id	sid	tid	token	lemma	pos
cana-851	1	1	communications	communication	NOUN
cana-851	1	2	on	on	ADP
cana-851	1	3	applied	apply	VERB
cana-851	1	4	nonlinear	nonlinear	ADJ
cana-851	1	5	analysis	analysis	NOUN
cana-851	1	6	issn	issn	NOUN
cana-851	1	7	:	:	PUNCT
cana-851	1	8	1074	1074	NUM
cana-851	1	9	-	-	PUNCT
cana-851	1	10	133x	133x	NUM
cana-851	1	11	vol	vol	NOUN
cana-851	1	12	31	31	NUM
cana-851	1	13	no	no	NOUN
cana-851	1	14	.	.	PUNCT
cana-851	2	1	4s	4s	NUM
cana-851	2	2	(	(	PUNCT
cana-851	2	3	2024	2024	NUM
cana-851	2	4	)	)	PUNCT
cana-851	2	5	271	271	NUM
cana-851	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	2	7	flowers	flower	NOUN
cana-851	2	8	images	image	VERB
cana-851	2	9	classification	classification	NOUN
cana-851	2	10	with	with	ADP
cana-851	2	11	deep	deep	ADJ
cana-851	2	12	learning	learning	NOUN
cana-851	2	13	:	:	PUNCT
cana-851	2	14	a	a	DET
cana-851	2	15	review	review	NOUN
cana-851	2	16	asia	asia	PROPN
cana-851	2	17	kamal	kamal	PROPN
cana-851	2	18	mustfa*1	mustfa*1	PROPN
cana-851	2	19	,	,	PUNCT
cana-851	2	20	salwa	salwa	PROPN
cana-851	2	21	khalid	khalid	PROPN
cana-851	2	22	abdulateef2	abdulateef2	PROPN
cana-851	2	23	,	,	PUNCT
cana-851	2	24	qabas	qabas	PROPN
cana-851	2	25	amer	amer	PROPN
cana-851	2	26	hameed3	hameed3	PROPN
cana-851	2	27	1,2,3computer	1,2,3computer	NUM
cana-851	2	28	science	science	NOUN
cana-851	2	29	department	department	NOUN
cana-851	2	30	computer	computer	NOUN
cana-851	2	31	science	science	NOUN
cana-851	2	32	and	and	CCONJ
cana-851	2	33	mathematics	mathematics	PROPN
cana-851	2	34	college	college	PROPN
cana-851	2	35	,	,	PUNCT
cana-851	2	36	tikrit	tikrit	NOUN
cana-851	2	37	university	university	NOUN
cana-851	2	38	,	,	PUNCT
cana-851	2	39	tikrit	tikrit	NOUN
cana-851	2	40	,	,	PUNCT
cana-851	2	41	corresponding	corresponding	ADJ
cana-851	2	42	author	author	NOUN
cana-851	2	43	:	:	PUNCT
cana-851	2	44	asia.k.mustfa@st.tu.edu.iq	asia.k.mustfa@st.tu.edu.iq	ADJ
cana-851	2	45	article	article	NOUN
cana-851	2	46	history	history	NOUN
cana-851	2	47	:	:	PUNCT
cana-851	2	48	received	receive	VERB
cana-851	2	49	:	:	PUNCT
cana-851	2	50	18	18	NUM
cana-851	2	51	-	-	PUNCT
cana-851	2	52	04	04	NUM
cana-851	2	53	-	-	PUNCT
cana-851	2	54	2024	2024	NUM
cana-851	2	55	revised	revise	VERB
cana-851	2	56	:	:	PUNCT
cana-851	2	57	10	10	NUM
cana-851	2	58	-	-	SYM
cana-851	2	59	06	06	NUM
cana-851	2	60	-	-	PUNCT
cana-851	2	61	2024	2024	NUM
cana-851	2	62	accepted	accept	VERB
cana-851	2	63	:	:	PUNCT
cana-851	2	64	25	25	NUM
cana-851	2	65	-	-	PUNCT
cana-851	2	66	06	06	NUM
cana-851	2	67	-	-	PUNCT
cana-851	2	68	2024	2024	NUM
cana-851	2	69	abstract	abstract	ADJ
cana-851	2	70	significant	significant	ADJ
cana-851	2	71	progress	progress	NOUN
cana-851	2	72	has	have	AUX
cana-851	2	73	been	be	AUX
cana-851	2	74	made	make	VERB
cana-851	2	75	in	in	ADP
cana-851	2	76	the	the	DET
cana-851	2	77	field	field	NOUN
cana-851	2	78	of	of	ADP
cana-851	2	79	digital	digital	ADJ
cana-851	2	80	image	image	NOUN
cana-851	2	81	processing	processing	NOUN
cana-851	2	82	in	in	ADP
cana-851	2	83	recent	recent	ADJ
cana-851	2	84	years	year	NOUN
cana-851	2	85	through	through	ADP
cana-851	2	86	the	the	DET
cana-851	2	87	utilization	utilization	NOUN
cana-851	2	88	of	of	ADP
cana-851	2	89	machine	machine	NOUN
cana-851	2	90	learning	learning	NOUN
cana-851	2	91	and	and	CCONJ
cana-851	2	92	deep	deep	ADJ
cana-851	2	93	learning	learning	NOUN
cana-851	2	94	,	,	PUNCT
cana-851	2	95	surpassing	surpass	VERB
cana-851	2	96	previous	previous	ADJ
cana-851	2	97	methods	method	NOUN
cana-851	2	98	by	by	ADP
cana-851	2	99	a	a	DET
cana-851	2	100	large	large	ADJ
cana-851	2	101	margin	margin	NOUN
cana-851	2	102	.	.	PUNCT
cana-851	3	1	deep	deep	ADJ
cana-851	3	2	learning	learning	NOUN
cana-851	3	3	methods	method	NOUN
cana-851	3	4	allow	allow	VERB
cana-851	3	5	devices	device	NOUN
cana-851	3	6	such	such	ADJ
cana-851	3	7	as	as	ADP
cana-851	3	8	computers	computer	NOUN
cana-851	3	9	and	and	CCONJ
cana-851	3	10	mobile	mobile	NOUN
cana-851	3	11	to	to	PART
cana-851	3	12	automatically	automatically	ADV
cana-851	3	13	understand	understand	VERB
cana-851	3	14	pattern	pattern	NOUN
cana-851	3	15	characteristics	characteristic	NOUN
cana-851	3	16	.	.	PUNCT
cana-851	4	1	this	this	DET
cana-851	4	2	review	review	NOUN
cana-851	4	3	paper	paper	NOUN
cana-851	4	4	highlights	highlight	NOUN
cana-851	4	5	challenges	challenge	NOUN
cana-851	4	6	and	and	CCONJ
cana-851	4	7	issues	issue	NOUN
cana-851	4	8	in	in	ADP
cana-851	4	9	machine	machine	NOUN
cana-851	4	10	-	-	PUNCT
cana-851	4	11	deep	deep	ADJ
cana-851	4	12	learning	learning	NOUN
cana-851	4	13	applied	apply	VERB
cana-851	4	14	to	to	ADP
cana-851	4	15	the	the	DET
cana-851	4	16	domain	domain	NOUN
cana-851	4	17	of	of	ADP
cana-851	4	18	flower	flower	NOUN
cana-851	4	19	classification	classification	NOUN
cana-851	4	20	.	.	PUNCT
cana-851	5	1	in	in	ADP
cana-851	5	2	addition	addition	NOUN
cana-851	5	3	,	,	PUNCT
cana-851	5	4	the	the	DET
cana-851	5	5	datasets	dataset	NOUN
cana-851	5	6	were	be	AUX
cana-851	5	7	extracted	extract	VERB
cana-851	5	8	that	that	PRON
cana-851	5	9	were	be	AUX
cana-851	5	10	found	find	VERB
cana-851	5	11	in	in	ADP
cana-851	5	12	the	the	DET
cana-851	5	13	literature	literature	NOUN
cana-851	5	14	.	.	PUNCT
cana-851	6	1	the	the	DET
cana-851	6	2	review	review	NOUN
cana-851	6	3	offered	offer	VERB
cana-851	6	4	in	in	ADP
cana-851	6	5	this	this	DET
cana-851	6	6	article	article	NOUN
cana-851	6	7	can	can	AUX
cana-851	6	8	encourage	encourage	VERB
cana-851	6	9	researchers	researcher	NOUN
cana-851	6	10	in	in	ADP
cana-851	6	11	the	the	DET
cana-851	6	12	domain	domain	NOUN
cana-851	6	13	of	of	ADP
cana-851	6	14	agriculture	agriculture	NOUN
cana-851	6	15	inspired	inspire	VERB
cana-851	6	16	techniques	technique	NOUN
cana-851	6	17	research	research	NOUN
cana-851	6	18	society	society	NOUN
cana-851	6	19	to	to	PART
cana-851	6	20	further	far	ADV
cana-851	6	21	enhance	enhance	VERB
cana-851	6	22	the	the	DET
cana-851	6	23	efficacy	efficacy	NOUN
cana-851	6	24	of	of	ADP
cana-851	6	25	the	the	DET
cana-851	6	26	ai	ai	PROPN
cana-851	6	27	methods	method	NOUN
cana-851	6	28	and	and	CCONJ
cana-851	6	29	to	to	PART
cana-851	6	30	use	use	VERB
cana-851	6	31	the	the	DET
cana-851	6	32	different	different	ADJ
cana-851	6	33	ai	ai	VERB
cana-851	6	34	techniques	technique	NOUN
cana-851	6	35	in	in	ADP
cana-851	6	36	other	other	ADJ
cana-851	6	37	fields	field	NOUN
cana-851	6	38	for	for	ADP
cana-851	6	39	solving	solve	VERB
cana-851	6	40	complicated	complicated	ADJ
cana-851	6	41	real	real	ADJ
cana-851	6	42	-	-	PUNCT
cana-851	6	43	life	life	NOUN
cana-851	6	44	challenges	challenge	NOUN
cana-851	6	45	.	.	PUNCT
cana-851	7	1	in	in	ADP
cana-851	7	2	addition	addition	NOUN
cana-851	7	3	,	,	PUNCT
cana-851	7	4	the	the	DET
cana-851	7	5	article	article	NOUN
cana-851	7	6	provides	provide	VERB
cana-851	7	7	an	an	DET
cana-851	7	8	overview	overview	NOUN
cana-851	7	9	of	of	ADP
cana-851	7	10	the	the	DET
cana-851	7	11	artificial	artificial	ADJ
cana-851	7	12	intelligence	intelligence	NOUN
cana-851	7	13	techniques	technique	NOUN
cana-851	7	14	employed	employ	VERB
cana-851	7	15	in	in	ADP
cana-851	7	16	the	the	DET
cana-851	7	17	field	field	NOUN
cana-851	7	18	of	of	ADP
cana-851	7	19	flower	flower	NOUN
cana-851	7	20	recognition	recognition	NOUN
cana-851	7	21	,	,	PUNCT
cana-851	7	22	detection	detection	NOUN
cana-851	7	23	,	,	PUNCT
cana-851	7	24	segmentation	segmentation	NOUN
cana-851	7	25	,	,	PUNCT
cana-851	7	26	and	and	CCONJ
cana-851	7	27	other	other	ADJ
cana-851	7	28	applications	application	NOUN
cana-851	7	29	,	,	PUNCT
cana-851	7	30	delivering	deliver	VERB
cana-851	7	31	the	the	DET
cana-851	7	32	most	most	ADV
cana-851	7	33	delinquent	delinquent	ADJ
cana-851	7	34	and	and	CCONJ
cana-851	7	35	recent	recent	ADJ
cana-851	7	36	literature	literature	NOUN
cana-851	7	37	for	for	ADP
cana-851	7	38	solving	solve	VERB
cana-851	7	39	issues	issue	NOUN
cana-851	7	40	for	for	ADP
cana-851	7	41	researchers	researcher	NOUN
cana-851	7	42	in	in	ADP
cana-851	7	43	the	the	DET
cana-851	7	44	area	area	NOUN
cana-851	7	45	of	of	ADP
cana-851	7	46	flowers	flower	NOUN
cana-851	7	47	.	.	PUNCT
cana-851	8	1	keywords	keyword	NOUN
cana-851	8	2	:	:	PUNCT
cana-851	8	3	machine	machine	NOUN
cana-851	8	4	learning	learning	NOUN
cana-851	8	5	,	,	PUNCT
cana-851	8	6	deep	deep	ADJ
cana-851	8	7	learning	learning	NOUN
cana-851	8	8	,	,	PUNCT
cana-851	8	9	flower	flower	NOUN
cana-851	8	10	images	image	NOUN
cana-851	8	11	,	,	PUNCT
cana-851	8	12	data	data	NOUN
cana-851	8	13	acquisition	acquisition	NOUN
cana-851	8	14	,	,	PUNCT
cana-851	8	15	methods	method	NOUN
cana-851	8	16	,	,	PUNCT
cana-851	8	17	evaluation	evaluation	NOUN
cana-851	8	18	metrics	metric	NOUN
cana-851	8	19	.	.	PUNCT
cana-851	9	1	1	1	X
cana-851	9	2	.	.	X
cana-851	9	3	introduction	introduction	NOUN
cana-851	9	4	flowers	flower	NOUN
cana-851	9	5	and	and	CCONJ
cana-851	9	6	the	the	DET
cana-851	9	7	ability	ability	NOUN
cana-851	9	8	to	to	PART
cana-851	9	9	identify	identify	VERB
cana-851	9	10	them	they	PRON
cana-851	9	11	have	have	VERB
cana-851	9	12	fascinated	fascinate	VERB
cana-851	9	13	mankind	mankind	NOUN
cana-851	9	14	for	for	ADP
cana-851	9	15	centuries[1	centuries[1	NOUN
cana-851	9	16	]	]	PUNCT
cana-851	9	17	.	.	PUNCT
cana-851	10	1	flowers	flower	NOUN
cana-851	10	2	,	,	PUNCT
cana-851	10	3	as	as	ADP
cana-851	10	4	a	a	DET
cana-851	10	5	botanical	botanical	ADJ
cana-851	10	6	species	specie	NOUN
cana-851	10	7	,	,	PUNCT
cana-851	10	8	play	play	VERB
cana-851	10	9	a	a	DET
cana-851	10	10	crucial	crucial	ADJ
cana-851	10	11	role	role	NOUN
cana-851	10	12	in	in	ADP
cana-851	10	13	maintaining	maintain	VERB
cana-851	10	14	ecological	ecological	ADJ
cana-851	10	15	balance	balance	NOUN
cana-851	10	16	.	.	PUNCT
cana-851	11	1	flowers	flower	NOUN
cana-851	11	2	have	have	VERB
cana-851	11	3	the	the	DET
cana-851	11	4	ability	ability	NOUN
cana-851	11	5	to	to	PART
cana-851	11	6	provide	provide	VERB
cana-851	11	7	sustenance	sustenance	NOUN
cana-851	11	8	to	to	ADP
cana-851	11	9	various	various	ADJ
cana-851	11	10	forms	form	NOUN
cana-851	11	11	of	of	ADP
cana-851	11	12	life[2	life[2	NOUN
cana-851	11	13	]	]	PUNCT
cana-851	11	14	by	by	ADP
cana-851	11	15	feeding	feed	VERB
cana-851	11	16	practically	practically	ADV
cana-851	11	17	all	all	DET
cana-851	11	18	insect	insect	VERB
cana-851	11	19	species	specie	NOUN
cana-851	11	20	on	on	ADP
cana-851	11	21	the	the	DET
cana-851	11	22	planet	planet	NOUN
cana-851	11	23	[	[	X
cana-851	11	24	3	3	NUM
cana-851	11	25	]	]	PUNCT
cana-851	11	26	,	,	PUNCT
cana-851	11	27	and	and	CCONJ
cana-851	11	28	are	be	AUX
cana-851	11	29	employed	employ	VERB
cana-851	11	30	in	in	ADP
cana-851	11	31	a	a	DET
cana-851	11	32	variety	variety	NOUN
cana-851	11	33	of	of	ADP
cana-851	11	34	helpful	helpful	ADJ
cana-851	11	35	applications	application	NOUN
cana-851	11	36	in	in	ADP
cana-851	11	37	relation	relation	NOUN
cana-851	11	38	to	to	ADP
cana-851	11	39	humans	human	NOUN
cana-851	11	40	[	[	X
cana-851	11	41	2	2	X
cana-851	11	42	]	]	PUNCT
cana-851	11	43	such	such	ADJ
cana-851	11	44	as	as	ADP
cana-851	11	45	pharmaceutical	pharmaceutical	ADJ
cana-851	11	46	applications	application	NOUN
cana-851	11	47	[	[	X
cana-851	11	48	4	4	NUM
cana-851	11	49	]	]	PUNCT
cana-851	11	50	.	.	PUNCT
cana-851	12	1	plants	plant	NOUN
cana-851	12	2	have	have	VERB
cana-851	12	3	a	a	DET
cana-851	12	4	crucial	crucial	ADJ
cana-851	12	5	role	role	NOUN
cana-851	12	6	in	in	ADP
cana-851	12	7	the	the	DET
cana-851	12	8	advancement	advancement	NOUN
cana-851	12	9	of	of	ADP
cana-851	12	10	society	society	NOUN
cana-851	12	11	,	,	PUNCT
cana-851	12	12	the	the	DET
cana-851	12	13	preservation	preservation	NOUN
cana-851	12	14	of	of	ADP
cana-851	12	15	the	the	DET
cana-851	12	16	environment	environment	NOUN
cana-851	12	17	,	,	PUNCT
cana-851	12	18	and	and	CCONJ
cana-851	12	19	the	the	DET
cana-851	12	20	progress	progress	NOUN
cana-851	12	21	of	of	ADP
cana-851	12	22	agriculture[5	agriculture[5	NOUN
cana-851	12	23	]	]	PUNCT
cana-851	12	24	.	.	PUNCT
cana-851	13	1	distinguishing	distinguish	VERB
cana-851	13	2	flowers	flower	NOUN
cana-851	13	3	remains	remain	VERB
cana-851	13	4	challenging	challenge	VERB
cana-851	13	5	for	for	ADP
cana-851	13	6	most	most	ADJ
cana-851	13	7	people[2	people[2	NUM
cana-851	13	8	]	]	PUNCT
cana-851	13	9	.	.	PUNCT
cana-851	14	1	the	the	DET
cana-851	14	2	primary	primary	ADJ
cana-851	14	3	reason	reason	NOUN
cana-851	14	4	for	for	ADP
cana-851	14	5	this	this	PRON
cana-851	14	6	is	be	AUX
cana-851	14	7	that	that	SCONJ
cana-851	14	8	several	several	ADJ
cana-851	14	9	flowers	flower	NOUN
cana-851	14	10	of	of	ADP
cana-851	14	11	various	various	ADJ
cana-851	14	12	kinds	kind	NOUN
cana-851	14	13	have	have	VERB
cana-851	14	14	similar	similar	ADJ
cana-851	14	15	color	color	NOUN
cana-851	14	16	,	,	PUNCT
cana-851	14	17	appearance	appearance	NOUN
cana-851	14	18	,	,	PUNCT
cana-851	14	19	and	and	CCONJ
cana-851	14	20	shape	shape	NOUN
cana-851	14	21	,	,	PUNCT
cana-851	14	22	furthermore	furthermore	ADV
cana-851	14	23	,	,	PUNCT
cana-851	14	24	photographs	photograph	NOUN
cana-851	14	25	of	of	ADP
cana-851	14	26	various	various	ADJ
cana-851	14	27	flowers	flower	NOUN
cana-851	14	28	typically	typically	ADV
cana-851	14	29	include	include	VERB
cana-851	14	30	similar	similar	ADJ
cana-851	14	31	surrounding	surround	VERB
cana-851	14	32	items	item	NOUN
cana-851	14	33	such	such	ADJ
cana-851	14	34	as	as	ADP
cana-851	14	35	grass	grass	NOUN
cana-851	14	36	,	,	PUNCT
cana-851	14	37	leaves	leave	NOUN
cana-851	14	38	,	,	PUNCT
cana-851	14	39	and	and	CCONJ
cana-851	14	40	so	so	ADV
cana-851	14	41	on	on	ADV
cana-851	14	42	.there	.there	X
cana-851	14	43	are	be	AUX
cana-851	14	44	around	around	ADV
cana-851	14	45	250,000	250,000	NUM
cana-851	14	46	identified	identify	VERB
cana-851	14	47	flowering	flowering	NOUN
cana-851	14	48	plant	plant	NOUN
cana-851	14	49	species	specie	NOUN
cana-851	14	50	categorized	categorize	VERB
cana-851	14	51	into	into	ADP
cana-851	14	52	approximately	approximately	ADV
cana-851	14	53	350	350	NUM
cana-851	14	54	families[6	families[6	NUM
cana-851	14	55	]	]	PUNCT
cana-851	14	56	.	.	PUNCT
cana-851	15	1	recognizing	recognize	VERB
cana-851	15	2	and	and	CCONJ
cana-851	15	3	classifying	classify	VERB
cana-851	15	4	these	these	DET
cana-851	15	5	entities	entity	NOUN
cana-851	15	6	takes	take	VERB
cana-851	15	7	significant	significant	ADJ
cana-851	15	8	time	time	NOUN
cana-851	15	9	and	and	CCONJ
cana-851	15	10	effort[7	effort[7	NOUN
cana-851	15	11	]	]	X
cana-851	15	12	.	.	PUNCT
cana-851	16	1	the	the	DET
cana-851	16	2	process	process	NOUN
cana-851	16	3	of	of	ADP
cana-851	16	4	manual	manual	ADJ
cana-851	16	5	classification	classification	NOUN
cana-851	16	6	is	be	AUX
cana-851	16	7	laborious	laborious	ADJ
cana-851	16	8	and	and	CCONJ
cana-851	16	9	prone	prone	ADJ
cana-851	16	10	to	to	ADP
cana-851	16	11	mistakes	mistake	NOUN
cana-851	16	12	that	that	PRON
cana-851	16	13	can	can	AUX
cana-851	16	14	accumulate	accumulate	VERB
cana-851	16	15	over	over	ADP
cana-851	16	16	time[8	time[8	NOUN
cana-851	16	17	]	]	PUNCT
cana-851	16	18	.	.	PUNCT
cana-851	17	1	as	as	ADP
cana-851	17	2	a	a	DET
cana-851	17	3	result	result	NOUN
cana-851	17	4	,	,	PUNCT
cana-851	17	5	developing	develop	VERB
cana-851	17	6	a	a	DET
cana-851	17	7	computer	computer	NOUN
cana-851	17	8	-	-	PUNCT
cana-851	17	9	aided	aid	VERB
cana-851	17	10	approach	approach	NOUN
cana-851	17	11	for	for	ADP
cana-851	17	12	fast	fast	ADJ
cana-851	17	13	and	and	CCONJ
cana-851	17	14	accurate	accurate	ADJ
cana-851	17	15	flower	flower	NOUN
cana-851	17	16	classification	classification	NOUN
cana-851	17	17	is	be	AUX
cana-851	17	18	an	an	DET
cana-851	17	19	imperative	imperative	ADJ
cana-851	17	20	step[9	step[9	NOUN
cana-851	17	21	]	]	PUNCT
cana-851	17	22	.	.	PUNCT
cana-851	18	1	flower	flower	NOUN
cana-851	18	2	classification	classification	NOUN
cana-851	18	3	is	be	AUX
cana-851	18	4	an	an	DET
cana-851	18	5	important	important	ADJ
cana-851	18	6	study	study	NOUN
cana-851	18	7	in	in	ADP
cana-851	18	8	botany	botany	NOUN
cana-851	18	9	.	.	PUNCT
cana-851	19	1	traditional	traditional	ADJ
cana-851	19	2	flower	flower	NOUN
cana-851	19	3	classification	classification	NOUN
cana-851	19	4	systems	system	NOUN
cana-851	19	5	have	have	VERB
cana-851	19	6	a	a	DET
cana-851	19	7	difficult	difficult	ADJ
cana-851	19	8	time	time	NOUN
cana-851	19	9	limiting	limit	VERB
cana-851	19	10	,	,	PUNCT
cana-851	19	11	the	the	DET
cana-851	19	12	impact	impact	NOUN
cana-851	19	13	of	of	ADP
cana-851	19	14	flowers	flower	NOUN
cana-851	19	15	backdrop	backdrop	ADJ
cana-851	19	16	.	.	PUNCT
cana-851	20	1	this	this	PRON
cana-851	20	2	results	result	VERB
cana-851	20	3	in	in	ADP
cana-851	20	4	matter	matter	NOUN
cana-851	20	5	of	of	ADP
cana-851	20	6	an	an	DET
cana-851	20	7	unsatisfying	unsatisfying	ADJ
cana-851	20	8	classification	classification	NOUN
cana-851	20	9	impact	impact	NOUN
cana-851	20	10	.	.	PUNCT
cana-851	21	1	deep	deep	ADJ
cana-851	21	2	communications	communication	NOUN
cana-851	21	3	on	on	ADP
cana-851	21	4	applied	apply	VERB
cana-851	21	5	nonlinear	nonlinear	ADJ
cana-851	21	6	analysis	analysis	NOUN
cana-851	21	7	issn	issn	NOUN
cana-851	21	8	:	:	PUNCT
cana-851	21	9	1074	1074	NUM
cana-851	21	10	-	-	PUNCT
cana-851	21	11	133x	133x	NUM
cana-851	21	12	vol	vol	NOUN
cana-851	21	13	31	31	NUM
cana-851	21	14	no	no	NOUN
cana-851	21	15	.	.	PUNCT
cana-851	22	1	4s	4s	NUM
cana-851	22	2	(	(	PUNCT
cana-851	22	3	2024	2024	NUM
cana-851	22	4	)	)	PUNCT
cana-851	22	5	272	272	NUM
cana-851	22	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	22	7	learning	learning	NOUN
cana-851	22	8	has	have	AUX
cana-851	22	9	gained	gain	VERB
cana-851	22	10	significant	significant	ADJ
cana-851	22	11	popularity	popularity	NOUN
cana-851	22	12	as	as	ADP
cana-851	22	13	a	a	DET
cana-851	22	14	study	study	NOUN
cana-851	22	15	field	field	NOUN
cana-851	22	16	in	in	ADP
cana-851	22	17	image	image	NOUN
cana-851	22	18	classification	classification	NOUN
cana-851	22	19	issues	issue	NOUN
cana-851	22	20	due	due	ADP
cana-851	22	21	to	to	ADP
cana-851	22	22	the	the	DET
cana-851	22	23	rise	rise	NOUN
cana-851	22	24	of	of	ADP
cana-851	22	25	huge	huge	ADJ
cana-851	22	26	data	datum	NOUN
cana-851	22	27	and	and	CCONJ
cana-851	22	28	the	the	DET
cana-851	22	29	quick	quick	ADJ
cana-851	22	30	progress	progress	NOUN
cana-851	22	31	of	of	ADP
cana-851	22	32	internet	internet	NOUN
cana-851	22	33	technology[10	technology[10	NOUN
cana-851	22	34	]	]	PUNCT
cana-851	22	35	.	.	PUNCT
cana-851	23	1	the	the	DET
cana-851	23	2	flower	flower	NOUN
cana-851	23	3	classification	classification	NOUN
cana-851	23	4	was	be	AUX
cana-851	23	5	executed	execute	VERB
cana-851	23	6	with	with	ADP
cana-851	23	7	machine	machine	NOUN
cana-851	23	8	learning	learning	NOUN
cana-851	23	9	and	and	CCONJ
cana-851	23	10	deep	deep	ADJ
cana-851	23	11	learning	learning	NOUN
cana-851	23	12	techniques	technique	NOUN
cana-851	23	13	.	.	PUNCT
cana-851	24	1	machine	machine	NOUN
cana-851	24	2	learning	learning	NOUN
cana-851	24	3	is	be	AUX
cana-851	24	4	an	an	DET
cana-851	24	5	ai	ai	NOUN
cana-851	24	6	approach	approach	NOUN
cana-851	24	7	used	use	VERB
cana-851	24	8	to	to	PART
cana-851	24	9	identify	identify	VERB
cana-851	24	10	patterns	pattern	NOUN
cana-851	24	11	in	in	ADP
cana-851	24	12	data[11]major	data[11]major	NOUN
cana-851	24	13	brief	brief	ADJ
cana-851	24	14	of	of	ADP
cana-851	24	15	machine	machine	NOUN
cana-851	24	16	learning	learning	NOUN
cana-851	24	17	is	be	AUX
cana-851	24	18	information	information	NOUN
cana-851	24	19	evaluation	evaluation	NOUN
cana-851	24	20	.	.	PUNCT
cana-851	25	1	numerous	numerous	ADJ
cana-851	25	2	algorithms	algorithm	NOUN
cana-851	25	3	present	present	ADJ
cana-851	25	4	for	for	ADP
cana-851	25	5	system	system	NOUN
cana-851	25	6	classification	classification	NOUN
cana-851	25	7	like	like	ADP
cana-851	25	8	decision	decision	NOUN
cana-851	25	9	trees	tree	NOUN
cana-851	25	10	(	(	PUNCT
cana-851	25	11	dt	dt	PROPN
cana-851	25	12	)	)	PUNCT
cana-851	25	13	,	,	PUNCT
cana-851	25	14	neural	neural	ADJ
cana-851	25	15	network	network	NOUN
cana-851	25	16	,	,	PUNCT
cana-851	25	17	navie	navie	ADJ
cana-851	25	18	bayes	bayes	NOUN
cana-851	25	19	,	,	PUNCT
cana-851	25	20	svm[12	svm[12	NOUN
cana-851	25	21	]	]	PUNCT
cana-851	25	22	.	.	PUNCT
cana-851	26	1	deep	deep	ADJ
cana-851	26	2	learning	learning	NOUN
cana-851	26	3	is	be	AUX
cana-851	26	4	a	a	DET
cana-851	26	5	particular	particular	ADJ
cana-851	26	6	type	type	NOUN
cana-851	26	7	of	of	ADP
cana-851	26	8	machine	machine	NOUN
cana-851	26	9	learning[13],such	learning[13],such	PROPN
cana-851	26	10	as	as	ADP
cana-851	26	11	resnet50	resnet50	NOUN
cana-851	26	12	,	,	PUNCT
cana-851	26	13	mobilenet	mobilenet	PROPN
cana-851	26	14	,	,	PUNCT
cana-851	26	15	densenet169	densenet169	PROPN
cana-851	26	16	,	,	PUNCT
cana-851	26	17	inceptionv3	inceptionv3	NOUN
cana-851	26	18	and	and	CCONJ
cana-851	26	19	vgg16[14],that	vgg16[14],that	PROPN
cana-851	26	20	enables	enable	VERB
cana-851	26	21	computers	computer	NOUN
cana-851	26	22	to	to	PART
cana-851	26	23	extract	extract	VERB
cana-851	26	24	data	datum	NOUN
cana-851	26	25	automatically[15	automatically[15	NOUN
cana-851	26	26	]	]	PUNCT
cana-851	26	27	.	.	PUNCT
cana-851	27	1	readers	reader	NOUN
cana-851	27	2	can	can	AUX
cana-851	27	3	quickly	quickly	ADV
cana-851	27	4	understand	understand	VERB
cana-851	27	5	the	the	DET
cana-851	27	6	concepts	concept	NOUN
cana-851	27	7	of	of	ADP
cana-851	27	8	data	datum	NOUN
cana-851	27	9	preparation	preparation	NOUN
cana-851	27	10	,	,	PUNCT
cana-851	27	11	model	model	NOUN
cana-851	27	12	selection	selection	NOUN
cana-851	27	13	,	,	PUNCT
cana-851	27	14	and	and	CCONJ
cana-851	27	15	improvement	improvement	NOUN
cana-851	27	16	in	in	ADP
cana-851	27	17	recent	recent	ADJ
cana-851	27	18	papers	paper	NOUN
cana-851	27	19	,	,	PUNCT
cana-851	27	20	enabling	enable	VERB
cana-851	27	21	them	they	PRON
cana-851	27	22	to	to	PART
cana-851	27	23	solve	solve	VERB
cana-851	27	24	more	more	ADV
cana-851	27	25	complex	complex	ADJ
cana-851	27	26	problems	problem	NOUN
cana-851	27	27	by	by	ADP
cana-851	27	28	building	build	VERB
cana-851	27	29	upon	upon	SCONJ
cana-851	27	30	past	past	ADJ
cana-851	27	31	research	research	NOUN
cana-851	27	32	.	.	PUNCT
cana-851	28	1	the	the	DET
cana-851	28	2	paper	paper	NOUN
cana-851	28	3	is	be	AUX
cana-851	28	4	structured	structure	VERB
cana-851	28	5	as	as	SCONJ
cana-851	28	6	follows	follow	VERB
cana-851	28	7	:	:	PUNCT
cana-851	28	8	section	section	NOUN
cana-851	28	9	2	2	NUM
cana-851	28	10	presents	present	VERB
cana-851	28	11	a	a	DET
cana-851	28	12	comprehensive	comprehensive	ADJ
cana-851	28	13	summary	summary	NOUN
cana-851	28	14	of	of	ADP
cana-851	28	15	the	the	DET
cana-851	28	16	application	application	NOUN
cana-851	28	17	types	type	NOUN
cana-851	28	18	in	in	ADP
cana-851	28	19	literature	literature	NOUN
cana-851	28	20	review	review	VERB
cana-851	28	21	current	current	ADJ
cana-851	28	22	methodologies	methodology	NOUN
cana-851	28	23	and	and	CCONJ
cana-851	28	24	approaches	approach	NOUN
cana-851	28	25	that	that	PRON
cana-851	28	26	have	have	AUX
cana-851	28	27	been	be	AUX
cana-851	28	28	reviewed	review	VERB
cana-851	28	29	in	in	ADP
cana-851	28	30	the	the	DET
cana-851	28	31	literature	literature	NOUN
cana-851	28	32	.	.	PUNCT
cana-851	29	1	section	section	NOUN
cana-851	29	2	3	3	NUM
cana-851	29	3	offers	offer	VERB
cana-851	29	4	challenge	challenge	NOUN
cana-851	29	5	solved	solve	VERB
cana-851	29	6	using	use	VERB
cana-851	29	7	machine	machine	NOUN
cana-851	29	8	learning	learning	NOUN
cana-851	29	9	in	in	ADP
cana-851	29	10	this	this	DET
cana-851	29	11	literature	literature	NOUN
cana-851	29	12	.	.	PUNCT
cana-851	30	1	section	section	NOUN
cana-851	30	2	4	4	NUM
cana-851	30	3	offers	offer	VERB
cana-851	30	4	challenge	challenge	NOUN
cana-851	30	5	solved	solve	VERB
cana-851	30	6	using	use	VERB
cana-851	30	7	deep	deep	ADJ
cana-851	30	8	learning	learning	NOUN
cana-851	30	9	in	in	ADP
cana-851	30	10	this	this	DET
cana-851	30	11	literature	literature	NOUN
cana-851	30	12	.	.	PUNCT
cana-851	31	1	section	section	NOUN
cana-851	31	2	5	5	NUM
cana-851	31	3	offers	offer	VERB
cana-851	31	4	challenge	challenge	NOUN
cana-851	31	5	solved	solve	VERB
cana-851	31	6	using	use	VERB
cana-851	31	7	hybrid	hybrid	ADJ
cana-851	31	8	models	model	NOUN
cana-851	31	9	in	in	ADP
cana-851	31	10	this	this	DET
cana-851	31	11	literature	literature	NOUN
cana-851	31	12	.	.	PUNCT
cana-851	32	1	section	section	NOUN
cana-851	32	2	6	6	NUM
cana-851	32	3	presents	present	VERB
cana-851	32	4	a	a	DET
cana-851	32	5	summary	summary	NOUN
cana-851	32	6	for	for	ADP
cana-851	32	7	ai	ai	PROPN
cana-851	32	8	techniques	technique	NOUN
cana-851	32	9	used	use	VERB
cana-851	32	10	through	through	ADP
cana-851	32	11	the	the	DET
cana-851	32	12	literature	literature	NOUN
cana-851	32	13	and	and	CCONJ
cana-851	32	14	the	the	DET
cana-851	32	15	dataset	dataset	NOUN
cana-851	32	16	mentioned	mention	VERB
cana-851	32	17	through	through	ADP
cana-851	32	18	the	the	DET
cana-851	32	19	literature	literature	NOUN
cana-851	32	20	.	.	PUNCT
cana-851	33	1	finally	finally	ADV
cana-851	33	2	,	,	PUNCT
cana-851	33	3	section	section	NOUN
cana-851	33	4	6	6	NUM
cana-851	33	5	the	the	DET
cana-851	33	6	conclusion	conclusion	NOUN
cana-851	33	7	of	of	ADP
cana-851	33	8	this	this	DET
cana-851	33	9	study	study	NOUN
cana-851	33	10	.	.	PUNCT
cana-851	34	1	2	2	X
cana-851	34	2	.	.	X
cana-851	34	3	application	application	NOUN
cana-851	34	4	types	type	NOUN
cana-851	34	5	in	in	ADP
cana-851	34	6	literature	literature	NOUN
cana-851	34	7	review	review	VERB
cana-851	34	8	a	a	DET
cana-851	34	9	result	result	NOUN
cana-851	34	10	of	of	ADP
cana-851	34	11	examining	examine	VERB
cana-851	34	12	the	the	DET
cana-851	34	13	various	various	ADJ
cana-851	34	14	literature	literature	NOUN
cana-851	34	15	,	,	PUNCT
cana-851	34	16	the	the	DET
cana-851	34	17	authors	author	NOUN
cana-851	34	18	highlight	highlight	VERB
cana-851	34	19	the	the	DET
cana-851	34	20	different	different	ADJ
cana-851	34	21	applications	application	NOUN
cana-851	34	22	that	that	PRON
cana-851	34	23	exist	exist	VERB
cana-851	34	24	in	in	ADP
cana-851	34	25	the	the	DET
cana-851	34	26	literature	literature	NOUN
cana-851	34	27	such	such	ADJ
cana-851	34	28	as	as	ADP
cana-851	34	29	classification	classification	NOUN
cana-851	34	30	,	,	PUNCT
cana-851	34	31	detection	detection	NOUN
cana-851	34	32	,	,	PUNCT
cana-851	34	33	segmentation	segmentation	NOUN
cana-851	34	34	,	,	PUNCT
cana-851	34	35	recognition	recognition	NOUN
cana-851	34	36	,	,	PUNCT
cana-851	34	37	identification	identification	NOUN
cana-851	34	38	,	,	PUNCT
cana-851	34	39	and	and	CCONJ
cana-851	34	40	lastly	lastly	ADV
cana-851	34	41	localization	localization	NOUN
cana-851	34	42	.	.	PUNCT
cana-851	35	1	table	table	NOUN
cana-851	35	2	1	1	NUM
cana-851	35	3	.	.	PUNCT
cana-851	35	4	summarizes	summarize	VERB
cana-851	35	5	the	the	DET
cana-851	35	6	application	application	NOUN
cana-851	35	7	types	type	NOUN
cana-851	35	8	used	use	VERB
cana-851	35	9	in	in	ADP
cana-851	35	10	the	the	DET
cana-851	35	11	literature	literature	NOUN
cana-851	35	12	review	review	NOUN
cana-851	35	13	of	of	ADP
cana-851	35	14	flower	flower	NOUN
cana-851	35	15	images	image	NOUN
cana-851	35	16	in	in	ADP
cana-851	35	17	this	this	DET
cana-851	35	18	study	study	NOUN
cana-851	35	19	.	.	PUNCT
cana-851	36	1	in	in	ADP
cana-851	36	2	addition	addition	NOUN
cana-851	36	3	,	,	PUNCT
cana-851	36	4	the	the	DET
cana-851	36	5	frequency	frequency	NOUN
cana-851	36	6	of	of	ADP
cana-851	36	7	each	each	DET
cana-851	36	8	application	application	NOUN
cana-851	36	9	determined	determine	VERB
cana-851	36	10	in	in	ADP
cana-851	36	11	the	the	DET
cana-851	36	12	literature	literature	NOUN
cana-851	36	13	was	be	AUX
cana-851	36	14	demonstrated	demonstrate	VERB
cana-851	36	15	in	in	ADP
cana-851	36	16	figure	figure	NOUN
cana-851	36	17	1	1	NUM
cana-851	36	18	.	.	PUNCT
cana-851	37	1	this	this	PRON
cana-851	37	2	indicate	indicate	VERB
cana-851	37	3	that	that	SCONJ
cana-851	37	4	classification	classification	NOUN
cana-851	37	5	is	be	AUX
cana-851	37	6	the	the	DET
cana-851	37	7	most	most	ADV
