id	sid	tid	token	lemma	pos
aiti-366	1	1	advances	advance	NOUN
aiti-366	1	2	in	in	ADP
aiti-366	1	3	technology	technology	NOUN
aiti-366	1	4	innovation	innovation	NOUN
aiti-366	1	5	,	,	PUNCT
aiti-366	1	6	vol	vol	NOUN
aiti-366	1	7	.	.	PROPN
aiti-366	2	1	2	2	NUM
aiti-366	2	2	,	,	PUNCT
aiti-366	2	3	no	no	INTJ
aiti-366	2	4	.	.	NOUN
aiti-366	2	5	4	4	NUM
aiti-366	2	6	,	,	PUNCT
aiti-366	2	7	2017	2017	NUM
aiti-366	2	8	,	,	PUNCT
aiti-366	3	1	pp	pp	ADJ
aiti-366	3	2	.	.	PUNCT
aiti-366	4	1	119	119	NUM
aiti-366	4	2	125	125	NUM
aiti-366	4	3	119	119	NUM
aiti-366	4	4	copyright	copyright	NOUN
aiti-366	4	5	©	©	PROPN
aiti-366	4	6	taeti	taeti	PROPN
aiti-366	4	7	a	a	DET
aiti-366	4	8	cnn	cnn	PROPN
aiti-366	4	9	based	base	VERB
aiti-366	4	10	approach	approach	NOUN
aiti-366	4	11	for	for	ADP
aiti-366	4	12	garments	garment	NOUN
aiti-366	4	13	texture	texture	NOUN
aiti-366	4	14	design	design	NOUN
aiti-366	4	15	classification	classification	NOUN
aiti-366	4	16	s.	s.	PROPN
aiti-366	4	17	m.	m.	PROPN
aiti-366	4	18	sofiqul	sofiqul	PROPN
aiti-366	4	19	islam	islam	PROPN
aiti-366	4	20	,	,	PUNCT
aiti-366	4	21	emon	emon	PROPN
aiti-366	4	22	kumar	kumar	PROPN
aiti-366	4	23	dey	dey	PROPN
aiti-366	4	24	*	*	PROPN
aiti-366	4	25	,	,	PUNCT
aiti-366	4	26	md	md	PROPN
aiti-366	4	27	.	.	PROPN
aiti-366	4	28	nurul	nurul	PROPN
aiti-366	4	29	ahad	ahad	PROPN
aiti-366	4	30	tawhid	tawhid	PROPN
aiti-366	4	31	,	,	PUNCT
aiti-366	4	32	b.	b.	PROPN
aiti-366	4	33	m.	m.	PROPN
aiti-366	4	34	mainul	mainul	PROPN
aiti-366	4	35	hossain	hossain	PROPN
aiti-366	4	36	institute	institute	PROPN
aiti-366	4	37	of	of	ADP
aiti-366	4	38	information	information	NOUN
aiti-366	4	39	technology	technology	NOUN
aiti-366	4	40	,	,	PUNCT
aiti-366	4	41	university	university	NOUN
aiti-366	4	42	of	of	ADP
aiti-366	4	43	dhaka	dhaka	PROPN
aiti-366	4	44	,	,	PUNCT
aiti-366	4	45	bangladesh	bangladesh	PROPN
aiti-366	4	46	.	.	PUNCT
aiti-366	4	47	received	receive	VERB
aiti-366	4	48	03	03	NUM
aiti-366	4	49	october	october	PROPN
aiti-366	4	50	2016	2016	NUM
aiti-366	4	51	;	;	PUNCT
aiti-366	4	52	received	receive	VERB
aiti-366	4	53	in	in	ADP
aiti-366	4	54	revised	revise	VERB
aiti-366	4	55	form	form	NOUN
aiti-366	4	56	04	04	NUM
aiti-366	4	57	february	february	PROPN
aiti-366	4	58	2017	2017	NUM
aiti-366	4	59	;	;	PUNCT
aiti-366	4	60	accepted	accept	VERB
aiti-366	4	61	08	08	NUM
aiti-366	4	62	february	february	PROPN
aiti-366	4	63	2017	2017	NUM
aiti-366	4	64	abstract	abstract	ADJ
aiti-366	4	65	identifying	identify	VERB
aiti-366	4	66	garments	garment	NOUN
aiti-366	4	67	texture	texture	NOUN
aiti-366	4	68	design	design	NOUN
aiti-366	4	69	automatically	automatically	ADV
aiti-366	4	70	for	for	ADP
aiti-366	4	71	recommending	recommend	VERB
aiti-366	4	72	the	the	DET
aiti-366	4	73	fashion	fashion	NOUN
aiti-366	4	74	trends	trend	NOUN
aiti-366	4	75	is	be	AUX
aiti-366	4	76	important	important	ADJ
aiti-366	4	77	nowadays	nowadays	ADV
aiti-366	4	78	because	because	SCONJ
aiti-366	4	79	of	of	ADP
aiti-366	4	80	the	the	DET
aiti-366	4	81	rapid	rapid	ADJ
aiti-366	4	82	growth	growth	NOUN
aiti-366	4	83	of	of	ADP
aiti-366	4	84	online	online	ADJ
aiti-366	4	85	shopping	shopping	NOUN
aiti-366	4	86	.	.	PUNCT
aiti-366	5	1	by	by	ADP
aiti-366	5	2	learning	learn	VERB
aiti-366	5	3	the	the	DET
aiti-366	5	4	properties	property	NOUN
aiti-366	5	5	of	of	ADP
aiti-366	5	6	images	image	NOUN
aiti-366	5	7	efficiently	efficiently	ADV
aiti-366	5	8	,	,	PUNCT
aiti-366	5	9	a	a	DET
aiti-366	5	10	machine	machine	NOUN
aiti-366	5	11	can	can	AUX
aiti-366	5	12	give	give	VERB
aiti-366	5	13	better	well	ADJ
aiti-366	5	14	accuracy	accuracy	NOUN
aiti-366	5	15	of	of	ADP
aiti-366	5	16	classification	classification	NOUN
aiti-366	5	17	.	.	PUNCT
aiti-366	6	1	several	several	ADJ
aiti-366	6	2	hand	hand	NOUN
aiti-366	6	3	-	-	PUNCT
aiti-366	6	4	engineered	engineer	VERB
aiti-366	6	5	feature	feature	NOUN
aiti-366	6	6	coding	coding	NOUN
aiti-366	6	7	exists	exist	VERB
aiti-366	6	8	for	for	ADP
aiti-366	6	9	identifying	identify	VERB
aiti-366	6	10	garments	garment	NOUN
aiti-366	6	11	design	design	NOUN
aiti-366	6	12	classes	class	NOUN
aiti-366	6	13	.	.	PUNCT
aiti-366	7	1	recently	recently	ADV
aiti-366	7	2	,	,	PUNCT
aiti-366	7	3	deep	deep	ADJ
aiti-366	7	4	convolutional	convolutional	ADJ
aiti-366	7	5	neural	neural	ADJ
aiti-366	7	6	networks	network	NOUN
aiti-366	7	7	(	(	PUNCT
aiti-366	7	8	cnns	cnns	PROPN
aiti-366	7	9	)	)	PUNCT
aiti-366	7	10	have	have	AUX
aiti-366	7	11	shown	show	VERB
aiti-366	7	12	better	well	ADJ
aiti-366	7	13	performances	performance	NOUN
aiti-366	7	14	for	for	ADP
aiti-366	7	15	different	different	ADJ
aiti-366	7	16	object	object	NOUN
aiti-366	7	17	recognition	recognition	NOUN
aiti-366	7	18	.	.	PUNCT
aiti-366	8	1	deep	deep	ADJ
aiti-366	8	2	cnn	cnn	PROPN
aiti-366	8	3	uses	use	VERB
aiti-366	8	4	multiple	multiple	ADJ
aiti-366	8	5	levels	level	NOUN
aiti-366	8	6	of	of	ADP
aiti-366	8	7	representation	representation	NOUN
aiti-366	8	8	and	and	CCONJ
aiti-366	8	9	abstraction	abstraction	NOUN
aiti-366	8	10	that	that	PRON
aiti-366	8	11	helps	help	VERB
aiti-366	8	12	a	a	DET
aiti-366	8	13	machine	machine	NOUN
aiti-366	8	14	to	to	PART
aiti-366	8	15	understand	understand	VERB
aiti-366	8	16	the	the	DET
aiti-366	8	17	types	type	NOUN
aiti-366	8	18	of	of	ADP
aiti-366	8	19	data	datum	NOUN
aiti-366	8	20	more	more	ADV
aiti-366	8	21	accurately	accurately	ADV
aiti-366	8	22	.	.	PUNCT
aiti-366	9	1	in	in	ADP
aiti-366	9	2	this	this	DET
aiti-366	9	3	paper	paper	NOUN
aiti-366	9	4	,	,	PUNCT
aiti-366	9	5	a	a	DET
aiti-366	9	6	cnn	cnn	PROPN
aiti-366	9	7	model	model	NOUN
aiti-366	9	8	for	for	ADP
aiti-366	9	9	identifying	identify	VERB
aiti-366	9	10	garments	garment	NOUN
aiti-366	9	11	design	design	NOUN
aiti-366	9	12	classes	class	NOUN
aiti-366	9	13	has	have	AUX
aiti-366	9	14	been	be	AUX
aiti-366	9	15	proposed	propose	VERB
aiti-366	9	16	.	.	PUNCT
aiti-366	10	1	experimental	experimental	ADJ
aiti-366	10	2	results	result	NOUN
aiti-366	10	3	on	on	ADP
aiti-366	10	4	two	two	NUM
aiti-366	10	5	different	different	ADJ
aiti-366	10	6	datasets	dataset	NOUN
aiti-366	10	7	show	show	VERB
aiti-366	10	8	better	well	ADJ
aiti-366	10	9	results	result	NOUN
aiti-366	10	10	than	than	ADP
aiti-366	10	11	existing	exist	VERB
aiti-366	10	12	two	two	NUM
aiti-366	10	13	well	well	ADV
aiti-366	10	14	-	-	PUNCT
aiti-366	10	15	known	know	VERB
aiti-366	10	16	cnn	cnn	NOUN
aiti-366	10	17	models	model	NOUN
aiti-366	10	18	(	(	PUNCT
aiti-366	10	19	alexnet	alexnet	NOUN
aiti-366	10	20	and	and	CCONJ
aiti-366	10	21	vggnet	vggnet	ADJ
aiti-366	10	22	)	)	PUNCT
aiti-366	10	23	and	and	CCONJ
aiti-366	10	24	some	some	DET
aiti-366	10	25	state	state	NOUN
aiti-366	10	26	-	-	PUNCT
aiti-366	10	27	of	of	ADP
aiti-366	10	28	-	-	PUNCT
aiti-366	10	29	the	the	DET
aiti-366	10	30	-	-	PUNCT
aiti-366	10	31	art	art	NOUN
aiti-366	10	32	hand	hand	NOUN
aiti-366	10	33	-	-	PUNCT
aiti-366	10	34	engineered	engineer	VERB
aiti-366	10	35	feature	feature	NOUN
aiti-366	10	36	extraction	extraction	NOUN
aiti-366	10	37	methods	method	NOUN
aiti-366	10	38	.	.	PUNCT
aiti-366	11	1	keywords	keyword	NOUN
aiti-366	11	2	:	:	PUNCT
aiti-366	11	3	cnn	cnn	PROPN
aiti-366	11	4	,	,	PUNCT
aiti-366	11	5	deep	deep	ADV
aiti-366	11	6	learn	learn	VERB
aiti-366	11	7	ing	ing	NOUN
aiti-366	11	8	,	,	PUNCT
aiti-366	11	9	a	a	DET
aiti-366	11	10	lexnet	lexnet	NOUN
aiti-366	11	11	,	,	PUNCT
aiti-366	11	12	vggnet	vggnet	NOUN
aiti-366	11	13	,	,	PUNCT
aiti-366	11	14	texture	texture	NOUN
aiti-366	11	15	descriptor	descriptor	NOUN
aiti-366	11	16	,	,	PUNCT
aiti-366	11	17	garment	garment	NOUN
aiti-366	11	18	categories	category	NOUN
aiti-366	11	19	,	,	PUNCT
aiti-366	11	20	garment	garment	NOUN
aiti-366	11	21	trend	trend	NOUN
aiti-366	11	22	identification	identification	NOUN
aiti-366	11	23	,	,	PUNCT
aiti-366	11	24	design	design	VERB
aiti-366	11	25	classification	classification	NOUN
aiti-366	11	26	for	for	ADP
aiti-366	11	27	garments	garment	NOUN
aiti-366	11	28	1	1	NUM
aiti-366	11	29	.	.	PUNCT
aiti-366	12	1	introduction	introduction	NOUN
aiti-366	12	2	online	online	ADJ
aiti-366	12	3	shopping	shopping	NOUN
aiti-366	12	4	is	be	AUX
aiti-366	12	5	popular	popular	ADJ
aiti-366	12	6	nowadays	nowadays	ADV
aiti-366	12	7	.	.	PUNCT
aiti-366	13	1	customer	customer	NOUN
aiti-366	13	2	select	select	ADJ
aiti-366	13	3	products	product	NOUN
aiti-366	13	4	from	from	ADP
aiti-366	13	5	the	the	DET
aiti-366	13	6	web	web	NOUN
aiti-366	13	7	pages	page	NOUN
aiti-366	13	8	according	accord	VERB
aiti-366	13	9	to	to	ADP
aiti-366	13	10	their	their	PRON
aiti-366	13	11	choice	choice	NOUN
aiti-366	13	12	and	and	CCONJ
aiti-366	13	13	that	that	PRON
aiti-366	13	14	can	can	AUX
aiti-366	13	15	help	help	VERB
aiti-366	13	16	to	to	PART
aiti-366	13	17	predict	predict	VERB
aiti-366	13	18	the	the	DET
aiti-366	13	19	direction	direction	NOUN
aiti-366	13	20	of	of	ADP
aiti-366	13	21	trends	trend	NOUN
aiti-366	13	22	.	.	PUNCT
aiti-366	14	1	if	if	SCONJ
aiti-366	14	2	a	a	DET
aiti-366	14	3	retailer	retailer	NOUN
aiti-366	14	4	knows	know	VERB
aiti-366	14	5	popular	popular	ADJ
aiti-366	14	6	design	design	NOUN
aiti-366	14	7	styles	style	NOUN
aiti-366	14	8	of	of	ADP
aiti-366	14	9	clothing	clothing	NOUN
aiti-366	14	10	products	product	NOUN
aiti-366	14	11	,	,	PUNCT
aiti-366	14	12	it	it	PRON
aiti-366	14	13	can	can	AUX
aiti-366	14	14	increase	increase	VERB
aiti-366	14	15	the	the	DET
aiti-366	14	16	production	production	NOUN
aiti-366	14	17	of	of	ADP
aiti-366	14	18	those	those	DET
aiti-366	14	19	styles	style	NOUN
aiti-366	14	20	to	to	PART
aiti-366	14	21	achieve	achieve	VERB
aiti-366	14	22	more	more	ADJ
aiti-366	14	23	profit	profit	NOUN
aiti-366	14	24	.	.	PUNCT
aiti-366	15	1	therefore	therefore	ADV
aiti-366	15	2	,	,	PUNCT
aiti-366	15	3	if	if	SCONJ
aiti-366	15	4	a	a	DET
aiti-366	15	5	system	system	NOUN
aiti-366	15	6	can	can	AUX
aiti-366	15	7	classify	classify	VERB
aiti-366	15	8	the	the	DET
aiti-366	15	9	garments	garment	NOUN
aiti-366	15	10	products	product	NOUN
aiti-366	15	11	according	accord	VERB
aiti-366	15	12	to	to	ADP
aiti-366	15	13	different	different	ADJ
aiti-366	15	14	style	style	NOUN
aiti-366	15	15	,	,	PUNCT
aiti-366	15	16	texture	texture	NOUN
aiti-366	15	17	,	,	PUNCT
aiti-366	15	18	size	size	NOUN
aiti-366	15	19	etc	etc	X
aiti-366	15	20	.	.	X
aiti-366	15	21	,	,	PUNCT
aiti-366	15	22	it	it	PRON
aiti-366	15	23	can	can	AUX
aiti-366	15	24	automatically	automatically	ADV
aiti-366	15	25	suggest	suggest	VERB
aiti-366	15	26	different	different	ADJ
aiti-366	15	27	products	product	NOUN
aiti-366	15	28	to	to	ADP
aiti-366	15	29	the	the	DET
aiti-366	15	30	customers	customer	NOUN
aiti-366	15	31	based	base	VERB
aiti-366	15	32	on	on	ADP
aiti-366	15	33	their	their	PRON
aiti-366	15	34	choices	choice	NOUN
aiti-366	15	35	.	.	PUNCT
aiti-366	16	1	the	the	DET
aiti-366	16	2	system	system	NOUN
aiti-366	16	3	proposed	propose	VERB
aiti-366	16	4	in	in	ADP
aiti-366	16	5	this	this	DET
aiti-366	16	6	paper	paper	NOUN
aiti-366	16	7	,	,	PUNCT
aiti-366	16	8	can	can	AUX
aiti-366	16	9	classify	classify	VERB
aiti-366	16	10	clothes	clothe	NOUN
aiti-366	16	11	according	accord	VERB
aiti-366	16	12	to	to	ADP
aiti-366	16	13	textures	texture	NOUN
aiti-366	16	14	.	.	PUNCT
aiti-366	17	1	effective	effective	ADJ
aiti-366	17	2	design	design	NOUN
aiti-366	17	3	classification	classification	NOUN
aiti-366	17	4	based	base	VERB
aiti-366	17	5	on	on	ADP
aiti-366	17	6	textures	texture	NOUN
aiti-366	17	7	,	,	PUNCT
aiti-366	17	8	local	local	ADJ
aiti-366	17	9	spatial	spatial	ADJ
aiti-366	17	10	variations	variation	NOUN
aiti-366	17	11	of	of	ADP
aiti-366	17	12	intensity	intensity	NOUN
aiti-366	17	13	or	or	CCONJ
aiti-366	17	14	colour	colour	NOUN
aiti-366	17	15	in	in	ADP
aiti-366	17	16	images	image	NOUN
aiti-366	17	17	has	have	AUX
aiti-366	17	18	been	be	AUX
aiti-366	17	19	an	an	DET
aiti-366	17	20	important	important	ADJ
aiti-366	17	21	topic	topic	NOUN
aiti-366	17	22	of	of	ADP
aiti-366	17	23	interest	interest	NOUN
aiti-366	17	24	in	in	ADP
aiti-366	17	25	the	the	DET
aiti-366	17	26	past	past	ADJ
aiti-366	17	27	decades	decade	NOUN
aiti-366	17	28	.	.	PUNCT
aiti-366	18	1	a	a	DET
aiti-366	18	2	successful	successful	ADJ
aiti-366	18	3	classification	classification	NOUN
aiti-366	18	4	,	,	PUNCT
aiti-366	18	5	detection	detection	NOUN
aiti-366	18	6	or	or	CCONJ
aiti-366	18	7	segmentation	segmentation	NOUN
aiti-366	18	8	requires	require	VERB
aiti-366	18	9	an	an	DET
aiti-366	18	10	efficient	efficient	ADJ
aiti-366	18	11	description	description	NOUN
aiti-366	18	12	of	of	ADP
aiti-366	18	13	image	image	NOUN
aiti-366	18	14	textures	texture	NOUN
aiti-366	18	15	.	.	PUNCT
aiti-366	19	1	to	to	PART
aiti-366	19	2	fulfil	fulfil	VERB
aiti-366	19	3	this	this	DET
aiti-366	19	4	purpose	purpose	NOUN
aiti-366	19	5	,	,	PUNCT
aiti-366	19	6	lots	lot	NOUN
aiti-366	19	7	of	of	ADP
aiti-366	19	8	well	well	ADV
aiti-366	19	9	-	-	PUNCT
aiti-366	19	10	known	know	VERB
aiti-366	19	11	hand	hand	NOUN
aiti-366	19	12	-	-	PUNCT
aiti-366	19	13	engineered	engineer	VERB
aiti-366	19	14	feature	feature	NOUN
aiti-366	19	15	extraction	extraction	NOUN
aiti-366	19	16	methods	method	NOUN
aiti-366	19	17	such	such	ADJ
aiti-366	19	18	as	as	ADP
aiti-366	19	19	census	census	NOUN
aiti-366	19	20	transform	transform	NOUN
aiti-366	19	21	histogram	histogram	NOUN
aiti-366	19	22	(	(	PUNCT
aiti-366	19	23	centrist	centrist	NOUN
aiti-366	19	24	)	)	PUNCT
aiti-366	20	1	[	[	X
aiti-366	20	2	1	1	NUM
aiti-366	20	3	]	]	PUNCT
aiti-366	20	4	,	,	PUNCT
aiti-366	20	5	local	local	ADJ
aiti-366	20	6	binary	binary	ADJ
aiti-366	20	7	pattern	pattern	NOUN
aiti-366	20	8	(	(	PUNCT
aiti-366	20	9	lbp	lbp	NOUN
aiti-366	20	10	)	)	PUNCT
aiti-366	21	1	[	[	X
aiti-366	21	2	2	2	NUM
aiti-366	21	3	]	]	PUNCT
aiti-366	21	4	,	,	PUNCT
aiti-366	21	5	histogram	histogram	NOUN
aiti-366	21	6	of	of	ADP
aiti-366	21	7	oriented	orient	VERB
aiti-366	21	8	gradient	gradient	NOUN
aiti-366	21	9	(	(	PUNCT
aiti-366	21	10	hog	hog	PROPN
aiti-366	21	11	)	)	PUNCT
aiti-366	22	1	[	[	X
aiti-366	22	2	3	3	NUM
aiti-366	22	3	]	]	PUNCT
aiti-366	22	4	etc	etc	X
aiti-366	22	5	.	.	X
aiti-366	22	6	,	,	PUNCT
aiti-366	22	7	are	be	AUX
aiti-366	22	8	exist	exist	VERB
aiti-366	22	9	.	.	PUNCT
aiti-366	23	1	lbp	lbp	PROPN
aiti-366	23	2	gains	gain	VERB
aiti-366	23	3	popularity	popularity	NOUN
aiti-366	23	4	because	because	SCONJ
aiti-366	23	5	of	of	ADP
aiti-366	23	6	their	their	PRON
aiti-366	23	7	computational	computational	ADJ
aiti-366	23	8	simplicities	simplicity	NOUN
aiti-366	23	9	and	and	CCONJ
aiti-366	23	10	better	well	ADJ
aiti-366	23	11	accuracies	accuracy	NOUN
aiti-366	23	12	.	.	PUNCT
aiti-366	24	1	but	but	CCONJ
aiti-366	24	2	,	,	PUNCT
aiti-366	24	3	it	it	PRON
aiti-366	24	4	is	be	AUX
aiti-366	24	5	very	very	ADV
aiti-366	24	6	sensitive	sensitive	ADJ
aiti-366	24	7	to	to	ADP
aiti-366	24	8	uniform	uniform	NOUN
aiti-366	24	9	and	and	CCONJ
aiti-366	24	10	near	near	ADP
aiti-366	24	11	uniform	uniform	ADJ
aiti-366	24	12	region	region	NOUN
aiti-366	24	13	.	.	PUNCT
aiti-366	25	1	ltp	ltp	X
aiti-366	26	1	[	[	X
aiti-366	26	2	4	4	NUM
aiti-366	26	3	]	]	PUNCT
aiti-366	26	4	,	,	PUNCT
aiti-366	26	5	completed	complete	VERB
aiti-366	26	6	local	local	ADJ
aiti-366	26	7	binary	binary	ADJ
aiti-366	26	8	pattern	pattern	NOUN
aiti-366	26	9	(	(	PUNCT
aiti-366	26	10	clbp	clbp	PROPN
aiti-366	26	11	)	)	PUNCT
aiti-366	27	1	[	[	X
aiti-366	27	2	5	5	NUM
aiti-366	27	3	]	]	PUNCT
aiti-366	27	4	can	can	AUX
aiti-366	27	5	handle	handle	VERB
aiti-366	27	6	this	this	DET
aiti-366	27	7	issue	issue	NOUN
aiti-366	27	8	more	more	ADV
aiti-366	27	9	accurately	accurately	ADV
aiti-366	27	10	.	.	PUNCT
aiti-366	28	1	between	between	ADP
aiti-366	28	2	these	these	DET
aiti-366	28	3	two	two	NUM
aiti-366	28	4	methods	method	NOUN
aiti-366	28	5	,	,	PUNCT
aiti-366	28	6	clbp	clbp	PROPN
aiti-366	28	7	is	be	AUX
aiti-366	28	8	better	well	ADJ
aiti-366	28	9	choice	choice	NOUN
aiti-366	28	10	because	because	SCONJ
aiti-366	28	11	this	this	DET
aiti-366	28	12	method	method	NOUN
aiti-366	28	13	is	be	AUX
aiti-366	28	14	rotation	rotation	NOUN
aiti-366	28	15	invariant	invariant	ADJ
aiti-366	28	16	.	.	PUNCT
aiti-366	29	1	centrist	centrist	NOUN
aiti-366	30	1	[	[	X
aiti-366	30	2	1	1	X
aiti-366	30	3	]	]	PUNCT
aiti-366	30	4	has	have	AUX
aiti-366	30	5	gain	gain	VERB
aiti-366	30	6	popularity	popularity	NOUN
aiti-366	30	7	by	by	ADP
aiti-366	30	8	incorporating	incorporate	VERB
aiti-366	30	9	spatial	spatial	ADJ
aiti-366	30	10	pyramid	pyramid	NOUN
aiti-366	30	11	(	(	PUNCT
aiti-366	30	12	sp	sp	NOUN
aiti-366	30	13	)	)	PUNCT
aiti-366	30	14	structure	structure	NOUN
aiti-366	30	15	.	.	PUNCT
aiti-366	31	1	but	but	CCONJ
aiti-366	31	2	,	,	PUNCT
aiti-366	31	3	most	most	ADV
aiti-366	31	4	recently	recently	ADV
aiti-366	31	5	completed	complete	VERB
aiti-366	31	6	centrist	centrist	NOUN
aiti-366	31	7	(	(	PUNCT
aiti-366	31	8	ccentrist	ccentrist	NOUN
aiti-366	31	9	)	)	PUNCT
aiti-366	31	10	and	and	CCONJ
aiti-366	31	11	ternary	ternary	ADJ
aiti-366	31	12	centrist	centrist	NOUN
aiti-366	31	13	(	(	PUNCT
aiti-366	31	14	tcentrist	tcentrist	NOUN
aiti-366	31	15	)	)	PUNCT
aiti-366	32	1	[	[	X
aiti-366	32	2	6	6	NUM
aiti-366	32	3	]	]	PUNCT
aiti-366	32	4	gained	gain	VERB
aiti-366	32	5	high	high	ADJ
aiti-366	32	6	accuracies	accuracy	NOUN
aiti-366	32	7	for	for	ADP
aiti-366	32	8	garments	garment	NOUN
aiti-366	32	9	design	design	NOUN
aiti-366	32	10	classification	classification	NOUN
aiti-366	32	11	.	.	PUNCT
aiti-366	33	1	although	although	SCONJ
aiti-366	33	2	several	several	ADJ
aiti-366	33	3	hand	hand	NOUN
aiti-366	33	4	-	-	PUNCT
aiti-366	33	5	engineered	engineer	VERB
aiti-366	33	6	feature	feature	NOUN
aiti-366	33	7	extraction	extraction	NOUN
aiti-366	33	8	approaches	approach	NOUN
aiti-366	33	9	exist	exist	VERB
aiti-366	33	10	for	for	ADP
aiti-366	33	11	garments	garment	NOUN
aiti-366	33	12	design	design	NOUN
aiti-366	33	13	classification	classification	NOUN
aiti-366	33	14	,	,	PUNCT
aiti-366	33	15	deep	deep	ADJ
aiti-366	33	16	learning	learning	NOUN
aiti-366	33	17	is	be	AUX
aiti-366	33	18	rarely	rarely	ADV
aiti-366	33	19	used	use	VERB
aiti-366	33	20	in	in	ADP
aiti-366	33	21	this	this	DET
aiti-366	33	22	field	field	NOUN
aiti-366	33	23	.	.	PUNCT
aiti-366	34	1	our	our	PRON
aiti-366	34	2	goal	goal	NOUN
aiti-366	34	3	is	be	AUX
aiti-366	34	4	to	to	PART
aiti-366	34	5	apply	apply	VERB
aiti-366	34	6	appropriate	appropriate	ADJ
aiti-366	34	7	deep	deep	ADJ
aiti-366	34	8	learning	learning	NOUN
aiti-366	34	9	model	model	NOUN
aiti-366	34	10	to	to	PART
aiti-366	34	11	measure	measure	VERB
aiti-366	34	12	the	the	DET
aiti-366	34	13	performance	performance	NOUN
aiti-366	34	14	of	of	ADP
aiti-366	34	15	garments	garment	NOUN
aiti-366	34	16	design	design	NOUN
aiti-366	34	17	identification	identification	NOUN
aiti-366	34	18	based	base	VERB
aiti-366	34	19	on	on	ADP
aiti-366	34	20	textures	texture	NOUN
aiti-366	34	21	.	.	PUNCT
aiti-366	35	1	in	in	ADP
aiti-366	35	2	recent	recent	ADJ
aiti-366	35	3	year	year	NOUN
aiti-366	35	4	,	,	PUNCT
aiti-366	35	5	deep	deep	ADJ
aiti-366	35	6	learning	learning	NOUN
aiti-366	35	7	has	have	AUX
aiti-366	35	8	become	become	VERB
aiti-366	35	9	popular	popular	ADJ
aiti-366	35	10	in	in	ADP
aiti-366	35	11	the	the	DET
aiti-366	35	12	field	field	NOUN
aiti-366	35	13	of	of	ADP
aiti-366	35	14	machine	machine	NOUN
aiti-366	35	15	learning	learning	NOUN
aiti-366	35	16	and	and	CCONJ
aiti-366	35	17	computer	computer	NOUN
aiti-366	35	18	vision	vision	NOUN
aiti-366	35	19	.	.	PUNCT
aiti-366	36	1	using	use	VERB
aiti-366	36	2	large	large	ADJ
aiti-366	36	3	architectures	architecture	NOUN
aiti-366	36	4	with	with	ADP
aiti-366	36	5	numerous	numerous	ADJ
aiti-366	36	6	features	feature	NOUN
aiti-366	36	7	,	,	PUNCT
aiti-366	36	8	many	many	ADJ
aiti-366	36	9	deep	deep	ADJ
aiti-366	36	10	learning	learning	NOUN
aiti-366	36	11	models	model	NOUN
aiti-366	36	12	achieve	achieve	VERB
aiti-366	36	13	high	high	ADJ
aiti-366	36	14	performance	performance	NOUN
aiti-366	36	15	in	in	ADP
aiti-366	36	16	the	the	DET
aiti-366	36	17	field	field	NOUN
aiti-366	36	18	of	of	ADP
aiti-366	36	19	object	object	NOUN
aiti-366	36	20	detection	detection	NOUN
aiti-366	36	21	,	,	PUNCT
aiti-366	36	22	text	text	NOUN
aiti-366	36	23	classification	classification	NOUN
aiti-366	36	24	,	,	PUNCT
aiti-366	36	25	image	image	NOUN
aiti-366	36	26	classification	classification	NOUN
aiti-366	36	27	,	,	PUNCT
aiti-366	36	28	face	face	NOUN
aiti-366	36	29	verification	verification	NOUN
aiti-366	36	30	,	,	PUNCT
aiti-366	36	31	gender	gender	NOUN
aiti-366	36	32	classification	classification	NOUN
aiti-366	36	33	,	,	PUNCT
aiti-366	36	34	scene	scene	NOUN
aiti-366	36	35	-	-	PUNCT
aiti-366	36	36	classification	classification	NOUN
aiti-366	36	37	,	,	PUNCT
aiti-366	36	38	digits	digit	NOUN
aiti-366	36	39	and	and	CCONJ
aiti-366	36	40	traffic	traffic	NOUN
aiti-366	36	41	signs	sign	NOUN
aiti-366	36	42	recognition	recognition	NOUN
aiti-366	36	43	,	,	PUNCT
aiti-366	36	44	etc	etc	X
aiti-366	36	45	.	.	X
aiti-366	37	1	some	some	PRON
aiti-366	37	2	of	of	ADP
aiti-366	37	3	the	the	DET
aiti-366	37	4	available	available	ADJ
aiti-366	37	5	deep	deep	ADJ
aiti-366	37	6	learning	learning	NOUN
aiti-366	37	7	models	model	NOUN
aiti-366	37	8	are	be	AUX
aiti-366	37	9	alexnet	alexnet	ADJ
aiti-366	37	10	[	[	X
aiti-366	37	11	7	7	NUM
aiti-366	37	12	]	]	PUNCT
aiti-366	37	13	,	,	PUNCT
aiti-366	37	14	vggnet	vggnet	PROPN
aiti-366	38	1	[	[	X
aiti-366	38	2	9	9	NUM
aiti-366	38	3	]	]	PUNCT
aiti-366	38	4	,	,	PUNCT
aiti-366	38	5	berkeley	berkeley	NOUN
aiti-366	38	6	-	-	PUNCT
aiti-366	38	7	trained	train	VERB
aiti-366	38	8	models	model	NOUN
aiti-366	38	9	[	[	X
aiti-366	38	10	10	10	NUM
aiti-366	38	11	]	]	PUNCT
aiti-366	38	12	,	,	PUNCT
aiti-366	38	13	places	places	PROPN
aiti-366	38	14	-	-	PUNCT
aiti-366	38	15	cnn	cnn	PROPN
aiti-366	38	16	model	model	NOUN
aiti-366	38	17	[	[	X
aiti-366	38	18	8	8	NUM
aiti-366	38	19	]	]	PUNCT
aiti-366	38	20	,	,	PUNCT
aiti-366	38	21	places	place	NOUN
aiti-366	38	22	-	-	PUNCT
aiti-366	38	23	cnds	cnd	VERB
aiti-366	38	24	models	model	NOUN
aiti-366	38	25	on	on	ADP
aiti-366	38	26	scene	scene	NOUN
aiti-366	38	27	recognition	recognition	NOUN
aiti-366	39	1	[	[	X
aiti-366	39	2	11	11	NUM
aiti-366	39	3	]	]	PUNCT
aiti-366	39	4	,	,	PUNCT
aiti-366	39	5	models	model	NOUN
aiti-366	39	6	for	for	ADP
aiti-366	39	7	age	age	NOUN
aiti-366	39	8	and	and	CCONJ
aiti-366	39	9	gender	gender	NOUN
aiti-366	39	10	classification	classification	NOUN
aiti-366	39	11	[	[	X
aiti-366	39	12	12	12	NUM
aiti-366	39	13	]	]	PUNCT
aiti-366	39	14	,	,	PUNCT
aiti-366	39	15	googlenet	googlenet	NOUN
aiti-366	39	16	model	model	NOUN
aiti-366	39	17	[	[	X
aiti-366	39	18	13	13	NUM
aiti-366	39	19	]	]	PUNCT
aiti-366	39	20	,	,	PUNCT
aiti-366	39	21	etc	etc	X
aiti-366	39	22	.	.	X
aiti-366	40	1	these	these	DET
aiti-366	40	2	methods	method	NOUN
aiti-366	40	3	have	have	AUX
aiti-366	40	4	achieved	achieve	VERB
aiti-366	40	5	dramatic	dramatic	ADJ
aiti-366	40	6	improvements	improvement	NOUN
aiti-366	40	7	and	and	CCONJ
aiti-366	40	8	attracted	attract	VERB
aiti-366	40	9	considerable	considerable	ADJ
aiti-366	40	10	interest	interest	NOUN
aiti-366	40	11	in	in	ADP
aiti-366	40	12	both	both	CCONJ
aiti-366	40	13	the	the	DET
aiti-366	40	14	academic	academic	ADJ
aiti-366	40	15	and	and	CCONJ
aiti-366	40	16	industrial	industrial	ADJ
aiti-366	40	17	communities	community	NOUN
aiti-366	40	18	.	.	PUNCT
aiti-366	41	1	in	in	ADP
aiti-366	41	2	general	general	ADJ
aiti-366	41	3	,	,	PUNCT
aiti-366	41	4	deep	deep	ADJ
aiti-366	41	5	learning	learn	VERB
aiti-366	41	6	algorithms	algorithm	NOUN
aiti-366	41	7	attempt	attempt	VERB
aiti-366	41	8	to	to	PART
aiti-366	41	9	learn	learn	VERB
aiti-366	41	10	hierarchical	hierarchical	ADJ
aiti-366	41	11	features	feature	NOUN
aiti-366	41	12	,	,	PUNCT
aiti-366	41	13	corresponding	correspond	VERB
aiti-366	41	14	to	to	ADP
aiti-366	41	15	different	different	ADJ
aiti-366	41	16	levels	level	NOUN
aiti-366	41	17	of	of	ADP
aiti-366	41	18	abstraction	abstraction	NOUN
aiti-366	41	19	.	.	PUNCT
aiti-366	42	1	each	each	PRON
aiti-366	42	2	of	of	ADP
aiti-366	42	3	these	these	DET
aiti-366	42	4	models	model	NOUN
aiti-366	42	5	concerned	concerned	ADJ
aiti-366	42	6	about	about	ADP
aiti-366	42	7	some	some	DET
aiti-366	42	8	specific	specific	ADJ
aiti-366	42	9	issues	issue	NOUN
aiti-366	42	10	:	:	PUNCT
aiti-366	42	11	preventing	prevent	VERB
aiti-366	42	12	over	over	ADP
aiti-366	42	13	-	-	PUNCT
aiti-366	42	14	fitting	fitting	ADJ
aiti-366	42	15	,	,	PUNCT
aiti-366	42	16	connection	connection	NOUN
aiti-366	42	17	of	of	ADP
aiti-366	42	18	nodes	node	NOUN
aiti-366	42	19	between	between	ADP
aiti-366	42	20	adjacent	adjacent	ADJ
aiti-366	42	21	layers	layer	NOUN
aiti-366	42	22	,	,	PUNCT
aiti-366	42	23	large	large	ADJ
aiti-366	42	24	learning	learning	NOUN
aiti-366	42	25	capacity	capacity	NOUN
aiti-366	42	26	,	,	PUNCT
aiti-366	42	27	etc	etc	X
aiti-366	42	28	.	.	X
aiti-366	42	29	several	several	ADJ
aiti-366	42	30	factors	factor	NOUN
aiti-366	42	31	need	need	VERB
aiti-366	42	32	to	to	PART
aiti-366	42	33	be	be	AUX
aiti-366	42	34	considered	consider	VERB
aiti-366	42	35	for	for	ADP
aiti-366	42	36	working	work	VERB
aiti-366	42	37	with	with	ADP
aiti-366	42	38	deep	deep	ADJ
aiti-366	42	39	learning	learning	NOUN
aiti-366	42	40	network	network	NOUN
aiti-366	42	41	such	such	ADJ
aiti-366	42	42	as	as	ADP
aiti-366	42	43	availability	availability	NOUN
aiti-366	42	44	of	of	ADP
aiti-366	42	45	large	large	ADJ
aiti-366	42	46	training	training	NOUN
aiti-366	42	47	set	set	NOUN
aiti-366	42	48	,	,	PUNCT
aiti-366	42	49	powerful	powerful	ADJ
aiti-366	42	50	gpu	gpu	NOUN
aiti-366	42	51	for	for	ADP
aiti-366	42	52	training	training	NOUN
aiti-366	42	53	and	and	CCONJ
aiti-366	42	54	testing	testing	NOUN
aiti-366	42	55	,	,	PUNCT
aiti-366	42	56	better	well	ADJ
aiti-366	42	57	model	model	NOUN
aiti-366	42	58	regularization	regularization	NOUN
aiti-366	42	59	strategies	strategy	NOUN
aiti-366	42	60	,	,	PUNCT
aiti-366	42	61	the	the	DET
aiti-366	42	62	amount	amount	NOUN
aiti-366	42	63	of	of	ADP
aiti-366	42	64	training	training	NOUN
aiti-366	42	65	time	time	NOUN
aiti-366	42	66	that	that	PRON
aiti-366	42	67	one	one	PRON
aiti-366	42	68	can	can	AUX
aiti-366	42	69	tolerate	tolerate	VERB
aiti-366	42	70	,	,	PUNCT
aiti-366	42	71	etc	etc	X
aiti-366	42	72	.	.	X
aiti-366	43	1	the	the	DET
aiti-366	43	2	major	major	ADJ
aiti-366	43	3	contributions	contribution	NOUN
aiti-366	43	4	of	of	ADP
aiti-366	43	5	this	this	DET
aiti-366	43	6	paper	paper	NOUN
aiti-366	43	7	are	be	AUX
aiti-366	43	8	as	as	SCONJ
aiti-366	43	9	follows	follow	VERB
aiti-366	43	10	.	.	PUNCT
aiti-366	44	1	(	(	PUNCT
aiti-366	44	2	1	1	X
aiti-366	44	3	)	)	PUNCT
aiti-366	44	4	in	in	ADP
aiti-366	44	5	this	this	DET
aiti-366	44	6	paper	paper	NOUN
aiti-366	44	7	,	,	PUNCT
aiti-366	44	8	a	a	DET
aiti-366	44	9	b	b	NOUN
aiti-366	44	10	rief	rief	NOUN
aiti-366	44	11	review	review	NOUN
aiti-366	44	12	on	on	ADP
aiti-366	44	13	existing	exist	VERB
aiti-366	44	14	well	well	ADV
aiti-366	44	15	known	know	VERB
aiti-366	44	16	hand	hand	NOUN
aiti-366	44	17	-	-	PUNCT
