id	sid	tid	token	lemma	pos
fcis-13148	1	1	frontiers	frontier	NOUN
fcis-13148	1	2	in	in	ADP
fcis-13148	1	3	computing	computing	NOUN
fcis-13148	1	4	and	and	CCONJ
fcis-13148	1	5	intelligent	intelligent	ADJ
fcis-13148	1	6	systems	system	NOUN
fcis-13148	1	7	issn	issn	VERB
fcis-13148	1	8	:	:	PUNCT
fcis-13148	1	9	2832	2832	NUM
fcis-13148	1	10	-	-	SYM
fcis-13148	1	11	6024	6024	NUM
fcis-13148	1	12	|	|	NOUN
fcis-13148	1	13	vol	vol	NOUN
fcis-13148	1	14	.	.	PROPN
fcis-13148	2	1	5	5	NUM
fcis-13148	2	2	,	,	PUNCT
fcis-13148	2	3	no	no	INTJ
fcis-13148	2	4	.	.	NOUN
fcis-13148	2	5	2	2	NUM
fcis-13148	2	6	,	,	PUNCT
fcis-13148	2	7	2023	2023	NUM
fcis-13148	2	8	148	148	NUM
fcis-13148	2	9	sichuan	sichuan	PROPN
fcis-13148	2	10	cuisine	cuisine	NOUN
fcis-13148	2	11	recognition	recognition	NOUN
fcis-13148	2	12	method	method	NOUN
fcis-13148	2	13	based	base	VERB
fcis-13148	2	14	on	on	ADP
fcis-13148	2	15	residual	residual	ADJ
fcis-13148	2	16	neural	neural	ADJ
fcis-13148	2	17	network	network	NOUN
fcis-13148	2	18	weifu	weifu	NOUN
fcis-13148	2	19	li	li	PROPN
fcis-13148	2	20	,	,	PUNCT
fcis-13148	2	21	yichong	yichong	PROPN
fcis-13148	2	22	cai	cai	PROPN
fcis-13148	2	23	and	and	CCONJ
fcis-13148	2	24	jinyu	jinyu	PROPN
fcis-13148	2	25	huang	huang	PROPN
fcis-13148	2	26	school	school	PROPN
fcis-13148	2	27	of	of	ADP
fcis-13148	2	28	sichuan	sichuan	PROPN
fcis-13148	2	29	university	university	PROPN
fcis-13148	2	30	of	of	ADP
fcis-13148	2	31	science	science	NOUN
fcis-13148	2	32	and	and	CCONJ
fcis-13148	2	33	engineering	engineering	NOUN
fcis-13148	2	34	,	,	PUNCT
fcis-13148	2	35	zigong	zigong	PROPN
fcis-13148	2	36	643000	643000	NUM
fcis-13148	2	37	,	,	PUNCT
fcis-13148	2	38	china	china	PROPN
fcis-13148	2	39	abstract	abstract	NOUN
fcis-13148	2	40	:	:	PUNCT
fcis-13148	2	41	to	to	PART
fcis-13148	2	42	address	address	VERB
fcis-13148	2	43	issues	issue	NOUN
fcis-13148	2	44	such	such	ADJ
fcis-13148	2	45	as	as	ADP
fcis-13148	2	46	the	the	DET
fcis-13148	2	47	high	high	ADJ
fcis-13148	2	48	number	number	NOUN
fcis-13148	2	49	of	of	ADP
fcis-13148	2	50	parameters	parameter	NOUN
fcis-13148	2	51	,	,	PUNCT
fcis-13148	2	52	significant	significant	ADJ
fcis-13148	2	53	variations	variation	NOUN
fcis-13148	2	54	among	among	ADP
fcis-13148	2	55	images	image	NOUN
fcis-13148	2	56	of	of	ADP
fcis-13148	2	57	similar	similar	ADJ
fcis-13148	2	58	dishes	dish	NOUN
fcis-13148	2	59	,	,	PUNCT
fcis-13148	2	60	weak	weak	ADJ
fcis-13148	2	61	geometric	geometric	ADJ
fcis-13148	2	62	invariance	invariance	NOUN
fcis-13148	2	63	,	,	PUNCT
fcis-13148	2	64	and	and	CCONJ
fcis-13148	2	65	low	low	ADJ
fcis-13148	2	66	recognition	recognition	NOUN
fcis-13148	2	67	rates	rate	NOUN
fcis-13148	2	68	in	in	ADP
fcis-13148	2	69	sichuan	sichuan	PROPN
fcis-13148	2	70	cuisine	cuisine	NOUN
fcis-13148	2	71	recognition	recognition	NOUN
fcis-13148	2	72	methods	method	NOUN
fcis-13148	2	73	,	,	PUNCT
fcis-13148	2	74	a	a	DET
fcis-13148	2	75	lightweight	lightweight	ADJ
fcis-13148	2	76	sichuan	sichuan	PROPN
fcis-13148	2	77	cuisine	cuisine	PROPN
fcis-13148	2	78	recognition	recognition	PROPN
fcis-13148	2	79	model	model	NOUN
fcis-13148	2	80	,	,	PUNCT
fcis-13148	2	81	rgbnet	rgbnet	ADJ
fcis-13148	2	82	,	,	PUNCT
fcis-13148	2	83	based	base	VERB
fcis-13148	2	84	on	on	ADP
fcis-13148	2	85	residual	residual	ADJ
fcis-13148	2	86	neural	neural	ADJ
fcis-13148	2	87	network	network	NOUN
fcis-13148	2	88	,	,	PUNCT
fcis-13148	2	89	is	be	AUX
fcis-13148	2	90	proposed	propose	VERB
fcis-13148	2	91	.	.	PUNCT
fcis-13148	3	1	the	the	DET
fcis-13148	3	2	model	model	NOUN
fcis-13148	3	3	employs	employ	VERB
fcis-13148	3	4	dilated	dilated	ADJ
fcis-13148	3	5	convolutions	convolution	NOUN
fcis-13148	3	6	to	to	PART
fcis-13148	3	7	increase	increase	VERB
fcis-13148	3	8	the	the	DET
fcis-13148	3	9	receptive	receptive	ADJ
fcis-13148	3	10	field	field	NOUN
fcis-13148	3	11	of	of	ADP
fcis-13148	3	12	convolutional	convolutional	ADJ
fcis-13148	3	13	kernels	kernel	NOUN
fcis-13148	3	14	while	while	SCONJ
fcis-13148	3	15	maintaining	maintain	VERB
fcis-13148	3	16	a	a	DET
fcis-13148	3	17	consistent	consistent	ADJ
fcis-13148	3	18	parameter	parameter	NOUN
fcis-13148	3	19	count	count	NOUN
fcis-13148	3	20	,	,	PUNCT
fcis-13148	3	21	thus	thus	ADV
fcis-13148	3	22	obtaining	obtain	VERB
fcis-13148	3	23	more	more	ADJ
fcis-13148	3	24	shallow	shallow	ADJ
fcis-13148	3	25	-	-	PUNCT
fcis-13148	3	26	level	level	NOUN
fcis-13148	3	27	features	feature	NOUN
fcis-13148	3	28	.	.	PUNCT
fcis-13148	4	1	an	an	DET
fcis-13148	4	2	rgb	rgb	PROPN
fcis-13148	4	3	module	module	NOUN
fcis-13148	4	4	is	be	AUX
fcis-13148	4	5	constructed	construct	VERB
fcis-13148	4	6	using	use	VERB
fcis-13148	4	7	asymmetric	asymmetric	ADJ
fcis-13148	4	8	convolutions	convolution	NOUN
fcis-13148	4	9	to	to	PART
fcis-13148	4	10	enhance	enhance	VERB
fcis-13148	4	11	the	the	DET
fcis-13148	4	12	model	model	NOUN
fcis-13148	4	13	's	's	PART
fcis-13148	4	14	geometric	geometric	ADJ
fcis-13148	4	15	invariance	invariance	NOUN
fcis-13148	4	16	,	,	PUNCT
fcis-13148	4	17	feature	feature	NOUN
fcis-13148	4	18	non	non	ADJ
fcis-13148	4	19	-	-	ADJ
fcis-13148	4	20	linear	linear	ADJ
fcis-13148	4	21	expression	expression	NOUN
fcis-13148	4	22	,	,	PUNCT
fcis-13148	4	23	and	and	CCONJ
fcis-13148	4	24	feature	feature	NOUN
fcis-13148	4	25	extraction	extraction	NOUN
fcis-13148	4	26	capabilities	capability	NOUN
fcis-13148	4	27	.	.	PUNCT
fcis-13148	5	1	finally	finally	ADV
fcis-13148	5	2	,	,	PUNCT
fcis-13148	5	3	the	the	DET
fcis-13148	5	4	dfc	dfc	PROPN
fcis-13148	5	5	long	long	ADJ
fcis-13148	5	6	-	-	PUNCT
fcis-13148	5	7	range	range	NOUN
fcis-13148	5	8	attention	attention	NOUN
fcis-13148	5	9	mechanism	mechanism	NOUN
fcis-13148	5	10	is	be	AUX
fcis-13148	5	11	introduced	introduce	VERB
fcis-13148	5	12	to	to	PART
fcis-13148	5	13	effectively	effectively	ADV
fcis-13148	5	14	capture	capture	VERB
fcis-13148	5	15	long	long	ADJ
fcis-13148	5	16	-	-	PUNCT
fcis-13148	5	17	range	range	NOUN
fcis-13148	5	18	information	information	NOUN
fcis-13148	5	19	,	,	PUNCT
fcis-13148	5	20	thereby	thereby	ADV
fcis-13148	5	21	improving	improve	VERB
fcis-13148	5	22	adaptive	adaptive	ADJ
fcis-13148	5	23	learning	learn	VERB
fcis-13148	5	24	capabilities	capability	NOUN
fcis-13148	5	25	.	.	PUNCT
fcis-13148	6	1	to	to	PART
fcis-13148	6	2	validate	validate	VERB
fcis-13148	6	3	the	the	DET
fcis-13148	6	4	model	model	NOUN
fcis-13148	6	5	's	's	PART
fcis-13148	6	6	performance	performance	NOUN
fcis-13148	6	7	,	,	PUNCT
fcis-13148	6	8	the	the	DET
fcis-13148	6	9	classic	classic	ADJ
fcis-13148	6	10	chinesefoodnet	chinesefoodnet	NOUN
fcis-13148	6	11	benchmark	benchmark	NOUN
fcis-13148	6	12	dataset	dataset	NOUN
fcis-13148	6	13	is	be	AUX
fcis-13148	6	14	utilized	utilize	VERB
fcis-13148	6	15	.	.	PUNCT
fcis-13148	7	1	a	a	DET
fcis-13148	7	2	minichinesefood	minichinesefood	NOUN
fcis-13148	7	3	dataset	dataset	NOUN
fcis-13148	7	4	is	be	AUX
fcis-13148	7	5	created	create	VERB
fcis-13148	7	6	by	by	ADP
fcis-13148	7	7	extracting	extract	VERB
fcis-13148	7	8	30	30	NUM
fcis-13148	7	9	classes	class	NOUN
fcis-13148	7	10	totaling	total	VERB
fcis-13148	7	11	20,000	20,000	NUM
fcis-13148	7	12	images	image	NOUN
fcis-13148	7	13	for	for	ADP
fcis-13148	7	14	experimentation	experimentation	NOUN
fcis-13148	7	15	.	.	PUNCT
fcis-13148	8	1	the	the	DET
fcis-13148	8	2	recognition	recognition	NOUN
fcis-13148	8	3	accuracy	accuracy	NOUN
fcis-13148	8	4	is	be	AUX
fcis-13148	8	5	measured	measure	VERB
fcis-13148	8	6	using	use	VERB
fcis-13148	8	7	the	the	DET
fcis-13148	8	8	top1	top1	PROPN
fcis-13148	8	9	method	method	NOUN
fcis-13148	8	10	of	of	ADP
fcis-13148	8	11	image	image	NOUN
fcis-13148	8	12	recognition	recognition	NOUN
fcis-13148	8	13	performance	performance	NOUN
fcis-13148	8	14	,	,	PUNCT
fcis-13148	8	15	achieving	achieve	VERB
fcis-13148	8	16	a	a	DET
fcis-13148	8	17	final	final	ADJ
fcis-13148	8	18	image	image	NOUN
fcis-13148	8	19	recognition	recognition	NOUN
fcis-13148	8	20	accuracy	accuracy	NOUN
fcis-13148	8	21	of	of	ADP
fcis-13148	8	22	96.62	96.62	NUM
fcis-13148	8	23	%	%	NOUN
fcis-13148	8	24	.	.	PUNCT
fcis-13148	9	1	compared	compare	VERB
fcis-13148	9	2	to	to	ADP
fcis-13148	9	3	models	model	NOUN
fcis-13148	9	4	such	such	ADJ
fcis-13148	9	5	as	as	ADP
fcis-13148	9	6	efficientnet	efficientnet	NOUN
fcis-13148	9	7	,	,	PUNCT
fcis-13148	9	8	shuffnet	shuffnet	NOUN
fcis-13148	9	9	,	,	PUNCT
fcis-13148	9	10	fasternet	fasternet	NOUN
fcis-13148	9	11	,	,	PUNCT
fcis-13148	9	12	and	and	CCONJ
fcis-13148	9	13	mobilenetv2	mobilenetv2	PROPN
fcis-13148	9	14	,	,	PUNCT
fcis-13148	9	15	rgbnet	rgbnet	PROPN
fcis-13148	9	16	demonstrates	demonstrate	VERB
fcis-13148	9	17	respective	respective	ADJ
fcis-13148	9	18	accuracy	accuracy	NOUN
fcis-13148	9	19	improvements	improvement	NOUN
fcis-13148	9	20	of	of	ADP
fcis-13148	9	21	16.57	16.57	NUM
fcis-13148	9	22	%	%	NOUN
fcis-13148	9	23	,	,	PUNCT
fcis-13148	9	24	18.52	18.52	NUM
fcis-13148	9	25	%	%	NOUN
fcis-13148	9	26	,	,	PUNCT
fcis-13148	9	27	17.12	17.12	NUM
fcis-13148	9	28	%	%	NOUN
fcis-13148	9	29	,	,	PUNCT
fcis-13148	9	30	and	and	CCONJ
fcis-13148	9	31	16.35	16.35	NUM
fcis-13148	9	32	%	%	NOUN
fcis-13148	9	33	.	.	PUNCT
fcis-13148	10	1	this	this	PRON
fcis-13148	10	2	presents	present	VERB
fcis-13148	10	3	a	a	DET
fcis-13148	10	4	novel	novel	ADJ
fcis-13148	10	5	approach	approach	NOUN
fcis-13148	10	6	for	for	ADP
fcis-13148	10	7	industrial	industrial	ADJ
fcis-13148	10	8	food	food	NOUN
fcis-13148	10	9	recognition	recognition	NOUN
fcis-13148	10	10	.	.	PUNCT
fcis-13148	11	1	keywords	keyword	NOUN
fcis-13148	11	2	:	:	PUNCT
fcis-13148	11	3	residual	residual	ADJ
fcis-13148	11	4	neural	neural	ADJ
fcis-13148	11	5	network	network	NOUN
fcis-13148	11	6	;	;	PUNCT
fcis-13148	11	7	attention	attention	NOUN
fcis-13148	11	8	mechanism	mechanism	NOUN
fcis-13148	11	9	;	;	PUNCT
fcis-13148	11	10	image	image	NOUN
fcis-13148	11	11	classification	classification	NOUN
fcis-13148	11	12	;	;	PUNCT
fcis-13148	11	13	sichuan	sichuan	PROPN
fcis-13148	11	14	cuisine	cuisine	PROPN
fcis-13148	11	15	recognition	recognition	PROPN
fcis-13148	11	16	.	.	PUNCT
fcis-13148	12	1	1	1	X
fcis-13148	12	2	.	.	X
fcis-13148	12	3	introduction	introduction	NOUN
fcis-13148	12	4	all	all	DET
fcis-13148	12	5	sichuan	sichuan	PROPN
fcis-13148	12	6	cuisine	cuisine	NOUN
fcis-13148	12	7	,	,	PUNCT
fcis-13148	12	8	also	also	ADV
fcis-13148	12	9	known	know	VERB
fcis-13148	12	10	as	as	ADP
fcis-13148	12	11	sichuan	sichuan	ADJ
fcis-13148	12	12	-	-	PUNCT
fcis-13148	12	13	style	style	NOUN
fcis-13148	12	14	cuisine	cuisine	NOUN
fcis-13148	12	15	,	,	PUNCT
fcis-13148	12	16	is	be	AUX
fcis-13148	12	17	a	a	DET
fcis-13148	12	18	regional	regional	ADJ
fcis-13148	12	19	culinary	culinary	ADJ
fcis-13148	12	20	style	style	NOUN
fcis-13148	12	21	represented	represent	VERB
fcis-13148	12	22	by	by	ADP
fcis-13148	12	23	sichuan	sichuan	PROPN
fcis-13148	12	24	province	province	PROPN
fcis-13148	12	25	.	.	PUNCT
fcis-13148	13	1	sichuan	sichuan	PROPN
fcis-13148	13	2	cuisine	cuisine	PROPN
fcis-13148	13	3	has	have	VERB
fcis-13148	13	4	profound	profound	ADJ
fcis-13148	13	5	effects	effect	NOUN
fcis-13148	13	6	on	on	ADP
fcis-13148	13	7	human	human	ADJ
fcis-13148	13	8	health	health	NOUN
fcis-13148	13	9	,	,	PUNCT
fcis-13148	13	10	nutrition	nutrition	NOUN
fcis-13148	13	11	,	,	PUNCT
fcis-13148	13	12	and	and	CCONJ
fcis-13148	13	13	various	various	ADJ
fcis-13148	13	14	aspects	aspect	NOUN
fcis-13148	13	15	of	of	ADP
fcis-13148	13	16	life	life	NOUN
fcis-13148	13	17	.	.	PUNCT
fcis-13148	14	1	with	with	ADP
fcis-13148	14	2	the	the	DET
fcis-13148	14	3	increase	increase	NOUN
fcis-13148	14	4	in	in	ADP
fcis-13148	14	5	per	per	ADP
fcis-13148	14	6	capita	capita	NOUN
fcis-13148	14	7	consumption	consumption	NOUN
fcis-13148	14	8	levels	level	NOUN
fcis-13148	14	9	,	,	PUNCT
fcis-13148	14	10	more	more	ADJ
fcis-13148	14	11	researchers	researcher	NOUN
fcis-13148	14	12	are	be	AUX
fcis-13148	14	13	turning	turn	VERB
fcis-13148	14	14	their	their	PRON
fcis-13148	14	15	attention	attention	NOUN
fcis-13148	14	16	to	to	ADP
fcis-13148	14	17	food	food	NOUN
fcis-13148	14	18	science	science	NOUN
fcis-13148	14	19	,	,	PUNCT
fcis-13148	14	20	aiming	aim	VERB
fcis-13148	14	21	to	to	PART
fcis-13148	14	22	achieve	achieve	VERB
fcis-13148	14	23	health	health	NOUN
fcis-13148	14	24	regulation	regulation	NOUN
fcis-13148	14	25	by	by	ADP
fcis-13148	14	26	analyzing	analyze	VERB
fcis-13148	14	27	the	the	DET
fcis-13148	14	28	nutritional	nutritional	ADJ
fcis-13148	14	29	components	component	NOUN
fcis-13148	14	30	and	and	CCONJ
fcis-13148	14	31	ingredient	ingredient	NOUN
fcis-13148	14	32	combinations	combination	NOUN
fcis-13148	14	33	of	of	ADP
fcis-13148	14	34	dishes	dish	NOUN
fcis-13148	14	35	[	[	X
fcis-13148	14	36	1	1	NUM
fcis-13148	14	37	]	]	PUNCT
fcis-13148	14	38	.	.	PUNCT
fcis-13148	15	1	methods	method	NOUN
fcis-13148	15	2	for	for	ADP
fcis-13148	15	3	recognizing	recognize	VERB
fcis-13148	15	4	sichuan	sichuan	PROPN
fcis-13148	15	5	cuisine	cuisine	NOUN
fcis-13148	15	6	have	have	AUX
fcis-13148	15	7	progressed	progress	VERB
fcis-13148	15	8	from	from	ADP
fcis-13148	15	9	early	early	ADJ
fcis-13148	15	10	traditional	traditional	ADJ
fcis-13148	15	11	wireless	wireless	ADJ
fcis-13148	15	12	rf	rf	NOUN
fcis-13148	15	13	signal	signal	ADJ
fcis-13148	15	14	methods	method	NOUN
fcis-13148	15	15	,	,	PUNCT
fcis-13148	15	16	traditional	traditional	ADJ
fcis-13148	15	17	machine	machine	NOUN
fcis-13148	15	18	learning	learning	NOUN
fcis-13148	15	19	methods	method	NOUN
fcis-13148	15	20	,	,	PUNCT
fcis-13148	15	21	to	to	ADP
fcis-13148	15	22	deep	deep	ADJ
fcis-13148	15	23	learning	learning	NOUN
fcis-13148	15	24	-	-	PUNCT
fcis-13148	15	25	based	base	VERB
fcis-13148	15	26	recognition	recognition	NOUN
fcis-13148	15	27	methods	method	NOUN
fcis-13148	15	28	.	.	PUNCT
fcis-13148	16	1	traditional	traditional	ADJ
fcis-13148	16	2	rf	rf	ADJ
fcis-13148	16	3	methods	method	NOUN
fcis-13148	16	4	[	[	X
fcis-13148	16	5	2	2	X
fcis-13148	16	6	]	]	PUNCT
fcis-13148	16	7	involve	involve	VERB
fcis-13148	16	8	implanting	implant	VERB
fcis-13148	16	9	wireless	wireless	ADJ
fcis-13148	16	10	rf	rf	NOUN
fcis-13148	16	11	chips	chip	NOUN
fcis-13148	16	12	in	in	ADP
fcis-13148	16	13	utensils	utensil	NOUN
fcis-13148	16	14	containing	contain	VERB
fcis-13148	16	15	dishes	dish	NOUN
fcis-13148	16	16	to	to	PART
fcis-13148	16	17	identify	identify	VERB
fcis-13148	16	18	and	and	CCONJ
fcis-13148	16	19	analyze	analyze	VERB
fcis-13148	16	20	the	the	DET
fcis-13148	16	21	dishes	dish	NOUN
fcis-13148	16	22	.	.	PUNCT
fcis-13148	17	1	although	although	SCONJ
fcis-13148	17	2	rf	rf	NOUN
fcis-13148	17	3	-	-	PUNCT
fcis-13148	17	4	based	base	VERB
fcis-13148	17	5	methods	method	NOUN
fcis-13148	17	6	have	have	VERB
fcis-13148	17	7	high	high	ADJ
fcis-13148	17	8	accuracy	accuracy	NOUN
fcis-13148	17	9	,	,	PUNCT
fcis-13148	17	10	they	they	PRON
fcis-13148	17	11	require	require	VERB
fcis-13148	17	12	customizing	customizing	NOUN
fcis-13148	17	13	utensils	utensil	NOUN
fcis-13148	17	14	in	in	ADP
fcis-13148	17	15	advance	advance	NOUN
fcis-13148	17	16	,	,	PUNCT
fcis-13148	17	17	and	and	CCONJ
fcis-13148	17	18	the	the	DET
fcis-13148	17	19	process	process	NOUN
fcis-13148	17	20	is	be	AUX
fcis-13148	17	21	cumbersome	cumbersome	ADJ
fcis-13148	17	22	,	,	PUNCT
fcis-13148	17	23	with	with	ADP
fcis-13148	17	24	limited	limited	ADJ
fcis-13148	17	25	functionality	functionality	NOUN
fcis-13148	17	26	and	and	CCONJ
fcis-13148	17	27	poor	poor	ADJ
fcis-13148	17	28	maintainability	maintainability	NOUN
fcis-13148	17	29	.	.	PUNCT
fcis-13148	18	1	traditional	traditional	ADJ
fcis-13148	18	2	machine	machine	NOUN
fcis-13148	18	3	learning	learning	NOUN
fcis-13148	18	4	methods	method	NOUN
fcis-13148	18	5	[	[	X
fcis-13148	18	6	3	3	X
fcis-13148	18	7	]	]	PUNCT
fcis-13148	18	8	rely	rely	NOUN
fcis-13148	18	9	on	on	ADP
fcis-13148	18	10	manually	manually	ADV
fcis-13148	18	11	selecting	select	VERB
fcis-13148	18	12	features	feature	NOUN
fcis-13148	18	13	,	,	PUNCT
fcis-13148	18	14	conducting	conduct	VERB
fcis-13148	18	15	statistical	statistical	ADJ
fcis-13148	18	16	analysis	analysis	NOUN
fcis-13148	18	17	,	,	PUNCT
fcis-13148	18	18	and	and	CCONJ
fcis-13148	18	19	inputting	inputte	VERB
fcis-13148	18	20	the	the	DET
fcis-13148	18	21	results	result	NOUN
fcis-13148	18	22	into	into	ADP
fcis-13148	18	23	classifiers	classifier	NOUN
fcis-13148	18	24	.	.	PUNCT
fcis-13148	19	1	the	the	DET
fcis-13148	19	2	accuracy	accuracy	NOUN
fcis-13148	19	3	is	be	AUX
fcis-13148	19	4	not	not	PART
fcis-13148	19	5	ideal	ideal	ADJ
fcis-13148	19	6	.	.	PUNCT
fcis-13148	20	1	recognition	recognition	NOUN
fcis-13148	20	2	methods	method	NOUN
fcis-13148	20	3	based	base	VERB
fcis-13148	20	4	on	on	ADP
fcis-13148	20	5	deep	deep	ADJ
fcis-13148	20	6	learning	learning	NOUN
fcis-13148	20	7	[	[	X
fcis-13148	20	8	4	4	X
fcis-13148	20	9	]	]	PUNCT
fcis-13148	20	10	are	be	AUX
fcis-13148	20	11	characterized	characterize	VERB
fcis-13148	20	12	by	by	ADP
fcis-13148	20	13	lossless	lossless	PROPN
fcis-13148	20	14	,	,	PUNCT
fcis-13148	20	15	realtime	realtime	NOUN
fcis-13148	20	16	,	,	PUNCT
fcis-13148	20	17	and	and	CCONJ
fcis-13148	20	18	pollution	pollution	NOUN
fcis-13148	20	19	-	-	PUNCT
fcis-13148	20	20	free	free	ADJ
fcis-13148	20	21	features	feature	NOUN
fcis-13148	20	22	.	.	PUNCT
fcis-13148	21	1	they	they	PRON
fcis-13148	21	2	can	can	AUX
fcis-13148	21	3	identify	identify	VERB
fcis-13148	21	4	dish	dish	NOUN
fcis-13148	21	5	categories	category	NOUN
fcis-13148	21	6	by	by	ADP
fcis-13148	21	7	capturing	capture	VERB
fcis-13148	21	8	images	image	NOUN
fcis-13148	21	9	through	through	ADP
fcis-13148	21	10	cameras	camera	NOUN
fcis-13148	21	11	.	.	PUNCT
fcis-13148	22	1	compared	compare	VERB
fcis-13148	22	2	to	to	ADP
fcis-13148	22	3	traditional	traditional	ADJ
fcis-13148	22	4	machine	machine	NOUN
fcis-13148	22	5	learning	learning	NOUN
fcis-13148	22	6	methods	method	NOUN
fcis-13148	22	7	,	,	PUNCT
fcis-13148	22	8	which	which	PRON
fcis-13148	22	9	require	require	VERB
fcis-13148	22	10	manual	manual	ADJ
fcis-13148	22	11	feature	feature	NOUN
fcis-13148	22	12	extraction	extraction	NOUN
fcis-13148	22	13	,	,	PUNCT
fcis-13148	22	14	convolutional	convolutional	ADJ
fcis-13148	22	15	neural	neural	ADJ
fcis-13148	22	16	networks	network	NOUN
fcis-13148	22	17	can	can	AUX
fcis-13148	22	18	automatically	automatically	ADV
fcis-13148	22	19	learn	learn	VERB
fcis-13148	22	20	and	and	CCONJ