cana-851	37	8	frequent	frequent	ADJ
cana-851	37	9	application	application	NOUN
cana-851	37	10	however	however	ADV
cana-851	37	11	identification	identification	NOUN
cana-851	37	12	and	and	CCONJ
cana-851	37	13	localization	localization	NOUN
cana-851	37	14	were	be	AUX
cana-851	37	15	the	the	DET
cana-851	37	16	least	least	ADV
cana-851	37	17	frequent	frequent	ADJ
cana-851	37	18	application	application	NOUN
cana-851	37	19	.	.	PUNCT
cana-851	38	1	table	table	NOUN
cana-851	38	2	1	1	NUM
cana-851	38	3	.	.	PUNCT
cana-851	39	1	the	the	DET
cana-851	39	2	application	application	NOUN
cana-851	39	3	types	type	NOUN
cana-851	39	4	used	use	VERB
cana-851	39	5	in	in	ADP
cana-851	39	6	the	the	DET
cana-851	39	7	literature	literature	PROPN
cana-851	39	8	review	review	PROPN
cana-851	39	9	.	.	PUNCT
cana-851	40	1	reference	reference	NOUN
cana-851	40	2	applications	application	NOUN
cana-851	41	1	[	[	X
cana-851	41	2	20],[21],[22],[23],[24],[9],[6],[25],[3],[26],[27],[29],[31],[2],[32],[33	20],[21],[22],[23],[24],[9],[6],[25],[3],[26],[27],[29],[31],[2],[32],[33	NUM
cana-851	41	3	]	]	PUNCT
cana-851	41	4	,	,	PUNCT
cana-851	41	5	[	[	X
cana-851	41	6	34],[37],[16],[17],[18],[4],[40],[41],[43],[19],[44],[42],[10	34],[37],[16],[17],[18],[4],[40],[41],[43],[19],[44],[42],[10	NUM
cana-851	41	7	]	]	X
cana-851	41	8	classification	classification	NOUN
cana-851	41	9	[	[	X
cana-851	41	10	21],[11],[23],[25],[28],[32	21],[11],[23],[25],[28],[32	X
cana-851	41	11	]	]	X
cana-851	41	12	detection	detection	NOUN
cana-851	41	13	[	[	X
cana-851	41	14	6],[32	6],[32	NOUN
cana-851	41	15	]	]	PUNCT
cana-851	41	16	segmentation	segmentation	NOUN
cana-851	42	1	[	[	X
cana-851	42	2	30],[35],[38],[39],[40],[10	30],[35],[38],[39],[40],[10	X
cana-851	42	3	]	]	X
cana-851	42	4	recognition	recognition	NOUN
cana-851	42	5	[	[	X
cana-851	42	6	36	36	NUM
cana-851	42	7	]	]	PUNCT
cana-851	42	8	identification	identification	NOUN
cana-851	42	9	[	[	X
cana-851	42	10	21	21	NUM
cana-851	42	11	]	]	X
cana-851	42	12	localization	localization	NOUN
cana-851	42	13	communications	communication	NOUN
cana-851	42	14	on	on	ADP
cana-851	42	15	applied	apply	VERB
cana-851	42	16	nonlinear	nonlinear	ADJ
cana-851	42	17	analysis	analysis	NOUN
cana-851	42	18	issn	issn	NOUN
cana-851	42	19	:	:	PUNCT
cana-851	42	20	1074	1074	NUM
cana-851	42	21	-	-	PUNCT
cana-851	42	22	133x	133x	NUM
cana-851	42	23	vol	vol	NOUN
cana-851	42	24	31	31	NUM
cana-851	42	25	no	no	NOUN
cana-851	42	26	.	.	PUNCT
cana-851	43	1	4s	4s	NUM
cana-851	43	2	(	(	PUNCT
cana-851	43	3	2024	2024	NUM
cana-851	43	4	)	)	PUNCT
cana-851	44	1	273	273	NUM
cana-851	44	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	44	3	figure	figure	NOUN
cana-851	44	4	1	1	NUM
cana-851	44	5	.	.	PUNCT
cana-851	44	6	number	number	NOUN
cana-851	44	7	of	of	ADP
cana-851	44	8	applications	application	NOUN
cana-851	44	9	utilized	utilize	VERB
cana-851	44	10	in	in	ADP
cana-851	44	11	literature	literature	NOUN
cana-851	44	12	review	review	NOUN
cana-851	44	13	3	3	X
cana-851	44	14	.	.	PUNCT
cana-851	44	15	challenge	challenge	NOUN
cana-851	44	16	solved	solve	VERB
cana-851	44	17	using	use	VERB
cana-851	44	18	ml	ml	ADP
cana-851	44	19	there	there	PRON
cana-851	44	20	are	be	VERB
cana-851	44	21	some	some	DET
cana-851	44	22	limitations	limitation	NOUN
cana-851	44	23	of	of	ADP
cana-851	44	24	this	this	DET
cana-851	44	25	work	work	NOUN
cana-851	44	26	.	.	PUNCT
cana-851	45	1	the	the	DET
cana-851	45	2	effect	effect	NOUN
cana-851	45	3	of	of	ADP
cana-851	45	4	training	training	NOUN
cana-851	45	5	and	and	CCONJ
cana-851	45	6	testing	testing	NOUN
cana-851	45	7	data	datum	NOUN
cana-851	45	8	splitting	splitting	NOUN
cana-851	45	9	can	can	AUX
cana-851	45	10	be	be	AUX
cana-851	45	11	checked[11	checked[11	VERB
cana-851	45	12	]	]	PUNCT
cana-851	45	13	.	.	PUNCT
cana-851	46	1	this	this	DET
cana-851	46	2	research	research	NOUN
cana-851	46	3	proposes	propose	VERB
cana-851	46	4	a	a	DET
cana-851	46	5	flower	flower	NOUN
cana-851	46	6	image	image	NOUN
cana-851	46	7	classification	classification	NOUN
cana-851	46	8	approach	approach	NOUN
cana-851	46	9	it	it	PRON
cana-851	46	10	use	use	VERB
cana-851	46	11	a	a	DET
cana-851	46	12	pre	pre	ADJ
cana-851	46	13	-	-	ADJ
cana-851	46	14	trained	train	VERB
cana-851	46	15	cnn	cnn	NOUN
cana-851	46	16	(	(	PUNCT
cana-851	46	17	convolutional	convolutional	ADJ
cana-851	46	18	neural	neural	ADJ
cana-851	46	19	network	network	NOUN
cana-851	46	20	)	)	PUNCT
cana-851	46	21	alexnet	alexnet	NOUN
cana-851	46	22	as	as	ADP
cana-851	46	23	a	a	DET
cana-851	46	24	tool	tool	NOUN
cana-851	46	25	to	to	PART
cana-851	46	26	extract	extract	VERB
cana-851	46	27	features	feature	NOUN
cana-851	46	28	.	.	PUNCT
cana-851	47	1	the	the	DET
cana-851	47	2	approach	approach	NOUN
cana-851	47	3	relies	rely	VERB
cana-851	47	4	on	on	ADP
cana-851	47	5	certain	certain	ADJ
cana-851	47	6	deep	deep	ADJ
cana-851	47	7	features	feature	NOUN
cana-851	47	8	and	and	CCONJ
cana-851	47	9	multiclass	multiclass	ADJ
cana-851	47	10	svm[16	svm[16	NOUN
cana-851	47	11	]	]	PUNCT
cana-851	47	12	.	.	PUNCT
cana-851	48	1	the	the	DET
cana-851	48	2	problem	problem	NOUN
cana-851	48	3	statement	statement	NOUN
cana-851	48	4	in	in	ADP
cana-851	48	5	the	the	DET
cana-851	48	6	first	first	ADJ
cana-851	48	7	source	source	NOUN
cana-851	48	8	is	be	AUX
cana-851	48	9	related	relate	VERB
cana-851	48	10	to	to	ADP
cana-851	48	11	the	the	DET
cana-851	48	12	classification	classification	NOUN
cana-851	48	13	of	of	ADP
cana-851	48	14	generating	generate	VERB
cana-851	48	15	sunflower	sunflower	NOUN
cana-851	48	16	images	image	NOUN
cana-851	48	17	by	by	ADP
cana-851	48	18	employing	employ	VERB
cana-851	48	19	a	a	DET
cana-851	48	20	feature	feature	NOUN
cana-851	48	21	extraction	extraction	NOUN
cana-851	48	22	approach	approach	NOUN
cana-851	48	23	based	base	VERB
cana-851	48	24	on	on	ADP
cana-851	48	25	first	first	ADJ
cana-851	48	26	-	-	PUNCT
cana-851	48	27	order	order	NOUN
cana-851	48	28	methods	method	NOUN
cana-851	48	29	and	and	CCONJ
cana-851	48	30	the	the	DET
cana-851	48	31	multiclass	multiclass	ADJ
cana-851	48	32	svm	svm	PROPN
cana-851	48	33	identification	identification	NOUN
cana-851	48	34	algorithm	algorithm	NOUN
cana-851	48	35	.	.	PUNCT
cana-851	49	1	the	the	DET
cana-851	49	2	aim	aim	NOUN
cana-851	49	3	is	be	AUX
cana-851	49	4	to	to	PART
cana-851	49	5	distinguish	distinguish	VERB
cana-851	49	6	between	between	ADP
cana-851	49	7	different	different	ADJ
cana-851	49	8	types	type	NOUN
cana-851	49	9	of	of	ADP
cana-851	49	10	sunflowers	sunflower	NOUN
cana-851	49	11	,	,	PUNCT
cana-851	49	12	which	which	PRON
cana-851	49	13	can	can	AUX
cana-851	49	14	be	be	AUX
cana-851	49	15	challenging	challenge	VERB
cana-851	49	16	due	due	ADJ
cana-851	49	17	to	to	ADP
cana-851	49	18	their	their	PRON
cana-851	49	19	similar	similar	ADJ
cana-851	49	20	shape	shape	NOUN
cana-851	49	21	.	.	PUNCT
cana-851	50	1	the	the	DET
cana-851	50	2	study	study	NOUN
cana-851	50	3	focuses	focus	VERB
cana-851	50	4	on	on	ADP
cana-851	50	5	using	use	VERB
cana-851	50	6	mean	mean	NOUN
cana-851	50	7	,	,	PUNCT
cana-851	50	8	skewness	skewness	NOUN
cana-851	50	9	,	,	PUNCT
cana-851	50	10	variance	variance	NOUN
cana-851	50	11	,	,	PUNCT
cana-851	50	12	kurtosis	kurtosis	NOUN
cana-851	50	13	,	,	PUNCT
cana-851	50	14	and	and	CCONJ
cana-851	50	15	entropy	entropy	NOUN
cana-851	50	16	as	as	ADP
cana-851	50	17	input	input	NOUN
cana-851	50	18	features	feature	NOUN
cana-851	50	19	for	for	ADP
cana-851	50	20	classification	classification	NOUN
cana-851	50	21	,	,	PUNCT
cana-851	50	22	and	and	CCONJ
cana-851	50	23	the	the	DET
cana-851	50	24	model	model	NOUN
cana-851	50	25	achieved	achieve	VERB
cana-851	50	26	an	an	DET
cana-851	50	27	average	average	ADJ
cana-851	50	28	accuracy	accuracy	NOUN
cana-851	50	29	of	of	ADP
cana-851	50	30	79%[17	79%[17	PROPN
cana-851	50	31	]	]	PUNCT
cana-851	50	32	.	.	PUNCT
cana-851	51	1	the	the	DET
cana-851	51	2	focus	focus	NOUN
cana-851	51	3	of	of	ADP
cana-851	51	4	the	the	DET
cana-851	51	5	paper	paper	NOUN
cana-851	51	6	is	be	AUX
cana-851	51	7	on	on	ADP
cana-851	51	8	comparing	compare	VERB
cana-851	51	9	the	the	DET
cana-851	51	10	performance	performance	NOUN
cana-851	51	11	of	of	ADP
cana-851	51	12	svm	svm	PROPN
cana-851	51	13	and	and	CCONJ
cana-851	51	14	laf	laf	PROPN
cana-851	51	15	regarding	regard	VERB
cana-851	51	16	the	the	DET
cana-851	51	17	precision	precision	NOUN
cana-851	51	18	in	in	ADP
cana-851	51	19	identifying	identify	VERB
cana-851	51	20	support	support	NOUN
cana-851	51	21	vectors	vector	NOUN
cana-851	51	22	,	,	PUNCT
cana-851	51	23	with	with	ADP
cana-851	51	24	svm	svm	ADJ
cana-851	51	25	demonstrating	demonstrate	VERB
cana-851	51	26	superior	superior	ADJ
cana-851	51	27	performance	performance	NOUN
cana-851	51	28	/	/	PUNCT
cana-851	51	29	the	the	DET
cana-851	51	30	researchers	researcher	NOUN
cana-851	51	31	employ	employ	VERB
cana-851	51	32	both	both	CCONJ
cana-851	51	33	the	the	DET
cana-851	51	34	innovative	innovative	ADJ
cana-851	51	35	support	support	NOUN
cana-851	51	36	vector	vector	NOUN
cana-851	51	37	machine	machine	NOUN
cana-851	51	38	technique	technique	NOUN
cana-851	51	39	and	and	CCONJ
cana-851	51	40	the	the	DET
cana-851	51	41	logistic	logistic	ADJ
cana-851	51	42	activation	activation	NOUN
cana-851	51	43	function	function	NOUN
cana-851	51	44	technique	technique	NOUN
cana-851	51	45	to	to	PART
cana-851	51	46	evaluate	evaluate	VERB
cana-851	51	47	the	the	DET
cana-851	51	48	iris	iris	NOUN
cana-851	51	49	dataset[18	dataset[18	PROPN
cana-851	51	50	]	]	PUNCT
cana-851	51	51	.	.	PUNCT
cana-851	52	1	the	the	DET
cana-851	52	2	study	study	NOUN
cana-851	52	3	aims	aim	VERB
cana-851	52	4	to	to	PART
cana-851	52	5	explore	explore	VERB
cana-851	52	6	the	the	DET
cana-851	52	7	effectiveness	effectiveness	NOUN
cana-851	52	8	of	of	ADP
cana-851	52	9	utilizing	utilize	VERB
cana-851	52	10	local	local	ADJ
cana-851	52	11	binary	binary	ADJ
cana-851	52	12	pattern	pattern	NOUN
cana-851	52	13	(	(	PUNCT
cana-851	52	14	lbp	lbp	PROPN
cana-851	52	15	)	)	PUNCT
cana-851	52	16	and	and	CCONJ
cana-851	52	17	speeded	speed	VERB
cana-851	52	18	-	-	PUNCT
cana-851	52	19	up	up	ADP
cana-851	52	20	robust	robust	ADJ
cana-851	52	21	features	feature	NOUN
cana-851	52	22	(	(	PUNCT
cana-851	52	23	surf	surf	NOUN
cana-851	52	24	)	)	PUNCT
cana-851	52	25	as	as	ADP
cana-851	52	26	feature	feature	NOUN
cana-851	52	27	descriptors	descriptor	NOUN
cana-851	52	28	for	for	ADP
cana-851	52	29	flower	flower	NOUN
cana-851	52	30	classification[19	classification[19	NOUN
cana-851	52	31	]	]	PUNCT
cana-851	52	32	.	.	PUNCT
cana-851	53	1	figure	figure	NOUN
cana-851	53	2	2	2	NUM
cana-851	53	3	.	.	PUNCT
cana-851	53	4	highlight	highlight	VERB
cana-851	53	5	the	the	DET
cana-851	53	6	number	number	NOUN
cana-851	53	7	of	of	ADP
cana-851	53	8	challenges	challenge	NOUN
cana-851	53	9	solved	solve	VERB
cana-851	53	10	using	use	VERB
cana-851	53	11	ml	ml	NOUN
cana-851	53	12	based	base	VERB
cana-851	53	13	on	on	ADP
cana-851	53	14	each	each	DET
cana-851	53	15	application	application	NOUN
cana-851	53	16	figure	figure	NOUN
cana-851	53	17	2	2	NUM
cana-851	53	18	.	.	PUNCT
cana-851	53	19	number	number	NOUN
cana-851	53	20	of	of	ADP
cana-851	53	21	applications	application	NOUN
cana-851	53	22	utilized	utilize	VERB
cana-851	53	23	machine	machine	NOUN
cana-851	53	24	learning	learn	VERB
cana-851	53	25	in	in	ADP
cana-851	53	26	literature	literature	NOUN
cana-851	53	27	review	review	NOUN
cana-851	53	28	communications	communication	NOUN
cana-851	53	29	on	on	ADP
cana-851	53	30	applied	apply	VERB
cana-851	53	31	nonlinear	nonlinear	ADJ
cana-851	53	32	analysis	analysis	NOUN
cana-851	53	33	issn	issn	NOUN
cana-851	53	34	:	:	PUNCT
cana-851	53	35	1074	1074	NUM
cana-851	53	36	-	-	PUNCT
cana-851	53	37	133x	133x	NUM
cana-851	53	38	vol	vol	NOUN
cana-851	53	39	31	31	NUM
cana-851	53	40	no	no	NOUN
cana-851	53	41	.	.	PUNCT
cana-851	54	1	4s	4s	NUM
cana-851	54	2	(	(	PUNCT
cana-851	54	3	2024	2024	NUM
cana-851	54	4	)	)	PUNCT
cana-851	54	5	274	274	NUM
cana-851	54	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	54	7	4	4	NUM
cana-851	54	8	.	.	X
cana-851	54	9	challenge	challenge	NOUN
cana-851	54	10	solved	solve	VERB
cana-851	54	11	using	use	VERB
cana-851	54	12	dl	dl	PROPN
cana-851	54	13	the	the	DET
cana-851	54	14	sample	sample	NOUN
cana-851	54	15	size	size	NOUN
cana-851	54	16	used	use	VERB
cana-851	54	17	in	in	ADP
cana-851	54	18	the	the	DET
cana-851	54	19	experiments	experiment	NOUN
cana-851	54	20	is	be	AUX
cana-851	54	21	relatively	relatively	ADV
cana-851	54	22	small	small	ADJ
cana-851	54	23	,	,	PUNCT
cana-851	54	24	with	with	ADP
cana-851	54	25	5120	5120	NUM
cana-851	54	26	training	training	NOUN
cana-851	54	27	images	image	NOUN
cana-851	54	28	and	and	CCONJ
cana-851	54	29	1280	1280	NUM
cana-851	54	30	test	test	NOUN
cana-851	54	31	images	image	NOUN
cana-851	54	32	.	.	PUNCT
cana-851	55	1	this	this	PRON
cana-851	55	2	may	may	AUX
cana-851	55	3	limit	limit	VERB
cana-851	55	4	the	the	DET
cana-851	55	5	generalizability	generalizability	NOUN
cana-851	55	6	of	of	ADP
cana-851	55	7	the	the	DET
cana-851	55	8	results	result	NOUN
cana-851	55	9	.	.	PUNCT
cana-851	56	1	the	the	DET
cana-851	56	2	paper	paper	NOUN
cana-851	56	3	does	do	AUX
cana-851	56	4	not	not	PART
cana-851	56	5	discuss	discuss	VERB
cana-851	56	6	the	the	DET
cana-851	56	7	potential	potential	ADJ
cana-851	56	8	impact	impact	NOUN
cana-851	56	9	or	or	CCONJ
cana-851	56	10	implications	implication	NOUN
cana-851	56	11	of	of	ADP
cana-851	56	12	the	the	DET
cana-851	56	13	proposed	propose	VERB
cana-851	56	14	approach	approach	NOUN
cana-851	56	15	beyond	beyond	ADP
cana-851	56	16	its	its	PRON
cana-851	56	17	application	application	NOUN
cana-851	56	18	in	in	ADP
cana-851	56	19	local	local	ADJ
cana-851	56	20	flower	flower	NOUN
cana-851	56	21	classification	classification	NOUN
cana-851	56	22	.	.	PUNCT
cana-851	57	1	/	/	PUNCT
cana-851	57	2	the	the	DET
cana-851	57	3	issue	issue	NOUN
cana-851	57	4	has	have	AUX
cana-851	57	5	been	be	AUX
cana-851	57	6	tackled	tackle	VERB
cana-851	57	7	and	and	CCONJ
cana-851	57	8	a	a	DET
cana-851	57	9	method	method	NOUN
cana-851	57	10	has	have	AUX
cana-851	57	11	been	be	AUX
cana-851	57	12	suggested	suggest	VERB
cana-851	57	13	to	to	PART
cana-851	57	14	identify	identify	VERB
cana-851	57	15	the	the	DET
cana-851	57	16	indigenous	indigenous	ADJ
cana-851	57	17	flowers	flower	NOUN
cana-851	57	18	of	of	ADP
cana-851	57	19	bangladesh[20	bangladesh[20	NOUN
cana-851	57	20	]	]	PUNCT
cana-851	57	21	.	.	PUNCT
cana-851	58	1	efficiently	efficiently	ADV
cana-851	58	2	performing	perform	VERB
cana-851	58	3	flower	flower	NOUN
cana-851	58	4	image	image	NOUN
cana-851	58	5	analysis	analysis	NOUN
cana-851	58	6	involving	involve	VERB
cana-851	58	7	the	the	DET
cana-851	58	8	detection	detection	NOUN
cana-851	58	9	,	,	PUNCT
cana-851	58	10	location	location	NOUN
cana-851	58	11	,	,	PUNCT
cana-851	58	12	and	and	CCONJ
cana-851	58	13	classification	classification	NOUN
cana-851	58	14	of	of	ADP
cana-851	58	15	multiple	multiple	ADJ
cana-851	58	16	flower	flower	NOUN
cana-851	58	17	classes	class	NOUN
cana-851	58	18	,	,	PUNCT
cana-851	58	19	collection	collection	NOUN
cana-851	58	20	is	be	AUX
cana-851	58	21	a	a	DET
cana-851	58	22	challenging	challenging	ADJ
cana-851	58	23	task	task	NOUN
cana-851	58	24	in	in	ADP
cana-851	58	25	the	the	DET
cana-851	58	26	realm	realm	NOUN
cana-851	58	27	of	of	ADP
cana-851	58	28	agriculture[21	agriculture[21	NOUN
cana-851	58	29	]	]	PUNCT
cana-851	58	30	.	.	PUNCT
cana-851	59	1	the	the	DET
cana-851	59	2	study	study	NOUN
cana-851	59	3	focuses	focus	VERB
cana-851	59	4	on	on	ADP
cana-851	59	5	a	a	DET
cana-851	59	6	specific	specific	ADJ
cana-851	59	7	set	set	NOUN
cana-851	59	8	of	of	ADP
cana-851	59	9	deep	deep	ADJ
cana-851	59	10	learning	learning	NOUN
cana-851	59	11	models	model	NOUN
cana-851	59	12	(	(	PUNCT
cana-851	59	13	mobilenet	mobilenet	NOUN
cana-851	59	14	,	,	PUNCT
cana-851	59	15	densenet	densenet	NOUN
cana-851	59	16	,	,	PUNCT
cana-851	59	17	inception	inception	NOUN
cana-851	59	18	,	,	PUNCT
cana-851	59	19	and	and	CCONJ
cana-851	59	20	resnet	resnet	NOUN
cana-851	59	21	)	)	PUNCT
cana-851	59	22	and	and	CCONJ
cana-851	59	23	optimizers	optimizer	NOUN
cana-851	59	24	(	(	PUNCT
cana-851	59	25	adam	adam	PROPN
cana-851	59	26	and	and	CCONJ
cana-851	59	27	sgd	sgd	NOUN
cana-851	59	28	)	)	PUNCT
cana-851	59	29	,	,	PUNCT
cana-851	59	30	without	without	ADP
cana-851	59	31	exploring	explore	VERB
cana-851	59	32	the	the	DET
cana-851	59	33	potential	potential	ADJ
cana-851	59	34	benefits	benefit	NOUN
cana-851	59	35	of	of	ADP
cana-851	59	36	other	other	ADJ
cana-851	59	37	models	model	NOUN
cana-851	59	38	or	or	CCONJ
cana-851	59	39	optimization	optimization	NOUN
cana-851	59	40	techniques./	techniques./	VERB
cana-851	59	41	the	the	DET
cana-851	59	42	researchers	researcher	NOUN
cana-851	59	43	aim	aim	VERB
cana-851	59	44	to	to	PART
cana-851	59	45	develop	develop	VERB
cana-851	59	46	an	an	DET
cana-851	59	47	application	application	NOUN
cana-851	59	48	that	that	PRON
cana-851	59	49	can	can	AUX
cana-851	59	50	accurately	accurately	ADV
cana-851	59	51	identify	identify	VERB
cana-851	59	52	different	different	ADJ
cana-851	59	53	flower	flower	NOUN
cana-851	59	54	species	specie	NOUN
cana-851	59	55	based	base	VERB
cana-851	59	56	on	on	ADP
cana-851	59	57	their	their	PRON
cana-851	59	58	images[22	images[22	NOUN
cana-851	59	59	]	]	PUNCT
cana-851	59	60	.	.	PUNCT
cana-851	60	1	however	however	ADV
cana-851	60	2	,	,	PUNCT
cana-851	60	3	keeping	keep	VERB
cana-851	60	4	the	the	DET
cana-851	60	5	number	number	NOUN
cana-851	60	6	of	of	ADP
cana-851	60	7	epochs	epoch	NOUN
cana-851	60	8	fixed	fix	VERB
cana-851	60	9	,	,	PUNCT
cana-851	60	10	increasing	increase	VERB
cana-851	60	11	the	the	DET
cana-851	60	12	depth	depth	NOUN
cana-851	60	13	and	and	CCONJ
cana-851	60	14	complexity	complexity	NOUN
cana-851	60	15	of	of	ADP
cana-851	60	16	a	a	DET
cana-851	60	17	network	network	NOUN
cana-851	60	18	substantially	substantially	ADV
cana-851	60	19	increases	increase	VERB
cana-851	60	20	the	the	DET
cana-851	60	21	computing	computing	NOUN
cana-851	60	22	time	time	NOUN
cana-851	60	23	for	for	ADP
cana-851	60	24	training	train	VERB
cana-851	60	25	the	the	DET
cana-851	60	26	network[23	network[23	PROPN
cana-851	60	27	]	]	PUNCT
cana-851	60	28	.	.	PUNCT
cana-851	61	1	the	the	DET
cana-851	61	2	paper	paper	NOUN
cana-851	61	3	acknowledges	acknowledge	VERB
cana-851	61	4	the	the	DET
cana-851	61	5	limitations	limitation	NOUN
cana-851	61	6	of	of	ADP
cana-851	61	7	flower	flower	NOUN
cana-851	61	8	classification	classification	NOUN
cana-851	61	9	,	,	PUNCT
cana-851	61	10	examples	example	NOUN
cana-851	61	11	of	of	ADP
cana-851	61	12	challenges	challenge	NOUN
cana-851	61	13	in	in	ADP
cana-851	61	14	floral	floral	ADJ
cana-851	61	15	picture	picture	NOUN
cana-851	61	16	analysis	analysis	NOUN
cana-851	61	17	include	include	VERB
cana-851	61	18	inter	inter	ADJ
cana-851	61	19	-	-	ADJ
cana-851	61	20	class	class	ADJ
cana-851	61	21	similarity	similarity	NOUN
cana-851	61	22	,	,	PUNCT
cana-851	61	23	significant	significant	ADJ
cana-851	61	24	intra	intra	ADJ
cana-851	61	25	-	-	ADJ
cana-851	61	26	class	class	ADJ
cana-851	61	27	variance	variance	NOUN
cana-851	61	28	,	,	PUNCT
cana-851	61	29	non	non	ADJ
cana-851	61	30	-	-	ADJ
cana-851	61	31	rigid	rigid	ADJ
cana-851	61	32	deformation	deformation	NOUN
cana-851	61	33	,	,	PUNCT
cana-851	61	34	changes	change	NOUN
cana-851	61	35	in	in	ADP
cana-851	61	36	illumination	illumination	NOUN
cana-851	61	37	,	,	PUNCT
cana-851	61	38	variations	variation	NOUN
cana-851	61	39	in	in	ADP
cana-851	61	40	viewpoint	viewpoint	NOUN
cana-851	61	41	,	,	PUNCT
cana-851	61	42	occlusions	occlusion	NOUN
cana-851	61	43	,	,	PUNCT
cana-851	61	44	and	and	CCONJ
cana-851	61	45	scale	scale	NOUN
cana-851	61	46	,	,	PUNCT
cana-851	61	47	the	the	DET
cana-851	61	48	background	background	NOUN
cana-851	61	49	of	of	ADP
cana-851	61	50	the	the	DET
cana-851	61	51	images	image	NOUN
cana-851	61	52	also	also	ADV
cana-851	61	53	poses	pose	VERB
cana-851	61	54	a	a	DET
cana-851	61	55	challenge	challenge	NOUN
cana-851	61	56	in	in	ADP
cana-851	61	57	flower	flower	NOUN
cana-851	61	58	classification	classification	NOUN
cana-851	61	59	[	[	X
cana-851	61	60	24	24	NUM
cana-851	61	61	]	]	PUNCT
cana-851	61	62	.	.	PUNCT
cana-851	62	1	training	train	VERB
cana-851	62	2	deep	deep	ADJ
cana-851	62	3	neural	neural	ADJ
cana-851	62	4	networks	network	NOUN
cana-851	62	5	can	can	AUX
cana-851	62	6	be	be	AUX
cana-851	62	7	computationally	computationally	ADV
cana-851	62	8	expensive	expensive	ADJ
cana-851	62	9	and	and	CCONJ
cana-851	62	10	timeconsuming	timeconsuming	ADJ
cana-851	62	11	,	,	PUNCT
cana-851	62	12	especially	especially	ADV
cana-851	62	13	when	when	SCONJ
cana-851	62	14	starting	start	VERB
cana-851	62	15	from	from	ADP
cana-851	62	16	scratch	scratch	NOUN
cana-851	62	17	,	,	PUNCT
cana-851	62	18	fine	fine	ADV
cana-851	62	19	-	-	PUNCT
cana-851	62	20	tuning	tune	VERB
cana-851	62	21	a	a	DET
cana-851	62	22	pre	pre	ADJ
cana-851	62	23	-	-	ADJ
cana-851	62	24	trained	train	VERB
cana-851	62	25	model	model	NOUN
cana-851	62	26	may	may	AUX
cana-851	62	27	not	not	PART
cana-851	62	28	always	always	ADV
cana-851	62	29	guarantee	guarantee	VERB
cana-851	62	30	improved	improved	ADJ
cana-851	62	31	performance	performance	NOUN
cana-851	62	32	,	,	PUNCT
cana-851	62	33	as	as	SCONJ
cana-851	62	34	it	it	PRON
cana-851	62	35	depends	depend	VERB
cana-851	62	36	on	on	ADP
cana-851	62	37	the	the	DET
cana-851	62	38	quality	quality	NOUN
cana-851	62	39	and	and	CCONJ
cana-851	62	40	relevance	relevance	NOUN
cana-851	62	41	of	of	ADP
cana-851	62	42	the	the	DET
cana-851	62	43	pre	pre	ADJ
cana-851	62	44	-	-	ADJ
cana-851	62	45	trained	train	VERB
cana-851	62	46	model	model	NOUN
cana-851	62	47	to	to	ADP
cana-851	62	48	the	the	DET
cana-851	62	49	specific	specific	ADJ
cana-851	62	50	task	task	NOUN
cana-851	62	51	/.	/.	PUNCT
cana-851	63	1	hence	hence	ADV
cana-851	63	2	,	,	PUNCT
cana-851	63	3	this	this	DET
cana-851	63	4	approach	approach	NOUN
cana-851	63	5	presents	present	VERB
cana-851	63	6	an	an	DET
cana-851	63	7	intriguing	intriguing	ADJ
cana-851	63	8	opportunity	opportunity	NOUN
cana-851	63	9	to	to	PART
cana-851	63	10	address	address	VERB
cana-851	63	11	the	the	DET
cana-851	63	12	issue	issue	NOUN
cana-851	63	13	of	of	ADP
cana-851	63	14	floral	floral	ADJ
cana-851	63	15	categorization	categorization	NOUN
cana-851	63	16	.	.	PUNCT
cana-851	64	1	the	the	DET
cana-851	64	2	pre	pre	ADJ
cana-851	64	3	-	-	ADJ
cana-851	64	4	trained	train	VERB
cana-851	64	5	model	model	NOUN
cana-851	64	6	has	have	AUX
cana-851	64	7	undergone	undergo	VERB
cana-851	64	8	training	training	NOUN
cana-851	64	9	and	and	CCONJ
cana-851	64	10	testing	testing	NOUN
cana-851	64	11	using	use	VERB
cana-851	64	12	the	the	DET
cana-851	64	13	102	102	NUM
cana-851	64	14	-	-	PUNCT
cana-851	64	15	oxford	oxford	ADJ
cana-851	64	16	flowers	flower	NOUN
cana-851	64	17	dataset	dataset	VERB
cana-851	64	18	,	,	PUNCT
cana-851	64	19	resulting	result	VERB
cana-851	64	20	in	in	ADP
cana-851	64	21	a	a	DET
cana-851	64	22	superior	superior	ADJ
cana-851	64	23	accuracy	accuracy	NOUN
cana-851	64	24	of	of	ADP
cana-851	64	25	98.6	98.6	NUM
cana-851	64	26	%	%	NOUN
cana-851	64	27	when	when	SCONJ
cana-851	64	28	compared	compare	VERB
cana-851	64	29	to	to	ADP
cana-851	64	30	other	other	ADJ
cana-851	64	31	methods	method	NOUN
cana-851	64	32	.	.	PUNCT
cana-851	65	1	we	we	PRON
cana-851	65	2	utilize	utilize	VERB
cana-851	65	3	the	the	DET
cana-851	65	4	pytorch	pytorch	NOUN
cana-851	65	5	framework	framework	NOUN
cana-851	65	6	.	.	PUNCT
cana-851	66	1	pytorch	pytorch	NOUN
cana-851	66	2	is	be	AUX
cana-851	66	3	largely	largely	ADV
cana-851	66	4	developed	develop	VERB
cana-851	66	5	by	by	ADP
cana-851	66	6	facebook	facebook	PROPN
cana-851	66	7	's	's	PART
cana-851	66	8	ai	ai	PROPN
cana-851	66	9	research	research	NOUN
cana-851	66	10	(	(	PUNCT
cana-851	66	11	fair	fair	ADJ
cana-851	66	12	)	)	PUNCT
cana-851	66	13	team	team	NOUN
cana-851	66	14	and	and	CCONJ
cana-851	66	15	serves	serve	VERB
cana-851	66	16	as	as	ADP
cana-851	66	17	a	a	DET
cana-851	66	18	deep	deep	ADJ
cana-851	66	19	learning	learning	NOUN
cana-851	66	20	research	research	NOUN
cana-851	66	21	framework	framework	NOUN
cana-851	66	22	that	that	PRON
cana-851	66	23	offers	offer	VERB
cana-851	66	24	exceptional	exceptional	ADJ
cana-851	66	25	flexibility	flexibility	NOUN
cana-851	66	26	and	and	CCONJ
cana-851	66	27	speed[9	speed[9	NOUN
cana-851	66	28	]	]	PUNCT
cana-851	66	29	.	.	PUNCT
cana-851	67	1	limited	limited	ADJ
cana-851	67	2	accuracy	accuracy	NOUN
cana-851	67	3	compared	compare	VERB
cana-851	67	4	to	to	ADP
cana-851	67	5	other	other	ADJ
cana-851	67	6	approaches	approach	NOUN
cana-851	67	7	:	:	PUNCT
cana-851	67	8	the	the	DET
cana-851	67	9	accuracy	accuracy	NOUN
cana-851	67	10	reported	report	VERB
cana-851	67	11	on	on	ADP
cana-851	67	12	flower	flower	NOUN
cana-851	67	13	classification	classification	NOUN
cana-851	67	14	using	use	VERB
cana-851	67	15	the	the	DET
cana-851	67	16	proposed	propose	VERB
cana-851	67	17	method	method	NOUN
cana-851	67	18	is	be	AUX
cana-851	67	19	limited	limit	VERB
cana-851	67	20	compared	compare	VERB
cana-851	67	21	to	to	ADP
cana-851	67	22	other	other	ADJ
cana-851	67	23	published	publish	VERB
cana-851	67	24	works	work	NOUN
cana-851	67	25	,	,	PUNCT
cana-851	67	26	such	such	ADJ
cana-851	67	27	as	as	ADP
cana-851	67	28	complexity	complexity	NOUN
cana-851	67	29	for	for	ADP
cana-851	67	30	handling	handle	VERB
cana-851	67	31	certain	certain	ADJ
cana-851	67	32	tasks	task	NOUN
cana-851	67	33	:	:	PUNCT
cana-851	67	34	deeper	deep	ADJ
cana-851	67	35	models	model	NOUN
cana-851	67	36	like	like	ADP
cana-851	67	37	resnet	resnet	NOUN
cana-851	67	38	are	be	AUX
cana-851	67	39	generally	generally	ADV
cana-851	67	40	too	too	ADV
cana-851	67	41	complex	complex	ADJ
cana-851	67	42	to	to	PART
cana-851	67	43	handle	handle	VERB
cana-851	67	44	the	the	DET
cana-851	67	45	flower	flower	NOUN
cana-851	67	46	classification	classification	NOUN
cana-851	67	47	task	task	NOUN
cana-851	67	48	due	due	ADP
cana-851	67	49	to	to	ADP
cana-851	67	50	the	the	DET
cana-851	67	51	large	large	ADJ
cana-851	67	52	number	number	NOUN
cana-851	67	53	of	of	ADP
cana-851	67	54	parameters	parameter	NOUN
cana-851	67	55	,	,	PUNCT
cana-851	67	56	making	make	VERB
cana-851	67	57	them	they	PRON
cana-851	67	58	less	less	ADV
cana-851	67	59	suitable	suitable	ADJ
cana-851	67	60	for	for	ADP
cana-851	67	61	this	this	DET
cana-851	67	62	specific	specific	ADJ
cana-851	67	63	application	application	NOUN
cana-851	67	64	/	/	SYM
cana-851	67	65	flower	flower	NOUN
cana-851	67	66	classification	classification	NOUN
cana-851	67	67	is	be	AUX
cana-851	67	68	a	a	DET
cana-851	67	69	formidable	formidable	ADJ
cana-851	67	70	challenge	challenge	NOUN
cana-851	67	71	due	due	ADP
cana-851	67	72	to	to	ADP
cana-851	67	73	the	the	DET
cana-851	67	74	vast	vast	ADJ
cana-851	67	75	array	array	NOUN
cana-851	67	76	of	of	ADP
cana-851	67	77	flower	flower	NOUN
cana-851	67	78	species	specie	NOUN
cana-851	67	79	that	that	PRON
cana-851	67	80	exhibit	exhibit	VERB
cana-851	67	81	comparable	comparable	ADJ
cana-851	67	82	characteristics	characteristic	NOUN
cana-851	67	83	in	in	ADP
cana-851	67	84	terms	term	NOUN
cana-851	67	85	of	of	ADP
cana-851	67	86	shape	shape	NOUN
cana-851	67	87	,	,	PUNCT
cana-851	67	88	look	look	VERB
cana-851	67	89	,	,	PUNCT
cana-851	67	90	and	and	CCONJ
cana-851	67	91	their	their	PRON
cana-851	67	92	surroundings	surrounding	NOUN
cana-851	67	93	,	,	PUNCT
cana-851	67	94	such	such	ADJ
cana-851	67	95	as	as	ADP
cana-851	67	96	leaves	leave	NOUN
cana-851	67	97	and	and	CCONJ
cana-851	67	98	grass[6	grass[6	NOUN
cana-851	67	99	]	]	PUNCT
cana-851	67	100	.	.	PUNCT
cana-851	68	1	the	the	DET
cana-851	68	2	yolov5	yolov5	NOUN
cana-851	68	3	model	model	NOUN
cana-851	68	4	used	use	VERB
cana-851	68	5	in	in	ADP
cana-851	68	6	the	the	DET
cana-851	68	7	research	research	NOUN
cana-851	68	8	,	,	PUNCT
cana-851	68	9	although	although	SCONJ
cana-851	68	10	effective	effective	ADJ
cana-851	68	11	,	,	PUNCT
cana-851	68	12	may	may	AUX
