT
cana-3107	25	3	2025	2025	NUM
cana-3107	25	4	)	)	PUNCT
cana-3107	25	5	362	362	NUM
cana-3107	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	25	7	in	in	ADP
cana-3107	25	8	insect	insect	NOUN
cana-3107	25	9	identification	identification	NOUN
cana-3107	25	10	.	.	PUNCT
cana-3107	26	1	in	in	ADP
cana-3107	26	2	the	the	DET
cana-3107	26	3	past	past	ADJ
cana-3107	26	4	two	two	NUM
cana-3107	26	5	decades	decade	NOUN
cana-3107	26	6	,	,	PUNCT
cana-3107	26	7	several	several	ADJ
cana-3107	26	8	other	other	ADJ
cana-3107	26	9	computer	computer	NOUN
cana-3107	26	10	-	-	PUNCT
cana-3107	26	11	based	base	VERB
cana-3107	26	12	insect	insect	NOUN
cana-3107	26	13	identification	identification	NOUN
cana-3107	26	14	aids	aid	NOUN
cana-3107	26	15	,	,	PUNCT
cana-3107	26	16	including	include	VERB
cana-3107	26	17	as	as	ADP
cana-3107	26	18	the	the	DET
cana-3107	26	19	automatic	automatic	ADJ
cana-3107	26	20	bee	bee	NOUN
cana-3107	26	21	identification	identification	NOUN
cana-3107	26	22	system	system	NOUN
cana-3107	26	23	(	(	PUNCT
cana-3107	26	24	abis	abis	PROPN
cana-3107	26	25	)	)	PUNCT
cana-3107	26	26	,	,	PUNCT
cana-3107	26	27	the	the	DET
cana-3107	26	28	digital	digital	ADJ
cana-3107	26	29	automated	automate	VERB
cana-3107	26	30	identification	identification	NOUN
cana-3107	26	31	system	system	NOUN
cana-3107	26	32	(	(	PUNCT
cana-3107	26	33	daisy	daisy	NOUN
cana-3107	26	34	)	)	PUNCT
cana-3107	26	35	,	,	PUNCT
cana-3107	26	36	bugvisux	bugvisux	NOUN
cana-3107	26	37	,	,	PUNCT
cana-3107	26	38	and	and	CCONJ
cana-3107	26	39	but2fly	but2fly	ADV
cana-3107	26	40	,	,	PUNCT
cana-3107	26	41	have	have	AUX
cana-3107	26	42	been	be	AUX
cana-3107	26	43	created	create	VERB
cana-3107	26	44	and	and	CCONJ
cana-3107	26	45	tested	test	VERB
cana-3107	26	46	.	.	PUNCT
cana-3107	27	1	built	build	VERB
cana-3107	27	2	in	in	ADP
cana-3107	27	3	1995	1995	NUM
cana-3107	27	4	,	,	PUNCT
cana-3107	27	5	abis	abis	PROPN
cana-3107	27	6	is	be	AUX
cana-3107	27	7	able	able	ADJ
cana-3107	27	8	to	to	PART
cana-3107	27	9	recognize	recognize	VERB
cana-3107	27	10	bees	bee	NOUN
cana-3107	27	11	in	in	ADP
cana-3107	27	12	the	the	DET
cana-3107	27	13	wild	wild	NOUN
cana-3107	27	14	by	by	ADP
cana-3107	27	15	examining	examine	VERB
cana-3107	27	16	digital	digital	ADJ
cana-3107	27	17	photos	photo	NOUN
cana-3107	27	18	of	of	ADP
cana-3107	27	19	their	their	PRON
cana-3107	27	20	wing	wing	NOUN
cana-3107	27	21	veins	vein	NOUN
cana-3107	27	22	.	.	PUNCT
cana-3107	28	1	daisy	daisy	NOUN
cana-3107	28	2	is	be	AUX
cana-3107	28	3	a	a	DET
cana-3107	28	4	prototype	prototype	NOUN
cana-3107	28	5	system	system	NOUN
cana-3107	28	6	used	use	VERB
cana-3107	28	7	for	for	ADP
cana-3107	28	8	recognizing	recognize	VERB
cana-3107	28	9	and	and	CCONJ
cana-3107	28	10	analyzing	analyze	VERB
cana-3107	28	11	museum	museum	NOUN
cana-3107	28	12	collections	collection	NOUN
cana-3107	28	13	;	;	PUNCT
cana-3107	28	14	it	it	PRON
cana-3107	28	15	is	be	AUX
cana-3107	28	16	based	base	VERB
cana-3107	28	17	on	on	ADP
cana-3107	28	18	fingerprint	fingerprint	NOUN
cana-3107	28	19	identification	identification	NOUN
cana-3107	28	20	technology	technology	NOUN
cana-3107	28	21	&	&	CCONJ
cana-3107	28	22	is	be	AUX
cana-3107	28	23	used	use	VERB
cana-3107	28	24	for	for	ADP
cana-3107	28	25	identifying	identify	VERB
cana-3107	28	26	insects	insect	NOUN
cana-3107	28	27	using	use	VERB
cana-3107	28	28	digital	digital	ADJ
cana-3107	28	29	imagery	imagery	NOUN
cana-3107	28	30	.	.	PUNCT
cana-3107	29	1	there	there	PRON
cana-3107	29	2	are	be	VERB
cana-3107	29	3	now	now	ADV
cana-3107	29	4	40	40	NUM
cana-3107	29	5	bug	bug	NOUN
cana-3107	29	6	species	specie	NOUN
cana-3107	29	7	that	that	PRON
cana-3107	29	8	can	can	AUX
cana-3107	29	9	be	be	AUX
cana-3107	29	10	identified	identify	VERB
cana-3107	29	11	with	with	ADP
cana-3107	29	12	bugvisux	bugvisux	NOUN
cana-3107	29	13	using	use	VERB
cana-3107	29	14	morphologic	morphologic	ADJ
cana-3107	29	15	traits	trait	NOUN
cana-3107	29	16	,	,	PUNCT
cana-3107	29	17	and	and	CCONJ
cana-3107	29	18	43	43	NUM
cana-3107	29	19	butterfly	butterfly	NOUN
cana-3107	29	20	species	specie	NOUN
cana-3107	29	21	that	that	PRON
cana-3107	29	22	can	can	AUX
cana-3107	29	23	be	be	AUX
cana-3107	29	24	identified	identify	VERB
cana-3107	29	25	with	with	ADP
cana-3107	29	26	but2fly	but2fly	ADV
cana-3107	29	27	using	use	VERB
cana-3107	29	28	color	color	NOUN
cana-3107	29	29	attributes	attribute	NOUN
cana-3107	29	30	of	of	ADP
cana-3107	29	31	wings	wing	NOUN
cana-3107	29	32	[	[	X
cana-3107	29	33	3	3	NUM
cana-3107	29	34	]	]	PUNCT
cana-3107	29	35	.	.	PUNCT
cana-3107	30	1	target	target	NOUN
cana-3107	30	2	detection	detection	NOUN
cana-3107	30	3	approaches	approach	NOUN
cana-3107	30	4	for	for	ADP
cana-3107	30	5	insects	insect	NOUN
cana-3107	30	6	have	have	AUX
cana-3107	30	7	historically	historically	ADV
cana-3107	30	8	relied	rely	VERB
cana-3107	30	9	heavily	heavily	ADV
cana-3107	30	10	on	on	ADP
cana-3107	30	11	visual	visual	ADJ
cana-3107	30	12	inspection	inspection	NOUN
cana-3107	30	13	of	of	ADP
cana-3107	30	14	the	the	DET
cana-3107	30	15	insects	insect	NOUN
cana-3107	30	16	themselves	themselves	PRON
cana-3107	30	17	,	,	PUNCT
cana-3107	30	18	with	with	ADP
cana-3107	30	19	human	human	ADJ
cana-3107	30	20	eyes	eye	NOUN
cana-3107	30	21	comparing	compare	VERB
cana-3107	30	22	observed	observed	ADJ
cana-3107	30	23	details	detail	NOUN
cana-3107	30	24	to	to	PART
cana-3107	30	25	well	well	ADV
cana-3107	30	26	documented	document	VERB
cana-3107	30	27	specimen	speciman	NOUN
cana-3107	30	28	models	model	NOUN
cana-3107	30	29	.	.	PUNCT
cana-3107	31	1	this	this	DET
cana-3107	31	2	technology	technology	NOUN
cana-3107	31	3	,	,	PUNCT
cana-3107	31	4	which	which	PRON
cana-3107	31	5	relies	rely	VERB
cana-3107	31	6	on	on	ADP
cana-3107	31	7	fabricated	fabricate	VERB
cana-3107	31	8	insect	insect	NOUN
cana-3107	31	9	detection	detection	NOUN
cana-3107	31	10	,	,	PUNCT
cana-3107	31	11	is	be	AUX
cana-3107	31	12	plagued	plague	VERB
cana-3107	31	13	by	by	ADP
cana-3107	31	14	a	a	DET
cana-3107	31	15	number	number	NOUN
cana-3107	31	16	of	of	ADP
cana-3107	31	17	drawbacks	drawback	NOUN
cana-3107	31	18	,	,	PUNCT
cana-3107	31	19	including	include	VERB
cana-3107	31	20	a	a	DET
cana-3107	31	21	high	high	ADJ
cana-3107	31	22	labor	labor	NOUN
cana-3107	31	23	cost	cost	NOUN
cana-3107	31	24	,	,	PUNCT
cana-3107	31	25	inconsistent	inconsistent	ADJ
cana-3107	31	26	target	target	NOUN
cana-3107	31	27	detection	detection	NOUN
cana-3107	31	28	criteria	criterion	NOUN
cana-3107	31	29	,	,	PUNCT
cana-3107	31	30	poor	poor	ADJ
cana-3107	31	31	efficiency	efficiency	NOUN
cana-3107	31	32	,	,	PUNCT
cana-3107	31	33	and	and	CCONJ
cana-3107	31	34	so	so	ADV
cana-3107	31	35	on	on	ADV
cana-3107	31	36	.	.	PUNCT
cana-3107	32	1	as	as	SCONJ
cana-3107	32	2	machine	machine	NOUN
cana-3107	32	3	vision	vision	NOUN
cana-3107	32	4	,	,	PUNCT
cana-3107	32	5	image	image	NOUN
cana-3107	32	6	processing	processing	NOUN
cana-3107	32	7	technology	technology	NOUN
cana-3107	32	8	,	,	PUNCT
cana-3107	32	9	and	and	CCONJ
cana-3107	32	10	deep	deep	ADJ
cana-3107	32	11	learning	learning	NOUN
cana-3107	32	12	have	have	AUX
cana-3107	32	13	advanced	advance	VERB
cana-3107	32	14	rapidly	rapidly	ADV
cana-3107	32	15	in	in	ADP
cana-3107	32	16	recent	recent	ADJ
cana-3107	32	17	years	year	NOUN
cana-3107	32	18	,	,	PUNCT
cana-3107	32	19	the	the	DET
cana-3107	32	20	deep	deep	ADJ
cana-3107	32	21	learning	learning	NOUN
cana-3107	32	22	-	-	PUNCT
cana-3107	32	23	based	base	VERB
cana-3107	32	24	target	target	NOUN
cana-3107	32	25	detection	detection	NOUN
cana-3107	32	26	technology	technology	NOUN
cana-3107	32	27	has	have	AUX
cana-3107	32	28	emerged	emerge	VERB
cana-3107	32	29	as	as	ADP
cana-3107	32	30	the	the	DET
cana-3107	32	31	dominant	dominant	ADJ
cana-3107	32	32	algorithm	algorithm	NOUN
cana-3107	32	33	in	in	ADP
cana-3107	32	34	this	this	DET
cana-3107	32	35	space	space	NOUN
cana-3107	32	36	,	,	PUNCT
cana-3107	32	37	finding	find	VERB
cana-3107	32	38	applications	application	NOUN
cana-3107	32	39	in	in	ADP
cana-3107	32	40	areas	area	NOUN
cana-3107	32	41	as	as	ADV
cana-3107	32	42	diverse	diverse	ADJ
cana-3107	32	43	as	as	ADP
cana-3107	32	44	pedestrian	pedestrian	NOUN
cana-3107	32	45	detection	detection	NOUN
cana-3107	32	46	,	,	PUNCT
cana-3107	32	47	vehicle	vehicle	NOUN
cana-3107	32	48	detection	detection	NOUN
cana-3107	32	49	,	,	PUNCT
cana-3107	32	50	face	face	NOUN
cana-3107	32	51	detection	detection	NOUN
cana-3107	32	52	,	,	PUNCT
cana-3107	32	53	and	and	CCONJ
cana-3107	32	54	driverless	driverless	NOUN
cana-3107	32	55	cars	car	NOUN
cana-3107	32	56	.	.	PUNCT
cana-3107	33	1	this	this	DET
cana-3107	33	2	technique	technique	NOUN
cana-3107	33	3	may	may	AUX
cana-3107	33	4	also	also	ADV
cana-3107	33	5	be	be	AUX
cana-3107	33	6	used	use	VERB
cana-3107	33	7	to	to	PART
cana-3107	33	8	locate	locate	VERB
cana-3107	33	9	insects	insect	NOUN
cana-3107	33	10	as	as	ADP
cana-3107	33	11	a	a	DET
cana-3107	33	12	target	target	NOUN
cana-3107	33	13	.	.	PUNCT
cana-3107	34	1	some	some	PRON
cana-3107	34	2	of	of	ADP
cana-3107	34	3	these	these	DET
cana-3107	34	4	methods	method	NOUN
cana-3107	34	5	for	for	ADP
cana-3107	34	6	spotting	spot	VERB
cana-3107	34	7	the	the	DET
cana-3107	34	8	corpses	corpse	NOUN
cana-3107	34	9	of	of	ADP
cana-3107	34	10	insects	insect	NOUN
cana-3107	34	11	,	,	PUNCT
cana-3107	34	12	however	however	ADV
cana-3107	34	13	,	,	PUNCT
cana-3107	34	14	are	be	AUX
cana-3107	34	15	laborious	laborious	ADJ
cana-3107	34	16	,	,	PUNCT
cana-3107	34	17	expensive	expensive	ADJ
cana-3107	34	18	,	,	PUNCT
cana-3107	34	19	and	and	CCONJ
cana-3107	34	20	inefficient	inefficient	ADJ
cana-3107	34	21	.	.	PUNCT
cana-3107	35	1	one	one	NUM
cana-3107	35	2	of	of	ADP
cana-3107	35	3	the	the	DET
cana-3107	35	4	hottest	hot	ADJ
cana-3107	35	5	subjects	subject	NOUN
cana-3107	35	6	in	in	ADP
cana-3107	35	7	recent	recent	ADJ
cana-3107	35	8	years	year	NOUN
cana-3107	35	9	is	be	AUX
cana-3107	35	10	application	application	NOUN
cana-3107	35	11	design	design	NOUN
cana-3107	35	12	,	,	PUNCT
cana-3107	35	13	and	and	CCONJ
cana-3107	35	14	one	one	NUM
cana-3107	35	15	popular	popular	ADJ
cana-3107	35	16	way	way	NOUN
cana-3107	35	17	is	be	AUX
cana-3107	35	18	based	base	VERB
cana-3107	35	19	on	on	ADP
cana-3107	35	20	image	image	NOUN
cana-3107	35	21	processing	processing	NOUN
cana-3107	35	22	since	since	SCONJ
cana-3107	35	23	it	it	PRON
cana-3107	35	24	is	be	AUX
cana-3107	35	25	nondestructive	nondestructive	ADJ
cana-3107	35	26	and	and	CCONJ
cana-3107	35	27	easy	easy	ADJ
cana-3107	35	28	to	to	PART
cana-3107	35	29	use	use	VERB
cana-3107	35	30	.	.	PUNCT
cana-3107	36	1	insects	insect	NOUN
cana-3107	36	2	may	may	AUX
cana-3107	36	3	be	be	AUX
cana-3107	36	4	counted	count	VERB
cana-3107	36	5	using	use	VERB
cana-3107	36	6	image	image	NOUN
cana-3107	36	7	processing	processing	NOUN
cana-3107	36	8	in	in	ADP
cana-3107	36	9	a	a	DET
cana-3107	36	10	few	few	ADJ
cana-3107	36	11	different	different	ADJ
cana-3107	36	12	ways	way	NOUN
cana-3107	36	13	,	,	PUNCT
cana-3107	36	14	the	the	DET
cana-3107	36	15	most	most	ADV
cana-3107	36	16	common	common	ADJ
cana-3107	36	17	of	of	ADP
cana-3107	36	18	which	which	PRON
cana-3107	36	19	are	be	AUX
cana-3107	36	20	by	by	ADP
cana-3107	36	21	counting	count	VERB
cana-3107	36	22	the	the	DET
cana-3107	36	23	insects	insect	NOUN
cana-3107	36	24	'	'	PART
cana-3107	36	25	morphological	morphological	ADJ
cana-3107	36	26	traits	trait	NOUN
cana-3107	36	27	,	,	PUNCT
cana-3107	36	28	the	the	DET
cana-3107	36	29	binary	binary	PROPN
cana-3107	36	30	sketch	sketch	NOUN
cana-3107	36	31	of	of	ADP
cana-3107	36	32	the	the	DET
cana-3107	36	33	grayscale	grayscale	NOUN
cana-3107	36	34	picture	picture	NOUN
cana-3107	36	35	,	,	PUNCT
cana-3107	36	36	and	and	CCONJ
cana-3107	36	37	the	the	DET
cana-3107	36	38	insects	insect	NOUN
cana-3107	36	39	'	'	PART
cana-3107	36	40	pixels	pixel	NOUN
cana-3107	36	41	.	.	PUNCT
cana-3107	37	1	unfortunately	unfortunately	ADV
cana-3107	37	2	,	,	PUNCT
cana-3107	37	3	these	these	DET
cana-3107	37	4	techniques	technique	NOUN
cana-3107	37	5	suffer	suffer	VERB
cana-3107	37	6	from	from	ADP
cana-3107	37	7	a	a	DET
cana-3107	37	8	number	number	NOUN
cana-3107	37	9	of	of	ADP
cana-3107	37	10	drawbacks	drawback	NOUN
cana-3107	37	11	,	,	PUNCT
cana-3107	37	12	including	include	VERB
cana-3107	37	13	a	a	DET
cana-3107	37	14	lack	lack	NOUN
cana-3107	37	15	of	of	ADP
cana-3107	37	16	precision	precision	NOUN
cana-3107	37	17	when	when	SCONJ
cana-3107	37	18	counting	count	VERB
cana-3107	37	19	tiny	tiny	ADJ
cana-3107	37	20	grain	grain	NOUN
cana-3107	37	21	pests	pest	NOUN
cana-3107	37	22	,	,	PUNCT
cana-3107	37	23	a	a	DET
cana-3107	37	24	high	high	ADJ
cana-3107	37	25	price	price	NOUN
cana-3107	37	26	tag	tag	NOUN
cana-3107	37	27	for	for	ADP
cana-3107	37	28	the	the	DET
cana-3107	37	29	necessary	necessary	ADJ
cana-3107	37	30	gear	gear	NOUN
cana-3107	37	31	for	for	ADP
cana-3107	37	32	picture	picture	NOUN
cana-3107	37	33	collecting	collecting	NOUN
cana-3107	37	34	and	and	CCONJ
cana-3107	37	35	monitoring	monitoring	NOUN
cana-3107	37	36	,	,	PUNCT
cana-3107	37	37	and	and	CCONJ
cana-3107	37	38	a	a	DET
cana-3107	37	39	computational	computational	ADJ
cana-3107	37	40	overhead	overhead	NOUN
cana-3107	37	41	that	that	PRON
cana-3107	37	42	prevents	prevent	VERB
cana-3107	37	43	real	real	ADJ
cana-3107	37	44	-	-	PUNCT
cana-3107	37	45	time	time	NOUN
cana-3107	37	46	detection	detection	NOUN
cana-3107	37	47	.	.	PUNCT
cana-3107	38	1	since	since	SCONJ
cana-3107	38	2	picture	picture	NOUN
cana-3107	38	3	-	-	PUNCT
cana-3107	38	4	based	base	VERB
cana-3107	38	5	insect	insect	NOUN
cana-3107	38	6	target	target	NOUN
cana-3107	38	7	detection	detection	NOUN
cana-3107	38	8	may	may	AUX
cana-3107	38	9	address	address	VERB
cana-3107	38	10	the	the	DET
cana-3107	38	11	aforementioned	aforementioned	ADJ
cana-3107	38	12	problems	problem	NOUN
cana-3107	38	13	with	with	ADP
cana-3107	38	14	artificial	artificial	ADJ
cana-3107	38	15	detection	detection	NOUN
cana-3107	38	16	,	,	PUNCT
cana-3107	38	17	the	the	DET
cana-3107	38	18	widespread	widespread	ADJ
cana-3107	38	19	adoption	adoption	NOUN
cana-3107	38	20	of	of	ADP
cana-3107	38	21	advanced	advanced	ADJ
cana-3107	38	22	computer	computer	NOUN
cana-3107	38	23	image	image	NOUN
cana-3107	38	24	recognition	recognition	NOUN
cana-3107	38	25	technology	technology	NOUN
cana-3107	38	26	in	in	ADP
cana-3107	38	27	this	this	DET
cana-3107	38	28	area	area	NOUN
cana-3107	38	29	promises	promise	VERB
cana-3107	38	30	to	to	PART
cana-3107	38	31	significantly	significantly	ADV
cana-3107	38	32	enhance	enhance	VERB
cana-3107	38	33	detection	detection	NOUN
cana-3107	38	34	accuracy	accuracy	NOUN
cana-3107	39	1	[	[	X
cana-3107	39	2	4	4	X
cana-3107	39	3	]	]	X
cana-3107	39	4	[	[	X
cana-3107	39	5	5	5	NUM
cana-3107	39	6	]	]	PUNCT
cana-3107	39	7	.	.	PUNCT
cana-3107	40	1	segmentation	segmentation	NOUN
cana-3107	40	2	is	be	AUX
cana-3107	40	3	the	the	DET
cana-3107	40	4	process	process	NOUN
cana-3107	40	5	of	of	ADP
cana-3107	40	6	dividing	divide	VERB
cana-3107	40	7	a	a	DET
cana-3107	40	8	picture	picture	NOUN
cana-3107	40	9	into	into	ADP
cana-3107	40	10	individual	individual	ADJ
cana-3107	40	11	,	,	PUNCT
cana-3107	40	12	distinct	distinct	ADJ
cana-3107	40	13	sections	section	NOUN
cana-3107	40	14	that	that	PRON
cana-3107	40	15	have	have	VERB
cana-3107	40	16	a	a	DET
cana-3107	40	17	common	common	ADJ
cana-3107	40	18	property	property	NOUN
cana-3107	40	19	,	,	PUNCT
cana-3107	40	20	such	such	ADJ
cana-3107	40	21	color	color	NOUN
cana-3107	40	22	or	or	CCONJ
cana-3107	40	23	texture	texture	NOUN
cana-3107	40	24	,	,	PUNCT
cana-3107	40	25	but	but	CCONJ
cana-3107	40	26	do	do	AUX
cana-3107	40	27	not	not	PART
cana-3107	40	28	overlap	overlap	VERB
cana-3107	40	29	.	.	PUNCT
cana-3107	41	1	color	color	NOUN
cana-3107	41	2	,	,	PUNCT
cana-3107	41	3	texture	texture	NOUN
cana-3107	41	4	,	,	PUNCT
cana-3107	41	5	and	and	CCONJ
cana-3107	41	6	edges	edge	NOUN
cana-3107	41	7	are	be	AUX
cana-3107	41	8	the	the	DET
cana-3107	41	9	three	three	NUM
cana-3107	41	10	main	main	ADJ
cana-3107	41	11	categories	category	NOUN
cana-3107	41	12	of	of	ADP
cana-3107	41	13	image	image	NOUN
cana-3107	41	14	attributes	attribute	NOUN
cana-3107	41	15	.	.	PUNCT
cana-3107	42	1	edge	edge	NOUN
cana-3107	42	2	features	feature	NOUN
cana-3107	42	3	are	be	AUX
cana-3107	42	4	simple	simple	ADJ
cana-3107	42	5	to	to	PART
cana-3107	42	6	extract	extract	VERB
cana-3107	42	7	and	and	CCONJ
cana-3107	42	8	are	be	AUX
cana-3107	42	9	particularly	particularly	ADV
cana-3107	42	10	adept	adept	ADJ
cana-3107	42	11	at	at	ADP
cana-3107	42	12	isolating	isolate	VERB
cana-3107	42	13	signal	signal	NOUN
cana-3107	42	14	from	from	ADP
cana-3107	42	15	noise	noise	NOUN
cana-3107	42	16	.	.	PUNCT
cana-3107	43	1	all	all	DET
cana-3107	43	2	fourteen	fourteen	NUM
cana-3107	43	3	characteristics	characteristic	NOUN
cana-3107	43	4	utilized	utilize	VERB
cana-3107	43	5	in	in	ADP
cana-3107	43	6	this	this	DET
cana-3107	43	7	study	study	NOUN
cana-3107	43	8	are	be	AUX
cana-3107	43	9	edges	edge	NOUN
cana-3107	43	10	[	[	X
cana-3107	43	11	6	6	NUM
cana-3107	43	12	]	]	PUNCT
cana-3107	43	13	.	.	PUNCT
cana-3107	44	1	automating	automate	VERB
cana-3107	44	2	the	the	DET
cana-3107	44	3	identification	identification	NOUN
cana-3107	44	4	and	and	CCONJ
cana-3107	44	5	counting	counting	NOUN
cana-3107	44	6	of	of	ADP
cana-3107	44	7	insects	insect	NOUN
cana-3107	44	8	using	use	VERB
cana-3107	44	9	data	datum	NOUN
cana-3107	44	10	extracted	extract	VERB
cana-3107	44	11	from	from	ADP
cana-3107	44	12	digital	digital	ADJ
cana-3107	44	13	images	image	NOUN
cana-3107	44	14	is	be	AUX
cana-3107	44	15	possible	possible	ADJ
cana-3107	44	16	with	with	ADP
cana-3107	44	17	the	the	DET
cana-3107	44	18	help	help	NOUN
cana-3107	44	19	of	of	ADP
cana-3107	44	20	modern	modern	ADJ
cana-3107	44	21	machine	machine	NOUN
cana-3107	44	22	learning	learning	NOUN
cana-3107	44	23	algorithms	algorithm	NOUN
cana-3107	44	24	,	,	PUNCT
cana-3107	44	25	computer	computer	NOUN
cana-3107	44	26	vision	vision	NOUN
cana-3107	44	27	techniques	technique	NOUN
cana-3107	44	28	,	,	PUNCT
cana-3107	44	29	and	and	CCONJ
cana-3107	44	30	image	image	NOUN
cana-3107	44	31	processing	processing	NOUN
cana-3107	44	32	(	(	PUNCT
cana-3107	44	33	ip	ip	NOUN
cana-3107	44	34	)	)	PUNCT
cana-3107	45	1	[	[	X
cana-3107	45	2	7	7	NUM
cana-3107	45	3	]	]	PUNCT
cana-3107	45	4	.	.	PUNCT
cana-3107	46	1	using	use	VERB
cana-3107	46	2	a	a	DET
cana-3107	46	3	more	more	ADJ
cana-3107	46	4	in	in	ADP
cana-3107	46	5	-	-	PUNCT
cana-3107	46	6	depth	depth	NOUN
cana-3107	46	7	network	network	NOUN
cana-3107	46	8	structure	structure	NOUN
cana-3107	46	9	,	,	PUNCT
cana-3107	46	10	cnn	cnn	PROPN
cana-3107	46	11	has	have	AUX
cana-3107	46	12	proven	prove	VERB
cana-3107	46	13	effective	effective	ADJ
cana-3107	46	14	in	in	ADP
cana-3107	46	15	recognizing	recognize	VERB
cana-3107	46	16	images	image	NOUN
cana-3107	46	17	in	in	ADP
cana-3107	46	18	computer	computer	NOUN
cana-3107	46	19	vision	vision	NOUN
cana-3107	46	20	.	.	PUNCT
cana-3107	47	1	having	have	VERB
cana-3107	47	2	additional	additional	ADJ
cana-3107	47	3	training	training	NOUN
cana-3107	47	4	data	datum	NOUN
cana-3107	47	5	is	be	AUX
cana-3107	47	6	essential	essential	ADJ
cana-3107	47	7	because	because	SCONJ
cana-3107	47	8	to	to	ADP
cana-3107	47	9	the	the	DET
cana-3107	47	10	deep	deep	ADJ
cana-3107	47	11	network	network	NOUN
cana-3107	47	12	topology	topology	NOUN
cana-3107	47	13	.	.	PUNCT
cana-3107	48	1	many	many	ADJ
cana-3107	48	2	researchers	researcher	NOUN
cana-3107	48	3	choose	choose	VERB
cana-3107	48	4	for	for	SCONJ
cana-3107	48	5	the	the	DET
cana-3107	48	6	imagenet	imagenet	PROPN
cana-3107	48	7	data	datum	NOUN
cana-3107	48	8	set	set	VERB
cana-3107	48	9	as	as	ADP
cana-3107	48	10	a	a	DET
cana-3107	48	11	starting	starting	NOUN
cana-3107	48	12	point	point	NOUN
cana-3107	48	13	for	for	ADP
cana-3107	48	14	their	their	PRON
cana-3107	48	15	models	model	NOUN
cana-3107	48	16	since	since	SCONJ
cana-3107	48	17	it	it	PRON
cana-3107	48	18	is	be	AUX
cana-3107	48	19	widely	widely	ADV
cana-3107	48	20	accepted	accept	VERB
cana-3107	48	21	as	as	ADP
cana-3107	48	22	the	the	DET
cana-3107	48	23	gold	gold	ADJ
cana-3107	48	24	standard	standard	NOUN
cana-3107	48	25	for	for	ADP
cana-3107	48	26	image	image	NOUN
cana-3107	48	27	recognition	recognition	NOUN
cana-3107	49	1	[	[	X
cana-3107	49	2	8	8	NUM
cana-3107	49	3	]	]	PUNCT
cana-3107	49	4	.	.	PUNCT
cana-3107	50	1	because	because	SCONJ
cana-3107	50	2	of	of	ADP
cana-3107	50	3	the	the	DET
cana-3107	50	4	availability	availability	NOUN
cana-3107	50	5	of	of	ADP
cana-3107	50	6	machine	machine	NOUN
cana-3107	50	7	learning	learn	VERB
cana-3107	50	8	frameworks	framework	NOUN
cana-3107	50	9	like	like	ADP
cana-3107	50	10	tensorflow	tensorflow	NOUN
cana-3107	50	11	and	and	CCONJ
cana-3107	50	12	models	model	NOUN
cana-3107	50	13	like	like	ADP
cana-3107	50	14	inception	inception	NOUN
cana-3107	50	15	and	and	CCONJ
cana-3107	50	16	googlenet	googlenet	NOUN
cana-3107	50	17	,	,	PUNCT
cana-3107	50	18	deep	deep	ADJ
cana-3107	50	19	convolutional	convolutional	ADJ
cana-3107	50	20	neural	neural	ADJ
cana-3107	50	21	networks	network	NOUN
cana-3107	50	22	have	have	AUX
cana-3107	50	23	made	make	VERB
cana-3107	50	24	great	great	ADJ
cana-3107	50	25	strides	stride	NOUN
cana-3107	50	26	in	in	ADP
cana-3107	50	27	recent	recent	ADJ
cana-3107	50	28	years	year	NOUN
cana-3107	50	29	.	.	PUNCT
cana-3107	51	1	the	the	DET
cana-3107	51	2	number	number	NOUN
cana-3107	51	3	of	of	ADP
cana-3107	51	4	taxa	taxa	NOUN
cana-3107	51	5	studied	study	VERB
cana-3107	51	6	,	,	PUNCT
cana-3107	51	7	communications	communication	NOUN
cana-3107	51	8	on	on	ADP
cana-3107	51	9	applied	apply	VERB
cana-3107	51	10	nonlinear	nonlinear	ADJ
cana-3107	51	11	analysis	analysis	NOUN
cana-3107	51	12	issn	issn	NOUN
cana-3107	51	13	:	:	PUNCT
cana-3107	51	14	1074	1074	NUM
cana-3107	51	15	-	-	PUNCT
cana-3107	51	16	133x	133x	NUM
cana-3107	51	17	vol	vol	NOUN
cana-3107	51	18	32	32	NUM
cana-3107	51	19	no	no	NOUN
cana-3107	51	20	.	.	PUNCT
cana-3107	52	1	5s	5s	NUM
cana-3107	52	2	(	(	PUNCT
cana-3107	52	3	2025	2025	NUM
cana-3107	52	4	)	)	PUNCT
cana-3107	52	5	363	363	NUM
cana-3107	52	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	52	7	as	as	ADV
cana-3107	52	8	well	well	ADV
cana-3107	52	9	as	as	ADP
cana-3107	52	10	the	the	DET
cana-3107	52	11	accuracy	accuracy	NOUN
cana-3107	52	12	and	and	CCONJ
cana-3107	52	13	effectiveness	effectiveness	NOUN
cana-3107	52	14	of	of	ADP
cana-3107	52	15	image	image	NOUN
cana-3107	52	16	classifiers	classifier	NOUN
cana-3107	52	17	used	use	VERB
cana-3107	52	18	for	for	ADP
cana-3107	52	19	species	species	NOUN
cana-3107	52	20	identification	identification	NOUN
cana-3107	52	21	,	,	PUNCT
cana-3107	52	22	have	have	AUX
cana-3107	52	23	both	both	PRON
cana-3107	52	24	improved	improve	VERB
cana-3107	52	25	considerably	considerably	ADV
cana-3107	52	26	in	in	ADP
cana-3107	52	27	recent	recent	ADJ
cana-3107	52	28	years	year	NOUN
cana-3107	53	1	[	[	X
cana-3107	53	2	9	9	NUM
cana-3107	53	3	]	]	PUNCT
cana-3107	53	4	.	.	PUNCT
cana-3107	54	1	while	while	SCONJ
cana-3107	54	2	there	there	PRON
cana-3107	54	3	have	have	AUX
cana-3107	54	4	been	be	AUX
cana-3107	54	5	significant	significant	ADJ
cana-3107	54	6	advancements	advancement	NOUN
cana-3107	54	7	in	in	ADP
cana-3107	54	8	the	the	DET
cana-3107	54	9	field	field	NOUN
cana-3107	54	10	of	of	ADP
cana-3107	54	11	automated	automate	VERB
cana-3107	54	12	insect	insect	NOUN
cana-3107	54	13	identification	identification	NOUN
cana-3107	54	14	using	use	VERB
cana-3107	54	15	images	image	NOUN
cana-3107	54	16	,	,	PUNCT
cana-3107	54	17	most	most	ADJ
cana-3107	54	18	of	of	ADP
cana-3107	54	19	these	these	DET
cana-3107	54	20	studies	study	NOUN
cana-3107	54	21	have	have	AUX
cana-3107	54	22	only	only	ADV
cana-3107	54	23	considered	consider	VERB
cana-3107	54	24	images	image	NOUN
cana-3107	54	25	with	with	ADP
cana-3107	54	26	ideal	ideal	ADJ
cana-3107	54	27	conditions	condition	NOUN
cana-3107	54	28	,	,	PUNCT
cana-3107	54	29	such	such	ADJ
cana-3107	54	30	as	as	ADP
cana-3107	54	31	bright	bright	ADJ
cana-3107	54	32	lighting	lighting	NOUN
cana-3107	54	33	,	,	PUNCT
cana-3107	54	34	a	a	DET
cana-3107	54	35	fixed	fix	VERB
cana-3107	54	36	insect	insect	NOUN
cana-3107	54	37	location	location	NOUN
cana-3107	54	38	,	,	PUNCT
cana-3107	54	39	and	and	CCONJ
cana-3107	54	40	a	a	DET
cana-3107	54	41	top	top	ADJ
cana-3107	54	42	-	-	PUNCT
cana-3107	54	43	down	down	ADP
cana-3107	54	44	perspective	perspective	NOUN
cana-3107	54	45	.	.	PUNCT
cana-3107	55	1	good	good	ADJ
cana-3107	55	2	results	result	NOUN
cana-3107	55	3	may	may	AUX
cana-3107	55	4	be	be	AUX
cana-3107	55	5	achieved	achieve	VERB
cana-3107	55	6	from	from	ADP
cana-3107	55	7	insect	insect	NOUN
cana-3107	55	8	identification	identification	NOUN
cana-3107	55	9	systems	system	NOUN
cana-3107	55	10	when	when	SCONJ
cana-3107	55	11	using	use	VERB
cana-3107	55	12	global	global	ADJ
cana-3107	55	13	features	feature	NOUN
cana-3107	55	14	—	—	PUNCT
cana-3107	55	15	those	those	PRON
cana-3107	55	16	that	that	PRON
cana-3107	55	17	provide	provide	VERB
cana-3107	55	18	a	a	DET
cana-3107	55	19	direct	direct	ADJ
cana-3107	55	20	and	and	CCONJ
cana-3107	55	21	broad	broad	ADJ
cana-3107	55	22	description	description	NOUN
cana-3107	55	23	of	of	ADP
cana-3107	55	24	an	an	DET
cana-3107	55	25	image	image	NOUN
cana-3107	55	26	or	or	CCONJ
cana-3107	55	27	insect	insect	NOUN
cana-3107	55	28	object	object	NOUN
cana-3107	55	29	—	—	PUNCT
cana-3107	55	30	under	under	ADP
cana-3107	55	31	conditions	condition	NOUN
cana-3107	55	32	of	of	ADP
cana-3107	55	33	high	high	ADJ
cana-3107	55	34	picture	picture	NOUN
cana-3107	55	35	quality	quality	NOUN
cana-3107	55	36	.	.	PUNCT
cana-3107	56	1	these	these	DET
cana-3107	56	2	systems	system	NOUN
cana-3107	56	3	are	be	AUX
cana-3107	56	4	limited	limit	VERB
cana-3107	56	5	by	by	ADP
cana-3107	56	6	their	their	PRON
cana-3107	56	7	susceptibility	susceptibility	NOUN
cana-3107	56	8	to	to	PART
cana-3107	56	9	noise	noise	NOUN
cana-3107	56	10	and	and	CCONJ
cana-3107	56	11	background	background	NOUN
cana-3107	56	12	clutter	clutter	NOUN
cana-3107	56	13	,	,	PUNCT
cana-3107	56	14	their	their	PRON
cana-3107	56	15	insistence	insistence	NOUN
cana-3107	56	16	on	on	ADP
cana-3107	56	17	a	a	DET
cana-3107	56	18	particular	particular	ADJ
cana-3107	56	19	insect	insect	NOUN
cana-3107	56	20	position	position	NOUN
cana-3107	56	21	,	,	PUNCT
cana-3107	56	22	and	and	CCONJ
cana-3107	56	23	the	the	DET
cana-3107	56	24	difficulty	difficulty	NOUN
cana-3107	56	25	of	of	ADP
cana-3107	56	26	their	their	PRON
cana-3107	56	27	picture	picture	NOUN
cana-3107	56	28	acquisition	acquisition	NOUN
cana-3107	56	29	procedure	procedure	NOUN
cana-3107	56	30	[	[	X
cana-3107	56	31	10	10	NUM
cana-3107	56	32	]	]	PUNCT
cana-3107	56	33	.	.	PUNCT
cana-3107	57	1	in	in	ADP
cana-3107	57	2	this	this	DET
cana-3107	57	3	study	study	NOUN
cana-3107	57	4	,	,	PUNCT
cana-3107	57	5	we	we	PRON
cana-3107	57	6	provide	provide	VERB
cana-3107	57	7	a	a	DET
cana-3107	57	8	novel	novel	ADJ
cana-3107	57	9	method	method	NOUN
cana-3107	57	10	for	for	ADP
cana-3107	57	11	identifying	identify	VERB
cana-3107	57	12	insects	insect	NOUN
cana-3107	57	13	using	use	VERB
cana-3107	57	14	picture	picture	NOUN
cana-3107	57	15	segmentation	segmentation	NOUN
cana-3107	57	16	.	.	PUNCT
cana-3107	58	1	for	for	ADP
cana-3107	58	2	insect	insect	NOUN
cana-3107	58	3	image	image	NOUN
cana-3107	58	4	segmentation	segmentation	NOUN
cana-3107	58	5	,	,	PUNCT
cana-3107	58	6	we	we	PRON
cana-3107	58	7	employed	employ	VERB
cana-3107	58	8	faster	fast	ADJ
cana-3107	58	9	rcnn	rcnn	NOUN
cana-3107	58	10	with	with	ADP
cana-3107	58	11	the	the	DET
cana-3107	58	12	adam	adam	PROPN
cana-3107	58	13	optimizer	optimizer	NOUN
cana-3107	58	14	.	.	PUNCT
cana-3107	59	1	2	2	X
cana-3107	59	2	.	.	X
cana-3107	59	3	related	relate	VERB
cana-3107	59	4	works	work	NOUN
cana-3107	59	5	using	use	VERB
cana-3107	59	6	computing	compute	VERB
cana-3107	59	7	resources	resource	NOUN
cana-3107	59	8	,	,	PUNCT
cana-3107	59	9	recent	recent	ADJ
cana-3107	59	10	research	research	NOUN
cana-3107	59	11	has	have	AUX
cana-3107	59	12	automated	automate	VERB
cana-3107	59	13	the	the	DET
cana-3107	59	14	process	process	NOUN
cana-3107	59	15	of	of	ADP
cana-3107	59	16	identifying	identify	VERB
cana-3107	59	17	and	and	CCONJ
cana-3107	59	18	counting	count	VERB
cana-3107	59	19	insects	insect	NOUN
cana-3107	59	20	,	,	PUNCT
cana-3107	59	21	worms	worm	NOUN
cana-3107	59	22	,	,	PUNCT
cana-3107	59	23	and	and	CCONJ
cana-3107	59	24	cells	cell	NOUN
cana-3107	59	25	in	in	ADP
cana-3107	59	26	digital	digital	ADJ
cana-3107	59	27	photographs	photograph	NOUN
cana-3107	59	28	.	.	PUNCT
cana-3107	60	1	the	the	DET
cana-3107	60	2	tests	test	NOUN
cana-3107	60	3	confirm	confirm	VERB
cana-3107	60	4	that	that	SCONJ
cana-3107	60	5	manual	manual	ADJ
cana-3107	60	6	identification	identification	NOUN
cana-3107	60	7	is	be	AUX
cana-3107	60	8	a	a	DET
cana-3107	60	9	time	time	NOUN
cana-3107	60	10	-	-	PUNCT
cana-3107	60	11	consuming	consume	VERB
cana-3107	60	12	procedure	procedure	NOUN
cana-3107	60	13	that	that	PRON
cana-3107	60	14	is	be	AUX
cana-3107	60	15	prone	prone	ADJ
cana-3107	60	16	to	to	ADP
cana-3107	60	17	mistakes	mistake	NOUN
cana-3107	60	18	and	and	CCONJ
cana-3107	60	19	lacks	lack	VERB
cana-3107	60	20	accuracy	accuracy	NOUN