aiti-366	44	18	engineered	engineer	VERB
aiti-366	44	19	feature	feature	NOUN
aiti-366	44	20	ext	ext	NOUN
aiti-366	44	21	raction	raction	NOUN
aiti-366	44	22	methods	method	NOUN
aiti-366	44	23	for	for	ADP
aiti-366	44	24	garments	garment	NOUN
aiti-366	44	25	design	design	NOUN
aiti-366	44	26	class	class	NOUN
aiti-366	44	27	identification	identification	NOUN
aiti-366	44	28	has	have	AUX
aiti-366	44	29	been	be	AUX
aiti-366	44	30	conducted	conduct	VERB
aiti-366	44	31	.	.	PUNCT
aiti-366	45	1	(	(	PUNCT
aiti-366	45	2	2	2	X
aiti-366	45	3	)	)	PUNCT
aiti-366	45	4	this	this	DET
aiti-366	45	5	research	research	NOUN
aiti-366	45	6	has	have	AUX
aiti-366	45	7	applied	apply	VERB
aiti-366	45	8	some	some	DET
aiti-366	45	9	existing	exist	VERB
aiti-366	45	10	deep	deep	ADJ
aiti-366	45	11	convolutional	convolutional	ADJ
aiti-366	45	12	neural	neural	ADJ
aiti-366	45	13	network	network	NOUN
aiti-366	45	14	models	model	NOUN
aiti-366	45	15	for	for	ADP
aiti-366	45	16	classifying	classify	VERB
aiti-366	45	17	the	the	DET
aiti-366	45	18	clothing	clothing	NOUN
aiti-366	45	19	products	product	NOUN
aiti-366	45	20	on	on	ADP
aiti-366	45	21	some	some	DET
aiti-366	45	22	datasets	dataset	NOUN
aiti-366	45	23	and	and	CCONJ
aiti-366	45	24	compared	compare	VERB
aiti-366	45	25	the	the	DET
aiti-366	45	26	results	result	NOUN
aiti-366	45	27	with	with	ADP
aiti-366	45	28	several	several	ADJ
aiti-366	45	29	state	state	NOUN
aiti-366	45	30	-	-	PUNCT
aiti-366	45	31	of	of	ADP
aiti-366	45	32	-	-	PUNCT
aiti-366	45	33	the	the	DET
aiti-366	45	34	-	-	PUNCT
aiti-366	45	35	art	art	NOUN
aiti-366	45	36	hand	hand	NOUN
aiti-366	45	37	-	-	PUNCT
aiti-366	45	38	engineered	engineer	VERB
aiti-366	45	39	feature	feature	NOUN
aiti-366	45	40	extraction	extraction	NOUN
aiti-366	45	41	methods	method	NOUN
aiti-366	45	42	.	.	PUNCT
aiti-366	46	1	(	(	PUNCT
aiti-366	46	2	3	3	X
aiti-366	46	3	)	)	PUNCT
aiti-366	46	4	a	a	DET
aiti-366	46	5	new	new	ADJ
aiti-366	46	6	deep	deep	ADJ
aiti-366	46	7	convolutional	convolutional	ADJ
aiti-366	46	8	neural	neural	ADJ
aiti-366	46	9	network	network	NOUN
aiti-366	46	10	model	model	NOUN
aiti-366	46	11	has	have	AUX
aiti-366	46	12	been	be	AUX
aiti-366	46	13	proposed	propose	VERB
aiti-366	46	14	for	for	ADP
aiti-366	46	15	classifying	classify	VERB
aiti-366	46	16	garments	garment	NOUN
aiti-366	46	17	design	design	NOUN
aiti-366	46	18	class	class	NOUN
aiti-366	46	19	.	.	PUNCT
aiti-366	47	1	this	this	DET
aiti-366	47	2	proposed	propose	VERB
aiti-366	47	3	model	model	NOUN
aiti-366	47	4	is	be	AUX
aiti-366	47	5	applied	apply	VERB
aiti-366	47	6	on	on	ADP
aiti-366	47	7	two	two	NUM
aiti-366	47	8	different	different	ADJ
aiti-366	47	9	datasets	dataset	NOUN
aiti-366	47	10	and	and	CCONJ
aiti-366	47	11	has	have	AUX
aiti-366	47	12	found	find	VERB
aiti-366	47	13	a	a	DET
aiti-366	47	14	remarkable	remarkable	ADJ
aiti-366	47	15	output	output	NOUN
aiti-366	47	16	.	.	PUNCT
aiti-366	48	1	the	the	DET
aiti-366	48	2	rest	rest	NOUN
aiti-366	48	3	of	of	ADP
aiti-366	48	4	the	the	DET
aiti-366	48	5	paper	paper	NOUN
aiti-366	48	6	is	be	AUX
aiti-366	48	7	structured	structure	VERB
aiti-366	48	8	as	as	SCONJ
aiti-366	48	9	follows	follow	VERB
aiti-366	48	10	.	.	PUNCT
aiti-366	49	1	section	section	NOUN
aiti-366	49	2	2	2	NUM
aiti-366	49	3	and	and	CCONJ
aiti-366	49	4	section	section	NOUN
aiti-366	49	5	3	3	NUM
aiti-366	49	6	describe	describe	VERB
aiti-366	49	7	the	the	DET
aiti-366	49	8	background	background	NOUN
aiti-366	49	9	studies	study	NOUN
aiti-366	49	10	and	and	CCONJ
aiti-366	49	11	the	the	DET
aiti-366	49	12	methodology	methodology	NOUN
aiti-366	49	13	respectively	respectively	ADV
aiti-366	49	14	.	.	PUNCT
aiti-366	50	1	section	section	NOUN
aiti-366	50	2	4	4	NUM
aiti-366	50	3	has	have	AUX
aiti-366	50	4	presented	present	VERB
aiti-366	50	5	the	the	DET
aiti-366	50	6	experimental	experimental	ADJ
aiti-366	50	7	results	result	NOUN
aiti-366	50	8	and	and	CCONJ
aiti-366	50	9	finally	finally	ADV
aiti-366	50	10	section	section	NOUN
aiti-366	50	11	5	5	NUM
aiti-366	50	12	concluded	conclude	VERB
aiti-366	50	13	the	the	DET
aiti-366	50	14	overall	overall	ADJ
aiti-366	50	15	work	work	NOUN
aiti-366	50	16	with	with	ADP
aiti-366	50	17	necessary	necessary	ADJ
aiti-366	50	18	explanation	explanation	NOUN
aiti-366	50	19	.	.	PUNCT
aiti-366	51	1	2	2	X
aiti-366	51	2	.	.	X
aiti-366	51	3	background	background	NOUN
aiti-366	51	4	studies	study	NOUN
aiti-366	51	5	in	in	ADP
aiti-366	51	6	this	this	DET
aiti-366	51	7	section	section	NOUN
aiti-366	51	8	,	,	PUNCT
aiti-366	51	9	some	some	DET
aiti-366	51	10	existing	exist	VERB
aiti-366	51	11	garments	garment	NOUN
aiti-366	51	12	clothing	clothing	NOUN
aiti-366	51	13	segmentation	segmentation	NOUN
aiti-366	51	14	and	and	CCONJ
aiti-366	51	15	classification	classification	NOUN
aiti-366	51	16	strategies	strategy	NOUN
aiti-366	51	17	have	have	AUX
aiti-366	51	18	been	be	AUX
aiti-366	51	19	described	describe	VERB
aiti-366	51	20	.	.	PUNCT
aiti-366	52	1	some	some	DET
aiti-366	52	2	existing	exist	VERB
aiti-366	52	3	deep	deep	ADJ
aiti-366	52	4	learning	learning	NOUN
aiti-366	52	5	models	model	NOUN
aiti-366	52	6	;	;	PUNCT
aiti-366	52	7	that	that	PRON
aiti-366	52	8	have	have	VERB
aiti-366	52	9	*	*	PUNCT
aiti-366	52	10	corresponding	correspond	VERB
aiti-366	52	11	author	author	NOUN
aiti-366	52	12	.	.	PUNCT
aiti-366	53	1	email	email	NOUN
aiti-366	53	2	:	:	PUNCT
aiti-366	53	3	emonkd@iit.du.ac.bd	emonkd@iit.du.ac.bd	NUM
aiti-366	53	4	advances	advance	NOUN
aiti-366	53	5	in	in	ADP
aiti-366	53	6	technology	technology	NOUN
aiti-366	53	7	innovation	innovation	NOUN
aiti-366	53	8	,	,	PUNCT
aiti-366	53	9	vol	vol	NOUN
aiti-366	53	10	.	.	PROPN
aiti-366	54	1	2	2	NUM
aiti-366	54	2	,	,	PUNCT
aiti-366	54	3	no	no	INTJ
aiti-366	54	4	.	.	NOUN
aiti-366	54	5	4	4	NUM
aiti-366	54	6	,	,	PUNCT
aiti-366	54	7	2017	2017	NUM
aiti-366	54	8	,	,	PUNCT
aiti-366	55	1	pp	pp	ADJ
aiti-366	55	2	.	.	PUNCT
aiti-366	56	1	119	119	NUM
aiti-366	56	2	125	125	NUM
aiti-366	56	3	120	120	NUM
aiti-366	56	4	copyright	copyright	NOUN
aiti-366	56	5	©	©	PROPN
aiti-366	56	6	taeti	taeti	PROPN
aiti-366	56	7	copyright	copyright	NOUN
aiti-366	56	8	©	©	PROPN
aiti-366	56	9	taeti	taeti	PROPN
aiti-366	57	1	copyright	copyright	NOUN
aiti-366	57	2	©	©	PROPN
aiti-366	57	3	taeti	taeti	PROPN
aiti-366	58	1	copyright	copyright	NOUN
aiti-366	58	2	©	©	PROPN
aiti-366	58	3	taeti	taeti	PROPN
aiti-366	59	1	copyright	copyright	NOUN
aiti-366	59	2	©	©	PROPN
aiti-366	59	3	taeti	taeti	PROPN
aiti-366	59	4	been	be	AUX
aiti-366	59	5	used	use	VERB
aiti-366	59	6	for	for	ADP
aiti-366	59	7	several	several	ADJ
aiti-366	59	8	applications	application	NOUN
aiti-366	59	9	in	in	ADP
aiti-366	59	10	computer	computer	NOUN
aiti-366	59	11	vision	vision	NOUN
aiti-366	59	12	are	be	AUX
aiti-366	59	13	also	also	ADV
aiti-366	59	14	narrated	narrate	VERB
aiti-366	59	15	in	in	ADP
aiti-366	59	16	this	this	DET
aiti-366	59	17	section	section	NOUN
aiti-366	59	18	.	.	PUNCT
aiti-366	60	1	2.1	2.1	NUM
aiti-366	60	2	.	.	PUNCT
aiti-366	60	3	garment	garment	NOUN
aiti-366	60	4	product	product	NOUN
aiti-366	60	5	segmentation	segmentation	NOUN
aiti-366	60	6	and	and	CCONJ
aiti-366	60	7	identification	identification	NOUN
aiti-366	60	8	yamaguchi	yamaguchi	PROPN
aiti-366	60	9	et	et	PROPN
aiti-366	60	10	al	al	PROPN
aiti-366	60	11	.	.	PUNCT
aiti-366	61	1	[	[	X
aiti-366	61	2	14	14	NUM
aiti-366	61	3	]	]	PUNCT
aiti-366	61	4	proposed	propose	VERB
aiti-366	61	5	a	a	DET
aiti-366	61	6	method	method	NOUN
aiti-366	61	7	for	for	ADP
aiti-366	61	8	clothing	clothing	NOUN
aiti-366	61	9	parsing	parsing	NOUN
aiti-366	61	10	.	.	PUNCT
aiti-366	62	1	for	for	ADP
aiti-366	62	2	this	this	DET
aiti-366	62	3	work	work	NOUN
aiti-366	62	4	,	,	PUNCT
aiti-366	62	5	they	they	PRON
aiti-366	62	6	created	create	VERB
aiti-366	62	7	fashionista	fashionista	ADJ
aiti-366	62	8	dataset	dataset	NOUN
aiti-366	62	9	consisting	consist	VERB
aiti-366	62	10	of	of	ADP
aiti-366	62	11	158,235	158,235	NUM
aiti-366	62	12	images	image	NOUN
aiti-366	62	13	.	.	PUNCT
aiti-366	63	1	from	from	ADP
aiti-366	63	2	this	this	DET
aiti-366	63	3	dataset	dataset	NOUN
aiti-366	63	4	,	,	PUNCT
aiti-366	63	5	they	they	PRON
aiti-366	63	6	selected	select	VERB
aiti-366	63	7	685	685	NUM
aiti-366	63	8	images	image	NOUN
aiti-366	63	9	for	for	ADP
aiti-366	63	10	training	training	NOUN
aiti-366	63	11	and	and	CCONJ
aiti-366	63	12	testing	test	VERB
aiti-366	63	13	their	their	PRON
aiti-366	63	14	system	system	NOUN
aiti-366	63	15	.	.	PUNCT
aiti-366	64	1	they	they	PRON
aiti-366	64	2	identified	identify	VERB
aiti-366	64	3	14	14	NUM
aiti-366	64	4	different	different	ADJ
aiti-366	64	5	parts	part	NOUN
aiti-366	64	6	of	of	ADP
aiti-366	64	7	a	a	DET
aiti-366	64	8	body	body	NOUN
aiti-366	64	9	and	and	CCONJ
aiti-366	64	10	different	different	ADJ
aiti-366	64	11	clothing	clothing	NOUN
aiti-366	64	12	regions	region	NOUN
aiti-366	64	13	.	.	PUNCT
aiti-366	65	1	in	in	ADP
aiti-366	65	2	[	[	X
aiti-366	65	3	15	15	NUM
aiti-366	65	4	]	]	PUNCT
aiti-366	65	5	,	,	PUNCT
aiti-366	65	6	they	they	PRON
aiti-366	65	7	deal	deal	VERB
aiti-366	65	8	with	with	ADP
aiti-366	65	9	clothing	clothing	NOUN
aiti-366	65	10	parsing	parsing	NOUN
aiti-366	65	11	problem	problem	NOUN
aiti-366	65	12	using	use	VERB
aiti-366	65	13	retrieval	retrieval	NOUN
aiti-366	65	14	based	base	VERB
aiti-366	65	15	approach	approach	NOUN
aiti-366	65	16	.	.	PUNCT
aiti-366	66	1	their	their	PRON
aiti-366	66	2	proposed	propose	VERB
aiti-366	66	3	approach	approach	NOUN
aiti-366	66	4	focused	focus	VERB
aiti-366	66	5	on	on	ADP
aiti-366	66	6	pre	pre	ADJ
aiti-366	66	7	-	-	ADJ
aiti-366	66	8	trained	train	VERB
aiti-366	66	9	global	global	ADJ
aiti-366	66	10	clothing	clothing	NOUN
aiti-366	66	11	models	model	NOUN
aiti-366	66	12	,	,	PUNCT
aiti-366	66	13	local	local	ADJ
aiti-366	66	14	clothing	clothing	NOUN
aiti-366	66	15	models	model	NOUN
aiti-366	66	16	,	,	PUNCT
aiti-366	66	17	and	and	CCONJ
aiti-366	66	18	transferred	transfer	VERB
aiti-366	66	19	parse	parse	NOUN
aiti-366	66	20	.	.	PUNCT
aiti-366	67	1	authors	author	NOUN
aiti-366	67	2	found	find	VERB
aiti-366	67	3	that	that	SCONJ
aiti-366	67	4	their	their	PRON
aiti-366	67	5	proposed	propose	VERB
aiti-366	67	6	final	final	ADJ
aiti-366	67	7	parse	parse	NOUN
aiti-366	67	8	achieve	achieve	VERB
aiti-366	67	9	84.68	84.68	NUM
aiti-366	67	10	%	%	NOUN
aiti-366	67	11	parsing	parsing	NOUN
aiti-366	67	12	accuracy	accuracy	NOUN
aiti-366	67	13	.	.	PUNCT
aiti-366	68	1	menfredi	menfredi	PROPN
aiti-366	68	2	et	et	PROPN
aiti-366	68	3	al	al	PROPN
aiti-366	68	4	.	.	PUNCT
aiti-366	69	1	[	[	X
aiti-366	69	2	16	16	NUM
aiti-366	69	3	]	]	PUNCT
aiti-366	69	4	proposed	propose	VERB
aiti-366	69	5	a	a	DET
aiti-366	69	6	new	new	ADJ
aiti-366	69	7	approach	approach	NOUN
aiti-366	69	8	for	for	ADP
aiti-366	69	9	automatic	automatic	ADJ
aiti-366	69	10	garments	garment	NOUN
aiti-366	69	11	segmentation	segmentation	NOUN
aiti-366	69	12	and	and	CCONJ
aiti-366	69	13	classification	classification	NOUN
aiti-366	69	14	.	.	PUNCT
aiti-366	70	1	they	they	PRON
aiti-366	70	2	classified	classify	VERB
aiti-366	70	3	garments	garment	NOUN
aiti-366	70	4	into	into	ADP
aiti-366	70	5	nine	nine	NUM
aiti-366	70	6	different	different	ADJ
aiti-366	70	7	classes	class	NOUN
aiti-366	70	8	such	such	ADJ
aiti-366	70	9	as	as	ADP
aiti-366	70	10	skirts	skirt	NOUN
aiti-366	70	11	,	,	PUNCT
aiti-366	70	12	shirt	shirt	NOUN
aiti-366	70	13	,	,	PUNCT
aiti-366	70	14	dresses	dress	NOUN
aiti-366	70	15	,	,	PUNCT
aiti-366	70	16	etc	etc	X
aiti-366	70	17	.	.	X
aiti-366	70	18	for	for	ADP
aiti-366	70	19	this	this	DET
aiti-366	70	20	work	work	NOUN
aiti-366	70	21	,	,	PUNCT
aiti-366	70	22	authors	author	NOUN
aiti-366	70	23	used	use	VERB
aiti-366	70	24	a	a	DET
aiti-366	70	25	projection	projection	ADJ
aiti-366	70	26	histogram	histogram	NOUN
aiti-366	70	27	for	for	ADP
aiti-366	70	28	extracting	extract	VERB
aiti-366	70	29	few	few	ADJ
aiti-366	70	30	specific	specific	ADJ
aiti-366	70	31	garments	garment	NOUN
aiti-366	70	32	.	.	PUNCT
aiti-366	71	1	they	they	PRON
aiti-366	71	2	divided	divide	VERB
aiti-366	71	3	the	the	DET
aiti-366	71	4	whole	whole	ADJ
aiti-366	71	5	image	image	NOUN
aiti-366	71	6	into	into	ADP
aiti-366	71	7	117	117	NUM
aiti-366	71	8	cells	cell	NOUN
aiti-366	71	9	and	and	CCONJ
aiti-366	71	10	group	group	VERB
aiti-366	71	11	them	they	PRON
aiti-366	71	12	into	into	ADP
aiti-366	71	13	3	3	NUM
aiti-366	71	14	*	*	SYM
aiti-366	71	15	3	3	NUM
aiti-366	71	16	cells	cell	NOUN
aiti-366	71	17	.	.	PUNCT
aiti-366	72	1	they	they	PRON
aiti-366	72	2	computed	compute	VERB
aiti-366	72	3	hog	hog	NOUN
aiti-366	72	4	features	feature	VERB
aiti-366	72	5	[	[	X
aiti-366	72	6	17	17	NUM
aiti-366	72	7	]	]	PUNCT
aiti-366	72	8	from	from	ADP
aiti-366	72	9	each	each	DET
aiti-366	72	10	cell	cell	NOUN
aiti-366	72	11	and	and	CCONJ
aiti-366	72	12	the	the	DET
aiti-366	72	13	orientations	orientation	NOUN
aiti-366	72	14	are	be	AUX
aiti-366	72	15	grouped	group	VERB
aiti-366	72	16	into	into	ADP
aiti-366	72	17	nine	nine	NUM
aiti-366	72	18	bins	bin	NOUN
aiti-366	72	19	.	.	PUNCT
aiti-366	73	1	they	they	PRON
aiti-366	73	2	used	use	VERB
aiti-366	73	3	multiclass	multiclass	ADJ
aiti-366	73	4	linear	linear	ADJ
aiti-366	73	5	support	support	NOUN
aiti-366	73	6	vector	vector	NOUN
aiti-366	73	7	for	for	ADP
aiti-366	73	8	training	training	NOUN
aiti-366	73	9	.	.	PUNCT
aiti-366	74	1	serra	serra	PROPN
aiti-366	74	2	et	et	PROPN
aiti-366	74	3	al	al	PROPN
aiti-366	74	4	.	.	PUNCT
aiti-366	75	1	[	[	X
aiti-366	75	2	18	18	NUM
aiti-366	75	3	]	]	PUNCT
aiti-366	75	4	did	do	VERB
aiti-366	75	5	similar	similar	ADJ
aiti-366	75	6	type	type	NOUN
aiti-366	75	7	of	of	ADP
aiti-366	75	8	work	work	NOUN
aiti-366	75	9	,	,	PUNCT
aiti-366	75	10	where	where	SCONJ
aiti-366	75	11	authors	author	NOUN
aiti-366	75	12	used	use	VERB
aiti-366	75	13	conditional	conditional	ADJ
aiti-366	75	14	random	random	ADJ
aiti-366	75	15	field	field	NOUN
aiti-366	75	16	(	(	PUNCT
aiti-366	75	17	crf	crf	NOUN
aiti-366	75	18	)	)	PUNCT
aiti-366	75	19	for	for	ADP
aiti-366	75	20	divided	divided	ADJ
aiti-366	75	21	outfits	outfit	NOUN
aiti-366	75	22	.	.	PUNCT
aiti-366	76	1	vittayakorn	vittayakorn	NOUN
aiti-366	76	2	et	et	PROPN
aiti-366	76	3	al	al	PROPN
aiti-366	76	4	.	.	PUNCT
aiti-366	77	1	[	[	X
aiti-366	77	2	19	19	NUM
aiti-366	77	3	]	]	PUNCT
aiti-366	77	4	used	use	VERB
aiti-366	77	5	five	five	NUM
aiti-366	77	6	different	different	ADJ
aiti-366	77	7	features	feature	NOUN
aiti-366	77	8	such	such	ADJ
aiti-366	77	9	as	as	ADP
aiti-366	77	10	color	color	NOUN
aiti-366	77	11	,	,	PUNCT
aiti-366	77	12	texture	texture	NOUN
aiti-366	77	13	,	,	PUNCT
aiti-366	77	14	shape	shape	NOUN
aiti-366	77	15	,	,	PUNCT
aiti-366	77	16	parse	parse	NOUN
aiti-366	77	17	and	and	CCONJ
aiti-366	77	18	style	style	NOUN
aiti-366	77	19	descriptor	descriptor	NOUN
aiti-366	77	20	to	to	PART
aiti-366	77	21	identify	identify	VERB
aiti-366	77	22	three	three	NUM
aiti-366	77	23	different	different	ADJ
aiti-366	77	24	visual	visual	ADJ
aiti-366	77	25	trends	trend	NOUN
aiti-366	77	26	,	,	PUNCT
aiti-366	77	27	namely	namely	ADV
aiti-366	77	28	floral	floral	ADJ
aiti-366	77	29	print	print	NOUN
aiti-366	77	30	,	,	PUNCT
aiti-366	77	31	pastel	pastel	ADJ
aiti-366	77	32	color	color	NOUN
aiti-366	77	33	and	and	CCONJ
aiti-366	77	34	neon	neon	NOUN
aiti-366	77	35	color	color	NOUN
aiti-366	77	36	from	from	ADP
aiti-366	77	37	runway	runway	NOUN
aiti-366	77	38	to	to	ADP
aiti-366	77	39	street	street	NOUN
aiti-366	77	40	fashion	fashion	NOUN
aiti-366	77	41	.	.	PUNCT
aiti-366	78	1	however	however	ADV
aiti-366	78	2	,	,	PUNCT
aiti-366	78	3	using	use	VERB
aiti-366	78	4	more	more	ADJ
aiti-366	78	5	color	color	NOUN
aiti-366	78	6	and	and	CCONJ
aiti-366	78	7	design	design	NOUN
aiti-366	78	8	classes	class	NOUN
aiti-366	78	9	would	would	AUX
aiti-366	78	10	be	be	AUX
aiti-366	78	11	more	more	ADV
aiti-366	78	12	beneficial	beneficial	ADJ
aiti-366	78	13	in	in	ADP
aiti-366	78	14	this	this	DET
aiti-366	78	15	field	field	NOUN
aiti-366	78	16	.	.	PUNCT
aiti-366	79	1	kalantidis	kalantidis	PROPN
aiti-366	79	2	et	et	PROPN
aiti-366	79	3	al	al	PROPN
aiti-366	79	4	.	.	PUNCT
aiti-366	80	1	[	[	X
aiti-366	80	2	20	20	NUM
aiti-366	80	3	]	]	PUNCT
aiti-366	80	4	proposed	propose	VERB
aiti-366	80	5	a	a	DET
aiti-366	80	6	system	system	NOUN
aiti-366	80	7	to	to	PART
aiti-366	80	8	identify	identify	VERB
aiti-366	80	9	the	the	DET
aiti-366	80	10	relevant	relevant	ADJ
aiti-366	80	11	product	product	NOUN
aiti-366	80	12	where	where	SCONJ
aiti-366	80	13	they	they	PRON
aiti-366	80	14	firstly	firstly	ADV
aiti-366	80	15	estimated	estimate	VERB
aiti-366	80	16	the	the	DET
aiti-366	80	17	pose	pose	NOUN
aiti-366	80	18	of	of	ADP
aiti-366	80	19	a	a	DET
aiti-366	80	20	person	person	NOUN
aiti-366	80	21	from	from	ADP
aiti-366	80	22	an	an	DET
aiti-366	80	23	input	input	NOUN
aiti-366	80	24	image	image	NOUN
aiti-366	80	25	and	and	CCONJ
aiti-366	80	26	then	then	ADV
aiti-366	80	27	segmented	segment	VERB
aiti-366	80	28	the	the	DET
aiti-366	80	29	clothing	clothing	NOUN
aiti-366	80	30	area	area	NOUN
aiti-366	80	31	such	such	ADJ
aiti-366	80	32	as	as	ADP
aiti-366	80	33	shirt	shirt	NOUN
aiti-366	80	34	,	,	PUNCT
aiti-366	80	35	tops	top	NOUN
aiti-366	80	36	,	,	PUNCT
aiti-366	80	37	jeans	jean	NOUN
aiti-366	80	38	,	,	PUNCT
aiti-366	80	39	etc	etc	X
aiti-366	80	40	.	.	X
aiti-366	80	41	finally	finally	ADV
aiti-366	80	42	,	,	PUNCT
aiti-366	80	43	they	they	PRON
aiti-366	80	44	applied	apply	VERB
aiti-366	80	45	an	an	DET
aiti-366	80	46	image	image	NOUN
aiti-366	80	47	retrieval	retrieval	NOUN
aiti-366	80	48	technique	technique	NOUN
aiti-366	80	49	which	which	PRON
aiti-366	80	50	is	be	AUX
aiti-366	80	51	50	50	NUM
aiti-366	80	52	times	time	NOUN
aiti-366	80	53	faster	fast	ADJ
aiti-366	80	54	than	than	ADP
aiti-366	80	55	[	[	X
aiti-366	80	56	14	14	NUM
aiti-366	80	57	]	]	PUNCT
aiti-366	80	58	for	for	ADP
aiti-366	80	59	identifying	identify	VERB
aiti-366	80	60	similar	similar	ADJ
aiti-366	80	61	clothes	clothe	NOUN
aiti-366	80	62	for	for	ADP
aiti-366	80	63	each	each	DET
aiti-366	80	64	class	class	NOUN
aiti-366	80	65	.	.	PUNCT
aiti-366	81	1	gallagher	gallagher	PROPN
aiti-366	81	2	et	et	PROPN
aiti-366	81	3	al	al	PROPN
aiti-366	81	4	.	.	PUNCT
aiti-366	82	1	[	[	X
aiti-366	82	2	21	21	NUM
aiti-366	82	3	]	]	X
aiti-366	82	4	used	use	VERB
aiti-366	82	5	grab	grab	NOUN
aiti-366	82	6	cut	cut	VERB
aiti-366	82	7	algorithm	algorithm	NOUN
aiti-366	82	8	for	for	ADP
aiti-366	82	9	identifying	identify	VERB
aiti-366	82	10	a	a	DET
aiti-366	82	11	person	person	NOUN
aiti-366	82	12	by	by	ADP
aiti-366	82	13	segmenting	segment	VERB
aiti-366	82	14	the	the	DET
aiti-366	82	15	clothing	clothing	NOUN
aiti-366	82	16	parts	part	NOUN
aiti-366	82	17	.	.	PUNCT
aiti-366	83	1	bourdev	bourdev	PROPN
aiti-366	83	2	et	et	PROPN
aiti-366	83	3	al	al	PROPN
aiti-366	83	4	.	.	PUNCT
aiti-366	84	1	[	[	X
aiti-366	84	2	22	22	NUM
aiti-366	84	3	]	]	PUNCT
aiti-366	84	4	proposed	propose	VERB
aiti-366	84	5	a	a	DET
aiti-366	84	6	new	new	ADJ
aiti-366	84	7	method	method	NOUN
aiti-366	84	8	for	for	ADP
aiti-366	84	9	detecting	detect	VERB
aiti-366	84	10	some	some	DET
aiti-366	84	11	attributes	attribute	NOUN
aiti-366	84	12	and	and	CCONJ
aiti-366	84	13	type	type	NOUN
aiti-366	84	14	of	of	ADP
aiti-366	84	15	cloths	cloth	NOUN
aiti-366	84	16	from	from	ADP
aiti-366	84	17	an	an	DET
aiti-366	84	18	input	input	NOUN
aiti-366	84	19	image	image	NOUN
aiti-366	84	20	.	.	PUNCT
aiti-366	85	1	here	here	ADV
aiti-366	85	2	attributes	attribute	NOUN
aiti-366	85	3	are	be	AUX
aiti-366	85	4	gender	gender	NOUN
aiti-366	85	5	,	,	PUNCT
aiti-366	85	6	hair	hair	NOUN
aiti-366	85	7	style	style	NOUN
aiti-366	85	8	and	and	CCONJ
aiti-366	85	9	types	type	NOUN
aiti-366	85	10	of	of	ADP
aiti-366	85	11	clothes	clothe	NOUN
aiti-366	85	12	such	such	ADJ
aiti-366	85	13	as	as	ADP
aiti-366	85	14	t	t	NOUN
aiti-366	85	15	-	-	PUNCT
aiti-366	85	16	shirts	shirt	NOUN
aiti-366	85	17	,	,	PUNCT
aiti-366	85	18	pants	pant	NOUN
aiti-366	85	19	,	,	PUNCT
aiti-366	85	20	jeans	jean	NOUN
aiti-366	85	21	,	,	PUNCT
aiti-366	85	22	and	and	CCONJ
aiti-366	85	23	shorts	short	NOUN
aiti-366	85	24	etc	etc	X
aiti-366	85	25	.	.	X
aiti-366	86	1	for	for	ADP
aiti-366	86	2	this	this	DET
aiti-366	86	3	work	work	NOUN
aiti-366	86	4	,	,	PUNCT
aiti-366	86	5	they	they	PRON
aiti-366	86	6	created	create	VERB
aiti-366	86	7	a	a	DET
aiti-366	86	8	dataset	dataset	NOUN
aiti-366	86	9	consisting	consist	VERB
aiti-366	86	10	of	of	ADP
aiti-366	86	11	8000	8000	NUM
aiti-366	86	12	people	people	NOUN
aiti-366	86	13	images	image	NOUN
aiti-366	86	14	with	with	ADP
aiti-366	86	15	annotation	annotation	NOUN
aiti-366	86	16	.	.	PUNCT
aiti-366	87	1	2.2	2.2	NUM
aiti-366	87	2	.	.	PUNCT
aiti-366	87	3	texture	texture	NOUN
aiti-366	87	4	based	base	VERB
aiti-366	87	5	classification	classification	NOUN
aiti-366	87	6	nowadays	nowadays	ADV
aiti-366	87	7	,	,	PUNCT
aiti-366	87	8	garments	garment	NOUN
aiti-366	87	9	design	design	NOUN
aiti-366	87	10	classification	classification	NOUN
aiti-366	87	11	based	base	VERB
aiti-366	87	12	on	on	ADP
aiti-366	87	13	texture	texture	NOUN
aiti-366	87	14	has	have	AUX
aiti-366	87	15	become	become	VERB
aiti-366	87	16	more	more	ADV
aiti-366	87	17	popular	popular	ADJ
aiti-366	87	18	and	and	CCONJ
aiti-366	87	19	there	there	PRON
aiti-366	87	20	are	be	VERB
aiti-366	87	21	several	several	ADJ
aiti-366	87	22	existing	exist	VERB
aiti-366	87	23	well	well	ADV
aiti-366	87	24	known	know	VERB
aiti-366	87	25	methods	method	NOUN
aiti-366	87	26	such	such	ADJ
aiti-366	87	27	as	as	ADP
aiti-366	87	28	histogram	histogram	NOUN
aiti-366	87	29	of	of	ADP
aiti-366	87	30	oriented	orient	VERB
aiti-366	87	31	gradients	gradient	NOUN
aiti-366	87	32	(	(	PUNCT
aiti-366	87	33	hog	hog	PROPN
aiti-366	87	34	)	)	PUNCT
aiti-366	87	35	,	,	PUNCT
aiti-366	87	36	local	local	ADJ
aiti-366	87	37	binary	binary	ADJ
aiti-366	87	38	pattern	pattern	NOUN
aiti-366	87	39	(	(	PUNCT
aiti-366	87	40	lbp	lbp	PROPN
aiti-366	87	41	)	)	PUNCT
aiti-366	87	42	,	,	PUNCT
aiti-366	87	43	features	feature	VERB
aiti-366	87	44	wavelets	wavelet	NOUN
aiti-366	87	45	transform	transform	VERB
aiti-366	87	46	,	,	PUNCT
aiti-366	87	47	noise	noise	VERB
aiti-366	87	48	adaptive	adaptive	ADJ
aiti-366	87	49	binary	binary	ADJ
aiti-366	87	50	pattern	pattern	NOUN
aiti-366	87	51	(	(	PUNCT
aiti-366	87	52	nabp	nabp	PROPN
aiti-366	87	53	)	)	PUNCT
aiti-366	87	54	,	,	PUNCT
aiti-366	87	55	gabor	gabor	PROPN
aiti-366	87	56	filters	filter	NOUN
aiti-366	87	57	,	,	PUNCT
aiti-366	87	58	scale	scale	NOUN
aiti-366	87	59	-	-	PUNCT
aiti-366	87	60	invariant	invariant	ADJ
aiti-366	87	61	feature	feature	NOUN
aiti-366	87	62	transform	transform	NOUN
aiti-366	87	63	(	(	PUNCT
aiti-366	87	64	sift	sift	NOUN
aiti-366	87	65	)	)	PUNCT
aiti-366	87	66	etc	etc	X
aiti-366	87	67	.	.	X
aiti-366	87	68	recently	recently	ADV
aiti-366	87	69	,	,	PUNCT
aiti-366	87	70	lbp	lbp	PROPN
aiti-366	87	71	has	have	AUX
aiti-366	87	72	become	become	VERB
aiti-366	87	73	popular	popular	ADJ
aiti-366	87	74	because	because	SCONJ
aiti-366	87	75	of	of	ADP
aiti-366	87	76	its	its	PRON
aiti-366	87	77	computational	computational	ADJ
aiti-366	87	78	simplicity	simplicity	NOUN
aiti-366	87	79	.	.	PUNCT
aiti-366	88	1	lbp	lbp	PROPN
aiti-366	88	2	was	be	AUX
aiti-366	88	3	proposed	propose	VERB
aiti-366	88	4	for	for	ADP
aiti-366	88	5	describing	describe	VERB
aiti-366	88	6	the	the	DET
aiti-366	88	7	local	local	ADJ
aiti-366	88	8	structure	structure	NOUN
aiti-366	88	9	of	of	ADP
aiti-366	88	10	an	an	DET
aiti-366	88	11	image	image	NOUN
aiti-366	88	12	and	and	CCONJ
aiti-366	88	13	it	it	PRON
aiti-366	88	14	has	have	AUX
aiti-366	88	15	been	be	AUX
aiti-366	88	16	used	use	VERB
aiti-366	88	17	in	in	ADP
aiti-366	88	18	several	several	ADJ
aiti-366	88	19	areas	area	NOUN
aiti-366	88	20	such	such	ADJ
aiti-366	88	21	as	as	ADP
aiti-366	88	22	facial	facial	ADJ
aiti-366	88	23	image	image	NOUN
aiti-366	88	24	analysis	analysis	NOUN
aiti-366	88	25	,	,	PUNCT
aiti-366	88	26	including	include	VERB
aiti-366	88	27	face	face	NOUN
aiti-366	88	28	detection	detection	NOUN
aiti-366	88	29	,	,	PUNCT
aiti-366	88	30	face	face	NOUN
aiti-366	88	31	recognition	recognition	NOUN
aiti-366	88	32	and	and	CCONJ
aiti-366	88	33	facial	facial	ADJ
aiti-366	88	34	expression	expression	NOUN
aiti-366	88	35	analysis	analysis	NOUN
aiti-366	88	36	,	,	PUNCT
aiti-366	88	37	demographic	demographic	ADJ
aiti-366	88	38	(	(	PUNCT
aiti-366	88	39	gender	gender	NOUN
aiti-366	88	40	,	,	PUNCT
aiti-366	88	41	race	race	NOUN
aiti-366	88	42	,	,	PUNCT
aiti-366	88	43	age	age	NOUN
aiti-366	88	44	,	,	PUNCT
aiti-366	88	45	etc	etc	X
aiti-366	88	46	.	.	X
aiti-366	88	47	)	)	PUNCT
aiti-366	89	1	classification	classification	NOUN
aiti-366	89	2	,	,	PUNCT
aiti-366	89	3	moving	move	VERB
aiti-366	89	4	object	object	NOUN
aiti-366	89	5	detection	detection	NOUN
aiti-366	89	6	,	,	PUNCT
aiti-366	89	7	etc	etc	X
aiti-366	89	8	.	.	X
aiti-366	90	1	however	however	ADV
aiti-366	90	2	,	,	PUNCT
aiti-366	90	3	lbp	lbp	PROPN
aiti-366	90	4	is	be	AUX
aiti-366	90	5	very	very	ADV
aiti-366	90	6	sensitive	sensitive	ADJ
aiti-366	90	7	in	in	ADP
aiti-366	90	8	uniform	uniform	NOUN
aiti-366	90	9	and	and	CCONJ
aiti-366	90	10	near	near	ADP
aiti-366	90	11	uniform	uniform	ADJ
aiti-366	90	12	regions	region	NOUN
aiti-366	90	13	.	.	PUNCT
aiti-366	91	1	in	in	ADP
aiti-366	91	2	the	the	DET
aiti-366	91	3	last	last	ADJ
aiti-366	91	4	few	few	ADJ
aiti-366	91	5	years	year	NOUN
aiti-366	91	6	,	,	PUNCT
aiti-366	91	7	lots	lot	NOUN
aiti-366	91	8	of	of	ADP
aiti-366	91	9	researches	research	NOUN
aiti-366	91	10	have	have	AUX
aiti-366	91	11	been	be	AUX
aiti-366	91	12	done	do	VERB
aiti-366	91	13	by	by	ADP
aiti-366	91	14	modification	modification	NOUN
aiti-366	91	15	of	of	ADP
aiti-366	91	16	lbp	lbp	NOUN
aiti-366	91	17	to	to	PART
aiti-366	91	18	improve	improve	VERB
aiti-366	91	19	the	the	DET
aiti-366	91	20	performance	performance	NOUN
aiti-366	91	21	.	.	PUNCT
aiti-366	92	1	such	such	ADJ
aiti-366	92	2	as	as	ADP
aiti-366	92	3	derivative	derivative	NOUN
aiti-366	92	4	-	-	PUNCT
aiti-366	92	5	based	base	VERB
aiti-366	92	6	lbp	lbp	NOUN
aiti-366	92	7	,	,	PUNCT
aiti-366	92	8	dominant	dominant	PROPN
aiti-366	92	9	lbp	lbp	PROPN
aiti-366	92	10	,	,	PUNCT
aiti-366	92	11	rotation	rotation	NOUN
aiti-366	92	12	invariant	invariant	ADJ
aiti-366	92	13	,	,	PUNCT
aiti-366	92	14	center	center	ADJ
aiti-366	92	15	-	-	PUNCT
aiti-366	92	16	symmetric	symmetric	ADJ
aiti-366	92	17	lbp	lbp	NOUN
aiti-366	92	18	,	,	PUNCT
aiti-366	92	19	etc	etc	X
aiti-366	92	20	.	.	X
aiti-366	92	21	tan	tan	PROPN
aiti-366	92	22	and	and	CCONJ
aiti-366	92	23	triggs	triggs	PROPN
aiti-366	93	1	[	[	X
aiti-366	93	2	4	4	X
aiti-366	93	3	]	]	PUNCT
aiti-366	93	4	proposed	propose	VERB
aiti-366	93	5	a	a	DET
aiti-366	93	6	new	new	ADJ
aiti-366	93	7	texture	texture	NOUN
aiti-366	93	8	based	base	VERB
aiti-366	93	9	method	method	NOUN
aiti-366	93	10	local	local	ADJ
aiti-366	93	11	ternary	ternary	ADJ
aiti-366	93	12	patterns	pattern	NOUN
aiti-366	93	13	(	(	PUNCT
aiti-366	93	14	ltp	ltp	NOUN
aiti-366	93	15	)	)	PUNCT
aiti-366	93	16	,	,	PUNCT