cana-851	68	13	have	have	VERB
cana-851	68	14	a	a	DET
cana-851	68	15	complex	complex	ADJ
cana-851	68	16	architecture	architecture	NOUN
cana-851	68	17	that	that	PRON
cana-851	68	18	requires	require	VERB
cana-851	68	19	careful	careful	ADJ
cana-851	68	20	implementation	implementation	NOUN
cana-851	68	21	and	and	CCONJ
cana-851	68	22	understanding/	understanding/	NUM
cana-851	68	23	the	the	DET
cana-851	68	24	project	project	NOUN
cana-851	68	25	aims	aim	VERB
cana-851	68	26	to	to	PART
cana-851	68	27	accomplish	accomplish	VERB
cana-851	68	28	precise	precise	ADJ
cana-851	68	29	picture	picture	NOUN
cana-851	68	30	categorization	categorization	NOUN
cana-851	68	31	of	of	ADP
cana-851	68	32	flowers	flower	NOUN
cana-851	68	33	by	by	ADP
cana-851	68	34	taking	take	VERB
cana-851	68	35	into	into	ADP
cana-851	68	36	account	account	NOUN
cana-851	68	37	the	the	DET
cana-851	68	38	similarities	similarity	NOUN
cana-851	68	39	between	between	ADP
cana-851	68	40	different	different	ADJ
cana-851	68	41	classes	class	NOUN
cana-851	68	42	and	and	CCONJ
cana-851	68	43	the	the	DET
cana-851	68	44	differences	difference	NOUN
cana-851	68	45	within	within	ADP
cana-851	68	46	the	the	DET
cana-851	68	47	same	same	ADJ
cana-851	68	48	class	class	NOUN
cana-851	68	49	in	in	ADP
cana-851	68	50	floral	floral	ADJ
cana-851	68	51	photos	photo	NOUN
cana-851	68	52	.	.	PUNCT
cana-851	69	1	the	the	DET
cana-851	69	2	objective	objective	NOUN
cana-851	69	3	is	be	AUX
cana-851	69	4	to	to	PART
cana-851	69	5	employ	employ	VERB
cana-851	69	6	the	the	DET
cana-851	69	7	yolov5	yolov5	NOUN
cana-851	69	8	object	object	NOUN
cana-851	69	9	identification	identification	NOUN
cana-851	69	10	algorithm	algorithm	NOUN
cana-851	69	11	to	to	PART
cana-851	69	12	create	create	VERB
cana-851	69	13	a	a	DET
cana-851	69	14	profound	profound	ADJ
cana-851	69	15	learning	learning	NOUN
cana-851	69	16	technique	technique	NOUN
cana-851	69	17	that	that	PRON
cana-851	69	18	can	can	AUX
cana-851	69	19	accurately	accurately	ADV
cana-851	69	20	recognize	recognize	VERB
cana-851	69	21	and	and	CCONJ
cana-851	69	22	classify	classify	VERB
cana-851	69	23	five	five	NUM
cana-851	69	24	distinct	distinct	ADJ
cana-851	69	25	categories	category	NOUN
cana-851	69	26	of	of	ADP
cana-851	69	27	flowers	flower	NOUN
cana-851	69	28	within	within	ADP
cana-851	69	29	the	the	DET
cana-851	69	30	dataset	dataset	NOUN
cana-851	69	31	.	.	PUNCT
cana-851	70	1	the	the	DET
cana-851	70	2	research	research	NOUN
cana-851	70	3	aims	aim	VERB
cana-851	70	4	to	to	PART
cana-851	70	5	address	address	VERB
cana-851	70	6	the	the	DET
cana-851	70	7	challenges	challenge	NOUN
cana-851	70	8	of	of	ADP
cana-851	70	9	overlap	overlap	NOUN
cana-851	70	10	and	and	CCONJ
cana-851	70	11	occlusion	occlusion	NOUN
cana-851	70	12	in	in	ADP
cana-851	70	13	flower	flower	NOUN
cana-851	70	14	images	image	NOUN
cana-851	70	15	and	and	CCONJ
cana-851	70	16	enhance	enhance	VERB
cana-851	70	17	the	the	DET
cana-851	70	18	detection	detection	NOUN
cana-851	70	19	of	of	ADP
cana-851	70	20	blocked	block	VERB
cana-851	70	21	objects[25	objects[25	NOUN
cana-851	70	22	]	]	X
cana-851	70	23	.	.	PUNCT
cana-851	71	1	the	the	DET
cana-851	71	2	presence	presence	NOUN
cana-851	71	3	of	of	ADP
cana-851	71	4	a	a	DET
cana-851	71	5	wide	wide	ADJ
cana-851	71	6	variety	variety	NOUN
cana-851	71	7	of	of	ADP
cana-851	71	8	flower	flower	NOUN
cana-851	71	9	species	species	NOUN
cana-851	71	10	poses	pose	VERB
cana-851	71	11	a	a	DET
cana-851	71	12	significant	significant	ADJ
cana-851	71	13	challenge	challenge	NOUN
cana-851	71	14	in	in	ADP
cana-851	71	15	their	their	PRON
cana-851	71	16	classification	classification	NOUN
cana-851	71	17	,	,	PUNCT
cana-851	71	18	particularly	particularly	ADV
cana-851	71	19	when	when	SCONJ
cana-851	71	20	they	they	PRON
cana-851	71	21	exhibit	exhibit	VERB
cana-851	71	22	striking	striking	ADJ
cana-851	71	23	similarities	similarity	NOUN
cana-851	71	24	.	.	PUNCT
cana-851	72	1	the	the	DET
cana-851	72	2	traditional	traditional	ADJ
cana-851	72	3	method	method	NOUN
cana-851	72	4	of	of	ADP
cana-851	72	5	segmenting	segment	VERB
cana-851	72	6	and	and	CCONJ
cana-851	72	7	selecting	select	VERB
cana-851	72	8	flower	flower	NOUN
cana-851	72	9	images	image	NOUN
cana-851	72	10	for	for	ADP
cana-851	72	11	classification	classification	NOUN
cana-851	72	12	is	be	AUX
cana-851	72	13	considered	consider	VERB
cana-851	72	14	primitive	primitive	ADJ
cana-851	72	15	and	and	CCONJ
cana-851	72	16	less	less	ADV
cana-851	72	17	accurate	accurate	ADJ
cana-851	72	18	compared	compare	VERB
cana-851	72	19	to	to	ADP
cana-851	72	20	the	the	DET
cana-851	72	21	use	use	NOUN
cana-851	72	22	of	of	ADP
cana-851	72	23	deep	deep	ADJ
cana-851	72	24	cnn	cnn	NOUN
cana-851	72	25	and	and	CCONJ
cana-851	72	26	machine	machine	NOUN
cana-851	72	27	learning	learn	VERB
cana-851	72	28	algorithms	algorithm	NOUN
cana-851	72	29	/	/	PUNCT
cana-851	72	30	nevertheless	nevertheless	ADV
cana-851	72	31	,	,	PUNCT
cana-851	72	32	it	it	PRON
cana-851	72	33	is	be	AUX
cana-851	72	34	an	an	DET
cana-851	72	35	undeniable	undeniable	ADJ
cana-851	72	36	fact	fact	NOUN
cana-851	72	37	that	that	SCONJ
cana-851	72	38	numerous	numerous	ADJ
cana-851	72	39	plants	plant	NOUN
cana-851	72	40	found	find	VERB
cana-851	72	41	in	in	ADP
cana-851	72	42	the	the	DET
cana-851	72	43	wild	wild	NOUN
cana-851	72	44	can	can	AUX
cana-851	72	45	be	be	AUX
cana-851	72	46	successfully	successfully	ADV
cana-851	72	47	farmed	farm	VERB
cana-851	72	48	.	.	PUNCT
cana-851	73	1	furthermore	furthermore	ADV
cana-851	73	2	,	,	PUNCT
cana-851	73	3	enhancing	enhance	VERB
cana-851	73	4	the	the	DET
cana-851	73	5	communications	communication	NOUN
cana-851	73	6	on	on	ADP
cana-851	73	7	applied	apply	VERB
cana-851	73	8	nonlinear	nonlinear	ADJ
cana-851	73	9	analysis	analysis	NOUN
cana-851	73	10	issn	issn	NOUN
cana-851	73	11	:	:	PUNCT
cana-851	73	12	1074	1074	NUM
cana-851	73	13	-	-	PUNCT
cana-851	73	14	133x	133x	NUM
cana-851	73	15	vol	vol	NOUN
cana-851	73	16	31	31	NUM
cana-851	73	17	no	no	NOUN
cana-851	73	18	.	.	PUNCT
cana-851	74	1	4s	4s	NUM
cana-851	74	2	(	(	PUNCT
cana-851	74	3	2024	2024	NUM
cana-851	74	4	)	)	PUNCT
cana-851	74	5	275	275	NUM
cana-851	74	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	74	7	discernment	discernment	NOUN
cana-851	74	8	ability	ability	NOUN
cana-851	74	9	of	of	ADP
cana-851	74	10	various	various	ADJ
cana-851	74	11	indigenous	indigenous	ADJ
cana-851	74	12	plant	plant	NOUN
cana-851	74	13	species	specie	NOUN
cana-851	74	14	,	,	PUNCT
cana-851	74	15	such	such	ADJ
cana-851	74	16	as	as	ADP
cana-851	74	17	elecampane	elecampane	NOUN
cana-851	74	18	and	and	CCONJ
cana-851	74	19	verbascum	verbascum	PROPN
cana-851	74	20	thapsus	thapsus	PROPN
cana-851	74	21	,	,	PUNCT
cana-851	74	22	which	which	PRON
cana-851	74	23	are	be	AUX
cana-851	74	24	restricted	restrict	VERB
cana-851	74	25	to	to	ADP
cana-851	74	26	a	a	DET
cana-851	74	27	certain	certain	ADJ
cana-851	74	28	region	region	NOUN
cana-851	74	29	and	and	CCONJ
cana-851	74	30	cultivated	cultivate	VERB
cana-851	74	31	exclusively	exclusively	ADV
cana-851	74	32	under	under	ADP
cana-851	74	33	specified	specified	ADJ
cana-851	74	34	weather	weather	NOUN
cana-851	74	35	conditions	condition	NOUN
cana-851	74	36	,	,	PUNCT
cana-851	74	37	would	would	AUX
cana-851	74	38	bolster	bolster	VERB
cana-851	74	39	the	the	DET
cana-851	74	40	advancement	advancement	NOUN
cana-851	74	41	of	of	ADP
cana-851	74	42	the	the	DET
cana-851	74	43	pharmaceutical	pharmaceutical	ADJ
cana-851	74	44	sector	sector	NOUN
cana-851	74	45	[	[	X
cana-851	74	46	3	3	NUM
cana-851	74	47	]	]	PUNCT
cana-851	74	48	.	.	PUNCT
cana-851	75	1	classifying	classify	VERB
cana-851	75	2	various	various	ADJ
cana-851	75	3	varieties	variety	NOUN
cana-851	75	4	of	of	ADP
cana-851	75	5	flowers	flower	NOUN
cana-851	75	6	is	be	AUX
cana-851	75	7	a	a	DET
cana-851	75	8	highly	highly	ADV
cana-851	75	9	challenging	challenging	ADJ
cana-851	75	10	task	task	NOUN
cana-851	75	11	due	due	ADP
cana-851	75	12	to	to	ADP
cana-851	75	13	multiple	multiple	ADJ
cana-851	75	14	factors	factor	NOUN
cana-851	75	15	.	.	PUNCT
cana-851	76	1	there	there	PRON
cana-851	76	2	is	be	VERB
cana-851	76	3	a	a	DET
cana-851	76	4	significant	significant	ADJ
cana-851	76	5	amount	amount	NOUN
cana-851	76	6	of	of	ADP
cana-851	76	7	diversity	diversity	NOUN
cana-851	76	8	in	in	ADP
cana-851	76	9	the	the	DET
cana-851	76	10	colors	color	NOUN
cana-851	76	11	exhibited	exhibit	VERB
cana-851	76	12	by	by	ADP
cana-851	76	13	flowers	flower	NOUN
cana-851	76	14	within	within	ADP
cana-851	76	15	a	a	DET
cana-851	76	16	single	single	ADJ
cana-851	76	17	class	class	NOUN
cana-851	76	18	,	,	PUNCT
cana-851	76	19	although	although	SCONJ
cana-851	76	20	there	there	PRON
cana-851	76	21	is	be	VERB
cana-851	76	22	also	also	ADV
cana-851	76	23	a	a	DET
cana-851	76	24	notable	notable	ADJ
cana-851	76	25	resemblance	resemblance	NOUN
cana-851	76	26	between	between	ADP
cana-851	76	27	multiple	multiple	ADJ
cana-851	76	28	classes	class	NOUN
cana-851	76	29	.	.	PUNCT
cana-851	77	1	even	even	ADV
cana-851	77	2	experienced	experienced	ADJ
cana-851	77	3	botanists	botanist	NOUN
cana-851	77	4	and	and	CCONJ
cana-851	77	5	gardeners	gardener	NOUN
cana-851	77	6	may	may	AUX
cana-851	77	7	struggle	struggle	VERB
cana-851	77	8	to	to	PART
cana-851	77	9	reliably	reliably	ADV
cana-851	77	10	identify	identify	VERB
cana-851	77	11	certain	certain	ADJ
cana-851	77	12	plants	plant	NOUN
cana-851	77	13	.	.	PUNCT
cana-851	78	1	however	however	ADV
cana-851	78	2	,	,	PUNCT
cana-851	78	3	pre	pre	ADJ
cana-851	78	4	-	-	ADJ
cana-851	78	5	trained	train	VERB
cana-851	78	6	models	model	NOUN
cana-851	78	7	that	that	PRON
cana-851	78	8	have	have	AUX
cana-851	78	9	been	be	AUX
cana-851	78	10	trained	train	VERB
cana-851	78	11	on	on	ADP
cana-851	78	12	imagenet	imagenet	NOUN
cana-851	78	13	for	for	ADP
cana-851	78	14	picture	picture	NOUN
cana-851	78	15	classification	classification	NOUN
cana-851	78	16	can	can	AUX
cana-851	78	17	be	be	AUX
cana-851	78	18	utilized	utilize	VERB
cana-851	78	19	for	for	ADP
cana-851	78	20	other	other	ADJ
cana-851	78	21	image	image	NOUN
cana-851	78	22	datasets	dataset	NOUN
cana-851	78	23	with	with	ADP
cana-851	78	24	minimal	minimal	ADJ
cana-851	78	25	data	datum	NOUN
cana-851	78	26	,	,	PUNCT
cana-851	78	27	without	without	ADP
cana-851	78	28	the	the	DET
cana-851	78	29	risk	risk	NOUN
cana-851	78	30	of	of	ADP
cana-851	78	31	overfitting[26	overfitting[26	NOUN
cana-851	78	32	]	]	PUNCT
cana-851	78	33	.	.	PUNCT
cana-851	79	1	the	the	DET
cana-851	79	2	inclusion	inclusion	NOUN
cana-851	79	3	of	of	ADP
cana-851	79	4	diverse	diverse	ADJ
cana-851	79	5	elements	element	NOUN
cana-851	79	6	is	be	AUX
cana-851	79	7	a	a	DET
cana-851	79	8	crucial	crucial	ADJ
cana-851	79	9	determinant	determinant	NOUN
cana-851	79	10	in	in	ADP
cana-851	79	11	enhancing	enhance	VERB
cana-851	79	12	the	the	DET
cana-851	79	13	efficacy	efficacy	NOUN
cana-851	79	14	of	of	ADP
cana-851	79	15	ensemble	ensemble	ADJ
cana-851	79	16	models	model	NOUN
cana-851	79	17	.	.	PUNCT
cana-851	80	1	our	our	PRON
cana-851	80	2	future	future	ADJ
cana-851	80	3	work	work	NOUN
cana-851	80	4	will	will	AUX
cana-851	80	5	focus	focus	VERB
cana-851	80	6	on	on	ADP
cana-851	80	7	generating	generate	VERB
cana-851	80	8	a	a	DET
cana-851	80	9	more	more	ADV
cana-851	80	10	diversified	diversified	ADJ
cana-851	80	11	network	network	NOUN
cana-851	80	12	for	for	ADP
cana-851	80	13	integration	integration	NOUN
cana-851	80	14	.	.	PUNCT
cana-851	81	1	nevertheless	nevertheless	ADV
cana-851	81	2	,	,	PUNCT
cana-851	81	3	there	there	PRON
cana-851	81	4	exist	exist	VERB
cana-851	81	5	certain	certain	ADJ
cana-851	81	6	constraints	constraint	NOUN
cana-851	81	7	when	when	SCONJ
cana-851	81	8	it	it	PRON
cana-851	81	9	comes	come	VERB
cana-851	81	10	to	to	ADP
cana-851	81	11	choosing	choose	VERB
cana-851	81	12	suitable	suitable	ADJ
cana-851	81	13	network	network	NOUN
cana-851	81	14	architectures	architecture	NOUN
cana-851	81	15	,	,	PUNCT
cana-851	81	16	parameters	parameter	NOUN
cana-851	81	17	,	,	PUNCT
cana-851	81	18	and	and	CCONJ
cana-851	81	19	algorithms	algorithm	NOUN
cana-851	81	20	,	,	PUNCT
cana-851	81	21	as	as	ADV
cana-851	81	22	well	well	ADV
cana-851	81	23	as	as	ADP
cana-851	81	24	the	the	DET
cana-851	81	25	need	need	NOUN
cana-851	81	26	for	for	ADP
cana-851	81	27	extensive	extensive	ADJ
cana-851	81	28	training	training	NOUN
cana-851	81	29	durations	duration	NOUN
cana-851	81	30	to	to	PART
cana-851	81	31	achieve	achieve	VERB
cana-851	81	32	optimal	optimal	ADJ
cana-851	81	33	recognition	recognition	NOUN
cana-851	81	34	performance	performance	NOUN
cana-851	81	35	in	in	ADP
cana-851	81	36	practical	practical	ADJ
cana-851	81	37	scenarios[27	scenarios[27	NOUN
cana-851	81	38	]	]	PUNCT
cana-851	81	39	.	.	PUNCT
cana-851	82	1	the	the	DET
cana-851	82	2	conventional	conventional	ADJ
cana-851	82	3	computer	computer	NOUN
cana-851	82	4	visual	visual	ADJ
cana-851	82	5	techniques	technique	NOUN
cana-851	82	6	are	be	AUX
cana-851	82	7	inefficient	inefficient	ADJ
cana-851	82	8	and	and	CCONJ
cana-851	82	9	imprecise	imprecise	ADV
cana-851	82	10	.	.	PUNCT
cana-851	83	1	thus	thus	ADV
cana-851	83	2	,	,	PUNCT
cana-851	83	3	our	our	PRON
cana-851	83	4	study	study	NOUN
cana-851	83	5	incorporated	incorporate	VERB
cana-851	83	6	ssd	ssd	NOUN
cana-851	83	7	deep	deep	ADJ
cana-851	83	8	learning	learning	NOUN
cana-851	83	9	technology	technology	NOUN
cana-851	83	10	into	into	ADP
cana-851	83	11	the	the	DET
cana-851	83	12	domain	domain	NOUN
cana-851	83	13	of	of	ADP
cana-851	83	14	flowers	flower	NOUN
cana-851	83	15	detection	detection	NOUN
cana-851	83	16	and	and	CCONJ
cana-851	83	17	identification[28	identification[28	NOUN
cana-851	83	18	]	]	PUNCT
cana-851	83	19	.	.	PUNCT
cana-851	84	1	flower	flower	NOUN
cana-851	84	2	classification	classification	NOUN
cana-851	84	3	is	be	AUX
cana-851	84	4	achieved	achieve	VERB
cana-851	84	5	by	by	ADP
cana-851	84	6	utilizing	utilize	VERB
cana-851	84	7	convolutional	convolutional	ADJ
cana-851	84	8	neural	neural	ADJ
cana-851	84	9	networks	network	NOUN
cana-851	84	10	(	(	PUNCT
cana-851	84	11	cnn	cnn	PROPN
cana-851	84	12	)	)	PUNCT
cana-851	84	13	and	and	CCONJ
cana-851	84	14	employing	employ	VERB
cana-851	84	15	transfer	transfer	NOUN
cana-851	84	16	learning	learning	NOUN
cana-851	84	17	within	within	ADP
cana-851	84	18	the	the	DET
cana-851	84	19	cnn	cnn	PROPN
cana-851	84	20	framework	framework	NOUN
cana-851	84	21	requires	require	VERB
cana-851	84	22	a	a	DET
cana-851	84	23	large	large	ADJ
cana-851	84	24	amount	amount	NOUN
cana-851	84	25	of	of	ADP
cana-851	84	26	labeled	label	VERB
cana-851	84	27	data	datum	NOUN
cana-851	84	28	for	for	ADP
cana-851	84	29	training	train	VERB
cana-851	84	30	the	the	DET
cana-851	84	31	models	model	NOUN
cana-851	84	32	,	,	PUNCT
cana-851	84	33	which	which	PRON
cana-851	84	34	can	can	AUX
cana-851	84	35	be	be	AUX
cana-851	84	36	time	time	NOUN
cana-851	84	37	-	-	PUNCT
cana-851	84	38	consuming	consume	VERB
cana-851	84	39	and	and	CCONJ
cana-851	84	40	require	require	VERB
cana-851	84	41	expertise	expertise	NOUN
cana-851	84	42	in	in	ADP
cana-851	84	43	the	the	DET
cana-851	84	44	field	field	NOUN
cana-851	84	45	.	.	PUNCT
cana-851	85	1	the	the	DET
cana-851	85	2	use	use	NOUN
cana-851	85	3	of	of	ADP
cana-851	85	4	deep	deep	ADJ
cana-851	85	5	learning	learning	NOUN
cana-851	85	6	methods	method	NOUN
cana-851	85	7	like	like	ADP
cana-851	85	8	cnn	cnn	PROPN
cana-851	85	9	and	and	CCONJ
cana-851	85	10	transfer	transfer	NOUN
cana-851	85	11	learning	learning	NOUN
cana-851	85	12	may	may	AUX
cana-851	85	13	require	require	VERB
cana-851	85	14	significant	significant	ADJ
cana-851	85	15	computational	computational	ADJ
cana-851	85	16	resources	resource	NOUN
cana-851	85	17	and	and	CCONJ
cana-851	85	18	processing	processing	NOUN
cana-851	85	19	power	power	NOUN
cana-851	85	20	,	,	PUNCT
cana-851	85	21	which	which	PRON
cana-851	85	22	can	can	AUX
cana-851	85	23	be	be	AUX
cana-851	85	24	a	a	DET
cana-851	85	25	limitation	limitation	NOUN
cana-851	85	26	for	for	ADP
cana-851	85	27	some	some	DET
cana-851	85	28	applications	application	NOUN
cana-851	85	29	,	,	PUNCT
cana-851	85	30	especially	especially	ADV
cana-851	85	31	in	in	ADP
cana-851	85	32	resource	resource	NOUN
cana-851	85	33	-	-	PUNCT
cana-851	85	34	constrained	constrain	VERB
cana-851	85	35	environments./	environments./	NOUN
cana-851	85	36	the	the	DET
cana-851	85	37	challenge	challenge	NOUN
cana-851	85	38	lies	lie	VERB
cana-851	85	39	in	in	ADP
cana-851	85	40	accurately	accurately	ADV
cana-851	85	41	classifying	classify	VERB
cana-851	85	42	flowers	flower	NOUN
cana-851	85	43	based	base	VERB
cana-851	85	44	on	on	ADP
cana-851	85	45	their	their	PRON
cana-851	85	46	visual	visual	ADJ
cana-851	85	47	characteristics[29	characteristics[29	NOUN
cana-851	85	48	]	]	PUNCT
cana-851	85	49	.	.	PUNCT
cana-851	86	1	flower	flower	NOUN
cana-851	86	2	recognition	recognition	NOUN
cana-851	86	3	is	be	AUX
cana-851	86	4	a	a	DET
cana-851	86	5	significant	significant	ADJ
cana-851	86	6	challenge	challenge	NOUN
cana-851	86	7	due	due	ADP
cana-851	86	8	to	to	ADP
cana-851	86	9	the	the	DET
cana-851	86	10	vast	vast	ADJ
cana-851	86	11	number	number	NOUN
cana-851	86	12	of	of	ADP
cana-851	86	13	flower	flower	NOUN
cana-851	86	14	species	specie	NOUN
cana-851	86	15	that	that	PRON
cana-851	86	16	exist	exist	VERB
cana-851	86	17	worldwide	worldwide	ADV
cana-851	86	18	.	.	PUNCT
cana-851	87	1	the	the	DET
cana-851	87	2	task	task	NOUN
cana-851	87	3	is	be	AUX
cana-851	87	4	quite	quite	ADV
cana-851	87	5	tough	tough	ADJ
cana-851	87	6	and	and	CCONJ
cana-851	87	7	requires	require	VERB
cana-851	87	8	a	a	DET
cana-851	87	9	significant	significant	ADJ
cana-851	87	10	amount	amount	NOUN
cana-851	87	11	of	of	ADP
cana-851	87	12	time	time	NOUN
cana-851	87	13	.	.	PUNCT
cana-851	88	1	it	it	PRON
cana-851	88	2	has	have	AUX
cana-851	88	3	primarily	primarily	ADV
cana-851	88	4	been	be	AUX
cana-851	88	5	undertaken	undertake	VERB
cana-851	88	6	by	by	ADP
cana-851	88	7	botanists./	botanists./	PROPN
cana-851	88	8	inter	inter	ADJ
cana-851	88	9	-	-	ADJ
cana-851	88	10	class	class	ADJ
cana-851	88	11	similarities	similarity	NOUN
cana-851	88	12	between	between	ADP
cana-851	88	13	different	different	ADJ
cana-851	88	14	species	specie	NOUN
cana-851	88	15	and	and	CCONJ
cana-851	88	16	the	the	DET
cana-851	88	17	intra	intra	ADJ
cana-851	88	18	-	-	ADJ
cana-851	88	19	class	class	ADJ
cana-851	88	20	variation	variation	NOUN
cana-851	88	21	among	among	ADP
cana-851	88	22	the	the	DET
cana-851	88	23	same	same	ADJ
cana-851	88	24	species	specie	NOUN
cana-851	88	25	pose	pose	VERB
cana-851	88	26	a	a	DET
cana-851	88	27	significant	significant	ADJ
cana-851	88	28	challenge	challenge	NOUN
cana-851	88	29	in	in	ADP
cana-851	88	30	flower	flower	NOUN
cana-851	88	31	recognition[30	recognition[30	NOUN
cana-851	88	32	]	]	X
cana-851	88	33	.	.	PUNCT
cana-851	89	1	the	the	DET
cana-851	89	2	efficacy	efficacy	NOUN
cana-851	89	3	of	of	ADP
cana-851	89	4	the	the	DET
cana-851	89	5	suggested	suggest	VERB
cana-851	89	6	approach	approach	NOUN
cana-851	89	7	in	in	ADP
cana-851	89	8	enhancing	enhance	VERB
cana-851	89	9	performance	performance	NOUN
cana-851	89	10	relative	relative	ADJ
cana-851	89	11	to	to	ADP
cana-851	89	12	alternative	alternative	ADJ
cana-851	89	13	data	data	NOUN
cana-851	89	14	fusion	fusion	NOUN
cana-851	89	15	methods	method	NOUN
cana-851	89	16	may	may	AUX
cana-851	89	17	vary	vary	VERB
cana-851	89	18	based	base	VERB
cana-851	89	19	on	on	ADP
cana-851	89	20	the	the	DET
cana-851	89	21	unique	unique	ADJ
cana-851	89	22	dataset	dataset	NOUN
cana-851	89	23	and	and	CCONJ
cana-851	89	24	classification	classification	NOUN
cana-851	89	25	objective	objective	NOUN
cana-851	89	26	.	.	PUNCT
cana-851	89	27	,	,	PUNCT
cana-851	89	28	and	and	CCONJ
cana-851	89	29	may	may	AUX
cana-851	89	30	not	not	PART
cana-851	89	31	always	always	ADV
cana-851	89	32	achieve	achieve	VERB
cana-851	89	33	superior	superior	ADJ
cana-851	89	34	results	result	NOUN
cana-851	89	35	,	,	PUNCT
cana-851	89	36	the	the	DET
cana-851	89	37	proposed	propose	VERB
cana-851	89	38	algorithm	algorithm	NOUN
cana-851	89	39	does	do	AUX
cana-851	89	40	not	not	PART
cana-851	89	41	address	address	VERB
cana-851	89	42	the	the	DET
cana-851	89	43	potential	potential	ADJ
cana-851	89	44	issue	issue	NOUN
cana-851	89	45	of	of	ADP
cana-851	89	46	class	class	NOUN
cana-851	89	47	confusion	confusion	NOUN
cana-851	89	48	in	in	ADP
cana-851	89	49	flower	flower	NOUN
cana-851	89	50	classification	classification	NOUN
cana-851	89	51	,	,	PUNCT
cana-851	89	52	which	which	PRON
cana-851	89	53	could	could	AUX
cana-851	89	54	affect	affect	VERB
cana-851	89	55	the	the	DET
cana-851	89	56	accuracy	accuracy	NOUN
cana-851	89	57	and	and	CCONJ
cana-851	89	58	reliability	reliability	NOUN
cana-851	89	59	of	of	ADP
cana-851	89	60	the	the	DET
cana-851	89	61	classification	classification	NOUN
cana-851	89	62	system	system	NOUN
cana-851	89	63	/	/	PUNCT
cana-851	89	64	the	the	DET
cana-851	89	65	study	study	NOUN
cana-851	89	66	aims	aim	VERB
cana-851	89	67	to	to	PART
cana-851	89	68	address	address	VERB
cana-851	89	69	the	the	DET
cana-851	89	70	problem	problem	NOUN
cana-851	89	71	of	of	ADP
cana-851	89	72	flower	flower	NOUN
cana-851	89	73	classification	classification	NOUN
cana-851	89	74	using	use	VERB
cana-851	89	75	both	both	CCONJ
cana-851	89	76	image	image	NOUN
cana-851	89	77	and	and	CCONJ
cana-851	89	78	text	text	NOUN
cana-851	89	79	data	datum	NOUN
cana-851	89	80	for	for	ADP
cana-851	89	81	improved	improved	ADJ
cana-851	89	82	performance[31	performance[31	NOUN
cana-851	89	83	]	]	X
cana-851	89	84	.	.	PUNCT
cana-851	90	1	the	the	DET
cana-851	90	2	learning	learning	NOUN
cana-851	90	3	accuracy	accuracy	NOUN
cana-851	90	4	of	of	ADP
cana-851	90	5	mdcnn	mdcnn	PROPN
cana-851	90	6	depends	depend	VERB
cana-851	90	7	on	on	ADP
cana-851	90	8	factors	factor	NOUN
cana-851	90	9	examples	example	NOUN
cana-851	90	10	of	of	ADP
cana-851	90	11	the	the	DET
cana-851	90	12	information	information	NOUN
cana-851	90	13	include	include	VERB
cana-851	90	14	the	the	DET
cana-851	90	15	learning	learning	NOUN
cana-851	90	16	rates	rate	NOUN
cana-851	90	17	,	,	PUNCT
cana-851	90	18	batch	batch	VERB
cana-851	90	19	loss	loss	NOUN
cana-851	90	20	values	value	NOUN
cana-851	90	21	,	,	PUNCT
cana-851	90	22	and	and	CCONJ
cana-851	90	23	the	the	DET
cana-851	90	24	specific	specific	ADJ
cana-851	90	25	sorts	sort	NOUN
cana-851	90	26	of	of	ADP
cana-851	90	27	photos	photo	NOUN
cana-851	90	28	utilized	utilize	VERB
cana-851	90	29	to	to	PART
cana-851	90	30	train	train	VERB
cana-851	90	31	the	the	DET
cana-851	90	32	model	model	NOUN
cana-851	90	33	.	.	PUNCT
cana-851	91	1	the	the	DET
cana-851	91	2	performance	performance	NOUN
cana-851	91	3	characteristics	characteristic	NOUN
cana-851	91	4	of	of	ADP
cana-851	91	5	the	the	DET
cana-851	91	6	mdcnn	mdcnn	PROPN
cana-851	91	7	model	model	NOUN
cana-851	91	8	are	be	AUX
cana-851	91	9	compared	compare	VERB
cana-851	91	10	with	with	ADP
cana-851	91	11	those	those	PRON
cana-851	91	12	of	of	ADP
cana-851	91	13	pretrained	pretraine	VERB
cana-851	91	14	convolutional	convolutional	ADJ
cana-851	91	15	neural	neural	ADJ
cana-851	91	16	networks	network	NOUN
cana-851	91	17	(	(	PUNCT
cana-851	91	18	vggnet-16	vggnet-16	PROPN
cana-851	91	19	,	,	PUNCT
cana-851	91	20	googlenet	googlenet	NOUN
cana-851	91	21	,	,	PUNCT
cana-851	91	22	alexnet	alexnet	NOUN
cana-851	91	23	,	,	PUNCT
cana-851	91	24	and	and	CCONJ
cana-851	91	25	resnet-50	resnet-50	NUM
cana-851	91	26	)	)	PUNCT
cana-851	91	27	demonstrating	demonstrate	VERB
cana-851	91	28	its	its	PRON
cana-851	91	29	superiority[32	superiority[32	NOUN
cana-851	91	30	]	]	PUNCT
cana-851	91	31	.	.	PUNCT
cana-851	92	1	the	the	DET
cana-851	92	2	paper	paper	NOUN
cana-851	92	3	does	do	AUX
cana-851	92	4	not	not	PART
cana-851	92	5	provide	provide	VERB
cana-851	92	6	a	a	DET
cana-851	92	7	detailed	detailed	ADJ
cana-851	92	8	analysis	analysis	NOUN
cana-851	92	9	of	of	ADP
cana-851	92	10	the	the	DET
cana-851	92	11	limitations	limitation	NOUN
cana-851	92	12	or	or	CCONJ
cana-851	92	13	potential	potential	ADJ
cana-851	92	14	drawbacks	drawback	NOUN
cana-851	92	15	of	of	ADP
cana-851	92	16	the	the	DET
cana-851	92	17	proposed	propose	VERB
cana-851	92	18	transfer	transfer	NOUN
cana-851	92	19	learning	learning	NOUN
cana-851	92	20	-	-	PUNCT
cana-851	92	21	based	base	VERB
cana-851	92	22	method	method	NOUN
cana-851	92	23	for	for	ADP
cana-851	92	24	flower	flower	NOUN
cana-851	92	25	image	image	NOUN
cana-851	92	26	classification	classification	NOUN
cana-851	92	27	.	.	PUNCT
cana-851	93	1	the	the	DET
cana-851	93	2	specific	specific	ADJ
cana-851	93	3	choices	choice	NOUN
cana-851	93	4	made	make	VERB
cana-851	93	5	in	in	ADP
cana-851	93	6	fine	fine	ADV
cana-851	93	7	-	-	PUNCT
cana-851	93	8	tuning	tune	VERB
cana-851	93	9	the	the	DET
cana-851	93	10	alexnet	alexnet	ADJ
cana-851	93	11	model	model	NOUN
cana-851	93	12	,	,	PUNCT
cana-851	93	13	such	such	ADJ
cana-851	93	14	as	as	ADP
cana-851	93	15	the	the	DET
cana-851	93	16	number	number	NOUN
cana-851	93	17	of	of	ADP
cana-851	93	18	layers	layer	NOUN
cana-851	93	19	replaced	replace	VERB
cana-851	93	20	and	and	CCONJ
cana-851	93	21	the	the	DET
cana-851	93	22	specific	specific	ADJ
cana-851	93	23	layers	layer	NOUN
cana-851	93	24	retained	retain	VERB
cana-851	93	25	,	,	PUNCT
cana-851	93	26	are	be	AUX
cana-851	93	27	not	not	PART
cana-851	93	28	explicitly	explicitly	ADV
cana-851	93	29	justified	justify	VERB
cana-851	93	30	or	or	CCONJ
cana-851	93	31	discussed	discuss	VERB
cana-851	93	32	in	in	ADP
cana-851	93	33	the	the	DET
cana-851	93	34	paper	paper	NOUN
cana-851	93	35	.	.	PUNCT
cana-851	94	1	/the	/the	DET
cana-851	94	2	problem	problem	NOUN
cana-851	94	3	addressed	address	VERB
cana-851	94	4	in	in	ADP
cana-851	94	5	the	the	DET
cana-851	94	6	paper	paper	NOUN
cana-851	94	7	is	be	AUX
cana-851	94	8	the	the	DET
cana-851	94	9	classification	classification	NOUN
cana-851	94	10	of	of	ADP
cana-851	94	11	flower	flower	NOUN
cana-851	94	12	images	image	NOUN
cana-851	94	13	using	use	VERB
cana-851	94	14	deep	deep	ADJ
cana-851	94	15	learning	learning	NOUN
cana-851	94	16	techniques	technique	NOUN
cana-851	94	17	.	.	PUNCT
cana-851	95	1	the	the	DET
cana-851	95	2	paper	paper	NOUN
cana-851	95	3	aims	aim	VERB
cana-851	95	4	to	to	PART
cana-851	95	5	improve	improve	VERB
cana-851	95	6	the	the	DET
cana-851	95	7	classification	classification	NOUN
cana-851	95	8	accuracy	accuracy	NOUN
cana-851	95	9	of	of	ADP
cana-851	95	10	flower	flower	NOUN
cana-851	95	11	images	image	NOUN
cana-851	95	12	by	by	ADP
cana-851	95	13	leveraging	leverage	VERB
cana-851	95	14	transfer	transfer	NOUN
cana-851	95	15	learning	learning	NOUN
cana-851	95	16	and	and	CCONJ
cana-851	95	17	a	a	DET
cana-851	95	18	pre	pre	ADJ
cana-851	95	19	-	-	ADJ
cana-851	95	20	trained	train	VERB
cana-851	95	21	alexnet	alexnet	ADJ
cana-851	95	22	model[33	model[33	NOUN
cana-851	95	23	]	]	X
cana-851	95	24	.	.	PUNCT
cana-851	96	1	classifying	classify	VERB
cana-851	96	2	flowers	flower	NOUN
cana-851	96	3	can	can	AUX
cana-851	96	4	be	be	AUX
cana-851	96	5	a	a	DET
cana-851	96	6	tough	tough	ADJ
cana-851	96	7	task	task	NOUN
cana-851	96	8	due	due	ADP
cana-851	96	9	to	to	ADP
cana-851	96	10	various	various	ADJ
cana-851	96	11	reasons	reason	NOUN
cana-851	96	12	,	,	PUNCT
cana-851	96	13	including	include	VERB
cana-851	96	14	the	the	DET
cana-851	96	15	presence	presence	NOUN
cana-851	96	16	of	of	ADP
cana-851	96	17	blurry	blurry	ADJ
cana-851	96	18	,	,	PUNCT
cana-851	96	19	noisy	noisy	ADJ
cana-851	96	20	,	,	PUNCT
cana-851	96	21	and	and	CCONJ
cana-851	96	22	low	low	ADJ
cana-851	96	23	-	-	PUNCT
cana-851	96	24	quality	quality	NOUN
cana-851	96	25	photographs	photograph	NOUN
cana-851	96	26	,	,	PUNCT
cana-851	96	27	as	as	ADV
cana-851	96	28	well	well	ADV
cana-851	96	29	as	as	ADP
cana-851	96	30	obstructions	obstruction	NOUN
cana-851	96	31	such	such	ADJ
cana-851	96	32	as	as	ADP
cana-851	96	33	communications	communication	NOUN
cana-851	96	34	on	on	ADP
cana-851	96	35	applied	apply	VERB
cana-851	96	36	nonlinear	nonlinear	ADJ
cana-851	96	37	analysis	analysis	NOUN