cana-3107	60	21	,	,	PUNCT
cana-3107	60	22	which	which	PRON
cana-3107	60	23	makes	make	VERB
cana-3107	60	24	it	it	PRON
cana-3107	60	25	unsuitable	unsuitable	ADJ
cana-3107	60	26	for	for	ADP
cana-3107	60	27	widespread	widespread	ADJ
cana-3107	60	28	use	use	NOUN
cana-3107	60	29	.	.	PUNCT
cana-3107	61	1	here	here	ADV
cana-3107	61	2	,	,	PUNCT
cana-3107	61	3	we	we	PRON
cana-3107	61	4	looked	look	VERB
cana-3107	61	5	at	at	ADP
cana-3107	61	6	many	many	ADJ
cana-3107	61	7	approaches	approach	NOUN
cana-3107	61	8	for	for	ADP
cana-3107	61	9	developing	develop	VERB
cana-3107	61	10	insect	insect	NOUN
cana-3107	61	11	identification	identification	NOUN
cana-3107	61	12	models	model	NOUN
cana-3107	61	13	.	.	PUNCT
cana-3107	62	1	a	a	DET
cana-3107	62	2	detection	detection	NOUN
cana-3107	62	3	instrument	instrument	NOUN
cana-3107	62	4	for	for	ADP
cana-3107	62	5	early	early	ADJ
cana-3107	62	6	detection	detection	NOUN
cana-3107	62	7	and	and	CCONJ
cana-3107	62	8	identification	identification	NOUN
cana-3107	62	9	of	of	ADP
cana-3107	62	10	agricultural	agricultural	ADJ
cana-3107	62	11	diseases	disease	NOUN
cana-3107	62	12	and	and	CCONJ
cana-3107	62	13	pests	pest	NOUN
cana-3107	62	14	was	be	AUX
cana-3107	62	15	developed	develop	VERB
cana-3107	62	16	by	by	ADP
cana-3107	62	17	lidia	lidia	PROPN
cana-3107	62	18	cleetus	cleetus	PROPN
cana-3107	62	19	et	et	PROPN
cana-3107	62	20	al	al	PROPN
cana-3107	62	21	.	.	PUNCT
cana-3107	63	1	[	[	X
cana-3107	63	2	11	11	NUM
cana-3107	63	3	]	]	PUNCT
cana-3107	63	4	.	.	PUNCT
cana-3107	64	1	to	to	PART
cana-3107	64	2	achieve	achieve	VERB
cana-3107	64	3	this	this	DET
cana-3107	64	4	goal	goal	NOUN
cana-3107	64	5	,	,	PUNCT
cana-3107	64	6	many	many	ADJ
cana-3107	64	7	deep	deep	ADJ
cana-3107	64	8	learning	learning	NOUN
cana-3107	64	9	architectures	architecture	NOUN
cana-3107	64	10	were	be	AUX
cana-3107	64	11	tested	test	VERB
cana-3107	64	12	to	to	PART
cana-3107	64	13	determine	determine	VERB
cana-3107	64	14	which	which	PRON
cana-3107	64	15	would	would	AUX
cana-3107	64	16	best	good	ADJ
cana-3107	64	17	aid	aid	VERB
cana-3107	64	18	in	in	ADP
cana-3107	64	19	the	the	DET
cana-3107	64	20	development	development	NOUN
cana-3107	64	21	of	of	ADP
cana-3107	64	22	a	a	DET
cana-3107	64	23	reliable	reliable	ADJ
cana-3107	64	24	and	and	CCONJ
cana-3107	64	25	productive	productive	ADJ
cana-3107	64	26	detection	detection	NOUN
cana-3107	64	27	model	model	NOUN
cana-3107	64	28	.	.	PUNCT
cana-3107	65	1	in	in	ADP
cana-3107	65	2	their	their	PRON
cana-3107	65	3	research	research	NOUN
cana-3107	65	4	,	,	PUNCT
cana-3107	65	5	they	they	PRON
cana-3107	65	6	used	use	VERB
cana-3107	65	7	convolutional	convolutional	ADJ
cana-3107	65	8	neural	neural	ADJ
cana-3107	65	9	network	network	NOUN
cana-3107	65	10	,	,	PUNCT
cana-3107	65	11	vgg16	vgg16	PROPN
cana-3107	65	12	,	,	PUNCT
cana-3107	65	13	inceptionv3	inceptionv3	PROPN
cana-3107	65	14	,	,	PUNCT
cana-3107	65	15	&	&	CCONJ
cana-3107	65	16	xception	xception	PROPN
cana-3107	65	17	deep	deep	ADJ
cana-3107	65	18	learning	learning	NOUN
cana-3107	65	19	architectures	architecture	NOUN
cana-3107	65	20	.	.	PUNCT
cana-3107	66	1	pre	pre	ADJ
cana-3107	66	2	-	-	ADJ
cana-3107	66	3	trained	train	VERB
cana-3107	66	4	models	model	NOUN
cana-3107	66	5	built	build	VERB
cana-3107	66	6	on	on	ADP
cana-3107	66	7	cnn	cnn	PROPN
cana-3107	66	8	architecture	architecture	NOUN
cana-3107	66	9	may	may	AUX
cana-3107	66	10	be	be	AUX
cana-3107	66	11	broken	break	VERB
cana-3107	66	12	down	down	ADP
cana-3107	66	13	into	into	ADP
cana-3107	66	14	three	three	NUM
cana-3107	66	15	distinct	distinct	ADJ
cana-3107	66	16	groups	group	NOUN
cana-3107	66	17	:	:	PUNCT
cana-3107	66	18	vgg16	vgg16	NOUN
cana-3107	66	19	,	,	PUNCT
cana-3107	66	20	inceptionv3	inceptionv3	NOUN
cana-3107	66	21	,	,	PUNCT
cana-3107	66	22	and	and	CCONJ
cana-3107	66	23	xception	xception	NOUN
cana-3107	66	24	.	.	PUNCT
cana-3107	67	1	the	the	DET
cana-3107	67	2	xception	xception	PROPN
cana-3107	67	3	model	model	NOUN
cana-3107	67	4	has	have	AUX
cana-3107	67	5	been	be	AUX
cana-3107	67	6	shown	show	VERB
cana-3107	67	7	to	to	PART
cana-3107	67	8	be	be	AUX
cana-3107	67	9	the	the	DET
cana-3107	67	10	most	most	ADV
cana-3107	67	11	effective	effective	ADJ
cana-3107	67	12	in	in	ADP
cana-3107	67	13	detecting	detect	VERB
cana-3107	67	14	and	and	CCONJ
cana-3107	67	15	identifying	identify	VERB
cana-3107	67	16	illnesses	illness	NOUN
cana-3107	67	17	and	and	CCONJ
cana-3107	67	18	pests	pest	NOUN
cana-3107	67	19	on	on	ADP
cana-3107	67	20	tomato	tomato	NOUN
cana-3107	67	21	leaves	leave	NOUN
cana-3107	67	22	after	after	ADP
cana-3107	67	23	being	be	AUX
cana-3107	67	24	compared	compare	VERB
cana-3107	67	25	to	to	ADP
cana-3107	67	26	other	other	ADJ
cana-3107	67	27	models	model	NOUN
cana-3107	67	28	using	use	VERB
cana-3107	67	29	test	test	NOUN
cana-3107	67	30	accuracy	accuracy	NOUN
cana-3107	67	31	scores	score	NOUN
cana-3107	67	32	.	.	PUNCT
cana-3107	68	1	the	the	DET
cana-3107	68	2	model	model	NOUN
cana-3107	68	3	achieves	achieve	VERB
cana-3107	68	4	an	an	DET
cana-3107	68	5	accuracy	accuracy	NOUN
cana-3107	68	6	of	of	ADP
cana-3107	68	7	82.89	82.89	NUM
cana-3107	68	8	percent	percent	NOUN
cana-3107	68	9	on	on	ADP
cana-3107	68	10	the	the	DET
cana-3107	68	11	tomato	tomato	NOUN
cana-3107	68	12	disease	disease	NOUN
cana-3107	68	13	dataset	dataset	NOUN
cana-3107	68	14	,	,	PUNCT
cana-3107	68	15	and	and	CCONJ
cana-3107	68	16	77.5	77.5	NUM
cana-3107	68	17	percent	percent	NOUN
cana-3107	68	18	on	on	ADP
cana-3107	68	19	the	the	DET
cana-3107	68	20	pest	pest	NOUN
cana-3107	68	21	dataset	dataset	NOUN
cana-3107	68	22	.	.	PUNCT
cana-3107	69	1	according	accord	VERB
cana-3107	69	2	to	to	ADP
cana-3107	69	3	maxime	maxime	PROPN
cana-3107	69	4	martineau	martineau	PROPN
cana-3107	69	5	et	et	PROPN
cana-3107	69	6	al	al	PROPN
cana-3107	69	7	.	.	PUNCT
cana-3107	70	1	[	[	X
cana-3107	70	2	12	12	NUM
cana-3107	70	3	]	]	PUNCT
cana-3107	70	4	,	,	PUNCT
cana-3107	70	5	entomology	entomology	NOUN
cana-3107	70	6	has	have	AUX
cana-3107	70	7	been	be	AUX
cana-3107	70	8	used	use	VERB
cana-3107	70	9	as	as	ADP
cana-3107	70	10	an	an	DET
cana-3107	70	11	indicator	indicator	NOUN
cana-3107	70	12	of	of	ADP
cana-3107	70	13	biodiversity	biodiversity	NOUN
cana-3107	70	14	and	and	CCONJ
cana-3107	70	15	has	have	VERB
cana-3107	70	16	implications	implication	NOUN
cana-3107	70	17	in	in	ADP
cana-3107	70	18	many	many	ADJ
cana-3107	70	19	other	other	ADJ
cana-3107	70	20	areas	area	NOUN
cana-3107	70	21	of	of	ADP
cana-3107	70	22	biology	biology	NOUN
cana-3107	70	23	.	.	PUNCT
cana-3107	71	1	automated	automate	VERB
cana-3107	71	2	entomology	entomology	NOUN
cana-3107	71	3	has	have	AUX
cana-3107	71	4	been	be	AUX
cana-3107	71	5	available	available	ADJ
cana-3107	71	6	for	for	ADP
cana-3107	71	7	decades	decade	NOUN
cana-3107	71	8	,	,	PUNCT
cana-3107	71	9	and	and	CCONJ
cana-3107	71	10	it	it	PRON
cana-3107	71	11	has	have	AUX
cana-3107	71	12	been	be	AUX
cana-3107	71	13	developed	develop	VERB
cana-3107	71	14	in	in	ADP
cana-3107	71	15	response	response	NOUN
cana-3107	71	16	to	to	ADP
cana-3107	71	17	the	the	DET
cana-3107	71	18	increasing	increase	VERB
cana-3107	71	19	biological	biological	ADJ
cana-3107	71	20	demand	demand	NOUN
cana-3107	71	21	and	and	CCONJ
cana-3107	71	22	the	the	DET
cana-3107	71	23	reducing	reduce	VERB
cana-3107	71	24	worker	worker	NOUN
cana-3107	71	25	quantity	quantity	NOUN
cana-3107	71	26	.	.	PUNCT
cana-3107	72	1	their	their	PRON
cana-3107	72	2	problem	problem	NOUN
cana-3107	72	3	has	have	AUX
cana-3107	72	4	been	be	AUX
cana-3107	72	5	worked	work	VERB
cana-3107	72	6	on	on	ADP
cana-3107	72	7	by	by	ADP
cana-3107	72	8	both	both	DET
cana-3107	72	9	computer	computer	NOUN
cana-3107	72	10	scientists	scientist	NOUN
cana-3107	72	11	and	and	CCONJ
cana-3107	72	12	biologists	biologist	NOUN
cana-3107	72	13	.	.	PUNCT
cana-3107	73	1	this	this	DET
cana-3107	73	2	review	review	NOUN
cana-3107	73	3	looks	look	VERB
cana-3107	73	4	at	at	ADP
cana-3107	73	5	forty	forty	NUM
cana-3107	73	6	-	-	PUNCT
cana-3107	73	7	four	four	NUM
cana-3107	73	8	research	research	NOUN
cana-3107	73	9	on	on	ADP
cana-3107	73	10	the	the	DET
cana-3107	73	11	subject	subject	NOUN
cana-3107	73	12	,	,	PUNCT
cana-3107	73	13	attempting	attempt	VERB
cana-3107	73	14	to	to	PART
cana-3107	73	15	provide	provide	VERB
cana-3107	73	16	a	a	DET
cana-3107	73	17	comprehensive	comprehensive	ADJ
cana-3107	73	18	picture	picture	NOUN
cana-3107	73	19	of	of	ADP
cana-3107	73	20	the	the	DET
cana-3107	73	21	scientific	scientific	ADJ
cana-3107	73	22	evidence	evidence	NOUN
cana-3107	73	23	and	and	CCONJ
cana-3107	73	24	how	how	SCONJ
cana-3107	73	25	the	the	DET
cana-3107	73	26	issue	issue	NOUN
cana-3107	73	27	was	be	AUX
cana-3107	73	28	treated	treat	VERB
cana-3107	73	29	.	.	PUNCT
cana-3107	74	1	opinions	opinion	NOUN
cana-3107	74	2	are	be	AUX
cana-3107	74	3	taken	take	VERB
cana-3107	74	4	on	on	ADP
cana-3107	74	5	the	the	DET
cana-3107	74	6	image	image	NOUN
cana-3107	74	7	-	-	PUNCT
cana-3107	74	8	taking	take	VERB
cana-3107	74	9	process	process	NOUN
cana-3107	74	10	,	,	PUNCT
cana-3107	74	11	feature	feature	NOUN
cana-3107	74	12	extraction	extraction	NOUN
cana-3107	74	13	,	,	PUNCT
cana-3107	74	14	classification	classification	NOUN
cana-3107	74	15	strategies	strategy	NOUN
cana-3107	74	16	,	,	PUNCT
cana-3107	74	17	and	and	CCONJ
cana-3107	74	18	datasets	dataset	NOUN
cana-3107	74	19	used	use	VERB
cana-3107	74	20	for	for	ADP
cana-3107	74	21	testing	testing	NOUN
cana-3107	74	22	.	.	PUNCT
cana-3107	75	1	the	the	DET
cana-3107	75	2	technique	technique	NOUN
cana-3107	75	3	and	and	CCONJ
cana-3107	75	4	effectiveness	effectiveness	NOUN
cana-3107	75	5	of	of	ADP
cana-3107	75	6	catching	catch	VERB
cana-3107	75	7	tomato	tomato	NOUN
cana-3107	75	8	whitefly	whitefly	NOUN
cana-3107	75	9	and	and	CCONJ
cana-3107	75	10	its	its	PRON
cana-3107	75	11	predatory	predatory	NOUN
cana-3107	75	12	bugs	bug	NOUN
cana-3107	75	13	using	use	VERB
cana-3107	75	14	yellow	yellow	ADJ
cana-3107	75	15	sticky	sticky	ADJ
cana-3107	75	16	traps	trap	NOUN
cana-3107	75	17	was	be	AUX
cana-3107	75	18	given	give	VERB
cana-3107	75	19	by	by	ADP
cana-3107	75	20	ard	ard	PROPN
cana-3107	75	21	nieuwenhuizen	nieuwenhuizen	PROPN
cana-3107	75	22	et	et	PROPN
cana-3107	75	23	al	al	PROPN
cana-3107	75	24	.	.	PUNCT
cana-3107	76	1	[	[	X
cana-3107	76	2	13	13	NUM
cana-3107	76	3	]	]	PUNCT
cana-3107	76	4	.	.	PUNCT
cana-3107	77	1	these	these	DET
cana-3107	77	2	devices	device	NOUN
cana-3107	77	3	are	be	AUX
cana-3107	77	4	photographed	photograph	VERB
cana-3107	77	5	using	use	VERB
cana-3107	77	6	a	a	DET
cana-3107	77	7	digital	digital	ADJ
cana-3107	77	8	single	single	ADJ
cana-3107	77	9	-	-	PUNCT
cana-3107	77	10	lens	lens	NOUN
cana-3107	77	11	reflex	reflex	ADJ
cana-3107	77	12	camera	camera	NOUN
cana-3107	77	13	and	and	CCONJ
cana-3107	77	14	a	a	DET
cana-3107	77	15	smartphone	smartphone	NOUN
cana-3107	77	16	camera	camera	NOUN
cana-3107	77	17	in	in	ADP
cana-3107	77	18	both	both	DET
cana-3107	77	19	controlled	controlled	ADJ
cana-3107	77	20	and	and	CCONJ
cana-3107	77	21	natural	natural	ADJ
cana-3107	77	22	lighting	lighting	NOUN
cana-3107	77	23	settings	setting	NOUN
cana-3107	77	24	.	.	PUNCT
cana-3107	78	1	the	the	DET
cana-3107	78	2	procedure	procedure	NOUN
cana-3107	78	3	includes	include	VERB
cana-3107	78	4	the	the	DET
cana-3107	78	5	following	following	ADJ
cana-3107	78	6	actions	action	NOUN
cana-3107	78	7	.	.	PUNCT
cana-3107	79	1	the	the	DET
cana-3107	79	2	first	first	ADJ
cana-3107	79	3	step	step	NOUN
cana-3107	79	4	is	be	AUX
cana-3107	79	5	to	to	PART
cana-3107	79	6	manually	manually	ADV
cana-3107	79	7	annotate	annotate	VERB
cana-3107	79	8	and	and	CCONJ
cana-3107	79	9	subset	subset	VERB
cana-3107	79	10	the	the	DET
cana-3107	79	11	images	image	NOUN
cana-3107	79	12	.	.	PUNCT
cana-3107	80	1	step	step	VERB
cana-3107	80	2	two	two	NUM
cana-3107	80	3	involves	involve	VERB
cana-3107	80	4	teaching	teach	VERB
cana-3107	80	5	a	a	DET
cana-3107	80	6	convolutional	convolutional	ADJ
cana-3107	80	7	neural	neural	ADJ
cana-3107	80	8	network	network	NOUN
cana-3107	80	9	to	to	PART
cana-3107	80	10	use	use	VERB
cana-3107	80	11	deep	deep	ADJ
cana-3107	80	12	learning	learning	NOUN
cana-3107	80	13	.	.	PUNCT
cana-3107	81	1	the	the	DET
cana-3107	81	2	third	third	ADJ
cana-3107	81	3	stage	stage	NOUN
cana-3107	81	4	involves	involve	VERB
cana-3107	81	5	sorting	sort	VERB
cana-3107	81	6	the	the	DET
cana-3107	81	7	photos	photo	NOUN
cana-3107	81	8	into	into	ADP
cana-3107	81	9	categories	category	NOUN
cana-3107	81	10	.	.	PUNCT
cana-3107	82	1	the	the	DET
cana-3107	82	2	last	last	ADJ
cana-3107	82	3	stage	stage	NOUN
cana-3107	82	4	is	be	AUX
cana-3107	82	5	a	a	DET
cana-3107	82	6	check	check	NOUN
cana-3107	82	7	against	against	ADP
cana-3107	82	8	manual	manual	ADJ
cana-3107	82	9	counts	count	NOUN
cana-3107	82	10	of	of	ADP
cana-3107	82	11	insects	insect	NOUN
cana-3107	82	12	.	.	PUNCT
cana-3107	83	1	when	when	SCONJ
cana-3107	83	2	applied	apply	VERB
cana-3107	83	3	to	to	ADP
cana-3107	83	4	the	the	DET
cana-3107	83	5	detection	detection	NOUN
cana-3107	83	6	of	of	ADP
cana-3107	83	7	insects	insect	NOUN
cana-3107	83	8	,	,	PUNCT
cana-3107	83	9	deep	deep	ADJ
cana-3107	83	10	learning	learning	NOUN
cana-3107	83	11	achieved	achieve	VERB
cana-3107	83	12	an	an	DET
cana-3107	83	13	average	average	ADJ
cana-3107	83	14	accuracy	accuracy	NOUN
cana-3107	83	15	of	of	ADP
cana-3107	83	16	87.4	87.4	NUM
cana-3107	83	17	percent	percent	NOUN
cana-3107	83	18	.	.	PUNCT
cana-3107	84	1	insects	insect	NOUN
cana-3107	84	2	in	in	ADP
cana-3107	84	3	smartphone	smartphone	NOUN
cana-3107	84	4	photographs	photograph	NOUN
cana-3107	84	5	were	be	AUX
cana-3107	84	6	tallied	tally	VERB
cana-3107	84	7	by	by	ADP
cana-3107	84	8	both	both	DET
cana-3107	84	9	humans	human	NOUN
cana-3107	84	10	and	and	CCONJ
cana-3107	84	11	deep	deep	ADJ
cana-3107	84	12	communications	communication	NOUN
cana-3107	84	13	on	on	ADP
cana-3107	84	14	applied	apply	VERB
cana-3107	84	15	nonlinear	nonlinear	ADJ
cana-3107	84	16	analysis	analysis	NOUN
cana-3107	84	17	issn	issn	NOUN
cana-3107	84	18	:	:	PUNCT
cana-3107	84	19	1074	1074	NUM
cana-3107	84	20	-	-	PUNCT
cana-3107	84	21	133x	133x	NUM
cana-3107	84	22	vol	vol	NOUN
cana-3107	84	23	32	32	NUM
cana-3107	84	24	no	no	NOUN
cana-3107	84	25	.	.	PUNCT
cana-3107	85	1	5s	5s	NUM
cana-3107	85	2	(	(	PUNCT
cana-3107	85	3	2025	2025	NUM
cana-3107	85	4	)	)	PUNCT
cana-3107	85	5	364	364	NUM
cana-3107	85	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	85	7	learning	learning	NOUN
cana-3107	85	8	systems	system	NOUN
cana-3107	85	9	,	,	PUNCT
cana-3107	85	10	with	with	ADP
cana-3107	85	11	a	a	DET
cana-3107	85	12	correlation	correlation	NOUN
cana-3107	85	13	of	of	ADP
cana-3107	85	14	above	above	ADP
cana-3107	85	15	0.95	0.95	NUM
cana-3107	85	16	.	.	PUNCT
cana-3107	86	1	the	the	DET
cana-3107	86	2	techniques	technique	NOUN
cana-3107	86	3	used	use	VERB
cana-3107	86	4	demonstrate	demonstrate	VERB
cana-3107	86	5	that	that	SCONJ
cana-3107	86	6	the	the	DET
cana-3107	86	7	offered	offer	VERB
cana-3107	86	8	data	datum	NOUN
cana-3107	86	9	may	may	AUX
cana-3107	86	10	be	be	AUX
cana-3107	86	11	transferred	transfer	VERB
cana-3107	86	12	from	from	ADP
cana-3107	86	13	controlled	control	VERB
cana-3107	86	14	settings	setting	NOUN
cana-3107	86	15	required	require	VERB
cana-3107	86	16	for	for	ADP
cana-3107	86	17	training	training	NOUN
cana-3107	86	18	data	datum	NOUN
cana-3107	86	19	utilized	utilize	VERB
cana-3107	86	20	in	in	ADP
cana-3107	86	21	smartphone	smartphone	NOUN
cana-3107	86	22	imaging	imaging	NOUN
cana-3107	86	23	.	.	PUNCT
cana-3107	87	1	conventional	conventional	ADJ
cana-3107	87	2	detection	detection	NOUN
cana-3107	87	3	and	and	CCONJ
cana-3107	87	4	eye	eye	NOUN
cana-3107	87	5	observation	observation	NOUN
cana-3107	87	6	approaches	approach	NOUN
cana-3107	87	7	,	,	PUNCT
cana-3107	87	8	as	as	SCONJ
cana-3107	87	9	noted	note	VERB
cana-3107	87	10	by	by	ADP
cana-3107	87	11	vivek	vivek	PROPN
cana-3107	87	12	tiwari	tiwari	PROPN
cana-3107	87	13	et	et	PROPN
cana-3107	87	14	al	al	PROPN
cana-3107	87	15	.	.	PUNCT
cana-3107	88	1	[	[	X
cana-3107	88	2	14	14	NUM
cana-3107	88	3	]	]	PUNCT
cana-3107	88	4	,	,	PUNCT
cana-3107	88	5	are	be	AUX
cana-3107	88	6	ineffective	ineffective	ADJ
cana-3107	88	7	for	for	ADP
cana-3107	88	8	big	big	ADJ
cana-3107	88	9	crops	crop	NOUN
cana-3107	88	10	.	.	PUNCT
cana-3107	89	1	they	they	PRON
cana-3107	89	2	presented	present	VERB
cana-3107	89	3	mask	mask	NOUN
cana-3107	89	4	rcnn	rcnn	PROPN
cana-3107	89	5	,	,	PUNCT
cana-3107	89	6	a	a	DET
cana-3107	89	7	theoretically	theoretically	ADV
cana-3107	89	8	versatile	versatile	ADJ
cana-3107	89	9	and	and	CCONJ
cana-3107	89	10	broad	broad	ADJ
cana-3107	89	11	framework	framework	NOUN
cana-3107	89	12	for	for	ADP
cana-3107	89	13	identifying	identify	VERB
cana-3107	89	14	,	,	PUNCT
cana-3107	89	15	localizing	localize	VERB
cana-3107	89	16	,	,	PUNCT
cana-3107	89	17	and	and	CCONJ
cana-3107	89	18	masking	mask	VERB
cana-3107	89	19	crop	crop	NOUN
cana-3107	89	20	-	-	PUNCT
cana-3107	89	21	damaging	damage	VERB
cana-3107	89	22	insects	insect	NOUN
cana-3107	89	23	.	.	PUNCT
cana-3107	90	1	it	it	PRON
cana-3107	90	2	combines	combine	VERB
cana-3107	90	3	the	the	DET
cana-3107	90	4	processes	process	NOUN
cana-3107	90	5	of	of	ADP
cana-3107	90	6	object	object	NOUN
cana-3107	90	7	detection	detection	NOUN
cana-3107	90	8	with	with	ADP
cana-3107	90	9	instance	instance	NOUN
cana-3107	90	10	segmentation	segmentation	NOUN
cana-3107	90	11	,	,	PUNCT
cana-3107	90	12	which	which	PRON
cana-3107	90	13	entails	entail	VERB
cana-3107	90	14	assigning	assign	VERB
cana-3107	90	15	each	each	DET
cana-3107	90	16	detected	detect	VERB
cana-3107	90	17	object	object	NOUN
cana-3107	90	18	's	's	PART
cana-3107	90	19	pixel	pixel	NOUN
cana-3107	90	20	to	to	ADP
cana-3107	90	21	one	one	NUM
cana-3107	90	22	of	of	ADP
cana-3107	90	23	many	many	ADJ
cana-3107	90	24	predetermined	predetermine	VERB
cana-3107	90	25	classes	class	NOUN
cana-3107	90	26	.	.	PUNCT
cana-3107	91	1	the	the	DET
cana-3107	91	2	main	main	ADJ
cana-3107	91	3	goal	goal	NOUN
cana-3107	91	4	of	of	ADP
cana-3107	91	5	mask	mask	NOUN
cana-3107	91	6	rcnn	rcnn	PROPN
cana-3107	91	7	is	be	AUX
cana-3107	91	8	to	to	PART
cana-3107	91	9	generate	generate	VERB
cana-3107	91	10	a	a	DET
cana-3107	91	11	mask	mask	NOUN
cana-3107	91	12	that	that	PRON
cana-3107	91	13	may	may	AUX
cana-3107	91	14	be	be	AUX
cana-3107	91	15	used	use	VERB
cana-3107	91	16	to	to	PART
cana-3107	91	17	identify	identify	VERB
cana-3107	91	18	the	the	DET
cana-3107	91	19	features	feature	NOUN
cana-3107	91	20	and	and	CCONJ
cana-3107	91	21	locations	location	NOUN
cana-3107	91	22	inside	inside	ADP
cana-3107	91	23	an	an	DET
cana-3107	91	24	image	image	NOUN
cana-3107	91	25	.	.	PUNCT
cana-3107	92	1	insect	insect	NOUN
cana-3107	92	2	detection	detection	NOUN
cana-3107	92	3	and	and	CCONJ
cana-3107	92	4	mask	mask	NOUN
cana-3107	92	5	generation	generation	NOUN
cana-3107	92	6	are	be	AUX
cana-3107	92	7	performed	perform	VERB
cana-3107	92	8	with	with	ADP
cana-3107	92	9	great	great	ADJ
cana-3107	92	10	efficacy	efficacy	NOUN
cana-3107	92	11	.	.	PUNCT
cana-3107	93	1	this	this	PRON
cana-3107	93	2	shortens	shorten	VERB
cana-3107	93	3	the	the	DET
cana-3107	93	4	time	time	NOUN
cana-3107	93	5	it	it	PRON
cana-3107	93	6	takes	take	VERB
cana-3107	93	7	to	to	PART
cana-3107	93	8	find	find	VERB
cana-3107	93	9	insects	insect	NOUN
cana-3107	93	10	and	and	CCONJ
cana-3107	93	11	requires	require	VERB
cana-3107	93	12	less	less	ADJ
cana-3107	93	13	human	human	ADJ
cana-3107	93	14	involvement	involvement	NOUN
cana-3107	93	15	.	.	PUNCT
cana-3107	94	1	proposed	propose	VERB
cana-3107	94	2	model	model	NOUN
cana-3107	94	3	is	be	AUX
cana-3107	94	4	now	now	ADV
cana-3107	94	5	trained	train	VERB
cana-3107	94	6	with	with	ADP
cana-3107	94	7	four	four	NUM
cana-3107	94	8	insects	insect	NOUN
cana-3107	94	9	,	,	PUNCT
cana-3107	94	10	but	but	CCONJ
cana-3107	94	11	may	may	AUX
cana-3107	94	12	be	be	AUX
cana-3107	94	13	readily	readily	ADV
cana-3107	94	14	expanded	expand	VERB
cana-3107	94	15	to	to	PART
cana-3107	94	16	categorize	categorize	VERB
cana-3107	94	17	additional	additional	ADJ
cana-3107	94	18	insects	insect	NOUN
cana-3107	94	19	,	,	PUNCT
cana-3107	94	20	assisting	assist	VERB
cana-3107	94	21	farmers	farmer	NOUN
cana-3107	94	22	in	in	ADP
cana-3107	94	23	accurate	accurate	ADJ
cana-3107	94	24	insect	insect	NOUN
cana-3107	94	25	identification	identification	NOUN
cana-3107	94	26	and	and	CCONJ
cana-3107	94	27	the	the	DET
cana-3107	94	28	use	use	NOUN
cana-3107	94	29	of	of	ADP
cana-3107	94	30	appropriate	appropriate	ADJ
cana-3107	94	31	pesticides	pesticide	NOUN
cana-3107	94	32	(	(	PUNCT
cana-3107	94	33	by	by	ADP
cana-3107	94	34	research	research	NOUN
cana-3107	94	35	into	into	ADP
cana-3107	94	36	insect	insect	NOUN
cana-3107	94	37	kind	kind	NOUN
cana-3107	94	38	and	and	CCONJ
cana-3107	94	39	population	population	NOUN
cana-3107	94	40	)	)	PUNCT
cana-3107	94	41	.	.	PUNCT
cana-3107	95	1	this	this	PRON
cana-3107	95	2	will	will	AUX
cana-3107	95	3	make	make	VERB
cana-3107	95	4	crop	crop	NOUN
cana-3107	95	5	protection	protection	NOUN
cana-3107	95	6	easier	easy	ADJ
cana-3107	95	7	for	for	ADP
cana-3107	95	8	them	they	PRON
cana-3107	95	9	.	.	PUNCT
cana-3107	96	1	moreover	moreover	ADV
cana-3107	96	2	,	,	PUNCT
cana-3107	96	3	by	by	ADP
cana-3107	96	4	incorporating	incorporate	VERB
cana-3107	96	5	this	this	DET
cana-3107	96	6	model	model	NOUN
cana-3107	96	7	into	into	ADP
cana-3107	96	8	a	a	DET
cana-3107	96	9	mobile	mobile	NOUN
cana-3107	96	10	-	-	PUNCT
cana-3107	96	11	based	base	VERB
cana-3107	96	12	application	application	NOUN
cana-3107	96	13	,	,	PUNCT
cana-3107	96	14	it	it	PRON
cana-3107	96	15	may	may	AUX
cana-3107	96	16	be	be	AUX
cana-3107	96	17	made	make	VERB
cana-3107	96	18	readily	readily	ADV
cana-3107	96	19	available	available	ADJ
cana-3107	96	20	to	to	ADP
cana-3107	96	21	them	they	PRON
cana-3107	96	22	.	.	PUNCT
cana-3107	97	1	the	the	DET
cana-3107	97	2	faster	fast	ADJ
cana-3107	97	3	r	r	NOUN
cana-3107	97	4	-	-	PUNCT
cana-3107	97	5	cnn	cnn	NOUN
cana-3107	97	6	-	-	PUNCT
cana-3107	97	7	based	base	VERB
cana-3107	97	8	object	object	NOUN
cana-3107	97	9	identification	identification	NOUN
cana-3107	97	10	method	method	NOUN
cana-3107	97	11	was	be	AUX
cana-3107	97	12	used	use	VERB
cana-3107	97	13	by	by	ADP
cana-3107	97	14	yufeng	yufeng	PROPN
cana-3107	97	15	shen	shen	PROPN
cana-3107	97	16	et	et	PROPN
cana-3107	97	17	al	al	PROPN
cana-3107	97	18	.	.	PUNCT
cana-3107	98	1	[	[	X
cana-3107	98	2	15	15	NUM
cana-3107	98	3	]	]	PUNCT
cana-3107	98	4	to	to	PART
cana-3107	98	5	identify	identify	VERB
cana-3107	98	6	stored	store	VERB
cana-3107	98	7	-	-	PUNCT
cana-3107	98	8	grain	grain	NOUN
cana-3107	98	9	insects	insect	NOUN
cana-3107	98	10	in	in	ADP
cana-3107	98	11	field	field	NOUN
cana-3107	98	12	conditions	condition	NOUN
cana-3107	98	13	with	with	ADP
cana-3107	98	14	contaminants	contaminant	NOUN
cana-3107	98	15	.	.	PUNCT
cana-3107	99	1	the	the	DET
cana-3107	99	2	technique	technique	NOUN
cana-3107	99	3	could	could	AUX
cana-3107	99	4	identify	identify	VERB
cana-3107	99	5	the	the	DET
cana-3107	99	6	insects	insect	NOUN
cana-3107	99	7	despite	despite	SCONJ
cana-3107	99	8	their	their	PRON
cana-3107	99	9	weak	weak	ADJ
cana-3107	99	10	adherence	adherence	NOUN
cana-3107	99	11	.	.	PUNCT
cana-3107	100	1	in	in	ADP
cana-3107	100	2	addition	addition	NOUN
cana-3107	100	3	to	to	ADP
cana-3107	100	4	developing	develop	VERB
cana-3107	100	5	deep	deep	ADJ
cana-3107	100	6	convolutional	convolutional	ADJ
cana-3107	100	7	neural	neural	ADJ
cana-3107	100	8	networks	network	NOUN
cana-3107	100	9	,	,	PUNCT
cana-3107	100	10	an	an	DET
cana-3107	100	11	enhanced	enhanced	ADJ
cana-3107	100	12	inception	inception	NOUN
cana-3107	100	13	network	network	NOUN
cana-3107	100	14	was	be	AUX
cana-3107	100	15	created	create	VERB
cana-3107	100	16	to	to	PART
cana-3107	100	17	increase	increase	VERB
cana-3107	100	18	the	the	DET
cana-3107	100	19	precision	precision	NOUN
cana-3107	100	20	with	with	ADP
cana-3107	100	21	which	which	PRON
cana-3107	100	22	microscopic	microscopic	ADJ
cana-3107	100	23	insects	insect	NOUN
cana-3107	100	24	could	could	AUX
cana-3107	100	25	be	be	AUX
cana-3107	100	26	detected	detect	VERB
cana-3107	100	27	.	.	PUNCT
cana-3107	101	1	with	with	ADP
cana-3107	101	2	an	an	DET
cana-3107	101	3	increased	increase	VERB
cana-3107	101	4	map	map	NOUN
cana-3107	101	5	of	of	ADP
cana-3107	101	6	87.99	87.99	NUM
cana-3107	101	7	,	,	PUNCT
cana-3107	101	8	the	the	DET
cana-3107	101	9	enhanced	enhanced	ADJ
cana-3107	101	10	inception	inception	NOUN
cana-3107	101	11	network	network	NOUN
cana-3107	101	12	outperformed	outperform	VERB
cana-3107	101	13	both	both	CCONJ
cana-3107	101	14	the	the	DET
cana-3107	101	15	suggested	suggested	ADJ
cana-3107	101	16	inception	inception	PROPN
cana-3107	101	17	network	network	NOUN
cana-3107	101	18	(	(	PUNCT
cana-3107	101	19	81.39	81.39	NUM
cana-3107	101	20	points	point	NOUN
cana-3107	101	21	)	)	PUNCT
cana-3107	101	22	and	and	CCONJ
cana-3107	101	23	vgg16	vgg16	PROPN
cana-3107	101	24	(	(	PUNCT
cana-3107	101	25	82.66	82.66	NUM
cana-3107	101	26	points	point	NOUN
cana-3107	101	27	)	)	PUNCT
cana-3107	101	28	.	.	PUNCT
cana-3107	102	1	we	we	PRON
cana-3107	102	2	also	also	ADV
cana-3107	102	3	reduced	reduce	VERB
cana-3107	102	4	the	the	DET
cana-3107	102	5	size	size	NOUN
cana-3107	102	6	of	of	ADP
cana-3107	102	7	the	the	DET
cana-3107	102	8	model	model	NOUN
cana-3107	102	9	from	from	ADP
cana-3107	102	10	261	261	NUM
cana-3107	102	11	m	m	NOUN
cana-3107	102	12	to	to	ADP
cana-3107	102	13	62	62	NUM
cana-3107	102	14	m	m	VERB
cana-3107	102	15	using	use	VERB
cana-3107	102	16	the	the	DET
cana-3107	102	17	svd	svd	PROPN
cana-3107	102	18	method	method	NOUN
cana-3107	102	19	,	,	PUNCT
cana-3107	102	20	and	and	CCONJ
cana-3107	102	21	the	the	DET
cana-3107	102	22	resulting	result	VERB
cana-3107	102	23	map	map	NOUN
cana-3107	102	24	improvement	improvement	NOUN
cana-3107	102	25	was	be	AUX
cana-3107	102	26	3.34	3.34	NUM
cana-3107	102	27	.	.	PUNCT
cana-3107	103	1	the	the	DET
cana-3107	103	2	compact	compact	ADJ
cana-3107	103	3	deep	deep	ADJ
cana-3107	103	4	network	network	NOUN
cana-3107	103	5	cpafnet	cpafnet	NOUN
cana-3107	103	6	was	be	AUX
cana-3107	103	7	developed	develop	VERB
cana-3107	103	8	by	by	ADP
cana-3107	103	9	jin	jin	PROPN
cana-3107	103	10	wang	wang	PROPN
cana-3107	103	11	et	et	PROPN
cana-3107	103	12	al	al	PROPN
cana-3107	103	13	.	.	PUNCT
cana-3107	104	1	[	[	X
cana-3107	104	2	16	16	NUM
cana-3107	104	3	]	]	PUNCT
cana-3107	104	4	.	.	PUNCT
cana-3107	105	1	the	the	DET
cana-3107	105	2	model	model	NOUN
cana-3107	105	3	achieved	achieve	VERB
cana-3107	105	4	a	a	DET
cana-3107	105	5	recognition	recognition	NOUN
cana-3107	105	6	accuracy	accuracy	NOUN
cana-3107	105	7	of	of	ADP
cana-3107	105	8	92.63	92.63	NUM
cana-3107	105	9	percent	percent	NOUN
cana-3107	105	10	after	after	ADP
cana-3107	105	11	a	a	DET
cana-3107	105	12	6000	6000	NUM
cana-3107	105	13	-	-	PUNCT
cana-3107	105	14	step	step	NOUN
cana-3107	105	15	iterative	iterative	NOUN
cana-3107	105	16	training	training	NOUN
cana-3107	105	17	experiment	experiment	NOUN
cana-3107	105	18	,	,	PUNCT
cana-3107	105	19	surpassing	surpass	VERB
cana-3107	105	20	the	the	DET
cana-3107	105	21	performance	performance	NOUN
cana-3107	105	22	of	of	ADP
cana-3107	105	23	the	the	DET
cana-3107	105	24	standard	standard	ADJ
cana-3107	105	25	deep	deep	ADJ
cana-3107	105	26	learning	learning	NOUN
cana-3107	105	27	models	model	NOUN
cana-3107	105	28	vgga	vgga	VERB
cana-3107	105	29	,	,	PUNCT
cana-3107	105	30	vgg16	vgg16	PROPN
cana-3107	105	31	,	,	PUNCT
cana-3107	105	32	inception	inception	NOUN
cana-3107	105	33	v3	v3	PROPN
cana-3107	105	34	,	,	PUNCT
cana-3107	105	35	and	and	CCONJ
cana-3107	105	36	resnet50	resnet50	NOUN
cana-3107	105	37	.	.	PUNCT
cana-3107	106	1	with	with	ADP
cana-3107	106	2	a	a	DET
cana-3107	106	3	training	training	NOUN
cana-3107	106	4	duration	duration	NOUN
cana-3107	106	5	that	that	PRON
cana-3107	106	6	is	be	AUX
cana-3107	106	7	just	just	ADV
cana-3107	106	8	1	1	NUM
cana-3107	106	9	hour	hour	NOUN
cana-3107	106	10	and	and	CCONJ
cana-3107	106	11	sixteen	sixteen	NUM
cana-3107	106	12	minutes	minute	NOUN
cana-3107	106	13	,	,	PUNCT
cana-3107	106	14	the	the	DET
cana-3107	106	15	cpafnet	cpafnet	ADJ
cana-3107	106	16	model	model	NOUN
cana-3107	106	17	outperforms	outperform	VERB
cana-3107	106	18	even	even	ADV
cana-3107	106	19	the	the	DET
cana-3107	106	20	most	most	ADV
cana-3107	106	21	conventional	conventional	ADJ
cana-3107	106	22	deep	deep	ADJ
cana-3107	106	23	learning	learning	NOUN
cana-3107	106	24	models	model	NOUN
cana-3107	106	25	.	.	PUNCT
cana-3107	107	1	in	in	ADP
cana-3107	107	2	order	order	NOUN
cana-3107	107	3	to	to	PART
cana-3107	107	4	classify	classify	VERB
cana-3107	107	5	photos	photo	NOUN
cana-3107	107	6	of	of	ADP
cana-3107	107	7	soybean	soybean	NOUN
cana-3107	107	8	pests	pest	NOUN
cana-3107	107	9	,	,	PUNCT
cana-3107	107	10	everton	everton	PROPN
cana-3107	107	11	castelao	castelao	PROPN
cana-3107	107	12	tetila	tetila	PROPN
cana-3107	107	13	et	et	PROPN
cana-3107	107	14	al	al	PROPN
cana-3107	107	15	.	.	PUNCT
cana-3107	108	1	[	[	X
cana-3107	108	2	17	17	NUM
cana-3107	108	3	]	]	PUNCT
cana-3107	108	4	compared	compare	VERB
cana-3107	108	5	the	the	DET
cana-3107	108	6	efficacy	efficacy	NOUN
cana-3107	108	7	of	of	ADP
