id	sid	tid	token	lemma	pos
fcis-11537	1	1	frontiers	frontier	NOUN
fcis-11537	1	2	in	in	ADP
fcis-11537	1	3	computing	computing	NOUN
fcis-11537	1	4	and	and	CCONJ
fcis-11537	1	5	intelligent	intelligent	ADJ
fcis-11537	1	6	systems	system	NOUN
fcis-11537	1	7	issn	issn	VERB
fcis-11537	1	8	:	:	PUNCT
fcis-11537	1	9	2832	2832	NUM
fcis-11537	1	10	-	-	SYM
fcis-11537	1	11	6024	6024	NUM
fcis-11537	1	12	|	|	NOUN
fcis-11537	1	13	vol	vol	NOUN
fcis-11537	1	14	.	.	PROPN
fcis-11537	2	1	5	5	NUM
fcis-11537	2	2	,	,	PUNCT
fcis-11537	2	3	no	no	INTJ
fcis-11537	2	4	.	.	NOUN
fcis-11537	2	5	1	1	NUM
fcis-11537	2	6	,	,	PUNCT
fcis-11537	2	7	2023	2023	NUM
fcis-11537	2	8	15	15	NUM
fcis-11537	2	9	identification	identification	NOUN
fcis-11537	2	10	of	of	ADP
fcis-11537	2	11	coffee	coffee	NOUN
fcis-11537	2	12	leaf	leaf	NOUN
fcis-11537	2	13	pests	pest	NOUN
fcis-11537	2	14	and	and	CCONJ
fcis-11537	2	15	diseases	disease	NOUN
fcis-11537	2	16	based	base	VERB
fcis-11537	2	17	on	on	ADP
fcis-11537	2	18	transfer	transfer	NOUN
fcis-11537	2	19	learning	learning	NOUN
fcis-11537	2	20	and	and	CCONJ
fcis-11537	2	21	knowledge	knowledge	NOUN
fcis-11537	2	22	distillation	distillation	NOUN
fcis-11537	2	23	zi	zi	PROPN
fcis-11537	2	24	wang	wang	PROPN
fcis-11537	2	25	1	1	NUM
fcis-11537	2	26	,	,	PUNCT
fcis-11537	2	27	*	*	PUNCT
fcis-11537	2	28	,	,	PUNCT
fcis-11537	2	29	zheng	zheng	PROPN
fcis-11537	2	30	ren	ren	PROPN
fcis-11537	2	31	1	1	NUM
fcis-11537	2	32	,	,	PUNCT
fcis-11537	2	33	xue	xue	PROPN
fcis-11537	2	34	li	li	PROPN
fcis-11537	2	35	2	2	NUM
fcis-11537	2	36	1	1	NUM
fcis-11537	2	37	school	school	NOUN
fcis-11537	2	38	of	of	ADP
fcis-11537	2	39	electrical	electrical	ADJ
fcis-11537	2	40	and	and	CCONJ
fcis-11537	2	41	information	information	NOUN
fcis-11537	2	42	engineering	engineering	NOUN
fcis-11537	2	43	,	,	PUNCT
fcis-11537	2	44	wanjiang	wanjiang	PROPN
fcis-11537	2	45	university	university	PROPN
fcis-11537	2	46	of	of	ADP
fcis-11537	2	47	technology	technology	PROPN
fcis-11537	2	48	,	,	PUNCT
fcis-11537	2	49	maanshan	maanshan	PROPN
fcis-11537	2	50	,	,	PUNCT
fcis-11537	2	51	co	co	NOUN
fcis-11537	2	52	243031	243031	NUM
fcis-11537	2	53	,	,	PUNCT
fcis-11537	2	54	china	china	PROPN
fcis-11537	2	55	2	2	NUM
fcis-11537	2	56	school	school	NOUN
fcis-11537	2	57	of	of	ADP
fcis-11537	2	58	economics	economic	NOUN
fcis-11537	2	59	and	and	CCONJ
fcis-11537	2	60	management	management	NOUN
fcis-11537	2	61	,	,	PUNCT
fcis-11537	2	62	yango	yango	PROPN
fcis-11537	2	63	university	university	PROPN
fcis-11537	2	64	,	,	PUNCT
fcis-11537	2	65	fuzhou	fuzhou	PROPN
fcis-11537	2	66	,	,	PUNCT
fcis-11537	2	67	co	co	NOUN
fcis-11537	2	68	350015	350015	NUM
fcis-11537	2	69	,	,	PUNCT
fcis-11537	2	70	china	china	PROPN
fcis-11537	2	71	*	*	PUNCT
fcis-11537	2	72	corresponding	correspond	VERB
fcis-11537	2	73	author	author	NOUN
fcis-11537	2	74	:	:	PUNCT
fcis-11537	2	75	zi	zi	PROPN
fcis-11537	2	76	wang	wang	PROPN
fcis-11537	2	77	(	(	PUNCT
fcis-11537	2	78	email	email	NOUN
fcis-11537	2	79	:	:	PUNCT
fcis-11537	2	80	1043901879@qq.com	1043901879@qq.com	NUM
fcis-11537	2	81	)	)	PUNCT
fcis-11537	2	82	abstract	abstract	NOUN
fcis-11537	2	83	:	:	PUNCT
fcis-11537	2	84	the	the	DET
fcis-11537	2	85	yield	yield	NOUN
fcis-11537	2	86	of	of	ADP
fcis-11537	2	87	coffee	coffee	NOUN
fcis-11537	2	88	has	have	VERB
fcis-11537	2	89	a	a	DET
fcis-11537	2	90	significant	significant	ADJ
fcis-11537	2	91	effect	effect	NOUN
fcis-11537	2	92	on	on	ADP
fcis-11537	2	93	the	the	DET
fcis-11537	2	94	development	development	NOUN
fcis-11537	2	95	of	of	ADP
fcis-11537	2	96	the	the	DET
fcis-11537	2	97	economy	economy	NOUN
fcis-11537	2	98	.	.	PUNCT
fcis-11537	3	1	it	it	PRON
fcis-11537	3	2	is	be	AUX
fcis-11537	3	3	important	important	ADJ
fcis-11537	3	4	to	to	PART
fcis-11537	3	5	monitor	monitor	VERB
fcis-11537	3	6	the	the	DET
fcis-11537	3	7	health	health	NOUN
fcis-11537	3	8	status	status	NOUN
fcis-11537	3	9	of	of	ADP
fcis-11537	3	10	coffee	coffee	NOUN
fcis-11537	3	11	plants	plant	NOUN
fcis-11537	3	12	.	.	PUNCT
fcis-11537	4	1	leaves	leave	NOUN
fcis-11537	4	2	can	can	AUX
fcis-11537	4	3	represent	represent	VERB
fcis-11537	4	4	the	the	DET
fcis-11537	4	5	growth	growth	NOUN
fcis-11537	4	6	of	of	ADP
fcis-11537	4	7	crops	crop	NOUN
fcis-11537	4	8	.	.	PUNCT
fcis-11537	5	1	analysis	analysis	NOUN
fcis-11537	5	2	leaf	leaf	NOUN
fcis-11537	5	3	image	image	NOUN
fcis-11537	5	4	is	be	AUX
fcis-11537	5	5	an	an	DET
fcis-11537	5	6	effective	effective	ADJ
fcis-11537	5	7	method	method	NOUN
fcis-11537	5	8	to	to	PART
fcis-11537	5	9	monitor	monitor	VERB
fcis-11537	5	10	crop	crop	NOUN
fcis-11537	5	11	growth	growth	NOUN
fcis-11537	5	12	status	status	NOUN
fcis-11537	5	13	.	.	PUNCT
fcis-11537	6	1	with	with	ADP
fcis-11537	6	2	the	the	DET
fcis-11537	6	3	advancement	advancement	NOUN
fcis-11537	6	4	of	of	ADP
fcis-11537	6	5	artificial	artificial	ADJ
fcis-11537	6	6	intelligence	intelligence	NOUN
fcis-11537	6	7	technology	technology	NOUN
fcis-11537	6	8	,	,	PUNCT
fcis-11537	6	9	neural	neural	ADJ
fcis-11537	6	10	networks	network	NOUN
fcis-11537	6	11	with	with	ADP
fcis-11537	6	12	strong	strong	ADJ
fcis-11537	6	13	learning	learning	NOUN
fcis-11537	6	14	ability	ability	NOUN
fcis-11537	6	15	have	have	AUX
fcis-11537	6	16	been	be	AUX
fcis-11537	6	17	proposed	propose	VERB
fcis-11537	6	18	.	.	PUNCT
fcis-11537	7	1	they	they	PRON
fcis-11537	7	2	have	have	VERB
fcis-11537	7	3	high	high	ADJ
fcis-11537	7	4	accuracy	accuracy	NOUN
fcis-11537	7	5	in	in	ADP
fcis-11537	7	6	identifying	identify	VERB
fcis-11537	7	7	leaf	leaf	NOUN
fcis-11537	7	8	pests	pest	NOUN
fcis-11537	7	9	and	and	CCONJ
fcis-11537	7	10	diseases	disease	NOUN
fcis-11537	7	11	.	.	PUNCT
fcis-11537	8	1	however	however	ADV
fcis-11537	8	2	,	,	PUNCT
fcis-11537	8	3	the	the	DET
fcis-11537	8	4	structure	structure	NOUN
fcis-11537	8	5	of	of	ADP
fcis-11537	8	6	these	these	DET
fcis-11537	8	7	networks	network	NOUN
fcis-11537	8	8	is	be	AUX
fcis-11537	8	9	complex	complex	ADJ
fcis-11537	8	10	and	and	CCONJ
fcis-11537	8	11	the	the	DET
fcis-11537	8	12	speed	speed	NOUN
fcis-11537	8	13	of	of	ADP
fcis-11537	8	14	computing	computing	NOUN
fcis-11537	8	15	is	be	AUX
fcis-11537	8	16	slow	slow	ADJ
fcis-11537	8	17	.	.	PUNCT
fcis-11537	9	1	they	they	PRON
fcis-11537	9	2	are	be	AUX
fcis-11537	9	3	not	not	PART
fcis-11537	9	4	conducive	conducive	ADJ
fcis-11537	9	5	to	to	ADP
fcis-11537	9	6	real	real	ADJ
fcis-11537	9	7	-	-	PUNCT
fcis-11537	9	8	time	time	NOUN
fcis-11537	9	9	analysis	analysis	NOUN
fcis-11537	9	10	.	.	PUNCT
fcis-11537	10	1	for	for	ADP
fcis-11537	10	2	simple	simple	ADJ
fcis-11537	10	3	networks	network	NOUN
fcis-11537	10	4	,	,	PUNCT
fcis-11537	10	5	it	it	PRON
fcis-11537	10	6	is	be	AUX
fcis-11537	10	7	difficult	difficult	ADJ
fcis-11537	10	8	to	to	PART
fcis-11537	10	9	achieve	achieve	VERB
fcis-11537	10	10	high	high	ADJ
fcis-11537	10	11	recognition	recognition	NOUN
fcis-11537	10	12	accuracy	accuracy	NOUN
fcis-11537	10	13	directly	directly	ADV
fcis-11537	10	14	.	.	PUNCT
fcis-11537	11	1	to	to	PART
fcis-11537	11	2	solve	solve	VERB
fcis-11537	11	3	this	this	DET
fcis-11537	11	4	problem	problem	NOUN
fcis-11537	11	5	,	,	PUNCT
fcis-11537	11	6	a	a	DET
fcis-11537	11	7	lightweight	lightweight	ADJ
fcis-11537	11	8	model	model	NOUN
fcis-11537	11	9	is	be	AUX
fcis-11537	11	10	designed	design	VERB
fcis-11537	11	11	for	for	ADP
fcis-11537	11	12	leaf	leaf	NOUN
fcis-11537	11	13	image	image	NOUN
fcis-11537	11	14	analysis	analysis	NOUN
fcis-11537	11	15	.	.	PUNCT
fcis-11537	12	1	leaf	leaf	NOUN
fcis-11537	12	2	images	image	NOUN
fcis-11537	12	3	are	be	AUX
fcis-11537	12	4	learned	learn	VERB
fcis-11537	12	5	by	by	ADP
fcis-11537	12	6	vgg	vgg	PROPN
fcis-11537	12	7	network	network	NOUN
fcis-11537	12	8	with	with	ADP
fcis-11537	12	9	pre	pre	ADJ
fcis-11537	12	10	-	-	ADJ
fcis-11537	12	11	trained	train	VERB
fcis-11537	12	12	weights	weight	NOUN
fcis-11537	12	13	on	on	ADP
fcis-11537	12	14	imagenet	imagenet	NOUN
fcis-11537	12	15	.	.	PUNCT
fcis-11537	13	1	use	use	VERB
fcis-11537	13	2	the	the	DET
fcis-11537	13	3	vgg	vgg	ADJ
fcis-11537	13	4	network	network	NOUN
fcis-11537	13	5	as	as	ADP
fcis-11537	13	6	a	a	DET
fcis-11537	13	7	teacher	teacher	NOUN
fcis-11537	13	8	network	network	NOUN
fcis-11537	13	9	.	.	PUNCT
fcis-11537	14	1	then	then	ADV
fcis-11537	14	2	design	design	VERB
fcis-11537	14	3	a	a	DET
fcis-11537	14	4	lightweight	lightweight	ADJ
fcis-11537	14	5	student	student	NOUN
fcis-11537	14	6	network	network	NOUN
fcis-11537	14	7	.	.	PUNCT
fcis-11537	15	1	train	train	NOUN
fcis-11537	15	2	student	student	NOUN
fcis-11537	15	3	network	network	NOUN
fcis-11537	15	4	with	with	ADP
fcis-11537	15	5	knowledge	knowledge	NOUN
fcis-11537	15	6	distillation	distillation	NOUN
fcis-11537	15	7	method	method	NOUN
fcis-11537	15	8	.	.	PUNCT
fcis-11537	16	1	a	a	DET
fcis-11537	16	2	lightweight	lightweight	ADJ
fcis-11537	16	3	model	model	NOUN
fcis-11537	16	4	with	with	ADP
fcis-11537	16	5	high	high	ADJ
fcis-11537	16	6	recognition	recognition	NOUN
fcis-11537	16	7	accuracy	accuracy	NOUN
fcis-11537	16	8	can	can	AUX
fcis-11537	16	9	be	be	AUX
fcis-11537	16	10	obtained	obtain	VERB
fcis-11537	16	11	.	.	PUNCT
fcis-11537	17	1	this	this	DET
fcis-11537	17	2	research	research	NOUN
fcis-11537	17	3	explored	explore	VERB
fcis-11537	17	4	the	the	DET
fcis-11537	17	5	effect	effect	NOUN
fcis-11537	17	6	of	of	ADP
fcis-11537	17	7	the	the	DET
fcis-11537	17	8	method	method	NOUN
fcis-11537	17	9	on	on	ADP
fcis-11537	17	10	the	the	DET
fcis-11537	17	11	coffee	coffee	NOUN
fcis-11537	17	12	leaf	leaf	NOUN
fcis-11537	17	13	data	datum	NOUN
fcis-11537	17	14	set	set	VERB
fcis-11537	17	15	.	.	PUNCT
fcis-11537	18	1	experiment	experiment	NOUN
fcis-11537	18	2	proved	prove	VERB
fcis-11537	18	3	that	that	SCONJ
fcis-11537	18	4	the	the	DET
fcis-11537	18	5	accuracy	accuracy	NOUN
fcis-11537	18	6	of	of	ADP
fcis-11537	18	7	the	the	DET
fcis-11537	18	8	proposed	propose	VERB
fcis-11537	18	9	method	method	NOUN
fcis-11537	18	10	is	be	AUX
fcis-11537	18	11	96.73	96.73	NUM
fcis-11537	18	12	%	%	NOUN
fcis-11537	18	13	.	.	PUNCT
fcis-11537	19	1	the	the	DET
fcis-11537	19	2	accuracy	accuracy	NOUN
fcis-11537	19	3	was	be	AUX
fcis-11537	19	4	4.29	4.29	NUM
fcis-11537	19	5	%	%	NOUN
fcis-11537	19	6	higher	high	ADJ
fcis-11537	19	7	than	than	ADP
fcis-11537	19	8	directly	directly	ADV
fcis-11537	19	9	training	training	NOUN
fcis-11537	19	10	.	.	PUNCT
fcis-11537	20	1	meantime	meantime	ADV
fcis-11537	20	2	,	,	PUNCT
fcis-11537	20	3	the	the	DET
fcis-11537	20	4	calculation	calculation	NOUN
fcis-11537	20	5	speed	speed	NOUN
fcis-11537	20	6	of	of	ADP
fcis-11537	20	7	the	the	DET
fcis-11537	20	8	model	model	NOUN
fcis-11537	20	9	is	be	AUX
fcis-11537	20	10	quick	quick	ADJ
fcis-11537	20	11	.	.	PUNCT
fcis-11537	21	1	the	the	DET
fcis-11537	21	2	proposed	propose	VERB
fcis-11537	21	3	method	method	NOUN
fcis-11537	21	4	is	be	AUX
fcis-11537	21	5	of	of	ADP
fcis-11537	21	6	great	great	ADJ
fcis-11537	21	7	practical	practical	ADJ
fcis-11537	21	8	significance	significance	NOUN
fcis-11537	21	9	for	for	ADP
fcis-11537	21	10	identifying	identify	VERB
fcis-11537	21	11	coffee	coffee	NOUN
fcis-11537	21	12	leaf	leaf	NOUN
fcis-11537	21	13	pests	pest	NOUN
fcis-11537	21	14	and	and	CCONJ
fcis-11537	21	15	diseases	disease	NOUN
fcis-11537	21	16	.	.	PUNCT
fcis-11537	22	1	keywords	keyword	NOUN
fcis-11537	22	2	:	:	PUNCT
fcis-11537	22	3	coffee	coffee	NOUN
fcis-11537	22	4	leaf	leaf	NOUN
fcis-11537	22	5	;	;	PUNCT
fcis-11537	22	6	transfer	transfer	NOUN
fcis-11537	22	7	learning	learning	NOUN
fcis-11537	22	8	;	;	PUNCT
fcis-11537	22	9	knowledge	knowledge	NOUN
fcis-11537	22	10	distillation	distillation	NOUN
fcis-11537	22	11	.	.	PUNCT
fcis-11537	23	1	1	1	X
fcis-11537	23	2	.	.	X
fcis-11537	23	3	introduction	introduction	NOUN
fcis-11537	23	4	the	the	DET
fcis-11537	23	5	fruit	fruit	NOUN
fcis-11537	23	6	of	of	ADP
fcis-11537	23	7	the	the	DET
fcis-11537	23	8	coffee	coffee	NOUN
fcis-11537	23	9	plant	plant	NOUN
fcis-11537	23	10	is	be	AUX
fcis-11537	23	11	nutritious	nutritious	ADJ
fcis-11537	23	12	.	.	PUNCT
fcis-11537	24	1	it	it	PRON
fcis-11537	24	2	has	have	VERB
fcis-11537	24	3	many	many	ADJ
fcis-11537	24	4	industrial	industrial	ADJ
fcis-11537	24	5	and	and	CCONJ
fcis-11537	24	6	product	product	NOUN
fcis-11537	24	7	chains	chain	NOUN
fcis-11537	24	8	.	.	PUNCT
fcis-11537	25	1	so	so	ADV
fcis-11537	25	2	,	,	PUNCT
fcis-11537	25	3	it	it	PRON
fcis-11537	25	4	has	have	VERB
fcis-11537	25	5	an	an	DET
fcis-11537	25	6	important	important	ADJ
fcis-11537	25	7	impact	impact	NOUN
fcis-11537	25	8	on	on	ADP
fcis-11537	25	9	economic	economic	ADJ
fcis-11537	25	10	development	development	NOUN
fcis-11537	25	11	[	[	X
fcis-11537	25	12	1	1	NUM
fcis-11537	25	13	]	]	PUNCT
fcis-11537	25	14	.	.	PUNCT
fcis-11537	26	1	coffee	coffee	NOUN
fcis-11537	26	2	leaves	leave	NOUN
fcis-11537	26	3	contain	contain	VERB
fcis-11537	26	4	nutrients	nutrient	NOUN
fcis-11537	26	5	such	such	ADJ
fcis-11537	26	6	as	as	ADP
fcis-11537	26	7	chlorophyll	chlorophyll	NOUN
fcis-11537	26	8	.	.	PUNCT
fcis-11537	27	1	its	its	PRON
fcis-11537	27	2	content	content	NOUN
fcis-11537	27	3	reflects	reflect	VERB
fcis-11537	27	4	the	the	DET
fcis-11537	27	5	health	health	NOUN
fcis-11537	27	6	status	status	NOUN
fcis-11537	27	7	of	of	ADP
fcis-11537	27	8	the	the	DET
fcis-11537	27	9	plant	plant	NOUN
fcis-11537	27	10	.	.	PUNCT
fcis-11537	28	1	analysis	analysis	NOUN
fcis-11537	28	2	plant	plant	NOUN
fcis-11537	28	3	leaf	leaf	NOUN
fcis-11537	28	4	image	image	NOUN
fcis-11537	28	5	is	be	AUX
fcis-11537	28	6	a	a	DET
fcis-11537	28	7	method	method	NOUN
fcis-11537	28	8	to	to	PART
fcis-11537	28	9	monitor	monitor	VERB
fcis-11537	28	10	plant	plant	NOUN
fcis-11537	28	11	health	health	NOUN
fcis-11537	28	12	.	.	PUNCT
fcis-11537	29	1	judging	judge	VERB
fcis-11537	29	2	the	the	DET
fcis-11537	29	3	growth	growth	NOUN
fcis-11537	29	4	state	state	NOUN
fcis-11537	29	5	of	of	ADP
fcis-11537	29	6	the	the	DET
fcis-11537	29	7	leaf	leaf	NOUN
fcis-11537	29	8	by	by	ADP
fcis-11537	29	9	human	human	ADJ
fcis-11537	29	10	eyes	eye	NOUN
fcis-11537	29	11	and	and	CCONJ
fcis-11537	29	12	experience	experience	NOUN
fcis-11537	29	13	are	be	AUX
fcis-11537	29	14	labor	labor	NOUN
fcis-11537	29	15	-	-	PUNCT
fcis-11537	29	16	intensive	intensive	ADJ
fcis-11537	29	17	.	.	PUNCT
fcis-11537	30	1	and	and	CCONJ
fcis-11537	30	2	it	it	PRON
fcis-11537	30	3	is	be	AUX
fcis-11537	30	4	also	also	ADV
fcis-11537	30	5	less	less	ADV
fcis-11537	30	6	efficient	efficient	ADJ
fcis-11537	30	7	.	.	PUNCT
fcis-11537	31	1	with	with	ADP
fcis-11537	31	2	the	the	DET
fcis-11537	31	3	promotion	promotion	NOUN
fcis-11537	31	4	of	of	ADP
fcis-11537	31	5	agricultural	agricultural	ADJ
fcis-11537	31	6	intelligence	intelligence	NOUN
fcis-11537	31	7	,	,	PUNCT
fcis-11537	31	8	machine	machine	NOUN
fcis-11537	31	9	learning	learning	NOUN
fcis-11537	31	10	and	and	CCONJ
fcis-11537	31	11	other	other	ADJ
fcis-11537	31	12	technologies	technology	NOUN
fcis-11537	31	13	have	have	AUX
fcis-11537	31	14	been	be	AUX
fcis-11537	31	15	introduced	introduce	VERB
fcis-11537	31	16	into	into	ADP
fcis-11537	31	17	agricultural	agricultural	ADJ
fcis-11537	31	18	production	production	NOUN
fcis-11537	31	19	[	[	X
fcis-11537	31	20	2	2	NUM
fcis-11537	31	21	]	]	PUNCT
fcis-11537	31	22	.	.	PUNCT
fcis-11537	32	1	deep	deep	ADJ
fcis-11537	32	2	learning	learning	NOUN
fcis-11537	32	3	methods	method	NOUN
fcis-11537	32	4	have	have	AUX
fcis-11537	32	5	shown	show	VERB
fcis-11537	32	6	excellent	excellent	ADJ
fcis-11537	32	7	efficiency	efficiency	NOUN
fcis-11537	32	8	in	in	ADP
fcis-11537	32	9	recent	recent	ADJ
fcis-11537	32	10	years	year	NOUN
fcis-11537	32	11	.	.	PUNCT
fcis-11537	33	1	they	they	PRON
fcis-11537	33	2	can	can	AUX
fcis-11537	33	3	process	process	VERB
fcis-11537	33	4	images	image	NOUN
fcis-11537	33	5	to	to	PART
fcis-11537	33	6	achieve	achieve	VERB
fcis-11537	33	7	reasonable	reasonable	ADJ
fcis-11537	33	8	analysis	analysis	NOUN
fcis-11537	33	9	results	result	NOUN
fcis-11537	33	10	.	.	PUNCT
fcis-11537	34	1	especially	especially	ADV
fcis-11537	34	2	,	,	PUNCT
fcis-11537	34	3	deep	deep	ADJ
fcis-11537	34	4	and	and	CCONJ
fcis-11537	34	5	large	large	ADJ
fcis-11537	34	6	neural	neural	ADJ
fcis-11537	34	7	networks	network	NOUN
fcis-11537	34	8	have	have	VERB
fcis-11537	34	9	great	great	ADJ
fcis-11537	34	10	learning	learning	NOUN
fcis-11537	34	11	abilities	ability	NOUN