cana-851	96	38	issn	issn	NOUN
cana-851	96	39	:	:	PUNCT
cana-851	96	40	1074	1074	NUM
cana-851	96	41	-	-	PUNCT
cana-851	96	42	133x	133x	NUM
cana-851	96	43	vol	vol	NOUN
cana-851	96	44	31	31	NUM
cana-851	96	45	no	no	NOUN
cana-851	96	46	.	.	PUNCT
cana-851	97	1	4s	4s	NUM
cana-851	97	2	(	(	PUNCT
cana-851	97	3	2024	2024	NUM
cana-851	97	4	)	)	PUNCT
cana-851	97	5	276	276	NUM
cana-851	97	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	97	7	plant	plant	NOUN
cana-851	97	8	leaves	leave	NOUN
cana-851	97	9	,	,	PUNCT
cana-851	97	10	stems	stem	NOUN
cana-851	97	11	,	,	PUNCT
cana-851	97	12	and	and	CCONJ
cana-851	97	13	insects	insect	NOUN
cana-851	97	14	.	.	PUNCT
cana-851	98	1	the	the	DET
cana-851	98	2	field	field	NOUN
cana-851	98	3	of	of	ADP
cana-851	98	4	object	object	NOUN
cana-851	98	5	identification	identification	NOUN
cana-851	98	6	,	,	PUNCT
cana-851	98	7	particularly	particularly	ADV
cana-851	98	8	recognizing	recognize	VERB
cana-851	98	9	flowers	flower	NOUN
cana-851	98	10	,	,	PUNCT
cana-851	98	11	poses	pose	VERB
cana-851	98	12	challenges	challenge	NOUN
cana-851	98	13	because	because	SCONJ
cana-851	98	14	of	of	ADP
cana-851	98	15	the	the	DET
cana-851	98	16	extensive	extensive	ADJ
cana-851	98	17	range	range	NOUN
cana-851	98	18	of	of	ADP
cana-851	98	19	flower	flower	NOUN
cana-851	98	20	species	specie	NOUN
cana-851	98	21	exhibiting	exhibit	VERB
cana-851	98	22	diverse	diverse	ADJ
cana-851	98	23	colors	color	NOUN
cana-851	98	24	,	,	PUNCT
cana-851	98	25	styles	style	NOUN
cana-851	98	26	,	,	PUNCT
cana-851	98	27	and	and	CCONJ
cana-851	98	28	sizes	size	NOUN
cana-851	98	29	,	,	PUNCT
cana-851	98	30	along	along	ADP
cana-851	98	31	with	with	ADP
cana-851	98	32	their	their	PRON
cana-851	98	33	accompanying	accompany	VERB
cana-851	98	34	foliage	foliage	NOUN
cana-851	98	35	,	,	PUNCT
cana-851	98	36	shrubs	shrub	NOUN
cana-851	98	37	,	,	PUNCT
cana-851	98	38	and	and	CCONJ
cana-851	98	39	other	other	ADJ
cana-851	98	40	objects./	objects./	ADP
cana-851	98	41	the	the	DET
cana-851	98	42	field	field	NOUN
cana-851	98	43	of	of	ADP
cana-851	98	44	object	object	NOUN
cana-851	98	45	identification	identification	NOUN
cana-851	98	46	faces	face	VERB
cana-851	98	47	challenges	challenge	NOUN
cana-851	98	48	in	in	ADP
cana-851	98	49	recognizing	recognize	VERB
cana-851	98	50	flowers	flower	NOUN
cana-851	98	51	due	due	ADJ
cana-851	98	52	to	to	ADP
cana-851	98	53	their	their	PRON
cana-851	98	54	diverse	diverse	ADJ
cana-851	98	55	colors	color	NOUN
cana-851	98	56	,	,	PUNCT
cana-851	98	57	forms	form	NOUN
cana-851	98	58	,	,	PUNCT
cana-851	98	59	sizes	size	NOUN
cana-851	98	60	,	,	PUNCT
cana-851	98	61	and	and	CCONJ
cana-851	98	62	surroundings	surroundings	PROPN
cana-851	98	63	.	.	PUNCT
cana-851	99	1	flower	flower	NOUN
cana-851	99	2	classification	classification	NOUN
cana-851	99	3	has	have	AUX
cana-851	99	4	benefited	benefit	VERB
cana-851	99	5	from	from	ADP
cana-851	99	6	the	the	DET
cana-851	99	7	use	use	NOUN
cana-851	99	8	of	of	ADP
cana-851	99	9	machine	machine	NOUN
cana-851	99	10	learning	learn	VERB
cana-851	99	11	techniques	technique	NOUN
cana-851	99	12	and	and	CCONJ
cana-851	99	13	deep	deep	ADJ
cana-851	99	14	neural	neural	ADJ
cana-851	99	15	networks	network	NOUN
cana-851	99	16	,	,	PUNCT
cana-851	99	17	which	which	PRON
cana-851	99	18	have	have	AUX
cana-851	99	19	replaced	replace	VERB
cana-851	99	20	traditional	traditional	ADJ
cana-851	99	21	manual	manual	ADJ
cana-851	99	22	ways	way	NOUN
cana-851	99	23	of	of	ADP
cana-851	99	24	extracting	extract	VERB
cana-851	99	25	characteristics[34].the	characteristics[34].the	NOUN
cana-851	99	26	problem	problem	NOUN
cana-851	99	27	addressed	address	VERB
cana-851	99	28	in	in	ADP
cana-851	99	29	the	the	DET
cana-851	99	30	paper	paper	NOUN
cana-851	99	31	is	be	AUX
cana-851	99	32	the	the	DET
cana-851	99	33	need	need	NOUN
cana-851	99	34	for	for	ADP
cana-851	99	35	an	an	DET
cana-851	99	36	improved	improved	ADJ
cana-851	99	37	flower	flower	NOUN
cana-851	99	38	image	image	NOUN
cana-851	99	39	recognition	recognition	NOUN
cana-851	99	40	method	method	NOUN
cana-851	99	41	that	that	PRON
cana-851	99	42	has	have	VERB
cana-851	99	43	higher	high	ADJ
cana-851	99	44	accuracy	accuracy	NOUN
cana-851	99	45	,	,	PUNCT
cana-851	99	46	better	well	ADJ
cana-851	99	47	generalization	generalization	NOUN
cana-851	99	48	,	,	PUNCT
cana-851	99	49	and	and	CCONJ
cana-851	99	50	a	a	DET
cana-851	99	51	shorter	short	ADJ
cana-851	99	52	recognition	recognition	NOUN
cana-851	99	53	process[35].the	process[35].the	DET
cana-851	99	54	accuracy	accuracy	NOUN
cana-851	99	55	of	of	ADP
cana-851	99	56	the	the	DET
cana-851	99	57	identification	identification	NOUN
cana-851	99	58	may	may	AUX
cana-851	99	59	be	be	AUX
cana-851	99	60	affected	affect	VERB
cana-851	99	61	by	by	ADP
cana-851	99	62	variations	variation	NOUN
cana-851	99	63	in	in	ADP
cana-851	99	64	lighting	lighting	NOUN
cana-851	99	65	conditions	condition	NOUN
cana-851	99	66	,	,	PUNCT
cana-851	99	67	camera	camera	NOUN
cana-851	99	68	angles	angle	NOUN
cana-851	99	69	,	,	PUNCT
cana-851	99	70	and	and	CCONJ
cana-851	99	71	other	other	ADJ
cana-851	99	72	environmental	environmental	ADJ
cana-851	99	73	factors	factor	NOUN
cana-851	99	74	,	,	PUNCT
cana-851	99	75	leading	lead	VERB
cana-851	99	76	to	to	ADP
cana-851	99	77	potential	potential	ADJ
cana-851	99	78	recognition	recognition	NOUN
cana-851	99	79	failures	failure	NOUN
cana-851	99	80	/	/	SYM
cana-851	99	81	the	the	DET
cana-851	99	82	problem	problem	NOUN
cana-851	99	83	addressed	address	VERB
cana-851	99	84	in	in	ADP
cana-851	99	85	the	the	DET
cana-851	99	86	provided	provide	VERB
cana-851	99	87	sources	source	NOUN
cana-851	99	88	is	be	AUX
cana-851	99	89	the	the	DET
cana-851	99	90	accurate	accurate	ADJ
cana-851	99	91	identification	identification	NOUN
cana-851	99	92	of	of	ADP
cana-851	99	93	flower	flower	NOUN
cana-851	99	94	species	specie	NOUN
cana-851	99	95	using	use	VERB
cana-851	99	96	deep	deep	ADJ
cana-851	99	97	learning	learning	NOUN
cana-851	99	98	techniques	technique	NOUN
cana-851	99	99	.	.	PUNCT
cana-851	100	1	the	the	DET
cana-851	100	2	existing	exist	VERB
cana-851	100	3	methods	method	NOUN
cana-851	100	4	for	for	ADP
cana-851	100	5	flower	flower	NOUN
cana-851	100	6	recognition	recognition	NOUN
cana-851	100	7	often	often	ADV
cana-851	100	8	require	require	VERB
cana-851	100	9	extensive	extensive	ADJ
cana-851	100	10	manual	manual	ADJ
cana-851	100	11	examination	examination	NOUN
cana-851	100	12	of	of	ADP
cana-851	100	13	botanical	botanical	ADJ
cana-851	100	14	guides	guide	NOUN
cana-851	100	15	,	,	PUNCT
cana-851	100	16	which	which	PRON
cana-851	100	17	can	can	AUX
cana-851	100	18	be	be	AUX
cana-851	100	19	time	time	NOUN
cana-851	100	20	-	-	PUNCT
cana-851	100	21	consuming	consume	VERB
cana-851	100	22	and	and	CCONJ
cana-851	100	23	challenging	challenge	VERB
cana-851	100	24	for	for	ADP
cana-851	100	25	non	non	NOUN
cana-851	100	26	-	-	NOUN
cana-851	100	27	experts	expert	NOUN
cana-851	100	28	.	.	PUNCT
cana-851	101	1	the	the	DET
cana-851	101	2	goal	goal	NOUN
cana-851	101	3	is	be	AUX
cana-851	101	4	to	to	PART
cana-851	101	5	develop	develop	VERB
cana-851	101	6	a	a	DET
cana-851	101	7	mobile	mobile	ADJ
cana-851	101	8	application	application	NOUN
cana-851	101	9	that	that	PRON
cana-851	101	10	can	can	AUX
cana-851	101	11	automatically	automatically	ADV
cana-851	101	12	identify	identify	VERB
cana-851	101	13	flower	flower	NOUN
cana-851	101	14	species	specie	NOUN
cana-851	101	15	based	base	VERB
cana-851	101	16	on	on	ADP
cana-851	101	17	images	image	NOUN
cana-851	101	18	captured	capture	VERB
cana-851	101	19	in	in	ADP
cana-851	101	20	a	a	DET
cana-851	101	21	natural	natural	ADJ
cana-851	101	22	environment	environment	NOUN
cana-851	101	23	setting	setting	NOUN
cana-851	101	24	.	.	PUNCT
cana-851	102	1	the	the	DET
cana-851	102	2	application	application	NOUN
cana-851	102	3	utilizes	utilize	VERB
cana-851	102	4	deep	deep	ADJ
cana-851	102	5	learning	learning	NOUN
cana-851	102	6	models	model	NOUN
cana-851	102	7	,	,	PUNCT
cana-851	102	8	such	such	ADJ
cana-851	102	9	as	as	ADP
cana-851	102	10	resnet50v2	resnet50v2	PROPN
cana-851	102	11	,	,	PUNCT
cana-851	102	12	inceptionv3	inceptionv3	NOUN
cana-851	102	13	,	,	PUNCT
cana-851	102	14	and	and	CCONJ
cana-851	102	15	mobilenetv2	mobilenetv2	PROPN
cana-851	102	16	,	,	PUNCT
cana-851	102	17	that	that	PRON
cana-851	102	18	have	have	AUX
cana-851	102	19	been	be	AUX
cana-851	102	20	fine	fine	ADV
cana-851	102	21	-	-	PUNCT
cana-851	102	22	tuned	tune	VERB
cana-851	102	23	on	on	ADP
cana-851	102	24	a	a	DET
cana-851	102	25	custom	custom	NOUN
cana-851	102	26	dataset	dataset	NOUN
cana-851	102	27	named	name	VERB
cana-851	102	28	flowernet	flowernet	NOUN
cana-851	102	29	.	.	PUNCT
cana-851	103	1	the	the	DET
cana-851	103	2	accuracy	accuracy	NOUN
cana-851	103	3	of	of	ADP
cana-851	103	4	the	the	DET
cana-851	103	5	models	model	NOUN
cana-851	103	6	is	be	AUX
cana-851	103	7	evaluated	evaluate	VERB
cana-851	103	8	using	use	VERB
cana-851	103	9	a	a	DET
cana-851	103	10	test	test	NOUN
cana-851	103	11	dataset	dataset	NOUN
cana-851	103	12	,	,	PUNCT
cana-851	103	13	and	and	CCONJ
cana-851	103	14	the	the	DET
cana-851	103	15	best	good	ADJ
cana-851	103	16	performing	perform	VERB
cana-851	103	17	model	model	NOUN
cana-851	103	18	achieves	achieve	VERB
cana-851	103	19	an	an	DET
cana-851	103	20	accuracy	accuracy	NOUN
cana-851	103	21	of	of	ADP
cana-851	103	22	99.74	99.74	NUM
cana-851	103	23	%	%	NOUN
cana-851	103	24	with	with	ADP
cana-851	103	25	a	a	DET
cana-851	103	26	prediction	prediction	NOUN
cana-851	103	27	period	period	NOUN
cana-851	103	28	of	of	ADP
cana-851	103	29	0.09	0.09	NUM
cana-851	103	30	seconds	second	NOUN
cana-851	103	31	.	.	PUNCT
cana-851	104	1	the	the	DET
cana-851	104	2	developed	develop	VERB
cana-851	104	3	mobile	mobile	ADJ
cana-851	104	4	application	application	NOUN
cana-851	104	5	,	,	PUNCT
cana-851	104	6	the	the	DET
cana-851	104	7	inclusion	inclusion	NOUN
cana-851	104	8	of	of	ADP
cana-851	104	9	the	the	DET
cana-851	104	10	dataset	dataset	NOUN
cana-851	104	11	and	and	CCONJ
cana-851	104	12	deep	deep	ADJ
cana-851	104	13	learning	learning	NOUN
cana-851	104	14	models	model	NOUN
cana-851	104	15	can	can	AUX
cana-851	104	16	facilitate	facilitate	VERB
cana-851	104	17	future	future	ADJ
cana-851	104	18	study	study	NOUN
cana-851	104	19	in	in	ADP
cana-851	104	20	the	the	DET
cana-851	104	21	field	field	NOUN
cana-851	104	22	of	of	ADP
cana-851	104	23	flower	flower	NOUN
cana-851	104	24	recognition[36].performs	recognition[36].perform	NOUN
cana-851	104	25	slightly	slightly	ADV
cana-851	104	26	worse	bad	ADJ
cana-851	104	27	in	in	ADP
cana-851	104	28	terms	term	NOUN
cana-851	104	29	of	of	ADP
cana-851	104	30	flops	flop	NOUN
cana-851	104	31	(	(	PUNCT
cana-851	104	32	floating	float	VERB
cana-851	104	33	point	point	NOUN
cana-851	104	34	operations	operation	NOUN
cana-851	104	35	)	)	PUNCT
cana-851	104	36	compared	compare	VERB
cana-851	104	37	to	to	ADP
cana-851	104	38	the	the	DET
cana-851	104	39	baseline	baseline	NOUN
cana-851	104	40	model	model	NOUN
cana-851	104	41	(	(	PUNCT
cana-851	104	42	alexnet)[37	alexnet)[37	PROPN
cana-851	104	43	]	]	PUNCT
cana-851	104	44	.	.	PUNCT
cana-851	105	1	however	however	ADV
cana-851	105	2	,	,	PUNCT
cana-851	105	3	the	the	DET
cana-851	105	4	presence	presence	NOUN
cana-851	105	5	of	of	ADP
cana-851	105	6	several	several	ADJ
cana-851	105	7	diverse	diverse	ADJ
cana-851	105	8	flower	flower	NOUN
cana-851	105	9	species	specie	NOUN
cana-851	105	10	is	be	AUX
cana-851	105	11	a	a	DET
cana-851	105	12	significant	significant	ADJ
cana-851	105	13	obstacle	obstacle	NOUN
cana-851	105	14	and	and	CCONJ
cana-851	105	15	adds	add	VERB
cana-851	105	16	complexity	complexity	NOUN
cana-851	105	17	to	to	ADP
cana-851	105	18	the	the	DET
cana-851	105	19	task	task	NOUN
cana-851	105	20	of	of	ADP
cana-851	105	21	accurately	accurately	ADV
cana-851	105	22	detecting	detect	VERB
cana-851	105	23	and	and	CCONJ
cana-851	105	24	classifying	classify	VERB
cana-851	105	25	them	they	PRON
cana-851	105	26	.	.	PUNCT
cana-851	106	1	furthermore	furthermore	ADV
cana-851	106	2	,	,	PUNCT
cana-851	106	3	the	the	DET
cana-851	106	4	conventional	conventional	ADJ
cana-851	106	5	cnn	cnn	NOUN
cana-851	106	6	model	model	NOUN
cana-851	106	7	and	and	CCONJ
cana-851	106	8	other	other	ADJ
cana-851	106	9	pre	pre	ADJ
cana-851	106	10	-	-	ADJ
cana-851	106	11	trained	train	VERB
cana-851	106	12	models	model	NOUN
cana-851	106	13	such	such	ADJ
cana-851	106	14	as	as	ADP
cana-851	106	15	vgg16	vgg16	PROPN
cana-851	106	16	,	,	PUNCT
cana-851	106	17	vgg19	vgg19	PROPN
cana-851	106	18	,	,	PUNCT
cana-851	106	19	xception	xception	NOUN
cana-851	106	20	,	,	PUNCT
cana-851	106	21	and	and	CCONJ
cana-851	106	22	mobilenet	mobilenet	NOUN
cana-851	106	23	-	-	PUNCT
cana-851	106	24	v2	v2	NOUN
cana-851	106	25	were	be	AUX
cana-851	106	26	unable	unable	ADJ
cana-851	106	27	to	to	PART
cana-851	106	28	achieve	achieve	VERB
cana-851	106	29	a	a	DET
cana-851	106	30	high	high	ADJ
cana-851	106	31	level	level	NOUN
cana-851	106	32	of	of	ADP
cana-851	106	33	validation	validation	NOUN
cana-851	106	34	accuracy[38	accuracy[38	NOUN
cana-851	106	35	]	]	PUNCT
cana-851	106	36	.	.	PUNCT
cana-851	107	1	identifying	identify	VERB
cana-851	107	2	flower	flower	NOUN
cana-851	107	3	species	specie	NOUN
cana-851	107	4	is	be	AUX
cana-851	107	5	a	a	DET
cana-851	107	6	difficult	difficult	ADJ
cana-851	107	7	undertaking	undertaking	NOUN
cana-851	107	8	because	because	SCONJ
cana-851	107	9	of	of	ADP
cana-851	107	10	the	the	DET
cana-851	107	11	differences	difference	NOUN
cana-851	107	12	in	in	ADP
cana-851	107	13	shape	shape	NOUN
cana-851	107	14	,	,	PUNCT
cana-851	107	15	size	size	NOUN
cana-851	107	16	,	,	PUNCT
cana-851	107	17	,	,	PUNCT
cana-851	107	18	and	and	CCONJ
cana-851	107	19	color	color	NOUN
cana-851	107	20	among	among	ADP
cana-851	107	21	various	various	ADJ
cana-851	107	22	flower	flower	NOUN
cana-851	107	23	types	type	NOUN
cana-851	107	24	[	[	X
cana-851	107	25	39	39	NUM
cana-851	107	26	]	]	PUNCT
cana-851	107	27	.	.	PUNCT
cana-851	108	1	nevertheless	nevertheless	ADV
cana-851	108	2	,	,	PUNCT
cana-851	108	3	the	the	DET
cana-851	108	4	research	research	NOUN
cana-851	108	5	recognizes	recognize	VERB
cana-851	108	6	the	the	DET
cana-851	108	7	difficulties	difficulty	NOUN
cana-851	108	8	encountered	encounter	VERB
cana-851	108	9	by	by	ADP
cana-851	108	10	current	current	ADJ
cana-851	108	11	technologies	technology	NOUN
cana-851	108	12	in	in	ADP
cana-851	108	13	the	the	DET
cana-851	108	14	classification	classification	NOUN
cana-851	108	15	of	of	ADP
cana-851	108	16	flowers	flower	NOUN
cana-851	108	17	,	,	PUNCT
cana-851	108	18	including	include	VERB
cana-851	108	19	issues	issue	NOUN
cana-851	108	20	like	like	ADP
cana-851	108	21	overfitting	overfitte	VERB
cana-851	108	22	,	,	PUNCT
cana-851	108	23	computational	computational	ADJ
cana-851	108	24	complexity	complexity	NOUN
cana-851	108	25	,	,	PUNCT
cana-851	108	26	restricted	restrict	VERB
cana-851	108	27	accuracy	accuracy	NOUN
cana-851	108	28	,	,	PUNCT
cana-851	108	29	and	and	CCONJ
cana-851	108	30	parameter	parameter	NOUN
cana-851	108	31	adjustment./	adjustment./	VERB
cana-851	108	32	the	the	DET
cana-851	108	33	goal	goal	NOUN
cana-851	108	34	is	be	AUX
cana-851	108	35	to	to	PART
cana-851	108	36	surpass	surpass	VERB
cana-851	108	37	the	the	DET
cana-851	108	38	performance	performance	NOUN
cana-851	108	39	of	of	ADP
cana-851	108	40	the	the	DET
cana-851	108	41	most	most	ADV
cana-851	108	42	advanced	advanced	ADJ
cana-851	108	43	techniques	technique	NOUN
cana-851	108	44	in	in	ADP
cana-851	108	45	the	the	DET
cana-851	108	46	classification	classification	NOUN
cana-851	108	47	of	of	ADP
cana-851	108	48	flowers	flower	NOUN
cana-851	108	49	and	and	CCONJ
cana-851	108	50	highlight	highlight	VERB
cana-851	108	51	the	the	DET
cana-851	108	52	significance	significance	NOUN
cana-851	108	53	of	of	ADP
cana-851	108	54	appropriate	appropriate	ADJ
cana-851	108	55	data	datum	NOUN
cana-851	108	56	preprocessing	preprocessing	NOUN
cana-851	108	57	and	and	CCONJ
cana-851	108	58	augmentation	augmentation	NOUN
cana-851	108	59	strategies	strategy	NOUN
cana-851	108	60	in	in	ADP
cana-851	108	61	attaining	attain	VERB
cana-851	108	62	optimal	optimal	ADJ
cana-851	108	63	performance	performance	NOUN
cana-851	108	64	[	[	PUNCT
cana-851	108	65	40].the	40].the	DET
cana-851	108	66	research	research	NOUN
cana-851	108	67	paper	paper	NOUN
cana-851	108	68	addresses	address	VERB
cana-851	108	69	the	the	DET
cana-851	108	70	challenge	challenge	NOUN
cana-851	108	71	of	of	ADP
cana-851	108	72	image	image	NOUN
cana-851	108	73	classification	classification	NOUN
cana-851	108	74	,	,	PUNCT
cana-851	108	75	pretrained	pretraine	VERB
cana-851	108	76	models	model	NOUN
cana-851	108	77	have	have	AUX
cana-851	108	78	been	be	AUX
cana-851	108	79	effectively	effectively	ADV
cana-851	108	80	employed	employ	VERB
cana-851	108	81	in	in	ADP
cana-851	108	82	a	a	DET
cana-851	108	83	notable	notable	ADJ
cana-851	108	84	domain	domain	NOUN
cana-851	108	85	of	of	ADP
cana-851	108	86	deep	deep	ADJ
cana-851	108	87	learning	learning	NOUN
cana-851	108	88	.	.	PUNCT
cana-851	109	1	[	[	X
cana-851	109	2	41].the	41].the	DET
cana-851	109	3	research	research	NOUN
cana-851	109	4	paper	paper	NOUN
cana-851	109	5	focuses	focus	VERB
cana-851	109	6	on	on	ADP
cana-851	109	7	the	the	DET
cana-851	109	8	challenges	challenge	NOUN
cana-851	109	9	faced	face	VERB
cana-851	109	10	in	in	ADP
cana-851	109	11	flower	flower	NOUN
cana-851	109	12	category	category	NOUN
cana-851	109	13	recognition	recognition	NOUN
cana-851	109	14	,	,	PUNCT
cana-851	109	15	a	a	DET
cana-851	109	16	fine	fine	ADV
cana-851	109	17	-	-	PUNCT
cana-851	109	18	grained	grain	VERB
cana-851	109	19	image	image	NOUN
cana-851	109	20	recognition	recognition	NOUN
cana-851	109	21	task	task	NOUN
cana-851	109	22	,	,	PUNCT
cana-851	109	23	including	include	VERB
cana-851	109	24	insufficient	insufficient	ADJ
cana-851	109	25	instances	instance	NOUN
cana-851	109	26	used	use	VERB
cana-851	109	27	for	for	ADP
cana-851	109	28	training	training	NOUN
cana-851	109	29	,	,	PUNCT
cana-851	109	30	similarity	similarity	NOUN
cana-851	109	31	within	within	ADP
cana-851	109	32	the	the	DET
cana-851	109	33	same	same	ADJ
cana-851	109	34	class	class	NOUN
cana-851	109	35	,	,	PUNCT
cana-851	109	36	and	and	CCONJ
cana-851	109	37	a	a	DET
cana-851	109	38	lack	lack	NOUN
cana-851	109	39	of	of	ADP
cana-851	109	40	precision	precision	NOUN
cana-851	109	41	in	in	ADP
cana-851	109	42	recognizing	recognize	VERB
cana-851	109	43	different	different	ADJ
cana-851	109	44	flower	flower	NOUN
cana-851	109	45	categories[42].the	categories[42].the	PROPN
cana-851	109	46	research	research	NOUN
cana-851	109	47	paper	paper	NOUN
cana-851	109	48	addresses	address	VERB
cana-851	109	49	the	the	DET
cana-851	109	50	issue	issue	NOUN
cana-851	109	51	that	that	SCONJ
cana-851	109	52	traditional	traditional	ADJ
cana-851	109	53	flower	flower	NOUN
cana-851	109	54	classification	classification	NOUN
cana-851	109	55	methods	method	NOUN
cana-851	109	56	and	and	CCONJ
cana-851	109	57	standard	standard	ADJ
cana-851	109	58	convolutional	convolutional	ADJ
cana-851	109	59	neural	neural	ADJ
cana-851	109	60	networks	network	NOUN
cana-851	109	61	struggle	struggle	VERB
cana-851	109	62	to	to	PART
cana-851	109	63	mitigate	mitigate	VERB
cana-851	109	64	the	the	DET
cana-851	109	65	impact	impact	NOUN
cana-851	109	66	of	of	ADP
cana-851	109	67	the	the	DET
cana-851	109	68	flower	flower	NOUN
cana-851	109	69	background	background	NOUN
cana-851	109	70	,	,	PUNCT
cana-851	109	71	leading	lead	VERB
cana-851	109	72	to	to	ADP
cana-851	109	73	suboptimal	suboptimal	ADJ
cana-851	109	74	classification	classification	NOUN
cana-851	109	75	results[10	results[10	NOUN
cana-851	109	76	]	]	PUNCT
cana-851	109	77	.	.	PUNCT
cana-851	110	1	[	[	X
cana-851	110	2	19	19	NUM
cana-851	110	3	]	]	PUNCT
cana-851	110	4	.	.	PUNCT
cana-851	111	1	figure	figure	NOUN
cana-851	111	2	2	2	NUM
cana-851	111	3	.	.	PUNCT
cana-851	111	4	highlight	highlight	VERB
cana-851	111	5	the	the	DET
cana-851	111	6	number	number	NOUN
cana-851	111	7	of	of	ADP
cana-851	111	8	challenges	challenge	NOUN
cana-851	111	9	solved	solve	VERB
cana-851	111	10	using	use	VERB
cana-851	111	11	dl	dl	PROPN
cana-851	111	12	based	base	VERB
cana-851	111	13	on	on	ADP
cana-851	111	14	each	each	DET
cana-851	111	15	application	application	NOUN
cana-851	111	16	communications	communication	NOUN
cana-851	111	17	on	on	ADP
cana-851	111	18	applied	apply	VERB
cana-851	111	19	nonlinear	nonlinear	ADJ
cana-851	111	20	analysis	analysis	NOUN
cana-851	111	21	issn	issn	NOUN
cana-851	111	22	:	:	PUNCT
cana-851	111	23	1074	1074	NUM
cana-851	111	24	-	-	PUNCT
cana-851	111	25	133x	133x	NUM
cana-851	111	26	vol	vol	NOUN
cana-851	111	27	31	31	NUM
cana-851	111	28	no	no	NOUN
cana-851	111	29	.	.	PUNCT
cana-851	112	1	4s	4s	NUM
cana-851	112	2	(	(	PUNCT
cana-851	112	3	2024	2024	NUM
cana-851	112	4	)	)	PUNCT
cana-851	112	5	277	277	NUM
cana-851	112	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	112	7	figure	figure	NOUN
cana-851	112	8	3	3	NUM
cana-851	112	9	.	.	NOUN
cana-851	112	10	number	number	NOUN
cana-851	112	11	of	of	ADP
cana-851	112	12	applications	application	NOUN
cana-851	112	13	utilized	utilize	VERB
cana-851	112	14	deep	deep	ADJ
cana-851	112	15	learning	learning	NOUN
cana-851	112	16	in	in	ADP
cana-851	112	17	literature	literature	NOUN
cana-851	112	18	review	review	PROPN
cana-851	112	19	5	5	NUM
cana-851	112	20	.	.	PUNCT
cana-851	112	21	challenge	challenge	NOUN
cana-851	112	22	solved	solve	VERB
cana-851	112	23	using	use	VERB
cana-851	112	24	hybrid	hybrid	ADJ
cana-851	112	25	models	model	NOUN
cana-851	112	26	currently	currently	ADV
cana-851	112	27	,	,	PUNCT
cana-851	112	28	differentiating	differentiate	VERB
cana-851	112	29	flowers	flower	NOUN
cana-851	112	30	in	in	ADP
cana-851	112	31	image	image	NOUN
cana-851	112	32	processing	processing	NOUN
cana-851	112	33	systems	system	NOUN
cana-851	112	34	remains	remain	VERB
cana-851	112	35	a	a	DET
cana-851	112	36	challenging	challenging	ADJ
cana-851	112	37	endeavor	endeavor	NOUN
cana-851	112	38	.	.	PUNCT
cana-851	113	1	the	the	DET
cana-851	113	2	primary	primary	ADJ
cana-851	113	3	factor	factor	NOUN
cana-851	113	4	contributing	contribute	VERB
cana-851	113	5	to	to	ADP
cana-851	113	6	this	this	DET
cana-851	113	7	phenomenon	phenomenon	NOUN
cana-851	113	8	is	be	AUX
cana-851	113	9	the	the	DET
cana-851	113	10	shared	share	VERB
cana-851	113	11	resemblance	resemblance	NOUN
cana-851	113	12	in	in	ADP
cana-851	113	13	shape	shape	NOUN
cana-851	113	14	and	and	CCONJ
cana-851	113	15	color	color	NOUN
cana-851	113	16	among	among	ADP
cana-851	113	17	many	many	ADJ
cana-851	113	18	flower	flower	NOUN
cana-851	113	19	species	specie	NOUN
cana-851	113	20	,	,	PUNCT
cana-851	113	21	including	include	VERB
cana-851	113	22	grass	grass	NOUN
cana-851	113	23	and	and	CCONJ
cana-851	113	24	leaves	leave	NOUN
cana-851	113	25	,	,	PUNCT
cana-851	113	26	which	which	PRON
cana-851	113	27	poses	pose	VERB
cana-851	113	28	challenges	challenge	NOUN
cana-851	113	29	in	in	ADP
cana-851	113	30	differentiation[2].while	differentiation[2].while	NOUN
cana-851	113	31	advancements	advancement	NOUN
cana-851	113	32	in	in	ADP
cana-851	113	33	deep	deep	ADJ
cana-851	113	34	neural	neural	ADJ
cana-851	113	35	networks	network	NOUN
cana-851	113	36	and	and	CCONJ
cana-851	113	37	computer	computer	NOUN
cana-851	113	38	vision	vision	NOUN
cana-851	113	39	have	have	AUX
cana-851	113	40	improved	improve	VERB
cana-851	113	41	the	the	DET
cana-851	113	42	accuracy	accuracy	NOUN
cana-851	113	43	of	of	ADP
cana-851	113	44	flower	flower	NOUN
cana-851	113	45	classification	classification	NOUN
cana-851	113	46	,	,	PUNCT
cana-851	113	47	there	there	PRON
cana-851	113	48	is	be	VERB
cana-851	113	49	still	still	ADV
cana-851	113	50	a	a	DET
cana-851	113	51	need	need	NOUN
cana-851	113	52	for	for	SCONJ
cana-851	113	53	further	further	ADJ
cana-851	113	54	improvement/	improvement/	NUM
cana-851	113	55	the	the	DET
cana-851	113	56	paper	paper	NOUN
cana-851	113	57	addresses	address	VERB
cana-851	113	58	the	the	DET
cana-851	113	59	problem	problem	NOUN
cana-851	113	60	of	of	ADP
cana-851	113	61	accurate	accurate	ADJ
cana-851	113	62	classification	classification	NOUN
cana-851	113	63	of	of	ADP
cana-851	113	64	flowers	flower	NOUN
cana-851	113	65	,	,	PUNCT
cana-851	113	66	which	which	PRON
cana-851	113	67	is	be	AUX
cana-851	113	68	a	a	DET
cana-851	113	69	challenging	challenging	ADJ
cana-851	113	70	task	task	NOUN
cana-851	113	71	because	because	SCONJ
cana-851	113	72	of	of	ADP
cana-851	113	73	the	the	DET
cana-851	113	74	significant	significant	ADJ
cana-851	113	75	diversity	diversity	NOUN
cana-851	113	76	of	of	ADP
cana-851	113	77	flowers	flower	NOUN
cana-851	113	78	types	type	NOUN
cana-851	113	79	and	and	CCONJ
cana-851	113	80	species	specie	NOUN
cana-851	113	81	[	[	X
cana-851	113	82	4	4	NUM
cana-851	113	83	]	]	PUNCT
cana-851	113	84	.	.	PUNCT
cana-851	114	1	manual	manual	ADJ
cana-851	114	2	classification	classification	NOUN
cana-851	114	3	can	can	AUX
cana-851	114	4	be	be	AUX
cana-851	114	5	subjective	subjective	ADJ
cana-851	114	6	and	and	CCONJ
cana-851	114	7	prone	prone	ADJ
cana-851	114	8	to	to	ADP
cana-851	114	9	human	human	ADJ
cana-851	114	10	error	error	NOUN
cana-851	114	11	,	,	PUNCT
cana-851	114	12	leading	lead	VERB
cana-851	114	13	to	to	ADP
cana-851	114	14	inconsistencies	inconsistency	NOUN
cana-851	114	15	in	in	ADP
cana-851	114	16	the	the	DET
cana-851	114	17	results	result	NOUN
cana-851	114	18	.	.	PUNCT
cana-851	115	1	this	this	DET
cana-851	115	2	manual	manual	ADJ
cana-851	115	3	process	process	NOUN
cana-851	115	4	is	be	AUX
cana-851	115	5	not	not	PART
cana-851	115	6	scalable	scalable	ADJ
cana-851	115	7	and	and	CCONJ
cana-851	115	8	may	may	AUX
cana-851	115	9	not	not	PART
cana-851	115	10	always	always	ADV
cana-851	115	11	yield	yield	VERB
cana-851	115	12	accurate	accurate	ADJ
cana-851	115	13	or	or	CCONJ
cana-851	115	14	reliable	reliable	ADJ
cana-851	115	15	classifications[43].the	classifications[43].the	DET
cana-851	115	16	research	research	NOUN
cana-851	115	17	paper	paper	NOUN
cana-851	115	18	addresses	address	VERB
cana-851	115	19	the	the	DET
cana-851	115	20	challenge	challenge	NOUN
cana-851	115	21	of	of	ADP
cana-851	115	22	flower	flower	NOUN
cana-851	115	23	classification	classification	NOUN
cana-851	115	24	in	in	ADP
cana-851	115	25	the	the	DET
cana-851	115	26	presence	presence	NOUN
cana-851	115	27	of	of	ADP
cana-851	115	28	high	high	ADJ
cana-851	115	29	intra	intra	ADJ
cana-851	115	30	-	-	ADJ
cana-851	115	31	class	class	ADJ
cana-851	115	32	variation	variation	NOUN
cana-851	115	33	within	within	ADP
cana-851	115	34	the	the	DET
cana-851	115	35	oxford	oxford	ADJ
cana-851	115	36	102	102	NUM
cana-851	115	37	flowers	flower	NOUN
cana-851	115	38	dataset[44	dataset[44	VERB
cana-851	115	39	]	]	PUNCT
cana-851	115	40	.	.	PUNCT
cana-851	116	1	6	6	X
cana-851	116	2	.	.	X
cana-851	116	3	ai	ai	AUX
cana-851	116	4	methods	method	NOUN
cana-851	116	5	and	and	CCONJ
cana-851	116	6	datasets	dataset	NOUN
cana-851	116	7	used	use	VERB
cana-851	116	8	in	in	ADP
cana-851	116	9	the	the	DET
cana-851	116	10	literature	literature	NOUN
cana-851	116	11	different	different	ADJ
cana-851	116	12	ai	ai	VERB
cana-851	116	13	techniques	technique	NOUN
cana-851	116	14	and	and	CCONJ
cana-851	116	15	algorithms	algorithm	NOUN
cana-851	116	16	have	have	AUX
cana-851	116	17	been	be	AUX
cana-851	116	18	developed	develop	VERB
cana-851	116	19	and	and	CCONJ
cana-851	116	20	presented	present	VERB
cana-851	116	21	throughout	throughout	ADP
cana-851	116	22	the	the	DET
cana-851	116	23	years	year	NOUN
cana-851	116	24	and	and	CCONJ
cana-851	116	25	various	various	ADJ
cana-851	116	26	researchers	researcher	NOUN
cana-851	116	27	worldwide	worldwide	ADV
cana-851	116	28	implemented	implement	VERB
cana-851	116	29	and	and	CCONJ
cana-851	116	30	enhanced	enhance	VERB
cana-851	116	31	these	these	DET
cana-851	116	32	methods	method	NOUN
cana-851	116	33	in	in	ADP
cana-851	116	34	different	different	ADJ
cana-851	116	35	applications	application	NOUN