aiti-366	93	17	which	which	PRON
aiti-366	93	18	can	can	AUX
aiti-366	93	19	tolerate	tolerate	VERB
aiti-366	93	20	noises	noise	NOUN
aiti-366	93	21	up	up	ADP
aiti-366	93	22	to	to	ADP
aiti-366	93	23	a	a	DET
aiti-366	93	24	certain	certain	ADJ
aiti-366	93	25	level	level	NOUN
aiti-366	93	26	.	.	PUNCT
aiti-366	94	1	they	they	PRON
aiti-366	94	2	used	use	VERB
aiti-366	94	3	a	a	DET
aiti-366	94	4	fixed	fix	VERB
aiti-366	94	5	threshold	threshold	NOUN
aiti-366	94	6	(	(	PUNCT
aiti-366	94	7	±5	±5	NOUN
aiti-366	94	8	)	)	PUNCT
aiti-366	94	9	,	,	PUNCT
aiti-366	94	10	for	for	ADP
aiti-366	94	11	making	make	VERB
aiti-366	94	12	ltp	ltp	PROPN
aiti-366	94	13	more	more	ADJ
aiti-366	94	14	discriminant	discriminant	NOUN
aiti-366	94	15	and	and	CCONJ
aiti-366	94	16	less	less	ADV
aiti-366	94	17	sensitive	sensitive	ADJ
aiti-366	94	18	to	to	PART
aiti-366	94	19	noise	noise	VERB
aiti-366	94	20	in	in	ADP
aiti-366	94	21	a	a	DET
aiti-366	94	22	uniform	uniform	ADJ
aiti-366	94	23	region	region	NOUN
aiti-366	94	24	.	.	PUNCT
aiti-366	95	1	there	there	PRON
aiti-366	95	2	are	be	VERB
aiti-366	95	3	also	also	ADV
aiti-366	95	4	several	several	ADJ
aiti-366	95	5	other	other	ADJ
aiti-366	95	6	methods	method	NOUN
aiti-366	95	7	that	that	PRON
aiti-366	95	8	can	can	AUX
aiti-366	95	9	handle	handle	VERB
aiti-366	95	10	noises	noise	NOUN
aiti-366	95	11	in	in	ADP
aiti-366	95	12	different	different	ADJ
aiti-366	95	13	application	application	NOUN
aiti-366	95	14	areas	area	NOUN
aiti-366	95	15	,	,	PUNCT
aiti-366	95	16	such	such	ADJ
aiti-366	95	17	as	as	ADP
aiti-366	95	18	the	the	DET
aiti-366	95	19	methods	method	NOUN
aiti-366	95	20	described	describe	VERB
aiti-366	95	21	by	by	ADP
aiti-366	95	22	jun	jun	PROPN
aiti-366	95	23	et	et	PROPN
aiti-366	95	24	al	al	PROPN
aiti-366	95	25	.	.	PUNCT
aiti-366	96	1	[	[	X
aiti-366	96	2	25	25	NUM
aiti-366	96	3	]	]	PUNCT
aiti-366	96	4	.	.	PUNCT
aiti-366	97	1	they	they	PRON
aiti-366	97	2	proposed	propose	VERB
aiti-366	97	3	local	local	ADJ
aiti-366	97	4	gradient	gradient	NOUN
aiti-366	97	5	pattern	pattern	NOUN
aiti-366	97	6	(	(	PUNCT
aiti-366	97	7	lgp	lgp	NOUN
aiti-366	97	8	)	)	PUNCT
aiti-366	97	9	for	for	ADP
aiti-366	97	10	texture	texture	NOUN
aiti-366	97	11	based	base	VERB
aiti-366	97	12	face	face	NOUN
aiti-366	97	13	detection	detection	NOUN
aiti-366	97	14	.	.	PUNCT
aiti-366	98	1	this	this	DET
aiti-366	98	2	method	method	NOUN
aiti-366	98	3	is	be	AUX
aiti-366	98	4	a	a	DET
aiti-366	98	5	variant	variant	NOUN
aiti-366	98	6	of	of	ADP
aiti-366	98	7	lbp	lbp	NOUN
aiti-366	98	8	and	and	CCONJ
aiti-366	98	9	uses	use	VERB
aiti-366	98	10	adaptive	adaptive	ADJ
aiti-366	98	11	threshold	threshold	NOUN
aiti-366	98	12	for	for	ADP
aiti-366	98	13	code	code	NOUN
aiti-366	98	14	generation	generation	NOUN
aiti-366	98	15	.	.	PUNCT
aiti-366	99	1	guo	guo	PROPN
aiti-366	99	2	et	et	PROPN
aiti-366	99	3	al	al	PROPN
aiti-366	99	4	.	.	PUNCT
aiti-366	100	1	[	[	X
aiti-366	100	2	5	5	NUM
aiti-366	100	3	]	]	PUNCT
aiti-366	100	4	proposed	propose	VERB
aiti-366	100	5	completed	complete	VERB
aiti-366	100	6	local	local	ADJ
aiti-366	100	7	binary	binary	NOUN
aiti-366	100	8	pattern	pattern	NOUN
aiti-366	100	9	(	(	PUNCT
aiti-366	100	10	clbp	clbp	PROPN
aiti-366	100	11	)	)	PUNCT
aiti-366	100	12	,	,	PUNCT
aiti-366	100	13	which	which	PRON
aiti-366	100	14	incorporates	incorporate	VERB
aiti-366	100	15	sign	sign	NOUN
aiti-366	100	16	,	,	PUNCT
aiti-366	100	17	magnitude	magnitude	NOUN
aiti-366	100	18	and	and	CCONJ
aiti-366	100	19	center	center	ADJ
aiti-366	100	20	pixel	pixel	PROPN
aiti-366	100	21	information	information	NOUN
aiti-366	100	22	.	.	PUNCT
aiti-366	101	1	this	this	DET
aiti-366	101	2	method	method	NOUN
aiti-366	101	3	is	be	AUX
aiti-366	101	4	rotation	rotation	NOUN
aiti-366	101	5	invariant	invariant	ADJ
aiti-366	101	6	and	and	CCONJ
aiti-366	101	7	capable	capable	ADJ
aiti-366	101	8	of	of	ADP
aiti-366	101	9	handling	handle	VERB
aiti-366	101	10	the	the	DET
aiti-366	101	11	fluctuation	fluctuation	NOUN
aiti-366	101	12	of	of	ADP
aiti-366	101	13	intensity	intensity	NOUN
aiti-366	101	14	.	.	PUNCT
aiti-366	102	1	wu	wu	PROPN
aiti-366	102	2	et	et	PROPN
aiti-366	102	3	al	al	PROPN
aiti-366	102	4	.	.	PUNCT
aiti-366	103	1	[	[	X
aiti-366	103	2	1	1	X
aiti-366	103	3	]	]	PUNCT
aiti-366	103	4	proposed	propose	VERB
aiti-366	103	5	census	census	NOUN
aiti-366	103	6	transform	transform	NOUN
aiti-366	103	7	histogram	histogram	NOUN
aiti-366	103	8	(	(	PUNCT
aiti-366	103	9	centrist	centrist	NOUN
aiti-366	103	10	)	)	PUNCT
aiti-366	103	11	which	which	PRON
aiti-366	103	12	is	be	AUX
aiti-366	103	13	very	very	ADV
aiti-366	103	14	similar	similar	ADJ
aiti-366	103	15	to	to	ADP
aiti-366	103	16	lbp	lbp	NOUN
aiti-366	103	17	and	and	CCONJ
aiti-366	103	18	mainly	mainly	ADV
aiti-366	103	19	work	work	VERB
aiti-366	103	20	as	as	ADP
aiti-366	103	21	a	a	DET
aiti-366	103	22	visual	visual	ADJ
aiti-366	103	23	descriptor	descriptor	NOUN
aiti-366	103	24	for	for	ADP
aiti-366	103	25	recognizing	recognize	VERB
aiti-366	103	26	scene	scene	NOUN
aiti-366	103	27	categories	category	NOUN
aiti-366	103	28	.	.	PUNCT
aiti-366	104	1	centrist	centrist	NOUN
aiti-366	104	2	proposes	propose	VERB
aiti-366	104	3	a	a	DET
aiti-366	104	4	spatial	spatial	ADJ
aiti-366	104	5	representation	representation	NOUN
aiti-366	104	6	based	base	VERB
aiti-366	104	7	on	on	ADP
aiti-366	104	8	a	a	DET
aiti-366	104	9	spatial	spatial	ADJ
aiti-366	104	10	pyramid	pyramid	NOUN
aiti-366	104	11	matching	matching	NOUN
aiti-366	104	12	scheme	scheme	NOUN
aiti-366	104	13	(	(	PUNCT
aiti-366	104	14	spm	spm	PROPN
aiti-366	104	15	)	)	PUNCT
aiti-366	105	1	[	[	X
aiti-366	105	2	26	26	NUM
aiti-366	105	3	]	]	PUNCT
aiti-366	105	4	to	to	PART
aiti-366	105	5	capture	capture	VERB
aiti-366	105	6	global	global	ADJ
aiti-366	105	7	structure	structure	NOUN
aiti-366	105	8	from	from	ADP
aiti-366	105	9	images	image	NOUN
aiti-366	105	10	.	.	PUNCT
aiti-366	106	1	centrist	centrist	NOUN
aiti-366	106	2	uses	uses	AUX
aiti-366	106	3	total	total	ADJ
aiti-366	106	4	31	31	NUM
aiti-366	106	5	blocks	block	NOUN
aiti-366	106	6	to	to	PART
aiti-366	106	7	avoid	avoid	VERB
aiti-366	106	8	the	the	DET
aiti-366	106	9	artefacts	artefact	NOUN
aiti-366	106	10	.	.	PUNCT
aiti-366	107	1	dey	dey	PROPN
aiti-366	107	2	et	et	PROPN
aiti-366	107	3	al	al	PROPN
aiti-366	107	4	.	.	PUNCT
aiti-366	108	1	[	[	X
aiti-366	108	2	6	6	NUM
aiti-366	108	3	]	]	PUNCT
aiti-366	108	4	proposed	propose	VERB
aiti-366	108	5	two	two	NUM
aiti-366	108	6	new	new	ADJ
aiti-366	108	7	descriptors	descriptor	NOUN
aiti-366	108	8	for	for	ADP
aiti-366	108	9	garments	garment	NOUN
aiti-366	108	10	design	design	NOUN
aiti-366	108	11	class	class	NOUN
aiti-366	108	12	identification	identification	NOUN
aiti-366	108	13	namely	namely	ADV
aiti-366	108	14	completed	complete	VERB
aiti-366	108	15	centrist	centrist	NOUN
aiti-366	108	16	(	(	PUNCT
aiti-366	108	17	ccentrist	ccentrist	NOUN
aiti-366	108	18	)	)	PUNCT
aiti-366	108	19	and	and	CCONJ
aiti-366	108	20	ternary	ternary	ADJ
aiti-366	108	21	centrist	centrist	NOUN
aiti-366	108	22	(	(	PUNCT
aiti-366	108	23	tcentrist	tcentrist	NOUN
aiti-366	108	24	)	)	PUNCT
aiti-366	108	25	.	.	PUNCT
aiti-366	109	1	these	these	DET
aiti-366	109	2	descriptors	descriptor	NOUN
aiti-366	109	3	are	be	AUX
aiti-366	109	4	based	base	VERB
aiti-366	109	5	on	on	ADP
aiti-366	109	6	completed	complete	VERB
aiti-366	109	7	local	local	ADJ
aiti-366	109	8	binary	binary	ADJ
aiti-366	109	9	pattern	pattern	NOUN
aiti-366	109	10	(	(	PUNCT
aiti-366	109	11	clbp	clbp	PROPN
aiti-366	109	12	)	)	PUNCT
aiti-366	109	13	,	,	PUNCT
aiti-366	109	14	local	local	ADJ
aiti-366	109	15	ternary	ternary	ADJ
aiti-366	109	16	pattern	pattern	NOUN
aiti-366	109	17	(	(	PUNCT
aiti-366	109	18	ltp	ltp	NOUN
aiti-366	109	19	)	)	PUNCT
aiti-366	109	20	and	and	CCONJ
aiti-366	109	21	census	census	NOUN
aiti-366	109	22	tranformed	tranforme	VERB
aiti-366	109	23	histogram	histogram	NOUN
aiti-366	109	24	(	(	PUNCT
aiti-366	109	25	centrist	centrist	NOUN
aiti-366	109	26	)	)	PUNCT
aiti-366	109	27	.	.	PUNCT
aiti-366	110	1	authors	author	NOUN
aiti-366	110	2	applied	apply	VERB
aiti-366	110	3	these	these	DET
aiti-366	110	4	two	two	NUM
aiti-366	110	5	descriptors	descriptor	NOUN
aiti-366	110	6	on	on	ADP
aiti-366	110	7	two	two	NUM
aiti-366	110	8	different	different	ADJ
aiti-366	110	9	publically	publically	ADV
aiti-366	110	10	available	available	ADJ
aiti-366	110	11	databases	database	NOUN
aiti-366	110	12	and	and	CCONJ
aiti-366	110	13	achieve	achieve	VERB
aiti-366	110	14	nearly	nearly	ADV
aiti-366	110	15	about	about	ADP
aiti-366	110	16	3	3	NUM
aiti-366	110	17	%	%	NOUN
aiti-366	110	18	more	more	ADJ
aiti-366	110	19	accuracy	accuracy	NOUN
aiti-366	110	20	than	than	ADP
aiti-366	110	21	the	the	DET
aiti-366	110	22	existing	exist	VERB
aiti-366	110	23	state	state	NOUN
aiti-366	110	24	-	-	PUNCT
aiti-366	110	25	of	of	ADP
aiti-366	110	26	-	-	PUNCT
aiti-366	110	27	the	the	DET
aiti-366	110	28	art	art	NOUN
aiti-366	110	29	methods	method	NOUN
aiti-366	110	30	.	.	PUNCT
aiti-366	111	1	2.3	2.3	NUM
aiti-366	111	2	.	.	PUNCT
aiti-366	112	1	deep	deep	ADJ
aiti-366	112	2	learning	learn	VERB
aiti-366	112	3	this	this	DET
aiti-366	112	4	sub	sub	NOUN
aiti-366	112	5	-	-	NOUN
aiti-366	112	6	section	section	NOUN
aiti-366	112	7	,	,	PUNCT
aiti-366	112	8	will	will	AUX
aiti-366	112	9	describe	describe	VERB
aiti-366	112	10	some	some	DET
aiti-366	112	11	deep	deep	ADJ
aiti-366	112	12	learning	learning	NOUN
aiti-366	112	13	techniques	technique	NOUN
aiti-366	112	14	for	for	ADP
aiti-366	112	15	garments	garment	NOUN
aiti-366	112	16	design	design	NOUN
aiti-366	112	17	classification	classification	NOUN
aiti-366	112	18	.	.	PUNCT
aiti-366	113	1	deep	deep	ADJ
aiti-366	113	2	network	network	NOUN
aiti-366	113	3	learn	learn	VERB
aiti-366	113	4	features	feature	NOUN
aiti-366	113	5	automatically	automatically	ADV
aiti-366	113	6	from	from	ADP
aiti-366	113	7	large	large	ADJ
aiti-366	113	8	number	number	NOUN
aiti-366	113	9	of	of	ADP
aiti-366	113	10	unlabelled	unlabelled	ADJ
aiti-366	113	11	data	datum	NOUN
aiti-366	113	12	,	,	PUNCT
aiti-366	113	13	hence	hence	ADV
aiti-366	113	14	more	more	ADV
aiti-366	113	15	useful	useful	ADJ
aiti-366	113	16	hidden	hide	VERB
aiti-366	113	17	discriminative	discriminative	NOUN
aiti-366	113	18	features	feature	NOUN
aiti-366	113	19	are	be	AUX
aiti-366	113	20	extracted	extract	VERB
aiti-366	113	21	.	.	PUNCT
aiti-366	114	1	it	it	PRON
aiti-366	114	2	has	have	AUX
aiti-366	114	3	achieved	achieve	VERB
aiti-366	114	4	popularity	popularity	NOUN
aiti-366	114	5	in	in	ADP
aiti-366	114	6	classic	classic	ADJ
aiti-366	114	7	problems	problem	NOUN
aiti-366	114	8	,	,	PUNCT
aiti-366	114	9	such	such	ADJ
aiti-366	114	10	as	as	ADP
aiti-366	114	11	speech	speech	NOUN
aiti-366	114	12	recognition	recognition	NOUN
aiti-366	114	13	,	,	PUNCT
aiti-366	114	14	object	object	NOUN
aiti-366	114	15	recognition	recognition	NOUN
aiti-366	114	16	and	and	CCONJ
aiti-366	114	17	detection	detection	NOUN
aiti-366	114	18	,	,	PUNCT
aiti-366	114	19	natural	natural	ADJ
aiti-366	114	20	language	language	NOUN
aiti-366	114	21	processing	processing	NOUN
aiti-366	114	22	,	,	PUNCT
aiti-366	114	23	etc	etc	X
aiti-366	114	24	.	.	X
aiti-366	114	25	convolutional	convolutional	ADJ
aiti-366	114	26	neural	neural	ADJ
aiti-366	114	27	networks	network	NOUN
aiti-366	114	28	(	(	PUNCT
aiti-366	114	29	cnn	cnn	PROPN
aiti-366	114	30	)	)	PUNCT
aiti-366	114	31	is	be	AUX
aiti-366	114	32	now	now	ADV
aiti-366	114	33	being	be	AUX
aiti-366	114	34	used	use	VERB
aiti-366	114	35	in	in	ADP
aiti-366	114	36	several	several	ADJ
aiti-366	114	37	image	image	NOUN
aiti-366	114	38	,	,	PUNCT
aiti-366	114	39	pattern	pattern	NOUN
aiti-366	114	40	and	and	CCONJ
aiti-366	114	41	signal	signal	ADJ
aiti-366	114	42	processing	processing	NOUN
aiti-366	114	43	researches	research	NOUN
aiti-366	114	44	.	.	PUNCT
aiti-366	115	1	liu	liu	PROPN
aiti-366	115	2	et	et	PROPN
aiti-366	115	3	al	al	PROPN
aiti-366	115	4	.	.	PUNCT
aiti-366	116	1	[	[	X
aiti-366	116	2	33	33	NUM
aiti-366	116	3	]	]	PUNCT
aiti-366	116	4	introduced	introduce	VERB
aiti-366	116	5	au	au	ADJ
aiti-366	116	6	-	-	ADJ
aiti-366	116	7	aware	aware	ADJ
aiti-366	116	8	deep	deep	ADJ
aiti-366	116	9	networks	network	NOUN
aiti-366	116	10	(	(	PUNCT
aiti-366	116	11	audn	audn	NOUN
aiti-366	116	12	)	)	PUNCT
aiti-366	116	13	by	by	ADP
aiti-366	116	14	constructing	construct	VERB
aiti-366	116	15	a	a	DET
aiti-366	116	16	deep	deep	ADJ
aiti-366	116	17	architecture	architecture	NOUN
aiti-366	116	18	for	for	ADP
aiti-366	116	19	facial	facial	ADJ
aiti-366	116	20	expression	expression	NOUN
aiti-366	116	21	recognition	recognition	NOUN
aiti-366	116	22	.	.	PUNCT
aiti-366	117	1	for	for	ADP
aiti-366	117	2	extracting	extract	VERB
aiti-366	117	3	high	high	ADJ
aiti-366	117	4	level	level	NOUN
aiti-366	117	5	features	feature	NOUN
aiti-366	117	6	from	from	ADP
aiti-366	117	7	each	each	DET
aiti-366	117	8	au	au	ADJ
aiti-366	117	9	-	-	ADJ
aiti-366	117	10	aware	aware	ADJ
aiti-366	117	11	receptive	receptive	ADJ
aiti-366	117	12	fields	field	NOUN
aiti-366	117	13	(	(	PUNCT
aiti-366	117	14	aurf	aurf	NOUN
aiti-366	117	15	)	)	PUNCT
aiti-366	117	16	,	,	PUNCT
aiti-366	117	17	they	they	PRON
aiti-366	117	18	used	use	VERB
aiti-366	117	19	restricted	restrict	VERB
aiti-366	117	20	boltzmann	boltzmann	PROPN
aiti-366	117	21	machine	machine	NOUN
aiti-366	117	22	(	(	PUNCT
aiti-366	117	23	rbms	rbms	ADV
aiti-366	117	24	)	)	PUNCT
aiti-366	117	25	.	.	PUNCT
aiti-366	118	1	later	later	ADV
aiti-366	118	2	,	,	PUNCT
aiti-366	118	3	this	this	DET
aiti-366	118	4	technique	technique	NOUN
aiti-366	118	5	was	be	AUX
aiti-366	118	6	applied	apply	VERB
aiti-366	118	7	on	on	ADP
aiti-366	118	8	three	three	NUM
aiti-366	118	9	expression	expression	NOUN
aiti-366	118	10	database	database	NOUN
aiti-366	118	11	namely	namely	ADV
aiti-366	118	12	ck+	ck+	NOUN
aiti-366	118	13	,	,	PUNCT
aiti-366	118	14	mmi	mmi	NOUN
aiti-366	118	15	and	and	CCONJ
aiti-366	118	16	sfew	sfew	NOUN
aiti-366	118	17	.	.	PUNCT
aiti-366	119	1	results	result	NOUN
aiti-366	119	2	achieved	achieve	VERB
aiti-366	119	3	from	from	ADP
aiti-366	119	4	this	this	DET
aiti-366	119	5	technique	technique	NOUN
aiti-366	119	6	were	be	AUX
aiti-366	119	7	better	well	ADJ
aiti-366	119	8	or	or	CCONJ
aiti-366	119	9	at	at	ADP
aiti-366	119	10	least	least	ADJ
aiti-366	119	11	competitive	competitive	ADJ
aiti-366	119	12	.	.	PUNCT
aiti-366	120	1	however	however	ADV
aiti-366	120	2	,	,	PUNCT
aiti-366	120	3	this	this	DET
aiti-366	120	4	method	method	NOUN
aiti-366	120	5	fails	fail	VERB
aiti-366	120	6	when	when	SCONJ
aiti-366	120	7	several	several	ADJ
aiti-366	120	8	kinds	kind	NOUN
aiti-366	120	9	of	of	ADP
aiti-366	120	10	challenging	challenge	VERB
aiti-366	120	11	images	image	NOUN
aiti-366	120	12	(	(	PUNCT
aiti-366	120	13	e.g.	e.g.	ADV
aiti-366	120	14	,	,	PUNCT
aiti-366	120	15	the	the	DET
aiti-366	120	16	subjects	subject	NOUN
aiti-366	120	17	have	have	VERB
aiti-366	120	18	higher	high	ADJ
aiti-366	120	19	expression	expression	NOUN
aiti-366	120	20	non	non	NOUN
aiti-366	120	21	-	-	NOUN
aiti-366	120	22	uniformity	uniformity	NOUN
aiti-366	120	23	,	,	PUNCT
aiti-366	120	24	most	most	ADJ
aiti-366	120	25	of	of	ADP
aiti-366	120	26	them	they	PRON
aiti-366	120	27	have	have	VERB
aiti-366	120	28	moustache	moustache	NOUN
aiti-366	120	29	and	and	CCONJ
aiti-366	120	30	wear	wear	VERB
aiti-366	120	31	accessories	accessory	NOUN
aiti-366	120	32	such	such	ADJ
aiti-366	120	33	as	as	ADP
aiti-366	120	34	glasses	glass	NOUN
aiti-366	120	35	)	)	PUNCT
aiti-366	120	36	are	be	AUX
aiti-366	120	37	appeared	appear	VERB
aiti-366	120	38	.	.	PUNCT
aiti-366	121	1	krizhevsky	krizhevsky	PROPN
aiti-366	121	2	et	et	PROPN
aiti-366	121	3	al	al	PROPN
aiti-366	121	4	.	.	PUNCT
aiti-366	122	1	[	[	X
aiti-366	122	2	7	7	X
aiti-366	122	3	]	]	PUNCT
aiti-366	122	4	proposed	propose	VERB
aiti-366	122	5	a	a	DET
aiti-366	122	6	new	new	ADJ
aiti-366	122	7	cnn	cnn	NOUN
aiti-366	122	8	architecture	architecture	NOUN
aiti-366	122	9	which	which	PRON
aiti-366	122	10	achieved	achieve	VERB
aiti-366	122	11	top-1	top-1	PUNCT
aiti-366	122	12	and	and	CCONJ
aiti-366	122	13	top-5	top-5	VERB
aiti-366	122	14	error	error	NOUN
aiti-366	122	15	rates	rate	NOUN
aiti-366	122	16	of	of	ADP
aiti-366	122	17	37.5	37.5	NUM
aiti-366	122	18	%	%	NOUN
aiti-366	122	19	and	and	CCONJ
aiti-366	122	20	17.0	17.0	NUM
aiti-366	122	21	%	%	NOUN
aiti-366	122	22	on	on	ADP
aiti-366	122	23	the	the	DET
aiti-366	122	24	test	test	NOUN
aiti-366	122	25	data	datum	NOUN
aiti-366	122	26	.	.	PUNCT
aiti-366	123	1	however	however	ADV
aiti-366	123	2	,	,	PUNCT
aiti-366	123	3	there	there	PRON
aiti-366	123	4	is	be	VERB
aiti-366	123	5	still	still	ADV
aiti-366	123	6	an	an	DET
aiti-366	123	7	open	open	ADJ
aiti-366	123	8	issue	issue	NOUN
aiti-366	123	9	that	that	SCONJ
aiti-366	123	10	,	,	PUNCT
aiti-366	123	11	if	if	SCONJ
aiti-366	123	12	a	a	DET
aiti-366	123	13	single	single	ADJ
aiti-366	123	14	convolutional	convolutional	ADJ
aiti-366	123	15	layer	layer	NOUN
aiti-366	123	16	is	be	AUX
aiti-366	123	17	removed	remove	VERB
aiti-366	123	18	,	,	PUNCT
aiti-366	123	19	network	network	NOUN
aiti-366	123	20	’s	’s	PART
aiti-366	123	21	performance	performance	NOUN
aiti-366	123	22	is	be	AUX
aiti-366	123	23	degraded	degrade	VERB
aiti-366	123	24	.	.	PUNCT
aiti-366	124	1	here	here	ADV
aiti-366	124	2	,	,	PUNCT
aiti-366	124	3	authors	author	NOUN
aiti-366	124	4	did	do	AUX
aiti-366	124	5	not	not	PART
aiti-366	124	6	use	use	VERB
aiti-366	124	7	any	any	DET
aiti-366	124	8	unsupervised	unsupervised	ADJ
aiti-366	124	9	pretraining	pretraine	VERB
aiti-366	124	10	data	datum	NOUN
aiti-366	124	11	to	to	PART
aiti-366	124	12	simplify	simplify	VERB
aiti-366	124	13	this	this	DET
aiti-366	124	14	work	work	NOUN
aiti-366	124	15	but	but	CCONJ
aiti-366	124	16	it	it	PRON
aiti-366	124	17	could	could	AUX
aiti-366	124	18	be	be	AUX
aiti-366	124	19	more	more	ADV
aiti-366	124	20	helpful	helpful	ADJ
aiti-366	124	21	if	if	SCONJ
aiti-366	124	22	the	the	DET
aiti-366	124	23	computational	computational	ADJ
aiti-366	124	24	power	power	NOUN
aiti-366	124	25	and	and	CCONJ
aiti-366	124	26	size	size	NOUN
aiti-366	124	27	of	of	ADP
aiti-366	124	28	the	the	DET
aiti-366	124	29	network	network	NOUN
aiti-366	124	30	were	be	AUX
aiti-366	124	31	increased	increase	VERB
aiti-366	124	32	.	.	PUNCT
aiti-366	125	1	dey	dey	PROPN
aiti-366	125	2	et	et	PROPN
aiti-366	125	3	al	al	PROPN
aiti-366	125	4	.	.	PUNCT
aiti-366	126	1	[	[	X
aiti-366	126	2	6	6	NUM
aiti-366	126	3	]	]	PUNCT
aiti-366	126	4	used	use	VERB
aiti-366	126	5	deep	deep	ADJ
aiti-366	126	6	learning	learning	NOUN
aiti-366	126	7	model	model	NOUN
aiti-366	126	8	in	in	ADP
aiti-366	126	9	texture	texture	NOUN
aiti-366	126	10	based	base	VERB
aiti-366	126	11	garments	garment	NOUN
aiti-366	126	12	design	design	NOUN
aiti-366	126	13	classification	classification	NOUN
aiti-366	126	14	.	.	PUNCT
aiti-366	127	1	in	in	ADP
aiti-366	127	2	their	their	PRON
aiti-366	127	3	experiment	experiment	NOUN
aiti-366	127	4	,	,	PUNCT
aiti-366	127	5	using	use	VERB
aiti-366	127	6	berkeley	berkeley	NOUN
aiti-366	127	7	-	-	PUNCT
aiti-366	127	8	trained	train	VERB
aiti-366	127	9	model	model	NOUN
aiti-366	127	10	[	[	X
aiti-366	127	11	10	10	NUM
aiti-366	127	12	]	]	PUNCT
aiti-366	127	13	,	,	PUNCT
aiti-366	127	14	they	they	PRON
aiti-366	127	15	obtained	obtain	VERB
aiti-366	127	16	advances	advance	NOUN
aiti-366	127	17	in	in	ADP
aiti-366	127	18	technology	technology	NOUN
aiti-366	127	19	innovation	innovation	NOUN
aiti-366	127	20	,	,	PUNCT
aiti-366	127	21	vol	vol	NOUN
aiti-366	127	22	.	.	PROPN
aiti-366	128	1	2	2	NUM
aiti-366	128	2	,	,	PUNCT
aiti-366	128	3	no	no	INTJ
aiti-366	128	4	.	.	NOUN
aiti-366	128	5	4	4	NUM
aiti-366	128	6	,	,	PUNCT
aiti-366	128	7	2017	2017	NUM
aiti-366	128	8	,	,	PUNCT
aiti-366	129	1	pp	pp	ADJ
aiti-366	129	2	.	.	PUNCT
aiti-366	130	1	119	119	NUM
aiti-366	130	2	125	125	NUM
aiti-366	130	3	121	121	NUM
aiti-366	130	4	copyright	copyright	NOUN
aiti-366	130	5	©	©	ADP
aiti-366	130	6	taeti	taeti	PROPN
aiti-366	130	7	73.54	73.54	NUM
aiti-366	130	8	%	%	NOUN
aiti-366	130	9	accuracy	accuracy	NOUN
aiti-366	130	10	in	in	ADP
aiti-366	130	11	clothing	clothing	NOUN
aiti-366	130	12	attribute	attribute	NOUN
aiti-366	130	13	dataset	dataset	VERB
aiti-366	130	14	.	.	PUNCT
aiti-366	131	1	however	however	ADV
aiti-366	131	2	,	,	PUNCT
aiti-366	131	3	they	they	PRON
aiti-366	131	4	claimed	claim	VERB
aiti-366	131	5	that	that	DET
aiti-366	131	6	accuracy	accuracy	NOUN
aiti-366	131	7	might	might	AUX
aiti-366	131	8	be	be	AUX
aiti-366	131	9	improved	improve	VERB
aiti-366	131	10	by	by	ADP
aiti-366	131	11	changing	change	VERB
aiti-366	131	12	layers	layer	NOUN
aiti-366	131	13	and	and	CCONJ
aiti-366	131	14	other	other	ADJ
aiti-366	131	15	related	related	ADJ
aiti-366	131	16	issues	issue	NOUN
aiti-366	131	17	.	.	PUNCT
aiti-366	132	1	zhoub	zhoub	PROPN
aiti-366	132	2	et	et	PROPN
aiti-366	132	3	al	al	PROPN
aiti-366	132	4	.	.	PUNCT
aiti-366	133	1	[	[	X
aiti-366	133	2	8	8	NUM
aiti-366	133	3	]	]	PUNCT
aiti-366	133	4	proposed	propose	VERB
aiti-366	133	5	a	a	DET
aiti-366	133	6	technique	technique	NOUN
aiti-366	133	7	which	which	PRON
aiti-366	133	8	extracted	extract	VERB
aiti-366	133	9	the	the	DET
aiti-366	133	10	difference	difference	NOUN
aiti-366	133	11	between	between	ADP
aiti-366	133	12	the	the	DET
aiti-366	133	13	density	density	NOUN
aiti-366	133	14	and	and	CCONJ
aiti-366	133	15	diversity	diversity	NOUN
aiti-366	133	16	of	of	ADP
aiti-366	133	17	image	image	NOUN
aiti-366	133	18	datasets	dataset	NOUN
aiti-366	133	19	.	.	PUNCT
aiti-366	134	1	here	here	ADV
aiti-366	134	2	,	,	PUNCT
aiti-366	134	3	authors	author	NOUN
aiti-366	134	4	used	use	VERB
aiti-366	134	5	cnn	cnn	PROPN
aiti-366	134	6	to	to	PART
aiti-366	134	7	learn	learn	VERB
aiti-366	134	8	deep	deep	ADJ
aiti-366	134	9	features	feature	NOUN
aiti-366	134	10	for	for	ADP
aiti-366	134	11	scene	scene	NOUN
aiti-366	134	12	recognition	recognition	NOUN
aiti-366	134	13	tasks	task	NOUN
aiti-366	134	14	.	.	PUNCT
aiti-366	135	1	for	for	ADP
aiti-366	135	2	their	their	PRON
aiti-366	135	3	dataset	dataset	ADJ
aiti-366	135	4	vgg	vgg	PROPN
aiti-366	135	5	s-16	s-16	PROPN
aiti-366	135	6	models	model	NOUN
aiti-366	135	7	achieved	achieve	VERB
aiti-366	135	8	88.8	88.8	NUM
aiti-366	135	9	%	%	NOUN
aiti-366	135	10	accuracy	accuracy	NOUN
aiti-366	135	11	in	in	ADP
aiti-366	135	12	top-5	top-5	PUNCT
aiti-366	135	13	val	val	NOUN
aiti-366	135	14	/	/	SYM
aiti-366	135	15	test	test	NOUN
aiti-366	135	16	.	.	PUNCT
aiti-366	136	1	however	however	ADV
aiti-366	136	2	,	,	PUNCT
aiti-366	136	3	there	there	PRON
aiti-366	136	4	exist	exist	VERB
aiti-366	136	5	some	some	DET
aiti-366	136	6	difficulties	difficulty	NOUN
aiti-366	136	7	such	such	ADJ
aiti-366	136	8	as	as	ADP
aiti-366	136	9	the	the	DET
aiti-366	136	10	variability	variability	NOUN
aiti-366	136	11	in	in	ADP
aiti-366	136	12	camera	camera	NOUN
aiti-366	136	13	poses	pose	NOUN
aiti-366	136	14	,	,	PUNCT
aiti-366	136	15	decoration	decoration	NOUN
aiti-366	136	16	styles	style	NOUN
aiti-366	136	17	or	or	CCONJ
aiti-366	136	18	the	the	DET
aiti-366	136	19	objects	object	NOUN
aiti-366	136	20	that	that	PRON
aiti-366	136	21	appear	appear	VERB
aiti-366	136	22	in	in	ADP
aiti-366	136	23	the	the	DET
aiti-366	136	24	scene	scene	NOUN
aiti-366	136	25	.	.	PUNCT
aiti-366	137	1	lao	lao	PROPN
aiti-366	137	2	et	et	PROPN
aiti-366	137	3	al	al	PROPN
aiti-366	137	4	.	.	PUNCT
aiti-366	138	1	[	[	X
aiti-366	138	2	27	27	NUM
aiti-366	138	3	]	]	PUNCT
aiti-366	138	4	used	use	VERB
aiti-366	138	5	convolutional	convolutional	ADJ
aiti-366	138	6	neural	neural	ADJ
aiti-366	138	7	network	network	NOUN
aiti-366	138	8	for	for	ADP
aiti-366	138	9	fashion	fashion	NOUN
aiti-366	138	10	class	class	NOUN
aiti-366	138	11	identification	identification	NOUN
aiti-366	138	12	.	.	PUNCT
aiti-366	139	1	authors	author	NOUN
aiti-366	139	2	divided	divide	VERB
aiti-366	139	3	their	their	PRON
aiti-366	139	4	work	work	NOUN
aiti-366	139	5	into	into	ADP
aiti-366	139	6	four	four	NUM
aiti-366	139	7	parts	part	NOUN
aiti-366	139	8	those	those	PRON
aiti-366	139	9	are	be	AUX
aiti-366	139	10	multiclass	multiclass	ADJ
aiti-366	139	11	classification	classification	NOUN
aiti-366	139	12	of	of	ADP
aiti-366	139	13	clothing	clothing	NOUN
aiti-366	139	14	type	type	NOUN
aiti-366	139	15	;	;	PUNCT
aiti-366	139	16	clothing	clothing	NOUN
aiti-366	139	17	attribute	attribute	NOUN
aiti-366	139	18	classification	classification	NOUN
aiti-366	139	19	;	;	PUNCT
aiti-366	139	20	clothing	clothing	NOUN
aiti-366	139	21	retrieval	retrieval	NOUN
aiti-366	139	22	of	of	ADP
aiti-366	139	23	nearest	near	ADJ
aiti-366	139	24	neighbours	neighbour	NOUN
aiti-366	139	25	;	;	PUNCT
aiti-366	139	26	and	and	CCONJ
aiti-366	139	27	clothing	clothing	NOUN
aiti-366	139	28	object	object	NOUN
aiti-366	139	29	detection	detection	NOUN
aiti-366	139	30	.	.	PUNCT
aiti-366	140	1	for	for	ADP
aiti-366	140	2	this	this	DET
aiti-366	140	3	work	work	NOUN
aiti-366	140	4	they	they	PRON
aiti-366	140	5	used	use	VERB
aiti-366	140	6	apparel	apparel	NOUN
aiti-366	140	7	classification	classification	NOUN
aiti-366	140	8	with	with	ADP
aiti-366	140	9	style	style	NOUN
aiti-366	140	10	(	(	PUNCT
aiti-366	140	11	acs	acs	PROPN
aiti-366	140	12	)	)	PUNCT
aiti-366	140	13	,	,	PUNCT
aiti-366	140	14	clothing	clothing	NOUN
aiti-366	140	15	attribute	attribute	NOUN
aiti-366	140	16	(	(	PUNCT
aiti-366	140	17	ca	ca	NOUN
aiti-366	140	18	)	)	PUNCT
aiti-366	140	19	and	and	CCONJ
aiti-366	140	20	colourful	colourful	ADJ
aiti-366	140	21	-	-	PUNCT
aiti-366	140	22	fashion	fashion	NOUN
aiti-366	140	23	(	(	PUNCT
aiti-366	140	24	cf	cf	NOUN
aiti-366	140	25	)	)	PUNCT
aiti-366	140	26	datasets	dataset	NOUN
aiti-366	140	27	and	and	CCONJ
aiti-366	140	28	found	find	VERB
aiti-366	140	29	50.2	50.2	NUM
aiti-366	140	30	%	%	NOUN
aiti-366	140	31	and	and	CCONJ
aiti-366	140	32	74.5	74.5	NUM
aiti-366	140	33	%	%	NOUN
aiti-366	140	34	accuracy	accuracy	NOUN
aiti-366	140	35	for	for	ADP
aiti-366	140	36	clothing	clothing	NOUN
aiti-366	140	37	style	style	NOUN
aiti-366	140	38	classification	classification	NOUN
aiti-366	140	39	and	and	CCONJ
aiti-366	140	40	clothing	clothing	NOUN
aiti-366	140	41	attribute	attribute	NOUN
aiti-366	140	42	datasets	dataset	NOUN
aiti-366	140	43	.	.	PUNCT
aiti-366	141	1	hu	hu	PROPN
aiti-366	141	2	et	et	PROPN
aiti-366	141	3	al	al	PROPN
aiti-366	141	4	.	.	PUNCT
aiti-366	142	1	[	[	X
aiti-366	142	2	28	28	NUM
aiti-366	142	3	]	]	X
aiti-366	142	4	used	use	VERB
aiti-366	142	5	deep	deep	ADJ
aiti-366	142	6	convolutional	convolutional	ADJ
aiti-366	142	7	neural	neural	ADJ
aiti-366	142	8	networks	network	NOUN
aiti-366	142	9	for	for	ADP
aiti-366	142	10	high	high	ADJ
aiti-366	142	11	-	-	PUNCT
aiti-366	142	12	resolution	resolution	NOUN
aiti-366	142	13	remote	remote	ADJ
aiti-366	142	14	sensing	sensing	NOUN
aiti-366	142	15	(	(	PUNCT
aiti-366	142	16	hrrs	hrrs	ADJ
aiti-366	142	17	)	)	PUNCT
aiti-366	142	18	scene	scene	NOUN
aiti-366	142	19	classification	classification	NOUN
aiti-366	142	20	.	.	PUNCT
aiti-366	143	1	for	for	ADP