fcis-11537	34	12	[	[	X
fcis-11537	34	13	3	3	NUM
fcis-11537	34	14	]	]	PUNCT
fcis-11537	34	15	.	.	PUNCT
fcis-11537	35	1	but	but	CCONJ
fcis-11537	35	2	their	their	PRON
fcis-11537	35	3	number	number	NOUN
fcis-11537	35	4	of	of	ADP
fcis-11537	35	5	parameters	parameter	NOUN
fcis-11537	35	6	makes	make	VERB
fcis-11537	35	7	calculation	calculation	NOUN
fcis-11537	35	8	difficult	difficult	ADJ
fcis-11537	35	9	.	.	PUNCT
fcis-11537	36	1	the	the	DET
fcis-11537	36	2	calculation	calculation	NOUN
fcis-11537	36	3	speed	speed	NOUN
fcis-11537	36	4	of	of	ADP
fcis-11537	36	5	the	the	DET
fcis-11537	36	6	model	model	NOUN
fcis-11537	36	7	is	be	AUX
fcis-11537	36	8	slow	slow	ADJ
fcis-11537	36	9	.	.	PUNCT
fcis-11537	37	1	realtime	realtime	VERB
fcis-11537	37	2	analysis	analysis	NOUN
fcis-11537	37	3	can	can	AUX
fcis-11537	37	4	not	not	PART
fcis-11537	37	5	be	be	AUX
fcis-11537	37	6	satisfied	satisfied	ADJ
fcis-11537	37	7	in	in	ADP
fcis-11537	37	8	production	production	NOUN
fcis-11537	37	9	.	.	PUNCT
fcis-11537	38	1	lightweight	lightweight	ADJ
fcis-11537	38	2	models	model	NOUN
fcis-11537	38	3	are	be	AUX
fcis-11537	38	4	much	much	ADV
fcis-11537	38	5	faster	fast	ADJ
fcis-11537	38	6	to	to	PART
fcis-11537	38	7	analyze	analyze	VERB
fcis-11537	38	8	[	[	X
fcis-11537	38	9	4	4	NUM
fcis-11537	38	10	]	]	PUNCT
fcis-11537	38	11	.	.	PUNCT
fcis-11537	39	1	however	however	ADV
fcis-11537	39	2	,	,	PUNCT
fcis-11537	39	3	it	it	PRON
fcis-11537	39	4	is	be	AUX
fcis-11537	39	5	difficult	difficult	ADJ
fcis-11537	39	6	for	for	SCONJ
fcis-11537	39	7	lightweight	lightweight	ADJ
fcis-11537	39	8	models	model	NOUN
fcis-11537	39	9	to	to	PART
fcis-11537	39	10	achieve	achieve	VERB
fcis-11537	39	11	high	high	ADJ
fcis-11537	39	12	recognition	recognition	NOUN
fcis-11537	39	13	accuracy	accuracy	NOUN
fcis-11537	39	14	directly	directly	ADV
fcis-11537	39	15	.	.	PUNCT
fcis-11537	40	1	they	they	PRON
fcis-11537	40	2	need	need	VERB
fcis-11537	40	3	knowledge	knowledge	NOUN
fcis-11537	40	4	base	base	NOUN
fcis-11537	40	5	during	during	ADP
fcis-11537	40	6	training	training	NOUN
fcis-11537	40	7	.	.	PUNCT
fcis-11537	41	1	the	the	DET
fcis-11537	41	2	parameters	parameter	NOUN
fcis-11537	41	3	are	be	AUX
fcis-11537	41	4	adjusted	adjust	VERB
fcis-11537	41	5	by	by	ADP
fcis-11537	41	6	iterative	iterative	NOUN
fcis-11537	41	7	fitting	fitting	ADJ
fcis-11537	41	8	.	.	PUNCT
fcis-11537	42	1	knowledge	knowledge	NOUN
fcis-11537	42	2	distillation	distillation	NOUN
fcis-11537	42	3	is	be	AUX
fcis-11537	42	4	a	a	DET
fcis-11537	42	5	feasible	feasible	ADJ
fcis-11537	42	6	way	way	NOUN
fcis-11537	42	7	.	.	PUNCT
fcis-11537	43	1	it	it	PRON
fcis-11537	43	2	can	can	AUX
fcis-11537	43	3	make	make	VERB
fcis-11537	43	4	lightweight	lightweight	ADJ
fcis-11537	43	5	models	model	NOUN
fcis-11537	43	6	learn	learn	VERB
fcis-11537	43	7	from	from	ADP
fcis-11537	43	8	larger	large	ADJ
fcis-11537	43	9	models	model	NOUN
fcis-11537	43	10	.	.	PUNCT
fcis-11537	44	1	the	the	DET
fcis-11537	44	2	results	result	NOUN
fcis-11537	44	3	are	be	AUX
fcis-11537	44	4	usually	usually	ADV
fcis-11537	44	5	better	well	ADJ
fcis-11537	44	6	than	than	ADP
fcis-11537	44	7	independent	independent	ADJ
fcis-11537	44	8	study	study	NOUN
fcis-11537	44	9	.	.	PUNCT
fcis-11537	45	1	therefore	therefore	ADV
fcis-11537	45	2	,	,	PUNCT
fcis-11537	45	3	a	a	DET
fcis-11537	45	4	rich	rich	ADJ
fcis-11537	45	5	knowledge	knowledge	NOUN
fcis-11537	45	6	base	base	NOUN
fcis-11537	45	7	and	and	CCONJ
fcis-11537	45	8	an	an	DET
fcis-11537	45	9	effective	effective	ADJ
fcis-11537	45	10	distillation	distillation	NOUN
fcis-11537	45	11	method	method	NOUN
fcis-11537	45	12	are	be	AUX
fcis-11537	45	13	necessary	necessary	ADJ
fcis-11537	45	14	elements	element	NOUN
fcis-11537	45	15	.	.	PUNCT
fcis-11537	46	1	this	this	PRON
fcis-11537	46	2	is	be	AUX
fcis-11537	46	3	also	also	ADV
fcis-11537	46	4	a	a	DET
fcis-11537	46	5	research	research	NOUN
fcis-11537	46	6	direction	direction	NOUN
fcis-11537	46	7	in	in	ADP
fcis-11537	46	8	current	current	ADJ
fcis-11537	46	9	production	production	NOUN
fcis-11537	46	10	and	and	CCONJ
fcis-11537	46	11	application	application	NOUN
fcis-11537	46	12	[	[	X
fcis-11537	46	13	5	5	NUM
fcis-11537	46	14	]	]	PUNCT
fcis-11537	46	15	.	.	PUNCT
fcis-11537	47	1	2	2	X
fcis-11537	47	2	.	.	X
fcis-11537	47	3	related	relate	VERB
fcis-11537	47	4	work	work	NOUN
fcis-11537	47	5	in	in	ADP
fcis-11537	47	6	recent	recent	ADJ
fcis-11537	47	7	years	year	NOUN
fcis-11537	47	8	,	,	PUNCT
fcis-11537	47	9	researchers	researcher	NOUN
fcis-11537	47	10	have	have	AUX
fcis-11537	47	11	carried	carry	VERB
fcis-11537	47	12	out	out	ADP
fcis-11537	47	13	a	a	DET
fcis-11537	47	14	series	series	NOUN
fcis-11537	47	15	of	of	ADP
fcis-11537	47	16	work	work	NOUN
fcis-11537	47	17	on	on	ADP
fcis-11537	47	18	crop	crop	NOUN
fcis-11537	47	19	leaf	leaf	NOUN
fcis-11537	47	20	pests	pest	NOUN
fcis-11537	47	21	and	and	CCONJ
fcis-11537	47	22	diseases	disease	NOUN
fcis-11537	47	23	.	.	PUNCT
fcis-11537	48	1	y	y	PROPN
fcis-11537	48	2	sun	sun	PROPN
fcis-11537	48	3	proposed	propose	VERB
fcis-11537	48	4	a	a	DET
fcis-11537	48	5	new	new	ADJ
fcis-11537	48	6	algorithm	algorithm	NOUN
fcis-11537	48	7	combining	combine	VERB
fcis-11537	48	8	slic	slic	NOUN
fcis-11537	48	9	(	(	PUNCT
fcis-11537	48	10	simple	simple	ADJ
fcis-11537	48	11	linear	linear	ADJ
fcis-11537	48	12	iterative	iterative	NOUN
fcis-11537	48	13	cluster	cluster	NOUN
fcis-11537	48	14	)	)	PUNCT
fcis-11537	48	15	with	with	ADP
fcis-11537	48	16	svm	svm	PROPN
fcis-11537	48	17	(	(	PUNCT
fcis-11537	48	18	support	support	NOUN
fcis-11537	48	19	vector	vector	NOUN
fcis-11537	48	20	machine	machine	NOUN
fcis-11537	48	21	)	)	PUNCT
fcis-11537	49	1	[	[	X
fcis-11537	49	2	6	6	NUM
fcis-11537	49	3	]	]	PUNCT
fcis-11537	49	4	.	.	PUNCT
fcis-11537	50	1	the	the	DET
fcis-11537	50	2	accuracy	accuracy	NOUN
fcis-11537	50	3	and	and	CCONJ
fcis-11537	50	4	f	f	X
fcis-11537	50	5	-	-	PUNCT
fcis-11537	50	6	value	value	NOUN
fcis-11537	50	7	are	be	AUX
fcis-11537	50	8	96.8	96.8	NUM
fcis-11537	50	9	%	%	NOUN
fcis-11537	50	10	and	and	CCONJ
fcis-11537	50	11	97.7	97.7	NUM
fcis-11537	50	12	%	%	NOUN
fcis-11537	50	13	respectively	respectively	ADV
fcis-11537	50	14	.	.	PUNCT
fcis-11537	51	1	jaaa	jaaa	PROPN
fcis-11537	51	2	basavaiah	basavaiah	PROPN
fcis-11537	51	3	used	use	VERB
fcis-11537	51	4	random	random	ADJ
fcis-11537	51	5	forest	forest	NOUN
fcis-11537	51	6	and	and	CCONJ
fcis-11537	51	7	decision	decision	NOUN
fcis-11537	51	8	tree	tree	NOUN
fcis-11537	51	9	classification	classification	NOUN
fcis-11537	51	10	algorithms	algorithm	NOUN
fcis-11537	51	11	to	to	PART
fcis-11537	51	12	classify	classify	VERB
fcis-11537	51	13	leaf	leaf	NOUN
fcis-11537	51	14	disease	disease	NOUN
fcis-11537	51	15	[	[	X
fcis-11537	51	16	7	7	NUM
fcis-11537	51	17	]	]	PUNCT
fcis-11537	51	18	.	.	PUNCT
fcis-11537	52	1	the	the	DET
fcis-11537	52	2	classification	classification	NOUN
fcis-11537	52	3	accuracy	accuracy	NOUN
fcis-11537	52	4	is	be	AUX
fcis-11537	52	5	90	90	NUM
fcis-11537	52	6	%	%	NOUN
fcis-11537	52	7	for	for	ADP
fcis-11537	52	8	decision	decision	NOUN
fcis-11537	52	9	tree	tree	NOUN
fcis-11537	52	10	classifier	classifier	NOUN
fcis-11537	52	11	and	and	CCONJ
fcis-11537	52	12	94	94	NUM
fcis-11537	52	13	%	%	NOUN
fcis-11537	52	14	for	for	ADP
fcis-11537	52	15	random	random	ADJ
fcis-11537	52	16	forest	forest	NOUN
fcis-11537	52	17	classifier	classifier	NOUN
fcis-11537	52	18	respectively	respectively	ADV
fcis-11537	52	19	.	.	PUNCT
fcis-11537	53	1	j	j	PROPN
fcis-11537	53	2	suto	suto	PROPN
fcis-11537	53	3	found	find	VERB
fcis-11537	53	4	an	an	DET
fcis-11537	53	5	interesting	interesting	ADJ
fcis-11537	53	6	deficiency	deficiency	NOUN
fcis-11537	53	7	and	and	CCONJ
fcis-11537	53	8	a	a	DET
fcis-11537	53	9	key	key	ADJ
fcis-11537	53	10	difference	difference	NOUN
fcis-11537	53	11	between	between	ADP
fcis-11537	53	12	studies	study	NOUN
fcis-11537	53	13	[	[	X
fcis-11537	53	14	8	8	NUM
fcis-11537	53	15	]	]	PUNCT
fcis-11537	53	16	.	.	PUNCT
fcis-11537	54	1	this	this	DET
fcis-11537	54	2	work	work	NOUN
fcis-11537	54	3	offered	offer	VERB
fcis-11537	54	4	an	an	DET
fcis-11537	54	5	overall	overall	ADJ
fcis-11537	54	6	review	review	NOUN
fcis-11537	54	7	about	about	ADP
fcis-11537	54	8	the	the	DET
fcis-11537	54	9	efficient	efficient	ADJ
fcis-11537	54	10	.	.	PUNCT
fcis-11537	55	1	in	in	ADP
fcis-11537	55	2	2020	2020	NUM
fcis-11537	55	3	,	,	PUNCT
fcis-11537	55	4	a	a	DET
fcis-11537	55	5	nigam	nigam	NOUN
fcis-11537	55	6	used	use	VERB
fcis-11537	55	7	the	the	DET
fcis-11537	55	8	pca	pca	PROPN
fcis-11537	55	9	algorithm	algorithm	NOUN
fcis-11537	55	10	to	to	PART
fcis-11537	55	11	extract	extract	VERB
fcis-11537	55	12	specific	specific	ADJ
fcis-11537	55	13	features	feature	NOUN
fcis-11537	55	14	[	[	X
fcis-11537	55	15	9	9	NUM
fcis-11537	55	16	]	]	PUNCT
fcis-11537	55	17	.	.	PUNCT
fcis-11537	56	1	moreover	moreover	ADV
fcis-11537	56	2	,	,	PUNCT
fcis-11537	56	3	the	the	DET
fcis-11537	56	4	feature	feature	NOUN
fcis-11537	56	5	extraction	extraction	NOUN
fcis-11537	56	6	and	and	CCONJ
fcis-11537	56	7	bfo	bfo	PROPN
fcis-11537	56	8	-	-	PUNCT
fcis-11537	56	9	dnn	dnn	PROPN
fcis-11537	56	10	method	method	NOUN
fcis-11537	56	11	was	be	AUX
fcis-11537	56	12	proposed	propose	VERB
fcis-11537	56	13	.	.	PUNCT
fcis-11537	57	1	and	and	CCONJ
fcis-11537	57	2	it	it	PRON
fcis-11537	57	3	achieved	achieve	VERB
fcis-11537	57	4	good	good	ADJ
fcis-11537	57	5	results	result	NOUN
fcis-11537	57	6	.	.	PUNCT
fcis-11537	58	1	in	in	ADP
fcis-11537	58	2	2021	2021	NUM
fcis-11537	58	3	,	,	PUNCT
fcis-11537	58	4	z	z	PROPN
fcis-11537	58	5	jiang	jiang	PROPN
fcis-11537	58	6	improved	improve	VERB
fcis-11537	58	7	the	the	DET
fcis-11537	58	8	visual	visual	ADJ
fcis-11537	58	9	geometry	geometry	NOUN
fcis-11537	58	10	group	group	NOUN
fcis-11537	58	11	network-16	network-16	PROPN
fcis-11537	58	12	model	model	NOUN
fcis-11537	58	13	based	base	VERB
fcis-11537	58	14	on	on	ADP
fcis-11537	58	15	the	the	DET
fcis-11537	58	16	idea	idea	NOUN
fcis-11537	58	17	of	of	ADP
fcis-11537	58	18	multi	multi	ADJ
fcis-11537	58	19	-	-	ADJ
fcis-11537	58	20	task	task	ADJ
fcis-11537	58	21	learning	learning	NOUN
fcis-11537	58	22	and	and	CCONJ
fcis-11537	58	23	then	then	ADV
fcis-11537	58	24	use	use	VERB
fcis-11537	58	25	the	the	DET
fcis-11537	58	26	pre	pre	ADJ
fcis-11537	58	27	-	-	ADJ
fcis-11537	58	28	training	training	ADJ
fcis-11537	58	29	model	model	NOUN
fcis-11537	58	30	on	on	ADP
fcis-11537	58	31	imagenet	imagenet	NOUN
fcis-11537	58	32	for	for	ADP
fcis-11537	58	33	transfer	transfer	NOUN
fcis-11537	58	34	learning	learning	NOUN
fcis-11537	58	35	and	and	CCONJ
fcis-11537	58	36	alternating	alternate	VERB
fcis-11537	58	37	learning	learn	VERB
fcis-11537	58	38	[	[	X
fcis-11537	58	39	10	10	NUM
fcis-11537	58	40	]	]	PUNCT
fcis-11537	58	41	.	.	PUNCT
fcis-11537	59	1	the	the	DET
fcis-11537	59	2	accuracy	accuracy	NOUN
fcis-11537	59	3	of	of	ADP
fcis-11537	59	4	such	such	ADJ
fcis-11537	59	5	model	model	NOUN
fcis-11537	59	6	is	be	AUX
fcis-11537	59	7	97.22	97.22	NUM
fcis-11537	59	8	%	%	NOUN
fcis-11537	59	9	for	for	ADP
fcis-11537	59	10	rice	rice	NOUN
fcis-11537	59	11	leaf	leaf	NOUN
fcis-11537	59	12	diseases	disease	NOUN
fcis-11537	59	13	and	and	CCONJ
fcis-11537	59	14	98.75	98.75	NUM
fcis-11537	59	15	%	%	NOUN
fcis-11537	59	16	for	for	ADP
fcis-11537	59	17	wheat	wheat	NOUN
fcis-11537	59	18	leaf	leaf	NOUN
fcis-11537	59	19	diseases	disease	NOUN
fcis-11537	59	20	.	.	PUNCT
fcis-11537	60	1	in	in	ADP
fcis-11537	60	2	the	the	DET
fcis-11537	60	3	same	same	ADJ
fcis-11537	60	4	year	year	NOUN
fcis-11537	60	5	,	,	PUNCT
fcis-11537	60	6	sk	sk	PROPN
fcis-11537	60	7	noon	noon	NOUN
fcis-11537	60	8	proposed	propose	VERB
fcis-11537	60	9	a	a	DET
fcis-11537	60	10	simple	simple	ADJ
fcis-11537	60	11	yet	yet	CCONJ
fcis-11537	60	12	efficient	efficient	ADJ
fcis-11537	60	13	deep	deep	ADJ
fcis-11537	60	14	learning	learning	NOUN
fcis-11537	60	15	-	-	PUNCT
fcis-11537	60	16	based	base	VERB
fcis-11537	60	17	framework	framework	NOUN
fcis-11537	60	18	to	to	PART
fcis-11537	60	19	recognize	recognize	VERB
fcis-11537	60	20	cotton	cotton	NOUN
fcis-11537	60	21	leaf	leaf	NOUN
fcis-11537	60	22	diseases	disease	NOUN
fcis-11537	60	23	[	[	X
fcis-11537	60	24	11	11	NUM
fcis-11537	60	25	]	]	PUNCT
fcis-11537	60	26	.	.	PUNCT
fcis-11537	61	1	the	the	DET
fcis-11537	61	2	proposed	propose	VERB
fcis-11537	61	3	model	model	NOUN
fcis-11537	61	4	is	be	AUX
fcis-11537	61	5	capable	capable	ADJ
fcis-11537	61	6	of	of	ADP
fcis-11537	61	7	achieving	achieve	VERB
fcis-11537	61	8	the	the	DET
fcis-11537	61	9	near	near	ADJ
fcis-11537	61	10	ideal	ideal	ADJ
fcis-11537	61	11	accuracy	accuracy	NOUN
fcis-11537	61	12	with	with	ADP
fcis-11537	61	13	early	early	ADJ
fcis-11537	61	14	convergence	convergence	NOUN
fcis-11537	61	15	to	to	PART
fcis-11537	61	16	save	save	VERB
fcis-11537	61	17	computational	computational	ADJ
fcis-11537	61	18	cost	cost	NOUN
fcis-11537	61	19	of	of	ADP
fcis-11537	61	20	training	training	NOUN
fcis-11537	61	21	.	.	PUNCT
fcis-11537	62	1	w	w	PROPN
fcis-11537	62	2	zeng	zeng	PROPN
fcis-11537	62	3	proposed	propose	VERB
fcis-11537	62	4	a	a	DET
fcis-11537	62	5	lightweight	lightweight	ADJ
fcis-11537	62	6	dense	dense	ADJ
fcis-11537	62	7	-	-	PUNCT
fcis-11537	62	8	scale	scale	NOUN
fcis-11537	62	9	network	network	NOUN
fcis-11537	62	10	for	for	ADP
fcis-11537	62	11	real	real	ADJ
fcis-11537	62	12	-	-	PUNCT
fcis-11537	62	13	world	world	NOUN
fcis-11537	62	14	corn	corn	NOUN
fcis-11537	62	15	leaf	leaf	NOUN
fcis-11537	62	16	disease	disease	NOUN
fcis-11537	62	17	image	image	NOUN
fcis-11537	62	18	identification	identification	NOUN
fcis-11537	62	19	and	and	CCONJ
fcis-11537	62	20	a	a	DET
fcis-11537	62	21	new	new	ADJ
fcis-11537	62	22	loss	loss	NOUN
fcis-11537	62	23	function	function	NOUN
fcis-11537	62	24	[	[	X
fcis-11537	62	25	12	12	NUM
fcis-11537	62	26	]	]	PUNCT
fcis-11537	62	27	.	.	PUNCT
fcis-11537	63	1	experimental	experimental	ADJ
fcis-11537	63	2	results	result	NOUN
fcis-11537	63	3	proved	prove	VERB
fcis-11537	63	4	that	that	SCONJ
fcis-11537	63	5	the	the	DET
fcis-11537	63	6	accuracy	accuracy	NOUN
fcis-11537	63	7	of	of	ADP
fcis-11537	63	8	the	the	DET
fcis-11537	63	9	optimized	optimize	VERB
fcis-11537	63	10	model	model	NOUN
fcis-11537	63	11	on	on	ADP
fcis-11537	63	12	the	the	DET
fcis-11537	63	13	test	test	NOUN
fcis-11537	63	14	data	datum	NOUN
fcis-11537	63	15	set	set	VERB
fcis-11537	63	16	reaches	reach	VERB
fcis-11537	63	17	95.4	95.4	NUM
fcis-11537	63	18	%	%	NOUN
fcis-11537	63	19	.	.	PUNCT
fcis-11537	64	1	in	in	ADP
fcis-11537	64	2	2022	2022	NUM
fcis-11537	64	3	,	,	PUNCT
fcis-11537	64	4	zhen	zhen	PROPN
fcis-11537	64	5	wang	wang	PROPN
fcis-11537	64	6	proposed	propose	VERB
fcis-11537	64	7	a	a	DET
fcis-11537	64	8	novel	novel	ADJ
fcis-11537	64	9	deep	deep	ADJ
fcis-11537	64	10	neural	neural	ADJ
fcis-11537	64	11	network	network	NOUN
fcis-11537	64	12	structure	structure	NOUN
fcis-11537	64	13	named	name	VERB
fcis-11537	64	14	as	as	ADP
fcis-11537	64	15	mpf	mpf	PROPN
fcis-11537	64	16	-	-	PUNCT
fcis-11537	64	17	net	net	NOUN
fcis-11537	64	18	for	for	ADP
fcis-11537	64	19	weed	weed	NOUN
fcis-11537	64	20	species	species	NOUN
fcis-11537	64	21	identification	identification	NOUN
fcis-11537	64	22	[	[	X
fcis-11537	64	23	13	13	NUM
fcis-11537	64	24	]	]	PUNCT
fcis-11537	64	25	.	.	PUNCT
fcis-11537	65	1	the	the	DET
fcis-11537	65	2	calculation	calculation	NOUN
fcis-11537	65	3	speed	speed	NOUN
fcis-11537	65	4	of	of	ADP
fcis-11537	65	5	this	this	DET
fcis-11537	65	6	model	model	NOUN
fcis-11537	65	7	is	be	AUX
fcis-11537	65	8	fast	fast	ADJ
fcis-11537	65	9	and	and	CCONJ
fcis-11537	65	10	the	the	DET
fcis-11537	65	11	accuracy	accuracy	NOUN
fcis-11537	65	12	is	be	AUX
fcis-11537	65	13	high	high	ADJ
fcis-11537	65	14	.	.	PUNCT
fcis-11537	66	1	among	among	ADP
fcis-11537	66	2	these	these	DET
fcis-11537	66	3	methods	method	NOUN
fcis-11537	66	4	,	,	PUNCT
fcis-11537	66	5	the	the	DET
fcis-11537	66	6	structure	structure	NOUN
fcis-11537	66	7	of	of	ADP
fcis-11537	66	8	some	some	DET
fcis-11537	66	9	models	model	NOUN
fcis-11537	66	10	is	be	AUX
fcis-11537	66	11	complicated	complicated	ADJ
fcis-11537	66	12	.	.	PUNCT
fcis-11537	67	1	their	their	PRON
fcis-11537	67	2	calculation	calculation	NOUN
fcis-11537	67	3	speed	speed	NOUN
fcis-11537	67	4	can	can	AUX
fcis-11537	67	5	not	not	PART