fcis-13148	22	21	extract	extract	VERB
fcis-13148	22	22	features	feature	NOUN
fcis-13148	22	23	.	.	PUNCT
fcis-13148	23	1	by	by	ADP
fcis-13148	23	2	stacking	stack	VERB
fcis-13148	23	3	multiple	multiple	ADJ
fcis-13148	23	4	convolutional	convolutional	ADJ
fcis-13148	23	5	and	and	CCONJ
fcis-13148	23	6	pooling	pool	VERB
fcis-13148	23	7	layers	layer	NOUN
fcis-13148	23	8	,	,	PUNCT
fcis-13148	23	9	abstract	abstract	ADJ
fcis-13148	23	10	features	feature	NOUN
fcis-13148	23	11	are	be	AUX
fcis-13148	23	12	extracted	extract	VERB
fcis-13148	23	13	layer	layer	NOUN
fcis-13148	23	14	by	by	ADP
fcis-13148	23	15	layer	layer	NOUN
fcis-13148	23	16	,	,	PUNCT
fcis-13148	23	17	achieving	achieve	VERB
fcis-13148	23	18	more	more	ADV
fcis-13148	23	19	accurate	accurate	ADJ
fcis-13148	23	20	and	and	CCONJ
fcis-13148	23	21	efficient	efficient	ADJ
fcis-13148	23	22	classification	classification	NOUN
fcis-13148	23	23	.	.	PUNCT
fcis-13148	24	1	research	research	NOUN
fcis-13148	24	2	on	on	ADP
fcis-13148	24	3	food	food	NOUN
fcis-13148	24	4	recognition	recognition	NOUN
fcis-13148	24	5	is	be	AUX
fcis-13148	24	6	interdisciplinary	interdisciplinary	ADJ
fcis-13148	24	7	,	,	PUNCT
fcis-13148	24	8	spanning	span	VERB
fcis-13148	24	9	fields	field	NOUN
fcis-13148	24	10	such	such	ADJ
fcis-13148	24	11	as	as	ADP
fcis-13148	24	12	computer	computer	NOUN
fcis-13148	24	13	vision	vision	NOUN
fcis-13148	24	14	[	[	X
fcis-13148	24	15	5	5	NUM
fcis-13148	24	16	]	]	PUNCT
fcis-13148	24	17	,	,	PUNCT
fcis-13148	24	18	new	new	ADJ
fcis-13148	24	19	media	medium	NOUN
fcis-13148	24	20	[	[	X
fcis-13148	24	21	6	6	NUM
fcis-13148	24	22	]	]	PUNCT
fcis-13148	24	23	,	,	PUNCT
fcis-13148	24	24	industrial	industrial	ADJ
fcis-13148	24	25	informatics	informatic	NOUN
fcis-13148	25	1	[	[	X
fcis-13148	25	2	7	7	NUM
fcis-13148	25	3	]	]	PUNCT
fcis-13148	25	4	,	,	PUNCT
fcis-13148	25	5	agriculture	agriculture	NOUN
fcis-13148	25	6	,	,	PUNCT
fcis-13148	25	7	medicine	medicine	NOUN
fcis-13148	25	8	,	,	PUNCT
fcis-13148	25	9	and	and	CCONJ
fcis-13148	25	10	nutrition	nutrition	NOUN
fcis-13148	25	11	science	science	NOUN
fcis-13148	26	1	[	[	X
fcis-13148	26	2	8	8	NUM
fcis-13148	26	3	]	]	PUNCT
fcis-13148	26	4	.	.	PUNCT
fcis-13148	27	1	the	the	DET
fcis-13148	27	2	widespread	widespread	ADJ
fcis-13148	27	3	use	use	NOUN
fcis-13148	27	4	of	of	ADP
fcis-13148	27	5	portable	portable	ADJ
fcis-13148	27	6	devices	device	NOUN
fcis-13148	27	7	(	(	PUNCT
fcis-13148	27	8	such	such	ADJ
fcis-13148	27	9	as	as	ADP
fcis-13148	27	10	smartphones	smartphone	NOUN
fcis-13148	27	11	and	and	CCONJ
fcis-13148	27	12	cameras	camera	NOUN
fcis-13148	27	13	)	)	PUNCT
fcis-13148	27	14	and	and	CCONJ
fcis-13148	27	15	the	the	DET
fcis-13148	27	16	development	development	NOUN
fcis-13148	27	17	of	of	ADP
fcis-13148	27	18	artificial	artificial	ADJ
fcis-13148	27	19	intelligence	intelligence	NOUN
fcis-13148	27	20	have	have	AUX
fcis-13148	27	21	led	lead	VERB
fcis-13148	27	22	to	to	ADP
fcis-13148	27	23	extensive	extensive	ADJ
fcis-13148	27	24	applications	application	NOUN
fcis-13148	27	25	in	in	ADP
fcis-13148	27	26	sichuan	sichuan	PROPN
fcis-13148	27	27	cuisine	cuisine	NOUN
fcis-13148	27	28	image	image	NOUN
fcis-13148	27	29	recognition	recognition	NOUN
fcis-13148	27	30	.	.	PUNCT
fcis-13148	28	1	therefore	therefore	ADV
fcis-13148	28	2	,	,	PUNCT
fcis-13148	28	3	the	the	DET
fcis-13148	28	4	development	development	NOUN
fcis-13148	28	5	of	of	ADP
fcis-13148	28	6	real	real	ADJ
fcis-13148	28	7	-	-	PUNCT
fcis-13148	28	8	time	time	NOUN
fcis-13148	28	9	and	and	CCONJ
fcis-13148	28	10	accurate	accurate	ADJ
fcis-13148	28	11	methods	method	NOUN
fcis-13148	28	12	and	and	CCONJ
fcis-13148	28	13	technologies	technology	NOUN
fcis-13148	28	14	for	for	ADP
fcis-13148	28	15	sichuan	sichuan	PROPN
fcis-13148	28	16	cuisine	cuisine	PROPN
fcis-13148	28	17	recognition	recognition	NOUN
fcis-13148	28	18	has	have	VERB
fcis-13148	28	19	significant	significant	ADJ
fcis-13148	28	20	practical	practical	ADJ
fcis-13148	28	21	value	value	NOUN
fcis-13148	28	22	.	.	PUNCT
fcis-13148	29	1	haiyan	haiyan	PROPN
fcis-13148	29	2	wang	wang	PROPN
fcis-13148	30	1	[	[	X
fcis-13148	30	2	9	9	NUM
fcis-13148	30	3	]	]	PUNCT
fcis-13148	30	4	and	and	CCONJ
fcis-13148	30	5	others	other	NOUN
fcis-13148	30	6	improved	improve	VERB
fcis-13148	30	7	local	local	ADJ
fcis-13148	30	8	skeleton	skeleton	NOUN
fcis-13148	30	9	information	information	NOUN
fcis-13148	30	10	learning	learn	VERB
fcis-13148	30	11	by	by	ADP
fcis-13148	30	12	integrating	integrate	VERB
fcis-13148	30	13	asymmetric	asymmetric	ADJ
fcis-13148	30	14	convolutions	convolution	NOUN
fcis-13148	30	15	to	to	PART
fcis-13148	30	16	enhance	enhance	VERB
fcis-13148	30	17	dish	dish	NOUN
fcis-13148	30	18	feature	feature	NOUN
fcis-13148	30	19	extraction	extraction	NOUN
fcis-13148	30	20	.	.	PUNCT
fcis-13148	31	1	deng	deng	PROPN
fcis-13148	31	2	zhiliang	zhiliang	PROPN
fcis-13148	32	1	[	[	X
fcis-13148	32	2	10	10	NUM
fcis-13148	32	3	]	]	PUNCT
fcis-13148	32	4	proposed	propose	VERB
fcis-13148	32	5	a	a	DET
fcis-13148	32	6	dish	dish	NOUN
fcis-13148	32	7	recognition	recognition	NOUN
fcis-13148	32	8	network	network	NOUN
fcis-13148	32	9	model	model	NOUN
fcis-13148	32	10	that	that	PRON
fcis-13148	32	11	integrates	integrate	NOUN
fcis-13148	32	12	multiscale	multiscale	NOUN
fcis-13148	32	13	features	feature	VERB
fcis-13148	32	14	to	to	PART
fcis-13148	32	15	extract	extract	VERB
fcis-13148	32	16	semantic	semantic	ADJ
fcis-13148	32	17	information	information	NOUN
fcis-13148	32	18	from	from	ADP
fcis-13148	32	19	deep	deep	ADJ
fcis-13148	32	20	-	-	PUNCT
fcis-13148	32	21	level	level	NOUN
fcis-13148	32	22	images	image	NOUN
fcis-13148	32	23	,	,	PUNCT
fcis-13148	32	24	and	and	CCONJ
fcis-13148	32	25	calculates	calculate	VERB
fcis-13148	32	26	inter	inter	ADJ
fcis-13148	32	27	-	-	ADJ
fcis-13148	32	28	class	class	ADJ
fcis-13148	32	29	similarity	similarity	NOUN
fcis-13148	32	30	using	use	VERB
fcis-13148	32	31	triplet	triplet	NOUN
fcis-13148	32	32	loss	loss	NOUN
fcis-13148	32	33	.	.	PUNCT
fcis-13148	33	1	wu	wu	PROPN
fcis-13148	33	2	zhengdong	zhengdong	PROPN
fcis-13148	34	1	[	[	X
fcis-13148	34	2	11	11	NUM
fcis-13148	34	3	]	]	PUNCT
fcis-13148	34	4	introduced	introduce	VERB
fcis-13148	34	5	a	a	DET
fcis-13148	34	6	multiscale	multiscale	ADJ
fcis-13148	34	7	sampling	sampling	NOUN
fcis-13148	34	8	module	module	NOUN
fcis-13148	34	9	to	to	PART
fcis-13148	34	10	address	address	VERB
fcis-13148	34	11	the	the	DET
fcis-13148	34	12	limitations	limitation	NOUN
fcis-13148	34	13	of	of	ADP
fcis-13148	34	14	fully	fully	ADV
fcis-13148	34	15	connected	connected	ADJ
fcis-13148	34	16	layers	layer	NOUN
fcis-13148	34	17	on	on	ADP
fcis-13148	34	18	input	input	NOUN
fcis-13148	34	19	sizes	size	NOUN
fcis-13148	34	20	.	.	PUNCT
fcis-13148	35	1	additionally	additionally	ADV
fcis-13148	35	2	,	,	PUNCT
fcis-13148	35	3	an	an	DET
fcis-13148	35	4	attention	attention	NOUN
fcis-13148	35	5	-	-	PUNCT
fcis-13148	35	6	based	base	VERB
fcis-13148	35	7	bilinear	bilinear	NOUN
fcis-13148	35	8	network	network	NOUN
fcis-13148	35	9	was	be	AUX
fcis-13148	35	10	proposed	propose	VERB
fcis-13148	35	11	to	to	PART
fcis-13148	35	12	construct	construct	VERB
fcis-13148	35	13	an	an	DET
fcis-13148	35	14	attention	attention	NOUN
fcis-13148	35	15	network	network	NOUN
fcis-13148	35	16	from	from	ADP
fcis-13148	35	17	both	both	DET
fcis-13148	35	18	channel	channel	NOUN
fcis-13148	35	19	and	and	CCONJ
fcis-13148	35	20	spatial	spatial	ADJ
fcis-13148	35	21	directions	direction	NOUN
fcis-13148	35	22	to	to	PART
fcis-13148	35	23	enhance	enhance	VERB
fcis-13148	35	24	feature	feature	NOUN
fcis-13148	35	25	extraction	extraction	NOUN
fcis-13148	35	26	capabilities	capability	NOUN
fcis-13148	35	27	.	.	PUNCT
fcis-13148	36	1	liao	liao	PROPN
fcis-13148	36	2	enhong	enhong	PROPN
fcis-13148	37	1	[	[	X
fcis-13148	37	2	12	12	NUM
fcis-13148	37	3	]	]	PUNCT
fcis-13148	37	4	addressed	address	VERB
fcis-13148	37	5	the	the	DET
fcis-13148	37	6	issue	issue	NOUN
fcis-13148	37	7	of	of	ADP
fcis-13148	37	8	accuracy	accuracy	NOUN
fcis-13148	37	9	errors	error	NOUN
fcis-13148	37	10	caused	cause	VERB
fcis-13148	37	11	by	by	ADP
fcis-13148	37	12	the	the	DET
fcis-13148	37	13	large	large	ADJ
fcis-13148	37	14	inter	inter	ADJ
fcis-13148	37	15	-	-	ADJ
fcis-13148	37	16	class	class	ADJ
fcis-13148	37	17	similarity	similarity	NOUN
fcis-13148	37	18	in	in	ADP
fcis-13148	37	19	sichuan	sichuan	PROPN
fcis-13148	37	20	cuisine	cuisine	NOUN
fcis-13148	37	21	dish	dish	NOUN
fcis-13148	37	22	images	image	NOUN
fcis-13148	37	23	using	use	VERB
fcis-13148	37	24	the	the	DET
fcis-13148	37	25	maximum	maximum	ADJ
fcis-13148	37	26	inter	inter	ADJ
fcis-13148	37	27	-	-	ADJ
fcis-13148	37	28	class	class	ADJ
fcis-13148	37	29	loss	loss	NOUN
fcis-13148	37	30	function	function	NOUN
fcis-13148	37	31	.	.	PUNCT
fcis-13148	38	1	although	although	SCONJ
fcis-13148	38	2	the	the	DET
fcis-13148	38	3	aforementioned	aforementioned	ADJ
fcis-13148	38	4	methods	method	NOUN
fcis-13148	38	5	can	can	AUX
fcis-13148	38	6	effectively	effectively	ADV
fcis-13148	38	7	identify	identify	VERB
fcis-13148	38	8	dish	dish	NOUN
fcis-13148	38	9	categories	category	NOUN
fcis-13148	38	10	,	,	PUNCT
fcis-13148	38	11	they	they	PRON
fcis-13148	38	12	often	often	ADV
fcis-13148	38	13	come	come	VERB
fcis-13148	38	14	with	with	ADP
fcis-13148	38	15	a	a	DET
fcis-13148	38	16	huge	huge	ADJ
fcis-13148	38	17	number	number	NOUN
fcis-13148	38	18	of	of	ADP
fcis-13148	38	19	parameters	parameter	NOUN
fcis-13148	38	20	and	and	CCONJ
fcis-13148	38	21	seldom	seldom	ADV
fcis-13148	38	22	consider	consider	VERB
fcis-13148	38	23	the	the	DET
fcis-13148	38	24	issue	issue	NOUN
fcis-13148	38	25	of	of	ADP
fcis-13148	38	26	lightweight	lightweight	ADJ
fcis-13148	38	27	design	design	NOUN
fcis-13148	38	28	.	.	PUNCT
fcis-13148	39	1	therefore	therefore	ADV
fcis-13148	39	2	,	,	PUNCT
fcis-13148	39	3	a	a	DET
fcis-13148	39	4	lightweight	lightweight	ADJ
fcis-13148	39	5	sichuan	sichuan	PROPN
fcis-13148	39	6	cuisine	cuisine	NOUN
fcis-13148	39	7	recognition	recognition	NOUN
fcis-13148	39	8	method	method	NOUN
fcis-13148	39	9	is	be	AUX
fcis-13148	39	10	proposed	propose	VERB
fcis-13148	39	11	by	by	ADP
fcis-13148	39	12	improving	improve	VERB
fcis-13148	39	13	the	the	DET
fcis-13148	39	14	residual	residual	ADJ
fcis-13148	39	15	neural	neural	ADJ
fcis-13148	39	16	network	network	NOUN
fcis-13148	39	17	model	model	NOUN
fcis-13148	39	18	.	.	PUNCT
fcis-13148	40	1	this	this	DET
fcis-13148	40	2	method	method	NOUN
fcis-13148	40	3	enhances	enhance	VERB
fcis-13148	40	4	the	the	DET
fcis-13148	40	5	convolutional	convolutional	ADJ
fcis-13148	40	6	neural	neural	ADJ
fcis-13148	40	7	network	network	NOUN
fcis-13148	40	8	backbone	backbone	NOUN
fcis-13148	40	9	based	base	VERB
fcis-13148	40	10	on	on	ADP
fcis-13148	40	11	the	the	DET
fcis-13148	40	12	characteristics	characteristic	NOUN
fcis-13148	40	13	of	of	ADP
fcis-13148	40	14	the	the	DET
fcis-13148	40	15	sichuan	sichuan	PROPN
fcis-13148	40	16	cuisine	cuisine	PROPN
fcis-13148	40	17	image	image	NOUN
fcis-13148	40	18	dataset	dataset	VERB
fcis-13148	40	19	and	and	CCONJ
fcis-13148	40	20	incorporates	incorporate	VERB
fcis-13148	40	21	attention	attention	NOUN
fcis-13148	40	22	mechanisms	mechanism	NOUN
fcis-13148	40	23	to	to	PART
fcis-13148	40	24	capture	capture	VERB
fcis-13148	40	25	pixel	pixel	ADJ
fcis-13148	40	26	-	-	PUNCT
fcis-13148	40	27	level	level	NOUN
fcis-13148	40	28	long	long	ADJ
fcis-13148	40	29	-	-	PUNCT
fcis-13148	40	30	range	range	NOUN
fcis-13148	40	31	relationship	relationship	NOUN
fcis-13148	40	32	information	information	NOUN
fcis-13148	40	33	.	.	PUNCT
fcis-13148	41	1	to	to	PART
fcis-13148	41	2	validate	validate	VERB
fcis-13148	41	3	the	the	DET
fcis-13148	41	4	model	model	NOUN
fcis-13148	41	5	's	's	PART
fcis-13148	41	6	performance	performance	NOUN
fcis-13148	41	7	,	,	PUNCT
fcis-13148	41	8	this	this	DET
fcis-13148	41	9	study	study	NOUN
fcis-13148	41	10	conducted	conduct	VERB
fcis-13148	41	11	comparative	comparative	ADJ
fcis-13148	41	12	experiments	experiment	NOUN
fcis-13148	41	13	,	,	PUNCT
fcis-13148	41	14	comparing	compare	VERB
fcis-13148	41	15	the	the	DET
fcis-13148	41	16	proposed	propose	VERB
fcis-13148	41	17	method	method	NOUN
fcis-13148	41	18	with	with	ADP
fcis-13148	41	19	lightweight	lightweight	ADJ
fcis-13148	41	20	network	network	NOUN
fcis-13148	41	21	models	model	NOUN
fcis-13148	41	22	such	such	ADJ
fcis-13148	41	23	as	as	ADP
fcis-13148	41	24	efficientnet	efficientnet	NOUN
fcis-13148	41	25	[	[	X
fcis-13148	41	26	13	13	NUM
fcis-13148	41	27	]	]	PUNCT
fcis-13148	41	28	,	,	PUNCT
fcis-13148	41	29	shuffnet	shuffnet	NOUN
fcis-13148	42	1	[	[	X
fcis-13148	42	2	14	14	NUM
fcis-13148	42	3	]	]	PUNCT
fcis-13148	42	4	,	,	PUNCT
fcis-13148	42	5	fasternet	fasternet	NOUN
fcis-13148	43	1	[	[	X
fcis-13148	43	2	15	15	NUM
fcis-13148	43	3	]	]	PUNCT
fcis-13148	43	4	,	,	PUNCT
fcis-13148	43	5	and	and	CCONJ
fcis-13148	43	6	mobilenetv2	mobilenetv2	PROPN
fcis-13148	44	1	[	[	X
fcis-13148	44	2	16	16	NUM
fcis-13148	44	3	]	]	PUNCT
fcis-13148	44	4	.	.	PUNCT
fcis-13148	45	1	2	2	X
fcis-13148	45	2	.	.	X
fcis-13148	45	3	cnn	cnn	PROPN
fcis-13148	45	4	-	-	PUNCT
fcis-13148	45	5	based	base	VERB
fcis-13148	45	6	sichuan	sichuan	PROPN
fcis-13148	45	7	cuisine	cuisine	NOUN
fcis-13148	45	8	image	image	NOUN
fcis-13148	45	9	recognition	recognition	NOUN
fcis-13148	45	10	2.1	2.1	NUM
fcis-13148	45	11	.	.	PUNCT
fcis-13148	46	1	the	the	DET
fcis-13148	46	2	fundamental	fundamental	ADJ
fcis-13148	46	3	principles	principle	NOUN
fcis-13148	46	4	of	of	ADP
fcis-13148	46	5	cnn	cnn	PROPN
fcis-13148	46	6	convolutional	convolutional	ADJ
fcis-13148	46	7	neural	neural	ADJ
fcis-13148	46	8	network	network	NOUN
fcis-13148	46	9	(	(	PUNCT
fcis-13148	46	10	cnn	cnn	PROPN
fcis-13148	46	11	)	)	PUNCT
fcis-13148	47	1	[	[	X
fcis-13148	47	2	17	17	NUM
fcis-13148	47	3	]	]	PUNCT
fcis-13148	47	4	is	be	AUX
fcis-13148	47	5	a	a	DET
fcis-13148	47	6	deep	deep	ADJ
fcis-13148	47	7	149	149	NUM
fcis-13148	47	8	learning	learning	NOUN
fcis-13148	47	9	model	model	NOUN
fcis-13148	47	10	widely	widely	ADV
fcis-13148	47	11	utilized	utilize	VERB
fcis-13148	47	12	in	in	ADP
fcis-13148	47	13	computer	computer	NOUN
fcis-13148	47	14	vision	vision	NOUN
fcis-13148	47	15	and	and	CCONJ
fcis-13148	47	16	image	image	NOUN
fcis-13148	47	17	processing	processing	NOUN
fcis-13148	47	18	tasks	task	NOUN
fcis-13148	47	19	.	.	PUNCT
fcis-13148	48	1	the	the	DET
fcis-13148	48	2	core	core	NOUN
fcis-13148	48	3	of	of	ADP
fcis-13148	48	4	cnn	cnn	PROPN
fcis-13148	48	5	is	be	AUX
fcis-13148	48	6	the	the	DET
fcis-13148	48	7	convolutional	convolutional	ADJ
fcis-13148	48	8	layer	layer	NOUN
fcis-13148	48	9	,	,	PUNCT
fcis-13148	48	10	which	which	PRON
fcis-13148	48	11	employs	employ	VERB
fcis-13148	48	12	convolution	convolution	NOUN
fcis-13148	48	13	operations	operation	NOUN
fcis-13148	48	14	to	to	PART
fcis-13148	48	15	extract	extract	VERB
fcis-13148	48	16	features	feature	NOUN
fcis-13148	48	17	from	from	ADP
fcis-13148	48	18	input	input	NOUN
fcis-13148	48	19	data	datum	NOUN
fcis-13148	48	20	.	.	PUNCT
fcis-13148	49	1	the	the	DET
fcis-13148	49	2	convolutional	convolutional	ADJ
fcis-13148	49	3	layer	layer	NOUN
fcis-13148	49	4	effectively	effectively	ADV
fcis-13148	49	5	captures	capture	VERB
fcis-13148	49	6	spatial	spatial	ADJ
fcis-13148	49	7	local	local	ADJ
fcis-13148	49	8	features	feature	NOUN
fcis-13148	49	9	in	in	ADP
fcis-13148	49	10	the	the	DET
fcis-13148	49	11	image	image	NOUN
fcis-13148	49	12	,	,	PUNCT
fcis-13148	49	13	such	such	ADJ
fcis-13148	49	14	as	as	ADP
fcis-13148	49	15	edges	edge	NOUN
fcis-13148	49	16	and	and	CCONJ
fcis-13148	49	17	textures	texture	NOUN
fcis-13148	49	18	.	.	PUNCT
fcis-13148	50	1	simultaneously	simultaneously	ADV
fcis-13148	50	2	,	,	PUNCT
fcis-13148	50	3	the	the	DET
fcis-13148	50	4	convolutional	convolutional	ADJ
fcis-13148	50	5	layer	layer	NOUN
fcis-13148	50	6	possesses	possess	VERB
fcis-13148	50	7	characteristics	characteristic	NOUN
fcis-13148	50	8	of	of	ADP
fcis-13148	50	9	parameter	parameter	NOUN
fcis-13148	50	10	sharing	sharing	NOUN
fcis-13148	50	11	and	and	CCONJ
fcis-13148	50	12	sparse	sparse	ADJ
fcis-13148	50	13	connections	connection	NOUN
fcis-13148	50	14	,	,	PUNCT
fcis-13148	50	15	significantly	significantly	ADV
fcis-13148	50	16	reducing	reduce	VERB
fcis-13148	50	17	the	the	DET
fcis-13148	50	18	number	number	NOUN
fcis-13148	50	19	of	of	ADP
fcis-13148	50	20	network	network	NOUN
fcis-13148	50	21	parameters	parameter	NOUN
fcis-13148	50	22	and	and	CCONJ
fcis-13148	50	23	enhancing	enhance	VERB
fcis-13148	50	24	computational	computational	ADJ
fcis-13148	50	25	efficiency	efficiency	NOUN
fcis-13148	50	26	.	.	PUNCT
fcis-13148	51	1	although	although	SCONJ
fcis-13148	51	2	increasing	increase	VERB
fcis-13148	51	3	the	the	DET
fcis-13148	51	4	number	number	NOUN
fcis-13148	51	5	of	of	ADP
fcis-13148	51	6	network	network	NOUN
fcis-13148	51	7	layers	layer	NOUN
fcis-13148	51	8	improves	improve	VERB
fcis-13148	51	9	the	the	DET
fcis-13148	51	10	model	model	NOUN
fcis-13148	51	11	's	's	PART
fcis-13148	51	12	generalization	generalization	NOUN
fcis-13148	51	13	ability	ability	NOUN
fcis-13148	51	14	to	to	ADP
fcis-13148	51	15	some	some	DET
fcis-13148	51	16	extent	extent	NOUN
fcis-13148	51	17	,	,	PUNCT
fcis-13148	51	18	the	the	DET
fcis-13148	51	19	high	high	ADJ
fcis-13148	51	20	time	time	NOUN
fcis-13148	51	21	and	and	CCONJ
fcis-13148	51	22	space	space	NOUN
fcis-13148	51	23	complexity	complexity	NOUN
fcis-13148	51	24	constrain	constrain	VERB
fcis-13148	51	25	the	the	DET
fcis-13148	51	26	application	application	NOUN
fcis-13148	51	27	of	of	ADP
fcis-13148	51	28	deep	deep	ADJ
fcis-13148	51	29	convolutional	convolutional	ADJ
fcis-13148	51	30	neural	neural	ADJ
fcis-13148	51	31	networks	network	NOUN
fcis-13148	51	32	in	in	ADP
fcis-13148	51	33	resourceconstrained	resourceconstraine	VERB
fcis-13148	51	34	environments	environment	NOUN
fcis-13148	51	35	such	such	ADJ
fcis-13148	51	36	as	as	ADP
fcis-13148	51	37	mobile	mobile	ADJ
fcis-13148	51	38	phones	phone	NOUN
fcis-13148	51	39	and	and	CCONJ
fcis-13148	51	40	embedded	embed	VERB
fcis-13148	51	41	devices	device	NOUN
fcis-13148	51	42	[	[	X
fcis-13148	51	43	18	18	NUM
fcis-13148	51	44	]	]	PUNCT
fcis-13148	51	45	.	.	PUNCT
fcis-13148	52	1	to	to	PART
fcis-13148	52	2	address	address	VERB
fcis-13148	52	3	the	the	DET