cana-851	116	36	.	.	PUNCT
cana-851	117	1	moreover	moreover	ADV
cana-851	117	2	,	,	PUNCT
cana-851	117	3	each	each	DET
cana-851	117	4	ai	ai	VERB
cana-851	117	5	method	method	NOUN
cana-851	117	6	required	require	VERB
cana-851	117	7	a	a	DET
cana-851	117	8	dataset	dataset	NOUN
cana-851	117	9	that	that	PRON
cana-851	117	10	was	be	AUX
cana-851	117	11	employed	employ	VERB
cana-851	117	12	to	to	PART
cana-851	117	13	train	train	VERB
cana-851	117	14	and	and	CCONJ
cana-851	117	15	improve	improve	VERB
cana-851	117	16	the	the	DET
cana-851	117	17	results	result	NOUN
cana-851	117	18	of	of	ADP
cana-851	117	19	these	these	DET
cana-851	117	20	techniques	technique	NOUN
cana-851	117	21	.	.	PUNCT
cana-851	118	1	table	table	NOUN
cana-851	118	2	2	2	NUM
cana-851	118	3	.	.	PUNCT
cana-851	118	4	summarizes	summarize	VERB
cana-851	118	5	the	the	DET
cana-851	118	6	machine	machine	NOUN
cana-851	118	7	learning	learning	NOUN
cana-851	118	8	and	and	CCONJ
cana-851	118	9	deep	deep	ADJ
cana-851	118	10	learning	learning	NOUN
cana-851	118	11	methodologies	methodology	NOUN
cana-851	118	12	,	,	PUNCT
cana-851	118	13	as	as	ADV
cana-851	118	14	well	well	ADV
cana-851	118	15	as	as	ADP
cana-851	118	16	the	the	DET
cana-851	118	17	metrics	metric	NOUN
cana-851	118	18	utilized	utilize	VERB
cana-851	118	19	for	for	ADP
cana-851	118	20	evaluating	evaluate	VERB
cana-851	118	21	these	these	DET
cana-851	118	22	techniques	technique	NOUN
cana-851	118	23	,	,	PUNCT
cana-851	118	24	aims	aim	NOUN
cana-851	118	25	of	of	ADP
cana-851	118	26	these	these	DET
cana-851	118	27	techniques	technique	NOUN
cana-851	118	28	must	must	AUX
cana-851	118	29	be	be	AUX
cana-851	118	30	classification	classification	NOUN
cana-851	118	31	-	-	PUNCT
cana-851	118	32	detection	detection	NOUN
cana-851	118	33	-	-	PUNCT
cana-851	118	34	segmentationrecognition	segmentationrecognition	NOUN
cana-851	118	35	-	-	PUNCT
cana-851	118	36	identification	identification	NOUN
cana-851	118	37	-	-	PUNCT
cana-851	118	38	localization	localization	NOUN
cana-851	118	39	with	with	ADP
cana-851	118	40	the	the	DET
cana-851	118	41	metrics	metric	NOUN
cana-851	118	42	used	use	VERB
cana-851	118	43	to	to	PART
cana-851	118	44	measure	measure	VERB
cana-851	118	45	the	the	DET
cana-851	118	46	performance	performance	NOUN
cana-851	118	47	.	.	PUNCT
cana-851	119	1	table	table	NOUN
cana-851	119	2	2	2	NUM
cana-851	119	3	.	.	PUNCT
cana-851	120	1	ml	ml	AUX
cana-851	120	2	dl	dl	PROPN
cana-851	120	3	methods	method	NOUN
cana-851	120	4	in	in	ADP
cana-851	120	5	the	the	DET
cana-851	120	6	literature	literature	NOUN
cana-851	120	7	ref	ref	NOUN
cana-851	120	8	dl	dl	X
cana-851	120	9	ml	ml	NOUN
cana-851	120	10	technique	technique	NOUN
cana-851	120	11	metrics	metric	NOUN
cana-851	120	12	used	use	VERB
cana-851	120	13	aim	aim	VERB
cana-851	120	14	[	[	X
cana-851	120	15	20	20	NUM
cana-851	120	16	]	]	SYM
cana-851	120	17	dl(cnn	dl(cnn	PROPN
cana-851	120	18	)	)	PUNCT
cana-851	120	19	the	the	DET
cana-851	120	20	f1	f1	NOUN
cana-851	120	21	-	-	PUNCT
cana-851	120	22	score	score	NOUN
cana-851	120	23	average=	average=	PROPN
cana-851	120	24	0.85	0.85	NUM
cana-851	120	25	,	,	PUNCT
cana-851	120	26	precession	precession	NOUN
cana-851	120	27	average=	average=	PROPN
cana-851	120	28	0.85	0.85	NUM
cana-851	120	29	,	,	PUNCT
cana-851	120	30	and	and	CCONJ
cana-851	120	31	recall	recall	VERB
cana-851	120	32	average=	average=	PROPN
cana-851	120	33	0.85	0.85	NUM
cana-851	120	34	.	.	PUNCT
cana-851	121	1	the	the	DET
cana-851	121	2	performance	performance	NOUN
cana-851	121	3	of	of	ADP
cana-851	121	4	this	this	DET
cana-851	121	5	model	model	NOUN
cana-851	121	6	is	be	AUX
cana-851	121	7	quite	quite	ADV
cana-851	121	8	good	good	ADJ
cana-851	121	9	with	with	ADP
cana-851	121	10	85	85	NUM
cana-851	121	11	%	%	NOUN
cana-851	121	12	accuracy	accuracy	NOUN
cana-851	121	13	classification	classification	NOUN
cana-851	121	14	[	[	X
cana-851	121	15	21	21	NUM
cana-851	121	16	]	]	X
cana-851	121	17	dl	dl	PROPN
cana-851	121	18	(	(	PUNCT
cana-851	121	19	nas	nas	PROPN
cana-851	121	20	-	-	PUNCT
cana-851	121	21	fpn	fpn	VERB
cana-851	121	22	r	r	NOUN
cana-851	121	23	-	-	PUNCT
cana-851	121	24	cnn	cnn	PROPN
cana-851	121	25	)	)	PUNCT
cana-851	121	26	the	the	DET
cana-851	121	27	maximum	maximum	ADJ
cana-851	121	28	average	average	ADJ
cana-851	121	29	precision	precision	NOUN
cana-851	121	30	(	(	PUNCT
cana-851	121	31	map	map	NOUN
cana-851	121	32	)	)	PUNCT
cana-851	121	33	score	score	NOUN
cana-851	121	34	achieved	achieve	VERB
cana-851	121	35	was	be	AUX
cana-851	121	36	87.6	87.6	NUM
cana-851	121	37	%	%	NOUN
cana-851	121	38	on	on	ADP
cana-851	121	39	a	a	DET
cana-851	121	40	dataset	dataset	NOUN
cana-851	121	41	consisting	consist	VERB
cana-851	121	42	of	of	ADP
cana-851	121	43	102	102	NUM
cana-851	121	44	flower	flower	NOUN
cana-851	121	45	classes	class	NOUN
cana-851	121	46	,	,	PUNCT
cana-851	121	47	and	and	CCONJ
cana-851	121	48	classification	classification	NOUN
cana-851	121	49	,	,	PUNCT
cana-851	121	50	localization	localization	NOUN
cana-851	121	51	,	,	PUNCT
cana-851	121	52	communications	communication	NOUN
cana-851	121	53	on	on	ADP
cana-851	121	54	applied	apply	VERB
cana-851	121	55	nonlinear	nonlinear	ADJ
cana-851	121	56	analysis	analysis	NOUN
cana-851	121	57	issn	issn	NOUN
cana-851	121	58	:	:	PUNCT
cana-851	121	59	1074	1074	NUM
cana-851	121	60	-	-	PUNCT
cana-851	121	61	133x	133x	NUM
cana-851	121	62	vol	vol	NOUN
cana-851	121	63	31	31	NUM
cana-851	121	64	no	no	NOUN
cana-851	121	65	.	.	PUNCT
cana-851	122	1	4s	4s	NUM
cana-851	122	2	(	(	PUNCT
cana-851	122	3	2024	2024	NUM
cana-851	122	4	)	)	PUNCT
cana-851	122	5	278	278	NUM
cana-851	122	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	122	7	96.2	96.2	NUM
cana-851	122	8	%	%	NOUN
cana-851	122	9	on	on	ADP
cana-851	122	10	a	a	DET
cana-851	122	11	dataset	dataset	NOUN
cana-851	122	12	consisting	consist	VERB
cana-851	122	13	of	of	ADP
cana-851	122	14	30	30	NUM
cana-851	122	15	flower	flower	NOUN
cana-851	122	16	classes	class	NOUN
cana-851	122	17	.	.	PUNCT
cana-851	123	1	detection	detection	NOUN
cana-851	123	2	,	,	PUNCT
cana-851	124	1	[	[	X
cana-851	124	2	22	22	NUM
cana-851	124	3	]	]	X
cana-851	124	4	dl	dl	PROPN
cana-851	124	5	(	(	PUNCT
cana-851	124	6	mobilenet	mobilenet	PROPN
cana-851	124	7	,	,	PUNCT
cana-851	124	8	densenet	densenet	NOUN
cana-851	124	9	,	,	PUNCT
cana-851	124	10	inception	inception	NOUN
cana-851	124	11	,	,	PUNCT
cana-851	124	12	and	and	CCONJ
cana-851	124	13	resnet	resnet	ADJ
cana-851	124	14	)	)	PUNCT
cana-851	124	15	null	null	ADJ
cana-851	124	16	classification	classification	NOUN
cana-851	124	17	[	[	X
cana-851	124	18	11	11	NUM
cana-851	124	19	]	]	SYM
cana-851	124	20	ml	ml	PROPN
cana-851	124	21	(	(	PUNCT
cana-851	124	22	knn	knn	VERB
cana-851	124	23	random	random	ADJ
cana-851	124	24	forest	forest	NOUN
cana-851	124	25	decision	decision	NOUN
cana-851	124	26	tree	tree	NOUN
cana-851	124	27	)	)	PUNCT
cana-851	124	28	system	system	NOUN
cana-851	124	29	achieves	achieve	VERB
cana-851	124	30	the	the	DET
cana-851	124	31	accuracy	accuracy	NOUN
cana-851	124	32	of	of	ADP
cana-851	124	33	94.8	94.8	NUM
cana-851	124	34	%	%	NOUN
cana-851	124	35	.	.	PUNCT
cana-851	125	1	detection	detection	NOUN
cana-851	125	2	[	[	X
cana-851	125	3	23	23	NUM
cana-851	125	4	]	]	X
cana-851	125	5	dl	dl	PROPN
cana-851	125	6	(	(	PUNCT
cana-851	125	7	light	light	PROPN
cana-851	125	8	cnn	cnn	PROPN
cana-851	125	9	)	)	PUNCT
cana-851	125	10	null	null	ADJ
cana-851	125	11	classification	classification	NOUN
cana-851	125	12	detection	detection	NOUN
cana-851	125	13	[	[	X
cana-851	125	14	24	24	NUM
cana-851	125	15	]	]	SYM
cana-851	125	16	dl(cnn	dl(cnn	PROPN
cana-851	125	17	)	)	PUNCT
cana-851	125	18	our	our	PRON
cana-851	125	19	approach	approach	NOUN
cana-851	125	20	achieves	achieve	VERB
cana-851	125	21	76.54	76.54	NUM
cana-851	125	22	%	%	NOUN
cana-851	125	23	classification	classification	NOUN
cana-851	125	24	accuracy	accuracy	NOUN
cana-851	125	25	classification	classification	NOUN
cana-851	125	26	[	[	X
cana-851	125	27	9	9	NUM
cana-851	125	28	]	]	PUNCT
cana-851	125	29	dl(densenet121	dl(densenet121	PROPN
cana-851	125	30	)	)	PUNCT
cana-851	125	31	achieve	achieve	VERB
cana-851	125	32	the	the	DET
cana-851	125	33	accuracy	accuracy	NOUN
cana-851	125	34	of	of	ADP
cana-851	125	35	98.6	98.6	NUM
cana-851	125	36	%	%	NOUN
cana-851	125	37	classification	classification	NOUN
cana-851	126	1	[	[	X
cana-851	126	2	6	6	NUM
cana-851	126	3	]	]	X
cana-851	126	4	dl	dl	PROPN
cana-851	126	5	(	(	PUNCT
cana-851	126	6	fcn	fcn	PROPN
cana-851	126	7	cnn	cnn	PROPN
cana-851	126	8	)	)	PUNCT
cana-851	126	9	accuracy	accuracy	NOUN
cana-851	126	10	:	:	PUNCT
cana-851	126	11	97	97	NUM
cana-851	126	12	%	%	NOUN
cana-851	126	13	on	on	ADP
cana-851	126	14	all	all	DET
cana-851	126	15	datasets	dataset	NOUN
cana-851	126	16	segmentation	segmentation	NOUN
cana-851	126	17	classification	classification	NOUN
cana-851	126	18	[	[	X
cana-851	126	19	25	25	NUM
cana-851	126	20	]	]	X
cana-851	126	21	dl	dl	PROPN
cana-851	126	22	(	(	PUNCT
cana-851	126	23	yolov5	yolov5	NOUN
cana-851	126	24	)	)	PUNCT
cana-851	126	25	precision	precision	NOUN
cana-851	126	26	reaching	reach	VERB
cana-851	126	27	0.942	0.942	NUM
cana-851	126	28	,	,	PUNCT
cana-851	126	29	recall	recall	VERB
cana-851	126	30	reaching	reach	VERB
cana-851	126	31	0.933	0.933	NUM
cana-851	126	32	,	,	PUNCT
cana-851	126	33	and	and	CCONJ
cana-851	126	34	map	map	VERB
cana-851	126	35	reaching	reach	VERB
cana-851	126	36	0.959	0.959	NUM
cana-851	126	37	.	.	PUNCT
cana-851	127	1	detection	detection	NOUN
cana-851	127	2	classification	classification	NOUN
cana-851	127	3	[	[	X
cana-851	127	4	3	3	NUM
cana-851	127	5	]	]	X
cana-851	127	6	dl	dl	X
cana-851	127	7	(	(	PUNCT
cana-851	127	8	deep	deep	PROPN
cana-851	127	9	cnn	cnn	PROPN
cana-851	127	10	)	)	PUNCT
cana-851	127	11	consequently	consequently	ADV
cana-851	127	12	,	,	PUNCT
cana-851	127	13	we	we	PRON
cana-851	127	14	achieved	achieve	VERB
cana-851	127	15	a	a	DET
cana-851	127	16	superior	superior	ADJ
cana-851	127	17	level	level	NOUN
cana-851	127	18	of	of	ADP
cana-851	127	19	accuracy	accuracy	NOUN
cana-851	127	20	of	of	ADP
cana-851	127	21	98.5	98.5	NUM
cana-851	127	22	%	%	NOUN
cana-851	127	23	for	for	ADP
cana-851	127	24	the	the	DET
cana-851	127	25	oxford	oxford	ADJ
cana-851	127	26	102	102	NUM
cana-851	127	27	-	-	PUNCT
cana-851	127	28	flowers	flower	NOUN
cana-851	127	29	dataset	dataset	VERB
cana-851	127	30	by	by	ADP
cana-851	127	31	employing	employ	VERB
cana-851	127	32	the	the	DET
cana-851	127	33	(	(	PUNCT
cana-851	127	34	svm	svm	ADJ
cana-851	127	35	)	)	PUNCT
cana-851	127	36	classifier	classifier	NOUN
cana-851	127	37	.	.	PUNCT
cana-851	128	1	the	the	DET
cana-851	128	2	oxford	oxford	ADJ
cana-851	128	3	17	17	NUM
cana-851	128	4	-	-	PUNCT
cana-851	128	5	flowers	flower	NOUN
cana-851	128	6	dataset	dataset	NOUN
cana-851	128	7	achieved	achieve	VERB
cana-851	128	8	a	a	DET
cana-851	128	9	remarkable	remarkable	ADJ
cana-851	128	10	accuracy	accuracy	NOUN
cana-851	128	11	of	of	ADP
cana-851	128	12	99.8	99.8	NUM
cana-851	128	13	%	%	NOUN
cana-851	128	14	using	use	VERB
cana-851	128	15	the	the	DET
cana-851	128	16	mlp	mlp	NOUN
cana-851	128	17	classifier	classifier	NOUN
cana-851	128	18	.	.	PUNCT
cana-851	129	1	classification	classification	NOUN
cana-851	130	1	[	[	X
cana-851	130	2	26	26	NUM
cana-851	130	3	]	]	X
cana-851	130	4	dl	dl	X
cana-851	130	5	(	(	PUNCT
cana-851	130	6	fine	fine	ADV
cana-851	130	7	-	-	PUNCT
cana-851	130	8	tuned	tune	VERB
cana-851	130	9	vgg16	vgg16	NOUN
cana-851	130	10	model	model	NOUN
cana-851	130	11	)	)	PUNCT
cana-851	130	12	the	the	DET
cana-851	130	13	model	model	NOUN
cana-851	130	14	attained	attain	VERB
cana-851	130	15	a	a	DET
cana-851	130	16	classification	classification	NOUN
cana-851	130	17	accuracy	accuracy	NOUN
cana-851	130	18	of	of	ADP
cana-851	130	19	97.67	97.67	NUM
cana-851	130	20	%	%	NOUN
cana-851	130	21	for	for	ADP
cana-851	130	22	the	the	DET
cana-851	130	23	validation	validation	NOUN
cana-851	130	24	set	set	NOUN
cana-851	130	25	and	and	CCONJ
cana-851	130	26	95.00	95.00	NUM
cana-851	130	27	%	%	NOUN
cana-851	130	28	for	for	ADP
cana-851	130	29	the	the	DET
cana-851	130	30	testing	testing	NOUN
cana-851	130	31	dataset	dataset	NOUN
cana-851	130	32	.	.	PUNCT
cana-851	131	1	classification	classification	NOUN
cana-851	131	2	[	[	X
cana-851	131	3	27	27	NUM
cana-851	131	4	]	]	SYM
cana-851	131	5	dl(mobilenet	dl(mobilenet	NOUN
cana-851	131	6	)	)	PUNCT
cana-851	131	7	null	null	ADJ
cana-851	131	8	classification	classification	NOUN
cana-851	131	9	[	[	X
cana-851	131	10	28	28	NUM
cana-851	131	11	]	]	X
cana-851	131	12	ssd	ssd	NOUN
cana-851	131	13	according	accord	VERB
cana-851	131	14	to	to	ADP
cana-851	131	15	the	the	DET
cana-851	131	16	experimental	experimental	ADJ
cana-851	131	17	data	datum	NOUN
cana-851	131	18	,	,	PUNCT
cana-851	131	19	the	the	DET
cana-851	131	20	average	average	ADJ
cana-851	131	21	accuracy	accuracy	NOUN
cana-851	131	22	is	be	AUX
cana-851	131	23	87.4	87.4	NUM
cana-851	131	24	%	%	NOUN
cana-851	131	25	using	use	VERB
cana-851	131	26	the	the	DET
cana-851	131	27	evaluation	evaluation	NOUN
cana-851	131	28	standard	standard	NOUN
cana-851	131	29	of	of	ADP
cana-851	131	30	pascal	pascal	PROPN
cana-851	131	31	voc2012	voc2012	NOUN
cana-851	131	32	,	,	PUNCT
cana-851	131	33	and	and	CCONJ
cana-851	131	34	83.64	83.64	NUM
cana-851	131	35	%	%	NOUN
cana-851	131	36	using	use	VERB
cana-851	131	37	the	the	DET
cana-851	131	38	evaluation	evaluation	NOUN
cana-851	131	39	standard	standard	NOUN
cana-851	131	40	of	of	ADP
cana-851	131	41	pascal	pascal	ADJ
cana-851	131	42	voc2007	voc2007	NOUN
cana-851	131	43	.	.	PUNCT
cana-851	132	1	detection	detection	NOUN
cana-851	132	2	[	[	X
cana-851	132	3	29	29	NUM
cana-851	132	4	]	]	SYM
cana-851	132	5	dl(cnn	dl(cnn	PROPN
cana-851	132	6	)	)	PUNCT
cana-851	132	7	and	and	CCONJ
cana-851	132	8	transfer	transfer	VERB
cana-851	132	9	learning	learning	NOUN
cana-851	132	10	in	in	ADP
cana-851	132	11	cnn	cnn	PROPN
cana-851	132	12	vgg16	vgg16	PROPN
cana-851	132	13	,	,	PUNCT
cana-851	132	14	mobilenet2	mobilenet2	PROPN
cana-851	132	15	,	,	PUNCT
cana-851	132	16	and	and	CCONJ
cana-851	132	17	resnet50	resnet50	VERB
cana-851	132	18	null	null	ADJ
cana-851	132	19	classification	classification	NOUN
cana-851	132	20	[	[	X
cana-851	132	21	30	30	NUM
cana-851	132	22	]	]	X
cana-851	132	23	dl(cnn	dl(cnn	PROPN
cana-851	132	24	)	)	PUNCT
cana-851	132	25	null	null	ADJ
cana-851	132	26	recognition	recognition	NOUN
cana-851	133	1	[	[	X
cana-851	133	2	31	31	NUM
cana-851	133	3	]	]	PUNCT
cana-851	133	4	dl(cnn	dl(cnn	PROPN
cana-851	133	5	)	)	PUNCT
cana-851	133	6	accuracy	accuracy	NOUN
cana-851	133	7	93.69	93.69	NUM
cana-851	133	8	classification	classification	NOUN
cana-851	134	1	[	[	X
cana-851	134	2	2	2	NUM
cana-851	134	3	]	]	PUNCT
cana-851	134	4	dl(cnn	dl(cnn	PROPN
cana-851	134	5	)	)	PUNCT
cana-851	134	6	and	and	CCONJ
cana-851	134	7	ml(svm	ml(svm	NOUN
cana-851	134	8	)	)	PUNCT
cana-851	134	9	the	the	DET
cana-851	134	10	support	support	NOUN
cana-851	134	11	vector	vector	NOUN
cana-851	134	12	machine	machine	NOUN
cana-851	134	13	(	(	PUNCT
cana-851	134	14	svm	svm	PROPN
cana-851	134	15	)	)	PUNCT
cana-851	134	16	approach	approach	NOUN
cana-851	134	17	produced	produce	VERB
cana-851	134	18	a	a	DET
cana-851	134	19	classification	classification	NOUN
cana-851	134	20	success	success	NOUN
cana-851	134	21	rate	rate	NOUN
cana-851	134	22	of	of	ADP
cana-851	134	23	98.91	98.91	NUM
cana-851	134	24	%	%	NOUN
cana-851	134	25	.	.	PUNCT
cana-851	135	1	classification	classification	NOUN
cana-851	135	2	[	[	X
cana-851	135	3	32	32	NUM
cana-851	135	4	]	]	X
cana-851	135	5	dl	dl	PROPN
cana-851	135	6	(	(	PUNCT
cana-851	135	7	modified	modify	VERB
cana-851	135	8	deepconvolution	deepconvolution	NOUN
cana-851	135	9	neural	neural	ADJ
cana-851	135	10	network	network	NOUN
cana-851	135	11	model	model	NOUN
cana-851	135	12	(	(	PUNCT
cana-851	135	13	mdcnn	mdcnn	PROPN
cana-851	135	14	)	)	PUNCT
cana-851	135	15	.	.	PUNCT
cana-851	136	1	accuracy	accuracy	NOUN
cana-851	136	2	up	up	ADP
cana-851	136	3	to	to	ADP
cana-851	136	4	98	98	NUM
cana-851	136	5	%	%	NOUN
cana-851	136	6	,	,	PUNCT
cana-851	136	7	classification	classification	NOUN
cana-851	136	8	,	,	PUNCT
cana-851	136	9	detection	detection	NOUN
cana-851	136	10	,	,	PUNCT
cana-851	136	11	segmentation	segmentation	NOUN
cana-851	137	1	[	[	X
cana-851	137	2	33	33	NUM
cana-851	137	3	]	]	X
cana-851	137	4	dl	dl	PROPN
cana-851	137	5	(	(	PUNCT
cana-851	137	6	alexnet	alexnet	ADJ
cana-851	137	7	model	model	NOUN
cana-851	137	8	)	)	PUNCT
cana-851	137	9	null	null	ADJ
cana-851	137	10	classification	classification	NOUN
cana-851	137	11	[	[	X
cana-851	137	12	34	34	NUM
cana-851	137	13	]	]	PUNCT
cana-851	137	14	dl(resnet50	dl(resnet50	NOUN
cana-851	137	15	)	)	PUNCT
cana-851	138	1	the	the	DET
cana-851	138	2	accuracy	accuracy	NOUN
cana-851	138	3	achieved	achieve	VERB
cana-851	138	4	by	by	ADP
cana-851	138	5	the	the	DET
cana-851	138	6	adam	adam	PROPN
cana-851	138	7	optimizer	optimizer	NOUN
cana-851	138	8	while	while	SCONJ
cana-851	138	9	using	use	VERB
cana-851	138	10	the	the	DET
cana-851	138	11	resnet50	resnet50	NOUN
cana-851	138	12	model	model	NOUN
cana-851	138	13	is	be	AUX
cana-851	138	14	93	93	NUM
cana-851	138	15	percent	percent	NOUN
cana-851	138	16	.	.	PUNCT
cana-851	139	1	classification	classification	NOUN
cana-851	139	2	[	[	X
cana-851	139	3	35	35	NUM
cana-851	139	4	]	]	SYM
cana-851	139	5	dl(mobilenetv3	dl(mobilenetv3	PROPN
cana-851	139	6	)	)	PUNCT
cana-851	139	7	higher	high	ADJ
cana-851	139	8	accuracy	accuracy	NOUN
cana-851	139	9	:	:	PUNCT
cana-851	139	10	the	the	DET
cana-851	139	11	improved	improved	ADJ
cana-851	139	12	mobilenetv3	mobilenetv3	NOUN
cana-851	139	13	achieved	achieve	VERB
cana-851	139	14	recognition	recognition	NOUN
cana-851	139	15	accuracy	accuracy	NOUN
cana-851	139	16	exceeding	exceed	VERB
cana-851	139	17	99	99	NUM
cana-851	139	18	%	%	NOUN
cana-851	139	19	recognition	recognition	NOUN
cana-851	140	1	[	[	X
cana-851	140	2	36	36	NUM
cana-851	140	3	]	]	X
cana-851	140	4	dl(mobilenetv2	dl(mobilenetv2	NOUN
cana-851	140	5	)	)	PUNCT
cana-851	140	6	got	get	VERB
cana-851	140	7	the	the	DET
cana-851	140	8	maximum	maximum	ADJ
cana-851	140	9	classification	classification	NOUN
cana-851	140	10	accuracy	accuracy	NOUN
cana-851	140	11	of	of	ADP
cana-851	140	12	95.90	95.90	NUM
cana-851	140	13	%	%	NOUN
cana-851	140	14	.	.	PUNCT
cana-851	141	1	identification	identification	NOUN
cana-851	141	2	[	[	X
cana-851	141	3	37	37	NUM
cana-851	141	4	]	]	X
cana-851	141	5	dl	dl	PROPN
cana-851	141	6	(	(	PUNCT
cana-851	141	7	alex	alex	PROPN
cana-851	141	8	net	net	PROPN
cana-851	141	9	)	)	PUNCT
cana-851	141	10	with	with	ADP
cana-851	141	11	oxford	oxford	PROPN
cana-851	141	12	17	17	NUM
cana-851	141	13	achieved	achieve	VERB
cana-851	141	14	accuracy	accuracy	NOUN
cana-851	141	15	89.3	89.3	NUM
cana-851	141	16	,	,	PUNCT
cana-851	141	17	with	with	ADP
cana-851	141	18	oxford	oxford	PROPN
cana-851	141	19	102	102	NUM
cana-851	141	20	achieved	achieve	VERB
cana-851	141	21	accuracy	accuracy	NOUN
cana-851	141	22	81.5	81.5	NUM
cana-851	141	23	,	,	PUNCT
cana-851	141	24	with	with	ADP
cana-851	141	25	china	china	PROPN
cana-851	141	26	5	5	NUM
cana-851	141	27	flower	flower	NOUN
cana-851	141	28	data	datum	NOUN
cana-851	141	29	set	set	VERB
cana-851	141	30	achieved	achieve	VERB
cana-851	141	31	accuracy	accuracy	NOUN
cana-851	141	32	93.3	93.3	NUM
cana-851	141	33	.	.	PUNCT
cana-851	142	1	classification	classification	NOUN
cana-851	142	2	[	[	X
cana-851	142	3	16	16	NUM
cana-851	142	4	]	]	SYM
cana-851	142	5	ml	ml	PROPN
cana-851	142	6	(	(	PUNCT
cana-851	142	7	multiclass	multiclass	ADJ
cana-851	142	8	svm	svm	PROPN
cana-851	142	9	)	)	PUNCT
cana-851	142	10	the	the	DET
cana-851	142	11	kl	kl	PROPN
cana-851	142	12	university	university	PROPN
cana-851	142	13	flower	flower	NOUN
cana-851	142	14	(	(	PUNCT
cana-851	142	15	kluf	kluf	ADV
cana-851	142	16	)	)	PUNCT
cana-851	142	17	dataset	dataset	NOUN
cana-851	142	18	achieves	achieve	VERB
cana-851	142	19	a	a	DET
cana-851	142	20	classification	classification	NOUN
cana-851	142	21	accuracy	accuracy	NOUN
cana-851	142	22	of	of	ADP
cana-851	142	23	98.3	98.3	NUM
cana-851	142	24	%	%	NOUN
cana-851	142	25	,	,	PUNCT
cana-851	142	26	while	while	SCONJ
cana-851	142	27	the	the	DET
cana-851	142	28	flower	flower	NOUN
cana-851	142	29	17	17	NUM
cana-851	142	30	dataset	dataset	NOUN
cana-851	142	31	has	have	VERB
cana-851	142	32	a	a	DET
cana-851	142	33	classification	classification	NOUN
cana-851	142	34	accuracy	accuracy	NOUN
cana-851	142	35	of	of	ADP
cana-851	142	36	97.7	97.7	NUM
cana-851	142	37	%	%	NOUN
cana-851	142	38	.	.	PUNCT
cana-851	143	1	classification	classification	NOUN
cana-851	143	2	[	[	X
cana-851	143	3	17	17	NUM
cana-851	143	4	]	]	SYM
cana-851	143	5	ml	ml	PROPN
cana-851	143	6	(	(	PUNCT
cana-851	143	7	multiclass	multiclass	ADJ
cana-851	143	8	svm	svm	PROPN
cana-851	143	9	)	)	PUNCT
cana-851	143	10	the	the	DET
cana-851	143	11	model	model	NOUN
cana-851	143	12	achieved	achieve	VERB
cana-851	143	13	an	an	DET
cana-851	143	14	average	average	ADJ
cana-851	143	15	accuracy	accuracy	NOUN
cana-851	143	16	of	of	ADP
cana-851	143	17	79	79	NUM
cana-851	143	18	%	%	NOUN
cana-851	143	19	classification	classification	NOUN
cana-851	143	20	communications	communication	NOUN
cana-851	143	21	on	on	ADP
cana-851	143	22	applied	apply	VERB
cana-851	143	23	nonlinear	nonlinear	ADJ
cana-851	143	24	analysis	analysis	NOUN
cana-851	143	25	issn	issn	NOUN
cana-851	143	26	:	:	PUNCT
cana-851	143	27	1074	1074	NUM
cana-851	143	28	-	-	PUNCT
cana-851	143	29	133x	133x	NUM
cana-851	143	30	vol	vol	NOUN
cana-851	143	31	31	31	NUM
cana-851	143	32	no	no	NOUN
cana-851	143	33	.	.	PUNCT
cana-851	144	1	4s	4s	NUM
cana-851	144	2	(	(	PUNCT
cana-851	144	3	2024	2024	NUM
cana-851	144	4	)	)	PUNCT
cana-851	144	5	279	279	NUM
cana-851	144	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	145	1	[	[	X
cana-851	145	2	18	18	NUM
cana-851	145	3	]	]	SYM
cana-851	145	4	ml	ml	X
cana-851	145	5	(	(	PUNCT
cana-851	145	6	support	support	NOUN
cana-851	145	7	vector	vector	NOUN
cana-851	145	8	machines	machine	NOUN
cana-851	145	9	(	(	PUNCT
cana-851	145	10	svm	svm	PROPN
cana-851	145	11	)	)	PUNCT
cana-851	145	12	and	and	CCONJ
cana-851	145	13	logistic	logistic	ADJ
cana-851	145	14	activation	activation	NOUN
cana-851	145	15	function	function	NOUN
cana-851	145	16	(	(	PUNCT
cana-851	145	17	laf	laf	PROPN
cana-851	145	18	)	)	PUNCT
cana-851	145	19	)	)	PUNCT
cana-851	146	1	the	the	DET
cana-851	146	2	accuracy	accuracy	NOUN
cana-851	146	3	rates	rate	NOUN
cana-851	146	4	of	of	ADP
cana-851	146	5	the	the	DET
cana-851	146	6	two	two	NUM
cana-851	146	7	methods	method	NOUN
cana-851	146	8	are	be	AUX
cana-851	146	9	compared	compare	VERB
cana-851	146	10	,	,	PUNCT
cana-851	146	11	with	with	ADP
cana-851	146	12	the	the	DET
cana-851	146	13	novel	novel	NOUN
cana-851	146	14	(	(	PUNCT
cana-851	146	15	svm	svm	ADJ
cana-851	146	16	)	)	PUNCT
cana-851	146	17	algorithms	algorithm	NOUN
cana-851	146	18	achieving	achieve	VERB
cana-851	146	19	a	a	DET
cana-851	146	20	better	well	ADJ
cana-851	146	21	accuracy	accuracy	NOUN
cana-851	146	22	of	of	ADP
cana-851	146	23	98.64	98.64	NUM
cana-851	146	24	%	%	NOUN
cana-851	146	25	compared	compare	VERB
cana-851	146	26	to	to	ADP
cana-851	146	27	the	the	DET
cana-851	146	28	(	(	PUNCT
cana-851	146	29	laf	laf	PROPN
cana-851	146	30	)	)	PUNCT
cana-851	146	31	algorithm	algorithm	PROPN
cana-851	146	32	's	's	PART
cana-851	146	33	accuracy	accuracy	NOUN
cana-851	146	34	of	of	ADP
cana-851	146	35	97.86	97.86	NUM
cana-851	146	36	%	%	NOUN
cana-851	146	37	.	.	PUNCT
cana-851	147	1	classification	classification	NOUN
cana-851	148	1	[	[	X
cana-851	148	2	4	4	NUM
cana-851	148	3	]	]	X
cana-851	148	4	(	(	PUNCT
cana-851	148	5	e.g.	e.g.	ADV
cana-851	148	6	,	,	PUNCT
cana-851	148	7	random	random	ADJ
cana-851	148	8	forest	forest	NOUN
cana-851	148	9	,	,	PUNCT
cana-851	148	10	k	k	PROPN
cana-851	148	11	nearest	near	ADJ
cana-851	148	12	neighbors	neighbor	NOUN
cana-851	148	13	,	,	PUNCT
cana-851	148	14	and	and	CCONJ
cana-851	148	15	support	support	VERB
cana-851	148	16	vector	vector	NOUN
cana-851	148	17	machine	machine	NOUN
cana-851	148	18	)	)	PUNCT
cana-851	148	19	and	and	CCONJ
cana-851	148	20	deep	deep	ADJ
cana-851	148	21	neural	neural	ADJ
cana-851	148	22	networks	network	NOUN
cana-851	148	23	(	(	PUNCT
cana-851	148	24	e.g.	e.g.	ADV
cana-851	148	25	,	,	PUNCT
cana-851	148	26	resnet	resnet	NOUN
cana-851	148	27	,	,	PUNCT
cana-851	148	28	inception	inception	NOUN
cana-851	148	29	,	,	PUNCT
cana-851	148	30	alexnet	alexnet	ADJ
cana-851	148	31	,	,	PUNCT
cana-851	148	32	and	and	CCONJ
cana-851	148	33	densenet	densenet	NOUN
cana-851	148	34	)	)	PUNCT
cana-851	148	35	null	null	ADJ
cana-851	148	36	classification	classification	NOUN
cana-851	149	1	[	[	X
cana-851	149	2	38	38	NUM
cana-851	149	3	]	]	X
cana-851	149	4	dl	dl	PROPN
cana-851	149	5	we	we	PRON
cana-851	149	6	renamed	rename	VERB
cana-851	149	7	(	(	PUNCT
cana-851	149	8	densenet201	densenet201	PROPN
cana-851	149	9	and	and	CCONJ
cana-851	149	10	efficientnet	efficientnet	NOUN
cana-851	149	11	-	-	PUNCT
cana-851	149	12	b7	b7	NOUN
cana-851	149	13	)	)	PUNCT
cana-851	149	14	as	as	ADP
cana-851	149	15	"	"	PUNCT
cana-851	149	16	flowerconvnet	flowerconvnet	NOUN
cana-851	149	17	"	"	PUNCT
cana-851	149	18	.	.	PUNCT
cana-851	150	1	95	95	NUM
cana-851	150	2	%	%	NOUN
cana-851	150	3	validation	validation	NOUN
cana-851	150	4	accuracy	accuracy	NOUN
cana-851	150	5	.	.	PUNCT
cana-851	151	1	recognition	recognition	NOUN
cana-851	152	1	[	[	X
cana-851	152	2	39	39	NUM
cana-851	152	3	]	]	X
cana-851	152	4	dl	dl	PROPN
cana-851	152	5	(	(	PUNCT
cana-851	152	6	combination	combination	NOUN
cana-851	152	7	of	of	ADP
cana-851	152	8	densenet201	densenet201	PROPN
cana-851	152	9	and	and	CCONJ
cana-851	152	10	mlp	mlp	PROPN
cana-851	152	11	)	)	PUNCT
cana-851	152	12	the	the	DET
cana-851	152	13	model	model	NOUN
cana-851	152	14	achieves	achieve	VERB
cana-851	152	15	impressive	impressive	ADJ
cana-851	152	16	classification	classification	NOUN
cana-851	152	17	results	result	NOUN
cana-851	152	18	on	on	ADP
cana-851	152	19	multiple	multiple	ADJ
cana-851	152	20	datasets	dataset	NOUN
cana-851	152	21	,	,	PUNCT
cana-851	152	22	including	include	VERB
cana-851	152	23	79.13	79.13	NUM
cana-851	152	24	%	%	NOUN
cana-851	152	25	on	on	ADP
cana-851	152	26	oxford102	oxford102	NUM
cana-851	152	27	,	,	PUNCT
cana-851	152	28	94.47	94.47	NUM
cana-851	152	29	%	%	NOUN
cana-851	152	30	accuracy	accuracy	NOUN
cana-851	152	31	on	on	ADP
cana-851	152	32	kaggle	kaggle	PROPN
cana-851	152	33	,	,	PUNCT
cana-851	152	34	and	and	CCONJ
cana-851	152	35	98.23	98.23	NUM
cana-851	152	36	%	%	NOUN
cana-851	152	37	and	and	CCONJ
cana-851	152	38	97.35	97.35	NUM
cana-851	152	39	%	%	NOUN
cana-851	152	40	on	on	ADP
cana-851	152	41	oxford17	oxford17	NOUN
cana-851	152	42	for	for	ADP
cana-851	152	43	two	two	NUM
cana-851	152	44	different	different	ADJ
cana-851	152	45	protocols	protocol	NOUN
cana-851	152	46	.	.	PUNCT
cana-851	153	1	recognition	recognition	NOUN
cana-851	154	1	[	[	X
cana-851	154	2	40	40	NUM
cana-851	154	3	]	]	PUNCT
cana-851	154	4	dl(xception	dl(xception	NOUN
cana-851	154	5	)	)	PUNCT
cana-851	154	6	70.03	70.03	NUM
cana-851	154	7	%	%	NOUN
cana-851	154	8	classification	classification	NOUN
cana-851	154	9	[	[	X
cana-851	154	10	41	41	NUM
cana-851	154	11	]	]	PUNCT
cana-851	154	12	dl(alexnet	dl(alexnet	PROPN
cana-851	154	13	,	,	PUNCT
cana-851	154	14	google	google	PROPN
cana-851	154	15	net	net	NOUN
cana-851	154	16	,	,	PUNCT
cana-851	154	17	vgg16	vgg16	NOUN
cana-851	154	18	,	,	PUNCT
cana-851	154	19	densenet	densenet	NOUN
cana-851	154	20	,	,	PUNCT
cana-851	154	21	and	and	CCONJ
cana-851	154	22	resnet	resnet	VERB
cana-851	154	23	)	)	PUNCT
cana-851	154	24	alexnet	alexnet	NOUN
cana-851	154	25	:	:	PUNCT
cana-851	154	26	86.28	86.28	NUM
cana-851	154	27	%	%	NOUN
cana-851	154	28	resnet18	resnet18	NOUN
cana-851	154	29	:	:	PUNCT
cana-851	154	30	91.29	91.29	NUM
cana-851	154	31	%	%	NOUN
cana-851	154	32	google	google	PROPN
cana-851	154	33	net	net	NOUN
cana-851	154	34	:	:	PUNCT
cana-851	154	35	89.75	89.75	NUM