fcis-11537	67	6	meet	meet	VERB
fcis-11537	67	7	the	the	DET
fcis-11537	67	8	real	real	ADJ
fcis-11537	67	9	-	-	PUNCT
fcis-11537	67	10	time	time	NOUN
fcis-11537	67	11	requirement	requirement	NOUN
fcis-11537	67	12	in	in	ADP
fcis-11537	67	13	production	production	NOUN
fcis-11537	67	14	.	.	PUNCT
fcis-11537	68	1	lightweight	lightweight	ADJ
fcis-11537	68	2	models	model	NOUN
fcis-11537	68	3	are	be	AUX
fcis-11537	68	4	difficult	difficult	ADJ
fcis-11537	68	5	to	to	PART
fcis-11537	68	6	achieve	achieve	VERB
fcis-11537	68	7	high	high	ADJ
fcis-11537	68	8	accuracy	accuracy	NOUN
fcis-11537	68	9	.	.	PUNCT
fcis-11537	69	1	after	after	ADP
fcis-11537	69	2	a	a	DET
fcis-11537	69	3	comprehensive	comprehensive	ADJ
fcis-11537	69	4	consideration	consideration	NOUN
fcis-11537	69	5	,	,	PUNCT
fcis-11537	69	6	knowledge	knowledge	NOUN
fcis-11537	69	7	distillation	distillation	NOUN
fcis-11537	69	8	is	be	AUX
fcis-11537	69	9	used	use	VERB
fcis-11537	69	10	to	to	PART
fcis-11537	69	11	train	train	VERB
fcis-11537	69	12	a	a	DET
fcis-11537	69	13	lightweight	lightweight	ADJ
fcis-11537	69	14	model	model	NOUN
fcis-11537	69	15	in	in	ADP
fcis-11537	69	16	this	this	DET
fcis-11537	69	17	research	research	NOUN
fcis-11537	69	18	.	.	PUNCT
fcis-11537	70	1	the	the	DET
fcis-11537	70	2	generated	generate	VERB
fcis-11537	70	3	model	model	NOUN
fcis-11537	70	4	has	have	VERB
fcis-11537	70	5	high	high	ADJ
fcis-11537	70	6	calculation	calculation	NOUN
fcis-11537	70	7	speed	speed	NOUN
fcis-11537	70	8	and	and	CCONJ
fcis-11537	70	9	high	high	ADJ
fcis-11537	70	10	accuracy	accuracy	NOUN
fcis-11537	70	11	.	.	PUNCT
fcis-11537	71	1	16	16	NUM
fcis-11537	71	2	3	3	NUM
fcis-11537	71	3	.	.	PUNCT
fcis-11537	71	4	method	method	PROPN
fcis-11537	71	5	3.1	3.1	NUM
fcis-11537	71	6	.	.	PUNCT
fcis-11537	72	1	data	datum	NOUN
fcis-11537	72	2	preprocessing	preprocesse	VERB
fcis-11537	72	3	the	the	DET
fcis-11537	72	4	experimental	experimental	ADJ
fcis-11537	72	5	object	object	NOUN
fcis-11537	72	6	of	of	ADP
fcis-11537	72	7	this	this	DET
fcis-11537	72	8	research	research	NOUN
fcis-11537	72	9	is	be	AUX
fcis-11537	72	10	coffee	coffee	NOUN
fcis-11537	72	11	leaves	leave	NOUN
fcis-11537	72	12	.	.	PUNCT
fcis-11537	73	1	there	there	PRON
fcis-11537	73	2	are	be	VERB
fcis-11537	73	3	5	5	NUM
fcis-11537	73	4	kinds	kind	NOUN
fcis-11537	73	5	of	of	ADP
fcis-11537	73	6	pests	pest	NOUN
fcis-11537	73	7	and	and	CCONJ
fcis-11537	73	8	diseases	disease	NOUN
fcis-11537	73	9	on	on	ADP
fcis-11537	73	10	coffee	coffee	NOUN
fcis-11537	73	11	leaves	leave	NOUN
fcis-11537	73	12	.	.	PUNCT
fcis-11537	74	1	they	they	PRON
fcis-11537	74	2	are	be	AUX
fcis-11537	74	3	respectively	respectively	ADV
fcis-11537	74	4	healthy	healthy	ADJ
fcis-11537	74	5	,	,	PUNCT
fcis-11537	74	6	browned	brown	VERB
fcis-11537	74	7	,	,	PUNCT
fcis-11537	74	8	withered	withered	ADJ
fcis-11537	74	9	,	,	PUNCT
fcis-11537	74	10	perforated	perforated	ADJ
fcis-11537	74	11	and	and	CCONJ
fcis-11537	74	12	spotted	spot	VERB
fcis-11537	74	13	.	.	PUNCT
fcis-11537	75	1	the	the	DET
fcis-11537	75	2	number	number	NOUN
fcis-11537	75	3	of	of	ADP
fcis-11537	75	4	5	5	NUM
fcis-11537	75	5	kinds	kind	NOUN
fcis-11537	75	6	of	of	ADP
fcis-11537	75	7	images	image	NOUN
fcis-11537	75	8	are	be	AUX
fcis-11537	75	9	327	327	NUM
fcis-11537	75	10	,	,	PUNCT
fcis-11537	75	11	286	286	NUM
fcis-11537	75	12	,	,	PUNCT
fcis-11537	75	13	295	295	NUM
fcis-11537	75	14	,	,	PUNCT
fcis-11537	75	15	351	351	NUM
fcis-11537	75	16	and	and	CCONJ
fcis-11537	75	17	332	332	NUM
fcis-11537	75	18	respectively	respectively	ADV
fcis-11537	75	19	.	.	PUNCT
fcis-11537	76	1	as	as	SCONJ
fcis-11537	76	2	shown	show	VERB
fcis-11537	76	3	in	in	ADP
fcis-11537	76	4	figure	figure	NOUN
fcis-11537	76	5	1	1	NUM
fcis-11537	76	6	.	.	PUNCT
fcis-11537	76	7	figure	figure	NOUN
fcis-11537	76	8	1	1	NUM
fcis-11537	76	9	.	.	NUM
fcis-11537	77	1	images	image	NOUN
fcis-11537	77	2	of	of	ADP
fcis-11537	77	3	coffee	coffee	NOUN
fcis-11537	77	4	leaf	leaf	NOUN
fcis-11537	77	5	there	there	PRON
fcis-11537	77	6	may	may	AUX
fcis-11537	77	7	be	be	AUX
fcis-11537	77	8	noise	noise	NOUN
fcis-11537	77	9	in	in	ADP
fcis-11537	77	10	the	the	DET
fcis-11537	77	11	original	original	ADJ
fcis-11537	77	12	images	image	NOUN
fcis-11537	77	13	.	.	PUNCT
fcis-11537	78	1	noise	noise	NOUN
fcis-11537	78	2	will	will	AUX
fcis-11537	78	3	affect	affect	VERB
fcis-11537	78	4	the	the	DET
fcis-11537	78	5	change	change	NOUN
fcis-11537	78	6	of	of	ADP
fcis-11537	78	7	image	image	NOUN
fcis-11537	78	8	gray	gray	ADJ
fcis-11537	78	9	value	value	NOUN
fcis-11537	78	10	and	and	CCONJ
fcis-11537	78	11	interfere	interfere	VERB
fcis-11537	78	12	with	with	ADP
fcis-11537	78	13	the	the	DET
fcis-11537	78	14	display	display	NOUN
fcis-11537	78	15	of	of	ADP
fcis-11537	78	16	detail	detail	NOUN
fcis-11537	78	17	features	feature	NOUN
fcis-11537	78	18	.	.	PUNCT
fcis-11537	79	1	in	in	ADP
fcis-11537	79	2	the	the	DET
fcis-11537	79	3	preprocessing	preprocessing	NOUN
fcis-11537	79	4	stage	stage	NOUN
fcis-11537	79	5	,	,	PUNCT
fcis-11537	79	6	the	the	DET
fcis-11537	79	7	mean	mean	ADJ
fcis-11537	79	8	filtering	filtering	NOUN
fcis-11537	79	9	method	method	NOUN
fcis-11537	79	10	is	be	AUX
fcis-11537	79	11	used	use	VERB
fcis-11537	79	12	to	to	PART
fcis-11537	79	13	suppress	suppress	VERB
fcis-11537	79	14	the	the	DET
fcis-11537	79	15	noise	noise	NOUN
fcis-11537	79	16	on	on	ADP
fcis-11537	79	17	the	the	DET
fcis-11537	79	18	image	image	NOUN
fcis-11537	79	19	[	[	X
fcis-11537	79	20	14	14	NUM
fcis-11537	79	21	]	]	PUNCT
fcis-11537	79	22	.	.	PUNCT
fcis-11537	80	1	mean	mean	VERB
fcis-11537	80	2	filtering	filtering	NOUN
fcis-11537	80	3	replaces	replace	VERB
fcis-11537	80	4	the	the	DET
fcis-11537	80	5	value	value	NOUN
fcis-11537	80	6	of	of	ADP
fcis-11537	80	7	the	the	DET
fcis-11537	80	8	center	center	NOUN
fcis-11537	80	9	pixel	pixel	VERB
fcis-11537	80	10	with	with	ADP
fcis-11537	80	11	the	the	DET
fcis-11537	80	12	mean	mean	NOUN
fcis-11537	80	13	of	of	ADP
fcis-11537	80	14	all	all	DET
fcis-11537	80	15	pixels	pixel	NOUN
fcis-11537	80	16	in	in	ADP
fcis-11537	80	17	a	a	DET
fcis-11537	80	18	fixed	fix	VERB
fcis-11537	80	19	window	window	NOUN
fcis-11537	80	20	.	.	PUNCT
fcis-11537	81	1	figure	figure	NOUN
fcis-11537	81	2	2(a	2(a	NUM
fcis-11537	81	3	)	)	PUNCT
fcis-11537	81	4	and	and	CCONJ
fcis-11537	81	5	figure	figure	VERB
fcis-11537	81	6	2(b	2(b	NUM
fcis-11537	81	7	)	)	PUNCT
fcis-11537	81	8	respectively	respectively	ADV
fcis-11537	81	9	show	show	VERB
fcis-11537	81	10	the	the	DET
fcis-11537	81	11	histogram	histogram	NOUN
fcis-11537	81	12	distribution	distribution	NOUN
fcis-11537	81	13	of	of	ADP
fcis-11537	81	14	the	the	DET
fcis-11537	81	15	image	image	NOUN
fcis-11537	81	16	before	before	ADP
fcis-11537	81	17	and	and	CCONJ
fcis-11537	81	18	after	after	ADP
fcis-11537	81	19	filtering	filter	VERB
fcis-11537	81	20	[	[	X
fcis-11537	81	21	15	15	NUM
fcis-11537	81	22	]	]	PUNCT
fcis-11537	81	23	.	.	PUNCT
fcis-11537	82	1	after	after	ADP
fcis-11537	82	2	filtering	filter	VERB
fcis-11537	82	3	,	,	PUNCT
fcis-11537	82	4	the	the	DET
fcis-11537	82	5	noise	noise	NOUN
fcis-11537	82	6	of	of	ADP
fcis-11537	82	7	the	the	DET
fcis-11537	82	8	image	image	NOUN
fcis-11537	82	9	is	be	AUX
fcis-11537	82	10	reduced	reduce	VERB
fcis-11537	82	11	and	and	CCONJ
fcis-11537	82	12	the	the	DET
fcis-11537	82	13	gray	gray	ADJ
fcis-11537	82	14	value	value	NOUN
fcis-11537	82	15	is	be	AUX
fcis-11537	82	16	stable	stable	ADJ
fcis-11537	82	17	.	.	PUNCT
fcis-11537	83	1	(	(	PUNCT
fcis-11537	83	2	a	a	X
fcis-11537	83	3	)	)	PUNCT
fcis-11537	83	4	(	(	PUNCT
fcis-11537	83	5	b	b	X
fcis-11537	83	6	)	)	PUNCT
fcis-11537	83	7	figure	figure	NOUN
fcis-11537	83	8	2	2	NUM
fcis-11537	83	9	.	.	PUNCT
fcis-11537	83	10	histogram	histogram	NOUN
fcis-11537	83	11	distribution	distribution	NOUN
fcis-11537	83	12	of	of	ADP
fcis-11537	83	13	the	the	DET
fcis-11537	83	14	image	image	NOUN
fcis-11537	83	15	before	before	ADP
fcis-11537	83	16	and	and	CCONJ
fcis-11537	83	17	after	after	ADP
fcis-11537	83	18	filtering	filter	VERB
fcis-11537	83	19	resize	resize	VERB
fcis-11537	83	20	all	all	DET
fcis-11537	83	21	images	image	NOUN
fcis-11537	83	22	to	to	ADP
fcis-11537	83	23	64×64	64×64	NUM
fcis-11537	83	24	.	.	PUNCT
fcis-11537	84	1	the	the	DET
fcis-11537	84	2	input	input	NOUN
fcis-11537	84	3	image	image	NOUN
fcis-11537	84	4	contains	contain	VERB
fcis-11537	84	5	three	three	NUM
fcis-11537	84	6	color	color	NOUN
fcis-11537	84	7	channels	channel	NOUN
fcis-11537	84	8	such	such	ADJ
fcis-11537	84	9	as	as	ADP
fcis-11537	84	10	r	r	NOUN
fcis-11537	84	11	,	,	PUNCT
fcis-11537	84	12	g	g	NOUN
fcis-11537	84	13	,	,	PUNCT
fcis-11537	84	14	and	and	CCONJ
fcis-11537	84	15	b.	b.	PROPN
fcis-11537	84	16	output	output	NOUN
fcis-11537	84	17	category	category	NOUN
fcis-11537	84	18	for	for	ADP
fcis-11537	84	19	each	each	DET
fcis-11537	84	20	image	image	NOUN
fcis-11537	84	21	.	.	PUNCT
fcis-11537	85	1	use	use	VERB
fcis-11537	85	2	one	one	NUM
fcis-11537	85	3	-	-	PUNCT
fcis-11537	85	4	hot	hot	ADJ
fcis-11537	85	5	to	to	PART
fcis-11537	85	6	encode	encode	VERB
fcis-11537	85	7	the	the	DET
fcis-11537	85	8	category	category	NOUN
fcis-11537	85	9	of	of	ADP
fcis-11537	85	10	each	each	DET
fcis-11537	85	11	image	image	NOUN
fcis-11537	85	12	.	.	PUNCT
fcis-11537	86	1	3.2	3.2	NUM
fcis-11537	86	2	.	.	PUNCT
fcis-11537	86	3	principle	principle	NOUN
fcis-11537	86	4	the	the	DET
fcis-11537	86	5	method	method	NOUN
fcis-11537	86	6	proposed	propose	VERB
fcis-11537	86	7	in	in	ADP
fcis-11537	86	8	this	this	DET
fcis-11537	86	9	research	research	NOUN
fcis-11537	86	10	is	be	AUX
fcis-11537	86	11	to	to	PART
fcis-11537	86	12	train	train	VERB
fcis-11537	86	13	and	and	CCONJ
fcis-11537	86	14	obtain	obtain	VERB
fcis-11537	86	15	a	a	DET
fcis-11537	86	16	large	large	ADJ
fcis-11537	86	17	network	network	NOUN
fcis-11537	86	18	with	with	ADP
fcis-11537	86	19	excellent	excellent	ADJ
fcis-11537	86	20	recognition	recognition	NOUN
fcis-11537	86	21	effect	effect	NOUN
fcis-11537	86	22	by	by	ADP
fcis-11537	86	23	transfer	transfer	NOUN
fcis-11537	86	24	learning	learn	VERB
fcis-11537	86	25	firstly	firstly	ADV
fcis-11537	86	26	.	.	PUNCT
fcis-11537	87	1	then	then	ADV
fcis-11537	87	2	,	,	PUNCT
fcis-11537	87	3	design	design	VERB
fcis-11537	87	4	a	a	DET
fcis-11537	87	5	small	small	ADJ
fcis-11537	87	6	network	network	NOUN
fcis-11537	87	7	.	.	PUNCT
fcis-11537	88	1	use	use	VERB
fcis-11537	88	2	knowledge	knowledge	NOUN
fcis-11537	88	3	distillation	distillation	NOUN
fcis-11537	88	4	to	to	PART
fcis-11537	88	5	make	make	VERB
fcis-11537	88	6	the	the	DET
fcis-11537	88	7	small	small	ADJ
fcis-11537	88	8	network	network	NOUN
fcis-11537	88	9	learn	learn	VERB
fcis-11537	88	10	information	information	NOUN
fcis-11537	88	11	extracted	extract	VERB
fcis-11537	88	12	by	by	ADP
fcis-11537	88	13	the	the	DET
fcis-11537	88	14	large	large	ADJ
fcis-11537	88	15	network	network	NOUN
fcis-11537	88	16	.	.	PUNCT
fcis-11537	89	1	finally	finally	ADV
fcis-11537	89	2	,	,	PUNCT
fcis-11537	89	3	a	a	DET
fcis-11537	89	4	lightweight	lightweight	ADJ
fcis-11537	89	5	model	model	NOUN
fcis-11537	89	6	with	with	ADP
fcis-11537	89	7	fast	fast	ADJ
fcis-11537	89	8	computing	computing	NOUN
fcis-11537	89	9	speed	speed	NOUN
fcis-11537	89	10	and	and	CCONJ
fcis-11537	89	11	high	high	ADJ
fcis-11537	89	12	recognition	recognition	NOUN
fcis-11537	89	13	accuracy	accuracy	NOUN
fcis-11537	89	14	is	be	AUX
fcis-11537	89	15	generated	generate	VERB
fcis-11537	89	16	.	.	PUNCT
fcis-11537	90	1	transfer	transfer	NOUN
fcis-11537	90	2	learning	learning	NOUN
fcis-11537	90	3	is	be	AUX
fcis-11537	90	4	a	a	DET
fcis-11537	90	5	machine	machine	NOUN
fcis-11537	90	6	learning	learning	NOUN
fcis-11537	90	7	method	method	NOUN
fcis-11537	90	8	.	.	PUNCT
fcis-11537	91	1	start	start	VERB
fcis-11537	91	2	with	with	ADP
fcis-11537	91	3	the	the	DET
fcis-11537	91	4	model	model	NOUN
fcis-11537	91	5	developed	develop	VERB
fcis-11537	91	6	in	in	ADP
fcis-11537	91	7	task	task	NOUN
fcis-11537	91	8	a.	a.	NOUN
fcis-11537	91	9	develop	develop	VERB
fcis-11537	91	10	the	the	DET
fcis-11537	91	11	model	model	NOUN
fcis-11537	91	12	in	in	ADP
fcis-11537	91	13	task	task	PROPN
fcis-11537	91	14	b	b	PROPN
fcis-11537	91	15	again	again	ADV
fcis-11537	91	16	.	.	PUNCT
fcis-11537	92	1	transfer	transfer	NOUN
fcis-11537	92	2	learning	learning	NOUN
fcis-11537	92	3	can	can	AUX
fcis-11537	92	4	use	use	VERB
fcis-11537	92	5	knowledge	knowledge	NOUN
fcis-11537	92	6	from	from	ADP
fcis-11537	92	7	a	a	DET
fcis-11537	92	8	related	related	ADJ
fcis-11537	92	9	task	task	NOUN
fcis-11537	92	10	that	that	PRON
fcis-11537	92	11	has	have	AUX
fcis-11537	92	12	been	be	AUX
fcis-11537	92	13	learned	learn	VERB
fcis-11537	92	14	to	to	PART
fcis-11537	92	15	learn	learn	VERB
fcis-11537	92	16	a	a	DET
fcis-11537	92	17	new	new	ADJ
fcis-11537	92	18	task	task	NOUN
fcis-11537	92	19	[	[	X
fcis-11537	92	20	16	16	NUM
fcis-11537	92	21	]	]	PUNCT
fcis-11537	92	22	.	.	PUNCT
fcis-11537	93	1	it	it	PRON
fcis-11537	93	2	is	be	AUX
fcis-11537	93	3	often	often	ADV
fcis-11537	93	4	difficult	difficult	ADJ
fcis-11537	93	5	for	for	ADP
fcis-11537	93	6	a	a	DET
fcis-11537	93	7	model	model	NOUN
fcis-11537	93	8	to	to	PART
fcis-11537	93	9	learn	learn	VERB
fcis-11537	93	10	all	all	DET
fcis-11537	93	11	the	the	DET
fcis-11537	93	12	feature	feature	NOUN
fcis-11537	93	13	representations	representation	NOUN
fcis-11537	93	14	in	in	ADP
fcis-11537	93	15	the	the	DET
fcis-11537	93	16	same	same	ADJ
fcis-11537	93	17	task	task	NOUN
fcis-11537	93	18	.	.	PUNCT
fcis-11537	94	1	this	this	PRON
fcis-11537	94	2	requires	require	VERB
fcis-11537	94	3	different	different	ADJ
fcis-11537	94	4	models	model	NOUN
fcis-11537	94	5	to	to	PART
fcis-11537	94	6	learn	learn	VERB
fcis-11537	94	7	and	and	CCONJ
fcis-11537	94	8	adjust	adjust	VERB
fcis-11537	94	9	from	from	ADP
fcis-11537	94	10	other	other	ADJ
fcis-11537	94	11	models	model	NOUN
fcis-11537	94	12	.	.	PUNCT
fcis-11537	95	1	this	this	DET
fcis-11537	95	2	research	research	NOUN
fcis-11537	95	3	used	use	VERB
fcis-11537	95	4	transfer	transfer	NOUN
fcis-11537	95	5	learning	learning	NOUN
fcis-11537	95	6	.	.	PUNCT
fcis-11537	96	1	its	its	PRON
fcis-11537	96	2	flow	flow	NOUN
fcis-11537	96	3	is	be	AUX
fcis-11537	96	4	shown	show	VERB
fcis-11537	96	5	in	in	ADP
fcis-11537	96	6	figure	figure	NOUN
fcis-11537	96	7	3	3	NUM
fcis-11537	96	8	.	.	PUNCT
fcis-11537	97	1	prepare	prepare	VERB
fcis-11537	97	2	the	the	DET
fcis-11537	97	3	pre	pre	ADJ
fcis-11537	97	4	-	-	ADJ
fcis-11537	97	5	trained	train	VERB
fcis-11537	97	6	weight	weight	NOUN
fcis-11537	97	7	of	of	ADP
fcis-11537	97	8	vgg	vgg	NOUN
fcis-11537	97	9	on	on	ADP
fcis-11537	97	10	imagenet	imagenet	NOUN
fcis-11537	97	11	.	.	PUNCT
fcis-11537	98	1	the	the	DET
fcis-11537	98	2	parameters	parameter	NOUN
fcis-11537	98	3	of	of	ADP
fcis-11537	98	4	the	the	DET
fcis-11537	98	5	vgg	vgg	PROPN
fcis-11537	98	6	network	network	NOUN
fcis-11537	98	7	were	be	AUX
fcis-11537	98	8	adjusted	adjust	VERB
fcis-11537	98	9	on	on	ADP
fcis-11537	98	10	the	the	DET
fcis-11537	98	11	coffee	coffee	NOUN
fcis-11537	98	12	leaves	leave	NOUN
fcis-11537	98	13	.	.	PUNCT
fcis-11537	99	1	this	this	PRON
fcis-11537	99	2	allows	allow	VERB
fcis-11537	99	3	the	the	DET
fcis-11537	99	4	model	model	NOUN
fcis-11537	99	5	to	to	PART
fcis-11537	99	6	be	be	AUX
fcis-11537	99	7	better	well	ADV
fcis-11537	99	8	optimized	optimize	VERB
fcis-11537	99	9	.	.	PUNCT
fcis-11537	100	1	use	use	VERB
fcis-11537	100	2	the	the	DET
fcis-11537	100	3	trained	train	VERB
fcis-11537	100	4	vgg	vgg	NOUN
fcis-11537	100	5	network	network	NOUN
fcis-11537	100	6	as	as	ADP
fcis-11537	100	7	a	a	DET
fcis-11537	100	8	teacher	teacher	NOUN
fcis-11537	100	9	network	network	NOUN
fcis-11537	100	10	.	.	PUNCT
fcis-11537	101	1	people	people	NOUN
fcis-11537	101	2	often	often	ADV
fcis-11537	101	3	use	use	VERB
fcis-11537	101	4	complex	complex	ADJ
fcis-11537	101	5	models	model	NOUN
fcis-11537	101	6	to	to	PART
fcis-11537	101	7	get	get	VERB
fcis-11537	101	8	the	the	DET
fcis-11537	101	9	best	good	ADJ
fcis-11537	101	10	results	result	NOUN
fcis-11537	101	11	.	.	PUNCT
fcis-11537	102	1	this	this	PRON
fcis-11537	102	2	may	may	AUX
fcis-11537	102	3	lead	lead	VERB
fcis-11537	102	4	to	to	ADP
fcis-11537	102	5	severe	severe	ADJ
fcis-11537	102	6	redundancy	redundancy	NOUN
fcis-11537	102	7	of	of	ADP