fcis-13148	52	4	issue	issue	NOUN
fcis-13148	52	5	of	of	ADP
fcis-13148	52	6	low	low	ADJ
fcis-13148	52	7	computational	computational	ADJ
fcis-13148	52	8	efficiency	efficiency	NOUN
fcis-13148	52	9	in	in	ADP
fcis-13148	52	10	large	large	ADJ
fcis-13148	52	11	convolutional	convolutional	ADJ
fcis-13148	52	12	network	network	NOUN
fcis-13148	52	13	models	model	NOUN
fcis-13148	52	14	,	,	PUNCT
fcis-13148	52	15	a	a	DET
fcis-13148	52	16	network	network	NOUN
fcis-13148	52	17	structure	structure	NOUN
fcis-13148	52	18	is	be	AUX
fcis-13148	52	19	constructed	construct	VERB
fcis-13148	52	20	using	use	VERB
fcis-13148	52	21	the	the	DET
fcis-13148	52	22	residual	residual	ADJ
fcis-13148	52	23	neural	neural	ADJ
fcis-13148	52	24	network	network	NOUN
fcis-13148	52	25	-	-	PUNCT
fcis-13148	52	26	based	base	VERB
fcis-13148	52	27	approach	approach	NOUN
fcis-13148	52	28	.	.	PUNCT
fcis-13148	53	1	2.2	2.2	NUM
fcis-13148	53	2	.	.	PUNCT
fcis-13148	54	1	optimizing	optimize	VERB
fcis-13148	54	2	the	the	DET
fcis-13148	54	3	design	design	NOUN
fcis-13148	54	4	of	of	ADP
fcis-13148	54	5	cnn	cnn	PROPN
fcis-13148	54	6	2.2.1	2.2.1	NUM
fcis-13148	54	7	.	.	PUNCT
fcis-13148	54	8	introducing	introduce	VERB
fcis-13148	54	9	dilated	dilated	ADJ
fcis-13148	54	10	convolution	convolution	NOUN
fcis-13148	54	11	in	in	ADP
fcis-13148	54	12	dish	dish	NOUN
fcis-13148	54	13	recognition	recognition	NOUN
fcis-13148	54	14	networks	network	NOUN
fcis-13148	54	15	,	,	PUNCT
fcis-13148	54	16	the	the	DET
fcis-13148	54	17	first	first	ADJ
fcis-13148	54	18	layer	layer	NOUN
fcis-13148	54	19	's	's	PART
fcis-13148	54	20	convolution	convolution	NOUN
fcis-13148	54	21	operation	operation	NOUN
fcis-13148	54	22	is	be	AUX
fcis-13148	54	23	typically	typically	ADV
fcis-13148	54	24	employed	employ	VERB
fcis-13148	54	25	to	to	PART
fcis-13148	54	26	extract	extract	VERB
fcis-13148	54	27	low	low	ADJ
fcis-13148	54	28	-	-	PUNCT
fcis-13148	54	29	level	level	NOUN
fcis-13148	54	30	features	feature	NOUN
fcis-13148	54	31	from	from	ADP
fcis-13148	54	32	the	the	DET
fcis-13148	54	33	input	input	NOUN
fcis-13148	54	34	image	image	NOUN
fcis-13148	54	35	,	,	PUNCT
fcis-13148	54	36	such	such	ADJ
fcis-13148	54	37	as	as	ADP
fcis-13148	54	38	edges	edge	NOUN
fcis-13148	54	39	and	and	CCONJ
fcis-13148	54	40	color	color	NOUN
fcis-13148	54	41	information	information	NOUN
fcis-13148	54	42	.	.	PUNCT
fcis-13148	55	1	this	this	DET
fcis-13148	55	2	layer	layer	NOUN
fcis-13148	55	3	performs	perform	VERB
fcis-13148	55	4	convolution	convolution	NOUN
fcis-13148	55	5	operations	operation	NOUN
fcis-13148	55	6	on	on	ADP
fcis-13148	55	7	the	the	DET
fcis-13148	55	8	pixel	pixel	ADJ
fcis-13148	55	9	values	value	NOUN
fcis-13148	55	10	of	of	ADP
fcis-13148	55	11	the	the	DET
fcis-13148	55	12	input	input	NOUN
fcis-13148	55	13	image	image	NOUN
fcis-13148	55	14	with	with	ADP
fcis-13148	55	15	convolutional	convolutional	ADJ
fcis-13148	55	16	kernels	kernel	NOUN
fcis-13148	55	17	,	,	PUNCT
fcis-13148	55	18	resulting	result	VERB
fcis-13148	55	19	in	in	ADP
fcis-13148	55	20	a	a	DET
fcis-13148	55	21	new	new	ADJ
fcis-13148	55	22	set	set	NOUN
fcis-13148	55	23	of	of	ADP
fcis-13148	55	24	feature	feature	NOUN
fcis-13148	55	25	maps	map	NOUN
fcis-13148	55	26	that	that	PRON
fcis-13148	55	27	better	well	ADV
fcis-13148	55	28	represent	represent	VERB
fcis-13148	55	29	the	the	DET
fcis-13148	55	30	texture	texture	ADJ
fcis-13148	55	31	information	information	NOUN
fcis-13148	55	32	of	of	ADP
fcis-13148	55	33	the	the	DET
fcis-13148	55	34	input	input	NOUN
fcis-13148	55	35	image	image	NOUN
fcis-13148	55	36	.	.	PUNCT
fcis-13148	56	1	fig	fig	NOUN
fcis-13148	56	2	1	1	NUM
fcis-13148	56	3	.	.	PUNCT
fcis-13148	56	4	standard	standard	ADJ
fcis-13148	56	5	convolution	convolution	NOUN
fcis-13148	56	6	and	and	CCONJ
fcis-13148	56	7	dilated	dilated	ADJ
fcis-13148	56	8	convolution	convolution	NOUN
fcis-13148	56	9	the	the	DET
fcis-13148	56	10	advantage	advantage	NOUN
fcis-13148	56	11	of	of	ADP
fcis-13148	56	12	using	use	VERB
fcis-13148	56	13	dilated	dilated	ADJ
fcis-13148	56	14	convolution	convolution	NOUN
fcis-13148	56	15	[	[	X
fcis-13148	56	16	19	19	NUM
fcis-13148	56	17	]	]	PUNCT
fcis-13148	56	18	for	for	ADP
fcis-13148	56	19	feature	feature	NOUN
fcis-13148	56	20	extraction	extraction	NOUN
fcis-13148	56	21	in	in	ADP
fcis-13148	56	22	the	the	DET
fcis-13148	56	23	first	first	ADJ
fcis-13148	56	24	layer	layer	NOUN
fcis-13148	56	25	lies	lie	VERB
fcis-13148	56	26	in	in	ADP
fcis-13148	56	27	its	its	PRON
fcis-13148	56	28	ability	ability	NOUN
fcis-13148	56	29	to	to	PART
fcis-13148	56	30	increase	increase	VERB
fcis-13148	56	31	the	the	DET
fcis-13148	56	32	receptive	receptive	ADJ
fcis-13148	56	33	field	field	NOUN
fcis-13148	56	34	of	of	ADP
fcis-13148	56	35	the	the	DET
fcis-13148	56	36	convolutional	convolutional	ADJ
fcis-13148	56	37	kernel	kernel	NOUN
fcis-13148	57	1	[	[	X
fcis-13148	57	2	20	20	NUM
fcis-13148	57	3	]	]	PUNCT
fcis-13148	57	4	while	while	SCONJ
fcis-13148	57	5	maintaining	maintain	VERB
fcis-13148	57	6	the	the	DET
fcis-13148	57	7	output	output	NOUN
fcis-13148	57	8	resolution	resolution	NOUN
fcis-13148	57	9	.	.	PUNCT
fcis-13148	58	1	this	this	DET
fcis-13148	58	2	enhancement	enhancement	NOUN
fcis-13148	58	3	contributes	contribute	VERB
fcis-13148	58	4	to	to	ADP
fcis-13148	58	5	an	an	DET
fcis-13148	58	6	improved	improved	ADJ
fcis-13148	58	7	perceptual	perceptual	ADJ
fcis-13148	58	8	capability	capability	NOUN
fcis-13148	58	9	of	of	ADP
fcis-13148	58	10	the	the	DET
fcis-13148	58	11	network	network	NOUN
fcis-13148	58	12	.	.	PUNCT
fcis-13148	59	1	in	in	ADP
fcis-13148	59	2	comparison	comparison	NOUN
fcis-13148	59	3	to	to	ADP
fcis-13148	59	4	standard	standard	ADJ
fcis-13148	59	5	convolution	convolution	NOUN
fcis-13148	59	6	,	,	PUNCT
fcis-13148	59	7	dilated	dilated	ADJ
fcis-13148	59	8	convolution	convolution	NOUN
fcis-13148	59	9	also	also	ADV
fcis-13148	59	10	effectively	effectively	ADV
fcis-13148	59	11	reduces	reduce	VERB
fcis-13148	59	12	the	the	DET
fcis-13148	59	13	number	number	NOUN
fcis-13148	59	14	of	of	ADP
fcis-13148	59	15	parameters	parameter	NOUN
fcis-13148	59	16	,	,	PUNCT
fcis-13148	59	17	mitigates	mitigate	VERB
fcis-13148	59	18	the	the	DET
fcis-13148	59	19	risk	risk	NOUN
fcis-13148	59	20	of	of	ADP
fcis-13148	59	21	overfitting	overfitte	VERB
fcis-13148	59	22	,	,	PUNCT
fcis-13148	59	23	and	and	CCONJ
fcis-13148	59	24	accelerates	accelerate	VERB
fcis-13148	59	25	the	the	DET
fcis-13148	59	26	speed	speed	NOUN
fcis-13148	59	27	of	of	ADP
fcis-13148	59	28	convolutional	convolutional	ADJ
fcis-13148	59	29	computations	computation	NOUN
fcis-13148	59	30	,	,	PUNCT
fcis-13148	59	31	thereby	thereby	ADV
fcis-13148	59	32	enhancing	enhance	VERB
fcis-13148	59	33	the	the	DET
fcis-13148	59	34	operational	operational	ADJ
fcis-13148	59	35	efficiency	efficiency	NOUN
fcis-13148	59	36	of	of	ADP
fcis-13148	59	37	the	the	DET
fcis-13148	59	38	model	model	NOUN
fcis-13148	59	39	.	.	PUNCT
fcis-13148	60	1	figure	figure	NOUN
fcis-13148	60	2	1	1	NUM
fcis-13148	60	3	illustrates	illustrate	VERB
fcis-13148	60	4	examples	example	NOUN
fcis-13148	60	5	of	of	ADP
fcis-13148	60	6	standard	standard	ADJ
fcis-13148	60	7	convolution	convolution	NOUN
fcis-13148	60	8	(	(	PUNCT
fcis-13148	60	9	figure	figure	NOUN
fcis-13148	60	10	1a	1a	NOUN
fcis-13148	60	11	)	)	PUNCT
fcis-13148	60	12	and	and	CCONJ
fcis-13148	60	13	dilated	dilate	VERB
fcis-13148	60	14	convolution	convolution	NOUN
fcis-13148	60	15	(	(	PUNCT
fcis-13148	60	16	figure	figure	NOUN
fcis-13148	60	17	1b	1b	NUM
fcis-13148	60	18	)	)	PUNCT
fcis-13148	60	19	.	.	PUNCT
fcis-13148	61	1	2.2.2	2.2.2	X
fcis-13148	61	2	.	.	X
fcis-13148	61	3	fusion	fusion	NOUN
fcis-13148	61	4	of	of	ADP
fcis-13148	61	5	asymmetric	asymmetric	ADJ
fcis-13148	61	6	convolution	convolution	NOUN
fcis-13148	61	7	in	in	ADP
fcis-13148	61	8	rgb	rgb	PROPN
fcis-13148	61	9	bottleneck	bottleneck	NOUN
fcis-13148	61	10	traditional	traditional	ADJ
fcis-13148	61	11	lightweight	lightweight	ADJ
fcis-13148	61	12	networks	network	NOUN
fcis-13148	61	13	primarily	primarily	ADV
fcis-13148	61	14	rely	rely	VERB
fcis-13148	61	15	on	on	ADP
fcis-13148	61	16	depthwise	depthwise	NOUN
fcis-13148	61	17	separable	separable	ADJ
fcis-13148	61	18	convolution	convolution	NOUN
fcis-13148	61	19	for	for	ADP
fcis-13148	61	20	feature	feature	NOUN
fcis-13148	61	21	extraction	extraction	NOUN
fcis-13148	61	22	.	.	PUNCT
fcis-13148	62	1	although	although	SCONJ
fcis-13148	62	2	this	this	DET
fcis-13148	62	3	method	method	NOUN
fcis-13148	62	4	enhances	enhance	VERB
fcis-13148	62	5	computational	computational	ADJ
fcis-13148	62	6	efficiency	efficiency	NOUN
fcis-13148	62	7	,	,	PUNCT
fcis-13148	62	8	splitting	split	VERB
fcis-13148	62	9	the	the	DET
fcis-13148	62	10	convolution	convolution	NOUN
fcis-13148	62	11	operation	operation	NOUN
fcis-13148	62	12	into	into	ADP
fcis-13148	62	13	two	two	NUM
fcis-13148	62	14	parts	part	NOUN
fcis-13148	62	15	during	during	ADP
fcis-13148	62	16	the	the	DET
fcis-13148	62	17	separable	separable	ADJ
fcis-13148	62	18	operation	operation	NOUN
fcis-13148	62	19	leads	lead	VERB
fcis-13148	62	20	to	to	ADP
fcis-13148	62	21	the	the	DET
fcis-13148	62	22	loss	loss	NOUN
fcis-13148	62	23	of	of	ADP
fcis-13148	62	24	partial	partial	ADJ
fcis-13148	62	25	multi	multi	ADJ
fcis-13148	62	26	-	-	ADJ
fcis-13148	62	27	scale	scale	ADJ
fcis-13148	62	28	feature	feature	NOUN
fcis-13148	62	29	information	information	NOUN
fcis-13148	62	30	.	.	PUNCT
fcis-13148	63	1	to	to	PART
fcis-13148	63	2	address	address	VERB
fcis-13148	63	3	these	these	DET
fcis-13148	63	4	limitations	limitation	NOUN
fcis-13148	63	5	,	,	PUNCT
fcis-13148	63	6	a	a	DET
fcis-13148	63	7	method	method	NOUN
fcis-13148	63	8	to	to	PART
fcis-13148	63	9	improve	improve	VERB
fcis-13148	63	10	convolutional	convolutional	ADJ
fcis-13148	63	11	neural	neural	ADJ
fcis-13148	63	12	networks	network	NOUN
fcis-13148	63	13	is	be	AUX
fcis-13148	63	14	proposed	propose	VERB
fcis-13148	63	15	by	by	ADP
fcis-13148	63	16	introducing	introduce	VERB
fcis-13148	63	17	asymmetric	asymmetric	ADJ
fcis-13148	63	18	convolution	convolution	NOUN
fcis-13148	63	19	blocks	block	NOUN
fcis-13148	63	20	[	[	X
fcis-13148	63	21	21	21	NUM
fcis-13148	63	22	]	]	PUNCT
fcis-13148	63	23	.	.	PUNCT
fcis-13148	64	1	the	the	DET
fcis-13148	64	2	aim	aim	NOUN
fcis-13148	64	3	is	be	AUX
fcis-13148	64	4	to	to	PART
fcis-13148	64	5	enhance	enhance	VERB
fcis-13148	64	6	the	the	DET
fcis-13148	64	7	modeling	modeling	NOUN
fcis-13148	64	8	of	of	ADP
fcis-13148	64	9	geometric	geometric	ADJ
fcis-13148	64	10	deformations	deformation	NOUN
fcis-13148	64	11	by	by	ADP
fcis-13148	64	12	strengthening	strengthen	VERB
fcis-13148	64	13	the	the	DET
fcis-13148	64	14	information	information	NOUN
fcis-13148	64	15	in	in	ADP
fcis-13148	64	16	the	the	DET
fcis-13148	64	17	convolutional	convolutional	ADJ
fcis-13148	64	18	kernel	kernel	NOUN
fcis-13148	64	19	skeleton	skeleton	NOUN
fcis-13148	64	20	,	,	PUNCT
fcis-13148	64	21	thereby	thereby	ADV
fcis-13148	64	22	improving	improve	VERB
fcis-13148	64	23	the	the	DET
fcis-13148	64	24	network	network	NOUN
fcis-13148	64	25	's	's	PART
fcis-13148	64	26	ability	ability	NOUN
fcis-13148	64	27	to	to	PART
fcis-13148	64	28	model	model	VERB
fcis-13148	64	29	geometric	geometric	ADJ
fcis-13148	64	30	deformations	deformation	NOUN
fcis-13148	64	31	and	and	CCONJ
fcis-13148	64	32	enhance	enhance	VERB
fcis-13148	64	33	generalization	generalization	NOUN
fcis-13148	64	34	performance	performance	NOUN
fcis-13148	64	35	.	.	PUNCT
fcis-13148	65	1	the	the	DET
fcis-13148	65	2	rgb	rgb	PROPN
fcis-13148	65	3	bottleneck	bottleneck	NOUN
fcis-13148	65	4	block	block	NOUN
fcis-13148	65	5	of	of	ADP
fcis-13148	65	6	asymmetric	asymmetric	ADJ
fcis-13148	65	7	convolution	convolution	NOUN
fcis-13148	65	8	consists	consist	VERB
fcis-13148	65	9	of	of	ADP
fcis-13148	65	10	three	three	NUM
fcis-13148	65	11	parallel	parallel	ADJ
fcis-13148	65	12	layers	layer	NOUN
fcis-13148	65	13	,	,	PUNCT
fcis-13148	65	14	each	each	PRON
fcis-13148	65	15	using	use	VERB
fcis-13148	65	16	convolutional	convolutional	ADJ
fcis-13148	65	17	kernels	kernel	NOUN
fcis-13148	65	18	of	of	ADP
fcis-13148	65	19	sizes	size	NOUN
fcis-13148	65	20	n×n	n×n	PROPN
fcis-13148	65	21	,	,	PUNCT
fcis-13148	65	22	1×n	1×n	NUM
fcis-13148	65	23	,	,	PUNCT
fcis-13148	65	24	and	and	CCONJ
fcis-13148	65	25	n×1	n×1	NOUN
fcis-13148	65	26	to	to	PART
fcis-13148	65	27	slide	slide	VERB
fcis-13148	65	28	and	and	CCONJ
fcis-13148	65	29	extract	extract	VERB
fcis-13148	65	30	features	feature	NOUN
fcis-13148	65	31	.	.	PUNCT
fcis-13148	66	1	after	after	ADP
fcis-13148	66	2	convolution	convolution	NOUN
fcis-13148	66	3	,	,	PUNCT
fcis-13148	66	4	batch	batch	NOUN
fcis-13148	66	5	normalization	normalization	NOUN
fcis-13148	66	6	is	be	AUX
fcis-13148	66	7	applied	apply	VERB
fcis-13148	66	8	to	to	ADP
fcis-13148	66	9	the	the	DET
fcis-13148	66	10	outputs	output	NOUN
fcis-13148	66	11	of	of	ADP
fcis-13148	66	12	the	the	DET
fcis-13148	66	13	three	three	NUM
fcis-13148	66	14	branches	branch	NOUN
fcis-13148	66	15	,	,	PUNCT
fcis-13148	66	16	and	and	CCONJ
fcis-13148	66	17	then	then	ADV
fcis-13148	66	18	the	the	DET
fcis-13148	66	19	outputs	output	NOUN
fcis-13148	66	20	of	of	ADP
fcis-13148	66	21	each	each	DET
fcis-13148	66	22	branch	branch	NOUN
fcis-13148	66	23	are	be	AUX
fcis-13148	66	24	summed	sum	VERB
fcis-13148	66	25	to	to	PART
fcis-13148	66	26	obtain	obtain	VERB
fcis-13148	66	27	a	a	DET
fcis-13148	66	28	rich	rich	ADJ
fcis-13148	66	29	feature	feature	NOUN
fcis-13148	66	30	space	space	NOUN
fcis-13148	66	31	.	.	PUNCT
fcis-13148	67	1	non	non	ADJ
fcis-13148	67	2	-	-	ADJ
fcis-13148	67	3	square	square	ADJ
fcis-13148	67	4	convolution	convolution	NOUN
fcis-13148	67	5	layers	layer	NOUN
fcis-13148	67	6	,	,	PUNCT
fcis-13148	67	7	such	such	ADJ
fcis-13148	67	8	as	as	ADP
fcis-13148	67	9	1×d	1×d	NUM
fcis-13148	67	10	and	and	CCONJ
fcis-13148	67	11	d×1	d×1	NOUN
fcis-13148	67	12	,	,	PUNCT
fcis-13148	67	13	are	be	AUX
fcis-13148	67	14	utilized	utilize	VERB
fcis-13148	67	15	.	.	PUNCT
fcis-13148	68	1	the	the	DET
fcis-13148	68	2	additivity	additivity	NOUN
fcis-13148	68	3	property	property	NOUN
fcis-13148	68	4	of	of	ADP
fcis-13148	68	5	convolution	convolution	NOUN
fcis-13148	68	6	is	be	AUX
fcis-13148	68	7	leveraged	leverage	VERB
fcis-13148	68	8	,	,	PUNCT
fcis-13148	68	9	as	as	SCONJ
fcis-13148	68	10	shown	show	VERB
fcis-13148	68	11	in	in	ADP
fcis-13148	68	12	the	the	DET
fcis-13148	68	13	following	follow	VERB
fcis-13148	68	14	formula	formula	NOUN
fcis-13148	68	15	(	(	PUNCT
fcis-13148	68	16	equation	equation	NOUN
fcis-13148	68	17	1	1	NUM
fcis-13148	68	18	)	)	PUNCT
fcis-13148	68	19	.	.	PUNCT
fcis-13148	69	1	c	c	NOUN
fcis-13148	69	2	∗	∗	PROPN
fcis-13148	69	3	k	k	PROPN
fcis-13148	69	4	c	c	PROPN
fcis-13148	69	5	∗	∗	X
fcis-13148	69	6	k	k	PROPN
fcis-13148	69	7	c	c	PROPN
fcis-13148	69	8	∗	∗	PROPN
fcis-13148	69	9	k	k	PROPN
fcis-13148	69	10	∗	∗	PROPN
fcis-13148	69	11	k	k	PROPN
fcis-13148	69	12	⨁	⨁	PROPN
fcis-13148	69	13	k	k	PROPN
fcis-13148	69	14	⨁	⨁	PROPN
fcis-13148	69	15	⨁	⨁	PROPN
fcis-13148	69	16	k	k	PROPN
fcis-13148	69	17	∗	∗	X
fcis-13148	69	18	(	(	PUNCT
fcis-13148	69	19	1	1	NUM
fcis-13148	69	20	)	)	PUNCT
fcis-13148	69	21	where	where	SCONJ
fcis-13148	69	22	a	a	PRON
fcis-13148	69	23	represents	represent	VERB
fcis-13148	69	24	the	the	DET
fcis-13148	69	25	equivalent	equivalent	ADJ
fcis-13148	69	26	output	output	NOUN
fcis-13148	69	27	,	,	PUNCT
fcis-13148	69	28	c	c	PROPN
fcis-13148	69	29	is	be	AUX
fcis-13148	69	30	the	the	DET
fcis-13148	69	31	input	input	NOUN
fcis-13148	69	32	,	,	PUNCT
fcis-13148	69	33	k	k	PROPN
fcis-13148	69	34	is	be	AUX
fcis-13148	69	35	the	the	DET
fcis-13148	69	36	2d	2d	NUM
fcis-13148	69	37	convolutional	convolutional	ADJ
fcis-13148	69	38	kernel	kernel	NOUN
fcis-13148	69	39	,	,	PUNCT
fcis-13148	69	40	and	and	CCONJ
fcis-13148	69	41	p	p	NOUN
fcis-13148	69	42	is	be	AUX
fcis-13148	69	43	the	the	DET
fcis-13148	69	44	number	number	NOUN
fcis-13148	69	45	of	of	ADP
fcis-13148	69	46	convolutional	convolutional	ADJ
fcis-13148	69	47	kernels	kernel	NOUN
fcis-13148	69	48	,	,	PUNCT
fcis-13148	69	49	if	if	SCONJ
fcis-13148	69	50	there	there	PRON
fcis-13148	69	51	exist	exist	VERB
fcis-13148	69	52	p	p	NOUN
fcis-13148	69	53	size	size	NOUN
fcis-13148	69	54	-	-	PUNCT
fcis-13148	69	55	compatible	compatible	ADJ
fcis-13148	69	56	2d	2d	NUM
fcis-13148	69	57	kernels	kernel	NOUN
fcis-13148	69	58	(	(	PUNCT
fcis-13148	69	59	kp	kp	PROPN
fcis-13148	69	60	)	)	PUNCT
fcis-13148	69	61	that	that	PRON
fcis-13148	69	62	,	,	PUNCT
fcis-13148	69	63	when	when	SCONJ
fcis-13148	69	64	applied	apply	VERB
fcis-13148	69	65	with	with	ADP
fcis-13148	69	66	the	the	DET
fcis-13148	69	67	same	same	ADJ
fcis-13148	69	68	stride	stride	NOUN
fcis-13148	69	69	on	on	ADP
fcis-13148	69	70	the	the	DET
fcis-13148	69	71	same	same	ADJ
fcis-13148	69	72	input	input	NOUN
fcis-13148	69	73	c	c	NOUN
fcis-13148	69	74	,	,	PUNCT
fcis-13148	69	75	generate	generate	VERB
fcis-13148	69	76	outputs	output	NOUN
fcis-13148	69	77	with	with	ADP
fcis-13148	69	78	the	the	DET
fcis-13148	69	79	same	same	ADJ
fcis-13148	69	80	resolution	resolution	NOUN
fcis-13148	69	81	,	,	PUNCT
fcis-13148	69	82	and	and	CCONJ
fcis-13148	69	83	if	if	SCONJ
fcis-13148	69	84	the	the	DET
fcis-13148	69	85	sum	sum	NOUN
fcis-13148	69	86	of	of	ADP
fcis-13148	69	87	these	these	DET
fcis-13148	69	88	outputs	output	NOUN
fcis-13148	69	89	is	be	AUX
fcis-13148	69	90	denoted	denote	VERB
fcis-13148	69	91	as	as	ADP
fcis-13148	69	92	a	a	PRON
fcis-13148	69	93	,	,	PUNCT
fcis-13148	69	94	then	then	ADV
fcis-13148	69	95	the	the	DET
fcis-13148	69	96	corresponding	correspond	VERB
fcis-13148	69	97	kernels	kernel	NOUN
fcis-13148	69	98	at	at	ADP
fcis-13148	69	99	each	each	DET
fcis-13148	69	100	position	position	NOUN
fcis-13148	69	101	can	can	AUX
fcis-13148	69	102	be	be	AUX
fcis-13148	69	103	summed	sum	VERB
fcis-13148	69	104	to	to	PART
fcis-13148	69	105	form	form	VERB
fcis-13148	69	106	an	an	DET
fcis-13148	69	107	equivalent	equivalent	ADJ
fcis-13148	69	108	kernel	kernel	NOUN
fcis-13148	69	109	k.	k.	PROPN
fcis-13148	70	1	this	this	DET
fcis-13148	70	2	equivalent	equivalent	ADJ
fcis-13148	70	3	kernel	kernel	NOUN
fcis-13148	70	4	k	k	PROPN
fcis-13148	70	5	produces	produce	VERB
fcis-13148	70	6	the	the	DET
fcis-13148	70	7	same	same	ADJ
fcis-13148	70	8	output	output	NOUN