cana-851	154	36	%	%	NOUN
cana-851	154	37	densenet201	densenet201	PROPN
cana-851	154	38	:	:	PUNCT
cana-851	154	39	93.06	93.06	NUM
cana-851	154	40	%	%	NOUN
cana-851	154	41	vgg16	vgg16	NOUN
cana-851	154	42	:	:	PUNCT
cana-851	154	43	93.52	93.52	NUM
cana-851	154	44	%	%	NOUN
cana-851	154	45	classification	classification	NOUN
cana-851	155	1	[	[	X
cana-851	155	2	43	43	NUM
cana-851	155	3	]	]	X
cana-851	155	4	dl+ml	dl+ml	PROPN
cana-851	155	5	(	(	PUNCT
cana-851	155	6	cnn	cnn	PROPN
cana-851	155	7	and	and	CCONJ
cana-851	155	8	svm	svm	PROPN
cana-851	155	9	)	)	PUNCT
cana-851	155	10	cnn	cnn	PROPN
cana-851	155	11	achieved	achieve	VERB
cana-851	155	12	an	an	DET
cana-851	155	13	accuracy	accuracy	NOUN
cana-851	155	14	of	of	ADP
cana-851	155	15	91.6	91.6	NUM
cana-851	155	16	%	%	NOUN
cana-851	155	17	in	in	ADP
cana-851	155	18	flower	flower	NOUN
cana-851	155	19	image	image	NOUN
cana-851	155	20	classification	classification	NOUN
cana-851	155	21	classification	classification	NOUN
cana-851	155	22	[	[	X
cana-851	155	23	19	19	NUM
cana-851	155	24	]	]	SYM
cana-851	155	25	ml	ml	PROPN
cana-851	155	26	(	(	PUNCT
cana-851	155	27	lbp	lbp	PROPN
cana-851	155	28	and	and	CCONJ
cana-851	155	29	surf	surf	NOUN
cana-851	155	30	as	as	ADP
cana-851	155	31	features	feature	NOUN
cana-851	155	32	and	and	CCONJ
cana-851	155	33	svm	svm	ADJ
cana-851	155	34	as	as	ADP
cana-851	155	35	a	a	DET
cana-851	155	36	classifier	classifier	NOUN
cana-851	155	37	)	)	PUNCT
cana-851	155	38	.	.	PUNCT
cana-851	156	1	accuracy	accuracy	NOUN
cana-851	156	2	,	,	PUNCT
cana-851	156	3	accounting	account	VERB
cana-851	156	4	for	for	ADP
cana-851	156	5	70	70	NUM
cana-851	156	6	%	%	NOUN
cana-851	156	7	of	of	ADP
cana-851	156	8	the	the	DET
cana-851	156	9	evaluation	evaluation	NOUN
cana-851	156	10	criteria	criterion	NOUN
cana-851	156	11	weight	weight	NOUN
cana-851	156	12	.	.	PUNCT
cana-851	157	1	classification	classification	NOUN
cana-851	157	2	[	[	X
cana-851	157	3	42	42	NUM
cana-851	157	4	]	]	X
cana-851	157	5	dl	dl	PROPN
cana-851	157	6	(	(	PUNCT
cana-851	157	7	novel	novel	ADJ
cana-851	157	8	attention	attention	NOUN
cana-851	157	9	-	-	PUNCT
cana-851	157	10	driven	drive	VERB
cana-851	157	11	)	)	PUNCT
cana-851	157	12	achieves	achieve	VERB
cana-851	157	13	the	the	DET
cana-851	157	14	recognition	recognition	NOUN
cana-851	157	15	accuracy	accuracy	NOUN
cana-851	157	16	of	of	ADP
cana-851	157	17	85.7	85.7	NUM
cana-851	157	18	%	%	NOUN
cana-851	157	19	.	.	PUNCT
cana-851	158	1	recognition	recognition	NOUN
cana-851	159	1	[	[	X
cana-851	159	2	44	44	NUM
cana-851	159	3	]	]	SYM
cana-851	159	4	ml+dl	ml+dl	NOUN
cana-851	159	5	(	(	PUNCT
cana-851	159	6	random	random	ADJ
cana-851	159	7	forest	forest	NOUN
cana-851	159	8	)	)	PUNCT
cana-851	159	9	achieving	achieve	VERB
cana-851	159	10	an	an	DET
cana-851	159	11	accuracy	accuracy	NOUN
cana-851	159	12	of	of	ADP
cana-851	159	13	88.74	88.74	NUM
cana-851	159	14	%	%	NOUN
cana-851	159	15	classification	classification	NOUN
cana-851	159	16	[	[	X
cana-851	159	17	10	10	NUM
cana-851	159	18	]	]	X
cana-851	159	19	dl(vgg-16	dl(vgg-16	PROPN
cana-851	159	20	)	)	PUNCT
cana-851	159	21	achieved	achieve	VERB
cana-851	159	22	accuracy	accuracy	NOUN
cana-851	159	23	of	of	ADP
cana-851	159	24	91.9	91.9	NUM
cana-851	159	25	%	%	NOUN
cana-851	159	26	classification	classification	NOUN
cana-851	159	27	recognition	recognition	NOUN
cana-851	159	28	as	as	ADP
cana-851	159	29	for	for	ADP
cana-851	159	30	datasets	dataset	NOUN
cana-851	159	31	,	,	PUNCT
cana-851	159	32	table	table	NOUN
cana-851	159	33	3	3	NUM
cana-851	159	34	.	.	PUNCT
cana-851	160	1	the	the	DET
cana-851	160	2	chosen	choose	VERB
cana-851	160	3	studies	study	NOUN
cana-851	160	4	employed	employ	VERB
cana-851	160	5	diverse	diverse	ADJ
cana-851	160	6	types	type	NOUN
cana-851	160	7	of	of	ADP
cana-851	160	8	datasets	dataset	NOUN
cana-851	160	9	and	and	CCONJ
cana-851	160	10	different	different	ADJ
cana-851	160	11	size	size	NOUN
cana-851	160	12	and	and	CCONJ
cana-851	160	13	types	type	NOUN
cana-851	160	14	of	of	ADP
cana-851	160	15	flowers	flower	NOUN
cana-851	160	16	.	.	PUNCT
cana-851	161	1	datasets	dataset	NOUN
cana-851	161	2	are	be	AUX
cana-851	161	3	a	a	DET
cana-851	161	4	crucial	crucial	ADJ
cana-851	161	5	component	component	NOUN
cana-851	161	6	of	of	ADP
cana-851	161	7	the	the	DET
cana-851	161	8	object	object	NOUN
cana-851	161	9	recognition	recognition	NOUN
cana-851	161	10	process	process	NOUN
cana-851	161	11	.	.	PUNCT
cana-851	162	1	our	our	PRON
cana-851	162	2	review	review	NOUN
cana-851	162	3	of	of	ADP
cana-851	162	4	the	the	DET
cana-851	162	5	academic	academic	ADJ
cana-851	162	6	literature	literature	NOUN
cana-851	162	7	identified	identify	VERB
cana-851	162	8	that	that	SCONJ
cana-851	162	9	researchers	researcher	NOUN
cana-851	162	10	utilized	utilize	VERB
cana-851	162	11	self	self	NOUN
cana-851	162	12	-	-	PUNCT
cana-851	162	13	constructed	construct	VERB
cana-851	162	14	datasets	dataset	NOUN
cana-851	162	15	,	,	PUNCT
cana-851	162	16	publicly	publicly	ADV
cana-851	162	17	available	available	ADJ
cana-851	162	18	datasets	dataset	NOUN
cana-851	162	19	,	,	PUNCT
cana-851	162	20	or	or	CCONJ
cana-851	162	21	a	a	DET
cana-851	162	22	combination	combination	NOUN
cana-851	162	23	of	of	ADP
cana-851	162	24	both[45	both[45	NOUN
cana-851	162	25	]	]	PUNCT
cana-851	162	26	.	.	PUNCT
cana-851	163	1	that	that	PRON
cana-851	163	2	may	may	AUX
cana-851	163	3	be	be	AUX
cana-851	163	4	available	available	ADJ
cana-851	163	5	or	or	CCONJ
cana-851	163	6	not	not	PART
cana-851	163	7	.	.	PUNCT
cana-851	164	1	table	table	NOUN
cana-851	164	2	3	3	NUM
cana-851	164	3	.	.	PUNCT
cana-851	165	1	dataset	dataset	VERB
cana-851	165	2	in	in	ADP
cana-851	165	3	the	the	DET
cana-851	165	4	literature	literature	NOUN
cana-851	165	5	ref	ref	NOUN
cana-851	165	6	dataset	dataset	VERB
cana-851	165	7	size	size	NOUN
cana-851	165	8	types	type	NOUN
cana-851	165	9	of	of	ADP
cana-851	165	10	flowers	flower	NOUN
cana-851	165	11	public	public	ADJ
cana-851	165	12	/	/	SYM
cana-851	165	13	private	private	ADJ
cana-851	166	1	[	[	X
cana-851	166	2	20	20	NUM
cana-851	166	3	]	]	PUNCT
cana-851	166	4	every	every	DET
cana-851	166	5	flower	flower	NOUN
cana-851	166	6	has	have	VERB
cana-851	166	7	800	800	NUM
cana-851	166	8	sample	sample	NOUN
cana-851	166	9	images	image	NOUN
cana-851	166	10	and	and	CCONJ
cana-851	166	11	total	total	NOUN
cana-851	166	12	of	of	ADP
cana-851	166	13	6400	6400	NUM
cana-851	166	14	samples	sample	NOUN
cana-851	166	15	later	later	ADV
cana-851	166	16	applying	apply	VERB
cana-851	166	17	augmentation	augmentation	NOUN
cana-851	166	18	techniques	technique	NOUN
cana-851	166	19	(	(	PUNCT
cana-851	166	20	shiuli	shiuli	PROPN
cana-851	166	21	,	,	PUNCT
cana-851	166	22	shapla	shapla	NOUN
cana-851	166	23	,	,	PUNCT
cana-851	166	24	rongon	rongon	NOUN
cana-851	166	25	,	,	PUNCT
cana-851	166	26	radhachura	radhachura	NOUN
cana-851	166	27	,	,	PUNCT
cana-851	166	28	rojonigondha	rojonigondha	NOUN
cana-851	166	29	,	,	PUNCT
cana-851	166	30	chapa	chapa	VERB
cana-851	166	31	,	,	PUNCT
cana-851	166	32	kadam	kadam	PROPN
cana-851	166	33	,	,	PUNCT
cana-851	166	34	kath	kath	PROPN
cana-851	166	35	golap	golap	PROPN
cana-851	166	36	)	)	PUNCT
cana-851	166	37	.	.	PUNCT
cana-851	167	1	private	private	ADJ
cana-851	167	2	[	[	X
cana-851	167	3	21	21	NUM
cana-851	167	4	]	]	SYM
cana-851	167	5	1)which	1)which	NUM
cana-851	167	6	has	have	VERB
cana-851	167	7	a	a	DET
cana-851	167	8	102	102	NUM
cana-851	167	9	-	-	PUNCT
cana-851	167	10	flower	flower	NOUN
cana-851	167	11	kind	kind	NOUN
cana-851	167	12	and	and	CCONJ
cana-851	167	13	a	a	DET
cana-851	167	14	total	total	ADJ
cana-851	167	15	number	number	NOUN
cana-851	167	16	18200	18200	NUM
cana-851	167	17	images	image	NOUN
cana-851	167	18	.	.	PUNCT
cana-851	168	1	2	2	X
cana-851	168	2	)	)	PUNCT
cana-851	168	3	one	one	NUM
cana-851	168	4	more	more	ADV
cana-851	168	5	dataset	dataset	NOUN
cana-851	168	6	6	6	NUM
cana-851	168	7	has	have	VERB
cana-851	168	8	a	a	DET
cana-851	168	9	total	total	ADJ
cana-851	168	10	30	30	NUM
cana-851	168	11	flowers	flower	NOUN
cana-851	168	12	and	and	CCONJ
cana-851	168	13	a	a	DET
cana-851	168	14	total	total	ADJ
cana-851	168	15	number	number	NOUN
cana-851	168	16	1479	1479	NUM
cana-851	168	17	images	image	NOUN
cana-851	168	18	.	.	PUNCT
cana-851	169	1	(	(	PUNCT
cana-851	169	2	8189	8189	NUM
cana-851	169	3	)	)	PUNCT
cana-851	169	4	of	of	ADP
cana-851	169	5	flower102	flower102	PROPN
cana-851	169	6	dataset	dataset	NOUN
cana-851	169	7	(	(	PUNCT
cana-851	169	8	3500	3500	NUM
cana-851	169	9	)	)	PUNCT
cana-851	169	10	of	of	ADP
cana-851	169	11	kaggle	kaggle	PROPN
cana-851	169	12	’s	’s	PART
cana-851	169	13	flower	flower	NOUN
cana-851	169	14	dataset	dataset	NOUN
cana-851	169	15	(	(	PUNCT
cana-851	169	16	5	5	NUM
cana-851	169	17	)	)	PUNCT
cana-851	169	18	(	(	PUNCT
cana-851	169	19	1360	1360	NUM
cana-851	169	20	)	)	PUNCT
cana-851	169	21	of	of	ADP
cana-851	169	22	flower17	flower17	ADJ
cana-851	169	23	dataset	dataset	NOUN
cana-851	169	24	(	(	PUNCT
cana-851	169	25	5157	5157	NUM
cana-851	169	26	)	)	PUNCT
cana-851	169	27	of	of	ADP
cana-851	169	28	dataset	dataset	NOUN
cana-851	169	29	accumulated	accumulate	VERB
cana-851	169	30	(	(	PUNCT
cana-851	169	31	20	20	NUM
cana-851	169	32	)	)	PUNCT
cana-851	169	33	public	public	ADJ
cana-851	169	34	public	public	ADJ
cana-851	169	35	public	public	ADJ
cana-851	169	36	private	private	ADJ
cana-851	169	37	communications	communication	NOUN
cana-851	169	38	on	on	ADP
cana-851	169	39	applied	apply	VERB
cana-851	169	40	nonlinear	nonlinear	ADJ
cana-851	169	41	analysis	analysis	NOUN
cana-851	169	42	issn	issn	NOUN
cana-851	169	43	:	:	PUNCT
cana-851	169	44	1074	1074	NUM
cana-851	169	45	-	-	PUNCT
cana-851	169	46	133x	133x	NUM
cana-851	169	47	vol	vol	NOUN
cana-851	169	48	31	31	NUM
cana-851	169	49	no	no	NOUN
cana-851	169	50	.	.	PUNCT
cana-851	170	1	4s	4s	NUM
cana-851	170	2	(	(	PUNCT
cana-851	170	3	2024	2024	NUM
cana-851	170	4	)	)	PUNCT
cana-851	170	5	280	280	NUM
cana-851	170	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	171	1	[	[	X
cana-851	171	2	22	22	NUM
cana-851	171	3	]	]	X
cana-851	171	4	1)flowersdataset	1)flowersdataset	NUM
cana-851	171	5	(	(	PUNCT
cana-851	171	6	5	5	NUM
cana-851	171	7	)	)	PUNCT
cana-851	171	8	(	(	PUNCT
cana-851	171	9	3673	3673	NUM
cana-851	171	10	)	)	PUNCT
cana-851	171	11	2	2	NUM
cana-851	171	12	)	)	PUNCT
cana-851	171	13	oxford-17	oxford-17	VERB
cana-851	171	14	is	be	AUX
cana-851	171	15	a	a	DET
cana-851	171	16	flower	flower	NOUN
cana-851	171	17	dataset	dataset	VERB
cana-851	171	18	with	with	ADP
cana-851	171	19	17	17	NUM
cana-851	171	20	different	different	ADJ
cana-851	171	21	flowers	flower	NOUN
cana-851	171	22	categories	category	NOUN
cana-851	171	23	and	and	CCONJ
cana-851	171	24	80	80	NUM
cana-851	171	25	images	image	NOUN
cana-851	171	26	in	in	ADP
cana-851	171	27	each	each	DET
cana-851	171	28	category	category	NOUN
cana-851	171	29	2)(daisy	2)(daisy	NOUN
cana-851	171	30	,	,	PUNCT
cana-851	171	31	tulip	tulip	VERB
cana-851	171	32	,	,	PUNCT
cana-851	171	33	rose	rise	VERB
cana-851	171	34	,	,	PUNCT
cana-851	171	35	sunflower	sunflower	NOUN
cana-851	171	36	,	,	PUNCT
cana-851	171	37	and	and	CCONJ
cana-851	171	38	dandelion	dandelion	NOUN
cana-851	171	39	)	)	PUNCT
cana-851	171	40	public	public	ADJ
cana-851	171	41	public	public	NOUN
cana-851	172	1	[	[	X
cana-851	172	2	24	24	NUM
cana-851	172	3	]	]	PUNCT
cana-851	173	1	which	which	PRON
cana-851	173	2	contains	contain	VERB
cana-851	173	3	79	79	NUM
cana-851	173	4	different	different	ADJ
cana-851	173	5	type	type	NOUN
cana-851	173	6	of	of	ADP
cana-851	173	7	flowers	flower	NOUN
cana-851	173	8	and	and	CCONJ
cana-851	173	9	52,775	52,775	NUM
cana-851	173	10	images	image	NOUN
cana-851	173	11	null	null	ADJ
cana-851	173	12	private	private	ADJ
cana-851	173	13	[	[	X
cana-851	173	14	9	9	NUM
cana-851	173	15	]	]	SYM
cana-851	173	16	oxford	oxford	PROPN
cana-851	173	17	102-(consists	102-(consists	PROPN
cana-851	173	18	of	of	ADP
cana-851	173	19	40	40	NUM
cana-851	173	20	to	to	PART
cana-851	173	21	258	258	NUM
cana-851	173	22	images	image	NOUN
cana-851	173	23	in	in	ADP
cana-851	173	24	each	each	DET
cana-851	173	25	category	category	NOUN
cana-851	173	26	)	)	PUNCT
cana-851	173	27	.	.	PUNCT
cana-851	174	1	null	null	ADJ
cana-851	174	2	public	public	ADJ
cana-851	174	3	[	[	X
cana-851	174	4	6	6	NUM
cana-851	174	5	]	]	PUNCT
cana-851	174	6	the	the	DET
cana-851	174	7	oxford102	oxford102	PROPN
cana-851	174	8	dataset	dataset	NOUN
cana-851	174	9	has	have	VERB
cana-851	174	10	8189	8189	NUM
cana-851	174	11	images	image	NOUN
cana-851	174	12	of	of	ADP
cana-851	174	13	flowers	flower	NOUN
cana-851	174	14	,	,	PUNCT
cana-851	174	15	divided	divide	VERB
cana-851	174	16	into	into	ADP
cana-851	174	17	102	102	NUM
cana-851	174	18	categories	category	NOUN
cana-851	174	19	.	.	PUNCT
cana-851	175	1	each	each	DET
cana-851	175	2	category	category	NOUN
cana-851	175	3	has	have	VERB
cana-851	175	4	between	between	ADP
cana-851	175	5	40	40	NUM
cana-851	175	6	and	and	CCONJ
cana-851	175	7	258	258	NUM
cana-851	175	8	images	image	NOUN
cana-851	175	9	,	,	PUNCT
cana-851	175	10	with	with	ADP
cana-851	175	11	varying	vary	VERB
cana-851	175	12	image	image	NOUN
cana-851	175	13	sizes	size	NOUN
cana-851	175	14	.	.	PUNCT
cana-851	176	1	the	the	DET
cana-851	176	2	oxford	oxford	PROPN
cana-851	176	3	17	17	NUM
cana-851	176	4	dataset	dataset	NOUN
cana-851	176	5	involves	involve	NOUN
cana-851	176	6	of	of	ADP
cana-851	176	7	1360	1360	NUM
cana-851	176	8	flower	flower	NOUN
cana-851	176	9	images	image	NOUN
cana-851	176	10	,	,	PUNCT
cana-851	176	11	categorized	categorize	VERB
cana-851	176	12	into	into	ADP
cana-851	176	13	17	17	NUM
cana-851	176	14	different	different	ADJ
cana-851	176	15	types.consisting	types.consisting	NOUN
cana-851	176	16	of	of	ADP
cana-851	176	17	80	80	NUM
cana-851	176	18	images	image	NOUN
cana-851	176	19	in	in	ADP
cana-851	176	20	each	each	DET
cana-851	176	21	type	type	NOUN
cana-851	176	22	with	with	ADP
cana-851	176	23	varying	vary	VERB
cana-851	176	24	image	image	NOUN
cana-851	176	25	sizes	size	NOUN
cana-851	176	26	.	.	PUNCT
cana-851	177	1	and	and	CCONJ
cana-851	177	2	zou	zou	PROPN
cana-851	177	3	–	–	PUNCT
cana-851	177	4	nagy	nagy	PROPN
cana-851	177	5	(	(	PUNCT
cana-851	177	6	consists	consist	VERB
cana-851	177	7	of	of	ADP
cana-851	177	8	612flowers	612flowers	PROPN
cana-851	177	9	images	image	NOUN
cana-851	177	10	from	from	ADP
cana-851	177	11	102	102	NUM
cana-851	177	12	classes	class	NOUN
cana-851	177	13	.	.	PUNCT
cana-851	178	1	each	each	DET
cana-851	178	2	class	class	NOUN
cana-851	178	3	contains	contain	VERB
cana-851	178	4	of	of	ADP
cana-851	178	5	six	six	NUM
cana-851	178	6	images	image	NOUN
cana-851	178	7	and	and	CCONJ
cana-851	178	8	each	each	DET
cana-851	178	9	image	image	NOUN
cana-851	178	10	size	size	NOUN
cana-851	178	11	are	be	AUX
cana-851	178	12	300	300	NUM
cana-851	178	13	×	×	NOUN
cana-851	178	14	240	240	NUM
cana-851	178	15	pixels	pixel	NOUN
cana-851	178	16	)	)	PUNCT
cana-851	178	17	.	.	PUNCT
cana-851	179	1	null	null	ADJ
cana-851	179	2	null	null	ADJ
cana-851	179	3	null	null	ADJ
cana-851	179	4	public	public	ADJ
cana-851	179	5	public	public	NOUN
cana-851	179	6	na	na	ADP
cana-851	180	1	[	[	X
cana-851	180	2	25	25	NUM
cana-851	180	3	]	]	SYM
cana-851	180	4	five	five	NUM
cana-851	180	5	types	type	NOUN
cana-851	180	6	of	of	ADP
cana-851	180	7	flowers	flower	NOUN
cana-851	180	8	contained	contain	VERB
cana-851	180	9	in	in	ADP
cana-851	180	10	the	the	DET
cana-851	180	11	dataset	dataset	NOUN
cana-851	180	12	(	(	PUNCT
cana-851	180	13	the	the	DET
cana-851	180	14	dataset	dataset	NOUN
cana-851	180	15	consists	consist	VERB
cana-851	180	16	of	of	ADP
cana-851	180	17	400	400	NUM
cana-851	180	18	images	image	NOUN
cana-851	180	19	,	,	PUNCT
cana-851	180	20	each	each	PRON
cana-851	180	21	of	of	ADP
cana-851	180	22	different	different	ADJ
cana-851	180	23	sizes	size	NOUN
cana-851	180	24	)	)	PUNCT
cana-851	180	25	.	.	PUNCT
cana-851	181	1	daisy	daisy	NOUN
cana-851	181	2	,	,	PUNCT
cana-851	181	3	dandelion	dandelion	NOUN
cana-851	181	4	,	,	PUNCT
cana-851	181	5	rose	rise	VERB
cana-851	181	6	,	,	PUNCT
cana-851	181	7	sunflower	sunflower	NOUN
cana-851	181	8	and	and	CCONJ
cana-851	181	9	tulip	tulip	NOUN
cana-851	181	10	.	.	PUNCT
cana-851	182	1	public	public	ADJ
cana-851	182	2	[	[	X
cana-851	182	3	3	3	X
cana-851	182	4	]	]	X
cana-851	182	5	oxford	oxford	NOUN
cana-851	182	6	102	102	NUM
cana-851	182	7	oxford	oxford	PROPN
cana-851	182	8	17	17	NUM
cana-851	182	9	null	null	ADJ
cana-851	182	10	public	public	ADJ
cana-851	182	11	public	public	NOUN
cana-851	182	12	[	[	X
cana-851	182	13	26	26	NUM
cana-851	182	14	]	]	SYM
cana-851	182	15	five	five	NUM
cana-851	182	16	types	type	NOUN
cana-851	182	17	of	of	ADP
cana-851	182	18	flowers	flower	NOUN
cana-851	182	19	contained	contain	VERB
cana-851	182	20	in	in	ADP
cana-851	182	21	the	the	DET
cana-851	182	22	dataset	dataset	NOUN
cana-851	182	23	daisy	daisy	NOUN
cana-851	182	24	,	,	PUNCT
cana-851	182	25	dandelion	dandelion	NOUN
cana-851	182	26	,	,	PUNCT
cana-851	182	27	rose	rise	VERB
cana-851	182	28	,	,	PUNCT
cana-851	182	29	sunflower	sunflower	NOUN
cana-851	182	30	and	and	CCONJ
cana-851	182	31	tulip	tulip	NOUN
cana-851	182	32	.	.	PUNCT
cana-851	183	1	public	public	ADJ
cana-851	183	2	[	[	X
cana-851	183	3	27	27	NUM
cana-851	183	4	]	]	PUNCT
cana-851	183	5	the	the	DET
cana-851	183	6	database	database	NOUN
cana-851	183	7	contains	contain	VERB
cana-851	183	8	a	a	DET
cana-851	183	9	total	total	NOUN
cana-851	183	10	of	of	ADP
cana-851	183	11	3670	3670	NUM
cana-851	183	12	flower	flower	NOUN
cana-851	183	13	images	image	NOUN
cana-851	183	14	,	,	PUNCT
cana-851	183	15	which	which	PRON
cana-851	183	16	are	be	AUX
cana-851	183	17	categorized	categorize	VERB
cana-851	183	18	into	into	ADP
cana-851	183	19	five	five	NUM
cana-851	183	20	different	different	ADJ
cana-851	183	21	species	specie	NOUN
cana-851	183	22	.	.	PUNCT
cana-851	184	1	these	these	DET
cana-851	184	2	images	image	NOUN
cana-851	184	3	were	be	AUX
cana-851	184	4	then	then	ADV
cana-851	184	5	split	split	VERB
cana-851	184	6	into	into	ADP
cana-851	184	7	two	two	NUM
cana-851	184	8	sets	set	NOUN
cana-851	184	9	:	:	PUNCT
cana-851	184	10	a	a	DET
cana-851	184	11	training	training	NOUN
cana-851	184	12	set	set	NOUN
cana-851	184	13	consisting	consist	VERB
cana-851	184	14	of	of	ADP
cana-851	184	15	3320	3320	NUM
cana-851	184	16	images	image	NOUN
cana-851	184	17	and	and	CCONJ
cana-851	184	18	a	a	DET
cana-851	184	19	test	test	NOUN
cana-851	184	20	set	set	NOUN
cana-851	184	21	consisting	consist	VERB
cana-851	184	22	of	of	ADP
cana-851	184	23	350	350	NUM
cana-851	184	24	images	image	NOUN
cana-851	184	25	.	.	PUNCT
cana-851	185	1	the	the	DET
cana-851	185	2	another	another	DET
cana-851	185	3	database	database	NOUN
cana-851	185	4	had	have	VERB
cana-851	185	5	1600	1600	NUM
cana-851	185	6	images	image	NOUN
cana-851	185	7	of	of	ADP
cana-851	185	8	the	the	DET
cana-851	185	9	identical	identical	ADJ
cana-851	185	10	flower	flower	NOUN
cana-851	185	11	species	specie	NOUN
cana-851	185	12	seen	see	VERB
cana-851	185	13	in	in	ADP
cana-851	185	14	the	the	DET
cana-851	185	15	first	first	ADJ
cana-851	185	16	database	database	NOUN
cana-851	185	17	.	.	PUNCT
cana-851	186	1	the	the	DET
cana-851	186	2	ilsvrc-2012	ilsvrc-2012	ADJ
cana-851	186	3	-	-	PUNCT
cana-851	186	4	cls	cls	NOUN
cana-851	186	5	image	image	NOUN
cana-851	186	6	classification	classification	NOUN
cana-851	186	7	dataset	dataset	NOUN
cana-851	186	8	was	be	AUX
cana-851	186	9	utilized	utilize	VERB
cana-851	186	10	as	as	ADP
cana-851	186	11	the	the	DET
cana-851	186	12	sole	sole	ADJ
cana-851	186	13	classifiers	classifier	NOUN
cana-851	186	14	for	for	ADP
cana-851	186	15	extracting	extract	VERB
cana-851	186	16	features	feature	NOUN
cana-851	186	17	.	.	PUNCT
cana-851	187	1	dandelion	dandelion	NOUN
cana-851	187	2	,	,	PUNCT
cana-851	187	3	daisy	daisy	NOUN
cana-851	187	4	,	,	PUNCT
cana-851	187	5	rose	rise	VERB
cana-851	187	6	,	,	PUNCT
cana-851	187	7	sunflower	sunflower	NOUN
cana-851	187	8	and	and	CCONJ
cana-851	187	9	tulip	tulip	NOUN
cana-851	187	10	.	.	PUNCT
cana-851	188	1	sunflower	sunflower	NOUN
cana-851	188	2	,	,	PUNCT
cana-851	188	3	dandelion	dandelion	NOUN
cana-851	188	4	,	,	PUNCT
cana-851	188	5	rose	rise	VERB
cana-851	188	6	,	,	PUNCT
cana-851	188	7	daisy	daisy	NOUN
cana-851	188	8	and	and	CCONJ
cana-851	188	9	tulip	tulip	VERB
cana-851	188	10	.	.	PUNCT
cana-851	189	1	null	null	ADJ
cana-851	189	2	public	public	ADJ
cana-851	189	3	public	public	ADJ
cana-851	189	4	public	public	NOUN
cana-851	189	5	[	[	X
cana-851	189	6	28	28	NUM
cana-851	189	7	]	]	PUNCT
cana-851	189	8	selected	select	VERB
cana-851	189	9	19	19	NUM
cana-851	189	10	public	public	ADJ
cana-851	189	11	flower	flower	NOUN
cana-851	189	12	images	image	NOUN
cana-851	189	13	from	from	ADP
cana-851	189	14	the	the	DET
cana-851	189	15	oxford	oxford	PROPN
cana-851	189	16	university	university	NOUN
cana-851	189	17	.	.	PUNCT
cana-851	190	1	pink	pink	ADJ
cana-851	190	2	primrose	primrose	NOUN
cana-851	190	3	,	,	PUNCT
cana-851	190	4	balloon	balloon	NOUN
cana-851	190	5	flower	flower	NOUN
cana-851	190	6	,	,	PUNCT
cana-851	190	7	canterbury	canterbury	PROPN
cana-851	190	8	bells	bell	NOUN
cana-851	190	9	,	,	PUNCT
cana-851	190	10	sweet	sweet	ADJ
cana-851	190	11	pea	pea	NOUN
cana-851	190	12	,	,	PUNCT
cana-851	190	13	english	english	ADJ
cana-851	190	14	marigold	marigold	NOUN
cana-851	190	15	,	,	PUNCT
cana-851	190	16	hard	hard	ADV
cana-851	190	17	-	-	PUNCT
cana-851	190	18	leaved	leave	VERB
cana-851	190	19	pocket	pocket	NOUN
cana-851	190	20	orchid	orchid	NOUN
cana-851	190	21	,	,	PUNCT
cana-851	190	22	moon	moon	NOUN
cana-851	190	23	orchid	orchid	NOUN
cana-851	190	24	,	,	PUNCT
cana-851	190	25	bird	bird	NOUN
cana-851	190	26	of	of	ADP
cana-851	190	27	paradise	paradise	PROPN
cana-851	190	28	,	,	PUNCT
cana-851	190	29	monkshood	monkshood	NOUN
cana-851	190	30	,	,	PUNCT
cana-851	190	31	tiger	tiger	NOUN
cana-851	190	32	lily	lily	NOUN
cana-851	190	33	,	,	PUNCT
cana-851	190	34	snapdragon	snapdragon	NOUN
cana-851	190	35	,	,	PUNCT
cana-851	190	36	colts	colt	NOUN
cana-851	190	37	foot	foot	PROPN
cana-851	190	38	,	,	PUNCT
cana-851	190	39	king	king	NOUN
cana-851	190	40	protea	protea	NOUN
cana-851	190	41	,	,	PUNCT
cana-851	190	42	globe	globe	NOUN
cana-851	190	43	thistle	thistle	NOUN
cana-851	190	44	,	,	PUNCT
cana-851	190	45	yellow	yellow	ADJ
cana-851	190	46	iris	iris	NOUN
cana-851	190	47	,	,	PUNCT
cana-851	190	48	globe	globe	NOUN
cana-851	190	49	-	-	PUNCT
cana-851	190	50	flower	flower	NOUN
cana-851	190	51	,	,	PUNCT
cana-851	190	52	spear	spear	NOUN
cana-851	190	53	thistle	thistle	NOUN
cana-851	190	54	,	,	PUNCT
cana-851	190	55	purple	purple	ADJ
cana-851	190	56	coneflower	coneflower	NOUN
cana-851	190	57	,	,	PUNCT
cana-851	190	58	peruvian	peruvian	ADJ
cana-851	190	59	lily	lily	NOUN
cana-851	190	60	.	.	PUNCT
cana-851	191	1	public	public	ADJ
cana-851	191	2	communications	communication	NOUN
cana-851	191	3	on	on	ADP
cana-851	191	4	applied	apply	VERB
cana-851	191	5	nonlinear	nonlinear	ADJ
cana-851	191	6	analysis	analysis	NOUN
cana-851	191	7	issn	issn	NOUN
cana-851	191	8	:	:	PUNCT
cana-851	191	9	1074	1074	NUM
cana-851	191	10	-	-	PUNCT
cana-851	191	11	133x	133x	NUM
cana-851	191	12	vol	vol	NOUN
cana-851	191	13	31	31	NUM
cana-851	191	14	no	no	NOUN
cana-851	191	15	.	.	PUNCT
cana-851	192	1	4s	4s	NUM
cana-851	192	2	(	(	PUNCT
cana-851	192	3	2024	2024	NUM
cana-851	192	4	)	)	PUNCT
cana-851	192	5	281	281	NUM
cana-851	192	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	193	1	[	[	X
cana-851	193	2	29	29	NUM
cana-851	193	3	]	]	PUNCT
cana-851	193	4	kaggle	kaggle	NOUN
cana-851	193	5	flower	flower	NOUN
cana-851	193	6	dataset	dataset	NOUN
cana-851	193	7	(	(	PUNCT
cana-851	193	8	dataset	dataset	NOUN
cana-851	193	9	size	size	NOUN
cana-851	193	10	is	be	AUX
cana-851	193	11	4323	4323	NUM
cana-851	193	12	images	image	NOUN
cana-851	193	13	splited	split	VERB
cana-851	193	14	into	into	ADP
cana-851	193	15	training	training	NOUN
cana-851	193	16	3890	3890	NUM
cana-851	193	17	and	and	CCONJ
cana-851	193	18	testing	test	VERB
cana-851	193	19	433	433	NUM
cana-851	193	20	.	.	PUNCT
cana-851	193	21	)	)	PUNCT
cana-851	194	1	null	null	ADJ
cana-851	194	2	public	public	NOUN
cana-851	194	3	[	[	X
cana-851	194	4	30	30	NUM
cana-851	194	5	]	]	PUNCT
cana-851	194	6	oxford-17	oxford-17	VERB
cana-851	194	7	oxford-102	oxford-102	ADJ
cana-851	194	8	flowers32	flowers32	ADJ
cana-851	194	9	dataset	dataset	NOUN
cana-851	194	10	(	(	PUNCT
cana-851	194	11	32	32	NUM
cana-851	194	12	classes	class	NOUN
cana-851	194	13	of	of	ADP
cana-851	194	14	flower	flower	NOUN
cana-851	194	15	kind	kind	NOUN
cana-851	194	16	)	)	PUNCT
cana-851	194	17	.	.	PUNCT
cana-851	195	1	the	the	DET
cana-851	195	2	flowers32	flowers32	NOUN
cana-851	195	3	has	have	VERB
cana-851	195	4	2560	2560	NUM
cana-851	195	5	images	image	NOUN
cana-851	195	6	completely	completely	ADV
cana-851	195	7	and	and	CCONJ
cana-851	195	8	80	80	NUM
cana-851	195	9	images	image	NOUN
cana-851	195	10	for	for	ADP
cana-851	195	11	each	each	DET
cana-851	195	12	kind	kind	NOUN
cana-851	195	13	.	.	PUNCT
cana-851	196	1	null	null	ADJ
cana-851	196	2	null	null	ADJ
cana-851	196	3	null	null	ADJ
cana-851	196	4	public	public	ADJ
cana-851	196	5	public	public	NOUN
cana-851	196	6	na	na	ADP
cana-851	197	1	[	[	X
cana-851	197	2	31	31	NUM
cana-851	197	3	]	]	PUNCT
cana-851	197	4	oxford	oxford	PROPN
cana-851	197	5	102	102	NUM
cana-851	197	6	null	null	ADJ
cana-851	197	7	public	public	NOUN
cana-851	197	8	[	[	X
cana-851	197	9	2	2	X
cana-851	197	10	]	]	PUNCT
cana-851	197	11	the	the	DET
cana-851	197	12	five	five	NUM
cana-851	197	13	categories	category	NOUN
cana-851	197	14	are	be	AUX
cana-851	197	15	sunflower	sunflower	NOUN
cana-851	197	16	,	,	PUNCT
cana-851	197	17	daisy	daisy	NOUN
cana-851	197	18	,	,	PUNCT
cana-851	197	19	rose	rise	VERB
cana-851	197	20	,	,	PUNCT
cana-851	197	21	dandelion	dandelion	NOUN
cana-851	197	22	,	,	PUNCT
cana-851	197	23	and	and	CCONJ
cana-851	197	24	tulip	tulip	VERB
cana-851	197	25	.	.	PUNCT
cana-851	198	1	the	the	DET
cana-851	198	2	flower	flower	NOUN
cana-851	198	3	dataset	dataset	NOUN
cana-851	198	4	comprises	comprise	VERB
cana-851	198	5	734	734	NUM
cana-851	198	6	images	image	NOUN
cana-851	198	7	of	of	ADP
cana-851	198	8	sunflowers,769	sunflowers,769	NOUN
cana-851	198	9	images	image	NOUN
cana-851	198	10	of	of	ADP
cana-851	198	11	daisies	daisy	NOUN
cana-851	198	12	,	,	PUNCT
cana-851	198	13	784	784	NUM
cana-851	198	14	images	image	NOUN
cana-851	198	15	of	of	ADP
cana-851	198	16	roses	rose	NOUN
cana-851	198	17	,	,	PUNCT
cana-851	198	18	1055	1055	NUM
cana-851	198	19	images	image	NOUN
cana-851	198	20	of	of	ADP
cana-851	198	21	dandelions	dandelion	NOUN
cana-851	198	22	,	,	PUNCT
cana-851	198	23	and	and	CCONJ
cana-851	198	24	984	984	NUM
cana-851	198	25	images	image	NOUN
cana-851	198	26	of	of	ADP
cana-851	198	27	tulips	tulip	NOUN
cana-851	198	28	.	.	PUNCT
cana-851	199	1	sunflower	sunflower	NOUN
cana-851	199	2	,	,	PUNCT
cana-851	199	3	daisy	daisy	NOUN
cana-851	199	4	,	,	PUNCT
cana-851	199	5	rose	rise	VERB
cana-851	199	6	,	,	PUNCT
cana-851	199	7	dandelion	dandelion	NOUN
cana-851	199	8	,	,	PUNCT
cana-851	199	9	and	and	CCONJ
cana-851	199	10	tulip	tulip	VERB
cana-851	199	11	.	.	PUNCT
cana-851	200	1	public	public	ADJ
cana-851	200	2	[	[	X
cana-851	200	3	32	32	NUM
cana-851	200	4	]	]	SYM
cana-851	200	5	five	five	NUM
cana-851	200	6	categories	category	NOUN
cana-851	200	7	of	of	ADP
cana-851	200	8	flowers	flower	NOUN
cana-851	200	9	dandelion	dandelion	NOUN
cana-851	200	10	,	,	PUNCT
cana-851	200	11	daisy	daisy	NOUN
cana-851	200	12	,	,	PUNCT
cana-851	200	13	sunflower	sunflower	NOUN
cana-851	200	14	,	,	PUNCT
cana-851	200	15	rose	rise	VERB
cana-851	200	16	,	,	PUNCT
cana-851	200	17	and	and	CCONJ
cana-851	200	18	tulip	tulip	VERB
cana-851	200	19	.	.	PUNCT
cana-851	201	1	public	public	ADJ
cana-851	202	1	[	[	X
cana-851	202	2	33	33	NUM
cana-851	202	3	]	]	PUNCT
cana-851	202	4	a	a	DET
cana-851	202	5	dataset	dataset	NOUN
cana-851	202	6	that	that	PRON
cana-851	202	7	covers	cover	VERB
cana-851	202	8	5	5	NUM
cana-851	202	9	types	type	NOUN