cana-3107	108	8	the	the	DET
cana-3107	108	9	inception	inception	NOUN
cana-3107	108	10	-	-	PUNCT
cana-3107	108	11	v3	v3	PROPN
cana-3107	108	12	,	,	PUNCT
cana-3107	108	13	resnet-50	resnet-50	PROPN
cana-3107	108	14	,	,	PUNCT
cana-3107	108	15	vgg-16	vgg-16	NOUN
cana-3107	108	16	,	,	PUNCT
cana-3107	108	17	vgg-19	vgg-19	NOUN
cana-3107	108	18	,	,	PUNCT
cana-3107	108	19	and	and	CCONJ
cana-3107	108	20	xception	xception	NOUN
cana-3107	108	21	deep	deep	ADJ
cana-3107	108	22	learning	learning	NOUN
cana-3107	108	23	architectures	architecture	NOUN
cana-3107	108	24	.	.	PUNCT
cana-3107	109	1	the	the	DET
cana-3107	109	2	slic	slic	PROPN
cana-3107	109	3	superpixels	superpixel	NOUN
cana-3107	109	4	technique	technique	NOUN
cana-3107	109	5	was	be	AUX
cana-3107	109	6	investigated	investigate	VERB
cana-3107	109	7	for	for	ADP
cana-3107	109	8	use	use	NOUN
cana-3107	109	9	in	in	ADP
cana-3107	109	10	an	an	DET
cana-3107	109	11	image	image	NOUN
cana-3107	109	12	segmentation	segmentation	NOUN
cana-3107	109	13	phase	phase	NOUN
cana-3107	109	14	to	to	PART
cana-3107	109	15	separate	separate	VERB
cana-3107	109	16	the	the	DET
cana-3107	109	17	insects	insect	NOUN
cana-3107	109	18	in	in	ADP
cana-3107	109	19	the	the	DET
cana-3107	109	20	field	field	NOUN
cana-3107	109	21	-	-	PUNCT
cana-3107	109	22	collected	collect	VERB
cana-3107	109	23	photos	photo	NOUN
cana-3107	109	24	.	.	PUNCT
cana-3107	110	1	the	the	DET
cana-3107	110	2	performance	performance	NOUN
cana-3107	110	3	of	of	ADP
cana-3107	110	4	deep	deep	ADJ
cana-3107	110	5	learning	learning	NOUN
cana-3107	110	6	architectures	architecture	NOUN
cana-3107	110	7	for	for	ADP
cana-3107	110	8	various	various	ADJ
cana-3107	110	9	finetuning	finetuning	NOUN
cana-3107	110	10	and	and	CCONJ
cana-3107	110	11	transfer	transfer	NOUN
cana-3107	110	12	learning	learning	NOUN
cana-3107	110	13	techniques	technique	NOUN
cana-3107	110	14	was	be	AUX
cana-3107	110	15	compared	compare	VERB
cana-3107	110	16	to	to	ADP
cana-3107	110	17	that	that	PRON
cana-3107	110	18	of	of	ADP
cana-3107	110	19	more	more	ADJ
cana-3107	110	20	conventional	conventional	ADJ
cana-3107	110	21	feature	feature	NOUN
cana-3107	110	22	extraction	extraction	NOUN
cana-3107	110	23	and	and	CCONJ
cana-3107	110	24	learning	learn	VERB
cana-3107	110	25	methods	method	NOUN
cana-3107	110	26	during	during	ADP
cana-3107	110	27	the	the	DET
cana-3107	110	28	classification	classification	NOUN
cana-3107	110	29	challenge	challenge	NOUN
cana-3107	110	30	.	.	PUNCT
cana-3107	111	1	the	the	DET
cana-3107	111	2	resnet-50	resnet-50	PROPN
cana-3107	111	3	architecture	architecture	NOUN
cana-3107	111	4	,	,	PUNCT
cana-3107	111	5	which	which	PRON
cana-3107	111	6	was	be	AUX
cana-3107	111	7	trained	train	VERB
cana-3107	111	8	via	via	ADP
cana-3107	111	9	fine	fine	ADV
cana-3107	111	10	-	-	PUNCT
cana-3107	111	11	tuning	tuning	NOUN
cana-3107	111	12	computed	compute	VERB
cana-3107	111	13	weights	weight	NOUN
cana-3107	111	14	,	,	PUNCT
cana-3107	111	15	achieved	achieve	VERB
cana-3107	111	16	an	an	DET
cana-3107	111	17	accuracy	accuracy	NOUN
cana-3107	111	18	of	of	ADP
cana-3107	111	19	up	up	ADP
cana-3107	111	20	to	to	PART
cana-3107	111	21	93.82	93.82	NUM
cana-3107	111	22	%	%	NOUN
cana-3107	111	23	in	in	ADP
cana-3107	111	24	experiments	experiment	NOUN
cana-3107	111	25	,	,	PUNCT
cana-3107	111	26	which	which	PRON
cana-3107	111	27	was	be	AUX
cana-3107	111	28	much	much	ADV
cana-3107	111	29	greater	great	ADJ
cana-3107	111	30	than	than	ADP
cana-3107	111	31	that	that	PRON
cana-3107	111	32	of	of	ADP
cana-3107	111	33	previous	previous	ADJ
cana-3107	111	34	machine	machine	NOUN
cana-3107	111	35	learning	learning	NOUN
cana-3107	111	36	approaches	approach	NOUN
cana-3107	111	37	.	.	PUNCT
cana-3107	112	1	as	as	SCONJ
cana-3107	112	2	shown	show	VERB
cana-3107	112	3	by	by	ADP
cana-3107	112	4	the	the	DET
cana-3107	112	5	findings	finding	NOUN
cana-3107	112	6	,	,	PUNCT
cana-3107	112	7	the	the	DET
cana-3107	112	8	analyzed	analyze	VERB
cana-3107	112	9	designs	design	NOUN
cana-3107	112	10	generalize	generalize	VERB
cana-3107	112	11	well	well	ADV
cana-3107	112	12	in	in	ADP
cana-3107	112	13	soybean	soybean	NOUN
cana-3107	112	14	pests	pest	NOUN
cana-3107	112	15	datasets	dataset	NOUN
cana-3107	112	16	and	and	CCONJ
cana-3107	112	17	may	may	AUX
cana-3107	112	18	aid	aid	VERB
cana-3107	112	19	professionals	professional	NOUN
cana-3107	112	20	and	and	CCONJ
cana-3107	112	21	farmers	farmer	NOUN
cana-3107	112	22	in	in	ADP
cana-3107	112	23	keeping	keep	VERB
cana-3107	112	24	pest	pest	NOUN
cana-3107	112	25	populations	population	NOUN
cana-3107	112	26	under	under	ADP
cana-3107	112	27	control	control	NOUN
cana-3107	112	28	.	.	PUNCT
cana-3107	113	1	a	a	DET
cana-3107	113	2	fresh	fresh	ADJ
cana-3107	113	3	open	open	ADJ
cana-3107	113	4	field	field	NOUN
cana-3107	113	5	-	-	PUNCT
cana-3107	113	6	image	image	NOUN
cana-3107	113	7	dataset	dataset	NOUN
cana-3107	113	8	of	of	ADP
cana-3107	113	9	important	important	ADJ
cana-3107	113	10	(	(	PUNCT
cana-3107	113	11	principal	principal	NOUN
cana-3107	113	12	and	and	CCONJ
cana-3107	113	13	secondary	secondary	ADJ
cana-3107	113	14	)	)	PUNCT
cana-3107	113	15	insect	insect	NOUN
cana-3107	113	16	pests	pest	NOUN
cana-3107	113	17	of	of	ADP
cana-3107	113	18	maize	maize	NOUN
cana-3107	113	19	plantations	plantation	NOUN
cana-3107	113	20	,	,	PUNCT
cana-3107	113	21	together	together	ADV
cana-3107	113	22	with	with	ADP
cana-3107	113	23	a	a	DET
cana-3107	113	24	deep	deep	ADJ
cana-3107	113	25	learning	learning	NOUN
cana-3107	113	26	model	model	NOUN
cana-3107	113	27	(	(	PUNCT
cana-3107	113	28	a	a	DET
cana-3107	113	29	modified	modified	ADJ
cana-3107	113	30	inceptionv3	inceptionv3	NOUN
cana-3107	113	31	*	*	NOUN
cana-3107	113	32	)	)	PUNCT
cana-3107	113	33	for	for	ADP
cana-3107	113	34	identification	identification	NOUN
cana-3107	113	35	of	of	ADP
cana-3107	113	36	communications	communication	NOUN
cana-3107	113	37	on	on	ADP
cana-3107	113	38	applied	apply	VERB
cana-3107	113	39	nonlinear	nonlinear	ADJ
cana-3107	113	40	analysis	analysis	NOUN
cana-3107	113	41	issn	issn	NOUN
cana-3107	113	42	:	:	PUNCT
cana-3107	113	43	1074	1074	NUM
cana-3107	113	44	-	-	PUNCT
cana-3107	113	45	133x	133x	NUM
cana-3107	113	46	vol	vol	NOUN
cana-3107	113	47	32	32	NUM
cana-3107	113	48	no	no	NOUN
cana-3107	113	49	.	.	PUNCT
cana-3107	114	1	5s	5s	NUM
cana-3107	114	2	(	(	PUNCT
cana-3107	114	3	2025	2025	NUM
cana-3107	114	4	)	)	PUNCT
cana-3107	114	5	365	365	NUM
cana-3107	114	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	114	7	those	those	DET
cana-3107	114	8	insects	insect	NOUN
cana-3107	114	9	,	,	PUNCT
cana-3107	114	10	were	be	AUX
cana-3107	114	11	presented	present	VERB
cana-3107	114	12	by	by	ADP
cana-3107	114	13	witenberg	witenberg	PROPN
cana-3107	114	14	s.	s.	PROPN
cana-3107	114	15	r.	r.	PROPN
cana-3107	114	16	souza	souza	PROPN
cana-3107	114	17	et	et	PROPN
cana-3107	114	18	al	al	PROPN
cana-3107	114	19	.	.	PUNCT
cana-3107	115	1	[	[	X
cana-3107	115	2	18	18	NUM
cana-3107	115	3	]	]	PUNCT
cana-3107	115	4	.	.	PUNCT
cana-3107	116	1	the	the	DET
cana-3107	116	2	collection	collection	NOUN
cana-3107	116	3	contains	contain	VERB
cana-3107	116	4	4320	4320	NUM
cana-3107	116	5	pictures	picture	NOUN
cana-3107	116	6	of	of	ADP
cana-3107	116	7	6	6	NUM
cana-3107	116	8	maize	maize	NOUN
cana-3107	116	9	-	-	PUNCT
cana-3107	116	10	related	relate	VERB
cana-3107	116	11	insect	insect	NOUN
cana-3107	116	12	pests	pest	NOUN
cana-3107	116	13	.	.	PUNCT
cana-3107	117	1	the	the	DET
cana-3107	117	2	suggested	suggest	VERB
cana-3107	117	3	model	model	NOUN
cana-3107	117	4	(	(	PUNCT
cana-3107	117	5	inception	inception	PROPN
cana-3107	117	6	-	-	PUNCT
cana-3107	117	7	v3	v3	NOUN
cana-3107	117	8	*	*	PUNCT
cana-3107	117	9	)	)	PUNCT
cana-3107	117	10	outperformed	outperform	VERB
cana-3107	117	11	both	both	CCONJ
cana-3107	117	12	the	the	DET
cana-3107	117	13	baseline	baseline	NOUN
cana-3107	117	14	(	(	PUNCT
cana-3107	117	15	regular	regular	ADJ
cana-3107	117	16	)	)	PUNCT
cana-3107	117	17	inception	inception	PROPN
cana-3107	117	18	-	-	PUNCT
cana-3107	117	19	v3	v3	PROPN
cana-3107	117	20	(	(	PUNCT
cana-3107	117	21	94.8	94.8	NUM
cana-3107	117	22	%	%	NOUN
cana-3107	117	23	)	)	PUNCT
cana-3107	117	24	and	and	CCONJ
cana-3107	117	25	the	the	DET
cana-3107	117	26	state	state	NOUN
cana-3107	117	27	-	-	PUNCT
cana-3107	117	28	of	of	ADP
cana-3107	117	29	-	-	PUNCT
cana-3107	117	30	the	the	DET
cana-3107	117	31	-	-	PUNCT
cana-3107	117	32	art	art	NOUN
cana-3107	117	33	(	(	PUNCT
cana-3107	117	34	96.3	96.3	NUM
cana-3107	117	35	%	%	NOUN
cana-3107	117	36	)	)	PUNCT
cana-3107	117	37	alexnet	alexnet	NOUN
cana-3107	117	38	in	in	ADP
cana-3107	117	39	terms	term	NOUN
cana-3107	117	40	of	of	ADP
cana-3107	117	41	average	average	ADJ
cana-3107	117	42	(	(	PUNCT
cana-3107	117	43	cross	cross	ADJ
cana-3107	117	44	-	-	ADJ
cana-3107	117	45	validated	validated	ADJ
cana-3107	117	46	)	)	PUNCT
cana-3107	117	47	accuracy	accuracy	NOUN
cana-3107	117	48	.	.	PUNCT
cana-3107	118	1	our	our	PRON
cana-3107	118	2	long	long	ADJ
cana-3107	118	3	-	-	PUNCT
cana-3107	118	4	term	term	NOUN
cana-3107	118	5	goal	goal	NOUN
cana-3107	118	6	is	be	AUX
cana-3107	118	7	to	to	PART
cana-3107	118	8	expand	expand	VERB
cana-3107	118	9	our	our	PRON
cana-3107	118	10	work	work	NOUN
cana-3107	118	11	with	with	ADP
cana-3107	118	12	this	this	DET
cana-3107	118	13	updated	update	VERB
cana-3107	118	14	version	version	NOUN
cana-3107	118	15	of	of	ADP
cana-3107	118	16	inception	inception	PROPN
cana-3107	118	17	-	-	PUNCT
cana-3107	118	18	v3	v3	NOUN
cana-3107	118	19	*	*	PUNCT
cana-3107	118	20	to	to	PART
cana-3107	118	21	include	include	VERB
cana-3107	118	22	other	other	ADJ
cana-3107	118	23	insect	insect	NOUN
cana-3107	118	24	classes	class	NOUN
cana-3107	118	25	and	and	CCONJ
cana-3107	118	26	crop	crop	NOUN
cana-3107	118	27	types	type	NOUN
cana-3107	118	28	,	,	PUNCT
cana-3107	118	29	despite	despite	SCONJ
cana-3107	118	30	its	its	PRON
cana-3107	118	31	similar	similar	ADJ
cana-3107	118	32	accuracy	accuracy	NOUN
cana-3107	118	33	to	to	ADP
cana-3107	118	34	the	the	DET
cana-3107	118	35	original	original	ADJ
cana-3107	118	36	model	model	NOUN
cana-3107	118	37	during	during	ADP
cana-3107	118	38	training	training	NOUN
cana-3107	118	39	.	.	PUNCT
cana-3107	119	1	to	to	PART
cana-3107	119	2	reduce	reduce	VERB
cana-3107	119	3	the	the	DET
cana-3107	119	4	use	use	NOUN
cana-3107	119	5	of	of	ADP
cana-3107	119	6	chemical	chemical	ADJ
cana-3107	119	7	pesticides	pesticide	NOUN
cana-3107	119	8	and	and	CCONJ
cana-3107	119	9	to	to	PART
cana-3107	119	10	promote	promote	VERB
cana-3107	119	11	more	more	ADV
cana-3107	119	12	sustainable	sustainable	ADJ
cana-3107	119	13	agricultural	agricultural	ADJ
cana-3107	119	14	ecosystems	ecosystem	NOUN
cana-3107	119	15	,	,	PUNCT
cana-3107	119	16	accurate	accurate	ADJ
cana-3107	119	17	identification	identification	NOUN
cana-3107	119	18	of	of	ADP
cana-3107	119	19	insect	insect	NOUN
cana-3107	119	20	pests	pest	NOUN
cana-3107	119	21	in	in	ADP
cana-3107	119	22	field	field	NOUN
cana-3107	119	23	pictures	picture	NOUN
cana-3107	119	24	is	be	AUX
cana-3107	119	25	a	a	DET
cana-3107	119	26	pressing	press	VERB
cana-3107	119	27	need	need	NOUN
cana-3107	119	28	.	.	PUNCT
cana-3107	120	1	using	use	VERB
cana-3107	120	2	enhanced	enhanced	ADJ
cana-3107	120	3	vgg19	vgg19	PROPN
cana-3107	120	4	,	,	PUNCT
cana-3107	120	5	denan	denan	NOUN
cana-3107	120	6	xia	xia	PROPN
cana-3107	120	7	et	et	PROPN
cana-3107	120	8	al	al	PROPN
cana-3107	120	9	.	.	PUNCT
cana-3107	121	1	[	[	X
cana-3107	121	2	19	19	NUM
cana-3107	121	3	]	]	PUNCT
cana-3107	121	4	introduced	introduce	VERB
cana-3107	121	5	a	a	DET
cana-3107	121	6	target	target	NOUN
cana-3107	121	7	identification	identification	NOUN
cana-3107	121	8	approach	approach	NOUN
cana-3107	121	9	for	for	ADP
cana-3107	121	10	fast	fast	ADJ
cana-3107	121	11	and	and	CCONJ
cana-3107	121	12	accurate	accurate	ADJ
cana-3107	121	13	insect	insect	NOUN
cana-3107	121	14	detection	detection	NOUN
cana-3107	121	15	in	in	ADP
cana-3107	121	16	pictures	picture	NOUN
cana-3107	121	17	.	.	PUNCT
cana-3107	122	1	the	the	DET
cana-3107	122	2	authors	author	NOUN
cana-3107	122	3	of	of	ADP
cana-3107	122	4	the	the	DET
cana-3107	122	5	present	present	ADJ
cana-3107	122	6	study	study	NOUN
cana-3107	122	7	used	use	VERB
cana-3107	122	8	the	the	DET
cana-3107	122	9	pre	pre	ADJ
cana-3107	122	10	-	-	ADJ
cana-3107	122	11	trained	train	VERB
cana-3107	122	12	vgg19	vgg19	NOUN
cana-3107	122	13	model	model	NOUN
cana-3107	122	14	from	from	ADP
cana-3107	122	15	the	the	DET
cana-3107	122	16	caffe	caffe	NOUN
cana-3107	122	17	library	library	NOUN
cana-3107	122	18	to	to	PART
cana-3107	122	19	train	train	VERB
cana-3107	122	20	the	the	DET
cana-3107	122	21	optimum	optimum	ADJ
cana-3107	122	22	model	model	NOUN
cana-3107	122	23	for	for	ADP
cana-3107	122	24	this	this	DET
cana-3107	122	25	research	research	NOUN
cana-3107	122	26	since	since	SCONJ
cana-3107	122	27	its	its	PRON
cana-3107	122	28	design	design	NOUN
cana-3107	122	29	strikes	strike	VERB
cana-3107	122	30	a	a	DET
cana-3107	122	31	good	good	ADJ
cana-3107	122	32	compromise	compromise	NOUN
cana-3107	122	33	between	between	ADP
cana-3107	122	34	feature	feature	NOUN
cana-3107	122	35	extraction	extraction	NOUN
cana-3107	122	36	and	and	CCONJ
cana-3107	122	37	model	model	NOUN
cana-3107	122	38	training	training	NOUN
cana-3107	122	39	.	.	PUNCT
cana-3107	123	1	the	the	DET
cana-3107	123	2	testing	testing	NOUN
cana-3107	123	3	results	result	VERB
cana-3107	123	4	on	on	ADP
cana-3107	123	5	the	the	DET
cana-3107	123	6	current	current	ADJ
cana-3107	123	7	dataset	dataset	NOUN
cana-3107	123	8	"	"	PUNCT
cana-3107	123	9	mpest	mpest	PROPN
cana-3107	123	10	"	"	PUNCT
cana-3107	123	11	demonstrated	demonstrate	VERB
cana-3107	123	12	the	the	DET
cana-3107	123	13	superior	superior	ADJ
cana-3107	123	14	speed	speed	NOUN
cana-3107	123	15	and	and	CCONJ
cana-3107	123	16	accuracy	accuracy	NOUN
cana-3107	123	17	of	of	ADP
cana-3107	123	18	this	this	DET
cana-3107	123	19	approach	approach	NOUN
cana-3107	123	20	compared	compare	VERB
cana-3107	123	21	to	to	ADP
cana-3107	123	22	the	the	DET
cana-3107	123	23	state	state	NOUN
cana-3107	123	24	-	-	PUNCT
cana-3107	123	25	of	of	ADP
cana-3107	123	26	-	-	PUNCT
cana-3107	123	27	the	the	DET
cana-3107	123	28	-	-	PUNCT
cana-3107	123	29	art	art	NOUN
cana-3107	123	30	.	.	PUNCT
cana-3107	124	1	butterfly	butterfly	NOUN
cana-3107	124	2	dataset	dataset	NOUN
cana-3107	124	3	selection	selection	NOUN
cana-3107	124	4	,	,	PUNCT
cana-3107	124	5	butterfly	butterfly	NOUN
cana-3107	124	6	data	datum	NOUN
cana-3107	124	7	set	set	NOUN
cana-3107	124	8	processing	processing	NOUN
cana-3107	124	9	,	,	PUNCT
cana-3107	124	10	butterfly	butterfly	NOUN
cana-3107	124	11	identification	identification	NOUN
cana-3107	124	12	and	and	CCONJ
cana-3107	124	13	classification	classification	NOUN
cana-3107	124	14	using	use	VERB
cana-3107	124	15	faster	fast	ADJ
cana-3107	124	16	r	r	NOUN
cana-3107	124	17	-	-	PUNCT
cana-3107	124	18	cnn	cnn	PROPN
cana-3107	124	19	,	,	PUNCT
cana-3107	124	20	and	and	CCONJ
cana-3107	124	21	a	a	DET
cana-3107	124	22	final	final	ADJ
cana-3107	124	23	average	average	ADJ
cana-3107	124	24	classification	classification	NOUN
cana-3107	124	25	accuracy	accuracy	NOUN
cana-3107	124	26	of	of	ADP
cana-3107	124	27	70.4	70.4	NUM
cana-3107	124	28	%	%	NOUN
cana-3107	124	29	are	be	AUX
cana-3107	124	30	all	all	ADV
cana-3107	124	31	addressed	address	VERB
cana-3107	124	32	in	in	ADP
cana-3107	124	33	a	a	DET
cana-3107	124	34	paper	paper	NOUN
cana-3107	124	35	by	by	ADP
cana-3107	124	36	ruoyan	ruoyan	PROPN
cana-3107	124	37	zhao	zhao	PROPN
cana-3107	124	38	et	et	PROPN
cana-3107	124	39	al	al	PROPN
cana-3107	124	40	.	.	PUNCT
cana-3107	125	1	[	[	X
cana-3107	125	2	20	20	NUM
cana-3107	125	3	]	]	PUNCT
cana-3107	125	4	.	.	PUNCT
cana-3107	126	1	justify	justify	VERB
cana-3107	126	2	your	your	PRON
cana-3107	126	3	findings	finding	NOUN
cana-3107	126	4	by	by	ADP
cana-3107	126	5	summarizing	summarize	VERB
cana-3107	126	6	the	the	DET
cana-3107	126	7	whole	whole	ADJ
cana-3107	126	8	experiment	experiment	NOUN
cana-3107	126	9	.	.	PUNCT
cana-3107	127	1	the	the	DET
cana-3107	127	2	first	first	ADJ
cana-3107	127	3	step	step	NOUN
cana-3107	127	4	is	be	AUX
cana-3107	127	5	to	to	PART
cana-3107	127	6	guarantee	guarantee	VERB
cana-3107	127	7	an	an	DET
cana-3107	127	8	adequate	adequate	ADJ
cana-3107	127	9	sample	sample	NOUN
cana-3107	127	10	size	size	NOUN
cana-3107	127	11	is	be	AUX
cana-3107	127	12	used	use	VERB
cana-3107	127	13	during	during	ADP
cana-3107	127	14	training	training	NOUN
cana-3107	127	15	.	.	PUNCT
cana-3107	128	1	to	to	PART
cana-3107	128	2	guarantee	guarantee	VERB
cana-3107	128	3	efficient	efficient	ADJ
cana-3107	128	4	training	training	NOUN
cana-3107	128	5	,	,	PUNCT
cana-3107	128	6	they	they	PRON
cana-3107	128	7	may	may	AUX
cana-3107	128	8	flip	flip	VERB
cana-3107	128	9	the	the	DET
cana-3107	128	10	dataset	dataset	NOUN
cana-3107	128	11	upside	upside	ADV
cana-3107	128	12	down	down	ADV
cana-3107	128	13	,	,	PUNCT
cana-3107	128	14	rotate	rotate	VERB
cana-3107	128	15	it	it	PRON
cana-3107	128	16	90	90	NUM
cana-3107	128	17	degrees	degree	NOUN
cana-3107	128	18	to	to	ADP
cana-3107	128	19	the	the	DET
cana-3107	128	20	left	left	NOUN
cana-3107	128	21	or	or	CCONJ
cana-3107	128	22	right	right	ADJ
cana-3107	128	23	,	,	PUNCT
cana-3107	128	24	provide	provide	VERB
cana-3107	128	25	a	a	DET
cana-3107	128	26	cooling	cool	VERB
cana-3107	128	27	effect	effect	NOUN
cana-3107	128	28	,	,	PUNCT
cana-3107	128	29	inject	inject	VERB
cana-3107	128	30	some	some	DET
cana-3107	128	31	noise	noise	NOUN
cana-3107	128	32	,	,	PUNCT
cana-3107	128	33	and	and	CCONJ
cana-3107	128	34	so	so	ADV
cana-3107	128	35	on	on	ADV
cana-3107	128	36	;	;	PUNCT
cana-3107	128	37	secondly	secondly	ADV
cana-3107	128	38	,	,	PUNCT
cana-3107	128	39	they	they	PRON
cana-3107	128	40	need	need	AUX
cana-3107	128	41	guarantee	guarantee	VERB
cana-3107	128	42	the	the	DET
cana-3107	128	43	unpredictability	unpredictability	NOUN
cana-3107	128	44	of	of	ADP
cana-3107	128	45	samples	sample	NOUN
cana-3107	128	46	while	while	SCONJ
cana-3107	128	47	assessing	assess	VERB
cana-3107	128	48	the	the	DET
cana-3107	128	49	accuracy	accuracy	NOUN
cana-3107	128	50	.	.	PUNCT
cana-3107	129	1	it	it	PRON
cana-3107	129	2	need	need	VERB
cana-3107	129	3	frequent	frequent	ADJ
cana-3107	129	4	parameter	parameter	NOUN
cana-3107	129	5	tuning	tuning	NOUN
cana-3107	129	6	and	and	CCONJ
cana-3107	129	7	replacement	replacement	NOUN
cana-3107	129	8	in	in	ADP
cana-3107	129	9	order	order	NOUN
cana-3107	129	10	to	to	PART
cana-3107	129	11	maintain	maintain	VERB
cana-3107	129	12	high	high	ADJ
cana-3107	129	13	accuracy	accuracy	NOUN
cana-3107	129	14	in	in	ADP
cana-3107	129	15	classification	classification	NOUN
cana-3107	129	16	and	and	CCONJ
cana-3107	129	17	identification	identification	NOUN
cana-3107	129	18	.	.	PUNCT
cana-3107	130	1	the	the	DET
cana-3107	130	2	study	study	NOUN
cana-3107	130	3	of	of	ADP
cana-3107	130	4	butterfly	butterfly	NOUN
cana-3107	130	5	identification	identification	NOUN
cana-3107	130	6	is	be	AUX
cana-3107	130	7	vital	vital	ADJ
cana-3107	130	8	not	not	PART
cana-3107	130	9	only	only	ADV
cana-3107	130	10	to	to	ADP
cana-3107	130	11	the	the	DET
cana-3107	130	12	development	development	NOUN
cana-3107	130	13	of	of	ADP
cana-3107	130	14	image	image	NOUN
cana-3107	130	15	recognition	recognition	NOUN
cana-3107	130	16	technology	technology	NOUN
cana-3107	130	17	but	but	CCONJ
cana-3107	130	18	also	also	ADV
cana-3107	130	19	to	to	ADP
cana-3107	130	20	the	the	DET
cana-3107	130	21	preservation	preservation	NOUN
cana-3107	130	22	of	of	ADP
cana-3107	130	23	butterfly	butterfly	NOUN
cana-3107	130	24	horticulture	horticulture	NOUN
cana-3107	130	25	.	.	PUNCT
cana-3107	131	1	summary	summary	NOUN
cana-3107	131	2	:	:	PUNCT
cana-3107	131	3	taxonomists	taxonomist	NOUN
cana-3107	131	4	often	often	ADV
cana-3107	131	5	need	need	VERB
cana-3107	131	6	to	to	PART
cana-3107	131	7	identify	identify	VERB
cana-3107	131	8	a	a	DET
cana-3107	131	9	specimen	speciman	NOUN
cana-3107	131	10	to	to	ADP
cana-3107	131	11	the	the	DET
cana-3107	131	12	order	order	NOUN
cana-3107	131	13	or	or	CCONJ
cana-3107	131	14	family	family	NOUN
cana-3107	131	15	level	level	NOUN
cana-3107	131	16	before	before	SCONJ
cana-3107	131	17	they	they	PRON
cana-3107	131	18	can	can	AUX
cana-3107	131	19	assign	assign	VERB
cana-3107	131	20	it	it	PRON
cana-3107	131	21	a	a	DET
cana-3107	131	22	species	species	NOUN
cana-3107	131	23	designation	designation	NOUN
cana-3107	131	24	,	,	PUNCT
cana-3107	131	25	and	and	CCONJ
cana-3107	131	26	identification	identification	NOUN
cana-3107	131	27	to	to	ADP
cana-3107	131	28	the	the	DET
cana-3107	131	29	order	order	NOUN
cana-3107	131	30	level	level	NOUN
cana-3107	131	31	is	be	AUX
cana-3107	131	32	more	more	ADV
cana-3107	131	33	useful	useful	ADJ
cana-3107	131	34	to	to	ADP
cana-3107	131	35	the	the	DET
cana-3107	131	36	general	general	ADJ
cana-3107	131	37	public	public	ADJ
cana-3107	131	38	and	and	CCONJ
cana-3107	131	39	younger	young	ADJ
cana-3107	131	40	taxonomists	taxonomist	NOUN
cana-3107	131	41	.	.	PUNCT
cana-3107	132	1	therefore	therefore	ADV
cana-3107	132	2	,	,	PUNCT
cana-3107	132	3	identifying	identify	VERB
cana-3107	132	4	an	an	DET
cana-3107	132	5	insect	insect	NOUN
cana-3107	132	6	at	at	ADP
cana-3107	132	7	the	the	DET
cana-3107	132	8	order	order	NOUN
cana-3107	132	9	level	level	NOUN
cana-3107	132	10	is	be	AUX
cana-3107	132	11	a	a	DET
cana-3107	132	12	crucial	crucial	ADJ
cana-3107	132	13	part	part	NOUN
cana-3107	132	14	of	of	ADP
cana-3107	132	15	the	the	DET
cana-3107	132	16	bigger	big	ADJ
cana-3107	132	17	picture	picture	NOUN
cana-3107	132	18	of	of	ADP
cana-3107	132	19	naming	name	VERB
cana-3107	132	20	insects	insect	NOUN
cana-3107	132	21	.	.	PUNCT
cana-3107	133	1	we	we	PRON
cana-3107	133	2	can	can	AUX
cana-3107	133	3	employ	employ	VERB
cana-3107	133	4	uavs	uavs	NOUN
cana-3107	133	5	with	with	ADP
cana-3107	133	6	higher	high	ADJ
cana-3107	133	7	-	-	PUNCT
cana-3107	133	8	resolution	resolution	NOUN
cana-3107	133	9	cameras	camera	NOUN
cana-3107	133	10	to	to	PART
cana-3107	133	11	measure	measure	VERB
cana-3107	133	12	how	how	SCONJ
cana-3107	133	13	well	well	ADV
cana-3107	133	14	a	a	DET
cana-3107	133	15	method	method	NOUN
cana-3107	133	16	works	work	VERB
cana-3107	133	17	with	with	ADP
cana-3107	133	18	data	datum	NOUN
cana-3107	133	19	from	from	ADP
cana-3107	133	20	a	a	DET
cana-3107	133	21	variety	variety	NOUN
cana-3107	133	22	of	of	ADP
cana-3107	133	23	altitudes	altitude	NOUN
cana-3107	133	24	.	.	PUNCT
cana-3107	134	1	insects	insect	NOUN
cana-3107	134	2	in	in	ADP
cana-3107	134	3	uav	uav	PROPN
cana-3107	134	4	-	-	PUNCT
cana-3107	134	5	captured	capture	VERB
cana-3107	134	6	photos	photo	NOUN
cana-3107	134	7	may	may	AUX
cana-3107	134	8	be	be	AUX
cana-3107	134	9	automatically	automatically	ADV
cana-3107	134	10	counted	count	VERB
cana-3107	134	11	,	,	PUNCT
cana-3107	134	12	allowing	allow	VERB
cana-3107	134	13	us	we	PRON
cana-3107	134	14	to	to	PART
cana-3107	134	15	gauge	gauge	VERB
cana-3107	134	16	the	the	DET
cana-3107	134	17	efficacy	efficacy	NOUN
cana-3107	134	18	of	of	ADP
cana-3107	134	19	current	current	ADJ
cana-3107	134	20	pest	pest	NOUN
cana-3107	134	21	control	control	NOUN
cana-3107	134	22	measures	measure	NOUN
cana-3107	134	23	.	.	PUNCT
cana-3107	135	1	we	we	PRON
cana-3107	135	2	need	need	VERB
cana-3107	135	3	to	to	PART
cana-3107	135	4	think	think	VERB
cana-3107	135	5	more	more	ADJ
cana-3107	135	6	about	about	ADP
cana-3107	135	7	the	the	DET
cana-3107	135	8	parameter	parameter	NOUN
cana-3107	135	9	redundancy	redundancy	NOUN
cana-3107	135	10	issue	issue	NOUN
cana-3107	135	11	in	in	ADP
cana-3107	135	12	the	the	DET
cana-3107	135	13	network	network	NOUN
cana-3107	135	14	and	and	CCONJ
cana-3107	135	15	how	how	SCONJ
cana-3107	135	16	to	to	PART
cana-3107	135	17	extract	extract	VERB
cana-3107	135	18	the	the	DET
cana-3107	135	19	crucial	crucial	ADJ
cana-3107	135	20	information	information	NOUN
cana-3107	135	21	in	in	ADP
cana-3107	135	22	the	the	DET
cana-3107	135	23	feature	feature	NOUN
cana-3107	135	24	map	map	NOUN
cana-3107	135	25	if	if	SCONJ
cana-3107	135	26	we	we	PRON
cana-3107	135	27	want	want	VERB
cana-3107	135	28	to	to	PART
cana-3107	135	29	boost	boost	VERB
cana-3107	135	30	a	a	DET
cana-3107	135	31	model	model	NOUN
cana-3107	135	32	's	's	PART
cana-3107	135	33	recognition	recognition	NOUN
cana-3107	135	34	rate	rate	NOUN
cana-3107	135	35	.	.	PUNCT
cana-3107	136	1	automatic	automatic	ADJ
cana-3107	136	2	feature	feature	NOUN
cana-3107	136	3	extraction	extraction	NOUN
cana-3107	136	4	is	be	AUX
cana-3107	136	5	a	a	DET
cana-3107	136	6	major	major	ADJ
cana-3107	136	7	benefit	benefit	NOUN
cana-3107	136	8	of	of	ADP
cana-3107	136	9	deep	deep	ADJ
cana-3107	136	10	learning	learning	NOUN
cana-3107	136	11	's	's	PART
cana-3107	136	12	recent	recent	ADJ
cana-3107	136	13	development	development	NOUN
cana-3107	136	14	,	,	PUNCT
cana-3107	136	15	giving	give	VERB
cana-3107	136	16	it	it	PRON
cana-3107	136	17	an	an	DET
cana-3107	136	18	edge	edge	NOUN
cana-3107	136	19	over	over	ADP
cana-3107	136	20	artificial	artificial	ADJ
cana-3107	136	21	extraction	extraction	NOUN
cana-3107	136	22	.	.	PUNCT
cana-3107	137	1	3	3	X
cana-3107	137	2	.	.	NUM
cana-3107	137	3	proposed	propose	VERB
cana-3107	137	4	method	method	NOUN
cana-3107	137	5	recently	recently	ADV
cana-3107	137	6	,	,	PUNCT
cana-3107	137	7	autonomous	autonomous	ADJ
cana-3107	137	8	feature	feature	NOUN
cana-3107	137	9	selection	selection	NOUN
cana-3107	137	10	has	have	AUX
cana-3107	137	11	allowed	allow	VERB
cana-3107	137	12	deep	deep	ADJ
cana-3107	137	13	learning	learning	NOUN
cana-3107	137	14	algorithms	algorithm	NOUN
cana-3107	137	15	to	to	PART
cana-3107	137	16	make	make	VERB
cana-3107	137	17	significant	significant	ADJ
cana-3107	137	18	advancements	advancement	NOUN
cana-3107	137	19	in	in	ADP
cana-3107	137	20	picture	picture	NOUN
cana-3107	137	21	identification	identification	NOUN
cana-3107	137	22	.	.	PUNCT
cana-3107	138	1	manually	manually	ADV
cana-3107	138	2	designed	design	VERB
cana-3107	138	3	features	feature	NOUN
cana-3107	138	4	are	be	AUX
cana-3107	138	5	utilized	utilize	VERB
cana-3107	138	6	in	in	ADP
cana-3107	138	7	conventional	conventional	ADJ
cana-3107	138	8	communications	communication	NOUN
cana-3107	138	9	on	on	ADP
cana-3107	138	10	applied	apply	VERB
cana-3107	138	11	nonlinear	nonlinear	ADJ
cana-3107	138	12	analysis	analysis	NOUN
cana-3107	138	13	issn	issn	NOUN
cana-3107	138	14	:	:	PUNCT
cana-3107	138	15	1074	1074	NUM
cana-3107	138	16	-	-	PUNCT
cana-3107	138	17	133x	133x	NUM
cana-3107	138	18	vol	vol	NOUN
cana-3107	138	19	32	32	NUM
cana-3107	138	20	no	no	NOUN
cana-3107	138	21	.	.	PUNCT
cana-3107	139	1	5s	5s	NUM
cana-3107	139	2	(	(	PUNCT
cana-3107	139	3	2025	2025	NUM
cana-3107	139	4	)	)	PUNCT
cana-3107	139	5	366	366	NUM
cana-3107	139	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	139	7	image	image	NOUN
cana-3107	139	8	recognition	recognition	NOUN
cana-3107	139	9	algorithms	algorithm	NOUN
cana-3107	139	10	.	.	PUNCT
cana-3107	140	1	these	these	PRON
cana-3107	140	2	include	include	VERB
cana-3107	140	3	features	feature	NOUN
cana-3107	140	4	from	from	ADP
cana-3107	140	5	the	the	DET
cana-3107	140	6	scale	scale	NOUN
cana-3107	140	7	-	-	PUNCT
cana-3107	140	8	invariant	invariant	ADJ
cana-3107	140	9	feature	feature	NOUN
cana-3107	140	10	transform	transform	NOUN
cana-3107	140	11	and	and	CCONJ
cana-3107	140	12	accelerated	accelerate	VERB
cana-3107	140	13	robust	robust	ADJ
cana-3107	140	14	features	feature	NOUN
cana-3107	140	15	.	.	PUNCT
cana-3107	141	1	once	once	SCONJ
cana-3107	141	2	features	feature	NOUN
cana-3107	141	3	have	have	AUX
cana-3107	141	4	been	be	AUX
cana-3107	141	5	collected	collect	VERB
cana-3107	141	6	,	,	PUNCT
cana-3107	141	7	they	they	PRON
cana-3107	141	8	are	be	AUX
cana-3107	141	9	fed	feed	VERB
cana-3107	141	10	into	into	ADP
cana-3107	141	11	machine	machine	NOUN
cana-3107	141	12	learning	learn	VERB
cana-3107	141	13	algorithms	algorithm	NOUN
cana-3107	141	14	to	to	PART
cana-3107	141	15	carry	carry	VERB
cana-3107	141	16	out	out	ADP
cana-3107	141	17	picture	picture	NOUN
cana-3107	141	18	identification	identification	NOUN
cana-3107	141	19	.	.	PUNCT
cana-3107	142	1	the	the	DET
cana-3107	142	2	performance	performance	NOUN
cana-3107	142	3	of	of	ADP
cana-3107	142	4	the	the	DET
cana-3107	142	5	standard	standard	ADJ
cana-3107	142	6	method	method	NOUN
cana-3107	142	7	for	for	ADP
cana-3107	142	8	picture	picture	NOUN
cana-3107	142	9	recognition	recognition	NOUN
cana-3107	142	10	relies	rely	VERB
cana-3107	142	11	greatly	greatly	ADV
cana-3107	142	12	on	on	ADP
cana-3107	142	13	the	the	DET
cana-3107	142	14	integrity	integrity	NOUN
cana-3107	142	15	of	of	ADP
cana-3107	142	16	the	the	DET
cana-3107	142	17	features	feature	NOUN
cana-3107	142	18	that	that	PRON
cana-3107	142	19	are	be	AUX
cana-3107	142	20	extracted	extract	VERB
cana-3107	142	21	.	.	PUNCT
cana-3107	143	1	feature	feature	NOUN
cana-3107	143	2	extraction	extraction	NOUN
cana-3107	143	3	,	,	PUNCT
cana-3107	143	4	however	however	ADV
cana-3107	143	5	,	,	PUNCT
cana-3107	143	6	is	be	AUX
cana-3107	143	7	difficult	difficult	ADJ
cana-3107	143	8	and	and	CCONJ
cana-3107	143	9	time	time	NOUN
cana-3107	143	10	-	-	PUNCT
cana-3107	143	11	consuming	consume	VERB