fcis-13148	70	9	a	a	PRON
fcis-13148	70	10	when	when	SCONJ
fcis-13148	70	11	applied	apply	VERB
fcis-13148	70	12	to	to	ADP
fcis-13148	70	13	the	the	DET
fcis-13148	70	14	same	same	ADJ
fcis-13148	70	15	input	input	NOUN
fcis-13148	70	16	.	.	PUNCT
fcis-13148	71	1	the	the	DET
fcis-13148	71	2	rgb	rgb	PROPN
fcis-13148	71	3	bottleneck	bottleneck	NOUN
fcis-13148	71	4	structure	structure	NOUN
fcis-13148	71	5	is	be	AUX
fcis-13148	71	6	illustrated	illustrate	VERB
fcis-13148	71	7	in	in	ADP
fcis-13148	71	8	figure	figure	NOUN
fcis-13148	71	9	2	2	NUM
fcis-13148	71	10	,	,	PUNCT
fcis-13148	71	11	where	where	SCONJ
fcis-13148	71	12	figure	figure	NOUN
fcis-13148	71	13	2(a	2(a	NUM
fcis-13148	71	14	)	)	PUNCT
fcis-13148	71	15	depicts	depict	VERB
fcis-13148	71	16	the	the	DET
fcis-13148	71	17	rgb	rgb	PROPN
fcis-13148	71	18	bottleneck	bottleneck	NOUN
fcis-13148	71	19	structure	structure	NOUN
fcis-13148	71	20	with	with	ADP
fcis-13148	71	21	a	a	DET
fcis-13148	71	22	stride	stride	NOUN
fcis-13148	71	23	of	of	ADP
fcis-13148	71	24	1	1	NUM
fcis-13148	71	25	,	,	PUNCT
fcis-13148	71	26	and	and	CCONJ
fcis-13148	71	27	figure	figure	VERB
fcis-13148	71	28	2(b	2(b	NUM
fcis-13148	71	29	)	)	PUNCT
fcis-13148	71	30	represents	represent	VERB
fcis-13148	71	31	the	the	DET
fcis-13148	71	32	rgb	rgb	PROPN
fcis-13148	71	33	bottleneck	bottleneck	NOUN
fcis-13148	71	34	structure	structure	NOUN
fcis-13148	71	35	with	with	ADP
fcis-13148	71	36	a	a	DET
fcis-13148	71	37	stride	stride	NOUN
fcis-13148	71	38	of	of	ADP
fcis-13148	71	39	2	2	NUM
fcis-13148	71	40	.	.	PUNCT
fcis-13148	71	41	fig	fig	NOUN
fcis-13148	71	42	2	2	NUM
fcis-13148	71	43	.	.	PUNCT
fcis-13148	72	1	rgb	rgb	PROPN
fcis-13148	72	2	bottleneck	bottleneck	NOUN
fcis-13148	72	3	150	150	NUM
fcis-13148	72	4	2.2.3	2.2.3	NUM
fcis-13148	72	5	.	.	PUNCT
fcis-13148	73	1	attention	attention	NOUN
fcis-13148	73	2	module	module	NOUN
fcis-13148	73	3	to	to	PART
fcis-13148	73	4	enhance	enhance	VERB
fcis-13148	73	5	geometric	geometric	ADJ
fcis-13148	73	6	deformation	deformation	NOUN
fcis-13148	73	7	performance	performance	NOUN
fcis-13148	73	8	by	by	ADP
fcis-13148	73	9	introducing	introduce	VERB
fcis-13148	73	10	a	a	DET
fcis-13148	73	11	decoupled	decouple	VERB
fcis-13148	73	12	fully	fully	ADV
fcis-13148	73	13	connected	connect	VERB
fcis-13148	73	14	(	(	PUNCT
fcis-13148	73	15	dfc	dfc	NOUN
fcis-13148	73	16	)	)	PUNCT
fcis-13148	73	17	attention	attention	NOUN
fcis-13148	73	18	mechanism	mechanism	NOUN
fcis-13148	73	19	branch	branch	NOUN
fcis-13148	73	20	,	,	PUNCT
fcis-13148	73	21	implemented	implement	VERB
fcis-13148	73	22	with	with	ADP
fcis-13148	73	23	asymmetric	asymmetric	ADJ
fcis-13148	73	24	convolutions	convolution	NOUN
fcis-13148	73	25	employing	employ	VERB
fcis-13148	73	26	unequal	unequal	ADJ
fcis-13148	73	27	horizontal	horizontal	ADJ
fcis-13148	73	28	and	and	CCONJ
fcis-13148	73	29	vertical	vertical	ADJ
fcis-13148	73	30	convolutions	convolution	NOUN
fcis-13148	74	1	[	[	X
fcis-13148	74	2	22	22	NUM
fcis-13148	74	3	]	]	PUNCT
fcis-13148	74	4	,	,	PUNCT
fcis-13148	74	5	into	into	ADP
fcis-13148	74	6	the	the	DET
fcis-13148	74	7	rgb	rgb	PROPN
fcis-13148	74	8	bottleneck	bottleneck	NOUN
fcis-13148	74	9	structure	structure	NOUN
fcis-13148	74	10	,	,	PUNCT
fcis-13148	74	11	the	the	DET
fcis-13148	74	12	model	model	NOUN
fcis-13148	74	13	captures	capture	VERB
fcis-13148	74	14	richer	rich	ADJ
fcis-13148	74	15	image	image	NOUN
fcis-13148	74	16	features	feature	NOUN
fcis-13148	74	17	using	use	VERB
fcis-13148	74	18	distinct	distinct	ADJ
fcis-13148	74	19	convolution	convolution	NOUN
fcis-13148	74	20	kernels	kernel	NOUN
fcis-13148	74	21	in	in	ADP
fcis-13148	74	22	different	different	ADJ
fcis-13148	74	23	directions	direction	NOUN
fcis-13148	74	24	.	.	PUNCT
fcis-13148	75	1	this	this	PRON
fcis-13148	75	2	significantly	significantly	ADV
fcis-13148	75	3	enhances	enhance	VERB
fcis-13148	75	4	the	the	DET
fcis-13148	75	5	model	model	NOUN
fcis-13148	75	6	's	's	PART
fcis-13148	75	7	capability	capability	NOUN
fcis-13148	75	8	to	to	PART
fcis-13148	75	9	capture	capture	VERB
fcis-13148	75	10	long	long	ADJ
fcis-13148	75	11	-	-	PUNCT
fcis-13148	75	12	range	range	NOUN
fcis-13148	75	13	spatial	spatial	ADJ
fcis-13148	75	14	information	information	NOUN
fcis-13148	75	15	and	and	CCONJ
fcis-13148	75	16	representation	representation	NOUN
fcis-13148	75	17	power	power	NOUN
fcis-13148	75	18	in	in	ADP
fcis-13148	75	19	images	image	NOUN
fcis-13148	75	20	.	.	PUNCT
fcis-13148	76	1	for	for	ADP
fcis-13148	76	2	a	a	DET
fcis-13148	76	3	given	give	VERB
fcis-13148	76	4	input	input	NOUN
fcis-13148	76	5	h	h	NOUN
fcis-13148	76	6	w	w	NOUN
fcis-13148	76	7	cz	cz	PROPN
fcis-13148	76	8			PROPN
fcis-13148	76	9			PROPN
fcis-13148	76	10	,	,	PUNCT
fcis-13148	76	11	which	which	PRON
fcis-13148	76	12	can	can	AUX
fcis-13148	76	13	be	be	AUX
fcis-13148	76	14	regarded	regard	VERB
fcis-13148	76	15	as	as	ADP
fcis-13148	76	16	a	a	DET
fcis-13148	76	17	tensor	tensor	NOUN
fcis-13148	76	18	of	of	ADP
fcis-13148	76	19	size	size	NOUN
fcis-13148	76	20	h*w	h*w	PROPN
fcis-13148	76	21	,	,	PUNCT
fcis-13148	76	22	the	the	DET
fcis-13148	76	23	mathematical	mathematical	ADJ
fcis-13148	76	24	expression	expression	NOUN
fcis-13148	76	25	for	for	ADP
fcis-13148	76	26	implementing	implement	VERB
fcis-13148	76	27	the	the	DET
fcis-13148	76	28	attention	attention	NOUN
fcis-13148	76	29	map	map	NOUN
fcis-13148	76	30	using	use	VERB
fcis-13148	76	31	an	an	DET
fcis-13148	76	32	ordinary	ordinary	ADJ
fcis-13148	76	33	fully	fully	ADV
fcis-13148	76	34	connected	connect	VERB
fcis-13148	76	35	layer	layer	NOUN
fcis-13148	76	36	is	be	AUX
fcis-13148	76	37	shown	show	VERB
fcis-13148	76	38	in	in	ADP
fcis-13148	76	39	equation	equation	NOUN
fcis-13148	76	40	(	(	PUNCT
fcis-13148	76	41	2	2	NUM
fcis-13148	76	42	):	):	PUNCT
fcis-13148	76	43	∑	∑	PUNCT
fcis-13148	76	44	,	,	PUNCT
fcis-13148	76	45	⨀	⨀	PROPN
fcis-13148	76	46	(	(	PUNCT
fcis-13148	76	47	2	2	NUM
fcis-13148	76	48	)	)	PUNCT
fcis-13148	76	49	in	in	ADP
fcis-13148	76	50	the	the	DET
fcis-13148	76	51	equation	equation	NOUN
fcis-13148	76	52	,	,	PUNCT
fcis-13148	76	53	⊙	⊙	PROPN
fcis-13148	76	54	denotes	denote	VERB
fcis-13148	76	55	element	element	ADJ
fcis-13148	76	56	-	-	PUNCT
fcis-13148	76	57	wise	wise	ADJ
fcis-13148	76	58	multiplication	multiplication	NOUN
fcis-13148	76	59	,	,	PUNCT
fcis-13148	76	60	represents	represent	VERB
fcis-13148	76	61	the	the	DET
fcis-13148	76	62	learnable	learnable	ADJ
fcis-13148	76	63	weights	weight	NOUN
fcis-13148	76	64	in	in	ADP
fcis-13148	76	65	the	the	DET
fcis-13148	76	66	fully	fully	ADV
fcis-13148	76	67	connected	connect	VERB
fcis-13148	76	68	layer	layer	NOUN
fcis-13148	76	69	,	,	PUNCT
fcis-13148	76	70	and	and	CCONJ
fcis-13148	76	71	is	be	AUX
fcis-13148	76	72	the	the	DET
fcis-13148	76	73	obtained	obtain	VERB
fcis-13148	76	74	attention	attention	NOUN
fcis-13148	76	75	map	map	NOUN
fcis-13148	76	76	,	,	PUNCT
fcis-13148	76	77	and	and	CCONJ
fcis-13148	76	78	zis	zi	NOUN
fcis-13148	76	79	the	the	DET
fcis-13148	76	80	original	original	ADJ
fcis-13148	76	81	feature	feature	NOUN
fcis-13148	76	82	.	.	PUNCT
fcis-13148	77	1	by	by	ADP
fcis-13148	77	2	decoupling	decouple	VERB
fcis-13148	77	3	equation	equation	NOUN
fcis-13148	77	4	(	(	PUNCT
fcis-13148	77	5	1	1	NUM
fcis-13148	77	6	)	)	PUNCT
fcis-13148	77	7	along	along	ADP
fcis-13148	77	8	both	both	CCONJ
fcis-13148	77	9	the	the	DET
fcis-13148	77	10	horizontal	horizontal	ADJ
fcis-13148	77	11	and	and	CCONJ
fcis-13148	77	12	vertical	vertical	ADJ
fcis-13148	77	13	directions	direction	NOUN
fcis-13148	77	14	,	,	PUNCT
fcis-13148	77	15	long	long	ADJ
fcis-13148	77	16	-	-	PUNCT
fcis-13148	77	17	range	range	NOUN
fcis-13148	77	18	correlations	correlation	NOUN
fcis-13148	77	19	in	in	ADP
fcis-13148	77	20	both	both	DET
fcis-13148	77	21	directions	direction	NOUN
fcis-13148	77	22	can	can	AUX
fcis-13148	77	23	be	be	AUX
fcis-13148	77	24	captured	capture	VERB
fcis-13148	77	25	,	,	PUNCT
fcis-13148	77	26	resulting	result	VERB
fcis-13148	77	27	in	in	ADP
fcis-13148	77	28	attention	attention	NOUN
fcis-13148	77	29	weights	weight	NOUN
fcis-13148	77	30	.	.	PUNCT
fcis-13148	78	1	the	the	DET
fcis-13148	78	2	feature	feature	NOUN
fcis-13148	78	3	aggregation	aggregation	NOUN
fcis-13148	78	4	processes	process	NOUN
fcis-13148	78	5	in	in	ADP
fcis-13148	78	6	the	the	DET
fcis-13148	78	7	horizontal	horizontal	ADJ
fcis-13148	78	8	and	and	CCONJ
fcis-13148	78	9	vertical	vertical	ADJ
fcis-13148	78	10	directions	direction	NOUN
fcis-13148	78	11	are	be	AUX
fcis-13148	78	12	illustrated	illustrate	VERB
fcis-13148	78	13	in	in	ADP
fcis-13148	78	14	equations	equation	NOUN
fcis-13148	78	15	(	(	PUNCT
fcis-13148	78	16	3	3	NUM
fcis-13148	78	17	)	)	PUNCT
fcis-13148	78	18	and	and	CCONJ
fcis-13148	78	19	(	(	PUNCT
fcis-13148	78	20	4	4	NUM
fcis-13148	78	21	)	)	PUNCT
fcis-13148	78	22	.	.	PUNCT
fcis-13148	79	1	(	(	PUNCT
fcis-13148	79	2	3	3	X
fcis-13148	79	3	)	)	PUNCT
fcis-13148	79	4	(	(	PUNCT
fcis-13148	79	5	4	4	X
fcis-13148	79	6	)	)	PUNCT
fcis-13148	79	7	in	in	ADP
fcis-13148	79	8	the	the	DET
fcis-13148	79	9	equation	equation	NOUN
fcis-13148	79	10	,	,	PUNCT
fcis-13148	79	11	in	in	ADP
fcis-13148	79	12	the	the	DET
fcis-13148	79	13	formula	formula	NOUN
fcis-13148	79	14	,	,	PUNCT
fcis-13148	79	15	represents	represent	VERB
fcis-13148	79	16	horizontal	horizontal	ADJ
fcis-13148	79	17	weights	weight	NOUN
fcis-13148	79	18	,	,	PUNCT
fcis-13148	79	19	represents	represent	VERB
fcis-13148	79	20	vertical	vertical	ADJ
fcis-13148	79	21	weights	weight	NOUN
fcis-13148	79	22	.	.	PUNCT
fcis-13148	80	1	the	the	DET
fcis-13148	80	2	dfc	dfc	NOUN
fcis-13148	80	3	(	(	PUNCT
fcis-13148	80	4	decoupled	decouple	VERB
fcis-13148	80	5	fully	fully	ADV
fcis-13148	80	6	connected	connect	VERB
fcis-13148	80	7	)	)	PUNCT
fcis-13148	80	8	attention	attention	NOUN
fcis-13148	80	9	mechanism	mechanism	NOUN
fcis-13148	80	10	is	be	AUX
fcis-13148	80	11	illustrated	illustrate	VERB
fcis-13148	80	12	in	in	ADP
fcis-13148	80	13	figure	figure	NOUN
fcis-13148	80	14	3	3	NUM
fcis-13148	80	15	.	.	PUNCT
fcis-13148	80	16	fig	fig	PROPN
fcis-13148	80	17	3	3	NUM
fcis-13148	80	18	.	.	PUNCT
fcis-13148	80	19	dfc	dfc	NOUN
fcis-13148	80	20	attention	attention	NOUN
fcis-13148	80	21	mechanism	mechanism	NOUN
fcis-13148	80	22	3	3	X
fcis-13148	80	23	.	.	PUNCT
fcis-13148	80	24	rgbnet	rgbnet	ADJ
fcis-13148	80	25	model	model	NOUN
fcis-13148	80	26	architecture	architecture	NOUN
fcis-13148	80	27	considering	consider	VERB
fcis-13148	80	28	the	the	DET
fcis-13148	80	29	small	small	ADJ
fcis-13148	80	30	inter	inter	ADJ
fcis-13148	80	31	-	-	ADJ
fcis-13148	80	32	class	class	ADJ
fcis-13148	80	33	differences	difference	NOUN
fcis-13148	80	34	and	and	CCONJ
fcis-13148	80	35	large	large	ADJ
fcis-13148	80	36	intra	intra	ADJ
fcis-13148	80	37	-	-	ADJ
fcis-13148	80	38	class	class	ADJ
fcis-13148	80	39	differences	difference	NOUN
fcis-13148	80	40	in	in	ADP
fcis-13148	80	41	the	the	DET
fcis-13148	80	42	chinese	chinese	ADJ
fcis-13148	80	43	cuisine	cuisine	NOUN
fcis-13148	80	44	dataset	dataset	PROPN
fcis-13148	80	45	,	,	PUNCT
fcis-13148	80	46	a	a	DET
fcis-13148	80	47	lightweight	lightweight	ADJ
fcis-13148	80	48	recognition	recognition	NOUN
fcis-13148	80	49	approach	approach	NOUN
fcis-13148	80	50	for	for	ADP
fcis-13148	80	51	sichuan	sichuan	PROPN
fcis-13148	80	52	dishes	dish	NOUN
fcis-13148	80	53	is	be	AUX
fcis-13148	80	54	proposed	propose	VERB
fcis-13148	80	55	,	,	PUNCT
fcis-13148	80	56	aiming	aim	VERB
fcis-13148	80	57	to	to	PART
fcis-13148	80	58	address	address	VERB
fcis-13148	80	59	the	the	DET
fcis-13148	80	60	task	task	NOUN
fcis-13148	80	61	of	of	ADP
fcis-13148	80	62	recognizing	recognize	VERB
fcis-13148	80	63	sichuan	sichuan	PROPN
fcis-13148	80	64	cuisine	cuisine	NOUN
fcis-13148	80	65	images	image	NOUN
fcis-13148	80	66	on	on	ADP
fcis-13148	80	67	edge	edge	NOUN
fcis-13148	80	68	devices	device	NOUN
fcis-13148	80	69	such	such	ADJ
fcis-13148	80	70	as	as	ADP
fcis-13148	80	71	mobile	mobile	ADJ
fcis-13148	80	72	phones	phone	NOUN
fcis-13148	80	73	.	.	PUNCT
fcis-13148	81	1	the	the	DET
fcis-13148	81	2	model	model	NOUN
fcis-13148	81	3	consists	consist	VERB
fcis-13148	81	4	of	of	ADP
fcis-13148	81	5	three	three	NUM
fcis-13148	81	6	main	main	ADJ
fcis-13148	81	7	parts	part	NOUN
fcis-13148	81	8	.	.	PUNCT
fcis-13148	82	1	firstly	firstly	ADV
fcis-13148	82	2	,	,	PUNCT
fcis-13148	82	3	in	in	ADP
fcis-13148	82	4	the	the	DET
fcis-13148	82	5	first	first	ADJ
fcis-13148	82	6	layer	layer	NOUN
fcis-13148	82	7	of	of	ADP
fcis-13148	82	8	the	the	DET
fcis-13148	82	9	network	network	NOUN
fcis-13148	82	10	,	,	PUNCT
fcis-13148	82	11	dilated	dilated	ADJ
fcis-13148	82	12	convolution	convolution	NOUN
fcis-13148	82	13	is	be	AUX
fcis-13148	82	14	employed	employ	VERB
fcis-13148	82	15	for	for	ADP
fcis-13148	82	16	feature	feature	NOUN
fcis-13148	82	17	extraction	extraction	NOUN
fcis-13148	82	18	,	,	PUNCT
fcis-13148	82	19	significantly	significantly	ADV
fcis-13148	82	20	reducing	reduce	VERB
fcis-13148	82	21	the	the	DET
fcis-13148	82	22	model	model	NOUN
fcis-13148	82	23	's	's	PART
fcis-13148	82	24	parameter	parameter	NOUN
fcis-13148	82	25	count	count	NOUN
fcis-13148	82	26	while	while	SCONJ
fcis-13148	82	27	maintaining	maintain	VERB
fcis-13148	82	28	accuracy	accuracy	NOUN
fcis-13148	82	29	,	,	PUNCT
fcis-13148	82	30	thereby	thereby	ADV
fcis-13148	82	31	enhancing	enhance	VERB
fcis-13148	82	32	computational	computational	ADJ
fcis-13148	82	33	efficiency	efficiency	NOUN
fcis-13148	82	34	.	.	PUNCT
fcis-13148	83	1	the	the	DET
fcis-13148	83	2	second	second	ADJ
fcis-13148	83	3	part	part	NOUN
fcis-13148	83	4	is	be	AUX
fcis-13148	83	5	primarily	primarily	ADV
fcis-13148	83	6	composed	compose	VERB
fcis-13148	83	7	of	of	ADP
fcis-13148	83	8	the	the	DET
fcis-13148	83	9	resghost	resghost	ADJ
fcis-13148	83	10	bottleneck	bottleneck	NOUN
fcis-13148	83	11	structure	structure	NOUN
fcis-13148	83	12	proposed	propose	VERB
fcis-13148	83	13	in	in	ADP
fcis-13148	83	14	this	this	DET
fcis-13148	83	15	paper	paper	NOUN
fcis-13148	83	16	,	,	PUNCT
fcis-13148	83	17	which	which	PRON
fcis-13148	83	18	employs	employ	VERB
fcis-13148	83	19	cost	cost	NOUN
fcis-13148	83	20	-	-	PUNCT
fcis-13148	83	21	effective	effective	ADJ
fcis-13148	83	22	operations	operation	NOUN
fcis-13148	83	23	[	[	X
fcis-13148	83	24	23	23	NUM
fcis-13148	83	25	]	]	PUNCT
fcis-13148	83	26	to	to	PART
fcis-13148	83	27	break	break	VERB
fcis-13148	83	28	down	down	ADP
fcis-13148	83	29	larger	large	ADJ
fcis-13148	83	30	convolutional	convolutional	ADJ
fcis-13148	83	31	layers	layer	NOUN
fcis-13148	83	32	into	into	ADP
fcis-13148	83	33	subnetworks	subnetwork	NOUN
fcis-13148	83	34	with	with	ADP
fcis-13148	83	35	shared	share	VERB
fcis-13148	83	36	weights	weight	NOUN
fcis-13148	83	37	.	.	PUNCT
fcis-13148	84	1	residual	residual	ADJ
fcis-13148	84	2	convolution	convolution	NOUN
fcis-13148	84	3	is	be	AUX
fcis-13148	84	4	utilized	utilize	VERB
fcis-13148	84	5	to	to	PART
fcis-13148	84	6	improve	improve	VERB
fcis-13148	84	7	the	the	DET
fcis-13148	84	8	model	model	NOUN
fcis-13148	84	9	's	's	PART
fcis-13148	84	10	generalization	generalization	NOUN
fcis-13148	84	11	ability	ability	NOUN
fcis-13148	84	12	and	and	CCONJ
fcis-13148	84	13	efficiency	efficiency	NOUN
fcis-13148	84	14	.	.	PUNCT
fcis-13148	85	1	the	the	DET
fcis-13148	85	2	third	third	ADJ
fcis-13148	85	3	part	part	NOUN
fcis-13148	85	4	introduces	introduce	VERB
fcis-13148	85	5	the	the	DET
fcis-13148	85	6	decoupled	decoupled	ADJ
fcis-13148	85	7	fully	fully	ADV
fcis-13148	85	8	connected	connected	ADJ
fcis-13148	85	9	attention	attention	NOUN
fcis-13148	85	10	mechanism	mechanism	NOUN
fcis-13148	85	11	(	(	PUNCT
fcis-13148	85	12	dfc	dfc	NOUN
fcis-13148	85	13	)	)	PUNCT
fcis-13148	85	14	,	,	PUNCT
fcis-13148	85	15	designed	design	VERB
fcis-13148	85	16	to	to	PART
fcis-13148	85	17	facilitate	facilitate	VERB
fcis-13148	85	18	long	long	ADJ
fcis-13148	85	19	-	-	PUNCT
fcis-13148	85	20	range	range	NOUN
fcis-13148	85	21	communication	communication	NOUN
fcis-13148	85	22	.	.	PUNCT
fcis-13148	86	1	it	it	PRON
fcis-13148	86	2	incorporates	incorporate	VERB
fcis-13148	86	3	dynamic	dynamic	ADJ
fcis-13148	86	4	normalization	normalization	NOUN
fcis-13148	86	5	parameters	parameter	NOUN
fcis-13148	86	6	to	to	PART
fcis-13148	86	7	adjust	adjust	VERB
fcis-13148	86	8	feature	feature	NOUN
fcis-13148	86	9	values	value	NOUN
fcis-13148	86	10	in	in	ADP
fcis-13148	86	11	different	different	ADJ
fcis-13148	86	12	regions	region	NOUN
fcis-13148	86	13	,	,	PUNCT
fcis-13148	86	14	ultimately	ultimately	ADV
fcis-13148	86	15	achieving	achieve	VERB
fcis-13148	86	16	information	information	NOUN
fcis-13148	86	17	exchange	exchange	NOUN
fcis-13148	86	18	and	and	CCONJ
fcis-13148	86	19	feature	feature	NOUN
fcis-13148	86	20	calibration	calibration	NOUN
fcis-13148	86	21	between	between	ADP
fcis-13148	86	22	different	different	ADJ
fcis-13148	86	23	regions	region	NOUN
fcis-13148	86	24	.	.	PUNCT
fcis-13148	87	1	the	the	DET
fcis-13148	87	2	structure	structure	NOUN
fcis-13148	87	3	of	of	ADP
fcis-13148	87	4	the	the	DET
fcis-13148	87	5	established	establish	VERB
fcis-13148	87	6	rgbnet	rgbnet	ADJ
fcis-13148	87	7	network	network	NOUN
fcis-13148	87	8	is	be	AUX
fcis-13148	87	9	shown	show	VERB
fcis-13148	87	10	in	in	ADP
fcis-13148	87	11	table	table	NOUN
fcis-13148	87	12	1	1	NUM
fcis-13148	87	13	.	.	PUNCT
fcis-13148	87	14	table	table	NOUN
fcis-13148	87	15	1	1	NUM
fcis-13148	87	16	.	.	PUNCT
fcis-13148	87	17	rgbnet	rgbnet	ADJ
fcis-13148	87	18	network	network	NOUN
fcis-13148	87	19	architecture	architecture	NOUN
fcis-13148	87	20	input	input	NOUN
fcis-13148	87	21	features	feature	VERB
fcis-13148	87	22	operation	operation	NOUN
fcis-13148	87	23	repetition	repetition	NOUN
fcis-13148	87	24	count	count	NOUN
fcis-13148	87	25	output	output	NOUN
fcis-13148	87	26	depth	depth	NOUN
fcis-13148	87	27	stride	stride	NOUN
fcis-13148	87	28	2242	2242	NUM
fcis-13148	87	29	x	x	SYM
fcis-13148	87	30	3	3	NUM
fcis-13148	87	31	5x5dilated	5x5dilate	VERB
fcis-13148	87	32	convolution	convolution	NOUN
fcis-13148	87	33	1	1	NUM
fcis-13148	87	34	16	16	NUM
fcis-13148	87	35	2	2	NUM
fcis-13148	87	36	1122	1122	NUM
fcis-13148	87	37	x	x	SYM
fcis-13148	87	38	16	16	NUM
fcis-13148	87	39	rgb	rgb	PROPN
fcis-13148	87	40	bottlenet	bottlenet	NOUN
fcis-13148	87	41	2	2	NUM
fcis-13148	87	42	24	24	NUM
fcis-13148	87	43	2	2	NUM
fcis-13148	87	44	562	562	NUM