cana-851	202	10	and	and	CCONJ
cana-851	202	11	containing	contain	VERB
cana-851	202	12	3500	3500	NUM
cana-851	202	13	images	image	NOUN
cana-851	202	14	of	of	ADP
cana-851	202	15	various	various	ADJ
cana-851	202	16	flowers	flower	NOUN
cana-851	202	17	classes	class	NOUN
cana-851	202	18	with	with	ADP
cana-851	202	19	nearly	nearly	ADV
cana-851	202	20	700	700	NUM
cana-851	202	21	images	image	NOUN
cana-851	202	22	in	in	ADP
cana-851	202	23	each	each	DET
cana-851	202	24	class	class	NOUN
cana-851	202	25	.	.	PUNCT
cana-851	203	1	rose	rise	VERB
cana-851	203	2	,	,	PUNCT
cana-851	203	3	daisy	daisy	NOUN
cana-851	203	4	,	,	PUNCT
cana-851	203	5	sunflower	sunflower	NOUN
cana-851	203	6	,	,	PUNCT
cana-851	203	7	dandelion	dandelion	NOUN
cana-851	203	8	,	,	PUNCT
cana-851	203	9	and	and	CCONJ
cana-851	203	10	tulip	tulip	VERB
cana-851	203	11	.	.	PUNCT
cana-851	204	1	public	public	ADJ
cana-851	204	2	[	[	X
cana-851	204	3	34	34	NUM
cana-851	204	4	]	]	PUNCT
cana-851	204	5	the	the	DET
cana-851	204	6	dataset	dataset	NOUN
cana-851	204	7	consists	consist	VERB
cana-851	204	8	of	of	ADP
cana-851	204	9	three	three	NUM
cana-851	204	10	distinct	distinct	ADJ
cana-851	204	11	groups	group	NOUN
cana-851	204	12	of	of	ADP
cana-851	204	13	images	image	NOUN
cana-851	204	14	,	,	PUNCT
cana-851	204	15	namely	namely	ADV
cana-851	204	16	12,753	12,753	NUM
cana-851	204	17	training	training	NOUN
cana-851	204	18	images	image	NOUN
cana-851	204	19	,	,	PUNCT
cana-851	204	20	3,712	3,712	NUM
cana-851	204	21	validation	validation	NOUN
cana-851	204	22	images	image	NOUN
cana-851	204	23	,	,	PUNCT
cana-851	204	24	and	and	CCONJ
cana-851	204	25	7,382	7,382	NUM
cana-851	204	26	test	test	NOUN
cana-851	204	27	images	image	NOUN
cana-851	204	28	.	.	PUNCT
cana-851	205	1	null	null	ADJ
cana-851	205	2	public	public	NOUN
cana-851	205	3	[	[	X
cana-851	205	4	35	35	NUM
cana-851	205	5	]	]	SYM
cana-851	205	6	oxford	oxford	NOUN
cana-851	205	7	102	102	NUM
cana-851	205	8	null	null	ADJ
cana-851	205	9	public	public	NOUN
cana-851	205	10	[	[	X
cana-851	205	11	36	36	NUM
cana-851	205	12	]	]	PUNCT
cana-851	205	13	oxford	oxford	PROPN
cana-851	205	14	102	102	NUM
cana-851	205	15	null	null	ADJ
cana-851	205	16	public	public	NOUN
cana-851	206	1	[	[	X
cana-851	206	2	37	37	NUM
cana-851	206	3	]	]	PUNCT
cana-851	206	4	oxford-17	oxford-17	VERB
cana-851	206	5	oxford-102	oxford-102	ADJ
cana-851	206	6	china	china	PROPN
cana-851	206	7	5	5	NUM
cana-851	206	8	flower	flower	NOUN
cana-851	206	9	,	,	PUNCT
cana-851	206	10	null	null	ADJ
cana-851	206	11	null	null	ADJ
cana-851	206	12	public	public	ADJ
cana-851	206	13	public	public	ADJ
cana-851	206	14	public	public	NOUN
cana-851	207	1	[	[	X
cana-851	207	2	16	16	NUM
cana-851	207	3	]	]	PUNCT
cana-851	207	4	the	the	DET
cana-851	207	5	datasets	dataset	NOUN
cana-851	207	6	mentioned	mention	VERB
cana-851	207	7	are	be	AUX
cana-851	207	8	the	the	DET
cana-851	207	9	kl	kl	PROPN
cana-851	207	10	university	university	PROPN
cana-851	207	11	flower	flower	NOUN
cana-851	207	12	(	(	PUNCT
cana-851	207	13	kluf	kluf	NOUN
cana-851	207	14	)	)	PUNCT
cana-851	207	15	dataset	dataset	NOUN
cana-851	207	16	and	and	CCONJ
cana-851	207	17	the	the	DET
cana-851	207	18	flower	flower	NOUN
cana-851	207	19	17	17	NUM
cana-851	207	20	dataset	dataset	NOUN
cana-851	207	21	.	.	PUNCT
cana-851	208	1	null	null	ADJ
cana-851	208	2	null	null	NOUN
cana-851	208	3	na	na	ADP
cana-851	208	4	public	public	NOUN
cana-851	209	1	[	[	X
cana-851	209	2	17	17	NUM
cana-851	209	3	]	]	PUNCT
cana-851	209	4	the	the	DET
cana-851	209	5	dataset	dataset	NOUN
cana-851	209	6	consists	consist	VERB
cana-851	209	7	of	of	ADP
cana-851	209	8	7	7	NUM
cana-851	209	9	types	type	NOUN
cana-851	209	10	of	of	ADP
cana-851	209	11	sunflowers	sunflower	NOUN
cana-851	209	12	,	,	PUNCT
cana-851	209	13	cherry	cherry	NOUN
cana-851	209	14	rose	rise	VERB
cana-851	209	15	,	,	PUNCT
cana-851	209	16	velvet	velvet	NOUN
cana-851	209	17	queen	queen	NOUN
cana-851	209	18	,	,	PUNCT
cana-851	209	19	early	early	ADJ
cana-851	209	20	russian	russian	ADJ
cana-851	209	21	,	,	PUNCT
cana-851	209	22	fiesta	fiesta	PROPN
cana-851	209	23	del	del	PROPN
cana-851	209	24	sol	sol	PROPN
cana-851	209	25	,	,	PUNCT
cana-851	209	26	teddy	teddy	PROPN
cana-851	209	27	bear	bear	PROPN
cana-851	209	28	,	,	PUNCT
cana-851	209	29	sunny	sunny	ADJ
cana-851	209	30	smile	smile	NOUN
cana-851	209	31	,	,	PUNCT
cana-851	209	32	and	and	CCONJ
cana-851	209	33	red	red	ADJ
cana-851	209	34	sun	sun	PROPN
cana-851	209	35	.	.	PUNCT
cana-851	210	1	public	public	ADJ
cana-851	210	2	[	[	X
cana-851	210	3	18	18	NUM
cana-851	210	4	]	]	X
cana-851	210	5	iris	iris	NOUN
cana-851	210	6	dataset	dataset	VERB
cana-851	210	7	null	null	ADJ
cana-851	210	8	public	public	NOUN
cana-851	211	1	[	[	X
cana-851	211	2	4	4	NUM
cana-851	211	3	]	]	SYM
cana-851	211	4	kaggle-5	kaggle-5	PROPN
cana-851	211	5	,	,	PUNCT
cana-851	211	6	oxford-17	oxford-17	NOUN
cana-851	211	7	,	,	PUNCT
cana-851	211	8	oxford-102	oxford-102	ADJ
cana-851	211	9	,	,	PUNCT
cana-851	211	10	and	and	CCONJ
cana-851	211	11	iris	iris	NOUN
cana-851	211	12	flower	flower	VERB
cana-851	211	13	null	null	PROPN
cana-851	211	14	null	null	ADJ
cana-851	211	15	null	null	ADJ
cana-851	211	16	public	public	ADJ
cana-851	211	17	public	public	ADJ
cana-851	211	18	public	public	NOUN
cana-851	211	19	[	[	X
cana-851	211	20	38	38	NUM
cana-851	211	21	]	]	PUNCT
cana-851	211	22	the	the	DET
cana-851	211	23	dataset	dataset	NOUN
cana-851	211	24	has	have	VERB
cana-851	211	25	4242	4242	NUM
cana-851	211	26	images	image	NOUN
cana-851	211	27	of	of	ADP
cana-851	211	28	flowers	flower	NOUN
cana-851	211	29	,	,	PUNCT
cana-851	211	30	which	which	PRON
cana-851	211	31	are	be	AUX
cana-851	211	32	classified	classify	VERB
cana-851	211	33	into	into	ADP
cana-851	211	34	five	five	NUM
cana-851	211	35	distinct	distinct	ADJ
cana-851	211	36	categories	category	NOUN
cana-851	211	37	.	.	PUNCT
cana-851	212	1	these	these	DET
cana-851	212	2	images	image	NOUN
cana-851	212	3	were	be	AUX
cana-851	212	4	obtained	obtain	VERB
cana-851	212	5	from	from	ADP
cana-851	212	6	the	the	DET
cana-851	212	7	kaggle	kaggle	ADJ
cana-851	212	8	flower	flower	NOUN
cana-851	212	9	recognition	recognition	PROPN
cana-851	212	10	dataset	dataset	NOUN
cana-851	212	11	.	.	PUNCT
cana-851	213	1	null	null	ADJ
cana-851	213	2	public	public	NOUN
cana-851	213	3	[	[	X
cana-851	213	4	39	39	NUM
cana-851	213	5	]	]	PUNCT
cana-851	213	6	kaggle	kaggle	NOUN
cana-851	213	7	oxford17	oxford17	PROPN
cana-851	213	8	oxford102	oxford102	PROPN
cana-851	213	9	.	.	PROPN
cana-851	213	10	null	null	ADJ
cana-851	213	11	null	null	ADJ
cana-851	213	12	null	null	ADJ
cana-851	213	13	public	public	ADJ
cana-851	213	14	public	public	ADJ
cana-851	213	15	public	public	NOUN
cana-851	213	16	[	[	X
cana-851	213	17	40	40	NUM
cana-851	213	18	]	]	PUNCT
cana-851	213	19	the	the	DET
cana-851	213	20	dataset	dataset	NOUN
cana-851	213	21	has	have	VERB
cana-851	213	22	three	three	NUM
cana-851	213	23	data	datum	NOUN
cana-851	213	24	files	file	NOUN
cana-851	213	25	,	,	PUNCT
cana-851	213	26	namely	namely	ADV
cana-851	213	27	testing	testing	NOUN
cana-851	213	28	,	,	PUNCT
cana-851	213	29	training	training	NOUN
cana-851	213	30	,	,	PUNCT
cana-851	213	31	and	and	CCONJ
cana-851	213	32	validation	validation	NOUN
cana-851	213	33	,	,	PUNCT
cana-851	213	34	each	each	PRON
cana-851	213	35	containing	contain	VERB
cana-851	213	36	16	16	NUM
cana-851	213	37	files	file	NOUN
cana-851	213	38	.	.	PUNCT
cana-851	214	1	a	a	DET
cana-851	214	2	total	total	NOUN
cana-851	214	3	of	of	ADP
cana-851	214	4	104	104	NUM
cana-851	214	5	unique	unique	ADJ
cana-851	214	6	flower	flower	NOUN
cana-851	214	7	species	specie	NOUN
cana-851	214	8	were	be	AUX
cana-851	214	9	identified	identify	VERB
cana-851	214	10	.	.	PUNCT
cana-851	215	1	null	null	ADJ
cana-851	215	2	public	public	ADJ
cana-851	215	3	communications	communication	NOUN
cana-851	215	4	on	on	ADP
cana-851	215	5	applied	apply	VERB
cana-851	215	6	nonlinear	nonlinear	ADJ
cana-851	215	7	analysis	analysis	NOUN
cana-851	215	8	issn	issn	NOUN
cana-851	215	9	:	:	PUNCT
cana-851	215	10	1074	1074	NUM
cana-851	215	11	-	-	PUNCT
cana-851	215	12	133x	133x	NUM
cana-851	215	13	vol	vol	NOUN
cana-851	215	14	31	31	NUM
cana-851	215	15	no	no	NOUN
cana-851	215	16	.	.	PUNCT
cana-851	216	1	4s	4s	NUM
cana-851	216	2	(	(	PUNCT
cana-851	216	3	2024	2024	NUM
cana-851	216	4	)	)	PUNCT
cana-851	216	5	282	282	NUM
cana-851	216	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-851	216	7	classified	classify	VERB
cana-851	216	8	with	with	ADP
cana-851	216	9	images	image	NOUN
cana-851	216	10	sourced	source	VERB
cana-851	216	11	from	from	ADP
cana-851	216	12	five	five	NUM
cana-851	216	13	distinct	distinct	ADJ
cana-851	216	14	public	public	ADJ
cana-851	216	15	repositories	repository	NOUN
cana-851	216	16	.	.	PUNCT
cana-851	217	1	[	[	X
cana-851	217	2	41	41	NUM
cana-851	217	3	]	]	PUNCT
cana-851	217	4	the	the	DET
cana-851	217	5	dataset	dataset	NOUN
cana-851	217	6	consists	consist	VERB
cana-851	217	7	of	of	ADP
cana-851	217	8	five	five	NUM
cana-851	217	9	classes	class	NOUN
cana-851	217	10	.	.	PUNCT
cana-851	218	1	including	include	VERB
cana-851	218	2	chamomile	chamomile	NOUN
cana-851	218	3	,	,	PUNCT
cana-851	218	4	tulip	tulip	VERB
cana-851	218	5	,	,	PUNCT
cana-851	218	6	rose	rise	VERB
cana-851	218	7	,	,	PUNCT
cana-851	218	8	sunflower	sunflower	NOUN
cana-851	218	9	and	and	CCONJ
cana-851	218	10	dandelion	dandelion	NOUN
cana-851	218	11	.	.	PUNCT
cana-851	219	1	public	public	ADJ
cana-851	219	2	,	,	PUNCT
cana-851	219	3	[	[	X
cana-851	219	4	43	43	NUM
cana-851	219	5	]	]	PUNCT
cana-851	219	6	the	the	DET
cana-851	219	7	total	total	ADJ
cana-851	219	8	dataset	dataset	NOUN
cana-851	219	9	used	use	VERB
cana-851	219	10	is	be	AUX
cana-851	219	11	1200	1200	NUM
cana-851	219	12	,	,	PUNCT
cana-851	219	13	and	and	CCONJ
cana-851	219	14	was	be	AUX
cana-851	219	15	obtained	obtain	VERB
cana-851	219	16	randomly	randomly	ADV
cana-851	219	17	using	use	VERB
cana-851	219	18	google	google	PROPN
cana-851	219	19	image	image	NOUN
cana-851	219	20	.	.	PUNCT
cana-851	220	1	the	the	DET
cana-851	220	2	data	datum	NOUN
cana-851	220	3	in	in	ADP
cana-851	220	4	the	the	DET
cana-851	220	5	rose	rose	NOUN
cana-851	220	6	category	category	NOUN
cana-851	220	7	are	be	AUX
cana-851	220	8	400	400	NUM
cana-851	220	9	,	,	PUNCT
cana-851	220	10	tulip	tulip	ADJ
cana-851	220	11	flowers	flower	NOUN
cana-851	220	12	are	be	AUX
cana-851	220	13	400	400	NUM
cana-851	220	14	and	and	CCONJ
cana-851	220	15	aster	aster	NOUN
cana-851	220	16	flowers	flower	NOUN
cana-851	220	17	are	be	AUX
cana-851	220	18	400	400	NUM
cana-851	220	19	.	.	PUNCT
cana-851	221	1	public	public	ADJ
cana-851	221	2	[	[	X
cana-851	221	3	19	19	NUM
cana-851	221	4	]	]	ADJ
cana-851	221	5	oxford17	oxford17	NOUN
cana-851	221	6	null	null	ADJ
cana-851	221	7	public	public	NOUN
cana-851	221	8	[	[	X
cana-851	221	9	42	42	NUM
cana-851	221	10	]	]	PUNCT
cana-851	221	11	the	the	DET
cana-851	221	12	research	research	NOUN
cana-851	221	13	paper	paper	NOUN
cana-851	221	14	utilizes	utilize	VERB
cana-851	221	15	the	the	DET
cana-851	221	16	flowers	flower	NOUN
cana-851	221	17	17	17	NUM
cana-851	221	18	dataset	dataset	NOUN
cana-851	221	19	,	,	PUNCT
cana-851	221	20	which	which	PRON
cana-851	221	21	consists	consist	VERB
cana-851	221	22	of	of	ADP
cana-851	221	23	17	17	NUM
cana-851	221	24	common	common	ADJ
cana-851	221	25	flowers	flower	NOUN
cana-851	221	26	in	in	ADP
cana-851	221	27	the	the	DET
cana-851	221	28	uk	uk	PROPN
cana-851	221	29	,	,	PUNCT
cana-851	221	30	including	include	VERB
cana-851	221	31	sunflowers	sunflower	NOUN
cana-851	221	32	,	,	PUNCT
cana-851	221	33	hyacinths	hyacinth	NOUN
cana-851	221	34	,	,	PUNCT
cana-851	221	35	daffodils	daffodil	NOUN
cana-851	221	36	,	,	PUNCT
cana-851	221	37	and	and	CCONJ
cana-851	221	38	chrysanthemums	chrysanthemum	NOUN
cana-851	221	39	,	,	PUNCT
cana-851	221	40	with	with	ADP
cana-851	221	41	each	each	DET
cana-851	221	42	category	category	NOUN
cana-851	221	43	having	have	VERB
cana-851	221	44	80	80	NUM
cana-851	221	45	images	image	NOUN
cana-851	221	46	with	with	ADP
cana-851	221	47	variations	variation	NOUN
cana-851	221	48	in	in	ADP
cana-851	221	49	pose	pose	NOUN
cana-851	221	50	,	,	PUNCT
cana-851	221	51	size	size	NOUN
cana-851	221	52	,	,	PUNCT
cana-851	221	53	and	and	CCONJ
cana-851	221	54	perspective	perspective	NOUN
cana-851	221	55	null	null	ADJ
cana-851	221	56	public	public	NOUN
cana-851	221	57	[	[	X
cana-851	221	58	44	44	NUM
cana-851	221	59	]	]	PUNCT
cana-851	221	60	oxford	oxford	PROPN
cana-851	221	61	102	102	NUM
cana-851	221	62	null	null	ADJ
cana-851	221	63	public	public	NOUN
cana-851	221	64	[	[	X
cana-851	221	65	10	10	NUM
cana-851	221	66	]	]	SYM
cana-851	221	67	oxford	oxford	NOUN
cana-851	221	68	102	102	NUM
cana-851	221	69	null	null	ADJ
cana-851	221	70	public	public	ADJ
cana-851	221	71	7	7	NUM
cana-851	221	72	.	.	PUNCT
cana-851	221	73	conclusion	conclusion	NOUN
cana-851	221	74	this	this	DET
cana-851	221	75	paper	paper	NOUN
cana-851	221	76	provides	provide	VERB
cana-851	221	77	a	a	DET
cana-851	221	78	comprehensive	comprehensive	ADJ
cana-851	221	79	summary	summary	NOUN
cana-851	221	80	of	of	ADP
cana-851	221	81	the	the	DET
cana-851	221	82	most	most	ADV
cana-851	221	83	recent	recent	ADJ
cana-851	221	84	advancements	advancement	NOUN
cana-851	221	85	in	in	ADP
cana-851	221	86	data	datum	NOUN
cana-851	221	87	,	,	PUNCT
cana-851	221	88	machine	machine	NOUN
cana-851	221	89	learning	learning	NOUN
cana-851	221	90	and	and	CCONJ
cana-851	221	91	deep	deep	ADJ
cana-851	221	92	learning	learning	NOUN
cana-851	221	93	algorithms	algorithm	NOUN
cana-851	221	94	are	be	AUX
cana-851	221	95	utilized	utilize	VERB
cana-851	221	96	for	for	ADP
cana-851	221	97	flowers	flower	NOUN
cana-851	221	98	image	image	NOUN
cana-851	221	99	classification	classification	NOUN
cana-851	221	100	.	.	PUNCT
cana-851	222	1	it	it	PRON
cana-851	222	2	combines	combine	VERB
cana-851	222	3	insights	insight	NOUN
cana-851	222	4	from	from	ADP
cana-851	222	5	over	over	ADP
cana-851	222	6	40	40	NUM
cana-851	222	7	studies	study	NOUN
cana-851	222	8	published	publish	VERB
cana-851	222	9	in	in	ADP
cana-851	222	10	the	the	DET
cana-851	222	11	previous	previous	ADJ
cana-851	222	12	few	few	ADJ
cana-851	222	13	years	year	NOUN
cana-851	222	14	that	that	PRON
cana-851	222	15	have	have	AUX
cana-851	222	16	utilized	utilize	VERB
cana-851	222	17	machine	machine	NOUN
cana-851	222	18	learning	learning	NOUN
cana-851	222	19	and	and	CCONJ
cana-851	222	20	deep	deep	ADJ
cana-851	222	21	learning	learning	NOUN
cana-851	222	22	techniques	technique	NOUN
cana-851	222	23	to	to	PART
cana-851	222	24	address	address	VERB
cana-851	222	25	this	this	DET
cana-851	222	26	topic	topic	NOUN
cana-851	222	27	.	.	PUNCT
cana-851	223	1	the	the	DET
cana-851	223	2	content	content	NOUN
cana-851	223	3	presented	present	VERB
cana-851	223	4	in	in	ADP
cana-851	223	5	the	the	DET
cana-851	223	6	whole	whole	ADJ
cana-851	223	7	document	document	NOUN
cana-851	223	8	can	can	AUX
cana-851	223	9	be	be	AUX
cana-851	223	10	condensed	condense	VERB
cana-851	223	11	as	as	SCONJ
cana-851	223	12	follows	follow	VERB
cana-851	223	13	.	.	PUNCT
cana-851	224	1	regarding	regard	VERB
cana-851	224	2	data	data	NOUN
cana-851	224	3	preparation	preparation	NOUN
cana-851	224	4	,	,	PUNCT
cana-851	224	5	the	the	DET
cana-851	224	6	initial	initial	ADJ
cana-851	224	7	step	step	NOUN
cana-851	224	8	involves	involve	VERB
cana-851	224	9	the	the	DET
cana-851	224	10	selection	selection	NOUN
cana-851	224	11	of	of	ADP
cana-851	224	12	public	public	ADJ
cana-851	224	13	datasets	dataset	NOUN
cana-851	224	14	for	for	ADP
cana-851	224	15	training	training	NOUN
cana-851	224	16	purposes	purpose	NOUN
cana-851	224	17	.	.	PUNCT
cana-851	225	1	if	if	SCONJ
cana-851	225	2	the	the	DET
cana-851	225	3	data	datum	NOUN
cana-851	225	4	in	in	ADP
cana-851	225	5	the	the	DET
cana-851	225	6	public	public	ADJ
cana-851	225	7	dataset	dataset	NOUN
cana-851	225	8	is	be	AUX
cana-851	225	9	not	not	PART
cana-851	225	10	enough	enough	ADJ
cana-851	225	11	,	,	PUNCT
cana-851	225	12	create	create	VERB
cana-851	225	13	a	a	DET
cana-851	225	14	new	new	ADJ
cana-851	225	15	dataset	dataset	NOUN
cana-851	225	16	and	and	CCONJ
cana-851	225	17	carry	carry	VERB
cana-851	225	18	out	out	ADP
cana-851	225	19	the	the	DET
cana-851	225	20	required	require	VERB
cana-851	225	21	picture	picture	NOUN
cana-851	225	22	pre	pre	ADJ
cana-851	225	23	-	-	ADJ
cana-851	225	24	processing	processing	ADJ
cana-851	225	25	and	and	CCONJ
cana-851	225	26	data	datum	NOUN
cana-851	225	27	improvement	improvement	NOUN
cana-851	225	28	.	.	PUNCT
cana-851	226	1	regarding	regard	VERB
cana-851	226	2	model	model	NOUN
cana-851	226	3	selection	selection	NOUN
cana-851	226	4	,	,	PUNCT
cana-851	226	5	based	base	VERB
cana-851	226	6	on	on	ADP
cana-851	226	7	the	the	DET
cana-851	226	8	complexity	complexity	NOUN
cana-851	226	9	of	of	ADP
cana-851	226	10	the	the	DET
cana-851	226	11	problem	problem	NOUN
cana-851	226	12	to	to	PART
cana-851	226	13	be	be	AUX
cana-851	226	14	resolved	resolve	VERB
cana-851	226	15	,	,	PUNCT
cana-851	226	16	therefore	therefore	ADV
cana-851	226	17	,	,	PUNCT
cana-851	226	18	based	base	VERB
cana-851	226	19	on	on	ADP
cana-851	226	20	these	these	DET
cana-851	226	21	findings	finding	NOUN
cana-851	226	22	,	,	PUNCT
cana-851	226	23	we	we	PRON
cana-851	226	24	may	may	AUX
cana-851	226	25	deduce	deduce	VERB
cana-851	226	26	that	that	SCONJ
cana-851	226	27	the	the	DET
cana-851	226	28	selection	selection	NOUN
cana-851	226	29	of	of	ADP
cana-851	226	30	a	a	DET
cana-851	226	31	classification	classification	NOUN
cana-851	226	32	method	method	NOUN
cana-851	226	33	is	be	AUX
cana-851	226	34	entirely	entirely	ADV
cana-851	226	35	contingent	contingent	ADJ
cana-851	226	36	upon	upon	SCONJ
cana-851	226	37	the	the	DET
cana-851	226	38	specific	specific	ADJ
cana-851	226	39	problem	problem	NOUN
cana-851	226	40	domain	domain	NOUN
cana-851	226	41	and	and	CCONJ
cana-851	226	42	the	the	DET
cana-851	226	43	research	research	NOUN
cana-851	226	44	work	work	NOUN
cana-851	226	45	's	's	PART
cana-851	226	46	requirements	requirement	NOUN
cana-851	226	47	.	.	PUNCT
cana-851	227	1	in	in	ADP
cana-851	227	2	the	the	DET
cana-851	227	3	field	field	NOUN
cana-851	227	4	of	of	ADP
cana-851	227	5	classification	classification	NOUN
cana-851	227	6	,	,	PUNCT
cana-851	227	7	it	it	PRON
cana-851	227	8	has	have	AUX
cana-851	227	9	been	be	AUX
cana-851	227	10	observed	observe	VERB
cana-851	227	11	that	that	SCONJ
cana-851	227	12	numerous	numerous	ADJ
cana-851	227	13	research	research	NOUN
cana-851	227	14	papers	paper	NOUN
cana-851	227	15	have	have	AUX
cana-851	227	16	utilized	utilize	VERB
cana-851	227	17	many	many	ADJ
cana-851	227	18	feature	feature	NOUN
cana-851	227	19	attributes	attribute	NOUN
cana-851	227	20	,	,	PUNCT
cana-851	227	21	such	such	ADJ
cana-851	227	22	as	as	ADP
cana-851	227	23	shape	shape	NOUN
cana-851	227	24	,	,	PUNCT
cana-851	227	25	color	color	NOUN
cana-851	227	26	,	,	PUNCT
cana-851	227	27	and	and	CCONJ
cana-851	227	28	texture	texture	NOUN
cana-851	227	29	,	,	PUNCT
cana-851	227	30	in	in	ADP
cana-851	227	31	conjunction	conjunction	NOUN
cana-851	227	32	with	with	ADP
cana-851	227	33	various	various	ADJ
cana-851	227	34	feature	feature	NOUN
cana-851	227	35	extraction	extraction	NOUN
cana-851	227	36	methods	method	NOUN
cana-851	227	37	.	.	PUNCT
cana-851	228	1	these	these	DET
cana-851	228	2	studies	study	NOUN
cana-851	228	3	have	have	AUX
cana-851	228	4	consistently	consistently	ADV
cana-851	228	5	demonstrated	demonstrate	VERB
cana-851	228	6	that	that	SCONJ
cana-851	228	7	using	use	VERB
cana-851	228	8	multiple	multiple	ADJ
cana-851	228	9	features	feature	NOUN
cana-851	228	10	leads	lead	VERB
cana-851	228	11	to	to	ADP
cana-851	228	12	improved	improved	ADJ
cana-851	228	13	performance	performance	NOUN
cana-851	228	14	compared	compare	VERB
cana-851	228	15	to	to	ADP
cana-851	228	16	using	use	VERB
cana-851	228	17	a	a	DET
cana-851	228	18	single	single	ADJ
cana-851	228	19	feature	feature	NOUN
cana-851	228	20	alone	alone	ADV
cana-851	228	21	.	.	PUNCT
cana-851	229	1	deep	deep	ADJ
cana-851	229	2	learning	learning	NOUN
cana-851	229	3	possesses	possess	VERB
cana-851	229	4	the	the	DET
cana-851	229	5	capability	capability	NOUN
cana-851	229	6	to	to	PART
cana-851	229	7	autonomously	autonomously	ADV
cana-851	229	8	extract	extract	VERB
cana-851	229	9	features	feature	NOUN
cana-851	229	10	and	and	CCONJ
cana-851	229	11	exhibits	exhibit	VERB
cana-851	229	12	a	a	DET
cana-851	229	13	robust	robust	ADJ
cana-851	229	14	ability	ability	NOUN
cana-851	229	15	to	to	PART
cana-851	229	16	generalize	generalize	VERB
cana-851	229	17	,	,	PUNCT
cana-851	229	18	hence	hence	ADV
cana-851	229	19	reducing	reduce	VERB
cana-851	229	20	the	the	DET
cana-851	229	21	need	need	NOUN
cana-851	229	22	for	for	ADP
cana-851	229	23	human	human	ADJ
cana-851	229	24	intervention	intervention	NOUN
cana-851	229	25	in	in	ADP
cana-851	229	26	the	the	DET
cana-851	229	27	processing	processing	NOUN
cana-851	229	28	of	of	ADP
cana-851	229	29	floral	floral	ADJ
cana-851	229	30	images	image	NOUN
cana-851	229	31	and	and	CCONJ
cana-851	229	32	significantly	significantly	ADV
cana-851	229	33	enhancing	enhance	VERB
cana-851	229	34	processing	processing	NOUN
cana-851	229	35	efficiency	efficiency	NOUN
cana-851	229	36	.	.	PUNCT
cana-851	230	1	by	by	ADP
cana-851	230	2	iteratively	iteratively	ADV
cana-851	230	3	optimizing	optimize	VERB
cana-851	230	4	the	the	DET
cana-851	230	5	model	model	NOUN
cana-851	230	6	and	and	CCONJ
cana-851	230	7	improving	improve	VERB
cana-851	230	8	the	the	DET
cana-851	230	9	dataset	dataset	NOUN
cana-851	230	10	,	,	PUNCT
cana-851	230	11	deep	deep	ADJ
cana-851	230	12	learning	learning	NOUN
cana-851	230	13	can	can	AUX
cana-851	230	14	be	be	AUX
cana-851	230	15	more	more	ADV
cana-851	230	16	capably	capably	ADV
cana-851	230	17	utilized	utilize	VERB
cana-851	230	18	in	in	ADP
cana-851	230	19	practical	practical	ADJ
cana-851	230	20	applications	application	NOUN
cana-851	230	21	related	relate	VERB
cana-851	230	22	to	to	ADP
cana-851	230	23	flowers	flower	NOUN
cana-851	230	24	,	,	PUNCT
cana-851	230	25	thus	thus	ADV
cana-851	230	26	making	make	VERB
cana-851	230	27	substantial	substantial	ADJ
cana-851	230	28	contributions	contribution	NOUN
cana-851	230	29	to	to	ADP
cana-851	230	30	human	human	ADJ
cana-851	230	31	society	society	NOUN
cana-851	230	32	.	.	PUNCT
cana-851	231	1	references	reference	NOUN
cana-851	231	2	[	[	X
cana-851	231	3	1	1	NUM
cana-851	231	4	]	]	PUNCT
cana-851	232	1	c.	c.	PROPN
cana-851	232	2	s.	s.	PROPN
cana-851	232	3	p.	p.	PROPN
cana-851	232	4	rabindra	rabindra	PROPN
cana-851	232	5	patel1	patel1	PROPN
cana-851	232	6	*	*	PROPN
cana-851	232	7	,	,	PUNCT
cana-851	232	8	"	"	PUNCT
cana-851	232	9	a	a	DET
cana-851	232	10	review	review	NOUN
cana-851	232	11	on	on	ADP
cana-851	232	12	flower	flower	NOUN
cana-851	232	13	image	image	NOUN
cana-851	232	14	recognition	recognition	NOUN
cana-851	232	15	,	,	PUNCT
cana-851	232	16	"	"	PUNCT
cana-851	232	17	,	,	PUNCT
cana-851	232	18	.	.	PUNCT
cana-851	233	1	international	international	ADJ
cana-851	233	2	journal	journal	PROPN
cana-851	233	3	of	of	ADP
cana-851	233	4	computer	computer	NOUN
cana-851	233	5	sciece	sciece	NOUN
cana-851	233	6	and	and	CCONJ
cana-851	233	7	engineering	engineering	NOUN
cana-851	233	8	7(12	7(12	NUM
cana-851	233	9	)	)	PUNCT
cana-851	233	10	,	,	PUNCT
cana-851	233	11	206	206	NUM
cana-851	233	12	-	-	SYM
cana-851	233	13	216	216	NUM
cana-851	233	14	,	,	PUNCT
cana-851	233	15	2019	2019	NUM
cana-851	233	16	.	.	PUNCT
cana-851	234	1	[	[	X
cana-851	234	2	2	2	NUM
cana-851	234	3	]	]	PUNCT
cana-851	234	4	m.	m.	NOUN
cana-851	234	5	toğaçar	toğaçar	PROPN
cana-851	234	6	,	,	PUNCT
cana-851	234	7	b.	b.	PROPN
cana-851	234	8	ergen	ergen	PROPN
cana-851	234	9	,	,	PUNCT
cana-851	234	10	and	and	CCONJ
cana-851	234	11	z.	z.	PROPN
cana-851	234	12	j.	j.	PROPN
cana-851	234	13	m.	m.	PROPN
cana-851	234	14	cömert	cömert	PROPN
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cana-851	234	28	of	of	ADP
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cana-851	234	32	in	in	ADP
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cana-851	234	34	neural	neural	ADJ
cana-851	234	35	network	network	NOUN
cana-851	234	36	models	model	NOUN
cana-851	234	37	,	,	PUNCT
cana-851	234	38	"	"	PUNCT
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cana-851	234	42	,	,	PUNCT
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cana-851	234	45	,	,	PUNCT
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cana-851	234	47	.	.	PUNCT
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cana-851	235	2	3	3	X
cana-851	235	3	]	]	PUNCT
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cana-851	235	21	,	,	PUNCT
cana-851	235	22	"	"	PUNCT
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cana-851	235	24	.	.	PUNCT
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cana-851	236	7	:	:	PUNCT
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cana-851	236	9	-	-	PUNCT
cana-851	236	10	133x	133x	NUM
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cana-851	237	2	(	(	PUNCT
cana-851	237	3	2024	2024	NUM
cana-851	237	4	)	)	PUNCT
cana-851	237	5	283	283	NUM
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cana-851	238	3	]	]	PUNCT
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cana-851	238	45	(	(	PUNCT
cana-851	238	46	iceccme	iceccme	NOUN
cana-851	238	47	)	)	PUNCT
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cana-851	238	56	:	:	PUNCT
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cana-851	239	3	]	]	X
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cana-851	239	25	,	,	PUNCT
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cana-851	245	46	4	4	NUM
cana-851	245	47	:	:	PUNCT
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cana-851	246	42	(	(	PUNCT
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cana-851	246	51	-	-	SYM
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cana-851	246	53	:	:	PUNCT
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cana-851	247	37	(	(	PUNCT
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cana-851	247	39	)	)	PUNCT
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cana-851	247	42	,	,	PUNCT
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cana-851	248	4	:	:	PUNCT
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cana-851	249	42	,	,	PUNCT
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cana-851	249	45	,	,	PUNCT
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cana-851	251	31	(	(	PUNCT
cana-851	251	32	iccubea	iccubea	NOUN
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cana-851	251	36	,	,	PUNCT
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cana-851	252	2	-	-	SYM
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cana-851	252	4	:	:	PUNCT
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cana-851	253	31	customized	customize	VERB
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cana-851	253	34	,	,	PUNCT
cana-851	253	35	"	"	PUNCT
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cana-851	253	39	,	,	PUNCT
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cana-851	253	41	.	.	NOUN
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cana-851	253	43	,	,	PUNCT
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cana-851	253	46	,	,	PUNCT
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cana-851	254	22	"	"	PUNCT
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cana-851	254	26	conference	conference	NOUN
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cana-851	254	30	power	power	NOUN
cana-851	254	31	and	and	CCONJ
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cana-851	254	33	technologies	technology	NOUN
cana-851	254	34	(	(	PUNCT
cana-851	254	35	gucon	gucon	NOUN
cana-851	254	36	)	)	PUNCT
cana-851	254	37	,	,	PUNCT
cana-851	254	38	2018	2018	NUM
cana-851	254	39	,	,	PUNCT
cana-851	254	40	pp	pp	ADJ
cana-851	254	41	.	.	PUNCT
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cana-851	254	43	-	-	SYM