cana-3107	143	12	.	.	PUNCT
cana-3107	144	1	redesigning	redesign	VERB
cana-3107	144	2	the	the	DET
cana-3107	144	3	features	feature	NOUN
cana-3107	144	4	is	be	AUX
cana-3107	144	5	often	often	ADV
cana-3107	144	6	required	require	VERB
cana-3107	144	7	when	when	SCONJ
cana-3107	144	8	applying	apply	VERB
cana-3107	144	9	them	they	PRON
cana-3107	144	10	to	to	ADP
cana-3107	144	11	various	various	ADJ
cana-3107	144	12	issues	issue	NOUN
cana-3107	144	13	or	or	CCONJ
cana-3107	144	14	uses	use	NOUN
cana-3107	144	15	.	.	PUNCT
cana-3107	145	1	we	we	PRON
cana-3107	145	2	use	use	VERB
cana-3107	145	3	the	the	DET
cana-3107	145	4	term	term	NOUN
cana-3107	145	5	"	"	PUNCT
cana-3107	145	6	feature	feature	NOUN
cana-3107	145	7	engineering	engineering	NOUN
cana-3107	145	8	"	"	PUNCT
cana-3107	145	9	to	to	PART
cana-3107	145	10	describe	describe	VERB
cana-3107	145	11	this	this	DET
cana-3107	145	12	process	process	NOUN
cana-3107	145	13	.	.	PUNCT
cana-3107	146	1	expertise	expertise	NOUN
cana-3107	146	2	and	and	CCONJ
cana-3107	146	3	a	a	DET
cana-3107	146	4	large	large	ADJ
cana-3107	146	5	number	number	NOUN
cana-3107	146	6	of	of	ADP
cana-3107	146	7	algorithms	algorithm	NOUN
cana-3107	146	8	are	be	AUX
cana-3107	146	9	needed	need	VERB
cana-3107	146	10	for	for	ADP
cana-3107	146	11	feature	feature	NOUN
cana-3107	146	12	engineering	engineering	NOUN
cana-3107	146	13	,	,	PUNCT
cana-3107	146	14	which	which	PRON
cana-3107	146	15	in	in	ADP
cana-3107	146	16	this	this	DET
cana-3107	146	17	instance	instance	NOUN
cana-3107	146	18	is	be	AUX
cana-3107	146	19	recognizing	recognize	VERB
cana-3107	146	20	pests	pest	NOUN
cana-3107	146	21	and	and	CCONJ
cana-3107	146	22	illnesses	illness	NOUN
cana-3107	146	23	.	.	PUNCT
cana-3107	147	1	for	for	ADP
cana-3107	147	2	different	different	ADJ
cana-3107	147	3	pests	pest	NOUN
cana-3107	147	4	or	or	CCONJ
cana-3107	147	5	crop	crop	NOUN
cana-3107	147	6	photos	photo	NOUN
cana-3107	147	7	,	,	PUNCT
cana-3107	147	8	conventional	conventional	ADJ
cana-3107	147	9	machine	machine	NOUN
cana-3107	147	10	learning	learning	NOUN
cana-3107	147	11	methods	method	NOUN
cana-3107	147	12	and	and	CCONJ
cana-3107	147	13	image	image	NOUN
cana-3107	147	14	characteristics	characteristic	NOUN
cana-3107	147	15	must	must	AUX
cana-3107	147	16	be	be	AUX
cana-3107	147	17	rethought	rethink	VERB
cana-3107	147	18	and	and	CCONJ
cana-3107	147	19	reselected	reselecte	VERB
cana-3107	147	20	,	,	PUNCT
cana-3107	147	21	respectively	respectively	ADV
cana-3107	147	22	.	.	PUNCT
cana-3107	148	1	the	the	DET
cana-3107	148	2	advent	advent	NOUN
cana-3107	148	3	of	of	ADP
cana-3107	148	4	deep	deep	ADJ
cana-3107	148	5	learning	learning	NOUN
cana-3107	148	6	in	in	ADP
cana-3107	148	7	recent	recent	ADJ
cana-3107	148	8	years	year	NOUN
cana-3107	148	9	has	have	AUX
cana-3107	148	10	made	make	VERB
cana-3107	148	11	it	it	PRON
cana-3107	148	12	possible	possible	ADJ
cana-3107	148	13	to	to	PART
cana-3107	148	14	employ	employ	VERB
cana-3107	148	15	cnn	cnn	PROPN
cana-3107	148	16	for	for	ADP
cana-3107	148	17	automated	automate	VERB
cana-3107	148	18	feature	feature	NOUN
cana-3107	148	19	extraction	extraction	NOUN
cana-3107	148	20	without	without	ADP
cana-3107	148	21	the	the	DET
cana-3107	148	22	need	need	NOUN
cana-3107	148	23	for	for	ADP
cana-3107	148	24	hand	hand	NOUN
cana-3107	148	25	-	-	PUNCT
cana-3107	148	26	crafted	craft	VERB
cana-3107	148	27	features	feature	NOUN
cana-3107	148	28	.	.	PUNCT
cana-3107	149	1	insect	insect	NOUN
cana-3107	149	2	images	image	NOUN
cana-3107	149	3	were	be	AUX
cana-3107	149	4	formerly	formerly	ADV
cana-3107	149	5	analyzed	analyze	VERB
cana-3107	149	6	only	only	ADV
cana-3107	149	7	by	by	ADP
cana-3107	149	8	human	human	ADJ
cana-3107	149	9	brains	brain	NOUN
cana-3107	149	10	,	,	PUNCT
cana-3107	149	11	but	but	CCONJ
cana-3107	149	12	now	now	ADV
cana-3107	149	13	that	that	SCONJ
cana-3107	149	14	computing	compute	VERB
cana-3107	149	15	power	power	NOUN
cana-3107	149	16	has	have	AUX
cana-3107	149	17	advanced	advance	VERB
cana-3107	149	18	,	,	PUNCT
cana-3107	149	19	computers	computer	NOUN
cana-3107	149	20	can	can	AUX
cana-3107	149	21	do	do	VERB
cana-3107	149	22	the	the	DET
cana-3107	149	23	job	job	NOUN
cana-3107	149	24	just	just	ADV
cana-3107	149	25	as	as	ADV
cana-3107	149	26	well	well	ADV
cana-3107	149	27	,	,	PUNCT
cana-3107	149	28	if	if	SCONJ
cana-3107	149	29	not	not	PART
cana-3107	149	30	better	well	ADJ
cana-3107	149	31	.	.	PUNCT
cana-3107	150	1	mathematical	mathematical	ADJ
cana-3107	150	2	morphology	morphology	NOUN
cana-3107	150	3	-	-	PUNCT
cana-3107	150	4	based	base	VERB
cana-3107	150	5	and	and	CCONJ
cana-3107	150	6	threshold	threshold	NOUN
cana-3107	150	7	-	-	PUNCT
cana-3107	150	8	based	base	VERB
cana-3107	150	9	segmentation	segmentation	NOUN
cana-3107	150	10	approaches	approach	NOUN
cana-3107	150	11	remain	remain	VERB
cana-3107	150	12	the	the	DET
cana-3107	150	13	gold	gold	ADJ
cana-3107	150	14	standard	standard	NOUN
cana-3107	150	15	for	for	ADP
cana-3107	150	16	insect	insect	NOUN
cana-3107	150	17	image	image	NOUN
cana-3107	150	18	segmentation	segmentation	NOUN
cana-3107	150	19	at	at	ADP
cana-3107	150	20	the	the	DET
cana-3107	150	21	current	current	ADJ
cana-3107	150	22	time	time	NOUN
cana-3107	150	23	[	[	X
cana-3107	150	24	1	1	NUM
cana-3107	150	25	]	]	PUNCT
cana-3107	150	26	.	.	PUNCT
cana-3107	151	1	the	the	DET
cana-3107	151	2	primary	primary	ADJ
cana-3107	151	3	process	process	NOUN
cana-3107	151	4	in	in	ADP
cana-3107	151	5	target	target	NOUN
cana-3107	151	6	identification	identification	NOUN
cana-3107	151	7	is	be	AUX
cana-3107	151	8	the	the	DET
cana-3107	151	9	accumulation	accumulation	NOUN
cana-3107	151	10	and	and	CCONJ
cana-3107	151	11	analysis	analysis	NOUN
cana-3107	151	12	of	of	ADP
cana-3107	151	13	data	datum	NOUN
cana-3107	151	14	.	.	PUNCT
cana-3107	152	1	faster	fast	ADJ
cana-3107	152	2	-	-	PUNCT
cana-3107	152	3	rcnn	rcnn	NOUN
cana-3107	152	4	target	target	NOUN
cana-3107	152	5	detection	detection	NOUN
cana-3107	152	6	model	model	NOUN
cana-3107	152	7	identification	identification	NOUN
cana-3107	152	8	outcomes	outcome	NOUN
cana-3107	152	9	are	be	AUX
cana-3107	152	10	somewhat	somewhat	ADV
cana-3107	152	11	dependent	dependent	ADJ
cana-3107	152	12	on	on	ADP
cana-3107	152	13	the	the	DET
cana-3107	152	14	quality	quality	NOUN
cana-3107	152	15	and	and	CCONJ
cana-3107	152	16	size	size	NOUN
cana-3107	152	17	of	of	ADP
cana-3107	152	18	the	the	DET
cana-3107	152	19	data	datum	NOUN
cana-3107	152	20	set	set	VERB
cana-3107	152	21	used	use	VERB
cana-3107	152	22	to	to	PART
cana-3107	152	23	train	train	VERB
cana-3107	152	24	the	the	DET
cana-3107	152	25	model	model	NOUN
cana-3107	152	26	.	.	PUNCT
cana-3107	153	1	therefore	therefore	ADV
cana-3107	153	2	,	,	PUNCT
cana-3107	153	3	it	it	PRON
cana-3107	153	4	is	be	AUX
cana-3107	153	5	important	important	ADJ
cana-3107	153	6	to	to	PART
cana-3107	153	7	amass	amass	VERB
cana-3107	153	8	a	a	DET
cana-3107	153	9	big	big	ADJ
cana-3107	153	10	number	number	NOUN
cana-3107	153	11	of	of	ADP
cana-3107	153	12	digital	digital	ADJ
cana-3107	153	13	photographs	photograph	NOUN
cana-3107	153	14	of	of	ADP
cana-3107	153	15	insects	insect	NOUN
cana-3107	153	16	from	from	ADP
cana-3107	153	17	their	their	PRON
cana-3107	153	18	natural	natural	ADJ
cana-3107	153	19	habitats	habitat	NOUN
cana-3107	153	20	.	.	PUNCT
cana-3107	154	1	for	for	ADP
cana-3107	154	2	each	each	DET
cana-3107	154	3	insect	insect	NOUN
cana-3107	154	4	species	specie	NOUN
cana-3107	154	5	,	,	PUNCT
cana-3107	154	6	researchers	researcher	NOUN
cana-3107	154	7	require	require	VERB
cana-3107	154	8	a	a	DET
cana-3107	154	9	large	large	ADJ
cana-3107	154	10	sample	sample	NOUN
cana-3107	154	11	size	size	NOUN
cana-3107	154	12	from	from	ADP
cana-3107	154	13	which	which	PRON
cana-3107	154	14	to	to	PART
cana-3107	154	15	draw	draw	VERB
cana-3107	154	16	conclusions	conclusion	NOUN
cana-3107	154	17	.	.	PUNCT
cana-3107	155	1	the	the	DET
cana-3107	155	2	input	input	NOUN
cana-3107	155	3	size	size	NOUN
cana-3107	155	4	of	of	ADP
cana-3107	155	5	a	a	DET
cana-3107	155	6	picture	picture	NOUN
cana-3107	155	7	including	include	VERB
cana-3107	155	8	insects	insect	NOUN
cana-3107	155	9	is	be	AUX
cana-3107	155	10	irrelevant	irrelevant	ADJ
cana-3107	155	11	to	to	ADP
cana-3107	155	12	the	the	DET
cana-3107	155	13	faster	fast	ADJ
cana-3107	155	14	-	-	PUNCT
cana-3107	155	15	rcnn	rcnn	NOUN
cana-3107	155	16	model	model	NOUN
cana-3107	155	17	.	.	PUNCT
cana-3107	156	1	figure	figure	NOUN
cana-3107	156	2	1	1	NUM
cana-3107	156	3	shows	show	VERB
cana-3107	156	4	the	the	DET
cana-3107	156	5	results	result	NOUN
cana-3107	156	6	of	of	ADP
cana-3107	156	7	our	our	PRON
cana-3107	156	8	fasterrcnn	fasterrcnn	NOUN
cana-3107	156	9	and	and	CCONJ
cana-3107	156	10	adam	adam	PROPN
cana-3107	156	11	optimizer	optimizer	NOUN
cana-3107	156	12	-	-	PUNCT
cana-3107	156	13	based	base	VERB
cana-3107	156	14	picture	picture	NOUN
cana-3107	156	15	segmentation	segmentation	NOUN
cana-3107	156	16	for	for	ADP
cana-3107	156	17	insect	insect	NOUN
cana-3107	156	18	identification	identification	NOUN
cana-3107	156	19	.	.	PUNCT
cana-3107	157	1	figure1	figure1	PROPN
cana-3107	157	2	.	.	PUNCT
cana-3107	158	1	proposed	propose	VERB
cana-3107	158	2	model	model	PROPN
cana-3107	158	3	block	block	PROPN
cana-3107	158	4	diagram	diagram	PROPN
cana-3107	158	5	dataset	dataset	VERB
cana-3107	158	6	thanks	thank	NOUN
cana-3107	158	7	to	to	ADP
cana-3107	158	8	"	"	PUNCT
cana-3107	158	9	feng	feng	PROPN
cana-3107	158	10	wu	wu	PROPN
cana-3107	158	11	and	and	CCONJ
cana-3107	158	12	yueying	yueying	PROPN
cana-3107	158	13	li	li	PROPN
cana-3107	158	14	"	"	PUNCT
cana-3107	158	15	for	for	ADP
cana-3107	158	16	their	their	PRON
cana-3107	158	17	dataset	dataset	NOUN
cana-3107	158	18	,	,	PUNCT
cana-3107	158	19	which	which	PRON
cana-3107	158	20	consists	consist	VERB
cana-3107	158	21	mostly	mostly	ADV
cana-3107	158	22	of	of	ADP
cana-3107	158	23	chilo	chilo	NOUN
cana-3107	158	24	suppressalis	suppressali	NOUN
cana-3107	158	25	,	,	PUNCT
cana-3107	158	26	cicadellidae	cicadellidae	ADJ
cana-3107	158	27	,	,	PUNCT
cana-3107	158	28	and	and	CCONJ
cana-3107	158	29	coleoptera	coleoptera	NOUN
cana-3107	158	30	,	,	PUNCT
cana-3107	158	31	and	and	CCONJ
cana-3107	158	32	which	which	PRON
cana-3107	158	33	was	be	AUX
cana-3107	158	34	used	use	VERB
cana-3107	158	35	to	to	PART
cana-3107	158	36	inform	inform	VERB
cana-3107	158	37	the	the	DET
cana-3107	158	38	proposed	propose	VERB
cana-3107	158	39	study	study	NOUN
cana-3107	158	40	.	.	PUNCT
cana-3107	159	1	we	we	PRON
cana-3107	159	2	also	also	ADV
cana-3107	159	3	included	include	VERB
cana-3107	159	4	information	information	NOUN
cana-3107	159	5	from	from	ADP
cana-3107	159	6	a	a	DET
cana-3107	159	7	kaggle	kaggle	ADJ
cana-3107	159	8	dataset	dataset	NOUN
cana-3107	159	9	called	call	VERB
cana-3107	159	10	"	"	PUNCT
cana-3107	159	11	dangerous	dangerous	ADJ
cana-3107	159	12	farm	farm	NOUN
cana-3107	159	13	insect	insect	NOUN
cana-3107	159	14	dataset	dataset	NOUN
cana-3107	159	15	"	"	PUNCT
cana-3107	159	16	that	that	PRON
cana-3107	159	17	includes	include	VERB
cana-3107	159	18	the	the	DET
cana-3107	159	19	africanized	africanized	ADJ
cana-3107	159	20	honey	honey	NOUN
cana-3107	159	21	bees	bee	NOUN
cana-3107	159	22	(	(	PUNCT
cana-3107	159	23	killer	killer	NOUN
cana-3107	159	24	bees	bee	NOUN
cana-3107	159	25	)	)	PUNCT
cana-3107	159	26	,	,	PUNCT
cana-3107	159	27	armyworms	armyworm	NOUN
cana-3107	159	28	,	,	PUNCT
cana-3107	159	29	brown	brown	ADJ
cana-3107	159	30	marmorated	marmorated	NOUN
cana-3107	159	31	stink	stink	VERB
cana-3107	159	32	bugs	bug	NOUN
cana-3107	159	33	,	,	PUNCT
cana-3107	159	34	and	and	CCONJ
cana-3107	159	35	colorado	colorado	NOUN
cana-3107	159	36	potato	potato	NOUN
cana-3107	159	37	beetles	beetle	NOUN
cana-3107	159	38	that	that	PRON
cana-3107	159	39	we	we	PRON
cana-3107	159	40	caught	catch	VERB
cana-3107	159	41	and	and	CCONJ
cana-3107	159	42	released	release	VERB
cana-3107	159	43	.	.	PUNCT
cana-3107	160	1	we	we	PRON
cana-3107	160	2	only	only	ADV
cana-3107	160	3	utilized	utilize	VERB
cana-3107	160	4	187	187	NUM
cana-3107	160	5	images	image	NOUN
cana-3107	160	6	total	total	NOUN
cana-3107	160	7	,	,	PUNCT
cana-3107	160	8	however	however	ADV
cana-3107	160	9	the	the	DET
cana-3107	160	10	communications	communication	NOUN
cana-3107	160	11	on	on	ADP
cana-3107	160	12	applied	apply	VERB
cana-3107	160	13	nonlinear	nonlinear	ADJ
cana-3107	160	14	analysis	analysis	NOUN
cana-3107	160	15	issn	issn	NOUN
cana-3107	160	16	:	:	PUNCT
cana-3107	160	17	1074	1074	NUM
cana-3107	160	18	-	-	PUNCT
cana-3107	160	19	133x	133x	NUM
cana-3107	160	20	vol	vol	NOUN
cana-3107	160	21	32	32	NUM
cana-3107	160	22	no	no	NOUN
cana-3107	160	23	.	.	PUNCT
cana-3107	161	1	5s	5s	NUM
cana-3107	161	2	(	(	PUNCT
cana-3107	161	3	2025	2025	NUM
cana-3107	161	4	)	)	PUNCT
cana-3107	161	5	367	367	NUM
cana-3107	162	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	162	2	dataset	dataset	NOUN
cana-3107	162	3	had	have	VERB
cana-3107	162	4	more	more	ADJ
cana-3107	162	5	than	than	ADP
cana-3107	162	6	90	90	NUM
cana-3107	162	7	images	image	NOUN
cana-3107	162	8	for	for	ADP
cana-3107	162	9	each	each	DET
cana-3107	162	10	category	category	NOUN
cana-3107	162	11	.	.	PUNCT
cana-3107	163	1	the	the	DET
cana-3107	163	2	information	information	NOUN
cana-3107	163	3	has	have	AUX
cana-3107	163	4	been	be	AUX
cana-3107	163	5	divided	divide	VERB
cana-3107	163	6	into	into	ADP
cana-3107	163	7	a	a	DET
cana-3107	163	8	70	70	NUM
cana-3107	163	9	%	%	NOUN
cana-3107	163	10	training	training	NOUN
cana-3107	163	11	data	datum	NOUN
cana-3107	163	12	and	and	CCONJ
cana-3107	163	13	30	30	NUM
cana-3107	163	14	%	%	NOUN
cana-3107	163	15	test	test	NOUN
cana-3107	163	16	data	datum	NOUN
cana-3107	163	17	set	set	VERB
cana-3107	163	18	.	.	PUNCT
cana-3107	164	1	data	datum	NOUN
cana-3107	164	2	preprocessing	preprocesse	VERB
cana-3107	164	3	data	datum	NOUN
cana-3107	164	4	collected	collect	VERB
cana-3107	164	5	in	in	ADP
cana-3107	164	6	part	part	NOUN
cana-3107	164	7	is	be	AUX
cana-3107	164	8	labeled	label	VERB
cana-3107	164	9	one	one	NUM
cana-3107	164	10	,	,	PUNCT
cana-3107	164	11	and	and	CCONJ
cana-3107	164	12	the	the	DET
cana-3107	164	13	remaining	remain	VERB
cana-3107	164	14	data	datum	NOUN
cana-3107	164	15	must	must	AUX
cana-3107	164	16	be	be	AUX
cana-3107	164	17	labeled	label	VERB
cana-3107	164	18	using	use	VERB
cana-3107	164	19	the	the	DET
cana-3107	164	20	matlab	matlab	PROPN
cana-3107	164	21	toolbox	toolbox	NOUN
cana-3107	164	22	for	for	ADP
cana-3107	164	23	images	image	NOUN
cana-3107	164	24	.	.	PUNCT
cana-3107	165	1	in	in	ADP
cana-3107	165	2	this	this	DET
cana-3107	165	3	stage	stage	NOUN
cana-3107	165	4	,	,	PUNCT
cana-3107	165	5	data	datum	NOUN
cana-3107	165	6	is	be	AUX
cana-3107	165	7	preprocessed	preprocesse	VERB
cana-3107	165	8	by	by	ADP
cana-3107	165	9	picking	pick	VERB
cana-3107	165	10	appropriate	appropriate	ADJ
cana-3107	165	11	photos	photo	NOUN
cana-3107	165	12	for	for	ADP
cana-3107	165	13	training	training	NOUN
cana-3107	165	14	and	and	CCONJ
cana-3107	165	15	testing	testing	NOUN
cana-3107	165	16	and	and	CCONJ
cana-3107	165	17	resizing	resize	VERB
cana-3107	165	18	them	they	PRON
cana-3107	165	19	to	to	ADP
cana-3107	165	20	a	a	DET
cana-3107	165	21	uniform	uniform	ADJ
cana-3107	165	22	200x200	200x200	NUM
cana-3107	165	23	.	.	PUNCT
cana-3107	165	24	providing	provide	VERB
cana-3107	165	25	data	datum	NOUN
cana-3107	165	26	variations	variation	NOUN
cana-3107	165	27	and	and	CCONJ
cana-3107	165	28	making	make	VERB
cana-3107	165	29	sure	sure	ADJ
cana-3107	165	30	each	each	DET
cana-3107	165	31	class	class	NOUN
cana-3107	165	32	has	have	VERB
cana-3107	165	33	an	an	DET
cana-3107	165	34	equal	equal	ADJ
cana-3107	165	35	number	number	NOUN
cana-3107	165	36	of	of	ADP
cana-3107	165	37	examples	example	NOUN
cana-3107	165	38	is	be	AUX
cana-3107	165	39	essential	essential	ADJ
cana-3107	165	40	for	for	ADP
cana-3107	165	41	training	train	VERB
cana-3107	165	42	a	a	DET
cana-3107	165	43	deep	deep	ADJ
cana-3107	165	44	learning	learning	NOUN
cana-3107	165	45	model	model	NOUN
cana-3107	165	46	that	that	PRON
cana-3107	165	47	can	can	AUX
cana-3107	165	48	generalize	generalize	VERB
cana-3107	165	49	.	.	PUNCT
cana-3107	166	1	train	train	NOUN
cana-3107	166	2	and	and	CCONJ
cana-3107	166	3	test	test	NOUN
cana-3107	166	4	split	split	NOUN
cana-3107	166	5	:	:	PUNCT
cana-3107	166	6	train	train	NOUN
cana-3107	166	7	and	and	CCONJ
cana-3107	166	8	test	test	NOUN
cana-3107	166	9	sets	set	NOUN
cana-3107	166	10	are	be	AUX
cana-3107	166	11	created	create	VERB
cana-3107	166	12	from	from	ADP
cana-3107	166	13	the	the	DET
cana-3107	166	14	collected	collect	VERB
cana-3107	166	15	data	datum	NOUN
cana-3107	166	16	[	[	X
cana-3107	166	17	13	13	NUM
cana-3107	166	18	]	]	PUNCT
cana-3107	166	19	.	.	PUNCT
cana-3107	167	1	it	it	PRON
cana-3107	167	2	is	be	AUX
cana-3107	167	3	important	important	ADJ
cana-3107	167	4	to	to	PART
cana-3107	167	5	keep	keep	VERB
cana-3107	167	6	the	the	DET
cana-3107	167	7	training	training	NOUN
cana-3107	167	8	set	set	VERB
cana-3107	167	9	the	the	DET
cana-3107	167	10	same	same	ADJ
cana-3107	167	11	so	so	SCONJ
cana-3107	167	12	as	as	SCONJ
cana-3107	167	13	to	to	PART
cana-3107	167	14	not	not	PART
cana-3107	167	15	favor	favor	VERB
cana-3107	167	16	one	one	NUM
cana-3107	167	17	bug	bug	NOUN
cana-3107	167	18	over	over	ADP
cana-3107	167	19	another	another	PRON
cana-3107	167	20	in	in	ADP
cana-3107	167	21	the	the	DET
cana-3107	167	22	final	final	ADJ
cana-3107	167	23	product	product	NOUN
cana-3107	167	24	.	.	PUNCT
cana-3107	168	1	split	split	VERB
cana-3107	168	2	ratio	ratio	NOUN
cana-3107	168	3	training	training	NOUN
cana-3107	168	4	:	:	PUNCT
cana-3107	168	5	test	test	NOUN
cana-3107	168	6	:	:	PUNCT
cana-3107	168	7	70	70	NUM
cana-3107	168	8	:	:	SYM
cana-3107	168	9	30	30	NUM
cana-3107	168	10	.	.	PUNCT
cana-3107	169	1	inceptionv3	inceptionv3	NOUN
cana-3107	169	2	feature	feature	NOUN
cana-3107	169	3	extraction	extraction	NOUN
cana-3107	169	4	feature	feature	NOUN
cana-3107	169	5	extraction	extraction	NOUN
cana-3107	169	6	is	be	AUX
cana-3107	169	7	crucial	crucial	ADJ
cana-3107	169	8	to	to	ADP
cana-3107	169	9	the	the	DET
cana-3107	169	10	final	final	ADJ
cana-3107	169	11	identification	identification	NOUN
cana-3107	169	12	outcome	outcome	NOUN
cana-3107	169	13	.	.	PUNCT
cana-3107	170	1	features	feature	NOUN
cana-3107	170	2	extracted	extract	VERB
cana-3107	170	3	from	from	ADP
cana-3107	170	4	photos	photo	NOUN
cana-3107	170	5	should	should	AUX
cana-3107	170	6	be	be	AUX
cana-3107	170	7	meaningful	meaningful	ADJ
cana-3107	170	8	in	in	ADP
cana-3107	170	9	terms	term	NOUN
cana-3107	170	10	of	of	ADP
cana-3107	170	11	taxonomy	taxonomy	NOUN
cana-3107	170	12	and	and	CCONJ
cana-3107	170	13	should	should	AUX
cana-3107	170	14	be	be	AUX
cana-3107	170	15	easily	easily	ADV
cana-3107	170	16	attainable	attainable	ADJ
cana-3107	170	17	.	.	PUNCT
cana-3107	171	1	the	the	DET
cana-3107	171	2	inception	inception	NOUN
cana-3107	171	3	challenges	challenge	VERB
cana-3107	171	4	the	the	DET
cana-3107	171	5	conventional	conventional	ADJ
cana-3107	171	6	wisdom	wisdom	NOUN
cana-3107	171	7	of	of	ADP
cana-3107	171	8	convolutional	convolutional	ADJ
cana-3107	171	9	neural	neural	ADJ
cana-3107	171	10	networks	network	NOUN
cana-3107	171	11	,	,	PUNCT
cana-3107	171	12	which	which	PRON
cana-3107	171	13	held	hold	VERB
cana-3107	171	14	that	that	SCONJ
cana-3107	171	15	adding	add	VERB
cana-3107	171	16	more	more	ADV
cana-3107	171	17	convolutional	convolutional	ADJ
cana-3107	171	18	layers	layer	NOUN
cana-3107	171	19	to	to	ADP
cana-3107	171	20	the	the	DET
cana-3107	171	21	network	network	NOUN
cana-3107	171	22	's	's	PART
cana-3107	171	23	depth	depth	NOUN
cana-3107	171	24	would	would	AUX
cana-3107	171	25	lead	lead	VERB
cana-3107	171	26	to	to	ADP
cana-3107	171	27	better	well	ADJ
cana-3107	171	28	results	result	NOUN
cana-3107	171	29	.	.	PUNCT
cana-3107	172	1	learning	learn	VERB
cana-3107	172	2	to	to	PART
cana-3107	172	3	approximate	approximate	VERB
cana-3107	172	4	the	the	DET
cana-3107	172	5	best	good	ADJ
cana-3107	172	6	local	local	ADJ
cana-3107	172	7	sparse	sparse	ADJ
cana-3107	172	8	nodes	node	NOUN
cana-3107	172	9	with	with	ADP
cana-3107	172	10	dense	dense	ADJ
cana-3107	172	11	components	component	NOUN
cana-3107	172	12	is	be	AUX
cana-3107	172	13	key	key	ADJ
cana-3107	172	14	to	to	ADP
cana-3107	172	15	the	the	DET
cana-3107	172	16	inception	inception	ADJ
cana-3107	172	17	architecture	architecture	NOUN
cana-3107	172	18	.	.	PUNCT
cana-3107	173	1	when	when	SCONJ
cana-3107	173	2	compared	compare	VERB
cana-3107	173	3	to	to	ADP
cana-3107	173	4	other	other	ADJ
cana-3107	173	5	convolutional	convolutional	ADJ
cana-3107	173	6	neural	neural	ADJ
cana-3107	173	7	networks	network	NOUN
cana-3107	173	8	,	,	PUNCT
cana-3107	173	9	inception	inception	NOUN
cana-3107	173	10	stands	stand	VERB
cana-3107	173	11	out	out	ADP
cana-3107	173	12	due	due	ADP
cana-3107	173	13	to	to	ADP
cana-3107	173	14	the	the	DET
cana-3107	173	15	fact	fact	NOUN
cana-3107	173	16	that	that	SCONJ
cana-3107	173	17	the	the	DET
cana-3107	173	18	network	network	NOUN
cana-3107	173	19	designer	designer	NOUN
cana-3107	173	20	is	be	AUX
cana-3107	173	21	not	not	PART
cana-3107	173	22	responsible	responsible	ADJ
cana-3107	173	23	for	for	ADP
cana-3107	173	24	choosing	choose	VERB
cana-3107	173	25	the	the	DET
cana-3107	173	26	convolutional	convolutional	ADJ
cana-3107	173	27	layer	layer	NOUN
cana-3107	173	28	's	's	PART
cana-3107	173	29	filter	filter	NOUN
cana-3107	173	30	type	type	NOUN
cana-3107	173	31	,	,	PUNCT
cana-3107	173	32	as	as	ADV
cana-3107	173	33	well	well	ADV
cana-3107	173	34	as	as	ADP
cana-3107	173	35	the	the	DET
cana-3107	173	36	layer	layer	NOUN
cana-3107	173	37	's	's	PART
cana-3107	173	38	placement	placement	NOUN
cana-3107	173	39	and	and	CCONJ
cana-3107	173	40	formation	formation	NOUN
cana-3107	173	41	.	.	PUNCT
cana-3107	174	1	the	the	DET
cana-3107	174	2	network	network	NOUN
cana-3107	174	3	model	model	NOUN
cana-3107	174	4	can	can	AUX
cana-3107	174	5	decide	decide	VERB
cana-3107	174	6	whether	whether	SCONJ
cana-3107	174	7	the	the	DET
cana-3107	174	8	convolutional	convolutional	ADJ
cana-3107	174	9	layer	layer	NOUN
cana-3107	174	10	is	be	AUX
cana-3107	174	11	necessary	necessary	ADJ
cana-3107	174	12	,	,	PUNCT
cana-3107	174	13	which	which	PRON
cana-3107	174	14	filters	filter	VERB
cana-3107	174	15	to	to	PART
cana-3107	174	16	apply	apply	VERB
cana-3107	174	17	,	,	PUNCT
cana-3107	174	18	and	and	CCONJ
cana-3107	174	19	what	what	DET
cana-3107	174	20	values	value	NOUN
cana-3107	174	21	to	to	PART
cana-3107	174	22	add	add	VERB
cana-3107	174	23	.	.	PUNCT
cana-3107	175	1	join	join	VERB
cana-3107	175	2	all	all	DET
cana-3107	175	3	the	the	DET
cana-3107	175	4	results	result	NOUN
cana-3107	175	5	together	together	ADV
cana-3107	175	6	,	,	PUNCT
cana-3107	175	7	and	and	CCONJ
cana-3107	175	8	the	the	DET
cana-3107	175	9	network	network	NOUN
cana-3107	175	10	will	will	AUX
cana-3107	175	11	figure	figure	VERB
cana-3107	175	12	out	out	ADP
cana-3107	175	13	how	how	SCONJ
cana-3107	175	14	to	to	PART
cana-3107	175	15	combine	combine	VERB
cana-3107	175	16	model	model	NOUN
cana-3107	175	17	filters	filter	NOUN
cana-3107	175	18	and	and	CCONJ
cana-3107	175	19	what	what	PRON
cana-3107	175	20	learning	learn	VERB
cana-3107	175	21	parameters	parameter	NOUN
cana-3107	175	22	to	to	PART
cana-3107	175	23	use	use	VERB
cana-3107	175	24	.	.	PUNCT
cana-3107	176	1	the	the	DET
cana-3107	176	2	inceptionv3	inceptionv3	NOUN
cana-3107	176	3	network	network	NOUN
cana-3107	176	4	model	model	NOUN
cana-3107	176	5	has	have	VERB
cana-3107	176	6	three	three	NUM
cana-3107	176	7	distinct	distinct	ADJ
cana-3107	176	8	inception	inception	NOUN
cana-3107	176	9	modules	module	NOUN
cana-3107	176	10	,	,	PUNCT
cana-3107	176	11	each	each	PRON
cana-3107	176	12	of	of	ADP
cana-3107	176	13	which	which	PRON
cana-3107	176	14	utilizes	utilize	VERB
cana-3107	176	15	a	a	DET
cana-3107	176	16	unique	unique	ADJ
cana-3107	176	17	set	set	NOUN
cana-3107	176	18	of	of	ADP
cana-3107	176	19	convolution	convolution	NOUN
cana-3107	176	20	kernels	kernel	NOUN
cana-3107	176	21	and	and	CCONJ
cana-3107	176	22	receptive	receptive	ADJ
cana-3107	176	23	field	field	NOUN
cana-3107	176	24	sizes	size	NOUN
cana-3107	176	25	to	to	PART
cana-3107	176	26	extract	extract	VERB
cana-3107	176	27	picture	picture	NOUN
cana-3107	176	28	characteristics	characteristic	NOUN
cana-3107	176	29	at	at	ADP
cana-3107	176	30	various	various	ADJ
cana-3107	176	31	scales	scale	NOUN
cana-3107	176	32	,	,	PUNCT
cana-3107	176	33	before	before	ADP
cana-3107	176	34	combining	combine	VERB
cana-3107	176	35	all	all	PRON
cana-3107	176	36	of	of	ADP
cana-3107	176	37	the	the	DET
cana-3107	176	38	recovered	recover	VERB
cana-3107	176	39	features	feature	NOUN
cana-3107	176	40	into	into	ADP
cana-3107	176	41	a	a	DET
cana-3107	176	42	single	single	ADJ
cana-3107	176	43	one	one	NUM
cana-3107	176	44	.	.	PUNCT
cana-3107	177	1	simultaneously	simultaneously	ADV
cana-3107	177	2	,	,	PUNCT
cana-3107	177	3	a	a	DET
cana-3107	177	4	1	1	NUM
cana-3107	177	5	x	x	SYM
cana-3107	177	6	1	1	NUM
cana-3107	177	7	convolution	convolution	NOUN
cana-3107	177	8	kernel	kernel	NOUN
cana-3107	177	9	is	be	AUX
cana-3107	177	10	implemented	implement	VERB
cana-3107	177	11	to	to	PART
cana-3107	177	12	accomplish	accomplish	VERB
cana-3107	177	13	the	the	DET
cana-3107	177	14	dimensionality	dimensionality	NOUN
cana-3107	177	15	reduction	reduction	NOUN
cana-3107	177	16	effect	effect	NOUN
cana-3107	177	17	.	.	PUNCT
cana-3107	178	1	by	by	ADP
cana-3107	178	2	applying	apply	VERB
cana-3107	178	3	1	1	NUM
cana-3107	178	4	x	x	SYM
cana-3107	178	5	1	1	NUM
cana-3107	178	6	convolutions	convolution	NOUN
cana-3107	178	7	to	to	ADP
cana-3107	178	8	the	the	DET
cana-3107	178	9	big	big	ADJ
cana-3107	178	10	input	input	NOUN
cana-3107	178	11	layer	layer	NOUN
cana-3107	178	12	,	,	PUNCT
cana-3107	178	13	we	we	PRON
cana-3107	178	14	may	may	AUX
cana-3107	178	15	create	create	VERB
cana-3107	178	16	a	a	DET
cana-3107	178	17	more	more	ADV
cana-3107	178	18	manageable	manageable	ADJ
cana-3107	178	19	bottleneck	bottleneck	NOUN
cana-3107	178	20	layer	layer	NOUN
cana-3107	178	21	.	.	PUNCT
cana-3107	179	1	without	without	ADP
cana-3107	179	2	compromising	compromise	VERB
cana-3107	179	3	on	on	ADP
cana-3107	179	4	network	network	NOUN
cana-3107	179	5	speed	speed	NOUN
cana-3107	179	6	,	,	PUNCT
cana-3107	179	7	it	it	PRON
cana-3107	179	8	may	may	AUX
cana-3107	179	9	drastically	drastically	ADV
cana-3107	179	10	cut	cut	VERB
cana-3107	179	11	down	down	ADP
cana-3107	179	12	on	on	ADP
cana-3107	179	13	the	the	DET
cana-3107	179	14	size	size	NOUN
cana-3107	179	15	of	of	ADP
cana-3107	179	16	the	the	DET
cana-3107	179	17	presentation	presentation	NOUN
cana-3107	179	18	layer	layer	NOUN
cana-3107	179	19	,	,	PUNCT
cana-3107	179	20	which	which	PRON
cana-3107	179	21	in	in	ADP
cana-3107	179	22	turn	turn	NOUN
cana-3107	179	23	reduces	reduce	VERB
cana-3107	179	24	computational	computational	ADJ
cana-3107	179	25	expenses	expense	NOUN
cana-3107	179	26	[	[	X
cana-3107	179	27	7	7	NUM
cana-3107	179	28	]	]	PUNCT
cana-3107	179	29	.	.	PUNCT
cana-3107	180	1	figure2	figure2	PROPN
cana-3107	180	2	.	.	PUNCT
cana-3107	181	1	inceptionv3	inceptionv3	NOUN
cana-3107	181	2	when	when	SCONJ
cana-3107	181	3	comparing	compare	VERB
cana-3107	181	4	the	the	DET
cana-3107	181	5	computational	computational	ADJ
cana-3107	181	6	efficiency	efficiency	NOUN
cana-3107	181	7	of	of	ADP
cana-3107	181	8	vggnet	vggnet	NOUN
cana-3107	181	9	and	and	CCONJ
cana-3107	181	10	other	other	ADJ
cana-3107	181	11	inception	inception	ADJ
cana-3107	181	12	networks	network	NOUN
cana-3107	181	13	,	,	PUNCT
cana-3107	181	14	it	it	PRON
cana-3107	181	15	has	have	AUX
cana-3107	181	16	been	be	AUX
cana-3107	181	17	shown	show	VERB
cana-3107	181	18	that	that	SCONJ
cana-3107	181	19	inception	inception	ADJ
cana-3107	181	20	networks	network	NOUN
cana-3107	181	21	like	like	ADP
cana-3107	181	22	googlenet	googlenet	NOUN
cana-3107	181	23	and	and	CCONJ
cana-3107	181	24	inception	inception	NOUN
cana-3107	181	25	v1	v1	NOUN
cana-3107	181	26	perform	perform	VERB
cana-3107	181	27	better	well	ADV
cana-3107	181	28	.	.	PUNCT
cana-3107	182	1	it	it	PRON
cana-3107	182	2	is	be	AUX
cana-3107	182	3	crucial	crucial	ADJ
cana-3107	182	4	that	that	SCONJ
cana-3107	182	5	communications	communication	NOUN
cana-3107	182	6	on	on	ADP
cana-3107	182	7	applied	apply	VERB
cana-3107	182	8	nonlinear	nonlinear	ADJ
cana-3107	182	9	analysis	analysis	NOUN
cana-3107	182	10	issn	issn	NOUN
cana-3107	182	11	:	:	PUNCT
cana-3107	182	12	1074	1074	NUM
cana-3107	182	13	-	-	PUNCT
cana-3107	182	14	133x	133x	NUM
cana-3107	182	15	vol	vol	NOUN
cana-3107	182	16	32	32	NUM
cana-3107	182	17	no	no	NOUN
cana-3107	182	18	.	.	PUNCT
cana-3107	183	1	5s	5s	NUM
cana-3107	183	2	(	(	PUNCT
cana-3107	183	3	2025	2025	NUM
cana-3107	183	4	)	)	PUNCT
cana-3107	183	5	368	368	NUM
cana-3107	183	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	183	7	computational	computational	ADJ
cana-3107	183	8	benefits	benefit	NOUN
cana-3107	183	9	of	of	ADP
cana-3107	183	10	an	an	DET
cana-3107	183	11	inception	inception	NOUN
cana-3107	183	12	network	network	NOUN
cana-3107	183	13	be	be	AUX
cana-3107	183	14	preserved	preserve	VERB
cana-3107	183	15	.	.	PUNCT
cana-3107	184	1	the	the	DET