fcis-13148	87	45	x	x	SYM
fcis-13148	87	46	24	24	NUM
fcis-13148	87	47	rgb	rgb	PROPN
fcis-13148	87	48	bottlenet	bottlenet	NOUN
fcis-13148	87	49	2	2	NUM
fcis-13148	87	50	40	40	NUM
fcis-13148	87	51	2	2	NUM
fcis-13148	87	52	282	282	NUM
fcis-13148	87	53	x	x	SYM
fcis-13148	87	54	40	40	NUM
fcis-13148	87	55	rgb	rgb	PROPN
fcis-13148	87	56	bottlenet	bottlenet	NOUN
fcis-13148	87	57	4	4	NUM
fcis-13148	87	58	80	80	NUM
fcis-13148	87	59	2	2	NUM
fcis-13148	87	60	142	142	NUM
fcis-13148	87	61	x	x	SYM
fcis-13148	87	62	112	112	NUM
fcis-13148	87	63	rgb	rgb	PROPN
fcis-13148	87	64	bottlenet	bottlenet	NOUN
fcis-13148	87	65	6	6	NUM
fcis-13148	87	66	160	160	NUM
fcis-13148	87	67	2	2	NUM
fcis-13148	87	68	72	72	NUM
fcis-13148	87	69	x	x	SYM
fcis-13148	87	70	160	160	NUM
fcis-13148	87	71	rgb	rgb	PROPN
fcis-13148	87	72	bottlenet	bottlenet	NOUN
fcis-13148	87	73	4	4	NUM
fcis-13148	87	74	160	160	NUM
fcis-13148	87	75	1	1	NUM
fcis-13148	87	76	72	72	NUM
fcis-13148	87	77	x	x	SYM
fcis-13148	87	78	160	160	NUM
fcis-13148	87	79	1x1conv	1x1conv	NUM
fcis-13148	87	80	1	1	NUM
fcis-13148	87	81	960	960	NUM
fcis-13148	87	82	1	1	NUM
fcis-13148	87	83	72	72	NUM
fcis-13148	87	84	x	x	SYM
fcis-13148	87	85	960	960	NUM
fcis-13148	87	86	7x7	7x7	NUM
fcis-13148	87	87	average	average	ADJ
fcis-13148	87	88	pooling	pool	VERB
fcis-13148	87	89	1	1	NUM
fcis-13148	87	90	12	12	NUM
fcis-13148	87	91	x	x	SYM
fcis-13148	87	92	960	960	NUM
fcis-13148	87	93	1x1conv	1x1conv	NUM
fcis-13148	87	94	1	1	NUM
fcis-13148	87	95	1280	1280	NUM
fcis-13148	87	96	1	1	NUM
fcis-13148	87	97	12	12	NUM
fcis-13148	87	98	x	x	SYM
fcis-13148	87	99	1280	1280	NUM
fcis-13148	87	100	fc	fc	NOUN
fcis-13148	87	101	convolution	convolution	NOUN
fcis-13148	87	102	1	1	NUM
fcis-13148	87	103	30	30	NUM
fcis-13148	87	104	151	151	NUM
fcis-13148	87	105	4	4	NUM
fcis-13148	87	106	.	.	PUNCT
fcis-13148	87	107	minichinesefood	minichinesefood	PROPN
fcis-13148	87	108	dataset	dataset	VERB
fcis-13148	87	109	chinesefoodnet	chinesefoodnet	NOUN
fcis-13148	88	1	[	[	X
fcis-13148	88	2	24	24	NUM
fcis-13148	88	3	]	]	PUNCT
fcis-13148	88	4	is	be	AUX
fcis-13148	88	5	a	a	DET
fcis-13148	88	6	large	large	ADJ
fcis-13148	88	7	-	-	PUNCT
fcis-13148	88	8	scale	scale	NOUN
fcis-13148	88	9	dataset	dataset	NOUN
fcis-13148	88	10	of	of	ADP
fcis-13148	88	11	food	food	NOUN
fcis-13148	88	12	images	image	NOUN
fcis-13148	88	13	,	,	PUNCT
fcis-13148	88	14	comprising	comprise	VERB
fcis-13148	88	15	208	208	NUM
fcis-13148	88	16	classes	class	NOUN
fcis-13148	88	17	with	with	ADP
fcis-13148	88	18	a	a	DET
fcis-13148	88	19	total	total	NOUN
fcis-13148	88	20	of	of	ADP
fcis-13148	88	21	180,000	180,000	NUM
fcis-13148	88	22	images	image	NOUN
fcis-13148	88	23	featuring	feature	VERB
fcis-13148	88	24	various	various	ADJ
fcis-13148	88	25	culinary	culinary	ADJ
fcis-13148	88	26	styles	style	NOUN
fcis-13148	88	27	from	from	ADP
fcis-13148	88	28	different	different	ADJ
fcis-13148	88	29	regions	region	NOUN
fcis-13148	88	30	in	in	ADP
fcis-13148	88	31	china	china	PROPN
fcis-13148	88	32	.	.	PUNCT
fcis-13148	89	1	each	each	DET
fcis-13148	89	2	dish	dish	NOUN
fcis-13148	89	3	is	be	AUX
fcis-13148	89	4	represented	represent	VERB
fcis-13148	89	5	by	by	ADP
fcis-13148	89	6	images	image	NOUN
fcis-13148	89	7	capturing	capture	VERB
fcis-13148	89	8	significant	significant	ADJ
fcis-13148	89	9	variations	variation	NOUN
fcis-13148	89	10	in	in	ADP
fcis-13148	89	11	angles	angle	NOUN
fcis-13148	89	12	,	,	PUNCT
fcis-13148	89	13	lighting	lighting	NOUN
fcis-13148	89	14	conditions	condition	NOUN
fcis-13148	89	15	,	,	PUNCT
fcis-13148	89	16	and	and	CCONJ
fcis-13148	89	17	plating	plating	NOUN
fcis-13148	89	18	.	.	PUNCT
fcis-13148	90	1	however	however	ADV
fcis-13148	90	2	,	,	PUNCT
fcis-13148	90	3	due	due	ADP
fcis-13148	90	4	to	to	ADP
fcis-13148	90	5	the	the	DET
fcis-13148	90	6	dataset	dataset	NOUN
fcis-13148	90	7	's	's	PART
fcis-13148	90	8	inclusion	inclusion	NOUN
fcis-13148	90	9	of	of	ADP
fcis-13148	90	10	a	a	DET
fcis-13148	90	11	substantial	substantial	ADJ
fcis-13148	90	12	number	number	NOUN
fcis-13148	90	13	of	of	ADP
fcis-13148	90	14	visually	visually	ADV
fcis-13148	90	15	distinct	distinct	ADJ
fcis-13148	90	16	dishes	dish	NOUN
fcis-13148	90	17	,	,	PUNCT
fcis-13148	90	18	which	which	PRON
fcis-13148	90	19	tend	tend	VERB
fcis-13148	90	20	to	to	PART
fcis-13148	90	21	achieve	achieve	VERB
fcis-13148	90	22	high	high	ADJ
fcis-13148	90	23	scores	score	NOUN
fcis-13148	90	24	during	during	ADP
fcis-13148	90	25	network	network	NOUN
fcis-13148	90	26	training	training	NOUN
fcis-13148	90	27	,	,	PUNCT
fcis-13148	90	28	it	it	PRON
fcis-13148	90	29	lacks	lack	VERB
fcis-13148	90	30	representativeness	representativeness	ADJ
fcis-13148	90	31	.	.	PUNCT
fcis-13148	91	1	to	to	PART
fcis-13148	91	2	address	address	VERB
fcis-13148	91	3	this	this	PRON
fcis-13148	91	4	,	,	PUNCT
fcis-13148	91	5	30	30	NUM
fcis-13148	91	6	classes	class	NOUN
fcis-13148	91	7	were	be	AUX
fcis-13148	91	8	extracted	extract	VERB
fcis-13148	91	9	from	from	ADP
fcis-13148	91	10	the	the	DET
fcis-13148	91	11	chinesefoodnet	chinesefoodnet	NOUN
fcis-13148	91	12	dataset	dataset	NOUN
fcis-13148	91	13	,	,	PUNCT
fcis-13148	91	14	resulting	result	VERB
fcis-13148	91	15	in	in	ADP
fcis-13148	91	16	a	a	DET
fcis-13148	91	17	practical	practical	ADJ
fcis-13148	91	18	set	set	NOUN
fcis-13148	91	19	of	of	ADP
fcis-13148	91	20	20,000	20,000	NUM
fcis-13148	91	21	images	image	NOUN
fcis-13148	91	22	.	.	PUNCT
fcis-13148	92	1	through	through	ADP
fcis-13148	92	2	data	data	NOUN
fcis-13148	92	3	augmentation	augmentation	NOUN
fcis-13148	92	4	techniques	technique	NOUN
fcis-13148	92	5	,	,	PUNCT
fcis-13148	92	6	including	include	VERB
fcis-13148	92	7	random	random	ADJ
fcis-13148	92	8	augmentation	augmentation	NOUN
fcis-13148	92	9	[	[	X
fcis-13148	92	10	25	25	NUM
fcis-13148	92	11	]	]	PUNCT
fcis-13148	92	12	and	and	CCONJ
fcis-13148	92	13	random	random	ADJ
fcis-13148	92	14	erasing	erasing	NOUN
fcis-13148	92	15	[	[	X
fcis-13148	92	16	26	26	NUM
fcis-13148	92	17	]	]	PUNCT
fcis-13148	92	18	,	,	PUNCT
fcis-13148	92	19	the	the	DET
fcis-13148	92	20	original	original	ADJ
fcis-13148	92	21	image	image	NOUN
fcis-13148	92	22	count	count	NOUN
fcis-13148	92	23	was	be	AUX
fcis-13148	92	24	expanded	expand	VERB
fcis-13148	92	25	to	to	ADP
fcis-13148	92	26	100,000	100,000	NUM
fcis-13148	92	27	images	image	NOUN
fcis-13148	92	28	.	.	PUNCT
fcis-13148	93	1	this	this	DET
fcis-13148	93	2	extended	extend	VERB
fcis-13148	93	3	dataset	dataset	NOUN
fcis-13148	93	4	is	be	AUX
fcis-13148	93	5	named	name	VERB
fcis-13148	93	6	minichinesefood	minichinesefood	NOUN
fcis-13148	93	7	,	,	PUNCT
fcis-13148	93	8	and	and	CCONJ
fcis-13148	93	9	it	it	PRON
fcis-13148	93	10	was	be	AUX
fcis-13148	93	11	divided	divide	VERB
fcis-13148	93	12	into	into	ADP
fcis-13148	93	13	a	a	DET
fcis-13148	93	14	training	training	NOUN
fcis-13148	93	15	set	set	NOUN
fcis-13148	93	16	and	and	CCONJ
fcis-13148	93	17	a	a	DET
fcis-13148	93	18	test	test	NOUN
fcis-13148	93	19	set	set	VERB
fcis-13148	93	20	in	in	ADP
fcis-13148	93	21	a	a	DET
fcis-13148	93	22	4:1	4:1	NUM
fcis-13148	93	23	ratio	ratio	NOUN
fcis-13148	93	24	for	for	ADP
fcis-13148	93	25	model	model	NOUN
fcis-13148	93	26	training	training	NOUN
fcis-13148	93	27	.	.	PUNCT
fcis-13148	94	1	some	some	DET
fcis-13148	94	2	images	image	NOUN
fcis-13148	94	3	from	from	ADP
fcis-13148	94	4	the	the	DET
fcis-13148	94	5	minichinesefood	minichinesefood	NOUN
fcis-13148	94	6	dataset	dataset	VERB
fcis-13148	94	7	are	be	AUX
fcis-13148	94	8	shown	show	VERB
fcis-13148	94	9	in	in	ADP
fcis-13148	94	10	figure	figure	NOUN
fcis-13148	94	11	4	4	NUM
fcis-13148	94	12	.	.	PUNCT
fcis-13148	94	13	fig	fig	NOUN
fcis-13148	94	14	4	4	NUM
fcis-13148	94	15	.	.	PUNCT
fcis-13148	95	1	minichinesefood	minichinesefood	PROPN
fcis-13148	95	2	dataset	dataset	VERB
fcis-13148	95	3	the	the	DET
fcis-13148	95	4	selected	select	VERB
fcis-13148	95	5	images	image	NOUN
fcis-13148	95	6	from	from	ADP
fcis-13148	95	7	the	the	DET
fcis-13148	95	8	chinesefoodnet	chinesefoodnet	NOUN
fcis-13148	95	9	dataset	dataset	NOUN
fcis-13148	95	10	adhere	adhere	ADV
fcis-13148	95	11	to	to	ADP
fcis-13148	95	12	the	the	DET
fcis-13148	95	13	following	follow	VERB
fcis-13148	95	14	criteria	criterion	NOUN
fcis-13148	95	15	:	:	PUNCT
fcis-13148	95	16	ensuring	ensure	VERB
fcis-13148	95	17	low	low	ADJ
fcis-13148	95	18	intra	intra	ADJ
fcis-13148	95	19	-	-	ADJ
fcis-13148	95	20	class	class	ADJ
fcis-13148	95	21	similarity	similarity	NOUN
fcis-13148	95	22	among	among	ADP
fcis-13148	95	23	extracted	extract	VERB
fcis-13148	95	24	dish	dish	NOUN
fcis-13148	95	25	images	image	NOUN
fcis-13148	95	26	,	,	PUNCT
fcis-13148	95	27	such	such	ADJ
fcis-13148	95	28	as	as	ADP
fcis-13148	95	29	different	different	ADJ
fcis-13148	95	30	shapes	shape	NOUN
fcis-13148	95	31	of	of	ADP
fcis-13148	95	32	ingredients	ingredient	NOUN
fcis-13148	95	33	(	(	PUNCT
fcis-13148	95	34	a	a	PRON
fcis-13148	95	35	and	and	CCONJ
fcis-13148	95	36	b	b	NOUN
fcis-13148	95	37	)	)	PUNCT
fcis-13148	95	38	,	,	PUNCT
fcis-13148	95	39	varied	varied	ADJ
fcis-13148	95	40	plating	plating	NOUN
fcis-13148	95	41	(	(	PUNCT
fcis-13148	95	42	c	c	NOUN
fcis-13148	95	43	and	and	CCONJ
fcis-13148	95	44	d	d	NOUN
fcis-13148	95	45	)	)	PUNCT
fcis-13148	95	46	,	,	PUNCT
fcis-13148	95	47	and	and	CCONJ
fcis-13148	95	48	distinct	distinct	ADJ
fcis-13148	95	49	types	type	NOUN
fcis-13148	95	50	of	of	ADP
fcis-13148	95	51	ingredients	ingredient	NOUN
fcis-13148	95	52	despite	despite	SCONJ
fcis-13148	95	53	having	have	VERB
fcis-13148	95	54	the	the	DET
fcis-13148	95	55	same	same	ADJ
fcis-13148	95	56	name	name	NOUN
fcis-13148	95	57	(	(	PUNCT
fcis-13148	95	58	e	e	NOUN
fcis-13148	95	59	,	,	PUNCT
fcis-13148	95	60	f	f	PROPN
fcis-13148	95	61	)	)	PUNCT
fcis-13148	95	62	;	;	PUNCT
fcis-13148	95	63	maintaining	maintain	VERB
fcis-13148	95	64	high	high	ADJ
fcis-13148	95	65	inter	inter	ADJ
fcis-13148	95	66	-	-	ADJ
fcis-13148	95	67	class	class	ADJ
fcis-13148	95	68	similarity	similarity	NOUN
fcis-13148	95	69	among	among	ADP
fcis-13148	95	70	extracted	extract	VERB
fcis-13148	95	71	dish	dish	NOUN
fcis-13148	95	72	images	image	NOUN
fcis-13148	95	73	,	,	PUNCT
fcis-13148	95	74	for	for	ADP
fcis-13148	95	75	instance	instance	NOUN
fcis-13148	95	76	,	,	PUNCT
fcis-13148	95	77	different	different	ADJ
fcis-13148	95	78	types	type	NOUN
fcis-13148	95	79	of	of	ADP
fcis-13148	95	80	ingredients	ingredient	NOUN
fcis-13148	95	81	(	(	PUNCT
fcis-13148	95	82	g	g	NOUN
fcis-13148	95	83	and	and	CCONJ
fcis-13148	95	84	h	h	NOUN
fcis-13148	95	85	)	)	PUNCT
fcis-13148	95	86	,	,	PUNCT
fcis-13148	95	87	different	different	ADJ
fcis-13148	95	88	cooking	cooking	NOUN
fcis-13148	95	89	methods	method	NOUN
fcis-13148	95	90	(	(	PUNCT
fcis-13148	95	91	i	i	NOUN
fcis-13148	95	92	and	and	CCONJ
fcis-13148	95	93	j	j	PROPN
fcis-13148	95	94	)	)	PUNCT
fcis-13148	95	95	for	for	ADP
fcis-13148	95	96	the	the	DET
fcis-13148	95	97	same	same	ADJ
fcis-13148	95	98	ingredient	ingredient	NOUN
fcis-13148	95	99	,	,	PUNCT
fcis-13148	95	100	and	and	CCONJ
fcis-13148	95	101	dishes	dish	NOUN
fcis-13148	95	102	with	with	ADP
fcis-13148	95	103	different	different	ADJ
fcis-13148	95	104	ingredients	ingredient	NOUN
fcis-13148	95	105	and	and	CCONJ
fcis-13148	95	106	cooking	cooking	NOUN
fcis-13148	95	107	methods	method	NOUN
fcis-13148	95	108	that	that	PRON
fcis-13148	95	109	appear	appear	VERB
fcis-13148	95	110	similar	similar	ADJ
fcis-13148	95	111	but	but	CCONJ
fcis-13148	95	112	belong	belong	VERB
fcis-13148	95	113	to	to	ADP
fcis-13148	95	114	different	different	ADJ
fcis-13148	95	115	categories	category	NOUN
fcis-13148	95	116	(	(	PUNCT
fcis-13148	95	117	k	k	NOUN
fcis-13148	95	118	and	and	CCONJ
fcis-13148	95	119	l	l	NOUN
fcis-13148	95	120	)	)	PUNCT
fcis-13148	95	121	.	.	PUNCT
fcis-13148	96	1	5	5	X
fcis-13148	96	2	.	.	X
fcis-13148	96	3	experimental	experimental	ADJ
fcis-13148	96	4	design	design	NOUN
fcis-13148	96	5	and	and	CCONJ
fcis-13148	96	6	analysis	analysis	NOUN
fcis-13148	96	7	5.1	5.1	NUM
fcis-13148	96	8	.	.	PUNCT
fcis-13148	96	9	model	model	NOUN
fcis-13148	96	10	training	training	NOUN
fcis-13148	96	11	and	and	CCONJ
fcis-13148	96	12	result	result	VERB
fcis-13148	96	13	analysis	analysis	NOUN
fcis-13148	96	14	to	to	PART
fcis-13148	96	15	evaluate	evaluate	VERB
fcis-13148	96	16	the	the	DET
fcis-13148	96	17	performance	performance	NOUN
fcis-13148	96	18	of	of	ADP
fcis-13148	96	19	the	the	DET
fcis-13148	96	20	rgbnet	rgbnet	ADJ
fcis-13148	96	21	network	network	NOUN
fcis-13148	96	22	in	in	ADP
fcis-13148	96	23	recognizing	recognize	VERB
fcis-13148	96	24	sichuan	sichuan	PROPN
fcis-13148	96	25	cuisine	cuisine	NOUN
fcis-13148	96	26	images	image	NOUN
fcis-13148	96	27	,	,	PUNCT
fcis-13148	96	28	this	this	DET
fcis-13148	96	29	study	study	NOUN
fcis-13148	96	30	selected	select	VERB
fcis-13148	96	31	representative	representative	ADJ
fcis-13148	96	32	lightweight	lightweight	PROPN
fcis-13148	96	33	cnn	cnn	PROPN
fcis-13148	96	34	networks	network	NOUN
fcis-13148	96	35	for	for	ADP
fcis-13148	96	36	performance	performance	NOUN
fcis-13148	96	37	comparison	comparison	NOUN
fcis-13148	96	38	,	,	PUNCT
fcis-13148	96	39	including	include	VERB
fcis-13148	96	40	mobilenetv2	mobilenetv2	PROPN
fcis-13148	96	41	,	,	PUNCT
fcis-13148	96	42	shufflenet	shufflenet	NOUN
fcis-13148	96	43	,	,	PUNCT
fcis-13148	96	44	efficientnet	efficientnet	NOUN
fcis-13148	96	45	,	,	PUNCT
fcis-13148	96	46	and	and	CCONJ
fcis-13148	96	47	fasternet	fasternet	NOUN
fcis-13148	96	48	.	.	PUNCT
fcis-13148	97	1	in	in	ADP
fcis-13148	97	2	the	the	DET
fcis-13148	97	3	rgbnet	rgbnet	NOUN
fcis-13148	97	4	,	,	PUNCT
fcis-13148	97	5	the	the	DET
fcis-13148	97	6	optimizer	optimizer	NOUN
fcis-13148	97	7	is	be	AUX
fcis-13148	97	8	sgd	sgd	NOUN
fcis-13148	97	9	,	,	PUNCT
fcis-13148	97	10	with	with	ADP
fcis-13148	97	11	a	a	DET
fcis-13148	97	12	learning	learning	NOUN
fcis-13148	97	13	rate	rate	NOUN
fcis-13148	97	14	(	(	PUNCT
fcis-13148	97	15	lr	lr	NOUN
fcis-13148	97	16	)	)	PUNCT
fcis-13148	97	17	of	of	ADP
fcis-13148	97	18	0.045	0.045	NUM
fcis-13148	97	19	,	,	PUNCT
fcis-13148	97	20	momentum	momentum	NOUN
fcis-13148	97	21	set	set	VERB
fcis-13148	97	22	to	to	ADP
fcis-13148	97	23	0.9	0.9	NUM
fcis-13148	97	24	,	,	PUNCT
fcis-13148	97	25	and	and	CCONJ
fcis-13148	97	26	weight	weight	NOUN
fcis-13148	97	27	decay	decay	NOUN
fcis-13148	97	28	(	(	PUNCT
fcis-13148	97	29	weight_decay	weight_decay	NOUN
fcis-13148	97	30	)	)	PUNCT
fcis-13148	97	31	of	of	ADP
fcis-13148	97	32	4e-05	4e-05	NUM
fcis-13148	97	33	.	.	PUNCT
fcis-13148	98	1	additionally	additionally	ADV
fcis-13148	98	2	,	,	PUNCT
fcis-13148	98	3	gradient	gradient	ADJ
fcis-13148	98	4	clipping	clipping	NOUN
fcis-13148	98	5	was	be	AUX
fcis-13148	98	6	not	not	PART
fcis-13148	98	7	applied	apply	VERB
fcis-13148	98	8	.	.	PUNCT
fcis-13148	99	1	the	the	DET
fcis-13148	99	2	learning	learning	NOUN
fcis-13148	99	3	rate	rate	NOUN
fcis-13148	99	4	was	be	AUX
fcis-13148	99	5	configured	configure	VERB
fcis-13148	99	6	using	use	VERB
fcis-13148	99	7	a	a	DET
fcis-13148	99	8	"	"	PUNCT
fcis-13148	99	9	step	step	NOUN
fcis-13148	99	10	"	"	PUNCT
fcis-13148	99	11	decay	decay	NOUN
fcis-13148	99	12	strategy	strategy	NOUN
fcis-13148	99	13	,	,	PUNCT
fcis-13148	99	14	where	where	SCONJ
fcis-13148	99	15	the	the	DET
fcis-13148	99	16	learning	learning	NOUN
fcis-13148	99	17	rate	rate	NOUN
fcis-13148	99	18	is	be	AUX
fcis-13148	99	19	multiplied	multiply	VERB
fcis-13148	99	20	by	by	ADP
fcis-13148	99	21	a	a	DET
fcis-13148	99	22	parameter	parameter	NOUN
fcis-13148	99	23	gamma	gamma	NOUN
fcis-13148	99	24	(	(	PUNCT
fcis-13148	99	25	set	set	VERB
fcis-13148	99	26	to	to	ADP
fcis-13148	99	27	0.98	0.98	NUM
fcis-13148	99	28	)	)	PUNCT
fcis-13148	99	29	after	after	ADP
fcis-13148	99	30	the	the	DET
fcis-13148	99	31	first	first	ADJ
fcis-13148	99	32	epoch	epoch	NOUN
fcis-13148	99	33	and	and	CCONJ
fcis-13148	99	34	gradually	gradually	ADV
fcis-13148	99	35	reduced	reduce	VERB
fcis-13148	99	36	in	in	ADP
fcis-13148	99	37	subsequent	subsequent	ADJ
fcis-13148	99	38	epochs	epoch	NOUN
fcis-13148	99	39	to	to	ADP
fcis-13148	99	40	fine	fine	ADJ
fcis-13148	99	41	-	-	PUNCT
fcis-13148	99	42	tune	tune	NOUN
fcis-13148	99	43	the	the	DET
fcis-13148	99	44	model	model	NOUN
fcis-13148	99	45	parameters	parameter	NOUN
fcis-13148	99	46	.	.	PUNCT
fcis-13148	100	1	the	the	DET
fcis-13148	100	2	changes	change	NOUN
fcis-13148	100	3	in	in	ADP
fcis-13148	100	4	model	model	NOUN
fcis-13148	100	5	accuracy	accuracy	NOUN
fcis-13148	100	6	and	and	CCONJ
fcis-13148	100	7	loss	loss	NOUN
fcis-13148	100	8	function	function	NOUN
fcis-13148	100	9	values	value	NOUN
fcis-13148	100	10	are	be	AUX
fcis-13148	100	11	illustrated	illustrate	VERB
fcis-13148	100	12	in	in	ADP
fcis-13148	100	13	figure	figure	NOUN
fcis-13148	100	14	5	5	NUM
fcis-13148	100	15	.	.	PUNCT
fcis-13148	100	16	from	from	ADP
fcis-13148	100	17	the	the	DET
fcis-13148	100	18	graph	graph	NOUN
fcis-13148	100	19	,	,	PUNCT
fcis-13148	100	20	it	it	PRON
fcis-13148	100	21	can	can	AUX
fcis-13148	100	22	be	be	AUX
fcis-13148	100	23	observed	observe	VERB
fcis-13148	100	24	that	that	SCONJ
fcis-13148	100	25	selecting	select	VERB
fcis-13148	100	26	top-1	top-1	DET
fcis-13148	100	27	accuracy	accuracy	NOUN
fcis-13148	100	28	as	as	ADP
fcis-13148	100	29	the	the	DET
fcis-13148	100	30	evaluation	evaluation	NOUN
fcis-13148	100	31	metric	metric	NOUN
fcis-13148	100	32	,	,	PUNCT
fcis-13148	100	33	at	at	ADP
fcis-13148	100	34	the	the	DET
fcis-13148	100	35	beginning	beginning	NOUN
fcis-13148	100	36	of	of	ADP
fcis-13148	100	37	training	training	NOUN
fcis-13148	100	38	,	,	PUNCT
fcis-13148	100	39	rgbnet	rgbnet	ADJ
fcis-13148	100	40	,	,	PUNCT
fcis-13148	100	41	like	like	ADP
fcis-13148	100	42	other	other	ADJ
fcis-13148	100	43	models	model	NOUN
fcis-13148	100	44	,	,	PUNCT
fcis-13148	100	45	exhibits	exhibit	VERB
fcis-13148	100	46	relatively	relatively	ADV
fcis-13148	100	47	low	low	ADJ
fcis-13148	100	48	accuracy	accuracy	NOUN
fcis-13148	100	49	.	.	PUNCT
fcis-13148	101	1	however	however	ADV
fcis-13148	101	2	,	,	PUNCT
fcis-13148	101	3	starting	start	VERB
fcis-13148	101	4	from	from	ADP
fcis-13148	101	5	the	the	DET
fcis-13148	101	6	10th	10th	ADJ
fcis-13148	101	7	epoch	epoch	NOUN
fcis-13148	101	8	,	,	PUNCT
fcis-13148	101	9	rgbnet	rgbnet	NOUN
fcis-13148	101	10	's	's	PART
fcis-13148	101	11	accuracy	accuracy	NOUN
fcis-13148	101	12	growth	growth	NOUN