fcis-11537	102	8	parameters	parameter	NOUN
fcis-11537	102	9	.	.	PUNCT
fcis-11537	103	1	for	for	ADP
fcis-11537	103	2	example	example	NOUN
fcis-11537	103	3	,	,	PUNCT
fcis-11537	103	4	vgg	vgg	PROPN
fcis-11537	103	5	has	have	VERB
fcis-11537	103	6	about	about	ADV
fcis-11537	103	7	100	100	NUM
fcis-11537	103	8	million	million	NUM
fcis-11537	103	9	parameters	parameter	NOUN
fcis-11537	103	10	.	.	PUNCT
fcis-11537	104	1	in	in	ADP
fcis-11537	104	2	the	the	DET
fcis-11537	104	3	case	case	NOUN
fcis-11537	104	4	of	of	ADP
fcis-11537	104	5	forward	forward	ADJ
fcis-11537	104	6	propagation	propagation	NOUN
fcis-11537	104	7	,	,	PUNCT
fcis-11537	104	8	it	it	PRON
fcis-11537	104	9	includes	include	VERB
fcis-11537	104	10	convolution	convolution	NOUN
fcis-11537	104	11	computation	computation	NOUN
fcis-11537	104	12	,	,	PUNCT
fcis-11537	104	13	compression	compression	NOUN
fcis-11537	104	14	and	and	CCONJ
fcis-11537	104	15	full	full	ADJ
fcis-11537	104	16	connection	connection	NOUN
fcis-11537	104	17	.	.	PUNCT
fcis-11537	105	1	the	the	DET
fcis-11537	105	2	process	process	NOUN
fcis-11537	105	3	of	of	ADP
fcis-11537	105	4	calculation	calculation	NOUN
fcis-11537	105	5	is	be	AUX
fcis-11537	105	6	complicated	complicated	ADJ
fcis-11537	105	7	.	.	PUNCT
fcis-11537	106	1	it	it	PRON
fcis-11537	106	2	has	have	VERB
fcis-11537	106	3	poor	poor	ADJ
fcis-11537	106	4	performance	performance	NOUN
fcis-11537	106	5	in	in	ADP
fcis-11537	106	6	practical	practical	ADJ
fcis-11537	106	7	engineering	engineering	NOUN
fcis-11537	106	8	application	application	NOUN
fcis-11537	106	9	.	.	PUNCT
fcis-11537	107	1	teach	teach	VERB
fcis-11537	107	2	what	what	PRON
fcis-11537	107	3	a	a	DET
fcis-11537	107	4	complex	complex	ADJ
fcis-11537	107	5	model	model	NOUN
fcis-11537	107	6	(	(	PUNCT
fcis-11537	107	7	teacher	teacher	NOUN
fcis-11537	107	8	)	)	PUNCT
fcis-11537	107	9	has	have	AUX
fcis-11537	107	10	learned	learn	VERB
fcis-11537	107	11	to	to	ADP
fcis-11537	107	12	another	another	DET
fcis-11537	107	13	lightweight	lightweight	ADJ
fcis-11537	107	14	model	model	NOUN
fcis-11537	107	15	(	(	PUNCT
fcis-11537	107	16	student	student	NOUN
fcis-11537	107	17	)	)	PUNCT
fcis-11537	107	18	.	.	PUNCT
fcis-11537	108	1	the	the	DET
fcis-11537	108	2	lightweight	lightweight	ADJ
fcis-11537	108	3	model	model	NOUN
fcis-11537	108	4	can	can	AUX
fcis-11537	108	5	often	often	ADV
fcis-11537	108	6	learn	learn	VERB
fcis-11537	108	7	more	more	ADJ
fcis-11537	108	8	than	than	ADP
fcis-11537	108	9	by	by	ADP
fcis-11537	108	10	its	its	PRON
fcis-11537	108	11	own	own	ADJ
fcis-11537	108	12	.	.	PUNCT
fcis-11537	109	1	and	and	CCONJ
fcis-11537	109	2	the	the	DET
fcis-11537	109	3	model	model	NOUN
fcis-11537	109	4	works	work	VERB
fcis-11537	109	5	a	a	DET
fcis-11537	109	6	lot	lot	NOUN
fcis-11537	109	7	faster	fast	ADV
fcis-11537	109	8	.	.	PUNCT
fcis-11537	110	1	this	this	DET
fcis-11537	110	2	method	method	NOUN
fcis-11537	110	3	is	be	AUX
fcis-11537	110	4	called	call	VERB
fcis-11537	110	5	knowledge	knowledge	NOUN
fcis-11537	110	6	distillation	distillation	NOUN
fcis-11537	110	7	[	[	X
fcis-11537	110	8	17	17	NUM
fcis-11537	110	9	]	]	PUNCT
fcis-11537	110	10	.	.	PUNCT
fcis-11537	111	1	as	as	SCONJ
fcis-11537	111	2	shown	show	VERB
fcis-11537	111	3	in	in	ADP
fcis-11537	111	4	figure	figure	NOUN
fcis-11537	111	5	4	4	NUM
fcis-11537	111	6	.	.	PUNCT
fcis-11537	112	1	it	it	PRON
fcis-11537	112	2	is	be	AUX
fcis-11537	112	3	an	an	DET
fcis-11537	112	4	effective	effective	ADJ
fcis-11537	112	5	model	model	NOUN
fcis-11537	112	6	compression	compression	NOUN
fcis-11537	112	7	method	method	NOUN
fcis-11537	112	8	.	.	PUNCT
fcis-11537	113	1	the	the	DET
fcis-11537	113	2	model	model	NOUN
fcis-11537	113	3	generated	generate	VERB
fcis-11537	113	4	by	by	ADP
fcis-11537	113	5	this	this	DET
fcis-11537	113	6	method	method	NOUN
fcis-11537	113	7	has	have	VERB
fcis-11537	113	8	good	good	ADJ
fcis-11537	113	9	practical	practical	ADJ
fcis-11537	113	10	application	application	NOUN
fcis-11537	113	11	value	value	NOUN
fcis-11537	113	12	.	.	PUNCT
fcis-11537	114	1	pretrained	pretraine	VERB
fcis-11537	114	2	model	model	NOUN
fcis-11537	114	3	input	input	PROPN
fcis-11537	114	4	cnn	cnn	PROPN
fcis-11537	114	5	layer	layer	NOUN
fcis-11537	114	6	fully	fully	ADV
fcis-11537	114	7	connected	connect	VERB
fcis-11537	114	8	layer	layer	NOUN
fcis-11537	114	9	...	...	PUNCT
fcis-11537	115	1	output	output	NOUN
fcis-11537	115	2	cnn	cnn	PROPN
fcis-11537	115	3	layer	layer	NOUN
fcis-11537	115	4	old	old	ADJ
fcis-11537	115	5	classifier	classifier	NOUN
fcis-11537	115	6	new	new	ADJ
fcis-11537	115	7	model	model	NOUN
fcis-11537	115	8	input	input	PROPN
fcis-11537	115	9	cnn	cnn	PROPN
fcis-11537	115	10	layer	layer	NOUN
fcis-11537	115	11	fully	fully	ADV
fcis-11537	115	12	connected	connect	VERB
fcis-11537	115	13	layer	layer	NOUN
fcis-11537	115	14	...	...	PUNCT
fcis-11537	116	1	output	output	NOUN
fcis-11537	116	2	cnn	cnn	PROPN
fcis-11537	116	3	layer	layer	NOUN
fcis-11537	116	4	new	new	ADJ
fcis-11537	116	5	classifier	classifier	NOUN
fcis-11537	116	6	extract	extract	NOUN
fcis-11537	116	7	pretrained	pretraine	VERB
fcis-11537	116	8	weights	weight	NOUN
fcis-11537	116	9	figure	figure	NOUN
fcis-11537	116	10	3	3	NUM
fcis-11537	116	11	.	.	PUNCT
fcis-11537	116	12	flow	flow	VERB
fcis-11537	116	13	chart	chart	NOUN
fcis-11537	116	14	of	of	ADP
fcis-11537	116	15	transfer	transfer	NOUN
fcis-11537	116	16	learning	learning	NOUN
fcis-11537	116	17	know	know	VERB
fcis-11537	116	18	ledge	ledge	NOUN
fcis-11537	116	19	extract	extract	NOUN
fcis-11537	116	20	distill	distill	VERB
fcis-11537	116	21	teacher	teacher	NOUN
fcis-11537	116	22	network	network	NOUN
fcis-11537	116	23	student	student	NOUN
fcis-11537	116	24	networkknowledge	networkknowledge	PROPN
fcis-11537	116	25	distill	distill	VERB
fcis-11537	116	26	data	datum	NOUN
fcis-11537	116	27	figure	figure	NOUN
fcis-11537	116	28	4	4	NUM
fcis-11537	116	29	.	.	PUNCT
fcis-11537	116	30	flow	flow	VERB
fcis-11537	116	31	chart	chart	NOUN
fcis-11537	116	32	of	of	ADP
fcis-11537	116	33	knowledge	knowledge	NOUN
fcis-11537	116	34	distillation	distillation	NOUN
fcis-11537	116	35	in	in	ADP
fcis-11537	116	36	neural	neural	ADJ
fcis-11537	116	37	network	network	NOUN
fcis-11537	116	38	model	model	NOUN
fcis-11537	116	39	,	,	PUNCT
fcis-11537	116	40	convolution	convolution	NOUN
fcis-11537	116	41	layer	layer	NOUN
fcis-11537	116	42	is	be	AUX
fcis-11537	116	43	used	use	VERB
fcis-11537	116	44	to	to	PART
fcis-11537	116	45	extract	extract	VERB
fcis-11537	116	46	image	image	NOUN
fcis-11537	116	47	feature	feature	NOUN
fcis-11537	116	48	information	information	NOUN
fcis-11537	117	1	[	[	X
fcis-11537	117	2	18	18	NUM
fcis-11537	117	3	]	]	PUNCT
fcis-11537	117	4	.	.	PUNCT
fcis-11537	118	1	the	the	DET
fcis-11537	118	2	calculation	calculation	NOUN
fcis-11537	118	3	formula	formula	NOUN
fcis-11537	118	4	of	of	ADP
fcis-11537	118	5	convolution	convolution	NOUN
fcis-11537	118	6	is	be	AUX
fcis-11537	118	7	shown	show	VERB
fcis-11537	118	8	in	in	ADP
fcis-11537	118	9	(	(	PUNCT
fcis-11537	118	10	1	1	NUM
fcis-11537	118	11	)	)	PUNCT
fcis-11537	118	12	.	.	PUNCT
fcis-11537	119	1			VERB
fcis-11537	119	2			PROPN
fcis-11537	119	3			PROPN
fcis-11537	119	4			PROPN
fcis-11537	119	5			PRON
fcis-11537	119	6	m	m	VERB
fcis-11537	119	7	p	p	NOUN
fcis-11537	119	8	p	p	X
fcis-11537	119	9	px	px	PROPN
fcis-11537	119	10	mi	mi	PROPN
fcis-11537	119	11	p	p	PROPN
fcis-11537	119	12	imij	imij	PROPN
fcis-11537	119	13	x	x	PUNCT
fcis-11537	119	14	ij	ij	INTJ
fcis-11537	119	15	i	i	PRON
fcis-11537	119	16	vwbv	vwbv	VERB
fcis-11537	119	17	1	1	NUM
fcis-11537	119	18	0	0	NUM
fcis-11537	119	19	)	)	PUNCT
fcis-11537	119	20	1	1	NUM
fcis-11537	119	21	(	(	PUNCT
fcis-11537	119	22	(	(	PUNCT
fcis-11537	119	23	1	1	X
fcis-11537	119	24	)	)	PUNCT
fcis-11537	119	25	where	where	SCONJ
fcis-11537	119	26	i	i	PRON
fcis-11537	119	27	represents	represent	VERB
fcis-11537	119	28	the	the	DET
fcis-11537	119	29	ith	ith	PROPN
fcis-11537	119	30	convolution	convolution	NOUN
fcis-11537	119	31	layer	layer	NOUN
fcis-11537	119	32	,	,	PUNCT
fcis-11537	119	33	j	j	PROPN
fcis-11537	119	34	represents	represent	VERB
fcis-11537	119	35	the	the	DET
fcis-11537	119	36	jth	jth	PROPN
fcis-11537	119	37	channel	channel	NOUN
fcis-11537	119	38	of	of	ADP
fcis-11537	119	39	the	the	DET
fcis-11537	119	40	current	current	ADJ
fcis-11537	119	41	convolution	convolution	NOUN
fcis-11537	119	42	layer	layer	NOUN
fcis-11537	119	43	,	,	PUNCT
fcis-11537	119	44	pi	pi	NOUN
fcis-11537	119	45	is	be	AUX
fcis-11537	119	46	the	the	DET
fcis-11537	119	47	width	width	NOUN
fcis-11537	119	48	of	of	ADP
fcis-11537	119	49	the	the	DET
fcis-11537	119	50	convolution	convolution	NOUN
fcis-11537	119	51	kernel	kernel	NOUN
fcis-11537	119	52	,	,	PUNCT
fcis-11537	119	53	m	m	VERB
fcis-11537	119	54	indicates	indicate	VERB
fcis-11537	119	55	the	the	DET
fcis-11537	119	56	feature	feature	NOUN
fcis-11537	119	57	mapping	mapping	NOUN
fcis-11537	119	58	from	from	ADP
fcis-11537	119	59	the	the	DET
fcis-11537	119	60	previous	previous	ADJ
fcis-11537	119	61	layer	layer	NOUN
fcis-11537	119	62	to	to	ADP
fcis-11537	119	63	the	the	DET
fcis-11537	119	64	current	current	ADJ
fcis-11537	119	65	layer	layer	NOUN
fcis-11537	119	66	,	,	PUNCT
fcis-11537	119	67	b	b	NOUN
fcis-11537	119	68	is	be	AUX
fcis-11537	119	69	bias	bias	NOUN
fcis-11537	119	70	,	,	PUNCT
fcis-11537	119	71	w	w	PROPN
fcis-11537	119	72	is	be	AUX
fcis-11537	119	73	the	the	DET
fcis-11537	119	74	weight	weight	NOUN
fcis-11537	119	75	matrix	matrix	NOUN
fcis-11537	119	76	.	.	PUNCT
fcis-11537	120	1	the	the	DET
fcis-11537	120	2	batch	batch	NOUN
fcis-11537	120	3	normalization	normalization	NOUN
fcis-11537	120	4	layer	layer	NOUN
fcis-11537	120	5	speeds	speed	VERB
fcis-11537	120	6	up	up	ADP
fcis-11537	120	7	the	the	DET
fcis-11537	120	8	iterative	iterative	ADJ
fcis-11537	120	9	convergence	convergence	NOUN
fcis-11537	120	10	of	of	ADP
fcis-11537	120	11	the	the	DET
fcis-11537	120	12	network	network	NOUN
fcis-11537	120	13	.	.	PUNCT
fcis-11537	121	1	the	the	DET
fcis-11537	121	2	pooling	pooling	NOUN
fcis-11537	121	3	layer	layer	NOUN
fcis-11537	121	4	are	be	AUX
fcis-11537	121	5	used	use	VERB
fcis-11537	121	6	to	to	PART
fcis-11537	121	7	compress	compress	VERB
fcis-11537	121	8	the	the	DET
fcis-11537	121	9	size	size	NOUN
fcis-11537	121	10	of	of	ADP
fcis-11537	121	11	feature	feature	NOUN
fcis-11537	121	12	map	map	NOUN
fcis-11537	121	13	.	.	PUNCT
fcis-11537	122	1	it	it	PRON
fcis-11537	122	2	speeds	speed	VERB
fcis-11537	122	3	up	up	ADP
fcis-11537	122	4	the	the	DET
fcis-11537	122	5	calculation	calculation	NOUN
fcis-11537	122	6	.	.	PUNCT
fcis-11537	123	1	the	the	DET
fcis-11537	123	2	role	role	NOUN
fcis-11537	123	3	of	of	ADP
fcis-11537	123	4	the	the	DET
fcis-11537	123	5	dropout	dropout	NOUN
fcis-11537	123	6	layer	layer	NOUN
fcis-11537	123	7	is	be	AUX
fcis-11537	123	8	to	to	PART
fcis-11537	123	9	prevent	prevent	VERB
fcis-11537	123	10	the	the	DET
fcis-11537	123	11	model	model	NOUN
fcis-11537	123	12	from	from	ADP
fcis-11537	123	13	overfitting	overfitte	VERB
fcis-11537	123	14	and	and	CCONJ
fcis-11537	123	15	make	make	VERB
fcis-11537	123	16	the	the	DET
fcis-11537	123	17	model	model	NOUN
fcis-11537	123	18	generalize	generalize	VERB
fcis-11537	123	19	.	.	PUNCT
fcis-11537	124	1	the	the	DET
fcis-11537	124	2	fully	fully	ADV
fcis-11537	124	3	connected	connect	VERB
fcis-11537	124	4	layer	layer	NOUN
fcis-11537	124	5	gets	get	VERB
fcis-11537	124	6	the	the	DET
fcis-11537	124	7	mapping	mapping	NOUN
fcis-11537	124	8	of	of	ADP
fcis-11537	124	9	the	the	DET
fcis-11537	124	10	feature	feature	NOUN
fcis-11537	124	11	data	datum	NOUN
fcis-11537	124	12	.	.	PUNCT
fcis-11537	125	1	its	its	PRON
fcis-11537	125	2	forward	forward	ADJ
fcis-11537	125	3	propagation	propagation	NOUN
fcis-11537	125	4	[	[	X
fcis-11537	125	5	19	19	NUM
fcis-11537	125	6	]	]	PUNCT
fcis-11537	125	7	formula	formula	NOUN
fcis-11537	125	8	is	be	AUX
fcis-11537	125	9	shown	show	VERB
fcis-11537	125	10	in	in	ADP
fcis-11537	125	11	(	(	PUNCT
fcis-11537	125	12	2	2	NUM
fcis-11537	125	13	)	)	PUNCT
fcis-11537	125	14	.	.	PUNCT
fcis-11537	126	1	it	it	PRON
fcis-11537	126	2	can	can	AUX
fcis-11537	126	3	also	also	ADV
fcis-11537	126	4	be	be	AUX
fcis-11537	126	5	used	use	VERB
fcis-11537	126	6	as	as	ADP
fcis-11537	126	7	the	the	DET
fcis-11537	126	8	final	final	ADJ
fcis-11537	126	9	forecast	forecast	NOUN
fcis-11537	126	10	output	output	NOUN
fcis-11537	126	11	.	.	PUNCT
fcis-11537	127	1			X
fcis-11537	128	1			NUM
fcis-11537	129	1			ADJ
fcis-11537	129	2	n	n	NOUN
fcis-11537	129	3	i	i	PRON
fcis-11537	129	4	jiijj	jiijj	NOUN
fcis-11537	129	5	bxwy	bxwy	VERB
fcis-11537	129	6	1	1	NUM
fcis-11537	129	7	(	(	PUNCT
fcis-11537	129	8	2	2	NUM
fcis-11537	129	9	)	)	PUNCT
fcis-11537	129	10	where	where	SCONJ
fcis-11537	129	11	xi	xi	PROPN
fcis-11537	129	12	is	be	AUX
fcis-11537	129	13	the	the	DET
fcis-11537	129	14	paved	paved	ADJ
fcis-11537	129	15	feature	feature	NOUN
fcis-11537	129	16	vector	vector	NOUN
fcis-11537	129	17	,	,	PUNCT
fcis-11537	129	18	wij	wij	PROPN
fcis-11537	129	19	is	be	AUX
fcis-11537	129	20	the	the	DET
fcis-11537	129	21	weight	weight	NOUN
fcis-11537	129	22	,	,	PUNCT
fcis-11537	129	23	bj	bj	NOUN
fcis-11537	129	24	is	be	AUX
fcis-11537	129	25	the	the	DET
fcis-11537	129	26	bias	bias	NOUN
fcis-11537	129	27	.	.	PUNCT
fcis-11537	130	1	3.3	3.3	NUM
fcis-11537	130	2	.	.	PUNCT
fcis-11537	130	3	model	model	NOUN
fcis-11537	130	4	in	in	ADP
fcis-11537	130	5	this	this	DET
fcis-11537	130	6	research	research	NOUN
fcis-11537	130	7	,	,	PUNCT
fcis-11537	130	8	the	the	DET
fcis-11537	130	9	vgg	vgg	ADJ
fcis-11537	130	10	network	network	NOUN
fcis-11537	131	1	[	[	X
fcis-11537	131	2	20	20	NUM
fcis-11537	131	3	]	]	PUNCT
fcis-11537	131	4	was	be	AUX
fcis-11537	131	5	used	use	VERB
fcis-11537	131	6	to	to	PART
fcis-11537	131	7	learn	learn	VERB
fcis-11537	131	8	the	the	DET
fcis-11537	131	9	information	information	NOUN
fcis-11537	131	10	of	of	ADP
fcis-11537	131	11	coffee	coffee	NOUN
fcis-11537	131	12	leaf	leaf	NOUN
fcis-11537	131	13	images	image	NOUN
fcis-11537	131	14	.	.	PUNCT
fcis-11537	132	1	pre	pre	VERB
fcis-11537	132	2	-	-	ADJ
fcis-11537	132	3	trained	train	VERB
fcis-11537	132	4	weights	weight	NOUN
fcis-11537	132	5	on	on	ADP
fcis-11537	132	6	imagenet	imagenet	NOUN
fcis-11537	132	7	were	be	AUX
fcis-11537	132	8	added	add	VERB
fcis-11537	132	9	at	at	ADP
fcis-11537	132	10	the	the	DET
fcis-11537	132	11	beginning	beginning	NOUN
fcis-11537	132	12	of	of	ADP
fcis-11537	132	13	training	training	NOUN
fcis-11537	132	14	.	.	PUNCT
fcis-11537	133	1	keep	keep	VERB
fcis-11537	133	2	training	training	NOUN
fcis-11537	133	3	until	until	SCONJ
fcis-11537	133	4	the	the	DET
fcis-11537	133	5	loss	loss	NOUN
fcis-11537	133	6	function	function	NOUN
fcis-11537	133	7	converged	converge	VERB
fcis-11537	133	8	,	,	PUNCT
fcis-11537	133	9	the	the	DET
fcis-11537	133	10	vgg	vgg	ADJ
fcis-11537	133	11	network	network	NOUN
fcis-11537	133	12	17	17	NUM
fcis-11537	133	13	with	with	ADP
fcis-11537	133	14	good	good	ADJ
fcis-11537	133	15	recognition	recognition	NOUN
fcis-11537	133	16	effect	effect	NOUN
fcis-11537	133	17	is	be	AUX
fcis-11537	133	18	obtained	obtain	VERB
fcis-11537	133	19	.	.	PUNCT
fcis-11537	134	1	use	use	VERB
fcis-11537	134	2	it	it	PRON
fcis-11537	134	3	as	as	ADP
fcis-11537	134	4	a	a	DET
fcis-11537	134	5	teacher	teacher	NOUN
fcis-11537	134	6	network	network	NOUN
fcis-11537	134	7	.	.	PUNCT
fcis-11537	135	1	a	a	DET
fcis-11537	135	2	lightweight	lightweight	ADJ
fcis-11537	135	3	convolution	convolution	NOUN
fcis-11537	135	4	neural	neural	ADJ
fcis-11537	135	5	network	network	NOUN
fcis-11537	135	6	is	be	AUX
fcis-11537	135	7	also	also	ADV
fcis-11537	135	8	designed	design	VERB
fcis-11537	135	9	.	.	PUNCT
fcis-11537	136	1	use	use	VERB
fcis-11537	136	2	it	it	PRON
fcis-11537	136	3	as	as	ADP
fcis-11537	136	4	a	a	DET
fcis-11537	136	5	student	student	NOUN
fcis-11537	136	6	network	network	NOUN
fcis-11537	136	7	.	.	PUNCT
fcis-11537	137	1	the	the	DET
fcis-11537	137	2	knowledge	knowledge	NOUN
fcis-11537	137	3	distillation	distillation	NOUN
fcis-11537	137	4	method	method	NOUN
fcis-11537	137	5	is	be	AUX
fcis-11537	137	6	used	use	VERB
fcis-11537	137	7	to	to	PART
fcis-11537	137	8	make	make	VERB
fcis-11537	137	9	student	student	NOUN
fcis-11537	137	10	network	network	NOUN
fcis-11537	137	11	learn	learn	VERB