cana-3107	184	2	vulnerability	vulnerability	NOUN
cana-3107	184	3	of	of	ADP
cana-3107	184	4	the	the	DET
cana-3107	184	5	resulting	result	VERB
cana-3107	184	6	network	network	NOUN
cana-3107	184	7	manifests	manifest	VERB
cana-3107	184	8	itself	itself	PRON
cana-3107	184	9	whenever	whenever	SCONJ
cana-3107	184	10	an	an	DET
cana-3107	184	11	inception	inception	NOUN
cana-3107	184	12	network	network	NOUN
cana-3107	184	13	is	be	AUX
cana-3107	184	14	repurposed	repurpose	VERB
cana-3107	184	15	for	for	ADP
cana-3107	184	16	a	a	DET
cana-3107	184	17	new	new	ADJ
cana-3107	184	18	application	application	NOUN
cana-3107	184	19	.	.	PUNCT
cana-3107	185	1	for	for	ADP
cana-3107	185	2	the	the	DET
cana-3107	185	3	purpose	purpose	NOUN
cana-3107	185	4	of	of	ADP
cana-3107	185	5	loosening	loosen	VERB
cana-3107	185	6	restrictions	restriction	NOUN
cana-3107	185	7	and	and	CCONJ
cana-3107	185	8	making	make	VERB
cana-3107	185	9	model	model	NOUN
cana-3107	185	10	adaption	adaption	NOUN
cana-3107	185	11	easier	easy	ADJ
cana-3107	185	12	,	,	PUNCT
cana-3107	185	13	many	many	ADJ
cana-3107	185	14	methods	method	NOUN
cana-3107	185	15	were	be	AUX
cana-3107	185	16	suggested	suggest	VERB
cana-3107	185	17	for	for	ADP
cana-3107	185	18	use	use	NOUN
cana-3107	185	19	in	in	ADP
cana-3107	185	20	the	the	DET
cana-3107	185	21	inception	inception	ADJ
cana-3107	185	22	v3	v3	PROPN
cana-3107	185	23	model	model	NOUN
cana-3107	185	24	's	's	PART
cana-3107	185	25	optimization	optimization	NOUN
cana-3107	185	26	of	of	ADP
cana-3107	185	27	the	the	DET
cana-3107	185	28	network	network	NOUN
cana-3107	185	29	[	[	X
cana-3107	185	30	10	10	NUM
cana-3107	185	31	]	]	PUNCT
cana-3107	185	32	.	.	PUNCT
cana-3107	186	1	widening	widen	VERB
cana-3107	186	2	the	the	DET
cana-3107	186	3	neural	neural	ADJ
cana-3107	186	4	network	network	NOUN
cana-3107	186	5	model	model	NOUN
cana-3107	186	6	(	(	PUNCT
cana-3107	186	7	several	several	ADJ
cana-3107	186	8	kernel	kernel	NOUN
cana-3107	186	9	sizes	size	NOUN
cana-3107	186	10	were	be	AUX
cana-3107	186	11	used	use	VERB
cana-3107	186	12	to	to	PART
cana-3107	186	13	extract	extract	VERB
cana-3107	186	14	the	the	DET
cana-3107	186	15	same	same	ADJ
cana-3107	186	16	feature	feature	NOUN
cana-3107	186	17	maps	map	NOUN
cana-3107	186	18	)	)	PUNCT
cana-3107	186	19	and	and	CCONJ
cana-3107	186	20	increasing	increase	VERB
cana-3107	186	21	its	its	PRON
cana-3107	186	22	depth	depth	NOUN
cana-3107	186	23	are	be	AUX
cana-3107	186	24	both	both	PRON
cana-3107	186	25	recommended	recommend	VERB
cana-3107	186	26	for	for	ADP
cana-3107	186	27	producing	produce	VERB
cana-3107	186	28	a	a	DET
cana-3107	186	29	high	high	ADJ
cana-3107	186	30	-	-	PUNCT
cana-3107	186	31	quality	quality	NOUN
cana-3107	186	32	model	model	NOUN
cana-3107	186	33	.	.	PUNCT
cana-3107	187	1	the	the	DET
cana-3107	187	2	model	model	NOUN
cana-3107	187	3	's	's	PART
cana-3107	187	4	convolutional	convolutional	ADJ
cana-3107	187	5	layers	layer	NOUN
cana-3107	187	6	were	be	AUX
cana-3107	187	7	expanded	expand	VERB
cana-3107	187	8	using	use	VERB
cana-3107	187	9	the	the	DET
cana-3107	187	10	inception	inception	ADJ
cana-3107	187	11	structure	structure	NOUN
cana-3107	187	12	.	.	PUNCT
cana-3107	188	1	the	the	DET
cana-3107	188	2	inception	inception	NOUN
cana-3107	188	3	structure	structure	NOUN
cana-3107	188	4	's	's	PART
cana-3107	188	5	primary	primary	ADJ
cana-3107	188	6	function	function	NOUN
cana-3107	188	7	was	be	AUX
cana-3107	188	8	to	to	PART
cana-3107	188	9	choose	choose	VERB
cana-3107	188	10	a	a	DET
cana-3107	188	11	suitable	suitable	ADJ
cana-3107	188	12	dense	dense	ADJ
cana-3107	188	13	component	component	NOUN
cana-3107	188	14	to	to	PART
cana-3107	188	15	substitute	substitute	VERB
cana-3107	188	16	for	for	ADP
cana-3107	188	17	the	the	DET
cana-3107	188	18	ideal	ideal	ADJ
cana-3107	188	19	local	local	ADJ
cana-3107	188	20	sparsity	sparsity	NOUN
cana-3107	188	21	structure	structure	NOUN
cana-3107	188	22	and	and	CCONJ
cana-3107	188	23	then	then	ADV
cana-3107	188	24	to	to	PART
cana-3107	188	25	replicate	replicate	VERB
cana-3107	188	26	this	this	DET
cana-3107	188	27	structure	structure	NOUN
cana-3107	188	28	in	in	ADP
cana-3107	188	29	other	other	ADJ
cana-3107	188	30	locations	location	NOUN
cana-3107	188	31	.	.	PUNCT
cana-3107	189	1	using	use	VERB
cana-3107	189	2	this	this	DET
cana-3107	189	3	method	method	NOUN
cana-3107	189	4	,	,	PUNCT
cana-3107	189	5	the	the	DET
cana-3107	189	6	units	unit	NOUN
cana-3107	189	7	with	with	ADP
cana-3107	189	8	the	the	DET
cana-3107	189	9	highest	high	ADJ
cana-3107	189	10	relative	relative	ADJ
cana-3107	189	11	correlation	correlation	NOUN
cana-3107	189	12	would	would	AUX
cana-3107	189	13	be	be	AUX
cana-3107	189	14	grouped	group	VERB
cana-3107	189	15	together	together	ADV
cana-3107	189	16	to	to	PART
cana-3107	189	17	create	create	VERB
cana-3107	189	18	a	a	DET
cana-3107	189	19	new	new	ADJ
cana-3107	189	20	layer	layer	NOUN
cana-3107	189	21	,	,	PUNCT
cana-3107	189	22	which	which	PRON
cana-3107	189	23	would	would	AUX
cana-3107	189	24	then	then	ADV
cana-3107	189	25	be	be	AUX
cana-3107	189	26	connected	connect	VERB
cana-3107	189	27	to	to	ADP
cana-3107	189	28	the	the	DET
cana-3107	189	29	one	one	NOUN
cana-3107	189	30	above	above	ADP
cana-3107	189	31	it	it	PRON
cana-3107	189	32	.	.	PUNCT
cana-3107	190	1	figure	figure	VERB
cana-3107	190	2	2	2	NUM
cana-3107	190	3	depicts	depict	VERB
cana-3107	190	4	the	the	DET
cana-3107	190	5	v3	v3	PROPN
cana-3107	190	6	structure	structure	NOUN
cana-3107	190	7	at	at	ADP
cana-3107	190	8	conception	conception	NOUN
cana-3107	190	9	.	.	PUNCT
cana-3107	191	1	the	the	DET
cana-3107	191	2	1	1	NUM
cana-3107	191	3	x	x	SYM
cana-3107	191	4	1	1	NUM
cana-3107	191	5	convolution	convolution	NOUN
cana-3107	191	6	kernels	kernel	NOUN
cana-3107	191	7	were	be	AUX
cana-3107	191	8	used	use	VERB
cana-3107	191	9	before	before	ADP
cana-3107	191	10	the	the	DET
cana-3107	191	11	3	3	NUM
cana-3107	191	12	x	x	SYM
cana-3107	191	13	3	3	NUM
cana-3107	191	14	and	and	CCONJ
cana-3107	191	15	5	5	NUM
cana-3107	191	16	x	x	SYM
cana-3107	191	17	5	5	NUM
cana-3107	191	18	convolution	convolution	NOUN
cana-3107	191	19	kernels	kernel	NOUN
cana-3107	191	20	[	[	X
cana-3107	191	21	14	14	NUM
cana-3107	191	22	]	]	PUNCT
cana-3107	191	23	because	because	SCONJ
cana-3107	191	24	they	they	PRON
cana-3107	191	25	required	require	VERB
cana-3107	191	26	fewer	few	ADJ
cana-3107	191	27	parameters	parameter	NOUN
cana-3107	191	28	and	and	CCONJ
cana-3107	191	29	ran	run	VERB
cana-3107	191	30	more	more	ADV
cana-3107	191	31	quickly	quickly	ADV
cana-3107	191	32	.	.	PUNCT
cana-3107	192	1	faster	fast	ADJ
cana-3107	192	2	rcnn	rcnn	NOUN
cana-3107	192	3	with	with	ADP
cana-3107	192	4	adam	adam	PROPN
cana-3107	192	5	optimizer	optimizer	NOUN
cana-3107	192	6	for	for	ADP
cana-3107	192	7	segmentation	segmentation	NOUN
cana-3107	192	8	insect	insect	NOUN
cana-3107	192	9	detection	detection	NOUN
cana-3107	192	10	requires	require	VERB
cana-3107	192	11	pinpointing	pinpoint	VERB
cana-3107	192	12	the	the	DET
cana-3107	192	13	exact	exact	ADJ
cana-3107	192	14	position	position	NOUN
cana-3107	192	15	of	of	ADP
cana-3107	192	16	insects	insect	NOUN
cana-3107	192	17	inside	inside	ADP
cana-3107	192	18	an	an	DET
cana-3107	192	19	image	image	NOUN
cana-3107	192	20	and	and	CCONJ
cana-3107	192	21	labeling	label	VERB
cana-3107	192	22	them	they	PRON
cana-3107	192	23	according	accord	VERB
cana-3107	192	24	to	to	ADP
cana-3107	192	25	kind	kind	NOUN
cana-3107	192	26	.	.	PUNCT
cana-3107	193	1	the	the	DET
cana-3107	193	2	r	r	NOUN
cana-3107	193	3	-	-	PUNCT
cana-3107	193	4	cnn	cnn	PROPN
cana-3107	193	5	detection	detection	NOUN
cana-3107	193	6	algorithm	algorithm	NOUN
cana-3107	193	7	takes	take	VERB
cana-3107	193	8	a	a	DET
cana-3107	193	9	more	more	ADV
cana-3107	193	10	conventional	conventional	ADJ
cana-3107	193	11	approach	approach	NOUN
cana-3107	193	12	by	by	ADP
cana-3107	193	13	first	first	ADV
cana-3107	193	14	pinpointing	pinpoint	VERB
cana-3107	193	15	a	a	DET
cana-3107	193	16	region	region	NOUN
cana-3107	193	17	that	that	PRON
cana-3107	193	18	could	could	AUX
cana-3107	193	19	contain	contain	VERB
cana-3107	193	20	an	an	DET
cana-3107	193	21	object	object	NOUN
cana-3107	193	22	,	,	PUNCT
cana-3107	193	23	then	then	ADV
cana-3107	193	24	transforming	transform	VERB
cana-3107	193	25	its	its	PRON
cana-3107	193	26	size	size	NOUN
cana-3107	193	27	into	into	ADP
cana-3107	193	28	the	the	DET
cana-3107	193	29	convolution	convolution	NOUN
cana-3107	193	30	network	network	NOUN
cana-3107	193	31	's	's	PART
cana-3107	193	32	input	input	NOUN
cana-3107	193	33	format	format	NOUN
cana-3107	193	34	,	,	PUNCT
cana-3107	193	35	and	and	CCONJ
cana-3107	193	36	finally	finally	ADV
cana-3107	193	37	determining	determine	VERB
cana-3107	193	38	whether	whether	SCONJ
cana-3107	193	39	or	or	CCONJ
cana-3107	193	40	not	not	PART
cana-3107	193	41	the	the	DET
cana-3107	193	42	region	region	NOUN
cana-3107	193	43	contains	contain	VERB
cana-3107	193	44	an	an	DET
cana-3107	193	45	object	object	NOUN
cana-3107	193	46	and	and	CCONJ
cana-3107	193	47	what	what	DET
cana-3107	193	48	kind	kind	NOUN
cana-3107	193	49	of	of	ADP
cana-3107	193	50	object	object	NOUN
cana-3107	193	51	it	it	PRON
cana-3107	193	52	is	be	AUX
cana-3107	193	53	.	.	PUNCT
cana-3107	194	1	finally	finally	ADV
cana-3107	194	2	,	,	PUNCT
cana-3107	194	3	the	the	DET
cana-3107	194	4	region	region	NOUN
cana-3107	194	5	containing	contain	VERB
cana-3107	194	6	an	an	DET
cana-3107	194	7	object	object	NOUN
cana-3107	194	8	is	be	AUX
cana-3107	194	9	subjected	subject	VERB
cana-3107	194	10	to	to	ADP
cana-3107	194	11	additional	additional	ADJ
cana-3107	194	12	regression	regression	NOUN
cana-3107	194	13	and	and	CCONJ
cana-3107	194	14	micro	micro	NOUN
cana-3107	194	15	-	-	NOUN
cana-3107	194	16	adjustment	adjustment	NOUN
cana-3107	194	17	to	to	PART
cana-3107	194	18	improve	improve	VERB
cana-3107	194	19	its	its	PRON
cana-3107	194	20	framing	frame	VERB
cana-3107	194	21	accuracy	accuracy	NOUN
cana-3107	194	22	.	.	PUNCT
cana-3107	195	1	a	a	DET
cana-3107	195	2	unique	unique	ADJ
cana-3107	195	3	layer	layer	NOUN
cana-3107	195	4	,	,	PUNCT
cana-3107	195	5	the	the	DET
cana-3107	195	6	roi	roi	NOUN
cana-3107	195	7	layer	layer	NOUN
cana-3107	195	8	,	,	PUNCT
cana-3107	195	9	is	be	AUX
cana-3107	195	10	proposed	propose	VERB
cana-3107	195	11	by	by	ADP
cana-3107	195	12	fast	fast	ADJ
cana-3107	195	13	r	r	NOUN
cana-3107	195	14	-	-	PUNCT
cana-3107	195	15	cnn	cnn	NOUN
cana-3107	195	16	.	.	PUNCT
cana-3107	196	1	since	since	SCONJ
cana-3107	196	2	r	r	NOUN
cana-3107	196	3	-	-	PUNCT
cana-3107	196	4	cnn	cnn	PROPN
cana-3107	196	5	and	and	CCONJ
cana-3107	196	6	fast	fast	ADJ
cana-3107	196	7	r	r	NOUN
cana-3107	196	8	-	-	PUNCT
cana-3107	196	9	cnn	cnn	PROPN
cana-3107	196	10	have	have	AUX
cana-3107	196	11	been	be	AUX
cana-3107	196	12	thrown	throw	VERB
cana-3107	196	13	out	out	ADP
cana-3107	196	14	,	,	PUNCT
cana-3107	196	15	a	a	DET
cana-3107	196	16	new	new	ADJ
cana-3107	196	17	method	method	NOUN
cana-3107	196	18	called	call	VERB
cana-3107	196	19	faster	fast	ADJ
cana-3107	196	20	rcnn	rcnn	PROPN
cana-3107	196	21	has	have	AUX
cana-3107	196	22	been	be	AUX
cana-3107	196	23	presented	present	VERB
cana-3107	196	24	.	.	PUNCT
cana-3107	197	1	its	its	PRON
cana-3107	197	2	primary	primary	ADJ
cana-3107	197	3	contributions	contribution	NOUN
cana-3107	197	4	are	be	AUX
cana-3107	197	5	twofold	twofold	ADJ
cana-3107	197	6	:	:	PUNCT
cana-3107	197	7	first	first	ADV
cana-3107	197	8	,	,	PUNCT
cana-3107	197	9	it	it	PRON
cana-3107	197	10	presents	present	VERB
cana-3107	197	11	a	a	DET
cana-3107	197	12	regional	regional	ADJ
cana-3107	197	13	recommendation	recommendation	NOUN
cana-3107	197	14	network	network	NOUN
cana-3107	197	15	(	(	PUNCT
cana-3107	197	16	rpn	rpn	PROPN
cana-3107	197	17	)	)	PUNCT
cana-3107	197	18	to	to	PART
cana-3107	197	19	rapidly	rapidly	ADV
cana-3107	197	20	create	create	VERB
cana-3107	197	21	candidate	candidate	NOUN
cana-3107	197	22	areas	area	NOUN
cana-3107	197	23	;	;	PUNCT
cana-3107	197	24	second	second	X
cana-3107	197	25	,	,	PUNCT
cana-3107	197	26	it	it	PRON
cana-3107	197	27	facilitates	facilitate	VERB
cana-3107	197	28	parameter	parameter	NOUN
cana-3107	197	29	sharing	sharing	NOUN
cana-3107	197	30	between	between	ADP
cana-3107	197	31	the	the	DET
cana-3107	197	32	rpn	rpn	PROPN
cana-3107	197	33	and	and	CCONJ
cana-3107	197	34	the	the	DET
cana-3107	197	35	fast	fast	ADJ
cana-3107	197	36	r	r	NOUN
cana-3107	197	37	-	-	PUNCT
cana-3107	197	38	cnn	cnn	PROPN
cana-3107	197	39	network	network	NOUN
cana-3107	197	40	by	by	ADP
cana-3107	197	41	means	mean	NOUN
cana-3107	197	42	of	of	ADP
cana-3107	197	43	alternating	alternate	VERB
cana-3107	197	44	training	training	NOUN
cana-3107	197	45	.	.	PUNCT
cana-3107	198	1	faster	fast	ADJ
cana-3107	198	2	rcnn	rcnn	PROPN
cana-3107	198	3	's	's	PART
cana-3107	198	4	structure	structure	NOUN
cana-3107	198	5	incorporates	incorporate	VERB
cana-3107	198	6	feature	feature	NOUN
cana-3107	198	7	extraction	extraction	NOUN
cana-3107	198	8	,	,	PUNCT
cana-3107	198	9	regression	regression	NOUN
cana-3107	198	10	,	,	PUNCT
cana-3107	198	11	and	and	CCONJ
cana-3107	198	12	classification	classification	NOUN
cana-3107	198	13	into	into	ADP
cana-3107	198	14	a	a	DET
cana-3107	198	15	single	single	ADJ
cana-3107	198	16	network	network	NOUN
cana-3107	198	17	,	,	PUNCT
cana-3107	198	18	which	which	PRON
cana-3107	198	19	boosts	boost	VERB
cana-3107	198	20	performance	performance	NOUN
cana-3107	198	21	across	across	ADP
cana-3107	198	22	the	the	DET
cana-3107	198	23	board	board	NOUN
cana-3107	198	24	,	,	PUNCT
cana-3107	198	25	particularly	particularly	ADV
cana-3107	198	26	in	in	ADP
cana-3107	198	27	terms	term	NOUN
cana-3107	198	28	of	of	ADP
cana-3107	198	29	how	how	SCONJ
cana-3107	198	30	quickly	quickly	ADV
cana-3107	198	31	classifications	classification	NOUN
cana-3107	198	32	can	can	AUX
cana-3107	198	33	be	be	AUX
cana-3107	198	34	made	make	VERB
cana-3107	198	35	.	.	PUNCT
cana-3107	199	1	insect	insect	NOUN
cana-3107	199	2	segmentation	segmentation	NOUN
cana-3107	199	3	using	use	VERB
cana-3107	199	4	faster	fast	ADJ
cana-3107	199	5	-	-	PUNCT
cana-3107	199	6	rcnn	rcnn	NOUN
cana-3107	199	7	.	.	PUNCT
cana-3107	200	1	figure	figure	NOUN
cana-3107	200	2	2	2	NUM
cana-3107	200	3	below	below	ADP
cana-3107	200	4	outlines	outline	NOUN
cana-3107	200	5	faster	fast	ADV
cana-3107	200	6	r	r	NOUN
cana-3107	200	7	-	-	PUNCT
cana-3107	200	8	cnn	cnn	PROPN
cana-3107	200	9	's	's	PART
cana-3107	200	10	fundamental	fundamental	ADJ
cana-3107	200	11	structure	structure	NOUN
cana-3107	200	12	.	.	PUNCT
cana-3107	201	1	figure3	figure3	NOUN
cana-3107	201	2	.	.	PUNCT
cana-3107	202	1	faster	fast	ADV
cana-3107	202	2	r	r	NOUN
cana-3107	202	3	-	-	PUNCT
cana-3107	202	4	cnn	cnn	PROPN
cana-3107	202	5	faster	fast	ADJ
cana-3107	202	6	rcnn	rcnn	PROPN
cana-3107	202	7	contains	contain	VERB
cana-3107	202	8	two	two	NUM
cana-3107	202	9	parts	part	NOUN
cana-3107	202	10	:	:	PUNCT
cana-3107	202	11	specifically	specifically	ADV
cana-3107	202	12	,	,	PUNCT
cana-3107	202	13	fast	fast	ADJ
cana-3107	202	14	rcnn	rcnn	NOUN
cana-3107	202	15	and	and	CCONJ
cana-3107	202	16	the	the	DET
cana-3107	202	17	regional	regional	ADJ
cana-3107	202	18	proposal	proposal	NOUN
cana-3107	202	19	network	network	NOUN
cana-3107	202	20	(	(	PUNCT
cana-3107	202	21	rpn	rpn	PROPN
cana-3107	202	22	)	)	PUNCT
cana-3107	202	23	.	.	PUNCT
cana-3107	203	1	rpn	rpn	PROPN
cana-3107	203	2	's	's	PART
cana-3107	203	3	goal	goal	NOUN
cana-3107	203	4	is	be	AUX
cana-3107	203	5	to	to	PART
cana-3107	203	6	identify	identify	VERB
cana-3107	203	7	potential	potential	ADJ
cana-3107	203	8	target	target	NOUN
cana-3107	203	9	locations	location	NOUN
cana-3107	203	10	in	in	ADP
cana-3107	203	11	an	an	DET
cana-3107	203	12	input	input	NOUN
cana-3107	203	13	picture	picture	NOUN
cana-3107	203	14	.	.	PUNCT
cana-3107	204	1	fast	fast	ADJ
cana-3107	204	2	rcnn	rcnn	PROPN
cana-3107	204	3	is	be	AUX
cana-3107	204	4	used	use	VERB
cana-3107	204	5	to	to	ADP
cana-3107	204	6	communications	communication	NOUN
cana-3107	204	7	on	on	ADP
cana-3107	204	8	applied	apply	VERB
cana-3107	204	9	nonlinear	nonlinear	ADJ
cana-3107	204	10	analysis	analysis	NOUN
cana-3107	204	11	issn	issn	NOUN
cana-3107	204	12	:	:	PUNCT
cana-3107	204	13	1074	1074	NUM
cana-3107	204	14	-	-	PUNCT
cana-3107	204	15	133x	133x	NUM
cana-3107	204	16	vol	vol	NOUN
cana-3107	204	17	32	32	NUM
cana-3107	204	18	no	no	NOUN
cana-3107	204	19	.	.	PUNCT
cana-3107	205	1	5s	5s	NUM
cana-3107	205	2	(	(	PUNCT
cana-3107	205	3	2025	2025	NUM
cana-3107	205	4	)	)	PUNCT
cana-3107	205	5	369	369	NUM
cana-3107	205	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	205	7	categorize	categorize	VERB
cana-3107	205	8	the	the	DET
cana-3107	205	9	candidate	candidate	NOUN
cana-3107	205	10	areas	area	NOUN
cana-3107	205	11	created	create	VERB
cana-3107	205	12	,	,	PUNCT
cana-3107	205	13	and	and	CCONJ
cana-3107	205	14	to	to	PART
cana-3107	205	15	refine	refine	VERB
cana-3107	205	16	the	the	DET
cana-3107	205	17	candidate	candidate	NOUN
cana-3107	205	18	region	region	NOUN
cana-3107	205	19	borders	border	NOUN
cana-3107	205	20	.	.	PUNCT
cana-3107	206	1	features	feature	NOUN
cana-3107	206	2	collected	collect	VERB
cana-3107	206	3	by	by	ADP
cana-3107	206	4	the	the	DET
cana-3107	206	5	convolutional	convolutional	ADJ
cana-3107	206	6	neural	neural	ADJ
cana-3107	206	7	network	network	NOUN
cana-3107	206	8	are	be	AUX
cana-3107	206	9	shared	share	VERB
cana-3107	206	10	across	across	ADP
cana-3107	206	11	these	these	DET
cana-3107	206	12	two	two	NUM
cana-3107	206	13	networks	network	NOUN
cana-3107	206	14	and	and	CCONJ
cana-3107	206	15	then	then	ADV
cana-3107	206	16	sent	send	VERB
cana-3107	206	17	into	into	ADP
cana-3107	206	18	the	the	DET
cana-3107	206	19	rpn	rpn	PROPN
cana-3107	206	20	for	for	ADP
cana-3107	206	21	further	further	ADJ
cana-3107	206	22	processing	processing	NOUN
cana-3107	206	23	.	.	PUNCT
cana-3107	207	1	to	to	PART
cana-3107	207	2	construct	construct	VERB
cana-3107	207	3	a	a	DET
cana-3107	207	4	feature	feature	NOUN
cana-3107	207	5	map	map	NOUN
cana-3107	207	6	of	of	ADP
cana-3107	207	7	size	size	NOUN
cana-3107	207	8	w	w	PROPN
cana-3107	207	9	h	h	PROPN
cana-3107	207	10	,	,	PUNCT
cana-3107	207	11	rpn	rpn	PROPN
cana-3107	207	12	employs	employ	VERB
cana-3107	207	13	a	a	DET
cana-3107	207	14	sliding	slide	VERB
cana-3107	207	15	window	window	NOUN
cana-3107	207	16	technique	technique	NOUN
cana-3107	207	17	to	to	PART
cana-3107	207	18	gather	gather	VERB
cana-3107	207	19	k	k	PROPN
cana-3107	207	20	starting	start	VERB
cana-3107	207	21	areas	area	NOUN
cana-3107	207	22	at	at	ADP
cana-3107	207	23	each	each	DET
cana-3107	207	24	pixel	pixel	PROPN
cana-3107	207	25	point	point	NOUN
cana-3107	207	26	.	.	PUNCT
cana-3107	208	1	there	there	PRON
cana-3107	208	2	are	be	VERB
cana-3107	208	3	a	a	DET
cana-3107	208	4	total	total	NOUN
cana-3107	208	5	of	of	ADP
cana-3107	208	6	4k	4k	NUM
cana-3107	208	7	outputs	output	NOUN
cana-3107	208	8	from	from	ADP
cana-3107	208	9	the	the	DET
cana-3107	208	10	regression	regression	NOUN
cana-3107	208	11	layer	layer	NOUN
cana-3107	208	12	,	,	PUNCT
cana-3107	208	13	each	each	PRON
cana-3107	208	14	of	of	ADP
cana-3107	208	15	which	which	PRON
cana-3107	208	16	encodes	encode	VERB
cana-3107	208	17	the	the	DET
cana-3107	208	18	4k	4k	NUM
cana-3107	208	19	coordinates	coordinate	NOUN
cana-3107	208	20	of	of	ADP
cana-3107	208	21	the	the	DET
cana-3107	208	22	k	k	PROPN
cana-3107	208	23	frame	frame	NOUN
cana-3107	208	24	,	,	PUNCT
cana-3107	208	25	and	and	CCONJ
cana-3107	208	26	a	a	DET
cana-3107	208	27	total	total	NOUN
cana-3107	208	28	of	of	ADP
cana-3107	208	29	2k	2k	NOUN
cana-3107	208	30	scores	score	NOUN
cana-3107	208	31	from	from	ADP
cana-3107	208	32	the	the	DET
cana-3107	208	33	classification	classification	NOUN
cana-3107	208	34	layer	layer	NOUN
cana-3107	208	35	,	,	PUNCT
cana-3107	208	36	each	each	PRON
cana-3107	208	37	of	of	ADP
cana-3107	208	38	which	which	PRON
cana-3107	208	39	predicts	predict	VERB
cana-3107	208	40	the	the	DET
cana-3107	208	41	chance	chance	NOUN
cana-3107	208	42	that	that	SCONJ
cana-3107	208	43	a	a	DET
cana-3107	208	44	given	give	VERB
cana-3107	208	45	area	area	NOUN
cana-3107	208	46	is	be	AUX
cana-3107	208	47	either	either	CCONJ
cana-3107	208	48	a	a	DET
cana-3107	208	49	target	target	NOUN
cana-3107	208	50	or	or	CCONJ
cana-3107	208	51	a	a	DET
cana-3107	208	52	background	background	NOUN
cana-3107	208	53	.	.	PUNCT
cana-3107	209	1	we	we	PRON
cana-3107	209	2	first	first	ADV
cana-3107	209	3	utilize	utilize	VERB
cana-3107	209	4	a	a	DET
cana-3107	209	5	radial	radial	ADJ
cana-3107	209	6	basis	basis	NOUN
cana-3107	209	7	function	function	NOUN
cana-3107	209	8	(	(	PUNCT
cana-3107	209	9	rpf	rpf	NOUN
cana-3107	209	10	)	)	PUNCT
cana-3107	209	11	network	network	NOUN
cana-3107	209	12	to	to	PART
cana-3107	209	13	locate	locate	VERB
cana-3107	209	14	potential	potential	ADJ
cana-3107	209	15	pest	pest	NOUN
cana-3107	209	16	anchors	anchor	NOUN
cana-3107	209	17	,	,	PUNCT
cana-3107	209	18	and	and	CCONJ
cana-3107	209	19	then	then	ADV
cana-3107	209	20	we	we	PRON
cana-3107	209	21	use	use	VERB
cana-3107	209	22	a	a	DET
cana-3107	209	23	boundary	boundary	ADJ
cana-3107	209	24	regression	regression	NOUN
cana-3107	209	25	approach	approach	NOUN
cana-3107	209	26	to	to	PART
cana-3107	209	27	precisely	precisely	ADV
cana-3107	209	28	identify	identify	VERB
cana-3107	209	29	suitable	suitable	ADJ
cana-3107	209	30	locations	location	NOUN
cana-3107	209	31	.	.	PUNCT
cana-3107	210	1	to	to	PART
cana-3107	210	2	classify	classify	VERB
cana-3107	210	3	these	these	DET
cana-3107	210	4	candidate	candidate	NOUN
cana-3107	210	5	areas	area	NOUN
cana-3107	210	6	,	,	PUNCT
cana-3107	210	7	we	we	PRON
cana-3107	210	8	then	then	ADV
cana-3107	210	9	send	send	VERB
cana-3107	210	10	them	they	PRON
cana-3107	210	11	to	to	ADP
cana-3107	210	12	the	the	DET
cana-3107	210	13	fast	fast	ADJ
cana-3107	210	14	rcnn	rcnn	NOUN
cana-3107	211	1	[	[	X
cana-3107	211	2	23	23	NUM
cana-3107	211	3	]	]	PUNCT
cana-3107	211	4	.	.	PUNCT
cana-3107	212	1	since	since	SCONJ
cana-3107	212	2	training	training	NOUN
cana-3107	212	3	in	in	ADP
cana-3107	212	4	deep	deep	ADJ
cana-3107	212	5	learning	learning	NOUN
cana-3107	212	6	often	often	ADV
cana-3107	212	7	takes	take	VERB
cana-3107	212	8	a	a	DET
cana-3107	212	9	significant	significant	ADJ
cana-3107	212	10	amount	amount	NOUN
cana-3107	212	11	of	of	ADP
cana-3107	212	12	time	time	NOUN
cana-3107	212	13	and	and	CCONJ
cana-3107	212	14	computational	computational	ADJ
cana-3107	212	15	resources	resource	NOUN
cana-3107	212	16	,	,	PUNCT
cana-3107	212	17	optimizing	optimize	VERB
cana-3107	212	18	the	the	DET
cana-3107	212	19	training	training	NOUN
cana-3107	212	20	process	process	NOUN
cana-3107	212	21	is	be	AUX
cana-3107	212	22	a	a	DET
cana-3107	212	23	common	common	ADJ
cana-3107	212	24	topic	topic	NOUN
cana-3107	212	25	of	of	ADP
cana-3107	212	26	discussion	discussion	NOUN
cana-3107	212	27	.	.	PUNCT
cana-3107	213	1	adam	adam	NOUN
cana-3107	213	2	(	(	PUNCT
cana-3107	213	3	adaptive	adaptive	ADJ
cana-3107	213	4	momentum	momentum	NOUN
cana-3107	213	5	)	)	PUNCT
cana-3107	213	6	is	be	AUX
cana-3107	213	7	a	a	DET
cana-3107	213	8	method	method	NOUN
cana-3107	213	9	that	that	PRON
cana-3107	213	10	may	may	AUX
cana-3107	213	11	increase	increase	VERB
cana-3107	213	12	learning	learn	VERB
cana-3107	213	13	speed	speed	NOUN
cana-3107	213	14	and	and	CCONJ
cana-3107	213	15	effect	effect	NOUN
cana-3107	213	16	by	by	ADP
cana-3107	213	17	using	use	VERB
cana-3107	213	18	less	less	ADJ
cana-3107	213	19	resources	resource	NOUN
cana-3107	213	20	while	while	SCONJ
cana-3107	213	21	hastening	hasten	VERB
cana-3107	213	22	model	model	NOUN
cana-3107	213	23	convergence	convergence	NOUN
cana-3107	213	24	.	.	PUNCT
cana-3107	214	1	adam	adam	PROPN
cana-3107	214	2	is	be	AUX
cana-3107	214	3	an	an	DET
cana-3107	214	4	alternative	alternative	NOUN
cana-3107	214	5	to	to	ADP
cana-3107	214	6	the	the	DET
cana-3107	214	7	standard	standard	ADJ
cana-3107	214	8	stochastic	stochastic	ADJ
cana-3107	214	9	gradient	gradient	ADJ
cana-3107	214	10	descent	descent	NOUN
cana-3107	214	11	optimization	optimization	NOUN
cana-3107	214	12	procedure	procedure	NOUN
cana-3107	214	13	.	.	PUNCT
cana-3107	215	1	adadelta	adadelta	ADJ
cana-3107	215	2	incorporates	incorporate	VERB
cana-3107	215	3	a	a	DET
cana-3107	215	4	moment	moment	NOUN
cana-3107	215	5	of	of	ADP
cana-3107	215	6	second	second	ADJ
cana-3107	215	7	-	-	PUNCT
cana-3107	215	8	order	order	NOUN
cana-3107	215	9	moment	moment	NOUN
cana-3107	215	10	estimate	estimate	NOUN
cana-3107	215	11	based	base	VERB
cana-3107	215	12	on	on	ADP
cana-3107	215	13	momentum	momentum	NOUN
cana-3107	215	14	's	's	PART
cana-3107	215	15	first	first	ADJ
cana-3107	215	16	-	-	PUNCT
cana-3107	215	17	order	order	NOUN
cana-3107	215	18	moment	moment	NOUN
cana-3107	215	19	estimation	estimation	NOUN
cana-3107	215	20	,	,	PUNCT
cana-3107	215	21	allowing	allow	VERB
cana-3107	215	22	for	for	ADP
cana-3107	215	23	the	the	DET
cana-3107	215	24	dynamic	dynamic	ADJ
cana-3107	215	25	adjustment	adjustment	NOUN
cana-3107	215	26	of	of	ADP
cana-3107	215	27	the	the	DET
cana-3107	215	28	learning	learning	NOUN
cana-3107	215	29	rate	rate	NOUN
cana-3107	215	30	of	of	ADP
cana-3107	215	31	each	each	DET
cana-3107	215	32	parameter	parameter	NOUN
cana-3107	215	33	.	.	PUNCT
cana-3107	216	1	the	the	DET
cana-3107	216	2	use	use	NOUN
cana-3107	216	3	of	of	ADP
cana-3107	216	4	a	a	DET
cana-3107	216	5	bias	bias	NOUN
cana-3107	216	6	adjustment	adjustment	NOUN
cana-3107	216	7	helps	help	VERB
cana-3107	216	8	keep	keep	VERB
cana-3107	216	9	the	the	DET
cana-3107	216	10	parameters	parameter	NOUN
cana-3107	216	11	steady	steady	ADJ
cana-3107	216	12	[	[	X
cana-3107	216	13	24	24	NUM
cana-3107	216	14	]	]	PUNCT
cana-3107	216	15	.	.	PUNCT
cana-3107	217	1	in	in	ADP
cana-3107	217	2	order	order	NOUN
cana-3107	217	3	to	to	PART
cana-3107	217	4	get	get	VERB
cana-3107	217	5	the	the	DET
cana-3107	217	6	optimal	optimal	ADJ
cana-3107	217	7	weights	weight	NOUN
cana-3107	217	8	for	for	ADP
cana-3107	217	9	each	each	DET
cana-3107	217	10	stage	stage	NOUN
cana-3107	217	11	,	,	PUNCT
cana-3107	217	12	the	the	DET
cana-3107	217	13	adam	adam	PROPN
cana-3107	217	14	algorithm	algorithm	PROPN
cana-3107	217	15	is	be	AUX
cana-3107	217	16	utilized	utilize	VERB
cana-3107	217	17	.	.	PUNCT
cana-3107	218	1	this	this	DET
cana-3107	218	2	algorithm	algorithm	NOUN
cana-3107	218	3	is	be	AUX
cana-3107	218	4	of	of	ADP
cana-3107	218	5	the	the	DET
cana-3107	218	6	first	first	ADJ
cana-3107	218	7	order	order	NOUN
cana-3107	218	8	and	and	CCONJ
cana-3107	218	9	runs	run	VERB
cana-3107	218	10	quickly	quickly	ADV
cana-3107	218	11	on	on	ADP
cana-3107	218	12	the	the	DET
cana-3107	218	13	computer	computer	NOUN
cana-3107	218	14	.	.	PUNCT
cana-3107	219	1	the	the	DET
cana-3107	219	2	accurate	accurate	ADJ
cana-3107	219	3	bias	bias	NOUN
cana-3107	219	4	ratings	rating	NOUN
cana-3107	219	5	of	of	ADP
cana-3107	219	6	the	the	DET
cana-3107	219	7	square	square	ADJ
cana-3107	219	8	gradient	gradient	NOUN
cana-3107	219	9	and	and	CCONJ
cana-3107	219	10	the	the	DET
cana-3107	219	11	moving	move	VERB
cana-3107	219	12	average	average	ADJ
cana-3107	219	13	gradient	gradient	NOUN
cana-3107	219	14	are	be	AUX
cana-3107	219	15	reflected	reflect	VERB
cana-3107	219	16	.	.	PUNCT
cana-3107	220	1	adam	adam	PROPN
cana-3107	220	2	's	's	PART
cana-3107	220	3	performance	performance	NOUN
cana-3107	220	4	suffers	suffer	VERB
cana-3107	220	5	from	from	ADP
cana-3107	220	6	two	two	NUM
cana-3107	220	7	issues	issue	NOUN
cana-3107	220	8	.	.	PUNCT
cana-3107	221	1	both	both	CCONJ
cana-3107	221	2	the	the	DET
cana-3107	221	3	effect	effect	NOUN
cana-3107	221	4	of	of	ADP
cana-3107	221	5	updates	update	NOUN
cana-3107	221	6	on	on	ADP
cana-3107	221	7	the	the	DET
cana-3107	221	8	network	network	NOUN
cana-3107	221	9	's	's	PART
cana-3107	221	10	overall	overall	ADJ
cana-3107	221	11	matching	matching	NOUN
cana-3107	221	12	function	function	NOUN
cana-3107	221	13	and	and	CCONJ
cana-3107	221	14	the	the	DET
cana-3107	221	15	number	number	NOUN
cana-3107	221	16	of	of	ADP
cana-3107	221	17	its	its	PRON
cana-3107	221	18	parameters	parameter	NOUN
cana-3107	221	19	depend	depend	VERB
cana-3107	221	20	on	on	ADP
cana-3107	221	21	the	the	DET
cana-3107	221	22	stochastic	stochastic	ADJ
cana-3107	221	23	gradient	gradient	NOUN
cana-3107	221	24	discovered	discover	VERB
cana-3107	221	25	during	during	ADP
cana-3107	221	26	the	the	DET
cana-3107	221	27	time	time	NOUN
cana-3107	221	28	of	of	ADP
cana-3107	221	29	historical	historical	ADJ
cana-3107	221	30	gradients	gradient	NOUN
cana-3107	221	31	.	.	PUNCT
cana-3107	222	1	we	we	PRON
cana-3107	222	2	suggested	suggest	VERB
cana-3107	222	3	a	a	DET
cana-3107	222	4	modified	modified	ADJ
cana-3107	222	5	version	version	NOUN
cana-3107	222	6	of	of	ADP
cana-3107	222	7	the	the	DET
cana-3107	222	8	adam	adam	PROPN
cana-3107	222	9	algorithm	algorithm	PROPN
cana-3107	222	10	as	as	ADP
cana-3107	222	11	a	a	DET
cana-3107	222	12	means	means	NOUN
cana-3107	222	13	of	of	ADP
cana-3107	222	14	overcoming	overcome	VERB
cana-3107	222	15	such	such	ADJ
cana-3107	222	16	challenges	challenge	NOUN
cana-3107	222	17	.	.	PUNCT
cana-3107	223	1	acute	acute	ADJ
cana-3107	223	2	local	local	ADJ
cana-3107	223	3	lows	low	NOUN
cana-3107	223	4	that	that	PRON
cana-3107	223	5	do	do	AUX