aiti-366	143	2	this	this	DET
aiti-366	143	3	work	work	NOUN
aiti-366	143	4	,	,	PUNCT
aiti-366	143	5	they	they	PRON
aiti-366	143	6	proposed	propose	VERB
aiti-366	143	7	two	two	NUM
aiti-366	143	8	models	model	NOUN
aiti-366	143	9	for	for	ADP
aiti-366	143	10	extracting	extract	VERB
aiti-366	143	11	cnn	cnn	PROPN
aiti-366	143	12	features	feature	NOUN
aiti-366	143	13	from	from	ADP
aiti-366	143	14	different	different	ADJ
aiti-366	143	15	layers	layer	NOUN
aiti-366	143	16	.	.	PUNCT
aiti-366	144	1	authors	author	NOUN
aiti-366	144	2	also	also	ADV
aiti-366	144	3	used	use	VERB
aiti-366	144	4	convolutional	convolutional	ADJ
aiti-366	144	5	feature	feature	NOUN
aiti-366	144	6	coding	code	VERB
aiti-366	144	7	scheme	scheme	NOUN
aiti-366	144	8	for	for	ADP
aiti-366	144	9	aggregating	aggregate	VERB
aiti-366	144	10	the	the	DET
aiti-366	144	11	dense	dense	ADJ
aiti-366	144	12	convolutional	convolutional	ADJ
aiti-366	144	13	features	feature	NOUN
aiti-366	144	14	into	into	ADP
aiti-366	144	15	a	a	DET
aiti-366	144	16	global	global	ADJ
aiti-366	144	17	representation	representation	NOUN
aiti-366	144	18	.	.	PUNCT
aiti-366	145	1	their	their	PRON
aiti-366	145	2	proposed	proposed	ADJ
aiti-366	145	3	two	two	NUM
aiti-366	145	4	models	model	NOUN
aiti-366	145	5	achieved	achieve	VERB
aiti-366	145	6	remarkable	remarkable	ADJ
aiti-366	145	7	performance	performance	NOUN
aiti-366	145	8	and	and	CCONJ
aiti-366	145	9	improved	improve	VERB
aiti-366	145	10	the	the	DET
aiti-366	145	11	state	state	NOUN
aiti-366	145	12	-	-	PUNCT
aiti-366	145	13	of	of	ADP
aiti-366	145	14	-	-	PUNCT
aiti-366	145	15	the	the	DET
aiti-366	145	16	-	-	PUNCT
aiti-366	145	17	art	art	NOUN
aiti-366	145	18	by	by	ADP
aiti-366	145	19	a	a	DET
aiti-366	145	20	significant	significant	ADJ
aiti-366	145	21	margin	margin	NOUN
aiti-366	145	22	.	.	PUNCT
aiti-366	146	1	for	for	ADP
aiti-366	146	2	garments	garment	NOUN
aiti-366	146	3	design	design	NOUN
aiti-366	146	4	class	class	NOUN
aiti-366	146	5	identification	identification	NOUN
aiti-366	146	6	many	many	ADJ
aiti-366	146	7	approaches	approach	NOUN
aiti-366	146	8	have	have	AUX
aiti-366	146	9	been	be	AUX
aiti-366	146	10	proposed	propose	VERB
aiti-366	146	11	.	.	PUNCT
aiti-366	147	1	but	but	CCONJ
aiti-366	147	2	,	,	PUNCT
aiti-366	147	3	there	there	PRON
aiti-366	147	4	are	be	VERB
aiti-366	147	5	only	only	ADV
aiti-366	147	6	a	a	DET
aiti-366	147	7	few	few	ADJ
aiti-366	147	8	works	work	NOUN
aiti-366	147	9	that	that	PRON
aiti-366	147	10	have	have	AUX
aiti-366	147	11	been	be	AUX
aiti-366	147	12	conducted	conduct	VERB
aiti-366	147	13	based	base	VERB
aiti-366	147	14	on	on	ADP
aiti-366	147	15	deep	deep	ADJ
aiti-366	147	16	learning	learning	NOUN
aiti-366	147	17	.	.	PUNCT
aiti-366	148	1	this	this	DET
aiti-366	148	2	research	research	NOUN
aiti-366	148	3	has	have	AUX
aiti-366	148	4	experimented	experiment	VERB
aiti-366	148	5	different	different	ADJ
aiti-366	148	6	deep	deep	ADJ
aiti-366	148	7	learning	learning	NOUN
aiti-366	148	8	methods	method	NOUN
aiti-366	148	9	for	for	ADP
aiti-366	148	10	identifying	identify	VERB
aiti-366	148	11	different	different	ADJ
aiti-366	148	12	garments	garment	NOUN
aiti-366	148	13	design	design	NOUN
aiti-366	148	14	class	class	NOUN
aiti-366	148	15	based	base	VERB
aiti-366	148	16	on	on	ADP
aiti-366	148	17	textures	texture	NOUN
aiti-366	148	18	.	.	PUNCT
aiti-366	149	1	3	3	X
aiti-366	149	2	.	.	X
aiti-366	149	3	methodology	methodology	NOUN
aiti-366	149	4	this	this	DET
aiti-366	149	5	section	section	NOUN
aiti-366	149	6	describes	describe	VERB
aiti-366	149	7	the	the	DET
aiti-366	149	8	methodology	methodology	NOUN
aiti-366	149	9	for	for	ADP
aiti-366	149	10	identifying	identify	VERB
aiti-366	149	11	the	the	DET
aiti-366	149	12	garments	garment	NOUN
aiti-366	149	13	design	design	NOUN
aiti-366	149	14	classes	class	NOUN
aiti-366	149	15	.	.	PUNCT
aiti-366	150	1	basic	basic	ADJ
aiti-366	150	2	steps	step	NOUN
aiti-366	150	3	of	of	ADP
aiti-366	150	4	the	the	DET
aiti-366	150	5	procedure	procedure	NOUN
aiti-366	150	6	are	be	AUX
aiti-366	150	7	shown	show	VERB
aiti-366	150	8	in	in	ADP
aiti-366	150	9	fig	fig	NOUN
aiti-366	150	10	.	.	PUNCT
aiti-366	151	1	1	1	X
aiti-366	151	2	.	.	X
aiti-366	151	3	input	input	NOUN
aiti-366	151	4	images	image	NOUN
aiti-366	151	5	are	be	AUX
aiti-366	151	6	firstly	firstly	ADV
aiti-366	151	7	segmented	segment	VERB
aiti-366	151	8	and	and	CCONJ
aiti-366	151	9	classified	classify	VERB
aiti-366	151	10	into	into	ADP
aiti-366	151	11	several	several	ADJ
aiti-366	151	12	classes	class	NOUN
aiti-366	151	13	based	base	VERB
aiti-366	151	14	on	on	ADP
aiti-366	151	15	their	their	PRON
aiti-366	151	16	texture	texture	ADJ
aiti-366	151	17	design	design	NOUN
aiti-366	151	18	.	.	PUNCT
aiti-366	152	1	after	after	ADP
aiti-366	152	2	that	that	PRON
aiti-366	152	3	,	,	PUNCT
aiti-366	152	4	these	these	DET
aiti-366	152	5	images	image	NOUN
aiti-366	152	6	are	be	AUX
aiti-366	152	7	separated	separate	VERB
aiti-366	152	8	for	for	ADP
aiti-366	152	9	training	training	NOUN
aiti-366	152	10	,	,	PUNCT
aiti-366	152	11	validation	validation	NOUN
aiti-366	152	12	and	and	CCONJ
aiti-366	152	13	testing	testing	NOUN
aiti-366	152	14	from	from	ADP
aiti-366	152	15	each	each	PRON
aiti-366	152	16	of	of	ADP
aiti-366	152	17	the	the	DET
aiti-366	152	18	class	class	NOUN
aiti-366	152	19	.	.	PUNCT
aiti-366	153	1	proposed	propose	VERB
aiti-366	153	2	model	model	NOUN
aiti-366	153	3	is	be	AUX
aiti-366	153	4	then	then	ADV
aiti-366	153	5	applied	apply	VERB
aiti-366	153	6	alongside	alongside	ADV
aiti-366	153	7	with	with	ADP
aiti-366	153	8	two	two	NUM
aiti-366	153	9	well	well	ADV
aiti-366	153	10	-	-	PUNCT
aiti-366	153	11	known	know	VERB
aiti-366	153	12	deep	deep	ADJ
aiti-366	153	13	convolutional	convolutional	ADJ
aiti-366	153	14	neural	neural	ADJ
aiti-366	153	15	network	network	NOUN
aiti-366	153	16	(	(	PUNCT
aiti-366	153	17	cnn	cnn	PROPN
aiti-366	153	18	)	)	PUNCT
aiti-366	153	19	models	model	VERB
aiti-366	153	20	alexnet	alexnet	NOUN
aiti-366	153	21	and	and	CCONJ
aiti-366	153	22	vgg_s	vgg_	NOUN
aiti-366	153	23	in	in	ADP
aiti-366	153	24	two	two	NUM
aiti-366	153	25	different	different	ADJ
aiti-366	153	26	garment	garment	NOUN
aiti-366	153	27	datasets	dataset	NOUN
aiti-366	153	28	for	for	ADP
aiti-366	153	29	the	the	DET
aiti-366	153	30	purpose	purpose	NOUN
aiti-366	153	31	of	of	ADP
aiti-366	153	32	training	training	NOUN
aiti-366	153	33	and	and	CCONJ
aiti-366	153	34	testing	testing	NOUN
aiti-366	153	35	.	.	PUNCT
aiti-366	154	1	finally	finally	ADV
aiti-366	154	2	,	,	PUNCT
aiti-366	154	3	the	the	DET
aiti-366	154	4	accuracy	accuracy	NOUN
aiti-366	154	5	of	of	ADP
aiti-366	154	6	proposed	propose	VERB
aiti-366	154	7	system	system	NOUN
aiti-366	154	8	is	be	AUX
aiti-366	154	9	compared	compare	VERB
aiti-366	154	10	with	with	ADP
aiti-366	154	11	the	the	DET
aiti-366	154	12	existing	exist	VERB
aiti-366	154	13	models	model	NOUN
aiti-366	154	14	.	.	PUNCT
aiti-366	155	1	we	we	PRON
aiti-366	155	2	have	have	AUX
aiti-366	155	3	also	also	ADV
aiti-366	155	4	compared	compare	VERB
aiti-366	155	5	the	the	DET
aiti-366	155	6	results	result	NOUN
aiti-366	155	7	with	with	ADP
aiti-366	155	8	traditional	traditional	ADJ
aiti-366	155	9	state	state	NOUN
aiti-366	155	10	-	-	PUNCT
aiti-366	155	11	of	of	ADP
aiti-366	155	12	-	-	PUNCT
aiti-366	155	13	the	the	DET
aiti-366	155	14	-	-	PUNCT
aiti-366	155	15	arts	arts	NOUN
aiti-366	155	16	hand	hand	NOUN
aiti-366	155	17	-	-	PUNCT
aiti-366	155	18	engineered	engineer	VERB
aiti-366	155	19	feature	feature	NOUN
aiti-366	155	20	extraction	extraction	NOUN
aiti-366	155	21	method	method	NOUN
aiti-366	155	22	.	.	PUNCT
aiti-366	156	1	alexnet	alexnet	PROPN
aiti-366	156	2	and	and	CCONJ
aiti-366	156	3	vgg_s	vgg_s	PROPN
aiti-366	156	4	have	have	AUX
aiti-366	156	5	been	be	AUX
aiti-366	156	6	chosen	choose	VERB
aiti-366	156	7	in	in	ADP
aiti-366	156	8	this	this	DET
aiti-366	156	9	work	work	NOUN
aiti-366	156	10	because	because	SCONJ
aiti-366	156	11	of	of	ADP
aiti-366	156	12	their	their	PRON
aiti-366	156	13	computational	computational	ADJ
aiti-366	156	14	simplicity	simplicity	NOUN
aiti-366	156	15	and	and	CCONJ
aiti-366	156	16	better	well	ADJ
aiti-366	156	17	performance	performance	NOUN
aiti-366	156	18	in	in	ADP
aiti-366	156	19	several	several	ADJ
aiti-366	156	20	areas	area	NOUN
aiti-366	156	21	.	.	PUNCT
aiti-366	157	1	they	they	PRON
aiti-366	157	2	work	work	VERB
aiti-366	157	3	well	well	ADV
aiti-366	157	4	on	on	ADP
aiti-366	157	5	unsupervised	unsupervised	ADJ
aiti-366	157	6	dataset	dataset	NOUN
aiti-366	157	7	.	.	PUNCT
aiti-366	158	1	these	these	DET
aiti-366	158	2	two	two	NUM
aiti-366	158	3	models	model	NOUN
aiti-366	158	4	can	can	AUX
aiti-366	158	5	handle	handle	VERB
aiti-366	158	6	over	over	ADV
aiti-366	158	7	-	-	PUNCT
aiti-366	158	8	fitting	fit	VERB
aiti-366	158	9	problem	problem	NOUN
aiti-366	158	10	when	when	SCONJ
aiti-366	158	11	working	work	VERB
aiti-366	158	12	with	with	ADP
aiti-366	158	13	large	large	ADJ
aiti-366	158	14	dataset	dataset	NOUN
aiti-366	158	15	by	by	ADP
aiti-366	158	16	using	use	VERB
aiti-366	158	17	data	datum	NOUN
aiti-366	158	18	augmentation	augmentation	NOUN
aiti-366	158	19	technique	technique	NOUN
aiti-366	158	20	.	.	PUNCT
aiti-366	159	1	besides	besides	SCONJ
aiti-366	159	2	,	,	PUNCT
aiti-366	159	3	these	these	DET
aiti-366	159	4	two	two	NUM
aiti-366	159	5	models	model	NOUN
aiti-366	159	6	use	use	VERB
aiti-366	159	7	a	a	DET
aiti-366	159	8	recently	recently	ADV
aiti-366	159	9	-	-	PUNCT
aiti-366	159	10	developed	develop	VERB
aiti-366	159	11	regularization	regularization	NOUN
aiti-366	159	12	method	method	NOUN
aiti-366	159	13	called	call	VERB
aiti-366	159	14	"	"	PUNCT
aiti-366	159	15	dropout	dropout	NOUN
aiti-366	159	16	"	"	PUNCT
aiti-366	159	17	that	that	PRON
aiti-366	159	18	is	be	AUX
aiti-366	159	19	proven	prove	VERB
aiti-366	159	20	to	to	PART
aiti-366	159	21	be	be	AUX
aiti-366	159	22	very	very	ADV
aiti-366	159	23	effective	effective	ADJ
aiti-366	159	24	.	.	PUNCT
aiti-366	160	1	these	these	DET
aiti-366	160	2	two	two	NUM
aiti-366	160	3	models	model	NOUN
aiti-366	160	4	gained	gain	VERB
aiti-366	160	5	significant	significant	ADJ
aiti-366	160	6	results	result	NOUN
aiti-366	160	7	in	in	ADP
aiti-366	160	8	challenging	challenging	ADJ
aiti-366	160	9	benchmarks	benchmark	NOUN
aiti-366	160	10	on	on	ADP
aiti-366	160	11	image	image	NOUN
aiti-366	160	12	recognition	recognition	NOUN
aiti-366	160	13	and	and	CCONJ
aiti-366	160	14	object	object	VERB
aiti-366	160	15	detection	detection	NOUN
aiti-366	160	16	.	.	PUNCT
aiti-366	161	1	brief	brief	ADJ
aiti-366	161	2	descriptions	description	NOUN
aiti-366	161	3	about	about	ADP
aiti-366	161	4	these	these	DET
aiti-366	161	5	two	two	NUM
aiti-366	161	6	models	model	NOUN
aiti-366	161	7	alongside	alongside	ADP
aiti-366	161	8	our	our	PRON
aiti-366	161	9	proposed	propose	VERB
aiti-366	161	10	model	model	NOUN
aiti-366	161	11	are	be	AUX
aiti-366	161	12	described	describe	VERB
aiti-366	161	13	in	in	ADP
aiti-366	161	14	the	the	DET
aiti-366	161	15	following	follow	VERB
aiti-366	161	16	sub	sub	NOUN
aiti-366	161	17	-	-	NOUN
aiti-366	161	18	sections	section	NOUN
aiti-366	161	19	.	.	PUNCT
aiti-366	162	1	fig	fig	NOUN
aiti-366	162	2	.	.	PUNCT
aiti-366	163	1	1	1	NUM
aiti-366	163	2	basic	basic	ADJ
aiti-366	163	3	steps	step	NOUN
aiti-366	163	4	of	of	ADP
aiti-366	163	5	our	our	PRON
aiti-366	163	6	working	work	VERB
aiti-366	163	7	procedure	procedure	NOUN
aiti-366	163	8	fig	fig	NOUN
aiti-366	163	9	.	.	PUNCT
aiti-366	164	1	2	2	NUM
aiti-366	165	1	the	the	DET
aiti-366	165	2	full	full	ADJ
aiti-366	165	3	architecture	architecture	NOUN
aiti-366	165	4	of	of	ADP
aiti-366	165	5	alexnet	alexnet	ADJ
aiti-366	165	6	model	model	NOUN
aiti-366	165	7	3.1	3.1	NUM
aiti-366	165	8	.	.	PUNCT
aiti-366	166	1	alexnet	alexnet	ADJ
aiti-366	166	2	model	model	NOUN
aiti-366	166	3	alexnet	alexnet	PROPN
aiti-366	166	4	model	model	NOUN
aiti-366	166	5	was	be	AUX
aiti-366	166	6	proposed	propose	VERB
aiti-366	166	7	by	by	ADP
aiti-366	166	8	krizhevsky	krizhevsky	PROPN
aiti-366	166	9	et	et	PROPN
aiti-366	166	10	al	al	PROPN
aiti-366	166	11	.	.	PUNCT
aiti-366	167	1	[	[	X
aiti-366	167	2	7	7	NUM
aiti-366	167	3	]	]	PUNCT
aiti-366	167	4	.	.	PUNCT
aiti-366	168	1	there	there	PRON
aiti-366	168	2	are	be	VERB
aiti-366	168	3	three	three	NUM
aiti-366	168	4	types	type	NOUN
aiti-366	168	5	of	of	ADP
aiti-366	168	6	layer	layer	NOUN
aiti-366	168	7	in	in	ADP
aiti-366	168	8	a	a	DET
aiti-366	168	9	deep	deep	ADJ
aiti-366	168	10	convolution	convolution	NOUN
aiti-366	168	11	neural	neural	ADJ
aiti-366	168	12	network	network	NOUN
aiti-366	168	13	;	;	PUNCT
aiti-366	168	14	such	such	ADJ
aiti-366	168	15	as	as	ADP
aiti-366	168	16	convolution	convolution	NOUN
aiti-366	168	17	layer	layer	NOUN
aiti-366	168	18	,	,	PUNCT
aiti-366	168	19	pooling	pool	VERB
aiti-366	168	20	layer	layer	NOUN
aiti-366	168	21	and	and	CCONJ
aiti-366	168	22	fully	fully	ADV
aiti-366	168	23	-	-	PUNCT
aiti-366	168	24	connected	connect	VERB
aiti-366	168	25	(	(	PUNCT
aiti-366	168	26	fc	fc	INTJ
aiti-366	168	27	)	)	PUNCT
aiti-366	168	28	layers	layer	NOUN
aiti-366	168	29	.	.	PUNCT
aiti-366	169	1	full	full	ADJ
aiti-366	169	2	architecture	architecture	NOUN
aiti-366	169	3	of	of	ADP
aiti-366	169	4	alexnet	alexnet	ADJ
aiti-366	169	5	model	model	NOUN
aiti-366	169	6	was	be	AUX
aiti-366	169	7	created	create	VERB
aiti-366	169	8	by	by	ADP
aiti-366	169	9	combining	combine	VERB
aiti-366	169	10	these	these	DET
aiti-366	169	11	three	three	NUM
aiti-366	169	12	layers	layer	NOUN
aiti-366	169	13	.	.	PUNCT
aiti-366	170	1	in	in	ADP
aiti-366	170	2	this	this	DET
aiti-366	170	3	architecture	architecture	NOUN
aiti-366	170	4	,	,	PUNCT
aiti-366	170	5	there	there	PRON
aiti-366	170	6	are	be	VERB
aiti-366	170	7	total	total	ADJ
aiti-366	170	8	eight	eight	NUM
aiti-366	170	9	learned	learn	VERB
aiti-366	170	10	layers	layer	NOUN
aiti-366	170	11	:	:	PUNCT
aiti-366	170	12	five	five	NUM
aiti-366	170	13	convolutional	convolutional	ADJ
aiti-366	170	14	layers	layer	NOUN
aiti-366	170	15	and	and	CCONJ
aiti-366	170	16	three	three	NUM
aiti-366	170	17	fully	fully	ADV
aiti-366	170	18	connected	connected	ADJ
aiti-366	170	19	layers	layer	NOUN
aiti-366	170	20	.	.	PUNCT
aiti-366	171	1	convolution	convolution	NOUN
aiti-366	171	2	layer	layer	NOUN
aiti-366	171	3	is	be	AUX
aiti-366	171	4	the	the	DET
aiti-366	171	5	core	core	NOUN
aiti-366	171	6	building	building	NOUN
aiti-366	171	7	block	block	NOUN
aiti-366	171	8	and	and	CCONJ
aiti-366	171	9	each	each	PRON
aiti-366	171	10	of	of	ADP
aiti-366	171	11	those	those	DET
aiti-366	171	12	convolution	convolution	NOUN
aiti-366	171	13	layer	layer	NOUN
aiti-366	171	14	consists	consist	VERB
aiti-366	171	15	of	of	ADP
aiti-366	171	16	some	some	DET
aiti-366	171	17	learnable	learnable	ADJ
aiti-366	171	18	filters	filter	NOUN
aiti-366	171	19	.	.	PUNCT
aiti-366	172	1	filters	filter	NOUN
aiti-366	172	2	size	size	NOUN
aiti-366	172	3	are	be	AUX
aiti-366	172	4	different	different	ADJ
aiti-366	172	5	from	from	ADP
aiti-366	172	6	one	one	NUM
aiti-366	172	7	another	another	DET
aiti-366	172	8	.	.	PUNCT
aiti-366	173	1	full	full	ADJ
aiti-366	173	2	alexnet	alexnet	ADJ
aiti-366	173	3	architectural	architectural	ADJ
aiti-366	173	4	model	model	NOUN
aiti-366	173	5	is	be	AUX
aiti-366	173	6	shown	show	VERB
aiti-366	173	7	in	in	ADP
aiti-366	173	8	fig	fig	NOUN
aiti-366	173	9	.	.	PUNCT
aiti-366	174	1	2	2	NUM
aiti-366	174	2	.	.	X
aiti-366	174	3	first	first	ADJ
aiti-366	174	4	convolution	convolution	NOUN
aiti-366	174	5	layer	layer	NOUN
aiti-366	174	6	takes	take	VERB
aiti-366	174	7	the	the	DET
aiti-366	174	8	input	input	NOUN
aiti-366	174	9	images	image	NOUN
aiti-366	174	10	by	by	ADP
aiti-366	174	11	resizing	resize	VERB
aiti-366	174	12	each	each	PRON
aiti-366	174	13	of	of	ADP
aiti-366	174	14	the	the	DET
aiti-366	174	15	images	image	NOUN
aiti-366	174	16	into	into	ADP
aiti-366	174	17	224×224	224×224	NUM
aiti-366	174	18	with	with	ADP
aiti-366	174	19	96	96	NUM
aiti-366	174	20	kernels	kernel	NOUN
aiti-366	174	21	.	.	PUNCT
aiti-366	175	1	the	the	DET
aiti-366	175	2	second	second	ADJ
aiti-366	175	3	layer	layer	NOUN
aiti-366	175	4	takes	take	VERB
aiti-366	175	5	the	the	DET
aiti-366	175	6	input	input	NOUN
aiti-366	175	7	from	from	ADP
aiti-366	175	8	first	first	ADJ
aiti-366	175	9	convolution	convolution	NOUN
aiti-366	175	10	layer	layer	NOUN
aiti-366	175	11	with	with	ADP
aiti-366	175	12	256	256	NUM
aiti-366	175	13	kernels	kernel	NOUN
aiti-366	175	14	after	after	ADP
aiti-366	175	15	passing	pass	VERB
aiti-366	175	16	through	through	ADP
aiti-366	175	17	a	a	DET
aiti-366	175	18	pooling	pool	VERB
aiti-366	175	19	layer	layer	NOUN
aiti-366	175	20	.	.	PUNCT
aiti-366	176	1	pooling	pool	VERB
aiti-366	176	2	layer	layer	NOUN
aiti-366	176	3	operates	operate	VERB
aiti-366	176	4	independently	independently	ADV
aiti-366	176	5	and	and	CCONJ
aiti-366	176	6	reduce	reduce	VERB
aiti-366	176	7	the	the	DET
aiti-366	176	8	amount	amount	NOUN
aiti-366	176	9	of	of	ADP
aiti-366	176	10	parameters	parameter	NOUN
aiti-366	176	11	and	and	CCONJ
aiti-366	176	12	computation	computation	NOUN
aiti-366	176	13	in	in	ADP
aiti-366	176	14	the	the	DET
aiti-366	176	15	network	network	NOUN
aiti-366	176	16	.	.	PUNCT
aiti-366	177	1	hence	hence	ADV
aiti-366	177	2	,	,	PUNCT
aiti-366	177	3	control	control	VERB
aiti-366	177	4	the	the	DET
aiti-366	177	5	over	over	ADV
aiti-366	177	6	-	-	PUNCT
aiti-366	177	7	fitting	fit	VERB
aiti-366	177	8	problems	problem	NOUN
aiti-366	177	9	.	.	PUNCT
aiti-366	178	1	in	in	ADP
aiti-366	178	2	this	this	DET
aiti-366	178	3	architecture	architecture	NOUN
aiti-366	178	4	,	,	PUNCT
aiti-366	178	5	the	the	DET
aiti-366	178	6	third	third	ADJ
aiti-366	178	7	,	,	PUNCT
aiti-366	178	8	fourth	fourth	ADJ
aiti-366	178	9	and	and	CCONJ
aiti-366	178	10	fifth	fifth	ADJ
aiti-366	178	11	layers	layer	NOUN
aiti-366	178	12	are	be	AUX
aiti-366	178	13	connected	connect	VERB
aiti-366	178	14	to	to	ADP
aiti-366	178	15	one	one	NUM
aiti-366	178	16	another	another	DET
aiti-366	178	17	without	without	ADP
aiti-366	178	18	any	any	DET
aiti-366	178	19	connection	connection	NOUN
aiti-366	178	20	of	of	ADP
aiti-366	178	21	pooling	pool	VERB
aiti-366	178	22	layers	layer	NOUN
aiti-366	178	23	.	.	PUNCT
aiti-366	179	1	the	the	DET
aiti-366	179	2	third	third	ADJ
aiti-366	179	3	layer	layer	NOUN
aiti-366	179	4	consists	consist	VERB
aiti-366	179	5	of	of	ADP
aiti-366	179	6	384	384	NUM
aiti-366	179	7	kernels	kernel	NOUN
aiti-366	179	8	which	which	PRON
aiti-366	179	9	takes	take	VERB
aiti-366	179	10	input	input	NOUN
aiti-366	179	11	from	from	ADP
aiti-366	179	12	the	the	DET
aiti-366	179	13	output	output	NOUN
aiti-366	179	14	of	of	ADP
aiti-366	179	15	second	second	ADJ
aiti-366	179	16	layer	layer	NOUN
aiti-366	179	17	.	.	PUNCT
aiti-366	180	1	the	the	DET
aiti-366	180	2	fourth	fourth	ADJ
aiti-366	180	3	layer	layer	NOUN
aiti-366	180	4	has	have	VERB
aiti-366	180	5	384	384	NUM
aiti-366	180	6	and	and	CCONJ
aiti-366	180	7	fifth	fifth	ADJ
aiti-366	180	8	layer	layer	NOUN
aiti-366	180	9	contains	contain	VERB
aiti-366	180	10	256	256	NUM
aiti-366	180	11	kernels	kernel	NOUN
aiti-366	180	12	.	.	PUNCT
aiti-366	181	1	each	each	PRON
aiti-366	181	2	of	of	ADP
aiti-366	181	3	last	last	ADJ
aiti-366	181	4	three	three	NUM
aiti-366	181	5	fully	fully	ADV
aiti-366	181	6	connected	connect	VERB
aiti-366	181	7	layers	layer	NOUN
aiti-366	181	8	contains	contain	VERB
aiti-366	181	9	4096	4096	NUM
aiti-366	181	10	neurons	neuron	NOUN
aiti-366	181	11	.	.	PUNCT
aiti-366	182	1	the	the	DET
aiti-366	182	2	output	output	NOUN
aiti-366	182	3	of	of	ADP
aiti-366	182	4	the	the	DET
aiti-366	182	5	last	last	ADJ
aiti-366	182	6	fully	fully	ADV
aiti-366	182	7	connected	connect	VERB
aiti-366	182	8	layer	layer	NOUN
aiti-366	182	9	is	be	AUX
aiti-366	182	10	sent	send	VERB
aiti-366	182	11	as	as	ADP
aiti-366	182	12	input	input	NOUN
aiti-366	182	13	to	to	ADP
aiti-366	182	14	a	a	DET
aiti-366	182	15	1000	1000	NUM
aiti-366	182	16	way	way	NOUN
aiti-366	182	17	softmax	softmax	NOUN
aiti-366	182	18	layer	layer	NOUN
aiti-366	182	19	which	which	PRON
aiti-366	182	20	produces	produce	VERB
aiti-366	182	21	a	a	DET
aiti-366	182	22	distribution	distribution	NOUN
aiti-366	182	23	over	over	ADP
aiti-366	182	24	the	the	DET
aiti-366	182	25	1000	1000	NUM
aiti-366	182	26	class	class	NOUN
aiti-366	182	27	labels	label	NOUN
aiti-366	182	28	.	.	PUNCT
aiti-366	183	1	here	here	ADV
aiti-366	183	2	,	,	PUNCT
aiti-366	183	3	multinomial	multinomial	ADJ
aiti-366	183	4	logistic	logistic	ADJ
aiti-366	183	5	regression	regression	NOUN
aiti-366	183	6	is	be	AUX
aiti-366	183	7	also	also	ADV
aiti-366	183	8	used	use	VERB
aiti-366	183	9	for	for	ADP
aiti-366	183	10	maximizing	maximize	VERB
aiti-366	183	11	the	the	DET
aiti-366	183	12	training	training	NOUN
aiti-366	183	13	cases	case	NOUN
aiti-366	183	14	.	.	PUNCT
aiti-366	184	1	3.2	3.2	NUM
aiti-366	184	2	.	.	PUNCT
aiti-366	185	1	vggnet	vggnet	PROPN
aiti-366	185	2	model	model	PROPN
aiti-366	185	3	chatfield	chatfield	PROPN
aiti-366	185	4	et	et	PROPN
aiti-366	185	5	al	al	PROPN
aiti-366	185	6	.	.	PUNCT
aiti-366	186	1	[	[	X
aiti-366	186	2	9	9	NUM
aiti-366	186	3	]	]	PUNCT
aiti-366	186	4	,	,	PUNCT
aiti-366	186	5	based	base	VERB
aiti-366	186	6	on	on	ADP
aiti-366	186	7	caffe	caffe	NOUN
aiti-366	186	8	toolkit	toolkit	NOUN
aiti-366	186	9	proposed	propose	VERB
aiti-366	186	10	three	three	NUM
aiti-366	186	11	different	different	ADJ
aiti-366	186	12	architectures	architecture	NOUN
aiti-366	186	13	of	of	ADP
aiti-366	186	14	deep	deep	ADJ
aiti-366	186	15	cnn	cnn	PROPN
aiti-366	186	16	models	model	NOUN
aiti-366	186	17	:	:	PUNCT
aiti-366	186	18	vgg_f	vgg_f	NOUN
aiti-366	186	19	,	,	PUNCT
aiti-366	186	20	vgg_m	vgg_m	NOUN
aiti-366	186	21	and	and	CCONJ
aiti-366	186	22	vgg_s	vgg_s	ADJ
aiti-366	186	23	;	;	PUNCT
aiti-366	186	24	each	each	PRON
aiti-366	186	25	of	of	ADP
aiti-366	186	26	which	which	PRON
aiti-366	186	27	explores	explore	VERB
aiti-366	186	28	a	a	DET
aiti-366	186	29	different	different	ADJ
aiti-366	186	30	speed	speed	NOUN
aiti-366	186	31	/	/	SYM
aiti-366	186	32	accuracy	accuracy	NOUN
aiti-366	186	33	trade	trade	NOUN
aiti-366	186	34	-	-	PUNCT
aiti-366	186	35	off	off	NOUN
aiti-366	186	36	:	:	PUNCT
aiti-366	186	37	(	(	PUNCT
aiti-366	186	38	1	1	X
aiti-366	186	39	)	)	PUNCT
aiti-366	186	40	vgg_f	vgg_f	NOUN
aiti-366	186	41	:	:	PUNCT
aiti-366	186	42	this	this	DET
aiti-366	186	43	cnn	cnn	PROPN
aiti-366	186	44	arch	arch	NOUN
aiti-366	186	45	itecture	itecture	PROPN
aiti-366	186	46	is	be	AUX
aiti-366	186	47	almost	almost	ADV
aiti-366	186	48	similar	similar	ADJ
aiti-366	186	49	to	to	ADP
aiti-366	186	50	alexnet	alexnet	NOUN
aiti-366	186	51	.	.	PUNCT
aiti-366	187	1	but	but	CCONJ
aiti-366	187	2	vgg_f	vgg_f	NOUN
aiti-366	187	3	contains	contain	VERB
aiti-366	187	4	smaller	small	ADJ
aiti-366	187	5	number	number	NOUN
aiti-366	187	6	of	of	ADP
aiti-366	187	7	filters	filter	NOUN
aiti-366	187	8	and	and	CCONJ
aiti-366	187	9	small	small	ADJ
aiti-366	187	10	stride	stride	NOUN
aiti-366	187	11	in	in	ADP
aiti-366	187	12	some	some	DET
aiti-366	187	13	convolutional	convolutional	ADJ
aiti-366	187	14	layers	layer	NOUN
aiti-366	187	15	.	.	PUNCT
aiti-366	188	1	(	(	PUNCT
aiti-366	188	2	2	2	X
aiti-366	188	3	)	)	PUNCT
aiti-366	188	4	vgg_m	vgg_m	NOUN
aiti-366	188	5	:	:	PUNCT
aiti-366	188	6	it	it	PRON
aiti-366	188	7	is	be	AUX
aiti-366	188	8	a	a	DET
aiti-366	188	9	medium	medium	ADJ
aiti-366	188	10	size	size	NOUN
aiti-366	188	11	cnn	cnn	NOUN
aiti-366	188	12	which	which	PRON
aiti-366	188	13	is	be	AUX
aiti-366	188	14	very	very	ADV
aiti-366	188	15	similar	similar	ADJ
aiti-366	188	16	proposed	propose	VERB
aiti-366	188	17	by	by	ADP
aiti-366	188	18	zeiler	zeiler	PROPN
aiti-366	188	19	et	et	PROPN
aiti-366	188	20	al	al	PROPN
aiti-366	188	21	.	.	PUNCT
aiti-366	189	1	[	[	X
aiti-366	189	2	30	30	NUM
aiti-366	189	3	]	]	PUNCT
aiti-366	189	4	.	.	PUNCT
aiti-366	190	1	the	the	DET
aiti-366	190	2	1	1	NUM
aiti-366	190	3	st	st	NOUN
aiti-366	190	4	convolution	convolution	NOUN
aiti-366	190	5	layer	layer	NOUN
aiti-366	190	6	of	of	ADP
aiti-366	190	7	this	this	DET
aiti-366	190	8	network	network	NOUN
aiti-366	190	9	has	have	VERB
aiti-366	190	10	s	s	PROPN
aiti-366	190	11	maller	maller	NOUN
aiti-366	190	12	stride	stride	NOUN
aiti-366	190	13	and	and	CCONJ
aiti-366	190	14	pooling	pool	VERB
aiti-366	190	15	layer	layer	NOUN
aiti-366	190	16	.	.	PUNCT
aiti-366	191	1	4th	4th	ADJ
aiti-366	191	2	convolution	convolution	NOUN
aiti-366	191	3	layer	layer	NOUN
aiti-366	191	4	use	use	VERB
aiti-366	191	5	smaller	small	ADJ
aiti-366	191	6	numbers	number	NOUN
aiti-366	191	7	of	of	ADP
aiti-366	191	8	filters	filter	NOUN
aiti-366	191	9	for	for	ADP
aiti-366	191	10	balancing	balance	VERB
aiti-366	191	11	the	the	DET
aiti-366	191	12	computational	computational	ADJ
aiti-366	191	13	speed	speed	NOUN
aiti-366	191	14	.	.	PUNCT
aiti-366	192	1	(	(	PUNCT
aiti-366	192	2	3	3	X
aiti-366	192	3	)	)	PUNCT
aiti-366	192	4	vgg_s	vgg_s	ADJ
aiti-366	192	5	:	:	PUNCT
aiti-366	192	6	this	this	DET
aiti-366	192	7	architecture	architecture	NOUN
aiti-366	192	8	is	be	AUX
aiti-366	192	9	relat	relat	ADJ
aiti-366	192	10	ively	ively	ADV
aiti-366	192	11	slow	slow	ADJ
aiti-366	192	12	than	than	ADP
aiti-366	192	13	vgg_f	vgg_f	NOUN
aiti-366	192	14	and	and	CCONJ
aiti-366	192	15	vgg_m	vgg_m	NOUN
aiti-366	192	16	and	and	CCONJ
aiti-366	192	17	it	it	PRON
aiti-366	192	18	is	be	AUX
aiti-366	192	19	a	a	DET
aiti-366	192	20	simplified	simplified	ADJ
aiti-366	192	21	version	version	NOUN
aiti-366	192	22	of	of	ADP
aiti-366	192	23	accurate	accurate	ADJ
aiti-366	192	24	model	model	NOUN
aiti-366	192	25	in	in	ADP
aiti-366	192	26	the	the	DET
aiti-366	192	27	over	over	ADP
aiti-366	192	28	-	-	PUNCT
aiti-366	192	29	feat	feat	NOUN
aiti-366	192	30	framework	framework	NOUN
aiti-366	192	31	which	which	PRON
aiti-366	192	32	has	have	VERB
aiti-366	192	33	six	six	NUM
aiti-366	192	34	convolutional	convolutional	ADJ
aiti-366	192	35	layers	layer	NOUN
aiti-366	192	36	.	.	PUNCT
aiti-366	193	1	fig	fig	NOUN
aiti-366	193	2	.	.	PUNCT
aiti-366	194	1	3	3	NUM
aiti-366	194	2	shows	show	VERB
aiti-366	194	3	the	the	DET
aiti-366	194	4	full	full	ADJ
aiti-366	194	5	architecture	architecture	NOUN
aiti-366	194	6	of	of	ADP
aiti-366	194	7	vgg_s	vgg_s	ADJ
aiti-366	194	8	model	model	NOUN
aiti-366	194	9	.	.	PUNCT
aiti-366	195	1	it	it	PRON
aiti-366	195	2	has	have	AUX
aiti-366	195	3	taken	take	VERB
aiti-366	195	4	the	the	DET
aiti-366	195	5	first	first	ADJ
aiti-366	195	6	five	five	NUM
aiti-366	195	7	layers	layer	NOUN
aiti-366	195	8	from	from	ADP
aiti-366	195	9	the	the	DET
aiti-366	195	10	original	original	ADJ
aiti-366	195	11	model	model	NOUN
aiti-366	195	12	and	and	CCONJ
aiti-366	195	13	has	have	VERB
aiti-366	195	14	a	a	DET
aiti-366	195	15	smaller	small	ADJ
aiti-366	195	16	number	number	NOUN
aiti-366	195	17	o	o	NOUN
aiti-366	195	18	f	f	PROPN
aiti-366	195	19	filters	filter	VERB
aiti-366	195	20	in	in	ADP
aiti-366	195	21	5th	5th	ADJ
aiti-366	195	22	layer	layer	NOUN
aiti-366	195	23	.	.	PUNCT
aiti-366	196	1	it	it	PRON