fcis-11537	137	12	the	the	DET
fcis-11537	137	13	information	information	NOUN
fcis-11537	137	14	extracted	extract	VERB
fcis-11537	137	15	by	by	ADP
fcis-11537	137	16	the	the	DET
fcis-11537	137	17	teacher	teacher	NOUN
fcis-11537	137	18	network	network	NOUN
fcis-11537	137	19	.	.	PUNCT
fcis-11537	138	1	finally	finally	ADV
fcis-11537	138	2	,	,	PUNCT
fcis-11537	138	3	the	the	DET
fcis-11537	138	4	lightweight	lightweight	ADJ
fcis-11537	138	5	network	network	NOUN
fcis-11537	138	6	with	with	ADP
fcis-11537	138	7	fast	fast	ADJ
fcis-11537	138	8	computing	computing	NOUN
fcis-11537	138	9	speed	speed	NOUN
fcis-11537	138	10	and	and	CCONJ
fcis-11537	138	11	high	high	ADJ
fcis-11537	138	12	accuracy	accuracy	NOUN
fcis-11537	138	13	was	be	AUX
fcis-11537	138	14	obtained	obtain	VERB
fcis-11537	138	15	.	.	PUNCT
fcis-11537	139	1	the	the	DET
fcis-11537	139	2	complete	complete	ADJ
fcis-11537	139	3	flow	flow	NOUN
fcis-11537	139	4	of	of	ADP
fcis-11537	139	5	the	the	DET
fcis-11537	139	6	proposed	propose	VERB
fcis-11537	139	7	method	method	NOUN
fcis-11537	139	8	is	be	AUX
fcis-11537	139	9	shown	show	VERB
fcis-11537	139	10	in	in	ADP
fcis-11537	139	11	figure	figure	NOUN
fcis-11537	139	12	5	5	NUM
fcis-11537	139	13	.	.	PUNCT
fcis-11537	140	1	tr	tr	VERB
fcis-11537	140	2	ai	ai	VERB
fcis-11537	140	3	n	n	ADV
fcis-11537	140	4	v	v	ADP
fcis-11537	140	5	g	g	PROPN
fcis-11537	140	6	g	g	PROPN
fcis-11537	140	7	n	n	INTJ
fcis-11537	140	8	et	et	NOUN
fcis-11537	140	9	w	w	NOUN
fcis-11537	141	1	or	or	CCONJ
fcis-11537	141	2	k	k	PROPN
fcis-11537	141	3	pr	pr	NOUN
fcis-11537	141	4	etr	etr	PROPN
fcis-11537	141	5	ai	ai	VERB
fcis-11537	141	6	ne	ne	PROPN
fcis-11537	141	7	d	d	PROPN
fcis-11537	141	8	w	w	PROPN
fcis-11537	141	9	ei	ei	PROPN
fcis-11537	141	10	gh	gh	PROPN
fcis-11537	141	11	t	t	PROPN
fcis-11537	141	12	a	a	PROPN
fcis-11537	141	13	cq	cq	PROPN
fcis-11537	141	14	ui	ui	NOUN
fcis-11537	141	15	re	re	PROPN
fcis-11537	141	16	d	d	PROPN
fcis-11537	141	17	kn	kn	PROPN
fcis-11537	141	18	ow	ow	PROPN
fcis-11537	141	19	le	le	X
fcis-11537	141	20	dg	dg	X
fcis-11537	141	21	e	e	NOUN
fcis-11537	141	22	tr	tr	NOUN
fcis-11537	141	23	ai	ai	VERB
fcis-11537	141	24	n	n	PRON
fcis-11537	141	25	pr	pr	NOUN
fcis-11537	141	26	op	op	NOUN
fcis-11537	141	27	os	os	PROPN
fcis-11537	141	28	ed	ed	PROPN
fcis-11537	141	29	m	m	PROPN
fcis-11537	141	30	od	od	PROPN
fcis-11537	141	31	el	el	PROPN
fcis-11537	141	32	pr	pr	PROPN
fcis-11537	141	33	ob	ob	INTJ
fcis-11537	141	34	ab	ab	PROPN
fcis-11537	141	35	ili	ili	PROPN
fcis-11537	142	1	ty	ty	INTJ
fcis-11537	142	2	d	d	NOUN
fcis-11537	142	3	is	be	AUX
fcis-11537	142	4	tr	tr	VERB
fcis-11537	142	5	ib	ib	PROPN
fcis-11537	142	6	ut	ut	PROPN
fcis-11537	142	7	io	io	PROPN
fcis-11537	142	8	n	n	ADV
fcis-11537	142	9	figure	figure	VERB
fcis-11537	142	10	5	5	NUM
fcis-11537	142	11	.	.	PUNCT
fcis-11537	143	1	the	the	DET
fcis-11537	143	2	complete	complete	ADJ
fcis-11537	143	3	flow	flow	NOUN
fcis-11537	143	4	of	of	ADP
fcis-11537	143	5	the	the	DET
fcis-11537	143	6	proposed	propose	VERB
fcis-11537	143	7	method	method	NOUN
fcis-11537	143	8	the	the	DET
fcis-11537	143	9	student	student	NOUN
fcis-11537	143	10	network	network	NOUN
fcis-11537	143	11	has	have	VERB
fcis-11537	143	12	two	two	NUM
fcis-11537	143	13	convolution	convolution	NOUN
fcis-11537	143	14	layers	layer	NOUN
fcis-11537	143	15	.	.	PUNCT
fcis-11537	144	1	the	the	DET
fcis-11537	144	2	first	first	ADJ
fcis-11537	144	3	convolution	convolution	NOUN
fcis-11537	144	4	layer	layer	NOUN
fcis-11537	144	5	has	have	VERB
fcis-11537	144	6	16	16	NUM
fcis-11537	144	7	filters	filter	NOUN
fcis-11537	144	8	.	.	PUNCT
fcis-11537	145	1	the	the	DET
fcis-11537	145	2	second	second	ADJ
fcis-11537	145	3	convolution	convolution	NOUN
fcis-11537	145	4	layer	layer	NOUN
fcis-11537	145	5	has	have	VERB
fcis-11537	145	6	32	32	NUM
fcis-11537	145	7	filters	filter	NOUN
fcis-11537	145	8	.	.	PUNCT
fcis-11537	146	1	each	each	DET
fcis-11537	146	2	convolution	convolution	NOUN
fcis-11537	146	3	layer	layer	NOUN
fcis-11537	146	4	is	be	AUX
fcis-11537	146	5	followed	follow	VERB
fcis-11537	146	6	by	by	ADP
fcis-11537	146	7	batch	batch	NOUN
fcis-11537	146	8	normalization	normalization	NOUN
fcis-11537	146	9	and	and	CCONJ
fcis-11537	146	10	pooling	pool	VERB
fcis-11537	146	11	operations	operation	NOUN
fcis-11537	146	12	.	.	PUNCT
fcis-11537	147	1	pooling	pool	VERB
fcis-11537	147	2	layer	layer	NOUN
fcis-11537	147	3	reduces	reduce	VERB
fcis-11537	147	4	the	the	DET
fcis-11537	147	5	length	length	NOUN
fcis-11537	147	6	and	and	CCONJ
fcis-11537	147	7	width	width	NOUN
fcis-11537	147	8	of	of	ADP
fcis-11537	147	9	the	the	DET
fcis-11537	147	10	feature	feature	NOUN
fcis-11537	147	11	map	map	NOUN
fcis-11537	147	12	to	to	ADP
fcis-11537	147	13	a	a	DET
fcis-11537	147	14	quarter	quarter	NOUN
fcis-11537	147	15	of	of	ADP
fcis-11537	147	16	its	its	PRON
fcis-11537	147	17	original	original	ADJ
fcis-11537	147	18	size	size	NOUN
fcis-11537	147	19	.	.	PUNCT
fcis-11537	148	1	the	the	DET
fcis-11537	148	2	goal	goal	NOUN
fcis-11537	148	3	is	be	AUX
fcis-11537	148	4	to	to	PART
fcis-11537	148	5	speed	speed	VERB
fcis-11537	148	6	up	up	ADP
fcis-11537	148	7	the	the	DET
fcis-11537	148	8	computational	computational	ADJ
fcis-11537	148	9	efficiency	efficiency	NOUN
fcis-11537	148	10	.	.	PUNCT
fcis-11537	149	1	the	the	DET
fcis-11537	149	2	multi	multi	ADJ
fcis-11537	149	3	-	-	ADJ
fcis-11537	149	4	dimensional	dimensional	ADJ
fcis-11537	149	5	feature	feature	NOUN
fcis-11537	149	6	map	map	NOUN
fcis-11537	149	7	is	be	AUX
fcis-11537	149	8	mapped	map	VERB
fcis-11537	149	9	to	to	ADP
fcis-11537	149	10	the	the	DET
fcis-11537	149	11	fully	fully	ADV
fcis-11537	149	12	connected	connected	ADJ
fcis-11537	149	13	layer	layer	NOUN
fcis-11537	149	14	containing	contain	VERB
fcis-11537	149	15	32	32	NUM
fcis-11537	149	16	neurons	neuron	NOUN
fcis-11537	149	17	.	.	PUNCT
fcis-11537	150	1	finally	finally	ADV
fcis-11537	150	2	,	,	PUNCT
fcis-11537	150	3	the	the	DET
fcis-11537	150	4	activation	activation	NOUN
fcis-11537	150	5	function	function	NOUN
fcis-11537	150	6	is	be	AUX
fcis-11537	150	7	the	the	DET
fcis-11537	150	8	softmax	softmax	NOUN
fcis-11537	150	9	function	function	NOUN
fcis-11537	150	10	of	of	ADP
fcis-11537	150	11	the	the	DET
fcis-11537	150	12	5	5	NUM
fcis-11537	150	13	neurons	neuron	NOUN
fcis-11537	150	14	.	.	PUNCT
fcis-11537	151	1	they	they	PRON
fcis-11537	151	2	output	output	VERB
fcis-11537	151	3	probability	probability	NOUN
fcis-11537	151	4	.	.	PUNCT
fcis-11537	152	1	it	it	PRON
fcis-11537	152	2	represents	represent	VERB
fcis-11537	152	3	the	the	DET
fcis-11537	152	4	probability	probability	NOUN
fcis-11537	152	5	of	of	ADP
fcis-11537	152	6	belonging	belong	VERB
fcis-11537	152	7	to	to	ADP
fcis-11537	152	8	a	a	DET
fcis-11537	152	9	certain	certain	ADJ
fcis-11537	152	10	class	class	NOUN
fcis-11537	152	11	.	.	PUNCT
fcis-11537	153	1	the	the	DET
fcis-11537	153	2	cross	cross	ADJ
fcis-11537	153	3	-	-	ADJ
fcis-11537	153	4	entropy	entropy	ADJ
fcis-11537	153	5	loss	loss	NOUN
fcis-11537	153	6	[	[	X
fcis-11537	153	7	21	21	NUM
fcis-11537	153	8	]	]	PUNCT
fcis-11537	153	9	function	function	NOUN
fcis-11537	153	10	is	be	AUX
fcis-11537	153	11	used	use	VERB
fcis-11537	153	12	in	in	ADP
fcis-11537	153	13	the	the	DET
fcis-11537	153	14	training	training	NOUN
fcis-11537	153	15	.	.	PUNCT
fcis-11537	154	1	the	the	DET
fcis-11537	154	2	formula	formula	NOUN
fcis-11537	154	3	is	be	AUX
fcis-11537	154	4	shown	show	VERB
fcis-11537	154	5	in	in	ADP
fcis-11537	154	6	(	(	PUNCT
fcis-11537	154	7	3	3	NUM
fcis-11537	154	8	)	)	PUNCT
fcis-11537	154	9	.	.	PUNCT
fcis-11537	155	1			PROPN
fcis-11537	155	2	)	)	PUNCT
fcis-11537	155	3	log	log	PROPN
fcis-11537	155	4	(	(	PUNCT
fcis-11537	155	5	*	*	PROPN
fcis-11537	155	6	ii	ii	PROPN
fcis-11537	155	7	pyl	pyl	NOUN
fcis-11537	155	8	(	(	PUNCT
fcis-11537	155	9	3	3	NUM
fcis-11537	155	10	)	)	PUNCT
fcis-11537	155	11	where	where	SCONJ
fcis-11537	155	12	yi	yi	PROPN
fcis-11537	155	13	is	be	AUX
fcis-11537	155	14	the	the	DET
fcis-11537	155	15	true	true	ADJ
fcis-11537	155	16	label	label	NOUN
fcis-11537	155	17	for	for	ADP
fcis-11537	155	18	which	which	DET
fcis-11537	155	19	class	class	NOUN
fcis-11537	155	20	the	the	DET
fcis-11537	155	21	sample	sample	NOUN
fcis-11537	155	22	belongs	belong	VERB
fcis-11537	155	23	to	to	ADP
fcis-11537	155	24	,	,	PUNCT
fcis-11537	155	25	pi	pi	PROPN
fcis-11537	155	26	is	be	AUX
fcis-11537	155	27	a	a	DET
fcis-11537	155	28	prediction	prediction	NOUN
fcis-11537	155	29	probability	probability	NOUN
fcis-11537	156	1	[	[	X
fcis-11537	156	2	22	22	NUM
fcis-11537	156	3	]	]	PUNCT
fcis-11537	156	4	belonging	belong	VERB
fcis-11537	156	5	to	to	ADP
fcis-11537	156	6	class	class	NOUN
fcis-11537	156	7	i.	i.	PROPN
fcis-11537	156	8	dropout	dropout	PROPN
fcis-11537	156	9	operation	operation	NOUN
fcis-11537	156	10	has	have	AUX
fcis-11537	156	11	been	be	AUX
fcis-11537	156	12	added	add	VERB
fcis-11537	156	13	.	.	PUNCT
fcis-11537	157	1	to	to	PART
fcis-11537	157	2	prevent	prevent	VERB
fcis-11537	157	3	the	the	DET
fcis-11537	157	4	model	model	NOUN
fcis-11537	157	5	from	from	ADP
fcis-11537	157	6	overfitting	overfitte	VERB
fcis-11537	157	7	.	.	PUNCT
fcis-11537	158	1	and	and	CCONJ
fcis-11537	158	2	make	make	VERB
fcis-11537	158	3	the	the	DET
fcis-11537	158	4	model	model	NOUN
fcis-11537	158	5	generalize	generalize	VERB
fcis-11537	158	6	.	.	PUNCT
fcis-11537	159	1	the	the	DET
fcis-11537	159	2	structure	structure	NOUN
fcis-11537	159	3	diagram	diagram	NOUN
fcis-11537	159	4	of	of	ADP
fcis-11537	159	5	teacher	teacher	NOUN
fcis-11537	159	6	network	network	NOUN
fcis-11537	159	7	and	and	CCONJ
fcis-11537	159	8	student	student	NOUN
fcis-11537	159	9	network	network	NOUN
fcis-11537	159	10	is	be	AUX
fcis-11537	159	11	shown	show	VERB
fcis-11537	159	12	in	in	ADP
fcis-11537	159	13	figure	figure	NOUN
fcis-11537	159	14	6	6	NUM
fcis-11537	159	15	.	.	PUNCT
fcis-11537	160	1	conv	conv	ADJ
fcis-11537	160	2	bn	bn	PROPN
fcis-11537	160	3	pool	pool	NOUN
fcis-11537	160	4	relu	relu	NOUN
fcis-11537	160	5	softmax	softmax	NOUN
fcis-11537	160	6	fully	fully	ADV
fcis-11537	160	7	connected	connect	VERB
fcis-11537	160	8	true	true	ADJ
fcis-11537	160	9	lab	lab	NOUN
fcis-11537	160	10	el	el	PROPN
fcis-11537	160	11	know	know	PROPN
fcis-11537	160	12	led	lead	VERB
fcis-11537	160	13	g	g	PROPN
fcis-11537	160	14	e	e	PROPN
fcis-11537	160	15	teacher	teacher	NOUN
fcis-11537	160	16	network	network	NOUN
fcis-11537	160	17	student	student	NOUN
fcis-11537	160	18	network	network	NOUN
fcis-11537	160	19	figure	figure	NOUN
fcis-11537	160	20	6	6	NUM
fcis-11537	160	21	.	.	PUNCT
fcis-11537	161	1	the	the	DET
fcis-11537	161	2	structure	structure	NOUN
fcis-11537	161	3	diagram	diagram	NOUN
fcis-11537	161	4	of	of	ADP
fcis-11537	161	5	teacher	teacher	NOUN
fcis-11537	161	6	network	network	NOUN
fcis-11537	161	7	and	and	CCONJ
fcis-11537	161	8	student	student	NOUN
fcis-11537	161	9	network	network	NOUN
fcis-11537	161	10	after	after	ADP
fcis-11537	161	11	knowledge	knowledge	NOUN
fcis-11537	161	12	distillation	distillation	NOUN
fcis-11537	161	13	,	,	PUNCT
fcis-11537	161	14	the	the	DET
fcis-11537	161	15	student	student	NOUN
fcis-11537	161	16	network	network	NOUN
fcis-11537	161	17	will	will	AUX
fcis-11537	161	18	have	have	VERB
fcis-11537	161	19	the	the	DET
fcis-11537	161	20	recognition	recognition	NOUN
fcis-11537	161	21	ability	ability	NOUN
fcis-11537	161	22	of	of	ADP
fcis-11537	161	23	the	the	DET
fcis-11537	161	24	teacher	teacher	NOUN
fcis-11537	161	25	model	model	NOUN
fcis-11537	161	26	.	.	PUNCT
fcis-11537	162	1	the	the	DET
fcis-11537	162	2	calculation	calculation	NOUN
fcis-11537	162	3	speed	speed	NOUN
fcis-11537	162	4	of	of	ADP
fcis-11537	162	5	the	the	DET
fcis-11537	162	6	model	model	NOUN
fcis-11537	162	7	is	be	AUX
fcis-11537	162	8	also	also	ADV
fcis-11537	162	9	improved	improve	VERB
fcis-11537	162	10	while	while	SCONJ
fcis-11537	162	11	the	the	DET
fcis-11537	162	12	accuracy	accuracy	NOUN
fcis-11537	162	13	is	be	AUX
fcis-11537	162	14	guaranteed	guarantee	VERB
fcis-11537	162	15	.	.	PUNCT
fcis-11537	163	1	4	4	X
fcis-11537	163	2	.	.	NOUN
fcis-11537	163	3	results	result	VERB
fcis-11537	163	4	the	the	DET
fcis-11537	163	5	calculation	calculation	NOUN
fcis-11537	163	6	framework	framework	NOUN
fcis-11537	163	7	of	of	ADP
fcis-11537	163	8	this	this	DET
fcis-11537	163	9	research	research	NOUN
fcis-11537	163	10	is	be	AUX
fcis-11537	163	11	tensorflow	tensorflow	ADJ
fcis-11537	163	12	.	.	PUNCT
fcis-11537	164	1	the	the	DET
fcis-11537	164	2	data	datum	NOUN
fcis-11537	164	3	set	set	VERB
fcis-11537	164	4	is	be	AUX
fcis-11537	164	5	divided	divide	VERB
fcis-11537	164	6	into	into	ADP
fcis-11537	164	7	the	the	DET
fcis-11537	164	8	train	train	NOUN
fcis-11537	164	9	set	set	NOUN
fcis-11537	164	10	and	and	CCONJ
fcis-11537	164	11	the	the	DET
fcis-11537	164	12	test	test	NOUN
fcis-11537	164	13	set	set	VERB
fcis-11537	164	14	in	in	ADP
fcis-11537	164	15	a	a	DET
fcis-11537	164	16	ratio	ratio	NOUN
fcis-11537	164	17	of	of	ADP
fcis-11537	164	18	3:1	3:1	NUM
fcis-11537	164	19	.	.	PUNCT
fcis-11537	165	1	use	use	VERB
fcis-11537	165	2	10	10	NUM
fcis-11537	165	3	%	%	NOUN
fcis-11537	165	4	of	of	ADP
fcis-11537	165	5	the	the	DET
fcis-11537	165	6	train	train	NOUN
fcis-11537	165	7	set	set	NOUN
fcis-11537	165	8	as	as	ADP
fcis-11537	165	9	the	the	DET
fcis-11537	165	10	verification	verification	NOUN
fcis-11537	165	11	set	set	NOUN
fcis-11537	165	12	.	.	PUNCT
fcis-11537	166	1	the	the	DET
fcis-11537	166	2	network	network	NOUN
fcis-11537	166	3	structure	structure	NOUN
fcis-11537	166	4	of	of	ADP
fcis-11537	166	5	the	the	DET
fcis-11537	166	6	proposed	propose	VERB
fcis-11537	166	7	model	model	NOUN
fcis-11537	166	8	is	be	AUX
fcis-11537	166	9	shown	show	VERB
fcis-11537	166	10	in	in	ADP
fcis-11537	166	11	table	table	NOUN
fcis-11537	166	12	1	1	NUM
fcis-11537	166	13	.	.	PUNCT
fcis-11537	167	1	the	the	DET
fcis-11537	167	2	proposed	propose	VERB
fcis-11537	167	3	model	model	NOUN
fcis-11537	167	4	is	be	AUX
fcis-11537	167	5	lightweight	lightweight	ADJ
fcis-11537	167	6	.	.	PUNCT
fcis-11537	168	1	compared	compare	VERB
fcis-11537	168	2	to	to	ADP
fcis-11537	168	3	large	large	ADJ
fcis-11537	168	4	models	model	NOUN
fcis-11537	168	5	,	,	PUNCT
fcis-11537	168	6	its	its	PRON
fcis-11537	168	7	speed	speed	NOUN
fcis-11537	168	8	of	of	ADP
fcis-11537	168	9	calculation	calculation	NOUN
fcis-11537	168	10	is	be	AUX
fcis-11537	168	11	very	very	ADV
fcis-11537	168	12	fast	fast	ADV
fcis-11537	168	13	.	.	PUNCT
fcis-11537	169	1	the	the	DET
fcis-11537	169	2	experiment	experiment	NOUN
fcis-11537	169	3	also	also	ADV
fcis-11537	169	4	compares	compare	VERB
fcis-11537	169	5	the	the	DET
fcis-11537	169	6	recognition	recognition	NOUN
fcis-11537	169	7	efficiency	efficiency	NOUN
fcis-11537	169	8	of	of	ADP
fcis-11537	169	9	different	different	ADJ
fcis-11537	169	10	models	model	NOUN
fcis-11537	169	11	.	.	PUNCT
fcis-11537	170	1	as	as	SCONJ
fcis-11537	170	2	shown	show	VERB
fcis-11537	170	3	in	in	ADP
fcis-11537	170	4	table	table	NOUN
fcis-11537	170	5	2	2	NUM
fcis-11537	170	6	.	.	PUNCT
fcis-11537	170	7	table	table	NOUN
fcis-11537	170	8	1	1	NUM
fcis-11537	170	9	.	.	PUNCT
fcis-11537	171	1	the	the	DET
fcis-11537	171	2	network	network	NOUN
fcis-11537	171	3	structure	structure	NOUN
fcis-11537	171	4	of	of	ADP
fcis-11537	171	5	the	the	DET
fcis-11537	171	6	proposed	propose	VERB
fcis-11537	171	7	model	model	NOUN
fcis-11537	171	8	name	name	PROPN
fcis-11537	171	9	kernel	kernel	PROPN
fcis-11537	171	10	size	size	NOUN
fcis-11537	171	11	stride	stride	ADJ
fcis-11537	171	12	output	output	NOUN
fcis-11537	171	13	size	size	NOUN
fcis-11537	171	14	conv1	conv1	ADP
fcis-11537	171	15	3×3	3×3	NUM
fcis-11537	171	16	1×1	1×1	NOUN
fcis-11537	171	17	64×64×16	64×64×16	NUM
fcis-11537	172	1	bn1	bn1	PROPN
fcis-11537	172	2	--64×64×16	--64×64×16	PROPN
fcis-11537	173	1	pooling1	pooling1	PROPN
fcis-11537	173	2	4×4	4×4	NUM
fcis-11537	173	3	4×4	4×4	NUM
fcis-11537	173	4	16×16×16	16×16×16	NUM
fcis-11537	173	5	conv2	conv2	X
fcis-11537	174	1	3×3	3×3	NUM
fcis-11537	174	2	1×1	1×1	NOUN
fcis-11537	174	3	16×16×32	16×16×32	NUM
fcis-11537	174	4	bn2	bn2	NOUN
fcis-11537	174	5	--16×16×32	--16×16×32	PRON
fcis-11537	174	6	pooling2	pooling2	NOUN
fcis-11537	174	7	4×4	4×4	NUM
fcis-11537	174	8	4×4	4×4	NUM
fcis-11537	175	1	4×4×32	4×4×32	NUM