fcis-13148	101	13	rate	rate	NOUN
fcis-13148	101	14	gradually	gradually	ADV
fcis-13148	101	15	surpasses	surpass	VERB
fcis-13148	101	16	other	other	ADJ
fcis-13148	101	17	networks	network	NOUN
fcis-13148	101	18	and	and	CCONJ
fcis-13148	101	19	reaches	reach	VERB
fcis-13148	101	20	its	its	PRON
fcis-13148	101	21	peak	peak	NOUN
fcis-13148	101	22	at	at	ADP
fcis-13148	101	23	the	the	DET
fcis-13148	101	24	196th	196th	ADJ
fcis-13148	101	25	epoch	epoch	NOUN
fcis-13148	101	26	.	.	PUNCT
fcis-13148	102	1	in	in	ADP
fcis-13148	102	2	comparison	comparison	NOUN
fcis-13148	102	3	to	to	ADP
fcis-13148	102	4	other	other	ADJ
fcis-13148	102	5	models	model	NOUN
fcis-13148	102	6	,	,	PUNCT
fcis-13148	102	7	which	which	PRON
fcis-13148	102	8	achieve	achieve	VERB
fcis-13148	102	9	convergence	convergence	NOUN
fcis-13148	102	10	around	around	ADP
fcis-13148	102	11	the	the	DET
fcis-13148	102	12	85th	85th	ADJ
fcis-13148	102	13	epoch	epoch	NOUN
fcis-13148	102	14	,	,	PUNCT
fcis-13148	102	15	rgbnet	rgbnet	NOUN
fcis-13148	102	16	converges	converge	VERB
fcis-13148	102	17	more	more	ADV
fcis-13148	102	18	slowly	slowly	ADV
fcis-13148	102	19	.	.	PUNCT
fcis-13148	103	1	this	this	PRON
fcis-13148	103	2	is	be	AUX
fcis-13148	103	3	attributed	attribute	VERB
fcis-13148	103	4	to	to	ADP
fcis-13148	103	5	the	the	DET
fcis-13148	103	6	resghost	resghost	ADJ
fcis-13148	103	7	module	module	NOUN
fcis-13148	103	8	requiring	require	VERB
fcis-13148	103	9	more	more	ADJ
fcis-13148	103	10	data	datum	NOUN
fcis-13148	103	11	for	for	ADP
fcis-13148	103	12	learning	learn	VERB
fcis-13148	103	13	to	to	PART
fcis-13148	103	14	achieve	achieve	VERB
fcis-13148	103	15	better	well	ADJ
fcis-13148	103	16	model	model	NOUN
fcis-13148	103	17	fitting	fitting	ADJ
fcis-13148	103	18	capability	capability	NOUN
fcis-13148	103	19	.	.	PUNCT
fcis-13148	104	1	after	after	ADP
fcis-13148	104	2	thorough	thorough	ADJ
fcis-13148	104	3	learning	learning	NOUN
fcis-13148	104	4	,	,	PUNCT
fcis-13148	104	5	all	all	DET
fcis-13148	104	6	performance	performance	NOUN
fcis-13148	104	7	metrics	metric	NOUN
fcis-13148	104	8	surpass	surpass	VERB
fcis-13148	104	9	those	those	PRON
fcis-13148	104	10	of	of	ADP
fcis-13148	104	11	the	the	DET
fcis-13148	104	12	comparative	comparative	ADJ
fcis-13148	104	13	models	model	NOUN
fcis-13148	104	14	,	,	PUNCT
fcis-13148	104	15	strongly	strongly	ADV
fcis-13148	104	16	indicating	indicate	VERB
fcis-13148	104	17	that	that	SCONJ
fcis-13148	104	18	rgbnet	rgbnet	ADJ
fcis-13148	104	19	possesses	possess	VERB
fcis-13148	104	20	robust	robust	ADJ
fcis-13148	104	21	feature	feature	NOUN
fcis-13148	104	22	extraction	extraction	NOUN
fcis-13148	104	23	and	and	CCONJ
fcis-13148	104	24	fitting	fitting	ADJ
fcis-13148	104	25	capabilities	capability	NOUN
fcis-13148	104	26	.	.	PUNCT
fcis-13148	105	1	(	(	PUNCT
fcis-13148	105	2	a	a	X
fcis-13148	105	3	)	)	PUNCT
fcis-13148	105	4	(	(	PUNCT
fcis-13148	105	5	b	b	X
fcis-13148	105	6	)	)	PUNCT
fcis-13148	105	7	fig	fig	NOUN
fcis-13148	105	8	5	5	NUM
fcis-13148	105	9	.	.	PUNCT
fcis-13148	106	1	(	(	PUNCT
fcis-13148	106	2	a	a	X
fcis-13148	106	3	)	)	PUNCT
fcis-13148	106	4	model	model	NOUN
fcis-13148	106	5	accuracy	accuracy	NOUN
fcis-13148	106	6	curve	curve	NOUN
fcis-13148	106	7	,	,	PUNCT
fcis-13148	106	8	(	(	PUNCT
fcis-13148	106	9	b	b	X
fcis-13148	106	10	)	)	PUNCT
fcis-13148	106	11	model	model	NOUN
fcis-13148	106	12	loss	loss	NOUN
fcis-13148	106	13	curve	curve	NOUN
fcis-13148	106	14	152	152	NUM
fcis-13148	106	15	table	table	NOUN
fcis-13148	106	16	2	2	NUM
fcis-13148	106	17	presents	present	VERB
fcis-13148	106	18	the	the	DET
fcis-13148	106	19	performance	performance	NOUN
fcis-13148	106	20	of	of	ADP
fcis-13148	106	21	the	the	DET
fcis-13148	106	22	model	model	NOUN
fcis-13148	106	23	on	on	ADP
fcis-13148	106	24	the	the	DET
fcis-13148	106	25	test	test	NOUN
fcis-13148	106	26	set	set	VERB
fcis-13148	106	27	after	after	ADP
fcis-13148	106	28	training	training	NOUN
fcis-13148	106	29	.	.	PUNCT
fcis-13148	107	1	compared	compare	VERB
fcis-13148	107	2	to	to	ADP
fcis-13148	107	3	other	other	ADJ
fcis-13148	107	4	models	model	NOUN
fcis-13148	107	5	,	,	PUNCT
fcis-13148	107	6	the	the	DET
fcis-13148	107	7	rgbnet	rgbnet	NOUN
fcis-13148	107	8	demonstrates	demonstrate	VERB
fcis-13148	107	9	excellent	excellent	ADJ
fcis-13148	107	10	performance	performance	NOUN
fcis-13148	107	11	,	,	PUNCT
fcis-13148	107	12	achieving	achieve	VERB
fcis-13148	107	13	an	an	DET
fcis-13148	107	14	accuracy	accuracy	NOUN
fcis-13148	107	15	of	of	ADP
fcis-13148	107	16	96.72	96.72	NUM
fcis-13148	107	17	%	%	NOUN
fcis-13148	107	18	,	,	PUNCT
fcis-13148	107	19	recall	recall	NOUN
fcis-13148	107	20	of	of	ADP
fcis-13148	107	21	0.9646	0.9646	NUM
fcis-13148	107	22	%	%	NOUN
fcis-13148	107	23	,	,	PUNCT
fcis-13148	107	24	precision	precision	NOUN
fcis-13148	107	25	of	of	ADP
fcis-13148	107	26	0.9739	0.9739	NUM
fcis-13148	107	27	%	%	NOUN
fcis-13148	107	28	,	,	PUNCT
fcis-13148	107	29	and	and	CCONJ
fcis-13148	107	30	an	an	DET
fcis-13148	107	31	f1	f1	ADJ
fcis-13148	107	32	score	score	NOUN
fcis-13148	107	33	of	of	ADP
fcis-13148	107	34	0.9625	0.9625	NUM
fcis-13148	107	35	%	%	NOUN
fcis-13148	107	36	.	.	PUNCT
fcis-13148	108	1	table	table	NOUN
fcis-13148	108	2	2	2	NUM
fcis-13148	108	3	.	.	PUNCT
fcis-13148	108	4	data	datum	NOUN
fcis-13148	108	5	results	result	VERB
fcis-13148	108	6	model	model	NOUN
fcis-13148	108	7	name	name	NOUN
fcis-13148	108	8	accuracy	accuracy	PROPN
fcis-13148	108	9	macro	macro	PROPN
fcis-13148	108	10	recall	recall	PROPN
fcis-13148	108	11	macro	macro	PROPN
fcis-13148	108	12	precision	precision	PROPN
fcis-13148	108	13	macro	macro	PROPN
fcis-13148	108	14	f1	f1	PROPN
fcis-13148	108	15	score	score	NOUN
fcis-13148	108	16	mobilenetv2	mobilenetv2	NOUN
fcis-13148	108	17	80.37	80.37	NUM
fcis-13148	108	18	%	%	NOUN
fcis-13148	108	19	0.8056	0.8056	NUM
fcis-13148	108	20	%	%	NOUN
fcis-13148	108	21	0.8173	0.8173	NUM
fcis-13148	108	22	0.8048	0.8048	NUM
fcis-13148	108	23	shufflenet	shufflenet	NOUN
fcis-13148	108	24	78.20	78.20	NUM
fcis-13148	108	25	%	%	NOUN
fcis-13148	108	26	0.7726	0.7726	NUM
fcis-13148	108	27	%	%	NOUN
fcis-13148	108	28	0.7812	0.7812	NUM
fcis-13148	108	29	0.7719	0.7719	NUM
fcis-13148	108	30	efficientnet	efficientnet	NOUN
fcis-13148	108	31	80.15	80.15	NUM
fcis-13148	108	32	%	%	NOUN
fcis-13148	108	33	0.7969	0.7969	NUM
fcis-13148	108	34	%	%	NOUN
fcis-13148	108	35	0.8116	0.8116	NUM
fcis-13148	108	36	0.8023	0.8023	NUM
fcis-13148	108	37	fasternet	fasternet	NOUN
fcis-13148	108	38	79.60	79.60	NUM
fcis-13148	108	39	%	%	NOUN
fcis-13148	108	40	0.7893	0.7893	NUM
fcis-13148	108	41	%	%	NOUN
fcis-13148	108	42	0.7965	0.7965	NUM
fcis-13148	108	43	0.7847	0.7847	NUM
fcis-13148	108	44	rgbnet	rgbnet	ADJ
fcis-13148	108	45	96.72	96.72	NUM
fcis-13148	108	46	%	%	NOUN
fcis-13148	108	47	0.9646	0.9646	NUM
fcis-13148	108	48	%	%	NOUN
fcis-13148	108	49	0.9739	0.9739	NUM
fcis-13148	108	50	0.9625	0.9625	NUM
fcis-13148	108	51	5.2	5.2	NUM
fcis-13148	108	52	.	.	PUNCT
fcis-13148	109	1	ablation	ablation	NOUN
fcis-13148	109	2	experiment	experiment	NOUN
fcis-13148	109	3	to	to	PART
fcis-13148	109	4	verify	verify	VERB
fcis-13148	109	5	the	the	DET
fcis-13148	109	6	impact	impact	NOUN
fcis-13148	109	7	of	of	ADP
fcis-13148	109	8	dilated	dilated	ADJ
fcis-13148	109	9	convolution	convolution	NOUN
fcis-13148	109	10	and	and	CCONJ
fcis-13148	109	11	dfc	dfc	NOUN
fcis-13148	109	12	attention	attention	NOUN
fcis-13148	109	13	mechanism	mechanism	NOUN
fcis-13148	109	14	on	on	ADP
fcis-13148	109	15	model	model	NOUN
fcis-13148	109	16	recognition	recognition	NOUN
fcis-13148	109	17	accuracy	accuracy	NOUN
fcis-13148	109	18	,	,	PUNCT
fcis-13148	109	19	rgbnet	rgbnet	ADJ
fcis-13148	109	20	(	(	PUNCT
fcis-13148	109	21	conv2d	conv2d	X
fcis-13148	109	22	)	)	PUNCT
fcis-13148	109	23	,	,	PUNCT
fcis-13148	109	24	rgbnet	rgbnet	PROPN
fcis-13148	109	25	(	(	PUNCT
fcis-13148	109	26	dilated	dilated	ADJ
fcis-13148	109	27	conv	conv	NOUN
fcis-13148	109	28	)	)	PUNCT
fcis-13148	109	29	,	,	PUNCT
fcis-13148	109	30	and	and	CCONJ
fcis-13148	109	31	rgbnet	rgbnet	ADJ
fcis-13148	109	32	(	(	PUNCT
fcis-13148	109	33	dilated	dilated	ADJ
fcis-13148	109	34	conv+dfc	conv+dfc	NOUN
fcis-13148	109	35	)	)	PUNCT
fcis-13148	109	36	were	be	AUX
fcis-13148	109	37	selected	select	VERB
fcis-13148	109	38	for	for	ADP
fcis-13148	109	39	ablation	ablation	NOUN
fcis-13148	109	40	experiments	experiment	NOUN
fcis-13148	109	41	.	.	PUNCT
fcis-13148	110	1	in	in	ADP
fcis-13148	110	2	rgbnet	rgbnet	NOUN
fcis-13148	110	3	(	(	PUNCT
fcis-13148	110	4	conv2d	conv2d	PROPN
fcis-13148	110	5	)	)	PUNCT
fcis-13148	110	6	,	,	PUNCT
fcis-13148	110	7	the	the	DET
fcis-13148	110	8	first	first	ADJ
fcis-13148	110	9	layer	layer	NOUN
fcis-13148	110	10	uses	use	VERB
fcis-13148	110	11	regular	regular	ADJ
fcis-13148	110	12	3×3	3×3	NUM
fcis-13148	110	13	convolution	convolution	NOUN
fcis-13148	110	14	;	;	PUNCT
fcis-13148	110	15	in	in	ADP
fcis-13148	110	16	rgbnet	rgbnet	NOUN
fcis-13148	110	17	(	(	PUNCT
fcis-13148	110	18	dilated	dilated	ADJ
fcis-13148	110	19	conv	conv	NOUN
fcis-13148	110	20	)	)	PUNCT
fcis-13148	110	21	,	,	PUNCT
fcis-13148	110	22	the	the	DET
fcis-13148	110	23	first	first	ADJ
fcis-13148	110	24	layer	layer	NOUN
fcis-13148	110	25	uses	use	VERB
fcis-13148	110	26	dilated	dilated	ADJ
fcis-13148	110	27	convolution	convolution	NOUN
fcis-13148	110	28	;	;	PUNCT
fcis-13148	110	29	and	and	CCONJ
fcis-13148	110	30	in	in	ADP
fcis-13148	110	31	rgbnet	rgbnet	NOUN
fcis-13148	110	32	(	(	PUNCT
fcis-13148	110	33	dilated	dilated	ADJ
fcis-13148	110	34	conv+dfc	conv+dfc	NOUN
fcis-13148	110	35	)	)	PUNCT
fcis-13148	110	36	,	,	PUNCT
fcis-13148	110	37	dfc	dfc	NOUN
fcis-13148	110	38	attention	attention	NOUN
fcis-13148	110	39	mechanism	mechanism	NOUN
fcis-13148	110	40	is	be	AUX
fcis-13148	110	41	incorporated	incorporate	VERB
fcis-13148	110	42	alongside	alongside	ADP
fcis-13148	110	43	dilated	dilated	ADJ
fcis-13148	110	44	convolution	convolution	NOUN
fcis-13148	110	45	.	.	PUNCT
fcis-13148	111	1	the	the	DET
fcis-13148	111	2	experimental	experimental	ADJ
fcis-13148	111	3	results	result	NOUN
fcis-13148	111	4	are	be	AUX
fcis-13148	111	5	shown	show	VERB
fcis-13148	111	6	in	in	ADP
fcis-13148	111	7	table	table	NOUN
fcis-13148	111	8	4	4	NUM
fcis-13148	111	9	.	.	PUNCT
fcis-13148	112	1	this	this	PRON
fcis-13148	112	2	fully	fully	ADV
fcis-13148	112	3	demonstrates	demonstrate	VERB
fcis-13148	112	4	that	that	SCONJ
fcis-13148	112	5	integrating	integrate	VERB
fcis-13148	112	6	dfc	dfc	NOUN
fcis-13148	112	7	effectively	effectively	ADV
fcis-13148	112	8	captures	capture	VERB
fcis-13148	112	9	long	long	ADJ
fcis-13148	112	10	-	-	PUNCT
fcis-13148	112	11	range	range	NOUN
fcis-13148	112	12	information	information	NOUN
fcis-13148	112	13	,	,	PUNCT
fcis-13148	112	14	enhancing	enhance	VERB
fcis-13148	112	15	accuracy	accuracy	NOUN
fcis-13148	112	16	,	,	PUNCT
fcis-13148	112	17	and	and	CCONJ
fcis-13148	112	18	combining	combine	VERB
fcis-13148	112	19	dilated	dilated	ADJ
fcis-13148	112	20	convolution	convolution	NOUN
fcis-13148	112	21	with	with	ADP
fcis-13148	112	22	the	the	DET
fcis-13148	112	23	lightweight	lightweight	ADJ
fcis-13148	112	24	rgb	rgb	PROPN
fcis-13148	112	25	module	module	NOUN
fcis-13148	112	26	can	can	AUX
fcis-13148	112	27	achieve	achieve	VERB
fcis-13148	112	28	better	well	ADJ
fcis-13148	112	29	recognition	recognition	NOUN
fcis-13148	112	30	results	result	NOUN
fcis-13148	112	31	.	.	PUNCT
fcis-13148	113	1	table	table	NOUN
fcis-13148	113	2	3	3	NUM
fcis-13148	113	3	.	.	PUNCT
fcis-13148	113	4	ablation	ablation	NOUN
fcis-13148	113	5	experiment	experiment	NOUN
fcis-13148	113	6	model	model	NOUN
fcis-13148	113	7	name	name	NOUN
fcis-13148	113	8	accuracy	accuracy	PROPN
fcis-13148	113	9	macro	macro	PROPN
fcis-13148	113	10	recall	recall	PROPN
fcis-13148	113	11	macro	macro	PROPN
fcis-13148	113	12	precision	precision	PROPN
fcis-13148	113	13	macro	macro	PROPN
fcis-13148	113	14	f1	f1	PROPN
fcis-13148	113	15	score	score	NOUN
fcis-13148	113	16	rgbnet	rgbnet	NOUN
fcis-13148	113	17	90.44	90.44	NUM
fcis-13148	113	18	%	%	NOUN
fcis-13148	113	19	0.9026	0.9026	NUM
fcis-13148	113	20	%	%	NOUN
fcis-13148	113	21	0.9089	0.9089	NUM
fcis-13148	113	22	%	%	NOUN
fcis-13148	113	23	0.9018	0.9018	NUM
fcis-13148	113	24	%	%	NOUN
fcis-13148	113	25	rgbnet	rgbnet	NOUN
fcis-13148	113	26	(	(	PUNCT
fcis-13148	113	27	dilated	dilated	ADJ
fcis-13148	113	28	conv	conv	NOUN
fcis-13148	113	29	)	)	PUNCT
fcis-13148	113	30	91.34	91.34	NUM
fcis-13148	113	31	%	%	NOUN
fcis-13148	113	32	0.9147	0.9147	NUM
fcis-13148	113	33	%	%	NOUN
fcis-13148	113	34	0.9226	0.9226	NUM
fcis-13148	113	35	%	%	NOUN
fcis-13148	113	36	0.9116	0.9116	NUM
fcis-13148	113	37	%	%	NOUN
fcis-13148	113	38	rgbnet	rgbnet	NOUN
fcis-13148	113	39	(	(	PUNCT
fcis-13148	113	40	dilated	dilate	VERB
fcis-13148	113	41	conv+	conv+	X
fcis-13148	113	42	dfc	dfc	NOUN
fcis-13148	113	43	)	)	PUNCT
fcis-13148	113	44	96.72	96.72	NUM
fcis-13148	113	45	%	%	NOUN
fcis-13148	113	46	0.9646	0.9646	NUM
fcis-13148	113	47	%	%	NOUN
fcis-13148	113	48	0.9739	0.9739	NUM
fcis-13148	113	49	%	%	NOUN
fcis-13148	113	50	0.9621	0.9621	NUM
fcis-13148	113	51	%	%	NOUN
fcis-13148	113	52	6	6	NUM
fcis-13148	113	53	.	.	PUNCT
fcis-13148	113	54	conclusion	conclusion	NOUN
fcis-13148	113	55	for	for	ADP
fcis-13148	113	56	the	the	DET
fcis-13148	113	57	sichuan	sichuan	PROPN
fcis-13148	113	58	cuisine	cuisine	PROPN
fcis-13148	113	59	recognition	recognition	PROPN
fcis-13148	113	60	task	task	PROPN
fcis-13148	113	61	,	,	PUNCT
fcis-13148	113	62	a	a	DET
fcis-13148	113	63	lightweight	lightweight	ADJ
fcis-13148	113	64	rgbnet	rgbnet	ADJ
fcis-13148	113	65	network	network	NOUN
fcis-13148	113	66	model	model	NOUN
fcis-13148	113	67	based	base	VERB
fcis-13148	113	68	on	on	ADP
fcis-13148	113	69	a	a	DET
fcis-13148	113	70	residual	residual	ADJ
fcis-13148	113	71	neural	neural	ADJ
fcis-13148	113	72	network	network	NOUN
fcis-13148	113	73	is	be	AUX
fcis-13148	113	74	proposed	propose	VERB
fcis-13148	113	75	.	.	PUNCT
fcis-13148	114	1	in	in	ADP
fcis-13148	114	2	the	the	DET
fcis-13148	114	3	backbone	backbone	NOUN
fcis-13148	114	4	network	network	NOUN
fcis-13148	114	5	,	,	PUNCT
fcis-13148	114	6	standard	standard	ADJ
fcis-13148	114	7	convolution	convolution	NOUN
fcis-13148	114	8	is	be	AUX
fcis-13148	114	9	channel	channel	NOUN
fcis-13148	114	10	-	-	PUNCT
fcis-13148	114	11	split	split	NOUN
fcis-13148	114	12	to	to	PART
fcis-13148	114	13	merge	merge	VERB
fcis-13148	114	14	multiple	multiple	ADJ
fcis-13148	114	15	asymmetric	asymmetric	ADJ
fcis-13148	114	16	convolutions	convolution	NOUN
fcis-13148	114	17	,	,	PUNCT
fcis-13148	114	18	acquiring	acquire	VERB
fcis-13148	114	19	richer	rich	ADJ
fcis-13148	114	20	features	feature	NOUN
fcis-13148	114	21	from	from	ADP
fcis-13148	114	22	multiple	multiple	ADJ
fcis-13148	114	23	directions	direction	NOUN
fcis-13148	114	24	.	.	PUNCT
fcis-13148	115	1	subsequently	subsequently	ADV
fcis-13148	115	2	,	,	PUNCT
fcis-13148	115	3	dfc	dfc	PROPN
fcis-13148	115	4	long	long	ADJ
fcis-13148	115	5	-	-	PUNCT
fcis-13148	115	6	range	range	NOUN
fcis-13148	115	7	attention	attention	NOUN
fcis-13148	115	8	is	be	AUX
fcis-13148	115	9	introduced	introduce	VERB
fcis-13148	115	10	to	to	PART
fcis-13148	115	11	capture	capture	VERB
fcis-13148	115	12	long	long	ADJ
fcis-13148	115	13	-	-	PUNCT
fcis-13148	115	14	distance	distance	NOUN
fcis-13148	115	15	dependencies	dependency	NOUN
fcis-13148	115	16	in	in	ADP
fcis-13148	115	17	sequences	sequence	NOUN
fcis-13148	115	18	.	.	PUNCT
fcis-13148	116	1	compared	compare	VERB
fcis-13148	116	2	to	to	ADP
fcis-13148	116	3	existing	exist	VERB
fcis-13148	116	4	convolutional	convolutional	ADJ
fcis-13148	116	5	neural	neural	ADJ
fcis-13148	116	6	networks	network	NOUN
fcis-13148	116	7	,	,	PUNCT
fcis-13148	116	8	the	the	DET
fcis-13148	116	9	proposed	propose	VERB
fcis-13148	116	10	model	model	NOUN
fcis-13148	116	11	performs	perform	VERB
fcis-13148	116	12	better	well	ADV
fcis-13148	116	13	on	on	ADP
fcis-13148	116	14	the	the	DET
fcis-13148	116	15	minichinesefood	minichinesefood	NOUN
fcis-13148	116	16	dataset	dataset	VERB
fcis-13148	116	17	.	.	PUNCT
fcis-13148	117	1	however	however	ADV
fcis-13148	117	2	,	,	PUNCT
fcis-13148	117	3	there	there	PRON
fcis-13148	117	4	are	be	VERB
fcis-13148	117	5	still	still	ADV
fcis-13148	117	6	areas	area	NOUN
fcis-13148	117	7	for	for	ADP
fcis-13148	117	8	further	further	ADJ
fcis-13148	117	9	improvement	improvement	NOUN
fcis-13148	117	10	in	in	ADP
fcis-13148	117	11	the	the	DET
fcis-13148	117	12	deep	deep	ADJ
fcis-13148	117	13	learning	learning	NOUN
fcis-13148	117	14	approach	approach	NOUN
fcis-13148	117	15	used	use	VERB
fcis-13148	117	16	by	by	ADP
fcis-13148	117	17	the	the	DET
fcis-13148	117	18	model	model	NOUN
fcis-13148	117	19	.	.	PUNCT
fcis-13148	118	1	firstly	firstly	ADV
fcis-13148	118	2	,	,	PUNCT
fcis-13148	118	3	due	due	ADP
fcis-13148	118	4	to	to	ADP
fcis-13148	118	5	the	the	DET
fcis-13148	118	6	diverse	diverse	ADJ
fcis-13148	118	7	nature	nature	NOUN
fcis-13148	118	8	of	of	ADP
fcis-13148	118	9	sichuan	sichuan	PROPN
fcis-13148	118	10	cuisine	cuisine	NOUN
fcis-13148	118	11	dishes	dish	NOUN
fcis-13148	118	12	and	and	CCONJ
fcis-13148	118	13	variations	variation	NOUN
fcis-13148	118	14	in	in	ADP
fcis-13148	118	15	ingredient	ingredient	NOUN
fcis-13148	118	16	types	type	NOUN
fcis-13148	118	17	and	and	CCONJ
fcis-13148	118	18	cooking	cooking	NOUN
fcis-13148	118	19	styles	style	NOUN
fcis-13148	118	20	,	,	PUNCT
fcis-13148	118	21	the	the	DET
fcis-13148	118	22	data	data	NOUN
fcis-13148	118	23	samples	sample	NOUN
fcis-13148	118	24	extracted	extract	VERB
fcis-13148	118	25	in	in	ADP
fcis-13148	118	26	the	the	DET
fcis-13148	118	27	experiments	experiment	NOUN
fcis-13148	118	28	are	be	AUX
fcis-13148	118	29	relatively	relatively	ADV
fcis-13148	118	30	singular	singular	ADJ
fcis-13148	118	31	.	.	PUNCT
fcis-13148	119	1	in	in	ADP
fcis-13148	119	2	future	future	ADJ
fcis-13148	119	3	research	research	NOUN
fcis-13148	119	4	,	,	PUNCT
fcis-13148	119	5	more	more	ADV
fcis-13148	119	6	advanced	advanced	ADJ
fcis-13148	119	7	object	object	NOUN
fcis-13148	119	8	detection	detection	NOUN
fcis-13148	119	9	algorithms	algorithm	NOUN
fcis-13148	119	10	will	will	AUX
fcis-13148	119	11	be	be	AUX
fcis-13148	119	12	integrated	integrate	VERB
fcis-13148	119	13	to	to	PART
fcis-13148	119	14	handle	handle	VERB
fcis-13148	119	15	multi	multi	ADJ