aiti-366	196	2	has	have	VERB
aiti-366	196	3	large	large	ADJ
aiti-366	196	4	pooling	pooling	NOUN
aiti-366	196	5	size	size	NOUN
aiti-366	196	6	in	in	ADP
aiti-366	196	7	1st	1st	ADJ
aiti-366	196	8	and	and	CCONJ
aiti-366	196	9	5th	5th	ADJ
aiti-366	196	10	convolutional	convolutional	ADJ
aiti-366	196	11	layer	layer	NOUN
aiti-366	196	12	than	than	ADP
aiti-366	196	13	vgg_m	vgg_m	NOUN
aiti-366	196	14	.	.	PUNCT
aiti-366	197	1	this	this	DET
aiti-366	197	2	model	model	NOUN
aiti-366	197	3	has	have	AUX
aiti-366	197	4	been	be	AUX
aiti-366	197	5	used	use	VERB
aiti-366	197	6	to	to	PART
aiti-366	197	7	evaluate	evaluate	VERB
aiti-366	197	8	the	the	DET
aiti-366	197	9	garments	garment	NOUN
aiti-366	197	10	design	design	NOUN
aiti-366	197	11	advances	advance	NOUN
aiti-366	197	12	in	in	ADP
aiti-366	197	13	technology	technology	NOUN
aiti-366	197	14	innovation	innovation	NOUN
aiti-366	197	15	,	,	PUNCT
aiti-366	197	16	vol	vol	NOUN
aiti-366	197	17	.	.	PROPN
aiti-366	198	1	2	2	NUM
aiti-366	198	2	,	,	PUNCT
aiti-366	198	3	no	no	INTJ
aiti-366	198	4	.	.	NOUN
aiti-366	198	5	4	4	NUM
aiti-366	198	6	,	,	PUNCT
aiti-366	198	7	2017	2017	NUM
aiti-366	198	8	,	,	PUNCT
aiti-366	199	1	pp	pp	ADJ
aiti-366	199	2	.	.	PUNCT
aiti-366	200	1	119	119	NUM
aiti-366	200	2	125	125	NUM
aiti-366	200	3	122	122	NUM
aiti-366	200	4	copyright	copyright	NOUN
aiti-366	200	5	©	©	PROPN
aiti-366	200	6	taeti	taeti	PROPN
aiti-366	201	1	copyright	copyright	NOUN
aiti-366	201	2	©	©	PROPN
aiti-366	201	3	taeti	taeti	PROPN
aiti-366	202	1	copyright	copyright	NOUN
aiti-366	202	2	©	©	PROPN
aiti-366	202	3	taeti	taeti	PROPN
aiti-366	203	1	copyright	copyright	NOUN
aiti-366	203	2	©	©	PROPN
aiti-366	203	3	taeti	taeti	PROPN
aiti-366	204	1	copyright	copyright	NOUN
aiti-366	204	2	©	©	PROPN
aiti-366	204	3	taeti	taeti	PROPN
aiti-366	204	4	class	class	NOUN
aiti-366	204	5	identification	identification	NOUN
aiti-366	204	6	.	.	PUNCT
aiti-366	205	1	as	as	SCONJ
aiti-366	205	2	depicted	depict	VERB
aiti-366	205	3	in	in	ADP
aiti-366	205	4	fig	fig	NOUN
aiti-366	205	5	.	.	PUNCT
aiti-366	206	1	3	3	NUM
aiti-366	206	2	,	,	PUNCT
aiti-366	206	3	this	this	DET
aiti-366	206	4	vgg_s	vgg_s	ADJ
aiti-366	206	5	model	model	NOUN
aiti-366	206	6	contains	contain	VERB
aiti-366	206	7	five	five	NUM
aiti-366	206	8	convolution	convolution	NOUN
aiti-366	206	9	layers	layer	NOUN
aiti-366	206	10	with	with	ADP
aiti-366	206	11	s	s	X
aiti-366	206	12	maller	maller	NOUN
aiti-366	206	13	number	number	NOUN
aiti-366	206	14	of	of	ADP
aiti-366	206	15	filters	filter	NOUN
aiti-366	206	16	in	in	ADP
aiti-366	206	17	the	the	DET
aiti-366	206	18	5th	5th	ADJ
aiti-366	206	19	layer	layer	NOUN
aiti-366	206	20	and	and	CCONJ
aiti-366	206	21	three	three	NUM
aiti-366	206	22	fully	fully	ADV
aiti-366	206	23	connected	connected	ADJ
aiti-366	206	24	layers	layer	NOUN
aiti-366	206	25	.	.	PUNCT
aiti-366	207	1	there	there	PRON
aiti-366	207	2	are	be	VERB
aiti-366	207	3	another	another	DET
aiti-366	207	4	two	two	NUM
aiti-366	207	5	models	model	NOUN
aiti-366	207	6	based	base	VERB
aiti-366	207	7	on	on	ADP
aiti-366	207	8	vggnet	vggnet	PROPN
aiti-366	207	9	namely	namely	ADV
aiti-366	207	10	vgg	vgg	NOUN
aiti-366	207	11	-	-	PUNCT
aiti-366	207	12	vd16	vd16	PROPN
aiti-366	207	13	and	and	CCONJ
aiti-366	207	14	vgg	vgg	PROPN
aiti-366	207	15	-	-	PUNCT
aiti-366	207	16	vd19	vd19	PROPN
aiti-366	207	17	.	.	PROPN
aiti-366	207	18	between	between	ADP
aiti-366	207	19	alexnet	alexnet	ADJ
aiti-366	207	20	and	and	CCONJ
aiti-366	207	21	vgg_s	vgg_s	ADJ
aiti-366	207	22	models	model	NOUN
aiti-366	207	23	,	,	PUNCT
aiti-366	207	24	the	the	DET
aiti-366	207	25	main	main	ADJ
aiti-366	207	26	difference	difference	NOUN
aiti-366	207	27	is	be	AUX
aiti-366	207	28	that	that	SCONJ
aiti-366	207	29	vgg_s	vgg_s	ADJ
aiti-366	207	30	model	model	NOUN
aiti-366	207	31	has	have	VERB
aiti-366	207	32	small	small	ADJ
aiti-366	207	33	stride	stride	NOUN
aiti-366	207	34	in	in	ADP
aiti-366	207	35	some	some	DET
aiti-366	207	36	convolutional	convolutional	ADJ
aiti-366	207	37	layers	layer	NOUN
aiti-366	207	38	and	and	CCONJ
aiti-366	207	39	pooling	pool	VERB
aiti-366	207	40	size	size	NOUN
aiti-366	207	41	is	be	AUX
aiti-366	207	42	large	large	ADJ
aiti-366	207	43	attached	attach	VERB
aiti-366	207	44	with	with	ADP
aiti-366	207	45	the	the	DET
aiti-366	207	46	1st	1st	ADJ
aiti-366	207	47	and	and	CCONJ
aiti-366	207	48	5th	5th	ADJ
aiti-366	207	49	convolutional	convolutional	ADJ
aiti-366	207	50	layer	layer	NOUN
aiti-366	207	51	.	.	PUNCT
aiti-366	208	1	here	here	ADV
aiti-366	208	2	,	,	PUNCT
aiti-366	208	3	fully	fully	ADV
aiti-366	208	4	-	-	PUNCT
aiti-366	208	5	connected	connect	VERB
aiti-366	208	6	layers	layer	NOUN
aiti-366	208	7	6	6	NUM
aiti-366	208	8	and	and	CCONJ
aiti-366	208	9	7	7	NUM
aiti-366	208	10	are	be	AUX
aiti-366	208	11	regularized	regularize	VERB
aiti-366	208	12	using	use	VERB
aiti-366	208	13	dropout	dropout	NOUN
aiti-366	208	14	and	and	CCONJ
aiti-366	208	15	the	the	DET
aiti-366	208	16	last	last	ADJ
aiti-366	208	17	layer	layer	NOUN
aiti-366	208	18	acts	act	VERB
aiti-366	208	19	as	as	ADP
aiti-366	208	20	a	a	DET
aiti-366	208	21	mult	mult	PROPN
aiti-366	208	22	i	i	PROPN
aiti-366	208	23	-	-	PUNCT
aiti-366	208	24	way	way	NOUN
aiti-366	208	25	soft	soft	ADJ
aiti-366	208	26	-	-	PUNCT
aiti-366	208	27	max	max	NOUN
aiti-366	208	28	classifier	classifier	NOUN
aiti-366	208	29	.	.	PUNCT
aiti-366	209	1	fig	fig	NOUN
aiti-366	209	2	.	.	PUNCT
aiti-366	210	1	3	3	NUM
aiti-366	210	2	the	the	DET
aiti-366	210	3	full	full	ADJ
aiti-366	210	4	architecture	architecture	NOUN
aiti-366	210	5	of	of	ADP
aiti-366	210	6	vgg_s	vgg_s	ADJ
aiti-366	210	7	model	model	NOUN
aiti-366	210	8	fig	fig	NOUN
aiti-366	210	9	.	.	PUNCT
aiti-366	211	1	4	4	NUM
aiti-366	211	2	the	the	DET
aiti-366	211	3	full	full	ADJ
aiti-366	211	4	architecture	architecture	NOUN
aiti-366	211	5	of	of	ADP
aiti-366	211	6	our	our	PRON
aiti-366	211	7	proposed	propose	VERB
aiti-366	211	8	model	model	NOUN
aiti-366	211	9	3.3	3.3	NUM
aiti-366	211	10	.	.	PUNCT
aiti-366	212	1	proposed	propose	VERB
aiti-366	212	2	transferred	transfer	VERB
aiti-366	212	3	cnn	cnn	PROPN
aiti-366	212	4	for	for	ADP
aiti-366	212	5	classifying	classify	VERB
aiti-366	212	6	garments	garment	NOUN
aiti-366	212	7	design	design	NOUN
aiti-366	212	8	class	class	NOUN
aiti-366	212	9	,	,	PUNCT
aiti-366	212	10	a	a	DET
aiti-366	212	11	new	new	ADJ
aiti-366	212	12	scenario	scenario	NOUN
aiti-366	212	13	has	have	AUX
aiti-366	212	14	been	be	AUX
aiti-366	212	15	proposed	propose	VERB
aiti-366	212	16	in	in	ADP
aiti-366	212	17	this	this	DET
aiti-366	212	18	paper	paper	NOUN
aiti-366	212	19	based	base	VERB
aiti-366	212	20	on	on	ADP
aiti-366	212	21	alexnet	alexnet	NOUN
aiti-366	212	22	,	,	PUNCT
aiti-366	212	23	to	to	PART
aiti-366	212	24	observe	observe	VERB
aiti-366	212	25	the	the	DET
aiti-366	212	26	performance	performance	NOUN
aiti-366	212	27	and	and	CCONJ
aiti-366	212	28	effectiveness	effectiveness	NOUN
aiti-366	212	29	of	of	ADP
aiti-366	212	30	deep	deep	ADJ
aiti-366	212	31	features	feature	NOUN
aiti-366	212	32	by	by	ADP
aiti-366	212	33	total	total	ADJ
aiti-366	212	34	nine	nine	NUM
aiti-366	212	35	learned	learn	VERB
aiti-366	212	36	layers	layer	NOUN
aiti-366	212	37	.	.	PUNCT
aiti-366	213	1	among	among	ADP
aiti-366	213	2	these	these	DET
aiti-366	213	3	layers	layer	NOUN
aiti-366	213	4	five	five	NUM
aiti-366	213	5	of	of	ADP
aiti-366	213	6	these	these	DET
aiti-366	213	7	layers	layer	NOUN
aiti-366	213	8	are	be	AUX
aiti-366	213	9	convolutional	convolutional	ADJ
aiti-366	213	10	layer	layer	NOUN
aiti-366	213	11	and	and	CCONJ
aiti-366	213	12	remaining	remain	VERB
aiti-366	213	13	four	four	NUM
aiti-366	213	14	are	be	AUX
aiti-366	213	15	fully	fully	ADV
aiti-366	213	16	connected	connected	ADJ
aiti-366	213	17	layers	layer	NOUN
aiti-366	213	18	.	.	PUNCT
aiti-366	214	1	like	like	ADP
aiti-366	214	2	alexnet	alexnet	NOUN
aiti-366	214	3	,	,	PUNCT
aiti-366	214	4	first	first	ADJ
aiti-366	214	5	convolution	convolution	NOUN
aiti-366	214	6	layer	layer	NOUN
aiti-366	214	7	of	of	ADP
aiti-366	214	8	proposed	propose	VERB
aiti-366	214	9	model	model	NOUN
aiti-366	214	10	takes	take	VERB
aiti-366	214	11	the	the	DET
aiti-366	214	12	input	input	NOUN
aiti-366	214	13	images	image	NOUN
aiti-366	214	14	by	by	ADP
aiti-366	214	15	filtering	filter	VERB
aiti-366	214	16	each	each	PRON
aiti-366	214	17	of	of	ADP
aiti-366	214	18	the	the	DET
aiti-366	214	19	images	image	NOUN
aiti-366	214	20	into	into	ADP
aiti-366	214	21	224×224	224×224	NUM
aiti-366	214	22	size	size	NOUN
aiti-366	214	23	with	with	ADP
aiti-366	214	24	96	96	NUM
aiti-366	214	25	kernels	kernel	NOUN
aiti-366	214	26	.	.	PUNCT
aiti-366	215	1	the	the	DET
aiti-366	215	2	second	second	ADJ
aiti-366	215	3	layer	layer	NOUN
aiti-366	215	4	takes	take	VERB
aiti-366	215	5	the	the	DET
aiti-366	215	6	input	input	NOUN
aiti-366	215	7	from	from	ADP
aiti-366	215	8	first	first	ADJ
aiti-366	215	9	convolution	convolution	NOUN
aiti-366	215	10	layer	layer	NOUN
aiti-366	215	11	after	after	ADP
aiti-366	215	12	passing	pass	VERB
aiti-366	215	13	through	through	ADP
aiti-366	215	14	a	a	DET
aiti-366	215	15	pooling	pool	VERB
aiti-366	215	16	layer	layer	NOUN
aiti-366	215	17	.	.	PUNCT
aiti-366	216	1	pooling	pool	VERB
aiti-366	216	2	layers	layer	NOUN
aiti-366	216	3	are	be	AUX
aiti-366	216	4	added	add	VERB
aiti-366	216	5	after	after	ADP
aiti-366	216	6	first	first	ADJ
aiti-366	216	7	,	,	PUNCT
aiti-366	216	8	second	second	ADJ
aiti-366	216	9	and	and	CCONJ
aiti-366	216	10	fifth	fifth	ADJ
aiti-366	216	11	convolution	convolution	NOUN
aiti-366	216	12	layer	layer	NOUN
aiti-366	216	13	like	like	ADP
aiti-366	216	14	alexnet	alexnet	NOUN
aiti-366	216	15	.	.	PUNCT
aiti-366	217	1	a	a	DET
aiti-366	217	2	new	new	ADJ
aiti-366	217	3	fully	fully	ADV
aiti-366	217	4	connected	connect	VERB
aiti-366	217	5	layer	layer	NOUN
aiti-366	217	6	(	(	PUNCT
aiti-366	217	7	fc3	fc3	PROPN
aiti-366	217	8	)	)	PUNCT
aiti-366	217	9	which	which	PRON
aiti-366	217	10	takes	take	VERB
aiti-366	217	11	input	input	NOUN
aiti-366	217	12	from	from	ADP
aiti-366	217	13	the	the	DET
aiti-366	217	14	output	output	NOUN
aiti-366	217	15	of	of	ADP
aiti-366	217	16	second	second	ADV
aiti-366	217	17	fully	fully	ADV
aiti-366	217	18	connected	connect	VERB
aiti-366	217	19	layer	layer	NOUN
aiti-366	217	20	(	(	PUNCT
aiti-366	217	21	fc2	fc2	PROPN
aiti-366	217	22	)	)	PUNCT
aiti-366	217	23	has	have	AUX
aiti-366	217	24	been	be	AUX
aiti-366	217	25	added	add	VERB
aiti-366	217	26	in	in	ADP
aiti-366	217	27	this	this	DET
aiti-366	217	28	proposed	propose	VERB
aiti-366	217	29	model	model	NOUN
aiti-366	217	30	.	.	PUNCT
aiti-366	218	1	output	output	NOUN
aiti-366	218	2	of	of	ADP
aiti-366	218	3	the	the	DET
aiti-366	218	4	last	last	ADJ
aiti-366	218	5	layer	layer	NOUN
aiti-366	218	6	(	(	PUNCT
aiti-366	218	7	fc4	fc4	PROPN
aiti-366	218	8	)	)	PUNCT
aiti-366	218	9	is	be	AUX
aiti-366	218	10	connected	connect	VERB
aiti-366	218	11	to	to	ADP
aiti-366	218	12	a	a	DET
aiti-366	218	13	softmax	softmax	NOUN
aiti-366	218	14	layer	layer	NOUN
aiti-366	218	15	for	for	ADP
aiti-366	218	16	classifying	classify	VERB
aiti-366	218	17	the	the	DET
aiti-366	218	18	categories	category	NOUN
aiti-366	218	19	.	.	PUNCT
aiti-366	219	1	the	the	DET
aiti-366	219	2	proposed	propose	VERB
aiti-366	219	3	model	model	NOUN
aiti-366	219	4	used	use	VERB
aiti-366	219	5	data	datum	NOUN
aiti-366	219	6	augmentation	augmentation	NOUN
aiti-366	219	7	technique	technique	NOUN
aiti-366	219	8	to	to	PART
aiti-366	219	9	reduce	reduce	VERB
aiti-366	219	10	overfitting	overfitting	NOUN
aiti-366	219	11	in	in	ADP
aiti-366	219	12	the	the	DET
aiti-366	219	13	training	training	NOUN
aiti-366	219	14	stage	stage	NOUN
aiti-366	219	15	.	.	PUNCT
aiti-366	220	1	because	because	SCONJ
aiti-366	220	2	,	,	PUNCT
aiti-366	220	3	recent	recent	ADJ
aiti-366	220	4	works	work	NOUN
aiti-366	220	5	show	show	VERB
aiti-366	220	6	that	that	SCONJ
aiti-366	220	7	data	datum	NOUN
aiti-366	220	8	augmentation	augmentation	NOUN
aiti-366	220	9	also	also	ADV
aiti-366	220	10	helps	help	VERB
aiti-366	220	11	to	to	PART
aiti-366	220	12	improve	improve	VERB
aiti-366	220	13	classification	classification	NOUN
aiti-366	220	14	performance	performance	NOUN
aiti-366	220	15	[	[	X
aiti-366	220	16	7	7	NUM
aiti-366	220	17	]	]	PUNCT
aiti-366	220	18	.	.	PUNCT
aiti-366	221	1	the	the	DET
aiti-366	221	2	full	full	ADJ
aiti-366	221	3	architecture	architecture	NOUN
aiti-366	221	4	of	of	ADP
aiti-366	221	5	the	the	DET
aiti-366	221	6	proposed	propose	VERB
aiti-366	221	7	model	model	NOUN
aiti-366	221	8	is	be	AUX
aiti-366	221	9	shown	show	VERB
aiti-366	221	10	in	in	ADP
aiti-366	221	11	fig	fig	NOUN
aiti-366	221	12	.	.	PUNCT
aiti-366	222	1	4	4	NUM
aiti-366	222	2	.	.	X
aiti-366	222	3	3.4	3.4	NUM
aiti-366	222	4	.	.	PUNCT
aiti-366	223	1	datasets	dataset	NOUN
aiti-366	223	2	fig	fig	NOUN
aiti-366	223	3	.	.	PUNCT
aiti-366	224	1	5	5	NUM
aiti-366	224	2	example	example	NOUN
aiti-366	224	3	of	of	ADP
aiti-366	224	4	clothing	clothing	NOUN
aiti-366	224	5	attribute	attribute	NOUN
aiti-366	224	6	dataset	dataset	NOUN
aiti-366	224	7	:	:	PUNCT
aiti-366	224	8	column	column	NOUN
aiti-366	224	9	1	1	NUM
aiti-366	224	10	to	to	PART
aiti-366	224	11	6	6	NUM
aiti-366	224	12	represents	represent	VERB
aiti-366	224	13	example	example	NOUN
aiti-366	224	14	of	of	ADP
aiti-366	224	15	floral	floral	ADJ
aiti-366	224	16	,	,	PUNCT
aiti-366	224	17	graphics	graphic	NOUN
aiti-366	224	18	,	,	PUNCT
aiti-366	224	19	plaid	plaid	NOUN
aiti-366	224	20	,	,	PUNCT
aiti-366	224	21	solid	solid	ADJ
aiti-366	224	22	color	color	NOUN
aiti-366	224	23	,	,	PUNCT
aiti-366	224	24	spotted	spot	VERB
aiti-366	224	25	and	and	CCONJ
aiti-366	224	26	stripe	stripe	VERB
aiti-366	224	27	respectively	respectively	ADV
aiti-366	224	28	fig	fig	NOUN
aiti-366	224	29	.	.	PUNCT
aiti-366	225	1	6	6	NUM
aiti-366	225	2	example	example	NOUN
aiti-366	225	3	images	image	NOUN
aiti-366	225	4	from	from	ADP
aiti-366	225	5	fashion	fashion	NOUN
aiti-366	225	6	dataset	dataset	NOUN
aiti-366	225	7	:	:	PUNCT
aiti-366	225	8	each	each	PRON
aiti-366	225	9	of	of	ADP
aiti-366	225	10	the	the	DET
aiti-366	225	11	row	row	NOUN
aiti-366	225	12	represents	represent	VERB
aiti-366	225	13	jeans	jean	NOUN
aiti-366	225	14	,	,	PUNCT
aiti-366	225	15	leather	leather	NOUN
aiti-366	225	16	,	,	PUNCT
aiti-366	225	17	print	print	NOUN
aiti-366	225	18	,	,	PUNCT
aiti-366	225	19	single	single	ADJ
aiti-366	225	20	co	co	X
aiti-366	225	21	lor	lor	NOUN
aiti-366	225	22	and	and	CCONJ
aiti-366	225	23	stripe	stripe	NOUN
aiti-366	225	24	category	category	NOUN
aiti-366	225	25	respectively	respectively	ADV
aiti-366	225	26	two	two	NUM
aiti-366	225	27	publicly	publicly	ADV
aiti-366	225	28	available	available	ADJ
aiti-366	225	29	datasets	dataset	NOUN
aiti-366	225	30	:	:	PUNCT
aiti-366	225	31	fashion	fashion	NOUN
aiti-366	225	32	[	[	X
aiti-366	225	33	31	31	NUM
aiti-366	225	34	]	]	PUNCT
aiti-366	225	35	and	and	CCONJ
aiti-366	225	36	clothing	clothing	NOUN
aiti-366	225	37	attribute	attribute	NOUN
aiti-366	225	38	datasets	dataset	NOUN
aiti-366	225	39	(	(	PUNCT
aiti-366	225	40	cad	cad	NOUN
aiti-366	225	41	)	)	PUNCT
aiti-366	226	1	[	[	X
aiti-366	226	2	32	32	NUM
aiti-366	226	3	]	]	PUNCT
aiti-366	226	4	that	that	PRON
aiti-366	226	5	was	be	AUX
aiti-366	226	6	originally	originally	ADV
aiti-366	226	7	created	create	VERB
aiti-366	226	8	for	for	ADP
aiti-366	226	9	garment	garment	NOUN
aiti-366	226	10	product	product	NOUN
aiti-366	226	11	recognition	recognition	NOUN
aiti-366	226	12	have	have	AUX
aiti-366	226	13	been	be	AUX
aiti-366	226	14	considered	consider	VERB
aiti-366	226	15	for	for	ADP
aiti-366	226	16	this	this	DET
aiti-366	226	17	research	research	NOUN
aiti-366	226	18	.	.	PUNCT
aiti-366	227	1	from	from	ADP
aiti-366	227	2	fashion	fashion	NOUN
aiti-366	227	3	dataset	dataset	NOUN
aiti-366	227	4	,	,	PUNCT
aiti-366	227	5	5400	5400	NUM
aiti-366	227	6	images	image	NOUN
aiti-366	227	7	are	be	AUX
aiti-366	227	8	manually	manually	ADV
aiti-366	227	9	selected	select	VERB
aiti-366	227	10	and	and	CCONJ
aiti-366	227	11	categorized	categorize	VERB
aiti-366	227	12	into	into	ADP
aiti-366	227	13	five	five	NUM
aiti-366	227	14	design	design	NOUN
aiti-366	227	15	classes	class	NOUN
aiti-366	227	16	,	,	PUNCT
aiti-366	227	17	namely	namely	ADV
aiti-366	227	18	“	"	PUNCT
aiti-366	227	19	single	single	ADJ
aiti-366	227	20	color	color	NOUN
aiti-366	227	21	”	"	PUNCT
aiti-366	227	22	(	(	PUNCT
aiti-366	227	23	2440	2440	NUM
aiti-366	227	24	images	image	NOUN
aiti-366	227	25	)	)	PUNCT
aiti-366	227	26	,	,	PUNCT
aiti-366	227	27	“	"	PUNCT
aiti-366	227	28	print	print	NOUN
aiti-366	227	29	”	"	PUNCT
aiti-366	227	30	(	(	PUNCT
aiti-366	227	31	1141	1141	NUM
aiti-366	227	32	images	image	NOUN
aiti-366	227	33	)	)	PUNCT
aiti-366	227	34	,	,	PUNCT
aiti-366	227	35	“	"	PUNCT
aiti-366	227	36	stripe	stripe	NOUN
aiti-366	227	37	”	"	PUNCT
aiti-366	227	38	(	(	PUNCT
aiti-366	227	39	565	565	NUM
aiti-366	227	40	images	image	NOUN
aiti-366	227	41	)	)	PUNCT
aiti-366	227	42	,	,	PUNCT
aiti-366	227	43	“	"	PUNCT
aiti-366	227	44	jeans	jean	NOUN
aiti-366	227	45	”	"	PUNCT
aiti-366	227	46	(	(	PUNCT
aiti-366	227	47	614	614	NUM
aiti-366	227	48	images	image	NOUN
aiti-366	227	49	)	)	PUNCT
aiti-366	227	50	and	and	CCONJ
aiti-366	227	51	“	"	PUNCT
aiti-366	227	52	leather	leather	NOUN
aiti-366	227	53	”	"	PUNCT
aiti-366	227	54	(	(	PUNCT
aiti-366	227	55	640	640	NUM
aiti-366	227	56	images	image	NOUN
aiti-366	227	57	)	)	PUNCT
aiti-366	227	58	.	.	PUNCT
aiti-366	228	1	again	again	ADV
aiti-366	228	2	from	from	ADP
aiti-366	228	3	clothing	clothing	NOUN
aiti-366	228	4	attribute	attribute	NOUN
aiti-366	228	5	dataset	dataset	NOUN
aiti-366	228	6	;	;	PUNCT
aiti-366	228	7	1575	1575	NUM
aiti-366	228	8	images	image	NOUN
aiti-366	228	9	and	and	CCONJ
aiti-366	228	10	manually	manually	ADV
aiti-366	228	11	selected	select	VERB
aiti-366	228	12	and	and	CCONJ
aiti-366	228	13	categorized	categorize	VERB
aiti-366	228	14	into	into	ADP
aiti-366	228	15	six	six	NUM
aiti-366	228	16	different	different	ADJ
aiti-366	228	17	categories	category	NOUN
aiti-366	228	18	;	;	PUNCT
aiti-366	228	19	after	after	ADP
aiti-366	228	20	segmenting	segment	VERB
aiti-366	228	21	garments	garment	NOUN
aiti-366	228	22	area	area	NOUN
aiti-366	228	23	from	from	ADP
aiti-366	228	24	the	the	DET
aiti-366	228	25	original	original	ADJ
aiti-366	228	26	dataset	dataset	NOUN
aiti-366	228	27	.	.	PUNCT
aiti-366	229	1	the	the	DET
aiti-366	229	2	categories	category	NOUN
aiti-366	229	3	are	be	AUX
aiti-366	229	4	“	"	PUNCT
aiti-366	229	5	floral	floral	ADJ
aiti-366	229	6	”	"	PUNCT
aiti-366	229	7	(	(	PUNCT
aiti-366	229	8	69	69	NUM
aiti-366	229	9	images	image	NOUN
aiti-366	229	10	)	)	PUNCT
aiti-366	229	11	,	,	PUNCT
aiti-366	229	12	“	"	PUNCT
aiti-366	229	13	graphics	graphic	NOUN
aiti-366	229	14	”	"	PUNCT
aiti-366	229	15	(	(	PUNCT
aiti-366	229	16	110	110	NUM
aiti-366	229	17	images	image	NOUN
aiti-366	229	18	)	)	PUNCT
aiti-366	229	19	,	,	PUNCT
aiti-366	229	20	“	"	PUNCT
aiti-366	229	21	plaid	plaid	NOUN
aiti-366	229	22	”	"	PUNCT
aiti-366	229	23	(	(	PUNCT
aiti-366	229	24	105	105	NUM
aiti-366	229	25	images	image	NOUN
aiti-366	229	26	)	)	PUNCT
aiti-366	229	27	,	,	PUNCT
aiti-366	229	28	“	"	PUNCT
aiti-366	229	29	spotted	spot	VERB
aiti-366	229	30	”	"	PUNCT
aiti-366	229	31	(	(	PUNCT
aiti-366	229	32	100	100	NUM
aiti-366	229	33	images	image	NOUN
aiti-366	229	34	)	)	PUNCT
aiti-366	229	35	,	,	PUNCT
aiti-366	229	36	“	"	PUNCT
aiti-366	229	37	striped	stripe	VERB
aiti-366	229	38	”	"	PUNCT
aiti-366	229	39	(	(	PUNCT
aiti-366	229	40	140	140	NUM
aiti-366	229	41	images	image	NOUN
aiti-366	229	42	)	)	PUNCT
aiti-366	229	43	and	and	CCONJ
aiti-366	229	44	“	"	PUNCT
aiti-366	229	45	solid	solid	ADJ
aiti-366	229	46	”	"	PUNCT
aiti-366	229	47	advances	advance	NOUN
aiti-366	229	48	in	in	ADP
aiti-366	229	49	technology	technology	NOUN
aiti-366	229	50	innovation	innovation	NOUN
aiti-366	229	51	,	,	PUNCT
aiti-366	229	52	vol	vol	NOUN
aiti-366	229	53	.	.	PROPN
aiti-366	230	1	2	2	NUM
aiti-366	230	2	,	,	PUNCT
aiti-366	230	3	no	no	INTJ
aiti-366	230	4	.	.	NOUN
aiti-366	230	5	4	4	NUM
aiti-366	230	6	,	,	PUNCT
aiti-366	230	7	2017	2017	NUM
aiti-366	230	8	,	,	PUNCT
aiti-366	231	1	pp	pp	ADJ
aiti-366	231	2	.	.	PUNCT
aiti-366	232	1	119	119	NUM
aiti-366	232	2	125	125	NUM
aiti-366	232	3	123	123	NUM
aiti-366	232	4	copyright	copyright	NOUN
aiti-366	232	5	©	©	PROPN
aiti-366	232	6	taeti	taeti	PROPN
aiti-366	232	7	pattern	pattern	NOUN
aiti-366	232	8	(	(	PUNCT
aiti-366	232	9	1051images	1051images	NUM
aiti-366	232	10	)	)	PUNCT
aiti-366	232	11	.	.	PUNCT
aiti-366	233	1	original	original	ADJ
aiti-366	233	2	cad	cad	PROPN
aiti-366	233	3	contain	contain	VERB
aiti-366	233	4	1856	1856	NUM
aiti-366	233	5	different	different	ADJ
aiti-366	233	6	images	image	NOUN
aiti-366	233	7	with	with	ADP
aiti-366	233	8	26	26	NUM
aiti-366	233	9	ground	ground	NOUN
aiti-366	233	10	truth	truth	NOUN
aiti-366	233	11	clothing	clothing	NOUN
aiti-366	233	12	attributes	attribute	VERB
aiti-366	233	13	such	such	ADJ
aiti-366	233	14	as	as	ADP
aiti-366	233	15	necktie	necktie	NOUN
aiti-366	233	16	,	,	PUNCT
aiti-366	233	17	color	color	NOUN
aiti-366	233	18	,	,	PUNCT
aiti-366	233	19	pattern	pattern	NOUN
aiti-366	233	20	etc	etc	X
aiti-366	233	21	.	.	X
aiti-366	233	22	fig	fig	NOUN
aiti-366	233	23	.	.	PUNCT
aiti-366	234	1	5	5	NUM
aiti-366	234	2	and	and	CCONJ
aiti-366	234	3	fig	fig	NOUN
aiti-366	234	4	.	.	PUNCT
aiti-366	235	1	6	6	NUM
aiti-366	235	2	show	show	VERB
aiti-366	235	3	some	some	DET
aiti-366	235	4	sample	sample	NOUN
aiti-366	235	5	images	image	NOUN
aiti-366	235	6	from	from	ADP
aiti-366	235	7	“	"	PUNCT
aiti-366	235	8	fashion	fashion	NOUN
aiti-366	235	9	”	"	PUNCT
aiti-366	235	10	and	and	CCONJ
aiti-366	235	11	“	"	PUNCT
aiti-366	235	12	clothing	clothing	NOUN
aiti-366	235	13	attribute	attribute	NOUN
aiti-366	235	14	”	"	PUNCT
aiti-366	235	15	datasets	dataset	NOUN
aiti-366	235	16	used	use	VERB
aiti-366	235	17	in	in	ADP
aiti-366	235	18	our	our	PRON
aiti-366	235	19	work	work	NOUN
aiti-366	235	20	.	.	PUNCT
aiti-366	236	1	table	table	NOUN
aiti-366	236	2	1	1	NUM
aiti-366	236	3	describes	describe	VERB
aiti-366	236	4	proper	proper	ADJ
aiti-366	236	5	training	training	NOUN
aiti-366	236	6	and	and	CCONJ
aiti-366	236	7	validation	validation	NOUN
aiti-366	236	8	samples	sample	NOUN
aiti-366	236	9	about	about	ADP
aiti-366	236	10	clothing	clothing	NOUN
aiti-366	236	11	attribute	attribute	NOUN
aiti-366	236	12	and	and	CCONJ
aiti-366	236	13	fashion	fashion	NOUN
aiti-366	236	14	datasets	dataset	NOUN
aiti-366	236	15	.	.	PUNCT
aiti-366	237	1	for	for	SCONJ
aiti-366	237	2	clothing	clothing	NOUN
aiti-366	237	3	attribute	attribute	NOUN
aiti-366	237	4	dataset	dataset	PROPN
aiti-366	237	5	,	,	PUNCT
aiti-366	237	6	different	different	ADJ
aiti-366	237	7	training	training	NOUN
aiti-366	237	8	and	and	CCONJ
aiti-366	237	9	validation	validation	NOUN
aiti-366	237	10	samples	sample	NOUN
aiti-366	237	11	has	have	AUX
aiti-366	237	12	been	be	AUX
aiti-366	237	13	used	use	VERB
aiti-366	237	14	;	;	PUNCT
aiti-366	237	15	such	such	ADJ
aiti-366	237	16	as	as	ADP
aiti-366	237	17	10	10	NUM
aiti-366	237	18	,	,	PUNCT
aiti-366	237	19	20	20	NUM
aiti-366	237	20	,	,	PUNCT
aiti-366	237	21	30	30	NUM
aiti-366	237	22	images	image	NOUN
aiti-366	237	23	per	per	ADP
aiti-366	237	24	class	class	NOUN
aiti-366	237	25	for	for	ADP
aiti-366	237	26	training	training	NOUN
aiti-366	237	27	and	and	CCONJ
aiti-366	237	28	validation	validation	NOUN
aiti-366	237	29	,	,	PUNCT
aiti-366	237	30	and	and	CCONJ
aiti-366	237	31	rest	rest	NOUN
aiti-366	237	32	of	of	ADP
aiti-366	237	33	the	the	DET
aiti-366	237	34	images	image	NOUN
aiti-366	237	35	for	for	ADP
aiti-366	237	36	testing	testing	NOUN
aiti-366	237	37	to	to	PART
aiti-366	237	38	identify	identify	VERB
aiti-366	237	39	the	the	DET
aiti-366	237	40	classification	classification	NOUN
aiti-366	237	41	results	result	NOUN
aiti-366	237	42	.	.	PUNCT
aiti-366	238	1	in	in	ADP
aiti-366	238	2	fashion	fashion	NOUN
aiti-366	238	3	dataset	dataset	NOUN
aiti-366	238	4	,	,	PUNCT
aiti-366	238	5	60	60	NUM
aiti-366	238	6	,	,	PUNCT
aiti-366	238	7	100	100	NUM
aiti-366	238	8	,	,	PUNCT
aiti-366	238	9	200	200	NUM
aiti-366	238	10	and	and	CCONJ
aiti-366	238	11	300	300	NUM
aiti-366	238	12	images	image	NOUN
aiti-366	238	13	are	be	AUX
aiti-366	238	14	used	use	VERB
aiti-366	238	15	for	for	ADP
aiti-366	238	16	training	training	NOUN
aiti-366	238	17	and	and	CCONJ
aiti-366	238	18	10	10	NUM
aiti-366	238	19	,	,	PUNCT
aiti-366	238	20	10	10	NUM
aiti-366	238	21	,	,	PUNCT
aiti-366	238	22	20	20	NUM
aiti-366	238	23	and	and	CCONJ
aiti-366	238	24	30	30	NUM
aiti-366	238	25	images	image	NOUN
aiti-366	238	26	for	for	ADP
aiti-366	238	27	validation	validation	NOUN
aiti-366	238	28	and	and	CCONJ
aiti-366	238	29	rest	rest	NOUN
aiti-366	238	30	of	of	ADP
aiti-366	238	31	the	the	DET
aiti-366	238	32	images	image	NOUN
aiti-366	238	33	for	for	ADP
aiti-366	238	34	testing	testing	NOUN
aiti-366	238	35	respectively	respectively	ADV
aiti-366	238	36	.	.	PUNCT
aiti-366	239	1	table	table	NOUN
aiti-366	239	2	1	1	NUM
aiti-366	239	3	dataset	dataset	NOUN
aiti-366	239	4	used	use	VERB
aiti-366	239	5	for	for	ADP
aiti-366	239	6	experiments	experiment	NOUN
aiti-366	239	7	sample	sample	NOUN
aiti-366	239	8	with	with	ADP
aiti-366	239	9	different	different	ADJ
aiti-366	239	10	training	training	NOUN
aiti-366	239	11	and	and	CCONJ
aiti-366	239	12	validation	validation	NOUN
aiti-366	239	13	samples	sample	NOUN
aiti-366	239	14	databases	database	VERB
aiti-366	239	15	clothing	clothing	NOUN
aiti-366	239	16	attribute	attribute	NOUN
aiti-366	239	17	dataset	dataset	NOUN
aiti-366	239	18	(	(	PUNCT
aiti-366	239	19	cad	cad	NOUN
aiti-366	239	20	)	)	PUNCT
aiti-366	239	21	fashion	fashion	NOUN
aiti-366	239	22	dataset	dataset	NOUN
aiti-366	239	23	classes	class	NOUN
aiti-366	239	24	6	6	NUM
aiti-366	239	25	5	5	NUM
aiti-366	239	26	total	total	ADJ
aiti-366	239	27	samples	sample	NOUN
aiti-366	239	28	1575	1575	NUM
aiti-366	239	29	5400	5400	NUM
aiti-366	239	30	training	training	NOUN
aiti-366	239	31	sample	sample	NOUN
aiti-366	239	32	/	/	SYM
aiti-366	239	33	class	class	NOUN
aiti-366	239	34	i)10	i)10	PROPN
aiti-366	239	35	ii	ii	PROPN
aiti-366	239	36	)	)	PUNCT
aiti-366	239	37	20	20	NUM
aiti-366	239	38	iii	iii	NOUN
aiti-366	239	39	)	)	PUNCT
aiti-366	239	40	30	30	NUM
aiti-366	239	41	i	i	NOUN
aiti-366	239	42	)	)	PUNCT
aiti-366	239	43	60	60	NUM
aiti-366	239	44	ii	ii	NOUN
aiti-366	239	45	)	)	PUNCT
aiti-366	239	46	100	100	NUM
aiti-366	239	47	iii	iii	NOUN
aiti-366	239	48	)	)	PUNCT
aiti-366	239	49	200	200	NUM
aiti-366	239	50	iv	iv	NOUN
aiti-366	239	51	)	)	PUNCT
aiti-366	239	52	300	300	NUM
aiti-366	239	53	validation	validation	NOUN
aiti-366	239	54	sample	sample	NOUN
aiti-366	239	55	/	/	SYM
aiti-366	239	56	class	class	NOUN
aiti-366	239	57	i	i	NOUN
aiti-366	239	58	)	)	PUNCT
aiti-366	239	59	10	10	NUM
aiti-366	239	60	ii	ii	NOUN
aiti-366	239	61	)	)	PUNCT
aiti-366	239	62	20	20	NUM
aiti-366	239	63	iii	iii	NOUN
aiti-366	239	64	)	)	PUNCT
aiti-366	239	65	30	30	NUM
aiti-366	239	66	i	i	NOUN