cana-3107	223	6	n't	not	PART
cana-3107	223	7	generalize	generalize	VERB
cana-3107	223	8	well	well	ADJ
cana-3107	223	9	result	result	NOUN
cana-3107	223	10	from	from	ADP
cana-3107	223	11	the	the	DET
cana-3107	223	12	training	training	NOUN
cana-3107	223	13	-	-	PUNCT
cana-3107	223	14	induced	induce	VERB
cana-3107	223	15	drop	drop	NOUN
cana-3107	223	16	in	in	ADP
cana-3107	223	17	weight	weight	NOUN
cana-3107	223	18	carriers	carrier	NOUN
cana-3107	223	19	'	'	PART
cana-3107	223	20	real	real	ADJ
cana-3107	223	21	learning	learning	NOUN
cana-3107	223	22	rates	rate	NOUN
cana-3107	223	23	.	.	PUNCT
cana-3107	224	1	each	each	DET
cana-3107	224	2	input	input	NOUN
cana-3107	224	3	weight	weight	NOUN
cana-3107	224	4	vector	vector	NOUN
cana-3107	224	5	,	,	PUNCT
cana-3107	224	6	rather	rather	ADV
cana-3107	224	7	than	than	ADP
cana-3107	224	8	each	each	DET
cana-3107	224	9	individual	individual	ADJ
cana-3107	224	10	weight	weight	NOUN
cana-3107	224	11	,	,	PUNCT
cana-3107	224	12	is	be	AUX
cana-3107	224	13	accelerated	accelerate	VERB
cana-3107	224	14	in	in	ADP
cana-3107	224	15	its	its	PRON
cana-3107	224	16	learning	learning	NOUN
cana-3107	224	17	rate	rate	NOUN
cana-3107	224	18	to	to	PART
cana-3107	224	19	preserve	preserve	VERB
cana-3107	224	20	the	the	DET
cana-3107	224	21	gradient	gradient	NOUN
cana-3107	224	22	's	's	PART
cana-3107	224	23	orientation	orientation	NOUN
cana-3107	224	24	.	.	PUNCT
cana-3107	225	1	the	the	DET
cana-3107	225	2	updated	update	VERB
cana-3107	225	3	adam	adam	PROPN
cana-3107	225	4	algorithm	algorithm	PROPN
cana-3107	225	5	retains	retain	VERB
cana-3107	225	6	its	its	PRON
cana-3107	225	7	original	original	ADJ
cana-3107	225	8	qualities	quality	NOUN
cana-3107	225	9	,	,	PUNCT
cana-3107	225	10	such	such	ADJ
cana-3107	225	11	as	as	ADP
cana-3107	225	12	the	the	DET
cana-3107	225	13	ability	ability	NOUN
cana-3107	225	14	to	to	PART
cana-3107	225	15	precisely	precisely	ADV
cana-3107	225	16	regulate	regulate	VERB
cana-3107	225	17	the	the	DET
cana-3107	225	18	learning	learning	NOUN
cana-3107	225	19	rate	rate	NOUN
cana-3107	225	20	and	and	CCONJ
cana-3107	225	21	the	the	DET
cana-3107	225	22	conservation	conservation	NOUN
cana-3107	225	23	of	of	ADP
cana-3107	225	24	gradient	gradient	ADJ
cana-3107	225	25	direction	direction	NOUN
cana-3107	225	26	for	for	ADP
cana-3107	225	27	each	each	DET
cana-3107	225	28	weight	weight	NOUN
cana-3107	225	29	.	.	PUNCT
cana-3107	226	1	in	in	ADP
cana-3107	226	2	addition	addition	NOUN
cana-3107	226	3	,	,	PUNCT
cana-3107	226	4	it	it	PRON
cana-3107	226	5	boosts	boost	VERB
cana-3107	226	6	efficiency	efficiency	NOUN
cana-3107	226	7	[	[	X
cana-3107	226	8	25	25	NUM
cana-3107	226	9	]	]	PUNCT
cana-3107	226	10	.	.	PUNCT
cana-3107	227	1	adam	adam	PROPN
cana-3107	227	2	algorithm	algorithm	PROPN
cana-3107	227	3	is	be	AUX
cana-3107	227	4	an	an	DET
cana-3107	227	5	adaptive	adaptive	ADJ
cana-3107	227	6	method	method	NOUN
cana-3107	227	7	for	for	ADP
cana-3107	227	8	optimizing	optimize	VERB
cana-3107	227	9	the	the	DET
cana-3107	227	10	learning	learning	NOUN
cana-3107	227	11	rate	rate	NOUN
cana-3107	227	12	.	.	PUNCT
cana-3107	228	1	this	this	DET
cana-3107	228	2	optimization	optimization	NOUN
cana-3107	228	3	method	method	NOUN
cana-3107	228	4	was	be	AUX
cana-3107	228	5	developed	develop	VERB
cana-3107	228	6	specifically	specifically	ADV
cana-3107	228	7	for	for	ADP
cana-3107	228	8	deep	deep	ADJ
cana-3107	228	9	learning	learning	NOUN
cana-3107	228	10	techniques	technique	NOUN
cana-3107	228	11	.	.	PUNCT
cana-3107	229	1	the	the	DET
cana-3107	229	2	algorithm	algorithm	NOUN
cana-3107	229	3	's	's	PART
cana-3107	229	4	primary	primary	ADJ
cana-3107	229	5	contribution	contribution	NOUN
cana-3107	229	6	is	be	AUX
cana-3107	229	7	the	the	DET
cana-3107	229	8	identification	identification	NOUN
cana-3107	229	9	of	of	ADP
cana-3107	229	10	unique	unique	ADJ
cana-3107	229	11	adaptive	adaptive	ADJ
cana-3107	229	12	learning	learning	NOUN
cana-3107	229	13	rates	rate	NOUN
cana-3107	229	14	for	for	ADP
cana-3107	229	15	different	different	ADJ
cana-3107	229	16	parameters	parameter	NOUN
cana-3107	229	17	.	.	PUNCT
cana-3107	230	1	the	the	DET
cana-3107	230	2	algorithm	algorithm	NOUN
cana-3107	230	3	's	's	PART
cana-3107	230	4	adaptive	adaptive	ADJ
cana-3107	230	5	moment	moment	NOUN
cana-3107	230	6	estimation	estimation	NOUN
cana-3107	230	7	process	process	NOUN
cana-3107	230	8	inspired	inspire	VERB
cana-3107	230	9	the	the	DET
cana-3107	230	10	name	name	NOUN
cana-3107	230	11	.	.	PUNCT
cana-3107	231	1	each	each	DET
cana-3107	231	2	weight	weight	NOUN
cana-3107	231	3	in	in	ADP
cana-3107	231	4	a	a	DET
cana-3107	231	5	deep	deep	ADJ
cana-3107	231	6	neural	neural	ADJ
cana-3107	231	7	network	network	NOUN
cana-3107	231	8	's	's	PART
cana-3107	231	9	activation	activation	NOUN
cana-3107	231	10	function	function	NOUN
cana-3107	231	11	has	have	VERB
cana-3107	231	12	its	its	PRON
cana-3107	231	13	learning	learning	NOUN
cana-3107	231	14	rate	rate	NOUN
cana-3107	231	15	adjusted	adjust	VERB
cana-3107	231	16	based	base	VERB
cana-3107	231	17	on	on	ADP
cana-3107	231	18	estimates	estimate	NOUN
cana-3107	231	19	of	of	ADP
cana-3107	231	20	its	its	PRON
cana-3107	231	21	gradient	gradient	NOUN
cana-3107	231	22	made	make	VERB
cana-3107	231	23	using	use	VERB
cana-3107	231	24	the	the	DET
cana-3107	231	25	network	network	NOUN
cana-3107	231	26	's	's	PART
cana-3107	231	27	first	first	ADJ
cana-3107	231	28	and	and	CCONJ
cana-3107	231	29	second	second	ADJ
cana-3107	231	30	moments	moment	NOUN
cana-3107	231	31	.	.	PUNCT
cana-3107	232	1	average	average	ADJ
cana-3107	232	2	and	and	CCONJ
cana-3107	232	3	variance	variance	NOUN
cana-3107	232	4	are	be	AUX
cana-3107	232	5	the	the	DET
cana-3107	232	6	first	first	ADJ
cana-3107	232	7	and	and	CCONJ
cana-3107	232	8	second	second	ADJ
cana-3107	232	9	moments	moment	NOUN
cana-3107	232	10	,	,	PUNCT
cana-3107	232	11	respectively	respectively	ADV
cana-3107	232	12	.	.	PUNCT
cana-3107	233	1	in	in	ADP
cana-3107	233	2	every	every	DET
cana-3107	233	3	iteration	iteration	NOUN
cana-3107	233	4	,	,	PUNCT
cana-3107	233	5	the	the	DET
cana-3107	233	6	adam	adam	PROPN
cana-3107	233	7	method	method	PROPN
cana-3107	233	8	employs	employ	VERB
cana-3107	233	9	exponential	exponential	ADJ
cana-3107	233	10	moving	moving	NOUN
cana-3107	233	11	averages	average	NOUN
cana-3107	233	12	to	to	PART
cana-3107	233	13	estimate	estimate	VERB
cana-3107	233	14	moments	moment	NOUN
cana-3107	233	15	in	in	ADP
cana-3107	233	16	each	each	DET
cana-3107	233	17	batch	batch	NOUN
cana-3107	233	18	[	[	X
cana-3107	233	19	26	26	NUM
cana-3107	233	20	]	]	PUNCT
cana-3107	233	21	.	.	PUNCT
cana-3107	234	1	following	follow	VERB
cana-3107	234	2	are	be	AUX
cana-3107	234	3	some	some	DET
cana-3107	234	4	mathematical	mathematical	ADJ
cana-3107	234	5	formulae	formulae	NOUN
cana-3107	234	6	that	that	PRON
cana-3107	234	7	may	may	AUX
cana-3107	234	8	be	be	AUX
cana-3107	234	9	understood	understand	VERB
cana-3107	234	10	in	in	ADP
cana-3107	234	11	light	light	NOUN
cana-3107	234	12	of	of	ADP
cana-3107	234	13	the	the	DET
cana-3107	234	14	update	update	NOUN
cana-3107	234	15	rule	rule	NOUN
cana-3107	234	16	for	for	ADP
cana-3107	234	17	the	the	DET
cana-3107	234	18	adam	adam	PROPN
cana-3107	234	19	optimizer	optimizer	NOUN
cana-3107	234	20	:	:	PUNCT
cana-3107	234	21	(	(	PUNCT
cana-3107	234	22	1	1	X
cana-3107	234	23	)	)	PUNCT
cana-3107	234	24	(	(	PUNCT
cana-3107	234	25	2	2	X
cana-3107	234	26	)	)	PUNCT
cana-3107	234	27	communications	communication	NOUN
cana-3107	234	28	on	on	ADP
cana-3107	234	29	applied	apply	VERB
cana-3107	234	30	nonlinear	nonlinear	ADJ
cana-3107	234	31	analysis	analysis	NOUN
cana-3107	234	32	issn	issn	NOUN
cana-3107	234	33	:	:	PUNCT
cana-3107	234	34	1074	1074	NUM
cana-3107	234	35	-	-	PUNCT
cana-3107	234	36	133x	133x	NUM
cana-3107	234	37	vol	vol	NOUN
cana-3107	234	38	32	32	NUM
cana-3107	234	39	no	no	NOUN
cana-3107	234	40	.	.	PUNCT
cana-3107	235	1	5s	5s	NUM
cana-3107	235	2	(	(	PUNCT
cana-3107	235	3	2025	2025	NUM
cana-3107	235	4	)	)	PUNCT
cana-3107	235	5	370	370	NUM
cana-3107	235	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	235	7	where	where	SCONJ
cana-3107	235	8	n	n	NOUN
cana-3107	235	9	and	and	CCONJ
cana-3107	235	10	s	s	VERB
cana-3107	235	11	are	be	AUX
cana-3107	235	12	weighted	weight	VERB
cana-3107	235	13	moving	move	VERB
cana-3107	235	14	averages	average	NOUN
cana-3107	235	15	,	,	PUNCT
cana-3107	235	16	g	g	PROPN
cana-3107	235	17	is	be	AUX
cana-3107	235	18	the	the	DET
cana-3107	235	19	gradient	gradient	NOUN
cana-3107	235	20	on	on	ADP
cana-3107	235	21	the	the	DET
cana-3107	235	22	current	current	ADJ
cana-3107	235	23	batch	batch	NOUN
cana-3107	235	24	,	,	PUNCT
cana-3107	235	25	t	t	PROPN
cana-3107	235	26	is	be	AUX
cana-3107	235	27	the	the	DET
cana-3107	235	28	number	number	NOUN
cana-3107	235	29	of	of	ADP
cana-3107	235	30	iterations	iteration	NOUN
cana-3107	235	31	,	,	PUNCT
cana-3107	235	32	and	and	CCONJ
cana-3107	235	33	β1	β1	PROPN
cana-3107	235	34	and	and	CCONJ
cana-3107	235	35	β2	β2	NOUN
cana-3107	235	36	are	be	AUX
cana-3107	235	37	algorithmic	algorithmic	ADJ
cana-3107	235	38	hyper	hyper	NOUN
cana-3107	235	39	-	-	NOUN
cana-3107	235	40	parameters	parameter	NOUN
cana-3107	235	41	.	.	PUNCT
cana-3107	236	1	the	the	DET
cana-3107	236	2	gradient	gradient	NOUN
cana-3107	236	3	and	and	CCONJ
cana-3107	236	4	the	the	DET
cana-3107	236	5	squared	square	VERB
cana-3107	236	6	gradient	gradient	NOUN
cana-3107	236	7	are	be	AUX
cana-3107	236	8	moving	move	VERB
cana-3107	236	9	averages	average	NOUN
cana-3107	236	10	,	,	PUNCT
cana-3107	236	11	respectively	respectively	ADV
cana-3107	236	12	,	,	PUNCT
cana-3107	236	13	in	in	ADP
cana-3107	236	14	equation	equation	NOUN
cana-3107	236	15	(	(	PUNCT
cana-3107	236	16	1	1	NUM
cana-3107	236	17	)	)	PUNCT
cana-3107	236	18	and	and	CCONJ
cana-3107	236	19	equation	equation	NOUN
cana-3107	236	20	(	(	PUNCT
cana-3107	236	21	2	2	NUM
cana-3107	236	22	)	)	PUNCT
cana-3107	236	23	.	.	PUNCT
cana-3107	237	1	algorithm1	algorithm1	PROPN
cana-3107	237	2	.	.	PUNCT
cana-3107	238	1	faster	fast	ADJ
cana-3107	238	2	rcnn	rcnn	PROPN
cana-3107	238	3	with	with	ADP
cana-3107	238	4	adam	adam	PROPN
cana-3107	238	5	optimizer	optimizer	PROPN
cana-3107	238	6	1	1	NUM
cana-3107	238	7	.	.	PUNCT
cana-3107	238	8	start	start	VERB
cana-3107	238	9	2	2	NUM
cana-3107	238	10	.	.	PUNCT
cana-3107	238	11	select	select	VERB
cana-3107	238	12	an	an	DET
cana-3107	238	13	image	image	NOUN
cana-3107	238	14	file	file	NOUN
cana-3107	238	15	to	to	ADP
cana-3107	238	16	load	load	NOUN
cana-3107	238	17	.	.	PUNCT
cana-3107	239	1	3	3	X
cana-3107	239	2	.	.	X
cana-3107	239	3	use	use	VERB
cana-3107	239	4	preprocessing	preprocesse	VERB
cana-3107	239	5	for	for	ADP
cana-3107	239	6	feature	feature	NOUN
cana-3107	239	7	extraction	extraction	NOUN
cana-3107	239	8	.	.	PUNCT
cana-3107	240	1	4	4	X
cana-3107	240	2	.	.	X
cana-3107	240	3	use	use	VERB
cana-3107	240	4	inceptionv3	inceptionv3	NOUN
cana-3107	240	5	for	for	ADP
cana-3107	240	6	feature	feature	NOUN
cana-3107	240	7	extraction	extraction	NOUN
cana-3107	240	8	5	5	NUM
cana-3107	240	9	.	.	PUNCT
cana-3107	240	10	locate	locate	ADJ
cana-3107	240	11	possible	possible	ADJ
cana-3107	240	12	object	object	NOUN
cana-3107	240	13	-	-	PUNCT
cana-3107	240	14	containing	contain	VERB
cana-3107	240	15	zones	zone	NOUN
cana-3107	240	16	in	in	ADP
cana-3107	240	17	the	the	DET
cana-3107	240	18	image	image	NOUN
cana-3107	240	19	.	.	PUNCT
cana-3107	241	1	proposed	propose	VERB
cana-3107	241	2	regions	region	NOUN
cana-3107	241	3	are	be	AUX
cana-3107	241	4	what	what	PRON
cana-3107	241	5	we	we	PRON
cana-3107	241	6	name	name	VERB
cana-3107	241	7	them	they	PRON
cana-3107	241	8	here	here	ADV
cana-3107	241	9	.	.	PUNCT
cana-3107	242	1	6	6	X
cana-3107	242	2	.	.	X
cana-3107	242	3	feature	feature	NOUN
cana-3107	242	4	extraction	extraction	NOUN
cana-3107	242	5	for	for	ADP
cana-3107	242	6	cnn	cnn	PROPN
cana-3107	242	7	using	use	VERB
cana-3107	242	8	proposed	propose	VERB
cana-3107	242	9	regions	region	NOUN
cana-3107	242	10	.	.	PUNCT
cana-3107	243	1	7	7	X
cana-3107	243	2	.	.	X
cana-3107	243	3	in	in	ADP
cana-3107	243	4	faster	fast	ADJ
cana-3107	243	5	-	-	PUNCT
cana-3107	243	6	rcnn	rcnn	NOUN
cana-3107	243	7	,	,	PUNCT
cana-3107	243	8	the	the	DET
cana-3107	243	9	search	search	NOUN
cana-3107	243	10	selection	selection	NOUN
cana-3107	243	11	is	be	AUX
cana-3107	243	12	replaced	replace	VERB
cana-3107	243	13	by	by	ADP
cana-3107	243	14	a	a	DET
cana-3107	243	15	recommendation	recommendation	NOUN
cana-3107	243	16	network	network	NOUN
cana-3107	243	17	(	(	PUNCT
cana-3107	243	18	rpn	rpn	PROPN
cana-3107	243	19	)	)	PUNCT
cana-3107	243	20	for	for	ADP
cana-3107	243	21	candidate	candidate	NOUN
cana-3107	243	22	regions	region	NOUN
cana-3107	243	23	.	.	PUNCT
cana-3107	244	1	8	8	X
cana-3107	244	2	.	.	X
cana-3107	244	3	when	when	SCONJ
cana-3107	244	4	it	it	PRON
cana-3107	244	5	comes	come	VERB
cana-3107	244	6	to	to	ADP
cana-3107	244	7	gathering	gather	VERB
cana-3107	244	8	candidate	candidate	NOUN
cana-3107	244	9	boxes	box	NOUN
cana-3107	244	10	,	,	PUNCT
cana-3107	244	11	computing	compute	VERB
cana-3107	244	12	their	their	PRON
cana-3107	244	13	characteristic	characteristic	ADJ
cana-3107	244	14	maps	map	NOUN
cana-3107	244	15	,	,	PUNCT
cana-3107	244	16	and	and	CCONJ
cana-3107	244	17	moving	move	VERB
cana-3107	244	18	them	they	PRON
cana-3107	244	19	on	on	ADP
cana-3107	244	20	to	to	ADP
cana-3107	244	21	the	the	DET
cana-3107	244	22	next	next	ADJ
cana-3107	244	23	network	network	NOUN
cana-3107	244	24	,	,	PUNCT
cana-3107	244	25	roi	roi	NOUN
cana-3107	244	26	pooling	pooling	NOUN
cana-3107	244	27	is	be	AUX
cana-3107	244	28	in	in	ADP
cana-3107	244	29	charge	charge	NOUN
cana-3107	244	30	.	.	PUNCT
cana-3107	245	1	9	9	X
cana-3107	245	2	.	.	X
cana-3107	245	3	classify	classify	VERB
cana-3107	245	4	the	the	DET
cana-3107	245	5	objects	object	NOUN
cana-3107	245	6	using	use	VERB
cana-3107	245	7	the	the	DET
cana-3107	245	8	extracted	extract	VERB
cana-3107	245	9	features	feature	NOUN
cana-3107	245	10	.	.	PUNCT
cana-3107	246	1	10	10	X
cana-3107	246	2	.	.	PUNCT
cana-3107	247	1	use	use	VERB
cana-3107	247	2	the	the	DET
cana-3107	247	3	train	train	NOUN
cana-3107	247	4	fast	fast	ADJ
cana-3107	247	5	rcnn	rcnn	NOUN
cana-3107	247	6	function	function	VERB
cana-3107	247	7	to	to	PART
cana-3107	247	8	train	train	VERB
cana-3107	247	9	a	a	DET
cana-3107	247	10	fast	fast	ADJ
cana-3107	247	11	r	r	NOUN
cana-3107	247	12	-	-	PUNCT
cana-3107	247	13	cnn	cnn	PROPN
cana-3107	247	14	object	object	NOUN
cana-3107	247	15	detection	detection	NOUN
cana-3107	247	16	11	11	NUM
cana-3107	247	17	.	.	PUNCT
cana-3107	248	1	returns	return	NOUN
cana-3107	248	2	faster	fast	ADV
cana-3107	248	3	rcnn	rcnn	PROPN
cana-3107	248	4	object	object	PROPN
cana-3107	248	5	detected	detect	VERB
cana-3107	248	6	12	12	NUM
cana-3107	248	7	.	.	PUNCT
cana-3107	249	1	initially	initially	ADV
cana-3107	249	2	,	,	PUNCT
cana-3107	249	3	both	both	CCONJ
cana-3107	249	4	nt	not	PART
cana-3107	249	5	and	and	CCONJ
cana-3107	249	6	st	st	PROPN
cana-3107	249	7	are	be	AUX
cana-3107	249	8	set	set	VERB
cana-3107	249	9	to	to	ADP
cana-3107	249	10	0	0	NUM
cana-3107	249	11	.	.	PROPN
cana-3107	250	1	13	13	NUM
cana-3107	250	2	.	.	PUNCT
cana-3107	251	1	both	both	PRON
cana-3107	251	2	tend	tend	VERB
cana-3107	251	3	to	to	PART
cana-3107	251	4	be	be	AUX
cana-3107	251	5	more	more	ADV
cana-3107	251	6	biased	biased	ADJ
cana-3107	251	7	towards	towards	ADP
cana-3107	251	8	0	0	NUM
cana-3107	251	9	as	as	SCONJ
cana-3107	251	10	β1	β1	PROPN
cana-3107	251	11	and	and	CCONJ
cana-3107	251	12	β2	β2	NOUN
cana-3107	251	13	are	be	AUX
cana-3107	251	14	equal	equal	ADJ
cana-3107	251	15	to	to	ADP
cana-3107	251	16	1	1	NUM
cana-3107	251	17	.	.	PUNCT
cana-3107	251	18	14	14	NUM
cana-3107	251	19	.	.	PUNCT
cana-3107	252	1	by	by	ADP
cana-3107	252	2	computing	compute	VERB
cana-3107	252	3	bias	bias	NOUN
cana-3107	252	4	-	-	PUNCT
cana-3107	252	5	corrected	correct	VERB
cana-3107	252	6	nt	not	PART
cana-3107	252	7	and	and	CCONJ
cana-3107	252	8	st	st	PROPN
cana-3107	252	9	this	this	DET
cana-3107	252	10	problem	problem	NOUN
cana-3107	252	11	is	be	AUX
cana-3107	252	12	corrected	correct	VERB
cana-3107	252	13	by	by	ADP
cana-3107	252	14	the	the	DET
cana-3107	252	15	adam	adam	PROPN
cana-3107	252	16	optimizer	optimizer	NOUN
cana-3107	252	17	.	.	PUNCT
cana-3107	253	1	15	15	NUM
cana-3107	253	2	.	.	PUNCT
cana-3107	254	1	while	while	SCONJ
cana-3107	254	2	w(t	w(t	PROPN
cana-3107	254	3	)	)	PUNCT
cana-3107	254	4	not	not	PART
cana-3107	254	5	converged	converge	VERB
cana-3107	254	6	do	do	VERB
cana-3107	254	7	16	16	NUM
cana-3107	254	8	.	.	PUNCT
cana-3107	255	1	t	t	PROPN
cana-3107	255	2	=	=	PROPN
cana-3107	255	3	t+1	t+1	PROPN
cana-3107	255	4	17	17	NUM
cana-3107	255	5	.	.	PUNCT
cana-3107	256	1	use	use	VERB
cana-3107	256	2	equation	equation	NOUN
cana-3107	256	3	1	1	NUM
cana-3107	256	4	and	and	CCONJ
cana-3107	256	5	equation	equation	NOUN
cana-3107	256	6	2	2	NUM
cana-3107	256	7	to	to	PART
cana-3107	256	8	get	get	VERB
cana-3107	256	9	nt	not	PART
cana-3107	256	10	and	and	CCONJ
cana-3107	256	11	st	st	PROPN
cana-3107	256	12	18	18	NUM
cana-3107	256	13	.	.	PUNCT
cana-3107	257	1	then	then	ADV
cana-3107	257	2	wt	wt	PROPN
cana-3107	257	3	=	=	NOUN
cana-3107	257	4	w(t-1)-(nt	w(t-1)-(nt	NOUN
cana-3107	257	5	/	/	SYM
cana-3107	257	6	st	st	NOUN
cana-3107	257	7	)	)	PUNCT
cana-3107	257	8	19	19	NUM
cana-3107	257	9	.	.	NOUN
cana-3107	257	10	end	end	NOUN
cana-3107	257	11	20	20	NUM
cana-3107	257	12	.	.	PUNCT
cana-3107	258	1	return	return	VERB
cana-3107	258	2	wt	wt	NOUN
cana-3107	258	3	figure	figure	NOUN
cana-3107	258	4	4	4	NUM
cana-3107	258	5	.	.	PUNCT
cana-3107	258	6	detecting	detect	VERB
cana-3107	258	7	insect	insect	NOUN
cana-3107	258	8	image	image	NOUN
cana-3107	258	9	with	with	ADP
cana-3107	258	10	higher	high	ADJ
cana-3107	258	11	accuracy	accuracy	NOUN
cana-3107	258	12	using	use	VERB
cana-3107	258	13	proposed	propose	VERB
cana-3107	258	14	frcnn	frcnn	NOUN
cana-3107	258	15	with	with	ADP
cana-3107	258	16	adam	adam	PROPN
cana-3107	258	17	optimizer	optimizer	NOUN
cana-3107	258	18	https://www.mathworks.com/help/vision/ref/trainfastrcnnobjectdetector.html	https://www.mathworks.com/help/vision/ref/trainfastrcnnobjectdetector.html	PROPN
cana-3107	258	19	communications	communication	NOUN
cana-3107	258	20	on	on	ADP
cana-3107	258	21	applied	apply	VERB
cana-3107	258	22	nonlinear	nonlinear	ADJ
cana-3107	258	23	analysis	analysis	NOUN
cana-3107	258	24	issn	issn	NOUN
cana-3107	258	25	:	:	PUNCT
cana-3107	258	26	1074	1074	NUM
cana-3107	258	27	-	-	PUNCT
cana-3107	258	28	133x	133x	NUM
cana-3107	258	29	vol	vol	NOUN
cana-3107	258	30	32	32	NUM
cana-3107	258	31	no	no	NOUN
cana-3107	258	32	.	.	PUNCT
cana-3107	259	1	5s	5s	NUM
cana-3107	259	2	(	(	PUNCT
cana-3107	259	3	2025	2025	NUM
cana-3107	259	4	)	)	PUNCT
cana-3107	259	5	371	371	NUM
cana-3107	259	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	259	7	figure	figure	NOUN
cana-3107	259	8	5	5	NUM
cana-3107	259	9	.	.	PUNCT
cana-3107	260	1	detecting	detect	VERB
cana-3107	260	2	insect	insect	NOUN
cana-3107	260	3	image	image	NOUN
cana-3107	260	4	with	with	ADP
cana-3107	260	5	moderate	moderate	ADJ
cana-3107	260	6	accuracyadam	accuracyadam	NOUN
cana-3107	260	7	optimizer	optimizer	NOUN
cana-3107	260	8	figure	figure	NOUN
cana-3107	260	9	6	6	NUM
cana-3107	260	10	.	.	PUNCT
cana-3107	260	11	detecting	detect	VERB
cana-3107	260	12	insect	insect	NOUN
cana-3107	260	13	image	image	NOUN
cana-3107	260	14	with	with	ADP
cana-3107	260	15	poor	poor	ADJ
cana-3107	260	16	accuracy	accuracy	NOUN
cana-3107	260	17	with	with	ADP
cana-3107	260	18	general	general	ADJ
cana-3107	260	19	frcnn	frcnn	NOUN
cana-3107	260	20	a	a	DET
cana-3107	260	21	total	total	NOUN
cana-3107	260	22	of	of	ADP
cana-3107	260	23	320	320	NUM
cana-3107	260	24	image	image	NOUN
cana-3107	260	25	frames	frame	NOUN
cana-3107	260	26	were	be	AUX
cana-3107	260	27	utilized	utilize	VERB
cana-3107	260	28	in	in	ADP
cana-3107	260	29	the	the	DET
cana-3107	260	30	training	training	NOUN
cana-3107	260	31	process	process	NOUN
cana-3107	260	32	,	,	PUNCT
cana-3107	260	33	with	with	ADP
cana-3107	260	34	a	a	DET
cana-3107	260	35	70	70	NUM
cana-3107	260	36	%	%	NOUN
cana-3107	260	37	train:30	train:30	NOUN
cana-3107	260	38	%	%	NOUN
cana-3107	260	39	test	test	NOUN
cana-3107	260	40	split	split	NOUN
cana-3107	260	41	.	.	PUNCT
cana-3107	261	1	to	to	PART
cana-3107	261	2	achieve	achieve	VERB
cana-3107	261	3	a	a	DET
cana-3107	261	4	95	95	NUM
cana-3107	261	5	%	%	NOUN
cana-3107	261	6	success	success	NOUN
cana-3107	261	7	rate	rate	NOUN
cana-3107	261	8	,	,	PUNCT
cana-3107	261	9	we	we	PRON
cana-3107	261	10	started	start	VERB
cana-3107	261	11	with	with	ADP
cana-3107	261	12	a	a	DET
cana-3107	261	13	learning	learn	VERB
cana-3107	261	14	rate	rate	NOUN
cana-3107	261	15	of	of	ADP
cana-3107	261	16	0.05	0.05	NUM
cana-3107	261	17	.	.	PUNCT
cana-3107	262	1	training	training	NOUN
cana-3107	262	2	continued	continue	VERB
cana-3107	262	3	until	until	SCONJ
cana-3107	262	4	the	the	DET
cana-3107	262	5	typical	typical	ADJ
cana-3107	262	6	drop	drop	NOUN
cana-3107	262	7	in	in	ADP
cana-3107	262	8	performance	performance	NOUN
cana-3107	262	9	was	be	AUX
cana-3107	262	10	almost	almost	ADV
cana-3107	262	11	continuous	continuous	ADJ
cana-3107	262	12	.	.	PUNCT
cana-3107	263	1	several	several	ADJ
cana-3107	263	2	loss	loss	NOUN
cana-3107	263	3	functions	function	NOUN
cana-3107	263	4	were	be	AUX
cana-3107	263	5	considered	consider	VERB
cana-3107	263	6	for	for	ADP
cana-3107	263	7	this	this	DET
cana-3107	263	8	analysis	analysis	NOUN
cana-3107	263	9	:	:	PUNCT
cana-3107	263	10	the	the	DET
cana-3107	263	11	rpn	rpn	PROPN
cana-3107	263	12	objectness	objectness	NOUN
cana-3107	263	13	localization	localization	NOUN
cana-3107	263	14	and	and	CCONJ
cana-3107	263	15	classification	classification	NOUN
cana-3107	263	16	loss	loss	NOUN
cana-3107	263	17	,	,	PUNCT
cana-3107	263	18	the	the	DET
cana-3107	263	19	rpn	rpn	PROPN
cana-3107	263	20	localization	localization	NOUN
cana-3107	263	21	loss	loss	NOUN
cana-3107	263	22	,	,	PUNCT
cana-3107	263	23	the	the	DET
cana-3107	263	24	total	total	ADJ
cana-3107	263	25	loss	loss	NOUN
cana-3107	263	26	,	,	PUNCT
cana-3107	263	27	and	and	CCONJ
cana-3107	263	28	the	the	DET
cana-3107	263	29	clone	clone	NOUN
cana-3107	263	30	loss	loss	NOUN
cana-3107	263	31	.	.	PUNCT
cana-3107	264	1	after	after	ADP
cana-3107	264	2	training	train	VERB
cana-3107	264	3	the	the	DET
cana-3107	264	4	model	model	NOUN
cana-3107	264	5	,	,	PUNCT
cana-3107	264	6	we	we	PRON
cana-3107	264	7	put	put	VERB
cana-3107	264	8	it	it	PRON
cana-3107	264	9	through	through	ADP
cana-3107	264	10	its	its	PRON
cana-3107	264	11	paces	pace	NOUN
cana-3107	264	12	on	on	ADP
cana-3107	264	13	a	a	DET
cana-3107	264	14	set	set	NOUN
cana-3107	264	15	of	of	ADP
cana-3107	264	16	80	80	NUM
cana-3107	264	17	test	test	NOUN
cana-3107	264	18	images	image	NOUN
cana-3107	264	19	.	.	PUNCT
cana-3107	265	1	each	each	DET
cana-3107	265	2	anticipated	anticipate	VERB
cana-3107	265	3	location	location	NOUN
cana-3107	265	4	was	be	AUX
cana-3107	265	5	given	give	VERB
cana-3107	265	6	a	a	DET
cana-3107	265	7	detection	detection	NOUN
cana-3107	265	8	score	score	NOUN
cana-3107	265	9	to	to	PART
cana-3107	265	10	indicate	indicate	VERB
cana-3107	265	11	how	how	SCONJ
cana-3107	265	12	confident	confident	ADJ
cana-3107	265	13	we	we	PRON
cana-3107	265	14	were	be	AUX
cana-3107	265	15	in	in	ADP
cana-3107	265	16	our	our	PRON
cana-3107	265	17	prediction	prediction	NOUN
cana-3107	265	18	[	[	X
cana-3107	265	19	22	22	NUM
cana-3107	265	20	]	]	PUNCT
cana-3107	265	21	.	.	PUNCT
cana-3107	266	1	4	4	X
cana-3107	266	2	.	.	X
cana-3107	266	3	results	result	VERB
cana-3107	266	4	the	the	DET
cana-3107	266	5	suggested	suggested	ADJ
cana-3107	266	6	approach	approach	NOUN
cana-3107	266	7	for	for	ADP
cana-3107	266	8	insect	insect	NOUN
cana-3107	266	9	detection	detection	NOUN
cana-3107	266	10	was	be	AUX
cana-3107	266	11	tested	test	VERB
cana-3107	266	12	using	use	VERB
cana-3107	266	13	56	56	NUM
cana-3107	266	14	images	image	NOUN
cana-3107	266	15	from	from	ADP
cana-3107	266	16	the	the	DET
cana-3107	266	17	study	study	NOUN
cana-3107	266	18	.	.	PUNCT
cana-3107	267	1	with	with	ADP
cana-3107	267	2	131	131	NUM
cana-3107	267	3	images	image	NOUN
cana-3107	267	4	used	use	VERB
cana-3107	267	5	for	for	ADP
cana-3107	267	6	training	training	NOUN
cana-3107	267	7	and	and	CCONJ
cana-3107	267	8	the	the	DET
cana-3107	267	9	corresponding	corresponding	ADJ
cana-3107	267	10	predictions	prediction	NOUN
cana-3107	267	11	for	for	ADP
cana-3107	267	12	the	the	DET
cana-3107	267	13	confusion	confusion	NOUN
cana-3107	267	14	matrix	matrix	NOUN
cana-3107	267	15	and	and	CCONJ
cana-3107	267	16	validation	validation	NOUN
cana-3107	267	17	parameters	parameter	NOUN
cana-3107	267	18	provided	provide	VERB
cana-3107	267	19	below	below	ADP
cana-3107	267	20	.	.	PUNCT
cana-3107	268	1	table	table	NOUN
cana-3107	268	2	i.	i.	PROPN
cana-3107	268	3	detected	detect	VERB
cana-3107	268	4	and	and	CCONJ
cana-3107	268	5	non	non	ADJ
cana-3107	268	6	detected	detect	VERB
cana-3107	268	7	image	image	NOUN
cana-3107	268	8	count	count	NOUN
cana-3107	268	9	insect	insect	NOUN
cana-3107	268	10	categories	category	NOUN
cana-3107	268	11	detected	detect	VERB
cana-3107	268	12	images	image	NOUN
cana-3107	268	13	non	non	NOUN
cana-3107	268	14	detected	detect	VERB
cana-3107	268	15	images	image	NOUN
cana-3107	268	16	frcnn+adam	frcnn+adam	PROPN
cana-3107	268	17	frcnn	frcnn	VERB
cana-3107	268	18	frcnn+adam	frcnn+adam	PROPN
cana-3107	268	19	frcnn	frcnn	ADJ
cana-3107	268	20	chilo	chilo	NOUN
cana-3107	268	21	suppressalis	suppressali	VERB
cana-3107	268	22	21	21	NUM
cana-3107	268	23	16	16	NUM
cana-3107	268	24	7	7	NUM
cana-3107	268	25	12	12	NUM
cana-3107	268	26	cicadellidae	cicadellidae	NOUN
cana-3107	268	27	17	17	NUM
cana-3107	268	28	12	12	NUM
cana-3107	268	29	8	8	NUM
cana-3107	268	30	13	13	NUM
cana-3107	268	31	coleoptera	coleoptera	NOUN
cana-3107	268	32	38	38	NUM
cana-3107	268	33	31	31	NUM
cana-3107	268	34	12	12	NUM
cana-3107	268	35	19	19	NUM
cana-3107	269	1	africanized	africanized	ADJ
cana-3107	269	2	honey	honey	NOUN
cana-3107	269	3	bees	bee	NOUN
cana-3107	269	4	(	(	PUNCT
cana-3107	269	5	killer	killer	NOUN
cana-3107	269	6	bees	bee	NOUN
cana-3107	269	7	)	)	PUNCT
cana-3107	269	8	35	35	NUM
cana-3107	269	9	28	28	NUM
cana-3107	269	10	13	13	NUM
cana-3107	269	11	20	20	NUM
cana-3107	269	12	armyworms	armyworm	NOUN
cana-3107	269	13	8	8	NUM
cana-3107	269	14	6	6	NUM
cana-3107	269	15	4	4	NUM
cana-3107	269	16	6	6	NUM
cana-3107	269	17	brown	brown	ADJ
cana-3107	269	18	marmorated	marmorated	NOUN
cana-3107	269	19	stink	stink	VERB
cana-3107	269	20	bugs	bug	NOUN
cana-3107	269	21	9	9	NUM
cana-3107	269	22	6	6	NUM
cana-3107	269	23	2	2	NUM
cana-3107	269	24	5	5	NUM
cana-3107	269	25	colorado	colorado	NOUN
cana-3107	269	26	potato	potato	NOUN
cana-3107	269	27	beetles	beetle	NOUN
cana-3107	269	28	7	7	NUM
cana-3107	269	29	5	5	NUM
cana-3107	269	30	5	5	NUM
cana-3107	269	31	8	8	NUM
cana-3107	269	32	communications	communication	NOUN
cana-3107	269	33	on	on	ADP
cana-3107	269	34	applied	apply	VERB
cana-3107	269	35	nonlinear	nonlinear	ADJ
cana-3107	269	36	analysis	analysis	NOUN
cana-3107	269	37	issn	issn	NOUN
cana-3107	269	38	:	:	PUNCT
cana-3107	269	39	1074	1074	NUM
cana-3107	269	40	-	-	PUNCT
cana-3107	269	41	133x	133x	NUM
cana-3107	269	42	vol	vol	NOUN
cana-3107	269	43	32	32	NUM
cana-3107	269	44	no	no	NOUN
cana-3107	269	45	.	.	PUNCT
cana-3107	270	1	5s	5s	NUM
cana-3107	270	2	(	(	PUNCT
cana-3107	270	3	2025	2025	NUM
cana-3107	270	4	)	)	PUNCT
cana-3107	270	5	372	372	NUM
cana-3107	270	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	270	7	figure7	figure7	NOUN
cana-3107	270	8	.	.	PUNCT
cana-3107	271	1	no	no	PRON
cana-3107	271	2	of	of	ADP
cana-3107	271	3	images	image	NOUN
cana-3107	271	4	detected	detect	VERB
cana-3107	271	5	by	by	ADP
cana-3107	271	6	frcnn	frcnn	NOUN
cana-3107	271	7	-	-	PUNCT
cana-3107	271	8	adam	adam	PROPN
cana-3107	271	9	and	and	CCONJ
cana-3107	271	10	frcnn	frcnn	NOUN
cana-3107	271	11	figure7	figure7	PROPN
cana-3107	271	12	.	.	PUNCT
cana-3107	272	1	no	no	PRON
cana-3107	272	2	of	of	ADP
cana-3107	272	3	images	image	NOUN
cana-3107	272	4	non	non	ADJ
cana-3107	272	5	-	-	ADJ
cana-3107	272	6	detected	detect	VERB
cana-3107	272	7	by	by	ADP
cana-3107	272	8	frcnn	frcnn	NOUN
cana-3107	272	9	-	-	PUNCT
cana-3107	272	10	adam	adam	PROPN
cana-3107	272	11	and	and	CCONJ
cana-3107	272	12	frcnn	frcnn	ADJ
cana-3107	272	13	figure	figure	VERB
cana-3107	272	14	7	7	NUM
cana-3107	272	15	and	and	CCONJ
cana-3107	272	16	table	table	NOUN
cana-3107	272	17	i	i	PRON
cana-3107	272	18	show	show	VERB
cana-3107	272	19	the	the	DET
cana-3107	272	20	number	number	NOUN
cana-3107	272	21	of	of	ADP
cana-3107	272	22	correct	correct	ADJ
cana-3107	272	23	and	and	CCONJ
cana-3107	272	24	incorrect	incorrect	ADJ
cana-3107	272	25	insect	insect	NOUN
cana-3107	272	26	detections	detection	NOUN
cana-3107	272	27	made	make	VERB
cana-3107	272	28	by	by	ADP
cana-3107	272	29	the	the	DET
cana-3107	272	30	proposed	propose	VERB
cana-3107	272	31	frcnn	frcnn	NOUN
cana-3107	272	32	after	after	ADP
cana-3107	272	33	being	be	AUX
cana-3107	272	34	optimized	optimize	VERB
cana-3107	272	35	with	with	ADP
cana-3107	272	36	the	the	DET
cana-3107	272	37	adam	adam	PROPN
cana-3107	272	38	optimizer	optimizer	NOUN