fcis-13148	119	16	-	-	ADJ
fcis-13148	119	17	object	object	ADJ
fcis-13148	119	18	cuisine	cuisine	NOUN
fcis-13148	119	19	datasets	dataset	NOUN
fcis-13148	119	20	.	.	PUNCT
fcis-13148	120	1	secondly	secondly	ADV
fcis-13148	120	2	,	,	PUNCT
fcis-13148	120	3	although	although	SCONJ
fcis-13148	120	4	rgbnet	rgbnet	NOUN
fcis-13148	120	5	achieves	achieve	VERB
fcis-13148	120	6	good	good	ADJ
fcis-13148	120	7	performance	performance	NOUN
fcis-13148	120	8	in	in	ADP
fcis-13148	120	9	lightweight	lightweight	ADJ
fcis-13148	120	10	models	model	NOUN
fcis-13148	120	11	,	,	PUNCT
fcis-13148	120	12	its	its	PRON
fcis-13148	120	13	feature	feature	NOUN
fcis-13148	120	14	representation	representation	NOUN
fcis-13148	120	15	capability	capability	NOUN
fcis-13148	120	16	is	be	AUX
fcis-13148	120	17	weaker	weak	ADJ
fcis-13148	120	18	compared	compare	VERB
fcis-13148	120	19	to	to	ADP
fcis-13148	120	20	some	some	DET
fcis-13148	120	21	complex	complex	ADJ
fcis-13148	120	22	models	model	NOUN
fcis-13148	120	23	.	.	PUNCT
fcis-13148	121	1	this	this	PRON
fcis-13148	121	2	can	can	AUX
fcis-13148	121	3	be	be	AUX
fcis-13148	121	4	addressed	address	VERB
fcis-13148	121	5	by	by	ADP
fcis-13148	121	6	incorporating	incorporate	VERB
fcis-13148	121	7	more	more	ADJ
fcis-13148	121	8	network	network	NOUN
fcis-13148	121	9	layers	layer	NOUN
fcis-13148	121	10	and	and	CCONJ
fcis-13148	121	11	using	use	VERB
fcis-13148	121	12	more	more	ADJ
fcis-13148	121	13	complex	complex	ADJ
fcis-13148	121	14	features	feature	NOUN
fcis-13148	121	15	to	to	PART
fcis-13148	121	16	enhance	enhance	VERB
fcis-13148	121	17	the	the	DET
fcis-13148	121	18	algorithm	algorithm	NOUN
fcis-13148	121	19	for	for	ADP
fcis-13148	121	20	better	well	ADJ
fcis-13148	121	21	practical	practical	ADJ
fcis-13148	121	22	applications	application	NOUN
fcis-13148	121	23	in	in	ADP
fcis-13148	121	24	real	real	ADJ
fcis-13148	121	25	life	life	NOUN
fcis-13148	121	26	.	.	PUNCT
fcis-13148	122	1	acknowledgments	acknowledgment	NOUN
fcis-13148	122	2	sichuan	sichuan	PROPN
fcis-13148	122	3	province	province	PROPN
fcis-13148	122	4	's	's	PART
fcis-13148	122	5	returnee	returnee	NOUN
fcis-13148	122	6	science	science	NOUN
fcis-13148	122	7	and	and	CCONJ
fcis-13148	122	8	technology	technology	NOUN
fcis-13148	122	9	activities	activity	NOUN
fcis-13148	122	10	project	project	NOUN
fcis-13148	122	11	for	for	ADP
fcis-13148	122	12	overseas	overseas	ADJ
fcis-13148	122	13	students	student	NOUN
fcis-13148	122	14	;	;	PUNCT
fcis-13148	122	15	talent	talent	NOUN
fcis-13148	122	16	introduction	introduction	NOUN
fcis-13148	122	17	project	project	NOUN
fcis-13148	122	18	of	of	ADP
fcis-13148	122	19	sichuan	sichuan	PROPN
fcis-13148	122	20	university	university	PROPN
fcis-13148	122	21	of	of	ADP
fcis-13148	122	22	science	science	NOUN
fcis-13148	122	23	and	and	CCONJ
fcis-13148	122	24	technology	technology	NOUN
fcis-13148	122	25	(	(	PUNCT
fcis-13148	122	26	2021rc13	2021rc13	NUM
fcis-13148	122	27	)	)	PUNCT
fcis-13148	122	28	references	reference	NOUN
fcis-13148	122	29	[	[	X
fcis-13148	122	30	1	1	NUM
fcis-13148	122	31	]	]	X
fcis-13148	122	32	min	min	NOUN
fcis-13148	122	33	weiqing	weiqing	NOUN
fcis-13148	122	34	,	,	PUNCT
fcis-13148	122	35	liu	liu	PROPN
fcis-13148	122	36	linhu	linhu	PROPN
fcis-13148	122	37	,	,	PUNCT
fcis-13148	122	38	liu	liu	PROPN
fcis-13148	122	39	yuxin	yuxin	PROPN
fcis-13148	122	40	,	,	PUNCT
fcis-13148	122	41	et	et	PROPN
fcis-13148	122	42	al	al	PROPN
fcis-13148	122	43	.	.	PUNCT
fcis-13148	123	1	a	a	DET
fcis-13148	123	2	survey	survey	NOUN
fcis-13148	123	3	of	of	ADP
fcis-13148	123	4	food	food	NOUN
fcis-13148	123	5	image	image	NOUN
fcis-13148	123	6	recognition	recognition	NOUN
fcis-13148	123	7	methods[j	methods[j	PROPN
fcis-13148	123	8	]	]	PUNCT
fcis-13148	123	9	.	.	PUNCT
fcis-13148	124	1	journal	journal	PROPN
fcis-13148	124	2	of	of	ADP
fcis-13148	124	3	computer	computer	NOUN
fcis-13148	124	4	science	science	NOUN
fcis-13148	124	5	.	.	PUNCT
fcis-13148	125	1	vol.45	vol.45	X
fcis-13148	125	2	(	(	PUNCT
fcis-13148	125	3	2008	2008	NUM
fcis-13148	125	4	)	)	PUNCT
fcis-13148	125	5	no	no	INTJ
fcis-13148	125	6	.	.	NOUN
fcis-13148	125	7	03	03	NUM
fcis-13148	125	8	,	,	PUNCT
fcis-13148	125	9	p.542	p.542	NOUN
fcis-13148	125	10	-	-	SYM
fcis-13148	125	11	566	566	NUM
fcis-13148	125	12	.	.	PUNCT
fcis-13148	126	1	[	[	X
fcis-13148	126	2	2	2	X
fcis-13148	126	3	]	]	PUNCT
fcis-13148	126	4	wang	wang	PROPN
fcis-13148	126	5	hang	hang	PROPN
fcis-13148	126	6	.	.	PUNCT
fcis-13148	127	1	application	application	NOUN
fcis-13148	127	2	of	of	ADP
fcis-13148	127	3	rfid	rfid	NOUN
fcis-13148	127	4	technology	technology	NOUN
fcis-13148	127	5	in	in	ADP
fcis-13148	127	6	university	university	NOUN
fcis-13148	127	7	cafeteria	cafeteria	NOUN
fcis-13148	127	8	practice[j	practice[j	PROPN
fcis-13148	127	9	]	]	PUNCT
fcis-13148	127	10	.	.	PUNCT
fcis-13148	128	1	china	china	PROPN
fcis-13148	128	2	's	's	PART
fcis-13148	128	3	strategic	strategic	ADJ
fcis-13148	128	4	emerging	emerge	VERB
fcis-13148	128	5	industries	industry	NOUN
fcis-13148	128	6	vol	vol	NOUN
fcis-13148	128	7	.	.	PUNCT
fcis-13148	129	1	172	172	NUM
fcis-13148	129	2	(	(	PUNCT
fcis-13148	129	3	2008	2008	NUM
fcis-13148	129	4	)	)	PUNCT
fcis-13148	130	1	no	no	INTJ
fcis-13148	130	2	.	.	NOUN
fcis-13148	130	3	40	40	NUM
fcis-13148	130	4	,	,	PUNCT
fcis-13148	130	5	p.	p.	NOUN
fcis-13148	130	6	256	256	NUM
fcis-13148	130	7	.	.	PUNCT
fcis-13148	131	1	[	[	X
fcis-13148	131	2	3	3	X
fcis-13148	131	3	]	]	X
fcis-13148	131	4	chen	chen	PROPN
fcis-13148	131	5	mei	mei	PROPN
fcis-13148	131	6	,	,	PUNCT
fcis-13148	131	7	kapil	kapil	PROPN
fcis-13148	131	8	dhingra	dhingra	PROPN
fcis-13148	131	9	,	,	PUNCT
fcis-13148	131	10	wu	wu	PROPN
fcis-13148	131	11	wen	wen	PROPN
fcis-13148	131	12	,	,	PUNCT
fcis-13148	131	13	yang	yang	PROPN
fcis-13148	131	14	lei	lei	PROPN
fcis-13148	131	15	,	,	PUNCT
fcis-13148	131	16	et	et	PROPN
fcis-13148	131	17	al	al	PROPN
fcis-13148	131	18	.	.	PUNCT
fcis-13148	132	1	pfid	pfid	PROPN
fcis-13148	132	2	:	:	PUNCT
fcis-13148	132	3	pittsburgh	pittsburgh	PROPN
fcis-13148	132	4	fast	fast	ADJ
fcis-13148	132	5	-	-	PUNCT
fcis-13148	132	6	food	food	NOUN
fcis-13148	132	7	image	image	NOUN
fcis-13148	132	8	dataset[c]//	dataset[c]//	PROPN
fcis-13148	132	9	proceedings	proceeding	NOUN
fcis-13148	132	10	of	of	ADP
fcis-13148	132	11	the	the	DET
fcis-13148	132	12	international	international	ADJ
fcis-13148	132	13	conference	conference	NOUN
fcis-13148	132	14	on	on	ADP
fcis-13148	132	15	image	image	NOUN
fcis-13148	132	16	processing	processing	NOUN
fcis-13148	132	17	.	.	PUNCT
fcis-13148	133	1	cairo	cairo	PROPN
fcis-13148	133	2	,	,	PUNCT
fcis-13148	133	3	egypt	egypt	PROPN
fcis-13148	133	4	,	,	PUNCT
fcis-13148	133	5	2009	2009	NUM
fcis-13148	133	6	:	:	PUNCT
fcis-13148	133	7	289	289	NUM
fcis-13148	133	8	-	-	SYM
fcis-13148	133	9	292	292	NUM
fcis-13148	133	10	.	.	PUNCT
fcis-13148	134	1	[	[	X
fcis-13148	134	2	4	4	X
fcis-13148	134	3	]	]	X
fcis-13148	134	4	martinel	martinel	NOUN
fcis-13148	134	5	n	n	NOUN
fcis-13148	134	6	,	,	PUNCT
fcis-13148	134	7	foresti	foresti	NOUN
fcis-13148	134	8	g	g	PROPN
fcis-13148	134	9	l	l	PROPN
fcis-13148	134	10	,	,	PUNCT
fcis-13148	134	11	micheloni	micheloni	ADJ
fcis-13148	134	12	c.	c.	PROPN
fcis-13148	134	13	wide	wide	ADJ
fcis-13148	134	14	-	-	PUNCT
fcis-13148	134	15	slice	slice	NOUN
fcis-13148	134	16	residual	residual	ADJ
fcis-13148	134	17	networks	network	NOUN
fcis-13148	134	18	for	for	ADP
fcis-13148	134	19	food	food	NOUN
fcis-13148	134	20	recognition[c]//	recognition[c]//	PROPN
fcis-13148	134	21	proceedings	proceeding	NOUN
fcis-13148	134	22	of	of	ADP
fcis-13148	134	23	the	the	DET
fcis-13148	134	24	international	international	ADJ
fcis-13148	134	25	conference	conference	NOUN
fcis-13148	134	26	on	on	ADP
fcis-13148	134	27	applications	application	NOUN
fcis-13148	134	28	of	of	ADP
fcis-13148	134	29	computer	computer	NOUN
fcis-13148	134	30	vision	vision	NOUN
fcis-13148	134	31	.	.	PUNCT
fcis-13148	135	1	lake	lake	PROPN
fcis-13148	135	2	tahoe	tahoe	PROPN
fcis-13148	135	3	,	,	PUNCT
fcis-13148	135	4	usa,2018:567	usa,2018:567	NOUN
fcis-13148	135	5	-	-	PUNCT
fcis-13148	135	6	576	576	NUM
fcis-13148	135	7	.	.	PUNCT
fcis-13148	136	1	[	[	X
fcis-13148	136	2	5	5	X
fcis-13148	136	3	]	]	PUNCT
fcis-13148	136	4	austin	austin	PROPN
fcis-13148	136	5	meyers	meyers	PROPN
fcis-13148	136	6	,	,	PUNCT
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fcis-13148	136	9	,	,	PUNCT
fcis-13148	136	10	vivek	vivek	PROPN
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fcis-13148	136	12	,	,	PUNCT
fcis-13148	136	13	et	et	PROPN
fcis-13148	136	14	al	al	PROPN
fcis-13148	136	15	.	.	PROPN
fcis-13148	136	16	im2calories	im2calories	PROPN
fcis-13148	136	17	:	:	PUNCT
fcis-13148	136	18	towards	towards	ADP
fcis-13148	136	19	an	an	DET
fcis-13148	136	20	automated	automate	VERB
fcis-13148	136	21	mobile	mobile	ADJ
fcis-13148	136	22	vision	vision	NOUN
fcis-13148	136	23	food	food	NOUN
fcis-13148	136	24	diary	diary	NOUN
fcis-13148	136	25	[	[	X
fcis-13148	136	26	c]//	c]//	ADJ
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fcis-13148	136	28	of	of	ADP
fcis-13148	136	29	the	the	DET
fcis-13148	136	30	ieee	ieee	NOUN
fcis-13148	136	31	international	international	PROPN
fcis-13148	136	32	conference	conference	NOUN
fcis-13148	136	33	on	on	ADP
fcis-13148	136	34	computer	computer	NOUN
fcis-13148	136	35	vision	vision	NOUN
fcis-13148	136	36	.	.	PUNCT
fcis-13148	137	1	santiago	santiago	PROPN
fcis-13148	137	2	,	,	PUNCT
fcis-13148	137	3	chile,2015:1233–124	chile,2015:1233–124	ADJ
fcis-13148	137	4	.	.	PUNCT
fcis-13148	138	1	[	[	X
fcis-13148	138	2	6	6	NUM
fcis-13148	138	3	]	]	X
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fcis-13148	138	13	he	he	PRON
fcis-13148	138	14	,	,	PUNCT
fcis-13148	138	15	x.	x.	PROPN
fcis-13148	138	16	et	et	PROPN
fcis-13148	138	17	al	al	PROPN
fcis-13148	138	18	.	.	PROPN
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fcis-13148	138	20	-	-	PUNCT
fcis-13148	138	21	dish	dish	NOUN
fcis-13148	138	22	recognition	recognition	NOUN
fcis-13148	138	23	with	with	ADP
fcis-13148	138	24	contextual	contextual	ADJ
fcis-13148	138	25	relation	relation	NOUN
fcis-13148	138	26	networks[c]//proceedings	networks[c]//proceeding	NOUN
fcis-13148	138	27	of	of	ADP
fcis-13148	138	28	the	the	DET
fcis-13148	138	29	27th	27th	ADJ
fcis-13148	138	30	acm	acm	PROPN
fcis-13148	138	31	international	international	ADJ
fcis-13148	138	32	conference	conference	NOUN
fcis-13148	138	33	on	on	ADP
fcis-13148	138	34	multimedia,2019:112	multimedia,2019:112	PROPN
fcis-13148	138	35	-	-	SYM
fcis-13148	138	36	120	120	NUM
fcis-13148	138	37	.	.	PUNCT
fcis-13148	139	1	[	[	X
fcis-13148	139	2	7	7	X
fcis-13148	139	3	]	]	X
fcis-13148	139	4	xiao	xiao	PROPN
fcis-13148	139	5	g	g	PROPN
fcis-13148	139	6	,	,	PUNCT
fcis-13148	139	7	wu	wu	PROPN
fcis-13148	139	8	q	q	PROPN
fcis-13148	139	9	,	,	PUNCT
fcis-13148	139	10	chen	chen	PROPN
fcis-13148	139	11	h	h	PROPN
fcis-13148	139	12	,	,	PUNCT
fcis-13148	139	13	et	et	PROPN
fcis-13148	139	14	al	al	PROPN
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fcis-13148	140	1	a	a	DET
fcis-13148	140	2	deep	deep	ADJ
fcis-13148	140	3	transfer	transfer	NOUN
fcis-13148	140	4	learning	learning	NOUN
fcis-13148	140	5	solution	solution	NOUN
fcis-13148	140	6	for	for	ADP
fcis-13148	140	7	automating	automate	VERB
fcis-13148	140	8	food	food	NOUN
fcis-13148	140	9	material	material	NOUN
fcis-13148	140	10	procurement	procurement	NOUN
fcis-13148	140	11	using	use	VERB
fcis-13148	140	12	electronic	electronic	ADJ
fcis-13148	140	13	scales[j	scales[j	NOUN
fcis-13148	140	14	]	]	PUNCT
fcis-13148	140	15	.	.	PUNCT
fcis-13148	141	1	ieee	ieee	NOUN
fcis-13148	141	2	transactions	transaction	NOUN
fcis-13148	141	3	on	on	ADP
fcis-13148	141	4	industrial	industrial	ADJ
fcis-13148	141	5	informatics	informatic	NOUN
fcis-13148	141	6	,	,	PUNCT
fcis-13148	141	7	2019	2019	NUM
fcis-13148	141	8	,	,	PUNCT
fcis-13148	141	9	16	16	NUM
fcis-13148	141	10	(	(	PUNCT
fcis-13148	141	11	4):2290	4):2290	NUM
fcis-13148	141	12	-	-	SYM
fcis-13148	141	13	2300	2300	NUM
fcis-13148	141	14	.	.	PUNCT
fcis-13148	142	1	[	[	X
fcis-13148	142	2	8	8	NUM
fcis-13148	142	3	]	]	X
fcis-13148	142	4	lo	lo	NOUN
fcis-13148	142	5	f	f	PROPN
fcis-13148	142	6	p	p	PROPN
fcis-13148	142	7	w	w	PROPN
fcis-13148	142	8	,	,	PUNCT
fcis-13148	142	9	sun	sun	PROPN
fcis-13148	142	10	y	y	PROPN
fcis-13148	142	11	,	,	PUNCT
fcis-13148	142	12	qiu	qiu	PROPN
fcis-13148	142	13	j	j	PROPN
fcis-13148	142	14	,	,	PUNCT
fcis-13148	142	15	et	et	PROPN
fcis-13148	142	16	al	al	PROPN
fcis-13148	142	17	.	.	PUNCT
fcis-13148	142	18	image	image	NOUN
fcis-13148	142	19	-	-	PUNCT
fcis-13148	142	20	based	base	VERB
fcis-13148	142	21	food	food	NOUN
fcis-13148	142	22	classification	classification	NOUN
fcis-13148	142	23	and	and	CCONJ
fcis-13148	142	24	volume	volume	NOUN
fcis-13148	142	25	estimation	estimation	NOUN
fcis-13148	142	26	for	for	ADP
fcis-13148	142	27	dietary	dietary	ADJ
fcis-13148	142	28	assessment	assessment	NOUN
fcis-13148	142	29	:	:	PUNCT
fcis-13148	142	30	a	a	DET
fcis-13148	142	31	review[j	review[j	PROPN
fcis-13148	142	32	]	]	PUNCT
fcis-13148	142	33	.	.	PUNCT
fcis-13148	143	1	ieee	ieee	PROPN
fcis-13148	143	2	journal	journal	PROPN
fcis-13148	143	3	of	of	ADP
fcis-13148	143	4	biomedical	biomedical	ADJ
fcis-13148	143	5	and	and	CCONJ
fcis-13148	143	6	health	health	NOUN
fcis-13148	143	7	informatics	informatic	NOUN
fcis-13148	143	8	,	,	PUNCT
fcis-13148	143	9	2020	2020	NUM
fcis-13148	143	10	,	,	PUNCT
fcis-13148	143	11	24(7):1926	24(7):1926	NUM
fcis-13148	143	12	-	-	SYM
fcis-13148	143	13	1939	1939	NUM
fcis-13148	143	14	.	.	PUNCT
fcis-13148	144	1	doi:10.1109	doi:10.1109	VERB
fcis-13148	144	2	/	/	SYM
fcis-13148	145	1	jbhi.2020.2987943	jbhi.2020.2987943	PROPN
fcis-13148	145	2	.	.	PUNCT
fcis-13148	146	1	153	153	NUM
fcis-13148	147	1	[	[	X
fcis-13148	147	2	9	9	NUM
fcis-13148	147	3	]	]	X
fcis-13148	147	4	wang	wang	PROPN
fcis-13148	147	5	haiyan	haiyan	PROPN
fcis-13148	147	6	,	,	PUNCT
fcis-13148	147	7	zhang	zhang	PROPN
fcis-13148	147	8	miao	miao	PROPN
fcis-13148	147	9	,	,	PUNCT
fcis-13148	147	10	liu	liu	PROPN
fcis-13148	147	11	hulin	hulin	PROPN
fcis-13148	147	12	,	,	PUNCT
fcis-13148	147	13	et	et	PROPN
fcis-13148	147	14	al	al	PROPN
fcis-13148	147	15	.	.	PUNCT
fcis-13148	148	1	chinese	chinese	ADJ
fcis-13148	148	2	cuisine	cuisine	NOUN
fcis-13148	148	3	image	image	NOUN
fcis-13148	148	4	recognition	recognition	NOUN
fcis-13148	148	5	method	method	NOUN
fcis-13148	148	6	based	base	VERB
fcis-13148	148	7	on	on	ADP
fcis-13148	148	8	improved	improve	VERB
fcis-13148	148	9	resnet	resnet	NOUN
fcis-13148	148	10	network[j	network[j	NOUN
fcis-13148	148	11	]	]	PUNCT
fcis-13148	148	12	.	.	PUNCT
fcis-13148	149	1	journal	journal	PROPN
fcis-13148	149	2	of	of	ADP
fcis-13148	149	3	shanxi	shanxi	PROPN
fcis-13148	149	4	university	university	PROPN
fcis-13148	149	5	of	of	ADP
fcis-13148	149	6	science	science	NOUN
fcis-13148	149	7	and	and	CCONJ
fcis-13148	149	8	technology	technology	NOUN
fcis-13148	149	9	.	.	PUNCT
fcis-13148	150	1	vol	vol	NOUN
fcis-13148	150	2	.	.	PROPN
fcis-13148	151	1	40	40	NUM
fcis-13148	151	2	(	(	PUNCT
fcis-13148	151	3	2022	2022	NUM
fcis-13148	151	4	)	)	PUNCT
fcis-13148	152	1	no	no	INTJ
fcis-13148	152	2	.	.	NOUN
fcis-13148	152	3	01	01	NUM
fcis-13148	152	4	,	,	PUNCT
fcis-13148	152	5	p.	p.	NOUN
fcis-13148	152	6	154	154	NUM
fcis-13148	152	7	-	-	SYM
fcis-13148	152	8	160	160	NUM
fcis-13148	152	9	.	.	PUNCT
fcis-13148	153	1	[	[	X
fcis-13148	153	2	10	10	NUM
fcis-13148	153	3	]	]	X
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fcis-13148	153	11	dish	dish	PROPN
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fcis-13148	153	13	model	model	NOUN
fcis-13148	153	14	based	base	VERB
fcis-13148	153	15	on	on	ADP
fcis-13148	153	16	improved	improve	VERB
fcis-13148	153	17	residual	residual	ADJ
fcis-13148	153	18	networks[j	networks[j	NOUN
fcis-13148	153	19	]	]	X
fcis-13148	153	20	.	.	PUNCT
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fcis-13148	154	2	in	in	ADP
fcis-13148	154	3	laser	laser	NOUN
fcis-13148	154	4	and	and	CCONJ
fcis-13148	154	5	optoelectronics	optoelectronic	NOUN
fcis-13148	154	6	.	.	PUNCT
fcis-13148	155	1	vol	vol	NOUN
fcis-13148	155	2	.	.	PUNCT
fcis-13148	156	1	58	58	NUM
fcis-13148	156	2	(	(	PUNCT
fcis-13148	156	3	2021	2021	NUM
fcis-13148	156	4	)	)	PUNCT
fcis-13148	157	1	no	no	INTJ
fcis-13148	157	2	.	.	NOUN
fcis-13148	157	3	06	06	NUM
fcis-13148	157	4	,	,	PUNCT
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fcis-13148	157	6	264	264	NUM
fcis-13148	157	7	-	-	SYM
fcis-13148	157	8	272	272	NUM
fcis-13148	157	9	.	.	PUNCT
fcis-13148	158	1	[	[	X
fcis-13148	158	2	11	11	NUM
fcis-13148	158	3	]	]	SYM
fcis-13148	158	4	wu	wu	PROPN
fcis-13148	158	5	,	,	PUNCT
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fcis-13148	158	10	image	image	NOUN
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fcis-13148	158	15	cuisine	cuisine	NOUN
fcis-13148	158	16	(	(	PUNCT
fcis-13148	158	17	master	master	NOUN
fcis-13148	158	18	,	,	PUNCT
fcis-13148	158	19	university	university	NOUN
fcis-13148	158	20	of	of	ADP
fcis-13148	158	21	electronic	electronic	ADJ
fcis-13148	158	22	science	science	NOUN
fcis-13148	158	23	and	and	CCONJ
fcis-13148	158	24	technology	technology	NOUN
fcis-13148	158	25	of	of	ADP
fcis-13148	158	26	china	china	PROPN
fcis-13148	158	27	,	,	PUNCT
fcis-13148	158	28	chengdu	chengdu	PROPN
fcis-13148	158	29	,	,	PUNCT
fcis-13148	158	30	china	china	PROPN
fcis-13148	158	31	,	,	PUNCT
fcis-13148	158	32	2020	2020	NUM
fcis-13148	158	33	)	)	PUNCT
fcis-13148	158	34	.	.	PUNCT
fcis-13148	159	1	p.	p.	NOUN
fcis-13148	159	2	25	25	NUM
fcis-13148	159	3	-	-	SYM
fcis-13148	159	4	33	33	NUM
fcis-13148	159	5	.	.	PUNCT
fcis-13148	160	1	[	[	X
fcis-13148	160	2	12	12	NUM
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fcis-13148	160	4	liao	liao	PROPN
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fcis-13148	160	7	li	li	PROPN
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fcis-13148	160	13	et	et	PROPN
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fcis-13148	160	23	networks	network	NOUN
fcis-13148	160	24	.	.	PUNCT
fcis-13148	161	1	journal	journal	PROPN
fcis-13148	161	2	of	of	ADP
fcis-13148	161	3	south	south	PROPN
fcis-13148	161	4	china	china	PROPN
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fcis-13148	161	7	(	(	PUNCT