fcis-11537	175	2	flatten	flatten	VERB
fcis-11537	175	3	--512	--512	PROPN
fcis-11537	175	4	fc	fc	PROPN
fcis-11537	175	5	--32	--32	PROPN
fcis-11537	175	6	table	table	NOUN
fcis-11537	175	7	2	2	NUM
fcis-11537	175	8	.	.	PUNCT
fcis-11537	176	1	the	the	DET
fcis-11537	176	2	recognition	recognition	NOUN
fcis-11537	176	3	efficiency	efficiency	NOUN
fcis-11537	176	4	of	of	ADP
fcis-11537	176	5	different	different	ADJ
fcis-11537	176	6	models	model	NOUN
fcis-11537	176	7	method	method	VERB
fcis-11537	176	8	accuracy	accuracy	NOUN
fcis-11537	176	9	time	time	NOUN
fcis-11537	176	10	svm	svm	VERB
fcis-11537	176	11	87.91	87.91	NUM
fcis-11537	176	12	0.023s	0.023s	NUM
fcis-11537	176	13	vgg	vgg	PROPN
fcis-11537	176	14	97.23	97.23	NUM
fcis-11537	176	15	1.314s	1.314s	NUM
fcis-11537	176	16	vgg	vgg	NOUN
fcis-11537	176	17	with	with	ADP
fcis-11537	176	18	pre	pre	ADJ
fcis-11537	176	19	-	-	ADJ
fcis-11537	176	20	trained	train	VERB
fcis-11537	176	21	weights	weight	NOUN
fcis-11537	176	22	97.98	97.98	NUM
fcis-11537	176	23	1.297s	1.297s	NUM
fcis-11537	176	24	lightweight	lightweight	ADJ
fcis-11537	176	25	model	model	NOUN
fcis-11537	176	26	92.44	92.44	NUM
fcis-11537	176	27	0.065s	0.065s	PROPN
fcis-11537	176	28	proposed	propose	VERB
fcis-11537	176	29	model	model	NOUN
fcis-11537	176	30	96.73	96.73	NUM
fcis-11537	176	31	0.069s	0.069s	NOUN
fcis-11537	176	32	it	it	PRON
fcis-11537	176	33	can	can	AUX
fcis-11537	176	34	be	be	AUX
fcis-11537	176	35	seen	see	VERB
fcis-11537	176	36	from	from	ADP
fcis-11537	176	37	table	table	NOUN
fcis-11537	176	38	2	2	NUM
fcis-11537	176	39	that	that	SCONJ
fcis-11537	176	40	the	the	DET
fcis-11537	176	41	accuracy	accuracy	NOUN
fcis-11537	176	42	of	of	ADP
fcis-11537	176	43	the	the	DET
fcis-11537	176	44	method	method	NOUN
fcis-11537	176	45	proposed	propose	VERB
fcis-11537	176	46	is	be	AUX
fcis-11537	176	47	4.29	4.29	NUM
fcis-11537	176	48	%	%	NOUN
fcis-11537	176	49	higher	high	ADJ
fcis-11537	176	50	than	than	ADP
fcis-11537	176	51	the	the	DET
fcis-11537	176	52	model	model	NOUN
fcis-11537	176	53	directly	directly	ADV
fcis-11537	176	54	trained	train	VERB
fcis-11537	176	55	with	with	ADP
fcis-11537	176	56	light	light	ADJ
fcis-11537	176	57	weight	weight	NOUN
fcis-11537	176	58	.	.	PUNCT
fcis-11537	177	1	it	it	PRON
fcis-11537	177	2	was	be	AUX
fcis-11537	177	3	only	only	ADV
fcis-11537	177	4	1.25	1.25	NUM
fcis-11537	177	5	%	%	NOUN
fcis-11537	177	6	less	less	ADV
fcis-11537	177	7	accurate	accurate	ADJ
fcis-11537	177	8	than	than	ADP
fcis-11537	177	9	the	the	DET
fcis-11537	177	10	teacher	teacher	NOUN
fcis-11537	177	11	network	network	NOUN
fcis-11537	177	12	.	.	PUNCT
fcis-11537	178	1	it	it	PRON
fcis-11537	178	2	shows	show	VERB
fcis-11537	178	3	that	that	SCONJ
fcis-11537	178	4	the	the	DET
fcis-11537	178	5	proposed	propose	VERB
fcis-11537	178	6	method	method	NOUN
fcis-11537	178	7	not	not	PART
fcis-11537	178	8	only	only	ADV
fcis-11537	178	9	has	have	VERB
fcis-11537	178	10	high	high	ADJ
fcis-11537	178	11	computation	computation	NOUN
fcis-11537	178	12	speed	speed	NOUN
fcis-11537	178	13	,	,	PUNCT
fcis-11537	178	14	but	but	CCONJ
fcis-11537	178	15	also	also	ADV
fcis-11537	178	16	has	have	VERB
fcis-11537	178	17	good	good	ADJ
fcis-11537	178	18	recognition	recognition	NOUN
fcis-11537	178	19	effect	effect	NOUN
fcis-11537	178	20	.	.	PUNCT
fcis-11537	179	1	the	the	DET
fcis-11537	179	2	region	region	NOUN
fcis-11537	179	3	of	of	ADP
fcis-11537	179	4	interest	interest	NOUN
fcis-11537	179	5	of	of	ADP
fcis-11537	179	6	the	the	DET
fcis-11537	179	7	model	model	NOUN
fcis-11537	179	8	to	to	ADP
fcis-11537	179	9	the	the	DET
fcis-11537	179	10	leaf	leaf	NOUN
fcis-11537	179	11	image	image	NOUN
fcis-11537	179	12	is	be	AUX
fcis-11537	179	13	visualized	visualize	VERB
fcis-11537	179	14	[	[	X
fcis-11537	179	15	23	23	NUM
fcis-11537	179	16	]	]	PUNCT
fcis-11537	179	17	.	.	PUNCT
fcis-11537	180	1	verify	verify	VERB
fcis-11537	180	2	the	the	DET
fcis-11537	180	3	ability	ability	NOUN
fcis-11537	180	4	of	of	ADP
fcis-11537	180	5	the	the	DET
fcis-11537	180	6	model	model	NOUN
fcis-11537	180	7	to	to	PART
fcis-11537	180	8	extract	extract	VERB
fcis-11537	180	9	features	feature	NOUN
fcis-11537	180	10	.	.	PUNCT
fcis-11537	181	1	as	as	SCONJ
fcis-11537	181	2	shown	show	VERB
fcis-11537	181	3	in	in	ADP
fcis-11537	181	4	figure	figure	NOUN
fcis-11537	181	5	7	7	NUM
fcis-11537	181	6	.	.	PUNCT
fcis-11537	181	7	figure	figure	NOUN
fcis-11537	181	8	7	7	NUM
fcis-11537	181	9	.	.	PUNCT
fcis-11537	182	1	visualization	visualization	NOUN
fcis-11537	182	2	of	of	ADP
fcis-11537	182	3	the	the	DET
fcis-11537	182	4	feature	feature	NOUN
fcis-11537	182	5	region	region	NOUN
fcis-11537	182	6	of	of	ADP
fcis-11537	182	7	the	the	DET
fcis-11537	182	8	images	image	NOUN
fcis-11537	182	9	for	for	ADP
fcis-11537	182	10	leaves	leave	NOUN
fcis-11537	182	11	infected	infect	VERB
fcis-11537	182	12	with	with	ADP
fcis-11537	182	13	pests	pest	NOUN
fcis-11537	182	14	and	and	CCONJ
fcis-11537	182	15	diseases	disease	NOUN
fcis-11537	182	16	.	.	PUNCT
fcis-11537	183	1	the	the	DET
fcis-11537	183	2	model	model	NOUN
fcis-11537	183	3	can	can	AUX
fcis-11537	183	4	extract	extract	VERB
fcis-11537	183	5	the	the	DET
fcis-11537	183	6	feature	feature	NOUN
fcis-11537	183	7	region	region	NOUN
fcis-11537	183	8	of	of	ADP
fcis-11537	183	9	the	the	DET
fcis-11537	183	10	images	image	NOUN
fcis-11537	183	11	correctly	correctly	ADV
fcis-11537	183	12	.	.	PUNCT
fcis-11537	184	1	this	this	PRON
fcis-11537	184	2	is	be	AUX
fcis-11537	184	3	helpful	helpful	ADJ
fcis-11537	184	4	for	for	ADP
fcis-11537	184	5	analysis	analysis	NOUN
fcis-11537	184	6	of	of	ADP
fcis-11537	184	7	leaf	leaf	NOUN
fcis-11537	184	8	pathology	pathology	NOUN
fcis-11537	184	9	.	.	PUNCT
fcis-11537	185	1	properly	properly	ADV
fcis-11537	185	2	monitor	monitor	VERB
fcis-11537	185	3	crop	crop	NOUN
fcis-11537	185	4	health	health	NOUN
fcis-11537	185	5	and	and	CCONJ
fcis-11537	185	6	prevent	prevent	VERB
fcis-11537	185	7	the	the	DET
fcis-11537	185	8	spread	spread	NOUN
fcis-11537	185	9	of	of	ADP
fcis-11537	185	10	pests	pest	NOUN
fcis-11537	185	11	and	and	CCONJ
fcis-11537	185	12	diseases	disease	NOUN
fcis-11537	185	13	.	.	PUNCT
fcis-11537	186	1	plot	plot	VERB
fcis-11537	186	2	the	the	DET
fcis-11537	186	3	confusion	confusion	NOUN
fcis-11537	186	4	matrix	matrix	NOUN
fcis-11537	186	5	[	[	X
fcis-11537	186	6	24	24	NUM
fcis-11537	186	7	]	]	PUNCT
fcis-11537	186	8	and	and	CCONJ
fcis-11537	186	9	t	t	PROPN
fcis-11537	186	10	-	-	PUNCT
fcis-11537	186	11	sne	sne	NOUN
fcis-11537	186	12	visualization	visualization	NOUN
fcis-11537	186	13	[	[	X
fcis-11537	186	14	25	25	NUM
fcis-11537	186	15	]	]	PUNCT
fcis-11537	186	16	results	result	NOUN
fcis-11537	186	17	.	.	PUNCT
fcis-11537	187	1	as	as	SCONJ
fcis-11537	187	2	shown	show	VERB
fcis-11537	187	3	in	in	ADP
fcis-11537	187	4	figure	figure	NOUN
fcis-11537	187	5	8	8	NUM
fcis-11537	187	6	.	.	PUNCT
fcis-11537	187	7	confusion	confusion	NOUN
fcis-11537	187	8	matrix	matrix	NOUN
fcis-11537	187	9	of	of	ADP
fcis-11537	187	10	coffee	coffee	NOUN
fcis-11537	187	11	leaf	leaf	NOUN
fcis-11537	187	12	t	t	PROPN
fcis-11537	187	13	-	-	PUNCT
fcis-11537	187	14	sne	sne	NOUN
fcis-11537	187	15	visualization	visualization	NOUN
fcis-11537	187	16	of	of	ADP
fcis-11537	187	17	coffee	coffee	NOUN
fcis-11537	187	18	leaf	leaf	NOUN
fcis-11537	187	19	figure	figure	NOUN
fcis-11537	187	20	8	8	NUM
fcis-11537	187	21	.	.	PUNCT
fcis-11537	187	22	confusion	confusion	NOUN
fcis-11537	187	23	matrix	matrix	NOUN
fcis-11537	187	24	and	and	CCONJ
fcis-11537	187	25	t	t	PROPN
fcis-11537	187	26	-	-	PUNCT
fcis-11537	187	27	sne	sne	NOUN
fcis-11537	187	28	visualization	visualization	NOUN
fcis-11537	187	29	for	for	ADP
fcis-11537	187	30	most	most	ADJ
fcis-11537	187	31	categories	category	NOUN
fcis-11537	187	32	of	of	ADP
fcis-11537	187	33	samples	sample	NOUN
fcis-11537	187	34	,	,	PUNCT
fcis-11537	187	35	the	the	DET
fcis-11537	187	36	model	model	NOUN
fcis-11537	187	37	has	have	VERB
fcis-11537	187	38	a	a	DET
fcis-11537	187	39	high	high	ADJ
fcis-11537	187	40	recognition	recognition	NOUN
fcis-11537	187	41	accuracy	accuracy	NOUN
fcis-11537	187	42	.	.	PUNCT
fcis-11537	188	1	after	after	SCONJ
fcis-11537	188	2	the	the	DET
fcis-11537	188	3	data	datum	NOUN
fcis-11537	188	4	of	of	ADP
fcis-11537	188	5	the	the	DET
fcis-11537	188	6	fully	fully	ADV
fcis-11537	188	7	connected	connect	VERB
fcis-11537	188	8	layer	layer	NOUN
fcis-11537	188	9	are	be	AUX
fcis-11537	188	10	compressed	compress	VERB
fcis-11537	188	11	into	into	ADP
fcis-11537	188	12	two	two	NUM
fcis-11537	188	13	dimensions	dimension	NOUN
fcis-11537	188	14	,	,	PUNCT
fcis-11537	188	15	the	the	DET
fcis-11537	188	16	scatter	scatter	NOUN
fcis-11537	188	17	plot	plot	NOUN
fcis-11537	188	18	is	be	AUX
fcis-11537	188	19	drawn	draw	VERB
fcis-11537	188	20	.	.	PUNCT
fcis-11537	189	1	the	the	DET
fcis-11537	189	2	distribution	distribution	NOUN
fcis-11537	189	3	of	of	ADP
fcis-11537	189	4	samples	sample	NOUN
fcis-11537	189	5	with	with	ADP
fcis-11537	189	6	extracted	extract	VERB
fcis-11537	189	7	features	feature	NOUN
fcis-11537	189	8	18	18	NUM
fcis-11537	189	9	showed	show	VERB
fcis-11537	189	10	obvious	obvious	ADJ
fcis-11537	189	11	regularity	regularity	NOUN
fcis-11537	189	12	.	.	PUNCT
fcis-11537	190	1	samples	sample	NOUN
fcis-11537	190	2	of	of	ADP
fcis-11537	190	3	the	the	DET
fcis-11537	190	4	same	same	ADJ
fcis-11537	190	5	kind	kind	NOUN
fcis-11537	190	6	are	be	AUX
fcis-11537	190	7	close	close	ADJ
fcis-11537	190	8	together	together	ADV
fcis-11537	190	9	and	and	CCONJ
fcis-11537	190	10	samples	sample	NOUN
fcis-11537	190	11	of	of	ADP
fcis-11537	190	12	different	different	ADJ
fcis-11537	190	13	kinds	kind	NOUN
fcis-11537	190	14	are	be	AUX
fcis-11537	190	15	far	far	ADV
fcis-11537	190	16	apart	apart	ADV
fcis-11537	190	17	.	.	PUNCT
fcis-11537	191	1	this	this	PRON
fcis-11537	191	2	helps	helps	AUX
fcis-11537	191	3	identify	identify	VERB
fcis-11537	191	4	pests	pest	NOUN
fcis-11537	191	5	and	and	CCONJ
fcis-11537	191	6	diseases	disease	NOUN
fcis-11537	191	7	in	in	ADP
fcis-11537	191	8	the	the	DET
fcis-11537	191	9	sample	sample	NOUN
fcis-11537	191	10	.	.	PUNCT
fcis-11537	192	1	5	5	X
fcis-11537	192	2	.	.	X
fcis-11537	192	3	conclusion	conclusion	NOUN
fcis-11537	192	4	this	this	DET
fcis-11537	192	5	research	research	NOUN
fcis-11537	192	6	took	take	VERB
fcis-11537	192	7	into	into	ADP
fcis-11537	192	8	account	account	NOUN
fcis-11537	192	9	the	the	DET
fcis-11537	192	10	slow	slow	ADJ
fcis-11537	192	11	calculation	calculation	NOUN
fcis-11537	192	12	speed	speed	NOUN
fcis-11537	192	13	of	of	ADP
fcis-11537	192	14	large	large	ADJ
fcis-11537	192	15	models	model	NOUN
fcis-11537	192	16	.	.	PUNCT
fcis-11537	193	1	and	and	CCONJ
fcis-11537	193	2	the	the	DET
fcis-11537	193	3	direct	direct	ADJ
fcis-11537	193	4	learning	learning	NOUN
fcis-11537	193	5	efficiency	efficiency	NOUN
fcis-11537	193	6	of	of	ADP
fcis-11537	193	7	lightweight	lightweight	ADJ
fcis-11537	193	8	models	model	NOUN
fcis-11537	193	9	is	be	AUX
fcis-11537	193	10	not	not	PART
fcis-11537	193	11	good	good	ADJ
fcis-11537	193	12	.	.	PUNCT
fcis-11537	194	1	this	this	DET
fcis-11537	194	2	research	research	NOUN
fcis-11537	194	3	proposed	propose	VERB
fcis-11537	194	4	a	a	DET
fcis-11537	194	5	method	method	NOUN
fcis-11537	194	6	based	base	VERB
fcis-11537	194	7	on	on	ADP
fcis-11537	194	8	transfer	transfer	NOUN
fcis-11537	194	9	learning	learning	NOUN
fcis-11537	194	10	and	and	CCONJ
fcis-11537	194	11	knowledge	knowledge	NOUN
fcis-11537	194	12	distillation	distillation	NOUN
fcis-11537	194	13	to	to	PART
fcis-11537	194	14	identify	identify	VERB
fcis-11537	194	15	diseases	disease	NOUN
fcis-11537	194	16	in	in	ADP
fcis-11537	194	17	coffee	coffee	NOUN
fcis-11537	194	18	leaves	leave	NOUN
fcis-11537	194	19	.	.	PUNCT
fcis-11537	195	1	the	the	DET
fcis-11537	195	2	large	large	ADJ
fcis-11537	195	3	network	network	NOUN
fcis-11537	195	4	with	with	ADP
fcis-11537	195	5	pre	pre	ADJ
fcis-11537	195	6	-	-	ADJ
fcis-11537	195	7	trained	train	VERB
fcis-11537	195	8	weights	weight	NOUN
fcis-11537	195	9	on	on	ADP
fcis-11537	195	10	imagenet	imagenet	NOUN
fcis-11537	195	11	was	be	AUX
fcis-11537	195	12	used	use	VERB
fcis-11537	195	13	to	to	PART
fcis-11537	195	14	learn	learn	VERB
fcis-11537	195	15	information	information	NOUN
fcis-11537	195	16	about	about	ADP
fcis-11537	195	17	coffee	coffee	NOUN
fcis-11537	195	18	leaf	leaf	NOUN
fcis-11537	195	19	images	image	NOUN
fcis-11537	195	20	.	.	PUNCT
fcis-11537	196	1	use	use	VERB
fcis-11537	196	2	it	it	PRON
fcis-11537	196	3	as	as	ADP
fcis-11537	196	4	the	the	DET
fcis-11537	196	5	teacher	teacher	NOUN
fcis-11537	196	6	network	network	NOUN
fcis-11537	196	7	.	.	PUNCT
fcis-11537	197	1	design	design	VERB
fcis-11537	197	2	a	a	DET
fcis-11537	197	3	lightweight	lightweight	ADJ
fcis-11537	197	4	convolution	convolution	NOUN
fcis-11537	197	5	neural	neural	ADJ
fcis-11537	197	6	network	network	NOUN
fcis-11537	197	7	.	.	PUNCT
fcis-11537	198	1	use	use	VERB
fcis-11537	198	2	it	it	PRON
fcis-11537	198	3	as	as	ADP
fcis-11537	198	4	the	the	DET
fcis-11537	198	5	student	student	NOUN
fcis-11537	198	6	network	network	NOUN
fcis-11537	198	7	.	.	PUNCT
fcis-11537	199	1	the	the	DET
fcis-11537	199	2	knowledge	knowledge	NOUN
fcis-11537	199	3	distillation	distillation	NOUN
fcis-11537	199	4	method	method	NOUN
fcis-11537	199	5	is	be	AUX
fcis-11537	199	6	used	use	VERB
fcis-11537	199	7	to	to	PART
fcis-11537	199	8	make	make	VERB
fcis-11537	199	9	the	the	DET
fcis-11537	199	10	student	student	NOUN
fcis-11537	199	11	network	network	NOUN
fcis-11537	199	12	learn	learn	VERB
fcis-11537	199	13	the	the	DET
fcis-11537	199	14	information	information	NOUN
fcis-11537	199	15	extracted	extract	VERB
fcis-11537	199	16	by	by	ADP
fcis-11537	199	17	the	the	DET
fcis-11537	199	18	teacher	teacher	NOUN
fcis-11537	199	19	network	network	NOUN
fcis-11537	199	20	.	.	PUNCT
fcis-11537	200	1	finally	finally	ADV
fcis-11537	200	2	,	,	PUNCT
fcis-11537	200	3	a	a	DET
fcis-11537	200	4	lightweight	lightweight	ADJ
fcis-11537	200	5	network	network	NOUN
fcis-11537	200	6	with	with	ADP
fcis-11537	200	7	fast	fast	ADJ
fcis-11537	200	8	computing	computing	NOUN
fcis-11537	200	9	speed	speed	NOUN
fcis-11537	200	10	and	and	CCONJ
fcis-11537	200	11	high	high	ADJ
fcis-11537	200	12	accuracy	accuracy	NOUN
fcis-11537	200	13	is	be	AUX
fcis-11537	200	14	obtained	obtain	VERB
fcis-11537	200	15	.	.	PUNCT
fcis-11537	201	1	experimental	experimental	ADJ
fcis-11537	201	2	results	result	NOUN
fcis-11537	201	3	show	show	VERB
fcis-11537	201	4	that	that	SCONJ
fcis-11537	201	5	the	the	DET
fcis-11537	201	6	proposed	propose	VERB
fcis-11537	201	7	method	method	NOUN
fcis-11537	201	8	is	be	AUX
fcis-11537	201	9	fast	fast	ADJ
fcis-11537	201	10	in	in	ADP
fcis-11537	201	11	computation	computation	NOUN
fcis-11537	201	12	and	and	CCONJ
fcis-11537	201	13	high	high	ADJ
fcis-11537	201	14	in	in	ADP
fcis-11537	201	15	recognition	recognition	NOUN
fcis-11537	201	16	accuracy	accuracy	NOUN
fcis-11537	201	17	.	.	PUNCT
fcis-11537	202	1	the	the	DET
fcis-11537	202	2	model	model	NOUN
fcis-11537	202	3	can	can	AUX
fcis-11537	202	4	be	be	AUX
fcis-11537	202	5	used	use	VERB
fcis-11537	202	6	for	for	ADP
fcis-11537	202	7	real	real	ADJ
fcis-11537	202	8	-	-	PUNCT
fcis-11537	202	9	time	time	NOUN
fcis-11537	202	10	analysis	analysis	NOUN
fcis-11537	202	11	.	.	PUNCT
fcis-11537	203	1	it	it	PRON
fcis-11537	203	2	has	have	VERB
fcis-11537	203	3	good	good	ADJ
fcis-11537	203	4	practical	practical	ADJ
fcis-11537	203	5	significance	significance	NOUN
fcis-11537	203	6	for	for	ADP
fcis-11537	203	7	monitoring	monitor	VERB
fcis-11537	203	8	crop	crop	NOUN
fcis-11537	203	9	health	health	NOUN
fcis-11537	203	10	status	status	NOUN
fcis-11537	203	11	.	.	PUNCT
fcis-11537	204	1	references	reference	NOUN
fcis-11537	204	2	[	[	X
fcis-11537	204	3	1	1	NUM
fcis-11537	204	4	]	]	PUNCT
fcis-11537	204	5	m.	m.	NOUN
fcis-11537	204	6	zaccardelli	zaccardelli	PROPN
fcis-11537	204	7	,	,	PUNCT
fcis-11537	204	8	g.	g.	PROPN
fcis-11537	204	9	roscigno	roscigno	PROPN
fcis-11537	204	10	,	,	PUNCT
fcis-11537	204	11	c.	c.	PROPN
fcis-11537	204	12	pane	pane	PROPN
fcis-11537	204	13	.	.	PUNCT
fcis-11537	205	1	essential	essential	ADJ
fcis-11537	205	2	oils	oil	NOUN
fcis-11537	205	3	and	and	CCONJ
fcis-11537	205	4	quality	quality	NOUN
fcis-11537	205	5	composts	compost	NOUN