cana-3107	272	39	and	and	CCONJ
cana-3107	272	40	having	have	VERB
cana-3107	272	41	its	its	PRON
cana-3107	272	42	features	feature	NOUN
cana-3107	272	43	extracted	extract	VERB
cana-3107	272	44	using	use	VERB
cana-3107	272	45	the	the	DET
cana-3107	272	46	inception	inception	ADJ
cana-3107	272	47	v3	v3	PROPN
cana-3107	272	48	method	method	NOUN
cana-3107	272	49	.	.	PUNCT
cana-3107	273	1	this	this	DET
cana-3107	273	2	model	model	NOUN
cana-3107	273	3	is	be	AUX
cana-3107	273	4	then	then	ADV
cana-3107	273	5	compared	compare	VERB
cana-3107	273	6	to	to	ADP
cana-3107	273	7	the	the	DET
cana-3107	273	8	standard	standard	ADJ
cana-3107	273	9	frcnn	frcnn	NOUN
cana-3107	273	10	,	,	PUNCT
cana-3107	273	11	and	and	CCONJ
cana-3107	273	12	the	the	DET
cana-3107	273	13	results	result	NOUN
cana-3107	273	14	show	show	VERB
cana-3107	273	15	that	that	SCONJ
cana-3107	273	16	the	the	DET
cana-3107	273	17	improved	improved	ADJ
cana-3107	273	18	model	model	NOUN
cana-3107	273	19	is	be	AUX
cana-3107	273	20	more	more	ADV
cana-3107	273	21	accurate	accurate	ADJ
cana-3107	273	22	at	at	ADP
cana-3107	273	23	making	make	VERB
cana-3107	273	24	insect	insect	NOUN
cana-3107	273	25	detections	detection	NOUN
cana-3107	273	26	.	.	PUNCT
cana-3107	274	1	with	with	ADP
cana-3107	274	2	a	a	DET
cana-3107	274	3	lesser	less	ADJ
cana-3107	274	4	ability	ability	NOUN
cana-3107	274	5	to	to	PART
cana-3107	274	6	avoid	avoid	VERB
cana-3107	274	7	detection	detection	NOUN
cana-3107	274	8	.	.	PUNCT
cana-3107	275	1	table	table	PROPN
cana-3107	275	2	ii	ii	PROPN
cana-3107	275	3	.	.	PUNCT
cana-3107	275	4	accuracy	accuracy	NOUN
cana-3107	275	5	and	and	CCONJ
cana-3107	275	6	error	error	NOUN
cana-3107	275	7	of	of	ADP
cana-3107	275	8	detection	detection	NOUN
cana-3107	275	9	insect	insect	NOUN
cana-3107	275	10	categories	category	NOUN
cana-3107	275	11	accuracy	accuracy	NOUN
cana-3107	275	12	of	of	ADP
cana-3107	275	13	detection	detection	NOUN
cana-3107	275	14	error	error	NOUN
cana-3107	275	15	detection	detection	NOUN
cana-3107	275	16	frcnn+	frcnn+	ADP
cana-3107	275	17	adam	adam	PROPN
cana-3107	275	18	frcnn	frcnn	VERB
cana-3107	275	19	frcnn+adam	frcnn+adam	PROPN
cana-3107	275	20	frcnn	frcnn	VERB
cana-3107	275	21	chilo	chilo	NOUN
cana-3107	275	22	suppressalis	suppressali	VERB
cana-3107	275	23	0.75	0.75	NUM
cana-3107	275	24	0.57	0.57	NUM
cana-3107	275	25	0.28	0.28	NUM
cana-3107	275	26	0.42	0.42	NUM
cana-3107	275	27	cicadellidae	cicadellidae	NOUN
cana-3107	275	28	0.68	0.68	NUM
cana-3107	275	29	0.48	0.48	NUM
cana-3107	275	30	0.32	0.32	NUM
cana-3107	275	31	0.52	0.52	NUM
cana-3107	275	32	coleoptera	coleoptera	NOUN
cana-3107	275	33	0.76	0.76	NUM
cana-3107	275	34	0.62	0.62	NUM
cana-3107	275	35	0.24	0.24	NUM
cana-3107	275	36	0.38	0.38	NUM
cana-3107	275	37	africanized	africanized	ADJ
cana-3107	275	38	honey	honey	NOUN
cana-3107	275	39	bees	bee	NOUN
cana-3107	275	40	(	(	PUNCT
cana-3107	275	41	killer	killer	NOUN
cana-3107	275	42	bees	bee	NOUN
cana-3107	275	43	)	)	PUNCT
cana-3107	275	44	0.72	0.72	NUM
cana-3107	275	45	0.58	0.58	NUM
cana-3107	275	46	0.27	0.27	NUM
cana-3107	275	47	0.42	0.42	NUM
cana-3107	275	48	armyworms	armyworm	NOUN
cana-3107	275	49	0.66	0.66	NUM
cana-3107	275	50	0.5	0.5	NUM
cana-3107	275	51	0.33	0.33	NUM
cana-3107	275	52	0.5	0.5	NUM
cana-3107	275	53	brown	brown	ADJ
cana-3107	275	54	marmorated	marmorated	NOUN
cana-3107	275	55	stink	stink	VERB
cana-3107	275	56	bugs	bug	NOUN
cana-3107	275	57	0.81	0.81	NUM
cana-3107	275	58	0.54	0.54	NUM
cana-3107	275	59	0.18	0.18	NUM
cana-3107	275	60	0.45	0.45	NUM
cana-3107	275	61	colorado	colorado	NOUN
cana-3107	275	62	potato	potato	NOUN
cana-3107	275	63	beetles	beetle	NOUN
cana-3107	275	64	0.54	0.54	NUM
cana-3107	275	65	0.38	0.38	NUM
cana-3107	275	66	0.38	0.38	NUM
cana-3107	275	67	0.62	0.62	NUM
cana-3107	275	68	communications	communication	NOUN
cana-3107	275	69	on	on	ADP
cana-3107	275	70	applied	apply	VERB
cana-3107	275	71	nonlinear	nonlinear	ADJ
cana-3107	275	72	analysis	analysis	NOUN
cana-3107	275	73	issn	issn	NOUN
cana-3107	275	74	:	:	PUNCT
cana-3107	275	75	1074	1074	NUM
cana-3107	275	76	-	-	PUNCT
cana-3107	275	77	133x	133x	NUM
cana-3107	275	78	vol	vol	NOUN
cana-3107	275	79	32	32	NUM
cana-3107	275	80	no	no	NOUN
cana-3107	275	81	.	.	PUNCT
cana-3107	276	1	5s	5s	NUM
cana-3107	276	2	(	(	PUNCT
cana-3107	276	3	2025	2025	NUM
cana-3107	276	4	)	)	PUNCT
cana-3107	276	5	373	373	NUM
cana-3107	276	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	276	7	table	table	NOUN
cana-3107	276	8	iii	iii	PROPN
cana-3107	276	9	.	.	PUNCT
cana-3107	276	10	area	area	PROPN
cana-3107	276	11	comparison	comparison	NOUN
cana-3107	276	12	of	of	ADP
cana-3107	276	13	detected	detect	VERB
cana-3107	276	14	data	datum	NOUN
cana-3107	276	15	insect	insect	NOUN
cana-3107	276	16	categories	category	NOUN
cana-3107	276	17	sample	sample	NOUN
cana-3107	276	18	size	size	NOUN
cana-3107	276	19	target	target	NOUN
cana-3107	276	20	size	size	NOUN
cana-3107	276	21	frcnn+adam	frcnn+adam	PROPN
cana-3107	276	22	frcnn	frcnn	VERB
cana-3107	276	23	chilo	chilo	NOUN
cana-3107	276	24	suppressalis	suppressali	VERB
cana-3107	276	25	805	805	NUM
cana-3107	276	26	1246	1246	NUM
cana-3107	276	27	1533	1533	NUM
cana-3107	276	28	cicadellidae	cicadellidae	VERB
cana-3107	276	29	621	621	NUM
cana-3107	276	30	1526	1526	NUM
cana-3107	276	31	1825	1825	NUM
cana-3107	277	1	coleoptera	coleoptera	NOUN
cana-3107	277	2	1253	1253	NUM
cana-3107	277	3	2056	2056	NUM
cana-3107	277	4	2630	2630	NUM
cana-3107	277	5	africanized	africanized	ADJ
cana-3107	277	6	honey	honey	NOUN
cana-3107	277	7	bees	bee	NOUN
cana-3107	277	8	(	(	PUNCT
cana-3107	277	9	killer	killer	NOUN
cana-3107	277	10	bees	bee	NOUN
cana-3107	277	11	)	)	PUNCT
cana-3107	277	12	945	945	NUM
cana-3107	277	13	1463	1463	NUM
cana-3107	277	14	1924	1924	NUM
cana-3107	277	15	armyworms	armyworm	NOUN
cana-3107	277	16	1543	1543	NUM
cana-3107	277	17	2543	2543	NUM
cana-3107	277	18	2854	2854	NUM
cana-3107	277	19	brown	brown	ADJ
cana-3107	277	20	marmorated	marmorated	NOUN
cana-3107	277	21	stink	stink	VERB
cana-3107	277	22	bugs	bug	NOUN
cana-3107	277	23	1026	1026	NUM
cana-3107	277	24	1254	1254	NUM
cana-3107	277	25	1869	1869	NUM
cana-3107	277	26	colorado	colorado	NOUN
cana-3107	277	27	potato	potato	NOUN
cana-3107	277	28	beetles	beetle	NOUN
cana-3107	277	29	756	756	NUM
cana-3107	277	30	906	906	NUM
cana-3107	277	31	1325	1325	NUM
cana-3107	277	32	figure8	figure8	NOUN
cana-3107	277	33	.	.	PUNCT
cana-3107	278	1	sample	sample	NOUN
cana-3107	278	2	space	space	NOUN
cana-3107	278	3	and	and	CCONJ
cana-3107	278	4	target	target	NOUN
cana-3107	278	5	space	space	NOUN
cana-3107	278	6	comparison	comparison	NOUN
cana-3107	278	7	of	of	ADP
cana-3107	278	8	proposed	propose	VERB
cana-3107	278	9	and	and	CCONJ
cana-3107	278	10	existing	exist	VERB
cana-3107	278	11	model	model	NOUN
cana-3107	278	12	figure	figure	NOUN
cana-3107	278	13	8	8	NUM
cana-3107	278	14	and	and	CCONJ
cana-3107	278	15	table	table	NOUN
cana-3107	278	16	iii	iii	NOUN
cana-3107	278	17	above	above	ADV
cana-3107	278	18	show	show	VERB
cana-3107	278	19	the	the	DET
cana-3107	278	20	expected	expect	VERB
cana-3107	278	21	target	target	NOUN
cana-3107	278	22	picture	picture	NOUN
cana-3107	278	23	and	and	CCONJ
cana-3107	278	24	the	the	DET
cana-3107	278	25	example	example	NOUN
cana-3107	278	26	image	image	NOUN
cana-3107	278	27	with	with	ADP
cana-3107	278	28	insect	insect	NOUN
cana-3107	278	29	labels	label	NOUN
cana-3107	278	30	.	.	PUNCT
cana-3107	279	1	the	the	DET
cana-3107	279	2	number	number	NOUN
cana-3107	279	3	of	of	ADP
cana-3107	279	4	pixels	pixel	NOUN
cana-3107	279	5	is	be	AUX
cana-3107	279	6	shown	show	VERB
cana-3107	279	7	inside	inside	ADP
cana-3107	279	8	the	the	DET
cana-3107	279	9	border	border	NOUN
cana-3107	279	10	marker	marker	NOUN
cana-3107	279	11	's	's	PART
cana-3107	279	12	bounds	bound	NOUN
cana-3107	279	13	,	,	PUNCT
cana-3107	279	14	which	which	PRON
cana-3107	279	15	represents	represent	VERB
cana-3107	279	16	the	the	DET
cana-3107	279	17	region	region	NOUN
cana-3107	279	18	where	where	SCONJ
cana-3107	279	19	the	the	DET
cana-3107	279	20	bug	bug	NOUN
cana-3107	279	21	was	be	AUX
cana-3107	279	22	found	find	VERB
cana-3107	279	23	.	.	PUNCT
cana-3107	280	1	additionally	additionally	ADV
cana-3107	280	2	,	,	PUNCT
cana-3107	280	3	the	the	DET
cana-3107	280	4	labeling	labeling	NOUN
cana-3107	280	5	feature	feature	NOUN
cana-3107	280	6	in	in	ADP
cana-3107	280	7	the	the	DET
cana-3107	280	8	toolbox	toolbox	NOUN
cana-3107	280	9	allows	allow	VERB
cana-3107	280	10	for	for	ADP
cana-3107	280	11	sample	sample	NOUN
cana-3107	280	12	marking	marking	NOUN
cana-3107	280	13	,	,	PUNCT
cana-3107	280	14	and	and	CCONJ
cana-3107	280	15	the	the	DET
cana-3107	280	16	chart	chart	NOUN
cana-3107	280	17	demonstrates	demonstrate	VERB
cana-3107	280	18	that	that	SCONJ
cana-3107	280	19	the	the	DET
cana-3107	280	20	suggested	suggest	VERB
cana-3107	280	21	model	model	NOUN
cana-3107	280	22	has	have	AUX
cana-3107	280	23	spotted	spot	VERB
cana-3107	280	24	areas	area	NOUN
cana-3107	280	25	closer	close	ADV
cana-3107	280	26	to	to	ADP
cana-3107	280	27	the	the	DET
cana-3107	280	28	sample	sample	NOUN
cana-3107	280	29	.	.	PUNCT
cana-3107	281	1	5	5	X
cana-3107	281	2	.	.	X
cana-3107	281	3	conclusion	conclusion	NOUN
cana-3107	281	4	interest	interest	NOUN
cana-3107	281	5	in	in	ADP
cana-3107	281	6	automated	automate	VERB
cana-3107	281	7	insect	insect	NOUN
cana-3107	281	8	identification	identification	NOUN
cana-3107	281	9	is	be	AUX
cana-3107	281	10	growing	grow	VERB
cana-3107	281	11	in	in	ADP
cana-3107	281	12	many	many	ADJ
cana-3107	281	13	areas	area	NOUN
cana-3107	281	14	of	of	ADP
cana-3107	281	15	study	study	NOUN
cana-3107	281	16	,	,	PUNCT
cana-3107	281	17	including	include	VERB
cana-3107	281	18	entomological	entomological	ADJ
cana-3107	281	19	science	science	NOUN
cana-3107	281	20	,	,	PUNCT
cana-3107	281	21	environmental	environmental	ADJ
cana-3107	281	22	science	science	NOUN
cana-3107	281	23	,	,	PUNCT
cana-3107	281	24	and	and	CCONJ
cana-3107	281	25	agricultural	agricultural	ADJ
cana-3107	281	26	engineering	engineering	NOUN
cana-3107	281	27	.	.	PUNCT
cana-3107	282	1	a	a	DET
cana-3107	282	2	number	number	NOUN
cana-3107	282	3	of	of	ADP
cana-3107	282	4	contributors	contributor	NOUN
cana-3107	282	5	discussed	discuss	VERB
cana-3107	282	6	the	the	DET
cana-3107	282	7	many	many	ADJ
cana-3107	282	8	influences	influence	NOUN
cana-3107	282	9	on	on	ADP
cana-3107	282	10	automated	automate	VERB
cana-3107	282	11	insect	insect	NOUN
cana-3107	282	12	identification	identification	NOUN
cana-3107	282	13	studies	study	NOUN
cana-3107	282	14	.	.	PUNCT
cana-3107	283	1	low	low	ADJ
cana-3107	283	2	detection	detection	NOUN
cana-3107	283	3	accuracy	accuracy	NOUN
cana-3107	283	4	and	and	CCONJ
cana-3107	283	5	high	high	ADJ
cana-3107	283	6	processing	processing	NOUN
cana-3107	283	7	time	time	NOUN
cana-3107	283	8	are	be	AUX
cana-3107	283	9	addressed	address	VERB
cana-3107	283	10	by	by	ADP
cana-3107	283	11	using	use	VERB
cana-3107	283	12	the	the	DET
cana-3107	283	13	faster	fast	ADJ
cana-3107	283	14	-	-	PUNCT
cana-3107	283	15	rcnn	rcnn	NOUN
cana-3107	283	16	model	model	NOUN
cana-3107	283	17	for	for	ADP
cana-3107	283	18	insect	insect	NOUN
cana-3107	283	19	target	target	NOUN
cana-3107	283	20	identification	identification	NOUN
cana-3107	283	21	.	.	PUNCT
cana-3107	284	1	in	in	ADP
cana-3107	284	2	this	this	DET
cana-3107	284	3	study	study	NOUN
cana-3107	284	4	,	,	PUNCT
cana-3107	284	5	we	we	PRON
cana-3107	284	6	provide	provide	VERB
cana-3107	284	7	a	a	DET
cana-3107	284	8	novel	novel	ADJ
cana-3107	284	9	method	method	NOUN
cana-3107	284	10	for	for	ADP
cana-3107	284	11	identifying	identify	VERB
cana-3107	284	12	insects	insect	NOUN
cana-3107	284	13	using	use	VERB
cana-3107	284	14	picture	picture	NOUN
cana-3107	284	15	segmentation	segmentation	NOUN
cana-3107	284	16	.	.	PUNCT
cana-3107	285	1	insect	insect	NOUN
cana-3107	285	2	images	image	NOUN
cana-3107	285	3	were	be	AUX
cana-3107	285	4	segmented	segment	VERB
cana-3107	285	5	using	use	VERB
cana-3107	285	6	faster	fast	ADJ
cana-3107	285	7	rcnn	rcnn	NOUN
cana-3107	285	8	using	use	VERB
cana-3107	285	9	the	the	DET
cana-3107	285	10	adam	adam	PROPN
cana-3107	285	11	optimizer	optimizer	NOUN
cana-3107	285	12	,	,	PUNCT
cana-3107	285	13	and	and	CCONJ
cana-3107	285	14	features	feature	NOUN
cana-3107	285	15	were	be	AUX
cana-3107	285	16	extracted	extract	VERB
cana-3107	285	17	using	use	VERB
cana-3107	285	18	inceptionv3	inceptionv3	NOUN
cana-3107	285	19	.	.	PUNCT
cana-3107	286	1	according	accord	VERB
cana-3107	286	2	to	to	ADP
cana-3107	286	3	the	the	DET
cana-3107	286	4	findings	finding	NOUN
cana-3107	286	5	,	,	PUNCT
cana-3107	286	6	our	our	PRON
cana-3107	286	7	suggested	suggest	VERB
cana-3107	286	8	model	model	NOUN
cana-3107	286	9	outperformed	outperform	VERB
cana-3107	286	10	the	the	DET
cana-3107	286	11	state	state	NOUN
cana-3107	286	12	-	-	PUNCT
cana-3107	286	13	of	of	ADP
cana-3107	286	14	-	-	PUNCT
cana-3107	286	15	the	the	DET
cana-3107	286	16	-	-	PUNCT
cana-3107	286	17	art	art	NOUN
cana-3107	286	18	method	method	NOUN
cana-3107	286	19	.	.	PUNCT
cana-3107	287	1	effective	effective	ADJ
cana-3107	287	2	deep	deep	ADJ
cana-3107	287	3	learning	learning	NOUN
cana-3107	287	4	methods	method	NOUN
cana-3107	287	5	may	may	AUX
cana-3107	287	6	be	be	AUX
cana-3107	287	7	used	use	VERB
cana-3107	287	8	to	to	PART
cana-3107	287	9	construct	construct	VERB
cana-3107	287	10	a	a	DET
cana-3107	287	11	future	future	ADJ
cana-3107	287	12	-	-	PUNCT
cana-3107	287	13	proof	proof	ADJ
cana-3107	287	14	categorization	categorization	NOUN
cana-3107	287	15	system	system	NOUN
cana-3107	287	16	and	and	CCONJ
cana-3107	287	17	expand	expand	VERB
cana-3107	287	18	the	the	DET
cana-3107	287	19	available	available	ADJ
cana-3107	287	20	dataset	dataset	NOUN
cana-3107	287	21	.	.	PUNCT
cana-3107	288	1	communications	communication	NOUN
cana-3107	288	2	on	on	ADP
cana-3107	288	3	applied	apply	VERB
cana-3107	288	4	nonlinear	nonlinear	ADJ
cana-3107	288	5	analysis	analysis	NOUN
cana-3107	288	6	issn	issn	NOUN
cana-3107	288	7	:	:	PUNCT
cana-3107	288	8	1074	1074	NUM
cana-3107	288	9	-	-	PUNCT
cana-3107	288	10	133x	133x	NUM
cana-3107	288	11	vol	vol	NOUN
cana-3107	288	12	32	32	NUM
cana-3107	288	13	no	no	NOUN
cana-3107	288	14	.	.	PUNCT
cana-3107	289	1	5s	5s	NUM
cana-3107	289	2	(	(	PUNCT
cana-3107	289	3	2025	2025	NUM
cana-3107	289	4	)	)	PUNCT
cana-3107	289	5	374	374	NUM
cana-3107	289	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3107	289	7	refrences	refrence	NOUN
cana-3107	290	1	[	[	X
cana-3107	290	2	1	1	NUM
cana-3107	290	3	]	]	SYM
cana-3107	290	4	wu	wu	PROPN
cana-3107	290	5	,	,	PUNCT
cana-3107	290	6	f.	f.	PROPN
cana-3107	290	7	,	,	PUNCT
cana-3107	290	8	&	&	CCONJ
cana-3107	290	9	li	li	PROPN
cana-3107	290	10	,	,	PUNCT
cana-3107	290	11	y.	y.	PROPN
cana-3107	290	12	(	(	PUNCT
cana-3107	290	13	2023	2023	NUM
cana-3107	290	14	)	)	PUNCT
cana-3107	290	15	.	.	PUNCT
cana-3107	291	1	lightweight	lightweight	ADJ
cana-3107	291	2	field	field	NOUN
cana-3107	291	3	insect	insect	NOUN
cana-3107	291	4	recognition	recognition	NOUN
cana-3107	291	5	and	and	CCONJ
cana-3107	291	6	classification	classification	NOUN
cana-3107	291	7	model	model	NOUN
cana-3107	291	8	based	base	VERB
cana-3107	291	9	on	on	ADP
cana-3107	291	10	improved	improved	ADJ
cana-3107	291	11	deep	deep	ADJ
cana-3107	291	12	learning	learning	NOUN
cana-3107	291	13	under	under	ADP
cana-3107	291	14	complex	complex	ADJ
cana-3107	291	15	background	background	NOUN
cana-3107	291	16	.	.	PUNCT
cana-3107	292	1	security	security	NOUN
cana-3107	292	2	and	and	CCONJ
cana-3107	292	3	communication	communication	NOUN
cana-3107	292	4	networks	network	NOUN
cana-3107	292	5	,	,	PUNCT
cana-3107	292	6	2023	2023	NUM
cana-3107	292	7	.	.	PUNCT
cana-3107	293	1	[	[	X
cana-3107	293	2	2	2	NUM
cana-3107	293	3	]	]	SYM
cana-3107	293	4	rong	rong	PROPN
cana-3107	293	5	,	,	PUNCT
cana-3107	293	6	m.	m.	NOUN
cana-3107	293	7	,	,	PUNCT
cana-3107	293	8	wang	wang	PROPN
cana-3107	293	9	,	,	PUNCT
cana-3107	293	10	z.	z.	PROPN
cana-3107	293	11	,	,	PUNCT
cana-3107	293	12	ban	ban	PROPN
cana-3107	293	13	,	,	PUNCT
cana-3107	293	14	b.	b.	PROPN
cana-3107	293	15	,	,	PUNCT
cana-3107	293	16	&	&	CCONJ
cana-3107	293	17	guo	guo	PROPN
cana-3107	293	18	,	,	PUNCT
cana-3107	293	19	x.	x.	NOUN
cana-3107	293	20	(	(	PUNCT
cana-3107	293	21	2022	2022	NUM
cana-3107	293	22	)	)	PUNCT
cana-3107	293	23	.	.	PUNCT
cana-3107	294	1	pest	pest	VERB
cana-3107	294	2	identification	identification	NOUN
cana-3107	294	3	and	and	CCONJ
cana-3107	294	4	counting	counting	NOUN
cana-3107	294	5	of	of	ADP
cana-3107	294	6	yellow	yellow	ADJ
cana-3107	294	7	plate	plate	NOUN
cana-3107	294	8	in	in	ADP
cana-3107	294	9	field	field	NOUN
cana-3107	294	10	based	base	VERB
cana-3107	294	11	on	on	ADP
cana-3107	294	12	improved	improved	ADJ
cana-3107	294	13	mask	mask	NOUN
cana-3107	294	14	r	r	NOUN
cana-3107	294	15	-	-	PUNCT
cana-3107	294	16	cnn	cnn	PROPN
cana-3107	294	17	.	.	PUNCT
cana-3107	295	1	discrete	discrete	ADJ
cana-3107	295	2	dynamics	dynamic	NOUN
cana-3107	295	3	in	in	ADP
cana-3107	295	4	nature	nature	NOUN
cana-3107	295	5	and	and	CCONJ
cana-3107	295	6	society	society	NOUN
cana-3107	295	7	,	,	PUNCT
cana-3107	295	8	2022	2022	NUM
cana-3107	295	9	,	,	PUNCT
cana-3107	295	10	1	1	NUM
cana-3107	295	11	-	-	SYM
cana-3107	295	12	9	9	NUM
cana-3107	295	13	.	.	PUNCT
cana-3107	296	1	[	[	X
cana-3107	296	2	3	3	NUM
cana-3107	296	3	]	]	X
cana-3107	296	4	wang	wang	PROPN
cana-3107	296	5	,	,	PUNCT
cana-3107	296	6	j.	j.	PROPN
cana-3107	296	7	,	,	PUNCT
cana-3107	296	8	lin	lin	PROPN
cana-3107	296	9	,	,	PUNCT
cana-3107	296	10	c.	c.	PROPN
cana-3107	296	11	,	,	PUNCT
cana-3107	296	12	ji	ji	PROPN
cana-3107	296	13	,	,	PUNCT
cana-3107	296	14	l.	l.	PROPN
cana-3107	296	15	,	,	PUNCT
cana-3107	296	16	&	&	CCONJ
cana-3107	296	17	liang	liang	PROPN
cana-3107	296	18	,	,	PUNCT
cana-3107	296	19	a.	a.	PROPN
cana-3107	296	20	(	(	PUNCT
cana-3107	296	21	2012	2012	NUM
cana-3107	296	22	)	)	PUNCT
cana-3107	296	23	.	.	PUNCT
cana-3107	297	1	a	a	DET
cana-3107	297	2	new	new	ADJ
cana-3107	297	3	automatic	automatic	ADJ
cana-3107	297	4	identification	identification	NOUN
cana-3107	297	5	system	system	NOUN
cana-3107	297	6	of	of	ADP
cana-3107	297	7	insect	insect	NOUN
cana-3107	297	8	images	image	NOUN
cana-3107	297	9	at	at	ADP
cana-3107	297	10	the	the	DET
cana-3107	297	11	order	order	NOUN
cana-3107	297	12	level	level	NOUN
cana-3107	297	13	.	.	PUNCT
cana-3107	298	1	knowledge	knowledge	NOUN
cana-3107	298	2	-	-	PUNCT
cana-3107	298	3	based	base	VERB
cana-3107	298	4	systems	system	NOUN
cana-3107	298	5	,	,	PUNCT
cana-3107	298	6	33	33	NUM
cana-3107	298	7	,	,	PUNCT
cana-3107	298	8	102	102	NUM
cana-3107	298	9	-	-	SYM
cana-3107	298	10	110	110	NUM
cana-3107	298	11	.	.	PUNCT
cana-3107	299	1	[	[	X
cana-3107	299	2	4	4	NUM
cana-3107	299	3	]	]	SYM
cana-3107	299	4	du	du	X
cana-3107	299	5	,	,	PUNCT
cana-3107	299	6	y.	y.	PROPN
cana-3107	299	7	,	,	PUNCT
cana-3107	299	8	liu	liu	PROPN
cana-3107	299	9	,	,	PUNCT
cana-3107	299	10	y.	y.	PROPN
cana-3107	299	11	,	,	PUNCT
cana-3107	299	12	&	&	CCONJ
cana-3107	299	13	li	li	PROPN
cana-3107	299	14	,	,	PUNCT
cana-3107	299	15	n.	n.	PROPN
cana-3107	299	16	(	(	PUNCT
cana-3107	299	17	2020	2020	NUM
cana-3107	299	18	,	,	PUNCT
cana-3107	299	19	april	april	PROPN
cana-3107	299	20	)	)	PUNCT
cana-3107	299	21	.	.	PUNCT
cana-3107	300	1	insect	insect	NOUN
cana-3107	300	2	detection	detection	NOUN
cana-3107	300	3	research	research	NOUN
cana-3107	300	4	in	in	ADP
cana-3107	300	5	natural	natural	ADJ
cana-3107	300	6	environment	environment	NOUN
cana-3107	300	7	based	base	VERB
cana-3107	300	8	on	on	ADP
cana-3107	300	9	faster	fast	ADJ
cana-3107	300	10	-	-	PUNCT
cana-3107	300	11	r	r	NOUN
cana-3107	300	12	-	-	PUNCT
cana-3107	300	13	cnn	cnn	PROPN
cana-3107	300	14	model	model	NOUN
cana-3107	300	15	.	.	PUNCT
cana-3107	301	1	in	in	ADP
cana-3107	301	2	proceedings	proceeding	NOUN
cana-3107	301	3	of	of	ADP
cana-3107	301	4	the	the	DET
cana-3107	301	5	2020	2020	NUM
cana-3107	301	6	5th	5th	ADJ
cana-3107	301	7	international	international	ADJ
cana-3107	301	8	conference	conference	NOUN
cana-3107	301	9	on	on	ADP
cana-3107	301	10	mathematics	mathematic	NOUN
cana-3107	301	11	and	and	CCONJ
cana-3107	301	12	artificial	artificial	ADJ
cana-3107	301	13	intelligence	intelligence	NOUN
cana-3107	301	14	(	(	PUNCT
cana-3107	301	15	pp	pp	ADJ
cana-3107	301	16	.	.	PUNCT
cana-3107	302	1	182	182	NUM
cana-3107	302	2	-	-	SYM
cana-3107	302	3	186	186	NUM
cana-3107	302	4	)	)	PUNCT
cana-3107	302	5	.	.	PUNCT
cana-3107	303	1	[	[	X
cana-3107	303	2	5	5	NUM
cana-3107	303	3	]	]	X
cana-3107	303	4	zhu	zhu	PROPN
cana-3107	303	5	,	,	PUNCT
cana-3107	303	6	c.	c.	PROPN
cana-3107	303	7	,	,	PUNCT
cana-3107	303	8	wang	wang	PROPN
cana-3107	303	9	,	,	PUNCT
cana-3107	303	10	j.	j.	PROPN
cana-3107	303	11	,	,	PUNCT
cana-3107	303	12	liu	liu	PROPN
cana-3107	303	13	,	,	PUNCT
cana-3107	303	14	h.	h.	PROPN
cana-3107	303	15	,	,	PUNCT
cana-3107	303	16	&	&	CCONJ
cana-3107	303	17	mi	mi	PROPN
cana-3107	303	18	,	,	PUNCT
cana-3107	303	19	h.	h.	PROPN
cana-3107	303	20	(	(	PUNCT
cana-3107	303	21	2018	2018	NUM
cana-3107	303	22	)	)	PUNCT
cana-3107	303	23	.	.	PUNCT
cana-3107	304	1	insect	insect	NOUN
cana-3107	304	2	identification	identification	NOUN
cana-3107	304	3	and	and	CCONJ
cana-3107	304	4	counting	counting	NOUN
cana-3107	304	5	in	in	ADP
cana-3107	304	6	stored	store	VERB
cana-3107	304	7	grain	grain	NOUN
cana-3107	304	8	:	:	PUNCT
cana-3107	304	9	image	image	NOUN
cana-3107	304	10	processing	processing	NOUN
cana-3107	304	11	approach	approach	NOUN
cana-3107	304	12	and	and	CCONJ
cana-3107	304	13	application	application	NOUN
cana-3107	304	14	embedded	embed	VERB
cana-3107	304	15	in	in	ADP
cana-3107	304	16	smartphones	smartphone	NOUN
cana-3107	304	17	.	.	PUNCT
cana-3107	305	1	mobile	mobile	ADJ
cana-3107	305	2	information	information	NOUN
cana-3107	305	3	systems	system	NOUN
cana-3107	305	4	,	,	PUNCT
cana-3107	305	5	2018	2018	NUM
cana-3107	305	6	,	,	PUNCT
cana-3107	305	7	1	1	NUM
cana-3107	305	8	-	-	SYM
cana-3107	305	9	5	5	NUM
cana-3107	305	10	.	.	PUNCT
cana-3107	306	1	[	[	X
cana-3107	306	2	6	6	NUM
cana-3107	306	3	]	]	SYM
cana-3107	306	4	yang	yang	PROPN
cana-3107	306	5	,	,	PUNCT
cana-3107	306	6	h.	h.	PROPN
cana-3107	306	7	,	,	PUNCT
cana-3107	306	8	liu	liu	PROPN
cana-3107	306	9	,	,	PUNCT
cana-3107	306	10	w.	w.	PROPN
cana-3107	306	11	,	,	PUNCT
cana-3107	306	12	xing	xing	PROPN
cana-3107	306	13	,	,	PUNCT
cana-3107	306	14	k.	k.	PROPN
cana-3107	306	15	,	,	PUNCT
cana-3107	306	16	qiao	qiao	PROPN
cana-3107	306	17	,	,	PUNCT
cana-3107	306	18	j.	j.	PROPN
cana-3107	306	19	,	,	PUNCT
cana-3107	306	20	wang	wang	PROPN
cana-3107	306	21	,	,	PUNCT
cana-3107	306	22	x.	x.	PROPN
cana-3107	306	23	,	,	PUNCT
cana-3107	306	24	gao	gao	PROPN
cana-3107	306	25	,	,	PUNCT
cana-3107	306	26	l.	l.	PROPN
cana-3107	306	27	,	,	PUNCT
cana-3107	306	28	&	&	CCONJ
cana-3107	306	29	shen	shen	PROPN
cana-3107	306	30	,	,	PUNCT
cana-3107	306	31	z.	z.	PROPN
cana-3107	306	32	(	(	PUNCT
cana-3107	306	33	2010	2010	NUM
cana-3107	306	34	,	,	PUNCT
cana-3107	306	35	august	august	PROPN
cana-3107	306	36	)	)	PUNCT
cana-3107	306	37	.	.	PUNCT
cana-3107	307	1	research	research	NOUN
cana-3107	307	2	on	on	ADP
cana-3107	307	3	insect	insect	NOUN
cana-3107	307	4	identification	identification	NOUN
cana-3107	307	5	based	base	VERB
cana-3107	307	6	on	on	ADP
cana-3107	307	7	pattern	pattern	NOUN
cana-3107	307	8	recognition	recognition	NOUN
cana-3107	307	9	technology	technology	NOUN
cana-3107	307	10	.	.	PUNCT
cana-3107	308	1	in	in	ADP
cana-3107	308	2	2010	2010	NUM
cana-3107	308	3	sixth	sixth	ADJ
cana-3107	308	4	international	international	ADJ
cana-3107	308	5	conference	conference	NOUN
cana-3107	308	6	on	on	ADP
cana-3107	308	7	natural	natural	ADJ
cana-3107	308	8	computation	computation	NOUN
cana-3107	308	9	(	(	PUNCT
cana-3107	308	10	vol	vol	NOUN
cana-3107	308	11	.	.	NOUN
cana-3107	308	12	2	2	NUM
cana-3107	308	13	,	,	PUNCT
cana-3107	308	14	pp	pp	ADJ
cana-3107	308	15	.	.	PUNCT
cana-3107	309	1	545	545	NUM
cana-3107	309	2	-	-	SYM
cana-3107	309	3	548	548	NUM
cana-3107	309	4	)	)	PUNCT
cana-3107	309	5	.	.	PUNCT
cana-3107	310	1	ieee	ieee	NOUN
cana-3107	310	2	.	.	PUNCT
cana-3107	311	1	[	[	X
cana-3107	311	2	7	7	NUM
cana-3107	311	3	]	]	X
cana-3107	311	4	júnior	júnior	PROPN
cana-3107	311	5	,	,	PUNCT
cana-3107	311	6	t.	t.	PROPN
cana-3107	311	7	d.	d.	PROPN
cana-3107	311	8	c.	c.	PROPN
cana-3107	311	9	,	,	PUNCT
cana-3107	311	10	&	&	CCONJ
cana-3107	311	11	rieder	rieder	PROPN
cana-3107	311	12	,	,	PUNCT
cana-3107	311	13	r.	r.	PROPN
cana-3107	311	14	(	(	PUNCT
cana-3107	311	15	2020	2020	NUM
cana-3107	311	16	)	)	PUNCT
cana-3107	311	17	.	.	PUNCT
cana-3107	312	1	automatic	automatic	ADJ
cana-3107	312	2	identification	identification	NOUN
cana-3107	312	3	of	of	ADP
cana-3107	312	4	insects	insect	NOUN
cana-3107	312	5	from	from	ADP
cana-3107	312	6	digital	digital	ADJ
cana-3107	312	7	images	image	NOUN
cana-3107	312	8	:	:	PUNCT
cana-3107	312	9	a	a	DET
cana-3107	312	10	survey	survey	NOUN
cana-3107	312	11	.	.	PUNCT
cana-3107	313	1	computers	computer	NOUN
cana-3107	313	2	and	and	CCONJ
cana-3107	313	3	electronics	electronic	NOUN
cana-3107	313	4	in	in	ADP
cana-3107	313	5	agriculture	agriculture	NOUN
cana-3107	313	6	,	,	PUNCT
cana-3107	313	7	178	178	NUM
cana-3107	313	8	,	,	PUNCT
cana-3107	313	9	105784	105784	NUM
cana-3107	313	10	.	.	PUNCT
cana-3107	314	1	[	[	X
cana-3107	314	2	8	8	NUM
cana-3107	314	3	]	]	PUNCT
cana-3107	314	4	dongmei	dongmei	PROPN
cana-3107	314	5	,	,	PUNCT
cana-3107	314	6	z.	z.	PROPN
cana-3107	314	7	,	,	PUNCT
cana-3107	314	8	ke	ke	PROPN
cana-3107	314	9	,	,	PUNCT
cana-3107	314	10	w.	w.	PROPN
cana-3107	314	11	,	,	PUNCT
cana-3107	314	12	hongbo	hongbo	PROPN
cana-3107	314	13	,	,	PUNCT
cana-3107	314	14	g.	g.	PROPN
cana-3107	314	15	,	,	PUNCT
cana-3107	314	16	peng	peng	PROPN
cana-3107	314	17	,	,	PUNCT
cana-3107	314	18	w.	w.	PROPN
cana-3107	314	19	,	,	PUNCT
cana-3107	314	20	chao	chao	PROPN
cana-3107	314	21	,	,	PUNCT
cana-3107	314	22	w.	w.	PROPN
cana-3107	314	23	,	,	PUNCT
cana-3107	314	24	&	&	CCONJ
cana-3107	314	25	shaofeng	shaofeng	PROPN
cana-3107	314	26	,	,	PUNCT
cana-3107	314	27	p.	p.	NOUN
cana-3107	314	28	(	(	PUNCT
cana-3107	314	29	2020	2020	NUM
cana-3107	314	30	,	,	PUNCT
cana-3107	314	31	november	november	PROPN
cana-3107	314	32	)	)	PUNCT
cana-3107	314	33	.	.	PUNCT
cana-3107	315	1	classification	classification	NOUN
cana-3107	315	2	and	and	CCONJ
cana-3107	315	3	identification	identification	NOUN
cana-3107	315	4	of	of	ADP
cana-3107	315	5	citrus	citrus	NOUN
cana-3107	315	6	pests	pest	NOUN
cana-3107	315	7	based	base	VERB
cana-3107	315	8	on	on	ADP
cana-3107	315	9	inceptionv3	inceptionv3	NOUN
cana-3107	315	10	convolutional	convolutional	ADJ
cana-3107	315	11	neural	neural	ADJ
cana-3107	315	12	network	network	NOUN
cana-3107	315	13	and	and	CCONJ
cana-3107	315	14	migration	migration	NOUN
cana-3107	315	15	learning	learning	NOUN
cana-3107	315	16	.	.	PUNCT
cana-3107	316	1	in	in	ADP
cana-3107	316	2	2020	2020	NUM
cana-3107	316	3	international	international	ADJ
cana-3107	316	4	conference	conference	NOUN
cana-3107	316	5	on	on	ADP
cana-3107	316	6	internet	internet	NOUN
cana-3107	316	7	of	of	ADP
cana-3107	316	8	things	thing	NOUN
cana-3107	316	9	and	and	CCONJ
cana-3107	316	10	intelligent	intelligent	ADJ
cana-3107	316	11	applications	application	NOUN
cana-3107	316	12	(	(	PUNCT
cana-3107	316	13	itia	itia	NOUN
cana-3107	316	14	)	)	PUNCT
cana-3107	316	15	(	(	PUNCT
cana-3107	316	16	pp	pp	X
cana-3107	316	17	.	.	PUNCT
cana-3107	317	1	1	1	NUM
cana-3107	317	2	-	-	SYM
cana-3107	317	3	7	7	NUM
cana-3107	317	4	)	)	PUNCT
cana-3107	317	5	.	.	PUNCT
cana-3107	318	1	ieee	ieee	NOUN
cana-3107	318	2	.	.	PUNCT
cana-3107	319	1	[	[	X
cana-3107	319	2	9	9	NUM
cana-3107	319	3	]	]	X
cana-3107	319	4	hansen	hansen	PROPN
cana-3107	319	5	,	,	PUNCT
cana-3107	319	6	o.	o.	PROPN
cana-3107	319	7	l.	l.	PROPN
cana-3107	319	8	,	,	PUNCT
cana-3107	319	9	svenning	svenning	PROPN
cana-3107	319	10	,	,	PUNCT
cana-3107	319	11	j.	j.	PROPN
cana-3107	319	12	c.	c.	PROPN
cana-3107	319	13	,	,	PUNCT
cana-3107	319	14	olsen	olsen	PROPN
cana-3107	319	15	,	,	PUNCT
cana-3107	319	16	k.	k.	PROPN
cana-3107	319	17	,	,	PUNCT
cana-3107	319	18	dupont	dupont	PROPN
cana-3107	319	19	,	,	PUNCT
cana-3107	319	20	s.	s.	PROPN
cana-3107	319	21	,	,	PUNCT
cana-3107	319	22	garner	garner	PROPN
cana-3107	319	23	,	,	PUNCT
cana-3107	319	24	b.	b.	PROPN
cana-3107	319	25	h.	h.	PROPN
cana-3107	319	26	,	,	PUNCT
cana-3107	319	27	iosifidis	iosifidis	PROPN
cana-3107	319	28	,	,	PUNCT
cana-3107	319	29	a.	a.	NOUN
cana-3107	319	30	,	,	PUNCT
cana-3107	319	31	...	...	PUNCT
cana-3107	319	32	&	&	CCONJ
cana-3107	319	33	høye	høye	NOUN
cana-3107	319	34	,	,	PUNCT
cana-3107	319	35	t.	t.	NOUN
cana-3107	319	36	t.	t.	PROPN
cana-3107	319	37	(	(	PUNCT
cana-3107	319	38	2020	2020	NUM
cana-3107	319	39	)	)	PUNCT
cana-3107	319	40	.	.	PUNCT
cana-3107	320	1	species‐level	species‐level	ADJ
cana-3107	320	2	image	image	NOUN
cana-3107	320	3	classification	classification	NOUN
cana-3107	320	4	with	with	ADP
cana-3107	320	5	convolutional	convolutional	ADJ
cana-3107	320	6	neural	neural	ADJ
cana-3107	320	7	network	network	NOUN
cana-3107	320	8	enables	enable	VERB
cana-3107	320	9	insect	insect	VERB
cana-3107	320	10	identification	identification	NOUN
cana-3107	320	11	from	from	ADP
cana-3107	320	12	habitus	habitus	NOUN