aiti-366	239	67	)	)	PUNCT
aiti-366	239	68	10	10	NUM
aiti-366	239	69	ii	ii	NOUN
aiti-366	239	70	)	)	PUNCT
aiti-366	239	71	10	10	NUM
aiti-366	239	72	iii	iii	NOUN
aiti-366	239	73	)	)	PUNCT
aiti-366	239	74	20	20	NUM
aiti-366	239	75	iv	iv	NOUN
aiti-366	239	76	)	)	PUNCT
aiti-366	239	77	30	30	NUM
aiti-366	239	78	4	4	NUM
aiti-366	239	79	.	.	PUNCT
aiti-366	240	1	experimental	experimental	ADJ
aiti-366	240	2	result	result	NOUN
aiti-366	240	3	this	this	DET
aiti-366	240	4	section	section	NOUN
aiti-366	240	5	describes	describe	VERB
aiti-366	240	6	the	the	DET
aiti-366	240	7	experimental	experimental	ADJ
aiti-366	240	8	detail	detail	NOUN
aiti-366	240	9	and	and	CCONJ
aiti-366	240	10	divided	divide	VERB
aiti-366	240	11	into	into	ADP
aiti-366	240	12	two	two	NUM
aiti-366	240	13	sub	sub	NOUN
aiti-366	240	14	-	-	NOUN
aiti-366	240	15	sections	section	NOUN
aiti-366	240	16	.	.	PUNCT
aiti-366	241	1	first	first	ADJ
aiti-366	241	2	sub	sub	NOUN
aiti-366	241	3	-	-	NOUN
aiti-366	241	4	section	section	NOUN
aiti-366	241	5	discusses	discuss	VERB
aiti-366	241	6	about	about	ADP
aiti-366	241	7	the	the	DET
aiti-366	241	8	implementation	implementation	NOUN
aiti-366	241	9	environment	environment	NOUN
aiti-366	241	10	and	and	CCONJ
aiti-366	241	11	next	next	ADJ
aiti-366	241	12	one	one	NOUN
aiti-366	241	13	describes	describe	VERB
aiti-366	241	14	the	the	DET
aiti-366	241	15	results	result	NOUN
aiti-366	241	16	.	.	PUNCT
aiti-366	242	1	4.1	4.1	NUM
aiti-366	242	2	.	.	PUNCT
aiti-366	242	3	implementation	implementation	NOUN
aiti-366	242	4	environment	environment	NOUN
aiti-366	242	5	experimentation	experimentation	NOUN
aiti-366	242	6	environment	environment	NOUN
aiti-366	242	7	for	for	ADP
aiti-366	242	8	this	this	DET
aiti-366	242	9	research	research	NOUN
aiti-366	242	10	has	have	AUX
aiti-366	242	11	been	be	AUX
aiti-366	242	12	set	set	VERB
aiti-366	242	13	by	by	ADP
aiti-366	242	14	following	follow	VERB
aiti-366	242	15	a	a	DET
aiti-366	242	16	straightforward	straightforward	ADJ
aiti-366	242	17	process	process	NOUN
aiti-366	242	18	.	.	PUNCT
aiti-366	243	1	we	we	PRON
aiti-366	243	2	fine	fine	ADV
aiti-366	243	3	-	-	PUNCT
aiti-366	243	4	tuned	tune	VERB
aiti-366	243	5	the	the	DET
aiti-366	243	6	caffenet	caffenet	NOUN
aiti-366	243	7	[	[	X
aiti-366	243	8	29	29	NUM
aiti-366	243	9	]	]	X
aiti-366	243	10	model	model	NOUN
aiti-366	243	11	and	and	CCONJ
aiti-366	243	12	use	use	VERB
aiti-366	243	13	ubuntu	ubuntu	NOUN
aiti-366	243	14	12.4	12.4	NUM
aiti-366	243	15	operating	operating	NOUN
aiti-366	243	16	system	system	NOUN
aiti-366	243	17	.	.	PUNCT
aiti-366	244	1	this	this	DET
aiti-366	244	2	research	research	NOUN
aiti-366	244	3	considered	consider	VERB
aiti-366	244	4	high	high	ADJ
aiti-366	244	5	speed	speed	NOUN
aiti-366	244	6	gpu	gpu	NOUN
aiti-366	244	7	for	for	ADP
aiti-366	244	8	making	make	VERB
aiti-366	244	9	the	the	DET
aiti-366	244	10	computation	computation	NOUN
aiti-366	244	11	faster	fast	ADV
aiti-366	244	12	.	.	PUNCT
aiti-366	245	1	because	because	SCONJ
aiti-366	245	2	cpu	cpu	NOUN
aiti-366	245	3	is	be	AUX
aiti-366	245	4	nearly	nearly	ADV
aiti-366	245	5	ten	ten	NUM
aiti-366	245	6	times	time	NOUN
aiti-366	245	7	slower	slow	ADJ
aiti-366	245	8	than	than	ADP
aiti-366	245	9	gpu	gpu	NOUN
aiti-366	245	10	for	for	ADP
aiti-366	245	11	working	work	VERB
aiti-366	245	12	with	with	ADP
aiti-366	245	13	large	large	ADJ
aiti-366	245	14	datasets	dataset	NOUN
aiti-366	245	15	and	and	CCONJ
aiti-366	245	16	complex	complex	ADJ
aiti-366	245	17	cnn	cnn	PROPN
aiti-366	245	18	.	.	PUNCT
aiti-366	246	1	nvidia	nvidia	PROPN
aiti-366	246	2	geforce	geforce	PROPN
aiti-366	246	3	gtx	gtx	PROPN
aiti-366	246	4	950	950	NUM
aiti-366	246	5	4	4	NUM
aiti-366	246	6	gb	gb	PROPN
aiti-366	246	7	gpu	gpu	NOUN
aiti-366	246	8	and	and	CCONJ
aiti-366	246	9	intel	intel	PROPN
aiti-366	246	10	core	core	NOUN
aiti-366	246	11	i7	i7	NOUN
aiti-366	246	12	processor	processor	NOUN
aiti-366	246	13	has	have	AUX
aiti-366	246	14	been	be	AUX
aiti-366	246	15	used	use	VERB
aiti-366	246	16	for	for	ADP
aiti-366	246	17	faster	fast	ADJ
aiti-366	246	18	training	training	NOUN
aiti-366	246	19	and	and	CCONJ
aiti-366	246	20	testing	testing	NOUN
aiti-366	246	21	.	.	PUNCT
aiti-366	247	1	4.2	4.2	NUM
aiti-366	247	2	.	.	PUNCT
aiti-366	247	3	experimental	experimental	ADJ
aiti-366	247	4	result	result	NOUN
aiti-366	247	5	and	and	CCONJ
aiti-366	247	6	discussion	discussion	NOUN
aiti-366	247	7	this	this	DET
aiti-366	247	8	research	research	NOUN
aiti-366	247	9	mainly	mainly	ADV
aiti-366	247	10	experimented	experiment	VERB
aiti-366	247	11	on	on	ADP
aiti-366	247	12	two	two	NUM
aiti-366	247	13	existing	exist	VERB
aiti-366	247	14	deep	deep	ADJ
aiti-366	247	15	convolutional	convolutional	ADJ
aiti-366	247	16	neural	neural	ADJ
aiti-366	247	17	network	network	NOUN
aiti-366	247	18	models	model	NOUN
aiti-366	247	19	alongside	alongside	ADV
aiti-366	247	20	with	with	ADP
aiti-366	247	21	the	the	DET
aiti-366	247	22	proposed	propose	VERB
aiti-366	247	23	model	model	NOUN
aiti-366	247	24	on	on	ADP
aiti-366	247	25	fashion	fashion	NOUN
aiti-366	247	26	dataset	dataset	NOUN
aiti-366	247	27	and	and	CCONJ
aiti-366	247	28	clothing	clothing	NOUN
aiti-366	247	29	attribute	attribute	NOUN
aiti-366	247	30	dataset	dataset	NOUN
aiti-366	247	31	.	.	PUNCT
aiti-366	248	1	performance	performance	NOUN
aiti-366	248	2	of	of	ADP
aiti-366	248	3	the	the	DET
aiti-366	248	4	proposed	propose	VERB
aiti-366	248	5	deep	deep	ADJ
aiti-366	248	6	learning	learning	NOUN
aiti-366	248	7	model	model	NOUN
aiti-366	248	8	has	have	AUX
aiti-366	248	9	been	be	AUX
aiti-366	248	10	compared	compare	VERB
aiti-366	248	11	with	with	ADP
aiti-366	248	12	the	the	DET
aiti-366	248	13	existing	exist	VERB
aiti-366	248	14	models	model	NOUN
aiti-366	248	15	and	and	CCONJ
aiti-366	248	16	also	also	ADV
aiti-366	248	17	with	with	ADP
aiti-366	248	18	some	some	DET
aiti-366	248	19	existing	exist	VERB
aiti-366	248	20	well	well	ADV
aiti-366	248	21	-	-	PUNCT
aiti-366	248	22	known	know	VERB
aiti-366	248	23	hand	hand	NOUN
aiti-366	248	24	-	-	PUNCT
aiti-366	248	25	engineering	engineering	NOUN
aiti-366	248	26	feature	feature	NOUN
aiti-366	248	27	extraction	extraction	NOUN
aiti-366	248	28	approaches	approach	NOUN
aiti-366	248	29	for	for	ADP
aiti-366	248	30	garment	garment	NOUN
aiti-366	248	31	design	design	NOUN
aiti-366	248	32	class	class	NOUN
aiti-366	248	33	identification	identification	NOUN
aiti-366	248	34	.	.	PUNCT
aiti-366	249	1	different	different	ADJ
aiti-366	249	2	training	training	NOUN
aiti-366	249	3	,	,	PUNCT
aiti-366	249	4	validation	validation	NOUN
aiti-366	249	5	and	and	CCONJ
aiti-366	249	6	testing	testing	NOUN
aiti-366	249	7	sample	sample	NOUN
aiti-366	249	8	from	from	ADP
aiti-366	249	9	two	two	NUM
aiti-366	249	10	different	different	ADJ
aiti-366	249	11	datasets	dataset	NOUN
aiti-366	249	12	have	have	AUX
aiti-366	249	13	been	be	AUX
aiti-366	249	14	used	use	VERB
aiti-366	249	15	and	and	CCONJ
aiti-366	249	16	shown	show	VERB
aiti-366	249	17	in	in	ADP
aiti-366	249	18	table	table	NOUN
aiti-366	249	19	1	1	NUM
aiti-366	249	20	.	.	PUNCT
aiti-366	250	1	the	the	DET
aiti-366	250	2	training	training	NOUN
aiti-366	250	3	and	and	CCONJ
aiti-366	250	4	testing	testing	NOUN
aiti-366	250	5	results	result	NOUN
aiti-366	250	6	of	of	ADP
aiti-366	250	7	alexnet	alexnet	NOUN
aiti-366	250	8	,	,	PUNCT
aiti-366	250	9	vgg_s	vgg_s	ADJ
aiti-366	250	10	and	and	CCONJ
aiti-366	250	11	proposed	propose	VERB
aiti-366	250	12	model	model	NOUN
aiti-366	250	13	are	be	AUX
aiti-366	250	14	provided	provide	VERB
aiti-366	250	15	in	in	ADP
aiti-366	250	16	table	table	NOUN
aiti-366	250	17	2	2	NUM
aiti-366	250	18	,	,	PUNCT
aiti-366	250	19	table	table	NOUN
aiti-366	250	20	3	3	NUM
aiti-366	250	21	,	,	PUNCT
aiti-366	250	22	table	table	NOUN
aiti-366	250	23	4	4	NUM
aiti-366	250	24	,	,	PUNCT
aiti-366	250	25	and	and	CCONJ
aiti-366	250	26	table	table	NOUN
aiti-366	250	27	5	5	NUM
aiti-366	250	28	.	.	PUNCT
aiti-366	251	1	these	these	DET
aiti-366	251	2	accuracies	accuracy	NOUN
aiti-366	251	3	are	be	AUX
aiti-366	251	4	calculated	calculate	VERB
aiti-366	251	5	based	base	VERB
aiti-366	251	6	on	on	ADP
aiti-366	251	7	the	the	DET
aiti-366	251	8	training	training	NOUN
aiti-366	251	9	,	,	PUNCT
aiti-366	251	10	validation	validation	NOUN
aiti-366	251	11	samples	sample	NOUN
aiti-366	251	12	/	/	SYM
aiti-366	251	13	class	class	NOUN
aiti-366	251	14	used	use	VERB
aiti-366	251	15	for	for	ADP
aiti-366	251	16	each	each	DET
aiti-366	251	17	dataset	dataset	NOUN
aiti-366	251	18	.	.	PUNCT
aiti-366	252	1	from	from	ADP
aiti-366	252	2	table	table	NOUN
aiti-366	252	3	3	3	NUM
aiti-366	252	4	and	and	CCONJ
aiti-366	252	5	fig	fig	NOUN
aiti-366	252	6	.	.	PUNCT
aiti-366	253	1	7	7	NUM
aiti-366	253	2	it	it	PRON
aiti-366	253	3	can	can	AUX
aiti-366	253	4	be	be	AUX
aiti-366	253	5	found	find	VERB
aiti-366	253	6	that	that	SCONJ
aiti-366	253	7	in	in	ADP
aiti-366	253	8	most	most	ADJ
aiti-366	253	9	of	of	ADP
aiti-366	253	10	the	the	DET
aiti-366	253	11	cases	case	NOUN
aiti-366	253	12	vgg_s	vgg_s	ADJ
aiti-366	253	13	performs	perform	VERB
aiti-366	253	14	better	well	ADJ
aiti-366	253	15	than	than	ADP
aiti-366	253	16	alexnet	alexnet	ADJ
aiti-366	253	17	model	model	NOUN
aiti-366	253	18	.	.	PUNCT
aiti-366	254	1	table	table	NOUN
aiti-366	254	2	2	2	NUM
aiti-366	254	3	recognition	recognition	NOUN
aiti-366	254	4	rate	rate	NOUN
aiti-366	254	5	(	(	PUNCT
aiti-366	254	6	%	%	INTJ
aiti-366	254	7	)	)	PUNCT
aiti-366	254	8	in	in	ADP
aiti-366	254	9	training	training	NOUN
aiti-366	254	10	phase	phase	NOUN
aiti-366	254	11	of	of	ADP
aiti-366	254	12	cad	cad	PROPN
aiti-366	254	13	dataset	dataset	NOUN
aiti-366	254	14	models	model	NOUN
aiti-366	254	15	training	train	VERB
aiti-366	254	16	sample	sample	NOUN
aiti-366	254	17	validation	validation	NOUN
aiti-366	254	18	sample	sample	NOUN
aiti-366	254	19	results	result	VERB
aiti-366	254	20	cad	cad	NOUN
aiti-366	254	21	with	with	ADP
aiti-366	254	22	6	6	NUM
aiti-366	254	23	classes	class	NOUN
aiti-366	254	24	alexnet	alexnet	NOUN
aiti-366	254	25	10	10	NUM
aiti-366	254	26	10	10	NUM
aiti-366	254	27	75.1	75.1	NUM
aiti-366	254	28	20	20	NUM
aiti-366	254	29	20	20	NUM
aiti-366	254	30	75.6	75.6	NUM
aiti-366	254	31	30	30	NUM
aiti-366	254	32	30	30	NUM
aiti-366	254	33	75.5	75.5	NUM
aiti-366	254	34	vgg_s	vgg_s	NOUN
aiti-366	254	35	10	10	NUM
aiti-366	254	36	10	10	NUM
aiti-366	254	37	76.2	76.2	NUM
aiti-366	254	38	20	20	NUM
aiti-366	254	39	20	20	NUM
aiti-366	254	40	76.5	76.5	NUM
aiti-366	254	41	30	30	NUM
aiti-366	254	42	30	30	NUM
aiti-366	254	43	76.6	76.6	NUM
aiti-366	254	44	proposed	propose	VERB
aiti-366	254	45	model	model	NOUN
aiti-366	254	46	10	10	NUM
aiti-366	254	47	10	10	NUM
aiti-366	254	48	77.2	77.2	NUM
aiti-366	254	49	20	20	NUM
aiti-366	254	50	20	20	NUM
aiti-366	254	51	77.3	77.3	NUM
aiti-366	254	52	30	30	NUM
aiti-366	254	53	30	30	NUM
aiti-366	254	54	77.7	77.7	NUM
aiti-366	254	55	table	table	NOUN
aiti-366	254	56	3	3	NUM
aiti-366	254	57	recognition	recognition	NOUN
aiti-366	254	58	rate	rate	NOUN
aiti-366	254	59	(	(	PUNCT
aiti-366	254	60	%	%	INTJ
aiti-366	254	61	)	)	PUNCT
aiti-366	254	62	in	in	ADP
aiti-366	254	63	testing	testing	NOUN
aiti-366	254	64	phase	phase	NOUN
aiti-366	254	65	of	of	ADP
aiti-366	254	66	cad	cad	PROPN
aiti-366	254	67	dataset	dataset	NOUN
aiti-366	254	68	models	model	NOUN
aiti-366	254	69	training	train	VERB
aiti-366	254	70	sample	sample	NOUN
aiti-366	254	71	validation	validation	NOUN
aiti-366	254	72	sample	sample	NOUN
aiti-366	254	73	results	result	VERB
aiti-366	254	74	cad	cad	NOUN
aiti-366	254	75	with	with	ADP
aiti-366	254	76	6	6	NUM
aiti-366	254	77	classes	class	NOUN
aiti-366	254	78	alexnet	alexnet	NOUN
aiti-366	254	79	10	10	NUM
aiti-366	254	80	10	10	NUM
aiti-366	254	81	75.3	75.3	NUM
aiti-366	254	82	20	20	NUM
aiti-366	254	83	20	20	NUM
aiti-366	254	84	75.5	75.5	NUM
aiti-366	254	85	30	30	NUM
aiti-366	254	86	30	30	NUM
aiti-366	254	87	75.6	75.6	NUM
aiti-366	254	88	vgg_s	vgg_s	NOUN
aiti-366	254	89	10	10	NUM
aiti-366	254	90	10	10	NUM
aiti-366	254	91	76.5	76.5	NUM
aiti-366	254	92	20	20	NUM
aiti-366	254	93	20	20	NUM
aiti-366	254	94	76.4	76.4	NUM
aiti-366	254	95	30	30	NUM
aiti-366	254	96	30	30	NUM
aiti-366	254	97	76.8	76.8	NUM
aiti-366	254	98	proposed	propose	VERB
aiti-366	254	99	model	model	NOUN
aiti-366	254	100	10	10	NUM
aiti-366	254	101	10	10	NUM
aiti-366	254	102	77.1	77.1	NUM
aiti-366	254	103	20	20	NUM
aiti-366	254	104	20	20	NUM
aiti-366	254	105	77.4	77.4	NUM
aiti-366	254	106	30	30	NUM
aiti-366	254	107	30	30	NUM
aiti-366	254	108	77.8	77.8	NUM
aiti-366	254	109	table	table	NOUN
aiti-366	254	110	4	4	NUM
aiti-366	254	111	recognition	recognition	NOUN
aiti-366	254	112	rate	rate	NOUN
aiti-366	254	113	(	(	PUNCT
aiti-366	254	114	%	%	INTJ
aiti-366	254	115	)	)	PUNCT
aiti-366	254	116	in	in	ADP
aiti-366	254	117	training	training	NOUN
aiti-366	254	118	phase	phase	NOUN
aiti-366	254	119	of	of	ADP
aiti-366	254	120	fashion	fashion	NOUN
aiti-366	254	121	dataset	dataset	NOUN
aiti-366	254	122	dataset	dataset	NOUN
aiti-366	254	123	models	model	NOUN
aiti-366	254	124	training	train	VERB
aiti-366	254	125	sample	sample	NOUN
aiti-366	254	126	validation	validation	NOUN
aiti-366	254	127	sample	sample	NOUN
aiti-366	254	128	results	result	VERB
aiti-366	254	129	fashion	fashion	NOUN
aiti-366	254	130	dataset	dataset	VERB
aiti-366	254	131	with	with	ADP
aiti-366	254	132	5	5	NUM
aiti-366	254	133	classes	class	NOUN
aiti-366	254	134	alexnet	alexnet	NOUN
aiti-366	254	135	60	60	NUM
aiti-366	254	136	10	10	NUM
aiti-366	254	137	74.3	74.3	NUM
aiti-366	254	138	100	100	NUM
aiti-366	254	139	10	10	NUM
aiti-366	254	140	75.9	75.9	NUM
aiti-366	254	141	200	200	NUM
aiti-366	254	142	20	20	NUM
aiti-366	254	143	78.1	78.1	NUM
aiti-366	254	144	300	300	NUM
aiti-366	254	145	30	30	NUM
aiti-366	254	146	81.5	81.5	NUM
aiti-366	254	147	vgg_s	vgg_s	ADP
aiti-366	254	148	60	60	NUM
aiti-366	254	149	10	10	NUM
aiti-366	254	150	75.3	75.3	NUM
aiti-366	254	151	100	100	NUM
aiti-366	254	152	10	10	NUM
aiti-366	254	153	76.8	76.8	NUM
aiti-366	254	154	200	200	NUM
aiti-366	254	155	20	20	NUM
aiti-366	254	156	78.6	78.6	NUM
aiti-366	254	157	300	300	NUM
aiti-366	254	158	30	30	NUM
aiti-366	254	159	82.7	82.7	NUM
aiti-366	254	160	proposed	propose	VERB
aiti-366	254	161	model	model	NOUN
aiti-366	254	162	60	60	NUM
aiti-366	254	163	10	10	NUM
aiti-366	254	164	76.6	76.6	NUM
aiti-366	254	165	100	100	NUM
aiti-366	254	166	10	10	NUM
aiti-366	254	167	78.1	78.1	NUM
aiti-366	254	168	200	200	NUM
aiti-366	254	169	20	20	NUM
aiti-366	254	170	81.1	81.1	NUM
aiti-366	254	171	300	300	NUM
aiti-366	254	172	30	30	NUM
aiti-366	254	173	84.1	84.1	NUM
aiti-366	254	174	table	table	NOUN
aiti-366	254	175	5	5	NUM
aiti-366	254	176	recognition	recognition	NOUN
aiti-366	254	177	rate	rate	NOUN
aiti-366	254	178	(	(	PUNCT
aiti-366	254	179	%	%	INTJ
aiti-366	254	180	)	)	PUNCT
aiti-366	254	181	in	in	ADP
aiti-366	254	182	testing	testing	NOUN
aiti-366	254	183	phase	phase	NOUN
aiti-366	254	184	of	of	ADP
aiti-366	254	185	fashion	fashion	NOUN
aiti-366	254	186	dataset	dataset	NOUN
aiti-366	254	187	dataset	dataset	NOUN
aiti-366	254	188	models	model	NOUN
aiti-366	254	189	training	train	VERB
aiti-366	254	190	sample	sample	NOUN
aiti-366	254	191	validation	validation	NOUN
aiti-366	254	192	sample	sample	NOUN
aiti-366	254	193	results	result	VERB
aiti-366	254	194	fashion	fashion	NOUN
aiti-366	254	195	dataset	dataset	VERB
aiti-366	254	196	with	with	ADP
aiti-366	254	197	5	5	NUM
aiti-366	254	198	classes	class	NOUN
aiti-366	254	199	alexnet	alexnet	NOUN
aiti-366	254	200	60	60	NUM
aiti-366	254	201	10	10	NUM
aiti-366	254	202	74.8	74.8	NUM
aiti-366	254	203	100	100	NUM
aiti-366	254	204	10	10	NUM
aiti-366	254	205	76.6	76.6	NUM
aiti-366	254	206	200	200	NUM
aiti-366	254	207	20	20	NUM
aiti-366	254	208	79.1	79.1	NUM
aiti-366	254	209	300	300	NUM
aiti-366	254	210	30	30	NUM
aiti-366	254	211	81.8	81.8	NUM
aiti-366	254	212	vgg_s	vgg_s	ADP
aiti-366	254	213	60	60	NUM
aiti-366	254	214	10	10	NUM
aiti-366	254	215	76.1	76.1	NUM
aiti-366	254	216	100	100	NUM
aiti-366	254	217	10	10	NUM
aiti-366	254	218	77.3	77.3	NUM
aiti-366	254	219	200	200	NUM
aiti-366	254	220	20	20	NUM
aiti-366	254	221	80.8	80.8	NUM
aiti-366	254	222	300	300	NUM
aiti-366	254	223	30	30	NUM
aiti-366	254	224	82.9	82.9	NUM
aiti-366	254	225	proposed	propose	VERB
aiti-366	254	226	model	model	NOUN
aiti-366	254	227	60	60	NUM
aiti-366	254	228	10	10	NUM
aiti-366	254	229	76.7	76.7	NUM
aiti-366	254	230	100	100	NUM
aiti-366	254	231	10	10	NUM
aiti-366	254	232	78.1	78.1	NUM
aiti-366	254	233	200	200	NUM
aiti-366	254	234	20	20	NUM
aiti-366	254	235	82.7	82.7	NUM
aiti-366	254	236	300	300	NUM
aiti-366	254	237	30	30	NUM
aiti-366	254	238	84.5	84.5	NUM
aiti-366	254	239	using	use	VERB
aiti-366	254	240	clothing	clothing	NOUN
aiti-366	254	241	attribute	attribute	NOUN
aiti-366	254	242	dataset	dataset	NOUN
aiti-366	254	243	,	,	PUNCT
aiti-366	254	244	alexnet	alexnet	PROPN
aiti-366	254	245	and	and	CCONJ
aiti-366	254	246	vgg_s	vgg_s	ADJ
aiti-366	254	247	model	model	NOUN
aiti-366	254	248	of	of	ADP
aiti-366	254	249	cnn	cnn	PROPN
aiti-366	254	250	shows	show	VERB
aiti-366	254	251	maximum	maximum	ADJ
aiti-366	254	252	75.6	75.6	NUM
aiti-366	254	253	%	%	NOUN
aiti-366	254	254	and	and	CCONJ
aiti-366	254	255	76.8	76.8	NUM
aiti-366	254	256	%	%	NOUN
aiti-366	254	257	accuracies	accuracy	NOUN
aiti-366	254	258	respectively	respectively	ADV
aiti-366	254	259	while	while	SCONJ
aiti-366	254	260	our	our	PRON
aiti-366	254	261	proposed	propose	VERB
aiti-366	254	262	model	model	NOUN
aiti-366	254	263	of	of	ADP
aiti-366	254	264	cnn	cnn	PROPN
aiti-366	254	265	achieved	achieve	VERB
aiti-366	254	266	77.8	77.8	NUM
aiti-366	254	267	%	%	NOUN
aiti-366	254	268	accuracy	accuracy	NOUN
aiti-366	254	269	.	.	PUNCT
aiti-366	255	1	on	on	ADP
aiti-366	255	2	the	the	DET
aiti-366	255	3	other	other	ADJ
aiti-366	255	4	hand	hand	NOUN
aiti-366	255	5	,	,	PUNCT
aiti-366	255	6	using	use	VERB
aiti-366	255	7	fashion	fashion	NOUN
aiti-366	255	8	dataset	dataset	NOUN
aiti-366	255	9	with	with	ADP
aiti-366	255	10	5	5	NUM
aiti-366	255	11	different	different	ADJ
aiti-366	255	12	classes	class	NOUN
aiti-366	255	13	,	,	PUNCT
aiti-366	255	14	81.8	81.8	NUM
aiti-366	255	15	%	%	NOUN
aiti-366	255	16	accuracy	accuracy	NOUN
aiti-366	255	17	has	have	AUX
aiti-366	255	18	been	be	AUX
aiti-366	255	19	achieved	achieve	VERB
aiti-366	255	20	using	use	VERB
aiti-366	255	21	alexnet	alexnet	NOUN
aiti-366	255	22	and	and	CCONJ
aiti-366	255	23	82.9	82.9	NUM
aiti-366	255	24	%	%	NOUN
aiti-366	255	25	accuracy	accuracy	NOUN
aiti-366	255	26	using	use	VERB
aiti-366	255	27	vgg_s	vgg_s	NOUN
aiti-366	255	28	respectively	respectively	ADV
aiti-366	255	29	and	and	CCONJ
aiti-366	255	30	advances	advance	NOUN
aiti-366	255	31	in	in	ADP
aiti-366	255	32	technology	technology	NOUN
aiti-366	255	33	innovation	innovation	NOUN
aiti-366	255	34	,	,	PUNCT
aiti-366	255	35	vol	vol	NOUN
aiti-366	255	36	.	.	PROPN
aiti-366	256	1	2	2	NUM
aiti-366	256	2	,	,	PUNCT
aiti-366	256	3	no	no	INTJ
aiti-366	256	4	.	.	NOUN
aiti-366	256	5	4	4	NUM
aiti-366	256	6	,	,	PUNCT
aiti-366	256	7	2017	2017	NUM
aiti-366	256	8	,	,	PUNCT
aiti-366	256	9	pp	pp	ADJ
aiti-366	256	10	.	.	PUNCT
aiti-366	257	1	119	119	NUM
aiti-366	257	2	125	125	NUM
aiti-366	257	3	124	124	NUM
aiti-366	257	4	copyright	copyright	NOUN
aiti-366	257	5	©	©	PROPN
aiti-366	257	6	taeti	taeti	PROPN
aiti-366	257	7	copyright	copyright	NOUN
aiti-366	257	8	©	©	PROPN
aiti-366	257	9	taeti	taeti	PROPN
aiti-366	258	1	copyright	copyright	NOUN
aiti-366	258	2	©	©	PROPN
aiti-366	258	3	taeti	taeti	PROPN
aiti-366	259	1	copyright	copyright	NOUN
aiti-366	259	2	©	©	PROPN
aiti-366	259	3	taeti	taeti	PROPN
aiti-366	260	1	copyright	copyright	NOUN
aiti-366	260	2	©	©	PROPN
aiti-366	260	3	taeti	taeti	PROPN
aiti-366	260	4	our	our	PRON
aiti-366	260	5	proposed	propose	VERB
aiti-366	260	6	model	model	NOUN
aiti-366	260	7	achieved	achieve	VERB
aiti-366	260	8	84.5	84.5	NUM
aiti-366	260	9	%	%	NOUN
aiti-366	260	10	accuracy	accuracy	NOUN
aiti-366	260	11	.	.	PUNCT
aiti-366	261	1	from	from	ADP
aiti-366	261	2	table	table	NOUN
aiti-366	261	3	3	3	NUM
aiti-366	261	4	and	and	CCONJ
aiti-366	261	5	table	table	NOUN
aiti-366	261	6	5	5	NUM
aiti-366	261	7	,	,	PUNCT
aiti-366	261	8	it	it	PRON
aiti-366	261	9	is	be	AUX
aiti-366	261	10	clear	clear	ADJ
aiti-366	261	11	that	that	SCONJ
aiti-366	261	12	more	more	ADJ
aiti-366	261	13	training	training	NOUN
aiti-366	261	14	sample	sample	NOUN
aiti-366	261	15	increase	increase	VERB
aiti-366	261	16	the	the	DET
aiti-366	261	17	accuracy	accuracy	NOUN
aiti-366	261	18	.	.	PUNCT
aiti-366	262	1	table	table	NOUN
aiti-366	262	2	6	6	NUM
aiti-366	262	3	and	and	CCONJ
aiti-366	262	4	table	table	NOUN
aiti-366	262	5	7	7	NUM
aiti-366	262	6	describe	describe	VERB
aiti-366	262	7	the	the	DET
aiti-366	262	8	experimental	experimental	ADJ
aiti-366	262	9	results	result	NOUN
aiti-366	262	10	using	use	VERB
aiti-366	262	11	seven	seven	NUM
aiti-366	262	12	different	different	ADJ
aiti-366	262	13	hand	hand	NOUN
aiti-366	262	14	-	-	PUNCT
aiti-366	262	15	engineered	engineer	VERB
aiti-366	262	16	feature	feature	NOUN
aiti-366	262	17	extraction	extraction	NOUN
aiti-366	262	18	methods	method	NOUN
aiti-366	262	19	which	which	PRON
aiti-366	262	20	are	be	AUX
aiti-366	262	21	hog	hog	NOUN
aiti-366	262	22	,	,	PUNCT
aiti-366	262	23	gist	gist	NOUN
aiti-366	262	24	,	,	PUNCT
aiti-366	262	25	lgp	lgp	NOUN
aiti-366	262	26	,	,	PUNCT
aiti-366	262	27	centrist	centrist	NOUN
aiti-366	262	28	,	,	PUNCT
aiti-366	262	29	tcentrist	tcentrist	NOUN
aiti-366	262	30	,	,	PUNCT
aiti-366	262	31	ccentrist	ccentrist	NOUN
aiti-366	262	32	,	,	PUNCT
aiti-366	262	33	and	and	CCONJ
aiti-366	262	34	nabp	nabp	VERB
aiti-366	262	35	on	on	ADP
aiti-366	262	36	clothing	clothing	NOUN
aiti-366	262	37	attribute	attribute	NOUN
aiti-366	262	38	dataset	dataset	NOUN
aiti-366	262	39	and	and	CCONJ
aiti-366	262	40	fashion	fashion	NOUN
aiti-366	262	41	dataset	dataset	NOUN
aiti-366	262	42	.	.	PUNCT
aiti-366	263	1	for	for	ADP
aiti-366	263	2	these	these	DET
aiti-366	263	3	methods	method	NOUN
aiti-366	263	4	support	support	VERB
aiti-366	263	5	vector	vector	NOUN
aiti-366	263	6	machine	machine	NOUN
aiti-366	263	7	(	(	PUNCT
aiti-366	263	8	svm	svm	PROPN
aiti-366	263	9	)	)	PUNCT
aiti-366	263	10	was	be	AUX
aiti-366	263	11	used	use	VERB
aiti-366	263	12	for	for	ADP
aiti-366	263	13	classification	classification	NOUN
aiti-366	263	14	purpose	purpose	NOUN
aiti-366	263	15	.	.	PUNCT
aiti-366	264	1	table	table	NOUN
aiti-366	264	2	6	6	NUM
aiti-366	264	3	experimental	experimental	ADJ
aiti-366	264	4	results	result	NOUN
aiti-366	264	5	of	of	ADP
aiti-366	264	6	different	different	ADJ
aiti-366	264	7	methods	method	NOUN
aiti-366	264	8	for	for	ADP
aiti-366	264	9	clothing	clothing	NOUN
aiti-366	264	10	attribute	attribute	NOUN
aiti-366	264	11	dataset	dataset	NOUN
aiti-366	264	12	method	method	NOUN
aiti-366	264	13	accuracy	accuracy	NOUN
aiti-366	264	14	hog	hog	NOUN
aiti-366	264	15	63.76	63.76	NUM
aiti-366	264	16	%	%	NOUN
aiti-366	264	17	gist	gist	NOUN
aiti-366	264	18	72.31	72.31	NUM
aiti-366	264	19	%	%	NOUN
aiti-366	264	20	lgp	lgp	PROPN
aiti-366	264	21	65.55	65.55	NUM
aiti-366	264	22	%	%	NOUN
aiti-366	264	23	centrist	centrist	NOUN
aiti-366	264	24	71.97	71.97	NUM
aiti-366	264	25	%	%	NOUN
aiti-366	264	26	tcentrist	tcentrist	NOUN
aiti-366	264	27	74.48	74.48	NUM
aiti-366	264	28	%	%	NOUN
aiti-366	264	29	ccentrist	ccentrist	NOUN
aiti-366	264	30	74.97	74.97	NUM
aiti-366	264	31	%	%	NOUN
aiti-366	264	32	nabp	nabp	NOUN
aiti-366	264	33	74.18	74.18	NUM
aiti-366	264	34	%	%	NOUN
aiti-366	264	35	berkeley	berkeley	NOUN
aiti-366	264	36	73.54	73.54	NUM
aiti-366	264	37	%	%	NOUN
aiti-366	264	38	alexnet	alexnet	NOUN
aiti-366	264	39	(	(	PUNCT
aiti-366	264	40	30	30	NUM
aiti-366	264	41	)	)	PUNCT
aiti-366	264	42	75.6	75.6	NUM
aiti-366	264	43	%	%	NOUN
aiti-366	264	44	vgg_s	vgg_s	NOUN
aiti-366	264	45	(	(	PUNCT
aiti-366	264	46	30	30	NUM
aiti-366	264	47	)	)	PUNCT
aiti-366	264	48	76.8	76.8	NUM
aiti-366	264	49	%	%	NOUN
aiti-366	264	50	proposed	propose	VERB
aiti-366	264	51	model	model	NOUN
aiti-366	264	52	77.8	77.8	NUM
aiti-366	264	53	%	%	NOUN
aiti-366	264	54	table	table	NOUN
aiti-366	264	55	7	7	NUM
aiti-366	264	56	experimental	experimental	ADJ
aiti-366	264	57	results	result	NOUN
aiti-366	264	58	of	of	ADP
aiti-366	264	59	different	different	ADJ
aiti-366	264	60	methods	method	NOUN
aiti-366	264	61	for	for	ADP
aiti-366	264	62	fashion	fashion	NOUN
aiti-366	264	63	dataset	dataset	NOUN
aiti-366	264	64	method	method	NOUN
aiti-366	264	65	accuracy	accuracy	NOUN
aiti-366	264	66	hog	hog	NOUN
aiti-366	264	67	79.15	79.15	NUM
aiti-366	264	68	%	%	NOUN
aiti-366	264	69	gist	gist	NOUN
aiti-366	264	70	81.67	81.67	NUM
aiti-366	264	71	%	%	NOUN
aiti-366	264	72	lgp	lgp	PROPN
aiti-366	264	73	79.79	79.79	NUM
aiti-366	264	74	%	%	NOUN
aiti-366	264	75	centrist	centrist	NOUN
aiti-366	264	76	79.72	79.72	NUM
aiti-366	264	77	%	%	NOUN
aiti-366	264	78	tcentrist	tcentrist	NOUN
aiti-366	264	79	84.07	84.07	NUM
aiti-366	264	80	%	%	NOUN
aiti-366	264	81	ccentrist	ccentrist	NOUN
aiti-366	264	82	84.23	84.23	NUM
aiti-366	264	83	%	%	NOUN
aiti-366	264	84	nabp	nabp	NOUN
aiti-366	264	85	83.22	83.22	NUM
aiti-366	264	86	%	%	NOUN
aiti-366	264	87	alexnet	alexnet	ADJ
aiti-366	264	88	81.8	81.8	NUM
aiti-366	264	89	%	%	NOUN
aiti-366	264	90	vgg_s	vgg_s	ADJ
aiti-366	264	91	82.9	82.9	NUM
aiti-366	264	92	%	%	NOUN
aiti-366	264	93	proposed	propose	VERB
aiti-366	264	94	model	model	NOUN
aiti-366	264	95	84.5	84.5	NUM
aiti-366	264	96	%	%	NOUN
aiti-366	264	97	table	table	NOUN
aiti-366	264	98	6	6	NUM
aiti-366	264	99	also	also	ADV
aiti-366	264	100	shows	show	VERB
aiti-366	264	101	the	the	DET
aiti-366	264	102	result	result	NOUN
aiti-366	264	103	of	of	ADP
aiti-366	264	104	three	three	NUM
aiti-366	264	105	deep	deep	ADJ
aiti-366	264	106	learning	learning	NOUN
aiti-366	264	107	models	model	NOUN
aiti-366	264	108	berkeley	berkeley	PROPN
aiti-366	264	109	,	,	PUNCT
aiti-366	264	110	alexnet	alexnet	PROPN
aiti-366	264	111	,	,	PUNCT
aiti-366	264	112	vgg_s	vgg_s	ADV
aiti-366	264	113	along	along	ADV
aiti-366	264	114	with	with	ADP
aiti-366	264	115	our	our	PRON
aiti-366	264	116	proposed	propose	VERB
aiti-366	264	117	model	model	NOUN
aiti-366	264	118	for	for	SCONJ
aiti-366	264	119	clothing	clothing	NOUN
aiti-366	264	120	attribute	attribute	NOUN
aiti-366	264	121	dataset	dataset	VERB
aiti-366	264	122	.	.	PUNCT
aiti-366	265	1	from	from	ADP
aiti-366	265	2	this	this	DET
aiti-366	265	3	table	table	NOUN
aiti-366	265	4	,	,	PUNCT
aiti-366	265	5	it	it	PRON
aiti-366	265	6	is	be	AUX
aiti-366	265	7	clear	clear	ADJ
aiti-366	265	8	that	that	SCONJ
aiti-366	265	9	performance	performance	NOUN
aiti-366	265	10	of	of	ADP
aiti-366	265	11	different	different	ADJ
aiti-366	265	12	deep	deep	ADJ
aiti-366	265	13	learning	learning	NOUN
aiti-366	265	14	models	model	NOUN
aiti-366	265	15	are	be	AUX
aiti-366	265	16	better	well	ADJ
aiti-366	265	17	than	than	ADP
aiti-366	265	18	any	any	DET
aiti-366	265	19	hand	hand	NOUN
aiti-366	265	20	-	-	PUNCT