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cana-851	254	45	:	:	PUNCT
cana-851	254	46	ieee	ieee	NOUN
cana-851	254	47	.	.	PUNCT
cana-851	255	1	[	[	X
cana-851	255	2	16	16	NUM
cana-851	255	3	]	]	PUNCT
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cana-851	255	36	,	,	PUNCT
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cana-851	256	2	-	-	SYM
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cana-851	256	4	:	:	PUNCT
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cana-851	259	2	-	-	SYM
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cana-851	266	2	-	-	SYM
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cana-851	267	46	,	,	PUNCT
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cana-851	268	2	-	-	SYM
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cana-851	269	3	]	]	X
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cana-851	269	19	,	,	PUNCT
cana-851	269	20	"	"	PUNCT
cana-851	269	21	a	a	DET
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cana-851	269	31	,	,	PUNCT
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cana-851	269	42	.	.	PUNCT
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cana-851	270	2	-	-	SYM
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cana-851	270	4	,	,	PUNCT
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cana-851	271	3	]	]	X
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cana-851	271	25	,	,	PUNCT
cana-851	271	26	"	"	PUNCT
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cana-851	271	33	,	,	PUNCT
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cana-851	271	38	learning	learning	NOUN
cana-851	271	39	for	for	ADP
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cana-851	271	42	,	,	PUNCT
cana-851	271	43	2019	2019	NUM
cana-851	271	44	.	.	PUNCT
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cana-851	272	2	on	on	ADP
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cana-851	272	7	:	:	PUNCT
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cana-851	272	9	-	-	PUNCT
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cana-851	273	2	(	(	PUNCT
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cana-851	273	4	)	)	PUNCT
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cana-851	274	3	]	]	X
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cana-851	274	13	y.	y.	PROPN
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cana-851	274	17	w.	w.	PROPN
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cana-851	274	20	"	"	PUNCT
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cana-851	274	27	,	,	PUNCT
cana-851	274	28	"	"	PUNCT
cana-851	274	29	in	in	ADP
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cana-851	274	34	on	on	ADP
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cana-851	274	41	,	,	PUNCT
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cana-851	274	43	,	,	PUNCT
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cana-851	274	45	and	and	CCONJ
cana-851	274	46	applications	application	NOUN
cana-851	274	47	(	(	PUNCT
cana-851	274	48	fspma	fspma	NOUN
cana-851	274	49	)	)	PUNCT
cana-851	274	50	,	,	PUNCT
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cana-851	275	2	-	-	SYM
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cana-851	275	4	:	:	PUNCT
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cana-851	276	3	]	]	PUNCT
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cana-851	276	18	on	on	ADP
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cana-851	276	31	,	,	PUNCT
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cana-851	276	39	,	,	PUNCT
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cana-851	276	42	:	:	PUNCT
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cana-851	276	45	.	.	PUNCT
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cana-851	277	39	(	(	PUNCT
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cana-851	277	42	,	,	PUNCT
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cana-851	277	44	,	,	PUNCT
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cana-851	277	48	-	-	SYM
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cana-851	277	50	:	:	PUNCT
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cana-851	278	42	,	,	PUNCT
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cana-851	278	46	.	.	PUNCT
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cana-851	279	2	-	-	SYM
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cana-851	280	29	"	"	PUNCT
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cana-851	280	34	:	:	PUNCT
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cana-851	280	37	,	,	PUNCT
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cana-851	280	39	,	,	PUNCT
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cana-851	280	47	,	,	PUNCT
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cana-851	280	50	:	:	PUNCT
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cana-851	281	34	(	(	PUNCT
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cana-851	281	36	)	)	PUNCT
cana-851	281	37	,	,	PUNCT
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cana-851	281	39	,	,	PUNCT
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cana-851	282	1	660664	660664	NUM
cana-851	282	2	:	:	PUNCT
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cana-851	282	4	.	.	PUNCT
cana-851	283	1	[	[	X
cana-851	283	2	30	30	NUM
cana-851	283	3	]	]	X
cana-851	283	4	l.	l.	PROPN
cana-851	283	5	shi	shi	PROPN
cana-851	283	6	,	,	PUNCT
cana-851	283	7	z.	z.	PROPN
cana-851	283	8	li	li	PROPN
cana-851	283	9	,	,	PUNCT
cana-851	283	10	and	and	CCONJ
cana-851	283	11	d.	d.	PROPN
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cana-851	283	13	,	,	PUNCT
cana-851	283	14	"	"	PUNCT
cana-851	283	15	a	a	DET
cana-851	283	16	flower	flower	NOUN
cana-851	283	17	auto	auto	NOUN
cana-851	283	18	-	-	PUNCT
cana-851	283	19	recognition	recognition	NOUN
cana-851	283	20	system	system	NOUN
cana-851	283	21	based	base	VERB
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cana-851	283	23	deep	deep	ADJ
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cana-851	283	25	,	,	PUNCT
cana-851	283	26	"	"	PUNCT
cana-851	283	27	in	in	ADP
cana-851	283	28	iop	iop	PROPN
cana-851	283	29	conference	conference	NOUN
cana-851	283	30	series	series	NOUN
cana-851	283	31	:	:	PUNCT
cana-851	283	32	earth	earth	NOUN
cana-851	283	33	and	and	CCONJ
cana-851	283	34	environmental	environmental	ADJ
cana-851	283	35	science	science	NOUN
cana-851	283	36	,	,	PUNCT
cana-851	283	37	2019	2019	NUM
cana-851	283	38	,	,	PUNCT
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cana-851	283	42	,	,	PUNCT
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cana-851	283	44	.	.	NOUN
cana-851	283	45	1	1	NUM
cana-851	283	46	,	,	PUNCT
cana-851	283	47	p.	p.	NOUN
cana-851	283	48	012088	012088	NUM
cana-851	283	49	:	:	PUNCT
cana-851	283	50	iop	iop	NOUN
cana-851	283	51	publishing	publishing	NOUN
cana-851	283	52	.	.	PUNCT
cana-851	284	1	[	[	X
cana-851	284	2	31	31	NUM
cana-851	284	3	]	]	PUNCT
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cana-851	284	11	j.	j.	PROPN
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cana-851	284	13	,	,	PUNCT
cana-851	284	14	y.	y.	PROPN
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cana-851	284	16	,	,	PUNCT
cana-851	284	17	and	and	CCONJ
cana-851	284	18	c.	c.	PROPN
cana-851	284	19	j.	j.	PROPN
cana-851	284	20	e.	e.	PROPN
cana-851	284	21	s.	s.	PROPN
cana-851	284	22	w.	w.	PROPN
cana-851	284	23	a.	a.	PROPN
cana-851	284	24	lim	lim	PROPN
cana-851	284	25	,	,	PUNCT
cana-851	284	26	"	"	PUNCT
cana-851	284	27	flower	flower	VERB
cana-851	284	28	classification	classification	NOUN
cana-851	284	29	with	with	ADP
cana-851	284	30	modified	modify	VERB
cana-851	284	31	multimodal	multimodal	NOUN
cana-851	284	32	convolutional	convolutional	ADJ
cana-851	284	33	neural	neural	ADJ
cana-851	284	34	networks	network	NOUN
cana-851	284	35	,	,	PUNCT
cana-851	284	36	"	"	PUNCT
cana-851	284	37	vol	vol	NOUN
cana-851	284	38	.	.	PROPN
cana-851	284	39	159	159	NUM
cana-851	284	40	,	,	PUNCT
cana-851	284	41	p.	p.	NOUN
cana-851	284	42	113455	113455	NUM
cana-851	284	43	,	,	PUNCT
cana-851	284	44	2020	2020	NUM
cana-851	284	45	.	.	PUNCT
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cana-851	285	2	32	32	NUM
cana-851	285	3	]	]	X
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cana-851	285	5	jaiswal	jaiswal	PROPN
cana-851	285	6	,	,	PUNCT
cana-851	285	7	v.	v.	PROPN
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cana-851	285	10	d.	d.	PROPN
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cana-851	285	12	m.	m.	PROPN
cana-851	285	13	t.	t.	PROPN
cana-851	285	14	bisen	bisen	PROPN
cana-851	285	15	,	,	PUNCT
cana-851	285	16	and	and	CCONJ
cana-851	285	17	applications	application	NOUN
cana-851	285	18	,	,	PUNCT
cana-851	285	19	"	"	PUNCT
cana-851	285	20	modified	modify	VERB
cana-851	285	21	deep	deep	ADJ
cana-851	285	22	-	-	PUNCT
cana-851	285	23	convolution	convolution	NOUN
cana-851	285	24	neural	neural	ADJ
cana-851	285	25	network	network	NOUN
cana-851	285	26	model	model	NOUN
cana-851	285	27	for	for	ADP
cana-851	285	28	flower	flower	NOUN
cana-851	285	29	images	image	NOUN
cana-851	285	30	segmentation	segmentation	NOUN
cana-851	285	31	and	and	CCONJ
cana-851	285	32	predictions	prediction	NOUN
cana-851	285	33	,	,	PUNCT
cana-851	285	34	"	"	PUNCT
cana-851	285	35	vol	vol	NOUN
cana-851	285	36	.	.	PROPN
cana-851	285	37	83	83	NUM
cana-851	285	38	,	,	PUNCT
cana-851	285	39	no	no	INTJ
cana-851	285	40	.	.	NOUN
cana-851	285	41	9	9	NUM
cana-851	285	42	,	,	PUNCT
cana-851	285	43	pp	pp	ADJ
cana-851	285	44	.	.	PUNCT
cana-851	285	45	25713	25713	NUM
cana-851	285	46	-	-	SYM
cana-851	285	47	25739	25739	NUM
cana-851	285	48	,	,	PUNCT
cana-851	285	49	2024	2024	NUM
cana-851	285	50	.	.	PUNCT
cana-851	286	1	[	[	X
cana-851	286	2	33	33	NUM
cana-851	286	3	]	]	PUNCT
cana-851	286	4	r.	r.	PROPN
cana-851	286	5	xiao	xiao	PROPN
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cana-851	286	7	r.	r.	PROPN
cana-851	286	8	wang	wang	PROPN
cana-851	286	9	,	,	PUNCT
cana-851	286	10	"	"	PUNCT
cana-851	286	11	transfer	transfer	VERB
cana-851	286	12	learning	learning	NOUN
cana-851	286	13	-	-	PUNCT
cana-851	286	14	based	base	VERB
cana-851	286	15	flower	flower	NOUN
cana-851	286	16	image	image	NOUN
cana-851	286	17	classification	classification	NOUN
cana-851	286	18	:	:	PUNCT
cana-851	286	19	leveraging	leverage	VERB
cana-851	286	20	the	the	DET
cana-851	286	21	pre	pre	ADJ
cana-851	286	22	-	-	ADJ
cana-851	286	23	trained	train	VERB
cana-851	286	24	alexnet	alexnet	ADJ
cana-851	286	25	model	model	NOUN
cana-851	286	26	,	,	PUNCT
cana-851	286	27	"	"	PUNCT
cana-851	286	28	in	in	ADP
cana-851	286	29	2023	2023	NUM
cana-851	286	30	4th	4th	ADJ
cana-851	286	31	international	international	ADJ
cana-851	286	32	symposium	symposium	NOUN
cana-851	286	33	on	on	ADP
cana-851	286	34	computer	computer	NOUN
cana-851	286	35	engineering	engineering	NOUN
cana-851	286	36	and	and	CCONJ
cana-851	286	37	intelligent	intelligent	ADJ
cana-851	286	38	communications	communication	NOUN
cana-851	286	39	(	(	PUNCT
cana-851	286	40	isceic	isceic	PROPN
cana-851	286	41	)	)	PUNCT
cana-851	286	42	,	,	PUNCT
cana-851	286	43	2023	2023	NUM
cana-851	286	44	,	,	PUNCT
cana-851	286	45	pp	pp	ADJ
cana-851	286	46	.	.	PUNCT
cana-851	287	1	519	519	NUM
cana-851	287	2	-	-	SYM
cana-851	287	3	522	522	NUM
cana-851	287	4	:	:	PUNCT
cana-851	287	5	ieee	ieee	NOUN
cana-851	287	6	.	.	PUNCT
cana-851	288	1	[	[	X
cana-851	288	2	34	34	NUM
cana-851	288	3	]	]	PUNCT
cana-851	288	4	k.	k.	PROPN
cana-851	288	5	s.	s.	PROPN
cana-851	288	6	gill	gill	PROPN
cana-851	288	7	,	,	PUNCT
cana-851	288	8	a.	a.	NOUN
cana-851	288	9	sharma	sharma	PROPN
cana-851	288	10	,	,	PUNCT
cana-851	288	11	v.	v.	PROPN
cana-851	288	12	anand	anand	PROPN
cana-851	288	13	,	,	PUNCT
cana-851	288	14	and	and	CCONJ
cana-851	288	15	r.	r.	PROPN
cana-851	288	16	gupta	gupta	PROPN
cana-851	288	17	,	,	PUNCT
cana-851	288	18	"	"	PUNCT
cana-851	288	19	flower	flower	VERB
cana-851	288	20	classification	classification	NOUN
cana-851	288	21	utilisizing	utilisizing	NOUN
cana-851	288	22	tensor	tensor	NOUN
cana-851	288	23	processing	processing	NOUN
cana-851	288	24	unit	unit	NOUN
cana-851	288	25	mechanism	mechanism	NOUN
cana-851	288	26	,	,	PUNCT
cana-851	288	27	"	"	PUNCT
cana-851	288	28	in	in	ADP
cana-851	288	29	2023	2023	NUM
cana-851	288	30	2nd	2nd	ADJ
cana-851	288	31	international	international	ADJ
cana-851	288	32	conference	conference	NOUN
cana-851	288	33	for	for	ADP
cana-851	288	34	innovation	innovation	NOUN
cana-851	288	35	in	in	ADP
cana-851	288	36	technology	technology	NOUN
cana-851	288	37	(	(	PUNCT
cana-851	288	38	inocon	inocon	NOUN
cana-851	288	39	)	)	PUNCT
cana-851	288	40	,	,	PUNCT
cana-851	288	41	2023	2023	NUM
cana-851	288	42	,	,	PUNCT
cana-851	288	43	pp	pp	ADJ
cana-851	288	44	.	.	PUNCT
cana-851	289	1	1	1	NUM
cana-851	289	2	-	-	SYM
cana-851	289	3	5	5	NUM
cana-851	289	4	:	:	PUNCT
cana-851	289	5	ieee	ieee	NOUN
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cana-851	290	1	[	[	X
cana-851	290	2	35	35	NUM
cana-851	290	3	]	]	PUNCT
cana-851	290	4	r.	r.	NOUN
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cana-851	290	8	.	.	PROPN
cana-851	290	9	,	,	PUNCT
cana-851	290	10	"	"	PUNCT
cana-851	290	11	flower	flower	NOUN
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cana-851	290	14	on	on	ADP
cana-851	290	15	an	an	DET
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cana-851	290	17	convolutional	convolutional	ADJ
cana-851	290	18	neural	neural	ADJ
cana-851	290	19	network	network	NOUN
cana-851	290	20	mobilenetv3	mobilenetv3	PROPN
cana-851	290	21	,	,	PUNCT
cana-851	290	22	"	"	PUNCT
cana-851	290	23	in	in	ADP
cana-851	290	24	2023	2023	NUM
cana-851	290	25	8th	8th	ADJ
cana-851	290	26	international	international	ADJ
cana-851	290	27	conference	conference	NOUN
cana-851	290	28	on	on	ADP
cana-851	290	29	image	image	NOUN
cana-851	290	30	,	,	PUNCT
cana-851	290	31	vision	vision	NOUN
cana-851	290	32	and	and	CCONJ
cana-851	290	33	computing	computing	NOUN
cana-851	290	34	(	(	PUNCT
cana-851	290	35	icivc	icivc	NOUN
cana-851	290	36	)	)	PUNCT
cana-851	290	37	,	,	PUNCT
cana-851	290	38	2023	2023	NUM
cana-851	290	39	,	,	PUNCT
cana-851	290	40	pp	pp	ADV
cana-851	290	41	.	.	PUNCT
cana-851	290	42	688	688	NUM
cana-851	290	43	-	-	SYM
cana-851	290	44	692	692	NUM
cana-851	290	45	:	:	PUNCT
cana-851	290	46	ieee	ieee	NOUN
cana-851	290	47	.	.	PUNCT
cana-851	291	1	[	[	X
cana-851	291	2	36	36	NUM
cana-851	291	3	]	]	X
cana-851	291	4	g.	g.	PROPN
cana-851	291	5	rajkomar	rajkomar	PROPN
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cana-851	291	7	s.	s.	PROPN
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cana-851	291	11	o.	o.	PROPN
cana-851	291	12	a.	a.	PROPN
cana-851	291	13	c.	c.	PROPN
cana-851	291	14	s.	s.	PROPN
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cana-851	291	16	,	,	PUNCT
cana-851	291	17	and	and	CCONJ
cana-851	291	18	applications	application	NOUN
cana-851	291	19	,	,	PUNCT
cana-851	291	20	"	"	PUNCT
cana-851	291	21	a	a	DET
cana-851	291	22	mobile	mobile	ADJ
cana-851	291	23	app	app	NOUN
cana-851	291	24	for	for	ADP
cana-851	291	25	the	the	DET
cana-851	291	26	identification	identification	NOUN
cana-851	291	27	of	of	ADP
cana-851	291	28	flowers	flower	NOUN
cana-851	291	29	using	use	VERB
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cana-851	291	31	learning	learning	NOUN
cana-851	291	32	,	,	PUNCT
cana-851	291	33	"	"	PUNCT
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cana-851	291	35	.	.	PROPN
cana-851	291	36	14	14	NUM
cana-851	291	37	,	,	PUNCT
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cana-851	291	40	5	5	NUM
cana-851	291	41	,	,	PUNCT
cana-851	291	42	2023	2023	NUM
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cana-851	292	1	[	[	X
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cana-851	292	3	]	]	PUNCT
cana-851	292	4	z.	z.	PROPN
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cana-851	292	6	,	,	PUNCT
cana-851	292	7	c.	c.	PROPN
cana-851	292	8	huang	huang	PROPN
cana-851	292	9	,	,	PUNCT
cana-851	292	10	w.	w.	PROPN
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cana-851	292	16	x.	x.	PROPN
cana-851	292	17	j.	j.	PROPN
cana-851	292	18	m.	m.	PROPN
cana-851	292	19	b.	b.	PROPN
cana-851	292	20	yuan	yuan	PROPN
cana-851	292	21	,	,	PUNCT
cana-851	292	22	and	and	CCONJ
cana-851	292	23	engineering	engineering	NOUN
cana-851	292	24	,	,	PUNCT
cana-851	292	25	"	"	PUNCT
cana-851	292	26	flower	flower	NOUN
cana-851	292	27	image	image	NOUN
cana-851	292	28	classification	classification	NOUN
cana-851	292	29	based	base	VERB
cana-851	292	30	on	on	ADP
cana-851	292	31	an	an	DET
cana-851	292	32	improved	improved	ADJ
cana-851	292	33	lightweight	lightweight	ADJ
cana-851	292	34	neural	neural	ADJ
cana-851	292	35	network	network	NOUN
cana-851	292	36	with	with	ADP
cana-851	292	37	multi	multi	ADJ
cana-851	292	38	-	-	ADJ
cana-851	292	39	scale	scale	ADJ
cana-851	292	40	feature	feature	NOUN
cana-851	292	41	fusion	fusion	NOUN
cana-851	292	42	and	and	CCONJ
cana-851	292	43	attention	attention	NOUN
cana-851	292	44	mechanism	mechanism	NOUN
cana-851	292	45	,	,	PUNCT
cana-851	292	46	"	"	PUNCT
cana-851	292	47	vol	vol	NOUN
cana-851	292	48	.	.	PROPN
cana-851	292	49	20	20	NUM
cana-851	292	50	,	,	PUNCT
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cana-851	292	52	.	.	NOUN
cana-851	292	53	8	8	NUM
cana-851	292	54	,	,	PUNCT
cana-851	292	55	pp	pp	ADJ
cana-851	292	56	.	.	PUNCT
cana-851	292	57	13900	13900	NUM
cana-851	292	58	-	-	SYM
cana-851	292	59	13920	13920	NUM
cana-851	292	60	,	,	PUNCT
cana-851	292	61	2023	2023	NUM
cana-851	292	62	.	.	PUNCT
cana-851	293	1	[	[	X
cana-851	293	2	38	38	NUM
cana-851	293	3	]	]	PUNCT
cana-851	293	4	m.	m.	NOUN
cana-851	293	5	f.	f.	PROPN
cana-851	293	6	rabbi	rabbi	PROPN
cana-851	293	7	et	et	PROPN
cana-851	293	8	al	al	PROPN
cana-851	293	9	.	.	PROPN
cana-851	293	10	,	,	PUNCT
cana-851	293	11	"	"	PUNCT
cana-851	293	12	an	an	DET
cana-851	293	13	ensemble	ensemble	ADV
cana-851	293	14	-	-	PUNCT
cana-851	293	15	based	base	VERB
cana-851	293	16	deep	deep	ADJ
cana-851	293	17	learning	learning	NOUN
cana-851	293	18	model	model	NOUN
cana-851	293	19	for	for	ADP
cana-851	293	20	multi	multi	ADJ
cana-851	293	21	-	-	ADJ
cana-851	293	22	class	class	ADJ
cana-851	293	23	flower	flower	NOUN
cana-851	293	24	recognition	recognition	NOUN
cana-851	293	25	,	,	PUNCT
cana-851	293	26	"	"	PUNCT
cana-851	293	27	in	in	ADP
cana-851	293	28	2023	2023	NUM
cana-851	293	29	international	international	ADJ
cana-851	293	30	conference	conference	NOUN
cana-851	293	31	on	on	ADP
cana-851	293	32	next	next	ADJ
cana-851	293	33	-	-	PUNCT
cana-851	293	34	generation	generation	NOUN
cana-851	293	35	computing	computing	NOUN
cana-851	293	36	,	,	PUNCT
cana-851	293	37	iot	iot	NOUN
cana-851	293	38	and	and	CCONJ
cana-851	293	39	machine	machine	NOUN
cana-851	293	40	learning	learning	NOUN
cana-851	293	41	(	(	PUNCT
cana-851	293	42	ncim	ncim	PROPN
cana-851	293	43	)	)	PUNCT
cana-851	293	44	,	,	PUNCT
cana-851	293	45	2023	2023	NUM
cana-851	293	46	,	,	PUNCT
cana-851	293	47	pp	pp	ADJ
cana-851	293	48	.	.	PUNCT
cana-851	294	1	1	1	NUM
cana-851	294	2	-	-	SYM
cana-851	294	3	6	6	NUM
cana-851	294	4	:	:	PUNCT
cana-851	294	5	ieee	ieee	NOUN
cana-851	294	6	.	.	PUNCT
cana-851	295	1	[	[	X
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cana-851	295	3	]	]	PUNCT
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cana-851	295	5	x.	x.	PROPN
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cana-851	295	13	p.	p.	PROPN
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cana-851	295	28	multilayer	multilayer	PROPN
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cana-851	295	31	"	"	PUNCT
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cana-851	295	33	2023	2023	NUM
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cana-851	295	36	conference	conference	NOUN
cana-851	295	37	on	on	ADP
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cana-851	295	41	technology	technology	NOUN
cana-851	295	42	(	(	PUNCT
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cana-851	295	44	)	)	PUNCT
cana-851	295	45	,	,	PUNCT
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cana-851	295	47	,	,	PUNCT
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cana-851	295	53	:	:	PUNCT
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cana-851	296	3	]	]	PUNCT
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cana-851	296	5	shourie	shourie	PROPN
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cana-851	296	22	model	model	NOUN
cana-851	296	23	,	,	PUNCT
cana-851	296	24	"	"	PUNCT
cana-851	296	25	in	in	ADP
cana-851	296	26	2023	2023	NUM
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cana-851	296	28	international	international	ADJ
cana-851	296	29	conference	conference	NOUN
cana-851	296	30	on	on	ADP
cana-851	296	31	applied	apply	VERB
cana-851	296	32	artificial	artificial	ADJ
cana-851	296	33	intelligence	intelligence	NOUN
cana-851	296	34	and	and	CCONJ
cana-851	296	35	computing	computing	NOUN
cana-851	296	36	(	(	PUNCT
cana-851	296	37	icaaic	icaaic	ADJ
cana-851	296	38	)	)	PUNCT
cana-851	296	39	,	,	PUNCT
cana-851	296	40	2023	2023	NUM
cana-851	296	41	,	,	PUNCT
cana-851	296	42	pp	pp	ADJ
cana-851	296	43	.	.	PUNCT
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cana-851	297	2	-	-	SYM
cana-851	297	3	6	6	NUM
cana-851	297	4	:	:	PUNCT
cana-851	297	5	ieee	ieee	NOUN
cana-851	297	6	.	.	PUNCT
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cana-851	298	2	41	41	NUM
cana-851	298	3	]	]	X
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cana-851	298	7	a.	a.	NOUN
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cana-851	298	10	"	"	PUNCT
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cana-851	298	12	classification	classification	NOUN
cana-851	298	13	of	of	ADP
cana-851	298	14	flower	flower	NOUN
cana-851	298	15	images	image	NOUN
cana-851	298	16	using	use	VERB
cana-851	298	17	transfer	transfer	NOUN
cana-851	298	18	learning	learning	NOUN
cana-851	298	19	,	,	PUNCT
cana-851	298	20	"	"	PUNCT
cana-851	298	21	in	in	ADP
cana-851	298	22	2019	2019	NUM
cana-851	298	23	international	international	ADJ
cana-851	298	24	artificial	artificial	ADJ
cana-851	298	25	intelligence	intelligence	NOUN
cana-851	298	26	and	and	CCONJ
cana-851	298	27	data	datum	NOUN
cana-851	298	28	processing	processing	NOUN
cana-851	298	29	symposium	symposium	NOUN
cana-851	298	30	(	(	PUNCT
cana-851	298	31	idap	idap	NOUN
cana-851	298	32	)	)	PUNCT
cana-851	298	33	,	,	PUNCT
cana-851	298	34	2019	2019	NUM
cana-851	298	35	,	,	PUNCT
cana-851	298	36	pp	pp	ADJ
cana-851	298	37	.	.	PUNCT
cana-851	299	1	1	1	NUM
cana-851	299	2	-	-	SYM
cana-851	299	3	6	6	NUM
cana-851	299	4	:	:	PUNCT
cana-851	299	5	ieee	ieee	NOUN
cana-851	299	6	.	.	PUNCT
cana-851	300	1	[	[	X
cana-851	300	2	42	42	NUM
cana-851	300	3	]	]	PUNCT
cana-851	300	4	s.	s.	PROPN
cana-851	300	5	cao	cao	PROPN
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cana-851	300	9	m.	m.	PROPN
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cana-851	300	15	,	,	PUNCT
cana-851	300	16	"	"	PUNCT
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cana-851	300	19	-	-	PUNCT
cana-851	300	20	driven	drive	VERB
cana-851	300	21	deep	deep	ADJ
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cana-851	300	23	method	method	NOUN
cana-851	300	24	for	for	ADP
cana-851	300	25	flower	flower	NOUN
cana-851	300	26	recognition	recognition	NOUN
cana-851	300	27	,	,	PUNCT
cana-851	300	28	"	"	PUNCT
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cana-851	300	30	.	.	PROPN
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cana-851	300	32	,	,	PUNCT
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cana-851	300	34	.	.	NOUN
cana-851	300	35	3	3	NUM
cana-851	300	36	,	,	PUNCT
cana-851	300	37	pp	pp	ADJ
cana-851	300	38	.	.	PUNCT
cana-851	301	1	1981	1981	NUM
cana-851	301	2	-	-	SYM
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cana-851	301	4	,	,	PUNCT
cana-851	301	5	2021	2021	NUM
cana-851	301	6	.	.	PUNCT
cana-851	302	1	communications	communication	NOUN
cana-851	302	2	on	on	ADP
cana-851	302	3	applied	apply	VERB
cana-851	302	4	nonlinear	nonlinear	ADJ
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cana-851	302	6	issn	issn	NOUN
cana-851	302	7	:	:	PUNCT
cana-851	302	8	1074	1074	NUM
cana-851	302	9	-	-	PUNCT
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cana-851	303	2	(	(	PUNCT
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cana-851	303	4	)	)	PUNCT
cana-851	303	5	285	285	NUM
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cana-851	304	2	43	43	NUM
cana-851	304	3	]	]	PUNCT
cana-851	304	4	a.	a.	NOUN
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cana-851	304	8	yudhana	yudhana	PROPN
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cana-851	304	11	r.	r.	PROPN
cana-851	304	12	j.	j.	PROPN
cana-851	304	13	k.	k.	PROPN
cana-851	304	14	i.	i.	PROPN
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cana-851	304	17	k.	k.	PROPN
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cana-851	304	19	i.	i.	PROPN
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cana-851	304	22	"	"	PUNCT
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cana-851	304	29	machine	machine	NOUN
cana-851	304	30	in	in	ADP
cana-851	304	31	classification	classification	NOUN
cana-851	304	32	of	of	ADP
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cana-851	304	36	"	"	PUNCT
cana-851	304	37	vol	vol	NOUN
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cana-851	304	40	,	,	PUNCT
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cana-851	304	42	.	.	NOUN
cana-851	304	43	1	1	NUM
cana-851	304	44	,	,	PUNCT
cana-851	304	45	pp	pp	ADJ
cana-851	304	46	.	.	PUNCT
cana-851	305	1	1	1	NUM
cana-851	305	2	-	-	SYM
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cana-851	305	4	,	,	PUNCT
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cana-851	305	6	.	.	PUNCT
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cana-851	306	3	]	]	PUNCT
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cana-851	306	8	w.	w.	PROPN
cana-851	306	9	f.	f.	PROPN
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cana-851	306	12	,	,	PUNCT
cana-851	306	13	"	"	PUNCT
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cana-851	306	19	in	in	ADP
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cana-851	306	22	-	-	ADJ
cana-851	306	23	class	class	ADJ
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cana-851	306	25	,	,	PUNCT
cana-851	306	26	"	"	PUNCT
cana-851	306	27	in	in	ADP
cana-851	306	28	2020	2020	NUM
cana-851	306	29	3rd	3rd	ADJ
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cana-851	306	32	on	on	ADP
cana-851	306	33	research	research	NOUN
cana-851	306	34	of	of	ADP
cana-851	306	35	information	information	NOUN
cana-851	306	36	technology	technology	NOUN
cana-851	306	37	and	and	CCONJ
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cana-851	306	39	systems	system	NOUN
cana-851	306	40	(	(	PUNCT
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cana-851	306	42	)	)	PUNCT
cana-851	306	43	,	,	PUNCT
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cana-851	306	45	,	,	PUNCT
cana-851	306	46	pp	pp	ADV
cana-851	306	47	.	.	PUNCT
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cana-851	307	2	-	-	SYM
cana-851	307	3	78	78	NUM
cana-851	307	4	:	:	PUNCT
cana-851	307	5	ieee	ieee	NOUN
cana-851	307	6	.	.	PUNCT
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cana-851	308	3	]	]	PUNCT
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cana-851	308	27	,	,	PUNCT
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cana-851	308	29	recommendations	recommendation	NOUN
cana-851	308	30	in	in	ADP
cana-851	308	31	augmented	augment	VERB
cana-851	308	32	reality	reality	NOUN
cana-851	308	33	based	base	VERB
cana-851	308	34	on	on	ADP
cana-851	308	35	object	object	NOUN
cana-851	308	36	recognition	recognition	NOUN
cana-851	308	37	:	:	PUNCT
cana-851	308	38	systematic	systematic	ADJ
cana-851	308	39	.	.	PUNCT
cana-851	308	40	"	"	PUNCT