cana-3107	320	13	images	image	NOUN
cana-3107	320	14	.	.	PUNCT
cana-3107	321	1	ecology	ecology	NOUN
cana-3107	321	2	and	and	CCONJ
cana-3107	321	3	evolution	evolution	NOUN
cana-3107	321	4	,	,	PUNCT
cana-3107	321	5	10(2	10(2	NUM
cana-3107	321	6	)	)	PUNCT
cana-3107	321	7	,	,	PUNCT
cana-3107	321	8	737	737	NUM
cana-3107	321	9	-	-	SYM
cana-3107	321	10	747	747	NUM
cana-3107	321	11	.	.	PUNCT
cana-3107	322	1	[	[	X
cana-3107	322	2	10	10	NUM
cana-3107	322	3	]	]	X
cana-3107	322	4	wen	wen	PROPN
cana-3107	322	5	,	,	PUNCT
cana-3107	322	6	c.	c.	PROPN
cana-3107	322	7	,	,	PUNCT
cana-3107	322	8	&	&	CCONJ
cana-3107	322	9	guyer	guyer	PROPN
cana-3107	322	10	,	,	PUNCT
cana-3107	322	11	d.	d.	PROPN
cana-3107	322	12	(	(	PUNCT
cana-3107	322	13	2012	2012	NUM
cana-3107	322	14	)	)	PUNCT
cana-3107	322	15	.	.	PUNCT
cana-3107	323	1	image	image	NOUN
cana-3107	323	2	-	-	PUNCT
cana-3107	323	3	based	base	VERB
cana-3107	323	4	orchard	orchard	NOUN
cana-3107	323	5	insect	insect	NOUN
cana-3107	323	6	automated	automate	VERB
cana-3107	323	7	identification	identification	NOUN
cana-3107	323	8	and	and	CCONJ
cana-3107	323	9	classification	classification	NOUN
cana-3107	323	10	method	method	NOUN
cana-3107	323	11	.	.	PUNCT
cana-3107	324	1	computers	computer	NOUN
cana-3107	324	2	and	and	CCONJ
cana-3107	324	3	electronics	electronic	NOUN
cana-3107	324	4	in	in	ADP
cana-3107	324	5	agriculture	agriculture	NOUN
cana-3107	324	6	,	,	PUNCT
cana-3107	324	7	89	89	NUM
cana-3107	324	8	,	,	PUNCT
cana-3107	324	9	110	110	NUM
cana-3107	324	10	-	-	SYM
cana-3107	324	11	115	115	NUM
cana-3107	324	12	.	.	PUNCT
cana-3107	325	1	[	[	X
cana-3107	325	2	11	11	NUM
cana-3107	325	3	]	]	PUNCT
cana-3107	325	4	cleetus	cleetus	NOUN
cana-3107	325	5	,	,	PUNCT
cana-3107	325	6	l.	l.	PROPN
cana-3107	325	7	,	,	PUNCT
cana-3107	325	8	raji	raji	PROPN
cana-3107	325	9	sukumar	sukumar	PROPN
cana-3107	325	10	,	,	PUNCT
cana-3107	325	11	a.	a.	PROPN
cana-3107	325	12	,	,	PUNCT
cana-3107	325	13	&	&	CCONJ
cana-3107	325	14	hemalatha	hemalatha	PROPN
cana-3107	325	15	,	,	PUNCT
cana-3107	325	16	n.	n.	NOUN
cana-3107	325	17	(	(	PUNCT
cana-3107	325	18	2021	2021	NUM
cana-3107	325	19	)	)	PUNCT
cana-3107	325	20	.	.	PUNCT
cana-3107	326	1	computational	computational	ADJ
cana-3107	326	2	prediction	prediction	NOUN
cana-3107	326	3	of	of	ADP
cana-3107	326	4	disease	disease	NOUN
cana-3107	326	5	detection	detection	NOUN
cana-3107	326	6	and	and	CCONJ
cana-3107	326	7	insect	insect	NOUN
cana-3107	326	8	identification	identification	NOUN
cana-3107	326	9	using	use	VERB
cana-3107	326	10	xception	xception	PROPN
cana-3107	326	11	model	model	NOUN
cana-3107	326	12	.	.	PUNCT
cana-3107	327	1	biorxiv	biorxiv	NOUN
cana-3107	327	2	,	,	PUNCT
cana-3107	327	3	2021	2021	NUM
cana-3107	327	4	-	-	SYM
cana-3107	327	5	08	08	NUM
cana-3107	327	6	.	.	PUNCT
cana-3107	328	1	[	[	X
cana-3107	328	2	12	12	NUM
cana-3107	328	3	]	]	X
cana-3107	328	4	martineau	martineau	PROPN
cana-3107	328	5	,	,	PUNCT
cana-3107	328	6	m.	m.	NOUN
cana-3107	328	7	,	,	PUNCT
cana-3107	328	8	conte	conte	PROPN
cana-3107	328	9	,	,	PUNCT
cana-3107	328	10	d.	d.	PROPN
cana-3107	328	11	,	,	PUNCT
cana-3107	328	12	raveaux	raveaux	PROPN
cana-3107	328	13	,	,	PUNCT
cana-3107	328	14	r.	r.	PROPN
cana-3107	328	15	,	,	PUNCT
cana-3107	328	16	arnault	arnault	NOUN
cana-3107	328	17	,	,	PUNCT
cana-3107	328	18	i.	i.	NOUN
cana-3107	328	19	,	,	PUNCT
cana-3107	328	20	munier	munier	NOUN
cana-3107	328	21	,	,	PUNCT
cana-3107	328	22	d.	d.	PROPN
cana-3107	328	23	,	,	PUNCT
cana-3107	328	24	&	&	CCONJ
cana-3107	328	25	venturini	venturini	PROPN
cana-3107	328	26	,	,	PUNCT
cana-3107	328	27	g.	g.	PROPN
cana-3107	328	28	(	(	PUNCT
cana-3107	328	29	2017	2017	NUM
cana-3107	328	30	)	)	PUNCT
cana-3107	328	31	.	.	PUNCT
cana-3107	329	1	a	a	DET
cana-3107	329	2	survey	survey	NOUN
cana-3107	329	3	on	on	ADP
cana-3107	329	4	image	image	NOUN
cana-3107	329	5	-	-	PUNCT
cana-3107	329	6	based	base	VERB
cana-3107	329	7	insect	insect	NOUN
cana-3107	329	8	classification	classification	NOUN
cana-3107	329	9	.	.	PUNCT
cana-3107	330	1	pattern	pattern	NOUN
cana-3107	330	2	recognition	recognition	NOUN
cana-3107	330	3	,	,	PUNCT
cana-3107	330	4	65	65	NUM
cana-3107	330	5	,	,	PUNCT
cana-3107	330	6	273	273	NUM
cana-3107	330	7	-	-	SYM
cana-3107	330	8	284	284	NUM
cana-3107	330	9	.	.	PUNCT
cana-3107	331	1	[	[	X
cana-3107	331	2	13	13	NUM
cana-3107	331	3	]	]	X
cana-3107	331	4	nieuwenhuizen	nieuwenhuizen	NOUN
cana-3107	331	5	,	,	PUNCT
cana-3107	331	6	a.	a.	NOUN
cana-3107	331	7	t.	t.	PROPN
cana-3107	331	8	,	,	PUNCT
cana-3107	331	9	hemming	hemming	NOUN
cana-3107	331	10	,	,	PUNCT
cana-3107	331	11	j.	j.	PROPN
cana-3107	331	12	,	,	PUNCT
cana-3107	331	13	&	&	CCONJ
cana-3107	331	14	suh	suh	PROPN
cana-3107	331	15	,	,	PUNCT
cana-3107	331	16	h.	h.	PROPN
cana-3107	331	17	k.	k.	PROPN
cana-3107	331	18	(	(	PUNCT
cana-3107	331	19	2018	2018	NUM
cana-3107	331	20	)	)	PUNCT
cana-3107	331	21	.	.	PUNCT
cana-3107	332	1	detection	detection	NOUN
cana-3107	332	2	and	and	CCONJ
cana-3107	332	3	classification	classification	NOUN
cana-3107	332	4	of	of	ADP
cana-3107	332	5	insects	insect	NOUN
cana-3107	332	6	on	on	ADP
cana-3107	332	7	stick	stick	NOUN
cana-3107	332	8	-	-	PUNCT
cana-3107	332	9	traps	trap	NOUN
cana-3107	332	10	in	in	ADP
cana-3107	332	11	a	a	DET
cana-3107	332	12	tomato	tomato	NOUN
cana-3107	332	13	crop	crop	NOUN
cana-3107	332	14	using	use	VERB
cana-3107	332	15	faster	fast	ADJ
cana-3107	332	16	r	r	NOUN
cana-3107	332	17	-	-	PUNCT
cana-3107	332	18	cnn	cnn	NOUN
cana-3107	332	19	.	.	PUNCT
cana-3107	333	1	[	[	X
cana-3107	333	2	14	14	NUM
cana-3107	333	3	]	]	SYM
cana-3107	333	4	tiwari	tiwari	NOUN
cana-3107	333	5	,	,	PUNCT
cana-3107	333	6	v.	v.	PROPN
cana-3107	333	7	,	,	PUNCT
cana-3107	333	8	gupta	gupta	PROPN
cana-3107	333	9	,	,	PUNCT
cana-3107	333	10	s.	s.	PROPN
cana-3107	333	11	,	,	PUNCT
cana-3107	333	12	roy	roy	PROPN
cana-3107	333	13	,	,	PUNCT
cana-3107	333	14	p.	p.	PROPN
cana-3107	333	15	,	,	PUNCT
cana-3107	333	16	karda	karda	PROPN
cana-3107	333	17	,	,	PUNCT
cana-3107	333	18	c.	c.	PROPN
cana-3107	333	19	,	,	PUNCT
cana-3107	333	20	agrawal	agrawal	PROPN
cana-3107	333	21	,	,	PUNCT
cana-3107	333	22	s.	s.	PROPN
cana-3107	333	23	,	,	PUNCT
cana-3107	333	24	rathore	rathore	PROPN
cana-3107	333	25	,	,	PUNCT
cana-3107	333	26	m.	m.	NOUN
cana-3107	333	27	s.	s.	PROPN
cana-3107	333	28	,	,	PUNCT
cana-3107	333	29	...	...	PUNCT
cana-3107	333	30	&	&	CCONJ
cana-3107	333	31	pal	pal	NOUN
cana-3107	333	32	,	,	PUNCT
cana-3107	333	33	a.	a.	NOUN
cana-3107	333	34	(	(	PUNCT
cana-3107	333	35	2022	2022	NUM
cana-3107	333	36	)	)	PUNCT
cana-3107	333	37	.	.	PUNCT
cana-3107	334	1	soybean	soybean	NOUN
cana-3107	334	2	crop	crop	NOUN
cana-3107	334	3	nonbeneficial	nonbeneficial	ADJ
cana-3107	334	4	insect	insect	NOUN
cana-3107	334	5	identification	identification	NOUN
cana-3107	334	6	using	use	VERB
cana-3107	334	7	mask	mask	NOUN
cana-3107	334	8	rcnn	rcnn	PROPN
cana-3107	334	9	.	.	PUNCT
cana-3107	335	1	in	in	ADP
cana-3107	335	2	information	information	NOUN
cana-3107	335	3	and	and	CCONJ
cana-3107	335	4	communication	communication	NOUN
cana-3107	335	5	technology	technology	NOUN
cana-3107	335	6	for	for	ADP
cana-3107	335	7	competitive	competitive	ADJ
cana-3107	335	8	strategies	strategy	NOUN
cana-3107	335	9	(	(	PUNCT
cana-3107	335	10	ictcs	ictcs	NOUN
cana-3107	335	11	2020	2020	NUM
cana-3107	335	12	)	)	PUNCT
cana-3107	335	13	ict	ict	NOUN
cana-3107	335	14	:	:	PUNCT
cana-3107	335	15	applications	application	NOUN
cana-3107	335	16	and	and	CCONJ
cana-3107	335	17	social	social	ADJ
cana-3107	335	18	interfaces	interface	NOUN
cana-3107	335	19	(	(	PUNCT
cana-3107	335	20	pp	pp	ADJ
cana-3107	335	21	.	.	PUNCT
cana-3107	335	22	301	301	NUM
cana-3107	335	23	-	-	NUM
cana-3107	335	24	311	311	NUM
cana-3107	335	25	)	)	PUNCT
cana-3107	335	26	.	.	PUNCT
cana-3107	336	1	springer	springer	PROPN
cana-3107	336	2	singapore	singapore	PROPN
cana-3107	336	3	.	.	PUNCT
cana-3107	337	1	[	[	X
cana-3107	337	2	15	15	NUM
cana-3107	337	3	]	]	X
cana-3107	337	4	shen	shen	NOUN
cana-3107	337	5	,	,	PUNCT
cana-3107	337	6	y.	y.	PROPN
cana-3107	337	7	,	,	PUNCT
cana-3107	337	8	zhou	zhou	PROPN
cana-3107	337	9	,	,	PUNCT
cana-3107	337	10	h.	h.	PROPN
cana-3107	337	11	,	,	PUNCT
cana-3107	337	12	li	li	PROPN
cana-3107	337	13	,	,	PUNCT
cana-3107	337	14	j.	j.	PROPN
cana-3107	337	15	,	,	PUNCT
cana-3107	337	16	jian	jian	PROPN
cana-3107	337	17	,	,	PUNCT
cana-3107	337	18	f.	f.	PROPN
cana-3107	337	19	,	,	PUNCT
cana-3107	337	20	&	&	CCONJ
cana-3107	337	21	jayas	jayas	PROPN
cana-3107	337	22	,	,	PUNCT
cana-3107	337	23	d.	d.	PROPN
cana-3107	337	24	s.	s.	PROPN
cana-3107	337	25	(	(	PUNCT
cana-3107	337	26	2018	2018	NUM
cana-3107	337	27	)	)	PUNCT
cana-3107	337	28	.	.	PUNCT
cana-3107	338	1	detection	detection	NOUN
cana-3107	338	2	of	of	ADP
cana-3107	338	3	stored	store	VERB
cana-3107	338	4	-	-	PUNCT
cana-3107	338	5	grain	grain	NOUN
cana-3107	338	6	insects	insect	NOUN
cana-3107	338	7	using	use	VERB
cana-3107	338	8	deep	deep	ADJ
cana-3107	338	9	learning	learning	NOUN
cana-3107	338	10	.	.	PUNCT
cana-3107	339	1	computers	computer	NOUN
cana-3107	339	2	and	and	CCONJ
cana-3107	339	3	electronics	electronic	NOUN
cana-3107	339	4	in	in	ADP
cana-3107	339	5	agriculture	agriculture	NOUN
cana-3107	339	6	,	,	PUNCT
cana-3107	339	7	145	145	NUM
cana-3107	339	8	,	,	PUNCT
cana-3107	339	9	319	319	NUM
cana-3107	339	10	-	-	SYM
cana-3107	339	11	325	325	NUM
cana-3107	339	12	.	.	PUNCT
cana-3107	340	1	[	[	X
cana-3107	340	2	16	16	NUM
cana-3107	340	3	]	]	X
cana-3107	340	4	wang	wang	PROPN
cana-3107	340	5	,	,	PUNCT
cana-3107	340	6	j.	j.	PROPN
cana-3107	340	7	,	,	PUNCT
cana-3107	340	8	li	li	PROPN
cana-3107	340	9	,	,	PUNCT
cana-3107	340	10	y.	y.	PROPN
cana-3107	340	11	,	,	PUNCT
cana-3107	340	12	feng	feng	PROPN
cana-3107	340	13	,	,	PUNCT
cana-3107	340	14	h.	h.	PROPN
cana-3107	340	15	,	,	PUNCT
cana-3107	340	16	ren	ren	PROPN
cana-3107	340	17	,	,	PUNCT
cana-3107	340	18	l.	l.	PROPN
cana-3107	340	19	,	,	PUNCT
cana-3107	340	20	du	du	PROPN
cana-3107	340	21	,	,	PUNCT
cana-3107	340	22	x.	x.	NOUN
cana-3107	340	23	,	,	PUNCT
cana-3107	340	24	&	&	CCONJ
cana-3107	340	25	wu	wu	PROPN
cana-3107	340	26	,	,	PUNCT
cana-3107	340	27	j.	j.	PROPN
cana-3107	340	28	(	(	PUNCT
cana-3107	340	29	2020	2020	NUM
cana-3107	340	30	)	)	PUNCT
cana-3107	340	31	.	.	PUNCT
cana-3107	341	1	common	common	ADJ
cana-3107	341	2	pests	pest	NOUN
cana-3107	341	3	image	image	NOUN
cana-3107	341	4	recognition	recognition	NOUN
cana-3107	341	5	based	base	VERB
cana-3107	341	6	on	on	ADP
cana-3107	341	7	deep	deep	ADJ
cana-3107	341	8	convolutional	convolutional	ADJ
cana-3107	341	9	neural	neural	ADJ
cana-3107	341	10	network	network	NOUN
cana-3107	341	11	.	.	PUNCT
cana-3107	342	1	computers	computer	NOUN
cana-3107	342	2	and	and	CCONJ
cana-3107	342	3	electronics	electronic	NOUN
cana-3107	342	4	in	in	ADP
cana-3107	342	5	agriculture	agriculture	NOUN
cana-3107	342	6	,	,	PUNCT
cana-3107	342	7	179	179	NUM
cana-3107	342	8	,	,	PUNCT
cana-3107	342	9	105834	105834	NUM
cana-3107	342	10	.	.	PUNCT
cana-3107	343	1	[	[	X
cana-3107	343	2	17	17	NUM
cana-3107	343	3	]	]	SYM
cana-3107	343	4	tetila	tetila	PROPN
cana-3107	343	5	,	,	PUNCT
cana-3107	343	6	e.	e.	PROPN
cana-3107	343	7	c.	c.	PROPN
cana-3107	343	8	,	,	PUNCT
cana-3107	343	9	machado	machado	PROPN
cana-3107	343	10	,	,	PUNCT
cana-3107	343	11	b.	b.	PROPN
cana-3107	343	12	b.	b.	PROPN
cana-3107	343	13	,	,	PUNCT
cana-3107	343	14	astolfi	astolfi	PROPN
cana-3107	343	15	,	,	PUNCT
cana-3107	343	16	g.	g.	PROPN
cana-3107	343	17	,	,	PUNCT
cana-3107	343	18	de	de	PROPN
cana-3107	343	19	souza	souza	PROPN
cana-3107	343	20	belete	belete	PROPN
cana-3107	343	21	,	,	PUNCT
cana-3107	343	22	n.	n.	PROPN
cana-3107	343	23	a.	a.	PROPN
cana-3107	343	24	,	,	PUNCT
cana-3107	343	25	amorim	amorim	PROPN
cana-3107	343	26	,	,	PUNCT
cana-3107	343	27	w.	w.	PROPN
cana-3107	343	28	p.	p.	PROPN
cana-3107	343	29	,	,	PUNCT
cana-3107	343	30	roel	roel	PROPN
cana-3107	343	31	,	,	PUNCT
cana-3107	343	32	a.	a.	PROPN
cana-3107	343	33	r.	r.	PROPN
cana-3107	343	34	,	,	PUNCT
cana-3107	343	35	&	&	CCONJ
cana-3107	343	36	pistori	pistori	PROPN
cana-3107	343	37	,	,	PUNCT
cana-3107	343	38	h.	h.	PROPN
cana-3107	343	39	(	(	PUNCT
cana-3107	343	40	2020	2020	NUM
cana-3107	343	41	)	)	PUNCT
cana-3107	343	42	.	.	PUNCT
cana-3107	344	1	detection	detection	NOUN
cana-3107	344	2	and	and	CCONJ
cana-3107	344	3	classification	classification	NOUN
cana-3107	344	4	of	of	ADP
cana-3107	344	5	soybean	soybean	NOUN
cana-3107	344	6	pests	pest	NOUN
cana-3107	344	7	using	use	VERB
cana-3107	344	8	deep	deep	ADJ
cana-3107	344	9	learning	learning	NOUN
cana-3107	344	10	with	with	ADP
cana-3107	344	11	uav	uav	PROPN
cana-3107	344	12	images	image	NOUN
cana-3107	344	13	.	.	PUNCT
cana-3107	345	1	computers	computer	NOUN
cana-3107	345	2	and	and	CCONJ
cana-3107	345	3	electronics	electronic	NOUN
cana-3107	345	4	in	in	ADP
cana-3107	345	5	agriculture	agriculture	NOUN
cana-3107	345	6	,	,	PUNCT
cana-3107	345	7	179	179	NUM
cana-3107	345	8	,	,	PUNCT
cana-3107	345	9	105836	105836	NUM
cana-3107	345	10	.	.	PUNCT
cana-3107	346	1	[	[	X
cana-3107	346	2	18	18	NUM
cana-3107	346	3	]	]	X
cana-3107	346	4	souza	souza	PROPN
cana-3107	346	5	,	,	PUNCT
cana-3107	346	6	w.	w.	PROPN
cana-3107	346	7	s.	s.	PROPN
cana-3107	346	8	,	,	PUNCT
cana-3107	346	9	alves	alves	PROPN
cana-3107	346	10	,	,	PUNCT
cana-3107	346	11	a.	a.	NOUN
cana-3107	346	12	n.	n.	PROPN
cana-3107	346	13	,	,	PUNCT
cana-3107	346	14	&	&	CCONJ
cana-3107	346	15	borges	borges	PROPN
cana-3107	346	16	,	,	PUNCT
cana-3107	346	17	d.	d.	PROPN
cana-3107	346	18	l.	l.	PROPN
cana-3107	346	19	(	(	PUNCT
cana-3107	346	20	2019	2019	NUM
cana-3107	346	21	,	,	PUNCT
cana-3107	346	22	october	october	PROPN
cana-3107	346	23	)	)	PUNCT
cana-3107	346	24	.	.	PUNCT
cana-3107	347	1	a	a	DET
cana-3107	347	2	deep	deep	ADJ
cana-3107	347	3	learning	learning	NOUN
cana-3107	347	4	model	model	NOUN
cana-3107	347	5	for	for	ADP
cana-3107	347	6	recognition	recognition	NOUN
cana-3107	347	7	of	of	ADP
cana-3107	347	8	pest	pest	NOUN
cana-3107	347	9	insects	insect	NOUN
cana-3107	347	10	in	in	ADP
cana-3107	347	11	maize	maize	NOUN
cana-3107	347	12	plantations	plantation	NOUN
cana-3107	347	13	.	.	PUNCT
cana-3107	348	1	in	in	ADP
cana-3107	348	2	2019	2019	NUM
cana-3107	348	3	ieee	ieee	NOUN
cana-3107	348	4	international	international	ADJ
cana-3107	348	5	conference	conference	NOUN
cana-3107	348	6	on	on	ADP
cana-3107	348	7	systems	system	NOUN
cana-3107	348	8	,	,	PUNCT
cana-3107	348	9	man	man	NOUN
cana-3107	348	10	and	and	CCONJ
cana-3107	348	11	cybernetics	cybernetic	NOUN
cana-3107	348	12	(	(	PUNCT
cana-3107	348	13	smc	smc	PROPN
cana-3107	348	14	)	)	PUNCT
cana-3107	348	15	(	(	PUNCT
cana-3107	348	16	pp	pp	ADP
cana-3107	348	17	.	.	PUNCT
cana-3107	348	18	22852290	22852290	NUM
cana-3107	348	19	)	)	PUNCT
cana-3107	348	20	.	.	PUNCT
cana-3107	349	1	ieee	ieee	PROPN
cana-3107	349	2	.	.	PUNCT
cana-3107	350	1	[	[	X
cana-3107	350	2	19	19	NUM
cana-3107	350	3	]	]	X
cana-3107	350	4	xia	xia	PROPN
cana-3107	350	5	,	,	PUNCT
cana-3107	350	6	d.	d.	PROPN
cana-3107	350	7	,	,	PUNCT
cana-3107	350	8	chen	chen	PROPN
cana-3107	350	9	,	,	PUNCT
cana-3107	350	10	p.	p.	PROPN
cana-3107	350	11	,	,	PUNCT
cana-3107	350	12	wang	wang	PROPN
cana-3107	350	13	,	,	PUNCT
cana-3107	350	14	b.	b.	PROPN
cana-3107	350	15	,	,	PUNCT
cana-3107	350	16	zhang	zhang	PROPN
cana-3107	350	17	,	,	PUNCT
cana-3107	350	18	j.	j.	PROPN
cana-3107	350	19	,	,	PUNCT
cana-3107	350	20	&	&	CCONJ
cana-3107	350	21	xie	xie	PROPN
cana-3107	350	22	,	,	PUNCT
cana-3107	350	23	c.	c.	PROPN
cana-3107	350	24	(	(	PUNCT
cana-3107	350	25	2018	2018	NUM
cana-3107	350	26	)	)	PUNCT
cana-3107	350	27	.	.	PUNCT
cana-3107	351	1	insect	insect	NOUN
cana-3107	351	2	detection	detection	NOUN
cana-3107	351	3	and	and	CCONJ
cana-3107	351	4	classification	classification	NOUN
cana-3107	351	5	based	base	VERB
cana-3107	351	6	on	on	ADP
cana-3107	351	7	an	an	DET
cana-3107	351	8	improved	improved	ADJ
cana-3107	351	9	convolutional	convolutional	ADJ
cana-3107	351	10	neural	neural	ADJ
cana-3107	351	11	network	network	NOUN
cana-3107	351	12	.	.	PUNCT
cana-3107	352	1	sensors	sensor	NOUN
cana-3107	352	2	,	,	PUNCT
cana-3107	352	3	18(12	18(12	NUM
cana-3107	352	4	)	)	PUNCT
cana-3107	352	5	,	,	PUNCT
cana-3107	352	6	4169	4169	NUM
cana-3107	352	7	.	.	PUNCT
cana-3107	353	1	[	[	X
cana-3107	353	2	20	20	NUM
cana-3107	353	3	]	]	X
cana-3107	353	4	zhao	zhao	PROPN
cana-3107	353	5	,	,	PUNCT
cana-3107	353	6	r.	r.	PROPN
cana-3107	353	7	,	,	PUNCT
cana-3107	353	8	li	li	PROPN
cana-3107	353	9	,	,	PUNCT
cana-3107	353	10	c.	c.	PROPN
cana-3107	353	11	,	,	PUNCT
cana-3107	353	12	ye	ye	PROPN
cana-3107	353	13	,	,	PUNCT
cana-3107	353	14	s.	s.	PROPN
cana-3107	353	15	,	,	PUNCT
cana-3107	353	16	&	&	CCONJ
cana-3107	353	17	fang	fang	X
cana-3107	353	18	,	,	PUNCT
cana-3107	353	19	x.	x.	NOUN
cana-3107	353	20	(	(	PUNCT
cana-3107	353	21	2019	2019	NUM
cana-3107	353	22	,	,	PUNCT
cana-3107	353	23	march	march	PROPN
cana-3107	353	24	)	)	PUNCT
cana-3107	353	25	.	.	PUNCT
cana-3107	354	1	butterfly	butterfly	NOUN
cana-3107	354	2	recognition	recognition	NOUN
cana-3107	354	3	based	base	VERB
cana-3107	354	4	on	on	ADP
cana-3107	354	5	faster	fast	ADJ
cana-3107	354	6	r	r	NOUN
cana-3107	354	7	-	-	PUNCT
cana-3107	354	8	cnn	cnn	NOUN
cana-3107	354	9	.	.	PUNCT
cana-3107	355	1	in	in	ADP
cana-3107	355	2	journal	journal	PROPN
cana-3107	355	3	of	of	ADP
cana-3107	355	4	physics	physics	PROPN
cana-3107	355	5	:	:	PUNCT
cana-3107	355	6	conference	conference	NOUN
cana-3107	355	7	series	series	NOUN
cana-3107	355	8	(	(	PUNCT
cana-3107	355	9	vol	vol	NOUN
cana-3107	355	10	.	.	PUNCT
cana-3107	355	11	1176	1176	NUM
cana-3107	355	12	,	,	PUNCT
cana-3107	355	13	no	no	INTJ
cana-3107	355	14	.	.	NOUN
cana-3107	355	15	3	3	NUM
cana-3107	355	16	,	,	PUNCT
cana-3107	355	17	p.	p.	NOUN
cana-3107	355	18	032048	032048	NUM
cana-3107	355	19	)	)	PUNCT
cana-3107	355	20	.	.	PUNCT
cana-3107	356	1	iop	iop	NOUN
cana-3107	356	2	publishing	publishing	NOUN
cana-3107	356	3	.	.	PUNCT
cana-3107	357	1	[	[	X
cana-3107	357	2	21	21	NUM
cana-3107	357	3	]	]	X
cana-3107	357	4	lin	lin	PROPN
cana-3107	357	5	,	,	PUNCT
cana-3107	357	6	t.	t.	PROPN
cana-3107	357	7	l.	l.	PROPN
cana-3107	357	8	,	,	PUNCT
cana-3107	357	9	chang	chang	PROPN
cana-3107	357	10	,	,	PUNCT
cana-3107	357	11	h.	h.	PROPN
cana-3107	357	12	y.	y.	PROPN
cana-3107	357	13	,	,	PUNCT
cana-3107	357	14	&	&	CCONJ
cana-3107	357	15	chen	chen	PROPN
cana-3107	357	16	,	,	PUNCT
cana-3107	357	17	k.	k.	PROPN
cana-3107	357	18	h.	h.	PROPN
cana-3107	357	19	(	(	PUNCT
cana-3107	357	20	2020	2020	NUM
cana-3107	357	21	)	)	PUNCT
cana-3107	357	22	.	.	PUNCT
cana-3107	358	1	the	the	DET
cana-3107	358	2	pest	pest	NOUN
cana-3107	358	3	and	and	CCONJ
cana-3107	358	4	disease	disease	NOUN
cana-3107	358	5	identification	identification	NOUN
cana-3107	358	6	in	in	ADP
cana-3107	358	7	the	the	DET
cana-3107	358	8	growth	growth	NOUN
cana-3107	358	9	of	of	ADP
cana-3107	358	10	sweet	sweet	ADJ
cana-3107	358	11	peppers	pepper	NOUN
cana-3107	358	12	using	use	VERB
cana-3107	358	13	faster	fast	ADJ
cana-3107	358	14	r	r	NOUN
cana-3107	358	15	-	-	PUNCT
cana-3107	358	16	cnn	cnn	PROPN
cana-3107	358	17	and	and	CCONJ
cana-3107	358	18	mask	mask	VERB
cana-3107	358	19	r	r	PROPN
cana-3107	358	20	-	-	PUNCT
cana-3107	358	21	cnn	cnn	PROPN
cana-3107	358	22	.	.	PUNCT
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cana-3107	359	4	technology	technology	NOUN
cana-3107	359	5	,	,	PUNCT
cana-3107	359	6	21(2	21(2	NUM
cana-3107	359	7	)	)	PUNCT
cana-3107	359	8	,	,	PUNCT
cana-3107	359	9	605	605	NUM
cana-3107	359	10	-	-	SYM
cana-3107	359	11	614	614	NUM
cana-3107	359	12	.	.	PUNCT
cana-3107	360	1	communications	communication	NOUN
cana-3107	360	2	on	on	ADP
cana-3107	360	3	applied	apply	VERB
cana-3107	360	4	nonlinear	nonlinear	ADJ
cana-3107	360	5	analysis	analysis	NOUN
cana-3107	360	6	issn	issn	NOUN
cana-3107	360	7	:	:	PUNCT
cana-3107	360	8	1074	1074	NUM
cana-3107	360	9	-	-	PUNCT
cana-3107	360	10	133x	133x	NUM
cana-3107	360	11	vol	vol	NOUN
cana-3107	360	12	32	32	NUM
cana-3107	360	13	no	no	NOUN
cana-3107	360	14	.	.	PUNCT
cana-3107	361	1	5s	5s	NUM
cana-3107	361	2	(	(	PUNCT
cana-3107	361	3	2025	2025	NUM
cana-3107	361	4	)	)	PUNCT
cana-3107	361	5	375	375	NUM
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cana-3107	362	1	[	[	X
cana-3107	362	2	22	22	NUM
cana-3107	362	3	]	]	X
cana-3107	362	4	mohd	mohd	PROPN
cana-3107	362	5	-	-	PUNCT
cana-3107	362	6	isa	isa	PROPN
cana-3107	362	7	,	,	PUNCT
cana-3107	362	8	w.	w.	PROPN
cana-3107	362	9	n.	n.	PROPN
cana-3107	362	10	,	,	PUNCT
cana-3107	362	11	nizam	nizam	PROPN
cana-3107	362	12	,	,	PUNCT
cana-3107	362	13	a.	a.	PROPN
cana-3107	362	14	,	,	PUNCT
cana-3107	362	15	&	&	CCONJ
cana-3107	362	16	ali	ali	PROPN
cana-3107	362	17	,	,	PUNCT
cana-3107	362	18	a.	a.	PROPN
cana-3107	362	19	(	(	PUNCT
cana-3107	362	20	2019	2019	NUM
cana-3107	362	21	,	,	PUNCT
cana-3107	362	22	july	july	PROPN
cana-3107	362	23	)	)	PUNCT
cana-3107	362	24	.	.	PUNCT
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cana-3107	363	2	segmentation	segmentation	NOUN
cana-3107	363	3	of	of	ADP
cana-3107	363	4	meliponine	meliponine	ADJ
cana-3107	363	5	bee	bee	NOUN
cana-3107	363	6	using	use	VERB
cana-3107	363	7	faster	fast	ADJ
cana-3107	363	8	r	r	NOUN
cana-3107	363	9	-	-	PUNCT
cana-3107	363	10	cnn	cnn	NOUN
cana-3107	363	11	.	.	PUNCT
cana-3107	364	1	in	in	ADP
cana-3107	364	2	2019	2019	NUM
cana-3107	364	3	third	third	ADJ
cana-3107	364	4	world	world	NOUN
cana-3107	364	5	conference	conference	NOUN
cana-3107	364	6	on	on	ADP
cana-3107	364	7	smart	smart	ADJ
cana-3107	364	8	trends	trend	NOUN
cana-3107	364	9	in	in	ADP
cana-3107	364	10	systems	system	NOUN
cana-3107	364	11	security	security	NOUN
cana-3107	364	12	and	and	CCONJ
cana-3107	364	13	sustainablity	sustainablity	NOUN
cana-3107	364	14	(	(	PUNCT
cana-3107	364	15	worlds4	worlds4	PROPN
cana-3107	364	16	)	)	PUNCT
cana-3107	364	17	(	(	PUNCT
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cana-3107	364	19	.	.	PUNCT
cana-3107	364	20	235	235	NUM
cana-3107	364	21	-	-	SYM
cana-3107	364	22	238	238	NUM
cana-3107	364	23	)	)	PUNCT
cana-3107	364	24	.	.	PUNCT
cana-3107	365	1	ieee	ieee	NOUN
cana-3107	365	2	.	.	PUNCT
cana-3107	366	1	[	[	X
cana-3107	366	2	23	23	NUM
cana-3107	366	3	]	]	X
cana-3107	366	4	zhang	zhang	PROPN
cana-3107	366	5	,	,	PUNCT
cana-3107	366	6	m.	m.	NOUN
cana-3107	366	7	,	,	PUNCT
cana-3107	366	8	chen	chen	PROPN
cana-3107	366	9	,	,	PUNCT
cana-3107	366	10	y.	y.	PROPN
cana-3107	366	11	,	,	PUNCT
cana-3107	366	12	zhang	zhang	PROPN
cana-3107	366	13	,	,	PUNCT
cana-3107	366	14	b.	b.	PROPN
cana-3107	366	15	,	,	PUNCT
cana-3107	366	16	pang	pang	NOUN
cana-3107	366	17	,	,	PUNCT
cana-3107	366	18	k.	k.	PROPN
cana-3107	366	19	,	,	PUNCT
cana-3107	366	20	&	&	CCONJ
cana-3107	366	21	lv	lv	PROPN
cana-3107	366	22	,	,	PUNCT
cana-3107	366	23	b.	b.	PROPN
cana-3107	366	24	(	(	PUNCT
cana-3107	366	25	2020	2020	NUM
cana-3107	366	26	)	)	PUNCT
cana-3107	366	27	.	.	PUNCT
cana-3107	367	1	recognition	recognition	NOUN
cana-3107	367	2	of	of	ADP
cana-3107	367	3	pest	pest	NOUN
cana-3107	367	4	based	base	VERB
cana-3107	367	5	on	on	ADP
cana-3107	367	6	faster	fast	ADJ
cana-3107	367	7	rcnn	rcnn	NOUN
cana-3107	367	8	.	.	PUNCT
cana-3107	368	1	in	in	ADP
cana-3107	368	2	signal	signal	NOUN
cana-3107	368	3	and	and	CCONJ
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cana-3107	368	5	processing	processing	NOUN
cana-3107	368	6	,	,	PUNCT
cana-3107	368	7	networking	networking	NOUN
cana-3107	368	8	and	and	CCONJ
cana-3107	368	9	computers	computer	NOUN
cana-3107	368	10	:	:	PUNCT
cana-3107	368	11	proceedings	proceeding	NOUN
cana-3107	368	12	of	of	ADP
cana-3107	368	13	the	the	DET
cana-3107	368	14	6th	6th	ADJ
cana-3107	368	15	international	international	ADJ
cana-3107	368	16	conference	conference	NOUN
cana-3107	368	17	on	on	ADP
cana-3107	368	18	signal	signal	NOUN
cana-3107	368	19	and	and	CCONJ
cana-3107	368	20	information	information	NOUN
cana-3107	368	21	processing	processing	NOUN
cana-3107	368	22	,	,	PUNCT
cana-3107	368	23	networking	networking	NOUN
cana-3107	368	24	and	and	CCONJ
cana-3107	368	25	computers	computer	NOUN
cana-3107	368	26	(	(	PUNCT
cana-3107	368	27	icsinc	icsinc	PROPN
cana-3107	368	28	)	)	PUNCT
cana-3107	368	29	(	(	PUNCT
cana-3107	368	30	pp	pp	ADJ
cana-3107	368	31	.	.	PUNCT
cana-3107	368	32	62	62	NUM
cana-3107	368	33	-	-	SYM
cana-3107	368	34	69	69	NUM
cana-3107	368	35	)	)	PUNCT
cana-3107	368	36	.	.	PUNCT
cana-3107	369	1	springer	springer	PROPN
cana-3107	369	2	singapore	singapore	PROPN
cana-3107	369	3	.	.	PUNCT
cana-3107	370	1	[	[	X
cana-3107	370	2	24	24	NUM
cana-3107	370	3	]	]	X
cana-3107	370	4	jiang	jiang	PROPN
cana-3107	370	5	,	,	PUNCT
cana-3107	370	6	x.	x.	PROPN
cana-3107	370	7	,	,	PUNCT
cana-3107	370	8	hu	hu	PROPN
cana-3107	370	9	,	,	PUNCT
cana-3107	370	10	b.	b.	PROPN
cana-3107	370	11	,	,	PUNCT
cana-3107	370	12	chandra	chandra	PROPN
cana-3107	370	13	satapathy	satapathy	ADJ
cana-3107	370	14	,	,	PUNCT
cana-3107	370	15	s.	s.	PROPN
cana-3107	370	16	,	,	PUNCT
cana-3107	370	17	wang	wang	PROPN
cana-3107	370	18	,	,	PUNCT
cana-3107	370	19	s.	s.	PROPN
cana-3107	370	20	h.	h.	PROPN
cana-3107	370	21	,	,	PUNCT
cana-3107	370	22	&	&	CCONJ
cana-3107	370	23	zhang	zhang	PROPN
cana-3107	370	24	,	,	PUNCT
cana-3107	370	25	y.	y.	PROPN
cana-3107	370	26	d.	d.	PROPN
cana-3107	370	27	(	(	PUNCT
cana-3107	370	28	2020	2020	NUM
cana-3107	370	29	)	)	PUNCT
cana-3107	370	30	.	.	PUNCT
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cana-3107	371	2	identification	identification	NOUN
cana-3107	371	3	for	for	ADP
cana-3107	371	4	chinese	chinese	ADJ
cana-3107	371	5	sign	sign	NOUN
cana-3107	371	6	language	language	NOUN
cana-3107	371	7	via	via	ADP
cana-3107	371	8	alexnet	alexnet	ADV
cana-3107	371	9	-	-	PUNCT
cana-3107	371	10	based	base	VERB
cana-3107	371	11	transfer	transfer	NOUN
cana-3107	371	12	learning	learning	NOUN
cana-3107	371	13	and	and	CCONJ
cana-3107	371	14	adam	adam	PROPN
cana-3107	371	15	optimizer	optimizer	NOUN
cana-3107	371	16	.	.	PUNCT
cana-3107	372	1	scientific	scientific	ADJ
cana-3107	372	2	programming	programming	NOUN
cana-3107	372	3	,	,	PUNCT
cana-3107	372	4	2020	2020	NUM
cana-3107	372	5	,	,	PUNCT
cana-3107	372	6	113	113	NUM
cana-3107	372	7	.	.	PUNCT
cana-3107	373	1	[	[	X
cana-3107	373	2	25	25	NUM
cana-3107	373	3	]	]	X
cana-3107	373	4	chandriah	chandriah	PROPN
cana-3107	373	5	,	,	PUNCT
cana-3107	373	6	k.	k.	PROPN
cana-3107	373	7	k.	k.	PROPN
cana-3107	373	8	,	,	PUNCT
cana-3107	373	9	&	&	CCONJ
cana-3107	373	10	naraganahalli	naraganahalli	PROPN
cana-3107	373	11	,	,	PUNCT
cana-3107	373	12	r.	r.	PROPN
cana-3107	373	13	v.	v.	PROPN
cana-3107	373	14	(	(	PUNCT
cana-3107	373	15	2021	2021	NUM
cana-3107	373	16	)	)	PUNCT
cana-3107	373	17	.	.	PUNCT
cana-3107	374	1	rnn	rnn	PROPN
cana-3107	374	2	/	/	SYM
cana-3107	374	3	lstm	lstm	NOUN
cana-3107	374	4	with	with	ADP
cana-3107	374	5	modified	modify	VERB
cana-3107	374	6	adam	adam	PROPN
cana-3107	374	7	optimizer	optimizer	NOUN
cana-3107	374	8	in	in	ADP
cana-3107	374	9	deep	deep	ADJ
cana-3107	374	10	learning	learning	NOUN
cana-3107	374	11	approach	approach	NOUN
cana-3107	374	12	for	for	ADP
cana-3107	374	13	automobile	automobile	NOUN
cana-3107	374	14	spare	spare	ADJ
cana-3107	374	15	parts	part	NOUN
cana-3107	374	16	demand	demand	NOUN
cana-3107	374	17	forecasting	forecasting	NOUN
cana-3107	374	18	.	.	PUNCT
cana-3107	375	1	multimedia	multimedia	NOUN
cana-3107	375	2	tools	tool	NOUN
cana-3107	375	3	and	and	CCONJ
cana-3107	375	4	applications	application	NOUN
cana-3107	375	5	,	,	PUNCT
cana-3107	375	6	80(17	80(17	PROPN
cana-3107	375	7	)	)	PUNCT
cana-3107	375	8	,	,	PUNCT
cana-3107	375	9	26145	26145	NUM
cana-3107	375	10	-	-	SYM
cana-3107	375	11	26159	26159	NUM
cana-3107	375	12	.	.	PUNCT
cana-3107	376	1	[	[	X
cana-3107	376	2	26	26	NUM
cana-3107	376	3	]	]	X
cana-3107	376	4	şen	şen	PROPN
cana-3107	376	5	,	,	PUNCT
cana-3107	376	6	s.	s.	PROPN
cana-3107	376	7	y.	y.	PROPN
cana-3107	376	8	,	,	PUNCT
cana-3107	376	9	&	&	CCONJ
cana-3107	376	10	özkurt	özkurt	PROPN
cana-3107	376	11	,	,	PUNCT
cana-3107	376	12	n.	n.	PROPN
cana-3107	376	13	(	(	PUNCT
cana-3107	376	14	2020	2020	NUM
cana-3107	376	15	,	,	PUNCT
cana-3107	376	16	october	october	PROPN
cana-3107	376	17	)	)	PUNCT
cana-3107	376	18	.	.	PUNCT
cana-3107	377	1	convolutional	convolutional	ADJ
cana-3107	377	2	neural	neural	ADJ
cana-3107	377	3	network	network	NOUN
cana-3107	377	4	hyperparameter	hyperparameter	NOUN
cana-3107	377	5	tuning	tune	VERB
cana-3107	377	6	with	with	ADP
cana-3107	377	7	adam	adam	PROPN
cana-3107	377	8	optimizer	optimizer	NOUN
cana-3107	377	9	for	for	ADP
cana-3107	377	10	ecg	ecg	PROPN
cana-3107	377	11	classification	classification	NOUN
cana-3107	377	12	.	.	PUNCT
cana-3107	378	1	in	in	ADP
cana-3107	378	2	2020	2020	NUM
cana-3107	378	3	innovations	innovation	NOUN
cana-3107	378	4	in	in	ADP
cana-3107	378	5	intelligent	intelligent	ADJ
cana-3107	378	6	systems	system	NOUN
cana-3107	378	7	and	and	CCONJ
cana-3107	378	8	applications	application	NOUN
cana-3107	378	9	conference	conference	NOUN
cana-3107	378	10	(	(	PUNCT
cana-3107	378	11	asyu	asyu	NOUN
cana-3107	378	12	)	)	PUNCT
cana-3107	378	13	(	(	PUNCT
cana-3107	378	14	pp	pp	X
cana-3107	378	15	.	.	PUNCT
cana-3107	379	1	1	1	NUM
cana-3107	379	2	-	-	SYM
cana-3107	379	3	6	6	NUM
cana-3107	379	4	)	)	PUNCT
cana-3107	379	5	.	.	PUNCT
cana-3107	380	1	ieee	ieee	PROPN
cana-3107	380	2	.	.	PUNCT