fcis-13148	161	8	natural	natural	ADJ
fcis-13148	161	9	science	science	NOUN
fcis-13148	161	10	edition	edition	NOUN
fcis-13148	161	11	)	)	PUNCT
fcis-13148	161	12	.	.	PUNCT
fcis-13148	162	1	vol	vol	NOUN
fcis-13148	162	2	.	.	PUNCT
fcis-13148	163	1	51	51	NUM
fcis-13148	163	2	(	(	PUNCT
fcis-13148	163	3	2019	2019	NUM
fcis-13148	163	4	)	)	PUNCT
fcis-13148	164	1	no	no	INTJ
fcis-13148	164	2	.	.	NOUN
fcis-13148	164	3	4	4	NUM
fcis-13148	164	4	,	,	PUNCT
fcis-13148	164	5	p.	p.	NOUN
fcis-13148	164	6	113	113	NUM
fcis-13148	164	7	-	-	SYM
fcis-13148	164	8	119	119	NUM
fcis-13148	164	9	.	.	PUNCT
fcis-13148	165	1	[	[	X
fcis-13148	165	2	13	13	NUM
fcis-13148	165	3	]	]	X
fcis-13148	165	4	tan	tan	PROPN
fcis-13148	165	5	m	m	PROPN
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fcis-13148	165	8	q.	q.	PROPN
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fcis-13148	165	12	model	model	NOUN
fcis-13148	165	13	scaling	scale	VERB
fcis-13148	165	14	for	for	ADP
fcis-13148	165	15	convolutional	convolutional	ADJ
fcis-13148	165	16	neural	neural	ADJ
fcis-13148	165	17	networks[c]//international	networks[c]//international	PROPN
fcis-13148	165	18	conference	conference	NOUN
fcis-13148	165	19	on	on	ADP
fcis-13148	165	20	machine	machine	NOUN
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fcis-13148	165	22	.	.	PUNCT
fcis-13148	166	1	pmlr	pmlr	NOUN
fcis-13148	166	2	,	,	PUNCT
fcis-13148	166	3	2019:6105	2019:6105	NUM
fcis-13148	166	4	-	-	SYM
fcis-13148	166	5	6114	6114	NUM
fcis-13148	166	6	.	.	PUNCT
fcis-13148	167	1	[	[	X
fcis-13148	167	2	14	14	NUM
fcis-13148	167	3	]	]	X
fcis-13148	167	4	zhang	zhang	PROPN
fcis-13148	167	5	x	x	PROPN
fcis-13148	167	6	,	,	PUNCT
fcis-13148	167	7	zhou	zhou	PROPN
fcis-13148	167	8	x	x	PROPN
fcis-13148	167	9	,	,	PUNCT
fcis-13148	167	10	lin	lin	PROPN
fcis-13148	167	11	m	m	PROPN
fcis-13148	167	12	,	,	PUNCT
fcis-13148	167	13	et	et	PROPN
fcis-13148	167	14	al	al	PROPN
fcis-13148	167	15	.	.	PROPN
fcis-13148	167	16	shufflenet	shufflenet	PROPN
fcis-13148	167	17	:	:	PUNCT
fcis-13148	167	18	an	an	DET
fcis-13148	167	19	extremely	extremely	ADV
fcis-13148	167	20	efficient	efficient	ADJ
fcis-13148	167	21	convolutional	convolutional	ADJ
fcis-13148	167	22	neural	neural	ADJ
fcis-13148	167	23	network	network	NOUN
fcis-13148	167	24	for	for	ADP
fcis-13148	167	25	mobile	mobile	ADJ
fcis-13148	167	26	devices	device	NOUN
fcis-13148	167	27	[	[	X
fcis-13148	167	28	c]//	c]//	ADJ
fcis-13148	167	29	proceedings	proceeding	NOUN
fcis-13148	167	30	of	of	ADP
fcis-13148	167	31	the	the	DET
fcis-13148	167	32	ieee	ieee	NOUN
fcis-13148	167	33	conference	conference	NOUN
fcis-13148	167	34	on	on	ADP
fcis-13148	167	35	computer	computer	NOUN
fcis-13148	167	36	vision	vision	NOUN
fcis-13148	167	37	and	and	CCONJ
fcis-13148	167	38	pattern	pattern	NOUN
fcis-13148	167	39	recognition.2018:6848	recognition.2018:6848	NOUN
fcis-13148	167	40	-	-	PUNCT
fcis-13148	167	41	6856	6856	NUM
fcis-13148	167	42	.	.	PUNCT
fcis-13148	168	1	[	[	X
fcis-13148	168	2	15	15	NUM
fcis-13148	168	3	]	]	X
fcis-13148	168	4	chen	chen	PROPN
fcis-13148	168	5	j	j	PROPN
fcis-13148	168	6	,	,	PUNCT
fcis-13148	168	7	kao	kao	PROPN
fcis-13148	168	8	s	s	PROPN
fcis-13148	168	9	,	,	PUNCT
fcis-13148	168	10	he	he	PRON
fcis-13148	168	11	h	h	VERB
fcis-13148	168	12	,	,	PUNCT
fcis-13148	168	13	et	et	PROPN
fcis-13148	168	14	al	al	PROPN
fcis-13148	168	15	.	.	PROPN
fcis-13148	168	16	run	run	PROPN
fcis-13148	168	17	,	,	PUNCT
fcis-13148	168	18	do	do	AUX
fcis-13148	168	19	n't	not	PART
fcis-13148	168	20	walk	walk	VERB
fcis-13148	168	21	:	:	PUNCT
fcis-13148	168	22	chasing	chase	VERB
fcis-13148	168	23	higher	high	ADJ
fcis-13148	168	24	flops	flop	NOUN
fcis-13148	168	25	for	for	ADP
fcis-13148	168	26	faster	fast	ADJ
fcis-13148	168	27	neural	neural	ADJ
fcis-13148	168	28	networks[j	networks[j	PROPN
fcis-13148	168	29	]	]	X
fcis-13148	168	30	.	.	PUNCT
fcis-13148	169	1	arxiv	arxiv	PROPN
fcis-13148	169	2	preprint	preprint	PROPN
fcis-13148	169	3	arxiv	arxiv	PROPN
fcis-13148	169	4	:	:	PUNCT
fcis-13148	169	5	2303	2303	NUM
fcis-13148	169	6	.	.	PUNCT
fcis-13148	169	7	03667	03667	NUM
fcis-13148	169	8	,	,	PUNCT
fcis-13148	169	9	2023	2023	NUM
fcis-13148	169	10	.	.	PUNCT
fcis-13148	170	1	[	[	X
fcis-13148	170	2	16	16	NUM
fcis-13148	170	3	]	]	X
fcis-13148	170	4	sandler	sandler	PROPN
fcis-13148	170	5	m	m	PROPN
fcis-13148	170	6	,	,	PUNCT
fcis-13148	170	7	howard	howard	PROPN
fcis-13148	170	8	a	a	PRON
fcis-13148	170	9	,	,	PUNCT
fcis-13148	170	10	zhu	zhu	PROPN
fcis-13148	170	11	m	m	PROPN
fcis-13148	170	12	,	,	PUNCT
fcis-13148	170	13	et	et	PROPN
fcis-13148	170	14	al	al	PROPN
fcis-13148	170	15	.	.	PUNCT
fcis-13148	171	1	mobilenetv2	mobilenetv2	PROPN
fcis-13148	171	2	:	:	PUNCT
fcis-13148	172	1	inverted	inverted	ADJ
fcis-13148	172	2	residuals	residual	NOUN
fcis-13148	172	3	and	and	CCONJ
fcis-13148	172	4	linear	linear	ADJ
fcis-13148	172	5	bottlenecks[c]//proceedings	bottlenecks[c]//proceeding	NOUN
fcis-13148	172	6	of	of	ADP
fcis-13148	172	7	the	the	DET
fcis-13148	172	8	ieee	ieee	NOUN
fcis-13148	172	9	conference	conference	NOUN
fcis-13148	172	10	on	on	ADP
fcis-13148	172	11	computer	computer	NOUN
fcis-13148	172	12	vision	vision	NOUN
fcis-13148	172	13	and	and	CCONJ
fcis-13148	172	14	pattern	pattern	NOUN
fcis-13148	172	15	recognition	recognition	NOUN
fcis-13148	172	16	.	.	PUNCT
fcis-13148	173	1	2018	2018	NUM
fcis-13148	173	2	:	:	PUNCT
fcis-13148	173	3	4510	4510	NUM
fcis-13148	173	4	-	-	SYM
fcis-13148	173	5	4520	4520	NUM
fcis-13148	173	6	.	.	PUNCT
fcis-13148	174	1	[	[	X
fcis-13148	174	2	17	17	NUM
fcis-13148	174	3	]	]	PUNCT
fcis-13148	174	4	gai	gai	NOUN
fcis-13148	174	5	rongli	rongli	NOUN
fcis-13148	174	6	,	,	PUNCT
fcis-13148	174	7	cai	cai	PROPN
fcis-13148	174	8	jianrong	jianrong	PROPN
fcis-13148	174	9	,	,	PUNCT
fcis-13148	174	10	wang	wang	PROPN
fcis-13148	174	11	shiyu	shiyu	PROPN
fcis-13148	174	12	,	,	PUNCT
fcis-13148	174	13	et	et	PROPN
fcis-13148	174	14	al	al	PROPN
fcis-13148	174	15	.	.	PUNCT
fcis-13148	175	1	a	a	DET
fcis-13148	175	2	comprehensive	comprehensive	ADJ
fcis-13148	175	3	review	review	NOUN
fcis-13148	175	4	on	on	ADP
fcis-13148	175	5	the	the	DET
fcis-13148	175	6	application	application	NOUN
fcis-13148	175	7	of	of	ADP
fcis-13148	175	8	convolutional	convolutional	ADJ
fcis-13148	175	9	neural	neural	ADJ
fcis-13148	175	10	networks	network	NOUN
fcis-13148	175	11	in	in	ADP
fcis-13148	175	12	image	image	NOUN
fcis-13148	175	13	recognition[j	recognition[j	NOUN
fcis-13148	175	14	]	]	PUNCT
fcis-13148	175	15	.	.	PUNCT
fcis-13148	176	1	small	small	ADJ
fcis-13148	176	2	&	&	CCONJ
fcis-13148	176	3	miniaturized	miniaturized	ADJ
fcis-13148	176	4	computer	computer	NOUN
fcis-13148	176	5	systems	system	NOUN
fcis-13148	176	6	.	.	PUNCT
fcis-13148	177	1	vol	vol	NOUN
fcis-13148	177	2	.	.	PUNCT
fcis-13148	178	1	42	42	NUM
fcis-13148	178	2	(	(	PUNCT
fcis-13148	178	3	2021	2021	NUM
fcis-13148	178	4	)	)	PUNCT
fcis-13148	179	1	no	no	INTJ
fcis-13148	179	2	.	.	NOUN
fcis-13148	179	3	9	9	NUM
fcis-13148	179	4	,	,	PUNCT
fcis-13148	179	5	p.	p.	NOUN
fcis-13148	179	6	1980	1980	NUM
fcis-13148	179	7	-	-	SYM
fcis-13148	179	8	1984	1984	NUM
fcis-13148	179	9	.	.	PUNCT
fcis-13148	180	1	[	[	X
fcis-13148	180	2	18	18	NUM
fcis-13148	180	3	]	]	X
fcis-13148	180	4	lin	lin	PROPN
fcis-13148	180	5	jingdong	jingdong	PROPN
fcis-13148	180	6	,	,	PUNCT
fcis-13148	180	7	wu	wu	PROPN
fcis-13148	180	8	xinyi	xinyi	PROPN
fcis-13148	180	9	,	,	PUNCT
fcis-13148	180	10	chai	chai	NOUN
fcis-13148	180	11	yi	yi	PROPN
fcis-13148	180	12	,	,	PUNCT
fcis-13148	180	13	et	et	PROPN
fcis-13148	180	14	al	al	PROPN
fcis-13148	180	15	.	.	PROPN
fcis-13148	180	16	overview	overview	NOUN
fcis-13148	180	17	of	of	ADP
fcis-13148	180	18	optimizing	optimize	VERB
fcis-13148	180	19	convolutional	convolutional	ADJ
fcis-13148	180	20	neural	neural	ADJ
fcis-13148	180	21	network	network	NOUN
fcis-13148	180	22	structures	structure	NOUN
fcis-13148	180	23	.	.	PUNCT
fcis-13148	181	1	acta	acta	PROPN
fcis-13148	181	2	automatica	automatica	PROPN
fcis-13148	181	3	sinica	sinica	PROPN
fcis-13148	181	4	.	.	PUNCT
fcis-13148	182	1	2020	2020	NUM
fcis-13148	182	2	,	,	PUNCT
fcis-13148	182	3	46(1	46(1	NUM
fcis-13148	182	4	):	):	PUNCT
fcis-13148	182	5	24	24	NUM
fcis-13148	182	6	-	-	SYM
fcis-13148	182	7	37	37	NUM
fcis-13148	182	8	.	.	PUNCT
fcis-13148	183	1	[	[	X
fcis-13148	183	2	19	19	NUM
fcis-13148	183	3	]	]	PUNCT
fcis-13148	183	4	wu	wu	PROPN
fcis-13148	183	5	haohao	haohao	PROPN
fcis-13148	183	6	,	,	PUNCT
fcis-13148	183	7	wang	wang	PROPN
fcis-13148	183	8	fangshi	fangshi	PROPN
fcis-13148	183	9	.	.	PUNCT
fcis-13148	184	1	application	application	NOUN
fcis-13148	184	2	of	of	ADP
fcis-13148	184	3	multi	multi	ADJ
fcis-13148	184	4	-	-	ADJ
fcis-13148	184	5	scale	scale	ADJ
fcis-13148	184	6	dilated	dilated	ADJ
fcis-13148	184	7	convolution	convolution	NOUN
fcis-13148	184	8	in	in	ADP
fcis-13148	184	9	image	image	NOUN
fcis-13148	184	10	classification	classification	NOUN
fcis-13148	184	11	.	.	PUNCT
fcis-13148	185	1	computer	computer	NOUN
fcis-13148	185	2	science	science	NOUN
fcis-13148	185	3	.	.	PUNCT
fcis-13148	186	1	2020	2020	NUM
fcis-13148	186	2	,	,	PUNCT
fcis-13148	186	3	47(6a	47(6a	NUM
fcis-13148	186	4	):	):	PUNCT
fcis-13148	186	5	166	166	NUM
fcis-13148	186	6	-	-	SYM
fcis-13148	186	7	171	171	NUM
fcis-13148	186	8	.	.	PUNCT
fcis-13148	187	1	[	[	X
fcis-13148	187	2	20	20	NUM
fcis-13148	187	3	]	]	SYM
fcis-13148	187	4	li	li	PROPN
fcis-13148	187	5	y	y	PROPN
fcis-13148	187	6	,	,	PUNCT
fcis-13148	187	7	zhang	zhang	PROPN
fcis-13148	187	8	x	x	PROPN
fcis-13148	187	9	,	,	PUNCT
fcis-13148	187	10	chen	chen	PROPN
fcis-13148	187	11	d.	d.	PROPN
fcis-13148	187	12	csrnet	csrnet	PROPN
fcis-13148	187	13	:	:	PUNCT
fcis-13148	187	14	dilated	dilate	VERB
fcis-13148	187	15	convolutional	convolutional	ADJ
fcis-13148	187	16	neural	neural	ADJ
fcis-13148	187	17	networks	network	NOUN
fcis-13148	187	18	for	for	ADP
fcis-13148	187	19	understanding	understand	VERB
fcis-13148	187	20	the	the	DET
fcis-13148	187	21	highly	highly	ADV
fcis-13148	187	22	congested	congested	ADJ
fcis-13148	187	23	scenes[c]//	scenes[c]//	ADJ
fcis-13148	187	24	proceedings	proceeding	NOUN
fcis-13148	187	25	of	of	ADP
fcis-13148	187	26	the	the	DET
fcis-13148	187	27	ieee	ieee	NOUN
fcis-13148	187	28	conference	conference	NOUN
fcis-13148	187	29	on	on	ADP
fcis-13148	187	30	computer	computer	NOUN
fcis-13148	187	31	vision	vision	NOUN
fcis-13148	187	32	and	and	CCONJ
fcis-13148	187	33	pattern	pattern	NOUN
fcis-13148	187	34	recognition.2018:1091	recognition.2018:1091	NOUN
fcis-13148	187	35	-	-	NOUN
fcis-13148	187	36	1100	1100	NUM
fcis-13148	187	37	.	.	PUNCT
fcis-13148	188	1	[	[	X
fcis-13148	188	2	21	21	NUM
fcis-13148	188	3	]	]	X
fcis-13148	188	4	ding	ding	NOUN
fcis-13148	188	5	x	x	SYM
fcis-13148	188	6	,	,	PUNCT
fcis-13148	188	7	guo	guo	PROPN
fcis-13148	188	8	y	y	PROPN
fcis-13148	188	9	,	,	PUNCT
fcis-13148	188	10	ding	de	VERB
fcis-13148	188	11	g	g	NOUN
fcis-13148	188	12	,	,	PUNCT
fcis-13148	188	13	et	et	PROPN
fcis-13148	188	14	al	al	PROPN
fcis-13148	188	15	.	.	PROPN
fcis-13148	188	16	acnet	acnet	PROPN
fcis-13148	188	17	:	:	PUNCT
fcis-13148	188	18	strengthening	strengthen	VERB
fcis-13148	188	19	the	the	DET
fcis-13148	188	20	kernel	kernel	NOUN
fcis-13148	188	21	skeletons	skeleton	NOUN
fcis-13148	188	22	for	for	ADP
fcis-13148	188	23	powerful	powerful	ADJ
fcis-13148	188	24	cnn	cnn	PROPN
fcis-13148	188	25	via	via	ADP
fcis-13148	188	26	asymmetric	asymmetric	ADJ
fcis-13148	188	27	convolution	convolution	NOUN
fcis-13148	188	28	blocks	block	NOUN
fcis-13148	188	29	[	[	X
fcis-13148	188	30	c]//	c]//	ADJ
fcis-13148	188	31	proceedings	proceeding	NOUN
fcis-13148	188	32	of	of	ADP
fcis-13148	188	33	the	the	DET
fcis-13148	188	34	ieee	ieee	NOUN
fcis-13148	188	35	/	/	SYM
fcis-13148	188	36	cvf	cvf	NOUN
fcis-13148	188	37	international	international	ADJ
fcis-13148	188	38	conference	conference	NOUN
fcis-13148	188	39	on	on	ADP
fcis-13148	188	40	computer	computer	NOUN
fcis-13148	188	41	vision.2019:1911	vision.2019:1911	NOUN
fcis-13148	188	42	-	-	PUNCT
fcis-13148	188	43	1920	1920	NUM
fcis-13148	188	44	.	.	PUNCT
fcis-13148	189	1	[	[	X
fcis-13148	189	2	22	22	NUM
fcis-13148	189	3	]	]	PUNCT
fcis-13148	189	4	tang	tang	PROPN
fcis-13148	189	5	y	y	PROPN
fcis-13148	189	6	,	,	PUNCT
fcis-13148	189	7	han	han	PROPN
fcis-13148	189	8	k	k	PROPN
fcis-13148	189	9	,	,	PUNCT
fcis-13148	189	10	guo	guo	PROPN
fcis-13148	189	11	j	j	PROPN
fcis-13148	189	12	,	,	PUNCT
fcis-13148	189	13	et	et	PROPN
fcis-13148	189	14	al	al	PROPN
fcis-13148	189	15	.	.	PROPN
fcis-13148	189	16	ghostnetv2	ghostnetv2	PROPN
fcis-13148	189	17	:	:	PUNCT
fcis-13148	189	18	enhance	enhance	VERB
fcis-13148	189	19	cheap	cheap	ADJ
fcis-13148	189	20	operation	operation	NOUN
fcis-13148	189	21	with	with	ADP
fcis-13148	189	22	long	long	ADJ
fcis-13148	189	23	-	-	PUNCT
fcis-13148	189	24	range	range	NOUN
fcis-13148	189	25	attention[j].arxiv	attention[j].arxiv	PROPN
fcis-13148	189	26	preprint	preprint	NOUN
fcis-13148	189	27	arxiv	arxiv	PROPN
fcis-13148	189	28	:	:	PUNCT
fcis-13148	189	29	2211	2211	NUM
fcis-13148	189	30	.	.	PUNCT
fcis-13148	190	1	12905	12905	NUM
fcis-13148	190	2	,	,	PUNCT
fcis-13148	190	3	2022	2022	NUM
fcis-13148	190	4	.	.	PUNCT
fcis-13148	191	1	[	[	X
fcis-13148	191	2	23	23	NUM
fcis-13148	191	3	]	]	X
fcis-13148	191	4	han	han	PROPN
fcis-13148	191	5	k	k	PROPN
fcis-13148	191	6	,	,	PUNCT
fcis-13148	191	7	wang	wang	PROPN
fcis-13148	191	8	y	y	PROPN
fcis-13148	191	9	,	,	PUNCT
fcis-13148	191	10	tian	tian	PROPN
fcis-13148	191	11	q	q	NOUN
fcis-13148	191	12	,	,	PUNCT
fcis-13148	191	13	et	et	PROPN
fcis-13148	191	14	al	al	PROPN
fcis-13148	191	15	.	.	PROPN
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fcis-13148	191	17	:	:	PUNCT
fcis-13148	191	18	more	more	ADJ
fcis-13148	191	19	features	feature	NOUN
fcis-13148	191	20	from	from	ADP
fcis-13148	191	21	cheap	cheap	ADJ
fcis-13148	191	22	operations	operation	NOUN
fcis-13148	191	23	[	[	PUNCT
fcis-13148	191	24	c]//	c]//	ADJ
fcis-13148	191	25	proceedings	proceeding	NOUN
fcis-13148	191	26	of	of	ADP
fcis-13148	191	27	the	the	DET
fcis-13148	191	28	ieee	ieee	NOUN
fcis-13148	191	29	/	/	SYM
fcis-13148	191	30	cvf	cvf	NOUN
fcis-13148	191	31	conference	conference	NOUN
fcis-13148	191	32	on	on	ADP
fcis-13148	191	33	computer	computer	NOUN
fcis-13148	191	34	vision	vision	NOUN
fcis-13148	191	35	and	and	CCONJ
fcis-13148	191	36	pattern	pattern	NOUN
fcis-13148	191	37	recognition	recognition	NOUN
fcis-13148	191	38	.	.	PUNCT
fcis-13148	192	1	2020	2020	NUM
fcis-13148	192	2	:	:	PUNCT
fcis-13148	192	3	1580	1580	NUM
fcis-13148	192	4	-	-	SYM
fcis-13148	192	5	1589	1589	NUM
fcis-13148	192	6	.	.	PUNCT
fcis-13148	193	1	[	[	X
fcis-13148	193	2	24	24	NUM
fcis-13148	193	3	]	]	X
fcis-13148	193	4	chen	chen	PROPN
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fcis-13148	193	6	,	,	PUNCT
fcis-13148	193	7	zhu	zhu	PROPN
fcis-13148	193	8	y	y	PROPN
fcis-13148	193	9	,	,	PUNCT
fcis-13148	193	10	zhou	zhou	PROPN
fcis-13148	193	11	h	h	PROPN
fcis-13148	193	12	,	,	PUNCT
fcis-13148	193	13	et	et	PROPN
fcis-13148	193	14	al	al	PROPN
fcis-13148	193	15	.	.	PROPN
fcis-13148	193	16	chinesefoodnet	chinesefoodnet	PROPN
fcis-13148	193	17	:	:	PUNCT
fcis-13148	193	18	a	a	DET
fcis-13148	193	19	large	large	ADJ
fcis-13148	193	20	-	-	PUNCT
fcis-13148	193	21	scale	scale	NOUN
fcis-13148	193	22	image	image	NOUN
fcis-13148	193	23	dataset	dataset	VERB
fcis-13148	193	24	for	for	ADP
fcis-13148	193	25	chinese	chinese	ADJ
fcis-13148	193	26	food	food	PROPN
fcis-13148	193	27	recognition[j].arxiv	recognition[j].arxiv	PROPN
fcis-13148	193	28	preprint	preprint	NOUN
fcis-13148	193	29	arxiv	arxiv	PROPN
fcis-13148	193	30	:	:	PUNCT
fcis-13148	193	31	1705.02743	1705.02743	NUM
fcis-13148	193	32	,	,	PUNCT
fcis-13148	193	33	2017	2017	NUM
fcis-13148	193	34	.	.	PUNCT
fcis-13148	194	1	[	[	X
fcis-13148	194	2	25	25	NUM
fcis-13148	194	3	]	]	PUNCT
fcis-13148	194	4	cubuk	cubuk	X
fcis-13148	194	5	e	e	PROPN
fcis-13148	194	6	d	d	PROPN
fcis-13148	194	7	,	,	PUNCT
fcis-13148	194	8	zoph	zoph	NOUN
fcis-13148	194	9	b	b	PROPN
fcis-13148	194	10	,	,	PUNCT
fcis-13148	194	11	shlens	shlens	PROPN
fcis-13148	194	12	j	j	PROPN
fcis-13148	194	13	,	,	PUNCT
fcis-13148	194	14	et	et	PROPN
fcis-13148	194	15	al	al	PROPN
fcis-13148	194	16	.	.	PUNCT
fcis-13148	195	1	randaugment	randaugment	ADJ
fcis-13148	195	2	:	:	PUNCT
fcis-13148	195	3	practical	practical	ADJ
fcis-13148	195	4	automated	automate	VERB
fcis-13148	195	5	data	datum	NOUN
fcis-13148	195	6	augmentation	augmentation	NOUN
fcis-13148	195	7	with	with	ADP
fcis-13148	195	8	a	a	DET
fcis-13148	195	9	reduced	reduce	VERB
fcis-13148	195	10	search	search	NOUN
fcis-13148	195	11	space[c]//	space[c]//	PROPN
fcis-13148	195	12	proceedings	proceeding	NOUN
fcis-13148	195	13	of	of	ADP
fcis-13148	195	14	the	the	DET
fcis-13148	195	15	ieee	ieee	NOUN
fcis-13148	195	16	/	/	SYM
fcis-13148	195	17	cvf	cvf	NOUN
fcis-13148	195	18	conference	conference	NOUN
fcis-13148	195	19	on	on	ADP
fcis-13148	195	20	computer	computer	NOUN
fcis-13148	195	21	vision	vision	NOUN
fcis-13148	195	22	and	and	CCONJ
fcis-13148	195	23	pattern	pattern	NOUN
fcis-13148	195	24	recognition	recognition	NOUN
fcis-13148	195	25	workshops.2020:702	workshops.2020:702	NOUN
fcis-13148	195	26	-	-	PUNCT
fcis-13148	195	27	703	703	NUM
fcis-13148	195	28	.	.	PUNCT
fcis-13148	196	1	[	[	X
fcis-13148	196	2	26	26	NUM
fcis-13148	196	3	]	]	X
fcis-13148	196	4	zhong	zhong	PROPN
fcis-13148	196	5	z	z	PROPN
fcis-13148	196	6	,	,	PUNCT
fcis-13148	196	7	zheng	zheng	PROPN
fcis-13148	196	8	l	l	PROPN
fcis-13148	196	9	,	,	PUNCT
fcis-13148	196	10	kang	kang	PROPN
fcis-13148	196	11	g	g	PROPN
fcis-13148	196	12	,	,	PUNCT
fcis-13148	196	13	et	et	PROPN
fcis-13148	196	14	al	al	PROPN
fcis-13148	196	15	.	.	PUNCT
fcis-13148	196	16	random	random	ADJ
fcis-13148	196	17	erasing	erase	VERB
fcis-13148	196	18	data	datum	NOUN
fcis-13148	196	19	augmentation[c]//proceedings	augmentation[c]//proceeding	NOUN
fcis-13148	196	20	of	of	ADP
fcis-13148	196	21	the	the	DET
fcis-13148	196	22	aaai	aaai	PROPN
fcis-13148	196	23	conference	conference	NOUN
fcis-13148	196	24	on	on	ADP
fcis-13148	196	25	artificial	artificial	ADJ
fcis-13148	196	26	intelligence.2020,34(07):13001	intelligence.2020,34(07):13001	NOUN
fcis-13148	196	27	-	-	SYM
fcis-13148	196	28	13008	13008	NUM
fcis-13148	196	29	.	.	PUNCT