fcis-11537	205	6	sourced	source	VERB
fcis-11537	205	7	by	by	ADP
fcis-11537	205	8	recycling	recycle	VERB
fcis-11537	205	9	vegetable	vegetable	NOUN
fcis-11537	205	10	residues	residue	NOUN
fcis-11537	205	11	from	from	ADP
fcis-11537	205	12	the	the	DET
fcis-11537	205	13	aromatic	aromatic	ADJ
fcis-11537	205	14	plant	plant	NOUN
fcis-11537	205	15	supply	supply	NOUN
fcis-11537	205	16	chain[j	chain[j	PROPN
fcis-11537	205	17	]	]	PUNCT
fcis-11537	205	18	.	.	PUNCT
fcis-11537	206	1	industrial	industrial	ADJ
fcis-11537	206	2	crops	crop	NOUN
fcis-11537	206	3	and	and	CCONJ
fcis-11537	206	4	products	product	NOUN
fcis-11537	206	5	,	,	PUNCT
fcis-11537	206	6	2021	2021	NUM
fcis-11537	206	7	,	,	PUNCT
fcis-11537	206	8	162:113255	162:113255	NUM
fcis-11537	206	9	.	.	PUNCT
fcis-11537	207	1	[	[	X
fcis-11537	207	2	2	2	X
fcis-11537	207	3	]	]	PUNCT
fcis-11537	207	4	s.	s.	PROPN
fcis-11537	207	5	a.	a.	PROPN
fcis-11537	207	6	a	a	PROPN
fcis-11537	207	7	,	,	PUNCT
fcis-11537	207	8	j.	j.	PROPN
fcis-11537	207	9	s.	s.	PROPN
fcis-11537	207	10	b	b	PROPN
fcis-11537	207	11	,	,	PUNCT
fcis-11537	207	12	m.	m.	PROPN
fcis-11537	207	13	r.	r.	PROPN
fcis-11537	207	14	a.	a.	PROPN
fcis-11537	207	15	demystifying	demystify	VERB
fcis-11537	207	16	artificial	artificial	ADJ
fcis-11537	207	17	intelligence	intelligence	NOUN
fcis-11537	207	18	amidst	amidst	ADP
fcis-11537	207	19	sustainable	sustainable	ADJ
fcis-11537	207	20	agricultural	agricultural	ADJ
fcis-11537	207	21	water	water	NOUN
fcis-11537	207	22	management[j	management[j	NOUN
fcis-11537	207	23	]	]	PUNCT
fcis-11537	207	24	.	.	PUNCT
fcis-11537	208	1	current	current	ADJ
fcis-11537	208	2	directions	direction	NOUN
fcis-11537	208	3	in	in	ADP
fcis-11537	208	4	water	water	NOUN
fcis-11537	208	5	scarcity	scarcity	NOUN
fcis-11537	208	6	research	research	NOUN
fcis-11537	208	7	,	,	PUNCT
fcis-11537	208	8	2022	2022	NUM
fcis-11537	208	9	,	,	PUNCT
fcis-11537	208	10	7:17	7:17	NUM
fcis-11537	208	11	-	-	SYM
fcis-11537	208	12	35	35	NUM
fcis-11537	208	13	.	.	PUNCT
fcis-11537	209	1	[	[	X
fcis-11537	209	2	3	3	X
fcis-11537	209	3	]	]	X
fcis-11537	209	4	c.	c.	PROPN
fcis-11537	209	5	c.	c.	PROPN
fcis-11537	209	6	lee	lee	PROPN
fcis-11537	209	7	,	,	PUNCT
fcis-11537	209	8	h.	h.	PROPN
fcis-11537	209	9	m.	m.	PROPN
fcis-11537	209	10	fazalul	fazalul	PROPN
fcis-11537	209	11	r	r	PROPN
fcis-11537	209	12	,	,	PUNCT
fcis-11537	209	13	l.	l.	PROPN
fcis-11537	209	14	p.	p.	PROPN
fcis-11537	209	15	leow	leow	PROPN
fcis-11537	209	16	.	.	PUNCT
fcis-11537	210	1	a	a	DET
fcis-11537	210	2	deep	deep	ADJ
fcis-11537	210	3	neural	neural	ADJ
fcis-11537	210	4	networks	network	NOUN
fcis-11537	210	5	-	-	PUNCT
fcis-11537	210	6	based	base	VERB
fcis-11537	210	7	image	image	NOUN
fcis-11537	210	8	reconstruction	reconstruction	NOUN
fcis-11537	210	9	algorithm	algorithm	NOUN
fcis-11537	210	10	for	for	ADP
fcis-11537	210	11	a	a	DET
fcis-11537	210	12	reduced	reduce	VERB
fcis-11537	210	13	sensor	sensor	NOUN
fcis-11537	210	14	model	model	NOUN
fcis-11537	210	15	in	in	ADP
fcis-11537	210	16	large	large	ADJ
fcis-11537	210	17	-	-	PUNCT
fcis-11537	210	18	scale	scale	NOUN
fcis-11537	210	19	tomography	tomography	NOUN
fcis-11537	210	20	system	system	NOUN
fcis-11537	210	21	[	[	X
fcis-11537	210	22	j	j	X
fcis-11537	210	23	]	]	X
fcis-11537	210	24	.	.	PUNCT
fcis-11537	211	1	flow	flow	NOUN
fcis-11537	211	2	measurement	measurement	NOUN
fcis-11537	211	3	and	and	CCONJ
fcis-11537	211	4	instrumentation	instrumentation	NOUN
fcis-11537	211	5	,	,	PUNCT
fcis-11537	211	6	2022	2022	NUM
fcis-11537	211	7	.	.	PUNCT
fcis-11537	212	1	[	[	X
fcis-11537	212	2	4	4	X
fcis-11537	212	3	]	]	PUNCT
fcis-11537	212	4	j.	j.	PROPN
fcis-11537	212	5	he	he	PROPN
fcis-11537	212	6	,	,	PUNCT
fcis-11537	212	7	w.	w.	PROPN
fcis-11537	212	8	zhang	zhang	PROPN
fcis-11537	212	9	,	,	PUNCT
fcis-11537	212	10	r.	r.	PROPN
fcis-11537	212	11	shang	shang	PROPN
fcis-11537	212	12	.	.	PUNCT
fcis-11537	213	1	multi	multi	ADJ
fcis-11537	213	2	-	-	ADJ
fcis-11537	213	3	angle	angle	NOUN
fcis-11537	213	4	models	model	NOUN
fcis-11537	213	5	and	and	CCONJ
fcis-11537	213	6	lightweight	lightweight	ADJ
fcis-11537	213	7	unbiased	unbiased	ADJ
fcis-11537	213	8	decoding	decoding	NOUN
fcis-11537	213	9	-	-	PUNCT
fcis-11537	213	10	based	base	VERB
fcis-11537	213	11	algorithm	algorithm	NOUN
fcis-11537	213	12	for	for	ADP
fcis-11537	213	13	human	human	ADJ
fcis-11537	213	14	pose	pose	NOUN
fcis-11537	213	15	estimation	estimation	NOUN
fcis-11537	214	1	[	[	X
fcis-11537	214	2	j	j	X
fcis-11537	214	3	]	]	X
fcis-11537	214	4	.	.	PUNCT
fcis-11537	215	1	international	international	ADJ
fcis-11537	215	2	journal	journal	PROPN
fcis-11537	215	3	of	of	ADP
fcis-11537	215	4	pattern	pattern	NOUN
fcis-11537	215	5	recognition	recognition	NOUN
fcis-11537	215	6	and	and	CCONJ
fcis-11537	215	7	artificial	artificial	ADJ
fcis-11537	215	8	intelligence	intelligence	NOUN
fcis-11537	215	9	,	,	PUNCT
fcis-11537	215	10	2023	2023	NUM
fcis-11537	215	11	,	,	PUNCT
fcis-11537	215	12	37(08	37(08	NUM
fcis-11537	215	13	)	)	PUNCT
fcis-11537	215	14	.	.	PUNCT
fcis-11537	216	1	[	[	X
fcis-11537	216	2	5	5	X
fcis-11537	216	3	]	]	PUNCT
fcis-11537	216	4	z.	z.	PROPN
fcis-11537	216	5	tian	tian	PROPN
fcis-11537	216	6	,	,	PUNCT
fcis-11537	216	7	y.	y.	PROPN
fcis-11537	216	8	wang	wang	PROPN
fcis-11537	216	9	,	,	PUNCT
fcis-11537	216	10	x.	x.	PROPN
fcis-11537	216	11	zhen	zhen	PROPN
fcis-11537	216	12	.	.	PUNCT
fcis-11537	217	1	the	the	DET
fcis-11537	217	2	effect	effect	NOUN
fcis-11537	217	3	of	of	ADP
fcis-11537	217	4	methanol	methanol	NOUN
fcis-11537	217	5	production	production	NOUN
fcis-11537	217	6	and	and	CCONJ
fcis-11537	217	7	application	application	NOUN
fcis-11537	217	8	in	in	ADP
fcis-11537	217	9	internal	internal	ADJ
fcis-11537	217	10	combustion	combustion	NOUN
fcis-11537	217	11	engines	engine	NOUN
fcis-11537	217	12	on	on	ADP
fcis-11537	217	13	emissions	emission	NOUN
fcis-11537	217	14	in	in	ADP
fcis-11537	217	15	the	the	DET
fcis-11537	217	16	context	context	NOUN
fcis-11537	217	17	of	of	ADP
fcis-11537	217	18	carbon	carbon	NOUN
fcis-11537	217	19	neutrality	neutrality	NOUN
fcis-11537	217	20	:	:	PUNCT
fcis-11537	217	21	a	a	DET
fcis-11537	217	22	review[j	review[j	PROPN
fcis-11537	217	23	]	]	PUNCT
fcis-11537	217	24	.	.	PUNCT
fcis-11537	218	1	fuel	fuel	NOUN
fcis-11537	218	2	:	:	PUNCT
fcis-11537	218	3	a	a	DET
fcis-11537	218	4	journal	journal	NOUN
fcis-11537	218	5	of	of	ADP
fcis-11537	218	6	fuel	fuel	NOUN
fcis-11537	218	7	science	science	NOUN
fcis-11537	218	8	,	,	PUNCT
fcis-11537	218	9	2022(jul.15):320	2022(jul.15):320	NUM
fcis-11537	218	10	.	.	PUNCT
fcis-11537	219	1	[	[	X
fcis-11537	219	2	6	6	NUM
fcis-11537	219	3	]	]	X
fcis-11537	219	4	y.	y.	PROPN
fcis-11537	219	5	sun	sun	PROPN
fcis-11537	219	6	,	,	PUNCT
fcis-11537	219	7	z.	z.	PROPN
fcis-11537	219	8	jiang	jiang	PROPN
fcis-11537	219	9	,	,	PUNCT
fcis-11537	219	10	l.	l.	PROPN
fcis-11537	219	11	zhang	zhang	PROPN
fcis-11537	219	12	.	.	PUNCT
fcis-11537	220	1	slic_svm	slic_svm	PROPN
fcis-11537	220	2	based	base	VERB
fcis-11537	220	3	leaf	leaf	NOUN
fcis-11537	220	4	diseases	disease	NOUN
fcis-11537	220	5	saliency	saliency	NOUN
fcis-11537	220	6	map	map	NOUN
fcis-11537	220	7	extraction	extraction	NOUN
fcis-11537	220	8	of	of	ADP
fcis-11537	220	9	tea	tea	NOUN
fcis-11537	220	10	plant[j	plant[j	NOUN
fcis-11537	220	11	]	]	PUNCT
fcis-11537	220	12	.	.	PUNCT
fcis-11537	221	1	computers	computer	NOUN
fcis-11537	221	2	and	and	CCONJ
fcis-11537	221	3	electronics	electronic	NOUN
fcis-11537	221	4	in	in	ADP
fcis-11537	221	5	agriculture	agriculture	NOUN
fcis-11537	221	6	,	,	PUNCT
fcis-11537	221	7	2019	2019	NUM
fcis-11537	221	8	,	,	PUNCT
fcis-11537	221	9	157:102	157:102	NUM
fcis-11537	221	10	-	-	SYM
fcis-11537	221	11	109	109	NUM
fcis-11537	221	12	.	.	PUNCT
fcis-11537	222	1	[	[	X
fcis-11537	222	2	7	7	X
fcis-11537	222	3	]	]	PUNCT
fcis-11537	222	4	a.	a.	NOUN
fcis-11537	222	5	a.	a.	NOUN
fcis-11537	222	6	basavaiah	basavaiah	PROPN
fcis-11537	222	7	j	j	PROPN
fcis-11537	222	8	a.	a.	NOUN
fcis-11537	222	9	tomato	tomato	NOUN
fcis-11537	222	10	leaf	leaf	NOUN
fcis-11537	222	11	disease	disease	NOUN
fcis-11537	222	12	classification	classification	NOUN
fcis-11537	222	13	using	use	VERB
fcis-11537	222	14	multiple	multiple	ADJ
fcis-11537	222	15	feature	feature	NOUN
fcis-11537	222	16	extraction	extraction	NOUN
fcis-11537	222	17	techniques[j	techniques[j	NOUN
fcis-11537	222	18	]	]	PUNCT
fcis-11537	222	19	.	.	PUNCT
fcis-11537	223	1	wireless	wireless	ADJ
fcis-11537	223	2	personal	personal	ADJ
fcis-11537	223	3	communications	communication	NOUN
fcis-11537	223	4	:	:	PUNCT
fcis-11537	223	5	an	an	DET
fcis-11537	223	6	internaional	internaional	ADJ
fcis-11537	223	7	journal	journal	NOUN
fcis-11537	223	8	,	,	PUNCT
fcis-11537	223	9	2020	2020	NUM
fcis-11537	223	10	,	,	PUNCT
fcis-11537	223	11	115(1	115(1	NUM
fcis-11537	223	12	)	)	PUNCT
fcis-11537	223	13	.	.	PUNCT
fcis-11537	224	1	[	[	X
fcis-11537	224	2	8	8	X
fcis-11537	224	3	]	]	PUNCT
fcis-11537	224	4	j.	j.	PROPN
fcis-11537	224	5	suto	suto	PROPN
fcis-11537	224	6	.	.	PUNCT
fcis-11537	225	1	plant	plant	NOUN
fcis-11537	225	2	leaf	leaf	NOUN
fcis-11537	225	3	recognition	recognition	NOUN
fcis-11537	225	4	with	with	ADP
fcis-11537	225	5	shallow	shallow	ADJ
fcis-11537	225	6	and	and	CCONJ
fcis-11537	225	7	deep	deep	ADJ
fcis-11537	225	8	learning	learning	NOUN
fcis-11537	225	9	:	:	PUNCT
fcis-11537	225	10	a	a	DET
fcis-11537	225	11	comprehensive	comprehensive	ADJ
fcis-11537	225	12	study[j	study[j	NOUN
fcis-11537	225	13	]	]	PUNCT
fcis-11537	225	14	.	.	PUNCT
fcis-11537	226	1	intelligent	intelligent	ADJ
fcis-11537	226	2	data	datum	NOUN
fcis-11537	226	3	analysis	analysis	NOUN
fcis-11537	226	4	,	,	PUNCT
fcis-11537	226	5	2020	2020	NUM
fcis-11537	226	6	(	(	PUNCT
fcis-11537	226	7	6):24	6):24	NUM
fcis-11537	226	8	.	.	PUNCT
fcis-11537	227	1	[	[	X
fcis-11537	227	2	9	9	NUM
fcis-11537	227	3	]	]	PUNCT
fcis-11537	227	4	a.	a.	NOUN
fcis-11537	227	5	nigam	nigam	PROPN
fcis-11537	227	6	,	,	PUNCT
fcis-11537	227	7	a.	a.	PROPN
fcis-11537	227	8	k.	k.	PROPN
fcis-11537	227	9	tiwari	tiwari	PROPN
fcis-11537	227	10	,	,	PUNCT
fcis-11537	227	11	a.	a.	PROPN
fcis-11537	227	12	pandey	pandey	PROPN
fcis-11537	227	13	.	.	PUNCT
fcis-11537	227	14	paddy	paddy	NOUN
fcis-11537	227	15	leaf	leaf	NOUN
fcis-11537	227	16	diseases	disease	NOUN
fcis-11537	227	17	recognition	recognition	NOUN
fcis-11537	227	18	and	and	CCONJ
fcis-11537	227	19	classification	classification	NOUN
fcis-11537	227	20	using	use	VERB
fcis-11537	227	21	pca	pca	PROPN
fcis-11537	227	22	and	and	CCONJ
fcis-11537	227	23	bfo	bfo	PROPN
fcis-11537	227	24	-	-	PUNCT
fcis-11537	227	25	dnn	dnn	PROPN
fcis-11537	227	26	algorithm	algorithm	NOUN
fcis-11537	227	27	by	by	ADP
fcis-11537	227	28	image	image	NOUN
fcis-11537	227	29	processing	processing	NOUN
fcis-11537	227	30	[	[	X
fcis-11537	227	31	j	j	X
fcis-11537	227	32	]	]	X
fcis-11537	227	33	.	.	PUNCT
fcis-11537	228	1	materials	material	NOUN
fcis-11537	228	2	today	today	NOUN
fcis-11537	228	3	:	:	PUNCT
fcis-11537	228	4	proceedings	proceeding	NOUN
fcis-11537	228	5	,	,	PUNCT
fcis-11537	228	6	2020	2020	NUM
fcis-11537	228	7	,	,	PUNCT
fcis-11537	228	8	33(3	33(3	NOUN
fcis-11537	228	9	)	)	PUNCT
fcis-11537	228	10	.	.	PUNCT
fcis-11537	229	1	[	[	X
fcis-11537	229	2	10	10	NUM
fcis-11537	229	3	]	]	PUNCT
fcis-11537	229	4	z.	z.	PROPN
fcis-11537	229	5	jiang	jiang	PROPN
fcis-11537	229	6	,	,	PUNCT
fcis-11537	229	7	z.	z.	PROPN
fcis-11537	229	8	dong	dong	PROPN
fcis-11537	229	9	,	,	PUNCT
fcis-11537	229	10	w.	w.	PROPN
fcis-11537	229	11	jiang	jiang	PROPN
fcis-11537	229	12	,	,	PUNCT
fcis-11537	229	13	et	et	PROPN
fcis-11537	229	14	al	al	PROPN
fcis-11537	229	15	.	.	PUNCT
fcis-11537	229	16	recognition	recognition	NOUN
fcis-11537	229	17	of	of	ADP
fcis-11537	229	18	rice	rice	NOUN
fcis-11537	229	19	leaf	leaf	NOUN
fcis-11537	229	20	diseases	disease	NOUN
fcis-11537	229	21	and	and	CCONJ
fcis-11537	229	22	wheat	wheat	NOUN
fcis-11537	229	23	leaf	leaf	NOUN
fcis-11537	229	24	diseases	disease	NOUN
fcis-11537	229	25	based	base	VERB
fcis-11537	229	26	on	on	ADP
fcis-11537	229	27	multi	multi	ADJ
fcis-11537	229	28	-	-	ADJ
fcis-11537	229	29	task	task	ADJ
fcis-11537	229	30	deep	deep	ADJ
fcis-11537	229	31	transfer	transfer	NOUN
fcis-11537	229	32	learning	learn	VERB
fcis-11537	230	1	[	[	X
fcis-11537	230	2	j	j	X
fcis-11537	230	3	]	]	X
fcis-11537	230	4	.	.	PUNCT
fcis-11537	231	1	computers	computer	NOUN
fcis-11537	231	2	and	and	CCONJ
fcis-11537	231	3	electronics	electronic	NOUN
fcis-11537	231	4	in	in	ADP
fcis-11537	231	5	agriculture	agriculture	NOUN
fcis-11537	231	6	,	,	PUNCT
fcis-11537	231	7	2021	2021	NUM
fcis-11537	231	8	,	,	PUNCT
fcis-11537	231	9	186:106184-	186:106184-	NUM
fcis-11537	231	10	.	.	PUNCT
fcis-11537	232	1	[	[	X
fcis-11537	232	2	11	11	NUM
fcis-11537	232	3	]	]	PUNCT
fcis-11537	232	4	s.	s.	PROPN
fcis-11537	232	5	k.	k.	PROPN
fcis-11537	232	6	noon	noon	PROPN
fcis-11537	232	7	,	,	PUNCT
fcis-11537	232	8	m.	m.	PROPN
fcis-11537	232	9	amjad	amjad	PROPN
fcis-11537	232	10	,	,	PUNCT
fcis-11537	232	11	m.	m.	PROPN
fcis-11537	232	12	a.	a.	PROPN
fcis-11537	232	13	qureshi	qureshi	PROPN
fcis-11537	232	14	,	,	PUNCT
fcis-11537	232	15	et	et	PROPN
fcis-11537	232	16	al	al	PROPN
fcis-11537	232	17	.	.	PUNCT
fcis-11537	232	18	computationally	computationally	ADV
fcis-11537	232	19	light	light	ADJ
fcis-11537	232	20	deep	deep	ADJ
fcis-11537	232	21	learning	learning	NOUN
fcis-11537	232	22	framework	framework	NOUN
fcis-11537	232	23	to	to	PART
fcis-11537	232	24	recognize	recognize	VERB
fcis-11537	232	25	cotton	cotton	NOUN
fcis-11537	232	26	leaf	leaf	NOUN
fcis-11537	232	27	diseases	disease	NOUN
fcis-11537	233	1	[	[	X
fcis-11537	233	2	j	j	X
fcis-11537	233	3	]	]	X
fcis-11537	233	4	.	.	PUNCT
fcis-11537	234	1	journal	journal	PROPN
fcis-11537	234	2	of	of	ADP
fcis-11537	234	3	intelligent	intelligent	ADJ
fcis-11537	234	4	&	&	CCONJ
fcis-11537	234	5	fuzzy	fuzzy	ADJ
fcis-11537	234	6	systems	system	NOUN
fcis-11537	234	7	:	:	PUNCT
fcis-11537	234	8	applications	application	NOUN
fcis-11537	234	9	in	in	ADP
fcis-11537	234	10	engineering	engineering	NOUN
fcis-11537	234	11	and	and	CCONJ
fcis-11537	234	12	technology	technology	NOUN
fcis-11537	234	13	,	,	PUNCT
fcis-11537	234	14	2021(6):40	2021(6):40	NUM
fcis-11537	234	15	.	.	PUNCT
fcis-11537	235	1	[	[	X
fcis-11537	235	2	12	12	NUM
fcis-11537	235	3	]	]	PUNCT
fcis-11537	235	4	w.	w.	PROPN
fcis-11537	235	5	zeng	zeng	PROPN
fcis-11537	235	6	,	,	PUNCT
fcis-11537	235	7	h.	h.	PROPN
fcis-11537	235	8	li	li	PROPN
fcis-11537	235	9	,	,	PUNCT
fcis-11537	235	10	g.	g.	PROPN
fcis-11537	235	11	hu	hu	PROPN
fcis-11537	235	12	,	,	PUNCT
fcis-11537	235	13	et	et	PROPN
fcis-11537	235	14	al	al	PROPN
fcis-11537	235	15	.	.	PUNCT
fcis-11537	235	16	lightweight	lightweight	ADJ
fcis-11537	235	17	dense	dense	ADJ
fcis-11537	235	18	-	-	PUNCT
fcis-11537	235	19	scale	scale	NOUN
fcis-11537	235	20	network	network	NOUN
fcis-11537	235	21	(	(	PUNCT
fcis-11537	235	22	ldsnet	ldsnet	NOUN
fcis-11537	235	23	)	)	PUNCT
fcis-11537	235	24	for	for	ADP
fcis-11537	235	25	corn	corn	NOUN
fcis-11537	235	26	leaf	leaf	NOUN
fcis-11537	235	27	disease	disease	NOUN
fcis-11537	235	28	identification[j	identification[j	PROPN
fcis-11537	235	29	]	]	PUNCT
fcis-11537	235	30	.	.	PUNCT
fcis-11537	236	1	computers	computer	NOUN
fcis-11537	236	2	and	and	CCONJ
fcis-11537	236	3	electronics	electronic	NOUN
fcis-11537	236	4	in	in	ADP
fcis-11537	236	5	agriculture	agriculture	NOUN
fcis-11537	236	6	,	,	PUNCT
fcis-11537	236	7	2022	2022	NUM
fcis-11537	236	8	.	.	PUNCT
fcis-11537	237	1	[	[	X
fcis-11537	237	2	13	13	NUM
fcis-11537	237	3	]	]	PUNCT
fcis-11537	237	4	z.	z.	PROPN
fcis-11537	237	5	wang	wang	PROPN
fcis-11537	237	6	,	,	PUNCT
fcis-11537	237	7	j.	j.	PROPN
fcis-11537	237	8	guo	guo	PROPN
fcis-11537	237	9	,	,	PUNCT
fcis-11537	237	10	s.	s.	PROPN
fcis-11537	237	11	zhang	zhang	PROPN
fcis-11537	237	12	.	.	PUNCT
fcis-11537	238	1	lightweight	lightweight	ADJ
fcis-11537	238	2	convolution	convolution	NOUN
fcis-11537	238	3	neural	neural	ADJ
fcis-11537	238	4	network	network	NOUN
fcis-11537	238	5	based	base	VERB
fcis-11537	238	6	on	on	ADP
fcis-11537	238	7	multi	multi	ADJ
fcis-11537	238	8	-	-	ADJ
fcis-11537	238	9	scale	scale	ADJ
fcis-11537	238	10	parallel	parallel	ADJ
fcis-11537	238	11	fusion	fusion	NOUN
fcis-11537	238	12	for	for	ADP
fcis-11537	238	13	weed	weed	NOUN