aiti-366	265	21	engineering	engineering	NOUN
aiti-366	265	22	feature	feature	NOUN
aiti-366	265	23	extraction	extraction	NOUN
aiti-366	265	24	method	method	NOUN
aiti-366	265	25	for	for	ADP
aiti-366	265	26	clothing	clothing	NOUN
aiti-366	265	27	attribute	attribute	NOUN
aiti-366	265	28	dataset	dataset	VERB
aiti-366	265	29	.	.	PUNCT
aiti-366	266	1	table	table	NOUN
aiti-366	266	2	7	7	NUM
aiti-366	266	3	shows	show	VERB
aiti-366	266	4	that	that	SCONJ
aiti-366	266	5	,	,	PUNCT
aiti-366	266	6	for	for	ADP
aiti-366	266	7	fashion	fashion	NOUN
aiti-366	266	8	dataset	dataset	VERB
aiti-366	266	9	our	our	PRON
aiti-366	266	10	proposed	propose	VERB
aiti-366	266	11	method	method	NOUN
aiti-366	266	12	performs	perform	VERB
aiti-366	266	13	better	well	ADV
aiti-366	266	14	.	.	PUNCT
aiti-366	267	1	though	though	SCONJ
aiti-366	267	2	alexnet	alexnet	PROPN
aiti-366	267	3	and	and	CCONJ
aiti-366	267	4	vgg_s	vgg_s	PROPN
aiti-366	267	5	show	show	VERB
aiti-366	267	6	slightly	slightly	ADV
aiti-366	267	7	less	less	ADJ
aiti-366	267	8	accuracy	accuracy	NOUN
aiti-366	267	9	than	than	ADP
aiti-366	267	10	tcentrist	tcentrist	NOUN
aiti-366	267	11	,	,	PUNCT
aiti-366	267	12	ccentrist	ccentrist	NOUN
aiti-366	267	13	and	and	CCONJ
aiti-366	267	14	nabp	nabp	PROPN
aiti-366	267	15	.	.	PUNCT
aiti-366	268	1	fig	fig	NOUN
aiti-366	268	2	.	.	PUNCT
aiti-366	269	1	7	7	NUM
aiti-366	269	2	comparison	comparison	NOUN
aiti-366	269	3	between	between	ADP
aiti-366	269	4	alexnet	alexnet	NOUN
aiti-366	269	5	,	,	PUNCT
aiti-366	269	6	vgg	vgg	PROPN
aiti-366	269	7	s	s	X
aiti-366	269	8	and	and	CCONJ
aiti-366	269	9	our	our	PRON
aiti-366	269	10	proposed	propose	VERB
aiti-366	269	11	models	model	NOUN
aiti-366	269	12	for	for	ADP
aiti-366	269	13	clothing	clothing	NOUN
aiti-366	269	14	attribute	attribute	NOUN
aiti-366	269	15	dataset	dataset	VERB
aiti-366	269	16	fig	fig	NOUN
aiti-366	269	17	.	.	PUNCT
aiti-366	270	1	8	8	NUM
aiti-366	270	2	comparison	comparison	NOUN
aiti-366	270	3	between	between	ADP
aiti-366	270	4	alexnet	alexnet	NOUN
aiti-366	270	5	,	,	PUNCT
aiti-366	270	6	vgg	vgg	PROPN
aiti-366	270	7	s	s	X
aiti-366	270	8	and	and	CCONJ
aiti-366	270	9	our	our	PRON
aiti-366	270	10	proposed	propose	VERB
aiti-366	270	11	models	model	NOUN
aiti-366	270	12	for	for	ADP
aiti-366	270	13	fashion	fashion	NOUN
aiti-366	270	14	dataset	dataset	NOUN
aiti-366	270	15	5	5	NUM
aiti-366	270	16	.	.	PUNCT
aiti-366	270	17	conclusion	conclusion	NOUN
aiti-366	270	18	in	in	ADP
aiti-366	270	19	this	this	DET
aiti-366	270	20	paper	paper	NOUN
aiti-366	270	21	,	,	PUNCT
aiti-366	270	22	some	some	DET
aiti-366	270	23	deep	deep	ADJ
aiti-366	270	24	cnn	cnn	PROPN
aiti-366	270	25	models	model	NOUN
aiti-366	270	26	for	for	ADP
aiti-366	270	27	identifying	identify	VERB
aiti-366	270	28	garments	garment	NOUN
aiti-366	270	29	design	design	NOUN
aiti-366	270	30	class	class	NOUN
aiti-366	270	31	along	along	ADP
aiti-366	270	32	with	with	ADP
aiti-366	270	33	our	our	PRON
aiti-366	270	34	proposed	propose	VERB
aiti-366	270	35	cnn	cnn	PROPN
aiti-366	270	36	have	have	AUX
aiti-366	270	37	been	be	AUX
aiti-366	270	38	used	use	VERB
aiti-366	270	39	and	and	CCONJ
aiti-366	270	40	also	also	ADV
aiti-366	270	41	the	the	DET
aiti-366	270	42	results	result	NOUN
aiti-366	270	43	are	be	AUX
aiti-366	270	44	compared	compare	VERB
aiti-366	270	45	with	with	ADP
aiti-366	270	46	several	several	ADJ
aiti-366	270	47	hand	hand	NOUN
aiti-366	270	48	-	-	PUNCT
aiti-366	270	49	engineered	engineer	VERB
aiti-366	270	50	feature	feature	NOUN
aiti-366	270	51	extraction	extraction	NOUN
aiti-366	270	52	methods	method	NOUN
aiti-366	270	53	.	.	PUNCT
aiti-366	271	1	using	use	VERB
aiti-366	271	2	two	two	NUM
aiti-366	271	3	different	different	ADJ
aiti-366	271	4	datasets	dataset	NOUN
aiti-366	271	5	,	,	PUNCT
aiti-366	271	6	this	this	PRON
aiti-366	271	7	proposed	propose	VERB
aiti-366	271	8	deep	deep	ADJ
aiti-366	271	9	convolutional	convolutional	ADJ
aiti-366	271	10	neural	neural	ADJ
aiti-366	271	11	network	network	NOUN
aiti-366	271	12	with	with	ADP
aiti-366	271	13	five	five	NUM
aiti-366	271	14	convolutional	convolutional	ADJ
aiti-366	271	15	layers	layer	NOUN
aiti-366	271	16	and	and	CCONJ
aiti-366	271	17	four	four	NUM
aiti-366	271	18	fully	fully	ADV
aiti-366	271	19	connected	connect	VERB
aiti-366	271	20	layers	layer	NOUN
aiti-366	271	21	shows	show	VERB
aiti-366	271	22	better	well	ADJ
aiti-366	271	23	performance	performance	NOUN
aiti-366	271	24	than	than	ADP
aiti-366	271	25	some	some	DET
aiti-366	271	26	existing	exist	VERB
aiti-366	271	27	deep	deep	ADJ
aiti-366	271	28	convolutional	convolutional	ADJ
aiti-366	271	29	model	model	NOUN
aiti-366	271	30	as	as	ADV
aiti-366	271	31	well	well	ADV
aiti-366	271	32	as	as	ADP
aiti-366	271	33	several	several	ADJ
aiti-366	271	34	hand	hand	NOUN
aiti-366	271	35	-	-	PUNCT
aiti-366	271	36	engineered	engineer	VERB
aiti-366	271	37	feature	feature	NOUN
aiti-366	271	38	extraction	extraction	NOUN
aiti-366	271	39	methods	method	NOUN
aiti-366	271	40	.	.	PUNCT
aiti-366	272	1	fc	fc	PROPN
aiti-366	272	2	layers	layer	NOUN
aiti-366	272	3	and	and	CCONJ
aiti-366	272	4	convolutional	convolutional	ADJ
aiti-366	272	5	layers	layer	NOUN
aiti-366	272	6	used	use	VERB
aiti-366	272	7	in	in	ADP
aiti-366	272	8	a	a	DET
aiti-366	272	9	deep	deep	ADJ
aiti-366	272	10	cnn	cnn	NOUN
aiti-366	272	11	represent	represent	VERB
aiti-366	272	12	the	the	DET
aiti-366	272	13	features	feature	NOUN
aiti-366	272	14	more	more	ADV
aiti-366	272	15	elaborately	elaborately	ADV
aiti-366	272	16	,	,	PUNCT
aiti-366	272	17	which	which	PRON
aiti-366	272	18	are	be	AUX
aiti-366	272	19	stronger	strong	ADJ
aiti-366	272	20	than	than	ADP
aiti-366	272	21	any	any	PRON
aiti-366	272	22	of	of	ADP
aiti-366	272	23	hand	hand	NOUN
aiti-366	272	24	-	-	PUNCT
aiti-366	272	25	engineered	engineer	VERB
aiti-366	272	26	feature	feature	NOUN
aiti-366	272	27	extraction	extraction	NOUN
aiti-366	272	28	techniques	technique	NOUN
aiti-366	272	29	.	.	PUNCT
aiti-366	273	1	77.8	77.8	NUM
aiti-366	273	2	%	%	NOUN
aiti-366	273	3	accuracy	accuracy	NOUN
aiti-366	273	4	has	have	AUX
aiti-366	273	5	been	be	AUX
aiti-366	273	6	achieved	achieve	VERB
aiti-366	273	7	on	on	ADP
aiti-366	273	8	clothing	clothing	NOUN
aiti-366	273	9	attribute	attribute	NOUN
aiti-366	273	10	dataset	dataset	VERB
aiti-366	273	11	with	with	ADP
aiti-366	273	12	6	6	NUM
aiti-366	273	13	different	different	ADJ
aiti-366	273	14	classes	class	NOUN
aiti-366	273	15	and	and	CCONJ
aiti-366	273	16	84.5	84.5	NUM
aiti-366	273	17	%	%	NOUN
aiti-366	273	18	accuracy	accuracy	NOUN
aiti-366	273	19	on	on	ADP
aiti-366	273	20	fashion	fashion	NOUN
aiti-366	273	21	dataset	dataset	NOUN
aiti-366	273	22	containing	contain	VERB
aiti-366	273	23	5	5	NUM
aiti-366	273	24	texture	texture	NOUN
aiti-366	273	25	design	design	NOUN
aiti-366	273	26	categories	category	NOUN
aiti-366	273	27	using	use	VERB
aiti-366	273	28	the	the	DET
aiti-366	273	29	proposed	propose	VERB
aiti-366	273	30	model	model	NOUN
aiti-366	273	31	.	.	PUNCT
aiti-366	274	1	when	when	SCONJ
aiti-366	274	2	a	a	DET
aiti-366	274	3	database	database	NOUN
aiti-366	274	4	contains	contain	VERB
aiti-366	274	5	more	more	ADJ
aiti-366	274	6	generic	generic	ADJ
aiti-366	274	7	properties	property	NOUN
aiti-366	274	8	for	for	ADP
aiti-366	274	9	every	every	DET
aiti-366	274	10	class	class	NOUN
aiti-366	274	11	,	,	PUNCT
aiti-366	274	12	then	then	ADV
aiti-366	274	13	a	a	DET
aiti-366	274	14	deep	deep	ADJ
aiti-366	274	15	network	network	NOUN
aiti-366	274	16	can	can	AUX
aiti-366	274	17	extract	extract	VERB
aiti-366	274	18	the	the	DET
aiti-366	274	19	generic	generic	ADJ
aiti-366	274	20	features	feature	NOUN
aiti-366	274	21	easily	easily	ADV
aiti-366	274	22	and	and	CCONJ
aiti-366	274	23	accurately	accurately	ADV
aiti-366	274	24	.	.	PUNCT
aiti-366	275	1	it	it	PRON
aiti-366	275	2	is	be	AUX
aiti-366	275	3	mentioned	mention	VERB
aiti-366	275	4	earlier	early	ADV
aiti-366	275	5	that	that	SCONJ
aiti-366	275	6	the	the	DET
aiti-366	275	7	used	use	VERB
aiti-366	275	8	datasets	dataset	NOUN
aiti-366	275	9	were	be	AUX
aiti-366	275	10	manually	manually	ADV
aiti-366	275	11	categorized	categorize	VERB
aiti-366	275	12	in	in	ADP
aiti-366	275	13	different	different	ADJ
aiti-366	275	14	clothing	clothing	NOUN
aiti-366	275	15	product	product	NOUN
aiti-366	275	16	classes	class	NOUN
aiti-366	275	17	and	and	CCONJ
aiti-366	275	18	used	use	VERB
aiti-366	275	19	only	only	ADV
aiti-366	275	20	a	a	DET
aiti-366	275	21	few	few	ADJ
aiti-366	275	22	numbers	number	NOUN
aiti-366	275	23	of	of	ADP
aiti-366	275	24	classes	class	NOUN
aiti-366	275	25	.	.	PUNCT
aiti-366	276	1	for	for	ADP
aiti-366	276	2	this	this	DET
aiti-366	276	3	reason	reason	NOUN
aiti-366	276	4	,	,	PUNCT
aiti-366	276	5	the	the	DET
aiti-366	276	6	classes	class	NOUN
aiti-366	276	7	contain	contain	VERB
aiti-366	276	8	less	less	ADJ
aiti-366	276	9	generic	generic	ADJ
aiti-366	276	10	properties	property	NOUN
aiti-366	276	11	most	most	ADJ
aiti-366	276	12	of	of	ADP
aiti-366	276	13	the	the	DET
aiti-366	276	14	time	time	NOUN
aiti-366	276	15	.	.	PUNCT
aiti-366	277	1	additional	additional	ADJ
aiti-366	277	2	fc	fc	PROPN
aiti-366	277	3	layer	layer	NOUN
aiti-366	277	4	used	use	VERB
aiti-366	277	5	in	in	ADP
aiti-366	277	6	the	the	DET
aiti-366	277	7	proposed	propose	VERB
aiti-366	277	8	model	model	NOUN
aiti-366	277	9	helps	help	VERB
aiti-366	277	10	the	the	DET
aiti-366	277	11	model	model	NOUN
aiti-366	277	12	to	to	PART
aiti-366	277	13	understand	understand	VERB
aiti-366	277	14	the	the	DET
aiti-366	277	15	features	feature	NOUN
aiti-366	277	16	from	from	ADP
aiti-366	277	17	these	these	DET
aiti-366	277	18	datasets	dataset	NOUN
aiti-366	277	19	more	more	ADV
aiti-366	277	20	accurately	accurately	ADV
aiti-366	277	21	.	.	PUNCT
aiti-366	278	1	this	this	DET
aiti-366	278	2	research	research	NOUN
aiti-366	278	3	work	work	NOUN
aiti-366	278	4	will	will	AUX
aiti-366	278	5	help	help	VERB
aiti-366	278	6	other	other	ADJ
aiti-366	278	7	future	future	ADJ
aiti-366	278	8	researchers	researcher	NOUN
aiti-366	278	9	for	for	ADP
aiti-366	278	10	choosing	choose	VERB
aiti-366	278	11	appropriate	appropriate	ADJ
aiti-366	278	12	deep	deep	ADJ
aiti-366	278	13	learning	learning	NOUN
aiti-366	278	14	model	model	NOUN
aiti-366	278	15	for	for	ADP
aiti-366	278	16	garments	garment	NOUN
aiti-366	278	17	texture	texture	NOUN
aiti-366	278	18	design	design	NOUN
aiti-366	278	19	classification	classification	NOUN
aiti-366	278	20	.	.	PUNCT
aiti-366	279	1	in	in	ADP
aiti-366	279	2	future	future	NOUN
aiti-366	279	3	,	,	PUNCT
aiti-366	279	4	we	we	PRON
aiti-366	279	5	will	will	AUX
aiti-366	279	6	try	try	VERB
aiti-366	279	7	to	to	PART
aiti-366	279	8	improve	improve	VERB
aiti-366	279	9	the	the	DET
aiti-366	279	10	results	result	NOUN
aiti-366	279	11	by	by	ADP
aiti-366	279	12	adopting	adopt	VERB
aiti-366	279	13	more	more	ADV
aiti-366	279	14	sophisticated	sophisticated	ADJ
aiti-366	279	15	strategies	strategy	NOUN
aiti-366	279	16	.	.	PUNCT
aiti-366	280	1	acknowledgement	acknowledgement	NOUN
aiti-366	280	2	this	this	DET
aiti-366	280	3	research	research	NOUN
aiti-366	280	4	is	be	AUX
aiti-366	280	5	funded	fund	VERB
aiti-366	280	6	by	by	ADP
aiti-366	280	7	bangladesh	bangladesh	PROPN
aiti-366	280	8	university	university	PROPN
aiti-366	280	9	grants	grant	NOUN
aiti-366	280	10	commission	commission	PROPN
aiti-366	280	11	,	,	PUNCT
aiti-366	280	12	no	no	INTJ
aiti-366	280	13	:	:	PUNCT
aiti-366	280	14	reg	reg	NOUN
aiti-366	280	15	/	/	SYM
aiti-366	280	16	prosha-3/2016/46889	prosha-3/2016/46889	NOUN
aiti-366	280	17	.	.	PUNCT
aiti-366	281	1	references	reference	NOUN
aiti-366	281	2	[	[	X
aiti-366	281	3	1	1	X
aiti-366	281	4	]	]	PUNCT
aiti-366	281	5	j.	j.	PROPN
aiti-366	281	6	wu	wu	PROPN
aiti-366	281	7	and	and	CCONJ
aiti-366	281	8	j.	j.	PROPN
aiti-366	281	9	m.	m.	PROPN
aiti-366	281	10	rehg	rehg	PROPN
aiti-366	281	11	,	,	PUNCT
aiti-366	281	12	“	"	PUNCT
aiti-366	281	13	centrist	centrist	NOUN
aiti-366	281	14	:	:	PUNCT
aiti-366	281	15	a	a	DET
aiti-366	281	16	visual	visual	ADJ
aiti-366	281	17	descriptor	descriptor	NOUN
aiti-366	281	18	for	for	ADP
aiti-366	281	19	scene	scene	NOUN
aiti-366	281	20	categorization	categorization	NOUN
aiti-366	281	21	,	,	PUNCT
aiti-366	281	22	”	"	PUNCT
aiti-366	281	23	ieee	ieee	NOUN
aiti-366	281	24	transactions	transaction	NOUN
aiti-366	281	25	on	on	ADP
aiti-366	281	26	pattern	pattern	NOUN
aiti-366	281	27	analysis	analysis	NOUN
aiti-366	281	28	and	and	CCONJ
aiti-366	281	29	machine	machine	NOUN
aiti-366	281	30	intelligence	intelligence	NOUN
aiti-366	281	31	,	,	PUNCT
aiti-366	281	32	vol	vol	NOUN
aiti-366	281	33	.	.	PROPN
aiti-366	282	1	33	33	NUM
aiti-366	282	2	,	,	PUNCT
aiti-366	282	3	no	no	INTJ
aiti-366	282	4	.	.	NOUN
aiti-366	282	5	8	8	NUM
aiti-366	282	6	,	,	PUNCT
aiti-366	282	7	pp	pp	ADJ
aiti-366	282	8	.	.	PUNCT
aiti-366	282	9	1489	1489	NUM
aiti-366	282	10	-	-	SYM
aiti-366	282	11	1501	1501	NUM
aiti-366	282	12	,	,	PUNCT
aiti-366	282	13	august	august	PROPN
aiti-366	282	14	2011	2011	NUM
aiti-366	282	15	.	.	PUNCT
aiti-366	283	1	[	[	X
aiti-366	283	2	2	2	X
aiti-366	283	3	]	]	PUNCT
aiti-366	283	4	t.	t.	NOUN
aiti-366	283	5	ojala	ojala	PROPN
aiti-366	283	6	,	,	PUNCT
aiti-366	283	7	m.	m.	NOUN
aiti-366	283	8	piet	piet	PROPN
aiti-366	283	9	ikainen	ikainen	PROPN
aiti-366	283	10	and	and	CCONJ
aiti-366	283	11	t.	t.	NOUN
aiti-366	283	12	maenpaa	maenpaa	NOUN
aiti-366	283	13	,	,	PUNCT
aiti-366	283	14	“	"	PUNCT
aiti-366	283	15	mult	mult	PROPN
aiti-366	283	16	ireso	ireso	PROPN
aiti-366	283	17	lut	lut	PROPN
aiti-366	283	18	ion	ion	NOUN
aiti-366	283	19	g	g	PROPN
aiti-366	283	20	ray	ray	NOUN
aiti-366	283	21	-scale	-scale	PROPN
aiti-366	283	22	and	and	CCONJ
aiti-366	283	23	rotat	rotat	NOUN
aiti-366	283	24	ion	ion	NOUN
aiti-366	283	25	invariant	invariant	ADJ
aiti-366	283	26	texture	texture	ADJ
aiti-366	283	27	class	class	NOUN
aiti-366	283	28	ificat	ificat	NOUN
aiti-366	283	29	ion	ion	NOUN
aiti-366	283	30	with	with	ADP
aiti-366	283	31	local	local	ADJ
aiti-366	283	32	b	b	PROPN
aiti-366	283	33	inary	inary	ADJ
aiti-366	283	34	patterns	pattern	NOUN
aiti-366	283	35	,	,	PUNCT
aiti-366	283	36	”	"	PUNCT
aiti-366	283	37	ieee	ieee	NOUN
aiti-366	283	38	transact	transact	NOUN
aiti-366	283	39	ions	ion	NOUN
aiti-366	283	40	on	on	ADP
aiti-366	283	41	pattern	pattern	NOUN
aiti-366	283	42	analys	analy	NOUN
aiti-366	283	43	is	be	AUX
aiti-366	283	44	and	and	CCONJ
aiti-366	283	45	machine	machine	NOUN
aiti-366	283	46	intelligence	intelligence	NOUN
aiti-366	283	47	,	,	PUNCT
aiti-366	283	48	vol	vol	NOUN
aiti-366	283	49	.	.	PROPN
aiti-366	284	1	24	24	NUM
aiti-366	284	2	,	,	PUNCT
aiti-366	284	3	no	no	INTJ
aiti-366	284	4	.	.	NOUN
aiti-366	284	5	7	7	NUM
aiti-366	284	6	,	,	PUNCT
aiti-366	284	7	pp	pp	ADJ
aiti-366	284	8	.	.	PUNCT
aiti-366	285	1	971	971	NUM
aiti-366	285	2	-	-	SYM
aiti-366	285	3	987	987	NUM
aiti-366	285	4	,	,	PUNCT
aiti-366	285	5	2002	2002	NUM
aiti-366	285	6	.	.	PUNCT
aiti-366	286	1	advances	advance	NOUN
aiti-366	286	2	in	in	ADP
aiti-366	286	3	technology	technology	NOUN
aiti-366	286	4	innovation	innovation	NOUN
aiti-366	286	5	,	,	PUNCT
aiti-366	286	6	vol	vol	NOUN
aiti-366	286	7	.	.	PROPN
aiti-366	287	1	2	2	NUM
aiti-366	287	2	,	,	PUNCT
aiti-366	287	3	no	no	INTJ
aiti-366	287	4	.	.	NOUN
aiti-366	287	5	4	4	NUM
aiti-366	287	6	,	,	PUNCT
aiti-366	287	7	2017	2017	NUM
aiti-366	287	8	,	,	PUNCT
aiti-366	287	9	pp	pp	ADJ
aiti-366	287	10	.	.	PUNCT
aiti-366	288	1	119	119	NUM
aiti-366	288	2	125	125	NUM
aiti-366	288	3	125	125	NUM
aiti-366	288	4	copyright	copyright	NOUN
aiti-366	288	5	©	©	PROPN
aiti-366	288	6	taeti	taeti	NOUN
aiti-366	289	1	[	[	X
aiti-366	289	2	3	3	X
aiti-366	289	3	]	]	X
aiti-366	289	4	o.	o.	PROPN
aiti-366	289	5	l.	l.	PROPN
aiti-366	289	6	junior	junior	PROPN
aiti-366	289	7	,	,	PUNCT
aiti-366	289	8	d.	d.	PROPN
aiti-366	289	9	delgado	delgado	PROPN
aiti-366	289	10	,	,	PUNCT
aiti-366	289	11	v.	v.	PROPN
aiti-366	289	12	gonçalves	gonçalves	PROPN
aiti-366	289	13	and	and	CCONJ
aiti-366	289	14	u.	u.	PROPN
aiti-366	289	15	nunes	nunes	PROPN
aiti-366	289	16	,	,	PUNCT
aiti-366	289	17	“	"	PUNCT
aiti-366	289	18	trainable	trainable	ADJ
aiti-366	289	19	classifier	classifier	NOUN
aiti-366	289	20	-	-	PUNCT
aiti-366	289	21	fusion	fusion	NOUN
aiti-366	289	22	schemes	scheme	NOUN
aiti-366	289	23	:	:	PUNCT
aiti-366	289	24	an	an	DET
aiti-366	289	25	application	application	NOUN
aiti-366	289	26	to	to	ADP
aiti-366	289	27	pedestrian	pedestrian	NOUN
aiti-366	289	28	detection	detection	NOUN
aiti-366	289	29	,	,	PUNCT
aiti-366	289	30	”	"	PUNCT
aiti-366	289	31	proc	proc	NOUN
aiti-366	289	32	.	.	PUNCT
aiti-366	290	1	12th	12th	ADJ
aiti-366	290	2	international	international	ADJ
aiti-366	290	3	ieee	ieee	NOUN
aiti-366	290	4	conference	conference	NOUN
aiti-366	290	5	on	on	ADP
aiti-366	290	6	intelligent	intelligent	ADJ
aiti-366	290	7	transportation	transportation	NOUN
aiti-366	290	8	systems	system	NOUN
aiti-366	290	9	(	(	PUNCT
aiti-366	290	10	itcs	itcs	NOUN
aiti-366	290	11	09	09	NUM
aiti-366	290	12	)	)	PUNCT
aiti-366	290	13	,	,	PUNCT
aiti-366	290	14	ieee	ieee	NOUN
aiti-366	290	15	press	press	NOUN
aiti-366	290	16	,	,	PUNCT
aiti-366	290	17	pp	pp	ADJ
aiti-366	290	18	.	.	PUNCT
aiti-366	291	1	1	1	NUM
aiti-366	291	2	-	-	SYM
aiti-366	291	3	6	6	NUM
aiti-366	291	4	,	,	PUNCT
aiti-366	291	5	2009	2009	NUM
aiti-366	291	6	.	.	PUNCT
aiti-366	292	1	[	[	X
aiti-366	292	2	4	4	X
aiti-366	292	3	]	]	PUNCT
aiti-366	292	4	t.	t.	PROPN
aiti-366	292	5	x.	x.	PROPN
aiti-366	292	6	yang	yang	PROPN
aiti-366	292	7	and	and	CCONJ
aiti-366	292	8	b.	b.	PROPN
aiti-366	292	9	triggs	triggs	PROPN
aiti-366	292	10	,	,	PUNCT
aiti-366	292	11	“	"	PUNCT
aiti-366	292	12	enhanced	enhanced	ADJ
aiti-366	292	13	local	local	ADJ
aiti-366	292	14	texture	texture	ADJ
aiti-366	292	15	feature	feature	NOUN
aiti-366	292	16	sets	set	NOUN
aiti-366	292	17	for	for	ADP
aiti-366	292	18	face	face	NOUN
aiti-366	292	19	recognition	recognition	NOUN
aiti-366	292	20	under	under	ADP
aiti-366	292	21	difficult	difficult	ADJ
aiti-366	292	22	lighting	lighting	NOUN
aiti-366	292	23	conditions	condition	NOUN
aiti-366	292	24	,	,	PUNCT
aiti-366	292	25	”	"	PUNCT
aiti-366	292	26	ieee	ieee	NOUN
aiti-366	292	27	transactions	transaction	NOUN
aiti-366	292	28	on	on	ADP
aiti-366	292	29	image	image	NOUN
aiti-366	292	30	processing	processing	NOUN
aiti-366	292	31	,	,	PUNCT
aiti-366	292	32	vol	vol	NOUN
aiti-366	292	33	.	.	PROPN
aiti-366	292	34	19	19	NUM
aiti-366	292	35	,	,	PUNCT
aiti-366	292	36	no	no	INTJ
aiti-366	292	37	.	.	NOUN
aiti-366	292	38	6	6	NUM
aiti-366	292	39	,	,	PUNCT
aiti-366	292	40	pp	pp	ADJ
aiti-366	292	41	.	.	PUNCT
aiti-366	292	42	1635	1635	NUM
aiti-366	292	43	-	-	SYM
aiti-366	292	44	1650	1650	NUM
aiti-366	292	45	,	,	PUNCT
aiti-366	292	46	2010	2010	NUM
aiti-366	292	47	.	.	PUNCT
aiti-366	293	1	[	[	X
aiti-366	293	2	5	5	X
aiti-366	293	3	]	]	PUNCT
aiti-366	293	4	z.	z.	PROPN
aiti-366	293	5	guo	guo	PROPN
aiti-366	293	6	,	,	PUNCT
aiti-366	293	7	l.	l.	PROPN
aiti-366	293	8	zhang	zhang	PROPN
aiti-366	293	9	and	and	CCONJ
aiti-366	293	10	d.	d.	PROPN
aiti-366	293	11	zhang	zhang	PROPN
aiti-366	293	12	,	,	PUNCT
aiti-366	293	13	“	"	PUNCT
aiti-366	293	14	a	a	DET
aiti-366	293	15	completed	complete	VERB
aiti-366	293	16	modeling	modeling	NOUN
aiti-366	293	17	of	of	ADP
aiti-366	293	18	local	local	ADJ
aiti-366	293	19	binary	binary	ADJ
aiti-366	293	20	pattern	pattern	NOUN
aiti-366	293	21	operator	operator	NOUN
aiti-366	293	22	for	for	ADP
aiti-366	293	23	texture	texture	ADJ
aiti-366	293	24	classification	classification	NOUN
aiti-366	293	25	,	,	PUNCT
aiti-366	293	26	”	"	PUNCT
aiti-366	293	27	ieee	ieee	NOUN
aiti-366	293	28	transactions	transaction	NOUN
aiti-366	293	29	on	on	ADP
aiti-366	293	30	image	image	NOUN
aiti-366	293	31	processing	processing	NOUN
aiti-366	293	32	,	,	PUNCT
aiti-366	293	33	vol	vol	NOUN
aiti-366	293	34	.	.	PROPN
aiti-366	293	35	19	19	NUM
aiti-366	293	36	,	,	PUNCT
aiti-366	293	37	no	no	INTJ
aiti-366	293	38	.	.	NOUN
aiti-366	293	39	6	6	NUM
aiti-366	293	40	,	,	PUNCT
aiti-366	293	41	pp	pp	ADJ
aiti-366	293	42	.	.	PUNCT
aiti-366	293	43	1657	1657	NUM
aiti-366	293	44	-	-	SYM
aiti-366	293	45	1663	1663	NUM
aiti-366	293	46	,	,	PUNCT
aiti-366	293	47	2010	2010	NUM
aiti-366	293	48	.	.	PUNCT
aiti-366	294	1	[	[	X
aiti-366	294	2	6	6	NUM
aiti-366	294	3	]	]	PUNCT
aiti-366	294	4	e.	e.	PROPN
aiti-366	294	5	k.	k.	PROPN
aiti-366	294	6	dey	dey	PROPN
aiti-366	294	7	,	,	PUNCT
aiti-366	294	8	m.	m.	PROPN
aiti-366	294	9	n.	n.	PROPN
aiti-366	294	10	a.	a.	PROPN
aiti-366	294	11	tawhid	tawhid	PROPN
aiti-366	294	12	and	and	CCONJ
aiti-366	294	13	m.	m.	NOUN
aiti-366	294	14	shoyaib	shoyaib	PROPN
aiti-366	294	15	,	,	PUNCT
aiti-366	294	16	“	"	PUNCT
aiti-366	294	17	an	an	DET
aiti-366	294	18	automated	automate	VERB
aiti-366	294	19	system	system	NOUN
aiti-366	294	20	for	for	ADP
aiti-366	294	21	garment	garment	NOUN
aiti-366	294	22	texture	texture	NOUN
aiti-366	294	23	design	design	NOUN
aiti-366	294	24	class	class	NOUN
aiti-366	294	25	identification	identification	NOUN
aiti-366	294	26	,	,	PUNCT
aiti-366	294	27	”	"	PUNCT
aiti-366	294	28	computers	computer	NOUN
aiti-366	294	29	,	,	PUNCT
aiti-366	294	30	vol	vol	NOUN
aiti-366	294	31	.	.	PROPN
aiti-366	294	32	4	4	NUM
aiti-366	294	33	,	,	PUNCT
aiti-366	294	34	no	no	INTJ
aiti-366	294	35	.	.	NOUN
aiti-366	294	36	3	3	NUM
aiti-366	294	37	,	,	PUNCT
aiti-366	294	38	pp	pp	ADJ
aiti-366	294	39	.	.	PUNCT
aiti-366	295	1	265	265	NUM
aiti-366	295	2	-	-	SYM
aiti-366	295	3	282	282	NUM
aiti-366	295	4	,	,	PUNCT
aiti-366	295	5	2015	2015	NUM
aiti-366	295	6	.	.	PUNCT
aiti-366	296	1	[	[	X
aiti-366	296	2	7	7	NUM
aiti-366	296	3	]	]	PUNCT
aiti-366	296	4	a.	a.	NOUN
aiti-366	296	5	krizhevsky	krizhevsky	PROPN
aiti-366	296	6	,	,	PUNCT
aiti-366	296	7	i.	i.	PROPN
aiti-366	296	8	sutskever	sutskever	PROPN
aiti-366	296	9	and	and	CCONJ
aiti-366	296	10	g.	g.	PROPN
aiti-366	296	11	e.	e.	PROPN
aiti-366	296	12	hinton	hinton	PROPN
aiti-366	296	13	,	,	PUNCT
aiti-366	296	14	“	"	PUNCT
aiti-366	296	15	imagenet	imagenet	NOUN
aiti-366	296	16	classification	classification	NOUN
aiti-366	296	17	with	with	ADP
aiti-366	296	18	deep	deep	ADJ
aiti-366	296	19	convolutional	convolutional	ADJ
aiti-366	296	20	neural	neural	ADJ
aiti-366	296	21	networks	network	NOUN
aiti-366	296	22	,	,	PUNCT
aiti-366	296	23	”	"	PUNCT
aiti-366	296	24	proc	proc	NOUN
aiti-366	296	25	.	.	PUNCT
aiti-366	297	1	advances	advance	NOUN
aiti-366	297	2	in	in	ADP
aiti-366	297	3	neural	neural	ADJ
aiti-366	297	4	information	information	NOUN
aiti-366	297	5	processing	processing	NOUN
aiti-366	297	6	systems	system	NOUN
aiti-366	297	7	,	,	PUNCT
aiti-366	297	8	pp	pp	ADP
aiti-366	297	9	.	.	PUNCT
aiti-366	298	1	1097	1097	NUM
aiti-366	298	2	-	-	SYM
aiti-366	298	3	1105	1105	NUM
aiti-366	298	4	,	,	PUNCT
aiti-366	298	5	2012	2012	NUM
aiti-366	298	6	.	.	PUNCT
aiti-366	299	1	[	[	X
aiti-366	299	2	8	8	NUM
aiti-366	299	3	]	]	PUNCT
aiti-366	299	4	b.	b.	PROPN
aiti-366	299	5	zhou	zhou	PROPN
aiti-366	299	6	,	,	PUNCT
aiti-366	299	7	a.	a.	PROPN
aiti-366	299	8	lapedriza	lapedriza	PROPN
aiti-366	299	9	,	,	PUNCT
aiti-366	299	10	j.	j.	PROPN
aiti-366	299	11	xiao	xiao	PROPN
aiti-366	299	12	,	,	PUNCT
aiti-366	299	13	a.	a.	NOUN
aiti-366	299	14	torralba	torralba	PROPN
aiti-366	299	15	and	and	CCONJ
aiti-366	299	16	a.	a.	NOUN
aiti-366	299	17	oliva	oliva	PROPN
aiti-366	299	18	,	,	PUNCT
aiti-366	299	19	“	"	PUNCT
aiti-366	299	20	learning	learn	VERB
aiti-366	299	21	deep	deep	ADJ
aiti-366	299	22	features	feature	NOUN
aiti-366	299	23	for	for	ADP
aiti-366	299	24	scene	scene	NOUN
aiti-366	299	25	recognition	recognition	NOUN
aiti-366	299	26	using	use	VERB
aiti-366	299	27	places	place	NOUN
aiti-366	299	28	database	database	NOUN
aiti-366	299	29	,	,	PUNCT
aiti-366	299	30	”	"	PUNCT
aiti-366	299	31	proc	proc	NOUN
aiti-366	299	32	.	.	PUNCT
aiti-366	300	1	advances	advance	NOUN
aiti-366	300	2	in	in	ADP
aiti-366	300	3	neural	neural	ADJ
aiti-366	300	4	information	information	NOUN
aiti-366	300	5	processing	processing	NOUN
aiti-366	300	6	systems	system	NOUN
aiti-366	300	7	,	,	PUNCT
aiti-366	300	8	pp	pp	ADJ
aiti-366	300	9	.	.	PUNCT
aiti-366	301	1	487	487	NUM
aiti-366	301	2	-	-	SYM
aiti-366	301	3	495	495	NUM
aiti-366	301	4	,	,	PUNCT
aiti-366	301	5	2014	2014	NUM
aiti-366	301	6	.	.	PUNCT
aiti-366	302	1	[	[	X
aiti-366	302	2	9	9	NUM
aiti-366	302	3	]	]	PUNCT
aiti-366	302	4	k.	k.	PROPN
aiti-366	302	5	chatfield	chatfield	PROPN
aiti-366	302	6	,	,	PUNCT
aiti-366	302	7	k.	k.	PROPN
aiti-366	302	8	simonyan	simonyan	PROPN
aiti-366	302	9	,	,	PUNCT
aiti-366	302	10	a.	a.	NOUN
aiti-366	302	11	vedaldi	vedaldi	PROPN
aiti-366	302	12	and	and	CCONJ
aiti-366	302	13	a.	a.	NOUN
aiti-366	302	14	zisserman	zisserman	PROPN
aiti-366	302	15	,	,	PUNCT
aiti-366	302	16	“	"	PUNCT
aiti-366	302	17	return	return	NOUN
aiti-366	302	18	of	of	ADP
aiti-366	302	19	the	the	DET
aiti-366	302	20	devil	devil	NOUN
aiti-366	302	21	in	in	ADP
aiti-366	302	22	the	the	DET
aiti-366	302	23	details	detail	NOUN
aiti-366	302	24	:	:	PUNCT
aiti-366	302	25	delving	delve	VERB
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aiti-366	302	27	into	into	ADP
aiti-366	302	28	convolutional	convolutional	ADJ
aiti-366	302	29	nets	net	NOUN
aiti-366	302	30	,	,	PUNCT
aiti-366	302	31	”	"	PUNCT
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aiti-366	302	33	preprint	preprint	NOUN
aiti-366	302	34	arxiv	arxiv	PROPN
aiti-366	302	35	:	:	PUNCT
aiti-366	302	36	1405.3531	1405.3531	NUM
aiti-366	302	37	,	,	PUNCT
aiti-366	302	38	2014	2014	NUM
aiti-366	302	39	.	.	PUNCT
aiti-366	303	1	[	[	X
aiti-366	303	2	10	10	NUM
aiti-366	303	3	]	]	PUNCT
aiti-366	303	4	p.	p.	NOUN
aiti-366	303	5	heit	heit	PROPN
aiti-366	303	6	,	,	PUNCT
aiti-366	303	7	“	"	PUNCT
aiti-366	303	8	the	the	DET
aiti-366	303	9	berkeley	berkeley	PROPN
aiti-366	303	10	model	model	NOUN
aiti-366	303	11	,	,	PUNCT
aiti-366	303	12	”	"	PUNCT
aiti-366	303	13	health	health	NOUN
aiti-366	303	14	education	education	NOUN
aiti-366	303	15	,	,	PUNCT
aiti-366	303	16	vol	vol	NOUN
aiti-366	303	17	.	.	PROPN
aiti-366	303	18	8	8	NUM
aiti-366	303	19	,	,	PUNCT
aiti-366	303	20	no	no	INTJ
aiti-366	303	21	.	.	NOUN
aiti-366	303	22	1	1	NUM
aiti-366	303	23	,	,	PUNCT
aiti-366	303	24	pp	pp	ADJ
aiti-366	303	25	.	.	PUNCT
aiti-366	304	1	2	2	NUM
aiti-366	304	2	-	-	SYM
aiti-366	304	3	3	3	NUM
aiti-366	304	4	,	,	PUNCT
aiti-366	304	5	1977	1977	NUM
aiti-366	304	6	.	.	PUNCT
aiti-366	305	1	[	[	X
aiti-366	305	2	11	11	NUM
aiti-366	305	3	]	]	PUNCT
aiti-366	305	4	l.	l.	PROPN
aiti-366	305	5	wang	wang	PROPN
aiti-366	305	6	,	,	PUNCT
aiti-366	305	7	c.	c.	PROPN
aiti-366	305	8	y.	y.	PROPN
aiti-366	305	9	lee	lee	PROPN
aiti-366	305	10	,	,	PUNCT
aiti-366	305	11	z.	z.	PROPN
aiti-366	305	12	tu	tu	PROPN
aiti-366	305	13	and	and	CCONJ
aiti-366	305	14	s.	s.	PROPN
aiti-366	305	15	lazebnik	lazebnik	PROPN
aiti-366	305	16	,	,	PUNCT
aiti-366	305	17	“	"	PUNCT
aiti-366	305	18	training	train	VERB
aiti-366	305	19	deeper	deep	ADJ
aiti-366	305	20	convolutional	convolutional	ADJ
aiti-366	305	21	networks	network	NOUN
aiti-366	305	22	with	with	ADP
aiti-366	305	23	deep	deep	ADJ
aiti-366	305	24	supervision	supervision	NOUN
aiti-366	305	25	,	,	PUNCT
aiti-366	305	26	”	"	PUNCT
aiti-366	305	27	arxiv	arxiv	PROPN
aiti-366	305	28	preprint	preprint	NOUN
aiti-366	305	29	arxiv	arxiv	PROPN
aiti-366	305	30	:	:	PUNCT
aiti-366	305	31	1505.02496	1505.02496	NOUN
aiti-366	305	32	,	,	PUNCT
aiti-366	305	33	2015	2015	NUM
aiti-366	305	34	.	.	PUNCT
aiti-366	306	1	[	[	X
aiti-366	306	2	12	12	NUM
aiti-366	306	3	]	]	X
aiti-366	306	4	g.	g.	PROPN
aiti-366	306	5	levi	levi	PROPN
aiti-366	306	6	and	and	CCONJ
aiti-366	306	7	t.	t.	PROPN
aiti-366	306	8	hassner	hassner	NOUN
aiti-366	306	9	,	,	PUNCT
aiti-366	306	10	“	"	PUNCT
aiti-366	306	11	age	age	NOUN
aiti-366	306	12	and	and	CCONJ
aiti-366	306	13	gender	gender	NOUN
aiti-366	306	14	classification	classification	NOUN
aiti-366	306	15	using	use	VERB
aiti-366	306	16	convolutional	convolutional	ADJ
aiti-366	306	17	neural	neural	ADJ
aiti-366	306	18	networks	network	NOUN
aiti-366	306	19	,	,	PUNCT
aiti-366	306	20	”	"	PUNCT
aiti-366	306	21	proc	proc	NOUN
aiti-366	306	22	.	.	PUNCT
aiti-366	307	1	ieee	ieee	NOUN
aiti-366	307	2	conference	conference	PROPN
aiti-366	307	3	on	on	ADP
aiti-366	307	4	computer	computer	NOUN
aiti-366	307	5	vision	vision	NOUN
aiti-366	307	6	and	and	CCONJ
aiti-366	307	7	pattern	pattern	NOUN
aiti-366	307	8	recognition	recognition	NOUN
aiti-366	307	9	workshops	workshop	NOUN
aiti-366	307	10	,	,	PUNCT
aiti-366	307	11	pp	pp	ADJ
aiti-366	307	12	.	.	PUNCT
aiti-366	308	1	34	34	NUM
aiti-366	308	2	-	-	SYM
aiti-366	308	3	42	42	NUM
aiti-366	308	4	,	,	PUNCT
aiti-366	308	5	2015	2015	NUM
aiti-366	308	6	.	.	PUNCT
aiti-366	309	1	[	[	X
aiti-366	309	2	13	13	NUM
aiti-366	309	3	]	]	PUNCT
aiti-366	309	4	z.	z.	PROPN
aiti-366	309	5	ge	ge	PROPN
aiti-366	309	6	,	,	PUNCT
aiti-366	309	7	c.	c.	PROPN
aiti-366	309	8	mccool	mccool	PROPN
aiti-366	309	9	and	and	CCONJ
aiti-366	309	10	p.	p.	NOUN
aiti-366	309	11	corke	corke	NOUN
aiti-366	309	12	,	,	PUNCT
aiti-366	309	13	“	"	PUNCT
aiti-366	309	14	content	content	NOUN
aiti-366	309	15	specific	specific	ADJ
aiti-366	309	16	feature	feature	NOUN
aiti-366	309	17	learning	learn	VERB
aiti-366	309	18	for	for	ADP
aiti-366	309	19	fine	fine	ADV
aiti-366	309	20	-	-	PUNCT
aiti-366	309	21	grained	grain	VERB
aiti-366	309	22	plant	plant	NOUN
aiti-366	309	23	classification	classification	NOUN
aiti-366	309	24	,	,	PUNCT
aiti-366	309	25	”	"	PUNCT
aiti-366	309	26	proc	proc	NOUN
aiti-366	309	27	.	.	PUNCT
aiti-366	310	1	clef	clef	NOUN
aiti-366	310	2	(	(	PUNCT
aiti-366	310	3	working	working	NOUN
aiti-366	310	4	notes	note	NOUN
aiti-366	310	5	)	)	PUNCT
aiti-366	310	6	,	,	PUNCT
aiti-366	310	7	2015	2015	NUM
aiti-366	310	8	.	.	PUNCT
aiti-366	311	1	[	[	X
aiti-366	311	2	14	14	NUM
aiti-366	311	3	]	]	PUNCT
aiti-366	311	4	k.	k.	PROPN
aiti-366	311	5	yamaguchi	yamaguchi	PROPN
aiti-366	311	6	,	,	PUNCT
aiti-366	311	7	m.	m.	PROPN
aiti-366	311	8	h.	h.	PROPN
aiti-366	311	9	kiapour	kiapour	PROPN
aiti-366	311	10	,	,	PUNCT
aiti-366	311	11	l.	l.	PROPN
aiti-366	311	12	e.	e.	PROPN
aiti-366	311	13	ortiz	ortiz	PROPN
aiti-366	311	14	and	and	CCONJ
aiti-366	311	15	t.	t.	PROPN
aiti-366	311	16	l.	l.	PROPN
aiti-366	311	17	berg	berg	PROPN
aiti-366	311	18	,	,	PUNCT
aiti-366	311	19	“	"	PUNCT
aiti-366	311	20	parsing	parse	VERB
aiti-366	311	21	clothing	clothing	NOUN
aiti-366	311	22	in	in	ADP
aiti-366	311	23	fashion	fashion	NOUN
aiti-366	311	24	photographs	photograph	NOUN
aiti-366	311	25	,	,	PUNCT
aiti-366	311	26	”	"	PUNCT
aiti-366	311	27	proc	proc	NOUN
aiti-366	311	28	.	.	PUNCT
aiti-366	312	1	computer	computer	NOUN
aiti-366	312	2	vision	vision	NOUN
aiti-366	312	3	and	and	CCONJ
aiti-366	312	4	pattern	pattern	NOUN
aiti-366	312	5	recognition	recognition	NOUN
aiti-366	312	6	(	(	PUNCT
aiti-366	312	7	cvpr	cvpr	NOUN
aiti-366	312	8	)	)	PUNCT
aiti-366	312	9	,	,	PUNCT
aiti-366	312	10	pp	pp	ADJ
aiti-366	312	11	.	.	PUNCT
aiti-366	312	12	3570	3570	NUM
aiti-366	312	13	-	-	SYM
aiti-366	312	14	3577	3577	NUM
aiti-366	312	15	,	,	PUNCT
aiti-366	312	16	2012	2012	NUM
aiti-366	312	17	.	.	PUNCT
aiti-366	313	1	[	[	X
aiti-366	313	2	15	15	NUM
aiti-366	313	3	]	]	PUNCT
aiti-366	313	4	k.	k.	PROPN
aiti-366	313	5	yamaguchi	yamaguchi	PROPN
aiti-366	313	6	,	,	PUNCT
aiti-366	313	7	m.	m.	PROPN
aiti-366	313	8	h.	h.	PROPN
aiti-366	313	9	kiapour	kiapour	PROPN
aiti-366	313	10	and	and	CCONJ
aiti-366	313	11	t.	t.	PROPN
aiti-366	313	12	l.	l.	PROPN
aiti-366	313	13	berg	berg	PROPN
aiti-366	313	14	,	,	PUNCT
aiti-366	313	15	“	"	PUNCT
aiti-366	313	16	paper	paper	NOUN
aiti-366	313	17	doll	doll	NOUN
aiti-366	313	18	parsing	parse	VERB
aiti-366	313	19	:	:	PUNCT
aiti-366	313	20	retrieving	retrieve	VERB
aiti-366	313	21	similar	similar	ADJ
aiti-366	313	22	styles	style	NOUN
aiti-366	313	23	to	to	PART
aiti-366	313	24	parse	parse	VERB
aiti-366	313	25	clothing	clothing	NOUN
aiti-366	313	26	items	item	NOUN
aiti-366	313	27	,	,	PUNCT
aiti-366	313	28	”	"	PUNCT
aiti-366	313	29	proc	proc	NOUN
aiti-366	313	30	.	.	PUNCT
aiti-366	313	31	of	of	ADP
aiti-366	313	32	the	the	DET
aiti-366	313	33	ieee	ieee	NOUN
aiti-366	313	34	international	international	PROPN
aiti-366	313	35	conference	conference	NOUN
aiti-366	313	36	on	on	ADP
aiti-366	313	37	computer	computer	NOUN
aiti-366	313	38	vision	vision	NOUN
aiti-366	313	39	,	,	PUNCT
aiti-366	313	40	pp	pp	ADJ
aiti-366	313	41	.	.	PUNCT
aiti-366	314	1	3519	3519	NUM
aiti-366	314	2	-	-	SYM
aiti-366	314	3	3526	3526	NUM
aiti-366	314	4	,	,	PUNCT
aiti-366	314	5	2013	2013	NUM
aiti-366	314	6	.	.	PUNCT
aiti-366	315	1	[	[	X
aiti-366	315	2	16	16	NUM
aiti-366	315	3	]	]	X
aiti-366	315	4	c.	c.	PROPN
aiti-366	315	5	shan	shan	PROPN
aiti-366	315	6	,	,	PUNCT
aiti-366	315	7	s.	s.	PROPN
aiti-366	315	8	gong	gong	PROPN
aiti-366	315	9	and	and	CCONJ
aiti-366	315	10	p.	p.	PROPN
aiti-366	315	11	w.	w.	PROPN
aiti-366	315	12	mcowan	mcowan	PROPN
aiti-366	315	13	,	,	PUNCT
aiti-366	315	14	“	"	PUNCT
aiti-366	315	15	facial	facial	ADJ
aiti-366	315	16	expression	expression	NOUN
aiti-366	315	17	recognition	recognition	NOUN
aiti-366	315	18	based	base	VERB
aiti-366	315	19	on	on	ADP
aiti-366	315	20	local	local	ADJ
aiti-366	315	21	binary	binary	ADJ
aiti-366	315	22	patterns	pattern	NOUN
aiti-366	315	23	:	:	PUNCT
aiti-366	315	24	a	a	DET
aiti-366	315	25	comprehensive	comprehensive	ADJ
aiti-366	315	26	study	study	NOUN
aiti-366	315	27	,	,	PUNCT
aiti-366	315	28	”	"	PUNCT
aiti-366	315	29	image	image	NOUN
aiti-366	315	30	and	and	CCONJ
aiti-366	315	31	vision	vision	NOUN
aiti-366	315	32	computing	computing	NOUN
aiti-366	315	33	,	,	PUNCT
aiti-366	315	34	vol	vol	NOUN
aiti-366	315	35	.	.	PROPN
aiti-366	315	36	27	27	NUM
aiti-366	315	37	,	,	PUNCT
aiti-366	315	38	no	no	INTJ
aiti-366	315	39	.	.	NOUN
aiti-366	315	40	6	6	NUM
aiti-366	315	41	,	,	PUNCT
aiti-366	315	42	pp	pp	ADJ
aiti-366	315	43	.	.	PUNCT
aiti-366	315	44	803	803	NUM
aiti-366	315	45	-	-	SYM
aiti-366	315	46	816	816	NUM
aiti-366	315	47	,	,	PUNCT
aiti-366	315	48	2009	2009	NUM
aiti-366	315	49	.	.	PUNCT
aiti-366	316	1	[	[	X
aiti-366	316	2	17	17	NUM
aiti-366	316	3	]	]	PUNCT
aiti-366	316	4	x.	x.	NOUN
aiti-366	316	5	feng	feng	PROPN
aiti-366	316	6	,	,	PUNCT
aiti-366	316	7	a.	a.	PROPN
aiti-366	316	8	hadid	hadid	PROPN
aiti-366	316	9	and	and	CCONJ
aiti-366	316	10	m.	m.	NOUN
aiti-366	316	11	pietikäinen	pietikäinen	PROPN
aiti-366	316	12	,	,	PUNCT
aiti-366	316	13	“	"	PUNCT
aiti-366	316	14	a	a	DET
aiti-366	316	15	coarse	coarse	NOUN
aiti-366	316	16	-	-	PUNCT
aiti-366	316	17	to	to	ADP
aiti-366	316	18	-	-	PUNCT
aiti-366	316	19	fine	fine	ADJ
aiti-366	316	20	classification	classification	NOUN
aiti-366	316	21	scheme	scheme	NOUN
aiti-366	316	22	for	for	ADP
aiti-366	316	23	facial	facial	ADJ
aiti-366	316	24	expression	expression	NOUN
aiti-366	316	25	recognition	recognition	NOUN
aiti-366	316	26	,	,	PUNCT
aiti-366	316	27	”	"	PUNCT
aiti-366	316	28	proc	proc	NOUN
aiti-366	316	29	.	.	PUNCT
aiti-366	317	1	international	international	ADJ
aiti-366	317	2	conference	conference	NOUN
aiti-366	317	3	image	image	NOUN
aiti-366	317	4	analysis	analysis	NOUN
aiti-366	317	5	and	and	CCONJ
aiti-366	317	6	recognition	recognition	NOUN
aiti-366	317	7	,	,	PUNCT
aiti-366	317	8	springer	springer	NOUN
aiti-366	317	9	berlin	berlin	PROPN
aiti-366	317	10	heidelberg	heidelberg	PROPN
aiti-366	317	11	,	,	PUNCT
aiti-366	317	12	pp	pp	PROPN
aiti-366	317	13	.	.	PUNCT
aiti-366	318	1	668	668	NUM
aiti-366	318	2	-	-	SYM
aiti-366	318	3	675	675	NUM
aiti-366	318	4	,	,	PUNCT
aiti-366	318	5	2004	2004	NUM
aiti-366	318	6	.	.	PUNCT
aiti-366	319	1	[	[	X
aiti-366	319	2	18	18	NUM
aiti-366	319	3	]	]	X
aiti-366	319	4	e.	e.	PROPN
aiti-366	319	5	simo	simo	PROPN
aiti-366	319	6	-	-	PUNCT
aiti-366	319	7	serra	serra	PROPN
aiti-366	319	8	,	,	PUNCT
aiti-366	319	9	s.	s.	PROPN
aiti-366	319	10	fidler	fidler	PROPN
aiti-366	319	11	,	,	PUNCT
aiti-366	319	12	f.	f.	PROPN
aiti-366	319	13	moreno	moreno	PROPN
aiti-366	319	14	-	-	PUNCT
aiti-366	319	15	noguer	noguer	PROPN
aiti-366	319	16	and	and	CCONJ
aiti-366	319	17	r.	r.	PROPN
aiti-366	319	18	urtasun	urtasun	PROPN
aiti-366	319	19	,	,	PUNCT
aiti-366	319	20	“	"	PUNCT
aiti-366	319	21	a	a	DET
aiti-366	319	22	high	high	ADJ
aiti-366	319	23	performance	performance	NOUN
aiti-366	319	24	crf	crf	NOUN
aiti-366	319	25	model	model	NOUN
aiti-366	319	26	for	for	ADP
aiti-366	319	27	clothes	clothe	NOUN
aiti-366	319	28	parsing	parse	VERB
aiti-366	319	29	,	,	PUNCT
aiti-366	319	30	”	"	PUNCT
aiti-366	319	31	proc	proc	NOUN
aiti-366	319	32	.	.	PUNCT
aiti-366	320	1	asian	asian	ADJ
aiti-366	320	2	conference	conference	NOUN
aiti-366	320	3	on	on	ADP
aiti-366	320	4	computer	computer	NOUN
aiti-366	320	5	vision	vision	NOUN
aiti-366	320	6	,	,	PUNCT
aiti-366	320	7	springer	springer	NOUN
aiti-366	320	8	international	international	ADJ
aiti-366	320	9	publishing	publishing	NOUN
aiti-366	320	10	,	,	PUNCT
aiti-366	320	11	pp	pp	ADJ
aiti-366	320	12	.	.	PUNCT
aiti-366	321	1	64	64	NUM
aiti-366	321	2	-	-	SYM
aiti-366	321	3	81	81	NUM
aiti-366	321	4	,	,	PUNCT
aiti-366	321	5	2014	2014	NUM
aiti-366	321	6	.	.	PUNCT
aiti-366	322	1	[	[	X
aiti-366	322	2	19	19	NUM
aiti-366	322	3	]	]	X
aiti-366	322	4	s.	s.	PROPN
aiti-366	322	5	vittayakorn	vittayakorn	PROPN
aiti-366	322	6	,	,	PUNCT
aiti-366	322	7	k.	k.	PROPN
aiti-366	322	8	yamaguchi	yamaguchi	PROPN
aiti-366	322	9	,	,	PUNCT
aiti-366	322	10	a.	a.	PROPN
aiti-366	322	11	c.	c.	PROPN
aiti-366	322	12	berg	berg	PROPN
aiti-366	322	13	and	and	CCONJ
aiti-366	322	14	t.	t.	PROPN
aiti-366	322	15	l.	l.	PROPN
aiti-366	322	16	berg	berg	PROPN
aiti-366	322	17	,	,	PUNCT
aiti-366	322	18	“	"	PUNCT
aiti-366	322	19	runway	runway	NOUN
aiti-366	322	20	to	to	ADP
aiti-366	322	21	realway	realway	NOUN
aiti-366	322	22	:	:	PUNCT
aiti-366	322	23	visual	visual	ADJ
aiti-366	322	24	analysis	analysis	NOUN
aiti-366	322	25	of	of	ADP
aiti-366	322	26	fashion	fashion	NOUN
aiti-366	322	27	,	,	PUNCT
aiti-366	322	28	”	"	PUNCT
aiti-366	322	29	proc	proc	NOUN
aiti-366	322	30	.	.	PUNCT
aiti-366	323	1	ieee	ieee	PROPN
aiti-366	323	2	winter	winter	PROPN
aiti-366	323	3	conference	conference	NOUN
aiti-366	323	4	on	on	ADP
aiti-366	323	5	applications	application	NOUN
aiti-366	323	6	of	of	ADP
aiti-366	323	7	computer	computer	NOUN
aiti-366	323	8	vision	vision	NOUN
aiti-366	323	9	,	,	PUNCT
aiti-366	323	10	ieee	ieee	NOUN
aiti-366	323	11	press	press	NOUN
aiti-366	323	12	,	,	PUNCT
aiti-366	323	13	pp	pp	ADJ
aiti-366	323	14	.	.	PUNCT
aiti-366	324	1	951	951	NUM
aiti-366	324	2	-	-	SYM
aiti-366	324	3	958	958	NUM
aiti-366	324	4	,	,	PUNCT
aiti-366	324	5	2015	2015	NUM
aiti-366	324	6	.	.	PUNCT
aiti-366	325	1	[	[	X
aiti-366	325	2	20	20	NUM
aiti-366	325	3	]	]	X
aiti-366	325	4	y.	y.	PROPN
aiti-366	325	5	kalantidis	kalantidis	PROPN
aiti-366	325	6	,	,	PUNCT
aiti-366	325	7	l.	l.	PROPN
aiti-366	325	8	kennedy	kennedy	PROPN
aiti-366	325	9	and	and	CCONJ
aiti-366	325	10	l.	l.	PROPN
aiti-366	325	11	j.	j.	PROPN
aiti-366	325	12	li	li	PROPN
aiti-366	325	13	,	,	PUNCT
aiti-366	325	14	“	"	PUNCT
aiti-366	325	15	getting	get	VERB
aiti-366	325	16	the	the	DET
aiti-366	325	17	look	look	NOUN
aiti-366	325	18	:	:	PUNCT
aiti-366	325	19	clothing	clothing	NOUN
aiti-366	325	20	recognition	recognition	NOUN
aiti-366	325	21	and	and	CCONJ
aiti-366	325	22	segmentation	segmentation	NOUN
aiti-366	325	23	for	for	ADP
aiti-366	325	24	automatic	automatic	ADJ
aiti-366	325	25	product	product	NOUN
aiti-366	325	26	suggestions	suggestion	NOUN
aiti-366	325	27	in	in	ADP
aiti-366	325	28	everyday	everyday	ADJ
aiti-366	325	29	photos	photo	NOUN
aiti-366	325	30	,	,	PUNCT
aiti-366	325	31	”	"	PUNCT
aiti-366	325	32	proc	proc	NOUN
aiti-366	325	33	.	.	PUNCT
aiti-366	325	34	of	of	ADP
aiti-366	325	35	the	the	DET
aiti-366	325	36	3rd	3rd	PROPN
aiti-366	325	37	acm	acm	PROPN
aiti-366	325	38	conference	conference	NOUN
aiti-366	325	39	on	on	ADP
aiti-366	325	40	international	international	ADJ
aiti-366	325	41	conference	conference	NOUN
aiti-366	325	42	on	on	ADP
aiti-366	325	43	multimedia	multimedia	PROPN
aiti-366	325	44	retrieval	retrieval	NOUN
aiti-366	325	45	,	,	PUNCT
aiti-366	325	46	acm	acm	PROPN
aiti-366	325	47	,	,	PUNCT
aiti-366	325	48	pp	pp	PROPN
aiti-366	325	49	.	.	PUNCT
aiti-366	326	1	105	105	NUM
aiti-366	326	2	-	-	SYM
aiti-366	326	3	112	112	NUM
aiti-366	326	4	,	,	PUNCT
aiti-366	326	5	2013	2013	NUM
aiti-366	326	6	.	.	PUNCT
aiti-366	327	1	[	[	X
aiti-366	327	2	21	21	NUM
aiti-366	327	3	]	]	PUNCT
aiti-366	327	4	a.	a.	NOUN
aiti-366	327	5	c.	c.	PROPN
aiti-366	327	6	gallagher	gallagher	PROPN
aiti-366	327	7	and	and	CCONJ
aiti-366	327	8	t.	t.	PROPN
aiti-366	327	9	chen	chen	PROPN
aiti-366	327	10	,	,	PUNCT
aiti-366	327	11	“	"	PUNCT
aiti-366	327	12	clothing	clothing	NOUN
aiti-366	327	13	cosegmentation	cosegmentation	NOUN
aiti-366	327	14	for	for	ADP
aiti-366	327	15	recognizing	recognize	VERB
aiti-366	327	16	people	people	NOUN
aiti-366	327	17	,	,	PUNCT
aiti-366	327	18	”	"	PUNCT
aiti-366	327	19	proc	proc	NOUN
aiti-366	327	20	.	.	PUNCT
aiti-366	328	1	computer	computer	NOUN
aiti-366	328	2	vision	vision	NOUN
aiti-366	328	3	and	and	CCONJ
aiti-366	328	4	pattern	pattern	NOUN
aiti-366	328	5	recognition	recognition	NOUN
aiti-366	328	6	(	(	PUNCT
aiti-366	328	7	cvpr	cvpr	NOUN
aiti-366	328	8	2008	2008	NUM
aiti-366	328	9	)	)	PUNCT
aiti-366	328	10	,	,	PUNCT
aiti-366	328	11	ieee	ieee	NOUN
aiti-366	328	12	press	press	NOUN
aiti-366	328	13	,	,	PUNCT
aiti-366	328	14	pp	pp	ADJ
aiti-366	328	15	.	.	PUNCT
aiti-366	329	1	1	1	NUM
aiti-366	329	2	-	-	SYM
aiti-366	329	3	8	8	NUM
aiti-366	329	4	,	,	PUNCT
aiti-366	329	5	2008	2008	NUM
aiti-366	329	6	.	.	PUNCT
aiti-366	330	1	[	[	X
aiti-366	330	2	22	22	NUM
aiti-366	330	3	]	]	PUNCT
aiti-366	330	4	l.	l.	PROPN
aiti-366	330	5	bourdev	bourdev	PROPN
aiti-366	330	6	,	,	PUNCT
aiti-366	330	7	s.	s.	PROPN
aiti-366	330	8	maji	maji	PROPN
aiti-366	330	9	and	and	CCONJ
aiti-366	330	10	j.	j.	PROPN
aiti-366	330	11	malik	malik	PROPN
aiti-366	330	12	,	,	PUNCT
aiti-366	330	13	“	"	PUNCT
aiti-366	330	14	describing	describe	VERB
aiti-366	330	15	people	people	NOUN
aiti-366	330	16	:	:	PUNCT
aiti-366	330	17	a	a	DET
aiti-366	330	18	poselet	poselet	NOUN
aiti-366	330	19	-	-	PUNCT
aiti-366	330	20	based	base	VERB
aiti-366	330	21	approach	approach	NOUN
aiti-366	330	22	to	to	AUX
aiti-366	330	23	attribute	attribute	VERB
aiti-366	330	24	classification	classification	NOUN
aiti-366	330	25	,	,	PUNCT
aiti-366	330	26	”	"	PUNCT
aiti-366	330	27	proc	proc	NOUN
aiti-366	330	28	.	.	PUNCT
aiti-366	331	1	international	international	ADJ
aiti-366	331	2	conference	conference	NOUN
aiti-366	331	3	on	on	ADP
aiti-366	331	4	computer	computer	NOUN
aiti-366	331	5	vision	vision	NOUN
aiti-366	331	6	,	,	PUNCT
aiti-366	331	7	ieee	ieee	NOUN
aiti-366	331	8	press	press	NOUN
aiti-366	331	9	,	,	PUNCT
aiti-366	331	10	pp	pp	ADJ
aiti-366	331	11	.	.	PUNCT
aiti-366	332	1	1543	1543	NUM
aiti-366	332	2	-	-	SYM
aiti-366	332	3	1550	1550	NUM
aiti-366	332	4	,	,	PUNCT
aiti-366	332	5	2011	2011	NUM
aiti-366	332	6	.	.	PUNCT
aiti-366	333	1	[	[	X
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aiti-366	333	3	]	]	X
aiti-366	333	4	s.	s.	PROPN
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aiti-366	333	9	,	,	PUNCT
aiti-366	333	10	“	"	PUNCT
aiti-366	333	11	texture	texture	ADJ
aiti-366	333	12	classification	classification	NOUN
aiti-366	333	13	using	use	VERB
aiti-366	333	14	wavelet	wavelet	NOUN
aiti-366	333	15	transform	transform	NOUN
aiti-366	333	16	,	,	PUNCT
aiti-366	333	17	”	"	PUNCT
aiti-366	333	18	pattern	pattern	NOUN
aiti-366	333	19	recognition	recognition	NOUN
aiti-366	333	20	letters	letter	NOUN
aiti-366	333	21	,	,	PUNCT
aiti-366	333	22	vol	vol	NOUN
aiti-366	333	23	.	.	PROPN
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aiti-366	334	2	,	,	PUNCT
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aiti-366	334	6	,	,	PUNCT
aiti-366	334	7	pp	pp	ADJ
aiti-366	334	8	.	.	PUNCT
aiti-366	335	1	1513	1513	NUM
aiti-366	335	2	-	-	SYM
aiti-366	335	3	1521	1521	NUM
aiti-366	335	4	,	,	PUNCT
aiti-366	335	5	2003	2003	NUM
aiti-366	335	6	.	.	PUNCT
aiti-366	336	1	[	[	X
aiti-366	336	2	24	24	NUM
aiti-366	336	3	]	]	PUNCT
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aiti-366	336	5	m.	m.	PROPN
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aiti-366	336	7	,	,	PUNCT
aiti-366	336	8	s.	s.	PROPN
aiti-366	336	9	rahman	rahman	PROPN
aiti-366	336	10	,	,	PUNCT
aiti-366	336	11	m.	m.	PROPN
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aiti-366	336	13	,	,	PUNCT
aiti-366	336	14	e.	e.	PROPN
aiti-366	336	15	k.	k.	PROPN
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aiti-366	336	17	,	,	PUNCT
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aiti-366	336	19	a.	a.	PROPN
aiti-366	336	20	a.	a.	PROPN
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aiti-366	336	22	and	and	CCONJ
aiti-366	336	23	m.	m.	NOUN
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aiti-366	336	31	for	for	ADP
aiti-366	336	32	face	face	NOUN
aiti-366	336	33	image	image	NOUN
aiti-366	336	34	analysis	analysis	NOUN
aiti-366	336	35	,	,	PUNCT
aiti-366	336	36	”	"	PUNCT
aiti-366	336	37	proc	proc	NOUN
aiti-366	336	38	.	.	PUNCT
aiti-366	337	1	18th	18th	ADJ
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aiti-366	337	3	conference	conference	NOUN
aiti-366	337	4	on	on	ADP
aiti-366	337	5	computer	computer	NOUN
aiti-366	337	6	and	and	CCONJ
aiti-366	337	7	information	information	NOUN
aiti-366	337	8	technology	technology	NOUN
aiti-366	337	9	(	(	PUNCT
aiti-366	337	10	iccit	iccit	NOUN
aiti-366	337	11	)	)	PUNCT
aiti-366	337	12	,	,	PUNCT
aiti-366	337	13	ieee	ieee	NOUN
aiti-366	337	14	press	press	NOUN
aiti-366	337	15	,	,	PUNCT
aiti-366	337	16	pp	pp	ADJ
aiti-366	337	17	.	.	PUNCT
aiti-366	338	1	390	390	NUM
aiti-366	338	2	-	-	SYM
aiti-366	338	3	395	395	NUM
aiti-366	338	4	,	,	PUNCT
aiti-366	338	5	2015	2015	NUM
aiti-366	338	6	.	.	PUNCT
aiti-366	339	1	[	[	X
aiti-366	339	2	25	25	NUM
aiti-366	339	3	]	]	PUNCT
aiti-366	339	4	b.	b.	PROPN
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aiti-366	339	8	choi	choi	PROPN
aiti-366	339	9	and	and	CCONJ
aiti-366	339	10	d.	d.	PROPN
aiti-366	339	11	kim	kim	PROPN
aiti-366	339	12	,	,	PUNCT
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aiti-366	339	14	local	local	ADJ
aiti-366	339	15	transform	transform	NOUN
aiti-366	339	16	features	feature	NOUN
aiti-366	339	17	and	and	CCONJ
aiti-366	339	18	hybridization	hybridization	NOUN
aiti-366	339	19	for	for	ADP
aiti-366	339	20	accurate	accurate	ADJ
aiti-366	339	21	face	face	NOUN
aiti-366	339	22	and	and	CCONJ
aiti-366	339	23	human	human	ADJ
aiti-366	339	24	detection	detection	NOUN
aiti-366	339	25	,	,	PUNCT
aiti-366	339	26	”	"	PUNCT
aiti-366	339	27	ieee	ieee	NOUN
aiti-366	339	28	transactions	transaction	NOUN
aiti-366	339	29	on	on	ADP
aiti-366	339	30	pattern	pattern	NOUN
aiti-366	339	31	analysis	analysis	NOUN
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aiti-366	339	33	machine	machine	NOUN
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aiti-366	339	35	,	,	PUNCT
aiti-366	339	36	vol	vol	NOUN
aiti-366	339	37	.	.	PROPN
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aiti-366	339	39	,	,	PUNCT
aiti-366	339	40	no	no	INTJ
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aiti-366	339	43	,	,	PUNCT
aiti-366	339	44	pp	pp	ADJ
aiti-366	339	45	.	.	PUNCT
aiti-366	339	46	1423	1423	NUM
aiti-366	339	47	-	-	SYM
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aiti-366	339	49	,	,	PUNCT
aiti-366	339	50	2013	2013	NUM
aiti-366	339	51	.	.	PUNCT
aiti-366	340	1	[	[	X
aiti-366	340	2	26	26	NUM
aiti-366	340	3	]	]	X
aiti-366	340	4	s.	s.	PROPN
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aiti-366	340	7	c.	c.	PROPN
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aiti-366	340	10	j.	j.	PROPN
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aiti-366	340	12	,	,	PUNCT
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aiti-366	340	17	features	feature	NOUN
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aiti-366	340	19	spatial	spatial	ADJ
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aiti-366	340	21	matching	match	VERB
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aiti-366	340	27	,	,	PUNCT
aiti-366	340	28	”	"	PUNCT
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aiti-366	340	30	.	.	PUNCT
aiti-366	341	1	ieee	ieee	PROPN
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aiti-366	341	5	on	on	ADP
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aiti-366	341	9	pattern	pattern	NOUN
aiti-366	341	10	recognition	recognition	NOUN
aiti-366	341	11	(	(	PUNCT
aiti-366	341	12	cvpr'06	cvpr'06	PROPN
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aiti-366	341	14	,	,	PUNCT
aiti-366	341	15	ieee	ieee	NOUN
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aiti-366	341	17	,	,	PUNCT
aiti-366	341	18	pp	pp	ADJ
aiti-366	341	19	.	.	PUNCT
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aiti-366	342	2	-	-	SYM
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aiti-366	342	4	,	,	PUNCT
aiti-366	342	5	2006	2006	NUM
aiti-366	342	6	.	.	PUNCT
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aiti-366	343	7	k.	k.	PROPN
aiti-366	343	8	jagadeesh	jagadeesh	PROPN
aiti-366	343	9	,	,	PUNCT
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aiti-366	343	11	convolutional	convolutional	ADJ
aiti-366	343	12	neural	neural	ADJ
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aiti-366	343	14	for	for	ADP
aiti-366	343	15	fashion	fashion	NOUN
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aiti-366	343	18	object	object	NOUN
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aiti-366	343	20	,	,	PUNCT
aiti-366	343	21	”	"	PUNCT
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aiti-366	343	25	june	june	PROPN
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aiti-366	343	27	,	,	PUNCT
aiti-366	343	28	2016	2016	NUM
aiti-366	343	29	.	.	PUNCT
aiti-366	344	1	[	[	X
aiti-366	344	2	28	28	NUM
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aiti-366	344	4	f.	f.	PROPN
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aiti-366	344	6	,	,	PUNCT
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aiti-366	344	8	s.	s.	PROPN
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aiti-366	344	11	j.	j.	PROPN
aiti-366	344	12	hu	hu	PROPN
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aiti-366	344	46	,	,	PUNCT
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aiti-366	344	50	-	-	SYM
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aiti-366	344	52	,	,	PUNCT
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aiti-366	344	54	.	.	PUNCT
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aiti-366	345	9	,	,	PUNCT
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aiti-366	348	17	,	,	PUNCT
aiti-366	348	18	”	"	PUNCT
aiti-366	348	19	proc	proc	NOUN
aiti-366	348	20	.	.	PUNCT
aiti-366	349	1	european	european	ADJ
aiti-366	349	2	conference	conference	PROPN
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aiti-366	349	4	computer	computer	NOUN
aiti-366	349	5	vision	vision	NOUN
aiti-366	349	6	,	,	PUNCT
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aiti-366	349	10	,	,	PUNCT
aiti-366	349	11	pp	pp	ADP
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aiti-366	350	2	-	-	SYM
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aiti-366	350	4	,	,	PUNCT
aiti-366	350	5	2014	2014	NUM
aiti-366	350	6	.	.	PUNCT
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aiti-366	351	9	,	,	PUNCT
aiti-366	351	10	s.	s.	PROPN
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aiti-366	351	40	,	,	PUNCT
aiti-366	351	41	pp	pp	ADJ
aiti-366	351	42	.	.	PUNCT
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aiti-366	352	2	-	-	SYM
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aiti-366	352	4	,	,	PUNCT
aiti-366	352	5	2014	2014	NUM
aiti-366	352	6	.	.	PUNCT
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aiti-366	353	3	]	]	PUNCT
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aiti-366	353	22	.	.	PUNCT
aiti-366	354	1	european	european	ADJ
aiti-366	354	2	conference	conference	PROPN
aiti-366	354	3	on	on	ADP
aiti-366	354	4	computer	computer	NOUN
aiti-366	354	5	vision	vision	NOUN
aiti-366	354	6	,	,	PUNCT
aiti-366	354	7	springer	springer	NOUN
aiti-366	354	8	berlin	berlin	PROPN
aiti-366	354	9	heidelberg	heidelberg	PROPN
aiti-366	354	10	,	,	PUNCT
aiti-366	354	11	pp	pp	X
aiti-366	354	12	.	.	PUNCT
aiti-366	355	1	609	609	NUM
aiti-366	355	2	-	-	SYM
aiti-366	355	3	623	623	NUM
aiti-366	355	4	,	,	PUNCT
aiti-366	355	5	2012	2012	NUM
aiti-366	355	6	.	.	PUNCT
aiti-366	356	1	[	[	X
aiti-366	356	2	33	33	NUM
aiti-366	356	3	]	]	PUNCT
aiti-366	356	4	m.	m.	NOUN
aiti-366	356	5	liu	liu	PROPN
aiti-366	356	6	,	,	PUNCT
aiti-366	356	7	s.	s.	PROPN
aiti-366	356	8	li	li	PROPN
aiti-366	356	9	,	,	PUNCT
aiti-366	356	10	s.	s.	PROPN
aiti-366	356	11	shan	shan	PROPN
aiti-366	356	12	and	and	CCONJ
aiti-366	356	13	x.	x.	PROPN
aiti-366	356	14	chen	chen	PROPN
aiti-366	356	15	,	,	PUNCT
aiti-366	356	16	“	"	PUNCT
aiti-366	356	17	au	au	ADJ
aiti-366	356	18	-	-	ADJ
aiti-366	356	19	aware	aware	ADJ
aiti-366	356	20	deep	deep	ADJ
aiti-366	356	21	networks	network	NOUN
aiti-366	356	22	for	for	ADP
aiti-366	356	23	facial	facial	ADJ
aiti-366	356	24	expression	expression	NOUN
aiti-366	356	25	recognition	recognition	NOUN
aiti-366	356	26	,	,	PUNCT
aiti-366	356	27	”	"	PUNCT
aiti-366	356	28	proc	proc	NOUN
aiti-366	356	29	.	.	PUNCT
aiti-366	357	1	10th	10th	ADJ
aiti-366	357	2	automatic	automatic	ADJ
aiti-366	357	3	face	face	NOUN
aiti-366	357	4	and	and	CCONJ
aiti-366	357	5	gesture	gesture	NOUN
aiti-366	357	6	recognition	recognition	NOUN
aiti-366	357	7	(	(	PUNCT
aiti-366	357	8	fg	fg	PROPN
aiti-366	357	9	)	)	PUNCT
aiti-366	357	10	,	,	PUNCT
aiti-366	357	11	ieee	ieee	NOUN
aiti-366	357	12	press	press	NOUN
aiti-366	357	13	,	,	PUNCT
aiti-366	357	14	pp	pp	ADJ
aiti-366	357	15	.	.	PUNCT
aiti-366	358	1	1	1	NUM
aiti-366	358	2	-	-	SYM
aiti-366	358	3	6	6	NUM
aiti-366	358	4	,	,	PUNCT
aiti-366	358	5	2013	2013	NUM
aiti-366	358	6	.	.	PUNCT