fcis-11537	238	14	identification[j	identification[j	PROPN
fcis-11537	238	15	]	]	PUNCT
fcis-11537	238	16	.	.	PUNCT
fcis-11537	239	1	international	international	ADJ
fcis-11537	239	2	journal	journal	PROPN
fcis-11537	239	3	of	of	ADP
fcis-11537	239	4	pattern	pattern	NOUN
fcis-11537	239	5	recognition	recognition	NOUN
fcis-11537	239	6	and	and	CCONJ
fcis-11537	239	7	artificial	artificial	ADJ
fcis-11537	239	8	intelligence	intelligence	NOUN
fcis-11537	239	9	,	,	PUNCT
fcis-11537	239	10	2022	2022	NUM
fcis-11537	239	11	.	.	PUNCT
fcis-11537	240	1	[	[	X
fcis-11537	240	2	14	14	NUM
fcis-11537	240	3	]	]	X
fcis-11537	240	4	m.	m.	PROPN
fcis-11537	240	5	jia	jia	PROPN
fcis-11537	240	6	,	,	PUNCT
fcis-11537	240	7	m.	m.	PROPN
fcis-11537	240	8	dong	dong	PROPN
fcis-11537	240	9	.	.	PUNCT
fcis-11537	241	1	analysis	analysis	NOUN
fcis-11537	241	2	and	and	CCONJ
fcis-11537	241	3	comparison	comparison	NOUN
fcis-11537	241	4	of	of	ADP
fcis-11537	241	5	gaussian	gaussian	ADJ
fcis-11537	241	6	noise	noise	NOUN
fcis-11537	241	7	denoising	denoise	VERB
fcis-11537	241	8	algorithms[j	algorithms[j	PROPN
fcis-11537	241	9	]	]	X
fcis-11537	241	10	.	.	PUNCT
fcis-11537	242	1	journal	journal	PROPN
fcis-11537	242	2	of	of	ADP
fcis-11537	242	3	physics	physics	PROPN
fcis-11537	242	4	conference	conference	NOUN
fcis-11537	242	5	series	series	NOUN
fcis-11537	242	6	,	,	PUNCT
fcis-11537	242	7	2021	2021	NUM
fcis-11537	242	8	,	,	PUNCT
fcis-11537	242	9	1846(1):012069	1846(1):012069	NUM
fcis-11537	242	10	.	.	PUNCT
fcis-11537	243	1	[	[	X
fcis-11537	243	2	15	15	NUM
fcis-11537	243	3	]	]	X
fcis-11537	243	4	m.	m.	NOUN
fcis-11537	243	5	suresha	suresha	PROPN
fcis-11537	243	6	,	,	PUNCT
fcis-11537	243	7	d.	d.	PROPN
fcis-11537	243	8	s.	s.	PROPN
fcis-11537	243	9	raghukumar	raghukumar	PROPN
fcis-11537	243	10	,	,	PUNCT
fcis-11537	243	11	s.	s.	PROPN
fcis-11537	243	12	kuppa	kuppa	PROPN
fcis-11537	243	13	.	.	PUNCT
fcis-11537	244	1	kumaraswamy	kumaraswamy	ADJ
fcis-11537	244	2	distribution	distribution	NOUN
fcis-11537	244	3	based	base	VERB
fcis-11537	244	4	bi	bi	ADJ
fcis-11537	244	5	-	-	ADJ
fcis-11537	244	6	histogram	histogram	NOUN
fcis-11537	244	7	equalization	equalization	NOUN
fcis-11537	244	8	for	for	ADP
fcis-11537	244	9	enhancement	enhancement	NOUN
fcis-11537	244	10	of	of	ADP
fcis-11537	244	11	microscopic	microscopic	ADJ
fcis-11537	244	12	images[j	images[j	PROPN
fcis-11537	244	13	]	]	PUNCT
fcis-11537	244	14	.	.	PUNCT
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fcis-11537	245	2	journal	journal	PROPN
fcis-11537	245	3	of	of	ADP
fcis-11537	245	4	image	image	NOUN
fcis-11537	245	5	and	and	CCONJ
fcis-11537	245	6	graphics	graphic	NOUN
fcis-11537	245	7	,	,	PUNCT
fcis-11537	245	8	2022(1):22	2022(1):22	NUM
fcis-11537	245	9	.	.	PUNCT
fcis-11537	246	1	[	[	X
fcis-11537	246	2	16	16	NUM
fcis-11537	246	3	]	]	PUNCT
fcis-11537	246	4	p.	p.	PROPN
fcis-11537	246	5	kora	kora	PROPN
fcis-11537	246	6	,	,	PUNCT
fcis-11537	246	7	c.	c.	PROPN
fcis-11537	246	8	p.	p.	PROPN
fcis-11537	246	9	ooi	ooi	PROPN
fcis-11537	246	10	,	,	PUNCT
fcis-11537	246	11	o.	o.	PROPN
fcis-11537	246	12	faust	faust	PROPN
fcis-11537	246	13	.	.	PUNCT
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fcis-11537	247	2	learning	learn	VERB
fcis-11537	247	3	techniques	technique	NOUN
fcis-11537	247	4	for	for	ADP
fcis-11537	247	5	medical	medical	ADJ
fcis-11537	247	6	image	image	NOUN
fcis-11537	247	7	analysis	analysis	NOUN
fcis-11537	247	8	:	:	PUNCT
fcis-11537	247	9	a	a	DET
fcis-11537	247	10	review[j	review[j	PROPN
fcis-11537	247	11	]	]	PUNCT
fcis-11537	247	12	.	.	PUNCT
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fcis-11537	247	14	and	and	CCONJ
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fcis-11537	247	16	engineering	engineering	NOUN
fcis-11537	247	17	/	/	SYM
fcis-11537	247	18	,	,	PUNCT
fcis-11537	247	19	2022(1):42	2022(1):42	NUM
fcis-11537	247	20	.	.	PUNCT
fcis-11537	248	1	[	[	X
fcis-11537	248	2	17	17	NUM
fcis-11537	248	3	]	]	PUNCT
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fcis-11537	248	5	borup	borup	PROPN
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fcis-11537	248	7	p.	p.	PROPN
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fcis-11537	248	9	,	,	PUNCT
fcis-11537	248	10	h.	h.	PROPN
fcis-11537	248	11	phan	phan	PROPN
fcis-11537	248	12	,	,	PUNCT
fcis-11537	248	13	et	et	PROPN
fcis-11537	248	14	al	al	PROPN
fcis-11537	248	15	.	.	PROPN
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fcis-11537	248	17	sleep	sleep	NOUN
fcis-11537	248	18	scoring	score	VERB
fcis-11537	248	19	using	use	VERB
fcis-11537	248	20	patient	patient	NOUN
fcis-11537	248	21	-	-	PUNCT
fcis-11537	248	22	specific	specific	ADJ
fcis-11537	248	23	ensemble	ensemble	ADJ
fcis-11537	248	24	models	model	NOUN
fcis-11537	248	25	and	and	CCONJ
fcis-11537	248	26	knowledge	knowledge	NOUN
fcis-11537	248	27	distillation	distillation	NOUN
fcis-11537	248	28	for	for	ADP
fcis-11537	248	29	ear	ear	NOUN
fcis-11537	248	30	-	-	PUNCT
fcis-11537	248	31	eeg	eeg	NOUN
fcis-11537	248	32	data[j	data[j	NOUN
fcis-11537	248	33	]	]	PUNCT
fcis-11537	248	34	.	.	PUNCT
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fcis-11537	249	2	signal	signal	NOUN
fcis-11537	249	3	processing	processing	NOUN
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fcis-11537	249	5	control	control	NOUN
fcis-11537	249	6	,	,	PUNCT
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fcis-11537	249	8	.	.	PUNCT
fcis-11537	250	1	[	[	X
fcis-11537	250	2	18	18	NUM
fcis-11537	250	3	]	]	X
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fcis-11537	250	5	xu	xu	PROPN
fcis-11537	250	6	,	,	PUNCT
fcis-11537	250	7	b.	b.	PROPN
fcis-11537	250	8	zhou	zhou	PROPN
fcis-11537	250	9	,	,	PUNCT
fcis-11537	251	1	x.	x.	PROPN
fcis-11537	251	2	li	li	PROPN
fcis-11537	251	3	.	.	PROPN
fcis-11537	251	4	gaussian	gaussian	ADJ
fcis-11537	251	5	process	process	NOUN
fcis-11537	251	6	image	image	NOUN
fcis-11537	251	7	classification	classification	NOUN
fcis-11537	251	8	based	base	VERB
fcis-11537	251	9	on	on	ADP
fcis-11537	251	10	multi	multi	ADJ
fcis-11537	251	11	-	-	ADJ
fcis-11537	251	12	layer	layer	ADJ
fcis-11537	251	13	convolution	convolution	NOUN
fcis-11537	251	14	kernel	kernel	PROPN
fcis-11537	251	15	function[j	function[j	PROPN
fcis-11537	251	16	]	]	PUNCT
fcis-11537	251	17	.	.	PUNCT
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fcis-11537	252	2	,	,	PUNCT
fcis-11537	252	3	2022(apr.1):480	2022(apr.1):480	NUM
fcis-11537	252	4	.	.	PUNCT
fcis-11537	253	1	[	[	X
fcis-11537	253	2	19	19	NUM
fcis-11537	253	3	]	]	PUNCT
fcis-11537	253	4	x.	x.	NOUN
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fcis-11537	253	6	,	,	PUNCT
fcis-11537	253	7	y.	y.	PROPN
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fcis-11537	253	9	,	,	PUNCT
fcis-11537	253	10	x.	x.	NOUN
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fcis-11537	253	12	.	.	PUNCT
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fcis-11537	254	2	spoof	spoof	ADJ
fcis-11537	254	3	plasmonic	plasmonic	NOUN
fcis-11537	254	4	coupler	coupler	NOUN
fcis-11537	254	5	for	for	ADP
fcis-11537	254	6	dynamic	dynamic	ADJ
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fcis-11537	254	8	between	between	ADP
fcis-11537	254	9	forward	forward	ADJ
fcis-11537	254	10	and	and	CCONJ
fcis-11537	254	11	backward	backward	ADJ
fcis-11537	254	12	propagations[j	propagations[j	NOUN
fcis-11537	254	13	]	]	PUNCT
fcis-11537	254	14	.	.	PUNCT
fcis-11537	255	1	advanced	advanced	ADJ
fcis-11537	255	2	materials	material	NOUN
fcis-11537	255	3	technologies	technology	NOUN
fcis-11537	255	4	,	,	PUNCT
fcis-11537	255	5	2022	2022	NUM
fcis-11537	255	6	.	.	PUNCT
fcis-11537	256	1	[	[	X
fcis-11537	256	2	20	20	NUM
fcis-11537	256	3	]	]	PUNCT
fcis-11537	256	4	j.	j.	PROPN
fcis-11537	256	5	qiu	qiu	PROPN
fcis-11537	256	6	,	,	PUNCT
fcis-11537	256	7	x.	x.	PROPN
fcis-11537	256	8	lu	lu	PROPN
fcis-11537	256	9	,	,	PUNCT
fcis-11537	256	10	x.	x.	PROPN
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fcis-11537	256	12	,	,	PUNCT
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fcis-11537	256	14	al	al	PROPN
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fcis-11537	256	17	on	on	ADP
fcis-11537	256	18	rice	rice	NOUN
fcis-11537	256	19	disease	disease	NOUN
fcis-11537	256	20	identification	identification	NOUN
fcis-11537	256	21	model	model	NOUN
fcis-11537	256	22	based	base	VERB
fcis-11537	256	23	on	on	ADP
fcis-11537	256	24	migration	migration	NOUN
fcis-11537	256	25	learning	learning	NOUN
fcis-11537	256	26	in	in	ADP
fcis-11537	256	27	vgg	vgg	PROPN
fcis-11537	256	28	network[j	network[j	PROPN
fcis-11537	256	29	]	]	PUNCT
fcis-11537	256	30	.	.	PUNCT
fcis-11537	257	1	iop	iop	PROPN
fcis-11537	257	2	conference	conference	PROPN
fcis-11537	257	3	series	series	PROPN
fcis-11537	257	4	:	:	PUNCT
fcis-11537	257	5	earth	earth	NOUN
fcis-11537	257	6	and	and	CCONJ
fcis-11537	257	7	environmental	environmental	ADJ
fcis-11537	257	8	science	science	NOUN
fcis-11537	257	9	,	,	PUNCT
fcis-11537	257	10	2021	2021	NUM
fcis-11537	257	11	,	,	PUNCT
fcis-11537	257	12	680(1):012087	680(1):012087	NUM
fcis-11537	257	13	(	(	PUNCT
fcis-11537	257	14	10pp	10pp	NOUN
fcis-11537	257	15	)	)	PUNCT
fcis-11537	257	16	.	.	PUNCT
fcis-11537	258	1	[	[	X
fcis-11537	258	2	21	21	NUM
fcis-11537	258	3	]	]	PUNCT
fcis-11537	258	4	j.	j.	PROPN
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fcis-11537	258	7	l.	l.	PROPN
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fcis-11537	258	10	j.	j.	PROPN
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fcis-11537	258	12	.	.	PUNCT
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fcis-11537	259	2	mri	mri	NOUN
fcis-11537	259	3	glioma	glioma	NOUN
fcis-11537	259	4	segmentation	segmentation	NOUN
fcis-11537	259	5	via	via	ADP
fcis-11537	259	6	multiple	multiple	ADJ
fcis-11537	259	7	guidances	guidance	NOUN
fcis-11537	259	8	and	and	CCONJ
fcis-11537	259	9	hybrid	hybrid	ADJ
fcis-11537	259	10	enhanced	enhance	VERB
fcis-11537	259	11	-	-	PUNCT
fcis-11537	259	12	gradient	gradient	NOUN
fcis-11537	259	13	crossentropy	crossentropy	NOUN
fcis-11537	259	14	loss[j	loss[j	PROPN
fcis-11537	259	15	]	]	PUNCT
fcis-11537	259	16	.	.	PUNCT
fcis-11537	260	1	expert	expert	NOUN
fcis-11537	260	2	systems	system	NOUN
fcis-11537	260	3	with	with	ADP
fcis-11537	260	4	application	application	NOUN
fcis-11537	260	5	,	,	PUNCT
fcis-11537	260	6	2022	2022	NUM
fcis-11537	260	7	(	(	PUNCT
fcis-11537	260	8	jun	jun	PROPN
fcis-11537	260	9	.	.	PROPN
fcis-11537	260	10	):	):	PUNCT
fcis-11537	260	11	196	196	NUM
fcis-11537	260	12	.	.	PUNCT
fcis-11537	261	1	[	[	X
fcis-11537	261	2	22	22	NUM
fcis-11537	261	3	]	]	PUNCT
fcis-11537	261	4	h.	h.	PROPN
fcis-11537	261	5	q.	q.	PROPN
fcis-11537	261	6	mu	mu	PROPN
fcis-11537	261	7	,	,	PUNCT
fcis-11537	261	8	j.	j.	PROPN
fcis-11537	261	9	h.	h.	PROPN
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fcis-11537	261	13	t.	t.	PROPN
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fcis-11537	261	16	et	et	PROPN
fcis-11537	261	17	al	al	PROPN
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fcis-11537	262	1	a	a	DET
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fcis-11537	262	4	approach	approach	NOUN
fcis-11537	262	5	for	for	ADP
fcis-11537	262	6	modal	modal	ADJ
fcis-11537	262	7	frequency	frequency	NOUN
fcis-11537	262	8	probabilistic	probabilistic	ADJ
fcis-11537	262	9	prediction	prediction	NOUN
fcis-11537	262	10	under	under	ADP
fcis-11537	262	11	varying	vary	VERB
fcis-11537	262	12	environmental	environmental	ADJ
fcis-11537	262	13	condition	condition	NOUN
fcis-11537	262	14	using	use	VERB
fcis-11537	262	15	incomplete	incomplete	ADJ
fcis-11537	262	16	information	information	NOUN
fcis-11537	263	1	[	[	X
fcis-11537	263	2	j	j	X
fcis-11537	263	3	]	]	X
fcis-11537	263	4	.	.	PUNCT
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fcis-11537	264	2	structures	structure	NOUN
fcis-11537	264	3	,	,	PUNCT
fcis-11537	264	4	2022	2022	NUM
fcis-11537	264	5	,	,	PUNCT
fcis-11537	264	6	252:113571-	252:113571-	NUM
fcis-11537	264	7	.	.	PUNCT
fcis-11537	265	1	[	[	X
fcis-11537	265	2	23	23	NUM
fcis-11537	265	3	]	]	X
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fcis-11537	265	5	e.	e.	PROPN
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fcis-11537	265	8	l.	l.	PROPN
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fcis-11537	265	12	,	,	PUNCT
fcis-11537	265	13	l.	l.	PROPN
fcis-11537	265	14	i.	i.	PROPN
fcis-11537	265	15	hai	hai	PROPN
fcis-11537	265	16	-	-	PUNCT
fcis-11537	265	17	tao	tao	PROPN
fcis-11537	265	18	.	.	PUNCT
fcis-11537	266	1	research	research	NOUN
fcis-11537	266	2	on	on	ADP
fcis-11537	266	3	mesoscale	mesoscale	ADJ
fcis-11537	266	4	vortex	vortex	NOUN
fcis-11537	266	5	feature	feature	NOUN
fcis-11537	266	6	extraction	extraction	NOUN
fcis-11537	266	7	algorithm	algorithm	NOUN
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fcis-11537	266	9	visualization[j	visualization[j	NOUN
fcis-11537	266	10	]	]	PUNCT
fcis-11537	266	11	.	.	PUNCT
fcis-11537	267	1	computer	computer	NOUN
fcis-11537	267	2	systems	system	NOUN
fcis-11537	267	3	&	&	CCONJ
fcis-11537	267	4	applications	application	NOUN
fcis-11537	267	5	,	,	PUNCT
fcis-11537	267	6	2018	2018	NUM
fcis-11537	267	7	.	.	PUNCT
fcis-11537	268	1	[	[	X
fcis-11537	268	2	24	24	NUM
fcis-11537	268	3	]	]	X
fcis-11537	268	4	y.	y.	PROPN
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fcis-11537	268	6	,	,	PUNCT
fcis-11537	268	7	y.	y.	PROPN
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fcis-11537	268	10	y.	y.	PROPN
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fcis-11537	268	13	et	et	PROPN
fcis-11537	268	14	al	al	PROPN
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fcis-11537	269	2	reinforcement	reinforcement	NOUN
fcis-11537	269	3	learning	learning	NOUN
fcis-11537	269	4	with	with	ADP
fcis-11537	269	5	the	the	DET
fcis-11537	269	6	confusion	confusion	NOUN
fcis-11537	269	7	-	-	PUNCT
fcis-11537	269	8	matrix	matrix	NOUN
fcis-11537	269	9	-	-	PUNCT
fcis-11537	269	10	based	base	VERB
fcis-11537	269	11	dynamic	dynamic	ADJ
fcis-11537	269	12	reward	reward	NOUN
fcis-11537	269	13	function	function	NOUN
fcis-11537	269	14	for	for	ADP
fcis-11537	269	15	customer	customer	NOUN
fcis-11537	269	16	credit	credit	NOUN
fcis-11537	269	17	scoring[j	scoring[j	NOUN
fcis-11537	269	18	]	]	PUNCT
fcis-11537	269	19	.	.	PUNCT
fcis-11537	270	1	expert	expert	NOUN
fcis-11537	270	2	systems	system	NOUN
fcis-11537	270	3	with	with	ADP
fcis-11537	270	4	application	application	NOUN
fcis-11537	270	5	,	,	PUNCT
fcis-11537	270	6	2022(aug.):200	2022(aug.):200	NUM
fcis-11537	270	7	.	.	PUNCT
fcis-11537	271	1	[	[	X
fcis-11537	271	2	25	25	NUM
fcis-11537	271	3	]	]	X
fcis-11537	271	4	h.	h.	PROPN
fcis-11537	271	5	liu	liu	PROPN
fcis-11537	271	6	,	,	PUNCT
fcis-11537	271	7	j.	j.	PROPN
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fcis-11537	271	9	,	,	PUNCT
fcis-11537	271	10	m.	m.	NOUN
fcis-11537	271	11	ye	ye	PROPN
fcis-11537	271	12	,	,	PUNCT
fcis-11537	271	13	et	et	PROPN
fcis-11537	271	14	al	al	PROPN
fcis-11537	271	15	.	.	PUNCT
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fcis-11537	271	17	t	t	NOUN
fcis-11537	271	18	-	-	PUNCT
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fcis-11537	271	20	stochastic	stochastic	ADJ
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fcis-11537	271	22	embedding	embed	VERB
fcis-11537	271	23	(	(	PUNCT
fcis-11537	271	24	t	t	PROPN
fcis-11537	271	25	-	-	PUNCT
fcis-11537	271	26	sne	sne	NOUN
fcis-11537	271	27	)	)	PUNCT
fcis-11537	271	28	for	for	ADP
fcis-11537	271	29	cluster	cluster	NOUN
fcis-11537	271	30	analysis	analysis	NOUN
fcis-11537	271	31	and	and	CCONJ
fcis-11537	271	32	spatial	spatial	ADJ
fcis-11537	271	33	zone	zone	NOUN
fcis-11537	271	34	delineation	delineation	NOUN
fcis-11537	271	35	of	of	ADP
fcis-11537	271	36	groundwater	groundwater	NOUN
fcis-11537	271	37	geochemistry	geochemistry	NOUN
fcis-11537	271	38	data[j	data[j	NOUN
fcis-11537	271	39	]	]	PUNCT
fcis-11537	271	40	.	.	PUNCT
fcis-11537	272	1	journal	journal	PROPN
fcis-11537	272	2	of	of	ADP
fcis-11537	272	3	hydrology	hydrology	NOUN
fcis-11537	272	4	,	,	PUNCT
fcis-11537	272	5	2021	2021	NUM
fcis-11537	272	6	,	,	PUNCT
fcis-11537	272	7	597(43):126146	597(43):126146	PROPN
fcis-11537	272	8	.	.	PUNCT